diff --git a/7.3/404.html b/7.3/404.html
old mode 100755
new mode 100644
index 147589c429..ac4cd48f41
--- a/7.3/404.html
+++ b/7.3/404.html
@@ -9,7 +9,7 @@
       
       
       <link rel="icon" href="/7.3/img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -17,16 +17,18 @@
       
     
     
-      <link rel="stylesheet" href="/7.3/assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="/7.3/assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="/7.3/assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="/7.3/assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -39,7 +41,7 @@
       
     
     
-    <script>__md_scope=new URL("/7.3",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("/7.3",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -49,12 +51,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -63,7 +68,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -78,9 +83,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -129,7 +132,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -153,7 +156,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -197,7 +200,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1848,13 +1851,16 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
+                
   <h1>404 - Not found</h1>
 
-            </article>
-          </div>
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
@@ -1885,7 +1891,7 @@ <h1>404 - Not found</h1>
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -1894,7 +1900,7 @@ <h1>404 - Not found</h1>
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -1907,11 +1913,13 @@ <h1>404 - Not found</h1>
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "/7.3", "features": [], "search": "/7.3/assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "/7.3", "features": [], "search": "/7.3/assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="/7.3/assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="/7.3/assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/CNAME b/7.3/CNAME
old mode 100755
new mode 100644
index 85414296c0..cd73634f08
--- a/7.3/CNAME
+++ b/7.3/CNAME
@@ -1 +1 @@
-www.jspsych.org
+www.jspsych.org
diff --git a/7.3/about/about/index.html b/7.3/about/about/index.html
old mode 100755
new mode 100644
index e2066c3e7d..a36208306e
--- a/7.3/about/about/index.html
+++ b/7.3/about/about/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/about/about/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1915,19 +1918,21 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/about/about.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="about-jspsych">About jsPsych<a class="headerlink" href="#about-jspsych" title="Permanent link">&para;</a></h1>
 <p>jsPsych is open source project with <a href="https://github.com/jspsych/jsPsych/graphs/contributors">numerous contributors</a>. The project is currently managed by the core team of Josh de Leeuw (<a href="https://github.com/jodeleeuw">@jodeleeuw</a>), Becky Gilbert (<a href="https://github.com/becky-gilbert">@becky-gilbert</a>), and Björn Luchterhandt (<a href="https://github.com/bjoluc">@bjoluc</a>).</p>
-<p>jsPsych was created by <a href="http://www.twitter.com/joshdeleeuw">Josh de Leeuw <span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg></span></a>.</p>
+<p>jsPsych was created by <a href="http://www.twitter.com/joshdeleeuw">Josh de Leeuw <span class="twemoji"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg></span></a>.</p>
 <h3 id="citation">Citation<a class="headerlink" href="#citation" title="Permanent link">&para;</a></h3>
 <p>If you use this library in academic work, the preferred citation is:</p>
 <p>de Leeuw, J.R., Gilbert, R.A., &amp; Luchterhandt, B. (2023). jsPsych: Enabling an open-source collaborative ecosystem of behavioral experiments. <em>Journal of Open Source Software</em>, <em>8</em>(85), 5351, <a href="https://joss.theoj.org/papers/10.21105/joss.05351">https://joss.theoj.org/papers/10.21105/joss.05351</a>.</p>
@@ -1935,16 +1940,25 @@ <h3 id="citation">Citation<a class="headerlink" href="#citation" title="Permanen
 <p>de Leeuw, J.R. (2015). jsPsych: A JavaScript library for creating behavioral experiments in a Web browser. <em>Behavior Research Methods</em>, <em>47</em>(1), 1-12. doi:<a href="http://link.springer.com/article/10.3758%2Fs13428-014-0458-y">10.3758/s13428-014-0458-y</a></p>
 <p>Citations help us demonstrate that this library is used and valued, which allows us to continue working on it.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../../support/migration-v7/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Migrating from 6.x to 7.x" rel="prev">
@@ -2003,7 +2017,7 @@ <h3 id="citation">Citation<a class="headerlink" href="#citation" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2012,7 +2026,7 @@ <h3 id="citation">Citation<a class="headerlink" href="#citation" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2025,11 +2039,13 @@ <h3 id="citation">Citation<a class="headerlink" href="#citation" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/about/license/index.html b/7.3/about/license/index.html
old mode 100755
new mode 100644
index 2ebb7665ab..fb51753261
--- a/7.3/about/license/index.html
+++ b/7.3/about/license/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/about/license/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1869,16 +1872,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/about/license.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="license">License<a class="headerlink" href="#license" title="Permanent link">&para;</a></h1>
 <p>jsPsych is <a href="https://github.com/jspsych/jsPsych/blob/main/license.txt">licensed</a> under the MIT license.</p>
 <div class="highlight"><pre><span></span><code>The MIT License (MIT)
@@ -1904,16 +1909,25 @@ <h1 id="license">License<a class="headerlink" href="#license" title="Permanent l
 SOFTWARE.
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../about/" class="md-footer__link md-footer__link--prev" aria-label="Previous: About jsPsych" rel="prev">
@@ -1957,7 +1971,7 @@ <h1 id="license">License<a class="headerlink" href="#license" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -1966,7 +1980,7 @@ <h1 id="license">License<a class="headerlink" href="#license" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -1979,11 +1993,13 @@ <h1 id="license">License<a class="headerlink" href="#license" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/assets/images/favicon.png b/7.3/assets/images/favicon.png
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/bundle.5a2dcb6a.min.js b/7.3/assets/javascripts/bundle.5a2dcb6a.min.js
new file mode 100644
index 0000000000..6f9720b673
--- /dev/null
+++ b/7.3/assets/javascripts/bundle.5a2dcb6a.min.js
@@ -0,0 +1,29 @@
+"use strict";(()=>{var aa=Object.create;var wr=Object.defineProperty;var sa=Object.getOwnPropertyDescriptor;var ca=Object.getOwnPropertyNames,kt=Object.getOwnPropertySymbols,fa=Object.getPrototypeOf,Er=Object.prototype.hasOwnProperty,fn=Object.prototype.propertyIsEnumerable;var cn=(e,t,r)=>t in e?wr(e,t,{enumerable:!0,configurable:!0,writable:!0,value:r}):e[t]=r,H=(e,t)=>{for(var r in t||(t={}))Er.call(t,r)&&cn(e,r,t[r]);if(kt)for(var r of kt(t))fn.call(t,r)&&cn(e,r,t[r]);return e};var un=(e,t)=>{var r={};for(var n in e)Er.call(e,n)&&t.indexOf(n)<0&&(r[n]=e[n]);if(e!=null&&kt)for(var n of kt(e))t.indexOf(n)<0&&fn.call(e,n)&&(r[n]=e[n]);return r};var yt=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports);var ua=(e,t,r,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let o of ca(t))!Er.call(e,o)&&o!==r&&wr(e,o,{get:()=>t[o],enumerable:!(n=sa(t,o))||n.enumerable});return e};var Ye=(e,t,r)=>(r=e!=null?aa(fa(e)):{},ua(t||!e||!e.__esModule?wr(r,"default",{value:e,enumerable:!0}):r,e));var ln=yt((Sr,pn)=>{(function(e,t){typeof Sr=="object"&&typeof pn!="undefined"?t():typeof define=="function"&&define.amd?define(t):t()})(Sr,function(){"use strict";function e(r){var n=!0,o=!1,i=null,s={text:!0,search:!0,url:!0,tel:!0,email:!0,password:!0,number:!0,date:!0,month:!0,week:!0,time:!0,datetime:!0,"datetime-local":!0};function a(_){return!!(_&&_!==document&&_.nodeName!=="HTML"&&_.nodeName!=="BODY"&&"classList"in _&&"contains"in _.classList)}function c(_){var We=_.type,Fe=_.tagName;return!!(Fe==="INPUT"&&s[We]&&!_.readOnly||Fe==="TEXTAREA"&&!_.readOnly||_.isContentEditable)}function f(_){_.classList.contains("focus-visible")||(_.classList.add("focus-visible"),_.setAttribute("data-focus-visible-added",""))}function u(_){!_.hasAttribute("data-focus-visible-added")||(_.classList.remove("focus-visible"),_.removeAttribute("data-focus-visible-added"))}function p(_){_.metaKey||_.altKey||_.ctrlKey||(a(r.activeElement)&&f(r.activeElement),n=!0)}function l(_){n=!1}function d(_){!a(_.target)||(n||c(_.target))&&f(_.target)}function h(_){!a(_.target)||(_.target.classList.contains("focus-visible")||_.target.hasAttribute("data-focus-visible-added"))&&(o=!0,window.clearTimeout(i),i=window.setTimeout(function(){o=!1},100),u(_.target))}function b(_){document.visibilityState==="hidden"&&(o&&(n=!0),U())}function U(){document.addEventListener("mousemove",W),document.addEventListener("mousedown",W),document.addEventListener("mouseup",W),document.addEventListener("pointermove",W),document.addEventListener("pointerdown",W),document.addEventListener("pointerup",W),document.addEventListener("touchmove",W),document.addEventListener("touchstart",W),document.addEventListener("touchend",W)}function G(){document.removeEventListener("mousemove",W),document.removeEventListener("mousedown",W),document.removeEventListener("mouseup",W),document.removeEventListener("pointermove",W),document.removeEventListener("pointerdown",W),document.removeEventListener("pointerup",W),document.removeEventListener("touchmove",W),document.removeEventListener("touchstart",W),document.removeEventListener("touchend",W)}function W(_){_.target.nodeName&&_.target.nodeName.toLowerCase()==="html"||(n=!1,G())}document.addEventListener("keydown",p,!0),document.addEventListener("mousedown",l,!0),document.addEventListener("pointerdown",l,!0),document.addEventListener("touchstart",l,!0),document.addEventListener("visibilitychange",b,!0),U(),r.addEventListener("focus",d,!0),r.addEventListener("blur",h,!0),r.nodeType===Node.DOCUMENT_FRAGMENT_NODE&&r.host?r.host.setAttribute("data-js-focus-visible",""):r.nodeType===Node.DOCUMENT_NODE&&(document.documentElement.classList.add("js-focus-visible"),document.documentElement.setAttribute("data-js-focus-visible",""))}if(typeof window!="undefined"&&typeof document!="undefined"){window.applyFocusVisiblePolyfill=e;var t;try{t=new CustomEvent("focus-visible-polyfill-ready")}catch(r){t=document.createEvent("CustomEvent"),t.initCustomEvent("focus-visible-polyfill-ready",!1,!1,{})}window.dispatchEvent(t)}typeof document!="undefined"&&e(document)})});var mn=yt(Or=>{(function(e){var t=function(){try{return!!Symbol.iterator}catch(f){return!1}},r=t(),n=function(f){var u={next:function(){var p=f.shift();return{done:p===void 0,value:p}}};return r&&(u[Symbol.iterator]=function(){return u}),u},o=function(f){return encodeURIComponent(f).replace(/%20/g,"+")},i=function(f){return decodeURIComponent(String(f).replace(/\+/g," "))},s=function(){var f=function(p){Object.defineProperty(this,"_entries",{writable:!0,value:{}});var l=typeof p;if(l!=="undefined")if(l==="string")p!==""&&this._fromString(p);else if(p instanceof f){var d=this;p.forEach(function(G,W){d.append(W,G)})}else if(p!==null&&l==="object")if(Object.prototype.toString.call(p)==="[object Array]")for(var h=0;h<p.length;h++){var b=p[h];if(Object.prototype.toString.call(b)==="[object Array]"||b.length!==2)this.append(b[0],b[1]);else throw new TypeError("Expected [string, any] as entry at index "+h+" of URLSearchParams's input")}else for(var U in p)p.hasOwnProperty(U)&&this.append(U,p[U]);else throw new TypeError("Unsupported input's type for URLSearchParams")},u=f.prototype;u.append=function(p,l){p in this._entries?this._entries[p].push(String(l)):this._entries[p]=[String(l)]},u.delete=function(p){delete this._entries[p]},u.get=function(p){return p in this._entries?this._entries[p][0]:null},u.getAll=function(p){return p in this._entries?this._entries[p].slice(0):[]},u.has=function(p){return p in this._entries},u.set=function(p,l){this._entries[p]=[String(l)]},u.forEach=function(p,l){var d;for(var h in this._entries)if(this._entries.hasOwnProperty(h)){d=this._entries[h];for(var b=0;b<d.length;b++)p.call(l,d[b],h,this)}},u.keys=function(){var p=[];return this.forEach(function(l,d){p.push(d)}),n(p)},u.values=function(){var p=[];return this.forEach(function(l){p.push(l)}),n(p)},u.entries=function(){var p=[];return this.forEach(function(l,d){p.push([d,l])}),n(p)},r&&(u[Symbol.iterator]=u.entries),u.toString=function(){var p=[];return this.forEach(function(l,d){p.push(o(d)+"="+o(l))}),p.join("&")},e.URLSearchParams=f},a=function(){try{var f=e.URLSearchParams;return new f("?a=1").toString()==="a=1"&&typeof f.prototype.set=="function"&&typeof f.prototype.entries=="function"}catch(u){return!1}};a()||s();var c=e.URLSearchParams.prototype;typeof c.sort!="function"&&(c.sort=function(){var f=this,u=[];this.forEach(function(l,d){u.push([d,l]),f._entries||f.delete(d)}),u.sort(function(l,d){return l[0]<d[0]?-1:l[0]>d[0]?1:0}),f._entries&&(f._entries={});for(var p=0;p<u.length;p++)this.append(u[p][0],u[p][1])}),typeof c._fromString!="function"&&Object.defineProperty(c,"_fromString",{enumerable:!1,configurable:!1,writable:!1,value:function(f){if(this._entries)this._entries={};else{var u=[];this.forEach(function(h,b){u.push(b)});for(var p=0;p<u.length;p++)this.delete(u[p])}f=f.replace(/^\?/,"");for(var l=f.split("&"),d,p=0;p<l.length;p++)d=l[p].split("="),this.append(i(d[0]),d.length>1?i(d[1]):"")}})})(typeof global!="undefined"?global:typeof window!="undefined"?window:typeof self!="undefined"?self:Or);(function(e){var t=function(){try{var o=new e.URL("b","http://a");return o.pathname="c d",o.href==="http://a/c%20d"&&o.searchParams}catch(i){return!1}},r=function(){var o=e.URL,i=function(c,f){typeof c!="string"&&(c=String(c)),f&&typeof f!="string"&&(f=String(f));var u=document,p;if(f&&(e.location===void 0||f!==e.location.href)){f=f.toLowerCase(),u=document.implementation.createHTMLDocument(""),p=u.createElement("base"),p.href=f,u.head.appendChild(p);try{if(p.href.indexOf(f)!==0)throw new Error(p.href)}catch(_){throw new Error("URL unable to set base "+f+" due to "+_)}}var l=u.createElement("a");l.href=c,p&&(u.body.appendChild(l),l.href=l.href);var d=u.createElement("input");if(d.type="url",d.value=c,l.protocol===":"||!/:/.test(l.href)||!d.checkValidity()&&!f)throw new TypeError("Invalid URL");Object.defineProperty(this,"_anchorElement",{value:l});var h=new e.URLSearchParams(this.search),b=!0,U=!0,G=this;["append","delete","set"].forEach(function(_){var We=h[_];h[_]=function(){We.apply(h,arguments),b&&(U=!1,G.search=h.toString(),U=!0)}}),Object.defineProperty(this,"searchParams",{value:h,enumerable:!0});var W=void 0;Object.defineProperty(this,"_updateSearchParams",{enumerable:!1,configurable:!1,writable:!1,value:function(){this.search!==W&&(W=this.search,U&&(b=!1,this.searchParams._fromString(this.search),b=!0))}})},s=i.prototype,a=function(c){Object.defineProperty(s,c,{get:function(){return this._anchorElement[c]},set:function(f){this._anchorElement[c]=f},enumerable:!0})};["hash","host","hostname","port","protocol"].forEach(function(c){a(c)}),Object.defineProperty(s,"search",{get:function(){return this._anchorElement.search},set:function(c){this._anchorElement.search=c,this._updateSearchParams()},enumerable:!0}),Object.defineProperties(s,{toString:{get:function(){var c=this;return function(){return c.href}}},href:{get:function(){return this._anchorElement.href.replace(/\?$/,"")},set:function(c){this._anchorElement.href=c,this._updateSearchParams()},enumerable:!0},pathname:{get:function(){return this._anchorElement.pathname.replace(/(^\/?)/,"/")},set:function(c){this._anchorElement.pathname=c},enumerable:!0},origin:{get:function(){var c={"http:":80,"https:":443,"ftp:":21}[this._anchorElement.protocol],f=this._anchorElement.port!=c&&this._anchorElement.port!=="";return this._anchorElement.protocol+"//"+this._anchorElement.hostname+(f?":"+this._anchorElement.port:"")},enumerable:!0},password:{get:function(){return""},set:function(c){},enumerable:!0},username:{get:function(){return""},set:function(c){},enumerable:!0}}),i.createObjectURL=function(c){return o.createObjectURL.apply(o,arguments)},i.revokeObjectURL=function(c){return o.revokeObjectURL.apply(o,arguments)},e.URL=i};if(t()||r(),e.location!==void 0&&!("origin"in e.location)){var n=function(){return e.location.protocol+"//"+e.location.hostname+(e.location.port?":"+e.location.port:"")};try{Object.defineProperty(e.location,"origin",{get:n,enumerable:!0})}catch(o){setInterval(function(){e.location.origin=n()},100)}}})(typeof global!="undefined"?global:typeof window!="undefined"?window:typeof self!="undefined"?self:Or)});var Pn=yt((Ks,$t)=>{/*! *****************************************************************************
+Copyright (c) Microsoft Corporation.
+
+Permission to use, copy, modify, and/or distribute this software for any
+purpose with or without fee is hereby granted.
+
+THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
+REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
+AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
+INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
+LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
+OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
+PERFORMANCE OF THIS SOFTWARE.
+***************************************************************************** */var dn,hn,bn,vn,gn,yn,xn,wn,En,Ht,_r,Sn,On,_n,rt,Tn,Mn,Ln,An,Cn,Rn,kn,Hn,Pt;(function(e){var t=typeof global=="object"?global:typeof self=="object"?self:typeof this=="object"?this:{};typeof define=="function"&&define.amd?define("tslib",["exports"],function(n){e(r(t,r(n)))}):typeof $t=="object"&&typeof $t.exports=="object"?e(r(t,r($t.exports))):e(r(t));function r(n,o){return n!==t&&(typeof Object.create=="function"?Object.defineProperty(n,"__esModule",{value:!0}):n.__esModule=!0),function(i,s){return n[i]=o?o(i,s):s}}})(function(e){var t=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(n,o){n.__proto__=o}||function(n,o){for(var i in o)Object.prototype.hasOwnProperty.call(o,i)&&(n[i]=o[i])};dn=function(n,o){if(typeof o!="function"&&o!==null)throw new TypeError("Class extends value "+String(o)+" is not a constructor or null");t(n,o);function i(){this.constructor=n}n.prototype=o===null?Object.create(o):(i.prototype=o.prototype,new i)},hn=Object.assign||function(n){for(var o,i=1,s=arguments.length;i<s;i++){o=arguments[i];for(var a in o)Object.prototype.hasOwnProperty.call(o,a)&&(n[a]=o[a])}return n},bn=function(n,o){var i={};for(var s in n)Object.prototype.hasOwnProperty.call(n,s)&&o.indexOf(s)<0&&(i[s]=n[s]);if(n!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,s=Object.getOwnPropertySymbols(n);a<s.length;a++)o.indexOf(s[a])<0&&Object.prototype.propertyIsEnumerable.call(n,s[a])&&(i[s[a]]=n[s[a]]);return i},vn=function(n,o,i,s){var a=arguments.length,c=a<3?o:s===null?s=Object.getOwnPropertyDescriptor(o,i):s,f;if(typeof Reflect=="object"&&typeof Reflect.decorate=="function")c=Reflect.decorate(n,o,i,s);else for(var u=n.length-1;u>=0;u--)(f=n[u])&&(c=(a<3?f(c):a>3?f(o,i,c):f(o,i))||c);return a>3&&c&&Object.defineProperty(o,i,c),c},gn=function(n,o){return function(i,s){o(i,s,n)}},yn=function(n,o){if(typeof Reflect=="object"&&typeof Reflect.metadata=="function")return Reflect.metadata(n,o)},xn=function(n,o,i,s){function a(c){return c instanceof i?c:new i(function(f){f(c)})}return new(i||(i=Promise))(function(c,f){function u(d){try{l(s.next(d))}catch(h){f(h)}}function p(d){try{l(s.throw(d))}catch(h){f(h)}}function l(d){d.done?c(d.value):a(d.value).then(u,p)}l((s=s.apply(n,o||[])).next())})},wn=function(n,o){var i={label:0,sent:function(){if(c[0]&1)throw c[1];return c[1]},trys:[],ops:[]},s,a,c,f;return f={next:u(0),throw:u(1),return:u(2)},typeof Symbol=="function"&&(f[Symbol.iterator]=function(){return this}),f;function u(l){return function(d){return p([l,d])}}function p(l){if(s)throw new TypeError("Generator is already executing.");for(;i;)try{if(s=1,a&&(c=l[0]&2?a.return:l[0]?a.throw||((c=a.return)&&c.call(a),0):a.next)&&!(c=c.call(a,l[1])).done)return c;switch(a=0,c&&(l=[l[0]&2,c.value]),l[0]){case 0:case 1:c=l;break;case 4:return i.label++,{value:l[1],done:!1};case 5:i.label++,a=l[1],l=[0];continue;case 7:l=i.ops.pop(),i.trys.pop();continue;default:if(c=i.trys,!(c=c.length>0&&c[c.length-1])&&(l[0]===6||l[0]===2)){i=0;continue}if(l[0]===3&&(!c||l[1]>c[0]&&l[1]<c[3])){i.label=l[1];break}if(l[0]===6&&i.label<c[1]){i.label=c[1],c=l;break}if(c&&i.label<c[2]){i.label=c[2],i.ops.push(l);break}c[2]&&i.ops.pop(),i.trys.pop();continue}l=o.call(n,i)}catch(d){l=[6,d],a=0}finally{s=c=0}if(l[0]&5)throw l[1];return{value:l[0]?l[1]:void 0,done:!0}}},En=function(n,o){for(var i in n)i!=="default"&&!Object.prototype.hasOwnProperty.call(o,i)&&Pt(o,n,i)},Pt=Object.create?function(n,o,i,s){s===void 0&&(s=i),Object.defineProperty(n,s,{enumerable:!0,get:function(){return o[i]}})}:function(n,o,i,s){s===void 0&&(s=i),n[s]=o[i]},Ht=function(n){var o=typeof Symbol=="function"&&Symbol.iterator,i=o&&n[o],s=0;if(i)return i.call(n);if(n&&typeof n.length=="number")return{next:function(){return n&&s>=n.length&&(n=void 0),{value:n&&n[s++],done:!n}}};throw new TypeError(o?"Object is not iterable.":"Symbol.iterator is not defined.")},_r=function(n,o){var i=typeof Symbol=="function"&&n[Symbol.iterator];if(!i)return n;var s=i.call(n),a,c=[],f;try{for(;(o===void 0||o-- >0)&&!(a=s.next()).done;)c.push(a.value)}catch(u){f={error:u}}finally{try{a&&!a.done&&(i=s.return)&&i.call(s)}finally{if(f)throw f.error}}return c},Sn=function(){for(var n=[],o=0;o<arguments.length;o++)n=n.concat(_r(arguments[o]));return n},On=function(){for(var n=0,o=0,i=arguments.length;o<i;o++)n+=arguments[o].length;for(var s=Array(n),a=0,o=0;o<i;o++)for(var c=arguments[o],f=0,u=c.length;f<u;f++,a++)s[a]=c[f];return s},_n=function(n,o,i){if(i||arguments.length===2)for(var s=0,a=o.length,c;s<a;s++)(c||!(s in o))&&(c||(c=Array.prototype.slice.call(o,0,s)),c[s]=o[s]);return n.concat(c||Array.prototype.slice.call(o))},rt=function(n){return this instanceof rt?(this.v=n,this):new rt(n)},Tn=function(n,o,i){if(!Symbol.asyncIterator)throw new TypeError("Symbol.asyncIterator is not defined.");var s=i.apply(n,o||[]),a,c=[];return a={},f("next"),f("throw"),f("return"),a[Symbol.asyncIterator]=function(){return this},a;function f(b){s[b]&&(a[b]=function(U){return new Promise(function(G,W){c.push([b,U,G,W])>1||u(b,U)})})}function u(b,U){try{p(s[b](U))}catch(G){h(c[0][3],G)}}function p(b){b.value instanceof rt?Promise.resolve(b.value.v).then(l,d):h(c[0][2],b)}function l(b){u("next",b)}function d(b){u("throw",b)}function h(b,U){b(U),c.shift(),c.length&&u(c[0][0],c[0][1])}},Mn=function(n){var o,i;return o={},s("next"),s("throw",function(a){throw a}),s("return"),o[Symbol.iterator]=function(){return this},o;function s(a,c){o[a]=n[a]?function(f){return(i=!i)?{value:rt(n[a](f)),done:a==="return"}:c?c(f):f}:c}},Ln=function(n){if(!Symbol.asyncIterator)throw new TypeError("Symbol.asyncIterator is not defined.");var o=n[Symbol.asyncIterator],i;return o?o.call(n):(n=typeof Ht=="function"?Ht(n):n[Symbol.iterator](),i={},s("next"),s("throw"),s("return"),i[Symbol.asyncIterator]=function(){return this},i);function s(c){i[c]=n[c]&&function(f){return new Promise(function(u,p){f=n[c](f),a(u,p,f.done,f.value)})}}function a(c,f,u,p){Promise.resolve(p).then(function(l){c({value:l,done:u})},f)}},An=function(n,o){return Object.defineProperty?Object.defineProperty(n,"raw",{value:o}):n.raw=o,n};var r=Object.create?function(n,o){Object.defineProperty(n,"default",{enumerable:!0,value:o})}:function(n,o){n.default=o};Cn=function(n){if(n&&n.__esModule)return n;var o={};if(n!=null)for(var i in n)i!=="default"&&Object.prototype.hasOwnProperty.call(n,i)&&Pt(o,n,i);return r(o,n),o},Rn=function(n){return n&&n.__esModule?n:{default:n}},kn=function(n,o,i,s){if(i==="a"&&!s)throw new TypeError("Private accessor was defined without a getter");if(typeof o=="function"?n!==o||!s:!o.has(n))throw new TypeError("Cannot read private member from an object whose class did not declare it");return i==="m"?s:i==="a"?s.call(n):s?s.value:o.get(n)},Hn=function(n,o,i,s,a){if(s==="m")throw new TypeError("Private method is not writable");if(s==="a"&&!a)throw new TypeError("Private accessor was defined without a setter");if(typeof o=="function"?n!==o||!a:!o.has(n))throw new TypeError("Cannot write private member to an object whose class did not declare it");return s==="a"?a.call(n,i):a?a.value=i:o.set(n,i),i},e("__extends",dn),e("__assign",hn),e("__rest",bn),e("__decorate",vn),e("__param",gn),e("__metadata",yn),e("__awaiter",xn),e("__generator",wn),e("__exportStar",En),e("__createBinding",Pt),e("__values",Ht),e("__read",_r),e("__spread",Sn),e("__spreadArrays",On),e("__spreadArray",_n),e("__await",rt),e("__asyncGenerator",Tn),e("__asyncDelegator",Mn),e("__asyncValues",Ln),e("__makeTemplateObject",An),e("__importStar",Cn),e("__importDefault",Rn),e("__classPrivateFieldGet",kn),e("__classPrivateFieldSet",Hn)})});var Br=yt((At,Yr)=>{/*!
+ * clipboard.js v2.0.11
+ * https://clipboardjs.com/
+ *
+ * Licensed MIT © Zeno Rocha
+ */(function(t,r){typeof At=="object"&&typeof Yr=="object"?Yr.exports=r():typeof define=="function"&&define.amd?define([],r):typeof At=="object"?At.ClipboardJS=r():t.ClipboardJS=r()})(At,function(){return function(){var e={686:function(n,o,i){"use strict";i.d(o,{default:function(){return ia}});var s=i(279),a=i.n(s),c=i(370),f=i.n(c),u=i(817),p=i.n(u);function l(j){try{return document.execCommand(j)}catch(T){return!1}}var d=function(T){var O=p()(T);return l("cut"),O},h=d;function b(j){var T=document.documentElement.getAttribute("dir")==="rtl",O=document.createElement("textarea");O.style.fontSize="12pt",O.style.border="0",O.style.padding="0",O.style.margin="0",O.style.position="absolute",O.style[T?"right":"left"]="-9999px";var k=window.pageYOffset||document.documentElement.scrollTop;return O.style.top="".concat(k,"px"),O.setAttribute("readonly",""),O.value=j,O}var U=function(T,O){var k=b(T);O.container.appendChild(k);var $=p()(k);return l("copy"),k.remove(),$},G=function(T){var O=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{container:document.body},k="";return typeof T=="string"?k=U(T,O):T instanceof HTMLInputElement&&!["text","search","url","tel","password"].includes(T==null?void 0:T.type)?k=U(T.value,O):(k=p()(T),l("copy")),k},W=G;function _(j){return typeof Symbol=="function"&&typeof Symbol.iterator=="symbol"?_=function(O){return typeof O}:_=function(O){return O&&typeof Symbol=="function"&&O.constructor===Symbol&&O!==Symbol.prototype?"symbol":typeof O},_(j)}var We=function(){var T=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{},O=T.action,k=O===void 0?"copy":O,$=T.container,q=T.target,Te=T.text;if(k!=="copy"&&k!=="cut")throw new Error('Invalid "action" value, use either "copy" or "cut"');if(q!==void 0)if(q&&_(q)==="object"&&q.nodeType===1){if(k==="copy"&&q.hasAttribute("disabled"))throw new Error('Invalid "target" attribute. Please use "readonly" instead of "disabled" attribute');if(k==="cut"&&(q.hasAttribute("readonly")||q.hasAttribute("disabled")))throw new Error(`Invalid "target" attribute. You can't cut text from elements with "readonly" or "disabled" attributes`)}else throw new Error('Invalid "target" value, use a valid Element');if(Te)return W(Te,{container:$});if(q)return k==="cut"?h(q):W(q,{container:$})},Fe=We;function Pe(j){return typeof Symbol=="function"&&typeof Symbol.iterator=="symbol"?Pe=function(O){return typeof O}:Pe=function(O){return O&&typeof Symbol=="function"&&O.constructor===Symbol&&O!==Symbol.prototype?"symbol":typeof O},Pe(j)}function Ji(j,T){if(!(j instanceof T))throw new TypeError("Cannot call a class as a function")}function sn(j,T){for(var O=0;O<T.length;O++){var k=T[O];k.enumerable=k.enumerable||!1,k.configurable=!0,"value"in k&&(k.writable=!0),Object.defineProperty(j,k.key,k)}}function Xi(j,T,O){return T&&sn(j.prototype,T),O&&sn(j,O),j}function Zi(j,T){if(typeof T!="function"&&T!==null)throw new TypeError("Super expression must either be null or a function");j.prototype=Object.create(T&&T.prototype,{constructor:{value:j,writable:!0,configurable:!0}}),T&&yr(j,T)}function yr(j,T){return yr=Object.setPrototypeOf||function(k,$){return k.__proto__=$,k},yr(j,T)}function ea(j){var T=na();return function(){var k=Ct(j),$;if(T){var q=Ct(this).constructor;$=Reflect.construct(k,arguments,q)}else $=k.apply(this,arguments);return ta(this,$)}}function ta(j,T){return T&&(Pe(T)==="object"||typeof T=="function")?T:ra(j)}function ra(j){if(j===void 0)throw new ReferenceError("this hasn't been initialised - super() hasn't been called");return j}function na(){if(typeof Reflect=="undefined"||!Reflect.construct||Reflect.construct.sham)return!1;if(typeof Proxy=="function")return!0;try{return Date.prototype.toString.call(Reflect.construct(Date,[],function(){})),!0}catch(j){return!1}}function Ct(j){return Ct=Object.setPrototypeOf?Object.getPrototypeOf:function(O){return O.__proto__||Object.getPrototypeOf(O)},Ct(j)}function xr(j,T){var O="data-clipboard-".concat(j);if(!!T.hasAttribute(O))return T.getAttribute(O)}var oa=function(j){Zi(O,j);var T=ea(O);function O(k,$){var q;return Ji(this,O),q=T.call(this),q.resolveOptions($),q.listenClick(k),q}return Xi(O,[{key:"resolveOptions",value:function(){var $=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{};this.action=typeof $.action=="function"?$.action:this.defaultAction,this.target=typeof $.target=="function"?$.target:this.defaultTarget,this.text=typeof $.text=="function"?$.text:this.defaultText,this.container=Pe($.container)==="object"?$.container:document.body}},{key:"listenClick",value:function($){var q=this;this.listener=f()($,"click",function(Te){return q.onClick(Te)})}},{key:"onClick",value:function($){var q=$.delegateTarget||$.currentTarget,Te=this.action(q)||"copy",Rt=Fe({action:Te,container:this.container,target:this.target(q),text:this.text(q)});this.emit(Rt?"success":"error",{action:Te,text:Rt,trigger:q,clearSelection:function(){q&&q.focus(),window.getSelection().removeAllRanges()}})}},{key:"defaultAction",value:function($){return xr("action",$)}},{key:"defaultTarget",value:function($){var q=xr("target",$);if(q)return document.querySelector(q)}},{key:"defaultText",value:function($){return xr("text",$)}},{key:"destroy",value:function(){this.listener.destroy()}}],[{key:"copy",value:function($){var q=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{container:document.body};return W($,q)}},{key:"cut",value:function($){return h($)}},{key:"isSupported",value:function(){var $=arguments.length>0&&arguments[0]!==void 0?arguments[0]:["copy","cut"],q=typeof $=="string"?[$]:$,Te=!!document.queryCommandSupported;return q.forEach(function(Rt){Te=Te&&!!document.queryCommandSupported(Rt)}),Te}}]),O}(a()),ia=oa},828:function(n){var o=9;if(typeof Element!="undefined"&&!Element.prototype.matches){var i=Element.prototype;i.matches=i.matchesSelector||i.mozMatchesSelector||i.msMatchesSelector||i.oMatchesSelector||i.webkitMatchesSelector}function s(a,c){for(;a&&a.nodeType!==o;){if(typeof a.matches=="function"&&a.matches(c))return a;a=a.parentNode}}n.exports=s},438:function(n,o,i){var s=i(828);function a(u,p,l,d,h){var b=f.apply(this,arguments);return u.addEventListener(l,b,h),{destroy:function(){u.removeEventListener(l,b,h)}}}function c(u,p,l,d,h){return typeof u.addEventListener=="function"?a.apply(null,arguments):typeof l=="function"?a.bind(null,document).apply(null,arguments):(typeof u=="string"&&(u=document.querySelectorAll(u)),Array.prototype.map.call(u,function(b){return a(b,p,l,d,h)}))}function f(u,p,l,d){return function(h){h.delegateTarget=s(h.target,p),h.delegateTarget&&d.call(u,h)}}n.exports=c},879:function(n,o){o.node=function(i){return i!==void 0&&i instanceof HTMLElement&&i.nodeType===1},o.nodeList=function(i){var s=Object.prototype.toString.call(i);return i!==void 0&&(s==="[object NodeList]"||s==="[object HTMLCollection]")&&"length"in i&&(i.length===0||o.node(i[0]))},o.string=function(i){return typeof i=="string"||i instanceof String},o.fn=function(i){var s=Object.prototype.toString.call(i);return s==="[object Function]"}},370:function(n,o,i){var s=i(879),a=i(438);function c(l,d,h){if(!l&&!d&&!h)throw new Error("Missing required arguments");if(!s.string(d))throw new TypeError("Second argument must be a String");if(!s.fn(h))throw new TypeError("Third argument must be a Function");if(s.node(l))return f(l,d,h);if(s.nodeList(l))return u(l,d,h);if(s.string(l))return p(l,d,h);throw new TypeError("First argument must be a String, HTMLElement, HTMLCollection, or NodeList")}function f(l,d,h){return l.addEventListener(d,h),{destroy:function(){l.removeEventListener(d,h)}}}function u(l,d,h){return Array.prototype.forEach.call(l,function(b){b.addEventListener(d,h)}),{destroy:function(){Array.prototype.forEach.call(l,function(b){b.removeEventListener(d,h)})}}}function p(l,d,h){return a(document.body,l,d,h)}n.exports=c},817:function(n){function o(i){var s;if(i.nodeName==="SELECT")i.focus(),s=i.value;else if(i.nodeName==="INPUT"||i.nodeName==="TEXTAREA"){var a=i.hasAttribute("readonly");a||i.setAttribute("readonly",""),i.select(),i.setSelectionRange(0,i.value.length),a||i.removeAttribute("readonly"),s=i.value}else{i.hasAttribute("contenteditable")&&i.focus();var c=window.getSelection(),f=document.createRange();f.selectNodeContents(i),c.removeAllRanges(),c.addRange(f),s=c.toString()}return s}n.exports=o},279:function(n){function o(){}o.prototype={on:function(i,s,a){var c=this.e||(this.e={});return(c[i]||(c[i]=[])).push({fn:s,ctx:a}),this},once:function(i,s,a){var c=this;function f(){c.off(i,f),s.apply(a,arguments)}return f._=s,this.on(i,f,a)},emit:function(i){var s=[].slice.call(arguments,1),a=((this.e||(this.e={}))[i]||[]).slice(),c=0,f=a.length;for(c;c<f;c++)a[c].fn.apply(a[c].ctx,s);return this},off:function(i,s){var a=this.e||(this.e={}),c=a[i],f=[];if(c&&s)for(var u=0,p=c.length;u<p;u++)c[u].fn!==s&&c[u].fn._!==s&&f.push(c[u]);return f.length?a[i]=f:delete a[i],this}},n.exports=o,n.exports.TinyEmitter=o}},t={};function r(n){if(t[n])return t[n].exports;var o=t[n]={exports:{}};return e[n](o,o.exports,r),o.exports}return function(){r.n=function(n){var o=n&&n.__esModule?function(){return n.default}:function(){return n};return r.d(o,{a:o}),o}}(),function(){r.d=function(n,o){for(var i in o)r.o(o,i)&&!r.o(n,i)&&Object.defineProperty(n,i,{enumerable:!0,get:o[i]})}}(),function(){r.o=function(n,o){return Object.prototype.hasOwnProperty.call(n,o)}}(),r(686)}().default})});var tn=yt((eE,Si)=>{"use strict";/*!
+ * escape-html
+ * Copyright(c) 2012-2013 TJ Holowaychuk
+ * Copyright(c) 2015 Andreas Lubbe
+ * Copyright(c) 2015 Tiancheng "Timothy" Gu
+ * MIT Licensed
+ */var Ms=/["'&<>]/;Si.exports=Ls;function Ls(e){var t=""+e,r=Ms.exec(t);if(!r)return t;var n,o="",i=0,s=0;for(i=r.index;i<t.length;i++){switch(t.charCodeAt(i)){case 34:n="&quot;";break;case 38:n="&amp;";break;case 39:n="&#39;";break;case 60:n="&lt;";break;case 62:n="&gt;";break;default:continue}s!==i&&(o+=t.substring(s,i)),s=i+1,o+=n}return s!==i?o+t.substring(s,i):o}});Array.prototype.flat||Object.defineProperty(Array.prototype,"flat",{configurable:!0,value:function e(){var t=isNaN(arguments[0])?1:Number(arguments[0]);return t?Array.prototype.reduce.call(this,function(r,n){return Array.isArray(n)?r.push.apply(r,e.call(n,t-1)):r.push(n),r},[]):Array.prototype.slice.call(this)},writable:!0}),Array.prototype.flatMap||Object.defineProperty(Array.prototype,"flatMap",{configurable:!0,value:function(e){return Array.prototype.map.apply(this,arguments).flat()},writable:!0});var X_=Ye(ln());self.fetch||(self.fetch=function(e,t){return t=t||{},new Promise(function(r,n){var o=new XMLHttpRequest,i=[],s=[],a={},c=function(){return{ok:(o.status/100|0)==2,statusText:o.statusText,status:o.status,url:o.responseURL,text:function(){return Promise.resolve(o.responseText)},json:function(){return Promise.resolve(o.responseText).then(JSON.parse)},blob:function(){return Promise.resolve(new Blob([o.response]))},clone:c,headers:{keys:function(){return i},entries:function(){return s},get:function(u){return a[u.toLowerCase()]},has:function(u){return u.toLowerCase()in a}}}};for(var f in o.open(t.method||"get",e,!0),o.onload=function(){o.getAllResponseHeaders().replace(/^(.*?):[^\S\n]*([\s\S]*?)$/gm,function(u,p,l){i.push(p=p.toLowerCase()),s.push([p,l]),a[p]=a[p]?a[p]+","+l:l}),r(c())},o.onerror=n,o.withCredentials=t.credentials=="include",t.headers)o.setRequestHeader(f,t.headers[f]);o.send(t.body||null)})});var eT=Ye(mn());var $n=Ye(Pn(),1),{__extends:ne,__assign:Qs,__rest:Ys,__decorate:Bs,__param:Gs,__metadata:Js,__awaiter:In,__generator:It,__exportStar:Xs,__createBinding:Zs,__values:ge,__read:D,__spread:ec,__spreadArrays:tc,__spreadArray:V,__await:jt,__asyncGenerator:jn,__asyncDelegator:rc,__asyncValues:Fn,__makeTemplateObject:nc,__importStar:oc,__importDefault:ic,__classPrivateFieldGet:ac,__classPrivateFieldSet:sc}=$n.default;function L(e){return typeof e=="function"}function Ft(e){var t=function(n){Error.call(n),n.stack=new Error().stack},r=e(t);return r.prototype=Object.create(Error.prototype),r.prototype.constructor=r,r}var Ut=Ft(function(e){return function(r){e(this),this.message=r?r.length+` errors occurred during unsubscription:
+`+r.map(function(n,o){return o+1+") "+n.toString()}).join(`
+  `):"",this.name="UnsubscriptionError",this.errors=r}});function Ue(e,t){if(e){var r=e.indexOf(t);0<=r&&e.splice(r,1)}}var $e=function(){function e(t){this.initialTeardown=t,this.closed=!1,this._parentage=null,this._finalizers=null}return e.prototype.unsubscribe=function(){var t,r,n,o,i;if(!this.closed){this.closed=!0;var s=this._parentage;if(s)if(this._parentage=null,Array.isArray(s))try{for(var a=ge(s),c=a.next();!c.done;c=a.next()){var f=c.value;f.remove(this)}}catch(b){t={error:b}}finally{try{c&&!c.done&&(r=a.return)&&r.call(a)}finally{if(t)throw t.error}}else s.remove(this);var u=this.initialTeardown;if(L(u))try{u()}catch(b){i=b instanceof Ut?b.errors:[b]}var p=this._finalizers;if(p){this._finalizers=null;try{for(var l=ge(p),d=l.next();!d.done;d=l.next()){var h=d.value;try{Un(h)}catch(b){i=i!=null?i:[],b instanceof Ut?i=V(V([],D(i)),D(b.errors)):i.push(b)}}}catch(b){n={error:b}}finally{try{d&&!d.done&&(o=l.return)&&o.call(l)}finally{if(n)throw n.error}}}if(i)throw new Ut(i)}},e.prototype.add=function(t){var r;if(t&&t!==this)if(this.closed)Un(t);else{if(t instanceof e){if(t.closed||t._hasParent(this))return;t._addParent(this)}(this._finalizers=(r=this._finalizers)!==null&&r!==void 0?r:[]).push(t)}},e.prototype._hasParent=function(t){var r=this._parentage;return r===t||Array.isArray(r)&&r.includes(t)},e.prototype._addParent=function(t){var r=this._parentage;this._parentage=Array.isArray(r)?(r.push(t),r):r?[r,t]:t},e.prototype._removeParent=function(t){var r=this._parentage;r===t?this._parentage=null:Array.isArray(r)&&Ue(r,t)},e.prototype.remove=function(t){var r=this._finalizers;r&&Ue(r,t),t instanceof e&&t._removeParent(this)},e.EMPTY=function(){var t=new e;return t.closed=!0,t}(),e}();var Tr=$e.EMPTY;function Dt(e){return e instanceof $e||e&&"closed"in e&&L(e.remove)&&L(e.add)&&L(e.unsubscribe)}function Un(e){L(e)?e():e.unsubscribe()}var Me={onUnhandledError:null,onStoppedNotification:null,Promise:void 0,useDeprecatedSynchronousErrorHandling:!1,useDeprecatedNextContext:!1};var nt={setTimeout:function(e,t){for(var r=[],n=2;n<arguments.length;n++)r[n-2]=arguments[n];var o=nt.delegate;return o!=null&&o.setTimeout?o.setTimeout.apply(o,V([e,t],D(r))):setTimeout.apply(void 0,V([e,t],D(r)))},clearTimeout:function(e){var t=nt.delegate;return((t==null?void 0:t.clearTimeout)||clearTimeout)(e)},delegate:void 0};function Wt(e){nt.setTimeout(function(){var t=Me.onUnhandledError;if(t)t(e);else throw e})}function me(){}var Dn=function(){return Mr("C",void 0,void 0)}();function Wn(e){return Mr("E",void 0,e)}function Vn(e){return Mr("N",e,void 0)}function Mr(e,t,r){return{kind:e,value:t,error:r}}var Be=null;function ot(e){if(Me.useDeprecatedSynchronousErrorHandling){var t=!Be;if(t&&(Be={errorThrown:!1,error:null}),e(),t){var r=Be,n=r.errorThrown,o=r.error;if(Be=null,n)throw o}}else e()}function zn(e){Me.useDeprecatedSynchronousErrorHandling&&Be&&(Be.errorThrown=!0,Be.error=e)}var xt=function(e){ne(t,e);function t(r){var n=e.call(this)||this;return n.isStopped=!1,r?(n.destination=r,Dt(r)&&r.add(n)):n.destination=da,n}return t.create=function(r,n,o){return new Ge(r,n,o)},t.prototype.next=function(r){this.isStopped?Ar(Vn(r),this):this._next(r)},t.prototype.error=function(r){this.isStopped?Ar(Wn(r),this):(this.isStopped=!0,this._error(r))},t.prototype.complete=function(){this.isStopped?Ar(Dn,this):(this.isStopped=!0,this._complete())},t.prototype.unsubscribe=function(){this.closed||(this.isStopped=!0,e.prototype.unsubscribe.call(this),this.destination=null)},t.prototype._next=function(r){this.destination.next(r)},t.prototype._error=function(r){try{this.destination.error(r)}finally{this.unsubscribe()}},t.prototype._complete=function(){try{this.destination.complete()}finally{this.unsubscribe()}},t}($e);var pa=Function.prototype.bind;function Lr(e,t){return pa.call(e,t)}var la=function(){function e(t){this.partialObserver=t}return e.prototype.next=function(t){var r=this.partialObserver;if(r.next)try{r.next(t)}catch(n){Vt(n)}},e.prototype.error=function(t){var r=this.partialObserver;if(r.error)try{r.error(t)}catch(n){Vt(n)}else Vt(t)},e.prototype.complete=function(){var t=this.partialObserver;if(t.complete)try{t.complete()}catch(r){Vt(r)}},e}(),Ge=function(e){ne(t,e);function t(r,n,o){var i=e.call(this)||this,s;if(L(r)||!r)s={next:r!=null?r:void 0,error:n!=null?n:void 0,complete:o!=null?o:void 0};else{var a;i&&Me.useDeprecatedNextContext?(a=Object.create(r),a.unsubscribe=function(){return i.unsubscribe()},s={next:r.next&&Lr(r.next,a),error:r.error&&Lr(r.error,a),complete:r.complete&&Lr(r.complete,a)}):s=r}return i.destination=new la(s),i}return t}(xt);function Vt(e){Me.useDeprecatedSynchronousErrorHandling?zn(e):Wt(e)}function ma(e){throw e}function Ar(e,t){var r=Me.onStoppedNotification;r&&nt.setTimeout(function(){return r(e,t)})}var da={closed:!0,next:me,error:ma,complete:me};var it=function(){return typeof Symbol=="function"&&Symbol.observable||"@@observable"}();function ye(e){return e}function Nn(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return Cr(e)}function Cr(e){return e.length===0?ye:e.length===1?e[0]:function(r){return e.reduce(function(n,o){return o(n)},r)}}var F=function(){function e(t){t&&(this._subscribe=t)}return e.prototype.lift=function(t){var r=new e;return r.source=this,r.operator=t,r},e.prototype.subscribe=function(t,r,n){var o=this,i=ba(t)?t:new Ge(t,r,n);return ot(function(){var s=o,a=s.operator,c=s.source;i.add(a?a.call(i,c):c?o._subscribe(i):o._trySubscribe(i))}),i},e.prototype._trySubscribe=function(t){try{return this._subscribe(t)}catch(r){t.error(r)}},e.prototype.forEach=function(t,r){var n=this;return r=qn(r),new r(function(o,i){var s=new Ge({next:function(a){try{t(a)}catch(c){i(c),s.unsubscribe()}},error:i,complete:o});n.subscribe(s)})},e.prototype._subscribe=function(t){var r;return(r=this.source)===null||r===void 0?void 0:r.subscribe(t)},e.prototype[it]=function(){return this},e.prototype.pipe=function(){for(var t=[],r=0;r<arguments.length;r++)t[r]=arguments[r];return Cr(t)(this)},e.prototype.toPromise=function(t){var r=this;return t=qn(t),new t(function(n,o){var i;r.subscribe(function(s){return i=s},function(s){return o(s)},function(){return n(i)})})},e.create=function(t){return new e(t)},e}();function qn(e){var t;return(t=e!=null?e:Me.Promise)!==null&&t!==void 0?t:Promise}function ha(e){return e&&L(e.next)&&L(e.error)&&L(e.complete)}function ba(e){return e&&e instanceof xt||ha(e)&&Dt(e)}function va(e){return L(e==null?void 0:e.lift)}function g(e){return function(t){if(va(t))return t.lift(function(r){try{return e(r,this)}catch(n){this.error(n)}});throw new TypeError("Unable to lift unknown Observable type")}}function y(e,t,r,n,o){return new ga(e,t,r,n,o)}var ga=function(e){ne(t,e);function t(r,n,o,i,s,a){var c=e.call(this,r)||this;return c.onFinalize=s,c.shouldUnsubscribe=a,c._next=n?function(f){try{n(f)}catch(u){r.error(u)}}:e.prototype._next,c._error=i?function(f){try{i(f)}catch(u){r.error(u)}finally{this.unsubscribe()}}:e.prototype._error,c._complete=o?function(){try{o()}catch(f){r.error(f)}finally{this.unsubscribe()}}:e.prototype._complete,c}return t.prototype.unsubscribe=function(){var r;if(!this.shouldUnsubscribe||this.shouldUnsubscribe()){var n=this.closed;e.prototype.unsubscribe.call(this),!n&&((r=this.onFinalize)===null||r===void 0||r.call(this))}},t}(xt);var at={schedule:function(e){var t=requestAnimationFrame,r=cancelAnimationFrame,n=at.delegate;n&&(t=n.requestAnimationFrame,r=n.cancelAnimationFrame);var o=t(function(i){r=void 0,e(i)});return new $e(function(){return r==null?void 0:r(o)})},requestAnimationFrame:function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=at.delegate;return((r==null?void 0:r.requestAnimationFrame)||requestAnimationFrame).apply(void 0,V([],D(e)))},cancelAnimationFrame:function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=at.delegate;return((r==null?void 0:r.cancelAnimationFrame)||cancelAnimationFrame).apply(void 0,V([],D(e)))},delegate:void 0};var Kn=Ft(function(e){return function(){e(this),this.name="ObjectUnsubscribedError",this.message="object unsubscribed"}});var E=function(e){ne(t,e);function t(){var r=e.call(this)||this;return r.closed=!1,r.currentObservers=null,r.observers=[],r.isStopped=!1,r.hasError=!1,r.thrownError=null,r}return t.prototype.lift=function(r){var n=new Qn(this,this);return n.operator=r,n},t.prototype._throwIfClosed=function(){if(this.closed)throw new Kn},t.prototype.next=function(r){var n=this;ot(function(){var o,i;if(n._throwIfClosed(),!n.isStopped){n.currentObservers||(n.currentObservers=Array.from(n.observers));try{for(var s=ge(n.currentObservers),a=s.next();!a.done;a=s.next()){var c=a.value;c.next(r)}}catch(f){o={error:f}}finally{try{a&&!a.done&&(i=s.return)&&i.call(s)}finally{if(o)throw o.error}}}})},t.prototype.error=function(r){var n=this;ot(function(){if(n._throwIfClosed(),!n.isStopped){n.hasError=n.isStopped=!0,n.thrownError=r;for(var o=n.observers;o.length;)o.shift().error(r)}})},t.prototype.complete=function(){var r=this;ot(function(){if(r._throwIfClosed(),!r.isStopped){r.isStopped=!0;for(var n=r.observers;n.length;)n.shift().complete()}})},t.prototype.unsubscribe=function(){this.isStopped=this.closed=!0,this.observers=this.currentObservers=null},Object.defineProperty(t.prototype,"observed",{get:function(){var r;return((r=this.observers)===null||r===void 0?void 0:r.length)>0},enumerable:!1,configurable:!0}),t.prototype._trySubscribe=function(r){return this._throwIfClosed(),e.prototype._trySubscribe.call(this,r)},t.prototype._subscribe=function(r){return this._throwIfClosed(),this._checkFinalizedStatuses(r),this._innerSubscribe(r)},t.prototype._innerSubscribe=function(r){var n=this,o=this,i=o.hasError,s=o.isStopped,a=o.observers;return i||s?Tr:(this.currentObservers=null,a.push(r),new $e(function(){n.currentObservers=null,Ue(a,r)}))},t.prototype._checkFinalizedStatuses=function(r){var n=this,o=n.hasError,i=n.thrownError,s=n.isStopped;o?r.error(i):s&&r.complete()},t.prototype.asObservable=function(){var r=new F;return r.source=this,r},t.create=function(r,n){return new Qn(r,n)},t}(F);var Qn=function(e){ne(t,e);function t(r,n){var o=e.call(this)||this;return o.destination=r,o.source=n,o}return t.prototype.next=function(r){var n,o;(o=(n=this.destination)===null||n===void 0?void 0:n.next)===null||o===void 0||o.call(n,r)},t.prototype.error=function(r){var n,o;(o=(n=this.destination)===null||n===void 0?void 0:n.error)===null||o===void 0||o.call(n,r)},t.prototype.complete=function(){var r,n;(n=(r=this.destination)===null||r===void 0?void 0:r.complete)===null||n===void 0||n.call(r)},t.prototype._subscribe=function(r){var n,o;return(o=(n=this.source)===null||n===void 0?void 0:n.subscribe(r))!==null&&o!==void 0?o:Tr},t}(E);var wt={now:function(){return(wt.delegate||Date).now()},delegate:void 0};var Et=function(e){ne(t,e);function t(r,n,o){r===void 0&&(r=1/0),n===void 0&&(n=1/0),o===void 0&&(o=wt);var i=e.call(this)||this;return i._bufferSize=r,i._windowTime=n,i._timestampProvider=o,i._buffer=[],i._infiniteTimeWindow=!0,i._infiniteTimeWindow=n===1/0,i._bufferSize=Math.max(1,r),i._windowTime=Math.max(1,n),i}return t.prototype.next=function(r){var n=this,o=n.isStopped,i=n._buffer,s=n._infiniteTimeWindow,a=n._timestampProvider,c=n._windowTime;o||(i.push(r),!s&&i.push(a.now()+c)),this._trimBuffer(),e.prototype.next.call(this,r)},t.prototype._subscribe=function(r){this._throwIfClosed(),this._trimBuffer();for(var n=this._innerSubscribe(r),o=this,i=o._infiniteTimeWindow,s=o._buffer,a=s.slice(),c=0;c<a.length&&!r.closed;c+=i?1:2)r.next(a[c]);return this._checkFinalizedStatuses(r),n},t.prototype._trimBuffer=function(){var r=this,n=r._bufferSize,o=r._timestampProvider,i=r._buffer,s=r._infiniteTimeWindow,a=(s?1:2)*n;if(n<1/0&&a<i.length&&i.splice(0,i.length-a),!s){for(var c=o.now(),f=0,u=1;u<i.length&&i[u]<=c;u+=2)f=u;f&&i.splice(0,f+1)}},t}(E);var Yn=function(e){ne(t,e);function t(r,n){return e.call(this)||this}return t.prototype.schedule=function(r,n){return n===void 0&&(n=0),this},t}($e);var St={setInterval:function(e,t){for(var r=[],n=2;n<arguments.length;n++)r[n-2]=arguments[n];var o=St.delegate;return o!=null&&o.setInterval?o.setInterval.apply(o,V([e,t],D(r))):setInterval.apply(void 0,V([e,t],D(r)))},clearInterval:function(e){var t=St.delegate;return((t==null?void 0:t.clearInterval)||clearInterval)(e)},delegate:void 0};var zt=function(e){ne(t,e);function t(r,n){var o=e.call(this,r,n)||this;return o.scheduler=r,o.work=n,o.pending=!1,o}return t.prototype.schedule=function(r,n){var o;if(n===void 0&&(n=0),this.closed)return this;this.state=r;var i=this.id,s=this.scheduler;return i!=null&&(this.id=this.recycleAsyncId(s,i,n)),this.pending=!0,this.delay=n,this.id=(o=this.id)!==null&&o!==void 0?o:this.requestAsyncId(s,this.id,n),this},t.prototype.requestAsyncId=function(r,n,o){return o===void 0&&(o=0),St.setInterval(r.flush.bind(r,this),o)},t.prototype.recycleAsyncId=function(r,n,o){if(o===void 0&&(o=0),o!=null&&this.delay===o&&this.pending===!1)return n;n!=null&&St.clearInterval(n)},t.prototype.execute=function(r,n){if(this.closed)return new Error("executing a cancelled action");this.pending=!1;var o=this._execute(r,n);if(o)return o;this.pending===!1&&this.id!=null&&(this.id=this.recycleAsyncId(this.scheduler,this.id,null))},t.prototype._execute=function(r,n){var o=!1,i;try{this.work(r)}catch(s){o=!0,i=s||new Error("Scheduled action threw falsy error")}if(o)return this.unsubscribe(),i},t.prototype.unsubscribe=function(){if(!this.closed){var r=this,n=r.id,o=r.scheduler,i=o.actions;this.work=this.state=this.scheduler=null,this.pending=!1,Ue(i,this),n!=null&&(this.id=this.recycleAsyncId(o,n,null)),this.delay=null,e.prototype.unsubscribe.call(this)}},t}(Yn);var Rr=function(){function e(t,r){r===void 0&&(r=e.now),this.schedulerActionCtor=t,this.now=r}return e.prototype.schedule=function(t,r,n){return r===void 0&&(r=0),new this.schedulerActionCtor(this,t).schedule(n,r)},e.now=wt.now,e}();var Nt=function(e){ne(t,e);function t(r,n){n===void 0&&(n=Rr.now);var o=e.call(this,r,n)||this;return o.actions=[],o._active=!1,o}return t.prototype.flush=function(r){var n=this.actions;if(this._active){n.push(r);return}var o;this._active=!0;do if(o=r.execute(r.state,r.delay))break;while(r=n.shift());if(this._active=!1,o){for(;r=n.shift();)r.unsubscribe();throw o}},t}(Rr);var fe=new Nt(zt),kr=fe;var Bn=function(e){ne(t,e);function t(r,n){var o=e.call(this,r,n)||this;return o.scheduler=r,o.work=n,o}return t.prototype.requestAsyncId=function(r,n,o){return o===void 0&&(o=0),o!==null&&o>0?e.prototype.requestAsyncId.call(this,r,n,o):(r.actions.push(this),r._scheduled||(r._scheduled=at.requestAnimationFrame(function(){return r.flush(void 0)})))},t.prototype.recycleAsyncId=function(r,n,o){var i;if(o===void 0&&(o=0),o!=null?o>0:this.delay>0)return e.prototype.recycleAsyncId.call(this,r,n,o);var s=r.actions;n!=null&&((i=s[s.length-1])===null||i===void 0?void 0:i.id)!==n&&(at.cancelAnimationFrame(n),r._scheduled=void 0)},t}(zt);var Gn=function(e){ne(t,e);function t(){return e!==null&&e.apply(this,arguments)||this}return t.prototype.flush=function(r){this._active=!0;var n=this._scheduled;this._scheduled=void 0;var o=this.actions,i;r=r||o.shift();do if(i=r.execute(r.state,r.delay))break;while((r=o[0])&&r.id===n&&o.shift());if(this._active=!1,i){for(;(r=o[0])&&r.id===n&&o.shift();)r.unsubscribe();throw i}},t}(Nt);var xe=new Gn(Bn);var R=new F(function(e){return e.complete()});function qt(e){return e&&L(e.schedule)}function Hr(e){return e[e.length-1]}function Ve(e){return L(Hr(e))?e.pop():void 0}function Ee(e){return qt(Hr(e))?e.pop():void 0}function Kt(e,t){return typeof Hr(e)=="number"?e.pop():t}var st=function(e){return e&&typeof e.length=="number"&&typeof e!="function"};function Qt(e){return L(e==null?void 0:e.then)}function Yt(e){return L(e[it])}function Bt(e){return Symbol.asyncIterator&&L(e==null?void 0:e[Symbol.asyncIterator])}function Gt(e){return new TypeError("You provided "+(e!==null&&typeof e=="object"?"an invalid object":"'"+e+"'")+" where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.")}function ya(){return typeof Symbol!="function"||!Symbol.iterator?"@@iterator":Symbol.iterator}var Jt=ya();function Xt(e){return L(e==null?void 0:e[Jt])}function Zt(e){return jn(this,arguments,function(){var r,n,o,i;return It(this,function(s){switch(s.label){case 0:r=e.getReader(),s.label=1;case 1:s.trys.push([1,,9,10]),s.label=2;case 2:return[4,jt(r.read())];case 3:return n=s.sent(),o=n.value,i=n.done,i?[4,jt(void 0)]:[3,5];case 4:return[2,s.sent()];case 5:return[4,jt(o)];case 6:return[4,s.sent()];case 7:return s.sent(),[3,2];case 8:return[3,10];case 9:return r.releaseLock(),[7];case 10:return[2]}})})}function er(e){return L(e==null?void 0:e.getReader)}function z(e){if(e instanceof F)return e;if(e!=null){if(Yt(e))return xa(e);if(st(e))return wa(e);if(Qt(e))return Ea(e);if(Bt(e))return Jn(e);if(Xt(e))return Sa(e);if(er(e))return Oa(e)}throw Gt(e)}function xa(e){return new F(function(t){var r=e[it]();if(L(r.subscribe))return r.subscribe(t);throw new TypeError("Provided object does not correctly implement Symbol.observable")})}function wa(e){return new F(function(t){for(var r=0;r<e.length&&!t.closed;r++)t.next(e[r]);t.complete()})}function Ea(e){return new F(function(t){e.then(function(r){t.closed||(t.next(r),t.complete())},function(r){return t.error(r)}).then(null,Wt)})}function Sa(e){return new F(function(t){var r,n;try{for(var o=ge(e),i=o.next();!i.done;i=o.next()){var s=i.value;if(t.next(s),t.closed)return}}catch(a){r={error:a}}finally{try{i&&!i.done&&(n=o.return)&&n.call(o)}finally{if(r)throw r.error}}t.complete()})}function Jn(e){return new F(function(t){_a(e,t).catch(function(r){return t.error(r)})})}function Oa(e){return Jn(Zt(e))}function _a(e,t){var r,n,o,i;return In(this,void 0,void 0,function(){var s,a;return It(this,function(c){switch(c.label){case 0:c.trys.push([0,5,6,11]),r=Fn(e),c.label=1;case 1:return[4,r.next()];case 2:if(n=c.sent(),!!n.done)return[3,4];if(s=n.value,t.next(s),t.closed)return[2];c.label=3;case 3:return[3,1];case 4:return[3,11];case 5:return a=c.sent(),o={error:a},[3,11];case 6:return c.trys.push([6,,9,10]),n&&!n.done&&(i=r.return)?[4,i.call(r)]:[3,8];case 7:c.sent(),c.label=8;case 8:return[3,10];case 9:if(o)throw o.error;return[7];case 10:return[7];case 11:return t.complete(),[2]}})})}function be(e,t,r,n,o){n===void 0&&(n=0),o===void 0&&(o=!1);var i=t.schedule(function(){r(),o?e.add(this.schedule(null,n)):this.unsubscribe()},n);if(e.add(i),!o)return i}function Le(e,t){return t===void 0&&(t=0),g(function(r,n){r.subscribe(y(n,function(o){return be(n,e,function(){return n.next(o)},t)},function(){return be(n,e,function(){return n.complete()},t)},function(o){return be(n,e,function(){return n.error(o)},t)}))})}function Je(e,t){return t===void 0&&(t=0),g(function(r,n){n.add(e.schedule(function(){return r.subscribe(n)},t))})}function Xn(e,t){return z(e).pipe(Je(t),Le(t))}function Zn(e,t){return z(e).pipe(Je(t),Le(t))}function eo(e,t){return new F(function(r){var n=0;return t.schedule(function(){n===e.length?r.complete():(r.next(e[n++]),r.closed||this.schedule())})})}function to(e,t){return new F(function(r){var n;return be(r,t,function(){n=e[Jt](),be(r,t,function(){var o,i,s;try{o=n.next(),i=o.value,s=o.done}catch(a){r.error(a);return}s?r.complete():r.next(i)},0,!0)}),function(){return L(n==null?void 0:n.return)&&n.return()}})}function tr(e,t){if(!e)throw new Error("Iterable cannot be null");return new F(function(r){be(r,t,function(){var n=e[Symbol.asyncIterator]();be(r,t,function(){n.next().then(function(o){o.done?r.complete():r.next(o.value)})},0,!0)})})}function ro(e,t){return tr(Zt(e),t)}function no(e,t){if(e!=null){if(Yt(e))return Xn(e,t);if(st(e))return eo(e,t);if(Qt(e))return Zn(e,t);if(Bt(e))return tr(e,t);if(Xt(e))return to(e,t);if(er(e))return ro(e,t)}throw Gt(e)}function ue(e,t){return t?no(e,t):z(e)}function I(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=Ee(e);return ue(e,r)}function Ot(e,t){var r=L(e)?e:function(){return e},n=function(o){return o.error(r())};return new F(t?function(o){return t.schedule(n,0,o)}:n)}function oo(e){return e instanceof Date&&!isNaN(e)}function m(e,t){return g(function(r,n){var o=0;r.subscribe(y(n,function(i){n.next(e.call(t,i,o++))}))})}var Ta=Array.isArray;function Ma(e,t){return Ta(t)?e.apply(void 0,V([],D(t))):e(t)}function ze(e){return m(function(t){return Ma(e,t)})}var La=Array.isArray,Aa=Object.getPrototypeOf,Ca=Object.prototype,Ra=Object.keys;function io(e){if(e.length===1){var t=e[0];if(La(t))return{args:t,keys:null};if(ka(t)){var r=Ra(t);return{args:r.map(function(n){return t[n]}),keys:r}}}return{args:e,keys:null}}function ka(e){return e&&typeof e=="object"&&Aa(e)===Ca}function ao(e,t){return e.reduce(function(r,n,o){return r[n]=t[o],r},{})}function Y(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=Ee(e),n=Ve(e),o=io(e),i=o.args,s=o.keys;if(i.length===0)return ue([],r);var a=new F(Pr(i,r,s?function(c){return ao(s,c)}:ye));return n?a.pipe(ze(n)):a}function Pr(e,t,r){return r===void 0&&(r=ye),function(n){so(t,function(){for(var o=e.length,i=new Array(o),s=o,a=o,c=function(u){so(t,function(){var p=ue(e[u],t),l=!1;p.subscribe(y(n,function(d){i[u]=d,l||(l=!0,a--),a||n.next(r(i.slice()))},function(){--s||n.complete()}))},n)},f=0;f<o;f++)c(f)},n)}}function so(e,t,r){e?be(r,e,t):t()}function co(e,t,r,n,o,i,s,a){var c=[],f=0,u=0,p=!1,l=function(){p&&!c.length&&!f&&t.complete()},d=function(b){return f<n?h(b):c.push(b)},h=function(b){i&&t.next(b),f++;var U=!1;z(r(b,u++)).subscribe(y(t,function(G){o==null||o(G),i?d(G):t.next(G)},function(){U=!0},void 0,function(){if(U)try{f--;for(var G=function(){var W=c.shift();s?be(t,s,function(){return h(W)}):h(W)};c.length&&f<n;)G();l()}catch(W){t.error(W)}}))};return e.subscribe(y(t,d,function(){p=!0,l()})),function(){a==null||a()}}function se(e,t,r){return r===void 0&&(r=1/0),L(t)?se(function(n,o){return m(function(i,s){return t(n,i,o,s)})(z(e(n,o)))},r):(typeof t=="number"&&(r=t),g(function(n,o){return co(n,o,e,r)}))}function ct(e){return e===void 0&&(e=1/0),se(ye,e)}function fo(){return ct(1)}function Xe(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return fo()(ue(e,Ee(e)))}function P(e){return new F(function(t){z(e()).subscribe(t)})}var Ha=["addListener","removeListener"],Pa=["addEventListener","removeEventListener"],$a=["on","off"];function v(e,t,r,n){if(L(r)&&(n=r,r=void 0),n)return v(e,t,r).pipe(ze(n));var o=D(Fa(e)?Pa.map(function(a){return function(c){return e[a](t,c,r)}}):Ia(e)?Ha.map(uo(e,t)):ja(e)?$a.map(uo(e,t)):[],2),i=o[0],s=o[1];if(!i&&st(e))return se(function(a){return v(a,t,r)})(z(e));if(!i)throw new TypeError("Invalid event target");return new F(function(a){var c=function(){for(var f=[],u=0;u<arguments.length;u++)f[u]=arguments[u];return a.next(1<f.length?f:f[0])};return i(c),function(){return s(c)}})}function uo(e,t){return function(r){return function(n){return e[r](t,n)}}}function Ia(e){return L(e.addListener)&&L(e.removeListener)}function ja(e){return L(e.on)&&L(e.off)}function Fa(e){return L(e.addEventListener)&&L(e.removeEventListener)}function rr(e,t,r){return r?rr(e,t).pipe(ze(r)):new F(function(n){var o=function(){for(var s=[],a=0;a<arguments.length;a++)s[a]=arguments[a];return n.next(s.length===1?s[0]:s)},i=e(o);return L(t)?function(){return t(o,i)}:void 0})}function Ne(e,t,r){e===void 0&&(e=0),r===void 0&&(r=kr);var n=-1;return t!=null&&(qt(t)?r=t:n=t),new F(function(o){var i=oo(e)?+e-r.now():e;i<0&&(i=0);var s=0;return r.schedule(function(){o.closed||(o.next(s++),0<=n?this.schedule(void 0,n):o.complete())},i)})}function A(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=Ee(e),n=Kt(e,1/0),o=e;return o.length?o.length===1?z(o[0]):ct(n)(ue(o,r)):R}var Se=new F(me);var Ua=Array.isArray;function ft(e){return e.length===1&&Ua(e[0])?e[0]:e}function x(e,t){return g(function(r,n){var o=0;r.subscribe(y(n,function(i){return e.call(t,i,o++)&&n.next(i)}))})}function _t(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=Ve(e),n=ft(e);return n.length?new F(function(o){var i=n.map(function(){return[]}),s=n.map(function(){return!1});o.add(function(){i=s=null});for(var a=function(f){z(n[f]).subscribe(y(o,function(u){if(i[f].push(u),i.every(function(l){return l.length})){var p=i.map(function(l){return l.shift()});o.next(r?r.apply(void 0,V([],D(p))):p),i.some(function(l,d){return!l.length&&s[d]})&&o.complete()}},function(){s[f]=!0,!i[f].length&&o.complete()}))},c=0;!o.closed&&c<n.length;c++)a(c);return function(){i=s=null}}):R}function po(e){return g(function(t,r){var n=!1,o=null,i=null,s=!1,a=function(){if(i==null||i.unsubscribe(),i=null,n){n=!1;var f=o;o=null,r.next(f)}s&&r.complete()},c=function(){i=null,s&&r.complete()};t.subscribe(y(r,function(f){n=!0,o=f,i||z(e(f)).subscribe(i=y(r,a,c))},function(){s=!0,(!n||!i||i.closed)&&r.complete()}))})}function Ae(e,t){return t===void 0&&(t=fe),po(function(){return Ne(e,t)})}function Ce(e,t){return t===void 0&&(t=null),t=t!=null?t:e,g(function(r,n){var o=[],i=0;r.subscribe(y(n,function(s){var a,c,f,u,p=null;i++%t===0&&o.push([]);try{for(var l=ge(o),d=l.next();!d.done;d=l.next()){var h=d.value;h.push(s),e<=h.length&&(p=p!=null?p:[],p.push(h))}}catch(G){a={error:G}}finally{try{d&&!d.done&&(c=l.return)&&c.call(l)}finally{if(a)throw a.error}}if(p)try{for(var b=ge(p),U=b.next();!U.done;U=b.next()){var h=U.value;Ue(o,h),n.next(h)}}catch(G){f={error:G}}finally{try{U&&!U.done&&(u=b.return)&&u.call(b)}finally{if(f)throw f.error}}},function(){var s,a;try{for(var c=ge(o),f=c.next();!f.done;f=c.next()){var u=f.value;n.next(u)}}catch(p){s={error:p}}finally{try{f&&!f.done&&(a=c.return)&&a.call(c)}finally{if(s)throw s.error}}n.complete()},void 0,function(){o=null}))})}function ce(e){return g(function(t,r){var n=null,o=!1,i;n=t.subscribe(y(r,void 0,void 0,function(s){i=z(e(s,ce(e)(t))),n?(n.unsubscribe(),n=null,i.subscribe(r)):o=!0})),o&&(n.unsubscribe(),n=null,i.subscribe(r))})}function lo(e,t,r,n,o){return function(i,s){var a=r,c=t,f=0;i.subscribe(y(s,function(u){var p=f++;c=a?e(c,u,p):(a=!0,u),n&&s.next(c)},o&&function(){a&&s.next(c),s.complete()}))}}function $r(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=Ve(e);return r?Nn($r.apply(void 0,V([],D(e))),ze(r)):g(function(n,o){Pr(V([n],D(ft(e))))(o)})}function Ze(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return $r.apply(void 0,V([],D(e)))}function Ir(e,t){return L(t)?se(e,t,1):se(e,1)}function Re(e,t){return t===void 0&&(t=fe),g(function(r,n){var o=null,i=null,s=null,a=function(){if(o){o.unsubscribe(),o=null;var f=i;i=null,n.next(f)}};function c(){var f=s+e,u=t.now();if(u<f){o=this.schedule(void 0,f-u),n.add(o);return}a()}r.subscribe(y(n,function(f){i=f,s=t.now(),o||(o=t.schedule(c,e),n.add(o))},function(){a(),n.complete()},void 0,function(){i=o=null}))})}function De(e){return g(function(t,r){var n=!1;t.subscribe(y(r,function(o){n=!0,r.next(o)},function(){n||r.next(e),r.complete()}))})}function oe(e){return e<=0?function(){return R}:g(function(t,r){var n=0;t.subscribe(y(r,function(o){++n<=e&&(r.next(o),e<=n&&r.complete())}))})}function mo(){return g(function(e,t){e.subscribe(y(t,me))})}function ho(e){return m(function(){return e})}function jr(e,t){return t?function(r){return Xe(t.pipe(oe(1),mo()),r.pipe(jr(e)))}:se(function(r,n){return e(r,n).pipe(oe(1),ho(r))})}function ke(e,t){t===void 0&&(t=fe);var r=Ne(e,t);return jr(function(){return r})}function B(e,t){return t===void 0&&(t=ye),e=e!=null?e:Da,g(function(r,n){var o,i=!0;r.subscribe(y(n,function(s){var a=t(s);(i||!e(o,a))&&(i=!1,o=a,n.next(s))}))})}function Da(e,t){return e===t}function J(e,t){return B(function(r,n){return t?t(r[e],n[e]):r[e]===n[e]})}function Fr(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return function(r){return Xe(r,I.apply(void 0,V([],D(e))))}}function C(e){return g(function(t,r){try{t.subscribe(r)}finally{r.add(e)}})}function de(e){return e<=0?function(){return R}:g(function(t,r){var n=[];t.subscribe(y(r,function(o){n.push(o),e<n.length&&n.shift()},function(){var o,i;try{for(var s=ge(n),a=s.next();!a.done;a=s.next()){var c=a.value;r.next(c)}}catch(f){o={error:f}}finally{try{a&&!a.done&&(i=s.return)&&i.call(s)}finally{if(o)throw o.error}}r.complete()},void 0,function(){n=null}))})}function bo(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=Ee(e),n=Kt(e,1/0);return e=ft(e),g(function(o,i){ct(n)(ue(V([o],D(e)),r)).subscribe(i)})}function et(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return bo.apply(void 0,V([],D(e)))}function Tt(e){var t,r=1/0,n;return e!=null&&(typeof e=="object"?(t=e.count,r=t===void 0?1/0:t,n=e.delay):r=e),r<=0?function(){return R}:g(function(o,i){var s=0,a,c=function(){if(a==null||a.unsubscribe(),a=null,n!=null){var u=typeof n=="number"?Ne(n):z(n(s)),p=y(i,function(){p.unsubscribe(),f()});u.subscribe(p)}else f()},f=function(){var u=!1;a=o.subscribe(y(i,void 0,function(){++s<r?a?c():u=!0:i.complete()})),u&&c()};f()})}function ut(e){return g(function(t,r){var n=!1,o=null;t.subscribe(y(r,function(i){n=!0,o=i})),e.subscribe(y(r,function(){if(n){n=!1;var i=o;o=null,r.next(i)}},me))})}function Ur(e,t){return g(lo(e,t,arguments.length>=2,!0))}function ie(e){e===void 0&&(e={});var t=e.connector,r=t===void 0?function(){return new E}:t,n=e.resetOnError,o=n===void 0?!0:n,i=e.resetOnComplete,s=i===void 0?!0:i,a=e.resetOnRefCountZero,c=a===void 0?!0:a;return function(f){var u,p,l,d=0,h=!1,b=!1,U=function(){p==null||p.unsubscribe(),p=void 0},G=function(){U(),u=l=void 0,h=b=!1},W=function(){var _=u;G(),_==null||_.unsubscribe()};return g(function(_,We){d++,!b&&!h&&U();var Fe=l=l!=null?l:r();We.add(function(){d--,d===0&&!b&&!h&&(p=Dr(W,c))}),Fe.subscribe(We),!u&&d>0&&(u=new Ge({next:function(Pe){return Fe.next(Pe)},error:function(Pe){b=!0,U(),p=Dr(G,o,Pe),Fe.error(Pe)},complete:function(){h=!0,U(),p=Dr(G,s),Fe.complete()}}),z(_).subscribe(u))})(f)}}function Dr(e,t){for(var r=[],n=2;n<arguments.length;n++)r[n-2]=arguments[n];if(t===!0){e();return}if(t!==!1){var o=new Ge({next:function(){o.unsubscribe(),e()}});return t.apply(void 0,V([],D(r))).subscribe(o)}}function X(e,t,r){var n,o,i,s,a=!1;return e&&typeof e=="object"?(n=e.bufferSize,s=n===void 0?1/0:n,o=e.windowTime,t=o===void 0?1/0:o,i=e.refCount,a=i===void 0?!1:i,r=e.scheduler):s=e!=null?e:1/0,ie({connector:function(){return new Et(s,t,r)},resetOnError:!0,resetOnComplete:!1,resetOnRefCountZero:a})}function He(e){return x(function(t,r){return e<=r})}function Mt(e){return g(function(t,r){var n=!1,o=y(r,function(){o==null||o.unsubscribe(),n=!0},me);z(e).subscribe(o),t.subscribe(y(r,function(i){return n&&r.next(i)}))})}function N(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=Ee(e);return g(function(n,o){(r?Xe(e,n,r):Xe(e,n)).subscribe(o)})}function S(e,t){return g(function(r,n){var o=null,i=0,s=!1,a=function(){return s&&!o&&n.complete()};r.subscribe(y(n,function(c){o==null||o.unsubscribe();var f=0,u=i++;z(e(c,u)).subscribe(o=y(n,function(p){return n.next(t?t(c,p,u,f++):p)},function(){o=null,a()}))},function(){s=!0,a()}))})}function ee(e){return g(function(t,r){z(e).subscribe(y(r,function(){return r.complete()},me)),!r.closed&&t.subscribe(r)})}function Wr(e,t){return t===void 0&&(t=!1),g(function(r,n){var o=0;r.subscribe(y(n,function(i){var s=e(i,o++);(s||t)&&n.next(i),!s&&n.complete()}))})}function w(e,t,r){var n=L(e)||t||r?{next:e,error:t,complete:r}:e;return n?g(function(o,i){var s;(s=n.subscribe)===null||s===void 0||s.call(n);var a=!0;o.subscribe(y(i,function(c){var f;(f=n.next)===null||f===void 0||f.call(n,c),i.next(c)},function(){var c;a=!1,(c=n.complete)===null||c===void 0||c.call(n),i.complete()},function(c){var f;a=!1,(f=n.error)===null||f===void 0||f.call(n,c),i.error(c)},function(){var c,f;a&&((c=n.unsubscribe)===null||c===void 0||c.call(n)),(f=n.finalize)===null||f===void 0||f.call(n)}))}):ye}var Vr={leading:!0,trailing:!1};function Lt(e,t){return t===void 0&&(t=Vr),g(function(r,n){var o=t.leading,i=t.trailing,s=!1,a=null,c=null,f=!1,u=function(){c==null||c.unsubscribe(),c=null,i&&(d(),f&&n.complete())},p=function(){c=null,f&&n.complete()},l=function(h){return c=z(e(h)).subscribe(y(n,u,p))},d=function(){if(s){s=!1;var h=a;a=null,n.next(h),!f&&l(h)}};r.subscribe(y(n,function(h){s=!0,a=h,!(c&&!c.closed)&&(o?d():l(h))},function(){f=!0,!(i&&s&&c&&!c.closed)&&n.complete()}))})}function zr(e,t,r){t===void 0&&(t=fe),r===void 0&&(r=Vr);var n=Ne(e,t);return Lt(function(){return n},r)}function ae(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=Ve(e);return g(function(n,o){for(var i=e.length,s=new Array(i),a=e.map(function(){return!1}),c=!1,f=function(p){z(e[p]).subscribe(y(o,function(l){s[p]=l,!c&&!a[p]&&(a[p]=!0,(c=a.every(ye))&&(a=null))},me))},u=0;u<i;u++)f(u);n.subscribe(y(o,function(p){if(c){var l=V([p],D(s));o.next(r?r.apply(void 0,V([],D(l))):l)}}))})}function vo(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return g(function(r,n){_t.apply(void 0,V([r],D(e))).subscribe(n)})}function Nr(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return vo.apply(void 0,V([],D(e)))}function go(){let e=new Et(1);return v(document,"DOMContentLoaded",{once:!0}).subscribe(()=>e.next(document)),e}function Q(e,t=document){return Array.from(t.querySelectorAll(e))}function K(e,t=document){let r=pe(e,t);if(typeof r=="undefined")throw new ReferenceError(`Missing element: expected "${e}" to be present`);return r}function pe(e,t=document){return t.querySelector(e)||void 0}function Ie(){return document.activeElement instanceof HTMLElement&&document.activeElement||void 0}function nr(e){return A(v(document.body,"focusin"),v(document.body,"focusout")).pipe(Re(1),m(()=>{let t=Ie();return typeof t!="undefined"?e.contains(t):!1}),N(e===Ie()),B())}function qe(e){return{x:e.offsetLeft,y:e.offsetTop}}function yo(e){return A(v(window,"load"),v(window,"resize")).pipe(Ae(0,xe),m(()=>qe(e)),N(qe(e)))}function or(e){return{x:e.scrollLeft,y:e.scrollTop}}function pt(e){return A(v(e,"scroll"),v(window,"resize")).pipe(Ae(0,xe),m(()=>or(e)),N(or(e)))}var wo=function(){if(typeof Map!="undefined")return Map;function e(t,r){var n=-1;return t.some(function(o,i){return o[0]===r?(n=i,!0):!1}),n}return function(){function t(){this.__entries__=[]}return Object.defineProperty(t.prototype,"size",{get:function(){return this.__entries__.length},enumerable:!0,configurable:!0}),t.prototype.get=function(r){var n=e(this.__entries__,r),o=this.__entries__[n];return o&&o[1]},t.prototype.set=function(r,n){var o=e(this.__entries__,r);~o?this.__entries__[o][1]=n:this.__entries__.push([r,n])},t.prototype.delete=function(r){var n=this.__entries__,o=e(n,r);~o&&n.splice(o,1)},t.prototype.has=function(r){return!!~e(this.__entries__,r)},t.prototype.clear=function(){this.__entries__.splice(0)},t.prototype.forEach=function(r,n){n===void 0&&(n=null);for(var o=0,i=this.__entries__;o<i.length;o++){var s=i[o];r.call(n,s[1],s[0])}},t}()}(),qr=typeof window!="undefined"&&typeof document!="undefined"&&window.document===document,ir=function(){return typeof global!="undefined"&&global.Math===Math?global:typeof self!="undefined"&&self.Math===Math?self:typeof window!="undefined"&&window.Math===Math?window:Function("return this")()}(),Wa=function(){return typeof requestAnimationFrame=="function"?requestAnimationFrame.bind(ir):function(e){return setTimeout(function(){return e(Date.now())},1e3/60)}}(),Va=2;function za(e,t){var r=!1,n=!1,o=0;function i(){r&&(r=!1,e()),n&&a()}function s(){Wa(i)}function a(){var c=Date.now();if(r){if(c-o<Va)return;n=!0}else r=!0,n=!1,setTimeout(s,t);o=c}return a}var Na=20,qa=["top","right","bottom","left","width","height","size","weight"],Ka=typeof MutationObserver!="undefined",Qa=function(){function e(){this.connected_=!1,this.mutationEventsAdded_=!1,this.mutationsObserver_=null,this.observers_=[],this.onTransitionEnd_=this.onTransitionEnd_.bind(this),this.refresh=za(this.refresh.bind(this),Na)}return e.prototype.addObserver=function(t){~this.observers_.indexOf(t)||this.observers_.push(t),this.connected_||this.connect_()},e.prototype.removeObserver=function(t){var r=this.observers_,n=r.indexOf(t);~n&&r.splice(n,1),!r.length&&this.connected_&&this.disconnect_()},e.prototype.refresh=function(){var t=this.updateObservers_();t&&this.refresh()},e.prototype.updateObservers_=function(){var t=this.observers_.filter(function(r){return r.gatherActive(),r.hasActive()});return t.forEach(function(r){return r.broadcastActive()}),t.length>0},e.prototype.connect_=function(){!qr||this.connected_||(document.addEventListener("transitionend",this.onTransitionEnd_),window.addEventListener("resize",this.refresh),Ka?(this.mutationsObserver_=new MutationObserver(this.refresh),this.mutationsObserver_.observe(document,{attributes:!0,childList:!0,characterData:!0,subtree:!0})):(document.addEventListener("DOMSubtreeModified",this.refresh),this.mutationEventsAdded_=!0),this.connected_=!0)},e.prototype.disconnect_=function(){!qr||!this.connected_||(document.removeEventListener("transitionend",this.onTransitionEnd_),window.removeEventListener("resize",this.refresh),this.mutationsObserver_&&this.mutationsObserver_.disconnect(),this.mutationEventsAdded_&&document.removeEventListener("DOMSubtreeModified",this.refresh),this.mutationsObserver_=null,this.mutationEventsAdded_=!1,this.connected_=!1)},e.prototype.onTransitionEnd_=function(t){var r=t.propertyName,n=r===void 0?"":r,o=qa.some(function(i){return!!~n.indexOf(i)});o&&this.refresh()},e.getInstance=function(){return this.instance_||(this.instance_=new e),this.instance_},e.instance_=null,e}(),Eo=function(e,t){for(var r=0,n=Object.keys(t);r<n.length;r++){var o=n[r];Object.defineProperty(e,o,{value:t[o],enumerable:!1,writable:!1,configurable:!0})}return e},lt=function(e){var t=e&&e.ownerDocument&&e.ownerDocument.defaultView;return t||ir},So=sr(0,0,0,0);function ar(e){return parseFloat(e)||0}function xo(e){for(var t=[],r=1;r<arguments.length;r++)t[r-1]=arguments[r];return t.reduce(function(n,o){var i=e["border-"+o+"-width"];return n+ar(i)},0)}function Ya(e){for(var t=["top","right","bottom","left"],r={},n=0,o=t;n<o.length;n++){var i=o[n],s=e["padding-"+i];r[i]=ar(s)}return r}function Ba(e){var t=e.getBBox();return sr(0,0,t.width,t.height)}function Ga(e){var t=e.clientWidth,r=e.clientHeight;if(!t&&!r)return So;var n=lt(e).getComputedStyle(e),o=Ya(n),i=o.left+o.right,s=o.top+o.bottom,a=ar(n.width),c=ar(n.height);if(n.boxSizing==="border-box"&&(Math.round(a+i)!==t&&(a-=xo(n,"left","right")+i),Math.round(c+s)!==r&&(c-=xo(n,"top","bottom")+s)),!Xa(e)){var f=Math.round(a+i)-t,u=Math.round(c+s)-r;Math.abs(f)!==1&&(a-=f),Math.abs(u)!==1&&(c-=u)}return sr(o.left,o.top,a,c)}var Ja=function(){return typeof SVGGraphicsElement!="undefined"?function(e){return e instanceof lt(e).SVGGraphicsElement}:function(e){return e instanceof lt(e).SVGElement&&typeof e.getBBox=="function"}}();function Xa(e){return e===lt(e).document.documentElement}function Za(e){return qr?Ja(e)?Ba(e):Ga(e):So}function es(e){var t=e.x,r=e.y,n=e.width,o=e.height,i=typeof DOMRectReadOnly!="undefined"?DOMRectReadOnly:Object,s=Object.create(i.prototype);return Eo(s,{x:t,y:r,width:n,height:o,top:r,right:t+n,bottom:o+r,left:t}),s}function sr(e,t,r,n){return{x:e,y:t,width:r,height:n}}var ts=function(){function e(t){this.broadcastWidth=0,this.broadcastHeight=0,this.contentRect_=sr(0,0,0,0),this.target=t}return e.prototype.isActive=function(){var t=Za(this.target);return this.contentRect_=t,t.width!==this.broadcastWidth||t.height!==this.broadcastHeight},e.prototype.broadcastRect=function(){var t=this.contentRect_;return this.broadcastWidth=t.width,this.broadcastHeight=t.height,t},e}(),rs=function(){function e(t,r){var n=es(r);Eo(this,{target:t,contentRect:n})}return e}(),ns=function(){function e(t,r,n){if(this.activeObservations_=[],this.observations_=new wo,typeof t!="function")throw new TypeError("The callback provided as parameter 1 is not a function.");this.callback_=t,this.controller_=r,this.callbackCtx_=n}return e.prototype.observe=function(t){if(!arguments.length)throw new TypeError("1 argument required, but only 0 present.");if(!(typeof Element=="undefined"||!(Element instanceof Object))){if(!(t instanceof lt(t).Element))throw new TypeError('parameter 1 is not of type "Element".');var r=this.observations_;r.has(t)||(r.set(t,new ts(t)),this.controller_.addObserver(this),this.controller_.refresh())}},e.prototype.unobserve=function(t){if(!arguments.length)throw new TypeError("1 argument required, but only 0 present.");if(!(typeof Element=="undefined"||!(Element instanceof Object))){if(!(t instanceof lt(t).Element))throw new TypeError('parameter 1 is not of type "Element".');var r=this.observations_;!r.has(t)||(r.delete(t),r.size||this.controller_.removeObserver(this))}},e.prototype.disconnect=function(){this.clearActive(),this.observations_.clear(),this.controller_.removeObserver(this)},e.prototype.gatherActive=function(){var t=this;this.clearActive(),this.observations_.forEach(function(r){r.isActive()&&t.activeObservations_.push(r)})},e.prototype.broadcastActive=function(){if(!!this.hasActive()){var t=this.callbackCtx_,r=this.activeObservations_.map(function(n){return new rs(n.target,n.broadcastRect())});this.callback_.call(t,r,t),this.clearActive()}},e.prototype.clearActive=function(){this.activeObservations_.splice(0)},e.prototype.hasActive=function(){return this.activeObservations_.length>0},e}(),Oo=typeof WeakMap!="undefined"?new WeakMap:new wo,_o=function(){function e(t){if(!(this instanceof e))throw new TypeError("Cannot call a class as a function.");if(!arguments.length)throw new TypeError("1 argument required, but only 0 present.");var r=Qa.getInstance(),n=new ns(t,r,this);Oo.set(this,n)}return e}();["observe","unobserve","disconnect"].forEach(function(e){_o.prototype[e]=function(){var t;return(t=Oo.get(this))[e].apply(t,arguments)}});var os=function(){return typeof ir.ResizeObserver!="undefined"?ir.ResizeObserver:_o}(),To=os;var Mo=new E,is=P(()=>I(new To(e=>{for(let t of e)Mo.next(t)}))).pipe(S(e=>A(Se,I(e)).pipe(C(()=>e.disconnect()))),X(1));function he(e){return{width:e.offsetWidth,height:e.offsetHeight}}function ve(e){return is.pipe(w(t=>t.observe(e)),S(t=>Mo.pipe(x(({target:r})=>r===e),C(()=>t.unobserve(e)),m(()=>he(e)))),N(he(e)))}function mt(e){return{width:e.scrollWidth,height:e.scrollHeight}}function cr(e){let t=e.parentElement;for(;t&&(e.scrollWidth<=t.scrollWidth&&e.scrollHeight<=t.scrollHeight);)t=(e=t).parentElement;return t?e:void 0}var Lo=new E,as=P(()=>I(new IntersectionObserver(e=>{for(let t of e)Lo.next(t)},{threshold:0}))).pipe(S(e=>A(Se,I(e)).pipe(C(()=>e.disconnect()))),X(1));function fr(e){return as.pipe(w(t=>t.observe(e)),S(t=>Lo.pipe(x(({target:r})=>r===e),C(()=>t.unobserve(e)),m(({isIntersecting:r})=>r))))}function Ao(e,t=16){return pt(e).pipe(m(({y:r})=>{let n=he(e),o=mt(e);return r>=o.height-n.height-t}),B())}var ur={drawer:K("[data-md-toggle=drawer]"),search:K("[data-md-toggle=search]")};function Co(e){return ur[e].checked}function Ke(e,t){ur[e].checked!==t&&ur[e].click()}function dt(e){let t=ur[e];return v(t,"change").pipe(m(()=>t.checked),N(t.checked))}function ss(e,t){switch(e.constructor){case HTMLInputElement:return e.type==="radio"?/^Arrow/.test(t):!0;case HTMLSelectElement:case HTMLTextAreaElement:return!0;default:return e.isContentEditable}}function Ro(){return v(window,"keydown").pipe(x(e=>!(e.metaKey||e.ctrlKey)),m(e=>({mode:Co("search")?"search":"global",type:e.key,claim(){e.preventDefault(),e.stopPropagation()}})),x(({mode:e,type:t})=>{if(e==="global"){let r=Ie();if(typeof r!="undefined")return!ss(r,t)}return!0}),ie())}function Oe(){return new URL(location.href)}function pr(e){location.href=e.href}function ko(){return new E}function Ho(e,t){if(typeof t=="string"||typeof t=="number")e.innerHTML+=t.toString();else if(t instanceof Node)e.appendChild(t);else if(Array.isArray(t))for(let r of t)Ho(e,r)}function M(e,t,...r){let n=document.createElement(e);if(t)for(let o of Object.keys(t))typeof t[o]!="undefined"&&(typeof t[o]!="boolean"?n.setAttribute(o,t[o]):n.setAttribute(o,""));for(let o of r)Ho(n,o);return n}function Po(e,t){let r=t;if(e.length>r){for(;e[r]!==" "&&--r>0;);return`${e.substring(0,r)}...`}return e}function lr(e){if(e>999){let t=+((e-950)%1e3>99);return`${((e+1e-6)/1e3).toFixed(t)}k`}else return e.toString()}function $o(){return location.hash.substring(1)}function Io(e){let t=M("a",{href:e});t.addEventListener("click",r=>r.stopPropagation()),t.click()}function cs(){return v(window,"hashchange").pipe(m($o),N($o()),x(e=>e.length>0),X(1))}function jo(){return cs().pipe(m(e=>pe(`[id="${e}"]`)),x(e=>typeof e!="undefined"))}function Kr(e){let t=matchMedia(e);return rr(r=>t.addListener(()=>r(t.matches))).pipe(N(t.matches))}function Fo(){let e=matchMedia("print");return A(v(window,"beforeprint").pipe(m(()=>!0)),v(window,"afterprint").pipe(m(()=>!1))).pipe(N(e.matches))}function Qr(e,t){return e.pipe(S(r=>r?t():R))}function mr(e,t={credentials:"same-origin"}){return ue(fetch(`${e}`,t)).pipe(ce(()=>R),S(r=>r.status!==200?Ot(()=>new Error(r.statusText)):I(r)))}function je(e,t){return mr(e,t).pipe(S(r=>r.json()),X(1))}function Uo(e,t){let r=new DOMParser;return mr(e,t).pipe(S(n=>n.text()),m(n=>r.parseFromString(n,"text/xml")),X(1))}function Do(e){let t=M("script",{src:e});return P(()=>(document.head.appendChild(t),A(v(t,"load"),v(t,"error").pipe(S(()=>Ot(()=>new ReferenceError(`Invalid script: ${e}`))))).pipe(m(()=>{}),C(()=>document.head.removeChild(t)),oe(1))))}function Wo(){return{x:Math.max(0,scrollX),y:Math.max(0,scrollY)}}function Vo(){return A(v(window,"scroll",{passive:!0}),v(window,"resize",{passive:!0})).pipe(m(Wo),N(Wo()))}function zo(){return{width:innerWidth,height:innerHeight}}function No(){return v(window,"resize",{passive:!0}).pipe(m(zo),N(zo()))}function qo(){return Y([Vo(),No()]).pipe(m(([e,t])=>({offset:e,size:t})),X(1))}function dr(e,{viewport$:t,header$:r}){let n=t.pipe(J("size")),o=Y([n,r]).pipe(m(()=>qe(e)));return Y([r,t,o]).pipe(m(([{height:i},{offset:s,size:a},{x:c,y:f}])=>({offset:{x:s.x-c,y:s.y-f+i},size:a})))}function Ko(e,{tx$:t}){let r=v(e,"message").pipe(m(({data:n})=>n));return t.pipe(Lt(()=>r,{leading:!0,trailing:!0}),w(n=>e.postMessage(n)),S(()=>r),ie())}var fs=K("#__config"),ht=JSON.parse(fs.textContent);ht.base=`${new URL(ht.base,Oe())}`;function le(){return ht}function Z(e){return ht.features.includes(e)}function re(e,t){return typeof t!="undefined"?ht.translations[e].replace("#",t.toString()):ht.translations[e]}function _e(e,t=document){return K(`[data-md-component=${e}]`,t)}function te(e,t=document){return Q(`[data-md-component=${e}]`,t)}function us(e){let t=K(".md-typeset > :first-child",e);return v(t,"click",{once:!0}).pipe(m(()=>K(".md-typeset",e)),m(r=>({hash:__md_hash(r.innerHTML)})))}function Qo(e){return!Z("announce.dismiss")||!e.childElementCount?R:P(()=>{let t=new E;return t.pipe(N({hash:__md_get("__announce")})).subscribe(({hash:r})=>{var n;r&&r===((n=__md_get("__announce"))!=null?n:r)&&(e.hidden=!0,__md_set("__announce",r))}),us(e).pipe(w(r=>t.next(r)),C(()=>t.complete()),m(r=>H({ref:e},r)))})}function ps(e,{target$:t}){return t.pipe(m(r=>({hidden:r!==e})))}function Yo(e,t){let r=new E;return r.subscribe(({hidden:n})=>{e.hidden=n}),ps(e,t).pipe(w(n=>r.next(n)),C(()=>r.complete()),m(n=>H({ref:e},n)))}var ii=Ye(Br());function Gr(e){return M("div",{class:"md-tooltip",id:e},M("div",{class:"md-tooltip__inner md-typeset"}))}function Bo(e,t){if(t=t?`${t}_annotation_${e}`:void 0,t){let r=t?`#${t}`:void 0;return M("aside",{class:"md-annotation",tabIndex:0},Gr(t),M("a",{href:r,class:"md-annotation__index",tabIndex:-1},M("span",{"data-md-annotation-id":e})))}else return M("aside",{class:"md-annotation",tabIndex:0},Gr(t),M("span",{class:"md-annotation__index",tabIndex:-1},M("span",{"data-md-annotation-id":e})))}function Go(e){return M("button",{class:"md-clipboard md-icon",title:re("clipboard.copy"),"data-clipboard-target":`#${e} > code`})}function Jr(e,t){let r=t&2,n=t&1,o=Object.keys(e.terms).filter(a=>!e.terms[a]).reduce((a,c)=>[...a,M("del",null,c)," "],[]).slice(0,-1),i=new URL(e.location);Z("search.highlight")&&i.searchParams.set("h",Object.entries(e.terms).filter(([,a])=>a).reduce((a,[c])=>`${a} ${c}`.trim(),""));let{tags:s}=le();return M("a",{href:`${i}`,class:"md-search-result__link",tabIndex:-1},M("article",{class:["md-search-result__article",...r?["md-search-result__article--document"]:[]].join(" "),"data-md-score":e.score.toFixed(2)},r>0&&M("div",{class:"md-search-result__icon md-icon"}),M("h1",{class:"md-search-result__title"},e.title),n>0&&e.text.length>0&&M("p",{class:"md-search-result__teaser"},Po(e.text,320)),e.tags&&M("div",{class:"md-typeset"},e.tags.map(a=>{let c=a.replace(/<[^>]+>/g,""),f=s?c in s?`md-tag-icon md-tag-icon--${s[c]}`:"md-tag-icon":"";return M("span",{class:`md-tag ${f}`},a)})),n>0&&o.length>0&&M("p",{class:"md-search-result__terms"},re("search.result.term.missing"),": ",...o)))}function Jo(e){let t=e[0].score,r=[...e],n=r.findIndex(f=>!f.location.includes("#")),[o]=r.splice(n,1),i=r.findIndex(f=>f.score<t);i===-1&&(i=r.length);let s=r.slice(0,i),a=r.slice(i),c=[Jr(o,2|+(!n&&i===0)),...s.map(f=>Jr(f,1)),...a.length?[M("details",{class:"md-search-result__more"},M("summary",{tabIndex:-1},a.length>0&&a.length===1?re("search.result.more.one"):re("search.result.more.other",a.length)),...a.map(f=>Jr(f,1)))]:[]];return M("li",{class:"md-search-result__item"},c)}function Xo(e){return M("ul",{class:"md-source__facts"},Object.entries(e).map(([t,r])=>M("li",{class:`md-source__fact md-source__fact--${t}`},typeof r=="number"?lr(r):r)))}function Xr(e){let t=`tabbed-control tabbed-control--${e}`;return M("div",{class:t,hidden:!0},M("button",{class:"tabbed-button",tabIndex:-1}))}function Zo(e){return M("div",{class:"md-typeset__scrollwrap"},M("div",{class:"md-typeset__table"},e))}function ls(e){let t=le(),r=new URL(`../${e.version}/`,t.base);return M("li",{class:"md-version__item"},M("a",{href:`${r}`,class:"md-version__link"},e.title))}function ei(e,t){return M("div",{class:"md-version"},M("button",{class:"md-version__current","aria-label":re("select.version.title")},t.title),M("ul",{class:"md-version__list"},e.map(ls)))}function ms(e,t){let r=P(()=>Y([yo(e),pt(t)])).pipe(m(([{x:n,y:o},i])=>{let{width:s,height:a}=he(e);return{x:n-i.x+s/2,y:o-i.y+a/2}}));return nr(e).pipe(S(n=>r.pipe(m(o=>({active:n,offset:o})),oe(+!n||1/0))))}function ti(e,t,{target$:r}){let[n,o]=Array.from(e.children);return P(()=>{let i=new E,s=i.pipe(de(1));return i.subscribe({next({offset:a}){e.style.setProperty("--md-tooltip-x",`${a.x}px`),e.style.setProperty("--md-tooltip-y",`${a.y}px`)},complete(){e.style.removeProperty("--md-tooltip-x"),e.style.removeProperty("--md-tooltip-y")}}),fr(e).pipe(ee(s)).subscribe(a=>{e.toggleAttribute("data-md-visible",a)}),A(i.pipe(x(({active:a})=>a)),i.pipe(Re(250),x(({active:a})=>!a))).subscribe({next({active:a}){a?e.prepend(n):n.remove()},complete(){e.prepend(n)}}),i.pipe(Ae(16,xe)).subscribe(({active:a})=>{n.classList.toggle("md-tooltip--active",a)}),i.pipe(zr(125,xe),x(()=>!!e.offsetParent),m(()=>e.offsetParent.getBoundingClientRect()),m(({x:a})=>a)).subscribe({next(a){a?e.style.setProperty("--md-tooltip-0",`${-a}px`):e.style.removeProperty("--md-tooltip-0")},complete(){e.style.removeProperty("--md-tooltip-0")}}),v(o,"click").pipe(ee(s),x(a=>!(a.metaKey||a.ctrlKey))).subscribe(a=>a.preventDefault()),v(o,"mousedown").pipe(ee(s),ae(i)).subscribe(([a,{active:c}])=>{var f;if(a.button!==0||a.metaKey||a.ctrlKey)a.preventDefault();else if(c){a.preventDefault();let u=e.parentElement.closest(".md-annotation");u instanceof HTMLElement?u.focus():(f=Ie())==null||f.blur()}}),r.pipe(ee(s),x(a=>a===n),ke(125)).subscribe(()=>e.focus()),ms(e,t).pipe(w(a=>i.next(a)),C(()=>i.complete()),m(a=>H({ref:e},a)))})}function ds(e){let t=[];for(let r of Q(".c, .c1, .cm",e)){let n=[],o=document.createNodeIterator(r,NodeFilter.SHOW_TEXT);for(let i=o.nextNode();i;i=o.nextNode())n.push(i);for(let i of n){let s;for(;s=/(\(\d+\))(!)?/.exec(i.textContent);){let[,a,c]=s;if(typeof c=="undefined"){let f=i.splitText(s.index);i=f.splitText(a.length),t.push(f)}else{i.textContent=a,t.push(i);break}}}}return t}function ri(e,t){t.append(...Array.from(e.childNodes))}function ni(e,t,{target$:r,print$:n}){let o=t.closest("[id]"),i=o==null?void 0:o.id,s=new Map;for(let a of ds(t)){let[,c]=a.textContent.match(/\((\d+)\)/);pe(`li:nth-child(${c})`,e)&&(s.set(c,Bo(c,i)),a.replaceWith(s.get(c)))}return s.size===0?R:P(()=>{let a=new E,c=[];for(let[f,u]of s)c.push([K(".md-typeset",u),K(`li:nth-child(${f})`,e)]);return n.pipe(ee(a.pipe(de(1)))).subscribe(f=>{e.hidden=!f;for(let[u,p]of c)f?ri(u,p):ri(p,u)}),A(...[...s].map(([,f])=>ti(f,t,{target$:r}))).pipe(C(()=>a.complete()),ie())})}var hs=0;function ai(e){if(e.nextElementSibling){let t=e.nextElementSibling;if(t.tagName==="OL")return t;if(t.tagName==="P"&&!t.children.length)return ai(t)}}function oi(e){return ve(e).pipe(m(({width:t})=>({scrollable:mt(e).width>t})),J("scrollable"))}function si(e,t){let{matches:r}=matchMedia("(hover)"),n=P(()=>{let o=new E;if(o.subscribe(({scrollable:s})=>{s&&r?e.setAttribute("tabindex","0"):e.removeAttribute("tabindex")}),ii.default.isSupported()){let s=e.closest("pre");s.id=`__code_${++hs}`,s.insertBefore(Go(s.id),e)}let i=e.closest(".highlight");if(i instanceof HTMLElement){let s=ai(i);if(typeof s!="undefined"&&(i.classList.contains("annotate")||Z("content.code.annotate"))){let a=ni(s,e,t);return oi(e).pipe(w(c=>o.next(c)),C(()=>o.complete()),m(c=>H({ref:e},c)),et(ve(i).pipe(m(({width:c,height:f})=>c&&f),B(),S(c=>c?a:R))))}}return oi(e).pipe(w(s=>o.next(s)),C(()=>o.complete()),m(s=>H({ref:e},s)))});return Z("content.lazy")?fr(e).pipe(x(o=>o),oe(1),S(()=>n)):n}var ci=".node circle,.node ellipse,.node path,.node polygon,.node rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}marker{fill:var(--md-mermaid-edge-color)!important}.edgeLabel .label rect{fill:#0000}.label{color:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.label foreignObject{line-height:normal;overflow:visible}.label div .edgeLabel{color:var(--md-mermaid-label-fg-color)}.edgeLabel,.edgeLabel rect,.label div .edgeLabel{background-color:var(--md-mermaid-label-bg-color)}.edgeLabel,.edgeLabel rect{fill:var(--md-mermaid-label-bg-color);color:var(--md-mermaid-edge-color)}.edgePath .path,.flowchart-link{stroke:var(--md-mermaid-edge-color)}.edgePath .arrowheadPath{fill:var(--md-mermaid-edge-color);stroke:none}.cluster rect{fill:var(--md-default-fg-color--lightest);stroke:var(--md-default-fg-color--lighter)}.cluster span{color:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}defs #flowchart-circleEnd,defs #flowchart-circleStart,defs #flowchart-crossEnd,defs #flowchart-crossStart,defs #flowchart-pointEnd,defs #flowchart-pointStart{stroke:none}g.classGroup line,g.classGroup rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}g.classGroup text{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.classLabel .box{fill:var(--md-mermaid-label-bg-color);background-color:var(--md-mermaid-label-bg-color);opacity:1}.classLabel .label{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.node .divider{stroke:var(--md-mermaid-node-fg-color)}.relation{stroke:var(--md-mermaid-edge-color)}.cardinality{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.cardinality text{fill:inherit!important}defs #classDiagram-compositionEnd,defs #classDiagram-compositionStart,defs #classDiagram-dependencyEnd,defs #classDiagram-dependencyStart,defs #classDiagram-extensionEnd,defs #classDiagram-extensionStart{fill:var(--md-mermaid-edge-color)!important;stroke:var(--md-mermaid-edge-color)!important}defs #classDiagram-aggregationEnd,defs #classDiagram-aggregationStart{fill:var(--md-mermaid-label-bg-color)!important;stroke:var(--md-mermaid-edge-color)!important}g.stateGroup rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}g.stateGroup .state-title{fill:var(--md-mermaid-label-fg-color)!important;font-family:var(--md-mermaid-font-family)}g.stateGroup .composit{fill:var(--md-mermaid-label-bg-color)}.nodeLabel{color:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.node circle.state-end,.node circle.state-start,.start-state{fill:var(--md-mermaid-edge-color);stroke:none}.end-state-inner,.end-state-outer{fill:var(--md-mermaid-edge-color)}.end-state-inner,.node circle.state-end{stroke:var(--md-mermaid-label-bg-color)}.transition{stroke:var(--md-mermaid-edge-color)}[id^=state-fork] rect,[id^=state-join] rect{fill:var(--md-mermaid-edge-color)!important;stroke:none!important}.statediagram-cluster.statediagram-cluster .inner{fill:var(--md-default-bg-color)}.statediagram-cluster rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}.statediagram-state rect.divider{fill:var(--md-default-fg-color--lightest);stroke:var(--md-default-fg-color--lighter)}defs #statediagram-barbEnd{stroke:var(--md-mermaid-edge-color)}.entityBox{fill:var(--md-mermaid-label-bg-color);stroke:var(--md-mermaid-node-fg-color)}.entityLabel{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.relationshipLabelBox{fill:var(--md-mermaid-label-bg-color);fill-opacity:1;background-color:var(--md-mermaid-label-bg-color);opacity:1}.relationshipLabel{fill:var(--md-mermaid-label-fg-color)}.relationshipLine{stroke:var(--md-mermaid-edge-color)}defs #ONE_OR_MORE_END *,defs #ONE_OR_MORE_START *,defs #ONLY_ONE_END *,defs #ONLY_ONE_START *,defs #ZERO_OR_MORE_END *,defs #ZERO_OR_MORE_START *,defs #ZERO_OR_ONE_END *,defs #ZERO_OR_ONE_START *{stroke:var(--md-mermaid-edge-color)!important}.actor,defs #ZERO_OR_MORE_END circle,defs #ZERO_OR_MORE_START circle{fill:var(--md-mermaid-label-bg-color)}.actor{stroke:var(--md-mermaid-node-fg-color)}text.actor>tspan{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}line{stroke:var(--md-default-fg-color--lighter)}.messageLine0,.messageLine1{stroke:var(--md-mermaid-edge-color)}.loopText>tspan,.messageText,.noteText>tspan{fill:var(--md-mermaid-edge-color);stroke:none;font-family:var(--md-mermaid-font-family)!important}.noteText>tspan{fill:#000}#arrowhead path{fill:var(--md-mermaid-edge-color);stroke:none}.loopLine{stroke:var(--md-mermaid-node-fg-color)}.labelBox,.loopLine{fill:var(--md-mermaid-node-bg-color)}.labelBox{stroke:none}.labelText,.labelText>span{fill:var(--md-mermaid-node-fg-color);font-family:var(--md-mermaid-font-family)}";var Zr,vs=0;function gs(){return typeof mermaid=="undefined"||mermaid instanceof Element?Do("https://unpkg.com/mermaid@9.1.7/dist/mermaid.min.js"):I(void 0)}function fi(e){return e.classList.remove("mermaid"),Zr||(Zr=gs().pipe(w(()=>mermaid.initialize({startOnLoad:!1,themeCSS:ci,sequence:{actorFontSize:"16px",messageFontSize:"16px",noteFontSize:"16px"}})),m(()=>{}),X(1))),Zr.subscribe(()=>{e.classList.add("mermaid");let t=`__mermaid_${vs++}`,r=M("div",{class:"mermaid"});mermaid.mermaidAPI.render(t,e.textContent,n=>{let o=r.attachShadow({mode:"closed"});o.innerHTML=n,e.replaceWith(r)})}),Zr.pipe(m(()=>({ref:e})))}function ys(e,{target$:t,print$:r}){let n=!0;return A(t.pipe(m(o=>o.closest("details:not([open])")),x(o=>e===o),m(()=>({action:"open",reveal:!0}))),r.pipe(x(o=>o||!n),w(()=>n=e.open),m(o=>({action:o?"open":"close"}))))}function ui(e,t){return P(()=>{let r=new E;return r.subscribe(({action:n,reveal:o})=>{e.toggleAttribute("open",n==="open"),o&&e.scrollIntoView()}),ys(e,t).pipe(w(n=>r.next(n)),C(()=>r.complete()),m(n=>H({ref:e},n)))})}var pi=M("table");function li(e){return e.replaceWith(pi),pi.replaceWith(Zo(e)),I({ref:e})}function xs(e){let t=Q(":scope > input",e),r=t.find(n=>n.checked)||t[0];return A(...t.map(n=>v(n,"change").pipe(m(()=>K(`label[for="${n.id}"]`))))).pipe(N(K(`label[for="${r.id}"]`)),m(n=>({active:n})))}function mi(e,{viewport$:t}){let r=Xr("prev");e.append(r);let n=Xr("next");e.append(n);let o=K(".tabbed-labels",e);return P(()=>{let i=new E,s=i.pipe(de(1));return Y([i,ve(e)]).pipe(Ae(1,xe),ee(s)).subscribe({next([{active:a},c]){let f=qe(a),{width:u}=he(a);e.style.setProperty("--md-indicator-x",`${f.x}px`),e.style.setProperty("--md-indicator-width",`${u}px`);let p=or(o);(f.x<p.x||f.x+u>p.x+c.width)&&o.scrollTo({left:Math.max(0,f.x-16),behavior:"smooth"})},complete(){e.style.removeProperty("--md-indicator-x"),e.style.removeProperty("--md-indicator-width")}}),Y([pt(o),ve(o)]).pipe(ee(s)).subscribe(([a,c])=>{let f=mt(o);r.hidden=a.x<16,n.hidden=a.x>f.width-c.width-16}),A(v(r,"click").pipe(m(()=>-1)),v(n,"click").pipe(m(()=>1))).pipe(ee(s)).subscribe(a=>{let{width:c}=he(o);o.scrollBy({left:c*a,behavior:"smooth"})}),Z("content.tabs.link")&&i.pipe(He(1),ae(t)).subscribe(([{active:a},{offset:c}])=>{let f=a.innerText.trim();if(a.hasAttribute("data-md-switching"))a.removeAttribute("data-md-switching");else{let u=e.offsetTop-c.y;for(let l of Q("[data-tabs]"))for(let d of Q(":scope > input",l)){let h=K(`label[for="${d.id}"]`);if(h!==a&&h.innerText.trim()===f){h.setAttribute("data-md-switching",""),d.click();break}}window.scrollTo({top:e.offsetTop-u});let p=__md_get("__tabs")||[];__md_set("__tabs",[...new Set([f,...p])])}}),xs(e).pipe(w(a=>i.next(a)),C(()=>i.complete()),m(a=>H({ref:e},a)))}).pipe(Je(fe))}function di(e,{viewport$:t,target$:r,print$:n}){return A(...Q("pre:not(.mermaid) > code",e).map(o=>si(o,{target$:r,print$:n})),...Q("pre.mermaid",e).map(o=>fi(o)),...Q("table:not([class])",e).map(o=>li(o)),...Q("details",e).map(o=>ui(o,{target$:r,print$:n})),...Q("[data-tabs]",e).map(o=>mi(o,{viewport$:t})))}function ws(e,{alert$:t}){return t.pipe(S(r=>A(I(!0),I(!1).pipe(ke(2e3))).pipe(m(n=>({message:r,active:n})))))}function hi(e,t){let r=K(".md-typeset",e);return P(()=>{let n=new E;return n.subscribe(({message:o,active:i})=>{e.classList.toggle("md-dialog--active",i),r.textContent=o}),ws(e,t).pipe(w(o=>n.next(o)),C(()=>n.complete()),m(o=>H({ref:e},o)))})}function Es({viewport$:e}){if(!Z("header.autohide"))return I(!1);let t=e.pipe(m(({offset:{y:o}})=>o),Ce(2,1),m(([o,i])=>[o<i,i]),J(0)),r=Y([e,t]).pipe(x(([{offset:o},[,i]])=>Math.abs(i-o.y)>100),m(([,[o]])=>o),B()),n=dt("search");return Y([e,n]).pipe(m(([{offset:o},i])=>o.y>400&&!i),B(),S(o=>o?r:I(!1)),N(!1))}function bi(e,t){return P(()=>Y([ve(e),Es(t)])).pipe(m(([{height:r},n])=>({height:r,hidden:n})),B((r,n)=>r.height===n.height&&r.hidden===n.hidden),X(1))}function vi(e,{header$:t,main$:r}){return P(()=>{let n=new E,o=n.pipe(de(1));return n.pipe(J("active"),Ze(t)).subscribe(([{active:i},{hidden:s}])=>{e.classList.toggle("md-header--shadow",i&&!s),e.hidden=s}),r.subscribe(n),t.pipe(ee(o),m(i=>H({ref:e},i)))})}function Ss(e,{viewport$:t,header$:r}){return dr(e,{viewport$:t,header$:r}).pipe(m(({offset:{y:n}})=>{let{height:o}=he(e);return{active:n>=o}}),J("active"))}function gi(e,t){return P(()=>{let r=new E;r.subscribe(({active:o})=>{e.classList.toggle("md-header__title--active",o)});let n=pe("article h1");return typeof n=="undefined"?R:Ss(n,t).pipe(w(o=>r.next(o)),C(()=>r.complete()),m(o=>H({ref:e},o)))})}function yi(e,{viewport$:t,header$:r}){let n=r.pipe(m(({height:i})=>i),B()),o=n.pipe(S(()=>ve(e).pipe(m(({height:i})=>({top:e.offsetTop,bottom:e.offsetTop+i})),J("bottom"))));return Y([n,o,t]).pipe(m(([i,{top:s,bottom:a},{offset:{y:c},size:{height:f}}])=>(f=Math.max(0,f-Math.max(0,s-c,i)-Math.max(0,f+c-a)),{offset:s-i,height:f,active:s-i<=c})),B((i,s)=>i.offset===s.offset&&i.height===s.height&&i.active===s.active))}function Os(e){let t=__md_get("__palette")||{index:e.findIndex(r=>matchMedia(r.getAttribute("data-md-color-media")).matches)};return I(...e).pipe(se(r=>v(r,"change").pipe(m(()=>r))),N(e[Math.max(0,t.index)]),m(r=>({index:e.indexOf(r),color:{scheme:r.getAttribute("data-md-color-scheme"),primary:r.getAttribute("data-md-color-primary"),accent:r.getAttribute("data-md-color-accent")}})),X(1))}function xi(e){return P(()=>{let t=new E;t.subscribe(n=>{document.body.setAttribute("data-md-color-switching","");for(let[o,i]of Object.entries(n.color))document.body.setAttribute(`data-md-color-${o}`,i);for(let o=0;o<r.length;o++){let i=r[o].nextElementSibling;i instanceof HTMLElement&&(i.hidden=n.index!==o)}__md_set("__palette",n)}),t.pipe(Le(fe)).subscribe(()=>{document.body.removeAttribute("data-md-color-switching")});let r=Q("input",e);return Os(r).pipe(w(n=>t.next(n)),C(()=>t.complete()),m(n=>H({ref:e},n)))})}var en=Ye(Br());function _s(e){e.setAttribute("data-md-copying","");let t=e.innerText;return e.removeAttribute("data-md-copying"),t}function wi({alert$:e}){en.default.isSupported()&&new F(t=>{new en.default("[data-clipboard-target], [data-clipboard-text]",{text:r=>r.getAttribute("data-clipboard-text")||_s(K(r.getAttribute("data-clipboard-target")))}).on("success",r=>t.next(r))}).pipe(w(t=>{t.trigger.focus()}),m(()=>re("clipboard.copied"))).subscribe(e)}function Ts(e){if(e.length<2)return[""];let[t,r]=[...e].sort((o,i)=>o.length-i.length).map(o=>o.replace(/[^/]+$/,"")),n=0;if(t===r)n=t.length;else for(;t.charCodeAt(n)===r.charCodeAt(n);)n++;return e.map(o=>o.replace(t.slice(0,n),""))}function hr(e){let t=__md_get("__sitemap",sessionStorage,e);if(t)return I(t);{let r=le();return Uo(new URL("sitemap.xml",e||r.base)).pipe(m(n=>Ts(Q("loc",n).map(o=>o.textContent))),ce(()=>R),De([]),w(n=>__md_set("__sitemap",n,sessionStorage,e)))}}function Ei({document$:e,location$:t,viewport$:r}){let n=le();if(location.protocol==="file:")return;"scrollRestoration"in history&&(history.scrollRestoration="manual",v(window,"beforeunload").subscribe(()=>{history.scrollRestoration="auto"}));let o=pe("link[rel=icon]");typeof o!="undefined"&&(o.href=o.href);let i=hr().pipe(m(f=>f.map(u=>`${new URL(u,n.base)}`)),S(f=>v(document.body,"click").pipe(x(u=>!u.metaKey&&!u.ctrlKey),S(u=>{if(u.target instanceof Element){let p=u.target.closest("a");if(p&&!p.target){let l=new URL(p.href);if(l.search="",l.hash="",l.pathname!==location.pathname&&f.includes(l.toString()))return u.preventDefault(),I({url:new URL(p.href)})}}return Se}))),ie()),s=v(window,"popstate").pipe(x(f=>f.state!==null),m(f=>({url:new URL(location.href),offset:f.state})),ie());A(i,s).pipe(B((f,u)=>f.url.href===u.url.href),m(({url:f})=>f)).subscribe(t);let a=t.pipe(J("pathname"),S(f=>mr(f.href).pipe(ce(()=>(pr(f),Se)))),ie());i.pipe(ut(a)).subscribe(({url:f})=>{history.pushState({},"",`${f}`)});let c=new DOMParser;a.pipe(S(f=>f.text()),m(f=>c.parseFromString(f,"text/html"))).subscribe(e),e.pipe(He(1)).subscribe(f=>{for(let u of["title","link[rel=canonical]","meta[name=author]","meta[name=description]","[data-md-component=announce]","[data-md-component=container]","[data-md-component=header-topic]","[data-md-component=outdated]","[data-md-component=logo]","[data-md-component=skip]",...Z("navigation.tabs.sticky")?["[data-md-component=tabs]"]:[]]){let p=pe(u),l=pe(u,f);typeof p!="undefined"&&typeof l!="undefined"&&p.replaceWith(l)}}),e.pipe(He(1),m(()=>_e("container")),S(f=>Q("script",f)),Ir(f=>{let u=M("script");if(f.src){for(let p of f.getAttributeNames())u.setAttribute(p,f.getAttribute(p));return f.replaceWith(u),new F(p=>{u.onload=()=>p.complete()})}else return u.textContent=f.textContent,f.replaceWith(u),R})).subscribe(),A(i,s).pipe(ut(e)).subscribe(({url:f,offset:u})=>{f.hash&&!u?Io(f.hash):window.scrollTo(0,(u==null?void 0:u.y)||0)}),r.pipe(Mt(i),Re(250),J("offset")).subscribe(({offset:f})=>{history.replaceState(f,"")}),A(i,s).pipe(Ce(2,1),x(([f,u])=>f.url.pathname===u.url.pathname),m(([,f])=>f)).subscribe(({offset:f})=>{window.scrollTo(0,(f==null?void 0:f.y)||0)})}var As=Ye(tn());var Oi=Ye(tn());function rn(e,t){let r=new RegExp(e.separator,"img"),n=(o,i,s)=>`${i}<mark data-md-highlight>${s}</mark>`;return o=>{o=o.replace(/[\s*+\-:~^]+/g," ").trim();let i=new RegExp(`(^|${e.separator})(${o.replace(/[|\\{}()[\]^$+*?.-]/g,"\\$&").replace(r,"|")})`,"img");return s=>(t?(0,Oi.default)(s):s).replace(i,n).replace(/<\/mark>(\s+)<mark[^>]*>/img,"$1")}}function _i(e){return e.split(/"([^"]+)"/g).map((t,r)=>r&1?t.replace(/^\b|^(?![^\x00-\x7F]|$)|\s+/g," +"):t).join("").replace(/"|(?:^|\s+)[*+\-:^~]+(?=\s+|$)/g,"").trim()}function bt(e){return e.type===1}function Ti(e){return e.type===2}function vt(e){return e.type===3}function Rs({config:e,docs:t}){e.lang.length===1&&e.lang[0]==="en"&&(e.lang=[re("search.config.lang")]),e.separator==="[\\s\\-]+"&&(e.separator=re("search.config.separator"));let n={pipeline:re("search.config.pipeline").split(/\s*,\s*/).filter(Boolean),suggestions:Z("search.suggest")};return{config:e,docs:t,options:n}}function Mi(e,t){let r=le(),n=new Worker(e),o=new E,i=Ko(n,{tx$:o}).pipe(m(s=>{if(vt(s))for(let a of s.data.items)for(let c of a)c.location=`${new URL(c.location,r.base)}`;return s}),ie());return ue(t).pipe(m(s=>({type:0,data:Rs(s)}))).subscribe(o.next.bind(o)),{tx$:o,rx$:i}}function Li({document$:e}){let t=le(),r=je(new URL("../versions.json",t.base)).pipe(ce(()=>R)),n=r.pipe(m(o=>{let[,i]=t.base.match(/([^/]+)\/?$/);return o.find(({version:s,aliases:a})=>s===i||a.includes(i))||o[0]}));r.pipe(m(o=>new Map(o.map(i=>[`${new URL(`../${i.version}/`,t.base)}`,i]))),S(o=>v(document.body,"click").pipe(x(i=>!i.metaKey&&!i.ctrlKey),ae(n),S(([i,s])=>{if(i.target instanceof Element){let a=i.target.closest("a");if(a&&!a.target&&o.has(a.href)){let c=a.href;return!i.target.closest(".md-version")&&o.get(c)===s?R:(i.preventDefault(),I(c))}}return R}),S(i=>{let{version:s}=o.get(i);return hr(new URL(i)).pipe(m(a=>{let f=Oe().href.replace(t.base,"");return a.includes(f.split("#")[0])?new URL(`../${s}/${f}`,t.base):new URL(i)}))})))).subscribe(o=>pr(o)),Y([r,n]).subscribe(([o,i])=>{K(".md-header__topic").appendChild(ei(o,i))}),e.pipe(S(()=>n)).subscribe(o=>{var s;let i=__md_get("__outdated",sessionStorage);if(i===null){let a=((s=t.version)==null?void 0:s.default)||"latest";i=!o.aliases.includes(a),__md_set("__outdated",i,sessionStorage)}if(i)for(let a of te("outdated"))a.hidden=!1})}function ks(e,{rx$:t}){let r=(__search==null?void 0:__search.transform)||_i,{searchParams:n}=Oe();n.has("q")&&Ke("search",!0);let o=t.pipe(x(bt),oe(1),m(()=>n.get("q")||""));dt("search").pipe(x(a=>!a),oe(1)).subscribe(()=>{let a=new URL(location.href);a.searchParams.delete("q"),history.replaceState({},"",`${a}`)}),o.subscribe(a=>{a&&(e.value=a,e.focus())});let i=nr(e),s=A(v(e,"keyup"),v(e,"focus").pipe(ke(1)),o).pipe(m(()=>r(e.value)),N(""),B());return Y([s,i]).pipe(m(([a,c])=>({value:a,focus:c})),X(1))}function Ai(e,{tx$:t,rx$:r}){let n=new E,o=n.pipe(de(1));return n.pipe(J("value"),m(({value:i})=>({type:2,data:i}))).subscribe(t.next.bind(t)),n.pipe(J("focus")).subscribe(({focus:i})=>{i?(Ke("search",i),e.placeholder=""):e.placeholder=re("search.placeholder")}),v(e.form,"reset").pipe(ee(o)).subscribe(()=>e.focus()),ks(e,{tx$:t,rx$:r}).pipe(w(i=>n.next(i)),C(()=>n.complete()),m(i=>H({ref:e},i)),ie())}function Ci(e,{rx$:t},{query$:r}){let n=new E,o=Ao(e.parentElement).pipe(x(Boolean)),i=K(":scope > :first-child",e),s=K(":scope > :last-child",e),a=t.pipe(x(bt),oe(1));return n.pipe(ae(r),Mt(a)).subscribe(([{items:f},{value:u}])=>{if(u)switch(f.length){case 0:i.textContent=re("search.result.none");break;case 1:i.textContent=re("search.result.one");break;default:i.textContent=re("search.result.other",lr(f.length))}else i.textContent=re("search.result.placeholder")}),n.pipe(w(()=>s.innerHTML=""),S(({items:f})=>A(I(...f.slice(0,10)),I(...f.slice(10)).pipe(Ce(4),Nr(o),S(([u])=>u))))).subscribe(f=>s.appendChild(Jo(f))),t.pipe(x(vt),m(({data:f})=>f)).pipe(w(f=>n.next(f)),C(()=>n.complete()),m(f=>H({ref:e},f)))}function Hs(e,{query$:t}){return t.pipe(m(({value:r})=>{let n=Oe();return n.hash="",n.searchParams.delete("h"),n.searchParams.set("q",r),{url:n}}))}function Ri(e,t){let r=new E;return r.subscribe(({url:n})=>{e.setAttribute("data-clipboard-text",e.href),e.href=`${n}`}),v(e,"click").subscribe(n=>n.preventDefault()),Hs(e,t).pipe(w(n=>r.next(n)),C(()=>r.complete()),m(n=>H({ref:e},n)))}function ki(e,{rx$:t},{keyboard$:r}){let n=new E,o=_e("search-query"),i=A(v(o,"keydown"),v(o,"focus")).pipe(Le(fe),m(()=>o.value),B());return n.pipe(Ze(i),m(([{suggestions:a},c])=>{let f=c.split(/([\s-]+)/);if((a==null?void 0:a.length)&&f[f.length-1]){let u=a[a.length-1];u.startsWith(f[f.length-1])&&(f[f.length-1]=u)}else f.length=0;return f})).subscribe(a=>e.innerHTML=a.join("").replace(/\s/g,"&nbsp;")),r.pipe(x(({mode:a})=>a==="search")).subscribe(a=>{switch(a.type){case"ArrowRight":e.innerText.length&&o.selectionStart===o.value.length&&(o.value=e.innerText);break}}),t.pipe(x(vt),m(({data:a})=>a)).pipe(w(a=>n.next(a)),C(()=>n.complete()),m(()=>({ref:e})))}function Hi(e,{index$:t,keyboard$:r}){let n=le();try{let o=(__search==null?void 0:__search.worker)||n.search,i=Mi(o,t),s=_e("search-query",e),a=_e("search-result",e),{tx$:c,rx$:f}=i;c.pipe(x(Ti),ut(f.pipe(x(bt))),oe(1)).subscribe(c.next.bind(c)),r.pipe(x(({mode:l})=>l==="search")).subscribe(l=>{let d=Ie();switch(l.type){case"Enter":if(d===s){let h=new Map;for(let b of Q(":first-child [href]",a)){let U=b.firstElementChild;h.set(b,parseFloat(U.getAttribute("data-md-score")))}if(h.size){let[[b]]=[...h].sort(([,U],[,G])=>G-U);b.click()}l.claim()}break;case"Escape":case"Tab":Ke("search",!1),s.blur();break;case"ArrowUp":case"ArrowDown":if(typeof d=="undefined")s.focus();else{let h=[s,...Q(":not(details) > [href], summary, details[open] [href]",a)],b=Math.max(0,(Math.max(0,h.indexOf(d))+h.length+(l.type==="ArrowUp"?-1:1))%h.length);h[b].focus()}l.claim();break;default:s!==Ie()&&s.focus()}}),r.pipe(x(({mode:l})=>l==="global")).subscribe(l=>{switch(l.type){case"f":case"s":case"/":s.focus(),s.select(),l.claim();break}});let u=Ai(s,i),p=Ci(a,i,{query$:u});return A(u,p).pipe(et(...te("search-share",e).map(l=>Ri(l,{query$:u})),...te("search-suggest",e).map(l=>ki(l,i,{keyboard$:r}))))}catch(o){return e.hidden=!0,Se}}function Pi(e,{index$:t,location$:r}){return Y([t,r.pipe(N(Oe()),x(n=>!!n.searchParams.get("h")))]).pipe(m(([n,o])=>rn(n.config,!0)(o.searchParams.get("h"))),m(n=>{var s;let o=new Map,i=document.createNodeIterator(e,NodeFilter.SHOW_TEXT);for(let a=i.nextNode();a;a=i.nextNode())if((s=a.parentElement)!=null&&s.offsetHeight){let c=a.textContent,f=n(c);f.length>c.length&&o.set(a,f)}for(let[a,c]of o){let{childNodes:f}=M("span",null,c);a.replaceWith(...Array.from(f))}return{ref:e,nodes:o}}))}function Ps(e,{viewport$:t,main$:r}){let n=e.parentElement,o=n.offsetTop-n.parentElement.offsetTop;return Y([r,t]).pipe(m(([{offset:i,height:s},{offset:{y:a}}])=>(s=s+Math.min(o,Math.max(0,a-i))-o,{height:s,locked:a>=i+o})),B((i,s)=>i.height===s.height&&i.locked===s.locked))}function nn(e,n){var o=n,{header$:t}=o,r=un(o,["header$"]);let i=K(".md-sidebar__scrollwrap",e),{y:s}=qe(i);return P(()=>{let a=new E;return a.pipe(Ae(0,xe),ae(t)).subscribe({next([{height:c},{height:f}]){i.style.height=`${c-2*s}px`,e.style.top=`${f}px`},complete(){i.style.height="",e.style.top=""}}),a.pipe(Le(xe),oe(1)).subscribe(()=>{for(let c of Q(".md-nav__link--active[href]",e)){let f=cr(c);if(typeof f!="undefined"){let u=c.offsetTop-f.offsetTop,{height:p}=he(f);f.scrollTo({top:u-p/2})}}}),Ps(e,r).pipe(w(c=>a.next(c)),C(()=>a.complete()),m(c=>H({ref:e},c)))})}function $i(e,t){if(typeof t!="undefined"){let r=`https://api.github.com/repos/${e}/${t}`;return _t(je(`${r}/releases/latest`).pipe(ce(()=>R),m(n=>({version:n.tag_name})),De({})),je(r).pipe(ce(()=>R),m(n=>({stars:n.stargazers_count,forks:n.forks_count})),De({}))).pipe(m(([n,o])=>H(H({},n),o)))}else{let r=`https://api.github.com/users/${e}`;return je(r).pipe(m(n=>({repositories:n.public_repos})),De({}))}}function Ii(e,t){let r=`https://${e}/api/v4/projects/${encodeURIComponent(t)}`;return je(r).pipe(ce(()=>R),m(({star_count:n,forks_count:o})=>({stars:n,forks:o})),De({}))}function ji(e){let t=e.match(/^.+github\.com\/([^/]+)\/?([^/]+)?/i);if(t){let[,r,n]=t;return $i(r,n)}if(t=e.match(/^.+?([^/]*gitlab[^/]+)\/(.+?)\/?$/i),t){let[,r,n]=t;return Ii(r,n)}return R}var $s;function Is(e){return $s||($s=P(()=>{let t=__md_get("__source",sessionStorage);if(t)return I(t);if(te("consent").length){let n=__md_get("__consent");if(!(n&&n.github))return R}return ji(e.href).pipe(w(n=>__md_set("__source",n,sessionStorage)))}).pipe(ce(()=>R),x(t=>Object.keys(t).length>0),m(t=>({facts:t})),X(1)))}function Fi(e){let t=K(":scope > :last-child",e);return P(()=>{let r=new E;return r.subscribe(({facts:n})=>{t.appendChild(Xo(n)),t.classList.add("md-source__repository--active")}),Is(e).pipe(w(n=>r.next(n)),C(()=>r.complete()),m(n=>H({ref:e},n)))})}function js(e,{viewport$:t,header$:r}){return ve(document.body).pipe(S(()=>dr(e,{header$:r,viewport$:t})),m(({offset:{y:n}})=>({hidden:n>=10})),J("hidden"))}function Ui(e,t){return P(()=>{let r=new E;return r.subscribe({next({hidden:n}){e.hidden=n},complete(){e.hidden=!1}}),(Z("navigation.tabs.sticky")?I({hidden:!1}):js(e,t)).pipe(w(n=>r.next(n)),C(()=>r.complete()),m(n=>H({ref:e},n)))})}function Fs(e,{viewport$:t,header$:r}){let n=new Map,o=Q("[href^=\\#]",e);for(let a of o){let c=decodeURIComponent(a.hash.substring(1)),f=pe(`[id="${c}"]`);typeof f!="undefined"&&n.set(a,f)}let i=r.pipe(J("height"),m(({height:a})=>{let c=_e("main"),f=K(":scope > :first-child",c);return a+.8*(f.offsetTop-c.offsetTop)}),ie());return ve(document.body).pipe(J("height"),S(a=>P(()=>{let c=[];return I([...n].reduce((f,[u,p])=>{for(;c.length&&n.get(c[c.length-1]).tagName>=p.tagName;)c.pop();let l=p.offsetTop;for(;!l&&p.parentElement;)p=p.parentElement,l=p.offsetTop;return f.set([...c=[...c,u]].reverse(),l)},new Map))}).pipe(m(c=>new Map([...c].sort(([,f],[,u])=>f-u))),Ze(i),S(([c,f])=>t.pipe(Ur(([u,p],{offset:{y:l},size:d})=>{let h=l+d.height>=Math.floor(a.height);for(;p.length;){let[,b]=p[0];if(b-f<l||h)u=[...u,p.shift()];else break}for(;u.length;){let[,b]=u[u.length-1];if(b-f>=l&&!h)p=[u.pop(),...p];else break}return[u,p]},[[],[...c]]),B((u,p)=>u[0]===p[0]&&u[1]===p[1])))))).pipe(m(([a,c])=>({prev:a.map(([f])=>f),next:c.map(([f])=>f)})),N({prev:[],next:[]}),Ce(2,1),m(([a,c])=>a.prev.length<c.prev.length?{prev:c.prev.slice(Math.max(0,a.prev.length-1),c.prev.length),next:[]}:{prev:c.prev.slice(-1),next:c.next.slice(0,c.next.length-a.next.length)}))}function Di(e,{viewport$:t,header$:r,target$:n}){return P(()=>{let o=new E,i=o.pipe(de(1));if(o.subscribe(({prev:s,next:a})=>{for(let[c]of a)c.classList.remove("md-nav__link--passed"),c.classList.remove("md-nav__link--active");for(let[c,[f]]of s.entries())f.classList.add("md-nav__link--passed"),f.classList.toggle("md-nav__link--active",c===s.length-1)}),Z("toc.follow")){let s=A(t.pipe(Re(1),m(()=>{})),t.pipe(Re(250),m(()=>"smooth")));o.pipe(x(({prev:a})=>a.length>0),ae(s)).subscribe(([{prev:a},c])=>{let[f]=a[a.length-1];if(f.offsetHeight){let u=cr(f);if(typeof u!="undefined"){let p=f.offsetTop-u.offsetTop,{height:l}=he(u);u.scrollTo({top:p-l/2,behavior:c})}}})}return Z("navigation.tracking")&&t.pipe(ee(i),J("offset"),Re(250),He(1),ee(n.pipe(He(1))),Tt({delay:250}),ae(o)).subscribe(([,{prev:s}])=>{let a=Oe(),c=s[s.length-1];if(c&&c.length){let[f]=c,{hash:u}=new URL(f.href);a.hash!==u&&(a.hash=u,history.replaceState({},"",`${a}`))}else a.hash="",history.replaceState({},"",`${a}`)}),Fs(e,{viewport$:t,header$:r}).pipe(w(s=>o.next(s)),C(()=>o.complete()),m(s=>H({ref:e},s)))})}function Us(e,{viewport$:t,main$:r,target$:n}){let o=t.pipe(m(({offset:{y:s}})=>s),Ce(2,1),m(([s,a])=>s>a&&a>0),B()),i=r.pipe(m(({active:s})=>s));return Y([i,o]).pipe(m(([s,a])=>!(s&&a)),B(),ee(n.pipe(He(1))),Fr(!0),Tt({delay:250}),m(s=>({hidden:s})))}function Wi(e,{viewport$:t,header$:r,main$:n,target$:o}){let i=new E,s=i.pipe(de(1));return i.subscribe({next({hidden:a}){e.hidden=a,a?(e.setAttribute("tabindex","-1"),e.blur()):e.removeAttribute("tabindex")},complete(){e.style.top="",e.hidden=!0,e.removeAttribute("tabindex")}}),r.pipe(ee(s),J("height")).subscribe(({height:a})=>{e.style.top=`${a+16}px`}),Us(e,{viewport$:t,main$:n,target$:o}).pipe(w(a=>i.next(a)),C(()=>i.complete()),m(a=>H({ref:e},a)))}function Vi({document$:e,tablet$:t}){e.pipe(S(()=>Q(".md-toggle--indeterminate, [data-md-state=indeterminate]")),w(r=>{r.indeterminate=!0,r.checked=!1}),se(r=>v(r,"change").pipe(Wr(()=>r.classList.contains("md-toggle--indeterminate")),m(()=>r))),ae(t)).subscribe(([r,n])=>{r.classList.remove("md-toggle--indeterminate"),n&&(r.checked=!1)})}function Ds(){return/(iPad|iPhone|iPod)/.test(navigator.userAgent)}function zi({document$:e}){e.pipe(S(()=>Q("[data-md-scrollfix]")),w(t=>t.removeAttribute("data-md-scrollfix")),x(Ds),se(t=>v(t,"touchstart").pipe(m(()=>t)))).subscribe(t=>{let r=t.scrollTop;r===0?t.scrollTop=1:r+t.offsetHeight===t.scrollHeight&&(t.scrollTop=r-1)})}function Ni({viewport$:e,tablet$:t}){Y([dt("search"),t]).pipe(m(([r,n])=>r&&!n),S(r=>I(r).pipe(ke(r?400:100))),ae(e)).subscribe(([r,{offset:{y:n}}])=>{if(r)document.body.setAttribute("data-md-scrolllock",""),document.body.style.top=`-${n}px`;else{let o=-1*parseInt(document.body.style.top,10);document.body.removeAttribute("data-md-scrolllock"),document.body.style.top="",o&&window.scrollTo(0,o)}})}Object.entries||(Object.entries=function(e){let t=[];for(let r of Object.keys(e))t.push([r,e[r]]);return t});Object.values||(Object.values=function(e){let t=[];for(let r of Object.keys(e))t.push(e[r]);return t});typeof Element!="undefined"&&(Element.prototype.scrollTo||(Element.prototype.scrollTo=function(e,t){typeof e=="object"?(this.scrollLeft=e.left,this.scrollTop=e.top):(this.scrollLeft=e,this.scrollTop=t)}),Element.prototype.replaceWith||(Element.prototype.replaceWith=function(...e){let t=this.parentNode;if(t){e.length===0&&t.removeChild(this);for(let r=e.length-1;r>=0;r--){let n=e[r];typeof n=="string"?n=document.createTextNode(n):n.parentNode&&n.parentNode.removeChild(n),r?t.insertBefore(this.previousSibling,n):t.replaceChild(n,this)}}}));document.documentElement.classList.remove("no-js");document.documentElement.classList.add("js");var tt=go(),vr=ko(),gt=jo(),on=Ro(),we=qo(),gr=Kr("(min-width: 960px)"),Ki=Kr("(min-width: 1220px)"),Qi=Fo(),Yi=le(),Bi=document.forms.namedItem("search")?(__search==null?void 0:__search.index)||je(new URL("search/search_index.json",Yi.base)):Se,an=new E;wi({alert$:an});Z("navigation.instant")&&Ei({document$:tt,location$:vr,viewport$:we});var qi;((qi=Yi.version)==null?void 0:qi.provider)==="mike"&&Li({document$:tt});A(vr,gt).pipe(ke(125)).subscribe(()=>{Ke("drawer",!1),Ke("search",!1)});on.pipe(x(({mode:e})=>e==="global")).subscribe(e=>{switch(e.type){case"p":case",":let t=pe("[href][rel=prev]");typeof t!="undefined"&&t.click();break;case"n":case".":let r=pe("[href][rel=next]");typeof r!="undefined"&&r.click();break}});Vi({document$:tt,tablet$:gr});zi({document$:tt});Ni({viewport$:we,tablet$:gr});var Qe=bi(_e("header"),{viewport$:we}),br=tt.pipe(m(()=>_e("main")),S(e=>yi(e,{viewport$:we,header$:Qe})),X(1)),Ws=A(...te("consent").map(e=>Yo(e,{target$:gt})),...te("dialog").map(e=>hi(e,{alert$:an})),...te("header").map(e=>vi(e,{viewport$:we,header$:Qe,main$:br})),...te("palette").map(e=>xi(e)),...te("search").map(e=>Hi(e,{index$:Bi,keyboard$:on})),...te("source").map(e=>Fi(e))),Vs=P(()=>A(...te("announce").map(e=>Qo(e)),...te("content").map(e=>di(e,{viewport$:we,target$:gt,print$:Qi})),...te("content").map(e=>Z("search.highlight")?Pi(e,{index$:Bi,location$:vr}):R),...te("header-title").map(e=>gi(e,{viewport$:we,header$:Qe})),...te("sidebar").map(e=>e.getAttribute("data-md-type")==="navigation"?Qr(Ki,()=>nn(e,{viewport$:we,header$:Qe,main$:br})):Qr(gr,()=>nn(e,{viewport$:we,header$:Qe,main$:br}))),...te("tabs").map(e=>Ui(e,{viewport$:we,header$:Qe})),...te("toc").map(e=>Di(e,{viewport$:we,header$:Qe,target$:gt})),...te("top").map(e=>Wi(e,{viewport$:we,header$:Qe,main$:br,target$:gt})))),Gi=tt.pipe(S(()=>Vs),et(Ws),X(1));Gi.subscribe();window.document$=tt;window.location$=vr;window.target$=gt;window.keyboard$=on;window.viewport$=we;window.tablet$=gr;window.screen$=Ki;window.print$=Qi;window.alert$=an;window.component$=Gi;})();
+//# sourceMappingURL=bundle.5a2dcb6a.min.js.map
+
diff --git a/7.3/assets/javascripts/bundle.5a2dcb6a.min.js.map b/7.3/assets/javascripts/bundle.5a2dcb6a.min.js.map
new file mode 100644
index 0000000000..34e26a3ad3
--- /dev/null
+++ b/7.3/assets/javascripts/bundle.5a2dcb6a.min.js.map
@@ -0,0 +1,8 @@
+{
+  "version": 3,
+  "sources": ["node_modules/focus-visible/dist/focus-visible.js", "node_modules/url-polyfill/url-polyfill.js", "node_modules/rxjs/node_modules/tslib/tslib.js", "node_modules/clipboard/dist/clipboard.js", "node_modules/escape-html/index.js", "node_modules/array-flat-polyfill/index.mjs", "src/assets/javascripts/bundle.ts", "node_modules/unfetch/polyfill/index.js", "node_modules/rxjs/node_modules/tslib/modules/index.js", "node_modules/rxjs/src/internal/util/isFunction.ts", "node_modules/rxjs/src/internal/util/createErrorClass.ts", "node_modules/rxjs/src/internal/util/UnsubscriptionError.ts", "node_modules/rxjs/src/internal/util/arrRemove.ts", "node_modules/rxjs/src/internal/Subscription.ts", "node_modules/rxjs/src/internal/config.ts", "node_modules/rxjs/src/internal/scheduler/timeoutProvider.ts", "node_modules/rxjs/src/internal/util/reportUnhandledError.ts", "node_modules/rxjs/src/internal/util/noop.ts", "node_modules/rxjs/src/internal/NotificationFactories.ts", "node_modules/rxjs/src/internal/util/errorContext.ts", "node_modules/rxjs/src/internal/Subscriber.ts", "node_modules/rxjs/src/internal/symbol/observable.ts", "node_modules/rxjs/src/internal/util/identity.ts", "node_modules/rxjs/src/internal/util/pipe.ts", "node_modules/rxjs/src/internal/Observable.ts", "node_modules/rxjs/src/internal/util/lift.ts", "node_modules/rxjs/src/internal/operators/OperatorSubscriber.ts", "node_modules/rxjs/src/internal/scheduler/animationFrameProvider.ts", "node_modules/rxjs/src/internal/util/ObjectUnsubscribedError.ts", "node_modules/rxjs/src/internal/Subject.ts", "node_modules/rxjs/src/internal/scheduler/dateTimestampProvider.ts", "node_modules/rxjs/src/internal/ReplaySubject.ts", "node_modules/rxjs/src/internal/scheduler/Action.ts", "node_modules/rxjs/src/internal/scheduler/intervalProvider.ts", "node_modules/rxjs/src/internal/scheduler/AsyncAction.ts", "node_modules/rxjs/src/internal/Scheduler.ts", "node_modules/rxjs/src/internal/scheduler/AsyncScheduler.ts", "node_modules/rxjs/src/internal/scheduler/async.ts", "node_modules/rxjs/src/internal/scheduler/AnimationFrameAction.ts", "node_modules/rxjs/src/internal/scheduler/AnimationFrameScheduler.ts", "node_modules/rxjs/src/internal/scheduler/animationFrame.ts", "node_modules/rxjs/src/internal/observable/empty.ts", "node_modules/rxjs/src/internal/util/isScheduler.ts", "node_modules/rxjs/src/internal/util/args.ts", "node_modules/rxjs/src/internal/util/isArrayLike.ts", "node_modules/rxjs/src/internal/util/isPromise.ts", "node_modules/rxjs/src/internal/util/isInteropObservable.ts", "node_modules/rxjs/src/internal/util/isAsyncIterable.ts", "node_modules/rxjs/src/internal/util/throwUnobservableError.ts", "node_modules/rxjs/src/internal/symbol/iterator.ts", "node_modules/rxjs/src/internal/util/isIterable.ts", "node_modules/rxjs/src/internal/util/isReadableStreamLike.ts", "node_modules/rxjs/src/internal/observable/innerFrom.ts", "node_modules/rxjs/src/internal/util/executeSchedule.ts", "node_modules/rxjs/src/internal/operators/observeOn.ts", "node_modules/rxjs/src/internal/operators/subscribeOn.ts", "node_modules/rxjs/src/internal/scheduled/scheduleObservable.ts", "node_modules/rxjs/src/internal/scheduled/schedulePromise.ts", "node_modules/rxjs/src/internal/scheduled/scheduleArray.ts", "node_modules/rxjs/src/internal/scheduled/scheduleIterable.ts", "node_modules/rxjs/src/internal/scheduled/scheduleAsyncIterable.ts", "node_modules/rxjs/src/internal/scheduled/scheduleReadableStreamLike.ts", "node_modules/rxjs/src/internal/scheduled/scheduled.ts", "node_modules/rxjs/src/internal/observable/from.ts", "node_modules/rxjs/src/internal/observable/of.ts", "node_modules/rxjs/src/internal/observable/throwError.ts", "node_modules/rxjs/src/internal/util/isDate.ts", "node_modules/rxjs/src/internal/operators/map.ts", "node_modules/rxjs/src/internal/util/mapOneOrManyArgs.ts", "node_modules/rxjs/src/internal/util/argsArgArrayOrObject.ts", "node_modules/rxjs/src/internal/util/createObject.ts", "node_modules/rxjs/src/internal/observable/combineLatest.ts", "node_modules/rxjs/src/internal/operators/mergeInternals.ts", "node_modules/rxjs/src/internal/operators/mergeMap.ts", "node_modules/rxjs/src/internal/operators/mergeAll.ts", "node_modules/rxjs/src/internal/operators/concatAll.ts", "node_modules/rxjs/src/internal/observable/concat.ts", "node_modules/rxjs/src/internal/observable/defer.ts", "node_modules/rxjs/src/internal/observable/fromEvent.ts", "node_modules/rxjs/src/internal/observable/fromEventPattern.ts", "node_modules/rxjs/src/internal/observable/timer.ts", "node_modules/rxjs/src/internal/observable/merge.ts", "node_modules/rxjs/src/internal/observable/never.ts", "node_modules/rxjs/src/internal/util/argsOrArgArray.ts", "node_modules/rxjs/src/internal/operators/filter.ts", "node_modules/rxjs/src/internal/observable/zip.ts", "node_modules/rxjs/src/internal/operators/audit.ts", "node_modules/rxjs/src/internal/operators/auditTime.ts", "node_modules/rxjs/src/internal/operators/bufferCount.ts", "node_modules/rxjs/src/internal/operators/catchError.ts", "node_modules/rxjs/src/internal/operators/scanInternals.ts", "node_modules/rxjs/src/internal/operators/combineLatest.ts", "node_modules/rxjs/src/internal/operators/combineLatestWith.ts", "node_modules/rxjs/src/internal/operators/concatMap.ts", "node_modules/rxjs/src/internal/operators/debounceTime.ts", "node_modules/rxjs/src/internal/operators/defaultIfEmpty.ts", "node_modules/rxjs/src/internal/operators/take.ts", "node_modules/rxjs/src/internal/operators/ignoreElements.ts", "node_modules/rxjs/src/internal/operators/mapTo.ts", "node_modules/rxjs/src/internal/operators/delayWhen.ts", "node_modules/rxjs/src/internal/operators/delay.ts", "node_modules/rxjs/src/internal/operators/distinctUntilChanged.ts", "node_modules/rxjs/src/internal/operators/distinctUntilKeyChanged.ts", "node_modules/rxjs/src/internal/operators/endWith.ts", "node_modules/rxjs/src/internal/operators/finalize.ts", "node_modules/rxjs/src/internal/operators/takeLast.ts", "node_modules/rxjs/src/internal/operators/merge.ts", "node_modules/rxjs/src/internal/operators/mergeWith.ts", "node_modules/rxjs/src/internal/operators/repeat.ts", "node_modules/rxjs/src/internal/operators/sample.ts", "node_modules/rxjs/src/internal/operators/scan.ts", "node_modules/rxjs/src/internal/operators/share.ts", "node_modules/rxjs/src/internal/operators/shareReplay.ts", "node_modules/rxjs/src/internal/operators/skip.ts", "node_modules/rxjs/src/internal/operators/skipUntil.ts", "node_modules/rxjs/src/internal/operators/startWith.ts", "node_modules/rxjs/src/internal/operators/switchMap.ts", "node_modules/rxjs/src/internal/operators/takeUntil.ts", "node_modules/rxjs/src/internal/operators/takeWhile.ts", "node_modules/rxjs/src/internal/operators/tap.ts", "node_modules/rxjs/src/internal/operators/throttle.ts", "node_modules/rxjs/src/internal/operators/throttleTime.ts", "node_modules/rxjs/src/internal/operators/withLatestFrom.ts", "node_modules/rxjs/src/internal/operators/zip.ts", "node_modules/rxjs/src/internal/operators/zipWith.ts", "src/assets/javascripts/browser/document/index.ts", "src/assets/javascripts/browser/element/_/index.ts", "src/assets/javascripts/browser/element/focus/index.ts", "src/assets/javascripts/browser/element/offset/_/index.ts", "src/assets/javascripts/browser/element/offset/content/index.ts", "node_modules/resize-observer-polyfill/dist/ResizeObserver.es.js", "src/assets/javascripts/browser/element/size/_/index.ts", "src/assets/javascripts/browser/element/size/content/index.ts", "src/assets/javascripts/browser/element/visibility/index.ts", "src/assets/javascripts/browser/toggle/index.ts", "src/assets/javascripts/browser/keyboard/index.ts", "src/assets/javascripts/browser/location/_/index.ts", "src/assets/javascripts/utilities/h/index.ts", "src/assets/javascripts/utilities/string/index.ts", "src/assets/javascripts/browser/location/hash/index.ts", "src/assets/javascripts/browser/media/index.ts", "src/assets/javascripts/browser/request/index.ts", "src/assets/javascripts/browser/script/index.ts", "src/assets/javascripts/browser/viewport/offset/index.ts", "src/assets/javascripts/browser/viewport/size/index.ts", "src/assets/javascripts/browser/viewport/_/index.ts", "src/assets/javascripts/browser/viewport/at/index.ts", "src/assets/javascripts/browser/worker/index.ts", "src/assets/javascripts/_/index.ts", "src/assets/javascripts/components/_/index.ts", "src/assets/javascripts/components/announce/index.ts", "src/assets/javascripts/components/consent/index.ts", "src/assets/javascripts/components/content/code/_/index.ts", "src/assets/javascripts/templates/tooltip/index.tsx", "src/assets/javascripts/templates/annotation/index.tsx", "src/assets/javascripts/templates/clipboard/index.tsx", "src/assets/javascripts/templates/search/index.tsx", "src/assets/javascripts/templates/source/index.tsx", "src/assets/javascripts/templates/tabbed/index.tsx", "src/assets/javascripts/templates/table/index.tsx", "src/assets/javascripts/templates/version/index.tsx", "src/assets/javascripts/components/content/annotation/_/index.ts", "src/assets/javascripts/components/content/annotation/list/index.ts", "src/assets/javascripts/components/content/code/mermaid/index.ts", "src/assets/javascripts/components/content/details/index.ts", "src/assets/javascripts/components/content/table/index.ts", "src/assets/javascripts/components/content/tabs/index.ts", "src/assets/javascripts/components/content/_/index.ts", "src/assets/javascripts/components/dialog/index.ts", "src/assets/javascripts/components/header/_/index.ts", "src/assets/javascripts/components/header/title/index.ts", "src/assets/javascripts/components/main/index.ts", "src/assets/javascripts/components/palette/index.ts", "src/assets/javascripts/integrations/clipboard/index.ts", "src/assets/javascripts/integrations/sitemap/index.ts", "src/assets/javascripts/integrations/instant/index.ts", "src/assets/javascripts/integrations/search/document/index.ts", "src/assets/javascripts/integrations/search/highlighter/index.ts", "src/assets/javascripts/integrations/search/query/transform/index.ts", "src/assets/javascripts/integrations/search/worker/message/index.ts", "src/assets/javascripts/integrations/search/worker/_/index.ts", "src/assets/javascripts/integrations/version/index.ts", "src/assets/javascripts/components/search/query/index.ts", "src/assets/javascripts/components/search/result/index.ts", "src/assets/javascripts/components/search/share/index.ts", "src/assets/javascripts/components/search/suggest/index.ts", "src/assets/javascripts/components/search/_/index.ts", "src/assets/javascripts/components/search/highlight/index.ts", "src/assets/javascripts/components/sidebar/index.ts", "src/assets/javascripts/components/source/facts/github/index.ts", "src/assets/javascripts/components/source/facts/gitlab/index.ts", "src/assets/javascripts/components/source/facts/_/index.ts", "src/assets/javascripts/components/source/_/index.ts", "src/assets/javascripts/components/tabs/index.ts", "src/assets/javascripts/components/toc/index.ts", "src/assets/javascripts/components/top/index.ts", "src/assets/javascripts/patches/indeterminate/index.ts", "src/assets/javascripts/patches/scrollfix/index.ts", "src/assets/javascripts/patches/scrolllock/index.ts", "src/assets/javascripts/polyfills/index.ts"],
+  "sourceRoot": "../../../..",
+  "sourcesContent": ["(function (global, factory) {\n  typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n  typeof define === 'function' && define.amd ? define(factory) :\n  (factory());\n}(this, (function () { 'use strict';\n\n  /**\n   * Applies the :focus-visible polyfill at the given scope.\n   * A scope in this case is either the top-level Document or a Shadow Root.\n   *\n   * @param {(Document|ShadowRoot)} scope\n   * @see https://github.com/WICG/focus-visible\n   */\n  function applyFocusVisiblePolyfill(scope) {\n    var hadKeyboardEvent = true;\n    var hadFocusVisibleRecently = false;\n    var hadFocusVisibleRecentlyTimeout = null;\n\n    var inputTypesAllowlist = {\n      text: true,\n      search: true,\n      url: true,\n      tel: true,\n      email: true,\n      password: true,\n      number: true,\n      date: true,\n      month: true,\n      week: true,\n      time: true,\n      datetime: true,\n      'datetime-local': true\n    };\n\n    /**\n     * Helper function for legacy browsers and iframes which sometimes focus\n     * elements like document, body, and non-interactive SVG.\n     * @param {Element} el\n     */\n    function isValidFocusTarget(el) {\n      if (\n        el &&\n        el !== document &&\n        el.nodeName !== 'HTML' &&\n        el.nodeName !== 'BODY' &&\n        'classList' in el &&\n        'contains' in el.classList\n      ) {\n        return true;\n      }\n      return false;\n    }\n\n    /**\n     * Computes whether the given element should automatically trigger the\n     * `focus-visible` class being added, i.e. whether it should always match\n     * `:focus-visible` when focused.\n     * @param {Element} el\n     * @return {boolean}\n     */\n    function focusTriggersKeyboardModality(el) {\n      var type = el.type;\n      var tagName = el.tagName;\n\n      if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n        return true;\n      }\n\n      if (tagName === 'TEXTAREA' && !el.readOnly) {\n        return true;\n      }\n\n      if (el.isContentEditable) {\n        return true;\n      }\n\n      return false;\n    }\n\n    /**\n     * Add the `focus-visible` class to the given element if it was not added by\n     * the author.\n     * @param {Element} el\n     */\n    function addFocusVisibleClass(el) {\n      if (el.classList.contains('focus-visible')) {\n        return;\n      }\n      el.classList.add('focus-visible');\n      el.setAttribute('data-focus-visible-added', '');\n    }\n\n    /**\n     * Remove the `focus-visible` class from the given element if it was not\n     * originally added by the author.\n     * @param {Element} el\n     */\n    function removeFocusVisibleClass(el) {\n      if (!el.hasAttribute('data-focus-visible-added')) {\n        return;\n      }\n      el.classList.remove('focus-visible');\n      el.removeAttribute('data-focus-visible-added');\n    }\n\n    /**\n     * If the most recent user interaction was via the keyboard;\n     * and the key press did not include a meta, alt/option, or control key;\n     * then the modality is keyboard. Otherwise, the modality is not keyboard.\n     * Apply `focus-visible` to any current active element and keep track\n     * of our keyboard modality state with `hadKeyboardEvent`.\n     * @param {KeyboardEvent} e\n     */\n    function onKeyDown(e) {\n      if (e.metaKey || e.altKey || e.ctrlKey) {\n        return;\n      }\n\n      if (isValidFocusTarget(scope.activeElement)) {\n        addFocusVisibleClass(scope.activeElement);\n      }\n\n      hadKeyboardEvent = true;\n    }\n\n    /**\n     * If at any point a user clicks with a pointing device, ensure that we change\n     * the modality away from keyboard.\n     * This avoids the situation where a user presses a key on an already focused\n     * element, and then clicks on a different element, focusing it with a\n     * pointing device, while we still think we're in keyboard modality.\n     * @param {Event} e\n     */\n    function onPointerDown(e) {\n      hadKeyboardEvent = false;\n    }\n\n    /**\n     * On `focus`, add the `focus-visible` class to the target if:\n     * - the target received focus as a result of keyboard navigation, or\n     * - the event target is an element that will likely require interaction\n     *   via the keyboard (e.g. a text box)\n     * @param {Event} e\n     */\n    function onFocus(e) {\n      // Prevent IE from focusing the document or HTML element.\n      if (!isValidFocusTarget(e.target)) {\n        return;\n      }\n\n      if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n        addFocusVisibleClass(e.target);\n      }\n    }\n\n    /**\n     * On `blur`, remove the `focus-visible` class from the target.\n     * @param {Event} e\n     */\n    function onBlur(e) {\n      if (!isValidFocusTarget(e.target)) {\n        return;\n      }\n\n      if (\n        e.target.classList.contains('focus-visible') ||\n        e.target.hasAttribute('data-focus-visible-added')\n      ) {\n        // To detect a tab/window switch, we look for a blur event followed\n        // rapidly by a visibility change.\n        // If we don't see a visibility change within 100ms, it's probably a\n        // regular focus change.\n        hadFocusVisibleRecently = true;\n        window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n        hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n          hadFocusVisibleRecently = false;\n        }, 100);\n        removeFocusVisibleClass(e.target);\n      }\n    }\n\n    /**\n     * If the user changes tabs, keep track of whether or not the previously\n     * focused element had .focus-visible.\n     * @param {Event} e\n     */\n    function onVisibilityChange(e) {\n      if (document.visibilityState === 'hidden') {\n        // If the tab becomes active again, the browser will handle calling focus\n        // on the element (Safari actually calls it twice).\n        // If this tab change caused a blur on an element with focus-visible,\n        // re-apply the class when the user switches back to the tab.\n        if (hadFocusVisibleRecently) {\n          hadKeyboardEvent = true;\n        }\n        addInitialPointerMoveListeners();\n      }\n    }\n\n    /**\n     * Add a group of listeners to detect usage of any pointing devices.\n     * These listeners will be added when the polyfill first loads, and anytime\n     * the window is blurred, so that they are active when the window regains\n     * focus.\n     */\n    function addInitialPointerMoveListeners() {\n      document.addEventListener('mousemove', onInitialPointerMove);\n      document.addEventListener('mousedown', onInitialPointerMove);\n      document.addEventListener('mouseup', onInitialPointerMove);\n      document.addEventListener('pointermove', onInitialPointerMove);\n      document.addEventListener('pointerdown', onInitialPointerMove);\n      document.addEventListener('pointerup', onInitialPointerMove);\n      document.addEventListener('touchmove', onInitialPointerMove);\n      document.addEventListener('touchstart', onInitialPointerMove);\n      document.addEventListener('touchend', onInitialPointerMove);\n    }\n\n    function removeInitialPointerMoveListeners() {\n      document.removeEventListener('mousemove', onInitialPointerMove);\n      document.removeEventListener('mousedown', onInitialPointerMove);\n      document.removeEventListener('mouseup', onInitialPointerMove);\n      document.removeEventListener('pointermove', onInitialPointerMove);\n      document.removeEventListener('pointerdown', onInitialPointerMove);\n      document.removeEventListener('pointerup', onInitialPointerMove);\n      document.removeEventListener('touchmove', onInitialPointerMove);\n      document.removeEventListener('touchstart', onInitialPointerMove);\n      document.removeEventListener('touchend', onInitialPointerMove);\n    }\n\n    /**\n     * When the polfyill first loads, assume the user is in keyboard modality.\n     * If any event is received from a pointing device (e.g. mouse, pointer,\n     * touch), turn off keyboard modality.\n     * This accounts for situations where focus enters the page from the URL bar.\n     * @param {Event} e\n     */\n    function onInitialPointerMove(e) {\n      // Work around a Safari quirk that fires a mousemove on <html> whenever the\n      // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n      if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n        return;\n      }\n\n      hadKeyboardEvent = false;\n      removeInitialPointerMoveListeners();\n    }\n\n    // For some kinds of state, we are interested in changes at the global scope\n    // only. For example, global pointer input, global key presses and global\n    // visibility change should affect the state at every scope:\n    document.addEventListener('keydown', onKeyDown, true);\n    document.addEventListener('mousedown', onPointerDown, true);\n    document.addEventListener('pointerdown', onPointerDown, true);\n    document.addEventListener('touchstart', onPointerDown, true);\n    document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n    addInitialPointerMoveListeners();\n\n    // For focus and blur, we specifically care about state changes in the local\n    // scope. This is because focus / blur events that originate from within a\n    // shadow root are not re-dispatched from the host element if it was already\n    // the active element in its own scope:\n    scope.addEventListener('focus', onFocus, true);\n    scope.addEventListener('blur', onBlur, true);\n\n    // We detect that a node is a ShadowRoot by ensuring that it is a\n    // DocumentFragment and also has a host property. This check covers native\n    // implementation and polyfill implementation transparently. If we only cared\n    // about the native implementation, we could just check if the scope was\n    // an instance of a ShadowRoot.\n    if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n      // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n      // have a root element to add a class to. So, we add this attribute to the\n      // host element instead:\n      scope.host.setAttribute('data-js-focus-visible', '');\n    } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n      document.documentElement.classList.add('js-focus-visible');\n      document.documentElement.setAttribute('data-js-focus-visible', '');\n    }\n  }\n\n  // It is important to wrap all references to global window and document in\n  // these checks to support server-side rendering use cases\n  // @see https://github.com/WICG/focus-visible/issues/199\n  if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n    // Make the polyfill helper globally available. This can be used as a signal\n    // to interested libraries that wish to coordinate with the polyfill for e.g.,\n    // applying the polyfill to a shadow root:\n    window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n    // Notify interested libraries of the polyfill's presence, in case the\n    // polyfill was loaded lazily:\n    var event;\n\n    try {\n      event = new CustomEvent('focus-visible-polyfill-ready');\n    } catch (error) {\n      // IE11 does not support using CustomEvent as a constructor directly:\n      event = document.createEvent('CustomEvent');\n      event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n    }\n\n    window.dispatchEvent(event);\n  }\n\n  if (typeof document !== 'undefined') {\n    // Apply the polyfill to the global document, so that no JavaScript\n    // coordination is required to use the polyfill in the top-level document:\n    applyFocusVisiblePolyfill(document);\n  }\n\n})));\n", "(function(global) {\r\n  /**\r\n   * Polyfill URLSearchParams\r\n   *\r\n   * Inspired from : https://github.com/WebReflection/url-search-params/blob/master/src/url-search-params.js\r\n   */\r\n\r\n  var checkIfIteratorIsSupported = function() {\r\n    try {\r\n      return !!Symbol.iterator;\r\n    } catch (error) {\r\n      return false;\r\n    }\r\n  };\r\n\r\n\r\n  var iteratorSupported = checkIfIteratorIsSupported();\r\n\r\n  var createIterator = function(items) {\r\n    var iterator = {\r\n      next: function() {\r\n        var value = items.shift();\r\n        return { done: value === void 0, value: value };\r\n      }\r\n    };\r\n\r\n    if (iteratorSupported) {\r\n      iterator[Symbol.iterator] = function() {\r\n        return iterator;\r\n      };\r\n    }\r\n\r\n    return iterator;\r\n  };\r\n\r\n  /**\r\n   * Search param name and values should be encoded according to https://url.spec.whatwg.org/#urlencoded-serializing\r\n   * encodeURIComponent() produces the same result except encoding spaces as `%20` instead of `+`.\r\n   */\r\n  var serializeParam = function(value) {\r\n    return encodeURIComponent(value).replace(/%20/g, '+');\r\n  };\r\n\r\n  var deserializeParam = function(value) {\r\n    return decodeURIComponent(String(value).replace(/\\+/g, ' '));\r\n  };\r\n\r\n  var polyfillURLSearchParams = function() {\r\n\r\n    var URLSearchParams = function(searchString) {\r\n      Object.defineProperty(this, '_entries', { writable: true, value: {} });\r\n      var typeofSearchString = typeof searchString;\r\n\r\n      if (typeofSearchString === 'undefined') {\r\n        // do nothing\r\n      } else if (typeofSearchString === 'string') {\r\n        if (searchString !== '') {\r\n          this._fromString(searchString);\r\n        }\r\n      } else if (searchString instanceof URLSearchParams) {\r\n        var _this = this;\r\n        searchString.forEach(function(value, name) {\r\n          _this.append(name, value);\r\n        });\r\n      } else if ((searchString !== null) && (typeofSearchString === 'object')) {\r\n        if (Object.prototype.toString.call(searchString) === '[object Array]') {\r\n          for (var i = 0; i < searchString.length; i++) {\r\n            var entry = searchString[i];\r\n            if ((Object.prototype.toString.call(entry) === '[object Array]') || (entry.length !== 2)) {\r\n              this.append(entry[0], entry[1]);\r\n            } else {\r\n              throw new TypeError('Expected [string, any] as entry at index ' + i + ' of URLSearchParams\\'s input');\r\n            }\r\n          }\r\n        } else {\r\n          for (var key in searchString) {\r\n            if (searchString.hasOwnProperty(key)) {\r\n              this.append(key, searchString[key]);\r\n            }\r\n          }\r\n        }\r\n      } else {\r\n        throw new TypeError('Unsupported input\\'s type for URLSearchParams');\r\n      }\r\n    };\r\n\r\n    var proto = URLSearchParams.prototype;\r\n\r\n    proto.append = function(name, value) {\r\n      if (name in this._entries) {\r\n        this._entries[name].push(String(value));\r\n      } else {\r\n        this._entries[name] = [String(value)];\r\n      }\r\n    };\r\n\r\n    proto.delete = function(name) {\r\n      delete this._entries[name];\r\n    };\r\n\r\n    proto.get = function(name) {\r\n      return (name in this._entries) ? this._entries[name][0] : null;\r\n    };\r\n\r\n    proto.getAll = function(name) {\r\n      return (name in this._entries) ? this._entries[name].slice(0) : [];\r\n    };\r\n\r\n    proto.has = function(name) {\r\n      return (name in this._entries);\r\n    };\r\n\r\n    proto.set = function(name, value) {\r\n      this._entries[name] = [String(value)];\r\n    };\r\n\r\n    proto.forEach = function(callback, thisArg) {\r\n      var entries;\r\n      for (var name in this._entries) {\r\n        if (this._entries.hasOwnProperty(name)) {\r\n          entries = this._entries[name];\r\n          for (var i = 0; i < entries.length; i++) {\r\n            callback.call(thisArg, entries[i], name, this);\r\n          }\r\n        }\r\n      }\r\n    };\r\n\r\n    proto.keys = function() {\r\n      var items = [];\r\n      this.forEach(function(value, name) {\r\n        items.push(name);\r\n      });\r\n      return createIterator(items);\r\n    };\r\n\r\n    proto.values = function() {\r\n      var items = [];\r\n      this.forEach(function(value) {\r\n        items.push(value);\r\n      });\r\n      return createIterator(items);\r\n    };\r\n\r\n    proto.entries = function() {\r\n      var items = [];\r\n      this.forEach(function(value, name) {\r\n        items.push([name, value]);\r\n      });\r\n      return createIterator(items);\r\n    };\r\n\r\n    if (iteratorSupported) {\r\n      proto[Symbol.iterator] = proto.entries;\r\n    }\r\n\r\n    proto.toString = function() {\r\n      var searchArray = [];\r\n      this.forEach(function(value, name) {\r\n        searchArray.push(serializeParam(name) + '=' + serializeParam(value));\r\n      });\r\n      return searchArray.join('&');\r\n    };\r\n\r\n\r\n    global.URLSearchParams = URLSearchParams;\r\n  };\r\n\r\n  var checkIfURLSearchParamsSupported = function() {\r\n    try {\r\n      var URLSearchParams = global.URLSearchParams;\r\n\r\n      return (\r\n        (new URLSearchParams('?a=1').toString() === 'a=1') &&\r\n        (typeof URLSearchParams.prototype.set === 'function') &&\r\n        (typeof URLSearchParams.prototype.entries === 'function')\r\n      );\r\n    } catch (e) {\r\n      return false;\r\n    }\r\n  };\r\n\r\n  if (!checkIfURLSearchParamsSupported()) {\r\n    polyfillURLSearchParams();\r\n  }\r\n\r\n  var proto = global.URLSearchParams.prototype;\r\n\r\n  if (typeof proto.sort !== 'function') {\r\n    proto.sort = function() {\r\n      var _this = this;\r\n      var items = [];\r\n      this.forEach(function(value, name) {\r\n        items.push([name, value]);\r\n        if (!_this._entries) {\r\n          _this.delete(name);\r\n        }\r\n      });\r\n      items.sort(function(a, b) {\r\n        if (a[0] < b[0]) {\r\n          return -1;\r\n        } else if (a[0] > b[0]) {\r\n          return +1;\r\n        } else {\r\n          return 0;\r\n        }\r\n      });\r\n      if (_this._entries) { // force reset because IE keeps keys index\r\n        _this._entries = {};\r\n      }\r\n      for (var i = 0; i < items.length; i++) {\r\n        this.append(items[i][0], items[i][1]);\r\n      }\r\n    };\r\n  }\r\n\r\n  if (typeof proto._fromString !== 'function') {\r\n    Object.defineProperty(proto, '_fromString', {\r\n      enumerable: false,\r\n      configurable: false,\r\n      writable: false,\r\n      value: function(searchString) {\r\n        if (this._entries) {\r\n          this._entries = {};\r\n        } else {\r\n          var keys = [];\r\n          this.forEach(function(value, name) {\r\n            keys.push(name);\r\n          });\r\n          for (var i = 0; i < keys.length; i++) {\r\n            this.delete(keys[i]);\r\n          }\r\n        }\r\n\r\n        searchString = searchString.replace(/^\\?/, '');\r\n        var attributes = searchString.split('&');\r\n        var attribute;\r\n        for (var i = 0; i < attributes.length; i++) {\r\n          attribute = attributes[i].split('=');\r\n          this.append(\r\n            deserializeParam(attribute[0]),\r\n            (attribute.length > 1) ? deserializeParam(attribute[1]) : ''\r\n          );\r\n        }\r\n      }\r\n    });\r\n  }\r\n\r\n  // HTMLAnchorElement\r\n\r\n})(\r\n  (typeof global !== 'undefined') ? global\r\n    : ((typeof window !== 'undefined') ? window\r\n    : ((typeof self !== 'undefined') ? self : this))\r\n);\r\n\r\n(function(global) {\r\n  /**\r\n   * Polyfill URL\r\n   *\r\n   * Inspired from : https://github.com/arv/DOM-URL-Polyfill/blob/master/src/url.js\r\n   */\r\n\r\n  var checkIfURLIsSupported = function() {\r\n    try {\r\n      var u = new global.URL('b', 'http://a');\r\n      u.pathname = 'c d';\r\n      return (u.href === 'http://a/c%20d') && u.searchParams;\r\n    } catch (e) {\r\n      return false;\r\n    }\r\n  };\r\n\r\n\r\n  var polyfillURL = function() {\r\n    var _URL = global.URL;\r\n\r\n    var URL = function(url, base) {\r\n      if (typeof url !== 'string') url = String(url);\r\n      if (base && typeof base !== 'string') base = String(base);\r\n\r\n      // Only create another document if the base is different from current location.\r\n      var doc = document, baseElement;\r\n      if (base && (global.location === void 0 || base !== global.location.href)) {\r\n        base = base.toLowerCase();\r\n        doc = document.implementation.createHTMLDocument('');\r\n        baseElement = doc.createElement('base');\r\n        baseElement.href = base;\r\n        doc.head.appendChild(baseElement);\r\n        try {\r\n          if (baseElement.href.indexOf(base) !== 0) throw new Error(baseElement.href);\r\n        } catch (err) {\r\n          throw new Error('URL unable to set base ' + base + ' due to ' + err);\r\n        }\r\n      }\r\n\r\n      var anchorElement = doc.createElement('a');\r\n      anchorElement.href = url;\r\n      if (baseElement) {\r\n        doc.body.appendChild(anchorElement);\r\n        anchorElement.href = anchorElement.href; // force href to refresh\r\n      }\r\n\r\n      var inputElement = doc.createElement('input');\r\n      inputElement.type = 'url';\r\n      inputElement.value = url;\r\n\r\n      if (anchorElement.protocol === ':' || !/:/.test(anchorElement.href) || (!inputElement.checkValidity() && !base)) {\r\n        throw new TypeError('Invalid URL');\r\n      }\r\n\r\n      Object.defineProperty(this, '_anchorElement', {\r\n        value: anchorElement\r\n      });\r\n\r\n\r\n      // create a linked searchParams which reflect its changes on URL\r\n      var searchParams = new global.URLSearchParams(this.search);\r\n      var enableSearchUpdate = true;\r\n      var enableSearchParamsUpdate = true;\r\n      var _this = this;\r\n      ['append', 'delete', 'set'].forEach(function(methodName) {\r\n        var method = searchParams[methodName];\r\n        searchParams[methodName] = function() {\r\n          method.apply(searchParams, arguments);\r\n          if (enableSearchUpdate) {\r\n            enableSearchParamsUpdate = false;\r\n            _this.search = searchParams.toString();\r\n            enableSearchParamsUpdate = true;\r\n          }\r\n        };\r\n      });\r\n\r\n      Object.defineProperty(this, 'searchParams', {\r\n        value: searchParams,\r\n        enumerable: true\r\n      });\r\n\r\n      var search = void 0;\r\n      Object.defineProperty(this, '_updateSearchParams', {\r\n        enumerable: false,\r\n        configurable: false,\r\n        writable: false,\r\n        value: function() {\r\n          if (this.search !== search) {\r\n            search = this.search;\r\n            if (enableSearchParamsUpdate) {\r\n              enableSearchUpdate = false;\r\n              this.searchParams._fromString(this.search);\r\n              enableSearchUpdate = true;\r\n            }\r\n          }\r\n        }\r\n      });\r\n    };\r\n\r\n    var proto = URL.prototype;\r\n\r\n    var linkURLWithAnchorAttribute = function(attributeName) {\r\n      Object.defineProperty(proto, attributeName, {\r\n        get: function() {\r\n          return this._anchorElement[attributeName];\r\n        },\r\n        set: function(value) {\r\n          this._anchorElement[attributeName] = value;\r\n        },\r\n        enumerable: true\r\n      });\r\n    };\r\n\r\n    ['hash', 'host', 'hostname', 'port', 'protocol']\r\n      .forEach(function(attributeName) {\r\n        linkURLWithAnchorAttribute(attributeName);\r\n      });\r\n\r\n    Object.defineProperty(proto, 'search', {\r\n      get: function() {\r\n        return this._anchorElement['search'];\r\n      },\r\n      set: function(value) {\r\n        this._anchorElement['search'] = value;\r\n        this._updateSearchParams();\r\n      },\r\n      enumerable: true\r\n    });\r\n\r\n    Object.defineProperties(proto, {\r\n\r\n      'toString': {\r\n        get: function() {\r\n          var _this = this;\r\n          return function() {\r\n            return _this.href;\r\n          };\r\n        }\r\n      },\r\n\r\n      'href': {\r\n        get: function() {\r\n          return this._anchorElement.href.replace(/\\?$/, '');\r\n        },\r\n        set: function(value) {\r\n          this._anchorElement.href = value;\r\n          this._updateSearchParams();\r\n        },\r\n        enumerable: true\r\n      },\r\n\r\n      'pathname': {\r\n        get: function() {\r\n          return this._anchorElement.pathname.replace(/(^\\/?)/, '/');\r\n        },\r\n        set: function(value) {\r\n          this._anchorElement.pathname = value;\r\n        },\r\n        enumerable: true\r\n      },\r\n\r\n      'origin': {\r\n        get: function() {\r\n          // get expected port from protocol\r\n          var expectedPort = { 'http:': 80, 'https:': 443, 'ftp:': 21 }[this._anchorElement.protocol];\r\n          // add port to origin if, expected port is different than actual port\r\n          // and it is not empty f.e http://foo:8080\r\n          // 8080 != 80 && 8080 != ''\r\n          var addPortToOrigin = this._anchorElement.port != expectedPort &&\r\n            this._anchorElement.port !== '';\r\n\r\n          return this._anchorElement.protocol +\r\n            '//' +\r\n            this._anchorElement.hostname +\r\n            (addPortToOrigin ? (':' + this._anchorElement.port) : '');\r\n        },\r\n        enumerable: true\r\n      },\r\n\r\n      'password': { // TODO\r\n        get: function() {\r\n          return '';\r\n        },\r\n        set: function(value) {\r\n        },\r\n        enumerable: true\r\n      },\r\n\r\n      'username': { // TODO\r\n        get: function() {\r\n          return '';\r\n        },\r\n        set: function(value) {\r\n        },\r\n        enumerable: true\r\n      },\r\n    });\r\n\r\n    URL.createObjectURL = function(blob) {\r\n      return _URL.createObjectURL.apply(_URL, arguments);\r\n    };\r\n\r\n    URL.revokeObjectURL = function(url) {\r\n      return _URL.revokeObjectURL.apply(_URL, arguments);\r\n    };\r\n\r\n    global.URL = URL;\r\n\r\n  };\r\n\r\n  if (!checkIfURLIsSupported()) {\r\n    polyfillURL();\r\n  }\r\n\r\n  if ((global.location !== void 0) && !('origin' in global.location)) {\r\n    var getOrigin = function() {\r\n      return global.location.protocol + '//' + global.location.hostname + (global.location.port ? (':' + global.location.port) : '');\r\n    };\r\n\r\n    try {\r\n      Object.defineProperty(global.location, 'origin', {\r\n        get: getOrigin,\r\n        enumerable: true\r\n      });\r\n    } catch (e) {\r\n      setInterval(function() {\r\n        global.location.origin = getOrigin();\r\n      }, 100);\r\n    }\r\n  }\r\n\r\n})(\r\n  (typeof global !== 'undefined') ? global\r\n    : ((typeof window !== 'undefined') ? window\r\n    : ((typeof self !== 'undefined') ? self : this))\r\n);\r\n", "/*! *****************************************************************************\r\nCopyright (c) Microsoft Corporation.\r\n\r\nPermission to use, copy, modify, and/or distribute this software for any\r\npurpose with or without fee is hereby granted.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\r\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\r\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\r\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\r\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\r\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\r\nPERFORMANCE OF THIS SOFTWARE.\r\n***************************************************************************** */\r\n/* global global, define, System, Reflect, Promise */\r\nvar __extends;\r\nvar __assign;\r\nvar __rest;\r\nvar __decorate;\r\nvar __param;\r\nvar __metadata;\r\nvar __awaiter;\r\nvar __generator;\r\nvar __exportStar;\r\nvar __values;\r\nvar __read;\r\nvar __spread;\r\nvar __spreadArrays;\r\nvar __spreadArray;\r\nvar __await;\r\nvar __asyncGenerator;\r\nvar __asyncDelegator;\r\nvar __asyncValues;\r\nvar __makeTemplateObject;\r\nvar __importStar;\r\nvar __importDefault;\r\nvar __classPrivateFieldGet;\r\nvar __classPrivateFieldSet;\r\nvar __createBinding;\r\n(function (factory) {\r\n    var root = typeof global === \"object\" ? global : typeof self === \"object\" ? self : typeof this === \"object\" ? this : {};\r\n    if (typeof define === \"function\" && define.amd) {\r\n        define(\"tslib\", [\"exports\"], function (exports) { factory(createExporter(root, createExporter(exports))); });\r\n    }\r\n    else if (typeof module === \"object\" && typeof module.exports === \"object\") {\r\n        factory(createExporter(root, createExporter(module.exports)));\r\n    }\r\n    else {\r\n        factory(createExporter(root));\r\n    }\r\n    function createExporter(exports, previous) {\r\n        if (exports !== root) {\r\n            if (typeof Object.create === \"function\") {\r\n                Object.defineProperty(exports, \"__esModule\", { value: true });\r\n            }\r\n            else {\r\n                exports.__esModule = true;\r\n            }\r\n        }\r\n        return function (id, v) { return exports[id] = previous ? previous(id, v) : v; };\r\n    }\r\n})\r\n(function (exporter) {\r\n    var extendStatics = Object.setPrototypeOf ||\r\n        ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\r\n        function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\r\n\r\n    __extends = function (d, b) {\r\n        if (typeof b !== \"function\" && b !== null)\r\n            throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\r\n        extendStatics(d, b);\r\n        function __() { this.constructor = d; }\r\n        d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\r\n    };\r\n\r\n    __assign = Object.assign || function (t) {\r\n        for (var s, i = 1, n = arguments.length; i < n; i++) {\r\n            s = arguments[i];\r\n            for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\r\n        }\r\n        return t;\r\n    };\r\n\r\n    __rest = function (s, e) {\r\n        var t = {};\r\n        for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\r\n            t[p] = s[p];\r\n        if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\r\n            for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\r\n                if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\r\n                    t[p[i]] = s[p[i]];\r\n            }\r\n        return t;\r\n    };\r\n\r\n    __decorate = function (decorators, target, key, desc) {\r\n        var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\r\n        if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\r\n        else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\r\n        return c > 3 && r && Object.defineProperty(target, key, r), r;\r\n    };\r\n\r\n    __param = function (paramIndex, decorator) {\r\n        return function (target, key) { decorator(target, key, paramIndex); }\r\n    };\r\n\r\n    __metadata = function (metadataKey, metadataValue) {\r\n        if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\r\n    };\r\n\r\n    __awaiter = function (thisArg, _arguments, P, generator) {\r\n        function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\r\n        return new (P || (P = Promise))(function (resolve, reject) {\r\n            function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\r\n            function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\r\n            function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\r\n            step((generator = generator.apply(thisArg, _arguments || [])).next());\r\n        });\r\n    };\r\n\r\n    __generator = function (thisArg, body) {\r\n        var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;\r\n        return g = { next: verb(0), \"throw\": verb(1), \"return\": verb(2) }, typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\r\n        function verb(n) { return function (v) { return step([n, v]); }; }\r\n        function step(op) {\r\n            if (f) throw new TypeError(\"Generator is already executing.\");\r\n            while (_) try {\r\n                if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\r\n                if (y = 0, t) op = [op[0] & 2, t.value];\r\n                switch (op[0]) {\r\n                    case 0: case 1: t = op; break;\r\n                    case 4: _.label++; return { value: op[1], done: false };\r\n                    case 5: _.label++; y = op[1]; op = [0]; continue;\r\n                    case 7: op = _.ops.pop(); _.trys.pop(); continue;\r\n                    default:\r\n                        if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\r\n                        if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\r\n                        if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\r\n                        if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\r\n                        if (t[2]) _.ops.pop();\r\n                        _.trys.pop(); continue;\r\n                }\r\n                op = body.call(thisArg, _);\r\n            } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\r\n            if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\r\n        }\r\n    };\r\n\r\n    __exportStar = function(m, o) {\r\n        for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\r\n    };\r\n\r\n    __createBinding = Object.create ? (function(o, m, k, k2) {\r\n        if (k2 === undefined) k2 = k;\r\n        Object.defineProperty(o, k2, { enumerable: true, get: function() { return m[k]; } });\r\n    }) : (function(o, m, k, k2) {\r\n        if (k2 === undefined) k2 = k;\r\n        o[k2] = m[k];\r\n    });\r\n\r\n    __values = function (o) {\r\n        var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\r\n        if (m) return m.call(o);\r\n        if (o && typeof o.length === \"number\") return {\r\n            next: function () {\r\n                if (o && i >= o.length) o = void 0;\r\n                return { value: o && o[i++], done: !o };\r\n            }\r\n        };\r\n        throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\r\n    };\r\n\r\n    __read = function (o, n) {\r\n        var m = typeof Symbol === \"function\" && o[Symbol.iterator];\r\n        if (!m) return o;\r\n        var i = m.call(o), r, ar = [], e;\r\n        try {\r\n            while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\r\n        }\r\n        catch (error) { e = { error: error }; }\r\n        finally {\r\n            try {\r\n                if (r && !r.done && (m = i[\"return\"])) m.call(i);\r\n            }\r\n            finally { if (e) throw e.error; }\r\n        }\r\n        return ar;\r\n    };\r\n\r\n    /** @deprecated */\r\n    __spread = function () {\r\n        for (var ar = [], i = 0; i < arguments.length; i++)\r\n            ar = ar.concat(__read(arguments[i]));\r\n        return ar;\r\n    };\r\n\r\n    /** @deprecated */\r\n    __spreadArrays = function () {\r\n        for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\r\n        for (var r = Array(s), k = 0, i = 0; i < il; i++)\r\n            for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\r\n                r[k] = a[j];\r\n        return r;\r\n    };\r\n\r\n    __spreadArray = function (to, from, pack) {\r\n        if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\r\n            if (ar || !(i in from)) {\r\n                if (!ar) ar = Array.prototype.slice.call(from, 0, i);\r\n                ar[i] = from[i];\r\n            }\r\n        }\r\n        return to.concat(ar || Array.prototype.slice.call(from));\r\n    };\r\n\r\n    __await = function (v) {\r\n        return this instanceof __await ? (this.v = v, this) : new __await(v);\r\n    };\r\n\r\n    __asyncGenerator = function (thisArg, _arguments, generator) {\r\n        if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n        var g = generator.apply(thisArg, _arguments || []), i, q = [];\r\n        return i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i;\r\n        function verb(n) { if (g[n]) i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; }\r\n        function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\r\n        function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r);  }\r\n        function fulfill(value) { resume(\"next\", value); }\r\n        function reject(value) { resume(\"throw\", value); }\r\n        function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\r\n    };\r\n\r\n    __asyncDelegator = function (o) {\r\n        var i, p;\r\n        return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\r\n        function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: n === \"return\" } : f ? f(v) : v; } : f; }\r\n    };\r\n\r\n    __asyncValues = function (o) {\r\n        if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n        var m = o[Symbol.asyncIterator], i;\r\n        return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\r\n        function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\r\n        function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\r\n    };\r\n\r\n    __makeTemplateObject = function (cooked, raw) {\r\n        if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\r\n        return cooked;\r\n    };\r\n\r\n    var __setModuleDefault = Object.create ? (function(o, v) {\r\n        Object.defineProperty(o, \"default\", { enumerable: true, value: v });\r\n    }) : function(o, v) {\r\n        o[\"default\"] = v;\r\n    };\r\n\r\n    __importStar = function (mod) {\r\n        if (mod && mod.__esModule) return mod;\r\n        var result = {};\r\n        if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\r\n        __setModuleDefault(result, mod);\r\n        return result;\r\n    };\r\n\r\n    __importDefault = function (mod) {\r\n        return (mod && mod.__esModule) ? mod : { \"default\": mod };\r\n    };\r\n\r\n    __classPrivateFieldGet = function (receiver, state, kind, f) {\r\n        if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\r\n        if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\r\n        return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\r\n    };\r\n\r\n    __classPrivateFieldSet = function (receiver, state, value, kind, f) {\r\n        if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\r\n        if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\r\n        if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\r\n        return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\r\n    };\r\n\r\n    exporter(\"__extends\", __extends);\r\n    exporter(\"__assign\", __assign);\r\n    exporter(\"__rest\", __rest);\r\n    exporter(\"__decorate\", __decorate);\r\n    exporter(\"__param\", __param);\r\n    exporter(\"__metadata\", __metadata);\r\n    exporter(\"__awaiter\", __awaiter);\r\n    exporter(\"__generator\", __generator);\r\n    exporter(\"__exportStar\", __exportStar);\r\n    exporter(\"__createBinding\", __createBinding);\r\n    exporter(\"__values\", __values);\r\n    exporter(\"__read\", __read);\r\n    exporter(\"__spread\", __spread);\r\n    exporter(\"__spreadArrays\", __spreadArrays);\r\n    exporter(\"__spreadArray\", __spreadArray);\r\n    exporter(\"__await\", __await);\r\n    exporter(\"__asyncGenerator\", __asyncGenerator);\r\n    exporter(\"__asyncDelegator\", __asyncDelegator);\r\n    exporter(\"__asyncValues\", __asyncValues);\r\n    exporter(\"__makeTemplateObject\", __makeTemplateObject);\r\n    exporter(\"__importStar\", __importStar);\r\n    exporter(\"__importDefault\", __importDefault);\r\n    exporter(\"__classPrivateFieldGet\", __classPrivateFieldGet);\r\n    exporter(\"__classPrivateFieldSet\", __classPrivateFieldSet);\r\n});\r\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n  \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n  try {\n    return document.execCommand(type);\n  } catch (err) {\n    return false;\n  }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n  var selectedText = select_default()(target);\n  command('cut');\n  return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n  var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n  var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n  fakeElement.style.fontSize = '12pt'; // Reset box model\n\n  fakeElement.style.border = '0';\n  fakeElement.style.padding = '0';\n  fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n  fakeElement.style.position = 'absolute';\n  fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n  var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n  fakeElement.style.top = \"\".concat(yPosition, \"px\");\n  fakeElement.setAttribute('readonly', '');\n  fakeElement.value = value;\n  return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n  var fakeElement = createFakeElement(value);\n  options.container.appendChild(fakeElement);\n  var selectedText = select_default()(fakeElement);\n  command('copy');\n  fakeElement.remove();\n  return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n  var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n    container: document.body\n  };\n  var selectedText = '';\n\n  if (typeof target === 'string') {\n    selectedText = fakeCopyAction(target, options);\n  } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n    // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n    selectedText = fakeCopyAction(target.value, options);\n  } else {\n    selectedText = select_default()(target);\n    command('copy');\n  }\n\n  return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n  var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n  // Defines base properties passed from constructor.\n  var _options$action = options.action,\n      action = _options$action === void 0 ? 'copy' : _options$action,\n      container = options.container,\n      target = options.target,\n      text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n  if (action !== 'copy' && action !== 'cut') {\n    throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n  } // Sets the `target` property using an element that will be have its content copied.\n\n\n  if (target !== undefined) {\n    if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n      if (action === 'copy' && target.hasAttribute('disabled')) {\n        throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n      }\n\n      if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n        throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n      }\n    } else {\n      throw new Error('Invalid \"target\" value, use a valid Element');\n    }\n  } // Define selection strategy based on `text` property.\n\n\n  if (text) {\n    return actions_copy(text, {\n      container: container\n    });\n  } // Defines which selection strategy based on `target` property.\n\n\n  if (target) {\n    return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n      container: container\n    });\n  }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n  var attribute = \"data-clipboard-\".concat(suffix);\n\n  if (!element.hasAttribute(attribute)) {\n    return;\n  }\n\n  return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n  _inherits(Clipboard, _Emitter);\n\n  var _super = _createSuper(Clipboard);\n\n  /**\n   * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n   * @param {Object} options\n   */\n  function Clipboard(trigger, options) {\n    var _this;\n\n    _classCallCheck(this, Clipboard);\n\n    _this = _super.call(this);\n\n    _this.resolveOptions(options);\n\n    _this.listenClick(trigger);\n\n    return _this;\n  }\n  /**\n   * Defines if attributes would be resolved using internal setter functions\n   * or custom functions that were passed in the constructor.\n   * @param {Object} options\n   */\n\n\n  _createClass(Clipboard, [{\n    key: \"resolveOptions\",\n    value: function resolveOptions() {\n      var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n      this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n      this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n      this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n      this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n    }\n    /**\n     * Adds a click event listener to the passed trigger.\n     * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n     */\n\n  }, {\n    key: \"listenClick\",\n    value: function listenClick(trigger) {\n      var _this2 = this;\n\n      this.listener = listen_default()(trigger, 'click', function (e) {\n        return _this2.onClick(e);\n      });\n    }\n    /**\n     * Defines a new `ClipboardAction` on each click event.\n     * @param {Event} e\n     */\n\n  }, {\n    key: \"onClick\",\n    value: function onClick(e) {\n      var trigger = e.delegateTarget || e.currentTarget;\n      var action = this.action(trigger) || 'copy';\n      var text = actions_default({\n        action: action,\n        container: this.container,\n        target: this.target(trigger),\n        text: this.text(trigger)\n      }); // Fires an event based on the copy operation result.\n\n      this.emit(text ? 'success' : 'error', {\n        action: action,\n        text: text,\n        trigger: trigger,\n        clearSelection: function clearSelection() {\n          if (trigger) {\n            trigger.focus();\n          }\n\n          window.getSelection().removeAllRanges();\n        }\n      });\n    }\n    /**\n     * Default `action` lookup function.\n     * @param {Element} trigger\n     */\n\n  }, {\n    key: \"defaultAction\",\n    value: function defaultAction(trigger) {\n      return getAttributeValue('action', trigger);\n    }\n    /**\n     * Default `target` lookup function.\n     * @param {Element} trigger\n     */\n\n  }, {\n    key: \"defaultTarget\",\n    value: function defaultTarget(trigger) {\n      var selector = getAttributeValue('target', trigger);\n\n      if (selector) {\n        return document.querySelector(selector);\n      }\n    }\n    /**\n     * Allow fire programmatically a copy action\n     * @param {String|HTMLElement} target\n     * @param {Object} options\n     * @returns Text copied.\n     */\n\n  }, {\n    key: \"defaultText\",\n\n    /**\n     * Default `text` lookup function.\n     * @param {Element} trigger\n     */\n    value: function defaultText(trigger) {\n      return getAttributeValue('text', trigger);\n    }\n    /**\n     * Destroy lifecycle.\n     */\n\n  }, {\n    key: \"destroy\",\n    value: function destroy() {\n      this.listener.destroy();\n    }\n  }], [{\n    key: \"copy\",\n    value: function copy(target) {\n      var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n        container: document.body\n      };\n      return actions_copy(target, options);\n    }\n    /**\n     * Allow fire programmatically a cut action\n     * @param {String|HTMLElement} target\n     * @returns Text cutted.\n     */\n\n  }, {\n    key: \"cut\",\n    value: function cut(target) {\n      return actions_cut(target);\n    }\n    /**\n     * Returns the support of the given action, or all actions if no action is\n     * given.\n     * @param {String} [action]\n     */\n\n  }, {\n    key: \"isSupported\",\n    value: function isSupported() {\n      var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n      var actions = typeof action === 'string' ? [action] : action;\n      var support = !!document.queryCommandSupported;\n      actions.forEach(function (action) {\n        support = support && !!document.queryCommandSupported(action);\n      });\n      return support;\n    }\n  }]);\n\n  return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n    var proto = Element.prototype;\n\n    proto.matches = proto.matchesSelector ||\n                    proto.mozMatchesSelector ||\n                    proto.msMatchesSelector ||\n                    proto.oMatchesSelector ||\n                    proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n    while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n        if (typeof element.matches === 'function' &&\n            element.matches(selector)) {\n          return element;\n        }\n        element = element.parentNode;\n    }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n    var listenerFn = listener.apply(this, arguments);\n\n    element.addEventListener(type, listenerFn, useCapture);\n\n    return {\n        destroy: function() {\n            element.removeEventListener(type, listenerFn, useCapture);\n        }\n    }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n    // Handle the regular Element usage\n    if (typeof elements.addEventListener === 'function') {\n        return _delegate.apply(null, arguments);\n    }\n\n    // Handle Element-less usage, it defaults to global delegation\n    if (typeof type === 'function') {\n        // Use `document` as the first parameter, then apply arguments\n        // This is a short way to .unshift `arguments` without running into deoptimizations\n        return _delegate.bind(null, document).apply(null, arguments);\n    }\n\n    // Handle Selector-based usage\n    if (typeof elements === 'string') {\n        elements = document.querySelectorAll(elements);\n    }\n\n    // Handle Array-like based usage\n    return Array.prototype.map.call(elements, function (element) {\n        return _delegate(element, selector, type, callback, useCapture);\n    });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n    return function(e) {\n        e.delegateTarget = closest(e.target, selector);\n\n        if (e.delegateTarget) {\n            callback.call(element, e);\n        }\n    }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n    return value !== undefined\n        && value instanceof HTMLElement\n        && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n    var type = Object.prototype.toString.call(value);\n\n    return value !== undefined\n        && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n        && ('length' in value)\n        && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n    return typeof value === 'string'\n        || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n    var type = Object.prototype.toString.call(value);\n\n    return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n    if (!target && !type && !callback) {\n        throw new Error('Missing required arguments');\n    }\n\n    if (!is.string(type)) {\n        throw new TypeError('Second argument must be a String');\n    }\n\n    if (!is.fn(callback)) {\n        throw new TypeError('Third argument must be a Function');\n    }\n\n    if (is.node(target)) {\n        return listenNode(target, type, callback);\n    }\n    else if (is.nodeList(target)) {\n        return listenNodeList(target, type, callback);\n    }\n    else if (is.string(target)) {\n        return listenSelector(target, type, callback);\n    }\n    else {\n        throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n    }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n    node.addEventListener(type, callback);\n\n    return {\n        destroy: function() {\n            node.removeEventListener(type, callback);\n        }\n    }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n    Array.prototype.forEach.call(nodeList, function(node) {\n        node.addEventListener(type, callback);\n    });\n\n    return {\n        destroy: function() {\n            Array.prototype.forEach.call(nodeList, function(node) {\n                node.removeEventListener(type, callback);\n            });\n        }\n    }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n    return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n    var selectedText;\n\n    if (element.nodeName === 'SELECT') {\n        element.focus();\n\n        selectedText = element.value;\n    }\n    else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n        var isReadOnly = element.hasAttribute('readonly');\n\n        if (!isReadOnly) {\n            element.setAttribute('readonly', '');\n        }\n\n        element.select();\n        element.setSelectionRange(0, element.value.length);\n\n        if (!isReadOnly) {\n            element.removeAttribute('readonly');\n        }\n\n        selectedText = element.value;\n    }\n    else {\n        if (element.hasAttribute('contenteditable')) {\n            element.focus();\n        }\n\n        var selection = window.getSelection();\n        var range = document.createRange();\n\n        range.selectNodeContents(element);\n        selection.removeAllRanges();\n        selection.addRange(range);\n\n        selectedText = selection.toString();\n    }\n\n    return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n  // Keep this empty so it's easier to inherit from\n  // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n  on: function (name, callback, ctx) {\n    var e = this.e || (this.e = {});\n\n    (e[name] || (e[name] = [])).push({\n      fn: callback,\n      ctx: ctx\n    });\n\n    return this;\n  },\n\n  once: function (name, callback, ctx) {\n    var self = this;\n    function listener () {\n      self.off(name, listener);\n      callback.apply(ctx, arguments);\n    };\n\n    listener._ = callback\n    return this.on(name, listener, ctx);\n  },\n\n  emit: function (name) {\n    var data = [].slice.call(arguments, 1);\n    var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n    var i = 0;\n    var len = evtArr.length;\n\n    for (i; i < len; i++) {\n      evtArr[i].fn.apply(evtArr[i].ctx, data);\n    }\n\n    return this;\n  },\n\n  off: function (name, callback) {\n    var e = this.e || (this.e = {});\n    var evts = e[name];\n    var liveEvents = [];\n\n    if (evts && callback) {\n      for (var i = 0, len = evts.length; i < len; i++) {\n        if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n          liveEvents.push(evts[i]);\n      }\n    }\n\n    // Remove event from queue to prevent memory leak\n    // Suggested by https://github.com/lazd\n    // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n    (liveEvents.length)\n      ? e[name] = liveEvents\n      : delete e[name];\n\n    return this;\n  }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param  {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n  var str = '' + string;\n  var match = matchHtmlRegExp.exec(str);\n\n  if (!match) {\n    return str;\n  }\n\n  var escape;\n  var html = '';\n  var index = 0;\n  var lastIndex = 0;\n\n  for (index = match.index; index < str.length; index++) {\n    switch (str.charCodeAt(index)) {\n      case 34: // \"\n        escape = '&quot;';\n        break;\n      case 38: // &\n        escape = '&amp;';\n        break;\n      case 39: // '\n        escape = '&#39;';\n        break;\n      case 60: // <\n        escape = '&lt;';\n        break;\n      case 62: // >\n        escape = '&gt;';\n        break;\n      default:\n        continue;\n    }\n\n    if (lastIndex !== index) {\n      html += str.substring(lastIndex, index);\n    }\n\n    lastIndex = index + 1;\n    html += escape;\n  }\n\n  return lastIndex !== index\n    ? html + str.substring(lastIndex, index)\n    : html;\n}\n", "Array.prototype.flat||Object.defineProperty(Array.prototype,\"flat\",{configurable:!0,value:function r(){var t=isNaN(arguments[0])?1:Number(arguments[0]);return t?Array.prototype.reduce.call(this,function(a,e){return Array.isArray(e)?a.push.apply(a,r.call(e,t-1)):a.push(e),a},[]):Array.prototype.slice.call(this)},writable:!0}),Array.prototype.flatMap||Object.defineProperty(Array.prototype,\"flatMap\",{configurable:!0,value:function(r){return Array.prototype.map.apply(this,arguments).flat()},writable:!0})\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"array-flat-polyfill\"\nimport \"focus-visible\"\nimport \"unfetch/polyfill\"\nimport \"url-polyfill\"\n\nimport {\n  EMPTY,\n  NEVER,\n  Subject,\n  defer,\n  delay,\n  filter,\n  map,\n  merge,\n  mergeWith,\n  shareReplay,\n  switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n  at,\n  getOptionalElement,\n  requestJSON,\n  setToggle,\n  watchDocument,\n  watchKeyboard,\n  watchLocation,\n  watchLocationTarget,\n  watchMedia,\n  watchPrint,\n  watchViewport\n} from \"./browser\"\nimport {\n  getComponentElement,\n  getComponentElements,\n  mountAnnounce,\n  mountBackToTop,\n  mountConsent,\n  mountContent,\n  mountDialog,\n  mountHeader,\n  mountHeaderTitle,\n  mountPalette,\n  mountSearch,\n  mountSearchHiglight,\n  mountSidebar,\n  mountSource,\n  mountTableOfContents,\n  mountTabs,\n  watchHeader,\n  watchMain\n} from \"./components\"\nimport {\n  SearchIndex,\n  setupClipboardJS,\n  setupInstantLoading,\n  setupVersionSelector\n} from \"./integrations\"\nimport {\n  patchIndeterminate,\n  patchScrollfix,\n  patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$   = watchLocationTarget()\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$   = watchMedia(\"(min-width: 960px)\")\nconst screen$   = watchMedia(\"(min-width: 1220px)\")\nconst print$    = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n  ? __search?.index || requestJSON<SearchIndex>(\n    new URL(\"search/search_index.json\", config.base)\n  )\n  : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject<string>()\nsetupClipboardJS({ alert$ })\n\n/* Set up instant loading, if enabled */\nif (feature(\"navigation.instant\"))\n  setupInstantLoading({ document$, location$, viewport$ })\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n  setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n  .pipe(\n    delay(125)\n  )\n    .subscribe(() => {\n      setToggle(\"drawer\", false)\n      setToggle(\"search\", false)\n    })\n\n/* Set up global keyboard handlers */\nkeyboard$\n  .pipe(\n    filter(({ mode }) => mode === \"global\")\n  )\n    .subscribe(key => {\n      switch (key.type) {\n\n        /* Go to previous page */\n        case \"p\":\n        case \",\":\n          const prev = getOptionalElement(\"[href][rel=prev]\")\n          if (typeof prev !== \"undefined\")\n            prev.click()\n          break\n\n        /* Go to next page */\n        case \"n\":\n        case \".\":\n          const next = getOptionalElement(\"[href][rel=next]\")\n          if (typeof next !== \"undefined\")\n            next.click()\n          break\n      }\n    })\n\n/* Set up patches */\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n  .pipe(\n    map(() => getComponentElement(\"main\")),\n    switchMap(el => watchMain(el, { viewport$, header$ })),\n    shareReplay(1)\n  )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n  /* Consent */\n  ...getComponentElements(\"consent\")\n    .map(el => mountConsent(el, { target$ })),\n\n  /* Dialog */\n  ...getComponentElements(\"dialog\")\n    .map(el => mountDialog(el, { alert$ })),\n\n  /* Header */\n  ...getComponentElements(\"header\")\n    .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n  /* Color palette */\n  ...getComponentElements(\"palette\")\n    .map(el => mountPalette(el)),\n\n  /* Search */\n  ...getComponentElements(\"search\")\n    .map(el => mountSearch(el, { index$, keyboard$ })),\n\n  /* Repository information */\n  ...getComponentElements(\"source\")\n    .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n  /* Announcement bar */\n  ...getComponentElements(\"announce\")\n    .map(el => mountAnnounce(el)),\n\n  /* Content */\n  ...getComponentElements(\"content\")\n    .map(el => mountContent(el, { viewport$, target$, print$ })),\n\n  /* Search highlighting */\n  ...getComponentElements(\"content\")\n    .map(el => feature(\"search.highlight\")\n      ? mountSearchHiglight(el, { index$, location$ })\n      : EMPTY\n    ),\n\n  /* Header title */\n  ...getComponentElements(\"header-title\")\n    .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n  /* Sidebar */\n  ...getComponentElements(\"sidebar\")\n    .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n      ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n      : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n    ),\n\n  /* Navigation tabs */\n  ...getComponentElements(\"tabs\")\n    .map(el => mountTabs(el, { viewport$, header$ })),\n\n  /* Table of contents */\n  ...getComponentElements(\"toc\")\n    .map(el => mountTableOfContents(el, { viewport$, header$, target$ })),\n\n  /* Back-to-top button */\n  ...getComponentElements(\"top\")\n    .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n  .pipe(\n    switchMap(() => content$),\n    mergeWith(control$),\n    shareReplay(1)\n  )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$  = document$          /* Document observable */\nwindow.location$  = location$          /* Location subject */\nwindow.target$    = target$            /* Location target observable */\nwindow.keyboard$  = keyboard$          /* Keyboard observable */\nwindow.viewport$  = viewport$          /* Viewport observable */\nwindow.tablet$    = tablet$            /* Media tablet observable */\nwindow.screen$    = screen$            /* Media screen observable */\nwindow.print$     = print$             /* Media print observable */\nwindow.alert$     = alert$             /* Alert subject */\nwindow.component$ = component$         /* Component observable */\n", "self.fetch||(self.fetch=function(e,n){return n=n||{},new Promise(function(t,s){var r=new XMLHttpRequest,o=[],u=[],i={},a=function(){return{ok:2==(r.status/100|0),statusText:r.statusText,status:r.status,url:r.responseURL,text:function(){return Promise.resolve(r.responseText)},json:function(){return Promise.resolve(r.responseText).then(JSON.parse)},blob:function(){return Promise.resolve(new Blob([r.response]))},clone:a,headers:{keys:function(){return o},entries:function(){return u},get:function(e){return i[e.toLowerCase()]},has:function(e){return e.toLowerCase()in i}}}};for(var c in r.open(n.method||\"get\",e,!0),r.onload=function(){r.getAllResponseHeaders().replace(/^(.*?):[^\\S\\n]*([\\s\\S]*?)$/gm,function(e,n,t){o.push(n=n.toLowerCase()),u.push([n,t]),i[n]=i[n]?i[n]+\",\"+t:t}),t(a())},r.onerror=s,r.withCredentials=\"include\"==n.credentials,n.headers)r.setRequestHeader(c,n.headers[c]);r.send(n.body||null)})});\n", "import tslib from '../tslib.js';\r\nconst {\r\n    __extends,\r\n    __assign,\r\n    __rest,\r\n    __decorate,\r\n    __param,\r\n    __metadata,\r\n    __awaiter,\r\n    __generator,\r\n    __exportStar,\r\n    __createBinding,\r\n    __values,\r\n    __read,\r\n    __spread,\r\n    __spreadArrays,\r\n    __spreadArray,\r\n    __await,\r\n    __asyncGenerator,\r\n    __asyncDelegator,\r\n    __asyncValues,\r\n    __makeTemplateObject,\r\n    __importStar,\r\n    __importDefault,\r\n    __classPrivateFieldGet,\r\n    __classPrivateFieldSet,\r\n} = tslib;\r\nexport {\r\n    __extends,\r\n    __assign,\r\n    __rest,\r\n    __decorate,\r\n    __param,\r\n    __metadata,\r\n    __awaiter,\r\n    __generator,\r\n    __exportStar,\r\n    __createBinding,\r\n    __values,\r\n    __read,\r\n    __spread,\r\n    __spreadArrays,\r\n    __spreadArray,\r\n    __await,\r\n    __asyncGenerator,\r\n    __asyncDelegator,\r\n    __asyncValues,\r\n    __makeTemplateObject,\r\n    __importStar,\r\n    __importDefault,\r\n    __classPrivateFieldGet,\r\n    __classPrivateFieldSet,\r\n};\r\n", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  ReplaySubject,\n  Subject,\n  fromEvent\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch document\n *\n * Documents are implemented as subjects, so all downstream observables are\n * automatically updated when a new document is emitted.\n *\n * @returns Document subject\n */\nexport function watchDocument(): Subject<Document> {\n  const document$ = new ReplaySubject<Document>(1)\n  fromEvent(document, \"DOMContentLoaded\", { once: true })\n    .subscribe(() => document$.next(document))\n\n  /* Return document */\n  return document$\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve all elements matching the query selector\n *\n * @template T - Element type\n *\n * @param selector - Query selector\n * @param node - Node of reference\n *\n * @returns Elements\n */\nexport function getElements<T extends keyof HTMLElementTagNameMap>(\n  selector: T, node?: ParentNode\n): HTMLElementTagNameMap[T][]\n\nexport function getElements<T extends HTMLElement>(\n  selector: string, node?: ParentNode\n): T[]\n\nexport function getElements<T extends HTMLElement>(\n  selector: string, node: ParentNode = document\n): T[] {\n  return Array.from(node.querySelectorAll<T>(selector))\n}\n\n/**\n * Retrieve an element matching a query selector or throw a reference error\n *\n * Note that this function assumes that the element is present. If unsure if an\n * element is existent, use the `getOptionalElement` function instead.\n *\n * @template T - Element type\n *\n * @param selector - Query selector\n * @param node - Node of reference\n *\n * @returns Element\n */\nexport function getElement<T extends keyof HTMLElementTagNameMap>(\n  selector: T, node?: ParentNode\n): HTMLElementTagNameMap[T]\n\nexport function getElement<T extends HTMLElement>(\n  selector: string, node?: ParentNode\n): T\n\nexport function getElement<T extends HTMLElement>(\n  selector: string, node: ParentNode = document\n): T {\n  const el = getOptionalElement<T>(selector, node)\n  if (typeof el === \"undefined\")\n    throw new ReferenceError(\n      `Missing element: expected \"${selector}\" to be present`\n    )\n\n  /* Return element */\n  return el\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Retrieve an optional element matching the query selector\n *\n * @template T - Element type\n *\n * @param selector - Query selector\n * @param node - Node of reference\n *\n * @returns Element or nothing\n */\nexport function getOptionalElement<T extends keyof HTMLElementTagNameMap>(\n  selector: T, node?: ParentNode\n): HTMLElementTagNameMap[T] | undefined\n\nexport function getOptionalElement<T extends HTMLElement>(\n  selector: string, node?: ParentNode\n): T | undefined\n\nexport function getOptionalElement<T extends HTMLElement>(\n  selector: string, node: ParentNode = document\n): T | undefined {\n  return node.querySelector<T>(selector) || undefined\n}\n\n/**\n * Retrieve the currently active element\n *\n * @returns Element or nothing\n */\nexport function getActiveElement(): HTMLElement | undefined {\n  return document.activeElement instanceof HTMLElement\n    ? document.activeElement || undefined\n    : undefined\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  debounceTime,\n  distinctUntilChanged,\n  fromEvent,\n  map,\n  merge,\n  startWith\n} from \"rxjs\"\n\nimport { getActiveElement } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch element focus\n *\n * Previously, this function used `focus` and `blur` events to determine whether\n * an element is focused, but this doesn't work if there are focusable elements\n * within the elements itself. A better solutions are `focusin` and `focusout`\n * events, which bubble up the tree and allow for more fine-grained control.\n *\n * `debounceTime` is necessary, because when a focus change happens inside an\n * element, the observable would first emit `false` and then `true` again.\n *\n * @param el - Element\n *\n * @returns Element focus observable\n */\nexport function watchElementFocus(\n  el: HTMLElement\n): Observable<boolean> {\n  return merge(\n    fromEvent(document.body, \"focusin\"),\n    fromEvent(document.body, \"focusout\")\n  )\n    .pipe(\n      debounceTime(1),\n      map(() => {\n        const active = getActiveElement()\n        return typeof active !== \"undefined\"\n          ? el.contains(active)\n          : false\n      }),\n      startWith(el === getActiveElement()),\n      distinctUntilChanged()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  animationFrameScheduler,\n  auditTime,\n  fromEvent,\n  map,\n  merge,\n  startWith\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Element offset\n */\nexport interface ElementOffset {\n  x: number                            /* Horizontal offset */\n  y: number                            /* Vertical offset */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve element offset\n *\n * @param el - Element\n *\n * @returns Element offset\n */\nexport function getElementOffset(\n  el: HTMLElement\n): ElementOffset {\n  return {\n    x: el.offsetLeft,\n    y: el.offsetTop\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch element offset\n *\n * @param el - Element\n *\n * @returns Element offset observable\n */\nexport function watchElementOffset(\n  el: HTMLElement\n): Observable<ElementOffset> {\n  return merge(\n    fromEvent(window, \"load\"),\n    fromEvent(window, \"resize\")\n  )\n    .pipe(\n      auditTime(0, animationFrameScheduler),\n      map(() => getElementOffset(el)),\n      startWith(getElementOffset(el))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  animationFrameScheduler,\n  auditTime,\n  fromEvent,\n  map,\n  merge,\n  startWith\n} from \"rxjs\"\n\nimport { ElementOffset } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve element content offset (= scroll offset)\n *\n * @param el - Element\n *\n * @returns Element content offset\n */\nexport function getElementContentOffset(\n  el: HTMLElement\n): ElementOffset {\n  return {\n    x: el.scrollLeft,\n    y: el.scrollTop\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch element content offset\n *\n * @param el - Element\n *\n * @returns Element content offset observable\n */\nexport function watchElementContentOffset(\n  el: HTMLElement\n): Observable<ElementOffset> {\n  return merge(\n    fromEvent(el, \"scroll\"),\n    fromEvent(window, \"resize\")\n  )\n    .pipe(\n      auditTime(0, animationFrameScheduler),\n      map(() => getElementContentOffset(el)),\n      startWith(getElementContentOffset(el))\n    )\n}\n", "/**\r\n * A collection of shims that provide minimal functionality of the ES6 collections.\r\n *\r\n * These implementations are not meant to be used outside of the ResizeObserver\r\n * modules as they cover only a limited range of use cases.\r\n */\r\n/* eslint-disable require-jsdoc, valid-jsdoc */\r\nvar MapShim = (function () {\r\n    if (typeof Map !== 'undefined') {\r\n        return Map;\r\n    }\r\n    /**\r\n     * Returns index in provided array that matches the specified key.\r\n     *\r\n     * @param {Array<Array>} arr\r\n     * @param {*} key\r\n     * @returns {number}\r\n     */\r\n    function getIndex(arr, key) {\r\n        var result = -1;\r\n        arr.some(function (entry, index) {\r\n            if (entry[0] === key) {\r\n                result = index;\r\n                return true;\r\n            }\r\n            return false;\r\n        });\r\n        return result;\r\n    }\r\n    return /** @class */ (function () {\r\n        function class_1() {\r\n            this.__entries__ = [];\r\n        }\r\n        Object.defineProperty(class_1.prototype, \"size\", {\r\n            /**\r\n             * @returns {boolean}\r\n             */\r\n            get: function () {\r\n                return this.__entries__.length;\r\n            },\r\n            enumerable: true,\r\n            configurable: true\r\n        });\r\n        /**\r\n         * @param {*} key\r\n         * @returns {*}\r\n         */\r\n        class_1.prototype.get = function (key) {\r\n            var index = getIndex(this.__entries__, key);\r\n            var entry = this.__entries__[index];\r\n            return entry && entry[1];\r\n        };\r\n        /**\r\n         * @param {*} key\r\n         * @param {*} value\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.set = function (key, value) {\r\n            var index = getIndex(this.__entries__, key);\r\n            if (~index) {\r\n                this.__entries__[index][1] = value;\r\n            }\r\n            else {\r\n                this.__entries__.push([key, value]);\r\n            }\r\n        };\r\n        /**\r\n         * @param {*} key\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.delete = function (key) {\r\n            var entries = this.__entries__;\r\n            var index = getIndex(entries, key);\r\n            if (~index) {\r\n                entries.splice(index, 1);\r\n            }\r\n        };\r\n        /**\r\n         * @param {*} key\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.has = function (key) {\r\n            return !!~getIndex(this.__entries__, key);\r\n        };\r\n        /**\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.clear = function () {\r\n            this.__entries__.splice(0);\r\n        };\r\n        /**\r\n         * @param {Function} callback\r\n         * @param {*} [ctx=null]\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.forEach = function (callback, ctx) {\r\n            if (ctx === void 0) { ctx = null; }\r\n            for (var _i = 0, _a = this.__entries__; _i < _a.length; _i++) {\r\n                var entry = _a[_i];\r\n                callback.call(ctx, entry[1], entry[0]);\r\n            }\r\n        };\r\n        return class_1;\r\n    }());\r\n})();\n\n/**\r\n * Detects whether window and document objects are available in current environment.\r\n */\r\nvar isBrowser = typeof window !== 'undefined' && typeof document !== 'undefined' && window.document === document;\n\n// Returns global object of a current environment.\r\nvar global$1 = (function () {\r\n    if (typeof global !== 'undefined' && global.Math === Math) {\r\n        return global;\r\n    }\r\n    if (typeof self !== 'undefined' && self.Math === Math) {\r\n        return self;\r\n    }\r\n    if (typeof window !== 'undefined' && window.Math === Math) {\r\n        return window;\r\n    }\r\n    // eslint-disable-next-line no-new-func\r\n    return Function('return this')();\r\n})();\n\n/**\r\n * A shim for the requestAnimationFrame which falls back to the setTimeout if\r\n * first one is not supported.\r\n *\r\n * @returns {number} Requests' identifier.\r\n */\r\nvar requestAnimationFrame$1 = (function () {\r\n    if (typeof requestAnimationFrame === 'function') {\r\n        // It's required to use a bounded function because IE sometimes throws\r\n        // an \"Invalid calling object\" error if rAF is invoked without the global\r\n        // object on the left hand side.\r\n        return requestAnimationFrame.bind(global$1);\r\n    }\r\n    return function (callback) { return setTimeout(function () { return callback(Date.now()); }, 1000 / 60); };\r\n})();\n\n// Defines minimum timeout before adding a trailing call.\r\nvar trailingTimeout = 2;\r\n/**\r\n * Creates a wrapper function which ensures that provided callback will be\r\n * invoked only once during the specified delay period.\r\n *\r\n * @param {Function} callback - Function to be invoked after the delay period.\r\n * @param {number} delay - Delay after which to invoke callback.\r\n * @returns {Function}\r\n */\r\nfunction throttle (callback, delay) {\r\n    var leadingCall = false, trailingCall = false, lastCallTime = 0;\r\n    /**\r\n     * Invokes the original callback function and schedules new invocation if\r\n     * the \"proxy\" was called during current request.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    function resolvePending() {\r\n        if (leadingCall) {\r\n            leadingCall = false;\r\n            callback();\r\n        }\r\n        if (trailingCall) {\r\n            proxy();\r\n        }\r\n    }\r\n    /**\r\n     * Callback invoked after the specified delay. It will further postpone\r\n     * invocation of the original function delegating it to the\r\n     * requestAnimationFrame.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    function timeoutCallback() {\r\n        requestAnimationFrame$1(resolvePending);\r\n    }\r\n    /**\r\n     * Schedules invocation of the original function.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    function proxy() {\r\n        var timeStamp = Date.now();\r\n        if (leadingCall) {\r\n            // Reject immediately following calls.\r\n            if (timeStamp - lastCallTime < trailingTimeout) {\r\n                return;\r\n            }\r\n            // Schedule new call to be in invoked when the pending one is resolved.\r\n            // This is important for \"transitions\" which never actually start\r\n            // immediately so there is a chance that we might miss one if change\r\n            // happens amids the pending invocation.\r\n            trailingCall = true;\r\n        }\r\n        else {\r\n            leadingCall = true;\r\n            trailingCall = false;\r\n            setTimeout(timeoutCallback, delay);\r\n        }\r\n        lastCallTime = timeStamp;\r\n    }\r\n    return proxy;\r\n}\n\n// Minimum delay before invoking the update of observers.\r\nvar REFRESH_DELAY = 20;\r\n// A list of substrings of CSS properties used to find transition events that\r\n// might affect dimensions of observed elements.\r\nvar transitionKeys = ['top', 'right', 'bottom', 'left', 'width', 'height', 'size', 'weight'];\r\n// Check if MutationObserver is available.\r\nvar mutationObserverSupported = typeof MutationObserver !== 'undefined';\r\n/**\r\n * Singleton controller class which handles updates of ResizeObserver instances.\r\n */\r\nvar ResizeObserverController = /** @class */ (function () {\r\n    /**\r\n     * Creates a new instance of ResizeObserverController.\r\n     *\r\n     * @private\r\n     */\r\n    function ResizeObserverController() {\r\n        /**\r\n         * Indicates whether DOM listeners have been added.\r\n         *\r\n         * @private {boolean}\r\n         */\r\n        this.connected_ = false;\r\n        /**\r\n         * Tells that controller has subscribed for Mutation Events.\r\n         *\r\n         * @private {boolean}\r\n         */\r\n        this.mutationEventsAdded_ = false;\r\n        /**\r\n         * Keeps reference to the instance of MutationObserver.\r\n         *\r\n         * @private {MutationObserver}\r\n         */\r\n        this.mutationsObserver_ = null;\r\n        /**\r\n         * A list of connected observers.\r\n         *\r\n         * @private {Array<ResizeObserverSPI>}\r\n         */\r\n        this.observers_ = [];\r\n        this.onTransitionEnd_ = this.onTransitionEnd_.bind(this);\r\n        this.refresh = throttle(this.refresh.bind(this), REFRESH_DELAY);\r\n    }\r\n    /**\r\n     * Adds observer to observers list.\r\n     *\r\n     * @param {ResizeObserverSPI} observer - Observer to be added.\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.addObserver = function (observer) {\r\n        if (!~this.observers_.indexOf(observer)) {\r\n            this.observers_.push(observer);\r\n        }\r\n        // Add listeners if they haven't been added yet.\r\n        if (!this.connected_) {\r\n            this.connect_();\r\n        }\r\n    };\r\n    /**\r\n     * Removes observer from observers list.\r\n     *\r\n     * @param {ResizeObserverSPI} observer - Observer to be removed.\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.removeObserver = function (observer) {\r\n        var observers = this.observers_;\r\n        var index = observers.indexOf(observer);\r\n        // Remove observer if it's present in registry.\r\n        if (~index) {\r\n            observers.splice(index, 1);\r\n        }\r\n        // Remove listeners if controller has no connected observers.\r\n        if (!observers.length && this.connected_) {\r\n            this.disconnect_();\r\n        }\r\n    };\r\n    /**\r\n     * Invokes the update of observers. It will continue running updates insofar\r\n     * it detects changes.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.refresh = function () {\r\n        var changesDetected = this.updateObservers_();\r\n        // Continue running updates if changes have been detected as there might\r\n        // be future ones caused by CSS transitions.\r\n        if (changesDetected) {\r\n            this.refresh();\r\n        }\r\n    };\r\n    /**\r\n     * Updates every observer from observers list and notifies them of queued\r\n     * entries.\r\n     *\r\n     * @private\r\n     * @returns {boolean} Returns \"true\" if any observer has detected changes in\r\n     *      dimensions of it's elements.\r\n     */\r\n    ResizeObserverController.prototype.updateObservers_ = function () {\r\n        // Collect observers that have active observations.\r\n        var activeObservers = this.observers_.filter(function (observer) {\r\n            return observer.gatherActive(), observer.hasActive();\r\n        });\r\n        // Deliver notifications in a separate cycle in order to avoid any\r\n        // collisions between observers, e.g. when multiple instances of\r\n        // ResizeObserver are tracking the same element and the callback of one\r\n        // of them changes content dimensions of the observed target. Sometimes\r\n        // this may result in notifications being blocked for the rest of observers.\r\n        activeObservers.forEach(function (observer) { return observer.broadcastActive(); });\r\n        return activeObservers.length > 0;\r\n    };\r\n    /**\r\n     * Initializes DOM listeners.\r\n     *\r\n     * @private\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.connect_ = function () {\r\n        // Do nothing if running in a non-browser environment or if listeners\r\n        // have been already added.\r\n        if (!isBrowser || this.connected_) {\r\n            return;\r\n        }\r\n        // Subscription to the \"Transitionend\" event is used as a workaround for\r\n        // delayed transitions. This way it's possible to capture at least the\r\n        // final state of an element.\r\n        document.addEventListener('transitionend', this.onTransitionEnd_);\r\n        window.addEventListener('resize', this.refresh);\r\n        if (mutationObserverSupported) {\r\n            this.mutationsObserver_ = new MutationObserver(this.refresh);\r\n            this.mutationsObserver_.observe(document, {\r\n                attributes: true,\r\n                childList: true,\r\n                characterData: true,\r\n                subtree: true\r\n            });\r\n        }\r\n        else {\r\n            document.addEventListener('DOMSubtreeModified', this.refresh);\r\n            this.mutationEventsAdded_ = true;\r\n        }\r\n        this.connected_ = true;\r\n    };\r\n    /**\r\n     * Removes DOM listeners.\r\n     *\r\n     * @private\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.disconnect_ = function () {\r\n        // Do nothing if running in a non-browser environment or if listeners\r\n        // have been already removed.\r\n        if (!isBrowser || !this.connected_) {\r\n            return;\r\n        }\r\n        document.removeEventListener('transitionend', this.onTransitionEnd_);\r\n        window.removeEventListener('resize', this.refresh);\r\n        if (this.mutationsObserver_) {\r\n            this.mutationsObserver_.disconnect();\r\n        }\r\n        if (this.mutationEventsAdded_) {\r\n            document.removeEventListener('DOMSubtreeModified', this.refresh);\r\n        }\r\n        this.mutationsObserver_ = null;\r\n        this.mutationEventsAdded_ = false;\r\n        this.connected_ = false;\r\n    };\r\n    /**\r\n     * \"Transitionend\" event handler.\r\n     *\r\n     * @private\r\n     * @param {TransitionEvent} event\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.onTransitionEnd_ = function (_a) {\r\n        var _b = _a.propertyName, propertyName = _b === void 0 ? '' : _b;\r\n        // Detect whether transition may affect dimensions of an element.\r\n        var isReflowProperty = transitionKeys.some(function (key) {\r\n            return !!~propertyName.indexOf(key);\r\n        });\r\n        if (isReflowProperty) {\r\n            this.refresh();\r\n        }\r\n    };\r\n    /**\r\n     * Returns instance of the ResizeObserverController.\r\n     *\r\n     * @returns {ResizeObserverController}\r\n     */\r\n    ResizeObserverController.getInstance = function () {\r\n        if (!this.instance_) {\r\n            this.instance_ = new ResizeObserverController();\r\n        }\r\n        return this.instance_;\r\n    };\r\n    /**\r\n     * Holds reference to the controller's instance.\r\n     *\r\n     * @private {ResizeObserverController}\r\n     */\r\n    ResizeObserverController.instance_ = null;\r\n    return ResizeObserverController;\r\n}());\n\n/**\r\n * Defines non-writable/enumerable properties of the provided target object.\r\n *\r\n * @param {Object} target - Object for which to define properties.\r\n * @param {Object} props - Properties to be defined.\r\n * @returns {Object} Target object.\r\n */\r\nvar defineConfigurable = (function (target, props) {\r\n    for (var _i = 0, _a = Object.keys(props); _i < _a.length; _i++) {\r\n        var key = _a[_i];\r\n        Object.defineProperty(target, key, {\r\n            value: props[key],\r\n            enumerable: false,\r\n            writable: false,\r\n            configurable: true\r\n        });\r\n    }\r\n    return target;\r\n});\n\n/**\r\n * Returns the global object associated with provided element.\r\n *\r\n * @param {Object} target\r\n * @returns {Object}\r\n */\r\nvar getWindowOf = (function (target) {\r\n    // Assume that the element is an instance of Node, which means that it\r\n    // has the \"ownerDocument\" property from which we can retrieve a\r\n    // corresponding global object.\r\n    var ownerGlobal = target && target.ownerDocument && target.ownerDocument.defaultView;\r\n    // Return the local global object if it's not possible extract one from\r\n    // provided element.\r\n    return ownerGlobal || global$1;\r\n});\n\n// Placeholder of an empty content rectangle.\r\nvar emptyRect = createRectInit(0, 0, 0, 0);\r\n/**\r\n * Converts provided string to a number.\r\n *\r\n * @param {number|string} value\r\n * @returns {number}\r\n */\r\nfunction toFloat(value) {\r\n    return parseFloat(value) || 0;\r\n}\r\n/**\r\n * Extracts borders size from provided styles.\r\n *\r\n * @param {CSSStyleDeclaration} styles\r\n * @param {...string} positions - Borders positions (top, right, ...)\r\n * @returns {number}\r\n */\r\nfunction getBordersSize(styles) {\r\n    var positions = [];\r\n    for (var _i = 1; _i < arguments.length; _i++) {\r\n        positions[_i - 1] = arguments[_i];\r\n    }\r\n    return positions.reduce(function (size, position) {\r\n        var value = styles['border-' + position + '-width'];\r\n        return size + toFloat(value);\r\n    }, 0);\r\n}\r\n/**\r\n * Extracts paddings sizes from provided styles.\r\n *\r\n * @param {CSSStyleDeclaration} styles\r\n * @returns {Object} Paddings box.\r\n */\r\nfunction getPaddings(styles) {\r\n    var positions = ['top', 'right', 'bottom', 'left'];\r\n    var paddings = {};\r\n    for (var _i = 0, positions_1 = positions; _i < positions_1.length; _i++) {\r\n        var position = positions_1[_i];\r\n        var value = styles['padding-' + position];\r\n        paddings[position] = toFloat(value);\r\n    }\r\n    return paddings;\r\n}\r\n/**\r\n * Calculates content rectangle of provided SVG element.\r\n *\r\n * @param {SVGGraphicsElement} target - Element content rectangle of which needs\r\n *      to be calculated.\r\n * @returns {DOMRectInit}\r\n */\r\nfunction getSVGContentRect(target) {\r\n    var bbox = target.getBBox();\r\n    return createRectInit(0, 0, bbox.width, bbox.height);\r\n}\r\n/**\r\n * Calculates content rectangle of provided HTMLElement.\r\n *\r\n * @param {HTMLElement} target - Element for which to calculate the content rectangle.\r\n * @returns {DOMRectInit}\r\n */\r\nfunction getHTMLElementContentRect(target) {\r\n    // Client width & height properties can't be\r\n    // used exclusively as they provide rounded values.\r\n    var clientWidth = target.clientWidth, clientHeight = target.clientHeight;\r\n    // By this condition we can catch all non-replaced inline, hidden and\r\n    // detached elements. Though elements with width & height properties less\r\n    // than 0.5 will be discarded as well.\r\n    //\r\n    // Without it we would need to implement separate methods for each of\r\n    // those cases and it's not possible to perform a precise and performance\r\n    // effective test for hidden elements. E.g. even jQuery's ':visible' filter\r\n    // gives wrong results for elements with width & height less than 0.5.\r\n    if (!clientWidth && !clientHeight) {\r\n        return emptyRect;\r\n    }\r\n    var styles = getWindowOf(target).getComputedStyle(target);\r\n    var paddings = getPaddings(styles);\r\n    var horizPad = paddings.left + paddings.right;\r\n    var vertPad = paddings.top + paddings.bottom;\r\n    // Computed styles of width & height are being used because they are the\r\n    // only dimensions available to JS that contain non-rounded values. It could\r\n    // be possible to utilize the getBoundingClientRect if only it's data wasn't\r\n    // affected by CSS transformations let alone paddings, borders and scroll bars.\r\n    var width = toFloat(styles.width), height = toFloat(styles.height);\r\n    // Width & height include paddings and borders when the 'border-box' box\r\n    // model is applied (except for IE).\r\n    if (styles.boxSizing === 'border-box') {\r\n        // Following conditions are required to handle Internet Explorer which\r\n        // doesn't include paddings and borders to computed CSS dimensions.\r\n        //\r\n        // We can say that if CSS dimensions + paddings are equal to the \"client\"\r\n        // properties then it's either IE, and thus we don't need to subtract\r\n        // anything, or an element merely doesn't have paddings/borders styles.\r\n        if (Math.round(width + horizPad) !== clientWidth) {\r\n            width -= getBordersSize(styles, 'left', 'right') + horizPad;\r\n        }\r\n        if (Math.round(height + vertPad) !== clientHeight) {\r\n            height -= getBordersSize(styles, 'top', 'bottom') + vertPad;\r\n        }\r\n    }\r\n    // Following steps can't be applied to the document's root element as its\r\n    // client[Width/Height] properties represent viewport area of the window.\r\n    // Besides, it's as well not necessary as the <html> itself neither has\r\n    // rendered scroll bars nor it can be clipped.\r\n    if (!isDocumentElement(target)) {\r\n        // In some browsers (only in Firefox, actually) CSS width & height\r\n        // include scroll bars size which can be removed at this step as scroll\r\n        // bars are the only difference between rounded dimensions + paddings\r\n        // and \"client\" properties, though that is not always true in Chrome.\r\n        var vertScrollbar = Math.round(width + horizPad) - clientWidth;\r\n        var horizScrollbar = Math.round(height + vertPad) - clientHeight;\r\n        // Chrome has a rather weird rounding of \"client\" properties.\r\n        // E.g. for an element with content width of 314.2px it sometimes gives\r\n        // the client width of 315px and for the width of 314.7px it may give\r\n        // 314px. And it doesn't happen all the time. So just ignore this delta\r\n        // as a non-relevant.\r\n        if (Math.abs(vertScrollbar) !== 1) {\r\n            width -= vertScrollbar;\r\n        }\r\n        if (Math.abs(horizScrollbar) !== 1) {\r\n            height -= horizScrollbar;\r\n        }\r\n    }\r\n    return createRectInit(paddings.left, paddings.top, width, height);\r\n}\r\n/**\r\n * Checks whether provided element is an instance of the SVGGraphicsElement.\r\n *\r\n * @param {Element} target - Element to be checked.\r\n * @returns {boolean}\r\n */\r\nvar isSVGGraphicsElement = (function () {\r\n    // Some browsers, namely IE and Edge, don't have the SVGGraphicsElement\r\n    // interface.\r\n    if (typeof SVGGraphicsElement !== 'undefined') {\r\n        return function (target) { return target instanceof getWindowOf(target).SVGGraphicsElement; };\r\n    }\r\n    // If it's so, then check that element is at least an instance of the\r\n    // SVGElement and that it has the \"getBBox\" method.\r\n    // eslint-disable-next-line no-extra-parens\r\n    return function (target) { return (target instanceof getWindowOf(target).SVGElement &&\r\n        typeof target.getBBox === 'function'); };\r\n})();\r\n/**\r\n * Checks whether provided element is a document element (<html>).\r\n *\r\n * @param {Element} target - Element to be checked.\r\n * @returns {boolean}\r\n */\r\nfunction isDocumentElement(target) {\r\n    return target === getWindowOf(target).document.documentElement;\r\n}\r\n/**\r\n * Calculates an appropriate content rectangle for provided html or svg element.\r\n *\r\n * @param {Element} target - Element content rectangle of which needs to be calculated.\r\n * @returns {DOMRectInit}\r\n */\r\nfunction getContentRect(target) {\r\n    if (!isBrowser) {\r\n        return emptyRect;\r\n    }\r\n    if (isSVGGraphicsElement(target)) {\r\n        return getSVGContentRect(target);\r\n    }\r\n    return getHTMLElementContentRect(target);\r\n}\r\n/**\r\n * Creates rectangle with an interface of the DOMRectReadOnly.\r\n * Spec: https://drafts.fxtf.org/geometry/#domrectreadonly\r\n *\r\n * @param {DOMRectInit} rectInit - Object with rectangle's x/y coordinates and dimensions.\r\n * @returns {DOMRectReadOnly}\r\n */\r\nfunction createReadOnlyRect(_a) {\r\n    var x = _a.x, y = _a.y, width = _a.width, height = _a.height;\r\n    // If DOMRectReadOnly is available use it as a prototype for the rectangle.\r\n    var Constr = typeof DOMRectReadOnly !== 'undefined' ? DOMRectReadOnly : Object;\r\n    var rect = Object.create(Constr.prototype);\r\n    // Rectangle's properties are not writable and non-enumerable.\r\n    defineConfigurable(rect, {\r\n        x: x, y: y, width: width, height: height,\r\n        top: y,\r\n        right: x + width,\r\n        bottom: height + y,\r\n        left: x\r\n    });\r\n    return rect;\r\n}\r\n/**\r\n * Creates DOMRectInit object based on the provided dimensions and the x/y coordinates.\r\n * Spec: https://drafts.fxtf.org/geometry/#dictdef-domrectinit\r\n *\r\n * @param {number} x - X coordinate.\r\n * @param {number} y - Y coordinate.\r\n * @param {number} width - Rectangle's width.\r\n * @param {number} height - Rectangle's height.\r\n * @returns {DOMRectInit}\r\n */\r\nfunction createRectInit(x, y, width, height) {\r\n    return { x: x, y: y, width: width, height: height };\r\n}\n\n/**\r\n * Class that is responsible for computations of the content rectangle of\r\n * provided DOM element and for keeping track of it's changes.\r\n */\r\nvar ResizeObservation = /** @class */ (function () {\r\n    /**\r\n     * Creates an instance of ResizeObservation.\r\n     *\r\n     * @param {Element} target - Element to be observed.\r\n     */\r\n    function ResizeObservation(target) {\r\n        /**\r\n         * Broadcasted width of content rectangle.\r\n         *\r\n         * @type {number}\r\n         */\r\n        this.broadcastWidth = 0;\r\n        /**\r\n         * Broadcasted height of content rectangle.\r\n         *\r\n         * @type {number}\r\n         */\r\n        this.broadcastHeight = 0;\r\n        /**\r\n         * Reference to the last observed content rectangle.\r\n         *\r\n         * @private {DOMRectInit}\r\n         */\r\n        this.contentRect_ = createRectInit(0, 0, 0, 0);\r\n        this.target = target;\r\n    }\r\n    /**\r\n     * Updates content rectangle and tells whether it's width or height properties\r\n     * have changed since the last broadcast.\r\n     *\r\n     * @returns {boolean}\r\n     */\r\n    ResizeObservation.prototype.isActive = function () {\r\n        var rect = getContentRect(this.target);\r\n        this.contentRect_ = rect;\r\n        return (rect.width !== this.broadcastWidth ||\r\n            rect.height !== this.broadcastHeight);\r\n    };\r\n    /**\r\n     * Updates 'broadcastWidth' and 'broadcastHeight' properties with a data\r\n     * from the corresponding properties of the last observed content rectangle.\r\n     *\r\n     * @returns {DOMRectInit} Last observed content rectangle.\r\n     */\r\n    ResizeObservation.prototype.broadcastRect = function () {\r\n        var rect = this.contentRect_;\r\n        this.broadcastWidth = rect.width;\r\n        this.broadcastHeight = rect.height;\r\n        return rect;\r\n    };\r\n    return ResizeObservation;\r\n}());\n\nvar ResizeObserverEntry = /** @class */ (function () {\r\n    /**\r\n     * Creates an instance of ResizeObserverEntry.\r\n     *\r\n     * @param {Element} target - Element that is being observed.\r\n     * @param {DOMRectInit} rectInit - Data of the element's content rectangle.\r\n     */\r\n    function ResizeObserverEntry(target, rectInit) {\r\n        var contentRect = createReadOnlyRect(rectInit);\r\n        // According to the specification following properties are not writable\r\n        // and are also not enumerable in the native implementation.\r\n        //\r\n        // Property accessors are not being used as they'd require to define a\r\n        // private WeakMap storage which may cause memory leaks in browsers that\r\n        // don't support this type of collections.\r\n        defineConfigurable(this, { target: target, contentRect: contentRect });\r\n    }\r\n    return ResizeObserverEntry;\r\n}());\n\nvar ResizeObserverSPI = /** @class */ (function () {\r\n    /**\r\n     * Creates a new instance of ResizeObserver.\r\n     *\r\n     * @param {ResizeObserverCallback} callback - Callback function that is invoked\r\n     *      when one of the observed elements changes it's content dimensions.\r\n     * @param {ResizeObserverController} controller - Controller instance which\r\n     *      is responsible for the updates of observer.\r\n     * @param {ResizeObserver} callbackCtx - Reference to the public\r\n     *      ResizeObserver instance which will be passed to callback function.\r\n     */\r\n    function ResizeObserverSPI(callback, controller, callbackCtx) {\r\n        /**\r\n         * Collection of resize observations that have detected changes in dimensions\r\n         * of elements.\r\n         *\r\n         * @private {Array<ResizeObservation>}\r\n         */\r\n        this.activeObservations_ = [];\r\n        /**\r\n         * Registry of the ResizeObservation instances.\r\n         *\r\n         * @private {Map<Element, ResizeObservation>}\r\n         */\r\n        this.observations_ = new MapShim();\r\n        if (typeof callback !== 'function') {\r\n            throw new TypeError('The callback provided as parameter 1 is not a function.');\r\n        }\r\n        this.callback_ = callback;\r\n        this.controller_ = controller;\r\n        this.callbackCtx_ = callbackCtx;\r\n    }\r\n    /**\r\n     * Starts observing provided element.\r\n     *\r\n     * @param {Element} target - Element to be observed.\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.observe = function (target) {\r\n        if (!arguments.length) {\r\n            throw new TypeError('1 argument required, but only 0 present.');\r\n        }\r\n        // Do nothing if current environment doesn't have the Element interface.\r\n        if (typeof Element === 'undefined' || !(Element instanceof Object)) {\r\n            return;\r\n        }\r\n        if (!(target instanceof getWindowOf(target).Element)) {\r\n            throw new TypeError('parameter 1 is not of type \"Element\".');\r\n        }\r\n        var observations = this.observations_;\r\n        // Do nothing if element is already being observed.\r\n        if (observations.has(target)) {\r\n            return;\r\n        }\r\n        observations.set(target, new ResizeObservation(target));\r\n        this.controller_.addObserver(this);\r\n        // Force the update of observations.\r\n        this.controller_.refresh();\r\n    };\r\n    /**\r\n     * Stops observing provided element.\r\n     *\r\n     * @param {Element} target - Element to stop observing.\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.unobserve = function (target) {\r\n        if (!arguments.length) {\r\n            throw new TypeError('1 argument required, but only 0 present.');\r\n        }\r\n        // Do nothing if current environment doesn't have the Element interface.\r\n        if (typeof Element === 'undefined' || !(Element instanceof Object)) {\r\n            return;\r\n        }\r\n        if (!(target instanceof getWindowOf(target).Element)) {\r\n            throw new TypeError('parameter 1 is not of type \"Element\".');\r\n        }\r\n        var observations = this.observations_;\r\n        // Do nothing if element is not being observed.\r\n        if (!observations.has(target)) {\r\n            return;\r\n        }\r\n        observations.delete(target);\r\n        if (!observations.size) {\r\n            this.controller_.removeObserver(this);\r\n        }\r\n    };\r\n    /**\r\n     * Stops observing all elements.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.disconnect = function () {\r\n        this.clearActive();\r\n        this.observations_.clear();\r\n        this.controller_.removeObserver(this);\r\n    };\r\n    /**\r\n     * Collects observation instances the associated element of which has changed\r\n     * it's content rectangle.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.gatherActive = function () {\r\n        var _this = this;\r\n        this.clearActive();\r\n        this.observations_.forEach(function (observation) {\r\n            if (observation.isActive()) {\r\n                _this.activeObservations_.push(observation);\r\n            }\r\n        });\r\n    };\r\n    /**\r\n     * Invokes initial callback function with a list of ResizeObserverEntry\r\n     * instances collected from active resize observations.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.broadcastActive = function () {\r\n        // Do nothing if observer doesn't have active observations.\r\n        if (!this.hasActive()) {\r\n            return;\r\n        }\r\n        var ctx = this.callbackCtx_;\r\n        // Create ResizeObserverEntry instance for every active observation.\r\n        var entries = this.activeObservations_.map(function (observation) {\r\n            return new ResizeObserverEntry(observation.target, observation.broadcastRect());\r\n        });\r\n        this.callback_.call(ctx, entries, ctx);\r\n        this.clearActive();\r\n    };\r\n    /**\r\n     * Clears the collection of active observations.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.clearActive = function () {\r\n        this.activeObservations_.splice(0);\r\n    };\r\n    /**\r\n     * Tells whether observer has active observations.\r\n     *\r\n     * @returns {boolean}\r\n     */\r\n    ResizeObserverSPI.prototype.hasActive = function () {\r\n        return this.activeObservations_.length > 0;\r\n    };\r\n    return ResizeObserverSPI;\r\n}());\n\n// Registry of internal observers. If WeakMap is not available use current shim\r\n// for the Map collection as it has all required methods and because WeakMap\r\n// can't be fully polyfilled anyway.\r\nvar observers = typeof WeakMap !== 'undefined' ? new WeakMap() : new MapShim();\r\n/**\r\n * ResizeObserver API. Encapsulates the ResizeObserver SPI implementation\r\n * exposing only those methods and properties that are defined in the spec.\r\n */\r\nvar ResizeObserver = /** @class */ (function () {\r\n    /**\r\n     * Creates a new instance of ResizeObserver.\r\n     *\r\n     * @param {ResizeObserverCallback} callback - Callback that is invoked when\r\n     *      dimensions of the observed elements change.\r\n     */\r\n    function ResizeObserver(callback) {\r\n        if (!(this instanceof ResizeObserver)) {\r\n            throw new TypeError('Cannot call a class as a function.');\r\n        }\r\n        if (!arguments.length) {\r\n            throw new TypeError('1 argument required, but only 0 present.');\r\n        }\r\n        var controller = ResizeObserverController.getInstance();\r\n        var observer = new ResizeObserverSPI(callback, controller, this);\r\n        observers.set(this, observer);\r\n    }\r\n    return ResizeObserver;\r\n}());\r\n// Expose public methods of ResizeObserver.\r\n[\r\n    'observe',\r\n    'unobserve',\r\n    'disconnect'\r\n].forEach(function (method) {\r\n    ResizeObserver.prototype[method] = function () {\r\n        var _a;\r\n        return (_a = observers.get(this))[method].apply(_a, arguments);\r\n    };\r\n});\n\nvar index = (function () {\r\n    // Export existing implementation if available.\r\n    if (typeof global$1.ResizeObserver !== 'undefined') {\r\n        return global$1.ResizeObserver;\r\n    }\r\n    return ResizeObserver;\r\n})();\n\nexport default index;\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport ResizeObserver from \"resize-observer-polyfill\"\nimport {\n  NEVER,\n  Observable,\n  Subject,\n  defer,\n  filter,\n  finalize,\n  map,\n  merge,\n  of,\n  shareReplay,\n  startWith,\n  switchMap,\n  tap\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Element offset\n */\nexport interface ElementSize {\n  width: number                        /* Element width */\n  height: number                       /* Element height */\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Resize observer entry subject\n */\nconst entry$ = new Subject<ResizeObserverEntry>()\n\n/**\n * Resize observer observable\n *\n * This observable will create a `ResizeObserver` on the first subscription\n * and will automatically terminate it when there are no more subscribers.\n * It's quite important to centralize observation in a single `ResizeObserver`,\n * as the performance difference can be quite dramatic, as the link shows.\n *\n * @see https://bit.ly/3iIYfEm - Google Groups on performance\n */\nconst observer$ = defer(() => of(\n  new ResizeObserver(entries => {\n    for (const entry of entries)\n      entry$.next(entry)\n  })\n))\n  .pipe(\n    switchMap(observer => merge(NEVER, of(observer))\n      .pipe(\n        finalize(() => observer.disconnect())\n      )\n    ),\n    shareReplay(1)\n  )\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve element size\n *\n * @param el - Element\n *\n * @returns Element size\n */\nexport function getElementSize(\n  el: HTMLElement\n): ElementSize {\n  return {\n    width:  el.offsetWidth,\n    height: el.offsetHeight\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch element size\n *\n * This function returns an observable that subscribes to a single internal\n * instance of `ResizeObserver` upon subscription, and emit resize events until\n * termination. Note that this function should not be called with the same\n * element twice, as the first unsubscription will terminate observation.\n *\n * Sadly, we can't use the `DOMRect` objects returned by the observer, because\n * we need the emitted values to be consistent with `getElementSize`, which will\n * return the used values (rounded) and not actual values (unrounded). Thus, we\n * use the `offset*` properties. See the linked GitHub issue.\n *\n * @see https://bit.ly/3m0k3he - GitHub issue\n *\n * @param el - Element\n *\n * @returns Element size observable\n */\nexport function watchElementSize(\n  el: HTMLElement\n): Observable<ElementSize> {\n  return observer$\n    .pipe(\n      tap(observer => observer.observe(el)),\n      switchMap(observer => entry$\n        .pipe(\n          filter(({ target }) => target === el),\n          finalize(() => observer.unobserve(el)),\n          map(() => getElementSize(el))\n        )\n      ),\n      startWith(getElementSize(el))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { ElementSize } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve element content size (= scroll width and height)\n *\n * @param el - Element\n *\n * @returns Element content size\n */\nexport function getElementContentSize(\n  el: HTMLElement\n): ElementSize {\n  return {\n    width:  el.scrollWidth,\n    height: el.scrollHeight\n  }\n}\n\n/**\n * Retrieve the overflowing container of an element, if any\n *\n * @param el - Element\n *\n * @returns Overflowing container or nothing\n */\nexport function getElementContainer(\n  el: HTMLElement\n): HTMLElement | undefined {\n  let parent = el.parentElement\n  while (parent)\n    if (\n      el.scrollWidth <= parent.scrollWidth &&\n      el.scrollHeight <= parent.scrollHeight\n    )\n      parent = (el = parent).parentElement\n    else\n      break\n\n  /* Return overflowing container */\n  return parent ? el : undefined\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  NEVER,\n  Observable,\n  Subject,\n  defer,\n  distinctUntilChanged,\n  filter,\n  finalize,\n  map,\n  merge,\n  of,\n  shareReplay,\n  switchMap,\n  tap\n} from \"rxjs\"\n\nimport {\n  getElementContentSize,\n  getElementSize,\n  watchElementContentOffset\n} from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Intersection observer entry subject\n */\nconst entry$ = new Subject<IntersectionObserverEntry>()\n\n/**\n * Intersection observer observable\n *\n * This observable will create an `IntersectionObserver` on first subscription\n * and will automatically terminate it when there are no more subscribers.\n *\n * @see https://bit.ly/3iIYfEm - Google Groups on performance\n */\nconst observer$ = defer(() => of(\n  new IntersectionObserver(entries => {\n    for (const entry of entries)\n      entry$.next(entry)\n  }, {\n    threshold: 0\n  })\n))\n  .pipe(\n    switchMap(observer => merge(NEVER, of(observer))\n      .pipe(\n        finalize(() => observer.disconnect())\n      )\n    ),\n    shareReplay(1)\n  )\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch element visibility\n *\n * @param el - Element\n *\n * @returns Element visibility observable\n */\nexport function watchElementVisibility(\n  el: HTMLElement\n): Observable<boolean> {\n  return observer$\n    .pipe(\n      tap(observer => observer.observe(el)),\n      switchMap(observer => entry$\n        .pipe(\n          filter(({ target }) => target === el),\n          finalize(() => observer.unobserve(el)),\n          map(({ isIntersecting }) => isIntersecting)\n        )\n      )\n    )\n}\n\n/**\n * Watch element boundary\n *\n * This function returns an observable which emits whether the bottom content\n * boundary (= scroll offset) of an element is within a certain threshold.\n *\n * @param el - Element\n * @param threshold - Threshold\n *\n * @returns Element boundary observable\n */\nexport function watchElementBoundary(\n  el: HTMLElement, threshold = 16\n): Observable<boolean> {\n  return watchElementContentOffset(el)\n    .pipe(\n      map(({ y }) => {\n        const visible = getElementSize(el)\n        const content = getElementContentSize(el)\n        return y >= (\n          content.height - visible.height - threshold\n        )\n      }),\n      distinctUntilChanged()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  fromEvent,\n  map,\n  startWith\n} from \"rxjs\"\n\nimport { getElement } from \"../element\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Toggle\n */\nexport type Toggle =\n  | \"drawer\"                           /* Toggle for drawer */\n  | \"search\"                           /* Toggle for search */\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Toggle map\n */\nconst toggles: Record<Toggle, HTMLInputElement> = {\n  drawer: getElement(\"[data-md-toggle=drawer]\"),\n  search: getElement(\"[data-md-toggle=search]\")\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve the value of a toggle\n *\n * @param name - Toggle\n *\n * @returns Toggle value\n */\nexport function getToggle(name: Toggle): boolean {\n  return toggles[name].checked\n}\n\n/**\n * Set toggle\n *\n * Simulating a click event seems to be the most cross-browser compatible way\n * of changing the value while also emitting a `change` event. Before, Material\n * used `CustomEvent` to programmatically change the value of a toggle, but this\n * is a much simpler and cleaner solution which doesn't require a polyfill.\n *\n * @param name - Toggle\n * @param value - Toggle value\n */\nexport function setToggle(name: Toggle, value: boolean): void {\n  if (toggles[name].checked !== value)\n    toggles[name].click()\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch toggle\n *\n * @param name - Toggle\n *\n * @returns Toggle value observable\n */\nexport function watchToggle(name: Toggle): Observable<boolean> {\n  const el = toggles[name]\n  return fromEvent(el, \"change\")\n    .pipe(\n      map(() => el.checked),\n      startWith(el.checked)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  filter,\n  fromEvent,\n  map,\n  share\n} from \"rxjs\"\n\nimport { getActiveElement } from \"../element\"\nimport { getToggle } from \"../toggle\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Keyboard mode\n */\nexport type KeyboardMode =\n  | \"global\"                           /* Global */\n  | \"search\"                           /* Search is open */\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Keyboard\n */\nexport interface Keyboard {\n  mode: KeyboardMode                   /* Keyboard mode */\n  type: string                         /* Key type */\n  claim(): void                        /* Key claim */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Check whether an element may receive keyboard input\n *\n * @param el - Element\n * @param type - Key type\n *\n * @returns Test result\n */\nfunction isSusceptibleToKeyboard(\n  el: HTMLElement, type: string\n): boolean {\n  switch (el.constructor) {\n\n    /* Input elements */\n    case HTMLInputElement:\n      /* @ts-expect-error - omit unnecessary type cast */\n      if (el.type === \"radio\")\n        return /^Arrow/.test(type)\n      else\n        return true\n\n    /* Select element and textarea */\n    case HTMLSelectElement:\n    case HTMLTextAreaElement:\n      return true\n\n    /* Everything else */\n    default:\n      return el.isContentEditable\n  }\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch keyboard\n *\n * @returns Keyboard observable\n */\nexport function watchKeyboard(): Observable<Keyboard> {\n  return fromEvent<KeyboardEvent>(window, \"keydown\")\n    .pipe(\n      filter(ev => !(ev.metaKey || ev.ctrlKey)),\n      map(ev => ({\n        mode: getToggle(\"search\") ? \"search\" : \"global\",\n        type: ev.key,\n        claim() {\n          ev.preventDefault()\n          ev.stopPropagation()\n        }\n      } as Keyboard)),\n      filter(({ mode, type }) => {\n        if (mode === \"global\") {\n          const active = getActiveElement()\n          if (typeof active !== \"undefined\")\n            return !isSusceptibleToKeyboard(active, type)\n        }\n        return true\n      }),\n      share()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { Subject } from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve location\n *\n * This function returns a `URL` object (and not `Location`) to normalize the\n * typings across the application. Furthermore, locations need to be tracked\n * without setting them and `Location` is a singleton which represents the\n * current location.\n *\n * @returns URL\n */\nexport function getLocation(): URL {\n  return new URL(location.href)\n}\n\n/**\n * Set location\n *\n * @param url - URL to change to\n */\nexport function setLocation(url: URL): void {\n  location.href = url.href\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch location\n *\n * @returns Location subject\n */\nexport function watchLocation(): Subject<URL> {\n  return new Subject<URL>()\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { JSX as JSXInternal } from \"preact\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * HTML attributes\n */\ntype Attributes =\n  & JSXInternal.HTMLAttributes\n  & JSXInternal.SVGAttributes\n  & Record<string, any>\n\n/**\n * Child element\n */\ntype Child =\n  | HTMLElement\n  | Text\n  | string\n  | number\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Append a child node to an element\n *\n * @param el - Element\n * @param child - Child node(s)\n */\nfunction appendChild(el: HTMLElement, child: Child | Child[]): void {\n\n  /* Handle primitive types (including raw HTML) */\n  if (typeof child === \"string\" || typeof child === \"number\") {\n    el.innerHTML += child.toString()\n\n  /* Handle nodes */\n  } else if (child instanceof Node) {\n    el.appendChild(child)\n\n  /* Handle nested children */\n  } else if (Array.isArray(child)) {\n    for (const node of child)\n      appendChild(el, node)\n  }\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * JSX factory\n *\n * @template T - Element type\n *\n * @param tag - HTML tag\n * @param attributes - HTML attributes\n * @param children - Child elements\n *\n * @returns Element\n */\nexport function h<T extends keyof HTMLElementTagNameMap>(\n  tag: T, attributes?: Attributes | null, ...children: Child[]\n): HTMLElementTagNameMap[T]\n\nexport function h<T extends h.JSX.Element>(\n  tag: string, attributes?: Attributes | null, ...children: Child[]\n): T\n\nexport function h<T extends h.JSX.Element>(\n  tag: string, attributes?: Attributes | null, ...children: Child[]\n): T {\n  const el = document.createElement(tag)\n\n  /* Set attributes, if any */\n  if (attributes)\n    for (const attr of Object.keys(attributes)) {\n      if (typeof attributes[attr] === \"undefined\")\n        continue\n\n      /* Set default attribute or boolean */\n      if (typeof attributes[attr] !== \"boolean\")\n        el.setAttribute(attr, attributes[attr])\n      else\n        el.setAttribute(attr, \"\")\n    }\n\n  /* Append child nodes */\n  for (const child of children)\n    appendChild(el, child)\n\n  /* Return element */\n  return el as T\n}\n\n/* ----------------------------------------------------------------------------\n * Namespace\n * ------------------------------------------------------------------------- */\n\nexport declare namespace h {\n  namespace JSX {\n    type Element = HTMLElement\n    type IntrinsicElements = JSXInternal.IntrinsicElements\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Truncate a string after the given number of characters\n *\n * This is not a very reasonable approach, since the summaries kind of suck.\n * It would be better to create something more intelligent, highlighting the\n * search occurrences and making a better summary out of it, but this note was\n * written three years ago, so who knows if we'll ever fix it.\n *\n * @param value - Value to be truncated\n * @param n - Number of characters\n *\n * @returns Truncated value\n */\nexport function truncate(value: string, n: number): string {\n  let i = n\n  if (value.length > i) {\n    while (value[i] !== \" \" && --i > 0) { /* keep eating */ }\n    return `${value.substring(0, i)}...`\n  }\n  return value\n}\n\n/**\n * Round a number for display with repository facts\n *\n * This is a reverse-engineered version of GitHub's weird rounding algorithm\n * for stars, forks and all other numbers. While all numbers below `1,000` are\n * returned as-is, bigger numbers are converted to fixed numbers:\n *\n * - `1,049` => `1k`\n * - `1,050` => `1.1k`\n * - `1,949` => `1.9k`\n * - `1,950` => `2k`\n *\n * @param value - Original value\n *\n * @returns Rounded value\n */\nexport function round(value: number): string {\n  if (value > 999) {\n    const digits = +((value - 950) % 1000 > 99)\n    return `${((value + 0.000001) / 1000).toFixed(digits)}k`\n  } else {\n    return value.toString()\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  filter,\n  fromEvent,\n  map,\n  shareReplay,\n  startWith\n} from \"rxjs\"\n\nimport { getOptionalElement } from \"~/browser\"\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve location hash\n *\n * @returns Location hash\n */\nexport function getLocationHash(): string {\n  return location.hash.substring(1)\n}\n\n/**\n * Set location hash\n *\n * Setting a new fragment identifier via `location.hash` will have no effect\n * if the value doesn't change. When a new fragment identifier is set, we want\n * the browser to target the respective element at all times, which is why we\n * use this dirty little trick.\n *\n * @param hash - Location hash\n */\nexport function setLocationHash(hash: string): void {\n  const el = h(\"a\", { href: hash })\n  el.addEventListener(\"click\", ev => ev.stopPropagation())\n  el.click()\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch location hash\n *\n * @returns Location hash observable\n */\nexport function watchLocationHash(): Observable<string> {\n  return fromEvent<HashChangeEvent>(window, \"hashchange\")\n    .pipe(\n      map(getLocationHash),\n      startWith(getLocationHash()),\n      filter(hash => hash.length > 0),\n      shareReplay(1)\n    )\n}\n\n/**\n * Watch location target\n *\n * @returns Location target observable\n */\nexport function watchLocationTarget(): Observable<HTMLElement> {\n  return watchLocationHash()\n    .pipe(\n      map(id => getOptionalElement(`[id=\"${id}\"]`)!),\n      filter(el => typeof el !== \"undefined\")\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  fromEvent,\n  fromEventPattern,\n  map,\n  merge,\n  startWith,\n  switchMap\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch media query\n *\n * Note that although `MediaQueryList.addListener` is deprecated we have to\n * use it, because it's the only way to ensure proper downward compatibility.\n *\n * @see https://bit.ly/3dUBH2m - GitHub issue\n *\n * @param query - Media query\n *\n * @returns Media observable\n */\nexport function watchMedia(query: string): Observable<boolean> {\n  const media = matchMedia(query)\n  return fromEventPattern<boolean>(next => (\n    media.addListener(() => next(media.matches))\n  ))\n    .pipe(\n      startWith(media.matches)\n    )\n}\n\n/**\n * Watch print mode\n *\n * @returns Print observable\n */\nexport function watchPrint(): Observable<boolean> {\n  const media = matchMedia(\"print\")\n  return merge(\n    fromEvent(window, \"beforeprint\").pipe(map(() => true)),\n    fromEvent(window, \"afterprint\").pipe(map(() => false))\n  )\n    .pipe(\n      startWith(media.matches)\n    )\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Toggle an observable with a media observable\n *\n * @template T - Data type\n *\n * @param query$ - Media observable\n * @param factory - Observable factory\n *\n * @returns Toggled observable\n */\nexport function at<T>(\n  query$: Observable<boolean>, factory: () => Observable<T>\n): Observable<T> {\n  return query$\n    .pipe(\n      switchMap(active => active ? factory() : EMPTY)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  catchError,\n  from,\n  map,\n  of,\n  shareReplay,\n  switchMap,\n  throwError\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch the given URL\n *\n * If the request fails (e.g. when dispatched from `file://` locations), the\n * observable will complete without emitting a value.\n *\n * @param url - Request URL\n * @param options - Options\n *\n * @returns Response observable\n */\nexport function request(\n  url: URL | string, options: RequestInit = { credentials: \"same-origin\" }\n): Observable<Response> {\n  return from(fetch(`${url}`, options))\n    .pipe(\n      catchError(() => EMPTY),\n      switchMap(res => res.status !== 200\n        ? throwError(() => new Error(res.statusText))\n        : of(res)\n      )\n    )\n}\n\n/**\n * Fetch JSON from the given URL\n *\n * @template T - Data type\n *\n * @param url - Request URL\n * @param options - Options\n *\n * @returns Data observable\n */\nexport function requestJSON<T>(\n  url: URL | string, options?: RequestInit\n): Observable<T> {\n  return request(url, options)\n    .pipe(\n      switchMap(res => res.json()),\n      shareReplay(1)\n    )\n}\n\n/**\n * Fetch XML from the given URL\n *\n * @param url - Request URL\n * @param options - Options\n *\n * @returns Data observable\n */\nexport function requestXML(\n  url: URL | string, options?: RequestInit\n): Observable<Document> {\n  const dom = new DOMParser()\n  return request(url, options)\n    .pipe(\n      switchMap(res => res.text()),\n      map(res => dom.parseFromString(res, \"text/xml\")),\n      shareReplay(1)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  defer,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  switchMap,\n  take,\n  throwError\n} from \"rxjs\"\n\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create and load a `script` element\n *\n * This function returns an observable that will emit when the script was\n * successfully loaded, or throw an error if it didn't.\n *\n * @param src - Script URL\n *\n * @returns Script observable\n */\nexport function watchScript(src: string): Observable<void> {\n  const script = h(\"script\", { src })\n  return defer(() => {\n    document.head.appendChild(script)\n    return merge(\n      fromEvent(script, \"load\"),\n      fromEvent(script, \"error\")\n        .pipe(\n          switchMap(() => (\n            throwError(() => new ReferenceError(`Invalid script: ${src}`))\n          ))\n        )\n    )\n      .pipe(\n        map(() => undefined),\n        finalize(() => document.head.removeChild(script)),\n        take(1)\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  fromEvent,\n  map,\n  merge,\n  startWith\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Viewport offset\n */\nexport interface ViewportOffset {\n  x: number                            /* Horizontal offset */\n  y: number                            /* Vertical offset */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve viewport offset\n *\n * On iOS Safari, viewport offset can be negative due to overflow scrolling.\n * As this may induce strange behaviors downstream, we'll just limit it to 0.\n *\n * @returns Viewport offset\n */\nexport function getViewportOffset(): ViewportOffset {\n  return {\n    x: Math.max(0, scrollX),\n    y: Math.max(0, scrollY)\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch viewport offset\n *\n * @returns Viewport offset observable\n */\nexport function watchViewportOffset(): Observable<ViewportOffset> {\n  return merge(\n    fromEvent(window, \"scroll\", { passive: true }),\n    fromEvent(window, \"resize\", { passive: true })\n  )\n    .pipe(\n      map(getViewportOffset),\n      startWith(getViewportOffset())\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  fromEvent,\n  map,\n  startWith\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Viewport size\n */\nexport interface ViewportSize {\n  width: number                        /* Viewport width */\n  height: number                       /* Viewport height */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve viewport size\n *\n * @returns Viewport size\n */\nexport function getViewportSize(): ViewportSize {\n  return {\n    width:  innerWidth,\n    height: innerHeight\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch viewport size\n *\n * @returns Viewport size observable\n */\nexport function watchViewportSize(): Observable<ViewportSize> {\n  return fromEvent(window, \"resize\", { passive: true })\n    .pipe(\n      map(getViewportSize),\n      startWith(getViewportSize())\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  combineLatest,\n  map,\n  shareReplay\n} from \"rxjs\"\n\nimport {\n  ViewportOffset,\n  watchViewportOffset\n} from \"../offset\"\nimport {\n  ViewportSize,\n  watchViewportSize\n} from \"../size\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Viewport\n */\nexport interface Viewport {\n  offset: ViewportOffset               /* Viewport offset */\n  size: ViewportSize                   /* Viewport size */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch viewport\n *\n * @returns Viewport observable\n */\nexport function watchViewport(): Observable<Viewport> {\n  return combineLatest([\n    watchViewportOffset(),\n    watchViewportSize()\n  ])\n    .pipe(\n      map(([offset, size]) => ({ offset, size })),\n      shareReplay(1)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  combineLatest,\n  distinctUntilKeyChanged,\n  map\n} from \"rxjs\"\n\nimport { Header } from \"~/components\"\n\nimport { getElementOffset } from \"../../element\"\nimport { Viewport } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch viewport relative to element\n *\n * @param el - Element\n * @param options - Options\n *\n * @returns Viewport observable\n */\nexport function watchViewportAt(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<Viewport> {\n  const size$ = viewport$\n    .pipe(\n      distinctUntilKeyChanged(\"size\")\n    )\n\n  /* Compute element offset */\n  const offset$ = combineLatest([size$, header$])\n    .pipe(\n      map(() => getElementOffset(el))\n    )\n\n  /* Compute relative viewport, return hot observable */\n  return combineLatest([header$, viewport$, offset$])\n    .pipe(\n      map(([{ height }, { offset, size }, { x, y }]) => ({\n        offset: {\n          x: offset.x - x,\n          y: offset.y - y + height\n        },\n        size\n      }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  fromEvent,\n  map,\n  share,\n  switchMap,\n  tap,\n  throttle\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Worker message\n */\nexport interface WorkerMessage {\n  type: unknown                        /* Message type */\n  data?: unknown                       /* Message data */\n}\n\n/**\n * Worker handler\n *\n * @template T - Message type\n */\nexport interface WorkerHandler<\n  T extends WorkerMessage\n> {\n  tx$: Subject<T>                      /* Message transmission subject */\n  rx$: Observable<T>                   /* Message receive observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n *\n * @template T - Worker message type\n */\ninterface WatchOptions<T extends WorkerMessage> {\n  tx$: Observable<T>                   /* Message transmission observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch a web worker\n *\n * This function returns an observable that sends all values emitted by the\n * message observable to the web worker. Web worker communication is expected\n * to be bidirectional (request-response) and synchronous. Messages that are\n * emitted during a pending request are throttled, the last one is emitted.\n *\n * @param worker - Web worker\n * @param options - Options\n *\n * @returns Worker message observable\n */\nexport function watchWorker<T extends WorkerMessage>(\n  worker: Worker, { tx$ }: WatchOptions<T>\n): Observable<T> {\n\n  /* Intercept messages from worker-like objects */\n  const rx$ = fromEvent<MessageEvent>(worker, \"message\")\n    .pipe(\n      map(({ data }) => data as T)\n    )\n\n  /* Send and receive messages, return hot observable */\n  return tx$\n    .pipe(\n      throttle(() => rx$, { leading: true, trailing: true }),\n      tap(message => worker.postMessage(message)),\n      switchMap(() => rx$),\n      share()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { getElement, getLocation } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Feature flag\n */\nexport type Flag =\n  | \"announce.dismiss\"                 /* Dismissable announcement bar */\n  | \"content.code.annotate\"            /* Code annotations */\n  | \"content.lazy\"                     /* Lazy content elements */\n  | \"content.tabs.link\"                /* Link content tabs */\n  | \"header.autohide\"                  /* Hide header */\n  | \"navigation.expand\"                /* Automatic expansion */\n  | \"navigation.indexes\"               /* Section pages */\n  | \"navigation.instant\"               /* Instant loading */\n  | \"navigation.sections\"              /* Section navigation */\n  | \"navigation.tabs\"                  /* Tabs navigation */\n  | \"navigation.tabs.sticky\"           /* Tabs navigation (sticky) */\n  | \"navigation.top\"                   /* Back-to-top button */\n  | \"navigation.tracking\"              /* Anchor tracking */\n  | \"search.highlight\"                 /* Search highlighting */\n  | \"search.share\"                     /* Search sharing */\n  | \"search.suggest\"                   /* Search suggestions */\n  | \"toc.follow\"                       /* Following table of contents */\n  | \"toc.integrate\"                    /* Integrated table of contents */\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Translation\n */\nexport type Translation =\n  | \"clipboard.copy\"                   /* Copy to clipboard */\n  | \"clipboard.copied\"                 /* Copied to clipboard */\n  | \"search.config.lang\"               /* Search language */\n  | \"search.config.pipeline\"           /* Search pipeline */\n  | \"search.config.separator\"          /* Search separator */\n  | \"search.placeholder\"               /* Search */\n  | \"search.result.placeholder\"        /* Type to start searching */\n  | \"search.result.none\"               /* No matching documents */\n  | \"search.result.one\"                /* 1 matching document */\n  | \"search.result.other\"              /* # matching documents */\n  | \"search.result.more.one\"           /* 1 more on this page */\n  | \"search.result.more.other\"         /* # more on this page */\n  | \"search.result.term.missing\"       /* Missing */\n  | \"select.version.title\"             /* Version selector */\n\n/**\n * Translations\n */\nexport type Translations = Record<Translation, string>\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Versioning\n */\nexport interface Versioning {\n  provider: \"mike\"                     /* Version provider */\n  default?: string                     /* Default version */\n}\n\n/**\n * Configuration\n */\nexport interface Config {\n  base: string                         /* Base URL */\n  features: Flag[]                     /* Feature flags */\n  translations: Translations           /* Translations */\n  search: string                       /* Search worker URL */\n  tags?: Record<string, string>        /* Tags mapping */\n  version?: Versioning                 /* Versioning */\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve global configuration and make base URL absolute\n */\nconst script = getElement(\"#__config\")\nconst config: Config = JSON.parse(script.textContent!)\nconfig.base = `${new URL(config.base, getLocation())}`\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve global configuration\n *\n * @returns Global configuration\n */\nexport function configuration(): Config {\n  return config\n}\n\n/**\n * Check whether a feature flag is enabled\n *\n * @param flag - Feature flag\n *\n * @returns Test result\n */\nexport function feature(flag: Flag): boolean {\n  return config.features.includes(flag)\n}\n\n/**\n * Retrieve the translation for the given key\n *\n * @param key - Key to be translated\n * @param value - Positional value, if any\n *\n * @returns Translation\n */\nexport function translation(\n  key: Translation, value?: string | number\n): string {\n  return typeof value !== \"undefined\"\n    ? config.translations[key].replace(\"#\", value.toString())\n    : config.translations[key]\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { getElement, getElements } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Component type\n */\nexport type ComponentType =\n  | \"announce\"                         /* Announcement bar */\n  | \"container\"                        /* Container */\n  | \"consent\"                          /* Consent */\n  | \"content\"                          /* Content */\n  | \"dialog\"                           /* Dialog */\n  | \"header\"                           /* Header */\n  | \"header-title\"                     /* Header title */\n  | \"header-topic\"                     /* Header topic */\n  | \"main\"                             /* Main area */\n  | \"outdated\"                         /* Version warning */\n  | \"palette\"                          /* Color palette */\n  | \"search\"                           /* Search */\n  | \"search-query\"                     /* Search input */\n  | \"search-result\"                    /* Search results */\n  | \"search-share\"                     /* Search sharing */\n  | \"search-suggest\"                   /* Search suggestions */\n  | \"sidebar\"                          /* Sidebar */\n  | \"skip\"                             /* Skip link */\n  | \"source\"                           /* Repository information */\n  | \"tabs\"                             /* Navigation tabs */\n  | \"toc\"                              /* Table of contents */\n  | \"top\"                              /* Back-to-top button */\n\n/**\n * Component\n *\n * @template T - Component type\n * @template U - Reference type\n */\nexport type Component<\n  T extends {} = {},\n  U extends HTMLElement = HTMLElement\n> =\n  T & {\n    ref: U                             /* Component reference */\n  }\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Component type map\n */\ninterface ComponentTypeMap {\n  \"announce\": HTMLElement              /* Announcement bar */\n  \"container\": HTMLElement             /* Container */\n  \"consent\": HTMLElement               /* Consent */\n  \"content\": HTMLElement               /* Content */\n  \"dialog\": HTMLElement                /* Dialog */\n  \"header\": HTMLElement                /* Header */\n  \"header-title\": HTMLElement          /* Header title */\n  \"header-topic\": HTMLElement          /* Header topic */\n  \"main\": HTMLElement                  /* Main area */\n  \"outdated\": HTMLElement              /* Version warning */\n  \"palette\": HTMLElement               /* Color palette */\n  \"search\": HTMLElement                /* Search */\n  \"search-query\": HTMLInputElement     /* Search input */\n  \"search-result\": HTMLElement         /* Search results */\n  \"search-share\": HTMLAnchorElement    /* Search sharing */\n  \"search-suggest\": HTMLElement        /* Search suggestions */\n  \"sidebar\": HTMLElement               /* Sidebar */\n  \"skip\": HTMLAnchorElement            /* Skip link */\n  \"source\": HTMLAnchorElement          /* Repository information */\n  \"tabs\": HTMLElement                  /* Navigation tabs */\n  \"toc\": HTMLElement                   /* Table of contents */\n  \"top\": HTMLAnchorElement             /* Back-to-top button */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve the element for a given component or throw a reference error\n *\n * @template T - Component type\n *\n * @param type - Component type\n * @param node - Node of reference\n *\n * @returns Element\n */\nexport function getComponentElement<T extends ComponentType>(\n  type: T, node: ParentNode = document\n): ComponentTypeMap[T] {\n  return getElement(`[data-md-component=${type}]`, node)\n}\n\n/**\n * Retrieve all elements for a given component\n *\n * @template T - Component type\n *\n * @param type - Component type\n * @param node - Node of reference\n *\n * @returns Elements\n */\nexport function getComponentElements<T extends ComponentType>(\n  type: T, node: ParentNode = document\n): ComponentTypeMap[T][] {\n  return getElements(`[data-md-component=${type}]`, node)\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  defer,\n  finalize,\n  fromEvent,\n  map,\n  startWith,\n  tap\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport { getElement } from \"~/browser\"\n\nimport { Component } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Announcement bar\n */\nexport interface Announce {\n  hash: number                        /* Content hash */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch announcement bar\n *\n * @param el - Announcement bar element\n *\n * @returns Announcement bar observable\n */\nexport function watchAnnounce(\n  el: HTMLElement\n): Observable<Announce> {\n  const button = getElement(\".md-typeset > :first-child\", el)\n  return fromEvent(button, \"click\", { once: true })\n    .pipe(\n      map(() => getElement(\".md-typeset\", el)),\n      map(content => ({ hash: __md_hash(content.innerHTML) }))\n    )\n}\n\n/**\n * Mount announcement bar\n *\n * @param el - Announcement bar element\n *\n * @returns Announcement bar component observable\n */\nexport function mountAnnounce(\n  el: HTMLElement\n): Observable<Component<Announce>> {\n  if (!feature(\"announce.dismiss\") || !el.childElementCount)\n    return EMPTY\n\n  /* Mount component on subscription */\n  return defer(() => {\n    const push$ = new Subject<Announce>()\n    push$\n      .pipe(\n        startWith({ hash: __md_get<number>(\"__announce\") })\n      )\n        .subscribe(({ hash }) => {\n          if (hash && hash === (__md_get<number>(\"__announce\") ?? hash)) {\n            el.hidden = true\n\n            /* Persist preference in local storage */\n            __md_set<number>(\"__announce\", hash)\n          }\n        })\n\n    /* Create and return component */\n    return watchAnnounce(el)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  finalize,\n  map,\n  tap\n} from \"rxjs\"\n\nimport { Component } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Consent\n */\nexport interface Consent {\n  hidden: boolean                      /* Consent is hidden */\n}\n\n/**\n * Consent defaults\n */\nexport interface ConsentDefaults {\n  analytics?: boolean                  /* Consent for Analytics */\n  github?: boolean                     /* Consent for GitHub */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  target$: Observable<HTMLElement>     /* Target observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  target$: Observable<HTMLElement>     /* Target observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch consent\n *\n * @param el - Consent element\n * @param options - Options\n *\n * @returns Consent observable\n */\nexport function watchConsent(\n  el: HTMLElement, { target$ }: WatchOptions\n): Observable<Consent> {\n  return target$\n    .pipe(\n      map(target => ({ hidden: target !== el }))\n    )\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Mount consent\n *\n * @param el - Consent element\n * @param options - Options\n *\n * @returns Consent component observable\n */\nexport function mountConsent(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<Consent>> {\n  const internal$ = new Subject<Consent>()\n  internal$.subscribe(({ hidden }) => {\n    el.hidden = hidden\n  })\n\n  /* Create and return component */\n  return watchConsent(el, options)\n    .pipe(\n      tap(state => internal$.next(state)),\n      finalize(() => internal$.complete()),\n      map(state => ({ ref: el, ...state }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport ClipboardJS from \"clipboard\"\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  defer,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  finalize,\n  map,\n  mergeWith,\n  switchMap,\n  take,\n  tap\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  getElementContentSize,\n  watchElementSize,\n  watchElementVisibility\n} from \"~/browser\"\nimport { renderClipboardButton } from \"~/templates\"\n\nimport { Component } from \"../../../_\"\nimport {\n  Annotation,\n  mountAnnotationList\n} from \"../../annotation\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Code block\n */\nexport interface CodeBlock {\n  scrollable: boolean                  /* Code block overflows */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  target$: Observable<HTMLElement>     /* Location target observable */\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Global sequence number for code blocks\n */\nlet sequence = 0\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Find candidate list element directly following a code block\n *\n * @param el - Code block element\n *\n * @returns List element or nothing\n */\nfunction findCandidateList(el: HTMLElement): HTMLElement | undefined {\n  if (el.nextElementSibling) {\n    const sibling = el.nextElementSibling as HTMLElement\n    if (sibling.tagName === \"OL\")\n      return sibling\n\n    /* Skip empty paragraphs - see https://bit.ly/3r4ZJ2O */\n    else if (sibling.tagName === \"P\" && !sibling.children.length)\n      return findCandidateList(sibling)\n  }\n\n  /* Everything else */\n  return undefined\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch code block\n *\n * This function monitors size changes of the viewport, as well as switches of\n * content tabs with embedded code blocks, as both may trigger overflow.\n *\n * @param el - Code block element\n *\n * @returns Code block observable\n */\nexport function watchCodeBlock(\n  el: HTMLElement\n): Observable<CodeBlock> {\n  return watchElementSize(el)\n    .pipe(\n      map(({ width }) => {\n        const content = getElementContentSize(el)\n        return {\n          scrollable: content.width > width\n        }\n      }),\n      distinctUntilKeyChanged(\"scrollable\")\n    )\n}\n\n/**\n * Mount code block\n *\n * This function ensures that an overflowing code block is focusable through\n * keyboard, so it can be scrolled without a mouse to improve on accessibility.\n * Furthermore, if code annotations are enabled, they are mounted if and only\n * if the code block is currently visible, e.g., not in a hidden content tab.\n *\n * Note that code blocks may be mounted eagerly or lazily. If they're mounted\n * lazily (on first visibility), code annotation anchor links will not work,\n * as they are evaluated on initial page load, and code annotations in general\n * might feel a little bumpier.\n *\n * @param el - Code block element\n * @param options - Options\n *\n * @returns Code block and annotation component observable\n */\nexport function mountCodeBlock(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<CodeBlock | Annotation>> {\n  const { matches: hover } = matchMedia(\"(hover)\")\n\n  /* Defer mounting of code block - see https://bit.ly/3vHVoVD */\n  const factory$ = defer(() => {\n    const push$ = new Subject<CodeBlock>()\n    push$.subscribe(({ scrollable }) => {\n      if (scrollable && hover)\n        el.setAttribute(\"tabindex\", \"0\")\n      else\n        el.removeAttribute(\"tabindex\")\n    })\n\n    /* Render button for Clipboard.js integration */\n    if (ClipboardJS.isSupported()) {\n      const parent = el.closest(\"pre\")!\n      parent.id = `__code_${++sequence}`\n      parent.insertBefore(\n        renderClipboardButton(parent.id),\n        el\n      )\n    }\n\n    /* Handle code annotations */\n    const container = el.closest(\".highlight\")\n    if (container instanceof HTMLElement) {\n      const list = findCandidateList(container)\n\n      /* Mount code annotations, if enabled */\n      if (typeof list !== \"undefined\" && (\n        container.classList.contains(\"annotate\") ||\n        feature(\"content.code.annotate\")\n      )) {\n        const annotations$ = mountAnnotationList(list, el, options)\n\n        /* Create and return component */\n        return watchCodeBlock(el)\n          .pipe(\n            tap(state => push$.next(state)),\n            finalize(() => push$.complete()),\n            map(state => ({ ref: el, ...state })),\n            mergeWith(\n              watchElementSize(container)\n                .pipe(\n                  map(({ width, height }) => width && height),\n                  distinctUntilChanged(),\n                  switchMap(active => active ? annotations$ : EMPTY)\n                )\n            )\n          )\n      }\n    }\n\n    /* Create and return component */\n    return watchCodeBlock(el)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n\n  /* Mount code block lazily */\n  if (feature(\"content.lazy\"))\n    return watchElementVisibility(el)\n      .pipe(\n        filter(visible => visible),\n        take(1),\n        switchMap(() => factory$)\n      )\n\n  /* Mount code block */\n  return factory$\n}\n", "/*\n * Copyright (c) 2016-2021 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a tooltip\n *\n * @param id - Tooltip identifier\n *\n * @returns Element\n */\nexport function renderTooltip(id?: string): HTMLElement {\n  return (\n    <div class=\"md-tooltip\" id={id}>\n      <div class=\"md-tooltip__inner md-typeset\"></div>\n    </div>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { h } from \"~/utilities\"\n\nimport { renderTooltip } from \"../tooltip\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render an annotation\n *\n * @param id - Annotation identifier\n * @param prefix - Tooltip identifier prefix\n *\n * @returns Element\n */\nexport function renderAnnotation(\n  id: string | number, prefix?: string\n): HTMLElement {\n  prefix = prefix ? `${prefix}_annotation_${id}` : undefined\n\n  /* Render tooltip with anchor, if given */\n  if (prefix) {\n    const anchor = prefix ? `#${prefix}` : undefined\n    return (\n      <aside class=\"md-annotation\" tabIndex={0}>\n        {renderTooltip(prefix)}\n        <a href={anchor} class=\"md-annotation__index\" tabIndex={-1}>\n          <span data-md-annotation-id={id}></span>\n        </a>\n      </aside>\n    )\n  } else {\n    return (\n      <aside class=\"md-annotation\" tabIndex={0}>\n        {renderTooltip(prefix)}\n        <span class=\"md-annotation__index\" tabIndex={-1}>\n          <span data-md-annotation-id={id}></span>\n        </span>\n      </aside>\n    )\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { translation } from \"~/_\"\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a 'copy-to-clipboard' button\n *\n * @param id - Unique identifier\n *\n * @returns Element\n */\nexport function renderClipboardButton(id: string): HTMLElement {\n  return (\n    <button\n      class=\"md-clipboard md-icon\"\n      title={translation(\"clipboard.copy\")}\n      data-clipboard-target={`#${id} > code`}\n    ></button>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { ComponentChild } from \"preact\"\n\nimport { configuration, feature, translation } from \"~/_\"\nimport {\n  SearchDocument,\n  SearchMetadata,\n  SearchResultItem\n} from \"~/integrations/search\"\nimport { h, truncate } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Render flag\n */\nconst enum Flag {\n  TEASER = 1,                          /* Render teaser */\n  PARENT = 2                           /* Render as parent */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper function\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a search document\n *\n * @param document - Search document\n * @param flag - Render flags\n *\n * @returns Element\n */\nfunction renderSearchDocument(\n  document: SearchDocument & SearchMetadata, flag: Flag\n): HTMLElement {\n  const parent = flag & Flag.PARENT\n  const teaser = flag & Flag.TEASER\n\n  /* Render missing query terms */\n  const missing = Object.keys(document.terms)\n    .filter(key => !document.terms[key])\n    .reduce<ComponentChild[]>((list, key) => [\n      ...list, <del>{key}</del>, \" \"\n    ], [])\n    .slice(0, -1)\n\n  /* Assemble query string for highlighting */\n  const url = new URL(document.location)\n  if (feature(\"search.highlight\"))\n    url.searchParams.set(\"h\", Object.entries(document.terms)\n      .filter(([, match]) => match)\n      .reduce((highlight, [value]) => `${highlight} ${value}`.trim(), \"\")\n    )\n\n  /* Render article or section, depending on flags */\n  const { tags } = configuration()\n  return (\n    <a href={`${url}`} class=\"md-search-result__link\" tabIndex={-1}>\n      <article\n        class={[\"md-search-result__article\", ...parent\n          ? [\"md-search-result__article--document\"]\n          : []\n        ].join(\" \")}\n        data-md-score={document.score.toFixed(2)}\n      >\n        {parent > 0 && <div class=\"md-search-result__icon md-icon\"></div>}\n        <h1 class=\"md-search-result__title\">{document.title}</h1>\n        {teaser > 0 && document.text.length > 0 &&\n          <p class=\"md-search-result__teaser\">\n            {truncate(document.text, 320)}\n          </p>\n        }\n        {document.tags && (\n          <div class=\"md-typeset\">\n            {document.tags.map(tag => {\n              const id = tag.replace(/<[^>]+>/g, \"\")\n              const type = tags\n                ? id in tags\n                  ? `md-tag-icon md-tag-icon--${tags[id]}`\n                  : \"md-tag-icon\"\n                : \"\"\n              return (\n                <span class={`md-tag ${type}`}>{tag}</span>\n              )\n            })}\n          </div>\n        )}\n        {teaser > 0 && missing.length > 0 &&\n          <p class=\"md-search-result__terms\">\n            {translation(\"search.result.term.missing\")}: {...missing}\n          </p>\n        }\n      </article>\n    </a>\n  )\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a search result\n *\n * @param result - Search result\n *\n * @returns Element\n */\nexport function renderSearchResultItem(\n  result: SearchResultItem\n): HTMLElement {\n  const threshold = result[0].score\n  const docs = [...result]\n\n  /* Find and extract parent article */\n  const parent = docs.findIndex(doc => !doc.location.includes(\"#\"))\n  const [article] = docs.splice(parent, 1)\n\n  /* Determine last index above threshold */\n  let index = docs.findIndex(doc => doc.score < threshold)\n  if (index === -1)\n    index = docs.length\n\n  /* Partition sections */\n  const best = docs.slice(0, index)\n  const more = docs.slice(index)\n\n  /* Render children */\n  const children = [\n    renderSearchDocument(article, Flag.PARENT | +(!parent && index === 0)),\n    ...best.map(section => renderSearchDocument(section, Flag.TEASER)),\n    ...more.length ? [\n      <details class=\"md-search-result__more\">\n        <summary tabIndex={-1}>\n          {more.length > 0 && more.length === 1\n            ? translation(\"search.result.more.one\")\n            : translation(\"search.result.more.other\", more.length)\n          }\n        </summary>\n        {...more.map(section => renderSearchDocument(section, Flag.TEASER))}\n      </details>\n    ] : []\n  ]\n\n  /* Render search result */\n  return (\n    <li class=\"md-search-result__item\">\n      {children}\n    </li>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { SourceFacts } from \"~/components\"\nimport { h, round } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render repository facts\n *\n * @param facts - Repository facts\n *\n * @returns Element\n */\nexport function renderSourceFacts(facts: SourceFacts): HTMLElement {\n  return (\n    <ul class=\"md-source__facts\">\n      {Object.entries(facts).map(([key, value]) => (\n        <li class={`md-source__fact md-source__fact--${key}`}>\n          {typeof value === \"number\" ? round(value) : value}\n        </li>\n      ))}\n    </ul>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Tabbed control type\n */\ntype TabbedControlType =\n  | \"prev\"\n  | \"next\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render control for content tabs\n *\n * @param type - Control type\n *\n * @returns Element\n */\nexport function renderTabbedControl(\n  type: TabbedControlType\n): HTMLElement {\n  const classes = `tabbed-control tabbed-control--${type}`\n  return (\n    <div class={classes} hidden>\n      <button class=\"tabbed-button\" tabIndex={-1}></button>\n    </div>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a table inside a wrapper to improve scrolling on mobile\n *\n * @param table - Table element\n *\n * @returns Element\n */\nexport function renderTable(table: HTMLElement): HTMLElement {\n  return (\n    <div class=\"md-typeset__scrollwrap\">\n      <div class=\"md-typeset__table\">\n        {table}\n      </div>\n    </div>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { configuration, translation } from \"~/_\"\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Version\n */\nexport interface Version {\n  version: string                      /* Version identifier */\n  title: string                        /* Version title */\n  aliases: string[]                    /* Version aliases */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a version\n *\n * @param version - Version\n *\n * @returns Element\n */\nfunction renderVersion(version: Version): HTMLElement {\n  const config = configuration()\n\n  /* Ensure trailing slash - see https://bit.ly/3rL5u3f */\n  const url = new URL(`../${version.version}/`, config.base)\n  return (\n    <li class=\"md-version__item\">\n      <a href={`${url}`} class=\"md-version__link\">\n        {version.title}\n      </a>\n    </li>\n  )\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a version selector\n *\n * @param versions - Versions\n * @param active - Active version\n *\n * @returns Element\n */\nexport function renderVersionSelector(\n  versions: Version[], active: Version\n): HTMLElement {\n  return (\n    <div class=\"md-version\">\n      <button\n        class=\"md-version__current\"\n        aria-label={translation(\"select.version.title\")}\n      >\n        {active.title}\n      </button>\n      <ul class=\"md-version__list\">\n        {versions.map(renderVersion)}\n      </ul>\n    </div>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  animationFrameScheduler,\n  auditTime,\n  combineLatest,\n  debounceTime,\n  defer,\n  delay,\n  filter,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  switchMap,\n  take,\n  takeLast,\n  takeUntil,\n  tap,\n  throttleTime,\n  withLatestFrom\n} from \"rxjs\"\n\nimport {\n  ElementOffset,\n  getActiveElement,\n  getElementSize,\n  watchElementContentOffset,\n  watchElementFocus,\n  watchElementOffset,\n  watchElementVisibility\n} from \"~/browser\"\n\nimport { Component } from \"../../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Annotation\n */\nexport interface Annotation {\n  active: boolean                      /* Annotation is active */\n  offset: ElementOffset                /* Annotation offset */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  target$: Observable<HTMLElement>     /* Location target observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch annotation\n *\n * @param el - Annotation element\n * @param container - Containing element\n *\n * @returns Annotation observable\n */\nexport function watchAnnotation(\n  el: HTMLElement, container: HTMLElement\n): Observable<Annotation> {\n  const offset$ = defer(() => combineLatest([\n    watchElementOffset(el),\n    watchElementContentOffset(container)\n  ]))\n    .pipe(\n      map(([{ x, y }, scroll]): ElementOffset => {\n        const { width, height } = getElementSize(el)\n        return ({\n          x: x - scroll.x + width / 2,\n          y: y - scroll.y + height / 2\n        })\n      })\n    )\n\n  /* Actively watch annotation on focus */\n  return watchElementFocus(el)\n    .pipe(\n      switchMap(active => offset$\n        .pipe(\n          map(offset => ({ active, offset })),\n          take(+!active || Infinity)\n        )\n      )\n    )\n}\n\n/**\n * Mount annotation\n *\n * @param el - Annotation element\n * @param container - Containing element\n * @param options - Options\n *\n * @returns Annotation component observable\n */\nexport function mountAnnotation(\n  el: HTMLElement, container: HTMLElement, { target$ }: MountOptions\n): Observable<Component<Annotation>> {\n  const [tooltip, index] = Array.from(el.children)\n\n  /* Mount component on subscription */\n  return defer(() => {\n    const push$ = new Subject<Annotation>()\n    const done$ = push$.pipe(takeLast(1))\n    push$.subscribe({\n\n      /* Handle emission */\n      next({ offset }) {\n        el.style.setProperty(\"--md-tooltip-x\", `${offset.x}px`)\n        el.style.setProperty(\"--md-tooltip-y\", `${offset.y}px`)\n      },\n\n      /* Handle complete */\n      complete() {\n        el.style.removeProperty(\"--md-tooltip-x\")\n        el.style.removeProperty(\"--md-tooltip-y\")\n      }\n    })\n\n    /* Start animation only when annotation is visible */\n    watchElementVisibility(el)\n      .pipe(\n        takeUntil(done$)\n      )\n        .subscribe(visible => {\n          el.toggleAttribute(\"data-md-visible\", visible)\n        })\n\n    /* Toggle tooltip presence to mitigate empty lines when copying */\n    merge(\n      push$.pipe(filter(({ active }) => active)),\n      push$.pipe(debounceTime(250), filter(({ active }) => !active))\n    )\n      .subscribe({\n\n        /* Handle emission */\n        next({ active }) {\n          if (active)\n            el.prepend(tooltip)\n          else\n            tooltip.remove()\n        },\n\n        /* Handle complete */\n        complete() {\n          el.prepend(tooltip)\n        }\n      })\n\n    /* Toggle tooltip visibility */\n    push$\n      .pipe(\n        auditTime(16, animationFrameScheduler)\n      )\n        .subscribe(({ active }) => {\n          tooltip.classList.toggle(\"md-tooltip--active\", active)\n        })\n\n    /* Track relative origin of tooltip */\n    push$\n      .pipe(\n        throttleTime(125, animationFrameScheduler),\n        filter(() => !!el.offsetParent),\n        map(() => el.offsetParent!.getBoundingClientRect()),\n        map(({ x }) => x)\n      )\n        .subscribe({\n\n          /* Handle emission */\n          next(origin) {\n            if (origin)\n              el.style.setProperty(\"--md-tooltip-0\", `${-origin}px`)\n            else\n              el.style.removeProperty(\"--md-tooltip-0\")\n          },\n\n          /* Handle complete */\n          complete() {\n            el.style.removeProperty(\"--md-tooltip-0\")\n          }\n        })\n\n    /* Allow to copy link without scrolling to anchor */\n    fromEvent<MouseEvent>(index, \"click\")\n      .pipe(\n        takeUntil(done$),\n        filter(ev => !(ev.metaKey || ev.ctrlKey))\n      )\n        .subscribe(ev => ev.preventDefault())\n\n    /* Allow to open link in new tab or blur on close */\n    fromEvent<MouseEvent>(index, \"mousedown\")\n      .pipe(\n        takeUntil(done$),\n        withLatestFrom(push$)\n      )\n        .subscribe(([ev, { active }]) => {\n\n          /* Open in new tab */\n          if (ev.button !== 0 || ev.metaKey || ev.ctrlKey) {\n            ev.preventDefault()\n\n          /* Close annotation */\n          } else if (active) {\n            ev.preventDefault()\n\n            /* Focus parent annotation, if any */\n            const parent = el.parentElement!.closest(\".md-annotation\")\n            if (parent instanceof HTMLElement)\n              parent.focus()\n            else\n              getActiveElement()?.blur()\n          }\n        })\n\n    /* Open and focus annotation on location target */\n    target$\n      .pipe(\n        takeUntil(done$),\n        filter(target => target === tooltip),\n        delay(125)\n      )\n        .subscribe(() => el.focus())\n\n    /* Create and return component */\n    return watchAnnotation(el, container)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  defer,\n  finalize,\n  merge,\n  share,\n  takeLast,\n  takeUntil\n} from \"rxjs\"\n\nimport {\n  getElement,\n  getElements,\n  getOptionalElement\n} from \"~/browser\"\nimport { renderAnnotation } from \"~/templates\"\n\nimport { Component } from \"../../../_\"\nimport {\n  Annotation,\n  mountAnnotation\n} from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  target$: Observable<HTMLElement>     /* Location target observable */\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Find all annotation markers in the given code block\n *\n * @param container - Containing element\n *\n * @returns Annotation markers\n */\nfunction findAnnotationMarkers(container: HTMLElement): Text[] {\n  const markers: Text[] = []\n  for (const el of getElements(\".c, .c1, .cm\", container)) {\n    const nodes: Text[] = []\n\n    /* Find all text nodes in current element */\n    const it = document.createNodeIterator(el, NodeFilter.SHOW_TEXT)\n    for (let node = it.nextNode(); node; node = it.nextNode())\n      nodes.push(node as Text)\n\n    /* Find all markers in each text node */\n    for (let text of nodes) {\n      let match: RegExpExecArray | null\n\n      /* Split text at marker and add to list */\n      while ((match = /(\\(\\d+\\))(!)?/.exec(text.textContent!))) {\n        const [, id, force] = match\n        if (typeof force === \"undefined\") {\n          const marker = text.splitText(match.index)\n          text = marker.splitText(id.length)\n          markers.push(marker)\n\n        /* Replace entire text with marker */\n        } else {\n          text.textContent = id\n          markers.push(text)\n          break\n        }\n      }\n    }\n  }\n  return markers\n}\n\n/**\n * Swap the child nodes of two elements\n *\n * @param source - Source element\n * @param target - Target element\n */\nfunction swap(source: HTMLElement, target: HTMLElement): void {\n  target.append(...Array.from(source.childNodes))\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount annotation list\n *\n * This function analyzes the containing code block and checks for markers\n * referring to elements in the given annotation list. If no markers are found,\n * the list is left untouched. Otherwise, list elements are rendered as\n * annotations inside the code block.\n *\n * @param el - Annotation list element\n * @param container - Containing element\n * @param options - Options\n *\n * @returns Annotation component observable\n */\nexport function mountAnnotationList(\n  el: HTMLElement, container: HTMLElement, { target$, print$ }: MountOptions\n): Observable<Component<Annotation>> {\n\n  /* Compute prefix for tooltip anchors */\n  const parent = container.closest(\"[id]\")\n  const prefix = parent?.id\n\n  /* Find and replace all markers with empty annotations */\n  const annotations = new Map<string, HTMLElement>()\n  for (const marker of findAnnotationMarkers(container)) {\n    const [, id] = marker.textContent!.match(/\\((\\d+)\\)/)!\n    if (getOptionalElement(`li:nth-child(${id})`, el)) {\n      annotations.set(id, renderAnnotation(id, prefix))\n      marker.replaceWith(annotations.get(id)!)\n    }\n  }\n\n  /* Keep list if there are no annotations to render */\n  if (annotations.size === 0)\n    return EMPTY\n\n  /* Mount component on subscription */\n  return defer(() => {\n    const done$ = new Subject()\n\n    /* Retrieve container pairs for swapping */\n    const pairs: [HTMLElement, HTMLElement][] = []\n    for (const [id, annotation] of annotations)\n      pairs.push([\n        getElement(\".md-typeset\", annotation),\n        getElement(`li:nth-child(${id})`, el)\n      ])\n\n    /* Handle print mode - see https://bit.ly/3rgPdpt */\n    print$\n      .pipe(\n        takeUntil(done$.pipe(takeLast(1)))\n      )\n        .subscribe(active => {\n          el.hidden = !active\n\n          /* Show annotations in code block or list (print) */\n          for (const [inner, child] of pairs)\n            if (!active)\n              swap(child, inner)\n            else\n              swap(inner, child)\n        })\n\n    /* Create and return component */\n    return merge(...[...annotations]\n      .map(([, annotation]) => (\n        mountAnnotation(annotation, container, { target$ })\n      ))\n    )\n      .pipe(\n        finalize(() => done$.complete()),\n        share()\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  map,\n  of,\n  shareReplay,\n  tap\n} from \"rxjs\"\n\nimport { watchScript } from \"~/browser\"\nimport { h } from \"~/utilities\"\n\nimport { Component } from \"../../../_\"\n\nimport themeCSS from \"./index.css\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mermaid diagram\n */\nexport interface Mermaid {}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Mermaid instance observable\n */\nlet mermaid$: Observable<void>\n\n/**\n * Global sequence number for diagrams\n */\nlet sequence = 0\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch Mermaid script\n *\n * @returns Mermaid scripts observable\n */\nfunction fetchScripts(): Observable<void> {\n  return typeof mermaid === \"undefined\" || mermaid instanceof Element\n    ? watchScript(\"https://unpkg.com/mermaid@9.1.7/dist/mermaid.min.js\")\n    : of(undefined)\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount Mermaid diagram\n *\n * @param el - Code block element\n *\n * @returns Mermaid diagram component observable\n */\nexport function mountMermaid(\n  el: HTMLElement\n): Observable<Component<Mermaid>> {\n  el.classList.remove(\"mermaid\") // Hack: mitigate https://bit.ly/3CiN6Du\n  mermaid$ ||= fetchScripts()\n    .pipe(\n      tap(() => mermaid.initialize({\n        startOnLoad: false,\n        themeCSS,\n        sequence: {\n          actorFontSize: \"16px\", // Hack: mitigate https://bit.ly/3y0NEi3\n          messageFontSize: \"16px\",\n          noteFontSize: \"16px\"\n        }\n      })),\n      map(() => undefined),\n      shareReplay(1)\n    )\n\n  /* Render diagram */\n  mermaid$.subscribe(() => {\n    el.classList.add(\"mermaid\") // Hack: mitigate https://bit.ly/3CiN6Du\n    const id = `__mermaid_${sequence++}`\n    const host = h(\"div\", { class: \"mermaid\" })\n    mermaid.mermaidAPI.render(id, el.textContent, (svg: string) => {\n\n      /* Create a shadow root and inject diagram */\n      const shadow = host.attachShadow({ mode: \"closed\" })\n      shadow.innerHTML = svg\n\n      /* Replace code block with diagram */\n      el.replaceWith(host)\n    })\n  })\n\n  /* Create and return component */\n  return mermaid$\n    .pipe(\n      map(() => ({ ref: el }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  defer,\n  filter,\n  finalize,\n  map,\n  merge,\n  tap\n} from \"rxjs\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Details\n */\nexport interface Details {\n  action: \"open\" | \"close\"             /* Details state */\n  reveal?: boolean                     /* Details is revealed */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  target$: Observable<HTMLElement>     /* Location target observable */\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  target$: Observable<HTMLElement>     /* Location target observable */\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch details\n *\n * @param el - Details element\n * @param options - Options\n *\n * @returns Details observable\n */\nexport function watchDetails(\n  el: HTMLDetailsElement, { target$, print$ }: WatchOptions\n): Observable<Details> {\n  let open = true\n  return merge(\n\n    /* Open and focus details on location target */\n    target$\n      .pipe(\n        map(target => target.closest(\"details:not([open])\")!),\n        filter(details => el === details),\n        map(() => ({\n          action: \"open\", reveal: true\n        }) as Details)\n      ),\n\n    /* Open details on print and close afterwards */\n    print$\n      .pipe(\n        filter(active => active || !open),\n        tap(() => open = el.open),\n        map(active => ({\n          action: active ? \"open\" : \"close\"\n        }) as Details)\n      )\n  )\n}\n\n/**\n * Mount details\n *\n * This function ensures that `details` tags are opened on anchor jumps and\n * prior to printing, so the whole content of the page is visible.\n *\n * @param el - Details element\n * @param options - Options\n *\n * @returns Details component observable\n */\nexport function mountDetails(\n  el: HTMLDetailsElement, options: MountOptions\n): Observable<Component<Details>> {\n  return defer(() => {\n    const push$ = new Subject<Details>()\n    push$.subscribe(({ action, reveal }) => {\n      el.toggleAttribute(\"open\", action === \"open\")\n      if (reveal)\n        el.scrollIntoView()\n    })\n\n    /* Create and return component */\n    return watchDetails(el, options)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { Observable, of } from \"rxjs\"\n\nimport { renderTable } from \"~/templates\"\nimport { h } from \"~/utilities\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Data table\n */\nexport interface DataTable {}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Sentinel for replacement\n */\nconst sentinel = h(\"table\")\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount data table\n *\n * This function wraps a data table in another scrollable container, so it can\n * be smoothly scrolled on smaller screen sizes and won't break the layout.\n *\n * @param el - Data table element\n *\n * @returns Data table component observable\n */\nexport function mountDataTable(\n  el: HTMLElement\n): Observable<Component<DataTable>> {\n  el.replaceWith(sentinel)\n  sentinel.replaceWith(renderTable(el))\n\n  /* Create and return component */\n  return of({ ref: el })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  animationFrameScheduler,\n  asyncScheduler,\n  auditTime,\n  combineLatest,\n  defer,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  skip,\n  startWith,\n  subscribeOn,\n  takeLast,\n  takeUntil,\n  tap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  Viewport,\n  getElement,\n  getElementContentOffset,\n  getElementContentSize,\n  getElementOffset,\n  getElementSize,\n  getElements,\n  watchElementContentOffset,\n  watchElementSize\n} from \"~/browser\"\nimport { renderTabbedControl } from \"~/templates\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Content tabs\n */\nexport interface ContentTabs {\n  active: HTMLLabelElement             /* Active tab label */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch content tabs\n *\n * @param el - Content tabs element\n *\n * @returns Content tabs observable\n */\nexport function watchContentTabs(\n  el: HTMLElement\n): Observable<ContentTabs> {\n  const inputs = getElements<HTMLInputElement>(\":scope > input\", el)\n  const initial = inputs.find(input => input.checked) || inputs[0]\n  return merge(...inputs.map(input => fromEvent(input, \"change\")\n    .pipe(\n      map(() => getElement<HTMLLabelElement>(`label[for=\"${input.id}\"]`))\n    )\n  ))\n    .pipe(\n      startWith(getElement<HTMLLabelElement>(`label[for=\"${initial.id}\"]`)),\n      map(active => ({ active }))\n    )\n}\n\n/**\n * Mount content tabs\n *\n * This function scrolls the active tab into view. While this functionality is\n * provided by browsers as part of `scrollInfoView`, browsers will always also\n * scroll the vertical axis, which we do not want. Thus, we decided to provide\n * this functionality ourselves.\n *\n * @param el - Content tabs element\n * @param options - Options\n *\n * @returns Content tabs component observable\n */\nexport function mountContentTabs(\n  el: HTMLElement, { viewport$ }: MountOptions\n): Observable<Component<ContentTabs>> {\n\n  /* Render content tab previous button for pagination */\n  const prev = renderTabbedControl(\"prev\")\n  el.append(prev)\n\n  /* Render content tab next button for pagination */\n  const next = renderTabbedControl(\"next\")\n  el.append(next)\n\n  /* Mount component on subscription */\n  const container = getElement(\".tabbed-labels\", el)\n  return defer(() => {\n    const push$ = new Subject<ContentTabs>()\n    const done$ = push$.pipe(takeLast(1))\n    combineLatest([push$, watchElementSize(el)])\n      .pipe(\n        auditTime(1, animationFrameScheduler),\n        takeUntil(done$)\n      )\n        .subscribe({\n\n          /* Handle emission */\n          next([{ active }, size]) {\n            const offset = getElementOffset(active)\n            const { width } = getElementSize(active)\n\n            /* Set tab indicator offset and width */\n            el.style.setProperty(\"--md-indicator-x\", `${offset.x}px`)\n            el.style.setProperty(\"--md-indicator-width\", `${width}px`)\n\n            /* Scroll container to active content tab */\n            const content = getElementContentOffset(container)\n            if (\n              offset.x         < content.x              ||\n              offset.x + width > content.x + size.width\n            )\n              container.scrollTo({\n                left: Math.max(0, offset.x - 16),\n                behavior: \"smooth\"\n              })\n          },\n\n          /* Handle complete */\n          complete() {\n            el.style.removeProperty(\"--md-indicator-x\")\n            el.style.removeProperty(\"--md-indicator-width\")\n          }\n        })\n\n    /* Hide content tab buttons on borders */\n    combineLatest([\n      watchElementContentOffset(container),\n      watchElementSize(container)\n    ])\n      .pipe(\n        takeUntil(done$)\n      )\n        .subscribe(([offset, size]) => {\n          const content = getElementContentSize(container)\n          prev.hidden = offset.x < 16\n          next.hidden = offset.x > content.width - size.width - 16\n        })\n\n    /* Paginate content tab container on click */\n    merge(\n      fromEvent(prev, \"click\").pipe(map(() => -1)),\n      fromEvent(next, \"click\").pipe(map(() => +1))\n    )\n      .pipe(\n        takeUntil(done$)\n      )\n        .subscribe(direction => {\n          const { width } = getElementSize(container)\n          container.scrollBy({\n            left: width * direction,\n            behavior: \"smooth\"\n          })\n        })\n\n    /* Set up linking of content tabs, if enabled */\n    if (feature(\"content.tabs.link\"))\n      push$.pipe(\n        skip(1),\n        withLatestFrom(viewport$)\n      )\n        .subscribe(([{ active }, { offset }]) => {\n          const tab = active.innerText.trim()\n          if (active.hasAttribute(\"data-md-switching\")) {\n            active.removeAttribute(\"data-md-switching\")\n\n          /* Determine viewport offset of active tab */\n          } else {\n            const y = el.offsetTop - offset.y\n\n            /* Passively activate other tabs */\n            for (const set of getElements(\"[data-tabs]\"))\n              for (const input of getElements<HTMLInputElement>(\n                \":scope > input\", set\n              )) {\n                const label = getElement(`label[for=\"${input.id}\"]`)\n                if (\n                  label !== active &&\n                  label.innerText.trim() === tab\n                ) {\n                  label.setAttribute(\"data-md-switching\", \"\")\n                  input.click()\n                  break\n                }\n              }\n\n            /* Bring active tab into view */\n            window.scrollTo({\n              top: el.offsetTop - y\n            })\n\n            /* Persist active tabs in local storage */\n            const tabs = __md_get<string[]>(\"__tabs\") || []\n            __md_set(\"__tabs\", [...new Set([tab, ...tabs])])\n          }\n        })\n\n    /* Create and return component */\n    return watchContentTabs(el)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n    .pipe(\n      subscribeOn(asyncScheduler)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { Observable, merge } from \"rxjs\"\n\nimport { Viewport, getElements } from \"~/browser\"\n\nimport { Component } from \"../../_\"\nimport { Annotation } from \"../annotation\"\nimport {\n  CodeBlock,\n  Mermaid,\n  mountCodeBlock,\n  mountMermaid\n} from \"../code\"\nimport {\n  Details,\n  mountDetails\n} from \"../details\"\nimport {\n  DataTable,\n  mountDataTable\n} from \"../table\"\nimport {\n  ContentTabs,\n  mountContentTabs\n} from \"../tabs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Content\n */\nexport type Content =\n  | Annotation\n  | ContentTabs\n  | CodeBlock\n  | Mermaid\n  | DataTable\n  | Details\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  target$: Observable<HTMLElement>     /* Location target observable */\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount content\n *\n * This function mounts all components that are found in the content of the\n * actual article, including code blocks, data tables and details.\n *\n * @param el - Content element\n * @param options - Options\n *\n * @returns Content component observable\n */\nexport function mountContent(\n  el: HTMLElement, { viewport$, target$, print$ }: MountOptions\n): Observable<Component<Content>> {\n  return merge(\n\n    /* Code blocks */\n    ...getElements(\"pre:not(.mermaid) > code\", el)\n      .map(child => mountCodeBlock(child, { target$, print$ })),\n\n    /* Mermaid diagrams */\n    ...getElements(\"pre.mermaid\", el)\n      .map(child => mountMermaid(child)),\n\n    /* Data tables */\n    ...getElements(\"table:not([class])\", el)\n      .map(child => mountDataTable(child)),\n\n    /* Details */\n    ...getElements(\"details\", el)\n      .map(child => mountDetails(child, { target$, print$ })),\n\n    /* Content tabs */\n    ...getElements(\"[data-tabs]\", el)\n      .map(child => mountContentTabs(child, { viewport$ }))\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  defer,\n  delay,\n  finalize,\n  map,\n  merge,\n  of,\n  switchMap,\n  tap\n} from \"rxjs\"\n\nimport { getElement } from \"~/browser\"\n\nimport { Component } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Dialog\n */\nexport interface Dialog {\n  message: string                      /* Dialog message */\n  active: boolean                      /* Dialog is active */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  alert$: Subject<string>              /* Alert subject */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  alert$: Subject<string>              /* Alert subject */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch dialog\n *\n * @param _el - Dialog element\n * @param options - Options\n *\n * @returns Dialog observable\n */\nexport function watchDialog(\n  _el: HTMLElement, { alert$ }: WatchOptions\n): Observable<Dialog> {\n  return alert$\n    .pipe(\n      switchMap(message => merge(\n        of(true),\n        of(false).pipe(delay(2000))\n      )\n        .pipe(\n          map(active => ({ message, active }))\n        )\n      )\n    )\n}\n\n/**\n * Mount dialog\n *\n * This function reveals the dialog in the right corner when a new alert is\n * emitted through the subject that is passed as part of the options.\n *\n * @param el - Dialog element\n * @param options - Options\n *\n * @returns Dialog component observable\n */\nexport function mountDialog(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<Dialog>> {\n  const inner = getElement(\".md-typeset\", el)\n  return defer(() => {\n    const push$ = new Subject<Dialog>()\n    push$.subscribe(({ message, active }) => {\n      el.classList.toggle(\"md-dialog--active\", active)\n      inner.textContent = message\n    })\n\n    /* Create and return component */\n    return watchDialog(el, options)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  bufferCount,\n  combineLatest,\n  combineLatestWith,\n  defer,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  map,\n  of,\n  shareReplay,\n  startWith,\n  switchMap,\n  takeLast,\n  takeUntil\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  Viewport,\n  watchElementSize,\n  watchToggle\n} from \"~/browser\"\n\nimport { Component } from \"../../_\"\nimport { Main } from \"../../main\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Header\n */\nexport interface Header {\n  height: number                       /* Header visible height */\n  hidden: boolean                      /* Header is hidden */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n  main$: Observable<Main>              /* Main area observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Compute whether the header is hidden\n *\n * If the user scrolls past a certain threshold, the header can be hidden when\n * scrolling down, and shown when scrolling up.\n *\n * @param options - Options\n *\n * @returns Toggle observable\n */\nfunction isHidden({ viewport$ }: WatchOptions): Observable<boolean> {\n  if (!feature(\"header.autohide\"))\n    return of(false)\n\n  /* Compute direction and turning point */\n  const direction$ = viewport$\n    .pipe(\n      map(({ offset: { y } }) => y),\n      bufferCount(2, 1),\n      map(([a, b]) => [a < b, b] as const),\n      distinctUntilKeyChanged(0)\n    )\n\n  /* Compute whether header should be hidden */\n  const hidden$ = combineLatest([viewport$, direction$])\n    .pipe(\n      filter(([{ offset }, [, y]]) => Math.abs(y - offset.y) > 100),\n      map(([, [direction]]) => direction),\n      distinctUntilChanged()\n    )\n\n  /* Compute threshold for hiding */\n  const search$ = watchToggle(\"search\")\n  return combineLatest([viewport$, search$])\n    .pipe(\n      map(([{ offset }, search]) => offset.y > 400 && !search),\n      distinctUntilChanged(),\n      switchMap(active => active ? hidden$ : of(false)),\n      startWith(false)\n    )\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch header\n *\n * @param el - Header element\n * @param options - Options\n *\n * @returns Header observable\n */\nexport function watchHeader(\n  el: HTMLElement, options: WatchOptions\n): Observable<Header> {\n  return defer(() => combineLatest([\n    watchElementSize(el),\n    isHidden(options)\n  ]))\n    .pipe(\n      map(([{ height }, hidden]) => ({\n        height,\n        hidden\n      })),\n      distinctUntilChanged((a, b) => (\n        a.height === b.height &&\n        a.hidden === b.hidden\n      )),\n      shareReplay(1)\n    )\n}\n\n/**\n * Mount header\n *\n * This function manages the different states of the header, i.e. whether it's\n * hidden or rendered with a shadow. This depends heavily on the main area.\n *\n * @param el - Header element\n * @param options - Options\n *\n * @returns Header component observable\n */\nexport function mountHeader(\n  el: HTMLElement, { header$, main$ }: MountOptions\n): Observable<Component<Header>> {\n  return defer(() => {\n    const push$ = new Subject<Main>()\n    const done$ = push$.pipe(takeLast(1))\n    push$\n      .pipe(\n        distinctUntilKeyChanged(\"active\"),\n        combineLatestWith(header$)\n      )\n        .subscribe(([{ active }, { hidden }]) => {\n          el.classList.toggle(\"md-header--shadow\", active && !hidden)\n          el.hidden = hidden\n        })\n\n    /* Link to main area */\n    main$.subscribe(push$)\n\n    /* Create and return component */\n    return header$\n      .pipe(\n        takeUntil(done$),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  defer,\n  distinctUntilKeyChanged,\n  finalize,\n  map,\n  tap\n} from \"rxjs\"\n\nimport {\n  Viewport,\n  getElementSize,\n  getOptionalElement,\n  watchViewportAt\n} from \"~/browser\"\n\nimport { Component } from \"../../_\"\nimport { Header } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Header\n */\nexport interface HeaderTitle {\n  active: boolean                      /* Header title is active */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch header title\n *\n * @param el - Heading element\n * @param options - Options\n *\n * @returns Header title observable\n */\nexport function watchHeaderTitle(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<HeaderTitle> {\n  return watchViewportAt(el, { viewport$, header$ })\n    .pipe(\n      map(({ offset: { y } }) => {\n        const { height } = getElementSize(el)\n        return {\n          active: y >= height\n        }\n      }),\n      distinctUntilKeyChanged(\"active\")\n    )\n}\n\n/**\n * Mount header title\n *\n * This function swaps the header title from the site title to the title of the\n * current page when the user scrolls past the first headline.\n *\n * @param el - Header title element\n * @param options - Options\n *\n * @returns Header title component observable\n */\nexport function mountHeaderTitle(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<HeaderTitle>> {\n  return defer(() => {\n    const push$ = new Subject<HeaderTitle>()\n    push$.subscribe(({ active }) => {\n      el.classList.toggle(\"md-header__title--active\", active)\n    })\n\n    /* Obtain headline, if any */\n    const heading = getOptionalElement(\"article h1\")\n    if (typeof heading === \"undefined\")\n      return EMPTY\n\n    /* Create and return component */\n    return watchHeaderTitle(heading, options)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  combineLatest,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  map,\n  switchMap\n} from \"rxjs\"\n\nimport {\n  Viewport,\n  watchElementSize\n} from \"~/browser\"\n\nimport { Header } from \"../header\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Main area\n */\nexport interface Main {\n  offset: number                       /* Main area top offset */\n  height: number                       /* Main area visible height */\n  active: boolean                      /* Main area is active */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch main area\n *\n * This function returns an observable that computes the visual parameters of\n * the main area which depends on the viewport vertical offset and height, as\n * well as the height of the header element, if the header is fixed.\n *\n * @param el - Main area element\n * @param options - Options\n *\n * @returns Main area observable\n */\nexport function watchMain(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<Main> {\n\n  /* Compute necessary adjustment for header */\n  const adjust$ = header$\n    .pipe(\n      map(({ height }) => height),\n      distinctUntilChanged()\n    )\n\n  /* Compute the main area's top and bottom borders */\n  const border$ = adjust$\n    .pipe(\n      switchMap(() => watchElementSize(el)\n        .pipe(\n          map(({ height }) => ({\n            top:    el.offsetTop,\n            bottom: el.offsetTop + height\n          })),\n          distinctUntilKeyChanged(\"bottom\")\n        )\n      )\n    )\n\n  /* Compute the main area's offset, visible height and if we scrolled past */\n  return combineLatest([adjust$, border$, viewport$])\n    .pipe(\n      map(([header, { top, bottom }, { offset: { y }, size: { height } }]) => {\n        height = Math.max(0, height\n          - Math.max(0, top    - y,  header)\n          - Math.max(0, height + y - bottom)\n        )\n        return {\n          offset: top - header,\n          height,\n          active: top - header <= y\n        }\n      }),\n      distinctUntilChanged((a, b) => (\n        a.offset === b.offset &&\n        a.height === b.height &&\n        a.active === b.active\n      ))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  asyncScheduler,\n  defer,\n  finalize,\n  fromEvent,\n  map,\n  mergeMap,\n  observeOn,\n  of,\n  shareReplay,\n  startWith,\n  tap\n} from \"rxjs\"\n\nimport { getElements } from \"~/browser\"\n\nimport { Component } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Palette colors\n */\nexport interface PaletteColor {\n  scheme?: string                      /* Color scheme */\n  primary?: string                     /* Primary color */\n  accent?: string                      /* Accent color */\n}\n\n/**\n * Palette\n */\nexport interface Palette {\n  index: number                        /* Palette index */\n  color: PaletteColor                  /* Palette colors */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch color palette\n *\n * @param inputs - Color palette element\n *\n * @returns Color palette observable\n */\nexport function watchPalette(\n  inputs: HTMLInputElement[]\n): Observable<Palette> {\n  const current = __md_get<Palette>(\"__palette\") || {\n    index: inputs.findIndex(input => matchMedia(\n      input.getAttribute(\"data-md-color-media\")!\n    ).matches)\n  }\n\n  /* Emit changes in color palette */\n  return of(...inputs)\n    .pipe(\n      mergeMap(input => fromEvent(input, \"change\")\n        .pipe(\n          map(() => input)\n        )\n      ),\n      startWith(inputs[Math.max(0, current.index)]),\n      map(input => ({\n        index: inputs.indexOf(input),\n        color: {\n          scheme:  input.getAttribute(\"data-md-color-scheme\"),\n          primary: input.getAttribute(\"data-md-color-primary\"),\n          accent:  input.getAttribute(\"data-md-color-accent\")\n        }\n      } as Palette)),\n      shareReplay(1)\n    )\n}\n\n/**\n * Mount color palette\n *\n * @param el - Color palette element\n *\n * @returns Color palette component observable\n */\nexport function mountPalette(\n  el: HTMLElement\n): Observable<Component<Palette>> {\n  return defer(() => {\n    const push$ = new Subject<Palette>()\n    push$.subscribe(palette => {\n      document.body.setAttribute(\"data-md-color-switching\", \"\")\n\n      /* Set color palette */\n      for (const [key, value] of Object.entries(palette.color))\n        document.body.setAttribute(`data-md-color-${key}`, value)\n\n      /* Toggle visibility */\n      for (let index = 0; index < inputs.length; index++) {\n        const label = inputs[index].nextElementSibling\n        if (label instanceof HTMLElement)\n          label.hidden = palette.index !== index\n      }\n\n      /* Persist preference in local storage */\n      __md_set(\"__palette\", palette)\n    })\n\n    /* Revert transition durations after color switch */\n    push$.pipe(observeOn(asyncScheduler))\n      .subscribe(() => {\n        document.body.removeAttribute(\"data-md-color-switching\")\n      })\n\n    /* Create and return component */\n    const inputs = getElements<HTMLInputElement>(\"input\", el)\n    return watchPalette(inputs)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport ClipboardJS from \"clipboard\"\nimport {\n  Observable,\n  Subject,\n  map,\n  tap\n} from \"rxjs\"\n\nimport { translation } from \"~/_\"\nimport { getElement } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Setup options\n */\ninterface SetupOptions {\n  alert$: Subject<string>              /* Alert subject */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Extract text to copy\n *\n * @param el - HTML element\n *\n * @returns Extracted text\n */\nfunction extract(el: HTMLElement): string {\n  el.setAttribute(\"data-md-copying\", \"\")\n  const text = el.innerText\n  el.removeAttribute(\"data-md-copying\")\n  return text\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up Clipboard.js integration\n *\n * @param options - Options\n */\nexport function setupClipboardJS(\n  { alert$ }: SetupOptions\n): void {\n  if (ClipboardJS.isSupported()) {\n    new Observable<ClipboardJS.Event>(subscriber => {\n      new ClipboardJS(\"[data-clipboard-target], [data-clipboard-text]\", {\n        text: el => (\n          el.getAttribute(\"data-clipboard-text\")! ||\n          extract(getElement(\n            el.getAttribute(\"data-clipboard-target\")!\n          ))\n        )\n      })\n        .on(\"success\", ev => subscriber.next(ev))\n    })\n      .pipe(\n        tap(ev => {\n          const trigger = ev.trigger as HTMLElement\n          trigger.focus()\n        }),\n        map(() => translation(\"clipboard.copied\"))\n      )\n        .subscribe(alert$)\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  catchError,\n  defaultIfEmpty,\n  map,\n  of,\n  tap\n} from \"rxjs\"\n\nimport { configuration } from \"~/_\"\nimport { getElements, requestXML } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Sitemap, i.e. a list of URLs\n */\nexport type Sitemap = string[]\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Preprocess a list of URLs\n *\n * This function replaces the `site_url` in the sitemap with the actual base\n * URL, to allow instant loading to work in occasions like Netlify previews.\n *\n * @param urls - URLs\n *\n * @returns URL path parts\n */\nfunction preprocess(urls: Sitemap): Sitemap {\n  if (urls.length < 2)\n    return [\"\"]\n\n  /* Take the first two URLs and remove everything after the last slash */\n  const [root, next] = [...urls]\n    .sort((a, b) => a.length - b.length)\n    .map(url => url.replace(/[^/]+$/, \"\"))\n\n  /* Compute common prefix */\n  let index = 0\n  if (root === next)\n    index = root.length\n  else\n    while (root.charCodeAt(index) === next.charCodeAt(index))\n      index++\n\n  /* Remove common prefix and return in original order */\n  return urls.map(url => url.replace(root.slice(0, index), \"\"))\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch the sitemap for the given base URL\n *\n * @param base - Base URL\n *\n * @returns Sitemap observable\n */\nexport function fetchSitemap(base?: URL): Observable<Sitemap> {\n  const cached = __md_get<Sitemap>(\"__sitemap\", sessionStorage, base)\n  if (cached) {\n    return of(cached)\n  } else {\n    const config = configuration()\n    return requestXML(new URL(\"sitemap.xml\", base || config.base))\n      .pipe(\n        map(sitemap => preprocess(getElements(\"loc\", sitemap)\n          .map(node => node.textContent!)\n        )),\n        catchError(() => EMPTY), // @todo refactor instant loading\n        defaultIfEmpty([]),\n        tap(sitemap => __md_set(\"__sitemap\", sitemap, sessionStorage, base))\n      )\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  NEVER,\n  Observable,\n  Subject,\n  bufferCount,\n  catchError,\n  concatMap,\n  debounceTime,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  fromEvent,\n  map,\n  merge,\n  of,\n  sample,\n  share,\n  skip,\n  skipUntil,\n  switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"~/_\"\nimport {\n  Viewport,\n  ViewportOffset,\n  getElements,\n  getOptionalElement,\n  request,\n  setLocation,\n  setLocationHash\n} from \"~/browser\"\nimport { getComponentElement } from \"~/components\"\nimport { h } from \"~/utilities\"\n\nimport { fetchSitemap } from \"../sitemap\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * History state\n */\nexport interface HistoryState {\n  url: URL                             /* State URL */\n  offset?: ViewportOffset              /* State viewport offset */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Setup options\n */\ninterface SetupOptions {\n  document$: Subject<Document>         /* Document subject */\n  location$: Subject<URL>              /* Location subject */\n  viewport$: Observable<Viewport>      /* Viewport observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up instant loading\n *\n * When fetching, theoretically, we could use `responseType: \"document\"`, but\n * since all MkDocs links are relative, we need to make sure that the current\n * location matches the document we just loaded. Otherwise any relative links\n * in the document could use the old location.\n *\n * This is the reason why we need to synchronize history events and the process\n * of fetching the document for navigation changes (except `popstate` events):\n *\n * 1. Fetch document via `XMLHTTPRequest`\n * 2. Set new location via `history.pushState`\n * 3. Parse and emit fetched document\n *\n * For `popstate` events, we must not use `history.pushState`, or the forward\n * history will be irreversibly overwritten. In case the request fails, the\n * location change is dispatched regularly.\n *\n * @param options - Options\n */\nexport function setupInstantLoading(\n  { document$, location$, viewport$ }: SetupOptions\n): void {\n  const config = configuration()\n  if (location.protocol === \"file:\")\n    return\n\n  /* Disable automatic scroll restoration */\n  if (\"scrollRestoration\" in history) {\n    history.scrollRestoration = \"manual\"\n\n    /* Hack: ensure that reloads restore viewport offset */\n    fromEvent(window, \"beforeunload\")\n      .subscribe(() => {\n        history.scrollRestoration = \"auto\"\n      })\n  }\n\n  /* Hack: ensure absolute favicon link to omit 404s when switching */\n  const favicon = getOptionalElement<HTMLLinkElement>(\"link[rel=icon]\")\n  if (typeof favicon !== \"undefined\")\n    favicon.href = favicon.href\n\n  /* Intercept internal navigation */\n  const push$ = fetchSitemap()\n    .pipe(\n      map(paths => paths.map(path => `${new URL(path, config.base)}`)),\n      switchMap(urls => fromEvent<MouseEvent>(document.body, \"click\")\n        .pipe(\n          filter(ev => !ev.metaKey && !ev.ctrlKey),\n          switchMap(ev => {\n            if (ev.target instanceof Element) {\n              const el = ev.target.closest(\"a\")\n              if (el && !el.target) {\n                const url = new URL(el.href)\n\n                /* Canonicalize URL */\n                url.search = \"\"\n                url.hash = \"\"\n\n                /* Check if URL should be intercepted */\n                if (\n                  url.pathname !== location.pathname &&\n                  urls.includes(url.toString())\n                ) {\n                  ev.preventDefault()\n                  return of({\n                    url: new URL(el.href)\n                  })\n                }\n              }\n            }\n            return NEVER\n          })\n        )\n      ),\n      share<HistoryState>()\n    )\n\n  /* Intercept history back and forward */\n  const pop$ = fromEvent<PopStateEvent>(window, \"popstate\")\n    .pipe(\n      filter(ev => ev.state !== null),\n      map(ev => ({\n        url: new URL(location.href),\n        offset: ev.state\n      })),\n      share<HistoryState>()\n    )\n\n  /* Emit location change */\n  merge(push$, pop$)\n    .pipe(\n      distinctUntilChanged((a, b) => a.url.href === b.url.href),\n      map(({ url }) => url)\n    )\n      .subscribe(location$)\n\n  /* Fetch document via `XMLHTTPRequest` */\n  const response$ = location$\n    .pipe(\n      distinctUntilKeyChanged(\"pathname\"),\n      switchMap(url => request(url.href)\n        .pipe(\n          catchError(() => {\n            setLocation(url)\n            return NEVER\n          })\n        )\n      ),\n      share()\n    )\n\n  /* Set new location via `history.pushState` */\n  push$\n    .pipe(\n      sample(response$)\n    )\n      .subscribe(({ url }) => {\n        history.pushState({}, \"\", `${url}`)\n      })\n\n  /* Parse and emit fetched document */\n  const dom = new DOMParser()\n  response$\n    .pipe(\n      switchMap(res => res.text()),\n      map(res => dom.parseFromString(res, \"text/html\"))\n    )\n      .subscribe(document$)\n\n  /* Replace meta tags and components */\n  document$\n    .pipe(\n      skip(1)\n    )\n      .subscribe(replacement => {\n        for (const selector of [\n\n          /* Meta tags */\n          \"title\",\n          \"link[rel=canonical]\",\n          \"meta[name=author]\",\n          \"meta[name=description]\",\n\n          /* Components */\n          \"[data-md-component=announce]\",\n          \"[data-md-component=container]\",\n          \"[data-md-component=header-topic]\",\n          \"[data-md-component=outdated]\",\n          \"[data-md-component=logo]\",\n          \"[data-md-component=skip]\",\n          ...feature(\"navigation.tabs.sticky\")\n            ? [\"[data-md-component=tabs]\"]\n            : []\n        ]) {\n          const source = getOptionalElement(selector)\n          const target = getOptionalElement(selector, replacement)\n          if (\n            typeof source !== \"undefined\" &&\n            typeof target !== \"undefined\"\n          ) {\n            source.replaceWith(target)\n          }\n        }\n      })\n\n  /* Re-evaluate scripts */\n  document$\n    .pipe(\n      skip(1),\n      map(() => getComponentElement(\"container\")),\n      switchMap(el => getElements(\"script\", el)),\n      concatMap(el => {\n        const script = h(\"script\")\n        if (el.src) {\n          for (const name of el.getAttributeNames())\n            script.setAttribute(name, el.getAttribute(name)!)\n          el.replaceWith(script)\n\n          /* Complete when script is loaded */\n          return new Observable(observer => {\n            script.onload = () => observer.complete()\n          })\n\n        /* Complete immediately */\n        } else {\n          script.textContent = el.textContent\n          el.replaceWith(script)\n          return EMPTY\n        }\n      })\n    )\n      .subscribe()\n\n  /* Emit history state change */\n  merge(push$, pop$)\n    .pipe(\n      sample(document$)\n    )\n      .subscribe(({ url, offset }) => {\n        if (url.hash && !offset) {\n          setLocationHash(url.hash)\n        } else {\n          window.scrollTo(0, offset?.y || 0)\n        }\n      })\n\n  /* Debounce update of viewport offset */\n  viewport$\n    .pipe(\n      skipUntil(push$),\n      debounceTime(250),\n      distinctUntilKeyChanged(\"offset\")\n    )\n      .subscribe(({ offset }) => {\n        history.replaceState(offset, \"\")\n      })\n\n  /* Set viewport offset from history */\n  merge(push$, pop$)\n    .pipe(\n      bufferCount(2, 1),\n      filter(([a, b]) => a.url.pathname === b.url.pathname),\n      map(([, state]) => state)\n    )\n      .subscribe(({ offset }) => {\n        window.scrollTo(0, offset?.y || 0)\n      })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport escapeHTML from \"escape-html\"\n\nimport { SearchIndexDocument } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search document\n */\nexport interface SearchDocument extends SearchIndexDocument {\n  parent?: SearchIndexDocument         /* Parent article */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search document mapping\n */\nexport type SearchDocumentMap = Map<string, SearchDocument>\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create a search document mapping\n *\n * @param docs - Search index documents\n *\n * @returns Search document map\n */\nexport function setupSearchDocumentMap(\n  docs: SearchIndexDocument[]\n): SearchDocumentMap {\n  const documents = new Map<string, SearchDocument>()\n  const parents   = new Set<SearchDocument>()\n  for (const doc of docs) {\n    const [path, hash] = doc.location.split(\"#\")\n\n    /* Extract location, title and tags */\n    const location = doc.location\n    const title    = doc.title\n    const tags     = doc.tags\n\n    /* Escape and cleanup text */\n    const text = escapeHTML(doc.text)\n      .replace(/\\s+(?=[,.:;!?])/g, \"\")\n      .replace(/\\s+/g, \" \")\n\n    /* Handle section */\n    if (hash) {\n      const parent = documents.get(path)!\n\n      /* Ignore first section, override article */\n      if (!parents.has(parent)) {\n        parent.title = doc.title\n        parent.text  = text\n\n        /* Remember that we processed the article */\n        parents.add(parent)\n\n      /* Add subsequent section */\n      } else {\n        documents.set(location, {\n          location,\n          title,\n          text,\n          parent\n        })\n      }\n\n    /* Add article */\n    } else {\n      documents.set(location, {\n        location,\n        title,\n        text,\n        ...tags && { tags }\n      })\n    }\n  }\n  return documents\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport escapeHTML from \"escape-html\"\n\nimport { SearchIndexConfig } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search highlight function\n *\n * @param value - Value\n *\n * @returns Highlighted value\n */\nexport type SearchHighlightFn = (value: string) => string\n\n/**\n * Search highlight factory function\n *\n * @param query - Query value\n *\n * @returns Search highlight function\n */\nexport type SearchHighlightFactoryFn = (query: string) => SearchHighlightFn\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create a search highlighter\n *\n * @param config - Search index configuration\n * @param escape - Whether to escape HTML\n *\n * @returns Search highlight factory function\n */\nexport function setupSearchHighlighter(\n  config: SearchIndexConfig, escape: boolean\n): SearchHighlightFactoryFn {\n  const separator = new RegExp(config.separator, \"img\")\n  const highlight = (_: unknown, data: string, term: string) => {\n    return `${data}<mark data-md-highlight>${term}</mark>`\n  }\n\n  /* Return factory function */\n  return (query: string) => {\n    query = query\n      .replace(/[\\s*+\\-:~^]+/g, \" \")\n      .trim()\n\n    /* Create search term match expression */\n    const match = new RegExp(`(^|${config.separator})(${\n      query\n        .replace(/[|\\\\{}()[\\]^$+*?.-]/g, \"\\\\$&\")\n        .replace(separator, \"|\")\n    })`, \"img\")\n\n    /* Highlight string value */\n    return value => (\n      escape\n        ? escapeHTML(value)\n        : value\n      )\n        .replace(match, highlight)\n        .replace(/<\\/mark>(\\s+)<mark[^>]*>/img, \"$1\")\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search transformation function\n *\n * @param value - Query value\n *\n * @returns Transformed query value\n */\nexport type SearchTransformFn = (value: string) => string\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Default transformation function\n *\n * 1. Search for terms in quotation marks and prepend a `+` modifier to denote\n *    that the resulting document must contain all terms, converting the query\n *    to an `AND` query (as opposed to the default `OR` behavior). While users\n *    may expect terms enclosed in quotation marks to map to span queries, i.e.\n *    for which order is important, Lunr.js doesn't support them, so the best\n *    we can do is to convert the terms to an `AND` query.\n *\n * 2. Replace control characters which are not located at the beginning of the\n *    query or preceded by white space, or are not followed by a non-whitespace\n *    character or are at the end of the query string. Furthermore, filter\n *    unmatched quotation marks.\n *\n * 3. Trim excess whitespace from left and right.\n *\n * @param query - Query value\n *\n * @returns Transformed query value\n */\nexport function defaultTransform(query: string): string {\n  return query\n    .split(/\"([^\"]+)\"/g)                            /* => 1 */\n      .map((terms, index) => index & 1\n        ? terms.replace(/^\\b|^(?![^\\x00-\\x7F]|$)|\\s+/g, \" +\")\n        : terms\n      )\n      .join(\"\")\n    .replace(/\"|(?:^|\\s+)[*+\\-:^~]+(?=\\s+|$)/g, \"\") /* => 2 */\n    .trim()                                         /* => 3 */\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A RTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { SearchIndex, SearchResult } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search message type\n */\nexport const enum SearchMessageType {\n  SETUP,                               /* Search index setup */\n  READY,                               /* Search index ready */\n  QUERY,                               /* Search query */\n  RESULT                               /* Search results */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Message containing the data necessary to setup the search index\n */\nexport interface SearchSetupMessage {\n  type: SearchMessageType.SETUP        /* Message type */\n  data: SearchIndex                    /* Message data */\n}\n\n/**\n * Message indicating the search index is ready\n */\nexport interface SearchReadyMessage {\n  type: SearchMessageType.READY        /* Message type */\n}\n\n/**\n * Message containing a search query\n */\nexport interface SearchQueryMessage {\n  type: SearchMessageType.QUERY        /* Message type */\n  data: string                         /* Message data */\n}\n\n/**\n * Message containing results for a search query\n */\nexport interface SearchResultMessage {\n  type: SearchMessageType.RESULT       /* Message type */\n  data: SearchResult                   /* Message data */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Message exchanged with the search worker\n */\nexport type SearchMessage =\n  | SearchSetupMessage\n  | SearchReadyMessage\n  | SearchQueryMessage\n  | SearchResultMessage\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Type guard for search setup messages\n *\n * @param message - Search worker message\n *\n * @returns Test result\n */\nexport function isSearchSetupMessage(\n  message: SearchMessage\n): message is SearchSetupMessage {\n  return message.type === SearchMessageType.SETUP\n}\n\n/**\n * Type guard for search ready messages\n *\n * @param message - Search worker message\n *\n * @returns Test result\n */\nexport function isSearchReadyMessage(\n  message: SearchMessage\n): message is SearchReadyMessage {\n  return message.type === SearchMessageType.READY\n}\n\n/**\n * Type guard for search query messages\n *\n * @param message - Search worker message\n *\n * @returns Test result\n */\nexport function isSearchQueryMessage(\n  message: SearchMessage\n): message is SearchQueryMessage {\n  return message.type === SearchMessageType.QUERY\n}\n\n/**\n * Type guard for search result messages\n *\n * @param message - Search worker message\n *\n * @returns Test result\n */\nexport function isSearchResultMessage(\n  message: SearchMessage\n): message is SearchResultMessage {\n  return message.type === SearchMessageType.RESULT\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A RTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  ObservableInput,\n  Subject,\n  from,\n  map,\n  share\n} from \"rxjs\"\n\nimport { configuration, feature, translation } from \"~/_\"\nimport { WorkerHandler, watchWorker } from \"~/browser\"\n\nimport { SearchIndex } from \"../../_\"\nimport {\n  SearchOptions,\n  SearchPipeline\n} from \"../../options\"\nimport {\n  SearchMessage,\n  SearchMessageType,\n  SearchSetupMessage,\n  isSearchResultMessage\n} from \"../message\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search worker\n */\nexport type SearchWorker = WorkerHandler<SearchMessage>\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up search index\n *\n * @param data - Search index\n *\n * @returns Search index\n */\nfunction setupSearchIndex({ config, docs }: SearchIndex): SearchIndex {\n\n  /* Override default language with value from translation */\n  if (config.lang.length === 1 && config.lang[0] === \"en\")\n    config.lang = [\n      translation(\"search.config.lang\")\n    ]\n\n  /* Override default separator with value from translation */\n  if (config.separator === \"[\\\\s\\\\-]+\")\n    config.separator = translation(\"search.config.separator\")\n\n  /* Set pipeline from translation */\n  const pipeline = translation(\"search.config.pipeline\")\n    .split(/\\s*,\\s*/)\n    .filter(Boolean) as SearchPipeline\n\n  /* Determine search options */\n  const options: SearchOptions = {\n    pipeline,\n    suggestions: feature(\"search.suggest\")\n  }\n\n  /* Return search index after defaulting */\n  return { config, docs, options }\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up search worker\n *\n * This function creates a web worker to set up and query the search index,\n * which is done using Lunr.js. The index must be passed as an observable to\n * enable hacks like _localsearch_ via search index embedding as JSON.\n *\n * @param url - Worker URL\n * @param index - Search index observable input\n *\n * @returns Search worker\n */\nexport function setupSearchWorker(\n  url: string, index: ObservableInput<SearchIndex>\n): SearchWorker {\n  const config = configuration()\n  const worker = new Worker(url)\n\n  /* Create communication channels and resolve relative links */\n  const tx$ = new Subject<SearchMessage>()\n  const rx$ = watchWorker(worker, { tx$ })\n    .pipe(\n      map(message => {\n        if (isSearchResultMessage(message)) {\n          for (const result of message.data.items)\n            for (const document of result)\n              document.location = `${new URL(document.location, config.base)}`\n        }\n        return message\n      }),\n      share()\n    )\n\n  /* Set up search index */\n  from(index)\n    .pipe(\n      map(data => ({\n        type: SearchMessageType.SETUP,\n        data: setupSearchIndex(data)\n      } as SearchSetupMessage))\n    )\n      .subscribe(tx$.next.bind(tx$))\n\n  /* Return search worker */\n  return { tx$, rx$ }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Subject,\n  catchError,\n  combineLatest,\n  filter,\n  fromEvent,\n  map,\n  of,\n  switchMap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport { configuration } from \"~/_\"\nimport {\n  getElement,\n  getLocation,\n  requestJSON,\n  setLocation\n} from \"~/browser\"\nimport { getComponentElements } from \"~/components\"\nimport {\n  Version,\n  renderVersionSelector\n} from \"~/templates\"\n\nimport { fetchSitemap } from \"../sitemap\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Setup options\n */\ninterface SetupOptions {\n  document$: Subject<Document>         /* Document subject */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up version selector\n *\n * @param options - Options\n */\nexport function setupVersionSelector(\n  { document$ }: SetupOptions\n): void {\n  const config = configuration()\n  const versions$ = requestJSON<Version[]>(\n    new URL(\"../versions.json\", config.base)\n  )\n    .pipe(\n      catchError(() => EMPTY) // @todo refactor instant loading\n    )\n\n  /* Determine current version */\n  const current$ = versions$\n    .pipe(\n      map(versions => {\n        const [, current] = config.base.match(/([^/]+)\\/?$/)!\n        return versions.find(({ version, aliases }) => (\n          version === current || aliases.includes(current)\n        )) || versions[0]\n      })\n    )\n\n  /* Intercept inter-version navigation */\n  versions$\n    .pipe(\n      map(versions => new Map(versions.map(version => [\n        `${new URL(`../${version.version}/`, config.base)}`,\n        version\n      ]))),\n      switchMap(urls => fromEvent<MouseEvent>(document.body, \"click\")\n        .pipe(\n          filter(ev => !ev.metaKey && !ev.ctrlKey),\n          withLatestFrom(current$),\n          switchMap(([ev, current]) => {\n            if (ev.target instanceof Element) {\n              const el = ev.target.closest(\"a\")\n              if (el && !el.target && urls.has(el.href)) {\n                const url = el.href\n                // This is a temporary hack to detect if a version inside the\n                // version selector or on another part of the site was clicked.\n                // If we're inside the version selector, we definitely want to\n                // find the same page, as we might have different deployments\n                // due to aliases. However, if we're outside the version\n                // selector, we must abort here, because we might otherwise\n                // interfere with instant loading. We need to refactor this\n                // at some point together with instant loading.\n                //\n                // See https://github.com/squidfunk/mkdocs-material/issues/4012\n                if (!ev.target.closest(\".md-version\")) {\n                  const version = urls.get(url)!\n                  if (version === current)\n                    return EMPTY\n                }\n                ev.preventDefault()\n                return of(url)\n              }\n            }\n            return EMPTY\n          }),\n          switchMap(url => {\n            const { version } = urls.get(url)!\n            return fetchSitemap(new URL(url))\n              .pipe(\n                map(sitemap => {\n                  const location = getLocation()\n                  const path = location.href.replace(config.base, \"\")\n                  return sitemap.includes(path.split(\"#\")[0])\n                    ? new URL(`../${version}/${path}`, config.base)\n                    : new URL(url)\n                })\n              )\n          })\n        )\n      )\n    )\n      .subscribe(url => setLocation(url))\n\n  /* Render version selector and warning */\n  combineLatest([versions$, current$])\n    .subscribe(([versions, current]) => {\n      const topic = getElement(\".md-header__topic\")\n      topic.appendChild(renderVersionSelector(versions, current))\n    })\n\n  /* Integrate outdated version banner with instant loading */\n  document$.pipe(switchMap(() => current$))\n    .subscribe(current => {\n\n      /* Check if version state was already determined */\n      let outdated = __md_get(\"__outdated\", sessionStorage)\n      if (outdated === null) {\n        const latest = config.version?.default || \"latest\"\n        outdated = !current.aliases.includes(latest)\n\n        /* Persist version state in session storage */\n        __md_set(\"__outdated\", outdated, sessionStorage)\n      }\n\n      /* Unhide outdated version banner */\n      if (outdated)\n        for (const warning of getComponentElements(\"outdated\"))\n          warning.hidden = false\n    })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  combineLatest,\n  delay,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  share,\n  shareReplay,\n  startWith,\n  take,\n  takeLast,\n  takeUntil,\n  tap\n} from \"rxjs\"\n\nimport { translation } from \"~/_\"\nimport {\n  getLocation,\n  setToggle,\n  watchElementFocus,\n  watchToggle\n} from \"~/browser\"\nimport {\n  SearchMessageType,\n  SearchQueryMessage,\n  SearchWorker,\n  defaultTransform,\n  isSearchReadyMessage\n} from \"~/integrations\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search query\n */\nexport interface SearchQuery {\n  value: string                        /* Query value */\n  focus: boolean                       /* Query focus */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch search query\n *\n * Note that the focus event which triggers re-reading the current query value\n * is delayed by `1ms` so the input's empty state is allowed to propagate.\n *\n * @param el - Search query element\n * @param worker - Search worker\n *\n * @returns Search query observable\n */\nexport function watchSearchQuery(\n  el: HTMLInputElement, { rx$ }: SearchWorker\n): Observable<SearchQuery> {\n  const fn = __search?.transform || defaultTransform\n\n  /* Immediately show search dialog */\n  const { searchParams } = getLocation()\n  if (searchParams.has(\"q\"))\n    setToggle(\"search\", true)\n\n  /* Intercept query parameter (deep link) */\n  const param$ = rx$\n    .pipe(\n      filter(isSearchReadyMessage),\n      take(1),\n      map(() => searchParams.get(\"q\") || \"\")\n    )\n\n  /* Remove query parameter when search is closed */\n  watchToggle(\"search\")\n    .pipe(\n      filter(active => !active),\n      take(1)\n    )\n      .subscribe(() => {\n        const url = new URL(location.href)\n        url.searchParams.delete(\"q\")\n        history.replaceState({}, \"\", `${url}`)\n      })\n\n  /* Set query from parameter */\n  param$.subscribe(value => { // TODO: not ideal - find a better way\n    if (value) {\n      el.value = value\n      el.focus()\n    }\n  })\n\n  /* Intercept focus and input events */\n  const focus$ = watchElementFocus(el)\n  const value$ = merge(\n    fromEvent(el, \"keyup\"),\n    fromEvent(el, \"focus\").pipe(delay(1)),\n    param$\n  )\n    .pipe(\n      map(() => fn(el.value)),\n      startWith(\"\"),\n      distinctUntilChanged(),\n    )\n\n  /* Combine into single observable */\n  return combineLatest([value$, focus$])\n    .pipe(\n      map(([value, focus]) => ({ value, focus })),\n      shareReplay(1)\n    )\n}\n\n/**\n * Mount search query\n *\n * @param el - Search query element\n * @param worker - Search worker\n *\n * @returns Search query component observable\n */\nexport function mountSearchQuery(\n  el: HTMLInputElement, { tx$, rx$ }: SearchWorker\n): Observable<Component<SearchQuery, HTMLInputElement>> {\n  const push$ = new Subject<SearchQuery>()\n  const done$ = push$.pipe(takeLast(1))\n\n  /* Handle value changes */\n  push$\n    .pipe(\n      distinctUntilKeyChanged(\"value\"),\n      map(({ value }): SearchQueryMessage => ({\n        type: SearchMessageType.QUERY,\n        data: value\n      }))\n    )\n      .subscribe(tx$.next.bind(tx$))\n\n  /* Handle focus changes */\n  push$\n    .pipe(\n      distinctUntilKeyChanged(\"focus\")\n    )\n      .subscribe(({ focus }) => {\n        if (focus) {\n          setToggle(\"search\", focus)\n          el.placeholder = \"\"\n        } else {\n          el.placeholder = translation(\"search.placeholder\")\n        }\n      })\n\n  /* Handle reset */\n  fromEvent(el.form!, \"reset\")\n    .pipe(\n      takeUntil(done$)\n    )\n      .subscribe(() => el.focus())\n\n  /* Create and return component */\n  return watchSearchQuery(el, { tx$, rx$ })\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(state => ({ ref: el, ...state })),\n      share()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  bufferCount,\n  filter,\n  finalize,\n  map,\n  merge,\n  of,\n  skipUntil,\n  switchMap,\n  take,\n  tap,\n  withLatestFrom,\n  zipWith\n} from \"rxjs\"\n\nimport { translation } from \"~/_\"\nimport {\n  getElement,\n  watchElementBoundary\n} from \"~/browser\"\nimport {\n  SearchResult,\n  SearchWorker,\n  isSearchReadyMessage,\n  isSearchResultMessage\n} from \"~/integrations\"\nimport { renderSearchResultItem } from \"~/templates\"\nimport { round } from \"~/utilities\"\n\nimport { Component } from \"../../_\"\nimport { SearchQuery } from \"../query\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  query$: Observable<SearchQuery>      /* Search query observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search result list\n *\n * This function performs a lazy rendering of the search results, depending on\n * the vertical offset of the search result container.\n *\n * @param el - Search result list element\n * @param worker - Search worker\n * @param options - Options\n *\n * @returns Search result list component observable\n */\nexport function mountSearchResult(\n  el: HTMLElement, { rx$ }: SearchWorker, { query$ }: MountOptions\n): Observable<Component<SearchResult>> {\n  const push$ = new Subject<SearchResult>()\n  const boundary$ = watchElementBoundary(el.parentElement!)\n    .pipe(\n      filter(Boolean)\n    )\n\n  /* Retrieve nested components */\n  const meta = getElement(\":scope > :first-child\", el)\n  const list = getElement(\":scope > :last-child\", el)\n\n  /* Wait until search is ready */\n  const ready$ = rx$\n    .pipe(\n      filter(isSearchReadyMessage),\n      take(1)\n    )\n\n  /* Update search result metadata */\n  push$\n    .pipe(\n      withLatestFrom(query$),\n      skipUntil(ready$)\n    )\n      .subscribe(([{ items }, { value }]) => {\n        if (value) {\n          switch (items.length) {\n\n            /* No results */\n            case 0:\n              meta.textContent = translation(\"search.result.none\")\n              break\n\n            /* One result */\n            case 1:\n              meta.textContent = translation(\"search.result.one\")\n              break\n\n            /* Multiple result */\n            default:\n              meta.textContent = translation(\n                \"search.result.other\",\n                round(items.length)\n              )\n          }\n        } else {\n          meta.textContent = translation(\"search.result.placeholder\")\n        }\n      })\n\n  /* Update search result list */\n  push$\n    .pipe(\n      tap(() => list.innerHTML = \"\"),\n      switchMap(({ items }) => merge(\n        of(...items.slice(0, 10)),\n        of(...items.slice(10))\n          .pipe(\n            bufferCount(4),\n            zipWith(boundary$),\n            switchMap(([chunk]) => chunk)\n          )\n      ))\n    )\n      .subscribe(result => list.appendChild(\n        renderSearchResultItem(result)\n      ))\n\n  /* Filter search result message */\n  const result$ = rx$\n    .pipe(\n      filter(isSearchResultMessage),\n      map(({ data }) => data)\n    )\n\n  /* Create and return component */\n  return result$\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(state => ({ ref: el, ...state }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  finalize,\n  fromEvent,\n  map,\n  tap\n} from \"rxjs\"\n\nimport { getLocation } from \"~/browser\"\n\nimport { Component } from \"../../_\"\nimport { SearchQuery } from \"../query\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search sharing\n */\nexport interface SearchShare {\n  url: URL                             /* Deep link for sharing */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  query$: Observable<SearchQuery>      /* Search query observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  query$: Observable<SearchQuery>      /* Search query observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search sharing\n *\n * @param _el - Search sharing element\n * @param options - Options\n *\n * @returns Search sharing observable\n */\nexport function watchSearchShare(\n  _el: HTMLElement, { query$ }: WatchOptions\n): Observable<SearchShare> {\n  return query$\n    .pipe(\n      map(({ value }) => {\n        const url = getLocation()\n        url.hash = \"\"\n        url.searchParams.delete(\"h\")\n        url.searchParams.set(\"q\", value)\n        return { url }\n      })\n    )\n}\n\n/**\n * Mount search sharing\n *\n * @param el - Search sharing element\n * @param options - Options\n *\n * @returns Search sharing component observable\n */\nexport function mountSearchShare(\n  el: HTMLAnchorElement, options: MountOptions\n): Observable<Component<SearchShare>> {\n  const push$ = new Subject<SearchShare>()\n  push$.subscribe(({ url }) => {\n    el.setAttribute(\"data-clipboard-text\", el.href)\n    el.href = `${url}`\n  })\n\n  /* Prevent following of link */\n  fromEvent(el, \"click\")\n    .subscribe(ev => ev.preventDefault())\n\n  /* Create and return component */\n  return watchSearchShare(el, options)\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(state => ({ ref: el, ...state }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  asyncScheduler,\n  combineLatestWith,\n  distinctUntilChanged,\n  filter,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  observeOn,\n  tap\n} from \"rxjs\"\n\nimport { Keyboard } from \"~/browser\"\nimport {\n  SearchResult,\n  SearchWorker,\n  isSearchResultMessage\n} from \"~/integrations\"\n\nimport { Component, getComponentElement } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search suggestions\n */\nexport interface SearchSuggest {}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  keyboard$: Observable<Keyboard>      /* Keyboard observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search suggestions\n *\n * This function will perform a lazy rendering of the search results, depending\n * on the vertical offset of the search result container.\n *\n * @param el - Search result list element\n * @param worker - Search worker\n * @param options - Options\n *\n * @returns Search result list component observable\n */\nexport function mountSearchSuggest(\n  el: HTMLElement, { rx$ }: SearchWorker, { keyboard$ }: MountOptions\n): Observable<Component<SearchSuggest>> {\n  const push$ = new Subject<SearchResult>()\n\n  /* Retrieve query component and track all changes */\n  const query  = getComponentElement(\"search-query\")\n  const query$ = merge(\n    fromEvent(query, \"keydown\"),\n    fromEvent(query, \"focus\")\n  )\n    .pipe(\n      observeOn(asyncScheduler),\n      map(() => query.value),\n      distinctUntilChanged(),\n    )\n\n  /* Update search suggestions */\n  push$\n    .pipe(\n      combineLatestWith(query$),\n      map(([{ suggestions }, value]) => {\n        const words = value.split(/([\\s-]+)/)\n        if (suggestions?.length && words[words.length - 1]) {\n          const last = suggestions[suggestions.length - 1]\n          if (last.startsWith(words[words.length - 1]))\n            words[words.length - 1] = last\n        } else {\n          words.length = 0\n        }\n        return words\n      })\n    )\n      .subscribe(words => el.innerHTML = words\n        .join(\"\")\n        .replace(/\\s/g, \"&nbsp;\")\n      )\n\n  /* Set up search keyboard handlers */\n  keyboard$\n    .pipe(\n      filter(({ mode }) => mode === \"search\")\n    )\n      .subscribe(key => {\n        switch (key.type) {\n\n          /* Right arrow: accept current suggestion */\n          case \"ArrowRight\":\n            if (\n              el.innerText.length &&\n              query.selectionStart === query.value.length\n            )\n              query.value = el.innerText\n            break\n        }\n      })\n\n  /* Filter search result message */\n  const result$ = rx$\n    .pipe(\n      filter(isSearchResultMessage),\n      map(({ data }) => data)\n    )\n\n  /* Create and return component */\n  return result$\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(() => ({ ref: el }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  NEVER,\n  Observable,\n  ObservableInput,\n  filter,\n  merge,\n  mergeWith,\n  sample,\n  take\n} from \"rxjs\"\n\nimport { configuration } from \"~/_\"\nimport {\n  Keyboard,\n  getActiveElement,\n  getElements,\n  setToggle\n} from \"~/browser\"\nimport {\n  SearchIndex,\n  SearchResult,\n  isSearchQueryMessage,\n  isSearchReadyMessage,\n  setupSearchWorker\n} from \"~/integrations\"\n\nimport {\n  Component,\n  getComponentElement,\n  getComponentElements\n} from \"../../_\"\nimport {\n  SearchQuery,\n  mountSearchQuery\n} from \"../query\"\nimport { mountSearchResult } from \"../result\"\nimport {\n  SearchShare,\n  mountSearchShare\n} from \"../share\"\nimport {\n  SearchSuggest,\n  mountSearchSuggest\n} from \"../suggest\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search\n */\nexport type Search =\n  | SearchQuery\n  | SearchResult\n  | SearchShare\n  | SearchSuggest\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  index$: ObservableInput<SearchIndex> /* Search index observable */\n  keyboard$: Observable<Keyboard>      /* Keyboard observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search\n *\n * This function sets up the search functionality, including the underlying\n * web worker and all keyboard bindings.\n *\n * @param el - Search element\n * @param options - Options\n *\n * @returns Search component observable\n */\nexport function mountSearch(\n  el: HTMLElement, { index$, keyboard$ }: MountOptions\n): Observable<Component<Search>> {\n  const config = configuration()\n  try {\n    const url = __search?.worker || config.search\n    const worker = setupSearchWorker(url, index$)\n\n    /* Retrieve query and result components */\n    const query  = getComponentElement(\"search-query\", el)\n    const result = getComponentElement(\"search-result\", el)\n\n    /* Re-emit query when search is ready */\n    const { tx$, rx$ } = worker\n    tx$\n      .pipe(\n        filter(isSearchQueryMessage),\n        sample(rx$.pipe(filter(isSearchReadyMessage))),\n        take(1)\n      )\n        .subscribe(tx$.next.bind(tx$))\n\n    /* Set up search keyboard handlers */\n    keyboard$\n      .pipe(\n        filter(({ mode }) => mode === \"search\")\n      )\n        .subscribe(key => {\n          const active = getActiveElement()\n          switch (key.type) {\n\n            /* Enter: go to first (best) result */\n            case \"Enter\":\n              if (active === query) {\n                const anchors = new Map<HTMLAnchorElement, number>()\n                for (const anchor of getElements<HTMLAnchorElement>(\n                  \":first-child [href]\", result\n                )) {\n                  const article = anchor.firstElementChild!\n                  anchors.set(anchor, parseFloat(\n                    article.getAttribute(\"data-md-score\")!\n                  ))\n                }\n\n                /* Go to result with highest score, if any */\n                if (anchors.size) {\n                  const [[best]] = [...anchors].sort(([, a], [, b]) => b - a)\n                  best.click()\n                }\n\n                /* Otherwise omit form submission */\n                key.claim()\n              }\n              break\n\n            /* Escape or Tab: close search */\n            case \"Escape\":\n            case \"Tab\":\n              setToggle(\"search\", false)\n              query.blur()\n              break\n\n            /* Vertical arrows: select previous or next search result */\n            case \"ArrowUp\":\n            case \"ArrowDown\":\n              if (typeof active === \"undefined\") {\n                query.focus()\n              } else {\n                const els = [query, ...getElements(\n                  \":not(details) > [href], summary, details[open] [href]\",\n                  result\n                )]\n                const i = Math.max(0, (\n                  Math.max(0, els.indexOf(active)) + els.length + (\n                    key.type === \"ArrowUp\" ? -1 : +1\n                  )\n                ) % els.length)\n                els[i].focus()\n              }\n\n              /* Prevent scrolling of page */\n              key.claim()\n              break\n\n            /* All other keys: hand to search query */\n            default:\n              if (query !== getActiveElement())\n                query.focus()\n          }\n        })\n\n    /* Set up global keyboard handlers */\n    keyboard$\n      .pipe(\n        filter(({ mode }) => mode === \"global\"),\n      )\n        .subscribe(key => {\n          switch (key.type) {\n\n            /* Open search and select query */\n            case \"f\":\n            case \"s\":\n            case \"/\":\n              query.focus()\n              query.select()\n\n              /* Prevent scrolling of page */\n              key.claim()\n              break\n          }\n        })\n\n    /* Create and return component */\n    const query$  = mountSearchQuery(query, worker)\n    const result$ = mountSearchResult(result, worker, { query$ })\n    return merge(query$, result$)\n      .pipe(\n        mergeWith(\n\n          /* Search sharing */\n          ...getComponentElements(\"search-share\", el)\n            .map(child => mountSearchShare(child, { query$ })),\n\n          /* Search suggestions */\n          ...getComponentElements(\"search-suggest\", el)\n            .map(child => mountSearchSuggest(child, worker, { keyboard$ }))\n        )\n      )\n\n  /* Gracefully handle broken search */\n  } catch (err) {\n    el.hidden = true\n    return NEVER\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  ObservableInput,\n  combineLatest,\n  filter,\n  map,\n  startWith\n} from \"rxjs\"\n\nimport { getLocation } from \"~/browser\"\nimport {\n  SearchIndex,\n  setupSearchHighlighter\n} from \"~/integrations\"\nimport { h } from \"~/utilities\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search highlighting\n */\nexport interface SearchHighlight {\n  nodes: Map<ChildNode, string>        /* Map of replacements */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  index$: ObservableInput<SearchIndex> /* Search index observable */\n  location$: Observable<URL>           /* Location observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search highlighting\n *\n * @param el - Content element\n * @param options - Options\n *\n * @returns Search highlighting component observable\n */\nexport function mountSearchHiglight(\n  el: HTMLElement, { index$, location$ }: MountOptions\n): Observable<Component<SearchHighlight>> {\n  return combineLatest([\n    index$,\n    location$\n      .pipe(\n        startWith(getLocation()),\n        filter(url => !!url.searchParams.get(\"h\"))\n      )\n  ])\n    .pipe(\n      map(([index, url]) => setupSearchHighlighter(index.config, true)(\n        url.searchParams.get(\"h\")!\n      )),\n      map(fn => {\n        const nodes = new Map<ChildNode, string>()\n\n        /* Traverse text nodes and collect matches */\n        const it = document.createNodeIterator(el, NodeFilter.SHOW_TEXT)\n        for (let node = it.nextNode(); node; node = it.nextNode()) {\n          if (node.parentElement?.offsetHeight) {\n            const original = node.textContent!\n            const replaced = fn(original)\n            if (replaced.length > original.length)\n              nodes.set(node as ChildNode, replaced)\n          }\n        }\n\n        /* Replace original nodes with matches */\n        for (const [node, text] of nodes) {\n          const { childNodes } = h(\"span\", null, text)\n          node.replaceWith(...Array.from(childNodes))\n        }\n\n        /* Return component */\n        return { ref: el, nodes }\n      })\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  animationFrameScheduler,\n  auditTime,\n  combineLatest,\n  defer,\n  distinctUntilChanged,\n  finalize,\n  map,\n  observeOn,\n  take,\n  tap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport {\n  Viewport,\n  getElement,\n  getElementContainer,\n  getElementOffset,\n  getElementSize,\n  getElements\n} from \"~/browser\"\n\nimport { Component } from \"../_\"\nimport { Header } from \"../header\"\nimport { Main } from \"../main\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Sidebar\n */\nexport interface Sidebar {\n  height: number                       /* Sidebar height */\n  locked: boolean                      /* Sidebar is locked */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  main$: Observable<Main>              /* Main area observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n  main$: Observable<Main>              /* Main area observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch sidebar\n *\n * This function returns an observable that computes the visual parameters of\n * the sidebar which depends on the vertical viewport offset, as well as the\n * height of the main area. When the page is scrolled beyond the header, the\n * sidebar is locked and fills the remaining space.\n *\n * @param el - Sidebar element\n * @param options - Options\n *\n * @returns Sidebar observable\n */\nexport function watchSidebar(\n  el: HTMLElement, { viewport$, main$ }: WatchOptions\n): Observable<Sidebar> {\n  const parent = el.parentElement!\n  const adjust =\n    parent.offsetTop -\n    parent.parentElement!.offsetTop\n\n  /* Compute the sidebar's available height and if it should be locked */\n  return combineLatest([main$, viewport$])\n    .pipe(\n      map(([{ offset, height }, { offset: { y } }]) => {\n        height = height\n          + Math.min(adjust, Math.max(0, y - offset))\n          - adjust\n        return {\n          height,\n          locked: y >= offset + adjust\n        }\n      }),\n      distinctUntilChanged((a, b) => (\n        a.height === b.height &&\n        a.locked === b.locked\n      ))\n    )\n}\n\n/**\n * Mount sidebar\n *\n * This function doesn't set the height of the actual sidebar, but of its first\n * child \u2013 the `.md-sidebar__scrollwrap` element in order to mitigiate jittery\n * sidebars when the footer is scrolled into view. At some point we switched\n * from `absolute` / `fixed` positioning to `sticky` positioning, significantly\n * reducing jitter in some browsers (respectively Firefox and Safari) when\n * scrolling from the top. However, top-aligned sticky positioning means that\n * the sidebar snaps to the bottom when the end of the container is reached.\n * This is what leads to the mentioned jitter, as the sidebar's height may be\n * updated too slowly.\n *\n * This behaviour can be mitigiated by setting the height of the sidebar to `0`\n * while preserving the padding, and the height on its first element.\n *\n * @param el - Sidebar element\n * @param options - Options\n *\n * @returns Sidebar component observable\n */\nexport function mountSidebar(\n  el: HTMLElement, { header$, ...options }: MountOptions\n): Observable<Component<Sidebar>> {\n  const inner = getElement(\".md-sidebar__scrollwrap\", el)\n  const { y } = getElementOffset(inner)\n  return defer(() => {\n    const push$ = new Subject<Sidebar>()\n    push$\n      .pipe(\n        auditTime(0, animationFrameScheduler),\n        withLatestFrom(header$)\n      )\n        .subscribe({\n\n          /* Handle emission */\n          next([{ height }, { height: offset }]) {\n            inner.style.height = `${height - 2 * y}px`\n            el.style.top       = `${offset}px`\n          },\n\n          /* Handle complete */\n          complete() {\n            inner.style.height = \"\"\n            el.style.top       = \"\"\n          }\n        })\n\n    /* Bring active item into view on initial load */\n    push$\n      .pipe(\n        observeOn(animationFrameScheduler),\n        take(1)\n      )\n        .subscribe(() => {\n          for (const item of getElements(\".md-nav__link--active[href]\", el)) {\n            const container = getElementContainer(item)\n            if (typeof container !== \"undefined\") {\n              const offset = item.offsetTop - container.offsetTop\n              const { height } = getElementSize(container)\n              container.scrollTo({\n                top: offset - height / 2\n              })\n            }\n          }\n        })\n\n    /* Create and return component */\n    return watchSidebar(el, options)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { Repo, User } from \"github-types\"\nimport {\n  EMPTY,\n  Observable,\n  catchError,\n  defaultIfEmpty,\n  map,\n  zip\n} from \"rxjs\"\n\nimport { requestJSON } from \"~/browser\"\n\nimport { SourceFacts } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * GitHub release (partial)\n */\ninterface Release {\n  tag_name: string                     /* Tag name */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch GitHub repository facts\n *\n * @param user - GitHub user or organization\n * @param repo - GitHub repository\n *\n * @returns Repository facts observable\n */\nexport function fetchSourceFactsFromGitHub(\n  user: string, repo?: string\n): Observable<SourceFacts> {\n  if (typeof repo !== \"undefined\") {\n    const url = `https://api.github.com/repos/${user}/${repo}`\n    return zip(\n\n      /* Fetch version */\n      requestJSON<Release>(`${url}/releases/latest`)\n        .pipe(\n          catchError(() => EMPTY), // @todo refactor instant loading\n          map(release => ({\n            version: release.tag_name\n          })),\n          defaultIfEmpty({})\n        ),\n\n      /* Fetch stars and forks */\n      requestJSON<Repo>(url)\n        .pipe(\n          catchError(() => EMPTY), // @todo refactor instant loading\n          map(info => ({\n            stars: info.stargazers_count,\n            forks: info.forks_count\n          })),\n          defaultIfEmpty({})\n        )\n    )\n      .pipe(\n        map(([release, info]) => ({ ...release, ...info }))\n      )\n\n  /* User or organization */\n  } else {\n    const url = `https://api.github.com/users/${user}`\n    return requestJSON<User>(url)\n      .pipe(\n        map(info => ({\n          repositories: info.public_repos\n        })),\n        defaultIfEmpty({})\n      )\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { ProjectSchema } from \"gitlab\"\nimport {\n  EMPTY,\n  Observable,\n  catchError,\n  defaultIfEmpty,\n  map\n} from \"rxjs\"\n\nimport { requestJSON } from \"~/browser\"\n\nimport { SourceFacts } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch GitLab repository facts\n *\n * @param base - GitLab base\n * @param project - GitLab project\n *\n * @returns Repository facts observable\n */\nexport function fetchSourceFactsFromGitLab(\n  base: string, project: string\n): Observable<SourceFacts> {\n  const url = `https://${base}/api/v4/projects/${encodeURIComponent(project)}`\n  return requestJSON<ProjectSchema>(url)\n    .pipe(\n      catchError(() => EMPTY), // @todo refactor instant loading\n      map(({ star_count, forks_count }) => ({\n        stars: star_count,\n        forks: forks_count\n      })),\n      defaultIfEmpty({})\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { EMPTY, Observable } from \"rxjs\"\n\nimport { fetchSourceFactsFromGitHub } from \"../github\"\nimport { fetchSourceFactsFromGitLab } from \"../gitlab\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Repository facts for repositories\n */\nexport interface RepositoryFacts {\n  stars?: number                       /* Number of stars */\n  forks?: number                       /* Number of forks */\n  version?: string                     /* Latest version */\n}\n\n/**\n * Repository facts for organizations\n */\nexport interface OrganizationFacts {\n  repositories?: number                /* Number of repositories */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Repository facts\n */\nexport type SourceFacts =\n  | RepositoryFacts\n  | OrganizationFacts\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch repository facts\n *\n * @param url - Repository URL\n *\n * @returns Repository facts observable\n */\nexport function fetchSourceFacts(\n  url: string\n): Observable<SourceFacts> {\n\n  /* Try to match GitHub repository */\n  let match = url.match(/^.+github\\.com\\/([^/]+)\\/?([^/]+)?/i)\n  if (match) {\n    const [, user, repo] = match\n    return fetchSourceFactsFromGitHub(user, repo)\n  }\n\n  /* Try to match GitLab repository */\n  match = url.match(/^.+?([^/]*gitlab[^/]+)\\/(.+?)\\/?$/i)\n  if (match) {\n    const [, base, slug] = match\n    return fetchSourceFactsFromGitLab(base, slug)\n  }\n\n  /* Fallback */\n  return EMPTY\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  catchError,\n  defer,\n  filter,\n  finalize,\n  map,\n  of,\n  shareReplay,\n  tap\n} from \"rxjs\"\n\nimport { getElement } from \"~/browser\"\nimport { ConsentDefaults } from \"~/components/consent\"\nimport { renderSourceFacts } from \"~/templates\"\n\nimport {\n  Component,\n  getComponentElements\n} from \"../../_\"\nimport {\n  SourceFacts,\n  fetchSourceFacts\n} from \"../facts\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Repository information\n */\nexport interface Source {\n  facts: SourceFacts                   /* Repository facts */\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Repository information observable\n */\nlet fetch$: Observable<Source>\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch repository information\n *\n * This function tries to read the repository facts from session storage, and\n * if unsuccessful, fetches them from the underlying provider.\n *\n * @param el - Repository information element\n *\n * @returns Repository information observable\n */\nexport function watchSource(\n  el: HTMLAnchorElement\n): Observable<Source> {\n  return fetch$ ||= defer(() => {\n    const cached = __md_get<SourceFacts>(\"__source\", sessionStorage)\n    if (cached) {\n      return of(cached)\n    } else {\n\n      /* Check if consent is configured and was given */\n      const els = getComponentElements(\"consent\")\n      if (els.length) {\n        const consent = __md_get<ConsentDefaults>(\"__consent\")\n        if (!(consent && consent.github))\n          return EMPTY\n      }\n\n      /* Fetch repository facts */\n      return fetchSourceFacts(el.href)\n        .pipe(\n          tap(facts => __md_set(\"__source\", facts, sessionStorage))\n        )\n    }\n  })\n    .pipe(\n      catchError(() => EMPTY),\n      filter(facts => Object.keys(facts).length > 0),\n      map(facts => ({ facts })),\n      shareReplay(1)\n    )\n}\n\n/**\n * Mount repository information\n *\n * @param el - Repository information element\n *\n * @returns Repository information component observable\n */\nexport function mountSource(\n  el: HTMLAnchorElement\n): Observable<Component<Source>> {\n  const inner = getElement(\":scope > :last-child\", el)\n  return defer(() => {\n    const push$ = new Subject<Source>()\n    push$.subscribe(({ facts }) => {\n      inner.appendChild(renderSourceFacts(facts))\n      inner.classList.add(\"md-source__repository--active\")\n    })\n\n    /* Create and return component */\n    return watchSource(el)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  defer,\n  distinctUntilKeyChanged,\n  finalize,\n  map,\n  of,\n  switchMap,\n  tap\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  Viewport,\n  watchElementSize,\n  watchViewportAt\n} from \"~/browser\"\n\nimport { Component } from \"../_\"\nimport { Header } from \"../header\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Navigation tabs\n */\nexport interface Tabs {\n  hidden: boolean                      /* Navigation tabs are hidden */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch navigation tabs\n *\n * @param el - Navigation tabs element\n * @param options - Options\n *\n * @returns Navigation tabs observable\n */\nexport function watchTabs(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<Tabs> {\n  return watchElementSize(document.body)\n    .pipe(\n      switchMap(() => watchViewportAt(el, { header$, viewport$ })),\n      map(({ offset: { y } }) => {\n        return {\n          hidden: y >= 10\n        }\n      }),\n      distinctUntilKeyChanged(\"hidden\")\n    )\n}\n\n/**\n * Mount navigation tabs\n *\n * This function hides the navigation tabs when scrolling past the threshold\n * and makes them reappear in a nice CSS animation when scrolling back up.\n *\n * @param el - Navigation tabs element\n * @param options - Options\n *\n * @returns Navigation tabs component observable\n */\nexport function mountTabs(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<Tabs>> {\n  return defer(() => {\n    const push$ = new Subject<Tabs>()\n    push$.subscribe({\n\n      /* Handle emission */\n      next({ hidden }) {\n        el.hidden = hidden\n      },\n\n      /* Handle complete */\n      complete() {\n        el.hidden = false\n      }\n    })\n\n    /* Create and return component */\n    return (\n      feature(\"navigation.tabs.sticky\")\n        ? of({ hidden: false })\n        : watchTabs(el, options)\n    )\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  bufferCount,\n  combineLatestWith,\n  debounceTime,\n  defer,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  finalize,\n  map,\n  merge,\n  of,\n  repeat,\n  scan,\n  share,\n  skip,\n  startWith,\n  switchMap,\n  takeLast,\n  takeUntil,\n  tap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  Viewport,\n  getElement,\n  getElementContainer,\n  getElementSize,\n  getElements,\n  getLocation,\n  getOptionalElement,\n  watchElementSize\n} from \"~/browser\"\n\nimport {\n  Component,\n  getComponentElement\n} from \"../_\"\nimport { Header } from \"../header\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Table of contents\n */\nexport interface TableOfContents {\n  prev: HTMLAnchorElement[][]          /* Anchors (previous) */\n  next: HTMLAnchorElement[][]          /* Anchors (next) */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n  target$: Observable<HTMLElement>     /* Location target observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch table of contents\n *\n * This is effectively a scroll spy implementation which will account for the\n * fixed header and automatically re-calculate anchor offsets when the viewport\n * is resized. The returned observable will only emit if the table of contents\n * needs to be repainted.\n *\n * This implementation tracks an anchor element's entire path starting from its\n * level up to the top-most anchor element, e.g. `[h3, h2, h1]`. Although the\n * Material theme currently doesn't make use of this information, it enables\n * the styling of the entire hierarchy through customization.\n *\n * Note that the current anchor is the last item of the `prev` anchor list.\n *\n * @param el - Table of contents element\n * @param options - Options\n *\n * @returns Table of contents observable\n */\nexport function watchTableOfContents(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<TableOfContents> {\n  const table = new Map<HTMLAnchorElement, HTMLElement>()\n\n  /* Compute anchor-to-target mapping */\n  const anchors = getElements<HTMLAnchorElement>(\"[href^=\\\\#]\", el)\n  for (const anchor of anchors) {\n    const id = decodeURIComponent(anchor.hash.substring(1))\n    const target = getOptionalElement(`[id=\"${id}\"]`)\n    if (typeof target !== \"undefined\")\n      table.set(anchor, target)\n  }\n\n  /* Compute necessary adjustment for header */\n  const adjust$ = header$\n    .pipe(\n      distinctUntilKeyChanged(\"height\"),\n      map(({ height }) => {\n        const main = getComponentElement(\"main\")\n        const grid = getElement(\":scope > :first-child\", main)\n        return height + 0.8 * (\n          grid.offsetTop -\n          main.offsetTop\n        )\n      }),\n      share()\n    )\n\n  /* Compute partition of previous and next anchors */\n  const partition$ = watchElementSize(document.body)\n    .pipe(\n      distinctUntilKeyChanged(\"height\"),\n\n      /* Build index to map anchor paths to vertical offsets */\n      switchMap(body => defer(() => {\n        let path: HTMLAnchorElement[] = []\n        return of([...table].reduce((index, [anchor, target]) => {\n          while (path.length) {\n            const last = table.get(path[path.length - 1])!\n            if (last.tagName >= target.tagName) {\n              path.pop()\n            } else {\n              break\n            }\n          }\n\n          /* If the current anchor is hidden, continue with its parent */\n          let offset = target.offsetTop\n          while (!offset && target.parentElement) {\n            target = target.parentElement\n            offset = target.offsetTop\n          }\n\n          /* Map reversed anchor path to vertical offset */\n          return index.set(\n            [...path = [...path, anchor]].reverse(),\n            offset\n          )\n        }, new Map<HTMLAnchorElement[], number>()))\n      })\n        .pipe(\n\n          /* Sort index by vertical offset (see https://bit.ly/30z6QSO) */\n          map(index => new Map([...index].sort(([, a], [, b]) => a - b))),\n          combineLatestWith(adjust$),\n\n          /* Re-compute partition when viewport offset changes */\n          switchMap(([index, adjust]) => viewport$\n            .pipe(\n              scan(([prev, next], { offset: { y }, size }) => {\n                const last = y + size.height >= Math.floor(body.height)\n\n                /* Look forward */\n                while (next.length) {\n                  const [, offset] = next[0]\n                  if (offset - adjust < y || last) {\n                    prev = [...prev, next.shift()!]\n                  } else {\n                    break\n                  }\n                }\n\n                /* Look backward */\n                while (prev.length) {\n                  const [, offset] = prev[prev.length - 1]\n                  if (offset - adjust >= y && !last) {\n                    next = [prev.pop()!, ...next]\n                  } else {\n                    break\n                  }\n                }\n\n                /* Return partition */\n                return [prev, next]\n              }, [[], [...index]]),\n              distinctUntilChanged((a, b) => (\n                a[0] === b[0] &&\n                a[1] === b[1]\n              ))\n            )\n          )\n        )\n      )\n    )\n\n  /* Compute and return anchor list migrations */\n  return partition$\n    .pipe(\n      map(([prev, next]) => ({\n        prev: prev.map(([path]) => path),\n        next: next.map(([path]) => path)\n      })),\n\n      /* Extract anchor list migrations */\n      startWith({ prev: [], next: [] }),\n      bufferCount(2, 1),\n      map(([a, b]) => {\n\n        /* Moving down */\n        if (a.prev.length < b.prev.length) {\n          return {\n            prev: b.prev.slice(Math.max(0, a.prev.length - 1), b.prev.length),\n            next: []\n          }\n\n        /* Moving up */\n        } else {\n          return {\n            prev: b.prev.slice(-1),\n            next: b.next.slice(0, b.next.length - a.next.length)\n          }\n        }\n      })\n    )\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Mount table of contents\n *\n * @param el - Table of contents element\n * @param options - Options\n *\n * @returns Table of contents component observable\n */\nexport function mountTableOfContents(\n  el: HTMLElement, { viewport$, header$, target$ }: MountOptions\n): Observable<Component<TableOfContents>> {\n  return defer(() => {\n    const push$ = new Subject<TableOfContents>()\n    const done$ = push$.pipe(takeLast(1))\n    push$.subscribe(({ prev, next }) => {\n\n      /* Look forward */\n      for (const [anchor] of next) {\n        anchor.classList.remove(\"md-nav__link--passed\")\n        anchor.classList.remove(\"md-nav__link--active\")\n      }\n\n      /* Look backward */\n      for (const [index, [anchor]] of prev.entries()) {\n        anchor.classList.add(\"md-nav__link--passed\")\n        anchor.classList.toggle(\n          \"md-nav__link--active\",\n          index === prev.length - 1\n        )\n      }\n    })\n\n    /* Set up following, if enabled */\n    if (feature(\"toc.follow\")) {\n\n      /* Toggle smooth scrolling only for anchor clicks */\n      const smooth$ = merge(\n        viewport$.pipe(debounceTime(1), map(() => undefined)),\n        viewport$.pipe(debounceTime(250), map(() => \"smooth\" as const))\n      )\n\n      /* Bring active anchor into view */\n      push$\n        .pipe(\n          filter(({ prev }) => prev.length > 0),\n          withLatestFrom(smooth$)\n        )\n          .subscribe(([{ prev }, behavior]) => {\n            const [anchor] = prev[prev.length - 1]\n            if (anchor.offsetHeight) {\n\n              /* Retrieve overflowing container and scroll */\n              const container = getElementContainer(anchor)\n              if (typeof container !== \"undefined\") {\n                const offset = anchor.offsetTop - container.offsetTop\n                const { height } = getElementSize(container)\n                container.scrollTo({\n                  top: offset - height / 2,\n                  behavior\n                })\n              }\n            }\n          })\n    }\n\n    /* Set up anchor tracking, if enabled */\n    if (feature(\"navigation.tracking\"))\n      viewport$\n        .pipe(\n          takeUntil(done$),\n          distinctUntilKeyChanged(\"offset\"),\n          debounceTime(250),\n          skip(1),\n          takeUntil(target$.pipe(skip(1))),\n          repeat({ delay: 250 }),\n          withLatestFrom(push$)\n        )\n          .subscribe(([, { prev }]) => {\n            const url = getLocation()\n\n            /* Set hash fragment to active anchor */\n            const anchor = prev[prev.length - 1]\n            if (anchor && anchor.length) {\n              const [active] = anchor\n              const { hash } = new URL(active.href)\n              if (url.hash !== hash) {\n                url.hash = hash\n                history.replaceState({}, \"\", `${url}`)\n              }\n\n            /* Reset anchor when at the top */\n            } else {\n              url.hash = \"\"\n              history.replaceState({}, \"\", `${url}`)\n            }\n          })\n\n    /* Create and return component */\n    return watchTableOfContents(el, { viewport$, header$ })\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  bufferCount,\n  combineLatest,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  endWith,\n  finalize,\n  map,\n  repeat,\n  skip,\n  takeLast,\n  takeUntil,\n  tap\n} from \"rxjs\"\n\nimport { Viewport } from \"~/browser\"\n\nimport { Component } from \"../_\"\nimport { Header } from \"../header\"\nimport { Main } from \"../main\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Back-to-top button\n */\nexport interface BackToTop {\n  hidden: boolean                      /* Back-to-top button is hidden */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  main$: Observable<Main>              /* Main area observable */\n  target$: Observable<HTMLElement>     /* Location target observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n  main$: Observable<Main>              /* Main area observable */\n  target$: Observable<HTMLElement>     /* Location target observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch back-to-top\n *\n * @param _el - Back-to-top element\n * @param options - Options\n *\n * @returns Back-to-top observable\n */\nexport function watchBackToTop(\n  _el: HTMLElement, { viewport$, main$, target$ }: WatchOptions\n): Observable<BackToTop> {\n\n  /* Compute direction */\n  const direction$ = viewport$\n    .pipe(\n      map(({ offset: { y } }) => y),\n      bufferCount(2, 1),\n      map(([a, b]) => a > b && b > 0),\n      distinctUntilChanged()\n    )\n\n  /* Compute whether main area is active */\n  const active$ = main$\n    .pipe(\n      map(({ active }) => active)\n    )\n\n  /* Compute threshold for hiding */\n  return combineLatest([active$, direction$])\n    .pipe(\n      map(([active, direction]) => !(active && direction)),\n      distinctUntilChanged(),\n      takeUntil(target$.pipe(skip(1))),\n      endWith(true),\n      repeat({ delay: 250 }),\n      map(hidden => ({ hidden }))\n    )\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Mount back-to-top\n *\n * @param el - Back-to-top element\n * @param options - Options\n *\n * @returns Back-to-top component observable\n */\nexport function mountBackToTop(\n  el: HTMLElement, { viewport$, header$, main$, target$ }: MountOptions\n): Observable<Component<BackToTop>> {\n  const push$ = new Subject<BackToTop>()\n  const done$ = push$.pipe(takeLast(1))\n  push$.subscribe({\n\n    /* Handle emission */\n    next({ hidden }) {\n      el.hidden = hidden\n      if (hidden) {\n        el.setAttribute(\"tabindex\", \"-1\")\n        el.blur()\n      } else {\n        el.removeAttribute(\"tabindex\")\n      }\n    },\n\n    /* Handle complete */\n    complete() {\n      el.style.top = \"\"\n      el.hidden = true\n      el.removeAttribute(\"tabindex\")\n    }\n  })\n\n  /* Watch header height */\n  header$\n    .pipe(\n      takeUntil(done$),\n      distinctUntilKeyChanged(\"height\")\n    )\n      .subscribe(({ height }) => {\n        el.style.top = `${height + 16}px`\n      })\n\n  /* Create and return component */\n  return watchBackToTop(el, { viewport$, main$, target$ })\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(state => ({ ref: el, ...state }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  fromEvent,\n  map,\n  mergeMap,\n  switchMap,\n  takeWhile,\n  tap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport { getElements } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch options\n */\ninterface PatchOptions {\n  document$: Observable<Document>      /* Document observable */\n  tablet$: Observable<boolean>         /* Media tablet observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch indeterminate checkboxes\n *\n * This function replaces the indeterminate \"pseudo state\" with the actual\n * indeterminate state, which is used to keep navigation always expanded.\n *\n * @param options - Options\n */\nexport function patchIndeterminate(\n  { document$, tablet$ }: PatchOptions\n): void {\n  document$\n    .pipe(\n      switchMap(() => getElements<HTMLInputElement>(\n        // @todo `data-md-state` is deprecated and removed in v9\n        \".md-toggle--indeterminate, [data-md-state=indeterminate]\"\n      )),\n      tap(el => {\n        el.indeterminate = true\n        el.checked = false\n      }),\n      mergeMap(el => fromEvent(el, \"change\")\n        .pipe(\n          takeWhile(() => el.classList.contains(\"md-toggle--indeterminate\")),\n          map(() => el)\n        )\n      ),\n      withLatestFrom(tablet$)\n    )\n      .subscribe(([el, tablet]) => {\n        el.classList.remove(\"md-toggle--indeterminate\")\n        if (tablet)\n          el.checked = false\n      })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  filter,\n  fromEvent,\n  map,\n  mergeMap,\n  switchMap,\n  tap\n} from \"rxjs\"\n\nimport { getElements } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch options\n */\ninterface PatchOptions {\n  document$: Observable<Document>      /* Document observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Check whether the given device is an Apple device\n *\n * @returns Test result\n */\nfunction isAppleDevice(): boolean {\n  return /(iPad|iPhone|iPod)/.test(navigator.userAgent)\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch all elements with `data-md-scrollfix` attributes\n *\n * This is a year-old patch which ensures that overflow scrolling works at the\n * top and bottom of containers on iOS by ensuring a `1px` scroll offset upon\n * the start of a touch event.\n *\n * @see https://bit.ly/2SCtAOO - Original source\n *\n * @param options - Options\n */\nexport function patchScrollfix(\n  { document$ }: PatchOptions\n): void {\n  document$\n    .pipe(\n      switchMap(() => getElements(\"[data-md-scrollfix]\")),\n      tap(el => el.removeAttribute(\"data-md-scrollfix\")),\n      filter(isAppleDevice),\n      mergeMap(el => fromEvent(el, \"touchstart\")\n        .pipe(\n          map(() => el)\n        )\n      )\n    )\n      .subscribe(el => {\n        const top = el.scrollTop\n\n        /* We're at the top of the container */\n        if (top === 0) {\n          el.scrollTop = 1\n\n        /* We're at the bottom of the container */\n        } else if (top + el.offsetHeight === el.scrollHeight) {\n          el.scrollTop = top - 1\n        }\n      })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  combineLatest,\n  delay,\n  map,\n  of,\n  switchMap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport {\n  Viewport,\n  watchToggle\n} from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch options\n */\ninterface PatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  tablet$: Observable<boolean>         /* Media tablet observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch the document body to lock when search is open\n *\n * For mobile and tablet viewports, the search is rendered full screen, which\n * leads to scroll leaking when at the top or bottom of the search result. This\n * function locks the body when the search is in full screen mode, and restores\n * the scroll position when leaving.\n *\n * @param options - Options\n */\nexport function patchScrolllock(\n  { viewport$, tablet$ }: PatchOptions\n): void {\n  combineLatest([watchToggle(\"search\"), tablet$])\n    .pipe(\n      map(([active, tablet]) => active && !tablet),\n      switchMap(active => of(active)\n        .pipe(\n          delay(active ? 400 : 100)\n        )\n      ),\n      withLatestFrom(viewport$)\n    )\n      .subscribe(([active, { offset: { y }}]) => {\n        if (active) {\n          document.body.setAttribute(\"data-md-scrolllock\", \"\")\n          document.body.style.top = `-${y}px`\n        } else {\n          const value = -1 * parseInt(document.body.style.top, 10)\n          document.body.removeAttribute(\"data-md-scrolllock\")\n          document.body.style.top = \"\"\n          if (value)\n            window.scrollTo(0, value)\n        }\n      })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Polyfills\n * ------------------------------------------------------------------------- */\n\n/* Polyfill `Object.entries` */\nif (!Object.entries)\n  Object.entries = function (obj: object) {\n    const data: [string, string][] = []\n    for (const key of Object.keys(obj))\n      // @ts-expect-error - ignore property access warning\n      data.push([key, obj[key]])\n\n    /* Return entries */\n    return data\n  }\n\n/* Polyfill `Object.values` */\nif (!Object.values)\n  Object.values = function (obj: object) {\n    const data: string[] = []\n    for (const key of Object.keys(obj))\n      // @ts-expect-error - ignore property access warning\n      data.push(obj[key])\n\n    /* Return values */\n    return data\n  }\n\n/* ------------------------------------------------------------------------- */\n\n/* Polyfills for `Element` */\nif (typeof Element !== \"undefined\") {\n\n  /* Polyfill `Element.scrollTo` */\n  if (!Element.prototype.scrollTo)\n    Element.prototype.scrollTo = function (\n      x?: ScrollToOptions | number, y?: number\n    ): void {\n      if (typeof x === \"object\") {\n        this.scrollLeft = x.left!\n        this.scrollTop = x.top!\n      } else {\n        this.scrollLeft = x!\n        this.scrollTop = y!\n      }\n    }\n\n  /* Polyfill `Element.replaceWith` */\n  if (!Element.prototype.replaceWith)\n    Element.prototype.replaceWith = function (\n      ...nodes: Array<string | Node>\n    ): void {\n      const parent = this.parentNode\n      if (parent) {\n        if (nodes.length === 0)\n          parent.removeChild(this)\n\n        /* Replace children and create text nodes */\n        for (let i = nodes.length - 1; i >= 0; i--) {\n          let node = nodes[i]\n          if (typeof node === \"string\")\n            node = document.createTextNode(node)\n          else if (node.parentNode)\n            node.parentNode.removeChild(node)\n\n          /* Replace child or insert before previous sibling */\n          if (!i)\n            parent.replaceChild(node, this)\n          else\n            parent.insertBefore(this.previousSibling!, node)\n        }\n      }\n    }\n}\n"],
+  "mappings": "6+BAAA,IAAAA,GAAAC,GAAA,CAAAC,GAAAC,KAAA,EAAC,SAAUC,EAAQC,EAAS,CAC1B,OAAOH,IAAY,UAAY,OAAOC,IAAW,YAAcE,EAAQ,EACvE,OAAO,QAAW,YAAc,OAAO,IAAM,OAAOA,CAAO,EAC1DA,EAAQ,CACX,GAAEH,GAAO,UAAY,CAAE,aASrB,SAASI,EAA0BC,EAAO,CACxC,IAAIC,EAAmB,GACnBC,EAA0B,GAC1BC,EAAiC,KAEjCC,EAAsB,CACxB,KAAM,GACN,OAAQ,GACR,IAAK,GACL,IAAK,GACL,MAAO,GACP,SAAU,GACV,OAAQ,GACR,KAAM,GACN,MAAO,GACP,KAAM,GACN,KAAM,GACN,SAAU,GACV,iBAAkB,EACpB,EAOA,SAASC,EAAmBC,EAAI,CAC9B,MACE,GAAAA,GACAA,IAAO,UACPA,EAAG,WAAa,QAChBA,EAAG,WAAa,QAChB,cAAeA,GACf,aAAcA,EAAG,UAKrB,CASA,SAASC,EAA8BD,EAAI,CACzC,IAAIE,GAAOF,EAAG,KACVG,GAAUH,EAAG,QAUjB,MARI,GAAAG,KAAY,SAAWL,EAAoBI,KAAS,CAACF,EAAG,UAIxDG,KAAY,YAAc,CAACH,EAAG,UAI9BA,EAAG,kBAKT,CAOA,SAASI,EAAqBJ,EAAI,CAC5BA,EAAG,UAAU,SAAS,eAAe,IAGzCA,EAAG,UAAU,IAAI,eAAe,EAChCA,EAAG,aAAa,2BAA4B,EAAE,EAChD,CAOA,SAASK,EAAwBL,EAAI,CAC/B,CAACA,EAAG,aAAa,0BAA0B,IAG/CA,EAAG,UAAU,OAAO,eAAe,EACnCA,EAAG,gBAAgB,0BAA0B,EAC/C,CAUA,SAASM,EAAUC,EAAG,CAChBA,EAAE,SAAWA,EAAE,QAAUA,EAAE,UAI3BR,EAAmBL,EAAM,aAAa,GACxCU,EAAqBV,EAAM,aAAa,EAG1CC,EAAmB,GACrB,CAUA,SAASa,EAAcD,EAAG,CACxBZ,EAAmB,EACrB,CASA,SAASc,EAAQF,EAAG,CAEd,CAACR,EAAmBQ,EAAE,MAAM,IAI5BZ,GAAoBM,EAA8BM,EAAE,MAAM,IAC5DH,EAAqBG,EAAE,MAAM,CAEjC,CAMA,SAASG,EAAOH,EAAG,CACb,CAACR,EAAmBQ,EAAE,MAAM,IAK9BA,EAAE,OAAO,UAAU,SAAS,eAAe,GAC3CA,EAAE,OAAO,aAAa,0BAA0B,KAMhDX,EAA0B,GAC1B,OAAO,aAAaC,CAA8B,EAClDA,EAAiC,OAAO,WAAW,UAAW,CAC5DD,EAA0B,EAC5B,EAAG,GAAG,EACNS,EAAwBE,EAAE,MAAM,EAEpC,CAOA,SAASI,EAAmBJ,EAAG,CACzB,SAAS,kBAAoB,WAK3BX,IACFD,EAAmB,IAErBiB,EAA+B,EAEnC,CAQA,SAASA,GAAiC,CACxC,SAAS,iBAAiB,YAAaC,CAAoB,EAC3D,SAAS,iBAAiB,YAAaA,CAAoB,EAC3D,SAAS,iBAAiB,UAAWA,CAAoB,EACzD,SAAS,iBAAiB,cAAeA,CAAoB,EAC7D,SAAS,iBAAiB,cAAeA,CAAoB,EAC7D,SAAS,iBAAiB,YAAaA,CAAoB,EAC3D,SAAS,iBAAiB,YAAaA,CAAoB,EAC3D,SAAS,iBAAiB,aAAcA,CAAoB,EAC5D,SAAS,iBAAiB,WAAYA,CAAoB,CAC5D,CAEA,SAASC,GAAoC,CAC3C,SAAS,oBAAoB,YAAaD,CAAoB,EAC9D,SAAS,oBAAoB,YAAaA,CAAoB,EAC9D,SAAS,oBAAoB,UAAWA,CAAoB,EAC5D,SAAS,oBAAoB,cAAeA,CAAoB,EAChE,SAAS,oBAAoB,cAAeA,CAAoB,EAChE,SAAS,oBAAoB,YAAaA,CAAoB,EAC9D,SAAS,oBAAoB,YAAaA,CAAoB,EAC9D,SAAS,oBAAoB,aAAcA,CAAoB,EAC/D,SAAS,oBAAoB,WAAYA,CAAoB,CAC/D,CASA,SAASA,EAAqBN,EAAG,CAG3BA,EAAE,OAAO,UAAYA,EAAE,OAAO,SAAS,YAAY,IAAM,SAI7DZ,EAAmB,GACnBmB,EAAkC,EACpC,CAKA,SAAS,iBAAiB,UAAWR,EAAW,EAAI,EACpD,SAAS,iBAAiB,YAAaE,EAAe,EAAI,EAC1D,SAAS,iBAAiB,cAAeA,EAAe,EAAI,EAC5D,SAAS,iBAAiB,aAAcA,EAAe,EAAI,EAC3D,SAAS,iBAAiB,mBAAoBG,EAAoB,EAAI,EAEtEC,EAA+B,EAM/BlB,EAAM,iBAAiB,QAASe,EAAS,EAAI,EAC7Cf,EAAM,iBAAiB,OAAQgB,EAAQ,EAAI,EAOvChB,EAAM,WAAa,KAAK,wBAA0BA,EAAM,KAI1DA,EAAM,KAAK,aAAa,wBAAyB,EAAE,EAC1CA,EAAM,WAAa,KAAK,gBACjC,SAAS,gBAAgB,UAAU,IAAI,kBAAkB,EACzD,SAAS,gBAAgB,aAAa,wBAAyB,EAAE,EAErE,CAKA,GAAI,OAAO,QAAW,aAAe,OAAO,UAAa,YAAa,CAIpE,OAAO,0BAA4BD,EAInC,IAAIsB,EAEJ,GAAI,CACFA,EAAQ,IAAI,YAAY,8BAA8B,CACxD,OAASC,EAAP,CAEAD,EAAQ,SAAS,YAAY,aAAa,EAC1CA,EAAM,gBAAgB,+BAAgC,GAAO,GAAO,CAAC,CAAC,CACxE,CAEA,OAAO,cAAcA,CAAK,CAC5B,CAEI,OAAO,UAAa,aAGtBtB,EAA0B,QAAQ,CAGtC,CAAE,ICvTF,IAAAwB,GAAAC,GAAAC,IAAA,EAAC,SAASC,EAAQ,CAOhB,IAAIC,EAA6B,UAAW,CAC1C,GAAI,CACF,MAAO,CAAC,CAAC,OAAO,QAClB,OAASC,EAAP,CACA,MAAO,EACT,CACF,EAGIC,EAAoBF,EAA2B,EAE/CG,EAAiB,SAASC,EAAO,CACnC,IAAIC,EAAW,CACb,KAAM,UAAW,CACf,IAAIC,EAAQF,EAAM,MAAM,EACxB,MAAO,CAAE,KAAME,IAAU,OAAQ,MAAOA,CAAM,CAChD,CACF,EAEA,OAAIJ,IACFG,EAAS,OAAO,UAAY,UAAW,CACrC,OAAOA,CACT,GAGKA,CACT,EAMIE,EAAiB,SAASD,EAAO,CACnC,OAAO,mBAAmBA,CAAK,EAAE,QAAQ,OAAQ,GAAG,CACtD,EAEIE,EAAmB,SAASF,EAAO,CACrC,OAAO,mBAAmB,OAAOA,CAAK,EAAE,QAAQ,MAAO,GAAG,CAAC,CAC7D,EAEIG,EAA0B,UAAW,CAEvC,IAAIC,EAAkB,SAASC,EAAc,CAC3C,OAAO,eAAe,KAAM,WAAY,CAAE,SAAU,GAAM,MAAO,CAAC,CAAE,CAAC,EACrE,IAAIC,EAAqB,OAAOD,EAEhC,GAAIC,IAAuB,YAEpB,GAAIA,IAAuB,SAC5BD,IAAiB,IACnB,KAAK,YAAYA,CAAY,UAEtBA,aAAwBD,EAAiB,CAClD,IAAIG,EAAQ,KACZF,EAAa,QAAQ,SAASL,EAAOQ,EAAM,CACzCD,EAAM,OAAOC,EAAMR,CAAK,CAC1B,CAAC,CACH,SAAYK,IAAiB,MAAUC,IAAuB,SAC5D,GAAI,OAAO,UAAU,SAAS,KAAKD,CAAY,IAAM,iBACnD,QAASI,EAAI,EAAGA,EAAIJ,EAAa,OAAQI,IAAK,CAC5C,IAAIC,EAAQL,EAAaI,GACzB,GAAK,OAAO,UAAU,SAAS,KAAKC,CAAK,IAAM,kBAAsBA,EAAM,SAAW,EACpF,KAAK,OAAOA,EAAM,GAAIA,EAAM,EAAE,MAE9B,OAAM,IAAI,UAAU,4CAA8CD,EAAI,6BAA8B,CAExG,KAEA,SAASE,KAAON,EACVA,EAAa,eAAeM,CAAG,GACjC,KAAK,OAAOA,EAAKN,EAAaM,EAAI,MAKxC,OAAM,IAAI,UAAU,8CAA+C,CAEvE,EAEIC,EAAQR,EAAgB,UAE5BQ,EAAM,OAAS,SAASJ,EAAMR,EAAO,CAC/BQ,KAAQ,KAAK,SACf,KAAK,SAASA,GAAM,KAAK,OAAOR,CAAK,CAAC,EAEtC,KAAK,SAASQ,GAAQ,CAAC,OAAOR,CAAK,CAAC,CAExC,EAEAY,EAAM,OAAS,SAASJ,EAAM,CAC5B,OAAO,KAAK,SAASA,EACvB,EAEAI,EAAM,IAAM,SAASJ,EAAM,CACzB,OAAQA,KAAQ,KAAK,SAAY,KAAK,SAASA,GAAM,GAAK,IAC5D,EAEAI,EAAM,OAAS,SAASJ,EAAM,CAC5B,OAAQA,KAAQ,KAAK,SAAY,KAAK,SAASA,GAAM,MAAM,CAAC,EAAI,CAAC,CACnE,EAEAI,EAAM,IAAM,SAASJ,EAAM,CACzB,OAAQA,KAAQ,KAAK,QACvB,EAEAI,EAAM,IAAM,SAASJ,EAAMR,EAAO,CAChC,KAAK,SAASQ,GAAQ,CAAC,OAAOR,CAAK,CAAC,CACtC,EAEAY,EAAM,QAAU,SAASC,EAAUC,EAAS,CAC1C,IAAIC,EACJ,QAASP,KAAQ,KAAK,SACpB,GAAI,KAAK,SAAS,eAAeA,CAAI,EAAG,CACtCO,EAAU,KAAK,SAASP,GACxB,QAASC,EAAI,EAAGA,EAAIM,EAAQ,OAAQN,IAClCI,EAAS,KAAKC,EAASC,EAAQN,GAAID,EAAM,IAAI,CAEjD,CAEJ,EAEAI,EAAM,KAAO,UAAW,CACtB,IAAId,EAAQ,CAAC,EACb,YAAK,QAAQ,SAASE,EAAOQ,EAAM,CACjCV,EAAM,KAAKU,CAAI,CACjB,CAAC,EACMX,EAAeC,CAAK,CAC7B,EAEAc,EAAM,OAAS,UAAW,CACxB,IAAId,EAAQ,CAAC,EACb,YAAK,QAAQ,SAASE,EAAO,CAC3BF,EAAM,KAAKE,CAAK,CAClB,CAAC,EACMH,EAAeC,CAAK,CAC7B,EAEAc,EAAM,QAAU,UAAW,CACzB,IAAId,EAAQ,CAAC,EACb,YAAK,QAAQ,SAASE,EAAOQ,EAAM,CACjCV,EAAM,KAAK,CAACU,EAAMR,CAAK,CAAC,CAC1B,CAAC,EACMH,EAAeC,CAAK,CAC7B,EAEIF,IACFgB,EAAM,OAAO,UAAYA,EAAM,SAGjCA,EAAM,SAAW,UAAW,CAC1B,IAAII,EAAc,CAAC,EACnB,YAAK,QAAQ,SAAShB,EAAOQ,EAAM,CACjCQ,EAAY,KAAKf,EAAeO,CAAI,EAAI,IAAMP,EAAeD,CAAK,CAAC,CACrE,CAAC,EACMgB,EAAY,KAAK,GAAG,CAC7B,EAGAvB,EAAO,gBAAkBW,CAC3B,EAEIa,EAAkC,UAAW,CAC/C,GAAI,CACF,IAAIb,EAAkBX,EAAO,gBAE7B,OACG,IAAIW,EAAgB,MAAM,EAAE,SAAS,IAAM,OAC3C,OAAOA,EAAgB,UAAU,KAAQ,YACzC,OAAOA,EAAgB,UAAU,SAAY,UAElD,OAASc,EAAP,CACA,MAAO,EACT,CACF,EAEKD,EAAgC,GACnCd,EAAwB,EAG1B,IAAIS,EAAQnB,EAAO,gBAAgB,UAE/B,OAAOmB,EAAM,MAAS,aACxBA,EAAM,KAAO,UAAW,CACtB,IAAIL,EAAQ,KACRT,EAAQ,CAAC,EACb,KAAK,QAAQ,SAASE,EAAOQ,EAAM,CACjCV,EAAM,KAAK,CAACU,EAAMR,CAAK,CAAC,EACnBO,EAAM,UACTA,EAAM,OAAOC,CAAI,CAErB,CAAC,EACDV,EAAM,KAAK,SAASqB,EAAGC,EAAG,CACxB,OAAID,EAAE,GAAKC,EAAE,GACJ,GACED,EAAE,GAAKC,EAAE,GACX,EAEA,CAEX,CAAC,EACGb,EAAM,WACRA,EAAM,SAAW,CAAC,GAEpB,QAASE,EAAI,EAAGA,EAAIX,EAAM,OAAQW,IAChC,KAAK,OAAOX,EAAMW,GAAG,GAAIX,EAAMW,GAAG,EAAE,CAExC,GAGE,OAAOG,EAAM,aAAgB,YAC/B,OAAO,eAAeA,EAAO,cAAe,CAC1C,WAAY,GACZ,aAAc,GACd,SAAU,GACV,MAAO,SAASP,EAAc,CAC5B,GAAI,KAAK,SACP,KAAK,SAAW,CAAC,MACZ,CACL,IAAIgB,EAAO,CAAC,EACZ,KAAK,QAAQ,SAASrB,EAAOQ,EAAM,CACjCa,EAAK,KAAKb,CAAI,CAChB,CAAC,EACD,QAASC,EAAI,EAAGA,EAAIY,EAAK,OAAQZ,IAC/B,KAAK,OAAOY,EAAKZ,EAAE,CAEvB,CAEAJ,EAAeA,EAAa,QAAQ,MAAO,EAAE,EAG7C,QAFIiB,EAAajB,EAAa,MAAM,GAAG,EACnCkB,EACKd,EAAI,EAAGA,EAAIa,EAAW,OAAQb,IACrCc,EAAYD,EAAWb,GAAG,MAAM,GAAG,EACnC,KAAK,OACHP,EAAiBqB,EAAU,EAAE,EAC5BA,EAAU,OAAS,EAAKrB,EAAiBqB,EAAU,EAAE,EAAI,EAC5D,CAEJ,CACF,CAAC,CAKL,GACG,OAAO,QAAW,YAAe,OAC5B,OAAO,QAAW,YAAe,OACjC,OAAO,MAAS,YAAe,KAAO/B,EAC9C,GAEC,SAASC,EAAQ,CAOhB,IAAI+B,EAAwB,UAAW,CACrC,GAAI,CACF,IAAIC,EAAI,IAAIhC,EAAO,IAAI,IAAK,UAAU,EACtC,OAAAgC,EAAE,SAAW,MACLA,EAAE,OAAS,kBAAqBA,EAAE,YAC5C,OAASP,EAAP,CACA,MAAO,EACT,CACF,EAGIQ,EAAc,UAAW,CAC3B,IAAIC,EAAOlC,EAAO,IAEdmC,EAAM,SAASC,EAAKC,EAAM,CACxB,OAAOD,GAAQ,WAAUA,EAAM,OAAOA,CAAG,GACzCC,GAAQ,OAAOA,GAAS,WAAUA,EAAO,OAAOA,CAAI,GAGxD,IAAIC,EAAM,SAAUC,EACpB,GAAIF,IAASrC,EAAO,WAAa,QAAUqC,IAASrC,EAAO,SAAS,MAAO,CACzEqC,EAAOA,EAAK,YAAY,EACxBC,EAAM,SAAS,eAAe,mBAAmB,EAAE,EACnDC,EAAcD,EAAI,cAAc,MAAM,EACtCC,EAAY,KAAOF,EACnBC,EAAI,KAAK,YAAYC,CAAW,EAChC,GAAI,CACF,GAAIA,EAAY,KAAK,QAAQF,CAAI,IAAM,EAAG,MAAM,IAAI,MAAME,EAAY,IAAI,CAC5E,OAASC,EAAP,CACA,MAAM,IAAI,MAAM,0BAA4BH,EAAO,WAAaG,CAAG,CACrE,CACF,CAEA,IAAIC,EAAgBH,EAAI,cAAc,GAAG,EACzCG,EAAc,KAAOL,EACjBG,IACFD,EAAI,KAAK,YAAYG,CAAa,EAClCA,EAAc,KAAOA,EAAc,MAGrC,IAAIC,EAAeJ,EAAI,cAAc,OAAO,EAI5C,GAHAI,EAAa,KAAO,MACpBA,EAAa,MAAQN,EAEjBK,EAAc,WAAa,KAAO,CAAC,IAAI,KAAKA,EAAc,IAAI,GAAM,CAACC,EAAa,cAAc,GAAK,CAACL,EACxG,MAAM,IAAI,UAAU,aAAa,EAGnC,OAAO,eAAe,KAAM,iBAAkB,CAC5C,MAAOI,CACT,CAAC,EAID,IAAIE,EAAe,IAAI3C,EAAO,gBAAgB,KAAK,MAAM,EACrD4C,EAAqB,GACrBC,EAA2B,GAC3B/B,EAAQ,KACZ,CAAC,SAAU,SAAU,KAAK,EAAE,QAAQ,SAASgC,EAAY,CACvD,IAAIC,GAASJ,EAAaG,GAC1BH,EAAaG,GAAc,UAAW,CACpCC,GAAO,MAAMJ,EAAc,SAAS,EAChCC,IACFC,EAA2B,GAC3B/B,EAAM,OAAS6B,EAAa,SAAS,EACrCE,EAA2B,GAE/B,CACF,CAAC,EAED,OAAO,eAAe,KAAM,eAAgB,CAC1C,MAAOF,EACP,WAAY,EACd,CAAC,EAED,IAAIK,EAAS,OACb,OAAO,eAAe,KAAM,sBAAuB,CACjD,WAAY,GACZ,aAAc,GACd,SAAU,GACV,MAAO,UAAW,CACZ,KAAK,SAAWA,IAClBA,EAAS,KAAK,OACVH,IACFD,EAAqB,GACrB,KAAK,aAAa,YAAY,KAAK,MAAM,EACzCA,EAAqB,IAG3B,CACF,CAAC,CACH,EAEIzB,EAAQgB,EAAI,UAEZc,EAA6B,SAASC,EAAe,CACvD,OAAO,eAAe/B,EAAO+B,EAAe,CAC1C,IAAK,UAAW,CACd,OAAO,KAAK,eAAeA,EAC7B,EACA,IAAK,SAAS3C,EAAO,CACnB,KAAK,eAAe2C,GAAiB3C,CACvC,EACA,WAAY,EACd,CAAC,CACH,EAEA,CAAC,OAAQ,OAAQ,WAAY,OAAQ,UAAU,EAC5C,QAAQ,SAAS2C,EAAe,CAC/BD,EAA2BC,CAAa,CAC1C,CAAC,EAEH,OAAO,eAAe/B,EAAO,SAAU,CACrC,IAAK,UAAW,CACd,OAAO,KAAK,eAAe,MAC7B,EACA,IAAK,SAASZ,EAAO,CACnB,KAAK,eAAe,OAAYA,EAChC,KAAK,oBAAoB,CAC3B,EACA,WAAY,EACd,CAAC,EAED,OAAO,iBAAiBY,EAAO,CAE7B,SAAY,CACV,IAAK,UAAW,CACd,IAAIL,EAAQ,KACZ,OAAO,UAAW,CAChB,OAAOA,EAAM,IACf,CACF,CACF,EAEA,KAAQ,CACN,IAAK,UAAW,CACd,OAAO,KAAK,eAAe,KAAK,QAAQ,MAAO,EAAE,CACnD,EACA,IAAK,SAASP,EAAO,CACnB,KAAK,eAAe,KAAOA,EAC3B,KAAK,oBAAoB,CAC3B,EACA,WAAY,EACd,EAEA,SAAY,CACV,IAAK,UAAW,CACd,OAAO,KAAK,eAAe,SAAS,QAAQ,SAAU,GAAG,CAC3D,EACA,IAAK,SAASA,EAAO,CACnB,KAAK,eAAe,SAAWA,CACjC,EACA,WAAY,EACd,EAEA,OAAU,CACR,IAAK,UAAW,CAEd,IAAI4C,EAAe,CAAE,QAAS,GAAI,SAAU,IAAK,OAAQ,EAAG,EAAE,KAAK,eAAe,UAI9EC,EAAkB,KAAK,eAAe,MAAQD,GAChD,KAAK,eAAe,OAAS,GAE/B,OAAO,KAAK,eAAe,SACzB,KACA,KAAK,eAAe,UACnBC,EAAmB,IAAM,KAAK,eAAe,KAAQ,GAC1D,EACA,WAAY,EACd,EAEA,SAAY,CACV,IAAK,UAAW,CACd,MAAO,EACT,EACA,IAAK,SAAS7C,EAAO,CACrB,EACA,WAAY,EACd,EAEA,SAAY,CACV,IAAK,UAAW,CACd,MAAO,EACT,EACA,IAAK,SAASA,EAAO,CACrB,EACA,WAAY,EACd,CACF,CAAC,EAED4B,EAAI,gBAAkB,SAASkB,EAAM,CACnC,OAAOnB,EAAK,gBAAgB,MAAMA,EAAM,SAAS,CACnD,EAEAC,EAAI,gBAAkB,SAASC,EAAK,CAClC,OAAOF,EAAK,gBAAgB,MAAMA,EAAM,SAAS,CACnD,EAEAlC,EAAO,IAAMmC,CAEf,EAMA,GAJKJ,EAAsB,GACzBE,EAAY,EAGTjC,EAAO,WAAa,QAAW,EAAE,WAAYA,EAAO,UAAW,CAClE,IAAIsD,EAAY,UAAW,CACzB,OAAOtD,EAAO,SAAS,SAAW,KAAOA,EAAO,SAAS,UAAYA,EAAO,SAAS,KAAQ,IAAMA,EAAO,SAAS,KAAQ,GAC7H,EAEA,GAAI,CACF,OAAO,eAAeA,EAAO,SAAU,SAAU,CAC/C,IAAKsD,EACL,WAAY,EACd,CAAC,CACH,OAAS7B,EAAP,CACA,YAAY,UAAW,CACrBzB,EAAO,SAAS,OAASsD,EAAU,CACrC,EAAG,GAAG,CACR,CACF,CAEF,GACG,OAAO,QAAW,YAAe,OAC5B,OAAO,QAAW,YAAe,OACjC,OAAO,MAAS,YAAe,KAAOvD,EAC9C,IC5eA,IAAAwD,GAAAC,GAAA,CAAAC,GAAAC,KAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gFAeA,IAAIC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,IACH,SAAUC,EAAS,CAChB,IAAIC,EAAO,OAAO,QAAW,SAAW,OAAS,OAAO,MAAS,SAAW,KAAO,OAAO,MAAS,SAAW,KAAO,CAAC,EAClH,OAAO,QAAW,YAAc,OAAO,IACvC,OAAO,QAAS,CAAC,SAAS,EAAG,SAAU3B,EAAS,CAAE0B,EAAQE,EAAeD,EAAMC,EAAe5B,CAAO,CAAC,CAAC,CAAG,CAAC,EAEtG,OAAOC,IAAW,UAAY,OAAOA,GAAO,SAAY,SAC7DyB,EAAQE,EAAeD,EAAMC,EAAe3B,GAAO,OAAO,CAAC,CAAC,EAG5DyB,EAAQE,EAAeD,CAAI,CAAC,EAEhC,SAASC,EAAe5B,EAAS6B,EAAU,CACvC,OAAI7B,IAAY2B,IACR,OAAO,OAAO,QAAW,WACzB,OAAO,eAAe3B,EAAS,aAAc,CAAE,MAAO,EAAK,CAAC,EAG5DA,EAAQ,WAAa,IAGtB,SAAU8B,EAAIC,EAAG,CAAE,OAAO/B,EAAQ8B,GAAMD,EAAWA,EAASC,EAAIC,CAAC,EAAIA,CAAG,CACnF,CACJ,GACC,SAAUC,EAAU,CACjB,IAAIC,EAAgB,OAAO,gBACtB,CAAE,UAAW,CAAC,CAAE,YAAa,OAAS,SAAUC,EAAGC,EAAG,CAAED,EAAE,UAAYC,CAAG,GAC1E,SAAUD,EAAGC,EAAG,CAAE,QAASC,KAAKD,EAAO,OAAO,UAAU,eAAe,KAAKA,EAAGC,CAAC,IAAGF,EAAEE,GAAKD,EAAEC,GAAI,EAEpGlC,GAAY,SAAUgC,EAAGC,EAAG,CACxB,GAAI,OAAOA,GAAM,YAAcA,IAAM,KACjC,MAAM,IAAI,UAAU,uBAAyB,OAAOA,CAAC,EAAI,+BAA+B,EAC5FF,EAAcC,EAAGC,CAAC,EAClB,SAASE,GAAK,CAAE,KAAK,YAAcH,CAAG,CACtCA,EAAE,UAAYC,IAAM,KAAO,OAAO,OAAOA,CAAC,GAAKE,EAAG,UAAYF,EAAE,UAAW,IAAIE,EACnF,EAEAlC,GAAW,OAAO,QAAU,SAAUmC,EAAG,CACrC,QAASC,EAAG,EAAI,EAAGC,EAAI,UAAU,OAAQ,EAAIA,EAAG,IAAK,CACjDD,EAAI,UAAU,GACd,QAASH,KAAKG,EAAO,OAAO,UAAU,eAAe,KAAKA,EAAGH,CAAC,IAAGE,EAAEF,GAAKG,EAAEH,GAC9E,CACA,OAAOE,CACX,EAEAlC,GAAS,SAAUmC,EAAGE,EAAG,CACrB,IAAIH,EAAI,CAAC,EACT,QAASF,KAAKG,EAAO,OAAO,UAAU,eAAe,KAAKA,EAAGH,CAAC,GAAKK,EAAE,QAAQL,CAAC,EAAI,IAC9EE,EAAEF,GAAKG,EAAEH,IACb,GAAIG,GAAK,MAAQ,OAAO,OAAO,uBAA0B,WACrD,QAASG,EAAI,EAAGN,EAAI,OAAO,sBAAsBG,CAAC,EAAGG,EAAIN,EAAE,OAAQM,IAC3DD,EAAE,QAAQL,EAAEM,EAAE,EAAI,GAAK,OAAO,UAAU,qBAAqB,KAAKH,EAAGH,EAAEM,EAAE,IACzEJ,EAAEF,EAAEM,IAAMH,EAAEH,EAAEM,KAE1B,OAAOJ,CACX,EAEAjC,GAAa,SAAUsC,EAAYC,EAAQC,EAAKC,EAAM,CAClD,IAAIC,EAAI,UAAU,OAAQC,EAAID,EAAI,EAAIH,EAASE,IAAS,KAAOA,EAAO,OAAO,yBAAyBF,EAAQC,CAAG,EAAIC,EAAMZ,EAC3H,GAAI,OAAO,SAAY,UAAY,OAAO,QAAQ,UAAa,WAAYc,EAAI,QAAQ,SAASL,EAAYC,EAAQC,EAAKC,CAAI,MACxH,SAASJ,EAAIC,EAAW,OAAS,EAAGD,GAAK,EAAGA,KAASR,EAAIS,EAAWD,MAAIM,GAAKD,EAAI,EAAIb,EAAEc,CAAC,EAAID,EAAI,EAAIb,EAAEU,EAAQC,EAAKG,CAAC,EAAId,EAAEU,EAAQC,CAAG,IAAMG,GAChJ,OAAOD,EAAI,GAAKC,GAAK,OAAO,eAAeJ,EAAQC,EAAKG,CAAC,EAAGA,CAChE,EAEA1C,GAAU,SAAU2C,EAAYC,EAAW,CACvC,OAAO,SAAUN,EAAQC,EAAK,CAAEK,EAAUN,EAAQC,EAAKI,CAAU,CAAG,CACxE,EAEA1C,GAAa,SAAU4C,EAAaC,EAAe,CAC/C,GAAI,OAAO,SAAY,UAAY,OAAO,QAAQ,UAAa,WAAY,OAAO,QAAQ,SAASD,EAAaC,CAAa,CACjI,EAEA5C,GAAY,SAAU6C,EAASC,EAAYC,EAAGC,EAAW,CACrD,SAASC,EAAMC,EAAO,CAAE,OAAOA,aAAiBH,EAAIG,EAAQ,IAAIH,EAAE,SAAUI,EAAS,CAAEA,EAAQD,CAAK,CAAG,CAAC,CAAG,CAC3G,OAAO,IAAKH,IAAMA,EAAI,UAAU,SAAUI,EAASC,EAAQ,CACvD,SAASC,EAAUH,EAAO,CAAE,GAAI,CAAEI,EAAKN,EAAU,KAAKE,CAAK,CAAC,CAAG,OAASjB,EAAP,CAAYmB,EAAOnB,CAAC,CAAG,CAAE,CAC1F,SAASsB,EAASL,EAAO,CAAE,GAAI,CAAEI,EAAKN,EAAU,MAASE,CAAK,CAAC,CAAG,OAASjB,EAAP,CAAYmB,EAAOnB,CAAC,CAAG,CAAE,CAC7F,SAASqB,EAAKE,EAAQ,CAAEA,EAAO,KAAOL,EAAQK,EAAO,KAAK,EAAIP,EAAMO,EAAO,KAAK,EAAE,KAAKH,EAAWE,CAAQ,CAAG,CAC7GD,GAAMN,EAAYA,EAAU,MAAMH,EAASC,GAAc,CAAC,CAAC,GAAG,KAAK,CAAC,CACxE,CAAC,CACL,EAEA7C,GAAc,SAAU4C,EAASY,EAAM,CACnC,IAAIC,EAAI,CAAE,MAAO,EAAG,KAAM,UAAW,CAAE,GAAI5B,EAAE,GAAK,EAAG,MAAMA,EAAE,GAAI,OAAOA,EAAE,EAAI,EAAG,KAAM,CAAC,EAAG,IAAK,CAAC,CAAE,EAAG6B,EAAGC,EAAG9B,EAAG+B,EAC/G,OAAOA,EAAI,CAAE,KAAMC,EAAK,CAAC,EAAG,MAASA,EAAK,CAAC,EAAG,OAAUA,EAAK,CAAC,CAAE,EAAG,OAAO,QAAW,aAAeD,EAAE,OAAO,UAAY,UAAW,CAAE,OAAO,IAAM,GAAIA,EACvJ,SAASC,EAAK9B,EAAG,CAAE,OAAO,SAAUT,EAAG,CAAE,OAAO+B,EAAK,CAACtB,EAAGT,CAAC,CAAC,CAAG,CAAG,CACjE,SAAS+B,EAAKS,EAAI,CACd,GAAIJ,EAAG,MAAM,IAAI,UAAU,iCAAiC,EAC5D,KAAOD,GAAG,GAAI,CACV,GAAIC,EAAI,EAAGC,IAAM9B,EAAIiC,EAAG,GAAK,EAAIH,EAAE,OAAYG,EAAG,GAAKH,EAAE,SAAc9B,EAAI8B,EAAE,SAAc9B,EAAE,KAAK8B,CAAC,EAAG,GAAKA,EAAE,OAAS,EAAE9B,EAAIA,EAAE,KAAK8B,EAAGG,EAAG,EAAE,GAAG,KAAM,OAAOjC,EAE3J,OADI8B,EAAI,EAAG9B,IAAGiC,EAAK,CAACA,EAAG,GAAK,EAAGjC,EAAE,KAAK,GAC9BiC,EAAG,GAAI,CACX,IAAK,GAAG,IAAK,GAAGjC,EAAIiC,EAAI,MACxB,IAAK,GAAG,OAAAL,EAAE,QAAgB,CAAE,MAAOK,EAAG,GAAI,KAAM,EAAM,EACtD,IAAK,GAAGL,EAAE,QAASE,EAAIG,EAAG,GAAIA,EAAK,CAAC,CAAC,EAAG,SACxC,IAAK,GAAGA,EAAKL,EAAE,IAAI,IAAI,EAAGA,EAAE,KAAK,IAAI,EAAG,SACxC,QACI,GAAM5B,EAAI4B,EAAE,KAAM,EAAA5B,EAAIA,EAAE,OAAS,GAAKA,EAAEA,EAAE,OAAS,MAAQiC,EAAG,KAAO,GAAKA,EAAG,KAAO,GAAI,CAAEL,EAAI,EAAG,QAAU,CAC3G,GAAIK,EAAG,KAAO,IAAM,CAACjC,GAAMiC,EAAG,GAAKjC,EAAE,IAAMiC,EAAG,GAAKjC,EAAE,IAAM,CAAE4B,EAAE,MAAQK,EAAG,GAAI,KAAO,CACrF,GAAIA,EAAG,KAAO,GAAKL,EAAE,MAAQ5B,EAAE,GAAI,CAAE4B,EAAE,MAAQ5B,EAAE,GAAIA,EAAIiC,EAAI,KAAO,CACpE,GAAIjC,GAAK4B,EAAE,MAAQ5B,EAAE,GAAI,CAAE4B,EAAE,MAAQ5B,EAAE,GAAI4B,EAAE,IAAI,KAAKK,CAAE,EAAG,KAAO,CAC9DjC,EAAE,IAAI4B,EAAE,IAAI,IAAI,EACpBA,EAAE,KAAK,IAAI,EAAG,QACtB,CACAK,EAAKN,EAAK,KAAKZ,EAASa,CAAC,CAC7B,OAASzB,EAAP,CAAY8B,EAAK,CAAC,EAAG9B,CAAC,EAAG2B,EAAI,CAAG,QAAE,CAAUD,EAAI7B,EAAI,CAAG,CACzD,GAAIiC,EAAG,GAAK,EAAG,MAAMA,EAAG,GAAI,MAAO,CAAE,MAAOA,EAAG,GAAKA,EAAG,GAAK,OAAQ,KAAM,EAAK,CACnF,CACJ,EAEA7D,GAAe,SAAS8D,EAAG,EAAG,CAC1B,QAASpC,KAAKoC,EAAOpC,IAAM,WAAa,CAAC,OAAO,UAAU,eAAe,KAAK,EAAGA,CAAC,GAAGX,GAAgB,EAAG+C,EAAGpC,CAAC,CAChH,EAEAX,GAAkB,OAAO,OAAU,SAASgD,EAAGD,EAAGE,EAAGC,EAAI,CACjDA,IAAO,SAAWA,EAAKD,GAC3B,OAAO,eAAeD,EAAGE,EAAI,CAAE,WAAY,GAAM,IAAK,UAAW,CAAE,OAAOH,EAAEE,EAAI,CAAE,CAAC,CACvF,EAAM,SAASD,EAAGD,EAAGE,EAAGC,EAAI,CACpBA,IAAO,SAAWA,EAAKD,GAC3BD,EAAEE,GAAMH,EAAEE,EACd,EAEA/D,GAAW,SAAU8D,EAAG,CACpB,IAAIlC,EAAI,OAAO,QAAW,YAAc,OAAO,SAAUiC,EAAIjC,GAAKkC,EAAElC,GAAIG,EAAI,EAC5E,GAAI8B,EAAG,OAAOA,EAAE,KAAKC,CAAC,EACtB,GAAIA,GAAK,OAAOA,EAAE,QAAW,SAAU,MAAO,CAC1C,KAAM,UAAY,CACd,OAAIA,GAAK/B,GAAK+B,EAAE,SAAQA,EAAI,QACrB,CAAE,MAAOA,GAAKA,EAAE/B,KAAM,KAAM,CAAC+B,CAAE,CAC1C,CACJ,EACA,MAAM,IAAI,UAAUlC,EAAI,0BAA4B,iCAAiC,CACzF,EAEA3B,GAAS,SAAU6D,EAAGjC,EAAG,CACrB,IAAIgC,EAAI,OAAO,QAAW,YAAcC,EAAE,OAAO,UACjD,GAAI,CAACD,EAAG,OAAOC,EACf,IAAI/B,EAAI8B,EAAE,KAAKC,CAAC,EAAGzB,EAAG4B,EAAK,CAAC,EAAGnC,EAC/B,GAAI,CACA,MAAQD,IAAM,QAAUA,KAAM,IAAM,EAAEQ,EAAIN,EAAE,KAAK,GAAG,MAAMkC,EAAG,KAAK5B,EAAE,KAAK,CAC7E,OACO6B,EAAP,CAAgBpC,EAAI,CAAE,MAAOoC,CAAM,CAAG,QACtC,CACI,GAAI,CACI7B,GAAK,CAACA,EAAE,OAASwB,EAAI9B,EAAE,SAAY8B,EAAE,KAAK9B,CAAC,CACnD,QACA,CAAU,GAAID,EAAG,MAAMA,EAAE,KAAO,CACpC,CACA,OAAOmC,CACX,EAGA/D,GAAW,UAAY,CACnB,QAAS+D,EAAK,CAAC,EAAGlC,EAAI,EAAGA,EAAI,UAAU,OAAQA,IAC3CkC,EAAKA,EAAG,OAAOhE,GAAO,UAAU8B,EAAE,CAAC,EACvC,OAAOkC,CACX,EAGA9D,GAAiB,UAAY,CACzB,QAASyB,EAAI,EAAGG,EAAI,EAAGoC,EAAK,UAAU,OAAQpC,EAAIoC,EAAIpC,IAAKH,GAAK,UAAUG,GAAG,OAC7E,QAASM,EAAI,MAAMT,CAAC,EAAGmC,EAAI,EAAGhC,EAAI,EAAGA,EAAIoC,EAAIpC,IACzC,QAASqC,EAAI,UAAUrC,GAAIsC,EAAI,EAAGC,EAAKF,EAAE,OAAQC,EAAIC,EAAID,IAAKN,IAC1D1B,EAAE0B,GAAKK,EAAEC,GACjB,OAAOhC,CACX,EAEAjC,GAAgB,SAAUmE,EAAIC,EAAMC,EAAM,CACtC,GAAIA,GAAQ,UAAU,SAAW,EAAG,QAAS1C,EAAI,EAAG2C,EAAIF,EAAK,OAAQP,EAAIlC,EAAI2C,EAAG3C,KACxEkC,GAAM,EAAElC,KAAKyC,MACRP,IAAIA,EAAK,MAAM,UAAU,MAAM,KAAKO,EAAM,EAAGzC,CAAC,GACnDkC,EAAGlC,GAAKyC,EAAKzC,IAGrB,OAAOwC,EAAG,OAAON,GAAM,MAAM,UAAU,MAAM,KAAKO,CAAI,CAAC,CAC3D,EAEAnE,GAAU,SAAUe,EAAG,CACnB,OAAO,gBAAgBf,IAAW,KAAK,EAAIe,EAAG,MAAQ,IAAIf,GAAQe,CAAC,CACvE,EAEAd,GAAmB,SAAUoC,EAASC,EAAYE,EAAW,CACzD,GAAI,CAAC,OAAO,cAAe,MAAM,IAAI,UAAU,sCAAsC,EACrF,IAAIa,EAAIb,EAAU,MAAMH,EAASC,GAAc,CAAC,CAAC,EAAGZ,EAAG4C,EAAI,CAAC,EAC5D,OAAO5C,EAAI,CAAC,EAAG4B,EAAK,MAAM,EAAGA,EAAK,OAAO,EAAGA,EAAK,QAAQ,EAAG5B,EAAE,OAAO,eAAiB,UAAY,CAAE,OAAO,IAAM,EAAGA,EACpH,SAAS4B,EAAK9B,EAAG,CAAM6B,EAAE7B,KAAIE,EAAEF,GAAK,SAAUT,EAAG,CAAE,OAAO,IAAI,QAAQ,SAAUgD,EAAG5C,EAAG,CAAEmD,EAAE,KAAK,CAAC9C,EAAGT,EAAGgD,EAAG5C,CAAC,CAAC,EAAI,GAAKoD,EAAO/C,EAAGT,CAAC,CAAG,CAAC,CAAG,EAAG,CACzI,SAASwD,EAAO/C,EAAGT,EAAG,CAAE,GAAI,CAAE+B,EAAKO,EAAE7B,GAAGT,CAAC,CAAC,CAAG,OAASU,EAAP,CAAY+C,EAAOF,EAAE,GAAG,GAAI7C,CAAC,CAAG,CAAE,CACjF,SAASqB,EAAKd,EAAG,CAAEA,EAAE,iBAAiBhC,GAAU,QAAQ,QAAQgC,EAAE,MAAM,CAAC,EAAE,KAAKyC,EAAS7B,CAAM,EAAI4B,EAAOF,EAAE,GAAG,GAAItC,CAAC,CAAI,CACxH,SAASyC,EAAQ/B,EAAO,CAAE6B,EAAO,OAAQ7B,CAAK,CAAG,CACjD,SAASE,EAAOF,EAAO,CAAE6B,EAAO,QAAS7B,CAAK,CAAG,CACjD,SAAS8B,EAAOrB,EAAGpC,EAAG,CAAMoC,EAAEpC,CAAC,EAAGuD,EAAE,MAAM,EAAGA,EAAE,QAAQC,EAAOD,EAAE,GAAG,GAAIA,EAAE,GAAG,EAAE,CAAG,CACrF,EAEApE,GAAmB,SAAUuD,EAAG,CAC5B,IAAI/B,EAAGN,EACP,OAAOM,EAAI,CAAC,EAAG4B,EAAK,MAAM,EAAGA,EAAK,QAAS,SAAU7B,EAAG,CAAE,MAAMA,CAAG,CAAC,EAAG6B,EAAK,QAAQ,EAAG5B,EAAE,OAAO,UAAY,UAAY,CAAE,OAAO,IAAM,EAAGA,EAC1I,SAAS4B,EAAK9B,EAAG2B,EAAG,CAAEzB,EAAEF,GAAKiC,EAAEjC,GAAK,SAAUT,EAAG,CAAE,OAAQK,EAAI,CAACA,GAAK,CAAE,MAAOpB,GAAQyD,EAAEjC,GAAGT,CAAC,CAAC,EAAG,KAAMS,IAAM,QAAS,EAAI2B,EAAIA,EAAEpC,CAAC,EAAIA,CAAG,EAAIoC,CAAG,CAClJ,EAEAhD,GAAgB,SAAUsD,EAAG,CACzB,GAAI,CAAC,OAAO,cAAe,MAAM,IAAI,UAAU,sCAAsC,EACrF,IAAID,EAAIC,EAAE,OAAO,eAAgB,EACjC,OAAOD,EAAIA,EAAE,KAAKC,CAAC,GAAKA,EAAI,OAAO9D,IAAa,WAAaA,GAAS8D,CAAC,EAAIA,EAAE,OAAO,UAAU,EAAG,EAAI,CAAC,EAAGH,EAAK,MAAM,EAAGA,EAAK,OAAO,EAAGA,EAAK,QAAQ,EAAG,EAAE,OAAO,eAAiB,UAAY,CAAE,OAAO,IAAM,EAAG,GAC9M,SAASA,EAAK9B,EAAG,CAAE,EAAEA,GAAKiC,EAAEjC,IAAM,SAAUT,EAAG,CAAE,OAAO,IAAI,QAAQ,SAAU4B,EAASC,EAAQ,CAAE7B,EAAI0C,EAAEjC,GAAGT,CAAC,EAAGyD,EAAO7B,EAASC,EAAQ7B,EAAE,KAAMA,EAAE,KAAK,CAAG,CAAC,CAAG,CAAG,CAC/J,SAASyD,EAAO7B,EAASC,EAAQ1B,EAAGH,EAAG,CAAE,QAAQ,QAAQA,CAAC,EAAE,KAAK,SAASA,EAAG,CAAE4B,EAAQ,CAAE,MAAO5B,EAAG,KAAMG,CAAE,CAAC,CAAG,EAAG0B,CAAM,CAAG,CAC/H,EAEAxC,GAAuB,SAAUsE,EAAQC,EAAK,CAC1C,OAAI,OAAO,eAAkB,OAAO,eAAeD,EAAQ,MAAO,CAAE,MAAOC,CAAI,CAAC,EAAYD,EAAO,IAAMC,EAClGD,CACX,EAEA,IAAIE,EAAqB,OAAO,OAAU,SAASnB,EAAG1C,EAAG,CACrD,OAAO,eAAe0C,EAAG,UAAW,CAAE,WAAY,GAAM,MAAO1C,CAAE,CAAC,CACtE,EAAK,SAAS0C,EAAG1C,EAAG,CAChB0C,EAAE,QAAa1C,CACnB,EAEAV,GAAe,SAAUwE,EAAK,CAC1B,GAAIA,GAAOA,EAAI,WAAY,OAAOA,EAClC,IAAI7B,EAAS,CAAC,EACd,GAAI6B,GAAO,KAAM,QAASnB,KAAKmB,EAASnB,IAAM,WAAa,OAAO,UAAU,eAAe,KAAKmB,EAAKnB,CAAC,GAAGjD,GAAgBuC,EAAQ6B,EAAKnB,CAAC,EACvI,OAAAkB,EAAmB5B,EAAQ6B,CAAG,EACvB7B,CACX,EAEA1C,GAAkB,SAAUuE,EAAK,CAC7B,OAAQA,GAAOA,EAAI,WAAcA,EAAM,CAAE,QAAWA,CAAI,CAC5D,EAEAtE,GAAyB,SAAUuE,EAAUC,EAAOC,EAAM7B,EAAG,CACzD,GAAI6B,IAAS,KAAO,CAAC7B,EAAG,MAAM,IAAI,UAAU,+CAA+C,EAC3F,GAAI,OAAO4B,GAAU,WAAaD,IAAaC,GAAS,CAAC5B,EAAI,CAAC4B,EAAM,IAAID,CAAQ,EAAG,MAAM,IAAI,UAAU,0EAA0E,EACjL,OAAOE,IAAS,IAAM7B,EAAI6B,IAAS,IAAM7B,EAAE,KAAK2B,CAAQ,EAAI3B,EAAIA,EAAE,MAAQ4B,EAAM,IAAID,CAAQ,CAChG,EAEAtE,GAAyB,SAAUsE,EAAUC,EAAOrC,EAAOsC,EAAM7B,EAAG,CAChE,GAAI6B,IAAS,IAAK,MAAM,IAAI,UAAU,gCAAgC,EACtE,GAAIA,IAAS,KAAO,CAAC7B,EAAG,MAAM,IAAI,UAAU,+CAA+C,EAC3F,GAAI,OAAO4B,GAAU,WAAaD,IAAaC,GAAS,CAAC5B,EAAI,CAAC4B,EAAM,IAAID,CAAQ,EAAG,MAAM,IAAI,UAAU,yEAAyE,EAChL,OAAQE,IAAS,IAAM7B,EAAE,KAAK2B,EAAUpC,CAAK,EAAIS,EAAIA,EAAE,MAAQT,EAAQqC,EAAM,IAAID,EAAUpC,CAAK,EAAIA,CACxG,EAEA1B,EAAS,YAAa9B,EAAS,EAC/B8B,EAAS,WAAY7B,EAAQ,EAC7B6B,EAAS,SAAU5B,EAAM,EACzB4B,EAAS,aAAc3B,EAAU,EACjC2B,EAAS,UAAW1B,EAAO,EAC3B0B,EAAS,aAAczB,EAAU,EACjCyB,EAAS,YAAaxB,EAAS,EAC/BwB,EAAS,cAAevB,EAAW,EACnCuB,EAAS,eAAgBtB,EAAY,EACrCsB,EAAS,kBAAmBP,EAAe,EAC3CO,EAAS,WAAYrB,EAAQ,EAC7BqB,EAAS,SAAUpB,EAAM,EACzBoB,EAAS,WAAYnB,EAAQ,EAC7BmB,EAAS,iBAAkBlB,EAAc,EACzCkB,EAAS,gBAAiBjB,EAAa,EACvCiB,EAAS,UAAWhB,EAAO,EAC3BgB,EAAS,mBAAoBf,EAAgB,EAC7Ce,EAAS,mBAAoBd,EAAgB,EAC7Cc,EAAS,gBAAiBb,EAAa,EACvCa,EAAS,uBAAwBZ,EAAoB,EACrDY,EAAS,eAAgBX,EAAY,EACrCW,EAAS,kBAAmBV,EAAe,EAC3CU,EAAS,yBAA0BT,EAAsB,EACzDS,EAAS,yBAA0BR,EAAsB,CAC7D,CAAC,ICjTD,IAAAyE,GAAAC,GAAA,CAAAC,GAAAC,KAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAMC,SAA0CC,EAAMC,EAAS,CACtD,OAAOH,IAAY,UAAY,OAAOC,IAAW,SACnDA,GAAO,QAAUE,EAAQ,EAClB,OAAO,QAAW,YAAc,OAAO,IAC9C,OAAO,CAAC,EAAGA,CAAO,EACX,OAAOH,IAAY,SAC1BA,GAAQ,YAAiBG,EAAQ,EAEjCD,EAAK,YAAiBC,EAAQ,CAChC,GAAGH,GAAM,UAAW,CACpB,OAAiB,UAAW,CAClB,IAAII,EAAuB,CAE/B,IACC,SAASC,EAAyBC,EAAqBC,EAAqB,CAEnF,aAGAA,EAAoB,EAAED,EAAqB,CACzC,QAAW,UAAW,CAAE,OAAqBE,EAAW,CAC1D,CAAC,EAGD,IAAIC,EAAeF,EAAoB,GAAG,EACtCG,EAAoCH,EAAoB,EAAEE,CAAY,EAEtEE,EAASJ,EAAoB,GAAG,EAChCK,EAA8BL,EAAoB,EAAEI,CAAM,EAE1DE,EAAaN,EAAoB,GAAG,EACpCO,EAA8BP,EAAoB,EAAEM,CAAU,EAOlE,SAASE,EAAQC,EAAM,CACrB,GAAI,CACF,OAAO,SAAS,YAAYA,CAAI,CAClC,OAASC,EAAP,CACA,MAAO,EACT,CACF,CAUA,IAAIC,EAAqB,SAA4BC,EAAQ,CAC3D,IAAIC,EAAeN,EAAe,EAAEK,CAAM,EAC1C,OAAAJ,EAAQ,KAAK,EACNK,CACT,EAEiCC,EAAeH,EAOhD,SAASI,EAAkBC,EAAO,CAChC,IAAIC,EAAQ,SAAS,gBAAgB,aAAa,KAAK,IAAM,MACzDC,EAAc,SAAS,cAAc,UAAU,EAEnDA,EAAY,MAAM,SAAW,OAE7BA,EAAY,MAAM,OAAS,IAC3BA,EAAY,MAAM,QAAU,IAC5BA,EAAY,MAAM,OAAS,IAE3BA,EAAY,MAAM,SAAW,WAC7BA,EAAY,MAAMD,EAAQ,QAAU,QAAU,UAE9C,IAAIE,EAAY,OAAO,aAAe,SAAS,gBAAgB,UAC/D,OAAAD,EAAY,MAAM,IAAM,GAAG,OAAOC,EAAW,IAAI,EACjDD,EAAY,aAAa,WAAY,EAAE,EACvCA,EAAY,MAAQF,EACbE,CACT,CAYA,IAAIE,EAAiB,SAAwBJ,EAAOK,EAAS,CAC3D,IAAIH,EAAcH,EAAkBC,CAAK,EACzCK,EAAQ,UAAU,YAAYH,CAAW,EACzC,IAAIL,EAAeN,EAAe,EAAEW,CAAW,EAC/C,OAAAV,EAAQ,MAAM,EACdU,EAAY,OAAO,EACZL,CACT,EASIS,EAAsB,SAA6BV,EAAQ,CAC7D,IAAIS,EAAU,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAChF,UAAW,SAAS,IACtB,EACIR,EAAe,GAEnB,OAAI,OAAOD,GAAW,SACpBC,EAAeO,EAAeR,EAAQS,CAAO,EACpCT,aAAkB,kBAAoB,CAAC,CAAC,OAAQ,SAAU,MAAO,MAAO,UAAU,EAAE,SAASA,GAAW,KAA4B,OAASA,EAAO,IAAI,EAEjKC,EAAeO,EAAeR,EAAO,MAAOS,CAAO,GAEnDR,EAAeN,EAAe,EAAEK,CAAM,EACtCJ,EAAQ,MAAM,GAGTK,CACT,EAEiCU,EAAgBD,EAEjD,SAASE,EAAQC,EAAK,CAA6B,OAAI,OAAO,QAAW,YAAc,OAAO,OAAO,UAAa,SAAYD,EAAU,SAAiBC,EAAK,CAAE,OAAO,OAAOA,CAAK,EAAYD,EAAU,SAAiBC,EAAK,CAAE,OAAOA,GAAO,OAAO,QAAW,YAAcA,EAAI,cAAgB,QAAUA,IAAQ,OAAO,UAAY,SAAW,OAAOA,CAAK,EAAYD,EAAQC,CAAG,CAAG,CAUzX,IAAIC,GAAyB,UAAkC,CAC7D,IAAIL,EAAU,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAAC,EAE/EM,EAAkBN,EAAQ,OAC1BO,EAASD,IAAoB,OAAS,OAASA,EAC/CE,EAAYR,EAAQ,UACpBT,EAASS,EAAQ,OACjBS,GAAOT,EAAQ,KAEnB,GAAIO,IAAW,QAAUA,IAAW,MAClC,MAAM,IAAI,MAAM,oDAAoD,EAItE,GAAIhB,IAAW,OACb,GAAIA,GAAUY,EAAQZ,CAAM,IAAM,UAAYA,EAAO,WAAa,EAAG,CACnE,GAAIgB,IAAW,QAAUhB,EAAO,aAAa,UAAU,EACrD,MAAM,IAAI,MAAM,mFAAmF,EAGrG,GAAIgB,IAAW,QAAUhB,EAAO,aAAa,UAAU,GAAKA,EAAO,aAAa,UAAU,GACxF,MAAM,IAAI,MAAM,uGAAwG,CAE5H,KACE,OAAM,IAAI,MAAM,6CAA6C,EAKjE,GAAIkB,GACF,OAAOP,EAAaO,GAAM,CACxB,UAAWD,CACb,CAAC,EAIH,GAAIjB,EACF,OAAOgB,IAAW,MAAQd,EAAYF,CAAM,EAAIW,EAAaX,EAAQ,CACnE,UAAWiB,CACb,CAAC,CAEL,EAEiCE,GAAmBL,GAEpD,SAASM,GAAiBP,EAAK,CAA6B,OAAI,OAAO,QAAW,YAAc,OAAO,OAAO,UAAa,SAAYO,GAAmB,SAAiBP,EAAK,CAAE,OAAO,OAAOA,CAAK,EAAYO,GAAmB,SAAiBP,EAAK,CAAE,OAAOA,GAAO,OAAO,QAAW,YAAcA,EAAI,cAAgB,QAAUA,IAAQ,OAAO,UAAY,SAAW,OAAOA,CAAK,EAAYO,GAAiBP,CAAG,CAAG,CAE7Z,SAASQ,GAAgBC,EAAUC,EAAa,CAAE,GAAI,EAAED,aAAoBC,GAAgB,MAAM,IAAI,UAAU,mCAAmC,CAAK,CAExJ,SAASC,GAAkBxB,EAAQyB,EAAO,CAAE,QAASC,EAAI,EAAGA,EAAID,EAAM,OAAQC,IAAK,CAAE,IAAIC,EAAaF,EAAMC,GAAIC,EAAW,WAAaA,EAAW,YAAc,GAAOA,EAAW,aAAe,GAAU,UAAWA,IAAYA,EAAW,SAAW,IAAM,OAAO,eAAe3B,EAAQ2B,EAAW,IAAKA,CAAU,CAAG,CAAE,CAE5T,SAASC,GAAaL,EAAaM,EAAYC,EAAa,CAAE,OAAID,GAAYL,GAAkBD,EAAY,UAAWM,CAAU,EAAOC,GAAaN,GAAkBD,EAAaO,CAAW,EAAUP,CAAa,CAEtN,SAASQ,GAAUC,EAAUC,EAAY,CAAE,GAAI,OAAOA,GAAe,YAAcA,IAAe,KAAQ,MAAM,IAAI,UAAU,oDAAoD,EAAKD,EAAS,UAAY,OAAO,OAAOC,GAAcA,EAAW,UAAW,CAAE,YAAa,CAAE,MAAOD,EAAU,SAAU,GAAM,aAAc,EAAK,CAAE,CAAC,EAAOC,GAAYC,GAAgBF,EAAUC,CAAU,CAAG,CAEhY,SAASC,GAAgBC,EAAGC,EAAG,CAAE,OAAAF,GAAkB,OAAO,gBAAkB,SAAyBC,EAAGC,EAAG,CAAE,OAAAD,EAAE,UAAYC,EAAUD,CAAG,EAAUD,GAAgBC,EAAGC,CAAC,CAAG,CAEzK,SAASC,GAAaC,EAAS,CAAE,IAAIC,EAA4BC,GAA0B,EAAG,OAAO,UAAgC,CAAE,IAAIC,EAAQC,GAAgBJ,CAAO,EAAGK,EAAQ,GAAIJ,EAA2B,CAAE,IAAIK,EAAYF,GAAgB,IAAI,EAAE,YAAaC,EAAS,QAAQ,UAAUF,EAAO,UAAWG,CAAS,CAAG,MAASD,EAASF,EAAM,MAAM,KAAM,SAAS,EAAK,OAAOI,GAA2B,KAAMF,CAAM,CAAG,CAAG,CAExa,SAASE,GAA2BC,EAAMC,EAAM,CAAE,OAAIA,IAAS3B,GAAiB2B,CAAI,IAAM,UAAY,OAAOA,GAAS,YAAsBA,EAAeC,GAAuBF,CAAI,CAAG,CAEzL,SAASE,GAAuBF,EAAM,CAAE,GAAIA,IAAS,OAAU,MAAM,IAAI,eAAe,2DAA2D,EAAK,OAAOA,CAAM,CAErK,SAASN,IAA4B,CAA0E,GAApE,OAAO,SAAY,aAAe,CAAC,QAAQ,WAA6B,QAAQ,UAAU,KAAM,MAAO,GAAO,GAAI,OAAO,OAAU,WAAY,MAAO,GAAM,GAAI,CAAE,YAAK,UAAU,SAAS,KAAK,QAAQ,UAAU,KAAM,CAAC,EAAG,UAAY,CAAC,CAAC,CAAC,EAAU,EAAM,OAASS,EAAP,CAAY,MAAO,EAAO,CAAE,CAEnU,SAASP,GAAgBP,EAAG,CAAE,OAAAO,GAAkB,OAAO,eAAiB,OAAO,eAAiB,SAAyBP,EAAG,CAAE,OAAOA,EAAE,WAAa,OAAO,eAAeA,CAAC,CAAG,EAAUO,GAAgBP,CAAC,CAAG,CAa5M,SAASe,GAAkBC,EAAQC,EAAS,CAC1C,IAAIC,EAAY,kBAAkB,OAAOF,CAAM,EAE/C,GAAI,EAACC,EAAQ,aAAaC,CAAS,EAInC,OAAOD,EAAQ,aAAaC,CAAS,CACvC,CAOA,IAAIC,GAAyB,SAAUC,EAAU,CAC/CxB,GAAUuB,EAAWC,CAAQ,EAE7B,IAAIC,EAASnB,GAAaiB,CAAS,EAMnC,SAASA,EAAUG,EAAShD,EAAS,CACnC,IAAIiD,EAEJ,OAAArC,GAAgB,KAAMiC,CAAS,EAE/BI,EAAQF,EAAO,KAAK,IAAI,EAExBE,EAAM,eAAejD,CAAO,EAE5BiD,EAAM,YAAYD,CAAO,EAElBC,CACT,CAQA,OAAA9B,GAAa0B,EAAW,CAAC,CACvB,IAAK,iBACL,MAAO,UAA0B,CAC/B,IAAI7C,EAAU,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAAC,EACnF,KAAK,OAAS,OAAOA,EAAQ,QAAW,WAAaA,EAAQ,OAAS,KAAK,cAC3E,KAAK,OAAS,OAAOA,EAAQ,QAAW,WAAaA,EAAQ,OAAS,KAAK,cAC3E,KAAK,KAAO,OAAOA,EAAQ,MAAS,WAAaA,EAAQ,KAAO,KAAK,YACrE,KAAK,UAAYW,GAAiBX,EAAQ,SAAS,IAAM,SAAWA,EAAQ,UAAY,SAAS,IACnG,CAMF,EAAG,CACD,IAAK,cACL,MAAO,SAAqBgD,EAAS,CACnC,IAAIE,EAAS,KAEb,KAAK,SAAWlE,EAAe,EAAEgE,EAAS,QAAS,SAAUR,GAAG,CAC9D,OAAOU,EAAO,QAAQV,EAAC,CACzB,CAAC,CACH,CAMF,EAAG,CACD,IAAK,UACL,MAAO,SAAiBA,EAAG,CACzB,IAAIQ,EAAUR,EAAE,gBAAkBA,EAAE,cAChCjC,GAAS,KAAK,OAAOyC,CAAO,GAAK,OACjCvC,GAAOC,GAAgB,CACzB,OAAQH,GACR,UAAW,KAAK,UAChB,OAAQ,KAAK,OAAOyC,CAAO,EAC3B,KAAM,KAAK,KAAKA,CAAO,CACzB,CAAC,EAED,KAAK,KAAKvC,GAAO,UAAY,QAAS,CACpC,OAAQF,GACR,KAAME,GACN,QAASuC,EACT,eAAgB,UAA0B,CACpCA,GACFA,EAAQ,MAAM,EAGhB,OAAO,aAAa,EAAE,gBAAgB,CACxC,CACF,CAAC,CACH,CAMF,EAAG,CACD,IAAK,gBACL,MAAO,SAAuBA,EAAS,CACrC,OAAOP,GAAkB,SAAUO,CAAO,CAC5C,CAMF,EAAG,CACD,IAAK,gBACL,MAAO,SAAuBA,EAAS,CACrC,IAAIG,EAAWV,GAAkB,SAAUO,CAAO,EAElD,GAAIG,EACF,OAAO,SAAS,cAAcA,CAAQ,CAE1C,CAQF,EAAG,CACD,IAAK,cAML,MAAO,SAAqBH,EAAS,CACnC,OAAOP,GAAkB,OAAQO,CAAO,CAC1C,CAKF,EAAG,CACD,IAAK,UACL,MAAO,UAAmB,CACxB,KAAK,SAAS,QAAQ,CACxB,CACF,CAAC,EAAG,CAAC,CACH,IAAK,OACL,MAAO,SAAczD,EAAQ,CAC3B,IAAIS,EAAU,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAChF,UAAW,SAAS,IACtB,EACA,OAAOE,EAAaX,EAAQS,CAAO,CACrC,CAOF,EAAG,CACD,IAAK,MACL,MAAO,SAAaT,EAAQ,CAC1B,OAAOE,EAAYF,CAAM,CAC3B,CAOF,EAAG,CACD,IAAK,cACL,MAAO,UAAuB,CAC5B,IAAIgB,EAAS,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAAC,OAAQ,KAAK,EAC3F6C,EAAU,OAAO7C,GAAW,SAAW,CAACA,CAAM,EAAIA,EAClD8C,GAAU,CAAC,CAAC,SAAS,sBACzB,OAAAD,EAAQ,QAAQ,SAAU7C,GAAQ,CAChC8C,GAAUA,IAAW,CAAC,CAAC,SAAS,sBAAsB9C,EAAM,CAC9D,CAAC,EACM8C,EACT,CACF,CAAC,CAAC,EAEKR,CACT,EAAG/D,EAAqB,CAAE,EAEOF,GAAaiE,EAExC,EAEA,IACC,SAASxE,EAAQ,CAExB,IAAIiF,EAAqB,EAKzB,GAAI,OAAO,SAAY,aAAe,CAAC,QAAQ,UAAU,QAAS,CAC9D,IAAIC,EAAQ,QAAQ,UAEpBA,EAAM,QAAUA,EAAM,iBACNA,EAAM,oBACNA,EAAM,mBACNA,EAAM,kBACNA,EAAM,qBAC1B,CASA,SAASC,EAASb,EAASQ,EAAU,CACjC,KAAOR,GAAWA,EAAQ,WAAaW,GAAoB,CACvD,GAAI,OAAOX,EAAQ,SAAY,YAC3BA,EAAQ,QAAQQ,CAAQ,EAC1B,OAAOR,EAETA,EAAUA,EAAQ,UACtB,CACJ,CAEAtE,EAAO,QAAUmF,CAGX,EAEA,IACC,SAASnF,EAAQoF,EAA0B9E,EAAqB,CAEvE,IAAI6E,EAAU7E,EAAoB,GAAG,EAYrC,SAAS+E,EAAUf,EAASQ,EAAU/D,EAAMuE,EAAUC,EAAY,CAC9D,IAAIC,EAAaC,EAAS,MAAM,KAAM,SAAS,EAE/C,OAAAnB,EAAQ,iBAAiBvD,EAAMyE,EAAYD,CAAU,EAE9C,CACH,QAAS,UAAW,CAChBjB,EAAQ,oBAAoBvD,EAAMyE,EAAYD,CAAU,CAC5D,CACJ,CACJ,CAYA,SAASG,EAASC,EAAUb,EAAU/D,EAAMuE,EAAUC,EAAY,CAE9D,OAAI,OAAOI,EAAS,kBAAqB,WAC9BN,EAAU,MAAM,KAAM,SAAS,EAItC,OAAOtE,GAAS,WAGTsE,EAAU,KAAK,KAAM,QAAQ,EAAE,MAAM,KAAM,SAAS,GAI3D,OAAOM,GAAa,WACpBA,EAAW,SAAS,iBAAiBA,CAAQ,GAI1C,MAAM,UAAU,IAAI,KAAKA,EAAU,SAAUrB,EAAS,CACzD,OAAOe,EAAUf,EAASQ,EAAU/D,EAAMuE,EAAUC,CAAU,CAClE,CAAC,EACL,CAWA,SAASE,EAASnB,EAASQ,EAAU/D,EAAMuE,EAAU,CACjD,OAAO,SAASnB,EAAG,CACfA,EAAE,eAAiBgB,EAAQhB,EAAE,OAAQW,CAAQ,EAEzCX,EAAE,gBACFmB,EAAS,KAAKhB,EAASH,CAAC,CAEhC,CACJ,CAEAnE,EAAO,QAAU0F,CAGX,EAEA,IACC,SAAStF,EAAyBL,EAAS,CAQlDA,EAAQ,KAAO,SAASuB,EAAO,CAC3B,OAAOA,IAAU,QACVA,aAAiB,aACjBA,EAAM,WAAa,CAC9B,EAQAvB,EAAQ,SAAW,SAASuB,EAAO,CAC/B,IAAIP,EAAO,OAAO,UAAU,SAAS,KAAKO,CAAK,EAE/C,OAAOA,IAAU,SACTP,IAAS,qBAAuBA,IAAS,4BACzC,WAAYO,IACZA,EAAM,SAAW,GAAKvB,EAAQ,KAAKuB,EAAM,EAAE,EACvD,EAQAvB,EAAQ,OAAS,SAASuB,EAAO,CAC7B,OAAO,OAAOA,GAAU,UACjBA,aAAiB,MAC5B,EAQAvB,EAAQ,GAAK,SAASuB,EAAO,CACzB,IAAIP,EAAO,OAAO,UAAU,SAAS,KAAKO,CAAK,EAE/C,OAAOP,IAAS,mBACpB,CAGM,EAEA,IACC,SAASf,EAAQoF,EAA0B9E,EAAqB,CAEvE,IAAIsF,EAAKtF,EAAoB,GAAG,EAC5BoF,EAAWpF,EAAoB,GAAG,EAWtC,SAASI,EAAOQ,EAAQH,EAAMuE,EAAU,CACpC,GAAI,CAACpE,GAAU,CAACH,GAAQ,CAACuE,EACrB,MAAM,IAAI,MAAM,4BAA4B,EAGhD,GAAI,CAACM,EAAG,OAAO7E,CAAI,EACf,MAAM,IAAI,UAAU,kCAAkC,EAG1D,GAAI,CAAC6E,EAAG,GAAGN,CAAQ,EACf,MAAM,IAAI,UAAU,mCAAmC,EAG3D,GAAIM,EAAG,KAAK1E,CAAM,EACd,OAAO2E,EAAW3E,EAAQH,EAAMuE,CAAQ,EAEvC,GAAIM,EAAG,SAAS1E,CAAM,EACvB,OAAO4E,EAAe5E,EAAQH,EAAMuE,CAAQ,EAE3C,GAAIM,EAAG,OAAO1E,CAAM,EACrB,OAAO6E,EAAe7E,EAAQH,EAAMuE,CAAQ,EAG5C,MAAM,IAAI,UAAU,2EAA2E,CAEvG,CAWA,SAASO,EAAWG,EAAMjF,EAAMuE,EAAU,CACtC,OAAAU,EAAK,iBAAiBjF,EAAMuE,CAAQ,EAE7B,CACH,QAAS,UAAW,CAChBU,EAAK,oBAAoBjF,EAAMuE,CAAQ,CAC3C,CACJ,CACJ,CAWA,SAASQ,EAAeG,EAAUlF,EAAMuE,EAAU,CAC9C,aAAM,UAAU,QAAQ,KAAKW,EAAU,SAASD,EAAM,CAClDA,EAAK,iBAAiBjF,EAAMuE,CAAQ,CACxC,CAAC,EAEM,CACH,QAAS,UAAW,CAChB,MAAM,UAAU,QAAQ,KAAKW,EAAU,SAASD,EAAM,CAClDA,EAAK,oBAAoBjF,EAAMuE,CAAQ,CAC3C,CAAC,CACL,CACJ,CACJ,CAWA,SAASS,EAAejB,EAAU/D,EAAMuE,EAAU,CAC9C,OAAOI,EAAS,SAAS,KAAMZ,EAAU/D,EAAMuE,CAAQ,CAC3D,CAEAtF,EAAO,QAAUU,CAGX,EAEA,IACC,SAASV,EAAQ,CAExB,SAASkG,EAAO5B,EAAS,CACrB,IAAInD,EAEJ,GAAImD,EAAQ,WAAa,SACrBA,EAAQ,MAAM,EAEdnD,EAAemD,EAAQ,cAElBA,EAAQ,WAAa,SAAWA,EAAQ,WAAa,WAAY,CACtE,IAAI6B,EAAa7B,EAAQ,aAAa,UAAU,EAE3C6B,GACD7B,EAAQ,aAAa,WAAY,EAAE,EAGvCA,EAAQ,OAAO,EACfA,EAAQ,kBAAkB,EAAGA,EAAQ,MAAM,MAAM,EAE5C6B,GACD7B,EAAQ,gBAAgB,UAAU,EAGtCnD,EAAemD,EAAQ,KAC3B,KACK,CACGA,EAAQ,aAAa,iBAAiB,GACtCA,EAAQ,MAAM,EAGlB,IAAI8B,EAAY,OAAO,aAAa,EAChCC,EAAQ,SAAS,YAAY,EAEjCA,EAAM,mBAAmB/B,CAAO,EAChC8B,EAAU,gBAAgB,EAC1BA,EAAU,SAASC,CAAK,EAExBlF,EAAeiF,EAAU,SAAS,CACtC,CAEA,OAAOjF,CACX,CAEAnB,EAAO,QAAUkG,CAGX,EAEA,IACC,SAASlG,EAAQ,CAExB,SAASsG,GAAK,CAGd,CAEAA,EAAE,UAAY,CACZ,GAAI,SAAUC,EAAMjB,EAAUkB,EAAK,CACjC,IAAIrC,EAAI,KAAK,IAAM,KAAK,EAAI,CAAC,GAE7B,OAACA,EAAEoC,KAAUpC,EAAEoC,GAAQ,CAAC,IAAI,KAAK,CAC/B,GAAIjB,EACJ,IAAKkB,CACP,CAAC,EAEM,IACT,EAEA,KAAM,SAAUD,EAAMjB,EAAUkB,EAAK,CACnC,IAAIxC,EAAO,KACX,SAASyB,GAAY,CACnBzB,EAAK,IAAIuC,EAAMd,CAAQ,EACvBH,EAAS,MAAMkB,EAAK,SAAS,CAC/B,CAEA,OAAAf,EAAS,EAAIH,EACN,KAAK,GAAGiB,EAAMd,EAAUe,CAAG,CACpC,EAEA,KAAM,SAAUD,EAAM,CACpB,IAAIE,EAAO,CAAC,EAAE,MAAM,KAAK,UAAW,CAAC,EACjCC,IAAW,KAAK,IAAM,KAAK,EAAI,CAAC,IAAIH,IAAS,CAAC,GAAG,MAAM,EACvD3D,EAAI,EACJ+D,EAAMD,EAAO,OAEjB,IAAK9D,EAAGA,EAAI+D,EAAK/D,IACf8D,EAAO9D,GAAG,GAAG,MAAM8D,EAAO9D,GAAG,IAAK6D,CAAI,EAGxC,OAAO,IACT,EAEA,IAAK,SAAUF,EAAMjB,EAAU,CAC7B,IAAInB,EAAI,KAAK,IAAM,KAAK,EAAI,CAAC,GACzByC,EAAOzC,EAAEoC,GACTM,EAAa,CAAC,EAElB,GAAID,GAAQtB,EACV,QAAS1C,EAAI,EAAG+D,EAAMC,EAAK,OAAQhE,EAAI+D,EAAK/D,IACtCgE,EAAKhE,GAAG,KAAO0C,GAAYsB,EAAKhE,GAAG,GAAG,IAAM0C,GAC9CuB,EAAW,KAAKD,EAAKhE,EAAE,EAQ7B,OAACiE,EAAW,OACR1C,EAAEoC,GAAQM,EACV,OAAO1C,EAAEoC,GAEN,IACT,CACF,EAEAvG,EAAO,QAAUsG,EACjBtG,EAAO,QAAQ,YAAcsG,CAGvB,CAEI,EAGIQ,EAA2B,CAAC,EAGhC,SAASxG,EAAoByG,EAAU,CAEtC,GAAGD,EAAyBC,GAC3B,OAAOD,EAAyBC,GAAU,QAG3C,IAAI/G,EAAS8G,EAAyBC,GAAY,CAGjD,QAAS,CAAC,CACX,EAGA,OAAA5G,EAAoB4G,GAAU/G,EAAQA,EAAO,QAASM,CAAmB,EAGlEN,EAAO,OACf,CAIA,OAAC,UAAW,CAEXM,EAAoB,EAAI,SAASN,EAAQ,CACxC,IAAIgH,EAAShH,GAAUA,EAAO,WAC7B,UAAW,CAAE,OAAOA,EAAO,OAAY,EACvC,UAAW,CAAE,OAAOA,CAAQ,EAC7B,OAAAM,EAAoB,EAAE0G,EAAQ,CAAE,EAAGA,CAAO,CAAC,EACpCA,CACR,CACD,EAAE,EAGD,UAAW,CAEX1G,EAAoB,EAAI,SAASP,EAASkH,EAAY,CACrD,QAAQC,KAAOD,EACX3G,EAAoB,EAAE2G,EAAYC,CAAG,GAAK,CAAC5G,EAAoB,EAAEP,EAASmH,CAAG,GAC/E,OAAO,eAAenH,EAASmH,EAAK,CAAE,WAAY,GAAM,IAAKD,EAAWC,EAAK,CAAC,CAGjF,CACD,EAAE,EAGD,UAAW,CACX5G,EAAoB,EAAI,SAASyB,EAAKoF,EAAM,CAAE,OAAO,OAAO,UAAU,eAAe,KAAKpF,EAAKoF,CAAI,CAAG,CACvG,EAAE,EAMK7G,EAAoB,GAAG,CAC/B,EAAG,EACX,OACD,CAAC,ICz3BD,IAAA8G,GAAAC,GAAA,CAAAC,GAAAC,KAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,GAeA,IAAIC,GAAkB,UAOtBD,GAAO,QAAUE,GAUjB,SAASA,GAAWC,EAAQ,CAC1B,IAAIC,EAAM,GAAKD,EACXE,EAAQJ,GAAgB,KAAKG,CAAG,EAEpC,GAAI,CAACC,EACH,OAAOD,EAGT,IAAIE,EACAC,EAAO,GACPC,EAAQ,EACRC,EAAY,EAEhB,IAAKD,EAAQH,EAAM,MAAOG,EAAQJ,EAAI,OAAQI,IAAS,CACrD,OAAQJ,EAAI,WAAWI,CAAK,EAAG,CAC7B,IAAK,IACHF,EAAS,SACT,MACF,IAAK,IACHA,EAAS,QACT,MACF,IAAK,IACHA,EAAS,QACT,MACF,IAAK,IACHA,EAAS,OACT,MACF,IAAK,IACHA,EAAS,OACT,MACF,QACE,QACJ,CAEIG,IAAcD,IAChBD,GAAQH,EAAI,UAAUK,EAAWD,CAAK,GAGxCC,EAAYD,EAAQ,EACpBD,GAAQD,CACV,CAEA,OAAOG,IAAcD,EACjBD,EAAOH,EAAI,UAAUK,EAAWD,CAAK,EACrCD,CACN,IC7EA,MAAM,UAAU,MAAM,OAAO,eAAe,MAAM,UAAU,OAAO,CAAC,aAAa,GAAG,MAAM,SAASG,GAAG,CAAC,IAAI,EAAE,MAAM,UAAU,EAAE,EAAE,EAAE,OAAO,UAAU,EAAE,EAAE,OAAO,EAAE,MAAM,UAAU,OAAO,KAAK,KAAK,SAASC,EAAEC,EAAE,CAAC,OAAO,MAAM,QAAQA,CAAC,EAAED,EAAE,KAAK,MAAMA,EAAED,EAAE,KAAKE,EAAE,EAAE,CAAC,CAAC,EAAED,EAAE,KAAKC,CAAC,EAAED,CAAC,EAAE,CAAC,CAAC,EAAE,MAAM,UAAU,MAAM,KAAK,IAAI,CAAC,EAAE,SAAS,EAAE,CAAC,EAAE,MAAM,UAAU,SAAS,OAAO,eAAe,MAAM,UAAU,UAAU,CAAC,aAAa,GAAG,MAAM,SAASD,EAAE,CAAC,OAAO,MAAM,UAAU,IAAI,MAAM,KAAK,SAAS,EAAE,KAAK,CAAC,EAAE,SAAS,EAAE,CAAC,ECuBxf,IAAAG,GAAO,SCvBP,KAAK,QAAQ,KAAK,MAAM,SAAS,EAAEC,EAAE,CAAC,OAAOA,EAAEA,GAAG,CAAC,EAAE,IAAI,QAAQ,SAASC,EAAEC,EAAE,CAAC,IAAIC,EAAE,IAAI,eAAeC,EAAE,CAAC,EAAEC,EAAE,CAAC,EAAEC,EAAE,CAAC,EAAEC,EAAE,UAAU,CAAC,MAAM,CAAC,IAAOJ,EAAE,OAAO,IAAI,IAAjB,EAAoB,WAAWA,EAAE,WAAW,OAAOA,EAAE,OAAO,IAAIA,EAAE,YAAY,KAAK,UAAU,CAAC,OAAO,QAAQ,QAAQA,EAAE,YAAY,CAAC,EAAE,KAAK,UAAU,CAAC,OAAO,QAAQ,QAAQA,EAAE,YAAY,EAAE,KAAK,KAAK,KAAK,CAAC,EAAE,KAAK,UAAU,CAAC,OAAO,QAAQ,QAAQ,IAAI,KAAK,CAACA,EAAE,QAAQ,CAAC,CAAC,CAAC,EAAE,MAAMI,EAAE,QAAQ,CAAC,KAAK,UAAU,CAAC,OAAOH,CAAC,EAAE,QAAQ,UAAU,CAAC,OAAOC,CAAC,EAAE,IAAI,SAASG,EAAE,CAAC,OAAOF,EAAEE,EAAE,YAAY,EAAE,EAAE,IAAI,SAASA,EAAE,CAAC,OAAOA,EAAE,YAAY,IAAIF,CAAC,CAAC,CAAC,CAAC,EAAE,QAAQG,KAAKN,EAAE,KAAKH,EAAE,QAAQ,MAAM,EAAE,EAAE,EAAEG,EAAE,OAAO,UAAU,CAACA,EAAE,sBAAsB,EAAE,QAAQ,+BAA+B,SAASK,EAAER,EAAEC,EAAE,CAACG,EAAE,KAAKJ,EAAEA,EAAE,YAAY,CAAC,EAAEK,EAAE,KAAK,CAACL,EAAEC,CAAC,CAAC,EAAEK,EAAEN,GAAGM,EAAEN,GAAGM,EAAEN,GAAG,IAAIC,EAAEA,CAAC,CAAC,EAAEA,EAAEM,EAAE,CAAC,CAAC,EAAEJ,EAAE,QAAQD,EAAEC,EAAE,gBAA2BH,EAAE,aAAb,UAAyBA,EAAE,QAAQG,EAAE,iBAAiBM,EAAET,EAAE,QAAQS,EAAE,EAAEN,EAAE,KAAKH,EAAE,MAAM,IAAI,CAAC,CAAC,CAAC,GDyBj5B,IAAAU,GAAO,SEzBP,IAAAC,GAAkB,WACZ,CACF,UAAAC,GACA,SAAAC,GACA,OAAAC,GACA,WAAAC,GACA,QAAAC,GACA,WAAAC,GACA,UAAAC,GACA,YAAAC,GACA,aAAAC,GACA,gBAAAC,GACA,SAAAC,GACA,OAAAC,EACA,SAAAC,GACA,eAAAC,GACA,cAAAC,EACA,QAAAC,GACA,iBAAAC,GACA,iBAAAC,GACA,cAAAC,GACA,qBAAAC,GACA,aAAAC,GACA,gBAAAC,GACA,uBAAAC,GACA,uBAAAC,EACJ,EAAI,GAAAC,QCtBE,SAAUC,EAAWC,EAAU,CACnC,OAAO,OAAOA,GAAU,UAC1B,CCGM,SAAUC,GAAoBC,EAAgC,CAClE,IAAMC,EAAS,SAACC,EAAa,CAC3B,MAAM,KAAKA,CAAQ,EACnBA,EAAS,MAAQ,IAAI,MAAK,EAAG,KAC/B,EAEMC,EAAWH,EAAWC,CAAM,EAClC,OAAAE,EAAS,UAAY,OAAO,OAAO,MAAM,SAAS,EAClDA,EAAS,UAAU,YAAcA,EAC1BA,CACT,CCDO,IAAMC,GAA+CC,GAC1D,SAACC,EAAM,CACL,OAAA,SAA4CC,EAA0B,CACpED,EAAO,IAAI,EACX,KAAK,QAAUC,EACRA,EAAO,OAAM;EACxBA,EAAO,IAAI,SAACC,EAAKC,EAAC,CAAK,OAAGA,EAAI,EAAC,KAAKD,EAAI,SAAQ,CAAzB,CAA6B,EAAE,KAAK;GAAM,EACzD,GACJ,KAAK,KAAO,sBACZ,KAAK,OAASD,CAChB,CARA,CAQC,ECvBC,SAAUG,GAAaC,EAA6BC,EAAO,CAC/D,GAAID,EAAK,CACP,IAAME,EAAQF,EAAI,QAAQC,CAAI,EAC9B,GAAKC,GAASF,EAAI,OAAOE,EAAO,CAAC,EAErC,CCOA,IAAAC,GAAA,UAAA,CAyBE,SAAAA,EAAoBC,EAA4B,CAA5B,KAAA,gBAAAA,EAdb,KAAA,OAAS,GAER,KAAA,WAAmD,KAMnD,KAAA,YAAqD,IAMV,CAQnD,OAAAD,EAAA,UAAA,YAAA,UAAA,aACME,EAEJ,GAAI,CAAC,KAAK,OAAQ,CAChB,KAAK,OAAS,GAGN,IAAAC,EAAe,KAAI,WAC3B,GAAIA,EAEF,GADA,KAAK,WAAa,KACd,MAAM,QAAQA,CAAU,MAC1B,QAAqBC,EAAAC,GAAAF,CAAU,EAAAG,EAAAF,EAAA,KAAA,EAAA,CAAAE,EAAA,KAAAA,EAAAF,EAAA,KAAA,EAAE,CAA5B,IAAMG,EAAMD,EAAA,MACfC,EAAO,OAAO,IAAI,yGAGpBJ,EAAW,OAAO,IAAI,EAIlB,IAAiBK,EAAqB,KAAI,gBAClD,GAAIC,EAAWD,CAAgB,EAC7B,GAAI,CACFA,EAAgB,QACTE,EAAP,CACAR,EAASQ,aAAaC,GAAsBD,EAAE,OAAS,CAACA,CAAC,EAIrD,IAAAE,EAAgB,KAAI,YAC5B,GAAIA,EAAa,CACf,KAAK,YAAc,SACnB,QAAwBC,EAAAR,GAAAO,CAAW,EAAAE,EAAAD,EAAA,KAAA,EAAA,CAAAC,EAAA,KAAAA,EAAAD,EAAA,KAAA,EAAE,CAAhC,IAAME,EAASD,EAAA,MAClB,GAAI,CACFE,GAAcD,CAAS,QAChBE,EAAP,CACAf,EAASA,GAAM,KAANA,EAAU,CAAA,EACfe,aAAeN,GACjBT,EAAMgB,EAAAA,EAAA,CAAA,EAAAC,EAAOjB,CAAM,CAAA,EAAAiB,EAAKF,EAAI,MAAM,CAAA,EAElCf,EAAO,KAAKe,CAAG,sGAMvB,GAAIf,EACF,MAAM,IAAIS,GAAoBT,CAAM,EAG1C,EAoBAF,EAAA,UAAA,IAAA,SAAIoB,EAAuB,OAGzB,GAAIA,GAAYA,IAAa,KAC3B,GAAI,KAAK,OAGPJ,GAAcI,CAAQ,MACjB,CACL,GAAIA,aAAoBpB,EAAc,CAGpC,GAAIoB,EAAS,QAAUA,EAAS,WAAW,IAAI,EAC7C,OAEFA,EAAS,WAAW,IAAI,GAEzB,KAAK,aAAcC,EAAA,KAAK,eAAW,MAAAA,IAAA,OAAAA,EAAI,CAAA,GAAI,KAAKD,CAAQ,EAG/D,EAOQpB,EAAA,UAAA,WAAR,SAAmBsB,EAAoB,CAC7B,IAAAnB,EAAe,KAAI,WAC3B,OAAOA,IAAemB,GAAW,MAAM,QAAQnB,CAAU,GAAKA,EAAW,SAASmB,CAAM,CAC1F,EASQtB,EAAA,UAAA,WAAR,SAAmBsB,EAAoB,CAC7B,IAAAnB,EAAe,KAAI,WAC3B,KAAK,WAAa,MAAM,QAAQA,CAAU,GAAKA,EAAW,KAAKmB,CAAM,EAAGnB,GAAcA,EAAa,CAACA,EAAYmB,CAAM,EAAIA,CAC5H,EAMQtB,EAAA,UAAA,cAAR,SAAsBsB,EAAoB,CAChC,IAAAnB,EAAe,KAAI,WACvBA,IAAemB,EACjB,KAAK,WAAa,KACT,MAAM,QAAQnB,CAAU,GACjCoB,GAAUpB,EAAYmB,CAAM,CAEhC,EAgBAtB,EAAA,UAAA,OAAA,SAAOoB,EAAsC,CACnC,IAAAR,EAAgB,KAAI,YAC5BA,GAAeW,GAAUX,EAAaQ,CAAQ,EAE1CA,aAAoBpB,GACtBoB,EAAS,cAAc,IAAI,CAE/B,EAlLcpB,EAAA,MAAS,UAAA,CACrB,IAAMwB,EAAQ,IAAIxB,EAClB,OAAAwB,EAAM,OAAS,GACRA,CACT,EAAE,EA+KJxB,GArLA,EAuLO,IAAMyB,GAAqBC,GAAa,MAEzC,SAAUC,GAAeC,EAAU,CACvC,OACEA,aAAiBF,IAChBE,GAAS,WAAYA,GAASC,EAAWD,EAAM,MAAM,GAAKC,EAAWD,EAAM,GAAG,GAAKC,EAAWD,EAAM,WAAW,CAEpH,CAEA,SAASE,GAAcC,EAAwC,CACzDF,EAAWE,CAAS,EACtBA,EAAS,EAETA,EAAU,YAAW,CAEzB,CChNO,IAAMC,GAAuB,CAClC,iBAAkB,KAClB,sBAAuB,KACvB,QAAS,OACT,sCAAuC,GACvC,yBAA0B,ICGrB,IAAMC,GAAmC,CAG9C,WAAA,SAAWC,EAAqBC,EAAgB,SAAEC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,EAAA,GAAA,UAAAA,GACxC,IAAAC,EAAaL,GAAe,SACpC,OAAIK,GAAQ,MAARA,EAAU,WACLA,EAAS,WAAU,MAAnBA,EAAQC,EAAA,CAAYL,EAASC,CAAO,EAAAK,EAAKJ,CAAI,CAAA,CAAA,EAE/C,WAAU,MAAA,OAAAG,EAAA,CAACL,EAASC,CAAO,EAAAK,EAAKJ,CAAI,CAAA,CAAA,CAC7C,EACA,aAAA,SAAaK,EAAM,CACT,IAAAH,EAAaL,GAAe,SACpC,QAAQK,GAAQ,KAAA,OAARA,EAAU,eAAgB,cAAcG,CAAa,CAC/D,EACA,SAAU,QCjBN,SAAUC,GAAqBC,EAAQ,CAC3CC,GAAgB,WAAW,UAAA,CACjB,IAAAC,EAAqBC,GAAM,iBACnC,GAAID,EAEFA,EAAiBF,CAAG,MAGpB,OAAMA,CAEV,CAAC,CACH,CCtBM,SAAUI,IAAI,CAAK,CCMlB,IAAMC,GAAyB,UAAA,CAAM,OAAAC,GAAmB,IAAK,OAAW,MAAS,CAA5C,EAAsE,EAO5G,SAAUC,GAAkBC,EAAU,CAC1C,OAAOF,GAAmB,IAAK,OAAWE,CAAK,CACjD,CAOM,SAAUC,GAAoBC,EAAQ,CAC1C,OAAOJ,GAAmB,IAAKI,EAAO,MAAS,CACjD,CAQM,SAAUJ,GAAmBK,EAAuBD,EAAYF,EAAU,CAC9E,MAAO,CACL,KAAIG,EACJ,MAAKD,EACL,MAAKF,EAET,CCrCA,IAAII,GAAuD,KASrD,SAAUC,GAAaC,EAAc,CACzC,GAAIC,GAAO,sCAAuC,CAChD,IAAMC,EAAS,CAACJ,GAKhB,GAJII,IACFJ,GAAU,CAAE,YAAa,GAAO,MAAO,IAAI,GAE7CE,EAAE,EACEE,EAAQ,CACJ,IAAAC,EAAyBL,GAAvBM,EAAWD,EAAA,YAAEE,EAAKF,EAAA,MAE1B,GADAL,GAAU,KACNM,EACF,MAAMC,QAMVL,EAAE,CAEN,CAMM,SAAUM,GAAaC,EAAQ,CAC/BN,GAAO,uCAAyCH,KAClDA,GAAQ,YAAc,GACtBA,GAAQ,MAAQS,EAEpB,CCrBA,IAAAC,GAAA,SAAAC,EAAA,CAAmCC,GAAAF,EAAAC,CAAA,EA6BjC,SAAAD,EAAYG,EAA6C,CAAzD,IAAAC,EACEH,EAAA,KAAA,IAAA,GAAO,KATC,OAAAG,EAAA,UAAqB,GAUzBD,GACFC,EAAK,YAAcD,EAGfE,GAAeF,CAAW,GAC5BA,EAAY,IAAIC,CAAI,GAGtBA,EAAK,YAAcE,IAEvB,CAzBO,OAAAN,EAAA,OAAP,SAAiBO,EAAwBC,EAA2BC,EAAqB,CACvF,OAAO,IAAIC,GAAeH,EAAMC,EAAOC,CAAQ,CACjD,EAgCAT,EAAA,UAAA,KAAA,SAAKW,EAAS,CACR,KAAK,UACPC,GAA0BC,GAAiBF,CAAK,EAAG,IAAI,EAEvD,KAAK,MAAMA,CAAM,CAErB,EASAX,EAAA,UAAA,MAAA,SAAMc,EAAS,CACT,KAAK,UACPF,GAA0BG,GAAkBD,CAAG,EAAG,IAAI,GAEtD,KAAK,UAAY,GACjB,KAAK,OAAOA,CAAG,EAEnB,EAQAd,EAAA,UAAA,SAAA,UAAA,CACM,KAAK,UACPY,GAA0BI,GAAuB,IAAI,GAErD,KAAK,UAAY,GACjB,KAAK,UAAS,EAElB,EAEAhB,EAAA,UAAA,YAAA,UAAA,CACO,KAAK,SACR,KAAK,UAAY,GACjBC,EAAA,UAAM,YAAW,KAAA,IAAA,EACjB,KAAK,YAAc,KAEvB,EAEUD,EAAA,UAAA,MAAV,SAAgBW,EAAQ,CACtB,KAAK,YAAY,KAAKA,CAAK,CAC7B,EAEUX,EAAA,UAAA,OAAV,SAAiBc,EAAQ,CACvB,GAAI,CACF,KAAK,YAAY,MAAMA,CAAG,UAE1B,KAAK,YAAW,EAEpB,EAEUd,EAAA,UAAA,UAAV,UAAA,CACE,GAAI,CACF,KAAK,YAAY,SAAQ,UAEzB,KAAK,YAAW,EAEpB,EACFA,CAAA,EApHmCiB,EAAY,EA2H/C,IAAMC,GAAQ,SAAS,UAAU,KAEjC,SAASC,GAAyCC,EAAQC,EAAY,CACpE,OAAOH,GAAM,KAAKE,EAAIC,CAAO,CAC/B,CAMA,IAAAC,GAAA,UAAA,CACE,SAAAA,EAAoBC,EAAqC,CAArC,KAAA,gBAAAA,CAAwC,CAE5D,OAAAD,EAAA,UAAA,KAAA,SAAKE,EAAQ,CACH,IAAAD,EAAoB,KAAI,gBAChC,GAAIA,EAAgB,KAClB,GAAI,CACFA,EAAgB,KAAKC,CAAK,QACnBC,EAAP,CACAC,GAAqBD,CAAK,EAGhC,EAEAH,EAAA,UAAA,MAAA,SAAMK,EAAQ,CACJ,IAAAJ,EAAoB,KAAI,gBAChC,GAAIA,EAAgB,MAClB,GAAI,CACFA,EAAgB,MAAMI,CAAG,QAClBF,EAAP,CACAC,GAAqBD,CAAK,OAG5BC,GAAqBC,CAAG,CAE5B,EAEAL,EAAA,UAAA,SAAA,UAAA,CACU,IAAAC,EAAoB,KAAI,gBAChC,GAAIA,EAAgB,SAClB,GAAI,CACFA,EAAgB,SAAQ,QACjBE,EAAP,CACAC,GAAqBD,CAAK,EAGhC,EACFH,CAAA,EArCA,EAuCAM,GAAA,SAAAC,EAAA,CAAuCC,GAAAF,EAAAC,CAAA,EACrC,SAAAD,EACEG,EACAN,EACAO,EAA8B,CAHhC,IAAAC,EAKEJ,EAAA,KAAA,IAAA,GAAO,KAEHN,EACJ,GAAIW,EAAWH,CAAc,GAAK,CAACA,EAGjCR,EAAkB,CAChB,KAAOQ,GAAc,KAAdA,EAAkB,OACzB,MAAON,GAAK,KAALA,EAAS,OAChB,SAAUO,GAAQ,KAARA,EAAY,YAEnB,CAEL,IAAIG,EACAF,GAAQG,GAAO,0BAIjBD,EAAU,OAAO,OAAOJ,CAAc,EACtCI,EAAQ,YAAc,UAAA,CAAM,OAAAF,EAAK,YAAW,CAAhB,EAC5BV,EAAkB,CAChB,KAAMQ,EAAe,MAAQZ,GAAKY,EAAe,KAAMI,CAAO,EAC9D,MAAOJ,EAAe,OAASZ,GAAKY,EAAe,MAAOI,CAAO,EACjE,SAAUJ,EAAe,UAAYZ,GAAKY,EAAe,SAAUI,CAAO,IAI5EZ,EAAkBQ,EAMtB,OAAAE,EAAK,YAAc,IAAIX,GAAiBC,CAAe,GACzD,CACF,OAAAK,CAAA,EAzCuCS,EAAU,EA2CjD,SAASC,GAAqBC,EAAU,CAClCC,GAAO,sCACTC,GAAaF,CAAK,EAIlBG,GAAqBH,CAAK,CAE9B,CAQA,SAASI,GAAoBC,EAAQ,CACnC,MAAMA,CACR,CAOA,SAASC,GAA0BC,EAA2CC,EAA2B,CAC/F,IAAAC,EAA0BR,GAAM,sBACxCQ,GAAyBC,GAAgB,WAAW,UAAA,CAAM,OAAAD,EAAsBF,EAAcC,CAAU,CAA9C,CAA+C,CAC3G,CAOO,IAAMG,GAA6D,CACxE,OAAQ,GACR,KAAMC,GACN,MAAOR,GACP,SAAUQ,ICjRL,IAAMC,GAA+B,UAAA,CAAM,OAAC,OAAO,QAAW,YAAc,OAAO,YAAe,cAAvD,EAAsE,ECyClH,SAAUC,GAAYC,EAAI,CAC9B,OAAOA,CACT,CCiCM,SAAUC,IAAI,SAACC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACnB,OAAOC,GAAcF,CAAG,CAC1B,CAGM,SAAUE,GAAoBF,EAA+B,CACjE,OAAIA,EAAI,SAAW,EACVG,GAGLH,EAAI,SAAW,EACVA,EAAI,GAGN,SAAeI,EAAQ,CAC5B,OAAOJ,EAAI,OAAO,SAACK,EAAWC,EAAuB,CAAK,OAAAA,EAAGD,CAAI,CAAP,EAAUD,CAAY,CAClF,CACF,CC9EA,IAAAG,EAAA,UAAA,CAkBE,SAAAA,EAAYC,EAA6E,CACnFA,IACF,KAAK,WAAaA,EAEtB,CA4BA,OAAAD,EAAA,UAAA,KAAA,SAAQE,EAAyB,CAC/B,IAAMC,EAAa,IAAIH,EACvB,OAAAG,EAAW,OAAS,KACpBA,EAAW,SAAWD,EACfC,CACT,EA8IAH,EAAA,UAAA,UAAA,SACEI,EACAC,EACAC,EAA8B,CAHhC,IAAAC,EAAA,KAKQC,EAAaC,GAAaL,CAAc,EAAIA,EAAiB,IAAIM,GAAeN,EAAgBC,EAAOC,CAAQ,EAErH,OAAAK,GAAa,UAAA,CACL,IAAAC,EAAuBL,EAArBL,EAAQU,EAAA,SAAEC,EAAMD,EAAA,OACxBJ,EAAW,IACTN,EAGIA,EAAS,KAAKM,EAAYK,CAAM,EAChCA,EAIAN,EAAK,WAAWC,CAAU,EAG1BD,EAAK,cAAcC,CAAU,CAAC,CAEtC,CAAC,EAEMA,CACT,EAGUR,EAAA,UAAA,cAAV,SAAwBc,EAAmB,CACzC,GAAI,CACF,OAAO,KAAK,WAAWA,CAAI,QACpBC,EAAP,CAIAD,EAAK,MAAMC,CAAG,EAElB,EA6DAf,EAAA,UAAA,QAAA,SAAQgB,EAA0BC,EAAoC,CAAtE,IAAAV,EAAA,KACE,OAAAU,EAAcC,GAAeD,CAAW,EAEjC,IAAIA,EAAkB,SAACE,EAASC,EAAM,CAC3C,IAAMZ,EAAa,IAAIE,GAAkB,CACvC,KAAM,SAACW,EAAK,CACV,GAAI,CACFL,EAAKK,CAAK,QACHN,EAAP,CACAK,EAAOL,CAAG,EACVP,EAAW,YAAW,EAE1B,EACA,MAAOY,EACP,SAAUD,EACX,EACDZ,EAAK,UAAUC,CAAU,CAC3B,CAAC,CACH,EAGUR,EAAA,UAAA,WAAV,SAAqBQ,EAA2B,OAC9C,OAAOI,EAAA,KAAK,UAAM,MAAAA,IAAA,OAAA,OAAAA,EAAE,UAAUJ,CAAU,CAC1C,EAOAR,EAAA,UAACG,IAAD,UAAA,CACE,OAAO,IACT,EA4FAH,EAAA,UAAA,KAAA,UAAA,SAAKsB,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACH,OAAOC,GAAcF,CAAU,EAAE,IAAI,CACvC,EA6BAtB,EAAA,UAAA,UAAA,SAAUiB,EAAoC,CAA9C,IAAAV,EAAA,KACE,OAAAU,EAAcC,GAAeD,CAAW,EAEjC,IAAIA,EAAY,SAACE,EAASC,EAAM,CACrC,IAAIC,EACJd,EAAK,UACH,SAACkB,EAAI,CAAK,OAACJ,EAAQI,CAAT,EACV,SAACV,EAAQ,CAAK,OAAAK,EAAOL,CAAG,CAAV,EACd,UAAA,CAAM,OAAAI,EAAQE,CAAK,CAAb,CAAc,CAExB,CAAC,CACH,EA3aOrB,EAAA,OAAkC,SAAIC,EAAwD,CACnG,OAAO,IAAID,EAAcC,CAAS,CACpC,EA0aFD,GA/cA,EAwdA,SAAS0B,GAAeC,EAA+C,OACrE,OAAOC,EAAAD,GAAW,KAAXA,EAAeE,GAAO,WAAO,MAAAD,IAAA,OAAAA,EAAI,OAC1C,CAEA,SAASE,GAAcC,EAAU,CAC/B,OAAOA,GAASC,EAAWD,EAAM,IAAI,GAAKC,EAAWD,EAAM,KAAK,GAAKC,EAAWD,EAAM,QAAQ,CAChG,CAEA,SAASE,GAAgBF,EAAU,CACjC,OAAQA,GAASA,aAAiBG,IAAgBJ,GAAWC,CAAK,GAAKI,GAAeJ,CAAK,CAC7F,CC1eM,SAAUK,GAAQC,EAAW,CACjC,OAAOC,EAAWD,GAAM,KAAA,OAANA,EAAQ,IAAI,CAChC,CAMM,SAAUE,EACdC,EAAqF,CAErF,OAAO,SAACH,EAAqB,CAC3B,GAAID,GAAQC,CAAM,EAChB,OAAOA,EAAO,KAAK,SAA+BI,EAA2B,CAC3E,GAAI,CACF,OAAOD,EAAKC,EAAc,IAAI,QACvBC,EAAP,CACA,KAAK,MAAMA,CAAG,EAElB,CAAC,EAEH,MAAM,IAAI,UAAU,wCAAwC,CAC9D,CACF,CCjBM,SAAUC,EACdC,EACAC,EACAC,EACAC,EACAC,EAAuB,CAEvB,OAAO,IAAIC,GAAmBL,EAAaC,EAAQC,EAAYC,EAASC,CAAU,CACpF,CAMA,IAAAC,GAAA,SAAAC,EAAA,CAA2CC,GAAAF,EAAAC,CAAA,EAiBzC,SAAAD,EACEL,EACAC,EACAC,EACAC,EACQC,EACAI,EAAiC,CAN3C,IAAAC,EAoBEH,EAAA,KAAA,KAAMN,CAAW,GAAC,KAfV,OAAAS,EAAA,WAAAL,EACAK,EAAA,kBAAAD,EAeRC,EAAK,MAAQR,EACT,SAAuCS,EAAQ,CAC7C,GAAI,CACFT,EAAOS,CAAK,QACLC,EAAP,CACAX,EAAY,MAAMW,CAAG,EAEzB,EACAL,EAAA,UAAM,MACVG,EAAK,OAASN,EACV,SAAuCQ,EAAQ,CAC7C,GAAI,CACFR,EAAQQ,CAAG,QACJA,EAAP,CAEAX,EAAY,MAAMW,CAAG,UAGrB,KAAK,YAAW,EAEpB,EACAL,EAAA,UAAM,OACVG,EAAK,UAAYP,EACb,UAAA,CACE,GAAI,CACFA,EAAU,QACHS,EAAP,CAEAX,EAAY,MAAMW,CAAG,UAGrB,KAAK,YAAW,EAEpB,EACAL,EAAA,UAAM,WACZ,CAEA,OAAAD,EAAA,UAAA,YAAA,UAAA,OACE,GAAI,CAAC,KAAK,mBAAqB,KAAK,kBAAiB,EAAI,CAC/C,IAAAO,EAAW,KAAI,OACvBN,EAAA,UAAM,YAAW,KAAA,IAAA,EAEjB,CAACM,KAAUC,EAAA,KAAK,cAAU,MAAAA,IAAA,QAAAA,EAAA,KAAf,IAAI,GAEnB,EACFR,CAAA,EAnF2CS,EAAU,ECd9C,IAAMC,GAAiD,CAG5D,SAAA,SAASC,EAAQ,CACf,IAAIC,EAAU,sBACVC,EAAkD,qBAC9CC,EAAaJ,GAAsB,SACvCI,IACFF,EAAUE,EAAS,sBACnBD,EAASC,EAAS,sBAEpB,IAAMC,EAASH,EAAQ,SAACI,EAAS,CAI/BH,EAAS,OACTF,EAASK,CAAS,CACpB,CAAC,EACD,OAAO,IAAIC,GAAa,UAAA,CAAM,OAAAJ,GAAM,KAAA,OAANA,EAASE,CAAM,CAAf,CAAgB,CAChD,EACA,sBAAqB,UAAA,SAACG,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACZ,IAAAL,EAAaJ,GAAsB,SAC3C,QAAQI,GAAQ,KAAA,OAARA,EAAU,wBAAyB,uBAAsB,MAAA,OAAAM,EAAA,CAAA,EAAAC,EAAIH,CAAI,CAAA,CAAA,CAC3E,EACA,qBAAoB,UAAA,SAACA,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACX,IAAAL,EAAaJ,GAAsB,SAC3C,QAAQI,GAAQ,KAAA,OAARA,EAAU,uBAAwB,sBAAqB,MAAA,OAAAM,EAAA,CAAA,EAAAC,EAAIH,CAAI,CAAA,CAAA,CACzE,EACA,SAAU,QCrBL,IAAMI,GAAuDC,GAClE,SAACC,EAAM,CACL,OAAA,UAAoC,CAClCA,EAAO,IAAI,EACX,KAAK,KAAO,0BACZ,KAAK,QAAU,qBACjB,CAJA,CAIC,ECXL,IAAAC,EAAA,SAAAC,EAAA,CAAgCC,GAAAF,EAAAC,CAAA,EAwB9B,SAAAD,GAAA,CAAA,IAAAG,EAEEF,EAAA,KAAA,IAAA,GAAO,KAzBT,OAAAE,EAAA,OAAS,GAEDA,EAAA,iBAAyC,KAGjDA,EAAA,UAA2B,CAAA,EAE3BA,EAAA,UAAY,GAEZA,EAAA,SAAW,GAEXA,EAAA,YAAmB,MAenB,CAGA,OAAAH,EAAA,UAAA,KAAA,SAAQI,EAAwB,CAC9B,IAAMC,EAAU,IAAIC,GAAiB,KAAM,IAAI,EAC/C,OAAAD,EAAQ,SAAWD,EACZC,CACT,EAGUL,EAAA,UAAA,eAAV,UAAA,CACE,GAAI,KAAK,OACP,MAAM,IAAIO,EAEd,EAEAP,EAAA,UAAA,KAAA,SAAKQ,EAAQ,CAAb,IAAAL,EAAA,KACEM,GAAa,UAAA,SAEX,GADAN,EAAK,eAAc,EACf,CAACA,EAAK,UAAW,CACdA,EAAK,mBACRA,EAAK,iBAAmB,MAAM,KAAKA,EAAK,SAAS,OAEnD,QAAuBO,EAAAC,GAAAR,EAAK,gBAAgB,EAAAS,EAAAF,EAAA,KAAA,EAAA,CAAAE,EAAA,KAAAA,EAAAF,EAAA,KAAA,EAAE,CAAzC,IAAMG,EAAQD,EAAA,MACjBC,EAAS,KAAKL,CAAK,qGAGzB,CAAC,CACH,EAEAR,EAAA,UAAA,MAAA,SAAMc,EAAQ,CAAd,IAAAX,EAAA,KACEM,GAAa,UAAA,CAEX,GADAN,EAAK,eAAc,EACf,CAACA,EAAK,UAAW,CACnBA,EAAK,SAAWA,EAAK,UAAY,GACjCA,EAAK,YAAcW,EAEnB,QADQC,EAAcZ,EAAI,UACnBY,EAAU,QACfA,EAAU,MAAK,EAAI,MAAMD,CAAG,EAGlC,CAAC,CACH,EAEAd,EAAA,UAAA,SAAA,UAAA,CAAA,IAAAG,EAAA,KACEM,GAAa,UAAA,CAEX,GADAN,EAAK,eAAc,EACf,CAACA,EAAK,UAAW,CACnBA,EAAK,UAAY,GAEjB,QADQY,EAAcZ,EAAI,UACnBY,EAAU,QACfA,EAAU,MAAK,EAAI,SAAQ,EAGjC,CAAC,CACH,EAEAf,EAAA,UAAA,YAAA,UAAA,CACE,KAAK,UAAY,KAAK,OAAS,GAC/B,KAAK,UAAY,KAAK,iBAAmB,IAC3C,EAEA,OAAA,eAAIA,EAAA,UAAA,WAAQ,KAAZ,UAAA,OACE,QAAOgB,EAAA,KAAK,aAAS,MAAAA,IAAA,OAAA,OAAAA,EAAE,QAAS,CAClC,kCAGUhB,EAAA,UAAA,cAAV,SAAwBiB,EAAyB,CAC/C,YAAK,eAAc,EACZhB,EAAA,UAAM,cAAa,KAAA,KAACgB,CAAU,CACvC,EAGUjB,EAAA,UAAA,WAAV,SAAqBiB,EAAyB,CAC5C,YAAK,eAAc,EACnB,KAAK,wBAAwBA,CAAU,EAChC,KAAK,gBAAgBA,CAAU,CACxC,EAGUjB,EAAA,UAAA,gBAAV,SAA0BiB,EAA2B,CAArD,IAAAd,EAAA,KACQa,EAAqC,KAAnCE,EAAQF,EAAA,SAAEG,EAASH,EAAA,UAAED,EAASC,EAAA,UACtC,OAAIE,GAAYC,EACPC,IAET,KAAK,iBAAmB,KACxBL,EAAU,KAAKE,CAAU,EAClB,IAAII,GAAa,UAAA,CACtBlB,EAAK,iBAAmB,KACxBmB,GAAUP,EAAWE,CAAU,CACjC,CAAC,EACH,EAGUjB,EAAA,UAAA,wBAAV,SAAkCiB,EAA2B,CACrD,IAAAD,EAAuC,KAArCE,EAAQF,EAAA,SAAEO,EAAWP,EAAA,YAAEG,EAASH,EAAA,UACpCE,EACFD,EAAW,MAAMM,CAAW,EACnBJ,GACTF,EAAW,SAAQ,CAEvB,EAQAjB,EAAA,UAAA,aAAA,UAAA,CACE,IAAMwB,EAAkB,IAAIC,EAC5B,OAAAD,EAAW,OAAS,KACbA,CACT,EAxHOxB,EAAA,OAAkC,SAAI0B,EAA0BC,EAAqB,CAC1F,OAAO,IAAIrB,GAAoBoB,EAAaC,CAAM,CACpD,EAuHF3B,GA7IgCyB,CAAU,EAkJ1C,IAAAG,GAAA,SAAAC,EAAA,CAAyCC,GAAAF,EAAAC,CAAA,EACvC,SAAAD,EAESG,EACPC,EAAsB,CAHxB,IAAAC,EAKEJ,EAAA,KAAA,IAAA,GAAO,KAHA,OAAAI,EAAA,YAAAF,EAIPE,EAAK,OAASD,GAChB,CAEA,OAAAJ,EAAA,UAAA,KAAA,SAAKM,EAAQ,UACXC,GAAAC,EAAA,KAAK,eAAW,MAAAA,IAAA,OAAA,OAAAA,EAAE,QAAI,MAAAD,IAAA,QAAAA,EAAA,KAAAC,EAAGF,CAAK,CAChC,EAEAN,EAAA,UAAA,MAAA,SAAMS,EAAQ,UACZF,GAAAC,EAAA,KAAK,eAAW,MAAAA,IAAA,OAAA,OAAAA,EAAE,SAAK,MAAAD,IAAA,QAAAA,EAAA,KAAAC,EAAGC,CAAG,CAC/B,EAEAT,EAAA,UAAA,SAAA,UAAA,UACEO,GAAAC,EAAA,KAAK,eAAW,MAAAA,IAAA,OAAA,OAAAA,EAAE,YAAQ,MAAAD,IAAA,QAAAA,EAAA,KAAAC,CAAA,CAC5B,EAGUR,EAAA,UAAA,WAAV,SAAqBU,EAAyB,SAC5C,OAAOH,GAAAC,EAAA,KAAK,UAAM,MAAAA,IAAA,OAAA,OAAAA,EAAE,UAAUE,CAAU,KAAC,MAAAH,IAAA,OAAAA,EAAII,EAC/C,EACFX,CAAA,EA1ByCY,CAAO,EC5JzC,IAAMC,GAA+C,CAC1D,IAAG,UAAA,CAGD,OAAQA,GAAsB,UAAY,MAAM,IAAG,CACrD,EACA,SAAU,QCwBZ,IAAAC,GAAA,SAAAC,EAAA,CAAsCC,GAAAF,EAAAC,CAAA,EAUpC,SAAAD,EACUG,EACAC,EACAC,EAA6D,CAF7DF,IAAA,SAAAA,EAAA,KACAC,IAAA,SAAAA,EAAA,KACAC,IAAA,SAAAA,EAAAC,IAHV,IAAAC,EAKEN,EAAA,KAAA,IAAA,GAAO,KAJC,OAAAM,EAAA,YAAAJ,EACAI,EAAA,YAAAH,EACAG,EAAA,mBAAAF,EAZFE,EAAA,QAA0B,CAAA,EAC1BA,EAAA,oBAAsB,GAc5BA,EAAK,oBAAsBH,IAAgB,IAC3CG,EAAK,YAAc,KAAK,IAAI,EAAGJ,CAAW,EAC1CI,EAAK,YAAc,KAAK,IAAI,EAAGH,CAAW,GAC5C,CAEA,OAAAJ,EAAA,UAAA,KAAA,SAAKQ,EAAQ,CACL,IAAAC,EAA+E,KAA7EC,EAASD,EAAA,UAAEE,EAAOF,EAAA,QAAEG,EAAmBH,EAAA,oBAAEJ,EAAkBI,EAAA,mBAAEL,EAAWK,EAAA,YAC3EC,IACHC,EAAQ,KAAKH,CAAK,EAClB,CAACI,GAAuBD,EAAQ,KAAKN,EAAmB,IAAG,EAAKD,CAAW,GAE7E,KAAK,YAAW,EAChBH,EAAA,UAAM,KAAI,KAAA,KAACO,CAAK,CAClB,EAGUR,EAAA,UAAA,WAAV,SAAqBa,EAAyB,CAC5C,KAAK,eAAc,EACnB,KAAK,YAAW,EAQhB,QANMC,EAAe,KAAK,gBAAgBD,CAAU,EAE9CJ,EAAmC,KAAjCG,EAAmBH,EAAA,oBAAEE,EAAOF,EAAA,QAG9BM,EAAOJ,EAAQ,MAAK,EACjBK,EAAI,EAAGA,EAAID,EAAK,QAAU,CAACF,EAAW,OAAQG,GAAKJ,EAAsB,EAAI,EACpFC,EAAW,KAAKE,EAAKC,EAAO,EAG9B,YAAK,wBAAwBH,CAAU,EAEhCC,CACT,EAEQd,EAAA,UAAA,YAAR,UAAA,CACQ,IAAAS,EAAoE,KAAlEN,EAAWM,EAAA,YAAEJ,EAAkBI,EAAA,mBAAEE,EAAOF,EAAA,QAAEG,EAAmBH,EAAA,oBAK/DQ,GAAsBL,EAAsB,EAAI,GAAKT,EAK3D,GAJAA,EAAc,KAAYc,EAAqBN,EAAQ,QAAUA,EAAQ,OAAO,EAAGA,EAAQ,OAASM,CAAkB,EAIlH,CAACL,EAAqB,CAKxB,QAJMM,EAAMb,EAAmB,IAAG,EAC9Bc,EAAO,EAGFH,EAAI,EAAGA,EAAIL,EAAQ,QAAWA,EAAQK,IAAiBE,EAAKF,GAAK,EACxEG,EAAOH,EAETG,GAAQR,EAAQ,OAAO,EAAGQ,EAAO,CAAC,EAEtC,EACFnB,CAAA,EAzEsCoB,CAAO,EClB7C,IAAAC,GAAA,SAAAC,EAAA,CAA+BC,GAAAF,EAAAC,CAAA,EAC7B,SAAAD,EAAYG,EAAsBC,EAAmD,QACnFH,EAAA,KAAA,IAAA,GAAO,IACT,CAWO,OAAAD,EAAA,UAAA,SAAP,SAAgBK,EAAWC,EAAiB,CAAjB,OAAAA,IAAA,SAAAA,EAAA,GAClB,IACT,EACFN,CAAA,EAjB+BO,EAAY,ECHpC,IAAMC,GAAqC,CAGhD,YAAA,SAAYC,EAAqBC,EAAgB,SAAEC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,EAAA,GAAA,UAAAA,GACzC,IAAAC,EAAaL,GAAgB,SACrC,OAAIK,GAAQ,MAARA,EAAU,YACLA,EAAS,YAAW,MAApBA,EAAQC,EAAA,CAAaL,EAASC,CAAO,EAAAK,EAAKJ,CAAI,CAAA,CAAA,EAEhD,YAAW,MAAA,OAAAG,EAAA,CAACL,EAASC,CAAO,EAAAK,EAAKJ,CAAI,CAAA,CAAA,CAC9C,EACA,cAAA,SAAcK,EAAM,CACV,IAAAH,EAAaL,GAAgB,SACrC,QAAQK,GAAQ,KAAA,OAARA,EAAU,gBAAiB,eAAeG,CAAa,CACjE,EACA,SAAU,QCrBZ,IAAAC,GAAA,SAAAC,EAAA,CAAoCC,GAAAF,EAAAC,CAAA,EAOlC,SAAAD,EAAsBG,EAAqCC,EAAmD,CAA9G,IAAAC,EACEJ,EAAA,KAAA,KAAME,EAAWC,CAAI,GAAC,KADF,OAAAC,EAAA,UAAAF,EAAqCE,EAAA,KAAAD,EAFjDC,EAAA,QAAmB,IAI7B,CAEO,OAAAL,EAAA,UAAA,SAAP,SAAgBM,EAAWC,EAAiB,OAC1C,GADyBA,IAAA,SAAAA,EAAA,GACrB,KAAK,OACP,OAAO,KAIT,KAAK,MAAQD,EAEb,IAAME,EAAK,KAAK,GACVL,EAAY,KAAK,UAuBvB,OAAIK,GAAM,OACR,KAAK,GAAK,KAAK,eAAeL,EAAWK,EAAID,CAAK,GAKpD,KAAK,QAAU,GAEf,KAAK,MAAQA,EAEb,KAAK,IAAKE,EAAA,KAAK,MAAE,MAAAA,IAAA,OAAAA,EAAI,KAAK,eAAeN,EAAW,KAAK,GAAII,CAAK,EAE3D,IACT,EAEUP,EAAA,UAAA,eAAV,SAAyBG,EAA2BO,EAAmBH,EAAiB,CAAjB,OAAAA,IAAA,SAAAA,EAAA,GAC9DI,GAAiB,YAAYR,EAAU,MAAM,KAAKA,EAAW,IAAI,EAAGI,CAAK,CAClF,EAEUP,EAAA,UAAA,eAAV,SAAyBY,EAA4BJ,EAAkBD,EAAwB,CAE7F,GAFqEA,IAAA,SAAAA,EAAA,GAEjEA,GAAS,MAAQ,KAAK,QAAUA,GAAS,KAAK,UAAY,GAC5D,OAAOC,EAILA,GAAM,MACRG,GAAiB,cAAcH,CAAE,CAIrC,EAMOR,EAAA,UAAA,QAAP,SAAeM,EAAUC,EAAa,CACpC,GAAI,KAAK,OACP,OAAO,IAAI,MAAM,8BAA8B,EAGjD,KAAK,QAAU,GACf,IAAMM,EAAQ,KAAK,SAASP,EAAOC,CAAK,EACxC,GAAIM,EACF,OAAOA,EACE,KAAK,UAAY,IAAS,KAAK,IAAM,OAc9C,KAAK,GAAK,KAAK,eAAe,KAAK,UAAW,KAAK,GAAI,IAAI,EAE/D,EAEUb,EAAA,UAAA,SAAV,SAAmBM,EAAUQ,EAAc,CACzC,IAAIC,EAAmB,GACnBC,EACJ,GAAI,CACF,KAAK,KAAKV,CAAK,QACRW,EAAP,CACAF,EAAU,GAIVC,EAAaC,GAAQ,IAAI,MAAM,oCAAoC,EAErE,GAAIF,EACF,YAAK,YAAW,EACTC,CAEX,EAEAhB,EAAA,UAAA,YAAA,UAAA,CACE,GAAI,CAAC,KAAK,OAAQ,CACV,IAAAS,EAAoB,KAAlBD,EAAEC,EAAA,GAAEN,EAASM,EAAA,UACbS,EAAYf,EAAS,QAE7B,KAAK,KAAO,KAAK,MAAQ,KAAK,UAAY,KAC1C,KAAK,QAAU,GAEfgB,GAAUD,EAAS,IAAI,EACnBV,GAAM,OACR,KAAK,GAAK,KAAK,eAAeL,EAAWK,EAAI,IAAI,GAGnD,KAAK,MAAQ,KACbP,EAAA,UAAM,YAAW,KAAA,IAAA,EAErB,EACFD,CAAA,EA9IoCoB,EAAM,ECgB1C,IAAAC,GAAA,UAAA,CAGE,SAAAA,EAAoBC,EAAoCC,EAAiC,CAAjCA,IAAA,SAAAA,EAAoBF,EAAU,KAAlE,KAAA,oBAAAC,EAClB,KAAK,IAAMC,CACb,CA6BO,OAAAF,EAAA,UAAA,SAAP,SAAmBG,EAAqDC,EAAmBC,EAAS,CAA5B,OAAAD,IAAA,SAAAA,EAAA,GAC/D,IAAI,KAAK,oBAAuB,KAAMD,CAAI,EAAE,SAASE,EAAOD,CAAK,CAC1E,EAnCcJ,EAAA,IAAoBM,GAAsB,IAoC1DN,GArCA,ECnBA,IAAAO,GAAA,SAAAC,EAAA,CAAoCC,GAAAF,EAAAC,CAAA,EAkBlC,SAAAD,EAAYG,EAAgCC,EAAiC,CAAjCA,IAAA,SAAAA,EAAoBC,GAAU,KAA1E,IAAAC,EACEL,EAAA,KAAA,KAAME,EAAiBC,CAAG,GAAC,KAlBtB,OAAAE,EAAA,QAAmC,CAAA,EAOnCA,EAAA,QAAmB,IAY1B,CAEO,OAAAN,EAAA,UAAA,MAAP,SAAaO,EAAwB,CAC3B,IAAAC,EAAY,KAAI,QAExB,GAAI,KAAK,QAAS,CAChBA,EAAQ,KAAKD,CAAM,EACnB,OAGF,IAAIE,EACJ,KAAK,QAAU,GAEf,EACE,IAAKA,EAAQF,EAAO,QAAQA,EAAO,MAAOA,EAAO,KAAK,EACpD,YAEMA,EAASC,EAAQ,MAAK,GAIhC,GAFA,KAAK,QAAU,GAEXC,EAAO,CACT,KAAQF,EAASC,EAAQ,MAAK,GAC5BD,EAAO,YAAW,EAEpB,MAAME,EAEV,EACFT,CAAA,EAhDoCK,EAAS,EC6CtC,IAAMK,GAAiB,IAAIC,GAAeC,EAAW,EAK/CC,GAAQH,GCjDrB,IAAAI,GAAA,SAAAC,EAAA,CAA6CC,GAAAF,EAAAC,CAAA,EAC3C,SAAAD,EAAsBG,EAA8CC,EAAmD,CAAvH,IAAAC,EACEJ,EAAA,KAAA,KAAME,EAAWC,CAAI,GAAC,KADF,OAAAC,EAAA,UAAAF,EAA8CE,EAAA,KAAAD,GAEpE,CAEU,OAAAJ,EAAA,UAAA,eAAV,SAAyBG,EAAoCG,EAAkBC,EAAiB,CAE9F,OAF6EA,IAAA,SAAAA,EAAA,GAEzEA,IAAU,MAAQA,EAAQ,EACrBN,EAAA,UAAM,eAAc,KAAA,KAACE,EAAWG,EAAIC,CAAK,GAGlDJ,EAAU,QAAQ,KAAK,IAAI,EAIpBA,EAAU,aAAeA,EAAU,WAAaK,GAAuB,sBAAsB,UAAA,CAAM,OAAAL,EAAU,MAAM,MAAS,CAAzB,CAA0B,GACtI,EAEUH,EAAA,UAAA,eAAV,SAAyBG,EAAoCG,EAAkBC,EAAiB,OAI9F,GAJ6EA,IAAA,SAAAA,EAAA,GAIzEA,GAAS,KAAOA,EAAQ,EAAI,KAAK,MAAQ,EAC3C,OAAON,EAAA,UAAM,eAAc,KAAA,KAACE,EAAWG,EAAIC,CAAK,EAK1C,IAAAE,EAAYN,EAAS,QACzBG,GAAM,QAAQI,EAAAD,EAAQA,EAAQ,OAAS,MAAE,MAAAC,IAAA,OAAA,OAAAA,EAAE,MAAOJ,IACpDE,GAAuB,qBAAqBF,CAAY,EACxDH,EAAU,WAAa,OAI3B,EACFH,CAAA,EApC6CW,EAAW,ECHxD,IAAAC,GAAA,SAAAC,EAAA,CAA6CC,GAAAF,EAAAC,CAAA,EAA7C,SAAAD,GAAA,+CAkCA,CAjCS,OAAAA,EAAA,UAAA,MAAP,SAAaG,EAAyB,CACpC,KAAK,QAAU,GAUf,IAAMC,EAAU,KAAK,WACrB,KAAK,WAAa,OAEV,IAAAC,EAAY,KAAI,QACpBC,EACJH,EAASA,GAAUE,EAAQ,MAAK,EAEhC,EACE,IAAKC,EAAQH,EAAO,QAAQA,EAAO,MAAOA,EAAO,KAAK,EACpD,aAEMA,EAASE,EAAQ,KAAOF,EAAO,KAAOC,GAAWC,EAAQ,MAAK,GAIxE,GAFA,KAAK,QAAU,GAEXC,EAAO,CACT,MAAQH,EAASE,EAAQ,KAAOF,EAAO,KAAOC,GAAWC,EAAQ,MAAK,GACpEF,EAAO,YAAW,EAEpB,MAAMG,EAEV,EACFN,CAAA,EAlC6CO,EAAc,ECgCpD,IAAMC,GAA0B,IAAIC,GAAwBC,EAAoB,EC8BhF,IAAMC,EAAQ,IAAIC,EAAkB,SAACC,EAAU,CAAK,OAAAA,EAAW,SAAQ,CAAnB,CAAqB,EC9D1E,SAAUC,GAAYC,EAAU,CACpC,OAAOA,GAASC,EAAWD,EAAM,QAAQ,CAC3C,CCDA,SAASE,GAAQC,EAAQ,CACvB,OAAOA,EAAIA,EAAI,OAAS,EAC1B,CAEM,SAAUC,GAAkBC,EAAW,CAC3C,OAAOC,EAAWJ,GAAKG,CAAI,CAAC,EAAIA,EAAK,IAAG,EAAK,MAC/C,CAEM,SAAUE,GAAaF,EAAW,CACtC,OAAOG,GAAYN,GAAKG,CAAI,CAAC,EAAIA,EAAK,IAAG,EAAK,MAChD,CAEM,SAAUI,GAAUJ,EAAaK,EAAoB,CACzD,OAAO,OAAOR,GAAKG,CAAI,GAAM,SAAWA,EAAK,IAAG,EAAMK,CACxD,CClBO,IAAMC,GAAe,SAAIC,EAAM,CAAwB,OAAAA,GAAK,OAAOA,EAAE,QAAW,UAAY,OAAOA,GAAM,UAAlD,ECMxD,SAAUC,GAAUC,EAAU,CAClC,OAAOC,EAAWD,GAAK,KAAA,OAALA,EAAO,IAAI,CAC/B,CCHM,SAAUE,GAAoBC,EAAU,CAC5C,OAAOC,EAAWD,EAAME,GAAkB,CAC5C,CCLM,SAAUC,GAAmBC,EAAQ,CACzC,OAAO,OAAO,eAAiBC,EAAWD,GAAG,KAAA,OAAHA,EAAM,OAAO,cAAc,CACvE,CCAM,SAAUE,GAAiCC,EAAU,CAEzD,OAAO,IAAI,UACT,iBACEA,IAAU,MAAQ,OAAOA,GAAU,SAAW,oBAAsB,IAAIA,EAAK,KAAG,0HACwC,CAE9H,CCXM,SAAUC,IAAiB,CAC/B,OAAI,OAAO,QAAW,YAAc,CAAC,OAAO,SACnC,aAGF,OAAO,QAChB,CAEO,IAAMC,GAAWD,GAAiB,ECJnC,SAAUE,GAAWC,EAAU,CACnC,OAAOC,EAAWD,GAAK,KAAA,OAALA,EAAQE,GAAgB,CAC5C,CCHM,SAAiBC,GAAsCC,EAAqC,mGAC1FC,EAASD,EAAe,UAAS,2DAGX,MAAA,CAAA,EAAAE,GAAMD,EAAO,KAAI,CAAE,CAAA,gBAArCE,EAAkBC,EAAA,KAAA,EAAhBC,EAAKF,EAAA,MAAEG,EAAIH,EAAA,KACfG,iBAAA,CAAA,EAAA,CAAA,SACF,MAAA,CAAA,EAAAF,EAAA,KAAA,CAAA,qBAEIC,CAAM,CAAA,SAAZ,MAAA,CAAA,EAAAD,EAAA,KAAA,CAAA,SAAA,OAAAA,EAAA,KAAA,mCAGF,OAAAH,EAAO,YAAW,6BAIhB,SAAUM,GAAwBC,EAAQ,CAG9C,OAAOC,EAAWD,GAAG,KAAA,OAAHA,EAAK,SAAS,CAClC,CCPM,SAAUE,EAAaC,EAAyB,CACpD,GAAIA,aAAiBC,EACnB,OAAOD,EAET,GAAIA,GAAS,KAAM,CACjB,GAAIE,GAAoBF,CAAK,EAC3B,OAAOG,GAAsBH,CAAK,EAEpC,GAAII,GAAYJ,CAAK,EACnB,OAAOK,GAAcL,CAAK,EAE5B,GAAIM,GAAUN,CAAK,EACjB,OAAOO,GAAYP,CAAK,EAE1B,GAAIQ,GAAgBR,CAAK,EACvB,OAAOS,GAAkBT,CAAK,EAEhC,GAAIU,GAAWV,CAAK,EAClB,OAAOW,GAAaX,CAAK,EAE3B,GAAIY,GAAqBZ,CAAK,EAC5B,OAAOa,GAAuBb,CAAK,EAIvC,MAAMc,GAAiCd,CAAK,CAC9C,CAMM,SAAUG,GAAyBY,EAAQ,CAC/C,OAAO,IAAId,EAAW,SAACe,EAAyB,CAC9C,IAAMC,EAAMF,EAAIG,IAAkB,EAClC,GAAIC,EAAWF,EAAI,SAAS,EAC1B,OAAOA,EAAI,UAAUD,CAAU,EAGjC,MAAM,IAAI,UAAU,gEAAgE,CACtF,CAAC,CACH,CASM,SAAUX,GAAiBe,EAAmB,CAClD,OAAO,IAAInB,EAAW,SAACe,EAAyB,CAU9C,QAASK,EAAI,EAAGA,EAAID,EAAM,QAAU,CAACJ,EAAW,OAAQK,IACtDL,EAAW,KAAKI,EAAMC,EAAE,EAE1BL,EAAW,SAAQ,CACrB,CAAC,CACH,CAEM,SAAUT,GAAee,EAAuB,CACpD,OAAO,IAAIrB,EAAW,SAACe,EAAyB,CAC9CM,EACG,KACC,SAACC,EAAK,CACCP,EAAW,SACdA,EAAW,KAAKO,CAAK,EACrBP,EAAW,SAAQ,EAEvB,EACA,SAACQ,EAAQ,CAAK,OAAAR,EAAW,MAAMQ,CAAG,CAApB,CAAqB,EAEpC,KAAK,KAAMC,EAAoB,CACpC,CAAC,CACH,CAEM,SAAUd,GAAgBe,EAAqB,CACnD,OAAO,IAAIzB,EAAW,SAACe,EAAyB,aAC9C,QAAoBW,EAAAC,GAAAF,CAAQ,EAAAG,EAAAF,EAAA,KAAA,EAAA,CAAAE,EAAA,KAAAA,EAAAF,EAAA,KAAA,EAAE,CAAzB,IAAMJ,EAAKM,EAAA,MAEd,GADAb,EAAW,KAAKO,CAAK,EACjBP,EAAW,OACb,yGAGJA,EAAW,SAAQ,CACrB,CAAC,CACH,CAEM,SAAUP,GAAqBqB,EAA+B,CAClE,OAAO,IAAI7B,EAAW,SAACe,EAAyB,CAC9Ce,GAAQD,EAAed,CAAU,EAAE,MAAM,SAACQ,EAAG,CAAK,OAAAR,EAAW,MAAMQ,CAAG,CAApB,CAAqB,CACzE,CAAC,CACH,CAEM,SAAUX,GAA0BmB,EAAqC,CAC7E,OAAOvB,GAAkBwB,GAAmCD,CAAc,CAAC,CAC7E,CAEA,SAAeD,GAAWD,EAAiCd,EAAyB,uIACxDkB,EAAAC,GAAAL,CAAa,gFAIrC,GAJeP,EAAKa,EAAA,MACpBpB,EAAW,KAAKO,CAAK,EAGjBP,EAAW,OACb,MAAA,CAAA,CAAA,6RAGJ,OAAAA,EAAW,SAAQ,WChHf,SAAUqB,GACdC,EACAC,EACAC,EACAC,EACAC,EAAc,CADdD,IAAA,SAAAA,EAAA,GACAC,IAAA,SAAAA,EAAA,IAEA,IAAMC,EAAuBJ,EAAU,SAAS,UAAA,CAC9CC,EAAI,EACAE,EACFJ,EAAmB,IAAI,KAAK,SAAS,KAAMG,CAAK,CAAC,EAEjD,KAAK,YAAW,CAEpB,EAAGA,CAAK,EAIR,GAFAH,EAAmB,IAAIK,CAAoB,EAEvC,CAACD,EAKH,OAAOC,CAEX,CCeM,SAAUC,GAAaC,EAA0BC,EAAS,CAAT,OAAAA,IAAA,SAAAA,EAAA,GAC9CC,EAAQ,SAACC,EAAQC,EAAU,CAChCD,EAAO,UACLE,EACED,EACA,SAACE,EAAK,CAAK,OAAAC,GAAgBH,EAAYJ,EAAW,UAAA,CAAM,OAAAI,EAAW,KAAKE,CAAK,CAArB,EAAwBL,CAAK,CAA1E,EACX,UAAA,CAAM,OAAAM,GAAgBH,EAAYJ,EAAW,UAAA,CAAM,OAAAI,EAAW,SAAQ,CAAnB,EAAuBH,CAAK,CAAzE,EACN,SAACO,EAAG,CAAK,OAAAD,GAAgBH,EAAYJ,EAAW,UAAA,CAAM,OAAAI,EAAW,MAAMI,CAAG,CAApB,EAAuBP,CAAK,CAAzE,CAA0E,CACpF,CAEL,CAAC,CACH,CCPM,SAAUQ,GAAeC,EAA0BC,EAAiB,CAAjB,OAAAA,IAAA,SAAAA,EAAA,GAChDC,EAAQ,SAACC,EAAQC,EAAU,CAChCA,EAAW,IAAIJ,EAAU,SAAS,UAAA,CAAM,OAAAG,EAAO,UAAUC,CAAU,CAA3B,EAA8BH,CAAK,CAAC,CAC9E,CAAC,CACH,CC7DM,SAAUI,GAAsBC,EAA6BC,EAAwB,CACzF,OAAOC,EAAUF,CAAK,EAAE,KAAKG,GAAYF,CAAS,EAAGG,GAAUH,CAAS,CAAC,CAC3E,CCFM,SAAUI,GAAmBC,EAAuBC,EAAwB,CAChF,OAAOC,EAAUF,CAAK,EAAE,KAAKG,GAAYF,CAAS,EAAGG,GAAUH,CAAS,CAAC,CAC3E,CCJM,SAAUI,GAAiBC,EAAqBC,EAAwB,CAC5E,OAAO,IAAIC,EAAc,SAACC,EAAU,CAElC,IAAIC,EAAI,EAER,OAAOH,EAAU,SAAS,UAAA,CACpBG,IAAMJ,EAAM,OAGdG,EAAW,SAAQ,GAInBA,EAAW,KAAKH,EAAMI,IAAI,EAIrBD,EAAW,QACd,KAAK,SAAQ,EAGnB,CAAC,CACH,CAAC,CACH,CCfM,SAAUE,GAAoBC,EAAoBC,EAAwB,CAC9E,OAAO,IAAIC,EAAc,SAACC,EAAU,CAClC,IAAIC,EAKJ,OAAAC,GAAgBF,EAAYF,EAAW,UAAA,CAErCG,EAAYJ,EAAcI,IAAgB,EAE1CC,GACEF,EACAF,EACA,UAAA,OACMK,EACAC,EACJ,GAAI,CAEDC,EAAkBJ,EAAS,KAAI,EAA7BE,EAAKE,EAAA,MAAED,EAAIC,EAAA,WACPC,EAAP,CAEAN,EAAW,MAAMM,CAAG,EACpB,OAGEF,EAKFJ,EAAW,SAAQ,EAGnBA,EAAW,KAAKG,CAAK,CAEzB,EACA,EACA,EAAI,CAER,CAAC,EAMM,UAAA,CAAM,OAAAI,EAAWN,GAAQ,KAAA,OAARA,EAAU,MAAM,GAAKA,EAAS,OAAM,CAA/C,CACf,CAAC,CACH,CCvDM,SAAUO,GAAyBC,EAAyBC,EAAwB,CACxF,GAAI,CAACD,EACH,MAAM,IAAI,MAAM,yBAAyB,EAE3C,OAAO,IAAIE,EAAc,SAACC,EAAU,CAClCC,GAAgBD,EAAYF,EAAW,UAAA,CACrC,IAAMI,EAAWL,EAAM,OAAO,eAAc,EAC5CI,GACED,EACAF,EACA,UAAA,CACEI,EAAS,KAAI,EAAG,KAAK,SAACC,EAAM,CACtBA,EAAO,KAGTH,EAAW,SAAQ,EAEnBA,EAAW,KAAKG,EAAO,KAAK,CAEhC,CAAC,CACH,EACA,EACA,EAAI,CAER,CAAC,CACH,CAAC,CACH,CCzBM,SAAUC,GAA8BC,EAA8BC,EAAwB,CAClG,OAAOC,GAAsBC,GAAmCH,CAAK,EAAGC,CAAS,CACnF,CCoBM,SAAUG,GAAaC,EAA2BC,EAAwB,CAC9E,GAAID,GAAS,KAAM,CACjB,GAAIE,GAAoBF,CAAK,EAC3B,OAAOG,GAAmBH,EAAOC,CAAS,EAE5C,GAAIG,GAAYJ,CAAK,EACnB,OAAOK,GAAcL,EAAOC,CAAS,EAEvC,GAAIK,GAAUN,CAAK,EACjB,OAAOO,GAAgBP,EAAOC,CAAS,EAEzC,GAAIO,GAAgBR,CAAK,EACvB,OAAOS,GAAsBT,EAAOC,CAAS,EAE/C,GAAIS,GAAWV,CAAK,EAClB,OAAOW,GAAiBX,EAAOC,CAAS,EAE1C,GAAIW,GAAqBZ,CAAK,EAC5B,OAAOa,GAA2Bb,EAAOC,CAAS,EAGtD,MAAMa,GAAiCd,CAAK,CAC9C,CCoDM,SAAUe,GAAQC,EAA2BC,EAAyB,CAC1E,OAAOA,EAAYC,GAAUF,EAAOC,CAAS,EAAIE,EAAUH,CAAK,CAClE,CCxBM,SAAUI,GAAE,SAAIC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACpB,IAAMC,EAAYC,GAAaH,CAAI,EACnC,OAAOI,GAAKJ,EAAaE,CAAS,CACpC,CCsCM,SAAUG,GAAWC,EAA0BC,EAAyB,CAC5E,IAAMC,EAAeC,EAAWH,CAAmB,EAAIA,EAAsB,UAAA,CAAM,OAAAA,CAAA,EAC7EI,EAAO,SAACC,EAA6B,CAAK,OAAAA,EAAW,MAAMH,EAAY,CAAE,CAA/B,EAChD,OAAO,IAAII,EAAWL,EAAY,SAACI,EAAU,CAAK,OAAAJ,EAAU,SAASG,EAAa,EAAGC,CAAU,CAA7C,EAAiDD,CAAI,CACzG,CCrHM,SAAUG,GAAYC,EAAU,CACpC,OAAOA,aAAiB,MAAQ,CAAC,MAAMA,CAAY,CACrD,CCsCM,SAAUC,EAAUC,EAAyCC,EAAa,CAC9E,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAEhC,IAAIC,EAAQ,EAGZF,EAAO,UACLG,EAAyBF,EAAY,SAACG,EAAQ,CAG5CH,EAAW,KAAKJ,EAAQ,KAAKC,EAASM,EAAOF,GAAO,CAAC,CACvD,CAAC,CAAC,CAEN,CAAC,CACH,CC1DQ,IAAAG,GAAY,MAAK,QAEzB,SAASC,GAAkBC,EAA6BC,EAAW,CAC/D,OAAOH,GAAQG,CAAI,EAAID,EAAE,MAAA,OAAAE,EAAA,CAAA,EAAAC,EAAIF,CAAI,CAAA,CAAA,EAAID,EAAGC,CAAI,CAChD,CAMM,SAAUG,GAAuBJ,EAA2B,CAC9D,OAAOK,EAAI,SAAAJ,EAAI,CAAI,OAAAF,GAAYC,EAAIC,CAAI,CAApB,CAAqB,CAC5C,CCfQ,IAAAK,GAAY,MAAK,QACjBC,GAA0D,OAAM,eAArCC,GAA+B,OAAM,UAAlBC,GAAY,OAAM,KAQlE,SAAUC,GAAqDC,EAAuB,CAC1F,GAAIA,EAAK,SAAW,EAAG,CACrB,IAAMC,EAAQD,EAAK,GACnB,GAAIL,GAAQM,CAAK,EACf,MAAO,CAAE,KAAMA,EAAO,KAAM,IAAI,EAElC,GAAIC,GAAOD,CAAK,EAAG,CACjB,IAAME,EAAOL,GAAQG,CAAK,EAC1B,MAAO,CACL,KAAME,EAAK,IAAI,SAACC,EAAG,CAAK,OAAAH,EAAMG,EAAN,CAAU,EAClC,KAAID,IAKV,MAAO,CAAE,KAAMH,EAAa,KAAM,IAAI,CACxC,CAEA,SAASE,GAAOG,EAAQ,CACtB,OAAOA,GAAO,OAAOA,GAAQ,UAAYT,GAAeS,CAAG,IAAMR,EACnE,CC7BM,SAAUS,GAAaC,EAAgBC,EAAa,CACxD,OAAOD,EAAK,OAAO,SAACE,EAAQC,EAAKC,EAAC,CAAK,OAAEF,EAAOC,GAAOF,EAAOG,GAAKF,CAA5B,EAAqC,CAAA,CAAS,CACvF,CCsMM,SAAUG,GAAa,SAAoCC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAC/D,IAAMC,EAAYC,GAAaH,CAAI,EAC7BI,EAAiBC,GAAkBL,CAAI,EAEvCM,EAA8BC,GAAqBP,CAAI,EAA/CQ,EAAWF,EAAA,KAAEG,EAAIH,EAAA,KAE/B,GAAIE,EAAY,SAAW,EAIzB,OAAOE,GAAK,CAAA,EAAIR,CAAgB,EAGlC,IAAMS,EAAS,IAAIC,EACjBC,GACEL,EACAN,EACAO,EAEI,SAACK,EAAM,CAAK,OAAAC,GAAaN,EAAMK,CAAM,CAAzB,EAEZE,EAAQ,CACb,EAGH,OAAOZ,EAAkBO,EAAO,KAAKM,GAAiBb,CAAc,CAAC,EAAsBO,CAC7F,CAEM,SAAUE,GACdL,EACAN,EACAgB,EAAiD,CAAjD,OAAAA,IAAA,SAAAA,EAAAF,IAEO,SAACG,EAA2B,CAGjCC,GACElB,EACA,UAAA,CAaE,QAZQmB,EAAWb,EAAW,OAExBM,EAAS,IAAI,MAAMO,CAAM,EAG3BC,EAASD,EAITE,EAAuBF,aAGlBG,EAAC,CACRJ,GACElB,EACA,UAAA,CACE,IAAMuB,EAASf,GAAKF,EAAYgB,GAAItB,CAAgB,EAChDwB,EAAgB,GACpBD,EAAO,UACLE,EACER,EACA,SAACS,EAAK,CAEJd,EAAOU,GAAKI,EACPF,IAEHA,EAAgB,GAChBH,KAEGA,GAGHJ,EAAW,KAAKD,EAAeJ,EAAO,MAAK,CAAE,CAAC,CAElD,EACA,UAAA,CACO,EAAEQ,GAGLH,EAAW,SAAQ,CAEvB,CAAC,CACF,CAEL,EACAA,CAAU,GAjCLK,EAAI,EAAGA,EAAIH,EAAQG,MAAnBA,CAAC,CAoCZ,EACAL,CAAU,CAEd,CACF,CAMA,SAASC,GAAclB,EAAsC2B,EAAqBC,EAA0B,CACtG5B,EACF6B,GAAgBD,EAAc5B,EAAW2B,CAAO,EAEhDA,EAAO,CAEX,CC3RM,SAAUG,GACdC,EACAC,EACAC,EACAC,EACAC,EACAC,EACAC,EACAC,EAAgC,CAGhC,IAAMC,EAAc,CAAA,EAEhBC,EAAS,EAETC,EAAQ,EAERC,EAAa,GAKXC,EAAgB,UAAA,CAIhBD,GAAc,CAACH,EAAO,QAAU,CAACC,GACnCR,EAAW,SAAQ,CAEvB,EAGMY,EAAY,SAACC,EAAQ,CAAK,OAACL,EAASN,EAAaY,EAAWD,CAAK,EAAIN,EAAO,KAAKM,CAAK,CAA5D,EAE1BC,EAAa,SAACD,EAAQ,CAI1BT,GAAUJ,EAAW,KAAKa,CAAY,EAItCL,IAKA,IAAIO,EAAgB,GAGpBC,EAAUf,EAAQY,EAAOJ,GAAO,CAAC,EAAE,UACjCQ,EACEjB,EACA,SAACkB,EAAU,CAGTf,GAAY,MAAZA,EAAee,CAAU,EAErBd,EAGFQ,EAAUM,CAAiB,EAG3BlB,EAAW,KAAKkB,CAAU,CAE9B,EACA,UAAA,CAGEH,EAAgB,EAClB,EAEA,OACA,UAAA,CAIE,GAAIA,EAKF,GAAI,CAIFP,IAKA,qBACE,IAAMW,EAAgBZ,EAAO,MAAK,EAI9BF,EACFe,GAAgBpB,EAAYK,EAAmB,UAAA,CAAM,OAAAS,EAAWK,CAAa,CAAxB,CAAyB,EAE9EL,EAAWK,CAAa,GARrBZ,EAAO,QAAUC,EAASN,OAYjCS,EAAa,QACNU,EAAP,CACArB,EAAW,MAAMqB,CAAG,EAG1B,CAAC,CACF,CAEL,EAGA,OAAAtB,EAAO,UACLkB,EAAyBjB,EAAYY,EAAW,UAAA,CAE9CF,EAAa,GACbC,EAAa,CACf,CAAC,CAAC,EAKG,UAAA,CACLL,GAAmB,MAAnBA,EAAmB,CACrB,CACF,CClEM,SAAUgB,GACdC,EACAC,EACAC,EAA6B,CAE7B,OAFAA,IAAA,SAAAA,EAAA,KAEIC,EAAWF,CAAc,EAEpBF,GAAS,SAACK,EAAGC,EAAC,CAAK,OAAAC,EAAI,SAACC,EAAQC,EAAU,CAAK,OAAAP,EAAeG,EAAGG,EAAGF,EAAGG,CAAE,CAA1B,CAA2B,EAAEC,EAAUT,EAAQI,EAAGC,CAAC,CAAC,CAAC,CAAjF,EAAoFH,CAAU,GAC/G,OAAOD,GAAmB,WACnCC,EAAaD,GAGRS,EAAQ,SAACC,EAAQC,EAAU,CAAK,OAAAC,GAAeF,EAAQC,EAAYZ,EAASE,CAAU,CAAtD,CAAuD,EAChG,CChCM,SAAUY,GAAyCC,EAA6B,CAA7B,OAAAA,IAAA,SAAAA,EAAA,KAChDC,GAASC,GAAUF,CAAU,CACtC,CCNM,SAAUG,IAAS,CACvB,OAAOC,GAAS,CAAC,CACnB,CCmDM,SAAUC,IAAM,SAACC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACrB,OAAOC,GAAS,EAAGC,GAAKH,EAAMI,GAAaJ,CAAI,CAAC,CAAC,CACnD,CC9DM,SAAUK,EAAsCC,EAA0B,CAC9E,OAAO,IAAIC,EAA+B,SAACC,EAAU,CACnDC,EAAUH,EAAiB,CAAE,EAAE,UAAUE,CAAU,CACrD,CAAC,CACH,CChDA,IAAME,GAA0B,CAAC,cAAe,gBAAgB,EAC1DC,GAAqB,CAAC,mBAAoB,qBAAqB,EAC/DC,GAAgB,CAAC,KAAM,KAAK,EA8N5B,SAAUC,EACdC,EACAC,EACAC,EACAC,EAAsC,CAMtC,GAJIC,EAAWF,CAAO,IACpBC,EAAiBD,EACjBA,EAAU,QAERC,EACF,OAAOJ,EAAaC,EAAQC,EAAWC,CAA+B,EAAE,KAAKG,GAAiBF,CAAc,CAAC,EAUzG,IAAAG,EAAAC,EAEJC,GAAcR,CAAM,EAChBH,GAAmB,IAAI,SAACY,EAAU,CAAK,OAAA,SAACC,EAAY,CAAK,OAAAV,EAAOS,GAAYR,EAAWS,EAASR,CAA+B,CAAtE,CAAlB,CAAyF,EAElIS,GAAwBX,CAAM,EAC5BJ,GAAwB,IAAIgB,GAAwBZ,EAAQC,CAAS,CAAC,EACtEY,GAA0Bb,CAAM,EAChCF,GAAc,IAAIc,GAAwBZ,EAAQC,CAAS,CAAC,EAC5D,CAAA,EAAE,CAAA,EATDa,EAAGR,EAAA,GAAES,EAAMT,EAAA,GAgBlB,GAAI,CAACQ,GACCE,GAAYhB,CAAM,EACpB,OAAOiB,GAAS,SAACC,EAAc,CAAK,OAAAnB,EAAUmB,EAAWjB,EAAWC,CAA+B,CAA/D,CAAgE,EAClGiB,EAAUnB,CAAM,CAAC,EAOvB,GAAI,CAACc,EACH,MAAM,IAAI,UAAU,sBAAsB,EAG5C,OAAO,IAAIM,EAAc,SAACC,EAAU,CAIlC,IAAMX,EAAU,UAAA,SAACY,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAAmB,OAAAF,EAAW,KAAK,EAAIC,EAAK,OAASA,EAAOA,EAAK,EAAE,CAAhD,EAEpC,OAAAR,EAAIJ,CAAO,EAEJ,UAAA,CAAM,OAAAK,EAAQL,CAAO,CAAf,CACf,CAAC,CACH,CASA,SAASE,GAAwBZ,EAAaC,EAAiB,CAC7D,OAAO,SAACQ,EAAkB,CAAK,OAAA,SAACC,EAAY,CAAK,OAAAV,EAAOS,GAAYR,EAAWS,CAAO,CAArC,CAAlB,CACjC,CAOA,SAASC,GAAwBX,EAAW,CAC1C,OAAOI,EAAWJ,EAAO,WAAW,GAAKI,EAAWJ,EAAO,cAAc,CAC3E,CAOA,SAASa,GAA0Bb,EAAW,CAC5C,OAAOI,EAAWJ,EAAO,EAAE,GAAKI,EAAWJ,EAAO,GAAG,CACvD,CAOA,SAASQ,GAAcR,EAAW,CAChC,OAAOI,EAAWJ,EAAO,gBAAgB,GAAKI,EAAWJ,EAAO,mBAAmB,CACrF,CC/LM,SAAUwB,GACdC,EACAC,EACAC,EAAsC,CAEtC,OAAIA,EACKH,GAAoBC,EAAYC,CAAa,EAAE,KAAKE,GAAiBD,CAAc,CAAC,EAGtF,IAAIE,EAAoB,SAACC,EAAU,CACxC,IAAMC,EAAU,UAAA,SAACC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAAc,OAAAH,EAAW,KAAKE,EAAE,SAAW,EAAIA,EAAE,GAAKA,CAAC,CAAzC,EACzBE,EAAWT,EAAWM,CAAO,EACnC,OAAOI,EAAWT,CAAa,EAAI,UAAA,CAAM,OAAAA,EAAcK,EAASG,CAAQ,CAA/B,EAAmC,MAC9E,CAAC,CACH,CCtBM,SAAUE,GACdC,EACAC,EACAC,EAAyC,CAFzCF,IAAA,SAAAA,EAAA,GAEAE,IAAA,SAAAA,EAAAC,IAIA,IAAIC,EAAmB,GAEvB,OAAIH,GAAuB,OAIrBI,GAAYJ,CAAmB,EACjCC,EAAYD,EAIZG,EAAmBH,GAIhB,IAAIK,EAAW,SAACC,EAAU,CAI/B,IAAIC,EAAMC,GAAYT,CAAO,EAAI,CAACA,EAAUE,EAAW,IAAG,EAAKF,EAE3DQ,EAAM,IAERA,EAAM,GAIR,IAAIE,EAAI,EAGR,OAAOR,EAAU,SAAS,UAAA,CACnBK,EAAW,SAEdA,EAAW,KAAKG,GAAG,EAEf,GAAKN,EAGP,KAAK,SAAS,OAAWA,CAAgB,EAGzCG,EAAW,SAAQ,EAGzB,EAAGC,CAAG,CACR,CAAC,CACH,CChGM,SAAUG,GAAK,SAACC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACpB,IAAMC,EAAYC,GAAaH,CAAI,EAC7BI,EAAaC,GAAUL,EAAM,GAAQ,EACrCM,EAAUN,EAChB,OAAQM,EAAQ,OAGZA,EAAQ,SAAW,EAEnBC,EAAUD,EAAQ,EAAE,EAEpBE,GAASJ,CAAU,EAAEK,GAAKH,EAASJ,CAAS,CAAC,EAL7CQ,CAMN,CCjEO,IAAMC,GAAQ,IAAIC,EAAkBC,EAAI,ECpCvC,IAAAC,GAAY,MAAK,QAMnB,SAAUC,GAAkBC,EAAiB,CACjD,OAAOA,EAAK,SAAW,GAAKF,GAAQE,EAAK,EAAE,EAAIA,EAAK,GAAMA,CAC5D,CCoDM,SAAUC,EAAUC,EAAiDC,EAAa,CACtF,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAEhC,IAAIC,EAAQ,EAIZF,EAAO,UAILG,EAAyBF,EAAY,SAACG,EAAK,CAAK,OAAAP,EAAU,KAAKC,EAASM,EAAOF,GAAO,GAAKD,EAAW,KAAKG,CAAK,CAAhE,CAAiE,CAAC,CAEtH,CAAC,CACH,CCxBM,SAAUC,IAAG,SAACC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAClB,IAAMC,EAAiBC,GAAkBH,CAAI,EAEvCI,EAAUC,GAAeL,CAAI,EAEnC,OAAOI,EAAQ,OACX,IAAIE,EAAsB,SAACC,EAAU,CAGnC,IAAIC,EAAuBJ,EAAQ,IAAI,UAAA,CAAM,MAAA,CAAA,CAAA,CAAE,EAK3CK,EAAYL,EAAQ,IAAI,UAAA,CAAM,MAAA,EAAA,CAAK,EAGvCG,EAAW,IAAI,UAAA,CACbC,EAAUC,EAAY,IACxB,CAAC,EAKD,mBAASC,EAAW,CAClBC,EAAUP,EAAQM,EAAY,EAAE,UAC9BE,EACEL,EACA,SAACM,EAAK,CAKJ,GAJAL,EAAQE,GAAa,KAAKG,CAAK,EAI3BL,EAAQ,MAAM,SAACM,EAAM,CAAK,OAAAA,EAAO,MAAP,CAAa,EAAG,CAC5C,IAAMC,EAAcP,EAAQ,IAAI,SAACM,EAAM,CAAK,OAAAA,EAAO,MAAK,CAAZ,CAAe,EAE3DP,EAAW,KAAKL,EAAiBA,EAAc,MAAA,OAAAc,EAAA,CAAA,EAAAC,EAAIF,CAAM,CAAA,CAAA,EAAIA,CAAM,EAI/DP,EAAQ,KAAK,SAACM,EAAQI,EAAC,CAAK,MAAA,CAACJ,EAAO,QAAUL,EAAUS,EAA5B,CAA8B,GAC5DX,EAAW,SAAQ,EAGzB,EACA,UAAA,CAGEE,EAAUC,GAAe,GAIzB,CAACF,EAAQE,GAAa,QAAUH,EAAW,SAAQ,CACrD,CAAC,CACF,GA9BIG,EAAc,EAAG,CAACH,EAAW,QAAUG,EAAcN,EAAQ,OAAQM,MAArEA,CAAW,EAmCpB,OAAO,UAAA,CACLF,EAAUC,EAAY,IACxB,CACF,CAAC,EACDU,CACN,CC9DM,SAAUC,GAASC,EAAoD,CAC3E,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAW,GACXC,EAAsB,KACtBC,EAA6C,KAC7CC,EAAa,GAEXC,EAAc,UAAA,CAGlB,GAFAF,GAAkB,MAAlBA,EAAoB,YAAW,EAC/BA,EAAqB,KACjBF,EAAU,CACZA,EAAW,GACX,IAAMK,EAAQJ,EACdA,EAAY,KACZF,EAAW,KAAKM,CAAK,EAEvBF,GAAcJ,EAAW,SAAQ,CACnC,EAEMO,EAAkB,UAAA,CACtBJ,EAAqB,KACrBC,GAAcJ,EAAW,SAAQ,CACnC,EAEAD,EAAO,UACLS,EACER,EACA,SAACM,EAAK,CACJL,EAAW,GACXC,EAAYI,EACPH,GACHM,EAAUZ,EAAiBS,CAAK,CAAC,EAAE,UAChCH,EAAqBK,EAAyBR,EAAYK,EAAaE,CAAe,CAAE,CAG/F,EACA,UAAA,CACEH,EAAa,IACZ,CAACH,GAAY,CAACE,GAAsBA,EAAmB,SAAWH,EAAW,SAAQ,CACxF,CAAC,CACF,CAEL,CAAC,CACH,CC3CM,SAAUU,GAAaC,EAAkBC,EAAyC,CAAzC,OAAAA,IAAA,SAAAA,EAAAC,IACtCC,GAAM,UAAA,CAAM,OAAAC,GAAMJ,EAAUC,CAAS,CAAzB,CAA0B,CAC/C,CCEM,SAAUI,GAAeC,EAAoBC,EAAsC,CAAtC,OAAAA,IAAA,SAAAA,EAAA,MAGjDA,EAAmBA,GAAgB,KAAhBA,EAAoBD,EAEhCE,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAiB,CAAA,EACjBC,EAAQ,EAEZH,EAAO,UACLI,EACEH,EACA,SAACI,EAAK,aACAC,EAAuB,KAKvBH,IAAUL,IAAsB,GAClCI,EAAQ,KAAK,CAAA,CAAE,MAIjB,QAAqBK,EAAAC,GAAAN,CAAO,EAAAO,EAAAF,EAAA,KAAA,EAAA,CAAAE,EAAA,KAAAA,EAAAF,EAAA,KAAA,EAAE,CAAzB,IAAMG,EAAMD,EAAA,MACfC,EAAO,KAAKL,CAAK,EAMbR,GAAca,EAAO,SACvBJ,EAASA,GAAM,KAANA,EAAU,CAAA,EACnBA,EAAO,KAAKI,CAAM,qGAItB,GAAIJ,MAIF,QAAqBK,EAAAH,GAAAF,CAAM,EAAAM,EAAAD,EAAA,KAAA,EAAA,CAAAC,EAAA,KAAAA,EAAAD,EAAA,KAAA,EAAE,CAAxB,IAAMD,EAAME,EAAA,MACfC,GAAUX,EAASQ,CAAM,EACzBT,EAAW,KAAKS,CAAM,oGAG5B,EACA,UAAA,aAGE,QAAqBI,EAAAN,GAAAN,CAAO,EAAAa,EAAAD,EAAA,KAAA,EAAA,CAAAC,EAAA,KAAAA,EAAAD,EAAA,KAAA,EAAE,CAAzB,IAAMJ,EAAMK,EAAA,MACfd,EAAW,KAAKS,CAAM,oGAExBT,EAAW,SAAQ,CACrB,EAEA,OACA,UAAA,CAEEC,EAAU,IACZ,CAAC,CACF,CAEL,CAAC,CACH,CCbM,SAAUc,GACdC,EAAgD,CAEhD,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAgC,KAChCC,EAAY,GACZC,EAEJF,EAAWF,EAAO,UAChBK,EAAyBJ,EAAY,OAAW,OAAW,SAACK,EAAG,CAC7DF,EAAgBG,EAAUT,EAASQ,EAAKT,GAAWC,CAAQ,EAAEE,CAAM,CAAC,CAAC,EACjEE,GACFA,EAAS,YAAW,EACpBA,EAAW,KACXE,EAAc,UAAUH,CAAU,GAIlCE,EAAY,EAEhB,CAAC,CAAC,EAGAA,IAMFD,EAAS,YAAW,EACpBA,EAAW,KACXE,EAAe,UAAUH,CAAU,EAEvC,CAAC,CACH,CC/HM,SAAUO,GACdC,EACAC,EACAC,EACAC,EACAC,EAAqC,CAErC,OAAO,SAACC,EAAuBC,EAA2B,CAIxD,IAAIC,EAAWL,EAIXM,EAAaP,EAEbQ,EAAQ,EAGZJ,EAAO,UACLK,EACEJ,EACA,SAACK,EAAK,CAEJ,IAAMC,EAAIH,IAEVD,EAAQD,EAEJP,EAAYQ,EAAOG,EAAOC,CAAC,GAIzBL,EAAW,GAAOI,GAGxBR,GAAcG,EAAW,KAAKE,CAAK,CACrC,EAGAJ,GACG,UAAA,CACCG,GAAYD,EAAW,KAAKE,CAAK,EACjCF,EAAW,SAAQ,CACrB,CAAE,CACL,CAEL,CACF,CCnCM,SAAUO,IAAa,SAAOC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAClC,IAAMC,EAAiBC,GAAkBH,CAAI,EAC7C,OAAOE,EACHE,GAAKL,GAAa,MAAA,OAAAM,EAAA,CAAA,EAAAC,EAAKN,CAAoC,CAAA,CAAA,EAAGO,GAAiBL,CAAc,CAAC,EAC9FM,EAAQ,SAACC,EAAQC,EAAU,CACzBC,GAAiBN,EAAA,CAAEI,CAAM,EAAAH,EAAKM,GAAeZ,CAAI,CAAC,CAAA,CAAA,EAAGU,CAAU,CACjE,CAAC,CACP,CCUM,SAAUG,IAAiB,SAC/BC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAEA,OAAOC,GAAa,MAAA,OAAAC,EAAA,CAAA,EAAAC,EAAIJ,CAAY,CAAA,CAAA,CACtC,CC+BM,SAAUK,GACdC,EACAC,EAA6G,CAE7G,OAAOC,EAAWD,CAAc,EAAIE,GAASH,EAASC,EAAgB,CAAC,EAAIE,GAASH,EAAS,CAAC,CAChG,CCpBM,SAAUI,GAAgBC,EAAiBC,EAAyC,CAAzC,OAAAA,IAAA,SAAAA,EAAAC,IACxCC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAkC,KAClCC,EAAsB,KACtBC,EAA0B,KAExBC,EAAO,UAAA,CACX,GAAIH,EAAY,CAEdA,EAAW,YAAW,EACtBA,EAAa,KACb,IAAMI,EAAQH,EACdA,EAAY,KACZF,EAAW,KAAKK,CAAK,EAEzB,EACA,SAASC,GAAY,CAInB,IAAMC,EAAaJ,EAAYR,EACzBa,EAAMZ,EAAU,IAAG,EACzB,GAAIY,EAAMD,EAAY,CAEpBN,EAAa,KAAK,SAAS,OAAWM,EAAaC,CAAG,EACtDR,EAAW,IAAIC,CAAU,EACzB,OAGFG,EAAI,CACN,CAEAL,EAAO,UACLU,EACET,EACA,SAACK,EAAQ,CACPH,EAAYG,EACZF,EAAWP,EAAU,IAAG,EAGnBK,IACHA,EAAaL,EAAU,SAASU,EAAcX,CAAO,EACrDK,EAAW,IAAIC,CAAU,EAE7B,EACA,UAAA,CAGEG,EAAI,EACJJ,EAAW,SAAQ,CACrB,EAEA,OACA,UAAA,CAEEE,EAAYD,EAAa,IAC3B,CAAC,CACF,CAEL,CAAC,CACH,CCpFM,SAAUS,GAAqBC,EAAe,CAClD,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAW,GACfF,EAAO,UACLG,EACEF,EACA,SAACG,EAAK,CACJF,EAAW,GACXD,EAAW,KAAKG,CAAK,CACvB,EACA,UAAA,CACOF,GACHD,EAAW,KAAKH,CAAa,EAE/BG,EAAW,SAAQ,CACrB,CAAC,CACF,CAEL,CAAC,CACH,CCXM,SAAUI,GAAQC,EAAa,CACnC,OAAOA,GAAS,EAEZ,UAAA,CAAM,OAAAC,CAAA,EACNC,EAAQ,SAACC,EAAQC,EAAU,CACzB,IAAIC,EAAO,EACXF,EAAO,UACLG,EAAyBF,EAAY,SAACG,EAAK,CAIrC,EAAEF,GAAQL,IACZI,EAAW,KAAKG,CAAK,EAIjBP,GAASK,GACXD,EAAW,SAAQ,EAGzB,CAAC,CAAC,CAEN,CAAC,CACP,CC9BM,SAAUI,IAAc,CAC5B,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChCD,EAAO,UAAUE,EAAyBD,EAAYE,EAAI,CAAC,CAC7D,CAAC,CACH,CCCM,SAAUC,GAASC,EAAQ,CAC/B,OAAOC,EAAI,UAAA,CAAM,OAAAD,CAAA,CAAK,CACxB,CCyCM,SAAUE,GACdC,EACAC,EAAmC,CAEnC,OAAIA,EAEK,SAACC,EAAqB,CAC3B,OAAAC,GAAOF,EAAkB,KAAKG,GAAK,CAAC,EAAGC,GAAc,CAAE,EAAGH,EAAO,KAAKH,GAAUC,CAAqB,CAAC,CAAC,CAAvG,EAGGM,GAAS,SAACC,EAAOC,EAAK,CAAK,OAAAR,EAAsBO,EAAOC,CAAK,EAAE,KAAKJ,GAAK,CAAC,EAAGK,GAAMF,CAAK,CAAC,CAA9D,CAA+D,CACnG,CCtCM,SAAUG,GAASC,EAAoBC,EAAyC,CAAzCA,IAAA,SAAAA,EAAAC,IAC3C,IAAMC,EAAWC,GAAMJ,EAAKC,CAAS,EACrC,OAAOI,GAAU,UAAA,CAAM,OAAAF,CAAA,CAAQ,CACjC,CC0EM,SAAUG,EACdC,EACAC,EAA0D,CAA1D,OAAAA,IAAA,SAAAA,EAA+BC,IAK/BF,EAAaA,GAAU,KAAVA,EAAcG,GAEpBC,EAAQ,SAACC,EAAQC,EAAU,CAGhC,IAAIC,EAEAC,EAAQ,GAEZH,EAAO,UACLI,EAAyBH,EAAY,SAACI,EAAK,CAEzC,IAAMC,EAAaV,EAAYS,CAAK,GAKhCF,GAAS,CAACR,EAAYO,EAAaI,CAAU,KAM/CH,EAAQ,GACRD,EAAcI,EAGdL,EAAW,KAAKI,CAAK,EAEzB,CAAC,CAAC,CAEN,CAAC,CACH,CAEA,SAASP,GAAeS,EAAQC,EAAM,CACpC,OAAOD,IAAMC,CACf,CCjHM,SAAUC,EAA8CC,EAAQC,EAAuC,CAC3G,OAAOC,EAAqB,SAACC,EAAMC,EAAI,CAAK,OAAAH,EAAUA,EAAQE,EAAEH,GAAMI,EAAEJ,EAAI,EAAIG,EAAEH,KAASI,EAAEJ,EAAjD,CAAqD,CACnG,CCLM,SAAUK,IAAO,SAAIC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACzB,OAAO,SAACC,EAAqB,CAAK,OAAAC,GAAOD,EAAQE,EAAE,MAAA,OAAAC,EAAA,CAAA,EAAAC,EAAIN,CAAM,CAAA,CAAA,CAAA,CAA3B,CACpC,CCHM,SAAUO,EAAYC,EAAoB,CAC9C,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAGhC,GAAI,CACFD,EAAO,UAAUC,CAAU,UAE3BA,EAAW,IAAIH,CAAQ,EAE3B,CAAC,CACH,CC9BM,SAAUI,GAAYC,EAAa,CACvC,OAAOA,GAAS,EACZ,UAAA,CAAM,OAAAC,CAAA,EACNC,EAAQ,SAACC,EAAQC,EAAU,CAKzB,IAAIC,EAAc,CAAA,EAClBF,EAAO,UACLG,EACEF,EACA,SAACG,EAAK,CAEJF,EAAO,KAAKE,CAAK,EAGjBP,EAAQK,EAAO,QAAUA,EAAO,MAAK,CACvC,EACA,UAAA,aAGE,QAAoBG,EAAAC,GAAAJ,CAAM,EAAAK,EAAAF,EAAA,KAAA,EAAA,CAAAE,EAAA,KAAAA,EAAAF,EAAA,KAAA,EAAE,CAAvB,IAAMD,EAAKG,EAAA,MACdN,EAAW,KAAKG,CAAK,oGAEvBH,EAAW,SAAQ,CACrB,EAEA,OACA,UAAA,CAEEC,EAAS,IACX,CAAC,CACF,CAEL,CAAC,CACP,CC1DM,SAAUM,IAAK,SAAIC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACvB,IAAMC,EAAYC,GAAaH,CAAI,EAC7BI,EAAaC,GAAUL,EAAM,GAAQ,EAC3C,OAAAA,EAAOM,GAAeN,CAAI,EAEnBO,EAAQ,SAACC,EAAQC,EAAU,CAChCC,GAASN,CAAU,EAAEO,GAAIC,EAAA,CAAEJ,CAAM,EAAAK,EAAMb,CAA6B,CAAA,EAAGE,CAAS,CAAC,EAAE,UAAUO,CAAU,CACzG,CAAC,CACH,CCcM,SAAUK,IAAS,SACvBC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAEA,OAAOC,GAAK,MAAA,OAAAC,EAAA,CAAA,EAAAC,EAAIJ,CAAY,CAAA,CAAA,CAC9B,CCmEM,SAAUK,GAAUC,EAAqC,OACzDC,EAAQ,IACRC,EAEJ,OAAIF,GAAiB,OACf,OAAOA,GAAkB,UACxBG,EAA4BH,EAAa,MAAzCC,EAAKE,IAAA,OAAG,IAAQA,EAAED,EAAUF,EAAa,OAE5CC,EAAQD,GAILC,GAAS,EACZ,UAAA,CAAM,OAAAG,CAAA,EACNC,EAAQ,SAACC,EAAQC,EAAU,CACzB,IAAIC,EAAQ,EACRC,EAEEC,EAAc,UAAA,CAGlB,GAFAD,GAAS,MAATA,EAAW,YAAW,EACtBA,EAAY,KACRP,GAAS,KAAM,CACjB,IAAMS,EAAW,OAAOT,GAAU,SAAWU,GAAMV,CAAK,EAAIW,EAAUX,EAAMM,CAAK,CAAC,EAC5EM,EAAqBC,EAAyBR,EAAY,UAAA,CAC9DO,EAAmB,YAAW,EAC9BE,EAAiB,CACnB,CAAC,EACDL,EAAS,UAAUG,CAAkB,OAErCE,EAAiB,CAErB,EAEMA,EAAoB,UAAA,CACxB,IAAIC,EAAY,GAChBR,EAAYH,EAAO,UACjBS,EAAyBR,EAAY,OAAW,UAAA,CAC1C,EAAEC,EAAQP,EACRQ,EACFC,EAAW,EAEXO,EAAY,GAGdV,EAAW,SAAQ,CAEvB,CAAC,CAAC,EAGAU,GACFP,EAAW,CAEf,EAEAM,EAAiB,CACnB,CAAC,CACP,CC7HM,SAAUE,GAAUC,EAAyB,CACjD,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAW,GACXC,EAAsB,KAC1BH,EAAO,UACLI,EAAyBH,EAAY,SAACI,EAAK,CACzCH,EAAW,GACXC,EAAYE,CACd,CAAC,CAAC,EAEJP,EAAS,UACPM,EACEH,EACA,UAAA,CACE,GAAIC,EAAU,CACZA,EAAW,GACX,IAAMG,EAAQF,EACdA,EAAY,KACZF,EAAW,KAAKI,CAAK,EAEzB,EACAC,EAAI,CACL,CAEL,CAAC,CACH,CCgBM,SAAUC,GAAcC,EAA6DC,EAAQ,CAMjG,OAAOC,EAAQC,GAAcH,EAAaC,EAAW,UAAU,QAAU,EAAG,EAAI,CAAC,CACnF,CCgDM,SAAUG,GAASC,EAA4B,CAA5BA,IAAA,SAAAA,EAAA,CAAA,GACf,IAAAC,EAAgHD,EAAO,UAAvHE,EAASD,IAAA,OAAG,UAAA,CAAM,OAAA,IAAIE,CAAJ,EAAgBF,EAAEG,EAA4EJ,EAAO,aAAnFK,EAAYD,IAAA,OAAG,GAAIA,EAAEE,EAAuDN,EAAO,gBAA9DO,EAAeD,IAAA,OAAG,GAAIA,EAAEE,EAA+BR,EAAO,oBAAtCS,EAAmBD,IAAA,OAAG,GAAIA,EAUnH,OAAO,SAACE,EAAa,CACnB,IAAIC,EACAC,EACAC,EACAC,EAAW,EACXC,EAAe,GACfC,EAAa,GAEXC,EAAc,UAAA,CAClBL,GAAe,MAAfA,EAAiB,YAAW,EAC5BA,EAAkB,MACpB,EAGMM,EAAQ,UAAA,CACZD,EAAW,EACXN,EAAaE,EAAU,OACvBE,EAAeC,EAAa,EAC9B,EACMG,EAAsB,UAAA,CAG1B,IAAMC,EAAOT,EACbO,EAAK,EACLE,GAAI,MAAJA,EAAM,YAAW,CACnB,EAEA,OAAOC,EAAc,SAACC,EAAQC,GAAU,CACtCT,IACI,CAACE,GAAc,CAACD,GAClBE,EAAW,EAOb,IAAMO,GAAQX,EAAUA,GAAO,KAAPA,EAAWX,EAAS,EAO5CqB,GAAW,IAAI,UAAA,CACbT,IAKIA,IAAa,GAAK,CAACE,GAAc,CAACD,IACpCH,EAAkBa,GAAYN,EAAqBV,CAAmB,EAE1E,CAAC,EAIDe,GAAK,UAAUD,EAAU,EAGvB,CAACZ,GAIDG,EAAW,IAOXH,EAAa,IAAIe,GAAe,CAC9B,KAAM,SAACC,GAAK,CAAK,OAAAH,GAAK,KAAKG,EAAK,CAAf,EACjB,MAAO,SAACC,GAAG,CACTZ,EAAa,GACbC,EAAW,EACXL,EAAkBa,GAAYP,EAAOb,EAAcuB,EAAG,EACtDJ,GAAK,MAAMI,EAAG,CAChB,EACA,SAAU,UAAA,CACRb,EAAe,GACfE,EAAW,EACXL,EAAkBa,GAAYP,EAAOX,CAAe,EACpDiB,GAAK,SAAQ,CACf,EACD,EACDK,EAAUP,CAAM,EAAE,UAAUX,CAAU,EAE1C,CAAC,EAAED,CAAa,CAClB,CACF,CAEA,SAASe,GACPP,EACAY,EAA+C,SAC/CC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,EAAA,GAAA,UAAAA,GAEA,GAAIF,IAAO,GAAM,CACfZ,EAAK,EACL,OAGF,GAAIY,IAAO,GAIX,KAAMG,EAAe,IAAIP,GAAe,CACtC,KAAM,UAAA,CACJO,EAAa,YAAW,EACxBf,EAAK,CACP,EACD,EAED,OAAOY,EAAE,MAAA,OAAAI,EAAA,CAAA,EAAAC,EAAIJ,CAAI,CAAA,CAAA,EAAE,UAAUE,CAAY,EAC3C,CCjHM,SAAUG,EACdC,EACAC,EACAC,EAAyB,WAErBC,EACAC,EAAW,GACf,OAAIJ,GAAsB,OAAOA,GAAuB,UACnDK,EAA8EL,EAAkB,WAAhGG,EAAUE,IAAA,OAAG,IAAQA,EAAEC,EAAuDN,EAAkB,WAAzEC,EAAUK,IAAA,OAAG,IAAQA,EAAEC,EAAgCP,EAAkB,SAAlDI,EAAQG,IAAA,OAAG,GAAKA,EAAEL,EAAcF,EAAkB,WAEnGG,EAAcH,GAAkB,KAAlBA,EAAsB,IAE/BQ,GAAS,CACd,UAAW,UAAA,CAAM,OAAA,IAAIC,GAAcN,EAAYF,EAAYC,CAAS,CAAnD,EACjB,aAAc,GACd,gBAAiB,GACjB,oBAAqBE,EACtB,CACH,CCxIM,SAAUM,GAAQC,EAAa,CACnC,OAAOC,EAAO,SAACC,EAAGC,EAAK,CAAK,OAAAH,GAASG,CAAT,CAAc,CAC5C,CCWM,SAAUC,GAAaC,EAAyB,CACpD,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAS,GAEPC,EAAiBC,EACrBH,EACA,UAAA,CACEE,GAAc,MAAdA,EAAgB,YAAW,EAC3BD,EAAS,EACX,EACAG,EAAI,EAGNC,EAAUR,CAAQ,EAAE,UAAUK,CAAc,EAE5CH,EAAO,UAAUI,EAAyBH,EAAY,SAACM,EAAK,CAAK,OAAAL,GAAUD,EAAW,KAAKM,CAAK,CAA/B,CAAgC,CAAC,CACpG,CAAC,CACH,CCRM,SAAUC,GAAS,SAAOC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAC9B,IAAMC,EAAYC,GAAaH,CAAM,EACrC,OAAOI,EAAQ,SAACC,EAAQC,EAAU,EAI/BJ,EAAYK,GAAOP,EAAQK,EAAQH,CAAS,EAAIK,GAAOP,EAAQK,CAAM,GAAG,UAAUC,CAAU,CAC/F,CAAC,CACH,CCmBM,SAAUE,EACdC,EACAC,EAA6G,CAE7G,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAyD,KACzDC,EAAQ,EAERC,EAAa,GAIXC,EAAgB,UAAA,CAAM,OAAAD,GAAc,CAACF,GAAmBD,EAAW,SAAQ,CAArD,EAE5BD,EAAO,UACLM,EACEL,EACA,SAACM,EAAK,CAEJL,GAAe,MAAfA,EAAiB,YAAW,EAC5B,IAAIM,EAAa,EACXC,EAAaN,IAEnBO,EAAUb,EAAQU,EAAOE,CAAU,CAAC,EAAE,UACnCP,EAAkBI,EACjBL,EAIA,SAACU,EAAU,CAAK,OAAAV,EAAW,KAAKH,EAAiBA,EAAeS,EAAOI,EAAYF,EAAYD,GAAY,EAAIG,CAAU,CAAzG,EAChB,UAAA,CAIET,EAAkB,KAClBG,EAAa,CACf,CAAC,CACD,CAEN,EACA,UAAA,CACED,EAAa,GACbC,EAAa,CACf,CAAC,CACF,CAEL,CAAC,CACH,CCvFM,SAAUO,GAAaC,EAA8B,CACzD,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChCC,EAAUJ,CAAQ,EAAE,UAAUK,EAAyBF,EAAY,UAAA,CAAM,OAAAA,EAAW,SAAQ,CAAnB,EAAuBG,EAAI,CAAC,EACrG,CAACH,EAAW,QAAUD,EAAO,UAAUC,CAAU,CACnD,CAAC,CACH,CCIM,SAAUI,GAAaC,EAAiDC,EAAiB,CAAjB,OAAAA,IAAA,SAAAA,EAAA,IACrEC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAQ,EACZF,EAAO,UACLG,EAAyBF,EAAY,SAACG,EAAK,CACzC,IAAMC,EAASR,EAAUO,EAAOF,GAAO,GACtCG,GAAUP,IAAcG,EAAW,KAAKG,CAAK,EAC9C,CAACC,GAAUJ,EAAW,SAAQ,CAChC,CAAC,CAAC,CAEN,CAAC,CACH,CCyCM,SAAUK,EACdC,EACAC,EACAC,EAA8B,CAK9B,IAAMC,EACJC,EAAWJ,CAAc,GAAKC,GAASC,EAElC,CAAE,KAAMF,EAA2E,MAAKC,EAAE,SAAQC,CAAA,EACnGF,EAEN,OAAOG,EACHE,EAAQ,SAACC,EAAQC,EAAU,QACzBC,EAAAL,EAAY,aAAS,MAAAK,IAAA,QAAAA,EAAA,KAArBL,CAAW,EACX,IAAIM,EAAU,GACdH,EAAO,UACLI,EACEH,EACA,SAACI,EAAK,QACJH,EAAAL,EAAY,QAAI,MAAAK,IAAA,QAAAA,EAAA,KAAhBL,EAAmBQ,CAAK,EACxBJ,EAAW,KAAKI,CAAK,CACvB,EACA,UAAA,OACEF,EAAU,IACVD,EAAAL,EAAY,YAAQ,MAAAK,IAAA,QAAAA,EAAA,KAApBL,CAAW,EACXI,EAAW,SAAQ,CACrB,EACA,SAACK,EAAG,OACFH,EAAU,IACVD,EAAAL,EAAY,SAAK,MAAAK,IAAA,QAAAA,EAAA,KAAjBL,EAAoBS,CAAG,EACvBL,EAAW,MAAMK,CAAG,CACtB,EACA,UAAA,SACMH,KACFD,EAAAL,EAAY,eAAW,MAAAK,IAAA,QAAAA,EAAA,KAAvBL,CAAW,IAEbU,EAAAV,EAAY,YAAQ,MAAAU,IAAA,QAAAA,EAAA,KAApBV,CAAW,CACb,CAAC,CACF,CAEL,CAAC,EAIDW,EACN,CC9IO,IAAMC,GAAwC,CACnD,QAAS,GACT,SAAU,IAiDN,SAAUC,GACdC,EACAC,EAA8C,CAA9C,OAAAA,IAAA,SAAAA,EAAAH,IAEOI,EAAQ,SAACC,EAAQC,EAAU,CACxB,IAAAC,EAAsBJ,EAAM,QAAnBK,EAAaL,EAAM,SAChCM,EAAW,GACXC,EAAsB,KACtBC,EAAiC,KACjCC,EAAa,GAEXC,EAAgB,UAAA,CACpBF,GAAS,MAATA,EAAW,YAAW,EACtBA,EAAY,KACRH,IACFM,EAAI,EACJF,GAAcN,EAAW,SAAQ,EAErC,EAEMS,EAAoB,UAAA,CACxBJ,EAAY,KACZC,GAAcN,EAAW,SAAQ,CACnC,EAEMU,EAAgB,SAACC,EAAQ,CAC7B,OAACN,EAAYO,EAAUhB,EAAiBe,CAAK,CAAC,EAAE,UAAUE,EAAyBb,EAAYO,EAAeE,CAAiB,CAAC,CAAhI,EAEID,EAAO,UAAA,CACX,GAAIL,EAAU,CAIZA,EAAW,GACX,IAAMQ,EAAQP,EACdA,EAAY,KAEZJ,EAAW,KAAKW,CAAK,EACrB,CAACL,GAAcI,EAAcC,CAAK,EAEtC,EAEAZ,EAAO,UACLc,EACEb,EAMA,SAACW,EAAK,CACJR,EAAW,GACXC,EAAYO,EACZ,EAAEN,GAAa,CAACA,EAAU,UAAYJ,EAAUO,EAAI,EAAKE,EAAcC,CAAK,EAC9E,EACA,UAAA,CACEL,EAAa,GACb,EAAEJ,GAAYC,GAAYE,GAAa,CAACA,EAAU,SAAWL,EAAW,SAAQ,CAClF,CAAC,CACF,CAEL,CAAC,CACH,CCvEM,SAAUc,GACdC,EACAC,EACAC,EAA8B,CAD9BD,IAAA,SAAAA,EAAAE,IACAD,IAAA,SAAAA,EAAAE,IAEA,IAAMC,EAAYC,GAAMN,EAAUC,CAAS,EAC3C,OAAOM,GAAS,UAAA,CAAM,OAAAF,CAAA,EAAWH,CAAM,CACzC,CCJM,SAAUM,IAAc,SAAOC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACnC,IAAMC,EAAUC,GAAkBH,CAAM,EAExC,OAAOI,EAAQ,SAACC,EAAQC,EAAU,CAehC,QAdMC,EAAMP,EAAO,OACbQ,EAAc,IAAI,MAAMD,CAAG,EAI7BE,EAAWT,EAAO,IAAI,UAAA,CAAM,MAAA,EAAA,CAAK,EAGjCU,EAAQ,cAMHC,EAAC,CACRC,EAAUZ,EAAOW,EAAE,EAAE,UACnBE,EACEP,EACA,SAACQ,EAAK,CACJN,EAAYG,GAAKG,EACb,CAACJ,GAAS,CAACD,EAASE,KAEtBF,EAASE,GAAK,IAKbD,EAAQD,EAAS,MAAMM,EAAQ,KAAON,EAAW,MAEtD,EAGAO,EAAI,CACL,GAnBIL,EAAI,EAAGA,EAAIJ,EAAKI,MAAhBA,CAAC,EAwBVN,EAAO,UACLQ,EAAyBP,EAAY,SAACQ,EAAK,CACzC,GAAIJ,EAAO,CAET,IAAMO,EAAMC,EAAA,CAAIJ,CAAK,EAAAK,EAAKX,CAAW,CAAA,EACrCF,EAAW,KAAKJ,EAAUA,EAAO,MAAA,OAAAgB,EAAA,CAAA,EAAAC,EAAIF,CAAM,CAAA,CAAA,EAAIA,CAAM,EAEzD,CAAC,CAAC,CAEN,CAAC,CACH,CCxFM,SAAUG,IAAG,SAAOC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACxB,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChCL,GAAS,MAAA,OAAAM,EAAA,CAACF,CAA8B,EAAAG,EAAMN,CAAuC,CAAA,CAAA,EAAE,UAAUI,CAAU,CAC7G,CAAC,CACH,CCCM,SAAUG,IAAO,SAAkCC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACvD,OAAOC,GAAG,MAAA,OAAAC,EAAA,CAAA,EAAAC,EAAIJ,CAAW,CAAA,CAAA,CAC3B,CCYO,SAASK,IAAmC,CACjD,IAAMC,EAAY,IAAIC,GAAwB,CAAC,EAC/C,OAAAC,EAAU,SAAU,mBAAoB,CAAE,KAAM,EAAK,CAAC,EACnD,UAAU,IAAMF,EAAU,KAAK,QAAQ,CAAC,EAGpCA,CACT,CCHO,SAASG,EACdC,EAAkBC,EAAmB,SAChC,CACL,OAAO,MAAM,KAAKA,EAAK,iBAAoBD,CAAQ,CAAC,CACtD,CAuBO,SAASE,EACdF,EAAkBC,EAAmB,SAClC,CACH,IAAME,EAAKC,GAAsBJ,EAAUC,CAAI,EAC/C,GAAI,OAAOE,GAAO,YAChB,MAAM,IAAI,eACR,8BAA8BH,kBAChC,EAGF,OAAOG,CACT,CAsBO,SAASC,GACdJ,EAAkBC,EAAmB,SACtB,CACf,OAAOA,EAAK,cAAiBD,CAAQ,GAAK,MAC5C,CAOO,SAASK,IAA4C,CAC1D,OAAO,SAAS,yBAAyB,aACrC,SAAS,eAAiB,MAEhC,CClEO,SAASC,GACdC,EACqB,CACrB,OAAOC,EACLC,EAAU,SAAS,KAAM,SAAS,EAClCA,EAAU,SAAS,KAAM,UAAU,CACrC,EACG,KACCC,GAAa,CAAC,EACdC,EAAI,IAAM,CACR,IAAMC,EAASC,GAAiB,EAChC,OAAO,OAAOD,GAAW,YACrBL,EAAG,SAASK,CAAM,EAClB,EACN,CAAC,EACDE,EAAUP,IAAOM,GAAiB,CAAC,EACnCE,EAAqB,CACvB,CACJ,CChBO,SAASC,GACdC,EACe,CACf,MAAO,CACL,EAAGA,EAAG,WACN,EAAGA,EAAG,SACR,CACF,CAWO,SAASC,GACdD,EAC2B,CAC3B,OAAOE,EACLC,EAAU,OAAQ,MAAM,EACxBA,EAAU,OAAQ,QAAQ,CAC5B,EACG,KACCC,GAAU,EAAGC,EAAuB,EACpCC,EAAI,IAAMP,GAAiBC,CAAE,CAAC,EAC9BO,EAAUR,GAAiBC,CAAE,CAAC,CAChC,CACJ,CCxCO,SAASQ,GACdC,EACe,CACf,MAAO,CACL,EAAGA,EAAG,WACN,EAAGA,EAAG,SACR,CACF,CAWO,SAASC,GACdD,EAC2B,CAC3B,OAAOE,EACLC,EAAUH,EAAI,QAAQ,EACtBG,EAAU,OAAQ,QAAQ,CAC5B,EACG,KACCC,GAAU,EAAGC,EAAuB,EACpCC,EAAI,IAAMP,GAAwBC,CAAE,CAAC,EACrCO,EAAUR,GAAwBC,CAAE,CAAC,CACvC,CACJ,CCpEA,IAAIQ,GAAW,UAAY,CACvB,GAAI,OAAO,KAAQ,YACf,OAAO,IASX,SAASC,EAASC,EAAKC,EAAK,CACxB,IAAIC,EAAS,GACb,OAAAF,EAAI,KAAK,SAAUG,EAAOC,EAAO,CAC7B,OAAID,EAAM,KAAOF,GACbC,EAASE,EACF,IAEJ,EACX,CAAC,EACMF,CACX,CACA,OAAsB,UAAY,CAC9B,SAASG,GAAU,CACf,KAAK,YAAc,CAAC,CACxB,CACA,cAAO,eAAeA,EAAQ,UAAW,OAAQ,CAI7C,IAAK,UAAY,CACb,OAAO,KAAK,YAAY,MAC5B,EACA,WAAY,GACZ,aAAc,EAClB,CAAC,EAKDA,EAAQ,UAAU,IAAM,SAAUJ,EAAK,CACnC,IAAIG,EAAQL,EAAS,KAAK,YAAaE,CAAG,EACtCE,EAAQ,KAAK,YAAYC,GAC7B,OAAOD,GAASA,EAAM,EAC1B,EAMAE,EAAQ,UAAU,IAAM,SAAUJ,EAAKK,EAAO,CAC1C,IAAIF,EAAQL,EAAS,KAAK,YAAaE,CAAG,EACtC,CAACG,EACD,KAAK,YAAYA,GAAO,GAAKE,EAG7B,KAAK,YAAY,KAAK,CAACL,EAAKK,CAAK,CAAC,CAE1C,EAKAD,EAAQ,UAAU,OAAS,SAAUJ,EAAK,CACtC,IAAIM,EAAU,KAAK,YACfH,EAAQL,EAASQ,EAASN,CAAG,EAC7B,CAACG,GACDG,EAAQ,OAAOH,EAAO,CAAC,CAE/B,EAKAC,EAAQ,UAAU,IAAM,SAAUJ,EAAK,CACnC,MAAO,CAAC,CAAC,CAACF,EAAS,KAAK,YAAaE,CAAG,CAC5C,EAIAI,EAAQ,UAAU,MAAQ,UAAY,CAClC,KAAK,YAAY,OAAO,CAAC,CAC7B,EAMAA,EAAQ,UAAU,QAAU,SAAUG,EAAUC,EAAK,CAC7CA,IAAQ,SAAUA,EAAM,MAC5B,QAASC,EAAK,EAAGC,EAAK,KAAK,YAAaD,EAAKC,EAAG,OAAQD,IAAM,CAC1D,IAAIP,EAAQQ,EAAGD,GACfF,EAAS,KAAKC,EAAKN,EAAM,GAAIA,EAAM,EAAE,CACzC,CACJ,EACOE,CACX,EAAE,CACN,EAAG,EAKCO,GAAY,OAAO,QAAW,aAAe,OAAO,UAAa,aAAe,OAAO,WAAa,SAGpGC,GAAY,UAAY,CACxB,OAAI,OAAO,QAAW,aAAe,OAAO,OAAS,KAC1C,OAEP,OAAO,MAAS,aAAe,KAAK,OAAS,KACtC,KAEP,OAAO,QAAW,aAAe,OAAO,OAAS,KAC1C,OAGJ,SAAS,aAAa,EAAE,CACnC,EAAG,EAQCC,GAA2B,UAAY,CACvC,OAAI,OAAO,uBAA0B,WAI1B,sBAAsB,KAAKD,EAAQ,EAEvC,SAAUL,EAAU,CAAE,OAAO,WAAW,UAAY,CAAE,OAAOA,EAAS,KAAK,IAAI,CAAC,CAAG,EAAG,IAAO,EAAE,CAAG,CAC7G,EAAG,EAGCO,GAAkB,EAStB,SAASC,GAAUR,EAAUS,EAAO,CAChC,IAAIC,EAAc,GAAOC,EAAe,GAAOC,EAAe,EAO9D,SAASC,GAAiB,CAClBH,IACAA,EAAc,GACdV,EAAS,GAETW,GACAG,EAAM,CAEd,CAQA,SAASC,GAAkB,CACvBT,GAAwBO,CAAc,CAC1C,CAMA,SAASC,GAAQ,CACb,IAAIE,EAAY,KAAK,IAAI,EACzB,GAAIN,EAAa,CAEb,GAAIM,EAAYJ,EAAeL,GAC3B,OAMJI,EAAe,EACnB,MAEID,EAAc,GACdC,EAAe,GACf,WAAWI,EAAiBN,CAAK,EAErCG,EAAeI,CACnB,CACA,OAAOF,CACX,CAGA,IAAIG,GAAgB,GAGhBC,GAAiB,CAAC,MAAO,QAAS,SAAU,OAAQ,QAAS,SAAU,OAAQ,QAAQ,EAEvFC,GAA4B,OAAO,kBAAqB,YAIxDC,GAA0C,UAAY,CAMtD,SAASA,GAA2B,CAMhC,KAAK,WAAa,GAMlB,KAAK,qBAAuB,GAM5B,KAAK,mBAAqB,KAM1B,KAAK,WAAa,CAAC,EACnB,KAAK,iBAAmB,KAAK,iBAAiB,KAAK,IAAI,EACvD,KAAK,QAAUZ,GAAS,KAAK,QAAQ,KAAK,IAAI,EAAGS,EAAa,CAClE,CAOA,OAAAG,EAAyB,UAAU,YAAc,SAAUC,EAAU,CAC5D,CAAC,KAAK,WAAW,QAAQA,CAAQ,GAClC,KAAK,WAAW,KAAKA,CAAQ,EAG5B,KAAK,YACN,KAAK,SAAS,CAEtB,EAOAD,EAAyB,UAAU,eAAiB,SAAUC,EAAU,CACpE,IAAIC,EAAY,KAAK,WACjB1B,EAAQ0B,EAAU,QAAQD,CAAQ,EAElC,CAACzB,GACD0B,EAAU,OAAO1B,EAAO,CAAC,EAGzB,CAAC0B,EAAU,QAAU,KAAK,YAC1B,KAAK,YAAY,CAEzB,EAOAF,EAAyB,UAAU,QAAU,UAAY,CACrD,IAAIG,EAAkB,KAAK,iBAAiB,EAGxCA,GACA,KAAK,QAAQ,CAErB,EASAH,EAAyB,UAAU,iBAAmB,UAAY,CAE9D,IAAII,EAAkB,KAAK,WAAW,OAAO,SAAUH,EAAU,CAC7D,OAAOA,EAAS,aAAa,EAAGA,EAAS,UAAU,CACvD,CAAC,EAMD,OAAAG,EAAgB,QAAQ,SAAUH,EAAU,CAAE,OAAOA,EAAS,gBAAgB,CAAG,CAAC,EAC3EG,EAAgB,OAAS,CACpC,EAOAJ,EAAyB,UAAU,SAAW,UAAY,CAGlD,CAAChB,IAAa,KAAK,aAMvB,SAAS,iBAAiB,gBAAiB,KAAK,gBAAgB,EAChE,OAAO,iBAAiB,SAAU,KAAK,OAAO,EAC1Ce,IACA,KAAK,mBAAqB,IAAI,iBAAiB,KAAK,OAAO,EAC3D,KAAK,mBAAmB,QAAQ,SAAU,CACtC,WAAY,GACZ,UAAW,GACX,cAAe,GACf,QAAS,EACb,CAAC,IAGD,SAAS,iBAAiB,qBAAsB,KAAK,OAAO,EAC5D,KAAK,qBAAuB,IAEhC,KAAK,WAAa,GACtB,EAOAC,EAAyB,UAAU,YAAc,UAAY,CAGrD,CAAChB,IAAa,CAAC,KAAK,aAGxB,SAAS,oBAAoB,gBAAiB,KAAK,gBAAgB,EACnE,OAAO,oBAAoB,SAAU,KAAK,OAAO,EAC7C,KAAK,oBACL,KAAK,mBAAmB,WAAW,EAEnC,KAAK,sBACL,SAAS,oBAAoB,qBAAsB,KAAK,OAAO,EAEnE,KAAK,mBAAqB,KAC1B,KAAK,qBAAuB,GAC5B,KAAK,WAAa,GACtB,EAQAgB,EAAyB,UAAU,iBAAmB,SAAUjB,EAAI,CAChE,IAAIsB,EAAKtB,EAAG,aAAcuB,EAAeD,IAAO,OAAS,GAAKA,EAE1DE,EAAmBT,GAAe,KAAK,SAAUzB,EAAK,CACtD,MAAO,CAAC,CAAC,CAACiC,EAAa,QAAQjC,CAAG,CACtC,CAAC,EACGkC,GACA,KAAK,QAAQ,CAErB,EAMAP,EAAyB,YAAc,UAAY,CAC/C,OAAK,KAAK,YACN,KAAK,UAAY,IAAIA,GAElB,KAAK,SAChB,EAMAA,EAAyB,UAAY,KAC9BA,CACX,EAAE,EASEQ,GAAsB,SAAUC,EAAQC,EAAO,CAC/C,QAAS5B,EAAK,EAAGC,EAAK,OAAO,KAAK2B,CAAK,EAAG5B,EAAKC,EAAG,OAAQD,IAAM,CAC5D,IAAIT,EAAMU,EAAGD,GACb,OAAO,eAAe2B,EAAQpC,EAAK,CAC/B,MAAOqC,EAAMrC,GACb,WAAY,GACZ,SAAU,GACV,aAAc,EAClB,CAAC,CACL,CACA,OAAOoC,CACX,EAQIE,GAAe,SAAUF,EAAQ,CAIjC,IAAIG,EAAcH,GAAUA,EAAO,eAAiBA,EAAO,cAAc,YAGzE,OAAOG,GAAe3B,EAC1B,EAGI4B,GAAYC,GAAe,EAAG,EAAG,EAAG,CAAC,EAOzC,SAASC,GAAQrC,EAAO,CACpB,OAAO,WAAWA,CAAK,GAAK,CAChC,CAQA,SAASsC,GAAeC,EAAQ,CAE5B,QADIC,EAAY,CAAC,EACRpC,EAAK,EAAGA,EAAK,UAAU,OAAQA,IACpCoC,EAAUpC,EAAK,GAAK,UAAUA,GAElC,OAAOoC,EAAU,OAAO,SAAUC,EAAMC,EAAU,CAC9C,IAAI1C,EAAQuC,EAAO,UAAYG,EAAW,UAC1C,OAAOD,EAAOJ,GAAQrC,CAAK,CAC/B,EAAG,CAAC,CACR,CAOA,SAAS2C,GAAYJ,EAAQ,CAGzB,QAFIC,EAAY,CAAC,MAAO,QAAS,SAAU,MAAM,EAC7CI,EAAW,CAAC,EACPxC,EAAK,EAAGyC,EAAcL,EAAWpC,EAAKyC,EAAY,OAAQzC,IAAM,CACrE,IAAIsC,EAAWG,EAAYzC,GACvBJ,EAAQuC,EAAO,WAAaG,GAChCE,EAASF,GAAYL,GAAQrC,CAAK,CACtC,CACA,OAAO4C,CACX,CAQA,SAASE,GAAkBf,EAAQ,CAC/B,IAAIgB,EAAOhB,EAAO,QAAQ,EAC1B,OAAOK,GAAe,EAAG,EAAGW,EAAK,MAAOA,EAAK,MAAM,CACvD,CAOA,SAASC,GAA0BjB,EAAQ,CAGvC,IAAIkB,EAAclB,EAAO,YAAamB,EAAenB,EAAO,aAS5D,GAAI,CAACkB,GAAe,CAACC,EACjB,OAAOf,GAEX,IAAII,EAASN,GAAYF,CAAM,EAAE,iBAAiBA,CAAM,EACpDa,EAAWD,GAAYJ,CAAM,EAC7BY,EAAWP,EAAS,KAAOA,EAAS,MACpCQ,EAAUR,EAAS,IAAMA,EAAS,OAKlCS,EAAQhB,GAAQE,EAAO,KAAK,EAAGe,EAASjB,GAAQE,EAAO,MAAM,EAqBjE,GAlBIA,EAAO,YAAc,eAOjB,KAAK,MAAMc,EAAQF,CAAQ,IAAMF,IACjCI,GAASf,GAAeC,EAAQ,OAAQ,OAAO,EAAIY,GAEnD,KAAK,MAAMG,EAASF,CAAO,IAAMF,IACjCI,GAAUhB,GAAeC,EAAQ,MAAO,QAAQ,EAAIa,IAOxD,CAACG,GAAkBxB,CAAM,EAAG,CAK5B,IAAIyB,EAAgB,KAAK,MAAMH,EAAQF,CAAQ,EAAIF,EAC/CQ,EAAiB,KAAK,MAAMH,EAASF,CAAO,EAAIF,EAMhD,KAAK,IAAIM,CAAa,IAAM,IAC5BH,GAASG,GAET,KAAK,IAAIC,CAAc,IAAM,IAC7BH,GAAUG,EAElB,CACA,OAAOrB,GAAeQ,EAAS,KAAMA,EAAS,IAAKS,EAAOC,CAAM,CACpE,CAOA,IAAII,GAAwB,UAAY,CAGpC,OAAI,OAAO,oBAAuB,YACvB,SAAU3B,EAAQ,CAAE,OAAOA,aAAkBE,GAAYF,CAAM,EAAE,kBAAoB,EAKzF,SAAUA,EAAQ,CAAE,OAAQA,aAAkBE,GAAYF,CAAM,EAAE,YACrE,OAAOA,EAAO,SAAY,UAAa,CAC/C,EAAG,EAOH,SAASwB,GAAkBxB,EAAQ,CAC/B,OAAOA,IAAWE,GAAYF,CAAM,EAAE,SAAS,eACnD,CAOA,SAAS4B,GAAe5B,EAAQ,CAC5B,OAAKzB,GAGDoD,GAAqB3B,CAAM,EACpBe,GAAkBf,CAAM,EAE5BiB,GAA0BjB,CAAM,EAL5BI,EAMf,CAQA,SAASyB,GAAmBvD,EAAI,CAC5B,IAAIwD,EAAIxD,EAAG,EAAGyD,EAAIzD,EAAG,EAAGgD,EAAQhD,EAAG,MAAOiD,EAASjD,EAAG,OAElD0D,EAAS,OAAO,iBAAoB,YAAc,gBAAkB,OACpEC,EAAO,OAAO,OAAOD,EAAO,SAAS,EAEzC,OAAAjC,GAAmBkC,EAAM,CACrB,EAAGH,EAAG,EAAGC,EAAG,MAAOT,EAAO,OAAQC,EAClC,IAAKQ,EACL,MAAOD,EAAIR,EACX,OAAQC,EAASQ,EACjB,KAAMD,CACV,CAAC,EACMG,CACX,CAWA,SAAS5B,GAAeyB,EAAGC,EAAGT,EAAOC,EAAQ,CACzC,MAAO,CAAE,EAAGO,EAAG,EAAGC,EAAG,MAAOT,EAAO,OAAQC,CAAO,CACtD,CAMA,IAAIW,GAAmC,UAAY,CAM/C,SAASA,EAAkBlC,EAAQ,CAM/B,KAAK,eAAiB,EAMtB,KAAK,gBAAkB,EAMvB,KAAK,aAAeK,GAAe,EAAG,EAAG,EAAG,CAAC,EAC7C,KAAK,OAASL,CAClB,CAOA,OAAAkC,EAAkB,UAAU,SAAW,UAAY,CAC/C,IAAID,EAAOL,GAAe,KAAK,MAAM,EACrC,YAAK,aAAeK,EACZA,EAAK,QAAU,KAAK,gBACxBA,EAAK,SAAW,KAAK,eAC7B,EAOAC,EAAkB,UAAU,cAAgB,UAAY,CACpD,IAAID,EAAO,KAAK,aAChB,YAAK,eAAiBA,EAAK,MAC3B,KAAK,gBAAkBA,EAAK,OACrBA,CACX,EACOC,CACX,EAAE,EAEEC,GAAqC,UAAY,CAOjD,SAASA,EAAoBnC,EAAQoC,EAAU,CAC3C,IAAIC,EAAcR,GAAmBO,CAAQ,EAO7CrC,GAAmB,KAAM,CAAE,OAAQC,EAAQ,YAAaqC,CAAY,CAAC,CACzE,CACA,OAAOF,CACX,EAAE,EAEEG,GAAmC,UAAY,CAW/C,SAASA,EAAkBnE,EAAUoE,EAAYC,EAAa,CAc1D,GAPA,KAAK,oBAAsB,CAAC,EAM5B,KAAK,cAAgB,IAAI/E,GACrB,OAAOU,GAAa,WACpB,MAAM,IAAI,UAAU,yDAAyD,EAEjF,KAAK,UAAYA,EACjB,KAAK,YAAcoE,EACnB,KAAK,aAAeC,CACxB,CAOA,OAAAF,EAAkB,UAAU,QAAU,SAAUtC,EAAQ,CACpD,GAAI,CAAC,UAAU,OACX,MAAM,IAAI,UAAU,0CAA0C,EAGlE,GAAI,SAAO,SAAY,aAAe,EAAE,mBAAmB,SAG3D,IAAI,EAAEA,aAAkBE,GAAYF,CAAM,EAAE,SACxC,MAAM,IAAI,UAAU,uCAAuC,EAE/D,IAAIyC,EAAe,KAAK,cAEpBA,EAAa,IAAIzC,CAAM,IAG3ByC,EAAa,IAAIzC,EAAQ,IAAIkC,GAAkBlC,CAAM,CAAC,EACtD,KAAK,YAAY,YAAY,IAAI,EAEjC,KAAK,YAAY,QAAQ,GAC7B,EAOAsC,EAAkB,UAAU,UAAY,SAAUtC,EAAQ,CACtD,GAAI,CAAC,UAAU,OACX,MAAM,IAAI,UAAU,0CAA0C,EAGlE,GAAI,SAAO,SAAY,aAAe,EAAE,mBAAmB,SAG3D,IAAI,EAAEA,aAAkBE,GAAYF,CAAM,EAAE,SACxC,MAAM,IAAI,UAAU,uCAAuC,EAE/D,IAAIyC,EAAe,KAAK,cAEpB,CAACA,EAAa,IAAIzC,CAAM,IAG5ByC,EAAa,OAAOzC,CAAM,EACrByC,EAAa,MACd,KAAK,YAAY,eAAe,IAAI,GAE5C,EAMAH,EAAkB,UAAU,WAAa,UAAY,CACjD,KAAK,YAAY,EACjB,KAAK,cAAc,MAAM,EACzB,KAAK,YAAY,eAAe,IAAI,CACxC,EAOAA,EAAkB,UAAU,aAAe,UAAY,CACnD,IAAII,EAAQ,KACZ,KAAK,YAAY,EACjB,KAAK,cAAc,QAAQ,SAAUC,EAAa,CAC1CA,EAAY,SAAS,GACrBD,EAAM,oBAAoB,KAAKC,CAAW,CAElD,CAAC,CACL,EAOAL,EAAkB,UAAU,gBAAkB,UAAY,CAEtD,GAAI,EAAC,KAAK,UAAU,EAGpB,KAAIlE,EAAM,KAAK,aAEXF,EAAU,KAAK,oBAAoB,IAAI,SAAUyE,EAAa,CAC9D,OAAO,IAAIR,GAAoBQ,EAAY,OAAQA,EAAY,cAAc,CAAC,CAClF,CAAC,EACD,KAAK,UAAU,KAAKvE,EAAKF,EAASE,CAAG,EACrC,KAAK,YAAY,EACrB,EAMAkE,EAAkB,UAAU,YAAc,UAAY,CAClD,KAAK,oBAAoB,OAAO,CAAC,CACrC,EAMAA,EAAkB,UAAU,UAAY,UAAY,CAChD,OAAO,KAAK,oBAAoB,OAAS,CAC7C,EACOA,CACX,EAAE,EAKE7C,GAAY,OAAO,SAAY,YAAc,IAAI,QAAY,IAAIhC,GAKjEmF,GAAgC,UAAY,CAO5C,SAASA,EAAezE,EAAU,CAC9B,GAAI,EAAE,gBAAgByE,GAClB,MAAM,IAAI,UAAU,oCAAoC,EAE5D,GAAI,CAAC,UAAU,OACX,MAAM,IAAI,UAAU,0CAA0C,EAElE,IAAIL,EAAahD,GAAyB,YAAY,EAClDC,EAAW,IAAI8C,GAAkBnE,EAAUoE,EAAY,IAAI,EAC/D9C,GAAU,IAAI,KAAMD,CAAQ,CAChC,CACA,OAAOoD,CACX,EAAE,EAEF,CACI,UACA,YACA,YACJ,EAAE,QAAQ,SAAUC,EAAQ,CACxBD,GAAe,UAAUC,GAAU,UAAY,CAC3C,IAAIvE,EACJ,OAAQA,EAAKmB,GAAU,IAAI,IAAI,GAAGoD,GAAQ,MAAMvE,EAAI,SAAS,CACjE,CACJ,CAAC,EAED,IAAIP,GAAS,UAAY,CAErB,OAAI,OAAOS,GAAS,gBAAmB,YAC5BA,GAAS,eAEboE,EACX,EAAG,EAEIE,GAAQ/E,GCr2Bf,IAAMgF,GAAS,IAAIC,EAYbC,GAAYC,EAAM,IAAMC,EAC5B,IAAIC,GAAeC,GAAW,CAC5B,QAAWC,KAASD,EAClBN,GAAO,KAAKO,CAAK,CACrB,CAAC,CACH,CAAC,EACE,KACCC,EAAUC,GAAYC,EAAMC,GAAOP,EAAGK,CAAQ,CAAC,EAC5C,KACCG,EAAS,IAAMH,EAAS,WAAW,CAAC,CACtC,CACF,EACAI,EAAY,CAAC,CACf,EAaK,SAASC,GACdC,EACa,CACb,MAAO,CACL,MAAQA,EAAG,YACX,OAAQA,EAAG,YACb,CACF,CAuBO,SAASC,GACdD,EACyB,CACzB,OAAOb,GACJ,KACCe,EAAIR,GAAYA,EAAS,QAAQM,CAAE,CAAC,EACpCP,EAAUC,GAAYT,GACnB,KACCkB,EAAO,CAAC,CAAE,OAAAC,CAAO,IAAMA,IAAWJ,CAAE,EACpCH,EAAS,IAAMH,EAAS,UAAUM,CAAE,CAAC,EACrCK,EAAI,IAAMN,GAAeC,CAAE,CAAC,CAC9B,CACF,EACAM,EAAUP,GAAeC,CAAE,CAAC,CAC9B,CACJ,CC1GO,SAASO,GACdC,EACa,CACb,MAAO,CACL,MAAQA,EAAG,YACX,OAAQA,EAAG,YACb,CACF,CASO,SAASC,GACdD,EACyB,CACzB,IAAIE,EAASF,EAAG,cAChB,KAAOE,IAEHF,EAAG,aAAeE,EAAO,aACzBF,EAAG,cAAgBE,EAAO,eAE1BA,GAAUF,EAAKE,GAAQ,cAK3B,OAAOA,EAASF,EAAK,MACvB,CCfA,IAAMG,GAAS,IAAIC,EAUbC,GAAYC,EAAM,IAAMC,EAC5B,IAAI,qBAAqBC,GAAW,CAClC,QAAWC,KAASD,EAClBL,GAAO,KAAKM,CAAK,CACrB,EAAG,CACD,UAAW,CACb,CAAC,CACH,CAAC,EACE,KACCC,EAAUC,GAAYC,EAAMC,GAAON,EAAGI,CAAQ,CAAC,EAC5C,KACCG,EAAS,IAAMH,EAAS,WAAW,CAAC,CACtC,CACF,EACAI,EAAY,CAAC,CACf,EAaK,SAASC,GACdC,EACqB,CACrB,OAAOZ,GACJ,KACCa,EAAIP,GAAYA,EAAS,QAAQM,CAAE,CAAC,EACpCP,EAAUC,GAAYR,GACnB,KACCgB,EAAO,CAAC,CAAE,OAAAC,CAAO,IAAMA,IAAWH,CAAE,EACpCH,EAAS,IAAMH,EAAS,UAAUM,CAAE,CAAC,EACrCI,EAAI,CAAC,CAAE,eAAAC,CAAe,IAAMA,CAAc,CAC5C,CACF,CACF,CACJ,CAaO,SAASC,GACdN,EAAiBO,EAAY,GACR,CACrB,OAAOC,GAA0BR,CAAE,EAChC,KACCI,EAAI,CAAC,CAAE,EAAAK,CAAE,IAAM,CACb,IAAMC,EAAUC,GAAeX,CAAE,EAC3BY,EAAUC,GAAsBb,CAAE,EACxC,OAAOS,GACLG,EAAQ,OAASF,EAAQ,OAASH,CAEtC,CAAC,EACDO,EAAqB,CACvB,CACJ,CCjFA,IAAMC,GAA4C,CAChD,OAAQC,EAAW,yBAAyB,EAC5C,OAAQA,EAAW,yBAAyB,CAC9C,EAaO,SAASC,GAAUC,EAAuB,CAC/C,OAAOH,GAAQG,GAAM,OACvB,CAaO,SAASC,GAAUD,EAAcE,EAAsB,CACxDL,GAAQG,GAAM,UAAYE,GAC5BL,GAAQG,GAAM,MAAM,CACxB,CAWO,SAASG,GAAYH,EAAmC,CAC7D,IAAMI,EAAKP,GAAQG,GACnB,OAAOK,EAAUD,EAAI,QAAQ,EAC1B,KACCE,EAAI,IAAMF,EAAG,OAAO,EACpBG,EAAUH,EAAG,OAAO,CACtB,CACJ,CClCA,SAASI,GACPC,EAAiBC,EACR,CACT,OAAQD,EAAG,YAAa,CAGtB,KAAK,iBAEH,OAAIA,EAAG,OAAS,QACP,SAAS,KAAKC,CAAI,EAElB,GAGX,KAAK,kBACL,KAAK,oBACH,MAAO,GAGT,QACE,OAAOD,EAAG,iBACd,CACF,CAWO,SAASE,IAAsC,CACpD,OAAOC,EAAyB,OAAQ,SAAS,EAC9C,KACCC,EAAOC,GAAM,EAAEA,EAAG,SAAWA,EAAG,QAAQ,EACxCC,EAAID,IAAO,CACT,KAAME,GAAU,QAAQ,EAAI,SAAW,SACvC,KAAMF,EAAG,IACT,OAAQ,CACNA,EAAG,eAAe,EAClBA,EAAG,gBAAgB,CACrB,CACF,EAAc,EACdD,EAAO,CAAC,CAAE,KAAAI,EAAM,KAAAP,CAAK,IAAM,CACzB,GAAIO,IAAS,SAAU,CACrB,IAAMC,EAASC,GAAiB,EAChC,GAAI,OAAOD,GAAW,YACpB,MAAO,CAACV,GAAwBU,EAAQR,CAAI,CAChD,CACA,MAAO,EACT,CAAC,EACDU,GAAM,CACR,CACJ,CCpFO,SAASC,IAAmB,CACjC,OAAO,IAAI,IAAI,SAAS,IAAI,CAC9B,CAOO,SAASC,GAAYC,EAAgB,CAC1C,SAAS,KAAOA,EAAI,IACtB,CASO,SAASC,IAA8B,CAC5C,OAAO,IAAIC,CACb,CCLA,SAASC,GAAYC,EAAiBC,EAA8B,CAGlE,GAAI,OAAOA,GAAU,UAAY,OAAOA,GAAU,SAChDD,EAAG,WAAaC,EAAM,SAAS,UAGtBA,aAAiB,KAC1BD,EAAG,YAAYC,CAAK,UAGX,MAAM,QAAQA,CAAK,EAC5B,QAAWC,KAAQD,EACjBF,GAAYC,EAAIE,CAAI,CAE1B,CAyBO,SAASC,EACdC,EAAaC,KAAmCC,EAC7C,CACH,IAAMN,EAAK,SAAS,cAAcI,CAAG,EAGrC,GAAIC,EACF,QAAWE,KAAQ,OAAO,KAAKF,CAAU,EACnC,OAAOA,EAAWE,IAAU,cAI5B,OAAOF,EAAWE,IAAU,UAC9BP,EAAG,aAAaO,EAAMF,EAAWE,EAAK,EAEtCP,EAAG,aAAaO,EAAM,EAAE,GAI9B,QAAWN,KAASK,EAClBP,GAAYC,EAAIC,CAAK,EAGvB,OAAOD,CACT,CChFO,SAASQ,GAASC,EAAeC,EAAmB,CACzD,IAAIC,EAAID,EACR,GAAID,EAAM,OAASE,EAAG,CACpB,KAAOF,EAAME,KAAO,KAAO,EAAEA,EAAI,GAAG,CACpC,MAAO,GAAGF,EAAM,UAAU,EAAGE,CAAC,MAChC,CACA,OAAOF,CACT,CAkBO,SAASG,GAAMH,EAAuB,CAC3C,GAAIA,EAAQ,IAAK,CACf,IAAMI,EAAS,GAAGJ,EAAQ,KAAO,IAAO,IACxC,MAAO,KAAKA,EAAQ,MAAY,KAAM,QAAQI,CAAM,IACtD,KACE,QAAOJ,EAAM,SAAS,CAE1B,CC5BO,SAASK,IAA0B,CACxC,OAAO,SAAS,KAAK,UAAU,CAAC,CAClC,CAYO,SAASC,GAAgBC,EAAoB,CAClD,IAAMC,EAAKC,EAAE,IAAK,CAAE,KAAMF,CAAK,CAAC,EAChCC,EAAG,iBAAiB,QAASE,GAAMA,EAAG,gBAAgB,CAAC,EACvDF,EAAG,MAAM,CACX,CASO,SAASG,IAAwC,CACtD,OAAOC,EAA2B,OAAQ,YAAY,EACnD,KACCC,EAAIR,EAAe,EACnBS,EAAUT,GAAgB,CAAC,EAC3BU,EAAOR,GAAQA,EAAK,OAAS,CAAC,EAC9BS,EAAY,CAAC,CACf,CACJ,CAOO,SAASC,IAA+C,CAC7D,OAAON,GAAkB,EACtB,KACCE,EAAIK,GAAMC,GAAmB,QAAQD,KAAM,CAAE,EAC7CH,EAAOP,GAAM,OAAOA,GAAO,WAAW,CACxC,CACJ,CC1CO,SAASY,GAAWC,EAAoC,CAC7D,IAAMC,EAAQ,WAAWD,CAAK,EAC9B,OAAOE,GAA0BC,GAC/BF,EAAM,YAAY,IAAME,EAAKF,EAAM,OAAO,CAAC,CAC5C,EACE,KACCG,EAAUH,EAAM,OAAO,CACzB,CACJ,CAOO,SAASI,IAAkC,CAChD,IAAMJ,EAAQ,WAAW,OAAO,EAChC,OAAOK,EACLC,EAAU,OAAQ,aAAa,EAAE,KAAKC,EAAI,IAAM,EAAI,CAAC,EACrDD,EAAU,OAAQ,YAAY,EAAE,KAAKC,EAAI,IAAM,EAAK,CAAC,CACvD,EACG,KACCJ,EAAUH,EAAM,OAAO,CACzB,CACJ,CAcO,SAASQ,GACdC,EAA6BC,EACd,CACf,OAAOD,EACJ,KACCE,EAAUC,GAAUA,EAASF,EAAQ,EAAIG,CAAK,CAChD,CACJ,CC7CO,SAASC,GACdC,EAAmBC,EAAuB,CAAE,YAAa,aAAc,EACjD,CACtB,OAAOC,GAAK,MAAM,GAAGF,IAAOC,CAAO,CAAC,EACjC,KACCE,GAAW,IAAMC,CAAK,EACtBC,EAAUC,GAAOA,EAAI,SAAW,IAC5BC,GAAW,IAAM,IAAI,MAAMD,EAAI,UAAU,CAAC,EAC1CE,EAAGF,CAAG,CACV,CACF,CACJ,CAYO,SAASG,GACdT,EAAmBC,EACJ,CACf,OAAOF,GAAQC,EAAKC,CAAO,EACxB,KACCI,EAAUC,GAAOA,EAAI,KAAK,CAAC,EAC3BI,EAAY,CAAC,CACf,CACJ,CAUO,SAASC,GACdX,EAAmBC,EACG,CACtB,IAAMW,EAAM,IAAI,UAChB,OAAOb,GAAQC,EAAKC,CAAO,EACxB,KACCI,EAAUC,GAAOA,EAAI,KAAK,CAAC,EAC3BO,EAAIP,GAAOM,EAAI,gBAAgBN,EAAK,UAAU,CAAC,EAC/CI,EAAY,CAAC,CACf,CACJ,CClDO,SAASI,GAAYC,EAA+B,CACzD,IAAMC,EAASC,EAAE,SAAU,CAAE,IAAAF,CAAI,CAAC,EAClC,OAAOG,EAAM,KACX,SAAS,KAAK,YAAYF,CAAM,EACzBG,EACLC,EAAUJ,EAAQ,MAAM,EACxBI,EAAUJ,EAAQ,OAAO,EACtB,KACCK,EAAU,IACRC,GAAW,IAAM,IAAI,eAAe,mBAAmBP,GAAK,CAAC,CAC9D,CACH,CACJ,EACG,KACCQ,EAAI,IAAG,EAAY,EACnBC,EAAS,IAAM,SAAS,KAAK,YAAYR,CAAM,CAAC,EAChDS,GAAK,CAAC,CACR,EACH,CACH,CCfO,SAASC,IAAoC,CAClD,MAAO,CACL,EAAG,KAAK,IAAI,EAAG,OAAO,EACtB,EAAG,KAAK,IAAI,EAAG,OAAO,CACxB,CACF,CASO,SAASC,IAAkD,CAChE,OAAOC,EACLC,EAAU,OAAQ,SAAU,CAAE,QAAS,EAAK,CAAC,EAC7CA,EAAU,OAAQ,SAAU,CAAE,QAAS,EAAK,CAAC,CAC/C,EACG,KACCC,EAAIJ,EAAiB,EACrBK,EAAUL,GAAkB,CAAC,CAC/B,CACJ,CC3BO,SAASM,IAAgC,CAC9C,MAAO,CACL,MAAQ,WACR,OAAQ,WACV,CACF,CASO,SAASC,IAA8C,CAC5D,OAAOC,EAAU,OAAQ,SAAU,CAAE,QAAS,EAAK,CAAC,EACjD,KACCC,EAAIH,EAAe,EACnBI,EAAUJ,GAAgB,CAAC,CAC7B,CACJ,CCXO,SAASK,IAAsC,CACpD,OAAOC,EAAc,CACnBC,GAAoB,EACpBC,GAAkB,CACpB,CAAC,EACE,KACCC,EAAI,CAAC,CAACC,EAAQC,CAAI,KAAO,CAAE,OAAAD,EAAQ,KAAAC,CAAK,EAAE,EAC1CC,EAAY,CAAC,CACf,CACJ,CCVO,SAASC,GACdC,EAAiB,CAAE,UAAAC,EAAW,QAAAC,CAAQ,EAChB,CACtB,IAAMC,EAAQF,EACX,KACCG,EAAwB,MAAM,CAChC,EAGIC,EAAUC,EAAc,CAACH,EAAOD,CAAO,CAAC,EAC3C,KACCK,EAAI,IAAMC,GAAiBR,CAAE,CAAC,CAChC,EAGF,OAAOM,EAAc,CAACJ,EAASD,EAAWI,CAAO,CAAC,EAC/C,KACCE,EAAI,CAAC,CAAC,CAAE,OAAAE,CAAO,EAAG,CAAE,OAAAC,EAAQ,KAAAC,CAAK,EAAG,CAAE,EAAAC,EAAG,EAAAC,CAAE,CAAC,KAAO,CACjD,OAAQ,CACN,EAAGH,EAAO,EAAIE,EACd,EAAGF,EAAO,EAAIG,EAAIJ,CACpB,EACA,KAAAE,CACF,EAAE,CACJ,CACJ,CCIO,SAASG,GACdC,EAAgB,CAAE,IAAAC,CAAI,EACP,CAGf,IAAMC,EAAMC,EAAwBH,EAAQ,SAAS,EAClD,KACCI,EAAI,CAAC,CAAE,KAAAC,CAAK,IAAMA,CAAS,CAC7B,EAGF,OAAOJ,EACJ,KACCK,GAAS,IAAMJ,EAAK,CAAE,QAAS,GAAM,SAAU,EAAK,CAAC,EACrDK,EAAIC,GAAWR,EAAO,YAAYQ,CAAO,CAAC,EAC1CC,EAAU,IAAMP,CAAG,EACnBQ,GAAM,CACR,CACJ,CCCA,IAAMC,GAASC,EAAW,WAAW,EAC/BC,GAAiB,KAAK,MAAMF,GAAO,WAAY,EACrDE,GAAO,KAAO,GAAG,IAAI,IAAIA,GAAO,KAAMC,GAAY,CAAC,IAW5C,SAASC,IAAwB,CACtC,OAAOF,EACT,CASO,SAASG,EAAQC,EAAqB,CAC3C,OAAOJ,GAAO,SAAS,SAASI,CAAI,CACtC,CAUO,SAASC,GACdC,EAAkBC,EACV,CACR,OAAO,OAAOA,GAAU,YACpBP,GAAO,aAAaM,GAAK,QAAQ,IAAKC,EAAM,SAAS,CAAC,EACtDP,GAAO,aAAaM,EAC1B,CCjCO,SAASE,GACdC,EAASC,EAAmB,SACP,CACrB,OAAOC,EAAW,sBAAsBF,KAASC,CAAI,CACvD,CAYO,SAASE,GACdH,EAASC,EAAmB,SACL,CACvB,OAAOG,EAAY,sBAAsBJ,KAASC,CAAI,CACxD,CC1EO,SAASI,GACdC,EACsB,CACtB,IAAMC,EAASC,EAAW,6BAA8BF,CAAE,EAC1D,OAAOG,EAAUF,EAAQ,QAAS,CAAE,KAAM,EAAK,CAAC,EAC7C,KACCG,EAAI,IAAMF,EAAW,cAAeF,CAAE,CAAC,EACvCI,EAAIC,IAAY,CAAE,KAAM,UAAUA,EAAQ,SAAS,CAAE,EAAE,CACzD,CACJ,CASO,SAASC,GACdN,EACiC,CACjC,MAAI,CAACO,EAAQ,kBAAkB,GAAK,CAACP,EAAG,kBAC/BQ,EAGFC,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EAClB,OAAAD,EACG,KACCE,EAAU,CAAE,KAAM,SAAiB,YAAY,CAAE,CAAC,CACpD,EACG,UAAU,CAAC,CAAE,KAAAC,CAAK,IAAM,CA5FjC,IAAAC,EA6FcD,GAAQA,MAAUC,EAAA,SAAiB,YAAY,IAA7B,KAAAA,EAAkCD,KACtDb,EAAG,OAAS,GAGZ,SAAiB,aAAca,CAAI,EAEvC,CAAC,EAGEd,GAAcC,CAAE,EACpB,KACCe,EAAIC,GAASN,EAAM,KAAKM,CAAK,CAAC,EAC9BC,EAAS,IAAMP,EAAM,SAAS,CAAC,EAC/BN,EAAIY,GAAUE,EAAA,CAAE,IAAKlB,GAAOgB,EAAQ,CACtC,CACJ,CAAC,CACH,CC5BO,SAASG,GACdC,EAAiB,CAAE,QAAAC,CAAQ,EACN,CACrB,OAAOA,EACJ,KACCC,EAAIC,IAAW,CAAE,OAAQA,IAAWH,CAAG,EAAE,CAC3C,CACJ,CAYO,SAASI,GACdJ,EAAiBK,EACe,CAChC,IAAMC,EAAY,IAAIC,EACtB,OAAAD,EAAU,UAAU,CAAC,CAAE,OAAAE,CAAO,IAAM,CAClCR,EAAG,OAASQ,CACd,CAAC,EAGMT,GAAaC,EAAIK,CAAO,EAC5B,KACCI,EAAIC,GAASJ,EAAU,KAAKI,CAAK,CAAC,EAClCC,EAAS,IAAML,EAAU,SAAS,CAAC,EACnCJ,EAAIQ,GAAUE,EAAA,CAAE,IAAKZ,GAAOU,EAAQ,CACtC,CACJ,CC7FA,IAAAG,GAAwB,SCajB,SAASC,GAAcC,EAA0B,CACtD,OACEC,EAAC,OAAI,MAAM,aAAa,GAAID,GAC1BC,EAAC,OAAI,MAAM,+BAA+B,CAC5C,CAEJ,CCHO,SAASC,GACdC,EAAqBC,EACR,CAIb,GAHAA,EAASA,EAAS,GAAGA,gBAAqBD,IAAO,OAG7CC,EAAQ,CACV,IAAMC,EAASD,EAAS,IAAIA,IAAW,OACvC,OACEE,EAAC,SAAM,MAAM,gBAAgB,SAAU,GACpCC,GAAcH,CAAM,EACrBE,EAAC,KAAE,KAAMD,EAAQ,MAAM,uBAAuB,SAAU,IACtDC,EAAC,QAAK,wBAAuBH,EAAI,CACnC,CACF,CAEJ,KACE,QACEG,EAAC,SAAM,MAAM,gBAAgB,SAAU,GACpCC,GAAcH,CAAM,EACrBE,EAAC,QAAK,MAAM,uBAAuB,SAAU,IAC3CA,EAAC,QAAK,wBAAuBH,EAAI,CACnC,CACF,CAGN,CC5BO,SAASK,GAAsBC,EAAyB,CAC7D,OACEC,EAAC,UACC,MAAM,uBACN,MAAOC,GAAY,gBAAgB,EACnC,wBAAuB,IAAIF,WAC5B,CAEL,CCYA,SAASG,GACPC,EAA2CC,EAC9B,CACb,IAAMC,EAASD,EAAO,EAChBE,EAASF,EAAO,EAGhBG,EAAU,OAAO,KAAKJ,EAAS,KAAK,EACvC,OAAOK,GAAO,CAACL,EAAS,MAAMK,EAAI,EAClC,OAAyB,CAACC,EAAMD,IAAQ,CACvC,GAAGC,EAAMC,EAAC,WAAKF,CAAI,EAAQ,GAC7B,EAAG,CAAC,CAAC,EACJ,MAAM,EAAG,EAAE,EAGRG,EAAM,IAAI,IAAIR,EAAS,QAAQ,EACjCS,EAAQ,kBAAkB,GAC5BD,EAAI,aAAa,IAAI,IAAK,OAAO,QAAQR,EAAS,KAAK,EACpD,OAAO,CAAC,CAAC,CAAEU,CAAK,IAAMA,CAAK,EAC3B,OAAO,CAACC,EAAW,CAACC,CAAK,IAAM,GAAGD,KAAaC,IAAQ,KAAK,EAAG,EAAE,CACpE,EAGF,GAAM,CAAE,KAAAC,CAAK,EAAIC,GAAc,EAC/B,OACEP,EAAC,KAAE,KAAM,GAAGC,IAAO,MAAM,yBAAyB,SAAU,IAC1DD,EAAC,WACC,MAAO,CAAC,4BAA6B,GAAGL,EACpC,CAAC,qCAAqC,EACtC,CAAC,CACL,EAAE,KAAK,GAAG,EACV,gBAAeF,EAAS,MAAM,QAAQ,CAAC,GAEtCE,EAAS,GAAKK,EAAC,OAAI,MAAM,iCAAiC,EAC3DA,EAAC,MAAG,MAAM,2BAA2BP,EAAS,KAAM,EACnDG,EAAS,GAAKH,EAAS,KAAK,OAAS,GACpCO,EAAC,KAAE,MAAM,4BACNQ,GAASf,EAAS,KAAM,GAAG,CAC9B,EAEDA,EAAS,MACRO,EAAC,OAAI,MAAM,cACRP,EAAS,KAAK,IAAIgB,GAAO,CACxB,IAAMC,EAAKD,EAAI,QAAQ,WAAY,EAAE,EAC/BE,EAAOL,EACTI,KAAMJ,EACJ,4BAA4BA,EAAKI,KACjC,cACF,GACJ,OACEV,EAAC,QAAK,MAAO,UAAUW,KAASF,CAAI,CAExC,CAAC,CACH,EAEDb,EAAS,GAAKC,EAAQ,OAAS,GAC9BG,EAAC,KAAE,MAAM,2BACNY,GAAY,4BAA4B,EAAE,KAAG,GAAGf,CACnD,CAEJ,CACF,CAEJ,CAaO,SAASgB,GACdC,EACa,CACb,IAAMC,EAAYD,EAAO,GAAG,MACtBE,EAAO,CAAC,GAAGF,CAAM,EAGjBnB,EAASqB,EAAK,UAAUC,GAAO,CAACA,EAAI,SAAS,SAAS,GAAG,CAAC,EAC1D,CAACC,CAAO,EAAIF,EAAK,OAAOrB,EAAQ,CAAC,EAGnCwB,EAAQH,EAAK,UAAUC,GAAOA,EAAI,MAAQF,CAAS,EACnDI,IAAU,KACZA,EAAQH,EAAK,QAGf,IAAMI,EAAOJ,EAAK,MAAM,EAAGG,CAAK,EAC1BE,EAAOL,EAAK,MAAMG,CAAK,EAGvBG,EAAW,CACf9B,GAAqB0B,EAAS,EAAc,EAAE,CAACvB,GAAUwB,IAAU,EAAE,EACrE,GAAGC,EAAK,IAAIG,GAAW/B,GAAqB+B,EAAS,CAAW,CAAC,EACjE,GAAGF,EAAK,OAAS,CACfrB,EAAC,WAAQ,MAAM,0BACbA,EAAC,WAAQ,SAAU,IAChBqB,EAAK,OAAS,GAAKA,EAAK,SAAW,EAChCT,GAAY,wBAAwB,EACpCA,GAAY,2BAA4BS,EAAK,MAAM,CAEzD,EACC,GAAGA,EAAK,IAAIE,GAAW/B,GAAqB+B,EAAS,CAAW,CAAC,CACpE,CACF,EAAI,CAAC,CACP,EAGA,OACEvB,EAAC,MAAG,MAAM,0BACPsB,CACH,CAEJ,CC1IO,SAASE,GAAkBC,EAAiC,CACjE,OACEC,EAAC,MAAG,MAAM,oBACP,OAAO,QAAQD,CAAK,EAAE,IAAI,CAAC,CAACE,EAAKC,CAAK,IACrCF,EAAC,MAAG,MAAO,oCAAoCC,KAC5C,OAAOC,GAAU,SAAWC,GAAMD,CAAK,EAAIA,CAC9C,CACD,CACH,CAEJ,CCAO,SAASE,GACdC,EACa,CACb,IAAMC,EAAU,kCAAkCD,IAClD,OACEE,EAAC,OAAI,MAAOD,EAAS,OAAM,IACzBC,EAAC,UAAO,MAAM,gBAAgB,SAAU,GAAI,CAC9C,CAEJ,CCpBO,SAASC,GAAYC,EAAiC,CAC3D,OACEC,EAAC,OAAI,MAAM,0BACTA,EAAC,OAAI,MAAM,qBACRD,CACH,CACF,CAEJ,CCMA,SAASE,GAAcC,EAA+B,CACpD,IAAMC,EAASC,GAAc,EAGvBC,EAAM,IAAI,IAAI,MAAMH,EAAQ,WAAYC,EAAO,IAAI,EACzD,OACEG,EAAC,MAAG,MAAM,oBACRA,EAAC,KAAE,KAAM,GAAGD,IAAO,MAAM,oBACtBH,EAAQ,KACX,CACF,CAEJ,CAcO,SAASK,GACdC,EAAqBC,EACR,CACb,OACEH,EAAC,OAAI,MAAM,cACTA,EAAC,UACC,MAAM,sBACN,aAAYI,GAAY,sBAAsB,GAE7CD,EAAO,KACV,EACAH,EAAC,MAAG,MAAM,oBACPE,EAAS,IAAIP,EAAa,CAC7B,CACF,CAEJ,CCCO,SAASU,GACdC,EAAiBC,EACO,CACxB,IAAMC,EAAUC,EAAM,IAAMC,EAAc,CACxCC,GAAmBL,CAAE,EACrBM,GAA0BL,CAAS,CACrC,CAAC,CAAC,EACC,KACCM,EAAI,CAAC,CAAC,CAAE,EAAAC,EAAG,EAAAC,CAAE,EAAGC,CAAM,IAAqB,CACzC,GAAM,CAAE,MAAAC,EAAO,OAAAC,CAAO,EAAIC,GAAeb,CAAE,EAC3C,MAAQ,CACN,EAAGQ,EAAIE,EAAO,EAAIC,EAAQ,EAC1B,EAAGF,EAAIC,EAAO,EAAIE,EAAS,CAC7B,CACF,CAAC,CACH,EAGF,OAAOE,GAAkBd,CAAE,EACxB,KACCe,EAAUC,GAAUd,EACjB,KACCK,EAAIU,IAAW,CAAE,OAAAD,EAAQ,OAAAC,CAAO,EAAE,EAClCC,GAAK,CAAC,CAACF,GAAU,GAAQ,CAC3B,CACF,CACF,CACJ,CAWO,SAASG,GACdnB,EAAiBC,EAAwB,CAAE,QAAAmB,CAAQ,EAChB,CACnC,GAAM,CAACC,EAASC,CAAK,EAAI,MAAM,KAAKtB,EAAG,QAAQ,EAG/C,OAAOG,EAAM,IAAM,CACjB,IAAMoB,EAAQ,IAAIC,EACZC,EAAQF,EAAM,KAAKG,GAAS,CAAC,CAAC,EACpC,OAAAH,EAAM,UAAU,CAGd,KAAK,CAAE,OAAAN,CAAO,EAAG,CACfjB,EAAG,MAAM,YAAY,iBAAkB,GAAGiB,EAAO,KAAK,EACtDjB,EAAG,MAAM,YAAY,iBAAkB,GAAGiB,EAAO,KAAK,CACxD,EAGA,UAAW,CACTjB,EAAG,MAAM,eAAe,gBAAgB,EACxCA,EAAG,MAAM,eAAe,gBAAgB,CAC1C,CACF,CAAC,EAGD2B,GAAuB3B,CAAE,EACtB,KACC4B,GAAUH,CAAK,CACjB,EACG,UAAUI,GAAW,CACpB7B,EAAG,gBAAgB,kBAAmB6B,CAAO,CAC/C,CAAC,EAGLC,EACEP,EAAM,KAAKQ,EAAO,CAAC,CAAE,OAAAf,CAAO,IAAMA,CAAM,CAAC,EACzCO,EAAM,KAAKS,GAAa,GAAG,EAAGD,EAAO,CAAC,CAAE,OAAAf,CAAO,IAAM,CAACA,CAAM,CAAC,CAC/D,EACG,UAAU,CAGT,KAAK,CAAE,OAAAA,CAAO,EAAG,CACXA,EACFhB,EAAG,QAAQqB,CAAO,EAElBA,EAAQ,OAAO,CACnB,EAGA,UAAW,CACTrB,EAAG,QAAQqB,CAAO,CACpB,CACF,CAAC,EAGHE,EACG,KACCU,GAAU,GAAIC,EAAuB,CACvC,EACG,UAAU,CAAC,CAAE,OAAAlB,CAAO,IAAM,CACzBK,EAAQ,UAAU,OAAO,qBAAsBL,CAAM,CACvD,CAAC,EAGLO,EACG,KACCY,GAAa,IAAKD,EAAuB,EACzCH,EAAO,IAAM,CAAC,CAAC/B,EAAG,YAAY,EAC9BO,EAAI,IAAMP,EAAG,aAAc,sBAAsB,CAAC,EAClDO,EAAI,CAAC,CAAE,EAAAC,CAAE,IAAMA,CAAC,CAClB,EACG,UAAU,CAGT,KAAK4B,EAAQ,CACPA,EACFpC,EAAG,MAAM,YAAY,iBAAkB,GAAG,CAACoC,KAAU,EAErDpC,EAAG,MAAM,eAAe,gBAAgB,CAC5C,EAGA,UAAW,CACTA,EAAG,MAAM,eAAe,gBAAgB,CAC1C,CACF,CAAC,EAGLqC,EAAsBf,EAAO,OAAO,EACjC,KACCM,GAAUH,CAAK,EACfM,EAAOO,GAAM,EAAEA,EAAG,SAAWA,EAAG,QAAQ,CAC1C,EACG,UAAUA,GAAMA,EAAG,eAAe,CAAC,EAGxCD,EAAsBf,EAAO,WAAW,EACrC,KACCM,GAAUH,CAAK,EACfc,GAAehB,CAAK,CACtB,EACG,UAAU,CAAC,CAACe,EAAI,CAAE,OAAAtB,CAAO,CAAC,IAAM,CAvOzC,IAAAwB,EA0OU,GAAIF,EAAG,SAAW,GAAKA,EAAG,SAAWA,EAAG,QACtCA,EAAG,eAAe,UAGTtB,EAAQ,CACjBsB,EAAG,eAAe,EAGlB,IAAMG,EAASzC,EAAG,cAAe,QAAQ,gBAAgB,EACrDyC,aAAkB,YACpBA,EAAO,MAAM,GAEbD,EAAAE,GAAiB,IAAjB,MAAAF,EAAoB,MACxB,CACF,CAAC,EAGLpB,EACG,KACCQ,GAAUH,CAAK,EACfM,EAAOY,GAAUA,IAAWtB,CAAO,EACnCuB,GAAM,GAAG,CACX,EACG,UAAU,IAAM5C,EAAG,MAAM,CAAC,EAGxBD,GAAgBC,EAAIC,CAAS,EACjC,KACC4C,EAAIC,GAASvB,EAAM,KAAKuB,CAAK,CAAC,EAC9BC,EAAS,IAAMxB,EAAM,SAAS,CAAC,EAC/BhB,EAAIuC,GAAUE,EAAA,CAAE,IAAKhD,GAAO8C,EAAQ,CACtC,CACJ,CAAC,CACH,CCrMA,SAASG,GAAsBC,EAAgC,CAC7D,IAAMC,EAAkB,CAAC,EACzB,QAAWC,KAAMC,EAAY,eAAgBH,CAAS,EAAG,CACvD,IAAMI,EAAgB,CAAC,EAGjBC,EAAK,SAAS,mBAAmBH,EAAI,WAAW,SAAS,EAC/D,QAASI,EAAOD,EAAG,SAAS,EAAGC,EAAMA,EAAOD,EAAG,SAAS,EACtDD,EAAM,KAAKE,CAAY,EAGzB,QAASC,KAAQH,EAAO,CACtB,IAAII,EAGJ,KAAQA,EAAQ,gBAAgB,KAAKD,EAAK,WAAY,GAAI,CACxD,GAAM,CAAC,CAAEE,EAAIC,CAAK,EAAIF,EACtB,GAAI,OAAOE,GAAU,YAAa,CAChC,IAAMC,EAASJ,EAAK,UAAUC,EAAM,KAAK,EACzCD,EAAOI,EAAO,UAAUF,EAAG,MAAM,EACjCR,EAAQ,KAAKU,CAAM,CAGrB,KAAO,CACLJ,EAAK,YAAcE,EACnBR,EAAQ,KAAKM,CAAI,EACjB,KACF,CACF,CACF,CACF,CACA,OAAON,CACT,CAQA,SAASW,GAAKC,EAAqBC,EAA2B,CAC5DA,EAAO,OAAO,GAAG,MAAM,KAAKD,EAAO,UAAU,CAAC,CAChD,CAoBO,SAASE,GACdb,EAAiBF,EAAwB,CAAE,QAAAgB,EAAS,OAAAC,CAAO,EACxB,CAGnC,IAAMC,EAASlB,EAAU,QAAQ,MAAM,EACjCmB,EAASD,GAAA,YAAAA,EAAQ,GAGjBE,EAAc,IAAI,IACxB,QAAWT,KAAUZ,GAAsBC,CAAS,EAAG,CACrD,GAAM,CAAC,CAAES,CAAE,EAAIE,EAAO,YAAa,MAAM,WAAW,EAChDU,GAAmB,gBAAgBZ,KAAOP,CAAE,IAC9CkB,EAAY,IAAIX,EAAIa,GAAiBb,EAAIU,CAAM,CAAC,EAChDR,EAAO,YAAYS,EAAY,IAAIX,CAAE,CAAE,EAE3C,CAGA,OAAIW,EAAY,OAAS,EAChBG,EAGFC,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EAGZC,EAAsC,CAAC,EAC7C,OAAW,CAAClB,EAAImB,CAAU,IAAKR,EAC7BO,EAAM,KAAK,CACTE,EAAW,cAAeD,CAAU,EACpCC,EAAW,gBAAgBpB,KAAOP,CAAE,CACtC,CAAC,EAGH,OAAAe,EACG,KACCa,GAAUL,EAAM,KAAKM,GAAS,CAAC,CAAC,CAAC,CACnC,EACG,UAAUC,GAAU,CACnB9B,EAAG,OAAS,CAAC8B,EAGb,OAAW,CAACC,EAAOC,CAAK,IAAKP,EACtBK,EAGHpB,GAAKqB,EAAOC,CAAK,EAFjBtB,GAAKsB,EAAOD,CAAK,CAGvB,CAAC,EAGEE,EAAM,GAAG,CAAC,GAAGf,CAAW,EAC5B,IAAI,CAAC,CAAC,CAAEQ,CAAU,IACjBQ,GAAgBR,EAAY5B,EAAW,CAAE,QAAAgB,CAAQ,CAAC,CACnD,CACH,EACG,KACCqB,EAAS,IAAMZ,EAAM,SAAS,CAAC,EAC/Ba,GAAM,CACR,CACJ,CAAC,CACH,CV9GA,IAAIC,GAAW,EAaf,SAASC,GAAkBC,EAA0C,CACnE,GAAIA,EAAG,mBAAoB,CACzB,IAAMC,EAAUD,EAAG,mBACnB,GAAIC,EAAQ,UAAY,KACtB,OAAOA,EAGJ,GAAIA,EAAQ,UAAY,KAAO,CAACA,EAAQ,SAAS,OACpD,OAAOF,GAAkBE,CAAO,CACpC,CAIF,CAgBO,SAASC,GACdF,EACuB,CACvB,OAAOG,GAAiBH,CAAE,EACvB,KACCI,EAAI,CAAC,CAAE,MAAAC,CAAM,KAEJ,CACL,WAFcC,GAAsBN,CAAE,EAElB,MAAQK,CAC9B,EACD,EACDE,EAAwB,YAAY,CACtC,CACJ,CAoBO,SAASC,GACdR,EAAiBS,EAC8B,CAC/C,GAAM,CAAE,QAASC,CAAM,EAAI,WAAW,SAAS,EAGzCC,EAAWC,EAAM,IAAM,CAC3B,IAAMC,EAAQ,IAAIC,EASlB,GARAD,EAAM,UAAU,CAAC,CAAE,WAAAE,CAAW,IAAM,CAC9BA,GAAcL,EAChBV,EAAG,aAAa,WAAY,GAAG,EAE/BA,EAAG,gBAAgB,UAAU,CACjC,CAAC,EAGG,GAAAgB,QAAY,YAAY,EAAG,CAC7B,IAAMC,EAASjB,EAAG,QAAQ,KAAK,EAC/BiB,EAAO,GAAK,UAAU,EAAEnB,KACxBmB,EAAO,aACLC,GAAsBD,EAAO,EAAE,EAC/BjB,CACF,CACF,CAGA,IAAMmB,EAAYnB,EAAG,QAAQ,YAAY,EACzC,GAAImB,aAAqB,YAAa,CACpC,IAAMC,EAAOrB,GAAkBoB,CAAS,EAGxC,GAAI,OAAOC,GAAS,cAClBD,EAAU,UAAU,SAAS,UAAU,GACvCE,EAAQ,uBAAuB,GAC9B,CACD,IAAMC,EAAeC,GAAoBH,EAAMpB,EAAIS,CAAO,EAG1D,OAAOP,GAAeF,CAAE,EACrB,KACCwB,EAAIC,GAASZ,EAAM,KAAKY,CAAK,CAAC,EAC9BC,EAAS,IAAMb,EAAM,SAAS,CAAC,EAC/BT,EAAIqB,GAAUE,EAAA,CAAE,IAAK3B,GAAOyB,EAAQ,EACpCG,GACEzB,GAAiBgB,CAAS,EACvB,KACCf,EAAI,CAAC,CAAE,MAAAC,EAAO,OAAAwB,CAAO,IAAMxB,GAASwB,CAAM,EAC1CC,EAAqB,EACrBC,EAAUC,GAAUA,EAASV,EAAeW,CAAK,CACnD,CACJ,CACF,CACJ,CACF,CAGA,OAAO/B,GAAeF,CAAE,EACrB,KACCwB,EAAIC,GAASZ,EAAM,KAAKY,CAAK,CAAC,EAC9BC,EAAS,IAAMb,EAAM,SAAS,CAAC,EAC/BT,EAAIqB,GAAUE,EAAA,CAAE,IAAK3B,GAAOyB,EAAQ,CACtC,CACJ,CAAC,EAGD,OAAIJ,EAAQ,cAAc,EACjBa,GAAuBlC,CAAE,EAC7B,KACCmC,EAAOC,GAAWA,CAAO,EACzBC,GAAK,CAAC,EACNN,EAAU,IAAMpB,CAAQ,CAC1B,EAGGA,CACT,iyJWpLA,IAAI2B,GAKAC,GAAW,EAWf,SAASC,IAAiC,CACxC,OAAO,OAAO,SAAY,aAAe,mBAAmB,QACxDC,GAAY,qDAAqD,EACjEC,EAAG,MAAS,CAClB,CAaO,SAASC,GACdC,EACgC,CAChC,OAAAA,EAAG,UAAU,OAAO,SAAS,EAC7BN,QAAaE,GAAa,EACvB,KACCK,EAAI,IAAM,QAAQ,WAAW,CAC3B,YAAa,GACb,SAAAC,GACA,SAAU,CACR,cAAe,OACf,gBAAiB,OACjB,aAAc,MAChB,CACF,CAAC,CAAC,EACFC,EAAI,IAAG,EAAY,EACnBC,EAAY,CAAC,CACf,GAGFV,GAAS,UAAU,IAAM,CACvBM,EAAG,UAAU,IAAI,SAAS,EAC1B,IAAMK,EAAK,aAAaV,OAClBW,EAAOC,EAAE,MAAO,CAAE,MAAO,SAAU,CAAC,EAC1C,QAAQ,WAAW,OAAOF,EAAIL,EAAG,YAAcQ,GAAgB,CAG7D,IAAMC,EAASH,EAAK,aAAa,CAAE,KAAM,QAAS,CAAC,EACnDG,EAAO,UAAYD,EAGnBR,EAAG,YAAYM,CAAI,CACrB,CAAC,CACH,CAAC,EAGMZ,GACJ,KACCS,EAAI,KAAO,CAAE,IAAKH,CAAG,EAAE,CACzB,CACJ,CC/CO,SAASU,GACdC,EAAwB,CAAE,QAAAC,EAAS,OAAAC,CAAO,EACrB,CACrB,IAAIC,EAAO,GACX,OAAOC,EAGLH,EACG,KACCI,EAAIC,GAAUA,EAAO,QAAQ,qBAAqB,CAAE,EACpDC,EAAOC,GAAWR,IAAOQ,CAAO,EAChCH,EAAI,KAAO,CACT,OAAQ,OAAQ,OAAQ,EAC1B,EAAa,CACf,EAGFH,EACG,KACCK,EAAOE,GAAUA,GAAU,CAACN,CAAI,EAChCO,EAAI,IAAMP,EAAOH,EAAG,IAAI,EACxBK,EAAII,IAAW,CACb,OAAQA,EAAS,OAAS,OAC5B,EAAa,CACf,CACJ,CACF,CAaO,SAASE,GACdX,EAAwBY,EACQ,CAChC,OAAOC,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EAClB,OAAAD,EAAM,UAAU,CAAC,CAAE,OAAAE,EAAQ,OAAAC,CAAO,IAAM,CACtCjB,EAAG,gBAAgB,OAAQgB,IAAW,MAAM,EACxCC,GACFjB,EAAG,eAAe,CACtB,CAAC,EAGMD,GAAaC,EAAIY,CAAO,EAC5B,KACCF,EAAIQ,GAASJ,EAAM,KAAKI,CAAK,CAAC,EAC9BC,EAAS,IAAML,EAAM,SAAS,CAAC,EAC/BT,EAAIa,GAAUE,EAAA,CAAE,IAAKpB,GAAOkB,EAAQ,CACtC,CACJ,CAAC,CACH,CC5FA,IAAMG,GAAWC,EAAE,OAAO,EAgBnB,SAASC,GACdC,EACkC,CAClC,OAAAA,EAAG,YAAYH,EAAQ,EACvBA,GAAS,YAAYI,GAAYD,CAAE,CAAC,EAG7BE,EAAG,CAAE,IAAKF,CAAG,CAAC,CACvB,CCuBO,SAASG,GACdC,EACyB,CACzB,IAAMC,EAASC,EAA8B,iBAAkBF,CAAE,EAC3DG,EAAUF,EAAO,KAAKG,GAASA,EAAM,OAAO,GAAKH,EAAO,GAC9D,OAAOI,EAAM,GAAGJ,EAAO,IAAIG,GAASE,EAAUF,EAAO,QAAQ,EAC1D,KACCG,EAAI,IAAMC,EAA6B,cAAcJ,EAAM,MAAM,CAAC,CACpE,CACF,CAAC,EACE,KACCK,EAAUD,EAA6B,cAAcL,EAAQ,MAAM,CAAC,EACpEI,EAAIG,IAAW,CAAE,OAAAA,CAAO,EAAE,CAC5B,CACJ,CAeO,SAASC,GACdX,EAAiB,CAAE,UAAAY,CAAU,EACO,CAGpC,IAAMC,EAAOC,GAAoB,MAAM,EACvCd,EAAG,OAAOa,CAAI,EAGd,IAAME,EAAOD,GAAoB,MAAM,EACvCd,EAAG,OAAOe,CAAI,EAGd,IAAMC,EAAYR,EAAW,iBAAkBR,CAAE,EACjD,OAAOiB,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EACZC,EAAQF,EAAM,KAAKG,GAAS,CAAC,CAAC,EACpC,OAAAC,EAAc,CAACJ,EAAOK,GAAiBvB,CAAE,CAAC,CAAC,EACxC,KACCwB,GAAU,EAAGC,EAAuB,EACpCC,GAAUN,CAAK,CACjB,EACG,UAAU,CAGT,KAAK,CAAC,CAAE,OAAAV,CAAO,EAAGiB,CAAI,EAAG,CACvB,IAAMC,EAASC,GAAiBnB,CAAM,EAChC,CAAE,MAAAoB,CAAM,EAAIC,GAAerB,CAAM,EAGvCV,EAAG,MAAM,YAAY,mBAAoB,GAAG4B,EAAO,KAAK,EACxD5B,EAAG,MAAM,YAAY,uBAAwB,GAAG8B,KAAS,EAGzD,IAAME,EAAUC,GAAwBjB,CAAS,GAE/CY,EAAO,EAAYI,EAAQ,GAC3BJ,EAAO,EAAIE,EAAQE,EAAQ,EAAIL,EAAK,QAEpCX,EAAU,SAAS,CACjB,KAAM,KAAK,IAAI,EAAGY,EAAO,EAAI,EAAE,EAC/B,SAAU,QACZ,CAAC,CACL,EAGA,UAAW,CACT5B,EAAG,MAAM,eAAe,kBAAkB,EAC1CA,EAAG,MAAM,eAAe,sBAAsB,CAChD,CACF,CAAC,EAGLsB,EAAc,CACZY,GAA0BlB,CAAS,EACnCO,GAAiBP,CAAS,CAC5B,CAAC,EACE,KACCU,GAAUN,CAAK,CACjB,EACG,UAAU,CAAC,CAACQ,EAAQD,CAAI,IAAM,CAC7B,IAAMK,EAAUG,GAAsBnB,CAAS,EAC/CH,EAAK,OAASe,EAAO,EAAI,GACzBb,EAAK,OAASa,EAAO,EAAII,EAAQ,MAAQL,EAAK,MAAQ,EACxD,CAAC,EAGLtB,EACEC,EAAUO,EAAM,OAAO,EAAE,KAAKN,EAAI,IAAM,EAAE,CAAC,EAC3CD,EAAUS,EAAM,OAAO,EAAE,KAAKR,EAAI,IAAM,CAAE,CAAC,CAC7C,EACG,KACCmB,GAAUN,CAAK,CACjB,EACG,UAAUgB,GAAa,CACtB,GAAM,CAAE,MAAAN,CAAM,EAAIC,GAAef,CAAS,EAC1CA,EAAU,SAAS,CACjB,KAAMc,EAAQM,EACd,SAAU,QACZ,CAAC,CACH,CAAC,EAGDC,EAAQ,mBAAmB,GAC7BnB,EAAM,KACJoB,GAAK,CAAC,EACNC,GAAe3B,CAAS,CAC1B,EACG,UAAU,CAAC,CAAC,CAAE,OAAAF,CAAO,EAAG,CAAE,OAAAkB,CAAO,CAAC,IAAM,CACvC,IAAMY,EAAM9B,EAAO,UAAU,KAAK,EAClC,GAAIA,EAAO,aAAa,mBAAmB,EACzCA,EAAO,gBAAgB,mBAAmB,MAGrC,CACL,IAAM+B,EAAIzC,EAAG,UAAY4B,EAAO,EAGhC,QAAWc,KAAOxC,EAAY,aAAa,EACzC,QAAWE,KAASF,EAClB,iBAAkBwC,CACpB,EAAG,CACD,IAAMC,EAAQnC,EAAW,cAAcJ,EAAM,MAAM,EACnD,GACEuC,IAAUjC,GACViC,EAAM,UAAU,KAAK,IAAMH,EAC3B,CACAG,EAAM,aAAa,oBAAqB,EAAE,EAC1CvC,EAAM,MAAM,EACZ,KACF,CACF,CAGF,OAAO,SAAS,CACd,IAAKJ,EAAG,UAAYyC,CACtB,CAAC,EAGD,IAAMG,EAAO,SAAmB,QAAQ,GAAK,CAAC,EAC9C,SAAS,SAAU,CAAC,GAAG,IAAI,IAAI,CAACJ,EAAK,GAAGI,CAAI,CAAC,CAAC,CAAC,CACjD,CACF,CAAC,EAGE7C,GAAiBC,CAAE,EACvB,KACC6C,EAAIC,GAAS5B,EAAM,KAAK4B,CAAK,CAAC,EAC9BC,EAAS,IAAM7B,EAAM,SAAS,CAAC,EAC/BX,EAAIuC,GAAUE,EAAA,CAAE,IAAKhD,GAAO8C,EAAQ,CACtC,CACJ,CAAC,EACE,KACCG,GAAYC,EAAc,CAC5B,CACJ,CCtKO,SAASC,GACdC,EAAiB,CAAE,UAAAC,EAAW,QAAAC,EAAS,OAAAC,CAAO,EACd,CAChC,OAAOC,EAGL,GAAGC,EAAY,2BAA4BL,CAAE,EAC1C,IAAIM,GAASC,GAAeD,EAAO,CAAE,QAAAJ,EAAS,OAAAC,CAAO,CAAC,CAAC,EAG1D,GAAGE,EAAY,cAAeL,CAAE,EAC7B,IAAIM,GAASE,GAAaF,CAAK,CAAC,EAGnC,GAAGD,EAAY,qBAAsBL,CAAE,EACpC,IAAIM,GAASG,GAAeH,CAAK,CAAC,EAGrC,GAAGD,EAAY,UAAWL,CAAE,EACzB,IAAIM,GAASI,GAAaJ,EAAO,CAAE,QAAAJ,EAAS,OAAAC,CAAO,CAAC,CAAC,EAGxD,GAAGE,EAAY,cAAeL,CAAE,EAC7B,IAAIM,GAASK,GAAiBL,EAAO,CAAE,UAAAL,CAAU,CAAC,CAAC,CACxD,CACF,CClCO,SAASW,GACdC,EAAkB,CAAE,OAAAC,CAAO,EACP,CACpB,OAAOA,EACJ,KACCC,EAAUC,GAAWC,EACnBC,EAAG,EAAI,EACPA,EAAG,EAAK,EAAE,KAAKC,GAAM,GAAI,CAAC,CAC5B,EACG,KACCC,EAAIC,IAAW,CAAE,QAAAL,EAAS,OAAAK,CAAO,EAAE,CACrC,CACF,CACF,CACJ,CAaO,SAASC,GACdC,EAAiBC,EACc,CAC/B,IAAMC,EAAQC,EAAW,cAAeH,CAAE,EAC1C,OAAOI,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EAClB,OAAAD,EAAM,UAAU,CAAC,CAAE,QAAAZ,EAAS,OAAAK,CAAO,IAAM,CACvCE,EAAG,UAAU,OAAO,oBAAqBF,CAAM,EAC/CI,EAAM,YAAcT,CACtB,CAAC,EAGMJ,GAAYW,EAAIC,CAAO,EAC3B,KACCM,EAAIC,GAASH,EAAM,KAAKG,CAAK,CAAC,EAC9BC,EAAS,IAAMJ,EAAM,SAAS,CAAC,EAC/BR,EAAIW,GAAUE,EAAA,CAAE,IAAKV,GAAOQ,EAAQ,CACtC,CACJ,CAAC,CACH,CC9BA,SAASG,GAAS,CAAE,UAAAC,CAAU,EAAsC,CAClE,GAAI,CAACC,EAAQ,iBAAiB,EAC5B,OAAOC,EAAG,EAAK,EAGjB,IAAMC,EAAaH,EAChB,KACCI,EAAI,CAAC,CAAE,OAAQ,CAAE,EAAAC,CAAE,CAAE,IAAMA,CAAC,EAC5BC,GAAY,EAAG,CAAC,EAChBF,EAAI,CAAC,CAACG,EAAGC,CAAC,IAAM,CAACD,EAAIC,EAAGA,CAAC,CAAU,EACnCC,EAAwB,CAAC,CAC3B,EAGIC,EAAUC,EAAc,CAACX,EAAWG,CAAU,CAAC,EAClD,KACCS,EAAO,CAAC,CAAC,CAAE,OAAAC,CAAO,EAAG,CAAC,CAAER,CAAC,CAAC,IAAM,KAAK,IAAIA,EAAIQ,EAAO,CAAC,EAAI,GAAG,EAC5DT,EAAI,CAAC,CAAC,CAAE,CAACU,CAAS,CAAC,IAAMA,CAAS,EAClCC,EAAqB,CACvB,EAGIC,EAAUC,GAAY,QAAQ,EACpC,OAAON,EAAc,CAACX,EAAWgB,CAAO,CAAC,EACtC,KACCZ,EAAI,CAAC,CAAC,CAAE,OAAAS,CAAO,EAAGK,CAAM,IAAML,EAAO,EAAI,KAAO,CAACK,CAAM,EACvDH,EAAqB,EACrBI,EAAUC,GAAUA,EAASV,EAAUR,EAAG,EAAK,CAAC,EAChDmB,EAAU,EAAK,CACjB,CACJ,CAcO,SAASC,GACdC,EAAiBC,EACG,CACpB,OAAOC,EAAM,IAAMd,EAAc,CAC/Be,GAAiBH,CAAE,EACnBxB,GAASyB,CAAO,CAClB,CAAC,CAAC,EACC,KACCpB,EAAI,CAAC,CAAC,CAAE,OAAAuB,CAAO,EAAGC,CAAM,KAAO,CAC7B,OAAAD,EACA,OAAAC,CACF,EAAE,EACFb,EAAqB,CAACR,EAAGC,IACvBD,EAAE,SAAWC,EAAE,QACfD,EAAE,SAAWC,EAAE,MAChB,EACDqB,EAAY,CAAC,CACf,CACJ,CAaO,SAASC,GACdP,EAAiB,CAAE,QAAAQ,EAAS,MAAAC,CAAM,EACH,CAC/B,OAAOP,EAAM,IAAM,CACjB,IAAMQ,EAAQ,IAAIC,EACZC,EAAQF,EAAM,KAAKG,GAAS,CAAC,CAAC,EACpC,OAAAH,EACG,KACCxB,EAAwB,QAAQ,EAChC4B,GAAkBN,CAAO,CAC3B,EACG,UAAU,CAAC,CAAC,CAAE,OAAAX,CAAO,EAAG,CAAE,OAAAQ,CAAO,CAAC,IAAM,CACvCL,EAAG,UAAU,OAAO,oBAAqBH,GAAU,CAACQ,CAAM,EAC1DL,EAAG,OAASK,CACd,CAAC,EAGLI,EAAM,UAAUC,CAAK,EAGdF,EACJ,KACCO,GAAUH,CAAK,EACf/B,EAAImC,GAAUC,EAAA,CAAE,IAAKjB,GAAOgB,EAAQ,CACtC,CACJ,CAAC,CACH,CChHO,SAASE,GACdC,EAAiB,CAAE,UAAAC,EAAW,QAAAC,CAAQ,EACb,CACzB,OAAOC,GAAgBH,EAAI,CAAE,UAAAC,EAAW,QAAAC,CAAQ,CAAC,EAC9C,KACCE,EAAI,CAAC,CAAE,OAAQ,CAAE,EAAAC,CAAE,CAAE,IAAM,CACzB,GAAM,CAAE,OAAAC,CAAO,EAAIC,GAAeP,CAAE,EACpC,MAAO,CACL,OAAQK,GAAKC,CACf,CACF,CAAC,EACDE,EAAwB,QAAQ,CAClC,CACJ,CAaO,SAASC,GACdT,EAAiBU,EACmB,CACpC,OAAOC,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EAClBD,EAAM,UAAU,CAAC,CAAE,OAAAE,CAAO,IAAM,CAC9Bd,EAAG,UAAU,OAAO,2BAA4Bc,CAAM,CACxD,CAAC,EAGD,IAAMC,EAAUC,GAAmB,YAAY,EAC/C,OAAI,OAAOD,GAAY,YACdE,EAGFlB,GAAiBgB,EAASL,CAAO,EACrC,KACCQ,EAAIC,GAASP,EAAM,KAAKO,CAAK,CAAC,EAC9BC,EAAS,IAAMR,EAAM,SAAS,CAAC,EAC/BR,EAAIe,GAAUE,EAAA,CAAE,IAAKrB,GAAOmB,EAAQ,CACtC,CACJ,CAAC,CACH,CCvDO,SAASG,GACdC,EAAiB,CAAE,UAAAC,EAAW,QAAAC,CAAQ,EACpB,CAGlB,IAAMC,EAAUD,EACb,KACCE,EAAI,CAAC,CAAE,OAAAC,CAAO,IAAMA,CAAM,EAC1BC,EAAqB,CACvB,EAGIC,EAAUJ,EACb,KACCK,EAAU,IAAMC,GAAiBT,CAAE,EAChC,KACCI,EAAI,CAAC,CAAE,OAAAC,CAAO,KAAO,CACnB,IAAQL,EAAG,UACX,OAAQA,EAAG,UAAYK,CACzB,EAAE,EACFK,EAAwB,QAAQ,CAClC,CACF,CACF,EAGF,OAAOC,EAAc,CAACR,EAASI,EAASN,CAAS,CAAC,EAC/C,KACCG,EAAI,CAAC,CAACQ,EAAQ,CAAE,IAAAC,EAAK,OAAAC,CAAO,EAAG,CAAE,OAAQ,CAAE,EAAAC,CAAE,EAAG,KAAM,CAAE,OAAAV,CAAO,CAAE,CAAC,KAChEA,EAAS,KAAK,IAAI,EAAGA,EACjB,KAAK,IAAI,EAAGQ,EAASE,EAAIH,CAAM,EAC/B,KAAK,IAAI,EAAGP,EAASU,EAAID,CAAM,CACnC,EACO,CACL,OAAQD,EAAMD,EACd,OAAAP,EACA,OAAQQ,EAAMD,GAAUG,CAC1B,EACD,EACDT,EAAqB,CAACU,EAAGC,IACvBD,EAAE,SAAWC,EAAE,QACfD,EAAE,SAAWC,EAAE,QACfD,EAAE,SAAWC,EAAE,MAChB,CACH,CACJ,CClDO,SAASC,GACdC,EACqB,CACrB,IAAMC,EAAU,SAAkB,WAAW,GAAK,CAChD,MAAOD,EAAO,UAAUE,GAAS,WAC/BA,EAAM,aAAa,qBAAqB,CAC1C,EAAE,OAAO,CACX,EAGA,OAAOC,EAAG,GAAGH,CAAM,EAChB,KACCI,GAASF,GAASG,EAAUH,EAAO,QAAQ,EACxC,KACCI,EAAI,IAAMJ,CAAK,CACjB,CACF,EACAK,EAAUP,EAAO,KAAK,IAAI,EAAGC,EAAQ,KAAK,EAAE,EAC5CK,EAAIJ,IAAU,CACZ,MAAOF,EAAO,QAAQE,CAAK,EAC3B,MAAO,CACL,OAASA,EAAM,aAAa,sBAAsB,EAClD,QAASA,EAAM,aAAa,uBAAuB,EACnD,OAASA,EAAM,aAAa,sBAAsB,CACpD,CACF,EAAa,EACbM,EAAY,CAAC,CACf,CACJ,CASO,SAASC,GACdC,EACgC,CAChC,OAAOC,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EAClBD,EAAM,UAAUE,GAAW,CACzB,SAAS,KAAK,aAAa,0BAA2B,EAAE,EAGxD,OAAW,CAACC,EAAKC,CAAK,IAAK,OAAO,QAAQF,EAAQ,KAAK,EACrD,SAAS,KAAK,aAAa,iBAAiBC,IAAOC,CAAK,EAG1D,QAASC,EAAQ,EAAGA,EAAQjB,EAAO,OAAQiB,IAAS,CAClD,IAAMC,EAAQlB,EAAOiB,GAAO,mBACxBC,aAAiB,cACnBA,EAAM,OAASJ,EAAQ,QAAUG,EACrC,CAGA,SAAS,YAAaH,CAAO,CAC/B,CAAC,EAGDF,EAAM,KAAKO,GAAUC,EAAc,CAAC,EACjC,UAAU,IAAM,CACf,SAAS,KAAK,gBAAgB,yBAAyB,CACzD,CAAC,EAGH,IAAMpB,EAASqB,EAA8B,QAASX,CAAE,EACxD,OAAOX,GAAaC,CAAM,EACvB,KACCsB,EAAIC,GAASX,EAAM,KAAKW,CAAK,CAAC,EAC9BC,EAAS,IAAMZ,EAAM,SAAS,CAAC,EAC/BN,EAAIiB,GAAUE,EAAA,CAAE,IAAKf,GAAOa,EAAQ,CACtC,CACJ,CAAC,CACH,CC/HA,IAAAG,GAAwB,SAiCxB,SAASC,GAAQC,EAAyB,CACxCA,EAAG,aAAa,kBAAmB,EAAE,EACrC,IAAMC,EAAOD,EAAG,UAChB,OAAAA,EAAG,gBAAgB,iBAAiB,EAC7BC,CACT,CAWO,SAASC,GACd,CAAE,OAAAC,CAAO,EACH,CACF,GAAAC,QAAY,YAAY,GAC1B,IAAIC,EAA8BC,GAAc,CAC9C,IAAI,GAAAF,QAAY,iDAAkD,CAChE,KAAMJ,GACJA,EAAG,aAAa,qBAAqB,GACrCD,GAAQQ,EACNP,EAAG,aAAa,uBAAuB,CACzC,CAAC,CAEL,CAAC,EACE,GAAG,UAAWQ,GAAMF,EAAW,KAAKE,CAAE,CAAC,CAC5C,CAAC,EACE,KACCC,EAAID,GAAM,CACQA,EAAG,QACX,MAAM,CAChB,CAAC,EACDE,EAAI,IAAMC,GAAY,kBAAkB,CAAC,CAC3C,EACG,UAAUR,CAAM,CAEzB,CCrCA,SAASS,GAAWC,EAAwB,CAC1C,GAAIA,EAAK,OAAS,EAChB,MAAO,CAAC,EAAE,EAGZ,GAAM,CAACC,EAAMC,CAAI,EAAI,CAAC,GAAGF,CAAI,EAC1B,KAAK,CAACG,EAAGC,IAAMD,EAAE,OAASC,EAAE,MAAM,EAClC,IAAIC,GAAOA,EAAI,QAAQ,SAAU,EAAE,CAAC,EAGnCC,EAAQ,EACZ,GAAIL,IAASC,EACXI,EAAQL,EAAK,WAEb,MAAOA,EAAK,WAAWK,CAAK,IAAMJ,EAAK,WAAWI,CAAK,GACrDA,IAGJ,OAAON,EAAK,IAAIK,GAAOA,EAAI,QAAQJ,EAAK,MAAM,EAAGK,CAAK,EAAG,EAAE,CAAC,CAC9D,CAaO,SAASC,GAAaC,EAAiC,CAC5D,IAAMC,EAAS,SAAkB,YAAa,eAAgBD,CAAI,EAClE,GAAIC,EACF,OAAOC,EAAGD,CAAM,EACX,CACL,IAAME,EAASC,GAAc,EAC7B,OAAOC,GAAW,IAAI,IAAI,cAAeL,GAAQG,EAAO,IAAI,CAAC,EAC1D,KACCG,EAAIC,GAAWhB,GAAWiB,EAAY,MAAOD,CAAO,EACjD,IAAIE,GAAQA,EAAK,WAAY,CAChC,CAAC,EACDC,GAAW,IAAMC,CAAK,EACtBC,GAAe,CAAC,CAAC,EACjBC,EAAIN,GAAW,SAAS,YAAaA,EAAS,eAAgBP,CAAI,CAAC,CACrE,CACJ,CACF,CCIO,SAASc,GACd,CAAE,UAAAC,EAAW,UAAAC,EAAW,UAAAC,CAAU,EAC5B,CACN,IAAMC,EAASC,GAAc,EAC7B,GAAI,SAAS,WAAa,QACxB,OAGE,sBAAuB,UACzB,QAAQ,kBAAoB,SAG5BC,EAAU,OAAQ,cAAc,EAC7B,UAAU,IAAM,CACf,QAAQ,kBAAoB,MAC9B,CAAC,GAIL,IAAMC,EAAUC,GAAoC,gBAAgB,EAChE,OAAOD,GAAY,cACrBA,EAAQ,KAAOA,EAAQ,MAGzB,IAAME,EAAQC,GAAa,EACxB,KACCC,EAAIC,GAASA,EAAM,IAAIC,GAAQ,GAAG,IAAI,IAAIA,EAAMT,EAAO,IAAI,GAAG,CAAC,EAC/DU,EAAUC,GAAQT,EAAsB,SAAS,KAAM,OAAO,EAC3D,KACCU,EAAOC,GAAM,CAACA,EAAG,SAAW,CAACA,EAAG,OAAO,EACvCH,EAAUG,GAAM,CACd,GAAIA,EAAG,kBAAkB,QAAS,CAChC,IAAMC,EAAKD,EAAG,OAAO,QAAQ,GAAG,EAChC,GAAIC,GAAM,CAACA,EAAG,OAAQ,CACpB,IAAMC,EAAM,IAAI,IAAID,EAAG,IAAI,EAO3B,GAJAC,EAAI,OAAS,GACbA,EAAI,KAAO,GAITA,EAAI,WAAa,SAAS,UAC1BJ,EAAK,SAASI,EAAI,SAAS,CAAC,EAE5B,OAAAF,EAAG,eAAe,EACXG,EAAG,CACR,IAAK,IAAI,IAAIF,EAAG,IAAI,CACtB,CAAC,CAEL,CACF,CACA,OAAOG,EACT,CAAC,CACH,CACF,EACAC,GAAoB,CACtB,EAGIC,EAAOjB,EAAyB,OAAQ,UAAU,EACrD,KACCU,EAAOC,GAAMA,EAAG,QAAU,IAAI,EAC9BN,EAAIM,IAAO,CACT,IAAK,IAAI,IAAI,SAAS,IAAI,EAC1B,OAAQA,EAAG,KACb,EAAE,EACFK,GAAoB,CACtB,EAGFE,EAAMf,EAAOc,CAAI,EACd,KACCE,EAAqB,CAACC,EAAGC,IAAMD,EAAE,IAAI,OAASC,EAAE,IAAI,IAAI,EACxDhB,EAAI,CAAC,CAAE,IAAAQ,CAAI,IAAMA,CAAG,CACtB,EACG,UAAUjB,CAAS,EAGxB,IAAM0B,EAAY1B,EACf,KACC2B,EAAwB,UAAU,EAClCf,EAAUK,GAAOW,GAAQX,EAAI,IAAI,EAC9B,KACCY,GAAW,KACTC,GAAYb,CAAG,EACRE,GACR,CACH,CACF,EACAC,GAAM,CACR,EAGFb,EACG,KACCwB,GAAOL,CAAS,CAClB,EACG,UAAU,CAAC,CAAE,IAAAT,CAAI,IAAM,CACtB,QAAQ,UAAU,CAAC,EAAG,GAAI,GAAGA,GAAK,CACpC,CAAC,EAGL,IAAMe,EAAM,IAAI,UAChBN,EACG,KACCd,EAAUqB,GAAOA,EAAI,KAAK,CAAC,EAC3BxB,EAAIwB,GAAOD,EAAI,gBAAgBC,EAAK,WAAW,CAAC,CAClD,EACG,UAAUlC,CAAS,EAGxBA,EACG,KACCmC,GAAK,CAAC,CACR,EACG,UAAUC,GAAe,CACxB,QAAWC,IAAY,CAGrB,QACA,sBACA,oBACA,yBAGA,+BACA,gCACA,mCACA,+BACA,2BACA,2BACA,GAAGC,EAAQ,wBAAwB,EAC/B,CAAC,0BAA0B,EAC3B,CAAC,CACP,EAAG,CACD,IAAMC,EAAShC,GAAmB8B,CAAQ,EACpCG,EAASjC,GAAmB8B,EAAUD,CAAW,EAErD,OAAOG,GAAW,aAClB,OAAOC,GAAW,aAElBD,EAAO,YAAYC,CAAM,CAE7B,CACF,CAAC,EAGLxC,EACG,KACCmC,GAAK,CAAC,EACNzB,EAAI,IAAM+B,GAAoB,WAAW,CAAC,EAC1C5B,EAAUI,GAAMyB,EAAY,SAAUzB,CAAE,CAAC,EACzC0B,GAAU1B,GAAM,CACd,IAAM2B,EAASC,EAAE,QAAQ,EACzB,GAAI5B,EAAG,IAAK,CACV,QAAW6B,KAAQ7B,EAAG,kBAAkB,EACtC2B,EAAO,aAAaE,EAAM7B,EAAG,aAAa6B,CAAI,CAAE,EAClD,OAAA7B,EAAG,YAAY2B,CAAM,EAGd,IAAIG,EAAWC,GAAY,CAChCJ,EAAO,OAAS,IAAMI,EAAS,SAAS,CAC1C,CAAC,CAGH,KACE,QAAAJ,EAAO,YAAc3B,EAAG,YACxBA,EAAG,YAAY2B,CAAM,EACdK,CAEX,CAAC,CACH,EACG,UAAU,EAGf1B,EAAMf,EAAOc,CAAI,EACd,KACCU,GAAOhC,CAAS,CAClB,EACG,UAAU,CAAC,CAAE,IAAAkB,EAAK,OAAAgC,CAAO,IAAM,CAC1BhC,EAAI,MAAQ,CAACgC,EACfC,GAAgBjC,EAAI,IAAI,EAExB,OAAO,SAAS,GAAGgC,GAAA,YAAAA,EAAQ,IAAK,CAAC,CAErC,CAAC,EAGLhD,EACG,KACCkD,GAAU5C,CAAK,EACf6C,GAAa,GAAG,EAChBzB,EAAwB,QAAQ,CAClC,EACG,UAAU,CAAC,CAAE,OAAAsB,CAAO,IAAM,CACzB,QAAQ,aAAaA,EAAQ,EAAE,CACjC,CAAC,EAGL3B,EAAMf,EAAOc,CAAI,EACd,KACCgC,GAAY,EAAG,CAAC,EAChBvC,EAAO,CAAC,CAACU,EAAGC,CAAC,IAAMD,EAAE,IAAI,WAAaC,EAAE,IAAI,QAAQ,EACpDhB,EAAI,CAAC,CAAC,CAAE6C,CAAK,IAAMA,CAAK,CAC1B,EACG,UAAU,CAAC,CAAE,OAAAL,CAAO,IAAM,CACzB,OAAO,SAAS,GAAGA,GAAA,YAAAA,EAAQ,IAAK,CAAC,CACnC,CAAC,CACP,CCzSA,IAAAM,GAAuB,SCAvB,IAAAC,GAAuB,SAsChB,SAASC,GACdC,EAA2BC,EACD,CAC1B,IAAMC,EAAY,IAAI,OAAOF,EAAO,UAAW,KAAK,EAC9CG,EAAY,CAACC,EAAYC,EAAcC,IACpC,GAAGD,4BAA+BC,WAI3C,OAAQC,GAAkB,CACxBA,EAAQA,EACL,QAAQ,gBAAiB,GAAG,EAC5B,KAAK,EAGR,IAAMC,EAAQ,IAAI,OAAO,MAAMR,EAAO,cACpCO,EACG,QAAQ,uBAAwB,MAAM,EACtC,QAAQL,EAAW,GAAG,KACtB,KAAK,EAGV,OAAOO,IACLR,KACI,GAAAS,SAAWD,CAAK,EAChBA,GAED,QAAQD,EAAOL,CAAS,EACxB,QAAQ,8BAA+B,IAAI,CAClD,CACF,CC9BO,SAASQ,GAAiBC,EAAuB,CACtD,OAAOA,EACJ,MAAM,YAAY,EAChB,IAAI,CAACC,EAAOC,IAAUA,EAAQ,EAC3BD,EAAM,QAAQ,+BAAgC,IAAI,EAClDA,CACJ,EACC,KAAK,EAAE,EACT,QAAQ,kCAAmC,EAAE,EAC7C,KAAK,CACV,CCoCO,SAASE,GACdC,EAC+B,CAC/B,OAAOA,EAAQ,OAAS,CAC1B,CASO,SAASC,GACdD,EAC+B,CAC/B,OAAOA,EAAQ,OAAS,CAC1B,CASO,SAASE,GACdF,EACgC,CAChC,OAAOA,EAAQ,OAAS,CAC1B,CCvEA,SAASG,GAAiB,CAAE,OAAAC,EAAQ,KAAAC,CAAK,EAA6B,CAGhED,EAAO,KAAK,SAAW,GAAKA,EAAO,KAAK,KAAO,OACjDA,EAAO,KAAO,CACZE,GAAY,oBAAoB,CAClC,GAGEF,EAAO,YAAc,cACvBA,EAAO,UAAYE,GAAY,yBAAyB,GAQ1D,IAAMC,EAAyB,CAC7B,SANeD,GAAY,wBAAwB,EAClD,MAAM,SAAS,EACf,OAAO,OAAO,EAKf,YAAaE,EAAQ,gBAAgB,CACvC,EAGA,MAAO,CAAE,OAAAJ,EAAQ,KAAAC,EAAM,QAAAE,CAAQ,CACjC,CAkBO,SAASE,GACdC,EAAaC,EACC,CACd,IAAMP,EAASQ,GAAc,EACvBC,EAAS,IAAI,OAAOH,CAAG,EAGvBI,EAAM,IAAIC,EACVC,EAAMC,GAAYJ,EAAQ,CAAE,IAAAC,CAAI,CAAC,EACpC,KACCI,EAAIC,GAAW,CACb,GAAIC,GAAsBD,CAAO,EAC/B,QAAWE,KAAUF,EAAQ,KAAK,MAChC,QAAWG,KAAYD,EACrBC,EAAS,SAAW,GAAG,IAAI,IAAIA,EAAS,SAAUlB,EAAO,IAAI,IAEnE,OAAOe,CACT,CAAC,EACDI,GAAM,CACR,EAGF,OAAAC,GAAKb,CAAK,EACP,KACCO,EAAIO,IAAS,CACX,OACA,KAAMtB,GAAiBsB,CAAI,CAC7B,EAAwB,CAC1B,EACG,UAAUX,EAAI,KAAK,KAAKA,CAAG,CAAC,EAG1B,CAAE,IAAAA,EAAK,IAAAE,CAAI,CACpB,CCvEO,SAASU,GACd,CAAE,UAAAC,CAAU,EACN,CACN,IAAMC,EAASC,GAAc,EACvBC,EAAYC,GAChB,IAAI,IAAI,mBAAoBH,EAAO,IAAI,CACzC,EACG,KACCI,GAAW,IAAMC,CAAK,CACxB,EAGIC,EAAWJ,EACd,KACCK,EAAIC,GAAY,CACd,GAAM,CAAC,CAAEC,CAAO,EAAIT,EAAO,KAAK,MAAM,aAAa,EACnD,OAAOQ,EAAS,KAAK,CAAC,CAAE,QAAAE,EAAS,QAAAC,CAAQ,IACvCD,IAAYD,GAAWE,EAAQ,SAASF,CAAO,CAChD,GAAKD,EAAS,EACjB,CAAC,CACH,EAGFN,EACG,KACCK,EAAIC,GAAY,IAAI,IAAIA,EAAS,IAAIE,GAAW,CAC9C,GAAG,IAAI,IAAI,MAAMA,EAAQ,WAAYV,EAAO,IAAI,IAChDU,CACF,CAAC,CAAC,CAAC,EACHE,EAAUC,GAAQC,EAAsB,SAAS,KAAM,OAAO,EAC3D,KACCC,EAAOC,GAAM,CAACA,EAAG,SAAW,CAACA,EAAG,OAAO,EACvCC,GAAeX,CAAQ,EACvBM,EAAU,CAAC,CAACI,EAAIP,CAAO,IAAM,CAC3B,GAAIO,EAAG,kBAAkB,QAAS,CAChC,IAAME,EAAKF,EAAG,OAAO,QAAQ,GAAG,EAChC,GAAIE,GAAM,CAACA,EAAG,QAAUL,EAAK,IAAIK,EAAG,IAAI,EAAG,CACzC,IAAMC,EAAMD,EAAG,KAWf,MAAI,CAACF,EAAG,OAAO,QAAQ,aAAa,GAClBH,EAAK,IAAIM,CAAG,IACZV,EACPJ,GAEXW,EAAG,eAAe,EACXI,EAAGD,CAAG,EACf,CACF,CACA,OAAOd,CACT,CAAC,EACDO,EAAUO,GAAO,CACf,GAAM,CAAE,QAAAT,CAAQ,EAAIG,EAAK,IAAIM,CAAG,EAChC,OAAOE,GAAa,IAAI,IAAIF,CAAG,CAAC,EAC7B,KACCZ,EAAIe,GAAW,CAEb,IAAMC,EADWC,GAAY,EACP,KAAK,QAAQxB,EAAO,KAAM,EAAE,EAClD,OAAOsB,EAAQ,SAASC,EAAK,MAAM,GAAG,EAAE,EAAE,EACtC,IAAI,IAAI,MAAMb,KAAWa,IAAQvB,EAAO,IAAI,EAC5C,IAAI,IAAImB,CAAG,CACjB,CAAC,CACH,CACJ,CAAC,CACH,CACF,CACF,EACG,UAAUA,GAAOM,GAAYN,CAAG,CAAC,EAGtCO,EAAc,CAACxB,EAAWI,CAAQ,CAAC,EAChC,UAAU,CAAC,CAACE,EAAUC,CAAO,IAAM,CACpBkB,EAAW,mBAAmB,EACtC,YAAYC,GAAsBpB,EAAUC,CAAO,CAAC,CAC5D,CAAC,EAGHV,EAAU,KAAKa,EAAU,IAAMN,CAAQ,CAAC,EACrC,UAAUG,GAAW,CA5J1B,IAAAoB,EA+JM,IAAIC,EAAW,SAAS,aAAc,cAAc,EACpD,GAAIA,IAAa,KAAM,CACrB,IAAMC,IAASF,EAAA7B,EAAO,UAAP,YAAA6B,EAAgB,UAAW,SAC1CC,EAAW,CAACrB,EAAQ,QAAQ,SAASsB,CAAM,EAG3C,SAAS,aAAcD,EAAU,cAAc,CACjD,CAGA,GAAIA,EACF,QAAWE,KAAWC,GAAqB,UAAU,EACnDD,EAAQ,OAAS,EACvB,CAAC,CACL,CCtFO,SAASE,GACdC,EAAsB,CAAE,IAAAC,CAAI,EACH,CACzB,IAAMC,GAAK,+BAAU,YAAaC,GAG5B,CAAE,aAAAC,CAAa,EAAIC,GAAY,EACjCD,EAAa,IAAI,GAAG,GACtBE,GAAU,SAAU,EAAI,EAG1B,IAAMC,EAASN,EACZ,KACCO,EAAOC,EAAoB,EAC3BC,GAAK,CAAC,EACNC,EAAI,IAAMP,EAAa,IAAI,GAAG,GAAK,EAAE,CACvC,EAGFQ,GAAY,QAAQ,EACjB,KACCJ,EAAOK,GAAU,CAACA,CAAM,EACxBH,GAAK,CAAC,CACR,EACG,UAAU,IAAM,CACf,IAAMI,EAAM,IAAI,IAAI,SAAS,IAAI,EACjCA,EAAI,aAAa,OAAO,GAAG,EAC3B,QAAQ,aAAa,CAAC,EAAG,GAAI,GAAGA,GAAK,CACvC,CAAC,EAGLP,EAAO,UAAUQ,GAAS,CACpBA,IACFf,EAAG,MAAQe,EACXf,EAAG,MAAM,EAEb,CAAC,EAGD,IAAMgB,EAASC,GAAkBjB,CAAE,EAC7BkB,EAASC,EACbC,EAAUpB,EAAI,OAAO,EACrBoB,EAAUpB,EAAI,OAAO,EAAE,KAAKqB,GAAM,CAAC,CAAC,EACpCd,CACF,EACG,KACCI,EAAI,IAAMT,EAAGF,EAAG,KAAK,CAAC,EACtBsB,EAAU,EAAE,EACZC,EAAqB,CACvB,EAGF,OAAOC,EAAc,CAACN,EAAQF,CAAM,CAAC,EAClC,KACCL,EAAI,CAAC,CAACI,EAAOU,CAAK,KAAO,CAAE,MAAAV,EAAO,MAAAU,CAAM,EAAE,EAC1CC,EAAY,CAAC,CACf,CACJ,CAUO,SAASC,GACd3B,EAAsB,CAAE,IAAA4B,EAAK,IAAA3B,CAAI,EACqB,CACtD,IAAM4B,EAAQ,IAAIC,EACZC,EAAQF,EAAM,KAAKG,GAAS,CAAC,CAAC,EAGpC,OAAAH,EACG,KACCI,EAAwB,OAAO,EAC/BtB,EAAI,CAAC,CAAE,MAAAI,CAAM,KAA2B,CACtC,OACA,KAAMA,CACR,EAAE,CACJ,EACG,UAAUa,EAAI,KAAK,KAAKA,CAAG,CAAC,EAGjCC,EACG,KACCI,EAAwB,OAAO,CACjC,EACG,UAAU,CAAC,CAAE,MAAAR,CAAM,IAAM,CACpBA,GACFnB,GAAU,SAAUmB,CAAK,EACzBzB,EAAG,YAAc,IAEjBA,EAAG,YAAckC,GAAY,oBAAoB,CAErD,CAAC,EAGLd,EAAUpB,EAAG,KAAO,OAAO,EACxB,KACCmC,GAAUJ,CAAK,CACjB,EACG,UAAU,IAAM/B,EAAG,MAAM,CAAC,EAGxBD,GAAiBC,EAAI,CAAE,IAAA4B,EAAK,IAAA3B,CAAI,CAAC,EACrC,KACCmC,EAAIC,GAASR,EAAM,KAAKQ,CAAK,CAAC,EAC9BC,EAAS,IAAMT,EAAM,SAAS,CAAC,EAC/BlB,EAAI0B,GAAUE,EAAA,CAAE,IAAKvC,GAAOqC,EAAQ,EACpCG,GAAM,CACR,CACJ,CCrHO,SAASC,GACdC,EAAiB,CAAE,IAAAC,CAAI,EAAiB,CAAE,OAAAC,CAAO,EACZ,CACrC,IAAMC,EAAQ,IAAIC,EACZC,EAAYC,GAAqBN,EAAG,aAAc,EACrD,KACCO,EAAO,OAAO,CAChB,EAGIC,EAAOC,EAAW,wBAAyBT,CAAE,EAC7CU,EAAOD,EAAW,uBAAwBT,CAAE,EAG5CW,EAASV,EACZ,KACCM,EAAOK,EAAoB,EAC3BC,GAAK,CAAC,CACR,EAGF,OAAAV,EACG,KACCW,GAAeZ,CAAM,EACrBa,GAAUJ,CAAM,CAClB,EACG,UAAU,CAAC,CAAC,CAAE,MAAAK,CAAM,EAAG,CAAE,MAAAC,CAAM,CAAC,IAAM,CACrC,GAAIA,EACF,OAAQD,EAAM,OAAQ,CAGpB,IAAK,GACHR,EAAK,YAAcU,GAAY,oBAAoB,EACnD,MAGF,IAAK,GACHV,EAAK,YAAcU,GAAY,mBAAmB,EAClD,MAGF,QACEV,EAAK,YAAcU,GACjB,sBACAC,GAAMH,EAAM,MAAM,CACpB,CACJ,MAEAR,EAAK,YAAcU,GAAY,2BAA2B,CAE9D,CAAC,EAGLf,EACG,KACCiB,EAAI,IAAMV,EAAK,UAAY,EAAE,EAC7BW,EAAU,CAAC,CAAE,MAAAL,CAAM,IAAMM,EACvBC,EAAG,GAAGP,EAAM,MAAM,EAAG,EAAE,CAAC,EACxBO,EAAG,GAAGP,EAAM,MAAM,EAAE,CAAC,EAClB,KACCQ,GAAY,CAAC,EACbC,GAAQpB,CAAS,EACjBgB,EAAU,CAAC,CAACK,CAAK,IAAMA,CAAK,CAC9B,CACJ,CAAC,CACH,EACG,UAAUC,GAAUjB,EAAK,YACxBkB,GAAuBD,CAAM,CAC/B,CAAC,EAGW1B,EACb,KACCM,EAAOsB,EAAqB,EAC5BC,EAAI,CAAC,CAAE,KAAAC,CAAK,IAAMA,CAAI,CACxB,EAIC,KACCX,EAAIY,GAAS7B,EAAM,KAAK6B,CAAK,CAAC,EAC9BC,EAAS,IAAM9B,EAAM,SAAS,CAAC,EAC/B2B,EAAIE,GAAUE,EAAA,CAAE,IAAKlC,GAAOgC,EAAQ,CACtC,CACJ,CC1FO,SAASG,GACdC,EAAkB,CAAE,OAAAC,CAAO,EACF,CACzB,OAAOA,EACJ,KACCC,EAAI,CAAC,CAAE,MAAAC,CAAM,IAAM,CACjB,IAAMC,EAAMC,GAAY,EACxB,OAAAD,EAAI,KAAO,GACXA,EAAI,aAAa,OAAO,GAAG,EAC3BA,EAAI,aAAa,IAAI,IAAKD,CAAK,EACxB,CAAE,IAAAC,CAAI,CACf,CAAC,CACH,CACJ,CAUO,SAASE,GACdC,EAAuBC,EACa,CACpC,IAAMC,EAAQ,IAAIC,EAClB,OAAAD,EAAM,UAAU,CAAC,CAAE,IAAAL,CAAI,IAAM,CAC3BG,EAAG,aAAa,sBAAuBA,EAAG,IAAI,EAC9CA,EAAG,KAAO,GAAGH,GACf,CAAC,EAGDO,EAAUJ,EAAI,OAAO,EAClB,UAAUK,GAAMA,EAAG,eAAe,CAAC,EAG/Bb,GAAiBQ,EAAIC,CAAO,EAChC,KACCK,EAAIC,GAASL,EAAM,KAAKK,CAAK,CAAC,EAC9BC,EAAS,IAAMN,EAAM,SAAS,CAAC,EAC/BP,EAAIY,GAAUE,EAAA,CAAE,IAAKT,GAAOO,EAAQ,CACtC,CACJ,CCtCO,SAASG,GACdC,EAAiB,CAAE,IAAAC,CAAI,EAAiB,CAAE,UAAAC,CAAU,EACd,CACtC,IAAMC,EAAQ,IAAIC,EAGZC,EAASC,GAAoB,cAAc,EAC3CC,EAASC,EACbC,EAAUJ,EAAO,SAAS,EAC1BI,EAAUJ,EAAO,OAAO,CAC1B,EACG,KACCK,GAAUC,EAAc,EACxBC,EAAI,IAAMP,EAAM,KAAK,EACrBQ,EAAqB,CACvB,EAGF,OAAAV,EACG,KACCW,GAAkBP,CAAM,EACxBK,EAAI,CAAC,CAAC,CAAE,YAAAG,CAAY,EAAGC,CAAK,IAAM,CAChC,IAAMC,EAAQD,EAAM,MAAM,UAAU,EACpC,IAAID,GAAA,YAAAA,EAAa,SAAUE,EAAMA,EAAM,OAAS,GAAI,CAClD,IAAMC,EAAOH,EAAYA,EAAY,OAAS,GAC1CG,EAAK,WAAWD,EAAMA,EAAM,OAAS,EAAE,IACzCA,EAAMA,EAAM,OAAS,GAAKC,EAC9B,MACED,EAAM,OAAS,EAEjB,OAAOA,CACT,CAAC,CACH,EACG,UAAUA,GAASjB,EAAG,UAAYiB,EAChC,KAAK,EAAE,EACP,QAAQ,MAAO,QAAQ,CAC1B,EAGJf,EACG,KACCiB,EAAO,CAAC,CAAE,KAAAC,CAAK,IAAMA,IAAS,QAAQ,CACxC,EACG,UAAUC,GAAO,CAChB,OAAQA,EAAI,KAAM,CAGhB,IAAK,aAEDrB,EAAG,UAAU,QACbK,EAAM,iBAAmBA,EAAM,MAAM,SAErCA,EAAM,MAAQL,EAAG,WACnB,KACJ,CACF,CAAC,EAGWC,EACb,KACCkB,EAAOG,EAAqB,EAC5BV,EAAI,CAAC,CAAE,KAAAW,CAAK,IAAMA,CAAI,CACxB,EAIC,KACCC,EAAIC,GAAStB,EAAM,KAAKsB,CAAK,CAAC,EAC9BC,EAAS,IAAMvB,EAAM,SAAS,CAAC,EAC/BS,EAAI,KAAO,CAAE,IAAKZ,CAAG,EAAE,CACzB,CACJ,CC9CO,SAAS2B,GACdC,EAAiB,CAAE,OAAAC,EAAQ,UAAAC,CAAU,EACN,CAC/B,IAAMC,EAASC,GAAc,EAC7B,GAAI,CACF,IAAMC,GAAM,+BAAU,SAAUF,EAAO,OACjCG,EAASC,GAAkBF,EAAKJ,CAAM,EAGtCO,EAASC,GAAoB,eAAgBT,CAAE,EAC/CU,EAASD,GAAoB,gBAAiBT,CAAE,EAGhD,CAAE,IAAAW,EAAK,IAAAC,CAAI,EAAIN,EACrBK,EACG,KACCE,EAAOC,EAAoB,EAC3BC,GAAOH,EAAI,KAAKC,EAAOG,EAAoB,CAAC,CAAC,EAC7CC,GAAK,CAAC,CACR,EACG,UAAUN,EAAI,KAAK,KAAKA,CAAG,CAAC,EAGjCT,EACG,KACCW,EAAO,CAAC,CAAE,KAAAK,CAAK,IAAMA,IAAS,QAAQ,CACxC,EACG,UAAUC,GAAO,CAChB,IAAMC,EAASC,GAAiB,EAChC,OAAQF,EAAI,KAAM,CAGhB,IAAK,QACH,GAAIC,IAAWZ,EAAO,CACpB,IAAMc,EAAU,IAAI,IACpB,QAAWC,KAAUC,EACnB,sBAAuBd,CACzB,EAAG,CACD,IAAMe,EAAUF,EAAO,kBACvBD,EAAQ,IAAIC,EAAQ,WAClBE,EAAQ,aAAa,eAAe,CACtC,CAAC,CACH,CAGA,GAAIH,EAAQ,KAAM,CAChB,GAAM,CAAC,CAACI,CAAI,CAAC,EAAI,CAAC,GAAGJ,CAAO,EAAE,KAAK,CAAC,CAAC,CAAEK,CAAC,EAAG,CAAC,CAAEC,CAAC,IAAMA,EAAID,CAAC,EAC1DD,EAAK,MAAM,CACb,CAGAP,EAAI,MAAM,CACZ,CACA,MAGF,IAAK,SACL,IAAK,MACHU,GAAU,SAAU,EAAK,EACzBrB,EAAM,KAAK,EACX,MAGF,IAAK,UACL,IAAK,YACH,GAAI,OAAOY,GAAW,YACpBZ,EAAM,MAAM,MACP,CACL,IAAMsB,EAAM,CAACtB,EAAO,GAAGgB,EACrB,wDACAd,CACF,CAAC,EACKqB,EAAI,KAAK,IAAI,GACjB,KAAK,IAAI,EAAGD,EAAI,QAAQV,CAAM,CAAC,EAAIU,EAAI,QACrCX,EAAI,OAAS,UAAY,GAAK,IAE9BW,EAAI,MAAM,EACdA,EAAIC,GAAG,MAAM,CACf,CAGAZ,EAAI,MAAM,EACV,MAGF,QACMX,IAAUa,GAAiB,GAC7Bb,EAAM,MAAM,CAClB,CACF,CAAC,EAGLN,EACG,KACCW,EAAO,CAAC,CAAE,KAAAK,CAAK,IAAMA,IAAS,QAAQ,CACxC,EACG,UAAUC,GAAO,CAChB,OAAQA,EAAI,KAAM,CAGhB,IAAK,IACL,IAAK,IACL,IAAK,IACHX,EAAM,MAAM,EACZA,EAAM,OAAO,EAGbW,EAAI,MAAM,EACV,KACJ,CACF,CAAC,EAGL,IAAMa,EAAUC,GAAiBzB,EAAOF,CAAM,EACxC4B,EAAUC,GAAkBzB,EAAQJ,EAAQ,CAAE,OAAA0B,CAAO,CAAC,EAC5D,OAAOI,EAAMJ,EAAQE,CAAO,EACzB,KACCG,GAGE,GAAGC,GAAqB,eAAgBtC,CAAE,EACvC,IAAIuC,GAASC,GAAiBD,EAAO,CAAE,OAAAP,CAAO,CAAC,CAAC,EAGnD,GAAGM,GAAqB,iBAAkBtC,CAAE,EACzC,IAAIuC,GAASE,GAAmBF,EAAOjC,EAAQ,CAAE,UAAAJ,CAAU,CAAC,CAAC,CAClE,CACF,CAGJ,OAASwC,EAAP,CACA,OAAA1C,EAAG,OAAS,GACL2C,EACT,CACF,CCtKO,SAASC,GACdC,EAAiB,CAAE,OAAAC,EAAQ,UAAAC,CAAU,EACG,CACxC,OAAOC,EAAc,CACnBF,EACAC,EACG,KACCE,EAAUC,GAAY,CAAC,EACvBC,EAAOC,GAAO,CAAC,CAACA,EAAI,aAAa,IAAI,GAAG,CAAC,CAC3C,CACJ,CAAC,EACE,KACCC,EAAI,CAAC,CAACC,EAAOF,CAAG,IAAMG,GAAuBD,EAAM,OAAQ,EAAI,EAC7DF,EAAI,aAAa,IAAI,GAAG,CAC1B,CAAC,EACDC,EAAIG,GAAM,CA1FhB,IAAAC,EA2FQ,IAAMC,EAAQ,IAAI,IAGZC,EAAK,SAAS,mBAAmBd,EAAI,WAAW,SAAS,EAC/D,QAASe,EAAOD,EAAG,SAAS,EAAGC,EAAMA,EAAOD,EAAG,SAAS,EACtD,IAAIF,EAAAG,EAAK,gBAAL,MAAAH,EAAoB,aAAc,CACpC,IAAMI,EAAWD,EAAK,YAChBE,EAAWN,EAAGK,CAAQ,EACxBC,EAAS,OAASD,EAAS,QAC7BH,EAAM,IAAIE,EAAmBE,CAAQ,CACzC,CAIF,OAAW,CAACF,EAAMG,CAAI,IAAKL,EAAO,CAChC,GAAM,CAAE,WAAAM,CAAW,EAAIC,EAAE,OAAQ,KAAMF,CAAI,EAC3CH,EAAK,YAAY,GAAG,MAAM,KAAKI,CAAU,CAAC,CAC5C,CAGA,MAAO,CAAE,IAAKnB,EAAI,MAAAa,CAAM,CAC1B,CAAC,CACH,CACJ,CCbO,SAASQ,GACdC,EAAiB,CAAE,UAAAC,EAAW,MAAAC,CAAM,EACf,CACrB,IAAMC,EAASH,EAAG,cACZI,EACJD,EAAO,UACPA,EAAO,cAAe,UAGxB,OAAOE,EAAc,CAACH,EAAOD,CAAS,CAAC,EACpC,KACCK,EAAI,CAAC,CAAC,CAAE,OAAAC,EAAQ,OAAAC,CAAO,EAAG,CAAE,OAAQ,CAAE,EAAAC,CAAE,CAAE,CAAC,KACzCD,EAASA,EACL,KAAK,IAAIJ,EAAQ,KAAK,IAAI,EAAGK,EAAIF,CAAM,CAAC,EACxCH,EACG,CACL,OAAAI,EACA,OAAQC,GAAKF,EAASH,CACxB,EACD,EACDM,EAAqB,CAACC,EAAGC,IACvBD,EAAE,SAAWC,EAAE,QACfD,EAAE,SAAWC,EAAE,MAChB,CACH,CACJ,CAuBO,SAASC,GACdb,EAAiBc,EACe,CADf,IAAAC,EAAAD,EAAE,SAAAE,CAtJrB,EAsJmBD,EAAcE,EAAAC,GAAdH,EAAc,CAAZ,YAEnB,IAAMI,EAAQC,EAAW,0BAA2BpB,CAAE,EAChD,CAAE,EAAAS,CAAE,EAAIY,GAAiBF,CAAK,EACpC,OAAOG,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EAClB,OAAAD,EACG,KACCE,GAAU,EAAGC,EAAuB,EACpCC,GAAeX,CAAO,CACxB,EACG,UAAU,CAGT,KAAK,CAAC,CAAE,OAAAR,CAAO,EAAG,CAAE,OAAQD,CAAO,CAAC,EAAG,CACrCY,EAAM,MAAM,OAAS,GAAGX,EAAS,EAAIC,MACrCT,EAAG,MAAM,IAAY,GAAGO,KAC1B,EAGA,UAAW,CACTY,EAAM,MAAM,OAAS,GACrBnB,EAAG,MAAM,IAAY,EACvB,CACF,CAAC,EAGLuB,EACG,KACCK,GAAUF,EAAuB,EACjCG,GAAK,CAAC,CACR,EACG,UAAU,IAAM,CACf,QAAWC,KAAQC,EAAY,8BAA+B/B,CAAE,EAAG,CACjE,IAAMgC,EAAYC,GAAoBH,CAAI,EAC1C,GAAI,OAAOE,GAAc,YAAa,CACpC,IAAMzB,EAASuB,EAAK,UAAYE,EAAU,UACpC,CAAE,OAAAxB,CAAO,EAAI0B,GAAeF,CAAS,EAC3CA,EAAU,SAAS,CACjB,IAAKzB,EAASC,EAAS,CACzB,CAAC,CACH,CACF,CACF,CAAC,EAGET,GAAaC,EAAIiB,CAAO,EAC5B,KACCkB,EAAIC,GAASb,EAAM,KAAKa,CAAK,CAAC,EAC9BC,EAAS,IAAMd,EAAM,SAAS,CAAC,EAC/BjB,EAAI8B,GAAUE,EAAA,CAAE,IAAKtC,GAAOoC,EAAQ,CACtC,CACJ,CAAC,CACH,CChJO,SAASG,GACdC,EAAcC,EACW,CACzB,GAAI,OAAOA,GAAS,YAAa,CAC/B,IAAMC,EAAM,gCAAgCF,KAAQC,IACpD,OAAOE,GAGLC,GAAqB,GAAGF,mBAAqB,EAC1C,KACCG,GAAW,IAAMC,CAAK,EACtBC,EAAIC,IAAY,CACd,QAASA,EAAQ,QACnB,EAAE,EACFC,GAAe,CAAC,CAAC,CACnB,EAGFL,GAAkBF,CAAG,EAClB,KACCG,GAAW,IAAMC,CAAK,EACtBC,EAAIG,IAAS,CACX,MAAOA,EAAK,iBACZ,MAAOA,EAAK,WACd,EAAE,EACFD,GAAe,CAAC,CAAC,CACnB,CACJ,EACG,KACCF,EAAI,CAAC,CAACC,EAASE,CAAI,IAAOC,IAAA,GAAKH,GAAYE,EAAO,CACpD,CAGJ,KAAO,CACL,IAAMR,EAAM,gCAAgCF,IAC5C,OAAOI,GAAkBF,CAAG,EACzB,KACCK,EAAIG,IAAS,CACX,aAAcA,EAAK,YACrB,EAAE,EACFD,GAAe,CAAC,CAAC,CACnB,CACJ,CACF,CCvDO,SAASG,GACdC,EAAcC,EACW,CACzB,IAAMC,EAAM,WAAWF,qBAAwB,mBAAmBC,CAAO,IACzE,OAAOE,GAA2BD,CAAG,EAClC,KACCE,GAAW,IAAMC,CAAK,EACtBC,EAAI,CAAC,CAAE,WAAAC,EAAY,YAAAC,CAAY,KAAO,CACpC,MAAOD,EACP,MAAOC,CACT,EAAE,EACFC,GAAe,CAAC,CAAC,CACnB,CACJ,CCOO,SAASC,GACdC,EACyB,CAGzB,IAAIC,EAAQD,EAAI,MAAM,qCAAqC,EAC3D,GAAIC,EAAO,CACT,GAAM,CAAC,CAAEC,EAAMC,CAAI,EAAIF,EACvB,OAAOG,GAA2BF,EAAMC,CAAI,CAC9C,CAIA,GADAF,EAAQD,EAAI,MAAM,oCAAoC,EAClDC,EAAO,CACT,GAAM,CAAC,CAAEI,EAAMC,CAAI,EAAIL,EACvB,OAAOM,GAA2BF,EAAMC,CAAI,CAC9C,CAGA,OAAOE,CACT,CCpBA,IAAIC,GAgBG,SAASC,GACdC,EACoB,CACpB,OAAOF,QAAWG,EAAM,IAAM,CAC5B,IAAMC,EAAS,SAAsB,WAAY,cAAc,EAC/D,GAAIA,EACF,OAAOC,EAAGD,CAAM,EAKhB,GADYE,GAAqB,SAAS,EAClC,OAAQ,CACd,IAAMC,EAAU,SAA0B,WAAW,EACrD,GAAI,EAAEA,GAAWA,EAAQ,QACvB,OAAOC,CACX,CAGA,OAAOC,GAAiBP,EAAG,IAAI,EAC5B,KACCQ,EAAIC,GAAS,SAAS,WAAYA,EAAO,cAAc,CAAC,CAC1D,CAEN,CAAC,EACE,KACCC,GAAW,IAAMJ,CAAK,EACtBK,EAAOF,GAAS,OAAO,KAAKA,CAAK,EAAE,OAAS,CAAC,EAC7CG,EAAIH,IAAU,CAAE,MAAAA,CAAM,EAAE,EACxBI,EAAY,CAAC,CACf,EACJ,CASO,SAASC,GACdd,EAC+B,CAC/B,IAAMe,EAAQC,EAAW,uBAAwBhB,CAAE,EACnD,OAAOC,EAAM,IAAM,CACjB,IAAMgB,EAAQ,IAAIC,EAClB,OAAAD,EAAM,UAAU,CAAC,CAAE,MAAAR,CAAM,IAAM,CAC7BM,EAAM,YAAYI,GAAkBV,CAAK,CAAC,EAC1CM,EAAM,UAAU,IAAI,+BAA+B,CACrD,CAAC,EAGMhB,GAAYC,CAAE,EAClB,KACCQ,EAAIY,GAASH,EAAM,KAAKG,CAAK,CAAC,EAC9BC,EAAS,IAAMJ,EAAM,SAAS,CAAC,EAC/BL,EAAIQ,GAAUE,EAAA,CAAE,IAAKtB,GAAOoB,EAAQ,CACtC,CACJ,CAAC,CACH,CCtDO,SAASG,GACdC,EAAiB,CAAE,UAAAC,EAAW,QAAAC,CAAQ,EACpB,CAClB,OAAOC,GAAiB,SAAS,IAAI,EAClC,KACCC,EAAU,IAAMC,GAAgBL,EAAI,CAAE,QAAAE,EAAS,UAAAD,CAAU,CAAC,CAAC,EAC3DK,EAAI,CAAC,CAAE,OAAQ,CAAE,EAAAC,CAAE,CAAE,KACZ,CACL,OAAQA,GAAK,EACf,EACD,EACDC,EAAwB,QAAQ,CAClC,CACJ,CAaO,SAASC,GACdT,EAAiBU,EACY,CAC7B,OAAOC,EAAM,IAAM,CACjB,IAAMC,EAAQ,IAAIC,EAClB,OAAAD,EAAM,UAAU,CAGd,KAAK,CAAE,OAAAE,CAAO,EAAG,CACfd,EAAG,OAASc,CACd,EAGA,UAAW,CACTd,EAAG,OAAS,EACd,CACF,CAAC,GAICe,EAAQ,wBAAwB,EAC5BC,EAAG,CAAE,OAAQ,EAAM,CAAC,EACpBjB,GAAUC,EAAIU,CAAO,GAExB,KACCO,EAAIC,GAASN,EAAM,KAAKM,CAAK,CAAC,EAC9BC,EAAS,IAAMP,EAAM,SAAS,CAAC,EAC/BN,EAAIY,GAAUE,EAAA,CAAE,IAAKpB,GAAOkB,EAAQ,CACtC,CACJ,CAAC,CACH,CCpBO,SAASG,GACdC,EAAiB,CAAE,UAAAC,EAAW,QAAAC,CAAQ,EACT,CAC7B,IAAMC,EAAQ,IAAI,IAGZC,EAAUC,EAA+B,cAAeL,CAAE,EAChE,QAAWM,KAAUF,EAAS,CAC5B,IAAMG,EAAK,mBAAmBD,EAAO,KAAK,UAAU,CAAC,CAAC,EAChDE,EAASC,GAAmB,QAAQF,KAAM,EAC5C,OAAOC,GAAW,aACpBL,EAAM,IAAIG,EAAQE,CAAM,CAC5B,CAGA,IAAME,EAAUR,EACb,KACCS,EAAwB,QAAQ,EAChCC,EAAI,CAAC,CAAE,OAAAC,CAAO,IAAM,CAClB,IAAMC,EAAOC,GAAoB,MAAM,EACjCC,EAAOC,EAAW,wBAAyBH,CAAI,EACrD,OAAOD,EAAS,IACdG,EAAK,UACLF,EAAK,UAET,CAAC,EACDI,GAAM,CACR,EAgFF,OA7EmBC,GAAiB,SAAS,IAAI,EAC9C,KACCR,EAAwB,QAAQ,EAGhCS,EAAUC,GAAQC,EAAM,IAAM,CAC5B,IAAIC,EAA4B,CAAC,EACjC,OAAOC,EAAG,CAAC,GAAGrB,CAAK,EAAE,OAAO,CAACsB,EAAO,CAACnB,EAAQE,CAAM,IAAM,CACvD,KAAOe,EAAK,QACGpB,EAAM,IAAIoB,EAAKA,EAAK,OAAS,EAAE,EACnC,SAAWf,EAAO,SACzBe,EAAK,IAAI,EAOb,IAAIG,EAASlB,EAAO,UACpB,KAAO,CAACkB,GAAUlB,EAAO,eACvBA,EAASA,EAAO,cAChBkB,EAASlB,EAAO,UAIlB,OAAOiB,EAAM,IACX,CAAC,GAAGF,EAAO,CAAC,GAAGA,EAAMjB,CAAM,CAAC,EAAE,QAAQ,EACtCoB,CACF,CACF,EAAG,IAAI,GAAkC,CAAC,CAC5C,CAAC,EACE,KAGCd,EAAIa,GAAS,IAAI,IAAI,CAAC,GAAGA,CAAK,EAAE,KAAK,CAAC,CAAC,CAAEE,CAAC,EAAG,CAAC,CAAEC,CAAC,IAAMD,EAAIC,CAAC,CAAC,CAAC,EAC9DC,GAAkBnB,CAAO,EAGzBU,EAAU,CAAC,CAACK,EAAOK,CAAM,IAAM7B,EAC5B,KACC8B,GAAK,CAAC,CAACC,EAAMC,CAAI,EAAG,CAAE,OAAQ,CAAE,EAAAC,CAAE,EAAG,KAAAC,CAAK,IAAM,CAC9C,IAAMC,EAAOF,EAAIC,EAAK,QAAU,KAAK,MAAMd,EAAK,MAAM,EAGtD,KAAOY,EAAK,QAAQ,CAClB,GAAM,CAAC,CAAEP,CAAM,EAAIO,EAAK,GACxB,GAAIP,EAASI,EAASI,GAAKE,EACzBJ,EAAO,CAAC,GAAGA,EAAMC,EAAK,MAAM,CAAE,MAE9B,MAEJ,CAGA,KAAOD,EAAK,QAAQ,CAClB,GAAM,CAAC,CAAEN,CAAM,EAAIM,EAAKA,EAAK,OAAS,GACtC,GAAIN,EAASI,GAAUI,GAAK,CAACE,EAC3BH,EAAO,CAACD,EAAK,IAAI,EAAI,GAAGC,CAAI,MAE5B,MAEJ,CAGA,MAAO,CAACD,EAAMC,CAAI,CACpB,EAAG,CAAC,CAAC,EAAG,CAAC,GAAGR,CAAK,CAAC,CAAC,EACnBY,EAAqB,CAACV,EAAGC,IACvBD,EAAE,KAAOC,EAAE,IACXD,EAAE,KAAOC,EAAE,EACZ,CACH,CACF,CACF,CACF,CACF,EAIC,KACChB,EAAI,CAAC,CAACoB,EAAMC,CAAI,KAAO,CACrB,KAAMD,EAAK,IAAI,CAAC,CAACT,CAAI,IAAMA,CAAI,EAC/B,KAAMU,EAAK,IAAI,CAAC,CAACV,CAAI,IAAMA,CAAI,CACjC,EAAE,EAGFe,EAAU,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,CAAE,CAAC,EAChCC,GAAY,EAAG,CAAC,EAChB3B,EAAI,CAAC,CAAC,EAAGgB,CAAC,IAGJ,EAAE,KAAK,OAASA,EAAE,KAAK,OAClB,CACL,KAAMA,EAAE,KAAK,MAAM,KAAK,IAAI,EAAG,EAAE,KAAK,OAAS,CAAC,EAAGA,EAAE,KAAK,MAAM,EAChE,KAAM,CAAC,CACT,EAIO,CACL,KAAMA,EAAE,KAAK,MAAM,EAAE,EACrB,KAAMA,EAAE,KAAK,MAAM,EAAGA,EAAE,KAAK,OAAS,EAAE,KAAK,MAAM,CACrD,CAEH,CACH,CACJ,CAYO,SAASY,GACdxC,EAAiB,CAAE,UAAAC,EAAW,QAAAC,EAAS,QAAAuC,CAAQ,EACP,CACxC,OAAOnB,EAAM,IAAM,CACjB,IAAMoB,EAAQ,IAAIC,EACZC,EAAQF,EAAM,KAAKG,GAAS,CAAC,CAAC,EAoBpC,GAnBAH,EAAM,UAAU,CAAC,CAAE,KAAAV,EAAM,KAAAC,CAAK,IAAM,CAGlC,OAAW,CAAC3B,CAAM,IAAK2B,EACrB3B,EAAO,UAAU,OAAO,sBAAsB,EAC9CA,EAAO,UAAU,OAAO,sBAAsB,EAIhD,OAAW,CAACmB,EAAO,CAACnB,CAAM,CAAC,IAAK0B,EAAK,QAAQ,EAC3C1B,EAAO,UAAU,IAAI,sBAAsB,EAC3CA,EAAO,UAAU,OACf,uBACAmB,IAAUO,EAAK,OAAS,CAC1B,CAEJ,CAAC,EAGGc,EAAQ,YAAY,EAAG,CAGzB,IAAMC,EAAUC,EACd/C,EAAU,KAAKgD,GAAa,CAAC,EAAGrC,EAAI,IAAG,EAAY,CAAC,EACpDX,EAAU,KAAKgD,GAAa,GAAG,EAAGrC,EAAI,IAAM,QAAiB,CAAC,CAChE,EAGA8B,EACG,KACCQ,EAAO,CAAC,CAAE,KAAAlB,CAAK,IAAMA,EAAK,OAAS,CAAC,EACpCmB,GAAeJ,CAAO,CACxB,EACG,UAAU,CAAC,CAAC,CAAE,KAAAf,CAAK,EAAGoB,CAAQ,IAAM,CACnC,GAAM,CAAC9C,CAAM,EAAI0B,EAAKA,EAAK,OAAS,GACpC,GAAI1B,EAAO,aAAc,CAGvB,IAAM+C,EAAYC,GAAoBhD,CAAM,EAC5C,GAAI,OAAO+C,GAAc,YAAa,CACpC,IAAM3B,EAASpB,EAAO,UAAY+C,EAAU,UACtC,CAAE,OAAAxC,CAAO,EAAI0C,GAAeF,CAAS,EAC3CA,EAAU,SAAS,CACjB,IAAK3B,EAASb,EAAS,EACvB,SAAAuC,CACF,CAAC,CACH,CACF,CACF,CAAC,CACP,CAGA,OAAIN,EAAQ,qBAAqB,GAC/B7C,EACG,KACCuD,GAAUZ,CAAK,EACfjC,EAAwB,QAAQ,EAChCsC,GAAa,GAAG,EAChBQ,GAAK,CAAC,EACND,GAAUf,EAAQ,KAAKgB,GAAK,CAAC,CAAC,CAAC,EAC/BC,GAAO,CAAE,MAAO,GAAI,CAAC,EACrBP,GAAeT,CAAK,CACtB,EACG,UAAU,CAAC,CAAC,CAAE,CAAE,KAAAV,CAAK,CAAC,IAAM,CAC3B,IAAM2B,EAAMC,GAAY,EAGlBtD,EAAS0B,EAAKA,EAAK,OAAS,GAClC,GAAI1B,GAAUA,EAAO,OAAQ,CAC3B,GAAM,CAACuD,CAAM,EAAIvD,EACX,CAAE,KAAAwD,CAAK,EAAI,IAAI,IAAID,EAAO,IAAI,EAChCF,EAAI,OAASG,IACfH,EAAI,KAAOG,EACX,QAAQ,aAAa,CAAC,EAAG,GAAI,GAAGH,GAAK,EAIzC,MACEA,EAAI,KAAO,GACX,QAAQ,aAAa,CAAC,EAAG,GAAI,GAAGA,GAAK,CAEzC,CAAC,EAGA5D,GAAqBC,EAAI,CAAE,UAAAC,EAAW,QAAAC,CAAQ,CAAC,EACnD,KACC6D,EAAIC,GAAStB,EAAM,KAAKsB,CAAK,CAAC,EAC9BC,EAAS,IAAMvB,EAAM,SAAS,CAAC,EAC/B9B,EAAIoD,GAAUE,EAAA,CAAE,IAAKlE,GAAOgE,EAAQ,CACtC,CACJ,CAAC,CACH,CCpRO,SAASG,GACdC,EAAkB,CAAE,UAAAC,EAAW,MAAAC,EAAO,QAAAC,CAAQ,EACvB,CAGvB,IAAMC,EAAaH,EAChB,KACCI,EAAI,CAAC,CAAE,OAAQ,CAAE,EAAAC,CAAE,CAAE,IAAMA,CAAC,EAC5BC,GAAY,EAAG,CAAC,EAChBF,EAAI,CAAC,CAACG,EAAGC,CAAC,IAAMD,EAAIC,GAAKA,EAAI,CAAC,EAC9BC,EAAqB,CACvB,EAGIC,EAAUT,EACb,KACCG,EAAI,CAAC,CAAE,OAAAO,CAAO,IAAMA,CAAM,CAC5B,EAGF,OAAOC,EAAc,CAACF,EAASP,CAAU,CAAC,EACvC,KACCC,EAAI,CAAC,CAACO,EAAQE,CAAS,IAAM,EAAEF,GAAUE,EAAU,EACnDJ,EAAqB,EACrBK,GAAUZ,EAAQ,KAAKa,GAAK,CAAC,CAAC,CAAC,EAC/BC,GAAQ,EAAI,EACZC,GAAO,CAAE,MAAO,GAAI,CAAC,EACrBb,EAAIc,IAAW,CAAE,OAAAA,CAAO,EAAE,CAC5B,CACJ,CAYO,SAASC,GACdC,EAAiB,CAAE,UAAApB,EAAW,QAAAqB,EAAS,MAAApB,EAAO,QAAAC,CAAQ,EACpB,CAClC,IAAMoB,EAAQ,IAAIC,EACZC,EAAQF,EAAM,KAAKG,GAAS,CAAC,CAAC,EACpC,OAAAH,EAAM,UAAU,CAGd,KAAK,CAAE,OAAAJ,CAAO,EAAG,CACfE,EAAG,OAASF,EACRA,GACFE,EAAG,aAAa,WAAY,IAAI,EAChCA,EAAG,KAAK,GAERA,EAAG,gBAAgB,UAAU,CAEjC,EAGA,UAAW,CACTA,EAAG,MAAM,IAAM,GACfA,EAAG,OAAS,GACZA,EAAG,gBAAgB,UAAU,CAC/B,CACF,CAAC,EAGDC,EACG,KACCP,GAAUU,CAAK,EACfE,EAAwB,QAAQ,CAClC,EACG,UAAU,CAAC,CAAE,OAAAC,CAAO,IAAM,CACzBP,EAAG,MAAM,IAAM,GAAGO,EAAS,MAC7B,CAAC,EAGE7B,GAAesB,EAAI,CAAE,UAAApB,EAAW,MAAAC,EAAO,QAAAC,CAAQ,CAAC,EACpD,KACC0B,EAAIC,GAASP,EAAM,KAAKO,CAAK,CAAC,EAC9BC,EAAS,IAAMR,EAAM,SAAS,CAAC,EAC/BlB,EAAIyB,GAAUE,EAAA,CAAE,IAAKX,GAAOS,EAAQ,CACtC,CACJ,CCpHO,SAASG,GACd,CAAE,UAAAC,EAAW,QAAAC,CAAQ,EACf,CACND,EACG,KACCE,EAAU,IAAMC,EAEd,0DACF,CAAC,EACDC,EAAIC,GAAM,CACRA,EAAG,cAAgB,GACnBA,EAAG,QAAU,EACf,CAAC,EACDC,GAASD,GAAME,EAAUF,EAAI,QAAQ,EAClC,KACCG,GAAU,IAAMH,EAAG,UAAU,SAAS,0BAA0B,CAAC,EACjEI,EAAI,IAAMJ,CAAE,CACd,CACF,EACAK,GAAeT,CAAO,CACxB,EACG,UAAU,CAAC,CAACI,EAAIM,CAAM,IAAM,CAC3BN,EAAG,UAAU,OAAO,0BAA0B,EAC1CM,IACFN,EAAG,QAAU,GACjB,CAAC,CACP,CC/BA,SAASO,IAAyB,CAChC,MAAO,qBAAqB,KAAK,UAAU,SAAS,CACtD,CAiBO,SAASC,GACd,CAAE,UAAAC,CAAU,EACN,CACNA,EACG,KACCC,EAAU,IAAMC,EAAY,qBAAqB,CAAC,EAClDC,EAAIC,GAAMA,EAAG,gBAAgB,mBAAmB,CAAC,EACjDC,EAAOP,EAAa,EACpBQ,GAASF,GAAMG,EAAUH,EAAI,YAAY,EACtC,KACCI,EAAI,IAAMJ,CAAE,CACd,CACF,CACF,EACG,UAAUA,GAAM,CACf,IAAMK,EAAML,EAAG,UAGXK,IAAQ,EACVL,EAAG,UAAY,EAGNK,EAAML,EAAG,eAAiBA,EAAG,eACtCA,EAAG,UAAYK,EAAM,EAEzB,CAAC,CACP,CCpCO,SAASC,GACd,CAAE,UAAAC,EAAW,QAAAC,CAAQ,EACf,CACNC,EAAc,CAACC,GAAY,QAAQ,EAAGF,CAAO,CAAC,EAC3C,KACCG,EAAI,CAAC,CAACC,EAAQC,CAAM,IAAMD,GAAU,CAACC,CAAM,EAC3CC,EAAUF,GAAUG,EAAGH,CAAM,EAC1B,KACCI,GAAMJ,EAAS,IAAM,GAAG,CAC1B,CACF,EACAK,GAAeV,CAAS,CAC1B,EACG,UAAU,CAAC,CAACK,EAAQ,CAAE,OAAQ,CAAE,EAAAM,CAAE,CAAC,CAAC,IAAM,CACzC,GAAIN,EACF,SAAS,KAAK,aAAa,qBAAsB,EAAE,EACnD,SAAS,KAAK,MAAM,IAAM,IAAIM,UACzB,CACL,IAAMC,EAAQ,GAAK,SAAS,SAAS,KAAK,MAAM,IAAK,EAAE,EACvD,SAAS,KAAK,gBAAgB,oBAAoB,EAClD,SAAS,KAAK,MAAM,IAAM,GACtBA,GACF,OAAO,SAAS,EAAGA,CAAK,CAC5B,CACF,CAAC,CACP,CC7DK,OAAO,UACV,OAAO,QAAU,SAAUC,EAAa,CACtC,IAAMC,EAA2B,CAAC,EAClC,QAAWC,KAAO,OAAO,KAAKF,CAAG,EAE/BC,EAAK,KAAK,CAACC,EAAKF,EAAIE,EAAI,CAAC,EAG3B,OAAOD,CACT,GAGG,OAAO,SACV,OAAO,OAAS,SAAUD,EAAa,CACrC,IAAMC,EAAiB,CAAC,EACxB,QAAWC,KAAO,OAAO,KAAKF,CAAG,EAE/BC,EAAK,KAAKD,EAAIE,EAAI,EAGpB,OAAOD,CACT,GAKE,OAAO,SAAY,cAGhB,QAAQ,UAAU,WACrB,QAAQ,UAAU,SAAW,SAC3BE,EAA8BC,EACxB,CACF,OAAOD,GAAM,UACf,KAAK,WAAaA,EAAE,KACpB,KAAK,UAAYA,EAAE,MAEnB,KAAK,WAAaA,EAClB,KAAK,UAAYC,EAErB,GAGG,QAAQ,UAAU,cACrB,QAAQ,UAAU,YAAc,YAC3BC,EACG,CACN,IAAMC,EAAS,KAAK,WACpB,GAAIA,EAAQ,CACND,EAAM,SAAW,GACnBC,EAAO,YAAY,IAAI,EAGzB,QAASC,EAAIF,EAAM,OAAS,EAAGE,GAAK,EAAGA,IAAK,CAC1C,IAAIC,EAAOH,EAAME,GACb,OAAOC,GAAS,SAClBA,EAAO,SAAS,eAAeA,CAAI,EAC5BA,EAAK,YACZA,EAAK,WAAW,YAAYA,CAAI,EAG7BD,EAGHD,EAAO,aAAa,KAAK,gBAAkBE,CAAI,EAF/CF,EAAO,aAAaE,EAAM,IAAI,CAGlC,CACF,CACF,IjMDJ,SAAS,gBAAgB,UAAU,OAAO,OAAO,EACjD,SAAS,gBAAgB,UAAU,IAAI,IAAI,EAG3C,IAAMC,GAAYC,GAAc,EAC1BC,GAAYC,GAAc,EAC1BC,GAAYC,GAAoB,EAChCC,GAAYC,GAAc,EAG1BC,GAAYC,GAAc,EAC1BC,GAAYC,GAAW,oBAAoB,EAC3CC,GAAYD,GAAW,qBAAqB,EAC5CE,GAAYC,GAAW,EAGvBC,GAASC,GAAc,EACvBC,GAAS,SAAS,MAAM,UAAU,QAAQ,GAC5C,+BAAU,QAASC,GACnB,IAAI,IAAI,2BAA4BH,GAAO,IAAI,CACjD,EACEI,GAGEC,GAAS,IAAIC,EACnBC,GAAiB,CAAE,OAAAF,EAAO,CAAC,EAGvBG,EAAQ,oBAAoB,GAC9BC,GAAoB,CAAE,UAAAxB,GAAW,UAAAE,GAAW,UAAAM,EAAU,CAAC,EA1HzD,IAAAiB,KA6HIA,GAAAV,GAAO,UAAP,YAAAU,GAAgB,YAAa,QAC/BC,GAAqB,CAAE,UAAA1B,EAAU,CAAC,EAGpC2B,EAAMzB,GAAWE,EAAO,EACrB,KACCwB,GAAM,GAAG,CACX,EACG,UAAU,IAAM,CACfC,GAAU,SAAU,EAAK,EACzBA,GAAU,SAAU,EAAK,CAC3B,CAAC,EAGLvB,GACG,KACCwB,EAAO,CAAC,CAAE,KAAAC,CAAK,IAAMA,IAAS,QAAQ,CACxC,EACG,UAAUC,GAAO,CAChB,OAAQA,EAAI,KAAM,CAGhB,IAAK,IACL,IAAK,IACH,IAAMC,EAAOC,GAAmB,kBAAkB,EAC9C,OAAOD,GAAS,aAClBA,EAAK,MAAM,EACb,MAGF,IAAK,IACL,IAAK,IACH,IAAME,EAAOD,GAAmB,kBAAkB,EAC9C,OAAOC,GAAS,aAClBA,EAAK,MAAM,EACb,KACJ,CACF,CAAC,EAGLC,GAAmB,CAAE,UAAApC,GAAW,QAAAU,EAAQ,CAAC,EACzC2B,GAAe,CAAE,UAAArC,EAAU,CAAC,EAC5BsC,GAAgB,CAAE,UAAA9B,GAAW,QAAAE,EAAQ,CAAC,EAGtC,IAAM6B,GAAUC,GAAYC,GAAoB,QAAQ,EAAG,CAAE,UAAAjC,EAAU,CAAC,EAClEkC,GAAQ1C,GACX,KACC2C,EAAI,IAAMF,GAAoB,MAAM,CAAC,EACrCG,EAAUC,GAAMC,GAAUD,EAAI,CAAE,UAAArC,GAAW,QAAA+B,EAAQ,CAAC,CAAC,EACrDQ,EAAY,CAAC,CACf,EAGIC,GAAWrB,EAGf,GAAGsB,GAAqB,SAAS,EAC9B,IAAIJ,GAAMK,GAAaL,EAAI,CAAE,QAAAzC,EAAQ,CAAC,CAAC,EAG1C,GAAG6C,GAAqB,QAAQ,EAC7B,IAAIJ,GAAMM,GAAYN,EAAI,CAAE,OAAAzB,EAAO,CAAC,CAAC,EAGxC,GAAG6B,GAAqB,QAAQ,EAC7B,IAAIJ,GAAMO,GAAYP,EAAI,CAAE,UAAArC,GAAW,QAAA+B,GAAS,MAAAG,EAAM,CAAC,CAAC,EAG3D,GAAGO,GAAqB,SAAS,EAC9B,IAAIJ,GAAMQ,GAAaR,CAAE,CAAC,EAG7B,GAAGI,GAAqB,QAAQ,EAC7B,IAAIJ,GAAMS,GAAYT,EAAI,CAAE,OAAA5B,GAAQ,UAAAX,EAAU,CAAC,CAAC,EAGnD,GAAG2C,GAAqB,QAAQ,EAC7B,IAAIJ,GAAMU,GAAYV,CAAE,CAAC,CAC9B,EAGMW,GAAWC,EAAM,IAAM9B,EAG3B,GAAGsB,GAAqB,UAAU,EAC/B,IAAIJ,GAAMa,GAAcb,CAAE,CAAC,EAG9B,GAAGI,GAAqB,SAAS,EAC9B,IAAIJ,GAAMc,GAAad,EAAI,CAAE,UAAArC,GAAW,QAAAJ,GAAS,OAAAS,EAAO,CAAC,CAAC,EAG7D,GAAGoC,GAAqB,SAAS,EAC9B,IAAIJ,GAAMtB,EAAQ,kBAAkB,EACjCqC,GAAoBf,EAAI,CAAE,OAAA5B,GAAQ,UAAAf,EAAU,CAAC,EAC7C2D,CACJ,EAGF,GAAGZ,GAAqB,cAAc,EACnC,IAAIJ,GAAMiB,GAAiBjB,EAAI,CAAE,UAAArC,GAAW,QAAA+B,EAAQ,CAAC,CAAC,EAGzD,GAAGU,GAAqB,SAAS,EAC9B,IAAIJ,GAAMA,EAAG,aAAa,cAAc,IAAM,aAC3CkB,GAAGnD,GAAS,IAAMoD,GAAanB,EAAI,CAAE,UAAArC,GAAW,QAAA+B,GAAS,MAAAG,EAAM,CAAC,CAAC,EACjEqB,GAAGrD,GAAS,IAAMsD,GAAanB,EAAI,CAAE,UAAArC,GAAW,QAAA+B,GAAS,MAAAG,EAAM,CAAC,CAAC,CACrE,EAGF,GAAGO,GAAqB,MAAM,EAC3B,IAAIJ,GAAMoB,GAAUpB,EAAI,CAAE,UAAArC,GAAW,QAAA+B,EAAQ,CAAC,CAAC,EAGlD,GAAGU,GAAqB,KAAK,EAC1B,IAAIJ,GAAMqB,GAAqBrB,EAAI,CAAE,UAAArC,GAAW,QAAA+B,GAAS,QAAAnC,EAAQ,CAAC,CAAC,EAGtE,GAAG6C,GAAqB,KAAK,EAC1B,IAAIJ,GAAMsB,GAAetB,EAAI,CAAE,UAAArC,GAAW,QAAA+B,GAAS,MAAAG,GAAO,QAAAtC,EAAQ,CAAC,CAAC,CACzE,CAAC,EAGKgE,GAAapE,GAChB,KACC4C,EAAU,IAAMY,EAAQ,EACxBa,GAAUrB,EAAQ,EAClBD,EAAY,CAAC,CACf,EAGFqB,GAAW,UAAU,EAMrB,OAAO,UAAapE,GACpB,OAAO,UAAaE,GACpB,OAAO,QAAaE,GACpB,OAAO,UAAaE,GACpB,OAAO,UAAaE,GACpB,OAAO,QAAaE,GACpB,OAAO,QAAaE,GACpB,OAAO,OAAaC,GACpB,OAAO,OAAaO,GACpB,OAAO,WAAagD",
+  "names": ["require_focus_visible", "__commonJSMin", "exports", "module", "global", "factory", "applyFocusVisiblePolyfill", "scope", "hadKeyboardEvent", "hadFocusVisibleRecently", "hadFocusVisibleRecentlyTimeout", "inputTypesAllowlist", "isValidFocusTarget", "el", "focusTriggersKeyboardModality", "type", "tagName", "addFocusVisibleClass", "removeFocusVisibleClass", "onKeyDown", "e", "onPointerDown", "onFocus", "onBlur", "onVisibilityChange", "addInitialPointerMoveListeners", "onInitialPointerMove", "removeInitialPointerMoveListeners", "event", "error", "require_url_polyfill", "__commonJSMin", "exports", "global", "checkIfIteratorIsSupported", "error", "iteratorSupported", "createIterator", "items", "iterator", "value", "serializeParam", "deserializeParam", "polyfillURLSearchParams", "URLSearchParams", "searchString", "typeofSearchString", "_this", "name", "i", "entry", "key", "proto", "callback", "thisArg", "entries", "searchArray", "checkIfURLSearchParamsSupported", "e", "a", "b", "keys", "attributes", "attribute", "checkIfURLIsSupported", "u", "polyfillURL", "_URL", "URL", "url", "base", "doc", "baseElement", "err", "anchorElement", "inputElement", "searchParams", "enableSearchUpdate", "enableSearchParamsUpdate", "methodName", "method", "search", "linkURLWithAnchorAttribute", "attributeName", "expectedPort", "addPortToOrigin", "blob", "getOrigin", "require_tslib", "__commonJSMin", "exports", "module", "__extends", "__assign", "__rest", "__decorate", "__param", "__metadata", "__awaiter", "__generator", "__exportStar", "__values", "__read", "__spread", "__spreadArrays", "__spreadArray", "__await", "__asyncGenerator", "__asyncDelegator", "__asyncValues", "__makeTemplateObject", "__importStar", "__importDefault", "__classPrivateFieldGet", "__classPrivateFieldSet", "__createBinding", "factory", "root", "createExporter", "previous", "id", "v", "exporter", "extendStatics", "d", "b", "p", "__", "t", "s", "n", "e", "i", "decorators", "target", "key", "desc", "c", "r", "paramIndex", "decorator", "metadataKey", "metadataValue", "thisArg", "_arguments", "P", "generator", "adopt", "value", "resolve", "reject", "fulfilled", "step", "rejected", "result", "body", "_", "f", "y", "g", "verb", "op", "m", "o", "k", "k2", "ar", "error", "il", "a", "j", "jl", "to", "from", "pack", "l", "q", "resume", "settle", "fulfill", "cooked", "raw", "__setModuleDefault", "mod", "receiver", "state", "kind", "require_clipboard", "__commonJSMin", "exports", "module", "root", "factory", "__webpack_modules__", "__unused_webpack_module", "__webpack_exports__", "__webpack_require__", "clipboard", "tiny_emitter", "tiny_emitter_default", "listen", "listen_default", "src_select", "select_default", "command", "type", "err", "ClipboardActionCut", "target", "selectedText", "actions_cut", "createFakeElement", "value", "isRTL", "fakeElement", "yPosition", "fakeCopyAction", "options", "ClipboardActionCopy", "actions_copy", "_typeof", "obj", "ClipboardActionDefault", "_options$action", "action", "container", "text", "actions_default", "clipboard_typeof", "_classCallCheck", "instance", "Constructor", "_defineProperties", "props", "i", "descriptor", "_createClass", "protoProps", "staticProps", "_inherits", "subClass", "superClass", "_setPrototypeOf", "o", "p", "_createSuper", "Derived", "hasNativeReflectConstruct", "_isNativeReflectConstruct", "Super", "_getPrototypeOf", "result", "NewTarget", "_possibleConstructorReturn", "self", "call", "_assertThisInitialized", "e", "getAttributeValue", "suffix", "element", "attribute", "Clipboard", "_Emitter", "_super", "trigger", "_this", "_this2", "selector", "actions", "support", "DOCUMENT_NODE_TYPE", "proto", "closest", "__unused_webpack_exports", "_delegate", "callback", "useCapture", "listenerFn", "listener", "delegate", "elements", "is", "listenNode", "listenNodeList", "listenSelector", "node", "nodeList", "select", "isReadOnly", "selection", "range", "E", "name", "ctx", "data", "evtArr", "len", "evts", "liveEvents", "__webpack_module_cache__", "moduleId", "getter", "definition", "key", "prop", "require_escape_html", "__commonJSMin", "exports", "module", "matchHtmlRegExp", "escapeHtml", "string", "str", "match", "escape", "html", "index", "lastIndex", "r", "a", "e", "import_focus_visible", "n", "t", "s", "r", "o", "u", "i", "a", "e", "c", "import_url_polyfill", "import_tslib", "__extends", "__assign", "__rest", "__decorate", "__param", "__metadata", "__awaiter", "__generator", "__exportStar", "__createBinding", "__values", "__read", "__spread", "__spreadArrays", "__spreadArray", "__await", "__asyncGenerator", "__asyncDelegator", "__asyncValues", "__makeTemplateObject", "__importStar", "__importDefault", "__classPrivateFieldGet", "__classPrivateFieldSet", "tslib", "isFunction", "value", "createErrorClass", "createImpl", "_super", "instance", "ctorFunc", "UnsubscriptionError", "createErrorClass", "_super", "errors", "err", "i", "arrRemove", "arr", "item", "index", "Subscription", "initialTeardown", "errors", "_parentage", "_parentage_1", "__values", "_parentage_1_1", "parent_1", "initialFinalizer", "isFunction", "e", "UnsubscriptionError", "_finalizers", "_finalizers_1", "_finalizers_1_1", "finalizer", "execFinalizer", "err", "__spreadArray", "__read", "teardown", "_a", "parent", "arrRemove", "empty", "EMPTY_SUBSCRIPTION", "Subscription", "isSubscription", "value", "isFunction", "execFinalizer", "finalizer", "config", "timeoutProvider", "handler", "timeout", "args", "_i", "delegate", "__spreadArray", "__read", "handle", "reportUnhandledError", "err", "timeoutProvider", "onUnhandledError", "config", "noop", "COMPLETE_NOTIFICATION", "createNotification", "errorNotification", "error", "nextNotification", "value", "kind", "context", "errorContext", "cb", "config", "isRoot", "_a", "errorThrown", "error", "captureError", "err", "Subscriber", "_super", "__extends", "destination", "_this", "isSubscription", "EMPTY_OBSERVER", "next", "error", "complete", "SafeSubscriber", "value", "handleStoppedNotification", "nextNotification", "err", "errorNotification", "COMPLETE_NOTIFICATION", "Subscription", "_bind", "bind", "fn", "thisArg", "ConsumerObserver", "partialObserver", "value", "error", "handleUnhandledError", "err", "SafeSubscriber", "_super", "__extends", "observerOrNext", "complete", "_this", "isFunction", "context_1", "config", "Subscriber", "handleUnhandledError", "error", "config", "captureError", "reportUnhandledError", "defaultErrorHandler", "err", "handleStoppedNotification", "notification", "subscriber", "onStoppedNotification", "timeoutProvider", "EMPTY_OBSERVER", "noop", "observable", "identity", "x", "pipe", "fns", "_i", "pipeFromArray", "identity", "input", "prev", "fn", "Observable", "subscribe", "operator", "observable", "observerOrNext", "error", "complete", "_this", "subscriber", "isSubscriber", "SafeSubscriber", "errorContext", "_a", "source", "sink", "err", "next", "promiseCtor", "getPromiseCtor", "resolve", "reject", "value", "operations", "_i", "pipeFromArray", "x", "getPromiseCtor", "promiseCtor", "_a", "config", "isObserver", "value", "isFunction", "isSubscriber", "Subscriber", "isSubscription", "hasLift", "source", "isFunction", "operate", "init", "liftedSource", "err", "createOperatorSubscriber", "destination", "onNext", "onComplete", "onError", "onFinalize", "OperatorSubscriber", "_super", "__extends", "shouldUnsubscribe", "_this", "value", "err", "closed_1", "_a", "Subscriber", "animationFrameProvider", "callback", "request", "cancel", "delegate", "handle", "timestamp", "Subscription", "args", "_i", "__spreadArray", "__read", "ObjectUnsubscribedError", "createErrorClass", "_super", "Subject", "_super", "__extends", "_this", "operator", "subject", "AnonymousSubject", "ObjectUnsubscribedError", "value", "errorContext", "_b", "__values", "_c", "observer", "err", "observers", "_a", "subscriber", "hasError", "isStopped", "EMPTY_SUBSCRIPTION", "Subscription", "arrRemove", "thrownError", "observable", "Observable", "destination", "source", "AnonymousSubject", "_super", "__extends", "destination", "source", "_this", "value", "_b", "_a", "err", "subscriber", "EMPTY_SUBSCRIPTION", "Subject", "dateTimestampProvider", "ReplaySubject", "_super", "__extends", "_bufferSize", "_windowTime", "_timestampProvider", "dateTimestampProvider", "_this", "value", "_a", "isStopped", "_buffer", "_infiniteTimeWindow", "subscriber", "subscription", "copy", "i", "adjustedBufferSize", "now", "last", "Subject", "Action", "_super", "__extends", "scheduler", "work", "state", "delay", "Subscription", "intervalProvider", "handler", "timeout", "args", "_i", "delegate", "__spreadArray", "__read", "handle", "AsyncAction", "_super", "__extends", "scheduler", "work", "_this", "state", "delay", "id", "_a", "_id", "intervalProvider", "_scheduler", "error", "_delay", "errored", "errorValue", "e", "actions", "arrRemove", "Action", "Scheduler", "schedulerActionCtor", "now", "work", "delay", "state", "dateTimestampProvider", "AsyncScheduler", "_super", "__extends", "SchedulerAction", "now", "Scheduler", "_this", "action", "actions", "error", "asyncScheduler", "AsyncScheduler", "AsyncAction", "async", "AnimationFrameAction", "_super", "__extends", "scheduler", "work", "_this", "id", "delay", "animationFrameProvider", "actions", "_a", "AsyncAction", "AnimationFrameScheduler", "_super", "__extends", "action", "flushId", "actions", "error", "AsyncScheduler", "animationFrameScheduler", "AnimationFrameScheduler", "AnimationFrameAction", "EMPTY", "Observable", "subscriber", "isScheduler", "value", "isFunction", "last", "arr", "popResultSelector", "args", "isFunction", "popScheduler", "isScheduler", "popNumber", "defaultValue", "isArrayLike", "x", "isPromise", "value", "isFunction", "isInteropObservable", "input", "isFunction", "observable", "isAsyncIterable", "obj", "isFunction", "createInvalidObservableTypeError", "input", "getSymbolIterator", "iterator", "isIterable", "input", "isFunction", "iterator", "readableStreamLikeToAsyncGenerator", "readableStream", "reader", "__await", "_a", "_b", "value", "done", "isReadableStreamLike", "obj", "isFunction", "innerFrom", "input", "Observable", "isInteropObservable", "fromInteropObservable", "isArrayLike", "fromArrayLike", "isPromise", "fromPromise", "isAsyncIterable", "fromAsyncIterable", "isIterable", "fromIterable", "isReadableStreamLike", "fromReadableStreamLike", "createInvalidObservableTypeError", "obj", "subscriber", "obs", "observable", "isFunction", "array", "i", "promise", "value", "err", "reportUnhandledError", "iterable", "iterable_1", "__values", "iterable_1_1", "asyncIterable", "process", "readableStream", "readableStreamLikeToAsyncGenerator", "asyncIterable_1", "__asyncValues", "asyncIterable_1_1", "executeSchedule", "parentSubscription", "scheduler", "work", "delay", "repeat", "scheduleSubscription", "observeOn", "scheduler", "delay", "operate", "source", "subscriber", "createOperatorSubscriber", "value", "executeSchedule", "err", "subscribeOn", "scheduler", "delay", "operate", "source", "subscriber", "scheduleObservable", "input", "scheduler", "innerFrom", "subscribeOn", "observeOn", "schedulePromise", "input", "scheduler", "innerFrom", "subscribeOn", "observeOn", "scheduleArray", "input", "scheduler", "Observable", "subscriber", "i", "scheduleIterable", "input", "scheduler", "Observable", "subscriber", "iterator", "executeSchedule", "value", "done", "_a", "err", "isFunction", "scheduleAsyncIterable", "input", "scheduler", "Observable", "subscriber", "executeSchedule", "iterator", "result", "scheduleReadableStreamLike", "input", "scheduler", "scheduleAsyncIterable", "readableStreamLikeToAsyncGenerator", "scheduled", "input", "scheduler", "isInteropObservable", "scheduleObservable", "isArrayLike", "scheduleArray", "isPromise", "schedulePromise", "isAsyncIterable", "scheduleAsyncIterable", "isIterable", "scheduleIterable", "isReadableStreamLike", "scheduleReadableStreamLike", "createInvalidObservableTypeError", "from", "input", "scheduler", "scheduled", "innerFrom", "of", "args", "_i", "scheduler", "popScheduler", "from", "throwError", "errorOrErrorFactory", "scheduler", "errorFactory", "isFunction", "init", "subscriber", "Observable", "isValidDate", "value", "map", "project", "thisArg", "operate", "source", "subscriber", "index", "createOperatorSubscriber", "value", "isArray", "callOrApply", "fn", "args", "__spreadArray", "__read", "mapOneOrManyArgs", "map", "isArray", "getPrototypeOf", "objectProto", "getKeys", "argsArgArrayOrObject", "args", "first_1", "isPOJO", "keys", "key", "obj", "createObject", "keys", "values", "result", "key", "i", "combineLatest", "args", "_i", "scheduler", "popScheduler", "resultSelector", "popResultSelector", "_a", "argsArgArrayOrObject", "observables", "keys", "from", "result", "Observable", "combineLatestInit", "values", "createObject", "identity", "mapOneOrManyArgs", "valueTransform", "subscriber", "maybeSchedule", "length", "active", "remainingFirstValues", "i", "source", "hasFirstValue", "createOperatorSubscriber", "value", "execute", "subscription", "executeSchedule", "mergeInternals", "source", "subscriber", "project", "concurrent", "onBeforeNext", "expand", "innerSubScheduler", "additionalFinalizer", "buffer", "active", "index", "isComplete", "checkComplete", "outerNext", "value", "doInnerSub", "innerComplete", "innerFrom", "createOperatorSubscriber", "innerValue", "bufferedValue", "executeSchedule", "err", "mergeMap", "project", "resultSelector", "concurrent", "isFunction", "a", "i", "map", "b", "ii", "innerFrom", "operate", "source", "subscriber", "mergeInternals", "mergeAll", "concurrent", "mergeMap", "identity", "concatAll", "mergeAll", "concat", "args", "_i", "concatAll", "from", "popScheduler", "defer", "observableFactory", "Observable", "subscriber", "innerFrom", "nodeEventEmitterMethods", "eventTargetMethods", "jqueryMethods", "fromEvent", "target", "eventName", "options", "resultSelector", "isFunction", "mapOneOrManyArgs", "_a", "__read", "isEventTarget", "methodName", "handler", "isNodeStyleEventEmitter", "toCommonHandlerRegistry", "isJQueryStyleEventEmitter", "add", "remove", "isArrayLike", "mergeMap", "subTarget", "innerFrom", "Observable", "subscriber", "args", "_i", "fromEventPattern", "addHandler", "removeHandler", "resultSelector", "mapOneOrManyArgs", "Observable", "subscriber", "handler", "e", "_i", "retValue", "isFunction", "timer", "dueTime", "intervalOrScheduler", "scheduler", "async", "intervalDuration", "isScheduler", "Observable", "subscriber", "due", "isValidDate", "n", "merge", "args", "_i", "scheduler", "popScheduler", "concurrent", "popNumber", "sources", "innerFrom", "mergeAll", "from", "EMPTY", "NEVER", "Observable", "noop", "isArray", "argsOrArgArray", "args", "filter", "predicate", "thisArg", "operate", "source", "subscriber", "index", "createOperatorSubscriber", "value", "zip", "args", "_i", "resultSelector", "popResultSelector", "sources", "argsOrArgArray", "Observable", "subscriber", "buffers", "completed", "sourceIndex", "innerFrom", "createOperatorSubscriber", "value", "buffer", "result", "__spreadArray", "__read", "i", "EMPTY", "audit", "durationSelector", "operate", "source", "subscriber", "hasValue", "lastValue", "durationSubscriber", "isComplete", "endDuration", "value", "cleanupDuration", "createOperatorSubscriber", "innerFrom", "auditTime", "duration", "scheduler", "asyncScheduler", "audit", "timer", "bufferCount", "bufferSize", "startBufferEvery", "operate", "source", "subscriber", "buffers", "count", "createOperatorSubscriber", "value", "toEmit", "buffers_1", "__values", "buffers_1_1", "buffer", "toEmit_1", "toEmit_1_1", "arrRemove", "buffers_2", "buffers_2_1", "catchError", "selector", "operate", "source", "subscriber", "innerSub", "syncUnsub", "handledResult", "createOperatorSubscriber", "err", "innerFrom", "scanInternals", "accumulator", "seed", "hasSeed", "emitOnNext", "emitBeforeComplete", "source", "subscriber", "hasState", "state", "index", "createOperatorSubscriber", "value", "i", "combineLatest", "args", "_i", "resultSelector", "popResultSelector", "pipe", "__spreadArray", "__read", "mapOneOrManyArgs", "operate", "source", "subscriber", "combineLatestInit", "argsOrArgArray", "combineLatestWith", "otherSources", "_i", "combineLatest", "__spreadArray", "__read", "concatMap", "project", "resultSelector", "isFunction", "mergeMap", "debounceTime", "dueTime", "scheduler", "asyncScheduler", "operate", "source", "subscriber", "activeTask", "lastValue", "lastTime", "emit", "value", "emitWhenIdle", "targetTime", "now", "createOperatorSubscriber", "defaultIfEmpty", "defaultValue", "operate", "source", "subscriber", "hasValue", "createOperatorSubscriber", "value", "take", "count", "EMPTY", "operate", "source", "subscriber", "seen", "createOperatorSubscriber", "value", "ignoreElements", "operate", "source", "subscriber", "createOperatorSubscriber", "noop", "mapTo", "value", "map", "delayWhen", "delayDurationSelector", "subscriptionDelay", "source", "concat", "take", "ignoreElements", "mergeMap", "value", "index", "mapTo", "delay", "due", "scheduler", "asyncScheduler", "duration", "timer", "delayWhen", "distinctUntilChanged", "comparator", "keySelector", "identity", "defaultCompare", "operate", "source", "subscriber", "previousKey", "first", "createOperatorSubscriber", "value", "currentKey", "a", "b", "distinctUntilKeyChanged", "key", "compare", "distinctUntilChanged", "x", "y", "endWith", "values", "_i", "source", "concat", "of", "__spreadArray", "__read", "finalize", "callback", "operate", "source", "subscriber", "takeLast", "count", "EMPTY", "operate", "source", "subscriber", "buffer", "createOperatorSubscriber", "value", "buffer_1", "__values", "buffer_1_1", "merge", "args", "_i", "scheduler", "popScheduler", "concurrent", "popNumber", "argsOrArgArray", "operate", "source", "subscriber", "mergeAll", "from", "__spreadArray", "__read", "mergeWith", "otherSources", "_i", "merge", "__spreadArray", "__read", "repeat", "countOrConfig", "count", "delay", "_a", "EMPTY", "operate", "source", "subscriber", "soFar", "sourceSub", "resubscribe", "notifier", "timer", "innerFrom", "notifierSubscriber_1", "createOperatorSubscriber", "subscribeToSource", "syncUnsub", "sample", "notifier", "operate", "source", "subscriber", "hasValue", "lastValue", "createOperatorSubscriber", "value", "noop", "scan", "accumulator", "seed", "operate", "scanInternals", "share", "options", "_a", "connector", "Subject", "_b", "resetOnError", "_c", "resetOnComplete", "_d", "resetOnRefCountZero", "wrapperSource", "connection", "resetConnection", "subject", "refCount", "hasCompleted", "hasErrored", "cancelReset", "reset", "resetAndUnsubscribe", "conn", "operate", "source", "subscriber", "dest", "handleReset", "SafeSubscriber", "value", "err", "innerFrom", "on", "args", "_i", "onSubscriber", "__spreadArray", "__read", "shareReplay", "configOrBufferSize", "windowTime", "scheduler", "bufferSize", "refCount", "_a", "_b", "_c", "share", "ReplaySubject", "skip", "count", "filter", "_", "index", "skipUntil", "notifier", "operate", "source", "subscriber", "taking", "skipSubscriber", "createOperatorSubscriber", "noop", "innerFrom", "value", "startWith", "values", "_i", "scheduler", "popScheduler", "operate", "source", "subscriber", "concat", "switchMap", "project", "resultSelector", "operate", "source", "subscriber", "innerSubscriber", "index", "isComplete", "checkComplete", "createOperatorSubscriber", "value", "innerIndex", "outerIndex", "innerFrom", "innerValue", "takeUntil", "notifier", "operate", "source", "subscriber", "innerFrom", "createOperatorSubscriber", "noop", "takeWhile", "predicate", "inclusive", "operate", "source", "subscriber", "index", "createOperatorSubscriber", "value", "result", "tap", "observerOrNext", "error", "complete", "tapObserver", "isFunction", "operate", "source", "subscriber", "_a", "isUnsub", "createOperatorSubscriber", "value", "err", "_b", "identity", "defaultThrottleConfig", "throttle", "durationSelector", "config", "operate", "source", "subscriber", "leading", "trailing", "hasValue", "sendValue", "throttled", "isComplete", "endThrottling", "send", "cleanupThrottling", "startThrottle", "value", "innerFrom", "createOperatorSubscriber", "throttleTime", "duration", "scheduler", "config", "asyncScheduler", "defaultThrottleConfig", "duration$", "timer", "throttle", "withLatestFrom", "inputs", "_i", "project", "popResultSelector", "operate", "source", "subscriber", "len", "otherValues", "hasValue", "ready", "i", "innerFrom", "createOperatorSubscriber", "value", "identity", "noop", "values", "__spreadArray", "__read", "zip", "sources", "_i", "operate", "source", "subscriber", "__spreadArray", "__read", "zipWith", "otherInputs", "_i", "zip", "__spreadArray", "__read", "watchDocument", "document$", "ReplaySubject", "fromEvent", "getElements", "selector", "node", "getElement", "el", "getOptionalElement", "getActiveElement", "watchElementFocus", "el", "merge", "fromEvent", "debounceTime", "map", "active", "getActiveElement", "startWith", "distinctUntilChanged", "getElementOffset", "el", "watchElementOffset", "merge", "fromEvent", "auditTime", "animationFrameScheduler", "map", "startWith", "getElementContentOffset", "el", "watchElementContentOffset", "merge", "fromEvent", "auditTime", "animationFrameScheduler", "map", "startWith", "MapShim", "getIndex", "arr", "key", "result", "entry", "index", "class_1", "value", "entries", "callback", "ctx", "_i", "_a", "isBrowser", "global$1", "requestAnimationFrame$1", "trailingTimeout", "throttle", "delay", "leadingCall", "trailingCall", "lastCallTime", "resolvePending", "proxy", "timeoutCallback", "timeStamp", "REFRESH_DELAY", "transitionKeys", "mutationObserverSupported", "ResizeObserverController", "observer", "observers", "changesDetected", "activeObservers", "_b", "propertyName", "isReflowProperty", "defineConfigurable", "target", "props", "getWindowOf", "ownerGlobal", "emptyRect", "createRectInit", "toFloat", "getBordersSize", "styles", "positions", "size", "position", "getPaddings", "paddings", "positions_1", "getSVGContentRect", "bbox", "getHTMLElementContentRect", "clientWidth", "clientHeight", "horizPad", "vertPad", "width", "height", "isDocumentElement", "vertScrollbar", "horizScrollbar", "isSVGGraphicsElement", "getContentRect", "createReadOnlyRect", "x", "y", "Constr", "rect", "ResizeObservation", "ResizeObserverEntry", "rectInit", "contentRect", "ResizeObserverSPI", "controller", "callbackCtx", "observations", "_this", "observation", "ResizeObserver", "method", "ResizeObserver_es_default", "entry$", "Subject", "observer$", "defer", "of", "ResizeObserver_es_default", "entries", "entry", "switchMap", "observer", "merge", "NEVER", "finalize", "shareReplay", "getElementSize", "el", "watchElementSize", "tap", "filter", "target", "map", "startWith", "getElementContentSize", "el", "getElementContainer", "parent", "entry$", "Subject", "observer$", "defer", "of", "entries", "entry", "switchMap", "observer", "merge", "NEVER", "finalize", "shareReplay", "watchElementVisibility", "el", "tap", "filter", "target", "map", "isIntersecting", "watchElementBoundary", "threshold", "watchElementContentOffset", "y", "visible", "getElementSize", "content", "getElementContentSize", "distinctUntilChanged", "toggles", "getElement", "getToggle", "name", "setToggle", "value", "watchToggle", "el", "fromEvent", "map", "startWith", "isSusceptibleToKeyboard", "el", "type", "watchKeyboard", "fromEvent", "filter", "ev", "map", "getToggle", "mode", "active", "getActiveElement", "share", "getLocation", "setLocation", "url", "watchLocation", "Subject", "appendChild", "el", "child", "node", "h", "tag", "attributes", "children", "attr", "truncate", "value", "n", "i", "round", "digits", "getLocationHash", "setLocationHash", "hash", "el", "h", "ev", "watchLocationHash", "fromEvent", "map", "startWith", "filter", "shareReplay", "watchLocationTarget", "id", "getOptionalElement", "watchMedia", "query", "media", "fromEventPattern", "next", "startWith", "watchPrint", "merge", "fromEvent", "map", "at", "query$", "factory", "switchMap", "active", "EMPTY", "request", "url", "options", "from", "catchError", "EMPTY", "switchMap", "res", "throwError", "of", "requestJSON", "shareReplay", "requestXML", "dom", "map", "watchScript", "src", "script", "h", "defer", "merge", "fromEvent", "switchMap", "throwError", "map", "finalize", "take", "getViewportOffset", "watchViewportOffset", "merge", "fromEvent", "map", "startWith", "getViewportSize", "watchViewportSize", "fromEvent", "map", "startWith", "watchViewport", "combineLatest", "watchViewportOffset", "watchViewportSize", "map", "offset", "size", "shareReplay", "watchViewportAt", "el", "viewport$", "header$", "size$", "distinctUntilKeyChanged", "offset$", "combineLatest", "map", "getElementOffset", "height", "offset", "size", "x", "y", "watchWorker", "worker", "tx$", "rx$", "fromEvent", "map", "data", "throttle", "tap", "message", "switchMap", "share", "script", "getElement", "config", "getLocation", "configuration", "feature", "flag", "translation", "key", "value", "getComponentElement", "type", "node", "getElement", "getComponentElements", "getElements", "watchAnnounce", "el", "button", "getElement", "fromEvent", "map", "content", "mountAnnounce", "feature", "EMPTY", "defer", "push$", "Subject", "startWith", "hash", "_a", "tap", "state", "finalize", "__spreadValues", "watchConsent", "el", "target$", "map", "target", "mountConsent", "options", "internal$", "Subject", "hidden", "tap", "state", "finalize", "__spreadValues", "import_clipboard", "renderTooltip", "id", "h", "renderAnnotation", "id", "prefix", "anchor", "h", "renderTooltip", "renderClipboardButton", "id", "h", "translation", "renderSearchDocument", "document", "flag", "parent", "teaser", "missing", "key", "list", "h", "url", "feature", "match", "highlight", "value", "tags", "configuration", "truncate", "tag", "id", "type", "translation", "renderSearchResultItem", "result", "threshold", "docs", "doc", "article", "index", "best", "more", "children", "section", "renderSourceFacts", "facts", "h", "key", "value", "round", "renderTabbedControl", "type", "classes", "h", "renderTable", "table", "h", "renderVersion", "version", "config", "configuration", "url", "h", "renderVersionSelector", "versions", "active", "translation", "watchAnnotation", "el", "container", "offset$", "defer", "combineLatest", "watchElementOffset", "watchElementContentOffset", "map", "x", "y", "scroll", "width", "height", "getElementSize", "watchElementFocus", "switchMap", "active", "offset", "take", "mountAnnotation", "target$", "tooltip", "index", "push$", "Subject", "done$", "takeLast", "watchElementVisibility", "takeUntil", "visible", "merge", "filter", "debounceTime", "auditTime", "animationFrameScheduler", "throttleTime", "origin", "fromEvent", "ev", "withLatestFrom", "_a", "parent", "getActiveElement", "target", "delay", "tap", "state", "finalize", "__spreadValues", "findAnnotationMarkers", "container", "markers", "el", "getElements", "nodes", "it", "node", "text", "match", "id", "force", "marker", "swap", "source", "target", "mountAnnotationList", "target$", "print$", "parent", "prefix", "annotations", "getOptionalElement", "renderAnnotation", "EMPTY", "defer", "done$", "Subject", "pairs", "annotation", "getElement", "takeUntil", "takeLast", "active", "inner", "child", "merge", "mountAnnotation", "finalize", "share", "sequence", "findCandidateList", "el", "sibling", "watchCodeBlock", "watchElementSize", "map", "width", "getElementContentSize", "distinctUntilKeyChanged", "mountCodeBlock", "options", "hover", "factory$", "defer", "push$", "Subject", "scrollable", "ClipboardJS", "parent", "renderClipboardButton", "container", "list", "feature", "annotations$", "mountAnnotationList", "tap", "state", "finalize", "__spreadValues", "mergeWith", "height", "distinctUntilChanged", "switchMap", "active", "EMPTY", "watchElementVisibility", "filter", "visible", "take", "mermaid$", "sequence", "fetchScripts", "watchScript", "of", "mountMermaid", "el", "tap", "mermaid_default", "map", "shareReplay", "id", "host", "h", "svg", "shadow", "watchDetails", "el", "target$", "print$", "open", "merge", "map", "target", "filter", "details", "active", "tap", "mountDetails", "options", "defer", "push$", "Subject", "action", "reveal", "state", "finalize", "__spreadValues", "sentinel", "h", "mountDataTable", "el", "renderTable", "of", "watchContentTabs", "el", "inputs", "getElements", "initial", "input", "merge", "fromEvent", "map", "getElement", "startWith", "active", "mountContentTabs", "viewport$", "prev", "renderTabbedControl", "next", "container", "defer", "push$", "Subject", "done$", "takeLast", "combineLatest", "watchElementSize", "auditTime", "animationFrameScheduler", "takeUntil", "size", "offset", "getElementOffset", "width", "getElementSize", "content", "getElementContentOffset", "watchElementContentOffset", "getElementContentSize", "direction", "feature", "skip", "withLatestFrom", "tab", "y", "set", "label", "tabs", "tap", "state", "finalize", "__spreadValues", "subscribeOn", "asyncScheduler", "mountContent", "el", "viewport$", "target$", "print$", "merge", "getElements", "child", "mountCodeBlock", "mountMermaid", "mountDataTable", "mountDetails", "mountContentTabs", "watchDialog", "_el", "alert$", "switchMap", "message", "merge", "of", "delay", "map", "active", "mountDialog", "el", "options", "inner", "getElement", "defer", "push$", "Subject", "tap", "state", "finalize", "__spreadValues", "isHidden", "viewport$", "feature", "of", "direction$", "map", "y", "bufferCount", "a", "b", "distinctUntilKeyChanged", "hidden$", "combineLatest", "filter", "offset", "direction", "distinctUntilChanged", "search$", "watchToggle", "search", "switchMap", "active", "startWith", "watchHeader", "el", "options", "defer", "watchElementSize", "height", "hidden", "shareReplay", "mountHeader", "header$", "main$", "push$", "Subject", "done$", "takeLast", "combineLatestWith", "takeUntil", "state", "__spreadValues", "watchHeaderTitle", "el", "viewport$", "header$", "watchViewportAt", "map", "y", "height", "getElementSize", "distinctUntilKeyChanged", "mountHeaderTitle", "options", "defer", "push$", "Subject", "active", "heading", "getOptionalElement", "EMPTY", "tap", "state", "finalize", "__spreadValues", "watchMain", "el", "viewport$", "header$", "adjust$", "map", "height", "distinctUntilChanged", "border$", "switchMap", "watchElementSize", "distinctUntilKeyChanged", "combineLatest", "header", "top", "bottom", "y", "a", "b", "watchPalette", "inputs", "current", "input", "of", "mergeMap", "fromEvent", "map", "startWith", "shareReplay", "mountPalette", "el", "defer", "push$", "Subject", "palette", "key", "value", "index", "label", "observeOn", "asyncScheduler", "getElements", "tap", "state", "finalize", "__spreadValues", "import_clipboard", "extract", "el", "text", "setupClipboardJS", "alert$", "ClipboardJS", "Observable", "subscriber", "getElement", "ev", "tap", "map", "translation", "preprocess", "urls", "root", "next", "a", "b", "url", "index", "fetchSitemap", "base", "cached", "of", "config", "configuration", "requestXML", "map", "sitemap", "getElements", "node", "catchError", "EMPTY", "defaultIfEmpty", "tap", "setupInstantLoading", "document$", "location$", "viewport$", "config", "configuration", "fromEvent", "favicon", "getOptionalElement", "push$", "fetchSitemap", "map", "paths", "path", "switchMap", "urls", "filter", "ev", "el", "url", "of", "NEVER", "share", "pop$", "merge", "distinctUntilChanged", "a", "b", "response$", "distinctUntilKeyChanged", "request", "catchError", "setLocation", "sample", "dom", "res", "skip", "replacement", "selector", "feature", "source", "target", "getComponentElement", "getElements", "concatMap", "script", "h", "name", "Observable", "observer", "EMPTY", "offset", "setLocationHash", "skipUntil", "debounceTime", "bufferCount", "state", "import_escape_html", "import_escape_html", "setupSearchHighlighter", "config", "escape", "separator", "highlight", "_", "data", "term", "query", "match", "value", "escapeHTML", "defaultTransform", "query", "terms", "index", "isSearchReadyMessage", "message", "isSearchQueryMessage", "isSearchResultMessage", "setupSearchIndex", "config", "docs", "translation", "options", "feature", "setupSearchWorker", "url", "index", "configuration", "worker", "tx$", "Subject", "rx$", "watchWorker", "map", "message", "isSearchResultMessage", "result", "document", "share", "from", "data", "setupVersionSelector", "document$", "config", "configuration", "versions$", "requestJSON", "catchError", "EMPTY", "current$", "map", "versions", "current", "version", "aliases", "switchMap", "urls", "fromEvent", "filter", "ev", "withLatestFrom", "el", "url", "of", "fetchSitemap", "sitemap", "path", "getLocation", "setLocation", "combineLatest", "getElement", "renderVersionSelector", "_a", "outdated", "latest", "warning", "getComponentElements", "watchSearchQuery", "el", "rx$", "fn", "defaultTransform", "searchParams", "getLocation", "setToggle", "param$", "filter", "isSearchReadyMessage", "take", "map", "watchToggle", "active", "url", "value", "focus$", "watchElementFocus", "value$", "merge", "fromEvent", "delay", "startWith", "distinctUntilChanged", "combineLatest", "focus", "shareReplay", "mountSearchQuery", "tx$", "push$", "Subject", "done$", "takeLast", "distinctUntilKeyChanged", "translation", "takeUntil", "tap", "state", "finalize", "__spreadValues", "share", "mountSearchResult", "el", "rx$", "query$", "push$", "Subject", "boundary$", "watchElementBoundary", "filter", "meta", "getElement", "list", "ready$", "isSearchReadyMessage", "take", "withLatestFrom", "skipUntil", "items", "value", "translation", "round", "tap", "switchMap", "merge", "of", "bufferCount", "zipWith", "chunk", "result", "renderSearchResultItem", "isSearchResultMessage", "map", "data", "state", "finalize", "__spreadValues", "watchSearchShare", "_el", "query$", "map", "value", "url", "getLocation", "mountSearchShare", "el", "options", "push$", "Subject", "fromEvent", "ev", "tap", "state", "finalize", "__spreadValues", "mountSearchSuggest", "el", "rx$", "keyboard$", "push$", "Subject", "query", "getComponentElement", "query$", "merge", "fromEvent", "observeOn", "asyncScheduler", "map", "distinctUntilChanged", "combineLatestWith", "suggestions", "value", "words", "last", "filter", "mode", "key", "isSearchResultMessage", "data", "tap", "state", "finalize", "mountSearch", "el", "index$", "keyboard$", "config", "configuration", "url", "worker", "setupSearchWorker", "query", "getComponentElement", "result", "tx$", "rx$", "filter", "isSearchQueryMessage", "sample", "isSearchReadyMessage", "take", "mode", "key", "active", "getActiveElement", "anchors", "anchor", "getElements", "article", "best", "a", "b", "setToggle", "els", "i", "query$", "mountSearchQuery", "result$", "mountSearchResult", "merge", "mergeWith", "getComponentElements", "child", "mountSearchShare", "mountSearchSuggest", "err", "NEVER", "mountSearchHiglight", "el", "index$", "location$", "combineLatest", "startWith", "getLocation", "filter", "url", "map", "index", "setupSearchHighlighter", "fn", "_a", "nodes", "it", "node", "original", "replaced", "text", "childNodes", "h", "watchSidebar", "el", "viewport$", "main$", "parent", "adjust", "combineLatest", "map", "offset", "height", "y", "distinctUntilChanged", "a", "b", "mountSidebar", "_a", "_b", "header$", "options", "__objRest", "inner", "getElement", "getElementOffset", "defer", "push$", "Subject", "auditTime", "animationFrameScheduler", "withLatestFrom", "observeOn", "take", "item", "getElements", "container", "getElementContainer", "getElementSize", "tap", "state", "finalize", "__spreadValues", "fetchSourceFactsFromGitHub", "user", "repo", "url", "zip", "requestJSON", "catchError", "EMPTY", "map", "release", "defaultIfEmpty", "info", "__spreadValues", "fetchSourceFactsFromGitLab", "base", "project", "url", "requestJSON", "catchError", "EMPTY", "map", "star_count", "forks_count", "defaultIfEmpty", "fetchSourceFacts", "url", "match", "user", "repo", "fetchSourceFactsFromGitHub", "base", "slug", "fetchSourceFactsFromGitLab", "EMPTY", "fetch$", "watchSource", "el", "defer", "cached", "of", "getComponentElements", "consent", "EMPTY", "fetchSourceFacts", "tap", "facts", "catchError", "filter", "map", "shareReplay", "mountSource", "inner", "getElement", "push$", "Subject", "renderSourceFacts", "state", "finalize", "__spreadValues", "watchTabs", "el", "viewport$", "header$", "watchElementSize", "switchMap", "watchViewportAt", "map", "y", "distinctUntilKeyChanged", "mountTabs", "options", "defer", "push$", "Subject", "hidden", "feature", "of", "tap", "state", "finalize", "__spreadValues", "watchTableOfContents", "el", "viewport$", "header$", "table", "anchors", "getElements", "anchor", "id", "target", "getOptionalElement", "adjust$", "distinctUntilKeyChanged", "map", "height", "main", "getComponentElement", "grid", "getElement", "share", "watchElementSize", "switchMap", "body", "defer", "path", "of", "index", "offset", "a", "b", "combineLatestWith", "adjust", "scan", "prev", "next", "y", "size", "last", "distinctUntilChanged", "startWith", "bufferCount", "mountTableOfContents", "target$", "push$", "Subject", "done$", "takeLast", "feature", "smooth$", "merge", "debounceTime", "filter", "withLatestFrom", "behavior", "container", "getElementContainer", "getElementSize", "takeUntil", "skip", "repeat", "url", "getLocation", "active", "hash", "tap", "state", "finalize", "__spreadValues", "watchBackToTop", "_el", "viewport$", "main$", "target$", "direction$", "map", "y", "bufferCount", "a", "b", "distinctUntilChanged", "active$", "active", "combineLatest", "direction", "takeUntil", "skip", "endWith", "repeat", "hidden", "mountBackToTop", "el", "header$", "push$", "Subject", "done$", "takeLast", "distinctUntilKeyChanged", "height", "tap", "state", "finalize", "__spreadValues", "patchIndeterminate", "document$", "tablet$", "switchMap", "getElements", "tap", "el", "mergeMap", "fromEvent", "takeWhile", "map", "withLatestFrom", "tablet", "isAppleDevice", "patchScrollfix", "document$", "switchMap", "getElements", "tap", "el", "filter", "mergeMap", "fromEvent", "map", "top", "patchScrolllock", "viewport$", "tablet$", "combineLatest", "watchToggle", "map", "active", "tablet", "switchMap", "of", "delay", "withLatestFrom", "y", "value", "obj", "data", "key", "x", "y", "nodes", "parent", "i", "node", "document$", "watchDocument", "location$", "watchLocation", "target$", "watchLocationTarget", "keyboard$", "watchKeyboard", "viewport$", "watchViewport", "tablet$", "watchMedia", "screen$", "print$", "watchPrint", "config", "configuration", "index$", "requestJSON", "NEVER", "alert$", "Subject", "setupClipboardJS", "feature", "setupInstantLoading", "_a", "setupVersionSelector", "merge", "delay", "setToggle", "filter", "mode", "key", "prev", "getOptionalElement", "next", "patchIndeterminate", "patchScrollfix", "patchScrolllock", "header$", "watchHeader", "getComponentElement", "main$", "map", "switchMap", "el", "watchMain", "shareReplay", "control$", "getComponentElements", "mountConsent", "mountDialog", "mountHeader", "mountPalette", "mountSearch", "mountSource", "content$", "defer", "mountAnnounce", "mountContent", "mountSearchHiglight", "EMPTY", "mountHeaderTitle", "at", "mountSidebar", "mountTabs", "mountTableOfContents", "mountBackToTop", "component$", "mergeWith"]
+}
diff --git a/7.3/assets/javascripts/bundle.a6c66575.min.js b/7.3/assets/javascripts/bundle.a6c66575.min.js
deleted file mode 100755
index 156f28c3cf..0000000000
--- a/7.3/assets/javascripts/bundle.a6c66575.min.js
+++ /dev/null
@@ -1,29 +0,0 @@
-(()=>{var ta=Object.create;var yr=Object.defineProperty;var ra=Object.getOwnPropertyDescriptor;var na=Object.getOwnPropertyNames,Ct=Object.getOwnPropertySymbols,oa=Object.getPrototypeOf,xr=Object.prototype.hasOwnProperty,nn=Object.prototype.propertyIsEnumerable;var rn=(e,t,r)=>t in e?yr(e,t,{enumerable:!0,configurable:!0,writable:!0,value:r}):e[t]=r,U=(e,t)=>{for(var r in t||(t={}))xr.call(t,r)&&rn(e,r,t[r]);if(Ct)for(var r of Ct(t))nn.call(t,r)&&rn(e,r,t[r]);return e};var on=(e,t)=>{var r={};for(var n in e)xr.call(e,n)&&t.indexOf(n)<0&&(r[n]=e[n]);if(e!=null&&Ct)for(var n of Ct(e))t.indexOf(n)<0&&nn.call(e,n)&&(r[n]=e[n]);return r};var bt=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports);var ia=(e,t,r,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let o of na(t))!xr.call(e,o)&&o!==r&&yr(e,o,{get:()=>t[o],enumerable:!(n=ra(t,o))||n.enumerable});return e};var Ye=(e,t,r)=>(r=e!=null?ta(oa(e)):{},ia(t||!e||!e.__esModule?yr(r,"default",{value:e,enumerable:!0}):r,e));var sn=bt((Sr,an)=>{(function(e,t){typeof Sr=="object"&&typeof an!="undefined"?t():typeof define=="function"&&define.amd?define(t):t()})(Sr,function(){"use strict";function e(r){var n=!0,o=!1,i=null,a={text:!0,search:!0,url:!0,tel:!0,email:!0,password:!0,number:!0,date:!0,month:!0,week:!0,time:!0,datetime:!0,"datetime-local":!0};function s(w){return!!(w&&w!==document&&w.nodeName!=="HTML"&&w.nodeName!=="BODY"&&"classList"in w&&"contains"in w.classList)}function c(w){var Ue=w.type,ke=w.tagName;return!!(ke==="INPUT"&&a[Ue]&&!w.readOnly||ke==="TEXTAREA"&&!w.readOnly||w.isContentEditable)}function u(w){w.classList.contains("focus-visible")||(w.classList.add("focus-visible"),w.setAttribute("data-focus-visible-added",""))}function f(w){!w.hasAttribute("data-focus-visible-added")||(w.classList.remove("focus-visible"),w.removeAttribute("data-focus-visible-added"))}function p(w){w.metaKey||w.altKey||w.ctrlKey||(s(r.activeElement)&&u(r.activeElement),n=!0)}function l(w){n=!1}function d(w){!s(w.target)||(n||c(w.target))&&u(w.target)}function h(w){!s(w.target)||(w.target.classList.contains("focus-visible")||w.target.hasAttribute("data-focus-visible-added"))&&(o=!0,window.clearTimeout(i),i=window.setTimeout(function(){o=!1},100),f(w.target))}function b(w){document.visibilityState==="hidden"&&(o&&(n=!0),F())}function F(){document.addEventListener("mousemove",W),document.addEventListener("mousedown",W),document.addEventListener("mouseup",W),document.addEventListener("pointermove",W),document.addEventListener("pointerdown",W),document.addEventListener("pointerup",W),document.addEventListener("touchmove",W),document.addEventListener("touchstart",W),document.addEventListener("touchend",W)}function B(){document.removeEventListener("mousemove",W),document.removeEventListener("mousedown",W),document.removeEventListener("mouseup",W),document.removeEventListener("pointermove",W),document.removeEventListener("pointerdown",W),document.removeEventListener("pointerup",W),document.removeEventListener("touchmove",W),document.removeEventListener("touchstart",W),document.removeEventListener("touchend",W)}function W(w){w.target.nodeName&&w.target.nodeName.toLowerCase()==="html"||(n=!1,B())}document.addEventListener("keydown",p,!0),document.addEventListener("mousedown",l,!0),document.addEventListener("pointerdown",l,!0),document.addEventListener("touchstart",l,!0),document.addEventListener("visibilitychange",b,!0),F(),r.addEventListener("focus",d,!0),r.addEventListener("blur",h,!0),r.nodeType===Node.DOCUMENT_FRAGMENT_NODE&&r.host?r.host.setAttribute("data-js-focus-visible",""):r.nodeType===Node.DOCUMENT_NODE&&(document.documentElement.classList.add("js-focus-visible"),document.documentElement.setAttribute("data-js-focus-visible",""))}if(typeof window!="undefined"&&typeof document!="undefined"){window.applyFocusVisiblePolyfill=e;var t;try{t=new CustomEvent("focus-visible-polyfill-ready")}catch(r){t=document.createEvent("CustomEvent"),t.initCustomEvent("focus-visible-polyfill-ready",!1,!1,{})}window.dispatchEvent(t)}typeof document!="undefined"&&e(document)})});var cn=bt(wr=>{(function(e){var t=function(){try{return!!Symbol.iterator}catch(u){return!1}},r=t(),n=function(u){var f={next:function(){var p=u.shift();return{done:p===void 0,value:p}}};return r&&(f[Symbol.iterator]=function(){return f}),f},o=function(u){return encodeURIComponent(u).replace(/%20/g,"+")},i=function(u){return decodeURIComponent(String(u).replace(/\+/g," "))},a=function(){var u=function(p){Object.defineProperty(this,"_entries",{writable:!0,value:{}});var l=typeof p;if(l!=="undefined")if(l==="string")p!==""&&this._fromString(p);else if(p instanceof u){var d=this;p.forEach(function(B,W){d.append(W,B)})}else if(p!==null&&l==="object")if(Object.prototype.toString.call(p)==="[object Array]")for(var h=0;h<p.length;h++){var b=p[h];if(Object.prototype.toString.call(b)==="[object Array]"||b.length!==2)this.append(b[0],b[1]);else throw new TypeError("Expected [string, any] as entry at index "+h+" of URLSearchParams's input")}else for(var F in p)p.hasOwnProperty(F)&&this.append(F,p[F]);else throw new TypeError("Unsupported input's type for URLSearchParams")},f=u.prototype;f.append=function(p,l){p in this._entries?this._entries[p].push(String(l)):this._entries[p]=[String(l)]},f.delete=function(p){delete this._entries[p]},f.get=function(p){return p in this._entries?this._entries[p][0]:null},f.getAll=function(p){return p in this._entries?this._entries[p].slice(0):[]},f.has=function(p){return p in this._entries},f.set=function(p,l){this._entries[p]=[String(l)]},f.forEach=function(p,l){var d;for(var h in this._entries)if(this._entries.hasOwnProperty(h)){d=this._entries[h];for(var b=0;b<d.length;b++)p.call(l,d[b],h,this)}},f.keys=function(){var p=[];return this.forEach(function(l,d){p.push(d)}),n(p)},f.values=function(){var p=[];return this.forEach(function(l){p.push(l)}),n(p)},f.entries=function(){var p=[];return this.forEach(function(l,d){p.push([d,l])}),n(p)},r&&(f[Symbol.iterator]=f.entries),f.toString=function(){var p=[];return this.forEach(function(l,d){p.push(o(d)+"="+o(l))}),p.join("&")},e.URLSearchParams=u},s=function(){try{var u=e.URLSearchParams;return new u("?a=1").toString()==="a=1"&&typeof u.prototype.set=="function"&&typeof u.prototype.entries=="function"}catch(f){return!1}};s()||a();var c=e.URLSearchParams.prototype;typeof c.sort!="function"&&(c.sort=function(){var u=this,f=[];this.forEach(function(l,d){f.push([d,l]),u._entries||u.delete(d)}),f.sort(function(l,d){return l[0]<d[0]?-1:l[0]>d[0]?1:0}),u._entries&&(u._entries={});for(var p=0;p<f.length;p++)this.append(f[p][0],f[p][1])}),typeof c._fromString!="function"&&Object.defineProperty(c,"_fromString",{enumerable:!1,configurable:!1,writable:!1,value:function(u){if(this._entries)this._entries={};else{var f=[];this.forEach(function(h,b){f.push(b)});for(var p=0;p<f.length;p++)this.delete(f[p])}u=u.replace(/^\?/,"");for(var l=u.split("&"),d,p=0;p<l.length;p++)d=l[p].split("="),this.append(i(d[0]),d.length>1?i(d[1]):"")}})})(typeof global!="undefined"?global:typeof window!="undefined"?window:typeof self!="undefined"?self:wr);(function(e){var t=function(){try{var o=new e.URL("b","http://a");return o.pathname="c d",o.href==="http://a/c%20d"&&o.searchParams}catch(i){return!1}},r=function(){var o=e.URL,i=function(c,u){typeof c!="string"&&(c=String(c)),u&&typeof u!="string"&&(u=String(u));var f=document,p;if(u&&(e.location===void 0||u!==e.location.href)){u=u.toLowerCase(),f=document.implementation.createHTMLDocument(""),p=f.createElement("base"),p.href=u,f.head.appendChild(p);try{if(p.href.indexOf(u)!==0)throw new Error(p.href)}catch(w){throw new Error("URL unable to set base "+u+" due to "+w)}}var l=f.createElement("a");l.href=c,p&&(f.body.appendChild(l),l.href=l.href);var d=f.createElement("input");if(d.type="url",d.value=c,l.protocol===":"||!/:/.test(l.href)||!d.checkValidity()&&!u)throw new TypeError("Invalid URL");Object.defineProperty(this,"_anchorElement",{value:l});var h=new e.URLSearchParams(this.search),b=!0,F=!0,B=this;["append","delete","set"].forEach(function(w){var Ue=h[w];h[w]=function(){Ue.apply(h,arguments),b&&(F=!1,B.search=h.toString(),F=!0)}}),Object.defineProperty(this,"searchParams",{value:h,enumerable:!0});var W=void 0;Object.defineProperty(this,"_updateSearchParams",{enumerable:!1,configurable:!1,writable:!1,value:function(){this.search!==W&&(W=this.search,F&&(b=!1,this.searchParams._fromString(this.search),b=!0))}})},a=i.prototype,s=function(c){Object.defineProperty(a,c,{get:function(){return this._anchorElement[c]},set:function(u){this._anchorElement[c]=u},enumerable:!0})};["hash","host","hostname","port","protocol"].forEach(function(c){s(c)}),Object.defineProperty(a,"search",{get:function(){return this._anchorElement.search},set:function(c){this._anchorElement.search=c,this._updateSearchParams()},enumerable:!0}),Object.defineProperties(a,{toString:{get:function(){var c=this;return function(){return c.href}}},href:{get:function(){return this._anchorElement.href.replace(/\?$/,"")},set:function(c){this._anchorElement.href=c,this._updateSearchParams()},enumerable:!0},pathname:{get:function(){return this._anchorElement.pathname.replace(/(^\/?)/,"/")},set:function(c){this._anchorElement.pathname=c},enumerable:!0},origin:{get:function(){var c={"http:":80,"https:":443,"ftp:":21}[this._anchorElement.protocol],u=this._anchorElement.port!=c&&this._anchorElement.port!=="";return this._anchorElement.protocol+"//"+this._anchorElement.hostname+(u?":"+this._anchorElement.port:"")},enumerable:!0},password:{get:function(){return""},set:function(c){},enumerable:!0},username:{get:function(){return""},set:function(c){},enumerable:!0}}),i.createObjectURL=function(c){return o.createObjectURL.apply(o,arguments)},i.revokeObjectURL=function(c){return o.revokeObjectURL.apply(o,arguments)},e.URL=i};if(t()||r(),e.location!==void 0&&!("origin"in e.location)){var n=function(){return e.location.protocol+"//"+e.location.hostname+(e.location.port?":"+e.location.port:"")};try{Object.defineProperty(e.location,"origin",{get:n,enumerable:!0})}catch(o){setInterval(function(){e.location.origin=n()},100)}}})(typeof global!="undefined"?global:typeof window!="undefined"?window:typeof self!="undefined"?self:wr)});var An=bt((Us,Ht)=>{/*! *****************************************************************************
-Copyright (c) Microsoft Corporation.
-
-Permission to use, copy, modify, and/or distribute this software for any
-purpose with or without fee is hereby granted.
-
-THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
-REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
-AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
-INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
-LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
-OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
-PERFORMANCE OF THIS SOFTWARE.
-***************************************************************************** */var un,fn,pn,ln,mn,dn,hn,bn,vn,Rt,Er,gn,yn,xn,tt,Sn,wn,En,On,_n,Tn,Mn,Ln,kt;(function(e){var t=typeof global=="object"?global:typeof self=="object"?self:typeof this=="object"?this:{};typeof define=="function"&&define.amd?define("tslib",["exports"],function(n){e(r(t,r(n)))}):typeof Ht=="object"&&typeof Ht.exports=="object"?e(r(t,r(Ht.exports))):e(r(t));function r(n,o){return n!==t&&(typeof Object.create=="function"?Object.defineProperty(n,"__esModule",{value:!0}):n.__esModule=!0),function(i,a){return n[i]=o?o(i,a):a}}})(function(e){var t=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(n,o){n.__proto__=o}||function(n,o){for(var i in o)Object.prototype.hasOwnProperty.call(o,i)&&(n[i]=o[i])};un=function(n,o){if(typeof o!="function"&&o!==null)throw new TypeError("Class extends value "+String(o)+" is not a constructor or null");t(n,o);function i(){this.constructor=n}n.prototype=o===null?Object.create(o):(i.prototype=o.prototype,new i)},fn=Object.assign||function(n){for(var o,i=1,a=arguments.length;i<a;i++){o=arguments[i];for(var s in o)Object.prototype.hasOwnProperty.call(o,s)&&(n[s]=o[s])}return n},pn=function(n,o){var i={};for(var a in n)Object.prototype.hasOwnProperty.call(n,a)&&o.indexOf(a)<0&&(i[a]=n[a]);if(n!=null&&typeof Object.getOwnPropertySymbols=="function")for(var s=0,a=Object.getOwnPropertySymbols(n);s<a.length;s++)o.indexOf(a[s])<0&&Object.prototype.propertyIsEnumerable.call(n,a[s])&&(i[a[s]]=n[a[s]]);return i},ln=function(n,o,i,a){var s=arguments.length,c=s<3?o:a===null?a=Object.getOwnPropertyDescriptor(o,i):a,u;if(typeof Reflect=="object"&&typeof Reflect.decorate=="function")c=Reflect.decorate(n,o,i,a);else for(var f=n.length-1;f>=0;f--)(u=n[f])&&(c=(s<3?u(c):s>3?u(o,i,c):u(o,i))||c);return s>3&&c&&Object.defineProperty(o,i,c),c},mn=function(n,o){return function(i,a){o(i,a,n)}},dn=function(n,o){if(typeof Reflect=="object"&&typeof Reflect.metadata=="function")return Reflect.metadata(n,o)},hn=function(n,o,i,a){function s(c){return c instanceof i?c:new i(function(u){u(c)})}return new(i||(i=Promise))(function(c,u){function f(d){try{l(a.next(d))}catch(h){u(h)}}function p(d){try{l(a.throw(d))}catch(h){u(h)}}function l(d){d.done?c(d.value):s(d.value).then(f,p)}l((a=a.apply(n,o||[])).next())})},bn=function(n,o){var i={label:0,sent:function(){if(c[0]&1)throw c[1];return c[1]},trys:[],ops:[]},a,s,c,u;return u={next:f(0),throw:f(1),return:f(2)},typeof Symbol=="function"&&(u[Symbol.iterator]=function(){return this}),u;function f(l){return function(d){return p([l,d])}}function p(l){if(a)throw new TypeError("Generator is already executing.");for(;i;)try{if(a=1,s&&(c=l[0]&2?s.return:l[0]?s.throw||((c=s.return)&&c.call(s),0):s.next)&&!(c=c.call(s,l[1])).done)return c;switch(s=0,c&&(l=[l[0]&2,c.value]),l[0]){case 0:case 1:c=l;break;case 4:return i.label++,{value:l[1],done:!1};case 5:i.label++,s=l[1],l=[0];continue;case 7:l=i.ops.pop(),i.trys.pop();continue;default:if(c=i.trys,!(c=c.length>0&&c[c.length-1])&&(l[0]===6||l[0]===2)){i=0;continue}if(l[0]===3&&(!c||l[1]>c[0]&&l[1]<c[3])){i.label=l[1];break}if(l[0]===6&&i.label<c[1]){i.label=c[1],c=l;break}if(c&&i.label<c[2]){i.label=c[2],i.ops.push(l);break}c[2]&&i.ops.pop(),i.trys.pop();continue}l=o.call(n,i)}catch(d){l=[6,d],s=0}finally{a=c=0}if(l[0]&5)throw l[1];return{value:l[0]?l[1]:void 0,done:!0}}},vn=function(n,o){for(var i in n)i!=="default"&&!Object.prototype.hasOwnProperty.call(o,i)&&kt(o,n,i)},kt=Object.create?function(n,o,i,a){a===void 0&&(a=i),Object.defineProperty(n,a,{enumerable:!0,get:function(){return o[i]}})}:function(n,o,i,a){a===void 0&&(a=i),n[a]=o[i]},Rt=function(n){var o=typeof Symbol=="function"&&Symbol.iterator,i=o&&n[o],a=0;if(i)return i.call(n);if(n&&typeof n.length=="number")return{next:function(){return n&&a>=n.length&&(n=void 0),{value:n&&n[a++],done:!n}}};throw new TypeError(o?"Object is not iterable.":"Symbol.iterator is not defined.")},Er=function(n,o){var i=typeof Symbol=="function"&&n[Symbol.iterator];if(!i)return n;var a=i.call(n),s,c=[],u;try{for(;(o===void 0||o-- >0)&&!(s=a.next()).done;)c.push(s.value)}catch(f){u={error:f}}finally{try{s&&!s.done&&(i=a.return)&&i.call(a)}finally{if(u)throw u.error}}return c},gn=function(){for(var n=[],o=0;o<arguments.length;o++)n=n.concat(Er(arguments[o]));return n},yn=function(){for(var n=0,o=0,i=arguments.length;o<i;o++)n+=arguments[o].length;for(var a=Array(n),s=0,o=0;o<i;o++)for(var c=arguments[o],u=0,f=c.length;u<f;u++,s++)a[s]=c[u];return a},xn=function(n,o,i){if(i||arguments.length===2)for(var a=0,s=o.length,c;a<s;a++)(c||!(a in o))&&(c||(c=Array.prototype.slice.call(o,0,a)),c[a]=o[a]);return n.concat(c||Array.prototype.slice.call(o))},tt=function(n){return this instanceof tt?(this.v=n,this):new tt(n)},Sn=function(n,o,i){if(!Symbol.asyncIterator)throw new TypeError("Symbol.asyncIterator is not defined.");var a=i.apply(n,o||[]),s,c=[];return s={},u("next"),u("throw"),u("return"),s[Symbol.asyncIterator]=function(){return this},s;function u(b){a[b]&&(s[b]=function(F){return new Promise(function(B,W){c.push([b,F,B,W])>1||f(b,F)})})}function f(b,F){try{p(a[b](F))}catch(B){h(c[0][3],B)}}function p(b){b.value instanceof tt?Promise.resolve(b.value.v).then(l,d):h(c[0][2],b)}function l(b){f("next",b)}function d(b){f("throw",b)}function h(b,F){b(F),c.shift(),c.length&&f(c[0][0],c[0][1])}},wn=function(n){var o,i;return o={},a("next"),a("throw",function(s){throw s}),a("return"),o[Symbol.iterator]=function(){return this},o;function a(s,c){o[s]=n[s]?function(u){return(i=!i)?{value:tt(n[s](u)),done:s==="return"}:c?c(u):u}:c}},En=function(n){if(!Symbol.asyncIterator)throw new TypeError("Symbol.asyncIterator is not defined.");var o=n[Symbol.asyncIterator],i;return o?o.call(n):(n=typeof Rt=="function"?Rt(n):n[Symbol.iterator](),i={},a("next"),a("throw"),a("return"),i[Symbol.asyncIterator]=function(){return this},i);function a(c){i[c]=n[c]&&function(u){return new Promise(function(f,p){u=n[c](u),s(f,p,u.done,u.value)})}}function s(c,u,f,p){Promise.resolve(p).then(function(l){c({value:l,done:f})},u)}},On=function(n,o){return Object.defineProperty?Object.defineProperty(n,"raw",{value:o}):n.raw=o,n};var r=Object.create?function(n,o){Object.defineProperty(n,"default",{enumerable:!0,value:o})}:function(n,o){n.default=o};_n=function(n){if(n&&n.__esModule)return n;var o={};if(n!=null)for(var i in n)i!=="default"&&Object.prototype.hasOwnProperty.call(n,i)&&kt(o,n,i);return r(o,n),o},Tn=function(n){return n&&n.__esModule?n:{default:n}},Mn=function(n,o,i,a){if(i==="a"&&!a)throw new TypeError("Private accessor was defined without a getter");if(typeof o=="function"?n!==o||!a:!o.has(n))throw new TypeError("Cannot read private member from an object whose class did not declare it");return i==="m"?a:i==="a"?a.call(n):a?a.value:o.get(n)},Ln=function(n,o,i,a,s){if(a==="m")throw new TypeError("Private method is not writable");if(a==="a"&&!s)throw new TypeError("Private accessor was defined without a setter");if(typeof o=="function"?n!==o||!s:!o.has(n))throw new TypeError("Cannot write private member to an object whose class did not declare it");return a==="a"?s.call(n,i):s?s.value=i:o.set(n,i),i},e("__extends",un),e("__assign",fn),e("__rest",pn),e("__decorate",ln),e("__param",mn),e("__metadata",dn),e("__awaiter",hn),e("__generator",bn),e("__exportStar",vn),e("__createBinding",kt),e("__values",Rt),e("__read",Er),e("__spread",gn),e("__spreadArrays",yn),e("__spreadArray",xn),e("__await",tt),e("__asyncGenerator",Sn),e("__asyncDelegator",wn),e("__asyncValues",En),e("__makeTemplateObject",On),e("__importStar",_n),e("__importDefault",Tn),e("__classPrivateFieldGet",Mn),e("__classPrivateFieldSet",Ln)})});var Qr=bt((Tt,qr)=>{/*!
- * clipboard.js v2.0.11
- * https://clipboardjs.com/
- *
- * Licensed MIT © Zeno Rocha
- */(function(t,r){typeof Tt=="object"&&typeof qr=="object"?qr.exports=r():typeof define=="function"&&define.amd?define([],r):typeof Tt=="object"?Tt.ClipboardJS=r():t.ClipboardJS=r()})(Tt,function(){return function(){var e={686:function(n,o,i){"use strict";i.d(o,{default:function(){return ea}});var a=i(279),s=i.n(a),c=i(370),u=i.n(c),f=i(817),p=i.n(f);function l(I){try{return document.execCommand(I)}catch(E){return!1}}var d=function(E){var S=p()(E);return l("cut"),S},h=d;function b(I){var E=document.documentElement.getAttribute("dir")==="rtl",S=document.createElement("textarea");S.style.fontSize="12pt",S.style.border="0",S.style.padding="0",S.style.margin="0",S.style.position="absolute",S.style[E?"right":"left"]="-9999px";var R=window.pageYOffset||document.documentElement.scrollTop;return S.style.top="".concat(R,"px"),S.setAttribute("readonly",""),S.value=I,S}var F=function(E,S){var R=b(E);S.container.appendChild(R);var H=p()(R);return l("copy"),R.remove(),H},B=function(E){var S=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{container:document.body},R="";return typeof E=="string"?R=F(E,S):E instanceof HTMLInputElement&&!["text","search","url","tel","password"].includes(E==null?void 0:E.type)?R=F(E.value,S):(R=p()(E),l("copy")),R},W=B;function w(I){return typeof Symbol=="function"&&typeof Symbol.iterator=="symbol"?w=function(S){return typeof S}:w=function(S){return S&&typeof Symbol=="function"&&S.constructor===Symbol&&S!==Symbol.prototype?"symbol":typeof S},w(I)}var Ue=function(){var E=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{},S=E.action,R=S===void 0?"copy":S,H=E.container,z=E.target,Ee=E.text;if(R!=="copy"&&R!=="cut")throw new Error('Invalid "action" value, use either "copy" or "cut"');if(z!==void 0)if(z&&w(z)==="object"&&z.nodeType===1){if(R==="copy"&&z.hasAttribute("disabled"))throw new Error('Invalid "target" attribute. Please use "readonly" instead of "disabled" attribute');if(R==="cut"&&(z.hasAttribute("readonly")||z.hasAttribute("disabled")))throw new Error(`Invalid "target" attribute. You can't cut text from elements with "readonly" or "disabled" attributes`)}else throw new Error('Invalid "target" value, use a valid Element');if(Ee)return W(Ee,{container:H});if(z)return R==="cut"?h(z):W(z,{container:H})},ke=Ue;function Le(I){return typeof Symbol=="function"&&typeof Symbol.iterator=="symbol"?Le=function(S){return typeof S}:Le=function(S){return S&&typeof Symbol=="function"&&S.constructor===Symbol&&S!==Symbol.prototype?"symbol":typeof S},Le(I)}function Qi(I,E){if(!(I instanceof E))throw new TypeError("Cannot call a class as a function")}function tn(I,E){for(var S=0;S<E.length;S++){var R=E[S];R.enumerable=R.enumerable||!1,R.configurable=!0,"value"in R&&(R.writable=!0),Object.defineProperty(I,R.key,R)}}function Yi(I,E,S){return E&&tn(I.prototype,E),S&&tn(I,S),I}function Ki(I,E){if(typeof E!="function"&&E!==null)throw new TypeError("Super expression must either be null or a function");I.prototype=Object.create(E&&E.prototype,{constructor:{value:I,writable:!0,configurable:!0}}),E&&vr(I,E)}function vr(I,E){return vr=Object.setPrototypeOf||function(R,H){return R.__proto__=H,R},vr(I,E)}function Bi(I){var E=Xi();return function(){var R=Lt(I),H;if(E){var z=Lt(this).constructor;H=Reflect.construct(R,arguments,z)}else H=R.apply(this,arguments);return Gi(this,H)}}function Gi(I,E){return E&&(Le(E)==="object"||typeof E=="function")?E:Ji(I)}function Ji(I){if(I===void 0)throw new ReferenceError("this hasn't been initialised - super() hasn't been called");return I}function Xi(){if(typeof Reflect=="undefined"||!Reflect.construct||Reflect.construct.sham)return!1;if(typeof Proxy=="function")return!0;try{return Date.prototype.toString.call(Reflect.construct(Date,[],function(){})),!0}catch(I){return!1}}function Lt(I){return Lt=Object.setPrototypeOf?Object.getPrototypeOf:function(S){return S.__proto__||Object.getPrototypeOf(S)},Lt(I)}function gr(I,E){var S="data-clipboard-".concat(I);if(!!E.hasAttribute(S))return E.getAttribute(S)}var Zi=function(I){Ki(S,I);var E=Bi(S);function S(R,H){var z;return Qi(this,S),z=E.call(this),z.resolveOptions(H),z.listenClick(R),z}return Yi(S,[{key:"resolveOptions",value:function(){var H=arguments.length>0&&arguments[0]!==void 0?arguments[0]:{};this.action=typeof H.action=="function"?H.action:this.defaultAction,this.target=typeof H.target=="function"?H.target:this.defaultTarget,this.text=typeof H.text=="function"?H.text:this.defaultText,this.container=Le(H.container)==="object"?H.container:document.body}},{key:"listenClick",value:function(H){var z=this;this.listener=u()(H,"click",function(Ee){return z.onClick(Ee)})}},{key:"onClick",value:function(H){var z=H.delegateTarget||H.currentTarget,Ee=this.action(z)||"copy",At=ke({action:Ee,container:this.container,target:this.target(z),text:this.text(z)});this.emit(At?"success":"error",{action:Ee,text:At,trigger:z,clearSelection:function(){z&&z.focus(),window.getSelection().removeAllRanges()}})}},{key:"defaultAction",value:function(H){return gr("action",H)}},{key:"defaultTarget",value:function(H){var z=gr("target",H);if(z)return document.querySelector(z)}},{key:"defaultText",value:function(H){return gr("text",H)}},{key:"destroy",value:function(){this.listener.destroy()}}],[{key:"copy",value:function(H){var z=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{container:document.body};return W(H,z)}},{key:"cut",value:function(H){return h(H)}},{key:"isSupported",value:function(){var H=arguments.length>0&&arguments[0]!==void 0?arguments[0]:["copy","cut"],z=typeof H=="string"?[H]:H,Ee=!!document.queryCommandSupported;return z.forEach(function(At){Ee=Ee&&!!document.queryCommandSupported(At)}),Ee}}]),S}(s()),ea=Zi},828:function(n){var o=9;if(typeof Element!="undefined"&&!Element.prototype.matches){var i=Element.prototype;i.matches=i.matchesSelector||i.mozMatchesSelector||i.msMatchesSelector||i.oMatchesSelector||i.webkitMatchesSelector}function a(s,c){for(;s&&s.nodeType!==o;){if(typeof s.matches=="function"&&s.matches(c))return s;s=s.parentNode}}n.exports=a},438:function(n,o,i){var a=i(828);function s(f,p,l,d,h){var b=u.apply(this,arguments);return f.addEventListener(l,b,h),{destroy:function(){f.removeEventListener(l,b,h)}}}function c(f,p,l,d,h){return typeof f.addEventListener=="function"?s.apply(null,arguments):typeof l=="function"?s.bind(null,document).apply(null,arguments):(typeof f=="string"&&(f=document.querySelectorAll(f)),Array.prototype.map.call(f,function(b){return s(b,p,l,d,h)}))}function u(f,p,l,d){return function(h){h.delegateTarget=a(h.target,p),h.delegateTarget&&d.call(f,h)}}n.exports=c},879:function(n,o){o.node=function(i){return i!==void 0&&i instanceof HTMLElement&&i.nodeType===1},o.nodeList=function(i){var a=Object.prototype.toString.call(i);return i!==void 0&&(a==="[object NodeList]"||a==="[object HTMLCollection]")&&"length"in i&&(i.length===0||o.node(i[0]))},o.string=function(i){return typeof i=="string"||i instanceof String},o.fn=function(i){var a=Object.prototype.toString.call(i);return a==="[object Function]"}},370:function(n,o,i){var a=i(879),s=i(438);function c(l,d,h){if(!l&&!d&&!h)throw new Error("Missing required arguments");if(!a.string(d))throw new TypeError("Second argument must be a String");if(!a.fn(h))throw new TypeError("Third argument must be a Function");if(a.node(l))return u(l,d,h);if(a.nodeList(l))return f(l,d,h);if(a.string(l))return p(l,d,h);throw new TypeError("First argument must be a String, HTMLElement, HTMLCollection, or NodeList")}function u(l,d,h){return l.addEventListener(d,h),{destroy:function(){l.removeEventListener(d,h)}}}function f(l,d,h){return Array.prototype.forEach.call(l,function(b){b.addEventListener(d,h)}),{destroy:function(){Array.prototype.forEach.call(l,function(b){b.removeEventListener(d,h)})}}}function p(l,d,h){return s(document.body,l,d,h)}n.exports=c},817:function(n){function o(i){var a;if(i.nodeName==="SELECT")i.focus(),a=i.value;else if(i.nodeName==="INPUT"||i.nodeName==="TEXTAREA"){var s=i.hasAttribute("readonly");s||i.setAttribute("readonly",""),i.select(),i.setSelectionRange(0,i.value.length),s||i.removeAttribute("readonly"),a=i.value}else{i.hasAttribute("contenteditable")&&i.focus();var c=window.getSelection(),u=document.createRange();u.selectNodeContents(i),c.removeAllRanges(),c.addRange(u),a=c.toString()}return a}n.exports=o},279:function(n){function o(){}o.prototype={on:function(i,a,s){var c=this.e||(this.e={});return(c[i]||(c[i]=[])).push({fn:a,ctx:s}),this},once:function(i,a,s){var c=this;function u(){c.off(i,u),a.apply(s,arguments)}return u._=a,this.on(i,u,s)},emit:function(i){var a=[].slice.call(arguments,1),s=((this.e||(this.e={}))[i]||[]).slice(),c=0,u=s.length;for(c;c<u;c++)s[c].fn.apply(s[c].ctx,a);return this},off:function(i,a){var s=this.e||(this.e={}),c=s[i],u=[];if(c&&a)for(var f=0,p=c.length;f<p;f++)c[f].fn!==a&&c[f].fn._!==a&&u.push(c[f]);return u.length?s[i]=u:delete s[i],this}},n.exports=o,n.exports.TinyEmitter=o}},t={};function r(n){if(t[n])return t[n].exports;var o=t[n]={exports:{}};return e[n](o,o.exports,r),o.exports}return function(){r.n=function(n){var o=n&&n.__esModule?function(){return n.default}:function(){return n};return r.d(o,{a:o}),o}}(),function(){r.d=function(n,o){for(var i in o)r.o(o,i)&&!r.o(n,i)&&Object.defineProperty(n,i,{enumerable:!0,get:o[i]})}}(),function(){r.o=function(n,o){return Object.prototype.hasOwnProperty.call(n,o)}}(),r(686)}().default})});var Gr=bt((xS,gi)=>{"use strict";/*!
- * escape-html
- * Copyright(c) 2012-2013 TJ Holowaychuk
- * Copyright(c) 2015 Andreas Lubbe
- * Copyright(c) 2015 Tiancheng "Timothy" Gu
- * MIT Licensed
- */var xs=/["'&<>]/;gi.exports=Ss;function Ss(e){var t=""+e,r=xs.exec(t);if(!r)return t;var n,o="",i=0,a=0;for(i=r.index;i<t.length;i++){switch(t.charCodeAt(i)){case 34:n="&quot;";break;case 38:n="&amp;";break;case 39:n="&#39;";break;case 60:n="&lt;";break;case 62:n="&gt;";break;default:continue}a!==i&&(o+=t.substring(a,i)),a=i+1,o+=n}return a!==i?o+t.substring(a,i):o}});Array.prototype.flat||Object.defineProperty(Array.prototype,"flat",{configurable:!0,value:function e(){var t=isNaN(arguments[0])?1:Number(arguments[0]);return t?Array.prototype.reduce.call(this,function(r,n){return Array.isArray(n)?r.push.apply(r,e.call(n,t-1)):r.push(n),r},[]):Array.prototype.slice.call(this)},writable:!0}),Array.prototype.flatMap||Object.defineProperty(Array.prototype,"flatMap",{configurable:!0,value:function(e){return Array.prototype.map.apply(this,arguments).flat()},writable:!0});var n_=Ye(sn());self.fetch||(self.fetch=function(e,t){return t=t||{},new Promise(function(r,n){var o=new XMLHttpRequest,i=[],a=[],s={},c=function(){return{ok:(o.status/100|0)==2,statusText:o.statusText,status:o.status,url:o.responseURL,text:function(){return Promise.resolve(o.responseText)},json:function(){return Promise.resolve(o.responseText).then(JSON.parse)},blob:function(){return Promise.resolve(new Blob([o.response]))},clone:c,headers:{keys:function(){return i},entries:function(){return a},get:function(f){return s[f.toLowerCase()]},has:function(f){return f.toLowerCase()in s}}}};for(var u in o.open(t.method||"get",e,!0),o.onload=function(){o.getAllResponseHeaders().replace(/^(.*?):[^\S\n]*([\s\S]*?)$/gm,function(f,p,l){i.push(p=p.toLowerCase()),a.push([p,l]),s[p]=s[p]?s[p]+","+l:l}),r(c())},o.onerror=n,o.withCredentials=t.credentials=="include",t.headers)o.setRequestHeader(u,t.headers[u]);o.send(t.body||null)})});var i_=Ye(cn());var Cn=Ye(An(),1),{__extends:ee,__assign:Ds,__rest:Ws,__decorate:Vs,__param:Ns,__metadata:zs,__awaiter:Rn,__generator:Pt,__exportStar:qs,__createBinding:Qs,__values:he,__read:D,__spread:Ys,__spreadArrays:Ks,__spreadArray:V,__await:It,__asyncGenerator:kn,__asyncDelegator:Bs,__asyncValues:Hn,__makeTemplateObject:Gs,__importStar:Js,__importDefault:Xs,__classPrivateFieldGet:Zs,__classPrivateFieldSet:ec}=Cn.default;function T(e){return typeof e=="function"}function $t(e){var t=function(n){Error.call(n),n.stack=new Error().stack},r=e(t);return r.prototype=Object.create(Error.prototype),r.prototype.constructor=r,r}var jt=$t(function(e){return function(r){e(this),this.message=r?r.length+` errors occurred during unsubscription:
-`+r.map(function(n,o){return o+1+") "+n.toString()}).join(`
-  `):"",this.name="UnsubscriptionError",this.errors=r}});function He(e,t){if(e){var r=e.indexOf(t);0<=r&&e.splice(r,1)}}var Ae=function(){function e(t){this.initialTeardown=t,this.closed=!1,this._parentage=null,this._finalizers=null}return e.prototype.unsubscribe=function(){var t,r,n,o,i;if(!this.closed){this.closed=!0;var a=this._parentage;if(a)if(this._parentage=null,Array.isArray(a))try{for(var s=he(a),c=s.next();!c.done;c=s.next()){var u=c.value;u.remove(this)}}catch(b){t={error:b}}finally{try{c&&!c.done&&(r=s.return)&&r.call(s)}finally{if(t)throw t.error}}else a.remove(this);var f=this.initialTeardown;if(T(f))try{f()}catch(b){i=b instanceof jt?b.errors:[b]}var p=this._finalizers;if(p){this._finalizers=null;try{for(var l=he(p),d=l.next();!d.done;d=l.next()){var h=d.value;try{Pn(h)}catch(b){i=i!=null?i:[],b instanceof jt?i=V(V([],D(i)),D(b.errors)):i.push(b)}}}catch(b){n={error:b}}finally{try{d&&!d.done&&(o=l.return)&&o.call(l)}finally{if(n)throw n.error}}}if(i)throw new jt(i)}},e.prototype.add=function(t){var r;if(t&&t!==this)if(this.closed)Pn(t);else{if(t instanceof e){if(t.closed||t._hasParent(this))return;t._addParent(this)}(this._finalizers=(r=this._finalizers)!==null&&r!==void 0?r:[]).push(t)}},e.prototype._hasParent=function(t){var r=this._parentage;return r===t||Array.isArray(r)&&r.includes(t)},e.prototype._addParent=function(t){var r=this._parentage;this._parentage=Array.isArray(r)?(r.push(t),r):r?[r,t]:t},e.prototype._removeParent=function(t){var r=this._parentage;r===t?this._parentage=null:Array.isArray(r)&&He(r,t)},e.prototype.remove=function(t){var r=this._finalizers;r&&He(r,t),t instanceof e&&t._removeParent(this)},e.EMPTY=function(){var t=new e;return t.closed=!0,t}(),e}();var Or=Ae.EMPTY;function Ft(e){return e instanceof Ae||e&&"closed"in e&&T(e.remove)&&T(e.add)&&T(e.unsubscribe)}function Pn(e){T(e)?e():e.unsubscribe()}var Oe={onUnhandledError:null,onStoppedNotification:null,Promise:void 0,useDeprecatedSynchronousErrorHandling:!1,useDeprecatedNextContext:!1};var rt={setTimeout:function(e,t){for(var r=[],n=2;n<arguments.length;n++)r[n-2]=arguments[n];var o=rt.delegate;return o!=null&&o.setTimeout?o.setTimeout.apply(o,V([e,t],D(r))):setTimeout.apply(void 0,V([e,t],D(r)))},clearTimeout:function(e){var t=rt.delegate;return((t==null?void 0:t.clearTimeout)||clearTimeout)(e)},delegate:void 0};function Ut(e){rt.setTimeout(function(){var t=Oe.onUnhandledError;if(t)t(e);else throw e})}function pe(){}var In=function(){return _r("C",void 0,void 0)}();function $n(e){return _r("E",void 0,e)}function jn(e){return _r("N",e,void 0)}function _r(e,t,r){return{kind:e,value:t,error:r}}var Ke=null;function nt(e){if(Oe.useDeprecatedSynchronousErrorHandling){var t=!Ke;if(t&&(Ke={errorThrown:!1,error:null}),e(),t){var r=Ke,n=r.errorThrown,o=r.error;if(Ke=null,n)throw o}}else e()}function Fn(e){Oe.useDeprecatedSynchronousErrorHandling&&Ke&&(Ke.errorThrown=!0,Ke.error=e)}var vt=function(e){ee(t,e);function t(r){var n=e.call(this)||this;return n.isStopped=!1,r?(n.destination=r,Ft(r)&&r.add(n)):n.destination=ua,n}return t.create=function(r,n,o){return new ot(r,n,o)},t.prototype.next=function(r){this.isStopped?Mr(jn(r),this):this._next(r)},t.prototype.error=function(r){this.isStopped?Mr($n(r),this):(this.isStopped=!0,this._error(r))},t.prototype.complete=function(){this.isStopped?Mr(In,this):(this.isStopped=!0,this._complete())},t.prototype.unsubscribe=function(){this.closed||(this.isStopped=!0,e.prototype.unsubscribe.call(this),this.destination=null)},t.prototype._next=function(r){this.destination.next(r)},t.prototype._error=function(r){try{this.destination.error(r)}finally{this.unsubscribe()}},t.prototype._complete=function(){try{this.destination.complete()}finally{this.unsubscribe()}},t}(Ae);var aa=Function.prototype.bind;function Tr(e,t){return aa.call(e,t)}var sa=function(){function e(t){this.partialObserver=t}return e.prototype.next=function(t){var r=this.partialObserver;if(r.next)try{r.next(t)}catch(n){Dt(n)}},e.prototype.error=function(t){var r=this.partialObserver;if(r.error)try{r.error(t)}catch(n){Dt(n)}else Dt(t)},e.prototype.complete=function(){var t=this.partialObserver;if(t.complete)try{t.complete()}catch(r){Dt(r)}},e}(),ot=function(e){ee(t,e);function t(r,n,o){var i=e.call(this)||this,a;if(T(r)||!r)a={next:r!=null?r:void 0,error:n!=null?n:void 0,complete:o!=null?o:void 0};else{var s;i&&Oe.useDeprecatedNextContext?(s=Object.create(r),s.unsubscribe=function(){return i.unsubscribe()},a={next:r.next&&Tr(r.next,s),error:r.error&&Tr(r.error,s),complete:r.complete&&Tr(r.complete,s)}):a=r}return i.destination=new sa(a),i}return t}(vt);function Dt(e){Oe.useDeprecatedSynchronousErrorHandling?Fn(e):Ut(e)}function ca(e){throw e}function Mr(e,t){var r=Oe.onStoppedNotification;r&&rt.setTimeout(function(){return r(e,t)})}var ua={closed:!0,next:pe,error:ca,complete:pe};var it=function(){return typeof Symbol=="function"&&Symbol.observable||"@@observable"}();function be(e){return e}function Un(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return Lr(e)}function Lr(e){return e.length===0?be:e.length===1?e[0]:function(r){return e.reduce(function(n,o){return o(n)},r)}}var $=function(){function e(t){t&&(this._subscribe=t)}return e.prototype.lift=function(t){var r=new e;return r.source=this,r.operator=t,r},e.prototype.subscribe=function(t,r,n){var o=this,i=pa(t)?t:new ot(t,r,n);return nt(function(){var a=o,s=a.operator,c=a.source;i.add(s?s.call(i,c):c?o._subscribe(i):o._trySubscribe(i))}),i},e.prototype._trySubscribe=function(t){try{return this._subscribe(t)}catch(r){t.error(r)}},e.prototype.forEach=function(t,r){var n=this;return r=Dn(r),new r(function(o,i){var a=new ot({next:function(s){try{t(s)}catch(c){i(c),a.unsubscribe()}},error:i,complete:o});n.subscribe(a)})},e.prototype._subscribe=function(t){var r;return(r=this.source)===null||r===void 0?void 0:r.subscribe(t)},e.prototype[it]=function(){return this},e.prototype.pipe=function(){for(var t=[],r=0;r<arguments.length;r++)t[r]=arguments[r];return Lr(t)(this)},e.prototype.toPromise=function(t){var r=this;return t=Dn(t),new t(function(n,o){var i;r.subscribe(function(a){return i=a},function(a){return o(a)},function(){return n(i)})})},e.create=function(t){return new e(t)},e}();function Dn(e){var t;return(t=e!=null?e:Oe.Promise)!==null&&t!==void 0?t:Promise}function fa(e){return e&&T(e.next)&&T(e.error)&&T(e.complete)}function pa(e){return e&&e instanceof vt||fa(e)&&Ft(e)}function la(e){return T(e==null?void 0:e.lift)}function v(e){return function(t){if(la(t))return t.lift(function(r){try{return e(r,this)}catch(n){this.error(n)}});throw new TypeError("Unable to lift unknown Observable type")}}function g(e,t,r,n,o){return new ma(e,t,r,n,o)}var ma=function(e){ee(t,e);function t(r,n,o,i,a,s){var c=e.call(this,r)||this;return c.onFinalize=a,c.shouldUnsubscribe=s,c._next=n?function(u){try{n(u)}catch(f){r.error(f)}}:e.prototype._next,c._error=i?function(u){try{i(u)}catch(f){r.error(f)}finally{this.unsubscribe()}}:e.prototype._error,c._complete=o?function(){try{o()}catch(u){r.error(u)}finally{this.unsubscribe()}}:e.prototype._complete,c}return t.prototype.unsubscribe=function(){var r;if(!this.shouldUnsubscribe||this.shouldUnsubscribe()){var n=this.closed;e.prototype.unsubscribe.call(this),!n&&((r=this.onFinalize)===null||r===void 0||r.call(this))}},t}(vt);var at={schedule:function(e){var t=requestAnimationFrame,r=cancelAnimationFrame,n=at.delegate;n&&(t=n.requestAnimationFrame,r=n.cancelAnimationFrame);var o=t(function(i){r=void 0,e(i)});return new Ae(function(){return r==null?void 0:r(o)})},requestAnimationFrame:function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=at.delegate;return((r==null?void 0:r.requestAnimationFrame)||requestAnimationFrame).apply(void 0,V([],D(e)))},cancelAnimationFrame:function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=at.delegate;return((r==null?void 0:r.cancelAnimationFrame)||cancelAnimationFrame).apply(void 0,V([],D(e)))},delegate:void 0};var Wn=$t(function(e){return function(){e(this),this.name="ObjectUnsubscribedError",this.message="object unsubscribed"}});var _=function(e){ee(t,e);function t(){var r=e.call(this)||this;return r.closed=!1,r.currentObservers=null,r.observers=[],r.isStopped=!1,r.hasError=!1,r.thrownError=null,r}return t.prototype.lift=function(r){var n=new Vn(this,this);return n.operator=r,n},t.prototype._throwIfClosed=function(){if(this.closed)throw new Wn},t.prototype.next=function(r){var n=this;nt(function(){var o,i;if(n._throwIfClosed(),!n.isStopped){n.currentObservers||(n.currentObservers=Array.from(n.observers));try{for(var a=he(n.currentObservers),s=a.next();!s.done;s=a.next()){var c=s.value;c.next(r)}}catch(u){o={error:u}}finally{try{s&&!s.done&&(i=a.return)&&i.call(a)}finally{if(o)throw o.error}}}})},t.prototype.error=function(r){var n=this;nt(function(){if(n._throwIfClosed(),!n.isStopped){n.hasError=n.isStopped=!0,n.thrownError=r;for(var o=n.observers;o.length;)o.shift().error(r)}})},t.prototype.complete=function(){var r=this;nt(function(){if(r._throwIfClosed(),!r.isStopped){r.isStopped=!0;for(var n=r.observers;n.length;)n.shift().complete()}})},t.prototype.unsubscribe=function(){this.isStopped=this.closed=!0,this.observers=this.currentObservers=null},Object.defineProperty(t.prototype,"observed",{get:function(){var r;return((r=this.observers)===null||r===void 0?void 0:r.length)>0},enumerable:!1,configurable:!0}),t.prototype._trySubscribe=function(r){return this._throwIfClosed(),e.prototype._trySubscribe.call(this,r)},t.prototype._subscribe=function(r){return this._throwIfClosed(),this._checkFinalizedStatuses(r),this._innerSubscribe(r)},t.prototype._innerSubscribe=function(r){var n=this,o=this,i=o.hasError,a=o.isStopped,s=o.observers;return i||a?Or:(this.currentObservers=null,s.push(r),new Ae(function(){n.currentObservers=null,He(s,r)}))},t.prototype._checkFinalizedStatuses=function(r){var n=this,o=n.hasError,i=n.thrownError,a=n.isStopped;o?r.error(i):a&&r.complete()},t.prototype.asObservable=function(){var r=new $;return r.source=this,r},t.create=function(r,n){return new Vn(r,n)},t}($);var Vn=function(e){ee(t,e);function t(r,n){var o=e.call(this)||this;return o.destination=r,o.source=n,o}return t.prototype.next=function(r){var n,o;(o=(n=this.destination)===null||n===void 0?void 0:n.next)===null||o===void 0||o.call(n,r)},t.prototype.error=function(r){var n,o;(o=(n=this.destination)===null||n===void 0?void 0:n.error)===null||o===void 0||o.call(n,r)},t.prototype.complete=function(){var r,n;(n=(r=this.destination)===null||r===void 0?void 0:r.complete)===null||n===void 0||n.call(r)},t.prototype._subscribe=function(r){var n,o;return(o=(n=this.source)===null||n===void 0?void 0:n.subscribe(r))!==null&&o!==void 0?o:Or},t}(_);var gt={now:function(){return(gt.delegate||Date).now()},delegate:void 0};var yt=function(e){ee(t,e);function t(r,n,o){r===void 0&&(r=1/0),n===void 0&&(n=1/0),o===void 0&&(o=gt);var i=e.call(this)||this;return i._bufferSize=r,i._windowTime=n,i._timestampProvider=o,i._buffer=[],i._infiniteTimeWindow=!0,i._infiniteTimeWindow=n===1/0,i._bufferSize=Math.max(1,r),i._windowTime=Math.max(1,n),i}return t.prototype.next=function(r){var n=this,o=n.isStopped,i=n._buffer,a=n._infiniteTimeWindow,s=n._timestampProvider,c=n._windowTime;o||(i.push(r),!a&&i.push(s.now()+c)),this._trimBuffer(),e.prototype.next.call(this,r)},t.prototype._subscribe=function(r){this._throwIfClosed(),this._trimBuffer();for(var n=this._innerSubscribe(r),o=this,i=o._infiniteTimeWindow,a=o._buffer,s=a.slice(),c=0;c<s.length&&!r.closed;c+=i?1:2)r.next(s[c]);return this._checkFinalizedStatuses(r),n},t.prototype._trimBuffer=function(){var r=this,n=r._bufferSize,o=r._timestampProvider,i=r._buffer,a=r._infiniteTimeWindow,s=(a?1:2)*n;if(n<1/0&&s<i.length&&i.splice(0,i.length-s),!a){for(var c=o.now(),u=0,f=1;f<i.length&&i[f]<=c;f+=2)u=f;u&&i.splice(0,u+1)}},t}(_);var Nn=function(e){ee(t,e);function t(r,n){return e.call(this)||this}return t.prototype.schedule=function(r,n){return n===void 0&&(n=0),this},t}(Ae);var xt={setInterval:function(e,t){for(var r=[],n=2;n<arguments.length;n++)r[n-2]=arguments[n];var o=xt.delegate;return o!=null&&o.setInterval?o.setInterval.apply(o,V([e,t],D(r))):setInterval.apply(void 0,V([e,t],D(r)))},clearInterval:function(e){var t=xt.delegate;return((t==null?void 0:t.clearInterval)||clearInterval)(e)},delegate:void 0};var Wt=function(e){ee(t,e);function t(r,n){var o=e.call(this,r,n)||this;return o.scheduler=r,o.work=n,o.pending=!1,o}return t.prototype.schedule=function(r,n){if(n===void 0&&(n=0),this.closed)return this;this.state=r;var o=this.id,i=this.scheduler;return o!=null&&(this.id=this.recycleAsyncId(i,o,n)),this.pending=!0,this.delay=n,this.id=this.id||this.requestAsyncId(i,this.id,n),this},t.prototype.requestAsyncId=function(r,n,o){return o===void 0&&(o=0),xt.setInterval(r.flush.bind(r,this),o)},t.prototype.recycleAsyncId=function(r,n,o){if(o===void 0&&(o=0),o!=null&&this.delay===o&&this.pending===!1)return n;xt.clearInterval(n)},t.prototype.execute=function(r,n){if(this.closed)return new Error("executing a cancelled action");this.pending=!1;var o=this._execute(r,n);if(o)return o;this.pending===!1&&this.id!=null&&(this.id=this.recycleAsyncId(this.scheduler,this.id,null))},t.prototype._execute=function(r,n){var o=!1,i;try{this.work(r)}catch(a){o=!0,i=a||new Error("Scheduled action threw falsy error")}if(o)return this.unsubscribe(),i},t.prototype.unsubscribe=function(){if(!this.closed){var r=this,n=r.id,o=r.scheduler,i=o.actions;this.work=this.state=this.scheduler=null,this.pending=!1,He(i,this),n!=null&&(this.id=this.recycleAsyncId(o,n,null)),this.delay=null,e.prototype.unsubscribe.call(this)}},t}(Nn);var Ar=function(){function e(t,r){r===void 0&&(r=e.now),this.schedulerActionCtor=t,this.now=r}return e.prototype.schedule=function(t,r,n){return r===void 0&&(r=0),new this.schedulerActionCtor(this,t).schedule(n,r)},e.now=gt.now,e}();var Vt=function(e){ee(t,e);function t(r,n){n===void 0&&(n=Ar.now);var o=e.call(this,r,n)||this;return o.actions=[],o._active=!1,o._scheduled=void 0,o}return t.prototype.flush=function(r){var n=this.actions;if(this._active){n.push(r);return}var o;this._active=!0;do if(o=r.execute(r.state,r.delay))break;while(r=n.shift());if(this._active=!1,o){for(;r=n.shift();)r.unsubscribe();throw o}},t}(Ar);var ue=new Vt(Wt),Cr=ue;var zn=function(e){ee(t,e);function t(r,n){var o=e.call(this,r,n)||this;return o.scheduler=r,o.work=n,o}return t.prototype.requestAsyncId=function(r,n,o){return o===void 0&&(o=0),o!==null&&o>0?e.prototype.requestAsyncId.call(this,r,n,o):(r.actions.push(this),r._scheduled||(r._scheduled=at.requestAnimationFrame(function(){return r.flush(void 0)})))},t.prototype.recycleAsyncId=function(r,n,o){if(o===void 0&&(o=0),o!=null&&o>0||o==null&&this.delay>0)return e.prototype.recycleAsyncId.call(this,r,n,o);r.actions.some(function(i){return i.id===n})||(at.cancelAnimationFrame(n),r._scheduled=void 0)},t}(Wt);var qn=function(e){ee(t,e);function t(){return e!==null&&e.apply(this,arguments)||this}return t.prototype.flush=function(r){this._active=!0;var n=this._scheduled;this._scheduled=void 0;var o=this.actions,i;r=r||o.shift();do if(i=r.execute(r.state,r.delay))break;while((r=o[0])&&r.id===n&&o.shift());if(this._active=!1,i){for(;(r=o[0])&&r.id===n&&o.shift();)r.unsubscribe();throw i}},t}(Vt);var _e=new qn(zn);var k=new $(function(e){return e.complete()});function Nt(e){return e&&T(e.schedule)}function Rr(e){return e[e.length-1]}function De(e){return T(Rr(e))?e.pop():void 0}function ge(e){return Nt(Rr(e))?e.pop():void 0}function zt(e,t){return typeof Rr(e)=="number"?e.pop():t}var st=function(e){return e&&typeof e.length=="number"&&typeof e!="function"};function qt(e){return T(e==null?void 0:e.then)}function Qt(e){return T(e[it])}function Yt(e){return Symbol.asyncIterator&&T(e==null?void 0:e[Symbol.asyncIterator])}function Kt(e){return new TypeError("You provided "+(e!==null&&typeof e=="object"?"an invalid object":"'"+e+"'")+" where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.")}function da(){return typeof Symbol!="function"||!Symbol.iterator?"@@iterator":Symbol.iterator}var Bt=da();function Gt(e){return T(e==null?void 0:e[Bt])}function Jt(e){return kn(this,arguments,function(){var r,n,o,i;return Pt(this,function(a){switch(a.label){case 0:r=e.getReader(),a.label=1;case 1:a.trys.push([1,,9,10]),a.label=2;case 2:return[4,It(r.read())];case 3:return n=a.sent(),o=n.value,i=n.done,i?[4,It(void 0)]:[3,5];case 4:return[2,a.sent()];case 5:return[4,It(o)];case 6:return[4,a.sent()];case 7:return a.sent(),[3,2];case 8:return[3,10];case 9:return r.releaseLock(),[7];case 10:return[2]}})})}function Xt(e){return T(e==null?void 0:e.getReader)}function N(e){if(e instanceof $)return e;if(e!=null){if(Qt(e))return ha(e);if(st(e))return ba(e);if(qt(e))return va(e);if(Yt(e))return Qn(e);if(Gt(e))return ga(e);if(Xt(e))return ya(e)}throw Kt(e)}function ha(e){return new $(function(t){var r=e[it]();if(T(r.subscribe))return r.subscribe(t);throw new TypeError("Provided object does not correctly implement Symbol.observable")})}function ba(e){return new $(function(t){for(var r=0;r<e.length&&!t.closed;r++)t.next(e[r]);t.complete()})}function va(e){return new $(function(t){e.then(function(r){t.closed||(t.next(r),t.complete())},function(r){return t.error(r)}).then(null,Ut)})}function ga(e){return new $(function(t){var r,n;try{for(var o=he(e),i=o.next();!i.done;i=o.next()){var a=i.value;if(t.next(a),t.closed)return}}catch(s){r={error:s}}finally{try{i&&!i.done&&(n=o.return)&&n.call(o)}finally{if(r)throw r.error}}t.complete()})}function Qn(e){return new $(function(t){xa(e,t).catch(function(r){return t.error(r)})})}function ya(e){return Qn(Jt(e))}function xa(e,t){var r,n,o,i;return Rn(this,void 0,void 0,function(){var a,s;return Pt(this,function(c){switch(c.label){case 0:c.trys.push([0,5,6,11]),r=Hn(e),c.label=1;case 1:return[4,r.next()];case 2:if(n=c.sent(),!!n.done)return[3,4];if(a=n.value,t.next(a),t.closed)return[2];c.label=3;case 3:return[3,1];case 4:return[3,11];case 5:return s=c.sent(),o={error:s},[3,11];case 6:return c.trys.push([6,,9,10]),n&&!n.done&&(i=r.return)?[4,i.call(r)]:[3,8];case 7:c.sent(),c.label=8;case 8:return[3,10];case 9:if(o)throw o.error;return[7];case 10:return[7];case 11:return t.complete(),[2]}})})}function me(e,t,r,n,o){n===void 0&&(n=0),o===void 0&&(o=!1);var i=t.schedule(function(){r(),o?e.add(this.schedule(null,n)):this.unsubscribe()},n);if(e.add(i),!o)return i}function Pe(e,t){return t===void 0&&(t=0),v(function(r,n){r.subscribe(g(n,function(o){return me(n,e,function(){return n.next(o)},t)},function(){return me(n,e,function(){return n.complete()},t)},function(o){return me(n,e,function(){return n.error(o)},t)}))})}function Be(e,t){return t===void 0&&(t=0),v(function(r,n){n.add(e.schedule(function(){return r.subscribe(n)},t))})}function Yn(e,t){return N(e).pipe(Be(t),Pe(t))}function Kn(e,t){return N(e).pipe(Be(t),Pe(t))}function Bn(e,t){return new $(function(r){var n=0;return t.schedule(function(){n===e.length?r.complete():(r.next(e[n++]),r.closed||this.schedule())})})}function Gn(e,t){return new $(function(r){var n;return me(r,t,function(){n=e[Bt](),me(r,t,function(){var o,i,a;try{o=n.next(),i=o.value,a=o.done}catch(s){r.error(s);return}a?r.complete():r.next(i)},0,!0)}),function(){return T(n==null?void 0:n.return)&&n.return()}})}function Zt(e,t){if(!e)throw new Error("Iterable cannot be null");return new $(function(r){me(r,t,function(){var n=e[Symbol.asyncIterator]();me(r,t,function(){n.next().then(function(o){o.done?r.complete():r.next(o.value)})},0,!0)})})}function Jn(e,t){return Zt(Jt(e),t)}function Xn(e,t){if(e!=null){if(Qt(e))return Yn(e,t);if(st(e))return Bn(e,t);if(qt(e))return Kn(e,t);if(Yt(e))return Zt(e,t);if(Gt(e))return Gn(e,t);if(Xt(e))return Jn(e,t)}throw Kt(e)}function re(e,t){return t?Xn(e,t):N(e)}function P(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=ge(e);return re(e,r)}function St(e,t){var r=T(e)?e:function(){return e},n=function(o){return o.error(r())};return new $(t?function(o){return t.schedule(n,0,o)}:n)}function Zn(e){return e instanceof Date&&!isNaN(e)}function m(e,t){return v(function(r,n){var o=0;r.subscribe(g(n,function(i){n.next(e.call(t,i,o++))}))})}var Sa=Array.isArray;function wa(e,t){return Sa(t)?e.apply(void 0,V([],D(t))):e(t)}function We(e){return m(function(t){return wa(e,t)})}var Ea=Array.isArray,Oa=Object.getPrototypeOf,_a=Object.prototype,Ta=Object.keys;function eo(e){if(e.length===1){var t=e[0];if(Ea(t))return{args:t,keys:null};if(Ma(t)){var r=Ta(t);return{args:r.map(function(n){return t[n]}),keys:r}}}return{args:e,keys:null}}function Ma(e){return e&&typeof e=="object"&&Oa(e)===_a}function to(e,t){return e.reduce(function(r,n,o){return r[n]=t[o],r},{})}function Y(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=ge(e),n=De(e),o=eo(e),i=o.args,a=o.keys;if(i.length===0)return re([],r);var s=new $(kr(i,r,a?function(c){return to(a,c)}:be));return n?s.pipe(We(n)):s}function kr(e,t,r){return r===void 0&&(r=be),function(n){ro(t,function(){for(var o=e.length,i=new Array(o),a=o,s=o,c=function(f){ro(t,function(){var p=re(e[f],t),l=!1;p.subscribe(g(n,function(d){i[f]=d,l||(l=!0,s--),s||n.next(r(i.slice()))},function(){--a||n.complete()}))},n)},u=0;u<o;u++)c(u)},n)}}function ro(e,t,r){e?me(r,e,t):t()}function no(e,t,r,n,o,i,a,s){var c=[],u=0,f=0,p=!1,l=function(){p&&!c.length&&!u&&t.complete()},d=function(b){return u<n?h(b):c.push(b)},h=function(b){i&&t.next(b),u++;var F=!1;N(r(b,f++)).subscribe(g(t,function(B){o==null||o(B),i?d(B):t.next(B)},function(){F=!0},void 0,function(){if(F)try{u--;for(var B=function(){var W=c.shift();a?me(t,a,function(){return h(W)}):h(W)};c.length&&u<n;)B();l()}catch(W){t.error(W)}}))};return e.subscribe(g(t,d,function(){p=!0,l()})),function(){s==null||s()}}function oe(e,t,r){return r===void 0&&(r=1/0),T(t)?oe(function(n,o){return m(function(i,a){return t(n,i,o,a)})(N(e(n,o)))},r):(typeof t=="number"&&(r=t),v(function(n,o){return no(n,o,e,r)}))}function ct(e){return e===void 0&&(e=1/0),oe(be,e)}function oo(){return ct(1)}function Ge(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return oo()(re(e,ge(e)))}function j(e){return new $(function(t){N(e()).subscribe(t)})}var La=["addListener","removeListener"],Aa=["addEventListener","removeEventListener"],Ca=["on","off"];function y(e,t,r,n){if(T(r)&&(n=r,r=void 0),n)return y(e,t,r).pipe(We(n));var o=D(Ha(e)?Aa.map(function(s){return function(c){return e[s](t,c,r)}}):Ra(e)?La.map(io(e,t)):ka(e)?Ca.map(io(e,t)):[],2),i=o[0],a=o[1];if(!i&&st(e))return oe(function(s){return y(s,t,r)})(N(e));if(!i)throw new TypeError("Invalid event target");return new $(function(s){var c=function(){for(var u=[],f=0;f<arguments.length;f++)u[f]=arguments[f];return s.next(1<u.length?u:u[0])};return i(c),function(){return a(c)}})}function io(e,t){return function(r){return function(n){return e[r](t,n)}}}function Ra(e){return T(e.addListener)&&T(e.removeListener)}function ka(e){return T(e.on)&&T(e.off)}function Ha(e){return T(e.addEventListener)&&T(e.removeEventListener)}function er(e,t,r){return r?er(e,t).pipe(We(r)):new $(function(n){var o=function(){for(var a=[],s=0;s<arguments.length;s++)a[s]=arguments[s];return n.next(a.length===1?a[0]:a)},i=e(o);return T(t)?function(){return t(o,i)}:void 0})}function Ve(e,t,r){e===void 0&&(e=0),r===void 0&&(r=Cr);var n=-1;return t!=null&&(Nt(t)?r=t:n=t),new $(function(o){var i=Zn(e)?+e-r.now():e;i<0&&(i=0);var a=0;return r.schedule(function(){o.closed||(o.next(a++),0<=n?this.schedule(void 0,n):o.complete())},i)})}function C(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=ge(e),n=zt(e,1/0),o=e;return o.length?o.length===1?N(o[0]):ct(n)(re(o,r)):k}var ye=new $(pe);var Pa=Array.isArray;function ut(e){return e.length===1&&Pa(e[0])?e[0]:e}function M(e,t){return v(function(r,n){var o=0;r.subscribe(g(n,function(i){return e.call(t,i,o++)&&n.next(i)}))})}function wt(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=De(e),n=ut(e);return n.length?new $(function(o){var i=n.map(function(){return[]}),a=n.map(function(){return!1});o.add(function(){i=a=null});for(var s=function(u){N(n[u]).subscribe(g(o,function(f){if(i[u].push(f),i.every(function(l){return l.length})){var p=i.map(function(l){return l.shift()});o.next(r?r.apply(void 0,V([],D(p))):p),i.some(function(l,d){return!l.length&&a[d]})&&o.complete()}},function(){a[u]=!0,!i[u].length&&o.complete()}))},c=0;!o.closed&&c<n.length;c++)s(c);return function(){i=a=null}}):k}function ao(e){return v(function(t,r){var n=!1,o=null,i=null,a=!1,s=function(){if(i==null||i.unsubscribe(),i=null,n){n=!1;var u=o;o=null,r.next(u)}a&&r.complete()},c=function(){i=null,a&&r.complete()};t.subscribe(g(r,function(u){n=!0,o=u,i||N(e(u)).subscribe(i=g(r,s,c))},function(){a=!0,(!n||!i||i.closed)&&r.complete()}))})}function Ie(e,t){return t===void 0&&(t=ue),ao(function(){return Ve(e,t)})}function Te(e,t){return t===void 0&&(t=null),t=t!=null?t:e,v(function(r,n){var o=[],i=0;r.subscribe(g(n,function(a){var s,c,u,f,p=null;i++%t===0&&o.push([]);try{for(var l=he(o),d=l.next();!d.done;d=l.next()){var h=d.value;h.push(a),e<=h.length&&(p=p!=null?p:[],p.push(h))}}catch(B){s={error:B}}finally{try{d&&!d.done&&(c=l.return)&&c.call(l)}finally{if(s)throw s.error}}if(p)try{for(var b=he(p),F=b.next();!F.done;F=b.next()){var h=F.value;He(o,h),n.next(h)}}catch(B){u={error:B}}finally{try{F&&!F.done&&(f=b.return)&&f.call(b)}finally{if(u)throw u.error}}},function(){var a,s;try{for(var c=he(o),u=c.next();!u.done;u=c.next()){var f=u.value;n.next(f)}}catch(p){a={error:p}}finally{try{u&&!u.done&&(s=c.return)&&s.call(c)}finally{if(a)throw a.error}}n.complete()},void 0,function(){o=null}))})}function ie(e){return v(function(t,r){var n=null,o=!1,i;n=t.subscribe(g(r,void 0,void 0,function(a){i=N(e(a,ie(e)(t))),n?(n.unsubscribe(),n=null,i.subscribe(r)):o=!0})),o&&(n.unsubscribe(),n=null,i.subscribe(r))})}function so(e,t,r,n,o){return function(i,a){var s=r,c=t,u=0;i.subscribe(g(a,function(f){var p=u++;c=s?e(c,f,p):(s=!0,f),n&&a.next(c)},o&&function(){s&&a.next(c),a.complete()}))}}function Hr(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=De(e);return r?Un(Hr.apply(void 0,V([],D(e))),We(r)):v(function(n,o){kr(V([n],D(ut(e))))(o)})}function Je(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return Hr.apply(void 0,V([],D(e)))}function Pr(e,t){return T(t)?oe(e,t,1):oe(e,1)}function Xe(e,t){return t===void 0&&(t=ue),v(function(r,n){var o=null,i=null,a=null,s=function(){if(o){o.unsubscribe(),o=null;var u=i;i=null,n.next(u)}};function c(){var u=a+e,f=t.now();if(f<u){o=this.schedule(void 0,u-f),n.add(o);return}s()}r.subscribe(g(n,function(u){i=u,a=t.now(),o||(o=t.schedule(c,e),n.add(o))},function(){s(),n.complete()},void 0,function(){i=o=null}))})}function $e(e){return v(function(t,r){var n=!1;t.subscribe(g(r,function(o){n=!0,r.next(o)},function(){n||r.next(e),r.complete()}))})}function te(e){return e<=0?function(){return k}:v(function(t,r){var n=0;t.subscribe(g(r,function(o){++n<=e&&(r.next(o),e<=n&&r.complete())}))})}function co(){return v(function(e,t){e.subscribe(g(t,pe))})}function uo(e){return m(function(){return e})}function Ir(e,t){return t?function(r){return Ge(t.pipe(te(1),co()),r.pipe(Ir(e)))}:oe(function(r,n){return e(r,n).pipe(te(1),uo(r))})}function je(e,t){t===void 0&&(t=ue);var r=Ve(e,t);return Ir(function(){return r})}function K(e,t){return t===void 0&&(t=be),e=e!=null?e:Ia,v(function(r,n){var o,i=!0;r.subscribe(g(n,function(a){var s=t(a);(i||!e(o,s))&&(i=!1,o=s,n.next(a))}))})}function Ia(e,t){return e===t}function J(e,t){return K(function(r,n){return t?t(r[e],n[e]):r[e]===n[e]})}function tr(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return function(r){return Ge(r,P.apply(void 0,V([],D(e))))}}function L(e){return v(function(t,r){try{t.subscribe(r)}finally{r.add(e)}})}function le(e){return e<=0?function(){return k}:v(function(t,r){var n=[];t.subscribe(g(r,function(o){n.push(o),e<n.length&&n.shift()},function(){var o,i;try{for(var a=he(n),s=a.next();!s.done;s=a.next()){var c=s.value;r.next(c)}}catch(u){o={error:u}}finally{try{s&&!s.done&&(i=a.return)&&i.call(a)}finally{if(o)throw o.error}}r.complete()},void 0,function(){n=null}))})}function fo(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=ge(e),n=zt(e,1/0);return e=ut(e),v(function(o,i){ct(n)(re(V([o],D(e)),r)).subscribe(i)})}function Ze(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return fo.apply(void 0,V([],D(e)))}function Et(e){var t,r=1/0,n;return e!=null&&(typeof e=="object"?(t=e.count,r=t===void 0?1/0:t,n=e.delay):r=e),r<=0?function(){return k}:v(function(o,i){var a=0,s,c=function(){if(s==null||s.unsubscribe(),s=null,n!=null){var f=typeof n=="number"?Ve(n):N(n(a)),p=g(i,function(){p.unsubscribe(),u()});f.subscribe(p)}else u()},u=function(){var f=!1;s=o.subscribe(g(i,void 0,function(){++a<r?s?c():f=!0:i.complete()})),f&&c()};u()})}function ft(e){return v(function(t,r){var n=!1,o=null;t.subscribe(g(r,function(i){n=!0,o=i})),e.subscribe(g(r,function(){if(n){n=!1;var i=o;o=null,r.next(i)}},pe))})}function $r(e,t){return v(so(e,t,arguments.length>=2,!0))}function ae(e){e===void 0&&(e={});var t=e.connector,r=t===void 0?function(){return new _}:t,n=e.resetOnError,o=n===void 0?!0:n,i=e.resetOnComplete,a=i===void 0?!0:i,s=e.resetOnRefCountZero,c=s===void 0?!0:s;return function(u){var f=null,p=null,l=null,d=0,h=!1,b=!1,F=function(){p==null||p.unsubscribe(),p=null},B=function(){F(),f=l=null,h=b=!1},W=function(){var w=f;B(),w==null||w.unsubscribe()};return v(function(w,Ue){d++,!b&&!h&&F();var ke=l=l!=null?l:r();Ue.add(function(){d--,d===0&&!b&&!h&&(p=jr(W,c))}),ke.subscribe(Ue),f||(f=new ot({next:function(Le){return ke.next(Le)},error:function(Le){b=!0,F(),p=jr(B,o,Le),ke.error(Le)},complete:function(){h=!0,F(),p=jr(B,a),ke.complete()}}),re(w).subscribe(f))})(u)}}function jr(e,t){for(var r=[],n=2;n<arguments.length;n++)r[n-2]=arguments[n];return t===!0?(e(),null):t===!1?null:t.apply(void 0,V([],D(r))).pipe(te(1)).subscribe(function(){return e()})}function X(e,t,r){var n,o,i,a,s=!1;return e&&typeof e=="object"?(n=e.bufferSize,a=n===void 0?1/0:n,o=e.windowTime,t=o===void 0?1/0:o,i=e.refCount,s=i===void 0?!1:i,r=e.scheduler):a=e!=null?e:1/0,ae({connector:function(){return new yt(a,t,r)},resetOnError:!0,resetOnComplete:!1,resetOnRefCountZero:s})}function Fe(e){return M(function(t,r){return e<=r})}function Ot(e){return v(function(t,r){var n=!1,o=g(r,function(){o==null||o.unsubscribe(),n=!0},pe);N(e).subscribe(o),t.subscribe(g(r,function(i){return n&&r.next(i)}))})}function q(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=ge(e);return v(function(n,o){(r?Ge(e,n,r):Ge(e,n)).subscribe(o)})}function x(e,t){return v(function(r,n){var o=null,i=0,a=!1,s=function(){return a&&!o&&n.complete()};r.subscribe(g(n,function(c){o==null||o.unsubscribe();var u=0,f=i++;N(e(c,f)).subscribe(o=g(n,function(p){return n.next(t?t(c,p,f,u++):p)},function(){o=null,s()}))},function(){a=!0,s()}))})}function se(e){return v(function(t,r){N(e).subscribe(g(r,function(){return r.complete()},pe)),!r.closed&&t.subscribe(r)})}function Fr(e,t){return t===void 0&&(t=!1),v(function(r,n){var o=0;r.subscribe(g(n,function(i){var a=e(i,o++);(a||t)&&n.next(i),!a&&n.complete()}))})}function O(e,t,r){var n=T(e)||t||r?{next:e,error:t,complete:r}:e;return n?v(function(o,i){var a;(a=n.subscribe)===null||a===void 0||a.call(n);var s=!0;o.subscribe(g(i,function(c){var u;(u=n.next)===null||u===void 0||u.call(n,c),i.next(c)},function(){var c;s=!1,(c=n.complete)===null||c===void 0||c.call(n),i.complete()},function(c){var u;s=!1,(u=n.error)===null||u===void 0||u.call(n,c),i.error(c)},function(){var c,u;s&&((c=n.unsubscribe)===null||c===void 0||c.call(n)),(u=n.finalize)===null||u===void 0||u.call(n)}))}):be}var Ur={leading:!0,trailing:!1};function _t(e,t){return t===void 0&&(t=Ur),v(function(r,n){var o=t.leading,i=t.trailing,a=!1,s=null,c=null,u=!1,f=function(){c==null||c.unsubscribe(),c=null,i&&(d(),u&&n.complete())},p=function(){c=null,u&&n.complete()},l=function(h){return c=N(e(h)).subscribe(g(n,f,p))},d=function(){if(a){a=!1;var h=s;s=null,n.next(h),!u&&l(h)}};r.subscribe(g(n,function(h){a=!0,s=h,!(c&&!c.closed)&&(o?d():l(h))},function(){u=!0,!(i&&a&&c&&!c.closed)&&n.complete()}))})}function Dr(e,t,r){t===void 0&&(t=ue),r===void 0&&(r=Ur);var n=Ve(e,t);return _t(function(){return n},r)}function Me(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];var r=De(e);return v(function(n,o){for(var i=e.length,a=new Array(i),s=e.map(function(){return!1}),c=!1,u=function(p){N(e[p]).subscribe(g(o,function(l){a[p]=l,!c&&!s[p]&&(s[p]=!0,(c=s.every(be))&&(s=null))},pe))},f=0;f<i;f++)u(f);n.subscribe(g(o,function(p){if(c){var l=V([p],D(a));o.next(r?r.apply(void 0,V([],D(l))):l)}}))})}function po(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return v(function(r,n){wt.apply(void 0,V([r],D(e))).subscribe(n)})}function Wr(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t];return po.apply(void 0,V([],D(e)))}function lo(){let e=new yt(1);return y(document,"DOMContentLoaded",{once:!0}).subscribe(()=>e.next(document)),e}function G(e,t=document){return Array.from(t.querySelectorAll(e))}function Q(e,t=document){let r=fe(e,t);if(typeof r=="undefined")throw new ReferenceError(`Missing element: expected "${e}" to be present`);return r}function fe(e,t=document){return t.querySelector(e)||void 0}function Ne(){return document.activeElement instanceof HTMLElement&&document.activeElement||void 0}function rr(e){return C(y(document.body,"focusin"),y(document.body,"focusout")).pipe(Xe(1),m(()=>{let t=Ne();return typeof t!="undefined"?e.contains(t):!1}),q(e===Ne()),K())}function ze(e){return{x:e.offsetLeft,y:e.offsetTop}}function mo(e){return C(y(window,"load"),y(window,"resize")).pipe(Ie(0,_e),m(()=>ze(e)),q(ze(e)))}function ho(e){return{x:e.scrollLeft,y:e.scrollTop}}function nr(e){return C(y(e,"scroll"),y(window,"resize")).pipe(Ie(0,_e),m(()=>ho(e)),q(ho(e)))}var vo=function(){if(typeof Map!="undefined")return Map;function e(t,r){var n=-1;return t.some(function(o,i){return o[0]===r?(n=i,!0):!1}),n}return function(){function t(){this.__entries__=[]}return Object.defineProperty(t.prototype,"size",{get:function(){return this.__entries__.length},enumerable:!0,configurable:!0}),t.prototype.get=function(r){var n=e(this.__entries__,r),o=this.__entries__[n];return o&&o[1]},t.prototype.set=function(r,n){var o=e(this.__entries__,r);~o?this.__entries__[o][1]=n:this.__entries__.push([r,n])},t.prototype.delete=function(r){var n=this.__entries__,o=e(n,r);~o&&n.splice(o,1)},t.prototype.has=function(r){return!!~e(this.__entries__,r)},t.prototype.clear=function(){this.__entries__.splice(0)},t.prototype.forEach=function(r,n){n===void 0&&(n=null);for(var o=0,i=this.__entries__;o<i.length;o++){var a=i[o];r.call(n,a[1],a[0])}},t}()}(),Vr=typeof window!="undefined"&&typeof document!="undefined"&&window.document===document,or=function(){return typeof global!="undefined"&&global.Math===Math?global:typeof self!="undefined"&&self.Math===Math?self:typeof window!="undefined"&&window.Math===Math?window:Function("return this")()}(),$a=function(){return typeof requestAnimationFrame=="function"?requestAnimationFrame.bind(or):function(e){return setTimeout(function(){return e(Date.now())},1e3/60)}}(),ja=2;function Fa(e,t){var r=!1,n=!1,o=0;function i(){r&&(r=!1,e()),n&&s()}function a(){$a(i)}function s(){var c=Date.now();if(r){if(c-o<ja)return;n=!0}else r=!0,n=!1,setTimeout(a,t);o=c}return s}var Ua=20,Da=["top","right","bottom","left","width","height","size","weight"],Wa=typeof MutationObserver!="undefined",Va=function(){function e(){this.connected_=!1,this.mutationEventsAdded_=!1,this.mutationsObserver_=null,this.observers_=[],this.onTransitionEnd_=this.onTransitionEnd_.bind(this),this.refresh=Fa(this.refresh.bind(this),Ua)}return e.prototype.addObserver=function(t){~this.observers_.indexOf(t)||this.observers_.push(t),this.connected_||this.connect_()},e.prototype.removeObserver=function(t){var r=this.observers_,n=r.indexOf(t);~n&&r.splice(n,1),!r.length&&this.connected_&&this.disconnect_()},e.prototype.refresh=function(){var t=this.updateObservers_();t&&this.refresh()},e.prototype.updateObservers_=function(){var t=this.observers_.filter(function(r){return r.gatherActive(),r.hasActive()});return t.forEach(function(r){return r.broadcastActive()}),t.length>0},e.prototype.connect_=function(){!Vr||this.connected_||(document.addEventListener("transitionend",this.onTransitionEnd_),window.addEventListener("resize",this.refresh),Wa?(this.mutationsObserver_=new MutationObserver(this.refresh),this.mutationsObserver_.observe(document,{attributes:!0,childList:!0,characterData:!0,subtree:!0})):(document.addEventListener("DOMSubtreeModified",this.refresh),this.mutationEventsAdded_=!0),this.connected_=!0)},e.prototype.disconnect_=function(){!Vr||!this.connected_||(document.removeEventListener("transitionend",this.onTransitionEnd_),window.removeEventListener("resize",this.refresh),this.mutationsObserver_&&this.mutationsObserver_.disconnect(),this.mutationEventsAdded_&&document.removeEventListener("DOMSubtreeModified",this.refresh),this.mutationsObserver_=null,this.mutationEventsAdded_=!1,this.connected_=!1)},e.prototype.onTransitionEnd_=function(t){var r=t.propertyName,n=r===void 0?"":r,o=Da.some(function(i){return!!~n.indexOf(i)});o&&this.refresh()},e.getInstance=function(){return this.instance_||(this.instance_=new e),this.instance_},e.instance_=null,e}(),go=function(e,t){for(var r=0,n=Object.keys(t);r<n.length;r++){var o=n[r];Object.defineProperty(e,o,{value:t[o],enumerable:!1,writable:!1,configurable:!0})}return e},pt=function(e){var t=e&&e.ownerDocument&&e.ownerDocument.defaultView;return t||or},yo=ar(0,0,0,0);function ir(e){return parseFloat(e)||0}function bo(e){for(var t=[],r=1;r<arguments.length;r++)t[r-1]=arguments[r];return t.reduce(function(n,o){var i=e["border-"+o+"-width"];return n+ir(i)},0)}function Na(e){for(var t=["top","right","bottom","left"],r={},n=0,o=t;n<o.length;n++){var i=o[n],a=e["padding-"+i];r[i]=ir(a)}return r}function za(e){var t=e.getBBox();return ar(0,0,t.width,t.height)}function qa(e){var t=e.clientWidth,r=e.clientHeight;if(!t&&!r)return yo;var n=pt(e).getComputedStyle(e),o=Na(n),i=o.left+o.right,a=o.top+o.bottom,s=ir(n.width),c=ir(n.height);if(n.boxSizing==="border-box"&&(Math.round(s+i)!==t&&(s-=bo(n,"left","right")+i),Math.round(c+a)!==r&&(c-=bo(n,"top","bottom")+a)),!Ya(e)){var u=Math.round(s+i)-t,f=Math.round(c+a)-r;Math.abs(u)!==1&&(s-=u),Math.abs(f)!==1&&(c-=f)}return ar(o.left,o.top,s,c)}var Qa=function(){return typeof SVGGraphicsElement!="undefined"?function(e){return e instanceof pt(e).SVGGraphicsElement}:function(e){return e instanceof pt(e).SVGElement&&typeof e.getBBox=="function"}}();function Ya(e){return e===pt(e).document.documentElement}function Ka(e){return Vr?Qa(e)?za(e):qa(e):yo}function Ba(e){var t=e.x,r=e.y,n=e.width,o=e.height,i=typeof DOMRectReadOnly!="undefined"?DOMRectReadOnly:Object,a=Object.create(i.prototype);return go(a,{x:t,y:r,width:n,height:o,top:r,right:t+n,bottom:o+r,left:t}),a}function ar(e,t,r,n){return{x:e,y:t,width:r,height:n}}var Ga=function(){function e(t){this.broadcastWidth=0,this.broadcastHeight=0,this.contentRect_=ar(0,0,0,0),this.target=t}return e.prototype.isActive=function(){var t=Ka(this.target);return this.contentRect_=t,t.width!==this.broadcastWidth||t.height!==this.broadcastHeight},e.prototype.broadcastRect=function(){var t=this.contentRect_;return this.broadcastWidth=t.width,this.broadcastHeight=t.height,t},e}(),Ja=function(){function e(t,r){var n=Ba(r);go(this,{target:t,contentRect:n})}return e}(),Xa=function(){function e(t,r,n){if(this.activeObservations_=[],this.observations_=new vo,typeof t!="function")throw new TypeError("The callback provided as parameter 1 is not a function.");this.callback_=t,this.controller_=r,this.callbackCtx_=n}return e.prototype.observe=function(t){if(!arguments.length)throw new TypeError("1 argument required, but only 0 present.");if(!(typeof Element=="undefined"||!(Element instanceof Object))){if(!(t instanceof pt(t).Element))throw new TypeError('parameter 1 is not of type "Element".');var r=this.observations_;r.has(t)||(r.set(t,new Ga(t)),this.controller_.addObserver(this),this.controller_.refresh())}},e.prototype.unobserve=function(t){if(!arguments.length)throw new TypeError("1 argument required, but only 0 present.");if(!(typeof Element=="undefined"||!(Element instanceof Object))){if(!(t instanceof pt(t).Element))throw new TypeError('parameter 1 is not of type "Element".');var r=this.observations_;!r.has(t)||(r.delete(t),r.size||this.controller_.removeObserver(this))}},e.prototype.disconnect=function(){this.clearActive(),this.observations_.clear(),this.controller_.removeObserver(this)},e.prototype.gatherActive=function(){var t=this;this.clearActive(),this.observations_.forEach(function(r){r.isActive()&&t.activeObservations_.push(r)})},e.prototype.broadcastActive=function(){if(!!this.hasActive()){var t=this.callbackCtx_,r=this.activeObservations_.map(function(n){return new Ja(n.target,n.broadcastRect())});this.callback_.call(t,r,t),this.clearActive()}},e.prototype.clearActive=function(){this.activeObservations_.splice(0)},e.prototype.hasActive=function(){return this.activeObservations_.length>0},e}(),xo=typeof WeakMap!="undefined"?new WeakMap:new vo,So=function(){function e(t){if(!(this instanceof e))throw new TypeError("Cannot call a class as a function.");if(!arguments.length)throw new TypeError("1 argument required, but only 0 present.");var r=Va.getInstance(),n=new Xa(t,r,this);xo.set(this,n)}return e}();["observe","unobserve","disconnect"].forEach(function(e){So.prototype[e]=function(){var t;return(t=xo.get(this))[e].apply(t,arguments)}});var Za=function(){return typeof or.ResizeObserver!="undefined"?or.ResizeObserver:So}(),wo=Za;var Eo=new _,es=j(()=>P(new wo(e=>{for(let t of e)Eo.next(t)}))).pipe(x(e=>C(ye,P(e)).pipe(L(()=>e.disconnect()))),X(1));function Ce(e){return{width:e.offsetWidth,height:e.offsetHeight}}function ve(e){return es.pipe(O(t=>t.observe(e)),x(t=>Eo.pipe(M(({target:r})=>r===e),L(()=>t.unobserve(e)),m(()=>Ce(e)))),q(Ce(e)))}function sr(e){return{width:e.scrollWidth,height:e.scrollHeight}}var Oo=new _,ts=j(()=>P(new IntersectionObserver(e=>{for(let t of e)Oo.next(t)},{threshold:0}))).pipe(x(e=>C(ye,P(e)).pipe(L(()=>e.disconnect()))),X(1));function _o(e){return ts.pipe(O(t=>t.observe(e)),x(t=>Oo.pipe(M(({target:r})=>r===e),L(()=>t.unobserve(e)),m(({isIntersecting:r})=>r))))}function To(e,t=16){return nr(e).pipe(m(({y:r})=>{let n=Ce(e),o=sr(e);return r>=o.height-n.height-t}),K())}var cr={drawer:Q("[data-md-toggle=drawer]"),search:Q("[data-md-toggle=search]")};function Mo(e){return cr[e].checked}function qe(e,t){cr[e].checked!==t&&cr[e].click()}function lt(e){let t=cr[e];return y(t,"change").pipe(m(()=>t.checked),q(t.checked))}function rs(e,t){switch(e.constructor){case HTMLInputElement:return e.type==="radio"?/^Arrow/.test(t):!0;case HTMLSelectElement:case HTMLTextAreaElement:return!0;default:return e.isContentEditable}}function Lo(){return y(window,"keydown").pipe(M(e=>!(e.metaKey||e.ctrlKey)),m(e=>({mode:Mo("search")?"search":"global",type:e.key,claim(){e.preventDefault(),e.stopPropagation()}})),M(({mode:e,type:t})=>{if(e==="global"){let r=Ne();if(typeof r!="undefined")return!rs(r,t)}return!0}),ae())}function xe(){return new URL(location.href)}function ur(e){location.href=e.href}function Ao(){return new _}function Co(e,t){if(typeof t=="string"||typeof t=="number")e.innerHTML+=t.toString();else if(t instanceof Node)e.appendChild(t);else if(Array.isArray(t))for(let r of t)Co(e,r)}function A(e,t,...r){let n=document.createElement(e);if(t)for(let o of Object.keys(t))typeof t[o]!="boolean"?n.setAttribute(o,t[o]):t[o]&&n.setAttribute(o,"");for(let o of r)Co(n,o);return n}function Ro(e,t){let r=t;if(e.length>r){for(;e[r]!==" "&&--r>0;);return`${e.substring(0,r)}...`}return e}function fr(e){if(e>999){let t=+((e-950)%1e3>99);return`${((e+1e-6)/1e3).toFixed(t)}k`}else return e.toString()}function ko(){return location.hash.substring(1)}function Ho(e){let t=A("a",{href:e});t.addEventListener("click",r=>r.stopPropagation()),t.click()}function ns(){return y(window,"hashchange").pipe(m(ko),q(ko()),M(e=>e.length>0),X(1))}function Po(){return ns().pipe(m(e=>fe(`[id="${e}"]`)),M(e=>typeof e!="undefined"))}function Nr(e){let t=matchMedia(e);return er(r=>t.addListener(()=>r(t.matches))).pipe(q(t.matches))}function Io(){let e=matchMedia("print");return C(y(window,"beforeprint").pipe(m(()=>!0)),y(window,"afterprint").pipe(m(()=>!1))).pipe(q(e.matches))}function zr(e,t){return e.pipe(x(r=>r?t():k))}function pr(e,t={credentials:"same-origin"}){return re(fetch(`${e}`,t)).pipe(ie(()=>k),x(r=>r.status!==200?St(()=>new Error(r.statusText)):P(r)))}function Re(e,t){return pr(e,t).pipe(x(r=>r.json()),X(1))}function $o(e,t){let r=new DOMParser;return pr(e,t).pipe(x(n=>n.text()),m(n=>r.parseFromString(n,"text/xml")),X(1))}function jo(e){let t=A("script",{src:e});return j(()=>(document.head.appendChild(t),C(y(t,"load"),y(t,"error").pipe(x(()=>St(()=>new ReferenceError(`Invalid script: ${e}`))))).pipe(m(()=>{}),L(()=>document.head.removeChild(t)),te(1))))}function Fo(){return{x:Math.max(0,scrollX),y:Math.max(0,scrollY)}}function Uo(){return C(y(window,"scroll",{passive:!0}),y(window,"resize",{passive:!0})).pipe(m(Fo),q(Fo()))}function Do(){return{width:innerWidth,height:innerHeight}}function Wo(){return y(window,"resize",{passive:!0}).pipe(m(Do),q(Do()))}function Vo(){return Y([Uo(),Wo()]).pipe(m(([e,t])=>({offset:e,size:t})),X(1))}function lr(e,{viewport$:t,header$:r}){let n=t.pipe(J("size")),o=Y([n,r]).pipe(m(()=>ze(e)));return Y([r,t,o]).pipe(m(([{height:i},{offset:a,size:s},{x:c,y:u}])=>({offset:{x:a.x-c,y:a.y-u+i},size:s})))}function No(e,{tx$:t}){let r=y(e,"message").pipe(m(({data:n})=>n));return t.pipe(_t(()=>r,{leading:!0,trailing:!0}),O(n=>e.postMessage(n)),x(()=>r),ae())}var os=Q("#__config"),mt=JSON.parse(os.textContent);mt.base=`${new URL(mt.base,xe())}`;function de(){return mt}function ce(e){return mt.features.includes(e)}function Z(e,t){return typeof t!="undefined"?mt.translations[e].replace("#",t.toString()):mt.translations[e]}function Se(e,t=document){return Q(`[data-md-component=${e}]`,t)}function ne(e,t=document){return G(`[data-md-component=${e}]`,t)}var ei=Ye(Qr());function zo(e){return A("aside",{class:"md-annotation",tabIndex:0},A("div",{class:"md-annotation__inner md-tooltip"},A("div",{class:"md-tooltip__inner md-typeset"})),A("span",{class:"md-annotation__index"},A("span",{"data-md-annotation-id":e})))}function qo(e){return A("button",{class:"md-clipboard md-icon",title:Z("clipboard.copy"),"data-clipboard-target":`#${e} > code`})}function Yr(e,t){let r=t&2,n=t&1,o=Object.keys(e.terms).filter(a=>!e.terms[a]).reduce((a,s)=>[...a,A("del",null,s)," "],[]).slice(0,-1),i=new URL(e.location);return ce("search.highlight")&&i.searchParams.set("h",Object.entries(e.terms).filter(([,a])=>a).reduce((a,[s])=>`${a} ${s}`.trim(),"")),A("a",{href:`${i}`,class:"md-search-result__link",tabIndex:-1},A("article",{class:["md-search-result__article",...r?["md-search-result__article--document"]:[]].join(" "),"data-md-score":e.score.toFixed(2)},r>0&&A("div",{class:"md-search-result__icon md-icon"}),A("h1",{class:"md-search-result__title"},e.title),n>0&&e.text.length>0&&A("p",{class:"md-search-result__teaser"},Ro(e.text,320)),e.tags&&e.tags.map(a=>A("span",{class:"md-tag"},a)),n>0&&o.length>0&&A("p",{class:"md-search-result__terms"},Z("search.result.term.missing"),": ",o)))}function Qo(e){let t=e[0].score,r=[...e],n=r.findIndex(u=>!u.location.includes("#")),[o]=r.splice(n,1),i=r.findIndex(u=>u.score<t);i===-1&&(i=r.length);let a=r.slice(0,i),s=r.slice(i),c=[Yr(o,2|+(!n&&i===0)),...a.map(u=>Yr(u,1)),...s.length?[A("details",{class:"md-search-result__more"},A("summary",{tabIndex:-1},s.length>0&&s.length===1?Z("search.result.more.one"):Z("search.result.more.other",s.length)),s.map(u=>Yr(u,1)))]:[]];return A("li",{class:"md-search-result__item"},c)}function Yo(e){return A("ul",{class:"md-source__facts"},Object.entries(e).map(([t,r])=>A("li",{class:`md-source__fact md-source__fact--${t}`},typeof r=="number"?fr(r):r)))}function Ko(e){return A("div",{class:"md-typeset__scrollwrap"},A("div",{class:"md-typeset__table"},e))}function is(e){let t=de(),r=new URL(`../${e.version}/`,t.base);return A("li",{class:"md-version__item"},A("a",{href:r.toString(),class:"md-version__link"},e.title))}function Bo(e,t){return A("div",{class:"md-version"},A("button",{class:"md-version__current","aria-label":Z("select.version.title")},t.title),A("ul",{class:"md-version__list"},e.map(is)))}function as(e,t){let r=j(()=>Y([mo(e),nr(t)])).pipe(m(([{x:n,y:o},i])=>{let{width:a}=Ce(e);return{x:n-i.x+a/2,y:o-i.y}}));return rr(e).pipe(x(n=>r.pipe(m(o=>({active:n,offset:o})),te(+!n||1/0))))}function Go(e,t){return j(()=>{let r=new _;r.subscribe({next({offset:i}){e.style.setProperty("--md-tooltip-x",`${i.x}px`),e.style.setProperty("--md-tooltip-y",`${i.y}px`)},complete(){e.style.removeProperty("--md-tooltip-x"),e.style.removeProperty("--md-tooltip-y")}}),r.pipe(Dr(500,_e),m(()=>t.getBoundingClientRect()),m(({x:i})=>i)).subscribe({next(i){i?e.style.setProperty("--md-tooltip-0",`${-i}px`):e.style.removeProperty("--md-tooltip-0")},complete(){e.style.removeProperty("--md-tooltip-0")}});let n=Q(":scope > :last-child",e),o=y(n,"mousedown",{once:!0});return r.pipe(x(({active:i})=>i?o:k),O(i=>i.preventDefault())).subscribe(()=>e.blur()),as(e,t).pipe(O(i=>r.next(i)),L(()=>r.complete()),m(i=>U({ref:e},i)))})}function ss(e){let t=[];for(let r of G(".c, .c1, .cm",e)){let n,o=r.firstChild;if(o instanceof Text)for(;n=/\((\d+)\)/.exec(o.textContent);){let i=o.splitText(n.index);o=i.splitText(n[0].length),t.push(i)}}return t}function Jo(e,t){t.append(...Array.from(e.childNodes))}function Xo(e,t,{print$:r}){let n=new Map;for(let o of ss(t)){let[,i]=o.textContent.match(/\((\d+)\)/);fe(`li:nth-child(${i})`,e)&&(n.set(+i,zo(+i)),o.replaceWith(n.get(+i)))}return n.size===0?k:j(()=>{let o=new _;return r.pipe(se(o.pipe(le(1)))).subscribe(i=>{e.hidden=!i;for(let[a,s]of n){let c=Q(".md-typeset",s),u=Q(`li:nth-child(${a})`,e);i?Jo(c,u):Jo(u,c)}}),C(...[...n].map(([,i])=>Go(i,t))).pipe(L(()=>o.complete()),ae())})}var cs=0;function ti(e){if(e.nextElementSibling){let t=e.nextElementSibling;if(t.tagName==="OL")return t;if(t.tagName==="P"&&!t.children.length)return ti(t)}}function Zo(e){return ve(e).pipe(m(({width:t})=>({scrollable:sr(e).width>t})),J("scrollable"))}function ri(e,t){let{matches:r}=matchMedia("(hover)"),n=j(()=>{let o=new _;if(o.subscribe(({scrollable:a})=>{a&&r?e.setAttribute("tabindex","0"):e.removeAttribute("tabindex")}),ei.default.isSupported()){let a=e.closest("pre");a.id=`__code_${++cs}`,a.insertBefore(qo(a.id),e)}let i=e.closest(".highlight");if(i instanceof HTMLElement){let a=ti(i);if(typeof a!="undefined"&&(i.classList.contains("annotate")||ce("content.code.annotate"))){let s=Xo(a,e,t);return Zo(e).pipe(O(c=>o.next(c)),L(()=>o.complete()),m(c=>U({ref:e},c)),Ze(ve(i).pipe(se(o.pipe(le(1))),m(({width:c,height:u})=>c&&u),K(),x(c=>c?s:k))))}}return Zo(e).pipe(O(a=>o.next(a)),L(()=>o.complete()),m(a=>U({ref:e},a)))});return _o(e).pipe(M(o=>o),te(1),x(()=>n))}var ni=".node circle,.node ellipse,.node path,.node polygon,.node rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}marker{fill:var(--md-mermaid-edge-color)!important}.edgeLabel .label rect{fill:transparent}.label{color:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.label foreignObject{line-height:normal;overflow:visible}.label div .edgeLabel{color:var(--md-mermaid-label-fg-color)}.edgeLabel,.edgeLabel rect,.label div .edgeLabel{background-color:var(--md-mermaid-label-bg-color)}.edgeLabel,.edgeLabel rect{fill:var(--md-mermaid-label-bg-color);color:var(--md-mermaid-edge-color)}.edgePath .path,.flowchart-link{stroke:var(--md-mermaid-edge-color)}.edgePath .arrowheadPath{fill:var(--md-mermaid-edge-color);stroke:none}.cluster rect{fill:var(--md-default-fg-color--lightest);stroke:var(--md-default-fg-color--lighter)}.cluster span{color:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}defs #flowchart-circleEnd,defs #flowchart-circleStart,defs #flowchart-crossEnd,defs #flowchart-crossStart,defs #flowchart-pointEnd,defs #flowchart-pointStart{stroke:none}g.classGroup line,g.classGroup rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}g.classGroup text{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.classLabel .box{fill:var(--md-mermaid-label-bg-color);background-color:var(--md-mermaid-label-bg-color);opacity:1}.classLabel .label{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.node .divider{stroke:var(--md-mermaid-node-fg-color)}.relation{stroke:var(--md-mermaid-edge-color)}.cardinality{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.cardinality text{fill:inherit!important}defs #classDiagram-compositionEnd,defs #classDiagram-compositionStart,defs #classDiagram-dependencyEnd,defs #classDiagram-dependencyStart,defs #classDiagram-extensionEnd,defs #classDiagram-extensionStart{fill:var(--md-mermaid-edge-color)!important;stroke:var(--md-mermaid-edge-color)!important}defs #classDiagram-aggregationEnd,defs #classDiagram-aggregationStart{fill:var(--md-mermaid-label-bg-color)!important;stroke:var(--md-mermaid-edge-color)!important}g.stateGroup rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}g.stateGroup .state-title{fill:var(--md-mermaid-label-fg-color)!important;font-family:var(--md-mermaid-font-family)}g.stateGroup .composit{fill:var(--md-mermaid-label-bg-color)}.nodeLabel{color:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.node circle.state-end,.node circle.state-start,.start-state{fill:var(--md-mermaid-edge-color);stroke:none}.end-state-inner,.end-state-outer{fill:var(--md-mermaid-edge-color)}.end-state-inner,.node circle.state-end{stroke:var(--md-mermaid-label-bg-color)}.transition{stroke:var(--md-mermaid-edge-color)}[id^=state-fork] rect,[id^=state-join] rect{fill:var(--md-mermaid-edge-color)!important;stroke:none!important}.statediagram-cluster.statediagram-cluster .inner{fill:var(--md-default-bg-color)}.statediagram-cluster rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}.statediagram-state rect.divider{fill:var(--md-default-fg-color--lightest);stroke:var(--md-default-fg-color--lighter)}defs #statediagram-barbEnd{stroke:var(--md-mermaid-edge-color)}.entityBox{fill:var(--md-mermaid-label-bg-color);stroke:var(--md-mermaid-node-fg-color)}.entityLabel{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.relationshipLabelBox{fill:var(--md-mermaid-label-bg-color);fill-opacity:1;background-color:var(--md-mermaid-label-bg-color);opacity:1}.relationshipLabel{fill:var(--md-mermaid-label-fg-color)}.relationshipLine{stroke:var(--md-mermaid-edge-color)}defs #ONE_OR_MORE_END *,defs #ONE_OR_MORE_START *,defs #ONLY_ONE_END *,defs #ONLY_ONE_START *,defs #ZERO_OR_MORE_END *,defs #ZERO_OR_MORE_START *,defs #ZERO_OR_ONE_END *,defs #ZERO_OR_ONE_START *{stroke:var(--md-mermaid-edge-color)!important}.actor,defs #ZERO_OR_MORE_END circle,defs #ZERO_OR_MORE_START circle{fill:var(--md-mermaid-label-bg-color)}.actor{stroke:var(--md-mermaid-node-fg-color)}text.actor>tspan{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}line{stroke:var(--md-default-fg-color--lighter)}.messageLine0,.messageLine1{stroke:var(--md-mermaid-edge-color)}.loopText>tspan,.messageText{font-family:var(--md-mermaid-font-family)!important}#arrowhead path,.loopText>tspan,.messageText{fill:var(--md-mermaid-edge-color);stroke:none}.loopLine{stroke:var(--md-mermaid-node-fg-color)}.labelBox,.loopLine{fill:var(--md-mermaid-node-bg-color)}.labelBox{stroke:none}.labelText,.labelText>span{fill:var(--md-mermaid-node-fg-color);font-family:var(--md-mermaid-font-family)}";var Kr,fs=0;function ps(){return typeof mermaid=="undefined"||mermaid instanceof Element?jo("https://unpkg.com/mermaid@9.0.1/dist/mermaid.min.js"):P(void 0)}function oi(e){return e.classList.remove("mermaid"),Kr||(Kr=ps().pipe(O(()=>mermaid.initialize({startOnLoad:!1,themeCSS:ni})),m(()=>{}),X(1))),Kr.subscribe(()=>{e.classList.add("mermaid");let t=`__mermaid_${fs++}`,r=A("div",{class:"mermaid"});mermaid.mermaidAPI.render(t,e.textContent,n=>{let o=r.attachShadow({mode:"closed"});o.innerHTML=n,e.replaceWith(r)})}),Kr.pipe(m(()=>({ref:e})))}function ls(e,{target$:t,print$:r}){let n=!0;return C(t.pipe(m(o=>o.closest("details:not([open])")),M(o=>e===o),m(()=>({action:"open",reveal:!0}))),r.pipe(M(o=>o||!n),O(()=>n=e.open),m(o=>({action:o?"open":"close"}))))}function ii(e,t){return j(()=>{let r=new _;return r.subscribe(({action:n,reveal:o})=>{n==="open"?e.setAttribute("open",""):e.removeAttribute("open"),o&&e.scrollIntoView()}),ls(e,t).pipe(O(n=>r.next(n)),L(()=>r.complete()),m(n=>U({ref:e},n)))})}var ai=A("table");function si(e){return e.replaceWith(ai),ai.replaceWith(Ko(e)),P({ref:e})}function ms(e){let t=G(":scope > input",e),r=t.find(n=>n.checked)||t[0];return C(...t.map(n=>y(n,"change").pipe(m(()=>({active:Q(`label[for=${n.id}]`)}))))).pipe(q({active:Q(`label[for=${r.id}]`)}))}function ci(e){let t=Q(".tabbed-labels",e);return j(()=>{let r=new _;return Y([r,ve(e)]).pipe(Ie(1,_e),se(r.pipe(le(1)))).subscribe({next([{active:n}]){let o=ze(n),{width:i}=Ce(n);e.style.setProperty("--md-indicator-x",`${o.x}px`),e.style.setProperty("--md-indicator-width",`${i}px`),t.scrollTo({behavior:"smooth",left:o.x})},complete(){e.style.removeProperty("--md-indicator-x"),e.style.removeProperty("--md-indicator-width")}}),ms(e).pipe(O(n=>r.next(n)),L(()=>r.complete()),m(n=>U({ref:e},n)))}).pipe(Be(ue))}function ui(e,{target$:t,print$:r}){return C(...G("pre:not(.mermaid) > code",e).map(n=>ri(n,{print$:r})),...G("pre.mermaid",e).map(n=>oi(n)),...G("table:not([class])",e).map(n=>si(n)),...G("details",e).map(n=>ii(n,{target$:t,print$:r})),...G("[data-tabs]",e).map(n=>ci(n)))}function ds(e,{alert$:t}){return t.pipe(x(r=>C(P(!0),P(!1).pipe(je(2e3))).pipe(m(n=>({message:r,active:n})))))}function fi(e,t){let r=Q(".md-typeset",e);return j(()=>{let n=new _;return n.subscribe(({message:o,active:i})=>{r.textContent=o,i?e.setAttribute("data-md-state","open"):e.removeAttribute("data-md-state")}),ds(e,t).pipe(O(o=>n.next(o)),L(()=>n.complete()),m(o=>U({ref:e},o)))})}function hs({viewport$:e}){if(!ce("header.autohide"))return P(!1);let t=e.pipe(m(({offset:{y:o}})=>o),Te(2,1),m(([o,i])=>[o<i,i]),J(0)),r=Y([e,t]).pipe(M(([{offset:o},[,i]])=>Math.abs(i-o.y)>100),m(([,[o]])=>o),K()),n=lt("search");return Y([e,n]).pipe(m(([{offset:o},i])=>o.y>400&&!i),K(),x(o=>o?r:P(!1)),q(!1))}function pi(e,t){return j(()=>Y([ve(e),hs(t)])).pipe(m(([{height:r},n])=>({height:r,hidden:n})),K((r,n)=>r.height===n.height&&r.hidden===n.hidden),X(1))}function li(e,{header$:t,main$:r}){return j(()=>{let n=new _;return n.pipe(J("active"),Je(t)).subscribe(([{active:o},{hidden:i}])=>{o?e.setAttribute("data-md-state",i?"hidden":"shadow"):e.removeAttribute("data-md-state")}),r.subscribe(n),t.pipe(se(n.pipe(le(1))),m(o=>U({ref:e},o)))})}function bs(e,{viewport$:t,header$:r}){return lr(e,{viewport$:t,header$:r}).pipe(m(({offset:{y:n}})=>{let{height:o}=Ce(e);return{active:n>=o}}),J("active"))}function mi(e,t){return j(()=>{let r=new _;r.subscribe(({active:o})=>{o?e.setAttribute("data-md-state","active"):e.removeAttribute("data-md-state")});let n=fe("article h1");return typeof n=="undefined"?k:bs(n,t).pipe(O(o=>r.next(o)),L(()=>r.complete()),m(o=>U({ref:e},o)))})}function di(e,{viewport$:t,header$:r}){let n=r.pipe(m(({height:i})=>i),K()),o=n.pipe(x(()=>ve(e).pipe(m(({height:i})=>({top:e.offsetTop,bottom:e.offsetTop+i})),J("bottom"))));return Y([n,o,t]).pipe(m(([i,{top:a,bottom:s},{offset:{y:c},size:{height:u}}])=>(u=Math.max(0,u-Math.max(0,a-c,i)-Math.max(0,u+c-s)),{offset:a-i,height:u,active:a-i<=c})),K((i,a)=>i.offset===a.offset&&i.height===a.height&&i.active===a.active))}function vs(e){let t=__md_get("__palette")||{index:e.findIndex(r=>matchMedia(r.getAttribute("data-md-color-media")).matches)};return P(...e).pipe(oe(r=>y(r,"change").pipe(m(()=>r))),q(e[Math.max(0,t.index)]),m(r=>({index:e.indexOf(r),color:{scheme:r.getAttribute("data-md-color-scheme"),primary:r.getAttribute("data-md-color-primary"),accent:r.getAttribute("data-md-color-accent")}})),X(1))}function hi(e){return j(()=>{let t=new _;t.subscribe(n=>{document.body.setAttribute("data-md-color-switching","");for(let[o,i]of Object.entries(n.color))document.body.setAttribute(`data-md-color-${o}`,i);for(let o=0;o<r.length;o++){let i=r[o].nextElementSibling;i instanceof HTMLElement&&(i.hidden=n.index!==o)}__md_set("__palette",n)}),t.pipe(Pe(ue)).subscribe(()=>{document.body.removeAttribute("data-md-color-switching")});let r=G("input",e);return vs(r).pipe(O(n=>t.next(n)),L(()=>t.complete()),m(n=>U({ref:e},n)))})}var Br=Ye(Qr());function gs(e){e.setAttribute("data-md-copying","");let t=e.innerText;return e.removeAttribute("data-md-copying"),t}function bi({alert$:e}){Br.default.isSupported()&&new $(t=>{new Br.default("[data-clipboard-target], [data-clipboard-text]",{text:r=>r.getAttribute("data-clipboard-text")||gs(Q(r.getAttribute("data-clipboard-target")))}).on("success",r=>t.next(r))}).pipe(O(t=>{t.trigger.focus()}),m(()=>Z("clipboard.copied"))).subscribe(e)}function ys(e){if(e.length<2)return[""];let[t,r]=[...e].sort((o,i)=>o.length-i.length).map(o=>o.replace(/[^/]+$/,"")),n=0;if(t===r)n=t.length;else for(;t.charCodeAt(n)===r.charCodeAt(n);)n++;return e.map(o=>o.replace(t.slice(0,n),""))}function mr(e){let t=__md_get("__sitemap",sessionStorage,e);if(t)return P(t);{let r=de();return $o(new URL("sitemap.xml",e||r.base)).pipe(m(n=>ys(G("loc",n).map(o=>o.textContent))),ie(()=>k),$e([]),O(n=>__md_set("__sitemap",n,sessionStorage,e)))}}function vi({document$:e,location$:t,viewport$:r}){let n=de();if(location.protocol==="file:")return;"scrollRestoration"in history&&(history.scrollRestoration="manual",y(window,"beforeunload").subscribe(()=>{history.scrollRestoration="auto"}));let o=fe("link[rel=icon]");typeof o!="undefined"&&(o.href=o.href);let i=mr().pipe(m(u=>u.map(f=>`${new URL(f,n.base)}`)),x(u=>y(document.body,"click").pipe(M(f=>!f.metaKey&&!f.ctrlKey),x(f=>{if(f.target instanceof Element){let p=f.target.closest("a");if(p&&!p.target){let l=new URL(p.href);if(l.search="",l.hash="",l.pathname!==location.pathname&&u.includes(l.toString()))return f.preventDefault(),P({url:new URL(p.href)})}}return ye}))),ae()),a=y(window,"popstate").pipe(M(u=>u.state!==null),m(u=>({url:new URL(location.href),offset:u.state})),ae());C(i,a).pipe(K((u,f)=>u.url.href===f.url.href),m(({url:u})=>u)).subscribe(t);let s=t.pipe(J("pathname"),x(u=>pr(u.href).pipe(ie(()=>(ur(u),ye)))),ae());i.pipe(ft(s)).subscribe(({url:u})=>{history.pushState({},"",`${u}`)});let c=new DOMParser;s.pipe(x(u=>u.text()),m(u=>c.parseFromString(u,"text/html"))).subscribe(e),e.pipe(Fe(1)).subscribe(u=>{for(let f of["title","link[rel=canonical]","meta[name=author]","meta[name=description]","[data-md-component=announce]","[data-md-component=container]","[data-md-component=header-topic]","[data-md-component=outdated]","[data-md-component=logo]","[data-md-component=skip]",...ce("navigation.tabs.sticky")?["[data-md-component=tabs]"]:[]]){let p=fe(f),l=fe(f,u);typeof p!="undefined"&&typeof l!="undefined"&&p.replaceWith(l)}}),e.pipe(Fe(1),m(()=>Se("container")),x(u=>G("script",u)),Pr(u=>{let f=A("script");if(u.src){for(let p of u.getAttributeNames())f.setAttribute(p,u.getAttribute(p));return u.replaceWith(f),new $(p=>{f.onload=()=>p.complete()})}else return f.textContent=u.textContent,u.replaceWith(f),k})).subscribe(),C(i,a).pipe(ft(e)).subscribe(({url:u,offset:f})=>{u.hash&&!f?Ho(u.hash):window.scrollTo(0,(f==null?void 0:f.y)||0)}),r.pipe(Ot(i),Xe(250),J("offset")).subscribe(({offset:u})=>{history.replaceState(u,"")}),C(i,a).pipe(Te(2,1),M(([u,f])=>u.url.pathname===f.url.pathname),m(([,u])=>u)).subscribe(({offset:u})=>{window.scrollTo(0,(u==null?void 0:u.y)||0)})}var ws=Ye(Gr());var yi=Ye(Gr());function Jr(e,t){let r=new RegExp(e.separator,"img"),n=(o,i,a)=>`${i}<mark data-md-highlight>${a}</mark>`;return o=>{o=o.replace(/[\s*+\-:~^]+/g," ").trim();let i=new RegExp(`(^|${e.separator})(${o.replace(/[|\\{}()[\]^$+*?.-]/g,"\\$&").replace(r,"|")})`,"img");return a=>(t?(0,yi.default)(a):a).replace(i,n).replace(/<\/mark>(\s+)<mark[^>]*>/img,"$1")}}function xi(e){return e.split(/"([^"]+)"/g).map((t,r)=>r&1?t.replace(/^\b|^(?![^\x00-\x7F]|$)|\s+/g," +"):t).join("").replace(/"|(?:^|\s+)[*+\-:^~]+(?=\s+|$)/g,"").trim()}function dt(e){return e.type===1}function Si(e){return e.type===2}function ht(e){return e.type===3}function Os({config:e,docs:t}){e.lang.length===1&&e.lang[0]==="en"&&(e.lang=[Z("search.config.lang")]),e.separator==="[\\s\\-]+"&&(e.separator=Z("search.config.separator"));let n={pipeline:Z("search.config.pipeline").split(/\s*,\s*/).filter(Boolean),suggestions:ce("search.suggest")};return{config:e,docs:t,options:n}}function wi(e,t){let r=de(),n=new Worker(e),o=new _,i=No(n,{tx$:o}).pipe(m(a=>{if(ht(a))for(let s of a.data.items)for(let c of s)c.location=`${new URL(c.location,r.base)}`;return a}),ae());return re(t).pipe(m(a=>({type:0,data:Os(a)}))).subscribe(o.next.bind(o)),{tx$:o,rx$:i}}function Ei({document$:e}){let t=de(),r=Re(new URL("../versions.json",t.base)).pipe(ie(()=>k)),n=r.pipe(m(o=>{let[,i]=t.base.match(/([^/]+)\/?$/);return o.find(({version:a,aliases:s})=>a===i||s.includes(i))||o[0]}));Y([r,n]).pipe(m(([o,i])=>new Map(o.filter(a=>a!==i).map(a=>[`${new URL(`../${a.version}/`,t.base)}`,a]))),x(o=>y(document.body,"click").pipe(M(i=>!i.metaKey&&!i.ctrlKey),x(i=>{if(i.target instanceof Element){let a=i.target.closest("a");if(a&&!a.target&&o.has(a.href))return i.preventDefault(),P(a.href)}return k}),x(i=>{let{version:a}=o.get(i);return mr(new URL(i)).pipe(m(s=>{let u=xe().href.replace(t.base,"");return s.includes(u)?new URL(`../${a}/${u}`,t.base):new URL(i)}))})))).subscribe(o=>ur(o)),Y([r,n]).subscribe(([o,i])=>{Q(".md-header__topic").appendChild(Bo(o,i))}),e.pipe(x(()=>n)).subscribe(o=>{var a;let i=__md_get("__outdated",sessionStorage);if(i===null){let s=((a=t.version)==null?void 0:a.default)||"latest";i=!o.aliases.includes(s),__md_set("__outdated",i,sessionStorage)}if(i)for(let s of ne("outdated"))s.hidden=!1})}function _s(e,{rx$:t}){let r=(__search==null?void 0:__search.transform)||xi,{searchParams:n}=xe();n.has("q")&&qe("search",!0);let o=t.pipe(M(dt),te(1),m(()=>n.get("q")||""));lt("search").pipe(M(s=>!s),te(1)).subscribe(()=>{let s=new URL(location.href);s.searchParams.delete("q"),history.replaceState({},"",`${s}`)}),o.subscribe(s=>{s&&(e.value=s,e.focus())});let i=rr(e),a=C(y(e,"keyup"),y(e,"focus").pipe(je(1)),o).pipe(m(()=>r(e.value)),q(""),K());return Y([a,i]).pipe(m(([s,c])=>({value:s,focus:c})),X(1))}function Oi(e,{tx$:t,rx$:r}){let n=new _;return n.pipe(J("value"),m(({value:o})=>({type:2,data:o}))).subscribe(t.next.bind(t)),n.pipe(J("focus")).subscribe(({focus:o})=>{o?(qe("search",o),e.placeholder=""):e.placeholder=Z("search.placeholder")}),y(e.form,"reset").pipe(se(n.pipe(le(1)))).subscribe(()=>e.focus()),_s(e,{tx$:t,rx$:r}).pipe(O(o=>n.next(o)),L(()=>n.complete()),m(o=>U({ref:e},o)))}function _i(e,{rx$:t},{query$:r}){let n=new _,o=To(e.parentElement).pipe(M(Boolean)),i=Q(":scope > :first-child",e),a=Q(":scope > :last-child",e),s=t.pipe(M(dt),te(1));return n.pipe(Me(r),Ot(s)).subscribe(([{items:u},{value:f}])=>{if(f)switch(u.length){case 0:i.textContent=Z("search.result.none");break;case 1:i.textContent=Z("search.result.one");break;default:i.textContent=Z("search.result.other",fr(u.length))}else i.textContent=Z("search.result.placeholder")}),n.pipe(O(()=>a.innerHTML=""),x(({items:u})=>C(P(...u.slice(0,10)),P(...u.slice(10)).pipe(Te(4),Wr(o),x(([f])=>f))))).subscribe(u=>a.appendChild(Qo(u))),t.pipe(M(ht),m(({data:u})=>u)).pipe(O(u=>n.next(u)),L(()=>n.complete()),m(u=>U({ref:e},u)))}function Ts(e,{query$:t}){return t.pipe(m(({value:r})=>{let n=xe();return n.hash="",n.searchParams.delete("h"),n.searchParams.set("q",r),{url:n}}))}function Ti(e,t){let r=new _;return r.subscribe(({url:n})=>{e.setAttribute("data-clipboard-text",e.href),e.href=`${n}`}),y(e,"click").subscribe(n=>n.preventDefault()),Ts(e,t).pipe(O(n=>r.next(n)),L(()=>r.complete()),m(n=>U({ref:e},n)))}function Mi(e,{rx$:t},{keyboard$:r}){let n=new _,o=Se("search-query"),i=C(y(o,"keydown"),y(o,"focus")).pipe(Pe(ue),m(()=>o.value),K());return n.pipe(Je(i),m(([{suggestions:s},c])=>{let u=c.split(/([\s-]+)/);if((s==null?void 0:s.length)&&u[u.length-1]){let f=s[s.length-1];f.startsWith(u[u.length-1])&&(u[u.length-1]=f)}else u.length=0;return u})).subscribe(s=>e.innerHTML=s.join("").replace(/\s/g,"&nbsp;")),r.pipe(M(({mode:s})=>s==="search")).subscribe(s=>{switch(s.type){case"ArrowRight":e.innerText.length&&o.selectionStart===o.value.length&&(o.value=e.innerText);break}}),t.pipe(M(ht),m(({data:s})=>s)).pipe(O(s=>n.next(s)),L(()=>n.complete()),m(()=>({ref:e})))}function Li(e,{index$:t,keyboard$:r}){let n=de();try{let o=(__search==null?void 0:__search.worker)||n.search,i=wi(o,t),a=Se("search-query",e),s=Se("search-result",e),{tx$:c,rx$:u}=i;c.pipe(M(Si),ft(u.pipe(M(dt))),te(1)).subscribe(c.next.bind(c)),r.pipe(M(({mode:l})=>l==="search")).subscribe(l=>{let d=Ne();switch(l.type){case"Enter":if(d===a){let h=new Map;for(let b of G(":first-child [href]",s)){let F=b.firstElementChild;h.set(b,parseFloat(F.getAttribute("data-md-score")))}if(h.size){let[[b]]=[...h].sort(([,F],[,B])=>B-F);b.click()}l.claim()}break;case"Escape":case"Tab":qe("search",!1),a.blur();break;case"ArrowUp":case"ArrowDown":if(typeof d=="undefined")a.focus();else{let h=[a,...G(":not(details) > [href], summary, details[open] [href]",s)],b=Math.max(0,(Math.max(0,h.indexOf(d))+h.length+(l.type==="ArrowUp"?-1:1))%h.length);h[b].focus()}l.claim();break;default:a!==Ne()&&a.focus()}}),r.pipe(M(({mode:l})=>l==="global")).subscribe(l=>{switch(l.type){case"f":case"s":case"/":a.focus(),a.select(),l.claim();break}});let f=Oi(a,i),p=_i(s,i,{query$:f});return C(f,p).pipe(Ze(...ne("search-share",e).map(l=>Ti(l,{query$:f})),...ne("search-suggest",e).map(l=>Mi(l,i,{keyboard$:r}))))}catch(o){return e.hidden=!0,ye}}function Ai(e,{index$:t,location$:r}){return Y([t,r.pipe(q(xe()),M(n=>!!n.searchParams.get("h")))]).pipe(m(([n,o])=>Jr(n.config,!0)(o.searchParams.get("h"))),m(n=>{var a;let o=new Map,i=document.createNodeIterator(e,NodeFilter.SHOW_TEXT);for(let s=i.nextNode();s;s=i.nextNode())if((a=s.parentElement)!=null&&a.offsetHeight){let c=s.textContent,u=n(c);u.length>c.length&&o.set(s,u)}for(let[s,c]of o){let{childNodes:u}=A("span",null,c);s.replaceWith(...Array.from(u))}return{ref:e,nodes:o}}))}function Ms(e,{viewport$:t,main$:r}){let n=e.parentElement,o=n.offsetTop-n.parentElement.offsetTop;return Y([r,t]).pipe(m(([{offset:i,height:a},{offset:{y:s}}])=>(a=a+Math.min(o,Math.max(0,s-i))-o,{height:a,locked:s>=i+o})),K((i,a)=>i.height===a.height&&i.locked===a.locked))}function Xr(e,n){var o=n,{header$:t}=o,r=on(o,["header$"]);let i=Q(".md-sidebar__scrollwrap",e),{y:a}=ze(i);return j(()=>{let s=new _;return s.pipe(Ie(0,_e),Me(t)).subscribe({next([{height:c},{height:u}]){i.style.height=`${c-2*a}px`,e.style.top=`${u}px`},complete(){i.style.height="",e.style.top=""}}),Ms(e,r).pipe(O(c=>s.next(c)),L(()=>s.complete()),m(c=>U({ref:e},c)))})}function Ci(e,t){if(typeof t!="undefined"){let r=`https://api.github.com/repos/${e}/${t}`;return wt(Re(`${r}/releases/latest`).pipe(ie(()=>k),m(n=>({version:n.tag_name})),$e({})),Re(r).pipe(ie(()=>k),m(n=>({stars:n.stargazers_count,forks:n.forks_count})),$e({}))).pipe(m(([n,o])=>U(U({},n),o)))}else{let r=`https://api.github.com/users/${e}`;return Re(r).pipe(m(n=>({repositories:n.public_repos})),$e({}))}}function Ri(e,t){let r=`https://${e}/api/v4/projects/${encodeURIComponent(t)}`;return Re(r).pipe(ie(()=>k),m(({star_count:n,forks_count:o})=>({stars:n,forks:o})),$e({}))}function ki(e){let[t]=e.match(/(git(?:hub|lab))/i)||[];switch(t.toLowerCase()){case"github":let[,r,n]=e.match(/^.+github\.com\/([^/]+)\/?([^/]+)?/i);return Ci(r,n);case"gitlab":let[,o,i]=e.match(/^.+?([^/]*gitlab[^/]+)\/(.+?)\/?$/i);return Ri(o,i);default:return k}}var Ls;function As(e){return Ls||(Ls=j(()=>{let t=__md_get("__source",sessionStorage);return t?P(t):ki(e.href).pipe(O(r=>__md_set("__source",r,sessionStorage)))}).pipe(ie(()=>k),M(t=>Object.keys(t).length>0),m(t=>({facts:t})),X(1)))}function Hi(e){let t=Q(":scope > :last-child",e);return j(()=>{let r=new _;return r.subscribe(({facts:n})=>{t.appendChild(Yo(n)),t.setAttribute("data-md-state","done")}),As(e).pipe(O(n=>r.next(n)),L(()=>r.complete()),m(n=>U({ref:e},n)))})}function Cs(e,{viewport$:t,header$:r}){return ve(document.body).pipe(x(()=>lr(e,{header$:r,viewport$:t})),m(({offset:{y:n}})=>({hidden:n>=10})),J("hidden"))}function Pi(e,t){return j(()=>{let r=new _;return r.subscribe({next({hidden:n}){n?e.setAttribute("data-md-state","hidden"):e.removeAttribute("data-md-state")},complete(){e.removeAttribute("data-md-state")}}),(ce("navigation.tabs.sticky")?P({hidden:!1}):Cs(e,t)).pipe(O(n=>r.next(n)),L(()=>r.complete()),m(n=>U({ref:e},n)))})}function Rs(e,{viewport$:t,header$:r}){let n=new Map,o=G("[href^=\\#]",e);for(let s of o){let c=decodeURIComponent(s.hash.substring(1)),u=fe(`[id="${c}"]`);typeof u!="undefined"&&n.set(s,u)}let i=r.pipe(J("height"),m(({height:s})=>{let c=Se("main"),u=Q(":scope > :first-child",c);return s+.8*(u.offsetTop-c.offsetTop)}),ae());return ve(document.body).pipe(J("height"),x(s=>j(()=>{let c=[];return P([...n].reduce((u,[f,p])=>{for(;c.length&&n.get(c[c.length-1]).tagName>=p.tagName;)c.pop();let l=p.offsetTop;for(;!l&&p.parentElement;)p=p.parentElement,l=p.offsetTop;return u.set([...c=[...c,f]].reverse(),l)},new Map))}).pipe(m(c=>new Map([...c].sort(([,u],[,f])=>u-f))),Je(i),x(([c,u])=>t.pipe($r(([f,p],{offset:{y:l},size:d})=>{let h=l+d.height>=Math.floor(s.height);for(;p.length;){let[,b]=p[0];if(b-u<l||h)f=[...f,p.shift()];else break}for(;f.length;){let[,b]=f[f.length-1];if(b-u>=l&&!h)p=[f.pop(),...p];else break}return[f,p]},[[],[...c]]),K((f,p)=>f[0]===p[0]&&f[1]===p[1])))))).pipe(m(([s,c])=>({prev:s.map(([u])=>u),next:c.map(([u])=>u)})),q({prev:[],next:[]}),Te(2,1),m(([s,c])=>s.prev.length<c.prev.length?{prev:c.prev.slice(Math.max(0,s.prev.length-1),c.prev.length),next:[]}:{prev:c.prev.slice(-1),next:c.next.slice(0,c.next.length-s.next.length)}))}function Ii(e,{viewport$:t,header$:r,target$:n}){return j(()=>{let o=new _;return o.subscribe(({prev:i,next:a})=>{for(let[s]of a)s.removeAttribute("data-md-state"),s.classList.remove("md-nav__link--active");for(let[s,[c]]of i.entries())c.setAttribute("data-md-state","blur"),c.classList.toggle("md-nav__link--active",s===i.length-1)}),ce("navigation.tracking")&&t.pipe(se(o.pipe(le(1))),J("offset"),Xe(250),Fe(1),se(n.pipe(Fe(1))),Et({delay:250}),Me(o)).subscribe(([,{prev:i}])=>{let a=xe(),s=i[i.length-1];if(s&&s.length){let[c]=s,{hash:u}=new URL(c.href);a.hash!==u&&(a.hash=u,history.replaceState({},"",`${a}`))}else a.hash="",history.replaceState({},"",`${a}`)}),Rs(e,{viewport$:t,header$:r}).pipe(O(i=>o.next(i)),L(()=>o.complete()),m(i=>U({ref:e},i)))})}function ks(e,{viewport$:t,main$:r,target$:n}){let o=t.pipe(m(({offset:{y:a}})=>a),Te(2,1),m(([a,s])=>a>s&&s>0),K()),i=r.pipe(m(({active:a})=>a));return Y([i,o]).pipe(m(([a,s])=>!(a&&s)),K(),se(n.pipe(Fe(1))),tr(!0),Et({delay:250}),m(a=>({hidden:a})))}function $i(e,{viewport$:t,header$:r,main$:n,target$:o}){let i=new _;return i.subscribe({next({hidden:a}){a?(e.setAttribute("data-md-state","hidden"),e.setAttribute("tabindex","-1"),e.blur()):(e.removeAttribute("data-md-state"),e.removeAttribute("tabindex"))},complete(){e.style.top="",e.setAttribute("data-md-state","hidden"),e.removeAttribute("tabindex")}}),r.pipe(se(i.pipe(tr(0),le(1))),J("height")).subscribe(({height:a})=>{e.style.top=`${a+16}px`}),ks(e,{viewport$:t,main$:n,target$:o}).pipe(O(a=>i.next(a)),L(()=>i.complete()),m(a=>U({ref:e},a)))}function ji({document$:e,tablet$:t}){e.pipe(x(()=>G("[data-md-state=indeterminate]")),O(r=>{r.indeterminate=!0,r.checked=!1}),oe(r=>y(r,"change").pipe(Fr(()=>r.hasAttribute("data-md-state")),m(()=>r))),Me(t)).subscribe(([r,n])=>{r.removeAttribute("data-md-state"),n&&(r.checked=!1)})}function Hs(){return/(iPad|iPhone|iPod)/.test(navigator.userAgent)}function Fi({document$:e}){e.pipe(x(()=>G("[data-md-scrollfix]")),O(t=>t.removeAttribute("data-md-scrollfix")),M(Hs),oe(t=>y(t,"touchstart").pipe(m(()=>t)))).subscribe(t=>{let r=t.scrollTop;r===0?t.scrollTop=1:r+t.offsetHeight===t.scrollHeight&&(t.scrollTop=r-1)})}function Ui({viewport$:e,tablet$:t}){Y([lt("search"),t]).pipe(m(([r,n])=>r&&!n),x(r=>P(r).pipe(je(r?400:100))),Me(e)).subscribe(([r,{offset:{y:n}}])=>{if(r)document.body.setAttribute("data-md-state","lock"),document.body.style.top=`-${n}px`;else{let o=-1*parseInt(document.body.style.top,10);document.body.removeAttribute("data-md-state"),document.body.style.top="",o&&window.scrollTo(0,o)}})}Object.entries||(Object.entries=function(e){let t=[];for(let r of Object.keys(e))t.push([r,e[r]]);return t});Object.values||(Object.values=function(e){let t=[];for(let r of Object.keys(e))t.push(e[r]);return t});typeof Element!="undefined"&&(Element.prototype.scrollTo||(Element.prototype.scrollTo=function(e,t){typeof e=="object"?(this.scrollLeft=e.left,this.scrollTop=e.top):(this.scrollLeft=e,this.scrollTop=t)}),Element.prototype.replaceWith||(Element.prototype.replaceWith=function(...e){let t=this.parentNode;if(t){e.length===0&&t.removeChild(this);for(let r=e.length-1;r>=0;r--){let n=e[r];typeof n!="object"?n=document.createTextNode(n):n.parentNode&&n.parentNode.removeChild(n),r?t.insertBefore(this.previousSibling,n):t.replaceChild(n,this)}}}));document.documentElement.classList.remove("no-js");document.documentElement.classList.add("js");var et=lo(),hr=Ao(),Mt=Po(),Zr=Lo(),we=Vo(),br=Nr("(min-width: 960px)"),Wi=Nr("(min-width: 1220px)"),Vi=Io(),Ni=de(),zi=document.forms.namedItem("search")?(__search==null?void 0:__search.index)||Re(new URL("search/search_index.json",Ni.base)):ye,en=new _;bi({alert$:en});ce("navigation.instant")&&vi({document$:et,location$:hr,viewport$:we});var Di;((Di=Ni.version)==null?void 0:Di.provider)==="mike"&&Ei({document$:et});C(hr,Mt).pipe(je(125)).subscribe(()=>{qe("drawer",!1),qe("search",!1)});Zr.pipe(M(({mode:e})=>e==="global")).subscribe(e=>{switch(e.type){case"p":case",":let t=fe("[href][rel=prev]");typeof t!="undefined"&&t.click();break;case"n":case".":let r=fe("[href][rel=next]");typeof r!="undefined"&&r.click();break}});ji({document$:et,tablet$:br});Fi({document$:et});Ui({viewport$:we,tablet$:br});var Qe=pi(Se("header"),{viewport$:we}),dr=et.pipe(m(()=>Se("main")),x(e=>di(e,{viewport$:we,header$:Qe})),X(1)),Ps=C(...ne("dialog").map(e=>fi(e,{alert$:en})),...ne("header").map(e=>li(e,{viewport$:we,header$:Qe,main$:dr})),...ne("palette").map(e=>hi(e)),...ne("search").map(e=>Li(e,{index$:zi,keyboard$:Zr})),...ne("source").map(e=>Hi(e))),Is=j(()=>C(...ne("content").map(e=>ui(e,{target$:Mt,print$:Vi})),...ne("content").map(e=>ce("search.highlight")?Ai(e,{index$:zi,location$:hr}):k),...ne("header-title").map(e=>mi(e,{viewport$:we,header$:Qe})),...ne("sidebar").map(e=>e.getAttribute("data-md-type")==="navigation"?zr(Wi,()=>Xr(e,{viewport$:we,header$:Qe,main$:dr})):zr(br,()=>Xr(e,{viewport$:we,header$:Qe,main$:dr}))),...ne("tabs").map(e=>Pi(e,{viewport$:we,header$:Qe})),...ne("toc").map(e=>Ii(e,{viewport$:we,header$:Qe,target$:Mt})),...ne("top").map(e=>$i(e,{viewport$:we,header$:Qe,main$:dr,target$:Mt})))),qi=et.pipe(x(()=>Is),Ze(Ps),X(1));qi.subscribe();window.document$=et;window.location$=hr;window.target$=Mt;window.keyboard$=Zr;window.viewport$=we;window.tablet$=br;window.screen$=Wi;window.print$=Vi;window.alert$=en;window.component$=qi;})();
-//# sourceMappingURL=bundle.a6c66575.min.js.map
-
diff --git a/7.3/assets/javascripts/bundle.a6c66575.min.js.map b/7.3/assets/javascripts/bundle.a6c66575.min.js.map
deleted file mode 100755
index c910e18a7f..0000000000
--- a/7.3/assets/javascripts/bundle.a6c66575.min.js.map
+++ /dev/null
@@ -1,8 +0,0 @@
-{
-  "version": 3,
-  "sources": ["node_modules/focus-visible/dist/focus-visible.js", "node_modules/url-polyfill/url-polyfill.js", "node_modules/rxjs/node_modules/tslib/tslib.js", "node_modules/clipboard/dist/clipboard.js", "node_modules/escape-html/index.js", "node_modules/array-flat-polyfill/index.mjs", "src/assets/javascripts/bundle.ts", "node_modules/unfetch/polyfill/index.js", "node_modules/rxjs/node_modules/tslib/modules/index.js", "node_modules/rxjs/src/internal/util/isFunction.ts", "node_modules/rxjs/src/internal/util/createErrorClass.ts", "node_modules/rxjs/src/internal/util/UnsubscriptionError.ts", "node_modules/rxjs/src/internal/util/arrRemove.ts", "node_modules/rxjs/src/internal/Subscription.ts", "node_modules/rxjs/src/internal/config.ts", "node_modules/rxjs/src/internal/scheduler/timeoutProvider.ts", "node_modules/rxjs/src/internal/util/reportUnhandledError.ts", "node_modules/rxjs/src/internal/util/noop.ts", "node_modules/rxjs/src/internal/NotificationFactories.ts", "node_modules/rxjs/src/internal/util/errorContext.ts", "node_modules/rxjs/src/internal/Subscriber.ts", "node_modules/rxjs/src/internal/symbol/observable.ts", "node_modules/rxjs/src/internal/util/identity.ts", "node_modules/rxjs/src/internal/util/pipe.ts", "node_modules/rxjs/src/internal/Observable.ts", "node_modules/rxjs/src/internal/util/lift.ts", "node_modules/rxjs/src/internal/operators/OperatorSubscriber.ts", "node_modules/rxjs/src/internal/scheduler/animationFrameProvider.ts", "node_modules/rxjs/src/internal/util/ObjectUnsubscribedError.ts", "node_modules/rxjs/src/internal/Subject.ts", "node_modules/rxjs/src/internal/scheduler/dateTimestampProvider.ts", "node_modules/rxjs/src/internal/ReplaySubject.ts", "node_modules/rxjs/src/internal/scheduler/Action.ts", "node_modules/rxjs/src/internal/scheduler/intervalProvider.ts", "node_modules/rxjs/src/internal/scheduler/AsyncAction.ts", "node_modules/rxjs/src/internal/Scheduler.ts", "node_modules/rxjs/src/internal/scheduler/AsyncScheduler.ts", "node_modules/rxjs/src/internal/scheduler/async.ts", "node_modules/rxjs/src/internal/scheduler/AnimationFrameAction.ts", "node_modules/rxjs/src/internal/scheduler/AnimationFrameScheduler.ts", "node_modules/rxjs/src/internal/scheduler/animationFrame.ts", "node_modules/rxjs/src/internal/observable/empty.ts", "node_modules/rxjs/src/internal/util/isScheduler.ts", "node_modules/rxjs/src/internal/util/args.ts", "node_modules/rxjs/src/internal/util/isArrayLike.ts", "node_modules/rxjs/src/internal/util/isPromise.ts", "node_modules/rxjs/src/internal/util/isInteropObservable.ts", "node_modules/rxjs/src/internal/util/isAsyncIterable.ts", "node_modules/rxjs/src/internal/util/throwUnobservableError.ts", "node_modules/rxjs/src/internal/symbol/iterator.ts", "node_modules/rxjs/src/internal/util/isIterable.ts", "node_modules/rxjs/src/internal/util/isReadableStreamLike.ts", "node_modules/rxjs/src/internal/observable/innerFrom.ts", "node_modules/rxjs/src/internal/util/executeSchedule.ts", "node_modules/rxjs/src/internal/operators/observeOn.ts", "node_modules/rxjs/src/internal/operators/subscribeOn.ts", "node_modules/rxjs/src/internal/scheduled/scheduleObservable.ts", "node_modules/rxjs/src/internal/scheduled/schedulePromise.ts", "node_modules/rxjs/src/internal/scheduled/scheduleArray.ts", "node_modules/rxjs/src/internal/scheduled/scheduleIterable.ts", "node_modules/rxjs/src/internal/scheduled/scheduleAsyncIterable.ts", "node_modules/rxjs/src/internal/scheduled/scheduleReadableStreamLike.ts", "node_modules/rxjs/src/internal/scheduled/scheduled.ts", "node_modules/rxjs/src/internal/observable/from.ts", "node_modules/rxjs/src/internal/observable/of.ts", "node_modules/rxjs/src/internal/observable/throwError.ts", "node_modules/rxjs/src/internal/util/isDate.ts", "node_modules/rxjs/src/internal/operators/map.ts", "node_modules/rxjs/src/internal/util/mapOneOrManyArgs.ts", "node_modules/rxjs/src/internal/util/argsArgArrayOrObject.ts", "node_modules/rxjs/src/internal/util/createObject.ts", "node_modules/rxjs/src/internal/observable/combineLatest.ts", "node_modules/rxjs/src/internal/operators/mergeInternals.ts", "node_modules/rxjs/src/internal/operators/mergeMap.ts", "node_modules/rxjs/src/internal/operators/mergeAll.ts", "node_modules/rxjs/src/internal/operators/concatAll.ts", "node_modules/rxjs/src/internal/observable/concat.ts", "node_modules/rxjs/src/internal/observable/defer.ts", "node_modules/rxjs/src/internal/observable/fromEvent.ts", "node_modules/rxjs/src/internal/observable/fromEventPattern.ts", "node_modules/rxjs/src/internal/observable/timer.ts", "node_modules/rxjs/src/internal/observable/merge.ts", "node_modules/rxjs/src/internal/observable/never.ts", "node_modules/rxjs/src/internal/util/argsOrArgArray.ts", "node_modules/rxjs/src/internal/operators/filter.ts", "node_modules/rxjs/src/internal/observable/zip.ts", "node_modules/rxjs/src/internal/operators/audit.ts", "node_modules/rxjs/src/internal/operators/auditTime.ts", "node_modules/rxjs/src/internal/operators/bufferCount.ts", "node_modules/rxjs/src/internal/operators/catchError.ts", "node_modules/rxjs/src/internal/operators/scanInternals.ts", "node_modules/rxjs/src/internal/operators/combineLatest.ts", "node_modules/rxjs/src/internal/operators/combineLatestWith.ts", "node_modules/rxjs/src/internal/operators/concatMap.ts", "node_modules/rxjs/src/internal/operators/debounceTime.ts", "node_modules/rxjs/src/internal/operators/defaultIfEmpty.ts", "node_modules/rxjs/src/internal/operators/take.ts", "node_modules/rxjs/src/internal/operators/ignoreElements.ts", "node_modules/rxjs/src/internal/operators/mapTo.ts", "node_modules/rxjs/src/internal/operators/delayWhen.ts", "node_modules/rxjs/src/internal/operators/delay.ts", "node_modules/rxjs/src/internal/operators/distinctUntilChanged.ts", "node_modules/rxjs/src/internal/operators/distinctUntilKeyChanged.ts", "node_modules/rxjs/src/internal/operators/endWith.ts", "node_modules/rxjs/src/internal/operators/finalize.ts", "node_modules/rxjs/src/internal/operators/takeLast.ts", "node_modules/rxjs/src/internal/operators/merge.ts", "node_modules/rxjs/src/internal/operators/mergeWith.ts", "node_modules/rxjs/src/internal/operators/repeat.ts", "node_modules/rxjs/src/internal/operators/sample.ts", "node_modules/rxjs/src/internal/operators/scan.ts", "node_modules/rxjs/src/internal/operators/share.ts", "node_modules/rxjs/src/internal/operators/shareReplay.ts", "node_modules/rxjs/src/internal/operators/skip.ts", "node_modules/rxjs/src/internal/operators/skipUntil.ts", "node_modules/rxjs/src/internal/operators/startWith.ts", "node_modules/rxjs/src/internal/operators/switchMap.ts", "node_modules/rxjs/src/internal/operators/takeUntil.ts", "node_modules/rxjs/src/internal/operators/takeWhile.ts", "node_modules/rxjs/src/internal/operators/tap.ts", "node_modules/rxjs/src/internal/operators/throttle.ts", "node_modules/rxjs/src/internal/operators/throttleTime.ts", "node_modules/rxjs/src/internal/operators/withLatestFrom.ts", "node_modules/rxjs/src/internal/operators/zip.ts", "node_modules/rxjs/src/internal/operators/zipWith.ts", "src/assets/javascripts/browser/document/index.ts", "src/assets/javascripts/browser/element/_/index.ts", "src/assets/javascripts/browser/element/focus/index.ts", "src/assets/javascripts/browser/element/offset/_/index.ts", "src/assets/javascripts/browser/element/offset/content/index.ts", "node_modules/resize-observer-polyfill/dist/ResizeObserver.es.js", "src/assets/javascripts/browser/element/size/_/index.ts", "src/assets/javascripts/browser/element/size/content/index.ts", "src/assets/javascripts/browser/element/visibility/index.ts", "src/assets/javascripts/browser/toggle/index.ts", "src/assets/javascripts/browser/keyboard/index.ts", "src/assets/javascripts/browser/location/_/index.ts", "src/assets/javascripts/utilities/h/index.ts", "src/assets/javascripts/utilities/string/index.ts", "src/assets/javascripts/browser/location/hash/index.ts", "src/assets/javascripts/browser/media/index.ts", "src/assets/javascripts/browser/request/index.ts", "src/assets/javascripts/browser/script/index.ts", "src/assets/javascripts/browser/viewport/offset/index.ts", "src/assets/javascripts/browser/viewport/size/index.ts", "src/assets/javascripts/browser/viewport/_/index.ts", "src/assets/javascripts/browser/viewport/at/index.ts", "src/assets/javascripts/browser/worker/index.ts", "src/assets/javascripts/_/index.ts", "src/assets/javascripts/components/_/index.ts", "src/assets/javascripts/components/content/code/_/index.ts", "src/assets/javascripts/templates/annotation/index.tsx", "src/assets/javascripts/templates/clipboard/index.tsx", "src/assets/javascripts/templates/search/index.tsx", "src/assets/javascripts/templates/source/index.tsx", "src/assets/javascripts/templates/table/index.tsx", "src/assets/javascripts/templates/version/index.tsx", "src/assets/javascripts/components/content/annotation/_/index.ts", "src/assets/javascripts/components/content/annotation/list/index.ts", "src/assets/javascripts/components/content/code/mermaid/index.ts", "src/assets/javascripts/components/content/details/index.ts", "src/assets/javascripts/components/content/table/index.ts", "src/assets/javascripts/components/content/tabs/index.ts", "src/assets/javascripts/components/content/_/index.ts", "src/assets/javascripts/components/dialog/index.ts", "src/assets/javascripts/components/header/_/index.ts", "src/assets/javascripts/components/header/title/index.ts", "src/assets/javascripts/components/main/index.ts", "src/assets/javascripts/components/palette/index.ts", "src/assets/javascripts/integrations/clipboard/index.ts", "src/assets/javascripts/integrations/sitemap/index.ts", "src/assets/javascripts/integrations/instant/index.ts", "src/assets/javascripts/integrations/search/document/index.ts", "src/assets/javascripts/integrations/search/highlighter/index.ts", "src/assets/javascripts/integrations/search/query/transform/index.ts", "src/assets/javascripts/integrations/search/worker/message/index.ts", "src/assets/javascripts/integrations/search/worker/_/index.ts", "src/assets/javascripts/integrations/version/index.ts", "src/assets/javascripts/components/search/query/index.ts", "src/assets/javascripts/components/search/result/index.ts", "src/assets/javascripts/components/search/share/index.ts", "src/assets/javascripts/components/search/suggest/index.ts", "src/assets/javascripts/components/search/_/index.ts", "src/assets/javascripts/components/search/highlight/index.ts", "src/assets/javascripts/components/sidebar/index.ts", "src/assets/javascripts/components/source/facts/github/index.ts", "src/assets/javascripts/components/source/facts/gitlab/index.ts", "src/assets/javascripts/components/source/facts/_/index.ts", "src/assets/javascripts/components/source/_/index.ts", "src/assets/javascripts/components/tabs/index.ts", "src/assets/javascripts/components/toc/index.ts", "src/assets/javascripts/components/top/index.ts", "src/assets/javascripts/patches/indeterminate/index.ts", "src/assets/javascripts/patches/scrollfix/index.ts", "src/assets/javascripts/patches/scrolllock/index.ts", "src/assets/javascripts/polyfills/index.ts"],
-  "sourceRoot": "../../../..",
-  "sourcesContent": ["(function (global, factory) {\n  typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n  typeof define === 'function' && define.amd ? define(factory) :\n  (factory());\n}(this, (function () { 'use strict';\n\n  /**\n   * Applies the :focus-visible polyfill at the given scope.\n   * A scope in this case is either the top-level Document or a Shadow Root.\n   *\n   * @param {(Document|ShadowRoot)} scope\n   * @see https://github.com/WICG/focus-visible\n   */\n  function applyFocusVisiblePolyfill(scope) {\n    var hadKeyboardEvent = true;\n    var hadFocusVisibleRecently = false;\n    var hadFocusVisibleRecentlyTimeout = null;\n\n    var inputTypesAllowlist = {\n      text: true,\n      search: true,\n      url: true,\n      tel: true,\n      email: true,\n      password: true,\n      number: true,\n      date: true,\n      month: true,\n      week: true,\n      time: true,\n      datetime: true,\n      'datetime-local': true\n    };\n\n    /**\n     * Helper function for legacy browsers and iframes which sometimes focus\n     * elements like document, body, and non-interactive SVG.\n     * @param {Element} el\n     */\n    function isValidFocusTarget(el) {\n      if (\n        el &&\n        el !== document &&\n        el.nodeName !== 'HTML' &&\n        el.nodeName !== 'BODY' &&\n        'classList' in el &&\n        'contains' in el.classList\n      ) {\n        return true;\n      }\n      return false;\n    }\n\n    /**\n     * Computes whether the given element should automatically trigger the\n     * `focus-visible` class being added, i.e. whether it should always match\n     * `:focus-visible` when focused.\n     * @param {Element} el\n     * @return {boolean}\n     */\n    function focusTriggersKeyboardModality(el) {\n      var type = el.type;\n      var tagName = el.tagName;\n\n      if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n        return true;\n      }\n\n      if (tagName === 'TEXTAREA' && !el.readOnly) {\n        return true;\n      }\n\n      if (el.isContentEditable) {\n        return true;\n      }\n\n      return false;\n    }\n\n    /**\n     * Add the `focus-visible` class to the given element if it was not added by\n     * the author.\n     * @param {Element} el\n     */\n    function addFocusVisibleClass(el) {\n      if (el.classList.contains('focus-visible')) {\n        return;\n      }\n      el.classList.add('focus-visible');\n      el.setAttribute('data-focus-visible-added', '');\n    }\n\n    /**\n     * Remove the `focus-visible` class from the given element if it was not\n     * originally added by the author.\n     * @param {Element} el\n     */\n    function removeFocusVisibleClass(el) {\n      if (!el.hasAttribute('data-focus-visible-added')) {\n        return;\n      }\n      el.classList.remove('focus-visible');\n      el.removeAttribute('data-focus-visible-added');\n    }\n\n    /**\n     * If the most recent user interaction was via the keyboard;\n     * and the key press did not include a meta, alt/option, or control key;\n     * then the modality is keyboard. Otherwise, the modality is not keyboard.\n     * Apply `focus-visible` to any current active element and keep track\n     * of our keyboard modality state with `hadKeyboardEvent`.\n     * @param {KeyboardEvent} e\n     */\n    function onKeyDown(e) {\n      if (e.metaKey || e.altKey || e.ctrlKey) {\n        return;\n      }\n\n      if (isValidFocusTarget(scope.activeElement)) {\n        addFocusVisibleClass(scope.activeElement);\n      }\n\n      hadKeyboardEvent = true;\n    }\n\n    /**\n     * If at any point a user clicks with a pointing device, ensure that we change\n     * the modality away from keyboard.\n     * This avoids the situation where a user presses a key on an already focused\n     * element, and then clicks on a different element, focusing it with a\n     * pointing device, while we still think we're in keyboard modality.\n     * @param {Event} e\n     */\n    function onPointerDown(e) {\n      hadKeyboardEvent = false;\n    }\n\n    /**\n     * On `focus`, add the `focus-visible` class to the target if:\n     * - the target received focus as a result of keyboard navigation, or\n     * - the event target is an element that will likely require interaction\n     *   via the keyboard (e.g. a text box)\n     * @param {Event} e\n     */\n    function onFocus(e) {\n      // Prevent IE from focusing the document or HTML element.\n      if (!isValidFocusTarget(e.target)) {\n        return;\n      }\n\n      if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n        addFocusVisibleClass(e.target);\n      }\n    }\n\n    /**\n     * On `blur`, remove the `focus-visible` class from the target.\n     * @param {Event} e\n     */\n    function onBlur(e) {\n      if (!isValidFocusTarget(e.target)) {\n        return;\n      }\n\n      if (\n        e.target.classList.contains('focus-visible') ||\n        e.target.hasAttribute('data-focus-visible-added')\n      ) {\n        // To detect a tab/window switch, we look for a blur event followed\n        // rapidly by a visibility change.\n        // If we don't see a visibility change within 100ms, it's probably a\n        // regular focus change.\n        hadFocusVisibleRecently = true;\n        window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n        hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n          hadFocusVisibleRecently = false;\n        }, 100);\n        removeFocusVisibleClass(e.target);\n      }\n    }\n\n    /**\n     * If the user changes tabs, keep track of whether or not the previously\n     * focused element had .focus-visible.\n     * @param {Event} e\n     */\n    function onVisibilityChange(e) {\n      if (document.visibilityState === 'hidden') {\n        // If the tab becomes active again, the browser will handle calling focus\n        // on the element (Safari actually calls it twice).\n        // If this tab change caused a blur on an element with focus-visible,\n        // re-apply the class when the user switches back to the tab.\n        if (hadFocusVisibleRecently) {\n          hadKeyboardEvent = true;\n        }\n        addInitialPointerMoveListeners();\n      }\n    }\n\n    /**\n     * Add a group of listeners to detect usage of any pointing devices.\n     * These listeners will be added when the polyfill first loads, and anytime\n     * the window is blurred, so that they are active when the window regains\n     * focus.\n     */\n    function addInitialPointerMoveListeners() {\n      document.addEventListener('mousemove', onInitialPointerMove);\n      document.addEventListener('mousedown', onInitialPointerMove);\n      document.addEventListener('mouseup', onInitialPointerMove);\n      document.addEventListener('pointermove', onInitialPointerMove);\n      document.addEventListener('pointerdown', onInitialPointerMove);\n      document.addEventListener('pointerup', onInitialPointerMove);\n      document.addEventListener('touchmove', onInitialPointerMove);\n      document.addEventListener('touchstart', onInitialPointerMove);\n      document.addEventListener('touchend', onInitialPointerMove);\n    }\n\n    function removeInitialPointerMoveListeners() {\n      document.removeEventListener('mousemove', onInitialPointerMove);\n      document.removeEventListener('mousedown', onInitialPointerMove);\n      document.removeEventListener('mouseup', onInitialPointerMove);\n      document.removeEventListener('pointermove', onInitialPointerMove);\n      document.removeEventListener('pointerdown', onInitialPointerMove);\n      document.removeEventListener('pointerup', onInitialPointerMove);\n      document.removeEventListener('touchmove', onInitialPointerMove);\n      document.removeEventListener('touchstart', onInitialPointerMove);\n      document.removeEventListener('touchend', onInitialPointerMove);\n    }\n\n    /**\n     * When the polfyill first loads, assume the user is in keyboard modality.\n     * If any event is received from a pointing device (e.g. mouse, pointer,\n     * touch), turn off keyboard modality.\n     * This accounts for situations where focus enters the page from the URL bar.\n     * @param {Event} e\n     */\n    function onInitialPointerMove(e) {\n      // Work around a Safari quirk that fires a mousemove on <html> whenever the\n      // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n      if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n        return;\n      }\n\n      hadKeyboardEvent = false;\n      removeInitialPointerMoveListeners();\n    }\n\n    // For some kinds of state, we are interested in changes at the global scope\n    // only. For example, global pointer input, global key presses and global\n    // visibility change should affect the state at every scope:\n    document.addEventListener('keydown', onKeyDown, true);\n    document.addEventListener('mousedown', onPointerDown, true);\n    document.addEventListener('pointerdown', onPointerDown, true);\n    document.addEventListener('touchstart', onPointerDown, true);\n    document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n    addInitialPointerMoveListeners();\n\n    // For focus and blur, we specifically care about state changes in the local\n    // scope. This is because focus / blur events that originate from within a\n    // shadow root are not re-dispatched from the host element if it was already\n    // the active element in its own scope:\n    scope.addEventListener('focus', onFocus, true);\n    scope.addEventListener('blur', onBlur, true);\n\n    // We detect that a node is a ShadowRoot by ensuring that it is a\n    // DocumentFragment and also has a host property. This check covers native\n    // implementation and polyfill implementation transparently. If we only cared\n    // about the native implementation, we could just check if the scope was\n    // an instance of a ShadowRoot.\n    if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n      // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n      // have a root element to add a class to. So, we add this attribute to the\n      // host element instead:\n      scope.host.setAttribute('data-js-focus-visible', '');\n    } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n      document.documentElement.classList.add('js-focus-visible');\n      document.documentElement.setAttribute('data-js-focus-visible', '');\n    }\n  }\n\n  // It is important to wrap all references to global window and document in\n  // these checks to support server-side rendering use cases\n  // @see https://github.com/WICG/focus-visible/issues/199\n  if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n    // Make the polyfill helper globally available. This can be used as a signal\n    // to interested libraries that wish to coordinate with the polyfill for e.g.,\n    // applying the polyfill to a shadow root:\n    window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n    // Notify interested libraries of the polyfill's presence, in case the\n    // polyfill was loaded lazily:\n    var event;\n\n    try {\n      event = new CustomEvent('focus-visible-polyfill-ready');\n    } catch (error) {\n      // IE11 does not support using CustomEvent as a constructor directly:\n      event = document.createEvent('CustomEvent');\n      event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n    }\n\n    window.dispatchEvent(event);\n  }\n\n  if (typeof document !== 'undefined') {\n    // Apply the polyfill to the global document, so that no JavaScript\n    // coordination is required to use the polyfill in the top-level document:\n    applyFocusVisiblePolyfill(document);\n  }\n\n})));\n", "(function(global) {\r\n  /**\r\n   * Polyfill URLSearchParams\r\n   *\r\n   * Inspired from : https://github.com/WebReflection/url-search-params/blob/master/src/url-search-params.js\r\n   */\r\n\r\n  var checkIfIteratorIsSupported = function() {\r\n    try {\r\n      return !!Symbol.iterator;\r\n    } catch (error) {\r\n      return false;\r\n    }\r\n  };\r\n\r\n\r\n  var iteratorSupported = checkIfIteratorIsSupported();\r\n\r\n  var createIterator = function(items) {\r\n    var iterator = {\r\n      next: function() {\r\n        var value = items.shift();\r\n        return { done: value === void 0, value: value };\r\n      }\r\n    };\r\n\r\n    if (iteratorSupported) {\r\n      iterator[Symbol.iterator] = function() {\r\n        return iterator;\r\n      };\r\n    }\r\n\r\n    return iterator;\r\n  };\r\n\r\n  /**\r\n   * Search param name and values should be encoded according to https://url.spec.whatwg.org/#urlencoded-serializing\r\n   * encodeURIComponent() produces the same result except encoding spaces as `%20` instead of `+`.\r\n   */\r\n  var serializeParam = function(value) {\r\n    return encodeURIComponent(value).replace(/%20/g, '+');\r\n  };\r\n\r\n  var deserializeParam = function(value) {\r\n    return decodeURIComponent(String(value).replace(/\\+/g, ' '));\r\n  };\r\n\r\n  var polyfillURLSearchParams = function() {\r\n\r\n    var URLSearchParams = function(searchString) {\r\n      Object.defineProperty(this, '_entries', { writable: true, value: {} });\r\n      var typeofSearchString = typeof searchString;\r\n\r\n      if (typeofSearchString === 'undefined') {\r\n        // do nothing\r\n      } else if (typeofSearchString === 'string') {\r\n        if (searchString !== '') {\r\n          this._fromString(searchString);\r\n        }\r\n      } else if (searchString instanceof URLSearchParams) {\r\n        var _this = this;\r\n        searchString.forEach(function(value, name) {\r\n          _this.append(name, value);\r\n        });\r\n      } else if ((searchString !== null) && (typeofSearchString === 'object')) {\r\n        if (Object.prototype.toString.call(searchString) === '[object Array]') {\r\n          for (var i = 0; i < searchString.length; i++) {\r\n            var entry = searchString[i];\r\n            if ((Object.prototype.toString.call(entry) === '[object Array]') || (entry.length !== 2)) {\r\n              this.append(entry[0], entry[1]);\r\n            } else {\r\n              throw new TypeError('Expected [string, any] as entry at index ' + i + ' of URLSearchParams\\'s input');\r\n            }\r\n          }\r\n        } else {\r\n          for (var key in searchString) {\r\n            if (searchString.hasOwnProperty(key)) {\r\n              this.append(key, searchString[key]);\r\n            }\r\n          }\r\n        }\r\n      } else {\r\n        throw new TypeError('Unsupported input\\'s type for URLSearchParams');\r\n      }\r\n    };\r\n\r\n    var proto = URLSearchParams.prototype;\r\n\r\n    proto.append = function(name, value) {\r\n      if (name in this._entries) {\r\n        this._entries[name].push(String(value));\r\n      } else {\r\n        this._entries[name] = [String(value)];\r\n      }\r\n    };\r\n\r\n    proto.delete = function(name) {\r\n      delete this._entries[name];\r\n    };\r\n\r\n    proto.get = function(name) {\r\n      return (name in this._entries) ? this._entries[name][0] : null;\r\n    };\r\n\r\n    proto.getAll = function(name) {\r\n      return (name in this._entries) ? this._entries[name].slice(0) : [];\r\n    };\r\n\r\n    proto.has = function(name) {\r\n      return (name in this._entries);\r\n    };\r\n\r\n    proto.set = function(name, value) {\r\n      this._entries[name] = [String(value)];\r\n    };\r\n\r\n    proto.forEach = function(callback, thisArg) {\r\n      var entries;\r\n      for (var name in this._entries) {\r\n        if (this._entries.hasOwnProperty(name)) {\r\n          entries = this._entries[name];\r\n          for (var i = 0; i < entries.length; i++) {\r\n            callback.call(thisArg, entries[i], name, this);\r\n          }\r\n        }\r\n      }\r\n    };\r\n\r\n    proto.keys = function() {\r\n      var items = [];\r\n      this.forEach(function(value, name) {\r\n        items.push(name);\r\n      });\r\n      return createIterator(items);\r\n    };\r\n\r\n    proto.values = function() {\r\n      var items = [];\r\n      this.forEach(function(value) {\r\n        items.push(value);\r\n      });\r\n      return createIterator(items);\r\n    };\r\n\r\n    proto.entries = function() {\r\n      var items = [];\r\n      this.forEach(function(value, name) {\r\n        items.push([name, value]);\r\n      });\r\n      return createIterator(items);\r\n    };\r\n\r\n    if (iteratorSupported) {\r\n      proto[Symbol.iterator] = proto.entries;\r\n    }\r\n\r\n    proto.toString = function() {\r\n      var searchArray = [];\r\n      this.forEach(function(value, name) {\r\n        searchArray.push(serializeParam(name) + '=' + serializeParam(value));\r\n      });\r\n      return searchArray.join('&');\r\n    };\r\n\r\n\r\n    global.URLSearchParams = URLSearchParams;\r\n  };\r\n\r\n  var checkIfURLSearchParamsSupported = function() {\r\n    try {\r\n      var URLSearchParams = global.URLSearchParams;\r\n\r\n      return (\r\n        (new URLSearchParams('?a=1').toString() === 'a=1') &&\r\n        (typeof URLSearchParams.prototype.set === 'function') &&\r\n        (typeof URLSearchParams.prototype.entries === 'function')\r\n      );\r\n    } catch (e) {\r\n      return false;\r\n    }\r\n  };\r\n\r\n  if (!checkIfURLSearchParamsSupported()) {\r\n    polyfillURLSearchParams();\r\n  }\r\n\r\n  var proto = global.URLSearchParams.prototype;\r\n\r\n  if (typeof proto.sort !== 'function') {\r\n    proto.sort = function() {\r\n      var _this = this;\r\n      var items = [];\r\n      this.forEach(function(value, name) {\r\n        items.push([name, value]);\r\n        if (!_this._entries) {\r\n          _this.delete(name);\r\n        }\r\n      });\r\n      items.sort(function(a, b) {\r\n        if (a[0] < b[0]) {\r\n          return -1;\r\n        } else if (a[0] > b[0]) {\r\n          return +1;\r\n        } else {\r\n          return 0;\r\n        }\r\n      });\r\n      if (_this._entries) { // force reset because IE keeps keys index\r\n        _this._entries = {};\r\n      }\r\n      for (var i = 0; i < items.length; i++) {\r\n        this.append(items[i][0], items[i][1]);\r\n      }\r\n    };\r\n  }\r\n\r\n  if (typeof proto._fromString !== 'function') {\r\n    Object.defineProperty(proto, '_fromString', {\r\n      enumerable: false,\r\n      configurable: false,\r\n      writable: false,\r\n      value: function(searchString) {\r\n        if (this._entries) {\r\n          this._entries = {};\r\n        } else {\r\n          var keys = [];\r\n          this.forEach(function(value, name) {\r\n            keys.push(name);\r\n          });\r\n          for (var i = 0; i < keys.length; i++) {\r\n            this.delete(keys[i]);\r\n          }\r\n        }\r\n\r\n        searchString = searchString.replace(/^\\?/, '');\r\n        var attributes = searchString.split('&');\r\n        var attribute;\r\n        for (var i = 0; i < attributes.length; i++) {\r\n          attribute = attributes[i].split('=');\r\n          this.append(\r\n            deserializeParam(attribute[0]),\r\n            (attribute.length > 1) ? deserializeParam(attribute[1]) : ''\r\n          );\r\n        }\r\n      }\r\n    });\r\n  }\r\n\r\n  // HTMLAnchorElement\r\n\r\n})(\r\n  (typeof global !== 'undefined') ? global\r\n    : ((typeof window !== 'undefined') ? window\r\n    : ((typeof self !== 'undefined') ? self : this))\r\n);\r\n\r\n(function(global) {\r\n  /**\r\n   * Polyfill URL\r\n   *\r\n   * Inspired from : https://github.com/arv/DOM-URL-Polyfill/blob/master/src/url.js\r\n   */\r\n\r\n  var checkIfURLIsSupported = function() {\r\n    try {\r\n      var u = new global.URL('b', 'http://a');\r\n      u.pathname = 'c d';\r\n      return (u.href === 'http://a/c%20d') && u.searchParams;\r\n    } catch (e) {\r\n      return false;\r\n    }\r\n  };\r\n\r\n\r\n  var polyfillURL = function() {\r\n    var _URL = global.URL;\r\n\r\n    var URL = function(url, base) {\r\n      if (typeof url !== 'string') url = String(url);\r\n      if (base && typeof base !== 'string') base = String(base);\r\n\r\n      // Only create another document if the base is different from current location.\r\n      var doc = document, baseElement;\r\n      if (base && (global.location === void 0 || base !== global.location.href)) {\r\n        base = base.toLowerCase();\r\n        doc = document.implementation.createHTMLDocument('');\r\n        baseElement = doc.createElement('base');\r\n        baseElement.href = base;\r\n        doc.head.appendChild(baseElement);\r\n        try {\r\n          if (baseElement.href.indexOf(base) !== 0) throw new Error(baseElement.href);\r\n        } catch (err) {\r\n          throw new Error('URL unable to set base ' + base + ' due to ' + err);\r\n        }\r\n      }\r\n\r\n      var anchorElement = doc.createElement('a');\r\n      anchorElement.href = url;\r\n      if (baseElement) {\r\n        doc.body.appendChild(anchorElement);\r\n        anchorElement.href = anchorElement.href; // force href to refresh\r\n      }\r\n\r\n      var inputElement = doc.createElement('input');\r\n      inputElement.type = 'url';\r\n      inputElement.value = url;\r\n\r\n      if (anchorElement.protocol === ':' || !/:/.test(anchorElement.href) || (!inputElement.checkValidity() && !base)) {\r\n        throw new TypeError('Invalid URL');\r\n      }\r\n\r\n      Object.defineProperty(this, '_anchorElement', {\r\n        value: anchorElement\r\n      });\r\n\r\n\r\n      // create a linked searchParams which reflect its changes on URL\r\n      var searchParams = new global.URLSearchParams(this.search);\r\n      var enableSearchUpdate = true;\r\n      var enableSearchParamsUpdate = true;\r\n      var _this = this;\r\n      ['append', 'delete', 'set'].forEach(function(methodName) {\r\n        var method = searchParams[methodName];\r\n        searchParams[methodName] = function() {\r\n          method.apply(searchParams, arguments);\r\n          if (enableSearchUpdate) {\r\n            enableSearchParamsUpdate = false;\r\n            _this.search = searchParams.toString();\r\n            enableSearchParamsUpdate = true;\r\n          }\r\n        };\r\n      });\r\n\r\n      Object.defineProperty(this, 'searchParams', {\r\n        value: searchParams,\r\n        enumerable: true\r\n      });\r\n\r\n      var search = void 0;\r\n      Object.defineProperty(this, '_updateSearchParams', {\r\n        enumerable: false,\r\n        configurable: false,\r\n        writable: false,\r\n        value: function() {\r\n          if (this.search !== search) {\r\n            search = this.search;\r\n            if (enableSearchParamsUpdate) {\r\n              enableSearchUpdate = false;\r\n              this.searchParams._fromString(this.search);\r\n              enableSearchUpdate = true;\r\n            }\r\n          }\r\n        }\r\n      });\r\n    };\r\n\r\n    var proto = URL.prototype;\r\n\r\n    var linkURLWithAnchorAttribute = function(attributeName) {\r\n      Object.defineProperty(proto, attributeName, {\r\n        get: function() {\r\n          return this._anchorElement[attributeName];\r\n        },\r\n        set: function(value) {\r\n          this._anchorElement[attributeName] = value;\r\n        },\r\n        enumerable: true\r\n      });\r\n    };\r\n\r\n    ['hash', 'host', 'hostname', 'port', 'protocol']\r\n      .forEach(function(attributeName) {\r\n        linkURLWithAnchorAttribute(attributeName);\r\n      });\r\n\r\n    Object.defineProperty(proto, 'search', {\r\n      get: function() {\r\n        return this._anchorElement['search'];\r\n      },\r\n      set: function(value) {\r\n        this._anchorElement['search'] = value;\r\n        this._updateSearchParams();\r\n      },\r\n      enumerable: true\r\n    });\r\n\r\n    Object.defineProperties(proto, {\r\n\r\n      'toString': {\r\n        get: function() {\r\n          var _this = this;\r\n          return function() {\r\n            return _this.href;\r\n          };\r\n        }\r\n      },\r\n\r\n      'href': {\r\n        get: function() {\r\n          return this._anchorElement.href.replace(/\\?$/, '');\r\n        },\r\n        set: function(value) {\r\n          this._anchorElement.href = value;\r\n          this._updateSearchParams();\r\n        },\r\n        enumerable: true\r\n      },\r\n\r\n      'pathname': {\r\n        get: function() {\r\n          return this._anchorElement.pathname.replace(/(^\\/?)/, '/');\r\n        },\r\n        set: function(value) {\r\n          this._anchorElement.pathname = value;\r\n        },\r\n        enumerable: true\r\n      },\r\n\r\n      'origin': {\r\n        get: function() {\r\n          // get expected port from protocol\r\n          var expectedPort = { 'http:': 80, 'https:': 443, 'ftp:': 21 }[this._anchorElement.protocol];\r\n          // add port to origin if, expected port is different than actual port\r\n          // and it is not empty f.e http://foo:8080\r\n          // 8080 != 80 && 8080 != ''\r\n          var addPortToOrigin = this._anchorElement.port != expectedPort &&\r\n            this._anchorElement.port !== '';\r\n\r\n          return this._anchorElement.protocol +\r\n            '//' +\r\n            this._anchorElement.hostname +\r\n            (addPortToOrigin ? (':' + this._anchorElement.port) : '');\r\n        },\r\n        enumerable: true\r\n      },\r\n\r\n      'password': { // TODO\r\n        get: function() {\r\n          return '';\r\n        },\r\n        set: function(value) {\r\n        },\r\n        enumerable: true\r\n      },\r\n\r\n      'username': { // TODO\r\n        get: function() {\r\n          return '';\r\n        },\r\n        set: function(value) {\r\n        },\r\n        enumerable: true\r\n      },\r\n    });\r\n\r\n    URL.createObjectURL = function(blob) {\r\n      return _URL.createObjectURL.apply(_URL, arguments);\r\n    };\r\n\r\n    URL.revokeObjectURL = function(url) {\r\n      return _URL.revokeObjectURL.apply(_URL, arguments);\r\n    };\r\n\r\n    global.URL = URL;\r\n\r\n  };\r\n\r\n  if (!checkIfURLIsSupported()) {\r\n    polyfillURL();\r\n  }\r\n\r\n  if ((global.location !== void 0) && !('origin' in global.location)) {\r\n    var getOrigin = function() {\r\n      return global.location.protocol + '//' + global.location.hostname + (global.location.port ? (':' + global.location.port) : '');\r\n    };\r\n\r\n    try {\r\n      Object.defineProperty(global.location, 'origin', {\r\n        get: getOrigin,\r\n        enumerable: true\r\n      });\r\n    } catch (e) {\r\n      setInterval(function() {\r\n        global.location.origin = getOrigin();\r\n      }, 100);\r\n    }\r\n  }\r\n\r\n})(\r\n  (typeof global !== 'undefined') ? global\r\n    : ((typeof window !== 'undefined') ? window\r\n    : ((typeof self !== 'undefined') ? self : this))\r\n);\r\n", "/*! *****************************************************************************\r\nCopyright (c) Microsoft Corporation.\r\n\r\nPermission to use, copy, modify, and/or distribute this software for any\r\npurpose with or without fee is hereby granted.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\r\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\r\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\r\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\r\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\r\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\r\nPERFORMANCE OF THIS SOFTWARE.\r\n***************************************************************************** */\r\n/* global global, define, System, Reflect, Promise */\r\nvar __extends;\r\nvar __assign;\r\nvar __rest;\r\nvar __decorate;\r\nvar __param;\r\nvar __metadata;\r\nvar __awaiter;\r\nvar __generator;\r\nvar __exportStar;\r\nvar __values;\r\nvar __read;\r\nvar __spread;\r\nvar __spreadArrays;\r\nvar __spreadArray;\r\nvar __await;\r\nvar __asyncGenerator;\r\nvar __asyncDelegator;\r\nvar __asyncValues;\r\nvar __makeTemplateObject;\r\nvar __importStar;\r\nvar __importDefault;\r\nvar __classPrivateFieldGet;\r\nvar __classPrivateFieldSet;\r\nvar __createBinding;\r\n(function (factory) {\r\n    var root = typeof global === \"object\" ? global : typeof self === \"object\" ? self : typeof this === \"object\" ? this : {};\r\n    if (typeof define === \"function\" && define.amd) {\r\n        define(\"tslib\", [\"exports\"], function (exports) { factory(createExporter(root, createExporter(exports))); });\r\n    }\r\n    else if (typeof module === \"object\" && typeof module.exports === \"object\") {\r\n        factory(createExporter(root, createExporter(module.exports)));\r\n    }\r\n    else {\r\n        factory(createExporter(root));\r\n    }\r\n    function createExporter(exports, previous) {\r\n        if (exports !== root) {\r\n            if (typeof Object.create === \"function\") {\r\n                Object.defineProperty(exports, \"__esModule\", { value: true });\r\n            }\r\n            else {\r\n                exports.__esModule = true;\r\n            }\r\n        }\r\n        return function (id, v) { return exports[id] = previous ? previous(id, v) : v; };\r\n    }\r\n})\r\n(function (exporter) {\r\n    var extendStatics = Object.setPrototypeOf ||\r\n        ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\r\n        function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\r\n\r\n    __extends = function (d, b) {\r\n        if (typeof b !== \"function\" && b !== null)\r\n            throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\r\n        extendStatics(d, b);\r\n        function __() { this.constructor = d; }\r\n        d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\r\n    };\r\n\r\n    __assign = Object.assign || function (t) {\r\n        for (var s, i = 1, n = arguments.length; i < n; i++) {\r\n            s = arguments[i];\r\n            for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\r\n        }\r\n        return t;\r\n    };\r\n\r\n    __rest = function (s, e) {\r\n        var t = {};\r\n        for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\r\n            t[p] = s[p];\r\n        if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\r\n            for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\r\n                if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\r\n                    t[p[i]] = s[p[i]];\r\n            }\r\n        return t;\r\n    };\r\n\r\n    __decorate = function (decorators, target, key, desc) {\r\n        var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\r\n        if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\r\n        else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\r\n        return c > 3 && r && Object.defineProperty(target, key, r), r;\r\n    };\r\n\r\n    __param = function (paramIndex, decorator) {\r\n        return function (target, key) { decorator(target, key, paramIndex); }\r\n    };\r\n\r\n    __metadata = function (metadataKey, metadataValue) {\r\n        if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\r\n    };\r\n\r\n    __awaiter = function (thisArg, _arguments, P, generator) {\r\n        function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\r\n        return new (P || (P = Promise))(function (resolve, reject) {\r\n            function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\r\n            function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\r\n            function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\r\n            step((generator = generator.apply(thisArg, _arguments || [])).next());\r\n        });\r\n    };\r\n\r\n    __generator = function (thisArg, body) {\r\n        var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;\r\n        return g = { next: verb(0), \"throw\": verb(1), \"return\": verb(2) }, typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\r\n        function verb(n) { return function (v) { return step([n, v]); }; }\r\n        function step(op) {\r\n            if (f) throw new TypeError(\"Generator is already executing.\");\r\n            while (_) try {\r\n                if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\r\n                if (y = 0, t) op = [op[0] & 2, t.value];\r\n                switch (op[0]) {\r\n                    case 0: case 1: t = op; break;\r\n                    case 4: _.label++; return { value: op[1], done: false };\r\n                    case 5: _.label++; y = op[1]; op = [0]; continue;\r\n                    case 7: op = _.ops.pop(); _.trys.pop(); continue;\r\n                    default:\r\n                        if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\r\n                        if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\r\n                        if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\r\n                        if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\r\n                        if (t[2]) _.ops.pop();\r\n                        _.trys.pop(); continue;\r\n                }\r\n                op = body.call(thisArg, _);\r\n            } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\r\n            if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\r\n        }\r\n    };\r\n\r\n    __exportStar = function(m, o) {\r\n        for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\r\n    };\r\n\r\n    __createBinding = Object.create ? (function(o, m, k, k2) {\r\n        if (k2 === undefined) k2 = k;\r\n        Object.defineProperty(o, k2, { enumerable: true, get: function() { return m[k]; } });\r\n    }) : (function(o, m, k, k2) {\r\n        if (k2 === undefined) k2 = k;\r\n        o[k2] = m[k];\r\n    });\r\n\r\n    __values = function (o) {\r\n        var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\r\n        if (m) return m.call(o);\r\n        if (o && typeof o.length === \"number\") return {\r\n            next: function () {\r\n                if (o && i >= o.length) o = void 0;\r\n                return { value: o && o[i++], done: !o };\r\n            }\r\n        };\r\n        throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\r\n    };\r\n\r\n    __read = function (o, n) {\r\n        var m = typeof Symbol === \"function\" && o[Symbol.iterator];\r\n        if (!m) return o;\r\n        var i = m.call(o), r, ar = [], e;\r\n        try {\r\n            while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\r\n        }\r\n        catch (error) { e = { error: error }; }\r\n        finally {\r\n            try {\r\n                if (r && !r.done && (m = i[\"return\"])) m.call(i);\r\n            }\r\n            finally { if (e) throw e.error; }\r\n        }\r\n        return ar;\r\n    };\r\n\r\n    /** @deprecated */\r\n    __spread = function () {\r\n        for (var ar = [], i = 0; i < arguments.length; i++)\r\n            ar = ar.concat(__read(arguments[i]));\r\n        return ar;\r\n    };\r\n\r\n    /** @deprecated */\r\n    __spreadArrays = function () {\r\n        for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\r\n        for (var r = Array(s), k = 0, i = 0; i < il; i++)\r\n            for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\r\n                r[k] = a[j];\r\n        return r;\r\n    };\r\n\r\n    __spreadArray = function (to, from, pack) {\r\n        if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\r\n            if (ar || !(i in from)) {\r\n                if (!ar) ar = Array.prototype.slice.call(from, 0, i);\r\n                ar[i] = from[i];\r\n            }\r\n        }\r\n        return to.concat(ar || Array.prototype.slice.call(from));\r\n    };\r\n\r\n    __await = function (v) {\r\n        return this instanceof __await ? (this.v = v, this) : new __await(v);\r\n    };\r\n\r\n    __asyncGenerator = function (thisArg, _arguments, generator) {\r\n        if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n        var g = generator.apply(thisArg, _arguments || []), i, q = [];\r\n        return i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i;\r\n        function verb(n) { if (g[n]) i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; }\r\n        function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\r\n        function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r);  }\r\n        function fulfill(value) { resume(\"next\", value); }\r\n        function reject(value) { resume(\"throw\", value); }\r\n        function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\r\n    };\r\n\r\n    __asyncDelegator = function (o) {\r\n        var i, p;\r\n        return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\r\n        function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: n === \"return\" } : f ? f(v) : v; } : f; }\r\n    };\r\n\r\n    __asyncValues = function (o) {\r\n        if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n        var m = o[Symbol.asyncIterator], i;\r\n        return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\r\n        function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\r\n        function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\r\n    };\r\n\r\n    __makeTemplateObject = function (cooked, raw) {\r\n        if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\r\n        return cooked;\r\n    };\r\n\r\n    var __setModuleDefault = Object.create ? (function(o, v) {\r\n        Object.defineProperty(o, \"default\", { enumerable: true, value: v });\r\n    }) : function(o, v) {\r\n        o[\"default\"] = v;\r\n    };\r\n\r\n    __importStar = function (mod) {\r\n        if (mod && mod.__esModule) return mod;\r\n        var result = {};\r\n        if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\r\n        __setModuleDefault(result, mod);\r\n        return result;\r\n    };\r\n\r\n    __importDefault = function (mod) {\r\n        return (mod && mod.__esModule) ? mod : { \"default\": mod };\r\n    };\r\n\r\n    __classPrivateFieldGet = function (receiver, state, kind, f) {\r\n        if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\r\n        if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\r\n        return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\r\n    };\r\n\r\n    __classPrivateFieldSet = function (receiver, state, value, kind, f) {\r\n        if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\r\n        if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\r\n        if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\r\n        return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\r\n    };\r\n\r\n    exporter(\"__extends\", __extends);\r\n    exporter(\"__assign\", __assign);\r\n    exporter(\"__rest\", __rest);\r\n    exporter(\"__decorate\", __decorate);\r\n    exporter(\"__param\", __param);\r\n    exporter(\"__metadata\", __metadata);\r\n    exporter(\"__awaiter\", __awaiter);\r\n    exporter(\"__generator\", __generator);\r\n    exporter(\"__exportStar\", __exportStar);\r\n    exporter(\"__createBinding\", __createBinding);\r\n    exporter(\"__values\", __values);\r\n    exporter(\"__read\", __read);\r\n    exporter(\"__spread\", __spread);\r\n    exporter(\"__spreadArrays\", __spreadArrays);\r\n    exporter(\"__spreadArray\", __spreadArray);\r\n    exporter(\"__await\", __await);\r\n    exporter(\"__asyncGenerator\", __asyncGenerator);\r\n    exporter(\"__asyncDelegator\", __asyncDelegator);\r\n    exporter(\"__asyncValues\", __asyncValues);\r\n    exporter(\"__makeTemplateObject\", __makeTemplateObject);\r\n    exporter(\"__importStar\", __importStar);\r\n    exporter(\"__importDefault\", __importDefault);\r\n    exporter(\"__classPrivateFieldGet\", __classPrivateFieldGet);\r\n    exporter(\"__classPrivateFieldSet\", __classPrivateFieldSet);\r\n});\r\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n  \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n  try {\n    return document.execCommand(type);\n  } catch (err) {\n    return false;\n  }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n  var selectedText = select_default()(target);\n  command('cut');\n  return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n  var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n  var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n  fakeElement.style.fontSize = '12pt'; // Reset box model\n\n  fakeElement.style.border = '0';\n  fakeElement.style.padding = '0';\n  fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n  fakeElement.style.position = 'absolute';\n  fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n  var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n  fakeElement.style.top = \"\".concat(yPosition, \"px\");\n  fakeElement.setAttribute('readonly', '');\n  fakeElement.value = value;\n  return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n  var fakeElement = createFakeElement(value);\n  options.container.appendChild(fakeElement);\n  var selectedText = select_default()(fakeElement);\n  command('copy');\n  fakeElement.remove();\n  return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n  var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n    container: document.body\n  };\n  var selectedText = '';\n\n  if (typeof target === 'string') {\n    selectedText = fakeCopyAction(target, options);\n  } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n    // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n    selectedText = fakeCopyAction(target.value, options);\n  } else {\n    selectedText = select_default()(target);\n    command('copy');\n  }\n\n  return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n  var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n  // Defines base properties passed from constructor.\n  var _options$action = options.action,\n      action = _options$action === void 0 ? 'copy' : _options$action,\n      container = options.container,\n      target = options.target,\n      text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n  if (action !== 'copy' && action !== 'cut') {\n    throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n  } // Sets the `target` property using an element that will be have its content copied.\n\n\n  if (target !== undefined) {\n    if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n      if (action === 'copy' && target.hasAttribute('disabled')) {\n        throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n      }\n\n      if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n        throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n      }\n    } else {\n      throw new Error('Invalid \"target\" value, use a valid Element');\n    }\n  } // Define selection strategy based on `text` property.\n\n\n  if (text) {\n    return actions_copy(text, {\n      container: container\n    });\n  } // Defines which selection strategy based on `target` property.\n\n\n  if (target) {\n    return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n      container: container\n    });\n  }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n  var attribute = \"data-clipboard-\".concat(suffix);\n\n  if (!element.hasAttribute(attribute)) {\n    return;\n  }\n\n  return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n  _inherits(Clipboard, _Emitter);\n\n  var _super = _createSuper(Clipboard);\n\n  /**\n   * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n   * @param {Object} options\n   */\n  function Clipboard(trigger, options) {\n    var _this;\n\n    _classCallCheck(this, Clipboard);\n\n    _this = _super.call(this);\n\n    _this.resolveOptions(options);\n\n    _this.listenClick(trigger);\n\n    return _this;\n  }\n  /**\n   * Defines if attributes would be resolved using internal setter functions\n   * or custom functions that were passed in the constructor.\n   * @param {Object} options\n   */\n\n\n  _createClass(Clipboard, [{\n    key: \"resolveOptions\",\n    value: function resolveOptions() {\n      var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n      this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n      this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n      this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n      this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n    }\n    /**\n     * Adds a click event listener to the passed trigger.\n     * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n     */\n\n  }, {\n    key: \"listenClick\",\n    value: function listenClick(trigger) {\n      var _this2 = this;\n\n      this.listener = listen_default()(trigger, 'click', function (e) {\n        return _this2.onClick(e);\n      });\n    }\n    /**\n     * Defines a new `ClipboardAction` on each click event.\n     * @param {Event} e\n     */\n\n  }, {\n    key: \"onClick\",\n    value: function onClick(e) {\n      var trigger = e.delegateTarget || e.currentTarget;\n      var action = this.action(trigger) || 'copy';\n      var text = actions_default({\n        action: action,\n        container: this.container,\n        target: this.target(trigger),\n        text: this.text(trigger)\n      }); // Fires an event based on the copy operation result.\n\n      this.emit(text ? 'success' : 'error', {\n        action: action,\n        text: text,\n        trigger: trigger,\n        clearSelection: function clearSelection() {\n          if (trigger) {\n            trigger.focus();\n          }\n\n          window.getSelection().removeAllRanges();\n        }\n      });\n    }\n    /**\n     * Default `action` lookup function.\n     * @param {Element} trigger\n     */\n\n  }, {\n    key: \"defaultAction\",\n    value: function defaultAction(trigger) {\n      return getAttributeValue('action', trigger);\n    }\n    /**\n     * Default `target` lookup function.\n     * @param {Element} trigger\n     */\n\n  }, {\n    key: \"defaultTarget\",\n    value: function defaultTarget(trigger) {\n      var selector = getAttributeValue('target', trigger);\n\n      if (selector) {\n        return document.querySelector(selector);\n      }\n    }\n    /**\n     * Allow fire programmatically a copy action\n     * @param {String|HTMLElement} target\n     * @param {Object} options\n     * @returns Text copied.\n     */\n\n  }, {\n    key: \"defaultText\",\n\n    /**\n     * Default `text` lookup function.\n     * @param {Element} trigger\n     */\n    value: function defaultText(trigger) {\n      return getAttributeValue('text', trigger);\n    }\n    /**\n     * Destroy lifecycle.\n     */\n\n  }, {\n    key: \"destroy\",\n    value: function destroy() {\n      this.listener.destroy();\n    }\n  }], [{\n    key: \"copy\",\n    value: function copy(target) {\n      var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n        container: document.body\n      };\n      return actions_copy(target, options);\n    }\n    /**\n     * Allow fire programmatically a cut action\n     * @param {String|HTMLElement} target\n     * @returns Text cutted.\n     */\n\n  }, {\n    key: \"cut\",\n    value: function cut(target) {\n      return actions_cut(target);\n    }\n    /**\n     * Returns the support of the given action, or all actions if no action is\n     * given.\n     * @param {String} [action]\n     */\n\n  }, {\n    key: \"isSupported\",\n    value: function isSupported() {\n      var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n      var actions = typeof action === 'string' ? [action] : action;\n      var support = !!document.queryCommandSupported;\n      actions.forEach(function (action) {\n        support = support && !!document.queryCommandSupported(action);\n      });\n      return support;\n    }\n  }]);\n\n  return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n    var proto = Element.prototype;\n\n    proto.matches = proto.matchesSelector ||\n                    proto.mozMatchesSelector ||\n                    proto.msMatchesSelector ||\n                    proto.oMatchesSelector ||\n                    proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n    while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n        if (typeof element.matches === 'function' &&\n            element.matches(selector)) {\n          return element;\n        }\n        element = element.parentNode;\n    }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n    var listenerFn = listener.apply(this, arguments);\n\n    element.addEventListener(type, listenerFn, useCapture);\n\n    return {\n        destroy: function() {\n            element.removeEventListener(type, listenerFn, useCapture);\n        }\n    }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n    // Handle the regular Element usage\n    if (typeof elements.addEventListener === 'function') {\n        return _delegate.apply(null, arguments);\n    }\n\n    // Handle Element-less usage, it defaults to global delegation\n    if (typeof type === 'function') {\n        // Use `document` as the first parameter, then apply arguments\n        // This is a short way to .unshift `arguments` without running into deoptimizations\n        return _delegate.bind(null, document).apply(null, arguments);\n    }\n\n    // Handle Selector-based usage\n    if (typeof elements === 'string') {\n        elements = document.querySelectorAll(elements);\n    }\n\n    // Handle Array-like based usage\n    return Array.prototype.map.call(elements, function (element) {\n        return _delegate(element, selector, type, callback, useCapture);\n    });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n    return function(e) {\n        e.delegateTarget = closest(e.target, selector);\n\n        if (e.delegateTarget) {\n            callback.call(element, e);\n        }\n    }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n    return value !== undefined\n        && value instanceof HTMLElement\n        && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n    var type = Object.prototype.toString.call(value);\n\n    return value !== undefined\n        && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n        && ('length' in value)\n        && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n    return typeof value === 'string'\n        || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n    var type = Object.prototype.toString.call(value);\n\n    return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n    if (!target && !type && !callback) {\n        throw new Error('Missing required arguments');\n    }\n\n    if (!is.string(type)) {\n        throw new TypeError('Second argument must be a String');\n    }\n\n    if (!is.fn(callback)) {\n        throw new TypeError('Third argument must be a Function');\n    }\n\n    if (is.node(target)) {\n        return listenNode(target, type, callback);\n    }\n    else if (is.nodeList(target)) {\n        return listenNodeList(target, type, callback);\n    }\n    else if (is.string(target)) {\n        return listenSelector(target, type, callback);\n    }\n    else {\n        throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n    }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n    node.addEventListener(type, callback);\n\n    return {\n        destroy: function() {\n            node.removeEventListener(type, callback);\n        }\n    }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n    Array.prototype.forEach.call(nodeList, function(node) {\n        node.addEventListener(type, callback);\n    });\n\n    return {\n        destroy: function() {\n            Array.prototype.forEach.call(nodeList, function(node) {\n                node.removeEventListener(type, callback);\n            });\n        }\n    }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n    return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n    var selectedText;\n\n    if (element.nodeName === 'SELECT') {\n        element.focus();\n\n        selectedText = element.value;\n    }\n    else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n        var isReadOnly = element.hasAttribute('readonly');\n\n        if (!isReadOnly) {\n            element.setAttribute('readonly', '');\n        }\n\n        element.select();\n        element.setSelectionRange(0, element.value.length);\n\n        if (!isReadOnly) {\n            element.removeAttribute('readonly');\n        }\n\n        selectedText = element.value;\n    }\n    else {\n        if (element.hasAttribute('contenteditable')) {\n            element.focus();\n        }\n\n        var selection = window.getSelection();\n        var range = document.createRange();\n\n        range.selectNodeContents(element);\n        selection.removeAllRanges();\n        selection.addRange(range);\n\n        selectedText = selection.toString();\n    }\n\n    return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n  // Keep this empty so it's easier to inherit from\n  // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n  on: function (name, callback, ctx) {\n    var e = this.e || (this.e = {});\n\n    (e[name] || (e[name] = [])).push({\n      fn: callback,\n      ctx: ctx\n    });\n\n    return this;\n  },\n\n  once: function (name, callback, ctx) {\n    var self = this;\n    function listener () {\n      self.off(name, listener);\n      callback.apply(ctx, arguments);\n    };\n\n    listener._ = callback\n    return this.on(name, listener, ctx);\n  },\n\n  emit: function (name) {\n    var data = [].slice.call(arguments, 1);\n    var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n    var i = 0;\n    var len = evtArr.length;\n\n    for (i; i < len; i++) {\n      evtArr[i].fn.apply(evtArr[i].ctx, data);\n    }\n\n    return this;\n  },\n\n  off: function (name, callback) {\n    var e = this.e || (this.e = {});\n    var evts = e[name];\n    var liveEvents = [];\n\n    if (evts && callback) {\n      for (var i = 0, len = evts.length; i < len; i++) {\n        if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n          liveEvents.push(evts[i]);\n      }\n    }\n\n    // Remove event from queue to prevent memory leak\n    // Suggested by https://github.com/lazd\n    // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n    (liveEvents.length)\n      ? e[name] = liveEvents\n      : delete e[name];\n\n    return this;\n  }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param  {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n  var str = '' + string;\n  var match = matchHtmlRegExp.exec(str);\n\n  if (!match) {\n    return str;\n  }\n\n  var escape;\n  var html = '';\n  var index = 0;\n  var lastIndex = 0;\n\n  for (index = match.index; index < str.length; index++) {\n    switch (str.charCodeAt(index)) {\n      case 34: // \"\n        escape = '&quot;';\n        break;\n      case 38: // &\n        escape = '&amp;';\n        break;\n      case 39: // '\n        escape = '&#39;';\n        break;\n      case 60: // <\n        escape = '&lt;';\n        break;\n      case 62: // >\n        escape = '&gt;';\n        break;\n      default:\n        continue;\n    }\n\n    if (lastIndex !== index) {\n      html += str.substring(lastIndex, index);\n    }\n\n    lastIndex = index + 1;\n    html += escape;\n  }\n\n  return lastIndex !== index\n    ? html + str.substring(lastIndex, index)\n    : html;\n}\n", "Array.prototype.flat||Object.defineProperty(Array.prototype,\"flat\",{configurable:!0,value:function r(){var t=isNaN(arguments[0])?1:Number(arguments[0]);return t?Array.prototype.reduce.call(this,function(a,e){return Array.isArray(e)?a.push.apply(a,r.call(e,t-1)):a.push(e),a},[]):Array.prototype.slice.call(this)},writable:!0}),Array.prototype.flatMap||Object.defineProperty(Array.prototype,\"flatMap\",{configurable:!0,value:function(r){return Array.prototype.map.apply(this,arguments).flat()},writable:!0})\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"array-flat-polyfill\"\nimport \"focus-visible\"\nimport \"unfetch/polyfill\"\nimport \"url-polyfill\"\n\nimport {\n  EMPTY,\n  NEVER,\n  Subject,\n  defer,\n  delay,\n  filter,\n  map,\n  merge,\n  mergeWith,\n  shareReplay,\n  switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n  at,\n  getOptionalElement,\n  requestJSON,\n  setToggle,\n  watchDocument,\n  watchKeyboard,\n  watchLocation,\n  watchLocationTarget,\n  watchMedia,\n  watchPrint,\n  watchViewport\n} from \"./browser\"\nimport {\n  getComponentElement,\n  getComponentElements,\n  mountBackToTop,\n  mountContent,\n  mountDialog,\n  mountHeader,\n  mountHeaderTitle,\n  mountPalette,\n  mountSearch,\n  mountSearchHiglight,\n  mountSidebar,\n  mountSource,\n  mountTableOfContents,\n  mountTabs,\n  watchHeader,\n  watchMain\n} from \"./components\"\nimport {\n  SearchIndex,\n  setupClipboardJS,\n  setupInstantLoading,\n  setupVersionSelector\n} from \"./integrations\"\nimport {\n  patchIndeterminate,\n  patchScrollfix,\n  patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$   = watchLocationTarget()\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$   = watchMedia(\"(min-width: 960px)\")\nconst screen$   = watchMedia(\"(min-width: 1220px)\")\nconst print$    = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n  ? __search?.index || requestJSON<SearchIndex>(\n    new URL(\"search/search_index.json\", config.base)\n  )\n  : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject<string>()\nsetupClipboardJS({ alert$ })\n\n/* Set up instant loading, if enabled */\nif (feature(\"navigation.instant\"))\n  setupInstantLoading({ document$, location$, viewport$ })\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n  setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n  .pipe(\n    delay(125)\n  )\n    .subscribe(() => {\n      setToggle(\"drawer\", false)\n      setToggle(\"search\", false)\n    })\n\n/* Set up global keyboard handlers */\nkeyboard$\n  .pipe(\n    filter(({ mode }) => mode === \"global\")\n  )\n    .subscribe(key => {\n      switch (key.type) {\n\n        /* Go to previous page */\n        case \"p\":\n        case \",\":\n          const prev = getOptionalElement(\"[href][rel=prev]\")\n          if (typeof prev !== \"undefined\")\n            prev.click()\n          break\n\n        /* Go to next page */\n        case \"n\":\n        case \".\":\n          const next = getOptionalElement(\"[href][rel=next]\")\n          if (typeof next !== \"undefined\")\n            next.click()\n          break\n      }\n    })\n\n/* Set up patches */\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n  .pipe(\n    map(() => getComponentElement(\"main\")),\n    switchMap(el => watchMain(el, { viewport$, header$ })),\n    shareReplay(1)\n  )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n  /* Dialog */\n  ...getComponentElements(\"dialog\")\n    .map(el => mountDialog(el, { alert$ })),\n\n  /* Header */\n  ...getComponentElements(\"header\")\n    .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n  /* Color palette */\n  ...getComponentElements(\"palette\")\n    .map(el => mountPalette(el)),\n\n  /* Search */\n  ...getComponentElements(\"search\")\n    .map(el => mountSearch(el, { index$, keyboard$ })),\n\n  /* Repository information */\n  ...getComponentElements(\"source\")\n    .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n  /* Content */\n  ...getComponentElements(\"content\")\n    .map(el => mountContent(el, { target$, print$ })),\n\n  /* Search highlighting */\n  ...getComponentElements(\"content\")\n    .map(el => feature(\"search.highlight\")\n      ? mountSearchHiglight(el, { index$, location$ })\n      : EMPTY\n    ),\n\n  /* Header title */\n  ...getComponentElements(\"header-title\")\n    .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n  /* Sidebar */\n  ...getComponentElements(\"sidebar\")\n    .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n      ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n      : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n    ),\n\n  /* Navigation tabs */\n  ...getComponentElements(\"tabs\")\n    .map(el => mountTabs(el, { viewport$, header$ })),\n\n  /* Table of contents */\n  ...getComponentElements(\"toc\")\n    .map(el => mountTableOfContents(el, { viewport$, header$, target$ })),\n\n  /* Back-to-top button */\n  ...getComponentElements(\"top\")\n    .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n  .pipe(\n    switchMap(() => content$),\n    mergeWith(control$),\n    shareReplay(1)\n  )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$  = document$          /* Document observable */\nwindow.location$  = location$          /* Location subject */\nwindow.target$    = target$            /* Location target observable */\nwindow.keyboard$  = keyboard$          /* Keyboard observable */\nwindow.viewport$  = viewport$          /* Viewport observable */\nwindow.tablet$    = tablet$            /* Media tablet observable */\nwindow.screen$    = screen$            /* Media screen observable */\nwindow.print$     = print$             /* Media print observable */\nwindow.alert$     = alert$             /* Alert subject */\nwindow.component$ = component$         /* Component observable */\n", "self.fetch||(self.fetch=function(e,n){return n=n||{},new Promise(function(t,s){var r=new XMLHttpRequest,o=[],u=[],i={},a=function(){return{ok:2==(r.status/100|0),statusText:r.statusText,status:r.status,url:r.responseURL,text:function(){return Promise.resolve(r.responseText)},json:function(){return Promise.resolve(r.responseText).then(JSON.parse)},blob:function(){return Promise.resolve(new Blob([r.response]))},clone:a,headers:{keys:function(){return o},entries:function(){return u},get:function(e){return i[e.toLowerCase()]},has:function(e){return e.toLowerCase()in i}}}};for(var c in r.open(n.method||\"get\",e,!0),r.onload=function(){r.getAllResponseHeaders().replace(/^(.*?):[^\\S\\n]*([\\s\\S]*?)$/gm,function(e,n,t){o.push(n=n.toLowerCase()),u.push([n,t]),i[n]=i[n]?i[n]+\",\"+t:t}),t(a())},r.onerror=s,r.withCredentials=\"include\"==n.credentials,n.headers)r.setRequestHeader(c,n.headers[c]);r.send(n.body||null)})});\n", "import tslib from '../tslib.js';\r\nconst {\r\n    __extends,\r\n    __assign,\r\n    __rest,\r\n    __decorate,\r\n    __param,\r\n    __metadata,\r\n    __awaiter,\r\n    __generator,\r\n    __exportStar,\r\n    __createBinding,\r\n    __values,\r\n    __read,\r\n    __spread,\r\n    __spreadArrays,\r\n    __spreadArray,\r\n    __await,\r\n    __asyncGenerator,\r\n    __asyncDelegator,\r\n    __asyncValues,\r\n    __makeTemplateObject,\r\n    __importStar,\r\n    __importDefault,\r\n    __classPrivateFieldGet,\r\n    __classPrivateFieldSet,\r\n} = tslib;\r\nexport {\r\n    __extends,\r\n    __assign,\r\n    __rest,\r\n    __decorate,\r\n    __param,\r\n    __metadata,\r\n    __awaiter,\r\n    __generator,\r\n    __exportStar,\r\n    __createBinding,\r\n    __values,\r\n    __read,\r\n    __spread,\r\n    __spreadArrays,\r\n    __spreadArray,\r\n    __await,\r\n    __asyncGenerator,\r\n    __asyncDelegator,\r\n    __asyncValues,\r\n    __makeTemplateObject,\r\n    __importStar,\r\n    __importDefault,\r\n    __classPrivateFieldGet,\r\n    __classPrivateFieldSet,\r\n};\r\n", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  ReplaySubject,\n  Subject,\n  fromEvent\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch document\n *\n * Documents are implemented as subjects, so all downstream observables are\n * automatically updated when a new document is emitted.\n *\n * @returns Document subject\n */\nexport function watchDocument(): Subject<Document> {\n  const document$ = new ReplaySubject<Document>(1)\n  fromEvent(document, \"DOMContentLoaded\", { once: true })\n    .subscribe(() => document$.next(document))\n\n  /* Return document */\n  return document$\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve all elements matching the query selector\n *\n * @template T - Element type\n *\n * @param selector - Query selector\n * @param node - Node of reference\n *\n * @returns Elements\n */\nexport function getElements<T extends keyof HTMLElementTagNameMap>(\n  selector: T, node?: ParentNode\n): HTMLElementTagNameMap[T][]\n\nexport function getElements<T extends HTMLElement>(\n  selector: string, node?: ParentNode\n): T[]\n\nexport function getElements<T extends HTMLElement>(\n  selector: string, node: ParentNode = document\n): T[] {\n  return Array.from(node.querySelectorAll<T>(selector))\n}\n\n/**\n * Retrieve an element matching a query selector or throw a reference error\n *\n * Note that this function assumes that the element is present. If unsure if an\n * element is existent, use the `getOptionalElement` function instead.\n *\n * @template T - Element type\n *\n * @param selector - Query selector\n * @param node - Node of reference\n *\n * @returns Element\n */\nexport function getElement<T extends keyof HTMLElementTagNameMap>(\n  selector: T, node?: ParentNode\n): HTMLElementTagNameMap[T]\n\nexport function getElement<T extends HTMLElement>(\n  selector: string, node?: ParentNode\n): T\n\nexport function getElement<T extends HTMLElement>(\n  selector: string, node: ParentNode = document\n): T {\n  const el = getOptionalElement<T>(selector, node)\n  if (typeof el === \"undefined\")\n    throw new ReferenceError(\n      `Missing element: expected \"${selector}\" to be present`\n    )\n\n  /* Return element */\n  return el\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Retrieve an optional element matching the query selector\n *\n * @template T - Element type\n *\n * @param selector - Query selector\n * @param node - Node of reference\n *\n * @returns Element or nothing\n */\nexport function getOptionalElement<T extends keyof HTMLElementTagNameMap>(\n  selector: T, node?: ParentNode\n): HTMLElementTagNameMap[T] | undefined\n\nexport function getOptionalElement<T extends HTMLElement>(\n  selector: string, node?: ParentNode\n): T | undefined\n\nexport function getOptionalElement<T extends HTMLElement>(\n  selector: string, node: ParentNode = document\n): T | undefined {\n  return node.querySelector<T>(selector) || undefined\n}\n\n/**\n * Retrieve the currently active element\n *\n * @returns Element or nothing\n */\nexport function getActiveElement(): HTMLElement | undefined {\n  return document.activeElement instanceof HTMLElement\n    ? document.activeElement || undefined\n    : undefined\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  debounceTime,\n  distinctUntilChanged,\n  fromEvent,\n  map,\n  merge,\n  startWith\n} from \"rxjs\"\n\nimport { getActiveElement } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch element focus\n *\n * Previously, this function used `focus` and `blur` events to determine whether\n * an element is focused, but this doesn't work if there are focusable elements\n * within the elements itself. A better solutions are `focusin` and `focusout`\n * events, which bubble up the tree and allow for more fine-grained control.\n *\n * `debounceTime` is necessary, because when a focus change happens inside an\n * element, the observable would first emit `false` and then `true` again.\n *\n * @param el - Element\n *\n * @returns Element focus observable\n */\nexport function watchElementFocus(\n  el: HTMLElement\n): Observable<boolean> {\n  return merge(\n    fromEvent(document.body, \"focusin\"),\n    fromEvent(document.body, \"focusout\")\n  )\n    .pipe(\n      debounceTime(1),\n      map(() => {\n        const active = getActiveElement()\n        return typeof active !== \"undefined\"\n          ? el.contains(active)\n          : false\n      }),\n      startWith(el === getActiveElement()),\n      distinctUntilChanged()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  animationFrameScheduler,\n  auditTime,\n  fromEvent,\n  map,\n  merge,\n  startWith\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Element offset\n */\nexport interface ElementOffset {\n  x: number                            /* Horizontal offset */\n  y: number                            /* Vertical offset */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve element offset\n *\n * @param el - Element\n *\n * @returns Element offset\n */\nexport function getElementOffset(\n  el: HTMLElement\n): ElementOffset {\n  return {\n    x: el.offsetLeft,\n    y: el.offsetTop\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch element offset\n *\n * @param el - Element\n *\n * @returns Element offset observable\n */\nexport function watchElementOffset(\n  el: HTMLElement\n): Observable<ElementOffset> {\n  return merge(\n    fromEvent(window, \"load\"),\n    fromEvent(window, \"resize\")\n  )\n    .pipe(\n      auditTime(0, animationFrameScheduler),\n      map(() => getElementOffset(el)),\n      startWith(getElementOffset(el))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  animationFrameScheduler,\n  auditTime,\n  fromEvent,\n  map,\n  merge,\n  startWith\n} from \"rxjs\"\n\nimport { ElementOffset } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve element content offset (= scroll offset)\n *\n * @param el - Element\n *\n * @returns Element content offset\n */\nexport function getElementContentOffset(\n  el: HTMLElement\n): ElementOffset {\n  return {\n    x: el.scrollLeft,\n    y: el.scrollTop\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch element content offset\n *\n * @param el - Element\n *\n * @returns Element content offset observable\n */\nexport function watchElementContentOffset(\n  el: HTMLElement\n): Observable<ElementOffset> {\n  return merge(\n    fromEvent(el, \"scroll\"),\n    fromEvent(window, \"resize\")\n  )\n    .pipe(\n      auditTime(0, animationFrameScheduler),\n      map(() => getElementContentOffset(el)),\n      startWith(getElementContentOffset(el))\n    )\n}\n", "/**\r\n * A collection of shims that provide minimal functionality of the ES6 collections.\r\n *\r\n * These implementations are not meant to be used outside of the ResizeObserver\r\n * modules as they cover only a limited range of use cases.\r\n */\r\n/* eslint-disable require-jsdoc, valid-jsdoc */\r\nvar MapShim = (function () {\r\n    if (typeof Map !== 'undefined') {\r\n        return Map;\r\n    }\r\n    /**\r\n     * Returns index in provided array that matches the specified key.\r\n     *\r\n     * @param {Array<Array>} arr\r\n     * @param {*} key\r\n     * @returns {number}\r\n     */\r\n    function getIndex(arr, key) {\r\n        var result = -1;\r\n        arr.some(function (entry, index) {\r\n            if (entry[0] === key) {\r\n                result = index;\r\n                return true;\r\n            }\r\n            return false;\r\n        });\r\n        return result;\r\n    }\r\n    return /** @class */ (function () {\r\n        function class_1() {\r\n            this.__entries__ = [];\r\n        }\r\n        Object.defineProperty(class_1.prototype, \"size\", {\r\n            /**\r\n             * @returns {boolean}\r\n             */\r\n            get: function () {\r\n                return this.__entries__.length;\r\n            },\r\n            enumerable: true,\r\n            configurable: true\r\n        });\r\n        /**\r\n         * @param {*} key\r\n         * @returns {*}\r\n         */\r\n        class_1.prototype.get = function (key) {\r\n            var index = getIndex(this.__entries__, key);\r\n            var entry = this.__entries__[index];\r\n            return entry && entry[1];\r\n        };\r\n        /**\r\n         * @param {*} key\r\n         * @param {*} value\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.set = function (key, value) {\r\n            var index = getIndex(this.__entries__, key);\r\n            if (~index) {\r\n                this.__entries__[index][1] = value;\r\n            }\r\n            else {\r\n                this.__entries__.push([key, value]);\r\n            }\r\n        };\r\n        /**\r\n         * @param {*} key\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.delete = function (key) {\r\n            var entries = this.__entries__;\r\n            var index = getIndex(entries, key);\r\n            if (~index) {\r\n                entries.splice(index, 1);\r\n            }\r\n        };\r\n        /**\r\n         * @param {*} key\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.has = function (key) {\r\n            return !!~getIndex(this.__entries__, key);\r\n        };\r\n        /**\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.clear = function () {\r\n            this.__entries__.splice(0);\r\n        };\r\n        /**\r\n         * @param {Function} callback\r\n         * @param {*} [ctx=null]\r\n         * @returns {void}\r\n         */\r\n        class_1.prototype.forEach = function (callback, ctx) {\r\n            if (ctx === void 0) { ctx = null; }\r\n            for (var _i = 0, _a = this.__entries__; _i < _a.length; _i++) {\r\n                var entry = _a[_i];\r\n                callback.call(ctx, entry[1], entry[0]);\r\n            }\r\n        };\r\n        return class_1;\r\n    }());\r\n})();\n\n/**\r\n * Detects whether window and document objects are available in current environment.\r\n */\r\nvar isBrowser = typeof window !== 'undefined' && typeof document !== 'undefined' && window.document === document;\n\n// Returns global object of a current environment.\r\nvar global$1 = (function () {\r\n    if (typeof global !== 'undefined' && global.Math === Math) {\r\n        return global;\r\n    }\r\n    if (typeof self !== 'undefined' && self.Math === Math) {\r\n        return self;\r\n    }\r\n    if (typeof window !== 'undefined' && window.Math === Math) {\r\n        return window;\r\n    }\r\n    // eslint-disable-next-line no-new-func\r\n    return Function('return this')();\r\n})();\n\n/**\r\n * A shim for the requestAnimationFrame which falls back to the setTimeout if\r\n * first one is not supported.\r\n *\r\n * @returns {number} Requests' identifier.\r\n */\r\nvar requestAnimationFrame$1 = (function () {\r\n    if (typeof requestAnimationFrame === 'function') {\r\n        // It's required to use a bounded function because IE sometimes throws\r\n        // an \"Invalid calling object\" error if rAF is invoked without the global\r\n        // object on the left hand side.\r\n        return requestAnimationFrame.bind(global$1);\r\n    }\r\n    return function (callback) { return setTimeout(function () { return callback(Date.now()); }, 1000 / 60); };\r\n})();\n\n// Defines minimum timeout before adding a trailing call.\r\nvar trailingTimeout = 2;\r\n/**\r\n * Creates a wrapper function which ensures that provided callback will be\r\n * invoked only once during the specified delay period.\r\n *\r\n * @param {Function} callback - Function to be invoked after the delay period.\r\n * @param {number} delay - Delay after which to invoke callback.\r\n * @returns {Function}\r\n */\r\nfunction throttle (callback, delay) {\r\n    var leadingCall = false, trailingCall = false, lastCallTime = 0;\r\n    /**\r\n     * Invokes the original callback function and schedules new invocation if\r\n     * the \"proxy\" was called during current request.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    function resolvePending() {\r\n        if (leadingCall) {\r\n            leadingCall = false;\r\n            callback();\r\n        }\r\n        if (trailingCall) {\r\n            proxy();\r\n        }\r\n    }\r\n    /**\r\n     * Callback invoked after the specified delay. It will further postpone\r\n     * invocation of the original function delegating it to the\r\n     * requestAnimationFrame.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    function timeoutCallback() {\r\n        requestAnimationFrame$1(resolvePending);\r\n    }\r\n    /**\r\n     * Schedules invocation of the original function.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    function proxy() {\r\n        var timeStamp = Date.now();\r\n        if (leadingCall) {\r\n            // Reject immediately following calls.\r\n            if (timeStamp - lastCallTime < trailingTimeout) {\r\n                return;\r\n            }\r\n            // Schedule new call to be in invoked when the pending one is resolved.\r\n            // This is important for \"transitions\" which never actually start\r\n            // immediately so there is a chance that we might miss one if change\r\n            // happens amids the pending invocation.\r\n            trailingCall = true;\r\n        }\r\n        else {\r\n            leadingCall = true;\r\n            trailingCall = false;\r\n            setTimeout(timeoutCallback, delay);\r\n        }\r\n        lastCallTime = timeStamp;\r\n    }\r\n    return proxy;\r\n}\n\n// Minimum delay before invoking the update of observers.\r\nvar REFRESH_DELAY = 20;\r\n// A list of substrings of CSS properties used to find transition events that\r\n// might affect dimensions of observed elements.\r\nvar transitionKeys = ['top', 'right', 'bottom', 'left', 'width', 'height', 'size', 'weight'];\r\n// Check if MutationObserver is available.\r\nvar mutationObserverSupported = typeof MutationObserver !== 'undefined';\r\n/**\r\n * Singleton controller class which handles updates of ResizeObserver instances.\r\n */\r\nvar ResizeObserverController = /** @class */ (function () {\r\n    /**\r\n     * Creates a new instance of ResizeObserverController.\r\n     *\r\n     * @private\r\n     */\r\n    function ResizeObserverController() {\r\n        /**\r\n         * Indicates whether DOM listeners have been added.\r\n         *\r\n         * @private {boolean}\r\n         */\r\n        this.connected_ = false;\r\n        /**\r\n         * Tells that controller has subscribed for Mutation Events.\r\n         *\r\n         * @private {boolean}\r\n         */\r\n        this.mutationEventsAdded_ = false;\r\n        /**\r\n         * Keeps reference to the instance of MutationObserver.\r\n         *\r\n         * @private {MutationObserver}\r\n         */\r\n        this.mutationsObserver_ = null;\r\n        /**\r\n         * A list of connected observers.\r\n         *\r\n         * @private {Array<ResizeObserverSPI>}\r\n         */\r\n        this.observers_ = [];\r\n        this.onTransitionEnd_ = this.onTransitionEnd_.bind(this);\r\n        this.refresh = throttle(this.refresh.bind(this), REFRESH_DELAY);\r\n    }\r\n    /**\r\n     * Adds observer to observers list.\r\n     *\r\n     * @param {ResizeObserverSPI} observer - Observer to be added.\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.addObserver = function (observer) {\r\n        if (!~this.observers_.indexOf(observer)) {\r\n            this.observers_.push(observer);\r\n        }\r\n        // Add listeners if they haven't been added yet.\r\n        if (!this.connected_) {\r\n            this.connect_();\r\n        }\r\n    };\r\n    /**\r\n     * Removes observer from observers list.\r\n     *\r\n     * @param {ResizeObserverSPI} observer - Observer to be removed.\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.removeObserver = function (observer) {\r\n        var observers = this.observers_;\r\n        var index = observers.indexOf(observer);\r\n        // Remove observer if it's present in registry.\r\n        if (~index) {\r\n            observers.splice(index, 1);\r\n        }\r\n        // Remove listeners if controller has no connected observers.\r\n        if (!observers.length && this.connected_) {\r\n            this.disconnect_();\r\n        }\r\n    };\r\n    /**\r\n     * Invokes the update of observers. It will continue running updates insofar\r\n     * it detects changes.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.refresh = function () {\r\n        var changesDetected = this.updateObservers_();\r\n        // Continue running updates if changes have been detected as there might\r\n        // be future ones caused by CSS transitions.\r\n        if (changesDetected) {\r\n            this.refresh();\r\n        }\r\n    };\r\n    /**\r\n     * Updates every observer from observers list and notifies them of queued\r\n     * entries.\r\n     *\r\n     * @private\r\n     * @returns {boolean} Returns \"true\" if any observer has detected changes in\r\n     *      dimensions of it's elements.\r\n     */\r\n    ResizeObserverController.prototype.updateObservers_ = function () {\r\n        // Collect observers that have active observations.\r\n        var activeObservers = this.observers_.filter(function (observer) {\r\n            return observer.gatherActive(), observer.hasActive();\r\n        });\r\n        // Deliver notifications in a separate cycle in order to avoid any\r\n        // collisions between observers, e.g. when multiple instances of\r\n        // ResizeObserver are tracking the same element and the callback of one\r\n        // of them changes content dimensions of the observed target. Sometimes\r\n        // this may result in notifications being blocked for the rest of observers.\r\n        activeObservers.forEach(function (observer) { return observer.broadcastActive(); });\r\n        return activeObservers.length > 0;\r\n    };\r\n    /**\r\n     * Initializes DOM listeners.\r\n     *\r\n     * @private\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.connect_ = function () {\r\n        // Do nothing if running in a non-browser environment or if listeners\r\n        // have been already added.\r\n        if (!isBrowser || this.connected_) {\r\n            return;\r\n        }\r\n        // Subscription to the \"Transitionend\" event is used as a workaround for\r\n        // delayed transitions. This way it's possible to capture at least the\r\n        // final state of an element.\r\n        document.addEventListener('transitionend', this.onTransitionEnd_);\r\n        window.addEventListener('resize', this.refresh);\r\n        if (mutationObserverSupported) {\r\n            this.mutationsObserver_ = new MutationObserver(this.refresh);\r\n            this.mutationsObserver_.observe(document, {\r\n                attributes: true,\r\n                childList: true,\r\n                characterData: true,\r\n                subtree: true\r\n            });\r\n        }\r\n        else {\r\n            document.addEventListener('DOMSubtreeModified', this.refresh);\r\n            this.mutationEventsAdded_ = true;\r\n        }\r\n        this.connected_ = true;\r\n    };\r\n    /**\r\n     * Removes DOM listeners.\r\n     *\r\n     * @private\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.disconnect_ = function () {\r\n        // Do nothing if running in a non-browser environment or if listeners\r\n        // have been already removed.\r\n        if (!isBrowser || !this.connected_) {\r\n            return;\r\n        }\r\n        document.removeEventListener('transitionend', this.onTransitionEnd_);\r\n        window.removeEventListener('resize', this.refresh);\r\n        if (this.mutationsObserver_) {\r\n            this.mutationsObserver_.disconnect();\r\n        }\r\n        if (this.mutationEventsAdded_) {\r\n            document.removeEventListener('DOMSubtreeModified', this.refresh);\r\n        }\r\n        this.mutationsObserver_ = null;\r\n        this.mutationEventsAdded_ = false;\r\n        this.connected_ = false;\r\n    };\r\n    /**\r\n     * \"Transitionend\" event handler.\r\n     *\r\n     * @private\r\n     * @param {TransitionEvent} event\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverController.prototype.onTransitionEnd_ = function (_a) {\r\n        var _b = _a.propertyName, propertyName = _b === void 0 ? '' : _b;\r\n        // Detect whether transition may affect dimensions of an element.\r\n        var isReflowProperty = transitionKeys.some(function (key) {\r\n            return !!~propertyName.indexOf(key);\r\n        });\r\n        if (isReflowProperty) {\r\n            this.refresh();\r\n        }\r\n    };\r\n    /**\r\n     * Returns instance of the ResizeObserverController.\r\n     *\r\n     * @returns {ResizeObserverController}\r\n     */\r\n    ResizeObserverController.getInstance = function () {\r\n        if (!this.instance_) {\r\n            this.instance_ = new ResizeObserverController();\r\n        }\r\n        return this.instance_;\r\n    };\r\n    /**\r\n     * Holds reference to the controller's instance.\r\n     *\r\n     * @private {ResizeObserverController}\r\n     */\r\n    ResizeObserverController.instance_ = null;\r\n    return ResizeObserverController;\r\n}());\n\n/**\r\n * Defines non-writable/enumerable properties of the provided target object.\r\n *\r\n * @param {Object} target - Object for which to define properties.\r\n * @param {Object} props - Properties to be defined.\r\n * @returns {Object} Target object.\r\n */\r\nvar defineConfigurable = (function (target, props) {\r\n    for (var _i = 0, _a = Object.keys(props); _i < _a.length; _i++) {\r\n        var key = _a[_i];\r\n        Object.defineProperty(target, key, {\r\n            value: props[key],\r\n            enumerable: false,\r\n            writable: false,\r\n            configurable: true\r\n        });\r\n    }\r\n    return target;\r\n});\n\n/**\r\n * Returns the global object associated with provided element.\r\n *\r\n * @param {Object} target\r\n * @returns {Object}\r\n */\r\nvar getWindowOf = (function (target) {\r\n    // Assume that the element is an instance of Node, which means that it\r\n    // has the \"ownerDocument\" property from which we can retrieve a\r\n    // corresponding global object.\r\n    var ownerGlobal = target && target.ownerDocument && target.ownerDocument.defaultView;\r\n    // Return the local global object if it's not possible extract one from\r\n    // provided element.\r\n    return ownerGlobal || global$1;\r\n});\n\n// Placeholder of an empty content rectangle.\r\nvar emptyRect = createRectInit(0, 0, 0, 0);\r\n/**\r\n * Converts provided string to a number.\r\n *\r\n * @param {number|string} value\r\n * @returns {number}\r\n */\r\nfunction toFloat(value) {\r\n    return parseFloat(value) || 0;\r\n}\r\n/**\r\n * Extracts borders size from provided styles.\r\n *\r\n * @param {CSSStyleDeclaration} styles\r\n * @param {...string} positions - Borders positions (top, right, ...)\r\n * @returns {number}\r\n */\r\nfunction getBordersSize(styles) {\r\n    var positions = [];\r\n    for (var _i = 1; _i < arguments.length; _i++) {\r\n        positions[_i - 1] = arguments[_i];\r\n    }\r\n    return positions.reduce(function (size, position) {\r\n        var value = styles['border-' + position + '-width'];\r\n        return size + toFloat(value);\r\n    }, 0);\r\n}\r\n/**\r\n * Extracts paddings sizes from provided styles.\r\n *\r\n * @param {CSSStyleDeclaration} styles\r\n * @returns {Object} Paddings box.\r\n */\r\nfunction getPaddings(styles) {\r\n    var positions = ['top', 'right', 'bottom', 'left'];\r\n    var paddings = {};\r\n    for (var _i = 0, positions_1 = positions; _i < positions_1.length; _i++) {\r\n        var position = positions_1[_i];\r\n        var value = styles['padding-' + position];\r\n        paddings[position] = toFloat(value);\r\n    }\r\n    return paddings;\r\n}\r\n/**\r\n * Calculates content rectangle of provided SVG element.\r\n *\r\n * @param {SVGGraphicsElement} target - Element content rectangle of which needs\r\n *      to be calculated.\r\n * @returns {DOMRectInit}\r\n */\r\nfunction getSVGContentRect(target) {\r\n    var bbox = target.getBBox();\r\n    return createRectInit(0, 0, bbox.width, bbox.height);\r\n}\r\n/**\r\n * Calculates content rectangle of provided HTMLElement.\r\n *\r\n * @param {HTMLElement} target - Element for which to calculate the content rectangle.\r\n * @returns {DOMRectInit}\r\n */\r\nfunction getHTMLElementContentRect(target) {\r\n    // Client width & height properties can't be\r\n    // used exclusively as they provide rounded values.\r\n    var clientWidth = target.clientWidth, clientHeight = target.clientHeight;\r\n    // By this condition we can catch all non-replaced inline, hidden and\r\n    // detached elements. Though elements with width & height properties less\r\n    // than 0.5 will be discarded as well.\r\n    //\r\n    // Without it we would need to implement separate methods for each of\r\n    // those cases and it's not possible to perform a precise and performance\r\n    // effective test for hidden elements. E.g. even jQuery's ':visible' filter\r\n    // gives wrong results for elements with width & height less than 0.5.\r\n    if (!clientWidth && !clientHeight) {\r\n        return emptyRect;\r\n    }\r\n    var styles = getWindowOf(target).getComputedStyle(target);\r\n    var paddings = getPaddings(styles);\r\n    var horizPad = paddings.left + paddings.right;\r\n    var vertPad = paddings.top + paddings.bottom;\r\n    // Computed styles of width & height are being used because they are the\r\n    // only dimensions available to JS that contain non-rounded values. It could\r\n    // be possible to utilize the getBoundingClientRect if only it's data wasn't\r\n    // affected by CSS transformations let alone paddings, borders and scroll bars.\r\n    var width = toFloat(styles.width), height = toFloat(styles.height);\r\n    // Width & height include paddings and borders when the 'border-box' box\r\n    // model is applied (except for IE).\r\n    if (styles.boxSizing === 'border-box') {\r\n        // Following conditions are required to handle Internet Explorer which\r\n        // doesn't include paddings and borders to computed CSS dimensions.\r\n        //\r\n        // We can say that if CSS dimensions + paddings are equal to the \"client\"\r\n        // properties then it's either IE, and thus we don't need to subtract\r\n        // anything, or an element merely doesn't have paddings/borders styles.\r\n        if (Math.round(width + horizPad) !== clientWidth) {\r\n            width -= getBordersSize(styles, 'left', 'right') + horizPad;\r\n        }\r\n        if (Math.round(height + vertPad) !== clientHeight) {\r\n            height -= getBordersSize(styles, 'top', 'bottom') + vertPad;\r\n        }\r\n    }\r\n    // Following steps can't be applied to the document's root element as its\r\n    // client[Width/Height] properties represent viewport area of the window.\r\n    // Besides, it's as well not necessary as the <html> itself neither has\r\n    // rendered scroll bars nor it can be clipped.\r\n    if (!isDocumentElement(target)) {\r\n        // In some browsers (only in Firefox, actually) CSS width & height\r\n        // include scroll bars size which can be removed at this step as scroll\r\n        // bars are the only difference between rounded dimensions + paddings\r\n        // and \"client\" properties, though that is not always true in Chrome.\r\n        var vertScrollbar = Math.round(width + horizPad) - clientWidth;\r\n        var horizScrollbar = Math.round(height + vertPad) - clientHeight;\r\n        // Chrome has a rather weird rounding of \"client\" properties.\r\n        // E.g. for an element with content width of 314.2px it sometimes gives\r\n        // the client width of 315px and for the width of 314.7px it may give\r\n        // 314px. And it doesn't happen all the time. So just ignore this delta\r\n        // as a non-relevant.\r\n        if (Math.abs(vertScrollbar) !== 1) {\r\n            width -= vertScrollbar;\r\n        }\r\n        if (Math.abs(horizScrollbar) !== 1) {\r\n            height -= horizScrollbar;\r\n        }\r\n    }\r\n    return createRectInit(paddings.left, paddings.top, width, height);\r\n}\r\n/**\r\n * Checks whether provided element is an instance of the SVGGraphicsElement.\r\n *\r\n * @param {Element} target - Element to be checked.\r\n * @returns {boolean}\r\n */\r\nvar isSVGGraphicsElement = (function () {\r\n    // Some browsers, namely IE and Edge, don't have the SVGGraphicsElement\r\n    // interface.\r\n    if (typeof SVGGraphicsElement !== 'undefined') {\r\n        return function (target) { return target instanceof getWindowOf(target).SVGGraphicsElement; };\r\n    }\r\n    // If it's so, then check that element is at least an instance of the\r\n    // SVGElement and that it has the \"getBBox\" method.\r\n    // eslint-disable-next-line no-extra-parens\r\n    return function (target) { return (target instanceof getWindowOf(target).SVGElement &&\r\n        typeof target.getBBox === 'function'); };\r\n})();\r\n/**\r\n * Checks whether provided element is a document element (<html>).\r\n *\r\n * @param {Element} target - Element to be checked.\r\n * @returns {boolean}\r\n */\r\nfunction isDocumentElement(target) {\r\n    return target === getWindowOf(target).document.documentElement;\r\n}\r\n/**\r\n * Calculates an appropriate content rectangle for provided html or svg element.\r\n *\r\n * @param {Element} target - Element content rectangle of which needs to be calculated.\r\n * @returns {DOMRectInit}\r\n */\r\nfunction getContentRect(target) {\r\n    if (!isBrowser) {\r\n        return emptyRect;\r\n    }\r\n    if (isSVGGraphicsElement(target)) {\r\n        return getSVGContentRect(target);\r\n    }\r\n    return getHTMLElementContentRect(target);\r\n}\r\n/**\r\n * Creates rectangle with an interface of the DOMRectReadOnly.\r\n * Spec: https://drafts.fxtf.org/geometry/#domrectreadonly\r\n *\r\n * @param {DOMRectInit} rectInit - Object with rectangle's x/y coordinates and dimensions.\r\n * @returns {DOMRectReadOnly}\r\n */\r\nfunction createReadOnlyRect(_a) {\r\n    var x = _a.x, y = _a.y, width = _a.width, height = _a.height;\r\n    // If DOMRectReadOnly is available use it as a prototype for the rectangle.\r\n    var Constr = typeof DOMRectReadOnly !== 'undefined' ? DOMRectReadOnly : Object;\r\n    var rect = Object.create(Constr.prototype);\r\n    // Rectangle's properties are not writable and non-enumerable.\r\n    defineConfigurable(rect, {\r\n        x: x, y: y, width: width, height: height,\r\n        top: y,\r\n        right: x + width,\r\n        bottom: height + y,\r\n        left: x\r\n    });\r\n    return rect;\r\n}\r\n/**\r\n * Creates DOMRectInit object based on the provided dimensions and the x/y coordinates.\r\n * Spec: https://drafts.fxtf.org/geometry/#dictdef-domrectinit\r\n *\r\n * @param {number} x - X coordinate.\r\n * @param {number} y - Y coordinate.\r\n * @param {number} width - Rectangle's width.\r\n * @param {number} height - Rectangle's height.\r\n * @returns {DOMRectInit}\r\n */\r\nfunction createRectInit(x, y, width, height) {\r\n    return { x: x, y: y, width: width, height: height };\r\n}\n\n/**\r\n * Class that is responsible for computations of the content rectangle of\r\n * provided DOM element and for keeping track of it's changes.\r\n */\r\nvar ResizeObservation = /** @class */ (function () {\r\n    /**\r\n     * Creates an instance of ResizeObservation.\r\n     *\r\n     * @param {Element} target - Element to be observed.\r\n     */\r\n    function ResizeObservation(target) {\r\n        /**\r\n         * Broadcasted width of content rectangle.\r\n         *\r\n         * @type {number}\r\n         */\r\n        this.broadcastWidth = 0;\r\n        /**\r\n         * Broadcasted height of content rectangle.\r\n         *\r\n         * @type {number}\r\n         */\r\n        this.broadcastHeight = 0;\r\n        /**\r\n         * Reference to the last observed content rectangle.\r\n         *\r\n         * @private {DOMRectInit}\r\n         */\r\n        this.contentRect_ = createRectInit(0, 0, 0, 0);\r\n        this.target = target;\r\n    }\r\n    /**\r\n     * Updates content rectangle and tells whether it's width or height properties\r\n     * have changed since the last broadcast.\r\n     *\r\n     * @returns {boolean}\r\n     */\r\n    ResizeObservation.prototype.isActive = function () {\r\n        var rect = getContentRect(this.target);\r\n        this.contentRect_ = rect;\r\n        return (rect.width !== this.broadcastWidth ||\r\n            rect.height !== this.broadcastHeight);\r\n    };\r\n    /**\r\n     * Updates 'broadcastWidth' and 'broadcastHeight' properties with a data\r\n     * from the corresponding properties of the last observed content rectangle.\r\n     *\r\n     * @returns {DOMRectInit} Last observed content rectangle.\r\n     */\r\n    ResizeObservation.prototype.broadcastRect = function () {\r\n        var rect = this.contentRect_;\r\n        this.broadcastWidth = rect.width;\r\n        this.broadcastHeight = rect.height;\r\n        return rect;\r\n    };\r\n    return ResizeObservation;\r\n}());\n\nvar ResizeObserverEntry = /** @class */ (function () {\r\n    /**\r\n     * Creates an instance of ResizeObserverEntry.\r\n     *\r\n     * @param {Element} target - Element that is being observed.\r\n     * @param {DOMRectInit} rectInit - Data of the element's content rectangle.\r\n     */\r\n    function ResizeObserverEntry(target, rectInit) {\r\n        var contentRect = createReadOnlyRect(rectInit);\r\n        // According to the specification following properties are not writable\r\n        // and are also not enumerable in the native implementation.\r\n        //\r\n        // Property accessors are not being used as they'd require to define a\r\n        // private WeakMap storage which may cause memory leaks in browsers that\r\n        // don't support this type of collections.\r\n        defineConfigurable(this, { target: target, contentRect: contentRect });\r\n    }\r\n    return ResizeObserverEntry;\r\n}());\n\nvar ResizeObserverSPI = /** @class */ (function () {\r\n    /**\r\n     * Creates a new instance of ResizeObserver.\r\n     *\r\n     * @param {ResizeObserverCallback} callback - Callback function that is invoked\r\n     *      when one of the observed elements changes it's content dimensions.\r\n     * @param {ResizeObserverController} controller - Controller instance which\r\n     *      is responsible for the updates of observer.\r\n     * @param {ResizeObserver} callbackCtx - Reference to the public\r\n     *      ResizeObserver instance which will be passed to callback function.\r\n     */\r\n    function ResizeObserverSPI(callback, controller, callbackCtx) {\r\n        /**\r\n         * Collection of resize observations that have detected changes in dimensions\r\n         * of elements.\r\n         *\r\n         * @private {Array<ResizeObservation>}\r\n         */\r\n        this.activeObservations_ = [];\r\n        /**\r\n         * Registry of the ResizeObservation instances.\r\n         *\r\n         * @private {Map<Element, ResizeObservation>}\r\n         */\r\n        this.observations_ = new MapShim();\r\n        if (typeof callback !== 'function') {\r\n            throw new TypeError('The callback provided as parameter 1 is not a function.');\r\n        }\r\n        this.callback_ = callback;\r\n        this.controller_ = controller;\r\n        this.callbackCtx_ = callbackCtx;\r\n    }\r\n    /**\r\n     * Starts observing provided element.\r\n     *\r\n     * @param {Element} target - Element to be observed.\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.observe = function (target) {\r\n        if (!arguments.length) {\r\n            throw new TypeError('1 argument required, but only 0 present.');\r\n        }\r\n        // Do nothing if current environment doesn't have the Element interface.\r\n        if (typeof Element === 'undefined' || !(Element instanceof Object)) {\r\n            return;\r\n        }\r\n        if (!(target instanceof getWindowOf(target).Element)) {\r\n            throw new TypeError('parameter 1 is not of type \"Element\".');\r\n        }\r\n        var observations = this.observations_;\r\n        // Do nothing if element is already being observed.\r\n        if (observations.has(target)) {\r\n            return;\r\n        }\r\n        observations.set(target, new ResizeObservation(target));\r\n        this.controller_.addObserver(this);\r\n        // Force the update of observations.\r\n        this.controller_.refresh();\r\n    };\r\n    /**\r\n     * Stops observing provided element.\r\n     *\r\n     * @param {Element} target - Element to stop observing.\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.unobserve = function (target) {\r\n        if (!arguments.length) {\r\n            throw new TypeError('1 argument required, but only 0 present.');\r\n        }\r\n        // Do nothing if current environment doesn't have the Element interface.\r\n        if (typeof Element === 'undefined' || !(Element instanceof Object)) {\r\n            return;\r\n        }\r\n        if (!(target instanceof getWindowOf(target).Element)) {\r\n            throw new TypeError('parameter 1 is not of type \"Element\".');\r\n        }\r\n        var observations = this.observations_;\r\n        // Do nothing if element is not being observed.\r\n        if (!observations.has(target)) {\r\n            return;\r\n        }\r\n        observations.delete(target);\r\n        if (!observations.size) {\r\n            this.controller_.removeObserver(this);\r\n        }\r\n    };\r\n    /**\r\n     * Stops observing all elements.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.disconnect = function () {\r\n        this.clearActive();\r\n        this.observations_.clear();\r\n        this.controller_.removeObserver(this);\r\n    };\r\n    /**\r\n     * Collects observation instances the associated element of which has changed\r\n     * it's content rectangle.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.gatherActive = function () {\r\n        var _this = this;\r\n        this.clearActive();\r\n        this.observations_.forEach(function (observation) {\r\n            if (observation.isActive()) {\r\n                _this.activeObservations_.push(observation);\r\n            }\r\n        });\r\n    };\r\n    /**\r\n     * Invokes initial callback function with a list of ResizeObserverEntry\r\n     * instances collected from active resize observations.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.broadcastActive = function () {\r\n        // Do nothing if observer doesn't have active observations.\r\n        if (!this.hasActive()) {\r\n            return;\r\n        }\r\n        var ctx = this.callbackCtx_;\r\n        // Create ResizeObserverEntry instance for every active observation.\r\n        var entries = this.activeObservations_.map(function (observation) {\r\n            return new ResizeObserverEntry(observation.target, observation.broadcastRect());\r\n        });\r\n        this.callback_.call(ctx, entries, ctx);\r\n        this.clearActive();\r\n    };\r\n    /**\r\n     * Clears the collection of active observations.\r\n     *\r\n     * @returns {void}\r\n     */\r\n    ResizeObserverSPI.prototype.clearActive = function () {\r\n        this.activeObservations_.splice(0);\r\n    };\r\n    /**\r\n     * Tells whether observer has active observations.\r\n     *\r\n     * @returns {boolean}\r\n     */\r\n    ResizeObserverSPI.prototype.hasActive = function () {\r\n        return this.activeObservations_.length > 0;\r\n    };\r\n    return ResizeObserverSPI;\r\n}());\n\n// Registry of internal observers. If WeakMap is not available use current shim\r\n// for the Map collection as it has all required methods and because WeakMap\r\n// can't be fully polyfilled anyway.\r\nvar observers = typeof WeakMap !== 'undefined' ? new WeakMap() : new MapShim();\r\n/**\r\n * ResizeObserver API. Encapsulates the ResizeObserver SPI implementation\r\n * exposing only those methods and properties that are defined in the spec.\r\n */\r\nvar ResizeObserver = /** @class */ (function () {\r\n    /**\r\n     * Creates a new instance of ResizeObserver.\r\n     *\r\n     * @param {ResizeObserverCallback} callback - Callback that is invoked when\r\n     *      dimensions of the observed elements change.\r\n     */\r\n    function ResizeObserver(callback) {\r\n        if (!(this instanceof ResizeObserver)) {\r\n            throw new TypeError('Cannot call a class as a function.');\r\n        }\r\n        if (!arguments.length) {\r\n            throw new TypeError('1 argument required, but only 0 present.');\r\n        }\r\n        var controller = ResizeObserverController.getInstance();\r\n        var observer = new ResizeObserverSPI(callback, controller, this);\r\n        observers.set(this, observer);\r\n    }\r\n    return ResizeObserver;\r\n}());\r\n// Expose public methods of ResizeObserver.\r\n[\r\n    'observe',\r\n    'unobserve',\r\n    'disconnect'\r\n].forEach(function (method) {\r\n    ResizeObserver.prototype[method] = function () {\r\n        var _a;\r\n        return (_a = observers.get(this))[method].apply(_a, arguments);\r\n    };\r\n});\n\nvar index = (function () {\r\n    // Export existing implementation if available.\r\n    if (typeof global$1.ResizeObserver !== 'undefined') {\r\n        return global$1.ResizeObserver;\r\n    }\r\n    return ResizeObserver;\r\n})();\n\nexport default index;\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport ResizeObserver from \"resize-observer-polyfill\"\nimport {\n  NEVER,\n  Observable,\n  Subject,\n  defer,\n  filter,\n  finalize,\n  map,\n  merge,\n  of,\n  shareReplay,\n  startWith,\n  switchMap,\n  tap\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Element offset\n */\nexport interface ElementSize {\n  width: number                        /* Element width */\n  height: number                       /* Element height */\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Resize observer entry subject\n */\nconst entry$ = new Subject<ResizeObserverEntry>()\n\n/**\n * Resize observer observable\n *\n * This observable will create a `ResizeObserver` on the first subscription\n * and will automatically terminate it when there are no more subscribers.\n * It's quite important to centralize observation in a single `ResizeObserver`,\n * as the performance difference can be quite dramatic, as the link shows.\n *\n * @see https://bit.ly/3iIYfEm - Google Groups on performance\n */\nconst observer$ = defer(() => of(\n  new ResizeObserver(entries => {\n    for (const entry of entries)\n      entry$.next(entry)\n  })\n))\n  .pipe(\n    switchMap(observer => merge(NEVER, of(observer))\n      .pipe(\n        finalize(() => observer.disconnect())\n      )\n    ),\n    shareReplay(1)\n  )\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve element size\n *\n * @param el - Element\n *\n * @returns Element size\n */\nexport function getElementSize(\n  el: HTMLElement\n): ElementSize {\n  return {\n    width:  el.offsetWidth,\n    height: el.offsetHeight\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch element size\n *\n * This function returns an observable that subscribes to a single internal\n * instance of `ResizeObserver` upon subscription, and emit resize events until\n * termination. Note that this function should not be called with the same\n * element twice, as the first unsubscription will terminate observation.\n *\n * Sadly, we can't use the `DOMRect` objects returned by the observer, because\n * we need the emitted values to be consistent with `getElementSize`, which will\n * return the used values (rounded) and not actual values (unrounded). Thus, we\n * use the `offset*` properties. See the linked GitHub issue.\n *\n * @see https://bit.ly/3m0k3he - GitHub issue\n *\n * @param el - Element\n *\n * @returns Element size observable\n */\nexport function watchElementSize(\n  el: HTMLElement\n): Observable<ElementSize> {\n  return observer$\n    .pipe(\n      tap(observer => observer.observe(el)),\n      switchMap(observer => entry$\n        .pipe(\n          filter(({ target }) => target === el),\n          finalize(() => observer.unobserve(el)),\n          map(() => getElementSize(el))\n        )\n      ),\n      startWith(getElementSize(el))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { ElementSize } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve element content size (= scroll width and height)\n *\n * @param el - Element\n *\n * @returns Element content size\n */\nexport function getElementContentSize(\n  el: HTMLElement\n): ElementSize {\n  return {\n    width:  el.scrollWidth,\n    height: el.scrollHeight\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  NEVER,\n  Observable,\n  Subject,\n  defer,\n  distinctUntilChanged,\n  filter,\n  finalize,\n  map,\n  merge,\n  of,\n  shareReplay,\n  switchMap,\n  tap\n} from \"rxjs\"\n\nimport {\n  getElementContentSize,\n  getElementSize,\n  watchElementContentOffset\n} from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Intersection observer entry subject\n */\nconst entry$ = new Subject<IntersectionObserverEntry>()\n\n/**\n * Intersection observer observable\n *\n * This observable will create an `IntersectionObserver` on first subscription\n * and will automatically terminate it when there are no more subscribers.\n *\n * @see https://bit.ly/3iIYfEm - Google Groups on performance\n */\nconst observer$ = defer(() => of(\n  new IntersectionObserver(entries => {\n    for (const entry of entries)\n      entry$.next(entry)\n  }, {\n    threshold: 0\n  })\n))\n  .pipe(\n    switchMap(observer => merge(NEVER, of(observer))\n      .pipe(\n        finalize(() => observer.disconnect())\n      )\n    ),\n    shareReplay(1)\n  )\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch element visibility\n *\n * @param el - Element\n *\n * @returns Element visibility observable\n */\nexport function watchElementVisibility(\n  el: HTMLElement\n): Observable<boolean> {\n  return observer$\n    .pipe(\n      tap(observer => observer.observe(el)),\n      switchMap(observer => entry$\n        .pipe(\n          filter(({ target }) => target === el),\n          finalize(() => observer.unobserve(el)),\n          map(({ isIntersecting }) => isIntersecting)\n        )\n      )\n    )\n}\n\n/**\n * Watch element boundary\n *\n * This function returns an observable which emits whether the bottom content\n * boundary (= scroll offset) of an element is within a certain threshold.\n *\n * @param el - Element\n * @param threshold - Threshold\n *\n * @returns Element boundary observable\n */\nexport function watchElementBoundary(\n  el: HTMLElement, threshold = 16\n): Observable<boolean> {\n  return watchElementContentOffset(el)\n    .pipe(\n      map(({ y }) => {\n        const visible = getElementSize(el)\n        const content = getElementContentSize(el)\n        return y >= (\n          content.height - visible.height - threshold\n        )\n      }),\n      distinctUntilChanged()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  fromEvent,\n  map,\n  startWith\n} from \"rxjs\"\n\nimport { getElement } from \"../element\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Toggle\n */\nexport type Toggle =\n  | \"drawer\"                           /* Toggle for drawer */\n  | \"search\"                           /* Toggle for search */\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Toggle map\n */\nconst toggles: Record<Toggle, HTMLInputElement> = {\n  drawer: getElement(\"[data-md-toggle=drawer]\"),\n  search: getElement(\"[data-md-toggle=search]\")\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve the value of a toggle\n *\n * @param name - Toggle\n *\n * @returns Toggle value\n */\nexport function getToggle(name: Toggle): boolean {\n  return toggles[name].checked\n}\n\n/**\n * Set toggle\n *\n * Simulating a click event seems to be the most cross-browser compatible way\n * of changing the value while also emitting a `change` event. Before, Material\n * used `CustomEvent` to programmatically change the value of a toggle, but this\n * is a much simpler and cleaner solution which doesn't require a polyfill.\n *\n * @param name - Toggle\n * @param value - Toggle value\n */\nexport function setToggle(name: Toggle, value: boolean): void {\n  if (toggles[name].checked !== value)\n    toggles[name].click()\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch toggle\n *\n * @param name - Toggle\n *\n * @returns Toggle value observable\n */\nexport function watchToggle(name: Toggle): Observable<boolean> {\n  const el = toggles[name]\n  return fromEvent(el, \"change\")\n    .pipe(\n      map(() => el.checked),\n      startWith(el.checked)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  filter,\n  fromEvent,\n  map,\n  share\n} from \"rxjs\"\n\nimport { getActiveElement } from \"../element\"\nimport { getToggle } from \"../toggle\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Keyboard mode\n */\nexport type KeyboardMode =\n  | \"global\"                           /* Global */\n  | \"search\"                           /* Search is open */\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Keyboard\n */\nexport interface Keyboard {\n  mode: KeyboardMode                   /* Keyboard mode */\n  type: string                         /* Key type */\n  claim(): void                        /* Key claim */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Check whether an element may receive keyboard input\n *\n * @param el - Element\n * @param type - Key type\n *\n * @returns Test result\n */\nfunction isSusceptibleToKeyboard(\n  el: HTMLElement, type: string\n): boolean {\n  switch (el.constructor) {\n\n    /* Input elements */\n    case HTMLInputElement:\n      /* @ts-expect-error - omit unnecessary type cast */\n      if (el.type === \"radio\")\n        return /^Arrow/.test(type)\n      else\n        return true\n\n    /* Select element and textarea */\n    case HTMLSelectElement:\n    case HTMLTextAreaElement:\n      return true\n\n    /* Everything else */\n    default:\n      return el.isContentEditable\n  }\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch keyboard\n *\n * @returns Keyboard observable\n */\nexport function watchKeyboard(): Observable<Keyboard> {\n  return fromEvent<KeyboardEvent>(window, \"keydown\")\n    .pipe(\n      filter(ev => !(ev.metaKey || ev.ctrlKey)),\n      map(ev => ({\n        mode: getToggle(\"search\") ? \"search\" : \"global\",\n        type: ev.key,\n        claim() {\n          ev.preventDefault()\n          ev.stopPropagation()\n        }\n      } as Keyboard)),\n      filter(({ mode, type }) => {\n        if (mode === \"global\") {\n          const active = getActiveElement()\n          if (typeof active !== \"undefined\")\n            return !isSusceptibleToKeyboard(active, type)\n        }\n        return true\n      }),\n      share()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { Subject } from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve location\n *\n * This function returns a `URL` object (and not `Location`) to normalize the\n * typings across the application. Furthermore, locations need to be tracked\n * without setting them and `Location` is a singleton which represents the\n * current location.\n *\n * @returns URL\n */\nexport function getLocation(): URL {\n  return new URL(location.href)\n}\n\n/**\n * Set location\n *\n * @param url - URL to change to\n */\nexport function setLocation(url: URL): void {\n  location.href = url.href\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch location\n *\n * @returns Location subject\n */\nexport function watchLocation(): Subject<URL> {\n  return new Subject<URL>()\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { JSX as JSXInternal } from \"preact\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * HTML attributes\n */\ntype Attributes =\n  & JSXInternal.HTMLAttributes\n  & JSXInternal.SVGAttributes\n  & Record<string, any>\n\n/**\n * Child element\n */\ntype Child =\n  | HTMLElement\n  | Text\n  | string\n  | number\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Append a child node to an element\n *\n * @param el - Element\n * @param child - Child node(s)\n */\nfunction appendChild(el: HTMLElement, child: Child | Child[]): void {\n\n  /* Handle primitive types (including raw HTML) */\n  if (typeof child === \"string\" || typeof child === \"number\") {\n    el.innerHTML += child.toString()\n\n  /* Handle nodes */\n  } else if (child instanceof Node) {\n    el.appendChild(child)\n\n  /* Handle nested children */\n  } else if (Array.isArray(child)) {\n    for (const node of child)\n      appendChild(el, node)\n  }\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * JSX factory\n *\n * @template T - Element type\n *\n * @param tag - HTML tag\n * @param attributes - HTML attributes\n * @param children - Child elements\n *\n * @returns Element\n */\nexport function h<T extends keyof HTMLElementTagNameMap>(\n  tag: T, attributes?: Attributes | null, ...children: Child[]\n): HTMLElementTagNameMap[T]\n\nexport function h<T extends h.JSX.Element>(\n  tag: string, attributes?: Attributes | null, ...children: Child[]\n): T\n\nexport function h<T extends h.JSX.Element>(\n  tag: string, attributes?: Attributes | null, ...children: Child[]\n): T {\n  const el = document.createElement(tag)\n\n  /* Set attributes, if any */\n  if (attributes)\n    for (const attr of Object.keys(attributes))\n      if (typeof attributes[attr] !== \"boolean\")\n        el.setAttribute(attr, attributes[attr])\n      else if (attributes[attr])\n        el.setAttribute(attr, \"\")\n\n  /* Append child nodes */\n  for (const child of children)\n    appendChild(el, child)\n\n  /* Return element */\n  return el as T\n}\n\n/* ----------------------------------------------------------------------------\n * Namespace\n * ------------------------------------------------------------------------- */\n\nexport declare namespace h {\n  namespace JSX {\n    type Element = HTMLElement\n    type IntrinsicElements = JSXInternal.IntrinsicElements\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Truncate a string after the given number of characters\n *\n * This is not a very reasonable approach, since the summaries kind of suck.\n * It would be better to create something more intelligent, highlighting the\n * search occurrences and making a better summary out of it, but this note was\n * written three years ago, so who knows if we'll ever fix it.\n *\n * @param value - Value to be truncated\n * @param n - Number of characters\n *\n * @returns Truncated value\n */\nexport function truncate(value: string, n: number): string {\n  let i = n\n  if (value.length > i) {\n    while (value[i] !== \" \" && --i > 0) { /* keep eating */ }\n    return `${value.substring(0, i)}...`\n  }\n  return value\n}\n\n/**\n * Round a number for display with repository facts\n *\n * This is a reverse-engineered version of GitHub's weird rounding algorithm\n * for stars, forks and all other numbers. While all numbers below `1,000` are\n * returned as-is, bigger numbers are converted to fixed numbers:\n *\n * - `1,049` => `1k`\n * - `1,050` => `1.1k`\n * - `1,949` => `1.9k`\n * - `1,950` => `2k`\n *\n * @param value - Original value\n *\n * @returns Rounded value\n */\nexport function round(value: number): string {\n  if (value > 999) {\n    const digits = +((value - 950) % 1000 > 99)\n    return `${((value + 0.000001) / 1000).toFixed(digits)}k`\n  } else {\n    return value.toString()\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  filter,\n  fromEvent,\n  map,\n  shareReplay,\n  startWith\n} from \"rxjs\"\n\nimport { getOptionalElement } from \"~/browser\"\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve location hash\n *\n * @returns Location hash\n */\nexport function getLocationHash(): string {\n  return location.hash.substring(1)\n}\n\n/**\n * Set location hash\n *\n * Setting a new fragment identifier via `location.hash` will have no effect\n * if the value doesn't change. When a new fragment identifier is set, we want\n * the browser to target the respective element at all times, which is why we\n * use this dirty little trick.\n *\n * @param hash - Location hash\n */\nexport function setLocationHash(hash: string): void {\n  const el = h(\"a\", { href: hash })\n  el.addEventListener(\"click\", ev => ev.stopPropagation())\n  el.click()\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch location hash\n *\n * @returns Location hash observable\n */\nexport function watchLocationHash(): Observable<string> {\n  return fromEvent<HashChangeEvent>(window, \"hashchange\")\n    .pipe(\n      map(getLocationHash),\n      startWith(getLocationHash()),\n      filter(hash => hash.length > 0),\n      shareReplay(1)\n    )\n}\n\n/**\n * Watch location target\n *\n * @returns Location target observable\n */\nexport function watchLocationTarget(): Observable<HTMLElement> {\n  return watchLocationHash()\n    .pipe(\n      map(id => getOptionalElement(`[id=\"${id}\"]`)!),\n      filter(el => typeof el !== \"undefined\")\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  fromEvent,\n  fromEventPattern,\n  map,\n  merge,\n  startWith,\n  switchMap\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch media query\n *\n * Note that although `MediaQueryList.addListener` is deprecated we have to\n * use it, because it's the only way to ensure proper downward compatibility.\n *\n * @see https://bit.ly/3dUBH2m - GitHub issue\n *\n * @param query - Media query\n *\n * @returns Media observable\n */\nexport function watchMedia(query: string): Observable<boolean> {\n  const media = matchMedia(query)\n  return fromEventPattern<boolean>(next => (\n    media.addListener(() => next(media.matches))\n  ))\n    .pipe(\n      startWith(media.matches)\n    )\n}\n\n/**\n * Watch print mode\n *\n * @returns Print observable\n */\nexport function watchPrint(): Observable<boolean> {\n  const media = matchMedia(\"print\")\n  return merge(\n    fromEvent(window, \"beforeprint\").pipe(map(() => true)),\n    fromEvent(window, \"afterprint\").pipe(map(() => false))\n  )\n    .pipe(\n      startWith(media.matches)\n    )\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Toggle an observable with a media observable\n *\n * @template T - Data type\n *\n * @param query$ - Media observable\n * @param factory - Observable factory\n *\n * @returns Toggled observable\n */\nexport function at<T>(\n  query$: Observable<boolean>, factory: () => Observable<T>\n): Observable<T> {\n  return query$\n    .pipe(\n      switchMap(active => active ? factory() : EMPTY)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  catchError,\n  from,\n  map,\n  of,\n  shareReplay,\n  switchMap,\n  throwError\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch the given URL\n *\n * If the request fails (e.g. when dispatched from `file://` locations), the\n * observable will complete without emitting a value.\n *\n * @param url - Request URL\n * @param options - Options\n *\n * @returns Response observable\n */\nexport function request(\n  url: URL | string, options: RequestInit = { credentials: \"same-origin\" }\n): Observable<Response> {\n  return from(fetch(`${url}`, options))\n    .pipe(\n      catchError(() => EMPTY),\n      switchMap(res => res.status !== 200\n        ? throwError(() => new Error(res.statusText))\n        : of(res)\n      )\n    )\n}\n\n/**\n * Fetch JSON from the given URL\n *\n * @template T - Data type\n *\n * @param url - Request URL\n * @param options - Options\n *\n * @returns Data observable\n */\nexport function requestJSON<T>(\n  url: URL | string, options?: RequestInit\n): Observable<T> {\n  return request(url, options)\n    .pipe(\n      switchMap(res => res.json()),\n      shareReplay(1)\n    )\n}\n\n/**\n * Fetch XML from the given URL\n *\n * @param url - Request URL\n * @param options - Options\n *\n * @returns Data observable\n */\nexport function requestXML(\n  url: URL | string, options?: RequestInit\n): Observable<Document> {\n  const dom = new DOMParser()\n  return request(url, options)\n    .pipe(\n      switchMap(res => res.text()),\n      map(res => dom.parseFromString(res, \"text/xml\")),\n      shareReplay(1)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  defer,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  switchMap,\n  take,\n  throwError\n} from \"rxjs\"\n\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create and load a `script` element\n *\n * This function returns an observable that will emit when the script was\n * successfully loaded, or throw an error if it didn't.\n *\n * @param src - Script URL\n *\n * @returns Script observable\n */\nexport function watchScript(src: string): Observable<void> {\n  const script = h(\"script\", { src })\n  return defer(() => {\n    document.head.appendChild(script)\n    return merge(\n      fromEvent(script, \"load\"),\n      fromEvent(script, \"error\")\n        .pipe(\n          switchMap(() => (\n            throwError(() => new ReferenceError(`Invalid script: ${src}`))\n          ))\n        )\n    )\n      .pipe(\n        map(() => undefined),\n        finalize(() => document.head.removeChild(script)),\n        take(1)\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  fromEvent,\n  map,\n  merge,\n  startWith\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Viewport offset\n */\nexport interface ViewportOffset {\n  x: number                            /* Horizontal offset */\n  y: number                            /* Vertical offset */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve viewport offset\n *\n * On iOS Safari, viewport offset can be negative due to overflow scrolling.\n * As this may induce strange behaviors downstream, we'll just limit it to 0.\n *\n * @returns Viewport offset\n */\nexport function getViewportOffset(): ViewportOffset {\n  return {\n    x: Math.max(0, scrollX),\n    y: Math.max(0, scrollY)\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch viewport offset\n *\n * @returns Viewport offset observable\n */\nexport function watchViewportOffset(): Observable<ViewportOffset> {\n  return merge(\n    fromEvent(window, \"scroll\", { passive: true }),\n    fromEvent(window, \"resize\", { passive: true })\n  )\n    .pipe(\n      map(getViewportOffset),\n      startWith(getViewportOffset())\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  fromEvent,\n  map,\n  startWith\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Viewport size\n */\nexport interface ViewportSize {\n  width: number                        /* Viewport width */\n  height: number                       /* Viewport height */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve viewport size\n *\n * @returns Viewport size\n */\nexport function getViewportSize(): ViewportSize {\n  return {\n    width:  innerWidth,\n    height: innerHeight\n  }\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Watch viewport size\n *\n * @returns Viewport size observable\n */\nexport function watchViewportSize(): Observable<ViewportSize> {\n  return fromEvent(window, \"resize\", { passive: true })\n    .pipe(\n      map(getViewportSize),\n      startWith(getViewportSize())\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  combineLatest,\n  map,\n  shareReplay\n} from \"rxjs\"\n\nimport {\n  ViewportOffset,\n  watchViewportOffset\n} from \"../offset\"\nimport {\n  ViewportSize,\n  watchViewportSize\n} from \"../size\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Viewport\n */\nexport interface Viewport {\n  offset: ViewportOffset               /* Viewport offset */\n  size: ViewportSize                   /* Viewport size */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch viewport\n *\n * @returns Viewport observable\n */\nexport function watchViewport(): Observable<Viewport> {\n  return combineLatest([\n    watchViewportOffset(),\n    watchViewportSize()\n  ])\n    .pipe(\n      map(([offset, size]) => ({ offset, size })),\n      shareReplay(1)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  combineLatest,\n  distinctUntilKeyChanged,\n  map\n} from \"rxjs\"\n\nimport { Header } from \"~/components\"\n\nimport { getElementOffset } from \"../../element\"\nimport { Viewport } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch viewport relative to element\n *\n * @param el - Element\n * @param options - Options\n *\n * @returns Viewport observable\n */\nexport function watchViewportAt(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<Viewport> {\n  const size$ = viewport$\n    .pipe(\n      distinctUntilKeyChanged(\"size\")\n    )\n\n  /* Compute element offset */\n  const offset$ = combineLatest([size$, header$])\n    .pipe(\n      map(() => getElementOffset(el))\n    )\n\n  /* Compute relative viewport, return hot observable */\n  return combineLatest([header$, viewport$, offset$])\n    .pipe(\n      map(([{ height }, { offset, size }, { x, y }]) => ({\n        offset: {\n          x: offset.x - x,\n          y: offset.y - y + height\n        },\n        size\n      }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  fromEvent,\n  map,\n  share,\n  switchMap,\n  tap,\n  throttle\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Worker message\n */\nexport interface WorkerMessage {\n  type: unknown                        /* Message type */\n  data?: unknown                       /* Message data */\n}\n\n/**\n * Worker handler\n *\n * @template T - Message type\n */\nexport interface WorkerHandler<\n  T extends WorkerMessage\n> {\n  tx$: Subject<T>                      /* Message transmission subject */\n  rx$: Observable<T>                   /* Message receive observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n *\n * @template T - Worker message type\n */\ninterface WatchOptions<T extends WorkerMessage> {\n  tx$: Observable<T>                   /* Message transmission observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch a web worker\n *\n * This function returns an observable that sends all values emitted by the\n * message observable to the web worker. Web worker communication is expected\n * to be bidirectional (request-response) and synchronous. Messages that are\n * emitted during a pending request are throttled, the last one is emitted.\n *\n * @param worker - Web worker\n * @param options - Options\n *\n * @returns Worker message observable\n */\nexport function watchWorker<T extends WorkerMessage>(\n  worker: Worker, { tx$ }: WatchOptions<T>\n): Observable<T> {\n\n  /* Intercept messages from worker-like objects */\n  const rx$ = fromEvent<MessageEvent>(worker, \"message\")\n    .pipe(\n      map(({ data }) => data as T)\n    )\n\n  /* Send and receive messages, return hot observable */\n  return tx$\n    .pipe(\n      throttle(() => rx$, { leading: true, trailing: true }),\n      tap(message => worker.postMessage(message)),\n      switchMap(() => rx$),\n      share()\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { getElement, getLocation } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Feature flag\n */\nexport type Flag =\n  | \"content.code.annotate\"            /* Code annotations */\n  | \"header.autohide\"                  /* Hide header */\n  | \"navigation.expand\"                /* Automatic expansion */\n  | \"navigation.indexes\"               /* Section pages */\n  | \"navigation.instant\"               /* Instant loading */\n  | \"navigation.sections\"              /* Section navigation */\n  | \"navigation.tabs\"                  /* Tabs navigation */\n  | \"navigation.tabs.sticky\"           /* Tabs navigation (sticky) */\n  | \"navigation.top\"                   /* Back-to-top button */\n  | \"navigation.tracking\"              /* Anchor tracking */\n  | \"search.highlight\"                 /* Search highlighting */\n  | \"search.share\"                     /* Search sharing */\n  | \"search.suggest\"                   /* Search suggestions */\n  | \"toc.integrate\"                    /* Integrated table of contents */\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Translation\n */\nexport type Translation =\n  | \"clipboard.copy\"                   /* Copy to clipboard */\n  | \"clipboard.copied\"                 /* Copied to clipboard */\n  | \"search.config.lang\"               /* Search language */\n  | \"search.config.pipeline\"           /* Search pipeline */\n  | \"search.config.separator\"          /* Search separator */\n  | \"search.placeholder\"               /* Search */\n  | \"search.result.placeholder\"        /* Type to start searching */\n  | \"search.result.none\"               /* No matching documents */\n  | \"search.result.one\"                /* 1 matching document */\n  | \"search.result.other\"              /* # matching documents */\n  | \"search.result.more.one\"           /* 1 more on this page */\n  | \"search.result.more.other\"         /* # more on this page */\n  | \"search.result.term.missing\"       /* Missing */\n  | \"select.version.title\"             /* Version selector */\n\n/**\n * Translations\n */\nexport type Translations = Record<Translation, string>\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Versioning\n */\nexport interface Versioning {\n  provider: \"mike\"                     /* Version provider */\n  default?: string                     /* Default version */\n}\n\n/**\n * Configuration\n */\nexport interface Config {\n  base: string                         /* Base URL */\n  features: Flag[]                     /* Feature flags */\n  translations: Translations           /* Translations */\n  search: string                       /* Search worker URL */\n  version?: Versioning                 /* Versioning */\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve global configuration and make base URL absolute\n */\nconst script = getElement(\"#__config\")\nconst config: Config = JSON.parse(script.textContent!)\nconfig.base = `${new URL(config.base, getLocation())}`\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve global configuration\n *\n * @returns Global configuration\n */\nexport function configuration(): Config {\n  return config\n}\n\n/**\n * Check whether a feature flag is enabled\n *\n * @param flag - Feature flag\n *\n * @returns Test result\n */\nexport function feature(flag: Flag): boolean {\n  return config.features.includes(flag)\n}\n\n/**\n * Retrieve the translation for the given key\n *\n * @param key - Key to be translated\n * @param value - Positional value, if any\n *\n * @returns Translation\n */\nexport function translation(\n  key: Translation, value?: string | number\n): string {\n  return typeof value !== \"undefined\"\n    ? config.translations[key].replace(\"#\", value.toString())\n    : config.translations[key]\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { getElement, getElements } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Component type\n */\nexport type ComponentType =\n  | \"announce\"                         /* Announcement bar */\n  | \"container\"                        /* Container */\n  | \"content\"                          /* Content */\n  | \"dialog\"                           /* Dialog */\n  | \"header\"                           /* Header */\n  | \"header-title\"                     /* Header title */\n  | \"header-topic\"                     /* Header topic */\n  | \"main\"                             /* Main area */\n  | \"outdated\"                         /* Version warning */\n  | \"palette\"                          /* Color palette */\n  | \"search\"                           /* Search */\n  | \"search-query\"                     /* Search input */\n  | \"search-result\"                    /* Search results */\n  | \"search-share\"                     /* Search sharing */\n  | \"search-suggest\"                   /* Search suggestions */\n  | \"sidebar\"                          /* Sidebar */\n  | \"skip\"                             /* Skip link */\n  | \"source\"                           /* Repository information */\n  | \"tabs\"                             /* Navigation tabs */\n  | \"toc\"                              /* Table of contents */\n  | \"top\"                              /* Back-to-top button */\n\n/**\n * Component\n *\n * @template T - Component type\n * @template U - Reference type\n */\nexport type Component<\n  T extends {} = {},\n  U extends HTMLElement = HTMLElement\n> =\n  T & {\n    ref: U                             /* Component reference */\n  }\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Component type map\n */\ninterface ComponentTypeMap {\n  \"announce\": HTMLElement              /* Announcement bar */\n  \"container\": HTMLElement             /* Container */\n  \"content\": HTMLElement               /* Content */\n  \"dialog\": HTMLElement                /* Dialog */\n  \"header\": HTMLElement                /* Header */\n  \"header-title\": HTMLElement          /* Header title */\n  \"header-topic\": HTMLElement          /* Header topic */\n  \"main\": HTMLElement                  /* Main area */\n  \"outdated\": HTMLElement              /* Version warning */\n  \"palette\": HTMLElement               /* Color palette */\n  \"search\": HTMLElement                /* Search */\n  \"search-query\": HTMLInputElement     /* Search input */\n  \"search-result\": HTMLElement         /* Search results */\n  \"search-share\": HTMLAnchorElement    /* Search sharing */\n  \"search-suggest\": HTMLElement        /* Search suggestions */\n  \"sidebar\": HTMLElement               /* Sidebar */\n  \"skip\": HTMLAnchorElement            /* Skip link */\n  \"source\": HTMLAnchorElement          /* Repository information */\n  \"tabs\": HTMLElement                  /* Navigation tabs */\n  \"toc\": HTMLElement                   /* Table of contents */\n  \"top\": HTMLAnchorElement             /* Back-to-top button */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Retrieve the element for a given component or throw a reference error\n *\n * @template T - Component type\n *\n * @param type - Component type\n * @param node - Node of reference\n *\n * @returns Element\n */\nexport function getComponentElement<T extends ComponentType>(\n  type: T, node: ParentNode = document\n): ComponentTypeMap[T] {\n  return getElement(`[data-md-component=${type}]`, node)\n}\n\n/**\n * Retrieve all elements for a given component\n *\n * @template T - Component type\n *\n * @param type - Component type\n * @param node - Node of reference\n *\n * @returns Elements\n */\nexport function getComponentElements<T extends ComponentType>(\n  type: T, node: ParentNode = document\n): ComponentTypeMap[T][] {\n  return getElements(`[data-md-component=${type}]`, node)\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport ClipboardJS from \"clipboard\"\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  defer,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  finalize,\n  map,\n  mergeWith,\n  switchMap,\n  take,\n  takeLast,\n  takeUntil,\n  tap\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  getElementContentSize,\n  watchElementSize,\n  watchElementVisibility\n} from \"~/browser\"\nimport { renderClipboardButton } from \"~/templates\"\n\nimport { Component } from \"../../../_\"\nimport {\n  Annotation,\n  mountAnnotationList\n} from \"../../annotation\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Code block\n */\nexport interface CodeBlock {\n  scrollable: boolean                  /* Code block overflows */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Global sequence number for Clipboard.js integration\n */\nlet sequence = 0\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Find candidate list element directly following a code block\n *\n * @param el - Code block element\n *\n * @returns List element or nothing\n */\nfunction findCandidateList(el: HTMLElement): HTMLElement | undefined {\n  if (el.nextElementSibling) {\n    const sibling = el.nextElementSibling as HTMLElement\n    if (sibling.tagName === \"OL\")\n      return sibling\n\n    /* Skip empty paragraphs - see https://bit.ly/3r4ZJ2O */\n    else if (sibling.tagName === \"P\" && !sibling.children.length)\n      return findCandidateList(sibling)\n  }\n\n  /* Everything else */\n  return undefined\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch code block\n *\n * This function monitors size changes of the viewport, as well as switches of\n * content tabs with embedded code blocks, as both may trigger overflow.\n *\n * @param el - Code block element\n *\n * @returns Code block observable\n */\nexport function watchCodeBlock(\n  el: HTMLElement\n): Observable<CodeBlock> {\n  return watchElementSize(el)\n    .pipe(\n      map(({ width }) => {\n        const content = getElementContentSize(el)\n        return {\n          scrollable: content.width > width\n        }\n      }),\n      distinctUntilKeyChanged(\"scrollable\")\n    )\n}\n\n/**\n * Mount code block\n *\n * This function ensures that an overflowing code block is focusable through\n * keyboard, so it can be scrolled without a mouse to improve on accessibility.\n * Furthermore, if code annotations are enabled, they are mounted if and only\n * if the code block is currently visible, e.g., not in a hidden content tab.\n *\n * @param el - Code block element\n * @param options - Options\n *\n * @returns Code block and annotation component observable\n */\nexport function mountCodeBlock(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<CodeBlock | Annotation>> {\n  const { matches: hover } = matchMedia(\"(hover)\")\n\n  /* Defer mounting of code block - see https://bit.ly/3vHVoVD */\n  const factory$ = defer(() => {\n    const push$ = new Subject<CodeBlock>()\n    push$.subscribe(({ scrollable }) => {\n      if (scrollable && hover)\n        el.setAttribute(\"tabindex\", \"0\")\n      else\n        el.removeAttribute(\"tabindex\")\n    })\n\n    /* Render button for Clipboard.js integration */\n    if (ClipboardJS.isSupported()) {\n      const parent = el.closest(\"pre\")!\n      parent.id = `__code_${++sequence}`\n      parent.insertBefore(\n        renderClipboardButton(parent.id),\n        el\n      )\n    }\n\n    /* Handle code annotations */\n    const container = el.closest(\".highlight\")\n    if (container instanceof HTMLElement) {\n      const list = findCandidateList(container)\n\n      /* Mount code annotations, if enabled */\n      if (typeof list !== \"undefined\" && (\n        container.classList.contains(\"annotate\") ||\n        feature(\"content.code.annotate\")\n      )) {\n        const annotations$ = mountAnnotationList(list, el, options)\n\n        /* Create and return component */\n        return watchCodeBlock(el)\n          .pipe(\n            tap(state => push$.next(state)),\n            finalize(() => push$.complete()),\n            map(state => ({ ref: el, ...state })),\n            mergeWith(\n              watchElementSize(container)\n                .pipe(\n                  takeUntil(push$.pipe(takeLast(1))),\n                  map(({ width, height }) => width && height),\n                  distinctUntilChanged(),\n                  switchMap(active => active ? annotations$ : EMPTY)\n                )\n            )\n          )\n      }\n    }\n\n    /* Create and return component */\n    return watchCodeBlock(el)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n\n  /* Mount code block on first sight */\n  return watchElementVisibility(el)\n    .pipe(\n      filter(visible => visible),\n      take(1),\n      switchMap(() => factory$)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render an empty annotation\n *\n * @param id - Annotation identifier\n *\n * @returns Element\n */\nexport function renderAnnotation(id: number): HTMLElement {\n  return (\n    <aside class=\"md-annotation\" tabIndex={0}>\n      <div class=\"md-annotation__inner md-tooltip\">\n        <div class=\"md-tooltip__inner md-typeset\"></div>\n      </div>\n      <span class=\"md-annotation__index\">\n        <span data-md-annotation-id={id}></span>\n      </span>\n    </aside>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { translation } from \"~/_\"\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a 'copy-to-clipboard' button\n *\n * @param id - Unique identifier\n *\n * @returns Element\n */\nexport function renderClipboardButton(id: string): HTMLElement {\n  return (\n    <button\n      class=\"md-clipboard md-icon\"\n      title={translation(\"clipboard.copy\")}\n      data-clipboard-target={`#${id} > code`}\n    ></button>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { ComponentChild } from \"preact\"\n\nimport { feature, translation } from \"~/_\"\nimport {\n  SearchDocument,\n  SearchMetadata,\n  SearchResultItem\n} from \"~/integrations/search\"\nimport { h, truncate } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Render flag\n */\nconst enum Flag {\n  TEASER = 1,                          /* Render teaser */\n  PARENT = 2                           /* Render as parent */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper function\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a search document\n *\n * @param document - Search document\n * @param flag - Render flags\n *\n * @returns Element\n */\nfunction renderSearchDocument(\n  document: SearchDocument & SearchMetadata, flag: Flag\n): HTMLElement {\n  const parent = flag & Flag.PARENT\n  const teaser = flag & Flag.TEASER\n\n  /* Render missing query terms */\n  const missing = Object.keys(document.terms)\n    .filter(key => !document.terms[key])\n    .reduce<ComponentChild[]>((list, key) => [\n      ...list, <del>{key}</del>, \" \"\n    ], [])\n    .slice(0, -1)\n\n  /* Assemble query string for highlighting */\n  const url = new URL(document.location)\n  if (feature(\"search.highlight\"))\n    url.searchParams.set(\"h\", Object.entries(document.terms)\n      .filter(([, match]) => match)\n      .reduce((highlight, [value]) => `${highlight} ${value}`.trim(), \"\")\n    )\n\n  /* Render article or section, depending on flags */\n  return (\n    <a href={`${url}`} class=\"md-search-result__link\" tabIndex={-1}>\n      <article\n        class={[\"md-search-result__article\", ...parent\n          ? [\"md-search-result__article--document\"]\n          : []\n        ].join(\" \")}\n        data-md-score={document.score.toFixed(2)}\n      >\n        {parent > 0 && <div class=\"md-search-result__icon md-icon\"></div>}\n        <h1 class=\"md-search-result__title\">{document.title}</h1>\n        {teaser > 0 && document.text.length > 0 &&\n          <p class=\"md-search-result__teaser\">\n            {truncate(document.text, 320)}\n          </p>\n        }\n        {document.tags && document.tags.map(tag => (\n          <span class=\"md-tag\">{tag}</span>\n        ))}\n        {teaser > 0 && missing.length > 0 &&\n          <p class=\"md-search-result__terms\">\n            {translation(\"search.result.term.missing\")}: {...missing}\n          </p>\n        }\n      </article>\n    </a>\n  )\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a search result\n *\n * @param result - Search result\n *\n * @returns Element\n */\nexport function renderSearchResultItem(\n  result: SearchResultItem\n): HTMLElement {\n  const threshold = result[0].score\n  const docs = [...result]\n\n  /* Find and extract parent article */\n  const parent = docs.findIndex(doc => !doc.location.includes(\"#\"))\n  const [article] = docs.splice(parent, 1)\n\n  /* Determine last index above threshold */\n  let index = docs.findIndex(doc => doc.score < threshold)\n  if (index === -1)\n    index = docs.length\n\n  /* Partition sections */\n  const best = docs.slice(0, index)\n  const more = docs.slice(index)\n\n  /* Render children */\n  const children = [\n    renderSearchDocument(article, Flag.PARENT | +(!parent && index === 0)),\n    ...best.map(section => renderSearchDocument(section, Flag.TEASER)),\n    ...more.length ? [\n      <details class=\"md-search-result__more\">\n        <summary tabIndex={-1}>\n          {more.length > 0 && more.length === 1\n            ? translation(\"search.result.more.one\")\n            : translation(\"search.result.more.other\", more.length)\n          }\n        </summary>\n        {...more.map(section => renderSearchDocument(section, Flag.TEASER))}\n      </details>\n    ] : []\n  ]\n\n  /* Render search result */\n  return (\n    <li class=\"md-search-result__item\">\n      {children}\n    </li>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { SourceFacts } from \"~/components\"\nimport { h, round } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render repository facts\n *\n * @param facts - Repository facts\n *\n * @returns Element\n */\nexport function renderSourceFacts(facts: SourceFacts): HTMLElement {\n  return (\n    <ul class=\"md-source__facts\">\n      {Object.entries(facts).map(([key, value]) => (\n        <li class={`md-source__fact md-source__fact--${key}`}>\n          {typeof value === \"number\" ? round(value) : value}\n        </li>\n      ))}\n    </ul>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a table inside a wrapper to improve scrolling on mobile\n *\n * @param table - Table element\n *\n * @returns Element\n */\nexport function renderTable(table: HTMLElement): HTMLElement {\n  return (\n    <div class=\"md-typeset__scrollwrap\">\n      <div class=\"md-typeset__table\">\n        {table}\n      </div>\n    </div>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { configuration, translation } from \"~/_\"\nimport { h } from \"~/utilities\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Version\n */\nexport interface Version {\n  version: string                      /* Version identifier */\n  title: string                        /* Version title */\n  aliases: string[]                    /* Version aliases */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a version\n *\n * @param version - Version\n *\n * @returns Element\n */\nfunction renderVersion(version: Version): HTMLElement {\n  const config = configuration()\n\n  /* Ensure trailing slash, see https://bit.ly/3rL5u3f */\n  const url = new URL(`../${version.version}/`, config.base)\n  return (\n    <li class=\"md-version__item\">\n      <a href={url.toString()} class=\"md-version__link\">\n        {version.title}\n      </a>\n    </li>\n  )\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Render a version selector\n *\n * @param versions - Versions\n * @param active - Active version\n *\n * @returns Element\n */\nexport function renderVersionSelector(\n  versions: Version[], active: Version\n): HTMLElement {\n  return (\n    <div class=\"md-version\">\n      <button\n        class=\"md-version__current\"\n        aria-label={translation(\"select.version.title\")}\n      >\n        {active.title}\n      </button>\n      <ul class=\"md-version__list\">\n        {versions.map(renderVersion)}\n      </ul>\n    </div>\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  animationFrameScheduler,\n  combineLatest,\n  defer,\n  finalize,\n  fromEvent,\n  map,\n  switchMap,\n  take,\n  tap,\n  throttleTime\n} from \"rxjs\"\n\nimport {\n  ElementOffset,\n  getElement,\n  getElementSize,\n  watchElementContentOffset,\n  watchElementFocus,\n  watchElementOffset\n} from \"~/browser\"\n\nimport { Component } from \"../../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Annotation\n */\nexport interface Annotation {\n  active: boolean                      /* Annotation is active */\n  offset: ElementOffset                /* Annotation offset */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch annotation\n *\n * @param el - Annotation element\n * @param container - Containing element\n *\n * @returns Annotation observable\n */\nexport function watchAnnotation(\n  el: HTMLElement, container: HTMLElement\n): Observable<Annotation> {\n  const offset$ = defer(() => combineLatest([\n    watchElementOffset(el),\n    watchElementContentOffset(container)\n  ]))\n    .pipe(\n      map(([{ x, y }, scroll]) => {\n        const { width } = getElementSize(el)\n        return ({\n          x: x - scroll.x + width / 2,\n          y: y - scroll.y\n        })\n      })\n    )\n\n  /* Actively watch annotation on focus */\n  return watchElementFocus(el)\n    .pipe(\n      switchMap(active => offset$\n        .pipe(\n          map(offset => ({ active, offset })),\n          take(+!active || Infinity)\n        )\n      )\n    )\n}\n\n/**\n * Mount annotation\n *\n * @param el - Annotation element\n * @param container - Containing element\n *\n * @returns Annotation component observable\n */\nexport function mountAnnotation(\n  el: HTMLElement, container: HTMLElement\n): Observable<Component<Annotation>> {\n  return defer(() => {\n    const push$ = new Subject<Annotation>()\n    push$.subscribe({\n\n      /* Handle emission */\n      next({ offset }) {\n        el.style.setProperty(\"--md-tooltip-x\", `${offset.x}px`)\n        el.style.setProperty(\"--md-tooltip-y\", `${offset.y}px`)\n      },\n\n      /* Handle complete */\n      complete() {\n        el.style.removeProperty(\"--md-tooltip-x\")\n        el.style.removeProperty(\"--md-tooltip-y\")\n      }\n    })\n\n    /* Track relative origin of tooltip */\n    push$\n      .pipe(\n        throttleTime(500, animationFrameScheduler),\n        map(() => container.getBoundingClientRect()),\n        map(({ x }) => x)\n      )\n        .subscribe({\n\n          /* Handle emission */\n          next(origin) {\n            if (origin)\n              el.style.setProperty(\"--md-tooltip-0\", `${-origin}px`)\n            else\n              el.style.removeProperty(\"--md-tooltip-0\")\n          },\n\n          /* Handle complete */\n          complete() {\n            el.style.removeProperty(\"--md-tooltip-0\")\n          }\n        })\n\n    /* Close open annotation on click */\n    const index = getElement(\":scope > :last-child\", el)\n    const blur$ = fromEvent(index, \"mousedown\", { once: true })\n    push$\n      .pipe(\n        switchMap(({ active }) => active ? blur$ : EMPTY),\n        tap(ev => ev.preventDefault())\n      )\n        .subscribe(() => el.blur())\n\n    /* Create and return component */\n    return watchAnnotation(el, container)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  defer,\n  finalize,\n  merge,\n  share,\n  takeLast,\n  takeUntil\n} from \"rxjs\"\n\nimport {\n  getElement,\n  getElements,\n  getOptionalElement\n} from \"~/browser\"\nimport { renderAnnotation } from \"~/templates\"\n\nimport { Component } from \"../../../_\"\nimport {\n  Annotation,\n  mountAnnotation\n} from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Find all annotation markers in the given code block\n *\n * @param container - Containing element\n *\n * @returns Annotation markers\n */\nfunction findAnnotationMarkers(container: HTMLElement): Text[] {\n  const markers: Text[] = []\n  for (const comment of getElements(\".c, .c1, .cm\", container)) {\n    let match: RegExpExecArray | null\n\n    /* Split text at marker and add to list */\n    let text = comment.firstChild as Text\n    if (text instanceof Text)\n      while ((match = /\\((\\d+)\\)/.exec(text.textContent!))) {\n        const marker = text.splitText(match.index)\n        text = marker.splitText(match[0].length)\n        markers.push(marker)\n      }\n  }\n  return markers\n}\n\n/**\n * Swap the child nodes of two elements\n *\n * @param source - Source element\n * @param target - Target element\n */\nfunction swap(source: HTMLElement, target: HTMLElement): void {\n  target.append(...Array.from(source.childNodes))\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount annotation list\n *\n * This function analyzes the containing code block and checks for markers\n * referring to elements in the given annotation list. If no markers are found,\n * the list is left untouched. Otherwise, list elements are rendered as\n * annotations inside the code block.\n *\n * @param el - Annotation list element\n * @param container - Containing element\n * @param options - Options\n *\n * @returns Annotation component observable\n */\nexport function mountAnnotationList(\n  el: HTMLElement, container: HTMLElement, { print$ }: MountOptions\n): Observable<Component<Annotation>> {\n\n  /* Find and replace all markers with empty annotations */\n  const annotations = new Map<number, HTMLElement>()\n  for (const marker of findAnnotationMarkers(container)) {\n    const [, id] = marker.textContent!.match(/\\((\\d+)\\)/)!\n    if (getOptionalElement(`li:nth-child(${id})`, el)) {\n      annotations.set(+id, renderAnnotation(+id))\n      marker.replaceWith(annotations.get(+id)!)\n    }\n  }\n\n  /* Keep list if there are no annotations to render */\n  if (annotations.size === 0)\n    return EMPTY\n\n  /* Create and return component */\n  return defer(() => {\n    const done$ = new Subject<void>()\n\n    /* Handle print mode - see https://bit.ly/3rgPdpt */\n    print$\n      .pipe(\n        takeUntil(done$.pipe(takeLast(1)))\n      )\n        .subscribe(active => {\n          el.hidden = !active\n\n          /* Show annotations in code block or list (print) */\n          for (const [id, annotation] of annotations) {\n            const inner = getElement(\".md-typeset\", annotation)\n            const child = getElement(`li:nth-child(${id})`, el)\n            if (!active)\n              swap(child, inner)\n            else\n              swap(inner, child)\n          }\n        })\n\n    /* Create and return component */\n    return merge(...[...annotations]\n      .map(([, annotation]) => (\n        mountAnnotation(annotation, container)\n      ))\n    )\n      .pipe(\n        finalize(() => done$.complete()),\n        share()\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  map,\n  of,\n  shareReplay,\n  tap\n} from \"rxjs\"\n\nimport { watchScript } from \"~/browser\"\nimport { h } from \"~/utilities\"\n\nimport { Component } from \"../../../_\"\n\nimport themeCSS from \"./index.css\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mermaid diagram\n */\nexport interface Mermaid {}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Mermaid instance observable\n */\nlet mermaid$: Observable<void>\n\n/**\n * Global index for Mermaid integration\n */\nlet index = 0\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch Mermaid script\n *\n * @returns Mermaid scripts observable\n */\nfunction fetchScripts(): Observable<void> {\n  return typeof mermaid === \"undefined\" || mermaid instanceof Element\n    ? watchScript(\"https://unpkg.com/mermaid@9.0.1/dist/mermaid.min.js\")\n    : of(undefined)\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount Mermaid diagram\n *\n * @param el - Code block element\n *\n * @returns Mermaid diagram component observable\n */\nexport function mountMermaid(\n  el: HTMLElement\n): Observable<Component<Mermaid>> {\n  el.classList.remove(\"mermaid\") // Hack: mitigate https://bit.ly/3CiN6Du\n  mermaid$ ||= fetchScripts()\n    .pipe(\n      tap(() => mermaid.initialize({\n        startOnLoad: false,\n        themeCSS\n      })),\n      map(() => undefined),\n      shareReplay(1)\n    )\n\n  /* Render diagram */\n  mermaid$.subscribe(() => {\n    el.classList.add(\"mermaid\") // Hack: mitigate https://bit.ly/3CiN6Du\n    const id = `__mermaid_${index++}`\n    const host = h(\"div\", { class: \"mermaid\" })\n    mermaid.mermaidAPI.render(id, el.textContent, (svg: string) => {\n\n      /* Create a shadow root and inject diagram */\n      const shadow = host.attachShadow({ mode: \"closed\" })\n      shadow.innerHTML = svg\n\n      /* Replace code block with diagram */\n      el.replaceWith(host)\n    })\n  })\n\n  /* Create and return component */\n  return mermaid$\n    .pipe(\n      map(() => ({ ref: el }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  defer,\n  filter,\n  finalize,\n  map,\n  merge,\n  tap\n} from \"rxjs\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Details\n */\nexport interface Details {\n  action: \"open\" | \"close\"             /* Details state */\n  reveal?: boolean                     /* Details is revealed */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  target$: Observable<HTMLElement>     /* Location target observable */\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  target$: Observable<HTMLElement>     /* Location target observable */\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch details\n *\n * @param el - Details element\n * @param options - Options\n *\n * @returns Details observable\n */\nexport function watchDetails(\n  el: HTMLDetailsElement, { target$, print$ }: WatchOptions\n): Observable<Details> {\n  let open = true\n  return merge(\n\n    /* Open and focus details on location target */\n    target$\n      .pipe(\n        map(target => target.closest(\"details:not([open])\")!),\n        filter(details => el === details),\n        map(() => ({\n          action: \"open\", reveal: true\n        }) as Details)\n      ),\n\n    /* Open details on print and close afterwards */\n    print$\n      .pipe(\n        filter(active => active || !open),\n        tap(() => open = el.open),\n        map(active => ({\n          action: active ? \"open\" : \"close\"\n        }) as Details)\n      )\n  )\n}\n\n/**\n * Mount details\n *\n * This function ensures that `details` tags are opened on anchor jumps and\n * prior to printing, so the whole content of the page is visible.\n *\n * @param el - Details element\n * @param options - Options\n *\n * @returns Details component observable\n */\nexport function mountDetails(\n  el: HTMLDetailsElement, options: MountOptions\n): Observable<Component<Details>> {\n  return defer(() => {\n    const push$ = new Subject<Details>()\n    push$.subscribe(({ action, reveal }) => {\n      if (action === \"open\")\n        el.setAttribute(\"open\", \"\")\n      else\n        el.removeAttribute(\"open\")\n      if (reveal)\n        el.scrollIntoView()\n    })\n\n    /* Create and return component */\n    return watchDetails(el, options)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { Observable, of } from \"rxjs\"\n\nimport { renderTable } from \"~/templates\"\nimport { h } from \"~/utilities\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Data table\n */\nexport interface DataTable {}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Sentinel for replacement\n */\nconst sentinel = h(\"table\")\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount data table\n *\n * This function wraps a data table in another scrollable container, so it can\n * be smoothly scrolled on smaller screen sizes and won't break the layout.\n *\n * @param el - Data table element\n *\n * @returns Data table component observable\n */\nexport function mountDataTable(\n  el: HTMLElement\n): Observable<Component<DataTable>> {\n  el.replaceWith(sentinel)\n  sentinel.replaceWith(renderTable(el))\n\n  /* Create and return component */\n  return of({ ref: el })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  animationFrameScheduler,\n  asyncScheduler,\n  auditTime,\n  combineLatest,\n  defer,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  startWith,\n  subscribeOn,\n  takeLast,\n  takeUntil,\n  tap\n} from \"rxjs\"\n\nimport {\n  getElement,\n  getElementOffset,\n  getElementSize,\n  getElements,\n  watchElementSize\n} from \"~/browser\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Content tabs\n */\nexport interface ContentTabs {\n  active: HTMLLabelElement             /* Active tab label */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch content tabs\n *\n * @param el - Content tabs element\n *\n * @returns Content tabs observable\n */\nexport function watchContentTabs(\n  el: HTMLElement\n): Observable<ContentTabs> {\n  const inputs = getElements<HTMLInputElement>(\":scope > input\", el)\n  const active = inputs.find(input => input.checked) || inputs[0]\n  return merge(...inputs.map(input => fromEvent(input, \"change\")\n    .pipe(\n      map(() => ({\n        active: getElement(`label[for=${input.id}]`)\n      }) as ContentTabs)\n    )\n  ))\n    .pipe(\n      startWith({\n        active: getElement(`label[for=${active.id}]`)\n      } as ContentTabs)\n    )\n}\n\n/**\n * Mount content tabs\n *\n * This function scrolls the active tab into view. While this functionality is\n * provided by browsers as part of `scrollInfoView`, browsers will always also\n * scroll the vertical axis, which we do not want. Thus, we decided to provide\n * this functionality ourselves.\n *\n * @param el - Content tabs element\n *\n * @returns Content tabs component observable\n */\nexport function mountContentTabs(\n  el: HTMLElement\n): Observable<Component<ContentTabs>> {\n  const container = getElement(\".tabbed-labels\", el)\n  return defer(() => {\n    const push$ = new Subject<ContentTabs>()\n    combineLatest([push$, watchElementSize(el)])\n      .pipe(\n        auditTime(1, animationFrameScheduler),\n        takeUntil(push$.pipe(takeLast(1)))\n      )\n        .subscribe({\n\n          /* Handle emission */\n          next([{ active }]) {\n            const offset = getElementOffset(active)\n            const { width } = getElementSize(active)\n\n            /* Set tab indicator offset and width */\n            el.style.setProperty(\"--md-indicator-x\", `${offset.x}px`)\n            el.style.setProperty(\"--md-indicator-width\", `${width}px`)\n\n            /* Smoothly scroll container */\n            container.scrollTo({\n              behavior: \"smooth\",\n              left: offset.x\n            })\n          },\n\n          /* Handle complete */\n          complete() {\n            el.style.removeProperty(\"--md-indicator-x\")\n            el.style.removeProperty(\"--md-indicator-width\")\n          }\n        })\n\n    /* Create and return component */\n    return watchContentTabs(el)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n    .pipe(\n      subscribeOn(asyncScheduler)\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { Observable, merge } from \"rxjs\"\n\nimport { getElements } from \"~/browser\"\n\nimport { Component } from \"../../_\"\nimport { Annotation } from \"../annotation\"\nimport {\n  CodeBlock,\n  Mermaid,\n  mountCodeBlock,\n  mountMermaid\n} from \"../code\"\nimport {\n  Details,\n  mountDetails\n} from \"../details\"\nimport {\n  DataTable,\n  mountDataTable\n} from \"../table\"\nimport {\n  ContentTabs,\n  mountContentTabs\n} from \"../tabs\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Content\n */\nexport type Content =\n  | Annotation\n  | ContentTabs\n  | CodeBlock\n  | Mermaid\n  | DataTable\n  | Details\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  target$: Observable<HTMLElement>     /* Location target observable */\n  print$: Observable<boolean>          /* Media print observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount content\n *\n * This function mounts all components that are found in the content of the\n * actual article, including code blocks, data tables and details.\n *\n * @param el - Content element\n * @param options - Options\n *\n * @returns Content component observable\n */\nexport function mountContent(\n  el: HTMLElement, { target$, print$ }: MountOptions\n): Observable<Component<Content>> {\n  return merge(\n\n    /* Code blocks */\n    ...getElements(\"pre:not(.mermaid) > code\", el)\n      .map(child => mountCodeBlock(child, { print$ })),\n\n    /* Mermaid diagrams */\n    ...getElements(\"pre.mermaid\", el)\n      .map(child => mountMermaid(child)),\n\n    /* Data tables */\n    ...getElements(\"table:not([class])\", el)\n      .map(child => mountDataTable(child)),\n\n    /* Details */\n    ...getElements(\"details\", el)\n      .map(child => mountDetails(child, { target$, print$ })),\n\n    /* Content tabs */\n    ...getElements(\"[data-tabs]\", el)\n      .map(child => mountContentTabs(child))\n  )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  defer,\n  delay,\n  finalize,\n  map,\n  merge,\n  of,\n  switchMap,\n  tap\n} from \"rxjs\"\n\nimport { getElement } from \"~/browser\"\n\nimport { Component } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Dialog\n */\nexport interface Dialog {\n  message: string                      /* Dialog message */\n  active: boolean                      /* Dialog is active */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  alert$: Subject<string>              /* Alert subject */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  alert$: Subject<string>              /* Alert subject */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch dialog\n *\n * @param _el - Dialog element\n * @param options - Options\n *\n * @returns Dialog observable\n */\nexport function watchDialog(\n  _el: HTMLElement, { alert$ }: WatchOptions\n): Observable<Dialog> {\n  return alert$\n    .pipe(\n      switchMap(message => merge(\n        of(true),\n        of(false).pipe(delay(2000))\n      )\n        .pipe(\n          map(active => ({ message, active }))\n        )\n      )\n    )\n}\n\n/**\n * Mount dialog\n *\n * This function reveals the dialog in the right corner when a new alert is\n * emitted through the subject that is passed as part of the options.\n *\n * @param el - Dialog element\n * @param options - Options\n *\n * @returns Dialog component observable\n */\nexport function mountDialog(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<Dialog>> {\n  const inner = getElement(\".md-typeset\", el)\n  return defer(() => {\n    const push$ = new Subject<Dialog>()\n    push$.subscribe(({ message, active }) => {\n      inner.textContent = message\n      if (active)\n        el.setAttribute(\"data-md-state\", \"open\")\n      else\n        el.removeAttribute(\"data-md-state\")\n    })\n\n    /* Create and return component */\n    return watchDialog(el, options)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  bufferCount,\n  combineLatest,\n  combineLatestWith,\n  defer,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  map,\n  of,\n  shareReplay,\n  startWith,\n  switchMap,\n  takeLast,\n  takeUntil\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  Viewport,\n  watchElementSize,\n  watchToggle\n} from \"~/browser\"\n\nimport { Component } from \"../../_\"\nimport { Main } from \"../../main\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Header\n */\nexport interface Header {\n  height: number                       /* Header visible height */\n  hidden: boolean                      /* Header is hidden */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n  main$: Observable<Main>              /* Main area observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Compute whether the header is hidden\n *\n * If the user scrolls past a certain threshold, the header can be hidden when\n * scrolling down, and shown when scrolling up.\n *\n * @param options - Options\n *\n * @returns Toggle observable\n */\nfunction isHidden({ viewport$ }: WatchOptions): Observable<boolean> {\n  if (!feature(\"header.autohide\"))\n    return of(false)\n\n  /* Compute direction and turning point */\n  const direction$ = viewport$\n    .pipe(\n      map(({ offset: { y } }) => y),\n      bufferCount(2, 1),\n      map(([a, b]) => [a < b, b] as const),\n      distinctUntilKeyChanged(0)\n    )\n\n  /* Compute whether header should be hidden */\n  const hidden$ = combineLatest([viewport$, direction$])\n    .pipe(\n      filter(([{ offset }, [, y]]) => Math.abs(y - offset.y) > 100),\n      map(([, [direction]]) => direction),\n      distinctUntilChanged()\n    )\n\n  /* Compute threshold for hiding */\n  const search$ = watchToggle(\"search\")\n  return combineLatest([viewport$, search$])\n    .pipe(\n      map(([{ offset }, search]) => offset.y > 400 && !search),\n      distinctUntilChanged(),\n      switchMap(active => active ? hidden$ : of(false)),\n      startWith(false)\n    )\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch header\n *\n * @param el - Header element\n * @param options - Options\n *\n * @returns Header observable\n */\nexport function watchHeader(\n  el: HTMLElement, options: WatchOptions\n): Observable<Header> {\n  return defer(() => combineLatest([\n    watchElementSize(el),\n    isHidden(options)\n  ]))\n    .pipe(\n      map(([{ height }, hidden]) => ({\n        height,\n        hidden\n      })),\n      distinctUntilChanged((a, b) => (\n        a.height === b.height &&\n        a.hidden === b.hidden\n      )),\n      shareReplay(1)\n    )\n}\n\n/**\n * Mount header\n *\n * This function manages the different states of the header, i.e. whether it's\n * hidden or rendered with a shadow. This depends heavily on the main area.\n *\n * @param el - Header element\n * @param options - Options\n *\n * @returns Header component observable\n */\nexport function mountHeader(\n  el: HTMLElement, { header$, main$ }: MountOptions\n): Observable<Component<Header>> {\n  return defer(() => {\n    const push$ = new Subject<Main>()\n    push$\n      .pipe(\n        distinctUntilKeyChanged(\"active\"),\n        combineLatestWith(header$)\n      )\n        .subscribe(([{ active }, { hidden }]) => {\n          if (active)\n            el.setAttribute(\"data-md-state\", hidden ? \"hidden\" : \"shadow\")\n          else\n            el.removeAttribute(\"data-md-state\")\n        })\n\n    /* Link to main area */\n    main$.subscribe(push$)\n\n    /* Create and return component */\n    return header$\n      .pipe(\n        takeUntil(push$.pipe(takeLast(1))),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  defer,\n  distinctUntilKeyChanged,\n  finalize,\n  map,\n  tap\n} from \"rxjs\"\n\nimport {\n  Viewport,\n  getElementSize,\n  getOptionalElement,\n  watchViewportAt\n} from \"~/browser\"\n\nimport { Component } from \"../../_\"\nimport { Header } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Header\n */\nexport interface HeaderTitle {\n  active: boolean                      /* Header title is active */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch header title\n *\n * @param el - Heading element\n * @param options - Options\n *\n * @returns Header title observable\n */\nexport function watchHeaderTitle(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<HeaderTitle> {\n  return watchViewportAt(el, { viewport$, header$ })\n    .pipe(\n      map(({ offset: { y } }) => {\n        const { height } = getElementSize(el)\n        return {\n          active: y >= height\n        }\n      }),\n      distinctUntilKeyChanged(\"active\")\n    )\n}\n\n/**\n * Mount header title\n *\n * This function swaps the header title from the site title to the title of the\n * current page when the user scrolls past the first headline.\n *\n * @param el - Header title element\n * @param options - Options\n *\n * @returns Header title component observable\n */\nexport function mountHeaderTitle(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<HeaderTitle>> {\n  return defer(() => {\n    const push$ = new Subject<HeaderTitle>()\n    push$.subscribe(({ active }) => {\n      if (active)\n        el.setAttribute(\"data-md-state\", \"active\")\n      else\n        el.removeAttribute(\"data-md-state\")\n    })\n\n    /* Obtain headline, if any */\n    const heading = getOptionalElement(\"article h1\")\n    if (typeof heading === \"undefined\")\n      return EMPTY\n\n    /* Create and return component */\n    return watchHeaderTitle(heading, options)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  combineLatest,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  map,\n  switchMap\n} from \"rxjs\"\n\nimport {\n  Viewport,\n  watchElementSize\n} from \"~/browser\"\n\nimport { Header } from \"../header\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Main area\n */\nexport interface Main {\n  offset: number                       /* Main area top offset */\n  height: number                       /* Main area visible height */\n  active: boolean                      /* Main area is active */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch main area\n *\n * This function returns an observable that computes the visual parameters of\n * the main area which depends on the viewport vertical offset and height, as\n * well as the height of the header element, if the header is fixed.\n *\n * @param el - Main area element\n * @param options - Options\n *\n * @returns Main area observable\n */\nexport function watchMain(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<Main> {\n\n  /* Compute necessary adjustment for header */\n  const adjust$ = header$\n    .pipe(\n      map(({ height }) => height),\n      distinctUntilChanged()\n    )\n\n  /* Compute the main area's top and bottom borders */\n  const border$ = adjust$\n    .pipe(\n      switchMap(() => watchElementSize(el)\n        .pipe(\n          map(({ height }) => ({\n            top:    el.offsetTop,\n            bottom: el.offsetTop + height\n          })),\n          distinctUntilKeyChanged(\"bottom\")\n        )\n      )\n    )\n\n  /* Compute the main area's offset, visible height and if we scrolled past */\n  return combineLatest([adjust$, border$, viewport$])\n    .pipe(\n      map(([header, { top, bottom }, { offset: { y }, size: { height } }]) => {\n        height = Math.max(0, height\n          - Math.max(0, top    - y,  header)\n          - Math.max(0, height + y - bottom)\n        )\n        return {\n          offset: top - header,\n          height,\n          active: top - header <= y\n        }\n      }),\n      distinctUntilChanged((a, b) => (\n        a.offset === b.offset &&\n        a.height === b.height &&\n        a.active === b.active\n      ))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  asyncScheduler,\n  defer,\n  finalize,\n  fromEvent,\n  map,\n  mergeMap,\n  observeOn,\n  of,\n  shareReplay,\n  startWith,\n  tap\n} from \"rxjs\"\n\nimport { getElements } from \"~/browser\"\n\nimport { Component } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Palette colors\n */\nexport interface PaletteColor {\n  scheme?: string                      /* Color scheme */\n  primary?: string                     /* Primary color */\n  accent?: string                      /* Accent color */\n}\n\n/**\n * Palette\n */\nexport interface Palette {\n  index: number                        /* Palette index */\n  color: PaletteColor                  /* Palette colors */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch color palette\n *\n * @param inputs - Color palette element\n *\n * @returns Color palette observable\n */\nexport function watchPalette(\n  inputs: HTMLInputElement[]\n): Observable<Palette> {\n  const current = __md_get<Palette>(\"__palette\") || {\n    index: inputs.findIndex(input => matchMedia(\n      input.getAttribute(\"data-md-color-media\")!\n    ).matches)\n  }\n\n  /* Emit changes in color palette */\n  return of(...inputs)\n    .pipe(\n      mergeMap(input => fromEvent(input, \"change\")\n        .pipe(\n          map(() => input)\n        )\n      ),\n      startWith(inputs[Math.max(0, current.index)]),\n      map(input => ({\n        index: inputs.indexOf(input),\n        color: {\n          scheme:  input.getAttribute(\"data-md-color-scheme\"),\n          primary: input.getAttribute(\"data-md-color-primary\"),\n          accent:  input.getAttribute(\"data-md-color-accent\")\n        }\n      } as Palette)),\n      shareReplay(1)\n    )\n}\n\n/**\n * Mount color palette\n *\n * @param el - Color palette element\n *\n * @returns Color palette component observable\n */\nexport function mountPalette(\n  el: HTMLElement\n): Observable<Component<Palette>> {\n  return defer(() => {\n    const push$ = new Subject<Palette>()\n    push$.subscribe(palette => {\n      document.body.setAttribute(\"data-md-color-switching\", \"\")\n\n      /* Set color palette */\n      for (const [key, value] of Object.entries(palette.color))\n        document.body.setAttribute(`data-md-color-${key}`, value)\n\n      /* Toggle visibility */\n      for (let index = 0; index < inputs.length; index++) {\n        const label = inputs[index].nextElementSibling\n        if (label instanceof HTMLElement)\n          label.hidden = palette.index !== index\n      }\n\n      /* Persist preference in local storage */\n      __md_set(\"__palette\", palette)\n    })\n\n    /* Revert transition durations after color switch */\n    push$.pipe(observeOn(asyncScheduler))\n      .subscribe(() => {\n        document.body.removeAttribute(\"data-md-color-switching\")\n      })\n\n    /* Create and return component */\n    const inputs = getElements<HTMLInputElement>(\"input\", el)\n    return watchPalette(inputs)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport ClipboardJS from \"clipboard\"\nimport {\n  Observable,\n  Subject,\n  map,\n  tap\n} from \"rxjs\"\n\nimport { translation } from \"~/_\"\nimport { getElement } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Setup options\n */\ninterface SetupOptions {\n  alert$: Subject<string>              /* Alert subject */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Extract text to copy\n *\n * @param el - HTML element\n *\n * @returns Extracted text\n */\nfunction extract(el: HTMLElement): string {\n  el.setAttribute(\"data-md-copying\", \"\")\n  const text = el.innerText\n  el.removeAttribute(\"data-md-copying\")\n  return text\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up Clipboard.js integration\n *\n * @param options - Options\n */\nexport function setupClipboardJS(\n  { alert$ }: SetupOptions\n): void {\n  if (ClipboardJS.isSupported()) {\n    new Observable<ClipboardJS.Event>(subscriber => {\n      new ClipboardJS(\"[data-clipboard-target], [data-clipboard-text]\", {\n        text: el => (\n          el.getAttribute(\"data-clipboard-text\")! ||\n          extract(getElement(\n            el.getAttribute(\"data-clipboard-target\")!\n          ))\n        )\n      })\n        .on(\"success\", ev => subscriber.next(ev))\n    })\n      .pipe(\n        tap(ev => {\n          const trigger = ev.trigger as HTMLElement\n          trigger.focus()\n        }),\n        map(() => translation(\"clipboard.copied\"))\n      )\n        .subscribe(alert$)\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  catchError,\n  defaultIfEmpty,\n  map,\n  of,\n  tap\n} from \"rxjs\"\n\nimport { configuration } from \"~/_\"\nimport { getElements, requestXML } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Sitemap, i.e. a list of URLs\n */\nexport type Sitemap = string[]\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Preprocess a list of URLs\n *\n * This function replaces the `site_url` in the sitemap with the actual base\n * URL, to allow instant loading to work in occasions like Netlify previews.\n *\n * @param urls - URLs\n *\n * @returns URL path parts\n */\nfunction preprocess(urls: Sitemap): Sitemap {\n  if (urls.length < 2)\n    return [\"\"]\n\n  /* Take the first two URLs and remove everything after the last slash */\n  const [root, next] = [...urls]\n    .sort((a, b) => a.length - b.length)\n    .map(url => url.replace(/[^/]+$/, \"\"))\n\n  /* Compute common prefix */\n  let index = 0\n  if (root === next)\n    index = root.length\n  else\n    while (root.charCodeAt(index) === next.charCodeAt(index))\n      index++\n\n  /* Remove common prefix and return in original order */\n  return urls.map(url => url.replace(root.slice(0, index), \"\"))\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch the sitemap for the given base URL\n *\n * @param base - Base URL\n *\n * @returns Sitemap observable\n */\nexport function fetchSitemap(base?: URL): Observable<Sitemap> {\n  const cached = __md_get<Sitemap>(\"__sitemap\", sessionStorage, base)\n  if (cached) {\n    return of(cached)\n  } else {\n    const config = configuration()\n    return requestXML(new URL(\"sitemap.xml\", base || config.base))\n      .pipe(\n        map(sitemap => preprocess(getElements(\"loc\", sitemap)\n          .map(node => node.textContent!)\n        )),\n        catchError(() => EMPTY), // @todo refactor instant loading\n        defaultIfEmpty([]),\n        tap(sitemap => __md_set(\"__sitemap\", sitemap, sessionStorage, base))\n      )\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  NEVER,\n  Observable,\n  Subject,\n  bufferCount,\n  catchError,\n  concatMap,\n  debounceTime,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  fromEvent,\n  map,\n  merge,\n  of,\n  sample,\n  share,\n  skip,\n  skipUntil,\n  switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"~/_\"\nimport {\n  Viewport,\n  ViewportOffset,\n  getElements,\n  getOptionalElement,\n  request,\n  setLocation,\n  setLocationHash\n} from \"~/browser\"\nimport { getComponentElement } from \"~/components\"\nimport { h } from \"~/utilities\"\n\nimport { fetchSitemap } from \"../sitemap\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * History state\n */\nexport interface HistoryState {\n  url: URL                             /* State URL */\n  offset?: ViewportOffset              /* State viewport offset */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Setup options\n */\ninterface SetupOptions {\n  document$: Subject<Document>         /* Document subject */\n  location$: Subject<URL>              /* Location subject */\n  viewport$: Observable<Viewport>      /* Viewport observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up instant loading\n *\n * When fetching, theoretically, we could use `responseType: \"document\"`, but\n * since all MkDocs links are relative, we need to make sure that the current\n * location matches the document we just loaded. Otherwise any relative links\n * in the document could use the old location.\n *\n * This is the reason why we need to synchronize history events and the process\n * of fetching the document for navigation changes (except `popstate` events):\n *\n * 1. Fetch document via `XMLHTTPRequest`\n * 2. Set new location via `history.pushState`\n * 3. Parse and emit fetched document\n *\n * For `popstate` events, we must not use `history.pushState`, or the forward\n * history will be irreversibly overwritten. In case the request fails, the\n * location change is dispatched regularly.\n *\n * @param options - Options\n */\nexport function setupInstantLoading(\n  { document$, location$, viewport$ }: SetupOptions\n): void {\n  const config = configuration()\n  if (location.protocol === \"file:\")\n    return\n\n  /* Disable automatic scroll restoration */\n  if (\"scrollRestoration\" in history) {\n    history.scrollRestoration = \"manual\"\n\n    /* Hack: ensure that reloads restore viewport offset */\n    fromEvent(window, \"beforeunload\")\n      .subscribe(() => {\n        history.scrollRestoration = \"auto\"\n      })\n  }\n\n  /* Hack: ensure absolute favicon link to omit 404s when switching */\n  const favicon = getOptionalElement<HTMLLinkElement>(\"link[rel=icon]\")\n  if (typeof favicon !== \"undefined\")\n    favicon.href = favicon.href\n\n  /* Intercept internal navigation */\n  const push$ = fetchSitemap()\n    .pipe(\n      map(paths => paths.map(path => `${new URL(path, config.base)}`)),\n      switchMap(urls => fromEvent<MouseEvent>(document.body, \"click\")\n        .pipe(\n          filter(ev => !ev.metaKey && !ev.ctrlKey),\n          switchMap(ev => {\n            if (ev.target instanceof Element) {\n              const el = ev.target.closest(\"a\")\n              if (el && !el.target) {\n                const url = new URL(el.href)\n\n                /* Canonicalize URL */\n                url.search = \"\"\n                url.hash = \"\"\n\n                /* Check if URL should be intercepted */\n                if (\n                  url.pathname !== location.pathname &&\n                  urls.includes(url.toString())\n                ) {\n                  ev.preventDefault()\n                  return of({\n                    url: new URL(el.href)\n                  })\n                }\n              }\n            }\n            return NEVER\n          })\n        )\n      ),\n      share<HistoryState>()\n    )\n\n  /* Intercept history back and forward */\n  const pop$ = fromEvent<PopStateEvent>(window, \"popstate\")\n    .pipe(\n      filter(ev => ev.state !== null),\n      map(ev => ({\n        url: new URL(location.href),\n        offset: ev.state\n      })),\n      share<HistoryState>()\n    )\n\n  /* Emit location change */\n  merge(push$, pop$)\n    .pipe(\n      distinctUntilChanged((a, b) => a.url.href === b.url.href),\n      map(({ url }) => url)\n    )\n      .subscribe(location$)\n\n  /* Fetch document via `XMLHTTPRequest` */\n  const response$ = location$\n    .pipe(\n      distinctUntilKeyChanged(\"pathname\"),\n      switchMap(url => request(url.href)\n        .pipe(\n          catchError(() => {\n            setLocation(url)\n            return NEVER\n          })\n        )\n      ),\n      share()\n    )\n\n  /* Set new location via `history.pushState` */\n  push$\n    .pipe(\n      sample(response$)\n    )\n      .subscribe(({ url }) => {\n        history.pushState({}, \"\", `${url}`)\n      })\n\n  /* Parse and emit fetched document */\n  const dom = new DOMParser()\n  response$\n    .pipe(\n      switchMap(res => res.text()),\n      map(res => dom.parseFromString(res, \"text/html\"))\n    )\n      .subscribe(document$)\n\n  /* Replace meta tags and components */\n  document$\n    .pipe(\n      skip(1)\n    )\n      .subscribe(replacement => {\n        for (const selector of [\n\n          /* Meta tags */\n          \"title\",\n          \"link[rel=canonical]\",\n          \"meta[name=author]\",\n          \"meta[name=description]\",\n\n          /* Components */\n          \"[data-md-component=announce]\",\n          \"[data-md-component=container]\",\n          \"[data-md-component=header-topic]\",\n          \"[data-md-component=outdated]\",\n          \"[data-md-component=logo]\",\n          \"[data-md-component=skip]\",\n          ...feature(\"navigation.tabs.sticky\")\n            ? [\"[data-md-component=tabs]\"]\n            : []\n        ]) {\n          const source = getOptionalElement(selector)\n          const target = getOptionalElement(selector, replacement)\n          if (\n            typeof source !== \"undefined\" &&\n            typeof target !== \"undefined\"\n          ) {\n            source.replaceWith(target)\n          }\n        }\n      })\n\n  /* Re-evaluate scripts */\n  document$\n    .pipe(\n      skip(1),\n      map(() => getComponentElement(\"container\")),\n      switchMap(el => getElements(\"script\", el)),\n      concatMap(el => {\n        const script = h(\"script\")\n        if (el.src) {\n          for (const name of el.getAttributeNames())\n            script.setAttribute(name, el.getAttribute(name)!)\n          el.replaceWith(script)\n\n          /* Complete when script is loaded */\n          return new Observable(observer => {\n            script.onload = () => observer.complete()\n          })\n\n        /* Complete immediately */\n        } else {\n          script.textContent = el.textContent\n          el.replaceWith(script)\n          return EMPTY\n        }\n      })\n    )\n      .subscribe()\n\n  /* Emit history state change */\n  merge(push$, pop$)\n    .pipe(\n      sample(document$)\n    )\n      .subscribe(({ url, offset }) => {\n        if (url.hash && !offset) {\n          setLocationHash(url.hash)\n        } else {\n          window.scrollTo(0, offset?.y || 0)\n        }\n      })\n\n  /* Debounce update of viewport offset */\n  viewport$\n    .pipe(\n      skipUntil(push$),\n      debounceTime(250),\n      distinctUntilKeyChanged(\"offset\")\n    )\n      .subscribe(({ offset }) => {\n        history.replaceState(offset, \"\")\n      })\n\n  /* Set viewport offset from history */\n  merge(push$, pop$)\n    .pipe(\n      bufferCount(2, 1),\n      filter(([a, b]) => a.url.pathname === b.url.pathname),\n      map(([, state]) => state)\n    )\n      .subscribe(({ offset }) => {\n        window.scrollTo(0, offset?.y || 0)\n      })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport escapeHTML from \"escape-html\"\n\nimport { SearchIndexDocument } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search document\n */\nexport interface SearchDocument extends SearchIndexDocument {\n  parent?: SearchIndexDocument         /* Parent article */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search document mapping\n */\nexport type SearchDocumentMap = Map<string, SearchDocument>\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create a search document mapping\n *\n * @param docs - Search index documents\n *\n * @returns Search document map\n */\nexport function setupSearchDocumentMap(\n  docs: SearchIndexDocument[]\n): SearchDocumentMap {\n  const documents = new Map<string, SearchDocument>()\n  const parents   = new Set<SearchDocument>()\n  for (const doc of docs) {\n    const [path, hash] = doc.location.split(\"#\")\n\n    /* Extract location, title and tags */\n    const location = doc.location\n    const title    = doc.title\n    const tags     = doc.tags\n\n    /* Escape and cleanup text */\n    const text = escapeHTML(doc.text)\n      .replace(/\\s+(?=[,.:;!?])/g, \"\")\n      .replace(/\\s+/g, \" \")\n\n    /* Handle section */\n    if (hash) {\n      const parent = documents.get(path)!\n\n      /* Ignore first section, override article */\n      if (!parents.has(parent)) {\n        parent.title = doc.title\n        parent.text  = text\n\n        /* Remember that we processed the article */\n        parents.add(parent)\n\n      /* Add subsequent section */\n      } else {\n        documents.set(location, {\n          location,\n          title,\n          text,\n          parent\n        })\n      }\n\n    /* Add article */\n    } else {\n      documents.set(location, {\n        location,\n        title,\n        text,\n        ...tags && { tags }\n      })\n    }\n  }\n  return documents\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport escapeHTML from \"escape-html\"\n\nimport { SearchIndexConfig } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search highlight function\n *\n * @param value - Value\n *\n * @returns Highlighted value\n */\nexport type SearchHighlightFn = (value: string) => string\n\n/**\n * Search highlight factory function\n *\n * @param query - Query value\n *\n * @returns Search highlight function\n */\nexport type SearchHighlightFactoryFn = (query: string) => SearchHighlightFn\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create a search highlighter\n *\n * @param config - Search index configuration\n * @param escape - Whether to escape HTML\n *\n * @returns Search highlight factory function\n */\nexport function setupSearchHighlighter(\n  config: SearchIndexConfig, escape: boolean\n): SearchHighlightFactoryFn {\n  const separator = new RegExp(config.separator, \"img\")\n  const highlight = (_: unknown, data: string, term: string) => {\n    return `${data}<mark data-md-highlight>${term}</mark>`\n  }\n\n  /* Return factory function */\n  return (query: string) => {\n    query = query\n      .replace(/[\\s*+\\-:~^]+/g, \" \")\n      .trim()\n\n    /* Create search term match expression */\n    const match = new RegExp(`(^|${config.separator})(${\n      query\n        .replace(/[|\\\\{}()[\\]^$+*?.-]/g, \"\\\\$&\")\n        .replace(separator, \"|\")\n    })`, \"img\")\n\n    /* Highlight string value */\n    return value => (\n      escape\n        ? escapeHTML(value)\n        : value\n      )\n        .replace(match, highlight)\n        .replace(/<\\/mark>(\\s+)<mark[^>]*>/img, \"$1\")\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search transformation function\n *\n * @param value - Query value\n *\n * @returns Transformed query value\n */\nexport type SearchTransformFn = (value: string) => string\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Default transformation function\n *\n * 1. Search for terms in quotation marks and prepend a `+` modifier to denote\n *    that the resulting document must contain all terms, converting the query\n *    to an `AND` query (as opposed to the default `OR` behavior). While users\n *    may expect terms enclosed in quotation marks to map to span queries, i.e.\n *    for which order is important, Lunr.js doesn't support them, so the best\n *    we can do is to convert the terms to an `AND` query.\n *\n * 2. Replace control characters which are not located at the beginning of the\n *    query or preceded by white space, or are not followed by a non-whitespace\n *    character or are at the end of the query string. Furthermore, filter\n *    unmatched quotation marks.\n *\n * 3. Trim excess whitespace from left and right.\n *\n * @param query - Query value\n *\n * @returns Transformed query value\n */\nexport function defaultTransform(query: string): string {\n  return query\n    .split(/\"([^\"]+)\"/g)                            /* => 1 */\n      .map((terms, index) => index & 1\n        ? terms.replace(/^\\b|^(?![^\\x00-\\x7F]|$)|\\s+/g, \" +\")\n        : terms\n      )\n      .join(\"\")\n    .replace(/\"|(?:^|\\s+)[*+\\-:^~]+(?=\\s+|$)/g, \"\") /* => 2 */\n    .trim()                                         /* => 3 */\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A RTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { SearchIndex, SearchResult } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search message type\n */\nexport const enum SearchMessageType {\n  SETUP,                               /* Search index setup */\n  READY,                               /* Search index ready */\n  QUERY,                               /* Search query */\n  RESULT                               /* Search results */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Message containing the data necessary to setup the search index\n */\nexport interface SearchSetupMessage {\n  type: SearchMessageType.SETUP        /* Message type */\n  data: SearchIndex                    /* Message data */\n}\n\n/**\n * Message indicating the search index is ready\n */\nexport interface SearchReadyMessage {\n  type: SearchMessageType.READY        /* Message type */\n}\n\n/**\n * Message containing a search query\n */\nexport interface SearchQueryMessage {\n  type: SearchMessageType.QUERY        /* Message type */\n  data: string                         /* Message data */\n}\n\n/**\n * Message containing results for a search query\n */\nexport interface SearchResultMessage {\n  type: SearchMessageType.RESULT       /* Message type */\n  data: SearchResult                   /* Message data */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Message exchanged with the search worker\n */\nexport type SearchMessage =\n  | SearchSetupMessage\n  | SearchReadyMessage\n  | SearchQueryMessage\n  | SearchResultMessage\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Type guard for search setup messages\n *\n * @param message - Search worker message\n *\n * @returns Test result\n */\nexport function isSearchSetupMessage(\n  message: SearchMessage\n): message is SearchSetupMessage {\n  return message.type === SearchMessageType.SETUP\n}\n\n/**\n * Type guard for search ready messages\n *\n * @param message - Search worker message\n *\n * @returns Test result\n */\nexport function isSearchReadyMessage(\n  message: SearchMessage\n): message is SearchReadyMessage {\n  return message.type === SearchMessageType.READY\n}\n\n/**\n * Type guard for search query messages\n *\n * @param message - Search worker message\n *\n * @returns Test result\n */\nexport function isSearchQueryMessage(\n  message: SearchMessage\n): message is SearchQueryMessage {\n  return message.type === SearchMessageType.QUERY\n}\n\n/**\n * Type guard for search result messages\n *\n * @param message - Search worker message\n *\n * @returns Test result\n */\nexport function isSearchResultMessage(\n  message: SearchMessage\n): message is SearchResultMessage {\n  return message.type === SearchMessageType.RESULT\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A RTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  ObservableInput,\n  Subject,\n  from,\n  map,\n  share\n} from \"rxjs\"\n\nimport { configuration, feature, translation } from \"~/_\"\nimport { WorkerHandler, watchWorker } from \"~/browser\"\n\nimport { SearchIndex } from \"../../_\"\nimport {\n  SearchOptions,\n  SearchPipeline\n} from \"../../options\"\nimport {\n  SearchMessage,\n  SearchMessageType,\n  SearchSetupMessage,\n  isSearchResultMessage\n} from \"../message\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search worker\n */\nexport type SearchWorker = WorkerHandler<SearchMessage>\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up search index\n *\n * @param data - Search index\n *\n * @returns Search index\n */\nfunction setupSearchIndex({ config, docs }: SearchIndex): SearchIndex {\n\n  /* Override default language with value from translation */\n  if (config.lang.length === 1 && config.lang[0] === \"en\")\n    config.lang = [\n      translation(\"search.config.lang\")\n    ]\n\n  /* Override default separator with value from translation */\n  if (config.separator === \"[\\\\s\\\\-]+\")\n    config.separator = translation(\"search.config.separator\")\n\n  /* Set pipeline from translation */\n  const pipeline = translation(\"search.config.pipeline\")\n    .split(/\\s*,\\s*/)\n    .filter(Boolean) as SearchPipeline\n\n  /* Determine search options */\n  const options: SearchOptions = {\n    pipeline,\n    suggestions: feature(\"search.suggest\")\n  }\n\n  /* Return search index after defaulting */\n  return { config, docs, options }\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up search worker\n *\n * This function creates a web worker to set up and query the search index,\n * which is done using Lunr.js. The index must be passed as an observable to\n * enable hacks like _localsearch_ via search index embedding as JSON.\n *\n * @param url - Worker URL\n * @param index - Search index observable input\n *\n * @returns Search worker\n */\nexport function setupSearchWorker(\n  url: string, index: ObservableInput<SearchIndex>\n): SearchWorker {\n  const config = configuration()\n  const worker = new Worker(url)\n\n  /* Create communication channels and resolve relative links */\n  const tx$ = new Subject<SearchMessage>()\n  const rx$ = watchWorker(worker, { tx$ })\n    .pipe(\n      map(message => {\n        if (isSearchResultMessage(message)) {\n          for (const result of message.data.items)\n            for (const document of result)\n              document.location = `${new URL(document.location, config.base)}`\n        }\n        return message\n      }),\n      share()\n    )\n\n  /* Set up search index */\n  from(index)\n    .pipe(\n      map(data => ({\n        type: SearchMessageType.SETUP,\n        data: setupSearchIndex(data)\n      } as SearchSetupMessage))\n    )\n      .subscribe(tx$.next.bind(tx$))\n\n  /* Return search worker */\n  return { tx$, rx$ }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Subject,\n  catchError,\n  combineLatest,\n  filter,\n  fromEvent,\n  map,\n  of,\n  switchMap\n} from \"rxjs\"\n\nimport { configuration } from \"~/_\"\nimport {\n  getElement,\n  getLocation,\n  requestJSON,\n  setLocation\n} from \"~/browser\"\nimport { getComponentElements } from \"~/components\"\nimport {\n  Version,\n  renderVersionSelector\n} from \"~/templates\"\n\nimport { fetchSitemap } from \"../sitemap\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Setup options\n */\ninterface SetupOptions {\n  document$: Subject<Document>         /* Document subject */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Set up version selector\n *\n * @param options - Options\n */\nexport function setupVersionSelector(\n  { document$ }: SetupOptions\n): void {\n  const config = configuration()\n  const versions$ = requestJSON<Version[]>(\n    new URL(\"../versions.json\", config.base)\n  )\n    .pipe(\n      catchError(() => EMPTY) // @todo refactor instant loading\n    )\n\n  /* Determine current version */\n  const current$ = versions$\n    .pipe(\n      map(versions => {\n        const [, current] = config.base.match(/([^/]+)\\/?$/)!\n        return versions.find(({ version, aliases }) => (\n          version === current || aliases.includes(current)\n        )) || versions[0]\n      })\n    )\n\n  /* Intercept inter-version navigation */\n  combineLatest([versions$, current$])\n    .pipe(\n      map(([versions, current]) => new Map(versions\n        .filter(version => version !== current)\n        .map(version => [\n          `${new URL(`../${version.version}/`, config.base)}`,\n          version\n        ])\n      )),\n      switchMap(urls => fromEvent<MouseEvent>(document.body, \"click\")\n        .pipe(\n          filter(ev => !ev.metaKey && !ev.ctrlKey),\n          switchMap(ev => {\n            if (ev.target instanceof Element) {\n              const el = ev.target.closest(\"a\")\n              if (el && !el.target && urls.has(el.href)) {\n                ev.preventDefault()\n                return of(el.href)\n              }\n            }\n            return EMPTY\n          }),\n          switchMap(url => {\n            const { version } = urls.get(url)!\n            return fetchSitemap(new URL(url))\n              .pipe(\n                map(sitemap => {\n                  const location = getLocation()\n                  const path = location.href.replace(config.base, \"\")\n                  return sitemap.includes(path)\n                    ? new URL(`../${version}/${path}`, config.base)\n                    : new URL(url)\n                })\n              )\n          })\n        )\n      )\n    )\n      .subscribe(url => setLocation(url))\n\n  /* Render version selector and warning */\n  combineLatest([versions$, current$])\n    .subscribe(([versions, current]) => {\n      const topic = getElement(\".md-header__topic\")\n      topic.appendChild(renderVersionSelector(versions, current))\n    })\n\n  /* Integrate outdated version banner with instant loading */\n  document$.pipe(switchMap(() => current$))\n    .subscribe(current => {\n\n      /* Check if version state was already determined */\n      let outdated = __md_get(\"__outdated\", sessionStorage)\n      if (outdated === null) {\n        const latest = config.version?.default || \"latest\"\n        outdated = !current.aliases.includes(latest)\n\n        /* Persist version state in session storage */\n        __md_set(\"__outdated\", outdated, sessionStorage)\n      }\n\n      /* Unhide outdated version banner */\n      if (outdated)\n        for (const warning of getComponentElements(\"outdated\"))\n          warning.hidden = false\n    })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  combineLatest,\n  delay,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  filter,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  shareReplay,\n  startWith,\n  take,\n  takeLast,\n  takeUntil,\n  tap\n} from \"rxjs\"\n\nimport { translation } from \"~/_\"\nimport {\n  getLocation,\n  setToggle,\n  watchElementFocus,\n  watchToggle\n} from \"~/browser\"\nimport {\n  SearchMessageType,\n  SearchQueryMessage,\n  SearchWorker,\n  defaultTransform,\n  isSearchReadyMessage\n} from \"~/integrations\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search query\n */\nexport interface SearchQuery {\n  value: string                        /* Query value */\n  focus: boolean                       /* Query focus */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch search query\n *\n * Note that the focus event which triggers re-reading the current query value\n * is delayed by `1ms` so the input's empty state is allowed to propagate.\n *\n * @param el - Search query element\n * @param worker - Search worker\n *\n * @returns Search query observable\n */\nexport function watchSearchQuery(\n  el: HTMLInputElement, { rx$ }: SearchWorker\n): Observable<SearchQuery> {\n  const fn = __search?.transform || defaultTransform\n\n  /* Immediately show search dialog */\n  const { searchParams } = getLocation()\n  if (searchParams.has(\"q\"))\n    setToggle(\"search\", true)\n\n  /* Intercept query parameter (deep link) */\n  const param$ = rx$\n    .pipe(\n      filter(isSearchReadyMessage),\n      take(1),\n      map(() => searchParams.get(\"q\") || \"\")\n    )\n\n  /* Remove query parameter when search is closed */\n  watchToggle(\"search\")\n    .pipe(\n      filter(active => !active),\n      take(1)\n    )\n      .subscribe(() => {\n        const url = new URL(location.href)\n        url.searchParams.delete(\"q\")\n        history.replaceState({}, \"\", `${url}`)\n      })\n\n  /* Set query from parameter */\n  param$.subscribe(value => { // TODO: not ideal - find a better way\n    if (value) {\n      el.value = value\n      el.focus()\n    }\n  })\n\n  /* Intercept focus and input events */\n  const focus$ = watchElementFocus(el)\n  const value$ = merge(\n    fromEvent(el, \"keyup\"),\n    fromEvent(el, \"focus\").pipe(delay(1)),\n    param$\n  )\n    .pipe(\n      map(() => fn(el.value)),\n      startWith(\"\"),\n      distinctUntilChanged(),\n    )\n\n  /* Combine into single observable */\n  return combineLatest([value$, focus$])\n    .pipe(\n      map(([value, focus]) => ({ value, focus })),\n      shareReplay(1)\n    )\n}\n\n/**\n * Mount search query\n *\n * @param el - Search query element\n * @param worker - Search worker\n *\n * @returns Search query component observable\n */\nexport function mountSearchQuery(\n  el: HTMLInputElement, { tx$, rx$ }: SearchWorker\n): Observable<Component<SearchQuery, HTMLInputElement>> {\n  const push$ = new Subject<SearchQuery>()\n\n  /* Handle value changes */\n  push$\n    .pipe(\n      distinctUntilKeyChanged(\"value\"),\n      map(({ value }): SearchQueryMessage => ({\n        type: SearchMessageType.QUERY,\n        data: value\n      }))\n    )\n      .subscribe(tx$.next.bind(tx$))\n\n  /* Handle focus changes */\n  push$\n    .pipe(\n      distinctUntilKeyChanged(\"focus\")\n    )\n      .subscribe(({ focus }) => {\n        if (focus) {\n          setToggle(\"search\", focus)\n          el.placeholder = \"\"\n        } else {\n          el.placeholder = translation(\"search.placeholder\")\n        }\n      })\n\n  /* Handle reset */\n  fromEvent(el.form!, \"reset\")\n    .pipe(\n      takeUntil(push$.pipe(takeLast(1)))\n    )\n      .subscribe(() => el.focus())\n\n  /* Create and return component */\n  return watchSearchQuery(el, { tx$, rx$ })\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(state => ({ ref: el, ...state }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  bufferCount,\n  filter,\n  finalize,\n  map,\n  merge,\n  of,\n  skipUntil,\n  switchMap,\n  take,\n  tap,\n  withLatestFrom,\n  zipWith\n} from \"rxjs\"\n\nimport { translation } from \"~/_\"\nimport {\n  getElement,\n  watchElementBoundary\n} from \"~/browser\"\nimport {\n  SearchResult,\n  SearchWorker,\n  isSearchReadyMessage,\n  isSearchResultMessage\n} from \"~/integrations\"\nimport { renderSearchResultItem } from \"~/templates\"\nimport { round } from \"~/utilities\"\n\nimport { Component } from \"../../_\"\nimport { SearchQuery } from \"../query\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  query$: Observable<SearchQuery>      /* Search query observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search result list\n *\n * This function performs a lazy rendering of the search results, depending on\n * the vertical offset of the search result container.\n *\n * @param el - Search result list element\n * @param worker - Search worker\n * @param options - Options\n *\n * @returns Search result list component observable\n */\nexport function mountSearchResult(\n  el: HTMLElement, { rx$ }: SearchWorker, { query$ }: MountOptions\n): Observable<Component<SearchResult>> {\n  const push$ = new Subject<SearchResult>()\n  const boundary$ = watchElementBoundary(el.parentElement!)\n    .pipe(\n      filter(Boolean)\n    )\n\n  /* Retrieve nested components */\n  const meta = getElement(\":scope > :first-child\", el)\n  const list = getElement(\":scope > :last-child\", el)\n\n  /* Wait until search is ready */\n  const ready$ = rx$\n    .pipe(\n      filter(isSearchReadyMessage),\n      take(1)\n    )\n\n  /* Update search result metadata */\n  push$\n    .pipe(\n      withLatestFrom(query$),\n      skipUntil(ready$)\n    )\n      .subscribe(([{ items }, { value }]) => {\n        if (value) {\n          switch (items.length) {\n\n            /* No results */\n            case 0:\n              meta.textContent = translation(\"search.result.none\")\n              break\n\n            /* One result */\n            case 1:\n              meta.textContent = translation(\"search.result.one\")\n              break\n\n            /* Multiple result */\n            default:\n              meta.textContent = translation(\n                \"search.result.other\",\n                round(items.length)\n              )\n          }\n        } else {\n          meta.textContent = translation(\"search.result.placeholder\")\n        }\n      })\n\n  /* Update search result list */\n  push$\n    .pipe(\n      tap(() => list.innerHTML = \"\"),\n      switchMap(({ items }) => merge(\n        of(...items.slice(0, 10)),\n        of(...items.slice(10))\n          .pipe(\n            bufferCount(4),\n            zipWith(boundary$),\n            switchMap(([chunk]) => chunk)\n          )\n      ))\n    )\n      .subscribe(result => list.appendChild(\n        renderSearchResultItem(result)\n      ))\n\n  /* Filter search result message */\n  const result$ = rx$\n    .pipe(\n      filter(isSearchResultMessage),\n      map(({ data }) => data)\n    )\n\n  /* Create and return component */\n  return result$\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(state => ({ ref: el, ...state }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  finalize,\n  fromEvent,\n  map,\n  tap\n} from \"rxjs\"\n\nimport { getLocation } from \"~/browser\"\n\nimport { Component } from \"../../_\"\nimport { SearchQuery } from \"../query\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search sharing\n */\nexport interface SearchShare {\n  url: URL                             /* Deep link for sharing */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  query$: Observable<SearchQuery>      /* Search query observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  query$: Observable<SearchQuery>      /* Search query observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search sharing\n *\n * @param _el - Search sharing element\n * @param options - Options\n *\n * @returns Search sharing observable\n */\nexport function watchSearchShare(\n  _el: HTMLElement, { query$ }: WatchOptions\n): Observable<SearchShare> {\n  return query$\n    .pipe(\n      map(({ value }) => {\n        const url = getLocation()\n        url.hash = \"\"\n        url.searchParams.delete(\"h\")\n        url.searchParams.set(\"q\", value)\n        return { url }\n      })\n    )\n}\n\n/**\n * Mount search sharing\n *\n * @param el - Search sharing element\n * @param options - Options\n *\n * @returns Search sharing component observable\n */\nexport function mountSearchShare(\n  el: HTMLAnchorElement, options: MountOptions\n): Observable<Component<SearchShare>> {\n  const push$ = new Subject<SearchShare>()\n  push$.subscribe(({ url }) => {\n    el.setAttribute(\"data-clipboard-text\", el.href)\n    el.href = `${url}`\n  })\n\n  /* Prevent following of link */\n  fromEvent(el, \"click\")\n    .subscribe(ev => ev.preventDefault())\n\n  /* Create and return component */\n  return watchSearchShare(el, options)\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(state => ({ ref: el, ...state }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  asyncScheduler,\n  combineLatestWith,\n  distinctUntilChanged,\n  filter,\n  finalize,\n  fromEvent,\n  map,\n  merge,\n  observeOn,\n  tap\n} from \"rxjs\"\n\nimport { Keyboard } from \"~/browser\"\nimport {\n  SearchResult,\n  SearchWorker,\n  isSearchResultMessage\n} from \"~/integrations\"\n\nimport { Component, getComponentElement } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search suggestions\n */\nexport interface SearchSuggest {}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  keyboard$: Observable<Keyboard>      /* Keyboard observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search suggestions\n *\n * This function will perform a lazy rendering of the search results, depending\n * on the vertical offset of the search result container.\n *\n * @param el - Search result list element\n * @param worker - Search worker\n * @param options - Options\n *\n * @returns Search result list component observable\n */\nexport function mountSearchSuggest(\n  el: HTMLElement, { rx$ }: SearchWorker, { keyboard$ }: MountOptions\n): Observable<Component<SearchSuggest>> {\n  const push$ = new Subject<SearchResult>()\n\n  /* Retrieve query component and track all changes */\n  const query  = getComponentElement(\"search-query\")\n  const query$ = merge(\n    fromEvent(query, \"keydown\"),\n    fromEvent(query, \"focus\")\n  )\n    .pipe(\n      observeOn(asyncScheduler),\n      map(() => query.value),\n      distinctUntilChanged(),\n    )\n\n  /* Update search suggestions */\n  push$\n    .pipe(\n      combineLatestWith(query$),\n      map(([{ suggestions }, value]) => {\n        const words = value.split(/([\\s-]+)/)\n        if (suggestions?.length && words[words.length - 1]) {\n          const last = suggestions[suggestions.length - 1]\n          if (last.startsWith(words[words.length - 1]))\n            words[words.length - 1] = last\n        } else {\n          words.length = 0\n        }\n        return words\n      })\n    )\n      .subscribe(words => el.innerHTML = words\n        .join(\"\")\n        .replace(/\\s/g, \"&nbsp;\")\n      )\n\n  /* Set up search keyboard handlers */\n  keyboard$\n    .pipe(\n      filter(({ mode }) => mode === \"search\")\n    )\n      .subscribe(key => {\n        switch (key.type) {\n\n          /* Right arrow: accept current suggestion */\n          case \"ArrowRight\":\n            if (\n              el.innerText.length &&\n              query.selectionStart === query.value.length\n            )\n              query.value = el.innerText\n            break\n        }\n      })\n\n  /* Filter search result message */\n  const result$ = rx$\n    .pipe(\n      filter(isSearchResultMessage),\n      map(({ data }) => data)\n    )\n\n  /* Create and return component */\n  return result$\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(() => ({ ref: el }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  NEVER,\n  Observable,\n  ObservableInput,\n  filter,\n  merge,\n  mergeWith,\n  sample,\n  take\n} from \"rxjs\"\n\nimport { configuration } from \"~/_\"\nimport {\n  Keyboard,\n  getActiveElement,\n  getElements,\n  setToggle\n} from \"~/browser\"\nimport {\n  SearchIndex,\n  SearchResult,\n  isSearchQueryMessage,\n  isSearchReadyMessage,\n  setupSearchWorker\n} from \"~/integrations\"\n\nimport {\n  Component,\n  getComponentElement,\n  getComponentElements\n} from \"../../_\"\nimport {\n  SearchQuery,\n  mountSearchQuery\n} from \"../query\"\nimport { mountSearchResult } from \"../result\"\nimport {\n  SearchShare,\n  mountSearchShare\n} from \"../share\"\nimport {\n  SearchSuggest,\n  mountSearchSuggest\n} from \"../suggest\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search\n */\nexport type Search =\n  | SearchQuery\n  | SearchResult\n  | SearchShare\n  | SearchSuggest\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  index$: ObservableInput<SearchIndex> /* Search index observable */\n  keyboard$: Observable<Keyboard>      /* Keyboard observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search\n *\n * This function sets up the search functionality, including the underlying\n * web worker and all keyboard bindings.\n *\n * @param el - Search element\n * @param options - Options\n *\n * @returns Search component observable\n */\nexport function mountSearch(\n  el: HTMLElement, { index$, keyboard$ }: MountOptions\n): Observable<Component<Search>> {\n  const config = configuration()\n  try {\n    const url = __search?.worker || config.search\n    const worker = setupSearchWorker(url, index$)\n\n    /* Retrieve query and result components */\n    const query  = getComponentElement(\"search-query\", el)\n    const result = getComponentElement(\"search-result\", el)\n\n    /* Re-emit query when search is ready */\n    const { tx$, rx$ } = worker\n    tx$\n      .pipe(\n        filter(isSearchQueryMessage),\n        sample(rx$.pipe(filter(isSearchReadyMessage))),\n        take(1)\n      )\n        .subscribe(tx$.next.bind(tx$))\n\n    /* Set up search keyboard handlers */\n    keyboard$\n      .pipe(\n        filter(({ mode }) => mode === \"search\")\n      )\n        .subscribe(key => {\n          const active = getActiveElement()\n          switch (key.type) {\n\n            /* Enter: go to first (best) result */\n            case \"Enter\":\n              if (active === query) {\n                const anchors = new Map<HTMLAnchorElement, number>()\n                for (const anchor of getElements<HTMLAnchorElement>(\n                  \":first-child [href]\", result\n                )) {\n                  const article = anchor.firstElementChild!\n                  anchors.set(anchor, parseFloat(\n                    article.getAttribute(\"data-md-score\")!\n                  ))\n                }\n\n                /* Go to result with highest score, if any */\n                if (anchors.size) {\n                  const [[best]] = [...anchors].sort(([, a], [, b]) => b - a)\n                  best.click()\n                }\n\n                /* Otherwise omit form submission */\n                key.claim()\n              }\n              break\n\n            /* Escape or Tab: close search */\n            case \"Escape\":\n            case \"Tab\":\n              setToggle(\"search\", false)\n              query.blur()\n              break\n\n            /* Vertical arrows: select previous or next search result */\n            case \"ArrowUp\":\n            case \"ArrowDown\":\n              if (typeof active === \"undefined\") {\n                query.focus()\n              } else {\n                const els = [query, ...getElements(\n                  \":not(details) > [href], summary, details[open] [href]\",\n                  result\n                )]\n                const i = Math.max(0, (\n                  Math.max(0, els.indexOf(active)) + els.length + (\n                    key.type === \"ArrowUp\" ? -1 : +1\n                  )\n                ) % els.length)\n                els[i].focus()\n              }\n\n              /* Prevent scrolling of page */\n              key.claim()\n              break\n\n            /* All other keys: hand to search query */\n            default:\n              if (query !== getActiveElement())\n                query.focus()\n          }\n        })\n\n    /* Set up global keyboard handlers */\n    keyboard$\n      .pipe(\n        filter(({ mode }) => mode === \"global\"),\n      )\n        .subscribe(key => {\n          switch (key.type) {\n\n            /* Open search and select query */\n            case \"f\":\n            case \"s\":\n            case \"/\":\n              query.focus()\n              query.select()\n\n              /* Prevent scrolling of page */\n              key.claim()\n              break\n          }\n        })\n\n    /* Create and return component */\n    const query$  = mountSearchQuery(query, worker)\n    const result$ = mountSearchResult(result, worker, { query$ })\n    return merge(query$, result$)\n      .pipe(\n        mergeWith(\n\n          /* Search sharing */\n          ...getComponentElements(\"search-share\", el)\n            .map(child => mountSearchShare(child, { query$ })),\n\n          /* Search suggestions */\n          ...getComponentElements(\"search-suggest\", el)\n            .map(child => mountSearchSuggest(child, worker, { keyboard$ }))\n        )\n      )\n\n  /* Gracefully handle broken search */\n  } catch (err) {\n    el.hidden = true\n    return NEVER\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  ObservableInput,\n  combineLatest,\n  filter,\n  map,\n  startWith\n} from \"rxjs\"\n\nimport { getLocation } from \"~/browser\"\nimport {\n  SearchIndex,\n  setupSearchHighlighter\n} from \"~/integrations\"\nimport { h } from \"~/utilities\"\n\nimport { Component } from \"../../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search highlighting\n */\nexport interface SearchHighlight {\n  nodes: Map<ChildNode, string>        /* Map of replacements */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  index$: ObservableInput<SearchIndex> /* Search index observable */\n  location$: Observable<URL>           /* Location observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Mount search highlighting\n *\n * @param el - Content element\n * @param options - Options\n *\n * @returns Search highlighting component observable\n */\nexport function mountSearchHiglight(\n  el: HTMLElement, { index$, location$ }: MountOptions\n): Observable<Component<SearchHighlight>> {\n  return combineLatest([\n    index$,\n    location$\n      .pipe(\n        startWith(getLocation()),\n        filter(url => !!url.searchParams.get(\"h\"))\n      )\n  ])\n    .pipe(\n      map(([index, url]) => setupSearchHighlighter(index.config, true)(\n        url.searchParams.get(\"h\")!\n      )),\n      map(fn => {\n        const nodes = new Map<ChildNode, string>()\n\n        /* Traverse text nodes and collect matches */\n        const it = document.createNodeIterator(el, NodeFilter.SHOW_TEXT)\n        for (let node = it.nextNode(); node; node = it.nextNode()) {\n          if (node.parentElement?.offsetHeight) {\n            const original = node.textContent!\n            const replaced = fn(original)\n            if (replaced.length > original.length)\n              nodes.set(node as ChildNode, replaced)\n          }\n        }\n\n        /* Replace original nodes with matches */\n        for (const [node, text] of nodes) {\n          const { childNodes } = h(\"span\", null, text)\n          node.replaceWith(...Array.from(childNodes))\n        }\n\n        /* Return component */\n        return { ref: el, nodes }\n      })\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  animationFrameScheduler,\n  auditTime,\n  combineLatest,\n  defer,\n  distinctUntilChanged,\n  finalize,\n  map,\n  tap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport {\n  Viewport,\n  getElement,\n  getElementOffset\n} from \"~/browser\"\n\nimport { Component } from \"../_\"\nimport { Header } from \"../header\"\nimport { Main } from \"../main\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Sidebar\n */\nexport interface Sidebar {\n  height: number                       /* Sidebar height */\n  locked: boolean                      /* Sidebar is locked */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  main$: Observable<Main>              /* Main area observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n  main$: Observable<Main>              /* Main area observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch sidebar\n *\n * This function returns an observable that computes the visual parameters of\n * the sidebar which depends on the vertical viewport offset, as well as the\n * height of the main area. When the page is scrolled beyond the header, the\n * sidebar is locked and fills the remaining space.\n *\n * @param el - Sidebar element\n * @param options - Options\n *\n * @returns Sidebar observable\n */\nexport function watchSidebar(\n  el: HTMLElement, { viewport$, main$ }: WatchOptions\n): Observable<Sidebar> {\n  const parent = el.parentElement!\n  const adjust =\n    parent.offsetTop -\n    parent.parentElement!.offsetTop\n\n  /* Compute the sidebar's available height and if it should be locked */\n  return combineLatest([main$, viewport$])\n    .pipe(\n      map(([{ offset, height }, { offset: { y } }]) => {\n        height = height\n          + Math.min(adjust, Math.max(0, y - offset))\n          - adjust\n        return {\n          height,\n          locked: y >= offset + adjust\n        }\n      }),\n      distinctUntilChanged((a, b) => (\n        a.height === b.height &&\n        a.locked === b.locked\n      ))\n    )\n}\n\n/**\n * Mount sidebar\n *\n * This function doesn't set the height of the actual sidebar, but of its first\n * child \u2013 the `.md-sidebar__scrollwrap` element in order to mitigiate jittery\n * sidebars when the footer is scrolled into view. At some point we switched\n * from `absolute` / `fixed` positioning to `sticky` positioning, significantly\n * reducing jitter in some browsers (respectively Firefox and Safari) when\n * scrolling from the top. However, top-aligned sticky positioning means that\n * the sidebar snaps to the bottom when the end of the container is reached.\n * This is what leads to the mentioned jitter, as the sidebar's height may be\n * updated too slowly.\n *\n * This behaviour can be mitigiated by setting the height of the sidebar to `0`\n * while preserving the padding, and the height on its first element.\n *\n * @param el - Sidebar element\n * @param options - Options\n *\n * @returns Sidebar component observable\n */\nexport function mountSidebar(\n  el: HTMLElement, { header$, ...options }: MountOptions\n): Observable<Component<Sidebar>> {\n  const inner = getElement(\".md-sidebar__scrollwrap\", el)\n  const { y } = getElementOffset(inner)\n  return defer(() => {\n    const push$ = new Subject<Sidebar>()\n    push$\n      .pipe(\n        auditTime(0, animationFrameScheduler),\n        withLatestFrom(header$)\n      )\n        .subscribe({\n\n          /* Handle emission */\n          next([{ height }, { height: offset }]) {\n            inner.style.height = `${height - 2 * y}px`\n            el.style.top       = `${offset}px`\n          },\n\n          /* Handle complete */\n          complete() {\n            inner.style.height = \"\"\n            el.style.top       = \"\"\n          }\n        })\n\n    /* Create and return component */\n    return watchSidebar(el, options)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { Repo, User } from \"github-types\"\nimport {\n  EMPTY,\n  Observable,\n  catchError,\n  defaultIfEmpty,\n  map,\n  zip\n} from \"rxjs\"\n\nimport { requestJSON } from \"~/browser\"\n\nimport { SourceFacts } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * GitHub release (partial)\n */\ninterface Release {\n  tag_name: string                     /* Tag name */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch GitHub repository facts\n *\n * @param user - GitHub user or organization\n * @param repo - GitHub repository\n *\n * @returns Repository facts observable\n */\nexport function fetchSourceFactsFromGitHub(\n  user: string, repo?: string\n): Observable<SourceFacts> {\n  if (typeof repo !== \"undefined\") {\n    const url = `https://api.github.com/repos/${user}/${repo}`\n    return zip(\n\n      /* Fetch version */\n      requestJSON<Release>(`${url}/releases/latest`)\n        .pipe(\n          catchError(() => EMPTY), // @todo refactor instant loading\n          map(release => ({\n            version: release.tag_name\n          })),\n          defaultIfEmpty({})\n        ),\n\n      /* Fetch stars and forks */\n      requestJSON<Repo>(url)\n        .pipe(\n          catchError(() => EMPTY), // @todo refactor instant loading\n          map(info => ({\n            stars: info.stargazers_count,\n            forks: info.forks_count\n          })),\n          defaultIfEmpty({})\n        )\n    )\n      .pipe(\n        map(([release, info]) => ({ ...release, ...info }))\n      )\n\n  /* User or organization */\n  } else {\n    const url = `https://api.github.com/users/${user}`\n    return requestJSON<User>(url)\n      .pipe(\n        map(info => ({\n          repositories: info.public_repos\n        })),\n        defaultIfEmpty({})\n      )\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { ProjectSchema } from \"gitlab\"\nimport {\n  EMPTY,\n  Observable,\n  catchError,\n  defaultIfEmpty,\n  map\n} from \"rxjs\"\n\nimport { requestJSON } from \"~/browser\"\n\nimport { SourceFacts } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch GitLab repository facts\n *\n * @param base - GitLab base\n * @param project - GitLab project\n *\n * @returns Repository facts observable\n */\nexport function fetchSourceFactsFromGitLab(\n  base: string, project: string\n): Observable<SourceFacts> {\n  const url = `https://${base}/api/v4/projects/${encodeURIComponent(project)}`\n  return requestJSON<ProjectSchema>(url)\n    .pipe(\n      catchError(() => EMPTY), // @todo refactor instant loading\n      map(({ star_count, forks_count }) => ({\n        stars: star_count,\n        forks: forks_count\n      })),\n      defaultIfEmpty({})\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport { EMPTY, Observable } from \"rxjs\"\n\nimport { fetchSourceFactsFromGitHub } from \"../github\"\nimport { fetchSourceFactsFromGitLab } from \"../gitlab\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Repository facts for repositories\n */\nexport interface RepositoryFacts {\n  stars?: number                       /* Number of stars */\n  forks?: number                       /* Number of forks */\n  version?: string                     /* Latest version */\n}\n\n/**\n * Repository facts for organizations\n */\nexport interface OrganizationFacts {\n  repositories?: number                /* Number of repositories */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Repository facts\n */\nexport type SourceFacts =\n  | RepositoryFacts\n  | OrganizationFacts\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch repository facts\n *\n * @param url - Repository URL\n *\n * @returns Repository facts observable\n */\nexport function fetchSourceFacts(\n  url: string\n): Observable<SourceFacts> {\n  const [type] = url.match(/(git(?:hub|lab))/i) || []\n  switch (type.toLowerCase()) {\n\n    /* GitHub repository */\n    case \"github\":\n      const [, user, repo] = url.match(/^.+github\\.com\\/([^/]+)\\/?([^/]+)?/i)!\n      return fetchSourceFactsFromGitHub(user, repo)\n\n    /* GitLab repository */\n    case \"gitlab\":\n      const [, base, slug] = url.match(/^.+?([^/]*gitlab[^/]+)\\/(.+?)\\/?$/i)!\n      return fetchSourceFactsFromGitLab(base, slug)\n\n    /* Everything else */\n    default:\n      return EMPTY\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  EMPTY,\n  Observable,\n  Subject,\n  catchError,\n  defer,\n  filter,\n  finalize,\n  map,\n  of,\n  shareReplay,\n  tap\n} from \"rxjs\"\n\nimport { getElement } from \"~/browser\"\nimport { renderSourceFacts } from \"~/templates\"\n\nimport { Component } from \"../../_\"\nimport {\n  SourceFacts,\n  fetchSourceFacts\n} from \"../facts\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Repository information\n */\nexport interface Source {\n  facts: SourceFacts                   /* Repository facts */\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Repository information observable\n */\nlet fetch$: Observable<Source>\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch repository information\n *\n * This function tries to read the repository facts from session storage, and\n * if unsuccessful, fetches them from the underlying provider.\n *\n * @param el - Repository information element\n *\n * @returns Repository information observable\n */\nexport function watchSource(\n  el: HTMLAnchorElement\n): Observable<Source> {\n  return fetch$ ||= defer(() => {\n    const cached = __md_get<SourceFacts>(\"__source\", sessionStorage)\n    if (cached)\n      return of(cached)\n    else\n      return fetchSourceFacts(el.href)\n        .pipe(\n          tap(facts => __md_set(\"__source\", facts, sessionStorage))\n        )\n  })\n    .pipe(\n      catchError(() => EMPTY),\n      filter(facts => Object.keys(facts).length > 0),\n      map(facts => ({ facts })),\n      shareReplay(1)\n    )\n}\n\n/**\n * Mount repository information\n *\n * @param el - Repository information element\n *\n * @returns Repository information component observable\n */\nexport function mountSource(\n  el: HTMLAnchorElement\n): Observable<Component<Source>> {\n  const inner = getElement(\":scope > :last-child\", el)\n  return defer(() => {\n    const push$ = new Subject<Source>()\n    push$.subscribe(({ facts }) => {\n      inner.appendChild(renderSourceFacts(facts))\n      inner.setAttribute(\"data-md-state\", \"done\")\n    })\n\n    /* Create and return component */\n    return watchSource(el)\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  defer,\n  distinctUntilKeyChanged,\n  finalize,\n  map,\n  of,\n  switchMap,\n  tap\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  Viewport,\n  watchElementSize,\n  watchViewportAt\n} from \"~/browser\"\n\nimport { Component } from \"../_\"\nimport { Header } from \"../header\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Navigation tabs\n */\nexport interface Tabs {\n  hidden: boolean                      /* Navigation tabs are hidden */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch navigation tabs\n *\n * @param el - Navigation tabs element\n * @param options - Options\n *\n * @returns Navigation tabs observable\n */\nexport function watchTabs(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<Tabs> {\n  return watchElementSize(document.body)\n    .pipe(\n      switchMap(() => watchViewportAt(el, { header$, viewport$ })),\n      map(({ offset: { y } }) => {\n        return {\n          hidden: y >= 10\n        }\n      }),\n      distinctUntilKeyChanged(\"hidden\")\n    )\n}\n\n/**\n * Mount navigation tabs\n *\n * This function hides the navigation tabs when scrolling past the threshold\n * and makes them reappear in a nice CSS animation when scrolling back up.\n *\n * @param el - Navigation tabs element\n * @param options - Options\n *\n * @returns Navigation tabs component observable\n */\nexport function mountTabs(\n  el: HTMLElement, options: MountOptions\n): Observable<Component<Tabs>> {\n  return defer(() => {\n    const push$ = new Subject<Tabs>()\n    push$.subscribe({\n\n      /* Handle emission */\n      next({ hidden }) {\n        if (hidden)\n          el.setAttribute(\"data-md-state\", \"hidden\")\n        else\n          el.removeAttribute(\"data-md-state\")\n      },\n\n      /* Handle complete */\n      complete() {\n        el.removeAttribute(\"data-md-state\")\n      }\n    })\n\n    /* Create and return component */\n    return (\n      feature(\"navigation.tabs.sticky\")\n        ? of({ hidden: false })\n        : watchTabs(el, options)\n    )\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  bufferCount,\n  combineLatestWith,\n  debounceTime,\n  defer,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  finalize,\n  map,\n  of,\n  repeat,\n  scan,\n  share,\n  skip,\n  startWith,\n  switchMap,\n  takeLast,\n  takeUntil,\n  tap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport { feature } from \"~/_\"\nimport {\n  Viewport,\n  getElement,\n  getElements,\n  getLocation,\n  getOptionalElement,\n  watchElementSize\n} from \"~/browser\"\n\nimport {\n  Component,\n  getComponentElement\n} from \"../_\"\nimport { Header } from \"../header\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Table of contents\n */\nexport interface TableOfContents {\n  prev: HTMLAnchorElement[][]          /* Anchors (previous) */\n  next: HTMLAnchorElement[][]          /* Anchors (next) */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n  target$: Observable<HTMLElement>     /* Location target observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch table of contents\n *\n * This is effectively a scroll spy implementation which will account for the\n * fixed header and automatically re-calculate anchor offsets when the viewport\n * is resized. The returned observable will only emit if the table of contents\n * needs to be repainted.\n *\n * This implementation tracks an anchor element's entire path starting from its\n * level up to the top-most anchor element, e.g. `[h3, h2, h1]`. Although the\n * Material theme currently doesn't make use of this information, it enables\n * the styling of the entire hierarchy through customization.\n *\n * Note that the current anchor is the last item of the `prev` anchor list.\n *\n * @param el - Table of contents element\n * @param options - Options\n *\n * @returns Table of contents observable\n */\nexport function watchTableOfContents(\n  el: HTMLElement, { viewport$, header$ }: WatchOptions\n): Observable<TableOfContents> {\n  const table = new Map<HTMLAnchorElement, HTMLElement>()\n\n  /* Compute anchor-to-target mapping */\n  const anchors = getElements<HTMLAnchorElement>(\"[href^=\\\\#]\", el)\n  for (const anchor of anchors) {\n    const id = decodeURIComponent(anchor.hash.substring(1))\n    const target = getOptionalElement(`[id=\"${id}\"]`)\n    if (typeof target !== \"undefined\")\n      table.set(anchor, target)\n  }\n\n  /* Compute necessary adjustment for header */\n  const adjust$ = header$\n    .pipe(\n      distinctUntilKeyChanged(\"height\"),\n      map(({ height }) => {\n        const main = getComponentElement(\"main\")\n        const grid = getElement(\":scope > :first-child\", main)\n        return height + 0.8 * (\n          grid.offsetTop -\n          main.offsetTop\n        )\n      }),\n      share()\n    )\n\n  /* Compute partition of previous and next anchors */\n  const partition$ = watchElementSize(document.body)\n    .pipe(\n      distinctUntilKeyChanged(\"height\"),\n\n      /* Build index to map anchor paths to vertical offsets */\n      switchMap(body => defer(() => {\n        let path: HTMLAnchorElement[] = []\n        return of([...table].reduce((index, [anchor, target]) => {\n          while (path.length) {\n            const last = table.get(path[path.length - 1])!\n            if (last.tagName >= target.tagName) {\n              path.pop()\n            } else {\n              break\n            }\n          }\n\n          /* If the current anchor is hidden, continue with its parent */\n          let offset = target.offsetTop\n          while (!offset && target.parentElement) {\n            target = target.parentElement\n            offset = target.offsetTop\n          }\n\n          /* Map reversed anchor path to vertical offset */\n          return index.set(\n            [...path = [...path, anchor]].reverse(),\n            offset\n          )\n        }, new Map<HTMLAnchorElement[], number>()))\n      })\n        .pipe(\n\n          /* Sort index by vertical offset (see https://bit.ly/30z6QSO) */\n          map(index => new Map([...index].sort(([, a], [, b]) => a - b))),\n          combineLatestWith(adjust$),\n\n          /* Re-compute partition when viewport offset changes */\n          switchMap(([index, adjust]) => viewport$\n            .pipe(\n              scan(([prev, next], { offset: { y }, size }) => {\n                const last = y + size.height >= Math.floor(body.height)\n\n                /* Look forward */\n                while (next.length) {\n                  const [, offset] = next[0]\n                  if (offset - adjust < y || last) {\n                    prev = [...prev, next.shift()!]\n                  } else {\n                    break\n                  }\n                }\n\n                /* Look backward */\n                while (prev.length) {\n                  const [, offset] = prev[prev.length - 1]\n                  if (offset - adjust >= y && !last) {\n                    next = [prev.pop()!, ...next]\n                  } else {\n                    break\n                  }\n                }\n\n                /* Return partition */\n                return [prev, next]\n              }, [[], [...index]]),\n              distinctUntilChanged((a, b) => (\n                a[0] === b[0] &&\n                a[1] === b[1]\n              ))\n            )\n          )\n        )\n      )\n    )\n\n  /* Compute and return anchor list migrations */\n  return partition$\n    .pipe(\n      map(([prev, next]) => ({\n        prev: prev.map(([path]) => path),\n        next: next.map(([path]) => path)\n      })),\n\n      /* Extract anchor list migrations */\n      startWith({ prev: [], next: [] }),\n      bufferCount(2, 1),\n      map(([a, b]) => {\n\n        /* Moving down */\n        if (a.prev.length < b.prev.length) {\n          return {\n            prev: b.prev.slice(Math.max(0, a.prev.length - 1), b.prev.length),\n            next: []\n          }\n\n        /* Moving up */\n        } else {\n          return {\n            prev: b.prev.slice(-1),\n            next: b.next.slice(0, b.next.length - a.next.length)\n          }\n        }\n      })\n    )\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Mount table of contents\n *\n * @param el - Table of contents element\n * @param options - Options\n *\n * @returns Table of contents component observable\n */\nexport function mountTableOfContents(\n  el: HTMLElement, { viewport$, header$, target$ }: MountOptions\n): Observable<Component<TableOfContents>> {\n  return defer(() => {\n    const push$ = new Subject<TableOfContents>()\n    push$.subscribe(({ prev, next }) => {\n\n      /* Look forward */\n      for (const [anchor] of next) {\n        anchor.removeAttribute(\"data-md-state\")\n        anchor.classList.remove(\n          \"md-nav__link--active\"\n        )\n      }\n\n      /* Look backward */\n      for (const [index, [anchor]] of prev.entries()) {\n        anchor.setAttribute(\"data-md-state\", \"blur\")\n        anchor.classList.toggle(\n          \"md-nav__link--active\",\n          index === prev.length - 1\n        )\n      }\n    })\n\n    /* Set up anchor tracking, if enabled */\n    if (feature(\"navigation.tracking\"))\n      viewport$\n        .pipe(\n          takeUntil(push$.pipe(takeLast(1))),\n          distinctUntilKeyChanged(\"offset\"),\n          debounceTime(250),\n          skip(1),\n          takeUntil(target$.pipe(skip(1))),\n          repeat({ delay: 250 }),\n          withLatestFrom(push$)\n        )\n          .subscribe(([, { prev }]) => {\n            const url = getLocation()\n\n            /* Set hash fragment to active anchor */\n            const anchor = prev[prev.length - 1]\n            if (anchor && anchor.length) {\n              const [active] = anchor\n              const { hash } = new URL(active.href)\n              if (url.hash !== hash) {\n                url.hash = hash\n                history.replaceState({}, \"\", `${url}`)\n              }\n\n            /* Reset anchor when at the top */\n            } else {\n              url.hash = \"\"\n              history.replaceState({}, \"\", `${url}`)\n            }\n          })\n\n    /* Create and return component */\n    return watchTableOfContents(el, { viewport$, header$ })\n      .pipe(\n        tap(state => push$.next(state)),\n        finalize(() => push$.complete()),\n        map(state => ({ ref: el, ...state }))\n      )\n  })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  Subject,\n  bufferCount,\n  combineLatest,\n  distinctUntilChanged,\n  distinctUntilKeyChanged,\n  endWith,\n  finalize,\n  map,\n  repeat,\n  skip,\n  takeLast,\n  takeUntil,\n  tap\n} from \"rxjs\"\n\nimport { Viewport } from \"~/browser\"\n\nimport { Component } from \"../_\"\nimport { Header } from \"../header\"\nimport { Main } from \"../main\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Back-to-top button\n */\nexport interface BackToTop {\n  hidden: boolean                      /* Back-to-top button is hidden */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch options\n */\ninterface WatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  main$: Observable<Main>              /* Main area observable */\n  target$: Observable<HTMLElement>     /* Location target observable */\n}\n\n/**\n * Mount options\n */\ninterface MountOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  header$: Observable<Header>          /* Header observable */\n  main$: Observable<Main>              /* Main area observable */\n  target$: Observable<HTMLElement>     /* Location target observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Watch back-to-top\n *\n * @param _el - Back-to-top element\n * @param options - Options\n *\n * @returns Back-to-top observable\n */\nexport function watchBackToTop(\n  _el: HTMLElement, { viewport$, main$, target$ }: WatchOptions\n): Observable<BackToTop> {\n\n  /* Compute direction */\n  const direction$ = viewport$\n    .pipe(\n      map(({ offset: { y } }) => y),\n      bufferCount(2, 1),\n      map(([a, b]) => a > b && b > 0),\n      distinctUntilChanged()\n    )\n\n  /* Compute whether main area is active */\n  const active$ = main$\n    .pipe(\n      map(({ active }) => active)\n    )\n\n  /* Compute threshold for hiding */\n  return combineLatest([active$, direction$])\n    .pipe(\n      map(([active, direction]) => !(active && direction)),\n      distinctUntilChanged(),\n      takeUntil(target$.pipe(skip(1))),\n      endWith(true),\n      repeat({ delay: 250 }),\n      map(hidden => ({ hidden }))\n    )\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Mount back-to-top\n *\n * @param el - Back-to-top element\n * @param options - Options\n *\n * @returns Back-to-top component observable\n */\nexport function mountBackToTop(\n  el: HTMLElement, { viewport$, header$, main$, target$ }: MountOptions\n): Observable<Component<BackToTop>> {\n  const push$ = new Subject<BackToTop>()\n  push$.subscribe({\n\n    /* Handle emission */\n    next({ hidden }) {\n      if (hidden) {\n        el.setAttribute(\"data-md-state\", \"hidden\")\n        el.setAttribute(\"tabindex\", \"-1\")\n        el.blur()\n      } else {\n        el.removeAttribute(\"data-md-state\")\n        el.removeAttribute(\"tabindex\")\n      }\n    },\n\n    /* Handle complete */\n    complete() {\n      el.style.top = \"\"\n      el.setAttribute(\"data-md-state\", \"hidden\")\n      el.removeAttribute(\"tabindex\")\n    }\n  })\n\n  /* Watch header height */\n  header$\n    .pipe(\n      takeUntil(push$.pipe(endWith(0), takeLast(1))),\n      distinctUntilKeyChanged(\"height\")\n    )\n      .subscribe(({ height }) => {\n        el.style.top = `${height + 16}px`\n      })\n\n  /* Create and return component */\n  return watchBackToTop(el, { viewport$, main$, target$ })\n    .pipe(\n      tap(state => push$.next(state)),\n      finalize(() => push$.complete()),\n      map(state => ({ ref: el, ...state }))\n    )\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  fromEvent,\n  map,\n  mergeMap,\n  switchMap,\n  takeWhile,\n  tap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport { getElements } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch options\n */\ninterface PatchOptions {\n  document$: Observable<Document>      /* Document observable */\n  tablet$: Observable<boolean>         /* Media tablet observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch indeterminate checkboxes\n *\n * This function replaces the indeterminate \"pseudo state\" with the actual\n * indeterminate state, which is used to keep navigation always expanded.\n *\n * @param options - Options\n */\nexport function patchIndeterminate(\n  { document$, tablet$ }: PatchOptions\n): void {\n  document$\n    .pipe(\n      switchMap(() => getElements<HTMLInputElement>(\n        \"[data-md-state=indeterminate]\"\n      )),\n      tap(el => {\n        el.indeterminate = true\n        el.checked = false\n      }),\n      mergeMap(el => fromEvent(el, \"change\")\n        .pipe(\n          takeWhile(() => el.hasAttribute(\"data-md-state\")),\n          map(() => el)\n        )\n      ),\n      withLatestFrom(tablet$)\n    )\n      .subscribe(([el, tablet]) => {\n        el.removeAttribute(\"data-md-state\")\n        if (tablet)\n          el.checked = false\n      })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  filter,\n  fromEvent,\n  map,\n  mergeMap,\n  switchMap,\n  tap\n} from \"rxjs\"\n\nimport { getElements } from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch options\n */\ninterface PatchOptions {\n  document$: Observable<Document>      /* Document observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Check whether the given device is an Apple device\n *\n * @returns Test result\n */\nfunction isAppleDevice(): boolean {\n  return /(iPad|iPhone|iPod)/.test(navigator.userAgent)\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch all elements with `data-md-scrollfix` attributes\n *\n * This is a year-old patch which ensures that overflow scrolling works at the\n * top and bottom of containers on iOS by ensuring a `1px` scroll offset upon\n * the start of a touch event.\n *\n * @see https://bit.ly/2SCtAOO - Original source\n *\n * @param options - Options\n */\nexport function patchScrollfix(\n  { document$ }: PatchOptions\n): void {\n  document$\n    .pipe(\n      switchMap(() => getElements(\"[data-md-scrollfix]\")),\n      tap(el => el.removeAttribute(\"data-md-scrollfix\")),\n      filter(isAppleDevice),\n      mergeMap(el => fromEvent(el, \"touchstart\")\n        .pipe(\n          map(() => el)\n        )\n      )\n    )\n      .subscribe(el => {\n        const top = el.scrollTop\n\n        /* We're at the top of the container */\n        if (top === 0) {\n          el.scrollTop = 1\n\n        /* We're at the bottom of the container */\n        } else if (top + el.offsetHeight === el.scrollHeight) {\n          el.scrollTop = top - 1\n        }\n      })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  Observable,\n  combineLatest,\n  delay,\n  map,\n  of,\n  switchMap,\n  withLatestFrom\n} from \"rxjs\"\n\nimport {\n  Viewport,\n  watchToggle\n} from \"~/browser\"\n\n/* ----------------------------------------------------------------------------\n * Helper types\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch options\n */\ninterface PatchOptions {\n  viewport$: Observable<Viewport>      /* Viewport observable */\n  tablet$: Observable<boolean>         /* Media tablet observable */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Patch the document body to lock when search is open\n *\n * For mobile and tablet viewports, the search is rendered full screen, which\n * leads to scroll leaking when at the top or bottom of the search result. This\n * function locks the body when the search is in full screen mode, and restores\n * the scroll position when leaving.\n *\n * @param options - Options\n */\nexport function patchScrolllock(\n  { viewport$, tablet$ }: PatchOptions\n): void {\n  combineLatest([watchToggle(\"search\"), tablet$])\n    .pipe(\n      map(([active, tablet]) => active && !tablet),\n      switchMap(active => of(active)\n        .pipe(\n          delay(active ? 400 : 100)\n        )\n      ),\n      withLatestFrom(viewport$)\n    )\n      .subscribe(([active, { offset: { y }}]) => {\n        if (active) {\n          document.body.setAttribute(\"data-md-state\", \"lock\")\n          document.body.style.top = `-${y}px`\n        } else {\n          const value = -1 * parseInt(document.body.style.top, 10)\n          document.body.removeAttribute(\"data-md-state\")\n          document.body.style.top = \"\"\n          if (value)\n            window.scrollTo(0, value)\n        }\n      })\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Polyfills\n * ------------------------------------------------------------------------- */\n\n/* Polyfill `Object.entries` */\nif (!Object.entries)\n  Object.entries = function (obj: object) {\n    const data: [string, string][] = []\n    for (const key of Object.keys(obj))\n      // @ts-expect-error - ignore property access warning\n      data.push([key, obj[key]])\n\n    /* Return entries */\n    return data\n  }\n\n/* Polyfill `Object.values` */\nif (!Object.values)\n  Object.values = function (obj: object) {\n    const data: string[] = []\n    for (const key of Object.keys(obj))\n      // @ts-expect-error - ignore property access warning\n      data.push(obj[key])\n\n    /* Return values */\n    return data\n  }\n\n/* ------------------------------------------------------------------------- */\n\n/* Polyfills for `Element` */\nif (typeof Element !== \"undefined\") {\n\n  /* Polyfill `Element.scrollTo` */\n  if (!Element.prototype.scrollTo)\n    Element.prototype.scrollTo = function (\n      x?: ScrollToOptions | number, y?: number\n    ): void {\n      if (typeof x === \"object\") {\n        this.scrollLeft = x.left!\n        this.scrollTop = x.top!\n      } else {\n        this.scrollLeft = x!\n        this.scrollTop = y!\n      }\n    }\n\n  /* Polyfill `Element.replaceWith` */\n  if (!Element.prototype.replaceWith)\n    Element.prototype.replaceWith = function (\n      ...nodes: Array<string | Node>\n    ): void {\n      const parent = this.parentNode\n      if (parent) {\n        if (nodes.length === 0)\n          parent.removeChild(this)\n\n        /* Replace children and create text nodes */\n        for (let i = nodes.length - 1; i >= 0; i--) {\n          let node = nodes[i]\n          if (typeof node !== \"object\")\n            node = document.createTextNode(node)\n          else if (node.parentNode)\n            node.parentNode.removeChild(node)\n\n          /* Replace child or insert before previous sibling */\n          if (!i)\n            parent.replaceChild(node, this)\n          else\n            parent.insertBefore(this.previousSibling!, node)\n        }\n      }\n    }\n}\n"],
-  "mappings": "g+BAAA,oBAAC,UAAU,EAAQ,EAAS,CAC1B,MAAO,KAAY,UAAY,MAAO,KAAW,YAAc,EAAQ,EACvE,MAAO,SAAW,YAAc,OAAO,IAAM,OAAO,CAAO,EAC1D,EAAQ,CACX,GAAE,GAAO,UAAY,CAAE,aASrB,WAAmC,EAAO,CACxC,GAAI,GAAmB,GACnB,EAA0B,GAC1B,EAAiC,KAEjC,EAAsB,CACxB,KAAM,GACN,OAAQ,GACR,IAAK,GACL,IAAK,GACL,MAAO,GACP,SAAU,GACV,OAAQ,GACR,KAAM,GACN,MAAO,GACP,KAAM,GACN,KAAM,GACN,SAAU,GACV,iBAAkB,EACpB,EAOA,WAA4B,EAAI,CAC9B,MACE,MACA,IAAO,UACP,EAAG,WAAa,QAChB,EAAG,WAAa,QAChB,aAAe,IACf,YAAc,GAAG,UAKrB,CASA,WAAuC,EAAI,CACzC,GAAI,IAAO,EAAG,KACV,GAAU,EAAG,QAUjB,MARI,QAAY,SAAW,EAAoB,KAAS,CAAC,EAAG,UAIxD,KAAY,YAAc,CAAC,EAAG,UAI9B,EAAG,kBAKT,CAOA,WAA8B,EAAI,CAChC,AAAI,EAAG,UAAU,SAAS,eAAe,GAGzC,GAAG,UAAU,IAAI,eAAe,EAChC,EAAG,aAAa,2BAA4B,EAAE,EAChD,CAOA,WAAiC,EAAI,CACnC,AAAI,CAAC,EAAG,aAAa,0BAA0B,GAG/C,GAAG,UAAU,OAAO,eAAe,EACnC,EAAG,gBAAgB,0BAA0B,EAC/C,CAUA,WAAmB,EAAG,CACpB,AAAI,EAAE,SAAW,EAAE,QAAU,EAAE,SAI3B,GAAmB,EAAM,aAAa,GACxC,EAAqB,EAAM,aAAa,EAG1C,EAAmB,GACrB,CAUA,WAAuB,EAAG,CACxB,EAAmB,EACrB,CASA,WAAiB,EAAG,CAElB,AAAI,CAAC,EAAmB,EAAE,MAAM,GAI5B,IAAoB,EAA8B,EAAE,MAAM,IAC5D,EAAqB,EAAE,MAAM,CAEjC,CAMA,WAAgB,EAAG,CACjB,AAAI,CAAC,EAAmB,EAAE,MAAM,GAK9B,GAAE,OAAO,UAAU,SAAS,eAAe,GAC3C,EAAE,OAAO,aAAa,0BAA0B,IAMhD,GAA0B,GAC1B,OAAO,aAAa,CAA8B,EAClD,EAAiC,OAAO,WAAW,UAAW,CAC5D,EAA0B,EAC5B,EAAG,GAAG,EACN,EAAwB,EAAE,MAAM,EAEpC,CAOA,WAA4B,EAAG,CAC7B,AAAI,SAAS,kBAAoB,UAK3B,IACF,GAAmB,IAErB,EAA+B,EAEnC,CAQA,YAA0C,CACxC,SAAS,iBAAiB,YAAa,CAAoB,EAC3D,SAAS,iBAAiB,YAAa,CAAoB,EAC3D,SAAS,iBAAiB,UAAW,CAAoB,EACzD,SAAS,iBAAiB,cAAe,CAAoB,EAC7D,SAAS,iBAAiB,cAAe,CAAoB,EAC7D,SAAS,iBAAiB,YAAa,CAAoB,EAC3D,SAAS,iBAAiB,YAAa,CAAoB,EAC3D,SAAS,iBAAiB,aAAc,CAAoB,EAC5D,SAAS,iBAAiB,WAAY,CAAoB,CAC5D,CAEA,YAA6C,CAC3C,SAAS,oBAAoB,YAAa,CAAoB,EAC9D,SAAS,oBAAoB,YAAa,CAAoB,EAC9D,SAAS,oBAAoB,UAAW,CAAoB,EAC5D,SAAS,oBAAoB,cAAe,CAAoB,EAChE,SAAS,oBAAoB,cAAe,CAAoB,EAChE,SAAS,oBAAoB,YAAa,CAAoB,EAC9D,SAAS,oBAAoB,YAAa,CAAoB,EAC9D,SAAS,oBAAoB,aAAc,CAAoB,EAC/D,SAAS,oBAAoB,WAAY,CAAoB,CAC/D,CASA,WAA8B,EAAG,CAG/B,AAAI,EAAE,OAAO,UAAY,EAAE,OAAO,SAAS,YAAY,IAAM,QAI7D,GAAmB,GACnB,EAAkC,EACpC,CAKA,SAAS,iBAAiB,UAAW,EAAW,EAAI,EACpD,SAAS,iBAAiB,YAAa,EAAe,EAAI,EAC1D,SAAS,iBAAiB,cAAe,EAAe,EAAI,EAC5D,SAAS,iBAAiB,aAAc,EAAe,EAAI,EAC3D,SAAS,iBAAiB,mBAAoB,EAAoB,EAAI,EAEtE,EAA+B,EAM/B,EAAM,iBAAiB,QAAS,EAAS,EAAI,EAC7C,EAAM,iBAAiB,OAAQ,EAAQ,EAAI,EAO3C,AAAI,EAAM,WAAa,KAAK,wBAA0B,EAAM,KAI1D,EAAM,KAAK,aAAa,wBAAyB,EAAE,EAC1C,EAAM,WAAa,KAAK,eACjC,UAAS,gBAAgB,UAAU,IAAI,kBAAkB,EACzD,SAAS,gBAAgB,aAAa,wBAAyB,EAAE,EAErE,CAKA,GAAI,MAAO,SAAW,aAAe,MAAO,WAAa,YAAa,CAIpE,OAAO,0BAA4B,EAInC,GAAI,GAEJ,GAAI,CACF,EAAQ,GAAI,aAAY,8BAA8B,CACxD,OAAS,EAAP,CAEA,EAAQ,SAAS,YAAY,aAAa,EAC1C,EAAM,gBAAgB,+BAAgC,GAAO,GAAO,CAAC,CAAC,CACxE,CAEA,OAAO,cAAc,CAAK,CAC5B,CAEA,AAAI,MAAO,WAAa,aAGtB,EAA0B,QAAQ,CAGtC,CAAE,ICvTF,eAAC,UAAS,EAAQ,CAOhB,GAAI,GAA6B,UAAW,CAC1C,GAAI,CACF,MAAO,CAAC,CAAC,OAAO,QAClB,OAAS,EAAP,CACA,MAAO,EACT,CACF,EAGI,EAAoB,EAA2B,EAE/C,EAAiB,SAAS,EAAO,CACnC,GAAI,GAAW,CACb,KAAM,UAAW,CACf,GAAI,GAAQ,EAAM,MAAM,EACxB,MAAO,CAAE,KAAM,IAAU,OAAQ,MAAO,CAAM,CAChD,CACF,EAEA,MAAI,IACF,GAAS,OAAO,UAAY,UAAW,CACrC,MAAO,EACT,GAGK,CACT,EAMI,EAAiB,SAAS,EAAO,CACnC,MAAO,oBAAmB,CAAK,EAAE,QAAQ,OAAQ,GAAG,CACtD,EAEI,EAAmB,SAAS,EAAO,CACrC,MAAO,oBAAmB,OAAO,CAAK,EAAE,QAAQ,MAAO,GAAG,CAAC,CAC7D,EAEI,EAA0B,UAAW,CAEvC,GAAI,GAAkB,SAAS,EAAc,CAC3C,OAAO,eAAe,KAAM,WAAY,CAAE,SAAU,GAAM,MAAO,CAAC,CAAE,CAAC,EACrE,GAAI,GAAqB,MAAO,GAEhC,GAAI,IAAuB,YAEpB,GAAI,IAAuB,SAChC,AAAI,IAAiB,IACnB,KAAK,YAAY,CAAY,UAEtB,YAAwB,GAAiB,CAClD,GAAI,GAAQ,KACZ,EAAa,QAAQ,SAAS,EAAO,EAAM,CACzC,EAAM,OAAO,EAAM,CAAK,CAC1B,CAAC,CACH,SAAY,IAAiB,MAAU,IAAuB,SAC5D,GAAI,OAAO,UAAU,SAAS,KAAK,CAAY,IAAM,iBACnD,OAAS,GAAI,EAAG,EAAI,EAAa,OAAQ,IAAK,CAC5C,GAAI,GAAQ,EAAa,GACzB,GAAK,OAAO,UAAU,SAAS,KAAK,CAAK,IAAM,kBAAsB,EAAM,SAAW,EACpF,KAAK,OAAO,EAAM,GAAI,EAAM,EAAE,MAE9B,MAAM,IAAI,WAAU,4CAA8C,EAAI,6BAA8B,CAExG,KAEA,QAAS,KAAO,GACd,AAAI,EAAa,eAAe,CAAG,GACjC,KAAK,OAAO,EAAK,EAAa,EAAI,MAKxC,MAAM,IAAI,WAAU,8CAA+C,CAEvE,EAEI,EAAQ,EAAgB,UAE5B,EAAM,OAAS,SAAS,EAAM,EAAO,CACnC,AAAI,IAAQ,MAAK,SACf,KAAK,SAAS,GAAM,KAAK,OAAO,CAAK,CAAC,EAEtC,KAAK,SAAS,GAAQ,CAAC,OAAO,CAAK,CAAC,CAExC,EAEA,EAAM,OAAS,SAAS,EAAM,CAC5B,MAAO,MAAK,SAAS,EACvB,EAEA,EAAM,IAAM,SAAS,EAAM,CACzB,MAAQ,KAAQ,MAAK,SAAY,KAAK,SAAS,GAAM,GAAK,IAC5D,EAEA,EAAM,OAAS,SAAS,EAAM,CAC5B,MAAQ,KAAQ,MAAK,SAAY,KAAK,SAAS,GAAM,MAAM,CAAC,EAAI,CAAC,CACnE,EAEA,EAAM,IAAM,SAAS,EAAM,CACzB,MAAQ,KAAQ,MAAK,QACvB,EAEA,EAAM,IAAM,SAAS,EAAM,EAAO,CAChC,KAAK,SAAS,GAAQ,CAAC,OAAO,CAAK,CAAC,CACtC,EAEA,EAAM,QAAU,SAAS,EAAU,EAAS,CAC1C,GAAI,GACJ,OAAS,KAAQ,MAAK,SACpB,GAAI,KAAK,SAAS,eAAe,CAAI,EAAG,CACtC,EAAU,KAAK,SAAS,GACxB,OAAS,GAAI,EAAG,EAAI,EAAQ,OAAQ,IAClC,EAAS,KAAK,EAAS,EAAQ,GAAI,EAAM,IAAI,CAEjD,CAEJ,EAEA,EAAM,KAAO,UAAW,CACtB,GAAI,GAAQ,CAAC,EACb,YAAK,QAAQ,SAAS,EAAO,EAAM,CACjC,EAAM,KAAK,CAAI,CACjB,CAAC,EACM,EAAe,CAAK,CAC7B,EAEA,EAAM,OAAS,UAAW,CACxB,GAAI,GAAQ,CAAC,EACb,YAAK,QAAQ,SAAS,EAAO,CAC3B,EAAM,KAAK,CAAK,CAClB,CAAC,EACM,EAAe,CAAK,CAC7B,EAEA,EAAM,QAAU,UAAW,CACzB,GAAI,GAAQ,CAAC,EACb,YAAK,QAAQ,SAAS,EAAO,EAAM,CACjC,EAAM,KAAK,CAAC,EAAM,CAAK,CAAC,CAC1B,CAAC,EACM,EAAe,CAAK,CAC7B,EAEI,GACF,GAAM,OAAO,UAAY,EAAM,SAGjC,EAAM,SAAW,UAAW,CAC1B,GAAI,GAAc,CAAC,EACnB,YAAK,QAAQ,SAAS,EAAO,EAAM,CACjC,EAAY,KAAK,EAAe,CAAI,EAAI,IAAM,EAAe,CAAK,CAAC,CACrE,CAAC,EACM,EAAY,KAAK,GAAG,CAC7B,EAGA,EAAO,gBAAkB,CAC3B,EAEI,EAAkC,UAAW,CAC/C,GAAI,CACF,GAAI,GAAkB,EAAO,gBAE7B,MACG,IAAI,GAAgB,MAAM,EAAE,SAAS,IAAM,OAC3C,MAAO,GAAgB,UAAU,KAAQ,YACzC,MAAO,GAAgB,UAAU,SAAY,UAElD,OAAS,EAAP,CACA,MAAO,EACT,CACF,EAEA,AAAK,EAAgC,GACnC,EAAwB,EAG1B,GAAI,GAAQ,EAAO,gBAAgB,UAEnC,AAAI,MAAO,GAAM,MAAS,YACxB,GAAM,KAAO,UAAW,CACtB,GAAI,GAAQ,KACR,EAAQ,CAAC,EACb,KAAK,QAAQ,SAAS,EAAO,EAAM,CACjC,EAAM,KAAK,CAAC,EAAM,CAAK,CAAC,EACnB,EAAM,UACT,EAAM,OAAO,CAAI,CAErB,CAAC,EACD,EAAM,KAAK,SAAS,EAAG,EAAG,CACxB,MAAI,GAAE,GAAK,EAAE,GACJ,GACE,EAAE,GAAK,EAAE,GACX,EAEA,CAEX,CAAC,EACG,EAAM,UACR,GAAM,SAAW,CAAC,GAEpB,OAAS,GAAI,EAAG,EAAI,EAAM,OAAQ,IAChC,KAAK,OAAO,EAAM,GAAG,GAAI,EAAM,GAAG,EAAE,CAExC,GAGE,MAAO,GAAM,aAAgB,YAC/B,OAAO,eAAe,EAAO,cAAe,CAC1C,WAAY,GACZ,aAAc,GACd,SAAU,GACV,MAAO,SAAS,EAAc,CAC5B,GAAI,KAAK,SACP,KAAK,SAAW,CAAC,MACZ,CACL,GAAI,GAAO,CAAC,EACZ,KAAK,QAAQ,SAAS,EAAO,EAAM,CACjC,EAAK,KAAK,CAAI,CAChB,CAAC,EACD,OAAS,GAAI,EAAG,EAAI,EAAK,OAAQ,IAC/B,KAAK,OAAO,EAAK,EAAE,CAEvB,CAEA,EAAe,EAAa,QAAQ,MAAO,EAAE,EAG7C,OAFI,GAAa,EAAa,MAAM,GAAG,EACnC,EACK,EAAI,EAAG,EAAI,EAAW,OAAQ,IACrC,EAAY,EAAW,GAAG,MAAM,GAAG,EACnC,KAAK,OACH,EAAiB,EAAU,EAAE,EAC5B,EAAU,OAAS,EAAK,EAAiB,EAAU,EAAE,EAAI,EAC5D,CAEJ,CACF,CAAC,CAKL,GACG,MAAO,SAAW,YAAe,OAC5B,MAAO,SAAW,YAAe,OACjC,MAAO,OAAS,YAAe,KAAO,EAC9C,EAEA,AAAC,UAAS,EAAQ,CAOhB,GAAI,GAAwB,UAAW,CACrC,GAAI,CACF,GAAI,GAAI,GAAI,GAAO,IAAI,IAAK,UAAU,EACtC,SAAE,SAAW,MACL,EAAE,OAAS,kBAAqB,EAAE,YAC5C,OAAS,EAAP,CACA,MAAO,EACT,CACF,EAGI,EAAc,UAAW,CAC3B,GAAI,GAAO,EAAO,IAEd,EAAM,SAAS,EAAK,EAAM,CAC5B,AAAI,MAAO,IAAQ,UAAU,GAAM,OAAO,CAAG,GACzC,GAAQ,MAAO,IAAS,UAAU,GAAO,OAAO,CAAI,GAGxD,GAAI,GAAM,SAAU,EACpB,GAAI,GAAS,GAAO,WAAa,QAAU,IAAS,EAAO,SAAS,MAAO,CACzE,EAAO,EAAK,YAAY,EACxB,EAAM,SAAS,eAAe,mBAAmB,EAAE,EACnD,EAAc,EAAI,cAAc,MAAM,EACtC,EAAY,KAAO,EACnB,EAAI,KAAK,YAAY,CAAW,EAChC,GAAI,CACF,GAAI,EAAY,KAAK,QAAQ,CAAI,IAAM,EAAG,KAAM,IAAI,OAAM,EAAY,IAAI,CAC5E,OAAS,EAAP,CACA,KAAM,IAAI,OAAM,0BAA4B,EAAO,WAAa,CAAG,CACrE,CACF,CAEA,GAAI,GAAgB,EAAI,cAAc,GAAG,EACzC,EAAc,KAAO,EACjB,GACF,GAAI,KAAK,YAAY,CAAa,EAClC,EAAc,KAAO,EAAc,MAGrC,GAAI,GAAe,EAAI,cAAc,OAAO,EAI5C,GAHA,EAAa,KAAO,MACpB,EAAa,MAAQ,EAEjB,EAAc,WAAa,KAAO,CAAC,IAAI,KAAK,EAAc,IAAI,GAAM,CAAC,EAAa,cAAc,GAAK,CAAC,EACxG,KAAM,IAAI,WAAU,aAAa,EAGnC,OAAO,eAAe,KAAM,iBAAkB,CAC5C,MAAO,CACT,CAAC,EAID,GAAI,GAAe,GAAI,GAAO,gBAAgB,KAAK,MAAM,EACrD,EAAqB,GACrB,EAA2B,GAC3B,EAAQ,KACZ,CAAC,SAAU,SAAU,KAAK,EAAE,QAAQ,SAAS,EAAY,CACvD,GAAI,IAAS,EAAa,GAC1B,EAAa,GAAc,UAAW,CACpC,GAAO,MAAM,EAAc,SAAS,EAChC,GACF,GAA2B,GAC3B,EAAM,OAAS,EAAa,SAAS,EACrC,EAA2B,GAE/B,CACF,CAAC,EAED,OAAO,eAAe,KAAM,eAAgB,CAC1C,MAAO,EACP,WAAY,EACd,CAAC,EAED,GAAI,GAAS,OACb,OAAO,eAAe,KAAM,sBAAuB,CACjD,WAAY,GACZ,aAAc,GACd,SAAU,GACV,MAAO,UAAW,CAChB,AAAI,KAAK,SAAW,GAClB,GAAS,KAAK,OACV,GACF,GAAqB,GACrB,KAAK,aAAa,YAAY,KAAK,MAAM,EACzC,EAAqB,IAG3B,CACF,CAAC,CACH,EAEI,EAAQ,EAAI,UAEZ,EAA6B,SAAS,EAAe,CACvD,OAAO,eAAe,EAAO,EAAe,CAC1C,IAAK,UAAW,CACd,MAAO,MAAK,eAAe,EAC7B,EACA,IAAK,SAAS,EAAO,CACnB,KAAK,eAAe,GAAiB,CACvC,EACA,WAAY,EACd,CAAC,CACH,EAEA,CAAC,OAAQ,OAAQ,WAAY,OAAQ,UAAU,EAC5C,QAAQ,SAAS,EAAe,CAC/B,EAA2B,CAAa,CAC1C,CAAC,EAEH,OAAO,eAAe,EAAO,SAAU,CACrC,IAAK,UAAW,CACd,MAAO,MAAK,eAAe,MAC7B,EACA,IAAK,SAAS,EAAO,CACnB,KAAK,eAAe,OAAY,EAChC,KAAK,oBAAoB,CAC3B,EACA,WAAY,EACd,CAAC,EAED,OAAO,iBAAiB,EAAO,CAE7B,SAAY,CACV,IAAK,UAAW,CACd,GAAI,GAAQ,KACZ,MAAO,WAAW,CAChB,MAAO,GAAM,IACf,CACF,CACF,EAEA,KAAQ,CACN,IAAK,UAAW,CACd,MAAO,MAAK,eAAe,KAAK,QAAQ,MAAO,EAAE,CACnD,EACA,IAAK,SAAS,EAAO,CACnB,KAAK,eAAe,KAAO,EAC3B,KAAK,oBAAoB,CAC3B,EACA,WAAY,EACd,EAEA,SAAY,CACV,IAAK,UAAW,CACd,MAAO,MAAK,eAAe,SAAS,QAAQ,SAAU,GAAG,CAC3D,EACA,IAAK,SAAS,EAAO,CACnB,KAAK,eAAe,SAAW,CACjC,EACA,WAAY,EACd,EAEA,OAAU,CACR,IAAK,UAAW,CAEd,GAAI,GAAe,CAAE,QAAS,GAAI,SAAU,IAAK,OAAQ,EAAG,EAAE,KAAK,eAAe,UAI9E,EAAkB,KAAK,eAAe,MAAQ,GAChD,KAAK,eAAe,OAAS,GAE/B,MAAO,MAAK,eAAe,SACzB,KACA,KAAK,eAAe,SACnB,GAAmB,IAAM,KAAK,eAAe,KAAQ,GAC1D,EACA,WAAY,EACd,EAEA,SAAY,CACV,IAAK,UAAW,CACd,MAAO,EACT,EACA,IAAK,SAAS,EAAO,CACrB,EACA,WAAY,EACd,EAEA,SAAY,CACV,IAAK,UAAW,CACd,MAAO,EACT,EACA,IAAK,SAAS,EAAO,CACrB,EACA,WAAY,EACd,CACF,CAAC,EAED,EAAI,gBAAkB,SAAS,EAAM,CACnC,MAAO,GAAK,gBAAgB,MAAM,EAAM,SAAS,CACnD,EAEA,EAAI,gBAAkB,SAAS,EAAK,CAClC,MAAO,GAAK,gBAAgB,MAAM,EAAM,SAAS,CACnD,EAEA,EAAO,IAAM,CAEf,EAMA,GAJK,EAAsB,GACzB,EAAY,EAGT,EAAO,WAAa,QAAW,CAAE,WAAY,GAAO,UAAW,CAClE,GAAI,GAAY,UAAW,CACzB,MAAO,GAAO,SAAS,SAAW,KAAO,EAAO,SAAS,SAAY,GAAO,SAAS,KAAQ,IAAM,EAAO,SAAS,KAAQ,GAC7H,EAEA,GAAI,CACF,OAAO,eAAe,EAAO,SAAU,SAAU,CAC/C,IAAK,EACL,WAAY,EACd,CAAC,CACH,OAAS,EAAP,CACA,YAAY,UAAW,CACrB,EAAO,SAAS,OAAS,EAAU,CACrC,EAAG,GAAG,CACR,CACF,CAEF,GACG,MAAO,SAAW,YAAe,OAC5B,MAAO,SAAW,YAAe,OACjC,MAAO,OAAS,YAAe,KAAO,EAC9C,IC5eA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gFAeA,GAAI,IACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACA,GACJ,AAAC,UAAU,EAAS,CAChB,GAAI,GAAO,MAAO,SAAW,SAAW,OAAS,MAAO,OAAS,SAAW,KAAO,MAAO,OAAS,SAAW,KAAO,CAAC,EACtH,AAAI,MAAO,SAAW,YAAc,OAAO,IACvC,OAAO,QAAS,CAAC,SAAS,EAAG,SAAU,EAAS,CAAE,EAAQ,EAAe,EAAM,EAAe,CAAO,CAAC,CAAC,CAAG,CAAC,EAE1G,AAAI,MAAO,KAAW,UAAY,MAAO,IAAO,SAAY,SAC7D,EAAQ,EAAe,EAAM,EAAe,GAAO,OAAO,CAAC,CAAC,EAG5D,EAAQ,EAAe,CAAI,CAAC,EAEhC,WAAwB,EAAS,EAAU,CACvC,MAAI,KAAY,GACZ,CAAI,MAAO,QAAO,QAAW,WACzB,OAAO,eAAe,EAAS,aAAc,CAAE,MAAO,EAAK,CAAC,EAG5D,EAAQ,WAAa,IAGtB,SAAU,EAAI,EAAG,CAAE,MAAO,GAAQ,GAAM,EAAW,EAAS,EAAI,CAAC,EAAI,CAAG,CACnF,CACJ,GACC,SAAU,EAAU,CACjB,GAAI,GAAgB,OAAO,gBACtB,CAAE,UAAW,CAAC,CAAE,WAAa,QAAS,SAAU,EAAG,EAAG,CAAE,EAAE,UAAY,CAAG,GAC1E,SAAU,EAAG,EAAG,CAAE,OAAS,KAAK,GAAG,AAAI,OAAO,UAAU,eAAe,KAAK,EAAG,CAAC,GAAG,GAAE,GAAK,EAAE,GAAI,EAEpG,GAAY,SAAU,EAAG,EAAG,CACxB,GAAI,MAAO,IAAM,YAAc,IAAM,KACjC,KAAM,IAAI,WAAU,uBAAyB,OAAO,CAAC,EAAI,+BAA+B,EAC5F,EAAc,EAAG,CAAC,EAClB,YAAc,CAAE,KAAK,YAAc,CAAG,CACtC,EAAE,UAAY,IAAM,KAAO,OAAO,OAAO,CAAC,EAAK,GAAG,UAAY,EAAE,UAAW,GAAI,GACnF,EAEA,GAAW,OAAO,QAAU,SAAU,EAAG,CACrC,OAAS,GAAG,EAAI,EAAG,EAAI,UAAU,OAAQ,EAAI,EAAG,IAAK,CACjD,EAAI,UAAU,GACd,OAAS,KAAK,GAAG,AAAI,OAAO,UAAU,eAAe,KAAK,EAAG,CAAC,GAAG,GAAE,GAAK,EAAE,GAC9E,CACA,MAAO,EACX,EAEA,GAAS,SAAU,EAAG,EAAG,CACrB,GAAI,GAAI,CAAC,EACT,OAAS,KAAK,GAAG,AAAI,OAAO,UAAU,eAAe,KAAK,EAAG,CAAC,GAAK,EAAE,QAAQ,CAAC,EAAI,GAC9E,GAAE,GAAK,EAAE,IACb,GAAI,GAAK,MAAQ,MAAO,QAAO,uBAA0B,WACrD,OAAS,GAAI,EAAG,EAAI,OAAO,sBAAsB,CAAC,EAAG,EAAI,EAAE,OAAQ,IAC/D,AAAI,EAAE,QAAQ,EAAE,EAAE,EAAI,GAAK,OAAO,UAAU,qBAAqB,KAAK,EAAG,EAAE,EAAE,GACzE,GAAE,EAAE,IAAM,EAAE,EAAE,KAE1B,MAAO,EACX,EAEA,GAAa,SAAU,EAAY,EAAQ,EAAK,EAAM,CAClD,GAAI,GAAI,UAAU,OAAQ,EAAI,EAAI,EAAI,EAAS,IAAS,KAAO,EAAO,OAAO,yBAAyB,EAAQ,CAAG,EAAI,EAAM,EAC3H,GAAI,MAAO,UAAY,UAAY,MAAO,SAAQ,UAAa,WAAY,EAAI,QAAQ,SAAS,EAAY,EAAQ,EAAK,CAAI,MACxH,QAAS,GAAI,EAAW,OAAS,EAAG,GAAK,EAAG,IAAK,AAAI,GAAI,EAAW,KAAI,GAAK,GAAI,EAAI,EAAE,CAAC,EAAI,EAAI,EAAI,EAAE,EAAQ,EAAK,CAAC,EAAI,EAAE,EAAQ,CAAG,IAAM,GAChJ,MAAO,GAAI,GAAK,GAAK,OAAO,eAAe,EAAQ,EAAK,CAAC,EAAG,CAChE,EAEA,GAAU,SAAU,EAAY,EAAW,CACvC,MAAO,UAAU,EAAQ,EAAK,CAAE,EAAU,EAAQ,EAAK,CAAU,CAAG,CACxE,EAEA,GAAa,SAAU,EAAa,EAAe,CAC/C,GAAI,MAAO,UAAY,UAAY,MAAO,SAAQ,UAAa,WAAY,MAAO,SAAQ,SAAS,EAAa,CAAa,CACjI,EAEA,GAAY,SAAU,EAAS,EAAY,EAAG,EAAW,CACrD,WAAe,EAAO,CAAE,MAAO,aAAiB,GAAI,EAAQ,GAAI,GAAE,SAAU,EAAS,CAAE,EAAQ,CAAK,CAAG,CAAC,CAAG,CAC3G,MAAO,IAAK,IAAM,GAAI,UAAU,SAAU,EAAS,EAAQ,CACvD,WAAmB,EAAO,CAAE,GAAI,CAAE,EAAK,EAAU,KAAK,CAAK,CAAC,CAAG,OAAS,EAAP,CAAY,EAAO,CAAC,CAAG,CAAE,CAC1F,WAAkB,EAAO,CAAE,GAAI,CAAE,EAAK,EAAU,MAAS,CAAK,CAAC,CAAG,OAAS,EAAP,CAAY,EAAO,CAAC,CAAG,CAAE,CAC7F,WAAc,EAAQ,CAAE,EAAO,KAAO,EAAQ,EAAO,KAAK,EAAI,EAAM,EAAO,KAAK,EAAE,KAAK,EAAW,CAAQ,CAAG,CAC7G,EAAM,GAAY,EAAU,MAAM,EAAS,GAAc,CAAC,CAAC,GAAG,KAAK,CAAC,CACxE,CAAC,CACL,EAEA,GAAc,SAAU,EAAS,EAAM,CACnC,GAAI,GAAI,CAAE,MAAO,EAAG,KAAM,UAAW,CAAE,GAAI,EAAE,GAAK,EAAG,KAAM,GAAE,GAAI,MAAO,GAAE,EAAI,EAAG,KAAM,CAAC,EAAG,IAAK,CAAC,CAAE,EAAG,EAAG,EAAG,EAAG,EAC/G,MAAO,GAAI,CAAE,KAAM,EAAK,CAAC,EAAG,MAAS,EAAK,CAAC,EAAG,OAAU,EAAK,CAAC,CAAE,EAAG,MAAO,SAAW,YAAe,GAAE,OAAO,UAAY,UAAW,CAAE,MAAO,KAAM,GAAI,EACvJ,WAAc,EAAG,CAAE,MAAO,UAAU,EAAG,CAAE,MAAO,GAAK,CAAC,EAAG,CAAC,CAAC,CAAG,CAAG,CACjE,WAAc,EAAI,CACd,GAAI,EAAG,KAAM,IAAI,WAAU,iCAAiC,EAC5D,KAAO,GAAG,GAAI,CACV,GAAI,EAAI,EAAG,GAAM,GAAI,EAAG,GAAK,EAAI,EAAE,OAAY,EAAG,GAAK,EAAE,OAAc,IAAI,EAAE,SAAc,EAAE,KAAK,CAAC,EAAG,GAAK,EAAE,OAAS,CAAE,GAAI,EAAE,KAAK,EAAG,EAAG,EAAE,GAAG,KAAM,MAAO,GAE3J,OADI,EAAI,EAAG,GAAG,GAAK,CAAC,EAAG,GAAK,EAAG,EAAE,KAAK,GAC9B,EAAG,QACF,OAAQ,GAAG,EAAI,EAAI,UACnB,GAAG,SAAE,QAAgB,CAAE,MAAO,EAAG,GAAI,KAAM,EAAM,MACjD,GAAG,EAAE,QAAS,EAAI,EAAG,GAAI,EAAK,CAAC,CAAC,EAAG,aACnC,GAAG,EAAK,EAAE,IAAI,IAAI,EAAG,EAAE,KAAK,IAAI,EAAG,iBAEpC,GAAM,EAAI,EAAE,KAAM,IAAI,EAAE,OAAS,GAAK,EAAE,EAAE,OAAS,KAAQ,GAAG,KAAO,GAAK,EAAG,KAAO,GAAI,CAAE,EAAI,EAAG,QAAU,CAC3G,GAAI,EAAG,KAAO,GAAM,EAAC,GAAM,EAAG,GAAK,EAAE,IAAM,EAAG,GAAK,EAAE,IAAM,CAAE,EAAE,MAAQ,EAAG,GAAI,KAAO,CACrF,GAAI,EAAG,KAAO,GAAK,EAAE,MAAQ,EAAE,GAAI,CAAE,EAAE,MAAQ,EAAE,GAAI,EAAI,EAAI,KAAO,CACpE,GAAI,GAAK,EAAE,MAAQ,EAAE,GAAI,CAAE,EAAE,MAAQ,EAAE,GAAI,EAAE,IAAI,KAAK,CAAE,EAAG,KAAO,CAClE,AAAI,EAAE,IAAI,EAAE,IAAI,IAAI,EACpB,EAAE,KAAK,IAAI,EAAG,SAEtB,EAAK,EAAK,KAAK,EAAS,CAAC,CAC7B,OAAS,EAAP,CAAY,EAAK,CAAC,EAAG,CAAC,EAAG,EAAI,CAAG,QAAE,CAAU,EAAI,EAAI,CAAG,CACzD,GAAI,EAAG,GAAK,EAAG,KAAM,GAAG,GAAI,MAAO,CAAE,MAAO,EAAG,GAAK,EAAG,GAAK,OAAQ,KAAM,EAAK,CACnF,CACJ,EAEA,GAAe,SAAS,EAAG,EAAG,CAC1B,OAAS,KAAK,GAAG,AAAI,IAAM,WAAa,CAAC,OAAO,UAAU,eAAe,KAAK,EAAG,CAAC,GAAG,GAAgB,EAAG,EAAG,CAAC,CAChH,EAEA,GAAkB,OAAO,OAAU,SAAS,EAAG,EAAG,EAAG,EAAI,CACrD,AAAI,IAAO,QAAW,GAAK,GAC3B,OAAO,eAAe,EAAG,EAAI,CAAE,WAAY,GAAM,IAAK,UAAW,CAAE,MAAO,GAAE,EAAI,CAAE,CAAC,CACvF,EAAM,SAAS,EAAG,EAAG,EAAG,EAAI,CACxB,AAAI,IAAO,QAAW,GAAK,GAC3B,EAAE,GAAM,EAAE,EACd,EAEA,GAAW,SAAU,EAAG,CACpB,GAAI,GAAI,MAAO,SAAW,YAAc,OAAO,SAAU,EAAI,GAAK,EAAE,GAAI,EAAI,EAC5E,GAAI,EAAG,MAAO,GAAE,KAAK,CAAC,EACtB,GAAI,GAAK,MAAO,GAAE,QAAW,SAAU,MAAO,CAC1C,KAAM,UAAY,CACd,MAAI,IAAK,GAAK,EAAE,QAAQ,GAAI,QACrB,CAAE,MAAO,GAAK,EAAE,KAAM,KAAM,CAAC,CAAE,CAC1C,CACJ,EACA,KAAM,IAAI,WAAU,EAAI,0BAA4B,iCAAiC,CACzF,EAEA,GAAS,SAAU,EAAG,EAAG,CACrB,GAAI,GAAI,MAAO,SAAW,YAAc,EAAE,OAAO,UACjD,GAAI,CAAC,EAAG,MAAO,GACf,GAAI,GAAI,EAAE,KAAK,CAAC,EAAG,EAAG,EAAK,CAAC,EAAG,EAC/B,GAAI,CACA,KAAQ,KAAM,QAAU,KAAM,IAAM,CAAE,GAAI,EAAE,KAAK,GAAG,MAAM,EAAG,KAAK,EAAE,KAAK,CAC7E,OACO,EAAP,CAAgB,EAAI,CAAE,MAAO,CAAM,CAAG,QACtC,CACI,GAAI,CACA,AAAI,GAAK,CAAC,EAAE,MAAS,GAAI,EAAE,SAAY,EAAE,KAAK,CAAC,CACnD,QACA,CAAU,GAAI,EAAG,KAAM,GAAE,KAAO,CACpC,CACA,MAAO,EACX,EAGA,GAAW,UAAY,CACnB,OAAS,GAAK,CAAC,EAAG,EAAI,EAAG,EAAI,UAAU,OAAQ,IAC3C,EAAK,EAAG,OAAO,GAAO,UAAU,EAAE,CAAC,EACvC,MAAO,EACX,EAGA,GAAiB,UAAY,CACzB,OAAS,GAAI,EAAG,EAAI,EAAG,EAAK,UAAU,OAAQ,EAAI,EAAI,IAAK,GAAK,UAAU,GAAG,OAC7E,OAAS,GAAI,MAAM,CAAC,EAAG,EAAI,EAAG,EAAI,EAAG,EAAI,EAAI,IACzC,OAAS,GAAI,UAAU,GAAI,EAAI,EAAG,EAAK,EAAE,OAAQ,EAAI,EAAI,IAAK,IAC1D,EAAE,GAAK,EAAE,GACjB,MAAO,EACX,EAEA,GAAgB,SAAU,EAAI,EAAM,EAAM,CACtC,GAAI,GAAQ,UAAU,SAAW,EAAG,OAAS,GAAI,EAAG,EAAI,EAAK,OAAQ,EAAI,EAAI,EAAG,IAC5E,AAAI,IAAM,CAAE,KAAK,MACR,IAAI,GAAK,MAAM,UAAU,MAAM,KAAK,EAAM,EAAG,CAAC,GACnD,EAAG,GAAK,EAAK,IAGrB,MAAO,GAAG,OAAO,GAAM,MAAM,UAAU,MAAM,KAAK,CAAI,CAAC,CAC3D,EAEA,GAAU,SAAU,EAAG,CACnB,MAAO,gBAAgB,IAAW,MAAK,EAAI,EAAG,MAAQ,GAAI,IAAQ,CAAC,CACvE,EAEA,GAAmB,SAAU,EAAS,EAAY,EAAW,CACzD,GAAI,CAAC,OAAO,cAAe,KAAM,IAAI,WAAU,sCAAsC,EACrF,GAAI,GAAI,EAAU,MAAM,EAAS,GAAc,CAAC,CAAC,EAAG,EAAG,EAAI,CAAC,EAC5D,MAAO,GAAI,CAAC,EAAG,EAAK,MAAM,EAAG,EAAK,OAAO,EAAG,EAAK,QAAQ,EAAG,EAAE,OAAO,eAAiB,UAAY,CAAE,MAAO,KAAM,EAAG,EACpH,WAAc,EAAG,CAAE,AAAI,EAAE,IAAI,GAAE,GAAK,SAAU,EAAG,CAAE,MAAO,IAAI,SAAQ,SAAU,EAAG,EAAG,CAAE,EAAE,KAAK,CAAC,EAAG,EAAG,EAAG,CAAC,CAAC,EAAI,GAAK,EAAO,EAAG,CAAC,CAAG,CAAC,CAAG,EAAG,CACzI,WAAgB,EAAG,EAAG,CAAE,GAAI,CAAE,EAAK,EAAE,GAAG,CAAC,CAAC,CAAG,OAAS,EAAP,CAAY,EAAO,EAAE,GAAG,GAAI,CAAC,CAAG,CAAE,CACjF,WAAc,EAAG,CAAE,EAAE,gBAAiB,IAAU,QAAQ,QAAQ,EAAE,MAAM,CAAC,EAAE,KAAK,EAAS,CAAM,EAAI,EAAO,EAAE,GAAG,GAAI,CAAC,CAAI,CACxH,WAAiB,EAAO,CAAE,EAAO,OAAQ,CAAK,CAAG,CACjD,WAAgB,EAAO,CAAE,EAAO,QAAS,CAAK,CAAG,CACjD,WAAgB,EAAG,EAAG,CAAE,AAAI,EAAE,CAAC,EAAG,EAAE,MAAM,EAAG,EAAE,QAAQ,EAAO,EAAE,GAAG,GAAI,EAAE,GAAG,EAAE,CAAG,CACrF,EAEA,GAAmB,SAAU,EAAG,CAC5B,GAAI,GAAG,EACP,MAAO,GAAI,CAAC,EAAG,EAAK,MAAM,EAAG,EAAK,QAAS,SAAU,EAAG,CAAE,KAAM,EAAG,CAAC,EAAG,EAAK,QAAQ,EAAG,EAAE,OAAO,UAAY,UAAY,CAAE,MAAO,KAAM,EAAG,EAC1I,WAAc,EAAG,EAAG,CAAE,EAAE,GAAK,EAAE,GAAK,SAAU,EAAG,CAAE,MAAQ,GAAI,CAAC,GAAK,CAAE,MAAO,GAAQ,EAAE,GAAG,CAAC,CAAC,EAAG,KAAM,IAAM,QAAS,EAAI,EAAI,EAAE,CAAC,EAAI,CAAG,EAAI,CAAG,CAClJ,EAEA,GAAgB,SAAU,EAAG,CACzB,GAAI,CAAC,OAAO,cAAe,KAAM,IAAI,WAAU,sCAAsC,EACrF,GAAI,GAAI,EAAE,OAAO,eAAgB,EACjC,MAAO,GAAI,EAAE,KAAK,CAAC,EAAK,GAAI,MAAO,KAAa,WAAa,GAAS,CAAC,EAAI,EAAE,OAAO,UAAU,EAAG,EAAI,CAAC,EAAG,EAAK,MAAM,EAAG,EAAK,OAAO,EAAG,EAAK,QAAQ,EAAG,EAAE,OAAO,eAAiB,UAAY,CAAE,MAAO,KAAM,EAAG,GAC9M,WAAc,EAAG,CAAE,EAAE,GAAK,EAAE,IAAM,SAAU,EAAG,CAAE,MAAO,IAAI,SAAQ,SAAU,EAAS,EAAQ,CAAE,EAAI,EAAE,GAAG,CAAC,EAAG,EAAO,EAAS,EAAQ,EAAE,KAAM,EAAE,KAAK,CAAG,CAAC,CAAG,CAAG,CAC/J,WAAgB,EAAS,EAAQ,EAAG,EAAG,CAAE,QAAQ,QAAQ,CAAC,EAAE,KAAK,SAAS,EAAG,CAAE,EAAQ,CAAE,MAAO,EAAG,KAAM,CAAE,CAAC,CAAG,EAAG,CAAM,CAAG,CAC/H,EAEA,GAAuB,SAAU,EAAQ,EAAK,CAC1C,MAAI,QAAO,eAAkB,OAAO,eAAe,EAAQ,MAAO,CAAE,MAAO,CAAI,CAAC,EAAY,EAAO,IAAM,EAClG,CACX,EAEA,GAAI,GAAqB,OAAO,OAAU,SAAS,EAAG,EAAG,CACrD,OAAO,eAAe,EAAG,UAAW,CAAE,WAAY,GAAM,MAAO,CAAE,CAAC,CACtE,EAAK,SAAS,EAAG,EAAG,CAChB,EAAE,QAAa,CACnB,EAEA,GAAe,SAAU,EAAK,CAC1B,GAAI,GAAO,EAAI,WAAY,MAAO,GAClC,GAAI,GAAS,CAAC,EACd,GAAI,GAAO,KAAM,OAAS,KAAK,GAAK,AAAI,IAAM,WAAa,OAAO,UAAU,eAAe,KAAK,EAAK,CAAC,GAAG,GAAgB,EAAQ,EAAK,CAAC,EACvI,SAAmB,EAAQ,CAAG,EACvB,CACX,EAEA,GAAkB,SAAU,EAAK,CAC7B,MAAQ,IAAO,EAAI,WAAc,EAAM,CAAE,QAAW,CAAI,CAC5D,EAEA,GAAyB,SAAU,EAAU,EAAO,EAAM,EAAG,CACzD,GAAI,IAAS,KAAO,CAAC,EAAG,KAAM,IAAI,WAAU,+CAA+C,EAC3F,GAAI,MAAO,IAAU,WAAa,IAAa,GAAS,CAAC,EAAI,CAAC,EAAM,IAAI,CAAQ,EAAG,KAAM,IAAI,WAAU,0EAA0E,EACjL,MAAO,KAAS,IAAM,EAAI,IAAS,IAAM,EAAE,KAAK,CAAQ,EAAI,EAAI,EAAE,MAAQ,EAAM,IAAI,CAAQ,CAChG,EAEA,GAAyB,SAAU,EAAU,EAAO,EAAO,EAAM,EAAG,CAChE,GAAI,IAAS,IAAK,KAAM,IAAI,WAAU,gCAAgC,EACtE,GAAI,IAAS,KAAO,CAAC,EAAG,KAAM,IAAI,WAAU,+CAA+C,EAC3F,GAAI,MAAO,IAAU,WAAa,IAAa,GAAS,CAAC,EAAI,CAAC,EAAM,IAAI,CAAQ,EAAG,KAAM,IAAI,WAAU,yEAAyE,EAChL,MAAQ,KAAS,IAAM,EAAE,KAAK,EAAU,CAAK,EAAI,EAAI,EAAE,MAAQ,EAAQ,EAAM,IAAI,EAAU,CAAK,EAAI,CACxG,EAEA,EAAS,YAAa,EAAS,EAC/B,EAAS,WAAY,EAAQ,EAC7B,EAAS,SAAU,EAAM,EACzB,EAAS,aAAc,EAAU,EACjC,EAAS,UAAW,EAAO,EAC3B,EAAS,aAAc,EAAU,EACjC,EAAS,YAAa,EAAS,EAC/B,EAAS,cAAe,EAAW,EACnC,EAAS,eAAgB,EAAY,EACrC,EAAS,kBAAmB,EAAe,EAC3C,EAAS,WAAY,EAAQ,EAC7B,EAAS,SAAU,EAAM,EACzB,EAAS,WAAY,EAAQ,EAC7B,EAAS,iBAAkB,EAAc,EACzC,EAAS,gBAAiB,EAAa,EACvC,EAAS,UAAW,EAAO,EAC3B,EAAS,mBAAoB,EAAgB,EAC7C,EAAS,mBAAoB,EAAgB,EAC7C,EAAS,gBAAiB,EAAa,EACvC,EAAS,uBAAwB,EAAoB,EACrD,EAAS,eAAgB,EAAY,EACrC,EAAS,kBAAmB,EAAe,EAC3C,EAAS,yBAA0B,EAAsB,EACzD,EAAS,yBAA0B,EAAsB,CAC7D,CAAC,ICjTD;AAAA;AAAA;AAAA;AAAA;AAAA,GAMA,AAAC,UAA0C,EAAM,EAAS,CACzD,AAAG,MAAO,KAAY,UAAY,MAAO,KAAW,SACnD,GAAO,QAAU,EAAQ,EACrB,AAAG,MAAO,SAAW,YAAc,OAAO,IAC9C,OAAO,CAAC,EAAG,CAAO,EACd,AAAG,MAAO,KAAY,SAC1B,GAAQ,YAAiB,EAAQ,EAEjC,EAAK,YAAiB,EAAQ,CAChC,GAAG,GAAM,UAAW,CACpB,MAAiB,WAAW,CAClB,GAAI,GAAuB,CAE/B,IACC,SAAS,EAAyB,EAAqB,EAAqB,CAEnF,aAGA,EAAoB,EAAE,EAAqB,CACzC,QAAW,UAAW,CAAE,MAAqB,GAAW,CAC1D,CAAC,EAGD,GAAI,GAAe,EAAoB,GAAG,EACtC,EAAoC,EAAoB,EAAE,CAAY,EAEtE,EAAS,EAAoB,GAAG,EAChC,EAA8B,EAAoB,EAAE,CAAM,EAE1D,EAAa,EAAoB,GAAG,EACpC,EAA8B,EAAoB,EAAE,CAAU,EAOlE,WAAiB,EAAM,CACrB,GAAI,CACF,MAAO,UAAS,YAAY,CAAI,CAClC,OAAS,EAAP,CACA,MAAO,EACT,CACF,CAUA,GAAI,GAAqB,SAA4B,EAAQ,CAC3D,GAAI,GAAe,EAAe,EAAE,CAAM,EAC1C,SAAQ,KAAK,EACN,CACT,EAEiC,EAAe,EAOhD,WAA2B,EAAO,CAChC,GAAI,GAAQ,SAAS,gBAAgB,aAAa,KAAK,IAAM,MACzD,EAAc,SAAS,cAAc,UAAU,EAEnD,EAAY,MAAM,SAAW,OAE7B,EAAY,MAAM,OAAS,IAC3B,EAAY,MAAM,QAAU,IAC5B,EAAY,MAAM,OAAS,IAE3B,EAAY,MAAM,SAAW,WAC7B,EAAY,MAAM,EAAQ,QAAU,QAAU,UAE9C,GAAI,GAAY,OAAO,aAAe,SAAS,gBAAgB,UAC/D,SAAY,MAAM,IAAM,GAAG,OAAO,EAAW,IAAI,EACjD,EAAY,aAAa,WAAY,EAAE,EACvC,EAAY,MAAQ,EACb,CACT,CAYA,GAAI,GAAiB,SAAwB,EAAO,EAAS,CAC3D,GAAI,GAAc,EAAkB,CAAK,EACzC,EAAQ,UAAU,YAAY,CAAW,EACzC,GAAI,GAAe,EAAe,EAAE,CAAW,EAC/C,SAAQ,MAAM,EACd,EAAY,OAAO,EACZ,CACT,EASI,EAAsB,SAA6B,EAAQ,CAC7D,GAAI,GAAU,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAChF,UAAW,SAAS,IACtB,EACI,EAAe,GAEnB,MAAI,OAAO,IAAW,SACpB,EAAe,EAAe,EAAQ,CAAO,EACxC,AAAI,YAAkB,mBAAoB,CAAC,CAAC,OAAQ,SAAU,MAAO,MAAO,UAAU,EAAE,SAAS,GAAW,KAA4B,OAAS,EAAO,IAAI,EAEjK,EAAe,EAAe,EAAO,MAAO,CAAO,EAEnD,GAAe,EAAe,EAAE,CAAM,EACtC,EAAQ,MAAM,GAGT,CACT,EAEiC,EAAgB,EAEjD,WAAiB,EAAK,CAA6B,MAAI,OAAO,SAAW,YAAc,MAAO,QAAO,UAAa,SAAY,EAAU,SAAiB,EAAK,CAAE,MAAO,OAAO,EAAK,EAAY,EAAU,SAAiB,EAAK,CAAE,MAAO,IAAO,MAAO,SAAW,YAAc,EAAI,cAAgB,QAAU,IAAQ,OAAO,UAAY,SAAW,MAAO,EAAK,EAAY,EAAQ,CAAG,CAAG,CAUzX,GAAI,IAAyB,UAAkC,CAC7D,GAAI,GAAU,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAAC,EAE/E,EAAkB,EAAQ,OAC1B,EAAS,IAAoB,OAAS,OAAS,EAC/C,EAAY,EAAQ,UACpB,EAAS,EAAQ,OACjB,GAAO,EAAQ,KAEnB,GAAI,IAAW,QAAU,IAAW,MAClC,KAAM,IAAI,OAAM,oDAAoD,EAItE,GAAI,IAAW,OACb,GAAI,GAAU,EAAQ,CAAM,IAAM,UAAY,EAAO,WAAa,EAAG,CACnE,GAAI,IAAW,QAAU,EAAO,aAAa,UAAU,EACrD,KAAM,IAAI,OAAM,mFAAmF,EAGrG,GAAI,IAAW,OAAU,GAAO,aAAa,UAAU,GAAK,EAAO,aAAa,UAAU,GACxF,KAAM,IAAI,OAAM,uGAAwG,CAE5H,KACE,MAAM,IAAI,OAAM,6CAA6C,EAKjE,GAAI,GACF,MAAO,GAAa,GAAM,CACxB,UAAW,CACb,CAAC,EAIH,GAAI,EACF,MAAO,KAAW,MAAQ,EAAY,CAAM,EAAI,EAAa,EAAQ,CACnE,UAAW,CACb,CAAC,CAEL,EAEiC,GAAmB,GAEpD,YAA0B,EAAK,CAA6B,MAAI,OAAO,SAAW,YAAc,MAAO,QAAO,UAAa,SAAY,GAAmB,SAAiB,EAAK,CAAE,MAAO,OAAO,EAAK,EAAY,GAAmB,SAAiB,EAAK,CAAE,MAAO,IAAO,MAAO,SAAW,YAAc,EAAI,cAAgB,QAAU,IAAQ,OAAO,UAAY,SAAW,MAAO,EAAK,EAAY,GAAiB,CAAG,CAAG,CAE7Z,YAAyB,EAAU,EAAa,CAAE,GAAI,CAAE,aAAoB,IAAgB,KAAM,IAAI,WAAU,mCAAmC,CAAK,CAExJ,YAA2B,EAAQ,EAAO,CAAE,OAAS,GAAI,EAAG,EAAI,EAAM,OAAQ,IAAK,CAAE,GAAI,GAAa,EAAM,GAAI,EAAW,WAAa,EAAW,YAAc,GAAO,EAAW,aAAe,GAAU,SAAW,IAAY,GAAW,SAAW,IAAM,OAAO,eAAe,EAAQ,EAAW,IAAK,CAAU,CAAG,CAAE,CAE5T,YAAsB,EAAa,EAAY,EAAa,CAAE,MAAI,IAAY,GAAkB,EAAY,UAAW,CAAU,EAAO,GAAa,GAAkB,EAAa,CAAW,EAAU,CAAa,CAEtN,YAAmB,EAAU,EAAY,CAAE,GAAI,MAAO,IAAe,YAAc,IAAe,KAAQ,KAAM,IAAI,WAAU,oDAAoD,EAAK,EAAS,UAAY,OAAO,OAAO,GAAc,EAAW,UAAW,CAAE,YAAa,CAAE,MAAO,EAAU,SAAU,GAAM,aAAc,EAAK,CAAE,CAAC,EAAO,GAAY,GAAgB,EAAU,CAAU,CAAG,CAEhY,YAAyB,EAAG,EAAG,CAAE,UAAkB,OAAO,gBAAkB,SAAyB,EAAG,EAAG,CAAE,SAAE,UAAY,EAAU,CAAG,EAAU,GAAgB,EAAG,CAAC,CAAG,CAEzK,YAAsB,EAAS,CAAE,GAAI,GAA4B,GAA0B,EAAG,MAAO,WAAgC,CAAE,GAAI,GAAQ,GAAgB,CAAO,EAAG,EAAQ,GAAI,EAA2B,CAAE,GAAI,GAAY,GAAgB,IAAI,EAAE,YAAa,EAAS,QAAQ,UAAU,EAAO,UAAW,CAAS,CAAG,KAAS,GAAS,EAAM,MAAM,KAAM,SAAS,EAAK,MAAO,IAA2B,KAAM,CAAM,CAAG,CAAG,CAExa,YAAoC,EAAM,EAAM,CAAE,MAAI,IAAS,IAAiB,CAAI,IAAM,UAAY,MAAO,IAAS,YAAsB,EAAe,GAAuB,CAAI,CAAG,CAEzL,YAAgC,EAAM,CAAE,GAAI,IAAS,OAAU,KAAM,IAAI,gBAAe,2DAA2D,EAAK,MAAO,EAAM,CAErK,aAAqC,CAA0E,GAApE,MAAO,UAAY,aAAe,CAAC,QAAQ,WAA6B,QAAQ,UAAU,KAAM,MAAO,GAAO,GAAI,MAAO,QAAU,WAAY,MAAO,GAAM,GAAI,CAAE,YAAK,UAAU,SAAS,KAAK,QAAQ,UAAU,KAAM,CAAC,EAAG,UAAY,CAAC,CAAC,CAAC,EAAU,EAAM,OAAS,EAAP,CAAY,MAAO,EAAO,CAAE,CAEnU,YAAyB,EAAG,CAAE,UAAkB,OAAO,eAAiB,OAAO,eAAiB,SAAyB,EAAG,CAAE,MAAO,GAAE,WAAa,OAAO,eAAe,CAAC,CAAG,EAAU,GAAgB,CAAC,CAAG,CAa5M,YAA2B,EAAQ,EAAS,CAC1C,GAAI,GAAY,kBAAkB,OAAO,CAAM,EAE/C,GAAI,EAAC,EAAQ,aAAa,CAAS,EAInC,MAAO,GAAQ,aAAa,CAAS,CACvC,CAOA,GAAI,IAAyB,SAAU,EAAU,CAC/C,GAAU,EAAW,CAAQ,EAE7B,GAAI,GAAS,GAAa,CAAS,EAMnC,WAAmB,EAAS,EAAS,CACnC,GAAI,GAEJ,UAAgB,KAAM,CAAS,EAE/B,EAAQ,EAAO,KAAK,IAAI,EAExB,EAAM,eAAe,CAAO,EAE5B,EAAM,YAAY,CAAO,EAElB,CACT,CAQA,UAAa,EAAW,CAAC,CACvB,IAAK,iBACL,MAAO,UAA0B,CAC/B,GAAI,GAAU,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAAC,EACnF,KAAK,OAAS,MAAO,GAAQ,QAAW,WAAa,EAAQ,OAAS,KAAK,cAC3E,KAAK,OAAS,MAAO,GAAQ,QAAW,WAAa,EAAQ,OAAS,KAAK,cAC3E,KAAK,KAAO,MAAO,GAAQ,MAAS,WAAa,EAAQ,KAAO,KAAK,YACrE,KAAK,UAAY,GAAiB,EAAQ,SAAS,IAAM,SAAW,EAAQ,UAAY,SAAS,IACnG,CAMF,EAAG,CACD,IAAK,cACL,MAAO,SAAqB,EAAS,CACnC,GAAI,GAAS,KAEb,KAAK,SAAW,EAAe,EAAE,EAAS,QAAS,SAAU,GAAG,CAC9D,MAAO,GAAO,QAAQ,EAAC,CACzB,CAAC,CACH,CAMF,EAAG,CACD,IAAK,UACL,MAAO,SAAiB,EAAG,CACzB,GAAI,GAAU,EAAE,gBAAkB,EAAE,cAChC,GAAS,KAAK,OAAO,CAAO,GAAK,OACjC,GAAO,GAAgB,CACzB,OAAQ,GACR,UAAW,KAAK,UAChB,OAAQ,KAAK,OAAO,CAAO,EAC3B,KAAM,KAAK,KAAK,CAAO,CACzB,CAAC,EAED,KAAK,KAAK,GAAO,UAAY,QAAS,CACpC,OAAQ,GACR,KAAM,GACN,QAAS,EACT,eAAgB,UAA0B,CACxC,AAAI,GACF,EAAQ,MAAM,EAGhB,OAAO,aAAa,EAAE,gBAAgB,CACxC,CACF,CAAC,CACH,CAMF,EAAG,CACD,IAAK,gBACL,MAAO,SAAuB,EAAS,CACrC,MAAO,IAAkB,SAAU,CAAO,CAC5C,CAMF,EAAG,CACD,IAAK,gBACL,MAAO,SAAuB,EAAS,CACrC,GAAI,GAAW,GAAkB,SAAU,CAAO,EAElD,GAAI,EACF,MAAO,UAAS,cAAc,CAAQ,CAE1C,CAQF,EAAG,CACD,IAAK,cAML,MAAO,SAAqB,EAAS,CACnC,MAAO,IAAkB,OAAQ,CAAO,CAC1C,CAKF,EAAG,CACD,IAAK,UACL,MAAO,UAAmB,CACxB,KAAK,SAAS,QAAQ,CACxB,CACF,CAAC,EAAG,CAAC,CACH,IAAK,OACL,MAAO,SAAc,EAAQ,CAC3B,GAAI,GAAU,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAChF,UAAW,SAAS,IACtB,EACA,MAAO,GAAa,EAAQ,CAAO,CACrC,CAOF,EAAG,CACD,IAAK,MACL,MAAO,SAAa,EAAQ,CAC1B,MAAO,GAAY,CAAM,CAC3B,CAOF,EAAG,CACD,IAAK,cACL,MAAO,UAAuB,CAC5B,GAAI,GAAS,UAAU,OAAS,GAAK,UAAU,KAAO,OAAY,UAAU,GAAK,CAAC,OAAQ,KAAK,EAC3F,EAAU,MAAO,IAAW,SAAW,CAAC,CAAM,EAAI,EAClD,GAAU,CAAC,CAAC,SAAS,sBACzB,SAAQ,QAAQ,SAAU,GAAQ,CAChC,GAAU,IAAW,CAAC,CAAC,SAAS,sBAAsB,EAAM,CAC9D,CAAC,EACM,EACT,CACF,CAAC,CAAC,EAEK,CACT,EAAG,EAAqB,CAAE,EAEO,GAAa,EAExC,EAEA,IACC,SAAS,EAAQ,CAExB,GAAI,GAAqB,EAKzB,GAAI,MAAO,UAAY,aAAe,CAAC,QAAQ,UAAU,QAAS,CAC9D,GAAI,GAAQ,QAAQ,UAEpB,EAAM,QAAU,EAAM,iBACN,EAAM,oBACN,EAAM,mBACN,EAAM,kBACN,EAAM,qBAC1B,CASA,WAAkB,EAAS,EAAU,CACjC,KAAO,GAAW,EAAQ,WAAa,GAAoB,CACvD,GAAI,MAAO,GAAQ,SAAY,YAC3B,EAAQ,QAAQ,CAAQ,EAC1B,MAAO,GAET,EAAU,EAAQ,UACtB,CACJ,CAEA,EAAO,QAAU,CAGX,EAEA,IACC,SAAS,EAAQ,EAA0B,EAAqB,CAEvE,GAAI,GAAU,EAAoB,GAAG,EAYrC,WAAmB,EAAS,EAAU,EAAM,EAAU,EAAY,CAC9D,GAAI,GAAa,EAAS,MAAM,KAAM,SAAS,EAE/C,SAAQ,iBAAiB,EAAM,EAAY,CAAU,EAE9C,CACH,QAAS,UAAW,CAChB,EAAQ,oBAAoB,EAAM,EAAY,CAAU,CAC5D,CACJ,CACJ,CAYA,WAAkB,EAAU,EAAU,EAAM,EAAU,EAAY,CAE9D,MAAI,OAAO,GAAS,kBAAqB,WAC9B,EAAU,MAAM,KAAM,SAAS,EAItC,MAAO,IAAS,WAGT,EAAU,KAAK,KAAM,QAAQ,EAAE,MAAM,KAAM,SAAS,EAI3D,OAAO,IAAa,UACpB,GAAW,SAAS,iBAAiB,CAAQ,GAI1C,MAAM,UAAU,IAAI,KAAK,EAAU,SAAU,EAAS,CACzD,MAAO,GAAU,EAAS,EAAU,EAAM,EAAU,CAAU,CAClE,CAAC,EACL,CAWA,WAAkB,EAAS,EAAU,EAAM,EAAU,CACjD,MAAO,UAAS,EAAG,CACf,EAAE,eAAiB,EAAQ,EAAE,OAAQ,CAAQ,EAEzC,EAAE,gBACF,EAAS,KAAK,EAAS,CAAC,CAEhC,CACJ,CAEA,EAAO,QAAU,CAGX,EAEA,IACC,SAAS,EAAyB,EAAS,CAQlD,EAAQ,KAAO,SAAS,EAAO,CAC3B,MAAO,KAAU,QACV,YAAiB,cACjB,EAAM,WAAa,CAC9B,EAQA,EAAQ,SAAW,SAAS,EAAO,CAC/B,GAAI,GAAO,OAAO,UAAU,SAAS,KAAK,CAAK,EAE/C,MAAO,KAAU,QACT,KAAS,qBAAuB,IAAS,4BACzC,UAAY,IACZ,GAAM,SAAW,GAAK,EAAQ,KAAK,EAAM,EAAE,EACvD,EAQA,EAAQ,OAAS,SAAS,EAAO,CAC7B,MAAO,OAAO,IAAU,UACjB,YAAiB,OAC5B,EAQA,EAAQ,GAAK,SAAS,EAAO,CACzB,GAAI,GAAO,OAAO,UAAU,SAAS,KAAK,CAAK,EAE/C,MAAO,KAAS,mBACpB,CAGM,EAEA,IACC,SAAS,EAAQ,EAA0B,EAAqB,CAEvE,GAAI,GAAK,EAAoB,GAAG,EAC5B,EAAW,EAAoB,GAAG,EAWtC,WAAgB,EAAQ,EAAM,EAAU,CACpC,GAAI,CAAC,GAAU,CAAC,GAAQ,CAAC,EACrB,KAAM,IAAI,OAAM,4BAA4B,EAGhD,GAAI,CAAC,EAAG,OAAO,CAAI,EACf,KAAM,IAAI,WAAU,kCAAkC,EAG1D,GAAI,CAAC,EAAG,GAAG,CAAQ,EACf,KAAM,IAAI,WAAU,mCAAmC,EAG3D,GAAI,EAAG,KAAK,CAAM,EACd,MAAO,GAAW,EAAQ,EAAM,CAAQ,EAEvC,GAAI,EAAG,SAAS,CAAM,EACvB,MAAO,GAAe,EAAQ,EAAM,CAAQ,EAE3C,GAAI,EAAG,OAAO,CAAM,EACrB,MAAO,GAAe,EAAQ,EAAM,CAAQ,EAG5C,KAAM,IAAI,WAAU,2EAA2E,CAEvG,CAWA,WAAoB,EAAM,EAAM,EAAU,CACtC,SAAK,iBAAiB,EAAM,CAAQ,EAE7B,CACH,QAAS,UAAW,CAChB,EAAK,oBAAoB,EAAM,CAAQ,CAC3C,CACJ,CACJ,CAWA,WAAwB,EAAU,EAAM,EAAU,CAC9C,aAAM,UAAU,QAAQ,KAAK,EAAU,SAAS,EAAM,CAClD,EAAK,iBAAiB,EAAM,CAAQ,CACxC,CAAC,EAEM,CACH,QAAS,UAAW,CAChB,MAAM,UAAU,QAAQ,KAAK,EAAU,SAAS,EAAM,CAClD,EAAK,oBAAoB,EAAM,CAAQ,CAC3C,CAAC,CACL,CACJ,CACJ,CAWA,WAAwB,EAAU,EAAM,EAAU,CAC9C,MAAO,GAAS,SAAS,KAAM,EAAU,EAAM,CAAQ,CAC3D,CAEA,EAAO,QAAU,CAGX,EAEA,IACC,SAAS,EAAQ,CAExB,WAAgB,EAAS,CACrB,GAAI,GAEJ,GAAI,EAAQ,WAAa,SACrB,EAAQ,MAAM,EAEd,EAAe,EAAQ,cAElB,EAAQ,WAAa,SAAW,EAAQ,WAAa,WAAY,CACtE,GAAI,GAAa,EAAQ,aAAa,UAAU,EAEhD,AAAK,GACD,EAAQ,aAAa,WAAY,EAAE,EAGvC,EAAQ,OAAO,EACf,EAAQ,kBAAkB,EAAG,EAAQ,MAAM,MAAM,EAE5C,GACD,EAAQ,gBAAgB,UAAU,EAGtC,EAAe,EAAQ,KAC3B,KACK,CACD,AAAI,EAAQ,aAAa,iBAAiB,GACtC,EAAQ,MAAM,EAGlB,GAAI,GAAY,OAAO,aAAa,EAChC,EAAQ,SAAS,YAAY,EAEjC,EAAM,mBAAmB,CAAO,EAChC,EAAU,gBAAgB,EAC1B,EAAU,SAAS,CAAK,EAExB,EAAe,EAAU,SAAS,CACtC,CAEA,MAAO,EACX,CAEA,EAAO,QAAU,CAGX,EAEA,IACC,SAAS,EAAQ,CAExB,YAAc,CAGd,CAEA,EAAE,UAAY,CACZ,GAAI,SAAU,EAAM,EAAU,EAAK,CACjC,GAAI,GAAI,KAAK,GAAM,MAAK,EAAI,CAAC,GAE7B,MAAC,GAAE,IAAU,GAAE,GAAQ,CAAC,IAAI,KAAK,CAC/B,GAAI,EACJ,IAAK,CACP,CAAC,EAEM,IACT,EAEA,KAAM,SAAU,EAAM,EAAU,EAAK,CACnC,GAAI,GAAO,KACX,YAAqB,CACnB,EAAK,IAAI,EAAM,CAAQ,EACvB,EAAS,MAAM,EAAK,SAAS,CAC/B,CAEA,SAAS,EAAI,EACN,KAAK,GAAG,EAAM,EAAU,CAAG,CACpC,EAEA,KAAM,SAAU,EAAM,CACpB,GAAI,GAAO,CAAC,EAAE,MAAM,KAAK,UAAW,CAAC,EACjC,EAAW,OAAK,GAAM,MAAK,EAAI,CAAC,IAAI,IAAS,CAAC,GAAG,MAAM,EACvD,EAAI,EACJ,EAAM,EAAO,OAEjB,IAAK,EAAG,EAAI,EAAK,IACf,EAAO,GAAG,GAAG,MAAM,EAAO,GAAG,IAAK,CAAI,EAGxC,MAAO,KACT,EAEA,IAAK,SAAU,EAAM,EAAU,CAC7B,GAAI,GAAI,KAAK,GAAM,MAAK,EAAI,CAAC,GACzB,EAAO,EAAE,GACT,EAAa,CAAC,EAElB,GAAI,GAAQ,EACV,OAAS,GAAI,EAAG,EAAM,EAAK,OAAQ,EAAI,EAAK,IAC1C,AAAI,EAAK,GAAG,KAAO,GAAY,EAAK,GAAG,GAAG,IAAM,GAC9C,EAAW,KAAK,EAAK,EAAE,EAQ7B,MAAC,GAAW,OACR,EAAE,GAAQ,EACV,MAAO,GAAE,GAEN,IACT,CACF,EAEA,EAAO,QAAU,EACjB,EAAO,QAAQ,YAAc,CAGvB,CAEI,EAGI,EAA2B,CAAC,EAGhC,WAA6B,EAAU,CAEtC,GAAG,EAAyB,GAC3B,MAAO,GAAyB,GAAU,QAG3C,GAAI,GAAS,EAAyB,GAAY,CAGjD,QAAS,CAAC,CACX,EAGA,SAAoB,GAAU,EAAQ,EAAO,QAAS,CAAmB,EAGlE,EAAO,OACf,CAIA,MAAC,WAAW,CAEX,EAAoB,EAAI,SAAS,EAAQ,CACxC,GAAI,GAAS,GAAU,EAAO,WAC7B,UAAW,CAAE,MAAO,GAAO,OAAY,EACvC,UAAW,CAAE,MAAO,EAAQ,EAC7B,SAAoB,EAAE,EAAQ,CAAE,EAAG,CAAO,CAAC,EACpC,CACR,CACD,EAAE,EAGD,UAAW,CAEX,EAAoB,EAAI,SAAS,EAAS,EAAY,CACrD,OAAQ,KAAO,GACd,AAAG,EAAoB,EAAE,EAAY,CAAG,GAAK,CAAC,EAAoB,EAAE,EAAS,CAAG,GAC/E,OAAO,eAAe,EAAS,EAAK,CAAE,WAAY,GAAM,IAAK,EAAW,EAAK,CAAC,CAGjF,CACD,EAAE,EAGD,UAAW,CACX,EAAoB,EAAI,SAAS,EAAK,EAAM,CAAE,MAAO,QAAO,UAAU,eAAe,KAAK,EAAK,CAAI,CAAG,CACvG,EAAE,EAMK,EAAoB,GAAG,CAC/B,EAAG,EACX,OACD,CAAC,ICz3BD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,GAeA,GAAI,IAAkB,UAOtB,GAAO,QAAU,GAUjB,YAAoB,EAAQ,CAC1B,GAAI,GAAM,GAAK,EACX,EAAQ,GAAgB,KAAK,CAAG,EAEpC,GAAI,CAAC,EACH,MAAO,GAGT,GAAI,GACA,EAAO,GACP,EAAQ,EACR,EAAY,EAEhB,IAAK,EAAQ,EAAM,MAAO,EAAQ,EAAI,OAAQ,IAAS,CACrD,OAAQ,EAAI,WAAW,CAAK,OACrB,IACH,EAAS,SACT,UACG,IACH,EAAS,QACT,UACG,IACH,EAAS,QACT,UACG,IACH,EAAS,OACT,UACG,IACH,EAAS,OACT,cAEA,SAGJ,AAAI,IAAc,GAChB,IAAQ,EAAI,UAAU,EAAW,CAAK,GAGxC,EAAY,EAAQ,EACpB,GAAQ,CACV,CAEA,MAAO,KAAc,EACjB,EAAO,EAAI,UAAU,EAAW,CAAK,EACrC,CACN,IC7EA,MAAM,UAAU,MAAM,OAAO,eAAe,MAAM,UAAU,OAAO,CAAC,aAAa,GAAG,MAAM,YAAY,CAAC,GAAI,GAAE,MAAM,UAAU,EAAE,EAAE,EAAE,OAAO,UAAU,EAAE,EAAE,MAAO,GAAE,MAAM,UAAU,OAAO,KAAK,KAAK,SAAS,EAAE,EAAE,CAAC,MAAO,OAAM,QAAQ,CAAC,EAAE,EAAE,KAAK,MAAM,EAAE,EAAE,KAAK,EAAE,EAAE,CAAC,CAAC,EAAE,EAAE,KAAK,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,MAAM,UAAU,MAAM,KAAK,IAAI,CAAC,EAAE,SAAS,EAAE,CAAC,EAAE,MAAM,UAAU,SAAS,OAAO,eAAe,MAAM,UAAU,UAAU,CAAC,aAAa,GAAG,MAAM,SAAS,EAAE,CAAC,MAAO,OAAM,UAAU,IAAI,MAAM,KAAK,SAAS,EAAE,KAAK,CAAC,EAAE,SAAS,EAAE,CAAC,ECuBxf,OAAO,SCvBP,KAAK,OAAQ,MAAK,MAAM,SAAS,EAAE,EAAE,CAAC,MAAO,GAAE,GAAG,CAAC,EAAE,GAAI,SAAQ,SAAS,EAAE,EAAE,CAAC,GAAI,GAAE,GAAI,gBAAe,EAAE,CAAC,EAAE,EAAE,CAAC,EAAE,EAAE,CAAC,EAAE,EAAE,UAAU,CAAC,MAAM,CAAC,GAAG,AAAI,GAAE,OAAO,IAAI,IAAjB,EAAoB,WAAW,EAAE,WAAW,OAAO,EAAE,OAAO,IAAI,EAAE,YAAY,KAAK,UAAU,CAAC,MAAO,SAAQ,QAAQ,EAAE,YAAY,CAAC,EAAE,KAAK,UAAU,CAAC,MAAO,SAAQ,QAAQ,EAAE,YAAY,EAAE,KAAK,KAAK,KAAK,CAAC,EAAE,KAAK,UAAU,CAAC,MAAO,SAAQ,QAAQ,GAAI,MAAK,CAAC,EAAE,QAAQ,CAAC,CAAC,CAAC,EAAE,MAAM,EAAE,QAAQ,CAAC,KAAK,UAAU,CAAC,MAAO,EAAC,EAAE,QAAQ,UAAU,CAAC,MAAO,EAAC,EAAE,IAAI,SAAS,EAAE,CAAC,MAAO,GAAE,EAAE,YAAY,EAAE,EAAE,IAAI,SAAS,EAAE,CAAC,MAAO,GAAE,YAAY,GAAI,EAAC,CAAC,CAAC,CAAC,EAAE,OAAQ,KAAK,GAAE,KAAK,EAAE,QAAQ,MAAM,EAAE,EAAE,EAAE,EAAE,OAAO,UAAU,CAAC,EAAE,sBAAsB,EAAE,QAAQ,+BAA+B,SAAS,EAAE,EAAE,EAAE,CAAC,EAAE,KAAK,EAAE,EAAE,YAAY,CAAC,EAAE,EAAE,KAAK,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,IAAI,EAAE,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,EAAE,EAAE,QAAQ,EAAE,EAAE,gBAAgB,AAAW,EAAE,aAAb,UAAyB,EAAE,QAAQ,EAAE,iBAAiB,EAAE,EAAE,QAAQ,EAAE,EAAE,EAAE,KAAK,EAAE,MAAM,IAAI,CAAC,CAAC,CAAC,GDyBj5B,OAAO,SEzBP,OAAkB,WACZ,CACF,aACA,YACA,UACA,cACA,WACA,cACA,aACA,eACA,gBACA,mBACA,YACA,SACA,YACA,kBACA,gBACA,WACA,oBACA,oBACA,iBACA,wBACA,gBACA,mBACA,0BACA,2BACA,WCtBE,WAAqB,EAAU,CACnC,MAAO,OAAO,IAAU,UAC1B,CCGM,YAA8B,EAAgC,CAClE,GAAM,GAAS,SAAC,EAAa,CAC3B,MAAM,KAAK,CAAQ,EACnB,EAAS,MAAQ,GAAI,OAAK,EAAG,KAC/B,EAEM,EAAW,EAAW,CAAM,EAClC,SAAS,UAAY,OAAO,OAAO,MAAM,SAAS,EAClD,EAAS,UAAU,YAAc,EAC1B,CACT,CCDO,GAAM,IAA+C,GAC1D,SAAC,EAAM,CACL,MAAA,UAA4C,EAA0B,CACpE,EAAO,IAAI,EACX,KAAK,QAAU,EACR,EAAO,OAAM;EACxB,EAAO,IAAI,SAAC,EAAK,EAAC,CAAK,MAAG,GAAI,EAAC,KAAK,EAAI,SAAQ,CAAzB,CAA6B,EAAE,KAAK;GAAM,EACzD,GACJ,KAAK,KAAO,sBACZ,KAAK,OAAS,CAChB,CARA,CAQC,ECvBC,YAAuB,EAA6B,EAAO,CAC/D,GAAI,EAAK,CACP,GAAM,GAAQ,EAAI,QAAQ,CAAI,EAC9B,GAAK,GAAS,EAAI,OAAO,EAAO,CAAC,EAErC,CCOA,GAAA,IAAA,UAAA,CAyBE,WAAoB,EAA4B,CAA5B,KAAA,gBAAA,EAdb,KAAA,OAAS,GAER,KAAA,WAAmD,KAMnD,KAAA,YAAqD,IAMV,CAQnD,SAAA,UAAA,YAAA,UAAA,aACM,EAEJ,GAAI,CAAC,KAAK,OAAQ,CAChB,KAAK,OAAS,GAGN,GAAA,GAAe,KAAI,WAC3B,GAAI,EAEF,GADA,KAAK,WAAa,KACd,MAAM,QAAQ,CAAU,MAC1B,OAAqB,GAAA,GAAA,CAAU,EAAA,EAAA,EAAA,KAAA,EAAA,CAAA,EAAA,KAAA,EAAA,EAAA,KAAA,EAAE,CAA5B,GAAM,GAAM,EAAA,MACf,EAAO,OAAO,IAAI,wGAGpB,GAAW,OAAO,IAAI,EAIlB,GAAiB,GAAqB,KAAI,gBAClD,GAAI,EAAW,CAAgB,EAC7B,GAAI,CACF,EAAgB,QACT,EAAP,CACA,EAAS,YAAa,IAAsB,EAAE,OAAS,CAAC,CAAC,EAIrD,GAAA,GAAgB,KAAI,YAC5B,GAAI,EAAa,CACf,KAAK,YAAc,SACnB,OAAwB,GAAA,GAAA,CAAW,EAAA,EAAA,EAAA,KAAA,EAAA,CAAA,EAAA,KAAA,EAAA,EAAA,KAAA,EAAE,CAAhC,GAAM,GAAS,EAAA,MAClB,GAAI,CACF,GAAc,CAAS,QAChB,EAAP,CACA,EAAS,GAAM,KAAN,EAAU,CAAA,EACnB,AAAI,YAAe,IACjB,EAAM,EAAA,EAAA,CAAA,EAAA,EAAO,CAAM,CAAA,EAAA,EAAK,EAAI,MAAM,CAAA,EAElC,EAAO,KAAK,CAAG,sGAMvB,GAAI,EACF,KAAM,IAAI,IAAoB,CAAM,EAG1C,EAoBA,EAAA,UAAA,IAAA,SAAI,EAAuB,OAGzB,GAAI,GAAY,IAAa,KAC3B,GAAI,KAAK,OAGP,GAAc,CAAQ,MACjB,CACL,GAAI,YAAoB,GAAc,CAGpC,GAAI,EAAS,QAAU,EAAS,WAAW,IAAI,EAC7C,OAEF,EAAS,WAAW,IAAI,EAE1B,AAAC,MAAK,YAAc,GAAA,KAAK,eAAW,MAAA,IAAA,OAAA,EAAI,CAAA,GAAI,KAAK,CAAQ,EAG/D,EAOQ,EAAA,UAAA,WAAR,SAAmB,EAAoB,CAC7B,GAAA,GAAe,KAAI,WAC3B,MAAO,KAAe,GAAW,MAAM,QAAQ,CAAU,GAAK,EAAW,SAAS,CAAM,CAC1F,EASQ,EAAA,UAAA,WAAR,SAAmB,EAAoB,CAC7B,GAAA,GAAe,KAAI,WAC3B,KAAK,WAAa,MAAM,QAAQ,CAAU,EAAK,GAAW,KAAK,CAAM,EAAG,GAAc,EAAa,CAAC,EAAY,CAAM,EAAI,CAC5H,EAMQ,EAAA,UAAA,cAAR,SAAsB,EAAoB,CAChC,GAAA,GAAe,KAAI,WAC3B,AAAI,IAAe,EACjB,KAAK,WAAa,KACT,MAAM,QAAQ,CAAU,GACjC,GAAU,EAAY,CAAM,CAEhC,EAgBA,EAAA,UAAA,OAAA,SAAO,EAAsC,CACnC,GAAA,GAAgB,KAAI,YAC5B,GAAe,GAAU,EAAa,CAAQ,EAE1C,YAAoB,IACtB,EAAS,cAAc,IAAI,CAE/B,EAlLc,EAAA,MAAS,UAAA,CACrB,GAAM,GAAQ,GAAI,GAClB,SAAM,OAAS,GACR,CACT,EAAE,EA+KJ,GArLA,EAuLO,GAAM,IAAqB,GAAa,MAEzC,YAAyB,EAAU,CACvC,MACE,aAAiB,KAChB,GAAS,UAAY,IAAS,EAAW,EAAM,MAAM,GAAK,EAAW,EAAM,GAAG,GAAK,EAAW,EAAM,WAAW,CAEpH,CAEA,YAAuB,EAAwC,CAC7D,AAAI,EAAW,CAAS,EACtB,EAAS,EAET,EAAU,YAAW,CAEzB,CChNO,GAAM,IAAuB,CAClC,iBAAkB,KAClB,sBAAuB,KACvB,QAAS,OACT,sCAAuC,GACvC,yBAA0B,ICErB,GAAM,IAAmC,CAG9C,WAAA,SAAW,EAAqB,EAAgB,QAAE,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,EAAA,GAAA,UAAA,GACzC,GAAA,GAAY,GAAe,SAClC,MAAI,IAAQ,MAAR,EAAU,WACL,EAAS,WAAU,MAAnB,EAAQ,EAAA,CAAY,EAAS,CAAO,EAAA,EAAK,CAAI,CAAA,CAAA,EAE/C,WAAU,MAAA,OAAA,EAAA,CAAC,EAAS,CAAO,EAAA,EAAK,CAAI,CAAA,CAAA,CAC7C,EACA,aAAY,SAAC,EAAM,CACT,GAAA,GAAa,GAAe,SACpC,MAAQ,KAAQ,KAAA,OAAR,EAAU,eAAgB,cAAc,CAAM,CACxD,EACA,SAAU,QChBN,YAA+B,EAAQ,CAC3C,GAAgB,WAAW,UAAA,CACjB,GAAA,GAAqB,GAAM,iBACnC,GAAI,EAEF,EAAiB,CAAG,MAGpB,MAAM,EAEV,CAAC,CACH,CCtBM,aAAc,CAAK,CCMlB,GAAM,IAAyB,UAAA,CAAM,MAAA,IAAmB,IAAK,OAAW,MAAS,CAA5C,EAAsE,EAO5G,YAA4B,EAAU,CAC1C,MAAO,IAAmB,IAAK,OAAW,CAAK,CACjD,CAOM,YAA8B,EAAQ,CAC1C,MAAO,IAAmB,IAAK,EAAO,MAAS,CACjD,CAQM,YAA6B,EAAuB,EAAY,EAAU,CAC9E,MAAO,CACL,KAAI,EACJ,MAAK,EACL,MAAK,EAET,CCrCA,GAAI,IAAuD,KASrD,YAAuB,EAAc,CACzC,GAAI,GAAO,sCAAuC,CAChD,GAAM,GAAS,CAAC,GAKhB,GAJI,GACF,IAAU,CAAE,YAAa,GAAO,MAAO,IAAI,GAE7C,EAAE,EACE,EAAQ,CACJ,GAAA,GAAyB,GAAvB,EAAW,EAAA,YAAE,EAAK,EAAA,MAE1B,GADA,GAAU,KACN,EACF,KAAM,QAMV,GAAE,CAEN,CAMM,YAAuB,EAAQ,CACnC,AAAI,GAAO,uCAAyC,IAClD,IAAQ,YAAc,GACtB,GAAQ,MAAQ,EAEpB,CCrBA,GAAA,IAAA,SAAA,EAAA,CAAmC,GAAA,EAAA,CAAA,EA6BjC,WAAY,EAA6C,CAAzD,GAAA,GACE,EAAA,KAAA,IAAA,GAAO,KATC,SAAA,UAAqB,GAU7B,AAAI,EACF,GAAK,YAAc,EAGf,GAAe,CAAW,GAC5B,EAAY,IAAI,CAAI,GAGtB,EAAK,YAAc,IAEvB,CAzBO,SAAA,OAAP,SAAiB,EAAwB,EAA2B,EAAqB,CACvF,MAAO,IAAI,IAAe,EAAM,EAAO,CAAQ,CACjD,EAgCA,EAAA,UAAA,KAAA,SAAK,EAAS,CACZ,AAAI,KAAK,UACP,GAA0B,GAAiB,CAAK,EAAG,IAAI,EAEvD,KAAK,MAAM,CAAM,CAErB,EASA,EAAA,UAAA,MAAA,SAAM,EAAS,CACb,AAAI,KAAK,UACP,GAA0B,GAAkB,CAAG,EAAG,IAAI,EAEtD,MAAK,UAAY,GACjB,KAAK,OAAO,CAAG,EAEnB,EAQA,EAAA,UAAA,SAAA,UAAA,CACE,AAAI,KAAK,UACP,GAA0B,GAAuB,IAAI,EAErD,MAAK,UAAY,GACjB,KAAK,UAAS,EAElB,EAEA,EAAA,UAAA,YAAA,UAAA,CACE,AAAK,KAAK,QACR,MAAK,UAAY,GACjB,EAAA,UAAM,YAAW,KAAA,IAAA,EACjB,KAAK,YAAc,KAEvB,EAEU,EAAA,UAAA,MAAV,SAAgB,EAAQ,CACtB,KAAK,YAAY,KAAK,CAAK,CAC7B,EAEU,EAAA,UAAA,OAAV,SAAiB,EAAQ,CACvB,GAAI,CACF,KAAK,YAAY,MAAM,CAAG,UAE1B,KAAK,YAAW,EAEpB,EAEU,EAAA,UAAA,UAAV,UAAA,CACE,GAAI,CACF,KAAK,YAAY,SAAQ,UAEzB,KAAK,YAAW,EAEpB,EACF,CAAA,EApHmC,EAAY,EA2H/C,GAAM,IAAQ,SAAS,UAAU,KAEjC,YAAkD,EAAQ,EAAY,CACpE,MAAO,IAAM,KAAK,EAAI,CAAO,CAC/B,CAMA,GAAA,IAAA,UAAA,CACE,WAAoB,EAAqC,CAArC,KAAA,gBAAA,CAAwC,CAE5D,SAAA,UAAA,KAAA,SAAK,EAAQ,CACH,GAAA,GAAoB,KAAI,gBAChC,GAAI,EAAgB,KAClB,GAAI,CACF,EAAgB,KAAK,CAAK,QACnB,EAAP,CACA,GAAqB,CAAK,EAGhC,EAEA,EAAA,UAAA,MAAA,SAAM,EAAQ,CACJ,GAAA,GAAoB,KAAI,gBAChC,GAAI,EAAgB,MAClB,GAAI,CACF,EAAgB,MAAM,CAAG,QAClB,EAAP,CACA,GAAqB,CAAK,MAG5B,IAAqB,CAAG,CAE5B,EAEA,EAAA,UAAA,SAAA,UAAA,CACU,GAAA,GAAoB,KAAI,gBAChC,GAAI,EAAgB,SAClB,GAAI,CACF,EAAgB,SAAQ,QACjB,EAAP,CACA,GAAqB,CAAK,EAGhC,EACF,CAAA,EArCA,EAuCA,GAAA,SAAA,EAAA,CAAuC,GAAA,EAAA,CAAA,EACrC,WACE,EACA,EACA,EAA8B,CAHhC,GAAA,GAKE,EAAA,KAAA,IAAA,GAAO,KAEH,EACJ,GAAI,EAAW,CAAc,GAAK,CAAC,EAGjC,EAAkB,CAChB,KAAM,GAAc,KAAd,EAAkB,OACxB,MAAO,GAAK,KAAL,EAAS,OAChB,SAAU,GAAQ,KAAR,EAAY,YAEnB,CAEL,GAAI,GACJ,AAAI,GAAQ,GAAO,yBAIjB,GAAU,OAAO,OAAO,CAAc,EACtC,EAAQ,YAAc,UAAA,CAAM,MAAA,GAAK,YAAW,CAAhB,EAC5B,EAAkB,CAChB,KAAM,EAAe,MAAQ,GAAK,EAAe,KAAM,CAAO,EAC9D,MAAO,EAAe,OAAS,GAAK,EAAe,MAAO,CAAO,EACjE,SAAU,EAAe,UAAY,GAAK,EAAe,SAAU,CAAO,IAI5E,EAAkB,EAMtB,SAAK,YAAc,GAAI,IAAiB,CAAe,GACzD,CACF,MAAA,EAAA,EAzCuC,EAAU,EA2CjD,YAA8B,EAAU,CACtC,AAAI,GAAO,sCACT,GAAa,CAAK,EAIlB,GAAqB,CAAK,CAE9B,CAQA,YAA6B,EAAQ,CACnC,KAAM,EACR,CAOA,YAAmC,EAA2C,EAA2B,CAC/F,GAAA,GAA0B,GAAM,sBACxC,GAAyB,GAAgB,WAAW,UAAA,CAAM,MAAA,GAAsB,EAAc,CAAU,CAA9C,CAA+C,CAC3G,CAOO,GAAM,IAA6D,CACxE,OAAQ,GACR,KAAM,GACN,MAAO,GACP,SAAU,ICjRL,GAAM,IAA+B,UAAA,CAAM,MAAC,OAAO,SAAW,YAAc,OAAO,YAAe,cAAvD,EAAsE,ECyClH,YAAsB,EAAI,CAC9B,MAAO,EACT,CCiCM,aAAc,QAAC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACnB,MAAO,IAAc,CAAG,CAC1B,CAGM,YAA8B,EAA+B,CACjE,MAAI,GAAI,SAAW,EACV,GAGL,EAAI,SAAW,EACV,EAAI,GAGN,SAAe,EAAQ,CAC5B,MAAO,GAAI,OAAO,SAAC,EAAW,EAAuB,CAAK,MAAA,GAAG,CAAI,CAAP,EAAU,CAAY,CAClF,CACF,CC9EA,GAAA,GAAA,UAAA,CAkBE,WAAY,EAA6E,CACvF,AAAI,GACF,MAAK,WAAa,EAEtB,CA4BA,SAAA,UAAA,KAAA,SAAQ,EAAyB,CAC/B,GAAM,GAAa,GAAI,GACvB,SAAW,OAAS,KACpB,EAAW,SAAW,EACf,CACT,EA8IA,EAAA,UAAA,UAAA,SACE,EACA,EACA,EAA8B,CAHhC,GAAA,GAAA,KAKQ,EAAa,GAAa,CAAc,EAAI,EAAiB,GAAI,IAAe,EAAgB,EAAO,CAAQ,EAErH,UAAa,UAAA,CACL,GAAA,GAAuB,EAArB,EAAQ,EAAA,SAAE,EAAM,EAAA,OACxB,EAAW,IACT,EAGI,EAAS,KAAK,EAAY,CAAM,EAChC,EAIA,EAAK,WAAW,CAAU,EAG1B,EAAK,cAAc,CAAU,CAAC,CAEtC,CAAC,EAEM,CACT,EAGU,EAAA,UAAA,cAAV,SAAwB,EAAmB,CACzC,GAAI,CACF,MAAO,MAAK,WAAW,CAAI,QACpB,EAAP,CAIA,EAAK,MAAM,CAAG,EAElB,EA6DA,EAAA,UAAA,QAAA,SAAQ,EAA0B,EAAoC,CAAtE,GAAA,GAAA,KACE,SAAc,GAAe,CAAW,EAEjC,GAAI,GAAkB,SAAC,EAAS,EAAM,CAC3C,GAAM,GAAa,GAAI,IAAkB,CACvC,KAAM,SAAC,EAAK,CACV,GAAI,CACF,EAAK,CAAK,QACH,EAAP,CACA,EAAO,CAAG,EACV,EAAW,YAAW,EAE1B,EACA,MAAO,EACP,SAAU,EACX,EACD,EAAK,UAAU,CAAU,CAC3B,CAAC,CACH,EAGU,EAAA,UAAA,WAAV,SAAqB,EAA2B,OAC9C,MAAO,GAAA,KAAK,UAAM,MAAA,IAAA,OAAA,OAAA,EAAE,UAAU,CAAU,CAC1C,EAOA,EAAA,UAAC,IAAD,UAAA,CACE,MAAO,KACT,EA4FA,EAAA,UAAA,KAAA,UAAA,QAAK,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACH,MAAO,IAAc,CAAU,EAAE,IAAI,CACvC,EA6BA,EAAA,UAAA,UAAA,SAAU,EAAoC,CAA9C,GAAA,GAAA,KACE,SAAc,GAAe,CAAW,EAEjC,GAAI,GAAY,SAAC,EAAS,EAAM,CACrC,GAAI,GACJ,EAAK,UACH,SAAC,EAAI,CAAK,MAAC,GAAQ,CAAT,EACV,SAAC,EAAQ,CAAK,MAAA,GAAO,CAAG,CAAV,EACd,UAAA,CAAM,MAAA,GAAQ,CAAK,CAAb,CAAc,CAExB,CAAC,CACH,EA3aO,EAAA,OAAkC,SAAI,EAAwD,CACnG,MAAO,IAAI,GAAc,CAAS,CACpC,EA0aF,GA/cA,EAwdA,YAAwB,EAA+C,OACrE,MAAO,GAAA,GAAW,KAAX,EAAe,GAAO,WAAO,MAAA,IAAA,OAAA,EAAI,OAC1C,CAEA,YAAuB,EAAU,CAC/B,MAAO,IAAS,EAAW,EAAM,IAAI,GAAK,EAAW,EAAM,KAAK,GAAK,EAAW,EAAM,QAAQ,CAChG,CAEA,YAAyB,EAAU,CACjC,MAAQ,IAAS,YAAiB,KAAgB,GAAW,CAAK,GAAK,GAAe,CAAK,CAC7F,CC1eM,YAAkB,EAAW,CACjC,MAAO,GAAW,GAAM,KAAA,OAAN,EAAQ,IAAI,CAChC,CAMM,WACJ,EAAqF,CAErF,MAAO,UAAC,EAAqB,CAC3B,GAAI,GAAQ,CAAM,EAChB,MAAO,GAAO,KAAK,SAA+B,EAA2B,CAC3E,GAAI,CACF,MAAO,GAAK,EAAc,IAAI,QACvB,EAAP,CACA,KAAK,MAAM,CAAG,EAElB,CAAC,EAEH,KAAM,IAAI,WAAU,wCAAwC,CAC9D,CACF,CCjBM,WACJ,EACA,EACA,EACA,EACA,EAAuB,CAEvB,MAAO,IAAI,IAAmB,EAAa,EAAQ,EAAY,EAAS,CAAU,CACpF,CAMA,GAAA,IAAA,SAAA,EAAA,CAA2C,GAAA,EAAA,CAAA,EAiBzC,WACE,EACA,EACA,EACA,EACQ,EACA,EAAiC,CAN3C,GAAA,GAoBE,EAAA,KAAA,KAAM,CAAW,GAAC,KAfV,SAAA,WAAA,EACA,EAAA,kBAAA,EAeR,EAAK,MAAQ,EACT,SAAuC,EAAQ,CAC7C,GAAI,CACF,EAAO,CAAK,QACL,EAAP,CACA,EAAY,MAAM,CAAG,EAEzB,EACA,EAAA,UAAM,MACV,EAAK,OAAS,EACV,SAAuC,EAAQ,CAC7C,GAAI,CACF,EAAQ,CAAG,QACJ,EAAP,CAEA,EAAY,MAAM,CAAG,UAGrB,KAAK,YAAW,EAEpB,EACA,EAAA,UAAM,OACV,EAAK,UAAY,EACb,UAAA,CACE,GAAI,CACF,EAAU,QACH,EAAP,CAEA,EAAY,MAAM,CAAG,UAGrB,KAAK,YAAW,EAEpB,EACA,EAAA,UAAM,WACZ,CAEA,SAAA,UAAA,YAAA,UAAA,OACE,GAAI,CAAC,KAAK,mBAAqB,KAAK,kBAAiB,EAAI,CAC/C,GAAA,GAAW,KAAI,OACvB,EAAA,UAAM,YAAW,KAAA,IAAA,EAEjB,CAAC,GAAU,IAAA,KAAK,cAAU,MAAA,IAAA,QAAA,EAAA,KAAf,IAAI,GAEnB,EACF,CAAA,EAnF2C,EAAU,ECd9C,GAAM,IAAiD,CAG5D,SAAA,SAAS,EAAQ,CACf,GAAI,GAAU,sBACV,EAAkD,qBAC9C,EAAa,GAAsB,SAC3C,AAAI,GACF,GAAU,EAAS,sBACnB,EAAS,EAAS,sBAEpB,GAAM,GAAS,EAAQ,SAAC,EAAS,CAI/B,EAAS,OACT,EAAS,CAAS,CACpB,CAAC,EACD,MAAO,IAAI,IAAa,UAAA,CAAM,MAAA,IAAM,KAAA,OAAN,EAAS,CAAM,CAAf,CAAgB,CAChD,EACA,sBAAqB,UAAA,QAAC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACZ,GAAA,GAAa,GAAsB,SAC3C,MAAQ,KAAQ,KAAA,OAAR,EAAU,wBAAyB,uBAAsB,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAI,CAAA,CAAA,CAC3E,EACA,qBAAoB,UAAA,QAAC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACX,GAAA,GAAa,GAAsB,SAC3C,MAAQ,KAAQ,KAAA,OAAR,EAAU,uBAAwB,sBAAqB,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAI,CAAA,CAAA,CACzE,EACA,SAAU,QCrBL,GAAM,IAAuD,GAClE,SAAC,EAAM,CACL,MAAA,WAAoC,CAClC,EAAO,IAAI,EACX,KAAK,KAAO,0BACZ,KAAK,QAAU,qBACjB,CAJA,CAIC,ECXL,GAAA,GAAA,SAAA,EAAA,CAAgC,GAAA,EAAA,CAAA,EAwB9B,YAAA,CAAA,GAAA,GAEE,EAAA,KAAA,IAAA,GAAO,KAzBT,SAAA,OAAS,GAED,EAAA,iBAAyC,KAGjD,EAAA,UAA2B,CAAA,EAE3B,EAAA,UAAY,GAEZ,EAAA,SAAW,GAEX,EAAA,YAAmB,MAenB,CAGA,SAAA,UAAA,KAAA,SAAQ,EAAwB,CAC9B,GAAM,GAAU,GAAI,IAAiB,KAAM,IAAI,EAC/C,SAAQ,SAAW,EACZ,CACT,EAGU,EAAA,UAAA,eAAV,UAAA,CACE,GAAI,KAAK,OACP,KAAM,IAAI,GAEd,EAEA,EAAA,UAAA,KAAA,SAAK,EAAQ,CAAb,GAAA,GAAA,KACE,GAAa,UAAA,SAEX,GADA,EAAK,eAAc,EACf,CAAC,EAAK,UAAW,CACnB,AAAK,EAAK,kBACR,GAAK,iBAAmB,MAAM,KAAK,EAAK,SAAS,OAEnD,OAAuB,GAAA,GAAA,EAAK,gBAAgB,EAAA,EAAA,EAAA,KAAA,EAAA,CAAA,EAAA,KAAA,EAAA,EAAA,KAAA,EAAE,CAAzC,GAAM,GAAQ,EAAA,MACjB,EAAS,KAAK,CAAK,qGAGzB,CAAC,CACH,EAEA,EAAA,UAAA,MAAA,SAAM,EAAQ,CAAd,GAAA,GAAA,KACE,GAAa,UAAA,CAEX,GADA,EAAK,eAAc,EACf,CAAC,EAAK,UAAW,CACnB,EAAK,SAAW,EAAK,UAAY,GACjC,EAAK,YAAc,EAEnB,OADQ,GAAc,EAAI,UACnB,EAAU,QACf,EAAU,MAAK,EAAI,MAAM,CAAG,EAGlC,CAAC,CACH,EAEA,EAAA,UAAA,SAAA,UAAA,CAAA,GAAA,GAAA,KACE,GAAa,UAAA,CAEX,GADA,EAAK,eAAc,EACf,CAAC,EAAK,UAAW,CACnB,EAAK,UAAY,GAEjB,OADQ,GAAc,EAAI,UACnB,EAAU,QACf,EAAU,MAAK,EAAI,SAAQ,EAGjC,CAAC,CACH,EAEA,EAAA,UAAA,YAAA,UAAA,CACE,KAAK,UAAY,KAAK,OAAS,GAC/B,KAAK,UAAY,KAAK,iBAAmB,IAC3C,EAEA,OAAA,eAAI,EAAA,UAAA,WAAQ,KAAZ,UAAA,OACE,MAAO,IAAA,KAAK,aAAS,MAAA,IAAA,OAAA,OAAA,EAAE,QAAS,CAClC,kCAGU,EAAA,UAAA,cAAV,SAAwB,EAAyB,CAC/C,YAAK,eAAc,EACZ,EAAA,UAAM,cAAa,KAAA,KAAC,CAAU,CACvC,EAGU,EAAA,UAAA,WAAV,SAAqB,EAAyB,CAC5C,YAAK,eAAc,EACnB,KAAK,wBAAwB,CAAU,EAChC,KAAK,gBAAgB,CAAU,CACxC,EAGU,EAAA,UAAA,gBAAV,SAA0B,EAA2B,CAArD,GAAA,GAAA,KACQ,EAAqC,KAAnC,EAAQ,EAAA,SAAE,EAAS,EAAA,UAAE,EAAS,EAAA,UACtC,MAAI,IAAY,EACP,GAET,MAAK,iBAAmB,KACxB,EAAU,KAAK,CAAU,EAClB,GAAI,IAAa,UAAA,CACtB,EAAK,iBAAmB,KACxB,GAAU,EAAW,CAAU,CACjC,CAAC,EACH,EAGU,EAAA,UAAA,wBAAV,SAAkC,EAA2B,CACrD,GAAA,GAAuC,KAArC,EAAQ,EAAA,SAAE,EAAW,EAAA,YAAE,EAAS,EAAA,UACxC,AAAI,EACF,EAAW,MAAM,CAAW,EACnB,GACT,EAAW,SAAQ,CAEvB,EAQA,EAAA,UAAA,aAAA,UAAA,CACE,GAAM,GAAkB,GAAI,GAC5B,SAAW,OAAS,KACb,CACT,EAxHO,EAAA,OAAkC,SAAI,EAA0B,EAAqB,CAC1F,MAAO,IAAI,IAAoB,EAAa,CAAM,CACpD,EAuHF,GA7IgC,CAAU,EAkJ1C,GAAA,IAAA,SAAA,EAAA,CAAyC,GAAA,EAAA,CAAA,EACvC,WAES,EACP,EAAsB,CAHxB,GAAA,GAKE,EAAA,KAAA,IAAA,GAAO,KAHA,SAAA,YAAA,EAIP,EAAK,OAAS,GAChB,CAEA,SAAA,UAAA,KAAA,SAAK,EAAQ,SACX,AAAA,GAAA,GAAA,KAAK,eAAW,MAAA,IAAA,OAAA,OAAA,EAAE,QAAI,MAAA,IAAA,QAAA,EAAA,KAAA,EAAG,CAAK,CAChC,EAEA,EAAA,UAAA,MAAA,SAAM,EAAQ,SACZ,AAAA,GAAA,GAAA,KAAK,eAAW,MAAA,IAAA,OAAA,OAAA,EAAE,SAAK,MAAA,IAAA,QAAA,EAAA,KAAA,EAAG,CAAG,CAC/B,EAEA,EAAA,UAAA,SAAA,UAAA,SACE,AAAA,GAAA,GAAA,KAAK,eAAW,MAAA,IAAA,OAAA,OAAA,EAAE,YAAQ,MAAA,IAAA,QAAA,EAAA,KAAA,CAAA,CAC5B,EAGU,EAAA,UAAA,WAAV,SAAqB,EAAyB,SAC5C,MAAO,GAAA,GAAA,KAAK,UAAM,MAAA,IAAA,OAAA,OAAA,EAAE,UAAU,CAAU,KAAC,MAAA,IAAA,OAAA,EAAI,EAC/C,EACF,CAAA,EA1ByC,CAAO,EC5JzC,GAAM,IAA+C,CAC1D,IAAG,UAAA,CAGD,MAAQ,IAAsB,UAAY,MAAM,IAAG,CACrD,EACA,SAAU,QCwBZ,GAAA,IAAA,SAAA,EAAA,CAAsC,GAAA,EAAA,CAAA,EAUpC,WACU,EACA,EACA,EAA6D,CAF7D,AAAA,IAAA,QAAA,GAAA,KACA,IAAA,QAAA,GAAA,KACA,IAAA,QAAA,GAAA,IAHV,GAAA,GAKE,EAAA,KAAA,IAAA,GAAO,KAJC,SAAA,YAAA,EACA,EAAA,YAAA,EACA,EAAA,mBAAA,EAZF,EAAA,QAA0B,CAAA,EAC1B,EAAA,oBAAsB,GAc5B,EAAK,oBAAsB,IAAgB,IAC3C,EAAK,YAAc,KAAK,IAAI,EAAG,CAAW,EAC1C,EAAK,YAAc,KAAK,IAAI,EAAG,CAAW,GAC5C,CAEA,SAAA,UAAA,KAAA,SAAK,EAAQ,CACL,GAAA,GAA+E,KAA7E,EAAS,EAAA,UAAE,EAAO,EAAA,QAAE,EAAmB,EAAA,oBAAE,EAAkB,EAAA,mBAAE,EAAW,EAAA,YAChF,AAAK,GACH,GAAQ,KAAK,CAAK,EAClB,CAAC,GAAuB,EAAQ,KAAK,EAAmB,IAAG,EAAK,CAAW,GAE7E,KAAK,YAAW,EAChB,EAAA,UAAM,KAAI,KAAA,KAAC,CAAK,CAClB,EAGU,EAAA,UAAA,WAAV,SAAqB,EAAyB,CAC5C,KAAK,eAAc,EACnB,KAAK,YAAW,EAQhB,OANM,GAAe,KAAK,gBAAgB,CAAU,EAE9C,EAAmC,KAAjC,EAAmB,EAAA,oBAAE,EAAO,EAAA,QAG9B,EAAO,EAAQ,MAAK,EACjB,EAAI,EAAG,EAAI,EAAK,QAAU,CAAC,EAAW,OAAQ,GAAK,EAAsB,EAAI,EACpF,EAAW,KAAK,EAAK,EAAO,EAG9B,YAAK,wBAAwB,CAAU,EAEhC,CACT,EAEQ,EAAA,UAAA,YAAR,UAAA,CACQ,GAAA,GAAoE,KAAlE,EAAW,EAAA,YAAE,EAAkB,EAAA,mBAAE,EAAO,EAAA,QAAE,EAAmB,EAAA,oBAK/D,EAAsB,GAAsB,EAAI,GAAK,EAK3D,GAJA,EAAc,KAAY,EAAqB,EAAQ,QAAU,EAAQ,OAAO,EAAG,EAAQ,OAAS,CAAkB,EAIlH,CAAC,EAAqB,CAKxB,OAJM,GAAM,EAAmB,IAAG,EAC9B,EAAO,EAGF,EAAI,EAAG,EAAI,EAAQ,QAAW,EAAQ,IAAiB,EAAK,GAAK,EACxE,EAAO,EAET,GAAQ,EAAQ,OAAO,EAAG,EAAO,CAAC,EAEtC,EACF,CAAA,EAzEsC,CAAO,EClB7C,GAAA,IAAA,SAAA,EAAA,CAA+B,GAAA,EAAA,CAAA,EAC7B,WAAY,EAAsB,EAAmD,OACnF,GAAA,KAAA,IAAA,GAAO,IACT,CAWO,SAAA,UAAA,SAAP,SAAgB,EAAW,EAAiB,CAAjB,MAAA,KAAA,QAAA,GAAA,GAClB,IACT,EACF,CAAA,EAjB+B,EAAY,ECJpC,GAAM,IAAqC,CAGhD,YAAA,SAAY,EAAqB,EAAgB,QAAE,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,EAAA,GAAA,UAAA,GAC1C,GAAA,GAAY,GAAgB,SACnC,MAAI,IAAQ,MAAR,EAAU,YACL,EAAS,YAAW,MAApB,EAAQ,EAAA,CAAa,EAAS,CAAO,EAAA,EAAK,CAAI,CAAA,CAAA,EAEhD,YAAW,MAAA,OAAA,EAAA,CAAC,EAAS,CAAO,EAAA,EAAK,CAAI,CAAA,CAAA,CAC9C,EACA,cAAa,SAAC,EAAM,CACV,GAAA,GAAa,GAAgB,SACrC,MAAQ,KAAQ,KAAA,OAAR,EAAU,gBAAiB,eAAe,CAAM,CAC1D,EACA,SAAU,QCrBZ,GAAA,IAAA,SAAA,EAAA,CAAoC,GAAA,EAAA,CAAA,EAOlC,WAAsB,EAAqC,EAAmD,CAA9G,GAAA,GACE,EAAA,KAAA,KAAM,EAAW,CAAI,GAAC,KADF,SAAA,UAAA,EAAqC,EAAA,KAAA,EAFjD,EAAA,QAAmB,IAI7B,CAEO,SAAA,UAAA,SAAP,SAAgB,EAAW,EAAiB,CAC1C,GADyB,IAAA,QAAA,GAAA,GACrB,KAAK,OACP,MAAO,MAIT,KAAK,MAAQ,EAEb,GAAM,GAAK,KAAK,GACV,EAAY,KAAK,UAuBvB,MAAI,IAAM,MACR,MAAK,GAAK,KAAK,eAAe,EAAW,EAAI,CAAK,GAKpD,KAAK,QAAU,GAEf,KAAK,MAAQ,EAEb,KAAK,GAAK,KAAK,IAAM,KAAK,eAAe,EAAW,KAAK,GAAI,CAAK,EAE3D,IACT,EAEU,EAAA,UAAA,eAAV,SAAyB,EAA2B,EAAW,EAAiB,CAAjB,MAAA,KAAA,QAAA,GAAA,GACtD,GAAiB,YAAY,EAAU,MAAM,KAAK,EAAW,IAAI,EAAG,CAAK,CAClF,EAEU,EAAA,UAAA,eAAV,SAAyB,EAA4B,EAAS,EAAwB,CAEpF,GAF4D,IAAA,QAAA,GAAA,GAExD,GAAS,MAAQ,KAAK,QAAU,GAAS,KAAK,UAAY,GAC5D,MAAO,GAIT,GAAiB,cAAc,CAAE,CAEnC,EAMO,EAAA,UAAA,QAAP,SAAe,EAAU,EAAa,CACpC,GAAI,KAAK,OACP,MAAO,IAAI,OAAM,8BAA8B,EAGjD,KAAK,QAAU,GACf,GAAM,GAAQ,KAAK,SAAS,EAAO,CAAK,EACxC,GAAI,EACF,MAAO,GACF,AAAI,KAAK,UAAY,IAAS,KAAK,IAAM,MAc9C,MAAK,GAAK,KAAK,eAAe,KAAK,UAAW,KAAK,GAAI,IAAI,EAE/D,EAEU,EAAA,UAAA,SAAV,SAAmB,EAAU,EAAc,CACzC,GAAI,GAAmB,GACnB,EACJ,GAAI,CACF,KAAK,KAAK,CAAK,QACR,EAAP,CACA,EAAU,GAIV,EAAa,GAAQ,GAAI,OAAM,oCAAoC,EAErE,GAAI,EACF,YAAK,YAAW,EACT,CAEX,EAEA,EAAA,UAAA,YAAA,UAAA,CACE,GAAI,CAAC,KAAK,OAAQ,CACV,GAAA,GAAoB,KAAlB,EAAE,EAAA,GAAE,EAAS,EAAA,UACb,EAAY,EAAS,QAE7B,KAAK,KAAO,KAAK,MAAQ,KAAK,UAAY,KAC1C,KAAK,QAAU,GAEf,GAAU,EAAS,IAAI,EACnB,GAAM,MACR,MAAK,GAAK,KAAK,eAAe,EAAW,EAAI,IAAI,GAGnD,KAAK,MAAQ,KACb,EAAA,UAAM,YAAW,KAAA,IAAA,EAErB,EACF,CAAA,EA3IoC,EAAM,ECiB1C,GAAA,IAAA,UAAA,CAGE,WAAoB,EAAoC,EAAiC,CAAjC,AAAA,IAAA,QAAA,GAAoB,EAAU,KAAlE,KAAA,oBAAA,EAClB,KAAK,IAAM,CACb,CA6BO,SAAA,UAAA,SAAP,SAAmB,EAAqD,EAAmB,EAAS,CAA5B,MAAA,KAAA,QAAA,GAAA,GAC/D,GAAI,MAAK,oBAAuB,KAAM,CAAI,EAAE,SAAS,EAAO,CAAK,CAC1E,EAnCc,EAAA,IAAoB,GAAsB,IAoC1D,GArCA,ECpBA,GAAA,IAAA,SAAA,EAAA,CAAoC,GAAA,EAAA,CAAA,EAkBlC,WAAY,EAAgC,EAAiC,CAAjC,AAAA,IAAA,QAAA,GAAoB,GAAU,KAA1E,GAAA,GACE,EAAA,KAAA,KAAM,EAAiB,CAAG,GAAC,KAlBtB,SAAA,QAAmC,CAAA,EAOnC,EAAA,QAAmB,GAQnB,EAAA,WAAkB,QAIzB,CAEO,SAAA,UAAA,MAAP,SAAa,EAAwB,CAC3B,GAAA,GAAY,KAAI,QAExB,GAAI,KAAK,QAAS,CAChB,EAAQ,KAAK,CAAM,EACnB,OAGF,GAAI,GACJ,KAAK,QAAU,GAEf,EACE,IAAK,EAAQ,EAAO,QAAQ,EAAO,MAAO,EAAO,KAAK,EACpD,YAEM,EAAS,EAAQ,MAAK,GAIhC,GAFA,KAAK,QAAU,GAEX,EAAO,CACT,KAAQ,EAAS,EAAQ,MAAK,GAC5B,EAAO,YAAW,EAEpB,KAAM,GAEV,EACF,CAAA,EAhDoC,EAAS,EC8CtC,GAAM,IAAiB,GAAI,IAAe,EAAW,EAK/C,GAAQ,GClDrB,GAAA,IAAA,SAAA,EAAA,CAA6C,GAAA,EAAA,CAAA,EAC3C,WAAsB,EAA8C,EAAmD,CAAvH,GAAA,GACE,EAAA,KAAA,KAAM,EAAW,CAAI,GAAC,KADF,SAAA,UAAA,EAA8C,EAAA,KAAA,GAEpE,CAEU,SAAA,UAAA,eAAV,SAAyB,EAAoC,EAAU,EAAiB,CAEtF,MAFqE,KAAA,QAAA,GAAA,GAEjE,IAAU,MAAQ,EAAQ,EACrB,EAAA,UAAM,eAAc,KAAA,KAAC,EAAW,EAAI,CAAK,EAGlD,GAAU,QAAQ,KAAK,IAAI,EAIpB,EAAU,YAAe,GAAU,WAAa,GAAuB,sBAAsB,UAAA,CAAM,MAAA,GAAU,MAAM,MAAS,CAAzB,CAA0B,GACtI,EACU,EAAA,UAAA,eAAV,SAAyB,EAAoC,EAAU,EAAiB,CAItF,GAJqE,IAAA,QAAA,GAAA,GAIhE,GAAS,MAAQ,EAAQ,GAAO,GAAS,MAAQ,KAAK,MAAQ,EACjE,MAAO,GAAA,UAAM,eAAc,KAAA,KAAC,EAAW,EAAI,CAAK,EAKlD,AAAK,EAAU,QAAQ,KAAK,SAAC,EAAM,CAAK,MAAA,GAAO,KAAO,CAAd,CAAgB,GACtD,IAAuB,qBAAqB,CAAE,EAC9C,EAAU,WAAa,OAI3B,EACF,CAAA,EAlC6C,EAAW,ECFxD,GAAA,IAAA,SAAA,EAAA,CAA6C,GAAA,EAAA,CAAA,EAA7C,YAAA,+CAkCA,CAjCS,SAAA,UAAA,MAAP,SAAa,EAAyB,CACpC,KAAK,QAAU,GAUf,GAAM,GAAU,KAAK,WACrB,KAAK,WAAa,OAEV,GAAA,GAAY,KAAI,QACpB,EACJ,EAAS,GAAU,EAAQ,MAAK,EAEhC,EACE,IAAK,EAAQ,EAAO,QAAQ,EAAO,MAAO,EAAO,KAAK,EACpD,YAEM,GAAS,EAAQ,KAAO,EAAO,KAAO,GAAW,EAAQ,MAAK,GAIxE,GAFA,KAAK,QAAU,GAEX,EAAO,CACT,KAAQ,GAAS,EAAQ,KAAO,EAAO,KAAO,GAAW,EAAQ,MAAK,GACpE,EAAO,YAAW,EAEpB,KAAM,GAEV,EACF,CAAA,EAlC6C,EAAc,ECgCpD,GAAM,IAA0B,GAAI,IAAwB,EAAoB,EC8BhF,GAAM,GAAQ,GAAI,GAAkB,SAAC,EAAU,CAAK,MAAA,GAAW,SAAQ,CAAnB,CAAqB,EC9D1E,YAAsB,EAAU,CACpC,MAAO,IAAS,EAAW,EAAM,QAAQ,CAC3C,CCDA,YAAiB,EAAQ,CACvB,MAAO,GAAI,EAAI,OAAS,EAC1B,CAEM,YAA4B,EAAW,CAC3C,MAAO,GAAW,GAAK,CAAI,CAAC,EAAI,EAAK,IAAG,EAAK,MAC/C,CAEM,YAAuB,EAAW,CACtC,MAAO,IAAY,GAAK,CAAI,CAAC,EAAI,EAAK,IAAG,EAAK,MAChD,CAEM,YAAoB,EAAa,EAAoB,CACzD,MAAO,OAAO,IAAK,CAAI,GAAM,SAAW,EAAK,IAAG,EAAM,CACxD,CClBO,GAAM,IAAe,SAAI,EAAM,CAAwB,MAAA,IAAK,MAAO,GAAE,QAAW,UAAY,MAAO,IAAM,UAAlD,ECMxD,YAAoB,EAAU,CAClC,MAAO,GAAW,GAAK,KAAA,OAAL,EAAO,IAAI,CAC/B,CCHM,YAA8B,EAAU,CAC5C,MAAO,GAAW,EAAM,GAAkB,CAC5C,CCLM,YAA6B,EAAQ,CACzC,MAAO,QAAO,eAAiB,EAAW,GAAG,KAAA,OAAH,EAAM,OAAO,cAAc,CACvE,CCAM,YAA2C,EAAU,CAEzD,MAAO,IAAI,WACT,gBACE,KAAU,MAAQ,MAAO,IAAU,SAAW,oBAAsB,IAAI,EAAK,KAAG,0HACwC,CAE9H,CCXM,aAA2B,CAC/B,MAAI,OAAO,SAAW,YAAc,CAAC,OAAO,SACnC,aAGF,OAAO,QAChB,CAEO,GAAM,IAAW,GAAiB,ECJnC,YAAqB,EAAU,CACnC,MAAO,GAAW,GAAK,KAAA,OAAL,EAAQ,GAAgB,CAC5C,CCHM,YAAuD,EAAqC,mGAC1F,EAAS,EAAe,UAAS,2DAGX,MAAA,CAAA,EAAA,GAAM,EAAO,KAAI,CAAE,CAAA,eAArC,GAAkB,EAAA,KAAA,EAAhB,EAAK,EAAA,MAAE,EAAI,EAAA,KACf,iBAAA,CAAA,EAAA,CAAA,SACF,MAAA,CAAA,EAAA,EAAA,KAAA,CAAA,qBAEI,CAAM,CAAA,SAAZ,MAAA,CAAA,EAAA,EAAA,KAAA,CAAA,SAAA,SAAA,KAAA,mCAGF,SAAO,YAAW,6BAIhB,YAAkC,EAAQ,CAG9C,MAAO,GAAW,GAAG,KAAA,OAAH,EAAK,SAAS,CAClC,CCRM,WAAuB,EAAyB,CACpD,GAAI,YAAiB,GACnB,MAAO,GAET,GAAI,GAAS,KAAM,CACjB,GAAI,GAAoB,CAAK,EAC3B,MAAO,IAAsB,CAAK,EAEpC,GAAI,GAAY,CAAK,EACnB,MAAO,IAAc,CAAK,EAE5B,GAAI,GAAU,CAAK,EACjB,MAAO,IAAY,CAAK,EAE1B,GAAI,GAAgB,CAAK,EACvB,MAAO,IAAkB,CAAK,EAEhC,GAAI,GAAW,CAAK,EAClB,MAAO,IAAa,CAAK,EAE3B,GAAI,GAAqB,CAAK,EAC5B,MAAO,IAAuB,CAAK,EAIvC,KAAM,IAAiC,CAAK,CAC9C,CAMM,YAAmC,EAAQ,CAC/C,MAAO,IAAI,GAAW,SAAC,EAAyB,CAC9C,GAAM,GAAM,EAAI,IAAkB,EAClC,GAAI,EAAW,EAAI,SAAS,EAC1B,MAAO,GAAI,UAAU,CAAU,EAGjC,KAAM,IAAI,WAAU,gEAAgE,CACtF,CAAC,CACH,CASM,YAA2B,EAAmB,CAClD,MAAO,IAAI,GAAW,SAAC,EAAyB,CAU9C,OAAS,GAAI,EAAG,EAAI,EAAM,QAAU,CAAC,EAAW,OAAQ,IACtD,EAAW,KAAK,EAAM,EAAE,EAE1B,EAAW,SAAQ,CACrB,CAAC,CACH,CAEM,YAAyB,EAAuB,CACpD,MAAO,IAAI,GAAW,SAAC,EAAyB,CAC9C,EACG,KACC,SAAC,EAAK,CACJ,AAAK,EAAW,QACd,GAAW,KAAK,CAAK,EACrB,EAAW,SAAQ,EAEvB,EACA,SAAC,EAAQ,CAAK,MAAA,GAAW,MAAM,CAAG,CAApB,CAAqB,EAEpC,KAAK,KAAM,EAAoB,CACpC,CAAC,CACH,CAEM,YAA0B,EAAqB,CACnD,MAAO,IAAI,GAAW,SAAC,EAAyB,aAC9C,OAAoB,GAAA,GAAA,CAAQ,EAAA,EAAA,EAAA,KAAA,EAAA,CAAA,EAAA,KAAA,EAAA,EAAA,KAAA,EAAE,CAAzB,GAAM,GAAK,EAAA,MAEd,GADA,EAAW,KAAK,CAAK,EACjB,EAAW,OACb,yGAGJ,EAAW,SAAQ,CACrB,CAAC,CACH,CAEM,YAA+B,EAA+B,CAClE,MAAO,IAAI,GAAW,SAAC,EAAyB,CAC9C,GAAQ,EAAe,CAAU,EAAE,MAAM,SAAC,EAAG,CAAK,MAAA,GAAW,MAAM,CAAG,CAApB,CAAqB,CACzE,CAAC,CACH,CAEM,YAAoC,EAAqC,CAC7E,MAAO,IAAkB,GAAmC,CAAc,CAAC,CAC7E,CAEA,YAA0B,EAAiC,EAAyB,uIACxD,EAAA,GAAA,CAAa,gFAIrC,GAJe,EAAK,EAAA,MACpB,EAAW,KAAK,CAAK,EAGjB,EAAW,OACb,MAAA,CAAA,CAAA,6RAGJ,SAAW,SAAQ,WC/Gf,YACJ,EACA,EACA,EACA,EACA,EAAc,CADd,AAAA,IAAA,QAAA,GAAA,GACA,IAAA,QAAA,GAAA,IAEA,GAAM,GAAuB,EAAU,SAAS,UAAA,CAC9C,EAAI,EACJ,AAAI,EACF,EAAmB,IAAI,KAAK,SAAS,KAAM,CAAK,CAAC,EAEjD,KAAK,YAAW,CAEpB,EAAG,CAAK,EAIR,GAFA,EAAmB,IAAI,CAAoB,EAEvC,CAAC,EAKH,MAAO,EAEX,CCeM,YAAuB,EAA0B,EAAS,CAAT,MAAA,KAAA,QAAA,GAAA,GAC9C,EAAQ,SAAC,EAAQ,EAAU,CAChC,EAAO,UACL,EACE,EACA,SAAC,EAAK,CAAK,MAAA,IAAgB,EAAY,EAAW,UAAA,CAAM,MAAA,GAAW,KAAK,CAAK,CAArB,EAAwB,CAAK,CAA1E,EACX,UAAA,CAAM,MAAA,IAAgB,EAAY,EAAW,UAAA,CAAM,MAAA,GAAW,SAAQ,CAAnB,EAAuB,CAAK,CAAzE,EACN,SAAC,EAAG,CAAK,MAAA,IAAgB,EAAY,EAAW,UAAA,CAAM,MAAA,GAAW,MAAM,CAAG,CAApB,EAAuB,CAAK,CAAzE,CAA0E,CACpF,CAEL,CAAC,CACH,CCPM,YAAyB,EAA0B,EAAiB,CAAjB,MAAA,KAAA,QAAA,GAAA,GAChD,EAAQ,SAAC,EAAQ,EAAU,CAChC,EAAW,IAAI,EAAU,SAAS,UAAA,CAAM,MAAA,GAAO,UAAU,CAAU,CAA3B,EAA8B,CAAK,CAAC,CAC9E,CAAC,CACH,CC7DM,YAAgC,EAA6B,EAAwB,CACzF,MAAO,GAAU,CAAK,EAAE,KAAK,GAAY,CAAS,EAAG,GAAU,CAAS,CAAC,CAC3E,CCFM,YAA6B,EAAuB,EAAwB,CAChF,MAAO,GAAU,CAAK,EAAE,KAAK,GAAY,CAAS,EAAG,GAAU,CAAS,CAAC,CAC3E,CCJM,YAA2B,EAAqB,EAAwB,CAC5E,MAAO,IAAI,GAAc,SAAC,EAAU,CAElC,GAAI,GAAI,EAER,MAAO,GAAU,SAAS,UAAA,CACxB,AAAI,IAAM,EAAM,OAGd,EAAW,SAAQ,EAInB,GAAW,KAAK,EAAM,IAAI,EAIrB,EAAW,QACd,KAAK,SAAQ,EAGnB,CAAC,CACH,CAAC,CACH,CCfM,YAA8B,EAAoB,EAAwB,CAC9E,MAAO,IAAI,GAAc,SAAC,EAAU,CAClC,GAAI,GAKJ,UAAgB,EAAY,EAAW,UAAA,CAErC,EAAY,EAAc,IAAgB,EAE1C,GACE,EACA,EACA,UAAA,OACM,EACA,EACJ,GAAI,CAEF,AAAC,EAAkB,EAAS,KAAI,EAA7B,EAAK,EAAA,MAAE,EAAI,EAAA,WACP,EAAP,CAEA,EAAW,MAAM,CAAG,EACpB,OAGF,AAAI,EAKF,EAAW,SAAQ,EAGnB,EAAW,KAAK,CAAK,CAEzB,EACA,EACA,EAAI,CAER,CAAC,EAMM,UAAA,CAAM,MAAA,GAAW,GAAQ,KAAA,OAAR,EAAU,MAAM,GAAK,EAAS,OAAM,CAA/C,CACf,CAAC,CACH,CCvDM,YAAmC,EAAyB,EAAwB,CACxF,GAAI,CAAC,EACH,KAAM,IAAI,OAAM,yBAAyB,EAE3C,MAAO,IAAI,GAAc,SAAC,EAAU,CAClC,GAAgB,EAAY,EAAW,UAAA,CACrC,GAAM,GAAW,EAAM,OAAO,eAAc,EAC5C,GACE,EACA,EACA,UAAA,CACE,EAAS,KAAI,EAAG,KAAK,SAAC,EAAM,CAC1B,AAAI,EAAO,KAGT,EAAW,SAAQ,EAEnB,EAAW,KAAK,EAAO,KAAK,CAEhC,CAAC,CACH,EACA,EACA,EAAI,CAER,CAAC,CACH,CAAC,CACH,CCzBM,YAAwC,EAA8B,EAAwB,CAClG,MAAO,IAAsB,GAAmC,CAAK,EAAG,CAAS,CACnF,CCoBM,YAAuB,EAA2B,EAAwB,CAC9E,GAAI,GAAS,KAAM,CACjB,GAAI,GAAoB,CAAK,EAC3B,MAAO,IAAmB,EAAO,CAAS,EAE5C,GAAI,GAAY,CAAK,EACnB,MAAO,IAAc,EAAO,CAAS,EAEvC,GAAI,GAAU,CAAK,EACjB,MAAO,IAAgB,EAAO,CAAS,EAEzC,GAAI,GAAgB,CAAK,EACvB,MAAO,IAAsB,EAAO,CAAS,EAE/C,GAAI,GAAW,CAAK,EAClB,MAAO,IAAiB,EAAO,CAAS,EAE1C,GAAI,GAAqB,CAAK,EAC5B,MAAO,IAA2B,EAAO,CAAS,EAGtD,KAAM,IAAiC,CAAK,CAC9C,CCoDM,YAAkB,EAA2B,EAAyB,CAC1E,MAAO,GAAY,GAAU,EAAO,CAAS,EAAI,EAAU,CAAK,CAClE,CCxBM,YAAY,QAAI,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACpB,GAAM,GAAY,GAAa,CAAI,EACnC,MAAO,IAAK,EAAa,CAAS,CACpC,CCsCM,YAAqB,EAA0B,EAAyB,CAC5E,GAAM,GAAe,EAAW,CAAmB,EAAI,EAAsB,UAAA,CAAM,MAAA,EAAA,EAC7E,EAAO,SAAC,EAA6B,CAAK,MAAA,GAAW,MAAM,EAAY,CAAE,CAA/B,EAChD,MAAO,IAAI,GAAW,EAAY,SAAC,EAAU,CAAK,MAAA,GAAU,SAAS,EAAa,EAAG,CAAU,CAA7C,EAAiD,CAAI,CACzG,CCrHM,YAAsB,EAAU,CACpC,MAAO,aAAiB,OAAQ,CAAC,MAAM,CAAY,CACrD,CCsCM,WAAoB,EAAyC,EAAa,CAC9E,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAEhC,GAAI,GAAQ,EAGZ,EAAO,UACL,EAAyB,EAAY,SAAC,EAAQ,CAG5C,EAAW,KAAK,EAAQ,KAAK,EAAS,EAAO,GAAO,CAAC,CACvD,CAAC,CAAC,CAEN,CAAC,CACH,CC1DQ,GAAA,IAAY,MAAK,QAEzB,YAA2B,EAA6B,EAAW,CAC/D,MAAO,IAAQ,CAAI,EAAI,EAAE,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAI,CAAA,CAAA,EAAI,EAAG,CAAI,CAChD,CAMM,YAAiC,EAA2B,CAC9D,MAAO,GAAI,SAAA,EAAI,CAAI,MAAA,IAAY,EAAI,CAAI,CAApB,CAAqB,CAC5C,CCfQ,GAAA,IAAY,MAAK,QACjB,GAA0D,OAAM,eAArC,GAA+B,OAAM,UAAlB,GAAY,OAAM,KAQlE,YAA+D,EAAuB,CAC1F,GAAI,EAAK,SAAW,EAAG,CACrB,GAAM,GAAQ,EAAK,GACnB,GAAI,GAAQ,CAAK,EACf,MAAO,CAAE,KAAM,EAAO,KAAM,IAAI,EAElC,GAAI,GAAO,CAAK,EAAG,CACjB,GAAM,GAAO,GAAQ,CAAK,EAC1B,MAAO,CACL,KAAM,EAAK,IAAI,SAAC,EAAG,CAAK,MAAA,GAAM,EAAN,CAAU,EAClC,KAAI,IAKV,MAAO,CAAE,KAAM,EAAa,KAAM,IAAI,CACxC,CAEA,YAAgB,EAAQ,CACtB,MAAO,IAAO,MAAO,IAAQ,UAAY,GAAe,CAAG,IAAM,EACnE,CC7BM,YAAuB,EAAgB,EAAa,CACxD,MAAO,GAAK,OAAO,SAAC,EAAQ,EAAK,EAAC,CAAK,MAAE,GAAO,GAAO,EAAO,GAAK,CAA5B,EAAqC,CAAA,CAAS,CACvF,CCsMM,YAAuB,QAAoC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GAC/D,GAAM,GAAY,GAAa,CAAI,EAC7B,EAAiB,GAAkB,CAAI,EAEvC,EAA8B,GAAqB,CAAI,EAA/C,EAAW,EAAA,KAAE,EAAI,EAAA,KAE/B,GAAI,EAAY,SAAW,EAIzB,MAAO,IAAK,CAAA,EAAI,CAAgB,EAGlC,GAAM,GAAS,GAAI,GACjB,GACE,EACA,EACA,EAEI,SAAC,EAAM,CAAK,MAAA,IAAa,EAAM,CAAM,CAAzB,EAEZ,EAAQ,CACb,EAGH,MAAO,GAAkB,EAAO,KAAK,GAAiB,CAAc,CAAC,EAAsB,CAC7F,CAEM,YACJ,EACA,EACA,EAAiD,CAAjD,MAAA,KAAA,QAAA,GAAA,IAEO,SAAC,EAA2B,CAGjC,GACE,EACA,UAAA,CAaE,OAZQ,GAAW,EAAW,OAExB,EAAS,GAAI,OAAM,CAAM,EAG3B,EAAS,EAIT,EAAuB,aAGlB,EAAC,CACR,GACE,EACA,UAAA,CACE,GAAM,GAAS,GAAK,EAAY,GAAI,CAAgB,EAChD,EAAgB,GACpB,EAAO,UACL,EACE,EACA,SAAC,EAAK,CAEJ,EAAO,GAAK,EACP,GAEH,GAAgB,GAChB,KAEG,GAGH,EAAW,KAAK,EAAe,EAAO,MAAK,CAAE,CAAC,CAElD,EACA,UAAA,CACE,AAAK,EAAE,GAGL,EAAW,SAAQ,CAEvB,CAAC,CACF,CAEL,EACA,CAAU,GAjCL,EAAI,EAAG,EAAI,EAAQ,MAAnB,CAAC,CAoCZ,EACA,CAAU,CAEd,CACF,CAMA,YAAuB,EAAsC,EAAqB,EAA0B,CAC1G,AAAI,EACF,GAAgB,EAAc,EAAW,CAAO,EAEhD,EAAO,CAEX,CC3RM,YACJ,EACA,EACA,EACA,EACA,EACA,EACA,EACA,EAAgC,CAGhC,GAAM,GAAc,CAAA,EAEhB,EAAS,EAET,EAAQ,EAER,EAAa,GAKX,EAAgB,UAAA,CAIpB,AAAI,GAAc,CAAC,EAAO,QAAU,CAAC,GACnC,EAAW,SAAQ,CAEvB,EAGM,EAAY,SAAC,EAAQ,CAAK,MAAC,GAAS,EAAa,EAAW,CAAK,EAAI,EAAO,KAAK,CAAK,CAA5D,EAE1B,EAAa,SAAC,EAAQ,CAI1B,GAAU,EAAW,KAAK,CAAY,EAItC,IAKA,GAAI,GAAgB,GAGpB,EAAU,EAAQ,EAAO,GAAO,CAAC,EAAE,UACjC,EACE,EACA,SAAC,EAAU,CAGT,GAAY,MAAZ,EAAe,CAAU,EAEzB,AAAI,EAGF,EAAU,CAAiB,EAG3B,EAAW,KAAK,CAAU,CAE9B,EACA,UAAA,CAGE,EAAgB,EAClB,EAEA,OACA,UAAA,CAIE,GAAI,EAKF,GAAI,CAIF,IAKA,qBACE,GAAM,GAAgB,EAAO,MAAK,EAIlC,AAAI,EACF,GAAgB,EAAY,EAAmB,UAAA,CAAM,MAAA,GAAW,CAAa,CAAxB,CAAyB,EAE9E,EAAW,CAAa,GARrB,EAAO,QAAU,EAAS,OAYjC,EAAa,QACN,EAAP,CACA,EAAW,MAAM,CAAG,EAG1B,CAAC,CACF,CAEL,EAGA,SAAO,UACL,EAAyB,EAAY,EAAW,UAAA,CAE9C,EAAa,GACb,EAAa,CACf,CAAC,CAAC,EAKG,UAAA,CACL,GAAmB,MAAnB,EAAmB,CACrB,CACF,CClEM,YACJ,EACA,EACA,EAA6B,CAE7B,MAFA,KAAA,QAAA,GAAA,KAEI,EAAW,CAAc,EAEpB,GAAS,SAAC,EAAG,EAAC,CAAK,MAAA,GAAI,SAAC,EAAQ,EAAU,CAAK,MAAA,GAAe,EAAG,EAAG,EAAG,CAAE,CAA1B,CAA2B,EAAE,EAAU,EAAQ,EAAG,CAAC,CAAC,CAAC,CAAjF,EAAoF,CAAU,EAC/G,OAAO,IAAmB,UACnC,GAAa,GAGR,EAAQ,SAAC,EAAQ,EAAU,CAAK,MAAA,IAAe,EAAQ,EAAY,EAAS,CAAU,CAAtD,CAAuD,EAChG,CChCM,YAAmD,EAA6B,CAA7B,MAAA,KAAA,QAAA,GAAA,KAChD,GAAS,GAAU,CAAU,CACtC,CCNM,aAAmB,CACvB,MAAO,IAAS,CAAC,CACnB,CCmDM,aAAgB,QAAC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACrB,MAAO,IAAS,EAAG,GAAK,EAAM,GAAa,CAAI,CAAC,CAAC,CACnD,CC9DM,WAAgD,EAA0B,CAC9E,MAAO,IAAI,GAA+B,SAAC,EAAU,CACnD,EAAU,EAAiB,CAAE,EAAE,UAAU,CAAU,CACrD,CAAC,CACH,CChDA,GAAM,IAA0B,CAAC,cAAe,gBAAgB,EAC1D,GAAqB,CAAC,mBAAoB,qBAAqB,EAC/D,GAAgB,CAAC,KAAM,KAAK,EA8N5B,WACJ,EACA,EACA,EACA,EAAsC,CAMtC,GAJI,EAAW,CAAO,GACpB,GAAiB,EACjB,EAAU,QAER,EACF,MAAO,GAAa,EAAQ,EAAW,CAA+B,EAAE,KAAK,GAAiB,CAAc,CAAC,EAUzG,GAAA,GAAA,EAEJ,GAAc,CAAM,EAChB,GAAmB,IAAI,SAAC,EAAU,CAAK,MAAA,UAAC,EAAY,CAAK,MAAA,GAAO,GAAY,EAAW,EAAS,CAA+B,CAAtE,CAAlB,CAAyF,EAElI,GAAwB,CAAM,EAC5B,GAAwB,IAAI,GAAwB,EAAQ,CAAS,CAAC,EACtE,GAA0B,CAAM,EAChC,GAAc,IAAI,GAAwB,EAAQ,CAAS,CAAC,EAC5D,CAAA,EAAE,CAAA,EATD,EAAG,EAAA,GAAE,EAAM,EAAA,GAgBlB,GAAI,CAAC,GACC,GAAY,CAAM,EACpB,MAAO,IAAS,SAAC,EAAc,CAAK,MAAA,GAAU,EAAW,EAAW,CAA+B,CAA/D,CAAgE,EAClG,EAAU,CAAM,CAAC,EAOvB,GAAI,CAAC,EACH,KAAM,IAAI,WAAU,sBAAsB,EAG5C,MAAO,IAAI,GAAc,SAAC,EAAU,CAIlC,GAAM,GAAU,UAAA,QAAC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GAAmB,MAAA,GAAW,KAAK,EAAI,EAAK,OAAS,EAAO,EAAK,EAAE,CAAhD,EAEpC,SAAI,CAAO,EAEJ,UAAA,CAAM,MAAA,GAAQ,CAAO,CAAf,CACf,CAAC,CACH,CASA,YAAiC,EAAa,EAAiB,CAC7D,MAAO,UAAC,EAAkB,CAAK,MAAA,UAAC,EAAY,CAAK,MAAA,GAAO,GAAY,EAAW,CAAO,CAArC,CAAlB,CACjC,CAOA,YAAiC,EAAW,CAC1C,MAAO,GAAW,EAAO,WAAW,GAAK,EAAW,EAAO,cAAc,CAC3E,CAOA,YAAmC,EAAW,CAC5C,MAAO,GAAW,EAAO,EAAE,GAAK,EAAW,EAAO,GAAG,CACvD,CAOA,YAAuB,EAAW,CAChC,MAAO,GAAW,EAAO,gBAAgB,GAAK,EAAW,EAAO,mBAAmB,CACrF,CC/LM,YACJ,EACA,EACA,EAAsC,CAEtC,MAAI,GACK,GAAoB,EAAY,CAAa,EAAE,KAAK,GAAiB,CAAc,CAAC,EAGtF,GAAI,GAAoB,SAAC,EAAU,CACxC,GAAM,GAAU,UAAA,QAAC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GAAc,MAAA,GAAW,KAAK,EAAE,SAAW,EAAI,EAAE,GAAK,CAAC,CAAzC,EACzB,EAAW,EAAW,CAAO,EACnC,MAAO,GAAW,CAAa,EAAI,UAAA,CAAM,MAAA,GAAc,EAAS,CAAQ,CAA/B,EAAmC,MAC9E,CAAC,CACH,CCtBM,YACJ,EACA,EACA,EAAyC,CAFzC,AAAA,IAAA,QAAA,GAAA,GAEA,IAAA,QAAA,GAAA,IAIA,GAAI,GAAmB,GAEvB,MAAI,IAAuB,MAIzB,CAAI,GAAY,CAAmB,EACjC,EAAY,EAIZ,EAAmB,GAIhB,GAAI,GAAW,SAAC,EAAU,CAI/B,GAAI,GAAM,GAAY,CAAO,EAAI,CAAC,EAAU,EAAW,IAAG,EAAK,EAE/D,AAAI,EAAM,GAER,GAAM,GAIR,GAAI,GAAI,EAGR,MAAO,GAAU,SAAS,UAAA,CACxB,AAAK,EAAW,QAEd,GAAW,KAAK,GAAG,EAEnB,AAAI,GAAK,EAGP,KAAK,SAAS,OAAW,CAAgB,EAGzC,EAAW,SAAQ,EAGzB,EAAG,CAAG,CACR,CAAC,CACH,CChGM,YAAe,QAAC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACpB,GAAM,GAAY,GAAa,CAAI,EAC7B,EAAa,GAAU,EAAM,GAAQ,EACrC,EAAU,EAChB,MAAO,AAAC,GAAQ,OAGZ,EAAQ,SAAW,EAEnB,EAAU,EAAQ,EAAE,EAEpB,GAAS,CAAU,EAAE,GAAK,EAAS,CAAS,CAAC,EAL7C,CAMN,CCjEO,GAAM,IAAQ,GAAI,GAAkB,EAAI,ECpCvC,GAAA,IAAY,MAAK,QAMnB,YAA4B,EAAiB,CACjD,MAAO,GAAK,SAAW,GAAK,GAAQ,EAAK,EAAE,EAAI,EAAK,GAAM,CAC5D,CCoDM,WAAoB,EAAiD,EAAa,CACtF,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAEhC,GAAI,GAAQ,EAIZ,EAAO,UAIL,EAAyB,EAAY,SAAC,EAAK,CAAK,MAAA,GAAU,KAAK,EAAS,EAAO,GAAO,GAAK,EAAW,KAAK,CAAK,CAAhE,CAAiE,CAAC,CAEtH,CAAC,CACH,CCxBM,aAAa,QAAC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GAClB,GAAM,GAAiB,GAAkB,CAAI,EAEvC,EAAU,GAAe,CAAI,EAEnC,MAAO,GAAQ,OACX,GAAI,GAAsB,SAAC,EAAU,CAGnC,GAAI,GAAuB,EAAQ,IAAI,UAAA,CAAM,MAAA,CAAA,CAAA,CAAE,EAK3C,EAAY,EAAQ,IAAI,UAAA,CAAM,MAAA,EAAA,CAAK,EAGvC,EAAW,IAAI,UAAA,CACb,EAAU,EAAY,IACxB,CAAC,EAKD,mBAAS,EAAW,CAClB,EAAU,EAAQ,EAAY,EAAE,UAC9B,EACE,EACA,SAAC,EAAK,CAKJ,GAJA,EAAQ,GAAa,KAAK,CAAK,EAI3B,EAAQ,MAAM,SAAC,EAAM,CAAK,MAAA,GAAO,MAAP,CAAa,EAAG,CAC5C,GAAM,GAAc,EAAQ,IAAI,SAAC,EAAM,CAAK,MAAA,GAAO,MAAK,CAAZ,CAAe,EAE3D,EAAW,KAAK,EAAiB,EAAc,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAM,CAAA,CAAA,EAAI,CAAM,EAI/D,EAAQ,KAAK,SAAC,EAAQ,EAAC,CAAK,MAAA,CAAC,EAAO,QAAU,EAAU,EAA5B,CAA8B,GAC5D,EAAW,SAAQ,EAGzB,EACA,UAAA,CAGE,EAAU,GAAe,GAIzB,CAAC,EAAQ,GAAa,QAAU,EAAW,SAAQ,CACrD,CAAC,CACF,GA9BI,EAAc,EAAG,CAAC,EAAW,QAAU,EAAc,EAAQ,OAAQ,MAArE,CAAW,EAmCpB,MAAO,WAAA,CACL,EAAU,EAAY,IACxB,CACF,CAAC,EACD,CACN,CC9DM,YAAmB,EAAoD,CAC3E,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAW,GACX,EAAsB,KACtB,EAA6C,KAC7C,EAAa,GAEX,EAAc,UAAA,CAGlB,GAFA,GAAkB,MAAlB,EAAoB,YAAW,EAC/B,EAAqB,KACjB,EAAU,CACZ,EAAW,GACX,GAAM,GAAQ,EACd,EAAY,KACZ,EAAW,KAAK,CAAK,EAEvB,GAAc,EAAW,SAAQ,CACnC,EAEM,EAAkB,UAAA,CACtB,EAAqB,KACrB,GAAc,EAAW,SAAQ,CACnC,EAEA,EAAO,UACL,EACE,EACA,SAAC,EAAK,CACJ,EAAW,GACX,EAAY,EACP,GACH,EAAU,EAAiB,CAAK,CAAC,EAAE,UAChC,EAAqB,EAAyB,EAAY,EAAa,CAAe,CAAE,CAG/F,EACA,UAAA,CACE,EAAa,GACZ,EAAC,GAAY,CAAC,GAAsB,EAAmB,SAAW,EAAW,SAAQ,CACxF,CAAC,CACF,CAEL,CAAC,CACH,CC3CM,YAAuB,EAAkB,EAAyC,CAAzC,MAAA,KAAA,QAAA,GAAA,IACtC,GAAM,UAAA,CAAM,MAAA,IAAM,EAAU,CAAS,CAAzB,CAA0B,CAC/C,CCEM,YAAyB,EAAoB,EAAsC,CAAtC,MAAA,KAAA,QAAA,GAAA,MAGjD,EAAmB,GAAgB,KAAhB,EAAoB,EAEhC,EAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAiB,CAAA,EACjB,EAAQ,EAEZ,EAAO,UACL,EACE,EACA,SAAC,EAAK,aACA,EAAuB,KAK3B,AAAI,IAAU,IAAsB,GAClC,EAAQ,KAAK,CAAA,CAAE,MAIjB,OAAqB,GAAA,GAAA,CAAO,EAAA,EAAA,EAAA,KAAA,EAAA,CAAA,EAAA,KAAA,EAAA,EAAA,KAAA,EAAE,CAAzB,GAAM,GAAM,EAAA,MACf,EAAO,KAAK,CAAK,EAMb,GAAc,EAAO,QACvB,GAAS,GAAM,KAAN,EAAU,CAAA,EACnB,EAAO,KAAK,CAAM,qGAItB,GAAI,MAIF,OAAqB,GAAA,GAAA,CAAM,EAAA,EAAA,EAAA,KAAA,EAAA,CAAA,EAAA,KAAA,EAAA,EAAA,KAAA,EAAE,CAAxB,GAAM,GAAM,EAAA,MACf,GAAU,EAAS,CAAM,EACzB,EAAW,KAAK,CAAM,oGAG5B,EACA,UAAA,aAGE,OAAqB,GAAA,GAAA,CAAO,EAAA,EAAA,EAAA,KAAA,EAAA,CAAA,EAAA,KAAA,EAAA,EAAA,KAAA,EAAE,CAAzB,GAAM,GAAM,EAAA,MACf,EAAW,KAAK,CAAM,oGAExB,EAAW,SAAQ,CACrB,EAEA,OACA,UAAA,CAEE,EAAU,IACZ,CAAC,CACF,CAEL,CAAC,CACH,CCbM,YACJ,EAAgD,CAEhD,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAgC,KAChC,EAAY,GACZ,EAEJ,EAAW,EAAO,UAChB,EAAyB,EAAY,OAAW,OAAW,SAAC,EAAG,CAC7D,EAAgB,EAAU,EAAS,EAAK,GAAW,CAAQ,EAAE,CAAM,CAAC,CAAC,EACrE,AAAI,EACF,GAAS,YAAW,EACpB,EAAW,KACX,EAAc,UAAU,CAAU,GAIlC,EAAY,EAEhB,CAAC,CAAC,EAGA,GAMF,GAAS,YAAW,EACpB,EAAW,KACX,EAAe,UAAU,CAAU,EAEvC,CAAC,CACH,CC/HM,YACJ,EACA,EACA,EACA,EACA,EAAqC,CAErC,MAAO,UAAC,EAAuB,EAA2B,CAIxD,GAAI,GAAW,EAIX,EAAa,EAEb,EAAQ,EAGZ,EAAO,UACL,EACE,EACA,SAAC,EAAK,CAEJ,GAAM,GAAI,IAEV,EAAQ,EAEJ,EAAY,EAAO,EAAO,CAAC,EAIzB,GAAW,GAAO,GAGxB,GAAc,EAAW,KAAK,CAAK,CACrC,EAGA,GACG,UAAA,CACC,GAAY,EAAW,KAAK,CAAK,EACjC,EAAW,SAAQ,CACrB,CAAE,CACL,CAEL,CACF,CCnCM,aAAuB,QAAO,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GAClC,GAAM,GAAiB,GAAkB,CAAI,EAC7C,MAAO,GACH,GAAK,GAAa,MAAA,OAAA,EAAA,CAAA,EAAA,EAAK,CAAoC,CAAA,CAAA,EAAG,GAAiB,CAAc,CAAC,EAC9F,EAAQ,SAAC,EAAQ,EAAU,CACzB,GAAiB,EAAA,CAAE,CAAM,EAAA,EAAK,GAAe,CAAI,CAAC,CAAA,CAAA,EAAG,CAAU,CACjE,CAAC,CACP,CCUM,aAA2B,QAC/B,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GAEA,MAAO,IAAa,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAY,CAAA,CAAA,CACtC,CC+BM,YACJ,EACA,EAA6G,CAE7G,MAAO,GAAW,CAAc,EAAI,GAAS,EAAS,EAAgB,CAAC,EAAI,GAAS,EAAS,CAAC,CAChG,CCpBM,YAA0B,EAAiB,EAAyC,CAAzC,MAAA,KAAA,QAAA,GAAA,IACxC,EAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAkC,KAClC,EAAsB,KACtB,EAA0B,KAExB,EAAO,UAAA,CACX,GAAI,EAAY,CAEd,EAAW,YAAW,EACtB,EAAa,KACb,GAAM,GAAQ,EACd,EAAY,KACZ,EAAW,KAAK,CAAK,EAEzB,EACA,YAAqB,CAInB,GAAM,GAAa,EAAY,EACzB,EAAM,EAAU,IAAG,EACzB,GAAI,EAAM,EAAY,CAEpB,EAAa,KAAK,SAAS,OAAW,EAAa,CAAG,EACtD,EAAW,IAAI,CAAU,EACzB,OAGF,EAAI,CACN,CAEA,EAAO,UACL,EACE,EACA,SAAC,EAAQ,CACP,EAAY,EACZ,EAAW,EAAU,IAAG,EAGnB,GACH,GAAa,EAAU,SAAS,EAAc,CAAO,EACrD,EAAW,IAAI,CAAU,EAE7B,EACA,UAAA,CAGE,EAAI,EACJ,EAAW,SAAQ,CACrB,EAEA,OACA,UAAA,CAEE,EAAY,EAAa,IAC3B,CAAC,CACF,CAEL,CAAC,CACH,CCpFM,YAA+B,EAAe,CAClD,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAW,GACf,EAAO,UACL,EACE,EACA,SAAC,EAAK,CACJ,EAAW,GACX,EAAW,KAAK,CAAK,CACvB,EACA,UAAA,CACE,AAAK,GACH,EAAW,KAAK,CAAa,EAE/B,EAAW,SAAQ,CACrB,CAAC,CACF,CAEL,CAAC,CACH,CCXM,YAAkB,EAAa,CACnC,MAAO,IAAS,EAEZ,UAAA,CAAM,MAAA,EAAA,EACN,EAAQ,SAAC,EAAQ,EAAU,CACzB,GAAI,GAAO,EACX,EAAO,UACL,EAAyB,EAAY,SAAC,EAAK,CAIzC,AAAI,EAAE,GAAQ,GACZ,GAAW,KAAK,CAAK,EAIjB,GAAS,GACX,EAAW,SAAQ,EAGzB,CAAC,CAAC,CAEN,CAAC,CACP,CC9BM,aAAwB,CAC5B,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,EAAO,UAAU,EAAyB,EAAY,EAAI,CAAC,CAC7D,CAAC,CACH,CCCM,YAAmB,EAAQ,CAC/B,MAAO,GAAI,UAAA,CAAM,MAAA,EAAA,CAAK,CACxB,CC2BM,YACJ,EACA,EAAmC,CAEnC,MAAI,GAEK,SAAC,EAAqB,CAC3B,MAAA,IAAO,EAAkB,KAAK,GAAK,CAAC,EAAG,GAAc,CAAE,EAAG,EAAO,KAAK,GAAU,CAAqB,CAAC,CAAC,CAAvG,EAGG,GAAS,SAAC,EAAO,EAAK,CAAK,MAAA,GAAsB,EAAO,CAAK,EAAE,KAAK,GAAK,CAAC,EAAG,GAAM,CAAK,CAAC,CAA9D,CAA+D,CACnG,CCxBM,YAAmB,EAAoB,EAAyC,CAAzC,AAAA,IAAA,QAAA,GAAA,IAC3C,GAAM,GAAW,GAAM,EAAK,CAAS,EACrC,MAAO,IAAU,UAAA,CAAM,MAAA,EAAA,CAAQ,CACjC,CC4EM,WACJ,EACA,EAA0D,CAA1D,MAAA,KAAA,QAAA,GAA+B,IAK/B,EAAa,GAAU,KAAV,EAAc,GAEpB,EAAQ,SAAC,EAAQ,EAAU,CAGhC,GAAI,GAEA,EAAQ,GAEZ,EAAO,UACL,EAAyB,EAAY,SAAC,EAAK,CAEzC,GAAM,GAAa,EAAY,CAAK,EAKpC,AAAI,IAAS,CAAC,EAAY,EAAa,CAAU,IAM/C,GAAQ,GACR,EAAc,EAGd,EAAW,KAAK,CAAK,EAEzB,CAAC,CAAC,CAEN,CAAC,CACH,CAEA,YAAwB,EAAQ,EAAM,CACpC,MAAO,KAAM,CACf,CCnHM,WAAwD,EAAQ,EAAuC,CAC3G,MAAO,GAAqB,SAAC,EAAM,EAAI,CAAK,MAAA,GAAU,EAAQ,EAAE,GAAM,EAAE,EAAI,EAAI,EAAE,KAAS,EAAE,EAAjD,CAAqD,CACnG,CCLM,aAAiB,QAAI,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACzB,MAAO,UAAC,EAAqB,CAAK,MAAA,IAAO,EAAQ,EAAE,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAM,CAAA,CAAA,CAAA,CAA3B,CACpC,CCHM,WAAsB,EAAoB,CAC9C,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAGhC,GAAI,CACF,EAAO,UAAU,CAAU,UAE3B,EAAW,IAAI,CAAQ,EAE3B,CAAC,CACH,CC9BM,YAAsB,EAAa,CACvC,MAAO,IAAS,EACZ,UAAA,CAAM,MAAA,EAAA,EACN,EAAQ,SAAC,EAAQ,EAAU,CAKzB,GAAI,GAAc,CAAA,EAClB,EAAO,UACL,EACE,EACA,SAAC,EAAK,CAEJ,EAAO,KAAK,CAAK,EAGjB,EAAQ,EAAO,QAAU,EAAO,MAAK,CACvC,EACA,UAAA,aAGE,OAAoB,GAAA,GAAA,CAAM,EAAA,EAAA,EAAA,KAAA,EAAA,CAAA,EAAA,KAAA,EAAA,EAAA,KAAA,EAAE,CAAvB,GAAM,GAAK,EAAA,MACd,EAAW,KAAK,CAAK,oGAEvB,EAAW,SAAQ,CACrB,EAEA,OACA,UAAA,CAEE,EAAS,IACX,CAAC,CACF,CAEL,CAAC,CACP,CC1DM,aAAe,QAAI,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACvB,GAAM,GAAY,GAAa,CAAI,EAC7B,EAAa,GAAU,EAAM,GAAQ,EAC3C,SAAO,GAAe,CAAI,EAEnB,EAAQ,SAAC,EAAQ,EAAU,CAChC,GAAS,CAAU,EAAE,GAAI,EAAA,CAAE,CAAM,EAAA,EAAM,CAA6B,CAAA,EAAG,CAAS,CAAC,EAAE,UAAU,CAAU,CACzG,CAAC,CACH,CCcM,aAAmB,QACvB,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GAEA,MAAO,IAAK,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAY,CAAA,CAAA,CAC9B,CCmEM,YAAoB,EAAqC,OACzD,EAAQ,IACR,EAEJ,MAAI,IAAiB,MACnB,CAAI,MAAO,IAAkB,SACxB,GAA4B,EAAa,MAAzC,EAAK,IAAA,OAAG,IAAQ,EAAE,EAAU,EAAa,OAE5C,EAAQ,GAIL,GAAS,EACZ,UAAA,CAAM,MAAA,EAAA,EACN,EAAQ,SAAC,EAAQ,EAAU,CACzB,GAAI,GAAQ,EACR,EAEE,EAAc,UAAA,CAGlB,GAFA,GAAS,MAAT,EAAW,YAAW,EACtB,EAAY,KACR,GAAS,KAAM,CACjB,GAAM,GAAW,MAAO,IAAU,SAAW,GAAM,CAAK,EAAI,EAAU,EAAM,CAAK,CAAC,EAC5E,EAAqB,EAAyB,EAAY,UAAA,CAC9D,EAAmB,YAAW,EAC9B,EAAiB,CACnB,CAAC,EACD,EAAS,UAAU,CAAkB,MAErC,GAAiB,CAErB,EAEM,EAAoB,UAAA,CACxB,GAAI,GAAY,GAChB,EAAY,EAAO,UACjB,EAAyB,EAAY,OAAW,UAAA,CAC9C,AAAI,EAAE,EAAQ,EACZ,AAAI,EACF,EAAW,EAEX,EAAY,GAGd,EAAW,SAAQ,CAEvB,CAAC,CAAC,EAGA,GACF,EAAW,CAEf,EAEA,EAAiB,CACnB,CAAC,CACP,CC7HM,YAAoB,EAAyB,CACjD,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAW,GACX,EAAsB,KAC1B,EAAO,UACL,EAAyB,EAAY,SAAC,EAAK,CACzC,EAAW,GACX,EAAY,CACd,CAAC,CAAC,EAEJ,EAAS,UACP,EACE,EACA,UAAA,CACE,GAAI,EAAU,CACZ,EAAW,GACX,GAAM,GAAQ,EACd,EAAY,KACZ,EAAW,KAAK,CAAK,EAEzB,EACA,EAAI,CACL,CAEL,CAAC,CACH,CCgBM,YAAwB,EAA6D,EAAQ,CAMjG,MAAO,GAAQ,GAAc,EAAa,EAAW,UAAU,QAAU,EAAG,EAAI,CAAC,CACnF,CCiDM,YAAmB,EAA4B,CAA5B,AAAA,IAAA,QAAA,GAAA,CAAA,GACf,GAAA,GAAgH,EAAO,UAAvH,EAAS,IAAA,OAAG,UAAA,CAAM,MAAA,IAAI,EAAJ,EAAgB,EAAE,EAA4E,EAAO,aAAnF,EAAY,IAAA,OAAG,GAAI,EAAE,EAAuD,EAAO,gBAA9D,EAAe,IAAA,OAAG,GAAI,EAAE,EAA+B,EAAO,oBAAtC,EAAmB,IAAA,OAAG,GAAI,EAUnH,MAAO,UAAC,EAAa,CACnB,GAAI,GAAuC,KACvC,EAAuC,KACvC,EAAiC,KACjC,EAAW,EACX,EAAe,GACf,EAAa,GAEX,EAAc,UAAA,CAClB,GAAe,MAAf,EAAiB,YAAW,EAC5B,EAAkB,IACpB,EAGM,EAAQ,UAAA,CACZ,EAAW,EACX,EAAa,EAAU,KACvB,EAAe,EAAa,EAC9B,EACM,EAAsB,UAAA,CAG1B,GAAM,GAAO,EACb,EAAK,EACL,GAAI,MAAJ,EAAM,YAAW,CACnB,EAEA,MAAO,GAAc,SAAC,EAAQ,GAAU,CACtC,IACI,CAAC,GAAc,CAAC,GAClB,EAAW,EAOb,GAAM,IAAQ,EAAU,GAAO,KAAP,EAAW,EAAS,EAO5C,GAAW,IAAI,UAAA,CACb,IAKI,IAAa,GAAK,CAAC,GAAc,CAAC,GACpC,GAAkB,GAAY,EAAqB,CAAmB,EAE1E,CAAC,EAID,GAAK,UAAU,EAAU,EAEpB,GAMH,GAAa,GAAI,IAAe,CAC9B,KAAM,SAAC,GAAK,CAAK,MAAA,IAAK,KAAK,EAAK,CAAf,EACjB,MAAO,SAAC,GAAG,CACT,EAAa,GACb,EAAW,EACX,EAAkB,GAAY,EAAO,EAAc,EAAG,EACtD,GAAK,MAAM,EAAG,CAChB,EACA,SAAU,UAAA,CACR,EAAe,GACf,EAAW,EACX,EAAkB,GAAY,EAAO,CAAe,EACpD,GAAK,SAAQ,CACf,EACD,EACD,GAAK,CAAM,EAAE,UAAU,CAAU,EAErC,CAAC,EAAE,CAAa,CAClB,CACF,CAEA,YACE,EACA,EAA+C,QAC/C,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,EAAA,GAAA,UAAA,GAEA,MAAI,KAAO,GACT,GAAK,EAEE,MAGL,IAAO,GACF,KAGF,EAAE,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAI,CAAA,CAAA,EACd,KAAK,GAAK,CAAC,CAAC,EACZ,UAAU,UAAA,CAAM,MAAA,GAAK,CAAL,CAAO,CAC5B,CCzGM,WACJ,EACA,EACA,EAAyB,WAErB,EACA,EAAW,GACf,MAAI,IAAsB,MAAO,IAAuB,SACnD,GAA8E,EAAkB,WAAhG,EAAU,IAAA,OAAG,IAAQ,EAAE,EAAuD,EAAkB,WAAzE,EAAU,IAAA,OAAG,IAAQ,EAAE,EAAgC,EAAkB,SAAlD,EAAQ,IAAA,OAAG,GAAK,EAAE,EAAc,EAAkB,WAEnG,EAAa,GAAkB,KAAlB,EAAsB,IAE9B,GAAS,CACd,UAAW,UAAA,CAAM,MAAA,IAAI,IAAc,EAAY,EAAY,CAAS,CAAnD,EACjB,aAAc,GACd,gBAAiB,GACjB,oBAAqB,EACtB,CACH,CCvIM,YAAkB,EAAa,CACnC,MAAO,GAAO,SAAC,EAAG,EAAK,CAAK,MAAA,IAAS,CAAT,CAAc,CAC5C,CCWM,YAAuB,EAAyB,CACpD,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAS,GAEP,EAAiB,EACrB,EACA,UAAA,CACE,GAAc,MAAd,EAAgB,YAAW,EAC3B,EAAS,EACX,EACA,EAAI,EAGN,EAAU,CAAQ,EAAE,UAAU,CAAc,EAE5C,EAAO,UAAU,EAAyB,EAAY,SAAC,EAAK,CAAK,MAAA,IAAU,EAAW,KAAK,CAAK,CAA/B,CAAgC,CAAC,CACpG,CAAC,CACH,CCRM,YAAmB,QAAO,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GAC9B,GAAM,GAAY,GAAa,CAAM,EACrC,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAIhC,AAAC,GAAY,GAAO,EAAQ,EAAQ,CAAS,EAAI,GAAO,EAAQ,CAAM,GAAG,UAAU,CAAU,CAC/F,CAAC,CACH,CCmBM,WACJ,EACA,EAA6G,CAE7G,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAyD,KACzD,EAAQ,EAER,EAAa,GAIX,EAAgB,UAAA,CAAM,MAAA,IAAc,CAAC,GAAmB,EAAW,SAAQ,CAArD,EAE5B,EAAO,UACL,EACE,EACA,SAAC,EAAK,CAEJ,GAAe,MAAf,EAAiB,YAAW,EAC5B,GAAI,GAAa,EACX,EAAa,IAEnB,EAAU,EAAQ,EAAO,CAAU,CAAC,EAAE,UACnC,EAAkB,EACjB,EAIA,SAAC,EAAU,CAAK,MAAA,GAAW,KAAK,EAAiB,EAAe,EAAO,EAAY,EAAY,GAAY,EAAI,CAAU,CAAzG,EAChB,UAAA,CAIE,EAAkB,KAClB,EAAa,CACf,CAAC,CACD,CAEN,EACA,UAAA,CACE,EAAa,GACb,EAAa,CACf,CAAC,CACF,CAEL,CAAC,CACH,CCvFM,YAAuB,EAA8B,CACzD,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,EAAU,CAAQ,EAAE,UAAU,EAAyB,EAAY,UAAA,CAAM,MAAA,GAAW,SAAQ,CAAnB,EAAuB,EAAI,CAAC,EACrG,CAAC,EAAW,QAAU,EAAO,UAAU,CAAU,CACnD,CAAC,CACH,CCIM,YAAuB,EAAiD,EAAiB,CAAjB,MAAA,KAAA,QAAA,GAAA,IACrE,EAAQ,SAAC,EAAQ,EAAU,CAChC,GAAI,GAAQ,EACZ,EAAO,UACL,EAAyB,EAAY,SAAC,EAAK,CACzC,GAAM,GAAS,EAAU,EAAO,GAAO,EACvC,AAAC,IAAU,IAAc,EAAW,KAAK,CAAK,EAC9C,CAAC,GAAU,EAAW,SAAQ,CAChC,CAAC,CAAC,CAEN,CAAC,CACH,CCyCM,WACJ,EACA,EACA,EAA8B,CAK9B,GAAM,GACJ,EAAW,CAAc,GAAK,GAAS,EAElC,CAAE,KAAM,EAA2E,MAAK,EAAE,SAAQ,CAAA,EACnG,EAEN,MAAO,GACH,EAAQ,SAAC,EAAQ,EAAU,OACzB,AAAA,GAAA,EAAY,aAAS,MAAA,IAAA,QAAA,EAAA,KAArB,CAAW,EACX,GAAI,GAAU,GACd,EAAO,UACL,EACE,EACA,SAAC,EAAK,OACJ,AAAA,GAAA,EAAY,QAAI,MAAA,IAAA,QAAA,EAAA,KAAhB,EAAmB,CAAK,EACxB,EAAW,KAAK,CAAK,CACvB,EACA,UAAA,OACE,EAAU,GACV,GAAA,EAAY,YAAQ,MAAA,IAAA,QAAA,EAAA,KAApB,CAAW,EACX,EAAW,SAAQ,CACrB,EACA,SAAC,EAAG,OACF,EAAU,GACV,GAAA,EAAY,SAAK,MAAA,IAAA,QAAA,EAAA,KAAjB,EAAoB,CAAG,EACvB,EAAW,MAAM,CAAG,CACtB,EACA,UAAA,SACE,AAAI,GACF,IAAA,EAAY,eAAW,MAAA,IAAA,QAAA,EAAA,KAAvB,CAAW,GAEb,GAAA,EAAY,YAAQ,MAAA,IAAA,QAAA,EAAA,KAApB,CAAW,CACb,CAAC,CACF,CAEL,CAAC,EAID,EACN,CC9IO,GAAM,IAAwC,CACnD,QAAS,GACT,SAAU,IAiDN,YACJ,EACA,EAA8C,CAA9C,MAAA,KAAA,QAAA,GAAA,IAEO,EAAQ,SAAC,EAAQ,EAAU,CACxB,GAAA,GAAsB,EAAM,QAAnB,EAAa,EAAM,SAChC,EAAW,GACX,EAAsB,KACtB,EAAiC,KACjC,EAAa,GAEX,EAAgB,UAAA,CACpB,GAAS,MAAT,EAAW,YAAW,EACtB,EAAY,KACR,GACF,GAAI,EACJ,GAAc,EAAW,SAAQ,EAErC,EAEM,EAAoB,UAAA,CACxB,EAAY,KACZ,GAAc,EAAW,SAAQ,CACnC,EAEM,EAAgB,SAAC,EAAQ,CAC7B,MAAC,GAAY,EAAU,EAAiB,CAAK,CAAC,EAAE,UAAU,EAAyB,EAAY,EAAe,CAAiB,CAAC,CAAhI,EAEI,EAAO,UAAA,CACX,GAAI,EAAU,CAIZ,EAAW,GACX,GAAM,GAAQ,EACd,EAAY,KAEZ,EAAW,KAAK,CAAK,EACrB,CAAC,GAAc,EAAc,CAAK,EAEtC,EAEA,EAAO,UACL,EACE,EAMA,SAAC,EAAK,CACJ,EAAW,GACX,EAAY,EACZ,CAAE,IAAa,CAAC,EAAU,SAAY,GAAU,EAAI,EAAK,EAAc,CAAK,EAC9E,EACA,UAAA,CACE,EAAa,GACb,CAAE,IAAY,GAAY,GAAa,CAAC,EAAU,SAAW,EAAW,SAAQ,CAClF,CAAC,CACF,CAEL,CAAC,CACH,CCvEM,YACJ,EACA,EACA,EAA8B,CAD9B,AAAA,IAAA,QAAA,GAAA,IACA,IAAA,QAAA,GAAA,IAEA,GAAM,GAAY,GAAM,EAAU,CAAS,EAC3C,MAAO,IAAS,UAAA,CAAM,MAAA,EAAA,EAAW,CAAM,CACzC,CCJM,aAAwB,QAAO,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACnC,GAAM,GAAU,GAAkB,CAAM,EAExC,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAehC,OAdM,GAAM,EAAO,OACb,EAAc,GAAI,OAAM,CAAG,EAI7B,EAAW,EAAO,IAAI,UAAA,CAAM,MAAA,EAAA,CAAK,EAGjC,EAAQ,cAMH,EAAC,CACR,EAAU,EAAO,EAAE,EAAE,UACnB,EACE,EACA,SAAC,EAAK,CACJ,EAAY,GAAK,EACb,CAAC,GAAS,CAAC,EAAS,IAEtB,GAAS,GAAK,GAKb,GAAQ,EAAS,MAAM,EAAQ,IAAO,GAAW,MAEtD,EAGA,EAAI,CACL,GAnBI,EAAI,EAAG,EAAI,EAAK,MAAhB,CAAC,EAwBV,EAAO,UACL,EAAyB,EAAY,SAAC,EAAK,CACzC,GAAI,EAAO,CAET,GAAM,GAAM,EAAA,CAAI,CAAK,EAAA,EAAK,CAAW,CAAA,EACrC,EAAW,KAAK,EAAU,EAAO,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAM,CAAA,CAAA,EAAI,CAAM,EAEzD,CAAC,CAAC,CAEN,CAAC,CACH,CCxFM,aAAa,QAAO,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACxB,MAAO,GAAQ,SAAC,EAAQ,EAAU,CAChC,GAAS,MAAA,OAAA,EAAA,CAAC,CAA8B,EAAA,EAAM,CAAuC,CAAA,CAAA,EAAE,UAAU,CAAU,CAC7G,CAAC,CACH,CCCM,aAAiB,QAAkC,GAAA,CAAA,EAAA,EAAA,EAAA,EAAA,UAAA,OAAA,IAAA,EAAA,GAAA,UAAA,GACvD,MAAO,IAAG,MAAA,OAAA,EAAA,CAAA,EAAA,EAAI,CAAW,CAAA,CAAA,CAC3B,CCYO,aAA4C,CACjD,GAAM,GAAY,GAAI,IAAwB,CAAC,EAC/C,SAAU,SAAU,mBAAoB,CAAE,KAAM,EAAK,CAAC,EACnD,UAAU,IAAM,EAAU,KAAK,QAAQ,CAAC,EAGpC,CACT,CCHO,WACL,EAAkB,EAAmB,SAChC,CACL,MAAO,OAAM,KAAK,EAAK,iBAAoB,CAAQ,CAAC,CACtD,CAuBO,WACL,EAAkB,EAAmB,SAClC,CACH,GAAM,GAAK,GAAsB,EAAU,CAAI,EAC/C,GAAI,MAAO,IAAO,YAChB,KAAM,IAAI,gBACR,8BAA8B,kBAChC,EAGF,MAAO,EACT,CAsBO,YACL,EAAkB,EAAmB,SACtB,CACf,MAAO,GAAK,cAAiB,CAAQ,GAAK,MAC5C,CAOO,aAAqD,CAC1D,MAAO,UAAS,wBAAyB,cACrC,SAAS,eAAiB,MAEhC,CClEO,YACL,EACqB,CACrB,MAAO,GACL,EAAU,SAAS,KAAM,SAAS,EAClC,EAAU,SAAS,KAAM,UAAU,CACrC,EACG,KACC,GAAa,CAAC,EACd,EAAI,IAAM,CACR,GAAM,GAAS,GAAiB,EAChC,MAAO,OAAO,IAAW,YACrB,EAAG,SAAS,CAAM,EAClB,EACN,CAAC,EACD,EAAU,IAAO,GAAiB,CAAC,EACnC,EAAqB,CACvB,CACJ,CChBO,YACL,EACe,CACf,MAAO,CACL,EAAG,EAAG,WACN,EAAG,EAAG,SACR,CACF,CAWO,YACL,EAC2B,CAC3B,MAAO,GACL,EAAU,OAAQ,MAAM,EACxB,EAAU,OAAQ,QAAQ,CAC5B,EACG,KACC,GAAU,EAAG,EAAuB,EACpC,EAAI,IAAM,GAAiB,CAAE,CAAC,EAC9B,EAAU,GAAiB,CAAE,CAAC,CAChC,CACJ,CCxCO,YACL,EACe,CACf,MAAO,CACL,EAAG,EAAG,WACN,EAAG,EAAG,SACR,CACF,CAWO,YACL,EAC2B,CAC3B,MAAO,GACL,EAAU,EAAI,QAAQ,EACtB,EAAU,OAAQ,QAAQ,CAC5B,EACG,KACC,GAAU,EAAG,EAAuB,EACpC,EAAI,IAAM,GAAwB,CAAE,CAAC,EACrC,EAAU,GAAwB,CAAE,CAAC,CACvC,CACJ,CCpEA,GAAI,IAAW,UAAY,CACvB,GAAI,MAAO,MAAQ,YACf,MAAO,KASX,WAAkB,EAAK,EAAK,CACxB,GAAI,GAAS,GACb,SAAI,KAAK,SAAU,EAAO,EAAO,CAC7B,MAAI,GAAM,KAAO,EACb,GAAS,EACF,IAEJ,EACX,CAAC,EACM,CACX,CACA,MAAsB,WAAY,CAC9B,YAAmB,CACf,KAAK,YAAc,CAAC,CACxB,CACA,cAAO,eAAe,EAAQ,UAAW,OAAQ,CAI7C,IAAK,UAAY,CACb,MAAO,MAAK,YAAY,MAC5B,EACA,WAAY,GACZ,aAAc,EAClB,CAAC,EAKD,EAAQ,UAAU,IAAM,SAAU,EAAK,CACnC,GAAI,GAAQ,EAAS,KAAK,YAAa,CAAG,EACtC,EAAQ,KAAK,YAAY,GAC7B,MAAO,IAAS,EAAM,EAC1B,EAMA,EAAQ,UAAU,IAAM,SAAU,EAAK,EAAO,CAC1C,GAAI,GAAQ,EAAS,KAAK,YAAa,CAAG,EAC1C,AAAI,CAAC,EACD,KAAK,YAAY,GAAO,GAAK,EAG7B,KAAK,YAAY,KAAK,CAAC,EAAK,CAAK,CAAC,CAE1C,EAKA,EAAQ,UAAU,OAAS,SAAU,EAAK,CACtC,GAAI,GAAU,KAAK,YACf,EAAQ,EAAS,EAAS,CAAG,EACjC,AAAI,CAAC,GACD,EAAQ,OAAO,EAAO,CAAC,CAE/B,EAKA,EAAQ,UAAU,IAAM,SAAU,EAAK,CACnC,MAAO,CAAC,CAAC,CAAC,EAAS,KAAK,YAAa,CAAG,CAC5C,EAIA,EAAQ,UAAU,MAAQ,UAAY,CAClC,KAAK,YAAY,OAAO,CAAC,CAC7B,EAMA,EAAQ,UAAU,QAAU,SAAU,EAAU,EAAK,CACjD,AAAI,IAAQ,QAAU,GAAM,MAC5B,OAAS,GAAK,EAAG,EAAK,KAAK,YAAa,EAAK,EAAG,OAAQ,IAAM,CAC1D,GAAI,GAAQ,EAAG,GACf,EAAS,KAAK,EAAK,EAAM,GAAI,EAAM,EAAE,CACzC,CACJ,EACO,CACX,EAAE,CACN,EAAG,EAKC,GAAY,MAAO,SAAW,aAAe,MAAO,WAAa,aAAe,OAAO,WAAa,SAGpG,GAAY,UAAY,CACxB,MAAI,OAAO,SAAW,aAAe,OAAO,OAAS,KAC1C,OAEP,MAAO,OAAS,aAAe,KAAK,OAAS,KACtC,KAEP,MAAO,SAAW,aAAe,OAAO,OAAS,KAC1C,OAGJ,SAAS,aAAa,EAAE,CACnC,EAAG,EAQC,GAA2B,UAAY,CACvC,MAAI,OAAO,wBAA0B,WAI1B,sBAAsB,KAAK,EAAQ,EAEvC,SAAU,EAAU,CAAE,MAAO,YAAW,UAAY,CAAE,MAAO,GAAS,KAAK,IAAI,CAAC,CAAG,EAAG,IAAO,EAAE,CAAG,CAC7G,EAAG,EAGC,GAAkB,EAStB,YAAmB,EAAU,EAAO,CAChC,GAAI,GAAc,GAAO,EAAe,GAAO,EAAe,EAO9D,YAA0B,CACtB,AAAI,GACA,GAAc,GACd,EAAS,GAET,GACA,EAAM,CAEd,CAQA,YAA2B,CACvB,GAAwB,CAAc,CAC1C,CAMA,YAAiB,CACb,GAAI,GAAY,KAAK,IAAI,EACzB,GAAI,EAAa,CAEb,GAAI,EAAY,EAAe,GAC3B,OAMJ,EAAe,EACnB,KAEI,GAAc,GACd,EAAe,GACf,WAAW,EAAiB,CAAK,EAErC,EAAe,CACnB,CACA,MAAO,EACX,CAGA,GAAI,IAAgB,GAGhB,GAAiB,CAAC,MAAO,QAAS,SAAU,OAAQ,QAAS,SAAU,OAAQ,QAAQ,EAEvF,GAA4B,MAAO,mBAAqB,YAIxD,GAA0C,UAAY,CAMtD,YAAoC,CAMhC,KAAK,WAAa,GAMlB,KAAK,qBAAuB,GAM5B,KAAK,mBAAqB,KAM1B,KAAK,WAAa,CAAC,EACnB,KAAK,iBAAmB,KAAK,iBAAiB,KAAK,IAAI,EACvD,KAAK,QAAU,GAAS,KAAK,QAAQ,KAAK,IAAI,EAAG,EAAa,CAClE,CAOA,SAAyB,UAAU,YAAc,SAAU,EAAU,CACjE,AAAK,CAAC,KAAK,WAAW,QAAQ,CAAQ,GAClC,KAAK,WAAW,KAAK,CAAQ,EAG5B,KAAK,YACN,KAAK,SAAS,CAEtB,EAOA,EAAyB,UAAU,eAAiB,SAAU,EAAU,CACpE,GAAI,GAAY,KAAK,WACjB,EAAQ,EAAU,QAAQ,CAAQ,EAEtC,AAAI,CAAC,GACD,EAAU,OAAO,EAAO,CAAC,EAGzB,CAAC,EAAU,QAAU,KAAK,YAC1B,KAAK,YAAY,CAEzB,EAOA,EAAyB,UAAU,QAAU,UAAY,CACrD,GAAI,GAAkB,KAAK,iBAAiB,EAG5C,AAAI,GACA,KAAK,QAAQ,CAErB,EASA,EAAyB,UAAU,iBAAmB,UAAY,CAE9D,GAAI,GAAkB,KAAK,WAAW,OAAO,SAAU,EAAU,CAC7D,MAAO,GAAS,aAAa,EAAG,EAAS,UAAU,CACvD,CAAC,EAMD,SAAgB,QAAQ,SAAU,EAAU,CAAE,MAAO,GAAS,gBAAgB,CAAG,CAAC,EAC3E,EAAgB,OAAS,CACpC,EAOA,EAAyB,UAAU,SAAW,UAAY,CAGtD,AAAI,CAAC,IAAa,KAAK,YAMvB,UAAS,iBAAiB,gBAAiB,KAAK,gBAAgB,EAChE,OAAO,iBAAiB,SAAU,KAAK,OAAO,EAC9C,AAAI,GACA,MAAK,mBAAqB,GAAI,kBAAiB,KAAK,OAAO,EAC3D,KAAK,mBAAmB,QAAQ,SAAU,CACtC,WAAY,GACZ,UAAW,GACX,cAAe,GACf,QAAS,EACb,CAAC,GAGD,UAAS,iBAAiB,qBAAsB,KAAK,OAAO,EAC5D,KAAK,qBAAuB,IAEhC,KAAK,WAAa,GACtB,EAOA,EAAyB,UAAU,YAAc,UAAY,CAGzD,AAAI,CAAC,IAAa,CAAC,KAAK,YAGxB,UAAS,oBAAoB,gBAAiB,KAAK,gBAAgB,EACnE,OAAO,oBAAoB,SAAU,KAAK,OAAO,EAC7C,KAAK,oBACL,KAAK,mBAAmB,WAAW,EAEnC,KAAK,sBACL,SAAS,oBAAoB,qBAAsB,KAAK,OAAO,EAEnE,KAAK,mBAAqB,KAC1B,KAAK,qBAAuB,GAC5B,KAAK,WAAa,GACtB,EAQA,EAAyB,UAAU,iBAAmB,SAAU,EAAI,CAChE,GAAI,GAAK,EAAG,aAAc,EAAe,IAAO,OAAS,GAAK,EAE1D,EAAmB,GAAe,KAAK,SAAU,EAAK,CACtD,MAAO,CAAC,CAAC,CAAC,EAAa,QAAQ,CAAG,CACtC,CAAC,EACD,AAAI,GACA,KAAK,QAAQ,CAErB,EAMA,EAAyB,YAAc,UAAY,CAC/C,MAAK,MAAK,WACN,MAAK,UAAY,GAAI,IAElB,KAAK,SAChB,EAMA,EAAyB,UAAY,KAC9B,CACX,EAAE,EASE,GAAsB,SAAU,EAAQ,EAAO,CAC/C,OAAS,GAAK,EAAG,EAAK,OAAO,KAAK,CAAK,EAAG,EAAK,EAAG,OAAQ,IAAM,CAC5D,GAAI,GAAM,EAAG,GACb,OAAO,eAAe,EAAQ,EAAK,CAC/B,MAAO,EAAM,GACb,WAAY,GACZ,SAAU,GACV,aAAc,EAClB,CAAC,CACL,CACA,MAAO,EACX,EAQI,GAAe,SAAU,EAAQ,CAIjC,GAAI,GAAc,GAAU,EAAO,eAAiB,EAAO,cAAc,YAGzE,MAAO,IAAe,EAC1B,EAGI,GAAY,GAAe,EAAG,EAAG,EAAG,CAAC,EAOzC,YAAiB,EAAO,CACpB,MAAO,YAAW,CAAK,GAAK,CAChC,CAQA,YAAwB,EAAQ,CAE5B,OADI,GAAY,CAAC,EACR,EAAK,EAAG,EAAK,UAAU,OAAQ,IACpC,EAAU,EAAK,GAAK,UAAU,GAElC,MAAO,GAAU,OAAO,SAAU,EAAM,EAAU,CAC9C,GAAI,GAAQ,EAAO,UAAY,EAAW,UAC1C,MAAO,GAAO,GAAQ,CAAK,CAC/B,EAAG,CAAC,CACR,CAOA,YAAqB,EAAQ,CAGzB,OAFI,GAAY,CAAC,MAAO,QAAS,SAAU,MAAM,EAC7C,EAAW,CAAC,EACP,EAAK,EAAG,EAAc,EAAW,EAAK,EAAY,OAAQ,IAAM,CACrE,GAAI,GAAW,EAAY,GACvB,EAAQ,EAAO,WAAa,GAChC,EAAS,GAAY,GAAQ,CAAK,CACtC,CACA,MAAO,EACX,CAQA,YAA2B,EAAQ,CAC/B,GAAI,GAAO,EAAO,QAAQ,EAC1B,MAAO,IAAe,EAAG,EAAG,EAAK,MAAO,EAAK,MAAM,CACvD,CAOA,YAAmC,EAAQ,CAGvC,GAAI,GAAc,EAAO,YAAa,EAAe,EAAO,aAS5D,GAAI,CAAC,GAAe,CAAC,EACjB,MAAO,IAEX,GAAI,GAAS,GAAY,CAAM,EAAE,iBAAiB,CAAM,EACpD,EAAW,GAAY,CAAM,EAC7B,EAAW,EAAS,KAAO,EAAS,MACpC,EAAU,EAAS,IAAM,EAAS,OAKlC,EAAQ,GAAQ,EAAO,KAAK,EAAG,EAAS,GAAQ,EAAO,MAAM,EAqBjE,GAlBI,EAAO,YAAc,cAOjB,MAAK,MAAM,EAAQ,CAAQ,IAAM,GACjC,IAAS,GAAe,EAAQ,OAAQ,OAAO,EAAI,GAEnD,KAAK,MAAM,EAAS,CAAO,IAAM,GACjC,IAAU,GAAe,EAAQ,MAAO,QAAQ,EAAI,IAOxD,CAAC,GAAkB,CAAM,EAAG,CAK5B,GAAI,GAAgB,KAAK,MAAM,EAAQ,CAAQ,EAAI,EAC/C,EAAiB,KAAK,MAAM,EAAS,CAAO,EAAI,EAMpD,AAAI,KAAK,IAAI,CAAa,IAAM,GAC5B,IAAS,GAET,KAAK,IAAI,CAAc,IAAM,GAC7B,IAAU,EAElB,CACA,MAAO,IAAe,EAAS,KAAM,EAAS,IAAK,EAAO,CAAM,CACpE,CAOA,GAAI,IAAwB,UAAY,CAGpC,MAAI,OAAO,qBAAuB,YACvB,SAAU,EAAQ,CAAE,MAAO,aAAkB,IAAY,CAAM,EAAE,kBAAoB,EAKzF,SAAU,EAAQ,CAAE,MAAQ,aAAkB,IAAY,CAAM,EAAE,YACrE,MAAO,GAAO,SAAY,UAAa,CAC/C,EAAG,EAOH,YAA2B,EAAQ,CAC/B,MAAO,KAAW,GAAY,CAAM,EAAE,SAAS,eACnD,CAOA,YAAwB,EAAQ,CAC5B,MAAK,IAGD,GAAqB,CAAM,EACpB,GAAkB,CAAM,EAE5B,GAA0B,CAAM,EAL5B,EAMf,CAQA,YAA4B,EAAI,CAC5B,GAAI,GAAI,EAAG,EAAG,EAAI,EAAG,EAAG,EAAQ,EAAG,MAAO,EAAS,EAAG,OAElD,EAAS,MAAO,kBAAoB,YAAc,gBAAkB,OACpE,EAAO,OAAO,OAAO,EAAO,SAAS,EAEzC,UAAmB,EAAM,CACrB,EAAG,EAAG,EAAG,EAAG,MAAO,EAAO,OAAQ,EAClC,IAAK,EACL,MAAO,EAAI,EACX,OAAQ,EAAS,EACjB,KAAM,CACV,CAAC,EACM,CACX,CAWA,YAAwB,EAAG,EAAG,EAAO,EAAQ,CACzC,MAAO,CAAE,EAAG,EAAG,EAAG,EAAG,MAAO,EAAO,OAAQ,CAAO,CACtD,CAMA,GAAI,IAAmC,UAAY,CAM/C,WAA2B,EAAQ,CAM/B,KAAK,eAAiB,EAMtB,KAAK,gBAAkB,EAMvB,KAAK,aAAe,GAAe,EAAG,EAAG,EAAG,CAAC,EAC7C,KAAK,OAAS,CAClB,CAOA,SAAkB,UAAU,SAAW,UAAY,CAC/C,GAAI,GAAO,GAAe,KAAK,MAAM,EACrC,YAAK,aAAe,EACZ,EAAK,QAAU,KAAK,gBACxB,EAAK,SAAW,KAAK,eAC7B,EAOA,EAAkB,UAAU,cAAgB,UAAY,CACpD,GAAI,GAAO,KAAK,aAChB,YAAK,eAAiB,EAAK,MAC3B,KAAK,gBAAkB,EAAK,OACrB,CACX,EACO,CACX,EAAE,EAEE,GAAqC,UAAY,CAOjD,WAA6B,EAAQ,EAAU,CAC3C,GAAI,GAAc,GAAmB,CAAQ,EAO7C,GAAmB,KAAM,CAAE,OAAQ,EAAQ,YAAa,CAAY,CAAC,CACzE,CACA,MAAO,EACX,EAAE,EAEE,GAAmC,UAAY,CAW/C,WAA2B,EAAU,EAAY,EAAa,CAc1D,GAPA,KAAK,oBAAsB,CAAC,EAM5B,KAAK,cAAgB,GAAI,IACrB,MAAO,IAAa,WACpB,KAAM,IAAI,WAAU,yDAAyD,EAEjF,KAAK,UAAY,EACjB,KAAK,YAAc,EACnB,KAAK,aAAe,CACxB,CAOA,SAAkB,UAAU,QAAU,SAAU,EAAQ,CACpD,GAAI,CAAC,UAAU,OACX,KAAM,IAAI,WAAU,0CAA0C,EAGlE,GAAI,QAAO,UAAY,aAAe,CAAE,mBAAmB,UAG3D,IAAI,CAAE,aAAkB,IAAY,CAAM,EAAE,SACxC,KAAM,IAAI,WAAU,uCAAuC,EAE/D,GAAI,GAAe,KAAK,cAExB,AAAI,EAAa,IAAI,CAAM,GAG3B,GAAa,IAAI,EAAQ,GAAI,IAAkB,CAAM,CAAC,EACtD,KAAK,YAAY,YAAY,IAAI,EAEjC,KAAK,YAAY,QAAQ,GAC7B,EAOA,EAAkB,UAAU,UAAY,SAAU,EAAQ,CACtD,GAAI,CAAC,UAAU,OACX,KAAM,IAAI,WAAU,0CAA0C,EAGlE,GAAI,QAAO,UAAY,aAAe,CAAE,mBAAmB,UAG3D,IAAI,CAAE,aAAkB,IAAY,CAAM,EAAE,SACxC,KAAM,IAAI,WAAU,uCAAuC,EAE/D,GAAI,GAAe,KAAK,cAExB,AAAI,CAAC,EAAa,IAAI,CAAM,GAG5B,GAAa,OAAO,CAAM,EACrB,EAAa,MACd,KAAK,YAAY,eAAe,IAAI,GAE5C,EAMA,EAAkB,UAAU,WAAa,UAAY,CACjD,KAAK,YAAY,EACjB,KAAK,cAAc,MAAM,EACzB,KAAK,YAAY,eAAe,IAAI,CACxC,EAOA,EAAkB,UAAU,aAAe,UAAY,CACnD,GAAI,GAAQ,KACZ,KAAK,YAAY,EACjB,KAAK,cAAc,QAAQ,SAAU,EAAa,CAC9C,AAAI,EAAY,SAAS,GACrB,EAAM,oBAAoB,KAAK,CAAW,CAElD,CAAC,CACL,EAOA,EAAkB,UAAU,gBAAkB,UAAY,CAEtD,GAAI,EAAC,KAAK,UAAU,EAGpB,IAAI,GAAM,KAAK,aAEX,EAAU,KAAK,oBAAoB,IAAI,SAAU,EAAa,CAC9D,MAAO,IAAI,IAAoB,EAAY,OAAQ,EAAY,cAAc,CAAC,CAClF,CAAC,EACD,KAAK,UAAU,KAAK,EAAK,EAAS,CAAG,EACrC,KAAK,YAAY,EACrB,EAMA,EAAkB,UAAU,YAAc,UAAY,CAClD,KAAK,oBAAoB,OAAO,CAAC,CACrC,EAMA,EAAkB,UAAU,UAAY,UAAY,CAChD,MAAO,MAAK,oBAAoB,OAAS,CAC7C,EACO,CACX,EAAE,EAKE,GAAY,MAAO,UAAY,YAAc,GAAI,SAAY,GAAI,IAKjE,GAAgC,UAAY,CAO5C,WAAwB,EAAU,CAC9B,GAAI,CAAE,gBAAgB,IAClB,KAAM,IAAI,WAAU,oCAAoC,EAE5D,GAAI,CAAC,UAAU,OACX,KAAM,IAAI,WAAU,0CAA0C,EAElE,GAAI,GAAa,GAAyB,YAAY,EAClD,EAAW,GAAI,IAAkB,EAAU,EAAY,IAAI,EAC/D,GAAU,IAAI,KAAM,CAAQ,CAChC,CACA,MAAO,EACX,EAAE,EAEF,CACI,UACA,YACA,YACJ,EAAE,QAAQ,SAAU,EAAQ,CACxB,GAAe,UAAU,GAAU,UAAY,CAC3C,GAAI,GACJ,MAAQ,GAAK,GAAU,IAAI,IAAI,GAAG,GAAQ,MAAM,EAAI,SAAS,CACjE,CACJ,CAAC,EAED,GAAI,IAAS,UAAY,CAErB,MAAI,OAAO,IAAS,gBAAmB,YAC5B,GAAS,eAEb,EACX,EAAG,EAEI,GAAQ,GCr2Bf,GAAM,IAAS,GAAI,GAYb,GAAY,EAAM,IAAM,EAC5B,GAAI,IAAe,GAAW,CAC5B,OAAW,KAAS,GAClB,GAAO,KAAK,CAAK,CACrB,CAAC,CACH,CAAC,EACE,KACC,EAAU,GAAY,EAAM,GAAO,EAAG,CAAQ,CAAC,EAC5C,KACC,EAAS,IAAM,EAAS,WAAW,CAAC,CACtC,CACF,EACA,EAAY,CAAC,CACf,EAaK,YACL,EACa,CACb,MAAO,CACL,MAAQ,EAAG,YACX,OAAQ,EAAG,YACb,CACF,CAuBO,YACL,EACyB,CACzB,MAAO,IACJ,KACC,EAAI,GAAY,EAAS,QAAQ,CAAE,CAAC,EACpC,EAAU,GAAY,GACnB,KACC,EAAO,CAAC,CAAE,YAAa,IAAW,CAAE,EACpC,EAAS,IAAM,EAAS,UAAU,CAAE,CAAC,EACrC,EAAI,IAAM,GAAe,CAAE,CAAC,CAC9B,CACF,EACA,EAAU,GAAe,CAAE,CAAC,CAC9B,CACJ,CC1GO,YACL,EACa,CACb,MAAO,CACL,MAAQ,EAAG,YACX,OAAQ,EAAG,YACb,CACF,CCSA,GAAM,IAAS,GAAI,GAUb,GAAY,EAAM,IAAM,EAC5B,GAAI,sBAAqB,GAAW,CAClC,OAAW,KAAS,GAClB,GAAO,KAAK,CAAK,CACrB,EAAG,CACD,UAAW,CACb,CAAC,CACH,CAAC,EACE,KACC,EAAU,GAAY,EAAM,GAAO,EAAG,CAAQ,CAAC,EAC5C,KACC,EAAS,IAAM,EAAS,WAAW,CAAC,CACtC,CACF,EACA,EAAY,CAAC,CACf,EAaK,YACL,EACqB,CACrB,MAAO,IACJ,KACC,EAAI,GAAY,EAAS,QAAQ,CAAE,CAAC,EACpC,EAAU,GAAY,GACnB,KACC,EAAO,CAAC,CAAE,YAAa,IAAW,CAAE,EACpC,EAAS,IAAM,EAAS,UAAU,CAAE,CAAC,EACrC,EAAI,CAAC,CAAE,oBAAqB,CAAc,CAC5C,CACF,CACF,CACJ,CAaO,YACL,EAAiB,EAAY,GACR,CACrB,MAAO,IAA0B,CAAE,EAChC,KACC,EAAI,CAAC,CAAE,OAAQ,CACb,GAAM,GAAU,GAAe,CAAE,EAC3B,EAAU,GAAsB,CAAE,EACxC,MAAO,IACL,EAAQ,OAAS,EAAQ,OAAS,CAEtC,CAAC,EACD,EAAqB,CACvB,CACJ,CCjFA,GAAM,IAA4C,CAChD,OAAQ,EAAW,yBAAyB,EAC5C,OAAQ,EAAW,yBAAyB,CAC9C,EAaO,YAAmB,EAAuB,CAC/C,MAAO,IAAQ,GAAM,OACvB,CAaO,YAAmB,EAAc,EAAsB,CAC5D,AAAI,GAAQ,GAAM,UAAY,GAC5B,GAAQ,GAAM,MAAM,CACxB,CAWO,YAAqB,EAAmC,CAC7D,GAAM,GAAK,GAAQ,GACnB,MAAO,GAAU,EAAI,QAAQ,EAC1B,KACC,EAAI,IAAM,EAAG,OAAO,EACpB,EAAU,EAAG,OAAO,CACtB,CACJ,CClCA,YACE,EAAiB,EACR,CACT,OAAQ,EAAG,iBAGJ,kBAEH,MAAI,GAAG,OAAS,QACP,SAAS,KAAK,CAAI,EAElB,OAGN,uBACA,qBACH,MAAO,WAIP,MAAO,GAAG,kBAEhB,CAWO,aAA+C,CACpD,MAAO,GAAyB,OAAQ,SAAS,EAC9C,KACC,EAAO,GAAM,CAAE,GAAG,SAAW,EAAG,QAAQ,EACxC,EAAI,GAAO,EACT,KAAM,GAAU,QAAQ,EAAI,SAAW,SACvC,KAAM,EAAG,IACT,OAAQ,CACN,EAAG,eAAe,EAClB,EAAG,gBAAgB,CACrB,CACF,EAAc,EACd,EAAO,CAAC,CAAE,OAAM,UAAW,CACzB,GAAI,IAAS,SAAU,CACrB,GAAM,GAAS,GAAiB,EAChC,GAAI,MAAO,IAAW,YACpB,MAAO,CAAC,GAAwB,EAAQ,CAAI,CAChD,CACA,MAAO,EACT,CAAC,EACD,GAAM,CACR,CACJ,CCpFO,aAA4B,CACjC,MAAO,IAAI,KAAI,SAAS,IAAI,CAC9B,CAOO,YAAqB,EAAgB,CAC1C,SAAS,KAAO,EAAI,IACtB,CASO,aAAuC,CAC5C,MAAO,IAAI,EACb,CCLA,YAAqB,EAAiB,EAA8B,CAGlE,GAAI,MAAO,IAAU,UAAY,MAAO,IAAU,SAChD,EAAG,WAAa,EAAM,SAAS,UAGtB,YAAiB,MAC1B,EAAG,YAAY,CAAK,UAGX,MAAM,QAAQ,CAAK,EAC5B,OAAW,KAAQ,GACjB,GAAY,EAAI,CAAI,CAE1B,CAyBO,WACL,EAAa,KAAmC,EAC7C,CACH,GAAM,GAAK,SAAS,cAAc,CAAG,EAGrC,GAAI,EACF,OAAW,KAAQ,QAAO,KAAK,CAAU,EACvC,AAAI,MAAO,GAAW,IAAU,UAC9B,EAAG,aAAa,EAAM,EAAW,EAAK,EAC/B,EAAW,IAClB,EAAG,aAAa,EAAM,EAAE,EAG9B,OAAW,KAAS,GAClB,GAAY,EAAI,CAAK,EAGvB,MAAO,EACT,CC3EO,YAAkB,EAAe,EAAmB,CACzD,GAAI,GAAI,EACR,GAAI,EAAM,OAAS,EAAG,CACpB,KAAO,EAAM,KAAO,KAAO,EAAE,EAAI,GAAG,CACpC,MAAO,GAAG,EAAM,UAAU,EAAG,CAAC,MAChC,CACA,MAAO,EACT,CAkBO,YAAe,EAAuB,CAC3C,GAAI,EAAQ,IAAK,CACf,GAAM,GAAS,CAAG,IAAQ,KAAO,IAAO,IACxC,MAAO,GAAK,IAAQ,MAAY,KAAM,QAAQ,CAAM,IACtD,KACE,OAAO,GAAM,SAAS,CAE1B,CC5BO,aAAmC,CACxC,MAAO,UAAS,KAAK,UAAU,CAAC,CAClC,CAYO,YAAyB,EAAoB,CAClD,GAAM,GAAK,EAAE,IAAK,CAAE,KAAM,CAAK,CAAC,EAChC,EAAG,iBAAiB,QAAS,GAAM,EAAG,gBAAgB,CAAC,EACvD,EAAG,MAAM,CACX,CASO,aAAiD,CACtD,MAAO,GAA2B,OAAQ,YAAY,EACnD,KACC,EAAI,EAAe,EACnB,EAAU,GAAgB,CAAC,EAC3B,EAAO,GAAQ,EAAK,OAAS,CAAC,EAC9B,EAAY,CAAC,CACf,CACJ,CAOO,aAAwD,CAC7D,MAAO,IAAkB,EACtB,KACC,EAAI,GAAM,GAAmB,QAAQ,KAAM,CAAE,EAC7C,EAAO,GAAM,MAAO,IAAO,WAAW,CACxC,CACJ,CC1CO,YAAoB,EAAoC,CAC7D,GAAM,GAAQ,WAAW,CAAK,EAC9B,MAAO,IAA0B,GAC/B,EAAM,YAAY,IAAM,EAAK,EAAM,OAAO,CAAC,CAC5C,EACE,KACC,EAAU,EAAM,OAAO,CACzB,CACJ,CAOO,aAA2C,CAChD,GAAM,GAAQ,WAAW,OAAO,EAChC,MAAO,GACL,EAAU,OAAQ,aAAa,EAAE,KAAK,EAAI,IAAM,EAAI,CAAC,EACrD,EAAU,OAAQ,YAAY,EAAE,KAAK,EAAI,IAAM,EAAK,CAAC,CACvD,EACG,KACC,EAAU,EAAM,OAAO,CACzB,CACJ,CAcO,YACL,EAA6B,EACd,CACf,MAAO,GACJ,KACC,EAAU,GAAU,EAAS,EAAQ,EAAI,CAAK,CAChD,CACJ,CC7CO,YACL,EAAmB,EAAuB,CAAE,YAAa,aAAc,EACjD,CACtB,MAAO,IAAK,MAAM,GAAG,IAAO,CAAO,CAAC,EACjC,KACC,GAAW,IAAM,CAAK,EACtB,EAAU,GAAO,EAAI,SAAW,IAC5B,GAAW,IAAM,GAAI,OAAM,EAAI,UAAU,CAAC,EAC1C,EAAG,CAAG,CACV,CACF,CACJ,CAYO,YACL,EAAmB,EACJ,CACf,MAAO,IAAQ,EAAK,CAAO,EACxB,KACC,EAAU,GAAO,EAAI,KAAK,CAAC,EAC3B,EAAY,CAAC,CACf,CACJ,CAUO,YACL,EAAmB,EACG,CACtB,GAAM,GAAM,GAAI,WAChB,MAAO,IAAQ,EAAK,CAAO,EACxB,KACC,EAAU,GAAO,EAAI,KAAK,CAAC,EAC3B,EAAI,GAAO,EAAI,gBAAgB,EAAK,UAAU,CAAC,EAC/C,EAAY,CAAC,CACf,CACJ,CClDO,YAAqB,EAA+B,CACzD,GAAM,GAAS,EAAE,SAAU,CAAE,KAAI,CAAC,EAClC,MAAO,GAAM,IACX,UAAS,KAAK,YAAY,CAAM,EACzB,EACL,EAAU,EAAQ,MAAM,EACxB,EAAU,EAAQ,OAAO,EACtB,KACC,EAAU,IACR,GAAW,IAAM,GAAI,gBAAe,mBAAmB,GAAK,CAAC,CAC9D,CACH,CACJ,EACG,KACC,EAAI,IAAG,EAAY,EACnB,EAAS,IAAM,SAAS,KAAK,YAAY,CAAM,CAAC,EAChD,GAAK,CAAC,CACR,EACH,CACH,CCfO,aAA6C,CAClD,MAAO,CACL,EAAG,KAAK,IAAI,EAAG,OAAO,EACtB,EAAG,KAAK,IAAI,EAAG,OAAO,CACxB,CACF,CASO,aAA2D,CAChE,MAAO,GACL,EAAU,OAAQ,SAAU,CAAE,QAAS,EAAK,CAAC,EAC7C,EAAU,OAAQ,SAAU,CAAE,QAAS,EAAK,CAAC,CAC/C,EACG,KACC,EAAI,EAAiB,EACrB,EAAU,GAAkB,CAAC,CAC/B,CACJ,CC3BO,aAAyC,CAC9C,MAAO,CACL,MAAQ,WACR,OAAQ,WACV,CACF,CASO,aAAuD,CAC5D,MAAO,GAAU,OAAQ,SAAU,CAAE,QAAS,EAAK,CAAC,EACjD,KACC,EAAI,EAAe,EACnB,EAAU,GAAgB,CAAC,CAC7B,CACJ,CCXO,aAA+C,CACpD,MAAO,GAAc,CACnB,GAAoB,EACpB,GAAkB,CACpB,CAAC,EACE,KACC,EAAI,CAAC,CAAC,EAAQ,KAAW,EAAE,SAAQ,MAAK,EAAE,EAC1C,EAAY,CAAC,CACf,CACJ,CCVO,YACL,EAAiB,CAAE,YAAW,WACR,CACtB,GAAM,GAAQ,EACX,KACC,EAAwB,MAAM,CAChC,EAGI,EAAU,EAAc,CAAC,EAAO,CAAO,CAAC,EAC3C,KACC,EAAI,IAAM,GAAiB,CAAE,CAAC,CAChC,EAGF,MAAO,GAAc,CAAC,EAAS,EAAW,CAAO,CAAC,EAC/C,KACC,EAAI,CAAC,CAAC,CAAE,UAAU,CAAE,SAAQ,QAAQ,CAAE,IAAG,QAAU,EACjD,OAAQ,CACN,EAAG,EAAO,EAAI,EACd,EAAG,EAAO,EAAI,EAAI,CACpB,EACA,MACF,EAAE,CACJ,CACJ,CCIO,YACL,EAAgB,CAAE,OACH,CAGf,GAAM,GAAM,EAAwB,EAAQ,SAAS,EAClD,KACC,EAAI,CAAC,CAAE,UAAW,CAAS,CAC7B,EAGF,MAAO,GACJ,KACC,GAAS,IAAM,EAAK,CAAE,QAAS,GAAM,SAAU,EAAK,CAAC,EACrD,EAAI,GAAW,EAAO,YAAY,CAAO,CAAC,EAC1C,EAAU,IAAM,CAAG,EACnB,GAAM,CACR,CACJ,CCJA,GAAM,IAAS,EAAW,WAAW,EAC/B,GAAiB,KAAK,MAAM,GAAO,WAAY,EACrD,GAAO,KAAO,GAAG,GAAI,KAAI,GAAO,KAAM,GAAY,CAAC,IAW5C,aAAiC,CACtC,MAAO,GACT,CASO,YAAiB,EAAqB,CAC3C,MAAO,IAAO,SAAS,SAAS,CAAI,CACtC,CAUO,WACL,EAAkB,EACV,CACR,MAAO,OAAO,IAAU,YACpB,GAAO,aAAa,GAAK,QAAQ,IAAK,EAAM,SAAS,CAAC,EACtD,GAAO,aAAa,EAC1B,CC9BO,YACL,EAAS,EAAmB,SACP,CACrB,MAAO,GAAW,sBAAsB,KAAS,CAAI,CACvD,CAYO,YACL,EAAS,EAAmB,SACL,CACvB,MAAO,GAAY,sBAAsB,KAAS,CAAI,CACxD,CC/GA,OAAwB,SCajB,YAA0B,EAAyB,CACxD,MACE,GAAC,SAAM,MAAM,gBAAgB,SAAU,GACrC,EAAC,OAAI,MAAM,mCACT,EAAC,OAAI,MAAM,+BAA+B,CAC5C,EACA,EAAC,QAAK,MAAM,wBACV,EAAC,QAAK,wBAAuB,EAAI,CACnC,CACF,CAEJ,CCVO,YAA+B,EAAyB,CAC7D,MACE,GAAC,UACC,MAAM,uBACN,MAAO,EAAY,gBAAgB,EACnC,wBAAuB,IAAI,WAC5B,CAEL,CCYA,YACE,EAA2C,EAC9B,CACb,GAAM,GAAS,EAAO,EAChB,EAAS,EAAO,EAGhB,EAAU,OAAO,KAAK,EAAS,KAAK,EACvC,OAAO,GAAO,CAAC,EAAS,MAAM,EAAI,EAClC,OAAyB,CAAC,EAAM,IAAQ,CACvC,GAAG,EAAM,EAAC,WAAK,CAAI,EAAQ,GAC7B,EAAG,CAAC,CAAC,EACJ,MAAM,EAAG,EAAE,EAGR,EAAM,GAAI,KAAI,EAAS,QAAQ,EACrC,MAAI,IAAQ,kBAAkB,GAC5B,EAAI,aAAa,IAAI,IAAK,OAAO,QAAQ,EAAS,KAAK,EACpD,OAAO,CAAC,CAAC,CAAE,KAAW,CAAK,EAC3B,OAAO,CAAC,EAAW,CAAC,KAAW,GAAG,KAAa,IAAQ,KAAK,EAAG,EAAE,CACpE,EAIA,EAAC,KAAE,KAAM,GAAG,IAAO,MAAM,yBAAyB,SAAU,IAC1D,EAAC,WACC,MAAO,CAAC,4BAA6B,GAAG,EACpC,CAAC,qCAAqC,EACtC,CAAC,CACL,EAAE,KAAK,GAAG,EACV,gBAAe,EAAS,MAAM,QAAQ,CAAC,GAEtC,EAAS,GAAK,EAAC,OAAI,MAAM,iCAAiC,EAC3D,EAAC,MAAG,MAAM,2BAA2B,EAAS,KAAM,EACnD,EAAS,GAAK,EAAS,KAAK,OAAS,GACpC,EAAC,KAAE,MAAM,4BACN,GAAS,EAAS,KAAM,GAAG,CAC9B,EAED,EAAS,MAAQ,EAAS,KAAK,IAAI,GAClC,EAAC,QAAK,MAAM,UAAU,CAAI,CAC3B,EACA,EAAS,GAAK,EAAQ,OAAS,GAC9B,EAAC,KAAE,MAAM,2BACN,EAAY,4BAA4B,EAAE,KAAM,CACnD,CAEJ,CACF,CAEJ,CAaO,YACL,EACa,CACb,GAAM,GAAY,EAAO,GAAG,MACtB,EAAO,CAAC,GAAG,CAAM,EAGjB,EAAS,EAAK,UAAU,GAAO,CAAC,EAAI,SAAS,SAAS,GAAG,CAAC,EAC1D,CAAC,GAAW,EAAK,OAAO,EAAQ,CAAC,EAGnC,EAAQ,EAAK,UAAU,GAAO,EAAI,MAAQ,CAAS,EACvD,AAAI,IAAU,IACZ,GAAQ,EAAK,QAGf,GAAM,GAAO,EAAK,MAAM,EAAG,CAAK,EAC1B,EAAO,EAAK,MAAM,CAAK,EAGvB,EAAW,CACf,GAAqB,EAAS,EAAc,CAAE,EAAC,GAAU,IAAU,EAAE,EACrE,GAAG,EAAK,IAAI,GAAW,GAAqB,EAAS,CAAW,CAAC,EACjE,GAAG,EAAK,OAAS,CACf,EAAC,WAAQ,MAAM,0BACb,EAAC,WAAQ,SAAU,IAChB,EAAK,OAAS,GAAK,EAAK,SAAW,EAChC,EAAY,wBAAwB,EACpC,EAAY,2BAA4B,EAAK,MAAM,CAEzD,EACI,EAAK,IAAI,GAAW,GAAqB,EAAS,CAAW,CAAC,CACpE,CACF,EAAI,CAAC,CACP,EAGA,MACE,GAAC,MAAG,MAAM,0BACP,CACH,CAEJ,CC7HO,YAA2B,EAAiC,CACjE,MACE,GAAC,MAAG,MAAM,oBACP,OAAO,QAAQ,CAAK,EAAE,IAAI,CAAC,CAAC,EAAK,KAChC,EAAC,MAAG,MAAO,oCAAoC,KAC5C,MAAO,IAAU,SAAW,GAAM,CAAK,EAAI,CAC9C,CACD,CACH,CAEJ,CCXO,YAAqB,EAAiC,CAC3D,MACE,GAAC,OAAI,MAAM,0BACT,EAAC,OAAI,MAAM,qBACR,CACH,CACF,CAEJ,CCMA,YAAuB,EAA+B,CACpD,GAAM,GAAS,GAAc,EAGvB,EAAM,GAAI,KAAI,MAAM,EAAQ,WAAY,EAAO,IAAI,EACzD,MACE,GAAC,MAAG,MAAM,oBACR,EAAC,KAAE,KAAM,EAAI,SAAS,EAAG,MAAM,oBAC5B,EAAQ,KACX,CACF,CAEJ,CAcO,YACL,EAAqB,EACR,CACb,MACE,GAAC,OAAI,MAAM,cACT,EAAC,UACC,MAAM,sBACN,aAAY,EAAY,sBAAsB,GAE7C,EAAO,KACV,EACA,EAAC,MAAG,MAAM,oBACP,EAAS,IAAI,EAAa,CAC7B,CACF,CAEJ,CClBO,YACL,EAAiB,EACO,CACxB,GAAM,GAAU,EAAM,IAAM,EAAc,CACxC,GAAmB,CAAE,EACrB,GAA0B,CAAS,CACrC,CAAC,CAAC,EACC,KACC,EAAI,CAAC,CAAC,CAAE,IAAG,KAAK,KAAY,CAC1B,GAAM,CAAE,SAAU,GAAe,CAAE,EACnC,MAAQ,CACN,EAAG,EAAI,EAAO,EAAI,EAAQ,EAC1B,EAAG,EAAI,EAAO,CAChB,CACF,CAAC,CACH,EAGF,MAAO,IAAkB,CAAE,EACxB,KACC,EAAU,GAAU,EACjB,KACC,EAAI,GAAW,EAAE,SAAQ,QAAO,EAAE,EAClC,GAAK,CAAC,CAAC,GAAU,GAAQ,CAC3B,CACF,CACF,CACJ,CAUO,YACL,EAAiB,EACkB,CACnC,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,EAAM,UAAU,CAGd,KAAK,CAAE,UAAU,CACf,EAAG,MAAM,YAAY,iBAAkB,GAAG,EAAO,KAAK,EACtD,EAAG,MAAM,YAAY,iBAAkB,GAAG,EAAO,KAAK,CACxD,EAGA,UAAW,CACT,EAAG,MAAM,eAAe,gBAAgB,EACxC,EAAG,MAAM,eAAe,gBAAgB,CAC1C,CACF,CAAC,EAGD,EACG,KACC,GAAa,IAAK,EAAuB,EACzC,EAAI,IAAM,EAAU,sBAAsB,CAAC,EAC3C,EAAI,CAAC,CAAE,OAAQ,CAAC,CAClB,EACG,UAAU,CAGT,KAAK,EAAQ,CACX,AAAI,EACF,EAAG,MAAM,YAAY,iBAAkB,GAAG,CAAC,KAAU,EAErD,EAAG,MAAM,eAAe,gBAAgB,CAC5C,EAGA,UAAW,CACT,EAAG,MAAM,eAAe,gBAAgB,CAC1C,CACF,CAAC,EAGL,GAAM,GAAQ,EAAW,uBAAwB,CAAE,EAC7C,EAAQ,EAAU,EAAO,YAAa,CAAE,KAAM,EAAK,CAAC,EAC1D,SACG,KACC,EAAU,CAAC,CAAE,YAAa,EAAS,EAAQ,CAAK,EAChD,EAAI,GAAM,EAAG,eAAe,CAAC,CAC/B,EACG,UAAU,IAAM,EAAG,KAAK,CAAC,EAGvB,GAAgB,EAAI,CAAS,EACjC,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CCtGA,YAA+B,EAAgC,CAC7D,GAAM,GAAkB,CAAC,EACzB,OAAW,KAAW,GAAY,eAAgB,CAAS,EAAG,CAC5D,GAAI,GAGA,EAAO,EAAQ,WACnB,GAAI,YAAgB,MAClB,KAAQ,EAAQ,YAAY,KAAK,EAAK,WAAY,GAAI,CACpD,GAAM,GAAS,EAAK,UAAU,EAAM,KAAK,EACzC,EAAO,EAAO,UAAU,EAAM,GAAG,MAAM,EACvC,EAAQ,KAAK,CAAM,CACrB,CACJ,CACA,MAAO,EACT,CAQA,YAAc,EAAqB,EAA2B,CAC5D,EAAO,OAAO,GAAG,MAAM,KAAK,EAAO,UAAU,CAAC,CAChD,CAoBO,YACL,EAAiB,EAAwB,CAAE,UACR,CAGnC,GAAM,GAAc,GAAI,KACxB,OAAW,KAAU,IAAsB,CAAS,EAAG,CACrD,GAAM,CAAC,CAAE,GAAM,EAAO,YAAa,MAAM,WAAW,EACpD,AAAI,GAAmB,gBAAgB,KAAO,CAAE,GAC9C,GAAY,IAAI,CAAC,EAAI,GAAiB,CAAC,CAAE,CAAC,EAC1C,EAAO,YAAY,EAAY,IAAI,CAAC,CAAE,CAAE,EAE5C,CAGA,MAAI,GAAY,OAAS,EAChB,EAGF,EAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAGlB,SACG,KACC,GAAU,EAAM,KAAK,GAAS,CAAC,CAAC,CAAC,CACnC,EACG,UAAU,GAAU,CACnB,EAAG,OAAS,CAAC,EAGb,OAAW,CAAC,EAAI,IAAe,GAAa,CAC1C,GAAM,GAAQ,EAAW,cAAe,CAAU,EAC5C,EAAQ,EAAW,gBAAgB,KAAO,CAAE,EAClD,AAAK,EAGH,GAAK,EAAO,CAAK,EAFjB,GAAK,EAAO,CAAK,CAGrB,CACF,CAAC,EAGE,EAAM,GAAG,CAAC,GAAG,CAAW,EAC5B,IAAI,CAAC,CAAC,CAAE,KACP,GAAgB,EAAY,CAAS,CACtC,CACH,EACG,KACC,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,GAAM,CACR,CACJ,CAAC,CACH,CRlFA,GAAI,IAAW,EAaf,YAA2B,EAA0C,CACnE,GAAI,EAAG,mBAAoB,CACzB,GAAM,GAAU,EAAG,mBACnB,GAAI,EAAQ,UAAY,KACtB,MAAO,GAGJ,GAAI,EAAQ,UAAY,KAAO,CAAC,EAAQ,SAAS,OACpD,MAAO,IAAkB,CAAO,CACpC,CAIF,CAgBO,YACL,EACuB,CACvB,MAAO,IAAiB,CAAE,EACvB,KACC,EAAI,CAAC,CAAE,WAEE,EACL,WAAY,AAFE,GAAsB,CAAE,EAElB,MAAQ,CAC9B,EACD,EACD,EAAwB,YAAY,CACtC,CACJ,CAeO,YACL,EAAiB,EAC8B,CAC/C,GAAM,CAAE,QAAS,GAAU,WAAW,SAAS,EAGzC,EAAW,EAAM,IAAM,CAC3B,GAAM,GAAQ,GAAI,GASlB,GARA,EAAM,UAAU,CAAC,CAAE,gBAAiB,CAClC,AAAI,GAAc,EAChB,EAAG,aAAa,WAAY,GAAG,EAE/B,EAAG,gBAAgB,UAAU,CACjC,CAAC,EAGG,WAAY,YAAY,EAAG,CAC7B,GAAM,GAAS,EAAG,QAAQ,KAAK,EAC/B,EAAO,GAAK,UAAU,EAAE,KACxB,EAAO,aACL,GAAsB,EAAO,EAAE,EAC/B,CACF,CACF,CAGA,GAAM,GAAY,EAAG,QAAQ,YAAY,EACzC,GAAI,YAAqB,aAAa,CACpC,GAAM,GAAO,GAAkB,CAAS,EAGxC,GAAI,MAAO,IAAS,aAClB,GAAU,UAAU,SAAS,UAAU,GACvC,GAAQ,uBAAuB,GAC9B,CACD,GAAM,GAAe,GAAoB,EAAM,EAAI,CAAO,EAG1D,MAAO,IAAe,CAAE,EACrB,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,EACpC,GACE,GAAiB,CAAS,EACvB,KACC,GAAU,EAAM,KAAK,GAAS,CAAC,CAAC,CAAC,EACjC,EAAI,CAAC,CAAE,QAAO,YAAa,GAAS,CAAM,EAC1C,EAAqB,EACrB,EAAU,GAAU,EAAS,EAAe,CAAK,CACnD,CACJ,CACF,CACJ,CACF,CAGA,MAAO,IAAe,CAAE,EACrB,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,EAGD,MAAO,IAAuB,CAAE,EAC7B,KACC,EAAO,GAAW,CAAO,EACzB,GAAK,CAAC,EACN,EAAU,IAAM,CAAQ,CAC1B,CACJ,4uJS7KA,GAAI,IAKA,GAAQ,EAWZ,aAA0C,CACxC,MAAO,OAAO,UAAY,aAAe,kBAAmB,SACxD,GAAY,qDAAqD,EACjE,EAAG,MAAS,CAClB,CAaO,YACL,EACgC,CAChC,SAAG,UAAU,OAAO,SAAS,EAC7B,QAAa,GAAa,EACvB,KACC,EAAI,IAAM,QAAQ,WAAW,CAC3B,YAAa,GACb,WACF,CAAC,CAAC,EACF,EAAI,IAAG,EAAY,EACnB,EAAY,CAAC,CACf,GAGF,GAAS,UAAU,IAAM,CACvB,EAAG,UAAU,IAAI,SAAS,EAC1B,GAAM,GAAK,aAAa,OAClB,EAAO,EAAE,MAAO,CAAE,MAAO,SAAU,CAAC,EAC1C,QAAQ,WAAW,OAAO,EAAI,EAAG,YAAa,AAAC,GAAgB,CAG7D,GAAM,GAAS,EAAK,aAAa,CAAE,KAAM,QAAS,CAAC,EACnD,EAAO,UAAY,EAGnB,EAAG,YAAY,CAAI,CACrB,CAAC,CACH,CAAC,EAGM,GACJ,KACC,EAAI,IAAO,EAAE,IAAK,CAAG,EAAE,CACzB,CACJ,CC1CO,YACL,EAAwB,CAAE,UAAS,UACd,CACrB,GAAI,GAAO,GACX,MAAO,GAGL,EACG,KACC,EAAI,GAAU,EAAO,QAAQ,qBAAqB,CAAE,EACpD,EAAO,GAAW,IAAO,CAAO,EAChC,EAAI,IAAO,EACT,OAAQ,OAAQ,OAAQ,EAC1B,EAAa,CACf,EAGF,EACG,KACC,EAAO,GAAU,GAAU,CAAC,CAAI,EAChC,EAAI,IAAM,EAAO,EAAG,IAAI,EACxB,EAAI,GAAW,EACb,OAAQ,EAAS,OAAS,OAC5B,EAAa,CACf,CACJ,CACF,CAaO,YACL,EAAwB,EACQ,CAChC,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,SAAM,UAAU,CAAC,CAAE,SAAQ,YAAa,CACtC,AAAI,IAAW,OACb,EAAG,aAAa,OAAQ,EAAE,EAE1B,EAAG,gBAAgB,MAAM,EACvB,GACF,EAAG,eAAe,CACtB,CAAC,EAGM,GAAa,EAAI,CAAO,EAC5B,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CC/FA,GAAM,IAAW,EAAE,OAAO,EAgBnB,YACL,EACkC,CAClC,SAAG,YAAY,EAAQ,EACvB,GAAS,YAAY,GAAY,CAAE,CAAC,EAG7B,EAAG,CAAE,IAAK,CAAG,CAAC,CACvB,CCIO,YACL,EACyB,CACzB,GAAM,GAAS,EAA8B,iBAAkB,CAAE,EAC3D,EAAS,EAAO,KAAK,GAAS,EAAM,OAAO,GAAK,EAAO,GAC7D,MAAO,GAAM,GAAG,EAAO,IAAI,GAAS,EAAU,EAAO,QAAQ,EAC1D,KACC,EAAI,IAAO,EACT,OAAQ,EAAW,aAAa,EAAM,KAAK,CAC7C,EAAiB,CACnB,CACF,CAAC,EACE,KACC,EAAU,CACR,OAAQ,EAAW,aAAa,EAAO,KAAK,CAC9C,CAAgB,CAClB,CACJ,CAcO,YACL,EACoC,CACpC,GAAM,GAAY,EAAW,iBAAkB,CAAE,EACjD,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,SAAc,CAAC,EAAO,GAAiB,CAAE,CAAC,CAAC,EACxC,KACC,GAAU,EAAG,EAAuB,EACpC,GAAU,EAAM,KAAK,GAAS,CAAC,CAAC,CAAC,CACnC,EACG,UAAU,CAGT,KAAK,CAAC,CAAE,WAAW,CACjB,GAAM,GAAS,GAAiB,CAAM,EAChC,CAAE,SAAU,GAAe,CAAM,EAGvC,EAAG,MAAM,YAAY,mBAAoB,GAAG,EAAO,KAAK,EACxD,EAAG,MAAM,YAAY,uBAAwB,GAAG,KAAS,EAGzD,EAAU,SAAS,CACjB,SAAU,SACV,KAAM,EAAO,CACf,CAAC,CACH,EAGA,UAAW,CACT,EAAG,MAAM,eAAe,kBAAkB,EAC1C,EAAG,MAAM,eAAe,sBAAsB,CAChD,CACF,CAAC,EAGE,GAAiB,CAAE,EACvB,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,EACE,KACC,GAAY,EAAc,CAC5B,CACJ,CC9DO,YACL,EAAiB,CAAE,UAAS,UACI,CAChC,MAAO,GAGL,GAAG,EAAY,2BAA4B,CAAE,EAC1C,IAAI,GAAS,GAAe,EAAO,CAAE,QAAO,CAAC,CAAC,EAGjD,GAAG,EAAY,cAAe,CAAE,EAC7B,IAAI,GAAS,GAAa,CAAK,CAAC,EAGnC,GAAG,EAAY,qBAAsB,CAAE,EACpC,IAAI,GAAS,GAAe,CAAK,CAAC,EAGrC,GAAG,EAAY,UAAW,CAAE,EACzB,IAAI,GAAS,GAAa,EAAO,CAAE,UAAS,QAAO,CAAC,CAAC,EAGxD,GAAG,EAAY,cAAe,CAAE,EAC7B,IAAI,GAAS,GAAiB,CAAK,CAAC,CACzC,CACF,CCjCO,YACL,EAAkB,CAAE,UACA,CACpB,MAAO,GACJ,KACC,EAAU,GAAW,EACnB,EAAG,EAAI,EACP,EAAG,EAAK,EAAE,KAAK,GAAM,GAAI,CAAC,CAC5B,EACG,KACC,EAAI,GAAW,EAAE,UAAS,QAAO,EAAE,CACrC,CACF,CACF,CACJ,CAaO,YACL,EAAiB,EACc,CAC/B,GAAM,GAAQ,EAAW,cAAe,CAAE,EAC1C,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,SAAM,UAAU,CAAC,CAAE,UAAS,YAAa,CACvC,EAAM,YAAc,EACpB,AAAI,EACF,EAAG,aAAa,gBAAiB,MAAM,EAEvC,EAAG,gBAAgB,eAAe,CACtC,CAAC,EAGM,GAAY,EAAI,CAAO,EAC3B,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CCjCA,YAAkB,CAAE,aAAgD,CAClE,GAAI,CAAC,GAAQ,iBAAiB,EAC5B,MAAO,GAAG,EAAK,EAGjB,GAAM,GAAa,EAChB,KACC,EAAI,CAAC,CAAE,OAAQ,CAAE,QAAU,CAAC,EAC5B,GAAY,EAAG,CAAC,EAChB,EAAI,CAAC,CAAC,EAAG,KAAO,CAAC,EAAI,EAAG,CAAC,CAAU,EACnC,EAAwB,CAAC,CAC3B,EAGI,EAAU,EAAc,CAAC,EAAW,CAAU,CAAC,EAClD,KACC,EAAO,CAAC,CAAC,CAAE,UAAU,CAAC,CAAE,MAAQ,KAAK,IAAI,EAAI,EAAO,CAAC,EAAI,GAAG,EAC5D,EAAI,CAAC,CAAC,CAAE,CAAC,MAAgB,CAAS,EAClC,EAAqB,CACvB,EAGI,EAAU,GAAY,QAAQ,EACpC,MAAO,GAAc,CAAC,EAAW,CAAO,CAAC,EACtC,KACC,EAAI,CAAC,CAAC,CAAE,UAAU,KAAY,EAAO,EAAI,KAAO,CAAC,CAAM,EACvD,EAAqB,EACrB,EAAU,GAAU,EAAS,EAAU,EAAG,EAAK,CAAC,EAChD,EAAU,EAAK,CACjB,CACJ,CAcO,YACL,EAAiB,EACG,CACpB,MAAO,GAAM,IAAM,EAAc,CAC/B,GAAiB,CAAE,EACnB,GAAS,CAAO,CAClB,CAAC,CAAC,EACC,KACC,EAAI,CAAC,CAAC,CAAE,UAAU,KAAa,EAC7B,SACA,QACF,EAAE,EACF,EAAqB,CAAC,EAAG,IACvB,EAAE,SAAW,EAAE,QACf,EAAE,SAAW,EAAE,MAChB,EACD,EAAY,CAAC,CACf,CACJ,CAaO,YACL,EAAiB,CAAE,UAAS,SACG,CAC/B,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,SACG,KACC,EAAwB,QAAQ,EAChC,GAAkB,CAAO,CAC3B,EACG,UAAU,CAAC,CAAC,CAAE,UAAU,CAAE,aAAc,CACvC,AAAI,EACF,EAAG,aAAa,gBAAiB,EAAS,SAAW,QAAQ,EAE7D,EAAG,gBAAgB,eAAe,CACtC,CAAC,EAGL,EAAM,UAAU,CAAK,EAGd,EACJ,KACC,GAAU,EAAM,KAAK,GAAS,CAAC,CAAC,CAAC,EACjC,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CCjHO,YACL,EAAiB,CAAE,YAAW,WACL,CACzB,MAAO,IAAgB,EAAI,CAAE,YAAW,SAAQ,CAAC,EAC9C,KACC,EAAI,CAAC,CAAE,OAAQ,CAAE,QAAU,CACzB,GAAM,CAAE,UAAW,GAAe,CAAE,EACpC,MAAO,CACL,OAAQ,GAAK,CACf,CACF,CAAC,EACD,EAAwB,QAAQ,CAClC,CACJ,CAaO,YACL,EAAiB,EACmB,CACpC,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,EAAM,UAAU,CAAC,CAAE,YAAa,CAC9B,AAAI,EACF,EAAG,aAAa,gBAAiB,QAAQ,EAEzC,EAAG,gBAAgB,eAAe,CACtC,CAAC,EAGD,GAAM,GAAU,GAAmB,YAAY,EAC/C,MAAI,OAAO,IAAY,YACd,EAGF,GAAiB,EAAS,CAAO,EACrC,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CC1DO,YACL,EAAiB,CAAE,YAAW,WACZ,CAGlB,GAAM,GAAU,EACb,KACC,EAAI,CAAC,CAAE,YAAa,CAAM,EAC1B,EAAqB,CACvB,EAGI,EAAU,EACb,KACC,EAAU,IAAM,GAAiB,CAAE,EAChC,KACC,EAAI,CAAC,CAAE,YAAc,EACnB,IAAQ,EAAG,UACX,OAAQ,EAAG,UAAY,CACzB,EAAE,EACF,EAAwB,QAAQ,CAClC,CACF,CACF,EAGF,MAAO,GAAc,CAAC,EAAS,EAAS,CAAS,CAAC,EAC/C,KACC,EAAI,CAAC,CAAC,EAAQ,CAAE,MAAK,UAAU,CAAE,OAAQ,CAAE,KAAK,KAAM,CAAE,cACtD,GAAS,KAAK,IAAI,EAAG,EACjB,KAAK,IAAI,EAAG,EAAS,EAAI,CAAM,EAC/B,KAAK,IAAI,EAAG,EAAS,EAAI,CAAM,CACnC,EACO,CACL,OAAQ,EAAM,EACd,SACA,OAAQ,EAAM,GAAU,CAC1B,EACD,EACD,EAAqB,CAAC,EAAG,IACvB,EAAE,SAAW,EAAE,QACf,EAAE,SAAW,EAAE,QACf,EAAE,SAAW,EAAE,MAChB,CACH,CACJ,CClDO,YACL,EACqB,CACrB,GAAM,GAAU,SAAkB,WAAW,GAAK,CAChD,MAAO,EAAO,UAAU,GAAS,WAC/B,EAAM,aAAa,qBAAqB,CAC1C,EAAE,OAAO,CACX,EAGA,MAAO,GAAG,GAAG,CAAM,EAChB,KACC,GAAS,GAAS,EAAU,EAAO,QAAQ,EACxC,KACC,EAAI,IAAM,CAAK,CACjB,CACF,EACA,EAAU,EAAO,KAAK,IAAI,EAAG,EAAQ,KAAK,EAAE,EAC5C,EAAI,GAAU,EACZ,MAAO,EAAO,QAAQ,CAAK,EAC3B,MAAO,CACL,OAAS,EAAM,aAAa,sBAAsB,EAClD,QAAS,EAAM,aAAa,uBAAuB,EACnD,OAAS,EAAM,aAAa,sBAAsB,CACpD,CACF,EAAa,EACb,EAAY,CAAC,CACf,CACJ,CASO,YACL,EACgC,CAChC,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,EAAM,UAAU,GAAW,CACzB,SAAS,KAAK,aAAa,0BAA2B,EAAE,EAGxD,OAAW,CAAC,EAAK,IAAU,QAAO,QAAQ,EAAQ,KAAK,EACrD,SAAS,KAAK,aAAa,iBAAiB,IAAO,CAAK,EAG1D,OAAS,GAAQ,EAAG,EAAQ,EAAO,OAAQ,IAAS,CAClD,GAAM,GAAQ,EAAO,GAAO,mBAC5B,AAAI,YAAiB,cACnB,GAAM,OAAS,EAAQ,QAAU,EACrC,CAGA,SAAS,YAAa,CAAO,CAC/B,CAAC,EAGD,EAAM,KAAK,GAAU,EAAc,CAAC,EACjC,UAAU,IAAM,CACf,SAAS,KAAK,gBAAgB,yBAAyB,CACzD,CAAC,EAGH,GAAM,GAAS,EAA8B,QAAS,CAAE,EACxD,MAAO,IAAa,CAAM,EACvB,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CC/HA,OAAwB,SAiCxB,YAAiB,EAAyB,CACxC,EAAG,aAAa,kBAAmB,EAAE,EACrC,GAAM,GAAO,EAAG,UAChB,SAAG,gBAAgB,iBAAiB,EAC7B,CACT,CAWO,YACL,CAAE,UACI,CACN,AAAI,WAAY,YAAY,GAC1B,GAAI,GAA8B,GAAc,CAC9C,GAAI,YAAY,iDAAkD,CAChE,KAAM,GACJ,EAAG,aAAa,qBAAqB,GACrC,GAAQ,EACN,EAAG,aAAa,uBAAuB,CACzC,CAAC,CAEL,CAAC,EACE,GAAG,UAAW,GAAM,EAAW,KAAK,CAAE,CAAC,CAC5C,CAAC,EACE,KACC,EAAI,GAAM,CAER,AADgB,EAAG,QACX,MAAM,CAChB,CAAC,EACD,EAAI,IAAM,EAAY,kBAAkB,CAAC,CAC3C,EACG,UAAU,CAAM,CAEzB,CCrCA,YAAoB,EAAwB,CAC1C,GAAI,EAAK,OAAS,EAChB,MAAO,CAAC,EAAE,EAGZ,GAAM,CAAC,EAAM,GAAQ,CAAC,GAAG,CAAI,EAC1B,KAAK,CAAC,EAAG,IAAM,EAAE,OAAS,EAAE,MAAM,EAClC,IAAI,GAAO,EAAI,QAAQ,SAAU,EAAE,CAAC,EAGnC,EAAQ,EACZ,GAAI,IAAS,EACX,EAAQ,EAAK,WAEb,MAAO,EAAK,WAAW,CAAK,IAAM,EAAK,WAAW,CAAK,GACrD,IAGJ,MAAO,GAAK,IAAI,GAAO,EAAI,QAAQ,EAAK,MAAM,EAAG,CAAK,EAAG,EAAE,CAAC,CAC9D,CAaO,YAAsB,EAAiC,CAC5D,GAAM,GAAS,SAAkB,YAAa,eAAgB,CAAI,EAClE,GAAI,EACF,MAAO,GAAG,CAAM,EACX,CACL,GAAM,GAAS,GAAc,EAC7B,MAAO,IAAW,GAAI,KAAI,cAAe,GAAQ,EAAO,IAAI,CAAC,EAC1D,KACC,EAAI,GAAW,GAAW,EAAY,MAAO,CAAO,EACjD,IAAI,GAAQ,EAAK,WAAY,CAChC,CAAC,EACD,GAAW,IAAM,CAAK,EACtB,GAAe,CAAC,CAAC,EACjB,EAAI,GAAW,SAAS,YAAa,EAAS,eAAgB,CAAI,CAAC,CACrE,CACJ,CACF,CCIO,YACL,CAAE,YAAW,YAAW,aAClB,CACN,GAAM,GAAS,GAAc,EAC7B,GAAI,SAAS,WAAa,QACxB,OAGF,AAAI,qBAAuB,UACzB,SAAQ,kBAAoB,SAG5B,EAAU,OAAQ,cAAc,EAC7B,UAAU,IAAM,CACf,QAAQ,kBAAoB,MAC9B,CAAC,GAIL,GAAM,GAAU,GAAoC,gBAAgB,EACpE,AAAI,MAAO,IAAY,aACrB,GAAQ,KAAO,EAAQ,MAGzB,GAAM,GAAQ,GAAa,EACxB,KACC,EAAI,GAAS,EAAM,IAAI,GAAQ,GAAG,GAAI,KAAI,EAAM,EAAO,IAAI,GAAG,CAAC,EAC/D,EAAU,GAAQ,EAAsB,SAAS,KAAM,OAAO,EAC3D,KACC,EAAO,GAAM,CAAC,EAAG,SAAW,CAAC,EAAG,OAAO,EACvC,EAAU,GAAM,CACd,GAAI,EAAG,iBAAkB,SAAS,CAChC,GAAM,GAAK,EAAG,OAAO,QAAQ,GAAG,EAChC,GAAI,GAAM,CAAC,EAAG,OAAQ,CACpB,GAAM,GAAM,GAAI,KAAI,EAAG,IAAI,EAO3B,GAJA,EAAI,OAAS,GACb,EAAI,KAAO,GAIT,EAAI,WAAa,SAAS,UAC1B,EAAK,SAAS,EAAI,SAAS,CAAC,EAE5B,SAAG,eAAe,EACX,EAAG,CACR,IAAK,GAAI,KAAI,EAAG,IAAI,CACtB,CAAC,CAEL,CACF,CACA,MAAO,GACT,CAAC,CACH,CACF,EACA,GAAoB,CACtB,EAGI,EAAO,EAAyB,OAAQ,UAAU,EACrD,KACC,EAAO,GAAM,EAAG,QAAU,IAAI,EAC9B,EAAI,GAAO,EACT,IAAK,GAAI,KAAI,SAAS,IAAI,EAC1B,OAAQ,EAAG,KACb,EAAE,EACF,GAAoB,CACtB,EAGF,EAAM,EAAO,CAAI,EACd,KACC,EAAqB,CAAC,EAAG,IAAM,EAAE,IAAI,OAAS,EAAE,IAAI,IAAI,EACxD,EAAI,CAAC,CAAE,SAAU,CAAG,CACtB,EACG,UAAU,CAAS,EAGxB,GAAM,GAAY,EACf,KACC,EAAwB,UAAU,EAClC,EAAU,GAAO,GAAQ,EAAI,IAAI,EAC9B,KACC,GAAW,IACT,IAAY,CAAG,EACR,GACR,CACH,CACF,EACA,GAAM,CACR,EAGF,EACG,KACC,GAAO,CAAS,CAClB,EACG,UAAU,CAAC,CAAE,SAAU,CACtB,QAAQ,UAAU,CAAC,EAAG,GAAI,GAAG,GAAK,CACpC,CAAC,EAGL,GAAM,GAAM,GAAI,WAChB,EACG,KACC,EAAU,GAAO,EAAI,KAAK,CAAC,EAC3B,EAAI,GAAO,EAAI,gBAAgB,EAAK,WAAW,CAAC,CAClD,EACG,UAAU,CAAS,EAGxB,EACG,KACC,GAAK,CAAC,CACR,EACG,UAAU,GAAe,CACxB,OAAW,KAAY,CAGrB,QACA,sBACA,oBACA,yBAGA,+BACA,gCACA,mCACA,+BACA,2BACA,2BACA,GAAG,GAAQ,wBAAwB,EAC/B,CAAC,0BAA0B,EAC3B,CAAC,CACP,EAAG,CACD,GAAM,GAAS,GAAmB,CAAQ,EACpC,EAAS,GAAmB,EAAU,CAAW,EACvD,AACE,MAAO,IAAW,aAClB,MAAO,IAAW,aAElB,EAAO,YAAY,CAAM,CAE7B,CACF,CAAC,EAGL,EACG,KACC,GAAK,CAAC,EACN,EAAI,IAAM,GAAoB,WAAW,CAAC,EAC1C,EAAU,GAAM,EAAY,SAAU,CAAE,CAAC,EACzC,GAAU,GAAM,CACd,GAAM,GAAS,EAAE,QAAQ,EACzB,GAAI,EAAG,IAAK,CACV,OAAW,KAAQ,GAAG,kBAAkB,EACtC,EAAO,aAAa,EAAM,EAAG,aAAa,CAAI,CAAE,EAClD,SAAG,YAAY,CAAM,EAGd,GAAI,GAAW,GAAY,CAChC,EAAO,OAAS,IAAM,EAAS,SAAS,CAC1C,CAAC,CAGH,KACE,UAAO,YAAc,EAAG,YACxB,EAAG,YAAY,CAAM,EACd,CAEX,CAAC,CACH,EACG,UAAU,EAGf,EAAM,EAAO,CAAI,EACd,KACC,GAAO,CAAS,CAClB,EACG,UAAU,CAAC,CAAE,MAAK,YAAa,CAC9B,AAAI,EAAI,MAAQ,CAAC,EACf,GAAgB,EAAI,IAAI,EAExB,OAAO,SAAS,EAAG,kBAAQ,IAAK,CAAC,CAErC,CAAC,EAGL,EACG,KACC,GAAU,CAAK,EACf,GAAa,GAAG,EAChB,EAAwB,QAAQ,CAClC,EACG,UAAU,CAAC,CAAE,YAAa,CACzB,QAAQ,aAAa,EAAQ,EAAE,CACjC,CAAC,EAGL,EAAM,EAAO,CAAI,EACd,KACC,GAAY,EAAG,CAAC,EAChB,EAAO,CAAC,CAAC,EAAG,KAAO,EAAE,IAAI,WAAa,EAAE,IAAI,QAAQ,EACpD,EAAI,CAAC,CAAC,CAAE,KAAW,CAAK,CAC1B,EACG,UAAU,CAAC,CAAE,YAAa,CACzB,OAAO,SAAS,EAAG,kBAAQ,IAAK,CAAC,CACnC,CAAC,CACP,CCzSA,OAAuB,SCAvB,OAAuB,SAsChB,YACL,EAA2B,EACD,CAC1B,GAAM,GAAY,GAAI,QAAO,EAAO,UAAW,KAAK,EAC9C,EAAY,CAAC,EAAY,EAAc,IACpC,GAAG,4BAA+B,WAI3C,MAAO,AAAC,IAAkB,CACxB,EAAQ,EACL,QAAQ,gBAAiB,GAAG,EAC5B,KAAK,EAGR,GAAM,GAAQ,GAAI,QAAO,MAAM,EAAO,cACpC,EACG,QAAQ,uBAAwB,MAAM,EACtC,QAAQ,EAAW,GAAG,KACtB,KAAK,EAGV,MAAO,IACL,GACI,eAAW,CAAK,EAChB,GAED,QAAQ,EAAO,CAAS,EACxB,QAAQ,8BAA+B,IAAI,CAClD,CACF,CC9BO,YAA0B,EAAuB,CACtD,MAAO,GACJ,MAAM,YAAY,EAChB,IAAI,CAAC,EAAO,IAAU,EAAQ,EAC3B,EAAM,QAAQ,+BAAgC,IAAI,EAClD,CACJ,EACC,KAAK,EAAE,EACT,QAAQ,kCAAmC,EAAE,EAC7C,KAAK,CACV,CCoCO,YACL,EAC+B,CAC/B,MAAO,GAAQ,OAAS,CAC1B,CASO,YACL,EAC+B,CAC/B,MAAO,GAAQ,OAAS,CAC1B,CASO,YACL,EACgC,CAChC,MAAO,GAAQ,OAAS,CAC1B,CCvEA,YAA0B,CAAE,SAAQ,QAAkC,CAGpE,AAAI,EAAO,KAAK,SAAW,GAAK,EAAO,KAAK,KAAO,MACjD,GAAO,KAAO,CACZ,EAAY,oBAAoB,CAClC,GAGE,EAAO,YAAc,aACvB,GAAO,UAAY,EAAY,yBAAyB,GAQ1D,GAAM,GAAyB,CAC7B,SANe,EAAY,wBAAwB,EAClD,MAAM,SAAS,EACf,OAAO,OAAO,EAKf,YAAa,GAAQ,gBAAgB,CACvC,EAGA,MAAO,CAAE,SAAQ,OAAM,SAAQ,CACjC,CAkBO,YACL,EAAa,EACC,CACd,GAAM,GAAS,GAAc,EACvB,EAAS,GAAI,QAAO,CAAG,EAGvB,EAAM,GAAI,GACV,EAAM,GAAY,EAAQ,CAAE,KAAI,CAAC,EACpC,KACC,EAAI,GAAW,CACb,GAAI,GAAsB,CAAO,EAC/B,OAAW,KAAU,GAAQ,KAAK,MAChC,OAAW,KAAY,GACrB,EAAS,SAAW,GAAG,GAAI,KAAI,EAAS,SAAU,EAAO,IAAI,IAEnE,MAAO,EACT,CAAC,EACD,GAAM,CACR,EAGF,UAAK,CAAK,EACP,KACC,EAAI,GAAS,EACX,KAAM,EACN,KAAM,GAAiB,CAAI,CAC7B,EAAwB,CAC1B,EACG,UAAU,EAAI,KAAK,KAAK,CAAG,CAAC,EAG1B,CAAE,MAAK,KAAI,CACpB,CCxEO,YACL,CAAE,aACI,CACN,GAAM,GAAS,GAAc,EACvB,EAAY,GAChB,GAAI,KAAI,mBAAoB,EAAO,IAAI,CACzC,EACG,KACC,GAAW,IAAM,CAAK,CACxB,EAGI,EAAW,EACd,KACC,EAAI,GAAY,CACd,GAAM,CAAC,CAAE,GAAW,EAAO,KAAK,MAAM,aAAa,EACnD,MAAO,GAAS,KAAK,CAAC,CAAE,UAAS,aAC/B,IAAY,GAAW,EAAQ,SAAS,CAAO,CAChD,GAAK,EAAS,EACjB,CAAC,CACH,EAGF,EAAc,CAAC,EAAW,CAAQ,CAAC,EAChC,KACC,EAAI,CAAC,CAAC,EAAU,KAAa,GAAI,KAAI,EAClC,OAAO,GAAW,IAAY,CAAO,EACrC,IAAI,GAAW,CACd,GAAG,GAAI,KAAI,MAAM,EAAQ,WAAY,EAAO,IAAI,IAChD,CACF,CAAC,CACH,CAAC,EACD,EAAU,GAAQ,EAAsB,SAAS,KAAM,OAAO,EAC3D,KACC,EAAO,GAAM,CAAC,EAAG,SAAW,CAAC,EAAG,OAAO,EACvC,EAAU,GAAM,CACd,GAAI,EAAG,iBAAkB,SAAS,CAChC,GAAM,GAAK,EAAG,OAAO,QAAQ,GAAG,EAChC,GAAI,GAAM,CAAC,EAAG,QAAU,EAAK,IAAI,EAAG,IAAI,EACtC,SAAG,eAAe,EACX,EAAG,EAAG,IAAI,CAErB,CACA,MAAO,EACT,CAAC,EACD,EAAU,GAAO,CACf,GAAM,CAAE,WAAY,EAAK,IAAI,CAAG,EAChC,MAAO,IAAa,GAAI,KAAI,CAAG,CAAC,EAC7B,KACC,EAAI,GAAW,CAEb,GAAM,GAAO,AADI,GAAY,EACP,KAAK,QAAQ,EAAO,KAAM,EAAE,EAClD,MAAO,GAAQ,SAAS,CAAI,EACxB,GAAI,KAAI,MAAM,KAAW,IAAQ,EAAO,IAAI,EAC5C,GAAI,KAAI,CAAG,CACjB,CAAC,CACH,CACJ,CAAC,CACH,CACF,CACF,EACG,UAAU,GAAO,GAAY,CAAG,CAAC,EAGtC,EAAc,CAAC,EAAW,CAAQ,CAAC,EAChC,UAAU,CAAC,CAAC,EAAU,KAAa,CAElC,AADc,EAAW,mBAAmB,EACtC,YAAY,GAAsB,EAAU,CAAO,CAAC,CAC5D,CAAC,EAGH,EAAU,KAAK,EAAU,IAAM,CAAQ,CAAC,EACrC,UAAU,GAAW,CA7I1B,MAgJM,GAAI,GAAW,SAAS,aAAc,cAAc,EACpD,GAAI,IAAa,KAAM,CACrB,GAAM,GAAS,MAAO,UAAP,cAAgB,UAAW,SAC1C,EAAW,CAAC,EAAQ,QAAQ,SAAS,CAAM,EAG3C,SAAS,aAAc,EAAU,cAAc,CACjD,CAGA,GAAI,EACF,OAAW,KAAW,IAAqB,UAAU,EACnD,EAAQ,OAAS,EACvB,CAAC,CACL,CCxEO,YACL,EAAsB,CAAE,OACC,CACzB,GAAM,GAAK,gCAAU,YAAa,GAG5B,CAAE,gBAAiB,GAAY,EACrC,AAAI,EAAa,IAAI,GAAG,GACtB,GAAU,SAAU,EAAI,EAG1B,GAAM,GAAS,EACZ,KACC,EAAO,EAAoB,EAC3B,GAAK,CAAC,EACN,EAAI,IAAM,EAAa,IAAI,GAAG,GAAK,EAAE,CACvC,EAGF,GAAY,QAAQ,EACjB,KACC,EAAO,GAAU,CAAC,CAAM,EACxB,GAAK,CAAC,CACR,EACG,UAAU,IAAM,CACf,GAAM,GAAM,GAAI,KAAI,SAAS,IAAI,EACjC,EAAI,aAAa,OAAO,GAAG,EAC3B,QAAQ,aAAa,CAAC,EAAG,GAAI,GAAG,GAAK,CACvC,CAAC,EAGL,EAAO,UAAU,GAAS,CACxB,AAAI,GACF,GAAG,MAAQ,EACX,EAAG,MAAM,EAEb,CAAC,EAGD,GAAM,GAAS,GAAkB,CAAE,EAC7B,EAAS,EACb,EAAU,EAAI,OAAO,EACrB,EAAU,EAAI,OAAO,EAAE,KAAK,GAAM,CAAC,CAAC,EACpC,CACF,EACG,KACC,EAAI,IAAM,EAAG,EAAG,KAAK,CAAC,EACtB,EAAU,EAAE,EACZ,EAAqB,CACvB,EAGF,MAAO,GAAc,CAAC,EAAQ,CAAM,CAAC,EAClC,KACC,EAAI,CAAC,CAAC,EAAO,KAAY,EAAE,QAAO,OAAM,EAAE,EAC1C,EAAY,CAAC,CACf,CACJ,CAUO,YACL,EAAsB,CAAE,MAAK,OACyB,CACtD,GAAM,GAAQ,GAAI,GAGlB,SACG,KACC,EAAwB,OAAO,EAC/B,EAAI,CAAC,CAAE,WAAiC,EACtC,KAAM,EACN,KAAM,CACR,EAAE,CACJ,EACG,UAAU,EAAI,KAAK,KAAK,CAAG,CAAC,EAGjC,EACG,KACC,EAAwB,OAAO,CACjC,EACG,UAAU,CAAC,CAAE,WAAY,CACxB,AAAI,EACF,IAAU,SAAU,CAAK,EACzB,EAAG,YAAc,IAEjB,EAAG,YAAc,EAAY,oBAAoB,CAErD,CAAC,EAGL,EAAU,EAAG,KAAO,OAAO,EACxB,KACC,GAAU,EAAM,KAAK,GAAS,CAAC,CAAC,CAAC,CACnC,EACG,UAAU,IAAM,EAAG,MAAM,CAAC,EAGxB,GAAiB,EAAI,CAAE,MAAK,KAAI,CAAC,EACrC,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CClHO,YACL,EAAiB,CAAE,OAAqB,CAAE,UACL,CACrC,GAAM,GAAQ,GAAI,GACZ,EAAY,GAAqB,EAAG,aAAc,EACrD,KACC,EAAO,OAAO,CAChB,EAGI,EAAO,EAAW,wBAAyB,CAAE,EAC7C,EAAO,EAAW,uBAAwB,CAAE,EAG5C,EAAS,EACZ,KACC,EAAO,EAAoB,EAC3B,GAAK,CAAC,CACR,EAGF,SACG,KACC,GAAe,CAAM,EACrB,GAAU,CAAM,CAClB,EACG,UAAU,CAAC,CAAC,CAAE,SAAS,CAAE,YAAa,CACrC,GAAI,EACF,OAAQ,EAAM,YAGP,GACH,EAAK,YAAc,EAAY,oBAAoB,EACnD,UAGG,GACH,EAAK,YAAc,EAAY,mBAAmB,EAClD,cAIA,EAAK,YAAc,EACjB,sBACA,GAAM,EAAM,MAAM,CACpB,MAGJ,GAAK,YAAc,EAAY,2BAA2B,CAE9D,CAAC,EAGL,EACG,KACC,EAAI,IAAM,EAAK,UAAY,EAAE,EAC7B,EAAU,CAAC,CAAE,WAAY,EACvB,EAAG,GAAG,EAAM,MAAM,EAAG,EAAE,CAAC,EACxB,EAAG,GAAG,EAAM,MAAM,EAAE,CAAC,EAClB,KACC,GAAY,CAAC,EACb,GAAQ,CAAS,EACjB,EAAU,CAAC,CAAC,KAAW,CAAK,CAC9B,CACJ,CAAC,CACH,EACG,UAAU,GAAU,EAAK,YACxB,GAAuB,CAAM,CAC/B,CAAC,EAUE,AAPS,EACb,KACC,EAAO,EAAqB,EAC5B,EAAI,CAAC,CAAE,UAAW,CAAI,CACxB,EAIC,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CC1FO,YACL,EAAkB,CAAE,UACK,CACzB,MAAO,GACJ,KACC,EAAI,CAAC,CAAE,WAAY,CACjB,GAAM,GAAM,GAAY,EACxB,SAAI,KAAO,GACX,EAAI,aAAa,OAAO,GAAG,EAC3B,EAAI,aAAa,IAAI,IAAK,CAAK,EACxB,CAAE,KAAI,CACf,CAAC,CACH,CACJ,CAUO,YACL,EAAuB,EACa,CACpC,GAAM,GAAQ,GAAI,GAClB,SAAM,UAAU,CAAC,CAAE,SAAU,CAC3B,EAAG,aAAa,sBAAuB,EAAG,IAAI,EAC9C,EAAG,KAAO,GAAG,GACf,CAAC,EAGD,EAAU,EAAI,OAAO,EAClB,UAAU,GAAM,EAAG,eAAe,CAAC,EAG/B,GAAiB,EAAI,CAAO,EAChC,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CCtCO,YACL,EAAiB,CAAE,OAAqB,CAAE,aACJ,CACtC,GAAM,GAAQ,GAAI,GAGZ,EAAS,GAAoB,cAAc,EAC3C,EAAS,EACb,EAAU,EAAO,SAAS,EAC1B,EAAU,EAAO,OAAO,CAC1B,EACG,KACC,GAAU,EAAc,EACxB,EAAI,IAAM,EAAM,KAAK,EACrB,EAAqB,CACvB,EAGF,SACG,KACC,GAAkB,CAAM,EACxB,EAAI,CAAC,CAAC,CAAE,eAAe,KAAW,CAChC,GAAM,GAAQ,EAAM,MAAM,UAAU,EACpC,GAAI,kBAAa,SAAU,EAAM,EAAM,OAAS,GAAI,CAClD,GAAM,GAAO,EAAY,EAAY,OAAS,GAC9C,AAAI,EAAK,WAAW,EAAM,EAAM,OAAS,EAAE,GACzC,GAAM,EAAM,OAAS,GAAK,EAC9B,KACE,GAAM,OAAS,EAEjB,MAAO,EACT,CAAC,CACH,EACG,UAAU,GAAS,EAAG,UAAY,EAChC,KAAK,EAAE,EACP,QAAQ,MAAO,QAAQ,CAC1B,EAGJ,EACG,KACC,EAAO,CAAC,CAAE,UAAW,IAAS,QAAQ,CACxC,EACG,UAAU,GAAO,CAChB,OAAQ,EAAI,UAGL,aACH,AACE,EAAG,UAAU,QACb,EAAM,iBAAmB,EAAM,MAAM,QAErC,GAAM,MAAQ,EAAG,WACnB,MAEN,CAAC,EAUE,AAPS,EACb,KACC,EAAO,EAAqB,EAC5B,EAAI,CAAC,CAAE,UAAW,CAAI,CACxB,EAIC,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,IAAO,EAAE,IAAK,CAAG,EAAE,CACzB,CACJ,CC9CO,YACL,EAAiB,CAAE,SAAQ,aACI,CAC/B,GAAM,GAAS,GAAc,EAC7B,GAAI,CACF,GAAM,GAAM,gCAAU,SAAU,EAAO,OACjC,EAAS,GAAkB,EAAK,CAAM,EAGtC,EAAS,GAAoB,eAAgB,CAAE,EAC/C,EAAS,GAAoB,gBAAiB,CAAE,EAGhD,CAAE,MAAK,OAAQ,EACrB,EACG,KACC,EAAO,EAAoB,EAC3B,GAAO,EAAI,KAAK,EAAO,EAAoB,CAAC,CAAC,EAC7C,GAAK,CAAC,CACR,EACG,UAAU,EAAI,KAAK,KAAK,CAAG,CAAC,EAGjC,EACG,KACC,EAAO,CAAC,CAAE,UAAW,IAAS,QAAQ,CACxC,EACG,UAAU,GAAO,CAChB,GAAM,GAAS,GAAiB,EAChC,OAAQ,EAAI,UAGL,QACH,GAAI,IAAW,EAAO,CACpB,GAAM,GAAU,GAAI,KACpB,OAAW,KAAU,GACnB,sBAAuB,CACzB,EAAG,CACD,GAAM,GAAU,EAAO,kBACvB,EAAQ,IAAI,EAAQ,WAClB,EAAQ,aAAa,eAAe,CACtC,CAAC,CACH,CAGA,GAAI,EAAQ,KAAM,CAChB,GAAM,CAAC,CAAC,IAAS,CAAC,GAAG,CAAO,EAAE,KAAK,CAAC,CAAC,CAAE,GAAI,CAAC,CAAE,KAAO,EAAI,CAAC,EAC1D,EAAK,MAAM,CACb,CAGA,EAAI,MAAM,CACZ,CACA,UAGG,aACA,MACH,GAAU,SAAU,EAAK,EACzB,EAAM,KAAK,EACX,UAGG,cACA,YACH,GAAI,MAAO,IAAW,YACpB,EAAM,MAAM,MACP,CACL,GAAM,GAAM,CAAC,EAAO,GAAG,EACrB,wDACA,CACF,CAAC,EACK,EAAI,KAAK,IAAI,EACjB,MAAK,IAAI,EAAG,EAAI,QAAQ,CAAM,CAAC,EAAI,EAAI,OACrC,GAAI,OAAS,UAAY,GAAK,IAE9B,EAAI,MAAM,EACd,EAAI,GAAG,MAAM,CACf,CAGA,EAAI,MAAM,EACV,cAIA,AAAI,IAAU,GAAiB,GAC7B,EAAM,MAAM,EAEpB,CAAC,EAGL,EACG,KACC,EAAO,CAAC,CAAE,UAAW,IAAS,QAAQ,CACxC,EACG,UAAU,GAAO,CAChB,OAAQ,EAAI,UAGL,QACA,QACA,IACH,EAAM,MAAM,EACZ,EAAM,OAAO,EAGb,EAAI,MAAM,EACV,MAEN,CAAC,EAGL,GAAM,GAAU,GAAiB,EAAO,CAAM,EACxC,EAAU,GAAkB,EAAQ,EAAQ,CAAE,QAAO,CAAC,EAC5D,MAAO,GAAM,EAAQ,CAAO,EACzB,KACC,GAGE,GAAG,GAAqB,eAAgB,CAAE,EACvC,IAAI,GAAS,GAAiB,EAAO,CAAE,QAAO,CAAC,CAAC,EAGnD,GAAG,GAAqB,iBAAkB,CAAE,EACzC,IAAI,GAAS,GAAmB,EAAO,EAAQ,CAAE,WAAU,CAAC,CAAC,CAClE,CACF,CAGJ,OAAS,EAAP,CACA,SAAG,OAAS,GACL,EACT,CACF,CCtKO,YACL,EAAiB,CAAE,SAAQ,aACa,CACxC,MAAO,GAAc,CACnB,EACA,EACG,KACC,EAAU,GAAY,CAAC,EACvB,EAAO,GAAO,CAAC,CAAC,EAAI,aAAa,IAAI,GAAG,CAAC,CAC3C,CACJ,CAAC,EACE,KACC,EAAI,CAAC,CAAC,EAAO,KAAS,GAAuB,EAAM,OAAQ,EAAI,EAC7D,EAAI,aAAa,IAAI,GAAG,CAC1B,CAAC,EACD,EAAI,GAAM,CA1FhB,MA2FQ,GAAM,GAAQ,GAAI,KAGZ,EAAK,SAAS,mBAAmB,EAAI,WAAW,SAAS,EAC/D,OAAS,GAAO,EAAG,SAAS,EAAG,EAAM,EAAO,EAAG,SAAS,EACtD,GAAI,KAAK,gBAAL,QAAoB,aAAc,CACpC,GAAM,GAAW,EAAK,YAChB,EAAW,EAAG,CAAQ,EAC5B,AAAI,EAAS,OAAS,EAAS,QAC7B,EAAM,IAAI,EAAmB,CAAQ,CACzC,CAIF,OAAW,CAAC,EAAM,IAAS,GAAO,CAChC,GAAM,CAAE,cAAe,EAAE,OAAQ,KAAM,CAAI,EAC3C,EAAK,YAAY,GAAG,MAAM,KAAK,CAAU,CAAC,CAC5C,CAGA,MAAO,CAAE,IAAK,EAAI,OAAM,CAC1B,CAAC,CACH,CACJ,CClBO,YACL,EAAiB,CAAE,YAAW,SACT,CACrB,GAAM,GAAS,EAAG,cACZ,EACJ,EAAO,UACP,EAAO,cAAe,UAGxB,MAAO,GAAc,CAAC,EAAO,CAAS,CAAC,EACpC,KACC,EAAI,CAAC,CAAC,CAAE,SAAQ,UAAU,CAAE,OAAQ,CAAE,SACpC,GAAS,EACL,KAAK,IAAI,EAAQ,KAAK,IAAI,EAAG,EAAI,CAAM,CAAC,EACxC,EACG,CACL,SACA,OAAQ,GAAK,EAAS,CACxB,EACD,EACD,EAAqB,CAAC,EAAG,IACvB,EAAE,SAAW,EAAE,QACf,EAAE,SAAW,EAAE,MAChB,CACH,CACJ,CAuBO,YACL,EAAiB,EACe,CADf,QAAE,YAAF,EAAc,KAAd,EAAc,CAAZ,YAEnB,GAAM,GAAQ,EAAW,0BAA2B,CAAE,EAChD,CAAE,KAAM,GAAiB,CAAK,EACpC,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,SACG,KACC,GAAU,EAAG,EAAuB,EACpC,GAAe,CAAO,CACxB,EACG,UAAU,CAGT,KAAK,CAAC,CAAE,UAAU,CAAE,OAAQ,IAAW,CACrC,EAAM,MAAM,OAAS,GAAG,EAAS,EAAI,MACrC,EAAG,MAAM,IAAY,GAAG,KAC1B,EAGA,UAAW,CACT,EAAM,MAAM,OAAS,GACrB,EAAG,MAAM,IAAY,EACvB,CACF,CAAC,EAGE,GAAa,EAAI,CAAO,EAC5B,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CCxHO,YACL,EAAc,EACW,CACzB,GAAI,MAAO,IAAS,YAAa,CAC/B,GAAM,GAAM,gCAAgC,KAAQ,IACpD,MAAO,IAGL,GAAqB,GAAG,mBAAqB,EAC1C,KACC,GAAW,IAAM,CAAK,EACtB,EAAI,GAAY,EACd,QAAS,EAAQ,QACnB,EAAE,EACF,GAAe,CAAC,CAAC,CACnB,EAGF,GAAkB,CAAG,EAClB,KACC,GAAW,IAAM,CAAK,EACtB,EAAI,GAAS,EACX,MAAO,EAAK,iBACZ,MAAO,EAAK,WACd,EAAE,EACF,GAAe,CAAC,CAAC,CACnB,CACJ,EACG,KACC,EAAI,CAAC,CAAC,EAAS,KAAW,OAAK,GAAY,EAAO,CACpD,CAGJ,KAAO,CACL,GAAM,GAAM,gCAAgC,IAC5C,MAAO,IAAkB,CAAG,EACzB,KACC,EAAI,GAAS,EACX,aAAc,EAAK,YACrB,EAAE,EACF,GAAe,CAAC,CAAC,CACnB,CACJ,CACF,CCvDO,YACL,EAAc,EACW,CACzB,GAAM,GAAM,WAAW,qBAAwB,mBAAmB,CAAO,IACzE,MAAO,IAA2B,CAAG,EAClC,KACC,GAAW,IAAM,CAAK,EACtB,EAAI,CAAC,CAAE,aAAY,iBAAmB,EACpC,MAAO,EACP,MAAO,CACT,EAAE,EACF,GAAe,CAAC,CAAC,CACnB,CACJ,CCOO,YACL,EACyB,CACzB,GAAM,CAAC,GAAQ,EAAI,MAAM,mBAAmB,GAAK,CAAC,EAClD,OAAQ,EAAK,YAAY,OAGlB,SACH,GAAM,CAAC,CAAE,EAAM,GAAQ,EAAI,MAAM,qCAAqC,EACtE,MAAO,IAA2B,EAAM,CAAI,MAGzC,SACH,GAAM,CAAC,CAAE,EAAM,GAAQ,EAAI,MAAM,oCAAoC,EACrE,MAAO,IAA2B,EAAM,CAAI,UAI5C,MAAO,GAEb,CCxBA,GAAI,IAgBG,YACL,EACoB,CACpB,MAAO,SAAW,EAAM,IAAM,CAC5B,GAAM,GAAS,SAAsB,WAAY,cAAc,EAC/D,MAAI,GACK,EAAG,CAAM,EAET,GAAiB,EAAG,IAAI,EAC5B,KACC,EAAI,GAAS,SAAS,WAAY,EAAO,cAAc,CAAC,CAC1D,CACN,CAAC,EACE,KACC,GAAW,IAAM,CAAK,EACtB,EAAO,GAAS,OAAO,KAAK,CAAK,EAAE,OAAS,CAAC,EAC7C,EAAI,GAAU,EAAE,OAAM,EAAE,EACxB,EAAY,CAAC,CACf,EACJ,CASO,YACL,EAC+B,CAC/B,GAAM,GAAQ,EAAW,uBAAwB,CAAE,EACnD,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,SAAM,UAAU,CAAC,CAAE,WAAY,CAC7B,EAAM,YAAY,GAAkB,CAAK,CAAC,EAC1C,EAAM,aAAa,gBAAiB,MAAM,CAC5C,CAAC,EAGM,GAAY,CAAE,EAClB,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CCvCO,YACL,EAAiB,CAAE,YAAW,WACZ,CAClB,MAAO,IAAiB,SAAS,IAAI,EAClC,KACC,EAAU,IAAM,GAAgB,EAAI,CAAE,UAAS,WAAU,CAAC,CAAC,EAC3D,EAAI,CAAC,CAAE,OAAQ,CAAE,QACR,EACL,OAAQ,GAAK,EACf,EACD,EACD,EAAwB,QAAQ,CAClC,CACJ,CAaO,YACL,EAAiB,EACY,CAC7B,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,SAAM,UAAU,CAGd,KAAK,CAAE,UAAU,CACf,AAAI,EACF,EAAG,aAAa,gBAAiB,QAAQ,EAEzC,EAAG,gBAAgB,eAAe,CACtC,EAGA,UAAW,CACT,EAAG,gBAAgB,eAAe,CACpC,CACF,CAAC,EAIC,IAAQ,wBAAwB,EAC5B,EAAG,CAAE,OAAQ,EAAM,CAAC,EACpB,GAAU,EAAI,CAAO,GAExB,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CC3BO,YACL,EAAiB,CAAE,YAAW,WACD,CAC7B,GAAM,GAAQ,GAAI,KAGZ,EAAU,EAA+B,cAAe,CAAE,EAChE,OAAW,KAAU,GAAS,CAC5B,GAAM,GAAK,mBAAmB,EAAO,KAAK,UAAU,CAAC,CAAC,EAChD,EAAS,GAAmB,QAAQ,KAAM,EAChD,AAAI,MAAO,IAAW,aACpB,EAAM,IAAI,EAAQ,CAAM,CAC5B,CAGA,GAAM,GAAU,EACb,KACC,EAAwB,QAAQ,EAChC,EAAI,CAAC,CAAE,YAAa,CAClB,GAAM,GAAO,GAAoB,MAAM,EACjC,EAAO,EAAW,wBAAyB,CAAI,EACrD,MAAO,GAAS,GACd,GAAK,UACL,EAAK,UAET,CAAC,EACD,GAAM,CACR,EAgFF,MAAO,AA7EY,IAAiB,SAAS,IAAI,EAC9C,KACC,EAAwB,QAAQ,EAGhC,EAAU,GAAQ,EAAM,IAAM,CAC5B,GAAI,GAA4B,CAAC,EACjC,MAAO,GAAG,CAAC,GAAG,CAAK,EAAE,OAAO,CAAC,EAAO,CAAC,EAAQ,KAAY,CACvD,KAAO,EAAK,QAEN,AADS,EAAM,IAAI,EAAK,EAAK,OAAS,EAAE,EACnC,SAAW,EAAO,SACzB,EAAK,IAAI,EAOb,GAAI,GAAS,EAAO,UACpB,KAAO,CAAC,GAAU,EAAO,eACvB,EAAS,EAAO,cAChB,EAAS,EAAO,UAIlB,MAAO,GAAM,IACX,CAAC,GAAG,EAAO,CAAC,GAAG,EAAM,CAAM,CAAC,EAAE,QAAQ,EACtC,CACF,CACF,EAAG,GAAI,IAAkC,CAAC,CAC5C,CAAC,EACE,KAGC,EAAI,GAAS,GAAI,KAAI,CAAC,GAAG,CAAK,EAAE,KAAK,CAAC,CAAC,CAAE,GAAI,CAAC,CAAE,KAAO,EAAI,CAAC,CAAC,CAAC,EAC9D,GAAkB,CAAO,EAGzB,EAAU,CAAC,CAAC,EAAO,KAAY,EAC5B,KACC,GAAK,CAAC,CAAC,EAAM,GAAO,CAAE,OAAQ,CAAE,KAAK,UAAW,CAC9C,GAAM,GAAO,EAAI,EAAK,QAAU,KAAK,MAAM,EAAK,MAAM,EAGtD,KAAO,EAAK,QAAQ,CAClB,GAAM,CAAC,CAAE,GAAU,EAAK,GACxB,GAAI,EAAS,EAAS,GAAK,EACzB,EAAO,CAAC,GAAG,EAAM,EAAK,MAAM,CAAE,MAE9B,MAEJ,CAGA,KAAO,EAAK,QAAQ,CAClB,GAAM,CAAC,CAAE,GAAU,EAAK,EAAK,OAAS,GACtC,GAAI,EAAS,GAAU,GAAK,CAAC,EAC3B,EAAO,CAAC,EAAK,IAAI,EAAI,GAAG,CAAI,MAE5B,MAEJ,CAGA,MAAO,CAAC,EAAM,CAAI,CACpB,EAAG,CAAC,CAAC,EAAG,CAAC,GAAG,CAAK,CAAC,CAAC,EACnB,EAAqB,CAAC,EAAG,IACvB,EAAE,KAAO,EAAE,IACX,EAAE,KAAO,EAAE,EACZ,CACH,CACF,CACF,CACF,CACF,EAIC,KACC,EAAI,CAAC,CAAC,EAAM,KAAW,EACrB,KAAM,EAAK,IAAI,CAAC,CAAC,KAAU,CAAI,EAC/B,KAAM,EAAK,IAAI,CAAC,CAAC,KAAU,CAAI,CACjC,EAAE,EAGF,EAAU,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,CAAE,CAAC,EAChC,GAAY,EAAG,CAAC,EAChB,EAAI,CAAC,CAAC,EAAG,KAGH,EAAE,KAAK,OAAS,EAAE,KAAK,OAClB,CACL,KAAM,EAAE,KAAK,MAAM,KAAK,IAAI,EAAG,EAAE,KAAK,OAAS,CAAC,EAAG,EAAE,KAAK,MAAM,EAChE,KAAM,CAAC,CACT,EAIO,CACL,KAAM,EAAE,KAAK,MAAM,EAAE,EACrB,KAAM,EAAE,KAAK,MAAM,EAAG,EAAE,KAAK,OAAS,EAAE,KAAK,MAAM,CACrD,CAEH,CACH,CACJ,CAYO,YACL,EAAiB,CAAE,YAAW,UAAS,WACC,CACxC,MAAO,GAAM,IAAM,CACjB,GAAM,GAAQ,GAAI,GAClB,SAAM,UAAU,CAAC,CAAE,OAAM,UAAW,CAGlC,OAAW,CAAC,IAAW,GACrB,EAAO,gBAAgB,eAAe,EACtC,EAAO,UAAU,OACf,sBACF,EAIF,OAAW,CAAC,EAAO,CAAC,KAAY,GAAK,QAAQ,EAC3C,EAAO,aAAa,gBAAiB,MAAM,EAC3C,EAAO,UAAU,OACf,uBACA,IAAU,EAAK,OAAS,CAC1B,CAEJ,CAAC,EAGG,GAAQ,qBAAqB,GAC/B,EACG,KACC,GAAU,EAAM,KAAK,GAAS,CAAC,CAAC,CAAC,EACjC,EAAwB,QAAQ,EAChC,GAAa,GAAG,EAChB,GAAK,CAAC,EACN,GAAU,EAAQ,KAAK,GAAK,CAAC,CAAC,CAAC,EAC/B,GAAO,CAAE,MAAO,GAAI,CAAC,EACrB,GAAe,CAAK,CACtB,EACG,UAAU,CAAC,CAAC,CAAE,CAAE,WAAY,CAC3B,GAAM,GAAM,GAAY,EAGlB,EAAS,EAAK,EAAK,OAAS,GAClC,GAAI,GAAU,EAAO,OAAQ,CAC3B,GAAM,CAAC,GAAU,EACX,CAAE,QAAS,GAAI,KAAI,EAAO,IAAI,EACpC,AAAI,EAAI,OAAS,GACf,GAAI,KAAO,EACX,QAAQ,aAAa,CAAC,EAAG,GAAI,GAAG,GAAK,EAIzC,KACE,GAAI,KAAO,GACX,QAAQ,aAAa,CAAC,EAAG,GAAI,GAAG,GAAK,CAEzC,CAAC,EAGA,GAAqB,EAAI,CAAE,YAAW,SAAQ,CAAC,EACnD,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CAAC,CACH,CChPO,YACL,EAAkB,CAAE,YAAW,QAAO,WACf,CAGvB,GAAM,GAAa,EAChB,KACC,EAAI,CAAC,CAAE,OAAQ,CAAE,QAAU,CAAC,EAC5B,GAAY,EAAG,CAAC,EAChB,EAAI,CAAC,CAAC,EAAG,KAAO,EAAI,GAAK,EAAI,CAAC,EAC9B,EAAqB,CACvB,EAGI,EAAU,EACb,KACC,EAAI,CAAC,CAAE,YAAa,CAAM,CAC5B,EAGF,MAAO,GAAc,CAAC,EAAS,CAAU,CAAC,EACvC,KACC,EAAI,CAAC,CAAC,EAAQ,KAAe,CAAE,IAAU,EAAU,EACnD,EAAqB,EACrB,GAAU,EAAQ,KAAK,GAAK,CAAC,CAAC,CAAC,EAC/B,GAAQ,EAAI,EACZ,GAAO,CAAE,MAAO,GAAI,CAAC,EACrB,EAAI,GAAW,EAAE,QAAO,EAAE,CAC5B,CACJ,CAYO,YACL,EAAiB,CAAE,YAAW,UAAS,QAAO,WACZ,CAClC,GAAM,GAAQ,GAAI,GAClB,SAAM,UAAU,CAGd,KAAK,CAAE,UAAU,CACf,AAAI,EACF,GAAG,aAAa,gBAAiB,QAAQ,EACzC,EAAG,aAAa,WAAY,IAAI,EAChC,EAAG,KAAK,GAER,GAAG,gBAAgB,eAAe,EAClC,EAAG,gBAAgB,UAAU,EAEjC,EAGA,UAAW,CACT,EAAG,MAAM,IAAM,GACf,EAAG,aAAa,gBAAiB,QAAQ,EACzC,EAAG,gBAAgB,UAAU,CAC/B,CACF,CAAC,EAGD,EACG,KACC,GAAU,EAAM,KAAK,GAAQ,CAAC,EAAG,GAAS,CAAC,CAAC,CAAC,EAC7C,EAAwB,QAAQ,CAClC,EACG,UAAU,CAAC,CAAE,YAAa,CACzB,EAAG,MAAM,IAAM,GAAG,EAAS,MAC7B,CAAC,EAGE,GAAe,EAAI,CAAE,YAAW,QAAO,SAAQ,CAAC,EACpD,KACC,EAAI,GAAS,EAAM,KAAK,CAAK,CAAC,EAC9B,EAAS,IAAM,EAAM,SAAS,CAAC,EAC/B,EAAI,GAAU,GAAE,IAAK,GAAO,EAAQ,CACtC,CACJ,CCpHO,YACL,CAAE,YAAW,WACP,CACN,EACG,KACC,EAAU,IAAM,EACd,+BACF,CAAC,EACD,EAAI,GAAM,CACR,EAAG,cAAgB,GACnB,EAAG,QAAU,EACf,CAAC,EACD,GAAS,GAAM,EAAU,EAAI,QAAQ,EAClC,KACC,GAAU,IAAM,EAAG,aAAa,eAAe,CAAC,EAChD,EAAI,IAAM,CAAE,CACd,CACF,EACA,GAAe,CAAO,CACxB,EACG,UAAU,CAAC,CAAC,EAAI,KAAY,CAC3B,EAAG,gBAAgB,eAAe,EAC9B,GACF,GAAG,QAAU,GACjB,CAAC,CACP,CC9BA,aAAkC,CAChC,MAAO,qBAAqB,KAAK,UAAU,SAAS,CACtD,CAiBO,YACL,CAAE,aACI,CACN,EACG,KACC,EAAU,IAAM,EAAY,qBAAqB,CAAC,EAClD,EAAI,GAAM,EAAG,gBAAgB,mBAAmB,CAAC,EACjD,EAAO,EAAa,EACpB,GAAS,GAAM,EAAU,EAAI,YAAY,EACtC,KACC,EAAI,IAAM,CAAE,CACd,CACF,CACF,EACG,UAAU,GAAM,CACf,GAAM,GAAM,EAAG,UAGf,AAAI,IAAQ,EACV,EAAG,UAAY,EAGN,EAAM,EAAG,eAAiB,EAAG,cACtC,GAAG,UAAY,EAAM,EAEzB,CAAC,CACP,CCpCO,YACL,CAAE,YAAW,WACP,CACN,EAAc,CAAC,GAAY,QAAQ,EAAG,CAAO,CAAC,EAC3C,KACC,EAAI,CAAC,CAAC,EAAQ,KAAY,GAAU,CAAC,CAAM,EAC3C,EAAU,GAAU,EAAG,CAAM,EAC1B,KACC,GAAM,EAAS,IAAM,GAAG,CAC1B,CACF,EACA,GAAe,CAAS,CAC1B,EACG,UAAU,CAAC,CAAC,EAAQ,CAAE,OAAQ,CAAE,SAAU,CACzC,GAAI,EACF,SAAS,KAAK,aAAa,gBAAiB,MAAM,EAClD,SAAS,KAAK,MAAM,IAAM,IAAI,UACzB,CACL,GAAM,GAAQ,GAAK,SAAS,SAAS,KAAK,MAAM,IAAK,EAAE,EACvD,SAAS,KAAK,gBAAgB,eAAe,EAC7C,SAAS,KAAK,MAAM,IAAM,GACtB,GACF,OAAO,SAAS,EAAG,CAAK,CAC5B,CACF,CAAC,CACP,CC7DA,AAAK,OAAO,SACV,QAAO,QAAU,SAAU,EAAa,CACtC,GAAM,GAA2B,CAAC,EAClC,OAAW,KAAO,QAAO,KAAK,CAAG,EAE/B,EAAK,KAAK,CAAC,EAAK,EAAI,EAAI,CAAC,EAG3B,MAAO,EACT,GAGF,AAAK,OAAO,QACV,QAAO,OAAS,SAAU,EAAa,CACrC,GAAM,GAAiB,CAAC,EACxB,OAAW,KAAO,QAAO,KAAK,CAAG,EAE/B,EAAK,KAAK,EAAI,EAAI,EAGpB,MAAO,EACT,GAKF,AAAI,MAAO,UAAY,aAGhB,SAAQ,UAAU,UACrB,SAAQ,UAAU,SAAW,SAC3B,EAA8B,EACxB,CACN,AAAI,MAAO,IAAM,SACf,MAAK,WAAa,EAAE,KACpB,KAAK,UAAY,EAAE,KAEnB,MAAK,WAAa,EAClB,KAAK,UAAY,EAErB,GAGG,QAAQ,UAAU,aACrB,SAAQ,UAAU,YAAc,YAC3B,EACG,CACN,GAAM,GAAS,KAAK,WACpB,GAAI,EAAQ,CACV,AAAI,EAAM,SAAW,GACnB,EAAO,YAAY,IAAI,EAGzB,OAAS,GAAI,EAAM,OAAS,EAAG,GAAK,EAAG,IAAK,CAC1C,GAAI,GAAO,EAAM,GACjB,AAAI,MAAO,IAAS,SAClB,EAAO,SAAS,eAAe,CAAI,EAC5B,EAAK,YACZ,EAAK,WAAW,YAAY,CAAI,EAGlC,AAAK,EAGH,EAAO,aAAa,KAAK,gBAAkB,CAAI,EAF/C,EAAO,aAAa,EAAM,IAAI,CAGlC,CACF,CACF,I7LHJ,SAAS,gBAAgB,UAAU,OAAO,OAAO,EACjD,SAAS,gBAAgB,UAAU,IAAI,IAAI,EAG3C,GAAM,IAAY,GAAc,EAC1B,GAAY,GAAc,EAC1B,GAAY,GAAoB,EAChC,GAAY,GAAc,EAG1B,GAAY,GAAc,EAC1B,GAAY,GAAW,oBAAoB,EAC3C,GAAY,GAAW,qBAAqB,EAC5C,GAAY,GAAW,EAGvB,GAAS,GAAc,EACvB,GAAS,SAAS,MAAM,UAAU,QAAQ,EAC5C,gCAAU,QAAS,GACnB,GAAI,KAAI,2BAA4B,GAAO,IAAI,CACjD,EACE,GAGE,GAAS,GAAI,GACnB,GAAiB,CAAE,SAAO,CAAC,EAG3B,AAAI,GAAQ,oBAAoB,GAC9B,GAAoB,CAAE,aAAW,aAAW,YAAU,CAAC,EAxHzD,OA2HA,AAAI,QAAO,UAAP,eAAgB,YAAa,QAC/B,GAAqB,CAAE,YAAU,CAAC,EAGpC,EAAM,GAAW,EAAO,EACrB,KACC,GAAM,GAAG,CACX,EACG,UAAU,IAAM,CACf,GAAU,SAAU,EAAK,EACzB,GAAU,SAAU,EAAK,CAC3B,CAAC,EAGL,GACG,KACC,EAAO,CAAC,CAAE,UAAW,IAAS,QAAQ,CACxC,EACG,UAAU,GAAO,CAChB,OAAQ,EAAI,UAGL,QACA,IACH,GAAM,GAAO,GAAmB,kBAAkB,EAClD,AAAI,MAAO,IAAS,aAClB,EAAK,MAAM,EACb,UAGG,QACA,IACH,GAAM,GAAO,GAAmB,kBAAkB,EAClD,AAAI,MAAO,IAAS,aAClB,EAAK,MAAM,EACb,MAEN,CAAC,EAGL,GAAmB,CAAE,aAAW,UAAQ,CAAC,EACzC,GAAe,CAAE,YAAU,CAAC,EAC5B,GAAgB,CAAE,aAAW,UAAQ,CAAC,EAGtC,GAAM,IAAU,GAAY,GAAoB,QAAQ,EAAG,CAAE,YAAU,CAAC,EAClE,GAAQ,GACX,KACC,EAAI,IAAM,GAAoB,MAAM,CAAC,EACrC,EAAU,GAAM,GAAU,EAAI,CAAE,aAAW,UAAQ,CAAC,CAAC,EACrD,EAAY,CAAC,CACf,EAGI,GAAW,EAGf,GAAG,GAAqB,QAAQ,EAC7B,IAAI,GAAM,GAAY,EAAI,CAAE,SAAO,CAAC,CAAC,EAGxC,GAAG,GAAqB,QAAQ,EAC7B,IAAI,GAAM,GAAY,EAAI,CAAE,aAAW,WAAS,QAAM,CAAC,CAAC,EAG3D,GAAG,GAAqB,SAAS,EAC9B,IAAI,GAAM,GAAa,CAAE,CAAC,EAG7B,GAAG,GAAqB,QAAQ,EAC7B,IAAI,GAAM,GAAY,EAAI,CAAE,UAAQ,YAAU,CAAC,CAAC,EAGnD,GAAG,GAAqB,QAAQ,EAC7B,IAAI,GAAM,GAAY,CAAE,CAAC,CAC9B,EAGM,GAAW,EAAM,IAAM,EAG3B,GAAG,GAAqB,SAAS,EAC9B,IAAI,GAAM,GAAa,EAAI,CAAE,WAAS,SAAO,CAAC,CAAC,EAGlD,GAAG,GAAqB,SAAS,EAC9B,IAAI,GAAM,GAAQ,kBAAkB,EACjC,GAAoB,EAAI,CAAE,UAAQ,YAAU,CAAC,EAC7C,CACJ,EAGF,GAAG,GAAqB,cAAc,EACnC,IAAI,GAAM,GAAiB,EAAI,CAAE,aAAW,UAAQ,CAAC,CAAC,EAGzD,GAAG,GAAqB,SAAS,EAC9B,IAAI,GAAM,EAAG,aAAa,cAAc,IAAM,aAC3C,GAAG,GAAS,IAAM,GAAa,EAAI,CAAE,aAAW,WAAS,QAAM,CAAC,CAAC,EACjE,GAAG,GAAS,IAAM,GAAa,EAAI,CAAE,aAAW,WAAS,QAAM,CAAC,CAAC,CACrE,EAGF,GAAG,GAAqB,MAAM,EAC3B,IAAI,GAAM,GAAU,EAAI,CAAE,aAAW,UAAQ,CAAC,CAAC,EAGlD,GAAG,GAAqB,KAAK,EAC1B,IAAI,GAAM,GAAqB,EAAI,CAAE,aAAW,WAAS,UAAQ,CAAC,CAAC,EAGtE,GAAG,GAAqB,KAAK,EAC1B,IAAI,GAAM,GAAe,EAAI,CAAE,aAAW,WAAS,SAAO,UAAQ,CAAC,CAAC,CACzE,CAAC,EAGK,GAAa,GAChB,KACC,EAAU,IAAM,EAAQ,EACxB,GAAU,EAAQ,EAClB,EAAY,CAAC,CACf,EAGF,GAAW,UAAU,EAMrB,OAAO,UAAa,GACpB,OAAO,UAAa,GACpB,OAAO,QAAa,GACpB,OAAO,UAAa,GACpB,OAAO,UAAa,GACpB,OAAO,QAAa,GACpB,OAAO,QAAa,GACpB,OAAO,OAAa,GACpB,OAAO,OAAa,GACpB,OAAO,WAAa",
-  "names": []
-}
diff --git a/7.3/assets/javascripts/extra/bundle.5f09fbc3.min.js b/7.3/assets/javascripts/extra/bundle.5f09fbc3.min.js
new file mode 100644
index 0000000000..48b752cd03
--- /dev/null
+++ b/7.3/assets/javascripts/extra/bundle.5f09fbc3.min.js
@@ -0,0 +1,18 @@
+"use strict";(()=>{var Je=Object.create;var qr=Object.defineProperty;var $e=Object.getOwnPropertyDescriptor;var Qe=Object.getOwnPropertyNames;var Xe=Object.getPrototypeOf,Ze=Object.prototype.hasOwnProperty;var rt=(r,o)=>()=>(o||r((o={exports:{}}).exports,o),o.exports);var et=(r,o,t,e)=>{if(o&&typeof o=="object"||typeof o=="function")for(let n of Qe(o))!Ze.call(r,n)&&n!==t&&qr(r,n,{get:()=>o[n],enumerable:!(e=$e(o,n))||e.enumerable});return r};var tt=(r,o,t)=>(t=r!=null?Je(Xe(r)):{},et(o||!r||!r.__esModule?qr(t,"default",{value:r,enumerable:!0}):t,r));var me=rt((Tt,er)=>{/*! *****************************************************************************
+Copyright (c) Microsoft Corporation.
+
+Permission to use, copy, modify, and/or distribute this software for any
+purpose with or without fee is hereby granted.
+
+THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
+REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
+AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
+INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
+LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
+OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
+PERFORMANCE OF THIS SOFTWARE.
+***************************************************************************** */var Hr,Kr,Jr,$r,Qr,Xr,Zr,re,ee,Z,Ar,te,oe,ne,k,ie,fe,ae,ue,ce,se,pe,le,rr;(function(r){var o=typeof global=="object"?global:typeof self=="object"?self:typeof this=="object"?this:{};typeof define=="function"&&define.amd?define("tslib",["exports"],function(e){r(t(o,t(e)))}):typeof er=="object"&&typeof er.exports=="object"?r(t(o,t(er.exports))):r(t(o));function t(e,n){return e!==o&&(typeof Object.create=="function"?Object.defineProperty(e,"__esModule",{value:!0}):e.__esModule=!0),function(i,f){return e[i]=n?n(i,f):f}}})(function(r){var o=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,n){e.__proto__=n}||function(e,n){for(var i in n)Object.prototype.hasOwnProperty.call(n,i)&&(e[i]=n[i])};Hr=function(e,n){if(typeof n!="function"&&n!==null)throw new TypeError("Class extends value "+String(n)+" is not a constructor or null");o(e,n);function i(){this.constructor=e}e.prototype=n===null?Object.create(n):(i.prototype=n.prototype,new i)},Kr=Object.assign||function(e){for(var n,i=1,f=arguments.length;i<f;i++){n=arguments[i];for(var u in n)Object.prototype.hasOwnProperty.call(n,u)&&(e[u]=n[u])}return e},Jr=function(e,n){var i={};for(var f in e)Object.prototype.hasOwnProperty.call(e,f)&&n.indexOf(f)<0&&(i[f]=e[f]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var u=0,f=Object.getOwnPropertySymbols(e);u<f.length;u++)n.indexOf(f[u])<0&&Object.prototype.propertyIsEnumerable.call(e,f[u])&&(i[f[u]]=e[f[u]]);return i},$r=function(e,n,i,f){var u=arguments.length,a=u<3?n:f===null?f=Object.getOwnPropertyDescriptor(n,i):f,c;if(typeof Reflect=="object"&&typeof Reflect.decorate=="function")a=Reflect.decorate(e,n,i,f);else for(var s=e.length-1;s>=0;s--)(c=e[s])&&(a=(u<3?c(a):u>3?c(n,i,a):c(n,i))||a);return u>3&&a&&Object.defineProperty(n,i,a),a},Qr=function(e,n){return function(i,f){n(i,f,e)}},Xr=function(e,n){if(typeof Reflect=="object"&&typeof Reflect.metadata=="function")return Reflect.metadata(e,n)},Zr=function(e,n,i,f){function u(a){return a instanceof i?a:new i(function(c){c(a)})}return new(i||(i=Promise))(function(a,c){function s(y){try{p(f.next(y))}catch(g){c(g)}}function d(y){try{p(f.throw(y))}catch(g){c(g)}}function p(y){y.done?a(y.value):u(y.value).then(s,d)}p((f=f.apply(e,n||[])).next())})},re=function(e,n){var i={label:0,sent:function(){if(a[0]&1)throw a[1];return a[1]},trys:[],ops:[]},f,u,a,c;return c={next:s(0),throw:s(1),return:s(2)},typeof Symbol=="function"&&(c[Symbol.iterator]=function(){return this}),c;function s(p){return function(y){return d([p,y])}}function d(p){if(f)throw new TypeError("Generator is already executing.");for(;i;)try{if(f=1,u&&(a=p[0]&2?u.return:p[0]?u.throw||((a=u.return)&&a.call(u),0):u.next)&&!(a=a.call(u,p[1])).done)return a;switch(u=0,a&&(p=[p[0]&2,a.value]),p[0]){case 0:case 1:a=p;break;case 4:return i.label++,{value:p[1],done:!1};case 5:i.label++,u=p[1],p=[0];continue;case 7:p=i.ops.pop(),i.trys.pop();continue;default:if(a=i.trys,!(a=a.length>0&&a[a.length-1])&&(p[0]===6||p[0]===2)){i=0;continue}if(p[0]===3&&(!a||p[1]>a[0]&&p[1]<a[3])){i.label=p[1];break}if(p[0]===6&&i.label<a[1]){i.label=a[1],a=p;break}if(a&&i.label<a[2]){i.label=a[2],i.ops.push(p);break}a[2]&&i.ops.pop(),i.trys.pop();continue}p=n.call(e,i)}catch(y){p=[6,y],u=0}finally{f=a=0}if(p[0]&5)throw p[1];return{value:p[0]?p[1]:void 0,done:!0}}},ee=function(e,n){for(var i in e)i!=="default"&&!Object.prototype.hasOwnProperty.call(n,i)&&rr(n,e,i)},rr=Object.create?function(e,n,i,f){f===void 0&&(f=i),Object.defineProperty(e,f,{enumerable:!0,get:function(){return n[i]}})}:function(e,n,i,f){f===void 0&&(f=i),e[f]=n[i]},Z=function(e){var n=typeof Symbol=="function"&&Symbol.iterator,i=n&&e[n],f=0;if(i)return i.call(e);if(e&&typeof e.length=="number")return{next:function(){return e&&f>=e.length&&(e=void 0),{value:e&&e[f++],done:!e}}};throw new TypeError(n?"Object is not iterable.":"Symbol.iterator is not defined.")},Ar=function(e,n){var i=typeof Symbol=="function"&&e[Symbol.iterator];if(!i)return e;var f=i.call(e),u,a=[],c;try{for(;(n===void 0||n-- >0)&&!(u=f.next()).done;)a.push(u.value)}catch(s){c={error:s}}finally{try{u&&!u.done&&(i=f.return)&&i.call(f)}finally{if(c)throw c.error}}return a},te=function(){for(var e=[],n=0;n<arguments.length;n++)e=e.concat(Ar(arguments[n]));return e},oe=function(){for(var e=0,n=0,i=arguments.length;n<i;n++)e+=arguments[n].length;for(var f=Array(e),u=0,n=0;n<i;n++)for(var a=arguments[n],c=0,s=a.length;c<s;c++,u++)f[u]=a[c];return f},ne=function(e,n,i){if(i||arguments.length===2)for(var f=0,u=n.length,a;f<u;f++)(a||!(f in n))&&(a||(a=Array.prototype.slice.call(n,0,f)),a[f]=n[f]);return e.concat(a||Array.prototype.slice.call(n))},k=function(e){return this instanceof k?(this.v=e,this):new k(e)},ie=function(e,n,i){if(!Symbol.asyncIterator)throw new TypeError("Symbol.asyncIterator is not defined.");var f=i.apply(e,n||[]),u,a=[];return u={},c("next"),c("throw"),c("return"),u[Symbol.asyncIterator]=function(){return this},u;function c(m){f[m]&&(u[m]=function(P){return new Promise(function(j,R){a.push([m,P,j,R])>1||s(m,P)})})}function s(m,P){try{d(f[m](P))}catch(j){g(a[0][3],j)}}function d(m){m.value instanceof k?Promise.resolve(m.value.v).then(p,y):g(a[0][2],m)}function p(m){s("next",m)}function y(m){s("throw",m)}function g(m,P){m(P),a.shift(),a.length&&s(a[0][0],a[0][1])}},fe=function(e){var n,i;return n={},f("next"),f("throw",function(u){throw u}),f("return"),n[Symbol.iterator]=function(){return this},n;function f(u,a){n[u]=e[u]?function(c){return(i=!i)?{value:k(e[u](c)),done:u==="return"}:a?a(c):c}:a}},ae=function(e){if(!Symbol.asyncIterator)throw new TypeError("Symbol.asyncIterator is not defined.");var n=e[Symbol.asyncIterator],i;return n?n.call(e):(e=typeof Z=="function"?Z(e):e[Symbol.iterator](),i={},f("next"),f("throw"),f("return"),i[Symbol.asyncIterator]=function(){return this},i);function f(a){i[a]=e[a]&&function(c){return new Promise(function(s,d){c=e[a](c),u(s,d,c.done,c.value)})}}function u(a,c,s,d){Promise.resolve(d).then(function(p){a({value:p,done:s})},c)}},ue=function(e,n){return Object.defineProperty?Object.defineProperty(e,"raw",{value:n}):e.raw=n,e};var t=Object.create?function(e,n){Object.defineProperty(e,"default",{enumerable:!0,value:n})}:function(e,n){e.default=n};ce=function(e){if(e&&e.__esModule)return e;var n={};if(e!=null)for(var i in e)i!=="default"&&Object.prototype.hasOwnProperty.call(e,i)&&rr(n,e,i);return t(n,e),n},se=function(e){return e&&e.__esModule?e:{default:e}},pe=function(e,n,i,f){if(i==="a"&&!f)throw new TypeError("Private accessor was defined without a getter");if(typeof n=="function"?e!==n||!f:!n.has(e))throw new TypeError("Cannot read private member from an object whose class did not declare it");return i==="m"?f:i==="a"?f.call(e):f?f.value:n.get(e)},le=function(e,n,i,f,u){if(f==="m")throw new TypeError("Private method is not writable");if(f==="a"&&!u)throw new TypeError("Private accessor was defined without a setter");if(typeof n=="function"?e!==n||!u:!n.has(e))throw new TypeError("Cannot write private member to an object whose class did not declare it");return f==="a"?u.call(e,i):u?u.value=i:n.set(e,i),i},r("__extends",Hr),r("__assign",Kr),r("__rest",Jr),r("__decorate",$r),r("__param",Qr),r("__metadata",Xr),r("__awaiter",Zr),r("__generator",re),r("__exportStar",ee),r("__createBinding",rr),r("__values",Z),r("__read",Ar),r("__spread",te),r("__spreadArrays",oe),r("__spreadArray",ne),r("__await",k),r("__asyncGenerator",ie),r("__asyncDelegator",fe),r("__asyncValues",ae),r("__makeTemplateObject",ue),r("__importStar",ce),r("__importDefault",se),r("__classPrivateFieldGet",pe),r("__classPrivateFieldSet",le)})});var de=tt(me(),1),{__extends:_,__assign:Pt,__rest:jt,__decorate:Ft,__param:Mt,__metadata:Ct,__awaiter:he,__generator:tr,__exportStar:Lt,__createBinding:Rt,__values:M,__read:w,__spread:kt,__spreadArrays:Ut,__spreadArray:S,__await:or,__asyncGenerator:ve,__asyncDelegator:Wt,__asyncValues:be,__makeTemplateObject:Dt,__importStar:Vt,__importDefault:Bt,__classPrivateFieldGet:Gt,__classPrivateFieldSet:Nt}=de.default;function l(r){return typeof r=="function"}function nr(r){var o=function(e){Error.call(e),e.stack=new Error().stack},t=r(o);return t.prototype=Object.create(Error.prototype),t.prototype.constructor=t,t}var ir=nr(function(r){return function(t){r(this),this.message=t?t.length+` errors occurred during unsubscription:
+`+t.map(function(e,n){return n+1+") "+e.toString()}).join(`
+  `):"",this.name="UnsubscriptionError",this.errors=t}});function C(r,o){if(r){var t=r.indexOf(o);0<=t&&r.splice(t,1)}}var F=function(){function r(o){this.initialTeardown=o,this.closed=!1,this._parentage=null,this._finalizers=null}return r.prototype.unsubscribe=function(){var o,t,e,n,i;if(!this.closed){this.closed=!0;var f=this._parentage;if(f)if(this._parentage=null,Array.isArray(f))try{for(var u=M(f),a=u.next();!a.done;a=u.next()){var c=a.value;c.remove(this)}}catch(m){o={error:m}}finally{try{a&&!a.done&&(t=u.return)&&t.call(u)}finally{if(o)throw o.error}}else f.remove(this);var s=this.initialTeardown;if(l(s))try{s()}catch(m){i=m instanceof ir?m.errors:[m]}var d=this._finalizers;if(d){this._finalizers=null;try{for(var p=M(d),y=p.next();!y.done;y=p.next()){var g=y.value;try{ye(g)}catch(m){i=i!=null?i:[],m instanceof ir?i=S(S([],w(i)),w(m.errors)):i.push(m)}}}catch(m){e={error:m}}finally{try{y&&!y.done&&(n=p.return)&&n.call(p)}finally{if(e)throw e.error}}}if(i)throw new ir(i)}},r.prototype.add=function(o){var t;if(o&&o!==this)if(this.closed)ye(o);else{if(o instanceof r){if(o.closed||o._hasParent(this))return;o._addParent(this)}(this._finalizers=(t=this._finalizers)!==null&&t!==void 0?t:[]).push(o)}},r.prototype._hasParent=function(o){var t=this._parentage;return t===o||Array.isArray(t)&&t.includes(o)},r.prototype._addParent=function(o){var t=this._parentage;this._parentage=Array.isArray(t)?(t.push(o),t):t?[t,o]:o},r.prototype._removeParent=function(o){var t=this._parentage;t===o?this._parentage=null:Array.isArray(t)&&C(t,o)},r.prototype.remove=function(o){var t=this._finalizers;t&&C(t,o),o instanceof r&&o._removeParent(this)},r.EMPTY=function(){var o=new r;return o.closed=!0,o}(),r}();var Ir=F.EMPTY;function fr(r){return r instanceof F||r&&"closed"in r&&l(r.remove)&&l(r.add)&&l(r.unsubscribe)}function ye(r){l(r)?r():r.unsubscribe()}var O={onUnhandledError:null,onStoppedNotification:null,Promise:void 0,useDeprecatedSynchronousErrorHandling:!1,useDeprecatedNextContext:!1};var U={setTimeout:function(r,o){for(var t=[],e=2;e<arguments.length;e++)t[e-2]=arguments[e];var n=U.delegate;return n!=null&&n.setTimeout?n.setTimeout.apply(n,S([r,o],w(t))):setTimeout.apply(void 0,S([r,o],w(t)))},clearTimeout:function(r){var o=U.delegate;return((o==null?void 0:o.clearTimeout)||clearTimeout)(r)},delegate:void 0};function ar(r){U.setTimeout(function(){var o=O.onUnhandledError;if(o)o(r);else throw r})}function A(){}var xe=function(){return Tr("C",void 0,void 0)}();function _e(r){return Tr("E",void 0,r)}function we(r){return Tr("N",r,void 0)}function Tr(r,o,t){return{kind:r,value:o,error:t}}var L=null;function W(r){if(O.useDeprecatedSynchronousErrorHandling){var o=!L;if(o&&(L={errorThrown:!1,error:null}),r(),o){var t=L,e=t.errorThrown,n=t.error;if(L=null,e)throw n}}else r()}function Se(r){O.useDeprecatedSynchronousErrorHandling&&L&&(L.errorThrown=!0,L.error=r)}var K=function(r){_(o,r);function o(t){var e=r.call(this)||this;return e.isStopped=!1,t?(e.destination=t,fr(t)&&t.add(e)):e.destination=ft,e}return o.create=function(t,e,n){return new cr(t,e,n)},o.prototype.next=function(t){this.isStopped?jr(we(t),this):this._next(t)},o.prototype.error=function(t){this.isStopped?jr(_e(t),this):(this.isStopped=!0,this._error(t))},o.prototype.complete=function(){this.isStopped?jr(xe,this):(this.isStopped=!0,this._complete())},o.prototype.unsubscribe=function(){this.closed||(this.isStopped=!0,r.prototype.unsubscribe.call(this),this.destination=null)},o.prototype._next=function(t){this.destination.next(t)},o.prototype._error=function(t){try{this.destination.error(t)}finally{this.unsubscribe()}},o.prototype._complete=function(){try{this.destination.complete()}finally{this.unsubscribe()}},o}(F);var ot=Function.prototype.bind;function Pr(r,o){return ot.call(r,o)}var nt=function(){function r(o){this.partialObserver=o}return r.prototype.next=function(o){var t=this.partialObserver;if(t.next)try{t.next(o)}catch(e){ur(e)}},r.prototype.error=function(o){var t=this.partialObserver;if(t.error)try{t.error(o)}catch(e){ur(e)}else ur(o)},r.prototype.complete=function(){var o=this.partialObserver;if(o.complete)try{o.complete()}catch(t){ur(t)}},r}(),cr=function(r){_(o,r);function o(t,e,n){var i=r.call(this)||this,f;if(l(t)||!t)f={next:t!=null?t:void 0,error:e!=null?e:void 0,complete:n!=null?n:void 0};else{var u;i&&O.useDeprecatedNextContext?(u=Object.create(t),u.unsubscribe=function(){return i.unsubscribe()},f={next:t.next&&Pr(t.next,u),error:t.error&&Pr(t.error,u),complete:t.complete&&Pr(t.complete,u)}):f=t}return i.destination=new nt(f),i}return o}(K);function ur(r){O.useDeprecatedSynchronousErrorHandling?Se(r):ar(r)}function it(r){throw r}function jr(r,o){var t=O.onStoppedNotification;t&&U.setTimeout(function(){return t(r,o)})}var ft={closed:!0,next:A,error:it,complete:A};var D=function(){return typeof Symbol=="function"&&Symbol.observable||"@@observable"}();function I(r){return r}function ge(r){return r.length===0?I:r.length===1?r[0]:function(t){return r.reduce(function(e,n){return n(e)},t)}}var b=function(){function r(o){o&&(this._subscribe=o)}return r.prototype.lift=function(o){var t=new r;return t.source=this,t.operator=o,t},r.prototype.subscribe=function(o,t,e){var n=this,i=ut(o)?o:new cr(o,t,e);return W(function(){var f=n,u=f.operator,a=f.source;i.add(u?u.call(i,a):a?n._subscribe(i):n._trySubscribe(i))}),i},r.prototype._trySubscribe=function(o){try{return this._subscribe(o)}catch(t){o.error(t)}},r.prototype.forEach=function(o,t){var e=this;return t=Ee(t),new t(function(n,i){var f=new cr({next:function(u){try{o(u)}catch(a){i(a),f.unsubscribe()}},error:i,complete:n});e.subscribe(f)})},r.prototype._subscribe=function(o){var t;return(t=this.source)===null||t===void 0?void 0:t.subscribe(o)},r.prototype[D]=function(){return this},r.prototype.pipe=function(){for(var o=[],t=0;t<arguments.length;t++)o[t]=arguments[t];return ge(o)(this)},r.prototype.toPromise=function(o){var t=this;return o=Ee(o),new o(function(e,n){var i;t.subscribe(function(f){return i=f},function(f){return n(f)},function(){return e(i)})})},r.create=function(o){return new r(o)},r}();function Ee(r){var o;return(o=r!=null?r:O.Promise)!==null&&o!==void 0?o:Promise}function at(r){return r&&l(r.next)&&l(r.error)&&l(r.complete)}function ut(r){return r&&r instanceof K||at(r)&&fr(r)}function ct(r){return l(r==null?void 0:r.lift)}function h(r){return function(o){if(ct(o))return o.lift(function(t){try{return r(t,this)}catch(e){this.error(e)}});throw new TypeError("Unable to lift unknown Observable type")}}function v(r,o,t,e,n){return new st(r,o,t,e,n)}var st=function(r){_(o,r);function o(t,e,n,i,f,u){var a=r.call(this,t)||this;return a.onFinalize=f,a.shouldUnsubscribe=u,a._next=e?function(c){try{e(c)}catch(s){t.error(s)}}:r.prototype._next,a._error=i?function(c){try{i(c)}catch(s){t.error(s)}finally{this.unsubscribe()}}:r.prototype._error,a._complete=n?function(){try{n()}catch(c){t.error(c)}finally{this.unsubscribe()}}:r.prototype._complete,a}return o.prototype.unsubscribe=function(){var t;if(!this.shouldUnsubscribe||this.shouldUnsubscribe()){var e=this.closed;r.prototype.unsubscribe.call(this),!e&&((t=this.onFinalize)===null||t===void 0||t.call(this))}},o}(K);var Oe=nr(function(r){return function(){r(this),this.name="ObjectUnsubscribedError",this.message="object unsubscribed"}});var Fr=function(r){_(o,r);function o(){var t=r.call(this)||this;return t.closed=!1,t.currentObservers=null,t.observers=[],t.isStopped=!1,t.hasError=!1,t.thrownError=null,t}return o.prototype.lift=function(t){var e=new Ae(this,this);return e.operator=t,e},o.prototype._throwIfClosed=function(){if(this.closed)throw new Oe},o.prototype.next=function(t){var e=this;W(function(){var n,i;if(e._throwIfClosed(),!e.isStopped){e.currentObservers||(e.currentObservers=Array.from(e.observers));try{for(var f=M(e.currentObservers),u=f.next();!u.done;u=f.next()){var a=u.value;a.next(t)}}catch(c){n={error:c}}finally{try{u&&!u.done&&(i=f.return)&&i.call(f)}finally{if(n)throw n.error}}}})},o.prototype.error=function(t){var e=this;W(function(){if(e._throwIfClosed(),!e.isStopped){e.hasError=e.isStopped=!0,e.thrownError=t;for(var n=e.observers;n.length;)n.shift().error(t)}})},o.prototype.complete=function(){var t=this;W(function(){if(t._throwIfClosed(),!t.isStopped){t.isStopped=!0;for(var e=t.observers;e.length;)e.shift().complete()}})},o.prototype.unsubscribe=function(){this.isStopped=this.closed=!0,this.observers=this.currentObservers=null},Object.defineProperty(o.prototype,"observed",{get:function(){var t;return((t=this.observers)===null||t===void 0?void 0:t.length)>0},enumerable:!1,configurable:!0}),o.prototype._trySubscribe=function(t){return this._throwIfClosed(),r.prototype._trySubscribe.call(this,t)},o.prototype._subscribe=function(t){return this._throwIfClosed(),this._checkFinalizedStatuses(t),this._innerSubscribe(t)},o.prototype._innerSubscribe=function(t){var e=this,n=this,i=n.hasError,f=n.isStopped,u=n.observers;return i||f?Ir:(this.currentObservers=null,u.push(t),new F(function(){e.currentObservers=null,C(u,t)}))},o.prototype._checkFinalizedStatuses=function(t){var e=this,n=e.hasError,i=e.thrownError,f=e.isStopped;n?t.error(i):f&&t.complete()},o.prototype.asObservable=function(){var t=new b;return t.source=this,t},o.create=function(t,e){return new Ae(t,e)},o}(b);var Ae=function(r){_(o,r);function o(t,e){var n=r.call(this)||this;return n.destination=t,n.source=e,n}return o.prototype.next=function(t){var e,n;(n=(e=this.destination)===null||e===void 0?void 0:e.next)===null||n===void 0||n.call(e,t)},o.prototype.error=function(t){var e,n;(n=(e=this.destination)===null||e===void 0?void 0:e.error)===null||n===void 0||n.call(e,t)},o.prototype.complete=function(){var t,e;(e=(t=this.destination)===null||t===void 0?void 0:t.complete)===null||e===void 0||e.call(t)},o.prototype._subscribe=function(t){var e,n;return(n=(e=this.source)===null||e===void 0?void 0:e.subscribe(t))!==null&&n!==void 0?n:Ir},o}(Fr);var J={now:function(){return(J.delegate||Date).now()},delegate:void 0};var Mr=function(r){_(o,r);function o(t,e,n){t===void 0&&(t=1/0),e===void 0&&(e=1/0),n===void 0&&(n=J);var i=r.call(this)||this;return i._bufferSize=t,i._windowTime=e,i._timestampProvider=n,i._buffer=[],i._infiniteTimeWindow=!0,i._infiniteTimeWindow=e===1/0,i._bufferSize=Math.max(1,t),i._windowTime=Math.max(1,e),i}return o.prototype.next=function(t){var e=this,n=e.isStopped,i=e._buffer,f=e._infiniteTimeWindow,u=e._timestampProvider,a=e._windowTime;n||(i.push(t),!f&&i.push(u.now()+a)),this._trimBuffer(),r.prototype.next.call(this,t)},o.prototype._subscribe=function(t){this._throwIfClosed(),this._trimBuffer();for(var e=this._innerSubscribe(t),n=this,i=n._infiniteTimeWindow,f=n._buffer,u=f.slice(),a=0;a<u.length&&!t.closed;a+=i?1:2)t.next(u[a]);return this._checkFinalizedStatuses(t),e},o.prototype._trimBuffer=function(){var t=this,e=t._bufferSize,n=t._timestampProvider,i=t._buffer,f=t._infiniteTimeWindow,u=(f?1:2)*e;if(e<1/0&&u<i.length&&i.splice(0,i.length-u),!f){for(var a=n.now(),c=0,s=1;s<i.length&&i[s]<=a;s+=2)c=s;c&&i.splice(0,c+1)}},o}(Fr);var Ie=function(r){_(o,r);function o(t,e){return r.call(this)||this}return o.prototype.schedule=function(t,e){return e===void 0&&(e=0),this},o}(F);var $={setInterval:function(r,o){for(var t=[],e=2;e<arguments.length;e++)t[e-2]=arguments[e];var n=$.delegate;return n!=null&&n.setInterval?n.setInterval.apply(n,S([r,o],w(t))):setInterval.apply(void 0,S([r,o],w(t)))},clearInterval:function(r){var o=$.delegate;return((o==null?void 0:o.clearInterval)||clearInterval)(r)},delegate:void 0};var Te=function(r){_(o,r);function o(t,e){var n=r.call(this,t,e)||this;return n.scheduler=t,n.work=e,n.pending=!1,n}return o.prototype.schedule=function(t,e){var n;if(e===void 0&&(e=0),this.closed)return this;this.state=t;var i=this.id,f=this.scheduler;return i!=null&&(this.id=this.recycleAsyncId(f,i,e)),this.pending=!0,this.delay=e,this.id=(n=this.id)!==null&&n!==void 0?n:this.requestAsyncId(f,this.id,e),this},o.prototype.requestAsyncId=function(t,e,n){return n===void 0&&(n=0),$.setInterval(t.flush.bind(t,this),n)},o.prototype.recycleAsyncId=function(t,e,n){if(n===void 0&&(n=0),n!=null&&this.delay===n&&this.pending===!1)return e;e!=null&&$.clearInterval(e)},o.prototype.execute=function(t,e){if(this.closed)return new Error("executing a cancelled action");this.pending=!1;var n=this._execute(t,e);if(n)return n;this.pending===!1&&this.id!=null&&(this.id=this.recycleAsyncId(this.scheduler,this.id,null))},o.prototype._execute=function(t,e){var n=!1,i;try{this.work(t)}catch(f){n=!0,i=f||new Error("Scheduled action threw falsy error")}if(n)return this.unsubscribe(),i},o.prototype.unsubscribe=function(){if(!this.closed){var t=this,e=t.id,n=t.scheduler,i=n.actions;this.work=this.state=this.scheduler=null,this.pending=!1,C(i,this),e!=null&&(this.id=this.recycleAsyncId(n,e,null)),this.delay=null,r.prototype.unsubscribe.call(this)}},o}(Ie);var Cr=function(){function r(o,t){t===void 0&&(t=r.now),this.schedulerActionCtor=o,this.now=t}return r.prototype.schedule=function(o,t,e){return t===void 0&&(t=0),new this.schedulerActionCtor(this,o).schedule(e,t)},r.now=J.now,r}();var Pe=function(r){_(o,r);function o(t,e){e===void 0&&(e=Cr.now);var n=r.call(this,t,e)||this;return n.actions=[],n._active=!1,n}return o.prototype.flush=function(t){var e=this.actions;if(this._active){e.push(t);return}var n;this._active=!0;do if(n=t.execute(t.state,t.delay))break;while(t=e.shift());if(this._active=!1,n){for(;t=e.shift();)t.unsubscribe();throw n}},o}(Cr);var Q=new Pe(Te),je=Q;var V=new b(function(r){return r.complete()});function sr(r){return r&&l(r.schedule)}function Lr(r){return r[r.length-1]}function Fe(r){return l(Lr(r))?r.pop():void 0}function B(r){return sr(Lr(r))?r.pop():void 0}function Me(r,o){return typeof Lr(r)=="number"?r.pop():o}var G=function(r){return r&&typeof r.length=="number"&&typeof r!="function"};function pr(r){return l(r==null?void 0:r.then)}function lr(r){return l(r[D])}function mr(r){return Symbol.asyncIterator&&l(r==null?void 0:r[Symbol.asyncIterator])}function dr(r){return new TypeError("You provided "+(r!==null&&typeof r=="object"?"an invalid object":"'"+r+"'")+" where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.")}function pt(){return typeof Symbol!="function"||!Symbol.iterator?"@@iterator":Symbol.iterator}var hr=pt();function vr(r){return l(r==null?void 0:r[hr])}function br(r){return ve(this,arguments,function(){var t,e,n,i;return tr(this,function(f){switch(f.label){case 0:t=r.getReader(),f.label=1;case 1:f.trys.push([1,,9,10]),f.label=2;case 2:return[4,or(t.read())];case 3:return e=f.sent(),n=e.value,i=e.done,i?[4,or(void 0)]:[3,5];case 4:return[2,f.sent()];case 5:return[4,or(n)];case 6:return[4,f.sent()];case 7:return f.sent(),[3,2];case 8:return[3,10];case 9:return t.releaseLock(),[7];case 10:return[2]}})})}function yr(r){return l(r==null?void 0:r.getReader)}function x(r){if(r instanceof b)return r;if(r!=null){if(lr(r))return lt(r);if(G(r))return mt(r);if(pr(r))return dt(r);if(mr(r))return Ce(r);if(vr(r))return ht(r);if(yr(r))return vt(r)}throw dr(r)}function lt(r){return new b(function(o){var t=r[D]();if(l(t.subscribe))return t.subscribe(o);throw new TypeError("Provided object does not correctly implement Symbol.observable")})}function mt(r){return new b(function(o){for(var t=0;t<r.length&&!o.closed;t++)o.next(r[t]);o.complete()})}function dt(r){return new b(function(o){r.then(function(t){o.closed||(o.next(t),o.complete())},function(t){return o.error(t)}).then(null,ar)})}function ht(r){return new b(function(o){var t,e;try{for(var n=M(r),i=n.next();!i.done;i=n.next()){var f=i.value;if(o.next(f),o.closed)return}}catch(u){t={error:u}}finally{try{i&&!i.done&&(e=n.return)&&e.call(n)}finally{if(t)throw t.error}}o.complete()})}function Ce(r){return new b(function(o){bt(r,o).catch(function(t){return o.error(t)})})}function vt(r){return Ce(br(r))}function bt(r,o){var t,e,n,i;return he(this,void 0,void 0,function(){var f,u;return tr(this,function(a){switch(a.label){case 0:a.trys.push([0,5,6,11]),t=be(r),a.label=1;case 1:return[4,t.next()];case 2:if(e=a.sent(),!!e.done)return[3,4];if(f=e.value,o.next(f),o.closed)return[2];a.label=3;case 3:return[3,1];case 4:return[3,11];case 5:return u=a.sent(),n={error:u},[3,11];case 6:return a.trys.push([6,,9,10]),e&&!e.done&&(i=t.return)?[4,i.call(t)]:[3,8];case 7:a.sent(),a.label=8;case 8:return[3,10];case 9:if(n)throw n.error;return[7];case 10:return[7];case 11:return o.complete(),[2]}})})}function E(r,o,t,e,n){e===void 0&&(e=0),n===void 0&&(n=!1);var i=o.schedule(function(){t(),n?r.add(this.schedule(null,e)):this.unsubscribe()},e);if(r.add(i),!n)return i}function xr(r,o){return o===void 0&&(o=0),h(function(t,e){t.subscribe(v(e,function(n){return E(e,r,function(){return e.next(n)},o)},function(){return E(e,r,function(){return e.complete()},o)},function(n){return E(e,r,function(){return e.error(n)},o)}))})}function _r(r,o){return o===void 0&&(o=0),h(function(t,e){e.add(r.schedule(function(){return t.subscribe(e)},o))})}function Le(r,o){return x(r).pipe(_r(o),xr(o))}function Re(r,o){return x(r).pipe(_r(o),xr(o))}function ke(r,o){return new b(function(t){var e=0;return o.schedule(function(){e===r.length?t.complete():(t.next(r[e++]),t.closed||this.schedule())})})}function Ue(r,o){return new b(function(t){var e;return E(t,o,function(){e=r[hr](),E(t,o,function(){var n,i,f;try{n=e.next(),i=n.value,f=n.done}catch(u){t.error(u);return}f?t.complete():t.next(i)},0,!0)}),function(){return l(e==null?void 0:e.return)&&e.return()}})}function wr(r,o){if(!r)throw new Error("Iterable cannot be null");return new b(function(t){E(t,o,function(){var e=r[Symbol.asyncIterator]();E(t,o,function(){e.next().then(function(n){n.done?t.complete():t.next(n.value)})},0,!0)})})}function We(r,o){return wr(br(r),o)}function De(r,o){if(r!=null){if(lr(r))return Le(r,o);if(G(r))return ke(r,o);if(pr(r))return Re(r,o);if(mr(r))return wr(r,o);if(vr(r))return Ue(r,o);if(yr(r))return We(r,o)}throw dr(r)}function N(r,o){return o?De(r,o):x(r)}function Rr(){for(var r=[],o=0;o<arguments.length;o++)r[o]=arguments[o];var t=B(r);return N(r,t)}function Ve(r){return r instanceof Date&&!isNaN(r)}function Y(r,o){return h(function(t,e){var n=0;t.subscribe(v(e,function(i){e.next(r.call(o,i,n++))}))})}var yt=Array.isArray;function xt(r,o){return yt(o)?r.apply(void 0,S([],w(o))):r(o)}function Be(r){return Y(function(o){return xt(r,o)})}function Ge(r,o,t,e,n,i,f,u){var a=[],c=0,s=0,d=!1,p=function(){d&&!a.length&&!c&&o.complete()},y=function(m){return c<e?g(m):a.push(m)},g=function(m){i&&o.next(m),c++;var P=!1;x(t(m,s++)).subscribe(v(o,function(j){n==null||n(j),i?y(j):o.next(j)},function(){P=!0},void 0,function(){if(P)try{c--;for(var j=function(){var R=a.shift();f?E(o,f,function(){return g(R)}):g(R)};a.length&&c<e;)j();p()}catch(R){o.error(R)}}))};return r.subscribe(v(o,y,function(){d=!0,p()})),function(){u==null||u()}}function T(r,o,t){return t===void 0&&(t=1/0),l(o)?T(function(e,n){return Y(function(i,f){return o(e,i,n,f)})(x(r(e,n)))},t):(typeof o=="number"&&(t=o),h(function(e,n){return Ge(e,n,r,t)}))}function Sr(r){return r===void 0&&(r=1/0),T(I,r)}function Ne(){return Sr(1)}function Ye(){for(var r=[],o=0;o<arguments.length;o++)r[o]=arguments[o];return Ne()(N(r,B(r)))}var _t=["addListener","removeListener"],wt=["addEventListener","removeEventListener"],St=["on","off"];function z(r,o,t,e){if(l(t)&&(e=t,t=void 0),e)return z(r,o,t).pipe(Be(e));var n=w(Ot(r)?wt.map(function(u){return function(a){return r[u](o,a,t)}}):gt(r)?_t.map(ze(r,o)):Et(r)?St.map(ze(r,o)):[],2),i=n[0],f=n[1];if(!i&&G(r))return T(function(u){return z(u,o,t)})(x(r));if(!i)throw new TypeError("Invalid event target");return new b(function(u){var a=function(){for(var c=[],s=0;s<arguments.length;s++)c[s]=arguments[s];return u.next(1<c.length?c:c[0])};return i(a),function(){return f(a)}})}function ze(r,o){return function(t){return function(e){return r[t](o,e)}}}function gt(r){return l(r.addListener)&&l(r.removeListener)}function Et(r){return l(r.on)&&l(r.off)}function Ot(r){return l(r.addEventListener)&&l(r.removeEventListener)}function q(r,o,t){r===void 0&&(r=0),t===void 0&&(t=je);var e=-1;return o!=null&&(sr(o)?t=o:e=o),new b(function(n){var i=Ve(r)?+r-t.now():r;i<0&&(i=0);var f=0;return t.schedule(function(){n.closed||(n.next(f++),0<=e?this.schedule(void 0,e):n.complete())},i)})}function kr(r,o){return r===void 0&&(r=0),o===void 0&&(o=Q),r<0&&(r=0),q(r,r,o)}function Ur(){for(var r=[],o=0;o<arguments.length;o++)r[o]=arguments[o];var t=B(r),e=Me(r,1/0),n=r;return n.length?n.length===1?x(n[0]):Sr(e)(N(n,t)):V}var Wr=new b(A);function X(r,o){return h(function(t,e){var n=0;t.subscribe(v(e,function(i){return r.call(o,i,n++)&&e.next(i)}))})}function H(r){return r<=0?function(){return V}:h(function(o,t){var e=0;o.subscribe(v(t,function(n){++e<=r&&(t.next(n),r<=e&&t.complete())}))})}function qe(){return h(function(r,o){r.subscribe(v(o,A))})}function He(r){return Y(function(){return r})}function Dr(r,o){return o?function(t){return Ye(o.pipe(H(1),qe()),t.pipe(Dr(r)))}:T(function(t,e){return r(t,e).pipe(H(1),He(t))})}function Vr(r,o){o===void 0&&(o=Q);var t=q(r,o);return Dr(function(){return t})}function Br(r,o){return o===void 0&&(o=I),r=r!=null?r:At,h(function(t,e){var n,i=!0;t.subscribe(v(e,function(f){var u=o(f);(i||!r(n,u))&&(i=!1,n=u,e.next(f))}))})}function At(r,o){return r===o}function Gr(r){return h(function(o,t){try{o.subscribe(t)}finally{t.add(r)}})}function Nr(r){var o,t=1/0,e;return r!=null&&(typeof r=="object"?(o=r.count,t=o===void 0?1/0:o,e=r.delay):t=r),t<=0?function(){return V}:h(function(n,i){var f=0,u,a=function(){if(u==null||u.unsubscribe(),u=null,e!=null){var s=typeof e=="number"?q(e):x(e(f)),d=v(i,function(){d.unsubscribe(),c()});s.subscribe(d)}else c()},c=function(){var s=!1;u=n.subscribe(v(i,void 0,function(){++f<t?u?a():s=!0:i.complete()})),s&&a()};c()})}function Yr(r,o){return h(function(t,e){var n=null,i=0,f=!1,u=function(){return f&&!n&&e.complete()};t.subscribe(v(e,function(a){n==null||n.unsubscribe();var c=0,s=i++;x(r(a,s)).subscribe(n=v(e,function(d){return e.next(o?o(a,d,s,c++):d)},function(){n=null,u()}))},function(){f=!0,u()}))})}function gr(r){return h(function(o,t){x(r).subscribe(v(t,function(){return t.complete()},A)),!t.closed&&o.subscribe(t)})}function Er(r,o,t){var e=l(r)||o||t?{next:r,error:o,complete:t}:r;return e?h(function(n,i){var f;(f=e.subscribe)===null||f===void 0||f.call(e);var u=!0;n.subscribe(v(i,function(a){var c;(c=e.next)===null||c===void 0||c.call(e,a),i.next(a)},function(){var a;u=!1,(a=e.complete)===null||a===void 0||a.call(e),i.complete()},function(a){var c;u=!1,(c=e.error)===null||c===void 0||c.call(e,a),i.error(a)},function(){var a,c;u&&((a=e.unsubscribe)===null||a===void 0||a.call(e)),(c=e.finalize)===null||c===void 0||c.call(e)}))}):I}function zr(){for(var r=[],o=0;o<arguments.length;o++)r[o]=arguments[o];var t=Fe(r);return h(function(e,n){for(var i=r.length,f=new Array(i),u=r.map(function(){return!1}),a=!1,c=function(d){x(r[d]).subscribe(v(n,function(p){f[d]=p,!a&&!u[d]&&(u[d]=!0,(a=u.every(I))&&(u=null))},A))},s=0;s<i;s++)c(s);e.subscribe(v(n,function(d){if(a){var p=S([d],w(f));n.next(t?t.apply(void 0,S([],w(p))):p)}}))})}var Ke=document.createElement("div");document.body.appendChild(Ke);var Or=document.querySelector(".md-header__option");if(Or){let r=document.createElement("button");r.className="md-header__button md-icon \u1D34\u2092\u1D34\u2092\u1D34\u2092__button",Or.parentElement&&Or.parentElement.insertBefore(r,Or);let o=new Mr(1);o.pipe(Br()).subscribe(t=>{sessionStorage.setItem("\u1D34\u2092\u1D34\u2092\u1D34\u2092",`${t}`),r.hidden=!t}),o.next(JSON.parse(sessionStorage.getItem("\u1D34\u2092\u1D34\u2092\u1D34\u2092")||"true")),z(r,"click").pipe(zr(o)).subscribe(([,t])=>o.next(!t)),kr(250).pipe(gr(o.pipe(X(t=>!t))),H(75),Nr({delay:()=>o.pipe(X(t=>t))}),T(()=>{let t=document.createElement("div");return t.className="\u1D34\u2092\u1D34\u2092\u1D34\u2092",t.ariaHidden="true",Ke.appendChild(t),Ur(Wr,Rr(t)).pipe(Gr(()=>t.remove()),gr(o.pipe(X(e=>!e))),Yr(e=>z(e,"click").pipe(Er(()=>e.classList.add("\u1D34\u2092\u1D34\u2092\u1D34\u2092--\u1D4D\u2092\u1D57\uA700\u1D34\u2090")),Vr(1e3),Er(()=>e.classList.remove("\u1D34\u2092\u1D34\u2092\u1D34\u2092--\u1D4D\u2092\u1D57\uA700\u1D34\u2090")))))})).subscribe()}})();
+//# sourceMappingURL=bundle.5f09fbc3.min.js.map
+
diff --git a/7.3/assets/javascripts/extra/bundle.5f09fbc3.min.js.map b/7.3/assets/javascripts/extra/bundle.5f09fbc3.min.js.map
new file mode 100644
index 0000000000..24f3674600
--- /dev/null
+++ b/7.3/assets/javascripts/extra/bundle.5f09fbc3.min.js.map
@@ -0,0 +1,8 @@
+{
+  "version": 3,
+  "sources": ["node_modules/rxjs/node_modules/tslib/tslib.js", "node_modules/rxjs/node_modules/tslib/modules/index.js", "node_modules/rxjs/src/internal/util/isFunction.ts", "node_modules/rxjs/src/internal/util/createErrorClass.ts", "node_modules/rxjs/src/internal/util/UnsubscriptionError.ts", "node_modules/rxjs/src/internal/util/arrRemove.ts", "node_modules/rxjs/src/internal/Subscription.ts", "node_modules/rxjs/src/internal/config.ts", "node_modules/rxjs/src/internal/scheduler/timeoutProvider.ts", "node_modules/rxjs/src/internal/util/reportUnhandledError.ts", "node_modules/rxjs/src/internal/util/noop.ts", "node_modules/rxjs/src/internal/NotificationFactories.ts", "node_modules/rxjs/src/internal/util/errorContext.ts", "node_modules/rxjs/src/internal/Subscriber.ts", "node_modules/rxjs/src/internal/symbol/observable.ts", "node_modules/rxjs/src/internal/util/identity.ts", "node_modules/rxjs/src/internal/util/pipe.ts", "node_modules/rxjs/src/internal/Observable.ts", "node_modules/rxjs/src/internal/util/lift.ts", "node_modules/rxjs/src/internal/operators/OperatorSubscriber.ts", "node_modules/rxjs/src/internal/util/ObjectUnsubscribedError.ts", "node_modules/rxjs/src/internal/Subject.ts", "node_modules/rxjs/src/internal/scheduler/dateTimestampProvider.ts", "node_modules/rxjs/src/internal/ReplaySubject.ts", "node_modules/rxjs/src/internal/scheduler/Action.ts", "node_modules/rxjs/src/internal/scheduler/intervalProvider.ts", "node_modules/rxjs/src/internal/scheduler/AsyncAction.ts", "node_modules/rxjs/src/internal/Scheduler.ts", "node_modules/rxjs/src/internal/scheduler/AsyncScheduler.ts", "node_modules/rxjs/src/internal/scheduler/async.ts", "node_modules/rxjs/src/internal/observable/empty.ts", "node_modules/rxjs/src/internal/util/isScheduler.ts", "node_modules/rxjs/src/internal/util/args.ts", "node_modules/rxjs/src/internal/util/isArrayLike.ts", "node_modules/rxjs/src/internal/util/isPromise.ts", "node_modules/rxjs/src/internal/util/isInteropObservable.ts", "node_modules/rxjs/src/internal/util/isAsyncIterable.ts", "node_modules/rxjs/src/internal/util/throwUnobservableError.ts", "node_modules/rxjs/src/internal/symbol/iterator.ts", "node_modules/rxjs/src/internal/util/isIterable.ts", "node_modules/rxjs/src/internal/util/isReadableStreamLike.ts", "node_modules/rxjs/src/internal/observable/innerFrom.ts", "node_modules/rxjs/src/internal/util/executeSchedule.ts", "node_modules/rxjs/src/internal/operators/observeOn.ts", "node_modules/rxjs/src/internal/operators/subscribeOn.ts", "node_modules/rxjs/src/internal/scheduled/scheduleObservable.ts", "node_modules/rxjs/src/internal/scheduled/schedulePromise.ts", "node_modules/rxjs/src/internal/scheduled/scheduleArray.ts", "node_modules/rxjs/src/internal/scheduled/scheduleIterable.ts", "node_modules/rxjs/src/internal/scheduled/scheduleAsyncIterable.ts", "node_modules/rxjs/src/internal/scheduled/scheduleReadableStreamLike.ts", "node_modules/rxjs/src/internal/scheduled/scheduled.ts", "node_modules/rxjs/src/internal/observable/from.ts", "node_modules/rxjs/src/internal/observable/of.ts", "node_modules/rxjs/src/internal/util/isDate.ts", "node_modules/rxjs/src/internal/operators/map.ts", "node_modules/rxjs/src/internal/util/mapOneOrManyArgs.ts", "node_modules/rxjs/src/internal/operators/mergeInternals.ts", "node_modules/rxjs/src/internal/operators/mergeMap.ts", "node_modules/rxjs/src/internal/operators/mergeAll.ts", "node_modules/rxjs/src/internal/operators/concatAll.ts", "node_modules/rxjs/src/internal/observable/concat.ts", "node_modules/rxjs/src/internal/observable/fromEvent.ts", "node_modules/rxjs/src/internal/observable/timer.ts", "node_modules/rxjs/src/internal/observable/interval.ts", "node_modules/rxjs/src/internal/observable/merge.ts", "node_modules/rxjs/src/internal/observable/never.ts", "node_modules/rxjs/src/internal/operators/filter.ts", "node_modules/rxjs/src/internal/operators/take.ts", "node_modules/rxjs/src/internal/operators/ignoreElements.ts", "node_modules/rxjs/src/internal/operators/mapTo.ts", "node_modules/rxjs/src/internal/operators/delayWhen.ts", "node_modules/rxjs/src/internal/operators/delay.ts", "node_modules/rxjs/src/internal/operators/distinctUntilChanged.ts", "node_modules/rxjs/src/internal/operators/finalize.ts", "node_modules/rxjs/src/internal/operators/repeat.ts", "node_modules/rxjs/src/internal/operators/switchMap.ts", "node_modules/rxjs/src/internal/operators/takeUntil.ts", "node_modules/rxjs/src/internal/operators/tap.ts", "node_modules/rxjs/src/internal/operators/withLatestFrom.ts", "src/assets/javascripts/extra/bundle.ts"],
+  "sourceRoot": "../../../..",
+  "sourcesContent": ["/*! *****************************************************************************\r\nCopyright (c) Microsoft Corporation.\r\n\r\nPermission to use, copy, modify, and/or distribute this software for any\r\npurpose with or without fee is hereby granted.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\r\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\r\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\r\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\r\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\r\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\r\nPERFORMANCE OF THIS SOFTWARE.\r\n***************************************************************************** */\r\n/* global global, define, System, Reflect, Promise */\r\nvar __extends;\r\nvar __assign;\r\nvar __rest;\r\nvar __decorate;\r\nvar __param;\r\nvar __metadata;\r\nvar __awaiter;\r\nvar __generator;\r\nvar __exportStar;\r\nvar __values;\r\nvar __read;\r\nvar __spread;\r\nvar __spreadArrays;\r\nvar __spreadArray;\r\nvar __await;\r\nvar __asyncGenerator;\r\nvar __asyncDelegator;\r\nvar __asyncValues;\r\nvar __makeTemplateObject;\r\nvar __importStar;\r\nvar __importDefault;\r\nvar __classPrivateFieldGet;\r\nvar __classPrivateFieldSet;\r\nvar __createBinding;\r\n(function (factory) {\r\n    var root = typeof global === \"object\" ? global : typeof self === \"object\" ? self : typeof this === \"object\" ? this : {};\r\n    if (typeof define === \"function\" && define.amd) {\r\n        define(\"tslib\", [\"exports\"], function (exports) { factory(createExporter(root, createExporter(exports))); });\r\n    }\r\n    else if (typeof module === \"object\" && typeof module.exports === \"object\") {\r\n        factory(createExporter(root, createExporter(module.exports)));\r\n    }\r\n    else {\r\n        factory(createExporter(root));\r\n    }\r\n    function createExporter(exports, previous) {\r\n        if (exports !== root) {\r\n            if (typeof Object.create === \"function\") {\r\n                Object.defineProperty(exports, \"__esModule\", { value: true });\r\n            }\r\n            else {\r\n                exports.__esModule = true;\r\n            }\r\n        }\r\n        return function (id, v) { return exports[id] = previous ? previous(id, v) : v; };\r\n    }\r\n})\r\n(function (exporter) {\r\n    var extendStatics = Object.setPrototypeOf ||\r\n        ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\r\n        function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\r\n\r\n    __extends = function (d, b) {\r\n        if (typeof b !== \"function\" && b !== null)\r\n            throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\r\n        extendStatics(d, b);\r\n        function __() { this.constructor = d; }\r\n        d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\r\n    };\r\n\r\n    __assign = Object.assign || function (t) {\r\n        for (var s, i = 1, n = arguments.length; i < n; i++) {\r\n            s = arguments[i];\r\n            for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\r\n        }\r\n        return t;\r\n    };\r\n\r\n    __rest = function (s, e) {\r\n        var t = {};\r\n        for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\r\n            t[p] = s[p];\r\n        if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\r\n            for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\r\n                if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\r\n                    t[p[i]] = s[p[i]];\r\n            }\r\n        return t;\r\n    };\r\n\r\n    __decorate = function (decorators, target, key, desc) {\r\n        var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\r\n        if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\r\n        else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\r\n        return c > 3 && r && Object.defineProperty(target, key, r), r;\r\n    };\r\n\r\n    __param = function (paramIndex, decorator) {\r\n        return function (target, key) { decorator(target, key, paramIndex); }\r\n    };\r\n\r\n    __metadata = function (metadataKey, metadataValue) {\r\n        if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\r\n    };\r\n\r\n    __awaiter = function (thisArg, _arguments, P, generator) {\r\n        function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\r\n        return new (P || (P = Promise))(function (resolve, reject) {\r\n            function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\r\n            function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\r\n            function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\r\n            step((generator = generator.apply(thisArg, _arguments || [])).next());\r\n        });\r\n    };\r\n\r\n    __generator = function (thisArg, body) {\r\n        var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;\r\n        return g = { next: verb(0), \"throw\": verb(1), \"return\": verb(2) }, typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\r\n        function verb(n) { return function (v) { return step([n, v]); }; }\r\n        function step(op) {\r\n            if (f) throw new TypeError(\"Generator is already executing.\");\r\n            while (_) try {\r\n                if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\r\n                if (y = 0, t) op = [op[0] & 2, t.value];\r\n                switch (op[0]) {\r\n                    case 0: case 1: t = op; break;\r\n                    case 4: _.label++; return { value: op[1], done: false };\r\n                    case 5: _.label++; y = op[1]; op = [0]; continue;\r\n                    case 7: op = _.ops.pop(); _.trys.pop(); continue;\r\n                    default:\r\n                        if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\r\n                        if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\r\n                        if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\r\n                        if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\r\n                        if (t[2]) _.ops.pop();\r\n                        _.trys.pop(); continue;\r\n                }\r\n                op = body.call(thisArg, _);\r\n            } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\r\n            if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\r\n        }\r\n    };\r\n\r\n    __exportStar = function(m, o) {\r\n        for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\r\n    };\r\n\r\n    __createBinding = Object.create ? (function(o, m, k, k2) {\r\n        if (k2 === undefined) k2 = k;\r\n        Object.defineProperty(o, k2, { enumerable: true, get: function() { return m[k]; } });\r\n    }) : (function(o, m, k, k2) {\r\n        if (k2 === undefined) k2 = k;\r\n        o[k2] = m[k];\r\n    });\r\n\r\n    __values = function (o) {\r\n        var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\r\n        if (m) return m.call(o);\r\n        if (o && typeof o.length === \"number\") return {\r\n            next: function () {\r\n                if (o && i >= o.length) o = void 0;\r\n                return { value: o && o[i++], done: !o };\r\n            }\r\n        };\r\n        throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\r\n    };\r\n\r\n    __read = function (o, n) {\r\n        var m = typeof Symbol === \"function\" && o[Symbol.iterator];\r\n        if (!m) return o;\r\n        var i = m.call(o), r, ar = [], e;\r\n        try {\r\n            while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\r\n        }\r\n        catch (error) { e = { error: error }; }\r\n        finally {\r\n            try {\r\n                if (r && !r.done && (m = i[\"return\"])) m.call(i);\r\n            }\r\n            finally { if (e) throw e.error; }\r\n        }\r\n        return ar;\r\n    };\r\n\r\n    /** @deprecated */\r\n    __spread = function () {\r\n        for (var ar = [], i = 0; i < arguments.length; i++)\r\n            ar = ar.concat(__read(arguments[i]));\r\n        return ar;\r\n    };\r\n\r\n    /** @deprecated */\r\n    __spreadArrays = function () {\r\n        for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\r\n        for (var r = Array(s), k = 0, i = 0; i < il; i++)\r\n            for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\r\n                r[k] = a[j];\r\n        return r;\r\n    };\r\n\r\n    __spreadArray = function (to, from, pack) {\r\n        if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\r\n            if (ar || !(i in from)) {\r\n                if (!ar) ar = Array.prototype.slice.call(from, 0, i);\r\n                ar[i] = from[i];\r\n            }\r\n        }\r\n        return to.concat(ar || Array.prototype.slice.call(from));\r\n    };\r\n\r\n    __await = function (v) {\r\n        return this instanceof __await ? (this.v = v, this) : new __await(v);\r\n    };\r\n\r\n    __asyncGenerator = function (thisArg, _arguments, generator) {\r\n        if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n        var g = generator.apply(thisArg, _arguments || []), i, q = [];\r\n        return i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i;\r\n        function verb(n) { if (g[n]) i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; }\r\n        function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\r\n        function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r);  }\r\n        function fulfill(value) { resume(\"next\", value); }\r\n        function reject(value) { resume(\"throw\", value); }\r\n        function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\r\n    };\r\n\r\n    __asyncDelegator = function (o) {\r\n        var i, p;\r\n        return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\r\n        function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: n === \"return\" } : f ? f(v) : v; } : f; }\r\n    };\r\n\r\n    __asyncValues = function (o) {\r\n        if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n        var m = o[Symbol.asyncIterator], i;\r\n        return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\r\n        function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\r\n        function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\r\n    };\r\n\r\n    __makeTemplateObject = function (cooked, raw) {\r\n        if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\r\n        return cooked;\r\n    };\r\n\r\n    var __setModuleDefault = Object.create ? (function(o, v) {\r\n        Object.defineProperty(o, \"default\", { enumerable: true, value: v });\r\n    }) : function(o, v) {\r\n        o[\"default\"] = v;\r\n    };\r\n\r\n    __importStar = function (mod) {\r\n        if (mod && mod.__esModule) return mod;\r\n        var result = {};\r\n        if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\r\n        __setModuleDefault(result, mod);\r\n        return result;\r\n    };\r\n\r\n    __importDefault = function (mod) {\r\n        return (mod && mod.__esModule) ? mod : { \"default\": mod };\r\n    };\r\n\r\n    __classPrivateFieldGet = function (receiver, state, kind, f) {\r\n        if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\r\n        if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\r\n        return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\r\n    };\r\n\r\n    __classPrivateFieldSet = function (receiver, state, value, kind, f) {\r\n        if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\r\n        if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\r\n        if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\r\n        return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\r\n    };\r\n\r\n    exporter(\"__extends\", __extends);\r\n    exporter(\"__assign\", __assign);\r\n    exporter(\"__rest\", __rest);\r\n    exporter(\"__decorate\", __decorate);\r\n    exporter(\"__param\", __param);\r\n    exporter(\"__metadata\", __metadata);\r\n    exporter(\"__awaiter\", __awaiter);\r\n    exporter(\"__generator\", __generator);\r\n    exporter(\"__exportStar\", __exportStar);\r\n    exporter(\"__createBinding\", __createBinding);\r\n    exporter(\"__values\", __values);\r\n    exporter(\"__read\", __read);\r\n    exporter(\"__spread\", __spread);\r\n    exporter(\"__spreadArrays\", __spreadArrays);\r\n    exporter(\"__spreadArray\", __spreadArray);\r\n    exporter(\"__await\", __await);\r\n    exporter(\"__asyncGenerator\", __asyncGenerator);\r\n    exporter(\"__asyncDelegator\", __asyncDelegator);\r\n    exporter(\"__asyncValues\", __asyncValues);\r\n    exporter(\"__makeTemplateObject\", __makeTemplateObject);\r\n    exporter(\"__importStar\", __importStar);\r\n    exporter(\"__importDefault\", __importDefault);\r\n    exporter(\"__classPrivateFieldGet\", __classPrivateFieldGet);\r\n    exporter(\"__classPrivateFieldSet\", __classPrivateFieldSet);\r\n});\r\n", "import tslib from '../tslib.js';\r\nconst {\r\n    __extends,\r\n    __assign,\r\n    __rest,\r\n    __decorate,\r\n    __param,\r\n    __metadata,\r\n    __awaiter,\r\n    __generator,\r\n    __exportStar,\r\n    __createBinding,\r\n    __values,\r\n    __read,\r\n    __spread,\r\n    __spreadArrays,\r\n    __spreadArray,\r\n    __await,\r\n    __asyncGenerator,\r\n    __asyncDelegator,\r\n    __asyncValues,\r\n    __makeTemplateObject,\r\n    __importStar,\r\n    __importDefault,\r\n    __classPrivateFieldGet,\r\n    __classPrivateFieldSet,\r\n} = tslib;\r\nexport {\r\n    __extends,\r\n    __assign,\r\n    __rest,\r\n    __decorate,\r\n    __param,\r\n    __metadata,\r\n    __awaiter,\r\n    __generator,\r\n    __exportStar,\r\n    __createBinding,\r\n    __values,\r\n    __read,\r\n    __spread,\r\n    __spreadArrays,\r\n    __spreadArray,\r\n    __await,\r\n    __asyncGenerator,\r\n    __asyncDelegator,\r\n    __asyncValues,\r\n    __makeTemplateObject,\r\n    __importStar,\r\n    __importDefault,\r\n    __classPrivateFieldGet,\r\n    __classPrivateFieldSet,\r\n};\r\n", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  NEVER,\n  ReplaySubject,\n  delay,\n  distinctUntilChanged,\n  filter,\n  finalize,\n  fromEvent,\n  interval,\n  merge,\n  mergeMap,\n  of,\n  repeat,\n  switchMap,\n  take,\n  takeUntil,\n  tap,\n  withLatestFrom\n} from \"rxjs\"\n\n/* ----------------------------------------------------------------------------\n * Script\n * ------------------------------------------------------------------------- */\n\n/* Append container for instances */\nconst container = document.createElement(\"div\")\ndocument.body.appendChild(container)\n\n/* Append button next to palette toggle */\nconst header = document.querySelector(\".md-header__option\")\nif (header) {\n  const button = document.createElement(\"button\")\n  button.className = \"md-header__button md-icon \u1D34\u2092\u1D34\u2092\u1D34\u2092__button\"\n  if (header.parentElement)\n    header.parentElement.insertBefore(button, header)\n\n  /* Toggle animation */\n  const on$ = new ReplaySubject<boolean>(1)\n  on$\n    .pipe(\n      distinctUntilChanged()\n    )\n      .subscribe(on => {\n        sessionStorage.setItem(\"\u1D34\u2092\u1D34\u2092\u1D34\u2092\", `${on}`)\n        button.hidden = !on\n      })\n\n  /* Load state from session storage */\n  on$.next(JSON.parse(sessionStorage.getItem(\"\u1D34\u2092\u1D34\u2092\u1D34\u2092\") || \"true\"))\n  fromEvent(button, \"click\")\n    .pipe(\n      withLatestFrom(on$)\n    )\n      .subscribe(([, on]) => on$.next(!on))\n\n  /* Generate instances */\n  interval(250)\n    .pipe(\n      takeUntil(on$.pipe(filter(on => !on))),\n      take(75),\n      repeat({ delay: () => on$.pipe(filter(on => on)) }),\n      mergeMap(() => {\n        const instance = document.createElement(\"div\")\n        instance.className = \"\u1D34\u2092\u1D34\u2092\u1D34\u2092\"\n        instance.ariaHidden = \"true\"\n        container.appendChild(instance)\n        return merge(NEVER, of(instance))\n          .pipe(\n            finalize(() => instance.remove()),\n            takeUntil(on$.pipe(filter(on => !on))),\n            switchMap(el => fromEvent(el, \"click\")\n              .pipe(\n                tap(() => el.classList.add(\"\u1D34\u2092\u1D34\u2092\u1D34\u2092--\u1D4D\u2092\u1D57\uA700\u1D34\u2090\")),\n                delay(1000),\n                tap(() => el.classList.remove(\"\u1D34\u2092\u1D34\u2092\u1D34\u2092--\u1D4D\u2092\u1D57\uA700\u1D34\u2090\"))\n              )\n            )\n          )\n      })\n    )\n      .subscribe()\n}\n"],
+  "mappings": "6iBAAA,IAAAA,GAAAC,GAAA,CAAAC,GAAAC,KAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gFAeA,IAAIC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,EACAC,GACAC,GACAC,GACAC,GACAC,EACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,GACAC,IACH,SAAUC,EAAS,CAChB,IAAIC,EAAO,OAAO,QAAW,SAAW,OAAS,OAAO,MAAS,SAAW,KAAO,OAAO,MAAS,SAAW,KAAO,CAAC,EAClH,OAAO,QAAW,YAAc,OAAO,IACvC,OAAO,QAAS,CAAC,SAAS,EAAG,SAAU3B,EAAS,CAAE0B,EAAQE,EAAeD,EAAMC,EAAe5B,CAAO,CAAC,CAAC,CAAG,CAAC,EAEtG,OAAOC,IAAW,UAAY,OAAOA,GAAO,SAAY,SAC7DyB,EAAQE,EAAeD,EAAMC,EAAe3B,GAAO,OAAO,CAAC,CAAC,EAG5DyB,EAAQE,EAAeD,CAAI,CAAC,EAEhC,SAASC,EAAe5B,EAAS6B,EAAU,CACvC,OAAI7B,IAAY2B,IACR,OAAO,OAAO,QAAW,WACzB,OAAO,eAAe3B,EAAS,aAAc,CAAE,MAAO,EAAK,CAAC,EAG5DA,EAAQ,WAAa,IAGtB,SAAU8B,EAAIC,EAAG,CAAE,OAAO/B,EAAQ8B,GAAMD,EAAWA,EAASC,EAAIC,CAAC,EAAIA,CAAG,CACnF,CACJ,GACC,SAAUC,EAAU,CACjB,IAAIC,EAAgB,OAAO,gBACtB,CAAE,UAAW,CAAC,CAAE,YAAa,OAAS,SAAUC,EAAGC,EAAG,CAAED,EAAE,UAAYC,CAAG,GAC1E,SAAUD,EAAGC,EAAG,CAAE,QAASC,KAAKD,EAAO,OAAO,UAAU,eAAe,KAAKA,EAAGC,CAAC,IAAGF,EAAEE,GAAKD,EAAEC,GAAI,EAEpGlC,GAAY,SAAUgC,EAAGC,EAAG,CACxB,GAAI,OAAOA,GAAM,YAAcA,IAAM,KACjC,MAAM,IAAI,UAAU,uBAAyB,OAAOA,CAAC,EAAI,+BAA+B,EAC5FF,EAAcC,EAAGC,CAAC,EAClB,SAASE,GAAK,CAAE,KAAK,YAAcH,CAAG,CACtCA,EAAE,UAAYC,IAAM,KAAO,OAAO,OAAOA,CAAC,GAAKE,EAAG,UAAYF,EAAE,UAAW,IAAIE,EACnF,EAEAlC,GAAW,OAAO,QAAU,SAAUmC,EAAG,CACrC,QAASC,EAAG,EAAI,EAAGC,EAAI,UAAU,OAAQ,EAAIA,EAAG,IAAK,CACjDD,EAAI,UAAU,GACd,QAASH,KAAKG,EAAO,OAAO,UAAU,eAAe,KAAKA,EAAGH,CAAC,IAAGE,EAAEF,GAAKG,EAAEH,GAC9E,CACA,OAAOE,CACX,EAEAlC,GAAS,SAAUmC,EAAGE,EAAG,CACrB,IAAIH,EAAI,CAAC,EACT,QAASF,KAAKG,EAAO,OAAO,UAAU,eAAe,KAAKA,EAAGH,CAAC,GAAKK,EAAE,QAAQL,CAAC,EAAI,IAC9EE,EAAEF,GAAKG,EAAEH,IACb,GAAIG,GAAK,MAAQ,OAAO,OAAO,uBAA0B,WACrD,QAASG,EAAI,EAAGN,EAAI,OAAO,sBAAsBG,CAAC,EAAGG,EAAIN,EAAE,OAAQM,IAC3DD,EAAE,QAAQL,EAAEM,EAAE,EAAI,GAAK,OAAO,UAAU,qBAAqB,KAAKH,EAAGH,EAAEM,EAAE,IACzEJ,EAAEF,EAAEM,IAAMH,EAAEH,EAAEM,KAE1B,OAAOJ,CACX,EAEAjC,GAAa,SAAUsC,EAAYC,EAAQC,EAAKC,EAAM,CAClD,IAAIC,EAAI,UAAU,OAAQC,EAAID,EAAI,EAAIH,EAASE,IAAS,KAAOA,EAAO,OAAO,yBAAyBF,EAAQC,CAAG,EAAIC,EAAMZ,EAC3H,GAAI,OAAO,SAAY,UAAY,OAAO,QAAQ,UAAa,WAAYc,EAAI,QAAQ,SAASL,EAAYC,EAAQC,EAAKC,CAAI,MACxH,SAASJ,EAAIC,EAAW,OAAS,EAAGD,GAAK,EAAGA,KAASR,EAAIS,EAAWD,MAAIM,GAAKD,EAAI,EAAIb,EAAEc,CAAC,EAAID,EAAI,EAAIb,EAAEU,EAAQC,EAAKG,CAAC,EAAId,EAAEU,EAAQC,CAAG,IAAMG,GAChJ,OAAOD,EAAI,GAAKC,GAAK,OAAO,eAAeJ,EAAQC,EAAKG,CAAC,EAAGA,CAChE,EAEA1C,GAAU,SAAU2C,EAAYC,EAAW,CACvC,OAAO,SAAUN,EAAQC,EAAK,CAAEK,EAAUN,EAAQC,EAAKI,CAAU,CAAG,CACxE,EAEA1C,GAAa,SAAU4C,EAAaC,EAAe,CAC/C,GAAI,OAAO,SAAY,UAAY,OAAO,QAAQ,UAAa,WAAY,OAAO,QAAQ,SAASD,EAAaC,CAAa,CACjI,EAEA5C,GAAY,SAAU6C,EAASC,EAAYC,EAAGC,EAAW,CACrD,SAASC,EAAMC,EAAO,CAAE,OAAOA,aAAiBH,EAAIG,EAAQ,IAAIH,EAAE,SAAUI,EAAS,CAAEA,EAAQD,CAAK,CAAG,CAAC,CAAG,CAC3G,OAAO,IAAKH,IAAMA,EAAI,UAAU,SAAUI,EAASC,EAAQ,CACvD,SAASC,EAAUH,EAAO,CAAE,GAAI,CAAEI,EAAKN,EAAU,KAAKE,CAAK,CAAC,CAAG,OAASjB,EAAP,CAAYmB,EAAOnB,CAAC,CAAG,CAAE,CAC1F,SAASsB,EAASL,EAAO,CAAE,GAAI,CAAEI,EAAKN,EAAU,MAASE,CAAK,CAAC,CAAG,OAASjB,EAAP,CAAYmB,EAAOnB,CAAC,CAAG,CAAE,CAC7F,SAASqB,EAAKE,EAAQ,CAAEA,EAAO,KAAOL,EAAQK,EAAO,KAAK,EAAIP,EAAMO,EAAO,KAAK,EAAE,KAAKH,EAAWE,CAAQ,CAAG,CAC7GD,GAAMN,EAAYA,EAAU,MAAMH,EAASC,GAAc,CAAC,CAAC,GAAG,KAAK,CAAC,CACxE,CAAC,CACL,EAEA7C,GAAc,SAAU4C,EAASY,EAAM,CACnC,IAAIC,EAAI,CAAE,MAAO,EAAG,KAAM,UAAW,CAAE,GAAI5B,EAAE,GAAK,EAAG,MAAMA,EAAE,GAAI,OAAOA,EAAE,EAAI,EAAG,KAAM,CAAC,EAAG,IAAK,CAAC,CAAE,EAAG,EAAG6B,EAAG7B,EAAG8B,EAC/G,OAAOA,EAAI,CAAE,KAAMC,EAAK,CAAC,EAAG,MAASA,EAAK,CAAC,EAAG,OAAUA,EAAK,CAAC,CAAE,EAAG,OAAO,QAAW,aAAeD,EAAE,OAAO,UAAY,UAAW,CAAE,OAAO,IAAM,GAAIA,EACvJ,SAASC,EAAK7B,EAAG,CAAE,OAAO,SAAUT,EAAG,CAAE,OAAO+B,EAAK,CAACtB,EAAGT,CAAC,CAAC,CAAG,CAAG,CACjE,SAAS+B,EAAKQ,EAAI,CACd,GAAI,EAAG,MAAM,IAAI,UAAU,iCAAiC,EAC5D,KAAOJ,GAAG,GAAI,CACV,GAAI,EAAI,EAAGC,IAAM7B,EAAIgC,EAAG,GAAK,EAAIH,EAAE,OAAYG,EAAG,GAAKH,EAAE,SAAc7B,EAAI6B,EAAE,SAAc7B,EAAE,KAAK6B,CAAC,EAAG,GAAKA,EAAE,OAAS,EAAE7B,EAAIA,EAAE,KAAK6B,EAAGG,EAAG,EAAE,GAAG,KAAM,OAAOhC,EAE3J,OADI6B,EAAI,EAAG7B,IAAGgC,EAAK,CAACA,EAAG,GAAK,EAAGhC,EAAE,KAAK,GAC9BgC,EAAG,GAAI,CACX,IAAK,GAAG,IAAK,GAAGhC,EAAIgC,EAAI,MACxB,IAAK,GAAG,OAAAJ,EAAE,QAAgB,CAAE,MAAOI,EAAG,GAAI,KAAM,EAAM,EACtD,IAAK,GAAGJ,EAAE,QAASC,EAAIG,EAAG,GAAIA,EAAK,CAAC,CAAC,EAAG,SACxC,IAAK,GAAGA,EAAKJ,EAAE,IAAI,IAAI,EAAGA,EAAE,KAAK,IAAI,EAAG,SACxC,QACI,GAAM5B,EAAI4B,EAAE,KAAM,EAAA5B,EAAIA,EAAE,OAAS,GAAKA,EAAEA,EAAE,OAAS,MAAQgC,EAAG,KAAO,GAAKA,EAAG,KAAO,GAAI,CAAEJ,EAAI,EAAG,QAAU,CAC3G,GAAII,EAAG,KAAO,IAAM,CAAChC,GAAMgC,EAAG,GAAKhC,EAAE,IAAMgC,EAAG,GAAKhC,EAAE,IAAM,CAAE4B,EAAE,MAAQI,EAAG,GAAI,KAAO,CACrF,GAAIA,EAAG,KAAO,GAAKJ,EAAE,MAAQ5B,EAAE,GAAI,CAAE4B,EAAE,MAAQ5B,EAAE,GAAIA,EAAIgC,EAAI,KAAO,CACpE,GAAIhC,GAAK4B,EAAE,MAAQ5B,EAAE,GAAI,CAAE4B,EAAE,MAAQ5B,EAAE,GAAI4B,EAAE,IAAI,KAAKI,CAAE,EAAG,KAAO,CAC9DhC,EAAE,IAAI4B,EAAE,IAAI,IAAI,EACpBA,EAAE,KAAK,IAAI,EAAG,QACtB,CACAI,EAAKL,EAAK,KAAKZ,EAASa,CAAC,CAC7B,OAASzB,EAAP,CAAY6B,EAAK,CAAC,EAAG7B,CAAC,EAAG0B,EAAI,CAAG,QAAE,CAAU,EAAI7B,EAAI,CAAG,CACzD,GAAIgC,EAAG,GAAK,EAAG,MAAMA,EAAG,GAAI,MAAO,CAAE,MAAOA,EAAG,GAAKA,EAAG,GAAK,OAAQ,KAAM,EAAK,CACnF,CACJ,EAEA5D,GAAe,SAAS6D,EAAGC,EAAG,CAC1B,QAASpC,KAAKmC,EAAOnC,IAAM,WAAa,CAAC,OAAO,UAAU,eAAe,KAAKoC,EAAGpC,CAAC,GAAGX,GAAgB+C,EAAGD,EAAGnC,CAAC,CAChH,EAEAX,GAAkB,OAAO,OAAU,SAAS+C,EAAGD,EAAGE,EAAGC,EAAI,CACjDA,IAAO,SAAWA,EAAKD,GAC3B,OAAO,eAAeD,EAAGE,EAAI,CAAE,WAAY,GAAM,IAAK,UAAW,CAAE,OAAOH,EAAEE,EAAI,CAAE,CAAC,CACvF,EAAM,SAASD,EAAGD,EAAGE,EAAGC,EAAI,CACpBA,IAAO,SAAWA,EAAKD,GAC3BD,EAAEE,GAAMH,EAAEE,EACd,EAEA9D,EAAW,SAAU6D,EAAG,CACpB,IAAIjC,EAAI,OAAO,QAAW,YAAc,OAAO,SAAUgC,EAAIhC,GAAKiC,EAAEjC,GAAIG,EAAI,EAC5E,GAAI6B,EAAG,OAAOA,EAAE,KAAKC,CAAC,EACtB,GAAIA,GAAK,OAAOA,EAAE,QAAW,SAAU,MAAO,CAC1C,KAAM,UAAY,CACd,OAAIA,GAAK9B,GAAK8B,EAAE,SAAQA,EAAI,QACrB,CAAE,MAAOA,GAAKA,EAAE9B,KAAM,KAAM,CAAC8B,CAAE,CAC1C,CACJ,EACA,MAAM,IAAI,UAAUjC,EAAI,0BAA4B,iCAAiC,CACzF,EAEA3B,GAAS,SAAU4D,EAAG,EAAG,CACrB,IAAID,EAAI,OAAO,QAAW,YAAcC,EAAE,OAAO,UACjD,GAAI,CAACD,EAAG,OAAOC,EACf,IAAI9B,EAAI6B,EAAE,KAAKC,CAAC,EAAGxB,EAAG2B,EAAK,CAAC,EAAGlC,EAC/B,GAAI,CACA,MAAQ,IAAM,QAAU,KAAM,IAAM,EAAEO,EAAIN,EAAE,KAAK,GAAG,MAAMiC,EAAG,KAAK3B,EAAE,KAAK,CAC7E,OACO4B,EAAP,CAAgBnC,EAAI,CAAE,MAAOmC,CAAM,CAAG,QACtC,CACI,GAAI,CACI5B,GAAK,CAACA,EAAE,OAASuB,EAAI7B,EAAE,SAAY6B,EAAE,KAAK7B,CAAC,CACnD,QACA,CAAU,GAAID,EAAG,MAAMA,EAAE,KAAO,CACpC,CACA,OAAOkC,CACX,EAGA9D,GAAW,UAAY,CACnB,QAAS8D,EAAK,CAAC,EAAGjC,EAAI,EAAGA,EAAI,UAAU,OAAQA,IAC3CiC,EAAKA,EAAG,OAAO/D,GAAO,UAAU8B,EAAE,CAAC,EACvC,OAAOiC,CACX,EAGA7D,GAAiB,UAAY,CACzB,QAASyB,EAAI,EAAGG,EAAI,EAAGmC,EAAK,UAAU,OAAQnC,EAAImC,EAAInC,IAAKH,GAAK,UAAUG,GAAG,OAC7E,QAASM,EAAI,MAAMT,CAAC,EAAGkC,EAAI,EAAG/B,EAAI,EAAGA,EAAImC,EAAInC,IACzC,QAAS,EAAI,UAAUA,GAAIoC,EAAI,EAAGC,EAAK,EAAE,OAAQD,EAAIC,EAAID,IAAKL,IAC1DzB,EAAEyB,GAAK,EAAEK,GACjB,OAAO9B,CACX,EAEAjC,GAAgB,SAAUiE,EAAIC,EAAMC,EAAM,CACtC,GAAIA,GAAQ,UAAU,SAAW,EAAG,QAASxC,EAAI,EAAGyC,EAAIF,EAAK,OAAQN,EAAIjC,EAAIyC,EAAGzC,KACxEiC,GAAM,EAAEjC,KAAKuC,MACRN,IAAIA,EAAK,MAAM,UAAU,MAAM,KAAKM,EAAM,EAAGvC,CAAC,GACnDiC,EAAGjC,GAAKuC,EAAKvC,IAGrB,OAAOsC,EAAG,OAAOL,GAAM,MAAM,UAAU,MAAM,KAAKM,CAAI,CAAC,CAC3D,EAEAjE,EAAU,SAAUe,EAAG,CACnB,OAAO,gBAAgBf,GAAW,KAAK,EAAIe,EAAG,MAAQ,IAAIf,EAAQe,CAAC,CACvE,EAEAd,GAAmB,SAAUoC,EAASC,EAAYE,EAAW,CACzD,GAAI,CAAC,OAAO,cAAe,MAAM,IAAI,UAAU,sCAAsC,EACrF,IAAIY,EAAIZ,EAAU,MAAMH,EAASC,GAAc,CAAC,CAAC,EAAGZ,EAAG0C,EAAI,CAAC,EAC5D,OAAO1C,EAAI,CAAC,EAAG2B,EAAK,MAAM,EAAGA,EAAK,OAAO,EAAGA,EAAK,QAAQ,EAAG3B,EAAE,OAAO,eAAiB,UAAY,CAAE,OAAO,IAAM,EAAGA,EACpH,SAAS2B,EAAK7B,EAAG,CAAM4B,EAAE5B,KAAIE,EAAEF,GAAK,SAAUT,EAAG,CAAE,OAAO,IAAI,QAAQ,SAAUsD,EAAGlD,EAAG,CAAEiD,EAAE,KAAK,CAAC5C,EAAGT,EAAGsD,EAAGlD,CAAC,CAAC,EAAI,GAAKmD,EAAO9C,EAAGT,CAAC,CAAG,CAAC,CAAG,EAAG,CACzI,SAASuD,EAAO9C,EAAGT,EAAG,CAAE,GAAI,CAAE+B,EAAKM,EAAE5B,GAAGT,CAAC,CAAC,CAAG,OAASU,EAAP,CAAY8C,EAAOH,EAAE,GAAG,GAAI3C,CAAC,CAAG,CAAE,CACjF,SAASqB,EAAKd,EAAG,CAAEA,EAAE,iBAAiBhC,EAAU,QAAQ,QAAQgC,EAAE,MAAM,CAAC,EAAE,KAAKwC,EAAS5B,CAAM,EAAI2B,EAAOH,EAAE,GAAG,GAAIpC,CAAC,CAAI,CACxH,SAASwC,EAAQ9B,EAAO,CAAE4B,EAAO,OAAQ5B,CAAK,CAAG,CACjD,SAASE,EAAOF,EAAO,CAAE4B,EAAO,QAAS5B,CAAK,CAAG,CACjD,SAAS6B,EAAOE,EAAG1D,EAAG,CAAM0D,EAAE1D,CAAC,EAAGqD,EAAE,MAAM,EAAGA,EAAE,QAAQE,EAAOF,EAAE,GAAG,GAAIA,EAAE,GAAG,EAAE,CAAG,CACrF,EAEAlE,GAAmB,SAAUsD,EAAG,CAC5B,IAAI9B,EAAGN,EACP,OAAOM,EAAI,CAAC,EAAG2B,EAAK,MAAM,EAAGA,EAAK,QAAS,SAAU5B,EAAG,CAAE,MAAMA,CAAG,CAAC,EAAG4B,EAAK,QAAQ,EAAG3B,EAAE,OAAO,UAAY,UAAY,CAAE,OAAO,IAAM,EAAGA,EAC1I,SAAS2B,EAAK7B,EAAGiD,EAAG,CAAE/C,EAAEF,GAAKgC,EAAEhC,GAAK,SAAUT,EAAG,CAAE,OAAQK,EAAI,CAACA,GAAK,CAAE,MAAOpB,EAAQwD,EAAEhC,GAAGT,CAAC,CAAC,EAAG,KAAMS,IAAM,QAAS,EAAIiD,EAAIA,EAAE1D,CAAC,EAAIA,CAAG,EAAI0D,CAAG,CAClJ,EAEAtE,GAAgB,SAAUqD,EAAG,CACzB,GAAI,CAAC,OAAO,cAAe,MAAM,IAAI,UAAU,sCAAsC,EACrF,IAAID,EAAIC,EAAE,OAAO,eAAgB,EACjC,OAAOD,EAAIA,EAAE,KAAKC,CAAC,GAAKA,EAAI,OAAO7D,GAAa,WAAaA,EAAS6D,CAAC,EAAIA,EAAE,OAAO,UAAU,EAAG,EAAI,CAAC,EAAGH,EAAK,MAAM,EAAGA,EAAK,OAAO,EAAGA,EAAK,QAAQ,EAAG,EAAE,OAAO,eAAiB,UAAY,CAAE,OAAO,IAAM,EAAG,GAC9M,SAASA,EAAK7B,EAAG,CAAE,EAAEA,GAAKgC,EAAEhC,IAAM,SAAUT,EAAG,CAAE,OAAO,IAAI,QAAQ,SAAU4B,EAASC,EAAQ,CAAE7B,EAAIyC,EAAEhC,GAAGT,CAAC,EAAGwD,EAAO5B,EAASC,EAAQ7B,EAAE,KAAMA,EAAE,KAAK,CAAG,CAAC,CAAG,CAAG,CAC/J,SAASwD,EAAO5B,EAASC,EAAQ1B,EAAGH,EAAG,CAAE,QAAQ,QAAQA,CAAC,EAAE,KAAK,SAASA,EAAG,CAAE4B,EAAQ,CAAE,MAAO5B,EAAG,KAAMG,CAAE,CAAC,CAAG,EAAG0B,CAAM,CAAG,CAC/H,EAEAxC,GAAuB,SAAUsE,EAAQC,EAAK,CAC1C,OAAI,OAAO,eAAkB,OAAO,eAAeD,EAAQ,MAAO,CAAE,MAAOC,CAAI,CAAC,EAAYD,EAAO,IAAMC,EAClGD,CACX,EAEA,IAAIE,EAAqB,OAAO,OAAU,SAASpB,EAAGzC,EAAG,CACrD,OAAO,eAAeyC,EAAG,UAAW,CAAE,WAAY,GAAM,MAAOzC,CAAE,CAAC,CACtE,EAAK,SAASyC,EAAGzC,EAAG,CAChByC,EAAE,QAAazC,CACnB,EAEAV,GAAe,SAAUwE,EAAK,CAC1B,GAAIA,GAAOA,EAAI,WAAY,OAAOA,EAClC,IAAI7B,EAAS,CAAC,EACd,GAAI6B,GAAO,KAAM,QAASpB,KAAKoB,EAASpB,IAAM,WAAa,OAAO,UAAU,eAAe,KAAKoB,EAAKpB,CAAC,GAAGhD,GAAgBuC,EAAQ6B,EAAKpB,CAAC,EACvI,OAAAmB,EAAmB5B,EAAQ6B,CAAG,EACvB7B,CACX,EAEA1C,GAAkB,SAAUuE,EAAK,CAC7B,OAAQA,GAAOA,EAAI,WAAcA,EAAM,CAAE,QAAWA,CAAI,CAC5D,EAEAtE,GAAyB,SAAUuE,EAAUC,EAAOC,EAAM,EAAG,CACzD,GAAIA,IAAS,KAAO,CAAC,EAAG,MAAM,IAAI,UAAU,+CAA+C,EAC3F,GAAI,OAAOD,GAAU,WAAaD,IAAaC,GAAS,CAAC,EAAI,CAACA,EAAM,IAAID,CAAQ,EAAG,MAAM,IAAI,UAAU,0EAA0E,EACjL,OAAOE,IAAS,IAAM,EAAIA,IAAS,IAAM,EAAE,KAAKF,CAAQ,EAAI,EAAI,EAAE,MAAQC,EAAM,IAAID,CAAQ,CAChG,EAEAtE,GAAyB,SAAUsE,EAAUC,EAAOrC,EAAOsC,EAAMP,EAAG,CAChE,GAAIO,IAAS,IAAK,MAAM,IAAI,UAAU,gCAAgC,EACtE,GAAIA,IAAS,KAAO,CAACP,EAAG,MAAM,IAAI,UAAU,+CAA+C,EAC3F,GAAI,OAAOM,GAAU,WAAaD,IAAaC,GAAS,CAACN,EAAI,CAACM,EAAM,IAAID,CAAQ,EAAG,MAAM,IAAI,UAAU,yEAAyE,EAChL,OAAQE,IAAS,IAAMP,EAAE,KAAKK,EAAUpC,CAAK,EAAI+B,EAAIA,EAAE,MAAQ/B,EAAQqC,EAAM,IAAID,EAAUpC,CAAK,EAAIA,CACxG,EAEA1B,EAAS,YAAa9B,EAAS,EAC/B8B,EAAS,WAAY7B,EAAQ,EAC7B6B,EAAS,SAAU5B,EAAM,EACzB4B,EAAS,aAAc3B,EAAU,EACjC2B,EAAS,UAAW1B,EAAO,EAC3B0B,EAAS,aAAczB,EAAU,EACjCyB,EAAS,YAAaxB,EAAS,EAC/BwB,EAAS,cAAevB,EAAW,EACnCuB,EAAS,eAAgBtB,EAAY,EACrCsB,EAAS,kBAAmBP,EAAe,EAC3CO,EAAS,WAAYrB,CAAQ,EAC7BqB,EAAS,SAAUpB,EAAM,EACzBoB,EAAS,WAAYnB,EAAQ,EAC7BmB,EAAS,iBAAkBlB,EAAc,EACzCkB,EAAS,gBAAiBjB,EAAa,EACvCiB,EAAS,UAAWhB,CAAO,EAC3BgB,EAAS,mBAAoBf,EAAgB,EAC7Ce,EAAS,mBAAoBd,EAAgB,EAC7Cc,EAAS,gBAAiBb,EAAa,EACvCa,EAAS,uBAAwBZ,EAAoB,EACrDY,EAAS,eAAgBX,EAAY,EACrCW,EAAS,kBAAmBV,EAAe,EAC3CU,EAAS,yBAA0BT,EAAsB,EACzDS,EAAS,yBAA0BR,EAAsB,CAC7D,CAAC,ICjTD,IAAAyE,GAAkB,WACZ,CACF,UAAAC,EACA,SAAAC,GACA,OAAAC,GACA,WAAAC,GACA,QAAAC,GACA,WAAAC,GACA,UAAAC,GACA,YAAAC,GACA,aAAAC,GACA,gBAAAC,GACA,SAAAC,EACA,OAAAC,EACA,SAAAC,GACA,eAAAC,GACA,cAAAC,EACA,QAAAC,GACA,iBAAAC,GACA,iBAAAC,GACA,cAAAC,GACA,qBAAAC,GACA,aAAAC,GACA,gBAAAC,GACA,uBAAAC,GACA,uBAAAC,EACJ,EAAI,GAAAC,QCtBE,SAAUC,EAAWC,EAAU,CACnC,OAAO,OAAOA,GAAU,UAC1B,CCGM,SAAUC,GAAoBC,EAAgC,CAClE,IAAMC,EAAS,SAACC,EAAa,CAC3B,MAAM,KAAKA,CAAQ,EACnBA,EAAS,MAAQ,IAAI,MAAK,EAAG,KAC/B,EAEMC,EAAWH,EAAWC,CAAM,EAClC,OAAAE,EAAS,UAAY,OAAO,OAAO,MAAM,SAAS,EAClDA,EAAS,UAAU,YAAcA,EAC1BA,CACT,CCDO,IAAMC,GAA+CC,GAC1D,SAACC,EAAM,CACL,OAAA,SAA4CC,EAA0B,CACpED,EAAO,IAAI,EACX,KAAK,QAAUC,EACRA,EAAO,OAAM;EACxBA,EAAO,IAAI,SAACC,EAAKC,EAAC,CAAK,OAAGA,EAAI,EAAC,KAAKD,EAAI,SAAQ,CAAzB,CAA6B,EAAE,KAAK;GAAM,EACzD,GACJ,KAAK,KAAO,sBACZ,KAAK,OAASD,CAChB,CARA,CAQC,ECvBC,SAAUG,EAAaC,EAA6BC,EAAO,CAC/D,GAAID,EAAK,CACP,IAAME,EAAQF,EAAI,QAAQC,CAAI,EAC9B,GAAKC,GAASF,EAAI,OAAOE,EAAO,CAAC,EAErC,CCOA,IAAAC,EAAA,UAAA,CAyBE,SAAAA,EAAoBC,EAA4B,CAA5B,KAAA,gBAAAA,EAdb,KAAA,OAAS,GAER,KAAA,WAAmD,KAMnD,KAAA,YAAqD,IAMV,CAQnD,OAAAD,EAAA,UAAA,YAAA,UAAA,aACME,EAEJ,GAAI,CAAC,KAAK,OAAQ,CAChB,KAAK,OAAS,GAGN,IAAAC,EAAe,KAAI,WAC3B,GAAIA,EAEF,GADA,KAAK,WAAa,KACd,MAAM,QAAQA,CAAU,MAC1B,QAAqBC,EAAAC,EAAAF,CAAU,EAAAG,EAAAF,EAAA,KAAA,EAAA,CAAAE,EAAA,KAAAA,EAAAF,EAAA,KAAA,EAAE,CAA5B,IAAMG,EAAMD,EAAA,MACfC,EAAO,OAAO,IAAI,yGAGpBJ,EAAW,OAAO,IAAI,EAIlB,IAAiBK,EAAqB,KAAI,gBAClD,GAAIC,EAAWD,CAAgB,EAC7B,GAAI,CACFA,EAAgB,QACTE,EAAP,CACAR,EAASQ,aAAaC,GAAsBD,EAAE,OAAS,CAACA,CAAC,EAIrD,IAAAE,EAAgB,KAAI,YAC5B,GAAIA,EAAa,CACf,KAAK,YAAc,SACnB,QAAwBC,EAAAR,EAAAO,CAAW,EAAAE,EAAAD,EAAA,KAAA,EAAA,CAAAC,EAAA,KAAAA,EAAAD,EAAA,KAAA,EAAE,CAAhC,IAAME,EAASD,EAAA,MAClB,GAAI,CACFE,GAAcD,CAAS,QAChBE,EAAP,CACAf,EAASA,GAAM,KAANA,EAAU,CAAA,EACfe,aAAeN,GACjBT,EAAMgB,EAAAA,EAAA,CAAA,EAAAC,EAAOjB,CAAM,CAAA,EAAAiB,EAAKF,EAAI,MAAM,CAAA,EAElCf,EAAO,KAAKe,CAAG,sGAMvB,GAAIf,EACF,MAAM,IAAIS,GAAoBT,CAAM,EAG1C,EAoBAF,EAAA,UAAA,IAAA,SAAIoB,EAAuB,OAGzB,GAAIA,GAAYA,IAAa,KAC3B,GAAI,KAAK,OAGPJ,GAAcI,CAAQ,MACjB,CACL,GAAIA,aAAoBpB,EAAc,CAGpC,GAAIoB,EAAS,QAAUA,EAAS,WAAW,IAAI,EAC7C,OAEFA,EAAS,WAAW,IAAI,GAEzB,KAAK,aAAcC,EAAA,KAAK,eAAW,MAAAA,IAAA,OAAAA,EAAI,CAAA,GAAI,KAAKD,CAAQ,EAG/D,EAOQpB,EAAA,UAAA,WAAR,SAAmBsB,EAAoB,CAC7B,IAAAnB,EAAe,KAAI,WAC3B,OAAOA,IAAemB,GAAW,MAAM,QAAQnB,CAAU,GAAKA,EAAW,SAASmB,CAAM,CAC1F,EASQtB,EAAA,UAAA,WAAR,SAAmBsB,EAAoB,CAC7B,IAAAnB,EAAe,KAAI,WAC3B,KAAK,WAAa,MAAM,QAAQA,CAAU,GAAKA,EAAW,KAAKmB,CAAM,EAAGnB,GAAcA,EAAa,CAACA,EAAYmB,CAAM,EAAIA,CAC5H,EAMQtB,EAAA,UAAA,cAAR,SAAsBsB,EAAoB,CAChC,IAAAnB,EAAe,KAAI,WACvBA,IAAemB,EACjB,KAAK,WAAa,KACT,MAAM,QAAQnB,CAAU,GACjCoB,EAAUpB,EAAYmB,CAAM,CAEhC,EAgBAtB,EAAA,UAAA,OAAA,SAAOoB,EAAsC,CACnC,IAAAR,EAAgB,KAAI,YAC5BA,GAAeW,EAAUX,EAAaQ,CAAQ,EAE1CA,aAAoBpB,GACtBoB,EAAS,cAAc,IAAI,CAE/B,EAlLcpB,EAAA,MAAS,UAAA,CACrB,IAAMwB,EAAQ,IAAIxB,EAClB,OAAAwB,EAAM,OAAS,GACRA,CACT,EAAE,EA+KJxB,GArLA,EAuLO,IAAMyB,GAAqBC,EAAa,MAEzC,SAAUC,GAAeC,EAAU,CACvC,OACEA,aAAiBF,GAChBE,GAAS,WAAYA,GAASC,EAAWD,EAAM,MAAM,GAAKC,EAAWD,EAAM,GAAG,GAAKC,EAAWD,EAAM,WAAW,CAEpH,CAEA,SAASE,GAAcC,EAAwC,CACzDF,EAAWE,CAAS,EACtBA,EAAS,EAETA,EAAU,YAAW,CAEzB,CChNO,IAAMC,EAAuB,CAClC,iBAAkB,KAClB,sBAAuB,KACvB,QAAS,OACT,sCAAuC,GACvC,yBAA0B,ICGrB,IAAMC,EAAmC,CAG9C,WAAA,SAAWC,EAAqBC,EAAgB,SAAEC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,EAAA,GAAA,UAAAA,GACxC,IAAAC,EAAaL,EAAe,SACpC,OAAIK,GAAQ,MAARA,EAAU,WACLA,EAAS,WAAU,MAAnBA,EAAQC,EAAA,CAAYL,EAASC,CAAO,EAAAK,EAAKJ,CAAI,CAAA,CAAA,EAE/C,WAAU,MAAA,OAAAG,EAAA,CAACL,EAASC,CAAO,EAAAK,EAAKJ,CAAI,CAAA,CAAA,CAC7C,EACA,aAAA,SAAaK,EAAM,CACT,IAAAH,EAAaL,EAAe,SACpC,QAAQK,GAAQ,KAAA,OAARA,EAAU,eAAgB,cAAcG,CAAa,CAC/D,EACA,SAAU,QCjBN,SAAUC,GAAqBC,EAAQ,CAC3CC,EAAgB,WAAW,UAAA,CACjB,IAAAC,EAAqBC,EAAM,iBACnC,GAAID,EAEFA,EAAiBF,CAAG,MAGpB,OAAMA,CAEV,CAAC,CACH,CCtBM,SAAUI,GAAI,CAAK,CCMlB,IAAMC,GAAyB,UAAA,CAAM,OAAAC,GAAmB,IAAK,OAAW,MAAS,CAA5C,EAAsE,EAO5G,SAAUC,GAAkBC,EAAU,CAC1C,OAAOF,GAAmB,IAAK,OAAWE,CAAK,CACjD,CAOM,SAAUC,GAAoBC,EAAQ,CAC1C,OAAOJ,GAAmB,IAAKI,EAAO,MAAS,CACjD,CAQM,SAAUJ,GAAmBK,EAAuBD,EAAYF,EAAU,CAC9E,MAAO,CACL,KAAIG,EACJ,MAAKD,EACL,MAAKF,EAET,CCrCA,IAAII,EAAuD,KASrD,SAAUC,EAAaC,EAAc,CACzC,GAAIC,EAAO,sCAAuC,CAChD,IAAMC,EAAS,CAACJ,EAKhB,GAJII,IACFJ,EAAU,CAAE,YAAa,GAAO,MAAO,IAAI,GAE7CE,EAAE,EACEE,EAAQ,CACJ,IAAAC,EAAyBL,EAAvBM,EAAWD,EAAA,YAAEE,EAAKF,EAAA,MAE1B,GADAL,EAAU,KACNM,EACF,MAAMC,QAMVL,EAAE,CAEN,CAMM,SAAUM,GAAaC,EAAQ,CAC/BN,EAAO,uCAAyCH,IAClDA,EAAQ,YAAc,GACtBA,EAAQ,MAAQS,EAEpB,CCrBA,IAAAC,EAAA,SAAAC,EAAA,CAAmCC,EAAAF,EAAAC,CAAA,EA6BjC,SAAAD,EAAYG,EAA6C,CAAzD,IAAAC,EACEH,EAAA,KAAA,IAAA,GAAO,KATC,OAAAG,EAAA,UAAqB,GAUzBD,GACFC,EAAK,YAAcD,EAGfE,GAAeF,CAAW,GAC5BA,EAAY,IAAIC,CAAI,GAGtBA,EAAK,YAAcE,IAEvB,CAzBO,OAAAN,EAAA,OAAP,SAAiBO,EAAwBC,EAA2BC,EAAqB,CACvF,OAAO,IAAIC,GAAeH,EAAMC,EAAOC,CAAQ,CACjD,EAgCAT,EAAA,UAAA,KAAA,SAAKW,EAAS,CACR,KAAK,UACPC,GAA0BC,GAAiBF,CAAK,EAAG,IAAI,EAEvD,KAAK,MAAMA,CAAM,CAErB,EASAX,EAAA,UAAA,MAAA,SAAMc,EAAS,CACT,KAAK,UACPF,GAA0BG,GAAkBD,CAAG,EAAG,IAAI,GAEtD,KAAK,UAAY,GACjB,KAAK,OAAOA,CAAG,EAEnB,EAQAd,EAAA,UAAA,SAAA,UAAA,CACM,KAAK,UACPY,GAA0BI,GAAuB,IAAI,GAErD,KAAK,UAAY,GACjB,KAAK,UAAS,EAElB,EAEAhB,EAAA,UAAA,YAAA,UAAA,CACO,KAAK,SACR,KAAK,UAAY,GACjBC,EAAA,UAAM,YAAW,KAAA,IAAA,EACjB,KAAK,YAAc,KAEvB,EAEUD,EAAA,UAAA,MAAV,SAAgBW,EAAQ,CACtB,KAAK,YAAY,KAAKA,CAAK,CAC7B,EAEUX,EAAA,UAAA,OAAV,SAAiBc,EAAQ,CACvB,GAAI,CACF,KAAK,YAAY,MAAMA,CAAG,UAE1B,KAAK,YAAW,EAEpB,EAEUd,EAAA,UAAA,UAAV,UAAA,CACE,GAAI,CACF,KAAK,YAAY,SAAQ,UAEzB,KAAK,YAAW,EAEpB,EACFA,CAAA,EApHmCiB,CAAY,EA2H/C,IAAMC,GAAQ,SAAS,UAAU,KAEjC,SAASC,GAAyCC,EAAQC,EAAY,CACpE,OAAOH,GAAM,KAAKE,EAAIC,CAAO,CAC/B,CAMA,IAAAC,GAAA,UAAA,CACE,SAAAA,EAAoBC,EAAqC,CAArC,KAAA,gBAAAA,CAAwC,CAE5D,OAAAD,EAAA,UAAA,KAAA,SAAKE,EAAQ,CACH,IAAAD,EAAoB,KAAI,gBAChC,GAAIA,EAAgB,KAClB,GAAI,CACFA,EAAgB,KAAKC,CAAK,QACnBC,EAAP,CACAC,GAAqBD,CAAK,EAGhC,EAEAH,EAAA,UAAA,MAAA,SAAMK,EAAQ,CACJ,IAAAJ,EAAoB,KAAI,gBAChC,GAAIA,EAAgB,MAClB,GAAI,CACFA,EAAgB,MAAMI,CAAG,QAClBF,EAAP,CACAC,GAAqBD,CAAK,OAG5BC,GAAqBC,CAAG,CAE5B,EAEAL,EAAA,UAAA,SAAA,UAAA,CACU,IAAAC,EAAoB,KAAI,gBAChC,GAAIA,EAAgB,SAClB,GAAI,CACFA,EAAgB,SAAQ,QACjBE,EAAP,CACAC,GAAqBD,CAAK,EAGhC,EACFH,CAAA,EArCA,EAuCAM,GAAA,SAAAC,EAAA,CAAuCC,EAAAF,EAAAC,CAAA,EACrC,SAAAD,EACEG,EACAN,EACAO,EAA8B,CAHhC,IAAAC,EAKEJ,EAAA,KAAA,IAAA,GAAO,KAEHN,EACJ,GAAIW,EAAWH,CAAc,GAAK,CAACA,EAGjCR,EAAkB,CAChB,KAAOQ,GAAc,KAAdA,EAAkB,OACzB,MAAON,GAAK,KAALA,EAAS,OAChB,SAAUO,GAAQ,KAARA,EAAY,YAEnB,CAEL,IAAIG,EACAF,GAAQG,EAAO,0BAIjBD,EAAU,OAAO,OAAOJ,CAAc,EACtCI,EAAQ,YAAc,UAAA,CAAM,OAAAF,EAAK,YAAW,CAAhB,EAC5BV,EAAkB,CAChB,KAAMQ,EAAe,MAAQZ,GAAKY,EAAe,KAAMI,CAAO,EAC9D,MAAOJ,EAAe,OAASZ,GAAKY,EAAe,MAAOI,CAAO,EACjE,SAAUJ,EAAe,UAAYZ,GAAKY,EAAe,SAAUI,CAAO,IAI5EZ,EAAkBQ,EAMtB,OAAAE,EAAK,YAAc,IAAIX,GAAiBC,CAAe,GACzD,CACF,OAAAK,CAAA,EAzCuCS,CAAU,EA2CjD,SAASC,GAAqBC,EAAU,CAClCC,EAAO,sCACTC,GAAaF,CAAK,EAIlBG,GAAqBH,CAAK,CAE9B,CAQA,SAASI,GAAoBC,EAAQ,CACnC,MAAMA,CACR,CAOA,SAASC,GAA0BC,EAA2CC,EAA2B,CAC/F,IAAAC,EAA0BR,EAAM,sBACxCQ,GAAyBC,EAAgB,WAAW,UAAA,CAAM,OAAAD,EAAsBF,EAAcC,CAAU,CAA9C,CAA+C,CAC3G,CAOO,IAAMG,GAA6D,CACxE,OAAQ,GACR,KAAMC,EACN,MAAOR,GACP,SAAUQ,GCjRL,IAAMC,EAA+B,UAAA,CAAM,OAAC,OAAO,QAAW,YAAc,OAAO,YAAe,cAAvD,EAAsE,ECyClH,SAAUC,EAAYC,EAAI,CAC9B,OAAOA,CACT,CCsCM,SAAUC,GAAoBC,EAA+B,CACjE,OAAIA,EAAI,SAAW,EACVC,EAGLD,EAAI,SAAW,EACVA,EAAI,GAGN,SAAeE,EAAQ,CAC5B,OAAOF,EAAI,OAAO,SAACG,EAAWC,EAAuB,CAAK,OAAAA,EAAGD,CAAI,CAAP,EAAUD,CAAY,CAClF,CACF,CC9EA,IAAAG,EAAA,UAAA,CAkBE,SAAAA,EAAYC,EAA6E,CACnFA,IACF,KAAK,WAAaA,EAEtB,CA4BA,OAAAD,EAAA,UAAA,KAAA,SAAQE,EAAyB,CAC/B,IAAMC,EAAa,IAAIH,EACvB,OAAAG,EAAW,OAAS,KACpBA,EAAW,SAAWD,EACfC,CACT,EA8IAH,EAAA,UAAA,UAAA,SACEI,EACAC,EACAC,EAA8B,CAHhC,IAAAC,EAAA,KAKQC,EAAaC,GAAaL,CAAc,EAAIA,EAAiB,IAAIM,GAAeN,EAAgBC,EAAOC,CAAQ,EAErH,OAAAK,EAAa,UAAA,CACL,IAAAC,EAAuBL,EAArBL,EAAQU,EAAA,SAAEC,EAAMD,EAAA,OACxBJ,EAAW,IACTN,EAGIA,EAAS,KAAKM,EAAYK,CAAM,EAChCA,EAIAN,EAAK,WAAWC,CAAU,EAG1BD,EAAK,cAAcC,CAAU,CAAC,CAEtC,CAAC,EAEMA,CACT,EAGUR,EAAA,UAAA,cAAV,SAAwBc,EAAmB,CACzC,GAAI,CACF,OAAO,KAAK,WAAWA,CAAI,QACpBC,EAAP,CAIAD,EAAK,MAAMC,CAAG,EAElB,EA6DAf,EAAA,UAAA,QAAA,SAAQgB,EAA0BC,EAAoC,CAAtE,IAAAV,EAAA,KACE,OAAAU,EAAcC,GAAeD,CAAW,EAEjC,IAAIA,EAAkB,SAACE,EAASC,EAAM,CAC3C,IAAMZ,EAAa,IAAIE,GAAkB,CACvC,KAAM,SAACW,EAAK,CACV,GAAI,CACFL,EAAKK,CAAK,QACHN,EAAP,CACAK,EAAOL,CAAG,EACVP,EAAW,YAAW,EAE1B,EACA,MAAOY,EACP,SAAUD,EACX,EACDZ,EAAK,UAAUC,CAAU,CAC3B,CAAC,CACH,EAGUR,EAAA,UAAA,WAAV,SAAqBQ,EAA2B,OAC9C,OAAOI,EAAA,KAAK,UAAM,MAAAA,IAAA,OAAA,OAAAA,EAAE,UAAUJ,CAAU,CAC1C,EAOAR,EAAA,UAACG,GAAD,UAAA,CACE,OAAO,IACT,EA4FAH,EAAA,UAAA,KAAA,UAAA,SAAKsB,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACH,OAAOC,GAAcF,CAAU,EAAE,IAAI,CACvC,EA6BAtB,EAAA,UAAA,UAAA,SAAUiB,EAAoC,CAA9C,IAAAV,EAAA,KACE,OAAAU,EAAcC,GAAeD,CAAW,EAEjC,IAAIA,EAAY,SAACE,EAASC,EAAM,CACrC,IAAIC,EACJd,EAAK,UACH,SAACkB,EAAI,CAAK,OAACJ,EAAQI,CAAT,EACV,SAACV,EAAQ,CAAK,OAAAK,EAAOL,CAAG,CAAV,EACd,UAAA,CAAM,OAAAI,EAAQE,CAAK,CAAb,CAAc,CAExB,CAAC,CACH,EA3aOrB,EAAA,OAAkC,SAAIC,EAAwD,CACnG,OAAO,IAAID,EAAcC,CAAS,CACpC,EA0aFD,GA/cA,EAwdA,SAAS0B,GAAeC,EAA+C,OACrE,OAAOC,EAAAD,GAAW,KAAXA,EAAeE,EAAO,WAAO,MAAAD,IAAA,OAAAA,EAAI,OAC1C,CAEA,SAASE,GAAcC,EAAU,CAC/B,OAAOA,GAASC,EAAWD,EAAM,IAAI,GAAKC,EAAWD,EAAM,KAAK,GAAKC,EAAWD,EAAM,QAAQ,CAChG,CAEA,SAASE,GAAgBF,EAAU,CACjC,OAAQA,GAASA,aAAiBG,GAAgBJ,GAAWC,CAAK,GAAKI,GAAeJ,CAAK,CAC7F,CC1eM,SAAUK,GAAQC,EAAW,CACjC,OAAOC,EAAWD,GAAM,KAAA,OAANA,EAAQ,IAAI,CAChC,CAMM,SAAUE,EACdC,EAAqF,CAErF,OAAO,SAACH,EAAqB,CAC3B,GAAID,GAAQC,CAAM,EAChB,OAAOA,EAAO,KAAK,SAA+BI,EAA2B,CAC3E,GAAI,CACF,OAAOD,EAAKC,EAAc,IAAI,QACvBC,EAAP,CACA,KAAK,MAAMA,CAAG,EAElB,CAAC,EAEH,MAAM,IAAI,UAAU,wCAAwC,CAC9D,CACF,CCjBM,SAAUC,EACdC,EACAC,EACAC,EACAC,EACAC,EAAuB,CAEvB,OAAO,IAAIC,GAAmBL,EAAaC,EAAQC,EAAYC,EAASC,CAAU,CACpF,CAMA,IAAAC,GAAA,SAAAC,EAAA,CAA2CC,EAAAF,EAAAC,CAAA,EAiBzC,SAAAD,EACEL,EACAC,EACAC,EACAC,EACQC,EACAI,EAAiC,CAN3C,IAAAC,EAoBEH,EAAA,KAAA,KAAMN,CAAW,GAAC,KAfV,OAAAS,EAAA,WAAAL,EACAK,EAAA,kBAAAD,EAeRC,EAAK,MAAQR,EACT,SAAuCS,EAAQ,CAC7C,GAAI,CACFT,EAAOS,CAAK,QACLC,EAAP,CACAX,EAAY,MAAMW,CAAG,EAEzB,EACAL,EAAA,UAAM,MACVG,EAAK,OAASN,EACV,SAAuCQ,EAAQ,CAC7C,GAAI,CACFR,EAAQQ,CAAG,QACJA,EAAP,CAEAX,EAAY,MAAMW,CAAG,UAGrB,KAAK,YAAW,EAEpB,EACAL,EAAA,UAAM,OACVG,EAAK,UAAYP,EACb,UAAA,CACE,GAAI,CACFA,EAAU,QACHS,EAAP,CAEAX,EAAY,MAAMW,CAAG,UAGrB,KAAK,YAAW,EAEpB,EACAL,EAAA,UAAM,WACZ,CAEA,OAAAD,EAAA,UAAA,YAAA,UAAA,OACE,GAAI,CAAC,KAAK,mBAAqB,KAAK,kBAAiB,EAAI,CAC/C,IAAAO,EAAW,KAAI,OACvBN,EAAA,UAAM,YAAW,KAAA,IAAA,EAEjB,CAACM,KAAUC,EAAA,KAAK,cAAU,MAAAA,IAAA,QAAAA,EAAA,KAAf,IAAI,GAEnB,EACFR,CAAA,EAnF2CS,CAAU,ECP9C,IAAMC,GAAuDC,GAClE,SAACC,EAAM,CACL,OAAA,UAAoC,CAClCA,EAAO,IAAI,EACX,KAAK,KAAO,0BACZ,KAAK,QAAU,qBACjB,CAJA,CAIC,ECXL,IAAAC,GAAA,SAAAC,EAAA,CAAgCC,EAAAF,EAAAC,CAAA,EAwB9B,SAAAD,GAAA,CAAA,IAAAG,EAEEF,EAAA,KAAA,IAAA,GAAO,KAzBT,OAAAE,EAAA,OAAS,GAEDA,EAAA,iBAAyC,KAGjDA,EAAA,UAA2B,CAAA,EAE3BA,EAAA,UAAY,GAEZA,EAAA,SAAW,GAEXA,EAAA,YAAmB,MAenB,CAGA,OAAAH,EAAA,UAAA,KAAA,SAAQI,EAAwB,CAC9B,IAAMC,EAAU,IAAIC,GAAiB,KAAM,IAAI,EAC/C,OAAAD,EAAQ,SAAWD,EACZC,CACT,EAGUL,EAAA,UAAA,eAAV,UAAA,CACE,GAAI,KAAK,OACP,MAAM,IAAIO,EAEd,EAEAP,EAAA,UAAA,KAAA,SAAKQ,EAAQ,CAAb,IAAAL,EAAA,KACEM,EAAa,UAAA,SAEX,GADAN,EAAK,eAAc,EACf,CAACA,EAAK,UAAW,CACdA,EAAK,mBACRA,EAAK,iBAAmB,MAAM,KAAKA,EAAK,SAAS,OAEnD,QAAuBO,EAAAC,EAAAR,EAAK,gBAAgB,EAAAS,EAAAF,EAAA,KAAA,EAAA,CAAAE,EAAA,KAAAA,EAAAF,EAAA,KAAA,EAAE,CAAzC,IAAMG,EAAQD,EAAA,MACjBC,EAAS,KAAKL,CAAK,qGAGzB,CAAC,CACH,EAEAR,EAAA,UAAA,MAAA,SAAMc,EAAQ,CAAd,IAAAX,EAAA,KACEM,EAAa,UAAA,CAEX,GADAN,EAAK,eAAc,EACf,CAACA,EAAK,UAAW,CACnBA,EAAK,SAAWA,EAAK,UAAY,GACjCA,EAAK,YAAcW,EAEnB,QADQC,EAAcZ,EAAI,UACnBY,EAAU,QACfA,EAAU,MAAK,EAAI,MAAMD,CAAG,EAGlC,CAAC,CACH,EAEAd,EAAA,UAAA,SAAA,UAAA,CAAA,IAAAG,EAAA,KACEM,EAAa,UAAA,CAEX,GADAN,EAAK,eAAc,EACf,CAACA,EAAK,UAAW,CACnBA,EAAK,UAAY,GAEjB,QADQY,EAAcZ,EAAI,UACnBY,EAAU,QACfA,EAAU,MAAK,EAAI,SAAQ,EAGjC,CAAC,CACH,EAEAf,EAAA,UAAA,YAAA,UAAA,CACE,KAAK,UAAY,KAAK,OAAS,GAC/B,KAAK,UAAY,KAAK,iBAAmB,IAC3C,EAEA,OAAA,eAAIA,EAAA,UAAA,WAAQ,KAAZ,UAAA,OACE,QAAOgB,EAAA,KAAK,aAAS,MAAAA,IAAA,OAAA,OAAAA,EAAE,QAAS,CAClC,kCAGUhB,EAAA,UAAA,cAAV,SAAwBiB,EAAyB,CAC/C,YAAK,eAAc,EACZhB,EAAA,UAAM,cAAa,KAAA,KAACgB,CAAU,CACvC,EAGUjB,EAAA,UAAA,WAAV,SAAqBiB,EAAyB,CAC5C,YAAK,eAAc,EACnB,KAAK,wBAAwBA,CAAU,EAChC,KAAK,gBAAgBA,CAAU,CACxC,EAGUjB,EAAA,UAAA,gBAAV,SAA0BiB,EAA2B,CAArD,IAAAd,EAAA,KACQa,EAAqC,KAAnCE,EAAQF,EAAA,SAAEG,EAASH,EAAA,UAAED,EAASC,EAAA,UACtC,OAAIE,GAAYC,EACPC,IAET,KAAK,iBAAmB,KACxBL,EAAU,KAAKE,CAAU,EAClB,IAAII,EAAa,UAAA,CACtBlB,EAAK,iBAAmB,KACxBmB,EAAUP,EAAWE,CAAU,CACjC,CAAC,EACH,EAGUjB,EAAA,UAAA,wBAAV,SAAkCiB,EAA2B,CACrD,IAAAD,EAAuC,KAArCE,EAAQF,EAAA,SAAEO,EAAWP,EAAA,YAAEG,EAASH,EAAA,UACpCE,EACFD,EAAW,MAAMM,CAAW,EACnBJ,GACTF,EAAW,SAAQ,CAEvB,EAQAjB,EAAA,UAAA,aAAA,UAAA,CACE,IAAMwB,EAAkB,IAAIC,EAC5B,OAAAD,EAAW,OAAS,KACbA,CACT,EAxHOxB,EAAA,OAAkC,SAAI0B,EAA0BC,EAAqB,CAC1F,OAAO,IAAIrB,GAAoBoB,EAAaC,CAAM,CACpD,EAuHF3B,GA7IgCyB,CAAU,EAkJ1C,IAAAG,GAAA,SAAAC,EAAA,CAAyCC,EAAAF,EAAAC,CAAA,EACvC,SAAAD,EAESG,EACPC,EAAsB,CAHxB,IAAAC,EAKEJ,EAAA,KAAA,IAAA,GAAO,KAHA,OAAAI,EAAA,YAAAF,EAIPE,EAAK,OAASD,GAChB,CAEA,OAAAJ,EAAA,UAAA,KAAA,SAAKM,EAAQ,UACXC,GAAAC,EAAA,KAAK,eAAW,MAAAA,IAAA,OAAA,OAAAA,EAAE,QAAI,MAAAD,IAAA,QAAAA,EAAA,KAAAC,EAAGF,CAAK,CAChC,EAEAN,EAAA,UAAA,MAAA,SAAMS,EAAQ,UACZF,GAAAC,EAAA,KAAK,eAAW,MAAAA,IAAA,OAAA,OAAAA,EAAE,SAAK,MAAAD,IAAA,QAAAA,EAAA,KAAAC,EAAGC,CAAG,CAC/B,EAEAT,EAAA,UAAA,SAAA,UAAA,UACEO,GAAAC,EAAA,KAAK,eAAW,MAAAA,IAAA,OAAA,OAAAA,EAAE,YAAQ,MAAAD,IAAA,QAAAA,EAAA,KAAAC,CAAA,CAC5B,EAGUR,EAAA,UAAA,WAAV,SAAqBU,EAAyB,SAC5C,OAAOH,GAAAC,EAAA,KAAK,UAAM,MAAAA,IAAA,OAAA,OAAAA,EAAE,UAAUE,CAAU,KAAC,MAAAH,IAAA,OAAAA,EAAII,EAC/C,EACFX,CAAA,EA1ByCY,EAAO,EC5JzC,IAAMC,EAA+C,CAC1D,IAAG,UAAA,CAGD,OAAQA,EAAsB,UAAY,MAAM,IAAG,CACrD,EACA,SAAU,QCwBZ,IAAAC,GAAA,SAAAC,EAAA,CAAsCC,EAAAF,EAAAC,CAAA,EAUpC,SAAAD,EACUG,EACAC,EACAC,EAA6D,CAF7DF,IAAA,SAAAA,EAAA,KACAC,IAAA,SAAAA,EAAA,KACAC,IAAA,SAAAA,EAAAC,GAHV,IAAAC,EAKEN,EAAA,KAAA,IAAA,GAAO,KAJC,OAAAM,EAAA,YAAAJ,EACAI,EAAA,YAAAH,EACAG,EAAA,mBAAAF,EAZFE,EAAA,QAA0B,CAAA,EAC1BA,EAAA,oBAAsB,GAc5BA,EAAK,oBAAsBH,IAAgB,IAC3CG,EAAK,YAAc,KAAK,IAAI,EAAGJ,CAAW,EAC1CI,EAAK,YAAc,KAAK,IAAI,EAAGH,CAAW,GAC5C,CAEA,OAAAJ,EAAA,UAAA,KAAA,SAAKQ,EAAQ,CACL,IAAAC,EAA+E,KAA7EC,EAASD,EAAA,UAAEE,EAAOF,EAAA,QAAEG,EAAmBH,EAAA,oBAAEJ,EAAkBI,EAAA,mBAAEL,EAAWK,EAAA,YAC3EC,IACHC,EAAQ,KAAKH,CAAK,EAClB,CAACI,GAAuBD,EAAQ,KAAKN,EAAmB,IAAG,EAAKD,CAAW,GAE7E,KAAK,YAAW,EAChBH,EAAA,UAAM,KAAI,KAAA,KAACO,CAAK,CAClB,EAGUR,EAAA,UAAA,WAAV,SAAqBa,EAAyB,CAC5C,KAAK,eAAc,EACnB,KAAK,YAAW,EAQhB,QANMC,EAAe,KAAK,gBAAgBD,CAAU,EAE9CJ,EAAmC,KAAjCG,EAAmBH,EAAA,oBAAEE,EAAOF,EAAA,QAG9BM,EAAOJ,EAAQ,MAAK,EACjBK,EAAI,EAAGA,EAAID,EAAK,QAAU,CAACF,EAAW,OAAQG,GAAKJ,EAAsB,EAAI,EACpFC,EAAW,KAAKE,EAAKC,EAAO,EAG9B,YAAK,wBAAwBH,CAAU,EAEhCC,CACT,EAEQd,EAAA,UAAA,YAAR,UAAA,CACQ,IAAAS,EAAoE,KAAlEN,EAAWM,EAAA,YAAEJ,EAAkBI,EAAA,mBAAEE,EAAOF,EAAA,QAAEG,EAAmBH,EAAA,oBAK/DQ,GAAsBL,EAAsB,EAAI,GAAKT,EAK3D,GAJAA,EAAc,KAAYc,EAAqBN,EAAQ,QAAUA,EAAQ,OAAO,EAAGA,EAAQ,OAASM,CAAkB,EAIlH,CAACL,EAAqB,CAKxB,QAJMM,EAAMb,EAAmB,IAAG,EAC9Bc,EAAO,EAGFH,EAAI,EAAGA,EAAIL,EAAQ,QAAWA,EAAQK,IAAiBE,EAAKF,GAAK,EACxEG,EAAOH,EAETG,GAAQR,EAAQ,OAAO,EAAGQ,EAAO,CAAC,EAEtC,EACFnB,CAAA,EAzEsCoB,EAAO,EClB7C,IAAAC,GAAA,SAAAC,EAAA,CAA+BC,EAAAF,EAAAC,CAAA,EAC7B,SAAAD,EAAYG,EAAsBC,EAAmD,QACnFH,EAAA,KAAA,IAAA,GAAO,IACT,CAWO,OAAAD,EAAA,UAAA,SAAP,SAAgBK,EAAWC,EAAiB,CAAjB,OAAAA,IAAA,SAAAA,EAAA,GAClB,IACT,EACFN,CAAA,EAjB+BO,CAAY,ECHpC,IAAMC,EAAqC,CAGhD,YAAA,SAAYC,EAAqBC,EAAgB,SAAEC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,EAAA,GAAA,UAAAA,GACzC,IAAAC,EAAaL,EAAgB,SACrC,OAAIK,GAAQ,MAARA,EAAU,YACLA,EAAS,YAAW,MAApBA,EAAQC,EAAA,CAAaL,EAASC,CAAO,EAAAK,EAAKJ,CAAI,CAAA,CAAA,EAEhD,YAAW,MAAA,OAAAG,EAAA,CAACL,EAASC,CAAO,EAAAK,EAAKJ,CAAI,CAAA,CAAA,CAC9C,EACA,cAAA,SAAcK,EAAM,CACV,IAAAH,EAAaL,EAAgB,SACrC,QAAQK,GAAQ,KAAA,OAARA,EAAU,gBAAiB,eAAeG,CAAa,CACjE,EACA,SAAU,QCrBZ,IAAAC,GAAA,SAAAC,EAAA,CAAoCC,EAAAF,EAAAC,CAAA,EAOlC,SAAAD,EAAsBG,EAAqCC,EAAmD,CAA9G,IAAAC,EACEJ,EAAA,KAAA,KAAME,EAAWC,CAAI,GAAC,KADF,OAAAC,EAAA,UAAAF,EAAqCE,EAAA,KAAAD,EAFjDC,EAAA,QAAmB,IAI7B,CAEO,OAAAL,EAAA,UAAA,SAAP,SAAgBM,EAAWC,EAAiB,OAC1C,GADyBA,IAAA,SAAAA,EAAA,GACrB,KAAK,OACP,OAAO,KAIT,KAAK,MAAQD,EAEb,IAAME,EAAK,KAAK,GACVL,EAAY,KAAK,UAuBvB,OAAIK,GAAM,OACR,KAAK,GAAK,KAAK,eAAeL,EAAWK,EAAID,CAAK,GAKpD,KAAK,QAAU,GAEf,KAAK,MAAQA,EAEb,KAAK,IAAKE,EAAA,KAAK,MAAE,MAAAA,IAAA,OAAAA,EAAI,KAAK,eAAeN,EAAW,KAAK,GAAII,CAAK,EAE3D,IACT,EAEUP,EAAA,UAAA,eAAV,SAAyBG,EAA2BO,EAAmBH,EAAiB,CAAjB,OAAAA,IAAA,SAAAA,EAAA,GAC9DI,EAAiB,YAAYR,EAAU,MAAM,KAAKA,EAAW,IAAI,EAAGI,CAAK,CAClF,EAEUP,EAAA,UAAA,eAAV,SAAyBY,EAA4BJ,EAAkBD,EAAwB,CAE7F,GAFqEA,IAAA,SAAAA,EAAA,GAEjEA,GAAS,MAAQ,KAAK,QAAUA,GAAS,KAAK,UAAY,GAC5D,OAAOC,EAILA,GAAM,MACRG,EAAiB,cAAcH,CAAE,CAIrC,EAMOR,EAAA,UAAA,QAAP,SAAeM,EAAUC,EAAa,CACpC,GAAI,KAAK,OACP,OAAO,IAAI,MAAM,8BAA8B,EAGjD,KAAK,QAAU,GACf,IAAMM,EAAQ,KAAK,SAASP,EAAOC,CAAK,EACxC,GAAIM,EACF,OAAOA,EACE,KAAK,UAAY,IAAS,KAAK,IAAM,OAc9C,KAAK,GAAK,KAAK,eAAe,KAAK,UAAW,KAAK,GAAI,IAAI,EAE/D,EAEUb,EAAA,UAAA,SAAV,SAAmBM,EAAUQ,EAAc,CACzC,IAAIC,EAAmB,GACnBC,EACJ,GAAI,CACF,KAAK,KAAKV,CAAK,QACRW,EAAP,CACAF,EAAU,GAIVC,EAAaC,GAAQ,IAAI,MAAM,oCAAoC,EAErE,GAAIF,EACF,YAAK,YAAW,EACTC,CAEX,EAEAhB,EAAA,UAAA,YAAA,UAAA,CACE,GAAI,CAAC,KAAK,OAAQ,CACV,IAAAS,EAAoB,KAAlBD,EAAEC,EAAA,GAAEN,EAASM,EAAA,UACbS,EAAYf,EAAS,QAE7B,KAAK,KAAO,KAAK,MAAQ,KAAK,UAAY,KAC1C,KAAK,QAAU,GAEfgB,EAAUD,EAAS,IAAI,EACnBV,GAAM,OACR,KAAK,GAAK,KAAK,eAAeL,EAAWK,EAAI,IAAI,GAGnD,KAAK,MAAQ,KACbP,EAAA,UAAM,YAAW,KAAA,IAAA,EAErB,EACFD,CAAA,EA9IoCoB,EAAM,ECgB1C,IAAAC,GAAA,UAAA,CAGE,SAAAA,EAAoBC,EAAoCC,EAAiC,CAAjCA,IAAA,SAAAA,EAAoBF,EAAU,KAAlE,KAAA,oBAAAC,EAClB,KAAK,IAAMC,CACb,CA6BO,OAAAF,EAAA,UAAA,SAAP,SAAmBG,EAAqDC,EAAmBC,EAAS,CAA5B,OAAAD,IAAA,SAAAA,EAAA,GAC/D,IAAI,KAAK,oBAAuB,KAAMD,CAAI,EAAE,SAASE,EAAOD,CAAK,CAC1E,EAnCcJ,EAAA,IAAoBM,EAAsB,IAoC1DN,GArCA,ECnBA,IAAAO,GAAA,SAAAC,EAAA,CAAoCC,EAAAF,EAAAC,CAAA,EAkBlC,SAAAD,EAAYG,EAAgCC,EAAiC,CAAjCA,IAAA,SAAAA,EAAoBC,GAAU,KAA1E,IAAAC,EACEL,EAAA,KAAA,KAAME,EAAiBC,CAAG,GAAC,KAlBtB,OAAAE,EAAA,QAAmC,CAAA,EAOnCA,EAAA,QAAmB,IAY1B,CAEO,OAAAN,EAAA,UAAA,MAAP,SAAaO,EAAwB,CAC3B,IAAAC,EAAY,KAAI,QAExB,GAAI,KAAK,QAAS,CAChBA,EAAQ,KAAKD,CAAM,EACnB,OAGF,IAAIE,EACJ,KAAK,QAAU,GAEf,EACE,IAAKA,EAAQF,EAAO,QAAQA,EAAO,MAAOA,EAAO,KAAK,EACpD,YAEMA,EAASC,EAAQ,MAAK,GAIhC,GAFA,KAAK,QAAU,GAEXC,EAAO,CACT,KAAQF,EAASC,EAAQ,MAAK,GAC5BD,EAAO,YAAW,EAEpB,MAAME,EAEV,EACFT,CAAA,EAhDoCK,EAAS,EC6CtC,IAAMK,EAAiB,IAAIC,GAAeC,EAAW,EAK/CC,GAAQH,ECUd,IAAMI,EAAQ,IAAIC,EAAkB,SAACC,EAAU,CAAK,OAAAA,EAAW,SAAQ,CAAnB,CAAqB,EC9D1E,SAAUC,GAAYC,EAAU,CACpC,OAAOA,GAASC,EAAWD,EAAM,QAAQ,CAC3C,CCDA,SAASE,GAAQC,EAAQ,CACvB,OAAOA,EAAIA,EAAI,OAAS,EAC1B,CAEM,SAAUC,GAAkBC,EAAW,CAC3C,OAAOC,EAAWJ,GAAKG,CAAI,CAAC,EAAIA,EAAK,IAAG,EAAK,MAC/C,CAEM,SAAUE,EAAaF,EAAW,CACtC,OAAOG,GAAYN,GAAKG,CAAI,CAAC,EAAIA,EAAK,IAAG,EAAK,MAChD,CAEM,SAAUI,GAAUJ,EAAaK,EAAoB,CACzD,OAAO,OAAOR,GAAKG,CAAI,GAAM,SAAWA,EAAK,IAAG,EAAMK,CACxD,CClBO,IAAMC,EAAe,SAAIC,EAAM,CAAwB,OAAAA,GAAK,OAAOA,EAAE,QAAW,UAAY,OAAOA,GAAM,UAAlD,ECMxD,SAAUC,GAAUC,EAAU,CAClC,OAAOC,EAAWD,GAAK,KAAA,OAALA,EAAO,IAAI,CAC/B,CCHM,SAAUE,GAAoBC,EAAU,CAC5C,OAAOC,EAAWD,EAAME,EAAkB,CAC5C,CCLM,SAAUC,GAAmBC,EAAQ,CACzC,OAAO,OAAO,eAAiBC,EAAWD,GAAG,KAAA,OAAHA,EAAM,OAAO,cAAc,CACvE,CCAM,SAAUE,GAAiCC,EAAU,CAEzD,OAAO,IAAI,UACT,iBACEA,IAAU,MAAQ,OAAOA,GAAU,SAAW,oBAAsB,IAAIA,EAAK,KAAG,0HACwC,CAE9H,CCXM,SAAUC,IAAiB,CAC/B,OAAI,OAAO,QAAW,YAAc,CAAC,OAAO,SACnC,aAGF,OAAO,QAChB,CAEO,IAAMC,GAAWD,GAAiB,ECJnC,SAAUE,GAAWC,EAAU,CACnC,OAAOC,EAAWD,GAAK,KAAA,OAALA,EAAQE,GAAgB,CAC5C,CCHM,SAAiBC,GAAsCC,EAAqC,mGAC1FC,EAASD,EAAe,UAAS,2DAGX,MAAA,CAAA,EAAAE,GAAMD,EAAO,KAAI,CAAE,CAAA,gBAArCE,EAAkBC,EAAA,KAAA,EAAhBC,EAAKF,EAAA,MAAEG,EAAIH,EAAA,KACfG,iBAAA,CAAA,EAAA,CAAA,SACF,MAAA,CAAA,EAAAF,EAAA,KAAA,CAAA,qBAEIC,CAAM,CAAA,SAAZ,MAAA,CAAA,EAAAD,EAAA,KAAA,CAAA,SAAA,OAAAA,EAAA,KAAA,mCAGF,OAAAH,EAAO,YAAW,6BAIhB,SAAUM,GAAwBC,EAAQ,CAG9C,OAAOC,EAAWD,GAAG,KAAA,OAAHA,EAAK,SAAS,CAClC,CCPM,SAAUE,EAAaC,EAAyB,CACpD,GAAIA,aAAiBC,EACnB,OAAOD,EAET,GAAIA,GAAS,KAAM,CACjB,GAAIE,GAAoBF,CAAK,EAC3B,OAAOG,GAAsBH,CAAK,EAEpC,GAAII,EAAYJ,CAAK,EACnB,OAAOK,GAAcL,CAAK,EAE5B,GAAIM,GAAUN,CAAK,EACjB,OAAOO,GAAYP,CAAK,EAE1B,GAAIQ,GAAgBR,CAAK,EACvB,OAAOS,GAAkBT,CAAK,EAEhC,GAAIU,GAAWV,CAAK,EAClB,OAAOW,GAAaX,CAAK,EAE3B,GAAIY,GAAqBZ,CAAK,EAC5B,OAAOa,GAAuBb,CAAK,EAIvC,MAAMc,GAAiCd,CAAK,CAC9C,CAMM,SAAUG,GAAyBY,EAAQ,CAC/C,OAAO,IAAId,EAAW,SAACe,EAAyB,CAC9C,IAAMC,EAAMF,EAAIG,GAAkB,EAClC,GAAIC,EAAWF,EAAI,SAAS,EAC1B,OAAOA,EAAI,UAAUD,CAAU,EAGjC,MAAM,IAAI,UAAU,gEAAgE,CACtF,CAAC,CACH,CASM,SAAUX,GAAiBe,EAAmB,CAClD,OAAO,IAAInB,EAAW,SAACe,EAAyB,CAU9C,QAASK,EAAI,EAAGA,EAAID,EAAM,QAAU,CAACJ,EAAW,OAAQK,IACtDL,EAAW,KAAKI,EAAMC,EAAE,EAE1BL,EAAW,SAAQ,CACrB,CAAC,CACH,CAEM,SAAUT,GAAee,EAAuB,CACpD,OAAO,IAAIrB,EAAW,SAACe,EAAyB,CAC9CM,EACG,KACC,SAACC,EAAK,CACCP,EAAW,SACdA,EAAW,KAAKO,CAAK,EACrBP,EAAW,SAAQ,EAEvB,EACA,SAACQ,EAAQ,CAAK,OAAAR,EAAW,MAAMQ,CAAG,CAApB,CAAqB,EAEpC,KAAK,KAAMC,EAAoB,CACpC,CAAC,CACH,CAEM,SAAUd,GAAgBe,EAAqB,CACnD,OAAO,IAAIzB,EAAW,SAACe,EAAyB,aAC9C,QAAoBW,EAAAC,EAAAF,CAAQ,EAAAG,EAAAF,EAAA,KAAA,EAAA,CAAAE,EAAA,KAAAA,EAAAF,EAAA,KAAA,EAAE,CAAzB,IAAMJ,EAAKM,EAAA,MAEd,GADAb,EAAW,KAAKO,CAAK,EACjBP,EAAW,OACb,yGAGJA,EAAW,SAAQ,CACrB,CAAC,CACH,CAEM,SAAUP,GAAqBqB,EAA+B,CAClE,OAAO,IAAI7B,EAAW,SAACe,EAAyB,CAC9Ce,GAAQD,EAAed,CAAU,EAAE,MAAM,SAACQ,EAAG,CAAK,OAAAR,EAAW,MAAMQ,CAAG,CAApB,CAAqB,CACzE,CAAC,CACH,CAEM,SAAUX,GAA0BmB,EAAqC,CAC7E,OAAOvB,GAAkBwB,GAAmCD,CAAc,CAAC,CAC7E,CAEA,SAAeD,GAAWD,EAAiCd,EAAyB,uIACxDkB,EAAAC,GAAAL,CAAa,gFAIrC,GAJeP,EAAKa,EAAA,MACpBpB,EAAW,KAAKO,CAAK,EAGjBP,EAAW,OACb,MAAA,CAAA,CAAA,6RAGJ,OAAAA,EAAW,SAAQ,WChHf,SAAUqB,EACdC,EACAC,EACAC,EACAC,EACAC,EAAc,CADdD,IAAA,SAAAA,EAAA,GACAC,IAAA,SAAAA,EAAA,IAEA,IAAMC,EAAuBJ,EAAU,SAAS,UAAA,CAC9CC,EAAI,EACAE,EACFJ,EAAmB,IAAI,KAAK,SAAS,KAAMG,CAAK,CAAC,EAEjD,KAAK,YAAW,CAEpB,EAAGA,CAAK,EAIR,GAFAH,EAAmB,IAAIK,CAAoB,EAEvC,CAACD,EAKH,OAAOC,CAEX,CCeM,SAAUC,GAAaC,EAA0BC,EAAS,CAAT,OAAAA,IAAA,SAAAA,EAAA,GAC9CC,EAAQ,SAACC,EAAQC,EAAU,CAChCD,EAAO,UACLE,EACED,EACA,SAACE,EAAK,CAAK,OAAAC,EAAgBH,EAAYJ,EAAW,UAAA,CAAM,OAAAI,EAAW,KAAKE,CAAK,CAArB,EAAwBL,CAAK,CAA1E,EACX,UAAA,CAAM,OAAAM,EAAgBH,EAAYJ,EAAW,UAAA,CAAM,OAAAI,EAAW,SAAQ,CAAnB,EAAuBH,CAAK,CAAzE,EACN,SAACO,EAAG,CAAK,OAAAD,EAAgBH,EAAYJ,EAAW,UAAA,CAAM,OAAAI,EAAW,MAAMI,CAAG,CAApB,EAAuBP,CAAK,CAAzE,CAA0E,CACpF,CAEL,CAAC,CACH,CCPM,SAAUQ,GAAeC,EAA0BC,EAAiB,CAAjB,OAAAA,IAAA,SAAAA,EAAA,GAChDC,EAAQ,SAACC,EAAQC,EAAU,CAChCA,EAAW,IAAIJ,EAAU,SAAS,UAAA,CAAM,OAAAG,EAAO,UAAUC,CAAU,CAA3B,EAA8BH,CAAK,CAAC,CAC9E,CAAC,CACH,CC7DM,SAAUI,GAAsBC,EAA6BC,EAAwB,CACzF,OAAOC,EAAUF,CAAK,EAAE,KAAKG,GAAYF,CAAS,EAAGG,GAAUH,CAAS,CAAC,CAC3E,CCFM,SAAUI,GAAmBC,EAAuBC,EAAwB,CAChF,OAAOC,EAAUF,CAAK,EAAE,KAAKG,GAAYF,CAAS,EAAGG,GAAUH,CAAS,CAAC,CAC3E,CCJM,SAAUI,GAAiBC,EAAqBC,EAAwB,CAC5E,OAAO,IAAIC,EAAc,SAACC,EAAU,CAElC,IAAIC,EAAI,EAER,OAAOH,EAAU,SAAS,UAAA,CACpBG,IAAMJ,EAAM,OAGdG,EAAW,SAAQ,GAInBA,EAAW,KAAKH,EAAMI,IAAI,EAIrBD,EAAW,QACd,KAAK,SAAQ,EAGnB,CAAC,CACH,CAAC,CACH,CCfM,SAAUE,GAAoBC,EAAoBC,EAAwB,CAC9E,OAAO,IAAIC,EAAc,SAACC,EAAU,CAClC,IAAIC,EAKJ,OAAAC,EAAgBF,EAAYF,EAAW,UAAA,CAErCG,EAAYJ,EAAcI,IAAgB,EAE1CC,EACEF,EACAF,EACA,UAAA,OACMK,EACAC,EACJ,GAAI,CAEDC,EAAkBJ,EAAS,KAAI,EAA7BE,EAAKE,EAAA,MAAED,EAAIC,EAAA,WACPC,EAAP,CAEAN,EAAW,MAAMM,CAAG,EACpB,OAGEF,EAKFJ,EAAW,SAAQ,EAGnBA,EAAW,KAAKG,CAAK,CAEzB,EACA,EACA,EAAI,CAER,CAAC,EAMM,UAAA,CAAM,OAAAI,EAAWN,GAAQ,KAAA,OAARA,EAAU,MAAM,GAAKA,EAAS,OAAM,CAA/C,CACf,CAAC,CACH,CCvDM,SAAUO,GAAyBC,EAAyBC,EAAwB,CACxF,GAAI,CAACD,EACH,MAAM,IAAI,MAAM,yBAAyB,EAE3C,OAAO,IAAIE,EAAc,SAACC,EAAU,CAClCC,EAAgBD,EAAYF,EAAW,UAAA,CACrC,IAAMI,EAAWL,EAAM,OAAO,eAAc,EAC5CI,EACED,EACAF,EACA,UAAA,CACEI,EAAS,KAAI,EAAG,KAAK,SAACC,EAAM,CACtBA,EAAO,KAGTH,EAAW,SAAQ,EAEnBA,EAAW,KAAKG,EAAO,KAAK,CAEhC,CAAC,CACH,EACA,EACA,EAAI,CAER,CAAC,CACH,CAAC,CACH,CCzBM,SAAUC,GAA8BC,EAA8BC,EAAwB,CAClG,OAAOC,GAAsBC,GAAmCH,CAAK,EAAGC,CAAS,CACnF,CCoBM,SAAUG,GAAaC,EAA2BC,EAAwB,CAC9E,GAAID,GAAS,KAAM,CACjB,GAAIE,GAAoBF,CAAK,EAC3B,OAAOG,GAAmBH,EAAOC,CAAS,EAE5C,GAAIG,EAAYJ,CAAK,EACnB,OAAOK,GAAcL,EAAOC,CAAS,EAEvC,GAAIK,GAAUN,CAAK,EACjB,OAAOO,GAAgBP,EAAOC,CAAS,EAEzC,GAAIO,GAAgBR,CAAK,EACvB,OAAOS,GAAsBT,EAAOC,CAAS,EAE/C,GAAIS,GAAWV,CAAK,EAClB,OAAOW,GAAiBX,EAAOC,CAAS,EAE1C,GAAIW,GAAqBZ,CAAK,EAC5B,OAAOa,GAA2Bb,EAAOC,CAAS,EAGtD,MAAMa,GAAiCd,CAAK,CAC9C,CCoDM,SAAUe,EAAQC,EAA2BC,EAAyB,CAC1E,OAAOA,EAAYC,GAAUF,EAAOC,CAAS,EAAIE,EAAUH,CAAK,CAClE,CCxBM,SAAUI,IAAE,SAAIC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACpB,IAAMC,EAAYC,EAAaH,CAAI,EACnC,OAAOI,EAAKJ,EAAaE,CAAS,CACpC,CC3EM,SAAUG,GAAYC,EAAU,CACpC,OAAOA,aAAiB,MAAQ,CAAC,MAAMA,CAAY,CACrD,CCsCM,SAAUC,EAAUC,EAAyCC,EAAa,CAC9E,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAEhC,IAAIC,EAAQ,EAGZF,EAAO,UACLG,EAAyBF,EAAY,SAACG,EAAQ,CAG5CH,EAAW,KAAKJ,EAAQ,KAAKC,EAASM,EAAOF,GAAO,CAAC,CACvD,CAAC,CAAC,CAEN,CAAC,CACH,CC1DQ,IAAAG,GAAY,MAAK,QAEzB,SAASC,GAAkBC,EAA6BC,EAAW,CAC/D,OAAOH,GAAQG,CAAI,EAAID,EAAE,MAAA,OAAAE,EAAA,CAAA,EAAAC,EAAIF,CAAI,CAAA,CAAA,EAAID,EAAGC,CAAI,CAChD,CAMM,SAAUG,GAAuBJ,EAA2B,CAC9D,OAAOK,EAAI,SAAAJ,EAAI,CAAI,OAAAF,GAAYC,EAAIC,CAAI,CAApB,CAAqB,CAC5C,CCKM,SAAUK,GACdC,EACAC,EACAC,EACAC,EACAC,EACAC,EACAC,EACAC,EAAgC,CAGhC,IAAMC,EAAc,CAAA,EAEhBC,EAAS,EAETC,EAAQ,EAERC,EAAa,GAKXC,EAAgB,UAAA,CAIhBD,GAAc,CAACH,EAAO,QAAU,CAACC,GACnCR,EAAW,SAAQ,CAEvB,EAGMY,EAAY,SAACC,EAAQ,CAAK,OAACL,EAASN,EAAaY,EAAWD,CAAK,EAAIN,EAAO,KAAKM,CAAK,CAA5D,EAE1BC,EAAa,SAACD,EAAQ,CAI1BT,GAAUJ,EAAW,KAAKa,CAAY,EAItCL,IAKA,IAAIO,EAAgB,GAGpBC,EAAUf,EAAQY,EAAOJ,GAAO,CAAC,EAAE,UACjCQ,EACEjB,EACA,SAACkB,EAAU,CAGTf,GAAY,MAAZA,EAAee,CAAU,EAErBd,EAGFQ,EAAUM,CAAiB,EAG3BlB,EAAW,KAAKkB,CAAU,CAE9B,EACA,UAAA,CAGEH,EAAgB,EAClB,EAEA,OACA,UAAA,CAIE,GAAIA,EAKF,GAAI,CAIFP,IAKA,qBACE,IAAMW,EAAgBZ,EAAO,MAAK,EAI9BF,EACFe,EAAgBpB,EAAYK,EAAmB,UAAA,CAAM,OAAAS,EAAWK,CAAa,CAAxB,CAAyB,EAE9EL,EAAWK,CAAa,GARrBZ,EAAO,QAAUC,EAASN,OAYjCS,EAAa,QACNU,EAAP,CACArB,EAAW,MAAMqB,CAAG,EAG1B,CAAC,CACF,CAEL,EAGA,OAAAtB,EAAO,UACLkB,EAAyBjB,EAAYY,EAAW,UAAA,CAE9CF,EAAa,GACbC,EAAa,CACf,CAAC,CAAC,EAKG,UAAA,CACLL,GAAmB,MAAnBA,EAAmB,CACrB,CACF,CClEM,SAAUgB,EACdC,EACAC,EACAC,EAA6B,CAE7B,OAFAA,IAAA,SAAAA,EAAA,KAEIC,EAAWF,CAAc,EAEpBF,EAAS,SAACK,EAAGC,EAAC,CAAK,OAAAC,EAAI,SAACC,EAAQC,EAAU,CAAK,OAAAP,EAAeG,EAAGG,EAAGF,EAAGG,CAAE,CAA1B,CAA2B,EAAEC,EAAUT,EAAQI,EAAGC,CAAC,CAAC,CAAC,CAAjF,EAAoFH,CAAU,GAC/G,OAAOD,GAAmB,WACnCC,EAAaD,GAGRS,EAAQ,SAACC,EAAQC,EAAU,CAAK,OAAAC,GAAeF,EAAQC,EAAYZ,EAASE,CAAU,CAAtD,CAAuD,EAChG,CChCM,SAAUY,GAAyCC,EAA6B,CAA7B,OAAAA,IAAA,SAAAA,EAAA,KAChDC,EAASC,EAAUF,CAAU,CACtC,CCNM,SAAUG,IAAS,CACvB,OAAOC,GAAS,CAAC,CACnB,CCmDM,SAAUC,IAAM,SAACC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACrB,OAAOC,GAAS,EAAGC,EAAKH,EAAMI,EAAaJ,CAAI,CAAC,CAAC,CACnD,CC1GA,IAAMK,GAA0B,CAAC,cAAe,gBAAgB,EAC1DC,GAAqB,CAAC,mBAAoB,qBAAqB,EAC/DC,GAAgB,CAAC,KAAM,KAAK,EA8N5B,SAAUC,EACdC,EACAC,EACAC,EACAC,EAAsC,CAMtC,GAJIC,EAAWF,CAAO,IACpBC,EAAiBD,EACjBA,EAAU,QAERC,EACF,OAAOJ,EAAaC,EAAQC,EAAWC,CAA+B,EAAE,KAAKG,GAAiBF,CAAc,CAAC,EAUzG,IAAAG,EAAAC,EAEJC,GAAcR,CAAM,EAChBH,GAAmB,IAAI,SAACY,EAAU,CAAK,OAAA,SAACC,EAAY,CAAK,OAAAV,EAAOS,GAAYR,EAAWS,EAASR,CAA+B,CAAtE,CAAlB,CAAyF,EAElIS,GAAwBX,CAAM,EAC5BJ,GAAwB,IAAIgB,GAAwBZ,EAAQC,CAAS,CAAC,EACtEY,GAA0Bb,CAAM,EAChCF,GAAc,IAAIc,GAAwBZ,EAAQC,CAAS,CAAC,EAC5D,CAAA,EAAE,CAAA,EATDa,EAAGR,EAAA,GAAES,EAAMT,EAAA,GAgBlB,GAAI,CAACQ,GACCE,EAAYhB,CAAM,EACpB,OAAOiB,EAAS,SAACC,EAAc,CAAK,OAAAnB,EAAUmB,EAAWjB,EAAWC,CAA+B,CAA/D,CAAgE,EAClGiB,EAAUnB,CAAM,CAAC,EAOvB,GAAI,CAACc,EACH,MAAM,IAAI,UAAU,sBAAsB,EAG5C,OAAO,IAAIM,EAAc,SAACC,EAAU,CAIlC,IAAMX,EAAU,UAAA,SAACY,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GAAmB,OAAAF,EAAW,KAAK,EAAIC,EAAK,OAASA,EAAOA,EAAK,EAAE,CAAhD,EAEpC,OAAAR,EAAIJ,CAAO,EAEJ,UAAA,CAAM,OAAAK,EAAQL,CAAO,CAAf,CACf,CAAC,CACH,CASA,SAASE,GAAwBZ,EAAaC,EAAiB,CAC7D,OAAO,SAACQ,EAAkB,CAAK,OAAA,SAACC,EAAY,CAAK,OAAAV,EAAOS,GAAYR,EAAWS,CAAO,CAArC,CAAlB,CACjC,CAOA,SAASC,GAAwBX,EAAW,CAC1C,OAAOI,EAAWJ,EAAO,WAAW,GAAKI,EAAWJ,EAAO,cAAc,CAC3E,CAOA,SAASa,GAA0Bb,EAAW,CAC5C,OAAOI,EAAWJ,EAAO,EAAE,GAAKI,EAAWJ,EAAO,GAAG,CACvD,CAOA,SAASQ,GAAcR,EAAW,CAChC,OAAOI,EAAWJ,EAAO,gBAAgB,GAAKI,EAAWJ,EAAO,mBAAmB,CACrF,CCvMM,SAAUwB,EACdC,EACAC,EACAC,EAAyC,CAFzCF,IAAA,SAAAA,EAAA,GAEAE,IAAA,SAAAA,EAAAC,IAIA,IAAIC,EAAmB,GAEvB,OAAIH,GAAuB,OAIrBI,GAAYJ,CAAmB,EACjCC,EAAYD,EAIZG,EAAmBH,GAIhB,IAAIK,EAAW,SAACC,EAAU,CAI/B,IAAIC,EAAMC,GAAYT,CAAO,EAAI,CAACA,EAAUE,EAAW,IAAG,EAAKF,EAE3DQ,EAAM,IAERA,EAAM,GAIR,IAAIE,EAAI,EAGR,OAAOR,EAAU,SAAS,UAAA,CACnBK,EAAW,SAEdA,EAAW,KAAKG,GAAG,EAEf,GAAKN,EAGP,KAAK,SAAS,OAAWA,CAAgB,EAGzCG,EAAW,SAAQ,EAGzB,EAAGC,CAAG,CACR,CAAC,CACH,CCvIM,SAAUG,GAASC,EAAYC,EAAyC,CAArD,OAAAD,IAAA,SAAAA,EAAA,GAAYC,IAAA,SAAAA,EAAAC,GAC/BF,EAAS,IAEXA,EAAS,GAGJG,EAAMH,EAAQA,EAAQC,CAAS,CACxC,CCgCM,SAAUG,IAAK,SAACC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACpB,IAAMC,EAAYC,EAAaH,CAAI,EAC7BI,EAAaC,GAAUL,EAAM,GAAQ,EACrCM,EAAUN,EAChB,OAAQM,EAAQ,OAGZA,EAAQ,SAAW,EAEnBC,EAAUD,EAAQ,EAAE,EAEpBE,GAASJ,CAAU,EAAEK,EAAKH,EAASJ,CAAS,CAAC,EAL7CQ,CAMN,CCjEO,IAAMC,GAAQ,IAAIC,EAAkBC,CAAI,ECwBzC,SAAUC,EAAUC,EAAiDC,EAAa,CACtF,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAEhC,IAAIC,EAAQ,EAIZF,EAAO,UAILG,EAAyBF,EAAY,SAACG,EAAK,CAAK,OAAAP,EAAU,KAAKC,EAASM,EAAOF,GAAO,GAAKD,EAAW,KAAKG,CAAK,CAAhE,CAAiE,CAAC,CAEtH,CAAC,CACH,CC3BM,SAAUC,EAAQC,EAAa,CACnC,OAAOA,GAAS,EAEZ,UAAA,CAAM,OAAAC,CAAA,EACNC,EAAQ,SAACC,EAAQC,EAAU,CACzB,IAAIC,EAAO,EACXF,EAAO,UACLG,EAAyBF,EAAY,SAACG,EAAK,CAIrC,EAAEF,GAAQL,IACZI,EAAW,KAAKG,CAAK,EAIjBP,GAASK,GACXD,EAAW,SAAQ,EAGzB,CAAC,CAAC,CAEN,CAAC,CACP,CC9BM,SAAUI,IAAc,CAC5B,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChCD,EAAO,UAAUE,EAAyBD,EAAYE,CAAI,CAAC,CAC7D,CAAC,CACH,CCCM,SAAUC,GAASC,EAAQ,CAC/B,OAAOC,EAAI,UAAA,CAAM,OAAAD,CAAA,CAAK,CACxB,CCyCM,SAAUE,GACdC,EACAC,EAAmC,CAEnC,OAAIA,EAEK,SAACC,EAAqB,CAC3B,OAAAC,GAAOF,EAAkB,KAAKG,EAAK,CAAC,EAAGC,GAAc,CAAE,EAAGH,EAAO,KAAKH,GAAUC,CAAqB,CAAC,CAAC,CAAvG,EAGGM,EAAS,SAACC,EAAOC,EAAK,CAAK,OAAAR,EAAsBO,EAAOC,CAAK,EAAE,KAAKJ,EAAK,CAAC,EAAGK,GAAMF,CAAK,CAAC,CAA9D,CAA+D,CACnG,CCtCM,SAAUG,GAASC,EAAoBC,EAAyC,CAAzCA,IAAA,SAAAA,EAAAC,GAC3C,IAAMC,EAAWC,EAAMJ,EAAKC,CAAS,EACrC,OAAOI,GAAU,UAAA,CAAM,OAAAF,CAAA,CAAQ,CACjC,CC0EM,SAAUG,GACdC,EACAC,EAA0D,CAA1D,OAAAA,IAAA,SAAAA,EAA+BC,GAK/BF,EAAaA,GAAU,KAAVA,EAAcG,GAEpBC,EAAQ,SAACC,EAAQC,EAAU,CAGhC,IAAIC,EAEAC,EAAQ,GAEZH,EAAO,UACLI,EAAyBH,EAAY,SAACI,EAAK,CAEzC,IAAMC,EAAaV,EAAYS,CAAK,GAKhCF,GAAS,CAACR,EAAYO,EAAaI,CAAU,KAM/CH,EAAQ,GACRD,EAAcI,EAGdL,EAAW,KAAKI,CAAK,EAEzB,CAAC,CAAC,CAEN,CAAC,CACH,CAEA,SAASP,GAAeS,EAAQC,EAAM,CACpC,OAAOD,IAAMC,CACf,CCrHM,SAAUC,GAAYC,EAAoB,CAC9C,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAGhC,GAAI,CACFD,EAAO,UAAUC,CAAU,UAE3BA,EAAW,IAAIH,CAAQ,EAE3B,CAAC,CACH,CCyCM,SAAUI,GAAUC,EAAqC,OACzDC,EAAQ,IACRC,EAEJ,OAAIF,GAAiB,OACf,OAAOA,GAAkB,UACxBG,EAA4BH,EAAa,MAAzCC,EAAKE,IAAA,OAAG,IAAQA,EAAED,EAAUF,EAAa,OAE5CC,EAAQD,GAILC,GAAS,EACZ,UAAA,CAAM,OAAAG,CAAA,EACNC,EAAQ,SAACC,EAAQC,EAAU,CACzB,IAAIC,EAAQ,EACRC,EAEEC,EAAc,UAAA,CAGlB,GAFAD,GAAS,MAATA,EAAW,YAAW,EACtBA,EAAY,KACRP,GAAS,KAAM,CACjB,IAAMS,EAAW,OAAOT,GAAU,SAAWU,EAAMV,CAAK,EAAIW,EAAUX,EAAMM,CAAK,CAAC,EAC5EM,EAAqBC,EAAyBR,EAAY,UAAA,CAC9DO,EAAmB,YAAW,EAC9BE,EAAiB,CACnB,CAAC,EACDL,EAAS,UAAUG,CAAkB,OAErCE,EAAiB,CAErB,EAEMA,EAAoB,UAAA,CACxB,IAAIC,EAAY,GAChBR,EAAYH,EAAO,UACjBS,EAAyBR,EAAY,OAAW,UAAA,CAC1C,EAAEC,EAAQP,EACRQ,EACFC,EAAW,EAEXO,EAAY,GAGdV,EAAW,SAAQ,CAEvB,CAAC,CAAC,EAGAU,GACFP,EAAW,CAEf,EAEAM,EAAiB,CACnB,CAAC,CACP,CCtFM,SAAUE,GACdC,EACAC,EAA6G,CAE7G,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChC,IAAIC,EAAyD,KACzDC,EAAQ,EAERC,EAAa,GAIXC,EAAgB,UAAA,CAAM,OAAAD,GAAc,CAACF,GAAmBD,EAAW,SAAQ,CAArD,EAE5BD,EAAO,UACLM,EACEL,EACA,SAACM,EAAK,CAEJL,GAAe,MAAfA,EAAiB,YAAW,EAC5B,IAAIM,EAAa,EACXC,EAAaN,IAEnBO,EAAUb,EAAQU,EAAOE,CAAU,CAAC,EAAE,UACnCP,EAAkBI,EACjBL,EAIA,SAACU,EAAU,CAAK,OAAAV,EAAW,KAAKH,EAAiBA,EAAeS,EAAOI,EAAYF,EAAYD,GAAY,EAAIG,CAAU,CAAzG,EAChB,UAAA,CAIET,EAAkB,KAClBG,EAAa,CACf,CAAC,CACD,CAEN,EACA,UAAA,CACED,EAAa,GACbC,EAAa,CACf,CAAC,CACF,CAEL,CAAC,CACH,CCvFM,SAAUO,GAAaC,EAA8B,CACzD,OAAOC,EAAQ,SAACC,EAAQC,EAAU,CAChCC,EAAUJ,CAAQ,EAAE,UAAUK,EAAyBF,EAAY,UAAA,CAAM,OAAAA,EAAW,SAAQ,CAAnB,EAAuBG,CAAI,CAAC,EACrG,CAACH,EAAW,QAAUD,EAAO,UAAUC,CAAU,CACnD,CAAC,CACH,CCwDM,SAAUI,GACdC,EACAC,EACAC,EAA8B,CAK9B,IAAMC,EACJC,EAAWJ,CAAc,GAAKC,GAASC,EAElC,CAAE,KAAMF,EAA2E,MAAKC,EAAE,SAAQC,CAAA,EACnGF,EAEN,OAAOG,EACHE,EAAQ,SAACC,EAAQC,EAAU,QACzBC,EAAAL,EAAY,aAAS,MAAAK,IAAA,QAAAA,EAAA,KAArBL,CAAW,EACX,IAAIM,EAAU,GACdH,EAAO,UACLI,EACEH,EACA,SAACI,EAAK,QACJH,EAAAL,EAAY,QAAI,MAAAK,IAAA,QAAAA,EAAA,KAAhBL,EAAmBQ,CAAK,EACxBJ,EAAW,KAAKI,CAAK,CACvB,EACA,UAAA,OACEF,EAAU,IACVD,EAAAL,EAAY,YAAQ,MAAAK,IAAA,QAAAA,EAAA,KAApBL,CAAW,EACXI,EAAW,SAAQ,CACrB,EACA,SAACK,EAAG,OACFH,EAAU,IACVD,EAAAL,EAAY,SAAK,MAAAK,IAAA,QAAAA,EAAA,KAAjBL,EAAoBS,CAAG,EACvBL,EAAW,MAAMK,CAAG,CACtB,EACA,UAAA,SACMH,KACFD,EAAAL,EAAY,eAAW,MAAAK,IAAA,QAAAA,EAAA,KAAvBL,CAAW,IAEbU,EAAAV,EAAY,YAAQ,MAAAU,IAAA,QAAAA,EAAA,KAApBV,CAAW,CACb,CAAC,CACF,CAEL,CAAC,EAIDW,CACN,CCjGM,SAAUC,IAAc,SAAOC,EAAA,CAAA,EAAAC,EAAA,EAAAA,EAAA,UAAA,OAAAA,IAAAD,EAAAC,GAAA,UAAAA,GACnC,IAAMC,EAAUC,GAAkBH,CAAM,EAExC,OAAOI,EAAQ,SAACC,EAAQC,EAAU,CAehC,QAdMC,EAAMP,EAAO,OACbQ,EAAc,IAAI,MAAMD,CAAG,EAI7BE,EAAWT,EAAO,IAAI,UAAA,CAAM,MAAA,EAAA,CAAK,EAGjCU,EAAQ,cAMHC,EAAC,CACRC,EAAUZ,EAAOW,EAAE,EAAE,UACnBE,EACEP,EACA,SAACQ,EAAK,CACJN,EAAYG,GAAKG,EACb,CAACJ,GAAS,CAACD,EAASE,KAEtBF,EAASE,GAAK,IAKbD,EAAQD,EAAS,MAAMM,CAAQ,KAAON,EAAW,MAEtD,EAGAO,CAAI,CACL,GAnBIL,EAAI,EAAGA,EAAIJ,EAAKI,MAAhBA,CAAC,EAwBVN,EAAO,UACLQ,EAAyBP,EAAY,SAACQ,EAAK,CACzC,GAAIJ,EAAO,CAET,IAAMO,EAAMC,EAAA,CAAIJ,CAAK,EAAAK,EAAKX,CAAW,CAAA,EACrCF,EAAW,KAAKJ,EAAUA,EAAO,MAAA,OAAAgB,EAAA,CAAA,EAAAC,EAAIF,CAAM,CAAA,CAAA,EAAIA,CAAM,EAEzD,CAAC,CAAC,CAEN,CAAC,CACH,CC9DA,IAAMG,GAAY,SAAS,cAAc,KAAK,EAC9C,SAAS,KAAK,YAAYA,EAAS,EAGnC,IAAMC,GAAS,SAAS,cAAc,oBAAoB,EAC1D,GAAIA,GAAQ,CACV,IAAMC,EAAS,SAAS,cAAc,QAAQ,EAC9CA,EAAO,UAAY,yEACfD,GAAO,eACTA,GAAO,cAAc,aAAaC,EAAQD,EAAM,EAGlD,IAAME,EAAM,IAAIC,GAAuB,CAAC,EACxCD,EACG,KACCE,GAAqB,CACvB,EACG,UAAUC,GAAM,CACf,eAAe,QAAQ,uCAAU,GAAGA,GAAI,EACxCJ,EAAO,OAAS,CAACI,CACnB,CAAC,EAGLH,EAAI,KAAK,KAAK,MAAM,eAAe,QAAQ,sCAAQ,GAAK,MAAM,CAAC,EAC/DI,EAAUL,EAAQ,OAAO,EACtB,KACCM,GAAeL,CAAG,CACpB,EACG,UAAU,CAAC,CAAC,CAAEG,CAAE,IAAMH,EAAI,KAAK,CAACG,CAAE,CAAC,EAGxCG,GAAS,GAAG,EACT,KACCC,GAAUP,EAAI,KAAKQ,EAAOL,GAAM,CAACA,CAAE,CAAC,CAAC,EACrCM,EAAK,EAAE,EACPC,GAAO,CAAE,MAAO,IAAMV,EAAI,KAAKQ,EAAOL,GAAMA,CAAE,CAAC,CAAE,CAAC,EAClDQ,EAAS,IAAM,CACb,IAAMC,EAAW,SAAS,cAAc,KAAK,EAC7C,OAAAA,EAAS,UAAY,uCACrBA,EAAS,WAAa,OACtBf,GAAU,YAAYe,CAAQ,EACvBC,GAAMC,GAAOC,GAAGH,CAAQ,CAAC,EAC7B,KACCI,GAAS,IAAMJ,EAAS,OAAO,CAAC,EAChCL,GAAUP,EAAI,KAAKQ,EAAOL,GAAM,CAACA,CAAE,CAAC,CAAC,EACrCc,GAAUC,GAAMd,EAAUc,EAAI,OAAO,EAClC,KACCC,GAAI,IAAMD,EAAG,UAAU,IAAI,4EAAgB,CAAC,EAC5CE,GAAM,GAAI,EACVD,GAAI,IAAMD,EAAG,UAAU,OAAO,4EAAgB,CAAC,CACjD,CACF,CACF,CACJ,CAAC,CACH,EACG,UAAU,CACjB",
+  "names": ["require_tslib", "__commonJSMin", "exports", "module", "__extends", "__assign", "__rest", "__decorate", "__param", "__metadata", "__awaiter", "__generator", "__exportStar", "__values", "__read", "__spread", "__spreadArrays", "__spreadArray", "__await", "__asyncGenerator", "__asyncDelegator", "__asyncValues", "__makeTemplateObject", "__importStar", "__importDefault", "__classPrivateFieldGet", "__classPrivateFieldSet", "__createBinding", "factory", "root", "createExporter", "previous", "id", "v", "exporter", "extendStatics", "d", "b", "p", "__", "t", "s", "n", "e", "i", "decorators", "target", "key", "desc", "c", "r", "paramIndex", "decorator", "metadataKey", "metadataValue", "thisArg", "_arguments", "P", "generator", "adopt", "value", "resolve", "reject", "fulfilled", "step", "rejected", "result", "body", "_", "y", "g", "verb", "op", "m", "o", "k", "k2", "ar", "error", "il", "j", "jl", "to", "from", "pack", "l", "q", "a", "resume", "settle", "fulfill", "f", "cooked", "raw", "__setModuleDefault", "mod", "receiver", "state", "kind", "import_tslib", "__extends", "__assign", "__rest", "__decorate", "__param", "__metadata", "__awaiter", "__generator", "__exportStar", "__createBinding", "__values", "__read", "__spread", "__spreadArrays", "__spreadArray", "__await", "__asyncGenerator", "__asyncDelegator", "__asyncValues", "__makeTemplateObject", "__importStar", "__importDefault", "__classPrivateFieldGet", "__classPrivateFieldSet", "tslib", "isFunction", "value", "createErrorClass", "createImpl", "_super", "instance", "ctorFunc", "UnsubscriptionError", "createErrorClass", "_super", "errors", "err", "i", "arrRemove", "arr", "item", "index", "Subscription", "initialTeardown", "errors", "_parentage", "_parentage_1", "__values", "_parentage_1_1", "parent_1", "initialFinalizer", "isFunction", "e", "UnsubscriptionError", "_finalizers", "_finalizers_1", "_finalizers_1_1", "finalizer", "execFinalizer", "err", "__spreadArray", "__read", "teardown", "_a", "parent", "arrRemove", "empty", "EMPTY_SUBSCRIPTION", "Subscription", "isSubscription", "value", "isFunction", "execFinalizer", "finalizer", "config", "timeoutProvider", "handler", "timeout", "args", "_i", "delegate", "__spreadArray", "__read", "handle", "reportUnhandledError", "err", "timeoutProvider", "onUnhandledError", "config", "noop", "COMPLETE_NOTIFICATION", "createNotification", "errorNotification", "error", "nextNotification", "value", "kind", "context", "errorContext", "cb", "config", "isRoot", "_a", "errorThrown", "error", "captureError", "err", "Subscriber", "_super", "__extends", "destination", "_this", "isSubscription", "EMPTY_OBSERVER", "next", "error", "complete", "SafeSubscriber", "value", "handleStoppedNotification", "nextNotification", "err", "errorNotification", "COMPLETE_NOTIFICATION", "Subscription", "_bind", "bind", "fn", "thisArg", "ConsumerObserver", "partialObserver", "value", "error", "handleUnhandledError", "err", "SafeSubscriber", "_super", "__extends", "observerOrNext", "complete", "_this", "isFunction", "context_1", "config", "Subscriber", "handleUnhandledError", "error", "config", "captureError", "reportUnhandledError", "defaultErrorHandler", "err", "handleStoppedNotification", "notification", "subscriber", "onStoppedNotification", "timeoutProvider", "EMPTY_OBSERVER", "noop", "observable", "identity", "x", "pipeFromArray", "fns", "identity", "input", "prev", "fn", "Observable", "subscribe", "operator", "observable", "observerOrNext", "error", "complete", "_this", "subscriber", "isSubscriber", "SafeSubscriber", "errorContext", "_a", "source", "sink", "err", "next", "promiseCtor", "getPromiseCtor", "resolve", "reject", "value", "operations", "_i", "pipeFromArray", "x", "getPromiseCtor", "promiseCtor", "_a", "config", "isObserver", "value", "isFunction", "isSubscriber", "Subscriber", "isSubscription", "hasLift", "source", "isFunction", "operate", "init", "liftedSource", "err", "createOperatorSubscriber", "destination", "onNext", "onComplete", "onError", "onFinalize", "OperatorSubscriber", "_super", "__extends", "shouldUnsubscribe", "_this", "value", "err", "closed_1", "_a", "Subscriber", "ObjectUnsubscribedError", "createErrorClass", "_super", "Subject", "_super", "__extends", "_this", "operator", "subject", "AnonymousSubject", "ObjectUnsubscribedError", "value", "errorContext", "_b", "__values", "_c", "observer", "err", "observers", "_a", "subscriber", "hasError", "isStopped", "EMPTY_SUBSCRIPTION", "Subscription", "arrRemove", "thrownError", "observable", "Observable", "destination", "source", "AnonymousSubject", "_super", "__extends", "destination", "source", "_this", "value", "_b", "_a", "err", "subscriber", "EMPTY_SUBSCRIPTION", "Subject", "dateTimestampProvider", "ReplaySubject", "_super", "__extends", "_bufferSize", "_windowTime", "_timestampProvider", "dateTimestampProvider", "_this", "value", "_a", "isStopped", "_buffer", "_infiniteTimeWindow", "subscriber", "subscription", "copy", "i", "adjustedBufferSize", "now", "last", "Subject", "Action", "_super", "__extends", "scheduler", "work", "state", "delay", "Subscription", "intervalProvider", "handler", "timeout", "args", "_i", "delegate", "__spreadArray", "__read", "handle", "AsyncAction", "_super", "__extends", "scheduler", "work", "_this", "state", "delay", "id", "_a", "_id", "intervalProvider", "_scheduler", "error", "_delay", "errored", "errorValue", "e", "actions", "arrRemove", "Action", "Scheduler", "schedulerActionCtor", "now", "work", "delay", "state", "dateTimestampProvider", "AsyncScheduler", "_super", "__extends", "SchedulerAction", "now", "Scheduler", "_this", "action", "actions", "error", "asyncScheduler", "AsyncScheduler", "AsyncAction", "async", "EMPTY", "Observable", "subscriber", "isScheduler", "value", "isFunction", "last", "arr", "popResultSelector", "args", "isFunction", "popScheduler", "isScheduler", "popNumber", "defaultValue", "isArrayLike", "x", "isPromise", "value", "isFunction", "isInteropObservable", "input", "isFunction", "observable", "isAsyncIterable", "obj", "isFunction", "createInvalidObservableTypeError", "input", "getSymbolIterator", "iterator", "isIterable", "input", "isFunction", "iterator", "readableStreamLikeToAsyncGenerator", "readableStream", "reader", "__await", "_a", "_b", "value", "done", "isReadableStreamLike", "obj", "isFunction", "innerFrom", "input", "Observable", "isInteropObservable", "fromInteropObservable", "isArrayLike", "fromArrayLike", "isPromise", "fromPromise", "isAsyncIterable", "fromAsyncIterable", "isIterable", "fromIterable", "isReadableStreamLike", "fromReadableStreamLike", "createInvalidObservableTypeError", "obj", "subscriber", "obs", "observable", "isFunction", "array", "i", "promise", "value", "err", "reportUnhandledError", "iterable", "iterable_1", "__values", "iterable_1_1", "asyncIterable", "process", "readableStream", "readableStreamLikeToAsyncGenerator", "asyncIterable_1", "__asyncValues", "asyncIterable_1_1", "executeSchedule", "parentSubscription", "scheduler", "work", "delay", "repeat", "scheduleSubscription", "observeOn", "scheduler", "delay", "operate", "source", "subscriber", "createOperatorSubscriber", "value", "executeSchedule", "err", "subscribeOn", "scheduler", "delay", "operate", "source", "subscriber", "scheduleObservable", "input", "scheduler", "innerFrom", "subscribeOn", "observeOn", "schedulePromise", "input", "scheduler", "innerFrom", "subscribeOn", "observeOn", "scheduleArray", "input", "scheduler", "Observable", "subscriber", "i", "scheduleIterable", "input", "scheduler", "Observable", "subscriber", "iterator", "executeSchedule", "value", "done", "_a", "err", "isFunction", "scheduleAsyncIterable", "input", "scheduler", "Observable", "subscriber", "executeSchedule", "iterator", "result", "scheduleReadableStreamLike", "input", "scheduler", "scheduleAsyncIterable", "readableStreamLikeToAsyncGenerator", "scheduled", "input", "scheduler", "isInteropObservable", "scheduleObservable", "isArrayLike", "scheduleArray", "isPromise", "schedulePromise", "isAsyncIterable", "scheduleAsyncIterable", "isIterable", "scheduleIterable", "isReadableStreamLike", "scheduleReadableStreamLike", "createInvalidObservableTypeError", "from", "input", "scheduler", "scheduled", "innerFrom", "of", "args", "_i", "scheduler", "popScheduler", "from", "isValidDate", "value", "map", "project", "thisArg", "operate", "source", "subscriber", "index", "createOperatorSubscriber", "value", "isArray", "callOrApply", "fn", "args", "__spreadArray", "__read", "mapOneOrManyArgs", "map", "mergeInternals", "source", "subscriber", "project", "concurrent", "onBeforeNext", "expand", "innerSubScheduler", "additionalFinalizer", "buffer", "active", "index", "isComplete", "checkComplete", "outerNext", "value", "doInnerSub", "innerComplete", "innerFrom", "createOperatorSubscriber", "innerValue", "bufferedValue", "executeSchedule", "err", "mergeMap", "project", "resultSelector", "concurrent", "isFunction", "a", "i", "map", "b", "ii", "innerFrom", "operate", "source", "subscriber", "mergeInternals", "mergeAll", "concurrent", "mergeMap", "identity", "concatAll", "mergeAll", "concat", "args", "_i", "concatAll", "from", "popScheduler", "nodeEventEmitterMethods", "eventTargetMethods", "jqueryMethods", "fromEvent", "target", "eventName", "options", "resultSelector", "isFunction", "mapOneOrManyArgs", "_a", "__read", "isEventTarget", "methodName", "handler", "isNodeStyleEventEmitter", "toCommonHandlerRegistry", "isJQueryStyleEventEmitter", "add", "remove", "isArrayLike", "mergeMap", "subTarget", "innerFrom", "Observable", "subscriber", "args", "_i", "timer", "dueTime", "intervalOrScheduler", "scheduler", "async", "intervalDuration", "isScheduler", "Observable", "subscriber", "due", "isValidDate", "n", "interval", "period", "scheduler", "asyncScheduler", "timer", "merge", "args", "_i", "scheduler", "popScheduler", "concurrent", "popNumber", "sources", "innerFrom", "mergeAll", "from", "EMPTY", "NEVER", "Observable", "noop", "filter", "predicate", "thisArg", "operate", "source", "subscriber", "index", "createOperatorSubscriber", "value", "take", "count", "EMPTY", "operate", "source", "subscriber", "seen", "createOperatorSubscriber", "value", "ignoreElements", "operate", "source", "subscriber", "createOperatorSubscriber", "noop", "mapTo", "value", "map", "delayWhen", "delayDurationSelector", "subscriptionDelay", "source", "concat", "take", "ignoreElements", "mergeMap", "value", "index", "mapTo", "delay", "due", "scheduler", "asyncScheduler", "duration", "timer", "delayWhen", "distinctUntilChanged", "comparator", "keySelector", "identity", "defaultCompare", "operate", "source", "subscriber", "previousKey", "first", "createOperatorSubscriber", "value", "currentKey", "a", "b", "finalize", "callback", "operate", "source", "subscriber", "repeat", "countOrConfig", "count", "delay", "_a", "EMPTY", "operate", "source", "subscriber", "soFar", "sourceSub", "resubscribe", "notifier", "timer", "innerFrom", "notifierSubscriber_1", "createOperatorSubscriber", "subscribeToSource", "syncUnsub", "switchMap", "project", "resultSelector", "operate", "source", "subscriber", "innerSubscriber", "index", "isComplete", "checkComplete", "createOperatorSubscriber", "value", "innerIndex", "outerIndex", "innerFrom", "innerValue", "takeUntil", "notifier", "operate", "source", "subscriber", "innerFrom", "createOperatorSubscriber", "noop", "tap", "observerOrNext", "error", "complete", "tapObserver", "isFunction", "operate", "source", "subscriber", "_a", "isUnsub", "createOperatorSubscriber", "value", "err", "_b", "identity", "withLatestFrom", "inputs", "_i", "project", "popResultSelector", "operate", "source", "subscriber", "len", "otherValues", "hasValue", "ready", "i", "innerFrom", "createOperatorSubscriber", "value", "identity", "noop", "values", "__spreadArray", "__read", "container", "header", "button", "on$", "ReplaySubject", "distinctUntilChanged", "on", "fromEvent", "withLatestFrom", "interval", "takeUntil", "filter", "take", "repeat", "mergeMap", "instance", "merge", "NEVER", "of", "finalize", "switchMap", "el", "tap", "delay"]
+}
diff --git a/7.3/assets/javascripts/lunr/min/lunr.ar.min.js b/7.3/assets/javascripts/lunr/min/lunr.ar.min.js
old mode 100755
new mode 100644
index 248ddc5d14..9b06c26c1f
--- a/7.3/assets/javascripts/lunr/min/lunr.ar.min.js
+++ b/7.3/assets/javascripts/lunr/min/lunr.ar.min.js
@@ -1 +1 @@
-!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ar=function(){this.pipeline.reset(),this.pipeline.add(e.ar.trimmer,e.ar.stopWordFilter,e.ar.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.ar.stemmer))},e.ar.wordCharacters="ء-ٛٱـ",e.ar.trimmer=e.trimmerSupport.generateTrimmer(e.ar.wordCharacters),e.Pipeline.registerFunction(e.ar.trimmer,"trimmer-ar"),e.ar.stemmer=function(){var e=this;return e.result=!1,e.preRemoved=!1,e.sufRemoved=!1,e.pre={pre1:"ف ك ب و س ل ن ا ي ت",pre2:"ال لل",pre3:"بال وال فال تال كال ولل",pre4:"فبال كبال وبال وكال"},e.suf={suf1:"ه ك ت ن ا ي",suf2:"نك نه ها وك يا اه ون ين تن تم نا وا ان كم كن ني نن ما هم هن تك ته ات يه",suf3:"تين كهم نيه نهم ونه وها يهم ونا ونك وني وهم تكم تنا تها تني تهم كما كها ناه نكم هنا تان يها",suf4:"كموه ناها ونني ونهم تكما تموه تكاه كماه ناكم ناهم نيها وننا"},e.patterns=JSON.parse('{"pt43":[{"pt":[{"c":"ا","l":1}]},{"pt":[{"c":"ا,ت,ن,ي","l":0}],"mPt":[{"c":"ف","l":0,"m":1},{"c":"ع","l":1,"m":2},{"c":"ل","l":2,"m":3}]},{"pt":[{"c":"و","l":2}],"mPt":[{"c":"ف","l":0,"m":0},{"c":"ع","l":1,"m":1},{"c":"ل","l":2,"m":3}]},{"pt":[{"c":"ا","l":2}]},{"pt":[{"c":"ي","l":2}],"mPt":[{"c":"ف","l":0,"m":0},{"c":"ع","l":1,"m":1},{"c":"ا","l":2},{"c":"ل","l":3,"m":3}]},{"pt":[{"c":"م","l":0}]}],"pt53":[{"pt":[{"c":"ت","l":0},{"c":"ا","l":2}]},{"pt":[{"c":"ا,ن,ت,ي","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":0},{"c":"ا","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":3},{"c":"ل","l":3,"m":4},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":0},{"c":"ا","l":3}],"mPt":[{"c":"ف","l":0,"m":1},{"c":"ع","l":1,"m":2},{"c":"ل","l":2,"m":4}]},{"pt":[{"c":"ا","l":3},{"c":"ن","l":4}]},{"pt":[{"c":"ت","l":0},{"c":"ي","l":3}]},{"pt":[{"c":"م","l":0},{"c":"و","l":3}]},{"pt":[{"c":"ا","l":1},{"c":"و","l":3}]},{"pt":[{"c":"و","l":1},{"c":"ا","l":2}]},{"pt":[{"c":"م","l":0},{"c":"ا","l":3}]},{"pt":[{"c":"م","l":0},{"c":"ي","l":3}]},{"pt":[{"c":"ا","l":2},{"c":"ن","l":3}]},{"pt":[{"c":"م","l":0},{"c":"ن","l":1}],"mPt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ف","l":2,"m":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"م","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"م","l":0},{"c":"ا","l":2}]},{"pt":[{"c":"م","l":1},{"c":"ا","l":3}]},{"pt":[{"c":"ي,ت,ا,ن","l":0},{"c":"ت","l":1}],"mPt":[{"c":"ف","l":0,"m":2},{"c":"ع","l":1,"m":3},{"c":"ا","l":2},{"c":"ل","l":3,"m":4}]},{"pt":[{"c":"ت,ي,ا,ن","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":2},{"c":"ي","l":3}]},{"pt":[{"c":"ا,ي,ت,ن","l":0},{"c":"ن","l":1}],"mPt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ف","l":2,"m":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":3},{"c":"ء","l":4}]}],"pt63":[{"pt":[{"c":"ا","l":0},{"c":"ت","l":2},{"c":"ا","l":4}]},{"pt":[{"c":"ا,ت,ن,ي","l":0},{"c":"س","l":1},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"س","l":1},{"c":"ت","l":2},{"c":"ف","l":3,"m":3},{"c":"ع","l":4,"m":4},{"c":"ا","l":5},{"c":"ل","l":6,"m":5}]},{"pt":[{"c":"ا,ن,ت,ي","l":0},{"c":"و","l":3}]},{"pt":[{"c":"م","l":0},{"c":"س","l":1},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"س","l":1},{"c":"ت","l":2},{"c":"ف","l":3,"m":3},{"c":"ع","l":4,"m":4},{"c":"ا","l":5},{"c":"ل","l":6,"m":5}]},{"pt":[{"c":"ي","l":1},{"c":"ي","l":3},{"c":"ا","l":4},{"c":"ء","l":5}]},{"pt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ا","l":4}]}],"pt54":[{"pt":[{"c":"ت","l":0}]},{"pt":[{"c":"ا,ي,ت,ن","l":0}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":2},{"c":"ل","l":3,"m":3},{"c":"ر","l":4,"m":4},{"c":"ا","l":5},{"c":"ر","l":6,"m":4}]},{"pt":[{"c":"م","l":0}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":2},{"c":"ل","l":3,"m":3},{"c":"ر","l":4,"m":4},{"c":"ا","l":5},{"c":"ر","l":6,"m":4}]},{"pt":[{"c":"ا","l":2}]},{"pt":[{"c":"ا","l":0},{"c":"ن","l":2}]}],"pt64":[{"pt":[{"c":"ا","l":0},{"c":"ا","l":4}]},{"pt":[{"c":"م","l":0},{"c":"ت","l":1}]}],"pt73":[{"pt":[{"c":"ا","l":0},{"c":"س","l":1},{"c":"ت","l":2},{"c":"ا","l":5}]}],"pt75":[{"pt":[{"c":"ا","l":0},{"c":"ا","l":5}]}]}'),e.execArray=["cleanWord","removeDiacritics","cleanAlef","removeStopWords","normalizeHamzaAndAlef","removeStartWaw","removePre432","removeEndTaa","wordCheck"],e.stem=function(){var r=0;for(e.result=!1,e.preRemoved=!1,e.sufRemoved=!1;r<e.execArray.length&&1!=e.result;)e.result=e[e.execArray[r]](),r++},e.setCurrent=function(r){e.word=r},e.getCurrent=function(){return e.word},e.cleanWord=function(){var r=new RegExp("[^ء-ٛٱـ]");return e.word=e.word.replace("ـ",""),!!r.test("")},e.removeDiacritics=function(){new RegExp("[ً-ٛ]");return e.word=e.word.replace(/[\u064b-\u065b]/gi,""),!1},e.cleanAlef=function(){var r=new RegExp("[آأإٱى]");return e.word=e.word.replace(r,"ا"),!1},e.removeStopWords=function(){if("، اض امين اه اها اي ا اب اجل اجمع اخ اخذ اصبح اضحى اقبل اقل اكثر الا ام اما امامك امامك امسى اما ان انا انت انتم انتما انتن انت انشا انى او اوشك اولئك اولئكم اولاء اولالك اوه اي ايا اين اينما اي ان اي اف اذ اذا اذا اذما اذن الى اليكم اليكما اليكن اليك اليك الا اما ان انما اي اياك اياكم اياكما اياكن ايانا اياه اياها اياهم اياهما اياهن اياي ايه ان ا ابتدا اثر اجل احد اخرى اخلولق اذا اربعة ارتد استحال اطار اعادة اعلنت اف اكثر اكد الالاء الالى الا الاخيرة الان الاول الاولى التى التي الثاني الثانية الذاتي الذى الذي الذين السابق الف اللائي اللاتي اللتان اللتيا اللتين اللذان اللذين اللواتي الماضي المقبل الوقت الى اليوم اما امام امس ان انبرى انقلب انه انها او اول اي ايار ايام ايضا ب بات باسم بان بخ برس بسبب بس بشكل بضع بطان بعد بعض بك بكم بكما بكن بل بلى بما بماذا بمن بن بنا به بها بي بيد بين بس بله بئس تان تانك تبدل تجاه تحول تلقاء تلك تلكم تلكما تم تينك تين ته تي ثلاثة ثم ثم ثمة ثم جعل جلل جميع جير حار حاشا حاليا حاي حتى حرى حسب حم حوالى حول حيث حيثما حين حي حبذا حتى حذار خلا خلال دون دونك ذا ذات ذاك ذانك ذان ذلك ذلكم ذلكما ذلكن ذو ذوا ذواتا ذواتي ذيت ذينك ذين ذه ذي راح رجع رويدك ريث رب زيارة سبحان سرعان سنة سنوات سوف سوى ساء ساءما شبه شخصا شرع شتان صار صباح صفر صه صه ضد ضمن طاق طالما طفق طق ظل عاد عام عاما عامة عدا عدة عدد عدم عسى عشر عشرة علق على عليك عليه عليها عل عن عند عندما عوض عين عدس عما غدا غير  ف فان فلان فو فى في فيم فيما فيه فيها قال قام قبل قد قط قلما قوة كانما كاين كاي كاين كاد كان كانت كذا كذلك كرب كل كلا كلاهما كلتا كلم كليكما كليهما كلما كلا كم كما كي كيت كيف كيفما كان كخ لئن لا لات لاسيما لدن لدى لعمر لقاء لك لكم لكما لكن لكنما لكي لكيلا للامم لم لما لما لن لنا له لها لو لوكالة لولا لوما لي لست لست لستم لستما لستن لست لسن لعل لكن ليت ليس ليسا ليستا ليست ليسوا لسنا ما ماانفك مابرح مادام ماذا مازال مافتئ مايو متى مثل مذ مساء مع معاذ مقابل مكانكم مكانكما مكانكن مكانك مليار مليون مما ممن من منذ منها مه مهما من من نحن نحو نعم نفس نفسه نهاية نخ نعما نعم ها هاؤم هاك هاهنا هب هذا هذه هكذا هل هلم هلا هم هما هن هنا هناك هنالك هو هي هيا هيت هيا هؤلاء هاتان هاتين هاته هاتي هج هذا هذان هذين هذه هذي هيهات و وا واحد واضاف واضافت واكد وان واها واوضح وراءك وفي وقال وقالت وقد وقف وكان وكانت ولا ولم ومن وهو وهي ويكان وي وشكان يكون يمكن يوم ايان".split(" ").indexOf(e.word)>=0)return!0},e.normalizeHamzaAndAlef=function(){return e.word=e.word.replace("ؤ","ء"),e.word=e.word.replace("ئ","ء"),e.word=e.word.replace(/([\u0627])\1+/gi,"ا"),!1},e.removeEndTaa=function(){return!(e.word.length>2)||(e.word=e.word.replace(/[\u0627]$/,""),e.word=e.word.replace("ة",""),!1)},e.removeStartWaw=function(){return e.word.length>3&&"و"==e.word[0]&&"و"==e.word[1]&&(e.word=e.word.slice(1)),!1},e.removePre432=function(){var r=e.word;if(e.word.length>=7){var t=new RegExp("^("+e.pre.pre4.split(" ").join("|")+")");e.word=e.word.replace(t,"")}if(e.word==r&&e.word.length>=6){var c=new RegExp("^("+e.pre.pre3.split(" ").join("|")+")");e.word=e.word.replace(c,"")}if(e.word==r&&e.word.length>=5){var l=new RegExp("^("+e.pre.pre2.split(" ").join("|")+")");e.word=e.word.replace(l,"")}return r!=e.word&&(e.preRemoved=!0),!1},e.patternCheck=function(r){for(var t=0;t<r.length;t++){for(var c=!0,l=0;l<r[t].pt.length;l++){var o=r[t].pt[l].c.split(","),n=!1;if(o.forEach(function(c){e.word[r[t].pt[l].l]==c&&(n=!0)}),!n){c=!1;break}}if(1==c){if(r[t].mPt){for(var p=[],m=0;m<r[t].mPt.length;m++)null!=r[t].mPt[m].m?p[r[t].mPt[m].l]=e.word[r[t].mPt[m].m]:p[r[t].mPt[m].l]=r[t].mPt[m].c;e.word=p.join("")}e.result=!0;break}}},e.removePre1=function(){var r=e.word;if(0==e.preRemoved&&e.word.length>3){var t=new RegExp("^("+e.pre.pre1.split(" ").join("|")+")");e.word=e.word.replace(t,"")}return r!=e.word&&(e.preRemoved=!0),!1},e.removeSuf1=function(){var r=e.word;if(0==e.sufRemoved&&e.word.length>3){var t=new RegExp("("+e.suf.suf1.split(" ").join("|")+")$");e.word=e.word.replace(t,"")}return r!=e.word&&(e.sufRemoved=!0),!1},e.removeSuf432=function(){var r=e.word;if(e.word.length>=6){var t=new RegExp("("+e.suf.suf4.split(" ").join("|")+")$");e.word=e.word.replace(t,"")}if(e.word==r&&e.word.length>=5){var c=new RegExp("("+e.suf.suf3.split(" ").join("|")+")$");e.word=e.word.replace(c,"")}if(e.word==r&&e.word.length>=4){var l=new RegExp("("+e.suf.suf2.split(" ").join("|")+")$");e.word=e.word.replace(l,"")}return r!=e.word&&(e.sufRemoved=!0),!1},e.wordCheck=function(){for(var r=(e.word,[e.removeSuf432,e.removeSuf1,e.removePre1]),t=0,c=!1;e.word.length>=7&&!e.result&&t<r.length;)7!=e.word.length||c?(r[t](),t++,c=!1):(e.checkPattern73(),c=!0);var l=[e.checkPattern63,e.removeSuf432,e.removeSuf1,e.removePre1,e.checkPattern64];for(t=0;6==e.word.length&&!e.result&&t<l.length;)l[t](),t++;var o=[e.checkPattern53,e.removeSuf432,e.removeSuf1,e.removePre1,e.checkPattern54];for(t=0;5==e.word.length&&!e.result&&t<o.length;)o[t](),t++;var n=[e.checkPattern43,e.removeSuf1,e.removePre1,e.removeSuf432];for(t=0;4==e.word.length&&!e.result&&t<n.length;)n[t](),t++;return!0},e.checkPattern43=function(){e.patternCheck(e.patterns.pt43)},e.checkPattern53=function(){e.patternCheck(e.patterns.pt53)},e.checkPattern54=function(){e.patternCheck(e.patterns.pt54)},e.checkPattern63=function(){e.patternCheck(e.patterns.pt63)},e.checkPattern64=function(){e.patternCheck(e.patterns.pt64)},e.checkPattern73=function(){e.patternCheck(e.patterns.pt73)},function(r){return"function"==typeof r.update?r.update(function(r){return e.setCurrent(r),e.stem(),e.getCurrent()}):(e.setCurrent(r),e.stem(),e.getCurrent())}}(),e.Pipeline.registerFunction(e.ar.stemmer,"stemmer-ar"),e.ar.stopWordFilter=e.generateStopWordFilter("، اض امين اه اها اي ا اب اجل اجمع اخ اخذ اصبح اضحى اقبل اقل اكثر الا ام اما امامك امامك امسى اما ان انا انت انتم انتما انتن انت انشا انى او اوشك اولئك اولئكم اولاء اولالك اوه اي ايا اين اينما اي ان اي اف اذ اذا اذا اذما اذن الى اليكم اليكما اليكن اليك اليك الا اما ان انما اي اياك اياكم اياكما اياكن ايانا اياه اياها اياهم اياهما اياهن اياي ايه ان ا ابتدا اثر اجل احد اخرى اخلولق اذا اربعة ارتد استحال اطار اعادة اعلنت اف اكثر اكد الالاء الالى الا الاخيرة الان الاول الاولى التى التي الثاني الثانية الذاتي الذى الذي الذين السابق الف اللائي اللاتي اللتان اللتيا اللتين اللذان اللذين اللواتي الماضي المقبل الوقت الى اليوم اما امام امس ان انبرى انقلب انه انها او اول اي ايار ايام ايضا ب بات باسم بان بخ برس بسبب بس بشكل بضع بطان بعد بعض بك بكم بكما بكن بل بلى بما بماذا بمن بن بنا به بها بي بيد بين بس بله بئس تان تانك تبدل تجاه تحول تلقاء تلك تلكم تلكما تم تينك تين ته تي ثلاثة ثم ثم ثمة ثم جعل جلل جميع جير حار حاشا حاليا حاي حتى حرى حسب حم حوالى حول حيث حيثما حين حي حبذا حتى حذار خلا خلال دون دونك ذا ذات ذاك ذانك ذان ذلك ذلكم ذلكما ذلكن ذو ذوا ذواتا ذواتي ذيت ذينك ذين ذه ذي راح رجع رويدك ريث رب زيارة سبحان سرعان سنة سنوات سوف سوى ساء ساءما شبه شخصا شرع شتان صار صباح صفر صه صه ضد ضمن طاق طالما طفق طق ظل عاد عام عاما عامة عدا عدة عدد عدم عسى عشر عشرة علق على عليك عليه عليها عل عن عند عندما عوض عين عدس عما غدا غير  ف فان فلان فو فى في فيم فيما فيه فيها قال قام قبل قد قط قلما قوة كانما كاين كاي كاين كاد كان كانت كذا كذلك كرب كل كلا كلاهما كلتا كلم كليكما كليهما كلما كلا كم كما كي كيت كيف كيفما كان كخ لئن لا لات لاسيما لدن لدى لعمر لقاء لك لكم لكما لكن لكنما لكي لكيلا للامم لم لما لما لن لنا له لها لو لوكالة لولا لوما لي لست لست لستم لستما لستن لست لسن لعل لكن ليت ليس ليسا ليستا ليست ليسوا لسنا ما ماانفك مابرح مادام ماذا مازال مافتئ مايو متى مثل مذ مساء مع معاذ مقابل مكانكم مكانكما مكانكن مكانك مليار مليون مما ممن من منذ منها مه مهما من من نحن نحو نعم نفس نفسه نهاية نخ نعما نعم ها هاؤم هاك هاهنا هب هذا هذه هكذا هل هلم هلا هم هما هن هنا هناك هنالك هو هي هيا هيت هيا هؤلاء هاتان هاتين هاته هاتي هج هذا هذان هذين هذه هذي هيهات وا واحد واضاف واضافت واكد وان واها واوضح وراءك وفي وقال وقالت وقد وقف وكان وكانت ولا ولم ومن وهو وهي ويكان وي وشكان يكون يمكن يوم ايان".split(" ")),e.Pipeline.registerFunction(e.ar.stopWordFilter,"stopWordFilter-ar")}});
\ No newline at end of file
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ar=function(){this.pipeline.reset(),this.pipeline.add(e.ar.trimmer,e.ar.stopWordFilter,e.ar.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.ar.stemmer))},e.ar.wordCharacters="ء-ٛٱـ",e.ar.trimmer=e.trimmerSupport.generateTrimmer(e.ar.wordCharacters),e.Pipeline.registerFunction(e.ar.trimmer,"trimmer-ar"),e.ar.stemmer=function(){var e=this;return e.result=!1,e.preRemoved=!1,e.sufRemoved=!1,e.pre={pre1:"ف ك ب و س ل ن ا ي ت",pre2:"ال لل",pre3:"بال وال فال تال كال ولل",pre4:"فبال كبال وبال وكال"},e.suf={suf1:"ه ك ت ن ا ي",suf2:"نك نه ها وك يا اه ون ين تن تم نا وا ان كم كن ني نن ما هم هن تك ته ات يه",suf3:"تين كهم نيه نهم ونه وها يهم ونا ونك وني وهم تكم تنا تها تني تهم كما كها ناه نكم هنا تان يها",suf4:"كموه ناها ونني ونهم تكما تموه تكاه كماه ناكم ناهم نيها وننا"},e.patterns=JSON.parse('{"pt43":[{"pt":[{"c":"ا","l":1}]},{"pt":[{"c":"ا,ت,ن,ي","l":0}],"mPt":[{"c":"ف","l":0,"m":1},{"c":"ع","l":1,"m":2},{"c":"ل","l":2,"m":3}]},{"pt":[{"c":"و","l":2}],"mPt":[{"c":"ف","l":0,"m":0},{"c":"ع","l":1,"m":1},{"c":"ل","l":2,"m":3}]},{"pt":[{"c":"ا","l":2}]},{"pt":[{"c":"ي","l":2}],"mPt":[{"c":"ف","l":0,"m":0},{"c":"ع","l":1,"m":1},{"c":"ا","l":2},{"c":"ل","l":3,"m":3}]},{"pt":[{"c":"م","l":0}]}],"pt53":[{"pt":[{"c":"ت","l":0},{"c":"ا","l":2}]},{"pt":[{"c":"ا,ن,ت,ي","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":0},{"c":"ا","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":3},{"c":"ل","l":3,"m":4},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":0},{"c":"ا","l":3}],"mPt":[{"c":"ف","l":0,"m":1},{"c":"ع","l":1,"m":2},{"c":"ل","l":2,"m":4}]},{"pt":[{"c":"ا","l":3},{"c":"ن","l":4}]},{"pt":[{"c":"ت","l":0},{"c":"ي","l":3}]},{"pt":[{"c":"م","l":0},{"c":"و","l":3}]},{"pt":[{"c":"ا","l":1},{"c":"و","l":3}]},{"pt":[{"c":"و","l":1},{"c":"ا","l":2}]},{"pt":[{"c":"م","l":0},{"c":"ا","l":3}]},{"pt":[{"c":"م","l":0},{"c":"ي","l":3}]},{"pt":[{"c":"ا","l":2},{"c":"ن","l":3}]},{"pt":[{"c":"م","l":0},{"c":"ن","l":1}],"mPt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ف","l":2,"m":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"م","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"م","l":0},{"c":"ا","l":2}]},{"pt":[{"c":"م","l":1},{"c":"ا","l":3}]},{"pt":[{"c":"ي,ت,ا,ن","l":0},{"c":"ت","l":1}],"mPt":[{"c":"ف","l":0,"m":2},{"c":"ع","l":1,"m":3},{"c":"ا","l":2},{"c":"ل","l":3,"m":4}]},{"pt":[{"c":"ت,ي,ا,ن","l":0},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ت","l":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":2},{"c":"ي","l":3}]},{"pt":[{"c":"ا,ي,ت,ن","l":0},{"c":"ن","l":1}],"mPt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ف","l":2,"m":2},{"c":"ع","l":3,"m":3},{"c":"ا","l":4},{"c":"ل","l":5,"m":4}]},{"pt":[{"c":"ا","l":3},{"c":"ء","l":4}]}],"pt63":[{"pt":[{"c":"ا","l":0},{"c":"ت","l":2},{"c":"ا","l":4}]},{"pt":[{"c":"ا,ت,ن,ي","l":0},{"c":"س","l":1},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"س","l":1},{"c":"ت","l":2},{"c":"ف","l":3,"m":3},{"c":"ع","l":4,"m":4},{"c":"ا","l":5},{"c":"ل","l":6,"m":5}]},{"pt":[{"c":"ا,ن,ت,ي","l":0},{"c":"و","l":3}]},{"pt":[{"c":"م","l":0},{"c":"س","l":1},{"c":"ت","l":2}],"mPt":[{"c":"ا","l":0},{"c":"س","l":1},{"c":"ت","l":2},{"c":"ف","l":3,"m":3},{"c":"ع","l":4,"m":4},{"c":"ا","l":5},{"c":"ل","l":6,"m":5}]},{"pt":[{"c":"ي","l":1},{"c":"ي","l":3},{"c":"ا","l":4},{"c":"ء","l":5}]},{"pt":[{"c":"ا","l":0},{"c":"ن","l":1},{"c":"ا","l":4}]}],"pt54":[{"pt":[{"c":"ت","l":0}]},{"pt":[{"c":"ا,ي,ت,ن","l":0}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":2},{"c":"ل","l":3,"m":3},{"c":"ر","l":4,"m":4},{"c":"ا","l":5},{"c":"ر","l":6,"m":4}]},{"pt":[{"c":"م","l":0}],"mPt":[{"c":"ا","l":0},{"c":"ف","l":1,"m":1},{"c":"ع","l":2,"m":2},{"c":"ل","l":3,"m":3},{"c":"ر","l":4,"m":4},{"c":"ا","l":5},{"c":"ر","l":6,"m":4}]},{"pt":[{"c":"ا","l":2}]},{"pt":[{"c":"ا","l":0},{"c":"ن","l":2}]}],"pt64":[{"pt":[{"c":"ا","l":0},{"c":"ا","l":4}]},{"pt":[{"c":"م","l":0},{"c":"ت","l":1}]}],"pt73":[{"pt":[{"c":"ا","l":0},{"c":"س","l":1},{"c":"ت","l":2},{"c":"ا","l":5}]}],"pt75":[{"pt":[{"c":"ا","l":0},{"c":"ا","l":5}]}]}'),e.execArray=["cleanWord","removeDiacritics","cleanAlef","removeStopWords","normalizeHamzaAndAlef","removeStartWaw","removePre432","removeEndTaa","wordCheck"],e.stem=function(){var r=0;for(e.result=!1,e.preRemoved=!1,e.sufRemoved=!1;r<e.execArray.length&&1!=e.result;)e.result=e[e.execArray[r]](),r++},e.setCurrent=function(r){e.word=r},e.getCurrent=function(){return e.word},e.cleanWord=function(){var r=new RegExp("[^ء-ٛٱـ]");return e.word=e.word.replace(new RegExp("ـ","g"),""),!!r.test("")},e.removeDiacritics=function(){new RegExp("[ً-ٛ]");return e.word=e.word.replace(/[\u064b-\u065b]/gi,""),!1},e.cleanAlef=function(){var r=new RegExp("[آأإٱى]");return e.word=e.word.replace(r,"ا"),!1},e.removeStopWords=function(){if("، اض امين اه اها اي ا اب اجل اجمع اخ اخذ اصبح اضحى اقبل اقل اكثر الا ام اما امامك امامك امسى اما ان انا انت انتم انتما انتن انت انشا انى او اوشك اولئك اولئكم اولاء اولالك اوه اي ايا اين اينما اي ان اي اف اذ اذا اذا اذما اذن الى اليكم اليكما اليكن اليك اليك الا اما ان انما اي اياك اياكم اياكما اياكن ايانا اياه اياها اياهم اياهما اياهن اياي ايه ان ا ابتدا اثر اجل احد اخرى اخلولق اذا اربعة ارتد استحال اطار اعادة اعلنت اف اكثر اكد الالاء الالى الا الاخيرة الان الاول الاولى التى التي الثاني الثانية الذاتي الذى الذي الذين السابق الف اللائي اللاتي اللتان اللتيا اللتين اللذان اللذين اللواتي الماضي المقبل الوقت الى اليوم اما امام امس ان انبرى انقلب انه انها او اول اي ايار ايام ايضا ب بات باسم بان بخ برس بسبب بس بشكل بضع بطان بعد بعض بك بكم بكما بكن بل بلى بما بماذا بمن بن بنا به بها بي بيد بين بس بله بئس تان تانك تبدل تجاه تحول تلقاء تلك تلكم تلكما تم تينك تين ته تي ثلاثة ثم ثم ثمة ثم جعل جلل جميع جير حار حاشا حاليا حاي حتى حرى حسب حم حوالى حول حيث حيثما حين حي حبذا حتى حذار خلا خلال دون دونك ذا ذات ذاك ذانك ذان ذلك ذلكم ذلكما ذلكن ذو ذوا ذواتا ذواتي ذيت ذينك ذين ذه ذي راح رجع رويدك ريث رب زيارة سبحان سرعان سنة سنوات سوف سوى ساء ساءما شبه شخصا شرع شتان صار صباح صفر صه صه ضد ضمن طاق طالما طفق طق ظل عاد عام عاما عامة عدا عدة عدد عدم عسى عشر عشرة علق على عليك عليه عليها عل عن عند عندما عوض عين عدس عما غدا غير  ف فان فلان فو فى في فيم فيما فيه فيها قال قام قبل قد قط قلما قوة كانما كاين كاي كاين كاد كان كانت كذا كذلك كرب كل كلا كلاهما كلتا كلم كليكما كليهما كلما كلا كم كما كي كيت كيف كيفما كان كخ لئن لا لات لاسيما لدن لدى لعمر لقاء لك لكم لكما لكن لكنما لكي لكيلا للامم لم لما لما لن لنا له لها لو لوكالة لولا لوما لي لست لست لستم لستما لستن لست لسن لعل لكن ليت ليس ليسا ليستا ليست ليسوا لسنا ما ماانفك مابرح مادام ماذا مازال مافتئ مايو متى مثل مذ مساء مع معاذ مقابل مكانكم مكانكما مكانكن مكانك مليار مليون مما ممن من منذ منها مه مهما من من نحن نحو نعم نفس نفسه نهاية نخ نعما نعم ها هاؤم هاك هاهنا هب هذا هذه هكذا هل هلم هلا هم هما هن هنا هناك هنالك هو هي هيا هيت هيا هؤلاء هاتان هاتين هاته هاتي هج هذا هذان هذين هذه هذي هيهات و وا واحد واضاف واضافت واكد وان واها واوضح وراءك وفي وقال وقالت وقد وقف وكان وكانت ولا ولم ومن وهو وهي ويكان وي وشكان يكون يمكن يوم ايان".split(" ").indexOf(e.word)>=0)return!0},e.normalizeHamzaAndAlef=function(){return e.word=e.word.replace("ؤ","ء"),e.word=e.word.replace("ئ","ء"),e.word=e.word.replace(/([\u0627])\1+/gi,"ا"),!1},e.removeEndTaa=function(){return!(e.word.length>2)||(e.word=e.word.replace(/[\u0627]$/,""),e.word=e.word.replace("ة",""),!1)},e.removeStartWaw=function(){return e.word.length>3&&"و"==e.word[0]&&"و"==e.word[1]&&(e.word=e.word.slice(1)),!1},e.removePre432=function(){var r=e.word;if(e.word.length>=7){var t=new RegExp("^("+e.pre.pre4.split(" ").join("|")+")");e.word=e.word.replace(t,"")}if(e.word==r&&e.word.length>=6){var c=new RegExp("^("+e.pre.pre3.split(" ").join("|")+")");e.word=e.word.replace(c,"")}if(e.word==r&&e.word.length>=5){var l=new RegExp("^("+e.pre.pre2.split(" ").join("|")+")");e.word=e.word.replace(l,"")}return r!=e.word&&(e.preRemoved=!0),!1},e.patternCheck=function(r){for(var t=0;t<r.length;t++){for(var c=!0,l=0;l<r[t].pt.length;l++){var n=r[t].pt[l].c.split(","),o=!1;if(n.forEach(function(c){e.word[r[t].pt[l].l]==c&&(o=!0)}),!o){c=!1;break}}if(1==c){if(r[t].mPt){for(var p=[],m=0;m<r[t].mPt.length;m++)null!=r[t].mPt[m].m?p[r[t].mPt[m].l]=e.word[r[t].mPt[m].m]:p[r[t].mPt[m].l]=r[t].mPt[m].c;e.word=p.join("")}e.result=!0;break}}},e.removePre1=function(){var r=e.word;if(0==e.preRemoved&&e.word.length>3){var t=new RegExp("^("+e.pre.pre1.split(" ").join("|")+")");e.word=e.word.replace(t,"")}return r!=e.word&&(e.preRemoved=!0),!1},e.removeSuf1=function(){var r=e.word;if(0==e.sufRemoved&&e.word.length>3){var t=new RegExp("("+e.suf.suf1.split(" ").join("|")+")$");e.word=e.word.replace(t,"")}return r!=e.word&&(e.sufRemoved=!0),!1},e.removeSuf432=function(){var r=e.word;if(e.word.length>=6){var t=new RegExp("("+e.suf.suf4.split(" ").join("|")+")$");e.word=e.word.replace(t,"")}if(e.word==r&&e.word.length>=5){var c=new RegExp("("+e.suf.suf3.split(" ").join("|")+")$");e.word=e.word.replace(c,"")}if(e.word==r&&e.word.length>=4){var l=new RegExp("("+e.suf.suf2.split(" ").join("|")+")$");e.word=e.word.replace(l,"")}return r!=e.word&&(e.sufRemoved=!0),!1},e.wordCheck=function(){for(var r=(e.word,[e.removeSuf432,e.removeSuf1,e.removePre1]),t=0,c=!1;e.word.length>=7&&!e.result&&t<r.length;)7!=e.word.length||c?(r[t](),t++,c=!1):(e.checkPattern73(),c=!0);var l=[e.checkPattern63,e.removeSuf432,e.removeSuf1,e.removePre1,e.checkPattern64];for(t=0;6==e.word.length&&!e.result&&t<l.length;)l[t](),t++;var n=[e.checkPattern53,e.removeSuf432,e.removeSuf1,e.removePre1,e.checkPattern54];for(t=0;5==e.word.length&&!e.result&&t<n.length;)n[t](),t++;var o=[e.checkPattern43,e.removeSuf1,e.removePre1,e.removeSuf432];for(t=0;4==e.word.length&&!e.result&&t<o.length;)o[t](),t++;return!0},e.checkPattern43=function(){e.patternCheck(e.patterns.pt43)},e.checkPattern53=function(){e.patternCheck(e.patterns.pt53)},e.checkPattern54=function(){e.patternCheck(e.patterns.pt54)},e.checkPattern63=function(){e.patternCheck(e.patterns.pt63)},e.checkPattern64=function(){e.patternCheck(e.patterns.pt64)},e.checkPattern73=function(){e.patternCheck(e.patterns.pt73)},function(r){return"function"==typeof r.update?r.update(function(r){return e.setCurrent(r),e.stem(),e.getCurrent()}):(e.setCurrent(r),e.stem(),e.getCurrent())}}(),e.Pipeline.registerFunction(e.ar.stemmer,"stemmer-ar"),e.ar.stopWordFilter=e.generateStopWordFilter("، اض امين اه اها اي ا اب اجل اجمع اخ اخذ اصبح اضحى اقبل اقل اكثر الا ام اما امامك امامك امسى اما ان انا انت انتم انتما انتن انت انشا انى او اوشك اولئك اولئكم اولاء اولالك اوه اي ايا اين اينما اي ان اي اف اذ اذا اذا اذما اذن الى اليكم اليكما اليكن اليك اليك الا اما ان انما اي اياك اياكم اياكما اياكن ايانا اياه اياها اياهم اياهما اياهن اياي ايه ان ا ابتدا اثر اجل احد اخرى اخلولق اذا اربعة ارتد استحال اطار اعادة اعلنت اف اكثر اكد الالاء الالى الا الاخيرة الان الاول الاولى التى التي الثاني الثانية الذاتي الذى الذي الذين السابق الف اللائي اللاتي اللتان اللتيا اللتين اللذان اللذين اللواتي الماضي المقبل الوقت الى اليوم اما امام امس ان انبرى انقلب انه انها او اول اي ايار ايام ايضا ب بات باسم بان بخ برس بسبب بس بشكل بضع بطان بعد بعض بك بكم بكما بكن بل بلى بما بماذا بمن بن بنا به بها بي بيد بين بس بله بئس تان تانك تبدل تجاه تحول تلقاء تلك تلكم تلكما تم تينك تين ته تي ثلاثة ثم ثم ثمة ثم جعل جلل جميع جير حار حاشا حاليا حاي حتى حرى حسب حم حوالى حول حيث حيثما حين حي حبذا حتى حذار خلا خلال دون دونك ذا ذات ذاك ذانك ذان ذلك ذلكم ذلكما ذلكن ذو ذوا ذواتا ذواتي ذيت ذينك ذين ذه ذي راح رجع رويدك ريث رب زيارة سبحان سرعان سنة سنوات سوف سوى ساء ساءما شبه شخصا شرع شتان صار صباح صفر صه صه ضد ضمن طاق طالما طفق طق ظل عاد عام عاما عامة عدا عدة عدد عدم عسى عشر عشرة علق على عليك عليه عليها عل عن عند عندما عوض عين عدس عما غدا غير  ف فان فلان فو فى في فيم فيما فيه فيها قال قام قبل قد قط قلما قوة كانما كاين كاي كاين كاد كان كانت كذا كذلك كرب كل كلا كلاهما كلتا كلم كليكما كليهما كلما كلا كم كما كي كيت كيف كيفما كان كخ لئن لا لات لاسيما لدن لدى لعمر لقاء لك لكم لكما لكن لكنما لكي لكيلا للامم لم لما لما لن لنا له لها لو لوكالة لولا لوما لي لست لست لستم لستما لستن لست لسن لعل لكن ليت ليس ليسا ليستا ليست ليسوا لسنا ما ماانفك مابرح مادام ماذا مازال مافتئ مايو متى مثل مذ مساء مع معاذ مقابل مكانكم مكانكما مكانكن مكانك مليار مليون مما ممن من منذ منها مه مهما من من نحن نحو نعم نفس نفسه نهاية نخ نعما نعم ها هاؤم هاك هاهنا هب هذا هذه هكذا هل هلم هلا هم هما هن هنا هناك هنالك هو هي هيا هيت هيا هؤلاء هاتان هاتين هاته هاتي هج هذا هذان هذين هذه هذي هيهات وا واحد واضاف واضافت واكد وان واها واوضح وراءك وفي وقال وقالت وقد وقف وكان وكانت ولا ولم ومن وهو وهي ويكان وي وشكان يكون يمكن يوم ايان".split(" ")),e.Pipeline.registerFunction(e.ar.stopWordFilter,"stopWordFilter-ar")}});
\ No newline at end of file
diff --git a/7.3/assets/javascripts/lunr/min/lunr.da.min.js b/7.3/assets/javascripts/lunr/min/lunr.da.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.de.min.js b/7.3/assets/javascripts/lunr/min/lunr.de.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.du.min.js b/7.3/assets/javascripts/lunr/min/lunr.du.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.es.min.js b/7.3/assets/javascripts/lunr/min/lunr.es.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.fi.min.js b/7.3/assets/javascripts/lunr/min/lunr.fi.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.fr.min.js b/7.3/assets/javascripts/lunr/min/lunr.fr.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.hi.min.js b/7.3/assets/javascripts/lunr/min/lunr.hi.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.hu.min.js b/7.3/assets/javascripts/lunr/min/lunr.hu.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.it.min.js b/7.3/assets/javascripts/lunr/min/lunr.it.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.ja.min.js b/7.3/assets/javascripts/lunr/min/lunr.ja.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.jp.min.js b/7.3/assets/javascripts/lunr/min/lunr.jp.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.ko.min.js b/7.3/assets/javascripts/lunr/min/lunr.ko.min.js
new file mode 100644
index 0000000000..749abfe02b
--- /dev/null
+++ b/7.3/assets/javascripts/lunr/min/lunr.ko.min.js
@@ -0,0 +1 @@
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r():r()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ko=function(){this.pipeline.reset(),this.pipeline.add(e.ko.trimmer,e.ko.stopWordFilter)},e.ko.wordCharacters="[A-Za-z가-힯a]",e.ko.trimmer=e.trimmerSupport.generateTrimmer(e.ko.wordCharacters),e.Pipeline.registerFunction(e.ko.trimmer,"trimmer-ko"),e.ko.stopWordFilter=e.generateStopWordFilter("아 휴 아이구 아이쿠 아이고 어 나 우리 저희 따라 의해 을 를 에 의 가 으로 로 에게 뿐이다 의거하여 근거하여 입각하여 기준으로 예하면 예를 들면 예를 들자면 저 소인 소생 저희 지말고 하지마 하지마라 다른 물론 또한 그리고 비길수 없다 해서는 안된다 뿐만 아니라 만이 아니다 만은 아니다 막론하고 관계없이 그치지 않다 그러나 그런데 하지만 든간에 논하지 않다 따지지 않다 설사 비록 더라도 아니면 만 못하다 하는 편이 낫다 불문하고 향하여 향해서 향하다 쪽으로 틈타 이용하여 타다 오르다 제외하고 이 외에 이 밖에 하여야 비로소 한다면 몰라도 외에도 이곳 여기 부터 기점으로 따라서 할 생각이다 하려고하다 이리하여 그리하여 그렇게 함으로써 하지만 일때 할때 앞에서 중에서 보는데서 으로써 로써 까지 해야한다 일것이다 반드시 할줄알다 할수있다 할수있어 임에 틀림없다 한다면 등 등등 제 겨우 단지 다만 할뿐 딩동 댕그 대해서 대하여 대하면 훨씬 얼마나 얼마만큼 얼마큼 남짓 여 얼마간 약간 다소 좀 조금 다수 몇 얼마 지만 하물며 또한 그러나 그렇지만 하지만 이외에도 대해 말하자면 뿐이다 다음에 반대로 반대로 말하자면 이와 반대로 바꾸어서 말하면 바꾸어서 한다면 만약 그렇지않으면 까악 툭 딱 삐걱거리다 보드득 비걱거리다 꽈당 응당 해야한다 에 가서 각 각각 여러분 각종 각자 제각기 하도록하다 와 과 그러므로 그래서 고로 한 까닭에 하기 때문에 거니와 이지만 대하여 관하여 관한 과연 실로 아니나다를가 생각한대로 진짜로 한적이있다 하곤하였다 하 하하 허허 아하 거바 와 오 왜 어째서 무엇때문에 어찌 하겠는가 무슨 어디 어느곳 더군다나 하물며 더욱이는 어느때 언제 야 이봐 어이 여보시오 흐흐 흥 휴 헉헉 헐떡헐떡 영차 여차 어기여차 끙끙 아야 앗 아야 콸콸 졸졸 좍좍 뚝뚝 주룩주룩 솨 우르르 그래도 또 그리고 바꾸어말하면 바꾸어말하자면 혹은 혹시 답다 및 그에 따르는 때가 되어 즉 지든지 설령 가령 하더라도 할지라도 일지라도 지든지 몇 거의 하마터면 인젠 이젠 된바에야 된이상 만큼\t어찌됏든 그위에 게다가 점에서 보아 비추어 보아 고려하면 하게될것이다 일것이다 비교적 좀 보다더 비하면 시키다 하게하다 할만하다 의해서 연이서 이어서 잇따라 뒤따라 뒤이어 결국 의지하여 기대여 통하여 자마자 더욱더 불구하고 얼마든지 마음대로 주저하지 않고 곧 즉시 바로 당장 하자마자 밖에 안된다 하면된다 그래 그렇지 요컨대 다시 말하자면 바꿔 말하면 즉 구체적으로 말하자면 시작하여 시초에 이상 허 헉 허걱 바와같이 해도좋다 해도된다 게다가 더구나 하물며 와르르 팍 퍽 펄렁 동안 이래 하고있었다 이었다 에서 로부터 까지 예하면 했어요 해요 함께 같이 더불어 마저 마저도 양자 모두 습니다 가까스로 하려고하다 즈음하여 다른 다른 방면으로 해봐요 습니까 했어요 말할것도 없고 무릎쓰고 개의치않고 하는것만 못하다 하는것이 낫다 매 매번 들 모 어느것 어느 로써 갖고말하자면 어디 어느쪽 어느것 어느해 어느 년도 라 해도 언젠가 어떤것 어느것 저기 저쪽 저것 그때 그럼 그러면 요만한걸 그래 그때 저것만큼 그저 이르기까지 할 줄 안다 할 힘이 있다 너 너희 당신 어찌 설마 차라리 할지언정 할지라도 할망정 할지언정 구토하다 게우다 토하다 메쓰겁다 옆사람 퉤 쳇 의거하여 근거하여 의해 따라 힘입어 그 다음 버금 두번째로 기타 첫번째로 나머지는 그중에서 견지에서 형식으로 쓰여 입장에서 위해서 단지 의해되다 하도록시키다 뿐만아니라 반대로 전후 전자 앞의것 잠시 잠깐 하면서 그렇지만 다음에 그러한즉 그런즉 남들 아무거나 어찌하든지 같다 비슷하다 예컨대 이럴정도로 어떻게 만약 만일 위에서 서술한바와같이 인 듯하다 하지 않는다면 만약에 무엇 무슨 어느 어떤 아래윗 조차 한데 그럼에도 불구하고 여전히 심지어 까지도 조차도 하지 않도록 않기 위하여 때 시각 무렵 시간 동안 어때 어떠한 하여금 네 예 우선 누구 누가 알겠는가 아무도 줄은모른다 줄은 몰랏다 하는 김에 겸사겸사 하는바 그런 까닭에 한 이유는 그러니 그러니까 때문에 그 너희 그들 너희들 타인 것 것들 너 위하여 공동으로 동시에 하기 위하여 어찌하여 무엇때문에 붕붕 윙윙 나 우리 엉엉 휘익 윙윙 오호 아하 어쨋든 만 못하다\t하기보다는 차라리 하는 편이 낫다 흐흐 놀라다 상대적으로 말하자면 마치 아니라면 쉿 그렇지 않으면 그렇지 않다면 안 그러면 아니었다면 하든지 아니면 이라면 좋아 알았어 하는것도 그만이다 어쩔수 없다 하나 일 일반적으로 일단 한켠으로는 오자마자 이렇게되면 이와같다면 전부 한마디 한항목 근거로 하기에 아울러 하지 않도록 않기 위해서 이르기까지 이 되다 로 인하여 까닭으로 이유만으로 이로 인하여 그래서 이 때문에 그러므로 그런 까닭에 알 수 있다 결론을 낼 수 있다 으로 인하여 있다 어떤것 관계가 있다 관련이 있다 연관되다 어떤것들 에 대해 이리하여 그리하여 여부 하기보다는 하느니 하면 할수록 운운 이러이러하다 하구나 하도다 다시말하면 다음으로 에 있다 에 달려 있다 우리 우리들 오히려 하기는한데 어떻게 어떻해 어찌됏어 어때 어째서 본대로 자 이 이쪽 여기 이것 이번 이렇게말하자면 이런 이러한 이와 같은 요만큼 요만한 것 얼마 안 되는 것 이만큼 이 정도의 이렇게 많은 것 이와 같다 이때 이렇구나 것과 같이 끼익 삐걱 따위 와 같은 사람들 부류의 사람들 왜냐하면 중의하나 오직 오로지 에 한하다 하기만 하면 도착하다 까지 미치다 도달하다 정도에 이르다 할 지경이다 결과에 이르다 관해서는 여러분 하고 있다 한 후 혼자 자기 자기집 자신 우에 종합한것과같이 총적으로 보면 총적으로 말하면 총적으로 대로 하다 으로서 참 그만이다 할 따름이다 쿵 탕탕 쾅쾅 둥둥 봐 봐라 아이야 아니 와아 응 아이 참나 년 월 일 령 영 일 이 삼 사 오 육 륙 칠 팔 구 이천육 이천칠 이천팔 이천구 하나 둘 셋 넷 다섯 여섯 일곱 여덟 아홉 령 영".split(" ")),e.Pipeline.registerFunction(e.ko.stopWordFilter,"stopWordFilter-ko"),e.ko.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}(),e.Pipeline.registerFunction(e.ko.stemmer,"stemmer-ko")}});
\ No newline at end of file
diff --git a/7.3/assets/javascripts/lunr/min/lunr.multi.min.js b/7.3/assets/javascripts/lunr/min/lunr.multi.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.nl.min.js b/7.3/assets/javascripts/lunr/min/lunr.nl.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.no.min.js b/7.3/assets/javascripts/lunr/min/lunr.no.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.pt.min.js b/7.3/assets/javascripts/lunr/min/lunr.pt.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.ro.min.js b/7.3/assets/javascripts/lunr/min/lunr.ro.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.ru.min.js b/7.3/assets/javascripts/lunr/min/lunr.ru.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.stemmer.support.min.js b/7.3/assets/javascripts/lunr/min/lunr.stemmer.support.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.sv.min.js b/7.3/assets/javascripts/lunr/min/lunr.sv.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.ta.min.js b/7.3/assets/javascripts/lunr/min/lunr.ta.min.js
new file mode 100644
index 0000000000..a644bed228
--- /dev/null
+++ b/7.3/assets/javascripts/lunr/min/lunr.ta.min.js
@@ -0,0 +1 @@
+!function(e,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():t()(e.lunr)}(this,function(){return function(e){if(void 0===e)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===e.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");e.ta=function(){this.pipeline.reset(),this.pipeline.add(e.ta.trimmer,e.ta.stopWordFilter,e.ta.stemmer),this.searchPipeline&&(this.searchPipeline.reset(),this.searchPipeline.add(e.ta.stemmer))},e.ta.wordCharacters="஀-உஊ-ஏஐ-ஙச-ட஠-னப-யர-ஹ஺-ிீ-௉ொ-௏ௐ-௙௚-௟௠-௩௪-௯௰-௹௺-௿a-zA-Zａ-ｚＡ-Ｚ0-9０-９",e.ta.trimmer=e.trimmerSupport.generateTrimmer(e.ta.wordCharacters),e.Pipeline.registerFunction(e.ta.trimmer,"trimmer-ta"),e.ta.stopWordFilter=e.generateStopWordFilter("அங்கு அங்கே அது அதை அந்த அவர் அவர்கள் அவள் அவன் அவை ஆக ஆகவே ஆகையால் ஆதலால் ஆதலினால் ஆனாலும் ஆனால் இங்கு இங்கே இது இதை இந்த இப்படி இவர் இவர்கள் இவள் இவன் இவை இவ்வளவு உனக்கு உனது உன் உன்னால் எங்கு எங்கே எது எதை எந்த எப்படி எவர் எவர்கள் எவள் எவன் எவை எவ்வளவு எனக்கு எனது எனவே என் என்ன என்னால் ஏது ஏன் தனது தன்னால் தானே தான் நாங்கள் நாம் நான் நீ நீங்கள்".split(" ")),e.ta.stemmer=function(){return function(e){return"function"==typeof e.update?e.update(function(e){return e}):e}}();var t=e.wordcut;t.init(),e.ta.tokenizer=function(r){if(!arguments.length||null==r||void 0==r)return[];if(Array.isArray(r))return r.map(function(t){return isLunr2?new e.Token(t.toLowerCase()):t.toLowerCase()});var i=r.toString().toLowerCase().replace(/^\s+/,"");return t.cut(i).split("|")},e.Pipeline.registerFunction(e.ta.stemmer,"stemmer-ta"),e.Pipeline.registerFunction(e.ta.stopWordFilter,"stopWordFilter-ta")}});
\ No newline at end of file
diff --git a/7.3/assets/javascripts/lunr/min/lunr.th.min.js b/7.3/assets/javascripts/lunr/min/lunr.th.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.tr.min.js b/7.3/assets/javascripts/lunr/min/lunr.tr.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.vi.min.js b/7.3/assets/javascripts/lunr/min/lunr.vi.min.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/min/lunr.zh.min.js b/7.3/assets/javascripts/lunr/min/lunr.zh.min.js
old mode 100755
new mode 100644
index 7727bbe24d..9838ef96da
--- a/7.3/assets/javascripts/lunr/min/lunr.zh.min.js
+++ b/7.3/assets/javascripts/lunr/min/lunr.zh.min.js
@@ -1 +1 @@
-!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r(require("nodejieba")):r()(e.lunr)}(this,function(e){return function(r,t){if(void 0===r)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===r.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");var i="2"==r.version[0];r.zh=function(){this.pipeline.reset(),this.pipeline.add(r.zh.trimmer,r.zh.stopWordFilter,r.zh.stemmer),i?this.tokenizer=r.zh.tokenizer:(r.tokenizer&&(r.tokenizer=r.zh.tokenizer),this.tokenizerFn&&(this.tokenizerFn=r.zh.tokenizer))},r.zh.tokenizer=function(n){if(!arguments.length||null==n||void 0==n)return[];if(Array.isArray(n))return n.map(function(e){return i?new r.Token(e.toLowerCase()):e.toLowerCase()});t&&e.load(t);var o=n.toString().trim().toLowerCase(),s=[];e.cut(o,!0).forEach(function(e){s=s.concat(e.split(" "))}),s=s.filter(function(e){return!!e});var u=0;return s.map(function(e,t){if(i){var n=o.indexOf(e,u),s={};return s.position=[n,e.length],s.index=t,u=n,new r.Token(e,s)}return e})},r.zh.wordCharacters="\\w一-龥",r.zh.trimmer=r.trimmerSupport.generateTrimmer(r.zh.wordCharacters),r.Pipeline.registerFunction(r.zh.trimmer,"trimmer-zh"),r.zh.stemmer=function(){return function(e){return e}}(),r.Pipeline.registerFunction(r.zh.stemmer,"stemmer-zh"),r.zh.stopWordFilter=r.generateStopWordFilter("的 一 不 在 人 有 是 为 以 于 上 他 而 后 之 来 及 了 因 下 可 到 由 这 与 也 此 但 并 个 其 已 无 小 我 们 起 最 再 今 去 好 只 又 或 很 亦 某 把 那 你 乃 它 吧 被 比 别 趁 当 从 到 得 打 凡 儿 尔 该 各 给 跟 和 何 还 即 几 既 看 据 距 靠 啦 了 另 么 每 们 嘛 拿 哪 那 您 凭 且 却 让 仍 啥 如 若 使 谁 虽 随 同 所 她 哇 嗡 往 哪 些 向 沿 哟 用 于 咱 则 怎 曾 至 致 着 诸 自".split(" ")),r.Pipeline.registerFunction(r.zh.stopWordFilter,"stopWordFilter-zh")}});
\ No newline at end of file
+!function(e,r){"function"==typeof define&&define.amd?define(r):"object"==typeof exports?module.exports=r(require("@node-rs/jieba")):r()(e.lunr)}(this,function(e){return function(r,t){if(void 0===r)throw new Error("Lunr is not present. Please include / require Lunr before this script.");if(void 0===r.stemmerSupport)throw new Error("Lunr stemmer support is not present. Please include / require Lunr stemmer support before this script.");var i="2"==r.version[0];r.zh=function(){this.pipeline.reset(),this.pipeline.add(r.zh.trimmer,r.zh.stopWordFilter,r.zh.stemmer),i?this.tokenizer=r.zh.tokenizer:(r.tokenizer&&(r.tokenizer=r.zh.tokenizer),this.tokenizerFn&&(this.tokenizerFn=r.zh.tokenizer))},r.zh.tokenizer=function(n){if(!arguments.length||null==n||void 0==n)return[];if(Array.isArray(n))return n.map(function(e){return i?new r.Token(e.toLowerCase()):e.toLowerCase()});t&&e.load(t);var o=n.toString().trim().toLowerCase(),s=[];e.cut(o,!0).forEach(function(e){s=s.concat(e.split(" "))}),s=s.filter(function(e){return!!e});var u=0;return s.map(function(e,t){if(i){var n=o.indexOf(e,u),s={};return s.position=[n,e.length],s.index=t,u=n,new r.Token(e,s)}return e})},r.zh.wordCharacters="\\w一-龥",r.zh.trimmer=r.trimmerSupport.generateTrimmer(r.zh.wordCharacters),r.Pipeline.registerFunction(r.zh.trimmer,"trimmer-zh"),r.zh.stemmer=function(){return function(e){return e}}(),r.Pipeline.registerFunction(r.zh.stemmer,"stemmer-zh"),r.zh.stopWordFilter=r.generateStopWordFilter("的 一 不 在 人 有 是 为 以 于 上 他 而 后 之 来 及 了 因 下 可 到 由 这 与 也 此 但 并 个 其 已 无 小 我 们 起 最 再 今 去 好 只 又 或 很 亦 某 把 那 你 乃 它 吧 被 比 别 趁 当 从 到 得 打 凡 儿 尔 该 各 给 跟 和 何 还 即 几 既 看 据 距 靠 啦 了 另 么 每 们 嘛 拿 哪 那 您 凭 且 却 让 仍 啥 如 若 使 谁 虽 随 同 所 她 哇 嗡 往 哪 些 向 沿 哟 用 于 咱 则 怎 曾 至 致 着 诸 自".split(" ")),r.Pipeline.registerFunction(r.zh.stopWordFilter,"stopWordFilter-zh")}});
\ No newline at end of file
diff --git a/7.3/assets/javascripts/lunr/tinyseg.js b/7.3/assets/javascripts/lunr/tinyseg.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/lunr/wordcut.js b/7.3/assets/javascripts/lunr/wordcut.js
old mode 100755
new mode 100644
diff --git a/7.3/assets/javascripts/workers/search.2a1c317c.min.js b/7.3/assets/javascripts/workers/search.16e2a7d4.min.js
old mode 100755
new mode 100644
similarity index 90%
rename from 7.3/assets/javascripts/workers/search.2a1c317c.min.js
rename to 7.3/assets/javascripts/workers/search.16e2a7d4.min.js
index 59bf8384f5..e0dc159e89
--- a/7.3/assets/javascripts/workers/search.2a1c317c.min.js
+++ b/7.3/assets/javascripts/workers/search.16e2a7d4.min.js
@@ -1,4 +1,4 @@
-(()=>{var ge=Object.create;var W=Object.defineProperty,ye=Object.defineProperties,me=Object.getOwnPropertyDescriptor,ve=Object.getOwnPropertyDescriptors,xe=Object.getOwnPropertyNames,G=Object.getOwnPropertySymbols,Se=Object.getPrototypeOf,X=Object.prototype.hasOwnProperty,Qe=Object.prototype.propertyIsEnumerable;var J=(t,e,r)=>e in t?W(t,e,{enumerable:!0,configurable:!0,writable:!0,value:r}):t[e]=r,M=(t,e)=>{for(var r in e||(e={}))X.call(e,r)&&J(t,r,e[r]);if(G)for(var r of G(e))Qe.call(e,r)&&J(t,r,e[r]);return t},Z=(t,e)=>ye(t,ve(e));var K=(t,e)=>()=>(e||t((e={exports:{}}).exports,e),e.exports);var be=(t,e,r,n)=>{if(e&&typeof e=="object"||typeof e=="function")for(let i of xe(e))!X.call(t,i)&&i!==r&&W(t,i,{get:()=>e[i],enumerable:!(n=me(e,i))||n.enumerable});return t};var H=(t,e,r)=>(r=t!=null?ge(Se(t)):{},be(e||!t||!t.__esModule?W(r,"default",{value:t,enumerable:!0}):r,t));var z=(t,e,r)=>new Promise((n,i)=>{var s=u=>{try{a(r.next(u))}catch(c){i(c)}},o=u=>{try{a(r.throw(u))}catch(c){i(c)}},a=u=>u.done?n(u.value):Promise.resolve(u.value).then(s,o);a((r=r.apply(t,e)).next())});var re=K((ee,te)=>{/**
+"use strict";(()=>{var ge=Object.create;var W=Object.defineProperty,ye=Object.defineProperties,me=Object.getOwnPropertyDescriptor,ve=Object.getOwnPropertyDescriptors,xe=Object.getOwnPropertyNames,G=Object.getOwnPropertySymbols,Se=Object.getPrototypeOf,X=Object.prototype.hasOwnProperty,Qe=Object.prototype.propertyIsEnumerable;var J=(t,e,r)=>e in t?W(t,e,{enumerable:!0,configurable:!0,writable:!0,value:r}):t[e]=r,M=(t,e)=>{for(var r in e||(e={}))X.call(e,r)&&J(t,r,e[r]);if(G)for(var r of G(e))Qe.call(e,r)&&J(t,r,e[r]);return t},Z=(t,e)=>ye(t,ve(e));var K=(t,e)=>()=>(e||t((e={exports:{}}).exports,e),e.exports);var be=(t,e,r,n)=>{if(e&&typeof e=="object"||typeof e=="function")for(let i of xe(e))!X.call(t,i)&&i!==r&&W(t,i,{get:()=>e[i],enumerable:!(n=me(e,i))||n.enumerable});return t};var H=(t,e,r)=>(r=t!=null?ge(Se(t)):{},be(e||!t||!t.__esModule?W(r,"default",{value:t,enumerable:!0}):r,t));var z=(t,e,r)=>new Promise((n,i)=>{var s=u=>{try{a(r.next(u))}catch(c){i(c)}},o=u=>{try{a(r.throw(u))}catch(c){i(c)}},a=u=>u.done?n(u.value):Promise.resolve(u.value).then(s,o);a((r=r.apply(t,e)).next())});var re=K((ee,te)=>{/**
  * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9
  * Copyright (C) 2020 Oliver Nightingale
  * @license MIT
@@ -43,6 +43,6 @@
  * Copyright(c) 2015 Andreas Lubbe
  * Copyright(c) 2015 Tiancheng "Timothy" Gu
  * MIT Licensed
- */var Le=/["'&<>]/;ne.exports=we;function we(t){var e=""+t,r=Le.exec(e);if(!r)return e;var n,i="",s=0,o=0;for(s=r.index;s<e.length;s++){switch(e.charCodeAt(s)){case 34:n="&quot;";break;case 38:n="&amp;";break;case 39:n="&#39;";break;case 60:n="&lt;";break;case 62:n="&gt;";break;default:continue}o!==s&&(i+=e.substring(o,s)),o=s+1,i+=n}return o!==s?i+e.substring(o,s):i}});var le=H(re());Object.entries||(Object.entries=function(t){let e=[];for(let r of Object.keys(t))e.push([r,t[r]]);return e});Object.values||(Object.values=function(t){let e=[];for(let r of Object.keys(t))e.push(t[r]);return e});typeof Element!="undefined"&&(Element.prototype.scrollTo||(Element.prototype.scrollTo=function(t,e){typeof t=="object"?(this.scrollLeft=t.left,this.scrollTop=t.top):(this.scrollLeft=t,this.scrollTop=e)}),Element.prototype.replaceWith||(Element.prototype.replaceWith=function(...t){let e=this.parentNode;if(e){t.length===0&&e.removeChild(this);for(let r=t.length-1;r>=0;r--){let n=t[r];typeof n!="object"?n=document.createTextNode(n):n.parentNode&&n.parentNode.removeChild(n),r?e.insertBefore(this.previousSibling,n):e.replaceChild(n,this)}}}));var ie=H(q());function se(t){let e=new Map,r=new Set;for(let n of t){let[i,s]=n.location.split("#"),o=n.location,a=n.title,u=n.tags,c=(0,ie.default)(n.text).replace(/\s+(?=[,.:;!?])/g,"").replace(/\s+/g," ");if(s){let h=e.get(i);r.has(h)?e.set(o,{location:o,title:a,text:c,parent:h}):(h.title=n.title,h.text=c,r.add(h))}else e.set(o,M({location:o,title:a,text:c},u&&{tags:u}))}return e}var oe=H(q());function ae(t,e){let r=new RegExp(t.separator,"img"),n=(i,s,o)=>`${s}<mark data-md-highlight>${o}</mark>`;return i=>{i=i.replace(/[\s*+\-:~^]+/g," ").trim();let s=new RegExp(`(^|${t.separator})(${i.replace(/[|\\{}()[\]^$+*?.-]/g,"\\$&").replace(r,"|")})`,"img");return o=>(e?(0,oe.default)(o):o).replace(s,n).replace(/<\/mark>(\s+)<mark[^>]*>/img,"$1")}}function ue(t){let e=new lunr.Query(["title","text"]);return new lunr.QueryParser(t,e).parse(),e.clauses}function ce(t,e){var i;let r=new Set(t),n={};for(let s=0;s<e.length;s++)for(let o of r)e[s].startsWith(o.term)&&(n[o.term]=!0,r.delete(o));for(let s of r)(i=lunr.stopWordFilter)!=null&&i.call(lunr,s.term)&&(n[s.term]=!1);return n}function Ee(t,e){let[r,n]=[new Set(t),new Set(e)];return[...new Set([...r].filter(i=>!n.has(i)))]}var U=class{constructor({config:e,docs:r,options:n}){this.options=n,this.documents=se(r),this.highlight=ae(e,!1),lunr.tokenizer.separator=new RegExp(e.separator),this.index=lunr(function(){e.lang.length===1&&e.lang[0]!=="en"?this.use(lunr[e.lang[0]]):e.lang.length>1&&this.use(lunr.multiLanguage(...e.lang));let i=Ee(["trimmer","stopWordFilter","stemmer"],n.pipeline);for(let s of e.lang.map(o=>o==="en"?lunr:lunr[o]))for(let o of i)this.pipeline.remove(s[o]),this.searchPipeline.remove(s[o]);this.ref("location"),this.field("title",{boost:1e3}),this.field("text"),this.field("tags",{boost:1e6});for(let s of r)this.add(s)})}search(e){if(e)try{let r=this.highlight(e),n=ue(e).filter(o=>o.presence!==lunr.Query.presence.PROHIBITED),i=this.index.search(`${e}*`).reduce((o,{ref:a,score:u,matchData:c})=>{let h=this.documents.get(a);if(typeof h!="undefined"){let{location:y,title:g,text:b,tags:m,parent:Q}=h,p=ce(n,Object.keys(c.metadata)),d=+!Q+ +Object.values(p).every(w=>w);o.push(Z(M({location:y,title:r(g),text:r(b)},m&&{tags:m.map(r)}),{score:u*(1+d),terms:p}))}return o},[]).sort((o,a)=>a.score-o.score).reduce((o,a)=>{let u=this.documents.get(a.location);if(typeof u!="undefined"){let c="parent"in u?u.parent.location:u.location;o.set(c,[...o.get(c)||[],a])}return o},new Map),s;if(this.options.suggestions){let o=this.index.query(a=>{for(let u of n)a.term(u.term,{fields:["title"],presence:lunr.Query.presence.REQUIRED,wildcard:lunr.Query.wildcard.TRAILING})});s=o.length?Object.keys(o[0].matchData.metadata):[]}return M({items:[...i.values()]},typeof s!="undefined"&&{suggestions:s})}catch(r){console.warn(`Invalid query: ${e} \u2013 see https://bit.ly/2s3ChXG`)}return{items:[]}}};var Y;function ke(t){return z(this,null,function*(){let e="../lunr";if(typeof parent!="undefined"&&"IFrameWorker"in parent){let n=document.querySelector("script[src]"),[i]=n.src.split("/worker");e=e.replace("..",i)}let r=[];for(let n of t.lang){switch(n){case"ja":r.push(`${e}/tinyseg.js`);break;case"hi":case"th":r.push(`${e}/wordcut.js`);break}n!=="en"&&r.push(`${e}/min/lunr.${n}.min.js`)}t.lang.length>1&&r.push(`${e}/min/lunr.multi.min.js`),r.length&&(yield importScripts(`${e}/min/lunr.stemmer.support.min.js`,...r))})}function Te(t){return z(this,null,function*(){switch(t.type){case 0:return yield ke(t.data.config),Y=new U(t.data),{type:1};case 2:return{type:3,data:Y?Y.search(t.data):{items:[]}};default:throw new TypeError("Invalid message type")}})}self.lunr=le.default;addEventListener("message",t=>z(void 0,null,function*(){postMessage(yield Te(t.data))}));})();
-//# sourceMappingURL=search.2a1c317c.min.js.map
+ */var Le=/["'&<>]/;ne.exports=we;function we(t){var e=""+t,r=Le.exec(e);if(!r)return e;var n,i="",s=0,o=0;for(s=r.index;s<e.length;s++){switch(e.charCodeAt(s)){case 34:n="&quot;";break;case 38:n="&amp;";break;case 39:n="&#39;";break;case 60:n="&lt;";break;case 62:n="&gt;";break;default:continue}o!==s&&(i+=e.substring(o,s)),o=s+1,i+=n}return o!==s?i+e.substring(o,s):i}});var le=H(re());Object.entries||(Object.entries=function(t){let e=[];for(let r of Object.keys(t))e.push([r,t[r]]);return e});Object.values||(Object.values=function(t){let e=[];for(let r of Object.keys(t))e.push(t[r]);return e});typeof Element!="undefined"&&(Element.prototype.scrollTo||(Element.prototype.scrollTo=function(t,e){typeof t=="object"?(this.scrollLeft=t.left,this.scrollTop=t.top):(this.scrollLeft=t,this.scrollTop=e)}),Element.prototype.replaceWith||(Element.prototype.replaceWith=function(...t){let e=this.parentNode;if(e){t.length===0&&e.removeChild(this);for(let r=t.length-1;r>=0;r--){let n=t[r];typeof n=="string"?n=document.createTextNode(n):n.parentNode&&n.parentNode.removeChild(n),r?e.insertBefore(this.previousSibling,n):e.replaceChild(n,this)}}}));var ie=H(q());function se(t){let e=new Map,r=new Set;for(let n of t){let[i,s]=n.location.split("#"),o=n.location,a=n.title,u=n.tags,c=(0,ie.default)(n.text).replace(/\s+(?=[,.:;!?])/g,"").replace(/\s+/g," ");if(s){let h=e.get(i);r.has(h)?e.set(o,{location:o,title:a,text:c,parent:h}):(h.title=n.title,h.text=c,r.add(h))}else e.set(o,M({location:o,title:a,text:c},u&&{tags:u}))}return e}var oe=H(q());function ae(t,e){let r=new RegExp(t.separator,"img"),n=(i,s,o)=>`${s}<mark data-md-highlight>${o}</mark>`;return i=>{i=i.replace(/[\s*+\-:~^]+/g," ").trim();let s=new RegExp(`(^|${t.separator})(${i.replace(/[|\\{}()[\]^$+*?.-]/g,"\\$&").replace(r,"|")})`,"img");return o=>(e?(0,oe.default)(o):o).replace(s,n).replace(/<\/mark>(\s+)<mark[^>]*>/img,"$1")}}function ue(t){let e=new lunr.Query(["title","text"]);return new lunr.QueryParser(t,e).parse(),e.clauses}function ce(t,e){var i;let r=new Set(t),n={};for(let s=0;s<e.length;s++)for(let o of r)e[s].startsWith(o.term)&&(n[o.term]=!0,r.delete(o));for(let s of r)(i=lunr.stopWordFilter)!=null&&i.call(lunr,s.term)&&(n[s.term]=!1);return n}function Ee(t,e){let[r,n]=[new Set(t),new Set(e)];return[...new Set([...r].filter(i=>!n.has(i)))]}var U=class{constructor({config:e,docs:r,options:n}){this.options=n,this.documents=se(r),this.highlight=ae(e,!1),lunr.tokenizer.separator=new RegExp(e.separator),this.index=lunr(function(){e.lang.length===1&&e.lang[0]!=="en"?this.use(lunr[e.lang[0]]):e.lang.length>1&&this.use(lunr.multiLanguage(...e.lang));let i=Ee(["trimmer","stopWordFilter","stemmer"],n.pipeline);for(let s of e.lang.map(o=>o==="en"?lunr:lunr[o]))for(let o of i)this.pipeline.remove(s[o]),this.searchPipeline.remove(s[o]);this.ref("location"),this.field("title",{boost:1e3}),this.field("text"),this.field("tags",{boost:1e6,extractor:s=>{let{tags:o=[]}=s;return o.reduce((a,u)=>[...a,...lunr.tokenizer(u)],[])}});for(let s of r)this.add(s,{boost:s.boost})})}search(e){if(e)try{let r=this.highlight(e),n=ue(e).filter(o=>o.presence!==lunr.Query.presence.PROHIBITED),i=this.index.search(`${e}*`).reduce((o,{ref:a,score:u,matchData:c})=>{let h=this.documents.get(a);if(typeof h!="undefined"){let{location:y,title:g,text:b,tags:m,parent:Q}=h,p=ce(n,Object.keys(c.metadata)),d=+!Q+ +Object.values(p).every(w=>w);o.push(Z(M({location:y,title:r(g),text:r(b)},m&&{tags:m.map(r)}),{score:u*(1+d),terms:p}))}return o},[]).sort((o,a)=>a.score-o.score).reduce((o,a)=>{let u=this.documents.get(a.location);if(typeof u!="undefined"){let c="parent"in u?u.parent.location:u.location;o.set(c,[...o.get(c)||[],a])}return o},new Map),s;if(this.options.suggestions){let o=this.index.query(a=>{for(let u of n)a.term(u.term,{fields:["title"],presence:lunr.Query.presence.REQUIRED,wildcard:lunr.Query.wildcard.TRAILING})});s=o.length?Object.keys(o[0].matchData.metadata):[]}return M({items:[...i.values()]},typeof s!="undefined"&&{suggestions:s})}catch(r){console.warn(`Invalid query: ${e} \u2013 see https://bit.ly/2s3ChXG`)}return{items:[]}}};var Y;function ke(t){return z(this,null,function*(){let e="../lunr";if(typeof parent!="undefined"&&"IFrameWorker"in parent){let n=document.querySelector("script[src]"),[i]=n.src.split("/worker");e=e.replace("..",i)}let r=[];for(let n of t.lang){switch(n){case"ja":r.push(`${e}/tinyseg.js`);break;case"hi":case"th":r.push(`${e}/wordcut.js`);break}n!=="en"&&r.push(`${e}/min/lunr.${n}.min.js`)}t.lang.length>1&&r.push(`${e}/min/lunr.multi.min.js`),r.length&&(yield importScripts(`${e}/min/lunr.stemmer.support.min.js`,...r))})}function Te(t){return z(this,null,function*(){switch(t.type){case 0:return yield ke(t.data.config),Y=new U(t.data),{type:1};case 2:return{type:3,data:Y?Y.search(t.data):{items:[]}};default:throw new TypeError("Invalid message type")}})}self.lunr=le.default;addEventListener("message",t=>z(void 0,null,function*(){postMessage(yield Te(t.data))}));})();
+//# sourceMappingURL=search.16e2a7d4.min.js.map
 
diff --git a/7.3/assets/javascripts/workers/search.2a1c317c.min.js.map b/7.3/assets/javascripts/workers/search.16e2a7d4.min.js.map
old mode 100755
new mode 100644
similarity index 69%
rename from 7.3/assets/javascripts/workers/search.2a1c317c.min.js.map
rename to 7.3/assets/javascripts/workers/search.16e2a7d4.min.js.map
index 06d43304ec..fa01f37427
--- a/7.3/assets/javascripts/workers/search.2a1c317c.min.js.map
+++ b/7.3/assets/javascripts/workers/search.16e2a7d4.min.js.map
@@ -2,7 +2,7 @@
   "version": 3,
   "sources": ["node_modules/lunr/lunr.js", "node_modules/escape-html/index.js", "src/assets/javascripts/integrations/search/worker/main/index.ts", "src/assets/javascripts/polyfills/index.ts", "src/assets/javascripts/integrations/search/document/index.ts", "src/assets/javascripts/integrations/search/highlighter/index.ts", "src/assets/javascripts/integrations/search/query/_/index.ts", "src/assets/javascripts/integrations/search/_/index.ts"],
   "sourceRoot": "../../../..",
-  "sourcesContent": ["/**\n * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9\n * Copyright (C) 2020 Oliver Nightingale\n * @license MIT\n */\n\n;(function(){\n\n/**\n * A convenience function for configuring and constructing\n * a new lunr Index.\n *\n * A lunr.Builder instance is created and the pipeline setup\n * with a trimmer, stop word filter and stemmer.\n *\n * This builder object is yielded to the configuration function\n * that is passed as a parameter, allowing the list of fields\n * and other builder parameters to be customised.\n *\n * All documents _must_ be added within the passed config function.\n *\n * @example\n * var idx = lunr(function () {\n *   this.field('title')\n *   this.field('body')\n *   this.ref('id')\n *\n *   documents.forEach(function (doc) {\n *     this.add(doc)\n *   }, this)\n * })\n *\n * @see {@link lunr.Builder}\n * @see {@link lunr.Pipeline}\n * @see {@link lunr.trimmer}\n * @see {@link lunr.stopWordFilter}\n * @see {@link lunr.stemmer}\n * @namespace {function} lunr\n */\nvar lunr = function (config) {\n  var builder = new lunr.Builder\n\n  builder.pipeline.add(\n    lunr.trimmer,\n    lunr.stopWordFilter,\n    lunr.stemmer\n  )\n\n  builder.searchPipeline.add(\n    lunr.stemmer\n  )\n\n  config.call(builder, builder)\n  return builder.build()\n}\n\nlunr.version = \"2.3.9\"\n/*!\n * lunr.utils\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A namespace containing utils for the rest of the lunr library\n * @namespace lunr.utils\n */\nlunr.utils = {}\n\n/**\n * Print a warning message to the console.\n *\n * @param {String} message The message to be printed.\n * @memberOf lunr.utils\n * @function\n */\nlunr.utils.warn = (function (global) {\n  /* eslint-disable no-console */\n  return function (message) {\n    if (global.console && console.warn) {\n      console.warn(message)\n    }\n  }\n  /* eslint-enable no-console */\n})(this)\n\n/**\n * Convert an object to a string.\n *\n * In the case of `null` and `undefined` the function returns\n * the empty string, in all other cases the result of calling\n * `toString` on the passed object is returned.\n *\n * @param {Any} obj The object to convert to a string.\n * @return {String} string representation of the passed object.\n * @memberOf lunr.utils\n */\nlunr.utils.asString = function (obj) {\n  if (obj === void 0 || obj === null) {\n    return \"\"\n  } else {\n    return obj.toString()\n  }\n}\n\n/**\n * Clones an object.\n *\n * Will create a copy of an existing object such that any mutations\n * on the copy cannot affect the original.\n *\n * Only shallow objects are supported, passing a nested object to this\n * function will cause a TypeError.\n *\n * Objects with primitives, and arrays of primitives are supported.\n *\n * @param {Object} obj The object to clone.\n * @return {Object} a clone of the passed object.\n * @throws {TypeError} when a nested object is passed.\n * @memberOf Utils\n */\nlunr.utils.clone = function (obj) {\n  if (obj === null || obj === undefined) {\n    return obj\n  }\n\n  var clone = Object.create(null),\n      keys = Object.keys(obj)\n\n  for (var i = 0; i < keys.length; i++) {\n    var key = keys[i],\n        val = obj[key]\n\n    if (Array.isArray(val)) {\n      clone[key] = val.slice()\n      continue\n    }\n\n    if (typeof val === 'string' ||\n        typeof val === 'number' ||\n        typeof val === 'boolean') {\n      clone[key] = val\n      continue\n    }\n\n    throw new TypeError(\"clone is not deep and does not support nested objects\")\n  }\n\n  return clone\n}\nlunr.FieldRef = function (docRef, fieldName, stringValue) {\n  this.docRef = docRef\n  this.fieldName = fieldName\n  this._stringValue = stringValue\n}\n\nlunr.FieldRef.joiner = \"/\"\n\nlunr.FieldRef.fromString = function (s) {\n  var n = s.indexOf(lunr.FieldRef.joiner)\n\n  if (n === -1) {\n    throw \"malformed field ref string\"\n  }\n\n  var fieldRef = s.slice(0, n),\n      docRef = s.slice(n + 1)\n\n  return new lunr.FieldRef (docRef, fieldRef, s)\n}\n\nlunr.FieldRef.prototype.toString = function () {\n  if (this._stringValue == undefined) {\n    this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef\n  }\n\n  return this._stringValue\n}\n/*!\n * lunr.Set\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A lunr set.\n *\n * @constructor\n */\nlunr.Set = function (elements) {\n  this.elements = Object.create(null)\n\n  if (elements) {\n    this.length = elements.length\n\n    for (var i = 0; i < this.length; i++) {\n      this.elements[elements[i]] = true\n    }\n  } else {\n    this.length = 0\n  }\n}\n\n/**\n * A complete set that contains all elements.\n *\n * @static\n * @readonly\n * @type {lunr.Set}\n */\nlunr.Set.complete = {\n  intersect: function (other) {\n    return other\n  },\n\n  union: function () {\n    return this\n  },\n\n  contains: function () {\n    return true\n  }\n}\n\n/**\n * An empty set that contains no elements.\n *\n * @static\n * @readonly\n * @type {lunr.Set}\n */\nlunr.Set.empty = {\n  intersect: function () {\n    return this\n  },\n\n  union: function (other) {\n    return other\n  },\n\n  contains: function () {\n    return false\n  }\n}\n\n/**\n * Returns true if this set contains the specified object.\n *\n * @param {object} object - Object whose presence in this set is to be tested.\n * @returns {boolean} - True if this set contains the specified object.\n */\nlunr.Set.prototype.contains = function (object) {\n  return !!this.elements[object]\n}\n\n/**\n * Returns a new set containing only the elements that are present in both\n * this set and the specified set.\n *\n * @param {lunr.Set} other - set to intersect with this set.\n * @returns {lunr.Set} a new set that is the intersection of this and the specified set.\n */\n\nlunr.Set.prototype.intersect = function (other) {\n  var a, b, elements, intersection = []\n\n  if (other === lunr.Set.complete) {\n    return this\n  }\n\n  if (other === lunr.Set.empty) {\n    return other\n  }\n\n  if (this.length < other.length) {\n    a = this\n    b = other\n  } else {\n    a = other\n    b = this\n  }\n\n  elements = Object.keys(a.elements)\n\n  for (var i = 0; i < elements.length; i++) {\n    var element = elements[i]\n    if (element in b.elements) {\n      intersection.push(element)\n    }\n  }\n\n  return new lunr.Set (intersection)\n}\n\n/**\n * Returns a new set combining the elements of this and the specified set.\n *\n * @param {lunr.Set} other - set to union with this set.\n * @return {lunr.Set} a new set that is the union of this and the specified set.\n */\n\nlunr.Set.prototype.union = function (other) {\n  if (other === lunr.Set.complete) {\n    return lunr.Set.complete\n  }\n\n  if (other === lunr.Set.empty) {\n    return this\n  }\n\n  return new lunr.Set(Object.keys(this.elements).concat(Object.keys(other.elements)))\n}\n/**\n * A function to calculate the inverse document frequency for\n * a posting. This is shared between the builder and the index\n *\n * @private\n * @param {object} posting - The posting for a given term\n * @param {number} documentCount - The total number of documents.\n */\nlunr.idf = function (posting, documentCount) {\n  var documentsWithTerm = 0\n\n  for (var fieldName in posting) {\n    if (fieldName == '_index') continue // Ignore the term index, its not a field\n    documentsWithTerm += Object.keys(posting[fieldName]).length\n  }\n\n  var x = (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5)\n\n  return Math.log(1 + Math.abs(x))\n}\n\n/**\n * A token wraps a string representation of a token\n * as it is passed through the text processing pipeline.\n *\n * @constructor\n * @param {string} [str=''] - The string token being wrapped.\n * @param {object} [metadata={}] - Metadata associated with this token.\n */\nlunr.Token = function (str, metadata) {\n  this.str = str || \"\"\n  this.metadata = metadata || {}\n}\n\n/**\n * Returns the token string that is being wrapped by this object.\n *\n * @returns {string}\n */\nlunr.Token.prototype.toString = function () {\n  return this.str\n}\n\n/**\n * A token update function is used when updating or optionally\n * when cloning a token.\n *\n * @callback lunr.Token~updateFunction\n * @param {string} str - The string representation of the token.\n * @param {Object} metadata - All metadata associated with this token.\n */\n\n/**\n * Applies the given function to the wrapped string token.\n *\n * @example\n * token.update(function (str, metadata) {\n *   return str.toUpperCase()\n * })\n *\n * @param {lunr.Token~updateFunction} fn - A function to apply to the token string.\n * @returns {lunr.Token}\n */\nlunr.Token.prototype.update = function (fn) {\n  this.str = fn(this.str, this.metadata)\n  return this\n}\n\n/**\n * Creates a clone of this token. Optionally a function can be\n * applied to the cloned token.\n *\n * @param {lunr.Token~updateFunction} [fn] - An optional function to apply to the cloned token.\n * @returns {lunr.Token}\n */\nlunr.Token.prototype.clone = function (fn) {\n  fn = fn || function (s) { return s }\n  return new lunr.Token (fn(this.str, this.metadata), this.metadata)\n}\n/*!\n * lunr.tokenizer\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A function for splitting a string into tokens ready to be inserted into\n * the search index. Uses `lunr.tokenizer.separator` to split strings, change\n * the value of this property to change how strings are split into tokens.\n *\n * This tokenizer will convert its parameter to a string by calling `toString` and\n * then will split this string on the character in `lunr.tokenizer.separator`.\n * Arrays will have their elements converted to strings and wrapped in a lunr.Token.\n *\n * Optional metadata can be passed to the tokenizer, this metadata will be cloned and\n * added as metadata to every token that is created from the object to be tokenized.\n *\n * @static\n * @param {?(string|object|object[])} obj - The object to convert into tokens\n * @param {?object} metadata - Optional metadata to associate with every token\n * @returns {lunr.Token[]}\n * @see {@link lunr.Pipeline}\n */\nlunr.tokenizer = function (obj, metadata) {\n  if (obj == null || obj == undefined) {\n    return []\n  }\n\n  if (Array.isArray(obj)) {\n    return obj.map(function (t) {\n      return new lunr.Token(\n        lunr.utils.asString(t).toLowerCase(),\n        lunr.utils.clone(metadata)\n      )\n    })\n  }\n\n  var str = obj.toString().toLowerCase(),\n      len = str.length,\n      tokens = []\n\n  for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) {\n    var char = str.charAt(sliceEnd),\n        sliceLength = sliceEnd - sliceStart\n\n    if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) {\n\n      if (sliceLength > 0) {\n        var tokenMetadata = lunr.utils.clone(metadata) || {}\n        tokenMetadata[\"position\"] = [sliceStart, sliceLength]\n        tokenMetadata[\"index\"] = tokens.length\n\n        tokens.push(\n          new lunr.Token (\n            str.slice(sliceStart, sliceEnd),\n            tokenMetadata\n          )\n        )\n      }\n\n      sliceStart = sliceEnd + 1\n    }\n\n  }\n\n  return tokens\n}\n\n/**\n * The separator used to split a string into tokens. Override this property to change the behaviour of\n * `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens.\n *\n * @static\n * @see lunr.tokenizer\n */\nlunr.tokenizer.separator = /[\\s\\-]+/\n/*!\n * lunr.Pipeline\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.Pipelines maintain an ordered list of functions to be applied to all\n * tokens in documents entering the search index and queries being ran against\n * the index.\n *\n * An instance of lunr.Index created with the lunr shortcut will contain a\n * pipeline with a stop word filter and an English language stemmer. Extra\n * functions can be added before or after either of these functions or these\n * default functions can be removed.\n *\n * When run the pipeline will call each function in turn, passing a token, the\n * index of that token in the original list of all tokens and finally a list of\n * all the original tokens.\n *\n * The output of functions in the pipeline will be passed to the next function\n * in the pipeline. To exclude a token from entering the index the function\n * should return undefined, the rest of the pipeline will not be called with\n * this token.\n *\n * For serialisation of pipelines to work, all functions used in an instance of\n * a pipeline should be registered with lunr.Pipeline. Registered functions can\n * then be loaded. If trying to load a serialised pipeline that uses functions\n * that are not registered an error will be thrown.\n *\n * If not planning on serialising the pipeline then registering pipeline functions\n * is not necessary.\n *\n * @constructor\n */\nlunr.Pipeline = function () {\n  this._stack = []\n}\n\nlunr.Pipeline.registeredFunctions = Object.create(null)\n\n/**\n * A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token\n * string as well as all known metadata. A pipeline function can mutate the token string\n * or mutate (or add) metadata for a given token.\n *\n * A pipeline function can indicate that the passed token should be discarded by returning\n * null, undefined or an empty string. This token will not be passed to any downstream pipeline\n * functions and will not be added to the index.\n *\n * Multiple tokens can be returned by returning an array of tokens. Each token will be passed\n * to any downstream pipeline functions and all will returned tokens will be added to the index.\n *\n * Any number of pipeline functions may be chained together using a lunr.Pipeline.\n *\n * @interface lunr.PipelineFunction\n * @param {lunr.Token} token - A token from the document being processed.\n * @param {number} i - The index of this token in the complete list of tokens for this document/field.\n * @param {lunr.Token[]} tokens - All tokens for this document/field.\n * @returns {(?lunr.Token|lunr.Token[])}\n */\n\n/**\n * Register a function with the pipeline.\n *\n * Functions that are used in the pipeline should be registered if the pipeline\n * needs to be serialised, or a serialised pipeline needs to be loaded.\n *\n * Registering a function does not add it to a pipeline, functions must still be\n * added to instances of the pipeline for them to be used when running a pipeline.\n *\n * @param {lunr.PipelineFunction} fn - The function to check for.\n * @param {String} label - The label to register this function with\n */\nlunr.Pipeline.registerFunction = function (fn, label) {\n  if (label in this.registeredFunctions) {\n    lunr.utils.warn('Overwriting existing registered function: ' + label)\n  }\n\n  fn.label = label\n  lunr.Pipeline.registeredFunctions[fn.label] = fn\n}\n\n/**\n * Warns if the function is not registered as a Pipeline function.\n *\n * @param {lunr.PipelineFunction} fn - The function to check for.\n * @private\n */\nlunr.Pipeline.warnIfFunctionNotRegistered = function (fn) {\n  var isRegistered = fn.label && (fn.label in this.registeredFunctions)\n\n  if (!isRegistered) {\n    lunr.utils.warn('Function is not registered with pipeline. This may cause problems when serialising the index.\\n', fn)\n  }\n}\n\n/**\n * Loads a previously serialised pipeline.\n *\n * All functions to be loaded must already be registered with lunr.Pipeline.\n * If any function from the serialised data has not been registered then an\n * error will be thrown.\n *\n * @param {Object} serialised - The serialised pipeline to load.\n * @returns {lunr.Pipeline}\n */\nlunr.Pipeline.load = function (serialised) {\n  var pipeline = new lunr.Pipeline\n\n  serialised.forEach(function (fnName) {\n    var fn = lunr.Pipeline.registeredFunctions[fnName]\n\n    if (fn) {\n      pipeline.add(fn)\n    } else {\n      throw new Error('Cannot load unregistered function: ' + fnName)\n    }\n  })\n\n  return pipeline\n}\n\n/**\n * Adds new functions to the end of the pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction[]} functions - Any number of functions to add to the pipeline.\n */\nlunr.Pipeline.prototype.add = function () {\n  var fns = Array.prototype.slice.call(arguments)\n\n  fns.forEach(function (fn) {\n    lunr.Pipeline.warnIfFunctionNotRegistered(fn)\n    this._stack.push(fn)\n  }, this)\n}\n\n/**\n * Adds a single function after a function that already exists in the\n * pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.\n * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.\n */\nlunr.Pipeline.prototype.after = function (existingFn, newFn) {\n  lunr.Pipeline.warnIfFunctionNotRegistered(newFn)\n\n  var pos = this._stack.indexOf(existingFn)\n  if (pos == -1) {\n    throw new Error('Cannot find existingFn')\n  }\n\n  pos = pos + 1\n  this._stack.splice(pos, 0, newFn)\n}\n\n/**\n * Adds a single function before a function that already exists in the\n * pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.\n * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.\n */\nlunr.Pipeline.prototype.before = function (existingFn, newFn) {\n  lunr.Pipeline.warnIfFunctionNotRegistered(newFn)\n\n  var pos = this._stack.indexOf(existingFn)\n  if (pos == -1) {\n    throw new Error('Cannot find existingFn')\n  }\n\n  this._stack.splice(pos, 0, newFn)\n}\n\n/**\n * Removes a function from the pipeline.\n *\n * @param {lunr.PipelineFunction} fn The function to remove from the pipeline.\n */\nlunr.Pipeline.prototype.remove = function (fn) {\n  var pos = this._stack.indexOf(fn)\n  if (pos == -1) {\n    return\n  }\n\n  this._stack.splice(pos, 1)\n}\n\n/**\n * Runs the current list of functions that make up the pipeline against the\n * passed tokens.\n *\n * @param {Array} tokens The tokens to run through the pipeline.\n * @returns {Array}\n */\nlunr.Pipeline.prototype.run = function (tokens) {\n  var stackLength = this._stack.length\n\n  for (var i = 0; i < stackLength; i++) {\n    var fn = this._stack[i]\n    var memo = []\n\n    for (var j = 0; j < tokens.length; j++) {\n      var result = fn(tokens[j], j, tokens)\n\n      if (result === null || result === void 0 || result === '') continue\n\n      if (Array.isArray(result)) {\n        for (var k = 0; k < result.length; k++) {\n          memo.push(result[k])\n        }\n      } else {\n        memo.push(result)\n      }\n    }\n\n    tokens = memo\n  }\n\n  return tokens\n}\n\n/**\n * Convenience method for passing a string through a pipeline and getting\n * strings out. This method takes care of wrapping the passed string in a\n * token and mapping the resulting tokens back to strings.\n *\n * @param {string} str - The string to pass through the pipeline.\n * @param {?object} metadata - Optional metadata to associate with the token\n * passed to the pipeline.\n * @returns {string[]}\n */\nlunr.Pipeline.prototype.runString = function (str, metadata) {\n  var token = new lunr.Token (str, metadata)\n\n  return this.run([token]).map(function (t) {\n    return t.toString()\n  })\n}\n\n/**\n * Resets the pipeline by removing any existing processors.\n *\n */\nlunr.Pipeline.prototype.reset = function () {\n  this._stack = []\n}\n\n/**\n * Returns a representation of the pipeline ready for serialisation.\n *\n * Logs a warning if the function has not been registered.\n *\n * @returns {Array}\n */\nlunr.Pipeline.prototype.toJSON = function () {\n  return this._stack.map(function (fn) {\n    lunr.Pipeline.warnIfFunctionNotRegistered(fn)\n\n    return fn.label\n  })\n}\n/*!\n * lunr.Vector\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A vector is used to construct the vector space of documents and queries. These\n * vectors support operations to determine the similarity between two documents or\n * a document and a query.\n *\n * Normally no parameters are required for initializing a vector, but in the case of\n * loading a previously dumped vector the raw elements can be provided to the constructor.\n *\n * For performance reasons vectors are implemented with a flat array, where an elements\n * index is immediately followed by its value. E.g. [index, value, index, value]. This\n * allows the underlying array to be as sparse as possible and still offer decent\n * performance when being used for vector calculations.\n *\n * @constructor\n * @param {Number[]} [elements] - The flat list of element index and element value pairs.\n */\nlunr.Vector = function (elements) {\n  this._magnitude = 0\n  this.elements = elements || []\n}\n\n\n/**\n * Calculates the position within the vector to insert a given index.\n *\n * This is used internally by insert and upsert. If there are duplicate indexes then\n * the position is returned as if the value for that index were to be updated, but it\n * is the callers responsibility to check whether there is a duplicate at that index\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @returns {Number}\n */\nlunr.Vector.prototype.positionForIndex = function (index) {\n  // For an empty vector the tuple can be inserted at the beginning\n  if (this.elements.length == 0) {\n    return 0\n  }\n\n  var start = 0,\n      end = this.elements.length / 2,\n      sliceLength = end - start,\n      pivotPoint = Math.floor(sliceLength / 2),\n      pivotIndex = this.elements[pivotPoint * 2]\n\n  while (sliceLength > 1) {\n    if (pivotIndex < index) {\n      start = pivotPoint\n    }\n\n    if (pivotIndex > index) {\n      end = pivotPoint\n    }\n\n    if (pivotIndex == index) {\n      break\n    }\n\n    sliceLength = end - start\n    pivotPoint = start + Math.floor(sliceLength / 2)\n    pivotIndex = this.elements[pivotPoint * 2]\n  }\n\n  if (pivotIndex == index) {\n    return pivotPoint * 2\n  }\n\n  if (pivotIndex > index) {\n    return pivotPoint * 2\n  }\n\n  if (pivotIndex < index) {\n    return (pivotPoint + 1) * 2\n  }\n}\n\n/**\n * Inserts an element at an index within the vector.\n *\n * Does not allow duplicates, will throw an error if there is already an entry\n * for this index.\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @param {Number} val - The value to be inserted into the vector.\n */\nlunr.Vector.prototype.insert = function (insertIdx, val) {\n  this.upsert(insertIdx, val, function () {\n    throw \"duplicate index\"\n  })\n}\n\n/**\n * Inserts or updates an existing index within the vector.\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @param {Number} val - The value to be inserted into the vector.\n * @param {function} fn - A function that is called for updates, the existing value and the\n * requested value are passed as arguments\n */\nlunr.Vector.prototype.upsert = function (insertIdx, val, fn) {\n  this._magnitude = 0\n  var position = this.positionForIndex(insertIdx)\n\n  if (this.elements[position] == insertIdx) {\n    this.elements[position + 1] = fn(this.elements[position + 1], val)\n  } else {\n    this.elements.splice(position, 0, insertIdx, val)\n  }\n}\n\n/**\n * Calculates the magnitude of this vector.\n *\n * @returns {Number}\n */\nlunr.Vector.prototype.magnitude = function () {\n  if (this._magnitude) return this._magnitude\n\n  var sumOfSquares = 0,\n      elementsLength = this.elements.length\n\n  for (var i = 1; i < elementsLength; i += 2) {\n    var val = this.elements[i]\n    sumOfSquares += val * val\n  }\n\n  return this._magnitude = Math.sqrt(sumOfSquares)\n}\n\n/**\n * Calculates the dot product of this vector and another vector.\n *\n * @param {lunr.Vector} otherVector - The vector to compute the dot product with.\n * @returns {Number}\n */\nlunr.Vector.prototype.dot = function (otherVector) {\n  var dotProduct = 0,\n      a = this.elements, b = otherVector.elements,\n      aLen = a.length, bLen = b.length,\n      aVal = 0, bVal = 0,\n      i = 0, j = 0\n\n  while (i < aLen && j < bLen) {\n    aVal = a[i], bVal = b[j]\n    if (aVal < bVal) {\n      i += 2\n    } else if (aVal > bVal) {\n      j += 2\n    } else if (aVal == bVal) {\n      dotProduct += a[i + 1] * b[j + 1]\n      i += 2\n      j += 2\n    }\n  }\n\n  return dotProduct\n}\n\n/**\n * Calculates the similarity between this vector and another vector.\n *\n * @param {lunr.Vector} otherVector - The other vector to calculate the\n * similarity with.\n * @returns {Number}\n */\nlunr.Vector.prototype.similarity = function (otherVector) {\n  return this.dot(otherVector) / this.magnitude() || 0\n}\n\n/**\n * Converts the vector to an array of the elements within the vector.\n *\n * @returns {Number[]}\n */\nlunr.Vector.prototype.toArray = function () {\n  var output = new Array (this.elements.length / 2)\n\n  for (var i = 1, j = 0; i < this.elements.length; i += 2, j++) {\n    output[j] = this.elements[i]\n  }\n\n  return output\n}\n\n/**\n * A JSON serializable representation of the vector.\n *\n * @returns {Number[]}\n */\nlunr.Vector.prototype.toJSON = function () {\n  return this.elements\n}\n/* eslint-disable */\n/*!\n * lunr.stemmer\n * Copyright (C) 2020 Oliver Nightingale\n * Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt\n */\n\n/**\n * lunr.stemmer is an english language stemmer, this is a JavaScript\n * implementation of the PorterStemmer taken from http://tartarus.org/~martin\n *\n * @static\n * @implements {lunr.PipelineFunction}\n * @param {lunr.Token} token - The string to stem\n * @returns {lunr.Token}\n * @see {@link lunr.Pipeline}\n * @function\n */\nlunr.stemmer = (function(){\n  var step2list = {\n      \"ational\" : \"ate\",\n      \"tional\" : \"tion\",\n      \"enci\" : \"ence\",\n      \"anci\" : \"ance\",\n      \"izer\" : \"ize\",\n      \"bli\" : \"ble\",\n      \"alli\" : \"al\",\n      \"entli\" : \"ent\",\n      \"eli\" : \"e\",\n      \"ousli\" : \"ous\",\n      \"ization\" : \"ize\",\n      \"ation\" : \"ate\",\n      \"ator\" : \"ate\",\n      \"alism\" : \"al\",\n      \"iveness\" : \"ive\",\n      \"fulness\" : \"ful\",\n      \"ousness\" : \"ous\",\n      \"aliti\" : \"al\",\n      \"iviti\" : \"ive\",\n      \"biliti\" : \"ble\",\n      \"logi\" : \"log\"\n    },\n\n    step3list = {\n      \"icate\" : \"ic\",\n      \"ative\" : \"\",\n      \"alize\" : \"al\",\n      \"iciti\" : \"ic\",\n      \"ical\" : \"ic\",\n      \"ful\" : \"\",\n      \"ness\" : \"\"\n    },\n\n    c = \"[^aeiou]\",          // consonant\n    v = \"[aeiouy]\",          // vowel\n    C = c + \"[^aeiouy]*\",    // consonant sequence\n    V = v + \"[aeiou]*\",      // vowel sequence\n\n    mgr0 = \"^(\" + C + \")?\" + V + C,               // [C]VC... is m>0\n    meq1 = \"^(\" + C + \")?\" + V + C + \"(\" + V + \")?$\",  // [C]VC[V] is m=1\n    mgr1 = \"^(\" + C + \")?\" + V + C + V + C,       // [C]VCVC... is m>1\n    s_v = \"^(\" + C + \")?\" + v;                   // vowel in stem\n\n  var re_mgr0 = new RegExp(mgr0);\n  var re_mgr1 = new RegExp(mgr1);\n  var re_meq1 = new RegExp(meq1);\n  var re_s_v = new RegExp(s_v);\n\n  var re_1a = /^(.+?)(ss|i)es$/;\n  var re2_1a = /^(.+?)([^s])s$/;\n  var re_1b = /^(.+?)eed$/;\n  var re2_1b = /^(.+?)(ed|ing)$/;\n  var re_1b_2 = /.$/;\n  var re2_1b_2 = /(at|bl|iz)$/;\n  var re3_1b_2 = new RegExp(\"([^aeiouylsz])\\\\1$\");\n  var re4_1b_2 = new RegExp(\"^\" + C + v + \"[^aeiouwxy]$\");\n\n  var re_1c = /^(.+?[^aeiou])y$/;\n  var re_2 = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;\n\n  var re_3 = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;\n\n  var re_4 = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;\n  var re2_4 = /^(.+?)(s|t)(ion)$/;\n\n  var re_5 = /^(.+?)e$/;\n  var re_5_1 = /ll$/;\n  var re3_5 = new RegExp(\"^\" + C + v + \"[^aeiouwxy]$\");\n\n  var porterStemmer = function porterStemmer(w) {\n    var stem,\n      suffix,\n      firstch,\n      re,\n      re2,\n      re3,\n      re4;\n\n    if (w.length < 3) { return w; }\n\n    firstch = w.substr(0,1);\n    if (firstch == \"y\") {\n      w = firstch.toUpperCase() + w.substr(1);\n    }\n\n    // Step 1a\n    re = re_1a\n    re2 = re2_1a;\n\n    if (re.test(w)) { w = w.replace(re,\"$1$2\"); }\n    else if (re2.test(w)) { w = w.replace(re2,\"$1$2\"); }\n\n    // Step 1b\n    re = re_1b;\n    re2 = re2_1b;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      re = re_mgr0;\n      if (re.test(fp[1])) {\n        re = re_1b_2;\n        w = w.replace(re,\"\");\n      }\n    } else if (re2.test(w)) {\n      var fp = re2.exec(w);\n      stem = fp[1];\n      re2 = re_s_v;\n      if (re2.test(stem)) {\n        w = stem;\n        re2 = re2_1b_2;\n        re3 = re3_1b_2;\n        re4 = re4_1b_2;\n        if (re2.test(w)) { w = w + \"e\"; }\n        else if (re3.test(w)) { re = re_1b_2; w = w.replace(re,\"\"); }\n        else if (re4.test(w)) { w = w + \"e\"; }\n      }\n    }\n\n    // Step 1c - replace suffix y or Y by i if preceded by a non-vowel which is not the first letter of the word (so cry -> cri, by -> by, say -> say)\n    re = re_1c;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      w = stem + \"i\";\n    }\n\n    // Step 2\n    re = re_2;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      suffix = fp[2];\n      re = re_mgr0;\n      if (re.test(stem)) {\n        w = stem + step2list[suffix];\n      }\n    }\n\n    // Step 3\n    re = re_3;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      suffix = fp[2];\n      re = re_mgr0;\n      if (re.test(stem)) {\n        w = stem + step3list[suffix];\n      }\n    }\n\n    // Step 4\n    re = re_4;\n    re2 = re2_4;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      re = re_mgr1;\n      if (re.test(stem)) {\n        w = stem;\n      }\n    } else if (re2.test(w)) {\n      var fp = re2.exec(w);\n      stem = fp[1] + fp[2];\n      re2 = re_mgr1;\n      if (re2.test(stem)) {\n        w = stem;\n      }\n    }\n\n    // Step 5\n    re = re_5;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      re = re_mgr1;\n      re2 = re_meq1;\n      re3 = re3_5;\n      if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) {\n        w = stem;\n      }\n    }\n\n    re = re_5_1;\n    re2 = re_mgr1;\n    if (re.test(w) && re2.test(w)) {\n      re = re_1b_2;\n      w = w.replace(re,\"\");\n    }\n\n    // and turn initial Y back to y\n\n    if (firstch == \"y\") {\n      w = firstch.toLowerCase() + w.substr(1);\n    }\n\n    return w;\n  };\n\n  return function (token) {\n    return token.update(porterStemmer);\n  }\n})();\n\nlunr.Pipeline.registerFunction(lunr.stemmer, 'stemmer')\n/*!\n * lunr.stopWordFilter\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.generateStopWordFilter builds a stopWordFilter function from the provided\n * list of stop words.\n *\n * The built in lunr.stopWordFilter is built using this generator and can be used\n * to generate custom stopWordFilters for applications or non English languages.\n *\n * @function\n * @param {Array} token The token to pass through the filter\n * @returns {lunr.PipelineFunction}\n * @see lunr.Pipeline\n * @see lunr.stopWordFilter\n */\nlunr.generateStopWordFilter = function (stopWords) {\n  var words = stopWords.reduce(function (memo, stopWord) {\n    memo[stopWord] = stopWord\n    return memo\n  }, {})\n\n  return function (token) {\n    if (token && words[token.toString()] !== token.toString()) return token\n  }\n}\n\n/**\n * lunr.stopWordFilter is an English language stop word list filter, any words\n * contained in the list will not be passed through the filter.\n *\n * This is intended to be used in the Pipeline. If the token does not pass the\n * filter then undefined will be returned.\n *\n * @function\n * @implements {lunr.PipelineFunction}\n * @params {lunr.Token} token - A token to check for being a stop word.\n * @returns {lunr.Token}\n * @see {@link lunr.Pipeline}\n */\nlunr.stopWordFilter = lunr.generateStopWordFilter([\n  'a',\n  'able',\n  'about',\n  'across',\n  'after',\n  'all',\n  'almost',\n  'also',\n  'am',\n  'among',\n  'an',\n  'and',\n  'any',\n  'are',\n  'as',\n  'at',\n  'be',\n  'because',\n  'been',\n  'but',\n  'by',\n  'can',\n  'cannot',\n  'could',\n  'dear',\n  'did',\n  'do',\n  'does',\n  'either',\n  'else',\n  'ever',\n  'every',\n  'for',\n  'from',\n  'get',\n  'got',\n  'had',\n  'has',\n  'have',\n  'he',\n  'her',\n  'hers',\n  'him',\n  'his',\n  'how',\n  'however',\n  'i',\n  'if',\n  'in',\n  'into',\n  'is',\n  'it',\n  'its',\n  'just',\n  'least',\n  'let',\n  'like',\n  'likely',\n  'may',\n  'me',\n  'might',\n  'most',\n  'must',\n  'my',\n  'neither',\n  'no',\n  'nor',\n  'not',\n  'of',\n  'off',\n  'often',\n  'on',\n  'only',\n  'or',\n  'other',\n  'our',\n  'own',\n  'rather',\n  'said',\n  'say',\n  'says',\n  'she',\n  'should',\n  'since',\n  'so',\n  'some',\n  'than',\n  'that',\n  'the',\n  'their',\n  'them',\n  'then',\n  'there',\n  'these',\n  'they',\n  'this',\n  'tis',\n  'to',\n  'too',\n  'twas',\n  'us',\n  'wants',\n  'was',\n  'we',\n  'were',\n  'what',\n  'when',\n  'where',\n  'which',\n  'while',\n  'who',\n  'whom',\n  'why',\n  'will',\n  'with',\n  'would',\n  'yet',\n  'you',\n  'your'\n])\n\nlunr.Pipeline.registerFunction(lunr.stopWordFilter, 'stopWordFilter')\n/*!\n * lunr.trimmer\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.trimmer is a pipeline function for trimming non word\n * characters from the beginning and end of tokens before they\n * enter the index.\n *\n * This implementation may not work correctly for non latin\n * characters and should either be removed or adapted for use\n * with languages with non-latin characters.\n *\n * @static\n * @implements {lunr.PipelineFunction}\n * @param {lunr.Token} token The token to pass through the filter\n * @returns {lunr.Token}\n * @see lunr.Pipeline\n */\nlunr.trimmer = function (token) {\n  return token.update(function (s) {\n    return s.replace(/^\\W+/, '').replace(/\\W+$/, '')\n  })\n}\n\nlunr.Pipeline.registerFunction(lunr.trimmer, 'trimmer')\n/*!\n * lunr.TokenSet\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A token set is used to store the unique list of all tokens\n * within an index. Token sets are also used to represent an\n * incoming query to the index, this query token set and index\n * token set are then intersected to find which tokens to look\n * up in the inverted index.\n *\n * A token set can hold multiple tokens, as in the case of the\n * index token set, or it can hold a single token as in the\n * case of a simple query token set.\n *\n * Additionally token sets are used to perform wildcard matching.\n * Leading, contained and trailing wildcards are supported, and\n * from this edit distance matching can also be provided.\n *\n * Token sets are implemented as a minimal finite state automata,\n * where both common prefixes and suffixes are shared between tokens.\n * This helps to reduce the space used for storing the token set.\n *\n * @constructor\n */\nlunr.TokenSet = function () {\n  this.final = false\n  this.edges = {}\n  this.id = lunr.TokenSet._nextId\n  lunr.TokenSet._nextId += 1\n}\n\n/**\n * Keeps track of the next, auto increment, identifier to assign\n * to a new tokenSet.\n *\n * TokenSets require a unique identifier to be correctly minimised.\n *\n * @private\n */\nlunr.TokenSet._nextId = 1\n\n/**\n * Creates a TokenSet instance from the given sorted array of words.\n *\n * @param {String[]} arr - A sorted array of strings to create the set from.\n * @returns {lunr.TokenSet}\n * @throws Will throw an error if the input array is not sorted.\n */\nlunr.TokenSet.fromArray = function (arr) {\n  var builder = new lunr.TokenSet.Builder\n\n  for (var i = 0, len = arr.length; i < len; i++) {\n    builder.insert(arr[i])\n  }\n\n  builder.finish()\n  return builder.root\n}\n\n/**\n * Creates a token set from a query clause.\n *\n * @private\n * @param {Object} clause - A single clause from lunr.Query.\n * @param {string} clause.term - The query clause term.\n * @param {number} [clause.editDistance] - The optional edit distance for the term.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.fromClause = function (clause) {\n  if ('editDistance' in clause) {\n    return lunr.TokenSet.fromFuzzyString(clause.term, clause.editDistance)\n  } else {\n    return lunr.TokenSet.fromString(clause.term)\n  }\n}\n\n/**\n * Creates a token set representing a single string with a specified\n * edit distance.\n *\n * Insertions, deletions, substitutions and transpositions are each\n * treated as an edit distance of 1.\n *\n * Increasing the allowed edit distance will have a dramatic impact\n * on the performance of both creating and intersecting these TokenSets.\n * It is advised to keep the edit distance less than 3.\n *\n * @param {string} str - The string to create the token set from.\n * @param {number} editDistance - The allowed edit distance to match.\n * @returns {lunr.Vector}\n */\nlunr.TokenSet.fromFuzzyString = function (str, editDistance) {\n  var root = new lunr.TokenSet\n\n  var stack = [{\n    node: root,\n    editsRemaining: editDistance,\n    str: str\n  }]\n\n  while (stack.length) {\n    var frame = stack.pop()\n\n    // no edit\n    if (frame.str.length > 0) {\n      var char = frame.str.charAt(0),\n          noEditNode\n\n      if (char in frame.node.edges) {\n        noEditNode = frame.node.edges[char]\n      } else {\n        noEditNode = new lunr.TokenSet\n        frame.node.edges[char] = noEditNode\n      }\n\n      if (frame.str.length == 1) {\n        noEditNode.final = true\n      }\n\n      stack.push({\n        node: noEditNode,\n        editsRemaining: frame.editsRemaining,\n        str: frame.str.slice(1)\n      })\n    }\n\n    if (frame.editsRemaining == 0) {\n      continue\n    }\n\n    // insertion\n    if (\"*\" in frame.node.edges) {\n      var insertionNode = frame.node.edges[\"*\"]\n    } else {\n      var insertionNode = new lunr.TokenSet\n      frame.node.edges[\"*\"] = insertionNode\n    }\n\n    if (frame.str.length == 0) {\n      insertionNode.final = true\n    }\n\n    stack.push({\n      node: insertionNode,\n      editsRemaining: frame.editsRemaining - 1,\n      str: frame.str\n    })\n\n    // deletion\n    // can only do a deletion if we have enough edits remaining\n    // and if there are characters left to delete in the string\n    if (frame.str.length > 1) {\n      stack.push({\n        node: frame.node,\n        editsRemaining: frame.editsRemaining - 1,\n        str: frame.str.slice(1)\n      })\n    }\n\n    // deletion\n    // just removing the last character from the str\n    if (frame.str.length == 1) {\n      frame.node.final = true\n    }\n\n    // substitution\n    // can only do a substitution if we have enough edits remaining\n    // and if there are characters left to substitute\n    if (frame.str.length >= 1) {\n      if (\"*\" in frame.node.edges) {\n        var substitutionNode = frame.node.edges[\"*\"]\n      } else {\n        var substitutionNode = new lunr.TokenSet\n        frame.node.edges[\"*\"] = substitutionNode\n      }\n\n      if (frame.str.length == 1) {\n        substitutionNode.final = true\n      }\n\n      stack.push({\n        node: substitutionNode,\n        editsRemaining: frame.editsRemaining - 1,\n        str: frame.str.slice(1)\n      })\n    }\n\n    // transposition\n    // can only do a transposition if there are edits remaining\n    // and there are enough characters to transpose\n    if (frame.str.length > 1) {\n      var charA = frame.str.charAt(0),\n          charB = frame.str.charAt(1),\n          transposeNode\n\n      if (charB in frame.node.edges) {\n        transposeNode = frame.node.edges[charB]\n      } else {\n        transposeNode = new lunr.TokenSet\n        frame.node.edges[charB] = transposeNode\n      }\n\n      if (frame.str.length == 1) {\n        transposeNode.final = true\n      }\n\n      stack.push({\n        node: transposeNode,\n        editsRemaining: frame.editsRemaining - 1,\n        str: charA + frame.str.slice(2)\n      })\n    }\n  }\n\n  return root\n}\n\n/**\n * Creates a TokenSet from a string.\n *\n * The string may contain one or more wildcard characters (*)\n * that will allow wildcard matching when intersecting with\n * another TokenSet.\n *\n * @param {string} str - The string to create a TokenSet from.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.fromString = function (str) {\n  var node = new lunr.TokenSet,\n      root = node\n\n  /*\n   * Iterates through all characters within the passed string\n   * appending a node for each character.\n   *\n   * When a wildcard character is found then a self\n   * referencing edge is introduced to continually match\n   * any number of any characters.\n   */\n  for (var i = 0, len = str.length; i < len; i++) {\n    var char = str[i],\n        final = (i == len - 1)\n\n    if (char == \"*\") {\n      node.edges[char] = node\n      node.final = final\n\n    } else {\n      var next = new lunr.TokenSet\n      next.final = final\n\n      node.edges[char] = next\n      node = next\n    }\n  }\n\n  return root\n}\n\n/**\n * Converts this TokenSet into an array of strings\n * contained within the TokenSet.\n *\n * This is not intended to be used on a TokenSet that\n * contains wildcards, in these cases the results are\n * undefined and are likely to cause an infinite loop.\n *\n * @returns {string[]}\n */\nlunr.TokenSet.prototype.toArray = function () {\n  var words = []\n\n  var stack = [{\n    prefix: \"\",\n    node: this\n  }]\n\n  while (stack.length) {\n    var frame = stack.pop(),\n        edges = Object.keys(frame.node.edges),\n        len = edges.length\n\n    if (frame.node.final) {\n      /* In Safari, at this point the prefix is sometimes corrupted, see:\n       * https://github.com/olivernn/lunr.js/issues/279 Calling any\n       * String.prototype method forces Safari to \"cast\" this string to what\n       * it's supposed to be, fixing the bug. */\n      frame.prefix.charAt(0)\n      words.push(frame.prefix)\n    }\n\n    for (var i = 0; i < len; i++) {\n      var edge = edges[i]\n\n      stack.push({\n        prefix: frame.prefix.concat(edge),\n        node: frame.node.edges[edge]\n      })\n    }\n  }\n\n  return words\n}\n\n/**\n * Generates a string representation of a TokenSet.\n *\n * This is intended to allow TokenSets to be used as keys\n * in objects, largely to aid the construction and minimisation\n * of a TokenSet. As such it is not designed to be a human\n * friendly representation of the TokenSet.\n *\n * @returns {string}\n */\nlunr.TokenSet.prototype.toString = function () {\n  // NOTE: Using Object.keys here as this.edges is very likely\n  // to enter 'hash-mode' with many keys being added\n  //\n  // avoiding a for-in loop here as it leads to the function\n  // being de-optimised (at least in V8). From some simple\n  // benchmarks the performance is comparable, but allowing\n  // V8 to optimize may mean easy performance wins in the future.\n\n  if (this._str) {\n    return this._str\n  }\n\n  var str = this.final ? '1' : '0',\n      labels = Object.keys(this.edges).sort(),\n      len = labels.length\n\n  for (var i = 0; i < len; i++) {\n    var label = labels[i],\n        node = this.edges[label]\n\n    str = str + label + node.id\n  }\n\n  return str\n}\n\n/**\n * Returns a new TokenSet that is the intersection of\n * this TokenSet and the passed TokenSet.\n *\n * This intersection will take into account any wildcards\n * contained within the TokenSet.\n *\n * @param {lunr.TokenSet} b - An other TokenSet to intersect with.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.prototype.intersect = function (b) {\n  var output = new lunr.TokenSet,\n      frame = undefined\n\n  var stack = [{\n    qNode: b,\n    output: output,\n    node: this\n  }]\n\n  while (stack.length) {\n    frame = stack.pop()\n\n    // NOTE: As with the #toString method, we are using\n    // Object.keys and a for loop instead of a for-in loop\n    // as both of these objects enter 'hash' mode, causing\n    // the function to be de-optimised in V8\n    var qEdges = Object.keys(frame.qNode.edges),\n        qLen = qEdges.length,\n        nEdges = Object.keys(frame.node.edges),\n        nLen = nEdges.length\n\n    for (var q = 0; q < qLen; q++) {\n      var qEdge = qEdges[q]\n\n      for (var n = 0; n < nLen; n++) {\n        var nEdge = nEdges[n]\n\n        if (nEdge == qEdge || qEdge == '*') {\n          var node = frame.node.edges[nEdge],\n              qNode = frame.qNode.edges[qEdge],\n              final = node.final && qNode.final,\n              next = undefined\n\n          if (nEdge in frame.output.edges) {\n            // an edge already exists for this character\n            // no need to create a new node, just set the finality\n            // bit unless this node is already final\n            next = frame.output.edges[nEdge]\n            next.final = next.final || final\n\n          } else {\n            // no edge exists yet, must create one\n            // set the finality bit and insert it\n            // into the output\n            next = new lunr.TokenSet\n            next.final = final\n            frame.output.edges[nEdge] = next\n          }\n\n          stack.push({\n            qNode: qNode,\n            output: next,\n            node: node\n          })\n        }\n      }\n    }\n  }\n\n  return output\n}\nlunr.TokenSet.Builder = function () {\n  this.previousWord = \"\"\n  this.root = new lunr.TokenSet\n  this.uncheckedNodes = []\n  this.minimizedNodes = {}\n}\n\nlunr.TokenSet.Builder.prototype.insert = function (word) {\n  var node,\n      commonPrefix = 0\n\n  if (word < this.previousWord) {\n    throw new Error (\"Out of order word insertion\")\n  }\n\n  for (var i = 0; i < word.length && i < this.previousWord.length; i++) {\n    if (word[i] != this.previousWord[i]) break\n    commonPrefix++\n  }\n\n  this.minimize(commonPrefix)\n\n  if (this.uncheckedNodes.length == 0) {\n    node = this.root\n  } else {\n    node = this.uncheckedNodes[this.uncheckedNodes.length - 1].child\n  }\n\n  for (var i = commonPrefix; i < word.length; i++) {\n    var nextNode = new lunr.TokenSet,\n        char = word[i]\n\n    node.edges[char] = nextNode\n\n    this.uncheckedNodes.push({\n      parent: node,\n      char: char,\n      child: nextNode\n    })\n\n    node = nextNode\n  }\n\n  node.final = true\n  this.previousWord = word\n}\n\nlunr.TokenSet.Builder.prototype.finish = function () {\n  this.minimize(0)\n}\n\nlunr.TokenSet.Builder.prototype.minimize = function (downTo) {\n  for (var i = this.uncheckedNodes.length - 1; i >= downTo; i--) {\n    var node = this.uncheckedNodes[i],\n        childKey = node.child.toString()\n\n    if (childKey in this.minimizedNodes) {\n      node.parent.edges[node.char] = this.minimizedNodes[childKey]\n    } else {\n      // Cache the key for this node since\n      // we know it can't change anymore\n      node.child._str = childKey\n\n      this.minimizedNodes[childKey] = node.child\n    }\n\n    this.uncheckedNodes.pop()\n  }\n}\n/*!\n * lunr.Index\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * An index contains the built index of all documents and provides a query interface\n * to the index.\n *\n * Usually instances of lunr.Index will not be created using this constructor, instead\n * lunr.Builder should be used to construct new indexes, or lunr.Index.load should be\n * used to load previously built and serialized indexes.\n *\n * @constructor\n * @param {Object} attrs - The attributes of the built search index.\n * @param {Object} attrs.invertedIndex - An index of term/field to document reference.\n * @param {Object<string, lunr.Vector>} attrs.fieldVectors - Field vectors\n * @param {lunr.TokenSet} attrs.tokenSet - An set of all corpus tokens.\n * @param {string[]} attrs.fields - The names of indexed document fields.\n * @param {lunr.Pipeline} attrs.pipeline - The pipeline to use for search terms.\n */\nlunr.Index = function (attrs) {\n  this.invertedIndex = attrs.invertedIndex\n  this.fieldVectors = attrs.fieldVectors\n  this.tokenSet = attrs.tokenSet\n  this.fields = attrs.fields\n  this.pipeline = attrs.pipeline\n}\n\n/**\n * A result contains details of a document matching a search query.\n * @typedef {Object} lunr.Index~Result\n * @property {string} ref - The reference of the document this result represents.\n * @property {number} score - A number between 0 and 1 representing how similar this document is to the query.\n * @property {lunr.MatchData} matchData - Contains metadata about this match including which term(s) caused the match.\n */\n\n/**\n * Although lunr provides the ability to create queries using lunr.Query, it also provides a simple\n * query language which itself is parsed into an instance of lunr.Query.\n *\n * For programmatically building queries it is advised to directly use lunr.Query, the query language\n * is best used for human entered text rather than program generated text.\n *\n * At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported\n * and will be combined with OR, e.g `hello world` will match documents that contain either 'hello'\n * or 'world', though those that contain both will rank higher in the results.\n *\n * Wildcards can be included in terms to match one or more unspecified characters, these wildcards can\n * be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding\n * wildcards will increase the number of documents that will be found but can also have a negative\n * impact on query performance, especially with wildcards at the beginning of a term.\n *\n * Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term\n * hello in the title field will match this query. Using a field not present in the index will lead\n * to an error being thrown.\n *\n * Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term\n * boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported\n * to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2.\n * Avoid large values for edit distance to improve query performance.\n *\n * Each term also supports a presence modifier. By default a term's presence in document is optional, however\n * this can be changed to either required or prohibited. For a term's presence to be required in a document the\n * term should be prefixed with a '+', e.g. `+foo bar` is a search for documents that must contain 'foo' and\n * optionally contain 'bar'. Conversely a leading '-' sets the terms presence to prohibited, i.e. it must not\n * appear in a document, e.g. `-foo bar` is a search for documents that do not contain 'foo' but may contain 'bar'.\n *\n * To escape special characters the backslash character '\\' can be used, this allows searches to include\n * characters that would normally be considered modifiers, e.g. `foo\\~2` will search for a term \"foo~2\" instead\n * of attempting to apply a boost of 2 to the search term \"foo\".\n *\n * @typedef {string} lunr.Index~QueryString\n * @example <caption>Simple single term query</caption>\n * hello\n * @example <caption>Multiple term query</caption>\n * hello world\n * @example <caption>term scoped to a field</caption>\n * title:hello\n * @example <caption>term with a boost of 10</caption>\n * hello^10\n * @example <caption>term with an edit distance of 2</caption>\n * hello~2\n * @example <caption>terms with presence modifiers</caption>\n * -foo +bar baz\n */\n\n/**\n * Performs a search against the index using lunr query syntax.\n *\n * Results will be returned sorted by their score, the most relevant results\n * will be returned first.  For details on how the score is calculated, please see\n * the {@link https://lunrjs.com/guides/searching.html#scoring|guide}.\n *\n * For more programmatic querying use lunr.Index#query.\n *\n * @param {lunr.Index~QueryString} queryString - A string containing a lunr query.\n * @throws {lunr.QueryParseError} If the passed query string cannot be parsed.\n * @returns {lunr.Index~Result[]}\n */\nlunr.Index.prototype.search = function (queryString) {\n  return this.query(function (query) {\n    var parser = new lunr.QueryParser(queryString, query)\n    parser.parse()\n  })\n}\n\n/**\n * A query builder callback provides a query object to be used to express\n * the query to perform on the index.\n *\n * @callback lunr.Index~queryBuilder\n * @param {lunr.Query} query - The query object to build up.\n * @this lunr.Query\n */\n\n/**\n * Performs a query against the index using the yielded lunr.Query object.\n *\n * If performing programmatic queries against the index, this method is preferred\n * over lunr.Index#search so as to avoid the additional query parsing overhead.\n *\n * A query object is yielded to the supplied function which should be used to\n * express the query to be run against the index.\n *\n * Note that although this function takes a callback parameter it is _not_ an\n * asynchronous operation, the callback is just yielded a query object to be\n * customized.\n *\n * @param {lunr.Index~queryBuilder} fn - A function that is used to build the query.\n * @returns {lunr.Index~Result[]}\n */\nlunr.Index.prototype.query = function (fn) {\n  // for each query clause\n  // * process terms\n  // * expand terms from token set\n  // * find matching documents and metadata\n  // * get document vectors\n  // * score documents\n\n  var query = new lunr.Query(this.fields),\n      matchingFields = Object.create(null),\n      queryVectors = Object.create(null),\n      termFieldCache = Object.create(null),\n      requiredMatches = Object.create(null),\n      prohibitedMatches = Object.create(null)\n\n  /*\n   * To support field level boosts a query vector is created per\n   * field. An empty vector is eagerly created to support negated\n   * queries.\n   */\n  for (var i = 0; i < this.fields.length; i++) {\n    queryVectors[this.fields[i]] = new lunr.Vector\n  }\n\n  fn.call(query, query)\n\n  for (var i = 0; i < query.clauses.length; i++) {\n    /*\n     * Unless the pipeline has been disabled for this term, which is\n     * the case for terms with wildcards, we need to pass the clause\n     * term through the search pipeline. A pipeline returns an array\n     * of processed terms. Pipeline functions may expand the passed\n     * term, which means we may end up performing multiple index lookups\n     * for a single query term.\n     */\n    var clause = query.clauses[i],\n        terms = null,\n        clauseMatches = lunr.Set.empty\n\n    if (clause.usePipeline) {\n      terms = this.pipeline.runString(clause.term, {\n        fields: clause.fields\n      })\n    } else {\n      terms = [clause.term]\n    }\n\n    for (var m = 0; m < terms.length; m++) {\n      var term = terms[m]\n\n      /*\n       * Each term returned from the pipeline needs to use the same query\n       * clause object, e.g. the same boost and or edit distance. The\n       * simplest way to do this is to re-use the clause object but mutate\n       * its term property.\n       */\n      clause.term = term\n\n      /*\n       * From the term in the clause we create a token set which will then\n       * be used to intersect the indexes token set to get a list of terms\n       * to lookup in the inverted index\n       */\n      var termTokenSet = lunr.TokenSet.fromClause(clause),\n          expandedTerms = this.tokenSet.intersect(termTokenSet).toArray()\n\n      /*\n       * If a term marked as required does not exist in the tokenSet it is\n       * impossible for the search to return any matches. We set all the field\n       * scoped required matches set to empty and stop examining any further\n       * clauses.\n       */\n      if (expandedTerms.length === 0 && clause.presence === lunr.Query.presence.REQUIRED) {\n        for (var k = 0; k < clause.fields.length; k++) {\n          var field = clause.fields[k]\n          requiredMatches[field] = lunr.Set.empty\n        }\n\n        break\n      }\n\n      for (var j = 0; j < expandedTerms.length; j++) {\n        /*\n         * For each term get the posting and termIndex, this is required for\n         * building the query vector.\n         */\n        var expandedTerm = expandedTerms[j],\n            posting = this.invertedIndex[expandedTerm],\n            termIndex = posting._index\n\n        for (var k = 0; k < clause.fields.length; k++) {\n          /*\n           * For each field that this query term is scoped by (by default\n           * all fields are in scope) we need to get all the document refs\n           * that have this term in that field.\n           *\n           * The posting is the entry in the invertedIndex for the matching\n           * term from above.\n           */\n          var field = clause.fields[k],\n              fieldPosting = posting[field],\n              matchingDocumentRefs = Object.keys(fieldPosting),\n              termField = expandedTerm + \"/\" + field,\n              matchingDocumentsSet = new lunr.Set(matchingDocumentRefs)\n\n          /*\n           * if the presence of this term is required ensure that the matching\n           * documents are added to the set of required matches for this clause.\n           *\n           */\n          if (clause.presence == lunr.Query.presence.REQUIRED) {\n            clauseMatches = clauseMatches.union(matchingDocumentsSet)\n\n            if (requiredMatches[field] === undefined) {\n              requiredMatches[field] = lunr.Set.complete\n            }\n          }\n\n          /*\n           * if the presence of this term is prohibited ensure that the matching\n           * documents are added to the set of prohibited matches for this field,\n           * creating that set if it does not yet exist.\n           */\n          if (clause.presence == lunr.Query.presence.PROHIBITED) {\n            if (prohibitedMatches[field] === undefined) {\n              prohibitedMatches[field] = lunr.Set.empty\n            }\n\n            prohibitedMatches[field] = prohibitedMatches[field].union(matchingDocumentsSet)\n\n            /*\n             * Prohibited matches should not be part of the query vector used for\n             * similarity scoring and no metadata should be extracted so we continue\n             * to the next field\n             */\n            continue\n          }\n\n          /*\n           * The query field vector is populated using the termIndex found for\n           * the term and a unit value with the appropriate boost applied.\n           * Using upsert because there could already be an entry in the vector\n           * for the term we are working with. In that case we just add the scores\n           * together.\n           */\n          queryVectors[field].upsert(termIndex, clause.boost, function (a, b) { return a + b })\n\n          /**\n           * If we've already seen this term, field combo then we've already collected\n           * the matching documents and metadata, no need to go through all that again\n           */\n          if (termFieldCache[termField]) {\n            continue\n          }\n\n          for (var l = 0; l < matchingDocumentRefs.length; l++) {\n            /*\n             * All metadata for this term/field/document triple\n             * are then extracted and collected into an instance\n             * of lunr.MatchData ready to be returned in the query\n             * results\n             */\n            var matchingDocumentRef = matchingDocumentRefs[l],\n                matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field),\n                metadata = fieldPosting[matchingDocumentRef],\n                fieldMatch\n\n            if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) {\n              matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata)\n            } else {\n              fieldMatch.add(expandedTerm, field, metadata)\n            }\n\n          }\n\n          termFieldCache[termField] = true\n        }\n      }\n    }\n\n    /**\n     * If the presence was required we need to update the requiredMatches field sets.\n     * We do this after all fields for the term have collected their matches because\n     * the clause terms presence is required in _any_ of the fields not _all_ of the\n     * fields.\n     */\n    if (clause.presence === lunr.Query.presence.REQUIRED) {\n      for (var k = 0; k < clause.fields.length; k++) {\n        var field = clause.fields[k]\n        requiredMatches[field] = requiredMatches[field].intersect(clauseMatches)\n      }\n    }\n  }\n\n  /**\n   * Need to combine the field scoped required and prohibited\n   * matching documents into a global set of required and prohibited\n   * matches\n   */\n  var allRequiredMatches = lunr.Set.complete,\n      allProhibitedMatches = lunr.Set.empty\n\n  for (var i = 0; i < this.fields.length; i++) {\n    var field = this.fields[i]\n\n    if (requiredMatches[field]) {\n      allRequiredMatches = allRequiredMatches.intersect(requiredMatches[field])\n    }\n\n    if (prohibitedMatches[field]) {\n      allProhibitedMatches = allProhibitedMatches.union(prohibitedMatches[field])\n    }\n  }\n\n  var matchingFieldRefs = Object.keys(matchingFields),\n      results = [],\n      matches = Object.create(null)\n\n  /*\n   * If the query is negated (contains only prohibited terms)\n   * we need to get _all_ fieldRefs currently existing in the\n   * index. This is only done when we know that the query is\n   * entirely prohibited terms to avoid any cost of getting all\n   * fieldRefs unnecessarily.\n   *\n   * Additionally, blank MatchData must be created to correctly\n   * populate the results.\n   */\n  if (query.isNegated()) {\n    matchingFieldRefs = Object.keys(this.fieldVectors)\n\n    for (var i = 0; i < matchingFieldRefs.length; i++) {\n      var matchingFieldRef = matchingFieldRefs[i]\n      var fieldRef = lunr.FieldRef.fromString(matchingFieldRef)\n      matchingFields[matchingFieldRef] = new lunr.MatchData\n    }\n  }\n\n  for (var i = 0; i < matchingFieldRefs.length; i++) {\n    /*\n     * Currently we have document fields that match the query, but we\n     * need to return documents. The matchData and scores are combined\n     * from multiple fields belonging to the same document.\n     *\n     * Scores are calculated by field, using the query vectors created\n     * above, and combined into a final document score using addition.\n     */\n    var fieldRef = lunr.FieldRef.fromString(matchingFieldRefs[i]),\n        docRef = fieldRef.docRef\n\n    if (!allRequiredMatches.contains(docRef)) {\n      continue\n    }\n\n    if (allProhibitedMatches.contains(docRef)) {\n      continue\n    }\n\n    var fieldVector = this.fieldVectors[fieldRef],\n        score = queryVectors[fieldRef.fieldName].similarity(fieldVector),\n        docMatch\n\n    if ((docMatch = matches[docRef]) !== undefined) {\n      docMatch.score += score\n      docMatch.matchData.combine(matchingFields[fieldRef])\n    } else {\n      var match = {\n        ref: docRef,\n        score: score,\n        matchData: matchingFields[fieldRef]\n      }\n      matches[docRef] = match\n      results.push(match)\n    }\n  }\n\n  /*\n   * Sort the results objects by score, highest first.\n   */\n  return results.sort(function (a, b) {\n    return b.score - a.score\n  })\n}\n\n/**\n * Prepares the index for JSON serialization.\n *\n * The schema for this JSON blob will be described in a\n * separate JSON schema file.\n *\n * @returns {Object}\n */\nlunr.Index.prototype.toJSON = function () {\n  var invertedIndex = Object.keys(this.invertedIndex)\n    .sort()\n    .map(function (term) {\n      return [term, this.invertedIndex[term]]\n    }, this)\n\n  var fieldVectors = Object.keys(this.fieldVectors)\n    .map(function (ref) {\n      return [ref, this.fieldVectors[ref].toJSON()]\n    }, this)\n\n  return {\n    version: lunr.version,\n    fields: this.fields,\n    fieldVectors: fieldVectors,\n    invertedIndex: invertedIndex,\n    pipeline: this.pipeline.toJSON()\n  }\n}\n\n/**\n * Loads a previously serialized lunr.Index\n *\n * @param {Object} serializedIndex - A previously serialized lunr.Index\n * @returns {lunr.Index}\n */\nlunr.Index.load = function (serializedIndex) {\n  var attrs = {},\n      fieldVectors = {},\n      serializedVectors = serializedIndex.fieldVectors,\n      invertedIndex = Object.create(null),\n      serializedInvertedIndex = serializedIndex.invertedIndex,\n      tokenSetBuilder = new lunr.TokenSet.Builder,\n      pipeline = lunr.Pipeline.load(serializedIndex.pipeline)\n\n  if (serializedIndex.version != lunr.version) {\n    lunr.utils.warn(\"Version mismatch when loading serialised index. Current version of lunr '\" + lunr.version + \"' does not match serialized index '\" + serializedIndex.version + \"'\")\n  }\n\n  for (var i = 0; i < serializedVectors.length; i++) {\n    var tuple = serializedVectors[i],\n        ref = tuple[0],\n        elements = tuple[1]\n\n    fieldVectors[ref] = new lunr.Vector(elements)\n  }\n\n  for (var i = 0; i < serializedInvertedIndex.length; i++) {\n    var tuple = serializedInvertedIndex[i],\n        term = tuple[0],\n        posting = tuple[1]\n\n    tokenSetBuilder.insert(term)\n    invertedIndex[term] = posting\n  }\n\n  tokenSetBuilder.finish()\n\n  attrs.fields = serializedIndex.fields\n\n  attrs.fieldVectors = fieldVectors\n  attrs.invertedIndex = invertedIndex\n  attrs.tokenSet = tokenSetBuilder.root\n  attrs.pipeline = pipeline\n\n  return new lunr.Index(attrs)\n}\n/*!\n * lunr.Builder\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.Builder performs indexing on a set of documents and\n * returns instances of lunr.Index ready for querying.\n *\n * All configuration of the index is done via the builder, the\n * fields to index, the document reference, the text processing\n * pipeline and document scoring parameters are all set on the\n * builder before indexing.\n *\n * @constructor\n * @property {string} _ref - Internal reference to the document reference field.\n * @property {string[]} _fields - Internal reference to the document fields to index.\n * @property {object} invertedIndex - The inverted index maps terms to document fields.\n * @property {object} documentTermFrequencies - Keeps track of document term frequencies.\n * @property {object} documentLengths - Keeps track of the length of documents added to the index.\n * @property {lunr.tokenizer} tokenizer - Function for splitting strings into tokens for indexing.\n * @property {lunr.Pipeline} pipeline - The pipeline performs text processing on tokens before indexing.\n * @property {lunr.Pipeline} searchPipeline - A pipeline for processing search terms before querying the index.\n * @property {number} documentCount - Keeps track of the total number of documents indexed.\n * @property {number} _b - A parameter to control field length normalization, setting this to 0 disabled normalization, 1 fully normalizes field lengths, the default value is 0.75.\n * @property {number} _k1 - A parameter to control how quickly an increase in term frequency results in term frequency saturation, the default value is 1.2.\n * @property {number} termIndex - A counter incremented for each unique term, used to identify a terms position in the vector space.\n * @property {array} metadataWhitelist - A list of metadata keys that have been whitelisted for entry in the index.\n */\nlunr.Builder = function () {\n  this._ref = \"id\"\n  this._fields = Object.create(null)\n  this._documents = Object.create(null)\n  this.invertedIndex = Object.create(null)\n  this.fieldTermFrequencies = {}\n  this.fieldLengths = {}\n  this.tokenizer = lunr.tokenizer\n  this.pipeline = new lunr.Pipeline\n  this.searchPipeline = new lunr.Pipeline\n  this.documentCount = 0\n  this._b = 0.75\n  this._k1 = 1.2\n  this.termIndex = 0\n  this.metadataWhitelist = []\n}\n\n/**\n * Sets the document field used as the document reference. Every document must have this field.\n * The type of this field in the document should be a string, if it is not a string it will be\n * coerced into a string by calling toString.\n *\n * The default ref is 'id'.\n *\n * The ref should _not_ be changed during indexing, it should be set before any documents are\n * added to the index. Changing it during indexing can lead to inconsistent results.\n *\n * @param {string} ref - The name of the reference field in the document.\n */\nlunr.Builder.prototype.ref = function (ref) {\n  this._ref = ref\n}\n\n/**\n * A function that is used to extract a field from a document.\n *\n * Lunr expects a field to be at the top level of a document, if however the field\n * is deeply nested within a document an extractor function can be used to extract\n * the right field for indexing.\n *\n * @callback fieldExtractor\n * @param {object} doc - The document being added to the index.\n * @returns {?(string|object|object[])} obj - The object that will be indexed for this field.\n * @example <caption>Extracting a nested field</caption>\n * function (doc) { return doc.nested.field }\n */\n\n/**\n * Adds a field to the list of document fields that will be indexed. Every document being\n * indexed should have this field. Null values for this field in indexed documents will\n * not cause errors but will limit the chance of that document being retrieved by searches.\n *\n * All fields should be added before adding documents to the index. Adding fields after\n * a document has been indexed will have no effect on already indexed documents.\n *\n * Fields can be boosted at build time. This allows terms within that field to have more\n * importance when ranking search results. Use a field boost to specify that matches within\n * one field are more important than other fields.\n *\n * @param {string} fieldName - The name of a field to index in all documents.\n * @param {object} attributes - Optional attributes associated with this field.\n * @param {number} [attributes.boost=1] - Boost applied to all terms within this field.\n * @param {fieldExtractor} [attributes.extractor] - Function to extract a field from a document.\n * @throws {RangeError} fieldName cannot contain unsupported characters '/'\n */\nlunr.Builder.prototype.field = function (fieldName, attributes) {\n  if (/\\//.test(fieldName)) {\n    throw new RangeError (\"Field '\" + fieldName + \"' contains illegal character '/'\")\n  }\n\n  this._fields[fieldName] = attributes || {}\n}\n\n/**\n * A parameter to tune the amount of field length normalisation that is applied when\n * calculating relevance scores. A value of 0 will completely disable any normalisation\n * and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b\n * will be clamped to the range 0 - 1.\n *\n * @param {number} number - The value to set for this tuning parameter.\n */\nlunr.Builder.prototype.b = function (number) {\n  if (number < 0) {\n    this._b = 0\n  } else if (number > 1) {\n    this._b = 1\n  } else {\n    this._b = number\n  }\n}\n\n/**\n * A parameter that controls the speed at which a rise in term frequency results in term\n * frequency saturation. The default value is 1.2. Setting this to a higher value will give\n * slower saturation levels, a lower value will result in quicker saturation.\n *\n * @param {number} number - The value to set for this tuning parameter.\n */\nlunr.Builder.prototype.k1 = function (number) {\n  this._k1 = number\n}\n\n/**\n * Adds a document to the index.\n *\n * Before adding fields to the index the index should have been fully setup, with the document\n * ref and all fields to index already having been specified.\n *\n * The document must have a field name as specified by the ref (by default this is 'id') and\n * it should have all fields defined for indexing, though null or undefined values will not\n * cause errors.\n *\n * Entire documents can be boosted at build time. Applying a boost to a document indicates that\n * this document should rank higher in search results than other documents.\n *\n * @param {object} doc - The document to add to the index.\n * @param {object} attributes - Optional attributes associated with this document.\n * @param {number} [attributes.boost=1] - Boost applied to all terms within this document.\n */\nlunr.Builder.prototype.add = function (doc, attributes) {\n  var docRef = doc[this._ref],\n      fields = Object.keys(this._fields)\n\n  this._documents[docRef] = attributes || {}\n  this.documentCount += 1\n\n  for (var i = 0; i < fields.length; i++) {\n    var fieldName = fields[i],\n        extractor = this._fields[fieldName].extractor,\n        field = extractor ? extractor(doc) : doc[fieldName],\n        tokens = this.tokenizer(field, {\n          fields: [fieldName]\n        }),\n        terms = this.pipeline.run(tokens),\n        fieldRef = new lunr.FieldRef (docRef, fieldName),\n        fieldTerms = Object.create(null)\n\n    this.fieldTermFrequencies[fieldRef] = fieldTerms\n    this.fieldLengths[fieldRef] = 0\n\n    // store the length of this field for this document\n    this.fieldLengths[fieldRef] += terms.length\n\n    // calculate term frequencies for this field\n    for (var j = 0; j < terms.length; j++) {\n      var term = terms[j]\n\n      if (fieldTerms[term] == undefined) {\n        fieldTerms[term] = 0\n      }\n\n      fieldTerms[term] += 1\n\n      // add to inverted index\n      // create an initial posting if one doesn't exist\n      if (this.invertedIndex[term] == undefined) {\n        var posting = Object.create(null)\n        posting[\"_index\"] = this.termIndex\n        this.termIndex += 1\n\n        for (var k = 0; k < fields.length; k++) {\n          posting[fields[k]] = Object.create(null)\n        }\n\n        this.invertedIndex[term] = posting\n      }\n\n      // add an entry for this term/fieldName/docRef to the invertedIndex\n      if (this.invertedIndex[term][fieldName][docRef] == undefined) {\n        this.invertedIndex[term][fieldName][docRef] = Object.create(null)\n      }\n\n      // store all whitelisted metadata about this token in the\n      // inverted index\n      for (var l = 0; l < this.metadataWhitelist.length; l++) {\n        var metadataKey = this.metadataWhitelist[l],\n            metadata = term.metadata[metadataKey]\n\n        if (this.invertedIndex[term][fieldName][docRef][metadataKey] == undefined) {\n          this.invertedIndex[term][fieldName][docRef][metadataKey] = []\n        }\n\n        this.invertedIndex[term][fieldName][docRef][metadataKey].push(metadata)\n      }\n    }\n\n  }\n}\n\n/**\n * Calculates the average document length for this index\n *\n * @private\n */\nlunr.Builder.prototype.calculateAverageFieldLengths = function () {\n\n  var fieldRefs = Object.keys(this.fieldLengths),\n      numberOfFields = fieldRefs.length,\n      accumulator = {},\n      documentsWithField = {}\n\n  for (var i = 0; i < numberOfFields; i++) {\n    var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),\n        field = fieldRef.fieldName\n\n    documentsWithField[field] || (documentsWithField[field] = 0)\n    documentsWithField[field] += 1\n\n    accumulator[field] || (accumulator[field] = 0)\n    accumulator[field] += this.fieldLengths[fieldRef]\n  }\n\n  var fields = Object.keys(this._fields)\n\n  for (var i = 0; i < fields.length; i++) {\n    var fieldName = fields[i]\n    accumulator[fieldName] = accumulator[fieldName] / documentsWithField[fieldName]\n  }\n\n  this.averageFieldLength = accumulator\n}\n\n/**\n * Builds a vector space model of every document using lunr.Vector\n *\n * @private\n */\nlunr.Builder.prototype.createFieldVectors = function () {\n  var fieldVectors = {},\n      fieldRefs = Object.keys(this.fieldTermFrequencies),\n      fieldRefsLength = fieldRefs.length,\n      termIdfCache = Object.create(null)\n\n  for (var i = 0; i < fieldRefsLength; i++) {\n    var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),\n        fieldName = fieldRef.fieldName,\n        fieldLength = this.fieldLengths[fieldRef],\n        fieldVector = new lunr.Vector,\n        termFrequencies = this.fieldTermFrequencies[fieldRef],\n        terms = Object.keys(termFrequencies),\n        termsLength = terms.length\n\n\n    var fieldBoost = this._fields[fieldName].boost || 1,\n        docBoost = this._documents[fieldRef.docRef].boost || 1\n\n    for (var j = 0; j < termsLength; j++) {\n      var term = terms[j],\n          tf = termFrequencies[term],\n          termIndex = this.invertedIndex[term]._index,\n          idf, score, scoreWithPrecision\n\n      if (termIdfCache[term] === undefined) {\n        idf = lunr.idf(this.invertedIndex[term], this.documentCount)\n        termIdfCache[term] = idf\n      } else {\n        idf = termIdfCache[term]\n      }\n\n      score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[fieldName])) + tf)\n      score *= fieldBoost\n      score *= docBoost\n      scoreWithPrecision = Math.round(score * 1000) / 1000\n      // Converts 1.23456789 to 1.234.\n      // Reducing the precision so that the vectors take up less\n      // space when serialised. Doing it now so that they behave\n      // the same before and after serialisation. Also, this is\n      // the fastest approach to reducing a number's precision in\n      // JavaScript.\n\n      fieldVector.insert(termIndex, scoreWithPrecision)\n    }\n\n    fieldVectors[fieldRef] = fieldVector\n  }\n\n  this.fieldVectors = fieldVectors\n}\n\n/**\n * Creates a token set of all tokens in the index using lunr.TokenSet\n *\n * @private\n */\nlunr.Builder.prototype.createTokenSet = function () {\n  this.tokenSet = lunr.TokenSet.fromArray(\n    Object.keys(this.invertedIndex).sort()\n  )\n}\n\n/**\n * Builds the index, creating an instance of lunr.Index.\n *\n * This completes the indexing process and should only be called\n * once all documents have been added to the index.\n *\n * @returns {lunr.Index}\n */\nlunr.Builder.prototype.build = function () {\n  this.calculateAverageFieldLengths()\n  this.createFieldVectors()\n  this.createTokenSet()\n\n  return new lunr.Index({\n    invertedIndex: this.invertedIndex,\n    fieldVectors: this.fieldVectors,\n    tokenSet: this.tokenSet,\n    fields: Object.keys(this._fields),\n    pipeline: this.searchPipeline\n  })\n}\n\n/**\n * Applies a plugin to the index builder.\n *\n * A plugin is a function that is called with the index builder as its context.\n * Plugins can be used to customise or extend the behaviour of the index\n * in some way. A plugin is just a function, that encapsulated the custom\n * behaviour that should be applied when building the index.\n *\n * The plugin function will be called with the index builder as its argument, additional\n * arguments can also be passed when calling use. The function will be called\n * with the index builder as its context.\n *\n * @param {Function} plugin The plugin to apply.\n */\nlunr.Builder.prototype.use = function (fn) {\n  var args = Array.prototype.slice.call(arguments, 1)\n  args.unshift(this)\n  fn.apply(this, args)\n}\n/**\n * Contains and collects metadata about a matching document.\n * A single instance of lunr.MatchData is returned as part of every\n * lunr.Index~Result.\n *\n * @constructor\n * @param {string} term - The term this match data is associated with\n * @param {string} field - The field in which the term was found\n * @param {object} metadata - The metadata recorded about this term in this field\n * @property {object} metadata - A cloned collection of metadata associated with this document.\n * @see {@link lunr.Index~Result}\n */\nlunr.MatchData = function (term, field, metadata) {\n  var clonedMetadata = Object.create(null),\n      metadataKeys = Object.keys(metadata || {})\n\n  // Cloning the metadata to prevent the original\n  // being mutated during match data combination.\n  // Metadata is kept in an array within the inverted\n  // index so cloning the data can be done with\n  // Array#slice\n  for (var i = 0; i < metadataKeys.length; i++) {\n    var key = metadataKeys[i]\n    clonedMetadata[key] = metadata[key].slice()\n  }\n\n  this.metadata = Object.create(null)\n\n  if (term !== undefined) {\n    this.metadata[term] = Object.create(null)\n    this.metadata[term][field] = clonedMetadata\n  }\n}\n\n/**\n * An instance of lunr.MatchData will be created for every term that matches a\n * document. However only one instance is required in a lunr.Index~Result. This\n * method combines metadata from another instance of lunr.MatchData with this\n * objects metadata.\n *\n * @param {lunr.MatchData} otherMatchData - Another instance of match data to merge with this one.\n * @see {@link lunr.Index~Result}\n */\nlunr.MatchData.prototype.combine = function (otherMatchData) {\n  var terms = Object.keys(otherMatchData.metadata)\n\n  for (var i = 0; i < terms.length; i++) {\n    var term = terms[i],\n        fields = Object.keys(otherMatchData.metadata[term])\n\n    if (this.metadata[term] == undefined) {\n      this.metadata[term] = Object.create(null)\n    }\n\n    for (var j = 0; j < fields.length; j++) {\n      var field = fields[j],\n          keys = Object.keys(otherMatchData.metadata[term][field])\n\n      if (this.metadata[term][field] == undefined) {\n        this.metadata[term][field] = Object.create(null)\n      }\n\n      for (var k = 0; k < keys.length; k++) {\n        var key = keys[k]\n\n        if (this.metadata[term][field][key] == undefined) {\n          this.metadata[term][field][key] = otherMatchData.metadata[term][field][key]\n        } else {\n          this.metadata[term][field][key] = this.metadata[term][field][key].concat(otherMatchData.metadata[term][field][key])\n        }\n\n      }\n    }\n  }\n}\n\n/**\n * Add metadata for a term/field pair to this instance of match data.\n *\n * @param {string} term - The term this match data is associated with\n * @param {string} field - The field in which the term was found\n * @param {object} metadata - The metadata recorded about this term in this field\n */\nlunr.MatchData.prototype.add = function (term, field, metadata) {\n  if (!(term in this.metadata)) {\n    this.metadata[term] = Object.create(null)\n    this.metadata[term][field] = metadata\n    return\n  }\n\n  if (!(field in this.metadata[term])) {\n    this.metadata[term][field] = metadata\n    return\n  }\n\n  var metadataKeys = Object.keys(metadata)\n\n  for (var i = 0; i < metadataKeys.length; i++) {\n    var key = metadataKeys[i]\n\n    if (key in this.metadata[term][field]) {\n      this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key])\n    } else {\n      this.metadata[term][field][key] = metadata[key]\n    }\n  }\n}\n/**\n * A lunr.Query provides a programmatic way of defining queries to be performed\n * against a {@link lunr.Index}.\n *\n * Prefer constructing a lunr.Query using the {@link lunr.Index#query} method\n * so the query object is pre-initialized with the right index fields.\n *\n * @constructor\n * @property {lunr.Query~Clause[]} clauses - An array of query clauses.\n * @property {string[]} allFields - An array of all available fields in a lunr.Index.\n */\nlunr.Query = function (allFields) {\n  this.clauses = []\n  this.allFields = allFields\n}\n\n/**\n * Constants for indicating what kind of automatic wildcard insertion will be used when constructing a query clause.\n *\n * This allows wildcards to be added to the beginning and end of a term without having to manually do any string\n * concatenation.\n *\n * The wildcard constants can be bitwise combined to select both leading and trailing wildcards.\n *\n * @constant\n * @default\n * @property {number} wildcard.NONE - The term will have no wildcards inserted, this is the default behaviour\n * @property {number} wildcard.LEADING - Prepend the term with a wildcard, unless a leading wildcard already exists\n * @property {number} wildcard.TRAILING - Append a wildcard to the term, unless a trailing wildcard already exists\n * @see lunr.Query~Clause\n * @see lunr.Query#clause\n * @see lunr.Query#term\n * @example <caption>query term with trailing wildcard</caption>\n * query.term('foo', { wildcard: lunr.Query.wildcard.TRAILING })\n * @example <caption>query term with leading and trailing wildcard</caption>\n * query.term('foo', {\n *   wildcard: lunr.Query.wildcard.LEADING | lunr.Query.wildcard.TRAILING\n * })\n */\n\nlunr.Query.wildcard = new String (\"*\")\nlunr.Query.wildcard.NONE = 0\nlunr.Query.wildcard.LEADING = 1\nlunr.Query.wildcard.TRAILING = 2\n\n/**\n * Constants for indicating what kind of presence a term must have in matching documents.\n *\n * @constant\n * @enum {number}\n * @see lunr.Query~Clause\n * @see lunr.Query#clause\n * @see lunr.Query#term\n * @example <caption>query term with required presence</caption>\n * query.term('foo', { presence: lunr.Query.presence.REQUIRED })\n */\nlunr.Query.presence = {\n  /**\n   * Term's presence in a document is optional, this is the default value.\n   */\n  OPTIONAL: 1,\n\n  /**\n   * Term's presence in a document is required, documents that do not contain\n   * this term will not be returned.\n   */\n  REQUIRED: 2,\n\n  /**\n   * Term's presence in a document is prohibited, documents that do contain\n   * this term will not be returned.\n   */\n  PROHIBITED: 3\n}\n\n/**\n * A single clause in a {@link lunr.Query} contains a term and details on how to\n * match that term against a {@link lunr.Index}.\n *\n * @typedef {Object} lunr.Query~Clause\n * @property {string[]} fields - The fields in an index this clause should be matched against.\n * @property {number} [boost=1] - Any boost that should be applied when matching this clause.\n * @property {number} [editDistance] - Whether the term should have fuzzy matching applied, and how fuzzy the match should be.\n * @property {boolean} [usePipeline] - Whether the term should be passed through the search pipeline.\n * @property {number} [wildcard=lunr.Query.wildcard.NONE] - Whether the term should have wildcards appended or prepended.\n * @property {number} [presence=lunr.Query.presence.OPTIONAL] - The terms presence in any matching documents.\n */\n\n/**\n * Adds a {@link lunr.Query~Clause} to this query.\n *\n * Unless the clause contains the fields to be matched all fields will be matched. In addition\n * a default boost of 1 is applied to the clause.\n *\n * @param {lunr.Query~Clause} clause - The clause to add to this query.\n * @see lunr.Query~Clause\n * @returns {lunr.Query}\n */\nlunr.Query.prototype.clause = function (clause) {\n  if (!('fields' in clause)) {\n    clause.fields = this.allFields\n  }\n\n  if (!('boost' in clause)) {\n    clause.boost = 1\n  }\n\n  if (!('usePipeline' in clause)) {\n    clause.usePipeline = true\n  }\n\n  if (!('wildcard' in clause)) {\n    clause.wildcard = lunr.Query.wildcard.NONE\n  }\n\n  if ((clause.wildcard & lunr.Query.wildcard.LEADING) && (clause.term.charAt(0) != lunr.Query.wildcard)) {\n    clause.term = \"*\" + clause.term\n  }\n\n  if ((clause.wildcard & lunr.Query.wildcard.TRAILING) && (clause.term.slice(-1) != lunr.Query.wildcard)) {\n    clause.term = \"\" + clause.term + \"*\"\n  }\n\n  if (!('presence' in clause)) {\n    clause.presence = lunr.Query.presence.OPTIONAL\n  }\n\n  this.clauses.push(clause)\n\n  return this\n}\n\n/**\n * A negated query is one in which every clause has a presence of\n * prohibited. These queries require some special processing to return\n * the expected results.\n *\n * @returns boolean\n */\nlunr.Query.prototype.isNegated = function () {\n  for (var i = 0; i < this.clauses.length; i++) {\n    if (this.clauses[i].presence != lunr.Query.presence.PROHIBITED) {\n      return false\n    }\n  }\n\n  return true\n}\n\n/**\n * Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause}\n * to the list of clauses that make up this query.\n *\n * The term is used as is, i.e. no tokenization will be performed by this method. Instead conversion\n * to a token or token-like string should be done before calling this method.\n *\n * The term will be converted to a string by calling `toString`. Multiple terms can be passed as an\n * array, each term in the array will share the same options.\n *\n * @param {object|object[]} term - The term(s) to add to the query.\n * @param {object} [options] - Any additional properties to add to the query clause.\n * @returns {lunr.Query}\n * @see lunr.Query#clause\n * @see lunr.Query~Clause\n * @example <caption>adding a single term to a query</caption>\n * query.term(\"foo\")\n * @example <caption>adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard</caption>\n * query.term(\"foo\", {\n *   fields: [\"title\"],\n *   boost: 10,\n *   wildcard: lunr.Query.wildcard.TRAILING\n * })\n * @example <caption>using lunr.tokenizer to convert a string to tokens before using them as terms</caption>\n * query.term(lunr.tokenizer(\"foo bar\"))\n */\nlunr.Query.prototype.term = function (term, options) {\n  if (Array.isArray(term)) {\n    term.forEach(function (t) { this.term(t, lunr.utils.clone(options)) }, this)\n    return this\n  }\n\n  var clause = options || {}\n  clause.term = term.toString()\n\n  this.clause(clause)\n\n  return this\n}\nlunr.QueryParseError = function (message, start, end) {\n  this.name = \"QueryParseError\"\n  this.message = message\n  this.start = start\n  this.end = end\n}\n\nlunr.QueryParseError.prototype = new Error\nlunr.QueryLexer = function (str) {\n  this.lexemes = []\n  this.str = str\n  this.length = str.length\n  this.pos = 0\n  this.start = 0\n  this.escapeCharPositions = []\n}\n\nlunr.QueryLexer.prototype.run = function () {\n  var state = lunr.QueryLexer.lexText\n\n  while (state) {\n    state = state(this)\n  }\n}\n\nlunr.QueryLexer.prototype.sliceString = function () {\n  var subSlices = [],\n      sliceStart = this.start,\n      sliceEnd = this.pos\n\n  for (var i = 0; i < this.escapeCharPositions.length; i++) {\n    sliceEnd = this.escapeCharPositions[i]\n    subSlices.push(this.str.slice(sliceStart, sliceEnd))\n    sliceStart = sliceEnd + 1\n  }\n\n  subSlices.push(this.str.slice(sliceStart, this.pos))\n  this.escapeCharPositions.length = 0\n\n  return subSlices.join('')\n}\n\nlunr.QueryLexer.prototype.emit = function (type) {\n  this.lexemes.push({\n    type: type,\n    str: this.sliceString(),\n    start: this.start,\n    end: this.pos\n  })\n\n  this.start = this.pos\n}\n\nlunr.QueryLexer.prototype.escapeCharacter = function () {\n  this.escapeCharPositions.push(this.pos - 1)\n  this.pos += 1\n}\n\nlunr.QueryLexer.prototype.next = function () {\n  if (this.pos >= this.length) {\n    return lunr.QueryLexer.EOS\n  }\n\n  var char = this.str.charAt(this.pos)\n  this.pos += 1\n  return char\n}\n\nlunr.QueryLexer.prototype.width = function () {\n  return this.pos - this.start\n}\n\nlunr.QueryLexer.prototype.ignore = function () {\n  if (this.start == this.pos) {\n    this.pos += 1\n  }\n\n  this.start = this.pos\n}\n\nlunr.QueryLexer.prototype.backup = function () {\n  this.pos -= 1\n}\n\nlunr.QueryLexer.prototype.acceptDigitRun = function () {\n  var char, charCode\n\n  do {\n    char = this.next()\n    charCode = char.charCodeAt(0)\n  } while (charCode > 47 && charCode < 58)\n\n  if (char != lunr.QueryLexer.EOS) {\n    this.backup()\n  }\n}\n\nlunr.QueryLexer.prototype.more = function () {\n  return this.pos < this.length\n}\n\nlunr.QueryLexer.EOS = 'EOS'\nlunr.QueryLexer.FIELD = 'FIELD'\nlunr.QueryLexer.TERM = 'TERM'\nlunr.QueryLexer.EDIT_DISTANCE = 'EDIT_DISTANCE'\nlunr.QueryLexer.BOOST = 'BOOST'\nlunr.QueryLexer.PRESENCE = 'PRESENCE'\n\nlunr.QueryLexer.lexField = function (lexer) {\n  lexer.backup()\n  lexer.emit(lunr.QueryLexer.FIELD)\n  lexer.ignore()\n  return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexTerm = function (lexer) {\n  if (lexer.width() > 1) {\n    lexer.backup()\n    lexer.emit(lunr.QueryLexer.TERM)\n  }\n\n  lexer.ignore()\n\n  if (lexer.more()) {\n    return lunr.QueryLexer.lexText\n  }\n}\n\nlunr.QueryLexer.lexEditDistance = function (lexer) {\n  lexer.ignore()\n  lexer.acceptDigitRun()\n  lexer.emit(lunr.QueryLexer.EDIT_DISTANCE)\n  return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexBoost = function (lexer) {\n  lexer.ignore()\n  lexer.acceptDigitRun()\n  lexer.emit(lunr.QueryLexer.BOOST)\n  return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexEOS = function (lexer) {\n  if (lexer.width() > 0) {\n    lexer.emit(lunr.QueryLexer.TERM)\n  }\n}\n\n// This matches the separator used when tokenising fields\n// within a document. These should match otherwise it is\n// not possible to search for some tokens within a document.\n//\n// It is possible for the user to change the separator on the\n// tokenizer so it _might_ clash with any other of the special\n// characters already used within the search string, e.g. :.\n//\n// This means that it is possible to change the separator in\n// such a way that makes some words unsearchable using a search\n// string.\nlunr.QueryLexer.termSeparator = lunr.tokenizer.separator\n\nlunr.QueryLexer.lexText = function (lexer) {\n  while (true) {\n    var char = lexer.next()\n\n    if (char == lunr.QueryLexer.EOS) {\n      return lunr.QueryLexer.lexEOS\n    }\n\n    // Escape character is '\\'\n    if (char.charCodeAt(0) == 92) {\n      lexer.escapeCharacter()\n      continue\n    }\n\n    if (char == \":\") {\n      return lunr.QueryLexer.lexField\n    }\n\n    if (char == \"~\") {\n      lexer.backup()\n      if (lexer.width() > 0) {\n        lexer.emit(lunr.QueryLexer.TERM)\n      }\n      return lunr.QueryLexer.lexEditDistance\n    }\n\n    if (char == \"^\") {\n      lexer.backup()\n      if (lexer.width() > 0) {\n        lexer.emit(lunr.QueryLexer.TERM)\n      }\n      return lunr.QueryLexer.lexBoost\n    }\n\n    // \"+\" indicates term presence is required\n    // checking for length to ensure that only\n    // leading \"+\" are considered\n    if (char == \"+\" && lexer.width() === 1) {\n      lexer.emit(lunr.QueryLexer.PRESENCE)\n      return lunr.QueryLexer.lexText\n    }\n\n    // \"-\" indicates term presence is prohibited\n    // checking for length to ensure that only\n    // leading \"-\" are considered\n    if (char == \"-\" && lexer.width() === 1) {\n      lexer.emit(lunr.QueryLexer.PRESENCE)\n      return lunr.QueryLexer.lexText\n    }\n\n    if (char.match(lunr.QueryLexer.termSeparator)) {\n      return lunr.QueryLexer.lexTerm\n    }\n  }\n}\n\nlunr.QueryParser = function (str, query) {\n  this.lexer = new lunr.QueryLexer (str)\n  this.query = query\n  this.currentClause = {}\n  this.lexemeIdx = 0\n}\n\nlunr.QueryParser.prototype.parse = function () {\n  this.lexer.run()\n  this.lexemes = this.lexer.lexemes\n\n  var state = lunr.QueryParser.parseClause\n\n  while (state) {\n    state = state(this)\n  }\n\n  return this.query\n}\n\nlunr.QueryParser.prototype.peekLexeme = function () {\n  return this.lexemes[this.lexemeIdx]\n}\n\nlunr.QueryParser.prototype.consumeLexeme = function () {\n  var lexeme = this.peekLexeme()\n  this.lexemeIdx += 1\n  return lexeme\n}\n\nlunr.QueryParser.prototype.nextClause = function () {\n  var completedClause = this.currentClause\n  this.query.clause(completedClause)\n  this.currentClause = {}\n}\n\nlunr.QueryParser.parseClause = function (parser) {\n  var lexeme = parser.peekLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  switch (lexeme.type) {\n    case lunr.QueryLexer.PRESENCE:\n      return lunr.QueryParser.parsePresence\n    case lunr.QueryLexer.FIELD:\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.TERM:\n      return lunr.QueryParser.parseTerm\n    default:\n      var errorMessage = \"expected either a field or a term, found \" + lexeme.type\n\n      if (lexeme.str.length >= 1) {\n        errorMessage += \" with value '\" + lexeme.str + \"'\"\n      }\n\n      throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n}\n\nlunr.QueryParser.parsePresence = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  switch (lexeme.str) {\n    case \"-\":\n      parser.currentClause.presence = lunr.Query.presence.PROHIBITED\n      break\n    case \"+\":\n      parser.currentClause.presence = lunr.Query.presence.REQUIRED\n      break\n    default:\n      var errorMessage = \"unrecognised presence operator'\" + lexeme.str + \"'\"\n      throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    var errorMessage = \"expecting term or field, found nothing\"\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.FIELD:\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.TERM:\n      return lunr.QueryParser.parseTerm\n    default:\n      var errorMessage = \"expecting term or field, found '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\nlunr.QueryParser.parseField = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  if (parser.query.allFields.indexOf(lexeme.str) == -1) {\n    var possibleFields = parser.query.allFields.map(function (f) { return \"'\" + f + \"'\" }).join(', '),\n        errorMessage = \"unrecognised field '\" + lexeme.str + \"', possible fields: \" + possibleFields\n\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  parser.currentClause.fields = [lexeme.str]\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    var errorMessage = \"expecting term, found nothing\"\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.TERM:\n      return lunr.QueryParser.parseTerm\n    default:\n      var errorMessage = \"expecting term, found '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\nlunr.QueryParser.parseTerm = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  parser.currentClause.term = lexeme.str.toLowerCase()\n\n  if (lexeme.str.indexOf(\"*\") != -1) {\n    parser.currentClause.usePipeline = false\n  }\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    parser.nextClause()\n    return\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.TERM:\n      parser.nextClause()\n      return lunr.QueryParser.parseTerm\n    case lunr.QueryLexer.FIELD:\n      parser.nextClause()\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.EDIT_DISTANCE:\n      return lunr.QueryParser.parseEditDistance\n    case lunr.QueryLexer.BOOST:\n      return lunr.QueryParser.parseBoost\n    case lunr.QueryLexer.PRESENCE:\n      parser.nextClause()\n      return lunr.QueryParser.parsePresence\n    default:\n      var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\nlunr.QueryParser.parseEditDistance = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  var editDistance = parseInt(lexeme.str, 10)\n\n  if (isNaN(editDistance)) {\n    var errorMessage = \"edit distance must be numeric\"\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  parser.currentClause.editDistance = editDistance\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    parser.nextClause()\n    return\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.TERM:\n      parser.nextClause()\n      return lunr.QueryParser.parseTerm\n    case lunr.QueryLexer.FIELD:\n      parser.nextClause()\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.EDIT_DISTANCE:\n      return lunr.QueryParser.parseEditDistance\n    case lunr.QueryLexer.BOOST:\n      return lunr.QueryParser.parseBoost\n    case lunr.QueryLexer.PRESENCE:\n      parser.nextClause()\n      return lunr.QueryParser.parsePresence\n    default:\n      var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\nlunr.QueryParser.parseBoost = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  var boost = parseInt(lexeme.str, 10)\n\n  if (isNaN(boost)) {\n    var errorMessage = \"boost must be numeric\"\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  parser.currentClause.boost = boost\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    parser.nextClause()\n    return\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.TERM:\n      parser.nextClause()\n      return lunr.QueryParser.parseTerm\n    case lunr.QueryLexer.FIELD:\n      parser.nextClause()\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.EDIT_DISTANCE:\n      return lunr.QueryParser.parseEditDistance\n    case lunr.QueryLexer.BOOST:\n      return lunr.QueryParser.parseBoost\n    case lunr.QueryLexer.PRESENCE:\n      parser.nextClause()\n      return lunr.QueryParser.parsePresence\n    default:\n      var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\n  /**\n   * export the module via AMD, CommonJS or as a browser global\n   * Export code from https://github.com/umdjs/umd/blob/master/returnExports.js\n   */\n  ;(function (root, factory) {\n    if (typeof define === 'function' && define.amd) {\n      // AMD. Register as an anonymous module.\n      define(factory)\n    } else if (typeof exports === 'object') {\n      /**\n       * Node. Does not work with strict CommonJS, but\n       * only CommonJS-like enviroments that support module.exports,\n       * like Node.\n       */\n      module.exports = factory()\n    } else {\n      // Browser globals (root is window)\n      root.lunr = factory()\n    }\n  }(this, function () {\n    /**\n     * Just return a value to define the module export.\n     * This example returns an object, but the module\n     * can return a function as the exported value.\n     */\n    return lunr\n  }))\n})();\n", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param  {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n  var str = '' + string;\n  var match = matchHtmlRegExp.exec(str);\n\n  if (!match) {\n    return str;\n  }\n\n  var escape;\n  var html = '';\n  var index = 0;\n  var lastIndex = 0;\n\n  for (index = match.index; index < str.length; index++) {\n    switch (str.charCodeAt(index)) {\n      case 34: // \"\n        escape = '&quot;';\n        break;\n      case 38: // &\n        escape = '&amp;';\n        break;\n      case 39: // '\n        escape = '&#39;';\n        break;\n      case 60: // <\n        escape = '&lt;';\n        break;\n      case 62: // >\n        escape = '&gt;';\n        break;\n      default:\n        continue;\n    }\n\n    if (lastIndex !== index) {\n      html += str.substring(lastIndex, index);\n    }\n\n    lastIndex = index + 1;\n    html += escape;\n  }\n\n  return lastIndex !== index\n    ? html + str.substring(lastIndex, index)\n    : html;\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A RTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport lunr from \"lunr\"\n\nimport \"~/polyfills\"\n\nimport { Search, SearchIndexConfig } from \"../../_\"\nimport {\n  SearchMessage,\n  SearchMessageType\n} from \"../message\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Add support for usage with `iframe-worker` polyfill\n *\n * While `importScripts` is synchronous when executed inside of a web worker,\n * it's not possible to provide a synchronous polyfilled implementation. The\n * cool thing is that awaiting a non-Promise is a noop, so extending the type\n * definition to return a `Promise` shouldn't break anything.\n *\n * @see https://bit.ly/2PjDnXi - GitHub comment\n */\ndeclare global {\n  function importScripts(...urls: string[]): Promise<void> | void\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Search index\n */\nlet index: Search\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch (= import) multi-language support through `lunr-languages`\n *\n * This function automatically imports the stemmers necessary to process the\n * languages, which are defined through the search index configuration.\n *\n * If the worker runs inside of an `iframe` (when using `iframe-worker` as\n * a shim), the base URL for the stemmers to be loaded must be determined by\n * searching for the first `script` element with a `src` attribute, which will\n * contain the contents of this script.\n *\n * @param config - Search index configuration\n *\n * @returns Promise resolving with no result\n */\nasync function setupSearchLanguages(\n  config: SearchIndexConfig\n): Promise<void> {\n  let base = \"../lunr\"\n\n  /* Detect `iframe-worker` and fix base URL */\n  if (typeof parent !== \"undefined\" && \"IFrameWorker\" in parent) {\n    const worker = document.querySelector<HTMLScriptElement>(\"script[src]\")!\n    const [path] = worker.src.split(\"/worker\")\n\n    /* Prefix base with path */\n    base = base.replace(\"..\", path)\n  }\n\n  /* Add scripts for languages */\n  const scripts = []\n  for (const lang of config.lang) {\n    switch (lang) {\n\n      /* Add segmenter for Japanese */\n      case \"ja\":\n        scripts.push(`${base}/tinyseg.js`)\n        break\n\n      /* Add segmenter for Hindi and Thai */\n      case \"hi\":\n      case \"th\":\n        scripts.push(`${base}/wordcut.js`)\n        break\n    }\n\n    /* Add language support */\n    if (lang !== \"en\")\n      scripts.push(`${base}/min/lunr.${lang}.min.js`)\n  }\n\n  /* Add multi-language support */\n  if (config.lang.length > 1)\n    scripts.push(`${base}/min/lunr.multi.min.js`)\n\n  /* Load scripts synchronously */\n  if (scripts.length)\n    await importScripts(\n      `${base}/min/lunr.stemmer.support.min.js`,\n      ...scripts\n    )\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Message handler\n *\n * @param message - Source message\n *\n * @returns Target message\n */\nexport async function handler(\n  message: SearchMessage\n): Promise<SearchMessage> {\n  switch (message.type) {\n\n    /* Search setup message */\n    case SearchMessageType.SETUP:\n      await setupSearchLanguages(message.data.config)\n      index = new Search(message.data)\n      return {\n        type: SearchMessageType.READY\n      }\n\n    /* Search query message */\n    case SearchMessageType.QUERY:\n      return {\n        type: SearchMessageType.RESULT,\n        data: index ? index.search(message.data) : { items: [] }\n      }\n\n    /* All other messages */\n    default:\n      throw new TypeError(\"Invalid message type\")\n  }\n}\n\n/* ----------------------------------------------------------------------------\n * Worker\n * ------------------------------------------------------------------------- */\n\n/* @ts-expect-error - expose Lunr.js in global scope, or stemmers won't work */\nself.lunr = lunr\n\n/* Handle messages */\naddEventListener(\"message\", async ev => {\n  postMessage(await handler(ev.data))\n})\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Polyfills\n * ------------------------------------------------------------------------- */\n\n/* Polyfill `Object.entries` */\nif (!Object.entries)\n  Object.entries = function (obj: object) {\n    const data: [string, string][] = []\n    for (const key of Object.keys(obj))\n      // @ts-expect-error - ignore property access warning\n      data.push([key, obj[key]])\n\n    /* Return entries */\n    return data\n  }\n\n/* Polyfill `Object.values` */\nif (!Object.values)\n  Object.values = function (obj: object) {\n    const data: string[] = []\n    for (const key of Object.keys(obj))\n      // @ts-expect-error - ignore property access warning\n      data.push(obj[key])\n\n    /* Return values */\n    return data\n  }\n\n/* ------------------------------------------------------------------------- */\n\n/* Polyfills for `Element` */\nif (typeof Element !== \"undefined\") {\n\n  /* Polyfill `Element.scrollTo` */\n  if (!Element.prototype.scrollTo)\n    Element.prototype.scrollTo = function (\n      x?: ScrollToOptions | number, y?: number\n    ): void {\n      if (typeof x === \"object\") {\n        this.scrollLeft = x.left!\n        this.scrollTop = x.top!\n      } else {\n        this.scrollLeft = x!\n        this.scrollTop = y!\n      }\n    }\n\n  /* Polyfill `Element.replaceWith` */\n  if (!Element.prototype.replaceWith)\n    Element.prototype.replaceWith = function (\n      ...nodes: Array<string | Node>\n    ): void {\n      const parent = this.parentNode\n      if (parent) {\n        if (nodes.length === 0)\n          parent.removeChild(this)\n\n        /* Replace children and create text nodes */\n        for (let i = nodes.length - 1; i >= 0; i--) {\n          let node = nodes[i]\n          if (typeof node !== \"object\")\n            node = document.createTextNode(node)\n          else if (node.parentNode)\n            node.parentNode.removeChild(node)\n\n          /* Replace child or insert before previous sibling */\n          if (!i)\n            parent.replaceChild(node, this)\n          else\n            parent.insertBefore(this.previousSibling!, node)\n        }\n      }\n    }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport escapeHTML from \"escape-html\"\n\nimport { SearchIndexDocument } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search document\n */\nexport interface SearchDocument extends SearchIndexDocument {\n  parent?: SearchIndexDocument         /* Parent article */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search document mapping\n */\nexport type SearchDocumentMap = Map<string, SearchDocument>\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create a search document mapping\n *\n * @param docs - Search index documents\n *\n * @returns Search document map\n */\nexport function setupSearchDocumentMap(\n  docs: SearchIndexDocument[]\n): SearchDocumentMap {\n  const documents = new Map<string, SearchDocument>()\n  const parents   = new Set<SearchDocument>()\n  for (const doc of docs) {\n    const [path, hash] = doc.location.split(\"#\")\n\n    /* Extract location, title and tags */\n    const location = doc.location\n    const title    = doc.title\n    const tags     = doc.tags\n\n    /* Escape and cleanup text */\n    const text = escapeHTML(doc.text)\n      .replace(/\\s+(?=[,.:;!?])/g, \"\")\n      .replace(/\\s+/g, \" \")\n\n    /* Handle section */\n    if (hash) {\n      const parent = documents.get(path)!\n\n      /* Ignore first section, override article */\n      if (!parents.has(parent)) {\n        parent.title = doc.title\n        parent.text  = text\n\n        /* Remember that we processed the article */\n        parents.add(parent)\n\n      /* Add subsequent section */\n      } else {\n        documents.set(location, {\n          location,\n          title,\n          text,\n          parent\n        })\n      }\n\n    /* Add article */\n    } else {\n      documents.set(location, {\n        location,\n        title,\n        text,\n        ...tags && { tags }\n      })\n    }\n  }\n  return documents\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport escapeHTML from \"escape-html\"\n\nimport { SearchIndexConfig } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search highlight function\n *\n * @param value - Value\n *\n * @returns Highlighted value\n */\nexport type SearchHighlightFn = (value: string) => string\n\n/**\n * Search highlight factory function\n *\n * @param query - Query value\n *\n * @returns Search highlight function\n */\nexport type SearchHighlightFactoryFn = (query: string) => SearchHighlightFn\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create a search highlighter\n *\n * @param config - Search index configuration\n * @param escape - Whether to escape HTML\n *\n * @returns Search highlight factory function\n */\nexport function setupSearchHighlighter(\n  config: SearchIndexConfig, escape: boolean\n): SearchHighlightFactoryFn {\n  const separator = new RegExp(config.separator, \"img\")\n  const highlight = (_: unknown, data: string, term: string) => {\n    return `${data}<mark data-md-highlight>${term}</mark>`\n  }\n\n  /* Return factory function */\n  return (query: string) => {\n    query = query\n      .replace(/[\\s*+\\-:~^]+/g, \" \")\n      .trim()\n\n    /* Create search term match expression */\n    const match = new RegExp(`(^|${config.separator})(${\n      query\n        .replace(/[|\\\\{}()[\\]^$+*?.-]/g, \"\\\\$&\")\n        .replace(separator, \"|\")\n    })`, \"img\")\n\n    /* Highlight string value */\n    return value => (\n      escape\n        ? escapeHTML(value)\n        : value\n      )\n        .replace(match, highlight)\n        .replace(/<\\/mark>(\\s+)<mark[^>]*>/img, \"$1\")\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search query clause\n */\nexport interface SearchQueryClause {\n  presence: lunr.Query.presence        /* Clause presence */\n  term: string                         /* Clause term */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search query terms\n */\nexport type SearchQueryTerms = Record<string, boolean>\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Parse a search query for analysis\n *\n * @param value - Query value\n *\n * @returns Search query clauses\n */\nexport function parseSearchQuery(\n  value: string\n): SearchQueryClause[] {\n  const query  = new (lunr as any).Query([\"title\", \"text\"])\n  const parser = new (lunr as any).QueryParser(value, query)\n\n  /* Parse and return query clauses */\n  parser.parse()\n  return query.clauses\n}\n\n/**\n * Analyze the search query clauses in regard to the search terms found\n *\n * @param query - Search query clauses\n * @param terms - Search terms\n *\n * @returns Search query terms\n */\nexport function getSearchQueryTerms(\n  query: SearchQueryClause[], terms: string[]\n): SearchQueryTerms {\n  const clauses = new Set<SearchQueryClause>(query)\n\n  /* Match query clauses against terms */\n  const result: SearchQueryTerms = {}\n  for (let t = 0; t < terms.length; t++)\n    for (const clause of clauses)\n      if (terms[t].startsWith(clause.term)) {\n        result[clause.term] = true\n        clauses.delete(clause)\n      }\n\n  /* Annotate unmatched non-stopword query clauses */\n  for (const clause of clauses)\n    if (lunr.stopWordFilter?.(clause.term as any))\n      result[clause.term] = false\n\n  /* Return query terms */\n  return result\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  SearchDocument,\n  SearchDocumentMap,\n  setupSearchDocumentMap\n} from \"../document\"\nimport {\n  SearchHighlightFactoryFn,\n  setupSearchHighlighter\n} from \"../highlighter\"\nimport { SearchOptions } from \"../options\"\nimport {\n  SearchQueryTerms,\n  getSearchQueryTerms,\n  parseSearchQuery\n} from \"../query\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search index configuration\n */\nexport interface SearchIndexConfig {\n  lang: string[]                       /* Search languages */\n  separator: string                    /* Search separator */\n}\n\n/**\n * Search index document\n */\nexport interface SearchIndexDocument {\n  location: string                     /* Document location */\n  title: string                        /* Document title */\n  text: string                         /* Document text */\n  tags?: string[]                      /* Document tags */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search index\n *\n * This interfaces describes the format of the `search_index.json` file which\n * is automatically built by the MkDocs search plugin.\n */\nexport interface SearchIndex {\n  config: SearchIndexConfig            /* Search index configuration */\n  docs: SearchIndexDocument[]          /* Search index documents */\n  options: SearchOptions               /* Search options */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search metadata\n */\nexport interface SearchMetadata {\n  score: number                        /* Score (relevance) */\n  terms: SearchQueryTerms              /* Search query terms */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search result document\n */\nexport type SearchResultDocument = SearchDocument & SearchMetadata\n\n/**\n * Search result item\n */\nexport type SearchResultItem = SearchResultDocument[]\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search result\n */\nexport interface SearchResult {\n  items: SearchResultItem[]            /* Search result items */\n  suggestions?: string[]               /* Search suggestions */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Compute the difference of two lists of strings\n *\n * @param a - 1st list of strings\n * @param b - 2nd list of strings\n *\n * @returns Difference\n */\nfunction difference(a: string[], b: string[]): string[] {\n  const [x, y] = [new Set(a), new Set(b)]\n  return [\n    ...new Set([...x].filter(value => !y.has(value)))\n  ]\n}\n\n/* ----------------------------------------------------------------------------\n * Class\n * ------------------------------------------------------------------------- */\n\n/**\n * Search index\n */\nexport class Search {\n\n  /**\n   * Search document mapping\n   *\n   * A mapping of URLs (including hash fragments) to the actual articles and\n   * sections of the documentation. The search document mapping must be created\n   * regardless of whether the index was prebuilt or not, as Lunr.js itself\n   * only stores the actual index.\n   */\n  protected documents: SearchDocumentMap\n\n  /**\n   * Search highlight factory function\n   */\n  protected highlight: SearchHighlightFactoryFn\n\n  /**\n   * The underlying Lunr.js search index\n   */\n  protected index: lunr.Index\n\n  /**\n   * Search options\n   */\n  protected options: SearchOptions\n\n  /**\n   * Create the search integration\n   *\n   * @param data - Search index\n   */\n  public constructor({ config, docs, options }: SearchIndex) {\n    this.options = options\n\n    /* Set up document map and highlighter factory */\n    this.documents = setupSearchDocumentMap(docs)\n    this.highlight = setupSearchHighlighter(config, false)\n\n    /* Set separator for tokenizer */\n    lunr.tokenizer.separator = new RegExp(config.separator)\n\n    /* Create search index */\n    this.index = lunr(function () {\n\n      /* Set up multi-language support */\n      if (config.lang.length === 1 && config.lang[0] !== \"en\") {\n        this.use((lunr as any)[config.lang[0]])\n      } else if (config.lang.length > 1) {\n        this.use((lunr as any).multiLanguage(...config.lang))\n      }\n\n      /* Compute functions to be removed from the pipeline */\n      const fns = difference([\n        \"trimmer\", \"stopWordFilter\", \"stemmer\"\n      ], options.pipeline)\n\n      /* Remove functions from the pipeline for registered languages */\n      for (const lang of config.lang.map(language => (\n        language === \"en\" ? lunr : (lunr as any)[language]\n      ))) {\n        for (const fn of fns) {\n          this.pipeline.remove(lang[fn])\n          this.searchPipeline.remove(lang[fn])\n        }\n      }\n\n      /* Set up reference */\n      this.ref(\"location\")\n\n      /* Set up fields */\n      this.field(\"title\", { boost: 1e3 })\n      this.field(\"text\")\n      this.field(\"tags\", { boost: 1e6 })\n\n      /* Index documents */\n      for (const doc of docs)\n        this.add(doc)\n    })\n  }\n\n  /**\n   * Search for matching documents\n   *\n   * The search index which MkDocs provides is divided up into articles, which\n   * contain the whole content of the individual pages, and sections, which only\n   * contain the contents of the subsections obtained by breaking the individual\n   * pages up at `h1` ... `h6`. As there may be many sections on different pages\n   * with identical titles (for example within this very project, e.g. \"Usage\"\n   * or \"Installation\"), they need to be put into the context of the containing\n   * page. For this reason, section results are grouped within their respective\n   * articles which are the top-level results that are returned.\n   *\n   * @param query - Query value\n   *\n   * @returns Search results\n   */\n  public search(query: string): SearchResult {\n    if (query) {\n      try {\n        const highlight = this.highlight(query)\n\n        /* Parse query to extract clauses for analysis */\n        const clauses = parseSearchQuery(query)\n          .filter(clause => (\n            clause.presence !== lunr.Query.presence.PROHIBITED\n          ))\n\n        /* Perform search and post-process results */\n        const groups = this.index.search(`${query}*`)\n\n          /* Apply post-query boosts based on title and search query terms */\n          .reduce<SearchResultItem>((item, { ref, score, matchData }) => {\n            const document = this.documents.get(ref)\n            if (typeof document !== \"undefined\") {\n              const { location, title, text, tags, parent } = document\n\n              /* Compute and analyze search query terms */\n              const terms = getSearchQueryTerms(\n                clauses,\n                Object.keys(matchData.metadata)\n              )\n\n              /* Highlight title and text and apply post-query boosts */\n              const boost = +!parent + +Object.values(terms).every(t => t)\n              item.push({\n                location,\n                title: highlight(title),\n                text:  highlight(text),\n                ...tags && { tags: tags.map(highlight) },\n                score: score * (1 + boost),\n                terms\n              })\n            }\n            return item\n          }, [])\n\n          /* Sort search results again after applying boosts */\n          .sort((a, b) => b.score - a.score)\n\n          /* Group search results by page */\n          .reduce((items, result) => {\n            const document = this.documents.get(result.location)\n            if (typeof document !== \"undefined\") {\n              const ref = \"parent\" in document\n                ? document.parent!.location\n                : document.location\n              items.set(ref, [...items.get(ref) || [], result])\n            }\n            return items\n          }, new Map<string, SearchResultItem>())\n\n        /* Generate search suggestions, if desired */\n        let suggestions: string[] | undefined\n        if (this.options.suggestions) {\n          const titles = this.index.query(builder => {\n            for (const clause of clauses)\n              builder.term(clause.term, {\n                fields: [\"title\"],\n                presence: lunr.Query.presence.REQUIRED,\n                wildcard: lunr.Query.wildcard.TRAILING\n              })\n          })\n\n          /* Retrieve suggestions for best match */\n          suggestions = titles.length\n            ? Object.keys(titles[0].matchData.metadata)\n            : []\n        }\n\n        /* Return items and suggestions */\n        return {\n          items: [...groups.values()],\n          ...typeof suggestions !== \"undefined\" && { suggestions }\n        }\n\n      /* Log errors to console (for now) */\n      } catch {\n        console.warn(`Invalid query: ${query} \u2013 see https://bit.ly/2s3ChXG`)\n      }\n    }\n\n    /* Return nothing in case of error or empty query */\n    return { items: [] }\n  }\n}\n"],
-  "mappings": "mkCAAA;AAAA;AAAA;AAAA;AAAA,GAMC,AAAC,WAAU,CAiCZ,GAAI,GAAO,SAAU,EAAQ,CAC3B,GAAI,GAAU,GAAI,GAAK,QAEvB,SAAQ,SAAS,IACf,EAAK,QACL,EAAK,eACL,EAAK,OACP,EAEA,EAAQ,eAAe,IACrB,EAAK,OACP,EAEA,EAAO,KAAK,EAAS,CAAO,EACrB,EAAQ,MAAM,CACvB,EAEA,EAAK,QAAU,QACf;AAAA;AAAA;AAAA,GASA,EAAK,MAAQ,CAAC,EASd,EAAK,MAAM,KAAQ,SAAU,EAAQ,CAEnC,MAAO,UAAU,EAAS,CACxB,AAAI,EAAO,SAAW,QAAQ,MAC5B,QAAQ,KAAK,CAAO,CAExB,CAEF,EAAG,IAAI,EAaP,EAAK,MAAM,SAAW,SAAU,EAAK,CACnC,MAAI,AAAkB,IAAQ,KACrB,GAEA,EAAI,SAAS,CAExB,EAkBA,EAAK,MAAM,MAAQ,SAAU,EAAK,CAChC,GAAI,GAAQ,KACV,MAAO,GAMT,OAHI,GAAQ,OAAO,OAAO,IAAI,EAC1B,EAAO,OAAO,KAAK,CAAG,EAEjB,EAAI,EAAG,EAAI,EAAK,OAAQ,IAAK,CACpC,GAAI,GAAM,EAAK,GACX,EAAM,EAAI,GAEd,GAAI,MAAM,QAAQ,CAAG,EAAG,CACtB,EAAM,GAAO,EAAI,MAAM,EACvB,QACF,CAEA,GAAI,MAAO,IAAQ,UACf,MAAO,IAAQ,UACf,MAAO,IAAQ,UAAW,CAC5B,EAAM,GAAO,EACb,QACF,CAEA,KAAM,IAAI,WAAU,uDAAuD,CAC7E,CAEA,MAAO,EACT,EACA,EAAK,SAAW,SAAU,EAAQ,EAAW,EAAa,CACxD,KAAK,OAAS,EACd,KAAK,UAAY,EACjB,KAAK,aAAe,CACtB,EAEA,EAAK,SAAS,OAAS,IAEvB,EAAK,SAAS,WAAa,SAAU,EAAG,CACtC,GAAI,GAAI,EAAE,QAAQ,EAAK,SAAS,MAAM,EAEtC,GAAI,IAAM,GACR,KAAM,6BAGR,GAAI,GAAW,EAAE,MAAM,EAAG,CAAC,EACvB,EAAS,EAAE,MAAM,EAAI,CAAC,EAE1B,MAAO,IAAI,GAAK,SAAU,EAAQ,EAAU,CAAC,CAC/C,EAEA,EAAK,SAAS,UAAU,SAAW,UAAY,CAC7C,MAAI,MAAK,cAAgB,MACvB,MAAK,aAAe,KAAK,UAAY,EAAK,SAAS,OAAS,KAAK,QAG5D,KAAK,YACd,EACA;AAAA;AAAA;AAAA,GAUA,EAAK,IAAM,SAAU,EAAU,CAG7B,GAFA,KAAK,SAAW,OAAO,OAAO,IAAI,EAE9B,EAAU,CACZ,KAAK,OAAS,EAAS,OAEvB,OAAS,GAAI,EAAG,EAAI,KAAK,OAAQ,IAC/B,KAAK,SAAS,EAAS,IAAM,EAEjC,KACE,MAAK,OAAS,CAElB,EASA,EAAK,IAAI,SAAW,CAClB,UAAW,SAAU,EAAO,CAC1B,MAAO,EACT,EAEA,MAAO,UAAY,CACjB,MAAO,KACT,EAEA,SAAU,UAAY,CACpB,MAAO,EACT,CACF,EASA,EAAK,IAAI,MAAQ,CACf,UAAW,UAAY,CACrB,MAAO,KACT,EAEA,MAAO,SAAU,EAAO,CACtB,MAAO,EACT,EAEA,SAAU,UAAY,CACpB,MAAO,EACT,CACF,EAQA,EAAK,IAAI,UAAU,SAAW,SAAU,EAAQ,CAC9C,MAAO,CAAC,CAAC,KAAK,SAAS,EACzB,EAUA,EAAK,IAAI,UAAU,UAAY,SAAU,EAAO,CAC9C,GAAI,GAAG,EAAG,EAAU,EAAe,CAAC,EAEpC,GAAI,IAAU,EAAK,IAAI,SACrB,MAAO,MAGT,GAAI,IAAU,EAAK,IAAI,MACrB,MAAO,GAGT,AAAI,KAAK,OAAS,EAAM,OACtB,GAAI,KACJ,EAAI,GAEJ,GAAI,EACJ,EAAI,MAGN,EAAW,OAAO,KAAK,EAAE,QAAQ,EAEjC,OAAS,GAAI,EAAG,EAAI,EAAS,OAAQ,IAAK,CACxC,GAAI,GAAU,EAAS,GACvB,AAAI,IAAW,GAAE,UACf,EAAa,KAAK,CAAO,CAE7B,CAEA,MAAO,IAAI,GAAK,IAAK,CAAY,CACnC,EASA,EAAK,IAAI,UAAU,MAAQ,SAAU,EAAO,CAC1C,MAAI,KAAU,EAAK,IAAI,SACd,EAAK,IAAI,SAGd,IAAU,EAAK,IAAI,MACd,KAGF,GAAI,GAAK,IAAI,OAAO,KAAK,KAAK,QAAQ,EAAE,OAAO,OAAO,KAAK,EAAM,QAAQ,CAAC,CAAC,CACpF,EASA,EAAK,IAAM,SAAU,EAAS,EAAe,CAC3C,GAAI,GAAoB,EAExB,OAAS,KAAa,GACpB,AAAI,GAAa,UACjB,IAAqB,OAAO,KAAK,EAAQ,EAAU,EAAE,QAGvD,GAAI,GAAK,GAAgB,EAAoB,IAAQ,GAAoB,IAEzE,MAAO,MAAK,IAAI,EAAI,KAAK,IAAI,CAAC,CAAC,CACjC,EAUA,EAAK,MAAQ,SAAU,EAAK,EAAU,CACpC,KAAK,IAAM,GAAO,GAClB,KAAK,SAAW,GAAY,CAAC,CAC/B,EAOA,EAAK,MAAM,UAAU,SAAW,UAAY,CAC1C,MAAO,MAAK,GACd,EAsBA,EAAK,MAAM,UAAU,OAAS,SAAU,EAAI,CAC1C,YAAK,IAAM,EAAG,KAAK,IAAK,KAAK,QAAQ,EAC9B,IACT,EASA,EAAK,MAAM,UAAU,MAAQ,SAAU,EAAI,CACzC,SAAK,GAAM,SAAU,EAAG,CAAE,MAAO,EAAE,EAC5B,GAAI,GAAK,MAAO,EAAG,KAAK,IAAK,KAAK,QAAQ,EAAG,KAAK,QAAQ,CACnE,EACA;AAAA;AAAA;AAAA,GAuBA,EAAK,UAAY,SAAU,EAAK,EAAU,CACxC,GAAI,GAAO,MAAQ,GAAO,KACxB,MAAO,CAAC,EAGV,GAAI,MAAM,QAAQ,CAAG,EACnB,MAAO,GAAI,IAAI,SAAU,EAAG,CAC1B,MAAO,IAAI,GAAK,MACd,EAAK,MAAM,SAAS,CAAC,EAAE,YAAY,EACnC,EAAK,MAAM,MAAM,CAAQ,CAC3B,CACF,CAAC,EAOH,OAJI,GAAM,EAAI,SAAS,EAAE,YAAY,EACjC,EAAM,EAAI,OACV,EAAS,CAAC,EAEL,EAAW,EAAG,EAAa,EAAG,GAAY,EAAK,IAAY,CAClE,GAAI,GAAO,EAAI,OAAO,CAAQ,EAC1B,EAAc,EAAW,EAE7B,GAAK,EAAK,MAAM,EAAK,UAAU,SAAS,GAAK,GAAY,EAAM,CAE7D,GAAI,EAAc,EAAG,CACnB,GAAI,GAAgB,EAAK,MAAM,MAAM,CAAQ,GAAK,CAAC,EACnD,EAAc,SAAc,CAAC,EAAY,CAAW,EACpD,EAAc,MAAW,EAAO,OAEhC,EAAO,KACL,GAAI,GAAK,MACP,EAAI,MAAM,EAAY,CAAQ,EAC9B,CACF,CACF,CACF,CAEA,EAAa,EAAW,CAC1B,CAEF,CAEA,MAAO,EACT,EASA,EAAK,UAAU,UAAY,UAC3B;AAAA;AAAA;AAAA,GAkCA,EAAK,SAAW,UAAY,CAC1B,KAAK,OAAS,CAAC,CACjB,EAEA,EAAK,SAAS,oBAAsB,OAAO,OAAO,IAAI,EAmCtD,EAAK,SAAS,iBAAmB,SAAU,EAAI,EAAO,CACpD,AAAI,IAAS,MAAK,qBAChB,EAAK,MAAM,KAAK,6CAA+C,CAAK,EAGtE,EAAG,MAAQ,EACX,EAAK,SAAS,oBAAoB,EAAG,OAAS,CAChD,EAQA,EAAK,SAAS,4BAA8B,SAAU,EAAI,CACxD,GAAI,GAAe,EAAG,OAAU,EAAG,QAAS,MAAK,oBAEjD,AAAK,GACH,EAAK,MAAM,KAAK;AAAA,EAAmG,CAAE,CAEzH,EAYA,EAAK,SAAS,KAAO,SAAU,EAAY,CACzC,GAAI,GAAW,GAAI,GAAK,SAExB,SAAW,QAAQ,SAAU,EAAQ,CACnC,GAAI,GAAK,EAAK,SAAS,oBAAoB,GAE3C,GAAI,EACF,EAAS,IAAI,CAAE,MAEf,MAAM,IAAI,OAAM,sCAAwC,CAAM,CAElE,CAAC,EAEM,CACT,EASA,EAAK,SAAS,UAAU,IAAM,UAAY,CACxC,GAAI,GAAM,MAAM,UAAU,MAAM,KAAK,SAAS,EAE9C,EAAI,QAAQ,SAAU,EAAI,CACxB,EAAK,SAAS,4BAA4B,CAAE,EAC5C,KAAK,OAAO,KAAK,CAAE,CACrB,EAAG,IAAI,CACT,EAWA,EAAK,SAAS,UAAU,MAAQ,SAAU,EAAY,EAAO,CAC3D,EAAK,SAAS,4BAA4B,CAAK,EAE/C,GAAI,GAAM,KAAK,OAAO,QAAQ,CAAU,EACxC,GAAI,GAAO,GACT,KAAM,IAAI,OAAM,wBAAwB,EAG1C,EAAM,EAAM,EACZ,KAAK,OAAO,OAAO,EAAK,EAAG,CAAK,CAClC,EAWA,EAAK,SAAS,UAAU,OAAS,SAAU,EAAY,EAAO,CAC5D,EAAK,SAAS,4BAA4B,CAAK,EAE/C,GAAI,GAAM,KAAK,OAAO,QAAQ,CAAU,EACxC,GAAI,GAAO,GACT,KAAM,IAAI,OAAM,wBAAwB,EAG1C,KAAK,OAAO,OAAO,EAAK,EAAG,CAAK,CAClC,EAOA,EAAK,SAAS,UAAU,OAAS,SAAU,EAAI,CAC7C,GAAI,GAAM,KAAK,OAAO,QAAQ,CAAE,EAChC,AAAI,GAAO,IAIX,KAAK,OAAO,OAAO,EAAK,CAAC,CAC3B,EASA,EAAK,SAAS,UAAU,IAAM,SAAU,EAAQ,CAG9C,OAFI,GAAc,KAAK,OAAO,OAErB,EAAI,EAAG,EAAI,EAAa,IAAK,CAIpC,OAHI,GAAK,KAAK,OAAO,GACjB,EAAO,CAAC,EAEH,EAAI,EAAG,EAAI,EAAO,OAAQ,IAAK,CACtC,GAAI,GAAS,EAAG,EAAO,GAAI,EAAG,CAAM,EAEpC,GAAI,KAAW,MAA6B,IAAW,IAEvD,GAAI,MAAM,QAAQ,CAAM,EACtB,OAAS,GAAI,EAAG,EAAI,EAAO,OAAQ,IACjC,EAAK,KAAK,EAAO,EAAE,MAGrB,GAAK,KAAK,CAAM,CAEpB,CAEA,EAAS,CACX,CAEA,MAAO,EACT,EAYA,EAAK,SAAS,UAAU,UAAY,SAAU,EAAK,EAAU,CAC3D,GAAI,GAAQ,GAAI,GAAK,MAAO,EAAK,CAAQ,EAEzC,MAAO,MAAK,IAAI,CAAC,CAAK,CAAC,EAAE,IAAI,SAAU,EAAG,CACxC,MAAO,GAAE,SAAS,CACpB,CAAC,CACH,EAMA,EAAK,SAAS,UAAU,MAAQ,UAAY,CAC1C,KAAK,OAAS,CAAC,CACjB,EASA,EAAK,SAAS,UAAU,OAAS,UAAY,CAC3C,MAAO,MAAK,OAAO,IAAI,SAAU,EAAI,CACnC,SAAK,SAAS,4BAA4B,CAAE,EAErC,EAAG,KACZ,CAAC,CACH,EACA;AAAA;AAAA;AAAA,GAqBA,EAAK,OAAS,SAAU,EAAU,CAChC,KAAK,WAAa,EAClB,KAAK,SAAW,GAAY,CAAC,CAC/B,EAaA,EAAK,OAAO,UAAU,iBAAmB,SAAU,EAAO,CAExD,GAAI,KAAK,SAAS,QAAU,EAC1B,MAAO,GAST,OANI,GAAQ,EACR,EAAM,KAAK,SAAS,OAAS,EAC7B,EAAc,EAAM,EACpB,EAAa,KAAK,MAAM,EAAc,CAAC,EACvC,EAAa,KAAK,SAAS,EAAa,GAErC,EAAc,GACf,GAAa,GACf,GAAQ,GAGN,EAAa,GACf,GAAM,GAGJ,GAAc,IAIlB,EAAc,EAAM,EACpB,EAAa,EAAQ,KAAK,MAAM,EAAc,CAAC,EAC/C,EAAa,KAAK,SAAS,EAAa,GAO1C,GAJI,GAAc,GAId,EAAa,EACf,MAAO,GAAa,EAGtB,GAAI,EAAa,EACf,MAAQ,GAAa,GAAK,CAE9B,EAWA,EAAK,OAAO,UAAU,OAAS,SAAU,EAAW,EAAK,CACvD,KAAK,OAAO,EAAW,EAAK,UAAY,CACtC,KAAM,iBACR,CAAC,CACH,EAUA,EAAK,OAAO,UAAU,OAAS,SAAU,EAAW,EAAK,EAAI,CAC3D,KAAK,WAAa,EAClB,GAAI,GAAW,KAAK,iBAAiB,CAAS,EAE9C,AAAI,KAAK,SAAS,IAAa,EAC7B,KAAK,SAAS,EAAW,GAAK,EAAG,KAAK,SAAS,EAAW,GAAI,CAAG,EAEjE,KAAK,SAAS,OAAO,EAAU,EAAG,EAAW,CAAG,CAEpD,EAOA,EAAK,OAAO,UAAU,UAAY,UAAY,CAC5C,GAAI,KAAK,WAAY,MAAO,MAAK,WAKjC,OAHI,GAAe,EACf,EAAiB,KAAK,SAAS,OAE1B,EAAI,EAAG,EAAI,EAAgB,GAAK,EAAG,CAC1C,GAAI,GAAM,KAAK,SAAS,GACxB,GAAgB,EAAM,CACxB,CAEA,MAAO,MAAK,WAAa,KAAK,KAAK,CAAY,CACjD,EAQA,EAAK,OAAO,UAAU,IAAM,SAAU,EAAa,CAOjD,OANI,GAAa,EACb,EAAI,KAAK,SAAU,EAAI,EAAY,SACnC,EAAO,EAAE,OAAQ,EAAO,EAAE,OAC1B,EAAO,EAAG,EAAO,EACjB,EAAI,EAAG,EAAI,EAER,EAAI,GAAQ,EAAI,GACrB,EAAO,EAAE,GAAI,EAAO,EAAE,GACtB,AAAI,EAAO,EACT,GAAK,EACA,AAAI,EAAO,EAChB,GAAK,EACI,GAAQ,GACjB,IAAc,EAAE,EAAI,GAAK,EAAE,EAAI,GAC/B,GAAK,EACL,GAAK,GAIT,MAAO,EACT,EASA,EAAK,OAAO,UAAU,WAAa,SAAU,EAAa,CACxD,MAAO,MAAK,IAAI,CAAW,EAAI,KAAK,UAAU,GAAK,CACrD,EAOA,EAAK,OAAO,UAAU,QAAU,UAAY,CAG1C,OAFI,GAAS,GAAI,OAAO,KAAK,SAAS,OAAS,CAAC,EAEvC,EAAI,EAAG,EAAI,EAAG,EAAI,KAAK,SAAS,OAAQ,GAAK,EAAG,IACvD,EAAO,GAAK,KAAK,SAAS,GAG5B,MAAO,EACT,EAOA,EAAK,OAAO,UAAU,OAAS,UAAY,CACzC,MAAO,MAAK,QACd,EAEA;AAAA;AAAA;AAAA;AAAA,GAiBA,EAAK,QAAW,UAAU,CACxB,GAAI,GAAY,CACZ,QAAY,MACZ,OAAW,OACX,KAAS,OACT,KAAS,OACT,KAAS,MACT,IAAQ,MACR,KAAS,KACT,MAAU,MACV,IAAQ,IACR,MAAU,MACV,QAAY,MACZ,MAAU,MACV,KAAS,MACT,MAAU,KACV,QAAY,MACZ,QAAY,MACZ,QAAY,MACZ,MAAU,KACV,MAAU,MACV,OAAW,MACX,KAAS,KACX,EAEA,EAAY,CACV,MAAU,KACV,MAAU,GACV,MAAU,KACV,MAAU,KACV,KAAS,KACT,IAAQ,GACR,KAAS,EACX,EAEA,EAAI,WACJ,EAAI,WACJ,EAAI,EAAI,aACR,EAAI,EAAI,WAER,EAAO,KAAO,EAAI,KAAO,EAAI,EAC7B,EAAO,KAAO,EAAI,KAAO,EAAI,EAAI,IAAM,EAAI,MAC3C,EAAO,KAAO,EAAI,KAAO,EAAI,EAAI,EAAI,EACrC,EAAM,KAAO,EAAI,KAAO,EAEtB,EAAU,GAAI,QAAO,CAAI,EACzB,EAAU,GAAI,QAAO,CAAI,EACzB,EAAU,GAAI,QAAO,CAAI,EACzB,EAAS,GAAI,QAAO,CAAG,EAEvB,EAAQ,kBACR,EAAS,iBACT,EAAQ,aACR,EAAS,kBACT,EAAU,KACV,EAAW,cACX,EAAW,GAAI,QAAO,oBAAoB,EAC1C,EAAW,GAAI,QAAO,IAAM,EAAI,EAAI,cAAc,EAElD,EAAQ,mBACR,EAAO,2IAEP,EAAO,iDAEP,EAAO,sFACP,EAAQ,oBAER,EAAO,WACP,EAAS,MACT,EAAQ,GAAI,QAAO,IAAM,EAAI,EAAI,cAAc,EAE/C,EAAgB,SAAuB,EAAG,CAC5C,GAAI,GACF,EACA,EACA,EACA,EACA,EACA,EAEF,GAAI,EAAE,OAAS,EAAK,MAAO,GAiB3B,GAfA,EAAU,EAAE,OAAO,EAAE,CAAC,EAClB,GAAW,KACb,GAAI,EAAQ,YAAY,EAAI,EAAE,OAAO,CAAC,GAIxC,EAAK,EACL,EAAM,EAEN,AAAI,EAAG,KAAK,CAAC,EAAK,EAAI,EAAE,QAAQ,EAAG,MAAM,EAChC,EAAI,KAAK,CAAC,GAAK,GAAI,EAAE,QAAQ,EAAI,MAAM,GAGhD,EAAK,EACL,EAAM,EACF,EAAG,KAAK,CAAC,EAAG,CACd,GAAI,GAAK,EAAG,KAAK,CAAC,EAClB,EAAK,EACD,EAAG,KAAK,EAAG,EAAE,GACf,GAAK,EACL,EAAI,EAAE,QAAQ,EAAG,EAAE,EAEvB,SAAW,EAAI,KAAK,CAAC,EAAG,CACtB,GAAI,GAAK,EAAI,KAAK,CAAC,EACnB,EAAO,EAAG,GACV,EAAM,EACF,EAAI,KAAK,CAAI,GACf,GAAI,EACJ,EAAM,EACN,EAAM,EACN,EAAM,EACN,AAAI,EAAI,KAAK,CAAC,EAAK,EAAI,EAAI,IACtB,AAAI,EAAI,KAAK,CAAC,EAAK,GAAK,EAAS,EAAI,EAAE,QAAQ,EAAG,EAAE,GAChD,EAAI,KAAK,CAAC,GAAK,GAAI,EAAI,KAEpC,CAIA,GADA,EAAK,EACD,EAAG,KAAK,CAAC,EAAG,CACd,GAAI,GAAK,EAAG,KAAK,CAAC,EAClB,EAAO,EAAG,GACV,EAAI,EAAO,GACb,CAIA,GADA,EAAK,EACD,EAAG,KAAK,CAAC,EAAG,CACd,GAAI,GAAK,EAAG,KAAK,CAAC,EAClB,EAAO,EAAG,GACV,EAAS,EAAG,GACZ,EAAK,EACD,EAAG,KAAK,CAAI,GACd,GAAI,EAAO,EAAU,GAEzB,CAIA,GADA,EAAK,EACD,EAAG,KAAK,CAAC,EAAG,CACd,GAAI,GAAK,EAAG,KAAK,CAAC,EAClB,EAAO,EAAG,GACV,EAAS,EAAG,GACZ,EAAK,EACD,EAAG,KAAK,CAAI,GACd,GAAI,EAAO,EAAU,GAEzB,CAKA,GAFA,EAAK,EACL,EAAM,EACF,EAAG,KAAK,CAAC,EAAG,CACd,GAAI,GAAK,EAAG,KAAK,CAAC,EAClB,EAAO,EAAG,GACV,EAAK,EACD,EAAG,KAAK,CAAI,GACd,GAAI,EAER,SAAW,EAAI,KAAK,CAAC,EAAG,CACtB,GAAI,GAAK,EAAI,KAAK,CAAC,EACnB,EAAO,EAAG,GAAK,EAAG,GAClB,EAAM,EACF,EAAI,KAAK,CAAI,GACf,GAAI,EAER,CAIA,GADA,EAAK,EACD,EAAG,KAAK,CAAC,EAAG,CACd,GAAI,GAAK,EAAG,KAAK,CAAC,EAClB,EAAO,EAAG,GACV,EAAK,EACL,EAAM,EACN,EAAM,EACF,GAAG,KAAK,CAAI,GAAM,EAAI,KAAK,CAAI,GAAK,CAAE,EAAI,KAAK,CAAI,IACrD,GAAI,EAER,CAEA,SAAK,EACL,EAAM,EACF,EAAG,KAAK,CAAC,GAAK,EAAI,KAAK,CAAC,GAC1B,GAAK,EACL,EAAI,EAAE,QAAQ,EAAG,EAAE,GAKjB,GAAW,KACb,GAAI,EAAQ,YAAY,EAAI,EAAE,OAAO,CAAC,GAGjC,CACT,EAEA,MAAO,UAAU,EAAO,CACtB,MAAO,GAAM,OAAO,CAAa,CACnC,CACF,EAAG,EAEH,EAAK,SAAS,iBAAiB,EAAK,QAAS,SAAS,EACtD;AAAA;AAAA;AAAA,GAkBA,EAAK,uBAAyB,SAAU,EAAW,CACjD,GAAI,GAAQ,EAAU,OAAO,SAAU,EAAM,EAAU,CACrD,SAAK,GAAY,EACV,CACT,EAAG,CAAC,CAAC,EAEL,MAAO,UAAU,EAAO,CACtB,GAAI,GAAS,EAAM,EAAM,SAAS,KAAO,EAAM,SAAS,EAAG,MAAO,EACpE,CACF,EAeA,EAAK,eAAiB,EAAK,uBAAuB,CAChD,IACA,OACA,QACA,SACA,QACA,MACA,SACA,OACA,KACA,QACA,KACA,MACA,MACA,MACA,KACA,KACA,KACA,UACA,OACA,MACA,KACA,MACA,SACA,QACA,OACA,MACA,KACA,OACA,SACA,OACA,OACA,QACA,MACA,OACA,MACA,MACA,MACA,MACA,OACA,KACA,MACA,OACA,MACA,MACA,MACA,UACA,IACA,KACA,KACA,OACA,KACA,KACA,MACA,OACA,QACA,MACA,OACA,SACA,MACA,KACA,QACA,OACA,OACA,KACA,UACA,KACA,MACA,MACA,KACA,MACA,QACA,KACA,OACA,KACA,QACA,MACA,MACA,SACA,OACA,MACA,OACA,MACA,SACA,QACA,KACA,OACA,OACA,OACA,MACA,QACA,OACA,OACA,QACA,QACA,OACA,OACA,MACA,KACA,MACA,OACA,KACA,QACA,MACA,KACA,OACA,OACA,OACA,QACA,QACA,QACA,MACA,OACA,MACA,OACA,OACA,QACA,MACA,MACA,MACF,CAAC,EAED,EAAK,SAAS,iBAAiB,EAAK,eAAgB,gBAAgB,EACpE;AAAA;AAAA;AAAA,GAoBA,EAAK,QAAU,SAAU,EAAO,CAC9B,MAAO,GAAM,OAAO,SAAU,EAAG,CAC/B,MAAO,GAAE,QAAQ,OAAQ,EAAE,EAAE,QAAQ,OAAQ,EAAE,CACjD,CAAC,CACH,EAEA,EAAK,SAAS,iBAAiB,EAAK,QAAS,SAAS,EACtD;AAAA;AAAA;AAAA,GA0BA,EAAK,SAAW,UAAY,CAC1B,KAAK,MAAQ,GACb,KAAK,MAAQ,CAAC,EACd,KAAK,GAAK,EAAK,SAAS,QACxB,EAAK,SAAS,SAAW,CAC3B,EAUA,EAAK,SAAS,QAAU,EASxB,EAAK,SAAS,UAAY,SAAU,EAAK,CAGvC,OAFI,GAAU,GAAI,GAAK,SAAS,QAEvB,EAAI,EAAG,EAAM,EAAI,OAAQ,EAAI,EAAK,IACzC,EAAQ,OAAO,EAAI,EAAE,EAGvB,SAAQ,OAAO,EACR,EAAQ,IACjB,EAWA,EAAK,SAAS,WAAa,SAAU,EAAQ,CAC3C,MAAI,gBAAkB,GACb,EAAK,SAAS,gBAAgB,EAAO,KAAM,EAAO,YAAY,EAE9D,EAAK,SAAS,WAAW,EAAO,IAAI,CAE/C,EAiBA,EAAK,SAAS,gBAAkB,SAAU,EAAK,EAAc,CAS3D,OARI,GAAO,GAAI,GAAK,SAEhB,EAAQ,CAAC,CACX,KAAM,EACN,eAAgB,EAChB,IAAK,CACP,CAAC,EAEM,EAAM,QAAQ,CACnB,GAAI,GAAQ,EAAM,IAAI,EAGtB,GAAI,EAAM,IAAI,OAAS,EAAG,CACxB,GAAI,GAAO,EAAM,IAAI,OAAO,CAAC,EACzB,EAEJ,AAAI,IAAQ,GAAM,KAAK,MACrB,EAAa,EAAM,KAAK,MAAM,GAE9B,GAAa,GAAI,GAAK,SACtB,EAAM,KAAK,MAAM,GAAQ,GAGvB,EAAM,IAAI,QAAU,GACtB,GAAW,MAAQ,IAGrB,EAAM,KAAK,CACT,KAAM,EACN,eAAgB,EAAM,eACtB,IAAK,EAAM,IAAI,MAAM,CAAC,CACxB,CAAC,CACH,CAEA,GAAI,EAAM,gBAAkB,EAK5B,IAAI,KAAO,GAAM,KAAK,MACpB,GAAI,GAAgB,EAAM,KAAK,MAAM,SAChC,CACL,GAAI,GAAgB,GAAI,GAAK,SAC7B,EAAM,KAAK,MAAM,KAAO,CAC1B,CAgCA,GA9BI,EAAM,IAAI,QAAU,GACtB,GAAc,MAAQ,IAGxB,EAAM,KAAK,CACT,KAAM,EACN,eAAgB,EAAM,eAAiB,EACvC,IAAK,EAAM,GACb,CAAC,EAKG,EAAM,IAAI,OAAS,GACrB,EAAM,KAAK,CACT,KAAM,EAAM,KACZ,eAAgB,EAAM,eAAiB,EACvC,IAAK,EAAM,IAAI,MAAM,CAAC,CACxB,CAAC,EAKC,EAAM,IAAI,QAAU,GACtB,GAAM,KAAK,MAAQ,IAMjB,EAAM,IAAI,QAAU,EAAG,CACzB,GAAI,KAAO,GAAM,KAAK,MACpB,GAAI,GAAmB,EAAM,KAAK,MAAM,SACnC,CACL,GAAI,GAAmB,GAAI,GAAK,SAChC,EAAM,KAAK,MAAM,KAAO,CAC1B,CAEA,AAAI,EAAM,IAAI,QAAU,GACtB,GAAiB,MAAQ,IAG3B,EAAM,KAAK,CACT,KAAM,EACN,eAAgB,EAAM,eAAiB,EACvC,IAAK,EAAM,IAAI,MAAM,CAAC,CACxB,CAAC,CACH,CAKA,GAAI,EAAM,IAAI,OAAS,EAAG,CACxB,GAAI,GAAQ,EAAM,IAAI,OAAO,CAAC,EAC1B,EAAQ,EAAM,IAAI,OAAO,CAAC,EAC1B,EAEJ,AAAI,IAAS,GAAM,KAAK,MACtB,EAAgB,EAAM,KAAK,MAAM,GAEjC,GAAgB,GAAI,GAAK,SACzB,EAAM,KAAK,MAAM,GAAS,GAGxB,EAAM,IAAI,QAAU,GACtB,GAAc,MAAQ,IAGxB,EAAM,KAAK,CACT,KAAM,EACN,eAAgB,EAAM,eAAiB,EACvC,IAAK,EAAQ,EAAM,IAAI,MAAM,CAAC,CAChC,CAAC,CACH,EACF,CAEA,MAAO,EACT,EAYA,EAAK,SAAS,WAAa,SAAU,EAAK,CAYxC,OAXI,GAAO,GAAI,GAAK,SAChB,EAAO,EAUF,EAAI,EAAG,EAAM,EAAI,OAAQ,EAAI,EAAK,IAAK,CAC9C,GAAI,GAAO,EAAI,GACX,EAAS,GAAK,EAAM,EAExB,GAAI,GAAQ,IACV,EAAK,MAAM,GAAQ,EACnB,EAAK,MAAQ,MAER,CACL,GAAI,GAAO,GAAI,GAAK,SACpB,EAAK,MAAQ,EAEb,EAAK,MAAM,GAAQ,EACnB,EAAO,CACT,CACF,CAEA,MAAO,EACT,EAYA,EAAK,SAAS,UAAU,QAAU,UAAY,CAQ5C,OAPI,GAAQ,CAAC,EAET,EAAQ,CAAC,CACX,OAAQ,GACR,KAAM,IACR,CAAC,EAEM,EAAM,QAAQ,CACnB,GAAI,GAAQ,EAAM,IAAI,EAClB,EAAQ,OAAO,KAAK,EAAM,KAAK,KAAK,EACpC,EAAM,EAAM,OAEhB,AAAI,EAAM,KAAK,OAKb,GAAM,OAAO,OAAO,CAAC,EACrB,EAAM,KAAK,EAAM,MAAM,GAGzB,OAAS,GAAI,EAAG,EAAI,EAAK,IAAK,CAC5B,GAAI,GAAO,EAAM,GAEjB,EAAM,KAAK,CACT,OAAQ,EAAM,OAAO,OAAO,CAAI,EAChC,KAAM,EAAM,KAAK,MAAM,EACzB,CAAC,CACH,CACF,CAEA,MAAO,EACT,EAYA,EAAK,SAAS,UAAU,SAAW,UAAY,CAS7C,GAAI,KAAK,KACP,MAAO,MAAK,KAOd,OAJI,GAAM,KAAK,MAAQ,IAAM,IACzB,EAAS,OAAO,KAAK,KAAK,KAAK,EAAE,KAAK,EACtC,EAAM,EAAO,OAER,EAAI,EAAG,EAAI,EAAK,IAAK,CAC5B,GAAI,GAAQ,EAAO,GACf,EAAO,KAAK,MAAM,GAEtB,EAAM,EAAM,EAAQ,EAAK,EAC3B,CAEA,MAAO,EACT,EAYA,EAAK,SAAS,UAAU,UAAY,SAAU,EAAG,CAU/C,OATI,GAAS,GAAI,GAAK,SAClB,EAAQ,OAER,EAAQ,CAAC,CACX,MAAO,EACP,OAAQ,EACR,KAAM,IACR,CAAC,EAEM,EAAM,QAAQ,CACnB,EAAQ,EAAM,IAAI,EAWlB,OALI,GAAS,OAAO,KAAK,EAAM,MAAM,KAAK,EACtC,EAAO,EAAO,OACd,EAAS,OAAO,KAAK,EAAM,KAAK,KAAK,EACrC,EAAO,EAAO,OAET,EAAI,EAAG,EAAI,EAAM,IAGxB,OAFI,GAAQ,EAAO,GAEV,EAAI,EAAG,EAAI,EAAM,IAAK,CAC7B,GAAI,GAAQ,EAAO,GAEnB,GAAI,GAAS,GAAS,GAAS,IAAK,CAClC,GAAI,GAAO,EAAM,KAAK,MAAM,GACxB,EAAQ,EAAM,MAAM,MAAM,GAC1B,EAAQ,EAAK,OAAS,EAAM,MAC5B,EAAO,OAEX,AAAI,IAAS,GAAM,OAAO,MAIxB,GAAO,EAAM,OAAO,MAAM,GAC1B,EAAK,MAAQ,EAAK,OAAS,GAM3B,GAAO,GAAI,GAAK,SAChB,EAAK,MAAQ,EACb,EAAM,OAAO,MAAM,GAAS,GAG9B,EAAM,KAAK,CACT,MAAO,EACP,OAAQ,EACR,KAAM,CACR,CAAC,CACH,CACF,CAEJ,CAEA,MAAO,EACT,EACA,EAAK,SAAS,QAAU,UAAY,CAClC,KAAK,aAAe,GACpB,KAAK,KAAO,GAAI,GAAK,SACrB,KAAK,eAAiB,CAAC,EACvB,KAAK,eAAiB,CAAC,CACzB,EAEA,EAAK,SAAS,QAAQ,UAAU,OAAS,SAAU,EAAM,CACvD,GAAI,GACA,EAAe,EAEnB,GAAI,EAAO,KAAK,aACd,KAAM,IAAI,OAAO,6BAA6B,EAGhD,OAAS,GAAI,EAAG,EAAI,EAAK,QAAU,EAAI,KAAK,aAAa,QACnD,EAAK,IAAM,KAAK,aAAa,GAD8B,IAE/D,IAGF,KAAK,SAAS,CAAY,EAE1B,AAAI,KAAK,eAAe,QAAU,EAChC,EAAO,KAAK,KAEZ,EAAO,KAAK,eAAe,KAAK,eAAe,OAAS,GAAG,MAG7D,OAAS,GAAI,EAAc,EAAI,EAAK,OAAQ,IAAK,CAC/C,GAAI,GAAW,GAAI,GAAK,SACpB,EAAO,EAAK,GAEhB,EAAK,MAAM,GAAQ,EAEnB,KAAK,eAAe,KAAK,CACvB,OAAQ,EACR,KAAM,EACN,MAAO,CACT,CAAC,EAED,EAAO,CACT,CAEA,EAAK,MAAQ,GACb,KAAK,aAAe,CACtB,EAEA,EAAK,SAAS,QAAQ,UAAU,OAAS,UAAY,CACnD,KAAK,SAAS,CAAC,CACjB,EAEA,EAAK,SAAS,QAAQ,UAAU,SAAW,SAAU,EAAQ,CAC3D,OAAS,GAAI,KAAK,eAAe,OAAS,EAAG,GAAK,EAAQ,IAAK,CAC7D,GAAI,GAAO,KAAK,eAAe,GAC3B,EAAW,EAAK,MAAM,SAAS,EAEnC,AAAI,IAAY,MAAK,eACnB,EAAK,OAAO,MAAM,EAAK,MAAQ,KAAK,eAAe,GAInD,GAAK,MAAM,KAAO,EAElB,KAAK,eAAe,GAAY,EAAK,OAGvC,KAAK,eAAe,IAAI,CAC1B,CACF,EACA;AAAA;AAAA;AAAA,GAqBA,EAAK,MAAQ,SAAU,EAAO,CAC5B,KAAK,cAAgB,EAAM,cAC3B,KAAK,aAAe,EAAM,aAC1B,KAAK,SAAW,EAAM,SACtB,KAAK,OAAS,EAAM,OACpB,KAAK,SAAW,EAAM,QACxB,EAyEA,EAAK,MAAM,UAAU,OAAS,SAAU,EAAa,CACnD,MAAO,MAAK,MAAM,SAAU,EAAO,CACjC,GAAI,GAAS,GAAI,GAAK,YAAY,EAAa,CAAK,EACpD,EAAO,MAAM,CACf,CAAC,CACH,EA2BA,EAAK,MAAM,UAAU,MAAQ,SAAU,EAAI,CAoBzC,OAZI,GAAQ,GAAI,GAAK,MAAM,KAAK,MAAM,EAClC,EAAiB,OAAO,OAAO,IAAI,EACnC,EAAe,OAAO,OAAO,IAAI,EACjC,EAAiB,OAAO,OAAO,IAAI,EACnC,EAAkB,OAAO,OAAO,IAAI,EACpC,EAAoB,OAAO,OAAO,IAAI,EAOjC,EAAI,EAAG,EAAI,KAAK,OAAO,OAAQ,IACtC,EAAa,KAAK,OAAO,IAAM,GAAI,GAAK,OAG1C,EAAG,KAAK,EAAO,CAAK,EAEpB,OAAS,GAAI,EAAG,EAAI,EAAM,QAAQ,OAAQ,IAAK,CAS7C,GAAI,GAAS,EAAM,QAAQ,GACvB,EAAQ,KACR,EAAgB,EAAK,IAAI,MAE7B,AAAI,EAAO,YACT,EAAQ,KAAK,SAAS,UAAU,EAAO,KAAM,CAC3C,OAAQ,EAAO,MACjB,CAAC,EAED,EAAQ,CAAC,EAAO,IAAI,EAGtB,OAAS,GAAI,EAAG,EAAI,EAAM,OAAQ,IAAK,CACrC,GAAI,GAAO,EAAM,GAQjB,EAAO,KAAO,EAOd,GAAI,GAAe,EAAK,SAAS,WAAW,CAAM,EAC9C,EAAgB,KAAK,SAAS,UAAU,CAAY,EAAE,QAAQ,EAQlE,GAAI,EAAc,SAAW,GAAK,EAAO,WAAa,EAAK,MAAM,SAAS,SAAU,CAClF,OAAS,GAAI,EAAG,EAAI,EAAO,OAAO,OAAQ,IAAK,CAC7C,GAAI,GAAQ,EAAO,OAAO,GAC1B,EAAgB,GAAS,EAAK,IAAI,KACpC,CAEA,KACF,CAEA,OAAS,GAAI,EAAG,EAAI,EAAc,OAAQ,IASxC,OAJI,GAAe,EAAc,GAC7B,EAAU,KAAK,cAAc,GAC7B,EAAY,EAAQ,OAEf,EAAI,EAAG,EAAI,EAAO,OAAO,OAAQ,IAAK,CAS7C,GAAI,GAAQ,EAAO,OAAO,GACtB,EAAe,EAAQ,GACvB,EAAuB,OAAO,KAAK,CAAY,EAC/C,EAAY,EAAe,IAAM,EACjC,EAAuB,GAAI,GAAK,IAAI,CAAoB,EAoB5D,GAbI,EAAO,UAAY,EAAK,MAAM,SAAS,UACzC,GAAgB,EAAc,MAAM,CAAoB,EAEpD,EAAgB,KAAW,QAC7B,GAAgB,GAAS,EAAK,IAAI,WASlC,EAAO,UAAY,EAAK,MAAM,SAAS,WAAY,CACrD,AAAI,EAAkB,KAAW,QAC/B,GAAkB,GAAS,EAAK,IAAI,OAGtC,EAAkB,GAAS,EAAkB,GAAO,MAAM,CAAoB,EAO9E,QACF,CAeA,GANA,EAAa,GAAO,OAAO,EAAW,EAAO,MAAO,SAAU,GAAG,GAAG,CAAE,MAAO,IAAI,EAAE,CAAC,EAMhF,GAAe,GAInB,QAAS,GAAI,EAAG,EAAI,EAAqB,OAAQ,IAAK,CAOpD,GAAI,GAAsB,EAAqB,GAC3C,EAAmB,GAAI,GAAK,SAAU,EAAqB,CAAK,EAChE,EAAW,EAAa,GACxB,EAEJ,AAAK,GAAa,EAAe,MAAuB,OACtD,EAAe,GAAoB,GAAI,GAAK,UAAW,EAAc,EAAO,CAAQ,EAEpF,EAAW,IAAI,EAAc,EAAO,CAAQ,CAGhD,CAEA,EAAe,GAAa,GAC9B,CAEJ,CAQA,GAAI,EAAO,WAAa,EAAK,MAAM,SAAS,SAC1C,OAAS,GAAI,EAAG,EAAI,EAAO,OAAO,OAAQ,IAAK,CAC7C,GAAI,GAAQ,EAAO,OAAO,GAC1B,EAAgB,GAAS,EAAgB,GAAO,UAAU,CAAa,CACzE,CAEJ,CAUA,OAHI,GAAqB,EAAK,IAAI,SAC9B,EAAuB,EAAK,IAAI,MAE3B,EAAI,EAAG,EAAI,KAAK,OAAO,OAAQ,IAAK,CAC3C,GAAI,GAAQ,KAAK,OAAO,GAExB,AAAI,EAAgB,IAClB,GAAqB,EAAmB,UAAU,EAAgB,EAAM,GAGtE,EAAkB,IACpB,GAAuB,EAAqB,MAAM,EAAkB,EAAM,EAE9E,CAEA,GAAI,GAAoB,OAAO,KAAK,CAAc,EAC9C,EAAU,CAAC,EACX,EAAU,OAAO,OAAO,IAAI,EAYhC,GAAI,EAAM,UAAU,EAAG,CACrB,EAAoB,OAAO,KAAK,KAAK,YAAY,EAEjD,OAAS,GAAI,EAAG,EAAI,EAAkB,OAAQ,IAAK,CACjD,GAAI,GAAmB,EAAkB,GACrC,EAAW,EAAK,SAAS,WAAW,CAAgB,EACxD,EAAe,GAAoB,GAAI,GAAK,SAC9C,CACF,CAEA,OAAS,GAAI,EAAG,EAAI,EAAkB,OAAQ,IAAK,CASjD,GAAI,GAAW,EAAK,SAAS,WAAW,EAAkB,EAAE,EACxD,EAAS,EAAS,OAEtB,GAAI,EAAC,EAAmB,SAAS,CAAM,GAInC,GAAqB,SAAS,CAAM,EAIxC,IAAI,GAAc,KAAK,aAAa,GAChC,EAAQ,EAAa,EAAS,WAAW,WAAW,CAAW,EAC/D,EAEJ,GAAK,GAAW,EAAQ,MAAa,OACnC,EAAS,OAAS,EAClB,EAAS,UAAU,QAAQ,EAAe,EAAS,MAC9C,CACL,GAAI,GAAQ,CACV,IAAK,EACL,MAAO,EACP,UAAW,EAAe,EAC5B,EACA,EAAQ,GAAU,EAClB,EAAQ,KAAK,CAAK,CACpB,EACF,CAKA,MAAO,GAAQ,KAAK,SAAU,GAAG,GAAG,CAClC,MAAO,IAAE,MAAQ,GAAE,KACrB,CAAC,CACH,EAUA,EAAK,MAAM,UAAU,OAAS,UAAY,CACxC,GAAI,GAAgB,OAAO,KAAK,KAAK,aAAa,EAC/C,KAAK,EACL,IAAI,SAAU,EAAM,CACnB,MAAO,CAAC,EAAM,KAAK,cAAc,EAAK,CACxC,EAAG,IAAI,EAEL,EAAe,OAAO,KAAK,KAAK,YAAY,EAC7C,IAAI,SAAU,EAAK,CAClB,MAAO,CAAC,EAAK,KAAK,aAAa,GAAK,OAAO,CAAC,CAC9C,EAAG,IAAI,EAET,MAAO,CACL,QAAS,EAAK,QACd,OAAQ,KAAK,OACb,aAAc,EACd,cAAe,EACf,SAAU,KAAK,SAAS,OAAO,CACjC,CACF,EAQA,EAAK,MAAM,KAAO,SAAU,EAAiB,CAC3C,GAAI,GAAQ,CAAC,EACT,EAAe,CAAC,EAChB,EAAoB,EAAgB,aACpC,EAAgB,OAAO,OAAO,IAAI,EAClC,EAA0B,EAAgB,cAC1C,EAAkB,GAAI,GAAK,SAAS,QACpC,EAAW,EAAK,SAAS,KAAK,EAAgB,QAAQ,EAE1D,AAAI,EAAgB,SAAW,EAAK,SAClC,EAAK,MAAM,KAAK,4EAA8E,EAAK,QAAU,sCAAwC,EAAgB,QAAU,GAAG,EAGpL,OAAS,GAAI,EAAG,EAAI,EAAkB,OAAQ,IAAK,CACjD,GAAI,GAAQ,EAAkB,GAC1B,EAAM,EAAM,GACZ,EAAW,EAAM,GAErB,EAAa,GAAO,GAAI,GAAK,OAAO,CAAQ,CAC9C,CAEA,OAAS,GAAI,EAAG,EAAI,EAAwB,OAAQ,IAAK,CACvD,GAAI,GAAQ,EAAwB,GAChC,EAAO,EAAM,GACb,EAAU,EAAM,GAEpB,EAAgB,OAAO,CAAI,EAC3B,EAAc,GAAQ,CACxB,CAEA,SAAgB,OAAO,EAEvB,EAAM,OAAS,EAAgB,OAE/B,EAAM,aAAe,EACrB,EAAM,cAAgB,EACtB,EAAM,SAAW,EAAgB,KACjC,EAAM,SAAW,EAEV,GAAI,GAAK,MAAM,CAAK,CAC7B,EACA;AAAA;AAAA;AAAA,GA6BA,EAAK,QAAU,UAAY,CACzB,KAAK,KAAO,KACZ,KAAK,QAAU,OAAO,OAAO,IAAI,EACjC,KAAK,WAAa,OAAO,OAAO,IAAI,EACpC,KAAK,cAAgB,OAAO,OAAO,IAAI,EACvC,KAAK,qBAAuB,CAAC,EAC7B,KAAK,aAAe,CAAC,EACrB,KAAK,UAAY,EAAK,UACtB,KAAK,SAAW,GAAI,GAAK,SACzB,KAAK,eAAiB,GAAI,GAAK,SAC/B,KAAK,cAAgB,EACrB,KAAK,GAAK,IACV,KAAK,IAAM,IACX,KAAK,UAAY,EACjB,KAAK,kBAAoB,CAAC,CAC5B,EAcA,EAAK,QAAQ,UAAU,IAAM,SAAU,EAAK,CAC1C,KAAK,KAAO,CACd,EAkCA,EAAK,QAAQ,UAAU,MAAQ,SAAU,EAAW,EAAY,CAC9D,GAAI,KAAK,KAAK,CAAS,EACrB,KAAM,IAAI,YAAY,UAAY,EAAY,kCAAkC,EAGlF,KAAK,QAAQ,GAAa,GAAc,CAAC,CAC3C,EAUA,EAAK,QAAQ,UAAU,EAAI,SAAU,EAAQ,CAC3C,AAAI,EAAS,EACX,KAAK,GAAK,EACL,AAAI,EAAS,EAClB,KAAK,GAAK,EAEV,KAAK,GAAK,CAEd,EASA,EAAK,QAAQ,UAAU,GAAK,SAAU,EAAQ,CAC5C,KAAK,IAAM,CACb,EAmBA,EAAK,QAAQ,UAAU,IAAM,SAAU,EAAK,EAAY,CACtD,GAAI,GAAS,EAAI,KAAK,MAClB,EAAS,OAAO,KAAK,KAAK,OAAO,EAErC,KAAK,WAAW,GAAU,GAAc,CAAC,EACzC,KAAK,eAAiB,EAEtB,OAAS,GAAI,EAAG,EAAI,EAAO,OAAQ,IAAK,CACtC,GAAI,GAAY,EAAO,GACnB,EAAY,KAAK,QAAQ,GAAW,UACpC,EAAQ,EAAY,EAAU,CAAG,EAAI,EAAI,GACzC,EAAS,KAAK,UAAU,EAAO,CAC7B,OAAQ,CAAC,CAAS,CACpB,CAAC,EACD,EAAQ,KAAK,SAAS,IAAI,CAAM,EAChC,EAAW,GAAI,GAAK,SAAU,EAAQ,CAAS,EAC/C,EAAa,OAAO,OAAO,IAAI,EAEnC,KAAK,qBAAqB,GAAY,EACtC,KAAK,aAAa,GAAY,EAG9B,KAAK,aAAa,IAAa,EAAM,OAGrC,OAAS,GAAI,EAAG,EAAI,EAAM,OAAQ,IAAK,CACrC,GAAI,GAAO,EAAM,GAUjB,GARI,EAAW,IAAS,MACtB,GAAW,GAAQ,GAGrB,EAAW,IAAS,EAIhB,KAAK,cAAc,IAAS,KAAW,CACzC,GAAI,GAAU,OAAO,OAAO,IAAI,EAChC,EAAQ,OAAY,KAAK,UACzB,KAAK,WAAa,EAElB,OAAS,GAAI,EAAG,EAAI,EAAO,OAAQ,IACjC,EAAQ,EAAO,IAAM,OAAO,OAAO,IAAI,EAGzC,KAAK,cAAc,GAAQ,CAC7B,CAGA,AAAI,KAAK,cAAc,GAAM,GAAW,IAAW,MACjD,MAAK,cAAc,GAAM,GAAW,GAAU,OAAO,OAAO,IAAI,GAKlE,OAAS,GAAI,EAAG,EAAI,KAAK,kBAAkB,OAAQ,IAAK,CACtD,GAAI,GAAc,KAAK,kBAAkB,GACrC,EAAW,EAAK,SAAS,GAE7B,AAAI,KAAK,cAAc,GAAM,GAAW,GAAQ,IAAgB,MAC9D,MAAK,cAAc,GAAM,GAAW,GAAQ,GAAe,CAAC,GAG9D,KAAK,cAAc,GAAM,GAAW,GAAQ,GAAa,KAAK,CAAQ,CACxE,CACF,CAEF,CACF,EAOA,EAAK,QAAQ,UAAU,6BAA+B,UAAY,CAOhE,OALI,GAAY,OAAO,KAAK,KAAK,YAAY,EACzC,EAAiB,EAAU,OAC3B,EAAc,CAAC,EACf,EAAqB,CAAC,EAEjB,EAAI,EAAG,EAAI,EAAgB,IAAK,CACvC,GAAI,GAAW,EAAK,SAAS,WAAW,EAAU,EAAE,EAChD,EAAQ,EAAS,UAErB,EAAmB,IAAW,GAAmB,GAAS,GAC1D,EAAmB,IAAU,EAE7B,EAAY,IAAW,GAAY,GAAS,GAC5C,EAAY,IAAU,KAAK,aAAa,EAC1C,CAIA,OAFI,GAAS,OAAO,KAAK,KAAK,OAAO,EAE5B,EAAI,EAAG,EAAI,EAAO,OAAQ,IAAK,CACtC,GAAI,GAAY,EAAO,GACvB,EAAY,GAAa,EAAY,GAAa,EAAmB,EACvE,CAEA,KAAK,mBAAqB,CAC5B,EAOA,EAAK,QAAQ,UAAU,mBAAqB,UAAY,CAMtD,OALI,GAAe,CAAC,EAChB,EAAY,OAAO,KAAK,KAAK,oBAAoB,EACjD,EAAkB,EAAU,OAC5B,EAAe,OAAO,OAAO,IAAI,EAE5B,EAAI,EAAG,EAAI,EAAiB,IAAK,CAaxC,OAZI,GAAW,EAAK,SAAS,WAAW,EAAU,EAAE,EAChD,EAAY,EAAS,UACrB,EAAc,KAAK,aAAa,GAChC,EAAc,GAAI,GAAK,OACvB,EAAkB,KAAK,qBAAqB,GAC5C,EAAQ,OAAO,KAAK,CAAe,EACnC,EAAc,EAAM,OAGpB,EAAa,KAAK,QAAQ,GAAW,OAAS,EAC9C,EAAW,KAAK,WAAW,EAAS,QAAQ,OAAS,EAEhD,EAAI,EAAG,EAAI,EAAa,IAAK,CACpC,GAAI,GAAO,EAAM,GACb,EAAK,EAAgB,GACrB,EAAY,KAAK,cAAc,GAAM,OACrC,EAAK,EAAO,EAEhB,AAAI,EAAa,KAAU,OACzB,GAAM,EAAK,IAAI,KAAK,cAAc,GAAO,KAAK,aAAa,EAC3D,EAAa,GAAQ,GAErB,EAAM,EAAa,GAGrB,EAAQ,EAAQ,OAAK,IAAM,GAAK,GAAO,MAAK,IAAO,GAAI,KAAK,GAAK,KAAK,GAAM,GAAc,KAAK,mBAAmB,KAAe,GACjI,GAAS,EACT,GAAS,EACT,EAAqB,KAAK,MAAM,EAAQ,GAAI,EAAI,IAQhD,EAAY,OAAO,EAAW,CAAkB,CAClD,CAEA,EAAa,GAAY,CAC3B,CAEA,KAAK,aAAe,CACtB,EAOA,EAAK,QAAQ,UAAU,eAAiB,UAAY,CAClD,KAAK,SAAW,EAAK,SAAS,UAC5B,OAAO,KAAK,KAAK,aAAa,EAAE,KAAK,CACvC,CACF,EAUA,EAAK,QAAQ,UAAU,MAAQ,UAAY,CACzC,YAAK,6BAA6B,EAClC,KAAK,mBAAmB,EACxB,KAAK,eAAe,EAEb,GAAI,GAAK,MAAM,CACpB,cAAe,KAAK,cACpB,aAAc,KAAK,aACnB,SAAU,KAAK,SACf,OAAQ,OAAO,KAAK,KAAK,OAAO,EAChC,SAAU,KAAK,cACjB,CAAC,CACH,EAgBA,EAAK,QAAQ,UAAU,IAAM,SAAU,EAAI,CACzC,GAAI,GAAO,MAAM,UAAU,MAAM,KAAK,UAAW,CAAC,EAClD,EAAK,QAAQ,IAAI,EACjB,EAAG,MAAM,KAAM,CAAI,CACrB,EAaA,EAAK,UAAY,SAAU,EAAM,EAAO,EAAU,CAShD,OARI,GAAiB,OAAO,OAAO,IAAI,EACnC,EAAe,OAAO,KAAK,GAAY,CAAC,CAAC,EAOpC,EAAI,EAAG,EAAI,EAAa,OAAQ,IAAK,CAC5C,GAAI,GAAM,EAAa,GACvB,EAAe,GAAO,EAAS,GAAK,MAAM,CAC5C,CAEA,KAAK,SAAW,OAAO,OAAO,IAAI,EAE9B,IAAS,QACX,MAAK,SAAS,GAAQ,OAAO,OAAO,IAAI,EACxC,KAAK,SAAS,GAAM,GAAS,EAEjC,EAWA,EAAK,UAAU,UAAU,QAAU,SAAU,EAAgB,CAG3D,OAFI,GAAQ,OAAO,KAAK,EAAe,QAAQ,EAEtC,EAAI,EAAG,EAAI,EAAM,OAAQ,IAAK,CACrC,GAAI,GAAO,EAAM,GACb,EAAS,OAAO,KAAK,EAAe,SAAS,EAAK,EAEtD,AAAI,KAAK,SAAS,IAAS,MACzB,MAAK,SAAS,GAAQ,OAAO,OAAO,IAAI,GAG1C,OAAS,GAAI,EAAG,EAAI,EAAO,OAAQ,IAAK,CACtC,GAAI,GAAQ,EAAO,GACf,EAAO,OAAO,KAAK,EAAe,SAAS,GAAM,EAAM,EAE3D,AAAI,KAAK,SAAS,GAAM,IAAU,MAChC,MAAK,SAAS,GAAM,GAAS,OAAO,OAAO,IAAI,GAGjD,OAAS,GAAI,EAAG,EAAI,EAAK,OAAQ,IAAK,CACpC,GAAI,GAAM,EAAK,GAEf,AAAI,KAAK,SAAS,GAAM,GAAO,IAAQ,KACrC,KAAK,SAAS,GAAM,GAAO,GAAO,EAAe,SAAS,GAAM,GAAO,GAEvE,KAAK,SAAS,GAAM,GAAO,GAAO,KAAK,SAAS,GAAM,GAAO,GAAK,OAAO,EAAe,SAAS,GAAM,GAAO,EAAI,CAGtH,CACF,CACF,CACF,EASA,EAAK,UAAU,UAAU,IAAM,SAAU,EAAM,EAAO,EAAU,CAC9D,GAAI,CAAE,KAAQ,MAAK,UAAW,CAC5B,KAAK,SAAS,GAAQ,OAAO,OAAO,IAAI,EACxC,KAAK,SAAS,GAAM,GAAS,EAC7B,MACF,CAEA,GAAI,CAAE,KAAS,MAAK,SAAS,IAAQ,CACnC,KAAK,SAAS,GAAM,GAAS,EAC7B,MACF,CAIA,OAFI,GAAe,OAAO,KAAK,CAAQ,EAE9B,EAAI,EAAG,EAAI,EAAa,OAAQ,IAAK,CAC5C,GAAI,GAAM,EAAa,GAEvB,AAAI,IAAO,MAAK,SAAS,GAAM,GAC7B,KAAK,SAAS,GAAM,GAAO,GAAO,KAAK,SAAS,GAAM,GAAO,GAAK,OAAO,EAAS,EAAI,EAEtF,KAAK,SAAS,GAAM,GAAO,GAAO,EAAS,EAE/C,CACF,EAYA,EAAK,MAAQ,SAAU,EAAW,CAChC,KAAK,QAAU,CAAC,EAChB,KAAK,UAAY,CACnB,EA0BA,EAAK,MAAM,SAAW,GAAI,QAAQ,GAAG,EACrC,EAAK,MAAM,SAAS,KAAO,EAC3B,EAAK,MAAM,SAAS,QAAU,EAC9B,EAAK,MAAM,SAAS,SAAW,EAa/B,EAAK,MAAM,SAAW,CAIpB,SAAU,EAMV,SAAU,EAMV,WAAY,CACd,EAyBA,EAAK,MAAM,UAAU,OAAS,SAAU,EAAQ,CAC9C,MAAM,UAAY,IAChB,GAAO,OAAS,KAAK,WAGjB,SAAW,IACf,GAAO,MAAQ,GAGX,eAAiB,IACrB,GAAO,YAAc,IAGjB,YAAc,IAClB,GAAO,SAAW,EAAK,MAAM,SAAS,MAGnC,EAAO,SAAW,EAAK,MAAM,SAAS,SAAa,EAAO,KAAK,OAAO,CAAC,GAAK,EAAK,MAAM,UAC1F,GAAO,KAAO,IAAM,EAAO,MAGxB,EAAO,SAAW,EAAK,MAAM,SAAS,UAAc,EAAO,KAAK,MAAM,EAAE,GAAK,EAAK,MAAM,UAC3F,GAAO,KAAO,GAAK,EAAO,KAAO,KAG7B,YAAc,IAClB,GAAO,SAAW,EAAK,MAAM,SAAS,UAGxC,KAAK,QAAQ,KAAK,CAAM,EAEjB,IACT,EASA,EAAK,MAAM,UAAU,UAAY,UAAY,CAC3C,OAAS,GAAI,EAAG,EAAI,KAAK,QAAQ,OAAQ,IACvC,GAAI,KAAK,QAAQ,GAAG,UAAY,EAAK,MAAM,SAAS,WAClD,MAAO,GAIX,MAAO,EACT,EA4BA,EAAK,MAAM,UAAU,KAAO,SAAU,EAAM,EAAS,CACnD,GAAI,MAAM,QAAQ,CAAI,EACpB,SAAK,QAAQ,SAAU,EAAG,CAAE,KAAK,KAAK,EAAG,EAAK,MAAM,MAAM,CAAO,CAAC,CAAE,EAAG,IAAI,EACpE,KAGT,GAAI,GAAS,GAAW,CAAC,EACzB,SAAO,KAAO,EAAK,SAAS,EAE5B,KAAK,OAAO,CAAM,EAEX,IACT,EACA,EAAK,gBAAkB,SAAU,EAAS,EAAO,EAAK,CACpD,KAAK,KAAO,kBACZ,KAAK,QAAU,EACf,KAAK,MAAQ,EACb,KAAK,IAAM,CACb,EAEA,EAAK,gBAAgB,UAAY,GAAI,OACrC,EAAK,WAAa,SAAU,EAAK,CAC/B,KAAK,QAAU,CAAC,EAChB,KAAK,IAAM,EACX,KAAK,OAAS,EAAI,OAClB,KAAK,IAAM,EACX,KAAK,MAAQ,EACb,KAAK,oBAAsB,CAAC,CAC9B,EAEA,EAAK,WAAW,UAAU,IAAM,UAAY,CAG1C,OAFI,GAAQ,EAAK,WAAW,QAErB,GACL,EAAQ,EAAM,IAAI,CAEtB,EAEA,EAAK,WAAW,UAAU,YAAc,UAAY,CAKlD,OAJI,GAAY,CAAC,EACb,EAAa,KAAK,MAClB,EAAW,KAAK,IAEX,EAAI,EAAG,EAAI,KAAK,oBAAoB,OAAQ,IACnD,EAAW,KAAK,oBAAoB,GACpC,EAAU,KAAK,KAAK,IAAI,MAAM,EAAY,CAAQ,CAAC,EACnD,EAAa,EAAW,EAG1B,SAAU,KAAK,KAAK,IAAI,MAAM,EAAY,KAAK,GAAG,CAAC,EACnD,KAAK,oBAAoB,OAAS,EAE3B,EAAU,KAAK,EAAE,CAC1B,EAEA,EAAK,WAAW,UAAU,KAAO,SAAU,EAAM,CAC/C,KAAK,QAAQ,KAAK,CAChB,KAAM,EACN,IAAK,KAAK,YAAY,EACtB,MAAO,KAAK,MACZ,IAAK,KAAK,GACZ,CAAC,EAED,KAAK,MAAQ,KAAK,GACpB,EAEA,EAAK,WAAW,UAAU,gBAAkB,UAAY,CACtD,KAAK,oBAAoB,KAAK,KAAK,IAAM,CAAC,EAC1C,KAAK,KAAO,CACd,EAEA,EAAK,WAAW,UAAU,KAAO,UAAY,CAC3C,GAAI,KAAK,KAAO,KAAK,OACnB,MAAO,GAAK,WAAW,IAGzB,GAAI,GAAO,KAAK,IAAI,OAAO,KAAK,GAAG,EACnC,YAAK,KAAO,EACL,CACT,EAEA,EAAK,WAAW,UAAU,MAAQ,UAAY,CAC5C,MAAO,MAAK,IAAM,KAAK,KACzB,EAEA,EAAK,WAAW,UAAU,OAAS,UAAY,CAC7C,AAAI,KAAK,OAAS,KAAK,KACrB,MAAK,KAAO,GAGd,KAAK,MAAQ,KAAK,GACpB,EAEA,EAAK,WAAW,UAAU,OAAS,UAAY,CAC7C,KAAK,KAAO,CACd,EAEA,EAAK,WAAW,UAAU,eAAiB,UAAY,CACrD,GAAI,GAAM,EAEV,EACE,GAAO,KAAK,KAAK,EACjB,EAAW,EAAK,WAAW,CAAC,QACrB,EAAW,IAAM,EAAW,IAErC,AAAI,GAAQ,EAAK,WAAW,KAC1B,KAAK,OAAO,CAEhB,EAEA,EAAK,WAAW,UAAU,KAAO,UAAY,CAC3C,MAAO,MAAK,IAAM,KAAK,MACzB,EAEA,EAAK,WAAW,IAAM,MACtB,EAAK,WAAW,MAAQ,QACxB,EAAK,WAAW,KAAO,OACvB,EAAK,WAAW,cAAgB,gBAChC,EAAK,WAAW,MAAQ,QACxB,EAAK,WAAW,SAAW,WAE3B,EAAK,WAAW,SAAW,SAAU,EAAO,CAC1C,SAAM,OAAO,EACb,EAAM,KAAK,EAAK,WAAW,KAAK,EAChC,EAAM,OAAO,EACN,EAAK,WAAW,OACzB,EAEA,EAAK,WAAW,QAAU,SAAU,EAAO,CAQzC,GAPI,EAAM,MAAM,EAAI,GAClB,GAAM,OAAO,EACb,EAAM,KAAK,EAAK,WAAW,IAAI,GAGjC,EAAM,OAAO,EAET,EAAM,KAAK,EACb,MAAO,GAAK,WAAW,OAE3B,EAEA,EAAK,WAAW,gBAAkB,SAAU,EAAO,CACjD,SAAM,OAAO,EACb,EAAM,eAAe,EACrB,EAAM,KAAK,EAAK,WAAW,aAAa,EACjC,EAAK,WAAW,OACzB,EAEA,EAAK,WAAW,SAAW,SAAU,EAAO,CAC1C,SAAM,OAAO,EACb,EAAM,eAAe,EACrB,EAAM,KAAK,EAAK,WAAW,KAAK,EACzB,EAAK,WAAW,OACzB,EAEA,EAAK,WAAW,OAAS,SAAU,EAAO,CACxC,AAAI,EAAM,MAAM,EAAI,GAClB,EAAM,KAAK,EAAK,WAAW,IAAI,CAEnC,EAaA,EAAK,WAAW,cAAgB,EAAK,UAAU,UAE/C,EAAK,WAAW,QAAU,SAAU,EAAO,CACzC,OAAa,CACX,GAAI,GAAO,EAAM,KAAK,EAEtB,GAAI,GAAQ,EAAK,WAAW,IAC1B,MAAO,GAAK,WAAW,OAIzB,GAAI,EAAK,WAAW,CAAC,GAAK,GAAI,CAC5B,EAAM,gBAAgB,EACtB,QACF,CAEA,GAAI,GAAQ,IACV,MAAO,GAAK,WAAW,SAGzB,GAAI,GAAQ,IACV,SAAM,OAAO,EACT,EAAM,MAAM,EAAI,GAClB,EAAM,KAAK,EAAK,WAAW,IAAI,EAE1B,EAAK,WAAW,gBAGzB,GAAI,GAAQ,IACV,SAAM,OAAO,EACT,EAAM,MAAM,EAAI,GAClB,EAAM,KAAK,EAAK,WAAW,IAAI,EAE1B,EAAK,WAAW,SAczB,GARI,GAAQ,KAAO,EAAM,MAAM,IAAM,GAQjC,GAAQ,KAAO,EAAM,MAAM,IAAM,EACnC,SAAM,KAAK,EAAK,WAAW,QAAQ,EAC5B,EAAK,WAAW,QAGzB,GAAI,EAAK,MAAM,EAAK,WAAW,aAAa,EAC1C,MAAO,GAAK,WAAW,OAE3B,CACF,EAEA,EAAK,YAAc,SAAU,EAAK,EAAO,CACvC,KAAK,MAAQ,GAAI,GAAK,WAAY,CAAG,EACrC,KAAK,MAAQ,EACb,KAAK,cAAgB,CAAC,EACtB,KAAK,UAAY,CACnB,EAEA,EAAK,YAAY,UAAU,MAAQ,UAAY,CAC7C,KAAK,MAAM,IAAI,EACf,KAAK,QAAU,KAAK,MAAM,QAI1B,OAFI,GAAQ,EAAK,YAAY,YAEtB,GACL,EAAQ,EAAM,IAAI,EAGpB,MAAO,MAAK,KACd,EAEA,EAAK,YAAY,UAAU,WAAa,UAAY,CAClD,MAAO,MAAK,QAAQ,KAAK,UAC3B,EAEA,EAAK,YAAY,UAAU,cAAgB,UAAY,CACrD,GAAI,GAAS,KAAK,WAAW,EAC7B,YAAK,WAAa,EACX,CACT,EAEA,EAAK,YAAY,UAAU,WAAa,UAAY,CAClD,GAAI,GAAkB,KAAK,cAC3B,KAAK,MAAM,OAAO,CAAe,EACjC,KAAK,cAAgB,CAAC,CACxB,EAEA,EAAK,YAAY,YAAc,SAAU,EAAQ,CAC/C,GAAI,GAAS,EAAO,WAAW,EAE/B,GAAI,GAAU,KAId,OAAQ,EAAO,UACR,GAAK,WAAW,SACnB,MAAO,GAAK,YAAY,kBACrB,GAAK,WAAW,MACnB,MAAO,GAAK,YAAY,eACrB,GAAK,WAAW,KACnB,MAAO,GAAK,YAAY,kBAExB,GAAI,GAAe,4CAA8C,EAAO,KAExE,KAAI,GAAO,IAAI,QAAU,GACvB,IAAgB,gBAAkB,EAAO,IAAM,KAG3C,GAAI,GAAK,gBAAiB,EAAc,EAAO,MAAO,EAAO,GAAG,EAE5E,EAEA,EAAK,YAAY,cAAgB,SAAU,EAAQ,CACjD,GAAI,GAAS,EAAO,cAAc,EAElC,GAAI,GAAU,KAId,QAAQ,EAAO,SACR,IACH,EAAO,cAAc,SAAW,EAAK,MAAM,SAAS,WACpD,UACG,IACH,EAAO,cAAc,SAAW,EAAK,MAAM,SAAS,SACpD,cAEA,GAAI,GAAe,kCAAoC,EAAO,IAAM,IACpE,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAO,MAAO,EAAO,GAAG,EAG1E,GAAI,GAAa,EAAO,WAAW,EAEnC,GAAI,GAAc,KAAW,CAC3B,GAAI,GAAe,yCACnB,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAO,MAAO,EAAO,GAAG,CACxE,CAEA,OAAQ,EAAW,UACZ,GAAK,WAAW,MACnB,MAAO,GAAK,YAAY,eACrB,GAAK,WAAW,KACnB,MAAO,GAAK,YAAY,kBAExB,GAAI,GAAe,mCAAqC,EAAW,KAAO,IAC1E,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAW,MAAO,EAAW,GAAG,GAEpF,EAEA,EAAK,YAAY,WAAa,SAAU,EAAQ,CAC9C,GAAI,GAAS,EAAO,cAAc,EAElC,GAAI,GAAU,KAId,IAAI,EAAO,MAAM,UAAU,QAAQ,EAAO,GAAG,GAAK,GAAI,CACpD,GAAI,GAAiB,EAAO,MAAM,UAAU,IAAI,SAAU,EAAG,CAAE,MAAO,IAAM,EAAI,GAAI,CAAC,EAAE,KAAK,IAAI,EAC5F,EAAe,uBAAyB,EAAO,IAAM,uBAAyB,EAElF,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAO,MAAO,EAAO,GAAG,CACxE,CAEA,EAAO,cAAc,OAAS,CAAC,EAAO,GAAG,EAEzC,GAAI,GAAa,EAAO,WAAW,EAEnC,GAAI,GAAc,KAAW,CAC3B,GAAI,GAAe,gCACnB,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAO,MAAO,EAAO,GAAG,CACxE,CAEA,OAAQ,EAAW,UACZ,GAAK,WAAW,KACnB,MAAO,GAAK,YAAY,kBAExB,GAAI,GAAe,0BAA4B,EAAW,KAAO,IACjE,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAW,MAAO,EAAW,GAAG,GAEpF,EAEA,EAAK,YAAY,UAAY,SAAU,EAAQ,CAC7C,GAAI,GAAS,EAAO,cAAc,EAElC,GAAI,GAAU,KAId,GAAO,cAAc,KAAO,EAAO,IAAI,YAAY,EAE/C,EAAO,IAAI,QAAQ,GAAG,GAAK,IAC7B,GAAO,cAAc,YAAc,IAGrC,GAAI,GAAa,EAAO,WAAW,EAEnC,GAAI,GAAc,KAAW,CAC3B,EAAO,WAAW,EAClB,MACF,CAEA,OAAQ,EAAW,UACZ,GAAK,WAAW,KACnB,SAAO,WAAW,EACX,EAAK,YAAY,cACrB,GAAK,WAAW,MACnB,SAAO,WAAW,EACX,EAAK,YAAY,eACrB,GAAK,WAAW,cACnB,MAAO,GAAK,YAAY,sBACrB,GAAK,WAAW,MACnB,MAAO,GAAK,YAAY,eACrB,GAAK,WAAW,SACnB,SAAO,WAAW,EACX,EAAK,YAAY,sBAExB,GAAI,GAAe,2BAA6B,EAAW,KAAO,IAClE,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAW,MAAO,EAAW,GAAG,GAEpF,EAEA,EAAK,YAAY,kBAAoB,SAAU,EAAQ,CACrD,GAAI,GAAS,EAAO,cAAc,EAElC,GAAI,GAAU,KAId,IAAI,GAAe,SAAS,EAAO,IAAK,EAAE,EAE1C,GAAI,MAAM,CAAY,EAAG,CACvB,GAAI,GAAe,gCACnB,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAO,MAAO,EAAO,GAAG,CACxE,CAEA,EAAO,cAAc,aAAe,EAEpC,GAAI,GAAa,EAAO,WAAW,EAEnC,GAAI,GAAc,KAAW,CAC3B,EAAO,WAAW,EAClB,MACF,CAEA,OAAQ,EAAW,UACZ,GAAK,WAAW,KACnB,SAAO,WAAW,EACX,EAAK,YAAY,cACrB,GAAK,WAAW,MACnB,SAAO,WAAW,EACX,EAAK,YAAY,eACrB,GAAK,WAAW,cACnB,MAAO,GAAK,YAAY,sBACrB,GAAK,WAAW,MACnB,MAAO,GAAK,YAAY,eACrB,GAAK,WAAW,SACnB,SAAO,WAAW,EACX,EAAK,YAAY,sBAExB,GAAI,GAAe,2BAA6B,EAAW,KAAO,IAClE,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAW,MAAO,EAAW,GAAG,GAEpF,EAEA,EAAK,YAAY,WAAa,SAAU,EAAQ,CAC9C,GAAI,GAAS,EAAO,cAAc,EAElC,GAAI,GAAU,KAId,IAAI,GAAQ,SAAS,EAAO,IAAK,EAAE,EAEnC,GAAI,MAAM,CAAK,EAAG,CAChB,GAAI,GAAe,wBACnB,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAO,MAAO,EAAO,GAAG,CACxE,CAEA,EAAO,cAAc,MAAQ,EAE7B,GAAI,GAAa,EAAO,WAAW,EAEnC,GAAI,GAAc,KAAW,CAC3B,EAAO,WAAW,EAClB,MACF,CAEA,OAAQ,EAAW,UACZ,GAAK,WAAW,KACnB,SAAO,WAAW,EACX,EAAK,YAAY,cACrB,GAAK,WAAW,MACnB,SAAO,WAAW,EACX,EAAK,YAAY,eACrB,GAAK,WAAW,cACnB,MAAO,GAAK,YAAY,sBACrB,GAAK,WAAW,MACnB,MAAO,GAAK,YAAY,eACrB,GAAK,WAAW,SACnB,SAAO,WAAW,EACX,EAAK,YAAY,sBAExB,GAAI,GAAe,2BAA6B,EAAW,KAAO,IAClE,KAAM,IAAI,GAAK,gBAAiB,EAAc,EAAW,MAAO,EAAW,GAAG,GAEpF,EAMI,SAAU,EAAM,EAAS,CACzB,AAAI,MAAO,SAAW,YAAc,OAAO,IAEzC,OAAO,CAAO,EACT,AAAI,MAAO,KAAY,SAM5B,GAAO,QAAU,EAAQ,EAGzB,EAAK,KAAO,EAAQ,CAExB,EAAE,KAAM,UAAY,CAMlB,MAAO,EACT,CAAC,CACH,GAAG,ICl5GH;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,GAeA,GAAI,IAAkB,UAOtB,GAAO,QAAU,GAUjB,YAAoB,EAAQ,CAC1B,GAAI,GAAM,GAAK,EACX,EAAQ,GAAgB,KAAK,CAAG,EAEpC,GAAI,CAAC,EACH,MAAO,GAGT,GAAI,GACA,EAAO,GACP,EAAQ,EACR,EAAY,EAEhB,IAAK,EAAQ,EAAM,MAAO,EAAQ,EAAI,OAAQ,IAAS,CACrD,OAAQ,EAAI,WAAW,CAAK,OACrB,IACH,EAAS,SACT,UACG,IACH,EAAS,QACT,UACG,IACH,EAAS,QACT,UACG,IACH,EAAS,OACT,UACG,IACH,EAAS,OACT,cAEA,SAGJ,AAAI,IAAc,GAChB,IAAQ,EAAI,UAAU,EAAW,CAAK,GAGxC,EAAY,EAAQ,EACpB,GAAQ,CACV,CAEA,MAAO,KAAc,EACjB,EAAO,EAAI,UAAU,EAAW,CAAK,EACrC,CACN,ICvDA,OAAiB,QCKjB,AAAK,OAAO,SACV,QAAO,QAAU,SAAU,EAAa,CACtC,GAAM,GAA2B,CAAC,EAClC,OAAW,KAAO,QAAO,KAAK,CAAG,EAE/B,EAAK,KAAK,CAAC,EAAK,EAAI,EAAI,CAAC,EAG3B,MAAO,EACT,GAGF,AAAK,OAAO,QACV,QAAO,OAAS,SAAU,EAAa,CACrC,GAAM,GAAiB,CAAC,EACxB,OAAW,KAAO,QAAO,KAAK,CAAG,EAE/B,EAAK,KAAK,EAAI,EAAI,EAGpB,MAAO,EACT,GAKF,AAAI,MAAO,UAAY,aAGhB,SAAQ,UAAU,UACrB,SAAQ,UAAU,SAAW,SAC3B,EAA8B,EACxB,CACN,AAAI,MAAO,IAAM,SACf,MAAK,WAAa,EAAE,KACpB,KAAK,UAAY,EAAE,KAEnB,MAAK,WAAa,EAClB,KAAK,UAAY,EAErB,GAGG,QAAQ,UAAU,aACrB,SAAQ,UAAU,YAAc,YAC3B,EACG,CACN,GAAM,GAAS,KAAK,WACpB,GAAI,EAAQ,CACV,AAAI,EAAM,SAAW,GACnB,EAAO,YAAY,IAAI,EAGzB,OAAS,GAAI,EAAM,OAAS,EAAG,GAAK,EAAG,IAAK,CAC1C,GAAI,GAAO,EAAM,GACjB,AAAI,MAAO,IAAS,SAClB,EAAO,SAAS,eAAe,CAAI,EAC5B,EAAK,YACZ,EAAK,WAAW,YAAY,CAAI,EAGlC,AAAK,EAGH,EAAO,aAAa,KAAK,gBAAkB,CAAI,EAF/C,EAAO,aAAa,EAAM,IAAI,CAGlC,CACF,CACF,ICxEJ,OAAuB,OAiChB,YACL,EACmB,CACnB,GAAM,GAAY,GAAI,KAChB,EAAY,GAAI,KACtB,OAAW,KAAO,GAAM,CACtB,GAAM,CAAC,EAAM,GAAQ,EAAI,SAAS,MAAM,GAAG,EAGrC,EAAW,EAAI,SACf,EAAW,EAAI,MACf,EAAW,EAAI,KAGf,EAAO,eAAW,EAAI,IAAI,EAC7B,QAAQ,mBAAoB,EAAE,EAC9B,QAAQ,OAAQ,GAAG,EAGtB,GAAI,EAAM,CACR,GAAM,GAAS,EAAU,IAAI,CAAI,EAGjC,AAAK,EAAQ,IAAI,CAAM,EASrB,EAAU,IAAI,EAAU,CACtB,WACA,QACA,OACA,QACF,CAAC,EAbD,GAAO,MAAQ,EAAI,MACnB,EAAO,KAAQ,EAGf,EAAQ,IAAI,CAAM,EAatB,KACE,GAAU,IAAI,EAAU,GACtB,WACA,QACA,QACG,GAAQ,CAAE,MAAK,EACnB,CAEL,CACA,MAAO,EACT,CCpFA,OAAuB,OAsChB,YACL,EAA2B,EACD,CAC1B,GAAM,GAAY,GAAI,QAAO,EAAO,UAAW,KAAK,EAC9C,EAAY,CAAC,EAAY,EAAc,IACpC,GAAG,4BAA+B,WAI3C,MAAO,AAAC,IAAkB,CACxB,EAAQ,EACL,QAAQ,gBAAiB,GAAG,EAC5B,KAAK,EAGR,GAAM,GAAQ,GAAI,QAAO,MAAM,EAAO,cACpC,EACG,QAAQ,uBAAwB,MAAM,EACtC,QAAQ,EAAW,GAAG,KACtB,KAAK,EAGV,MAAO,IACL,GACI,eAAW,CAAK,EAChB,GAED,QAAQ,EAAO,CAAS,EACxB,QAAQ,8BAA+B,IAAI,CAClD,CACF,CCtCO,YACL,EACqB,CACrB,GAAM,GAAS,GAAK,MAAa,MAAM,CAAC,QAAS,MAAM,CAAC,EAIxD,MAHe,IAAK,MAAa,YAAY,EAAO,CAAK,EAGlD,MAAM,EACN,EAAM,OACf,CAUO,YACL,EAA4B,EACV,CAzEpB,MA0EE,GAAM,GAAU,GAAI,KAAuB,CAAK,EAG1C,EAA2B,CAAC,EAClC,OAAS,GAAI,EAAG,EAAI,EAAM,OAAQ,IAChC,OAAW,KAAU,GACnB,AAAI,EAAM,GAAG,WAAW,EAAO,IAAI,GACjC,GAAO,EAAO,MAAQ,GACtB,EAAQ,OAAO,CAAM,GAI3B,OAAW,KAAU,GACnB,AAAI,QAAK,iBAAL,kBAAsB,EAAO,OAC/B,GAAO,EAAO,MAAQ,IAG1B,MAAO,EACT,CC0BA,YAAoB,EAAa,EAAuB,CACtD,GAAM,CAAC,EAAG,GAAK,CAAC,GAAI,KAAI,CAAC,EAAG,GAAI,KAAI,CAAC,CAAC,EACtC,MAAO,CACL,GAAG,GAAI,KAAI,CAAC,GAAG,CAAC,EAAE,OAAO,GAAS,CAAC,EAAE,IAAI,CAAK,CAAC,CAAC,CAClD,CACF,CASO,WAAa,CAgCX,YAAY,CAAE,SAAQ,OAAM,WAAwB,CACzD,KAAK,QAAU,EAGf,KAAK,UAAY,GAAuB,CAAI,EAC5C,KAAK,UAAY,GAAuB,EAAQ,EAAK,EAGrD,KAAK,UAAU,UAAY,GAAI,QAAO,EAAO,SAAS,EAGtD,KAAK,MAAQ,KAAK,UAAY,CAG5B,AAAI,EAAO,KAAK,SAAW,GAAK,EAAO,KAAK,KAAO,KACjD,KAAK,IAAK,KAAa,EAAO,KAAK,GAAG,EAC7B,EAAO,KAAK,OAAS,GAC9B,KAAK,IAAK,KAAa,cAAc,GAAG,EAAO,IAAI,CAAC,EAItD,GAAM,GAAM,GAAW,CACrB,UAAW,iBAAkB,SAC/B,EAAG,EAAQ,QAAQ,EAGnB,OAAW,KAAQ,GAAO,KAAK,IAAI,GACjC,IAAa,KAAO,KAAQ,KAAa,EAC1C,EACC,OAAW,KAAM,GACf,KAAK,SAAS,OAAO,EAAK,EAAG,EAC7B,KAAK,eAAe,OAAO,EAAK,EAAG,EAKvC,KAAK,IAAI,UAAU,EAGnB,KAAK,MAAM,QAAS,CAAE,MAAO,GAAI,CAAC,EAClC,KAAK,MAAM,MAAM,EACjB,KAAK,MAAM,OAAQ,CAAE,MAAO,GAAI,CAAC,EAGjC,OAAW,KAAO,GAChB,KAAK,IAAI,CAAG,CAChB,CAAC,CACH,CAkBO,OAAO,EAA6B,CACzC,GAAI,EACF,GAAI,CACF,GAAM,GAAY,KAAK,UAAU,CAAK,EAGhC,EAAU,GAAiB,CAAK,EACnC,OAAO,GACN,EAAO,WAAa,KAAK,MAAM,SAAS,UACzC,EAGG,EAAS,KAAK,MAAM,OAAO,GAAG,IAAQ,EAGzC,OAAyB,CAAC,EAAM,CAAE,MAAK,QAAO,eAAgB,CAC7D,GAAM,GAAW,KAAK,UAAU,IAAI,CAAG,EACvC,GAAI,MAAO,IAAa,YAAa,CACnC,GAAM,CAAE,WAAU,QAAO,OAAM,OAAM,UAAW,EAG1C,EAAQ,GACZ,EACA,OAAO,KAAK,EAAU,QAAQ,CAChC,EAGM,EAAQ,CAAC,CAAC,EAAS,EAAC,OAAO,OAAO,CAAK,EAAE,MAAM,GAAK,CAAC,EAC3D,EAAK,KAAK,KACR,WACA,MAAO,EAAU,CAAK,EACtB,KAAO,EAAU,CAAI,GAClB,GAAQ,CAAE,KAAM,EAAK,IAAI,CAAS,CAAE,GAJ/B,CAKR,MAAO,EAAS,GAAI,GACpB,OACF,EAAC,CACH,CACA,MAAO,EACT,EAAG,CAAC,CAAC,EAGJ,KAAK,CAAC,EAAG,IAAM,EAAE,MAAQ,EAAE,KAAK,EAGhC,OAAO,CAAC,EAAO,IAAW,CACzB,GAAM,GAAW,KAAK,UAAU,IAAI,EAAO,QAAQ,EACnD,GAAI,MAAO,IAAa,YAAa,CACnC,GAAM,GAAM,UAAY,GACpB,EAAS,OAAQ,SACjB,EAAS,SACb,EAAM,IAAI,EAAK,CAAC,GAAG,EAAM,IAAI,CAAG,GAAK,CAAC,EAAG,CAAM,CAAC,CAClD,CACA,MAAO,EACT,EAAG,GAAI,IAA+B,EAGpC,EACJ,GAAI,KAAK,QAAQ,YAAa,CAC5B,GAAM,GAAS,KAAK,MAAM,MAAM,GAAW,CACzC,OAAW,KAAU,GACnB,EAAQ,KAAK,EAAO,KAAM,CACxB,OAAQ,CAAC,OAAO,EAChB,SAAU,KAAK,MAAM,SAAS,SAC9B,SAAU,KAAK,MAAM,SAAS,QAChC,CAAC,CACL,CAAC,EAGD,EAAc,EAAO,OACjB,OAAO,KAAK,EAAO,GAAG,UAAU,QAAQ,EACxC,CAAC,CACP,CAGA,MAAO,IACL,MAAO,CAAC,GAAG,EAAO,OAAO,CAAC,GACvB,MAAO,IAAgB,aAAe,CAAE,aAAY,EAI3D,OAAQ,EAAN,CACA,QAAQ,KAAK,kBAAkB,qCAAoC,CACrE,CAIF,MAAO,CAAE,MAAO,CAAC,CAAE,CACrB,CACF,ELpQA,GAAI,GAqBJ,YACE,EACe,gCACf,GAAI,GAAO,UAGX,GAAI,MAAO,SAAW,aAAe,gBAAkB,QAAQ,CAC7D,GAAM,GAAS,SAAS,cAAiC,aAAa,EAChE,CAAC,GAAQ,EAAO,IAAI,MAAM,SAAS,EAGzC,EAAO,EAAK,QAAQ,KAAM,CAAI,CAChC,CAGA,GAAM,GAAU,CAAC,EACjB,OAAW,KAAQ,GAAO,KAAM,CAC9B,OAAQ,OAGD,KACH,EAAQ,KAAK,GAAG,cAAiB,EACjC,UAGG,SACA,KACH,EAAQ,KAAK,GAAG,cAAiB,EACjC,MAIJ,AAAI,IAAS,MACX,EAAQ,KAAK,GAAG,cAAiB,UAAa,CAClD,CAGA,AAAI,EAAO,KAAK,OAAS,GACvB,EAAQ,KAAK,GAAG,yBAA4B,EAG1C,EAAQ,QACV,MAAM,eACJ,GAAG,oCACH,GAAG,CACL,EACJ,GAaA,YACE,EACwB,gCACxB,OAAQ,EAAQ,UAGT,GACH,YAAM,IAAqB,EAAQ,KAAK,MAAM,EAC9C,EAAQ,GAAI,GAAO,EAAQ,IAAI,EACxB,CACL,KAAM,CACR,MAGG,GACH,MAAO,CACL,KAAM,EACN,KAAM,EAAQ,EAAM,OAAO,EAAQ,IAAI,EAAI,CAAE,MAAO,CAAC,CAAE,CACzD,UAIA,KAAM,IAAI,WAAU,sBAAsB,EAEhD,GAOA,KAAK,KAAO,WAGZ,iBAAiB,UAAW,AAAM,GAAM,0BACtC,YAAY,KAAM,IAAQ,EAAG,IAAI,CAAC,CACpC,EAAC",
-  "names": []
+  "sourcesContent": ["/**\n * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9\n * Copyright (C) 2020 Oliver Nightingale\n * @license MIT\n */\n\n;(function(){\n\n/**\n * A convenience function for configuring and constructing\n * a new lunr Index.\n *\n * A lunr.Builder instance is created and the pipeline setup\n * with a trimmer, stop word filter and stemmer.\n *\n * This builder object is yielded to the configuration function\n * that is passed as a parameter, allowing the list of fields\n * and other builder parameters to be customised.\n *\n * All documents _must_ be added within the passed config function.\n *\n * @example\n * var idx = lunr(function () {\n *   this.field('title')\n *   this.field('body')\n *   this.ref('id')\n *\n *   documents.forEach(function (doc) {\n *     this.add(doc)\n *   }, this)\n * })\n *\n * @see {@link lunr.Builder}\n * @see {@link lunr.Pipeline}\n * @see {@link lunr.trimmer}\n * @see {@link lunr.stopWordFilter}\n * @see {@link lunr.stemmer}\n * @namespace {function} lunr\n */\nvar lunr = function (config) {\n  var builder = new lunr.Builder\n\n  builder.pipeline.add(\n    lunr.trimmer,\n    lunr.stopWordFilter,\n    lunr.stemmer\n  )\n\n  builder.searchPipeline.add(\n    lunr.stemmer\n  )\n\n  config.call(builder, builder)\n  return builder.build()\n}\n\nlunr.version = \"2.3.9\"\n/*!\n * lunr.utils\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A namespace containing utils for the rest of the lunr library\n * @namespace lunr.utils\n */\nlunr.utils = {}\n\n/**\n * Print a warning message to the console.\n *\n * @param {String} message The message to be printed.\n * @memberOf lunr.utils\n * @function\n */\nlunr.utils.warn = (function (global) {\n  /* eslint-disable no-console */\n  return function (message) {\n    if (global.console && console.warn) {\n      console.warn(message)\n    }\n  }\n  /* eslint-enable no-console */\n})(this)\n\n/**\n * Convert an object to a string.\n *\n * In the case of `null` and `undefined` the function returns\n * the empty string, in all other cases the result of calling\n * `toString` on the passed object is returned.\n *\n * @param {Any} obj The object to convert to a string.\n * @return {String} string representation of the passed object.\n * @memberOf lunr.utils\n */\nlunr.utils.asString = function (obj) {\n  if (obj === void 0 || obj === null) {\n    return \"\"\n  } else {\n    return obj.toString()\n  }\n}\n\n/**\n * Clones an object.\n *\n * Will create a copy of an existing object such that any mutations\n * on the copy cannot affect the original.\n *\n * Only shallow objects are supported, passing a nested object to this\n * function will cause a TypeError.\n *\n * Objects with primitives, and arrays of primitives are supported.\n *\n * @param {Object} obj The object to clone.\n * @return {Object} a clone of the passed object.\n * @throws {TypeError} when a nested object is passed.\n * @memberOf Utils\n */\nlunr.utils.clone = function (obj) {\n  if (obj === null || obj === undefined) {\n    return obj\n  }\n\n  var clone = Object.create(null),\n      keys = Object.keys(obj)\n\n  for (var i = 0; i < keys.length; i++) {\n    var key = keys[i],\n        val = obj[key]\n\n    if (Array.isArray(val)) {\n      clone[key] = val.slice()\n      continue\n    }\n\n    if (typeof val === 'string' ||\n        typeof val === 'number' ||\n        typeof val === 'boolean') {\n      clone[key] = val\n      continue\n    }\n\n    throw new TypeError(\"clone is not deep and does not support nested objects\")\n  }\n\n  return clone\n}\nlunr.FieldRef = function (docRef, fieldName, stringValue) {\n  this.docRef = docRef\n  this.fieldName = fieldName\n  this._stringValue = stringValue\n}\n\nlunr.FieldRef.joiner = \"/\"\n\nlunr.FieldRef.fromString = function (s) {\n  var n = s.indexOf(lunr.FieldRef.joiner)\n\n  if (n === -1) {\n    throw \"malformed field ref string\"\n  }\n\n  var fieldRef = s.slice(0, n),\n      docRef = s.slice(n + 1)\n\n  return new lunr.FieldRef (docRef, fieldRef, s)\n}\n\nlunr.FieldRef.prototype.toString = function () {\n  if (this._stringValue == undefined) {\n    this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef\n  }\n\n  return this._stringValue\n}\n/*!\n * lunr.Set\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A lunr set.\n *\n * @constructor\n */\nlunr.Set = function (elements) {\n  this.elements = Object.create(null)\n\n  if (elements) {\n    this.length = elements.length\n\n    for (var i = 0; i < this.length; i++) {\n      this.elements[elements[i]] = true\n    }\n  } else {\n    this.length = 0\n  }\n}\n\n/**\n * A complete set that contains all elements.\n *\n * @static\n * @readonly\n * @type {lunr.Set}\n */\nlunr.Set.complete = {\n  intersect: function (other) {\n    return other\n  },\n\n  union: function () {\n    return this\n  },\n\n  contains: function () {\n    return true\n  }\n}\n\n/**\n * An empty set that contains no elements.\n *\n * @static\n * @readonly\n * @type {lunr.Set}\n */\nlunr.Set.empty = {\n  intersect: function () {\n    return this\n  },\n\n  union: function (other) {\n    return other\n  },\n\n  contains: function () {\n    return false\n  }\n}\n\n/**\n * Returns true if this set contains the specified object.\n *\n * @param {object} object - Object whose presence in this set is to be tested.\n * @returns {boolean} - True if this set contains the specified object.\n */\nlunr.Set.prototype.contains = function (object) {\n  return !!this.elements[object]\n}\n\n/**\n * Returns a new set containing only the elements that are present in both\n * this set and the specified set.\n *\n * @param {lunr.Set} other - set to intersect with this set.\n * @returns {lunr.Set} a new set that is the intersection of this and the specified set.\n */\n\nlunr.Set.prototype.intersect = function (other) {\n  var a, b, elements, intersection = []\n\n  if (other === lunr.Set.complete) {\n    return this\n  }\n\n  if (other === lunr.Set.empty) {\n    return other\n  }\n\n  if (this.length < other.length) {\n    a = this\n    b = other\n  } else {\n    a = other\n    b = this\n  }\n\n  elements = Object.keys(a.elements)\n\n  for (var i = 0; i < elements.length; i++) {\n    var element = elements[i]\n    if (element in b.elements) {\n      intersection.push(element)\n    }\n  }\n\n  return new lunr.Set (intersection)\n}\n\n/**\n * Returns a new set combining the elements of this and the specified set.\n *\n * @param {lunr.Set} other - set to union with this set.\n * @return {lunr.Set} a new set that is the union of this and the specified set.\n */\n\nlunr.Set.prototype.union = function (other) {\n  if (other === lunr.Set.complete) {\n    return lunr.Set.complete\n  }\n\n  if (other === lunr.Set.empty) {\n    return this\n  }\n\n  return new lunr.Set(Object.keys(this.elements).concat(Object.keys(other.elements)))\n}\n/**\n * A function to calculate the inverse document frequency for\n * a posting. This is shared between the builder and the index\n *\n * @private\n * @param {object} posting - The posting for a given term\n * @param {number} documentCount - The total number of documents.\n */\nlunr.idf = function (posting, documentCount) {\n  var documentsWithTerm = 0\n\n  for (var fieldName in posting) {\n    if (fieldName == '_index') continue // Ignore the term index, its not a field\n    documentsWithTerm += Object.keys(posting[fieldName]).length\n  }\n\n  var x = (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5)\n\n  return Math.log(1 + Math.abs(x))\n}\n\n/**\n * A token wraps a string representation of a token\n * as it is passed through the text processing pipeline.\n *\n * @constructor\n * @param {string} [str=''] - The string token being wrapped.\n * @param {object} [metadata={}] - Metadata associated with this token.\n */\nlunr.Token = function (str, metadata) {\n  this.str = str || \"\"\n  this.metadata = metadata || {}\n}\n\n/**\n * Returns the token string that is being wrapped by this object.\n *\n * @returns {string}\n */\nlunr.Token.prototype.toString = function () {\n  return this.str\n}\n\n/**\n * A token update function is used when updating or optionally\n * when cloning a token.\n *\n * @callback lunr.Token~updateFunction\n * @param {string} str - The string representation of the token.\n * @param {Object} metadata - All metadata associated with this token.\n */\n\n/**\n * Applies the given function to the wrapped string token.\n *\n * @example\n * token.update(function (str, metadata) {\n *   return str.toUpperCase()\n * })\n *\n * @param {lunr.Token~updateFunction} fn - A function to apply to the token string.\n * @returns {lunr.Token}\n */\nlunr.Token.prototype.update = function (fn) {\n  this.str = fn(this.str, this.metadata)\n  return this\n}\n\n/**\n * Creates a clone of this token. Optionally a function can be\n * applied to the cloned token.\n *\n * @param {lunr.Token~updateFunction} [fn] - An optional function to apply to the cloned token.\n * @returns {lunr.Token}\n */\nlunr.Token.prototype.clone = function (fn) {\n  fn = fn || function (s) { return s }\n  return new lunr.Token (fn(this.str, this.metadata), this.metadata)\n}\n/*!\n * lunr.tokenizer\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A function for splitting a string into tokens ready to be inserted into\n * the search index. Uses `lunr.tokenizer.separator` to split strings, change\n * the value of this property to change how strings are split into tokens.\n *\n * This tokenizer will convert its parameter to a string by calling `toString` and\n * then will split this string on the character in `lunr.tokenizer.separator`.\n * Arrays will have their elements converted to strings and wrapped in a lunr.Token.\n *\n * Optional metadata can be passed to the tokenizer, this metadata will be cloned and\n * added as metadata to every token that is created from the object to be tokenized.\n *\n * @static\n * @param {?(string|object|object[])} obj - The object to convert into tokens\n * @param {?object} metadata - Optional metadata to associate with every token\n * @returns {lunr.Token[]}\n * @see {@link lunr.Pipeline}\n */\nlunr.tokenizer = function (obj, metadata) {\n  if (obj == null || obj == undefined) {\n    return []\n  }\n\n  if (Array.isArray(obj)) {\n    return obj.map(function (t) {\n      return new lunr.Token(\n        lunr.utils.asString(t).toLowerCase(),\n        lunr.utils.clone(metadata)\n      )\n    })\n  }\n\n  var str = obj.toString().toLowerCase(),\n      len = str.length,\n      tokens = []\n\n  for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) {\n    var char = str.charAt(sliceEnd),\n        sliceLength = sliceEnd - sliceStart\n\n    if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) {\n\n      if (sliceLength > 0) {\n        var tokenMetadata = lunr.utils.clone(metadata) || {}\n        tokenMetadata[\"position\"] = [sliceStart, sliceLength]\n        tokenMetadata[\"index\"] = tokens.length\n\n        tokens.push(\n          new lunr.Token (\n            str.slice(sliceStart, sliceEnd),\n            tokenMetadata\n          )\n        )\n      }\n\n      sliceStart = sliceEnd + 1\n    }\n\n  }\n\n  return tokens\n}\n\n/**\n * The separator used to split a string into tokens. Override this property to change the behaviour of\n * `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens.\n *\n * @static\n * @see lunr.tokenizer\n */\nlunr.tokenizer.separator = /[\\s\\-]+/\n/*!\n * lunr.Pipeline\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.Pipelines maintain an ordered list of functions to be applied to all\n * tokens in documents entering the search index and queries being ran against\n * the index.\n *\n * An instance of lunr.Index created with the lunr shortcut will contain a\n * pipeline with a stop word filter and an English language stemmer. Extra\n * functions can be added before or after either of these functions or these\n * default functions can be removed.\n *\n * When run the pipeline will call each function in turn, passing a token, the\n * index of that token in the original list of all tokens and finally a list of\n * all the original tokens.\n *\n * The output of functions in the pipeline will be passed to the next function\n * in the pipeline. To exclude a token from entering the index the function\n * should return undefined, the rest of the pipeline will not be called with\n * this token.\n *\n * For serialisation of pipelines to work, all functions used in an instance of\n * a pipeline should be registered with lunr.Pipeline. Registered functions can\n * then be loaded. If trying to load a serialised pipeline that uses functions\n * that are not registered an error will be thrown.\n *\n * If not planning on serialising the pipeline then registering pipeline functions\n * is not necessary.\n *\n * @constructor\n */\nlunr.Pipeline = function () {\n  this._stack = []\n}\n\nlunr.Pipeline.registeredFunctions = Object.create(null)\n\n/**\n * A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token\n * string as well as all known metadata. A pipeline function can mutate the token string\n * or mutate (or add) metadata for a given token.\n *\n * A pipeline function can indicate that the passed token should be discarded by returning\n * null, undefined or an empty string. This token will not be passed to any downstream pipeline\n * functions and will not be added to the index.\n *\n * Multiple tokens can be returned by returning an array of tokens. Each token will be passed\n * to any downstream pipeline functions and all will returned tokens will be added to the index.\n *\n * Any number of pipeline functions may be chained together using a lunr.Pipeline.\n *\n * @interface lunr.PipelineFunction\n * @param {lunr.Token} token - A token from the document being processed.\n * @param {number} i - The index of this token in the complete list of tokens for this document/field.\n * @param {lunr.Token[]} tokens - All tokens for this document/field.\n * @returns {(?lunr.Token|lunr.Token[])}\n */\n\n/**\n * Register a function with the pipeline.\n *\n * Functions that are used in the pipeline should be registered if the pipeline\n * needs to be serialised, or a serialised pipeline needs to be loaded.\n *\n * Registering a function does not add it to a pipeline, functions must still be\n * added to instances of the pipeline for them to be used when running a pipeline.\n *\n * @param {lunr.PipelineFunction} fn - The function to check for.\n * @param {String} label - The label to register this function with\n */\nlunr.Pipeline.registerFunction = function (fn, label) {\n  if (label in this.registeredFunctions) {\n    lunr.utils.warn('Overwriting existing registered function: ' + label)\n  }\n\n  fn.label = label\n  lunr.Pipeline.registeredFunctions[fn.label] = fn\n}\n\n/**\n * Warns if the function is not registered as a Pipeline function.\n *\n * @param {lunr.PipelineFunction} fn - The function to check for.\n * @private\n */\nlunr.Pipeline.warnIfFunctionNotRegistered = function (fn) {\n  var isRegistered = fn.label && (fn.label in this.registeredFunctions)\n\n  if (!isRegistered) {\n    lunr.utils.warn('Function is not registered with pipeline. This may cause problems when serialising the index.\\n', fn)\n  }\n}\n\n/**\n * Loads a previously serialised pipeline.\n *\n * All functions to be loaded must already be registered with lunr.Pipeline.\n * If any function from the serialised data has not been registered then an\n * error will be thrown.\n *\n * @param {Object} serialised - The serialised pipeline to load.\n * @returns {lunr.Pipeline}\n */\nlunr.Pipeline.load = function (serialised) {\n  var pipeline = new lunr.Pipeline\n\n  serialised.forEach(function (fnName) {\n    var fn = lunr.Pipeline.registeredFunctions[fnName]\n\n    if (fn) {\n      pipeline.add(fn)\n    } else {\n      throw new Error('Cannot load unregistered function: ' + fnName)\n    }\n  })\n\n  return pipeline\n}\n\n/**\n * Adds new functions to the end of the pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction[]} functions - Any number of functions to add to the pipeline.\n */\nlunr.Pipeline.prototype.add = function () {\n  var fns = Array.prototype.slice.call(arguments)\n\n  fns.forEach(function (fn) {\n    lunr.Pipeline.warnIfFunctionNotRegistered(fn)\n    this._stack.push(fn)\n  }, this)\n}\n\n/**\n * Adds a single function after a function that already exists in the\n * pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.\n * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.\n */\nlunr.Pipeline.prototype.after = function (existingFn, newFn) {\n  lunr.Pipeline.warnIfFunctionNotRegistered(newFn)\n\n  var pos = this._stack.indexOf(existingFn)\n  if (pos == -1) {\n    throw new Error('Cannot find existingFn')\n  }\n\n  pos = pos + 1\n  this._stack.splice(pos, 0, newFn)\n}\n\n/**\n * Adds a single function before a function that already exists in the\n * pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.\n * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.\n */\nlunr.Pipeline.prototype.before = function (existingFn, newFn) {\n  lunr.Pipeline.warnIfFunctionNotRegistered(newFn)\n\n  var pos = this._stack.indexOf(existingFn)\n  if (pos == -1) {\n    throw new Error('Cannot find existingFn')\n  }\n\n  this._stack.splice(pos, 0, newFn)\n}\n\n/**\n * Removes a function from the pipeline.\n *\n * @param {lunr.PipelineFunction} fn The function to remove from the pipeline.\n */\nlunr.Pipeline.prototype.remove = function (fn) {\n  var pos = this._stack.indexOf(fn)\n  if (pos == -1) {\n    return\n  }\n\n  this._stack.splice(pos, 1)\n}\n\n/**\n * Runs the current list of functions that make up the pipeline against the\n * passed tokens.\n *\n * @param {Array} tokens The tokens to run through the pipeline.\n * @returns {Array}\n */\nlunr.Pipeline.prototype.run = function (tokens) {\n  var stackLength = this._stack.length\n\n  for (var i = 0; i < stackLength; i++) {\n    var fn = this._stack[i]\n    var memo = []\n\n    for (var j = 0; j < tokens.length; j++) {\n      var result = fn(tokens[j], j, tokens)\n\n      if (result === null || result === void 0 || result === '') continue\n\n      if (Array.isArray(result)) {\n        for (var k = 0; k < result.length; k++) {\n          memo.push(result[k])\n        }\n      } else {\n        memo.push(result)\n      }\n    }\n\n    tokens = memo\n  }\n\n  return tokens\n}\n\n/**\n * Convenience method for passing a string through a pipeline and getting\n * strings out. This method takes care of wrapping the passed string in a\n * token and mapping the resulting tokens back to strings.\n *\n * @param {string} str - The string to pass through the pipeline.\n * @param {?object} metadata - Optional metadata to associate with the token\n * passed to the pipeline.\n * @returns {string[]}\n */\nlunr.Pipeline.prototype.runString = function (str, metadata) {\n  var token = new lunr.Token (str, metadata)\n\n  return this.run([token]).map(function (t) {\n    return t.toString()\n  })\n}\n\n/**\n * Resets the pipeline by removing any existing processors.\n *\n */\nlunr.Pipeline.prototype.reset = function () {\n  this._stack = []\n}\n\n/**\n * Returns a representation of the pipeline ready for serialisation.\n *\n * Logs a warning if the function has not been registered.\n *\n * @returns {Array}\n */\nlunr.Pipeline.prototype.toJSON = function () {\n  return this._stack.map(function (fn) {\n    lunr.Pipeline.warnIfFunctionNotRegistered(fn)\n\n    return fn.label\n  })\n}\n/*!\n * lunr.Vector\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A vector is used to construct the vector space of documents and queries. These\n * vectors support operations to determine the similarity between two documents or\n * a document and a query.\n *\n * Normally no parameters are required for initializing a vector, but in the case of\n * loading a previously dumped vector the raw elements can be provided to the constructor.\n *\n * For performance reasons vectors are implemented with a flat array, where an elements\n * index is immediately followed by its value. E.g. [index, value, index, value]. This\n * allows the underlying array to be as sparse as possible and still offer decent\n * performance when being used for vector calculations.\n *\n * @constructor\n * @param {Number[]} [elements] - The flat list of element index and element value pairs.\n */\nlunr.Vector = function (elements) {\n  this._magnitude = 0\n  this.elements = elements || []\n}\n\n\n/**\n * Calculates the position within the vector to insert a given index.\n *\n * This is used internally by insert and upsert. If there are duplicate indexes then\n * the position is returned as if the value for that index were to be updated, but it\n * is the callers responsibility to check whether there is a duplicate at that index\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @returns {Number}\n */\nlunr.Vector.prototype.positionForIndex = function (index) {\n  // For an empty vector the tuple can be inserted at the beginning\n  if (this.elements.length == 0) {\n    return 0\n  }\n\n  var start = 0,\n      end = this.elements.length / 2,\n      sliceLength = end - start,\n      pivotPoint = Math.floor(sliceLength / 2),\n      pivotIndex = this.elements[pivotPoint * 2]\n\n  while (sliceLength > 1) {\n    if (pivotIndex < index) {\n      start = pivotPoint\n    }\n\n    if (pivotIndex > index) {\n      end = pivotPoint\n    }\n\n    if (pivotIndex == index) {\n      break\n    }\n\n    sliceLength = end - start\n    pivotPoint = start + Math.floor(sliceLength / 2)\n    pivotIndex = this.elements[pivotPoint * 2]\n  }\n\n  if (pivotIndex == index) {\n    return pivotPoint * 2\n  }\n\n  if (pivotIndex > index) {\n    return pivotPoint * 2\n  }\n\n  if (pivotIndex < index) {\n    return (pivotPoint + 1) * 2\n  }\n}\n\n/**\n * Inserts an element at an index within the vector.\n *\n * Does not allow duplicates, will throw an error if there is already an entry\n * for this index.\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @param {Number} val - The value to be inserted into the vector.\n */\nlunr.Vector.prototype.insert = function (insertIdx, val) {\n  this.upsert(insertIdx, val, function () {\n    throw \"duplicate index\"\n  })\n}\n\n/**\n * Inserts or updates an existing index within the vector.\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @param {Number} val - The value to be inserted into the vector.\n * @param {function} fn - A function that is called for updates, the existing value and the\n * requested value are passed as arguments\n */\nlunr.Vector.prototype.upsert = function (insertIdx, val, fn) {\n  this._magnitude = 0\n  var position = this.positionForIndex(insertIdx)\n\n  if (this.elements[position] == insertIdx) {\n    this.elements[position + 1] = fn(this.elements[position + 1], val)\n  } else {\n    this.elements.splice(position, 0, insertIdx, val)\n  }\n}\n\n/**\n * Calculates the magnitude of this vector.\n *\n * @returns {Number}\n */\nlunr.Vector.prototype.magnitude = function () {\n  if (this._magnitude) return this._magnitude\n\n  var sumOfSquares = 0,\n      elementsLength = this.elements.length\n\n  for (var i = 1; i < elementsLength; i += 2) {\n    var val = this.elements[i]\n    sumOfSquares += val * val\n  }\n\n  return this._magnitude = Math.sqrt(sumOfSquares)\n}\n\n/**\n * Calculates the dot product of this vector and another vector.\n *\n * @param {lunr.Vector} otherVector - The vector to compute the dot product with.\n * @returns {Number}\n */\nlunr.Vector.prototype.dot = function (otherVector) {\n  var dotProduct = 0,\n      a = this.elements, b = otherVector.elements,\n      aLen = a.length, bLen = b.length,\n      aVal = 0, bVal = 0,\n      i = 0, j = 0\n\n  while (i < aLen && j < bLen) {\n    aVal = a[i], bVal = b[j]\n    if (aVal < bVal) {\n      i += 2\n    } else if (aVal > bVal) {\n      j += 2\n    } else if (aVal == bVal) {\n      dotProduct += a[i + 1] * b[j + 1]\n      i += 2\n      j += 2\n    }\n  }\n\n  return dotProduct\n}\n\n/**\n * Calculates the similarity between this vector and another vector.\n *\n * @param {lunr.Vector} otherVector - The other vector to calculate the\n * similarity with.\n * @returns {Number}\n */\nlunr.Vector.prototype.similarity = function (otherVector) {\n  return this.dot(otherVector) / this.magnitude() || 0\n}\n\n/**\n * Converts the vector to an array of the elements within the vector.\n *\n * @returns {Number[]}\n */\nlunr.Vector.prototype.toArray = function () {\n  var output = new Array (this.elements.length / 2)\n\n  for (var i = 1, j = 0; i < this.elements.length; i += 2, j++) {\n    output[j] = this.elements[i]\n  }\n\n  return output\n}\n\n/**\n * A JSON serializable representation of the vector.\n *\n * @returns {Number[]}\n */\nlunr.Vector.prototype.toJSON = function () {\n  return this.elements\n}\n/* eslint-disable */\n/*!\n * lunr.stemmer\n * Copyright (C) 2020 Oliver Nightingale\n * Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt\n */\n\n/**\n * lunr.stemmer is an english language stemmer, this is a JavaScript\n * implementation of the PorterStemmer taken from http://tartarus.org/~martin\n *\n * @static\n * @implements {lunr.PipelineFunction}\n * @param {lunr.Token} token - The string to stem\n * @returns {lunr.Token}\n * @see {@link lunr.Pipeline}\n * @function\n */\nlunr.stemmer = (function(){\n  var step2list = {\n      \"ational\" : \"ate\",\n      \"tional\" : \"tion\",\n      \"enci\" : \"ence\",\n      \"anci\" : \"ance\",\n      \"izer\" : \"ize\",\n      \"bli\" : \"ble\",\n      \"alli\" : \"al\",\n      \"entli\" : \"ent\",\n      \"eli\" : \"e\",\n      \"ousli\" : \"ous\",\n      \"ization\" : \"ize\",\n      \"ation\" : \"ate\",\n      \"ator\" : \"ate\",\n      \"alism\" : \"al\",\n      \"iveness\" : \"ive\",\n      \"fulness\" : \"ful\",\n      \"ousness\" : \"ous\",\n      \"aliti\" : \"al\",\n      \"iviti\" : \"ive\",\n      \"biliti\" : \"ble\",\n      \"logi\" : \"log\"\n    },\n\n    step3list = {\n      \"icate\" : \"ic\",\n      \"ative\" : \"\",\n      \"alize\" : \"al\",\n      \"iciti\" : \"ic\",\n      \"ical\" : \"ic\",\n      \"ful\" : \"\",\n      \"ness\" : \"\"\n    },\n\n    c = \"[^aeiou]\",          // consonant\n    v = \"[aeiouy]\",          // vowel\n    C = c + \"[^aeiouy]*\",    // consonant sequence\n    V = v + \"[aeiou]*\",      // vowel sequence\n\n    mgr0 = \"^(\" + C + \")?\" + V + C,               // [C]VC... is m>0\n    meq1 = \"^(\" + C + \")?\" + V + C + \"(\" + V + \")?$\",  // [C]VC[V] is m=1\n    mgr1 = \"^(\" + C + \")?\" + V + C + V + C,       // [C]VCVC... is m>1\n    s_v = \"^(\" + C + \")?\" + v;                   // vowel in stem\n\n  var re_mgr0 = new RegExp(mgr0);\n  var re_mgr1 = new RegExp(mgr1);\n  var re_meq1 = new RegExp(meq1);\n  var re_s_v = new RegExp(s_v);\n\n  var re_1a = /^(.+?)(ss|i)es$/;\n  var re2_1a = /^(.+?)([^s])s$/;\n  var re_1b = /^(.+?)eed$/;\n  var re2_1b = /^(.+?)(ed|ing)$/;\n  var re_1b_2 = /.$/;\n  var re2_1b_2 = /(at|bl|iz)$/;\n  var re3_1b_2 = new RegExp(\"([^aeiouylsz])\\\\1$\");\n  var re4_1b_2 = new RegExp(\"^\" + C + v + \"[^aeiouwxy]$\");\n\n  var re_1c = /^(.+?[^aeiou])y$/;\n  var re_2 = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;\n\n  var re_3 = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;\n\n  var re_4 = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;\n  var re2_4 = /^(.+?)(s|t)(ion)$/;\n\n  var re_5 = /^(.+?)e$/;\n  var re_5_1 = /ll$/;\n  var re3_5 = new RegExp(\"^\" + C + v + \"[^aeiouwxy]$\");\n\n  var porterStemmer = function porterStemmer(w) {\n    var stem,\n      suffix,\n      firstch,\n      re,\n      re2,\n      re3,\n      re4;\n\n    if (w.length < 3) { return w; }\n\n    firstch = w.substr(0,1);\n    if (firstch == \"y\") {\n      w = firstch.toUpperCase() + w.substr(1);\n    }\n\n    // Step 1a\n    re = re_1a\n    re2 = re2_1a;\n\n    if (re.test(w)) { w = w.replace(re,\"$1$2\"); }\n    else if (re2.test(w)) { w = w.replace(re2,\"$1$2\"); }\n\n    // Step 1b\n    re = re_1b;\n    re2 = re2_1b;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      re = re_mgr0;\n      if (re.test(fp[1])) {\n        re = re_1b_2;\n        w = w.replace(re,\"\");\n      }\n    } else if (re2.test(w)) {\n      var fp = re2.exec(w);\n      stem = fp[1];\n      re2 = re_s_v;\n      if (re2.test(stem)) {\n        w = stem;\n        re2 = re2_1b_2;\n        re3 = re3_1b_2;\n        re4 = re4_1b_2;\n        if (re2.test(w)) { w = w + \"e\"; }\n        else if (re3.test(w)) { re = re_1b_2; w = w.replace(re,\"\"); }\n        else if (re4.test(w)) { w = w + \"e\"; }\n      }\n    }\n\n    // Step 1c - replace suffix y or Y by i if preceded by a non-vowel which is not the first letter of the word (so cry -> cri, by -> by, say -> say)\n    re = re_1c;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      w = stem + \"i\";\n    }\n\n    // Step 2\n    re = re_2;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      suffix = fp[2];\n      re = re_mgr0;\n      if (re.test(stem)) {\n        w = stem + step2list[suffix];\n      }\n    }\n\n    // Step 3\n    re = re_3;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      suffix = fp[2];\n      re = re_mgr0;\n      if (re.test(stem)) {\n        w = stem + step3list[suffix];\n      }\n    }\n\n    // Step 4\n    re = re_4;\n    re2 = re2_4;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      re = re_mgr1;\n      if (re.test(stem)) {\n        w = stem;\n      }\n    } else if (re2.test(w)) {\n      var fp = re2.exec(w);\n      stem = fp[1] + fp[2];\n      re2 = re_mgr1;\n      if (re2.test(stem)) {\n        w = stem;\n      }\n    }\n\n    // Step 5\n    re = re_5;\n    if (re.test(w)) {\n      var fp = re.exec(w);\n      stem = fp[1];\n      re = re_mgr1;\n      re2 = re_meq1;\n      re3 = re3_5;\n      if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) {\n        w = stem;\n      }\n    }\n\n    re = re_5_1;\n    re2 = re_mgr1;\n    if (re.test(w) && re2.test(w)) {\n      re = re_1b_2;\n      w = w.replace(re,\"\");\n    }\n\n    // and turn initial Y back to y\n\n    if (firstch == \"y\") {\n      w = firstch.toLowerCase() + w.substr(1);\n    }\n\n    return w;\n  };\n\n  return function (token) {\n    return token.update(porterStemmer);\n  }\n})();\n\nlunr.Pipeline.registerFunction(lunr.stemmer, 'stemmer')\n/*!\n * lunr.stopWordFilter\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.generateStopWordFilter builds a stopWordFilter function from the provided\n * list of stop words.\n *\n * The built in lunr.stopWordFilter is built using this generator and can be used\n * to generate custom stopWordFilters for applications or non English languages.\n *\n * @function\n * @param {Array} token The token to pass through the filter\n * @returns {lunr.PipelineFunction}\n * @see lunr.Pipeline\n * @see lunr.stopWordFilter\n */\nlunr.generateStopWordFilter = function (stopWords) {\n  var words = stopWords.reduce(function (memo, stopWord) {\n    memo[stopWord] = stopWord\n    return memo\n  }, {})\n\n  return function (token) {\n    if (token && words[token.toString()] !== token.toString()) return token\n  }\n}\n\n/**\n * lunr.stopWordFilter is an English language stop word list filter, any words\n * contained in the list will not be passed through the filter.\n *\n * This is intended to be used in the Pipeline. If the token does not pass the\n * filter then undefined will be returned.\n *\n * @function\n * @implements {lunr.PipelineFunction}\n * @params {lunr.Token} token - A token to check for being a stop word.\n * @returns {lunr.Token}\n * @see {@link lunr.Pipeline}\n */\nlunr.stopWordFilter = lunr.generateStopWordFilter([\n  'a',\n  'able',\n  'about',\n  'across',\n  'after',\n  'all',\n  'almost',\n  'also',\n  'am',\n  'among',\n  'an',\n  'and',\n  'any',\n  'are',\n  'as',\n  'at',\n  'be',\n  'because',\n  'been',\n  'but',\n  'by',\n  'can',\n  'cannot',\n  'could',\n  'dear',\n  'did',\n  'do',\n  'does',\n  'either',\n  'else',\n  'ever',\n  'every',\n  'for',\n  'from',\n  'get',\n  'got',\n  'had',\n  'has',\n  'have',\n  'he',\n  'her',\n  'hers',\n  'him',\n  'his',\n  'how',\n  'however',\n  'i',\n  'if',\n  'in',\n  'into',\n  'is',\n  'it',\n  'its',\n  'just',\n  'least',\n  'let',\n  'like',\n  'likely',\n  'may',\n  'me',\n  'might',\n  'most',\n  'must',\n  'my',\n  'neither',\n  'no',\n  'nor',\n  'not',\n  'of',\n  'off',\n  'often',\n  'on',\n  'only',\n  'or',\n  'other',\n  'our',\n  'own',\n  'rather',\n  'said',\n  'say',\n  'says',\n  'she',\n  'should',\n  'since',\n  'so',\n  'some',\n  'than',\n  'that',\n  'the',\n  'their',\n  'them',\n  'then',\n  'there',\n  'these',\n  'they',\n  'this',\n  'tis',\n  'to',\n  'too',\n  'twas',\n  'us',\n  'wants',\n  'was',\n  'we',\n  'were',\n  'what',\n  'when',\n  'where',\n  'which',\n  'while',\n  'who',\n  'whom',\n  'why',\n  'will',\n  'with',\n  'would',\n  'yet',\n  'you',\n  'your'\n])\n\nlunr.Pipeline.registerFunction(lunr.stopWordFilter, 'stopWordFilter')\n/*!\n * lunr.trimmer\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.trimmer is a pipeline function for trimming non word\n * characters from the beginning and end of tokens before they\n * enter the index.\n *\n * This implementation may not work correctly for non latin\n * characters and should either be removed or adapted for use\n * with languages with non-latin characters.\n *\n * @static\n * @implements {lunr.PipelineFunction}\n * @param {lunr.Token} token The token to pass through the filter\n * @returns {lunr.Token}\n * @see lunr.Pipeline\n */\nlunr.trimmer = function (token) {\n  return token.update(function (s) {\n    return s.replace(/^\\W+/, '').replace(/\\W+$/, '')\n  })\n}\n\nlunr.Pipeline.registerFunction(lunr.trimmer, 'trimmer')\n/*!\n * lunr.TokenSet\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A token set is used to store the unique list of all tokens\n * within an index. Token sets are also used to represent an\n * incoming query to the index, this query token set and index\n * token set are then intersected to find which tokens to look\n * up in the inverted index.\n *\n * A token set can hold multiple tokens, as in the case of the\n * index token set, or it can hold a single token as in the\n * case of a simple query token set.\n *\n * Additionally token sets are used to perform wildcard matching.\n * Leading, contained and trailing wildcards are supported, and\n * from this edit distance matching can also be provided.\n *\n * Token sets are implemented as a minimal finite state automata,\n * where both common prefixes and suffixes are shared between tokens.\n * This helps to reduce the space used for storing the token set.\n *\n * @constructor\n */\nlunr.TokenSet = function () {\n  this.final = false\n  this.edges = {}\n  this.id = lunr.TokenSet._nextId\n  lunr.TokenSet._nextId += 1\n}\n\n/**\n * Keeps track of the next, auto increment, identifier to assign\n * to a new tokenSet.\n *\n * TokenSets require a unique identifier to be correctly minimised.\n *\n * @private\n */\nlunr.TokenSet._nextId = 1\n\n/**\n * Creates a TokenSet instance from the given sorted array of words.\n *\n * @param {String[]} arr - A sorted array of strings to create the set from.\n * @returns {lunr.TokenSet}\n * @throws Will throw an error if the input array is not sorted.\n */\nlunr.TokenSet.fromArray = function (arr) {\n  var builder = new lunr.TokenSet.Builder\n\n  for (var i = 0, len = arr.length; i < len; i++) {\n    builder.insert(arr[i])\n  }\n\n  builder.finish()\n  return builder.root\n}\n\n/**\n * Creates a token set from a query clause.\n *\n * @private\n * @param {Object} clause - A single clause from lunr.Query.\n * @param {string} clause.term - The query clause term.\n * @param {number} [clause.editDistance] - The optional edit distance for the term.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.fromClause = function (clause) {\n  if ('editDistance' in clause) {\n    return lunr.TokenSet.fromFuzzyString(clause.term, clause.editDistance)\n  } else {\n    return lunr.TokenSet.fromString(clause.term)\n  }\n}\n\n/**\n * Creates a token set representing a single string with a specified\n * edit distance.\n *\n * Insertions, deletions, substitutions and transpositions are each\n * treated as an edit distance of 1.\n *\n * Increasing the allowed edit distance will have a dramatic impact\n * on the performance of both creating and intersecting these TokenSets.\n * It is advised to keep the edit distance less than 3.\n *\n * @param {string} str - The string to create the token set from.\n * @param {number} editDistance - The allowed edit distance to match.\n * @returns {lunr.Vector}\n */\nlunr.TokenSet.fromFuzzyString = function (str, editDistance) {\n  var root = new lunr.TokenSet\n\n  var stack = [{\n    node: root,\n    editsRemaining: editDistance,\n    str: str\n  }]\n\n  while (stack.length) {\n    var frame = stack.pop()\n\n    // no edit\n    if (frame.str.length > 0) {\n      var char = frame.str.charAt(0),\n          noEditNode\n\n      if (char in frame.node.edges) {\n        noEditNode = frame.node.edges[char]\n      } else {\n        noEditNode = new lunr.TokenSet\n        frame.node.edges[char] = noEditNode\n      }\n\n      if (frame.str.length == 1) {\n        noEditNode.final = true\n      }\n\n      stack.push({\n        node: noEditNode,\n        editsRemaining: frame.editsRemaining,\n        str: frame.str.slice(1)\n      })\n    }\n\n    if (frame.editsRemaining == 0) {\n      continue\n    }\n\n    // insertion\n    if (\"*\" in frame.node.edges) {\n      var insertionNode = frame.node.edges[\"*\"]\n    } else {\n      var insertionNode = new lunr.TokenSet\n      frame.node.edges[\"*\"] = insertionNode\n    }\n\n    if (frame.str.length == 0) {\n      insertionNode.final = true\n    }\n\n    stack.push({\n      node: insertionNode,\n      editsRemaining: frame.editsRemaining - 1,\n      str: frame.str\n    })\n\n    // deletion\n    // can only do a deletion if we have enough edits remaining\n    // and if there are characters left to delete in the string\n    if (frame.str.length > 1) {\n      stack.push({\n        node: frame.node,\n        editsRemaining: frame.editsRemaining - 1,\n        str: frame.str.slice(1)\n      })\n    }\n\n    // deletion\n    // just removing the last character from the str\n    if (frame.str.length == 1) {\n      frame.node.final = true\n    }\n\n    // substitution\n    // can only do a substitution if we have enough edits remaining\n    // and if there are characters left to substitute\n    if (frame.str.length >= 1) {\n      if (\"*\" in frame.node.edges) {\n        var substitutionNode = frame.node.edges[\"*\"]\n      } else {\n        var substitutionNode = new lunr.TokenSet\n        frame.node.edges[\"*\"] = substitutionNode\n      }\n\n      if (frame.str.length == 1) {\n        substitutionNode.final = true\n      }\n\n      stack.push({\n        node: substitutionNode,\n        editsRemaining: frame.editsRemaining - 1,\n        str: frame.str.slice(1)\n      })\n    }\n\n    // transposition\n    // can only do a transposition if there are edits remaining\n    // and there are enough characters to transpose\n    if (frame.str.length > 1) {\n      var charA = frame.str.charAt(0),\n          charB = frame.str.charAt(1),\n          transposeNode\n\n      if (charB in frame.node.edges) {\n        transposeNode = frame.node.edges[charB]\n      } else {\n        transposeNode = new lunr.TokenSet\n        frame.node.edges[charB] = transposeNode\n      }\n\n      if (frame.str.length == 1) {\n        transposeNode.final = true\n      }\n\n      stack.push({\n        node: transposeNode,\n        editsRemaining: frame.editsRemaining - 1,\n        str: charA + frame.str.slice(2)\n      })\n    }\n  }\n\n  return root\n}\n\n/**\n * Creates a TokenSet from a string.\n *\n * The string may contain one or more wildcard characters (*)\n * that will allow wildcard matching when intersecting with\n * another TokenSet.\n *\n * @param {string} str - The string to create a TokenSet from.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.fromString = function (str) {\n  var node = new lunr.TokenSet,\n      root = node\n\n  /*\n   * Iterates through all characters within the passed string\n   * appending a node for each character.\n   *\n   * When a wildcard character is found then a self\n   * referencing edge is introduced to continually match\n   * any number of any characters.\n   */\n  for (var i = 0, len = str.length; i < len; i++) {\n    var char = str[i],\n        final = (i == len - 1)\n\n    if (char == \"*\") {\n      node.edges[char] = node\n      node.final = final\n\n    } else {\n      var next = new lunr.TokenSet\n      next.final = final\n\n      node.edges[char] = next\n      node = next\n    }\n  }\n\n  return root\n}\n\n/**\n * Converts this TokenSet into an array of strings\n * contained within the TokenSet.\n *\n * This is not intended to be used on a TokenSet that\n * contains wildcards, in these cases the results are\n * undefined and are likely to cause an infinite loop.\n *\n * @returns {string[]}\n */\nlunr.TokenSet.prototype.toArray = function () {\n  var words = []\n\n  var stack = [{\n    prefix: \"\",\n    node: this\n  }]\n\n  while (stack.length) {\n    var frame = stack.pop(),\n        edges = Object.keys(frame.node.edges),\n        len = edges.length\n\n    if (frame.node.final) {\n      /* In Safari, at this point the prefix is sometimes corrupted, see:\n       * https://github.com/olivernn/lunr.js/issues/279 Calling any\n       * String.prototype method forces Safari to \"cast\" this string to what\n       * it's supposed to be, fixing the bug. */\n      frame.prefix.charAt(0)\n      words.push(frame.prefix)\n    }\n\n    for (var i = 0; i < len; i++) {\n      var edge = edges[i]\n\n      stack.push({\n        prefix: frame.prefix.concat(edge),\n        node: frame.node.edges[edge]\n      })\n    }\n  }\n\n  return words\n}\n\n/**\n * Generates a string representation of a TokenSet.\n *\n * This is intended to allow TokenSets to be used as keys\n * in objects, largely to aid the construction and minimisation\n * of a TokenSet. As such it is not designed to be a human\n * friendly representation of the TokenSet.\n *\n * @returns {string}\n */\nlunr.TokenSet.prototype.toString = function () {\n  // NOTE: Using Object.keys here as this.edges is very likely\n  // to enter 'hash-mode' with many keys being added\n  //\n  // avoiding a for-in loop here as it leads to the function\n  // being de-optimised (at least in V8). From some simple\n  // benchmarks the performance is comparable, but allowing\n  // V8 to optimize may mean easy performance wins in the future.\n\n  if (this._str) {\n    return this._str\n  }\n\n  var str = this.final ? '1' : '0',\n      labels = Object.keys(this.edges).sort(),\n      len = labels.length\n\n  for (var i = 0; i < len; i++) {\n    var label = labels[i],\n        node = this.edges[label]\n\n    str = str + label + node.id\n  }\n\n  return str\n}\n\n/**\n * Returns a new TokenSet that is the intersection of\n * this TokenSet and the passed TokenSet.\n *\n * This intersection will take into account any wildcards\n * contained within the TokenSet.\n *\n * @param {lunr.TokenSet} b - An other TokenSet to intersect with.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.prototype.intersect = function (b) {\n  var output = new lunr.TokenSet,\n      frame = undefined\n\n  var stack = [{\n    qNode: b,\n    output: output,\n    node: this\n  }]\n\n  while (stack.length) {\n    frame = stack.pop()\n\n    // NOTE: As with the #toString method, we are using\n    // Object.keys and a for loop instead of a for-in loop\n    // as both of these objects enter 'hash' mode, causing\n    // the function to be de-optimised in V8\n    var qEdges = Object.keys(frame.qNode.edges),\n        qLen = qEdges.length,\n        nEdges = Object.keys(frame.node.edges),\n        nLen = nEdges.length\n\n    for (var q = 0; q < qLen; q++) {\n      var qEdge = qEdges[q]\n\n      for (var n = 0; n < nLen; n++) {\n        var nEdge = nEdges[n]\n\n        if (nEdge == qEdge || qEdge == '*') {\n          var node = frame.node.edges[nEdge],\n              qNode = frame.qNode.edges[qEdge],\n              final = node.final && qNode.final,\n              next = undefined\n\n          if (nEdge in frame.output.edges) {\n            // an edge already exists for this character\n            // no need to create a new node, just set the finality\n            // bit unless this node is already final\n            next = frame.output.edges[nEdge]\n            next.final = next.final || final\n\n          } else {\n            // no edge exists yet, must create one\n            // set the finality bit and insert it\n            // into the output\n            next = new lunr.TokenSet\n            next.final = final\n            frame.output.edges[nEdge] = next\n          }\n\n          stack.push({\n            qNode: qNode,\n            output: next,\n            node: node\n          })\n        }\n      }\n    }\n  }\n\n  return output\n}\nlunr.TokenSet.Builder = function () {\n  this.previousWord = \"\"\n  this.root = new lunr.TokenSet\n  this.uncheckedNodes = []\n  this.minimizedNodes = {}\n}\n\nlunr.TokenSet.Builder.prototype.insert = function (word) {\n  var node,\n      commonPrefix = 0\n\n  if (word < this.previousWord) {\n    throw new Error (\"Out of order word insertion\")\n  }\n\n  for (var i = 0; i < word.length && i < this.previousWord.length; i++) {\n    if (word[i] != this.previousWord[i]) break\n    commonPrefix++\n  }\n\n  this.minimize(commonPrefix)\n\n  if (this.uncheckedNodes.length == 0) {\n    node = this.root\n  } else {\n    node = this.uncheckedNodes[this.uncheckedNodes.length - 1].child\n  }\n\n  for (var i = commonPrefix; i < word.length; i++) {\n    var nextNode = new lunr.TokenSet,\n        char = word[i]\n\n    node.edges[char] = nextNode\n\n    this.uncheckedNodes.push({\n      parent: node,\n      char: char,\n      child: nextNode\n    })\n\n    node = nextNode\n  }\n\n  node.final = true\n  this.previousWord = word\n}\n\nlunr.TokenSet.Builder.prototype.finish = function () {\n  this.minimize(0)\n}\n\nlunr.TokenSet.Builder.prototype.minimize = function (downTo) {\n  for (var i = this.uncheckedNodes.length - 1; i >= downTo; i--) {\n    var node = this.uncheckedNodes[i],\n        childKey = node.child.toString()\n\n    if (childKey in this.minimizedNodes) {\n      node.parent.edges[node.char] = this.minimizedNodes[childKey]\n    } else {\n      // Cache the key for this node since\n      // we know it can't change anymore\n      node.child._str = childKey\n\n      this.minimizedNodes[childKey] = node.child\n    }\n\n    this.uncheckedNodes.pop()\n  }\n}\n/*!\n * lunr.Index\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * An index contains the built index of all documents and provides a query interface\n * to the index.\n *\n * Usually instances of lunr.Index will not be created using this constructor, instead\n * lunr.Builder should be used to construct new indexes, or lunr.Index.load should be\n * used to load previously built and serialized indexes.\n *\n * @constructor\n * @param {Object} attrs - The attributes of the built search index.\n * @param {Object} attrs.invertedIndex - An index of term/field to document reference.\n * @param {Object<string, lunr.Vector>} attrs.fieldVectors - Field vectors\n * @param {lunr.TokenSet} attrs.tokenSet - An set of all corpus tokens.\n * @param {string[]} attrs.fields - The names of indexed document fields.\n * @param {lunr.Pipeline} attrs.pipeline - The pipeline to use for search terms.\n */\nlunr.Index = function (attrs) {\n  this.invertedIndex = attrs.invertedIndex\n  this.fieldVectors = attrs.fieldVectors\n  this.tokenSet = attrs.tokenSet\n  this.fields = attrs.fields\n  this.pipeline = attrs.pipeline\n}\n\n/**\n * A result contains details of a document matching a search query.\n * @typedef {Object} lunr.Index~Result\n * @property {string} ref - The reference of the document this result represents.\n * @property {number} score - A number between 0 and 1 representing how similar this document is to the query.\n * @property {lunr.MatchData} matchData - Contains metadata about this match including which term(s) caused the match.\n */\n\n/**\n * Although lunr provides the ability to create queries using lunr.Query, it also provides a simple\n * query language which itself is parsed into an instance of lunr.Query.\n *\n * For programmatically building queries it is advised to directly use lunr.Query, the query language\n * is best used for human entered text rather than program generated text.\n *\n * At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported\n * and will be combined with OR, e.g `hello world` will match documents that contain either 'hello'\n * or 'world', though those that contain both will rank higher in the results.\n *\n * Wildcards can be included in terms to match one or more unspecified characters, these wildcards can\n * be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding\n * wildcards will increase the number of documents that will be found but can also have a negative\n * impact on query performance, especially with wildcards at the beginning of a term.\n *\n * Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term\n * hello in the title field will match this query. Using a field not present in the index will lead\n * to an error being thrown.\n *\n * Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term\n * boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported\n * to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2.\n * Avoid large values for edit distance to improve query performance.\n *\n * Each term also supports a presence modifier. By default a term's presence in document is optional, however\n * this can be changed to either required or prohibited. For a term's presence to be required in a document the\n * term should be prefixed with a '+', e.g. `+foo bar` is a search for documents that must contain 'foo' and\n * optionally contain 'bar'. Conversely a leading '-' sets the terms presence to prohibited, i.e. it must not\n * appear in a document, e.g. `-foo bar` is a search for documents that do not contain 'foo' but may contain 'bar'.\n *\n * To escape special characters the backslash character '\\' can be used, this allows searches to include\n * characters that would normally be considered modifiers, e.g. `foo\\~2` will search for a term \"foo~2\" instead\n * of attempting to apply a boost of 2 to the search term \"foo\".\n *\n * @typedef {string} lunr.Index~QueryString\n * @example <caption>Simple single term query</caption>\n * hello\n * @example <caption>Multiple term query</caption>\n * hello world\n * @example <caption>term scoped to a field</caption>\n * title:hello\n * @example <caption>term with a boost of 10</caption>\n * hello^10\n * @example <caption>term with an edit distance of 2</caption>\n * hello~2\n * @example <caption>terms with presence modifiers</caption>\n * -foo +bar baz\n */\n\n/**\n * Performs a search against the index using lunr query syntax.\n *\n * Results will be returned sorted by their score, the most relevant results\n * will be returned first.  For details on how the score is calculated, please see\n * the {@link https://lunrjs.com/guides/searching.html#scoring|guide}.\n *\n * For more programmatic querying use lunr.Index#query.\n *\n * @param {lunr.Index~QueryString} queryString - A string containing a lunr query.\n * @throws {lunr.QueryParseError} If the passed query string cannot be parsed.\n * @returns {lunr.Index~Result[]}\n */\nlunr.Index.prototype.search = function (queryString) {\n  return this.query(function (query) {\n    var parser = new lunr.QueryParser(queryString, query)\n    parser.parse()\n  })\n}\n\n/**\n * A query builder callback provides a query object to be used to express\n * the query to perform on the index.\n *\n * @callback lunr.Index~queryBuilder\n * @param {lunr.Query} query - The query object to build up.\n * @this lunr.Query\n */\n\n/**\n * Performs a query against the index using the yielded lunr.Query object.\n *\n * If performing programmatic queries against the index, this method is preferred\n * over lunr.Index#search so as to avoid the additional query parsing overhead.\n *\n * A query object is yielded to the supplied function which should be used to\n * express the query to be run against the index.\n *\n * Note that although this function takes a callback parameter it is _not_ an\n * asynchronous operation, the callback is just yielded a query object to be\n * customized.\n *\n * @param {lunr.Index~queryBuilder} fn - A function that is used to build the query.\n * @returns {lunr.Index~Result[]}\n */\nlunr.Index.prototype.query = function (fn) {\n  // for each query clause\n  // * process terms\n  // * expand terms from token set\n  // * find matching documents and metadata\n  // * get document vectors\n  // * score documents\n\n  var query = new lunr.Query(this.fields),\n      matchingFields = Object.create(null),\n      queryVectors = Object.create(null),\n      termFieldCache = Object.create(null),\n      requiredMatches = Object.create(null),\n      prohibitedMatches = Object.create(null)\n\n  /*\n   * To support field level boosts a query vector is created per\n   * field. An empty vector is eagerly created to support negated\n   * queries.\n   */\n  for (var i = 0; i < this.fields.length; i++) {\n    queryVectors[this.fields[i]] = new lunr.Vector\n  }\n\n  fn.call(query, query)\n\n  for (var i = 0; i < query.clauses.length; i++) {\n    /*\n     * Unless the pipeline has been disabled for this term, which is\n     * the case for terms with wildcards, we need to pass the clause\n     * term through the search pipeline. A pipeline returns an array\n     * of processed terms. Pipeline functions may expand the passed\n     * term, which means we may end up performing multiple index lookups\n     * for a single query term.\n     */\n    var clause = query.clauses[i],\n        terms = null,\n        clauseMatches = lunr.Set.empty\n\n    if (clause.usePipeline) {\n      terms = this.pipeline.runString(clause.term, {\n        fields: clause.fields\n      })\n    } else {\n      terms = [clause.term]\n    }\n\n    for (var m = 0; m < terms.length; m++) {\n      var term = terms[m]\n\n      /*\n       * Each term returned from the pipeline needs to use the same query\n       * clause object, e.g. the same boost and or edit distance. The\n       * simplest way to do this is to re-use the clause object but mutate\n       * its term property.\n       */\n      clause.term = term\n\n      /*\n       * From the term in the clause we create a token set which will then\n       * be used to intersect the indexes token set to get a list of terms\n       * to lookup in the inverted index\n       */\n      var termTokenSet = lunr.TokenSet.fromClause(clause),\n          expandedTerms = this.tokenSet.intersect(termTokenSet).toArray()\n\n      /*\n       * If a term marked as required does not exist in the tokenSet it is\n       * impossible for the search to return any matches. We set all the field\n       * scoped required matches set to empty and stop examining any further\n       * clauses.\n       */\n      if (expandedTerms.length === 0 && clause.presence === lunr.Query.presence.REQUIRED) {\n        for (var k = 0; k < clause.fields.length; k++) {\n          var field = clause.fields[k]\n          requiredMatches[field] = lunr.Set.empty\n        }\n\n        break\n      }\n\n      for (var j = 0; j < expandedTerms.length; j++) {\n        /*\n         * For each term get the posting and termIndex, this is required for\n         * building the query vector.\n         */\n        var expandedTerm = expandedTerms[j],\n            posting = this.invertedIndex[expandedTerm],\n            termIndex = posting._index\n\n        for (var k = 0; k < clause.fields.length; k++) {\n          /*\n           * For each field that this query term is scoped by (by default\n           * all fields are in scope) we need to get all the document refs\n           * that have this term in that field.\n           *\n           * The posting is the entry in the invertedIndex for the matching\n           * term from above.\n           */\n          var field = clause.fields[k],\n              fieldPosting = posting[field],\n              matchingDocumentRefs = Object.keys(fieldPosting),\n              termField = expandedTerm + \"/\" + field,\n              matchingDocumentsSet = new lunr.Set(matchingDocumentRefs)\n\n          /*\n           * if the presence of this term is required ensure that the matching\n           * documents are added to the set of required matches for this clause.\n           *\n           */\n          if (clause.presence == lunr.Query.presence.REQUIRED) {\n            clauseMatches = clauseMatches.union(matchingDocumentsSet)\n\n            if (requiredMatches[field] === undefined) {\n              requiredMatches[field] = lunr.Set.complete\n            }\n          }\n\n          /*\n           * if the presence of this term is prohibited ensure that the matching\n           * documents are added to the set of prohibited matches for this field,\n           * creating that set if it does not yet exist.\n           */\n          if (clause.presence == lunr.Query.presence.PROHIBITED) {\n            if (prohibitedMatches[field] === undefined) {\n              prohibitedMatches[field] = lunr.Set.empty\n            }\n\n            prohibitedMatches[field] = prohibitedMatches[field].union(matchingDocumentsSet)\n\n            /*\n             * Prohibited matches should not be part of the query vector used for\n             * similarity scoring and no metadata should be extracted so we continue\n             * to the next field\n             */\n            continue\n          }\n\n          /*\n           * The query field vector is populated using the termIndex found for\n           * the term and a unit value with the appropriate boost applied.\n           * Using upsert because there could already be an entry in the vector\n           * for the term we are working with. In that case we just add the scores\n           * together.\n           */\n          queryVectors[field].upsert(termIndex, clause.boost, function (a, b) { return a + b })\n\n          /**\n           * If we've already seen this term, field combo then we've already collected\n           * the matching documents and metadata, no need to go through all that again\n           */\n          if (termFieldCache[termField]) {\n            continue\n          }\n\n          for (var l = 0; l < matchingDocumentRefs.length; l++) {\n            /*\n             * All metadata for this term/field/document triple\n             * are then extracted and collected into an instance\n             * of lunr.MatchData ready to be returned in the query\n             * results\n             */\n            var matchingDocumentRef = matchingDocumentRefs[l],\n                matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field),\n                metadata = fieldPosting[matchingDocumentRef],\n                fieldMatch\n\n            if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) {\n              matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata)\n            } else {\n              fieldMatch.add(expandedTerm, field, metadata)\n            }\n\n          }\n\n          termFieldCache[termField] = true\n        }\n      }\n    }\n\n    /**\n     * If the presence was required we need to update the requiredMatches field sets.\n     * We do this after all fields for the term have collected their matches because\n     * the clause terms presence is required in _any_ of the fields not _all_ of the\n     * fields.\n     */\n    if (clause.presence === lunr.Query.presence.REQUIRED) {\n      for (var k = 0; k < clause.fields.length; k++) {\n        var field = clause.fields[k]\n        requiredMatches[field] = requiredMatches[field].intersect(clauseMatches)\n      }\n    }\n  }\n\n  /**\n   * Need to combine the field scoped required and prohibited\n   * matching documents into a global set of required and prohibited\n   * matches\n   */\n  var allRequiredMatches = lunr.Set.complete,\n      allProhibitedMatches = lunr.Set.empty\n\n  for (var i = 0; i < this.fields.length; i++) {\n    var field = this.fields[i]\n\n    if (requiredMatches[field]) {\n      allRequiredMatches = allRequiredMatches.intersect(requiredMatches[field])\n    }\n\n    if (prohibitedMatches[field]) {\n      allProhibitedMatches = allProhibitedMatches.union(prohibitedMatches[field])\n    }\n  }\n\n  var matchingFieldRefs = Object.keys(matchingFields),\n      results = [],\n      matches = Object.create(null)\n\n  /*\n   * If the query is negated (contains only prohibited terms)\n   * we need to get _all_ fieldRefs currently existing in the\n   * index. This is only done when we know that the query is\n   * entirely prohibited terms to avoid any cost of getting all\n   * fieldRefs unnecessarily.\n   *\n   * Additionally, blank MatchData must be created to correctly\n   * populate the results.\n   */\n  if (query.isNegated()) {\n    matchingFieldRefs = Object.keys(this.fieldVectors)\n\n    for (var i = 0; i < matchingFieldRefs.length; i++) {\n      var matchingFieldRef = matchingFieldRefs[i]\n      var fieldRef = lunr.FieldRef.fromString(matchingFieldRef)\n      matchingFields[matchingFieldRef] = new lunr.MatchData\n    }\n  }\n\n  for (var i = 0; i < matchingFieldRefs.length; i++) {\n    /*\n     * Currently we have document fields that match the query, but we\n     * need to return documents. The matchData and scores are combined\n     * from multiple fields belonging to the same document.\n     *\n     * Scores are calculated by field, using the query vectors created\n     * above, and combined into a final document score using addition.\n     */\n    var fieldRef = lunr.FieldRef.fromString(matchingFieldRefs[i]),\n        docRef = fieldRef.docRef\n\n    if (!allRequiredMatches.contains(docRef)) {\n      continue\n    }\n\n    if (allProhibitedMatches.contains(docRef)) {\n      continue\n    }\n\n    var fieldVector = this.fieldVectors[fieldRef],\n        score = queryVectors[fieldRef.fieldName].similarity(fieldVector),\n        docMatch\n\n    if ((docMatch = matches[docRef]) !== undefined) {\n      docMatch.score += score\n      docMatch.matchData.combine(matchingFields[fieldRef])\n    } else {\n      var match = {\n        ref: docRef,\n        score: score,\n        matchData: matchingFields[fieldRef]\n      }\n      matches[docRef] = match\n      results.push(match)\n    }\n  }\n\n  /*\n   * Sort the results objects by score, highest first.\n   */\n  return results.sort(function (a, b) {\n    return b.score - a.score\n  })\n}\n\n/**\n * Prepares the index for JSON serialization.\n *\n * The schema for this JSON blob will be described in a\n * separate JSON schema file.\n *\n * @returns {Object}\n */\nlunr.Index.prototype.toJSON = function () {\n  var invertedIndex = Object.keys(this.invertedIndex)\n    .sort()\n    .map(function (term) {\n      return [term, this.invertedIndex[term]]\n    }, this)\n\n  var fieldVectors = Object.keys(this.fieldVectors)\n    .map(function (ref) {\n      return [ref, this.fieldVectors[ref].toJSON()]\n    }, this)\n\n  return {\n    version: lunr.version,\n    fields: this.fields,\n    fieldVectors: fieldVectors,\n    invertedIndex: invertedIndex,\n    pipeline: this.pipeline.toJSON()\n  }\n}\n\n/**\n * Loads a previously serialized lunr.Index\n *\n * @param {Object} serializedIndex - A previously serialized lunr.Index\n * @returns {lunr.Index}\n */\nlunr.Index.load = function (serializedIndex) {\n  var attrs = {},\n      fieldVectors = {},\n      serializedVectors = serializedIndex.fieldVectors,\n      invertedIndex = Object.create(null),\n      serializedInvertedIndex = serializedIndex.invertedIndex,\n      tokenSetBuilder = new lunr.TokenSet.Builder,\n      pipeline = lunr.Pipeline.load(serializedIndex.pipeline)\n\n  if (serializedIndex.version != lunr.version) {\n    lunr.utils.warn(\"Version mismatch when loading serialised index. Current version of lunr '\" + lunr.version + \"' does not match serialized index '\" + serializedIndex.version + \"'\")\n  }\n\n  for (var i = 0; i < serializedVectors.length; i++) {\n    var tuple = serializedVectors[i],\n        ref = tuple[0],\n        elements = tuple[1]\n\n    fieldVectors[ref] = new lunr.Vector(elements)\n  }\n\n  for (var i = 0; i < serializedInvertedIndex.length; i++) {\n    var tuple = serializedInvertedIndex[i],\n        term = tuple[0],\n        posting = tuple[1]\n\n    tokenSetBuilder.insert(term)\n    invertedIndex[term] = posting\n  }\n\n  tokenSetBuilder.finish()\n\n  attrs.fields = serializedIndex.fields\n\n  attrs.fieldVectors = fieldVectors\n  attrs.invertedIndex = invertedIndex\n  attrs.tokenSet = tokenSetBuilder.root\n  attrs.pipeline = pipeline\n\n  return new lunr.Index(attrs)\n}\n/*!\n * lunr.Builder\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.Builder performs indexing on a set of documents and\n * returns instances of lunr.Index ready for querying.\n *\n * All configuration of the index is done via the builder, the\n * fields to index, the document reference, the text processing\n * pipeline and document scoring parameters are all set on the\n * builder before indexing.\n *\n * @constructor\n * @property {string} _ref - Internal reference to the document reference field.\n * @property {string[]} _fields - Internal reference to the document fields to index.\n * @property {object} invertedIndex - The inverted index maps terms to document fields.\n * @property {object} documentTermFrequencies - Keeps track of document term frequencies.\n * @property {object} documentLengths - Keeps track of the length of documents added to the index.\n * @property {lunr.tokenizer} tokenizer - Function for splitting strings into tokens for indexing.\n * @property {lunr.Pipeline} pipeline - The pipeline performs text processing on tokens before indexing.\n * @property {lunr.Pipeline} searchPipeline - A pipeline for processing search terms before querying the index.\n * @property {number} documentCount - Keeps track of the total number of documents indexed.\n * @property {number} _b - A parameter to control field length normalization, setting this to 0 disabled normalization, 1 fully normalizes field lengths, the default value is 0.75.\n * @property {number} _k1 - A parameter to control how quickly an increase in term frequency results in term frequency saturation, the default value is 1.2.\n * @property {number} termIndex - A counter incremented for each unique term, used to identify a terms position in the vector space.\n * @property {array} metadataWhitelist - A list of metadata keys that have been whitelisted for entry in the index.\n */\nlunr.Builder = function () {\n  this._ref = \"id\"\n  this._fields = Object.create(null)\n  this._documents = Object.create(null)\n  this.invertedIndex = Object.create(null)\n  this.fieldTermFrequencies = {}\n  this.fieldLengths = {}\n  this.tokenizer = lunr.tokenizer\n  this.pipeline = new lunr.Pipeline\n  this.searchPipeline = new lunr.Pipeline\n  this.documentCount = 0\n  this._b = 0.75\n  this._k1 = 1.2\n  this.termIndex = 0\n  this.metadataWhitelist = []\n}\n\n/**\n * Sets the document field used as the document reference. Every document must have this field.\n * The type of this field in the document should be a string, if it is not a string it will be\n * coerced into a string by calling toString.\n *\n * The default ref is 'id'.\n *\n * The ref should _not_ be changed during indexing, it should be set before any documents are\n * added to the index. Changing it during indexing can lead to inconsistent results.\n *\n * @param {string} ref - The name of the reference field in the document.\n */\nlunr.Builder.prototype.ref = function (ref) {\n  this._ref = ref\n}\n\n/**\n * A function that is used to extract a field from a document.\n *\n * Lunr expects a field to be at the top level of a document, if however the field\n * is deeply nested within a document an extractor function can be used to extract\n * the right field for indexing.\n *\n * @callback fieldExtractor\n * @param {object} doc - The document being added to the index.\n * @returns {?(string|object|object[])} obj - The object that will be indexed for this field.\n * @example <caption>Extracting a nested field</caption>\n * function (doc) { return doc.nested.field }\n */\n\n/**\n * Adds a field to the list of document fields that will be indexed. Every document being\n * indexed should have this field. Null values for this field in indexed documents will\n * not cause errors but will limit the chance of that document being retrieved by searches.\n *\n * All fields should be added before adding documents to the index. Adding fields after\n * a document has been indexed will have no effect on already indexed documents.\n *\n * Fields can be boosted at build time. This allows terms within that field to have more\n * importance when ranking search results. Use a field boost to specify that matches within\n * one field are more important than other fields.\n *\n * @param {string} fieldName - The name of a field to index in all documents.\n * @param {object} attributes - Optional attributes associated with this field.\n * @param {number} [attributes.boost=1] - Boost applied to all terms within this field.\n * @param {fieldExtractor} [attributes.extractor] - Function to extract a field from a document.\n * @throws {RangeError} fieldName cannot contain unsupported characters '/'\n */\nlunr.Builder.prototype.field = function (fieldName, attributes) {\n  if (/\\//.test(fieldName)) {\n    throw new RangeError (\"Field '\" + fieldName + \"' contains illegal character '/'\")\n  }\n\n  this._fields[fieldName] = attributes || {}\n}\n\n/**\n * A parameter to tune the amount of field length normalisation that is applied when\n * calculating relevance scores. A value of 0 will completely disable any normalisation\n * and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b\n * will be clamped to the range 0 - 1.\n *\n * @param {number} number - The value to set for this tuning parameter.\n */\nlunr.Builder.prototype.b = function (number) {\n  if (number < 0) {\n    this._b = 0\n  } else if (number > 1) {\n    this._b = 1\n  } else {\n    this._b = number\n  }\n}\n\n/**\n * A parameter that controls the speed at which a rise in term frequency results in term\n * frequency saturation. The default value is 1.2. Setting this to a higher value will give\n * slower saturation levels, a lower value will result in quicker saturation.\n *\n * @param {number} number - The value to set for this tuning parameter.\n */\nlunr.Builder.prototype.k1 = function (number) {\n  this._k1 = number\n}\n\n/**\n * Adds a document to the index.\n *\n * Before adding fields to the index the index should have been fully setup, with the document\n * ref and all fields to index already having been specified.\n *\n * The document must have a field name as specified by the ref (by default this is 'id') and\n * it should have all fields defined for indexing, though null or undefined values will not\n * cause errors.\n *\n * Entire documents can be boosted at build time. Applying a boost to a document indicates that\n * this document should rank higher in search results than other documents.\n *\n * @param {object} doc - The document to add to the index.\n * @param {object} attributes - Optional attributes associated with this document.\n * @param {number} [attributes.boost=1] - Boost applied to all terms within this document.\n */\nlunr.Builder.prototype.add = function (doc, attributes) {\n  var docRef = doc[this._ref],\n      fields = Object.keys(this._fields)\n\n  this._documents[docRef] = attributes || {}\n  this.documentCount += 1\n\n  for (var i = 0; i < fields.length; i++) {\n    var fieldName = fields[i],\n        extractor = this._fields[fieldName].extractor,\n        field = extractor ? extractor(doc) : doc[fieldName],\n        tokens = this.tokenizer(field, {\n          fields: [fieldName]\n        }),\n        terms = this.pipeline.run(tokens),\n        fieldRef = new lunr.FieldRef (docRef, fieldName),\n        fieldTerms = Object.create(null)\n\n    this.fieldTermFrequencies[fieldRef] = fieldTerms\n    this.fieldLengths[fieldRef] = 0\n\n    // store the length of this field for this document\n    this.fieldLengths[fieldRef] += terms.length\n\n    // calculate term frequencies for this field\n    for (var j = 0; j < terms.length; j++) {\n      var term = terms[j]\n\n      if (fieldTerms[term] == undefined) {\n        fieldTerms[term] = 0\n      }\n\n      fieldTerms[term] += 1\n\n      // add to inverted index\n      // create an initial posting if one doesn't exist\n      if (this.invertedIndex[term] == undefined) {\n        var posting = Object.create(null)\n        posting[\"_index\"] = this.termIndex\n        this.termIndex += 1\n\n        for (var k = 0; k < fields.length; k++) {\n          posting[fields[k]] = Object.create(null)\n        }\n\n        this.invertedIndex[term] = posting\n      }\n\n      // add an entry for this term/fieldName/docRef to the invertedIndex\n      if (this.invertedIndex[term][fieldName][docRef] == undefined) {\n        this.invertedIndex[term][fieldName][docRef] = Object.create(null)\n      }\n\n      // store all whitelisted metadata about this token in the\n      // inverted index\n      for (var l = 0; l < this.metadataWhitelist.length; l++) {\n        var metadataKey = this.metadataWhitelist[l],\n            metadata = term.metadata[metadataKey]\n\n        if (this.invertedIndex[term][fieldName][docRef][metadataKey] == undefined) {\n          this.invertedIndex[term][fieldName][docRef][metadataKey] = []\n        }\n\n        this.invertedIndex[term][fieldName][docRef][metadataKey].push(metadata)\n      }\n    }\n\n  }\n}\n\n/**\n * Calculates the average document length for this index\n *\n * @private\n */\nlunr.Builder.prototype.calculateAverageFieldLengths = function () {\n\n  var fieldRefs = Object.keys(this.fieldLengths),\n      numberOfFields = fieldRefs.length,\n      accumulator = {},\n      documentsWithField = {}\n\n  for (var i = 0; i < numberOfFields; i++) {\n    var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),\n        field = fieldRef.fieldName\n\n    documentsWithField[field] || (documentsWithField[field] = 0)\n    documentsWithField[field] += 1\n\n    accumulator[field] || (accumulator[field] = 0)\n    accumulator[field] += this.fieldLengths[fieldRef]\n  }\n\n  var fields = Object.keys(this._fields)\n\n  for (var i = 0; i < fields.length; i++) {\n    var fieldName = fields[i]\n    accumulator[fieldName] = accumulator[fieldName] / documentsWithField[fieldName]\n  }\n\n  this.averageFieldLength = accumulator\n}\n\n/**\n * Builds a vector space model of every document using lunr.Vector\n *\n * @private\n */\nlunr.Builder.prototype.createFieldVectors = function () {\n  var fieldVectors = {},\n      fieldRefs = Object.keys(this.fieldTermFrequencies),\n      fieldRefsLength = fieldRefs.length,\n      termIdfCache = Object.create(null)\n\n  for (var i = 0; i < fieldRefsLength; i++) {\n    var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),\n        fieldName = fieldRef.fieldName,\n        fieldLength = this.fieldLengths[fieldRef],\n        fieldVector = new lunr.Vector,\n        termFrequencies = this.fieldTermFrequencies[fieldRef],\n        terms = Object.keys(termFrequencies),\n        termsLength = terms.length\n\n\n    var fieldBoost = this._fields[fieldName].boost || 1,\n        docBoost = this._documents[fieldRef.docRef].boost || 1\n\n    for (var j = 0; j < termsLength; j++) {\n      var term = terms[j],\n          tf = termFrequencies[term],\n          termIndex = this.invertedIndex[term]._index,\n          idf, score, scoreWithPrecision\n\n      if (termIdfCache[term] === undefined) {\n        idf = lunr.idf(this.invertedIndex[term], this.documentCount)\n        termIdfCache[term] = idf\n      } else {\n        idf = termIdfCache[term]\n      }\n\n      score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[fieldName])) + tf)\n      score *= fieldBoost\n      score *= docBoost\n      scoreWithPrecision = Math.round(score * 1000) / 1000\n      // Converts 1.23456789 to 1.234.\n      // Reducing the precision so that the vectors take up less\n      // space when serialised. Doing it now so that they behave\n      // the same before and after serialisation. Also, this is\n      // the fastest approach to reducing a number's precision in\n      // JavaScript.\n\n      fieldVector.insert(termIndex, scoreWithPrecision)\n    }\n\n    fieldVectors[fieldRef] = fieldVector\n  }\n\n  this.fieldVectors = fieldVectors\n}\n\n/**\n * Creates a token set of all tokens in the index using lunr.TokenSet\n *\n * @private\n */\nlunr.Builder.prototype.createTokenSet = function () {\n  this.tokenSet = lunr.TokenSet.fromArray(\n    Object.keys(this.invertedIndex).sort()\n  )\n}\n\n/**\n * Builds the index, creating an instance of lunr.Index.\n *\n * This completes the indexing process and should only be called\n * once all documents have been added to the index.\n *\n * @returns {lunr.Index}\n */\nlunr.Builder.prototype.build = function () {\n  this.calculateAverageFieldLengths()\n  this.createFieldVectors()\n  this.createTokenSet()\n\n  return new lunr.Index({\n    invertedIndex: this.invertedIndex,\n    fieldVectors: this.fieldVectors,\n    tokenSet: this.tokenSet,\n    fields: Object.keys(this._fields),\n    pipeline: this.searchPipeline\n  })\n}\n\n/**\n * Applies a plugin to the index builder.\n *\n * A plugin is a function that is called with the index builder as its context.\n * Plugins can be used to customise or extend the behaviour of the index\n * in some way. A plugin is just a function, that encapsulated the custom\n * behaviour that should be applied when building the index.\n *\n * The plugin function will be called with the index builder as its argument, additional\n * arguments can also be passed when calling use. The function will be called\n * with the index builder as its context.\n *\n * @param {Function} plugin The plugin to apply.\n */\nlunr.Builder.prototype.use = function (fn) {\n  var args = Array.prototype.slice.call(arguments, 1)\n  args.unshift(this)\n  fn.apply(this, args)\n}\n/**\n * Contains and collects metadata about a matching document.\n * A single instance of lunr.MatchData is returned as part of every\n * lunr.Index~Result.\n *\n * @constructor\n * @param {string} term - The term this match data is associated with\n * @param {string} field - The field in which the term was found\n * @param {object} metadata - The metadata recorded about this term in this field\n * @property {object} metadata - A cloned collection of metadata associated with this document.\n * @see {@link lunr.Index~Result}\n */\nlunr.MatchData = function (term, field, metadata) {\n  var clonedMetadata = Object.create(null),\n      metadataKeys = Object.keys(metadata || {})\n\n  // Cloning the metadata to prevent the original\n  // being mutated during match data combination.\n  // Metadata is kept in an array within the inverted\n  // index so cloning the data can be done with\n  // Array#slice\n  for (var i = 0; i < metadataKeys.length; i++) {\n    var key = metadataKeys[i]\n    clonedMetadata[key] = metadata[key].slice()\n  }\n\n  this.metadata = Object.create(null)\n\n  if (term !== undefined) {\n    this.metadata[term] = Object.create(null)\n    this.metadata[term][field] = clonedMetadata\n  }\n}\n\n/**\n * An instance of lunr.MatchData will be created for every term that matches a\n * document. However only one instance is required in a lunr.Index~Result. This\n * method combines metadata from another instance of lunr.MatchData with this\n * objects metadata.\n *\n * @param {lunr.MatchData} otherMatchData - Another instance of match data to merge with this one.\n * @see {@link lunr.Index~Result}\n */\nlunr.MatchData.prototype.combine = function (otherMatchData) {\n  var terms = Object.keys(otherMatchData.metadata)\n\n  for (var i = 0; i < terms.length; i++) {\n    var term = terms[i],\n        fields = Object.keys(otherMatchData.metadata[term])\n\n    if (this.metadata[term] == undefined) {\n      this.metadata[term] = Object.create(null)\n    }\n\n    for (var j = 0; j < fields.length; j++) {\n      var field = fields[j],\n          keys = Object.keys(otherMatchData.metadata[term][field])\n\n      if (this.metadata[term][field] == undefined) {\n        this.metadata[term][field] = Object.create(null)\n      }\n\n      for (var k = 0; k < keys.length; k++) {\n        var key = keys[k]\n\n        if (this.metadata[term][field][key] == undefined) {\n          this.metadata[term][field][key] = otherMatchData.metadata[term][field][key]\n        } else {\n          this.metadata[term][field][key] = this.metadata[term][field][key].concat(otherMatchData.metadata[term][field][key])\n        }\n\n      }\n    }\n  }\n}\n\n/**\n * Add metadata for a term/field pair to this instance of match data.\n *\n * @param {string} term - The term this match data is associated with\n * @param {string} field - The field in which the term was found\n * @param {object} metadata - The metadata recorded about this term in this field\n */\nlunr.MatchData.prototype.add = function (term, field, metadata) {\n  if (!(term in this.metadata)) {\n    this.metadata[term] = Object.create(null)\n    this.metadata[term][field] = metadata\n    return\n  }\n\n  if (!(field in this.metadata[term])) {\n    this.metadata[term][field] = metadata\n    return\n  }\n\n  var metadataKeys = Object.keys(metadata)\n\n  for (var i = 0; i < metadataKeys.length; i++) {\n    var key = metadataKeys[i]\n\n    if (key in this.metadata[term][field]) {\n      this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key])\n    } else {\n      this.metadata[term][field][key] = metadata[key]\n    }\n  }\n}\n/**\n * A lunr.Query provides a programmatic way of defining queries to be performed\n * against a {@link lunr.Index}.\n *\n * Prefer constructing a lunr.Query using the {@link lunr.Index#query} method\n * so the query object is pre-initialized with the right index fields.\n *\n * @constructor\n * @property {lunr.Query~Clause[]} clauses - An array of query clauses.\n * @property {string[]} allFields - An array of all available fields in a lunr.Index.\n */\nlunr.Query = function (allFields) {\n  this.clauses = []\n  this.allFields = allFields\n}\n\n/**\n * Constants for indicating what kind of automatic wildcard insertion will be used when constructing a query clause.\n *\n * This allows wildcards to be added to the beginning and end of a term without having to manually do any string\n * concatenation.\n *\n * The wildcard constants can be bitwise combined to select both leading and trailing wildcards.\n *\n * @constant\n * @default\n * @property {number} wildcard.NONE - The term will have no wildcards inserted, this is the default behaviour\n * @property {number} wildcard.LEADING - Prepend the term with a wildcard, unless a leading wildcard already exists\n * @property {number} wildcard.TRAILING - Append a wildcard to the term, unless a trailing wildcard already exists\n * @see lunr.Query~Clause\n * @see lunr.Query#clause\n * @see lunr.Query#term\n * @example <caption>query term with trailing wildcard</caption>\n * query.term('foo', { wildcard: lunr.Query.wildcard.TRAILING })\n * @example <caption>query term with leading and trailing wildcard</caption>\n * query.term('foo', {\n *   wildcard: lunr.Query.wildcard.LEADING | lunr.Query.wildcard.TRAILING\n * })\n */\n\nlunr.Query.wildcard = new String (\"*\")\nlunr.Query.wildcard.NONE = 0\nlunr.Query.wildcard.LEADING = 1\nlunr.Query.wildcard.TRAILING = 2\n\n/**\n * Constants for indicating what kind of presence a term must have in matching documents.\n *\n * @constant\n * @enum {number}\n * @see lunr.Query~Clause\n * @see lunr.Query#clause\n * @see lunr.Query#term\n * @example <caption>query term with required presence</caption>\n * query.term('foo', { presence: lunr.Query.presence.REQUIRED })\n */\nlunr.Query.presence = {\n  /**\n   * Term's presence in a document is optional, this is the default value.\n   */\n  OPTIONAL: 1,\n\n  /**\n   * Term's presence in a document is required, documents that do not contain\n   * this term will not be returned.\n   */\n  REQUIRED: 2,\n\n  /**\n   * Term's presence in a document is prohibited, documents that do contain\n   * this term will not be returned.\n   */\n  PROHIBITED: 3\n}\n\n/**\n * A single clause in a {@link lunr.Query} contains a term and details on how to\n * match that term against a {@link lunr.Index}.\n *\n * @typedef {Object} lunr.Query~Clause\n * @property {string[]} fields - The fields in an index this clause should be matched against.\n * @property {number} [boost=1] - Any boost that should be applied when matching this clause.\n * @property {number} [editDistance] - Whether the term should have fuzzy matching applied, and how fuzzy the match should be.\n * @property {boolean} [usePipeline] - Whether the term should be passed through the search pipeline.\n * @property {number} [wildcard=lunr.Query.wildcard.NONE] - Whether the term should have wildcards appended or prepended.\n * @property {number} [presence=lunr.Query.presence.OPTIONAL] - The terms presence in any matching documents.\n */\n\n/**\n * Adds a {@link lunr.Query~Clause} to this query.\n *\n * Unless the clause contains the fields to be matched all fields will be matched. In addition\n * a default boost of 1 is applied to the clause.\n *\n * @param {lunr.Query~Clause} clause - The clause to add to this query.\n * @see lunr.Query~Clause\n * @returns {lunr.Query}\n */\nlunr.Query.prototype.clause = function (clause) {\n  if (!('fields' in clause)) {\n    clause.fields = this.allFields\n  }\n\n  if (!('boost' in clause)) {\n    clause.boost = 1\n  }\n\n  if (!('usePipeline' in clause)) {\n    clause.usePipeline = true\n  }\n\n  if (!('wildcard' in clause)) {\n    clause.wildcard = lunr.Query.wildcard.NONE\n  }\n\n  if ((clause.wildcard & lunr.Query.wildcard.LEADING) && (clause.term.charAt(0) != lunr.Query.wildcard)) {\n    clause.term = \"*\" + clause.term\n  }\n\n  if ((clause.wildcard & lunr.Query.wildcard.TRAILING) && (clause.term.slice(-1) != lunr.Query.wildcard)) {\n    clause.term = \"\" + clause.term + \"*\"\n  }\n\n  if (!('presence' in clause)) {\n    clause.presence = lunr.Query.presence.OPTIONAL\n  }\n\n  this.clauses.push(clause)\n\n  return this\n}\n\n/**\n * A negated query is one in which every clause has a presence of\n * prohibited. These queries require some special processing to return\n * the expected results.\n *\n * @returns boolean\n */\nlunr.Query.prototype.isNegated = function () {\n  for (var i = 0; i < this.clauses.length; i++) {\n    if (this.clauses[i].presence != lunr.Query.presence.PROHIBITED) {\n      return false\n    }\n  }\n\n  return true\n}\n\n/**\n * Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause}\n * to the list of clauses that make up this query.\n *\n * The term is used as is, i.e. no tokenization will be performed by this method. Instead conversion\n * to a token or token-like string should be done before calling this method.\n *\n * The term will be converted to a string by calling `toString`. Multiple terms can be passed as an\n * array, each term in the array will share the same options.\n *\n * @param {object|object[]} term - The term(s) to add to the query.\n * @param {object} [options] - Any additional properties to add to the query clause.\n * @returns {lunr.Query}\n * @see lunr.Query#clause\n * @see lunr.Query~Clause\n * @example <caption>adding a single term to a query</caption>\n * query.term(\"foo\")\n * @example <caption>adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard</caption>\n * query.term(\"foo\", {\n *   fields: [\"title\"],\n *   boost: 10,\n *   wildcard: lunr.Query.wildcard.TRAILING\n * })\n * @example <caption>using lunr.tokenizer to convert a string to tokens before using them as terms</caption>\n * query.term(lunr.tokenizer(\"foo bar\"))\n */\nlunr.Query.prototype.term = function (term, options) {\n  if (Array.isArray(term)) {\n    term.forEach(function (t) { this.term(t, lunr.utils.clone(options)) }, this)\n    return this\n  }\n\n  var clause = options || {}\n  clause.term = term.toString()\n\n  this.clause(clause)\n\n  return this\n}\nlunr.QueryParseError = function (message, start, end) {\n  this.name = \"QueryParseError\"\n  this.message = message\n  this.start = start\n  this.end = end\n}\n\nlunr.QueryParseError.prototype = new Error\nlunr.QueryLexer = function (str) {\n  this.lexemes = []\n  this.str = str\n  this.length = str.length\n  this.pos = 0\n  this.start = 0\n  this.escapeCharPositions = []\n}\n\nlunr.QueryLexer.prototype.run = function () {\n  var state = lunr.QueryLexer.lexText\n\n  while (state) {\n    state = state(this)\n  }\n}\n\nlunr.QueryLexer.prototype.sliceString = function () {\n  var subSlices = [],\n      sliceStart = this.start,\n      sliceEnd = this.pos\n\n  for (var i = 0; i < this.escapeCharPositions.length; i++) {\n    sliceEnd = this.escapeCharPositions[i]\n    subSlices.push(this.str.slice(sliceStart, sliceEnd))\n    sliceStart = sliceEnd + 1\n  }\n\n  subSlices.push(this.str.slice(sliceStart, this.pos))\n  this.escapeCharPositions.length = 0\n\n  return subSlices.join('')\n}\n\nlunr.QueryLexer.prototype.emit = function (type) {\n  this.lexemes.push({\n    type: type,\n    str: this.sliceString(),\n    start: this.start,\n    end: this.pos\n  })\n\n  this.start = this.pos\n}\n\nlunr.QueryLexer.prototype.escapeCharacter = function () {\n  this.escapeCharPositions.push(this.pos - 1)\n  this.pos += 1\n}\n\nlunr.QueryLexer.prototype.next = function () {\n  if (this.pos >= this.length) {\n    return lunr.QueryLexer.EOS\n  }\n\n  var char = this.str.charAt(this.pos)\n  this.pos += 1\n  return char\n}\n\nlunr.QueryLexer.prototype.width = function () {\n  return this.pos - this.start\n}\n\nlunr.QueryLexer.prototype.ignore = function () {\n  if (this.start == this.pos) {\n    this.pos += 1\n  }\n\n  this.start = this.pos\n}\n\nlunr.QueryLexer.prototype.backup = function () {\n  this.pos -= 1\n}\n\nlunr.QueryLexer.prototype.acceptDigitRun = function () {\n  var char, charCode\n\n  do {\n    char = this.next()\n    charCode = char.charCodeAt(0)\n  } while (charCode > 47 && charCode < 58)\n\n  if (char != lunr.QueryLexer.EOS) {\n    this.backup()\n  }\n}\n\nlunr.QueryLexer.prototype.more = function () {\n  return this.pos < this.length\n}\n\nlunr.QueryLexer.EOS = 'EOS'\nlunr.QueryLexer.FIELD = 'FIELD'\nlunr.QueryLexer.TERM = 'TERM'\nlunr.QueryLexer.EDIT_DISTANCE = 'EDIT_DISTANCE'\nlunr.QueryLexer.BOOST = 'BOOST'\nlunr.QueryLexer.PRESENCE = 'PRESENCE'\n\nlunr.QueryLexer.lexField = function (lexer) {\n  lexer.backup()\n  lexer.emit(lunr.QueryLexer.FIELD)\n  lexer.ignore()\n  return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexTerm = function (lexer) {\n  if (lexer.width() > 1) {\n    lexer.backup()\n    lexer.emit(lunr.QueryLexer.TERM)\n  }\n\n  lexer.ignore()\n\n  if (lexer.more()) {\n    return lunr.QueryLexer.lexText\n  }\n}\n\nlunr.QueryLexer.lexEditDistance = function (lexer) {\n  lexer.ignore()\n  lexer.acceptDigitRun()\n  lexer.emit(lunr.QueryLexer.EDIT_DISTANCE)\n  return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexBoost = function (lexer) {\n  lexer.ignore()\n  lexer.acceptDigitRun()\n  lexer.emit(lunr.QueryLexer.BOOST)\n  return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexEOS = function (lexer) {\n  if (lexer.width() > 0) {\n    lexer.emit(lunr.QueryLexer.TERM)\n  }\n}\n\n// This matches the separator used when tokenising fields\n// within a document. These should match otherwise it is\n// not possible to search for some tokens within a document.\n//\n// It is possible for the user to change the separator on the\n// tokenizer so it _might_ clash with any other of the special\n// characters already used within the search string, e.g. :.\n//\n// This means that it is possible to change the separator in\n// such a way that makes some words unsearchable using a search\n// string.\nlunr.QueryLexer.termSeparator = lunr.tokenizer.separator\n\nlunr.QueryLexer.lexText = function (lexer) {\n  while (true) {\n    var char = lexer.next()\n\n    if (char == lunr.QueryLexer.EOS) {\n      return lunr.QueryLexer.lexEOS\n    }\n\n    // Escape character is '\\'\n    if (char.charCodeAt(0) == 92) {\n      lexer.escapeCharacter()\n      continue\n    }\n\n    if (char == \":\") {\n      return lunr.QueryLexer.lexField\n    }\n\n    if (char == \"~\") {\n      lexer.backup()\n      if (lexer.width() > 0) {\n        lexer.emit(lunr.QueryLexer.TERM)\n      }\n      return lunr.QueryLexer.lexEditDistance\n    }\n\n    if (char == \"^\") {\n      lexer.backup()\n      if (lexer.width() > 0) {\n        lexer.emit(lunr.QueryLexer.TERM)\n      }\n      return lunr.QueryLexer.lexBoost\n    }\n\n    // \"+\" indicates term presence is required\n    // checking for length to ensure that only\n    // leading \"+\" are considered\n    if (char == \"+\" && lexer.width() === 1) {\n      lexer.emit(lunr.QueryLexer.PRESENCE)\n      return lunr.QueryLexer.lexText\n    }\n\n    // \"-\" indicates term presence is prohibited\n    // checking for length to ensure that only\n    // leading \"-\" are considered\n    if (char == \"-\" && lexer.width() === 1) {\n      lexer.emit(lunr.QueryLexer.PRESENCE)\n      return lunr.QueryLexer.lexText\n    }\n\n    if (char.match(lunr.QueryLexer.termSeparator)) {\n      return lunr.QueryLexer.lexTerm\n    }\n  }\n}\n\nlunr.QueryParser = function (str, query) {\n  this.lexer = new lunr.QueryLexer (str)\n  this.query = query\n  this.currentClause = {}\n  this.lexemeIdx = 0\n}\n\nlunr.QueryParser.prototype.parse = function () {\n  this.lexer.run()\n  this.lexemes = this.lexer.lexemes\n\n  var state = lunr.QueryParser.parseClause\n\n  while (state) {\n    state = state(this)\n  }\n\n  return this.query\n}\n\nlunr.QueryParser.prototype.peekLexeme = function () {\n  return this.lexemes[this.lexemeIdx]\n}\n\nlunr.QueryParser.prototype.consumeLexeme = function () {\n  var lexeme = this.peekLexeme()\n  this.lexemeIdx += 1\n  return lexeme\n}\n\nlunr.QueryParser.prototype.nextClause = function () {\n  var completedClause = this.currentClause\n  this.query.clause(completedClause)\n  this.currentClause = {}\n}\n\nlunr.QueryParser.parseClause = function (parser) {\n  var lexeme = parser.peekLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  switch (lexeme.type) {\n    case lunr.QueryLexer.PRESENCE:\n      return lunr.QueryParser.parsePresence\n    case lunr.QueryLexer.FIELD:\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.TERM:\n      return lunr.QueryParser.parseTerm\n    default:\n      var errorMessage = \"expected either a field or a term, found \" + lexeme.type\n\n      if (lexeme.str.length >= 1) {\n        errorMessage += \" with value '\" + lexeme.str + \"'\"\n      }\n\n      throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n}\n\nlunr.QueryParser.parsePresence = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  switch (lexeme.str) {\n    case \"-\":\n      parser.currentClause.presence = lunr.Query.presence.PROHIBITED\n      break\n    case \"+\":\n      parser.currentClause.presence = lunr.Query.presence.REQUIRED\n      break\n    default:\n      var errorMessage = \"unrecognised presence operator'\" + lexeme.str + \"'\"\n      throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    var errorMessage = \"expecting term or field, found nothing\"\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.FIELD:\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.TERM:\n      return lunr.QueryParser.parseTerm\n    default:\n      var errorMessage = \"expecting term or field, found '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\nlunr.QueryParser.parseField = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  if (parser.query.allFields.indexOf(lexeme.str) == -1) {\n    var possibleFields = parser.query.allFields.map(function (f) { return \"'\" + f + \"'\" }).join(', '),\n        errorMessage = \"unrecognised field '\" + lexeme.str + \"', possible fields: \" + possibleFields\n\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  parser.currentClause.fields = [lexeme.str]\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    var errorMessage = \"expecting term, found nothing\"\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.TERM:\n      return lunr.QueryParser.parseTerm\n    default:\n      var errorMessage = \"expecting term, found '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\nlunr.QueryParser.parseTerm = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  parser.currentClause.term = lexeme.str.toLowerCase()\n\n  if (lexeme.str.indexOf(\"*\") != -1) {\n    parser.currentClause.usePipeline = false\n  }\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    parser.nextClause()\n    return\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.TERM:\n      parser.nextClause()\n      return lunr.QueryParser.parseTerm\n    case lunr.QueryLexer.FIELD:\n      parser.nextClause()\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.EDIT_DISTANCE:\n      return lunr.QueryParser.parseEditDistance\n    case lunr.QueryLexer.BOOST:\n      return lunr.QueryParser.parseBoost\n    case lunr.QueryLexer.PRESENCE:\n      parser.nextClause()\n      return lunr.QueryParser.parsePresence\n    default:\n      var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\nlunr.QueryParser.parseEditDistance = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  var editDistance = parseInt(lexeme.str, 10)\n\n  if (isNaN(editDistance)) {\n    var errorMessage = \"edit distance must be numeric\"\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  parser.currentClause.editDistance = editDistance\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    parser.nextClause()\n    return\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.TERM:\n      parser.nextClause()\n      return lunr.QueryParser.parseTerm\n    case lunr.QueryLexer.FIELD:\n      parser.nextClause()\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.EDIT_DISTANCE:\n      return lunr.QueryParser.parseEditDistance\n    case lunr.QueryLexer.BOOST:\n      return lunr.QueryParser.parseBoost\n    case lunr.QueryLexer.PRESENCE:\n      parser.nextClause()\n      return lunr.QueryParser.parsePresence\n    default:\n      var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\nlunr.QueryParser.parseBoost = function (parser) {\n  var lexeme = parser.consumeLexeme()\n\n  if (lexeme == undefined) {\n    return\n  }\n\n  var boost = parseInt(lexeme.str, 10)\n\n  if (isNaN(boost)) {\n    var errorMessage = \"boost must be numeric\"\n    throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n  }\n\n  parser.currentClause.boost = boost\n\n  var nextLexeme = parser.peekLexeme()\n\n  if (nextLexeme == undefined) {\n    parser.nextClause()\n    return\n  }\n\n  switch (nextLexeme.type) {\n    case lunr.QueryLexer.TERM:\n      parser.nextClause()\n      return lunr.QueryParser.parseTerm\n    case lunr.QueryLexer.FIELD:\n      parser.nextClause()\n      return lunr.QueryParser.parseField\n    case lunr.QueryLexer.EDIT_DISTANCE:\n      return lunr.QueryParser.parseEditDistance\n    case lunr.QueryLexer.BOOST:\n      return lunr.QueryParser.parseBoost\n    case lunr.QueryLexer.PRESENCE:\n      parser.nextClause()\n      return lunr.QueryParser.parsePresence\n    default:\n      var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n      throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n  }\n}\n\n  /**\n   * export the module via AMD, CommonJS or as a browser global\n   * Export code from https://github.com/umdjs/umd/blob/master/returnExports.js\n   */\n  ;(function (root, factory) {\n    if (typeof define === 'function' && define.amd) {\n      // AMD. Register as an anonymous module.\n      define(factory)\n    } else if (typeof exports === 'object') {\n      /**\n       * Node. Does not work with strict CommonJS, but\n       * only CommonJS-like enviroments that support module.exports,\n       * like Node.\n       */\n      module.exports = factory()\n    } else {\n      // Browser globals (root is window)\n      root.lunr = factory()\n    }\n  }(this, function () {\n    /**\n     * Just return a value to define the module export.\n     * This example returns an object, but the module\n     * can return a function as the exported value.\n     */\n    return lunr\n  }))\n})();\n", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param  {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n  var str = '' + string;\n  var match = matchHtmlRegExp.exec(str);\n\n  if (!match) {\n    return str;\n  }\n\n  var escape;\n  var html = '';\n  var index = 0;\n  var lastIndex = 0;\n\n  for (index = match.index; index < str.length; index++) {\n    switch (str.charCodeAt(index)) {\n      case 34: // \"\n        escape = '&quot;';\n        break;\n      case 38: // &\n        escape = '&amp;';\n        break;\n      case 39: // '\n        escape = '&#39;';\n        break;\n      case 60: // <\n        escape = '&lt;';\n        break;\n      case 62: // >\n        escape = '&gt;';\n        break;\n      default:\n        continue;\n    }\n\n    if (lastIndex !== index) {\n      html += str.substring(lastIndex, index);\n    }\n\n    lastIndex = index + 1;\n    html += escape;\n  }\n\n  return lastIndex !== index\n    ? html + str.substring(lastIndex, index)\n    : html;\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A RTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport lunr from \"lunr\"\n\nimport \"~/polyfills\"\n\nimport { Search, SearchIndexConfig } from \"../../_\"\nimport {\n  SearchMessage,\n  SearchMessageType\n} from \"../message\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Add support for usage with `iframe-worker` polyfill\n *\n * While `importScripts` is synchronous when executed inside of a web worker,\n * it's not possible to provide a synchronous polyfilled implementation. The\n * cool thing is that awaiting a non-Promise is a noop, so extending the type\n * definition to return a `Promise` shouldn't break anything.\n *\n * @see https://bit.ly/2PjDnXi - GitHub comment\n */\ndeclare global {\n  function importScripts(...urls: string[]): Promise<void> | void\n}\n\n/* ----------------------------------------------------------------------------\n * Data\n * ------------------------------------------------------------------------- */\n\n/**\n * Search index\n */\nlet index: Search\n\n/* ----------------------------------------------------------------------------\n * Helper functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch (= import) multi-language support through `lunr-languages`\n *\n * This function automatically imports the stemmers necessary to process the\n * languages, which are defined through the search index configuration.\n *\n * If the worker runs inside of an `iframe` (when using `iframe-worker` as\n * a shim), the base URL for the stemmers to be loaded must be determined by\n * searching for the first `script` element with a `src` attribute, which will\n * contain the contents of this script.\n *\n * @param config - Search index configuration\n *\n * @returns Promise resolving with no result\n */\nasync function setupSearchLanguages(\n  config: SearchIndexConfig\n): Promise<void> {\n  let base = \"../lunr\"\n\n  /* Detect `iframe-worker` and fix base URL */\n  if (typeof parent !== \"undefined\" && \"IFrameWorker\" in parent) {\n    const worker = document.querySelector<HTMLScriptElement>(\"script[src]\")!\n    const [path] = worker.src.split(\"/worker\")\n\n    /* Prefix base with path */\n    base = base.replace(\"..\", path)\n  }\n\n  /* Add scripts for languages */\n  const scripts = []\n  for (const lang of config.lang) {\n    switch (lang) {\n\n      /* Add segmenter for Japanese */\n      case \"ja\":\n        scripts.push(`${base}/tinyseg.js`)\n        break\n\n      /* Add segmenter for Hindi and Thai */\n      case \"hi\":\n      case \"th\":\n        scripts.push(`${base}/wordcut.js`)\n        break\n    }\n\n    /* Add language support */\n    if (lang !== \"en\")\n      scripts.push(`${base}/min/lunr.${lang}.min.js`)\n  }\n\n  /* Add multi-language support */\n  if (config.lang.length > 1)\n    scripts.push(`${base}/min/lunr.multi.min.js`)\n\n  /* Load scripts synchronously */\n  if (scripts.length)\n    await importScripts(\n      `${base}/min/lunr.stemmer.support.min.js`,\n      ...scripts\n    )\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Message handler\n *\n * @param message - Source message\n *\n * @returns Target message\n */\nexport async function handler(\n  message: SearchMessage\n): Promise<SearchMessage> {\n  switch (message.type) {\n\n    /* Search setup message */\n    case SearchMessageType.SETUP:\n      await setupSearchLanguages(message.data.config)\n      index = new Search(message.data)\n      return {\n        type: SearchMessageType.READY\n      }\n\n    /* Search query message */\n    case SearchMessageType.QUERY:\n      return {\n        type: SearchMessageType.RESULT,\n        data: index ? index.search(message.data) : { items: [] }\n      }\n\n    /* All other messages */\n    default:\n      throw new TypeError(\"Invalid message type\")\n  }\n}\n\n/* ----------------------------------------------------------------------------\n * Worker\n * ------------------------------------------------------------------------- */\n\n/* @ts-expect-error - expose Lunr.js in global scope, or stemmers won't work */\nself.lunr = lunr\n\n/* Handle messages */\naddEventListener(\"message\", async ev => {\n  postMessage(await handler(ev.data))\n})\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Polyfills\n * ------------------------------------------------------------------------- */\n\n/* Polyfill `Object.entries` */\nif (!Object.entries)\n  Object.entries = function (obj: object) {\n    const data: [string, string][] = []\n    for (const key of Object.keys(obj))\n      // @ts-expect-error - ignore property access warning\n      data.push([key, obj[key]])\n\n    /* Return entries */\n    return data\n  }\n\n/* Polyfill `Object.values` */\nif (!Object.values)\n  Object.values = function (obj: object) {\n    const data: string[] = []\n    for (const key of Object.keys(obj))\n      // @ts-expect-error - ignore property access warning\n      data.push(obj[key])\n\n    /* Return values */\n    return data\n  }\n\n/* ------------------------------------------------------------------------- */\n\n/* Polyfills for `Element` */\nif (typeof Element !== \"undefined\") {\n\n  /* Polyfill `Element.scrollTo` */\n  if (!Element.prototype.scrollTo)\n    Element.prototype.scrollTo = function (\n      x?: ScrollToOptions | number, y?: number\n    ): void {\n      if (typeof x === \"object\") {\n        this.scrollLeft = x.left!\n        this.scrollTop = x.top!\n      } else {\n        this.scrollLeft = x!\n        this.scrollTop = y!\n      }\n    }\n\n  /* Polyfill `Element.replaceWith` */\n  if (!Element.prototype.replaceWith)\n    Element.prototype.replaceWith = function (\n      ...nodes: Array<string | Node>\n    ): void {\n      const parent = this.parentNode\n      if (parent) {\n        if (nodes.length === 0)\n          parent.removeChild(this)\n\n        /* Replace children and create text nodes */\n        for (let i = nodes.length - 1; i >= 0; i--) {\n          let node = nodes[i]\n          if (typeof node === \"string\")\n            node = document.createTextNode(node)\n          else if (node.parentNode)\n            node.parentNode.removeChild(node)\n\n          /* Replace child or insert before previous sibling */\n          if (!i)\n            parent.replaceChild(node, this)\n          else\n            parent.insertBefore(this.previousSibling!, node)\n        }\n      }\n    }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport escapeHTML from \"escape-html\"\n\nimport { SearchIndexDocument } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search document\n */\nexport interface SearchDocument extends SearchIndexDocument {\n  parent?: SearchIndexDocument         /* Parent article */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search document mapping\n */\nexport type SearchDocumentMap = Map<string, SearchDocument>\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create a search document mapping\n *\n * @param docs - Search index documents\n *\n * @returns Search document map\n */\nexport function setupSearchDocumentMap(\n  docs: SearchIndexDocument[]\n): SearchDocumentMap {\n  const documents = new Map<string, SearchDocument>()\n  const parents   = new Set<SearchDocument>()\n  for (const doc of docs) {\n    const [path, hash] = doc.location.split(\"#\")\n\n    /* Extract location, title and tags */\n    const location = doc.location\n    const title    = doc.title\n    const tags     = doc.tags\n\n    /* Escape and cleanup text */\n    const text = escapeHTML(doc.text)\n      .replace(/\\s+(?=[,.:;!?])/g, \"\")\n      .replace(/\\s+/g, \" \")\n\n    /* Handle section */\n    if (hash) {\n      const parent = documents.get(path)!\n\n      /* Ignore first section, override article */\n      if (!parents.has(parent)) {\n        parent.title = doc.title\n        parent.text  = text\n\n        /* Remember that we processed the article */\n        parents.add(parent)\n\n      /* Add subsequent section */\n      } else {\n        documents.set(location, {\n          location,\n          title,\n          text,\n          parent\n        })\n      }\n\n    /* Add article */\n    } else {\n      documents.set(location, {\n        location,\n        title,\n        text,\n        ...tags && { tags }\n      })\n    }\n  }\n  return documents\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport escapeHTML from \"escape-html\"\n\nimport { SearchIndexConfig } from \"../_\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search highlight function\n *\n * @param value - Value\n *\n * @returns Highlighted value\n */\nexport type SearchHighlightFn = (value: string) => string\n\n/**\n * Search highlight factory function\n *\n * @param query - Query value\n *\n * @returns Search highlight function\n */\nexport type SearchHighlightFactoryFn = (query: string) => SearchHighlightFn\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Create a search highlighter\n *\n * @param config - Search index configuration\n * @param escape - Whether to escape HTML\n *\n * @returns Search highlight factory function\n */\nexport function setupSearchHighlighter(\n  config: SearchIndexConfig, escape: boolean\n): SearchHighlightFactoryFn {\n  const separator = new RegExp(config.separator, \"img\")\n  const highlight = (_: unknown, data: string, term: string) => {\n    return `${data}<mark data-md-highlight>${term}</mark>`\n  }\n\n  /* Return factory function */\n  return (query: string) => {\n    query = query\n      .replace(/[\\s*+\\-:~^]+/g, \" \")\n      .trim()\n\n    /* Create search term match expression */\n    const match = new RegExp(`(^|${config.separator})(${\n      query\n        .replace(/[|\\\\{}()[\\]^$+*?.-]/g, \"\\\\$&\")\n        .replace(separator, \"|\")\n    })`, \"img\")\n\n    /* Highlight string value */\n    return value => (\n      escape\n        ? escapeHTML(value)\n        : value\n      )\n        .replace(match, highlight)\n        .replace(/<\\/mark>(\\s+)<mark[^>]*>/img, \"$1\")\n  }\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search query clause\n */\nexport interface SearchQueryClause {\n  presence: lunr.Query.presence        /* Clause presence */\n  term: string                         /* Clause term */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search query terms\n */\nexport type SearchQueryTerms = Record<string, boolean>\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Parse a search query for analysis\n *\n * @param value - Query value\n *\n * @returns Search query clauses\n */\nexport function parseSearchQuery(\n  value: string\n): SearchQueryClause[] {\n  const query  = new (lunr as any).Query([\"title\", \"text\"])\n  const parser = new (lunr as any).QueryParser(value, query)\n\n  /* Parse and return query clauses */\n  parser.parse()\n  return query.clauses\n}\n\n/**\n * Analyze the search query clauses in regard to the search terms found\n *\n * @param query - Search query clauses\n * @param terms - Search terms\n *\n * @returns Search query terms\n */\nexport function getSearchQueryTerms(\n  query: SearchQueryClause[], terms: string[]\n): SearchQueryTerms {\n  const clauses = new Set<SearchQueryClause>(query)\n\n  /* Match query clauses against terms */\n  const result: SearchQueryTerms = {}\n  for (let t = 0; t < terms.length; t++)\n    for (const clause of clauses)\n      if (terms[t].startsWith(clause.term)) {\n        result[clause.term] = true\n        clauses.delete(clause)\n      }\n\n  /* Annotate unmatched non-stopword query clauses */\n  for (const clause of clauses)\n    if (lunr.stopWordFilter?.(clause.term as any))\n      result[clause.term] = false\n\n  /* Return query terms */\n  return result\n}\n", "/*\n * Copyright (c) 2016-2022 Martin Donath <martin.donath@squidfunk.com>\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport {\n  SearchDocument,\n  SearchDocumentMap,\n  setupSearchDocumentMap\n} from \"../document\"\nimport {\n  SearchHighlightFactoryFn,\n  setupSearchHighlighter\n} from \"../highlighter\"\nimport { SearchOptions } from \"../options\"\nimport {\n  SearchQueryTerms,\n  getSearchQueryTerms,\n  parseSearchQuery\n} from \"../query\"\n\n/* ----------------------------------------------------------------------------\n * Types\n * ------------------------------------------------------------------------- */\n\n/**\n * Search index configuration\n */\nexport interface SearchIndexConfig {\n  lang: string[]                       /* Search languages */\n  separator: string                    /* Search separator */\n}\n\n/**\n * Search index document\n */\nexport interface SearchIndexDocument {\n  location: string                     /* Document location */\n  title: string                        /* Document title */\n  text: string                         /* Document text */\n  tags?: string[]                      /* Document tags */\n  boost?: number                       /* Document boost */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search index\n *\n * This interfaces describes the format of the `search_index.json` file which\n * is automatically built by the MkDocs search plugin.\n */\nexport interface SearchIndex {\n  config: SearchIndexConfig            /* Search index configuration */\n  docs: SearchIndexDocument[]          /* Search index documents */\n  options: SearchOptions               /* Search options */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search metadata\n */\nexport interface SearchMetadata {\n  score: number                        /* Score (relevance) */\n  terms: SearchQueryTerms              /* Search query terms */\n}\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search result document\n */\nexport type SearchResultDocument = SearchDocument & SearchMetadata\n\n/**\n * Search result item\n */\nexport type SearchResultItem = SearchResultDocument[]\n\n/* ------------------------------------------------------------------------- */\n\n/**\n * Search result\n */\nexport interface SearchResult {\n  items: SearchResultItem[]            /* Search result items */\n  suggestions?: string[]               /* Search suggestions */\n}\n\n/* ----------------------------------------------------------------------------\n * Functions\n * ------------------------------------------------------------------------- */\n\n/**\n * Compute the difference of two lists of strings\n *\n * @param a - 1st list of strings\n * @param b - 2nd list of strings\n *\n * @returns Difference\n */\nfunction difference(a: string[], b: string[]): string[] {\n  const [x, y] = [new Set(a), new Set(b)]\n  return [\n    ...new Set([...x].filter(value => !y.has(value)))\n  ]\n}\n\n/* ----------------------------------------------------------------------------\n * Class\n * ------------------------------------------------------------------------- */\n\n/**\n * Search index\n */\nexport class Search {\n\n  /**\n   * Search document mapping\n   *\n   * A mapping of URLs (including hash fragments) to the actual articles and\n   * sections of the documentation. The search document mapping must be created\n   * regardless of whether the index was prebuilt or not, as Lunr.js itself\n   * only stores the actual index.\n   */\n  protected documents: SearchDocumentMap\n\n  /**\n   * Search highlight factory function\n   */\n  protected highlight: SearchHighlightFactoryFn\n\n  /**\n   * The underlying Lunr.js search index\n   */\n  protected index: lunr.Index\n\n  /**\n   * Search options\n   */\n  protected options: SearchOptions\n\n  /**\n   * Create the search integration\n   *\n   * @param data - Search index\n   */\n  public constructor({ config, docs, options }: SearchIndex) {\n    this.options = options\n\n    /* Set up document map and highlighter factory */\n    this.documents = setupSearchDocumentMap(docs)\n    this.highlight = setupSearchHighlighter(config, false)\n\n    /* Set separator for tokenizer */\n    lunr.tokenizer.separator = new RegExp(config.separator)\n\n    /* Create search index */\n    this.index = lunr(function () {\n\n      /* Set up multi-language support */\n      if (config.lang.length === 1 && config.lang[0] !== \"en\") {\n        this.use((lunr as any)[config.lang[0]])\n      } else if (config.lang.length > 1) {\n        this.use((lunr as any).multiLanguage(...config.lang))\n      }\n\n      /* Compute functions to be removed from the pipeline */\n      const fns = difference([\n        \"trimmer\", \"stopWordFilter\", \"stemmer\"\n      ], options.pipeline)\n\n      /* Remove functions from the pipeline for registered languages */\n      for (const lang of config.lang.map(language => (\n        language === \"en\" ? lunr : (lunr as any)[language]\n      ))) {\n        for (const fn of fns) {\n          this.pipeline.remove(lang[fn])\n          this.searchPipeline.remove(lang[fn])\n        }\n      }\n\n      /* Set up reference */\n      this.ref(\"location\")\n\n      /* Set up fields */\n      this.field(\"title\", { boost: 1e3 })\n      this.field(\"text\")\n      this.field(\"tags\", { boost: 1e6, extractor: doc => {\n        const { tags = [] } = doc as SearchDocument\n        return tags.reduce((list, tag) => [\n          ...list,\n          ...lunr.tokenizer(tag)\n        ], [] as lunr.Token[])\n      } })\n\n      /* Index documents */\n      for (const doc of docs)\n        this.add(doc, { boost: doc.boost })\n    })\n  }\n\n  /**\n   * Search for matching documents\n   *\n   * The search index which MkDocs provides is divided up into articles, which\n   * contain the whole content of the individual pages, and sections, which only\n   * contain the contents of the subsections obtained by breaking the individual\n   * pages up at `h1` ... `h6`. As there may be many sections on different pages\n   * with identical titles (for example within this very project, e.g. \"Usage\"\n   * or \"Installation\"), they need to be put into the context of the containing\n   * page. For this reason, section results are grouped within their respective\n   * articles which are the top-level results that are returned.\n   *\n   * @param query - Query value\n   *\n   * @returns Search results\n   */\n  public search(query: string): SearchResult {\n    if (query) {\n      try {\n        const highlight = this.highlight(query)\n\n        /* Parse query to extract clauses for analysis */\n        const clauses = parseSearchQuery(query)\n          .filter(clause => (\n            clause.presence !== lunr.Query.presence.PROHIBITED\n          ))\n\n        /* Perform search and post-process results */\n        const groups = this.index.search(`${query}*`)\n\n          /* Apply post-query boosts based on title and search query terms */\n          .reduce<SearchResultItem>((item, { ref, score, matchData }) => {\n            const document = this.documents.get(ref)\n            if (typeof document !== \"undefined\") {\n              const { location, title, text, tags, parent } = document\n\n              /* Compute and analyze search query terms */\n              const terms = getSearchQueryTerms(\n                clauses,\n                Object.keys(matchData.metadata)\n              )\n\n              /* Highlight title and text and apply post-query boosts */\n              const boost = +!parent + +Object.values(terms).every(t => t)\n              item.push({\n                location,\n                title: highlight(title),\n                text:  highlight(text),\n                ...tags && { tags: tags.map(highlight) },\n                score: score * (1 + boost),\n                terms\n              })\n            }\n            return item\n          }, [])\n\n          /* Sort search results again after applying boosts */\n          .sort((a, b) => b.score - a.score)\n\n          /* Group search results by page */\n          .reduce((items, result) => {\n            const document = this.documents.get(result.location)\n            if (typeof document !== \"undefined\") {\n              const ref = \"parent\" in document\n                ? document.parent!.location\n                : document.location\n              items.set(ref, [...items.get(ref) || [], result])\n            }\n            return items\n          }, new Map<string, SearchResultItem>())\n\n        /* Generate search suggestions, if desired */\n        let suggestions: string[] | undefined\n        if (this.options.suggestions) {\n          const titles = this.index.query(builder => {\n            for (const clause of clauses)\n              builder.term(clause.term, {\n                fields: [\"title\"],\n                presence: lunr.Query.presence.REQUIRED,\n                wildcard: lunr.Query.wildcard.TRAILING\n              })\n          })\n\n          /* Retrieve suggestions for best match */\n          suggestions = titles.length\n            ? Object.keys(titles[0].matchData.metadata)\n            : []\n        }\n\n        /* Return items and suggestions */\n        return {\n          items: [...groups.values()],\n          ...typeof suggestions !== \"undefined\" && { suggestions }\n        }\n\n      /* Log errors to console (for now) */\n      } catch {\n        console.warn(`Invalid query: ${query} \u2013 see https://bit.ly/2s3ChXG`)\n      }\n    }\n\n    /* Return nothing in case of error or empty query */\n    return { items: [] }\n  }\n}\n"],
+  "mappings": "glCAAA,IAAAA,GAAAC,EAAA,CAAAC,GAAAC,KAAA;AAAA;AAAA;AAAA;AAAA,IAME,UAAU,CAiCZ,IAAIC,EAAO,SAAUC,EAAQ,CAC3B,IAAIC,EAAU,IAAIF,EAAK,QAEvB,OAAAE,EAAQ,SAAS,IACfF,EAAK,QACLA,EAAK,eACLA,EAAK,OACP,EAEAE,EAAQ,eAAe,IACrBF,EAAK,OACP,EAEAC,EAAO,KAAKC,EAASA,CAAO,EACrBA,EAAQ,MAAM,CACvB,EAEAF,EAAK,QAAU,QACf;AAAA;AAAA;AAAA,GASAA,EAAK,MAAQ,CAAC,EASdA,EAAK,MAAM,KAAQ,SAAUG,EAAQ,CAEnC,OAAO,SAAUC,EAAS,CACpBD,EAAO,SAAW,QAAQ,MAC5B,QAAQ,KAAKC,CAAO,CAExB,CAEF,EAAG,IAAI,EAaPJ,EAAK,MAAM,SAAW,SAAUK,EAAK,CACnC,OAAsBA,GAAQ,KACrB,GAEAA,EAAI,SAAS,CAExB,EAkBAL,EAAK,MAAM,MAAQ,SAAUK,EAAK,CAChC,GAAIA,GAAQ,KACV,OAAOA,EAMT,QAHIC,EAAQ,OAAO,OAAO,IAAI,EAC1BC,EAAO,OAAO,KAAKF,CAAG,EAEjB,EAAI,EAAG,EAAIE,EAAK,OAAQ,IAAK,CACpC,IAAIC,EAAMD,EAAK,GACXE,EAAMJ,EAAIG,GAEd,GAAI,MAAM,QAAQC,CAAG,EAAG,CACtBH,EAAME,GAAOC,EAAI,MAAM,EACvB,QACF,CAEA,GAAI,OAAOA,GAAQ,UACf,OAAOA,GAAQ,UACf,OAAOA,GAAQ,UAAW,CAC5BH,EAAME,GAAOC,EACb,QACF,CAEA,MAAM,IAAI,UAAU,uDAAuD,CAC7E,CAEA,OAAOH,CACT,EACAN,EAAK,SAAW,SAAUU,EAAQC,EAAWC,EAAa,CACxD,KAAK,OAASF,EACd,KAAK,UAAYC,EACjB,KAAK,aAAeC,CACtB,EAEAZ,EAAK,SAAS,OAAS,IAEvBA,EAAK,SAAS,WAAa,SAAUa,EAAG,CACtC,IAAIC,EAAID,EAAE,QAAQb,EAAK,SAAS,MAAM,EAEtC,GAAIc,IAAM,GACR,KAAM,6BAGR,IAAIC,EAAWF,EAAE,MAAM,EAAGC,CAAC,EACvBJ,EAASG,EAAE,MAAMC,EAAI,CAAC,EAE1B,OAAO,IAAId,EAAK,SAAUU,EAAQK,EAAUF,CAAC,CAC/C,EAEAb,EAAK,SAAS,UAAU,SAAW,UAAY,CAC7C,OAAI,KAAK,cAAgB,OACvB,KAAK,aAAe,KAAK,UAAYA,EAAK,SAAS,OAAS,KAAK,QAG5D,KAAK,YACd,EACA;AAAA;AAAA;AAAA,GAUAA,EAAK,IAAM,SAAUgB,EAAU,CAG7B,GAFA,KAAK,SAAW,OAAO,OAAO,IAAI,EAE9BA,EAAU,CACZ,KAAK,OAASA,EAAS,OAEvB,QAASC,EAAI,EAAGA,EAAI,KAAK,OAAQA,IAC/B,KAAK,SAASD,EAASC,IAAM,EAEjC,MACE,KAAK,OAAS,CAElB,EASAjB,EAAK,IAAI,SAAW,CAClB,UAAW,SAAUkB,EAAO,CAC1B,OAAOA,CACT,EAEA,MAAO,UAAY,CACjB,OAAO,IACT,EAEA,SAAU,UAAY,CACpB,MAAO,EACT,CACF,EASAlB,EAAK,IAAI,MAAQ,CACf,UAAW,UAAY,CACrB,OAAO,IACT,EAEA,MAAO,SAAUkB,EAAO,CACtB,OAAOA,CACT,EAEA,SAAU,UAAY,CACpB,MAAO,EACT,CACF,EAQAlB,EAAK,IAAI,UAAU,SAAW,SAAUmB,EAAQ,CAC9C,MAAO,CAAC,CAAC,KAAK,SAASA,EACzB,EAUAnB,EAAK,IAAI,UAAU,UAAY,SAAUkB,EAAO,CAC9C,IAAIE,EAAGC,EAAGL,EAAUM,EAAe,CAAC,EAEpC,GAAIJ,IAAUlB,EAAK,IAAI,SACrB,OAAO,KAGT,GAAIkB,IAAUlB,EAAK,IAAI,MACrB,OAAOkB,EAGL,KAAK,OAASA,EAAM,QACtBE,EAAI,KACJC,EAAIH,IAEJE,EAAIF,EACJG,EAAI,MAGNL,EAAW,OAAO,KAAKI,EAAE,QAAQ,EAEjC,QAASH,EAAI,EAAGA,EAAID,EAAS,OAAQC,IAAK,CACxC,IAAIM,EAAUP,EAASC,GACnBM,KAAWF,EAAE,UACfC,EAAa,KAAKC,CAAO,CAE7B,CAEA,OAAO,IAAIvB,EAAK,IAAKsB,CAAY,CACnC,EASAtB,EAAK,IAAI,UAAU,MAAQ,SAAUkB,EAAO,CAC1C,OAAIA,IAAUlB,EAAK,IAAI,SACdA,EAAK,IAAI,SAGdkB,IAAUlB,EAAK,IAAI,MACd,KAGF,IAAIA,EAAK,IAAI,OAAO,KAAK,KAAK,QAAQ,EAAE,OAAO,OAAO,KAAKkB,EAAM,QAAQ,CAAC,CAAC,CACpF,EASAlB,EAAK,IAAM,SAAUwB,EAASC,EAAe,CAC3C,IAAIC,EAAoB,EAExB,QAASf,KAAaa,EAChBb,GAAa,WACjBe,GAAqB,OAAO,KAAKF,EAAQb,EAAU,EAAE,QAGvD,IAAIgB,GAAKF,EAAgBC,EAAoB,KAAQA,EAAoB,IAEzE,OAAO,KAAK,IAAI,EAAI,KAAK,IAAIC,CAAC,CAAC,CACjC,EAUA3B,EAAK,MAAQ,SAAU4B,EAAKC,EAAU,CACpC,KAAK,IAAMD,GAAO,GAClB,KAAK,SAAWC,GAAY,CAAC,CAC/B,EAOA7B,EAAK,MAAM,UAAU,SAAW,UAAY,CAC1C,OAAO,KAAK,GACd,EAsBAA,EAAK,MAAM,UAAU,OAAS,SAAU8B,EAAI,CAC1C,YAAK,IAAMA,EAAG,KAAK,IAAK,KAAK,QAAQ,EAC9B,IACT,EASA9B,EAAK,MAAM,UAAU,MAAQ,SAAU8B,EAAI,CACzC,OAAAA,EAAKA,GAAM,SAAUjB,EAAG,CAAE,OAAOA,CAAE,EAC5B,IAAIb,EAAK,MAAO8B,EAAG,KAAK,IAAK,KAAK,QAAQ,EAAG,KAAK,QAAQ,CACnE,EACA;AAAA;AAAA;AAAA,GAuBA9B,EAAK,UAAY,SAAUK,EAAKwB,EAAU,CACxC,GAAIxB,GAAO,MAAQA,GAAO,KACxB,MAAO,CAAC,EAGV,GAAI,MAAM,QAAQA,CAAG,EACnB,OAAOA,EAAI,IAAI,SAAU0B,EAAG,CAC1B,OAAO,IAAI/B,EAAK,MACdA,EAAK,MAAM,SAAS+B,CAAC,EAAE,YAAY,EACnC/B,EAAK,MAAM,MAAM6B,CAAQ,CAC3B,CACF,CAAC,EAOH,QAJID,EAAMvB,EAAI,SAAS,EAAE,YAAY,EACjC2B,EAAMJ,EAAI,OACVK,EAAS,CAAC,EAELC,EAAW,EAAGC,EAAa,EAAGD,GAAYF,EAAKE,IAAY,CAClE,IAAIE,EAAOR,EAAI,OAAOM,CAAQ,EAC1BG,EAAcH,EAAWC,EAE7B,GAAKC,EAAK,MAAMpC,EAAK,UAAU,SAAS,GAAKkC,GAAYF,EAAM,CAE7D,GAAIK,EAAc,EAAG,CACnB,IAAIC,EAAgBtC,EAAK,MAAM,MAAM6B,CAAQ,GAAK,CAAC,EACnDS,EAAc,SAAc,CAACH,EAAYE,CAAW,EACpDC,EAAc,MAAWL,EAAO,OAEhCA,EAAO,KACL,IAAIjC,EAAK,MACP4B,EAAI,MAAMO,EAAYD,CAAQ,EAC9BI,CACF,CACF,CACF,CAEAH,EAAaD,EAAW,CAC1B,CAEF,CAEA,OAAOD,CACT,EASAjC,EAAK,UAAU,UAAY,UAC3B;AAAA;AAAA;AAAA,GAkCAA,EAAK,SAAW,UAAY,CAC1B,KAAK,OAAS,CAAC,CACjB,EAEAA,EAAK,SAAS,oBAAsB,OAAO,OAAO,IAAI,EAmCtDA,EAAK,SAAS,iBAAmB,SAAU8B,EAAIS,EAAO,CAChDA,KAAS,KAAK,qBAChBvC,EAAK,MAAM,KAAK,6CAA+CuC,CAAK,EAGtET,EAAG,MAAQS,EACXvC,EAAK,SAAS,oBAAoB8B,EAAG,OAASA,CAChD,EAQA9B,EAAK,SAAS,4BAA8B,SAAU8B,EAAI,CACxD,IAAIU,EAAeV,EAAG,OAAUA,EAAG,SAAS,KAAK,oBAE5CU,GACHxC,EAAK,MAAM,KAAK;AAAA,EAAmG8B,CAAE,CAEzH,EAYA9B,EAAK,SAAS,KAAO,SAAUyC,EAAY,CACzC,IAAIC,EAAW,IAAI1C,EAAK,SAExB,OAAAyC,EAAW,QAAQ,SAAUE,EAAQ,CACnC,IAAIb,EAAK9B,EAAK,SAAS,oBAAoB2C,GAE3C,GAAIb,EACFY,EAAS,IAAIZ,CAAE,MAEf,OAAM,IAAI,MAAM,sCAAwCa,CAAM,CAElE,CAAC,EAEMD,CACT,EASA1C,EAAK,SAAS,UAAU,IAAM,UAAY,CACxC,IAAI4C,EAAM,MAAM,UAAU,MAAM,KAAK,SAAS,EAE9CA,EAAI,QAAQ,SAAUd,EAAI,CACxB9B,EAAK,SAAS,4BAA4B8B,CAAE,EAC5C,KAAK,OAAO,KAAKA,CAAE,CACrB,EAAG,IAAI,CACT,EAWA9B,EAAK,SAAS,UAAU,MAAQ,SAAU6C,EAAYC,EAAO,CAC3D9C,EAAK,SAAS,4BAA4B8C,CAAK,EAE/C,IAAIC,EAAM,KAAK,OAAO,QAAQF,CAAU,EACxC,GAAIE,GAAO,GACT,MAAM,IAAI,MAAM,wBAAwB,EAG1CA,EAAMA,EAAM,EACZ,KAAK,OAAO,OAAOA,EAAK,EAAGD,CAAK,CAClC,EAWA9C,EAAK,SAAS,UAAU,OAAS,SAAU6C,EAAYC,EAAO,CAC5D9C,EAAK,SAAS,4BAA4B8C,CAAK,EAE/C,IAAIC,EAAM,KAAK,OAAO,QAAQF,CAAU,EACxC,GAAIE,GAAO,GACT,MAAM,IAAI,MAAM,wBAAwB,EAG1C,KAAK,OAAO,OAAOA,EAAK,EAAGD,CAAK,CAClC,EAOA9C,EAAK,SAAS,UAAU,OAAS,SAAU8B,EAAI,CAC7C,IAAIiB,EAAM,KAAK,OAAO,QAAQjB,CAAE,EAC5BiB,GAAO,IAIX,KAAK,OAAO,OAAOA,EAAK,CAAC,CAC3B,EASA/C,EAAK,SAAS,UAAU,IAAM,SAAUiC,EAAQ,CAG9C,QAFIe,EAAc,KAAK,OAAO,OAErB/B,EAAI,EAAGA,EAAI+B,EAAa/B,IAAK,CAIpC,QAHIa,EAAK,KAAK,OAAOb,GACjBgC,EAAO,CAAC,EAEHC,EAAI,EAAGA,EAAIjB,EAAO,OAAQiB,IAAK,CACtC,IAAIC,EAASrB,EAAGG,EAAOiB,GAAIA,EAAGjB,CAAM,EAEpC,GAAI,EAAAkB,GAAW,MAA6BA,IAAW,IAEvD,GAAI,MAAM,QAAQA,CAAM,EACtB,QAASC,EAAI,EAAGA,EAAID,EAAO,OAAQC,IACjCH,EAAK,KAAKE,EAAOC,EAAE,OAGrBH,EAAK,KAAKE,CAAM,CAEpB,CAEAlB,EAASgB,CACX,CAEA,OAAOhB,CACT,EAYAjC,EAAK,SAAS,UAAU,UAAY,SAAU4B,EAAKC,EAAU,CAC3D,IAAIwB,EAAQ,IAAIrD,EAAK,MAAO4B,EAAKC,CAAQ,EAEzC,OAAO,KAAK,IAAI,CAACwB,CAAK,CAAC,EAAE,IAAI,SAAUtB,EAAG,CACxC,OAAOA,EAAE,SAAS,CACpB,CAAC,CACH,EAMA/B,EAAK,SAAS,UAAU,MAAQ,UAAY,CAC1C,KAAK,OAAS,CAAC,CACjB,EASAA,EAAK,SAAS,UAAU,OAAS,UAAY,CAC3C,OAAO,KAAK,OAAO,IAAI,SAAU8B,EAAI,CACnC,OAAA9B,EAAK,SAAS,4BAA4B8B,CAAE,EAErCA,EAAG,KACZ,CAAC,CACH,EACA;AAAA;AAAA;AAAA,GAqBA9B,EAAK,OAAS,SAAUgB,EAAU,CAChC,KAAK,WAAa,EAClB,KAAK,SAAWA,GAAY,CAAC,CAC/B,EAaAhB,EAAK,OAAO,UAAU,iBAAmB,SAAUsD,EAAO,CAExD,GAAI,KAAK,SAAS,QAAU,EAC1B,MAAO,GAST,QANIC,EAAQ,EACRC,EAAM,KAAK,SAAS,OAAS,EAC7BnB,EAAcmB,EAAMD,EACpBE,EAAa,KAAK,MAAMpB,EAAc,CAAC,EACvCqB,EAAa,KAAK,SAASD,EAAa,GAErCpB,EAAc,IACfqB,EAAaJ,IACfC,EAAQE,GAGNC,EAAaJ,IACfE,EAAMC,GAGJC,GAAcJ,IAIlBjB,EAAcmB,EAAMD,EACpBE,EAAaF,EAAQ,KAAK,MAAMlB,EAAc,CAAC,EAC/CqB,EAAa,KAAK,SAASD,EAAa,GAO1C,GAJIC,GAAcJ,GAIdI,EAAaJ,EACf,OAAOG,EAAa,EAGtB,GAAIC,EAAaJ,EACf,OAAQG,EAAa,GAAK,CAE9B,EAWAzD,EAAK,OAAO,UAAU,OAAS,SAAU2D,EAAWlD,EAAK,CACvD,KAAK,OAAOkD,EAAWlD,EAAK,UAAY,CACtC,KAAM,iBACR,CAAC,CACH,EAUAT,EAAK,OAAO,UAAU,OAAS,SAAU2D,EAAWlD,EAAKqB,EAAI,CAC3D,KAAK,WAAa,EAClB,IAAI8B,EAAW,KAAK,iBAAiBD,CAAS,EAE1C,KAAK,SAASC,IAAaD,EAC7B,KAAK,SAASC,EAAW,GAAK9B,EAAG,KAAK,SAAS8B,EAAW,GAAInD,CAAG,EAEjE,KAAK,SAAS,OAAOmD,EAAU,EAAGD,EAAWlD,CAAG,CAEpD,EAOAT,EAAK,OAAO,UAAU,UAAY,UAAY,CAC5C,GAAI,KAAK,WAAY,OAAO,KAAK,WAKjC,QAHI6D,EAAe,EACfC,EAAiB,KAAK,SAAS,OAE1B7C,EAAI,EAAGA,EAAI6C,EAAgB7C,GAAK,EAAG,CAC1C,IAAIR,EAAM,KAAK,SAASQ,GACxB4C,GAAgBpD,EAAMA,CACxB,CAEA,OAAO,KAAK,WAAa,KAAK,KAAKoD,CAAY,CACjD,EAQA7D,EAAK,OAAO,UAAU,IAAM,SAAU+D,EAAa,CAOjD,QANIC,EAAa,EACb5C,EAAI,KAAK,SAAUC,EAAI0C,EAAY,SACnCE,EAAO7C,EAAE,OAAQ8C,EAAO7C,EAAE,OAC1B8C,EAAO,EAAGC,EAAO,EACjBnD,EAAI,EAAGiC,EAAI,EAERjC,EAAIgD,GAAQf,EAAIgB,GACrBC,EAAO/C,EAAEH,GAAImD,EAAO/C,EAAE6B,GAClBiB,EAAOC,EACTnD,GAAK,EACIkD,EAAOC,EAChBlB,GAAK,EACIiB,GAAQC,IACjBJ,GAAc5C,EAAEH,EAAI,GAAKI,EAAE6B,EAAI,GAC/BjC,GAAK,EACLiC,GAAK,GAIT,OAAOc,CACT,EASAhE,EAAK,OAAO,UAAU,WAAa,SAAU+D,EAAa,CACxD,OAAO,KAAK,IAAIA,CAAW,EAAI,KAAK,UAAU,GAAK,CACrD,EAOA/D,EAAK,OAAO,UAAU,QAAU,UAAY,CAG1C,QAFIqE,EAAS,IAAI,MAAO,KAAK,SAAS,OAAS,CAAC,EAEvCpD,EAAI,EAAGiC,EAAI,EAAGjC,EAAI,KAAK,SAAS,OAAQA,GAAK,EAAGiC,IACvDmB,EAAOnB,GAAK,KAAK,SAASjC,GAG5B,OAAOoD,CACT,EAOArE,EAAK,OAAO,UAAU,OAAS,UAAY,CACzC,OAAO,KAAK,QACd,EAEA;AAAA;AAAA;AAAA;AAAA,GAiBAA,EAAK,QAAW,UAAU,CACxB,IAAIsE,EAAY,CACZ,QAAY,MACZ,OAAW,OACX,KAAS,OACT,KAAS,OACT,KAAS,MACT,IAAQ,MACR,KAAS,KACT,MAAU,MACV,IAAQ,IACR,MAAU,MACV,QAAY,MACZ,MAAU,MACV,KAAS,MACT,MAAU,KACV,QAAY,MACZ,QAAY,MACZ,QAAY,MACZ,MAAU,KACV,MAAU,MACV,OAAW,MACX,KAAS,KACX,EAEAC,EAAY,CACV,MAAU,KACV,MAAU,GACV,MAAU,KACV,MAAU,KACV,KAAS,KACT,IAAQ,GACR,KAAS,EACX,EAEAC,EAAI,WACJC,EAAI,WACJC,EAAIF,EAAI,aACRG,EAAIF,EAAI,WAERG,EAAO,KAAOF,EAAI,KAAOC,EAAID,EAC7BG,EAAO,KAAOH,EAAI,KAAOC,EAAID,EAAI,IAAMC,EAAI,MAC3CG,EAAO,KAAOJ,EAAI,KAAOC,EAAID,EAAIC,EAAID,EACrCK,EAAM,KAAOL,EAAI,KAAOD,EAEtBO,EAAU,IAAI,OAAOJ,CAAI,EACzBK,EAAU,IAAI,OAAOH,CAAI,EACzBI,EAAU,IAAI,OAAOL,CAAI,EACzBM,EAAS,IAAI,OAAOJ,CAAG,EAEvBK,EAAQ,kBACRC,EAAS,iBACTC,EAAQ,aACRC,EAAS,kBACTC,EAAU,KACVC,EAAW,cACXC,EAAW,IAAI,OAAO,oBAAoB,EAC1CC,EAAW,IAAI,OAAO,IAAMjB,EAAID,EAAI,cAAc,EAElDmB,EAAQ,mBACRC,EAAO,2IAEPC,EAAO,iDAEPC,EAAO,sFACPC,EAAQ,oBAERC,EAAO,WACPC,EAAS,MACTC,EAAQ,IAAI,OAAO,IAAMzB,EAAID,EAAI,cAAc,EAE/C2B,EAAgB,SAAuBC,EAAG,CAC5C,IAAIC,EACFC,EACAC,EACAC,EACAC,EACAC,EACAC,EAEF,GAAIP,EAAE,OAAS,EAAK,OAAOA,EAiB3B,GAfAG,EAAUH,EAAE,OAAO,EAAE,CAAC,EAClBG,GAAW,MACbH,EAAIG,EAAQ,YAAY,EAAIH,EAAE,OAAO,CAAC,GAIxCI,EAAKrB,EACLsB,EAAMrB,EAEFoB,EAAG,KAAKJ,CAAC,EAAKA,EAAIA,EAAE,QAAQI,EAAG,MAAM,EAChCC,EAAI,KAAKL,CAAC,IAAKA,EAAIA,EAAE,QAAQK,EAAI,MAAM,GAGhDD,EAAKnB,EACLoB,EAAMnB,EACFkB,EAAG,KAAKJ,CAAC,EAAG,CACd,IAAIQ,EAAKJ,EAAG,KAAKJ,CAAC,EAClBI,EAAKzB,EACDyB,EAAG,KAAKI,EAAG,EAAE,IACfJ,EAAKjB,EACLa,EAAIA,EAAE,QAAQI,EAAG,EAAE,EAEvB,SAAWC,EAAI,KAAKL,CAAC,EAAG,CACtB,IAAIQ,EAAKH,EAAI,KAAKL,CAAC,EACnBC,EAAOO,EAAG,GACVH,EAAMvB,EACFuB,EAAI,KAAKJ,CAAI,IACfD,EAAIC,EACJI,EAAMjB,EACNkB,EAAMjB,EACNkB,EAAMjB,EACFe,EAAI,KAAKL,CAAC,EAAKA,EAAIA,EAAI,IAClBM,EAAI,KAAKN,CAAC,GAAKI,EAAKjB,EAASa,EAAIA,EAAE,QAAQI,EAAG,EAAE,GAChDG,EAAI,KAAKP,CAAC,IAAKA,EAAIA,EAAI,KAEpC,CAIA,GADAI,EAAKb,EACDa,EAAG,KAAKJ,CAAC,EAAG,CACd,IAAIQ,EAAKJ,EAAG,KAAKJ,CAAC,EAClBC,EAAOO,EAAG,GACVR,EAAIC,EAAO,GACb,CAIA,GADAG,EAAKZ,EACDY,EAAG,KAAKJ,CAAC,EAAG,CACd,IAAIQ,EAAKJ,EAAG,KAAKJ,CAAC,EAClBC,EAAOO,EAAG,GACVN,EAASM,EAAG,GACZJ,EAAKzB,EACDyB,EAAG,KAAKH,CAAI,IACdD,EAAIC,EAAOhC,EAAUiC,GAEzB,CAIA,GADAE,EAAKX,EACDW,EAAG,KAAKJ,CAAC,EAAG,CACd,IAAIQ,EAAKJ,EAAG,KAAKJ,CAAC,EAClBC,EAAOO,EAAG,GACVN,EAASM,EAAG,GACZJ,EAAKzB,EACDyB,EAAG,KAAKH,CAAI,IACdD,EAAIC,EAAO/B,EAAUgC,GAEzB,CAKA,GAFAE,EAAKV,EACLW,EAAMV,EACFS,EAAG,KAAKJ,CAAC,EAAG,CACd,IAAIQ,EAAKJ,EAAG,KAAKJ,CAAC,EAClBC,EAAOO,EAAG,GACVJ,EAAKxB,EACDwB,EAAG,KAAKH,CAAI,IACdD,EAAIC,EAER,SAAWI,EAAI,KAAKL,CAAC,EAAG,CACtB,IAAIQ,EAAKH,EAAI,KAAKL,CAAC,EACnBC,EAAOO,EAAG,GAAKA,EAAG,GAClBH,EAAMzB,EACFyB,EAAI,KAAKJ,CAAI,IACfD,EAAIC,EAER,CAIA,GADAG,EAAKR,EACDQ,EAAG,KAAKJ,CAAC,EAAG,CACd,IAAIQ,EAAKJ,EAAG,KAAKJ,CAAC,EAClBC,EAAOO,EAAG,GACVJ,EAAKxB,EACLyB,EAAMxB,EACNyB,EAAMR,GACFM,EAAG,KAAKH,CAAI,GAAMI,EAAI,KAAKJ,CAAI,GAAK,CAAEK,EAAI,KAAKL,CAAI,KACrDD,EAAIC,EAER,CAEA,OAAAG,EAAKP,EACLQ,EAAMzB,EACFwB,EAAG,KAAKJ,CAAC,GAAKK,EAAI,KAAKL,CAAC,IAC1BI,EAAKjB,EACLa,EAAIA,EAAE,QAAQI,EAAG,EAAE,GAKjBD,GAAW,MACbH,EAAIG,EAAQ,YAAY,EAAIH,EAAE,OAAO,CAAC,GAGjCA,CACT,EAEA,OAAO,SAAUhD,EAAO,CACtB,OAAOA,EAAM,OAAO+C,CAAa,CACnC,CACF,EAAG,EAEHpG,EAAK,SAAS,iBAAiBA,EAAK,QAAS,SAAS,EACtD;AAAA;AAAA;AAAA,GAkBAA,EAAK,uBAAyB,SAAU8G,EAAW,CACjD,IAAIC,EAAQD,EAAU,OAAO,SAAU7D,EAAM+D,EAAU,CACrD,OAAA/D,EAAK+D,GAAYA,EACV/D,CACT,EAAG,CAAC,CAAC,EAEL,OAAO,SAAUI,EAAO,CACtB,GAAIA,GAAS0D,EAAM1D,EAAM,SAAS,KAAOA,EAAM,SAAS,EAAG,OAAOA,CACpE,CACF,EAeArD,EAAK,eAAiBA,EAAK,uBAAuB,CAChD,IACA,OACA,QACA,SACA,QACA,MACA,SACA,OACA,KACA,QACA,KACA,MACA,MACA,MACA,KACA,KACA,KACA,UACA,OACA,MACA,KACA,MACA,SACA,QACA,OACA,MACA,KACA,OACA,SACA,OACA,OACA,QACA,MACA,OACA,MACA,MACA,MACA,MACA,OACA,KACA,MACA,OACA,MACA,MACA,MACA,UACA,IACA,KACA,KACA,OACA,KACA,KACA,MACA,OACA,QACA,MACA,OACA,SACA,MACA,KACA,QACA,OACA,OACA,KACA,UACA,KACA,MACA,MACA,KACA,MACA,QACA,KACA,OACA,KACA,QACA,MACA,MACA,SACA,OACA,MACA,OACA,MACA,SACA,QACA,KACA,OACA,OACA,OACA,MACA,QACA,OACA,OACA,QACA,QACA,OACA,OACA,MACA,KACA,MACA,OACA,KACA,QACA,MACA,KACA,OACA,OACA,OACA,QACA,QACA,QACA,MACA,OACA,MACA,OACA,OACA,QACA,MACA,MACA,MACF,CAAC,EAEDA,EAAK,SAAS,iBAAiBA,EAAK,eAAgB,gBAAgB,EACpE;AAAA;AAAA;AAAA,GAoBAA,EAAK,QAAU,SAAUqD,EAAO,CAC9B,OAAOA,EAAM,OAAO,SAAUxC,EAAG,CAC/B,OAAOA,EAAE,QAAQ,OAAQ,EAAE,EAAE,QAAQ,OAAQ,EAAE,CACjD,CAAC,CACH,EAEAb,EAAK,SAAS,iBAAiBA,EAAK,QAAS,SAAS,EACtD;AAAA;AAAA;AAAA,GA0BAA,EAAK,SAAW,UAAY,CAC1B,KAAK,MAAQ,GACb,KAAK,MAAQ,CAAC,EACd,KAAK,GAAKA,EAAK,SAAS,QACxBA,EAAK,SAAS,SAAW,CAC3B,EAUAA,EAAK,SAAS,QAAU,EASxBA,EAAK,SAAS,UAAY,SAAUiH,EAAK,CAGvC,QAFI/G,EAAU,IAAIF,EAAK,SAAS,QAEvBiB,EAAI,EAAGe,EAAMiF,EAAI,OAAQhG,EAAIe,EAAKf,IACzCf,EAAQ,OAAO+G,EAAIhG,EAAE,EAGvB,OAAAf,EAAQ,OAAO,EACRA,EAAQ,IACjB,EAWAF,EAAK,SAAS,WAAa,SAAUkH,EAAQ,CAC3C,MAAI,iBAAkBA,EACblH,EAAK,SAAS,gBAAgBkH,EAAO,KAAMA,EAAO,YAAY,EAE9DlH,EAAK,SAAS,WAAWkH,EAAO,IAAI,CAE/C,EAiBAlH,EAAK,SAAS,gBAAkB,SAAU4B,EAAKuF,EAAc,CAS3D,QARIC,EAAO,IAAIpH,EAAK,SAEhBqH,EAAQ,CAAC,CACX,KAAMD,EACN,eAAgBD,EAChB,IAAKvF,CACP,CAAC,EAEMyF,EAAM,QAAQ,CACnB,IAAIC,EAAQD,EAAM,IAAI,EAGtB,GAAIC,EAAM,IAAI,OAAS,EAAG,CACxB,IAAIlF,EAAOkF,EAAM,IAAI,OAAO,CAAC,EACzBC,EAEAnF,KAAQkF,EAAM,KAAK,MACrBC,EAAaD,EAAM,KAAK,MAAMlF,IAE9BmF,EAAa,IAAIvH,EAAK,SACtBsH,EAAM,KAAK,MAAMlF,GAAQmF,GAGvBD,EAAM,IAAI,QAAU,IACtBC,EAAW,MAAQ,IAGrBF,EAAM,KAAK,CACT,KAAME,EACN,eAAgBD,EAAM,eACtB,IAAKA,EAAM,IAAI,MAAM,CAAC,CACxB,CAAC,CACH,CAEA,GAAIA,EAAM,gBAAkB,EAK5B,IAAI,MAAOA,EAAM,KAAK,MACpB,IAAIE,EAAgBF,EAAM,KAAK,MAAM,SAChC,CACL,IAAIE,EAAgB,IAAIxH,EAAK,SAC7BsH,EAAM,KAAK,MAAM,KAAOE,CAC1B,CAgCA,GA9BIF,EAAM,IAAI,QAAU,IACtBE,EAAc,MAAQ,IAGxBH,EAAM,KAAK,CACT,KAAMG,EACN,eAAgBF,EAAM,eAAiB,EACvC,IAAKA,EAAM,GACb,CAAC,EAKGA,EAAM,IAAI,OAAS,GACrBD,EAAM,KAAK,CACT,KAAMC,EAAM,KACZ,eAAgBA,EAAM,eAAiB,EACvC,IAAKA,EAAM,IAAI,MAAM,CAAC,CACxB,CAAC,EAKCA,EAAM,IAAI,QAAU,IACtBA,EAAM,KAAK,MAAQ,IAMjBA,EAAM,IAAI,QAAU,EAAG,CACzB,GAAI,MAAOA,EAAM,KAAK,MACpB,IAAIG,EAAmBH,EAAM,KAAK,MAAM,SACnC,CACL,IAAIG,EAAmB,IAAIzH,EAAK,SAChCsH,EAAM,KAAK,MAAM,KAAOG,CAC1B,CAEIH,EAAM,IAAI,QAAU,IACtBG,EAAiB,MAAQ,IAG3BJ,EAAM,KAAK,CACT,KAAMI,EACN,eAAgBH,EAAM,eAAiB,EACvC,IAAKA,EAAM,IAAI,MAAM,CAAC,CACxB,CAAC,CACH,CAKA,GAAIA,EAAM,IAAI,OAAS,EAAG,CACxB,IAAII,EAAQJ,EAAM,IAAI,OAAO,CAAC,EAC1BK,EAAQL,EAAM,IAAI,OAAO,CAAC,EAC1BM,EAEAD,KAASL,EAAM,KAAK,MACtBM,EAAgBN,EAAM,KAAK,MAAMK,IAEjCC,EAAgB,IAAI5H,EAAK,SACzBsH,EAAM,KAAK,MAAMK,GAASC,GAGxBN,EAAM,IAAI,QAAU,IACtBM,EAAc,MAAQ,IAGxBP,EAAM,KAAK,CACT,KAAMO,EACN,eAAgBN,EAAM,eAAiB,EACvC,IAAKI,EAAQJ,EAAM,IAAI,MAAM,CAAC,CAChC,CAAC,CACH,EACF,CAEA,OAAOF,CACT,EAYApH,EAAK,SAAS,WAAa,SAAU4B,EAAK,CAYxC,QAXIiG,EAAO,IAAI7H,EAAK,SAChBoH,EAAOS,EAUF,EAAI,EAAG7F,EAAMJ,EAAI,OAAQ,EAAII,EAAK,IAAK,CAC9C,IAAII,EAAOR,EAAI,GACXkG,EAAS,GAAK9F,EAAM,EAExB,GAAII,GAAQ,IACVyF,EAAK,MAAMzF,GAAQyF,EACnBA,EAAK,MAAQC,MAER,CACL,IAAIC,EAAO,IAAI/H,EAAK,SACpB+H,EAAK,MAAQD,EAEbD,EAAK,MAAMzF,GAAQ2F,EACnBF,EAAOE,CACT,CACF,CAEA,OAAOX,CACT,EAYApH,EAAK,SAAS,UAAU,QAAU,UAAY,CAQ5C,QAPI+G,EAAQ,CAAC,EAETM,EAAQ,CAAC,CACX,OAAQ,GACR,KAAM,IACR,CAAC,EAEMA,EAAM,QAAQ,CACnB,IAAIC,EAAQD,EAAM,IAAI,EAClBW,EAAQ,OAAO,KAAKV,EAAM,KAAK,KAAK,EACpCtF,EAAMgG,EAAM,OAEZV,EAAM,KAAK,QAKbA,EAAM,OAAO,OAAO,CAAC,EACrBP,EAAM,KAAKO,EAAM,MAAM,GAGzB,QAASrG,EAAI,EAAGA,EAAIe,EAAKf,IAAK,CAC5B,IAAIgH,EAAOD,EAAM/G,GAEjBoG,EAAM,KAAK,CACT,OAAQC,EAAM,OAAO,OAAOW,CAAI,EAChC,KAAMX,EAAM,KAAK,MAAMW,EACzB,CAAC,CACH,CACF,CAEA,OAAOlB,CACT,EAYA/G,EAAK,SAAS,UAAU,SAAW,UAAY,CAS7C,GAAI,KAAK,KACP,OAAO,KAAK,KAOd,QAJI4B,EAAM,KAAK,MAAQ,IAAM,IACzBsG,EAAS,OAAO,KAAK,KAAK,KAAK,EAAE,KAAK,EACtClG,EAAMkG,EAAO,OAER,EAAI,EAAG,EAAIlG,EAAK,IAAK,CAC5B,IAAIO,EAAQ2F,EAAO,GACfL,EAAO,KAAK,MAAMtF,GAEtBX,EAAMA,EAAMW,EAAQsF,EAAK,EAC3B,CAEA,OAAOjG,CACT,EAYA5B,EAAK,SAAS,UAAU,UAAY,SAAUqB,EAAG,CAU/C,QATIgD,EAAS,IAAIrE,EAAK,SAClBsH,EAAQ,OAERD,EAAQ,CAAC,CACX,MAAOhG,EACP,OAAQgD,EACR,KAAM,IACR,CAAC,EAEMgD,EAAM,QAAQ,CACnBC,EAAQD,EAAM,IAAI,EAWlB,QALIc,EAAS,OAAO,KAAKb,EAAM,MAAM,KAAK,EACtCc,EAAOD,EAAO,OACdE,EAAS,OAAO,KAAKf,EAAM,KAAK,KAAK,EACrCgB,EAAOD,EAAO,OAETE,EAAI,EAAGA,EAAIH,EAAMG,IAGxB,QAFIC,EAAQL,EAAOI,GAEVzH,EAAI,EAAGA,EAAIwH,EAAMxH,IAAK,CAC7B,IAAI2H,EAAQJ,EAAOvH,GAEnB,GAAI2H,GAASD,GAASA,GAAS,IAAK,CAClC,IAAIX,EAAOP,EAAM,KAAK,MAAMmB,GACxBC,EAAQpB,EAAM,MAAM,MAAMkB,GAC1BV,EAAQD,EAAK,OAASa,EAAM,MAC5BX,EAAO,OAEPU,KAASnB,EAAM,OAAO,OAIxBS,EAAOT,EAAM,OAAO,MAAMmB,GAC1BV,EAAK,MAAQA,EAAK,OAASD,IAM3BC,EAAO,IAAI/H,EAAK,SAChB+H,EAAK,MAAQD,EACbR,EAAM,OAAO,MAAMmB,GAASV,GAG9BV,EAAM,KAAK,CACT,MAAOqB,EACP,OAAQX,EACR,KAAMF,CACR,CAAC,CACH,CACF,CAEJ,CAEA,OAAOxD,CACT,EACArE,EAAK,SAAS,QAAU,UAAY,CAClC,KAAK,aAAe,GACpB,KAAK,KAAO,IAAIA,EAAK,SACrB,KAAK,eAAiB,CAAC,EACvB,KAAK,eAAiB,CAAC,CACzB,EAEAA,EAAK,SAAS,QAAQ,UAAU,OAAS,SAAU2I,EAAM,CACvD,IAAId,EACAe,EAAe,EAEnB,GAAID,EAAO,KAAK,aACd,MAAM,IAAI,MAAO,6BAA6B,EAGhD,QAAS,EAAI,EAAG,EAAIA,EAAK,QAAU,EAAI,KAAK,aAAa,QACnDA,EAAK,IAAM,KAAK,aAAa,GAD8B,IAE/DC,IAGF,KAAK,SAASA,CAAY,EAEtB,KAAK,eAAe,QAAU,EAChCf,EAAO,KAAK,KAEZA,EAAO,KAAK,eAAe,KAAK,eAAe,OAAS,GAAG,MAG7D,QAAS,EAAIe,EAAc,EAAID,EAAK,OAAQ,IAAK,CAC/C,IAAIE,EAAW,IAAI7I,EAAK,SACpBoC,EAAOuG,EAAK,GAEhBd,EAAK,MAAMzF,GAAQyG,EAEnB,KAAK,eAAe,KAAK,CACvB,OAAQhB,EACR,KAAMzF,EACN,MAAOyG,CACT,CAAC,EAEDhB,EAAOgB,CACT,CAEAhB,EAAK,MAAQ,GACb,KAAK,aAAec,CACtB,EAEA3I,EAAK,SAAS,QAAQ,UAAU,OAAS,UAAY,CACnD,KAAK,SAAS,CAAC,CACjB,EAEAA,EAAK,SAAS,QAAQ,UAAU,SAAW,SAAU8I,EAAQ,CAC3D,QAAS7H,EAAI,KAAK,eAAe,OAAS,EAAGA,GAAK6H,EAAQ7H,IAAK,CAC7D,IAAI4G,EAAO,KAAK,eAAe5G,GAC3B8H,EAAWlB,EAAK,MAAM,SAAS,EAE/BkB,KAAY,KAAK,eACnBlB,EAAK,OAAO,MAAMA,EAAK,MAAQ,KAAK,eAAekB,IAInDlB,EAAK,MAAM,KAAOkB,EAElB,KAAK,eAAeA,GAAYlB,EAAK,OAGvC,KAAK,eAAe,IAAI,CAC1B,CACF,EACA;AAAA;AAAA;AAAA,GAqBA7H,EAAK,MAAQ,SAAUgJ,EAAO,CAC5B,KAAK,cAAgBA,EAAM,cAC3B,KAAK,aAAeA,EAAM,aAC1B,KAAK,SAAWA,EAAM,SACtB,KAAK,OAASA,EAAM,OACpB,KAAK,SAAWA,EAAM,QACxB,EAyEAhJ,EAAK,MAAM,UAAU,OAAS,SAAUiJ,EAAa,CACnD,OAAO,KAAK,MAAM,SAAUC,EAAO,CACjC,IAAIC,EAAS,IAAInJ,EAAK,YAAYiJ,EAAaC,CAAK,EACpDC,EAAO,MAAM,CACf,CAAC,CACH,EA2BAnJ,EAAK,MAAM,UAAU,MAAQ,SAAU8B,EAAI,CAoBzC,QAZIoH,EAAQ,IAAIlJ,EAAK,MAAM,KAAK,MAAM,EAClCoJ,EAAiB,OAAO,OAAO,IAAI,EACnCC,EAAe,OAAO,OAAO,IAAI,EACjCC,EAAiB,OAAO,OAAO,IAAI,EACnCC,EAAkB,OAAO,OAAO,IAAI,EACpCC,EAAoB,OAAO,OAAO,IAAI,EAOjCvI,EAAI,EAAGA,EAAI,KAAK,OAAO,OAAQA,IACtCoI,EAAa,KAAK,OAAOpI,IAAM,IAAIjB,EAAK,OAG1C8B,EAAG,KAAKoH,EAAOA,CAAK,EAEpB,QAASjI,EAAI,EAAGA,EAAIiI,EAAM,QAAQ,OAAQjI,IAAK,CAS7C,IAAIiG,EAASgC,EAAM,QAAQjI,GACvBwI,EAAQ,KACRC,EAAgB1J,EAAK,IAAI,MAEzBkH,EAAO,YACTuC,EAAQ,KAAK,SAAS,UAAUvC,EAAO,KAAM,CAC3C,OAAQA,EAAO,MACjB,CAAC,EAEDuC,EAAQ,CAACvC,EAAO,IAAI,EAGtB,QAASyC,EAAI,EAAGA,EAAIF,EAAM,OAAQE,IAAK,CACrC,IAAIC,EAAOH,EAAME,GAQjBzC,EAAO,KAAO0C,EAOd,IAAIC,EAAe7J,EAAK,SAAS,WAAWkH,CAAM,EAC9C4C,EAAgB,KAAK,SAAS,UAAUD,CAAY,EAAE,QAAQ,EAQlE,GAAIC,EAAc,SAAW,GAAK5C,EAAO,WAAalH,EAAK,MAAM,SAAS,SAAU,CAClF,QAASoD,EAAI,EAAGA,EAAI8D,EAAO,OAAO,OAAQ9D,IAAK,CAC7C,IAAI2G,EAAQ7C,EAAO,OAAO9D,GAC1BmG,EAAgBQ,GAAS/J,EAAK,IAAI,KACpC,CAEA,KACF,CAEA,QAASkD,EAAI,EAAGA,EAAI4G,EAAc,OAAQ5G,IASxC,QAJI8G,EAAeF,EAAc5G,GAC7B1B,EAAU,KAAK,cAAcwI,GAC7BC,EAAYzI,EAAQ,OAEf4B,EAAI,EAAGA,EAAI8D,EAAO,OAAO,OAAQ9D,IAAK,CAS7C,IAAI2G,EAAQ7C,EAAO,OAAO9D,GACtB8G,EAAe1I,EAAQuI,GACvBI,EAAuB,OAAO,KAAKD,CAAY,EAC/CE,EAAYJ,EAAe,IAAMD,EACjCM,EAAuB,IAAIrK,EAAK,IAAImK,CAAoB,EAoB5D,GAbIjD,EAAO,UAAYlH,EAAK,MAAM,SAAS,WACzC0J,EAAgBA,EAAc,MAAMW,CAAoB,EAEpDd,EAAgBQ,KAAW,SAC7BR,EAAgBQ,GAAS/J,EAAK,IAAI,WASlCkH,EAAO,UAAYlH,EAAK,MAAM,SAAS,WAAY,CACjDwJ,EAAkBO,KAAW,SAC/BP,EAAkBO,GAAS/J,EAAK,IAAI,OAGtCwJ,EAAkBO,GAASP,EAAkBO,GAAO,MAAMM,CAAoB,EAO9E,QACF,CAeA,GANAhB,EAAaU,GAAO,OAAOE,EAAW/C,EAAO,MAAO,SAAU9F,GAAGC,GAAG,CAAE,OAAOD,GAAIC,EAAE,CAAC,EAMhF,CAAAiI,EAAec,GAInB,SAASE,EAAI,EAAGA,EAAIH,EAAqB,OAAQG,IAAK,CAOpD,IAAIC,EAAsBJ,EAAqBG,GAC3CE,EAAmB,IAAIxK,EAAK,SAAUuK,EAAqBR,CAAK,EAChElI,EAAWqI,EAAaK,GACxBE,GAECA,EAAarB,EAAeoB,MAAuB,OACtDpB,EAAeoB,GAAoB,IAAIxK,EAAK,UAAWgK,EAAcD,EAAOlI,CAAQ,EAEpF4I,EAAW,IAAIT,EAAcD,EAAOlI,CAAQ,CAGhD,CAEAyH,EAAec,GAAa,GAC9B,CAEJ,CAQA,GAAIlD,EAAO,WAAalH,EAAK,MAAM,SAAS,SAC1C,QAASoD,EAAI,EAAGA,EAAI8D,EAAO,OAAO,OAAQ9D,IAAK,CAC7C,IAAI2G,EAAQ7C,EAAO,OAAO9D,GAC1BmG,EAAgBQ,GAASR,EAAgBQ,GAAO,UAAUL,CAAa,CACzE,CAEJ,CAUA,QAHIgB,EAAqB1K,EAAK,IAAI,SAC9B2K,EAAuB3K,EAAK,IAAI,MAE3BiB,EAAI,EAAGA,EAAI,KAAK,OAAO,OAAQA,IAAK,CAC3C,IAAI8I,EAAQ,KAAK,OAAO9I,GAEpBsI,EAAgBQ,KAClBW,EAAqBA,EAAmB,UAAUnB,EAAgBQ,EAAM,GAGtEP,EAAkBO,KACpBY,EAAuBA,EAAqB,MAAMnB,EAAkBO,EAAM,EAE9E,CAEA,IAAIa,EAAoB,OAAO,KAAKxB,CAAc,EAC9CyB,EAAU,CAAC,EACXC,EAAU,OAAO,OAAO,IAAI,EAYhC,GAAI5B,EAAM,UAAU,EAAG,CACrB0B,EAAoB,OAAO,KAAK,KAAK,YAAY,EAEjD,QAAS3J,EAAI,EAAGA,EAAI2J,EAAkB,OAAQ3J,IAAK,CACjD,IAAIuJ,EAAmBI,EAAkB3J,GACrCF,EAAWf,EAAK,SAAS,WAAWwK,CAAgB,EACxDpB,EAAeoB,GAAoB,IAAIxK,EAAK,SAC9C,CACF,CAEA,QAASiB,EAAI,EAAGA,EAAI2J,EAAkB,OAAQ3J,IAAK,CASjD,IAAIF,EAAWf,EAAK,SAAS,WAAW4K,EAAkB3J,EAAE,EACxDP,EAASK,EAAS,OAEtB,GAAI,EAAC2J,EAAmB,SAAShK,CAAM,GAInC,CAAAiK,EAAqB,SAASjK,CAAM,EAIxC,KAAIqK,EAAc,KAAK,aAAahK,GAChCiK,EAAQ3B,EAAatI,EAAS,WAAW,WAAWgK,CAAW,EAC/DE,EAEJ,IAAKA,EAAWH,EAAQpK,MAAa,OACnCuK,EAAS,OAASD,EAClBC,EAAS,UAAU,QAAQ7B,EAAerI,EAAS,MAC9C,CACL,IAAImK,EAAQ,CACV,IAAKxK,EACL,MAAOsK,EACP,UAAW5B,EAAerI,EAC5B,EACA+J,EAAQpK,GAAUwK,EAClBL,EAAQ,KAAKK,CAAK,CACpB,EACF,CAKA,OAAOL,EAAQ,KAAK,SAAUzJ,GAAGC,GAAG,CAClC,OAAOA,GAAE,MAAQD,GAAE,KACrB,CAAC,CACH,EAUApB,EAAK,MAAM,UAAU,OAAS,UAAY,CACxC,IAAImL,EAAgB,OAAO,KAAK,KAAK,aAAa,EAC/C,KAAK,EACL,IAAI,SAAUvB,EAAM,CACnB,MAAO,CAACA,EAAM,KAAK,cAAcA,EAAK,CACxC,EAAG,IAAI,EAELwB,EAAe,OAAO,KAAK,KAAK,YAAY,EAC7C,IAAI,SAAUC,EAAK,CAClB,MAAO,CAACA,EAAK,KAAK,aAAaA,GAAK,OAAO,CAAC,CAC9C,EAAG,IAAI,EAET,MAAO,CACL,QAASrL,EAAK,QACd,OAAQ,KAAK,OACb,aAAcoL,EACd,cAAeD,EACf,SAAU,KAAK,SAAS,OAAO,CACjC,CACF,EAQAnL,EAAK,MAAM,KAAO,SAAUsL,EAAiB,CAC3C,IAAItC,EAAQ,CAAC,EACToC,EAAe,CAAC,EAChBG,EAAoBD,EAAgB,aACpCH,EAAgB,OAAO,OAAO,IAAI,EAClCK,EAA0BF,EAAgB,cAC1CG,EAAkB,IAAIzL,EAAK,SAAS,QACpC0C,EAAW1C,EAAK,SAAS,KAAKsL,EAAgB,QAAQ,EAEtDA,EAAgB,SAAWtL,EAAK,SAClCA,EAAK,MAAM,KAAK,4EAA8EA,EAAK,QAAU,sCAAwCsL,EAAgB,QAAU,GAAG,EAGpL,QAASrK,EAAI,EAAGA,EAAIsK,EAAkB,OAAQtK,IAAK,CACjD,IAAIyK,EAAQH,EAAkBtK,GAC1BoK,EAAMK,EAAM,GACZ1K,EAAW0K,EAAM,GAErBN,EAAaC,GAAO,IAAIrL,EAAK,OAAOgB,CAAQ,CAC9C,CAEA,QAASC,EAAI,EAAGA,EAAIuK,EAAwB,OAAQvK,IAAK,CACvD,IAAIyK,EAAQF,EAAwBvK,GAChC2I,EAAO8B,EAAM,GACblK,EAAUkK,EAAM,GAEpBD,EAAgB,OAAO7B,CAAI,EAC3BuB,EAAcvB,GAAQpI,CACxB,CAEA,OAAAiK,EAAgB,OAAO,EAEvBzC,EAAM,OAASsC,EAAgB,OAE/BtC,EAAM,aAAeoC,EACrBpC,EAAM,cAAgBmC,EACtBnC,EAAM,SAAWyC,EAAgB,KACjCzC,EAAM,SAAWtG,EAEV,IAAI1C,EAAK,MAAMgJ,CAAK,CAC7B,EACA;AAAA;AAAA;AAAA,GA6BAhJ,EAAK,QAAU,UAAY,CACzB,KAAK,KAAO,KACZ,KAAK,QAAU,OAAO,OAAO,IAAI,EACjC,KAAK,WAAa,OAAO,OAAO,IAAI,EACpC,KAAK,cAAgB,OAAO,OAAO,IAAI,EACvC,KAAK,qBAAuB,CAAC,EAC7B,KAAK,aAAe,CAAC,EACrB,KAAK,UAAYA,EAAK,UACtB,KAAK,SAAW,IAAIA,EAAK,SACzB,KAAK,eAAiB,IAAIA,EAAK,SAC/B,KAAK,cAAgB,EACrB,KAAK,GAAK,IACV,KAAK,IAAM,IACX,KAAK,UAAY,EACjB,KAAK,kBAAoB,CAAC,CAC5B,EAcAA,EAAK,QAAQ,UAAU,IAAM,SAAUqL,EAAK,CAC1C,KAAK,KAAOA,CACd,EAkCArL,EAAK,QAAQ,UAAU,MAAQ,SAAUW,EAAWgL,EAAY,CAC9D,GAAI,KAAK,KAAKhL,CAAS,EACrB,MAAM,IAAI,WAAY,UAAYA,EAAY,kCAAkC,EAGlF,KAAK,QAAQA,GAAagL,GAAc,CAAC,CAC3C,EAUA3L,EAAK,QAAQ,UAAU,EAAI,SAAU4L,EAAQ,CACvCA,EAAS,EACX,KAAK,GAAK,EACDA,EAAS,EAClB,KAAK,GAAK,EAEV,KAAK,GAAKA,CAEd,EASA5L,EAAK,QAAQ,UAAU,GAAK,SAAU4L,EAAQ,CAC5C,KAAK,IAAMA,CACb,EAmBA5L,EAAK,QAAQ,UAAU,IAAM,SAAU6L,EAAKF,EAAY,CACtD,IAAIjL,EAASmL,EAAI,KAAK,MAClBC,EAAS,OAAO,KAAK,KAAK,OAAO,EAErC,KAAK,WAAWpL,GAAUiL,GAAc,CAAC,EACzC,KAAK,eAAiB,EAEtB,QAAS1K,EAAI,EAAGA,EAAI6K,EAAO,OAAQ7K,IAAK,CACtC,IAAIN,EAAYmL,EAAO7K,GACnB8K,EAAY,KAAK,QAAQpL,GAAW,UACpCoJ,EAAQgC,EAAYA,EAAUF,CAAG,EAAIA,EAAIlL,GACzCsB,EAAS,KAAK,UAAU8H,EAAO,CAC7B,OAAQ,CAACpJ,CAAS,CACpB,CAAC,EACD8I,EAAQ,KAAK,SAAS,IAAIxH,CAAM,EAChClB,EAAW,IAAIf,EAAK,SAAUU,EAAQC,CAAS,EAC/CqL,EAAa,OAAO,OAAO,IAAI,EAEnC,KAAK,qBAAqBjL,GAAYiL,EACtC,KAAK,aAAajL,GAAY,EAG9B,KAAK,aAAaA,IAAa0I,EAAM,OAGrC,QAASvG,EAAI,EAAGA,EAAIuG,EAAM,OAAQvG,IAAK,CACrC,IAAI0G,EAAOH,EAAMvG,GAUjB,GARI8I,EAAWpC,IAAS,OACtBoC,EAAWpC,GAAQ,GAGrBoC,EAAWpC,IAAS,EAIhB,KAAK,cAAcA,IAAS,KAAW,CACzC,IAAIpI,EAAU,OAAO,OAAO,IAAI,EAChCA,EAAQ,OAAY,KAAK,UACzB,KAAK,WAAa,EAElB,QAAS4B,EAAI,EAAGA,EAAI0I,EAAO,OAAQ1I,IACjC5B,EAAQsK,EAAO1I,IAAM,OAAO,OAAO,IAAI,EAGzC,KAAK,cAAcwG,GAAQpI,CAC7B,CAGI,KAAK,cAAcoI,GAAMjJ,GAAWD,IAAW,OACjD,KAAK,cAAckJ,GAAMjJ,GAAWD,GAAU,OAAO,OAAO,IAAI,GAKlE,QAAS4J,EAAI,EAAGA,EAAI,KAAK,kBAAkB,OAAQA,IAAK,CACtD,IAAI2B,EAAc,KAAK,kBAAkB3B,GACrCzI,EAAW+H,EAAK,SAASqC,GAEzB,KAAK,cAAcrC,GAAMjJ,GAAWD,GAAQuL,IAAgB,OAC9D,KAAK,cAAcrC,GAAMjJ,GAAWD,GAAQuL,GAAe,CAAC,GAG9D,KAAK,cAAcrC,GAAMjJ,GAAWD,GAAQuL,GAAa,KAAKpK,CAAQ,CACxE,CACF,CAEF,CACF,EAOA7B,EAAK,QAAQ,UAAU,6BAA+B,UAAY,CAOhE,QALIkM,EAAY,OAAO,KAAK,KAAK,YAAY,EACzCC,EAAiBD,EAAU,OAC3BE,EAAc,CAAC,EACfC,EAAqB,CAAC,EAEjBpL,EAAI,EAAGA,EAAIkL,EAAgBlL,IAAK,CACvC,IAAIF,EAAWf,EAAK,SAAS,WAAWkM,EAAUjL,EAAE,EAChD8I,EAAQhJ,EAAS,UAErBsL,EAAmBtC,KAAWsC,EAAmBtC,GAAS,GAC1DsC,EAAmBtC,IAAU,EAE7BqC,EAAYrC,KAAWqC,EAAYrC,GAAS,GAC5CqC,EAAYrC,IAAU,KAAK,aAAahJ,EAC1C,CAIA,QAFI+K,EAAS,OAAO,KAAK,KAAK,OAAO,EAE5B7K,EAAI,EAAGA,EAAI6K,EAAO,OAAQ7K,IAAK,CACtC,IAAIN,EAAYmL,EAAO7K,GACvBmL,EAAYzL,GAAayL,EAAYzL,GAAa0L,EAAmB1L,EACvE,CAEA,KAAK,mBAAqByL,CAC5B,EAOApM,EAAK,QAAQ,UAAU,mBAAqB,UAAY,CAMtD,QALIoL,EAAe,CAAC,EAChBc,EAAY,OAAO,KAAK,KAAK,oBAAoB,EACjDI,EAAkBJ,EAAU,OAC5BK,EAAe,OAAO,OAAO,IAAI,EAE5BtL,EAAI,EAAGA,EAAIqL,EAAiBrL,IAAK,CAaxC,QAZIF,EAAWf,EAAK,SAAS,WAAWkM,EAAUjL,EAAE,EAChDN,EAAYI,EAAS,UACrByL,EAAc,KAAK,aAAazL,GAChCgK,EAAc,IAAI/K,EAAK,OACvByM,EAAkB,KAAK,qBAAqB1L,GAC5C0I,EAAQ,OAAO,KAAKgD,CAAe,EACnCC,EAAcjD,EAAM,OAGpBkD,EAAa,KAAK,QAAQhM,GAAW,OAAS,EAC9CiM,EAAW,KAAK,WAAW7L,EAAS,QAAQ,OAAS,EAEhDmC,EAAI,EAAGA,EAAIwJ,EAAaxJ,IAAK,CACpC,IAAI0G,EAAOH,EAAMvG,GACb2J,EAAKJ,EAAgB7C,GACrBK,EAAY,KAAK,cAAcL,GAAM,OACrCkD,EAAK9B,EAAO+B,EAEZR,EAAa3C,KAAU,QACzBkD,EAAM9M,EAAK,IAAI,KAAK,cAAc4J,GAAO,KAAK,aAAa,EAC3D2C,EAAa3C,GAAQkD,GAErBA,EAAMP,EAAa3C,GAGrBoB,EAAQ8B,IAAQ,KAAK,IAAM,GAAKD,IAAO,KAAK,KAAO,EAAI,KAAK,GAAK,KAAK,IAAML,EAAc,KAAK,mBAAmB7L,KAAekM,GACjI7B,GAAS2B,EACT3B,GAAS4B,EACTG,EAAqB,KAAK,MAAM/B,EAAQ,GAAI,EAAI,IAQhDD,EAAY,OAAOd,EAAW8C,CAAkB,CAClD,CAEA3B,EAAarK,GAAYgK,CAC3B,CAEA,KAAK,aAAeK,CACtB,EAOApL,EAAK,QAAQ,UAAU,eAAiB,UAAY,CAClD,KAAK,SAAWA,EAAK,SAAS,UAC5B,OAAO,KAAK,KAAK,aAAa,EAAE,KAAK,CACvC,CACF,EAUAA,EAAK,QAAQ,UAAU,MAAQ,UAAY,CACzC,YAAK,6BAA6B,EAClC,KAAK,mBAAmB,EACxB,KAAK,eAAe,EAEb,IAAIA,EAAK,MAAM,CACpB,cAAe,KAAK,cACpB,aAAc,KAAK,aACnB,SAAU,KAAK,SACf,OAAQ,OAAO,KAAK,KAAK,OAAO,EAChC,SAAU,KAAK,cACjB,CAAC,CACH,EAgBAA,EAAK,QAAQ,UAAU,IAAM,SAAU8B,EAAI,CACzC,IAAIkL,EAAO,MAAM,UAAU,MAAM,KAAK,UAAW,CAAC,EAClDA,EAAK,QAAQ,IAAI,EACjBlL,EAAG,MAAM,KAAMkL,CAAI,CACrB,EAaAhN,EAAK,UAAY,SAAU4J,EAAMG,EAAOlI,EAAU,CAShD,QARIoL,EAAiB,OAAO,OAAO,IAAI,EACnCC,EAAe,OAAO,KAAKrL,GAAY,CAAC,CAAC,EAOpCZ,EAAI,EAAGA,EAAIiM,EAAa,OAAQjM,IAAK,CAC5C,IAAIT,EAAM0M,EAAajM,GACvBgM,EAAezM,GAAOqB,EAASrB,GAAK,MAAM,CAC5C,CAEA,KAAK,SAAW,OAAO,OAAO,IAAI,EAE9BoJ,IAAS,SACX,KAAK,SAASA,GAAQ,OAAO,OAAO,IAAI,EACxC,KAAK,SAASA,GAAMG,GAASkD,EAEjC,EAWAjN,EAAK,UAAU,UAAU,QAAU,SAAUmN,EAAgB,CAG3D,QAFI1D,EAAQ,OAAO,KAAK0D,EAAe,QAAQ,EAEtClM,EAAI,EAAGA,EAAIwI,EAAM,OAAQxI,IAAK,CACrC,IAAI2I,EAAOH,EAAMxI,GACb6K,EAAS,OAAO,KAAKqB,EAAe,SAASvD,EAAK,EAElD,KAAK,SAASA,IAAS,OACzB,KAAK,SAASA,GAAQ,OAAO,OAAO,IAAI,GAG1C,QAAS1G,EAAI,EAAGA,EAAI4I,EAAO,OAAQ5I,IAAK,CACtC,IAAI6G,EAAQ+B,EAAO5I,GACf3C,EAAO,OAAO,KAAK4M,EAAe,SAASvD,GAAMG,EAAM,EAEvD,KAAK,SAASH,GAAMG,IAAU,OAChC,KAAK,SAASH,GAAMG,GAAS,OAAO,OAAO,IAAI,GAGjD,QAAS3G,EAAI,EAAGA,EAAI7C,EAAK,OAAQ6C,IAAK,CACpC,IAAI5C,EAAMD,EAAK6C,GAEX,KAAK,SAASwG,GAAMG,GAAOvJ,IAAQ,KACrC,KAAK,SAASoJ,GAAMG,GAAOvJ,GAAO2M,EAAe,SAASvD,GAAMG,GAAOvJ,GAEvE,KAAK,SAASoJ,GAAMG,GAAOvJ,GAAO,KAAK,SAASoJ,GAAMG,GAAOvJ,GAAK,OAAO2M,EAAe,SAASvD,GAAMG,GAAOvJ,EAAI,CAGtH,CACF,CACF,CACF,EASAR,EAAK,UAAU,UAAU,IAAM,SAAU4J,EAAMG,EAAOlI,EAAU,CAC9D,GAAI,EAAE+H,KAAQ,KAAK,UAAW,CAC5B,KAAK,SAASA,GAAQ,OAAO,OAAO,IAAI,EACxC,KAAK,SAASA,GAAMG,GAASlI,EAC7B,MACF,CAEA,GAAI,EAAEkI,KAAS,KAAK,SAASH,IAAQ,CACnC,KAAK,SAASA,GAAMG,GAASlI,EAC7B,MACF,CAIA,QAFIqL,EAAe,OAAO,KAAKrL,CAAQ,EAE9BZ,EAAI,EAAGA,EAAIiM,EAAa,OAAQjM,IAAK,CAC5C,IAAIT,EAAM0M,EAAajM,GAEnBT,KAAO,KAAK,SAASoJ,GAAMG,GAC7B,KAAK,SAASH,GAAMG,GAAOvJ,GAAO,KAAK,SAASoJ,GAAMG,GAAOvJ,GAAK,OAAOqB,EAASrB,EAAI,EAEtF,KAAK,SAASoJ,GAAMG,GAAOvJ,GAAOqB,EAASrB,EAE/C,CACF,EAYAR,EAAK,MAAQ,SAAUoN,EAAW,CAChC,KAAK,QAAU,CAAC,EAChB,KAAK,UAAYA,CACnB,EA0BApN,EAAK,MAAM,SAAW,IAAI,OAAQ,GAAG,EACrCA,EAAK,MAAM,SAAS,KAAO,EAC3BA,EAAK,MAAM,SAAS,QAAU,EAC9BA,EAAK,MAAM,SAAS,SAAW,EAa/BA,EAAK,MAAM,SAAW,CAIpB,SAAU,EAMV,SAAU,EAMV,WAAY,CACd,EAyBAA,EAAK,MAAM,UAAU,OAAS,SAAUkH,EAAQ,CAC9C,MAAM,WAAYA,IAChBA,EAAO,OAAS,KAAK,WAGjB,UAAWA,IACfA,EAAO,MAAQ,GAGX,gBAAiBA,IACrBA,EAAO,YAAc,IAGjB,aAAcA,IAClBA,EAAO,SAAWlH,EAAK,MAAM,SAAS,MAGnCkH,EAAO,SAAWlH,EAAK,MAAM,SAAS,SAAakH,EAAO,KAAK,OAAO,CAAC,GAAKlH,EAAK,MAAM,WAC1FkH,EAAO,KAAO,IAAMA,EAAO,MAGxBA,EAAO,SAAWlH,EAAK,MAAM,SAAS,UAAckH,EAAO,KAAK,MAAM,EAAE,GAAKlH,EAAK,MAAM,WAC3FkH,EAAO,KAAO,GAAKA,EAAO,KAAO,KAG7B,aAAcA,IAClBA,EAAO,SAAWlH,EAAK,MAAM,SAAS,UAGxC,KAAK,QAAQ,KAAKkH,CAAM,EAEjB,IACT,EASAlH,EAAK,MAAM,UAAU,UAAY,UAAY,CAC3C,QAASiB,EAAI,EAAGA,EAAI,KAAK,QAAQ,OAAQA,IACvC,GAAI,KAAK,QAAQA,GAAG,UAAYjB,EAAK,MAAM,SAAS,WAClD,MAAO,GAIX,MAAO,EACT,EA4BAA,EAAK,MAAM,UAAU,KAAO,SAAU4J,EAAMyD,EAAS,CACnD,GAAI,MAAM,QAAQzD,CAAI,EACpB,OAAAA,EAAK,QAAQ,SAAU7H,EAAG,CAAE,KAAK,KAAKA,EAAG/B,EAAK,MAAM,MAAMqN,CAAO,CAAC,CAAE,EAAG,IAAI,EACpE,KAGT,IAAInG,EAASmG,GAAW,CAAC,EACzB,OAAAnG,EAAO,KAAO0C,EAAK,SAAS,EAE5B,KAAK,OAAO1C,CAAM,EAEX,IACT,EACAlH,EAAK,gBAAkB,SAAUI,EAASmD,EAAOC,EAAK,CACpD,KAAK,KAAO,kBACZ,KAAK,QAAUpD,EACf,KAAK,MAAQmD,EACb,KAAK,IAAMC,CACb,EAEAxD,EAAK,gBAAgB,UAAY,IAAI,MACrCA,EAAK,WAAa,SAAU4B,EAAK,CAC/B,KAAK,QAAU,CAAC,EAChB,KAAK,IAAMA,EACX,KAAK,OAASA,EAAI,OAClB,KAAK,IAAM,EACX,KAAK,MAAQ,EACb,KAAK,oBAAsB,CAAC,CAC9B,EAEA5B,EAAK,WAAW,UAAU,IAAM,UAAY,CAG1C,QAFIsN,EAAQtN,EAAK,WAAW,QAErBsN,GACLA,EAAQA,EAAM,IAAI,CAEtB,EAEAtN,EAAK,WAAW,UAAU,YAAc,UAAY,CAKlD,QAJIuN,EAAY,CAAC,EACbpL,EAAa,KAAK,MAClBD,EAAW,KAAK,IAEX,EAAI,EAAG,EAAI,KAAK,oBAAoB,OAAQ,IACnDA,EAAW,KAAK,oBAAoB,GACpCqL,EAAU,KAAK,KAAK,IAAI,MAAMpL,EAAYD,CAAQ,CAAC,EACnDC,EAAaD,EAAW,EAG1B,OAAAqL,EAAU,KAAK,KAAK,IAAI,MAAMpL,EAAY,KAAK,GAAG,CAAC,EACnD,KAAK,oBAAoB,OAAS,EAE3BoL,EAAU,KAAK,EAAE,CAC1B,EAEAvN,EAAK,WAAW,UAAU,KAAO,SAAUwN,EAAM,CAC/C,KAAK,QAAQ,KAAK,CAChB,KAAMA,EACN,IAAK,KAAK,YAAY,EACtB,MAAO,KAAK,MACZ,IAAK,KAAK,GACZ,CAAC,EAED,KAAK,MAAQ,KAAK,GACpB,EAEAxN,EAAK,WAAW,UAAU,gBAAkB,UAAY,CACtD,KAAK,oBAAoB,KAAK,KAAK,IAAM,CAAC,EAC1C,KAAK,KAAO,CACd,EAEAA,EAAK,WAAW,UAAU,KAAO,UAAY,CAC3C,GAAI,KAAK,KAAO,KAAK,OACnB,OAAOA,EAAK,WAAW,IAGzB,IAAIoC,EAAO,KAAK,IAAI,OAAO,KAAK,GAAG,EACnC,YAAK,KAAO,EACLA,CACT,EAEApC,EAAK,WAAW,UAAU,MAAQ,UAAY,CAC5C,OAAO,KAAK,IAAM,KAAK,KACzB,EAEAA,EAAK,WAAW,UAAU,OAAS,UAAY,CACzC,KAAK,OAAS,KAAK,MACrB,KAAK,KAAO,GAGd,KAAK,MAAQ,KAAK,GACpB,EAEAA,EAAK,WAAW,UAAU,OAAS,UAAY,CAC7C,KAAK,KAAO,CACd,EAEAA,EAAK,WAAW,UAAU,eAAiB,UAAY,CACrD,IAAIoC,EAAMqL,EAEV,GACErL,EAAO,KAAK,KAAK,EACjBqL,EAAWrL,EAAK,WAAW,CAAC,QACrBqL,EAAW,IAAMA,EAAW,IAEjCrL,GAAQpC,EAAK,WAAW,KAC1B,KAAK,OAAO,CAEhB,EAEAA,EAAK,WAAW,UAAU,KAAO,UAAY,CAC3C,OAAO,KAAK,IAAM,KAAK,MACzB,EAEAA,EAAK,WAAW,IAAM,MACtBA,EAAK,WAAW,MAAQ,QACxBA,EAAK,WAAW,KAAO,OACvBA,EAAK,WAAW,cAAgB,gBAChCA,EAAK,WAAW,MAAQ,QACxBA,EAAK,WAAW,SAAW,WAE3BA,EAAK,WAAW,SAAW,SAAU0N,EAAO,CAC1C,OAAAA,EAAM,OAAO,EACbA,EAAM,KAAK1N,EAAK,WAAW,KAAK,EAChC0N,EAAM,OAAO,EACN1N,EAAK,WAAW,OACzB,EAEAA,EAAK,WAAW,QAAU,SAAU0N,EAAO,CAQzC,GAPIA,EAAM,MAAM,EAAI,IAClBA,EAAM,OAAO,EACbA,EAAM,KAAK1N,EAAK,WAAW,IAAI,GAGjC0N,EAAM,OAAO,EAETA,EAAM,KAAK,EACb,OAAO1N,EAAK,WAAW,OAE3B,EAEAA,EAAK,WAAW,gBAAkB,SAAU0N,EAAO,CACjD,OAAAA,EAAM,OAAO,EACbA,EAAM,eAAe,EACrBA,EAAM,KAAK1N,EAAK,WAAW,aAAa,EACjCA,EAAK,WAAW,OACzB,EAEAA,EAAK,WAAW,SAAW,SAAU0N,EAAO,CAC1C,OAAAA,EAAM,OAAO,EACbA,EAAM,eAAe,EACrBA,EAAM,KAAK1N,EAAK,WAAW,KAAK,EACzBA,EAAK,WAAW,OACzB,EAEAA,EAAK,WAAW,OAAS,SAAU0N,EAAO,CACpCA,EAAM,MAAM,EAAI,GAClBA,EAAM,KAAK1N,EAAK,WAAW,IAAI,CAEnC,EAaAA,EAAK,WAAW,cAAgBA,EAAK,UAAU,UAE/CA,EAAK,WAAW,QAAU,SAAU0N,EAAO,CACzC,OAAa,CACX,IAAItL,EAAOsL,EAAM,KAAK,EAEtB,GAAItL,GAAQpC,EAAK,WAAW,IAC1B,OAAOA,EAAK,WAAW,OAIzB,GAAIoC,EAAK,WAAW,CAAC,GAAK,GAAI,CAC5BsL,EAAM,gBAAgB,EACtB,QACF,CAEA,GAAItL,GAAQ,IACV,OAAOpC,EAAK,WAAW,SAGzB,GAAIoC,GAAQ,IACV,OAAAsL,EAAM,OAAO,EACTA,EAAM,MAAM,EAAI,GAClBA,EAAM,KAAK1N,EAAK,WAAW,IAAI,EAE1BA,EAAK,WAAW,gBAGzB,GAAIoC,GAAQ,IACV,OAAAsL,EAAM,OAAO,EACTA,EAAM,MAAM,EAAI,GAClBA,EAAM,KAAK1N,EAAK,WAAW,IAAI,EAE1BA,EAAK,WAAW,SAczB,GARIoC,GAAQ,KAAOsL,EAAM,MAAM,IAAM,GAQjCtL,GAAQ,KAAOsL,EAAM,MAAM,IAAM,EACnC,OAAAA,EAAM,KAAK1N,EAAK,WAAW,QAAQ,EAC5BA,EAAK,WAAW,QAGzB,GAAIoC,EAAK,MAAMpC,EAAK,WAAW,aAAa,EAC1C,OAAOA,EAAK,WAAW,OAE3B,CACF,EAEAA,EAAK,YAAc,SAAU4B,EAAKsH,EAAO,CACvC,KAAK,MAAQ,IAAIlJ,EAAK,WAAY4B,CAAG,EACrC,KAAK,MAAQsH,EACb,KAAK,cAAgB,CAAC,EACtB,KAAK,UAAY,CACnB,EAEAlJ,EAAK,YAAY,UAAU,MAAQ,UAAY,CAC7C,KAAK,MAAM,IAAI,EACf,KAAK,QAAU,KAAK,MAAM,QAI1B,QAFIsN,EAAQtN,EAAK,YAAY,YAEtBsN,GACLA,EAAQA,EAAM,IAAI,EAGpB,OAAO,KAAK,KACd,EAEAtN,EAAK,YAAY,UAAU,WAAa,UAAY,CAClD,OAAO,KAAK,QAAQ,KAAK,UAC3B,EAEAA,EAAK,YAAY,UAAU,cAAgB,UAAY,CACrD,IAAI2N,EAAS,KAAK,WAAW,EAC7B,YAAK,WAAa,EACXA,CACT,EAEA3N,EAAK,YAAY,UAAU,WAAa,UAAY,CAClD,IAAI4N,EAAkB,KAAK,cAC3B,KAAK,MAAM,OAAOA,CAAe,EACjC,KAAK,cAAgB,CAAC,CACxB,EAEA5N,EAAK,YAAY,YAAc,SAAUmJ,EAAQ,CAC/C,IAAIwE,EAASxE,EAAO,WAAW,EAE/B,GAAIwE,GAAU,KAId,OAAQA,EAAO,KAAM,CACnB,KAAK3N,EAAK,WAAW,SACnB,OAAOA,EAAK,YAAY,cAC1B,KAAKA,EAAK,WAAW,MACnB,OAAOA,EAAK,YAAY,WAC1B,KAAKA,EAAK,WAAW,KACnB,OAAOA,EAAK,YAAY,UAC1B,QACE,IAAI6N,EAAe,4CAA8CF,EAAO,KAExE,MAAIA,EAAO,IAAI,QAAU,IACvBE,GAAgB,gBAAkBF,EAAO,IAAM,KAG3C,IAAI3N,EAAK,gBAAiB6N,EAAcF,EAAO,MAAOA,EAAO,GAAG,CAC1E,CACF,EAEA3N,EAAK,YAAY,cAAgB,SAAUmJ,EAAQ,CACjD,IAAIwE,EAASxE,EAAO,cAAc,EAElC,GAAIwE,GAAU,KAId,QAAQA,EAAO,IAAK,CAClB,IAAK,IACHxE,EAAO,cAAc,SAAWnJ,EAAK,MAAM,SAAS,WACpD,MACF,IAAK,IACHmJ,EAAO,cAAc,SAAWnJ,EAAK,MAAM,SAAS,SACpD,MACF,QACE,IAAI6N,EAAe,kCAAoCF,EAAO,IAAM,IACpE,MAAM,IAAI3N,EAAK,gBAAiB6N,EAAcF,EAAO,MAAOA,EAAO,GAAG,CAC1E,CAEA,IAAIG,EAAa3E,EAAO,WAAW,EAEnC,GAAI2E,GAAc,KAAW,CAC3B,IAAID,EAAe,yCACnB,MAAM,IAAI7N,EAAK,gBAAiB6N,EAAcF,EAAO,MAAOA,EAAO,GAAG,CACxE,CAEA,OAAQG,EAAW,KAAM,CACvB,KAAK9N,EAAK,WAAW,MACnB,OAAOA,EAAK,YAAY,WAC1B,KAAKA,EAAK,WAAW,KACnB,OAAOA,EAAK,YAAY,UAC1B,QACE,IAAI6N,EAAe,mCAAqCC,EAAW,KAAO,IAC1E,MAAM,IAAI9N,EAAK,gBAAiB6N,EAAcC,EAAW,MAAOA,EAAW,GAAG,CAClF,EACF,EAEA9N,EAAK,YAAY,WAAa,SAAUmJ,EAAQ,CAC9C,IAAIwE,EAASxE,EAAO,cAAc,EAElC,GAAIwE,GAAU,KAId,IAAIxE,EAAO,MAAM,UAAU,QAAQwE,EAAO,GAAG,GAAK,GAAI,CACpD,IAAII,EAAiB5E,EAAO,MAAM,UAAU,IAAI,SAAU6E,EAAG,CAAE,MAAO,IAAMA,EAAI,GAAI,CAAC,EAAE,KAAK,IAAI,EAC5FH,EAAe,uBAAyBF,EAAO,IAAM,uBAAyBI,EAElF,MAAM,IAAI/N,EAAK,gBAAiB6N,EAAcF,EAAO,MAAOA,EAAO,GAAG,CACxE,CAEAxE,EAAO,cAAc,OAAS,CAACwE,EAAO,GAAG,EAEzC,IAAIG,EAAa3E,EAAO,WAAW,EAEnC,GAAI2E,GAAc,KAAW,CAC3B,IAAID,EAAe,gCACnB,MAAM,IAAI7N,EAAK,gBAAiB6N,EAAcF,EAAO,MAAOA,EAAO,GAAG,CACxE,CAEA,OAAQG,EAAW,KAAM,CACvB,KAAK9N,EAAK,WAAW,KACnB,OAAOA,EAAK,YAAY,UAC1B,QACE,IAAI6N,EAAe,0BAA4BC,EAAW,KAAO,IACjE,MAAM,IAAI9N,EAAK,gBAAiB6N,EAAcC,EAAW,MAAOA,EAAW,GAAG,CAClF,EACF,EAEA9N,EAAK,YAAY,UAAY,SAAUmJ,EAAQ,CAC7C,IAAIwE,EAASxE,EAAO,cAAc,EAElC,GAAIwE,GAAU,KAId,CAAAxE,EAAO,cAAc,KAAOwE,EAAO,IAAI,YAAY,EAE/CA,EAAO,IAAI,QAAQ,GAAG,GAAK,KAC7BxE,EAAO,cAAc,YAAc,IAGrC,IAAI2E,EAAa3E,EAAO,WAAW,EAEnC,GAAI2E,GAAc,KAAW,CAC3B3E,EAAO,WAAW,EAClB,MACF,CAEA,OAAQ2E,EAAW,KAAM,CACvB,KAAK9N,EAAK,WAAW,KACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,UAC1B,KAAKA,EAAK,WAAW,MACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,WAC1B,KAAKA,EAAK,WAAW,cACnB,OAAOA,EAAK,YAAY,kBAC1B,KAAKA,EAAK,WAAW,MACnB,OAAOA,EAAK,YAAY,WAC1B,KAAKA,EAAK,WAAW,SACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,cAC1B,QACE,IAAI6N,EAAe,2BAA6BC,EAAW,KAAO,IAClE,MAAM,IAAI9N,EAAK,gBAAiB6N,EAAcC,EAAW,MAAOA,EAAW,GAAG,CAClF,EACF,EAEA9N,EAAK,YAAY,kBAAoB,SAAUmJ,EAAQ,CACrD,IAAIwE,EAASxE,EAAO,cAAc,EAElC,GAAIwE,GAAU,KAId,KAAIxG,EAAe,SAASwG,EAAO,IAAK,EAAE,EAE1C,GAAI,MAAMxG,CAAY,EAAG,CACvB,IAAI0G,EAAe,gCACnB,MAAM,IAAI7N,EAAK,gBAAiB6N,EAAcF,EAAO,MAAOA,EAAO,GAAG,CACxE,CAEAxE,EAAO,cAAc,aAAehC,EAEpC,IAAI2G,EAAa3E,EAAO,WAAW,EAEnC,GAAI2E,GAAc,KAAW,CAC3B3E,EAAO,WAAW,EAClB,MACF,CAEA,OAAQ2E,EAAW,KAAM,CACvB,KAAK9N,EAAK,WAAW,KACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,UAC1B,KAAKA,EAAK,WAAW,MACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,WAC1B,KAAKA,EAAK,WAAW,cACnB,OAAOA,EAAK,YAAY,kBAC1B,KAAKA,EAAK,WAAW,MACnB,OAAOA,EAAK,YAAY,WAC1B,KAAKA,EAAK,WAAW,SACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,cAC1B,QACE,IAAI6N,EAAe,2BAA6BC,EAAW,KAAO,IAClE,MAAM,IAAI9N,EAAK,gBAAiB6N,EAAcC,EAAW,MAAOA,EAAW,GAAG,CAClF,EACF,EAEA9N,EAAK,YAAY,WAAa,SAAUmJ,EAAQ,CAC9C,IAAIwE,EAASxE,EAAO,cAAc,EAElC,GAAIwE,GAAU,KAId,KAAIM,EAAQ,SAASN,EAAO,IAAK,EAAE,EAEnC,GAAI,MAAMM,CAAK,EAAG,CAChB,IAAIJ,EAAe,wBACnB,MAAM,IAAI7N,EAAK,gBAAiB6N,EAAcF,EAAO,MAAOA,EAAO,GAAG,CACxE,CAEAxE,EAAO,cAAc,MAAQ8E,EAE7B,IAAIH,EAAa3E,EAAO,WAAW,EAEnC,GAAI2E,GAAc,KAAW,CAC3B3E,EAAO,WAAW,EAClB,MACF,CAEA,OAAQ2E,EAAW,KAAM,CACvB,KAAK9N,EAAK,WAAW,KACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,UAC1B,KAAKA,EAAK,WAAW,MACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,WAC1B,KAAKA,EAAK,WAAW,cACnB,OAAOA,EAAK,YAAY,kBAC1B,KAAKA,EAAK,WAAW,MACnB,OAAOA,EAAK,YAAY,WAC1B,KAAKA,EAAK,WAAW,SACnB,OAAAmJ,EAAO,WAAW,EACXnJ,EAAK,YAAY,cAC1B,QACE,IAAI6N,EAAe,2BAA6BC,EAAW,KAAO,IAClE,MAAM,IAAI9N,EAAK,gBAAiB6N,EAAcC,EAAW,MAAOA,EAAW,GAAG,CAClF,EACF,EAMI,SAAU1G,EAAM8G,EAAS,CACrB,OAAO,QAAW,YAAc,OAAO,IAEzC,OAAOA,CAAO,EACL,OAAOpO,IAAY,SAM5BC,GAAO,QAAUmO,EAAQ,EAGzB9G,EAAK,KAAO8G,EAAQ,CAExB,EAAE,KAAM,UAAY,CAMlB,OAAOlO,CACT,CAAC,CACH,GAAG,ICl5GH,IAAAmO,EAAAC,EAAA,CAAAC,GAAAC,KAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,GAeA,IAAIC,GAAkB,UAOtBD,GAAO,QAAUE,GAUjB,SAASA,GAAWC,EAAQ,CAC1B,IAAIC,EAAM,GAAKD,EACXE,EAAQJ,GAAgB,KAAKG,CAAG,EAEpC,GAAI,CAACC,EACH,OAAOD,EAGT,IAAIE,EACAC,EAAO,GACPC,EAAQ,EACRC,EAAY,EAEhB,IAAKD,EAAQH,EAAM,MAAOG,EAAQJ,EAAI,OAAQI,IAAS,CACrD,OAAQJ,EAAI,WAAWI,CAAK,EAAG,CAC7B,IAAK,IACHF,EAAS,SACT,MACF,IAAK,IACHA,EAAS,QACT,MACF,IAAK,IACHA,EAAS,QACT,MACF,IAAK,IACHA,EAAS,OACT,MACF,IAAK,IACHA,EAAS,OACT,MACF,QACE,QACJ,CAEIG,IAAcD,IAChBD,GAAQH,EAAI,UAAUK,EAAWD,CAAK,GAGxCC,EAAYD,EAAQ,EACpBD,GAAQD,CACV,CAEA,OAAOG,IAAcD,EACjBD,EAAOH,EAAI,UAAUK,EAAWD,CAAK,EACrCD,CACN,ICvDA,IAAAG,GAAiB,QCKZ,OAAO,UACV,OAAO,QAAU,SAAUC,EAAa,CACtC,IAAMC,EAA2B,CAAC,EAClC,QAAWC,KAAO,OAAO,KAAKF,CAAG,EAE/BC,EAAK,KAAK,CAACC,EAAKF,EAAIE,EAAI,CAAC,EAG3B,OAAOD,CACT,GAGG,OAAO,SACV,OAAO,OAAS,SAAUD,EAAa,CACrC,IAAMC,EAAiB,CAAC,EACxB,QAAWC,KAAO,OAAO,KAAKF,CAAG,EAE/BC,EAAK,KAAKD,EAAIE,EAAI,EAGpB,OAAOD,CACT,GAKE,OAAO,SAAY,cAGhB,QAAQ,UAAU,WACrB,QAAQ,UAAU,SAAW,SAC3BE,EAA8BC,EACxB,CACF,OAAOD,GAAM,UACf,KAAK,WAAaA,EAAE,KACpB,KAAK,UAAYA,EAAE,MAEnB,KAAK,WAAaA,EAClB,KAAK,UAAYC,EAErB,GAGG,QAAQ,UAAU,cACrB,QAAQ,UAAU,YAAc,YAC3BC,EACG,CACN,IAAMC,EAAS,KAAK,WACpB,GAAIA,EAAQ,CACND,EAAM,SAAW,GACnBC,EAAO,YAAY,IAAI,EAGzB,QAASC,EAAIF,EAAM,OAAS,EAAGE,GAAK,EAAGA,IAAK,CAC1C,IAAIC,EAAOH,EAAME,GACb,OAAOC,GAAS,SAClBA,EAAO,SAAS,eAAeA,CAAI,EAC5BA,EAAK,YACZA,EAAK,WAAW,YAAYA,CAAI,EAG7BD,EAGHD,EAAO,aAAa,KAAK,gBAAkBE,CAAI,EAF/CF,EAAO,aAAaE,EAAM,IAAI,CAGlC,CACF,CACF,ICxEJ,IAAAC,GAAuB,OAiChB,SAASC,GACdC,EACmB,CACnB,IAAMC,EAAY,IAAI,IAChBC,EAAY,IAAI,IACtB,QAAWC,KAAOH,EAAM,CACtB,GAAM,CAACI,EAAMC,CAAI,EAAIF,EAAI,SAAS,MAAM,GAAG,EAGrCG,EAAWH,EAAI,SACfI,EAAWJ,EAAI,MACfK,EAAWL,EAAI,KAGfM,KAAO,GAAAC,SAAWP,EAAI,IAAI,EAC7B,QAAQ,mBAAoB,EAAE,EAC9B,QAAQ,OAAQ,GAAG,EAGtB,GAAIE,EAAM,CACR,IAAMM,EAASV,EAAU,IAAIG,CAAI,EAG5BF,EAAQ,IAAIS,CAAM,EASrBV,EAAU,IAAIK,EAAU,CACtB,SAAAA,EACA,MAAAC,EACA,KAAAE,EACA,OAAAE,CACF,CAAC,GAbDA,EAAO,MAAQR,EAAI,MACnBQ,EAAO,KAAQF,EAGfP,EAAQ,IAAIS,CAAM,EAatB,MACEV,EAAU,IAAIK,EAAUM,EAAA,CACtB,SAAAN,EACA,MAAAC,EACA,KAAAE,GACGD,GAAQ,CAAE,KAAAA,CAAK,EACnB,CAEL,CACA,OAAOP,CACT,CCpFA,IAAAY,GAAuB,OAsChB,SAASC,GACdC,EAA2BC,EACD,CAC1B,IAAMC,EAAY,IAAI,OAAOF,EAAO,UAAW,KAAK,EAC9CG,EAAY,CAACC,EAAYC,EAAcC,IACpC,GAAGD,4BAA+BC,WAI3C,OAAQC,GAAkB,CACxBA,EAAQA,EACL,QAAQ,gBAAiB,GAAG,EAC5B,KAAK,EAGR,IAAMC,EAAQ,IAAI,OAAO,MAAMR,EAAO,cACpCO,EACG,QAAQ,uBAAwB,MAAM,EACtC,QAAQL,EAAW,GAAG,KACtB,KAAK,EAGV,OAAOO,IACLR,KACI,GAAAS,SAAWD,CAAK,EAChBA,GAED,QAAQD,EAAOL,CAAS,EACxB,QAAQ,8BAA+B,IAAI,CAClD,CACF,CCtCO,SAASQ,GACdC,EACqB,CACrB,IAAMC,EAAS,IAAK,KAAa,MAAM,CAAC,QAAS,MAAM,CAAC,EAIxD,OAHe,IAAK,KAAa,YAAYD,EAAOC,CAAK,EAGlD,MAAM,EACNA,EAAM,OACf,CAUO,SAASC,GACdD,EAA4BE,EACV,CAzEpB,IAAAC,EA0EE,IAAMC,EAAU,IAAI,IAAuBJ,CAAK,EAG1CK,EAA2B,CAAC,EAClC,QAASC,EAAI,EAAGA,EAAIJ,EAAM,OAAQI,IAChC,QAAWC,KAAUH,EACfF,EAAMI,GAAG,WAAWC,EAAO,IAAI,IACjCF,EAAOE,EAAO,MAAQ,GACtBH,EAAQ,OAAOG,CAAM,GAI3B,QAAWA,KAAUH,GACfD,EAAA,KAAK,iBAAL,MAAAA,EAAA,UAAsBI,EAAO,QAC/BF,EAAOE,EAAO,MAAQ,IAG1B,OAAOF,CACT,CC2BA,SAASG,GAAWC,EAAaC,EAAuB,CACtD,GAAM,CAACC,EAAGC,CAAC,EAAI,CAAC,IAAI,IAAIH,CAAC,EAAG,IAAI,IAAIC,CAAC,CAAC,EACtC,MAAO,CACL,GAAG,IAAI,IAAI,CAAC,GAAGC,CAAC,EAAE,OAAOE,GAAS,CAACD,EAAE,IAAIC,CAAK,CAAC,CAAC,CAClD,CACF,CASO,IAAMC,EAAN,KAAa,CAgCX,YAAY,CAAE,OAAAC,EAAQ,KAAAC,EAAM,QAAAC,CAAQ,EAAgB,CACzD,KAAK,QAAUA,EAGf,KAAK,UAAYC,GAAuBF,CAAI,EAC5C,KAAK,UAAYG,GAAuBJ,EAAQ,EAAK,EAGrD,KAAK,UAAU,UAAY,IAAI,OAAOA,EAAO,SAAS,EAGtD,KAAK,MAAQ,KAAK,UAAY,CAGxBA,EAAO,KAAK,SAAW,GAAKA,EAAO,KAAK,KAAO,KACjD,KAAK,IAAK,KAAaA,EAAO,KAAK,GAAG,EAC7BA,EAAO,KAAK,OAAS,GAC9B,KAAK,IAAK,KAAa,cAAc,GAAGA,EAAO,IAAI,CAAC,EAItD,IAAMK,EAAMZ,GAAW,CACrB,UAAW,iBAAkB,SAC/B,EAAGS,EAAQ,QAAQ,EAGnB,QAAWI,KAAQN,EAAO,KAAK,IAAIO,GACjCA,IAAa,KAAO,KAAQ,KAAaA,EAC1C,EACC,QAAWC,KAAMH,EACf,KAAK,SAAS,OAAOC,EAAKE,EAAG,EAC7B,KAAK,eAAe,OAAOF,EAAKE,EAAG,EAKvC,KAAK,IAAI,UAAU,EAGnB,KAAK,MAAM,QAAS,CAAE,MAAO,GAAI,CAAC,EAClC,KAAK,MAAM,MAAM,EACjB,KAAK,MAAM,OAAQ,CAAE,MAAO,IAAK,UAAWC,GAAO,CACjD,GAAM,CAAE,KAAAC,EAAO,CAAC,CAAE,EAAID,EACtB,OAAOC,EAAK,OAAO,CAACC,EAAMC,IAAQ,CAChC,GAAGD,EACH,GAAG,KAAK,UAAUC,CAAG,CACvB,EAAG,CAAC,CAAiB,CACvB,CAAE,CAAC,EAGH,QAAWH,KAAOR,EAChB,KAAK,IAAIQ,EAAK,CAAE,MAAOA,EAAI,KAAM,CAAC,CACtC,CAAC,CACH,CAkBO,OAAOI,EAA6B,CACzC,GAAIA,EACF,GAAI,CACF,IAAMC,EAAY,KAAK,UAAUD,CAAK,EAGhCE,EAAUC,GAAiBH,CAAK,EACnC,OAAOI,GACNA,EAAO,WAAa,KAAK,MAAM,SAAS,UACzC,EAGGC,EAAS,KAAK,MAAM,OAAO,GAAGL,IAAQ,EAGzC,OAAyB,CAACM,EAAM,CAAE,IAAAC,EAAK,MAAAC,EAAO,UAAAC,CAAU,IAAM,CAC7D,IAAMC,EAAW,KAAK,UAAU,IAAIH,CAAG,EACvC,GAAI,OAAOG,GAAa,YAAa,CACnC,GAAM,CAAE,SAAAC,EAAU,MAAAC,EAAO,KAAAC,EAAM,KAAAhB,EAAM,OAAAiB,CAAO,EAAIJ,EAG1CK,EAAQC,GACZd,EACA,OAAO,KAAKO,EAAU,QAAQ,CAChC,EAGMQ,EAAQ,CAAC,CAACH,GAAS,CAAC,OAAO,OAAOC,CAAK,EAAE,MAAMG,GAAKA,CAAC,EAC3DZ,EAAK,KAAKa,EAAAC,EAAA,CACR,SAAAT,EACA,MAAOV,EAAUW,CAAK,EACtB,KAAOX,EAAUY,CAAI,GAClBhB,GAAQ,CAAE,KAAMA,EAAK,IAAII,CAAS,CAAE,GAJ/B,CAKR,MAAOO,GAAS,EAAIS,GACpB,MAAAF,CACF,EAAC,CACH,CACA,OAAOT,CACT,EAAG,CAAC,CAAC,EAGJ,KAAK,CAACzB,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EAGhC,OAAO,CAACwC,EAAOC,IAAW,CACzB,IAAMZ,EAAW,KAAK,UAAU,IAAIY,EAAO,QAAQ,EACnD,GAAI,OAAOZ,GAAa,YAAa,CACnC,IAAMH,EAAM,WAAYG,EACpBA,EAAS,OAAQ,SACjBA,EAAS,SACbW,EAAM,IAAId,EAAK,CAAC,GAAGc,EAAM,IAAId,CAAG,GAAK,CAAC,EAAGe,CAAM,CAAC,CAClD,CACA,OAAOD,CACT,EAAG,IAAI,GAA+B,EAGpCE,EACJ,GAAI,KAAK,QAAQ,YAAa,CAC5B,IAAMC,EAAS,KAAK,MAAM,MAAMC,GAAW,CACzC,QAAWrB,KAAUF,EACnBuB,EAAQ,KAAKrB,EAAO,KAAM,CACxB,OAAQ,CAAC,OAAO,EAChB,SAAU,KAAK,MAAM,SAAS,SAC9B,SAAU,KAAK,MAAM,SAAS,QAChC,CAAC,CACL,CAAC,EAGDmB,EAAcC,EAAO,OACjB,OAAO,KAAKA,EAAO,GAAG,UAAU,QAAQ,EACxC,CAAC,CACP,CAGA,OAAOJ,EAAA,CACL,MAAO,CAAC,GAAGf,EAAO,OAAO,CAAC,GACvB,OAAOkB,GAAgB,aAAe,CAAE,YAAAA,CAAY,EAI3D,OAAQG,EAAN,CACA,QAAQ,KAAK,kBAAkB1B,qCAAoC,CACrE,CAIF,MAAO,CAAE,MAAO,CAAC,CAAE,CACrB,CACF,EL3QA,IAAI2B,EAqBJ,SAAeC,GACbC,EACe,QAAAC,EAAA,sBACf,IAAIC,EAAO,UAGX,GAAI,OAAO,QAAW,aAAe,iBAAkB,OAAQ,CAC7D,IAAMC,EAAS,SAAS,cAAiC,aAAa,EAChE,CAACC,CAAI,EAAID,EAAO,IAAI,MAAM,SAAS,EAGzCD,EAAOA,EAAK,QAAQ,KAAME,CAAI,CAChC,CAGA,IAAMC,EAAU,CAAC,EACjB,QAAWC,KAAQN,EAAO,KAAM,CAC9B,OAAQM,EAAM,CAGZ,IAAK,KACHD,EAAQ,KAAK,GAAGH,cAAiB,EACjC,MAGF,IAAK,KACL,IAAK,KACHG,EAAQ,KAAK,GAAGH,cAAiB,EACjC,KACJ,CAGII,IAAS,MACXD,EAAQ,KAAK,GAAGH,cAAiBI,UAAa,CAClD,CAGIN,EAAO,KAAK,OAAS,GACvBK,EAAQ,KAAK,GAAGH,yBAA4B,EAG1CG,EAAQ,SACV,MAAM,cACJ,GAAGH,oCACH,GAAGG,CACL,EACJ,GAaA,SAAsBE,GACpBC,EACwB,QAAAP,EAAA,sBACxB,OAAQO,EAAQ,KAAM,CAGpB,OACE,aAAMT,GAAqBS,EAAQ,KAAK,MAAM,EAC9CV,EAAQ,IAAIW,EAAOD,EAAQ,IAAI,EACxB,CACL,MACF,EAGF,OACE,MAAO,CACL,OACA,KAAMV,EAAQA,EAAM,OAAOU,EAAQ,IAAI,EAAI,CAAE,MAAO,CAAC,CAAE,CACzD,EAGF,QACE,MAAM,IAAI,UAAU,sBAAsB,CAC9C,CACF,GAOA,KAAK,KAAO,GAAAE,QAGZ,iBAAiB,UAAiBC,GAAMV,EAAA,wBACtC,YAAY,MAAMM,GAAQI,EAAG,IAAI,CAAC,CACpC,EAAC",
+  "names": ["require_lunr", "__commonJSMin", "exports", "module", "lunr", "config", "builder", "global", "message", "obj", "clone", "keys", "key", "val", "docRef", "fieldName", "stringValue", "s", "n", "fieldRef", "elements", "i", "other", "object", "a", "b", "intersection", "element", "posting", "documentCount", "documentsWithTerm", "x", "str", "metadata", "fn", "t", "len", "tokens", "sliceEnd", "sliceStart", "char", "sliceLength", "tokenMetadata", "label", "isRegistered", "serialised", "pipeline", "fnName", "fns", "existingFn", "newFn", "pos", "stackLength", "memo", "j", "result", "k", "token", "index", "start", "end", "pivotPoint", "pivotIndex", "insertIdx", "position", "sumOfSquares", "elementsLength", "otherVector", "dotProduct", "aLen", "bLen", "aVal", "bVal", "output", "step2list", "step3list", "c", "v", "C", "V", "mgr0", "meq1", "mgr1", "s_v", "re_mgr0", "re_mgr1", "re_meq1", "re_s_v", "re_1a", "re2_1a", "re_1b", "re2_1b", "re_1b_2", "re2_1b_2", "re3_1b_2", "re4_1b_2", "re_1c", "re_2", "re_3", "re_4", "re2_4", "re_5", "re_5_1", "re3_5", "porterStemmer", "w", "stem", "suffix", "firstch", "re", "re2", "re3", "re4", "fp", "stopWords", "words", "stopWord", "arr", "clause", "editDistance", "root", "stack", "frame", "noEditNode", "insertionNode", "substitutionNode", "charA", "charB", "transposeNode", "node", "final", "next", "edges", "edge", "labels", "qEdges", "qLen", "nEdges", "nLen", "q", "qEdge", "nEdge", "qNode", "word", "commonPrefix", "nextNode", "downTo", "childKey", "attrs", "queryString", "query", "parser", "matchingFields", "queryVectors", "termFieldCache", "requiredMatches", "prohibitedMatches", "terms", "clauseMatches", "m", "term", "termTokenSet", "expandedTerms", "field", "expandedTerm", "termIndex", "fieldPosting", "matchingDocumentRefs", "termField", "matchingDocumentsSet", "l", "matchingDocumentRef", "matchingFieldRef", "fieldMatch", "allRequiredMatches", "allProhibitedMatches", "matchingFieldRefs", "results", "matches", "fieldVector", "score", "docMatch", "match", "invertedIndex", "fieldVectors", "ref", "serializedIndex", "serializedVectors", "serializedInvertedIndex", "tokenSetBuilder", "tuple", "attributes", "number", "doc", "fields", "extractor", "fieldTerms", "metadataKey", "fieldRefs", "numberOfFields", "accumulator", "documentsWithField", "fieldRefsLength", "termIdfCache", "fieldLength", "termFrequencies", "termsLength", "fieldBoost", "docBoost", "tf", "idf", "scoreWithPrecision", "args", "clonedMetadata", "metadataKeys", "otherMatchData", "allFields", "options", "state", "subSlices", "type", "charCode", "lexer", "lexeme", "completedClause", "errorMessage", "nextLexeme", "possibleFields", "f", "boost", "factory", "require_escape_html", "__commonJSMin", "exports", "module", "matchHtmlRegExp", "escapeHtml", "string", "str", "match", "escape", "html", "index", "lastIndex", "import_lunr", "obj", "data", "key", "x", "y", "nodes", "parent", "i", "node", "import_escape_html", "setupSearchDocumentMap", "docs", "documents", "parents", "doc", "path", "hash", "location", "title", "tags", "text", "escapeHTML", "parent", "__spreadValues", "import_escape_html", "setupSearchHighlighter", "config", "escape", "separator", "highlight", "_", "data", "term", "query", "match", "value", "escapeHTML", "parseSearchQuery", "value", "query", "getSearchQueryTerms", "terms", "_a", "clauses", "result", "t", "clause", "difference", "a", "b", "x", "y", "value", "Search", "config", "docs", "options", "setupSearchDocumentMap", "setupSearchHighlighter", "fns", "lang", "language", "fn", "doc", "tags", "list", "tag", "query", "highlight", "clauses", "parseSearchQuery", "clause", "groups", "item", "ref", "score", "matchData", "document", "location", "title", "text", "parent", "terms", "getSearchQueryTerms", "boost", "t", "__spreadProps", "__spreadValues", "items", "result", "suggestions", "titles", "builder", "e", "index", "setupSearchLanguages", "config", "__async", "base", "worker", "path", "scripts", "lang", "handler", "message", "Search", "lunr", "ev"]
 }
diff --git a/7.3/assets/stylesheets/extra.0d2c79a8.min.css b/7.3/assets/stylesheets/extra.0d2c79a8.min.css
new file mode 100644
index 0000000000..6e23ef17d0
--- /dev/null
+++ b/7.3/assets/stylesheets/extra.0d2c79a8.min.css
@@ -0,0 +1 @@
+@charset "UTF-8";@keyframes ᴴₒᴴₒᴴₒ{0%{transform:translate3d(var(--left-start),0,0)}to{transform:translate3d(var(--left-end),110vh,0)}}.ᴴₒᴴₒᴴₒ{--size:1vw;background:#fff;border:1px solid #ddd;border-radius:50%;cursor:pointer;height:var(--size);opacity:1;position:fixed;top:-5vh;transition:opacity 1s;width:var(--size);z-index:10}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):first-child{--size:0.4vw;--left-start:7vw;--left-end:-8vw;animation:ᴴₒᴴₒᴴₒ 12s linear infinite both;animation-delay:-4s;left:24vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(2){--size:0.4vw;--left-start:9vw;--left-end:0vw;animation:ᴴₒᴴₒᴴₒ 18s linear infinite both;animation-delay:-2s;left:68vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(3){--size:0.4vw;--left-start:1vw;--left-end:7vw;animation:ᴴₒᴴₒᴴₒ 11s linear infinite both;animation-delay:-6s;left:10vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(4){--size:0.5vw;--left-start:8vw;--left-end:10vw;animation:ᴴₒᴴₒᴴₒ 18s linear infinite both;animation-delay:-8s;left:63vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(5){--size:0.5vw;--left-start:5vw;--left-end:9vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-4s;left:58vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(6){--size:0.1vw;--left-start:3vw;--left-end:10vw;animation:ᴴₒᴴₒᴴₒ 14s linear infinite both;animation-delay:-1s;left:55vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(7){--size:0.2vw;--left-start:-2vw;--left-end:6vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-7s;left:50vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(8){--size:0.3vw;--left-start:7vw;--left-end:7vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-3s;left:65vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(9){--size:0.2vw;--left-start:4vw;--left-end:5vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-2s;left:1vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(10){--size:0.3vw;--left-start:2vw;--left-end:-3vw;animation:ᴴₒᴴₒᴴₒ 12s linear infinite both;animation-delay:-10s;left:92vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(11){--size:0.2vw;--left-start:1vw;--left-end:8vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-6s;left:5vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(12){--size:0.4vw;--left-start:9vw;--left-end:1vw;animation:ᴴₒᴴₒᴴₒ 18s linear infinite both;animation-delay:-3s;left:77vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(13){--size:0.1vw;--left-start:-3vw;--left-end:3vw;animation:ᴴₒᴴₒᴴₒ 18s linear infinite both;animation-delay:-7s;left:93vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(14){--size:0.5vw;--left-start:0vw;--left-end:-5vw;animation:ᴴₒᴴₒᴴₒ 12s linear infinite both;animation-delay:-4s;left:35vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(15){--size:0.1vw;--left-start:-9vw;--left-end:4vw;animation:ᴴₒᴴₒᴴₒ 20s linear infinite both;animation-delay:-6s;left:15vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(16){--size:0.1vw;--left-start:1vw;--left-end:9vw;animation:ᴴₒᴴₒᴴₒ 17s linear infinite both;animation-delay:-6s;left:100vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(17){--size:0.1vw;--left-start:1vw;--left-end:0vw;animation:ᴴₒᴴₒᴴₒ 17s linear infinite both;animation-delay:-1s;left:44vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(18){--size:0.4vw;--left-start:-9vw;--left-end:-9vw;animation:ᴴₒᴴₒᴴₒ 16s linear infinite both;animation-delay:-6s;left:69vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(19){--size:0.2vw;--left-start:3vw;--left-end:-8vw;animation:ᴴₒᴴₒᴴₒ 14s linear infinite both;animation-delay:-1s;left:32vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(20){--size:0.1vw;--left-start:-7vw;--left-end:8vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-8s;left:59vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(21){--size:0.2vw;--left-start:-1vw;--left-end:-8vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-6s;left:96vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(22){--size:0.2vw;--left-start:9vw;--left-end:1vw;animation:ᴴₒᴴₒᴴₒ 11s linear infinite both;animation-delay:-7s;left:78vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(23){--size:0.4vw;--left-start:5vw;--left-end:-2vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-10s;left:29vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(24){--size:0.1vw;--left-start:-4vw;--left-end:1vw;animation:ᴴₒᴴₒᴴₒ 20s linear infinite both;animation-delay:-7s;left:83vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(25){--size:0.3vw;--left-start:-1vw;--left-end:2vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-8s;left:95vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(26){--size:0.5vw;--left-start:-3vw;--left-end:-6vw;animation:ᴴₒᴴₒᴴₒ 18s linear infinite both;animation-delay:-8s;left:74vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(27){--size:0.5vw;--left-start:9vw;--left-end:-9vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-2s;left:94vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(28){--size:0.1vw;--left-start:0vw;--left-end:-4vw;animation:ᴴₒᴴₒᴴₒ 15s linear infinite both;animation-delay:-4s;left:95vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(29){--size:0.5vw;--left-start:8vw;--left-end:4vw;animation:ᴴₒᴴₒᴴₒ 11s linear infinite both;animation-delay:-3s;left:42vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(30){--size:0.4vw;--left-start:-5vw;--left-end:0vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-10s;left:8vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(31){--size:0.4vw;--left-start:-7vw;--left-end:3vw;animation:ᴴₒᴴₒᴴₒ 11s linear infinite both;animation-delay:-4s;left:77vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(32){--size:0.4vw;--left-start:8vw;--left-end:-5vw;animation:ᴴₒᴴₒᴴₒ 15s linear infinite both;animation-delay:-3s;left:80vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(33){--size:0.2vw;--left-start:-3vw;--left-end:8vw;animation:ᴴₒᴴₒᴴₒ 20s linear infinite both;animation-delay:-6s;left:15vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(34){--size:0.5vw;--left-start:5vw;--left-end:1vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-1s;left:91vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(35){--size:0.3vw;--left-start:-6vw;--left-end:-5vw;animation:ᴴₒᴴₒᴴₒ 11s linear infinite both;animation-delay:-5s;left:93vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(36){--size:0.1vw;--left-start:10vw;--left-end:10vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-10s;left:59vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(37){--size:0.3vw;--left-start:4vw;--left-end:6vw;animation:ᴴₒᴴₒᴴₒ 14s linear infinite both;animation-delay:-8s;left:35vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(38){--size:0.5vw;--left-start:8vw;--left-end:-3vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-6s;left:6vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(39){--size:0.2vw;--left-start:-6vw;--left-end:-2vw;animation:ᴴₒᴴₒᴴₒ 14s linear infinite both;animation-delay:-7s;left:58vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(40){--size:0.4vw;--left-start:3vw;--left-end:-5vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-4s;left:15vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(41){--size:0.1vw;--left-start:2vw;--left-end:-7vw;animation:ᴴₒᴴₒᴴₒ 17s linear infinite both;animation-delay:-7s;left:24vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(42){--size:0.3vw;--left-start:8vw;--left-end:3vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-9s;left:36vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(43){--size:0.2vw;--left-start:-9vw;--left-end:-3vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-10s;left:23vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(44){--size:0.1vw;--left-start:4vw;--left-end:-6vw;animation:ᴴₒᴴₒᴴₒ 16s linear infinite both;animation-delay:-6s;left:9vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(45){--size:0.1vw;--left-start:-3vw;--left-end:-5vw;animation:ᴴₒᴴₒᴴₒ 19s linear infinite both;animation-delay:-5s;left:62vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(46){--size:0.3vw;--left-start:0vw;--left-end:2vw;animation:ᴴₒᴴₒᴴₒ 20s linear infinite both;animation-delay:-4s;left:1vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(47){--size:0.4vw;--left-start:8vw;--left-end:-4vw;animation:ᴴₒᴴₒᴴₒ 14s linear infinite both;animation-delay:-1s;left:76vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(48){--size:0.2vw;--left-start:5vw;--left-end:-3vw;animation:ᴴₒᴴₒᴴₒ 15s linear infinite both;animation-delay:-5s;left:19vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(49){--size:0.4vw;--left-start:1vw;--left-end:-1vw;animation:ᴴₒᴴₒᴴₒ 18s linear infinite both;animation-delay:-4s;left:72vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(50){--size:0.4vw;--left-start:8vw;--left-end:-6vw;animation:ᴴₒᴴₒᴴₒ 16s linear infinite both;animation-delay:-10s;left:25vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(51){--size:0.1vw;--left-start:-5vw;--left-end:-8vw;animation:ᴴₒᴴₒᴴₒ 17s linear infinite both;animation-delay:-9s;left:71vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(52){--size:0.4vw;--left-start:-4vw;--left-end:9vw;animation:ᴴₒᴴₒᴴₒ 15s linear infinite both;animation-delay:-7s;left:30vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(53){--size:0.5vw;--left-start:-1vw;--left-end:-8vw;animation:ᴴₒᴴₒᴴₒ 15s linear infinite both;animation-delay:-4s;left:37vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(54){--size:0.4vw;--left-start:-1vw;--left-end:-1vw;animation:ᴴₒᴴₒᴴₒ 12s linear infinite both;animation-delay:-9s;left:48vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(55){--size:0.5vw;--left-start:8vw;--left-end:6vw;animation:ᴴₒᴴₒᴴₒ 20s linear infinite both;animation-delay:-6s;left:65vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(56){--size:0.4vw;--left-start:9vw;--left-end:5vw;animation:ᴴₒᴴₒᴴₒ 18s linear infinite both;animation-delay:-6s;left:53vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(57){--size:0.4vw;--left-start:3vw;--left-end:-9vw;animation:ᴴₒᴴₒᴴₒ 12s linear infinite both;animation-delay:-1s;left:76vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(58){--size:0.2vw;--left-start:-7vw;--left-end:0vw;animation:ᴴₒᴴₒᴴₒ 16s linear infinite both;animation-delay:-9s;left:54vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(59){--size:0.1vw;--left-start:-9vw;--left-end:-2vw;animation:ᴴₒᴴₒᴴₒ 20s linear infinite both;animation-delay:-1s;left:66vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(60){--size:0.3vw;--left-start:-6vw;--left-end:2vw;animation:ᴴₒᴴₒᴴₒ 11s linear infinite both;animation-delay:-7s;left:91vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(61){--size:0.4vw;--left-start:6vw;--left-end:-8vw;animation:ᴴₒᴴₒᴴₒ 14s linear infinite both;animation-delay:-7s;left:35vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(62){--size:0.4vw;--left-start:-6vw;--left-end:2vw;animation:ᴴₒᴴₒᴴₒ 16s linear infinite both;animation-delay:-3s;left:86vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(63){--size:0.5vw;--left-start:-7vw;--left-end:7vw;animation:ᴴₒᴴₒᴴₒ 20s linear infinite both;animation-delay:-5s;left:86vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(64){--size:0.2vw;--left-start:-9vw;--left-end:1vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-5s;left:53vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(65){--size:0.2vw;--left-start:-2vw;--left-end:3vw;animation:ᴴₒᴴₒᴴₒ 11s linear infinite both;animation-delay:-6s;left:56vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(66){--size:0.5vw;--left-start:1vw;--left-end:8vw;animation:ᴴₒᴴₒᴴₒ 17s linear infinite both;animation-delay:-5s;left:58vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(67){--size:0.5vw;--left-start:2vw;--left-end:9vw;animation:ᴴₒᴴₒᴴₒ 15s linear infinite both;animation-delay:-5s;left:14vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(68){--size:0.3vw;--left-start:-1vw;--left-end:6vw;animation:ᴴₒᴴₒᴴₒ 14s linear infinite both;animation-delay:-1s;left:100vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(69){--size:0.2vw;--left-start:9vw;--left-end:-2vw;animation:ᴴₒᴴₒᴴₒ 15s linear infinite both;animation-delay:-7s;left:8vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(70){--size:0.4vw;--left-start:-5vw;--left-end:8vw;animation:ᴴₒᴴₒᴴₒ 11s linear infinite both;animation-delay:-4s;left:82vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(71){--size:0.4vw;--left-start:3vw;--left-end:-7vw;animation:ᴴₒᴴₒᴴₒ 13s linear infinite both;animation-delay:-6s;left:26vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(72){--size:0.2vw;--left-start:-2vw;--left-end:-3vw;animation:ᴴₒᴴₒᴴₒ 15s linear infinite both;animation-delay:-3s;left:24vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(73){--size:0.3vw;--left-start:-7vw;--left-end:-8vw;animation:ᴴₒᴴₒᴴₒ 16s linear infinite both;animation-delay:-2s;left:2vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(74){--size:0.4vw;--left-start:-9vw;--left-end:-3vw;animation:ᴴₒᴴₒᴴₒ 14s linear infinite both;animation-delay:-10s;left:94vw}.ᴴₒᴴₒᴴₒ:not(.ᴴₒᴴₒᴴₒ--gotcha):nth-child(75){--size:0.3vw;--left-start:7vw;--left-end:2vw;animation:ᴴₒᴴₒᴴₒ 17s linear infinite both;animation-delay:-2s;left:26vw}.ᴴₒᴴₒᴴₒ:nth-child(5n){filter:blur(2px)}.ᴴₒᴴₒᴴₒ--ᵍₒᵗ꜀ᴴₐ{opacity:0}.ᴴₒᴴₒᴴₒ__button{display:block}.ᴴₒᴴₒᴴₒ__button:after{background-color:currentcolor;content:"";display:block;height:24px;margin:0 auto;-webkit-mask-image:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m20.79 13.95-2.33.62-2-1.13v-2.88l2-1.13 2.33.62.52-1.93-1.77-.47.46-1.77-1.93-.52-.62 2.33-2 1.13L13 7.38V5.12l1.71-1.71L13.29 2 12 3.29 10.71 2 9.29 3.41 11 5.12v2.26L8.5 8.82l-2-1.13-.58-2.33L4 5.88l.47 1.77-1.77.47.52 1.93 2.33-.62 2 1.13v2.89l-2 1.13-2.33-.62-.52 1.93 1.77.47L4 18.12l1.93.52.62-2.33 2-1.13L11 16.62v2.26l-1.71 1.71L10.71 22 12 20.71 13.29 22l1.41-1.41-1.7-1.71v-2.26l2.5-1.45 2 1.13.62 2.33 1.88-.51-.47-1.77 1.77-.47-.51-1.93M9.5 10.56 12 9.11l2.5 1.45v2.88L12 14.89l-2.5-1.45v-2.88Z"/></svg>');mask-image:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m20.79 13.95-2.33.62-2-1.13v-2.88l2-1.13 2.33.62.52-1.93-1.77-.47.46-1.77-1.93-.52-.62 2.33-2 1.13L13 7.38V5.12l1.71-1.71L13.29 2 12 3.29 10.71 2 9.29 3.41 11 5.12v2.26L8.5 8.82l-2-1.13-.58-2.33L4 5.88l.47 1.77-1.77.47.52 1.93 2.33-.62 2 1.13v2.89l-2 1.13-2.33-.62-.52 1.93 1.77.47L4 18.12l1.93.52.62-2.33 2-1.13L11 16.62v2.26l-1.71 1.71L10.71 22 12 20.71 13.29 22l1.41-1.41-1.7-1.71v-2.26l2.5-1.45 2 1.13.62 2.33 1.88-.51-.47-1.77 1.77-.47-.51-1.93M9.5 10.56 12 9.11l2.5 1.45v2.88L12 14.89l-2.5-1.45v-2.88Z"/></svg>');-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:24px}.ᴴₒᴴₒᴴₒ__button[hidden]:after{-webkit-mask-image:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M11 5.12 9.29 3.41 10.71 2 12 3.29 13.29 2l1.42 1.41L13 5.12v2.26l2.45 1.44 2-1.13.62-2.33 1.93.52-.46 1.77 1.77.47-.52 1.93-2.33-.62-2 1.13v2.7L14.5 11.3v-.74l-1.76-1.02-2.01-2.01.27-.15V5.12m7.46 9.45-1.59-.9 2.68 2.68 1.75-.47-.51-1.93-2.33.62M13 16.62v2.26l1.7 1.71L13.29 22 12 20.71 10.71 22l-1.42-1.41L11 18.88v-2.26l-2.45-1.44-2 1.13-.62 2.33L4 18.12l.47-1.76-1.77-.47.52-1.93 2.33.62 2-1.13v-2.89l-2-1.13-2.33.62-.52-1.93 1.77-.47L4 5.89 1.11 3l1.28-1.27 19.72 19.73-1.27 1.27L14.1 16l-1.1.62m-1-1.73.63-.39-3.13-3.11v2.05l2.5 1.45Z"/></svg>');mask-image:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M11 5.12 9.29 3.41 10.71 2 12 3.29 13.29 2l1.42 1.41L13 5.12v2.26l2.45 1.44 2-1.13.62-2.33 1.93.52-.46 1.77 1.77.47-.52 1.93-2.33-.62-2 1.13v2.7L14.5 11.3v-.74l-1.76-1.02-2.01-2.01.27-.15V5.12m7.46 9.45-1.59-.9 2.68 2.68 1.75-.47-.51-1.93-2.33.62M13 16.62v2.26l1.7 1.71L13.29 22 12 20.71 10.71 22l-1.42-1.41L11 18.88v-2.26l-2.45-1.44-2 1.13-.62 2.33L4 18.12l.47-1.76-1.77-.47.52-1.93 2.33.62 2-1.13v-2.89l-2-1.13-2.33.62-.52-1.93 1.77-.47L4 5.89 1.11 3l1.28-1.27 19.72 19.73-1.27 1.27L14.1 16l-1.1.62m-1-1.73.63-.39-3.13-3.11v2.05l2.5 1.45Z"/></svg>')}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/extra.0d2c79a8.min.css.map b/7.3/assets/stylesheets/extra.0d2c79a8.min.css.map
new file mode 100644
index 0000000000..cd262c03a0
--- /dev/null
+++ b/7.3/assets/stylesheets/extra.0d2c79a8.min.css.map
@@ -0,0 +1 @@
+{"version":3,"sources":["src/assets/stylesheets/extra.scss","../../../src/assets/stylesheets/extra.scss"],"names":[],"mappings":"AA6BA,gBCpBA,CDoBA,kBACE,GACE,4CC1BF,CD4BA,GACE,8CC1BF,CACF,CDkCA,QACE,UAAA,CAOA,eAAA,CACA,qBAAA,CACA,iBAAA,CACA,cAAA,CAJA,kBAAA,CAMA,SAAA,CAVA,cAAA,CACA,QAAA,CAQA,qBAAA,CANA,iBAAA,CADA,UCzBF,CDqCI,yCACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SClCN,CD6BI,0CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC1BN,CDqBI,0CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SClBN,CDaI,0CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCVN,CDKI,0CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCFN,CDHI,0CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCMN,CDXI,0CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCcN,CDnBI,0CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsBN,CD3BI,0CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,QC8BN,CDnCI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,oBAAA,CAFA,SCsCN,CD3CI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,QC8CN,CDnDI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsDN,CD3DI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8DN,CDnEI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsEN,CD3EI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8EN,CDnFI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,UCsFN,CD3FI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8FN,CDnGI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsGN,CD3GI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8GN,CDnHI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsHN,CD3HI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8HN,CDnII,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsIN,CD3II,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,oBAAA,CAFA,SC8IN,CDnJI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsJN,CD3JI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8JN,CDnKI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsKN,CD3KI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8KN,CDnLI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsLN,CD3LI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8LN,CDnMI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,oBAAA,CAFA,QCsMN,CD3MI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8MN,CDnNI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsNN,CD3NI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8NN,CDnOI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsON,CD3OI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8ON,CDnPI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,oBAAA,CAFA,SCsPN,CD3PI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8PN,CDnQI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,QCsQN,CD3QI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8QN,CDnRI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsRN,CD3RI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8RN,CDnSI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsSN,CD3SI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,oBAAA,CAFA,SC8SN,CDnTI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,QCsTN,CD3TI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8TN,CDnUI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,QCsUN,CD3UI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8UN,CDnVI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsVN,CD3VI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8VN,CDnWI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,oBAAA,CAFA,SCsWN,CD3WI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8WN,CDnXI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsXN,CD3XI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8XN,CDnYI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsYN,CD3YI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8YN,CDnZI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsZN,CD3ZI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8ZN,CDnaI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsaN,CD3aI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8aN,CDnbI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsbN,CD3bI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8bN,CDncI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCscN,CD3cI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8cN,CDndI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsdN,CD3dI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8dN,CDneI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCseN,CD3eI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8eN,CDnfI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,UCsfN,CD3fI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,QC8fN,CDngBI,2CACE,YAAA,CACA,iBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCsgBN,CD3gBI,2CACE,YAAA,CACA,gBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8gBN,CDnhBI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SCshBN,CD3hBI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,QC8hBN,CDniBI,2CACE,YAAA,CACA,iBAAA,CACA,eAAA,CAGA,yCAAA,CACA,oBAAA,CAFA,SCsiBN,CD3iBI,2CACE,YAAA,CACA,gBAAA,CACA,cAAA,CAGA,yCAAA,CACA,mBAAA,CAFA,SC8iBN,CDviBE,sBACE,gBCyiBJ,CDriBE,gBACE,SCuiBJ,CDniBE,gBACE,aCqiBJ,CDjiBE,sBAKE,6BAAA,CAKA,UAAA,CATA,aAAA,CAEA,WAAA,CACA,aAAA,CAEA,ooBAAA,CAAA,4nBAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CAPA,UC2iBJ,CD/hBE,8BACE,qqBAAA,CAAA,6pBCiiBJ","file":"extra.css"}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/main.975780f9.min.css b/7.3/assets/stylesheets/main.975780f9.min.css
new file mode 100644
index 0000000000..dac48ba77e
--- /dev/null
+++ b/7.3/assets/stylesheets/main.975780f9.min.css
@@ -0,0 +1 @@
+@charset "UTF-8";html{-webkit-text-size-adjust:none;-moz-text-size-adjust:none;text-size-adjust:none;box-sizing:border-box}*,:after,:before{box-sizing:inherit}@media (prefers-reduced-motion){*,:after,:before{transition:none!important}}body{margin:0}a,button,input,label{-webkit-tap-highlight-color:transparent}a{color:inherit;text-decoration:none}hr{border:0;box-sizing:initial;display:block;height:.05rem;overflow:visible;padding:0}small{font-size:80%}sub,sup{line-height:1em}img{border-style:none}table{border-collapse:initial;border-spacing:0}td,th{font-weight:400;vertical-align:top}button{background:#0000;border:0;font-family:inherit;font-size:inherit;margin:0;padding:0}input{border:0;outline:none}:root{--md-primary-fg-color:#4051b5;--md-primary-fg-color--light:#5d6cc0;--md-primary-fg-color--dark:#303fa1;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3;--md-accent-fg-color:#526cfe;--md-accent-fg-color--transparent:#526cfe1a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}:root,[data-md-color-scheme=default]{--md-default-fg-color:#000000de;--md-default-fg-color--light:#0000008a;--md-default-fg-color--lighter:#00000052;--md-default-fg-color--lightest:#00000012;--md-default-bg-color:#fff;--md-default-bg-color--light:#ffffffb3;--md-default-bg-color--lighter:#ffffff4d;--md-default-bg-color--lightest:#ffffff1f;--md-code-fg-color:#36464e;--md-code-bg-color:#f5f5f5;--md-code-hl-color:#ffff0080;--md-code-hl-number-color:#d52a2a;--md-code-hl-special-color:#db1457;--md-code-hl-function-color:#a846b9;--md-code-hl-constant-color:#6e59d9;--md-code-hl-keyword-color:#3f6ec6;--md-code-hl-string-color:#1c7d4d;--md-code-hl-name-color:var(--md-code-fg-color);--md-code-hl-operator-color:var(--md-default-fg-color--light);--md-code-hl-punctuation-color:var(--md-default-fg-color--light);--md-code-hl-comment-color:var(--md-default-fg-color--light);--md-code-hl-generic-color:var(--md-default-fg-color--light);--md-code-hl-variable-color:var(--md-default-fg-color--light);--md-typeset-color:var(--md-default-fg-color);--md-typeset-a-color:var(--md-primary-fg-color);--md-typeset-mark-color:#ffff0080;--md-typeset-del-color:#f5503d26;--md-typeset-ins-color:#0bd57026;--md-typeset-kbd-color:#fafafa;--md-typeset-kbd-accent-color:#fff;--md-typeset-kbd-border-color:#b8b8b8;--md-typeset-table-color:#0000001f;--md-admonition-fg-color:var(--md-default-fg-color);--md-admonition-bg-color:var(--md-default-bg-color);--md-footer-fg-color:#fff;--md-footer-fg-color--light:#ffffffb3;--md-footer-fg-color--lighter:#ffffff4d;--md-footer-bg-color:#000000de;--md-footer-bg-color--dark:#00000052;--md-shadow-z1:0 0.2rem 0.5rem #0000000d,0 0 0.05rem #0000001a;--md-shadow-z2:0 0.2rem 0.5rem #0000001a,0 0 0.05rem #00000040;--md-shadow-z3:0 0.2rem 0.5rem #0003,0 0 0.05rem #00000059}.md-icon svg{fill:currentcolor;display:block;height:1.2rem;width:1.2rem}body{-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale;--md-text-font-family:var(--md-text-font,_),-apple-system,BlinkMacSystemFont,Helvetica,Arial,sans-serif;--md-code-font-family:var(--md-code-font,_),SFMono-Regular,Consolas,Menlo,monospace}body,input{font-feature-settings:"kern","liga";font-family:var(--md-text-font-family)}body,code,input,kbd,pre{color:var(--md-typeset-color)}code,kbd,pre{font-feature-settings:"kern";font-family:var(--md-code-font-family)}:root{--md-typeset-table-sort-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m18 21-4-4h3V7h-3l4-4 4 4h-3v10h3M2 19v-2h10v2M2 13v-2h7v2M2 7V5h4v2H2Z"/></svg>');--md-typeset-table-sort-icon--asc:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 17h3l-4 4-4-4h3V3h2M2 17h10v2H2M6 5v2H2V5m0 6h7v2H2v-2Z"/></svg>');--md-typeset-table-sort-icon--desc:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 7h3l-4-4-4 4h3v14h2M2 17h10v2H2M6 5v2H2V5m0 6h7v2H2v-2Z"/></svg>')}.md-typeset{-webkit-print-color-adjust:exact;color-adjust:exact;font-size:.8rem;line-height:1.6}@media print{.md-typeset{font-size:.68rem}}.md-typeset blockquote,.md-typeset dl,.md-typeset figure,.md-typeset ol,.md-typeset pre,.md-typeset ul{margin-bottom:1em;margin-top:1em}.md-typeset h1{color:var(--md-default-fg-color--light);font-size:2em;line-height:1.3;margin:0 0 1.25em}.md-typeset h1,.md-typeset h2{font-weight:300;letter-spacing:-.01em}.md-typeset h2{font-size:1.5625em;line-height:1.4;margin:1.6em 0 .64em}.md-typeset h3{font-size:1.25em;font-weight:400;letter-spacing:-.01em;line-height:1.5;margin:1.6em 0 .8em}.md-typeset h2+h3{margin-top:.8em}.md-typeset h4{font-weight:700;letter-spacing:-.01em;margin:1em 0}.md-typeset h5,.md-typeset h6{color:var(--md-default-fg-color--light);font-size:.8em;font-weight:700;letter-spacing:-.01em;margin:1.25em 0}.md-typeset h5{text-transform:uppercase}.md-typeset hr{border-bottom:.05rem solid var(--md-default-fg-color--lightest);display:flow-root;margin:1.5em 0}.md-typeset a{color:var(--md-typeset-a-color);word-break:break-word}.md-typeset a,.md-typeset a:before{transition:color 125ms}.md-typeset a:focus,.md-typeset a:hover{color:var(--md-accent-fg-color)}.md-typeset a:focus code,.md-typeset a:hover code{background-color:var(--md-accent-fg-color--transparent)}.md-typeset a code{color:currentcolor;transition:background-color 125ms}.md-typeset a.focus-visible{outline-color:var(--md-accent-fg-color);outline-offset:.2rem}.md-typeset code,.md-typeset kbd,.md-typeset pre{color:var(--md-code-fg-color);direction:ltr;font-variant-ligatures:none}@media print{.md-typeset code,.md-typeset kbd,.md-typeset pre{white-space:pre-wrap}}.md-typeset code{background-color:var(--md-code-bg-color);border-radius:.1rem;-webkit-box-decoration-break:clone;box-decoration-break:clone;font-size:.85em;padding:0 .2941176471em;word-break:break-word}.md-typeset code:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}.md-typeset pre{display:flow-root;line-height:1.4;position:relative}.md-typeset pre>code{-webkit-box-decoration-break:slice;box-decoration-break:slice;box-shadow:none;display:block;margin:0;outline-color:var(--md-accent-fg-color);overflow:auto;padding:.7720588235em 1.1764705882em;scrollbar-color:var(--md-default-fg-color--lighter) #0000;scrollbar-width:thin;touch-action:auto;word-break:normal}.md-typeset pre>code:hover{scrollbar-color:var(--md-accent-fg-color) #0000}.md-typeset pre>code::-webkit-scrollbar{height:.2rem;width:.2rem}.md-typeset pre>code::-webkit-scrollbar-thumb{background-color:var(--md-default-fg-color--lighter)}.md-typeset pre>code::-webkit-scrollbar-thumb:hover{background-color:var(--md-accent-fg-color)}.md-typeset kbd{background-color:var(--md-typeset-kbd-color);border-radius:.1rem;box-shadow:0 .1rem 0 .05rem var(--md-typeset-kbd-border-color),0 .1rem 0 var(--md-typeset-kbd-border-color),0 -.1rem .2rem var(--md-typeset-kbd-accent-color) inset;color:var(--md-default-fg-color);display:inline-block;font-size:.75em;padding:0 .6666666667em;vertical-align:text-top;word-break:break-word}.md-typeset mark{background-color:var(--md-typeset-mark-color);-webkit-box-decoration-break:clone;box-decoration-break:clone;color:inherit;word-break:break-word}.md-typeset abbr{border-bottom:.05rem dotted var(--md-default-fg-color--light);cursor:help;text-decoration:none}@media (hover:none){.md-typeset abbr{position:relative}.md-typeset abbr[title]:-webkit-any(:focus,:hover):after{background-color:var(--md-default-fg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z3);color:var(--md-default-bg-color);content:attr(title);display:inline-block;font-size:.7rem;margin-top:2em;max-width:80%;min-width:-webkit-max-content;min-width:max-content;padding:.2rem .3rem;position:absolute;width:auto}.md-typeset abbr[title]:-moz-any(:focus,:hover):after{background-color:var(--md-default-fg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z3);color:var(--md-default-bg-color);content:attr(title);display:inline-block;font-size:.7rem;margin-top:2em;max-width:80%;min-width:-moz-max-content;min-width:max-content;padding:.2rem .3rem;position:absolute;width:auto}[dir=ltr] .md-typeset abbr[title]:-webkit-any(:focus,:hover):after{left:0}[dir=ltr] .md-typeset abbr[title]:-moz-any(:focus,:hover):after{left:0}[dir=ltr] .md-typeset abbr[title]:is(:focus,:hover):after{left:0}[dir=rtl] .md-typeset abbr[title]:-webkit-any(:focus,:hover):after{right:0}[dir=rtl] .md-typeset abbr[title]:-moz-any(:focus,:hover):after{right:0}[dir=rtl] .md-typeset abbr[title]:is(:focus,:hover):after{right:0}.md-typeset abbr[title]:is(:focus,:hover):after{background-color:var(--md-default-fg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z3);color:var(--md-default-bg-color);content:attr(title);display:inline-block;font-size:.7rem;margin-top:2em;max-width:80%;min-width:-webkit-max-content;min-width:-moz-max-content;min-width:max-content;padding:.2rem .3rem;position:absolute;width:auto}}.md-typeset small{opacity:.75}[dir=ltr] .md-typeset sub,[dir=ltr] .md-typeset sup{margin-left:.078125em}[dir=rtl] .md-typeset sub,[dir=rtl] .md-typeset sup{margin-right:.078125em}[dir=ltr] .md-typeset blockquote{padding-left:.6rem}[dir=rtl] .md-typeset blockquote{padding-right:.6rem}[dir=ltr] .md-typeset blockquote{border-left:.2rem solid var(--md-default-fg-color--lighter)}[dir=rtl] .md-typeset blockquote{border-right:.2rem solid var(--md-default-fg-color--lighter)}.md-typeset blockquote{color:var(--md-default-fg-color--light);margin-left:0;margin-right:0}.md-typeset ul{list-style-type:disc}[dir=ltr] .md-typeset ol,[dir=ltr] .md-typeset ul{margin-left:.625em}[dir=rtl] .md-typeset ol,[dir=rtl] .md-typeset ul{margin-right:.625em}.md-typeset ol,.md-typeset ul{padding:0}.md-typeset ol:not([hidden]),.md-typeset ul:not([hidden]){display:flow-root}.md-typeset ol ol,.md-typeset ul ol{list-style-type:lower-alpha}.md-typeset ol ol ol,.md-typeset ul ol ol{list-style-type:lower-roman}[dir=ltr] .md-typeset ol li,[dir=ltr] .md-typeset ul li{margin-left:1.25em}[dir=rtl] .md-typeset ol li,[dir=rtl] .md-typeset ul li{margin-right:1.25em}.md-typeset ol li,.md-typeset ul li{margin-bottom:.5em}.md-typeset ol li blockquote,.md-typeset ol li p,.md-typeset ul li blockquote,.md-typeset ul li p{margin:.5em 0}.md-typeset ol li:last-child,.md-typeset ul li:last-child{margin-bottom:0}.md-typeset ol li :-webkit-any(ul,ol),.md-typeset ul li :-webkit-any(ul,ol){margin-bottom:.5em;margin-top:.5em}.md-typeset ol li :-moz-any(ul,ol),.md-typeset ul li :-moz-any(ul,ol){margin-bottom:.5em;margin-top:.5em}[dir=ltr] .md-typeset ol li :-webkit-any(ul,ol),[dir=ltr] .md-typeset ul li :-webkit-any(ul,ol){margin-left:.625em}[dir=ltr] .md-typeset ol li :-moz-any(ul,ol),[dir=ltr] .md-typeset ul li :-moz-any(ul,ol){margin-left:.625em}[dir=ltr] .md-typeset ol li :is(ul,ol),[dir=ltr] .md-typeset ul li :is(ul,ol){margin-left:.625em}[dir=rtl] .md-typeset ol li :-webkit-any(ul,ol),[dir=rtl] .md-typeset ul li :-webkit-any(ul,ol){margin-right:.625em}[dir=rtl] .md-typeset ol li :-moz-any(ul,ol),[dir=rtl] .md-typeset ul li :-moz-any(ul,ol){margin-right:.625em}[dir=rtl] .md-typeset ol li :is(ul,ol),[dir=rtl] .md-typeset ul li :is(ul,ol){margin-right:.625em}.md-typeset ol li :is(ul,ol),.md-typeset ul li :is(ul,ol){margin-bottom:.5em;margin-top:.5em}[dir=ltr] .md-typeset dd{margin-left:1.875em}[dir=rtl] .md-typeset dd{margin-right:1.875em}.md-typeset dd{margin-bottom:1.5em;margin-top:1em}.md-typeset img,.md-typeset svg,.md-typeset video{height:auto;max-width:100%}.md-typeset img[align=left]{margin:1em 1em 1em 0}.md-typeset img[align=right]{margin:1em 0 1em 1em}.md-typeset img[align]:only-child{margin-top:0}.md-typeset img[src$="#gh-dark-mode-only"],.md-typeset img[src$="#only-dark"]{display:none}.md-typeset figure{display:flow-root;margin:1em auto;max-width:100%;text-align:center;width:-webkit-fit-content;width:-moz-fit-content;width:fit-content}.md-typeset figure img{display:block}.md-typeset figcaption{font-style:italic;margin:1em auto;max-width:24rem}.md-typeset iframe{max-width:100%}.md-typeset table:not([class]){background-color:var(--md-default-bg-color);border:.05rem solid var(--md-typeset-table-color);border-radius:.1rem;display:inline-block;font-size:.64rem;max-width:100%;overflow:auto;touch-action:auto}@media print{.md-typeset table:not([class]){display:table}}.md-typeset table:not([class])+*{margin-top:1.5em}.md-typeset table:not([class]) :-webkit-any(th,td)>:first-child{margin-top:0}.md-typeset table:not([class]) :-moz-any(th,td)>:first-child{margin-top:0}.md-typeset table:not([class]) :is(th,td)>:first-child{margin-top:0}.md-typeset table:not([class]) :-webkit-any(th,td)>:last-child{margin-bottom:0}.md-typeset table:not([class]) :-moz-any(th,td)>:last-child{margin-bottom:0}.md-typeset table:not([class]) :is(th,td)>:last-child{margin-bottom:0}.md-typeset table:not([class]) :-webkit-any(th,td):not([align]){text-align:left}.md-typeset table:not([class]) :-moz-any(th,td):not([align]){text-align:left}.md-typeset table:not([class]) :is(th,td):not([align]){text-align:left}[dir=rtl] .md-typeset table:not([class]) :-webkit-any(th,td):not([align]){text-align:right}[dir=rtl] .md-typeset table:not([class]) :-moz-any(th,td):not([align]){text-align:right}[dir=rtl] .md-typeset table:not([class]) :is(th,td):not([align]){text-align:right}.md-typeset table:not([class]) th{font-weight:700;min-width:5rem;padding:.9375em 1.25em;vertical-align:top}.md-typeset table:not([class]) td{border-top:.05rem solid var(--md-typeset-table-color);padding:.9375em 1.25em;vertical-align:top}.md-typeset table:not([class]) tbody tr{transition:background-color 125ms}.md-typeset table:not([class]) tbody tr:hover{background-color:rgba(0,0,0,.035);box-shadow:0 .05rem 0 var(--md-default-bg-color) inset}.md-typeset table:not([class]) a{word-break:normal}.md-typeset table th[role=columnheader]{cursor:pointer}[dir=ltr] .md-typeset table th[role=columnheader]:after{margin-left:.5em}[dir=rtl] .md-typeset table th[role=columnheader]:after{margin-right:.5em}.md-typeset table th[role=columnheader]:after{content:"";display:inline-block;height:1.2em;-webkit-mask-image:var(--md-typeset-table-sort-icon);mask-image:var(--md-typeset-table-sort-icon);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;transition:background-color 125ms;vertical-align:text-bottom;width:1.2em}.md-typeset table th[role=columnheader]:hover:after{background-color:var(--md-default-fg-color--lighter)}.md-typeset table th[role=columnheader][aria-sort=ascending]:after{background-color:var(--md-default-fg-color--light);-webkit-mask-image:var(--md-typeset-table-sort-icon--asc);mask-image:var(--md-typeset-table-sort-icon--asc)}.md-typeset table th[role=columnheader][aria-sort=descending]:after{background-color:var(--md-default-fg-color--light);-webkit-mask-image:var(--md-typeset-table-sort-icon--desc);mask-image:var(--md-typeset-table-sort-icon--desc)}.md-typeset__scrollwrap{margin:1em -.8rem;overflow-x:auto;touch-action:auto}.md-typeset__table{display:inline-block;margin-bottom:.5em;padding:0 .8rem}@media print{.md-typeset__table{display:block}}html .md-typeset__table table{display:table;margin:0;overflow:hidden;width:100%}@media screen and (max-width:44.9375em){.md-content__inner>pre{margin:1em -.8rem}.md-content__inner>pre code{border-radius:0}}.md-banner{background-color:var(--md-footer-bg-color);color:var(--md-footer-fg-color);overflow:auto}@media print{.md-banner{display:none}}.md-banner--warning{background:var(--md-typeset-mark-color);color:var(--md-default-fg-color)}.md-banner__inner{font-size:.7rem;margin:.6rem auto;padding:0 .8rem}[dir=ltr] .md-banner__button{float:right}[dir=rtl] .md-banner__button{float:left}.md-banner__button{color:inherit;cursor:pointer;transition:opacity .25s}.md-banner__button:hover{opacity:.7}html{font-size:125%;height:100%;overflow-x:hidden}@media screen and (min-width:100em){html{font-size:137.5%}}@media screen and (min-width:125em){html{font-size:150%}}body{background-color:var(--md-default-bg-color);display:flex;flex-direction:column;font-size:.5rem;min-height:100%;position:relative;width:100%}@media print{body{display:block}}@media screen and (max-width:59.9375em){body[data-md-scrolllock]{position:fixed}}.md-grid{margin-left:auto;margin-right:auto;max-width:61rem}.md-container{display:flex;flex-direction:column;flex-grow:1}@media print{.md-container{display:block}}.md-main{flex-grow:1}.md-main__inner{display:flex;height:100%;margin-top:1.5rem}.md-ellipsis{overflow:hidden;text-overflow:ellipsis;white-space:nowrap}.md-toggle{display:none}.md-option{height:0;opacity:0;position:absolute;width:0}.md-option:checked+label:not([hidden]){display:block}.md-option.focus-visible+label{outline-color:var(--md-accent-fg-color);outline-style:auto}.md-skip{background-color:var(--md-default-fg-color);border-radius:.1rem;color:var(--md-default-bg-color);font-size:.64rem;margin:.5rem;opacity:0;outline-color:var(--md-accent-fg-color);padding:.3rem .5rem;position:fixed;transform:translateY(.4rem);z-index:-1}.md-skip:focus{opacity:1;transform:translateY(0);transition:transform .25s cubic-bezier(.4,0,.2,1),opacity 175ms 75ms;z-index:10}@page{margin:25mm}:root{--md-clipboard-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 21H8V7h11m0-2H8a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h11a2 2 0 0 0 2-2V7a2 2 0 0 0-2-2m-3-4H4a2 2 0 0 0-2 2v14h2V3h12V1Z"/></svg>')}.md-clipboard{border-radius:.1rem;color:var(--md-default-fg-color--lightest);cursor:pointer;height:1.5em;outline-color:var(--md-accent-fg-color);outline-offset:.1rem;position:absolute;right:.5em;top:.5em;transition:color .25s;width:1.5em;z-index:1}@media print{.md-clipboard{display:none}}.md-clipboard:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}:hover>.md-clipboard{color:var(--md-default-fg-color--light)}.md-clipboard:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-clipboard:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-clipboard:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-clipboard:after{background-color:currentcolor;content:"";display:block;height:1.125em;margin:0 auto;-webkit-mask-image:var(--md-clipboard-icon);mask-image:var(--md-clipboard-icon);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:1.125em}.md-clipboard--inline{cursor:pointer}.md-clipboard--inline code{transition:color .25s,background-color .25s}.md-clipboard--inline:-webkit-any(:focus,:hover) code{background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-clipboard--inline:-moz-any(:focus,:hover) code{background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-clipboard--inline:is(:focus,:hover) code{background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}@keyframes consent{0%{opacity:0;transform:translateY(100%)}to{opacity:1;transform:translateY(0)}}@keyframes overlay{0%{opacity:0}to{opacity:1}}.md-consent__overlay{animation:overlay .25s both;-webkit-backdrop-filter:blur(.1rem);backdrop-filter:blur(.1rem);background-color:#0000008a;height:100%;opacity:1;position:fixed;top:0;width:100%;z-index:5}.md-consent__inner{animation:consent .5s cubic-bezier(.1,.7,.1,1) both;background-color:var(--md-default-bg-color);border:0;border-radius:.1rem;bottom:0;box-shadow:0 0 .2rem #0000001a,0 .2rem .4rem #0003;max-height:100%;overflow:auto;padding:0;position:fixed;width:100%;z-index:5}.md-consent__form{padding:.8rem}.md-consent__settings{display:none;margin:1em 0}input:checked+.md-consent__settings{display:block}.md-consent__controls{margin-bottom:.8rem}.md-typeset .md-consent__controls .md-button{display:inline}@media screen and (max-width:44.9375em){.md-typeset .md-consent__controls .md-button{display:block;margin-top:.4rem;text-align:center;width:100%}}.md-consent label{cursor:pointer}.md-content{flex-grow:1;min-width:0}.md-content__inner{margin:0 .8rem 1.2rem;padding-top:.6rem}@media screen and (min-width:76.25em){[dir=ltr] .md-sidebar--primary:not([hidden])~.md-content>.md-content__inner{margin-left:1.2rem}[dir=ltr] .md-sidebar--secondary:not([hidden])~.md-content>.md-content__inner,[dir=rtl] .md-sidebar--primary:not([hidden])~.md-content>.md-content__inner{margin-right:1.2rem}[dir=rtl] .md-sidebar--secondary:not([hidden])~.md-content>.md-content__inner{margin-left:1.2rem}}.md-content__inner:before{content:"";display:block;height:.4rem}.md-content__inner>:last-child{margin-bottom:0}[dir=ltr] .md-content__button{float:right}[dir=rtl] .md-content__button{float:left}[dir=ltr] .md-content__button{margin-left:.4rem}[dir=rtl] .md-content__button{margin-right:.4rem}.md-content__button{margin:.4rem 0;padding:0}@media print{.md-content__button{display:none}}.md-typeset .md-content__button{color:var(--md-default-fg-color--lighter)}.md-content__button svg{display:inline;vertical-align:top}[dir=rtl] .md-content__button svg{transform:scaleX(-1)}[dir=ltr] .md-dialog{right:.8rem}[dir=rtl] .md-dialog{left:.8rem}.md-dialog{background-color:var(--md-default-fg-color);border-radius:.1rem;bottom:.8rem;box-shadow:var(--md-shadow-z3);min-width:11.1rem;opacity:0;padding:.4rem .6rem;pointer-events:none;position:fixed;transform:translateY(100%);transition:transform 0ms .4s,opacity .4s;z-index:4}@media print{.md-dialog{display:none}}.md-dialog--active{opacity:1;pointer-events:auto;transform:translateY(0);transition:transform .4s cubic-bezier(.075,.85,.175,1),opacity .4s}.md-dialog__inner{color:var(--md-default-bg-color);font-size:.7rem}.md-feedback{margin:2em 0 1em;text-align:center}.md-feedback fieldset{border:none;margin:0;padding:0}.md-feedback__title{font-weight:700;margin:1em auto}.md-feedback__inner{position:relative}.md-feedback__list{align-content:baseline;display:flex;flex-wrap:wrap;justify-content:center;position:relative}.md-feedback__list:hover .md-icon:not(:disabled){color:var(--md-default-fg-color--lighter)}:disabled .md-feedback__list{min-height:1.8rem}.md-feedback__icon{color:var(--md-default-fg-color--light);cursor:pointer;flex-shrink:0;margin:0 .1rem;transition:color 125ms}.md-feedback__icon:not(:disabled).md-icon:hover{color:var(--md-accent-fg-color)}.md-feedback__icon:disabled{color:var(--md-default-fg-color--lightest);pointer-events:none}.md-feedback__note{opacity:0;position:relative;transform:translateY(.4rem);transition:transform .4s cubic-bezier(.1,.7,.1,1),opacity .15s}.md-feedback__note>*{margin:0 auto;max-width:16rem}:disabled .md-feedback__note{opacity:1;transform:translateY(0)}.md-footer{background-color:var(--md-footer-bg-color);color:var(--md-footer-fg-color)}@media print{.md-footer{display:none}}.md-footer__inner{justify-content:space-between;overflow:auto;padding:.2rem}.md-footer__inner:not([hidden]){display:flex}.md-footer__link{display:flex;flex-grow:0.01;outline-color:var(--md-accent-fg-color);overflow:hidden;padding-bottom:.4rem;padding-top:1.4rem;transition:opacity .25s}.md-footer__link:-webkit-any(:focus,:hover){opacity:.7}.md-footer__link:-moz-any(:focus,:hover){opacity:.7}.md-footer__link:is(:focus,:hover){opacity:.7}[dir=rtl] .md-footer__link svg{transform:scaleX(-1)}@media screen and (max-width:44.9375em){.md-footer__link--prev .md-footer__title{display:none}}[dir=ltr] .md-footer__link--next{margin-left:auto}[dir=rtl] .md-footer__link--next{margin-right:auto}.md-footer__link--next{text-align:right}[dir=rtl] .md-footer__link--next{text-align:left}.md-footer__title{flex-grow:1;font-size:.9rem;line-height:2.4rem;max-width:calc(100% - 2.4rem);padding:0 1rem;position:relative;white-space:nowrap}.md-footer__button{margin:.2rem;padding:.4rem}.md-footer__direction{font-size:.64rem;left:0;margin-top:-1rem;opacity:.7;padding:0 1rem;position:absolute;right:0}.md-footer-meta{background-color:var(--md-footer-bg-color--dark)}.md-footer-meta__inner{display:flex;flex-wrap:wrap;justify-content:space-between;padding:.2rem}html .md-footer-meta.md-typeset a{color:var(--md-footer-fg-color--light)}html .md-footer-meta.md-typeset a:-webkit-any(:focus,:hover){color:var(--md-footer-fg-color)}html .md-footer-meta.md-typeset a:-moz-any(:focus,:hover){color:var(--md-footer-fg-color)}html .md-footer-meta.md-typeset a:is(:focus,:hover){color:var(--md-footer-fg-color)}.md-copyright{color:var(--md-footer-fg-color--lighter);font-size:.64rem;margin:auto .6rem;padding:.4rem 0;width:100%}@media screen and (min-width:45em){.md-copyright{width:auto}}.md-copyright__highlight{color:var(--md-footer-fg-color--light)}.md-social{margin:0 .4rem;padding:.2rem 0 .6rem}@media screen and (min-width:45em){.md-social{padding:.6rem 0}}.md-social__link{display:inline-block;height:1.6rem;text-align:center;width:1.6rem}.md-social__link:before{line-height:1.9}.md-social__link svg{fill:currentcolor;max-height:.8rem;vertical-align:-25%}.md-typeset .md-button{border:.1rem solid;border-radius:.1rem;color:var(--md-primary-fg-color);cursor:pointer;display:inline-block;font-weight:700;padding:.625em 2em;transition:color 125ms,background-color 125ms,border-color 125ms}.md-typeset .md-button--primary{background-color:var(--md-primary-fg-color);border-color:var(--md-primary-fg-color);color:var(--md-primary-bg-color)}.md-typeset .md-button:-webkit-any(:focus,:hover){background-color:var(--md-accent-fg-color);border-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-typeset .md-button:-moz-any(:focus,:hover){background-color:var(--md-accent-fg-color);border-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-typeset .md-button:is(:focus,:hover){background-color:var(--md-accent-fg-color);border-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}[dir=ltr] .md-typeset .md-input{border-top-left-radius:.1rem}[dir=ltr] .md-typeset .md-input,[dir=rtl] .md-typeset .md-input{border-top-right-radius:.1rem}[dir=rtl] .md-typeset .md-input{border-top-left-radius:.1rem}.md-typeset .md-input{border-bottom:.1rem solid var(--md-default-fg-color--lighter);box-shadow:var(--md-shadow-z1);font-size:.8rem;height:1.8rem;padding:0 .6rem;transition:border .25s,box-shadow .25s}.md-typeset .md-input:-webkit-any(:focus,:hover){border-bottom-color:var(--md-accent-fg-color);box-shadow:var(--md-shadow-z2)}.md-typeset .md-input:-moz-any(:focus,:hover){border-bottom-color:var(--md-accent-fg-color);box-shadow:var(--md-shadow-z2)}.md-typeset .md-input:is(:focus,:hover){border-bottom-color:var(--md-accent-fg-color);box-shadow:var(--md-shadow-z2)}.md-typeset .md-input--stretch{width:100%}.md-header{background-color:var(--md-primary-fg-color);box-shadow:0 0 .2rem #0000,0 .2rem .4rem #0000;color:var(--md-primary-bg-color);display:block;left:0;position:-webkit-sticky;position:sticky;right:0;top:0;z-index:4}@media print{.md-header{display:none}}.md-header[hidden]{transform:translateY(-100%);transition:transform .25s cubic-bezier(.8,0,.6,1),box-shadow .25s}.md-header--shadow{box-shadow:0 0 .2rem #0000001a,0 .2rem .4rem #0003;transition:transform .25s cubic-bezier(.1,.7,.1,1),box-shadow .25s}.md-header__inner{align-items:center;display:flex;padding:0 .2rem}.md-header__button{color:currentcolor;cursor:pointer;margin:.2rem;outline-color:var(--md-accent-fg-color);padding:.4rem;position:relative;transition:opacity .25s;vertical-align:middle;z-index:1}.md-header__button:hover{opacity:.7}.md-header__button:not([hidden]){display:inline-block}.md-header__button:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}.md-header__button.md-logo{margin:.2rem;padding:.4rem}@media screen and (max-width:76.1875em){.md-header__button.md-logo{display:none}}.md-header__button.md-logo :-webkit-any(img,svg){fill:currentcolor;display:block;height:1.2rem;width:auto}.md-header__button.md-logo :-moz-any(img,svg){fill:currentcolor;display:block;height:1.2rem;width:auto}.md-header__button.md-logo :is(img,svg){fill:currentcolor;display:block;height:1.2rem;width:auto}@media screen and (min-width:60em){.md-header__button[for=__search]{display:none}}.no-js .md-header__button[for=__search]{display:none}[dir=rtl] .md-header__button[for=__search] svg{transform:scaleX(-1)}@media screen and (min-width:76.25em){.md-header__button[for=__drawer]{display:none}}.md-header__topic{display:flex;max-width:100%;position:absolute;transition:transform .4s cubic-bezier(.1,.7,.1,1),opacity .15s;white-space:nowrap}.md-header__topic+.md-header__topic{opacity:0;pointer-events:none;transform:translateX(1.25rem);transition:transform .4s cubic-bezier(1,.7,.1,.1),opacity .15s;z-index:-1}[dir=rtl] .md-header__topic+.md-header__topic{transform:translateX(-1.25rem)}.md-header__topic:first-child{font-weight:700}[dir=ltr] .md-header__title{margin-right:.4rem}[dir=rtl] .md-header__title{margin-left:.4rem}[dir=ltr] .md-header__title{margin-left:1rem}[dir=rtl] .md-header__title{margin-right:1rem}.md-header__title{flex-grow:1;font-size:.9rem;height:2.4rem;line-height:2.4rem}.md-header__title--active .md-header__topic{opacity:0;pointer-events:none;transform:translateX(-1.25rem);transition:transform .4s cubic-bezier(1,.7,.1,.1),opacity .15s;z-index:-1}[dir=rtl] .md-header__title--active .md-header__topic{transform:translateX(1.25rem)}.md-header__title--active .md-header__topic+.md-header__topic{opacity:1;pointer-events:auto;transform:translateX(0);transition:transform .4s cubic-bezier(.1,.7,.1,1),opacity .15s;z-index:0}.md-header__title>.md-header__ellipsis{height:100%;position:relative;width:100%}.md-header__option{display:flex;flex-shrink:0;max-width:100%;transition:max-width 0ms .25s,opacity .25s .25s;white-space:nowrap}[data-md-toggle=search]:checked~.md-header .md-header__option{max-width:0;opacity:0;transition:max-width 0ms,opacity 0ms}.md-header__source{display:none}@media screen and (min-width:60em){[dir=ltr] .md-header__source{margin-left:1rem}[dir=rtl] .md-header__source{margin-right:1rem}.md-header__source{display:block;max-width:11.7rem;width:11.7rem}}@media screen and (min-width:76.25em){[dir=ltr] .md-header__source{margin-left:1.4rem}[dir=rtl] .md-header__source{margin-right:1.4rem}}:root{--md-nav-icon--prev:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11h12Z"/></svg>');--md-nav-icon--next:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M8.59 16.58 13.17 12 8.59 7.41 10 6l6 6-6 6-1.41-1.42Z"/></svg>');--md-toc-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M3 9h14V7H3v2m0 4h14v-2H3v2m0 4h14v-2H3v2m16 0h2v-2h-2v2m0-10v2h2V7h-2m0 6h2v-2h-2v2Z"/></svg>')}.md-nav{font-size:.7rem;line-height:1.3}.md-nav__title{display:block;font-weight:700;overflow:hidden;padding:0 .6rem;text-overflow:ellipsis}.md-nav__title .md-nav__button{display:none}.md-nav__title .md-nav__button img{height:100%;width:auto}.md-nav__title .md-nav__button.md-logo :-webkit-any(img,svg){fill:currentcolor;display:block;height:2.4rem;max-width:100%;object-fit:contain;width:auto}.md-nav__title .md-nav__button.md-logo :-moz-any(img,svg){fill:currentcolor;display:block;height:2.4rem;max-width:100%;object-fit:contain;width:auto}.md-nav__title .md-nav__button.md-logo :is(img,svg){fill:currentcolor;display:block;height:2.4rem;max-width:100%;object-fit:contain;width:auto}.md-nav__list{list-style:none;margin:0;padding:0}.md-nav__item{padding:0 .6rem}[dir=ltr] .md-nav__item .md-nav__item{padding-right:0}[dir=rtl] .md-nav__item .md-nav__item{padding-left:0}.md-nav__link{align-items:center;cursor:pointer;display:flex;justify-content:space-between;margin-top:.625em;overflow:hidden;scroll-snap-align:start;text-overflow:ellipsis;transition:color 125ms}.md-nav__link--passed{color:var(--md-default-fg-color--light)}.md-nav__item .md-nav__link--active{color:var(--md-typeset-a-color)}.md-nav__item .md-nav__link--index [href]{width:100%}.md-nav__link:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav__link:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav__link:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav__link.focus-visible{outline-color:var(--md-accent-fg-color);outline-offset:.2rem}.md-nav--primary .md-nav__link[for=__toc]{display:none}.md-nav--primary .md-nav__link[for=__toc] .md-icon:after{background-color:currentcolor;display:block;height:100%;-webkit-mask-image:var(--md-toc-icon);mask-image:var(--md-toc-icon);width:100%}.md-nav--primary .md-nav__link[for=__toc]~.md-nav{display:none}.md-nav__link>*{cursor:pointer;display:flex}.md-nav__icon{flex-shrink:0}.md-nav__source{display:none}@media screen and (max-width:76.1875em){.md-nav--primary,.md-nav--primary .md-nav{background-color:var(--md-default-bg-color);display:flex;flex-direction:column;height:100%;left:0;position:absolute;right:0;top:0;z-index:1}.md-nav--primary :-webkit-any(.md-nav__title,.md-nav__item){font-size:.8rem;line-height:1.5}.md-nav--primary :-moz-any(.md-nav__title,.md-nav__item){font-size:.8rem;line-height:1.5}.md-nav--primary :is(.md-nav__title,.md-nav__item){font-size:.8rem;line-height:1.5}.md-nav--primary .md-nav__title{background-color:var(--md-default-fg-color--lightest);color:var(--md-default-fg-color--light);cursor:pointer;height:5.6rem;line-height:2.4rem;padding:3rem .8rem .2rem;position:relative;white-space:nowrap}[dir=ltr] .md-nav--primary .md-nav__title .md-nav__icon{left:.4rem}[dir=rtl] .md-nav--primary .md-nav__title .md-nav__icon{right:.4rem}.md-nav--primary .md-nav__title .md-nav__icon{display:block;height:1.2rem;margin:.2rem;position:absolute;top:.4rem;width:1.2rem}.md-nav--primary .md-nav__title .md-nav__icon:after{background-color:currentcolor;content:"";display:block;height:100%;-webkit-mask-image:var(--md-nav-icon--prev);mask-image:var(--md-nav-icon--prev);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:100%}.md-nav--primary .md-nav__title~.md-nav__list{background-color:var(--md-default-bg-color);box-shadow:0 .05rem 0 var(--md-default-fg-color--lightest) inset;overflow-y:auto;scroll-snap-type:y mandatory;touch-action:pan-y}.md-nav--primary .md-nav__title~.md-nav__list>:first-child{border-top:0}.md-nav--primary .md-nav__title[for=__drawer]{background-color:var(--md-primary-fg-color);color:var(--md-primary-bg-color);font-weight:700}.md-nav--primary .md-nav__title .md-logo{display:block;left:.2rem;margin:.2rem;padding:.4rem;position:absolute;right:.2rem;top:.2rem}.md-nav--primary .md-nav__list{flex:1}.md-nav--primary .md-nav__item{border-top:.05rem solid var(--md-default-fg-color--lightest);padding:0}.md-nav--primary .md-nav__item--active>.md-nav__link{color:var(--md-typeset-a-color)}.md-nav--primary .md-nav__item--active>.md-nav__link:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav--primary .md-nav__item--active>.md-nav__link:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav--primary .md-nav__item--active>.md-nav__link:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav--primary .md-nav__link{margin-top:0;padding:.6rem .8rem}[dir=ltr] .md-nav--primary .md-nav__link .md-nav__icon{margin-right:-.2rem}[dir=rtl] .md-nav--primary .md-nav__link .md-nav__icon{margin-left:-.2rem}.md-nav--primary .md-nav__link .md-nav__icon{font-size:1.2rem;height:1.2rem;width:1.2rem}.md-nav--primary .md-nav__link .md-nav__icon:after{background-color:currentcolor;content:"";display:block;height:100%;-webkit-mask-image:var(--md-nav-icon--next);mask-image:var(--md-nav-icon--next);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:100%}[dir=rtl] .md-nav--primary .md-nav__icon:after{transform:scale(-1)}.md-nav--primary .md-nav--secondary .md-nav{background-color:initial;position:static}[dir=ltr] .md-nav--primary .md-nav--secondary .md-nav .md-nav__link{padding-left:1.4rem}[dir=rtl] .md-nav--primary .md-nav--secondary .md-nav .md-nav__link{padding-right:1.4rem}[dir=ltr] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav__link{padding-left:2rem}[dir=rtl] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav__link{padding-right:2rem}[dir=ltr] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav .md-nav__link{padding-left:2.6rem}[dir=rtl] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav .md-nav__link{padding-right:2.6rem}[dir=ltr] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav .md-nav .md-nav__link{padding-left:3.2rem}[dir=rtl] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav .md-nav .md-nav__link{padding-right:3.2rem}.md-nav--secondary{background-color:initial}.md-nav__toggle~.md-nav{display:flex;opacity:0;transform:translateX(100%);transition:transform .25s cubic-bezier(.8,0,.6,1),opacity 125ms 50ms}[dir=rtl] .md-nav__toggle~.md-nav{transform:translateX(-100%)}.md-nav__toggle:checked~.md-nav{opacity:1;transform:translateX(0);transition:transform .25s cubic-bezier(.4,0,.2,1),opacity 125ms 125ms}.md-nav__toggle:checked~.md-nav>.md-nav__list{-webkit-backface-visibility:hidden;backface-visibility:hidden}}@media screen and (max-width:59.9375em){.md-nav--primary .md-nav__link[for=__toc]{display:flex}.md-nav--primary .md-nav__link[for=__toc] .md-icon:after{content:""}.md-nav--primary .md-nav__link[for=__toc]+.md-nav__link{display:none}.md-nav--primary .md-nav__link[for=__toc]~.md-nav{display:flex}.md-nav__source{background-color:var(--md-primary-fg-color--dark);color:var(--md-primary-bg-color);display:block;padding:0 .2rem}}@media screen and (min-width:60em) and (max-width:76.1875em){.md-nav--integrated .md-nav__link[for=__toc]{display:flex}.md-nav--integrated .md-nav__link[for=__toc] .md-icon:after{content:""}.md-nav--integrated .md-nav__link[for=__toc]+.md-nav__link{display:none}.md-nav--integrated .md-nav__link[for=__toc]~.md-nav{display:flex}}@media screen and (min-width:60em){.md-nav--secondary .md-nav__title{background:var(--md-default-bg-color);box-shadow:0 0 .4rem .4rem var(--md-default-bg-color);position:-webkit-sticky;position:sticky;top:0;z-index:1}.md-nav--secondary .md-nav__title[for=__toc]{scroll-snap-align:start}.md-nav--secondary .md-nav__title .md-nav__icon{display:none}}@media screen and (min-width:76.25em){.md-nav{transition:max-height .25s cubic-bezier(.86,0,.07,1)}.md-nav--primary .md-nav__title{background:var(--md-default-bg-color);box-shadow:0 0 .4rem .4rem var(--md-default-bg-color);position:-webkit-sticky;position:sticky;top:0;z-index:1}.md-nav--primary .md-nav__title[for=__drawer]{scroll-snap-align:start}.md-nav--primary .md-nav__title .md-nav__icon,.md-nav__toggle~.md-nav{display:none}.md-nav__toggle:-webkit-any(:checked,:indeterminate)~.md-nav{display:block}.md-nav__toggle:-moz-any(:checked,:indeterminate)~.md-nav{display:block}.md-nav__toggle:is(:checked,:indeterminate)~.md-nav{display:block}.md-nav__item--nested>.md-nav>.md-nav__title{display:none}.md-nav__item--section{display:block;margin:1.25em 0}.md-nav__item--section:last-child{margin-bottom:0}.md-nav__item--section>.md-nav__link{font-weight:700;pointer-events:none}.md-nav__item--section>.md-nav__link--index [href]{pointer-events:auto}.md-nav__item--section>.md-nav__link .md-nav__icon{display:none}.md-nav__item--section>.md-nav{display:block}.md-nav__item--section>.md-nav>.md-nav__list>.md-nav__item{padding:0}.md-nav__icon{border-radius:100%;height:.9rem;transition:background-color .25s,transform .25s;width:.9rem}[dir=rtl] .md-nav__icon{transform:rotate(180deg)}.md-nav__icon:hover{background-color:var(--md-accent-fg-color--transparent)}.md-nav__icon:after{background-color:currentcolor;content:"";display:inline-block;height:100%;-webkit-mask-image:var(--md-nav-icon--next);mask-image:var(--md-nav-icon--next);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;vertical-align:-.1rem;width:100%}.md-nav__item--nested .md-nav__toggle:checked~.md-nav__link .md-nav__icon,.md-nav__item--nested .md-nav__toggle:indeterminate~.md-nav__link .md-nav__icon{transform:rotate(90deg)}.md-nav--lifted>.md-nav__list>.md-nav__item,.md-nav--lifted>.md-nav__list>.md-nav__item--nested,.md-nav--lifted>.md-nav__title{display:none}.md-nav--lifted>.md-nav__list>.md-nav__item--active{display:block;padding:0}.md-nav--lifted>.md-nav__list>.md-nav__item--active>.md-nav__link{background:var(--md-default-bg-color);box-shadow:0 0 .4rem .4rem var(--md-default-bg-color);font-weight:700;margin-top:0;padding:0 .6rem;position:-webkit-sticky;position:sticky;top:0;z-index:1}.md-nav--lifted>.md-nav__list>.md-nav__item--active>.md-nav__link:not(.md-nav__link--index){pointer-events:none}.md-nav--lifted>.md-nav__list>.md-nav__item--active>.md-nav__link .md-nav__icon{display:none}.md-nav--lifted .md-nav[data-md-level="1"]{display:block}[dir=ltr] .md-nav--lifted .md-nav[data-md-level="1"]>.md-nav__list>.md-nav__item{padding-right:.6rem}[dir=rtl] .md-nav--lifted .md-nav[data-md-level="1"]>.md-nav__list>.md-nav__item{padding-left:.6rem}.md-nav--integrated>.md-nav__list>.md-nav__item--active:not(.md-nav__item--nested){padding:0 .6rem}.md-nav--integrated>.md-nav__list>.md-nav__item--active:not(.md-nav__item--nested)>.md-nav__link{padding:0}[dir=ltr] .md-nav--integrated>.md-nav__list>.md-nav__item--active .md-nav--secondary{border-left:.05rem solid var(--md-primary-fg-color)}[dir=rtl] .md-nav--integrated>.md-nav__list>.md-nav__item--active .md-nav--secondary{border-right:.05rem solid var(--md-primary-fg-color)}.md-nav--integrated>.md-nav__list>.md-nav__item--active .md-nav--secondary{display:block;margin-bottom:1.25em}.md-nav--integrated>.md-nav__list>.md-nav__item--active .md-nav--secondary>.md-nav__title{display:none}}:root{--md-search-result-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h7c-.41-.25-.8-.56-1.14-.9-.33-.33-.61-.7-.86-1.1H6V4h7v5h5v1.18c.71.16 1.39.43 2 .82V8l-6-6m6.31 16.9c1.33-2.11.69-4.9-1.4-6.22-2.11-1.33-4.91-.68-6.22 1.4-1.34 2.11-.69 4.89 1.4 6.22 1.46.93 3.32.93 4.79.02L22 23.39 23.39 22l-3.08-3.1m-3.81.1a2.5 2.5 0 0 1-2.5-2.5 2.5 2.5 0 0 1 2.5-2.5 2.5 2.5 0 0 1 2.5 2.5 2.5 2.5 0 0 1-2.5 2.5Z"/></svg>')}.md-search{position:relative}@media screen and (min-width:60em){.md-search{padding:.2rem 0}}.no-js .md-search{display:none}.md-search__overlay{opacity:0;z-index:1}@media screen and (max-width:59.9375em){[dir=ltr] .md-search__overlay{left:-2.2rem}[dir=rtl] .md-search__overlay{right:-2.2rem}.md-search__overlay{background-color:var(--md-default-bg-color);border-radius:1rem;height:2rem;overflow:hidden;pointer-events:none;position:absolute;top:-1rem;transform-origin:center;transition:transform .3s .1s,opacity .2s .2s;width:2rem}[data-md-toggle=search]:checked~.md-header .md-search__overlay{opacity:1;transition:transform .4s,opacity .1s}}@media screen and (min-width:60em){[dir=ltr] .md-search__overlay{left:0}[dir=rtl] .md-search__overlay{right:0}.md-search__overlay{background-color:#0000008a;cursor:pointer;height:0;position:fixed;top:0;transition:width 0ms .25s,height 0ms .25s,opacity .25s;width:0}[data-md-toggle=search]:checked~.md-header .md-search__overlay{height:200vh;opacity:1;transition:width 0ms,height 0ms,opacity .25s;width:100%}}@media screen and (max-width:29.9375em){[data-md-toggle=search]:checked~.md-header .md-search__overlay{transform:scale(45)}}@media screen and (min-width:30em) and (max-width:44.9375em){[data-md-toggle=search]:checked~.md-header .md-search__overlay{transform:scale(60)}}@media screen and (min-width:45em) and (max-width:59.9375em){[data-md-toggle=search]:checked~.md-header .md-search__overlay{transform:scale(75)}}.md-search__inner{-webkit-backface-visibility:hidden;backface-visibility:hidden}@media screen and (max-width:59.9375em){[dir=ltr] .md-search__inner{left:0}[dir=rtl] .md-search__inner{right:0}.md-search__inner{height:0;opacity:0;overflow:hidden;position:fixed;top:0;transform:translateX(5%);transition:width 0ms .3s,height 0ms .3s,transform .15s cubic-bezier(.4,0,.2,1) .15s,opacity .15s .15s;width:0;z-index:2}[dir=rtl] .md-search__inner{transform:translateX(-5%)}[data-md-toggle=search]:checked~.md-header .md-search__inner{height:100%;opacity:1;transform:translateX(0);transition:width 0ms 0ms,height 0ms 0ms,transform .15s cubic-bezier(.1,.7,.1,1) .15s,opacity .15s .15s;width:100%}}@media screen and (min-width:60em){[dir=ltr] .md-search__inner{float:right}[dir=rtl] .md-search__inner{float:left}.md-search__inner{padding:.1rem 0;position:relative;transition:width .25s cubic-bezier(.1,.7,.1,1);width:11.7rem}}@media screen and (min-width:60em) and (max-width:76.1875em){[data-md-toggle=search]:checked~.md-header .md-search__inner{width:23.4rem}}@media screen and (min-width:76.25em){[data-md-toggle=search]:checked~.md-header .md-search__inner{width:34.4rem}}.md-search__form{background-color:var(--md-default-bg-color);box-shadow:0 0 .6rem #0000;height:2.4rem;position:relative;transition:color .25s,background-color .25s;z-index:2}@media screen and (min-width:60em){.md-search__form{background-color:#00000042;border-radius:.1rem;height:1.8rem}.md-search__form:hover{background-color:#ffffff1f}}[data-md-toggle=search]:checked~.md-header .md-search__form{background-color:var(--md-default-bg-color);border-radius:.1rem .1rem 0 0;box-shadow:0 0 .6rem #00000012;color:var(--md-default-fg-color)}[dir=ltr] .md-search__input{padding-left:3.6rem;padding-right:2.2rem}[dir=rtl] .md-search__input{padding-left:2.2rem;padding-right:3.6rem}.md-search__input{background:#0000;font-size:.9rem;height:100%;position:relative;text-overflow:ellipsis;width:100%;z-index:2}.md-search__input::placeholder{transition:color .25s}.md-search__input::placeholder,.md-search__input~.md-search__icon{color:var(--md-default-fg-color--light)}.md-search__input::-ms-clear{display:none}@media screen and (max-width:59.9375em){.md-search__input{font-size:.9rem;height:2.4rem;width:100%}}@media screen and (min-width:60em){[dir=ltr] .md-search__input{padding-left:2.2rem}[dir=rtl] .md-search__input{padding-right:2.2rem}.md-search__input{color:inherit;font-size:.8rem}.md-search__input::placeholder{color:var(--md-primary-bg-color--light)}.md-search__input+.md-search__icon{color:var(--md-primary-bg-color)}[data-md-toggle=search]:checked~.md-header .md-search__input{text-overflow:clip}[data-md-toggle=search]:checked~.md-header .md-search__input+.md-search__icon,[data-md-toggle=search]:checked~.md-header .md-search__input::placeholder{color:var(--md-default-fg-color--light)}}.md-search__icon{cursor:pointer;display:inline-block;height:1.2rem;transition:color .25s,opacity .25s;width:1.2rem}.md-search__icon:hover{opacity:.7}[dir=ltr] .md-search__icon[for=__search]{left:.5rem}[dir=rtl] .md-search__icon[for=__search]{right:.5rem}.md-search__icon[for=__search]{position:absolute;top:.3rem;z-index:2}[dir=rtl] .md-search__icon[for=__search] svg{transform:scaleX(-1)}@media screen and (max-width:59.9375em){[dir=ltr] .md-search__icon[for=__search]{left:.8rem}[dir=rtl] .md-search__icon[for=__search]{right:.8rem}.md-search__icon[for=__search]{top:.6rem}.md-search__icon[for=__search] svg:first-child{display:none}}@media screen and (min-width:60em){.md-search__icon[for=__search]{pointer-events:none}.md-search__icon[for=__search] svg:last-child{display:none}}[dir=ltr] .md-search__options{right:.5rem}[dir=rtl] .md-search__options{left:.5rem}.md-search__options{pointer-events:none;position:absolute;top:.3rem;z-index:2}@media screen and (max-width:59.9375em){[dir=ltr] .md-search__options{right:.8rem}[dir=rtl] .md-search__options{left:.8rem}.md-search__options{top:.6rem}}[dir=ltr] .md-search__options>*{margin-left:.2rem}[dir=rtl] .md-search__options>*{margin-right:.2rem}.md-search__options>*{color:var(--md-default-fg-color--light);opacity:0;transform:scale(.75);transition:transform .15s cubic-bezier(.1,.7,.1,1),opacity .15s}.md-search__options>:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}[data-md-toggle=search]:checked~.md-header .md-search__input:valid~.md-search__options>*{opacity:1;pointer-events:auto;transform:scale(1)}[data-md-toggle=search]:checked~.md-header .md-search__input:valid~.md-search__options>:hover{opacity:.7}[dir=ltr] .md-search__suggest{padding-left:3.6rem;padding-right:2.2rem}[dir=rtl] .md-search__suggest{padding-left:2.2rem;padding-right:3.6rem}.md-search__suggest{align-items:center;color:var(--md-default-fg-color--lighter);display:flex;font-size:.9rem;height:100%;opacity:0;position:absolute;top:0;transition:opacity 50ms;white-space:nowrap;width:100%}@media screen and (min-width:60em){[dir=ltr] .md-search__suggest{padding-left:2.2rem}[dir=rtl] .md-search__suggest{padding-right:2.2rem}.md-search__suggest{font-size:.8rem}}[data-md-toggle=search]:checked~.md-header .md-search__suggest{opacity:1;transition:opacity .3s .1s}[dir=ltr] .md-search__output{border-bottom-left-radius:.1rem}[dir=ltr] .md-search__output,[dir=rtl] .md-search__output{border-bottom-right-radius:.1rem}[dir=rtl] .md-search__output{border-bottom-left-radius:.1rem}.md-search__output{overflow:hidden;position:absolute;width:100%;z-index:1}@media screen and (max-width:59.9375em){.md-search__output{bottom:0;top:2.4rem}}@media screen and (min-width:60em){.md-search__output{opacity:0;top:1.9rem;transition:opacity .4s}[data-md-toggle=search]:checked~.md-header .md-search__output{box-shadow:var(--md-shadow-z3);opacity:1}}.md-search__scrollwrap{-webkit-backface-visibility:hidden;backface-visibility:hidden;background-color:var(--md-default-bg-color);height:100%;overflow-y:auto;touch-action:pan-y}@media (-webkit-max-device-pixel-ratio:1),(max-resolution:1dppx){.md-search__scrollwrap{transform:translateZ(0)}}@media screen and (min-width:60em) and (max-width:76.1875em){.md-search__scrollwrap{width:23.4rem}}@media screen and (min-width:76.25em){.md-search__scrollwrap{width:34.4rem}}@media screen and (min-width:60em){.md-search__scrollwrap{max-height:0;scrollbar-color:var(--md-default-fg-color--lighter) #0000;scrollbar-width:thin}[data-md-toggle=search]:checked~.md-header .md-search__scrollwrap{max-height:75vh}.md-search__scrollwrap:hover{scrollbar-color:var(--md-accent-fg-color) #0000}.md-search__scrollwrap::-webkit-scrollbar{height:.2rem;width:.2rem}.md-search__scrollwrap::-webkit-scrollbar-thumb{background-color:var(--md-default-fg-color--lighter)}.md-search__scrollwrap::-webkit-scrollbar-thumb:hover{background-color:var(--md-accent-fg-color)}}.md-search-result{color:var(--md-default-fg-color);word-break:break-word}.md-search-result__meta{background-color:var(--md-default-fg-color--lightest);color:var(--md-default-fg-color--light);font-size:.64rem;line-height:1.8rem;padding:0 .8rem;scroll-snap-align:start}@media screen and (min-width:60em){[dir=ltr] .md-search-result__meta{padding-left:2.2rem}[dir=rtl] .md-search-result__meta{padding-right:2.2rem}}.md-search-result__list{list-style:none;margin:0;padding:0;-webkit-user-select:none;-moz-user-select:none;user-select:none}.md-search-result__item{box-shadow:0 -.05rem var(--md-default-fg-color--lightest)}.md-search-result__item:first-child{box-shadow:none}.md-search-result__link{display:block;outline:none;scroll-snap-align:start;transition:background-color .25s}.md-search-result__link:-webkit-any(:focus,:hover){background-color:var(--md-accent-fg-color--transparent)}.md-search-result__link:-moz-any(:focus,:hover){background-color:var(--md-accent-fg-color--transparent)}.md-search-result__link:is(:focus,:hover){background-color:var(--md-accent-fg-color--transparent)}.md-search-result__link:last-child p:last-child{margin-bottom:.6rem}.md-search-result__more summary{color:var(--md-typeset-a-color);cursor:pointer;display:block;font-size:.64rem;outline:none;padding:.75em .8rem;scroll-snap-align:start;transition:color .25s,background-color .25s}@media screen and (min-width:60em){[dir=ltr] .md-search-result__more summary{padding-left:2.2rem}[dir=rtl] .md-search-result__more summary{padding-right:2.2rem}}.md-search-result__more summary:-webkit-any(:focus,:hover){background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-search-result__more summary:-moz-any(:focus,:hover){background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-search-result__more summary:is(:focus,:hover){background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-search-result__more summary::marker{display:none}.md-search-result__more summary::-webkit-details-marker{display:none}.md-search-result__more summary~*>*{opacity:.65}.md-search-result__article{overflow:hidden;padding:0 .8rem;position:relative}@media screen and (min-width:60em){[dir=ltr] .md-search-result__article{padding-left:2.2rem}[dir=rtl] .md-search-result__article{padding-right:2.2rem}}.md-search-result__article--document .md-search-result__title{font-size:.8rem;font-weight:400;line-height:1.4;margin:.55rem 0}[dir=ltr] .md-search-result__icon{left:0}[dir=rtl] .md-search-result__icon{right:0}.md-search-result__icon{color:var(--md-default-fg-color--light);height:1.2rem;margin:.5rem;position:absolute;width:1.2rem}@media screen and (max-width:59.9375em){.md-search-result__icon{display:none}}.md-search-result__icon:after{background-color:currentcolor;content:"";display:inline-block;height:100%;-webkit-mask-image:var(--md-search-result-icon);mask-image:var(--md-search-result-icon);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:100%}[dir=rtl] .md-search-result__icon:after{transform:scaleX(-1)}.md-search-result__title{font-size:.64rem;font-weight:700;line-height:1.6;margin:.5em 0}.md-search-result__teaser{-webkit-box-orient:vertical;-webkit-line-clamp:2;color:var(--md-default-fg-color--light);display:-webkit-box;font-size:.64rem;line-height:1.6;margin:.5em 0;max-height:2rem;overflow:hidden;text-overflow:ellipsis}@media screen and (max-width:44.9375em){.md-search-result__teaser{-webkit-line-clamp:3;max-height:3rem}}@media screen and (min-width:60em) and (max-width:76.1875em){.md-search-result__teaser{-webkit-line-clamp:3;max-height:3rem}}.md-search-result__teaser mark{background-color:initial;text-decoration:underline}.md-search-result__terms{font-size:.64rem;font-style:italic;margin:.5em 0}.md-search-result mark{background-color:initial;color:var(--md-accent-fg-color)}.md-select{position:relative;z-index:1}.md-select__inner{background-color:var(--md-default-bg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z2);color:var(--md-default-fg-color);left:50%;margin-top:.2rem;max-height:0;opacity:0;position:absolute;top:calc(100% - .2rem);transform:translate3d(-50%,.3rem,0);transition:transform .25s 375ms,opacity .25s .25s,max-height 0ms .5s}.md-select:-webkit-any(:focus-within,:hover) .md-select__inner{max-height:10rem;opacity:1;transform:translate3d(-50%,0,0);-webkit-transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms;transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms}.md-select:-moz-any(:focus-within,:hover) .md-select__inner{max-height:10rem;opacity:1;transform:translate3d(-50%,0,0);-moz-transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms;transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms}.md-select:is(:focus-within,:hover) .md-select__inner{max-height:10rem;opacity:1;transform:translate3d(-50%,0,0);transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms}.md-select__inner:after{border-bottom:.2rem solid #0000;border-bottom-color:var(--md-default-bg-color);border-left:.2rem solid #0000;border-right:.2rem solid #0000;border-top:0;content:"";height:0;left:50%;margin-left:-.2rem;margin-top:-.2rem;position:absolute;top:0;width:0}.md-select__list{border-radius:.1rem;font-size:.8rem;list-style-type:none;margin:0;max-height:inherit;overflow:auto;padding:0}.md-select__item{line-height:1.8rem}[dir=ltr] .md-select__link{padding-left:.6rem;padding-right:1.2rem}[dir=rtl] .md-select__link{padding-left:1.2rem;padding-right:.6rem}.md-select__link{cursor:pointer;display:block;outline:none;scroll-snap-align:start;transition:background-color .25s,color .25s;width:100%}.md-select__link:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-select__link:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-select__link:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-select__link:focus{background-color:var(--md-default-fg-color--lightest)}.md-sidebar{align-self:flex-start;flex-shrink:0;padding:1.2rem 0;position:-webkit-sticky;position:sticky;top:2.4rem;width:12.1rem}@media print{.md-sidebar{display:none}}@media screen and (max-width:76.1875em){[dir=ltr] .md-sidebar--primary{left:-12.1rem}[dir=rtl] .md-sidebar--primary{right:-12.1rem}.md-sidebar--primary{background-color:var(--md-default-bg-color);display:block;height:100%;position:fixed;top:0;transform:translateX(0);transition:transform .25s cubic-bezier(.4,0,.2,1),box-shadow .25s;width:12.1rem;z-index:5}[data-md-toggle=drawer]:checked~.md-container .md-sidebar--primary{box-shadow:var(--md-shadow-z3);transform:translateX(12.1rem)}[dir=rtl] [data-md-toggle=drawer]:checked~.md-container .md-sidebar--primary{transform:translateX(-12.1rem)}.md-sidebar--primary .md-sidebar__scrollwrap{bottom:0;left:0;margin:0;overflow:hidden;position:absolute;right:0;scroll-snap-type:none;top:0}}@media screen and (min-width:76.25em){.md-sidebar{height:0}.no-js .md-sidebar{height:auto}.md-header--lifted~.md-container .md-sidebar{top:4.8rem}}.md-sidebar--secondary{display:none;order:2}@media screen and (min-width:60em){.md-sidebar--secondary{height:0}.no-js .md-sidebar--secondary{height:auto}.md-sidebar--secondary:not([hidden]){display:block}.md-sidebar--secondary .md-sidebar__scrollwrap{touch-action:pan-y}}.md-sidebar__scrollwrap{scrollbar-gutter:stable;-webkit-backface-visibility:hidden;backface-visibility:hidden;margin:0 .2rem;overflow-y:auto;scrollbar-color:var(--md-default-fg-color--lighter) #0000;scrollbar-width:thin}.md-sidebar__scrollwrap:hover{scrollbar-color:var(--md-accent-fg-color) #0000}.md-sidebar__scrollwrap::-webkit-scrollbar{height:.2rem;width:.2rem}.md-sidebar__scrollwrap::-webkit-scrollbar-thumb{background-color:var(--md-default-fg-color--lighter)}.md-sidebar__scrollwrap::-webkit-scrollbar-thumb:hover{background-color:var(--md-accent-fg-color)}@supports selector(::-webkit-scrollbar){.md-sidebar__scrollwrap{scrollbar-gutter:auto}[dir=ltr] .md-sidebar__inner{padding-right:calc(100% - 11.5rem)}[dir=rtl] .md-sidebar__inner{padding-left:calc(100% - 11.5rem)}}@media screen and (max-width:76.1875em){.md-overlay{background-color:#0000008a;height:0;opacity:0;position:fixed;top:0;transition:width 0ms .25s,height 0ms .25s,opacity .25s;width:0;z-index:5}[data-md-toggle=drawer]:checked~.md-overlay{height:100%;opacity:1;transition:width 0ms,height 0ms,opacity .25s;width:100%}}@keyframes facts{0%{height:0}to{height:.65rem}}@keyframes fact{0%{opacity:0;transform:translateY(100%)}50%{opacity:0}to{opacity:1;transform:translateY(0)}}:root{--md-source-forks-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M5 3.25a.75.75 0 1 1-1.5 0 .75.75 0 0 1 1.5 0zm0 2.122a2.25 2.25 0 1 0-1.5 0v.878A2.25 2.25 0 0 0 5.75 8.5h1.5v2.128a2.251 2.251 0 1 0 1.5 0V8.5h1.5a2.25 2.25 0 0 0 2.25-2.25v-.878a2.25 2.25 0 1 0-1.5 0v.878a.75.75 0 0 1-.75.75h-4.5A.75.75 0 0 1 5 6.25v-.878zm3.75 7.378a.75.75 0 1 1-1.5 0 .75.75 0 0 1 1.5 0zm3-8.75a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5z"/></svg>');--md-source-repositories-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 1 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 0 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5v-9zm10.5-1V9h-8c-.356 0-.694.074-1 .208V2.5a1 1 0 0 1 1-1h8zM5 12.25v3.25a.25.25 0 0 0 .4.2l1.45-1.087a.25.25 0 0 1 .3 0L8.6 15.7a.25.25 0 0 0 .4-.2v-3.25a.25.25 0 0 0-.25-.25h-3.5a.25.25 0 0 0-.25.25z"/></svg>');--md-source-stars-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8 .25a.75.75 0 0 1 .673.418l1.882 3.815 4.21.612a.75.75 0 0 1 .416 1.279l-3.046 2.97.719 4.192a.75.75 0 0 1-1.088.791L8 12.347l-3.766 1.98a.75.75 0 0 1-1.088-.79l.72-4.194L.818 6.374a.75.75 0 0 1 .416-1.28l4.21-.611L7.327.668A.75.75 0 0 1 8 .25zm0 2.445L6.615 5.5a.75.75 0 0 1-.564.41l-3.097.45 2.24 2.184a.75.75 0 0 1 .216.664l-.528 3.084 2.769-1.456a.75.75 0 0 1 .698 0l2.77 1.456-.53-3.084a.75.75 0 0 1 .216-.664l2.24-2.183-3.096-.45a.75.75 0 0 1-.564-.41L8 2.694v.001z"/></svg>');--md-source-version-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M2.5 7.775V2.75a.25.25 0 0 1 .25-.25h5.025a.25.25 0 0 1 .177.073l6.25 6.25a.25.25 0 0 1 0 .354l-5.025 5.025a.25.25 0 0 1-.354 0l-6.25-6.25a.25.25 0 0 1-.073-.177zm-1.5 0V2.75C1 1.784 1.784 1 2.75 1h5.025c.464 0 .91.184 1.238.513l6.25 6.25a1.75 1.75 0 0 1 0 2.474l-5.026 5.026a1.75 1.75 0 0 1-2.474 0l-6.25-6.25A1.75 1.75 0 0 1 1 7.775zM6 5a1 1 0 1 0 0 2 1 1 0 0 0 0-2z"/></svg>')}.md-source{-webkit-backface-visibility:hidden;backface-visibility:hidden;display:block;font-size:.65rem;line-height:1.2;outline-color:var(--md-accent-fg-color);transition:opacity .25s;white-space:nowrap}.md-source:hover{opacity:.7}.md-source__icon{display:inline-block;height:2.4rem;vertical-align:middle;width:2rem}[dir=ltr] .md-source__icon svg{margin-left:.6rem}[dir=rtl] .md-source__icon svg{margin-right:.6rem}.md-source__icon svg{margin-top:.6rem}[dir=ltr] .md-source__icon+.md-source__repository{margin-left:-2rem}[dir=rtl] .md-source__icon+.md-source__repository{margin-right:-2rem}[dir=ltr] .md-source__icon+.md-source__repository{padding-left:2rem}[dir=rtl] .md-source__icon+.md-source__repository{padding-right:2rem}[dir=ltr] .md-source__repository{margin-left:.6rem}[dir=rtl] .md-source__repository{margin-right:.6rem}.md-source__repository{display:inline-block;max-width:calc(100% - 1.2rem);overflow:hidden;text-overflow:ellipsis;vertical-align:middle}.md-source__facts{display:flex;font-size:.55rem;gap:.4rem;list-style-type:none;margin:.1rem 0 0;opacity:.75;overflow:hidden;padding:0;width:100%}.md-source__repository--active .md-source__facts{animation:facts .25s ease-in}.md-source__fact{overflow:hidden;text-overflow:ellipsis}.md-source__repository--active .md-source__fact{animation:fact .4s ease-out}[dir=ltr] .md-source__fact:before{margin-right:.1rem}[dir=rtl] .md-source__fact:before{margin-left:.1rem}.md-source__fact:before{background-color:currentcolor;content:"";display:inline-block;height:.6rem;-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;vertical-align:text-top;width:.6rem}.md-source__fact:nth-child(1n+2){flex-shrink:0}.md-source__fact--version:before{-webkit-mask-image:var(--md-source-version-icon);mask-image:var(--md-source-version-icon)}.md-source__fact--stars:before{-webkit-mask-image:var(--md-source-stars-icon);mask-image:var(--md-source-stars-icon)}.md-source__fact--forks:before{-webkit-mask-image:var(--md-source-forks-icon);mask-image:var(--md-source-forks-icon)}.md-source__fact--repositories:before{-webkit-mask-image:var(--md-source-repositories-icon);mask-image:var(--md-source-repositories-icon)}.md-tabs{background-color:var(--md-primary-fg-color);color:var(--md-primary-bg-color);display:block;line-height:1.3;overflow:auto;width:100%;z-index:3}@media print{.md-tabs{display:none}}@media screen and (max-width:76.1875em){.md-tabs{display:none}}.md-tabs[hidden]{pointer-events:none}[dir=ltr] .md-tabs__list{margin-left:.2rem}[dir=rtl] .md-tabs__list{margin-right:.2rem}.md-tabs__list{contain:content;list-style:none;margin:0;padding:0;white-space:nowrap}.md-tabs__item{display:inline-block;height:2.4rem;padding-left:.6rem;padding-right:.6rem}.md-tabs__link{-webkit-backface-visibility:hidden;backface-visibility:hidden;display:block;font-size:.7rem;margin-top:.8rem;opacity:.7;outline-color:var(--md-accent-fg-color);outline-offset:.2rem;transition:transform .4s cubic-bezier(.1,.7,.1,1),opacity .25s}.md-tabs__link--active,.md-tabs__link:-webkit-any(:focus,:hover){color:inherit;opacity:1}.md-tabs__link--active,.md-tabs__link:-moz-any(:focus,:hover){color:inherit;opacity:1}.md-tabs__link--active,.md-tabs__link:is(:focus,:hover){color:inherit;opacity:1}.md-tabs__item:nth-child(2) .md-tabs__link{transition-delay:20ms}.md-tabs__item:nth-child(3) .md-tabs__link{transition-delay:40ms}.md-tabs__item:nth-child(4) .md-tabs__link{transition-delay:60ms}.md-tabs__item:nth-child(5) .md-tabs__link{transition-delay:80ms}.md-tabs__item:nth-child(6) .md-tabs__link{transition-delay:.1s}.md-tabs__item:nth-child(7) .md-tabs__link{transition-delay:.12s}.md-tabs__item:nth-child(8) .md-tabs__link{transition-delay:.14s}.md-tabs__item:nth-child(9) .md-tabs__link{transition-delay:.16s}.md-tabs__item:nth-child(10) .md-tabs__link{transition-delay:.18s}.md-tabs__item:nth-child(11) .md-tabs__link{transition-delay:.2s}.md-tabs__item:nth-child(12) .md-tabs__link{transition-delay:.22s}.md-tabs__item:nth-child(13) .md-tabs__link{transition-delay:.24s}.md-tabs__item:nth-child(14) .md-tabs__link{transition-delay:.26s}.md-tabs__item:nth-child(15) .md-tabs__link{transition-delay:.28s}.md-tabs__item:nth-child(16) .md-tabs__link{transition-delay:.3s}.md-tabs[hidden] .md-tabs__link{opacity:0;transform:translateY(50%);transition:transform 0ms .1s,opacity .1s}:root{--md-tag-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m5.41 21 .71-4h-4l.35-2h4l1.06-6h-4l.35-2h4l.71-4h2l-.71 4h6l.71-4h2l-.71 4h4l-.35 2h-4l-1.06 6h4l-.35 2h-4l-.71 4h-2l.71-4h-6l-.71 4h-2M9.53 9l-1.06 6h6l1.06-6h-6Z"/></svg>')}.md-typeset .md-tags{margin-bottom:.75em;margin-top:-.125em}[dir=ltr] .md-typeset .md-tag{margin-right:.5em}[dir=rtl] .md-typeset .md-tag{margin-left:.5em}.md-typeset .md-tag{background:var(--md-default-fg-color--lightest);border-radius:2.4rem;display:inline-block;font-size:.64rem;font-weight:700;letter-spacing:normal;line-height:1.6;margin-bottom:.5em;padding:.3125em .9375em;vertical-align:middle}.md-typeset .md-tag[href]{-webkit-tap-highlight-color:transparent;color:inherit;outline:none;transition:color 125ms,background-color 125ms}.md-typeset .md-tag[href]:focus,.md-typeset .md-tag[href]:hover{background-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}[id]>.md-typeset .md-tag{vertical-align:text-top}.md-typeset .md-tag-icon:before{background-color:var(--md-default-fg-color--lighter);content:"";display:inline-block;height:1.2em;margin-right:.4em;-webkit-mask-image:var(--md-tag-icon);mask-image:var(--md-tag-icon);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;transition:background-color 125ms;vertical-align:text-bottom;width:1.2em}.md-typeset .md-tag-icon:-webkit-any(a:focus,a:hover):before{background-color:var(--md-accent-bg-color)}.md-typeset .md-tag-icon:-moz-any(a:focus,a:hover):before{background-color:var(--md-accent-bg-color)}.md-typeset .md-tag-icon:is(a:focus,a:hover):before{background-color:var(--md-accent-bg-color)}@keyframes pulse{0%{box-shadow:0 0 0 0 var(--md-default-fg-color--lightest);transform:scale(.95)}75%{box-shadow:0 0 0 .625em #0000;transform:scale(1)}to{box-shadow:0 0 0 0 #0000;transform:scale(.95)}}:root{--md-tooltip-width:20rem}.md-tooltip{-webkit-backface-visibility:hidden;backface-visibility:hidden;background-color:var(--md-default-bg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z2);color:var(--md-default-fg-color);font-family:var(--md-text-font-family);left:clamp(var(--md-tooltip-0,0rem) + .8rem,var(--md-tooltip-x),100vw + var(--md-tooltip-0,0rem) + .8rem - var(--md-tooltip-width) - 2 * .8rem);max-width:calc(100vw - 1.6rem);opacity:0;position:absolute;top:var(--md-tooltip-y);transform:translateY(-.4rem);transition:transform 0ms .25s,opacity .25s,z-index .25s;width:var(--md-tooltip-width);z-index:0}.md-tooltip--active{opacity:1;transform:translateY(0);transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,z-index 0ms;z-index:2}:-webkit-any(.focus-visible>.md-tooltip,.md-tooltip:target){outline:var(--md-accent-fg-color) auto}:-moz-any(.focus-visible>.md-tooltip,.md-tooltip:target){outline:var(--md-accent-fg-color) auto}:is(.focus-visible>.md-tooltip,.md-tooltip:target){outline:var(--md-accent-fg-color) auto}.md-tooltip__inner{font-size:.64rem;padding:.8rem}.md-tooltip__inner.md-typeset>:first-child{margin-top:0}.md-tooltip__inner.md-typeset>:last-child{margin-bottom:0}.md-annotation{font-weight:400;outline:none;white-space:normal}[dir=rtl] .md-annotation{direction:rtl}.md-annotation:not([hidden]){display:inline-block;line-height:1.325}.md-annotation__index{cursor:pointer;font-family:var(--md-code-font-family);font-size:.85em;margin:0 1ch;outline:none;position:relative;-webkit-user-select:none;-moz-user-select:none;user-select:none;z-index:0}.md-annotation .md-annotation__index{color:#fff;transition:z-index .25s}.md-annotation .md-annotation__index:-webkit-any(:focus,:hover){color:#fff}.md-annotation .md-annotation__index:-moz-any(:focus,:hover){color:#fff}.md-annotation .md-annotation__index:is(:focus,:hover){color:#fff}.md-annotation__index:after{background-color:var(--md-default-fg-color--lighter);border-radius:2ch;content:"";height:2.2ch;left:-.125em;margin:0 -.4ch;padding:0 .4ch;position:absolute;top:0;transition:color .25s,background-color .25s;width:calc(100% + 1.2ch);width:max(2.2ch,100% + 1.2ch);z-index:-1}@media not all and (prefers-reduced-motion){[data-md-visible]>.md-annotation__index:after{animation:pulse 2s infinite}}.md-tooltip--active+.md-annotation__index:after{animation:none;transition:color .25s,background-color .25s}code .md-annotation__index{font-family:var(--md-code-font-family);font-size:inherit}:-webkit-any(.md-tooltip--active+.md-annotation__index,:hover>.md-annotation__index){color:var(--md-accent-bg-color)}:-moz-any(.md-tooltip--active+.md-annotation__index,:hover>.md-annotation__index){color:var(--md-accent-bg-color)}:is(.md-tooltip--active+.md-annotation__index,:hover>.md-annotation__index){color:var(--md-accent-bg-color)}:-webkit-any(.md-tooltip--active+.md-annotation__index,:hover>.md-annotation__index):after{background-color:var(--md-accent-fg-color)}:-moz-any(.md-tooltip--active+.md-annotation__index,:hover>.md-annotation__index):after{background-color:var(--md-accent-fg-color)}:is(.md-tooltip--active+.md-annotation__index,:hover>.md-annotation__index):after{background-color:var(--md-accent-fg-color)}.md-tooltip--active+.md-annotation__index{animation:none;transition:none;z-index:2}.md-annotation__index [data-md-annotation-id]{display:inline-block;line-height:90%}.md-annotation__index [data-md-annotation-id]:before{content:attr(data-md-annotation-id);display:inline-block;padding-bottom:.1em;transform:scale(1.15);transition:transform .4s cubic-bezier(.1,.7,.1,1);vertical-align:.065em}@media not print{.md-annotation__index [data-md-annotation-id]:before{content:"+"}:focus-within>.md-annotation__index [data-md-annotation-id]:before{transform:scale(1.25) rotate(45deg)}}[dir=ltr] .md-top{margin-left:50%}[dir=rtl] .md-top{margin-right:50%}.md-top{background-color:var(--md-default-bg-color);border-radius:1.6rem;box-shadow:var(--md-shadow-z2);color:var(--md-default-fg-color--light);display:block;font-size:.7rem;outline:none;padding:.4rem .8rem;position:fixed;top:3.2rem;transform:translate(-50%);transition:color 125ms,background-color 125ms,transform 125ms cubic-bezier(.4,0,.2,1),opacity 125ms;z-index:2}@media print{.md-top{display:none}}[dir=rtl] .md-top{transform:translate(50%)}.md-top[hidden]{opacity:0;pointer-events:none;transform:translate(-50%,.2rem);transition-duration:0ms}[dir=rtl] .md-top[hidden]{transform:translate(50%,.2rem)}.md-top:-webkit-any(:focus,:hover){background-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-top:-moz-any(:focus,:hover){background-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-top:is(:focus,:hover){background-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-top svg{display:inline-block;vertical-align:-.5em}@keyframes hoverfix{0%{pointer-events:none}}:root{--md-version-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9S301 191.9 288 191.9L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>')}.md-version{flex-shrink:0;font-size:.8rem;height:2.4rem}[dir=ltr] .md-version__current{margin-left:1.4rem;margin-right:.4rem}[dir=rtl] .md-version__current{margin-left:.4rem;margin-right:1.4rem}.md-version__current{color:inherit;cursor:pointer;outline:none;position:relative;top:.05rem}[dir=ltr] .md-version__current:after{margin-left:.4rem}[dir=rtl] .md-version__current:after{margin-right:.4rem}.md-version__current:after{background-color:currentcolor;content:"";display:inline-block;height:.6rem;-webkit-mask-image:var(--md-version-icon);mask-image:var(--md-version-icon);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:.4rem}.md-version__list{background-color:var(--md-default-bg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z2);color:var(--md-default-fg-color);list-style-type:none;margin:.2rem .8rem;max-height:0;opacity:0;overflow:auto;padding:0;position:absolute;scroll-snap-type:y mandatory;top:.15rem;transition:max-height 0ms .5s,opacity .25s .25s;z-index:3}.md-version:-webkit-any(:focus-within,:hover) .md-version__list{max-height:10rem;opacity:1;-webkit-transition:max-height 0ms,opacity .25s;transition:max-height 0ms,opacity .25s}.md-version:-moz-any(:focus-within,:hover) .md-version__list{max-height:10rem;opacity:1;-moz-transition:max-height 0ms,opacity .25s;transition:max-height 0ms,opacity .25s}.md-version:is(:focus-within,:hover) .md-version__list{max-height:10rem;opacity:1;transition:max-height 0ms,opacity .25s}@media (pointer:coarse){.md-version:hover .md-version__list{animation:hoverfix .25s forwards}.md-version:focus-within .md-version__list{animation:none}}.md-version__item{line-height:1.8rem}[dir=ltr] .md-version__link{padding-left:.6rem;padding-right:1.2rem}[dir=rtl] .md-version__link{padding-left:1.2rem;padding-right:.6rem}.md-version__link{cursor:pointer;display:block;outline:none;scroll-snap-align:start;transition:color .25s,background-color .25s;white-space:nowrap;width:100%}.md-version__link:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-version__link:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-version__link:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-version__link:focus{background-color:var(--md-default-fg-color--lightest)}:root{--md-admonition-icon--note:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M12 2C6.47 2 2 6.47 2 12s4.47 10 10 10 10-4.47 10-10S17.53 2 12 2m3.1 5.07c.14 0 .28.05.4.16l1.27 1.27c.23.22.23.57 0 .78l-1 1-2.05-2.05 1-1c.1-.11.24-.16.38-.16m-1.97 1.74 2.06 2.06-6.06 6.06H7.07v-2.06l6.06-6.06Z"/></svg>');--md-admonition-icon--abstract:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M17 9H7V7h10m0 6H7v-2h10m-3 6H7v-2h7M12 3a1 1 0 0 1 1 1 1 1 0 0 1-1 1 1 1 0 0 1-1-1 1 1 0 0 1 1-1m7 0h-4.18C14.4 1.84 13.3 1 12 1c-1.3 0-2.4.84-2.82 2H5a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2V5a2 2 0 0 0-2-2Z"/></svg>');--md-admonition-icon--info:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M13 9h-2V7h2m0 10h-2v-6h2m-1-9A10 10 0 0 0 2 12a10 10 0 0 0 10 10 10 10 0 0 0 10-10A10 10 0 0 0 12 2Z"/></svg>');--md-admonition-icon--tip:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M17.66 11.2c-.23-.3-.51-.56-.77-.82-.67-.6-1.43-1.03-2.07-1.66C13.33 7.26 13 4.85 13.95 3c-.95.23-1.78.75-2.49 1.32-2.59 2.08-3.61 5.75-2.39 8.9.04.1.08.2.08.33 0 .22-.15.42-.35.5-.23.1-.47.04-.66-.12a.58.58 0 0 1-.14-.17c-1.13-1.43-1.31-3.48-.55-5.12C5.78 10 4.87 12.3 5 14.47c.06.5.12 1 .29 1.5.14.6.41 1.2.71 1.73 1.08 1.73 2.95 2.97 4.96 3.22 2.14.27 4.43-.12 6.07-1.6 1.83-1.66 2.47-4.32 1.53-6.6l-.13-.26c-.21-.46-.77-1.26-.77-1.26m-3.16 6.3c-.28.24-.74.5-1.1.6-1.12.4-2.24-.16-2.9-.82 1.19-.28 1.9-1.16 2.11-2.05.17-.8-.15-1.46-.28-2.23-.12-.74-.1-1.37.17-2.06.19.38.39.76.63 1.06.77 1 1.98 1.44 2.24 2.8.04.14.06.28.06.43.03.82-.33 1.72-.93 2.27Z"/></svg>');--md-admonition-icon--success:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M21 7 9 19l-5.5-5.5 1.41-1.41L9 16.17 19.59 5.59 21 7Z"/></svg>');--md-admonition-icon--question:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m15.07 11.25-.9.92C13.45 12.89 13 13.5 13 15h-2v-.5c0-1.11.45-2.11 1.17-2.83l1.24-1.26c.37-.36.59-.86.59-1.41a2 2 0 0 0-2-2 2 2 0 0 0-2 2H8a4 4 0 0 1 4-4 4 4 0 0 1 4 4 3.2 3.2 0 0 1-.93 2.25M13 19h-2v-2h2M12 2A10 10 0 0 0 2 12a10 10 0 0 0 10 10 10 10 0 0 0 10-10c0-5.53-4.5-10-10-10Z"/></svg>');--md-admonition-icon--warning:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M13 14h-2V9h2m0 9h-2v-2h2M1 21h22L12 2 1 21Z"/></svg>');--md-admonition-icon--failure:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>');--md-admonition-icon--danger:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m11.5 20 4.86-9.73H13V4l-5 9.73h3.5V20M12 2c2.75 0 5.1 1 7.05 2.95C21 6.9 22 9.25 22 12s-1 5.1-2.95 7.05C17.1 21 14.75 22 12 22s-5.1-1-7.05-2.95C3 17.1 2 14.75 2 12s1-5.1 2.95-7.05C6.9 3 9.25 2 12 2Z"/></svg>');--md-admonition-icon--bug:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M11 13h2v1h-2v-1m10-8v6c0 5.5-3.8 10.7-9 12-5.2-1.3-9-6.5-9-12V5l9-4 9 4m-4 5h-2.2c-.2-.6-.6-1.1-1.1-1.5l1.2-1.2-.7-.7L12.8 8H12c-.2 0-.5 0-.7.1L9.9 6.6l-.8.8 1.2 1.2c-.5.3-.9.8-1.1 1.4H7v1h2v1H7v1h2v1H7v1h2.2c.4 1.2 1.5 2 2.8 2s2.4-.8 2.8-2H17v-1h-2v-1h2v-1h-2v-1h2v-1m-6 2h2v-1h-2v1Z"/></svg>');--md-admonition-icon--example:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M7 2v2h1v14a4 4 0 0 0 4 4 4 4 0 0 0 4-4V4h1V2H7m4 14c-.6 0-1-.4-1-1s.4-1 1-1 1 .4 1 1-.4 1-1 1m2-4c-.6 0-1-.4-1-1s.4-1 1-1 1 .4 1 1-.4 1-1 1m1-5h-4V4h4v3Z"/></svg>');--md-admonition-icon--quote:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M14 17h3l2-4V7h-6v6h3M6 17h3l2-4V7H5v6h3l-2 4Z"/></svg>')}.md-typeset .admonition,.md-typeset details{background-color:var(--md-admonition-bg-color);border:.05rem solid #448aff;border-radius:.2rem;box-shadow:var(--md-shadow-z1);color:var(--md-admonition-fg-color);display:flow-root;font-size:.64rem;margin:1.5625em 0;padding:0 .6rem;page-break-inside:avoid}@media print{.md-typeset .admonition,.md-typeset details{box-shadow:none}}.md-typeset .admonition>*,.md-typeset details>*{box-sizing:border-box}.md-typeset .admonition :-webkit-any(.admonition,details),.md-typeset details :-webkit-any(.admonition,details){margin-bottom:1em;margin-top:1em}.md-typeset .admonition :-moz-any(.admonition,details),.md-typeset details :-moz-any(.admonition,details){margin-bottom:1em;margin-top:1em}.md-typeset .admonition :is(.admonition,details),.md-typeset details :is(.admonition,details){margin-bottom:1em;margin-top:1em}.md-typeset .admonition .md-typeset__scrollwrap,.md-typeset details .md-typeset__scrollwrap{margin:1em -.6rem}.md-typeset .admonition .md-typeset__table,.md-typeset details .md-typeset__table{padding:0 .6rem}.md-typeset .admonition>.tabbed-set:only-child,.md-typeset details>.tabbed-set:only-child{margin-top:0}html .md-typeset .admonition>:last-child,html .md-typeset details>:last-child{margin-bottom:.6rem}[dir=ltr] .md-typeset .admonition-title,[dir=ltr] .md-typeset summary{padding-left:2rem;padding-right:.6rem}[dir=rtl] .md-typeset .admonition-title,[dir=rtl] .md-typeset summary{padding-left:.6rem;padding-right:2rem}[dir=ltr] .md-typeset .admonition-title,[dir=ltr] .md-typeset summary{border-left-width:.2rem}[dir=rtl] .md-typeset .admonition-title,[dir=rtl] .md-typeset summary{border-right-width:.2rem}[dir=ltr] .md-typeset .admonition-title,[dir=ltr] .md-typeset summary{border-top-left-radius:.1rem}[dir=ltr] .md-typeset .admonition-title,[dir=ltr] .md-typeset summary,[dir=rtl] .md-typeset .admonition-title,[dir=rtl] .md-typeset summary{border-top-right-radius:.1rem}[dir=rtl] .md-typeset .admonition-title,[dir=rtl] .md-typeset summary{border-top-left-radius:.1rem}.md-typeset .admonition-title,.md-typeset summary{background-color:#448aff1a;border:none;font-weight:700;margin:0 -.6rem;padding-bottom:.4rem;padding-top:.4rem;position:relative}html .md-typeset .admonition-title:last-child,html .md-typeset summary:last-child{margin-bottom:0}[dir=ltr] .md-typeset .admonition-title:before,[dir=ltr] .md-typeset summary:before{left:.6rem}[dir=rtl] .md-typeset .admonition-title:before,[dir=rtl] .md-typeset summary:before{right:.6rem}.md-typeset .admonition-title:before,.md-typeset summary:before{background-color:#448aff;content:"";height:1rem;-webkit-mask-image:var(--md-admonition-icon--note);mask-image:var(--md-admonition-icon--note);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;position:absolute;top:.625em;width:1rem}.md-typeset .admonition-title code,.md-typeset summary code{box-shadow:0 0 0 .05rem var(--md-default-fg-color--lightest)}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.note){border-color:#448aff}.md-typeset :-moz-any(.admonition,details):-moz-any(.note){border-color:#448aff}.md-typeset :is(.admonition,details):is(.note){border-color:#448aff}.md-typeset :-webkit-any(.note)>:-webkit-any(.admonition-title,summary){background-color:#448aff1a}.md-typeset :-moz-any(.note)>:-moz-any(.admonition-title,summary){background-color:#448aff1a}.md-typeset :is(.note)>:is(.admonition-title,summary){background-color:#448aff1a}.md-typeset :-webkit-any(.note)>:-webkit-any(.admonition-title,summary):before{background-color:#448aff;-webkit-mask-image:var(--md-admonition-icon--note);mask-image:var(--md-admonition-icon--note)}.md-typeset :-moz-any(.note)>:-moz-any(.admonition-title,summary):before{background-color:#448aff;mask-image:var(--md-admonition-icon--note)}.md-typeset :is(.note)>:is(.admonition-title,summary):before{background-color:#448aff;-webkit-mask-image:var(--md-admonition-icon--note);mask-image:var(--md-admonition-icon--note)}.md-typeset :-webkit-any(.note)>:-webkit-any(.admonition-title,summary):after{color:#448aff}.md-typeset :-moz-any(.note)>:-moz-any(.admonition-title,summary):after{color:#448aff}.md-typeset :is(.note)>:is(.admonition-title,summary):after{color:#448aff}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.abstract,.summary,.tldr){border-color:#00b0ff}.md-typeset :-moz-any(.admonition,details):-moz-any(.abstract,.summary,.tldr){border-color:#00b0ff}.md-typeset :is(.admonition,details):is(.abstract,.summary,.tldr){border-color:#00b0ff}.md-typeset :-webkit-any(.abstract,.summary,.tldr)>:-webkit-any(.admonition-title,summary){background-color:#00b0ff1a}.md-typeset :-moz-any(.abstract,.summary,.tldr)>:-moz-any(.admonition-title,summary){background-color:#00b0ff1a}.md-typeset :is(.abstract,.summary,.tldr)>:is(.admonition-title,summary){background-color:#00b0ff1a}.md-typeset :-webkit-any(.abstract,.summary,.tldr)>:-webkit-any(.admonition-title,summary):before{background-color:#00b0ff;-webkit-mask-image:var(--md-admonition-icon--abstract);mask-image:var(--md-admonition-icon--abstract)}.md-typeset :-moz-any(.abstract,.summary,.tldr)>:-moz-any(.admonition-title,summary):before{background-color:#00b0ff;mask-image:var(--md-admonition-icon--abstract)}.md-typeset :is(.abstract,.summary,.tldr)>:is(.admonition-title,summary):before{background-color:#00b0ff;-webkit-mask-image:var(--md-admonition-icon--abstract);mask-image:var(--md-admonition-icon--abstract)}.md-typeset :-webkit-any(.abstract,.summary,.tldr)>:-webkit-any(.admonition-title,summary):after{color:#00b0ff}.md-typeset :-moz-any(.abstract,.summary,.tldr)>:-moz-any(.admonition-title,summary):after{color:#00b0ff}.md-typeset :is(.abstract,.summary,.tldr)>:is(.admonition-title,summary):after{color:#00b0ff}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.info,.todo){border-color:#00b8d4}.md-typeset :-moz-any(.admonition,details):-moz-any(.info,.todo){border-color:#00b8d4}.md-typeset :is(.admonition,details):is(.info,.todo){border-color:#00b8d4}.md-typeset :-webkit-any(.info,.todo)>:-webkit-any(.admonition-title,summary){background-color:#00b8d41a}.md-typeset :-moz-any(.info,.todo)>:-moz-any(.admonition-title,summary){background-color:#00b8d41a}.md-typeset :is(.info,.todo)>:is(.admonition-title,summary){background-color:#00b8d41a}.md-typeset :-webkit-any(.info,.todo)>:-webkit-any(.admonition-title,summary):before{background-color:#00b8d4;-webkit-mask-image:var(--md-admonition-icon--info);mask-image:var(--md-admonition-icon--info)}.md-typeset :-moz-any(.info,.todo)>:-moz-any(.admonition-title,summary):before{background-color:#00b8d4;mask-image:var(--md-admonition-icon--info)}.md-typeset :is(.info,.todo)>:is(.admonition-title,summary):before{background-color:#00b8d4;-webkit-mask-image:var(--md-admonition-icon--info);mask-image:var(--md-admonition-icon--info)}.md-typeset :-webkit-any(.info,.todo)>:-webkit-any(.admonition-title,summary):after{color:#00b8d4}.md-typeset :-moz-any(.info,.todo)>:-moz-any(.admonition-title,summary):after{color:#00b8d4}.md-typeset :is(.info,.todo)>:is(.admonition-title,summary):after{color:#00b8d4}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.tip,.hint,.important){border-color:#00bfa5}.md-typeset :-moz-any(.admonition,details):-moz-any(.tip,.hint,.important){border-color:#00bfa5}.md-typeset :is(.admonition,details):is(.tip,.hint,.important){border-color:#00bfa5}.md-typeset :-webkit-any(.tip,.hint,.important)>:-webkit-any(.admonition-title,summary){background-color:#00bfa51a}.md-typeset :-moz-any(.tip,.hint,.important)>:-moz-any(.admonition-title,summary){background-color:#00bfa51a}.md-typeset :is(.tip,.hint,.important)>:is(.admonition-title,summary){background-color:#00bfa51a}.md-typeset :-webkit-any(.tip,.hint,.important)>:-webkit-any(.admonition-title,summary):before{background-color:#00bfa5;-webkit-mask-image:var(--md-admonition-icon--tip);mask-image:var(--md-admonition-icon--tip)}.md-typeset :-moz-any(.tip,.hint,.important)>:-moz-any(.admonition-title,summary):before{background-color:#00bfa5;mask-image:var(--md-admonition-icon--tip)}.md-typeset :is(.tip,.hint,.important)>:is(.admonition-title,summary):before{background-color:#00bfa5;-webkit-mask-image:var(--md-admonition-icon--tip);mask-image:var(--md-admonition-icon--tip)}.md-typeset :-webkit-any(.tip,.hint,.important)>:-webkit-any(.admonition-title,summary):after{color:#00bfa5}.md-typeset :-moz-any(.tip,.hint,.important)>:-moz-any(.admonition-title,summary):after{color:#00bfa5}.md-typeset :is(.tip,.hint,.important)>:is(.admonition-title,summary):after{color:#00bfa5}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.success,.check,.done){border-color:#00c853}.md-typeset :-moz-any(.admonition,details):-moz-any(.success,.check,.done){border-color:#00c853}.md-typeset :is(.admonition,details):is(.success,.check,.done){border-color:#00c853}.md-typeset :-webkit-any(.success,.check,.done)>:-webkit-any(.admonition-title,summary){background-color:#00c8531a}.md-typeset :-moz-any(.success,.check,.done)>:-moz-any(.admonition-title,summary){background-color:#00c8531a}.md-typeset :is(.success,.check,.done)>:is(.admonition-title,summary){background-color:#00c8531a}.md-typeset :-webkit-any(.success,.check,.done)>:-webkit-any(.admonition-title,summary):before{background-color:#00c853;-webkit-mask-image:var(--md-admonition-icon--success);mask-image:var(--md-admonition-icon--success)}.md-typeset :-moz-any(.success,.check,.done)>:-moz-any(.admonition-title,summary):before{background-color:#00c853;mask-image:var(--md-admonition-icon--success)}.md-typeset :is(.success,.check,.done)>:is(.admonition-title,summary):before{background-color:#00c853;-webkit-mask-image:var(--md-admonition-icon--success);mask-image:var(--md-admonition-icon--success)}.md-typeset :-webkit-any(.success,.check,.done)>:-webkit-any(.admonition-title,summary):after{color:#00c853}.md-typeset :-moz-any(.success,.check,.done)>:-moz-any(.admonition-title,summary):after{color:#00c853}.md-typeset :is(.success,.check,.done)>:is(.admonition-title,summary):after{color:#00c853}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.question,.help,.faq){border-color:#64dd17}.md-typeset :-moz-any(.admonition,details):-moz-any(.question,.help,.faq){border-color:#64dd17}.md-typeset :is(.admonition,details):is(.question,.help,.faq){border-color:#64dd17}.md-typeset :-webkit-any(.question,.help,.faq)>:-webkit-any(.admonition-title,summary){background-color:#64dd171a}.md-typeset :-moz-any(.question,.help,.faq)>:-moz-any(.admonition-title,summary){background-color:#64dd171a}.md-typeset :is(.question,.help,.faq)>:is(.admonition-title,summary){background-color:#64dd171a}.md-typeset :-webkit-any(.question,.help,.faq)>:-webkit-any(.admonition-title,summary):before{background-color:#64dd17;-webkit-mask-image:var(--md-admonition-icon--question);mask-image:var(--md-admonition-icon--question)}.md-typeset :-moz-any(.question,.help,.faq)>:-moz-any(.admonition-title,summary):before{background-color:#64dd17;mask-image:var(--md-admonition-icon--question)}.md-typeset :is(.question,.help,.faq)>:is(.admonition-title,summary):before{background-color:#64dd17;-webkit-mask-image:var(--md-admonition-icon--question);mask-image:var(--md-admonition-icon--question)}.md-typeset :-webkit-any(.question,.help,.faq)>:-webkit-any(.admonition-title,summary):after{color:#64dd17}.md-typeset :-moz-any(.question,.help,.faq)>:-moz-any(.admonition-title,summary):after{color:#64dd17}.md-typeset :is(.question,.help,.faq)>:is(.admonition-title,summary):after{color:#64dd17}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.warning,.caution,.attention){border-color:#ff9100}.md-typeset :-moz-any(.admonition,details):-moz-any(.warning,.caution,.attention){border-color:#ff9100}.md-typeset :is(.admonition,details):is(.warning,.caution,.attention){border-color:#ff9100}.md-typeset :-webkit-any(.warning,.caution,.attention)>:-webkit-any(.admonition-title,summary){background-color:#ff91001a}.md-typeset :-moz-any(.warning,.caution,.attention)>:-moz-any(.admonition-title,summary){background-color:#ff91001a}.md-typeset :is(.warning,.caution,.attention)>:is(.admonition-title,summary){background-color:#ff91001a}.md-typeset :-webkit-any(.warning,.caution,.attention)>:-webkit-any(.admonition-title,summary):before{background-color:#ff9100;-webkit-mask-image:var(--md-admonition-icon--warning);mask-image:var(--md-admonition-icon--warning)}.md-typeset :-moz-any(.warning,.caution,.attention)>:-moz-any(.admonition-title,summary):before{background-color:#ff9100;mask-image:var(--md-admonition-icon--warning)}.md-typeset :is(.warning,.caution,.attention)>:is(.admonition-title,summary):before{background-color:#ff9100;-webkit-mask-image:var(--md-admonition-icon--warning);mask-image:var(--md-admonition-icon--warning)}.md-typeset :-webkit-any(.warning,.caution,.attention)>:-webkit-any(.admonition-title,summary):after{color:#ff9100}.md-typeset :-moz-any(.warning,.caution,.attention)>:-moz-any(.admonition-title,summary):after{color:#ff9100}.md-typeset :is(.warning,.caution,.attention)>:is(.admonition-title,summary):after{color:#ff9100}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.failure,.fail,.missing){border-color:#ff5252}.md-typeset :-moz-any(.admonition,details):-moz-any(.failure,.fail,.missing){border-color:#ff5252}.md-typeset :is(.admonition,details):is(.failure,.fail,.missing){border-color:#ff5252}.md-typeset :-webkit-any(.failure,.fail,.missing)>:-webkit-any(.admonition-title,summary){background-color:#ff52521a}.md-typeset :-moz-any(.failure,.fail,.missing)>:-moz-any(.admonition-title,summary){background-color:#ff52521a}.md-typeset :is(.failure,.fail,.missing)>:is(.admonition-title,summary){background-color:#ff52521a}.md-typeset :-webkit-any(.failure,.fail,.missing)>:-webkit-any(.admonition-title,summary):before{background-color:#ff5252;-webkit-mask-image:var(--md-admonition-icon--failure);mask-image:var(--md-admonition-icon--failure)}.md-typeset :-moz-any(.failure,.fail,.missing)>:-moz-any(.admonition-title,summary):before{background-color:#ff5252;mask-image:var(--md-admonition-icon--failure)}.md-typeset :is(.failure,.fail,.missing)>:is(.admonition-title,summary):before{background-color:#ff5252;-webkit-mask-image:var(--md-admonition-icon--failure);mask-image:var(--md-admonition-icon--failure)}.md-typeset :-webkit-any(.failure,.fail,.missing)>:-webkit-any(.admonition-title,summary):after{color:#ff5252}.md-typeset :-moz-any(.failure,.fail,.missing)>:-moz-any(.admonition-title,summary):after{color:#ff5252}.md-typeset :is(.failure,.fail,.missing)>:is(.admonition-title,summary):after{color:#ff5252}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.danger,.error){border-color:#ff1744}.md-typeset :-moz-any(.admonition,details):-moz-any(.danger,.error){border-color:#ff1744}.md-typeset :is(.admonition,details):is(.danger,.error){border-color:#ff1744}.md-typeset :-webkit-any(.danger,.error)>:-webkit-any(.admonition-title,summary){background-color:#ff17441a}.md-typeset :-moz-any(.danger,.error)>:-moz-any(.admonition-title,summary){background-color:#ff17441a}.md-typeset :is(.danger,.error)>:is(.admonition-title,summary){background-color:#ff17441a}.md-typeset :-webkit-any(.danger,.error)>:-webkit-any(.admonition-title,summary):before{background-color:#ff1744;-webkit-mask-image:var(--md-admonition-icon--danger);mask-image:var(--md-admonition-icon--danger)}.md-typeset :-moz-any(.danger,.error)>:-moz-any(.admonition-title,summary):before{background-color:#ff1744;mask-image:var(--md-admonition-icon--danger)}.md-typeset :is(.danger,.error)>:is(.admonition-title,summary):before{background-color:#ff1744;-webkit-mask-image:var(--md-admonition-icon--danger);mask-image:var(--md-admonition-icon--danger)}.md-typeset :-webkit-any(.danger,.error)>:-webkit-any(.admonition-title,summary):after{color:#ff1744}.md-typeset :-moz-any(.danger,.error)>:-moz-any(.admonition-title,summary):after{color:#ff1744}.md-typeset :is(.danger,.error)>:is(.admonition-title,summary):after{color:#ff1744}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.bug){border-color:#f50057}.md-typeset :-moz-any(.admonition,details):-moz-any(.bug){border-color:#f50057}.md-typeset :is(.admonition,details):is(.bug){border-color:#f50057}.md-typeset :-webkit-any(.bug)>:-webkit-any(.admonition-title,summary){background-color:#f500571a}.md-typeset :-moz-any(.bug)>:-moz-any(.admonition-title,summary){background-color:#f500571a}.md-typeset :is(.bug)>:is(.admonition-title,summary){background-color:#f500571a}.md-typeset :-webkit-any(.bug)>:-webkit-any(.admonition-title,summary):before{background-color:#f50057;-webkit-mask-image:var(--md-admonition-icon--bug);mask-image:var(--md-admonition-icon--bug)}.md-typeset :-moz-any(.bug)>:-moz-any(.admonition-title,summary):before{background-color:#f50057;mask-image:var(--md-admonition-icon--bug)}.md-typeset :is(.bug)>:is(.admonition-title,summary):before{background-color:#f50057;-webkit-mask-image:var(--md-admonition-icon--bug);mask-image:var(--md-admonition-icon--bug)}.md-typeset :-webkit-any(.bug)>:-webkit-any(.admonition-title,summary):after{color:#f50057}.md-typeset :-moz-any(.bug)>:-moz-any(.admonition-title,summary):after{color:#f50057}.md-typeset :is(.bug)>:is(.admonition-title,summary):after{color:#f50057}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.example){border-color:#7c4dff}.md-typeset :-moz-any(.admonition,details):-moz-any(.example){border-color:#7c4dff}.md-typeset :is(.admonition,details):is(.example){border-color:#7c4dff}.md-typeset :-webkit-any(.example)>:-webkit-any(.admonition-title,summary){background-color:#7c4dff1a}.md-typeset :-moz-any(.example)>:-moz-any(.admonition-title,summary){background-color:#7c4dff1a}.md-typeset :is(.example)>:is(.admonition-title,summary){background-color:#7c4dff1a}.md-typeset :-webkit-any(.example)>:-webkit-any(.admonition-title,summary):before{background-color:#7c4dff;-webkit-mask-image:var(--md-admonition-icon--example);mask-image:var(--md-admonition-icon--example)}.md-typeset :-moz-any(.example)>:-moz-any(.admonition-title,summary):before{background-color:#7c4dff;mask-image:var(--md-admonition-icon--example)}.md-typeset :is(.example)>:is(.admonition-title,summary):before{background-color:#7c4dff;-webkit-mask-image:var(--md-admonition-icon--example);mask-image:var(--md-admonition-icon--example)}.md-typeset :-webkit-any(.example)>:-webkit-any(.admonition-title,summary):after{color:#7c4dff}.md-typeset :-moz-any(.example)>:-moz-any(.admonition-title,summary):after{color:#7c4dff}.md-typeset :is(.example)>:is(.admonition-title,summary):after{color:#7c4dff}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.quote,.cite){border-color:#9e9e9e}.md-typeset :-moz-any(.admonition,details):-moz-any(.quote,.cite){border-color:#9e9e9e}.md-typeset :is(.admonition,details):is(.quote,.cite){border-color:#9e9e9e}.md-typeset :-webkit-any(.quote,.cite)>:-webkit-any(.admonition-title,summary){background-color:#9e9e9e1a}.md-typeset :-moz-any(.quote,.cite)>:-moz-any(.admonition-title,summary){background-color:#9e9e9e1a}.md-typeset :is(.quote,.cite)>:is(.admonition-title,summary){background-color:#9e9e9e1a}.md-typeset :-webkit-any(.quote,.cite)>:-webkit-any(.admonition-title,summary):before{background-color:#9e9e9e;-webkit-mask-image:var(--md-admonition-icon--quote);mask-image:var(--md-admonition-icon--quote)}.md-typeset :-moz-any(.quote,.cite)>:-moz-any(.admonition-title,summary):before{background-color:#9e9e9e;mask-image:var(--md-admonition-icon--quote)}.md-typeset :is(.quote,.cite)>:is(.admonition-title,summary):before{background-color:#9e9e9e;-webkit-mask-image:var(--md-admonition-icon--quote);mask-image:var(--md-admonition-icon--quote)}.md-typeset :-webkit-any(.quote,.cite)>:-webkit-any(.admonition-title,summary):after{color:#9e9e9e}.md-typeset :-moz-any(.quote,.cite)>:-moz-any(.admonition-title,summary):after{color:#9e9e9e}.md-typeset :is(.quote,.cite)>:is(.admonition-title,summary):after{color:#9e9e9e}:root{--md-footnotes-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 7v4H5.83l3.58-3.59L8 6l-6 6 6 6 1.41-1.42L5.83 13H21V7h-2Z"/></svg>')}.md-typeset .footnote{color:var(--md-default-fg-color--light);font-size:.64rem}[dir=ltr] .md-typeset .footnote>ol{margin-left:0}[dir=rtl] .md-typeset .footnote>ol{margin-right:0}.md-typeset .footnote>ol>li{transition:color 125ms}.md-typeset .footnote>ol>li:target{color:var(--md-default-fg-color)}.md-typeset .footnote>ol>li:focus-within .footnote-backref{opacity:1;transform:translateX(0);transition:none}.md-typeset .footnote>ol>li:-webkit-any(:hover,:target) .footnote-backref{opacity:1;transform:translateX(0)}.md-typeset .footnote>ol>li:-moz-any(:hover,:target) .footnote-backref{opacity:1;transform:translateX(0)}.md-typeset .footnote>ol>li:is(:hover,:target) .footnote-backref{opacity:1;transform:translateX(0)}.md-typeset .footnote>ol>li>:first-child{margin-top:0}.md-typeset .footnote-ref{font-size:.75em;font-weight:700}html .md-typeset .footnote-ref{outline-offset:.1rem}.md-typeset [id^="fnref:"]:target>.footnote-ref{outline:auto}.md-typeset .footnote-backref{color:var(--md-typeset-a-color);display:inline-block;font-size:0;opacity:0;transform:translateX(.25rem);transition:color .25s,transform .25s .25s,opacity 125ms .25s;vertical-align:text-bottom}@media print{.md-typeset .footnote-backref{color:var(--md-typeset-a-color);opacity:1;transform:translateX(0)}}[dir=rtl] .md-typeset .footnote-backref{transform:translateX(-.25rem)}.md-typeset .footnote-backref:hover{color:var(--md-accent-fg-color)}.md-typeset .footnote-backref:before{background-color:currentcolor;content:"";display:inline-block;height:.8rem;-webkit-mask-image:var(--md-footnotes-icon);mask-image:var(--md-footnotes-icon);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:.8rem}[dir=rtl] .md-typeset .footnote-backref:before svg{transform:scaleX(-1)}[dir=ltr] .md-typeset .headerlink{margin-left:.5rem}[dir=rtl] .md-typeset .headerlink{margin-right:.5rem}.md-typeset .headerlink{color:var(--md-default-fg-color--lighter);display:inline-block;opacity:0;transition:color .25s,opacity 125ms}@media print{.md-typeset .headerlink{display:none}}.md-typeset .headerlink:focus,.md-typeset :-webkit-any(:hover,:target)>.headerlink{opacity:1;-webkit-transition:color .25s,opacity 125ms;transition:color .25s,opacity 125ms}.md-typeset .headerlink:focus,.md-typeset :-moz-any(:hover,:target)>.headerlink{opacity:1;-moz-transition:color .25s,opacity 125ms;transition:color .25s,opacity 125ms}.md-typeset .headerlink:focus,.md-typeset :is(:hover,:target)>.headerlink{opacity:1;transition:color .25s,opacity 125ms}.md-typeset .headerlink:-webkit-any(:focus,:hover),.md-typeset :target>.headerlink{color:var(--md-accent-fg-color)}.md-typeset .headerlink:-moz-any(:focus,:hover),.md-typeset :target>.headerlink{color:var(--md-accent-fg-color)}.md-typeset .headerlink:is(:focus,:hover),.md-typeset :target>.headerlink{color:var(--md-accent-fg-color)}.md-typeset :target{--md-scroll-margin:3.6rem;--md-scroll-offset:0rem;scroll-margin-top:calc(var(--md-scroll-margin) - var(--md-scroll-offset))}@media screen and (min-width:76.25em){.md-header--lifted~.md-container .md-typeset :target{--md-scroll-margin:6rem}}.md-typeset :-webkit-any(h1,h2,h3):target{--md-scroll-offset:0.2rem}.md-typeset :-moz-any(h1,h2,h3):target{--md-scroll-offset:0.2rem}.md-typeset :is(h1,h2,h3):target{--md-scroll-offset:0.2rem}.md-typeset h4:target{--md-scroll-offset:0.15rem}.md-typeset div.arithmatex{overflow:auto}@media screen and (max-width:44.9375em){.md-typeset div.arithmatex{margin:0 -.8rem}}.md-typeset div.arithmatex>*{margin-left:auto!important;margin-right:auto!important;padding:0 .8rem;touch-action:auto;width:-webkit-min-content;width:-moz-min-content;width:min-content}.md-typeset div.arithmatex>* mjx-container{margin:0!important}.md-typeset :-webkit-any(del,ins,.comment).critic{-webkit-box-decoration-break:clone;box-decoration-break:clone}.md-typeset :-moz-any(del,ins,.comment).critic{box-decoration-break:clone}.md-typeset :is(del,ins,.comment).critic{-webkit-box-decoration-break:clone;box-decoration-break:clone}.md-typeset del.critic{background-color:var(--md-typeset-del-color)}.md-typeset ins.critic{background-color:var(--md-typeset-ins-color)}.md-typeset .critic.comment{color:var(--md-code-hl-comment-color)}.md-typeset .critic.comment:before{content:"/* "}.md-typeset .critic.comment:after{content:" */"}.md-typeset .critic.block{box-shadow:none;display:block;margin:1em 0;overflow:auto;padding-left:.8rem;padding-right:.8rem}.md-typeset .critic.block>:first-child{margin-top:.5em}.md-typeset .critic.block>:last-child{margin-bottom:.5em}:root{--md-details-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M8.59 16.58 13.17 12 8.59 7.41 10 6l6 6-6 6-1.41-1.42Z"/></svg>')}.md-typeset details{display:flow-root;overflow:visible;padding-top:0}.md-typeset details[open]>summary:after{transform:rotate(90deg)}.md-typeset details:not([open]){box-shadow:none;padding-bottom:0}.md-typeset details:not([open])>summary{border-radius:.1rem}[dir=ltr] .md-typeset summary{padding-right:1.8rem}[dir=rtl] .md-typeset summary{padding-left:1.8rem}[dir=ltr] .md-typeset summary{border-top-left-radius:.1rem}[dir=ltr] .md-typeset summary,[dir=rtl] .md-typeset summary{border-top-right-radius:.1rem}[dir=rtl] .md-typeset summary{border-top-left-radius:.1rem}.md-typeset summary{cursor:pointer;display:block;min-height:1rem}.md-typeset summary.focus-visible{outline-color:var(--md-accent-fg-color);outline-offset:.2rem}.md-typeset summary:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}[dir=ltr] .md-typeset summary:after{right:.4rem}[dir=rtl] .md-typeset summary:after{left:.4rem}.md-typeset summary:after{background-color:currentcolor;content:"";height:1rem;-webkit-mask-image:var(--md-details-icon);mask-image:var(--md-details-icon);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;position:absolute;top:.625em;transform:rotate(0deg);transition:transform .25s;width:1rem}[dir=rtl] .md-typeset summary:after{transform:rotate(180deg)}.md-typeset summary::marker{display:none}.md-typeset summary::-webkit-details-marker{display:none}.md-typeset :-webkit-any(.emojione,.twemoji,.gemoji){display:inline-flex;height:1.125em;vertical-align:text-top}.md-typeset :-moz-any(.emojione,.twemoji,.gemoji){display:inline-flex;height:1.125em;vertical-align:text-top}.md-typeset :is(.emojione,.twemoji,.gemoji){display:inline-flex;height:1.125em;vertical-align:text-top}.md-typeset :-webkit-any(.emojione,.twemoji,.gemoji) svg{fill:currentcolor;max-height:100%;width:1.125em}.md-typeset :-moz-any(.emojione,.twemoji,.gemoji) svg{fill:currentcolor;max-height:100%;width:1.125em}.md-typeset :is(.emojione,.twemoji,.gemoji) svg{fill:currentcolor;max-height:100%;width:1.125em}.highlight :-webkit-any(.o,.ow){color:var(--md-code-hl-operator-color)}.highlight :-moz-any(.o,.ow){color:var(--md-code-hl-operator-color)}.highlight :is(.o,.ow){color:var(--md-code-hl-operator-color)}.highlight .p{color:var(--md-code-hl-punctuation-color)}.highlight :-webkit-any(.cpf,.l,.s,.sb,.sc,.s2,.si,.s1,.ss){color:var(--md-code-hl-string-color)}.highlight :-moz-any(.cpf,.l,.s,.sb,.sc,.s2,.si,.s1,.ss){color:var(--md-code-hl-string-color)}.highlight :is(.cpf,.l,.s,.sb,.sc,.s2,.si,.s1,.ss){color:var(--md-code-hl-string-color)}.highlight :-webkit-any(.cp,.se,.sh,.sr,.sx){color:var(--md-code-hl-special-color)}.highlight :-moz-any(.cp,.se,.sh,.sr,.sx){color:var(--md-code-hl-special-color)}.highlight :is(.cp,.se,.sh,.sr,.sx){color:var(--md-code-hl-special-color)}.highlight :-webkit-any(.m,.mb,.mf,.mh,.mi,.il,.mo){color:var(--md-code-hl-number-color)}.highlight :-moz-any(.m,.mb,.mf,.mh,.mi,.il,.mo){color:var(--md-code-hl-number-color)}.highlight :is(.m,.mb,.mf,.mh,.mi,.il,.mo){color:var(--md-code-hl-number-color)}.highlight :-webkit-any(.k,.kd,.kn,.kp,.kr,.kt){color:var(--md-code-hl-keyword-color)}.highlight :-moz-any(.k,.kd,.kn,.kp,.kr,.kt){color:var(--md-code-hl-keyword-color)}.highlight :is(.k,.kd,.kn,.kp,.kr,.kt){color:var(--md-code-hl-keyword-color)}.highlight :-webkit-any(.kc,.n){color:var(--md-code-hl-name-color)}.highlight :-moz-any(.kc,.n){color:var(--md-code-hl-name-color)}.highlight :is(.kc,.n){color:var(--md-code-hl-name-color)}.highlight :-webkit-any(.no,.nb,.bp){color:var(--md-code-hl-constant-color)}.highlight :-moz-any(.no,.nb,.bp){color:var(--md-code-hl-constant-color)}.highlight :is(.no,.nb,.bp){color:var(--md-code-hl-constant-color)}.highlight :-webkit-any(.nc,.ne,.nf,.nn){color:var(--md-code-hl-function-color)}.highlight :-moz-any(.nc,.ne,.nf,.nn){color:var(--md-code-hl-function-color)}.highlight :is(.nc,.ne,.nf,.nn){color:var(--md-code-hl-function-color)}.highlight :-webkit-any(.nd,.ni,.nl,.nt){color:var(--md-code-hl-keyword-color)}.highlight :-moz-any(.nd,.ni,.nl,.nt){color:var(--md-code-hl-keyword-color)}.highlight :is(.nd,.ni,.nl,.nt){color:var(--md-code-hl-keyword-color)}.highlight :-webkit-any(.c,.cm,.c1,.ch,.cs,.sd){color:var(--md-code-hl-comment-color)}.highlight :-moz-any(.c,.cm,.c1,.ch,.cs,.sd){color:var(--md-code-hl-comment-color)}.highlight :is(.c,.cm,.c1,.ch,.cs,.sd){color:var(--md-code-hl-comment-color)}.highlight :-webkit-any(.na,.nv,.vc,.vg,.vi){color:var(--md-code-hl-variable-color)}.highlight :-moz-any(.na,.nv,.vc,.vg,.vi){color:var(--md-code-hl-variable-color)}.highlight :is(.na,.nv,.vc,.vg,.vi){color:var(--md-code-hl-variable-color)}.highlight :-webkit-any(.ge,.gr,.gh,.go,.gp,.gs,.gu,.gt){color:var(--md-code-hl-generic-color)}.highlight :-moz-any(.ge,.gr,.gh,.go,.gp,.gs,.gu,.gt){color:var(--md-code-hl-generic-color)}.highlight :is(.ge,.gr,.gh,.go,.gp,.gs,.gu,.gt){color:var(--md-code-hl-generic-color)}.highlight :-webkit-any(.gd,.gi){border-radius:.1rem;margin:0 -.125em;padding:0 .125em}.highlight :-moz-any(.gd,.gi){border-radius:.1rem;margin:0 -.125em;padding:0 .125em}.highlight :is(.gd,.gi){border-radius:.1rem;margin:0 -.125em;padding:0 .125em}.highlight .gd{background-color:var(--md-typeset-del-color)}.highlight .gi{background-color:var(--md-typeset-ins-color)}.highlight .hll{background-color:var(--md-code-hl-color);display:block;margin:0 -1.1764705882em;padding:0 1.1764705882em}.highlight span.filename{background-color:var(--md-code-bg-color);border-bottom:.05rem solid var(--md-default-fg-color--lightest);border-top-left-radius:.1rem;border-top-right-radius:.1rem;display:flow-root;font-size:.85em;font-weight:700;margin-top:1em;padding:.6617647059em 1.1764705882em;position:relative}.highlight span.filename+pre{margin-top:0}.highlight span.filename+pre>code{border-top-left-radius:0;border-top-right-radius:0}.highlight [data-linenos]:before{background-color:var(--md-code-bg-color);box-shadow:-.05rem 0 var(--md-default-fg-color--lightest) inset;color:var(--md-default-fg-color--light);content:attr(data-linenos);float:left;left:-1.1764705882em;margin-left:-1.1764705882em;margin-right:1.1764705882em;padding-left:1.1764705882em;position:-webkit-sticky;position:sticky;-webkit-user-select:none;-moz-user-select:none;user-select:none;z-index:3}.highlight code a[id]{position:absolute;visibility:hidden}.highlight code[data-md-copying] .hll{display:contents}.highlight code[data-md-copying] .md-annotation{display:none}.highlighttable{display:flow-root}.highlighttable :-webkit-any(tbody,td){display:block;padding:0}.highlighttable :-moz-any(tbody,td){display:block;padding:0}.highlighttable :is(tbody,td){display:block;padding:0}.highlighttable tr{display:flex}.highlighttable pre{margin:0}.highlighttable th.filename{flex-grow:1;padding:0;text-align:left}.highlighttable th.filename span.filename{margin-top:0}.highlighttable .linenos{background-color:var(--md-code-bg-color);border-bottom-left-radius:.1rem;border-top-left-radius:.1rem;font-size:.85em;padding:.7720588235em 0 .7720588235em 1.1764705882em;-webkit-user-select:none;-moz-user-select:none;user-select:none}.highlighttable .linenodiv{box-shadow:-.05rem 0 var(--md-default-fg-color--lightest) inset;padding-right:.5882352941em}.highlighttable .linenodiv pre{color:var(--md-default-fg-color--light);text-align:right}.highlighttable .code{flex:1;min-width:0}.linenodiv a{color:inherit}.md-typeset .highlighttable{direction:ltr;margin:1em 0}.md-typeset .highlighttable>tbody>tr>.code>div>pre>code{border-bottom-left-radius:0;border-top-left-radius:0}.md-typeset .highlight+.result{border:.05rem solid var(--md-code-bg-color);border-bottom-left-radius:.1rem;border-bottom-right-radius:.1rem;border-top-width:.1rem;margin-top:-1.125em;overflow:visible;padding:0 1em}.md-typeset .highlight+.result:after{clear:both;content:"";display:block}@media screen and (max-width:44.9375em){.md-content__inner>.highlight{margin:1em -.8rem}.md-content__inner>.highlight>.filename,.md-content__inner>.highlight>.highlighttable>tbody>tr>.code>div>pre>code,.md-content__inner>.highlight>.highlighttable>tbody>tr>.filename span.filename,.md-content__inner>.highlight>.highlighttable>tbody>tr>.linenos,.md-content__inner>.highlight>pre>code{border-radius:0}.md-content__inner>.highlight+.result{border-left-width:0;border-radius:0;border-right-width:0;margin-left:-.8rem;margin-right:-.8rem}}.md-typeset .keys kbd:-webkit-any(:before,:after){-moz-osx-font-smoothing:initial;-webkit-font-smoothing:initial;color:inherit;margin:0;position:relative}.md-typeset .keys kbd:-moz-any(:before,:after){-moz-osx-font-smoothing:initial;-webkit-font-smoothing:initial;color:inherit;margin:0;position:relative}.md-typeset .keys kbd:is(:before,:after){-moz-osx-font-smoothing:initial;-webkit-font-smoothing:initial;color:inherit;margin:0;position:relative}.md-typeset .keys span{color:var(--md-default-fg-color--light);padding:0 .2em}.md-typeset .keys .key-alt:before,.md-typeset .keys .key-left-alt:before,.md-typeset .keys .key-right-alt:before{content:"⎇";padding-right:.4em}.md-typeset .keys .key-command:before,.md-typeset .keys .key-left-command:before,.md-typeset .keys .key-right-command:before{content:"⌘";padding-right:.4em}.md-typeset .keys .key-control:before,.md-typeset .keys .key-left-control:before,.md-typeset .keys .key-right-control:before{content:"⌃";padding-right:.4em}.md-typeset .keys .key-left-meta:before,.md-typeset .keys .key-meta:before,.md-typeset .keys .key-right-meta:before{content:"◆";padding-right:.4em}.md-typeset .keys .key-left-option:before,.md-typeset .keys .key-option:before,.md-typeset .keys .key-right-option:before{content:"⌥";padding-right:.4em}.md-typeset .keys .key-left-shift:before,.md-typeset .keys .key-right-shift:before,.md-typeset .keys .key-shift:before{content:"⇧";padding-right:.4em}.md-typeset .keys .key-left-super:before,.md-typeset .keys .key-right-super:before,.md-typeset .keys .key-super:before{content:"❖";padding-right:.4em}.md-typeset .keys .key-left-windows:before,.md-typeset .keys .key-right-windows:before,.md-typeset .keys .key-windows:before{content:"⊞";padding-right:.4em}.md-typeset .keys .key-arrow-down:before{content:"↓";padding-right:.4em}.md-typeset .keys .key-arrow-left:before{content:"←";padding-right:.4em}.md-typeset .keys .key-arrow-right:before{content:"→";padding-right:.4em}.md-typeset .keys .key-arrow-up:before{content:"↑";padding-right:.4em}.md-typeset .keys .key-backspace:before{content:"⌫";padding-right:.4em}.md-typeset .keys .key-backtab:before{content:"⇤";padding-right:.4em}.md-typeset .keys .key-caps-lock:before{content:"⇪";padding-right:.4em}.md-typeset .keys .key-clear:before{content:"⌧";padding-right:.4em}.md-typeset .keys .key-context-menu:before{content:"☰";padding-right:.4em}.md-typeset .keys .key-delete:before{content:"⌦";padding-right:.4em}.md-typeset .keys .key-eject:before{content:"⏏";padding-right:.4em}.md-typeset .keys .key-end:before{content:"⤓";padding-right:.4em}.md-typeset .keys .key-escape:before{content:"⎋";padding-right:.4em}.md-typeset .keys .key-home:before{content:"⤒";padding-right:.4em}.md-typeset .keys .key-insert:before{content:"⎀";padding-right:.4em}.md-typeset .keys .key-page-down:before{content:"⇟";padding-right:.4em}.md-typeset .keys .key-page-up:before{content:"⇞";padding-right:.4em}.md-typeset .keys .key-print-screen:before{content:"⎙";padding-right:.4em}.md-typeset .keys .key-tab:after{content:"⇥";padding-left:.4em}.md-typeset .keys .key-num-enter:after{content:"⌤";padding-left:.4em}.md-typeset .keys .key-enter:after{content:"⏎";padding-left:.4em}:root{--md-tabbed-icon--prev:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.41 16.58 10.83 12l4.58-4.59L14 6l-6 6 6 6 1.41-1.42Z"/></svg>');--md-tabbed-icon--next:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M8.59 16.58 13.17 12 8.59 7.41 10 6l6 6-6 6-1.41-1.42Z"/></svg>')}.md-typeset .tabbed-set{border-radius:.1rem;display:flex;flex-flow:column wrap;margin:1em 0;position:relative}.md-typeset .tabbed-set>input{height:0;opacity:0;position:absolute;width:0}.md-typeset .tabbed-set>input:target{--md-scroll-offset:0.625em}.md-typeset .tabbed-labels{-ms-overflow-style:none;box-shadow:0 -.05rem var(--md-default-fg-color--lightest) inset;display:flex;max-width:100%;overflow:auto;scrollbar-width:none}@media print{.md-typeset .tabbed-labels{display:contents}}@media screen{.js .md-typeset .tabbed-labels{position:relative}.js .md-typeset .tabbed-labels:before{background:var(--md-accent-fg-color);bottom:0;content:"";display:block;height:2px;left:0;position:absolute;transform:translateX(var(--md-indicator-x));transition:width 225ms,transform .25s;transition-timing-function:cubic-bezier(.4,0,.2,1);width:var(--md-indicator-width)}}.md-typeset .tabbed-labels::-webkit-scrollbar{display:none}.md-typeset .tabbed-labels>label{border-bottom:.1rem solid #0000;border-radius:.1rem .1rem 0 0;color:var(--md-default-fg-color--light);cursor:pointer;flex-shrink:0;font-size:.64rem;font-weight:700;padding:.78125em 1.25em .625em;scroll-margin-inline-start:1rem;transition:background-color .25s,color .25s;white-space:nowrap;width:auto}@media print{.md-typeset .tabbed-labels>label:first-child{order:1}.md-typeset .tabbed-labels>label:nth-child(2){order:2}.md-typeset .tabbed-labels>label:nth-child(3){order:3}.md-typeset .tabbed-labels>label:nth-child(4){order:4}.md-typeset .tabbed-labels>label:nth-child(5){order:5}.md-typeset .tabbed-labels>label:nth-child(6){order:6}.md-typeset .tabbed-labels>label:nth-child(7){order:7}.md-typeset .tabbed-labels>label:nth-child(8){order:8}.md-typeset .tabbed-labels>label:nth-child(9){order:9}.md-typeset .tabbed-labels>label:nth-child(10){order:10}.md-typeset .tabbed-labels>label:nth-child(11){order:11}.md-typeset .tabbed-labels>label:nth-child(12){order:12}.md-typeset .tabbed-labels>label:nth-child(13){order:13}.md-typeset .tabbed-labels>label:nth-child(14){order:14}.md-typeset .tabbed-labels>label:nth-child(15){order:15}.md-typeset .tabbed-labels>label:nth-child(16){order:16}.md-typeset .tabbed-labels>label:nth-child(17){order:17}.md-typeset .tabbed-labels>label:nth-child(18){order:18}.md-typeset .tabbed-labels>label:nth-child(19){order:19}.md-typeset .tabbed-labels>label:nth-child(20){order:20}}.md-typeset .tabbed-labels>label:hover{color:var(--md-accent-fg-color)}.md-typeset .tabbed-content{width:100%}@media print{.md-typeset .tabbed-content{display:contents}}.md-typeset .tabbed-block{display:none}@media print{.md-typeset .tabbed-block{display:block}.md-typeset .tabbed-block:first-child{order:1}.md-typeset .tabbed-block:nth-child(2){order:2}.md-typeset .tabbed-block:nth-child(3){order:3}.md-typeset .tabbed-block:nth-child(4){order:4}.md-typeset .tabbed-block:nth-child(5){order:5}.md-typeset .tabbed-block:nth-child(6){order:6}.md-typeset .tabbed-block:nth-child(7){order:7}.md-typeset .tabbed-block:nth-child(8){order:8}.md-typeset .tabbed-block:nth-child(9){order:9}.md-typeset .tabbed-block:nth-child(10){order:10}.md-typeset .tabbed-block:nth-child(11){order:11}.md-typeset .tabbed-block:nth-child(12){order:12}.md-typeset .tabbed-block:nth-child(13){order:13}.md-typeset .tabbed-block:nth-child(14){order:14}.md-typeset .tabbed-block:nth-child(15){order:15}.md-typeset .tabbed-block:nth-child(16){order:16}.md-typeset .tabbed-block:nth-child(17){order:17}.md-typeset .tabbed-block:nth-child(18){order:18}.md-typeset .tabbed-block:nth-child(19){order:19}.md-typeset .tabbed-block:nth-child(20){order:20}}.md-typeset .tabbed-block>.highlight:first-child>pre,.md-typeset .tabbed-block>pre:first-child{margin:0}.md-typeset .tabbed-block>.highlight:first-child>pre>code,.md-typeset .tabbed-block>pre:first-child>code{border-top-left-radius:0;border-top-right-radius:0}.md-typeset .tabbed-block>.highlight:first-child>.filename{border-top-left-radius:0;border-top-right-radius:0;margin:0}.md-typeset .tabbed-block>.highlight:first-child>.highlighttable{margin:0}.md-typeset .tabbed-block>.highlight:first-child>.highlighttable>tbody>tr>.filename span.filename,.md-typeset .tabbed-block>.highlight:first-child>.highlighttable>tbody>tr>.linenos{border-top-left-radius:0;border-top-right-radius:0;margin:0}.md-typeset .tabbed-block>.highlight:first-child>.highlighttable>tbody>tr>.code>div>pre>code{border-top-left-radius:0;border-top-right-radius:0}.md-typeset .tabbed-block>.highlight:first-child+.result{margin-top:-.125em}.md-typeset .tabbed-block>.tabbed-set{margin:0}.md-typeset .tabbed-button{align-self:center;border-radius:100%;color:var(--md-default-fg-color--light);cursor:pointer;display:block;height:.9rem;margin-top:.1rem;pointer-events:auto;transition:background-color .25s;width:.9rem}.md-typeset .tabbed-button:hover{background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-typeset .tabbed-button:after{background-color:currentcolor;content:"";display:block;height:100%;-webkit-mask-image:var(--md-tabbed-icon--prev);mask-image:var(--md-tabbed-icon--prev);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;transition:background-color .25s,transform .25s;width:100%}.md-typeset .tabbed-control{background:linear-gradient(to right,var(--md-default-bg-color) 60%,#0000);display:flex;height:1.9rem;justify-content:start;pointer-events:none;position:absolute;transition:opacity 125ms;width:1.2rem}[dir=rtl] .md-typeset .tabbed-control{transform:rotate(180deg)}.md-typeset .tabbed-control[hidden]{opacity:0}.md-typeset .tabbed-control--next{background:linear-gradient(to left,var(--md-default-bg-color) 60%,#0000);justify-content:end;right:0}.md-typeset .tabbed-control--next .tabbed-button:after{-webkit-mask-image:var(--md-tabbed-icon--next);mask-image:var(--md-tabbed-icon--next)}@media screen and (max-width:44.9375em){[dir=ltr] .md-content__inner>.tabbed-set .tabbed-labels{padding-left:.8rem}[dir=rtl] .md-content__inner>.tabbed-set .tabbed-labels{padding-right:.8rem}.md-content__inner>.tabbed-set .tabbed-labels{margin:0 -.8rem;max-width:100vw;scroll-padding-inline-start:.8rem}[dir=ltr] .md-content__inner>.tabbed-set .tabbed-labels:after{padding-right:.8rem}[dir=rtl] .md-content__inner>.tabbed-set .tabbed-labels:after{padding-left:.8rem}.md-content__inner>.tabbed-set .tabbed-labels:after{content:""}[dir=ltr] .md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--prev{margin-left:-.8rem}[dir=rtl] .md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--prev{margin-right:-.8rem}[dir=ltr] .md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--prev{padding-left:.8rem}[dir=rtl] .md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--prev{padding-right:.8rem}.md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--prev{width:2rem}[dir=ltr] .md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--next{margin-right:-.8rem}[dir=rtl] .md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--next{margin-left:-.8rem}[dir=ltr] .md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--next{padding-right:.8rem}[dir=rtl] .md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--next{padding-left:.8rem}.md-content__inner>.tabbed-set .tabbed-labels~.tabbed-control--next{width:2rem}}@media screen{.md-typeset .tabbed-set>input:first-child:checked~.tabbed-labels>:first-child,.md-typeset .tabbed-set>input:nth-child(10):checked~.tabbed-labels>:nth-child(10),.md-typeset .tabbed-set>input:nth-child(11):checked~.tabbed-labels>:nth-child(11),.md-typeset .tabbed-set>input:nth-child(12):checked~.tabbed-labels>:nth-child(12),.md-typeset .tabbed-set>input:nth-child(13):checked~.tabbed-labels>:nth-child(13),.md-typeset .tabbed-set>input:nth-child(14):checked~.tabbed-labels>:nth-child(14),.md-typeset .tabbed-set>input:nth-child(15):checked~.tabbed-labels>:nth-child(15),.md-typeset .tabbed-set>input:nth-child(16):checked~.tabbed-labels>:nth-child(16),.md-typeset .tabbed-set>input:nth-child(17):checked~.tabbed-labels>:nth-child(17),.md-typeset .tabbed-set>input:nth-child(18):checked~.tabbed-labels>:nth-child(18),.md-typeset .tabbed-set>input:nth-child(19):checked~.tabbed-labels>:nth-child(19),.md-typeset .tabbed-set>input:nth-child(2):checked~.tabbed-labels>:nth-child(2),.md-typeset .tabbed-set>input:nth-child(20):checked~.tabbed-labels>:nth-child(20),.md-typeset .tabbed-set>input:nth-child(3):checked~.tabbed-labels>:nth-child(3),.md-typeset .tabbed-set>input:nth-child(4):checked~.tabbed-labels>:nth-child(4),.md-typeset .tabbed-set>input:nth-child(5):checked~.tabbed-labels>:nth-child(5),.md-typeset .tabbed-set>input:nth-child(6):checked~.tabbed-labels>:nth-child(6),.md-typeset .tabbed-set>input:nth-child(7):checked~.tabbed-labels>:nth-child(7),.md-typeset .tabbed-set>input:nth-child(8):checked~.tabbed-labels>:nth-child(8),.md-typeset .tabbed-set>input:nth-child(9):checked~.tabbed-labels>:nth-child(9){color:var(--md-accent-fg-color)}.md-typeset .no-js .tabbed-set>input:first-child:checked~.tabbed-labels>:first-child,.md-typeset .no-js .tabbed-set>input:nth-child(10):checked~.tabbed-labels>:nth-child(10),.md-typeset .no-js .tabbed-set>input:nth-child(11):checked~.tabbed-labels>:nth-child(11),.md-typeset .no-js .tabbed-set>input:nth-child(12):checked~.tabbed-labels>:nth-child(12),.md-typeset .no-js .tabbed-set>input:nth-child(13):checked~.tabbed-labels>:nth-child(13),.md-typeset .no-js .tabbed-set>input:nth-child(14):checked~.tabbed-labels>:nth-child(14),.md-typeset .no-js .tabbed-set>input:nth-child(15):checked~.tabbed-labels>:nth-child(15),.md-typeset .no-js .tabbed-set>input:nth-child(16):checked~.tabbed-labels>:nth-child(16),.md-typeset .no-js .tabbed-set>input:nth-child(17):checked~.tabbed-labels>:nth-child(17),.md-typeset .no-js .tabbed-set>input:nth-child(18):checked~.tabbed-labels>:nth-child(18),.md-typeset .no-js .tabbed-set>input:nth-child(19):checked~.tabbed-labels>:nth-child(19),.md-typeset .no-js .tabbed-set>input:nth-child(2):checked~.tabbed-labels>:nth-child(2),.md-typeset .no-js .tabbed-set>input:nth-child(20):checked~.tabbed-labels>:nth-child(20),.md-typeset .no-js .tabbed-set>input:nth-child(3):checked~.tabbed-labels>:nth-child(3),.md-typeset .no-js .tabbed-set>input:nth-child(4):checked~.tabbed-labels>:nth-child(4),.md-typeset .no-js .tabbed-set>input:nth-child(5):checked~.tabbed-labels>:nth-child(5),.md-typeset .no-js .tabbed-set>input:nth-child(6):checked~.tabbed-labels>:nth-child(6),.md-typeset .no-js .tabbed-set>input:nth-child(7):checked~.tabbed-labels>:nth-child(7),.md-typeset .no-js .tabbed-set>input:nth-child(8):checked~.tabbed-labels>:nth-child(8),.md-typeset .no-js .tabbed-set>input:nth-child(9):checked~.tabbed-labels>:nth-child(9),.no-js .md-typeset .tabbed-set>input:first-child:checked~.tabbed-labels>:first-child,.no-js .md-typeset .tabbed-set>input:nth-child(10):checked~.tabbed-labels>:nth-child(10),.no-js .md-typeset .tabbed-set>input:nth-child(11):checked~.tabbed-labels>:nth-child(11),.no-js .md-typeset .tabbed-set>input:nth-child(12):checked~.tabbed-labels>:nth-child(12),.no-js .md-typeset .tabbed-set>input:nth-child(13):checked~.tabbed-labels>:nth-child(13),.no-js .md-typeset .tabbed-set>input:nth-child(14):checked~.tabbed-labels>:nth-child(14),.no-js .md-typeset .tabbed-set>input:nth-child(15):checked~.tabbed-labels>:nth-child(15),.no-js .md-typeset .tabbed-set>input:nth-child(16):checked~.tabbed-labels>:nth-child(16),.no-js .md-typeset .tabbed-set>input:nth-child(17):checked~.tabbed-labels>:nth-child(17),.no-js .md-typeset .tabbed-set>input:nth-child(18):checked~.tabbed-labels>:nth-child(18),.no-js .md-typeset .tabbed-set>input:nth-child(19):checked~.tabbed-labels>:nth-child(19),.no-js .md-typeset .tabbed-set>input:nth-child(2):checked~.tabbed-labels>:nth-child(2),.no-js .md-typeset .tabbed-set>input:nth-child(20):checked~.tabbed-labels>:nth-child(20),.no-js .md-typeset .tabbed-set>input:nth-child(3):checked~.tabbed-labels>:nth-child(3),.no-js .md-typeset .tabbed-set>input:nth-child(4):checked~.tabbed-labels>:nth-child(4),.no-js .md-typeset .tabbed-set>input:nth-child(5):checked~.tabbed-labels>:nth-child(5),.no-js .md-typeset .tabbed-set>input:nth-child(6):checked~.tabbed-labels>:nth-child(6),.no-js .md-typeset .tabbed-set>input:nth-child(7):checked~.tabbed-labels>:nth-child(7),.no-js .md-typeset .tabbed-set>input:nth-child(8):checked~.tabbed-labels>:nth-child(8),.no-js .md-typeset .tabbed-set>input:nth-child(9):checked~.tabbed-labels>:nth-child(9){border-color:var(--md-accent-fg-color)}}.md-typeset .tabbed-set>input:first-child.focus-visible~.tabbed-labels>:first-child,.md-typeset .tabbed-set>input:nth-child(10).focus-visible~.tabbed-labels>:nth-child(10),.md-typeset .tabbed-set>input:nth-child(11).focus-visible~.tabbed-labels>:nth-child(11),.md-typeset .tabbed-set>input:nth-child(12).focus-visible~.tabbed-labels>:nth-child(12),.md-typeset .tabbed-set>input:nth-child(13).focus-visible~.tabbed-labels>:nth-child(13),.md-typeset .tabbed-set>input:nth-child(14).focus-visible~.tabbed-labels>:nth-child(14),.md-typeset .tabbed-set>input:nth-child(15).focus-visible~.tabbed-labels>:nth-child(15),.md-typeset .tabbed-set>input:nth-child(16).focus-visible~.tabbed-labels>:nth-child(16),.md-typeset .tabbed-set>input:nth-child(17).focus-visible~.tabbed-labels>:nth-child(17),.md-typeset .tabbed-set>input:nth-child(18).focus-visible~.tabbed-labels>:nth-child(18),.md-typeset .tabbed-set>input:nth-child(19).focus-visible~.tabbed-labels>:nth-child(19),.md-typeset .tabbed-set>input:nth-child(2).focus-visible~.tabbed-labels>:nth-child(2),.md-typeset .tabbed-set>input:nth-child(20).focus-visible~.tabbed-labels>:nth-child(20),.md-typeset .tabbed-set>input:nth-child(3).focus-visible~.tabbed-labels>:nth-child(3),.md-typeset .tabbed-set>input:nth-child(4).focus-visible~.tabbed-labels>:nth-child(4),.md-typeset .tabbed-set>input:nth-child(5).focus-visible~.tabbed-labels>:nth-child(5),.md-typeset .tabbed-set>input:nth-child(6).focus-visible~.tabbed-labels>:nth-child(6),.md-typeset .tabbed-set>input:nth-child(7).focus-visible~.tabbed-labels>:nth-child(7),.md-typeset .tabbed-set>input:nth-child(8).focus-visible~.tabbed-labels>:nth-child(8),.md-typeset .tabbed-set>input:nth-child(9).focus-visible~.tabbed-labels>:nth-child(9){background-color:var(--md-accent-fg-color--transparent)}.md-typeset .tabbed-set>input:first-child:checked~.tabbed-content>:first-child,.md-typeset .tabbed-set>input:nth-child(10):checked~.tabbed-content>:nth-child(10),.md-typeset .tabbed-set>input:nth-child(11):checked~.tabbed-content>:nth-child(11),.md-typeset .tabbed-set>input:nth-child(12):checked~.tabbed-content>:nth-child(12),.md-typeset .tabbed-set>input:nth-child(13):checked~.tabbed-content>:nth-child(13),.md-typeset .tabbed-set>input:nth-child(14):checked~.tabbed-content>:nth-child(14),.md-typeset .tabbed-set>input:nth-child(15):checked~.tabbed-content>:nth-child(15),.md-typeset .tabbed-set>input:nth-child(16):checked~.tabbed-content>:nth-child(16),.md-typeset .tabbed-set>input:nth-child(17):checked~.tabbed-content>:nth-child(17),.md-typeset .tabbed-set>input:nth-child(18):checked~.tabbed-content>:nth-child(18),.md-typeset .tabbed-set>input:nth-child(19):checked~.tabbed-content>:nth-child(19),.md-typeset .tabbed-set>input:nth-child(2):checked~.tabbed-content>:nth-child(2),.md-typeset .tabbed-set>input:nth-child(20):checked~.tabbed-content>:nth-child(20),.md-typeset .tabbed-set>input:nth-child(3):checked~.tabbed-content>:nth-child(3),.md-typeset .tabbed-set>input:nth-child(4):checked~.tabbed-content>:nth-child(4),.md-typeset .tabbed-set>input:nth-child(5):checked~.tabbed-content>:nth-child(5),.md-typeset .tabbed-set>input:nth-child(6):checked~.tabbed-content>:nth-child(6),.md-typeset .tabbed-set>input:nth-child(7):checked~.tabbed-content>:nth-child(7),.md-typeset .tabbed-set>input:nth-child(8):checked~.tabbed-content>:nth-child(8),.md-typeset .tabbed-set>input:nth-child(9):checked~.tabbed-content>:nth-child(9){display:block}:root{--md-tasklist-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path fill-rule="evenodd" d="M1 12C1 5.925 5.925 1 12 1s11 4.925 11 11-4.925 11-11 11S1 18.075 1 12zm16.28-2.72a.75.75 0 0 0-1.06-1.06l-5.97 5.97-2.47-2.47a.75.75 0 0 0-1.06 1.06l3 3a.75.75 0 0 0 1.06 0l6.5-6.5z"/></svg>');--md-tasklist-icon--checked:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path fill-rule="evenodd" d="M1 12C1 5.925 5.925 1 12 1s11 4.925 11 11-4.925 11-11 11S1 18.075 1 12zm16.28-2.72a.75.75 0 0 0-1.06-1.06l-5.97 5.97-2.47-2.47a.75.75 0 0 0-1.06 1.06l3 3a.75.75 0 0 0 1.06 0l6.5-6.5z"/></svg>')}.md-typeset .task-list-item{list-style-type:none;position:relative}[dir=ltr] .md-typeset .task-list-item [type=checkbox]{left:-2em}[dir=rtl] .md-typeset .task-list-item [type=checkbox]{right:-2em}.md-typeset .task-list-item [type=checkbox]{position:absolute;top:.45em}.md-typeset .task-list-control [type=checkbox]{opacity:0;z-index:-1}[dir=ltr] .md-typeset .task-list-indicator:before{left:-1.5em}[dir=rtl] .md-typeset .task-list-indicator:before{right:-1.5em}.md-typeset .task-list-indicator:before{background-color:var(--md-default-fg-color--lightest);content:"";height:1.25em;-webkit-mask-image:var(--md-tasklist-icon);mask-image:var(--md-tasklist-icon);-webkit-mask-position:center;mask-position:center;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;position:absolute;top:.15em;width:1.25em}.md-typeset [type=checkbox]:checked+.task-list-indicator:before{background-color:#00e676;-webkit-mask-image:var(--md-tasklist-icon--checked);mask-image:var(--md-tasklist-icon--checked)}:root>*{--md-mermaid-font-family:var(--md-text-font-family),sans-serif;--md-mermaid-edge-color:var(--md-code-fg-color);--md-mermaid-node-bg-color:var(--md-accent-fg-color--transparent);--md-mermaid-node-fg-color:var(--md-accent-fg-color);--md-mermaid-label-bg-color:var(--md-default-bg-color);--md-mermaid-label-fg-color:var(--md-code-fg-color)}.mermaid{line-height:normal;margin:1em 0}@media screen and (min-width:45em){[dir=ltr] .md-typeset .inline{float:left}[dir=rtl] .md-typeset .inline{float:right}[dir=ltr] .md-typeset .inline{margin-right:.8rem}[dir=rtl] .md-typeset .inline{margin-left:.8rem}.md-typeset .inline{margin-bottom:.8rem;margin-top:0;width:11.7rem}[dir=ltr] .md-typeset .inline.end{float:right}[dir=rtl] .md-typeset .inline.end{float:left}[dir=ltr] .md-typeset .inline.end{margin-left:.8rem;margin-right:0}[dir=rtl] .md-typeset .inline.end{margin-left:0;margin-right:.8rem}}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/main.975780f9.min.css.map b/7.3/assets/stylesheets/main.975780f9.min.css.map
new file mode 100644
index 0000000000..5e13ffb9cb
--- /dev/null
+++ b/7.3/assets/stylesheets/main.975780f9.min.css.map
@@ -0,0 +1 @@
+{"version":3,"sources":["src/assets/stylesheets/main/extensions/pymdownx/_keys.scss","../../../src/assets/stylesheets/main.scss","src/assets/stylesheets/main/_resets.scss","src/assets/stylesheets/main/_colors.scss","src/assets/stylesheets/main/_icons.scss","src/assets/stylesheets/main/_typeset.scss","src/assets/stylesheets/utilities/_break.scss","src/assets/stylesheets/main/layout/_banner.scss","src/assets/stylesheets/main/layout/_base.scss","src/assets/stylesheets/main/layout/_clipboard.scss","src/assets/stylesheets/main/layout/_consent.scss","src/assets/stylesheets/main/layout/_content.scss","src/assets/stylesheets/main/layout/_dialog.scss","src/assets/stylesheets/main/layout/_feedback.scss","src/assets/stylesheets/main/layout/_footer.scss","src/assets/stylesheets/main/layout/_form.scss","src/assets/stylesheets/main/layout/_header.scss","src/assets/stylesheets/main/layout/_nav.scss","src/assets/stylesheets/main/layout/_search.scss","src/assets/stylesheets/main/layout/_select.scss","src/assets/stylesheets/main/layout/_sidebar.scss","src/assets/stylesheets/main/layout/_source.scss","src/assets/stylesheets/main/layout/_tabs.scss","src/assets/stylesheets/main/layout/_tag.scss","src/assets/stylesheets/main/layout/_tooltip.scss","src/assets/stylesheets/main/layout/_top.scss","src/assets/stylesheets/main/layout/_version.scss","src/assets/stylesheets/main/extensions/markdown/_admonition.scss","node_modules/material-design-color/material-color.scss","src/assets/stylesheets/main/extensions/markdown/_footnotes.scss","src/assets/stylesheets/main/extensions/markdown/_toc.scss","src/assets/stylesheets/main/extensions/pymdownx/_arithmatex.scss","src/assets/stylesheets/main/extensions/pymdownx/_critic.scss","src/assets/stylesheets/main/extensions/pymdownx/_details.scss","src/assets/stylesheets/main/extensions/pymdownx/_emoji.scss","src/assets/stylesheets/main/extensions/pymdownx/_highlight.scss","src/assets/stylesheets/main/extensions/pymdownx/_tabbed.scss","src/assets/stylesheets/main/extensions/pymdownx/_tasklist.scss","src/assets/stylesheets/main/integrations/_mermaid.scss","src/assets/stylesheets/main/_modifiers.scss"],"names":[],"mappings":"AAgGM,gBCo+GN,CCxiHA,KAEE,6BAAA,CAAA,0BAAA,CAAA,qBAAA,CADA,qBDzBF,CC8BA,iBAGE,kBD3BF,CC8BE,gCANF,iBAOI,yBDzBF,CACF,CC6BA,KACE,QD1BF,CC8BA,qBAIE,uCD3BF,CC+BA,EACE,aAAA,CACA,oBD5BF,CCgCA,GAME,QAAA,CAJA,kBAAA,CADA,aAAA,CAEA,aAAA,CAEA,gBAAA,CADA,SD3BF,CCiCA,MACE,aD9BF,CCkCA,QAEE,eD/BF,CCmCA,IACE,iBDhCF,CCoCA,MACE,uBAAA,CACA,gBDjCF,CCqCA,MAEE,eAAA,CACA,kBDlCF,CCsCA,OAKE,gBAAA,CACA,QAAA,CAFA,mBAAA,CADA,iBAAA,CAFA,QAAA,CACA,SD/BF,CCuCA,MACE,QAAA,CACA,YDpCF,CErDA,MAIE,6BAAA,CACA,oCAAA,CACA,mCAAA,CACA,0BAAA,CACA,sCAAA,CAGA,4BAAA,CACA,2CAAA,CACA,yBAAA,CACA,qCFmDF,CEpCA,qCAGE,+BAAA,CACA,sCAAA,CACA,wCAAA,CACA,yCAAA,CACA,0BAAA,CACA,sCAAA,CACA,wCAAA,CACA,yCAAA,CAGA,0BAAA,CACA,0BAAA,CAGA,4BAAA,CACA,iCAAA,CACA,kCAAA,CACA,mCAAA,CACA,mCAAA,CACA,kCAAA,CACA,iCAAA,CACA,+CAAA,CACA,6DAAA,CACA,gEAAA,CACA,4DAAA,CACA,4DAAA,CACA,6DAAA,CAGA,6CAAA,CAGA,+CAAA,CAGA,iCAAA,CAGA,gCAAA,CACA,gCAAA,CAGA,8BAAA,CACA,kCAAA,CACA,qCAAA,CAGA,kCAAA,CAGA,mDAAA,CACA,mDAAA,CAGA,yBAAA,CACA,qCAAA,CACA,uCAAA,CACA,8BAAA,CACA,oCAAA,CAGA,8DAAA,CAKA,8DAAA,CAKA,0DFaF,CGjHE,aAIE,iBAAA,CAHA,aAAA,CAEA,aAAA,CADA,YHsHJ,CI3HA,KACE,kCAAA,CACA,iCAAA,CAGA,uGAAA,CAKA,mFJ4HF,CItHA,WAGE,mCAAA,CACA,sCJyHF,CIrHA,wBANE,6BJmIF,CI7HA,aAIE,4BAAA,CACA,sCJwHF,CIhHA,MACE,0NAAA,CACA,mNAAA,CACA,oNJmHF,CI5GA,YAGE,gCAAA,CAAA,kBAAA,CAFA,eAAA,CACA,eJgHF,CI3GE,aAPF,YAQI,gBJ8GF,CACF,CI3GE,uGAME,iBAAA,CAAA,cJ6GJ,CIzGE,eAEE,uCAAA,CAEA,aAAA,CACA,eAAA,CAJA,iBJgHJ,CIvGE,8BAPE,eAAA,CAGA,qBJkHJ,CI9GE,eAGE,kBAAA,CACA,eAAA,CAHA,oBJ6GJ,CIrGE,eAGE,gBAAA,CADA,eAAA,CAGA,qBAAA,CADA,eAAA,CAHA,mBJ2GJ,CInGE,kBACE,eJqGJ,CIjGE,eAEE,eAAA,CACA,qBAAA,CAFA,YJqGJ,CI/FE,8BAGE,uCAAA,CAEA,cAAA,CADA,eAAA,CAEA,qBAAA,CAJA,eJqGJ,CI7FE,eACE,wBJ+FJ,CI3FE,eAGE,+DAAA,CAFA,iBAAA,CACA,cJ8FJ,CIzFE,cACE,+BAAA,CACA,qBJ2FJ,CIxFI,mCAEE,sBJyFN,CIrFI,wCAEE,+BJsFN,CInFM,kDACE,uDJqFR,CIhFI,mBACE,kBAAA,CACA,iCJkFN,CI9EI,4BACE,uCAAA,CACA,oBJgFN,CI3EE,iDAGE,6BAAA,CACA,aAAA,CACA,2BJ6EJ,CI1EI,aARF,iDASI,oBJ+EJ,CACF,CI3EE,iBAIE,wCAAA,CACA,mBAAA,CACA,kCAAA,CAAA,0BAAA,CAJA,eAAA,CADA,uBAAA,CAEA,qBJgFJ,CI1EI,qCAEE,uCAAA,CADA,YJ6EN,CIvEE,gBAEE,iBAAA,CACA,eAAA,CAFA,iBJ2EJ,CItEI,qBAQE,kCAAA,CAAA,0BAAA,CADA,eAAA,CANA,aAAA,CACA,QAAA,CAIA,uCAAA,CAFA,aAAA,CADA,oCAAA,CAQA,yDAAA,CADA,oBAAA,CADA,iBAAA,CAJA,iBJ8EN,CIrEM,2BACE,+CJuER,CInEM,wCAEE,YAAA,CADA,WJsER,CIjEM,8CACE,oDJmER,CIhEQ,oDACE,0CJkEV,CI3DE,gBAOE,4CAAA,CACA,mBAAA,CACA,mKACE,CAPF,gCAAA,CAFA,oBAAA,CAGA,eAAA,CAFA,uBAAA,CAGA,uBAAA,CACA,qBJgEJ,CItDE,iBAGE,6CAAA,CACA,kCAAA,CAAA,0BAAA,CAHA,aAAA,CACA,qBJ0DJ,CIpDE,iBAEE,6DAAA,CACA,WAAA,CAFA,oBJwDJ,CInDI,oBANF,iBAOI,iBJsDJ,CInDI,yDAWE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CAKA,mBAAA,CAXA,oBAAA,CAOA,eAAA,CAHA,cAAA,CADA,aAAA,CADA,6BAAA,CAAA,qBAAA,CAGA,mBAAA,CAPA,iBAAA,CAGA,UJ+DN,CInEI,sDAWE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CAKA,mBAAA,CAXA,oBAAA,CAOA,eAAA,CAHA,cAAA,CADA,aAAA,CADA,0BAAA,CAAA,qBAAA,CAGA,mBAAA,CAPA,iBAAA,CAGA,UJ+DN,CInEI,mEAEE,MJiEN,CInEI,gEAEE,MJiEN,CInEI,0DAEE,MJiEN,CInEI,mEAEE,OJiEN,CInEI,gEAEE,OJiEN,CInEI,0DAEE,OJiEN,CInEI,gDAWE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CAKA,mBAAA,CAXA,oBAAA,CAOA,eAAA,CAHA,cAAA,CADA,aAAA,CADA,6BAAA,CAAA,0BAAA,CAAA,qBAAA,CAGA,mBAAA,CAPA,iBAAA,CAGA,UJ+DN,CACF,CIhDE,kBACE,WJkDJ,CI9CE,oDAEE,qBJgDJ,CIlDE,oDAEE,sBJgDJ,CI5CE,iCACE,kBJiDJ,CIlDE,iCACE,mBJiDJ,CIlDE,iCAIE,2DJ8CJ,CIlDE,iCAIE,4DJ8CJ,CIlDE,uBAGE,uCAAA,CADA,aAAA,CAAA,cJgDJ,CI1CE,eACE,oBJ4CJ,CIxCE,kDAEE,kBJ2CJ,CI7CE,kDAEE,mBJ2CJ,CI7CE,8BAGE,SJ0CJ,CIvCI,0DACE,iBJ0CN,CItCI,oCACE,2BJyCN,CItCM,0CACE,2BJyCR,CIpCI,wDAEE,kBJuCN,CIzCI,wDAEE,mBJuCN,CIzCI,oCACE,kBJwCN,CIpCM,kGAEE,aJwCR,CIpCM,0DACE,eJuCR,CInCM,4EACE,kBAAA,CAAA,eJuCR,CIxCM,sEACE,kBAAA,CAAA,eJuCR,CIxCM,gGAEE,kBJsCR,CIxCM,0FAEE,kBJsCR,CIxCM,8EAEE,kBJsCR,CIxCM,gGAEE,mBJsCR,CIxCM,0FAEE,mBJsCR,CIxCM,8EAEE,mBJsCR,CIxCM,0DACE,kBAAA,CAAA,eJuCR,CIhCE,yBAEE,mBJkCJ,CIpCE,yBAEE,oBJkCJ,CIpCE,eACE,mBAAA,CAAA,cJmCJ,CI9BE,kDAIE,WAAA,CADA,cJiCJ,CIzBI,4BAEE,oBJ2BN,CIvBI,6BAEE,oBJyBN,CIrBI,kCACE,YJuBN,CInBI,8EAEE,YJoBN,CIfE,mBACE,iBAAA,CAGA,eAAA,CADA,cAAA,CAEA,iBAAA,CAHA,yBAAA,CAAA,sBAAA,CAAA,iBJoBJ,CIdI,uBACE,aJgBN,CIXE,uBAGE,iBAAA,CADA,eAAA,CADA,eJeJ,CITE,mBACE,cJWJ,CIPE,+BAKE,2CAAA,CACA,iDAAA,CACA,mBAAA,CANA,oBAAA,CAGA,gBAAA,CAFA,cAAA,CACA,aAAA,CAKA,iBJSJ,CINI,aAXF,+BAYI,aJSJ,CACF,CIJI,iCACE,gBJMN,CICM,gEACE,YJCR,CIFM,6DACE,YJCR,CIFM,uDACE,YJCR,CIGM,+DACE,eJDR,CIAM,4DACE,eJDR,CIAM,sDACE,eJDR,CIMI,gEACE,eJJN,CIGI,6DACE,eJJN,CIGI,uDACE,eJJN,CIOM,0EACE,gBJLR,CIIM,uEACE,gBJLR,CIIM,iEACE,gBJLR,CIUI,kCAGE,eAAA,CAFA,cAAA,CACA,sBAAA,CAEA,kBJRN,CIYI,kCAGE,qDAAA,CAFA,sBAAA,CACA,kBJTN,CIcI,wCACE,iCJZN,CIeM,8CACE,iCAAA,CACA,sDJbR,CIkBI,iCACE,iBJhBN,CIqBE,wCACE,cJnBJ,CIsBI,wDAIE,gBJdN,CIUI,wDAIE,iBJdN,CIUI,8CAUE,UAAA,CATA,oBAAA,CAEA,YAAA,CAGA,oDAAA,CAAA,4CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CACA,iCAAA,CAJA,0BAAA,CAHA,WJZN,CIwBI,oDACE,oDJtBN,CI0BI,mEACE,kDAAA,CACA,yDAAA,CAAA,iDJxBN,CI4BI,oEACE,kDAAA,CACA,0DAAA,CAAA,kDJ1BN,CI+BE,wBACE,iBAAA,CACA,eAAA,CACA,iBJ7BJ,CIiCE,mBACE,oBAAA,CACA,kBAAA,CACA,eJ/BJ,CIkCI,aANF,mBAOI,aJ/BJ,CACF,CIkCI,8BACE,aAAA,CAEA,QAAA,CACA,eAAA,CAFA,UJ9BN,CK7VI,wCD0YF,uBACE,iBJzCF,CI4CE,4BACE,eJ1CJ,CACF,CM/hBA,WAGE,0CAAA,CADA,+BAAA,CADA,aNmiBF,CM9hBE,aANF,WAOI,YNiiBF,CACF,CM9hBE,oBAEE,uCAAA,CADA,gCNiiBJ,CM5hBE,kBAGE,eAAA,CAFA,iBAAA,CACA,eN+hBJ,CM1hBE,6BACE,WN+hBJ,CMhiBE,6BACE,UN+hBJ,CMhiBE,mBAEE,aAAA,CACA,cAAA,CACA,uBN4hBJ,CMzhBI,yBACE,UN2hBN,CO3jBA,KASE,cAAA,CARA,WAAA,CACA,iBP+jBF,CK3ZI,oCEtKJ,KAaI,gBPwjBF,CACF,CKhaI,oCEtKJ,KAkBI,cPwjBF,CACF,COnjBA,KASE,2CAAA,CAPA,YAAA,CACA,qBAAA,CAKA,eAAA,CAHA,eAAA,CAJA,iBAAA,CAGA,UPyjBF,COjjBE,aAZF,KAaI,aPojBF,CACF,CKjaI,wCEhJF,yBAII,cPijBJ,CACF,COxiBA,SAEE,gBAAA,CAAA,iBAAA,CADA,eP4iBF,COviBA,cACE,YAAA,CACA,qBAAA,CACA,WP0iBF,COviBE,aANF,cAOI,aP0iBF,CACF,COtiBA,SACE,WPyiBF,COtiBE,gBACE,YAAA,CACA,WAAA,CACA,iBPwiBJ,COniBA,aACE,eAAA,CAEA,sBAAA,CADA,kBPuiBF,CO7hBA,WACE,YPgiBF,CO3hBA,WAGE,QAAA,CACA,SAAA,CAHA,iBAAA,CACA,OPgiBF,CO3hBE,uCACE,aP6hBJ,COzhBE,+BAEE,uCAAA,CADA,kBP4hBJ,COthBA,SASE,2CAAA,CACA,mBAAA,CAHA,gCAAA,CACA,gBAAA,CAHA,YAAA,CAQA,SAAA,CAFA,uCAAA,CALA,mBAAA,CALA,cAAA,CAWA,2BAAA,CARA,UPgiBF,COphBE,eAGE,SAAA,CADA,uBAAA,CAEA,oEACE,CAJF,UPyhBJ,CO3gBA,MACE,WP8gBF,CQxqBA,MACE,+PR0qBF,CQpqBA,cAQE,mBAAA,CADA,0CAAA,CAIA,cAAA,CALA,YAAA,CAGA,uCAAA,CACA,oBAAA,CATA,iBAAA,CAEA,UAAA,CADA,QAAA,CAUA,qBAAA,CAPA,WAAA,CADA,SR+qBF,CQpqBE,aAfF,cAgBI,YRuqBF,CACF,CQpqBE,kCAEE,uCAAA,CADA,YRuqBJ,CQlqBE,qBACE,uCRoqBJ,CQhqBE,yCACE,+BRkqBJ,CQnqBE,sCACE,+BRkqBJ,CQnqBE,gCACE,+BRkqBJ,CQ7pBE,oBAKE,6BAAA,CAKA,UAAA,CATA,aAAA,CAEA,cAAA,CACA,aAAA,CAEA,2CAAA,CAAA,mCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CAPA,aRuqBJ,CQ3pBE,sBACE,cR6pBJ,CQ1pBI,2BACE,2CR4pBN,CQtpBI,sDAEE,uDAAA,CADA,+BRypBN,CQ1pBI,mDAEE,uDAAA,CADA,+BRypBN,CQ1pBI,6CAEE,uDAAA,CADA,+BRypBN,CS/tBA,mBACE,GAEE,SAAA,CADA,0BTmuBF,CS/tBA,GAEE,SAAA,CADA,uBTkuBF,CACF,CS7tBA,mBACE,GACE,ST+tBF,CS5tBA,GACE,ST8tBF,CACF,CSntBE,qBASE,2BAAA,CADA,mCAAA,CAAA,2BAAA,CAFA,0BAAA,CADA,WAAA,CAEA,SAAA,CANA,cAAA,CACA,KAAA,CAEA,UAAA,CADA,ST2tBJ,CSjtBE,mBAcE,mDAAA,CANA,2CAAA,CACA,QAAA,CACA,mBAAA,CARA,QAAA,CASA,kDACE,CAPF,eAAA,CAEA,aAAA,CADA,SAAA,CALA,cAAA,CAGA,UAAA,CADA,ST4tBJ,CS7sBE,kBACE,aT+sBJ,CS3sBE,sBACE,YAAA,CACA,YT6sBJ,CS1sBI,oCACE,aT4sBN,CSvsBE,sBACE,mBTysBJ,CStsBI,6CACE,cTwsBN,CKlmBI,wCIvGA,6CAKI,aAAA,CAEA,gBAAA,CACA,iBAAA,CAFA,UT0sBN,CACF,CSnsBE,kBACE,cTqsBJ,CUtyBA,YACE,WAAA,CAIA,WVsyBF,CUnyBE,mBACE,qBAAA,CACA,iBVqyBJ,CKzoBI,sCKtJE,4EACE,kBVkyBN,CU9xBI,0JACE,mBVgyBN,CUjyBI,8EACE,kBVgyBN,CACF,CU3xBI,0BAGE,UAAA,CAFA,aAAA,CACA,YV8xBN,CUzxBI,+BACE,eV2xBN,CUrxBE,8BACE,WV0xBJ,CU3xBE,8BACE,UV0xBJ,CU3xBE,8BAGE,iBVwxBJ,CU3xBE,8BAGE,kBVwxBJ,CU3xBE,oBAEE,cAAA,CAEA,SVuxBJ,CUpxBI,aAPF,oBAQI,YVuxBJ,CACF,CUpxBI,gCACE,yCVsxBN,CUlxBI,wBACE,cAAA,CACA,kBVoxBN,CUjxBM,kCACE,oBVmxBR,CWp1BA,qBAEE,WXk2BF,CWp2BA,qBAEE,UXk2BF,CWp2BA,WAOE,2CAAA,CACA,mBAAA,CALA,YAAA,CAMA,8BAAA,CAJA,iBAAA,CAMA,SAAA,CALA,mBAAA,CASA,mBAAA,CAdA,cAAA,CASA,0BAAA,CAEA,wCACE,CATF,SXg2BF,CWl1BE,aAlBF,WAmBI,YXq1BF,CACF,CWl1BE,mBAEE,SAAA,CAIA,mBAAA,CALA,uBAAA,CAEA,kEXq1BJ,CW90BE,kBACE,gCAAA,CACA,eXg1BJ,CYn3BA,aACE,gBAAA,CACA,iBZs3BF,CYn3BE,sBAGE,WAAA,CAFA,QAAA,CACA,SZs3BJ,CYj3BE,oBAEE,eAAA,CADA,eZo3BJ,CY/2BE,oBACE,iBZi3BJ,CY72BE,mBAIE,sBAAA,CAFA,YAAA,CACA,cAAA,CAEA,sBAAA,CAJA,iBZm3BJ,CY52BI,iDACE,yCZ82BN,CY12BI,6BACE,iBZ42BN,CYv2BE,mBAGE,uCAAA,CACA,cAAA,CAHA,aAAA,CACA,cAAA,CAGA,sBZy2BJ,CYt2BI,gDACE,+BZw2BN,CYp2BI,4BACE,0CAAA,CACA,mBZs2BN,CYj2BE,mBAGE,SAAA,CAFA,iBAAA,CACA,2BAAA,CAEA,8DZm2BJ,CY91BI,qBAEE,aAAA,CADA,eZi2BN,CY51BI,6BAEE,SAAA,CADA,uBZ+1BN,Ca76BA,WAEE,0CAAA,CADA,+Bbi7BF,Ca76BE,aALF,WAMI,Ybg7BF,CACF,Ca76BE,kBACE,6BAAA,CAEA,aAAA,CADA,abg7BJ,Ca56BI,gCACE,Yb86BN,Caz6BE,iBACE,YAAA,CAKA,cAAA,CAIA,uCAAA,CADA,eAAA,CADA,oBAAA,CADA,kBAAA,CAIA,uBbu6BJ,Cap6BI,4CACE,Ubs6BN,Cav6BI,yCACE,Ubs6BN,Cav6BI,mCACE,Ubs6BN,Cal6BI,+BACE,oBbo6BN,CKrxBI,wCQrII,yCACE,Yb65BR,CACF,Cax5BI,iCACE,gBb25BN,Ca55BI,iCACE,iBb25BN,Ca55BI,uBAEE,gBb05BN,Cav5BM,iCACE,eby5BR,Can5BE,kBAEE,WAAA,CAGA,eAAA,CACA,kBAAA,CAHA,6BAAA,CACA,cAAA,CAHA,iBAAA,CAMA,kBbq5BJ,Caj5BE,mBACE,YAAA,CACA,abm5BJ,Ca/4BE,sBAKE,gBAAA,CAHA,MAAA,CACA,gBAAA,CAGA,UAAA,CAFA,cAAA,CAHA,iBAAA,CACA,Obq5BJ,Ca54BA,gBACE,gDb+4BF,Ca54BE,uBACE,YAAA,CACA,cAAA,CACA,6BAAA,CACA,ab84BJ,Ca14BE,kCACE,sCb44BJ,Caz4BI,6DACE,+Bb24BN,Ca54BI,0DACE,+Bb24BN,Ca54BI,oDACE,+Bb24BN,Can4BA,cAIE,wCAAA,CACA,gBAAA,CAHA,iBAAA,CACA,eAAA,CAFA,Ub04BF,CKj2BI,mCQ1CJ,cASI,Ubs4BF,CACF,Cal4BE,yBACE,sCbo4BJ,Ca73BA,WACE,cAAA,CACA,qBbg4BF,CK92BI,mCQpBJ,WAMI,ebg4BF,CACF,Ca73BE,iBACE,oBAAA,CAEA,aAAA,CACA,iBAAA,CAFA,Ybi4BJ,Ca53BI,wBACE,eb83BN,Ca13BI,qBAGE,iBAAA,CAFA,gBAAA,CACA,mBb63BN,CcpiCE,uBAKE,kBAAA,CACA,mBAAA,CAHA,gCAAA,CAIA,cAAA,CANA,oBAAA,CAGA,eAAA,CAFA,kBAAA,CAMA,gEduiCJ,CcjiCI,gCAEE,2CAAA,CACA,uCAAA,CAFA,gCdqiCN,Cc/hCI,kDAEE,0CAAA,CACA,sCAAA,CAFA,+BdmiCN,CcpiCI,+CAEE,0CAAA,CACA,sCAAA,CAFA,+BdmiCN,CcpiCI,yCAEE,0CAAA,CACA,sCAAA,CAFA,+BdmiCN,Cc5hCE,gCAKE,4BdiiCJ,CctiCE,gEAME,6BdgiCJ,CctiCE,gCAME,4BdgiCJ,CctiCE,sBAIE,6DAAA,CAGA,8BAAA,CAJA,eAAA,CAFA,aAAA,CACA,eAAA,CAMA,sCd8hCJ,CczhCI,iDACE,6CAAA,CACA,8Bd2hCN,Cc7hCI,8CACE,6CAAA,CACA,8Bd2hCN,Cc7hCI,wCACE,6CAAA,CACA,8Bd2hCN,CcvhCI,+BACE,UdyhCN,Ce5kCA,WAOE,2CAAA,CAGA,8CACE,CALF,gCAAA,CADA,aAAA,CAFA,MAAA,CAFA,uBAAA,CAAA,eAAA,CAEA,OAAA,CADA,KAAA,CAEA,SfmlCF,CexkCE,aAfF,WAgBI,Yf2kCF,CACF,CexkCE,mBACE,2BAAA,CACA,iEf0kCJ,CepkCE,mBACE,kDACE,CAEF,kEfokCJ,Ce9jCE,kBAEE,kBAAA,CADA,YAAA,CAEA,efgkCJ,Ce5jCE,mBAKE,kBAAA,CAGA,cAAA,CALA,YAAA,CAIA,uCAAA,CAHA,aAAA,CAHA,iBAAA,CAQA,uBAAA,CAHA,qBAAA,CAJA,SfqkCJ,Ce3jCI,yBACE,Uf6jCN,CezjCI,iCACE,oBf2jCN,CevjCI,uCAEE,uCAAA,CADA,Yf0jCN,CerjCI,2BACE,YAAA,CACA,afujCN,CK18BI,wCU/GA,2BAMI,YfujCN,CACF,CepjCM,iDAIE,iBAAA,CAHA,aAAA,CAEA,aAAA,CADA,UfwjCR,Ce1jCM,8CAIE,iBAAA,CAHA,aAAA,CAEA,aAAA,CADA,UfwjCR,Ce1jCM,wCAIE,iBAAA,CAHA,aAAA,CAEA,aAAA,CADA,UfwjCR,CKx+BI,mCUzEA,iCAII,YfijCN,CACF,Ce9iCM,wCACE,YfgjCR,Ce5iCM,+CACE,oBf8iCR,CKn/BI,sCUtDA,iCAII,YfyiCN,CACF,CepiCE,kBAEE,YAAA,CACA,cAAA,CAFA,iBAAA,CAIA,8DACE,CAFF,kBfuiCJ,CejiCI,oCAGE,SAAA,CAIA,mBAAA,CALA,6BAAA,CAEA,8DACE,CAJF,UfuiCN,Ce9hCM,8CACE,8BfgiCR,Ce3hCI,8BACE,ef6hCN,CexhCE,4BAGE,kBf6hCJ,CehiCE,4BAGE,iBf6hCJ,CehiCE,4BAIE,gBf4hCJ,CehiCE,4BAIE,iBf4hCJ,CehiCE,kBACE,WAAA,CAIA,eAAA,CAHA,aAAA,CAIA,kBf0hCJ,CevhCI,4CAGE,SAAA,CAIA,mBAAA,CALA,8BAAA,CAEA,8DACE,CAJF,Uf6hCN,CephCM,sDACE,6BfshCR,CelhCM,8DAGE,SAAA,CAIA,mBAAA,CALA,uBAAA,CAEA,8DACE,CAJF,SfwhCR,Ce7gCI,uCAGE,WAAA,CAFA,iBAAA,CACA,UfghCN,Ce1gCE,mBACE,YAAA,CACA,aAAA,CACA,cAAA,CAEA,+CACE,CAFF,kBf6gCJ,CevgCI,8DACE,WAAA,CACA,SAAA,CACA,oCfygCN,CelgCE,mBACE,YfogCJ,CKzjCI,mCUoDF,6BAQI,gBfogCJ,Ce5gCA,6BAQI,iBfogCJ,Ce5gCA,mBAKI,aAAA,CAEA,iBAAA,CADA,afsgCJ,CACF,CKjkCI,sCUoDF,6BAaI,kBfogCJ,CejhCA,6BAaI,mBfogCJ,CACF,CgB5uCA,MACE,0MAAA,CACA,gMAAA,CACA,yNhB+uCF,CgBzuCA,QACE,eAAA,CACA,ehB4uCF,CgBzuCE,eACE,aAAA,CAGA,eAAA,CADA,eAAA,CADA,eAAA,CAGA,sBhB2uCJ,CgBxuCI,+BACE,YhB0uCN,CgBvuCM,mCAEE,WAAA,CADA,UhB0uCR,CgBluCQ,6DAME,iBAAA,CALA,aAAA,CAGA,aAAA,CADA,cAAA,CAEA,kBAAA,CAHA,UhBwuCV,CgB1uCQ,0DAME,iBAAA,CALA,aAAA,CAGA,aAAA,CADA,cAAA,CAEA,kBAAA,CAHA,UhBwuCV,CgB1uCQ,oDAME,iBAAA,CALA,aAAA,CAGA,aAAA,CADA,cAAA,CAEA,kBAAA,CAHA,UhBwuCV,CgB7tCE,cAGE,eAAA,CAFA,QAAA,CACA,ShBguCJ,CgB3tCE,cACE,ehB6tCJ,CgB1tCI,sCACE,ehB4tCN,CgB7tCI,sCACE,chB4tCN,CgBvtCE,cAEE,kBAAA,CAKA,cAAA,CANA,YAAA,CAEA,6BAAA,CACA,iBAAA,CACA,eAAA,CAIA,uBAAA,CAHA,sBAAA,CAEA,sBhB0tCJ,CgBttCI,sBACE,uChBwtCN,CgBptCI,oCACE,+BhBstCN,CgBltCI,0CACE,UhBotCN,CgBhtCI,yCACE,+BhBktCN,CgBntCI,sCACE,+BhBktCN,CgBntCI,gCACE,+BhBktCN,CgB9sCI,4BACE,uCAAA,CACA,oBhBgtCN,CgB5sCI,0CACE,YhB8sCN,CgB3sCM,yDAKE,6BAAA,CAJA,aAAA,CAEA,WAAA,CACA,qCAAA,CAAA,6BAAA,CAFA,UhBgtCR,CgBzsCM,kDACE,YhB2sCR,CgBtsCI,gBAEE,cAAA,CADA,YhBysCN,CgBnsCE,cACE,ahBqsCJ,CgBjsCE,gBACE,YhBmsCJ,CKjpCI,wCW3CA,0CASE,2CAAA,CAHA,YAAA,CACA,qBAAA,CACA,WAAA,CAJA,MAAA,CAFA,iBAAA,CAEA,OAAA,CADA,KAAA,CAEA,ShBksCJ,CgBvrCI,4DACE,eAAA,CACA,ehByrCN,CgB3rCI,yDACE,eAAA,CACA,ehByrCN,CgB3rCI,mDACE,eAAA,CACA,ehByrCN,CgBrrCI,gCAOE,qDAAA,CAHA,uCAAA,CAIA,cAAA,CANA,aAAA,CAGA,kBAAA,CAFA,wBAAA,CAFA,iBAAA,CAKA,kBhByrCN,CgBprCM,wDAGE,UhB0rCR,CgB7rCM,wDAGE,WhB0rCR,CgB7rCM,8CAIE,aAAA,CAEA,aAAA,CACA,YAAA,CANA,iBAAA,CACA,SAAA,CAGA,YhBwrCR,CgBnrCQ,oDAIE,6BAAA,CAKA,UAAA,CARA,aAAA,CAEA,WAAA,CAEA,2CAAA,CAAA,mCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CANA,UhB4rCV,CgBhrCM,8CAEE,2CAAA,CACA,gEACE,CAHF,eAAA,CAIA,4BAAA,CACA,kBhBirCR,CgB9qCQ,2DACE,YhBgrCV,CgB3qCM,8CAGE,2CAAA,CAFA,gCAAA,CACA,ehB8qCR,CgBzqCM,yCAIE,aAAA,CADA,UAAA,CAEA,YAAA,CACA,aAAA,CALA,iBAAA,CAEA,WAAA,CADA,ShB+qCR,CgBtqCI,+BACE,MhBwqCN,CgBpqCI,+BAEE,4DAAA,CADA,ShBuqCN,CgBnqCM,qDACE,+BhBqqCR,CgBlqCQ,gFACE,+BhBoqCV,CgBrqCQ,6EACE,+BhBoqCV,CgBrqCQ,uEACE,+BhBoqCV,CgB9pCI,+BACE,YAAA,CACA,mBhBgqCN,CgB7pCM,uDAGE,mBhBgqCR,CgBnqCM,uDAGE,kBhBgqCR,CgBnqCM,6CAIE,gBAAA,CAFA,aAAA,CADA,YhBkqCR,CgB5pCQ,mDAIE,6BAAA,CAKA,UAAA,CARA,aAAA,CAEA,WAAA,CAEA,2CAAA,CAAA,mCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CANA,UhBqqCV,CgBrpCM,+CACE,mBhBupCR,CgB/oCM,4CAEE,wBAAA,CADA,ehBkpCR,CgB9oCQ,oEACE,mBhBgpCV,CgBjpCQ,oEACE,oBhBgpCV,CgB5oCQ,4EACE,iBhB8oCV,CgB/oCQ,4EACE,kBhB8oCV,CgB1oCQ,oFACE,mBhB4oCV,CgB7oCQ,oFACE,oBhB4oCV,CgBxoCQ,4FACE,mBhB0oCV,CgB3oCQ,4FACE,oBhB0oCV,CgBnoCE,mBACE,wBhBqoCJ,CgBjoCE,wBACE,YAAA,CAEA,SAAA,CADA,0BAAA,CAEA,oEhBmoCJ,CgB9nCI,kCACE,2BhBgoCN,CgB3nCE,gCAEE,SAAA,CADA,uBAAA,CAEA,qEhB6nCJ,CgBxnCI,8CAEE,kCAAA,CAAA,0BhBynCN,CACF,CK/xCI,wCW8KA,0CACE,YhBonCJ,CgBjnCI,yDACE,UhBmnCN,CgB/mCI,wDACE,YhBinCN,CgB7mCI,kDACE,YhB+mCN,CgB1mCE,gBAIE,iDAAA,CADA,gCAAA,CAFA,aAAA,CACA,ehB8mCJ,CACF,CK51CM,6DWuPF,6CACE,YhBwmCJ,CgBrmCI,4DACE,UhBumCN,CgBnmCI,2DACE,YhBqmCN,CgBjmCI,qDACE,YhBmmCN,CACF,CKp1CI,mCWyPA,kCAME,qCAAA,CACA,qDAAA,CANA,uBAAA,CAAA,eAAA,CACA,KAAA,CAGA,ShB8lCJ,CgBzlCI,6CACE,uBhB2lCN,CgBvlCI,gDACE,YhBylCN,CACF,CKn2CI,sCW7JJ,QA6aI,oDhBulCF,CgBplCE,gCAME,qCAAA,CACA,qDAAA,CANA,uBAAA,CAAA,eAAA,CACA,KAAA,CAGA,ShBslCJ,CgBjlCI,8CACE,uBhBmlCN,CgBzkCE,sEACE,YhB8kCJ,CgB1kCE,6DACE,ahB4kCJ,CgB7kCE,0DACE,ahB4kCJ,CgB7kCE,oDACE,ahB4kCJ,CgBxkCE,6CACE,YhB0kCJ,CgBtkCE,uBACE,aAAA,CACA,ehBwkCJ,CgBrkCI,kCACE,ehBukCN,CgBnkCI,qCACE,eAAA,CACA,mBhBqkCN,CgBlkCM,mDACE,mBhBokCR,CgBhkCM,mDACE,YhBkkCR,CgB7jCI,+BACE,ahB+jCN,CgB5jCM,2DACE,ShB8jCR,CgBxjCE,cAGE,kBAAA,CADA,YAAA,CAEA,+CACE,CAJF,WhB6jCJ,CgBrjCI,wBACE,wBhBujCN,CgBnjCI,oBACE,uDhBqjCN,CgBjjCI,oBAKE,6BAAA,CAKA,UAAA,CATA,oBAAA,CAEA,WAAA,CAGA,2CAAA,CAAA,mCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CALA,qBAAA,CAFA,UhB2jCN,CgB/iCI,0JAEE,uBhBgjCN,CgBliCI,+HACE,YhBwiCN,CgBriCM,oDACE,aAAA,CACA,ShBuiCR,CgBpiCQ,kEAOE,qCAAA,CACA,qDAAA,CAFA,eAAA,CAFA,YAAA,CACA,eAAA,CAJA,uBAAA,CAAA,eAAA,CACA,KAAA,CACA,ShB2iCV,CgBniCU,4FACE,mBhBqiCZ,CgBjiCU,gFACE,YhBmiCZ,CgB3hCI,2CACE,ahB6hCN,CgB1hCM,iFACE,mBhB4hCR,CgB7hCM,iFACE,kBhB4hCR,CgBnhCI,mFACE,ehBqhCN,CgBlhCM,iGACE,ShBohCR,CgB/gCI,qFAGE,mDhBihCN,CgBphCI,qFAGE,oDhBihCN,CgBphCI,2EACE,aAAA,CACA,oBhBkhCN,CgB9gCM,0FACE,YhBghCR,CACF,CiBroDA,MACE,igBjBwoDF,CiBloDA,WACE,iBjBqoDF,CKv+CI,mCY/JJ,WAKI,ejBqoDF,CACF,CiBloDE,kBACE,YjBooDJ,CiBhoDE,oBAEE,SAAA,CADA,SjBmoDJ,CKh+CI,wCYpKF,8BAQI,YjB0oDJ,CiBlpDA,8BAQI,ajB0oDJ,CiBlpDA,oBAYI,2CAAA,CACA,kBAAA,CAHA,WAAA,CACA,eAAA,CAOA,mBAAA,CAZA,iBAAA,CACA,SAAA,CAOA,uBAAA,CACA,4CACE,CAPF,UjByoDJ,CiB7nDI,+DACE,SAAA,CACA,oCjB+nDN,CACF,CKtgDI,mCYjJF,8BAiCI,MjBioDJ,CiBlqDA,8BAiCI,OjBioDJ,CiBlqDA,oBAoCI,0BAAA,CACA,cAAA,CAFA,QAAA,CAJA,cAAA,CACA,KAAA,CAMA,sDACE,CALF,OjBgoDJ,CiBtnDI,+DAME,YAAA,CACA,SAAA,CACA,4CACE,CARF,UjB2nDN,CACF,CKrgDI,wCYxGA,+DAII,mBjB6mDN,CACF,CKnjDM,6DY/DF,+DASI,mBjB6mDN,CACF,CKxjDM,6DY/DF,+DAcI,mBjB6mDN,CACF,CiBxmDE,kBAEE,kCAAA,CAAA,0BjBymDJ,CKvhDI,wCYpFF,4BAQI,MjBgnDJ,CiBxnDA,4BAQI,OjBgnDJ,CiBxnDA,kBAWI,QAAA,CAGA,SAAA,CAFA,eAAA,CANA,cAAA,CACA,KAAA,CAMA,wBAAA,CAEA,qGACE,CANF,OAAA,CADA,SjB+mDJ,CiBlmDI,4BACE,yBjBomDN,CiBhmDI,6DAEE,WAAA,CAEA,SAAA,CADA,uBAAA,CAEA,sGACE,CALF,UjBsmDN,CACF,CKlkDI,mCYjEF,4BA2CI,WjBgmDJ,CiB3oDA,4BA2CI,UjBgmDJ,CiB3oDA,kBA6CI,eAAA,CAHA,iBAAA,CAIA,8CAAA,CAFA,ajB+lDJ,CACF,CKjmDM,6DYOF,6DAII,ajB0lDN,CACF,CKhlDI,sCYfA,6DASI,ajB0lDN,CACF,CiBrlDE,iBAIE,2CAAA,CACA,0BAAA,CAFA,aAAA,CAFA,iBAAA,CAKA,2CACE,CALF,SjB2lDJ,CK7lDI,mCYAF,iBAaI,0BAAA,CACA,mBAAA,CAFA,ajBulDJ,CiBllDI,uBACE,0BjBolDN,CACF,CiBhlDI,4DAEE,2CAAA,CACA,6BAAA,CACA,8BAAA,CAHA,gCjBqlDN,CiB7kDE,4BAKE,mBAAA,CAAA,oBjBklDJ,CiBvlDE,4BAKE,mBAAA,CAAA,oBjBklDJ,CiBvlDE,kBAQE,gBAAA,CAFA,eAAA,CAFA,WAAA,CAHA,iBAAA,CAMA,sBAAA,CAJA,UAAA,CADA,SjBqlDJ,CiB5kDI,+BACE,qBjB8kDN,CiB1kDI,kEAEE,uCjB2kDN,CiBvkDI,6BACE,YjBykDN,CK7mDI,wCYaF,kBA8BI,eAAA,CADA,aAAA,CADA,UjB0kDJ,CACF,CKvoDI,mCYgCF,4BAmCI,mBjB0kDJ,CiB7mDA,4BAmCI,oBjB0kDJ,CiB7mDA,kBAoCI,aAAA,CACA,ejBwkDJ,CiBrkDI,+BACE,uCjBukDN,CiBnkDI,mCACE,gCjBqkDN,CiBjkDI,6DACE,kBjBmkDN,CiBhkDM,wJAEE,uCjBikDR,CACF,CiB3jDE,iBAIE,cAAA,CAHA,oBAAA,CAEA,aAAA,CAEA,kCACE,CAJF,YjBgkDJ,CiBxjDI,uBACE,UjB0jDN,CiBtjDI,yCAGE,UjByjDN,CiB5jDI,yCAGE,WjByjDN,CiB5jDI,+BACE,iBAAA,CACA,SAAA,CAEA,SjBwjDN,CiBrjDM,6CACE,oBjBujDR,CK1pDI,wCY2FA,yCAcI,UjBsjDN,CiBpkDE,yCAcI,WjBsjDN,CiBpkDE,+BAaI,SjBujDN,CiBnjDM,+CACE,YjBqjDR,CACF,CKtrDI,mCY8GA,+BAwBI,mBjBojDN,CiBjjDM,8CACE,YjBmjDR,CACF,CiB7iDE,8BAGE,WjBijDJ,CiBpjDE,8BAGE,UjBijDJ,CiBpjDE,oBAKE,mBAAA,CAJA,iBAAA,CACA,SAAA,CAEA,SjBgjDJ,CKlrDI,wCY8HF,8BAUI,WjB+iDJ,CiBzjDA,8BAUI,UjB+iDJ,CiBzjDA,oBASI,SjBgjDJ,CACF,CiB5iDI,gCACE,iBjBkjDN,CiBnjDI,gCACE,kBjBkjDN,CiBnjDI,sBAEE,uCAAA,CAEA,SAAA,CADA,oBAAA,CAEA,+DjB8iDN,CiBziDM,yCAEE,uCAAA,CADA,YjB4iDR,CiBviDM,yFAGE,SAAA,CACA,mBAAA,CAFA,kBjB0iDR,CiBriDQ,8FACE,UjBuiDV,CiBhiDE,8BAOE,mBAAA,CAAA,oBjBuiDJ,CiB9iDE,8BAOE,mBAAA,CAAA,oBjBuiDJ,CiB9iDE,oBAIE,kBAAA,CAIA,yCAAA,CALA,YAAA,CAMA,eAAA,CAHA,WAAA,CAKA,SAAA,CAVA,iBAAA,CACA,KAAA,CAUA,uBAAA,CAFA,kBAAA,CALA,UjByiDJ,CK5uDI,mCY8LF,8BAgBI,mBjBmiDJ,CiBnjDA,8BAgBI,oBjBmiDJ,CiBnjDA,oBAiBI,ejBkiDJ,CACF,CiB/hDI,+DACE,SAAA,CACA,0BjBiiDN,CiB5hDE,6BAKE,+BjB+hDJ,CiBpiDE,0DAME,gCjB8hDJ,CiBpiDE,6BAME,+BjB8hDJ,CiBpiDE,mBAIE,eAAA,CAHA,iBAAA,CAEA,UAAA,CADA,SjBkiDJ,CK3uDI,wCYuMF,mBAWI,QAAA,CADA,UjB+hDJ,CACF,CKpwDI,mCY0NF,mBAiBI,SAAA,CADA,UAAA,CAEA,sBjB8hDJ,CiB3hDI,8DACE,8BAAA,CACA,SjB6hDN,CACF,CiBxhDE,uBAKE,kCAAA,CAAA,0BAAA,CAFA,2CAAA,CAFA,WAAA,CACA,eAAA,CAOA,kBjBshDJ,CiBnhDI,iEAZF,uBAaI,uBjBshDJ,CACF,CKjzDM,6DY6QJ,uBAkBI,ajBshDJ,CACF,CKhyDI,sCYuPF,uBAuBI,ajBshDJ,CACF,CKryDI,mCYuPF,uBA4BI,YAAA,CAEA,yDAAA,CADA,oBjBuhDJ,CiBnhDI,kEACE,ejBqhDN,CiBjhDI,6BACE,+CjBmhDN,CiB/gDI,0CAEE,YAAA,CADA,WjBkhDN,CiB7gDI,gDACE,oDjB+gDN,CiB5gDM,sDACE,0CjB8gDR,CACF,CiBvgDA,kBACE,gCAAA,CACA,qBjB0gDF,CiBvgDE,wBAKE,qDAAA,CAHA,uCAAA,CACA,gBAAA,CACA,kBAAA,CAHA,eAAA,CAKA,uBjBygDJ,CKz0DI,mCY0TF,kCAUI,mBjBygDJ,CiBnhDA,kCAUI,oBjBygDJ,CACF,CiBrgDE,wBAGE,eAAA,CAFA,QAAA,CACA,SAAA,CAGA,wBAAA,CAAA,qBAAA,CAAA,gBjBsgDJ,CiBlgDE,wBACE,yDjBogDJ,CiBjgDI,oCACE,ejBmgDN,CiB9/CE,wBACE,aAAA,CACA,YAAA,CAEA,uBAAA,CADA,gCjBigDJ,CiB7/CI,mDACE,uDjB+/CN,CiBhgDI,gDACE,uDjB+/CN,CiBhgDI,0CACE,uDjB+/CN,CiB3/CI,gDACE,mBjB6/CN,CiBx/CE,gCAGE,+BAAA,CAGA,cAAA,CALA,aAAA,CAGA,gBAAA,CACA,YAAA,CAHA,mBAAA,CAQA,uBAAA,CAHA,2CjB2/CJ,CKh3DI,mCY8WF,0CAcI,mBjBw/CJ,CiBtgDA,0CAcI,oBjBw/CJ,CACF,CiBr/CI,2DAEE,uDAAA,CADA,+BjBw/CN,CiBz/CI,wDAEE,uDAAA,CADA,+BjBw/CN,CiBz/CI,kDAEE,uDAAA,CADA,+BjBw/CN,CiBn/CI,wCACE,YjBq/CN,CiBh/CI,wDACE,YjBk/CN,CiB9+CI,oCACE,WjBg/CN,CiB3+CE,2BAGE,eAAA,CADA,eAAA,CADA,iBjB++CJ,CKv4DI,mCYuZF,qCAOI,mBjB6+CJ,CiBp/CA,qCAOI,oBjB6+CJ,CACF,CiBv+CM,8DAGE,eAAA,CADA,eAAA,CAEA,eAAA,CAHA,ejB4+CR,CiBn+CE,kCAEE,MjBy+CJ,CiB3+CE,kCAEE,OjBy+CJ,CiB3+CE,wBAME,uCAAA,CAFA,aAAA,CACA,YAAA,CAJA,iBAAA,CAEA,YjBw+CJ,CKv4DI,wCY4ZF,wBAUI,YjBq+CJ,CACF,CiBl+CI,8BAIE,6BAAA,CAKA,UAAA,CARA,oBAAA,CAEA,WAAA,CAEA,+CAAA,CAAA,uCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CANA,UjB2+CN,CiBj+CM,wCACE,oBjBm+CR,CiB79CE,yBAGE,gBAAA,CADA,eAAA,CAEA,eAAA,CAHA,ajBk+CJ,CiB39CE,0BASE,2BAAA,CACA,oBAAA,CALA,uCAAA,CAJA,mBAAA,CAKA,gBAAA,CACA,eAAA,CAJA,aAAA,CADA,eAAA,CAEA,eAAA,CAIA,sBjB+9CJ,CK56DI,wCYqcF,0BAeI,oBAAA,CADA,ejB89CJ,CACF,CK39DM,6DY8eJ,0BAqBI,oBAAA,CADA,ejB89CJ,CACF,CiB19CI,+BAEE,wBAAA,CADA,yBjB69CN,CiBv9CE,yBAEE,gBAAA,CACA,iBAAA,CAFA,ajB29CJ,CiBr9CE,uBAEE,wBAAA,CADA,+BjBw9CJ,CkB9nEA,WACE,iBAAA,CACA,SlBioEF,CkB9nEE,kBAOE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAHA,gCAAA,CAHA,QAAA,CAEA,gBAAA,CADA,YAAA,CAOA,SAAA,CAVA,iBAAA,CACA,sBAAA,CAQA,mCAAA,CAEA,oElBgoEJ,CkB1nEI,+DACE,gBAAA,CAEA,SAAA,CADA,+BAAA,CAEA,sFACE,CADF,8ElB4nEN,CkBhoEI,4DACE,gBAAA,CAEA,SAAA,CADA,+BAAA,CAEA,mFACE,CADF,8ElB4nEN,CkBhoEI,sDACE,gBAAA,CAEA,SAAA,CADA,+BAAA,CAEA,8ElB4nEN,CkBrnEI,wBAUE,+BAAA,CAAA,8CAAA,CAFA,6BAAA,CAAA,8BAAA,CACA,YAAA,CAEA,UAAA,CANA,QAAA,CAFA,QAAA,CAIA,kBAAA,CADA,iBAAA,CALA,iBAAA,CACA,KAAA,CAEA,OlB8nEN,CkBlnEE,iBAOE,mBAAA,CAFA,eAAA,CACA,oBAAA,CAJA,QAAA,CADA,kBAAA,CAGA,aAAA,CADA,SlBwnEJ,CkBhnEE,iBACE,kBlBknEJ,CkB9mEE,2BAGE,kBAAA,CAAA,oBlBonEJ,CkBvnEE,2BAGE,mBAAA,CAAA,mBlBonEJ,CkBvnEE,iBAKE,cAAA,CAJA,aAAA,CAGA,YAAA,CAKA,uBAAA,CAHA,2CACE,CALF,UlBqnEJ,CkB3mEI,4CACE,+BlB6mEN,CkB9mEI,yCACE,+BlB6mEN,CkB9mEI,mCACE,+BlB6mEN,CkBzmEI,uBACE,qDlB2mEN,CmB/rEA,YAIE,qBAAA,CADA,aAAA,CAGA,gBAAA,CALA,uBAAA,CAAA,eAAA,CACA,UAAA,CAGA,anBmsEF,CmB/rEE,aATF,YAUI,YnBksEF,CACF,CKphEI,wCc3KF,+BAMI,anBssEJ,CmB5sEA,+BAMI,cnBssEJ,CmB5sEA,qBAWI,2CAAA,CAHA,aAAA,CAEA,WAAA,CANA,cAAA,CACA,KAAA,CAOA,uBAAA,CACA,iEACE,CALF,aAAA,CAFA,SnBqsEJ,CmB1rEI,mEACE,8BAAA,CACA,6BnB4rEN,CmBzrEM,6EACE,8BnB2rER,CmBtrEI,6CAEE,QAAA,CAAA,MAAA,CACA,QAAA,CAEA,eAAA,CAJA,iBAAA,CACA,OAAA,CAEA,qBAAA,CAFA,KnB2rEN,CACF,CKnkEI,sCctKJ,YAuDI,QnBsrEF,CmBnrEE,mBACE,WnBqrEJ,CmBjrEE,6CACE,UnBmrEJ,CACF,CmB/qEE,uBACE,YAAA,CACA,OnBirEJ,CKllEI,mCcjGF,uBAMI,QnBirEJ,CmB9qEI,8BACE,WnBgrEN,CmB5qEI,qCACE,anB8qEN,CmB1qEI,+CACE,kBnB4qEN,CACF,CmBvqEE,wBAUE,uBAAA,CANA,kCAAA,CAAA,0BAAA,CAHA,cAAA,CACA,eAAA,CASA,yDAAA,CAFA,oBnBsqEJ,CmBjqEI,8BACE,+CnBmqEN,CmB/pEI,2CAEE,YAAA,CADA,WnBkqEN,CmB7pEI,iDACE,oDnB+pEN,CmB5pEM,uDACE,0CnB8pER,CmBhpEE,wCAGE,wBACE,qBnBgpEJ,CmB5oEE,6BACE,kCnB8oEJ,CmB/oEE,6BACE,iCnB8oEJ,CACF,CK1mEI,wCc5BF,YAME,0BAAA,CADA,QAAA,CAEA,SAAA,CANA,cAAA,CACA,KAAA,CAMA,sDACE,CALF,OAAA,CADA,SnB+oEF,CmBpoEE,4CAEE,WAAA,CACA,SAAA,CACA,4CACE,CAJF,UnByoEJ,CACF,CoBtzEA,iBACE,GACE,QpBwzEF,CoBrzEA,GACE,apBuzEF,CACF,CoBnzEA,gBACE,GAEE,SAAA,CADA,0BpBszEF,CoBlzEA,IACE,SpBozEF,CoBjzEA,GAEE,SAAA,CADA,uBpBozEF,CACF,CoB3yEA,MACE,mgBAAA,CACA,oiBAAA,CACA,0nBAAA,CACA,mhBpB6yEF,CoBvyEA,WAOE,kCAAA,CAAA,0BAAA,CANA,aAAA,CACA,gBAAA,CACA,eAAA,CAEA,uCAAA,CAGA,uBAAA,CAJA,kBpB6yEF,CoBtyEE,iBACE,UpBwyEJ,CoBpyEE,iBACE,oBAAA,CAEA,aAAA,CACA,qBAAA,CAFA,UpBwyEJ,CoBnyEI,+BAEE,iBpBqyEN,CoBvyEI,+BAEE,kBpBqyEN,CoBvyEI,qBACE,gBpBsyEN,CoBjyEI,kDACE,iBpBoyEN,CoBryEI,kDACE,kBpBoyEN,CoBryEI,kDAEE,iBpBmyEN,CoBryEI,kDAEE,kBpBmyEN,CoB9xEE,iCAGE,iBpBmyEJ,CoBtyEE,iCAGE,kBpBmyEJ,CoBtyEE,uBACE,oBAAA,CACA,6BAAA,CAEA,eAAA,CACA,sBAAA,CACA,qBpBgyEJ,CoB5xEE,kBACE,YAAA,CAMA,gBAAA,CALA,SAAA,CAMA,oBAAA,CAJA,gBAAA,CAKA,WAAA,CAHA,eAAA,CADA,SAAA,CAFA,UpBoyEJ,CoB3xEI,iDACE,4BpB6xEN,CoBxxEE,iBACE,eAAA,CACA,sBpB0xEJ,CoBvxEI,gDACE,2BpByxEN,CoBrxEI,kCAIE,kBpB6xEN,CoBjyEI,kCAIE,iBpB6xEN,CoBjyEI,wBAME,6BAAA,CAIA,UAAA,CATA,oBAAA,CAEA,YAAA,CAIA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CAJA,uBAAA,CAHA,WpB+xEN,CoBnxEI,iCACE,apBqxEN,CoBjxEI,iCACE,gDAAA,CAAA,wCpBmxEN,CoB/wEI,+BACE,8CAAA,CAAA,sCpBixEN,CoB7wEI,+BACE,8CAAA,CAAA,sCpB+wEN,CoB3wEI,sCACE,qDAAA,CAAA,6CpB6wEN,CqBp6EA,SASE,2CAAA,CAFA,gCAAA,CAHA,aAAA,CAIA,eAAA,CAFA,aAAA,CADA,UAAA,CAFA,SrB26EF,CqBl6EE,aAZF,SAaI,YrBq6EF,CACF,CK1vEI,wCgBzLJ,SAkBI,YrBq6EF,CACF,CqBl6EE,iBACE,mBrBo6EJ,CqBh6EE,yBAEE,iBrBs6EJ,CqBx6EE,yBAEE,kBrBs6EJ,CqBx6EE,eAME,eAAA,CADA,eAAA,CAJA,QAAA,CAEA,SAAA,CACA,kBrBo6EJ,CqB95EE,eACE,oBAAA,CACA,aAAA,CACA,kBAAA,CAAA,mBrBg6EJ,CqB35EE,eAOE,kCAAA,CAAA,0BAAA,CANA,aAAA,CAEA,eAAA,CADA,gBAAA,CAMA,UAAA,CAJA,uCAAA,CACA,oBAAA,CAIA,8DrB45EJ,CqBv5EI,iEAEE,aAAA,CACA,SrBw5EN,CqB35EI,8DAEE,aAAA,CACA,SrBw5EN,CqB35EI,wDAEE,aAAA,CACA,SrBw5EN,CqBn5EM,2CACE,qBrBq5ER,CqBt5EM,2CACE,qBrBw5ER,CqBz5EM,2CACE,qBrB25ER,CqB55EM,2CACE,qBrB85ER,CqB/5EM,2CACE,oBrBi6ER,CqBl6EM,2CACE,qBrBo6ER,CqBr6EM,2CACE,qBrBu6ER,CqBx6EM,2CACE,qBrB06ER,CqB36EM,4CACE,qBrB66ER,CqB96EM,4CACE,oBrBg7ER,CqBj7EM,4CACE,qBrBm7ER,CqBp7EM,4CACE,qBrBs7ER,CqBv7EM,4CACE,qBrBy7ER,CqB17EM,4CACE,qBrB47ER,CqB77EM,4CACE,oBrB+7ER,CqBz7EI,gCAEE,SAAA,CADA,yBAAA,CAEA,wCrB27EN,CsBxgFA,MACE,wStB2gFF,CsBlgFE,qBAEE,mBAAA,CADA,kBtBsgFJ,CsBjgFE,8BAEE,iBtB4gFJ,CsB9gFE,8BAEE,gBtB4gFJ,CsB9gFE,oBAUE,+CAAA,CACA,oBAAA,CAVA,oBAAA,CAKA,gBAAA,CADA,eAAA,CAGA,qBAAA,CADA,eAAA,CAJA,kBAAA,CACA,uBAAA,CAKA,qBtBqgFJ,CsBhgFI,0BAGE,uCAAA,CAFA,aAAA,CACA,YAAA,CAEA,6CtBkgFN,CsB7/EM,gEAGE,0CAAA,CADA,+BtB+/ER,CsBz/EI,yBACE,uBtB2/EN,CsBn/EI,gCAME,oDAAA,CAMA,UAAA,CAXA,oBAAA,CAEA,YAAA,CACA,iBAAA,CAGA,qCAAA,CAAA,6BAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CACA,iCAAA,CANA,0BAAA,CAHA,WtB+/EN,CsBj/EI,6DACE,0CtBm/EN,CsBp/EI,0DACE,0CtBm/EN,CsBp/EI,oDACE,0CtBm/EN,CuB5jFA,iBACE,GACE,uDAAA,CACA,oBvB+jFF,CuB5jFA,IACE,6BAAA,CACA,kBvB8jFF,CuB3jFA,GACE,wBAAA,CACA,oBvB6jFF,CACF,CuBrjFA,MACE,wBvBujFF,CuBjjFA,YAwBE,kCAAA,CAAA,0BAAA,CALA,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CACA,sCAAA,CAfA,+IACE,CAYF,8BAAA,CASA,SAAA,CAxBA,iBAAA,CACA,uBAAA,CAoBA,4BAAA,CAIA,uDACE,CAZF,6BAAA,CADA,SvB4jFF,CuB1iFE,oBAGE,SAAA,CADA,uBAAA,CAEA,2EACE,CAJF,SvB+iFJ,CuBriFE,4DACE,sCvBuiFJ,CuBxiFE,yDACE,sCvBuiFJ,CuBxiFE,mDACE,sCvBuiFJ,CuBniFE,mBAEE,gBAAA,CADA,avBsiFJ,CuBliFI,2CACE,YvBoiFN,CuBhiFI,0CACE,evBkiFN,CuB1hFA,eACE,eAAA,CAEA,YAAA,CADA,kBvB8hFF,CuB1hFE,yBACE,avB4hFJ,CuBxhFE,6BACE,oBAAA,CAGA,iBvBwhFJ,CuBphFE,sBAOE,cAAA,CAFA,sCAAA,CADA,eAAA,CADA,YAAA,CAGA,YAAA,CALA,iBAAA,CAOA,wBAAA,CAAA,qBAAA,CAAA,gBAAA,CANA,SvB4hFJ,CuBnhFI,qCACE,UAAA,CACA,uBvBqhFN,CuBlhFM,gEACE,UvBohFR,CuBrhFM,6DACE,UvBohFR,CuBrhFM,uDACE,UvBohFR,CuB5gFI,4BAYE,oDAAA,CACA,iBAAA,CAIA,UAAA,CARA,YAAA,CANA,YAAA,CAOA,cAAA,CACA,cAAA,CAVA,iBAAA,CACA,KAAA,CAYA,2CACE,CARF,wBAAA,CACA,6BAAA,CAJA,UvBuhFN,CuBvgFM,4CAGE,8CACE,2BvBugFR,CACF,CuBngFM,gDAIE,cAAA,CAHA,2CvBsgFR,CuB9/EI,2BAEE,sCAAA,CADA,iBvBigFN,CuB5/EI,qFACE,+BvB8/EN,CuB//EI,kFACE,+BvB8/EN,CuB//EI,4EACE,+BvB8/EN,CuB3/EM,2FACE,0CvB6/ER,CuB9/EM,wFACE,0CvB6/ER,CuB9/EM,kFACE,0CvB6/ER,CuBx/EI,0CAGE,cAAA,CADA,eAAA,CADA,SvB4/EN,CuBt/EI,8CACE,oBAAA,CACA,evBw/EN,CuBr/EM,qDAME,mCAAA,CALA,oBAAA,CACA,mBAAA,CAEA,qBAAA,CACA,iDAAA,CAFA,qBvB0/ER,CuBn/EQ,iBAVF,qDAWI,WvBs/ER,CuBn/EQ,mEACE,mCvBq/EV,CACF,CwBntFA,kBAKE,exB+tFF,CwBpuFA,kBAKE,gBxB+tFF,CwBpuFA,QASE,2CAAA,CACA,oBAAA,CAEA,8BAAA,CALA,uCAAA,CAHA,aAAA,CAIA,eAAA,CAGA,YAAA,CALA,mBAAA,CALA,cAAA,CACA,UAAA,CAWA,yBAAA,CACA,mGACE,CAZF,SxBiuFF,CwB/sFE,aArBF,QAsBI,YxBktFF,CACF,CwB/sFE,kBACE,wBxBitFJ,CwB7sFE,gBAEE,SAAA,CAEA,mBAAA,CAHA,+BAAA,CAEA,uBxBgtFJ,CwB5sFI,0BACE,8BxB8sFN,CwBzsFE,mCAEE,0CAAA,CADA,+BxB4sFJ,CwB7sFE,gCAEE,0CAAA,CADA,+BxB4sFJ,CwB7sFE,0BAEE,0CAAA,CADA,+BxB4sFJ,CwBvsFE,YACE,oBAAA,CACA,oBxBysFJ,CyB7vFA,oBACE,GACE,mBzBgwFF,CACF,CyBxvFA,MACE,wfzB0vFF,CyBpvFA,YACE,aAAA,CAEA,eAAA,CADA,azBwvFF,CyBpvFE,+BAOE,kBAAA,CAAA,kBzBqvFJ,CyB5vFE,+BAOE,iBAAA,CAAA,mBzBqvFJ,CyB5vFE,qBAQE,aAAA,CAEA,cAAA,CADA,YAAA,CARA,iBAAA,CAKA,UzBsvFJ,CyB/uFI,qCAIE,iBzBuvFN,CyB3vFI,qCAIE,kBzBuvFN,CyB3vFI,2BAKE,6BAAA,CAKA,UAAA,CATA,oBAAA,CAEA,YAAA,CAGA,yCAAA,CAAA,iCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CAPA,WzByvFN,CyB5uFE,kBAUE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CACA,oBAAA,CAJA,kBAAA,CADA,YAAA,CASA,SAAA,CANA,aAAA,CADA,SAAA,CALA,iBAAA,CAgBA,4BAAA,CAfA,UAAA,CAYA,+CACE,CAZF,SzB0vFJ,CyBzuFI,gEACE,gBAAA,CACA,SAAA,CACA,8CACE,CADF,sCzB2uFN,CyB9uFI,6DACE,gBAAA,CACA,SAAA,CACA,2CACE,CADF,sCzB2uFN,CyB9uFI,uDACE,gBAAA,CACA,SAAA,CACA,sCzB2uFN,CyBruFI,wBAGE,oCACE,gCzBquFN,CyBjuFI,2CACE,czBmuFN,CACF,CyB9tFE,kBACE,kBzBguFJ,CyB5tFE,4BAGE,kBAAA,CAAA,oBzBmuFJ,CyBtuFE,4BAGE,mBAAA,CAAA,mBzBmuFJ,CyBtuFE,kBAME,cAAA,CALA,aAAA,CAIA,YAAA,CAKA,uBAAA,CAHA,2CACE,CAJF,kBAAA,CAFA,UzBouFJ,CyBztFI,6CACE,+BzB2tFN,CyB5tFI,0CACE,+BzB2tFN,CyB5tFI,oCACE,+BzB2tFN,CyBvtFI,wBACE,qDzBytFN,C0B1zFA,MAEI,uWAAA,CAAA,8WAAA,CAAA,sPAAA,CAAA,8xBAAA,CAAA,0MAAA,CAAA,gbAAA,CAAA,gMAAA,CAAA,iQAAA,CAAA,0VAAA,CAAA,6aAAA,CAAA,8SAAA,CAAA,gM1Bm1FJ,C0Bv0FE,4CAQE,8CAAA,CACA,2BAAA,CACA,mBAAA,CACA,8BAAA,CANA,mCAAA,CAHA,iBAAA,CAIA,gBAAA,CAHA,iBAAA,CACA,eAAA,CAGA,uB1B80FJ,C0Bv0FI,aAdF,4CAeI,e1B20FJ,CACF,C0Bv0FI,gDACE,qB1B00FN,C0Bt0FI,gHAEE,iBAAA,CADA,c1B00FN,C0B30FI,0GAEE,iBAAA,CADA,c1B00FN,C0B30FI,8FAEE,iBAAA,CADA,c1B00FN,C0Br0FI,4FACE,iB1Bw0FN,C0Bp0FI,kFACE,e1Bu0FN,C0Bn0FI,0FACE,Y1Bs0FN,C0Bl0FI,8EACE,mB1Bq0FN,C0Bh0FE,sEAME,iBAAA,CAAA,mB1Bw0FJ,C0B90FE,sEAME,kBAAA,CAAA,kB1Bw0FJ,C0B90FE,sEAUE,uB1Bo0FJ,C0B90FE,sEAUE,wB1Bo0FJ,C0B90FE,sEAWE,4B1Bm0FJ,C0B90FE,4IAYE,6B1Bk0FJ,C0B90FE,sEAYE,4B1Bk0FJ,C0B90FE,kDAQE,0BAAA,CACA,WAAA,CAFA,eAAA,CAHA,eAAA,CACA,oBAAA,CAAA,iBAAA,CAHA,iB1B40FJ,C0B/zFI,kFACE,e1Bk0FN,C0B9zFI,oFAGE,U1By0FN,C0B50FI,oFAGE,W1By0FN,C0B50FI,gEAME,wBCsIU,CDjIV,UAAA,CANA,WAAA,CAEA,kDAAA,CAAA,0CAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CATA,iBAAA,CACA,UAAA,CAEA,U1Bw0FN,C0B7zFI,4DACE,4D1Bg0FN,C0B3yFE,iEACE,oB1B8yFJ,C0B/yFE,2DACE,oB1B8yFJ,C0B/yFE,+CACE,oB1B8yFJ,C0B1yFE,wEACE,0B1B6yFJ,C0B9yFE,kEACE,0B1B6yFJ,C0B9yFE,sDACE,0B1B6yFJ,C0B1yFI,+EACE,wBAnBG,CAoBH,kDAAA,CAAA,0C1B4yFN,C0B9yFI,yEACE,wBAnBG,CAoBH,0C1B4yFN,C0B9yFI,6DACE,wBAnBG,CAoBH,kDAAA,CAAA,0C1B4yFN,C0BxyFI,8EACE,a1B0yFN,C0B3yFI,wEACE,a1B0yFN,C0B3yFI,4DACE,a1B0yFN,C0B1zFE,oFACE,oB1B6zFJ,C0B9zFE,8EACE,oB1B6zFJ,C0B9zFE,kEACE,oB1B6zFJ,C0BzzFE,2FACE,0B1B4zFJ,C0B7zFE,qFACE,0B1B4zFJ,C0B7zFE,yEACE,0B1B4zFJ,C0BzzFI,kGACE,wBAnBG,CAoBH,sDAAA,CAAA,8C1B2zFN,C0B7zFI,4FACE,wBAnBG,CAoBH,8C1B2zFN,C0B7zFI,gFACE,wBAnBG,CAoBH,sDAAA,CAAA,8C1B2zFN,C0BvzFI,iGACE,a1ByzFN,C0B1zFI,2FACE,a1ByzFN,C0B1zFI,+EACE,a1ByzFN,C0Bz0FE,uEACE,oB1B40FJ,C0B70FE,iEACE,oB1B40FJ,C0B70FE,qDACE,oB1B40FJ,C0Bx0FE,8EACE,0B1B20FJ,C0B50FE,wEACE,0B1B20FJ,C0B50FE,4DACE,0B1B20FJ,C0Bx0FI,qFACE,wBAnBG,CAoBH,kDAAA,CAAA,0C1B00FN,C0B50FI,+EACE,wBAnBG,CAoBH,0C1B00FN,C0B50FI,mEACE,wBAnBG,CAoBH,kDAAA,CAAA,0C1B00FN,C0Bt0FI,oFACE,a1Bw0FN,C0Bz0FI,8EACE,a1Bw0FN,C0Bz0FI,kEACE,a1Bw0FN,C0Bx1FE,iFACE,oB1B21FJ,C0B51FE,2EACE,oB1B21FJ,C0B51FE,+DACE,oB1B21FJ,C0Bv1FE,wFACE,0B1B01FJ,C0B31FE,kFACE,0B1B01FJ,C0B31FE,sEACE,0B1B01FJ,C0Bv1FI,+FACE,wBAnBG,CAoBH,iDAAA,CAAA,yC1By1FN,C0B31FI,yFACE,wBAnBG,CAoBH,yC1By1FN,C0B31FI,6EACE,wBAnBG,CAoBH,iDAAA,CAAA,yC1By1FN,C0Br1FI,8FACE,a1Bu1FN,C0Bx1FI,wFACE,a1Bu1FN,C0Bx1FI,4EACE,a1Bu1FN,C0Bv2FE,iFACE,oB1B02FJ,C0B32FE,2EACE,oB1B02FJ,C0B32FE,+DACE,oB1B02FJ,C0Bt2FE,wFACE,0B1By2FJ,C0B12FE,kFACE,0B1By2FJ,C0B12FE,sEACE,0B1By2FJ,C0Bt2FI,+FACE,wBAnBG,CAoBH,qDAAA,CAAA,6C1Bw2FN,C0B12FI,yFACE,wBAnBG,CAoBH,6C1Bw2FN,C0B12FI,6EACE,wBAnBG,CAoBH,qDAAA,CAAA,6C1Bw2FN,C0Bp2FI,8FACE,a1Bs2FN,C0Bv2FI,wFACE,a1Bs2FN,C0Bv2FI,4EACE,a1Bs2FN,C0Bt3FE,gFACE,oB1By3FJ,C0B13FE,0EACE,oB1By3FJ,C0B13FE,8DACE,oB1By3FJ,C0Br3FE,uFACE,0B1Bw3FJ,C0Bz3FE,iFACE,0B1Bw3FJ,C0Bz3FE,qEACE,0B1Bw3FJ,C0Br3FI,8FACE,wBAnBG,CAoBH,sDAAA,CAAA,8C1Bu3FN,C0Bz3FI,wFACE,wBAnBG,CAoBH,8C1Bu3FN,C0Bz3FI,4EACE,wBAnBG,CAoBH,sDAAA,CAAA,8C1Bu3FN,C0Bn3FI,6FACE,a1Bq3FN,C0Bt3FI,uFACE,a1Bq3FN,C0Bt3FI,2EACE,a1Bq3FN,C0Br4FE,wFACE,oB1Bw4FJ,C0Bz4FE,kFACE,oB1Bw4FJ,C0Bz4FE,sEACE,oB1Bw4FJ,C0Bp4FE,+FACE,0B1Bu4FJ,C0Bx4FE,yFACE,0B1Bu4FJ,C0Bx4FE,6EACE,0B1Bu4FJ,C0Bp4FI,sGACE,wBAnBG,CAoBH,qDAAA,CAAA,6C1Bs4FN,C0Bx4FI,gGACE,wBAnBG,CAoBH,6C1Bs4FN,C0Bx4FI,oFACE,wBAnBG,CAoBH,qDAAA,CAAA,6C1Bs4FN,C0Bl4FI,qGACE,a1Bo4FN,C0Br4FI,+FACE,a1Bo4FN,C0Br4FI,mFACE,a1Bo4FN,C0Bp5FE,mFACE,oB1Bu5FJ,C0Bx5FE,6EACE,oB1Bu5FJ,C0Bx5FE,iEACE,oB1Bu5FJ,C0Bn5FE,0FACE,0B1Bs5FJ,C0Bv5FE,oFACE,0B1Bs5FJ,C0Bv5FE,wEACE,0B1Bs5FJ,C0Bn5FI,iGACE,wBAnBG,CAoBH,qDAAA,CAAA,6C1Bq5FN,C0Bv5FI,2FACE,wBAnBG,CAoBH,6C1Bq5FN,C0Bv5FI,+EACE,wBAnBG,CAoBH,qDAAA,CAAA,6C1Bq5FN,C0Bj5FI,gGACE,a1Bm5FN,C0Bp5FI,0FACE,a1Bm5FN,C0Bp5FI,8EACE,a1Bm5FN,C0Bn6FE,0EACE,oB1Bs6FJ,C0Bv6FE,oEACE,oB1Bs6FJ,C0Bv6FE,wDACE,oB1Bs6FJ,C0Bl6FE,iFACE,0B1Bq6FJ,C0Bt6FE,2EACE,0B1Bq6FJ,C0Bt6FE,+DACE,0B1Bq6FJ,C0Bl6FI,wFACE,wBAnBG,CAoBH,oDAAA,CAAA,4C1Bo6FN,C0Bt6FI,kFACE,wBAnBG,CAoBH,4C1Bo6FN,C0Bt6FI,sEACE,wBAnBG,CAoBH,oDAAA,CAAA,4C1Bo6FN,C0Bh6FI,uFACE,a1Bk6FN,C0Bn6FI,iFACE,a1Bk6FN,C0Bn6FI,qEACE,a1Bk6FN,C0Bl7FE,gEACE,oB1Bq7FJ,C0Bt7FE,0DACE,oB1Bq7FJ,C0Bt7FE,8CACE,oB1Bq7FJ,C0Bj7FE,uEACE,0B1Bo7FJ,C0Br7FE,iEACE,0B1Bo7FJ,C0Br7FE,qDACE,0B1Bo7FJ,C0Bj7FI,8EACE,wBAnBG,CAoBH,iDAAA,CAAA,yC1Bm7FN,C0Br7FI,wEACE,wBAnBG,CAoBH,yC1Bm7FN,C0Br7FI,4DACE,wBAnBG,CAoBH,iDAAA,CAAA,yC1Bm7FN,C0B/6FI,6EACE,a1Bi7FN,C0Bl7FI,uEACE,a1Bi7FN,C0Bl7FI,2DACE,a1Bi7FN,C0Bj8FE,oEACE,oB1Bo8FJ,C0Br8FE,8DACE,oB1Bo8FJ,C0Br8FE,kDACE,oB1Bo8FJ,C0Bh8FE,2EACE,0B1Bm8FJ,C0Bp8FE,qEACE,0B1Bm8FJ,C0Bp8FE,yDACE,0B1Bm8FJ,C0Bh8FI,kFACE,wBAnBG,CAoBH,qDAAA,CAAA,6C1Bk8FN,C0Bp8FI,4EACE,wBAnBG,CAoBH,6C1Bk8FN,C0Bp8FI,gEACE,wBAnBG,CAoBH,qDAAA,CAAA,6C1Bk8FN,C0B97FI,iFACE,a1Bg8FN,C0Bj8FI,2EACE,a1Bg8FN,C0Bj8FI,+DACE,a1Bg8FN,C0Bh9FE,wEACE,oB1Bm9FJ,C0Bp9FE,kEACE,oB1Bm9FJ,C0Bp9FE,sDACE,oB1Bm9FJ,C0B/8FE,+EACE,0B1Bk9FJ,C0Bn9FE,yEACE,0B1Bk9FJ,C0Bn9FE,6DACE,0B1Bk9FJ,C0B/8FI,sFACE,wBAnBG,CAoBH,mDAAA,CAAA,2C1Bi9FN,C0Bn9FI,gFACE,wBAnBG,CAoBH,2C1Bi9FN,C0Bn9FI,oEACE,wBAnBG,CAoBH,mDAAA,CAAA,2C1Bi9FN,C0B78FI,qFACE,a1B+8FN,C0Bh9FI,+EACE,a1B+8FN,C0Bh9FI,mEACE,a1B+8FN,C4BjnGA,MACE,wM5BonGF,C4B3mGE,sBACE,uCAAA,CACA,gB5B8mGJ,C4B3mGI,mCACE,a5B6mGN,C4B9mGI,mCACE,c5B6mGN,C4BzmGM,4BACE,sB5B2mGR,C4BxmGQ,mCACE,gC5B0mGV,C4BtmGQ,2DAEE,SAAA,CADA,uBAAA,CAEA,e5BwmGV,C4BpmGQ,0EAEE,SAAA,CADA,uB5BumGV,C4BxmGQ,uEAEE,SAAA,CADA,uB5BumGV,C4BxmGQ,iEAEE,SAAA,CADA,uB5BumGV,C4BlmGQ,yCACE,Y5BomGV,C4B7lGE,0BAEE,eAAA,CADA,e5BgmGJ,C4B5lGI,+BACE,oB5B8lGN,C4BzlGE,gDACE,Y5B2lGJ,C4BvlGE,8BAEE,+BAAA,CADA,oBAAA,CAGA,WAAA,CAGA,SAAA,CADA,4BAAA,CAEA,4DACE,CAJF,0B5B2lGJ,C4BllGI,aAdF,8BAeI,+BAAA,CAEA,SAAA,CADA,uB5BslGJ,CACF,C4BllGI,wCACE,6B5BolGN,C4BhlGI,oCACE,+B5BklGN,C4B9kGI,qCAIE,6BAAA,CAKA,UAAA,CARA,oBAAA,CAEA,YAAA,CAEA,2CAAA,CAAA,mCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CANA,W5BulGN,C4B1kGQ,mDACE,oB5B4kGV,C6B1rGE,kCAEE,iB7BgsGJ,C6BlsGE,kCAEE,kB7BgsGJ,C6BlsGE,wBAGE,yCAAA,CAFA,oBAAA,CAGA,SAAA,CACA,mC7B6rGJ,C6BxrGI,aAVF,wBAWI,Y7B2rGJ,CACF,C6BvrGE,mFAEE,SAAA,CACA,2CACE,CADF,mC7ByrGJ,C6B5rGE,gFAEE,SAAA,CACA,wCACE,CADF,mC7ByrGJ,C6B5rGE,0EAEE,SAAA,CACA,mC7ByrGJ,C6BnrGE,mFAEE,+B7BqrGJ,C6BvrGE,gFAEE,+B7BqrGJ,C6BvrGE,0EAEE,+B7BqrGJ,C6BjrGE,oBACE,yBAAA,CACA,uBAAA,CAGA,yE7BirGJ,CKljGI,sCwBrHE,qDACE,uB7B0qGN,CACF,C6BrqGE,0CACE,yB7BuqGJ,C6BxqGE,uCACE,yB7BuqGJ,C6BxqGE,iCACE,yB7BuqGJ,C6BnqGE,sBACE,0B7BqqGJ,C8BhuGE,2BACE,a9BmuGJ,CK9iGI,wCyBtLF,2BAKI,e9BmuGJ,CACF,C8BhuGI,6BAEE,0BAAA,CAAA,2BAAA,CACA,eAAA,CACA,iBAAA,CAHA,yBAAA,CAAA,sBAAA,CAAA,iB9BquGN,C8B/tGM,2CACE,kB9BiuGR,C+BlvGE,kDACE,kCAAA,CAAA,0B/BqvGJ,C+BtvGE,+CACE,0B/BqvGJ,C+BtvGE,yCACE,kCAAA,CAAA,0B/BqvGJ,C+BjvGE,uBACE,4C/BmvGJ,C+B/uGE,uBACE,4C/BivGJ,C+B7uGE,4BACE,qC/B+uGJ,C+B5uGI,mCACE,a/B8uGN,C+B1uGI,kCACE,a/B4uGN,C+BvuGE,0BAKE,eAAA,CAJA,aAAA,CACA,YAAA,CAEA,aAAA,CADA,kBAAA,CAAA,mB/B2uGJ,C+BtuGI,uCACE,e/BwuGN,C+BpuGI,sCACE,kB/BsuGN,CgCrxGA,MACE,8LhCwxGF,CgC/wGE,oBACE,iBAAA,CAEA,gBAAA,CADA,ahCmxGJ,CgC/wGI,wCACE,uBhCixGN,CgC7wGI,gCAEE,eAAA,CADA,gBhCgxGN,CgCzwGM,wCACE,mBhC2wGR,CgCrwGE,8BAGE,oBhC0wGJ,CgC7wGE,8BAGE,mBhC0wGJ,CgC7wGE,8BAIE,4BhCywGJ,CgC7wGE,4DAKE,6BhCwwGJ,CgC7wGE,8BAKE,4BhCwwGJ,CgC7wGE,oBAME,cAAA,CALA,aAAA,CACA,ehC2wGJ,CgCpwGI,kCACE,uCAAA,CACA,oBhCswGN,CgClwGI,wCAEE,uCAAA,CADA,YhCqwGN,CgChwGI,oCAGE,WhC4wGN,CgC/wGI,oCAGE,UhC4wGN,CgC/wGI,0BAME,6BAAA,CAOA,UAAA,CARA,WAAA,CAEA,yCAAA,CAAA,iCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CATA,iBAAA,CACA,UAAA,CASA,sBAAA,CACA,yBAAA,CARA,UhC2wGN,CgC/vGM,oCACE,wBhCiwGR,CgC5vGI,4BACE,YhC8vGN,CgCzvGI,4CACE,YhC2vGN,CiC90GE,qDACE,mBAAA,CACA,cAAA,CACA,uBjCi1GJ,CiCp1GE,kDACE,mBAAA,CACA,cAAA,CACA,uBjCi1GJ,CiCp1GE,4CACE,mBAAA,CACA,cAAA,CACA,uBjCi1GJ,CiC90GI,yDAGE,iBAAA,CADA,eAAA,CADA,ajCk1GN,CiCn1GI,sDAGE,iBAAA,CADA,eAAA,CADA,ajCk1GN,CiCn1GI,gDAGE,iBAAA,CADA,eAAA,CADA,ajCk1GN,CkCx1GE,gCACE,sClC21GJ,CkC51GE,6BACE,sClC21GJ,CkC51GE,uBACE,sClC21GJ,CkCx1GE,cACE,yClC01GJ,CkC90GE,4DACE,oClCg1GJ,CkCj1GE,yDACE,oClCg1GJ,CkCj1GE,mDACE,oClCg1GJ,CkCx0GE,6CACE,qClC00GJ,CkC30GE,0CACE,qClC00GJ,CkC30GE,oCACE,qClC00GJ,CkCh0GE,oDACE,oClCk0GJ,CkCn0GE,iDACE,oClCk0GJ,CkCn0GE,2CACE,oClCk0GJ,CkCzzGE,gDACE,qClC2zGJ,CkC5zGE,6CACE,qClC2zGJ,CkC5zGE,uCACE,qClC2zGJ,CkCtzGE,gCACE,kClCwzGJ,CkCzzGE,6BACE,kClCwzGJ,CkCzzGE,uBACE,kClCwzGJ,CkClzGE,qCACE,sClCozGJ,CkCrzGE,kCACE,sClCozGJ,CkCrzGE,4BACE,sClCozGJ,CkC7yGE,yCACE,sClC+yGJ,CkChzGE,sCACE,sClC+yGJ,CkChzGE,gCACE,sClC+yGJ,CkCxyGE,yCACE,qClC0yGJ,CkC3yGE,sCACE,qClC0yGJ,CkC3yGE,gCACE,qClC0yGJ,CkCjyGE,gDACE,qClCmyGJ,CkCpyGE,6CACE,qClCmyGJ,CkCpyGE,uCACE,qClCmyGJ,CkC3xGE,6CACE,sClC6xGJ,CkC9xGE,0CACE,sClC6xGJ,CkC9xGE,oCACE,sClC6xGJ,CkClxGE,yDACE,qClCoxGJ,CkCrxGE,sDACE,qClCoxGJ,CkCrxGE,gDACE,qClCoxGJ,CkC/wGE,iCAGE,mBAAA,CAFA,gBAAA,CACA,gBlCkxGJ,CkCpxGE,8BAGE,mBAAA,CAFA,gBAAA,CACA,gBlCkxGJ,CkCpxGE,wBAGE,mBAAA,CAFA,gBAAA,CACA,gBlCkxGJ,CkC9wGE,eACE,4ClCgxGJ,CkC7wGE,eACE,4ClC+wGJ,CkC3wGE,gBAIE,wCAAA,CAHA,aAAA,CACA,wBAAA,CACA,wBlC8wGJ,CkCzwGE,yBAOE,wCAAA,CACA,+DAAA,CACA,4BAAA,CACA,6BAAA,CARA,iBAAA,CAIA,eAAA,CADA,eAAA,CAFA,cAAA,CACA,oCAAA,CAHA,iBlCoxGJ,CkCxwGI,6BACE,YlC0wGN,CkCvwGM,kCACE,wBAAA,CACA,yBlCywGR,CkCnwGE,iCAWE,wCAAA,CACA,+DAAA,CAFA,uCAAA,CAGA,0BAAA,CAPA,UAAA,CAJA,oBAAA,CAMA,2BAAA,CADA,2BAAA,CAEA,2BAAA,CARA,uBAAA,CAAA,eAAA,CAaA,wBAAA,CAAA,qBAAA,CAAA,gBAAA,CATA,SlC4wGJ,CkC1vGE,sBACE,iBAAA,CACA,iBlC4vGJ,CkCpvGI,sCACE,gBlCsvGN,CkClvGI,gDACE,YlCovGN,CkC1uGA,gBACE,iBlC6uGF,CkCzuGE,uCACE,aAAA,CACA,SlC2uGJ,CkC7uGE,oCACE,aAAA,CACA,SlC2uGJ,CkC7uGE,8BACE,aAAA,CACA,SlC2uGJ,CkCtuGE,mBACE,YlCwuGJ,CkCnuGE,oBACE,QlCquGJ,CkCjuGE,4BACE,WAAA,CACA,SAAA,CACA,elCmuGJ,CkChuGI,0CACE,YlCkuGN,CkC5tGE,yBAIE,wCAAA,CAEA,+BAAA,CADA,4BAAA,CAFA,eAAA,CADA,oDAAA,CAKA,wBAAA,CAAA,qBAAA,CAAA,gBlC8tGJ,CkC1tGE,2BAEE,+DAAA,CADA,2BlC6tGJ,CkCztGI,+BACE,uCAAA,CACA,gBlC2tGN,CkCttGE,sBACE,MAAA,CACA,WlCwtGJ,CkCntGA,aACE,alCstGF,CkC5sGE,4BAEE,aAAA,CADA,YlCgtGJ,CkC5sGI,wDAEE,2BAAA,CADA,wBlC+sGN,CkCzsGE,+BAKE,2CAAA,CAEA,+BAAA,CADA,gCAAA,CADA,sBAAA,CAJA,mBAAA,CAEA,gBAAA,CADA,alCgtGJ,CkCxsGI,qCAEE,UAAA,CACA,UAAA,CAFA,alC4sGN,CK70GI,wC6BgJF,8BACE,iBlCisGF,CkCvrGE,wSAGE,elC6rGJ,CkCzrGE,sCAEE,mBAAA,CACA,eAAA,CADA,oBAAA,CADA,kBAAA,CAAA,mBlC6rGJ,CACF,CDphHI,kDAIE,+BAAA,CACA,8BAAA,CAFA,aAAA,CADA,QAAA,CADA,iBC0hHN,CD3hHI,+CAIE,+BAAA,CACA,8BAAA,CAFA,aAAA,CADA,QAAA,CADA,iBC0hHN,CD3hHI,yCAIE,+BAAA,CACA,8BAAA,CAFA,aAAA,CADA,QAAA,CADA,iBC0hHN,CDlhHI,uBAEE,uCAAA,CADA,cCqhHN,CDh+GM,iHAEE,WAlDkB,CAiDlB,kBC2+GR,CD5+GM,6HAEE,WAlDkB,CAiDlB,kBCu/GR,CDx/GM,6HAEE,WAlDkB,CAiDlB,kBCmgHR,CDpgHM,oHAEE,WAlDkB,CAiDlB,kBC+gHR,CDhhHM,0HAEE,WAlDkB,CAiDlB,kBC2hHR,CD5hHM,uHAEE,WAlDkB,CAiDlB,kBCuiHR,CDxiHM,uHAEE,WAlDkB,CAiDlB,kBCmjHR,CDpjHM,6HAEE,WAlDkB,CAiDlB,kBC+jHR,CDhkHM,yCAEE,WAlDkB,CAiDlB,kBCmkHR,CDpkHM,yCAEE,WAlDkB,CAiDlB,kBCukHR,CDxkHM,0CAEE,WAlDkB,CAiDlB,kBC2kHR,CD5kHM,uCAEE,WAlDkB,CAiDlB,kBC+kHR,CDhlHM,wCAEE,WAlDkB,CAiDlB,kBCmlHR,CDplHM,sCAEE,WAlDkB,CAiDlB,kBCulHR,CDxlHM,wCAEE,WAlDkB,CAiDlB,kBC2lHR,CD5lHM,oCAEE,WAlDkB,CAiDlB,kBC+lHR,CDhmHM,2CAEE,WAlDkB,CAiDlB,kBCmmHR,CDpmHM,qCAEE,WAlDkB,CAiDlB,kBCumHR,CDxmHM,oCAEE,WAlDkB,CAiDlB,kBC2mHR,CD5mHM,kCAEE,WAlDkB,CAiDlB,kBC+mHR,CDhnHM,qCAEE,WAlDkB,CAiDlB,kBCmnHR,CDpnHM,mCAEE,WAlDkB,CAiDlB,kBCunHR,CDxnHM,qCAEE,WAlDkB,CAiDlB,kBC2nHR,CD5nHM,wCAEE,WAlDkB,CAiDlB,kBC+nHR,CDhoHM,sCAEE,WAlDkB,CAiDlB,kBCmoHR,CDpoHM,2CAEE,WAlDkB,CAiDlB,kBCuoHR,CD5nHM,iCAEE,WAPkB,CAMlB,iBC+nHR,CDhoHM,uCAEE,WAPkB,CAMlB,iBCmoHR,CDpoHM,mCAEE,WAPkB,CAMlB,iBCuoHR,CmCztHA,MACE,qMAAA,CACA,mMnC4tHF,CmCntHE,wBAKE,mBAAA,CAHA,YAAA,CACA,qBAAA,CACA,YAAA,CAHA,iBnC0tHJ,CmChtHI,8BAGE,QAAA,CACA,SAAA,CAHA,iBAAA,CACA,OnCotHN,CmC/sHM,qCACE,0BnCitHR,CmClrHE,2BAKE,uBAAA,CADA,+DAAA,CAHA,YAAA,CACA,cAAA,CACA,aAAA,CAGA,oBnCorHJ,CmCjrHI,aATF,2BAUI,gBnCorHJ,CACF,CmCjrHI,cAGE,+BACE,iBnCirHN,CmC9qHM,sCAOE,oCAAA,CALA,QAAA,CAWA,UAAA,CATA,aAAA,CAEA,UAAA,CAHA,MAAA,CAFA,iBAAA,CAOA,2CAAA,CACA,qCACE,CAEF,kDAAA,CAPA,+BnCsrHR,CACF,CmCzqHI,8CACE,YnC2qHN,CmCvqHI,iCAQE,+BAAA,CACA,6BAAA,CALA,uCAAA,CAMA,cAAA,CATA,aAAA,CAKA,gBAAA,CADA,eAAA,CAFA,8BAAA,CAWA,+BAAA,CAHA,2CACE,CALF,kBAAA,CALA,UnCmrHN,CmCpqHM,aAII,6CACE,OnCmqHV,CmCpqHQ,8CACE,OnCsqHV,CmCvqHQ,8CACE,OnCyqHV,CmC1qHQ,8CACE,OnC4qHV,CmC7qHQ,8CACE,OnC+qHV,CmChrHQ,8CACE,OnCkrHV,CmCnrHQ,8CACE,OnCqrHV,CmCtrHQ,8CACE,OnCwrHV,CmCzrHQ,8CACE,OnC2rHV,CmC5rHQ,+CACE,QnC8rHV,CmC/rHQ,+CACE,QnCisHV,CmClsHQ,+CACE,QnCosHV,CmCrsHQ,+CACE,QnCusHV,CmCxsHQ,+CACE,QnC0sHV,CmC3sHQ,+CACE,QnC6sHV,CmC9sHQ,+CACE,QnCgtHV,CmCjtHQ,+CACE,QnCmtHV,CmCptHQ,+CACE,QnCstHV,CmCvtHQ,+CACE,QnCytHV,CmC1tHQ,+CACE,QnC4tHV,CACF,CmCvtHM,uCACE,+BnCytHR,CmCntHE,4BACE,UnCqtHJ,CmCltHI,aAJF,4BAKI,gBnCqtHJ,CACF,CmCjtHE,0BACE,YnCmtHJ,CmChtHI,aAJF,0BAKI,anCmtHJ,CmC/sHM,sCACE,OnCitHR,CmCltHM,uCACE,OnCotHR,CmCrtHM,uCACE,OnCutHR,CmCxtHM,uCACE,OnC0tHR,CmC3tHM,uCACE,OnC6tHR,CmC9tHM,uCACE,OnCguHR,CmCjuHM,uCACE,OnCmuHR,CmCpuHM,uCACE,OnCsuHR,CmCvuHM,uCACE,OnCyuHR,CmC1uHM,wCACE,QnC4uHR,CmC7uHM,wCACE,QnC+uHR,CmChvHM,wCACE,QnCkvHR,CmCnvHM,wCACE,QnCqvHR,CmCtvHM,wCACE,QnCwvHR,CmCzvHM,wCACE,QnC2vHR,CmC5vHM,wCACE,QnC8vHR,CmC/vHM,wCACE,QnCiwHR,CmClwHM,wCACE,QnCowHR,CmCrwHM,wCACE,QnCuwHR,CmCxwHM,wCACE,QnC0wHR,CACF,CmCpwHI,+FAEE,QnCswHN,CmCnwHM,yGACE,wBAAA,CACA,yBnCswHR,CmC7vHM,2DAEE,wBAAA,CACA,yBAAA,CAFA,QnCiwHR,CmC1vHM,iEACE,QnC4vHR,CmCzvHQ,qLAGE,wBAAA,CACA,yBAAA,CAFA,QnC6vHV,CmCvvHQ,6FACE,wBAAA,CACA,yBnCyvHV,CmCpvHM,yDACE,kBnCsvHR,CmCjvHI,sCACE,QnCmvHN,CmC9uHE,2BAEE,iBAAA,CAKA,kBAAA,CADA,uCAAA,CAEA,cAAA,CAPA,aAAA,CAGA,YAAA,CACA,gBAAA,CAKA,mBAAA,CADA,gCAAA,CANA,WnCuvHJ,CmC7uHI,iCAEE,uDAAA,CADA,+BnCgvHN,CmC3uHI,iCAIE,6BAAA,CAQA,UAAA,CAXA,aAAA,CAEA,WAAA,CAKA,8CAAA,CAAA,sCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CANA,+CACE,CAJF,UnCqvHN,CmCtuHE,4BAME,yEACE,CALF,YAAA,CAGA,aAAA,CAFA,qBAAA,CAUA,mBAAA,CAZA,iBAAA,CAWA,wBAAA,CARA,YnC4uHJ,CmChuHI,sCACE,wBnCkuHN,CmC9tHI,oCACE,SnCguHN,CmC5tHI,kCAGE,wEACE,CAFF,mBAAA,CADA,OnCguHN,CmCttHM,uDACE,8CAAA,CAAA,sCnCwtHR,CKx0HI,wC8B8HF,wDAGE,kBnC+sHF,CmCltHA,wDAGE,mBnC+sHF,CmCltHA,8CAEE,eAAA,CADA,eAAA,CAGA,iCnC8sHF,CmC1sHE,8DACE,mBnC6sHJ,CmC9sHE,8DACE,kBnC6sHJ,CmC9sHE,oDAEE,UnC4sHJ,CmCxsHE,8EAEE,kBnC2sHJ,CmC7sHE,8EAEE,mBnC2sHJ,CmC7sHE,8EAGE,kBnC0sHJ,CmC7sHE,8EAGE,mBnC0sHJ,CmC7sHE,oEACE,UnC4sHJ,CmCtsHE,8EAEE,mBnCysHJ,CmC3sHE,8EAEE,kBnCysHJ,CmC3sHE,8EAGE,mBnCwsHJ,CmC3sHE,8EAGE,kBnCwsHJ,CmC3sHE,oEACE,UnC0sHJ,CACF,CmC5rHE,cAHF,olDAII,+BnC+rHF,CmC5rHE,g8GACE,sCnC8rHJ,CACF,CmCzrHA,4sDACE,uDnC4rHF,CmCxrHA,wmDACE,anC2rHF,CoCxiIA,MACE,mVAAA,CAEA,4VpC4iIF,CoCliIE,4BAEE,oBAAA,CADA,iBpCsiIJ,CoCjiII,sDAGE,SpCmiIN,CoCtiII,sDAGE,UpCmiIN,CoCtiII,4CACE,iBAAA,CACA,SpCoiIN,CoC9hIE,+CAEE,SAAA,CADA,UpCiiIJ,CoC5hIE,kDAGE,WpCsiIJ,CoCziIE,kDAGE,YpCsiIJ,CoCziIE,wCAME,qDAAA,CAKA,UAAA,CANA,aAAA,CAEA,0CAAA,CAAA,kCAAA,CACA,4BAAA,CAAA,oBAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CATA,iBAAA,CACA,SAAA,CAEA,YpCqiIJ,CoC1hIE,gEACE,wBTyWa,CSxWb,mDAAA,CAAA,2CpC4hIJ,CqC9kIA,QACE,8DAAA,CAGA,+CAAA,CACA,iEAAA,CACA,oDAAA,CACA,sDAAA,CACA,mDrC+kIF,CqC3kIA,SAEE,kBAAA,CADA,YrC+kIF,CKt7HI,mCiChKA,8BACE,UtC8lIJ,CsC/lIE,8BACE,WtC8lIJ,CsC/lIE,8BAIE,kBtC2lIJ,CsC/lIE,8BAIE,iBtC2lIJ,CsC/lIE,oBAKE,mBAAA,CAFA,YAAA,CADA,atC6lIJ,CsCvlII,kCACE,WtC0lIN,CsC3lII,kCACE,UtC0lIN,CsC3lII,kCAEE,iBAAA,CAAA,ctCylIN,CsC3lII,kCAEE,aAAA,CAAA,kBtCylIN,CACF","file":"main.css"}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/main.c382b1dc.min.css b/7.3/assets/stylesheets/main.c382b1dc.min.css
deleted file mode 100755
index 0e566cd89e..0000000000
--- a/7.3/assets/stylesheets/main.c382b1dc.min.css
+++ /dev/null
@@ -1 +0,0 @@
-@charset "UTF-8";html{-webkit-text-size-adjust:none;-moz-text-size-adjust:none;-ms-text-size-adjust:none;text-size-adjust:none;box-sizing:border-box}*,:after,:before{box-sizing:inherit}@media (prefers-reduced-motion){*,:after,:before{transition:none!important}}body{margin:0}a,button,input,label{-webkit-tap-highlight-color:transparent}a{color:inherit;text-decoration:none}hr{border:0;box-sizing:initial;display:block;height:.05rem;overflow:visible;padding:0}small{font-size:80%}sub,sup{line-height:1em}img{border-style:none}table{border-collapse:initial;border-spacing:0}td,th{font-weight:400;vertical-align:top}button{background:transparent;border:0;font-family:inherit;font-size:inherit;margin:0;padding:0}input{border:0;outline:none}:root{--md-default-fg-color:rgba(0,0,0,.87);--md-default-fg-color--light:rgba(0,0,0,.54);--md-default-fg-color--lighter:rgba(0,0,0,.32);--md-default-fg-color--lightest:rgba(0,0,0,.07);--md-default-bg-color:#fff;--md-default-bg-color--light:hsla(0,0%,100%,.7);--md-default-bg-color--lighter:hsla(0,0%,100%,.3);--md-default-bg-color--lightest:hsla(0,0%,100%,.12);--md-primary-fg-color:#4051b5;--md-primary-fg-color--light:#5d6cc0;--md-primary-fg-color--dark:#303fa1;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7);--md-accent-fg-color:#526cfe;--md-accent-fg-color--transparent:rgba(82,108,254,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7);--md-shadow-z1:0 0.2rem 0.5rem rgba(0,0,0,.05),0 0 0.05rem rgba(0,0,0,.1);--md-shadow-z2:0 0.2rem 0.5rem rgba(0,0,0,.1),0 0 0.05rem rgba(0,0,0,.25);--md-shadow-z3:0 0.2rem 0.5rem rgba(0,0,0,.2),0 0 0.05rem rgba(0,0,0,.35)}:root>*{--md-code-fg-color:#36464e;--md-code-bg-color:#f5f5f5;--md-code-hl-color:rgba(255,255,0,.5);--md-code-hl-number-color:#d52a2a;--md-code-hl-special-color:#db1457;--md-code-hl-function-color:#a846b9;--md-code-hl-constant-color:#6e59d9;--md-code-hl-keyword-color:#3f6ec6;--md-code-hl-string-color:#1c7d4d;--md-code-hl-name-color:var(--md-code-fg-color);--md-code-hl-operator-color:var(--md-default-fg-color--light);--md-code-hl-punctuation-color:var(--md-default-fg-color--light);--md-code-hl-comment-color:var(--md-default-fg-color--light);--md-code-hl-generic-color:var(--md-default-fg-color--light);--md-code-hl-variable-color:var(--md-default-fg-color--light);--md-typeset-color:var(--md-default-fg-color);--md-typeset-a-color:var(--md-primary-fg-color);--md-typeset-mark-color:rgba(255,255,0,.5);--md-typeset-del-color:rgba(245,80,61,.15);--md-typeset-ins-color:rgba(11,213,112,.15);--md-typeset-kbd-color:#fafafa;--md-typeset-kbd-accent-color:#fff;--md-typeset-kbd-border-color:#b8b8b8;--md-typeset-table-color:rgba(0,0,0,.12);--md-admonition-fg-color:var(--md-default-fg-color);--md-admonition-bg-color:var(--md-default-bg-color);--md-footer-fg-color:#fff;--md-footer-fg-color--light:hsla(0,0%,100%,.7);--md-footer-fg-color--lighter:hsla(0,0%,100%,.3);--md-footer-bg-color:rgba(0,0,0,.87);--md-footer-bg-color--dark:rgba(0,0,0,.32)}.md-icon svg{fill:currentcolor;display:block;height:1.2rem;width:1.2rem}body{-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale;--md-text-font-family:var(--md-text-font,_),-apple-system,BlinkMacSystemFont,Helvetica,Arial,sans-serif;--md-code-font-family:var(--md-code-font,_),SFMono-Regular,Consolas,Menlo,monospace}body,input{font-feature-settings:"kern","liga";font-family:var(--md-text-font-family)}body,code,input,kbd,pre{color:var(--md-typeset-color)}code,kbd,pre{font-feature-settings:"kern";font-family:var(--md-code-font-family)}:root{--md-typeset-table-sort-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m18 21-4-4h3V7h-3l4-4 4 4h-3v10h3M2 19v-2h10v2M2 13v-2h7v2M2 7V5h4v2H2Z"/></svg>');--md-typeset-table-sort-icon--asc:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 17h3l-4 4-4-4h3V3h2M2 17h10v2H2M6 5v2H2V5m0 6h7v2H2v-2Z"/></svg>');--md-typeset-table-sort-icon--desc:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 7h3l-4-4-4 4h3v14h2M2 17h10v2H2M6 5v2H2V5m0 6h7v2H2v-2Z"/></svg>')}.md-typeset{-webkit-print-color-adjust:exact;color-adjust:exact;font-size:.8rem;line-height:1.6}@media print{.md-typeset{font-size:.68rem}}.md-typeset blockquote,.md-typeset dl,.md-typeset figure,.md-typeset ol,.md-typeset pre,.md-typeset ul{margin-bottom:1em;margin-top:1em}.md-typeset h1{color:var(--md-default-fg-color--light);font-size:2em;line-height:1.3;margin:0 0 1.25em}.md-typeset h1,.md-typeset h2{font-weight:300;letter-spacing:-.01em}.md-typeset h2{font-size:1.5625em;line-height:1.4;margin:1.6em 0 .64em}.md-typeset h3{font-size:1.25em;font-weight:400;letter-spacing:-.01em;line-height:1.5;margin:1.6em 0 .8em}.md-typeset h2+h3{margin-top:.8em}.md-typeset h4{font-weight:700;letter-spacing:-.01em;margin:1em 0}.md-typeset h5,.md-typeset h6{color:var(--md-default-fg-color--light);font-size:.8em;font-weight:700;letter-spacing:-.01em;margin:1.25em 0}.md-typeset h5{text-transform:uppercase}.md-typeset hr{border-bottom:.05rem solid var(--md-default-fg-color--lightest);display:flow-root;margin:1.5em 0}.md-typeset a{color:var(--md-typeset-a-color);word-break:break-word}.md-typeset a,.md-typeset a:before{transition:color 125ms}.md-typeset a:focus,.md-typeset a:hover{color:var(--md-accent-fg-color)}.md-typeset a:focus code,.md-typeset a:hover code{background-color:var(--md-accent-fg-color--transparent)}.md-typeset a code{color:currentcolor;transition:background-color 125ms}.md-typeset a.focus-visible{outline-color:var(--md-accent-fg-color);outline-offset:.2rem}.md-typeset code,.md-typeset kbd,.md-typeset pre{color:var(--md-code-fg-color);direction:ltr}@media print{.md-typeset code,.md-typeset kbd,.md-typeset pre{white-space:pre-wrap}}.md-typeset code{background-color:var(--md-code-bg-color);border-radius:.1rem;-webkit-box-decoration-break:clone;box-decoration-break:clone;font-size:.85em;padding:0 .2941176471em;word-break:break-word}.md-typeset code:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}.md-typeset pre{display:flow-root;line-height:1.4;position:relative}.md-typeset pre>code{-webkit-box-decoration-break:slice;box-decoration-break:slice;box-shadow:none;display:block;margin:0;outline-color:var(--md-accent-fg-color);overflow:auto;padding:.7720588235em 1.1764705882em;scrollbar-color:var(--md-default-fg-color--lighter) transparent;scrollbar-width:thin;touch-action:auto;word-break:normal}.md-typeset pre>code:hover{scrollbar-color:var(--md-accent-fg-color) transparent}.md-typeset pre>code::-webkit-scrollbar{height:.2rem;width:.2rem}.md-typeset pre>code::-webkit-scrollbar-thumb{background-color:var(--md-default-fg-color--lighter)}.md-typeset pre>code::-webkit-scrollbar-thumb:hover{background-color:var(--md-accent-fg-color)}.md-typeset kbd{background-color:var(--md-typeset-kbd-color);border-radius:.1rem;box-shadow:0 .1rem 0 .05rem var(--md-typeset-kbd-border-color),0 .1rem 0 var(--md-typeset-kbd-border-color),0 -.1rem .2rem var(--md-typeset-kbd-accent-color) inset;color:var(--md-default-fg-color);display:inline-block;font-size:.75em;padding:0 .6666666667em;vertical-align:text-top;word-break:break-word}.md-typeset mark{background-color:var(--md-typeset-mark-color);-webkit-box-decoration-break:clone;box-decoration-break:clone;color:inherit;word-break:break-word}.md-typeset abbr{border-bottom:.05rem dotted var(--md-default-fg-color--light);cursor:help;text-decoration:none}@media (hover:none){.md-typeset abbr{position:relative}.md-typeset abbr[title]:-webkit-any(:focus,:hover):after{background-color:var(--md-default-fg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z3);color:var(--md-default-bg-color);content:attr(title);display:inline-block;font-size:.7rem;margin-top:2em;max-width:80%;min-width:-webkit-max-content;min-width:max-content;padding:.2rem .3rem;position:absolute;width:auto}.md-typeset abbr[title]:-moz-any(:focus,:hover):after{background-color:var(--md-default-fg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z3);color:var(--md-default-bg-color);content:attr(title);display:inline-block;font-size:.7rem;margin-top:2em;max-width:80%;min-width:-moz-max-content;min-width:max-content;padding:.2rem .3rem;position:absolute;width:auto}[dir=ltr] .md-typeset abbr[title]:-webkit-any(:focus,:hover):after{left:0}[dir=ltr] .md-typeset abbr[title]:-moz-any(:focus,:hover):after{left:0}[dir=ltr] .md-typeset abbr[title]:is(:focus,:hover):after{left:0}[dir=rtl] .md-typeset abbr[title]:-webkit-any(:focus,:hover):after{right:0}[dir=rtl] .md-typeset abbr[title]:-moz-any(:focus,:hover):after{right:0}[dir=rtl] .md-typeset abbr[title]:is(:focus,:hover):after{right:0}.md-typeset abbr[title]:is(:focus,:hover):after{background-color:var(--md-default-fg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z3);color:var(--md-default-bg-color);content:attr(title);display:inline-block;font-size:.7rem;margin-top:2em;max-width:80%;min-width:-webkit-max-content;min-width:-moz-max-content;min-width:max-content;padding:.2rem .3rem;position:absolute;width:auto}}.md-typeset small{opacity:.75}[dir=ltr] .md-typeset sub,[dir=ltr] .md-typeset sup{margin-left:.078125em}[dir=rtl] .md-typeset sub,[dir=rtl] .md-typeset sup{margin-right:.078125em}[dir=ltr] .md-typeset blockquote{padding-left:.6rem}[dir=rtl] .md-typeset blockquote{padding-right:.6rem}[dir=ltr] .md-typeset blockquote{border-left:.2rem solid var(--md-default-fg-color--lighter)}[dir=rtl] .md-typeset blockquote{border-right:.2rem solid var(--md-default-fg-color--lighter)}.md-typeset blockquote{color:var(--md-default-fg-color--light);margin-left:0;margin-right:0}.md-typeset ul{list-style-type:disc}[dir=ltr] .md-typeset ol,[dir=ltr] .md-typeset ul{margin-left:.625em}[dir=rtl] .md-typeset ol,[dir=rtl] .md-typeset ul{margin-right:.625em}.md-typeset ol,.md-typeset ul{padding:0}.md-typeset ol:not([hidden]),.md-typeset ul:not([hidden]){display:flow-root}.md-typeset ol ol,.md-typeset ul ol{list-style-type:lower-alpha}.md-typeset ol ol ol,.md-typeset ul ol ol{list-style-type:lower-roman}[dir=ltr] .md-typeset ol li,[dir=ltr] .md-typeset ul li{margin-left:1.25em}[dir=rtl] .md-typeset ol li,[dir=rtl] .md-typeset ul li{margin-right:1.25em}.md-typeset ol li,.md-typeset ul li{margin-bottom:.5em}.md-typeset ol li blockquote,.md-typeset ol li p,.md-typeset ul li blockquote,.md-typeset ul li p{margin:.5em 0}.md-typeset ol li:last-child,.md-typeset ul li:last-child{margin-bottom:0}.md-typeset ol li :-webkit-any(ul,ol),.md-typeset ul li :-webkit-any(ul,ol){margin-bottom:.5em;margin-top:.5em}.md-typeset ol li :-moz-any(ul,ol),.md-typeset ul li :-moz-any(ul,ol){margin-bottom:.5em;margin-top:.5em}[dir=ltr] .md-typeset ol li :-webkit-any(ul,ol),[dir=ltr] .md-typeset ul li :-webkit-any(ul,ol){margin-left:.625em}[dir=ltr] .md-typeset ol li :-moz-any(ul,ol),[dir=ltr] .md-typeset ul li :-moz-any(ul,ol){margin-left:.625em}[dir=ltr] .md-typeset ol li :is(ul,ol),[dir=ltr] .md-typeset ul li :is(ul,ol){margin-left:.625em}[dir=rtl] .md-typeset ol li :-webkit-any(ul,ol),[dir=rtl] .md-typeset ul li :-webkit-any(ul,ol){margin-right:.625em}[dir=rtl] .md-typeset ol li :-moz-any(ul,ol),[dir=rtl] .md-typeset ul li :-moz-any(ul,ol){margin-right:.625em}[dir=rtl] .md-typeset ol li :is(ul,ol),[dir=rtl] .md-typeset ul li :is(ul,ol){margin-right:.625em}.md-typeset ol li :is(ul,ol),.md-typeset ul li :is(ul,ol){margin-bottom:.5em;margin-top:.5em}[dir=ltr] .md-typeset dd{margin-left:1.875em}[dir=rtl] .md-typeset dd{margin-right:1.875em}.md-typeset dd{margin-bottom:1.5em;margin-top:1em}.md-typeset img,.md-typeset svg{height:auto;max-width:100%}.md-typeset img[align=left],.md-typeset svg[align=left]{margin:1em 1em 1em 0}.md-typeset img[align=right],.md-typeset svg[align=right]{margin:1em 0 1em 1em}.md-typeset img[align]:only-child,.md-typeset svg[align]:only-child{margin-top:0}.md-typeset img[src$="#gh-dark-mode-only"],.md-typeset img[src$="#only-dark"]{display:none}.md-typeset figure{display:flow-root;margin:1em auto;max-width:100%;text-align:center;width:-webkit-fit-content;width:-moz-fit-content;width:fit-content}.md-typeset figure img{display:block}.md-typeset figcaption{font-style:italic;margin:1em auto;max-width:24rem}.md-typeset iframe{max-width:100%}.md-typeset table:not([class]){background-color:var(--md-default-bg-color);border:.05rem solid var(--md-typeset-table-color);border-radius:.1rem;display:inline-block;font-size:.64rem;max-width:100%;overflow:auto;touch-action:auto}@media print{.md-typeset table:not([class]){display:table}}.md-typeset table:not([class])+*{margin-top:1.5em}.md-typeset table:not([class]) :-webkit-any(th,td)>:first-child{margin-top:0}.md-typeset table:not([class]) :-moz-any(th,td)>:first-child{margin-top:0}.md-typeset table:not([class]) :is(th,td)>:first-child{margin-top:0}.md-typeset table:not([class]) :-webkit-any(th,td)>:last-child{margin-bottom:0}.md-typeset table:not([class]) :-moz-any(th,td)>:last-child{margin-bottom:0}.md-typeset table:not([class]) :is(th,td)>:last-child{margin-bottom:0}.md-typeset table:not([class]) :-webkit-any(th,td):not([align]){text-align:left}.md-typeset table:not([class]) :-moz-any(th,td):not([align]){text-align:left}.md-typeset table:not([class]) :is(th,td):not([align]){text-align:left}[dir=rtl] .md-typeset table:not([class]) :-webkit-any(th,td):not([align]){text-align:right}[dir=rtl] .md-typeset table:not([class]) :-moz-any(th,td):not([align]){text-align:right}[dir=rtl] .md-typeset table:not([class]) :is(th,td):not([align]){text-align:right}.md-typeset table:not([class]) th{font-weight:700;min-width:5rem;padding:.9375em 1.25em;vertical-align:top}.md-typeset table:not([class]) th a{color:inherit}.md-typeset table:not([class]) td{border-top:.05rem solid var(--md-typeset-table-color);padding:.9375em 1.25em;vertical-align:top}.md-typeset table:not([class]) tbody tr{transition:background-color 125ms}.md-typeset table:not([class]) tbody tr:hover{background-color:rgba(0,0,0,.035);box-shadow:0 .05rem 0 var(--md-default-bg-color) inset}.md-typeset table:not([class]) a{word-break:normal}.md-typeset table th[role=columnheader]{cursor:pointer}[dir=ltr] .md-typeset table th[role=columnheader]:after{margin-left:.5em}[dir=rtl] .md-typeset table th[role=columnheader]:after{margin-right:.5em}.md-typeset table th[role=columnheader]:after{content:"";display:inline-block;height:1.2em;-webkit-mask-image:var(--md-typeset-table-sort-icon);mask-image:var(--md-typeset-table-sort-icon);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;transition:background-color 125ms;vertical-align:text-bottom;width:1.2em}.md-typeset table th[role=columnheader]:hover:after{background-color:var(--md-default-fg-color--lighter)}.md-typeset table th[role=columnheader][aria-sort=ascending]:after{background-color:var(--md-default-fg-color--light);-webkit-mask-image:var(--md-typeset-table-sort-icon--asc);mask-image:var(--md-typeset-table-sort-icon--asc)}.md-typeset table th[role=columnheader][aria-sort=descending]:after{background-color:var(--md-default-fg-color--light);-webkit-mask-image:var(--md-typeset-table-sort-icon--desc);mask-image:var(--md-typeset-table-sort-icon--desc)}.md-typeset__scrollwrap{margin:1em -.8rem;overflow-x:auto;touch-action:auto}.md-typeset__table{display:inline-block;margin-bottom:.5em;padding:0 .8rem}@media print{.md-typeset__table{display:block}}html .md-typeset__table table{display:table;margin:0;overflow:hidden;width:100%}@media screen and (max-width:44.9375em){.md-content__inner>pre{margin:1em -.8rem}.md-content__inner>pre code{border-radius:0}}.md-banner{background-color:var(--md-footer-bg-color);color:var(--md-footer-fg-color);overflow:auto}@media print{.md-banner{display:none}}.md-banner--warning{background:var(--md-typeset-mark-color);color:var(--md-default-fg-color)}.md-banner__inner{font-size:.7rem;margin:.6rem auto;padding:0 .8rem}html{font-size:125%;height:100%;overflow-x:hidden}@media screen and (min-width:100em){html{font-size:137.5%}}@media screen and (min-width:125em){html{font-size:150%}}body{background-color:var(--md-default-bg-color);display:flex;flex-direction:column;font-size:.5rem;min-height:100%;position:relative;width:100%}@media print{body{display:block}}@media screen and (max-width:59.9375em){body[data-md-state=lock]{position:fixed}}.md-grid{margin-left:auto;margin-right:auto;max-width:61rem}.md-container{display:flex;flex-direction:column;flex-grow:1}@media print{.md-container{display:block}}.md-main{flex-grow:1}.md-main__inner{display:flex;height:100%;margin-top:1.5rem}.md-ellipsis{overflow:hidden;text-overflow:ellipsis;white-space:nowrap}.md-toggle{display:none}.md-option{height:0;opacity:0;position:absolute;width:0}.md-option:checked+label:not([hidden]){display:block}.md-option.focus-visible+label{outline-color:var(--md-accent-fg-color);outline-style:auto}.md-skip{background-color:var(--md-default-fg-color);border-radius:.1rem;color:var(--md-default-bg-color);font-size:.64rem;margin:.5rem;opacity:0;outline-color:var(--md-accent-fg-color);padding:.3rem .5rem;position:fixed;transform:translateY(.4rem);z-index:-1}.md-skip:focus{opacity:1;transform:translateY(0);transition:transform .25s cubic-bezier(.4,0,.2,1),opacity 175ms 75ms;z-index:10}@page{margin:25mm}:root{--md-clipboard-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 21H8V7h11m0-2H8a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h11a2 2 0 0 0 2-2V7a2 2 0 0 0-2-2m-3-4H4a2 2 0 0 0-2 2v14h2V3h12V1Z"/></svg>')}.md-clipboard{border-radius:.1rem;color:var(--md-default-fg-color--lightest);cursor:pointer;height:1.5em;outline-color:var(--md-accent-fg-color);outline-offset:.1rem;position:absolute;right:.5em;top:.5em;transition:color .25s;width:1.5em;z-index:1}@media print{.md-clipboard{display:none}}.md-clipboard:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}:hover>.md-clipboard{color:var(--md-default-fg-color--light)}.md-clipboard:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-clipboard:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-clipboard:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-clipboard:after{background-color:currentcolor;content:"";display:block;height:1.125em;margin:0 auto;-webkit-mask-image:var(--md-clipboard-icon);mask-image:var(--md-clipboard-icon);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:1.125em}.md-clipboard--inline{cursor:pointer}.md-clipboard--inline code{transition:color .25s,background-color .25s}.md-clipboard--inline:-webkit-any(:focus,:hover) code{background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-clipboard--inline:-moz-any(:focus,:hover) code{background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-clipboard--inline:is(:focus,:hover) code{background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-content{flex-grow:1;min-width:0}.md-content__inner{margin:0 .8rem 1.2rem;padding-top:.6rem}@media screen and (min-width:76.25em){[dir=ltr] .md-sidebar--primary:not([hidden])~.md-content>.md-content__inner{margin-left:1.2rem}[dir=ltr] .md-sidebar--secondary:not([hidden])~.md-content>.md-content__inner,[dir=rtl] .md-sidebar--primary:not([hidden])~.md-content>.md-content__inner{margin-right:1.2rem}[dir=rtl] .md-sidebar--secondary:not([hidden])~.md-content>.md-content__inner{margin-left:1.2rem}}.md-content__inner:before{content:"";display:block;height:.4rem}.md-content__inner>:last-child{margin-bottom:0}[dir=ltr] .md-content__button{margin-left:.4rem}[dir=rtl] .md-content__button{margin-right:.4rem}.md-content__button{float:right;margin:.4rem 0;padding:0}@media print{.md-content__button{display:none}}[dir=rtl] .md-content__button{float:left}.md-typeset .md-content__button{color:var(--md-default-fg-color--lighter)}.md-content__button svg{display:inline;vertical-align:top}[dir=rtl] .md-content__button svg{transform:scaleX(-1)}[dir=ltr] .md-dialog{right:.8rem}[dir=rtl] .md-dialog{left:.8rem}.md-dialog{background-color:var(--md-default-fg-color);border-radius:.1rem;bottom:.8rem;box-shadow:var(--md-shadow-z3);min-width:11.1rem;opacity:0;padding:.4rem .6rem;pointer-events:none;position:fixed;transform:translateY(100%);transition:transform 0ms .4s,opacity .4s;z-index:4}@media print{.md-dialog{display:none}}.md-dialog[data-md-state=open]{opacity:1;pointer-events:auto;transform:translateY(0);transition:transform .4s cubic-bezier(.075,.85,.175,1),opacity .4s}.md-dialog__inner{color:var(--md-default-bg-color);font-size:.7rem}.md-footer{background-color:var(--md-footer-bg-color);color:var(--md-footer-fg-color)}@media print{.md-footer{display:none}}.md-footer__inner{display:flex;justify-content:space-between;overflow:auto;padding:.2rem}.md-footer__link{display:flex;flex-grow:0.01;outline-color:var(--md-accent-fg-color);overflow:hidden;padding-bottom:.4rem;padding-top:1.4rem;transition:opacity .25s}.md-footer__link:-webkit-any(:focus,:hover){opacity:.7}.md-footer__link:-moz-any(:focus,:hover){opacity:.7}.md-footer__link:is(:focus,:hover){opacity:.7}[dir=rtl] .md-footer__link svg{transform:scaleX(-1)}@media screen and (max-width:44.9375em){.md-footer__link--prev .md-footer__title{display:none}}[dir=ltr] .md-footer__link--next{margin-left:auto}[dir=rtl] .md-footer__link--next{margin-right:auto}.md-footer__link--next{text-align:right}[dir=rtl] .md-footer__link--next{text-align:left}.md-footer__title{flex-grow:1;font-size:.9rem;line-height:2.4rem;max-width:calc(100% - 2.4rem);padding:0 1rem;position:relative}.md-footer__button{margin:.2rem;padding:.4rem}.md-footer__direction{font-size:.64rem;left:0;margin-top:-1rem;opacity:.7;padding:0 1rem;position:absolute;right:0}.md-footer-meta{background-color:var(--md-footer-bg-color--dark)}.md-footer-meta__inner{display:flex;flex-wrap:wrap;justify-content:space-between;padding:.2rem}html .md-footer-meta.md-typeset a{color:var(--md-footer-fg-color--light)}html .md-footer-meta.md-typeset a:-webkit-any(:focus,:hover){color:var(--md-footer-fg-color)}html .md-footer-meta.md-typeset a:-moz-any(:focus,:hover){color:var(--md-footer-fg-color)}html .md-footer-meta.md-typeset a:is(:focus,:hover){color:var(--md-footer-fg-color)}.md-copyright{color:var(--md-footer-fg-color--lighter);font-size:.64rem;margin:auto .6rem;padding:.4rem 0;width:100%}@media screen and (min-width:45em){.md-copyright{width:auto}}.md-copyright__highlight{color:var(--md-footer-fg-color--light)}.md-social{margin:0 .4rem;padding:.2rem 0 .6rem}@media screen and (min-width:45em){.md-social{padding:.6rem 0}}.md-social__link{display:inline-block;height:1.6rem;text-align:center;width:1.6rem}.md-social__link:before{line-height:1.9}.md-social__link svg{fill:currentcolor;max-height:.8rem;vertical-align:-25%}.md-typeset .md-button{border:.1rem solid;border-radius:.1rem;color:var(--md-primary-fg-color);cursor:pointer;display:inline-block;font-weight:700;padding:.625em 2em;transition:color 125ms,background-color 125ms,border-color 125ms}.md-typeset .md-button--primary{background-color:var(--md-primary-fg-color);border-color:var(--md-primary-fg-color);color:var(--md-primary-bg-color)}.md-typeset .md-button:-webkit-any(:focus,:hover){background-color:var(--md-accent-fg-color);border-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-typeset .md-button:-moz-any(:focus,:hover){background-color:var(--md-accent-fg-color);border-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-typeset .md-button:is(:focus,:hover){background-color:var(--md-accent-fg-color);border-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}[dir=ltr] .md-typeset .md-input{border-top-left-radius:.1rem}[dir=ltr] .md-typeset .md-input,[dir=rtl] .md-typeset .md-input{border-top-right-radius:.1rem}[dir=rtl] .md-typeset .md-input{border-top-left-radius:.1rem}.md-typeset .md-input{border-bottom:.1rem solid var(--md-default-fg-color--lighter);box-shadow:var(--md-shadow-z1);font-size:.8rem;height:1.8rem;padding:0 .6rem;transition:border .25s,box-shadow .25s}.md-typeset .md-input:-webkit-any(:focus,:hover){border-bottom-color:var(--md-accent-fg-color);box-shadow:var(--md-shadow-z2)}.md-typeset .md-input:-moz-any(:focus,:hover){border-bottom-color:var(--md-accent-fg-color);box-shadow:var(--md-shadow-z2)}.md-typeset .md-input:is(:focus,:hover){border-bottom-color:var(--md-accent-fg-color);box-shadow:var(--md-shadow-z2)}.md-typeset .md-input--stretch{width:100%}.md-header{background-color:var(--md-primary-fg-color);box-shadow:0 0 .2rem transparent,0 .2rem .4rem transparent;color:var(--md-primary-bg-color);left:0;position:-webkit-sticky;position:sticky;right:0;top:0;z-index:4}@media print{.md-header{display:none}}.md-header[data-md-state=shadow]{box-shadow:0 0 .2rem rgba(0,0,0,.1),0 .2rem .4rem rgba(0,0,0,.2);transition:transform .25s cubic-bezier(.1,.7,.1,1),box-shadow .25s}.md-header[data-md-state=hidden]{transform:translateY(-100%);transition:transform .25s cubic-bezier(.8,0,.6,1),box-shadow .25s}.md-header__inner{align-items:center;display:flex;padding:0 .2rem}.md-header__button{color:currentcolor;cursor:pointer;margin:.2rem;outline-color:var(--md-accent-fg-color);padding:.4rem;position:relative;transition:opacity .25s;vertical-align:middle;z-index:1}.md-header__button:hover{opacity:.7}.md-header__button:not([hidden]){display:inline-block}.md-header__button:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}.md-header__button.md-logo{margin:.2rem;padding:.4rem}@media screen and (max-width:76.1875em){.md-header__button.md-logo{display:none}}.md-header__button.md-logo :-webkit-any(img,svg){fill:currentcolor;display:block;height:1.2rem;width:auto}.md-header__button.md-logo :-moz-any(img,svg){fill:currentcolor;display:block;height:1.2rem;width:auto}.md-header__button.md-logo :is(img,svg){fill:currentcolor;display:block;height:1.2rem;width:auto}@media screen and (min-width:60em){.md-header__button[for=__search]{display:none}}.no-js .md-header__button[for=__search]{display:none}[dir=rtl] .md-header__button[for=__search] svg{transform:scaleX(-1)}@media screen and (min-width:76.25em){.md-header__button[for=__drawer]{display:none}}.md-header__topic{display:flex;max-width:100%;position:absolute;transition:transform .4s cubic-bezier(.1,.7,.1,1),opacity .15s}.md-header__topic+.md-header__topic{opacity:0;pointer-events:none;transform:translateX(1.25rem);transition:transform .4s cubic-bezier(1,.7,.1,.1),opacity .15s;z-index:-1}[dir=rtl] .md-header__topic+.md-header__topic{transform:translateX(-1.25rem)}.md-header__topic:first-child{font-weight:700}[dir=ltr] .md-header__title{margin-right:.4rem}[dir=rtl] .md-header__title{margin-left:.4rem}[dir=ltr] .md-header__title{margin-left:1rem}[dir=rtl] .md-header__title{margin-right:1rem}.md-header__title{flex-grow:1;font-size:.9rem;height:2.4rem;line-height:2.4rem}.md-header__title[data-md-state=active] .md-header__topic{opacity:0;pointer-events:none;transform:translateX(-1.25rem);transition:transform .4s cubic-bezier(1,.7,.1,.1),opacity .15s;z-index:-1}[dir=rtl] .md-header__title[data-md-state=active] .md-header__topic{transform:translateX(1.25rem)}.md-header__title[data-md-state=active] .md-header__topic+.md-header__topic{opacity:1;pointer-events:auto;transform:translateX(0);transition:transform .4s cubic-bezier(.1,.7,.1,1),opacity .15s;z-index:0}.md-header__title>.md-header__ellipsis{height:100%;position:relative;width:100%}.md-header__option{display:flex;flex-shrink:0;max-width:100%;transition:max-width 0ms .25s,opacity .25s .25s;white-space:nowrap}[data-md-toggle=search]:checked~.md-header .md-header__option{max-width:0;opacity:0;transition:max-width 0ms,opacity 0ms}.md-header__source{display:none}@media screen and (min-width:60em){[dir=ltr] .md-header__source{margin-left:1rem}[dir=rtl] .md-header__source{margin-right:1rem}.md-header__source{display:block;max-width:11.7rem;width:11.7rem}}@media screen and (min-width:76.25em){[dir=ltr] .md-header__source{margin-left:1.4rem}[dir=rtl] .md-header__source{margin-right:1.4rem}}:root{--md-nav-icon--prev:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11h12Z"/></svg>');--md-nav-icon--next:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M8.59 16.58 13.17 12 8.59 7.41 10 6l6 6-6 6-1.41-1.42Z"/></svg>');--md-toc-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M3 9h14V7H3v2m0 4h14v-2H3v2m0 4h14v-2H3v2m16 0h2v-2h-2v2m0-10v2h2V7h-2m0 6h2v-2h-2v2Z"/></svg>')}.md-nav{font-size:.7rem;line-height:1.3}.md-nav__title{display:block;font-weight:700;overflow:hidden;padding:0 .6rem;text-overflow:ellipsis}.md-nav__title .md-nav__button{display:none}.md-nav__title .md-nav__button img{height:100%;width:auto}.md-nav__title .md-nav__button.md-logo :-webkit-any(img,svg){fill:currentcolor;display:block;height:2.4rem;max-width:100%;object-fit:contain;width:auto}.md-nav__title .md-nav__button.md-logo :-moz-any(img,svg){fill:currentcolor;display:block;height:2.4rem;max-width:100%;object-fit:contain;width:auto}.md-nav__title .md-nav__button.md-logo :is(img,svg){fill:currentcolor;display:block;height:2.4rem;max-width:100%;object-fit:contain;width:auto}.md-nav__list{list-style:none;margin:0;padding:0}.md-nav__item{padding:0 .6rem}[dir=ltr] .md-nav__item .md-nav__item{padding-right:0}[dir=rtl] .md-nav__item .md-nav__item{padding-left:0}.md-nav__link{align-items:center;cursor:pointer;display:flex;justify-content:space-between;margin-top:.625em;overflow:hidden;scroll-snap-align:start;text-overflow:ellipsis;transition:color 125ms}.md-nav__link[data-md-state=blur]{color:var(--md-default-fg-color--light)}.md-nav__item .md-nav__link--active{color:var(--md-typeset-a-color)}.md-nav__item .md-nav__link--index [href]{width:100%}.md-nav__link:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav__link:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav__link:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav__link.focus-visible{outline-color:var(--md-accent-fg-color);outline-offset:.2rem}.md-nav--primary .md-nav__link[for=__toc]{display:none}.md-nav--primary .md-nav__link[for=__toc] .md-icon:after{background-color:currentcolor;display:block;height:100%;-webkit-mask-image:var(--md-toc-icon);mask-image:var(--md-toc-icon);width:100%}.md-nav--primary .md-nav__link[for=__toc]~.md-nav{display:none}.md-nav__link>*{cursor:pointer;display:flex}.md-nav__icon{flex-shrink:0}.md-nav__source{display:none}@media screen and (max-width:76.1875em){.md-nav--primary,.md-nav--primary .md-nav{background-color:var(--md-default-bg-color);display:flex;flex-direction:column;height:100%;left:0;position:absolute;right:0;top:0;z-index:1}.md-nav--primary :-webkit-any(.md-nav__title,.md-nav__item){font-size:.8rem;line-height:1.5}.md-nav--primary :-moz-any(.md-nav__title,.md-nav__item){font-size:.8rem;line-height:1.5}.md-nav--primary :is(.md-nav__title,.md-nav__item){font-size:.8rem;line-height:1.5}.md-nav--primary .md-nav__title{background-color:var(--md-default-fg-color--lightest);color:var(--md-default-fg-color--light);cursor:pointer;height:5.6rem;line-height:2.4rem;padding:3rem .8rem .2rem;position:relative;white-space:nowrap}[dir=ltr] .md-nav--primary .md-nav__title .md-nav__icon{left:.4rem}[dir=rtl] .md-nav--primary .md-nav__title .md-nav__icon{right:.4rem}.md-nav--primary .md-nav__title .md-nav__icon{display:block;height:1.2rem;margin:.2rem;position:absolute;top:.4rem;width:1.2rem}.md-nav--primary .md-nav__title .md-nav__icon:after{background-color:currentcolor;content:"";display:block;height:100%;-webkit-mask-image:var(--md-nav-icon--prev);mask-image:var(--md-nav-icon--prev);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:100%}.md-nav--primary .md-nav__title~.md-nav__list{background-color:var(--md-default-bg-color);box-shadow:0 .05rem 0 var(--md-default-fg-color--lightest) inset;overflow-y:auto;-ms-scroll-snap-type:y mandatory;scroll-snap-type:y mandatory;touch-action:pan-y}.md-nav--primary .md-nav__title~.md-nav__list>:first-child{border-top:0}.md-nav--primary .md-nav__title[for=__drawer]{background-color:var(--md-primary-fg-color);color:var(--md-primary-bg-color);font-weight:700}.md-nav--primary .md-nav__title .md-logo{display:block;left:.2rem;margin:.2rem;padding:.4rem;position:absolute;right:.2rem;top:.2rem}.md-nav--primary .md-nav__list{flex:1}.md-nav--primary .md-nav__item{border-top:.05rem solid var(--md-default-fg-color--lightest);padding:0}.md-nav--primary .md-nav__item--active>.md-nav__link{color:var(--md-typeset-a-color)}.md-nav--primary .md-nav__item--active>.md-nav__link:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav--primary .md-nav__item--active>.md-nav__link:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav--primary .md-nav__item--active>.md-nav__link:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-nav--primary .md-nav__link{margin-top:0;padding:.6rem .8rem}[dir=ltr] .md-nav--primary .md-nav__link .md-nav__icon{margin-right:-.2rem}[dir=rtl] .md-nav--primary .md-nav__link .md-nav__icon{margin-left:-.2rem}.md-nav--primary .md-nav__link .md-nav__icon{font-size:1.2rem;height:1.2rem;width:1.2rem}.md-nav--primary .md-nav__link .md-nav__icon:after{background-color:currentcolor;content:"";display:block;height:100%;-webkit-mask-image:var(--md-nav-icon--next);mask-image:var(--md-nav-icon--next);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:100%}[dir=rtl] .md-nav--primary .md-nav__icon:after{transform:scale(-1)}.md-nav--primary .md-nav--secondary .md-nav{background-color:initial;position:static}[dir=ltr] .md-nav--primary .md-nav--secondary .md-nav .md-nav__link{padding-left:1.4rem}[dir=rtl] .md-nav--primary .md-nav--secondary .md-nav .md-nav__link{padding-right:1.4rem}[dir=ltr] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav__link{padding-left:2rem}[dir=rtl] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav__link{padding-right:2rem}[dir=ltr] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav .md-nav__link{padding-left:2.6rem}[dir=rtl] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav .md-nav__link{padding-right:2.6rem}[dir=ltr] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav .md-nav .md-nav__link{padding-left:3.2rem}[dir=rtl] .md-nav--primary .md-nav--secondary .md-nav .md-nav .md-nav .md-nav .md-nav__link{padding-right:3.2rem}.md-nav--secondary{background-color:initial}.md-nav__toggle~.md-nav{display:flex;opacity:0;transform:translateX(100%);transition:transform .25s cubic-bezier(.8,0,.6,1),opacity 125ms 50ms}[dir=rtl] .md-nav__toggle~.md-nav{transform:translateX(-100%)}.md-nav__toggle:checked~.md-nav{opacity:1;transform:translateX(0);transition:transform .25s cubic-bezier(.4,0,.2,1),opacity 125ms 125ms}.md-nav__toggle:checked~.md-nav>.md-nav__list{-webkit-backface-visibility:hidden;backface-visibility:hidden}}@media screen and (max-width:59.9375em){.md-nav--primary .md-nav__link[for=__toc]{display:flex}.md-nav--primary .md-nav__link[for=__toc] .md-icon:after{content:""}.md-nav--primary .md-nav__link[for=__toc]+.md-nav__link{display:none}.md-nav--primary .md-nav__link[for=__toc]~.md-nav{display:flex}.md-nav__source{background-color:var(--md-primary-fg-color--dark);color:var(--md-primary-bg-color);display:block;padding:0 .2rem}}@media screen and (min-width:60em) and (max-width:76.1875em){.md-nav--integrated .md-nav__link[for=__toc]{display:flex}.md-nav--integrated .md-nav__link[for=__toc] .md-icon:after{content:""}.md-nav--integrated .md-nav__link[for=__toc]+.md-nav__link{display:none}.md-nav--integrated .md-nav__link[for=__toc]~.md-nav{display:flex}}@media screen and (min-width:60em){.md-nav--secondary .md-nav__title[for=__toc]{scroll-snap-align:start}.md-nav--secondary .md-nav__title .md-nav__icon{display:none}}@media screen and (min-width:76.25em){.md-nav{transition:max-height .25s cubic-bezier(.86,0,.07,1)}.md-nav--primary .md-nav__title[for=__drawer]{scroll-snap-align:start}.md-nav--primary .md-nav__title .md-nav__icon,.md-nav__toggle~.md-nav{display:none}.md-nav__toggle:-webkit-any(:checked,:indeterminate)~.md-nav{display:block}.md-nav__toggle:-moz-any(:checked,:indeterminate)~.md-nav{display:block}.md-nav__toggle:is(:checked,:indeterminate)~.md-nav{display:block}.md-nav__item--nested>.md-nav>.md-nav__title{display:none}.md-nav__item--section{display:block;margin:1.25em 0}.md-nav__item--section:last-child{margin-bottom:0}.md-nav__item--section>.md-nav__link{font-weight:700;pointer-events:none}.md-nav__item--section>.md-nav__link--index [href]{pointer-events:auto}.md-nav__item--section>.md-nav__link .md-nav__icon{display:none}.md-nav__item--section>.md-nav{display:block}.md-nav__item--section>.md-nav>.md-nav__list>.md-nav__item{padding:0}.md-nav__icon{border-radius:100%;float:right;height:.9rem;transition:background-color .25s,transform .25s;width:.9rem}[dir=rtl] .md-nav__icon{float:left;transform:rotate(180deg)}.md-nav__icon:hover{background-color:var(--md-accent-fg-color--transparent)}.md-nav__icon:after{background-color:currentcolor;content:"";display:inline-block;height:100%;-webkit-mask-image:var(--md-nav-icon--next);mask-image:var(--md-nav-icon--next);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;vertical-align:-.1rem;width:100%}.md-nav__item--nested .md-nav__toggle:checked~.md-nav__link .md-nav__icon,.md-nav__item--nested .md-nav__toggle:indeterminate~.md-nav__link .md-nav__icon{transform:rotate(90deg)}.md-nav--lifted>.md-nav__list>.md-nav__item,.md-nav--lifted>.md-nav__list>.md-nav__item--nested,.md-nav--lifted>.md-nav__title{display:none}.md-nav--lifted>.md-nav__list>.md-nav__item--active{display:block;padding:0}.md-nav--lifted>.md-nav__list>.md-nav__item--active>.md-nav__link{font-weight:700;margin-top:0;padding:0 .6rem;pointer-events:none}.md-nav--lifted>.md-nav__list>.md-nav__item--active>.md-nav__link--index [href]{pointer-events:auto}.md-nav--lifted>.md-nav__list>.md-nav__item--active>.md-nav__link .md-nav__icon{display:none}.md-nav--lifted .md-nav[data-md-level="1"]{display:block}[dir=ltr] .md-nav--lifted .md-nav[data-md-level="1"]>.md-nav__list>.md-nav__item{padding-right:.6rem}[dir=rtl] .md-nav--lifted .md-nav[data-md-level="1"]>.md-nav__list>.md-nav__item{padding-left:.6rem}.md-nav--integrated>.md-nav__list>.md-nav__item--active:not(.md-nav__item--nested){padding:0 .6rem}.md-nav--integrated>.md-nav__list>.md-nav__item--active:not(.md-nav__item--nested)>.md-nav__link{padding:0}[dir=ltr] .md-nav--integrated>.md-nav__list>.md-nav__item--active .md-nav--secondary{border-left:.05rem solid var(--md-primary-fg-color)}[dir=rtl] .md-nav--integrated>.md-nav__list>.md-nav__item--active .md-nav--secondary{border-right:.05rem solid var(--md-primary-fg-color)}.md-nav--integrated>.md-nav__list>.md-nav__item--active .md-nav--secondary{display:block;margin-bottom:1.25em}.md-nav--integrated>.md-nav__list>.md-nav__item--active .md-nav--secondary>.md-nav__title{display:none}}:root{--md-search-result-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h7c-.41-.25-.8-.56-1.14-.9-.33-.33-.61-.7-.86-1.1H6V4h7v5h5v1.18c.71.16 1.39.43 2 .82V8l-6-6m6.31 16.9c1.33-2.11.69-4.9-1.4-6.22-2.11-1.33-4.91-.68-6.22 1.4-1.34 2.11-.69 4.89 1.4 6.22 1.46.93 3.32.93 4.79.02L22 23.39 23.39 22l-3.08-3.1m-3.81.1a2.5 2.5 0 0 1-2.5-2.5 2.5 2.5 0 0 1 2.5-2.5 2.5 2.5 0 0 1 2.5 2.5 2.5 2.5 0 0 1-2.5 2.5Z"/></svg>')}.md-search{position:relative}@media screen and (min-width:60em){.md-search{padding:.2rem 0}}.no-js .md-search{display:none}.md-search__overlay{opacity:0;z-index:1}@media screen and (max-width:59.9375em){[dir=ltr] .md-search__overlay{left:-2.2rem}[dir=rtl] .md-search__overlay{right:-2.2rem}.md-search__overlay{background-color:var(--md-default-bg-color);border-radius:1rem;height:2rem;overflow:hidden;pointer-events:none;position:absolute;top:-1rem;transform-origin:center;transition:transform .3s .1s,opacity .2s .2s;width:2rem}[data-md-toggle=search]:checked~.md-header .md-search__overlay{opacity:1;transition:transform .4s,opacity .1s}}@media screen and (min-width:60em){[dir=ltr] .md-search__overlay{left:0}[dir=rtl] .md-search__overlay{right:0}.md-search__overlay{background-color:rgba(0,0,0,.54);cursor:pointer;height:0;position:fixed;top:0;transition:width 0ms .25s,height 0ms .25s,opacity .25s;width:0}[data-md-toggle=search]:checked~.md-header .md-search__overlay{height:200vh;opacity:1;transition:width 0ms,height 0ms,opacity .25s;width:100%}}@media screen and (max-width:29.9375em){[data-md-toggle=search]:checked~.md-header .md-search__overlay{transform:scale(45)}}@media screen and (min-width:30em) and (max-width:44.9375em){[data-md-toggle=search]:checked~.md-header .md-search__overlay{transform:scale(60)}}@media screen and (min-width:45em) and (max-width:59.9375em){[data-md-toggle=search]:checked~.md-header .md-search__overlay{transform:scale(75)}}.md-search__inner{-webkit-backface-visibility:hidden;backface-visibility:hidden}@media screen and (max-width:59.9375em){[dir=ltr] .md-search__inner{left:0}[dir=rtl] .md-search__inner{right:0}.md-search__inner{height:0;opacity:0;overflow:hidden;position:fixed;top:0;transform:translateX(5%);transition:width 0ms .3s,height 0ms .3s,transform .15s cubic-bezier(.4,0,.2,1) .15s,opacity .15s .15s;width:0;z-index:2}[dir=rtl] .md-search__inner{transform:translateX(-5%)}[data-md-toggle=search]:checked~.md-header .md-search__inner{height:100%;opacity:1;transform:translateX(0);transition:width 0ms 0ms,height 0ms 0ms,transform .15s cubic-bezier(.1,.7,.1,1) .15s,opacity .15s .15s;width:100%}}@media screen and (min-width:60em){.md-search__inner{float:right;padding:.1rem 0;position:relative;transition:width .25s cubic-bezier(.1,.7,.1,1);width:11.7rem}[dir=rtl] .md-search__inner{float:left}}@media screen and (min-width:60em) and (max-width:76.1875em){[data-md-toggle=search]:checked~.md-header .md-search__inner{width:23.4rem}}@media screen and (min-width:76.25em){[data-md-toggle=search]:checked~.md-header .md-search__inner{width:34.4rem}}.md-search__form{background-color:var(--md-default-bg-color);box-shadow:0 0 .6rem transparent;height:2.4rem;position:relative;transition:color .25s,background-color .25s;z-index:2}@media screen and (min-width:60em){.md-search__form{background-color:rgba(0,0,0,.26);border-radius:.1rem;height:1.8rem}.md-search__form:hover{background-color:hsla(0,0%,100%,.12)}}[data-md-toggle=search]:checked~.md-header .md-search__form{background-color:var(--md-default-bg-color);border-radius:.1rem .1rem 0 0;box-shadow:0 0 .6rem rgba(0,0,0,.07);color:var(--md-default-fg-color)}[dir=ltr] .md-search__input{padding-left:3.6rem;padding-right:2.2rem}[dir=rtl] .md-search__input{padding-left:2.2rem;padding-right:3.6rem}.md-search__input{background:transparent;font-size:.9rem;height:100%;position:relative;text-overflow:ellipsis;width:100%;z-index:2}.md-search__input::-moz-placeholder{-moz-transition:color .25s;transition:color .25s}.md-search__input::-ms-input-placeholder{-ms-transition:color .25s;transition:color .25s}.md-search__input::placeholder{transition:color .25s}.md-search__input::-moz-placeholder{color:var(--md-default-fg-color--light)}.md-search__input::-ms-input-placeholder{color:var(--md-default-fg-color--light)}.md-search__input::placeholder,.md-search__input~.md-search__icon{color:var(--md-default-fg-color--light)}.md-search__input::-ms-clear{display:none}@media screen and (max-width:59.9375em){.md-search__input{font-size:.9rem;height:2.4rem;width:100%}}@media screen and (min-width:60em){[dir=ltr] .md-search__input{padding-left:2.2rem}[dir=rtl] .md-search__input{padding-right:2.2rem}.md-search__input{color:inherit;font-size:.8rem}.md-search__input::-moz-placeholder{color:var(--md-primary-bg-color--light)}.md-search__input::-ms-input-placeholder{color:var(--md-primary-bg-color--light)}.md-search__input::placeholder{color:var(--md-primary-bg-color--light)}.md-search__input+.md-search__icon{color:var(--md-primary-bg-color)}[data-md-toggle=search]:checked~.md-header .md-search__input{text-overflow:clip}[data-md-toggle=search]:checked~.md-header .md-search__input::-moz-placeholder{color:var(--md-default-fg-color--light)}[data-md-toggle=search]:checked~.md-header .md-search__input::-ms-input-placeholder{color:var(--md-default-fg-color--light)}[data-md-toggle=search]:checked~.md-header .md-search__input+.md-search__icon,[data-md-toggle=search]:checked~.md-header .md-search__input::placeholder{color:var(--md-default-fg-color--light)}}.md-search__icon{cursor:pointer;display:inline-block;height:1.2rem;transition:color .25s,opacity .25s;width:1.2rem}.md-search__icon:hover{opacity:.7}[dir=ltr] .md-search__icon[for=__search]{left:.5rem}[dir=rtl] .md-search__icon[for=__search]{right:.5rem}.md-search__icon[for=__search]{position:absolute;top:.3rem;z-index:2}[dir=rtl] .md-search__icon[for=__search] svg{transform:scaleX(-1)}@media screen and (max-width:59.9375em){[dir=ltr] .md-search__icon[for=__search]{left:.8rem}[dir=rtl] .md-search__icon[for=__search]{right:.8rem}.md-search__icon[for=__search]{top:.6rem}.md-search__icon[for=__search] svg:first-child{display:none}}@media screen and (min-width:60em){.md-search__icon[for=__search]{pointer-events:none}.md-search__icon[for=__search] svg:last-child{display:none}}[dir=ltr] .md-search__options{right:.5rem}[dir=rtl] .md-search__options{left:.5rem}.md-search__options{pointer-events:none;position:absolute;top:.3rem;z-index:2}@media screen and (max-width:59.9375em){[dir=ltr] .md-search__options{right:.8rem}[dir=rtl] .md-search__options{left:.8rem}.md-search__options{top:.6rem}}[dir=ltr] .md-search__options>*{margin-left:.2rem}[dir=rtl] .md-search__options>*{margin-right:.2rem}.md-search__options>*{color:var(--md-default-fg-color--light);opacity:0;transform:scale(.75);transition:transform .15s cubic-bezier(.1,.7,.1,1),opacity .15s}.md-search__options>:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}[data-md-toggle=search]:checked~.md-header .md-search__input:valid~.md-search__options>*{opacity:1;pointer-events:auto;transform:scale(1)}[data-md-toggle=search]:checked~.md-header .md-search__input:valid~.md-search__options>:hover{opacity:.7}[dir=ltr] .md-search__suggest{padding-left:3.6rem;padding-right:2.2rem}[dir=rtl] .md-search__suggest{padding-left:2.2rem;padding-right:3.6rem}.md-search__suggest{align-items:center;color:var(--md-default-fg-color--lighter);display:flex;font-size:.9rem;height:100%;opacity:0;position:absolute;top:0;transition:opacity 50ms;white-space:nowrap;width:100%}@media screen and (min-width:60em){[dir=ltr] .md-search__suggest{padding-left:2.2rem}[dir=rtl] .md-search__suggest{padding-right:2.2rem}.md-search__suggest{font-size:.8rem}}[data-md-toggle=search]:checked~.md-header .md-search__suggest{opacity:1;transition:opacity .3s .1s}[dir=ltr] .md-search__output{border-bottom-left-radius:.1rem}[dir=ltr] .md-search__output,[dir=rtl] .md-search__output{border-bottom-right-radius:.1rem}[dir=rtl] .md-search__output{border-bottom-left-radius:.1rem}.md-search__output{overflow:hidden;position:absolute;width:100%;z-index:1}@media screen and (max-width:59.9375em){.md-search__output{bottom:0;top:2.4rem}}@media screen and (min-width:60em){.md-search__output{opacity:0;top:1.9rem;transition:opacity .4s}[data-md-toggle=search]:checked~.md-header .md-search__output{box-shadow:var(--md-shadow-z3);opacity:1}}.md-search__scrollwrap{-webkit-backface-visibility:hidden;backface-visibility:hidden;background-color:var(--md-default-bg-color);height:100%;overflow-y:auto;touch-action:pan-y}@media (-webkit-max-device-pixel-ratio:1),(max-resolution:1dppx){.md-search__scrollwrap{transform:translateZ(0)}}@media screen and (min-width:60em) and (max-width:76.1875em){.md-search__scrollwrap{width:23.4rem}}@media screen and (min-width:76.25em){.md-search__scrollwrap{width:34.4rem}}@media screen and (min-width:60em){.md-search__scrollwrap{max-height:0;scrollbar-color:var(--md-default-fg-color--lighter) transparent;scrollbar-width:thin}[data-md-toggle=search]:checked~.md-header .md-search__scrollwrap{max-height:75vh}.md-search__scrollwrap:hover{scrollbar-color:var(--md-accent-fg-color) transparent}.md-search__scrollwrap::-webkit-scrollbar{height:.2rem;width:.2rem}.md-search__scrollwrap::-webkit-scrollbar-thumb{background-color:var(--md-default-fg-color--lighter)}.md-search__scrollwrap::-webkit-scrollbar-thumb:hover{background-color:var(--md-accent-fg-color)}}.md-search-result{color:var(--md-default-fg-color);word-break:break-word}.md-search-result__meta{background-color:var(--md-default-fg-color--lightest);color:var(--md-default-fg-color--light);font-size:.64rem;line-height:1.8rem;padding:0 .8rem;scroll-snap-align:start}@media screen and (min-width:60em){[dir=ltr] .md-search-result__meta{padding-left:2.2rem}[dir=rtl] .md-search-result__meta{padding-right:2.2rem}}.md-search-result__list{list-style:none;margin:0;padding:0}.md-search-result__item{box-shadow:0 -.05rem var(--md-default-fg-color--lightest)}.md-search-result__item:first-child{box-shadow:none}.md-search-result__link{display:block;outline:none;scroll-snap-align:start;transition:background-color .25s}.md-search-result__link:-webkit-any(:focus,:hover){background-color:var(--md-accent-fg-color--transparent)}.md-search-result__link:-moz-any(:focus,:hover){background-color:var(--md-accent-fg-color--transparent)}.md-search-result__link:is(:focus,:hover){background-color:var(--md-accent-fg-color--transparent)}.md-search-result__link:last-child p:last-child{margin-bottom:.6rem}.md-search-result__more summary{color:var(--md-typeset-a-color);cursor:pointer;display:block;font-size:.64rem;outline:none;padding:.75em .8rem;scroll-snap-align:start;transition:color .25s,background-color .25s}@media screen and (min-width:60em){[dir=ltr] .md-search-result__more summary{padding-left:2.2rem}[dir=rtl] .md-search-result__more summary{padding-right:2.2rem}}.md-search-result__more summary:-webkit-any(:focus,:hover){background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-search-result__more summary:-moz-any(:focus,:hover){background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-search-result__more summary:is(:focus,:hover){background-color:var(--md-accent-fg-color--transparent);color:var(--md-accent-fg-color)}.md-search-result__more summary::marker{display:none}.md-search-result__more summary::-webkit-details-marker{display:none}.md-search-result__more summary~*>*{opacity:.65}.md-search-result__article{overflow:hidden;padding:0 .8rem;position:relative}@media screen and (min-width:60em){[dir=ltr] .md-search-result__article{padding-left:2.2rem}[dir=rtl] .md-search-result__article{padding-right:2.2rem}}.md-search-result__article--document .md-search-result__title{font-size:.8rem;font-weight:400;line-height:1.4;margin:.55rem 0}[dir=ltr] .md-search-result__icon{left:0}[dir=rtl] .md-search-result__icon{right:0}.md-search-result__icon{color:var(--md-default-fg-color--light);height:1.2rem;margin:.5rem;position:absolute;width:1.2rem}@media screen and (max-width:59.9375em){.md-search-result__icon{display:none}}.md-search-result__icon:after{background-color:currentcolor;content:"";display:inline-block;height:100%;-webkit-mask-image:var(--md-search-result-icon);mask-image:var(--md-search-result-icon);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:100%}[dir=rtl] .md-search-result__icon:after{transform:scaleX(-1)}.md-search-result__title{font-size:.64rem;font-weight:700;line-height:1.6;margin:.5em 0}.md-search-result__teaser{-webkit-box-orient:vertical;-webkit-line-clamp:2;color:var(--md-default-fg-color--light);display:-webkit-box;font-size:.64rem;line-height:1.6;margin:.5em 0;max-height:2rem;overflow:hidden;text-overflow:ellipsis}@media screen and (max-width:44.9375em){.md-search-result__teaser{-webkit-line-clamp:3;max-height:3rem}}@media screen and (min-width:60em) and (max-width:76.1875em){.md-search-result__teaser{-webkit-line-clamp:3;max-height:3rem}}.md-search-result__teaser mark{background-color:initial;text-decoration:underline}.md-search-result__terms{font-size:.64rem;font-style:italic;margin:.5em 0}.md-search-result mark{background-color:initial;color:var(--md-accent-fg-color)}.md-select{position:relative;z-index:1}.md-select__inner{background-color:var(--md-default-bg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z2);color:var(--md-default-fg-color);left:50%;margin-top:.2rem;max-height:0;opacity:0;position:absolute;top:calc(100% - .2rem);transform:translate3d(-50%,.3rem,0);transition:transform .25s 375ms,opacity .25s .25s,max-height 0ms .5s}.md-select:-webkit-any(:focus-within,:hover) .md-select__inner{max-height:10rem;opacity:1;transform:translate3d(-50%,0,0);-webkit-transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms;transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms}.md-select:-moz-any(:focus-within,:hover) .md-select__inner{max-height:10rem;opacity:1;transform:translate3d(-50%,0,0);-moz-transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms;transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms}.md-select:is(:focus-within,:hover) .md-select__inner{max-height:10rem;opacity:1;transform:translate3d(-50%,0,0);transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height 0ms}.md-select__inner:after{border-bottom:.2rem solid transparent;border-bottom-color:var(--md-default-bg-color);border-left:.2rem solid transparent;border-right:.2rem solid transparent;border-top:0;content:"";height:0;left:50%;margin-left:-.2rem;margin-top:-.2rem;position:absolute;top:0;width:0}.md-select__list{border-radius:.1rem;font-size:.8rem;list-style-type:none;margin:0;max-height:inherit;overflow:auto;padding:0}.md-select__item{line-height:1.8rem}[dir=ltr] .md-select__link{padding-left:.6rem;padding-right:1.2rem}[dir=rtl] .md-select__link{padding-left:1.2rem;padding-right:.6rem}.md-select__link{cursor:pointer;display:block;outline:none;scroll-snap-align:start;transition:background-color .25s,color .25s;width:100%}.md-select__link:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-select__link:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-select__link:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-select__link:focus{background-color:var(--md-default-fg-color--lightest)}.md-sidebar{align-self:flex-start;flex-shrink:0;padding:1.2rem 0;position:-webkit-sticky;position:sticky;top:2.4rem;width:12.1rem}@media print{.md-sidebar{display:none}}@media screen and (max-width:76.1875em){[dir=ltr] .md-sidebar--primary{left:-12.1rem}[dir=rtl] .md-sidebar--primary{right:-12.1rem}.md-sidebar--primary{background-color:var(--md-default-bg-color);display:block;height:100%;position:fixed;top:0;transform:translateX(0);transition:transform .25s cubic-bezier(.4,0,.2,1),box-shadow .25s;width:12.1rem;z-index:5}[data-md-toggle=drawer]:checked~.md-container .md-sidebar--primary{box-shadow:var(--md-shadow-z3);transform:translateX(12.1rem)}[dir=rtl] [data-md-toggle=drawer]:checked~.md-container .md-sidebar--primary{transform:translateX(-12.1rem)}.md-sidebar--primary .md-sidebar__scrollwrap{bottom:0;left:0;margin:0;overflow:hidden;position:absolute;right:0;-ms-scroll-snap-type:none;scroll-snap-type:none;top:0}}@media screen and (min-width:76.25em){.md-sidebar{height:0}.no-js .md-sidebar{height:auto}}.md-sidebar--secondary{display:none;order:2}@media screen and (min-width:60em){.md-sidebar--secondary{height:0}.no-js .md-sidebar--secondary{height:auto}.md-sidebar--secondary:not([hidden]){display:block}.md-sidebar--secondary .md-sidebar__scrollwrap{touch-action:pan-y}}.md-sidebar__scrollwrap{-webkit-backface-visibility:hidden;backface-visibility:hidden;margin:0 .2rem;overflow-y:auto;scrollbar-color:var(--md-default-fg-color--lighter) transparent;scrollbar-width:thin}.md-sidebar__scrollwrap:hover{scrollbar-color:var(--md-accent-fg-color) transparent}.md-sidebar__scrollwrap::-webkit-scrollbar{height:.2rem;width:.2rem}.md-sidebar__scrollwrap::-webkit-scrollbar-thumb{background-color:var(--md-default-fg-color--lighter)}.md-sidebar__scrollwrap::-webkit-scrollbar-thumb:hover{background-color:var(--md-accent-fg-color)}@media screen and (max-width:76.1875em){.md-overlay{background-color:rgba(0,0,0,.54);height:0;opacity:0;position:fixed;top:0;transition:width 0ms .25s,height 0ms .25s,opacity .25s;width:0;z-index:5}[data-md-toggle=drawer]:checked~.md-overlay{height:100%;opacity:1;transition:width 0ms,height 0ms,opacity .25s;width:100%}}@-webkit-keyframes facts{0%{height:0}to{height:.65rem}}@keyframes facts{0%{height:0}to{height:.65rem}}@-webkit-keyframes fact{0%{opacity:0;transform:translateY(100%)}50%{opacity:0}to{opacity:1;transform:translateY(0)}}@keyframes fact{0%{opacity:0;transform:translateY(100%)}50%{opacity:0}to{opacity:1;transform:translateY(0)}}:root{--md-source-forks-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M5 3.25a.75.75 0 1 1-1.5 0 .75.75 0 0 1 1.5 0zm0 2.122a2.25 2.25 0 1 0-1.5 0v.878A2.25 2.25 0 0 0 5.75 8.5h1.5v2.128a2.251 2.251 0 1 0 1.5 0V8.5h1.5a2.25 2.25 0 0 0 2.25-2.25v-.878a2.25 2.25 0 1 0-1.5 0v.878a.75.75 0 0 1-.75.75h-4.5A.75.75 0 0 1 5 6.25v-.878zm3.75 7.378a.75.75 0 1 1-1.5 0 .75.75 0 0 1 1.5 0zm3-8.75a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5z"/></svg>');--md-source-repositories-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M2 2.5A2.5 2.5 0 0 1 4.5 0h8.75a.75.75 0 0 1 .75.75v12.5a.75.75 0 0 1-.75.75h-2.5a.75.75 0 1 1 0-1.5h1.75v-2h-8a1 1 0 0 0-.714 1.7.75.75 0 0 1-1.072 1.05A2.495 2.495 0 0 1 2 11.5v-9zm10.5-1V9h-8c-.356 0-.694.074-1 .208V2.5a1 1 0 0 1 1-1h8zM5 12.25v3.25a.25.25 0 0 0 .4.2l1.45-1.087a.25.25 0 0 1 .3 0L8.6 15.7a.25.25 0 0 0 .4-.2v-3.25a.25.25 0 0 0-.25-.25h-3.5a.25.25 0 0 0-.25.25z"/></svg>');--md-source-stars-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8 .25a.75.75 0 0 1 .673.418l1.882 3.815 4.21.612a.75.75 0 0 1 .416 1.279l-3.046 2.97.719 4.192a.75.75 0 0 1-1.088.791L8 12.347l-3.766 1.98a.75.75 0 0 1-1.088-.79l.72-4.194L.818 6.374a.75.75 0 0 1 .416-1.28l4.21-.611L7.327.668A.75.75 0 0 1 8 .25zm0 2.445L6.615 5.5a.75.75 0 0 1-.564.41l-3.097.45 2.24 2.184a.75.75 0 0 1 .216.664l-.528 3.084 2.769-1.456a.75.75 0 0 1 .698 0l2.77 1.456-.53-3.084a.75.75 0 0 1 .216-.664l2.24-2.183-3.096-.45a.75.75 0 0 1-.564-.41L8 2.694v.001z"/></svg>');--md-source-version-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M2.5 7.775V2.75a.25.25 0 0 1 .25-.25h5.025a.25.25 0 0 1 .177.073l6.25 6.25a.25.25 0 0 1 0 .354l-5.025 5.025a.25.25 0 0 1-.354 0l-6.25-6.25a.25.25 0 0 1-.073-.177zm-1.5 0V2.75C1 1.784 1.784 1 2.75 1h5.025c.464 0 .91.184 1.238.513l6.25 6.25a1.75 1.75 0 0 1 0 2.474l-5.026 5.026a1.75 1.75 0 0 1-2.474 0l-6.25-6.25A1.75 1.75 0 0 1 1 7.775zM6 5a1 1 0 1 0 0 2 1 1 0 0 0 0-2z"/></svg>')}.md-source{-webkit-backface-visibility:hidden;backface-visibility:hidden;display:block;font-size:.65rem;line-height:1.2;outline-color:var(--md-accent-fg-color);transition:opacity .25s;white-space:nowrap}.md-source:hover{opacity:.7}.md-source__icon{display:inline-block;height:2.4rem;vertical-align:middle;width:2rem}[dir=ltr] .md-source__icon svg{margin-left:.6rem}[dir=rtl] .md-source__icon svg{margin-right:.6rem}.md-source__icon svg{margin-top:.6rem}[dir=ltr] .md-source__icon+.md-source__repository{margin-left:-2rem}[dir=rtl] .md-source__icon+.md-source__repository{margin-right:-2rem}[dir=ltr] .md-source__icon+.md-source__repository{padding-left:2rem}[dir=rtl] .md-source__icon+.md-source__repository{padding-right:2rem}[dir=ltr] .md-source__repository{margin-left:.6rem}[dir=rtl] .md-source__repository{margin-right:.6rem}.md-source__repository{display:inline-block;max-width:calc(100% - 1.2rem);overflow:hidden;text-overflow:ellipsis;vertical-align:middle}.md-source__facts{font-size:.55rem;list-style-type:none;margin:.1rem 0 0;opacity:.75;overflow:hidden;padding:0}[data-md-state=done] .md-source__facts{-webkit-animation:facts .25s ease-in;animation:facts .25s ease-in}.md-source__fact{display:inline-block}[data-md-state=done] .md-source__fact{-webkit-animation:fact .4s ease-out;animation:fact .4s ease-out}[dir=ltr] .md-source__fact:before{margin-right:.1rem}[dir=rtl] .md-source__fact:before{margin-left:.1rem}.md-source__fact:before{background-color:currentcolor;content:"";display:inline-block;height:.6rem;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;vertical-align:text-top;width:.6rem}[dir=ltr] .md-source__fact:nth-child(1n+2):before{margin-left:.4rem}[dir=rtl] .md-source__fact:nth-child(1n+2):before{margin-right:.4rem}.md-source__fact--version:before{-webkit-mask-image:var(--md-source-version-icon);mask-image:var(--md-source-version-icon)}.md-source__fact--stars:before{-webkit-mask-image:var(--md-source-stars-icon);mask-image:var(--md-source-stars-icon)}.md-source__fact--forks:before{-webkit-mask-image:var(--md-source-forks-icon);mask-image:var(--md-source-forks-icon)}.md-source__fact--repositories:before{-webkit-mask-image:var(--md-source-repositories-icon);mask-image:var(--md-source-repositories-icon)}.md-tabs{background-color:var(--md-primary-fg-color);color:var(--md-primary-bg-color);overflow:auto;width:100%}@media print{.md-tabs{display:none}}@media screen and (max-width:76.1875em){.md-tabs{display:none}}.md-tabs[data-md-state=hidden]{pointer-events:none}[dir=ltr] .md-tabs__list{margin-left:.2rem}[dir=rtl] .md-tabs__list{margin-right:.2rem}.md-tabs__list{contain:content;list-style:none;margin:0;padding:0;white-space:nowrap}.md-tabs__item{display:inline-block;height:2.4rem;padding-left:.6rem;padding-right:.6rem}.md-tabs__link{-webkit-backface-visibility:hidden;backface-visibility:hidden;display:block;font-size:.7rem;margin-top:.8rem;opacity:.7;outline-color:var(--md-accent-fg-color);outline-offset:.2rem;transition:transform .4s cubic-bezier(.1,.7,.1,1),opacity .25s}.md-tabs__link--active,.md-tabs__link:-webkit-any(:focus,:hover){color:inherit;opacity:1}.md-tabs__link--active,.md-tabs__link:-moz-any(:focus,:hover){color:inherit;opacity:1}.md-tabs__link--active,.md-tabs__link:is(:focus,:hover){color:inherit;opacity:1}.md-tabs__item:nth-child(2) .md-tabs__link{transition-delay:20ms}.md-tabs__item:nth-child(3) .md-tabs__link{transition-delay:40ms}.md-tabs__item:nth-child(4) .md-tabs__link{transition-delay:60ms}.md-tabs__item:nth-child(5) .md-tabs__link{transition-delay:80ms}.md-tabs__item:nth-child(6) .md-tabs__link{transition-delay:.1s}.md-tabs__item:nth-child(7) .md-tabs__link{transition-delay:.12s}.md-tabs__item:nth-child(8) .md-tabs__link{transition-delay:.14s}.md-tabs__item:nth-child(9) .md-tabs__link{transition-delay:.16s}.md-tabs__item:nth-child(10) .md-tabs__link{transition-delay:.18s}.md-tabs__item:nth-child(11) .md-tabs__link{transition-delay:.2s}.md-tabs__item:nth-child(12) .md-tabs__link{transition-delay:.22s}.md-tabs__item:nth-child(13) .md-tabs__link{transition-delay:.24s}.md-tabs__item:nth-child(14) .md-tabs__link{transition-delay:.26s}.md-tabs__item:nth-child(15) .md-tabs__link{transition-delay:.28s}.md-tabs__item:nth-child(16) .md-tabs__link{transition-delay:.3s}.md-tabs[data-md-state=hidden] .md-tabs__link{opacity:0;transform:translateY(50%);transition:transform 0ms .1s,opacity .1s}.md-tags{margin-bottom:.75em}[dir=ltr] .md-tag{margin-right:.5em}[dir=rtl] .md-tag{margin-left:.5em}.md-tag{background:var(--md-default-fg-color--lightest);border-radius:.4rem;display:inline-block;font-size:.64rem;font-weight:700;line-height:1.6;margin-bottom:.5em;padding:.3125em .9375em}.md-tag[href]{-webkit-tap-highlight-color:transparent;color:inherit;outline:none;transition:color 125ms,background-color 125ms}.md-tag[href]:focus,.md-tag[href]:hover{background-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}[id]>.md-tag{vertical-align:text-top}@-webkit-keyframes pulse{0%{box-shadow:0 0 0 0 var(--md-default-fg-color--lightest)}75%{box-shadow:0 0 0 .625em transparent}to{box-shadow:0 0 0 0 transparent}}@keyframes pulse{0%{box-shadow:0 0 0 0 var(--md-default-fg-color--lightest)}75%{box-shadow:0 0 0 .625em transparent}to{box-shadow:0 0 0 0 transparent}}:root{--md-tooltip-width:20rem}.md-tooltip{-webkit-backface-visibility:hidden;backface-visibility:hidden;background-color:var(--md-default-bg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z2);color:var(--md-default-fg-color);left:clamp(var(--md-tooltip-0,0rem) + .8rem,var(--md-tooltip-x),(100vw + var(--md-tooltip-0,0rem) + .8rem - var(--md-tooltip-width) - 2 * .8rem));max-height:0;max-width:calc(100vw - 1.6rem);opacity:0;position:absolute;top:var(--md-tooltip-y);transform:translateY(-.4rem);transition:transform 0ms .25s,opacity .25s,max-height 0ms .25s,z-index .25s;width:var(--md-tooltip-width);z-index:0}:focus-within>.md-tooltip{max-height:1000%;opacity:1;transform:translateY(0);transition:transform .25s cubic-bezier(.1,.7,.1,1),opacity .25s,max-height .25s,z-index 0ms}.focus-visible>.md-tooltip{outline:var(--md-accent-fg-color) auto}.md-tooltip__inner{font-size:.64rem;padding:.8rem}.md-tooltip__inner.md-typeset>:first-child{margin-top:0}.md-tooltip__inner.md-typeset>:last-child{margin-bottom:0}.md-annotation{outline:none;white-space:normal}[dir=rtl] .md-annotation{direction:rtl}.md-annotation:not([hidden]){display:inline-block;line-height:1.325}.md-annotation:focus-within>*{z-index:2}.md-annotation__inner{font-family:var(--md-text-font-family);top:calc(var(--md-tooltip-y) + 1.2ch)}:not(:focus-within)>.md-annotation__inner{pointer-events:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.md-annotation__index{color:#fff;cursor:pointer;margin:0 1ch;position:relative;transition:z-index .25s;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;z-index:0}.md-annotation__index:after{-webkit-animation:pulse 2s infinite;animation:pulse 2s infinite;background-color:var(--md-default-fg-color--lighter);border-radius:2ch;content:"";height:2.2ch;left:-.126em;margin:0 -.4ch;padding:0 .4ch;position:absolute;transition:color .25s,background-color .25s;width:calc(100% + 1.2ch);width:max(2.2ch,100% + 1.2ch);z-index:-1}@media (prefers-reduced-motion){.md-annotation__index:after{-webkit-animation:none;animation:none}}:-webkit-any(:focus-within,:hover)>.md-annotation__index:after{background-color:var(--md-accent-fg-color)}:-moz-any(:focus-within,:hover)>.md-annotation__index:after{background-color:var(--md-accent-fg-color)}:is(:focus-within,:hover)>.md-annotation__index:after{background-color:var(--md-accent-fg-color)}:focus-within>.md-annotation__index:after{-webkit-animation:none;animation:none;transition:color .25s,background-color .25s}.md-annotation__index [data-md-annotation-id]{display:inline-block;line-height:90%}.md-annotation__index [data-md-annotation-id]:before{content:attr(data-md-annotation-id);display:inline-block;padding-bottom:.1em;transform:scale(1.15);transition:transform .4s cubic-bezier(.1,.7,.1,1);vertical-align:.065em}@media not print{.md-annotation__index [data-md-annotation-id]:before{content:"+"}:focus-within>.md-annotation__index [data-md-annotation-id]:before{transform:scale(1.25) rotate(45deg)}}:-webkit-any(:focus-within,:hover)>.md-annotation__index{color:var(--md-accent-bg-color)}:-moz-any(:focus-within,:hover)>.md-annotation__index{color:var(--md-accent-bg-color)}:is(:focus-within,:hover)>.md-annotation__index{color:var(--md-accent-bg-color)}:focus-within>.md-annotation__index{-webkit-animation:none;animation:none;transition:none}[dir=ltr] .md-top{margin-left:50%}[dir=rtl] .md-top{margin-right:50%}.md-top{background-color:var(--md-default-bg-color);border-radius:1.6rem;box-shadow:var(--md-shadow-z2);color:var(--md-default-fg-color--light);font-size:.7rem;outline:none;padding:.4rem .8rem;position:fixed;top:3.2rem;transform:translate(-50%);transition:color 125ms,background-color 125ms,transform 125ms cubic-bezier(.4,0,.2,1),opacity 125ms;z-index:2}@media print{.md-top{display:none}}[dir=rtl] .md-top{transform:translate(50%)}.md-top[data-md-state=hidden]{opacity:0;pointer-events:none;transform:translate(-50%,.2rem);transition-duration:0ms}[dir=rtl] .md-top[data-md-state=hidden]{transform:translate(50%,.2rem)}.md-top:-webkit-any(:focus,:hover){background-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-top:-moz-any(:focus,:hover){background-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-top:is(:focus,:hover){background-color:var(--md-accent-fg-color);color:var(--md-accent-bg-color)}.md-top svg{display:inline-block;vertical-align:-.5em}@-webkit-keyframes hoverfix{0%{pointer-events:none}}@keyframes hoverfix{0%{pointer-events:none}}:root{--md-version-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="m310.6 246.6-127.1 128c-7.1 6.3-15.3 9.4-23.5 9.4s-16.38-3.125-22.63-9.375l-127.1-128C.224 237.5-2.516 223.7 2.438 211.8S19.07 192 32 192h255.1c12.94 0 24.62 7.781 29.58 19.75s3.12 25.75-6.08 34.85z"/></svg>')}.md-version{flex-shrink:0;font-size:.8rem;height:2.4rem}[dir=ltr] .md-version__current{margin-left:1.4rem;margin-right:.4rem}[dir=rtl] .md-version__current{margin-left:.4rem;margin-right:1.4rem}.md-version__current{color:inherit;cursor:pointer;outline:none;position:relative;top:.05rem}[dir=ltr] .md-version__current:after{margin-left:.4rem}[dir=rtl] .md-version__current:after{margin-right:.4rem}.md-version__current:after{background-color:currentcolor;content:"";display:inline-block;height:.6rem;-webkit-mask-image:var(--md-version-icon);mask-image:var(--md-version-icon);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;width:.4rem}.md-version__list{background-color:var(--md-default-bg-color);border-radius:.1rem;box-shadow:var(--md-shadow-z2);color:var(--md-default-fg-color);list-style-type:none;margin:.2rem .8rem;max-height:0;opacity:0;overflow:auto;padding:0;position:absolute;-ms-scroll-snap-type:y mandatory;scroll-snap-type:y mandatory;top:.15rem;transition:max-height 0ms .5s,opacity .25s .25s;z-index:3}.md-version:-webkit-any(:focus-within,:hover) .md-version__list{max-height:10rem;opacity:1;-webkit-transition:max-height 0ms,opacity .25s;transition:max-height 0ms,opacity .25s}.md-version:-moz-any(:focus-within,:hover) .md-version__list{max-height:10rem;opacity:1;-moz-transition:max-height 0ms,opacity .25s;transition:max-height 0ms,opacity .25s}.md-version:is(:focus-within,:hover) .md-version__list{max-height:10rem;opacity:1;transition:max-height 0ms,opacity .25s}@media (pointer:coarse){.md-version:hover .md-version__list{-webkit-animation:hoverfix .25s forwards;animation:hoverfix .25s forwards}.md-version:focus-within .md-version__list{-webkit-animation:none;animation:none}}.md-version__item{line-height:1.8rem}[dir=ltr] .md-version__link{padding-left:.6rem;padding-right:1.2rem}[dir=rtl] .md-version__link{padding-left:1.2rem;padding-right:.6rem}.md-version__link{cursor:pointer;display:block;outline:none;scroll-snap-align:start;transition:color .25s,background-color .25s;white-space:nowrap;width:100%}.md-version__link:-webkit-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-version__link:-moz-any(:focus,:hover){color:var(--md-accent-fg-color)}.md-version__link:is(:focus,:hover){color:var(--md-accent-fg-color)}.md-version__link:focus{background-color:var(--md-default-fg-color--lightest)}:root{--md-admonition-icon--note:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>');--md-admonition-icon--abstract:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M17 9H7V7h10m0 6H7v-2h10m-3 6H7v-2h7M12 3a1 1 0 0 1 1 1 1 1 0 0 1-1 1 1 1 0 0 1-1-1 1 1 0 0 1 1-1m7 0h-4.18C14.4 1.84 13.3 1 12 1c-1.3 0-2.4.84-2.82 2H5a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2V5a2 2 0 0 0-2-2Z"/></svg>');--md-admonition-icon--info:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M13 9h-2V7h2m0 10h-2v-6h2m-1-9A10 10 0 0 0 2 12a10 10 0 0 0 10 10 10 10 0 0 0 10-10A10 10 0 0 0 12 2Z"/></svg>');--md-admonition-icon--tip:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M17.66 11.2c-.23-.3-.51-.56-.77-.82-.67-.6-1.43-1.03-2.07-1.66C13.33 7.26 13 4.85 13.95 3c-.95.23-1.78.75-2.49 1.32-2.59 2.08-3.61 5.75-2.39 8.9.04.1.08.2.08.33 0 .22-.15.42-.35.5-.23.1-.47.04-.66-.12a.58.58 0 0 1-.14-.17c-1.13-1.43-1.31-3.48-.55-5.12C5.78 10 4.87 12.3 5 14.47c.06.5.12 1 .29 1.5.14.6.41 1.2.71 1.73 1.08 1.73 2.95 2.97 4.96 3.22 2.14.27 4.43-.12 6.07-1.6 1.83-1.66 2.47-4.32 1.53-6.6l-.13-.26c-.21-.46-.77-1.26-.77-1.26m-3.16 6.3c-.28.24-.74.5-1.1.6-1.12.4-2.24-.16-2.9-.82 1.19-.28 1.9-1.16 2.11-2.05.17-.8-.15-1.46-.28-2.23-.12-.74-.1-1.37.17-2.06.19.38.39.76.63 1.06.77 1 1.98 1.44 2.24 2.8.04.14.06.28.06.43.03.82-.33 1.72-.93 2.27Z"/></svg>');--md-admonition-icon--success:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m9 20.42-6.21-6.21 2.83-2.83L9 14.77l9.88-9.89 2.83 2.83L9 20.42Z"/></svg>');--md-admonition-icon--question:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="m15.07 11.25-.9.92C13.45 12.89 13 13.5 13 15h-2v-.5c0-1.11.45-2.11 1.17-2.83l1.24-1.26c.37-.36.59-.86.59-1.41a2 2 0 0 0-2-2 2 2 0 0 0-2 2H8a4 4 0 0 1 4-4 4 4 0 0 1 4 4 3.2 3.2 0 0 1-.93 2.25M13 19h-2v-2h2M12 2A10 10 0 0 0 2 12a10 10 0 0 0 10 10 10 10 0 0 0 10-10c0-5.53-4.5-10-10-10Z"/></svg>');--md-admonition-icon--warning:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M13 14h-2V9h2m0 9h-2v-2h2M1 21h22L12 2 1 21Z"/></svg>');--md-admonition-icon--failure:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 6.91 17.09 4 12 9.09 6.91 4 4 6.91 9.09 12 4 17.09 6.91 20 12 14.91 17.09 20 20 17.09 14.91 12 20 6.91Z"/></svg>');--md-admonition-icon--danger:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M11 15H6l7-14v8h5l-7 14v-8Z"/></svg>');--md-admonition-icon--bug:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M14 12h-4v-2h4m0 6h-4v-2h4m6-6h-2.81a5.985 5.985 0 0 0-1.82-1.96L17 4.41 15.59 3l-2.17 2.17a6.002 6.002 0 0 0-2.83 0L8.41 3 7 4.41l1.62 1.63C7.88 6.55 7.26 7.22 6.81 8H4v2h2.09c-.05.33-.09.66-.09 1v1H4v2h2v1c0 .34.04.67.09 1H4v2h2.81c1.04 1.79 2.97 3 5.19 3s4.15-1.21 5.19-3H20v-2h-2.09c.05-.33.09-.66.09-1v-1h2v-2h-2v-1c0-.34-.04-.67-.09-1H20V8Z"/></svg>');--md-admonition-icon--example:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M7 13v-2h14v2H7m0 6v-2h14v2H7M7 7V5h14v2H7M3 8V5H2V4h2v4H3m-1 9v-1h3v4H2v-1h2v-.5H3v-1h1V17H2m2.25-7a.75.75 0 0 1 .75.75c0 .2-.08.39-.21.52L3.12 13H5v1H2v-.92L4 11H2v-1h2.25Z"/></svg>');--md-admonition-icon--quote:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M14 17h3l2-4V7h-6v6h3M6 17h3l2-4V7H5v6h3l-2 4Z"/></svg>')}.md-typeset :-webkit-any(.admonition,details){background-color:var(--md-admonition-bg-color);border:0 solid #448aff;border-radius:.1rem;box-shadow:var(--md-shadow-z1);color:var(--md-admonition-fg-color);display:flow-root;font-size:.64rem;margin:1.5625em 0;padding:0 .6rem;page-break-inside:avoid}.md-typeset :-moz-any(.admonition,details){background-color:var(--md-admonition-bg-color);border:0 solid #448aff;border-radius:.1rem;box-shadow:var(--md-shadow-z1);color:var(--md-admonition-fg-color);display:flow-root;font-size:.64rem;margin:1.5625em 0;padding:0 .6rem;page-break-inside:avoid}[dir=ltr] .md-typeset :-webkit-any(.admonition,details){border-left-width:.2rem}[dir=ltr] .md-typeset :-moz-any(.admonition,details){border-left-width:.2rem}[dir=ltr] .md-typeset :is(.admonition,details){border-left-width:.2rem}[dir=rtl] .md-typeset :-webkit-any(.admonition,details){border-right-width:.2rem}[dir=rtl] .md-typeset :-moz-any(.admonition,details){border-right-width:.2rem}[dir=rtl] .md-typeset :is(.admonition,details){border-right-width:.2rem}.md-typeset :is(.admonition,details){background-color:var(--md-admonition-bg-color);border:0 solid #448aff;border-radius:.1rem;box-shadow:var(--md-shadow-z1);color:var(--md-admonition-fg-color);display:flow-root;font-size:.64rem;margin:1.5625em 0;padding:0 .6rem;page-break-inside:avoid}@media print{.md-typeset :-webkit-any(.admonition,details){box-shadow:none}.md-typeset :-moz-any(.admonition,details){box-shadow:none}.md-typeset :is(.admonition,details){box-shadow:none}}.md-typeset :-webkit-any(.admonition,details)>*{box-sizing:border-box}.md-typeset :-moz-any(.admonition,details)>*{box-sizing:border-box}.md-typeset :is(.admonition,details)>*{box-sizing:border-box}.md-typeset :-webkit-any(.admonition,details) :-webkit-any(.admonition,details){margin-bottom:1em;margin-top:1em}.md-typeset :-moz-any(.admonition,details) :-moz-any(.admonition,details){margin-bottom:1em;margin-top:1em}.md-typeset :is(.admonition,details) :is(.admonition,details){margin-bottom:1em;margin-top:1em}.md-typeset :-webkit-any(.admonition,details) .md-typeset__scrollwrap{margin:1em -.6rem}.md-typeset :-moz-any(.admonition,details) .md-typeset__scrollwrap{margin:1em -.6rem}.md-typeset :is(.admonition,details) .md-typeset__scrollwrap{margin:1em -.6rem}.md-typeset :-webkit-any(.admonition,details) .md-typeset__table{padding:0 .6rem}.md-typeset :-moz-any(.admonition,details) .md-typeset__table{padding:0 .6rem}.md-typeset :is(.admonition,details) .md-typeset__table{padding:0 .6rem}.md-typeset :-webkit-any(.admonition,details)>.tabbed-set:only-child{margin-top:0}.md-typeset :-moz-any(.admonition,details)>.tabbed-set:only-child{margin-top:0}.md-typeset :is(.admonition,details)>.tabbed-set:only-child{margin-top:0}html .md-typeset :-webkit-any(.admonition,details)>:last-child{margin-bottom:.6rem}html .md-typeset :-moz-any(.admonition,details)>:last-child{margin-bottom:.6rem}html .md-typeset :is(.admonition,details)>:last-child{margin-bottom:.6rem}.md-typeset :-webkit-any(.admonition-title,summary){background-color:rgba(68,138,255,.1);border:none;font-weight:700;margin-bottom:0;margin-top:0;padding-bottom:.4rem;padding-top:.4rem;position:relative}.md-typeset :-moz-any(.admonition-title,summary){background-color:rgba(68,138,255,.1);border:none;font-weight:700;margin-bottom:0;margin-top:0;padding-bottom:.4rem;padding-top:.4rem;position:relative}[dir=ltr] .md-typeset :-webkit-any(.admonition-title,summary){margin-left:-.8rem;margin-right:-.6rem}[dir=ltr] .md-typeset :-moz-any(.admonition-title,summary){margin-left:-.8rem;margin-right:-.6rem}[dir=ltr] .md-typeset :is(.admonition-title,summary){margin-left:-.8rem;margin-right:-.6rem}[dir=rtl] .md-typeset :-webkit-any(.admonition-title,summary){margin-left:-.6rem;margin-right:-.8rem}[dir=rtl] .md-typeset :-moz-any(.admonition-title,summary){margin-left:-.6rem;margin-right:-.8rem}[dir=rtl] .md-typeset :is(.admonition-title,summary){margin-left:-.6rem;margin-right:-.8rem}[dir=ltr] .md-typeset :-webkit-any(.admonition-title,summary){padding-left:2.2rem;padding-right:.6rem}[dir=ltr] .md-typeset :-moz-any(.admonition-title,summary){padding-left:2.2rem;padding-right:.6rem}[dir=ltr] .md-typeset :is(.admonition-title,summary){padding-left:2.2rem;padding-right:.6rem}[dir=rtl] .md-typeset :-webkit-any(.admonition-title,summary){padding-left:.6rem;padding-right:2.2rem}[dir=rtl] .md-typeset :-moz-any(.admonition-title,summary){padding-left:.6rem;padding-right:2.2rem}[dir=rtl] .md-typeset :is(.admonition-title,summary){padding-left:.6rem;padding-right:2.2rem}[dir=ltr] .md-typeset :-webkit-any(.admonition-title,summary){border-left-width:.2rem}[dir=ltr] .md-typeset :-moz-any(.admonition-title,summary){border-left-width:.2rem}[dir=ltr] .md-typeset :is(.admonition-title,summary){border-left-width:.2rem}[dir=rtl] .md-typeset :-webkit-any(.admonition-title,summary){border-right-width:.2rem}[dir=rtl] .md-typeset :-moz-any(.admonition-title,summary){border-right-width:.2rem}[dir=rtl] .md-typeset :is(.admonition-title,summary){border-right-width:.2rem}[dir=ltr] .md-typeset :-webkit-any(.admonition-title,summary){border-top-left-radius:.1rem}[dir=ltr] .md-typeset :-moz-any(.admonition-title,summary){border-top-left-radius:.1rem}[dir=ltr] .md-typeset :is(.admonition-title,summary){border-top-left-radius:.1rem}[dir=rtl] .md-typeset :-webkit-any(.admonition-title,summary){border-top-right-radius:.1rem}[dir=rtl] .md-typeset :-moz-any(.admonition-title,summary){border-top-right-radius:.1rem}[dir=rtl] .md-typeset :is(.admonition-title,summary){border-top-right-radius:.1rem}[dir=ltr] .md-typeset :-webkit-any(.admonition-title,summary){border-top-right-radius:.1rem}[dir=ltr] .md-typeset :-moz-any(.admonition-title,summary){border-top-right-radius:.1rem}[dir=ltr] .md-typeset :is(.admonition-title,summary){border-top-right-radius:.1rem}[dir=rtl] .md-typeset :-webkit-any(.admonition-title,summary){border-top-left-radius:.1rem}[dir=rtl] .md-typeset :-moz-any(.admonition-title,summary){border-top-left-radius:.1rem}[dir=rtl] .md-typeset :is(.admonition-title,summary){border-top-left-radius:.1rem}.md-typeset :is(.admonition-title,summary){background-color:rgba(68,138,255,.1);border:none;font-weight:700;margin-bottom:0;margin-top:0;padding-bottom:.4rem;padding-top:.4rem;position:relative}html .md-typeset :-webkit-any(.admonition-title,summary):last-child{margin-bottom:0}html .md-typeset :-moz-any(.admonition-title,summary):last-child{margin-bottom:0}html .md-typeset :is(.admonition-title,summary):last-child{margin-bottom:0}.md-typeset :-webkit-any(.admonition-title,summary):before{background-color:#448aff;content:"";height:1rem;-webkit-mask-image:var(--md-admonition-icon--note);mask-image:var(--md-admonition-icon--note);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;position:absolute;top:.625em;width:1rem}.md-typeset :-moz-any(.admonition-title,summary):before{background-color:#448aff;content:"";height:1rem;mask-image:var(--md-admonition-icon--note);mask-repeat:no-repeat;mask-size:contain;position:absolute;top:.625em;width:1rem}[dir=ltr] .md-typeset :-webkit-any(.admonition-title,summary):before{left:.8rem}[dir=ltr] .md-typeset :-moz-any(.admonition-title,summary):before{left:.8rem}[dir=ltr] .md-typeset :is(.admonition-title,summary):before{left:.8rem}[dir=rtl] .md-typeset :-webkit-any(.admonition-title,summary):before{right:.8rem}[dir=rtl] .md-typeset :-moz-any(.admonition-title,summary):before{right:.8rem}[dir=rtl] .md-typeset :is(.admonition-title,summary):before{right:.8rem}.md-typeset :is(.admonition-title,summary):before{background-color:#448aff;content:"";height:1rem;-webkit-mask-image:var(--md-admonition-icon--note);mask-image:var(--md-admonition-icon--note);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;position:absolute;top:.625em;width:1rem}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.note){border-color:#448aff}.md-typeset :-moz-any(.admonition,details):-moz-any(.note){border-color:#448aff}.md-typeset :is(.admonition,details):is(.note){border-color:#448aff}.md-typeset :-webkit-any(.note)>:-webkit-any(.admonition-title,summary){background-color:rgba(68,138,255,.1)}.md-typeset :-moz-any(.note)>:-moz-any(.admonition-title,summary){background-color:rgba(68,138,255,.1)}.md-typeset :is(.note)>:is(.admonition-title,summary){background-color:rgba(68,138,255,.1)}.md-typeset :-webkit-any(.note)>:-webkit-any(.admonition-title,summary):before{background-color:#448aff;-webkit-mask-image:var(--md-admonition-icon--note);mask-image:var(--md-admonition-icon--note);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.note)>:-moz-any(.admonition-title,summary):before{background-color:#448aff;mask-image:var(--md-admonition-icon--note);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.note)>:is(.admonition-title,summary):before{background-color:#448aff;-webkit-mask-image:var(--md-admonition-icon--note);mask-image:var(--md-admonition-icon--note);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.abstract,.summary,.tldr){border-color:#00b0ff}.md-typeset :-moz-any(.admonition,details):-moz-any(.abstract,.summary,.tldr){border-color:#00b0ff}.md-typeset :is(.admonition,details):is(.abstract,.summary,.tldr){border-color:#00b0ff}.md-typeset :-webkit-any(.abstract,.summary,.tldr)>:-webkit-any(.admonition-title,summary){background-color:rgba(0,176,255,.1)}.md-typeset :-moz-any(.abstract,.summary,.tldr)>:-moz-any(.admonition-title,summary){background-color:rgba(0,176,255,.1)}.md-typeset :is(.abstract,.summary,.tldr)>:is(.admonition-title,summary){background-color:rgba(0,176,255,.1)}.md-typeset :-webkit-any(.abstract,.summary,.tldr)>:-webkit-any(.admonition-title,summary):before{background-color:#00b0ff;-webkit-mask-image:var(--md-admonition-icon--abstract);mask-image:var(--md-admonition-icon--abstract);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.abstract,.summary,.tldr)>:-moz-any(.admonition-title,summary):before{background-color:#00b0ff;mask-image:var(--md-admonition-icon--abstract);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.abstract,.summary,.tldr)>:is(.admonition-title,summary):before{background-color:#00b0ff;-webkit-mask-image:var(--md-admonition-icon--abstract);mask-image:var(--md-admonition-icon--abstract);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.info,.todo){border-color:#00b8d4}.md-typeset :-moz-any(.admonition,details):-moz-any(.info,.todo){border-color:#00b8d4}.md-typeset :is(.admonition,details):is(.info,.todo){border-color:#00b8d4}.md-typeset :-webkit-any(.info,.todo)>:-webkit-any(.admonition-title,summary){background-color:rgba(0,184,212,.1)}.md-typeset :-moz-any(.info,.todo)>:-moz-any(.admonition-title,summary){background-color:rgba(0,184,212,.1)}.md-typeset :is(.info,.todo)>:is(.admonition-title,summary){background-color:rgba(0,184,212,.1)}.md-typeset :-webkit-any(.info,.todo)>:-webkit-any(.admonition-title,summary):before{background-color:#00b8d4;-webkit-mask-image:var(--md-admonition-icon--info);mask-image:var(--md-admonition-icon--info);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.info,.todo)>:-moz-any(.admonition-title,summary):before{background-color:#00b8d4;mask-image:var(--md-admonition-icon--info);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.info,.todo)>:is(.admonition-title,summary):before{background-color:#00b8d4;-webkit-mask-image:var(--md-admonition-icon--info);mask-image:var(--md-admonition-icon--info);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.tip,.hint,.important){border-color:#00bfa5}.md-typeset :-moz-any(.admonition,details):-moz-any(.tip,.hint,.important){border-color:#00bfa5}.md-typeset :is(.admonition,details):is(.tip,.hint,.important){border-color:#00bfa5}.md-typeset :-webkit-any(.tip,.hint,.important)>:-webkit-any(.admonition-title,summary){background-color:rgba(0,191,165,.1)}.md-typeset :-moz-any(.tip,.hint,.important)>:-moz-any(.admonition-title,summary){background-color:rgba(0,191,165,.1)}.md-typeset :is(.tip,.hint,.important)>:is(.admonition-title,summary){background-color:rgba(0,191,165,.1)}.md-typeset :-webkit-any(.tip,.hint,.important)>:-webkit-any(.admonition-title,summary):before{background-color:#00bfa5;-webkit-mask-image:var(--md-admonition-icon--tip);mask-image:var(--md-admonition-icon--tip);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.tip,.hint,.important)>:-moz-any(.admonition-title,summary):before{background-color:#00bfa5;mask-image:var(--md-admonition-icon--tip);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.tip,.hint,.important)>:is(.admonition-title,summary):before{background-color:#00bfa5;-webkit-mask-image:var(--md-admonition-icon--tip);mask-image:var(--md-admonition-icon--tip);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.success,.check,.done){border-color:#00c853}.md-typeset :-moz-any(.admonition,details):-moz-any(.success,.check,.done){border-color:#00c853}.md-typeset :is(.admonition,details):is(.success,.check,.done){border-color:#00c853}.md-typeset :-webkit-any(.success,.check,.done)>:-webkit-any(.admonition-title,summary){background-color:rgba(0,200,83,.1)}.md-typeset :-moz-any(.success,.check,.done)>:-moz-any(.admonition-title,summary){background-color:rgba(0,200,83,.1)}.md-typeset :is(.success,.check,.done)>:is(.admonition-title,summary){background-color:rgba(0,200,83,.1)}.md-typeset :-webkit-any(.success,.check,.done)>:-webkit-any(.admonition-title,summary):before{background-color:#00c853;-webkit-mask-image:var(--md-admonition-icon--success);mask-image:var(--md-admonition-icon--success);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.success,.check,.done)>:-moz-any(.admonition-title,summary):before{background-color:#00c853;mask-image:var(--md-admonition-icon--success);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.success,.check,.done)>:is(.admonition-title,summary):before{background-color:#00c853;-webkit-mask-image:var(--md-admonition-icon--success);mask-image:var(--md-admonition-icon--success);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.question,.help,.faq){border-color:#64dd17}.md-typeset :-moz-any(.admonition,details):-moz-any(.question,.help,.faq){border-color:#64dd17}.md-typeset :is(.admonition,details):is(.question,.help,.faq){border-color:#64dd17}.md-typeset :-webkit-any(.question,.help,.faq)>:-webkit-any(.admonition-title,summary){background-color:rgba(100,221,23,.1)}.md-typeset :-moz-any(.question,.help,.faq)>:-moz-any(.admonition-title,summary){background-color:rgba(100,221,23,.1)}.md-typeset :is(.question,.help,.faq)>:is(.admonition-title,summary){background-color:rgba(100,221,23,.1)}.md-typeset :-webkit-any(.question,.help,.faq)>:-webkit-any(.admonition-title,summary):before{background-color:#64dd17;-webkit-mask-image:var(--md-admonition-icon--question);mask-image:var(--md-admonition-icon--question);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.question,.help,.faq)>:-moz-any(.admonition-title,summary):before{background-color:#64dd17;mask-image:var(--md-admonition-icon--question);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.question,.help,.faq)>:is(.admonition-title,summary):before{background-color:#64dd17;-webkit-mask-image:var(--md-admonition-icon--question);mask-image:var(--md-admonition-icon--question);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.warning,.caution,.attention){border-color:#ff9100}.md-typeset :-moz-any(.admonition,details):-moz-any(.warning,.caution,.attention){border-color:#ff9100}.md-typeset :is(.admonition,details):is(.warning,.caution,.attention){border-color:#ff9100}.md-typeset :-webkit-any(.warning,.caution,.attention)>:-webkit-any(.admonition-title,summary){background-color:rgba(255,145,0,.1)}.md-typeset :-moz-any(.warning,.caution,.attention)>:-moz-any(.admonition-title,summary){background-color:rgba(255,145,0,.1)}.md-typeset :is(.warning,.caution,.attention)>:is(.admonition-title,summary){background-color:rgba(255,145,0,.1)}.md-typeset :-webkit-any(.warning,.caution,.attention)>:-webkit-any(.admonition-title,summary):before{background-color:#ff9100;-webkit-mask-image:var(--md-admonition-icon--warning);mask-image:var(--md-admonition-icon--warning);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.warning,.caution,.attention)>:-moz-any(.admonition-title,summary):before{background-color:#ff9100;mask-image:var(--md-admonition-icon--warning);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.warning,.caution,.attention)>:is(.admonition-title,summary):before{background-color:#ff9100;-webkit-mask-image:var(--md-admonition-icon--warning);mask-image:var(--md-admonition-icon--warning);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.failure,.fail,.missing){border-color:#ff5252}.md-typeset :-moz-any(.admonition,details):-moz-any(.failure,.fail,.missing){border-color:#ff5252}.md-typeset :is(.admonition,details):is(.failure,.fail,.missing){border-color:#ff5252}.md-typeset :-webkit-any(.failure,.fail,.missing)>:-webkit-any(.admonition-title,summary){background-color:rgba(255,82,82,.1)}.md-typeset :-moz-any(.failure,.fail,.missing)>:-moz-any(.admonition-title,summary){background-color:rgba(255,82,82,.1)}.md-typeset :is(.failure,.fail,.missing)>:is(.admonition-title,summary){background-color:rgba(255,82,82,.1)}.md-typeset :-webkit-any(.failure,.fail,.missing)>:-webkit-any(.admonition-title,summary):before{background-color:#ff5252;-webkit-mask-image:var(--md-admonition-icon--failure);mask-image:var(--md-admonition-icon--failure);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.failure,.fail,.missing)>:-moz-any(.admonition-title,summary):before{background-color:#ff5252;mask-image:var(--md-admonition-icon--failure);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.failure,.fail,.missing)>:is(.admonition-title,summary):before{background-color:#ff5252;-webkit-mask-image:var(--md-admonition-icon--failure);mask-image:var(--md-admonition-icon--failure);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.danger,.error){border-color:#ff1744}.md-typeset :-moz-any(.admonition,details):-moz-any(.danger,.error){border-color:#ff1744}.md-typeset :is(.admonition,details):is(.danger,.error){border-color:#ff1744}.md-typeset :-webkit-any(.danger,.error)>:-webkit-any(.admonition-title,summary){background-color:rgba(255,23,68,.1)}.md-typeset :-moz-any(.danger,.error)>:-moz-any(.admonition-title,summary){background-color:rgba(255,23,68,.1)}.md-typeset :is(.danger,.error)>:is(.admonition-title,summary){background-color:rgba(255,23,68,.1)}.md-typeset :-webkit-any(.danger,.error)>:-webkit-any(.admonition-title,summary):before{background-color:#ff1744;-webkit-mask-image:var(--md-admonition-icon--danger);mask-image:var(--md-admonition-icon--danger);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.danger,.error)>:-moz-any(.admonition-title,summary):before{background-color:#ff1744;mask-image:var(--md-admonition-icon--danger);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.danger,.error)>:is(.admonition-title,summary):before{background-color:#ff1744;-webkit-mask-image:var(--md-admonition-icon--danger);mask-image:var(--md-admonition-icon--danger);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.bug){border-color:#f50057}.md-typeset :-moz-any(.admonition,details):-moz-any(.bug){border-color:#f50057}.md-typeset :is(.admonition,details):is(.bug){border-color:#f50057}.md-typeset :-webkit-any(.bug)>:-webkit-any(.admonition-title,summary){background-color:rgba(245,0,87,.1)}.md-typeset :-moz-any(.bug)>:-moz-any(.admonition-title,summary){background-color:rgba(245,0,87,.1)}.md-typeset :is(.bug)>:is(.admonition-title,summary){background-color:rgba(245,0,87,.1)}.md-typeset :-webkit-any(.bug)>:-webkit-any(.admonition-title,summary):before{background-color:#f50057;-webkit-mask-image:var(--md-admonition-icon--bug);mask-image:var(--md-admonition-icon--bug);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.bug)>:-moz-any(.admonition-title,summary):before{background-color:#f50057;mask-image:var(--md-admonition-icon--bug);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.bug)>:is(.admonition-title,summary):before{background-color:#f50057;-webkit-mask-image:var(--md-admonition-icon--bug);mask-image:var(--md-admonition-icon--bug);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.example){border-color:#7c4dff}.md-typeset :-moz-any(.admonition,details):-moz-any(.example){border-color:#7c4dff}.md-typeset :is(.admonition,details):is(.example){border-color:#7c4dff}.md-typeset :-webkit-any(.example)>:-webkit-any(.admonition-title,summary){background-color:rgba(124,77,255,.1)}.md-typeset :-moz-any(.example)>:-moz-any(.admonition-title,summary){background-color:rgba(124,77,255,.1)}.md-typeset :is(.example)>:is(.admonition-title,summary){background-color:rgba(124,77,255,.1)}.md-typeset :-webkit-any(.example)>:-webkit-any(.admonition-title,summary):before{background-color:#7c4dff;-webkit-mask-image:var(--md-admonition-icon--example);mask-image:var(--md-admonition-icon--example);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.example)>:-moz-any(.admonition-title,summary):before{background-color:#7c4dff;mask-image:var(--md-admonition-icon--example);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.example)>:is(.admonition-title,summary):before{background-color:#7c4dff;-webkit-mask-image:var(--md-admonition-icon--example);mask-image:var(--md-admonition-icon--example);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-webkit-any(.admonition,details):-webkit-any(.quote,.cite){border-color:#9e9e9e}.md-typeset :-moz-any(.admonition,details):-moz-any(.quote,.cite){border-color:#9e9e9e}.md-typeset :is(.admonition,details):is(.quote,.cite){border-color:#9e9e9e}.md-typeset :-webkit-any(.quote,.cite)>:-webkit-any(.admonition-title,summary){background-color:hsla(0,0%,62%,.1)}.md-typeset :-moz-any(.quote,.cite)>:-moz-any(.admonition-title,summary){background-color:hsla(0,0%,62%,.1)}.md-typeset :is(.quote,.cite)>:is(.admonition-title,summary){background-color:hsla(0,0%,62%,.1)}.md-typeset :-webkit-any(.quote,.cite)>:-webkit-any(.admonition-title,summary):before{background-color:#9e9e9e;-webkit-mask-image:var(--md-admonition-icon--quote);mask-image:var(--md-admonition-icon--quote);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}.md-typeset :-moz-any(.quote,.cite)>:-moz-any(.admonition-title,summary):before{background-color:#9e9e9e;mask-image:var(--md-admonition-icon--quote);mask-repeat:no-repeat;mask-size:contain}.md-typeset :is(.quote,.cite)>:is(.admonition-title,summary):before{background-color:#9e9e9e;-webkit-mask-image:var(--md-admonition-icon--quote);mask-image:var(--md-admonition-icon--quote);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain}:root{--md-footnotes-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 7v4H5.83l3.58-3.59L8 6l-6 6 6 6 1.41-1.42L5.83 13H21V7h-2Z"/></svg>')}.md-typeset .footnote{color:var(--md-default-fg-color--light);font-size:.64rem}[dir=ltr] .md-typeset .footnote>ol{margin-left:0}[dir=rtl] .md-typeset .footnote>ol{margin-right:0}.md-typeset .footnote>ol>li{transition:color 125ms}.md-typeset .footnote>ol>li:target{color:var(--md-default-fg-color)}.md-typeset .footnote>ol>li:focus-within .footnote-backref{opacity:1;transform:translateX(0);transition:none}.md-typeset .footnote>ol>li:-webkit-any(:hover,:target) .footnote-backref{opacity:1;transform:translateX(0)}.md-typeset .footnote>ol>li:-moz-any(:hover,:target) .footnote-backref{opacity:1;transform:translateX(0)}.md-typeset .footnote>ol>li:is(:hover,:target) .footnote-backref{opacity:1;transform:translateX(0)}.md-typeset .footnote>ol>li>:first-child{margin-top:0}.md-typeset .footnote-ref{font-size:.75em;font-weight:700}html .md-typeset .footnote-ref{outline-offset:.1rem}.md-typeset [id^="fnref:"]:target>.footnote-ref{outline:auto}.md-typeset .footnote-backref{color:var(--md-typeset-a-color);display:inline-block;font-size:0;opacity:0;transform:translateX(.25rem);transition:color .25s,transform .25s .25s,opacity 125ms .25s;vertical-align:text-bottom}@media print{.md-typeset .footnote-backref{color:var(--md-typeset-a-color);opacity:1;transform:translateX(0)}}[dir=rtl] .md-typeset .footnote-backref{transform:translateX(-.25rem)}.md-typeset .footnote-backref:hover{color:var(--md-accent-fg-color)}.md-typeset .footnote-backref:before{background-color:currentcolor;content:"";display:inline-block;height:.8rem;-webkit-mask-image:var(--md-footnotes-icon);mask-image:var(--md-footnotes-icon);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;width:.8rem}[dir=rtl] .md-typeset .footnote-backref:before svg{transform:scaleX(-1)}[dir=ltr] .md-typeset .headerlink{margin-left:.5rem}[dir=rtl] .md-typeset .headerlink{margin-right:.5rem}.md-typeset .headerlink{color:var(--md-default-fg-color--lighter);display:inline-block;opacity:0;transition:color .25s,opacity 125ms}@media print{.md-typeset .headerlink{display:none}}.md-typeset .headerlink:focus,.md-typeset :-webkit-any(:hover,:target)>.headerlink{opacity:1;-webkit-transition:color .25s,opacity 125ms;transition:color .25s,opacity 125ms}.md-typeset .headerlink:focus,.md-typeset :-moz-any(:hover,:target)>.headerlink{opacity:1;-moz-transition:color .25s,opacity 125ms;transition:color .25s,opacity 125ms}.md-typeset .headerlink:focus,.md-typeset :is(:hover,:target)>.headerlink{opacity:1;transition:color .25s,opacity 125ms}.md-typeset .headerlink:-webkit-any(:focus,:hover),.md-typeset :target>.headerlink{color:var(--md-accent-fg-color)}.md-typeset .headerlink:-moz-any(:focus,:hover),.md-typeset :target>.headerlink{color:var(--md-accent-fg-color)}.md-typeset .headerlink:is(:focus,:hover),.md-typeset :target>.headerlink{color:var(--md-accent-fg-color)}.md-typeset :target{--md-scroll-margin:3.6rem;--md-scroll-offset:0rem;scroll-margin-top:calc(var(--md-scroll-margin) - var(--md-scroll-offset))}@media screen and (min-width:76.25em){.md-header--lifted~.md-container .md-typeset :target{--md-scroll-margin:6rem}}.md-typeset :-webkit-any(h1,h2,h3):target{--md-scroll-offset:0.2rem}.md-typeset :-moz-any(h1,h2,h3):target{--md-scroll-offset:0.2rem}.md-typeset :is(h1,h2,h3):target{--md-scroll-offset:0.2rem}.md-typeset h4:target{--md-scroll-offset:0.15rem}.md-typeset div.arithmatex{overflow:auto}@media screen and (max-width:44.9375em){.md-typeset div.arithmatex{margin:0 -.8rem}}.md-typeset div.arithmatex>*{margin-left:auto!important;margin-right:auto!important;padding:0 .8rem;touch-action:auto;width:-webkit-min-content;width:-moz-min-content;width:min-content}.md-typeset div.arithmatex>* mjx-container{margin:0!important}.md-typeset :-webkit-any(del,ins,.comment).critic{-webkit-box-decoration-break:clone;box-decoration-break:clone}.md-typeset :-moz-any(del,ins,.comment).critic{box-decoration-break:clone}.md-typeset :is(del,ins,.comment).critic{-webkit-box-decoration-break:clone;box-decoration-break:clone}.md-typeset del.critic{background-color:var(--md-typeset-del-color)}.md-typeset ins.critic{background-color:var(--md-typeset-ins-color)}.md-typeset .critic.comment{color:var(--md-code-hl-comment-color)}.md-typeset .critic.comment:before{content:"/* "}.md-typeset .critic.comment:after{content:" */"}.md-typeset .critic.block{box-shadow:none;display:block;margin:1em 0;overflow:auto;padding-left:.8rem;padding-right:.8rem}.md-typeset .critic.block>:first-child{margin-top:.5em}.md-typeset .critic.block>:last-child{margin-bottom:.5em}:root{--md-details-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M8.59 16.58 13.17 12 8.59 7.41 10 6l6 6-6 6-1.41-1.42Z"/></svg>')}.md-typeset details{display:flow-root;overflow:visible;padding-top:0}.md-typeset details[open]>summary:after{transform:rotate(90deg)}.md-typeset details:not([open]){box-shadow:none;padding-bottom:0}.md-typeset details:not([open])>summary{border-radius:.1rem}[dir=ltr] .md-typeset summary{padding-right:1.8rem}[dir=rtl] .md-typeset summary{padding-left:1.8rem}[dir=ltr] .md-typeset summary{border-top-left-radius:.1rem}[dir=ltr] .md-typeset summary,[dir=rtl] .md-typeset summary{border-top-right-radius:.1rem}[dir=rtl] .md-typeset summary{border-top-left-radius:.1rem}.md-typeset summary{cursor:pointer;display:block;min-height:1rem}.md-typeset summary.focus-visible{outline-color:var(--md-accent-fg-color);outline-offset:.2rem}.md-typeset summary:not(.focus-visible){-webkit-tap-highlight-color:transparent;outline:none}[dir=ltr] .md-typeset summary:after{right:.4rem}[dir=rtl] .md-typeset summary:after{left:.4rem}.md-typeset summary:after{background-color:currentcolor;content:"";height:1rem;-webkit-mask-image:var(--md-details-icon);mask-image:var(--md-details-icon);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;position:absolute;top:.625em;transform:rotate(0deg);transition:transform .25s;width:1rem}[dir=rtl] .md-typeset summary:after{transform:rotate(180deg)}.md-typeset summary::marker{display:none}.md-typeset summary::-webkit-details-marker{display:none}.md-typeset :-webkit-any(.emojione,.twemoji,.gemoji){display:inline-flex;height:1.125em;vertical-align:text-top}.md-typeset :-moz-any(.emojione,.twemoji,.gemoji){display:inline-flex;height:1.125em;vertical-align:text-top}.md-typeset :is(.emojione,.twemoji,.gemoji){display:inline-flex;height:1.125em;vertical-align:text-top}.md-typeset :-webkit-any(.emojione,.twemoji,.gemoji) svg{fill:currentcolor;max-height:100%;width:1.125em}.md-typeset :-moz-any(.emojione,.twemoji,.gemoji) svg{fill:currentcolor;max-height:100%;width:1.125em}.md-typeset :is(.emojione,.twemoji,.gemoji) svg{fill:currentcolor;max-height:100%;width:1.125em}.highlight :-webkit-any(.o,.ow){color:var(--md-code-hl-operator-color)}.highlight :-moz-any(.o,.ow){color:var(--md-code-hl-operator-color)}.highlight :is(.o,.ow){color:var(--md-code-hl-operator-color)}.highlight .p{color:var(--md-code-hl-punctuation-color)}.highlight :-webkit-any(.cpf,.l,.s,.sb,.sc,.s2,.si,.s1,.ss){color:var(--md-code-hl-string-color)}.highlight :-moz-any(.cpf,.l,.s,.sb,.sc,.s2,.si,.s1,.ss){color:var(--md-code-hl-string-color)}.highlight :is(.cpf,.l,.s,.sb,.sc,.s2,.si,.s1,.ss){color:var(--md-code-hl-string-color)}.highlight :-webkit-any(.cp,.se,.sh,.sr,.sx){color:var(--md-code-hl-special-color)}.highlight :-moz-any(.cp,.se,.sh,.sr,.sx){color:var(--md-code-hl-special-color)}.highlight :is(.cp,.se,.sh,.sr,.sx){color:var(--md-code-hl-special-color)}.highlight :-webkit-any(.m,.mb,.mf,.mh,.mi,.il,.mo){color:var(--md-code-hl-number-color)}.highlight :-moz-any(.m,.mb,.mf,.mh,.mi,.il,.mo){color:var(--md-code-hl-number-color)}.highlight :is(.m,.mb,.mf,.mh,.mi,.il,.mo){color:var(--md-code-hl-number-color)}.highlight :-webkit-any(.k,.kd,.kn,.kp,.kr,.kt){color:var(--md-code-hl-keyword-color)}.highlight :-moz-any(.k,.kd,.kn,.kp,.kr,.kt){color:var(--md-code-hl-keyword-color)}.highlight :is(.k,.kd,.kn,.kp,.kr,.kt){color:var(--md-code-hl-keyword-color)}.highlight :-webkit-any(.kc,.n){color:var(--md-code-hl-name-color)}.highlight :-moz-any(.kc,.n){color:var(--md-code-hl-name-color)}.highlight :is(.kc,.n){color:var(--md-code-hl-name-color)}.highlight :-webkit-any(.no,.nb,.bp){color:var(--md-code-hl-constant-color)}.highlight :-moz-any(.no,.nb,.bp){color:var(--md-code-hl-constant-color)}.highlight :is(.no,.nb,.bp){color:var(--md-code-hl-constant-color)}.highlight :-webkit-any(.nc,.ne,.nf,.nn){color:var(--md-code-hl-function-color)}.highlight :-moz-any(.nc,.ne,.nf,.nn){color:var(--md-code-hl-function-color)}.highlight :is(.nc,.ne,.nf,.nn){color:var(--md-code-hl-function-color)}.highlight :-webkit-any(.nd,.ni,.nl,.nt){color:var(--md-code-hl-keyword-color)}.highlight :-moz-any(.nd,.ni,.nl,.nt){color:var(--md-code-hl-keyword-color)}.highlight :is(.nd,.ni,.nl,.nt){color:var(--md-code-hl-keyword-color)}.highlight :-webkit-any(.c,.cm,.c1,.ch,.cs,.sd){color:var(--md-code-hl-comment-color)}.highlight :-moz-any(.c,.cm,.c1,.ch,.cs,.sd){color:var(--md-code-hl-comment-color)}.highlight :is(.c,.cm,.c1,.ch,.cs,.sd){color:var(--md-code-hl-comment-color)}.highlight :-webkit-any(.na,.nv,.vc,.vg,.vi){color:var(--md-code-hl-variable-color)}.highlight :-moz-any(.na,.nv,.vc,.vg,.vi){color:var(--md-code-hl-variable-color)}.highlight :is(.na,.nv,.vc,.vg,.vi){color:var(--md-code-hl-variable-color)}.highlight :-webkit-any(.ge,.gr,.gh,.go,.gp,.gs,.gu,.gt){color:var(--md-code-hl-generic-color)}.highlight :-moz-any(.ge,.gr,.gh,.go,.gp,.gs,.gu,.gt){color:var(--md-code-hl-generic-color)}.highlight :is(.ge,.gr,.gh,.go,.gp,.gs,.gu,.gt){color:var(--md-code-hl-generic-color)}.highlight :-webkit-any(.gd,.gi){border-radius:.1rem;margin:0 -.125em;padding:0 .125em}.highlight :-moz-any(.gd,.gi){border-radius:.1rem;margin:0 -.125em;padding:0 .125em}.highlight :is(.gd,.gi){border-radius:.1rem;margin:0 -.125em;padding:0 .125em}.highlight .gd{background-color:var(--md-typeset-del-color)}.highlight .gi{background-color:var(--md-typeset-ins-color)}.highlight .hll{background-color:var(--md-code-hl-color);display:block;margin:0 -1.1764705882em;padding:0 1.1764705882em}.highlight span.filename{background-color:var(--md-code-bg-color);border-bottom:.05rem solid var(--md-default-fg-color--lightest);border-top-left-radius:.1rem;border-top-right-radius:.1rem;display:flow-root;font-size:.85em;font-weight:700;margin-top:1em;padding:.6617647059em 1.1764705882em;position:relative}.highlight span.filename+pre{margin-top:0}.highlight span.filename+pre>code{border-top-left-radius:0;border-top-right-radius:0}.highlight [data-linenos]:before{background-color:var(--md-code-bg-color);box-shadow:-.05rem 0 var(--md-default-fg-color--lightest) inset;color:var(--md-default-fg-color--light);content:attr(data-linenos);float:left;left:-1.1764705882em;margin-left:-1.1764705882em;margin-right:1.1764705882em;padding-left:1.1764705882em;position:-webkit-sticky;position:sticky;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;z-index:3}.highlight code a[id]{position:absolute;visibility:hidden}.highlight code[data-md-copying] .hll{display:contents}.highlight code[data-md-copying] .md-annotation{display:none}.highlighttable{display:flow-root}.highlighttable :-webkit-any(tbody,td){display:block;padding:0}.highlighttable :-moz-any(tbody,td){display:block;padding:0}.highlighttable :is(tbody,td){display:block;padding:0}.highlighttable tr{display:flex}.highlighttable pre{margin:0}.highlighttable th.filename{flex-grow:1;padding:0;text-align:left}.highlighttable th.filename span.filename{margin-top:0}.highlighttable .linenos{background-color:var(--md-code-bg-color);border-bottom-left-radius:.1rem;border-top-left-radius:.1rem;font-size:.85em;padding:.7720588235em 0 .7720588235em 1.1764705882em;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.highlighttable .linenodiv{box-shadow:-.05rem 0 var(--md-default-fg-color--lightest) inset;padding-right:.5882352941em}.highlighttable .linenodiv pre{color:var(--md-default-fg-color--light);text-align:right}.highlighttable .code{flex:1;min-width:0}.linenodiv a{color:inherit}.md-typeset .highlighttable{direction:ltr;margin:1em 0}.md-typeset .highlighttable>tbody>tr>.code>div>pre>code{border-bottom-left-radius:0;border-top-left-radius:0}.md-typeset .highlight+.result{border:.05rem solid var(--md-code-bg-color);border-bottom-left-radius:.1rem;border-bottom-right-radius:.1rem;border-top-width:.1rem;margin-top:-1.125em;overflow:visible;padding:0 1em}.md-typeset .highlight+.result:after{clear:both;content:"";display:block}@media screen and (max-width:44.9375em){.md-content__inner>.highlight{margin:1em -.8rem}.md-content__inner>.highlight>.filename,.md-content__inner>.highlight>.highlighttable>tbody>tr>.code>div>pre>code,.md-content__inner>.highlight>.highlighttable>tbody>tr>.filename span.filename,.md-content__inner>.highlight>.highlighttable>tbody>tr>.linenos,.md-content__inner>.highlight>pre>code{border-radius:0}.md-content__inner>.highlight+.result{border-left-width:0;border-radius:0;border-right-width:0;margin-left:-.8rem;margin-right:-.8rem}}.md-typeset .keys kbd:-webkit-any(:before,:after){-moz-osx-font-smoothing:initial;-webkit-font-smoothing:initial;color:inherit;margin:0;position:relative}.md-typeset .keys kbd:-moz-any(:before,:after){-moz-osx-font-smoothing:initial;-webkit-font-smoothing:initial;color:inherit;margin:0;position:relative}.md-typeset .keys kbd:is(:before,:after){-moz-osx-font-smoothing:initial;-webkit-font-smoothing:initial;color:inherit;margin:0;position:relative}.md-typeset .keys span{color:var(--md-default-fg-color--light);padding:0 .2em}.md-typeset .keys .key-alt:before,.md-typeset .keys .key-left-alt:before,.md-typeset .keys .key-right-alt:before{content:"⎇";padding-right:.4em}.md-typeset .keys .key-command:before,.md-typeset .keys .key-left-command:before,.md-typeset .keys .key-right-command:before{content:"⌘";padding-right:.4em}.md-typeset .keys .key-control:before,.md-typeset .keys .key-left-control:before,.md-typeset .keys .key-right-control:before{content:"⌃";padding-right:.4em}.md-typeset .keys .key-left-meta:before,.md-typeset .keys .key-meta:before,.md-typeset .keys .key-right-meta:before{content:"◆";padding-right:.4em}.md-typeset .keys .key-left-option:before,.md-typeset .keys .key-option:before,.md-typeset .keys .key-right-option:before{content:"⌥";padding-right:.4em}.md-typeset .keys .key-left-shift:before,.md-typeset .keys .key-right-shift:before,.md-typeset .keys .key-shift:before{content:"⇧";padding-right:.4em}.md-typeset .keys .key-left-super:before,.md-typeset .keys .key-right-super:before,.md-typeset .keys .key-super:before{content:"❖";padding-right:.4em}.md-typeset .keys .key-left-windows:before,.md-typeset .keys .key-right-windows:before,.md-typeset .keys .key-windows:before{content:"⊞";padding-right:.4em}.md-typeset .keys .key-arrow-down:before{content:"↓";padding-right:.4em}.md-typeset .keys .key-arrow-left:before{content:"←";padding-right:.4em}.md-typeset .keys .key-arrow-right:before{content:"→";padding-right:.4em}.md-typeset .keys .key-arrow-up:before{content:"↑";padding-right:.4em}.md-typeset .keys .key-backspace:before{content:"⌫";padding-right:.4em}.md-typeset .keys .key-backtab:before{content:"⇤";padding-right:.4em}.md-typeset .keys .key-caps-lock:before{content:"⇪";padding-right:.4em}.md-typeset .keys .key-clear:before{content:"⌧";padding-right:.4em}.md-typeset .keys .key-context-menu:before{content:"☰";padding-right:.4em}.md-typeset .keys .key-delete:before{content:"⌦";padding-right:.4em}.md-typeset .keys .key-eject:before{content:"⏏";padding-right:.4em}.md-typeset .keys .key-end:before{content:"⤓";padding-right:.4em}.md-typeset .keys .key-escape:before{content:"⎋";padding-right:.4em}.md-typeset .keys .key-home:before{content:"⤒";padding-right:.4em}.md-typeset .keys .key-insert:before{content:"⎀";padding-right:.4em}.md-typeset .keys .key-page-down:before{content:"⇟";padding-right:.4em}.md-typeset .keys .key-page-up:before{content:"⇞";padding-right:.4em}.md-typeset .keys .key-print-screen:before{content:"⎙";padding-right:.4em}.md-typeset .keys .key-tab:after{content:"⇥";padding-left:.4em}.md-typeset .keys .key-num-enter:after{content:"⌤";padding-left:.4em}.md-typeset .keys .key-enter:after{content:"⏎";padding-left:.4em}.md-typeset .tabbed-set{border-radius:.1rem;display:flex;flex-flow:column wrap;margin:1em 0;position:relative}.md-typeset .tabbed-set>input{height:0;opacity:0;position:absolute;width:0}.md-typeset .tabbed-set>input:target{--md-scroll-offset:0.625em}.md-typeset .tabbed-labels{-ms-overflow-style:none;box-shadow:0 -.05rem var(--md-default-fg-color--lightest) inset;display:flex;max-width:100%;overflow:auto;-ms-scroll-snap-type:x proximity;scroll-snap-type:x proximity;scrollbar-width:none}@media print{.md-typeset .tabbed-labels{display:contents}}@media screen{.js .md-typeset .tabbed-labels{position:relative}.js .md-typeset .tabbed-labels:before{background:var(--md-accent-fg-color);bottom:0;content:"";display:block;height:2px;left:0;position:absolute;transform:translateX(var(--md-indicator-x));transition:width 225ms,transform .25s;transition-timing-function:cubic-bezier(.4,0,.2,1);width:var(--md-indicator-width)}}.md-typeset .tabbed-labels::-webkit-scrollbar{display:none}.md-typeset .tabbed-labels>label{border-bottom:.1rem solid transparent;border-radius:.1rem .1rem 0 0;color:var(--md-default-fg-color--light);cursor:pointer;flex-shrink:0;font-size:.64rem;font-weight:700;padding:.78125em 1.25em .625em;scroll-snap-align:start;transition:background-color .25s,color .25s;white-space:nowrap;width:auto}@media print{.md-typeset .tabbed-labels>label:first-child{order:1}.md-typeset .tabbed-labels>label:nth-child(2){order:2}.md-typeset .tabbed-labels>label:nth-child(3){order:3}.md-typeset .tabbed-labels>label:nth-child(4){order:4}.md-typeset .tabbed-labels>label:nth-child(5){order:5}.md-typeset .tabbed-labels>label:nth-child(6){order:6}.md-typeset .tabbed-labels>label:nth-child(7){order:7}.md-typeset .tabbed-labels>label:nth-child(8){order:8}.md-typeset .tabbed-labels>label:nth-child(9){order:9}.md-typeset .tabbed-labels>label:nth-child(10){order:10}.md-typeset .tabbed-labels>label:nth-child(11){order:11}.md-typeset .tabbed-labels>label:nth-child(12){order:12}.md-typeset .tabbed-labels>label:nth-child(13){order:13}.md-typeset .tabbed-labels>label:nth-child(14){order:14}.md-typeset .tabbed-labels>label:nth-child(15){order:15}.md-typeset .tabbed-labels>label:nth-child(16){order:16}.md-typeset .tabbed-labels>label:nth-child(17){order:17}.md-typeset .tabbed-labels>label:nth-child(18){order:18}.md-typeset .tabbed-labels>label:nth-child(19){order:19}.md-typeset .tabbed-labels>label:nth-child(20){order:20}}.md-typeset .tabbed-labels>label:hover{color:var(--md-accent-fg-color)}.md-typeset .tabbed-content{width:100%}@media print{.md-typeset .tabbed-content{display:contents}}.md-typeset .tabbed-block{display:none}@media print{.md-typeset .tabbed-block{display:block}.md-typeset .tabbed-block:first-child{order:1}.md-typeset .tabbed-block:nth-child(2){order:2}.md-typeset .tabbed-block:nth-child(3){order:3}.md-typeset .tabbed-block:nth-child(4){order:4}.md-typeset .tabbed-block:nth-child(5){order:5}.md-typeset .tabbed-block:nth-child(6){order:6}.md-typeset .tabbed-block:nth-child(7){order:7}.md-typeset .tabbed-block:nth-child(8){order:8}.md-typeset .tabbed-block:nth-child(9){order:9}.md-typeset .tabbed-block:nth-child(10){order:10}.md-typeset .tabbed-block:nth-child(11){order:11}.md-typeset .tabbed-block:nth-child(12){order:12}.md-typeset .tabbed-block:nth-child(13){order:13}.md-typeset .tabbed-block:nth-child(14){order:14}.md-typeset .tabbed-block:nth-child(15){order:15}.md-typeset .tabbed-block:nth-child(16){order:16}.md-typeset .tabbed-block:nth-child(17){order:17}.md-typeset .tabbed-block:nth-child(18){order:18}.md-typeset .tabbed-block:nth-child(19){order:19}.md-typeset .tabbed-block:nth-child(20){order:20}}.md-typeset .tabbed-block>.highlight:first-child>pre,.md-typeset .tabbed-block>pre:first-child{margin:0}.md-typeset .tabbed-block>.highlight:first-child>pre>code,.md-typeset .tabbed-block>pre:first-child>code{border-top-left-radius:0;border-top-right-radius:0}.md-typeset .tabbed-block>.highlight:first-child>.filename{border-top-left-radius:0;border-top-right-radius:0;margin:0}.md-typeset .tabbed-block>.highlight:first-child>.highlighttable{margin:0}.md-typeset .tabbed-block>.highlight:first-child>.highlighttable>tbody>tr>.filename span.filename,.md-typeset .tabbed-block>.highlight:first-child>.highlighttable>tbody>tr>.linenos{border-top-left-radius:0;border-top-right-radius:0;margin:0}.md-typeset .tabbed-block>.highlight:first-child>.highlighttable>tbody>tr>.code>div>pre>code{border-top-left-radius:0;border-top-right-radius:0}.md-typeset .tabbed-block>.highlight:first-child+.result{margin-top:-.125em}.md-typeset .tabbed-block>.tabbed-set{margin:0}@media screen and (max-width:44.9375em){[dir=ltr] .md-content__inner>.tabbed-set .tabbed-labels{padding-left:.8rem}[dir=rtl] .md-content__inner>.tabbed-set .tabbed-labels{padding-right:.8rem}.md-content__inner>.tabbed-set .tabbed-labels{margin:0 -.8rem;max-width:100vw;scroll-padding-inline-start:.8rem}[dir=ltr] .md-content__inner>.tabbed-set .tabbed-labels:after{padding-right:.8rem}[dir=rtl] .md-content__inner>.tabbed-set .tabbed-labels:after{padding-left:.8rem}.md-content__inner>.tabbed-set .tabbed-labels:after{content:""}}@media screen{.md-typeset .tabbed-set>input:first-child:checked~.tabbed-labels>:first-child,.md-typeset .tabbed-set>input:nth-child(10):checked~.tabbed-labels>:nth-child(10),.md-typeset .tabbed-set>input:nth-child(11):checked~.tabbed-labels>:nth-child(11),.md-typeset .tabbed-set>input:nth-child(12):checked~.tabbed-labels>:nth-child(12),.md-typeset .tabbed-set>input:nth-child(13):checked~.tabbed-labels>:nth-child(13),.md-typeset .tabbed-set>input:nth-child(14):checked~.tabbed-labels>:nth-child(14),.md-typeset .tabbed-set>input:nth-child(15):checked~.tabbed-labels>:nth-child(15),.md-typeset .tabbed-set>input:nth-child(16):checked~.tabbed-labels>:nth-child(16),.md-typeset .tabbed-set>input:nth-child(17):checked~.tabbed-labels>:nth-child(17),.md-typeset .tabbed-set>input:nth-child(18):checked~.tabbed-labels>:nth-child(18),.md-typeset .tabbed-set>input:nth-child(19):checked~.tabbed-labels>:nth-child(19),.md-typeset .tabbed-set>input:nth-child(2):checked~.tabbed-labels>:nth-child(2),.md-typeset .tabbed-set>input:nth-child(20):checked~.tabbed-labels>:nth-child(20),.md-typeset .tabbed-set>input:nth-child(3):checked~.tabbed-labels>:nth-child(3),.md-typeset .tabbed-set>input:nth-child(4):checked~.tabbed-labels>:nth-child(4),.md-typeset .tabbed-set>input:nth-child(5):checked~.tabbed-labels>:nth-child(5),.md-typeset .tabbed-set>input:nth-child(6):checked~.tabbed-labels>:nth-child(6),.md-typeset .tabbed-set>input:nth-child(7):checked~.tabbed-labels>:nth-child(7),.md-typeset .tabbed-set>input:nth-child(8):checked~.tabbed-labels>:nth-child(8),.md-typeset .tabbed-set>input:nth-child(9):checked~.tabbed-labels>:nth-child(9){color:var(--md-accent-fg-color)}.md-typeset .no-js .tabbed-set>input:first-child:checked~.tabbed-labels>:first-child,.md-typeset .no-js .tabbed-set>input:nth-child(10):checked~.tabbed-labels>:nth-child(10),.md-typeset .no-js .tabbed-set>input:nth-child(11):checked~.tabbed-labels>:nth-child(11),.md-typeset .no-js .tabbed-set>input:nth-child(12):checked~.tabbed-labels>:nth-child(12),.md-typeset .no-js .tabbed-set>input:nth-child(13):checked~.tabbed-labels>:nth-child(13),.md-typeset .no-js .tabbed-set>input:nth-child(14):checked~.tabbed-labels>:nth-child(14),.md-typeset .no-js .tabbed-set>input:nth-child(15):checked~.tabbed-labels>:nth-child(15),.md-typeset .no-js .tabbed-set>input:nth-child(16):checked~.tabbed-labels>:nth-child(16),.md-typeset .no-js .tabbed-set>input:nth-child(17):checked~.tabbed-labels>:nth-child(17),.md-typeset .no-js .tabbed-set>input:nth-child(18):checked~.tabbed-labels>:nth-child(18),.md-typeset .no-js .tabbed-set>input:nth-child(19):checked~.tabbed-labels>:nth-child(19),.md-typeset .no-js .tabbed-set>input:nth-child(2):checked~.tabbed-labels>:nth-child(2),.md-typeset .no-js .tabbed-set>input:nth-child(20):checked~.tabbed-labels>:nth-child(20),.md-typeset .no-js .tabbed-set>input:nth-child(3):checked~.tabbed-labels>:nth-child(3),.md-typeset .no-js .tabbed-set>input:nth-child(4):checked~.tabbed-labels>:nth-child(4),.md-typeset .no-js .tabbed-set>input:nth-child(5):checked~.tabbed-labels>:nth-child(5),.md-typeset .no-js .tabbed-set>input:nth-child(6):checked~.tabbed-labels>:nth-child(6),.md-typeset .no-js .tabbed-set>input:nth-child(7):checked~.tabbed-labels>:nth-child(7),.md-typeset .no-js .tabbed-set>input:nth-child(8):checked~.tabbed-labels>:nth-child(8),.md-typeset .no-js .tabbed-set>input:nth-child(9):checked~.tabbed-labels>:nth-child(9),.no-js .md-typeset .tabbed-set>input:first-child:checked~.tabbed-labels>:first-child,.no-js .md-typeset .tabbed-set>input:nth-child(10):checked~.tabbed-labels>:nth-child(10),.no-js .md-typeset .tabbed-set>input:nth-child(11):checked~.tabbed-labels>:nth-child(11),.no-js .md-typeset .tabbed-set>input:nth-child(12):checked~.tabbed-labels>:nth-child(12),.no-js .md-typeset .tabbed-set>input:nth-child(13):checked~.tabbed-labels>:nth-child(13),.no-js .md-typeset .tabbed-set>input:nth-child(14):checked~.tabbed-labels>:nth-child(14),.no-js .md-typeset .tabbed-set>input:nth-child(15):checked~.tabbed-labels>:nth-child(15),.no-js .md-typeset .tabbed-set>input:nth-child(16):checked~.tabbed-labels>:nth-child(16),.no-js .md-typeset .tabbed-set>input:nth-child(17):checked~.tabbed-labels>:nth-child(17),.no-js .md-typeset .tabbed-set>input:nth-child(18):checked~.tabbed-labels>:nth-child(18),.no-js .md-typeset .tabbed-set>input:nth-child(19):checked~.tabbed-labels>:nth-child(19),.no-js .md-typeset .tabbed-set>input:nth-child(2):checked~.tabbed-labels>:nth-child(2),.no-js .md-typeset .tabbed-set>input:nth-child(20):checked~.tabbed-labels>:nth-child(20),.no-js .md-typeset .tabbed-set>input:nth-child(3):checked~.tabbed-labels>:nth-child(3),.no-js .md-typeset .tabbed-set>input:nth-child(4):checked~.tabbed-labels>:nth-child(4),.no-js .md-typeset .tabbed-set>input:nth-child(5):checked~.tabbed-labels>:nth-child(5),.no-js .md-typeset .tabbed-set>input:nth-child(6):checked~.tabbed-labels>:nth-child(6),.no-js .md-typeset .tabbed-set>input:nth-child(7):checked~.tabbed-labels>:nth-child(7),.no-js .md-typeset .tabbed-set>input:nth-child(8):checked~.tabbed-labels>:nth-child(8),.no-js .md-typeset .tabbed-set>input:nth-child(9):checked~.tabbed-labels>:nth-child(9){border-color:var(--md-accent-fg-color)}}.md-typeset .tabbed-set>input:first-child.focus-visible~.tabbed-labels>:first-child,.md-typeset .tabbed-set>input:nth-child(10).focus-visible~.tabbed-labels>:nth-child(10),.md-typeset .tabbed-set>input:nth-child(11).focus-visible~.tabbed-labels>:nth-child(11),.md-typeset .tabbed-set>input:nth-child(12).focus-visible~.tabbed-labels>:nth-child(12),.md-typeset .tabbed-set>input:nth-child(13).focus-visible~.tabbed-labels>:nth-child(13),.md-typeset .tabbed-set>input:nth-child(14).focus-visible~.tabbed-labels>:nth-child(14),.md-typeset .tabbed-set>input:nth-child(15).focus-visible~.tabbed-labels>:nth-child(15),.md-typeset .tabbed-set>input:nth-child(16).focus-visible~.tabbed-labels>:nth-child(16),.md-typeset .tabbed-set>input:nth-child(17).focus-visible~.tabbed-labels>:nth-child(17),.md-typeset .tabbed-set>input:nth-child(18).focus-visible~.tabbed-labels>:nth-child(18),.md-typeset .tabbed-set>input:nth-child(19).focus-visible~.tabbed-labels>:nth-child(19),.md-typeset .tabbed-set>input:nth-child(2).focus-visible~.tabbed-labels>:nth-child(2),.md-typeset .tabbed-set>input:nth-child(20).focus-visible~.tabbed-labels>:nth-child(20),.md-typeset .tabbed-set>input:nth-child(3).focus-visible~.tabbed-labels>:nth-child(3),.md-typeset .tabbed-set>input:nth-child(4).focus-visible~.tabbed-labels>:nth-child(4),.md-typeset .tabbed-set>input:nth-child(5).focus-visible~.tabbed-labels>:nth-child(5),.md-typeset .tabbed-set>input:nth-child(6).focus-visible~.tabbed-labels>:nth-child(6),.md-typeset .tabbed-set>input:nth-child(7).focus-visible~.tabbed-labels>:nth-child(7),.md-typeset .tabbed-set>input:nth-child(8).focus-visible~.tabbed-labels>:nth-child(8),.md-typeset .tabbed-set>input:nth-child(9).focus-visible~.tabbed-labels>:nth-child(9){background-color:var(--md-accent-fg-color--transparent)}.md-typeset .tabbed-set>input:first-child:checked~.tabbed-content>:first-child,.md-typeset .tabbed-set>input:nth-child(10):checked~.tabbed-content>:nth-child(10),.md-typeset .tabbed-set>input:nth-child(11):checked~.tabbed-content>:nth-child(11),.md-typeset .tabbed-set>input:nth-child(12):checked~.tabbed-content>:nth-child(12),.md-typeset .tabbed-set>input:nth-child(13):checked~.tabbed-content>:nth-child(13),.md-typeset .tabbed-set>input:nth-child(14):checked~.tabbed-content>:nth-child(14),.md-typeset .tabbed-set>input:nth-child(15):checked~.tabbed-content>:nth-child(15),.md-typeset .tabbed-set>input:nth-child(16):checked~.tabbed-content>:nth-child(16),.md-typeset .tabbed-set>input:nth-child(17):checked~.tabbed-content>:nth-child(17),.md-typeset .tabbed-set>input:nth-child(18):checked~.tabbed-content>:nth-child(18),.md-typeset .tabbed-set>input:nth-child(19):checked~.tabbed-content>:nth-child(19),.md-typeset .tabbed-set>input:nth-child(2):checked~.tabbed-content>:nth-child(2),.md-typeset .tabbed-set>input:nth-child(20):checked~.tabbed-content>:nth-child(20),.md-typeset .tabbed-set>input:nth-child(3):checked~.tabbed-content>:nth-child(3),.md-typeset .tabbed-set>input:nth-child(4):checked~.tabbed-content>:nth-child(4),.md-typeset .tabbed-set>input:nth-child(5):checked~.tabbed-content>:nth-child(5),.md-typeset .tabbed-set>input:nth-child(6):checked~.tabbed-content>:nth-child(6),.md-typeset .tabbed-set>input:nth-child(7):checked~.tabbed-content>:nth-child(7),.md-typeset .tabbed-set>input:nth-child(8):checked~.tabbed-content>:nth-child(8),.md-typeset .tabbed-set>input:nth-child(9):checked~.tabbed-content>:nth-child(9){display:block}:root{--md-tasklist-icon:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path fill-rule="evenodd" d="M1 12C1 5.925 5.925 1 12 1s11 4.925 11 11-4.925 11-11 11S1 18.075 1 12zm16.28-2.72a.75.75 0 0 0-1.06-1.06l-5.97 5.97-2.47-2.47a.75.75 0 0 0-1.06 1.06l3 3a.75.75 0 0 0 1.06 0l6.5-6.5z"/></svg>');--md-tasklist-icon--checked:url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path fill-rule="evenodd" d="M1 12C1 5.925 5.925 1 12 1s11 4.925 11 11-4.925 11-11 11S1 18.075 1 12zm16.28-2.72a.75.75 0 0 0-1.06-1.06l-5.97 5.97-2.47-2.47a.75.75 0 0 0-1.06 1.06l3 3a.75.75 0 0 0 1.06 0l6.5-6.5z"/></svg>')}.md-typeset .task-list-item{list-style-type:none;position:relative}[dir=ltr] .md-typeset .task-list-item [type=checkbox]{left:-2em}[dir=rtl] .md-typeset .task-list-item [type=checkbox]{right:-2em}.md-typeset .task-list-item [type=checkbox]{position:absolute;top:.45em}.md-typeset .task-list-control [type=checkbox]{opacity:0;z-index:-1}[dir=ltr] .md-typeset .task-list-indicator:before{left:-1.5em}[dir=rtl] .md-typeset .task-list-indicator:before{right:-1.5em}.md-typeset .task-list-indicator:before{background-color:var(--md-default-fg-color--lightest);content:"";height:1.25em;-webkit-mask-image:var(--md-tasklist-icon);mask-image:var(--md-tasklist-icon);-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-size:contain;mask-size:contain;position:absolute;top:.15em;width:1.25em}.md-typeset [type=checkbox]:checked+.task-list-indicator:before{background-color:#00e676;-webkit-mask-image:var(--md-tasklist-icon--checked);mask-image:var(--md-tasklist-icon--checked)}:root>*{--md-mermaid-font-family:var(--md-text-font-family),sans-serif;--md-mermaid-edge-color:var(--md-code-fg-color);--md-mermaid-node-bg-color:var(--md-accent-fg-color--transparent);--md-mermaid-node-fg-color:var(--md-accent-fg-color);--md-mermaid-label-bg-color:var(--md-default-bg-color);--md-mermaid-label-fg-color:var(--md-code-fg-color)}.mermaid{line-height:normal;margin:1em 0}@media screen and (min-width:45em){[dir=ltr] .md-typeset .inline{margin-right:.8rem}[dir=rtl] .md-typeset .inline{margin-left:.8rem}.md-typeset .inline{float:left;margin-bottom:.8rem;margin-top:0;width:11.7rem}[dir=rtl] .md-typeset .inline{float:right}[dir=ltr] .md-typeset .inline.end{margin-left:.8rem;margin-right:0}[dir=rtl] .md-typeset .inline.end{margin-left:0;margin-right:.8rem}.md-typeset .inline.end{float:right}[dir=rtl] .md-typeset .inline.end{float:left}}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/main.c382b1dc.min.css.map b/7.3/assets/stylesheets/main.c382b1dc.min.css.map
deleted file mode 100755
index 7f0dc97b26..0000000000
--- a/7.3/assets/stylesheets/main.c382b1dc.min.css.map
+++ /dev/null
@@ -1 +0,0 @@
-{"version":3,"sources":["src/assets/stylesheets/main/extensions/pymdownx/_keys.scss","../../../src/assets/stylesheets/main.scss","src/assets/stylesheets/main/_resets.scss","src/assets/stylesheets/main/_colors.scss","src/assets/stylesheets/main/_icons.scss","src/assets/stylesheets/main/_typeset.scss","src/assets/stylesheets/utilities/_break.scss","src/assets/stylesheets/main/layout/_banner.scss","src/assets/stylesheets/main/layout/_base.scss","src/assets/stylesheets/main/layout/_clipboard.scss","src/assets/stylesheets/main/layout/_content.scss","src/assets/stylesheets/main/layout/_dialog.scss","src/assets/stylesheets/main/layout/_footer.scss","src/assets/stylesheets/main/layout/_form.scss","src/assets/stylesheets/main/layout/_header.scss","src/assets/stylesheets/main/layout/_nav.scss","src/assets/stylesheets/main/layout/_search.scss","src/assets/stylesheets/main/layout/_select.scss","src/assets/stylesheets/main/layout/_sidebar.scss","src/assets/stylesheets/main/layout/_source.scss","src/assets/stylesheets/main/layout/_tabs.scss","src/assets/stylesheets/main/layout/_tag.scss","src/assets/stylesheets/main/layout/_tooltip.scss","src/assets/stylesheets/main/layout/_top.scss","src/assets/stylesheets/main/layout/_version.scss","src/assets/stylesheets/main/extensions/markdown/_admonition.scss","node_modules/material-design-color/material-color.scss","src/assets/stylesheets/main/extensions/markdown/_footnotes.scss","src/assets/stylesheets/main/extensions/markdown/_toc.scss","src/assets/stylesheets/main/extensions/pymdownx/_arithmatex.scss","src/assets/stylesheets/main/extensions/pymdownx/_critic.scss","src/assets/stylesheets/main/extensions/pymdownx/_details.scss","src/assets/stylesheets/main/extensions/pymdownx/_emoji.scss","src/assets/stylesheets/main/extensions/pymdownx/_highlight.scss","src/assets/stylesheets/main/extensions/pymdownx/_tabbed.scss","src/assets/stylesheets/main/extensions/pymdownx/_tasklist.scss","src/assets/stylesheets/main/integrations/_mermaid.scss","src/assets/stylesheets/main/_modifiers.scss"],"names":[],"mappings":"AAgGM,gBC0vGN,CC9zGA,KAEE,6BAAA,CAAA,0BAAA,CAAA,yBAAA,CAAA,qBAAA,CADA,qBDzBF,CC8BA,iBAGE,kBD3BF,CC8BE,gCANF,iBAOI,yBDzBF,CACF,CC6BA,KACE,QD1BF,CC8BA,qBAIE,uCD3BF,CC+BA,EACE,aAAA,CACA,oBD5BF,CCgCA,GAME,QAAA,CAJA,kBAAA,CADA,aAAA,CAEA,aAAA,CAEA,gBAAA,CADA,SD3BF,CCiCA,MACE,aD9BF,CCkCA,QAEE,eD/BF,CCmCA,IACE,iBDhCF,CCoCA,MACE,uBAAA,CACA,gBDjCF,CCqCA,MAEE,eAAA,CACA,kBDlCF,CCsCA,OAKE,sBAAA,CACA,QAAA,CAFA,mBAAA,CADA,iBAAA,CAFA,QAAA,CACA,SD/BF,CCuCA,MACE,QAAA,CACA,YDpCF,CErDA,MAGE,qCAAA,CACA,4CAAA,CACA,8CAAA,CACA,+CAAA,CACA,0BAAA,CACA,+CAAA,CACA,iDAAA,CACA,mDAAA,CAGA,6BAAA,CACA,oCAAA,CACA,mCAAA,CACA,0BAAA,CACA,+CAAA,CAGA,4BAAA,CACA,qDAAA,CACA,yBAAA,CACA,8CAAA,CA0DA,yEAAA,CAKA,yEAAA,CAKA,yEFTF,CExDE,QAGE,0BAAA,CACA,0BAAA,CAGA,qCAAA,CACA,iCAAA,CACA,kCAAA,CACA,mCAAA,CACA,mCAAA,CACA,kCAAA,CACA,iCAAA,CACA,+CAAA,CACA,6DAAA,CACA,gEAAA,CACA,4DAAA,CACA,4DAAA,CACA,6DAAA,CAGA,6CAAA,CAGA,+CAAA,CAGA,0CAAA,CAGA,0CAAA,CACA,2CAAA,CAGA,8BAAA,CACA,kCAAA,CACA,qCAAA,CAGA,wCAAA,CAGA,mDAAA,CACA,mDAAA,CAGA,yBAAA,CACA,8CAAA,CACA,gDAAA,CACA,oCAAA,CACA,0CFsCJ,CGhHE,aAIE,iBAAA,CAHA,aAAA,CAEA,aAAA,CADA,YHqHJ,CI1HA,KACE,kCAAA,CACA,iCAAA,CAGA,uGAAA,CAKA,mFJ2HF,CIrHA,WAGE,mCAAA,CACA,sCJwHF,CIpHA,wBANE,6BJkIF,CI5HA,aAIE,4BAAA,CACA,sCJuHF,CI/GA,MACE,0NAAA,CACA,mNAAA,CACA,oNJkHF,CI3GA,YAGE,gCAAA,CAAA,kBAAA,CAFA,eAAA,CACA,eJ+GF,CI1GE,aAPF,YAQI,gBJ6GF,CACF,CI1GE,uGAME,iBAAA,CAAA,cJ4GJ,CIxGE,eAEE,uCAAA,CAEA,aAAA,CACA,eAAA,CAJA,iBJ+GJ,CItGE,8BAPE,eAAA,CAGA,qBJiHJ,CI7GE,eAGE,kBAAA,CACA,eAAA,CAHA,oBJ4GJ,CIpGE,eAGE,gBAAA,CADA,eAAA,CAGA,qBAAA,CADA,eAAA,CAHA,mBJ0GJ,CIlGE,kBACE,eJoGJ,CIhGE,eAEE,eAAA,CACA,qBAAA,CAFA,YJoGJ,CI9FE,8BAGE,uCAAA,CAEA,cAAA,CADA,eAAA,CAEA,qBAAA,CAJA,eJoGJ,CI5FE,eACE,wBJ8FJ,CI1FE,eAGE,+DAAA,CAFA,iBAAA,CACA,cJ6FJ,CIxFE,cACE,+BAAA,CACA,qBJ0FJ,CIvFI,mCAEE,sBJwFN,CIpFI,wCAEE,+BJqFN,CIlFM,kDACE,uDJoFR,CI/EI,mBACE,kBAAA,CACA,iCJiFN,CI7EI,4BACE,uCAAA,CACA,oBJ+EN,CI1EE,iDAGE,6BAAA,CACA,aJ4EJ,CIzEI,aAPF,iDAQI,oBJ8EJ,CACF,CI1EE,iBAIE,wCAAA,CACA,mBAAA,CACA,kCAAA,CAAA,0BAAA,CAJA,eAAA,CADA,uBAAA,CAEA,qBJ+EJ,CIzEI,qCAEE,uCAAA,CADA,YJ4EN,CItEE,gBAEE,iBAAA,CACA,eAAA,CAFA,iBJ0EJ,CIrEI,qBAQE,kCAAA,CAAA,0BAAA,CADA,eAAA,CANA,aAAA,CACA,QAAA,CAIA,uCAAA,CAFA,aAAA,CADA,oCAAA,CAQA,+DAAA,CADA,oBAAA,CADA,iBAAA,CAJA,iBJ6EN,CIpEM,2BACE,qDJsER,CIlEM,wCAEE,YAAA,CADA,WJqER,CIhEM,8CACE,oDJkER,CI/DQ,oDACE,0CJiEV,CI1DE,gBAOE,4CAAA,CACA,mBAAA,CACA,mKACE,CAPF,gCAAA,CAFA,oBAAA,CAGA,eAAA,CAFA,uBAAA,CAGA,uBAAA,CACA,qBJ+DJ,CIrDE,iBAGE,6CAAA,CACA,kCAAA,CAAA,0BAAA,CAHA,aAAA,CACA,qBJyDJ,CInDE,iBAEE,6DAAA,CACA,WAAA,CAFA,oBJuDJ,CIlDI,oBANF,iBAOI,iBJqDJ,CIlDI,yDAWE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CAKA,mBAAA,CAXA,oBAAA,CAOA,eAAA,CAHA,cAAA,CADA,aAAA,CADA,6BAAA,CAAA,qBAAA,CAGA,mBAAA,CAPA,iBAAA,CAGA,UJ8DN,CIlEI,sDAWE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CAKA,mBAAA,CAXA,oBAAA,CAOA,eAAA,CAHA,cAAA,CADA,aAAA,CADA,0BAAA,CAAA,qBAAA,CAGA,mBAAA,CAPA,iBAAA,CAGA,UJ8DN,CIlEI,mEAEE,MJgEN,CIlEI,gEAEE,MJgEN,CIlEI,0DAEE,MJgEN,CIlEI,mEAEE,OJgEN,CIlEI,gEAEE,OJgEN,CIlEI,0DAEE,OJgEN,CIlEI,gDAWE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CAKA,mBAAA,CAXA,oBAAA,CAOA,eAAA,CAHA,cAAA,CADA,aAAA,CADA,6BAAA,CAAA,0BAAA,CAAA,qBAAA,CAGA,mBAAA,CAPA,iBAAA,CAGA,UJ8DN,CACF,CI/CE,kBACE,WJiDJ,CI7CE,oDAEE,qBJ+CJ,CIjDE,oDAEE,sBJ+CJ,CI3CE,iCACE,kBJgDJ,CIjDE,iCACE,mBJgDJ,CIjDE,iCAIE,2DJ6CJ,CIjDE,iCAIE,4DJ6CJ,CIjDE,uBAGE,uCAAA,CADA,aAAA,CAAA,cJ+CJ,CIzCE,eACE,oBJ2CJ,CIvCE,kDAEE,kBJ0CJ,CI5CE,kDAEE,mBJ0CJ,CI5CE,8BAGE,SJyCJ,CItCI,0DACE,iBJyCN,CIrCI,oCACE,2BJwCN,CIrCM,0CACE,2BJwCR,CInCI,wDAEE,kBJsCN,CIxCI,wDAEE,mBJsCN,CIxCI,oCACE,kBJuCN,CInCM,kGAEE,aJuCR,CInCM,0DACE,eJsCR,CIlCM,4EACE,kBAAA,CAAA,eJsCR,CIvCM,sEACE,kBAAA,CAAA,eJsCR,CIvCM,gGAEE,kBJqCR,CIvCM,0FAEE,kBJqCR,CIvCM,8EAEE,kBJqCR,CIvCM,gGAEE,mBJqCR,CIvCM,0FAEE,mBJqCR,CIvCM,8EAEE,mBJqCR,CIvCM,0DACE,kBAAA,CAAA,eJsCR,CI/BE,yBAEE,mBJiCJ,CInCE,yBAEE,oBJiCJ,CInCE,eACE,mBAAA,CAAA,cJkCJ,CI7BE,gCAGE,WAAA,CADA,cJgCJ,CI5BI,wDAEE,oBJ+BN,CI3BI,0DAEE,oBJ8BN,CI1BI,oEACE,YJ6BN,CIxBE,8EAEE,YJ0BJ,CItBE,mBACE,iBAAA,CAGA,eAAA,CADA,cAAA,CAEA,iBAAA,CAHA,yBAAA,CAAA,sBAAA,CAAA,iBJ2BJ,CIrBI,uBACE,aJuBN,CIlBE,uBAGE,iBAAA,CADA,eAAA,CADA,eJsBJ,CIhBE,mBACE,cJkBJ,CIdE,+BAKE,2CAAA,CACA,iDAAA,CACA,mBAAA,CANA,oBAAA,CAGA,gBAAA,CAFA,cAAA,CACA,aAAA,CAKA,iBJgBJ,CIbI,aAXF,+BAYI,aJgBJ,CACF,CIXI,iCACE,gBJaN,CINM,gEACE,YJQR,CITM,6DACE,YJQR,CITM,uDACE,YJQR,CIJM,+DACE,eJMR,CIPM,4DACE,eJMR,CIPM,sDACE,eJMR,CIDI,gEACE,eJGN,CIJI,6DACE,eJGN,CIJI,uDACE,eJGN,CIAM,0EACE,gBJER,CIHM,uEACE,gBJER,CIHM,iEACE,gBJER,CIGI,kCAGE,eAAA,CAFA,cAAA,CACA,sBAAA,CAEA,kBJDN,CIIM,oCACE,aJFR,CIOI,kCAGE,qDAAA,CAFA,sBAAA,CACA,kBJJN,CISI,wCACE,iCJPN,CIUM,8CACE,iCAAA,CACA,sDJRR,CIaI,iCACE,iBJXN,CIgBE,wCACE,cJdJ,CIiBI,wDAIE,gBJTN,CIKI,wDAIE,iBJTN,CIKI,8CAUE,UAAA,CATA,oBAAA,CAEA,YAAA,CAGA,oDAAA,CAAA,4CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CACA,iCAAA,CAJA,0BAAA,CAHA,WJPN,CImBI,oDACE,oDJjBN,CIqBI,mEACE,kDAAA,CACA,yDAAA,CAAA,iDJnBN,CIuBI,oEACE,kDAAA,CACA,0DAAA,CAAA,kDJrBN,CI0BE,wBACE,iBAAA,CACA,eAAA,CACA,iBJxBJ,CI4BE,mBACE,oBAAA,CACA,kBAAA,CACA,eJ1BJ,CI6BI,aANF,mBAOI,aJ1BJ,CACF,CI6BI,8BACE,aAAA,CAEA,QAAA,CACA,eAAA,CAFA,UJzBN,CKjWI,wCDyYF,uBACE,iBJpCF,CIuCE,4BACE,eJrCJ,CACF,CMniBA,WAGE,0CAAA,CADA,+BAAA,CADA,aNuiBF,CMliBE,aANF,WAOI,YNqiBF,CACF,CMliBE,oBAEE,uCAAA,CADA,gCNqiBJ,CMhiBE,kBAGE,eAAA,CAFA,iBAAA,CACA,eNmiBJ,COtjBA,KASE,cAAA,CARA,WAAA,CACA,iBP0jBF,CKtZI,oCEtKJ,KAaI,gBPmjBF,CACF,CK3ZI,oCEtKJ,KAkBI,cPmjBF,CACF,CO9iBA,KASE,2CAAA,CAPA,YAAA,CACA,qBAAA,CAKA,eAAA,CAHA,eAAA,CAJA,iBAAA,CAGA,UPojBF,CO5iBE,aAZF,KAaI,aP+iBF,CACF,CK5ZI,wCEhJF,yBAII,cP4iBJ,CACF,COniBA,SAEE,gBAAA,CAAA,iBAAA,CADA,ePuiBF,COliBA,cACE,YAAA,CACA,qBAAA,CACA,WPqiBF,COliBE,aANF,cAOI,aPqiBF,CACF,COjiBA,SACE,WPoiBF,COjiBE,gBACE,YAAA,CACA,WAAA,CACA,iBPmiBJ,CO9hBA,aACE,eAAA,CAEA,sBAAA,CADA,kBPkiBF,COxhBA,WACE,YP2hBF,COthBA,WAGE,QAAA,CACA,SAAA,CAHA,iBAAA,CACA,OP2hBF,COthBE,uCACE,aPwhBJ,COphBE,+BAEE,uCAAA,CADA,kBPuhBJ,COjhBA,SASE,2CAAA,CACA,mBAAA,CAHA,gCAAA,CACA,gBAAA,CAHA,YAAA,CAQA,SAAA,CAFA,uCAAA,CALA,mBAAA,CALA,cAAA,CAWA,2BAAA,CARA,UP2hBF,CO/gBE,eAGE,SAAA,CADA,uBAAA,CAEA,oEACE,CAJF,UPohBJ,COtgBA,MACE,WPygBF,CQnqBA,MACE,+PRqqBF,CQ/pBA,cAQE,mBAAA,CADA,0CAAA,CAIA,cAAA,CALA,YAAA,CAGA,uCAAA,CACA,oBAAA,CATA,iBAAA,CAEA,UAAA,CADA,QAAA,CAUA,qBAAA,CAPA,WAAA,CADA,SR0qBF,CQ/pBE,aAfF,cAgBI,YRkqBF,CACF,CQ/pBE,kCAEE,uCAAA,CADA,YRkqBJ,CQ7pBE,qBACE,uCR+pBJ,CQ3pBE,yCACE,+BR6pBJ,CQ9pBE,sCACE,+BR6pBJ,CQ9pBE,gCACE,+BR6pBJ,CQxpBE,oBAKE,6BAAA,CAIA,UAAA,CARA,aAAA,CAEA,cAAA,CACA,aAAA,CAEA,2CAAA,CAAA,mCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CANA,aRiqBJ,CQtpBE,sBACE,cRwpBJ,CQrpBI,2BACE,2CRupBN,CQjpBI,sDAEE,uDAAA,CADA,+BRopBN,CQrpBI,mDAEE,uDAAA,CADA,+BRopBN,CQrpBI,6CAEE,uDAAA,CADA,+BRopBN,CSztBA,YACE,WAAA,CAIA,WTytBF,CSttBE,mBACE,qBAAA,CACA,iBTwtBJ,CK5jBI,sCItJE,4EACE,kBTqtBN,CSjtBI,0JACE,mBTmtBN,CSptBI,8EACE,kBTmtBN,CACF,CS9sBI,0BAGE,UAAA,CAFA,aAAA,CACA,YTitBN,CS5sBI,+BACE,eT8sBN,CSxsBE,8BAGE,iBT2sBJ,CS9sBE,8BAGE,kBT2sBJ,CS9sBE,oBACE,WAAA,CACA,cAAA,CAEA,ST0sBJ,CSvsBI,aAPF,oBAQI,YT0sBJ,CACF,CSvsBI,8BACE,UTysBN,CSrsBI,gCACE,yCTusBN,CSnsBI,wBACE,cAAA,CACA,kBTqsBN,CSlsBM,kCACE,oBTosBR,CU1wBA,qBAEE,WVwxBF,CU1xBA,qBAEE,UVwxBF,CU1xBA,WAOE,2CAAA,CACA,mBAAA,CALA,YAAA,CAMA,8BAAA,CAJA,iBAAA,CAMA,SAAA,CALA,mBAAA,CASA,mBAAA,CAdA,cAAA,CASA,0BAAA,CAEA,wCACE,CATF,SVsxBF,CUxwBE,aAlBF,WAmBI,YV2wBF,CACF,CUxwBE,+BAEE,SAAA,CAIA,mBAAA,CALA,uBAAA,CAEA,kEV2wBJ,CUpwBE,kBACE,gCAAA,CACA,eVswBJ,CWzyBA,WAEE,0CAAA,CADA,+BX6yBF,CWzyBE,aALF,WAMI,YX4yBF,CACF,CWzyBE,kBACE,YAAA,CACA,6BAAA,CAEA,aAAA,CADA,aX4yBJ,CWvyBE,iBACE,YAAA,CAKA,cAAA,CAIA,uCAAA,CADA,eAAA,CADA,oBAAA,CADA,kBAAA,CAIA,uBXqyBJ,CWlyBI,4CACE,UXoyBN,CWryBI,yCACE,UXoyBN,CWryBI,mCACE,UXoyBN,CWhyBI,+BACE,oBXkyBN,CK/oBI,wCMzII,yCACE,YX2xBR,CACF,CWtxBI,iCACE,gBXyxBN,CW1xBI,iCACE,iBXyxBN,CW1xBI,uBAEE,gBXwxBN,CWrxBM,iCACE,eXuxBR,CWjxBE,kBAEE,WAAA,CAGA,eAAA,CACA,kBAAA,CAHA,6BAAA,CACA,cAAA,CAHA,iBXwxBJ,CW/wBE,mBACE,YAAA,CACA,aXixBJ,CW7wBE,sBAKE,gBAAA,CAHA,MAAA,CACA,gBAAA,CAGA,UAAA,CAFA,cAAA,CAHA,iBAAA,CACA,OXmxBJ,CW1wBA,gBACE,gDX6wBF,CW1wBE,uBACE,YAAA,CACA,cAAA,CACA,6BAAA,CACA,aX4wBJ,CWxwBE,kCACE,sCX0wBJ,CWvwBI,6DACE,+BXywBN,CW1wBI,0DACE,+BXywBN,CW1wBI,oDACE,+BXywBN,CWjwBA,cAIE,wCAAA,CACA,gBAAA,CAHA,iBAAA,CACA,eAAA,CAFA,UXwwBF,CK1tBI,mCM/CJ,cASI,UXowBF,CACF,CWhwBE,yBACE,sCXkwBJ,CW3vBA,WACE,cAAA,CACA,qBX8vBF,CKvuBI,mCMzBJ,WAMI,eX8vBF,CACF,CW3vBE,iBACE,oBAAA,CAEA,aAAA,CACA,iBAAA,CAFA,YX+vBJ,CW1vBI,wBACE,eX4vBN,CWxvBI,qBAGE,iBAAA,CAFA,gBAAA,CACA,mBX2vBN,CY75BE,uBAKE,kBAAA,CACA,mBAAA,CAHA,gCAAA,CAIA,cAAA,CANA,oBAAA,CAGA,eAAA,CAFA,kBAAA,CAMA,gEZg6BJ,CY15BI,gCAEE,2CAAA,CACA,uCAAA,CAFA,gCZ85BN,CYx5BI,kDAEE,0CAAA,CACA,sCAAA,CAFA,+BZ45BN,CY75BI,+CAEE,0CAAA,CACA,sCAAA,CAFA,+BZ45BN,CY75BI,yCAEE,0CAAA,CACA,sCAAA,CAFA,+BZ45BN,CYr5BE,gCAKE,4BZ05BJ,CY/5BE,gEAME,6BZy5BJ,CY/5BE,gCAME,4BZy5BJ,CY/5BE,sBAIE,6DAAA,CAGA,8BAAA,CAJA,eAAA,CAFA,aAAA,CACA,eAAA,CAMA,sCZu5BJ,CYl5BI,iDACE,6CAAA,CACA,8BZo5BN,CYt5BI,8CACE,6CAAA,CACA,8BZo5BN,CYt5BI,wCACE,6CAAA,CACA,8BZo5BN,CYh5BI,+BACE,UZk5BN,Car8BA,WAME,2CAAA,CAGA,0DACE,CALF,gCAAA,CAFA,MAAA,CAFA,uBAAA,CAAA,eAAA,CAEA,OAAA,CADA,KAAA,CAEA,Sb28BF,Caj8BE,aAdF,WAeI,Ybo8BF,CACF,Caj8BE,iCACE,gEACE,CAEF,kEbi8BJ,Ca37BE,iCACE,2BAAA,CACA,iEb67BJ,Cav7BE,kBAEE,kBAAA,CADA,YAAA,CAEA,eby7BJ,Car7BE,mBAKE,kBAAA,CAGA,cAAA,CALA,YAAA,CAIA,uCAAA,CAHA,aAAA,CAHA,iBAAA,CAQA,uBAAA,CAHA,qBAAA,CAJA,Sb87BJ,Cap7BI,yBACE,Ubs7BN,Cal7BI,iCACE,oBbo7BN,Cah7BI,uCAEE,uCAAA,CADA,Ybm7BN,Ca96BI,2BACE,YAAA,CACA,abg7BN,CKl0BI,wCQhHA,2BAMI,Ybg7BN,CACF,Ca76BM,iDAIE,iBAAA,CAHA,aAAA,CAEA,aAAA,CADA,Ubi7BR,Can7BM,8CAIE,iBAAA,CAHA,aAAA,CAEA,aAAA,CADA,Ubi7BR,Can7BM,wCAIE,iBAAA,CAHA,aAAA,CAEA,aAAA,CADA,Ubi7BR,CKh2BI,mCQ1EA,iCAII,Yb06BN,CACF,Cav6BM,wCACE,Yby6BR,Car6BM,+CACE,oBbu6BR,CK32BI,sCQvDA,iCAII,Ybk6BN,CACF,Ca75BE,kBAEE,YAAA,CACA,cAAA,CAFA,iBAAA,CAGA,8Db+5BJ,Ca15BI,oCAGE,SAAA,CAIA,mBAAA,CALA,6BAAA,CAEA,8DACE,CAJF,Ubg6BN,Cav5BM,8CACE,8Bby5BR,Cap5BI,8BACE,ebs5BN,Caj5BE,4BAGE,kBbs5BJ,Caz5BE,4BAGE,iBbs5BJ,Caz5BE,4BAIE,gBbq5BJ,Caz5BE,4BAIE,iBbq5BJ,Caz5BE,kBACE,WAAA,CAIA,eAAA,CAHA,aAAA,CAIA,kBbm5BJ,Cah5BI,0DAGE,SAAA,CAIA,mBAAA,CALA,8BAAA,CAEA,8DACE,CAJF,Ubs5BN,Ca74BM,oEACE,6Bb+4BR,Ca34BM,4EAGE,SAAA,CAIA,mBAAA,CALA,uBAAA,CAEA,8DACE,CAJF,Sbi5BR,Cat4BI,uCAGE,WAAA,CAFA,iBAAA,CACA,Uby4BN,Can4BE,mBACE,YAAA,CACA,aAAA,CACA,cAAA,CAEA,+CACE,CAFF,kBbs4BJ,Cah4BI,8DACE,WAAA,CACA,SAAA,CACA,oCbk4BN,Ca33BE,mBACE,Yb63BJ,CKh7BI,mCQkDF,6BAQI,gBb63BJ,Car4BA,6BAQI,iBb63BJ,Car4BA,mBAKI,aAAA,CAEA,iBAAA,CADA,ab+3BJ,CACF,CKx7BI,sCQkDF,6BAaI,kBb63BJ,Ca14BA,6BAaI,mBb63BJ,CACF,CcnmCA,MACE,0MAAA,CACA,gMAAA,CACA,yNdsmCF,CchmCA,QACE,eAAA,CACA,edmmCF,CchmCE,eACE,aAAA,CAGA,eAAA,CADA,eAAA,CADA,eAAA,CAGA,sBdkmCJ,Cc/lCI,+BACE,YdimCN,Cc9lCM,mCAEE,WAAA,CADA,UdimCR,CczlCQ,6DAME,iBAAA,CALA,aAAA,CAGA,aAAA,CADA,cAAA,CAEA,kBAAA,CAHA,Ud+lCV,CcjmCQ,0DAME,iBAAA,CALA,aAAA,CAGA,aAAA,CADA,cAAA,CAEA,kBAAA,CAHA,Ud+lCV,CcjmCQ,oDAME,iBAAA,CALA,aAAA,CAGA,aAAA,CADA,cAAA,CAEA,kBAAA,CAHA,Ud+lCV,CcplCE,cAGE,eAAA,CAFA,QAAA,CACA,SdulCJ,CcllCE,cACE,edolCJ,CcjlCI,sCACE,edmlCN,CcplCI,sCACE,cdmlCN,Cc9kCE,cAEE,kBAAA,CAKA,cAAA,CANA,YAAA,CAEA,6BAAA,CACA,iBAAA,CACA,eAAA,CAIA,uBAAA,CAHA,sBAAA,CAEA,sBdilCJ,Cc7kCI,kCACE,uCd+kCN,Cc3kCI,oCACE,+Bd6kCN,CczkCI,0CACE,Ud2kCN,CcvkCI,yCACE,+BdykCN,Cc1kCI,sCACE,+BdykCN,Cc1kCI,gCACE,+BdykCN,CcrkCI,4BACE,uCAAA,CACA,oBdukCN,CcnkCI,0CACE,YdqkCN,CclkCM,yDAKE,6BAAA,CAJA,aAAA,CAEA,WAAA,CACA,qCAAA,CAAA,6BAAA,CAFA,UdukCR,CchkCM,kDACE,YdkkCR,Cc7jCI,gBAEE,cAAA,CADA,YdgkCN,Cc1jCE,cACE,ad4jCJ,CcxjCE,gBACE,Yd0jCJ,CKxgCI,wCS3CA,0CASE,2CAAA,CAHA,YAAA,CACA,qBAAA,CACA,WAAA,CAJA,MAAA,CAFA,iBAAA,CAEA,OAAA,CADA,KAAA,CAEA,SdyjCJ,Cc9iCI,4DACE,eAAA,CACA,edgjCN,CcljCI,yDACE,eAAA,CACA,edgjCN,CcljCI,mDACE,eAAA,CACA,edgjCN,Cc5iCI,gCAOE,qDAAA,CAHA,uCAAA,CAIA,cAAA,CANA,aAAA,CAGA,kBAAA,CAFA,wBAAA,CAFA,iBAAA,CAKA,kBdgjCN,Cc3iCM,wDAGE,UdijCR,CcpjCM,wDAGE,WdijCR,CcpjCM,8CAIE,aAAA,CAEA,aAAA,CACA,YAAA,CANA,iBAAA,CACA,SAAA,CAGA,Yd+iCR,Cc1iCQ,oDAIE,6BAAA,CAIA,UAAA,CAPA,aAAA,CAEA,WAAA,CAEA,2CAAA,CAAA,mCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CALA,UdkjCV,CcviCM,8CAEE,2CAAA,CACA,gEACE,CAHF,eAAA,CAIA,gCAAA,CAAA,4BAAA,CACA,kBdwiCR,CcriCQ,2DACE,YduiCV,CcliCM,8CAGE,2CAAA,CAFA,gCAAA,CACA,edqiCR,CchiCM,yCAIE,aAAA,CADA,UAAA,CAEA,YAAA,CACA,aAAA,CALA,iBAAA,CAEA,WAAA,CADA,SdsiCR,Cc7hCI,+BACE,Md+hCN,Cc3hCI,+BAEE,4DAAA,CADA,Sd8hCN,Cc1hCM,qDACE,+Bd4hCR,CczhCQ,gFACE,+Bd2hCV,Cc5hCQ,6EACE,+Bd2hCV,Cc5hCQ,uEACE,+Bd2hCV,CcrhCI,+BACE,YAAA,CACA,mBduhCN,CcphCM,uDAGE,mBduhCR,Cc1hCM,uDAGE,kBduhCR,Cc1hCM,6CAIE,gBAAA,CAFA,aAAA,CADA,YdyhCR,CcnhCQ,mDAIE,6BAAA,CAIA,UAAA,CAPA,aAAA,CAEA,WAAA,CAEA,2CAAA,CAAA,mCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CALA,Ud2hCV,Cc5gCM,+CACE,mBd8gCR,CctgCM,4CAEE,wBAAA,CADA,edygCR,CcrgCQ,oEACE,mBdugCV,CcxgCQ,oEACE,oBdugCV,CcngCQ,4EACE,iBdqgCV,CctgCQ,4EACE,kBdqgCV,CcjgCQ,oFACE,mBdmgCV,CcpgCQ,oFACE,oBdmgCV,Cc//BQ,4FACE,mBdigCV,CclgCQ,4FACE,oBdigCV,Cc1/BE,mBACE,wBd4/BJ,Ccx/BE,wBACE,YAAA,CAEA,SAAA,CADA,0BAAA,CAEA,oEd0/BJ,Ccr/BI,kCACE,2Bdu/BN,Ccl/BE,gCAEE,SAAA,CADA,uBAAA,CAEA,qEdo/BJ,Cc/+BI,8CAEE,kCAAA,CAAA,0Bdg/BN,CACF,CKppCI,wCS4KA,0CACE,Yd2+BJ,Ccx+BI,yDACE,Ud0+BN,Cct+BI,wDACE,Ydw+BN,Ccp+BI,kDACE,Yds+BN,Ccj+BE,gBAIE,iDAAA,CADA,gCAAA,CAFA,aAAA,CACA,edq+BJ,CACF,CKjtCM,6DSqPF,6CACE,Yd+9BJ,Cc59BI,4DACE,Ud89BN,Cc19BI,2DACE,Yd49BN,Ccx9BI,qDACE,Yd09BN,CACF,CKzsCI,mCS0PE,6CACE,uBdk9BN,Cc98BI,gDACE,Ydg9BN,CACF,CKjtCI,sCS7JJ,QAoaI,oDd88BF,Ccx8BI,8CACE,uBd08BN,Cch8BE,sEACE,Ydq8BJ,Ccj8BE,6DACE,adm8BJ,Ccp8BE,0DACE,adm8BJ,Ccp8BE,oDACE,adm8BJ,Cc/7BE,6CACE,Ydi8BJ,Cc77BE,uBACE,aAAA,CACA,ed+7BJ,Cc57BI,kCACE,ed87BN,Cc17BI,qCACE,eAAA,CACA,mBd47BN,Ccz7BM,mDACE,mBd27BR,Ccv7BM,mDACE,Ydy7BR,Ccp7BI,+BACE,ads7BN,Ccn7BM,2DACE,Sdq7BR,Cc/6BE,cAIE,kBAAA,CAHA,WAAA,CAEA,YAAA,CAEA,+CACE,CAJF,Wdo7BJ,Cc56BI,wBACE,UAAA,CACA,wBd86BN,Cc16BI,oBACE,uDd46BN,Ccx6BI,oBAKE,6BAAA,CAIA,UAAA,CARA,oBAAA,CAEA,WAAA,CAGA,2CAAA,CAAA,mCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CAJA,qBAAA,CAFA,Udi7BN,Cct6BI,0JAEE,uBdu6BN,Ccz5BI,+HACE,Yd+5BN,Cc55BM,oDACE,aAAA,CACA,Sd85BR,Cc35BQ,kEAGE,eAAA,CAFA,YAAA,CACA,eAAA,CAEA,mBd65BV,Cc15BU,gFACE,mBd45BZ,Ccx5BU,gFACE,Yd05BZ,Ccl5BI,2CACE,ado5BN,Ccj5BM,iFACE,mBdm5BR,Ccp5BM,iFACE,kBdm5BR,Cc14BI,mFACE,ed44BN,Ccz4BM,iGACE,Sd24BR,Cct4BI,qFAGE,mDdw4BN,Cc34BI,qFAGE,oDdw4BN,Cc34BI,2EACE,aAAA,CACA,oBdy4BN,Ccr4BM,0FACE,Ydu4BR,CACF,Cez+CA,MACE,igBf4+CF,Cet+CA,WACE,iBfy+CF,CK30CI,mCU/JJ,WAKI,efy+CF,CACF,Cet+CE,kBACE,Yfw+CJ,Cep+CE,oBAEE,SAAA,CADA,Sfu+CJ,CKp0CI,wCUpKF,8BAQI,Yf8+CJ,Cet/CA,8BAQI,af8+CJ,Cet/CA,oBAYI,2CAAA,CACA,kBAAA,CAHA,WAAA,CACA,eAAA,CAOA,mBAAA,CAZA,iBAAA,CACA,SAAA,CAOA,uBAAA,CACA,4CACE,CAPF,Uf6+CJ,Cej+CI,+DACE,SAAA,CACA,oCfm+CN,CACF,CK12CI,mCUjJF,8BAiCI,Mfq+CJ,CetgDA,8BAiCI,Ofq+CJ,CetgDA,oBAoCI,gCAAA,CACA,cAAA,CAFA,QAAA,CAJA,cAAA,CACA,KAAA,CAMA,sDACE,CALF,Ofo+CJ,Ce19CI,+DAME,YAAA,CACA,SAAA,CACA,4CACE,CARF,Uf+9CN,CACF,CKz2CI,wCUxGA,+DAII,mBfi9CN,CACF,CKv5CM,6DU/DF,+DASI,mBfi9CN,CACF,CK55CM,6DU/DF,+DAcI,mBfi9CN,CACF,Ce58CE,kBAEE,kCAAA,CAAA,0Bf68CJ,CK33CI,wCUpFF,4BAQI,Mfo9CJ,Ce59CA,4BAQI,Ofo9CJ,Ce59CA,kBAWI,QAAA,CAGA,SAAA,CAFA,eAAA,CANA,cAAA,CACA,KAAA,CAMA,wBAAA,CAEA,qGACE,CANF,OAAA,CADA,Sfm9CJ,Cet8CI,4BACE,yBfw8CN,Cep8CI,6DAEE,WAAA,CAEA,SAAA,CADA,uBAAA,CAEA,sGACE,CALF,Uf08CN,CACF,CKt6CI,mCUjEF,kBA2CI,WAAA,CAEA,eAAA,CAHA,iBAAA,CAIA,8CAAA,CAFA,afm8CJ,Ce97CI,4BACE,Ufg8CN,CACF,CKx8CM,6DUYF,6DAII,af47CN,CACF,CKv7CI,sCUVA,6DASI,af47CN,CACF,Cev7CE,iBAIE,2CAAA,CACA,gCAAA,CAFA,aAAA,CAFA,iBAAA,CAKA,2CACE,CALF,Sf67CJ,CKp8CI,mCUKF,iBAaI,gCAAA,CACA,mBAAA,CAFA,afy7CJ,Cep7CI,uBACE,oCfs7CN,CACF,Cel7CI,4DAEE,2CAAA,CACA,6BAAA,CACA,oCAAA,CAHA,gCfu7CN,Ce/6CE,4BAKE,mBAAA,CAAA,oBfo7CJ,Cez7CE,4BAKE,mBAAA,CAAA,oBfo7CJ,Cez7CE,kBAQE,sBAAA,CAFA,eAAA,CAFA,WAAA,CAHA,iBAAA,CAMA,sBAAA,CAJA,UAAA,CADA,Sfu7CJ,Ce96CI,oCACE,0BAAA,CAAA,qBfg7CN,Cej7CI,yCACE,yBAAA,CAAA,qBfg7CN,Cej7CI,+BACE,qBfg7CN,Ce56CI,oCAEE,uCf66CN,Ce/6CI,yCAEE,uCf66CN,Ce/6CI,kEAEE,uCf66CN,Cez6CI,6BACE,Yf26CN,CKp9CI,wCUkBF,kBA8BI,eAAA,CADA,aAAA,CADA,Uf46CJ,CACF,CK9+CI,mCUqCF,4BAmCI,mBf46CJ,Ce/8CA,4BAmCI,oBf46CJ,Ce/8CA,kBAoCI,aAAA,CACA,ef06CJ,Cev6CI,oCACE,uCfy6CN,Ce16CI,yCACE,uCfy6CN,Ce16CI,+BACE,uCfy6CN,Cer6CI,mCACE,gCfu6CN,Cen6CI,6DACE,kBfq6CN,Cel6CM,+EAEE,uCfm6CR,Cer6CM,oFAEE,uCfm6CR,Cer6CM,wJAEE,uCfm6CR,CACF,Ce75CE,iBAIE,cAAA,CAHA,oBAAA,CAEA,aAAA,CAEA,kCACE,CAJF,Yfk6CJ,Ce15CI,uBACE,Uf45CN,Cex5CI,yCAGE,Uf25CN,Ce95CI,yCAGE,Wf25CN,Ce95CI,+BACE,iBAAA,CACA,SAAA,CAEA,Sf05CN,Cev5CM,6CACE,oBfy5CR,CKjgDI,wCUgGA,yCAcI,Ufw5CN,Cet6CE,yCAcI,Wfw5CN,Cet6CE,+BAaI,Sfy5CN,Cer5CM,+CACE,Yfu5CR,CACF,CK7hDI,mCUmHA,+BAwBI,mBfs5CN,Cen5CM,8CACE,Yfq5CR,CACF,Ce/4CE,8BAGE,Wfm5CJ,Cet5CE,8BAGE,Ufm5CJ,Cet5CE,oBAKE,mBAAA,CAJA,iBAAA,CACA,SAAA,CAEA,Sfk5CJ,CKzhDI,wCUmIF,8BAUI,Wfi5CJ,Ce35CA,8BAUI,Ufi5CJ,Ce35CA,oBASI,Sfk5CJ,CACF,Ce94CI,gCACE,iBfo5CN,Cer5CI,gCACE,kBfo5CN,Cer5CI,sBAEE,uCAAA,CAEA,SAAA,CADA,oBAAA,CAEA,+Dfg5CN,Ce34CM,yCAEE,uCAAA,CADA,Yf84CR,Cez4CM,yFAGE,SAAA,CACA,mBAAA,CAFA,kBf44CR,Cev4CQ,8FACE,Ufy4CV,Cel4CE,8BAOE,mBAAA,CAAA,oBfy4CJ,Ceh5CE,8BAOE,mBAAA,CAAA,oBfy4CJ,Ceh5CE,oBAIE,kBAAA,CAIA,yCAAA,CALA,YAAA,CAMA,eAAA,CAHA,WAAA,CAKA,SAAA,CAVA,iBAAA,CACA,KAAA,CAUA,uBAAA,CAFA,kBAAA,CALA,Uf24CJ,CKnlDI,mCUmMF,8BAgBI,mBfq4CJ,Cer5CA,8BAgBI,oBfq4CJ,Cer5CA,oBAiBI,efo4CJ,CACF,Cej4CI,+DACE,SAAA,CACA,0Bfm4CN,Ce93CE,6BAKE,+Bfi4CJ,Cet4CE,0DAME,gCfg4CJ,Cet4CE,6BAME,+Bfg4CJ,Cet4CE,mBAIE,eAAA,CAHA,iBAAA,CAEA,UAAA,CADA,Sfo4CJ,CKllDI,wCU4MF,mBAWI,QAAA,CADA,Ufi4CJ,CACF,CK3mDI,mCU+NF,mBAiBI,SAAA,CADA,UAAA,CAEA,sBfg4CJ,Ce73CI,8DACE,8BAAA,CACA,Sf+3CN,CACF,Ce13CE,uBAKE,kCAAA,CAAA,0BAAA,CAFA,2CAAA,CAFA,WAAA,CACA,eAAA,CAOA,kBfw3CJ,Cer3CI,iEAZF,uBAaI,uBfw3CJ,CACF,CKxpDM,6DUkRJ,uBAkBI,afw3CJ,CACF,CKvoDI,sCU4PF,uBAuBI,afw3CJ,CACF,CK5oDI,mCU4PF,uBA4BI,YAAA,CAEA,+DAAA,CADA,oBfy3CJ,Cer3CI,kEACE,efu3CN,Cen3CI,6BACE,qDfq3CN,Cej3CI,0CAEE,YAAA,CADA,Wfo3CN,Ce/2CI,gDACE,oDfi3CN,Ce92CM,sDACE,0Cfg3CR,CACF,Cez2CA,kBACE,gCAAA,CACA,qBf42CF,Cez2CE,wBAKE,qDAAA,CAHA,uCAAA,CACA,gBAAA,CACA,kBAAA,CAHA,eAAA,CAKA,uBf22CJ,CKhrDI,mCU+TF,kCAUI,mBf22CJ,Cer3CA,kCAUI,oBf22CJ,CACF,Cev2CE,wBAGE,eAAA,CAFA,QAAA,CACA,Sf02CJ,Cer2CE,wBACE,yDfu2CJ,Cep2CI,oCACE,efs2CN,Cej2CE,wBACE,aAAA,CACA,YAAA,CAEA,uBAAA,CADA,gCfo2CJ,Ceh2CI,mDACE,uDfk2CN,Cen2CI,gDACE,uDfk2CN,Cen2CI,0CACE,uDfk2CN,Ce91CI,gDACE,mBfg2CN,Ce31CE,gCAGE,+BAAA,CAGA,cAAA,CALA,aAAA,CAGA,gBAAA,CACA,YAAA,CAHA,mBAAA,CAQA,uBAAA,CAHA,2Cf81CJ,CKttDI,mCUiXF,0CAcI,mBf21CJ,Cez2CA,0CAcI,oBf21CJ,CACF,Cex1CI,2DAEE,uDAAA,CADA,+Bf21CN,Ce51CI,wDAEE,uDAAA,CADA,+Bf21CN,Ce51CI,kDAEE,uDAAA,CADA,+Bf21CN,Cet1CI,wCACE,Yfw1CN,Cen1CI,wDACE,Yfq1CN,Cej1CI,oCACE,Wfm1CN,Ce90CE,2BAGE,eAAA,CADA,eAAA,CADA,iBfk1CJ,CK7uDI,mCU0ZF,qCAOI,mBfg1CJ,Cev1CA,qCAOI,oBfg1CJ,CACF,Ce10CM,8DAGE,eAAA,CADA,eAAA,CAEA,eAAA,CAHA,ef+0CR,Cet0CE,kCAEE,Mf40CJ,Ce90CE,kCAEE,Of40CJ,Ce90CE,wBAME,uCAAA,CAFA,aAAA,CACA,YAAA,CAJA,iBAAA,CAEA,Yf20CJ,CK7uDI,wCU+ZF,wBAUI,Yfw0CJ,CACF,Cer0CI,8BAIE,6BAAA,CAIA,UAAA,CAPA,oBAAA,CAEA,WAAA,CAEA,+CAAA,CAAA,uCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CALA,Uf60CN,Cep0CM,wCACE,oBfs0CR,Ceh0CE,yBAGE,gBAAA,CADA,eAAA,CAEA,eAAA,CAHA,afq0CJ,Ce9zCE,0BASE,2BAAA,CACA,oBAAA,CALA,uCAAA,CAJA,mBAAA,CAKA,gBAAA,CACA,eAAA,CAJA,aAAA,CADA,eAAA,CAEA,eAAA,CAIA,sBfk0CJ,CKjxDI,wCUucF,0BAeI,oBAAA,CADA,efi0CJ,CACF,CKh0DM,6DUgfJ,0BAqBI,oBAAA,CADA,efi0CJ,CACF,Ce7zCI,+BAEE,wBAAA,CADA,yBfg0CN,Ce1zCE,yBAEE,gBAAA,CACA,iBAAA,CAFA,af8zCJ,CexzCE,uBAEE,wBAAA,CADA,+Bf2zCJ,CgBn+DA,WACE,iBAAA,CACA,ShBs+DF,CgBn+DE,kBAOE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAHA,gCAAA,CAHA,QAAA,CAEA,gBAAA,CADA,YAAA,CAOA,SAAA,CAVA,iBAAA,CACA,sBAAA,CAQA,mCAAA,CAEA,oEhBq+DJ,CgB/9DI,+DACE,gBAAA,CAEA,SAAA,CADA,+BAAA,CAEA,sFACE,CADF,8EhBi+DN,CgBr+DI,4DACE,gBAAA,CAEA,SAAA,CADA,+BAAA,CAEA,mFACE,CADF,8EhBi+DN,CgBr+DI,sDACE,gBAAA,CAEA,SAAA,CADA,+BAAA,CAEA,8EhBi+DN,CgB19DI,wBAUE,qCAAA,CAAA,8CAAA,CAFA,mCAAA,CAAA,oCAAA,CACA,YAAA,CAEA,UAAA,CANA,QAAA,CAFA,QAAA,CAIA,kBAAA,CADA,iBAAA,CALA,iBAAA,CACA,KAAA,CAEA,OhBm+DN,CgBv9DE,iBAOE,mBAAA,CAFA,eAAA,CACA,oBAAA,CAJA,QAAA,CADA,kBAAA,CAGA,aAAA,CADA,ShB69DJ,CgBr9DE,iBACE,kBhBu9DJ,CgBn9DE,2BAGE,kBAAA,CAAA,oBhBy9DJ,CgB59DE,2BAGE,mBAAA,CAAA,mBhBy9DJ,CgB59DE,iBAKE,cAAA,CAJA,aAAA,CAGA,YAAA,CAKA,uBAAA,CAHA,2CACE,CALF,UhB09DJ,CgBh9DI,4CACE,+BhBk9DN,CgBn9DI,yCACE,+BhBk9DN,CgBn9DI,mCACE,+BhBk9DN,CgB98DI,uBACE,qDhBg9DN,CiBpiEA,YAIE,qBAAA,CADA,aAAA,CAGA,gBAAA,CALA,uBAAA,CAAA,eAAA,CACA,UAAA,CAGA,ajBwiEF,CiBpiEE,aATF,YAUI,YjBuiEF,CACF,CKz3DI,wCYxKA,+BAGE,ajB2iEJ,CiB9iEE,+BAGE,cjB2iEJ,CiB9iEE,qBAQE,2CAAA,CAHA,aAAA,CAEA,WAAA,CANA,cAAA,CACA,KAAA,CAOA,uBAAA,CACA,iEACE,CALF,aAAA,CAFA,SjB0iEJ,CiB/hEI,mEACE,8BAAA,CACA,6BjBiiEN,CiB9hEM,6EACE,8BjBgiER,CiB3hEI,6CAEE,QAAA,CAAA,MAAA,CACA,QAAA,CAEA,eAAA,CAJA,iBAAA,CACA,OAAA,CAEA,yBAAA,CAAA,qBAAA,CAFA,KjBgiEN,CACF,CKx6DI,sCYtKJ,YAuDI,QjB2hEF,CiBxhEE,mBACE,WjB0hEJ,CACF,CiBthEE,uBACE,YAAA,CACA,OjBwhEJ,CKp7DI,mCYtGF,uBAMI,QjBwhEJ,CiBrhEI,8BACE,WjBuhEN,CiBnhEI,qCACE,ajBqhEN,CiBjhEI,+CACE,kBjBmhEN,CACF,CiB9gEE,wBAIE,kCAAA,CAAA,0BAAA,CAHA,cAAA,CACA,eAAA,CAQA,+DAAA,CADA,oBjB4gEJ,CiBxgEI,8BACE,qDjB0gEN,CiBtgEI,2CAEE,YAAA,CADA,WjBygEN,CiBpgEI,iDACE,oDjBsgEN,CiBngEM,uDACE,0CjBqgER,CKn8DI,wCYxDF,YAME,gCAAA,CADA,QAAA,CAEA,SAAA,CANA,cAAA,CACA,KAAA,CAMA,sDACE,CALF,OAAA,CADA,SjBogEF,CiBz/DE,4CAEE,WAAA,CACA,SAAA,CACA,4CACE,CAJF,UjB8/DJ,CACF,CkB/oEA,yBACE,GACE,QlBipEF,CkB9oEA,GACE,alBgpEF,CACF,CkBvpEA,iBACE,GACE,QlBipEF,CkB9oEA,GACE,alBgpEF,CACF,CkB5oEA,wBACE,GAEE,SAAA,CADA,0BlB+oEF,CkB3oEA,IACE,SlB6oEF,CkB1oEA,GAEE,SAAA,CADA,uBlB6oEF,CACF,CkBzpEA,gBACE,GAEE,SAAA,CADA,0BlB+oEF,CkB3oEA,IACE,SlB6oEF,CkB1oEA,GAEE,SAAA,CADA,uBlB6oEF,CACF,CkBpoEA,MACE,mgBAAA,CACA,oiBAAA,CACA,0nBAAA,CACA,mhBlBsoEF,CkBhoEA,WAOE,kCAAA,CAAA,0BAAA,CANA,aAAA,CACA,gBAAA,CACA,eAAA,CAEA,uCAAA,CAGA,uBAAA,CAJA,kBlBsoEF,CkB/nEE,iBACE,UlBioEJ,CkB7nEE,iBACE,oBAAA,CAEA,aAAA,CACA,qBAAA,CAFA,UlBioEJ,CkB5nEI,+BAEE,iBlB8nEN,CkBhoEI,+BAEE,kBlB8nEN,CkBhoEI,qBACE,gBlB+nEN,CkB1nEI,kDACE,iBlB6nEN,CkB9nEI,kDACE,kBlB6nEN,CkB9nEI,kDAEE,iBlB4nEN,CkB9nEI,kDAEE,kBlB4nEN,CkBvnEE,iCAGE,iBlB4nEJ,CkB/nEE,iCAGE,kBlB4nEJ,CkB/nEE,uBACE,oBAAA,CACA,6BAAA,CAEA,eAAA,CACA,sBAAA,CACA,qBlBynEJ,CkBrnEE,kBAIE,gBAAA,CACA,oBAAA,CAJA,gBAAA,CAKA,WAAA,CAHA,eAAA,CADA,SlB2nEJ,CkBpnEI,uCACE,oCAAA,CAAA,4BlBsnEN,CkBjnEE,iBACE,oBlBmnEJ,CkBhnEI,sCACE,mCAAA,CAAA,2BlBknEN,CkB9mEI,kCAIE,kBlBqnEN,CkBznEI,kCAIE,iBlBqnEN,CkBznEI,wBAME,6BAAA,CAGA,UAAA,CARA,oBAAA,CAEA,YAAA,CAIA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CAHA,uBAAA,CAHA,WlBunEN,CkB5mEI,kDACE,iBlB8mEN,CkB/mEI,kDACE,kBlB8mEN,CkB1mEI,iCACE,gDAAA,CAAA,wClB4mEN,CkBxmEI,+BACE,8CAAA,CAAA,sClB0mEN,CkBtmEI,+BACE,8CAAA,CAAA,sClBwmEN,CkBpmEI,sCACE,qDAAA,CAAA,6ClBsmEN,CmBxvEA,SAIE,2CAAA,CADA,gCAAA,CADA,aAAA,CADA,UnB8vEF,CmBxvEE,aAPF,SAQI,YnB2vEF,CACF,CK3kEI,wCczLJ,SAaI,YnB2vEF,CACF,CmBxvEE,+BACE,mBnB0vEJ,CmBtvEE,yBAEE,iBnB4vEJ,CmB9vEE,yBAEE,kBnB4vEJ,CmB9vEE,eAME,eAAA,CADA,eAAA,CAJA,QAAA,CAEA,SAAA,CACA,kBnB0vEJ,CmBpvEE,eACE,oBAAA,CACA,aAAA,CACA,kBAAA,CAAA,mBnBsvEJ,CmBjvEE,eAOE,kCAAA,CAAA,0BAAA,CANA,aAAA,CAEA,eAAA,CADA,gBAAA,CAMA,UAAA,CAJA,uCAAA,CACA,oBAAA,CAIA,8DnBkvEJ,CmB7uEI,iEAEE,aAAA,CACA,SnB8uEN,CmBjvEI,8DAEE,aAAA,CACA,SnB8uEN,CmBjvEI,wDAEE,aAAA,CACA,SnB8uEN,CmBzuEM,2CACE,qBnB2uER,CmB5uEM,2CACE,qBnB8uER,CmB/uEM,2CACE,qBnBivER,CmBlvEM,2CACE,qBnBovER,CmBrvEM,2CACE,oBnBuvER,CmBxvEM,2CACE,qBnB0vER,CmB3vEM,2CACE,qBnB6vER,CmB9vEM,2CACE,qBnBgwER,CmBjwEM,4CACE,qBnBmwER,CmBpwEM,4CACE,oBnBswER,CmBvwEM,4CACE,qBnBywER,CmB1wEM,4CACE,qBnB4wER,CmB7wEM,4CACE,qBnB+wER,CmBhxEM,4CACE,qBnBkxER,CmBnxEM,4CACE,oBnBqxER,CmB/wEI,8CAEE,SAAA,CADA,yBAAA,CAEA,wCnBixEN,CoBz1EA,SACE,mBpB41EF,CoBx1EA,kBAEE,iBpBk2EF,CoBp2EA,kBAEE,gBpBk2EF,CoBp2EA,QAQE,+CAAA,CACA,mBAAA,CARA,oBAAA,CAKA,gBAAA,CADA,eAAA,CAEA,eAAA,CAJA,kBAAA,CACA,uBpBg2EF,CoBx1EE,cAGE,uCAAA,CAFA,aAAA,CACA,YAAA,CAEA,6CpB01EJ,CoBr1EI,wCAGE,0CAAA,CADA,+BpBu1EN,CoBj1EE,aACE,uBpBm1EJ,CqBt3EA,yBACE,GACE,uDrBy3EF,CqBt3EA,IACE,mCrBw3EF,CqBr3EA,GACE,8BrBu3EF,CACF,CqBl4EA,iBACE,GACE,uDrBy3EF,CqBt3EA,IACE,mCrBw3EF,CqBr3EA,GACE,8BrBu3EF,CACF,CqB/2EA,MACE,wBrBi3EF,CqB32EA,YA0BE,kCAAA,CAAA,0BAAA,CALA,2CAAA,CACA,mBAAA,CACA,8BAAA,CAHA,gCAAA,CAjBA,iJACE,CAeF,YAAA,CADA,8BAAA,CASA,SAAA,CA1BA,iBAAA,CACA,uBAAA,CAsBA,4BAAA,CAIA,2EACE,CAZF,6BAAA,CADA,SrBs3EF,CqBn2EE,0BACE,gBAAA,CAEA,SAAA,CADA,uBAAA,CAEA,2FrBq2EJ,CqB71EE,2BACE,sCrB+1EJ,CqB31EE,mBAEE,gBAAA,CADA,arB81EJ,CqB11EI,2CACE,YrB41EN,CqBx1EI,0CACE,erB01EN,CqBl1EA,eAEE,YAAA,CADA,kBrBs1EF,CqBl1EE,yBACE,arBo1EJ,CqBh1EE,6BACE,oBAAA,CAGA,iBrBg1EJ,CqB50EE,8BACE,SrB80EJ,CqB10EE,sBAEE,sCAAA,CADA,qCrB60EJ,CqBz0EI,0CAEE,mBAAA,CADA,wBAAA,CAAA,qBAAA,CAAA,oBAAA,CAAA,gBrB40EN,CqBt0EE,sBAIE,UAAA,CACA,cAAA,CAFA,YAAA,CAFA,iBAAA,CAKA,uBAAA,CACA,wBAAA,CAAA,qBAAA,CAAA,oBAAA,CAAA,gBAAA,CALA,SrB60EJ,CqBl0EI,4BAgBE,mCAAA,CAAA,2BAAA,CALA,oDAAA,CACA,iBAAA,CAKA,UAAA,CATA,YAAA,CANA,YAAA,CAOA,cAAA,CACA,cAAA,CATA,iBAAA,CAYA,2CACE,CARF,wBAAA,CACA,6BAAA,CAJA,UrB80EN,CqB7zEM,gCApBF,4BAqBI,sBAAA,CAAA,crBg0EN,CACF,CqB7zEM,+DACE,0CrB+zER,CqBh0EM,4DACE,0CrB+zER,CqBh0EM,sDACE,0CrB+zER,CqB3zEM,0CAIE,sBAAA,CAAA,cAAA,CAHA,2CrB8zER,CqBtzEI,8CACE,oBAAA,CACA,erBwzEN,CqBrzEM,qDAME,mCAAA,CALA,oBAAA,CACA,mBAAA,CAEA,qBAAA,CACA,iDAAA,CAFA,qBrB0zER,CqBnzEQ,iBAVF,qDAWI,WrBszER,CqBnzEQ,mEACE,mCrBqzEV,CACF,CqB/yEI,yDACE,+BrBizEN,CqBlzEI,sDACE,+BrBizEN,CqBlzEI,gDACE,+BrBizEN,CqB7yEI,oCAEE,sBAAA,CAAA,cAAA,CADA,erBgzEN,CsBzgFA,kBAIE,etBqhFF,CsBzhFA,kBAIE,gBtBqhFF,CsBzhFA,QAQE,2CAAA,CACA,oBAAA,CAEA,8BAAA,CALA,uCAAA,CACA,eAAA,CAGA,YAAA,CALA,mBAAA,CAJA,cAAA,CACA,UAAA,CAUA,yBAAA,CACA,mGACE,CAXF,StBshFF,CsBrgFE,aApBF,QAqBI,YtBwgFF,CACF,CsBrgFE,kBACE,wBtBugFJ,CsBngFE,8BAEE,SAAA,CAEA,mBAAA,CAHA,+BAAA,CAEA,uBtBsgFJ,CsBlgFI,wCACE,8BtBogFN,CsB//EE,mCAEE,0CAAA,CADA,+BtBkgFJ,CsBngFE,gCAEE,0CAAA,CADA,+BtBkgFJ,CsBngFE,0BAEE,0CAAA,CADA,+BtBkgFJ,CsB7/EE,YACE,oBAAA,CACA,oBtB+/EJ,CuBljFA,4BACE,GACE,mBvBqjFF,CACF,CuBxjFA,oBACE,GACE,mBvBqjFF,CACF,CuB7iFA,MACE,kiBvB+iFF,CuBziFA,YACE,aAAA,CAEA,eAAA,CADA,avB6iFF,CuBziFE,+BAOE,kBAAA,CAAA,kBvB0iFJ,CuBjjFE,+BAOE,iBAAA,CAAA,mBvB0iFJ,CuBjjFE,qBAQE,aAAA,CAEA,cAAA,CADA,YAAA,CARA,iBAAA,CAKA,UvB2iFJ,CuBpiFI,qCAIE,iBvB0iFN,CuB9iFI,qCAIE,kBvB0iFN,CuB9iFI,2BAKE,6BAAA,CAGA,UAAA,CAPA,oBAAA,CAEA,YAAA,CAGA,yCAAA,CAAA,iCAAA,CACA,6BAAA,CAAA,qBAAA,CALA,WvB4iFN,CuBjiFE,kBAUE,2CAAA,CACA,mBAAA,CACA,8BAAA,CAJA,gCAAA,CACA,oBAAA,CAJA,kBAAA,CADA,YAAA,CASA,SAAA,CANA,aAAA,CADA,SAAA,CALA,iBAAA,CAgBA,gCAAA,CAAA,4BAAA,CAfA,UAAA,CAYA,+CACE,CAZF,SvB+iFJ,CuB9hFI,gEACE,gBAAA,CACA,SAAA,CACA,8CACE,CADF,sCvBgiFN,CuBniFI,6DACE,gBAAA,CACA,SAAA,CACA,2CACE,CADF,sCvBgiFN,CuBniFI,uDACE,gBAAA,CACA,SAAA,CACA,sCvBgiFN,CuB1hFI,wBAGE,oCACE,wCAAA,CAAA,gCvB0hFN,CuBthFI,2CACE,sBAAA,CAAA,cvBwhFN,CACF,CuBnhFE,kBACE,kBvBqhFJ,CuBjhFE,4BAGE,kBAAA,CAAA,oBvBwhFJ,CuB3hFE,4BAGE,mBAAA,CAAA,mBvBwhFJ,CuB3hFE,kBAME,cAAA,CALA,aAAA,CAIA,YAAA,CAKA,uBAAA,CAHA,2CACE,CAJF,kBAAA,CAFA,UvByhFJ,CuB9gFI,6CACE,+BvBghFN,CuBjhFI,0CACE,+BvBghFN,CuBjhFI,oCACE,+BvBghFN,CuB5gFI,wBACE,qDvB8gFN,CwB7mFA,MAEI,2RAAA,CAAA,8WAAA,CAAA,sPAAA,CAAA,8xBAAA,CAAA,qNAAA,CAAA,gbAAA,CAAA,gMAAA,CAAA,+PAAA,CAAA,8KAAA,CAAA,0eAAA,CAAA,kUAAA,CAAA,gMxBsoFJ,CwB1nFE,8CAOE,8CAAA,CACA,sBAAA,CAEA,mBAAA,CACA,8BAAA,CAPA,mCAAA,CAHA,iBAAA,CAIA,gBAAA,CAHA,iBAAA,CACA,eAAA,CAGA,uBxBkoFJ,CwBxoFE,2CAOE,8CAAA,CACA,sBAAA,CAEA,mBAAA,CACA,8BAAA,CAPA,mCAAA,CAHA,iBAAA,CAIA,gBAAA,CAHA,iBAAA,CACA,eAAA,CAGA,uBxBkoFJ,CwBxoFE,wDASE,uBxB+nFJ,CwBxoFE,qDASE,uBxB+nFJ,CwBxoFE,+CASE,uBxB+nFJ,CwBxoFE,wDASE,wBxB+nFJ,CwBxoFE,qDASE,wBxB+nFJ,CwBxoFE,+CASE,wBxB+nFJ,CwBxoFE,qCAOE,8CAAA,CACA,sBAAA,CAEA,mBAAA,CACA,8BAAA,CAPA,mCAAA,CAHA,iBAAA,CAIA,gBAAA,CAHA,iBAAA,CACA,eAAA,CAGA,uBxBkoFJ,CwB1nFI,aAdF,8CAeI,exB6nFJ,CwB5oFA,2CAeI,exB6nFJ,CwB5oFA,qCAeI,exB6nFJ,CACF,CwBznFI,gDACE,qBxB2nFN,CwB5nFI,6CACE,qBxB2nFN,CwB5nFI,uCACE,qBxB2nFN,CwBvnFI,gFAEE,iBAAA,CADA,cxB0nFN,CwB3nFI,0EAEE,iBAAA,CADA,cxB0nFN,CwB3nFI,8DAEE,iBAAA,CADA,cxB0nFN,CwBrnFI,sEACE,iBxBunFN,CwBxnFI,mEACE,iBxBunFN,CwBxnFI,6DACE,iBxBunFN,CwBnnFI,iEACE,exBqnFN,CwBtnFI,8DACE,exBqnFN,CwBtnFI,wDACE,exBqnFN,CwBjnFI,qEACE,YxBmnFN,CwBpnFI,kEACE,YxBmnFN,CwBpnFI,4DACE,YxBmnFN,CwB/mFI,+DACE,mBxBinFN,CwBlnFI,4DACE,mBxBinFN,CwBlnFI,sDACE,mBxBinFN,CwB5mFE,oDAOE,oCAAA,CACA,WAAA,CAFA,eAAA,CAJA,eAAA,CAAA,YAAA,CAEA,oBAAA,CAAA,iBAAA,CAHA,iBxBwnFJ,CwBznFE,iDAOE,oCAAA,CACA,WAAA,CAFA,eAAA,CAJA,eAAA,CAAA,YAAA,CAEA,oBAAA,CAAA,iBAAA,CAHA,iBxBwnFJ,CwBznFE,8DAGE,kBAAA,CAAA,mBxBsnFJ,CwBznFE,2DAGE,kBAAA,CAAA,mBxBsnFJ,CwBznFE,qDAGE,kBAAA,CAAA,mBxBsnFJ,CwBznFE,8DAGE,kBAAA,CAAA,mBxBsnFJ,CwBznFE,2DAGE,kBAAA,CAAA,mBxBsnFJ,CwBznFE,qDAGE,kBAAA,CAAA,mBxBsnFJ,CwBznFE,8DAKE,mBAAA,CAAA,mBxBonFJ,CwBznFE,2DAKE,mBAAA,CAAA,mBxBonFJ,CwBznFE,qDAKE,mBAAA,CAAA,mBxBonFJ,CwBznFE,8DAKE,kBAAA,CAAA,oBxBonFJ,CwBznFE,2DAKE,kBAAA,CAAA,oBxBonFJ,CwBznFE,qDAKE,kBAAA,CAAA,oBxBonFJ,CwBznFE,8DASE,uBxBgnFJ,CwBznFE,2DASE,uBxBgnFJ,CwBznFE,qDASE,uBxBgnFJ,CwBznFE,8DASE,wBxBgnFJ,CwBznFE,2DASE,wBxBgnFJ,CwBznFE,qDASE,wBxBgnFJ,CwBznFE,8DAUE,4BxB+mFJ,CwBznFE,2DAUE,4BxB+mFJ,CwBznFE,qDAUE,4BxB+mFJ,CwBznFE,8DAUE,6BxB+mFJ,CwBznFE,2DAUE,6BxB+mFJ,CwBznFE,qDAUE,6BxB+mFJ,CwBznFE,8DAWE,6BxB8mFJ,CwBznFE,2DAWE,6BxB8mFJ,CwBznFE,qDAWE,6BxB8mFJ,CwBznFE,8DAWE,4BxB8mFJ,CwBznFE,2DAWE,4BxB8mFJ,CwBznFE,qDAWE,4BxB8mFJ,CwBznFE,2CAOE,oCAAA,CACA,WAAA,CAFA,eAAA,CAJA,eAAA,CAAA,YAAA,CAEA,oBAAA,CAAA,iBAAA,CAHA,iBxBwnFJ,CwB3mFI,oEACE,exB6mFN,CwB9mFI,iEACE,exB6mFN,CwB9mFI,2DACE,exB6mFN,CwBzmFI,2DAME,wBCuIU,CDnIV,UAAA,CALA,WAAA,CAEA,kDAAA,CAAA,0CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CARA,iBAAA,CACA,UAAA,CAEA,UxBinFN,CwBrnFI,wDAME,wBCuIU,CDnIV,UAAA,CALA,WAAA,CAEA,0CAAA,CACA,qBAAA,CACA,iBAAA,CARA,iBAAA,CACA,UAAA,CAEA,UxBinFN,CwBrnFI,qEAGE,UxBknFN,CwBrnFI,kEAGE,UxBknFN,CwBrnFI,4DAGE,UxBknFN,CwBrnFI,qEAGE,WxBknFN,CwBrnFI,kEAGE,WxBknFN,CwBrnFI,4DAGE,WxBknFN,CwBrnFI,kDAME,wBCuIU,CDnIV,UAAA,CALA,WAAA,CAEA,kDAAA,CAAA,0CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CARA,iBAAA,CACA,UAAA,CAEA,UxBinFN,CwBvlFE,iEACE,oBxB0lFJ,CwB3lFE,2DACE,oBxB0lFJ,CwB3lFE,+CACE,oBxB0lFJ,CwBtlFE,wEACE,oCxBylFJ,CwB1lFE,kEACE,oCxBylFJ,CwB1lFE,sDACE,oCxBylFJ,CwBtlFI,+EACE,wBAnBG,CAoBH,kDAAA,CAAA,0CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBwlFN,CwB5lFI,yEACE,wBAnBG,CAoBH,0CAAA,CACA,qBAAA,CACA,iBxBwlFN,CwB5lFI,6DACE,wBAnBG,CAoBH,kDAAA,CAAA,0CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBwlFN,CwBrmFE,oFACE,oBxBwmFJ,CwBzmFE,8EACE,oBxBwmFJ,CwBzmFE,kEACE,oBxBwmFJ,CwBpmFE,2FACE,mCxBumFJ,CwBxmFE,qFACE,mCxBumFJ,CwBxmFE,yEACE,mCxBumFJ,CwBpmFI,kGACE,wBAnBG,CAoBH,sDAAA,CAAA,8CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBsmFN,CwB1mFI,4FACE,wBAnBG,CAoBH,8CAAA,CACA,qBAAA,CACA,iBxBsmFN,CwB1mFI,gFACE,wBAnBG,CAoBH,sDAAA,CAAA,8CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBsmFN,CwBnnFE,uEACE,oBxBsnFJ,CwBvnFE,iEACE,oBxBsnFJ,CwBvnFE,qDACE,oBxBsnFJ,CwBlnFE,8EACE,mCxBqnFJ,CwBtnFE,wEACE,mCxBqnFJ,CwBtnFE,4DACE,mCxBqnFJ,CwBlnFI,qFACE,wBAnBG,CAoBH,kDAAA,CAAA,0CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBonFN,CwBxnFI,+EACE,wBAnBG,CAoBH,0CAAA,CACA,qBAAA,CACA,iBxBonFN,CwBxnFI,mEACE,wBAnBG,CAoBH,kDAAA,CAAA,0CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBonFN,CwBjoFE,iFACE,oBxBooFJ,CwBroFE,2EACE,oBxBooFJ,CwBroFE,+DACE,oBxBooFJ,CwBhoFE,wFACE,mCxBmoFJ,CwBpoFE,kFACE,mCxBmoFJ,CwBpoFE,sEACE,mCxBmoFJ,CwBhoFI,+FACE,wBAnBG,CAoBH,iDAAA,CAAA,yCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBkoFN,CwBtoFI,yFACE,wBAnBG,CAoBH,yCAAA,CACA,qBAAA,CACA,iBxBkoFN,CwBtoFI,6EACE,wBAnBG,CAoBH,iDAAA,CAAA,yCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBkoFN,CwB/oFE,iFACE,oBxBkpFJ,CwBnpFE,2EACE,oBxBkpFJ,CwBnpFE,+DACE,oBxBkpFJ,CwB9oFE,wFACE,kCxBipFJ,CwBlpFE,kFACE,kCxBipFJ,CwBlpFE,sEACE,kCxBipFJ,CwB9oFI,+FACE,wBAnBG,CAoBH,qDAAA,CAAA,6CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBgpFN,CwBppFI,yFACE,wBAnBG,CAoBH,6CAAA,CACA,qBAAA,CACA,iBxBgpFN,CwBppFI,6EACE,wBAnBG,CAoBH,qDAAA,CAAA,6CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBgpFN,CwB7pFE,gFACE,oBxBgqFJ,CwBjqFE,0EACE,oBxBgqFJ,CwBjqFE,8DACE,oBxBgqFJ,CwB5pFE,uFACE,oCxB+pFJ,CwBhqFE,iFACE,oCxB+pFJ,CwBhqFE,qEACE,oCxB+pFJ,CwB5pFI,8FACE,wBAnBG,CAoBH,sDAAA,CAAA,8CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxB8pFN,CwBlqFI,wFACE,wBAnBG,CAoBH,8CAAA,CACA,qBAAA,CACA,iBxB8pFN,CwBlqFI,4EACE,wBAnBG,CAoBH,sDAAA,CAAA,8CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxB8pFN,CwB3qFE,wFACE,oBxB8qFJ,CwB/qFE,kFACE,oBxB8qFJ,CwB/qFE,sEACE,oBxB8qFJ,CwB1qFE,+FACE,mCxB6qFJ,CwB9qFE,yFACE,mCxB6qFJ,CwB9qFE,6EACE,mCxB6qFJ,CwB1qFI,sGACE,wBAnBG,CAoBH,qDAAA,CAAA,6CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxB4qFN,CwBhrFI,gGACE,wBAnBG,CAoBH,6CAAA,CACA,qBAAA,CACA,iBxB4qFN,CwBhrFI,oFACE,wBAnBG,CAoBH,qDAAA,CAAA,6CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxB4qFN,CwBzrFE,mFACE,oBxB4rFJ,CwB7rFE,6EACE,oBxB4rFJ,CwB7rFE,iEACE,oBxB4rFJ,CwBxrFE,0FACE,mCxB2rFJ,CwB5rFE,oFACE,mCxB2rFJ,CwB5rFE,wEACE,mCxB2rFJ,CwBxrFI,iGACE,wBAnBG,CAoBH,qDAAA,CAAA,6CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxB0rFN,CwB9rFI,2FACE,wBAnBG,CAoBH,6CAAA,CACA,qBAAA,CACA,iBxB0rFN,CwB9rFI,+EACE,wBAnBG,CAoBH,qDAAA,CAAA,6CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxB0rFN,CwBvsFE,0EACE,oBxB0sFJ,CwB3sFE,oEACE,oBxB0sFJ,CwB3sFE,wDACE,oBxB0sFJ,CwBtsFE,iFACE,mCxBysFJ,CwB1sFE,2EACE,mCxBysFJ,CwB1sFE,+DACE,mCxBysFJ,CwBtsFI,wFACE,wBAnBG,CAoBH,oDAAA,CAAA,4CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBwsFN,CwB5sFI,kFACE,wBAnBG,CAoBH,4CAAA,CACA,qBAAA,CACA,iBxBwsFN,CwB5sFI,sEACE,wBAnBG,CAoBH,oDAAA,CAAA,4CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBwsFN,CwBrtFE,gEACE,oBxBwtFJ,CwBztFE,0DACE,oBxBwtFJ,CwBztFE,8CACE,oBxBwtFJ,CwBptFE,uEACE,kCxButFJ,CwBxtFE,iEACE,kCxButFJ,CwBxtFE,qDACE,kCxButFJ,CwBptFI,8EACE,wBAnBG,CAoBH,iDAAA,CAAA,yCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBstFN,CwB1tFI,wEACE,wBAnBG,CAoBH,yCAAA,CACA,qBAAA,CACA,iBxBstFN,CwB1tFI,4DACE,wBAnBG,CAoBH,iDAAA,CAAA,yCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBstFN,CwBnuFE,oEACE,oBxBsuFJ,CwBvuFE,8DACE,oBxBsuFJ,CwBvuFE,kDACE,oBxBsuFJ,CwBluFE,2EACE,oCxBquFJ,CwBtuFE,qEACE,oCxBquFJ,CwBtuFE,yDACE,oCxBquFJ,CwBluFI,kFACE,wBAnBG,CAoBH,qDAAA,CAAA,6CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBouFN,CwBxuFI,4EACE,wBAnBG,CAoBH,6CAAA,CACA,qBAAA,CACA,iBxBouFN,CwBxuFI,gEACE,wBAnBG,CAoBH,qDAAA,CAAA,6CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBouFN,CwBjvFE,wEACE,oBxBovFJ,CwBrvFE,kEACE,oBxBovFJ,CwBrvFE,sDACE,oBxBovFJ,CwBhvFE,+EACE,kCxBmvFJ,CwBpvFE,yEACE,kCxBmvFJ,CwBpvFE,6DACE,kCxBmvFJ,CwBhvFI,sFACE,wBAnBG,CAoBH,mDAAA,CAAA,2CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBkvFN,CwBtvFI,gFACE,wBAnBG,CAoBH,2CAAA,CACA,qBAAA,CACA,iBxBkvFN,CwBtvFI,oEACE,wBAnBG,CAoBH,mDAAA,CAAA,2CAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBxBkvFN,C0Bz4FA,MACE,wM1B44FF,C0Bn4FE,sBACE,uCAAA,CACA,gB1Bs4FJ,C0Bn4FI,mCACE,a1Bq4FN,C0Bt4FI,mCACE,c1Bq4FN,C0Bj4FM,4BACE,sB1Bm4FR,C0Bh4FQ,mCACE,gC1Bk4FV,C0B93FQ,2DAEE,SAAA,CADA,uBAAA,CAEA,e1Bg4FV,C0B53FQ,0EAEE,SAAA,CADA,uB1B+3FV,C0Bh4FQ,uEAEE,SAAA,CADA,uB1B+3FV,C0Bh4FQ,iEAEE,SAAA,CADA,uB1B+3FV,C0B13FQ,yCACE,Y1B43FV,C0Br3FE,0BAEE,eAAA,CADA,e1Bw3FJ,C0Bp3FI,+BACE,oB1Bs3FN,C0Bj3FE,gDACE,Y1Bm3FJ,C0B/2FE,8BAEE,+BAAA,CADA,oBAAA,CAGA,WAAA,CAGA,SAAA,CADA,4BAAA,CAEA,4DACE,CAJF,0B1Bm3FJ,C0B12FI,aAdF,8BAeI,+BAAA,CAEA,SAAA,CADA,uB1B82FJ,CACF,C0B12FI,wCACE,6B1B42FN,C0Bx2FI,oCACE,+B1B02FN,C0Bt2FI,qCAIE,6BAAA,CAIA,UAAA,CAPA,oBAAA,CAEA,YAAA,CAEA,2CAAA,CAAA,mCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CALA,W1B82FN,C0Bl2FQ,mDACE,oB1Bo2FV,C2Bj9FE,kCAEE,iB3Bu9FJ,C2Bz9FE,kCAEE,kB3Bu9FJ,C2Bz9FE,wBAGE,yCAAA,CAFA,oBAAA,CAGA,SAAA,CACA,mC3Bo9FJ,C2B/8FI,aAVF,wBAWI,Y3Bk9FJ,CACF,C2B98FE,mFAEE,SAAA,CACA,2CACE,CADF,mC3Bg9FJ,C2Bn9FE,gFAEE,SAAA,CACA,wCACE,CADF,mC3Bg9FJ,C2Bn9FE,0EAEE,SAAA,CACA,mC3Bg9FJ,C2B18FE,mFAEE,+B3B48FJ,C2B98FE,gFAEE,+B3B48FJ,C2B98FE,0EAEE,+B3B48FJ,C2Bx8FE,oBACE,yBAAA,CACA,uBAAA,CAGA,yE3Bw8FJ,CKz0FI,sCsBrHE,qDACE,uB3Bi8FN,CACF,C2B57FE,0CACE,yB3B87FJ,C2B/7FE,uCACE,yB3B87FJ,C2B/7FE,iCACE,yB3B87FJ,C2B17FE,sBACE,0B3B47FJ,C4Bv/FE,2BACE,a5B0/FJ,CKr0FI,wCuBtLF,2BAKI,e5B0/FJ,CACF,C4Bv/FI,6BAEE,0BAAA,CAAA,2BAAA,CACA,eAAA,CACA,iBAAA,CAHA,yBAAA,CAAA,sBAAA,CAAA,iB5B4/FN,C4Bt/FM,2CACE,kB5Bw/FR,C6BzgGE,kDACE,kCAAA,CAAA,0B7B4gGJ,C6B7gGE,+CACE,0B7B4gGJ,C6B7gGE,yCACE,kCAAA,CAAA,0B7B4gGJ,C6BxgGE,uBACE,4C7B0gGJ,C6BtgGE,uBACE,4C7BwgGJ,C6BpgGE,4BACE,qC7BsgGJ,C6BngGI,mCACE,a7BqgGN,C6BjgGI,kCACE,a7BmgGN,C6B9/FE,0BAKE,eAAA,CAJA,aAAA,CACA,YAAA,CAEA,aAAA,CADA,kBAAA,CAAA,mB7BkgGJ,C6B7/FI,uCACE,e7B+/FN,C6B3/FI,sCACE,kB7B6/FN,C8B5iGA,MACE,8L9B+iGF,C8BtiGE,oBACE,iBAAA,CAEA,gBAAA,CADA,a9B0iGJ,C8BtiGI,wCACE,uB9BwiGN,C8BpiGI,gCAEE,eAAA,CADA,gB9BuiGN,C8BhiGM,wCACE,mB9BkiGR,C8B5hGE,8BAGE,oB9BiiGJ,C8BpiGE,8BAGE,mB9BiiGJ,C8BpiGE,8BAIE,4B9BgiGJ,C8BpiGE,4DAKE,6B9B+hGJ,C8BpiGE,8BAKE,4B9B+hGJ,C8BpiGE,oBAME,cAAA,CALA,aAAA,CACA,e9BkiGJ,C8B3hGI,kCACE,uCAAA,CACA,oB9B6hGN,C8BzhGI,wCAEE,uCAAA,CADA,Y9B4hGN,C8BvhGI,oCAGE,W9BkiGN,C8BriGI,oCAGE,U9BkiGN,C8BriGI,0BAME,6BAAA,CAMA,UAAA,CAPA,WAAA,CAEA,yCAAA,CAAA,iCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CARA,iBAAA,CACA,UAAA,CAQA,sBAAA,CACA,yBAAA,CAPA,U9BiiGN,C8BthGM,oCACE,wB9BwhGR,C8BnhGI,4BACE,Y9BqhGN,C8BhhGI,4CACE,Y9BkhGN,C+BpmGE,qDACE,mBAAA,CACA,cAAA,CACA,uB/BumGJ,C+B1mGE,kDACE,mBAAA,CACA,cAAA,CACA,uB/BumGJ,C+B1mGE,4CACE,mBAAA,CACA,cAAA,CACA,uB/BumGJ,C+BpmGI,yDAGE,iBAAA,CADA,eAAA,CADA,a/BwmGN,C+BzmGI,sDAGE,iBAAA,CADA,eAAA,CADA,a/BwmGN,C+BzmGI,gDAGE,iBAAA,CADA,eAAA,CADA,a/BwmGN,CgC9mGE,gCACE,sChCinGJ,CgClnGE,6BACE,sChCinGJ,CgClnGE,uBACE,sChCinGJ,CgC9mGE,cACE,yChCgnGJ,CgCpmGE,4DACE,oChCsmGJ,CgCvmGE,yDACE,oChCsmGJ,CgCvmGE,mDACE,oChCsmGJ,CgC9lGE,6CACE,qChCgmGJ,CgCjmGE,0CACE,qChCgmGJ,CgCjmGE,oCACE,qChCgmGJ,CgCtlGE,oDACE,oChCwlGJ,CgCzlGE,iDACE,oChCwlGJ,CgCzlGE,2CACE,oChCwlGJ,CgC/kGE,gDACE,qChCilGJ,CgCllGE,6CACE,qChCilGJ,CgCllGE,uCACE,qChCilGJ,CgC5kGE,gCACE,kChC8kGJ,CgC/kGE,6BACE,kChC8kGJ,CgC/kGE,uBACE,kChC8kGJ,CgCxkGE,qCACE,sChC0kGJ,CgC3kGE,kCACE,sChC0kGJ,CgC3kGE,4BACE,sChC0kGJ,CgCnkGE,yCACE,sChCqkGJ,CgCtkGE,sCACE,sChCqkGJ,CgCtkGE,gCACE,sChCqkGJ,CgC9jGE,yCACE,qChCgkGJ,CgCjkGE,sCACE,qChCgkGJ,CgCjkGE,gCACE,qChCgkGJ,CgCvjGE,gDACE,qChCyjGJ,CgC1jGE,6CACE,qChCyjGJ,CgC1jGE,uCACE,qChCyjGJ,CgCjjGE,6CACE,sChCmjGJ,CgCpjGE,0CACE,sChCmjGJ,CgCpjGE,oCACE,sChCmjGJ,CgCxiGE,yDACE,qChC0iGJ,CgC3iGE,sDACE,qChC0iGJ,CgC3iGE,gDACE,qChC0iGJ,CgCriGE,iCAGE,mBAAA,CAFA,gBAAA,CACA,gBhCwiGJ,CgC1iGE,8BAGE,mBAAA,CAFA,gBAAA,CACA,gBhCwiGJ,CgC1iGE,wBAGE,mBAAA,CAFA,gBAAA,CACA,gBhCwiGJ,CgCpiGE,eACE,4ChCsiGJ,CgCniGE,eACE,4ChCqiGJ,CgCjiGE,gBAIE,wCAAA,CAHA,aAAA,CACA,wBAAA,CACA,wBhCoiGJ,CgC/hGE,yBAOE,wCAAA,CACA,+DAAA,CACA,4BAAA,CACA,6BAAA,CARA,iBAAA,CAIA,eAAA,CADA,eAAA,CAFA,cAAA,CACA,oCAAA,CAHA,iBhC0iGJ,CgC9hGI,6BACE,YhCgiGN,CgC7hGM,kCACE,wBAAA,CACA,yBhC+hGR,CgCzhGE,iCAWE,wCAAA,CACA,+DAAA,CAFA,uCAAA,CAGA,0BAAA,CAPA,UAAA,CAJA,oBAAA,CAMA,2BAAA,CADA,2BAAA,CAEA,2BAAA,CARA,uBAAA,CAAA,eAAA,CAaA,wBAAA,CAAA,qBAAA,CAAA,oBAAA,CAAA,gBAAA,CATA,ShCkiGJ,CgChhGE,sBACE,iBAAA,CACA,iBhCkhGJ,CgC1gGI,sCACE,gBhC4gGN,CgCxgGI,gDACE,YhC0gGN,CgChgGA,gBACE,iBhCmgGF,CgC//FE,uCACE,aAAA,CACA,ShCigGJ,CgCngGE,oCACE,aAAA,CACA,ShCigGJ,CgCngGE,8BACE,aAAA,CACA,ShCigGJ,CgC5/FE,mBACE,YhC8/FJ,CgCz/FE,oBACE,QhC2/FJ,CgCv/FE,4BACE,WAAA,CACA,SAAA,CACA,ehCy/FJ,CgCt/FI,0CACE,YhCw/FN,CgCl/FE,yBAIE,wCAAA,CAEA,+BAAA,CADA,4BAAA,CAFA,eAAA,CADA,oDAAA,CAKA,wBAAA,CAAA,qBAAA,CAAA,oBAAA,CAAA,gBhCo/FJ,CgCh/FE,2BAEE,+DAAA,CADA,2BhCm/FJ,CgC/+FI,+BACE,uCAAA,CACA,gBhCi/FN,CgC5+FE,sBACE,MAAA,CACA,WhC8+FJ,CgCz+FA,aACE,ahC4+FF,CgCl+FE,4BAEE,aAAA,CADA,YhCs+FJ,CgCl+FI,wDAEE,2BAAA,CADA,wBhCq+FN,CgC/9FE,+BAKE,2CAAA,CAEA,+BAAA,CADA,gCAAA,CADA,sBAAA,CAJA,mBAAA,CAEA,gBAAA,CADA,ahCs+FJ,CgC99FI,qCAEE,UAAA,CACA,UAAA,CAFA,ahCk+FN,CKnmGI,wC2BgJF,8BACE,iBhCu9FF,CgC78FE,wSAGE,ehCm9FJ,CgC/8FE,sCAEE,mBAAA,CACA,eAAA,CADA,oBAAA,CADA,kBAAA,CAAA,mBhCm9FJ,CACF,CD1yGI,kDAIE,+BAAA,CACA,8BAAA,CAFA,aAAA,CADA,QAAA,CADA,iBCgzGN,CDjzGI,+CAIE,+BAAA,CACA,8BAAA,CAFA,aAAA,CADA,QAAA,CADA,iBCgzGN,CDjzGI,yCAIE,+BAAA,CACA,8BAAA,CAFA,aAAA,CADA,QAAA,CADA,iBCgzGN,CDxyGI,uBAEE,uCAAA,CADA,cC2yGN,CDtvGM,iHAEE,WAlDkB,CAiDlB,kBCiwGR,CDlwGM,6HAEE,WAlDkB,CAiDlB,kBC6wGR,CD9wGM,6HAEE,WAlDkB,CAiDlB,kBCyxGR,CD1xGM,oHAEE,WAlDkB,CAiDlB,kBCqyGR,CDtyGM,0HAEE,WAlDkB,CAiDlB,kBCizGR,CDlzGM,uHAEE,WAlDkB,CAiDlB,kBC6zGR,CD9zGM,uHAEE,WAlDkB,CAiDlB,kBCy0GR,CD10GM,6HAEE,WAlDkB,CAiDlB,kBCq1GR,CDt1GM,yCAEE,WAlDkB,CAiDlB,kBCy1GR,CD11GM,yCAEE,WAlDkB,CAiDlB,kBC61GR,CD91GM,0CAEE,WAlDkB,CAiDlB,kBCi2GR,CDl2GM,uCAEE,WAlDkB,CAiDlB,kBCq2GR,CDt2GM,wCAEE,WAlDkB,CAiDlB,kBCy2GR,CD12GM,sCAEE,WAlDkB,CAiDlB,kBC62GR,CD92GM,wCAEE,WAlDkB,CAiDlB,kBCi3GR,CDl3GM,oCAEE,WAlDkB,CAiDlB,kBCq3GR,CDt3GM,2CAEE,WAlDkB,CAiDlB,kBCy3GR,CD13GM,qCAEE,WAlDkB,CAiDlB,kBC63GR,CD93GM,oCAEE,WAlDkB,CAiDlB,kBCi4GR,CDl4GM,kCAEE,WAlDkB,CAiDlB,kBCq4GR,CDt4GM,qCAEE,WAlDkB,CAiDlB,kBCy4GR,CD14GM,mCAEE,WAlDkB,CAiDlB,kBC64GR,CD94GM,qCAEE,WAlDkB,CAiDlB,kBCi5GR,CDl5GM,wCAEE,WAlDkB,CAiDlB,kBCq5GR,CDt5GM,sCAEE,WAlDkB,CAiDlB,kBCy5GR,CD15GM,2CAEE,WAlDkB,CAiDlB,kBC65GR,CDl5GM,iCAEE,WAPkB,CAMlB,iBCq5GR,CDt5GM,uCAEE,WAPkB,CAMlB,iBCy5GR,CD15GM,mCAEE,WAPkB,CAMlB,iBC65GR,CiC5+GE,wBAKE,mBAAA,CAHA,YAAA,CACA,qBAAA,CACA,YAAA,CAHA,iBjCm/GJ,CiCz+GI,8BAGE,QAAA,CACA,SAAA,CAHA,iBAAA,CACA,OjC6+GN,CiCx+GM,qCACE,0BjC0+GR,CiC38GE,2BAME,uBAAA,CAFA,+DAAA,CAHA,YAAA,CACA,cAAA,CACA,aAAA,CAEA,gCAAA,CAAA,4BAAA,CAEA,oBjC68GJ,CiC18GI,aAVF,2BAWI,gBjC68GJ,CACF,CiC18GI,cAGE,+BACE,iBjC08GN,CiCv8GM,sCAOE,oCAAA,CALA,QAAA,CAWA,UAAA,CATA,aAAA,CAEA,UAAA,CAHA,MAAA,CAFA,iBAAA,CAOA,2CAAA,CACA,qCACE,CAEF,kDAAA,CAPA,+BjC+8GR,CACF,CiCl8GI,8CACE,YjCo8GN,CiCh8GI,iCAQE,qCAAA,CAEA,6BAAA,CANA,uCAAA,CAOA,cAAA,CAVA,aAAA,CAKA,gBAAA,CADA,eAAA,CAFA,8BAAA,CAMA,uBAAA,CAGA,2CACE,CANF,kBAAA,CALA,UjC48GN,CiC77GM,aAII,6CACE,OjC47GV,CiC77GQ,8CACE,OjC+7GV,CiCh8GQ,8CACE,OjCk8GV,CiCn8GQ,8CACE,OjCq8GV,CiCt8GQ,8CACE,OjCw8GV,CiCz8GQ,8CACE,OjC28GV,CiC58GQ,8CACE,OjC88GV,CiC/8GQ,8CACE,OjCi9GV,CiCl9GQ,8CACE,OjCo9GV,CiCr9GQ,+CACE,QjCu9GV,CiCx9GQ,+CACE,QjC09GV,CiC39GQ,+CACE,QjC69GV,CiC99GQ,+CACE,QjCg+GV,CiCj+GQ,+CACE,QjCm+GV,CiCp+GQ,+CACE,QjCs+GV,CiCv+GQ,+CACE,QjCy+GV,CiC1+GQ,+CACE,QjC4+GV,CiC7+GQ,+CACE,QjC++GV,CiCh/GQ,+CACE,QjCk/GV,CiCn/GQ,+CACE,QjCq/GV,CACF,CiCh/GM,uCACE,+BjCk/GR,CiC5+GE,4BACE,UjC8+GJ,CiC3+GI,aAJF,4BAKI,gBjC8+GJ,CACF,CiC1+GE,0BACE,YjC4+GJ,CiCz+GI,aAJF,0BAKI,ajC4+GJ,CiCx+GM,sCACE,OjC0+GR,CiC3+GM,uCACE,OjC6+GR,CiC9+GM,uCACE,OjCg/GR,CiCj/GM,uCACE,OjCm/GR,CiCp/GM,uCACE,OjCs/GR,CiCv/GM,uCACE,OjCy/GR,CiC1/GM,uCACE,OjC4/GR,CiC7/GM,uCACE,OjC+/GR,CiChgHM,uCACE,OjCkgHR,CiCngHM,wCACE,QjCqgHR,CiCtgHM,wCACE,QjCwgHR,CiCzgHM,wCACE,QjC2gHR,CiC5gHM,wCACE,QjC8gHR,CiC/gHM,wCACE,QjCihHR,CiClhHM,wCACE,QjCohHR,CiCrhHM,wCACE,QjCuhHR,CiCxhHM,wCACE,QjC0hHR,CiC3hHM,wCACE,QjC6hHR,CiC9hHM,wCACE,QjCgiHR,CiCjiHM,wCACE,QjCmiHR,CACF,CiC7hHI,+FAEE,QjC+hHN,CiC5hHM,yGACE,wBAAA,CACA,yBjC+hHR,CiCthHM,2DAEE,wBAAA,CACA,yBAAA,CAFA,QjC0hHR,CiCnhHM,iEACE,QjCqhHR,CiClhHQ,qLAGE,wBAAA,CACA,yBAAA,CAFA,QjCshHV,CiChhHQ,6FACE,wBAAA,CACA,yBjCkhHV,CiC7gHM,yDACE,kBjC+gHR,CiC1gHI,sCACE,QjC4gHN,CKtiHI,wC4BuCF,wDAGE,kBjCogHF,CiCvgHA,wDAGE,mBjCogHF,CiCvgHA,8CAEE,eAAA,CADA,eAAA,CAGA,iCjCmgHF,CiC//GE,8DACE,mBjCkgHJ,CiCngHE,8DACE,kBjCkgHJ,CiCngHE,oDAEE,UjCigHJ,CACF,CiCr/GE,cAHF,olDAII,+BjCw/GF,CiCr/GE,g8GACE,sCjCu/GJ,CACF,CiCl/GA,4sDACE,uDjCq/GF,CiCj/GA,wmDACE,ajCo/GF,CkC5vHA,MACE,mVAAA,CAEA,4VlCgwHF,CkCtvHE,4BAEE,oBAAA,CADA,iBlC0vHJ,CkCrvHI,sDAGE,SlCuvHN,CkC1vHI,sDAGE,UlCuvHN,CkC1vHI,4CACE,iBAAA,CACA,SlCwvHN,CkClvHE,+CAEE,SAAA,CADA,UlCqvHJ,CkChvHE,kDAGE,WlCyvHJ,CkC5vHE,kDAGE,YlCyvHJ,CkC5vHE,wCAME,qDAAA,CAIA,UAAA,CALA,aAAA,CAEA,0CAAA,CAAA,kCAAA,CACA,6BAAA,CAAA,qBAAA,CACA,yBAAA,CAAA,iBAAA,CARA,iBAAA,CACA,SAAA,CAEA,YlCwvHJ,CkC9uHE,gEACE,wBT0Wa,CSzWb,mDAAA,CAAA,2ClCgvHJ,CmCjyHA,QACE,8DAAA,CAGA,+CAAA,CACA,iEAAA,CACA,oDAAA,CACA,sDAAA,CACA,mDnCkyHF,CmC9xHA,SAEE,kBAAA,CADA,YnCkyHF,CKzoHI,mC+BhKA,8BAIE,kBpC8yHJ,CoClzHE,8BAIE,iBpC8yHJ,CoClzHE,oBACE,UAAA,CAIA,mBAAA,CAFA,YAAA,CADA,apCgzHJ,CoC1yHI,8BACE,WpC4yHN,CoCxyHI,kCAEE,iBAAA,CAAA,cpC0yHN,CoC5yHI,kCAEE,aAAA,CAAA,kBpC0yHN,CoC5yHI,wBACE,WpC2yHN,CoCvyHM,kCACE,UpCyyHR,CACF","file":"main.css"}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/palette.2505c338.min.css b/7.3/assets/stylesheets/palette.2505c338.min.css
new file mode 100644
index 0000000000..3c005dd683
--- /dev/null
+++ b/7.3/assets/stylesheets/palette.2505c338.min.css
@@ -0,0 +1 @@
+@media screen{[data-md-color-scheme=slate]{--md-hue:232;--md-default-fg-color:hsla(var(--md-hue),75%,95%,1);--md-default-fg-color--light:hsla(var(--md-hue),75%,90%,0.62);--md-default-fg-color--lighter:hsla(var(--md-hue),75%,90%,0.32);--md-default-fg-color--lightest:hsla(var(--md-hue),75%,90%,0.12);--md-default-bg-color:hsla(var(--md-hue),15%,21%,1);--md-default-bg-color--light:hsla(var(--md-hue),15%,21%,0.54);--md-default-bg-color--lighter:hsla(var(--md-hue),15%,21%,0.26);--md-default-bg-color--lightest:hsla(var(--md-hue),15%,21%,0.07);--md-code-fg-color:hsla(var(--md-hue),18%,86%,1);--md-code-bg-color:hsla(var(--md-hue),15%,15%,1);--md-code-hl-color:#4287ff26;--md-code-hl-number-color:#e6695b;--md-code-hl-special-color:#f06090;--md-code-hl-function-color:#c973d9;--md-code-hl-constant-color:#9383e2;--md-code-hl-keyword-color:#6791e0;--md-code-hl-string-color:#2fb170;--md-code-hl-name-color:var(--md-code-fg-color);--md-code-hl-operator-color:var(--md-default-fg-color--light);--md-code-hl-punctuation-color:var(--md-default-fg-color--light);--md-code-hl-comment-color:var(--md-default-fg-color--light);--md-code-hl-generic-color:var(--md-default-fg-color--light);--md-code-hl-variable-color:var(--md-default-fg-color--light);--md-typeset-color:var(--md-default-fg-color);--md-typeset-a-color:var(--md-primary-fg-color);--md-typeset-mark-color:#4287ff4d;--md-typeset-kbd-color:hsla(var(--md-hue),15%,94%,0.12);--md-typeset-kbd-accent-color:hsla(var(--md-hue),15%,94%,0.2);--md-typeset-kbd-border-color:hsla(var(--md-hue),15%,14%,1);--md-typeset-table-color:hsla(var(--md-hue),75%,95%,0.12);--md-admonition-fg-color:var(--md-default-fg-color);--md-admonition-bg-color:var(--md-default-bg-color);--md-footer-bg-color:hsla(var(--md-hue),15%,12%,0.87);--md-footer-bg-color--dark:hsla(var(--md-hue),15%,10%,1);--md-shadow-z1:0 0.2rem 0.5rem #0003,0 0 0.05rem #0000001a;--md-shadow-z2:0 0.2rem 0.5rem #0000004d,0 0 0.05rem #00000040;--md-shadow-z3:0 0.2rem 0.5rem #0006,0 0 0.05rem #00000059}[data-md-color-scheme=slate] img[src$="#gh-light-mode-only"],[data-md-color-scheme=slate] img[src$="#only-light"]{display:none}[data-md-color-scheme=slate] img[src$="#gh-dark-mode-only"],[data-md-color-scheme=slate] img[src$="#only-dark"]{display:initial}[data-md-color-scheme=slate][data-md-color-primary=pink]{--md-typeset-a-color:#ed5487}[data-md-color-scheme=slate][data-md-color-primary=purple]{--md-typeset-a-color:#bd78c9}[data-md-color-scheme=slate][data-md-color-primary=deep-purple]{--md-typeset-a-color:#a682e3}[data-md-color-scheme=slate][data-md-color-primary=indigo]{--md-typeset-a-color:#6c91d5}[data-md-color-scheme=slate][data-md-color-primary=teal]{--md-typeset-a-color:#00ccb8}[data-md-color-scheme=slate][data-md-color-primary=green]{--md-typeset-a-color:#71c174}[data-md-color-scheme=slate][data-md-color-primary=deep-orange]{--md-typeset-a-color:#ff9575}[data-md-color-scheme=slate][data-md-color-primary=brown]{--md-typeset-a-color:#c7846b}[data-md-color-scheme=slate][data-md-color-primary=black],[data-md-color-scheme=slate][data-md-color-primary=blue-grey],[data-md-color-scheme=slate][data-md-color-primary=grey],[data-md-color-scheme=slate][data-md-color-primary=white]{--md-typeset-a-color:#6c91d5}[data-md-color-switching] *,[data-md-color-switching] :after,[data-md-color-switching] :before{transition-duration:0ms!important}}[data-md-color-accent=red]{--md-accent-fg-color:#ff1947;--md-accent-fg-color--transparent:#ff19471a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=pink]{--md-accent-fg-color:#f50056;--md-accent-fg-color--transparent:#f500561a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=purple]{--md-accent-fg-color:#df41fb;--md-accent-fg-color--transparent:#df41fb1a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=deep-purple]{--md-accent-fg-color:#7c4dff;--md-accent-fg-color--transparent:#7c4dff1a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=indigo]{--md-accent-fg-color:#526cfe;--md-accent-fg-color--transparent:#526cfe1a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=blue]{--md-accent-fg-color:#4287ff;--md-accent-fg-color--transparent:#4287ff1a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=light-blue]{--md-accent-fg-color:#0091eb;--md-accent-fg-color--transparent:#0091eb1a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=cyan]{--md-accent-fg-color:#00bad6;--md-accent-fg-color--transparent:#00bad61a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=teal]{--md-accent-fg-color:#00bda4;--md-accent-fg-color--transparent:#00bda41a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=green]{--md-accent-fg-color:#00c753;--md-accent-fg-color--transparent:#00c7531a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=light-green]{--md-accent-fg-color:#63de17;--md-accent-fg-color--transparent:#63de171a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-accent=lime]{--md-accent-fg-color:#b0eb00;--md-accent-fg-color--transparent:#b0eb001a;--md-accent-bg-color:#000000de;--md-accent-bg-color--light:#0000008a}[data-md-color-accent=yellow]{--md-accent-fg-color:#ffd500;--md-accent-fg-color--transparent:#ffd5001a;--md-accent-bg-color:#000000de;--md-accent-bg-color--light:#0000008a}[data-md-color-accent=amber]{--md-accent-fg-color:#fa0;--md-accent-fg-color--transparent:#ffaa001a;--md-accent-bg-color:#000000de;--md-accent-bg-color--light:#0000008a}[data-md-color-accent=orange]{--md-accent-fg-color:#ff9100;--md-accent-fg-color--transparent:#ff91001a;--md-accent-bg-color:#000000de;--md-accent-bg-color--light:#0000008a}[data-md-color-accent=deep-orange]{--md-accent-fg-color:#ff6e42;--md-accent-fg-color--transparent:#ff6e421a;--md-accent-bg-color:#fff;--md-accent-bg-color--light:#ffffffb3}[data-md-color-primary=red]{--md-primary-fg-color:#ef5552;--md-primary-fg-color--light:#e57171;--md-primary-fg-color--dark:#e53734;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=pink]{--md-primary-fg-color:#e92063;--md-primary-fg-color--light:#ec417a;--md-primary-fg-color--dark:#c3185d;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=purple]{--md-primary-fg-color:#ab47bd;--md-primary-fg-color--light:#bb69c9;--md-primary-fg-color--dark:#8c24a8;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=deep-purple]{--md-primary-fg-color:#7e56c2;--md-primary-fg-color--light:#9574cd;--md-primary-fg-color--dark:#673ab6;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=indigo]{--md-primary-fg-color:#4051b5;--md-primary-fg-color--light:#5d6cc0;--md-primary-fg-color--dark:#303fa1;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=blue]{--md-primary-fg-color:#2094f3;--md-primary-fg-color--light:#42a5f5;--md-primary-fg-color--dark:#1975d2;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=light-blue]{--md-primary-fg-color:#02a6f2;--md-primary-fg-color--light:#28b5f6;--md-primary-fg-color--dark:#0287cf;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=cyan]{--md-primary-fg-color:#00bdd6;--md-primary-fg-color--light:#25c5da;--md-primary-fg-color--dark:#0097a8;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=teal]{--md-primary-fg-color:#009485;--md-primary-fg-color--light:#26a699;--md-primary-fg-color--dark:#007a6c;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=green]{--md-primary-fg-color:#4cae4f;--md-primary-fg-color--light:#68bb6c;--md-primary-fg-color--dark:#398e3d;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=light-green]{--md-primary-fg-color:#8bc34b;--md-primary-fg-color--light:#9ccc66;--md-primary-fg-color--dark:#689f38;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=lime]{--md-primary-fg-color:#cbdc38;--md-primary-fg-color--light:#d3e156;--md-primary-fg-color--dark:#b0b52c;--md-primary-bg-color:#000000de;--md-primary-bg-color--light:#0000008a}[data-md-color-primary=yellow]{--md-primary-fg-color:#ffec3d;--md-primary-fg-color--light:#ffee57;--md-primary-fg-color--dark:#fbc02d;--md-primary-bg-color:#000000de;--md-primary-bg-color--light:#0000008a}[data-md-color-primary=amber]{--md-primary-fg-color:#ffc105;--md-primary-fg-color--light:#ffc929;--md-primary-fg-color--dark:#ffa200;--md-primary-bg-color:#000000de;--md-primary-bg-color--light:#0000008a}[data-md-color-primary=orange]{--md-primary-fg-color:#ffa724;--md-primary-fg-color--light:#ffa724;--md-primary-fg-color--dark:#fa8900;--md-primary-bg-color:#000000de;--md-primary-bg-color--light:#0000008a}[data-md-color-primary=deep-orange]{--md-primary-fg-color:#ff6e42;--md-primary-fg-color--light:#ff8a66;--md-primary-fg-color--dark:#f4511f;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=brown]{--md-primary-fg-color:#795649;--md-primary-fg-color--light:#8d6e62;--md-primary-fg-color--dark:#5d4037;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3}[data-md-color-primary=grey]{--md-primary-fg-color:#757575;--md-primary-fg-color--light:#9e9e9e;--md-primary-fg-color--dark:#616161;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3;--md-typeset-a-color:#4051b5}[data-md-color-primary=blue-grey]{--md-primary-fg-color:#546d78;--md-primary-fg-color--light:#607c8a;--md-primary-fg-color--dark:#455a63;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3;--md-typeset-a-color:#4051b5}[data-md-color-primary=light-green]:not([data-md-color-scheme=slate]){--md-typeset-a-color:#72ad2e}[data-md-color-primary=lime]:not([data-md-color-scheme=slate]){--md-typeset-a-color:#8b990a}[data-md-color-primary=yellow]:not([data-md-color-scheme=slate]){--md-typeset-a-color:#b8a500}[data-md-color-primary=amber]:not([data-md-color-scheme=slate]){--md-typeset-a-color:#d19d00}[data-md-color-primary=orange]:not([data-md-color-scheme=slate]){--md-typeset-a-color:#e68a00}[data-md-color-primary=white]{--md-primary-fg-color:#fff;--md-primary-fg-color--light:#ffffffb3;--md-primary-fg-color--dark:#00000012;--md-primary-bg-color:#000000de;--md-primary-bg-color--light:#0000008a;--md-typeset-a-color:#4051b5}[data-md-color-primary=white] .md-button{color:var(--md-typeset-a-color)}[data-md-color-primary=white] .md-button--primary{background-color:var(--md-typeset-a-color);border-color:var(--md-typeset-a-color);color:#fff}@media screen and (min-width:60em){[data-md-color-primary=white] .md-search__form{background-color:#00000012}[data-md-color-primary=white] .md-search__form:hover{background-color:#00000052}[data-md-color-primary=white] .md-search__input+.md-search__icon{color:#000000de}}@media screen and (min-width:76.25em){[data-md-color-primary=white] .md-tabs{border-bottom:.05rem solid #00000012}}[data-md-color-primary=black]{--md-primary-fg-color:#000;--md-primary-fg-color--light:#0000008a;--md-primary-fg-color--dark:#000;--md-primary-bg-color:#fff;--md-primary-bg-color--light:#ffffffb3;--md-typeset-a-color:#4051b5}[data-md-color-primary=black] .md-button{color:var(--md-typeset-a-color)}[data-md-color-primary=black] .md-button--primary{background-color:var(--md-typeset-a-color);border-color:var(--md-typeset-a-color);color:#fff}[data-md-color-primary=black] .md-header{background-color:#000}@media screen and (max-width:59.9375em){[data-md-color-primary=black] .md-nav__source{background-color:#000000de}}@media screen and (min-width:60em){[data-md-color-primary=black] .md-search__form{background-color:#ffffff1f}[data-md-color-primary=black] .md-search__form:hover{background-color:#ffffff4d}}@media screen and (max-width:76.1875em){html [data-md-color-primary=black] .md-nav--primary .md-nav__title[for=__drawer]{background-color:#000}}@media screen and (min-width:76.25em){[data-md-color-primary=black] .md-tabs{background-color:#000}}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/palette.2505c338.min.css.map b/7.3/assets/stylesheets/palette.2505c338.min.css.map
new file mode 100644
index 0000000000..3aec190345
--- /dev/null
+++ b/7.3/assets/stylesheets/palette.2505c338.min.css.map
@@ -0,0 +1 @@
+{"version":3,"sources":["src/assets/stylesheets/palette/_scheme.scss","../../../src/assets/stylesheets/palette.scss","src/assets/stylesheets/palette/_accent.scss","src/assets/stylesheets/palette/_primary.scss","src/assets/stylesheets/utilities/_break.scss"],"names":[],"mappings":"AA2BA,cAGE,6BAKE,YAAA,CAGA,mDAAA,CACA,6DAAA,CACA,+DAAA,CACA,gEAAA,CACA,mDAAA,CACA,6DAAA,CACA,+DAAA,CACA,gEAAA,CAGA,gDAAA,CACA,gDAAA,CAGA,4BAAA,CACA,iCAAA,CACA,kCAAA,CACA,mCAAA,CACA,mCAAA,CACA,kCAAA,CACA,iCAAA,CACA,+CAAA,CACA,6DAAA,CACA,gEAAA,CACA,4DAAA,CACA,4DAAA,CACA,6DAAA,CAGA,6CAAA,CAGA,+CAAA,CAGA,iCAAA,CAGA,uDAAA,CACA,6DAAA,CACA,2DAAA,CAGA,yDAAA,CAGA,mDAAA,CACA,mDAAA,CAGA,qDAAA,CACA,wDAAA,CAGA,0DAAA,CAKA,8DAAA,CAKA,0DCxDF,CD6DE,kHAEE,YC3DJ,CD+DE,gHAEE,eC7DJ,CDoFE,yDACE,4BClFJ,CDiFE,2DACE,4BC/EJ,CD8EE,gEACE,4BC5EJ,CD2EE,2DACE,4BCzEJ,CDwEE,yDACE,4BCtEJ,CDqEE,0DACE,4BCnEJ,CDkEE,gEACE,4BChEJ,CD+DE,0DACE,4BC7DJ,CD4DE,2OACE,4BCjDJ,CDwDA,+FAGE,iCCtDF,CACF,CCjDE,2BACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCD6CN,CCvDE,4BACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCDoDN,CC9DE,8BACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCD2DN,CCrEE,mCACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCDkEN,CC5EE,8BACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCDyEN,CCnFE,4BACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCDgFN,CC1FE,kCACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCDuFN,CCjGE,4BACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCD8FN,CCxGE,4BACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCDqGN,CC/GE,6BACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCD4GN,CCtHE,mCACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCDmHN,CC7HE,4BACE,4BAAA,CACA,2CAAA,CAIE,8BAAA,CACA,qCD6HN,CCpIE,8BACE,4BAAA,CACA,2CAAA,CAIE,8BAAA,CACA,qCDoIN,CC3IE,6BACE,yBAAA,CACA,2CAAA,CAIE,8BAAA,CACA,qCD2IN,CClJE,8BACE,4BAAA,CACA,2CAAA,CAIE,8BAAA,CACA,qCDkJN,CCzJE,mCACE,4BAAA,CACA,2CAAA,CAOE,yBAAA,CACA,qCDsJN,CE3JE,4BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFwJN,CEnKE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFgKN,CE3KE,+BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFwKN,CEnLE,oCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFgLN,CE3LE,+BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFwLN,CEnME,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFgMN,CE3ME,mCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFwMN,CEnNE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFgNN,CE3NE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFwNN,CEnOE,8BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFgON,CE3OE,oCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFwON,CEnPE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAIE,+BAAA,CACA,sCFmPN,CE3PE,+BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAIE,+BAAA,CACA,sCF2PN,CEnQE,8BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAIE,+BAAA,CACA,sCFmQN,CE3QE,+BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAIE,+BAAA,CACA,sCF2QN,CEnRE,oCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFgRN,CE3RE,8BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCFwRN,CEnSE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCAAA,CAKA,4BF4RN,CE5SE,kCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,sCAAA,CAKA,4BFqSN,CEtRE,sEACE,4BFyRJ,CE1RE,+DACE,4BF6RJ,CE9RE,iEACE,4BFiSJ,CElSE,gEACE,4BFqSJ,CEtSE,iEACE,4BFySJ,CEhSA,8BACE,0BAAA,CACA,sCAAA,CACA,qCAAA,CACA,+BAAA,CACA,sCAAA,CAGA,4BFiSF,CE9RE,yCACE,+BFgSJ,CE7RI,kDAEE,0CAAA,CACA,sCAAA,CAFA,UFiSN,CG7MI,mCD1EA,+CACE,0BF0RJ,CEvRI,qDACE,0BFyRN,CEpRE,iEACE,eFsRJ,CACF,CGxNI,sCDvDA,uCACE,oCFkRJ,CACF,CEzQA,8BACE,0BAAA,CACA,sCAAA,CACA,gCAAA,CACA,0BAAA,CACA,sCAAA,CAGA,4BF0QF,CEvQE,yCACE,+BFyQJ,CEtQI,kDAEE,0CAAA,CACA,sCAAA,CAFA,UF0QN,CEnQE,yCACE,qBFqQJ,CG9NI,wCDhCA,8CACE,0BFiQJ,CACF,CGtPI,mCDJA,+CACE,0BF6PJ,CE1PI,qDACE,0BF4PN,CACF,CG3OI,wCDTA,iFACE,qBFuPJ,CACF,CGnQI,sCDmBA,uCACE,qBFmPJ,CACF","file":"palette.css"}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/palette.cc9b2e1e.min.css b/7.3/assets/stylesheets/palette.cc9b2e1e.min.css
deleted file mode 100755
index d0fd19a25e..0000000000
--- a/7.3/assets/stylesheets/palette.cc9b2e1e.min.css
+++ /dev/null
@@ -1 +0,0 @@
-[data-md-color-accent=red]{--md-accent-fg-color:#ff1947;--md-accent-fg-color--transparent:rgba(255,25,71,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=pink]{--md-accent-fg-color:#f50056;--md-accent-fg-color--transparent:rgba(245,0,86,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=purple]{--md-accent-fg-color:#df41fb;--md-accent-fg-color--transparent:rgba(223,65,251,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=deep-purple]{--md-accent-fg-color:#7c4dff;--md-accent-fg-color--transparent:rgba(124,77,255,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=indigo]{--md-accent-fg-color:#526cfe;--md-accent-fg-color--transparent:rgba(82,108,254,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=blue]{--md-accent-fg-color:#4287ff;--md-accent-fg-color--transparent:rgba(66,135,255,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=light-blue]{--md-accent-fg-color:#0091eb;--md-accent-fg-color--transparent:rgba(0,145,235,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=cyan]{--md-accent-fg-color:#00bad6;--md-accent-fg-color--transparent:rgba(0,186,214,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=teal]{--md-accent-fg-color:#00bda4;--md-accent-fg-color--transparent:rgba(0,189,164,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=green]{--md-accent-fg-color:#00c753;--md-accent-fg-color--transparent:rgba(0,199,83,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=light-green]{--md-accent-fg-color:#63de17;--md-accent-fg-color--transparent:rgba(99,222,23,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-accent=lime]{--md-accent-fg-color:#b0eb00;--md-accent-fg-color--transparent:rgba(176,235,0,.1);--md-accent-bg-color:rgba(0,0,0,.87);--md-accent-bg-color--light:rgba(0,0,0,.54)}[data-md-color-accent=yellow]{--md-accent-fg-color:#ffd500;--md-accent-fg-color--transparent:rgba(255,213,0,.1);--md-accent-bg-color:rgba(0,0,0,.87);--md-accent-bg-color--light:rgba(0,0,0,.54)}[data-md-color-accent=amber]{--md-accent-fg-color:#fa0;--md-accent-fg-color--transparent:rgba(255,170,0,.1);--md-accent-bg-color:rgba(0,0,0,.87);--md-accent-bg-color--light:rgba(0,0,0,.54)}[data-md-color-accent=orange]{--md-accent-fg-color:#ff9100;--md-accent-fg-color--transparent:rgba(255,145,0,.1);--md-accent-bg-color:rgba(0,0,0,.87);--md-accent-bg-color--light:rgba(0,0,0,.54)}[data-md-color-accent=deep-orange]{--md-accent-fg-color:#ff6e42;--md-accent-fg-color--transparent:rgba(255,110,66,.1);--md-accent-bg-color:#fff;--md-accent-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=red]{--md-primary-fg-color:#ef5552;--md-primary-fg-color--light:#e57171;--md-primary-fg-color--dark:#e53734;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=pink]{--md-primary-fg-color:#e92063;--md-primary-fg-color--light:#ec417a;--md-primary-fg-color--dark:#c3185d;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=purple]{--md-primary-fg-color:#ab47bd;--md-primary-fg-color--light:#bb69c9;--md-primary-fg-color--dark:#8c24a8;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=deep-purple]{--md-primary-fg-color:#7e56c2;--md-primary-fg-color--light:#9574cd;--md-primary-fg-color--dark:#673ab6;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=indigo]{--md-primary-fg-color:#4051b5;--md-primary-fg-color--light:#5d6cc0;--md-primary-fg-color--dark:#303fa1;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=blue]{--md-primary-fg-color:#2094f3;--md-primary-fg-color--light:#42a5f5;--md-primary-fg-color--dark:#1975d2;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=light-blue]{--md-primary-fg-color:#02a6f2;--md-primary-fg-color--light:#28b5f6;--md-primary-fg-color--dark:#0287cf;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=cyan]{--md-primary-fg-color:#00bdd6;--md-primary-fg-color--light:#25c5da;--md-primary-fg-color--dark:#0097a8;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=teal]{--md-primary-fg-color:#009485;--md-primary-fg-color--light:#26a699;--md-primary-fg-color--dark:#007a6c;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=green]{--md-primary-fg-color:#4cae4f;--md-primary-fg-color--light:#68bb6c;--md-primary-fg-color--dark:#398e3d;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=light-green]{--md-primary-fg-color:#8bc34b;--md-primary-fg-color--light:#9ccc66;--md-primary-fg-color--dark:#689f38;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=lime]{--md-primary-fg-color:#cbdc38;--md-primary-fg-color--light:#d3e156;--md-primary-fg-color--dark:#b0b52c;--md-primary-bg-color:rgba(0,0,0,.87);--md-primary-bg-color--light:rgba(0,0,0,.54)}[data-md-color-primary=yellow]{--md-primary-fg-color:#ffec3d;--md-primary-fg-color--light:#ffee57;--md-primary-fg-color--dark:#fbc02d;--md-primary-bg-color:rgba(0,0,0,.87);--md-primary-bg-color--light:rgba(0,0,0,.54)}[data-md-color-primary=amber]{--md-primary-fg-color:#ffc105;--md-primary-fg-color--light:#ffc929;--md-primary-fg-color--dark:#ffa200;--md-primary-bg-color:rgba(0,0,0,.87);--md-primary-bg-color--light:rgba(0,0,0,.54)}[data-md-color-primary=orange]{--md-primary-fg-color:#ffa724;--md-primary-fg-color--light:#ffa724;--md-primary-fg-color--dark:#fa8900;--md-primary-bg-color:rgba(0,0,0,.87);--md-primary-bg-color--light:rgba(0,0,0,.54)}[data-md-color-primary=deep-orange]{--md-primary-fg-color:#ff6e42;--md-primary-fg-color--light:#ff8a66;--md-primary-fg-color--dark:#f4511f;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=brown]{--md-primary-fg-color:#795649;--md-primary-fg-color--light:#8d6e62;--md-primary-fg-color--dark:#5d4037;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=grey]{--md-primary-fg-color:#757575;--md-primary-fg-color--light:#9e9e9e;--md-primary-fg-color--dark:#616161;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=blue-grey]{--md-primary-fg-color:#546d78;--md-primary-fg-color--light:#607c8a;--md-primary-fg-color--dark:#455a63;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7)}[data-md-color-primary=white]{--md-primary-fg-color:#fff;--md-primary-fg-color--light:hsla(0,0%,100%,.7);--md-primary-fg-color--dark:rgba(0,0,0,.07);--md-primary-bg-color:rgba(0,0,0,.87);--md-primary-bg-color--light:rgba(0,0,0,.54);--md-typeset-a-color:#4051b5}@media screen and (min-width:60em){[data-md-color-primary=white] .md-search__form{background-color:rgba(0,0,0,.07)}[data-md-color-primary=white] .md-search__form:hover{background-color:rgba(0,0,0,.32)}[data-md-color-primary=white] .md-search__input+.md-search__icon{color:rgba(0,0,0,.87)}}@media screen and (min-width:76.25em){[data-md-color-primary=white] .md-tabs{border-bottom:.05rem solid rgba(0,0,0,.07)}}[data-md-color-primary=black]{--md-primary-fg-color:#000;--md-primary-fg-color--light:rgba(0,0,0,.54);--md-primary-fg-color--dark:#000;--md-primary-bg-color:#fff;--md-primary-bg-color--light:hsla(0,0%,100%,.7);--md-typeset-a-color:#4051b5}[data-md-color-primary=black] .md-header{background-color:#000}@media screen and (max-width:59.9375em){[data-md-color-primary=black] .md-nav__source{background-color:rgba(0,0,0,.87)}}@media screen and (min-width:60em){[data-md-color-primary=black] .md-search__form{background-color:hsla(0,0%,100%,.12)}[data-md-color-primary=black] .md-search__form:hover{background-color:hsla(0,0%,100%,.3)}}@media screen and (max-width:76.1875em){html [data-md-color-primary=black] .md-nav--primary .md-nav__title[for=__drawer]{background-color:#000}}@media screen and (min-width:76.25em){[data-md-color-primary=black] .md-tabs{background-color:#000}}@media screen{[data-md-color-scheme=slate]{--md-hue:232;--md-default-fg-color:hsla(var(--md-hue),75%,95%,1);--md-default-fg-color--light:hsla(var(--md-hue),75%,90%,0.62);--md-default-fg-color--lighter:hsla(var(--md-hue),75%,90%,0.32);--md-default-fg-color--lightest:hsla(var(--md-hue),75%,90%,0.12);--md-default-bg-color:hsla(var(--md-hue),15%,21%,1);--md-default-bg-color--light:hsla(var(--md-hue),15%,21%,0.54);--md-default-bg-color--lighter:hsla(var(--md-hue),15%,21%,0.26);--md-default-bg-color--lightest:hsla(var(--md-hue),15%,21%,0.07);--md-code-fg-color:hsla(var(--md-hue),18%,86%,1);--md-code-bg-color:hsla(var(--md-hue),15%,15%,1);--md-code-hl-color:rgba(66,135,255,.15);--md-code-hl-number-color:#e6695b;--md-code-hl-special-color:#f06090;--md-code-hl-function-color:#c973d9;--md-code-hl-constant-color:#9383e2;--md-code-hl-keyword-color:#6791e0;--md-code-hl-string-color:#2fb170;--md-code-hl-name-color:var(--md-code-fg-color);--md-code-hl-operator-color:var(--md-default-fg-color--light);--md-code-hl-punctuation-color:var(--md-default-fg-color--light);--md-code-hl-comment-color:var(--md-default-fg-color--light);--md-code-hl-generic-color:var(--md-default-fg-color--light);--md-code-hl-variable-color:var(--md-default-fg-color--light);--md-typeset-color:var(--md-default-fg-color);--md-typeset-a-color:var(--md-primary-fg-color);--md-typeset-mark-color:rgba(66,135,255,.3);--md-typeset-kbd-color:hsla(var(--md-hue),15%,94%,0.12);--md-typeset-kbd-accent-color:hsla(var(--md-hue),15%,94%,0.2);--md-typeset-kbd-border-color:hsla(var(--md-hue),15%,14%,1);--md-typeset-table-color:hsla(var(--md-hue),75%,95%,0.12);--md-admonition-bg-color:hsla(var(--md-hue),0%,100%,0.025);--md-footer-bg-color:hsla(var(--md-hue),15%,12%,0.87);--md-footer-bg-color--dark:hsla(var(--md-hue),15%,10%,1)}[data-md-color-scheme=slate][data-md-color-primary=black],[data-md-color-scheme=slate][data-md-color-primary=white]{--md-typeset-a-color:#5d6cc0}[data-md-color-scheme=slate] img[src$="#gh-light-mode-only"],[data-md-color-scheme=slate] img[src$="#only-light"]{display:none}[data-md-color-scheme=slate] img[src$="#gh-dark-mode-only"],[data-md-color-scheme=slate] img[src$="#only-dark"]{display:initial}[data-md-color-switching] *,[data-md-color-switching] :after,[data-md-color-switching] :before{transition-duration:0ms!important}}
\ No newline at end of file
diff --git a/7.3/assets/stylesheets/palette.cc9b2e1e.min.css.map b/7.3/assets/stylesheets/palette.cc9b2e1e.min.css.map
deleted file mode 100755
index 46620900a8..0000000000
--- a/7.3/assets/stylesheets/palette.cc9b2e1e.min.css.map
+++ /dev/null
@@ -1 +0,0 @@
-{"version":3,"sources":["src/assets/stylesheets/palette/_accent.scss","../../../src/assets/stylesheets/palette.scss","src/assets/stylesheets/palette/_primary.scss","src/assets/stylesheets/utilities/_break.scss","src/assets/stylesheets/palette/_scheme.scss"],"names":[],"mappings":"AA8CE,2BACE,4BAAA,CACA,oDAAA,CAOE,yBAAA,CACA,8CCnDN,CDyCE,4BACE,4BAAA,CACA,mDAAA,CAOE,yBAAA,CACA,8CC5CN,CDkCE,8BACE,4BAAA,CACA,qDAAA,CAOE,yBAAA,CACA,8CCrCN,CD2BE,mCACE,4BAAA,CACA,qDAAA,CAOE,yBAAA,CACA,8CC9BN,CDoBE,8BACE,4BAAA,CACA,qDAAA,CAOE,yBAAA,CACA,8CCvBN,CDaE,4BACE,4BAAA,CACA,qDAAA,CAOE,yBAAA,CACA,8CChBN,CDME,kCACE,4BAAA,CACA,oDAAA,CAOE,yBAAA,CACA,8CCTN,CDDE,4BACE,4BAAA,CACA,oDAAA,CAOE,yBAAA,CACA,8CCFN,CDRE,4BACE,4BAAA,CACA,oDAAA,CAOE,yBAAA,CACA,8CCKN,CDfE,6BACE,4BAAA,CACA,mDAAA,CAOE,yBAAA,CACA,8CCYN,CDtBE,mCACE,4BAAA,CACA,oDAAA,CAOE,yBAAA,CACA,8CCmBN,CD7BE,4BACE,4BAAA,CACA,oDAAA,CAIE,oCAAA,CACA,2CC6BN,CDpCE,8BACE,4BAAA,CACA,oDAAA,CAIE,oCAAA,CACA,2CCoCN,CD3CE,6BACE,yBAAA,CACA,oDAAA,CAIE,oCAAA,CACA,2CC2CN,CDlDE,8BACE,4BAAA,CACA,oDAAA,CAIE,oCAAA,CACA,2CCkDN,CDzDE,mCACE,4BAAA,CACA,qDAAA,CAOE,yBAAA,CACA,8CCsDN,CC3DE,4BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDwDN,CCnEE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDgEN,CC3EE,+BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDwEN,CCnFE,oCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDgFN,CC3FE,+BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDwFN,CCnGE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDgGN,CC3GE,mCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDwGN,CCnHE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDgHN,CC3HE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDwHN,CCnIE,8BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDgIN,CC3IE,oCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDwIN,CCnJE,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAIE,qCAAA,CACA,4CDmJN,CC3JE,+BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAIE,qCAAA,CACA,4CD2JN,CCnKE,8BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAIE,qCAAA,CACA,4CDmKN,CC3KE,+BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAIE,qCAAA,CACA,4CD2KN,CCnLE,oCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDgLN,CC3LE,8BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDwLN,CCnME,6BACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDgMN,CC3ME,kCACE,6BAAA,CACA,oCAAA,CACA,mCAAA,CAOE,0BAAA,CACA,+CDwMN,CC9LA,8BACE,0BAAA,CACA,+CAAA,CACA,2CAAA,CACA,qCAAA,CACA,4CAAA,CAGA,4BD+LF,CE9EI,mCD3GA,+CACE,gCD4LJ,CCzLI,qDACE,gCD2LN,CCtLE,iEACE,qBDwLJ,CACF,CEzFI,sCDxFA,uCACE,0CDoLJ,CACF,CC3KA,8BACE,0BAAA,CACA,4CAAA,CACA,gCAAA,CACA,0BAAA,CACA,+CAAA,CAGA,4BD4KF,CCzKE,yCACE,qBD2KJ,CEvFI,wCD7EA,8CACE,gCDuKJ,CACF,CE/GI,mCDjDA,+CACE,oCDmKJ,CChKI,qDACE,mCDkKN,CACF,CEpGI,wCDtDA,iFACE,qBD6JJ,CACF,CE5HI,sCD1BA,uCACE,qBDyJJ,CACF,CGvSA,cAGE,6BAKE,YAAA,CAGA,mDAAA,CACA,6DAAA,CACA,+DAAA,CACA,gEAAA,CACA,mDAAA,CACA,6DAAA,CACA,+DAAA,CACA,gEAAA,CAGA,gDAAA,CACA,gDAAA,CAGA,uCAAA,CACA,iCAAA,CACA,kCAAA,CACA,mCAAA,CACA,mCAAA,CACA,kCAAA,CACA,iCAAA,CACA,+CAAA,CACA,6DAAA,CACA,gEAAA,CACA,4DAAA,CACA,4DAAA,CACA,6DAAA,CAGA,6CAAA,CAGA,+CAAA,CAGA,2CAAA,CAGA,uDAAA,CACA,6DAAA,CACA,2DAAA,CAGA,yDAAA,CAGA,0DAAA,CAGA,qDAAA,CACA,wDHgRF,CG7QE,oHAIE,4BH4QJ,CGxQE,kHAEE,YH0QJ,CGtQE,gHAEE,eHwQJ,CGnQA,+FAGE,iCHsQF,CACF","file":"palette.css"}
\ No newline at end of file
diff --git a/7.3/demos/docs-demo-timeline.js b/7.3/demos/docs-demo-timeline.js
old mode 100755
new mode 100644
index 8b92246afa..d621ca131a
--- a/7.3/demos/docs-demo-timeline.js
+++ b/7.3/demos/docs-demo-timeline.js
@@ -1,52 +1,52 @@
-function generateDocsDemoTimeline(timeline, setup_timeline) {
-  let setup;
-  if (setup_timeline) {
-    setup = {
-      timeline: setup_timeline,
-    };
-  }
-
-  const start = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: "",
-    choices: ["Run demo"],
-  };
-
-  let run = 0;
-
-  let trial = {
-    timeline: timeline,
-    data: {
-      run: () => {
-        return run;
-      },
-    },
-  };
-
-  const show_data = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: `
-      <p style="margin-bottom:0px; font-weight: bold;">Trial data:</p>
-      <pre style="margin-top:0px; text-align:left; font-size:14px; line-height:1.3em;"></pre>`,
-    on_load: function () {
-      const trial_data = jsPsych.data.get().filter({ run: run }).ignore("run").values();
-      const trial_json = JSON.stringify(trial_data, null, 2);
-      jsPsych.getDisplayElement().querySelector("pre").innerText = trial_json;
-    },
-    choices: ["Repeat demo"],
-  };
-
-  const trial_loop = {
-    timeline: [trial, show_data],
-    loop_function: function () {
-      run++;
-      return true;
-    },
-  };
-
-  if (setup_timeline) {
-    return [setup, start, trial_loop];
-  } else {
-    return [start, trial_loop];
-  }
-}
+function generateDocsDemoTimeline(timeline, setup_timeline) {
+  let setup;
+  if (setup_timeline) {
+    setup = {
+      timeline: setup_timeline,
+    };
+  }
+
+  const start = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: "",
+    choices: ["Run demo"],
+  };
+
+  let run = 0;
+
+  let trial = {
+    timeline: timeline,
+    data: {
+      run: () => {
+        return run;
+      },
+    },
+  };
+
+  const show_data = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: `
+      <p style="margin-bottom:0px; font-weight: bold;">Trial data:</p>
+      <pre style="margin-top:0px; text-align:left; font-size:14px; line-height:1.3em;"></pre>`,
+    on_load: function () {
+      const trial_data = jsPsych.data.get().filter({ run: run }).ignore("run").values();
+      const trial_json = JSON.stringify(trial_data, null, 2);
+      jsPsych.getDisplayElement().querySelector("pre").innerText = trial_json;
+    },
+    choices: ["Repeat demo"],
+  };
+
+  const trial_loop = {
+    timeline: [trial, show_data],
+    loop_function: function () {
+      run++;
+      return true;
+    },
+  };
+
+  if (setup_timeline) {
+    return [setup, start, trial_loop];
+  } else {
+    return [start, trial_loop];
+  }
+}
diff --git a/7.3/demos/docs-demo.css b/7.3/demos/docs-demo.css
old mode 100755
new mode 100644
diff --git a/7.3/demos/external_page.html b/7.3/demos/external_page.html
old mode 100755
new mode 100644
index 6f7a5f806b..525e75bf18
--- a/7.3/demos/external_page.html
+++ b/7.3/demos/external_page.html
@@ -1,12 +1,12 @@
-<div id="consent">
-  <p>
-    This is a demo experiment, with this minimal consent form being loaded
-    as an external html document. To continue, click the checkbox below
-    and hit "Start Experiment".
-  </p>
-  <p>
-    <input type="checkbox" id="consent_checkbox" />
-    I agree to take part in this study.
-  </p>
-  <button type="button" id="start">Start Experiment</button>
+<div id="consent">
+  <p>
+    This is a demo experiment, with this minimal consent form being loaded
+    as an external html document. To continue, click the checkbox below
+    and hit "Start Experiment".
+  </p>
+  <p>
+    <input type="checkbox" id="consent_checkbox" />
+    I agree to take part in this study.
+  </p>
+  <button type="button" id="start">Start Experiment</button>
 </div>
\ No newline at end of file
diff --git a/7.3/demos/eye-tracking-with-webgazer.html b/7.3/demos/eye-tracking-with-webgazer.html
old mode 100755
new mode 100644
index e8505b51de..53efb609c9
--- a/7.3/demos/eye-tracking-with-webgazer.html
+++ b/7.3/demos/eye-tracking-with-webgazer.html
@@ -1,171 +1,171 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.2"></script>
-    <script src="js/webgazer/webgazer.js"></script>
-    <script src="https://unpkg.com/@jspsych/extension-webgazer@1.0.2"></script>
-    <link
-      rel="stylesheet"
-      href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css"
-    />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-      var jsPsych = initJsPsych({
-        extensions: [
-            {type: jsPsychExtensionWebgazer}
-        ]
-      });
-
-      var preload = {
-        type: jsPsychPreload,
-        images: ['img/blue.png']
-      }
-
-      var camera_instructions = {
-        type: jsPsychHtmlButtonResponse,
-        stimulus: `
-          <p>In order to participate you must allow the experiment to use your camera.</p>
-          <p>You will be prompted to do this on the next screen.</p>
-          <p>If you do not wish to allow use of your camera, you cannot participate in this experiment.<p>
-          <p>It may take up to 30 seconds for the camera to initialize after you give permission.</p>
-        `,
-        choices: ['Got it'],
-      }
-
-      var init_camera = {
-        type: jsPsychWebgazerInitCamera
-      }
-
-      var calibration_instructions = {
-        type: jsPsychHtmlButtonResponse,
-        stimulus: `
-          <p>Now you'll calibrate the eye tracking, so that the software can use the image of your eyes to predict where you are looking.</p>
-          <p>You'll see a series of dots appear on the screen. Look at each dot and click on it.</p>
-        `,
-        choices: ['Got it'],
-      }
-
-      var calibration = {
-        type: jsPsychWebgazerCalibrate,
-        calibration_points: [
-          [25,25],[75,25],[50,50],[25,75],[75,75]
-        ],
-        repetitions_per_point: 2,
-        randomize_calibration_order: true
-      }
-
-      var validation_instructions = {
-        type: jsPsychHtmlButtonResponse,
-        stimulus: `
-          <p>Now we'll measure the accuracy of the calibration.</p>
-          <p>Look at each dot as it appears on the screen.</p>
-          <p style="font-weight: bold;">You do not need to click on the dots this time.</p>
-        `,
-        choices: ['Got it'],
-        post_trial_gap: 1000
-      }
-
-      var validation = {
-        type: jsPsychWebgazerValidate,
-        validation_points: [
-          [25,25],[75,25],[50,50],[25,75],[75,75]
-        ],
-        roi_radius: 200,
-        time_to_saccade: 1000,
-        validation_duration: 2000,
-        data: {
-          task: 'validate'
-        }
-      }
-
-      var recalibrate_instructions = {
-        type: jsPsychHtmlButtonResponse,
-        stimulus: `
-          <p>The accuracy of the calibration is a little lower than we'd like.</p>
-          <p>Let's try calibrating one more time.</p>
-          <p>On the next screen, look at the dots and click on them.<p>
-        `,
-        choices: ['OK'],
-      }
-
-      var recalibrate = {
-        timeline: [recalibrate_instructions, calibration, validation_instructions, validation],
-        conditional_function: function(){
-          var validation_data = jsPsych.data.get().filter({task: 'validate'}).values()[0];
-          return validation_data.percent_in_roi.some(function(x){
-            var minimum_percent_acceptable = 50;
-            return x < minimum_percent_acceptable;
-          });
-        },
-        data: {
-          phase: 'recalibration'
-        }
-      }
-
-      var calibration_done = {
-        type: jsPsychHtmlButtonResponse,
-        stimulus: `
-          <p>Great, we're done with calibration!</p>
-        `,
-        choices: ['OK']
-      }
-
-      var begin = {
-        type: jsPsychHtmKeyboardResponse,
-        stimulus: `<p>The next screen will show an image to demonstrate adding the webgazer extension to a trial.</p>
-          <p>Just look at the image while eye tracking data is collected. The trial will end automatically.</p>
-          <p>Press any key to start.</p>
-        `
-      }
-
-      const trial = {
-        type: jsPsychImageKeyboardResponse,
-        stimulus: 'img/blue.png',
-        choices: "NO_KEYS",
-        trial_duration: 2000,
-        extensions: [
-          {
-            type: jsPsychExtensionWebgazer, 
-            params: {targets: ['#jspsych-image-keyboard-response-stimulus']}
-          }
-        ]
-      }
-
-      var show_data = {
-        type: jsPsychHtmKeyboardResponse,
-        stimulus: function() {
-          var trial_data = jsPsych.data.getLastTrialData().values();
-          var trial_json = JSON.stringify(trial_data, null, 2);
-          return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
-            <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
-        },
-        choices: "NO_KEYS"
-      };
-      
-      jsPsych.run([
-          preload, 
-          camera_instructions, 
-          init_camera, 
-          calibration_instructions, 
-          calibration, 
-          validation_instructions, 
-          validation, 
-          recalibrate,
-          calibration_done,
-          begin, 
-          trial, 
-          show_data
-        ]);
-      
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.3"></script>
+    <script src="js/webgazer/webgazer.js"></script>
+    <script src="https://unpkg.com/@jspsych/extension-webgazer@1.0.3"></script>
+    <link
+      rel="stylesheet"
+      href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css"
+    />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+      var jsPsych = initJsPsych({
+        extensions: [
+            {type: jsPsychExtensionWebgazer}
+        ]
+      });
+
+      var preload = {
+        type: jsPsychPreload,
+        images: ['img/blue.png']
+      }
+
+      var camera_instructions = {
+        type: jsPsychHtmlButtonResponse,
+        stimulus: `
+          <p>In order to participate you must allow the experiment to use your camera.</p>
+          <p>You will be prompted to do this on the next screen.</p>
+          <p>If you do not wish to allow use of your camera, you cannot participate in this experiment.<p>
+          <p>It may take up to 30 seconds for the camera to initialize after you give permission.</p>
+        `,
+        choices: ['Got it'],
+      }
+
+      var init_camera = {
+        type: jsPsychWebgazerInitCamera
+      }
+
+      var calibration_instructions = {
+        type: jsPsychHtmlButtonResponse,
+        stimulus: `
+          <p>Now you'll calibrate the eye tracking, so that the software can use the image of your eyes to predict where you are looking.</p>
+          <p>You'll see a series of dots appear on the screen. Look at each dot and click on it.</p>
+        `,
+        choices: ['Got it'],
+      }
+
+      var calibration = {
+        type: jsPsychWebgazerCalibrate,
+        calibration_points: [
+          [25,25],[75,25],[50,50],[25,75],[75,75]
+        ],
+        repetitions_per_point: 2,
+        randomize_calibration_order: true
+      }
+
+      var validation_instructions = {
+        type: jsPsychHtmlButtonResponse,
+        stimulus: `
+          <p>Now we'll measure the accuracy of the calibration.</p>
+          <p>Look at each dot as it appears on the screen.</p>
+          <p style="font-weight: bold;">You do not need to click on the dots this time.</p>
+        `,
+        choices: ['Got it'],
+        post_trial_gap: 1000
+      }
+
+      var validation = {
+        type: jsPsychWebgazerValidate,
+        validation_points: [
+          [25,25],[75,25],[50,50],[25,75],[75,75]
+        ],
+        roi_radius: 200,
+        time_to_saccade: 1000,
+        validation_duration: 2000,
+        data: {
+          task: 'validate'
+        }
+      }
+
+      var recalibrate_instructions = {
+        type: jsPsychHtmlButtonResponse,
+        stimulus: `
+          <p>The accuracy of the calibration is a little lower than we'd like.</p>
+          <p>Let's try calibrating one more time.</p>
+          <p>On the next screen, look at the dots and click on them.<p>
+        `,
+        choices: ['OK'],
+      }
+
+      var recalibrate = {
+        timeline: [recalibrate_instructions, calibration, validation_instructions, validation],
+        conditional_function: function(){
+          var validation_data = jsPsych.data.get().filter({task: 'validate'}).values()[0];
+          return validation_data.percent_in_roi.some(function(x){
+            var minimum_percent_acceptable = 50;
+            return x < minimum_percent_acceptable;
+          });
+        },
+        data: {
+          phase: 'recalibration'
+        }
+      }
+
+      var calibration_done = {
+        type: jsPsychHtmlButtonResponse,
+        stimulus: `
+          <p>Great, we're done with calibration!</p>
+        `,
+        choices: ['OK']
+      }
+
+      var begin = {
+        type: jsPsychHtmlKeyboardResponse,
+        stimulus: `<p>The next screen will show an image to demonstrate adding the webgazer extension to a trial.</p>
+          <p>Just look at the image while eye tracking data is collected. The trial will end automatically.</p>
+          <p>Press any key to start.</p>
+        `
+      }
+
+      const trial = {
+        type: jsPsychImageKeyboardResponse,
+        stimulus: 'img/blue.png',
+        choices: "NO_KEYS",
+        trial_duration: 2000,
+        extensions: [
+          {
+            type: jsPsychExtensionWebgazer, 
+            params: {targets: ['#jspsych-image-keyboard-response-stimulus']}
+          }
+        ]
+      }
+
+      var show_data = {
+        type: jsPsychHtmlKeyboardResponse,
+        stimulus: function() {
+          var trial_data = jsPsych.data.getLastTrialData().values();
+          var trial_json = JSON.stringify(trial_data, null, 2);
+          return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
+            <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
+        },
+        choices: "NO_KEYS"
+      };
+      
+      jsPsych.run([
+          preload, 
+          camera_instructions, 
+          init_camera, 
+          calibration_instructions, 
+          calibration, 
+          validation_instructions, 
+          validation, 
+          recalibrate,
+          calibration_done,
+          begin, 
+          trial, 
+          show_data
+        ]);
+      
+  </script>
+</html>
diff --git a/7.3/demos/img/1.gif b/7.3/demos/img/1.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/10.gif b/7.3/demos/img/10.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/11.gif b/7.3/demos/img/11.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/12.gif b/7.3/demos/img/12.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/2.gif b/7.3/demos/img/2.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/3.gif b/7.3/demos/img/3.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/4.gif b/7.3/demos/img/4.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/5.gif b/7.3/demos/img/5.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/6.gif b/7.3/demos/img/6.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/7.gif b/7.3/demos/img/7.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/8.gif b/7.3/demos/img/8.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/9.gif b/7.3/demos/img/9.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/backwardN.gif b/7.3/demos/img/backwardN.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/blue.png b/7.3/demos/img/blue.png
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/card.png b/7.3/demos/img/card.png
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/con2.png b/7.3/demos/img/con2.png
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/elephant.png b/7.3/demos/img/elephant.png
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/fixation.gif b/7.3/demos/img/fixation.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/happy_face_1.jpg b/7.3/demos/img/happy_face_1.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/happy_face_2.jpg b/7.3/demos/img/happy_face_2.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/happy_face_3.jpg b/7.3/demos/img/happy_face_3.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/happy_face_4.jpg b/7.3/demos/img/happy_face_4.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/iat_old_face.jpg b/7.3/demos/img/iat_old_face.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/lion.png b/7.3/demos/img/lion.png
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/monkey.png b/7.3/demos/img/monkey.png
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/navarro_burst_03.jpg b/7.3/demos/img/navarro_burst_03.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/normalN.gif b/7.3/demos/img/normalN.gif
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/orange.png b/7.3/demos/img/orange.png
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/sad_face_1.jpg b/7.3/demos/img/sad_face_1.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/sad_face_2.jpg b/7.3/demos/img/sad_face_2.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/sad_face_3.jpg b/7.3/demos/img/sad_face_3.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/img/sad_face_4.jpg b/7.3/demos/img/sad_face_4.jpg
old mode 100755
new mode 100644
diff --git a/7.3/demos/js/snap.svg-min.js b/7.3/demos/js/snap.svg-min.js
old mode 100755
new mode 100644
index 423daf631b..aae6cfb848
--- a/7.3/demos/js/snap.svg-min.js
+++ b/7.3/demos/js/snap.svg-min.js
@@ -1,4451 +1,4451 @@
-// Snap.svg 0.5.1
-//
-// Copyright (c) 2013 – 2017 Adobe Systems Incorporated. All rights reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-// http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-//
-// build: 2017-02-07
-
-!(function (a) {
-  var b,
-    c,
-    d = "0.5.0",
-    e = "hasOwnProperty",
-    f = /[\.\/]/,
-    g = /\s*,\s*/,
-    h = "*",
-    i = function (a, b) {
-      return a - b;
-    },
-    j = { n: {} },
-    k = function () {
-      for (var a = 0, b = this.length; b > a; a++)
-        if ("undefined" != typeof this[a]) return this[a];
-    },
-    l = function () {
-      for (var a = this.length; --a; ) if ("undefined" != typeof this[a]) return this[a];
-    },
-    m = Object.prototype.toString,
-    n = String,
-    o =
-      Array.isArray ||
-      function (a) {
-        return a instanceof Array || "[object Array]" == m.call(a);
-      };
-  (eve = function (a, d) {
-    var e,
-      f = c,
-      g = Array.prototype.slice.call(arguments, 2),
-      h = eve.listeners(a),
-      j = 0,
-      m = [],
-      n = {},
-      o = [],
-      p = b;
-    (o.firstDefined = k), (o.lastDefined = l), (b = a), (c = 0);
-    for (var q = 0, r = h.length; r > q; q++)
-      "zIndex" in h[q] && (m.push(h[q].zIndex), h[q].zIndex < 0 && (n[h[q].zIndex] = h[q]));
-    for (m.sort(i); m[j] < 0; ) if (((e = n[m[j++]]), o.push(e.apply(d, g)), c)) return (c = f), o;
-    for (q = 0; r > q; q++)
-      if (((e = h[q]), "zIndex" in e))
-        if (e.zIndex == m[j]) {
-          if ((o.push(e.apply(d, g)), c)) break;
-          do if ((j++, (e = n[m[j]]), e && o.push(e.apply(d, g)), c)) break;
-          while (e);
-        } else n[e.zIndex] = e;
-      else if ((o.push(e.apply(d, g)), c)) break;
-    return (c = f), (b = p), o;
-  }),
-    (eve._events = j),
-    (eve.listeners = function (a) {
-      var b,
-        c,
-        d,
-        e,
-        g,
-        i,
-        k,
-        l,
-        m = o(a) ? a : a.split(f),
-        n = j,
-        p = [n],
-        q = [];
-      for (e = 0, g = m.length; g > e; e++) {
-        for (l = [], i = 0, k = p.length; k > i; i++)
-          for (n = p[i].n, c = [n[m[e]], n[h]], d = 2; d--; )
-            (b = c[d]), b && (l.push(b), (q = q.concat(b.f || [])));
-        p = l;
-      }
-      return q;
-    }),
-    (eve.separator = function (a) {
-      a
-        ? ((a = n(a).replace(/(?=[\.\^\]\[\-])/g, "\\")), (a = "[" + a + "]"), (f = new RegExp(a)))
-        : (f = /[\.\/]/);
-    }),
-    (eve.on = function (a, b) {
-      if ("function" != typeof b) return function () {};
-      for (var c = o(a) ? (o(a[0]) ? a : [a]) : n(a).split(g), d = 0, e = c.length; e > d; d++)
-        !(function (a) {
-          for (var c, d = o(a) ? a : n(a).split(f), e = j, g = 0, h = d.length; h > g; g++)
-            (e = e.n), (e = (e.hasOwnProperty(d[g]) && e[d[g]]) || (e[d[g]] = { n: {} }));
-          for (e.f = e.f || [], g = 0, h = e.f.length; h > g; g++)
-            if (e.f[g] == b) {
-              c = !0;
-              break;
-            }
-          !c && e.f.push(b);
-        })(c[d]);
-      return function (a) {
-        +a == +a && (b.zIndex = +a);
-      };
-    }),
-    (eve.f = function (a) {
-      var b = [].slice.call(arguments, 1);
-      return function () {
-        eve.apply(null, [a, null].concat(b).concat([].slice.call(arguments, 0)));
-      };
-    }),
-    (eve.stop = function () {
-      c = 1;
-    }),
-    (eve.nt = function (a) {
-      var c = o(b) ? b.join(".") : b;
-      return a ? new RegExp("(?:\\.|\\/|^)" + a + "(?:\\.|\\/|$)").test(c) : c;
-    }),
-    (eve.nts = function () {
-      return o(b) ? b : b.split(f);
-    }),
-    (eve.off = eve.unbind =
-      function (a, b) {
-        if (!a) return void (eve._events = j = { n: {} });
-        var c = o(a) ? (o(a[0]) ? a : [a]) : n(a).split(g);
-        if (c.length > 1) for (var d = 0, i = c.length; i > d; d++) eve.off(c[d], b);
-        else {
-          c = o(a) ? a : n(a).split(f);
-          var k,
-            l,
-            m,
-            d,
-            i,
-            p,
-            q,
-            r = [j],
-            s = [];
-          for (d = 0, i = c.length; i > d; d++)
-            for (p = 0; p < r.length; p += m.length - 2) {
-              if (((m = [p, 1]), (k = r[p].n), c[d] != h))
-                k[c[d]] && (m.push(k[c[d]]), s.unshift({ n: k, name: c[d] }));
-              else for (l in k) k[e](l) && (m.push(k[l]), s.unshift({ n: k, name: l }));
-              r.splice.apply(r, m);
-            }
-          for (d = 0, i = r.length; i > d; d++)
-            for (k = r[d]; k.n; ) {
-              if (b) {
-                if (k.f) {
-                  for (p = 0, q = k.f.length; q > p; p++)
-                    if (k.f[p] == b) {
-                      k.f.splice(p, 1);
-                      break;
-                    }
-                  !k.f.length && delete k.f;
-                }
-                for (l in k.n)
-                  if (k.n[e](l) && k.n[l].f) {
-                    var t = k.n[l].f;
-                    for (p = 0, q = t.length; q > p; p++)
-                      if (t[p] == b) {
-                        t.splice(p, 1);
-                        break;
-                      }
-                    !t.length && delete k.n[l].f;
-                  }
-              } else {
-                delete k.f;
-                for (l in k.n) k.n[e](l) && k.n[l].f && delete k.n[l].f;
-              }
-              k = k.n;
-            }
-          a: for (d = 0, i = s.length; i > d; d++) {
-            k = s[d];
-            for (l in k.n[k.name].f) continue a;
-            for (l in k.n[k.name].n) continue a;
-            delete k.n[k.name];
-          }
-        }
-      }),
-    (eve.once = function (a, b) {
-      var c = function () {
-        return eve.off(a, c), b.apply(this, arguments);
-      };
-      return eve.on(a, c);
-    }),
-    (eve.version = d),
-    (eve.toString = function () {
-      return "You are running Eve " + d;
-    }),
-    "undefined" != typeof module && module.exports
-      ? (module.exports = eve)
-      : "function" == typeof define && define.amd
-      ? define("eve", [], function () {
-          return eve;
-        })
-      : (a.eve = eve);
-})(this),
-  (function (a, b) {
-    if ("function" == typeof define && define.amd)
-      define(["eve"], function (c) {
-        return b(a, c);
-      });
-    else if ("undefined" != typeof exports) {
-      var c = require("eve");
-      module.exports = b(a, c);
-    } else b(a, a.eve);
-  })(window || this, function (a, b) {
-    var c = (function (b) {
-        var c,
-          d = {},
-          e =
-            a.requestAnimationFrame ||
-            a.webkitRequestAnimationFrame ||
-            a.mozRequestAnimationFrame ||
-            a.oRequestAnimationFrame ||
-            a.msRequestAnimationFrame ||
-            function (a) {
-              return setTimeout(a, 16, new Date().getTime()), !0;
-            },
-          f =
-            Array.isArray ||
-            function (a) {
-              return a instanceof Array || "[object Array]" == Object.prototype.toString.call(a);
-            },
-          g = 0,
-          h = "M" + (+new Date()).toString(36),
-          i = function () {
-            return h + (g++).toString(36);
-          },
-          j =
-            Date.now ||
-            function () {
-              return +new Date();
-            },
-          k = function (a) {
-            var b = this;
-            if (null == a) return b.s;
-            var c = b.s - a;
-            (b.b += b.dur * c), (b.B += b.dur * c), (b.s = a);
-          },
-          l = function (a) {
-            var b = this;
-            return null == a ? b.spd : void (b.spd = a);
-          },
-          m = function (a) {
-            var b = this;
-            return null == a ? b.dur : ((b.s = (b.s * a) / b.dur), void (b.dur = a));
-          },
-          n = function () {
-            var a = this;
-            delete d[a.id], a.update(), b("mina.stop." + a.id, a);
-          },
-          o = function () {
-            var a = this;
-            a.pdif || (delete d[a.id], a.update(), (a.pdif = a.get() - a.b));
-          },
-          p = function () {
-            var a = this;
-            a.pdif && ((a.b = a.get() - a.pdif), delete a.pdif, (d[a.id] = a), r());
-          },
-          q = function () {
-            var a,
-              b = this;
-            if (f(b.start)) {
-              a = [];
-              for (var c = 0, d = b.start.length; d > c; c++)
-                a[c] = +b.start[c] + (b.end[c] - b.start[c]) * b.easing(b.s);
-            } else a = +b.start + (b.end - b.start) * b.easing(b.s);
-            b.set(a);
-          },
-          r = function (a) {
-            if (!a) return void (c || (c = e(r)));
-            var f = 0;
-            for (var g in d)
-              if (d.hasOwnProperty(g)) {
-                var h = d[g],
-                  i = h.get();
-                f++,
-                  (h.s = (i - h.b) / (h.dur / h.spd)),
-                  h.s >= 1 &&
-                    (delete d[g],
-                    (h.s = 1),
-                    f--,
-                    (function (a) {
-                      setTimeout(function () {
-                        b("mina.finish." + a.id, a);
-                      });
-                    })(h)),
-                  h.update();
-              }
-            c = f ? e(r) : !1;
-          },
-          s = function (a, b, c, e, f, g, h) {
-            var j = {
-              id: i(),
-              start: a,
-              end: b,
-              b: c,
-              s: 0,
-              dur: e - c,
-              spd: 1,
-              get: f,
-              set: g,
-              easing: h || s.linear,
-              status: k,
-              speed: l,
-              duration: m,
-              stop: n,
-              pause: o,
-              resume: p,
-              update: q,
-            };
-            d[j.id] = j;
-            var t,
-              u = 0;
-            for (t in d) if (d.hasOwnProperty(t) && (u++, 2 == u)) break;
-            return 1 == u && r(), j;
-          };
-        return (
-          (s.time = j),
-          (s.getById = function (a) {
-            return d[a] || null;
-          }),
-          (s.linear = function (a) {
-            return a;
-          }),
-          (s.easeout = function (a) {
-            return Math.pow(a, 1.7);
-          }),
-          (s.easein = function (a) {
-            return Math.pow(a, 0.48);
-          }),
-          (s.easeinout = function (a) {
-            if (1 == a) return 1;
-            if (0 == a) return 0;
-            var b = 0.48 - a / 1.04,
-              c = Math.sqrt(0.1734 + b * b),
-              d = c - b,
-              e = Math.pow(Math.abs(d), 1 / 3) * (0 > d ? -1 : 1),
-              f = -c - b,
-              g = Math.pow(Math.abs(f), 1 / 3) * (0 > f ? -1 : 1),
-              h = e + g + 0.5;
-            return 3 * (1 - h) * h * h + h * h * h;
-          }),
-          (s.backin = function (a) {
-            if (1 == a) return 1;
-            var b = 1.70158;
-            return a * a * ((b + 1) * a - b);
-          }),
-          (s.backout = function (a) {
-            if (0 == a) return 0;
-            a -= 1;
-            var b = 1.70158;
-            return a * a * ((b + 1) * a + b) + 1;
-          }),
-          (s.elastic = function (a) {
-            return a == !!a
-              ? a
-              : Math.pow(2, -10 * a) * Math.sin(((a - 0.075) * (2 * Math.PI)) / 0.3) + 1;
-          }),
-          (s.bounce = function (a) {
-            var b,
-              c = 7.5625,
-              d = 2.75;
-            return (
-              1 / d > a
-                ? (b = c * a * a)
-                : 2 / d > a
-                ? ((a -= 1.5 / d), (b = c * a * a + 0.75))
-                : 2.5 / d > a
-                ? ((a -= 2.25 / d), (b = c * a * a + 0.9375))
-                : ((a -= 2.625 / d), (b = c * a * a + 0.984375)),
-              b
-            );
-          }),
-          (a.mina = s),
-          s
-        );
-      })("undefined" == typeof b ? function () {} : b),
-      d = (function (a) {
-        function c(a, b) {
-          if (a) {
-            if (a.nodeType) return w(a);
-            if (e(a, "array") && c.set) return c.set.apply(c, a);
-            if (a instanceof s) return a;
-            if (null == b)
-              try {
-                return (a = y.doc.querySelector(String(a))), w(a);
-              } catch (d) {
-                return null;
-              }
-          }
-          return (a = null == a ? "100%" : a), (b = null == b ? "100%" : b), new v(a, b);
-        }
-        function d(a, b) {
-          if (b) {
-            if (
-              ("#text" == a && (a = y.doc.createTextNode(b.text || b["#text"] || "")),
-              "#comment" == a && (a = y.doc.createComment(b.text || b["#text"] || "")),
-              "string" == typeof a && (a = d(a)),
-              "string" == typeof b)
-            )
-              return 1 == a.nodeType
-                ? "xlink:" == b.substring(0, 6)
-                  ? a.getAttributeNS(T, b.substring(6))
-                  : "xml:" == b.substring(0, 4)
-                  ? a.getAttributeNS(U, b.substring(4))
-                  : a.getAttribute(b)
-                : "text" == b
-                ? a.nodeValue
-                : null;
-            if (1 == a.nodeType) {
-              for (var c in b)
-                if (b[z](c)) {
-                  var e = A(b[c]);
-                  e
-                    ? "xlink:" == c.substring(0, 6)
-                      ? a.setAttributeNS(T, c.substring(6), e)
-                      : "xml:" == c.substring(0, 4)
-                      ? a.setAttributeNS(U, c.substring(4), e)
-                      : a.setAttribute(c, e)
-                    : a.removeAttribute(c);
-                }
-            } else "text" in b && (a.nodeValue = b.text);
-          } else a = y.doc.createElementNS(U, a);
-          return a;
-        }
-        function e(a, b) {
-          return (
-            (b = A.prototype.toLowerCase.call(b)),
-            "finite" == b
-              ? isFinite(a)
-              : "array" == b && (a instanceof Array || (Array.isArray && Array.isArray(a)))
-              ? !0
-              : ("null" == b && null === a) ||
-                (b == typeof a && null !== a) ||
-                ("object" == b && a === Object(a)) ||
-                J.call(a).slice(8, -1).toLowerCase() == b
-          );
-        }
-        function f(a) {
-          if ("function" == typeof a || Object(a) !== a) return a;
-          var b = new a.constructor();
-          for (var c in a) a[z](c) && (b[c] = f(a[c]));
-          return b;
-        }
-        function h(a, b) {
-          for (var c = 0, d = a.length; d > c; c++)
-            if (a[c] === b) return a.push(a.splice(c, 1)[0]);
-        }
-        function i(a, b, c) {
-          function d() {
-            var e = Array.prototype.slice.call(arguments, 0),
-              f = e.join("␀"),
-              g = (d.cache = d.cache || {}),
-              i = (d.count = d.count || []);
-            return g[z](f)
-              ? (h(i, f), c ? c(g[f]) : g[f])
-              : (i.length >= 1e3 && delete g[i.shift()],
-                i.push(f),
-                (g[f] = a.apply(b, e)),
-                c ? c(g[f]) : g[f]);
-          }
-          return d;
-        }
-        function j(a, b, c, d, e, f) {
-          if (null == e) {
-            var g = a - c,
-              h = b - d;
-            return g || h ? (180 + (180 * D.atan2(-h, -g)) / H + 360) % 360 : 0;
-          }
-          return j(a, b, e, f) - j(c, d, e, f);
-        }
-        function k(a) {
-          return ((a % 360) * H) / 180;
-        }
-        function l(a) {
-          return ((180 * a) / H) % 360;
-        }
-        function m(a) {
-          var b = [];
-          return (
-            (a = a.replace(/(?:^|\s)(\w+)\(([^)]+)\)/g, function (a, c, d) {
-              return (
-                (d = d.split(/\s*,\s*|\s+/)),
-                "rotate" == c && 1 == d.length && d.push(0, 0),
-                "scale" == c &&
-                  (d.length > 2 ? (d = d.slice(0, 2)) : 2 == d.length && d.push(0, 0),
-                  1 == d.length && d.push(d[0], 0, 0)),
-                "skewX" == c
-                  ? b.push(["m", 1, 0, D.tan(k(d[0])), 1, 0, 0])
-                  : "skewY" == c
-                  ? b.push(["m", 1, D.tan(k(d[0])), 0, 1, 0, 0])
-                  : b.push([c.charAt(0)].concat(d)),
-                a
-              );
-            })),
-            b
-          );
-        }
-        function n(a, b) {
-          var d = aa(a),
-            e = new c.Matrix();
-          if (d)
-            for (var f = 0, g = d.length; g > f; f++) {
-              var h,
-                i,
-                j,
-                k,
-                l,
-                m = d[f],
-                n = m.length,
-                o = A(m[0]).toLowerCase(),
-                p = m[0] != o,
-                q = p ? e.invert() : 0;
-              "t" == o && 2 == n
-                ? e.translate(m[1], 0)
-                : "t" == o && 3 == n
-                ? p
-                  ? ((h = q.x(0, 0)),
-                    (i = q.y(0, 0)),
-                    (j = q.x(m[1], m[2])),
-                    (k = q.y(m[1], m[2])),
-                    e.translate(j - h, k - i))
-                  : e.translate(m[1], m[2])
-                : "r" == o
-                ? 2 == n
-                  ? ((l = l || b), e.rotate(m[1], l.x + l.width / 2, l.y + l.height / 2))
-                  : 4 == n &&
-                    (p
-                      ? ((j = q.x(m[2], m[3])), (k = q.y(m[2], m[3])), e.rotate(m[1], j, k))
-                      : e.rotate(m[1], m[2], m[3]))
-                : "s" == o
-                ? 2 == n || 3 == n
-                  ? ((l = l || b), e.scale(m[1], m[n - 1], l.x + l.width / 2, l.y + l.height / 2))
-                  : 4 == n
-                  ? p
-                    ? ((j = q.x(m[2], m[3])), (k = q.y(m[2], m[3])), e.scale(m[1], m[1], j, k))
-                    : e.scale(m[1], m[1], m[2], m[3])
-                  : 5 == n &&
-                    (p
-                      ? ((j = q.x(m[3], m[4])), (k = q.y(m[3], m[4])), e.scale(m[1], m[2], j, k))
-                      : e.scale(m[1], m[2], m[3], m[4]))
-                : "m" == o && 7 == n && e.add(m[1], m[2], m[3], m[4], m[5], m[6]);
-            }
-          return e;
-        }
-        function o(a) {
-          var b =
-              (a.node.ownerSVGElement && w(a.node.ownerSVGElement)) ||
-              (a.node.parentNode && w(a.node.parentNode)) ||
-              c.select("svg") ||
-              c(0, 0),
-            d = b.select("defs"),
-            e = null == d ? !1 : d.node;
-          return e || (e = u("defs", b.node).node), e;
-        }
-        function p(a) {
-          return (a.node.ownerSVGElement && w(a.node.ownerSVGElement)) || c.select("svg");
-        }
-        function q(a, b, c) {
-          function e(a) {
-            if (null == a) return I;
-            if (a == +a) return a;
-            d(j, { width: a });
-            try {
-              return j.getBBox().width;
-            } catch (b) {
-              return 0;
-            }
-          }
-          function f(a) {
-            if (null == a) return I;
-            if (a == +a) return a;
-            d(j, { height: a });
-            try {
-              return j.getBBox().height;
-            } catch (b) {
-              return 0;
-            }
-          }
-          function g(d, e) {
-            null == b
-              ? (i[d] = e(a.attr(d) || 0))
-              : d == b && (i = e(null == c ? a.attr(d) || 0 : c));
-          }
-          var h = p(a).node,
-            i = {},
-            j = h.querySelector(".svg---mgr");
-          switch (
-            (j ||
-              ((j = d("rect")),
-              d(j, { x: -9e9, y: -9e9, width: 10, height: 10, class: "svg---mgr", fill: "none" }),
-              h.appendChild(j)),
-            a.type)
-          ) {
-            case "rect":
-              g("rx", e), g("ry", f);
-            case "image":
-              g("width", e), g("height", f);
-            case "text":
-              g("x", e), g("y", f);
-              break;
-            case "circle":
-              g("cx", e), g("cy", f), g("r", e);
-              break;
-            case "ellipse":
-              g("cx", e), g("cy", f), g("rx", e), g("ry", f);
-              break;
-            case "line":
-              g("x1", e), g("x2", e), g("y1", f), g("y2", f);
-              break;
-            case "marker":
-              g("refX", e), g("markerWidth", e), g("refY", f), g("markerHeight", f);
-              break;
-            case "radialGradient":
-              g("fx", e), g("fy", f);
-              break;
-            case "tspan":
-              g("dx", e), g("dy", f);
-              break;
-            default:
-              g(b, e);
-          }
-          return h.removeChild(j), i;
-        }
-        function r(a) {
-          e(a, "array") || (a = Array.prototype.slice.call(arguments, 0));
-          for (var b = 0, c = 0, d = this.node; this[b]; ) delete this[b++];
-          for (b = 0; b < a.length; b++)
-            "set" == a[b].type
-              ? a[b].forEach(function (a) {
-                  d.appendChild(a.node);
-                })
-              : d.appendChild(a[b].node);
-          var f = d.childNodes;
-          for (b = 0; b < f.length; b++) this[c++] = w(f[b]);
-          return this;
-        }
-        function s(a) {
-          if (a.snap in V) return V[a.snap];
-          var b;
-          try {
-            b = a.ownerSVGElement;
-          } catch (c) {}
-          (this.node = a), b && (this.paper = new v(b)), (this.type = a.tagName || a.nodeName);
-          var d = (this.id = S(this));
-          if (
-            ((this.anims = {}),
-            (this._ = { transform: [] }),
-            (a.snap = d),
-            (V[d] = this),
-            "g" == this.type && (this.add = r),
-            this.type in { g: 1, mask: 1, pattern: 1, symbol: 1 })
-          )
-            for (var e in v.prototype) v.prototype[z](e) && (this[e] = v.prototype[e]);
-        }
-        function t(a) {
-          this.node = a;
-        }
-        function u(a, b) {
-          var c = d(a);
-          b.appendChild(c);
-          var e = w(c);
-          return e;
-        }
-        function v(a, b) {
-          var c,
-            e,
-            f,
-            g = v.prototype;
-          if (a && a.tagName && "svg" == a.tagName.toLowerCase()) {
-            if (a.snap in V) return V[a.snap];
-            var h = a.ownerDocument;
-            (c = new s(a)),
-              (e = a.getElementsByTagName("desc")[0]),
-              (f = a.getElementsByTagName("defs")[0]),
-              e ||
-                ((e = d("desc")),
-                e.appendChild(h.createTextNode("Created with Snap")),
-                c.node.appendChild(e)),
-              f || ((f = d("defs")), c.node.appendChild(f)),
-              (c.defs = f);
-            for (var i in g) g[z](i) && (c[i] = g[i]);
-            c.paper = c.root = c;
-          } else
-            (c = u("svg", y.doc.body)), d(c.node, { height: b, version: 1.1, width: a, xmlns: U });
-          return c;
-        }
-        function w(a) {
-          return a
-            ? a instanceof s || a instanceof t
-              ? a
-              : a.tagName && "svg" == a.tagName.toLowerCase()
-              ? new v(a)
-              : a.tagName && "object" == a.tagName.toLowerCase() && "image/svg+xml" == a.type
-              ? new v(a.contentDocument.getElementsByTagName("svg")[0])
-              : new s(a)
-            : a;
-        }
-        function x(a, b) {
-          for (var c = 0, d = a.length; d > c; c++) {
-            var e = { type: a[c].type, attr: a[c].attr() },
-              f = a[c].children();
-            b.push(e), f.length && x(f, (e.childNodes = []));
-          }
-        }
-        (c.version = "0.5.1"),
-          (c.toString = function () {
-            return "Snap v" + this.version;
-          }),
-          (c._ = {});
-        var y = { win: a.window, doc: a.window.document };
-        c._.glob = y;
-        var z = "hasOwnProperty",
-          A = String,
-          B = parseFloat,
-          C = parseInt,
-          D = Math,
-          E = D.max,
-          F = D.min,
-          G = D.abs,
-          H = (D.pow, D.PI),
-          I = (D.round, ""),
-          J = Object.prototype.toString,
-          K =
-            /^\s*((#[a-f\d]{6})|(#[a-f\d]{3})|rgba?\(\s*([\d\.]+%?\s*,\s*[\d\.]+%?\s*,\s*[\d\.]+%?(?:\s*,\s*[\d\.]+%?)?)\s*\)|hsba?\(\s*([\d\.]+(?:deg|\xb0|%)?\s*,\s*[\d\.]+%?\s*,\s*[\d\.]+(?:%?\s*,\s*[\d\.]+)?%?)\s*\)|hsla?\(\s*([\d\.]+(?:deg|\xb0|%)?\s*,\s*[\d\.]+%?\s*,\s*[\d\.]+(?:%?\s*,\s*[\d\.]+)?%?)\s*\))\s*$/i,
-          L = ((c._.separator = /[,\s]+/), /[\s]*,[\s]*/),
-          M = { hs: 1, rg: 1 },
-          N = /([a-z])[\s,]*((-?\d*\.?\d*(?:e[\-+]?\d+)?[\s]*,?[\s]*)+)/gi,
-          O = /([rstm])[\s,]*((-?\d*\.?\d*(?:e[\-+]?\d+)?[\s]*,?[\s]*)+)/gi,
-          P = /(-?\d*\.?\d*(?:e[\-+]?\d+)?)[\s]*,?[\s]*/gi,
-          Q = 0,
-          R = "S" + (+new Date()).toString(36),
-          S = function (a) {
-            return (a && a.type ? a.type : I) + R + (Q++).toString(36);
-          },
-          T = "http://www.w3.org/1999/xlink",
-          U = "http://www.w3.org/2000/svg",
-          V = {};
-        c.url = function (a) {
-          return "url('#" + a + "')";
-        };
-        (c._.$ = d),
-          (c._.id = S),
-          (c.format = (function () {
-            var a = /\{([^\}]+)\}/g,
-              b = /(?:(?:^|\.)(.+?)(?=\[|\.|$|\()|\[('|")(.+?)\2\])(\(\))?/g,
-              c = function (a, c, d) {
-                var e = d;
-                return (
-                  c.replace(b, function (a, b, c, d, f) {
-                    (b = b || d),
-                      e && (b in e && (e = e[b]), "function" == typeof e && f && (e = e()));
-                  }),
-                  (e = (null == e || e == d ? a : e) + "")
-                );
-              };
-            return function (b, d) {
-              return A(b).replace(a, function (a, b) {
-                return c(a, b, d);
-              });
-            };
-          })()),
-          (c._.clone = f),
-          (c._.cacher = i),
-          (c.rad = k),
-          (c.deg = l),
-          (c.sin = function (a) {
-            return D.sin(c.rad(a));
-          }),
-          (c.tan = function (a) {
-            return D.tan(c.rad(a));
-          }),
-          (c.cos = function (a) {
-            return D.cos(c.rad(a));
-          }),
-          (c.asin = function (a) {
-            return c.deg(D.asin(a));
-          }),
-          (c.acos = function (a) {
-            return c.deg(D.acos(a));
-          }),
-          (c.atan = function (a) {
-            return c.deg(D.atan(a));
-          }),
-          (c.atan2 = function (a) {
-            return c.deg(D.atan2(a));
-          }),
-          (c.angle = j),
-          (c.len = function (a, b, d, e) {
-            return Math.sqrt(c.len2(a, b, d, e));
-          }),
-          (c.len2 = function (a, b, c, d) {
-            return (a - c) * (a - c) + (b - d) * (b - d);
-          }),
-          (c.closestPoint = function (a, b, c) {
-            function d(a) {
-              var d = a.x - b,
-                e = a.y - c;
-              return d * d + e * e;
-            }
-            for (
-              var e,
-                f,
-                g,
-                h,
-                i = a.node,
-                j = i.getTotalLength(),
-                k = (j / i.pathSegList.numberOfItems) * 0.125,
-                l = 1 / 0,
-                m = 0;
-              j >= m;
-              m += k
-            )
-              (h = d((g = i.getPointAtLength(m)))) < l && ((e = g), (f = m), (l = h));
-            for (k *= 0.5; k > 0.5; ) {
-              var n, o, p, q, r, s;
-              (p = f - k) >= 0 && (r = d((n = i.getPointAtLength(p)))) < l
-                ? ((e = n), (f = p), (l = r))
-                : (q = f + k) <= j && (s = d((o = i.getPointAtLength(q)))) < l
-                ? ((e = o), (f = q), (l = s))
-                : (k *= 0.5);
-            }
-            return (e = { x: e.x, y: e.y, length: f, distance: Math.sqrt(l) });
-          }),
-          (c.is = e),
-          (c.snapTo = function (a, b, c) {
-            if (((c = e(c, "finite") ? c : 10), e(a, "array"))) {
-              for (var d = a.length; d--; ) if (G(a[d] - b) <= c) return a[d];
-            } else {
-              a = +a;
-              var f = b % a;
-              if (c > f) return b - f;
-              if (f > a - c) return b - f + a;
-            }
-            return b;
-          }),
-          (c.getRGB = i(function (a) {
-            if (!a || (a = A(a)).indexOf("-") + 1)
-              return { r: -1, g: -1, b: -1, hex: "none", error: 1, toString: Z };
-            if ("none" == a) return { r: -1, g: -1, b: -1, hex: "none", toString: Z };
-            if ((!(M[z](a.toLowerCase().substring(0, 2)) || "#" == a.charAt()) && (a = W(a)), !a))
-              return { r: -1, g: -1, b: -1, hex: "none", error: 1, toString: Z };
-            var b,
-              d,
-              f,
-              g,
-              h,
-              i,
-              j = a.match(K);
-            return j
-              ? (j[2] &&
-                  ((f = C(j[2].substring(5), 16)),
-                  (d = C(j[2].substring(3, 5), 16)),
-                  (b = C(j[2].substring(1, 3), 16))),
-                j[3] &&
-                  ((f = C((h = j[3].charAt(3)) + h, 16)),
-                  (d = C((h = j[3].charAt(2)) + h, 16)),
-                  (b = C((h = j[3].charAt(1)) + h, 16))),
-                j[4] &&
-                  ((i = j[4].split(L)),
-                  (b = B(i[0])),
-                  "%" == i[0].slice(-1) && (b *= 2.55),
-                  (d = B(i[1])),
-                  "%" == i[1].slice(-1) && (d *= 2.55),
-                  (f = B(i[2])),
-                  "%" == i[2].slice(-1) && (f *= 2.55),
-                  "rgba" == j[1].toLowerCase().slice(0, 4) && (g = B(i[3])),
-                  i[3] && "%" == i[3].slice(-1) && (g /= 100)),
-                j[5]
-                  ? ((i = j[5].split(L)),
-                    (b = B(i[0])),
-                    "%" == i[0].slice(-1) && (b /= 100),
-                    (d = B(i[1])),
-                    "%" == i[1].slice(-1) && (d /= 100),
-                    (f = B(i[2])),
-                    "%" == i[2].slice(-1) && (f /= 100),
-                    ("deg" == i[0].slice(-3) || "°" == i[0].slice(-1)) && (b /= 360),
-                    "hsba" == j[1].toLowerCase().slice(0, 4) && (g = B(i[3])),
-                    i[3] && "%" == i[3].slice(-1) && (g /= 100),
-                    c.hsb2rgb(b, d, f, g))
-                  : j[6]
-                  ? ((i = j[6].split(L)),
-                    (b = B(i[0])),
-                    "%" == i[0].slice(-1) && (b /= 100),
-                    (d = B(i[1])),
-                    "%" == i[1].slice(-1) && (d /= 100),
-                    (f = B(i[2])),
-                    "%" == i[2].slice(-1) && (f /= 100),
-                    ("deg" == i[0].slice(-3) || "°" == i[0].slice(-1)) && (b /= 360),
-                    "hsla" == j[1].toLowerCase().slice(0, 4) && (g = B(i[3])),
-                    i[3] && "%" == i[3].slice(-1) && (g /= 100),
-                    c.hsl2rgb(b, d, f, g))
-                  : ((b = F(D.round(b), 255)),
-                    (d = F(D.round(d), 255)),
-                    (f = F(D.round(f), 255)),
-                    (g = F(E(g, 0), 1)),
-                    (j = { r: b, g: d, b: f, toString: Z }),
-                    (j.hex = "#" + (16777216 | f | (d << 8) | (b << 16)).toString(16).slice(1)),
-                    (j.opacity = e(g, "finite") ? g : 1),
-                    j))
-              : { r: -1, g: -1, b: -1, hex: "none", error: 1, toString: Z };
-          }, c)),
-          (c.hsb = i(function (a, b, d) {
-            return c.hsb2rgb(a, b, d).hex;
-          })),
-          (c.hsl = i(function (a, b, d) {
-            return c.hsl2rgb(a, b, d).hex;
-          })),
-          (c.rgb = i(function (a, b, c, d) {
-            if (e(d, "finite")) {
-              var f = D.round;
-              return "rgba(" + [f(a), f(b), f(c), +d.toFixed(2)] + ")";
-            }
-            return "#" + (16777216 | c | (b << 8) | (a << 16)).toString(16).slice(1);
-          }));
-        var W = function (a) {
-            var b = y.doc.getElementsByTagName("head")[0] || y.doc.getElementsByTagName("svg")[0],
-              c = "rgb(255, 0, 0)";
-            return (W = i(function (a) {
-              if ("red" == a.toLowerCase()) return c;
-              (b.style.color = c), (b.style.color = a);
-              var d = y.doc.defaultView.getComputedStyle(b, I).getPropertyValue("color");
-              return d == c ? null : d;
-            }))(a);
-          },
-          X = function () {
-            return "hsb(" + [this.h, this.s, this.b] + ")";
-          },
-          Y = function () {
-            return "hsl(" + [this.h, this.s, this.l] + ")";
-          },
-          Z = function () {
-            return 1 == this.opacity || null == this.opacity
-              ? this.hex
-              : "rgba(" + [this.r, this.g, this.b, this.opacity] + ")";
-          },
-          $ = function (a, b, d) {
-            if (
-              (null == b &&
-                e(a, "object") &&
-                "r" in a &&
-                "g" in a &&
-                "b" in a &&
-                ((d = a.b), (b = a.g), (a = a.r)),
-              null == b && e(a, string))
-            ) {
-              var f = c.getRGB(a);
-              (a = f.r), (b = f.g), (d = f.b);
-            }
-            return (a > 1 || b > 1 || d > 1) && ((a /= 255), (b /= 255), (d /= 255)), [a, b, d];
-          },
-          _ = function (a, b, d, f) {
-            (a = D.round(255 * a)), (b = D.round(255 * b)), (d = D.round(255 * d));
-            var g = {
-              r: a,
-              g: b,
-              b: d,
-              opacity: e(f, "finite") ? f : 1,
-              hex: c.rgb(a, b, d),
-              toString: Z,
-            };
-            return e(f, "finite") && (g.opacity = f), g;
-          };
-        (c.color = function (a) {
-          var b;
-          return (
-            e(a, "object") && "h" in a && "s" in a && "b" in a
-              ? ((b = c.hsb2rgb(a)),
-                (a.r = b.r),
-                (a.g = b.g),
-                (a.b = b.b),
-                (a.opacity = 1),
-                (a.hex = b.hex))
-              : e(a, "object") && "h" in a && "s" in a && "l" in a
-              ? ((b = c.hsl2rgb(a)),
-                (a.r = b.r),
-                (a.g = b.g),
-                (a.b = b.b),
-                (a.opacity = 1),
-                (a.hex = b.hex))
-              : (e(a, "string") && (a = c.getRGB(a)),
-                e(a, "object") && "r" in a && "g" in a && "b" in a && !("error" in a)
-                  ? ((b = c.rgb2hsl(a)),
-                    (a.h = b.h),
-                    (a.s = b.s),
-                    (a.l = b.l),
-                    (b = c.rgb2hsb(a)),
-                    (a.v = b.b))
-                  : ((a = { hex: "none" }),
-                    (a.r = a.g = a.b = a.h = a.s = a.v = a.l = -1),
-                    (a.error = 1))),
-            (a.toString = Z),
-            a
-          );
-        }),
-          (c.hsb2rgb = function (a, b, c, d) {
-            e(a, "object") &&
-              "h" in a &&
-              "s" in a &&
-              "b" in a &&
-              ((c = a.b), (b = a.s), (d = a.o), (a = a.h)),
-              (a *= 360);
-            var f, g, h, i, j;
-            return (
-              (a = (a % 360) / 60),
-              (j = c * b),
-              (i = j * (1 - G((a % 2) - 1))),
-              (f = g = h = c - j),
-              (a = ~~a),
-              (f += [j, i, 0, 0, i, j][a]),
-              (g += [i, j, j, i, 0, 0][a]),
-              (h += [0, 0, i, j, j, i][a]),
-              _(f, g, h, d)
-            );
-          }),
-          (c.hsl2rgb = function (a, b, c, d) {
-            e(a, "object") && "h" in a && "s" in a && "l" in a && ((c = a.l), (b = a.s), (a = a.h)),
-              (a > 1 || b > 1 || c > 1) && ((a /= 360), (b /= 100), (c /= 100)),
-              (a *= 360);
-            var f, g, h, i, j;
-            return (
-              (a = (a % 360) / 60),
-              (j = 2 * b * (0.5 > c ? c : 1 - c)),
-              (i = j * (1 - G((a % 2) - 1))),
-              (f = g = h = c - j / 2),
-              (a = ~~a),
-              (f += [j, i, 0, 0, i, j][a]),
-              (g += [i, j, j, i, 0, 0][a]),
-              (h += [0, 0, i, j, j, i][a]),
-              _(f, g, h, d)
-            );
-          }),
-          (c.rgb2hsb = function (a, b, c) {
-            (c = $(a, b, c)), (a = c[0]), (b = c[1]), (c = c[2]);
-            var d, e, f, g;
-            return (
-              (f = E(a, b, c)),
-              (g = f - F(a, b, c)),
-              (d =
-                0 == g ? null : f == a ? (b - c) / g : f == b ? (c - a) / g + 2 : (a - b) / g + 4),
-              (d = (((d + 360) % 6) * 60) / 360),
-              (e = 0 == g ? 0 : g / f),
-              { h: d, s: e, b: f, toString: X }
-            );
-          }),
-          (c.rgb2hsl = function (a, b, c) {
-            (c = $(a, b, c)), (a = c[0]), (b = c[1]), (c = c[2]);
-            var d, e, f, g, h, i;
-            return (
-              (g = E(a, b, c)),
-              (h = F(a, b, c)),
-              (i = g - h),
-              (d =
-                0 == i ? null : g == a ? (b - c) / i : g == b ? (c - a) / i + 2 : (a - b) / i + 4),
-              (d = (((d + 360) % 6) * 60) / 360),
-              (f = (g + h) / 2),
-              (e = 0 == i ? 0 : 0.5 > f ? i / (2 * f) : i / (2 - 2 * f)),
-              { h: d, s: e, l: f, toString: Y }
-            );
-          }),
-          (c.parsePathString = function (a) {
-            if (!a) return null;
-            var b = c.path(a);
-            if (b.arr) return c.path.clone(b.arr);
-            var d = {
-                a: 7,
-                c: 6,
-                o: 2,
-                h: 1,
-                l: 2,
-                m: 2,
-                r: 4,
-                q: 4,
-                s: 4,
-                t: 2,
-                v: 1,
-                u: 3,
-                z: 0,
-              },
-              f = [];
-            return (
-              e(a, "array") && e(a[0], "array") && (f = c.path.clone(a)),
-              f.length ||
-                A(a).replace(N, function (a, b, c) {
-                  var e = [],
-                    g = b.toLowerCase();
-                  if (
-                    (c.replace(P, function (a, b) {
-                      b && e.push(+b);
-                    }),
-                    "m" == g &&
-                      e.length > 2 &&
-                      (f.push([b].concat(e.splice(0, 2))), (g = "l"), (b = "m" == b ? "l" : "L")),
-                    "o" == g && 1 == e.length && f.push([b, e[0]]),
-                    "r" == g)
-                  )
-                    f.push([b].concat(e));
-                  else for (; e.length >= d[g] && (f.push([b].concat(e.splice(0, d[g]))), d[g]); );
-                }),
-              (f.toString = c.path.toString),
-              (b.arr = c.path.clone(f)),
-              f
-            );
-          });
-        var aa = (c.parseTransformString = function (a) {
-          if (!a) return null;
-          var b = [];
-          return (
-            e(a, "array") && e(a[0], "array") && (b = c.path.clone(a)),
-            b.length ||
-              A(a).replace(O, function (a, c, d) {
-                var e = [];
-                c.toLowerCase();
-                d.replace(P, function (a, b) {
-                  b && e.push(+b);
-                }),
-                  b.push([c].concat(e));
-              }),
-            (b.toString = c.path.toString),
-            b
-          );
-        });
-        (c._.svgTransform2string = m),
-          (c._.rgTransform = /^[a-z][\s]*-?\.?\d/i),
-          (c._.transform2matrix = n),
-          (c._unit2px = q);
-        y.doc.contains || y.doc.compareDocumentPosition
-          ? function (a, b) {
-              var c = 9 == a.nodeType ? a.documentElement : a,
-                d = b && b.parentNode;
-              return (
-                a == d ||
-                !(
-                  !d ||
-                  1 != d.nodeType ||
-                  !(c.contains
-                    ? c.contains(d)
-                    : a.compareDocumentPosition && 16 & a.compareDocumentPosition(d))
-                )
-              );
-            }
-          : function (a, b) {
-              if (b) for (; b; ) if (((b = b.parentNode), b == a)) return !0;
-              return !1;
-            };
-        (c._.getSomeDefs = o),
-          (c._.getSomeSVG = p),
-          (c.select = function (a) {
-            return (a = A(a).replace(/([^\\]):/g, "$1\\:")), w(y.doc.querySelector(a));
-          }),
-          (c.selectAll = function (a) {
-            for (
-              var b = y.doc.querySelectorAll(a), d = (c.set || Array)(), e = 0;
-              e < b.length;
-              e++
-            )
-              d.push(w(b[e]));
-            return d;
-          }),
-          setInterval(function () {
-            for (var a in V)
-              if (V[z](a)) {
-                var b = V[a],
-                  c = b.node;
-                (("svg" != b.type && !c.ownerSVGElement) ||
-                  ("svg" == b.type &&
-                    (!c.parentNode ||
-                      ("ownerSVGElement" in c.parentNode && !c.ownerSVGElement)))) &&
-                  delete V[a];
-              }
-          }, 1e4),
-          (s.prototype.attr = function (a, c) {
-            var d = this,
-              f = d.node;
-            if (!a) {
-              if (1 != f.nodeType) return { text: f.nodeValue };
-              for (var g = f.attributes, h = {}, i = 0, j = g.length; j > i; i++)
-                h[g[i].nodeName] = g[i].nodeValue;
-              return h;
-            }
-            if (e(a, "string")) {
-              if (!(arguments.length > 1)) return b("snap.util.getattr." + a, d).firstDefined();
-              var k = {};
-              (k[a] = c), (a = k);
-            }
-            for (var l in a) a[z](l) && b("snap.util.attr." + l, d, a[l]);
-            return d;
-          }),
-          (c.parse = function (a) {
-            var b = y.doc.createDocumentFragment(),
-              c = !0,
-              d = y.doc.createElement("div");
-            if (
-              ((a = A(a)),
-              a.match(/^\s*<\s*svg(?:\s|>)/) || ((a = "<svg>" + a + "</svg>"), (c = !1)),
-              (d.innerHTML = a),
-              (a = d.getElementsByTagName("svg")[0]))
-            )
-              if (c) b = a;
-              else for (; a.firstChild; ) b.appendChild(a.firstChild);
-            return new t(b);
-          }),
-          (c.fragment = function () {
-            for (
-              var a = Array.prototype.slice.call(arguments, 0),
-                b = y.doc.createDocumentFragment(),
-                d = 0,
-                e = a.length;
-              e > d;
-              d++
-            ) {
-              var f = a[d];
-              f.node && f.node.nodeType && b.appendChild(f.node),
-                f.nodeType && b.appendChild(f),
-                "string" == typeof f && b.appendChild(c.parse(f).node);
-            }
-            return new t(b);
-          }),
-          (c._.make = u),
-          (c._.wrap = w),
-          (v.prototype.el = function (a, b) {
-            var c = u(a, this.node);
-            return b && c.attr(b), c;
-          }),
-          (s.prototype.children = function () {
-            for (var a = [], b = this.node.childNodes, d = 0, e = b.length; e > d; d++)
-              a[d] = c(b[d]);
-            return a;
-          }),
-          (s.prototype.toJSON = function () {
-            var a = [];
-            return x([this], a), a[0];
-          }),
-          b.on("snap.util.getattr", function () {
-            var a = b.nt();
-            a = a.substring(a.lastIndexOf(".") + 1);
-            var c = a.replace(/[A-Z]/g, function (a) {
-              return "-" + a.toLowerCase();
-            });
-            return ba[z](c)
-              ? this.node.ownerDocument.defaultView
-                  .getComputedStyle(this.node, null)
-                  .getPropertyValue(c)
-              : d(this.node, a);
-          });
-        var ba = {
-          "alignment-baseline": 0,
-          "baseline-shift": 0,
-          clip: 0,
-          "clip-path": 0,
-          "clip-rule": 0,
-          color: 0,
-          "color-interpolation": 0,
-          "color-interpolation-filters": 0,
-          "color-profile": 0,
-          "color-rendering": 0,
-          cursor: 0,
-          direction: 0,
-          display: 0,
-          "dominant-baseline": 0,
-          "enable-background": 0,
-          fill: 0,
-          "fill-opacity": 0,
-          "fill-rule": 0,
-          filter: 0,
-          "flood-color": 0,
-          "flood-opacity": 0,
-          font: 0,
-          "font-family": 0,
-          "font-size": 0,
-          "font-size-adjust": 0,
-          "font-stretch": 0,
-          "font-style": 0,
-          "font-variant": 0,
-          "font-weight": 0,
-          "glyph-orientation-horizontal": 0,
-          "glyph-orientation-vertical": 0,
-          "image-rendering": 0,
-          kerning: 0,
-          "letter-spacing": 0,
-          "lighting-color": 0,
-          marker: 0,
-          "marker-end": 0,
-          "marker-mid": 0,
-          "marker-start": 0,
-          mask: 0,
-          opacity: 0,
-          overflow: 0,
-          "pointer-events": 0,
-          "shape-rendering": 0,
-          "stop-color": 0,
-          "stop-opacity": 0,
-          stroke: 0,
-          "stroke-dasharray": 0,
-          "stroke-dashoffset": 0,
-          "stroke-linecap": 0,
-          "stroke-linejoin": 0,
-          "stroke-miterlimit": 0,
-          "stroke-opacity": 0,
-          "stroke-width": 0,
-          "text-anchor": 0,
-          "text-decoration": 0,
-          "text-rendering": 0,
-          "unicode-bidi": 0,
-          visibility: 0,
-          "word-spacing": 0,
-          "writing-mode": 0,
-        };
-        b.on("snap.util.attr", function (a) {
-          var c = b.nt(),
-            e = {};
-          (c = c.substring(c.lastIndexOf(".") + 1)), (e[c] = a);
-          var f = c.replace(/-(\w)/gi, function (a, b) {
-              return b.toUpperCase();
-            }),
-            g = c.replace(/[A-Z]/g, function (a) {
-              return "-" + a.toLowerCase();
-            });
-          ba[z](g) ? (this.node.style[f] = null == a ? I : a) : d(this.node, e);
-        }),
-          (function (a) {})(v.prototype),
-          (c.ajax = function (a, c, d, f) {
-            var g = new XMLHttpRequest(),
-              h = S();
-            if (g) {
-              if (e(c, "function")) (f = d), (d = c), (c = null);
-              else if (e(c, "object")) {
-                var i = [];
-                for (var j in c)
-                  c.hasOwnProperty(j) &&
-                    i.push(encodeURIComponent(j) + "=" + encodeURIComponent(c[j]));
-                c = i.join("&");
-              }
-              return (
-                g.open(c ? "POST" : "GET", a, !0),
-                c &&
-                  (g.setRequestHeader("X-Requested-With", "XMLHttpRequest"),
-                  g.setRequestHeader("Content-type", "application/x-www-form-urlencoded")),
-                d &&
-                  (b.once("snap.ajax." + h + ".0", d),
-                  b.once("snap.ajax." + h + ".200", d),
-                  b.once("snap.ajax." + h + ".304", d)),
-                (g.onreadystatechange = function () {
-                  4 == g.readyState && b("snap.ajax." + h + "." + g.status, f, g);
-                }),
-                4 == g.readyState ? g : (g.send(c), g)
-              );
-            }
-          }),
-          (c.load = function (a, b, d) {
-            c.ajax(a, function (a) {
-              var e = c.parse(a.responseText);
-              d ? b.call(d, e) : b(e);
-            });
-          });
-        var ca = function (a) {
-          var b = a.getBoundingClientRect(),
-            c = a.ownerDocument,
-            d = c.body,
-            e = c.documentElement,
-            f = e.clientTop || d.clientTop || 0,
-            h = e.clientLeft || d.clientLeft || 0,
-            i = b.top + (g.win.pageYOffset || e.scrollTop || d.scrollTop) - f,
-            j = b.left + (g.win.pageXOffset || e.scrollLeft || d.scrollLeft) - h;
-          return { y: i, x: j };
-        };
-        return (
-          (c.getElementByPoint = function (a, b) {
-            var c = this,
-              d = (c.canvas, y.doc.elementFromPoint(a, b));
-            if (y.win.opera && "svg" == d.tagName) {
-              var e = ca(d),
-                f = d.createSVGRect();
-              (f.x = a - e.x), (f.y = b - e.y), (f.width = f.height = 1);
-              var g = d.getIntersectionList(f, null);
-              g.length && (d = g[g.length - 1]);
-            }
-            return d ? w(d) : null;
-          }),
-          (c.plugin = function (a) {
-            a(c, s, v, y, t);
-          }),
-          (y.win.Snap = c),
-          c
-        );
-      })(a || this);
-    return (
-      d.plugin(function (c, d, e, f, g) {
-        function h(a, b) {
-          if (null == b) {
-            var d = !0;
-            if (
-              ((b =
-                "linearGradient" == a.type || "radialGradient" == a.type
-                  ? a.node.getAttribute("gradientTransform")
-                  : "pattern" == a.type
-                  ? a.node.getAttribute("patternTransform")
-                  : a.node.getAttribute("transform")),
-              !b)
-            )
-              return new c.Matrix();
-            b = c._.svgTransform2string(b);
-          } else (b = c._.rgTransform.test(b) ? m(b).replace(/\.{3}|\u2026/g, a._.transform || "") : c._.svgTransform2string(b)), l(b, "array") && (b = c.path ? c.path.toString.call(b) : m(b)), (a._.transform = b);
-          var e = c._.transform2matrix(b, a.getBBox(1));
-          return d ? e : void (a.matrix = e);
-        }
-        function i(a) {
-          function b(a, b) {
-            var d = o(a.node, b);
-            (d = d && d.match(g)),
-              (d = d && d[2]),
-              d &&
-                "#" == d.charAt() &&
-                ((d = d.substring(1)),
-                d &&
-                  (i[d] = (i[d] || []).concat(function (d) {
-                    var e = {};
-                    (e[b] = c.url(d)), o(a.node, e);
-                  })));
-          }
-          function d(a) {
-            var b = o(a.node, "xlink:href");
-            b &&
-              "#" == b.charAt() &&
-              ((b = b.substring(1)),
-              b &&
-                (i[b] = (i[b] || []).concat(function (b) {
-                  a.attr("xlink:href", "#" + b);
-                })));
-          }
-          for (
-            var e,
-              f = a.selectAll("*"),
-              g = /^\s*url\(("|'|)(.*)\1\)\s*$/,
-              h = [],
-              i = {},
-              j = 0,
-              k = f.length;
-            k > j;
-            j++
-          ) {
-            (e = f[j]),
-              b(e, "fill"),
-              b(e, "stroke"),
-              b(e, "filter"),
-              b(e, "mask"),
-              b(e, "clip-path"),
-              d(e);
-            var l = o(e.node, "id");
-            l && (o(e.node, { id: e.id }), h.push({ old: l, id: e.id }));
-          }
-          for (j = 0, k = h.length; k > j; j++) {
-            var m = i[h[j].old];
-            if (m) for (var n = 0, p = m.length; p > n; n++) m[n](h[j].id);
-          }
-        }
-        function j(a) {
-          return function () {
-            var b = a ? "<" + this.type : "",
-              c = this.node.attributes,
-              d = this.node.childNodes;
-            if (a)
-              for (var e = 0, f = c.length; f > e; e++)
-                b += " " + c[e].name + '="' + c[e].value.replace(/"/g, '\\"') + '"';
-            if (d.length) {
-              for (a && (b += ">"), e = 0, f = d.length; f > e; e++)
-                3 == d[e].nodeType
-                  ? (b += d[e].nodeValue)
-                  : 1 == d[e].nodeType && (b += s(d[e]).toString());
-              a && (b += "</" + this.type + ">");
-            } else a && (b += "/>");
-            return b;
-          };
-        }
-        var k = d.prototype,
-          l = c.is,
-          m = String,
-          n = c._unit2px,
-          o = c._.$,
-          p = c._.make,
-          q = c._.getSomeDefs,
-          r = "hasOwnProperty",
-          s = c._.wrap;
-        k.getBBox = function (a) {
-          if ("tspan" == this.type) return c._.box(this.node.getClientRects().item(0));
-          if (!c.Matrix || !c.path) return this.node.getBBox();
-          var b = this,
-            d = new c.Matrix();
-          if (b.removed) return c._.box();
-          for (; "use" == b.type; )
-            if (
-              (a ||
-                (d = d.add(
-                  b.transform().localMatrix.translate(b.attr("x") || 0, b.attr("y") || 0)
-                )),
-              b.original)
-            )
-              b = b.original;
-            else {
-              var e = b.attr("xlink:href");
-              b = b.original = b.node.ownerDocument.getElementById(e.substring(e.indexOf("#") + 1));
-            }
-          var f = b._,
-            g = c.path.get[b.type] || c.path.get.deflt;
-          try {
-            return a
-              ? ((f.bboxwt = g ? c.path.getBBox((b.realPath = g(b))) : c._.box(b.node.getBBox())),
-                c._.box(f.bboxwt))
-              : ((b.realPath = g(b)),
-                (b.matrix = b.transform().localMatrix),
-                (f.bbox = c.path.getBBox(c.path.map(b.realPath, d.add(b.matrix)))),
-                c._.box(f.bbox));
-          } catch (h) {
-            return c._.box();
-          }
-        };
-        var t = function () {
-          return this.string;
-        };
-        (k.transform = function (a) {
-          var b = this._;
-          if (null == a) {
-            for (
-              var d,
-                e = this,
-                f = new c.Matrix(this.node.getCTM()),
-                g = h(this),
-                i = [g],
-                j = new c.Matrix(),
-                k = g.toTransformString(),
-                l = m(g) == m(this.matrix) ? m(b.transform) : k;
-              "svg" != e.type && (e = e.parent());
-
-            )
-              i.push(h(e));
-            for (d = i.length; d--; ) j.add(i[d]);
-            return {
-              string: l,
-              globalMatrix: f,
-              totalMatrix: j,
-              localMatrix: g,
-              diffMatrix: f.clone().add(g.invert()),
-              global: f.toTransformString(),
-              total: j.toTransformString(),
-              local: k,
-              toString: t,
-            };
-          }
-          return (
-            a instanceof c.Matrix
-              ? ((this.matrix = a), (this._.transform = a.toTransformString()))
-              : h(this, a),
-            this.node &&
-              ("linearGradient" == this.type || "radialGradient" == this.type
-                ? o(this.node, { gradientTransform: this.matrix })
-                : "pattern" == this.type
-                ? o(this.node, { patternTransform: this.matrix })
-                : o(this.node, { transform: this.matrix })),
-            this
-          );
-        }),
-          (k.parent = function () {
-            return s(this.node.parentNode);
-          }),
-          (k.append = k.add =
-            function (a) {
-              if (a) {
-                if ("set" == a.type) {
-                  var b = this;
-                  return (
-                    a.forEach(function (a) {
-                      b.add(a);
-                    }),
-                    this
-                  );
-                }
-                (a = s(a)), this.node.appendChild(a.node), (a.paper = this.paper);
-              }
-              return this;
-            }),
-          (k.appendTo = function (a) {
-            return a && ((a = s(a)), a.append(this)), this;
-          }),
-          (k.prepend = function (a) {
-            if (a) {
-              if ("set" == a.type) {
-                var b,
-                  c = this;
-                return (
-                  a.forEach(function (a) {
-                    b ? b.after(a) : c.prepend(a), (b = a);
-                  }),
-                  this
-                );
-              }
-              a = s(a);
-              var d = a.parent();
-              this.node.insertBefore(a.node, this.node.firstChild),
-                this.add && this.add(),
-                (a.paper = this.paper),
-                this.parent() && this.parent().add(),
-                d && d.add();
-            }
-            return this;
-          }),
-          (k.prependTo = function (a) {
-            return (a = s(a)), a.prepend(this), this;
-          }),
-          (k.before = function (a) {
-            if ("set" == a.type) {
-              var b = this;
-              return (
-                a.forEach(function (a) {
-                  var c = a.parent();
-                  b.node.parentNode.insertBefore(a.node, b.node), c && c.add();
-                }),
-                this.parent().add(),
-                this
-              );
-            }
-            a = s(a);
-            var c = a.parent();
-            return (
-              this.node.parentNode.insertBefore(a.node, this.node),
-              this.parent() && this.parent().add(),
-              c && c.add(),
-              (a.paper = this.paper),
-              this
-            );
-          }),
-          (k.after = function (a) {
-            a = s(a);
-            var b = a.parent();
-            return (
-              this.node.nextSibling
-                ? this.node.parentNode.insertBefore(a.node, this.node.nextSibling)
-                : this.node.parentNode.appendChild(a.node),
-              this.parent() && this.parent().add(),
-              b && b.add(),
-              (a.paper = this.paper),
-              this
-            );
-          }),
-          (k.insertBefore = function (a) {
-            a = s(a);
-            var b = this.parent();
-            return (
-              a.node.parentNode.insertBefore(this.node, a.node),
-              (this.paper = a.paper),
-              b && b.add(),
-              a.parent() && a.parent().add(),
-              this
-            );
-          }),
-          (k.insertAfter = function (a) {
-            a = s(a);
-            var b = this.parent();
-            return (
-              a.node.parentNode.insertBefore(this.node, a.node.nextSibling),
-              (this.paper = a.paper),
-              b && b.add(),
-              a.parent() && a.parent().add(),
-              this
-            );
-          }),
-          (k.remove = function () {
-            var a = this.parent();
-            return (
-              this.node.parentNode && this.node.parentNode.removeChild(this.node),
-              delete this.paper,
-              (this.removed = !0),
-              a && a.add(),
-              this
-            );
-          }),
-          (k.select = function (a) {
-            return s(this.node.querySelector(a));
-          }),
-          (k.selectAll = function (a) {
-            for (
-              var b = this.node.querySelectorAll(a), d = (c.set || Array)(), e = 0;
-              e < b.length;
-              e++
-            )
-              d.push(s(b[e]));
-            return d;
-          }),
-          (k.asPX = function (a, b) {
-            return null == b && (b = this.attr(a)), +n(this, a, b);
-          }),
-          (k.use = function () {
-            var a,
-              b = this.node.id;
-            return (
-              b || ((b = this.id), o(this.node, { id: b })),
-              (a =
-                "linearGradient" == this.type ||
-                "radialGradient" == this.type ||
-                "pattern" == this.type
-                  ? p(this.type, this.node.parentNode)
-                  : p("use", this.node.parentNode)),
-              o(a.node, { "xlink:href": "#" + b }),
-              (a.original = this),
-              a
-            );
-          }),
-          (k.clone = function () {
-            var a = s(this.node.cloneNode(!0));
-            return o(a.node, "id") && o(a.node, { id: a.id }), i(a), a.insertAfter(this), a;
-          }),
-          (k.toDefs = function () {
-            var a = q(this);
-            return a.appendChild(this.node), this;
-          }),
-          (k.pattern = k.toPattern =
-            function (a, b, c, d) {
-              var e = p("pattern", q(this));
-              return (
-                null == a && (a = this.getBBox()),
-                l(a, "object") && "x" in a && ((b = a.y), (c = a.width), (d = a.height), (a = a.x)),
-                o(e.node, {
-                  x: a,
-                  y: b,
-                  width: c,
-                  height: d,
-                  patternUnits: "userSpaceOnUse",
-                  id: e.id,
-                  viewBox: [a, b, c, d].join(" "),
-                }),
-                e.node.appendChild(this.node),
-                e
-              );
-            }),
-          (k.marker = function (a, b, c, d, e, f) {
-            var g = p("marker", q(this));
-            return (
-              null == a && (a = this.getBBox()),
-              l(a, "object") &&
-                "x" in a &&
-                ((b = a.y),
-                (c = a.width),
-                (d = a.height),
-                (e = a.refX || a.cx),
-                (f = a.refY || a.cy),
-                (a = a.x)),
-              o(g.node, {
-                viewBox: [a, b, c, d].join(" "),
-                markerWidth: c,
-                markerHeight: d,
-                orient: "auto",
-                refX: e || 0,
-                refY: f || 0,
-                id: g.id,
-              }),
-              g.node.appendChild(this.node),
-              g
-            );
-          });
-        var u = {};
-        (k.data = function (a, d) {
-          var e = (u[this.id] = u[this.id] || {});
-          if (0 == arguments.length) return b("snap.data.get." + this.id, this, e, null), e;
-          if (1 == arguments.length) {
-            if (c.is(a, "object")) {
-              for (var f in a) a[r](f) && this.data(f, a[f]);
-              return this;
-            }
-            return b("snap.data.get." + this.id, this, e[a], a), e[a];
-          }
-          return (e[a] = d), b("snap.data.set." + this.id, this, d, a), this;
-        }),
-          (k.removeData = function (a) {
-            return null == a ? (u[this.id] = {}) : u[this.id] && delete u[this.id][a], this;
-          }),
-          (k.outerSVG = k.toString = j(1)),
-          (k.innerSVG = j()),
-          (k.toDataURL = function () {
-            if (a && a.btoa) {
-              var b = this.getBBox(),
-                d = c.format(
-                  '<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="{width}" height="{height}" viewBox="{x} {y} {width} {height}">{contents}</svg>',
-                  {
-                    x: +b.x.toFixed(3),
-                    y: +b.y.toFixed(3),
-                    width: +b.width.toFixed(3),
-                    height: +b.height.toFixed(3),
-                    contents: this.outerSVG(),
-                  }
-                );
-              return "data:image/svg+xml;base64," + btoa(unescape(encodeURIComponent(d)));
-            }
-          }),
-          (g.prototype.select = k.select),
-          (g.prototype.selectAll = k.selectAll);
-      }),
-      d.plugin(function (a, d, e, f, g) {
-        function h(a, b, c) {
-          return function (d) {
-            var e = d.slice(a, b);
-            return 1 == e.length && (e = e[0]), c ? c(e) : e;
-          };
-        }
-        var i = d.prototype,
-          j = a.is,
-          k = String,
-          l = "hasOwnProperty",
-          m = function (a, b, d, e) {
-            "function" != typeof d || d.length || ((e = d), (d = c.linear)),
-              (this.attr = a),
-              (this.dur = b),
-              d && (this.easing = d),
-              e && (this.callback = e);
-          };
-        (a._.Animation = m),
-          (a.animation = function (a, b, c, d) {
-            return new m(a, b, c, d);
-          }),
-          (i.inAnim = function () {
-            var a = this,
-              b = [];
-            for (var c in a.anims)
-              a.anims[l](c) &&
-                !(function (a) {
-                  b.push({
-                    anim: new m(a._attrs, a.dur, a.easing, a._callback),
-                    mina: a,
-                    curStatus: a.status(),
-                    status: function (b) {
-                      return a.status(b);
-                    },
-                    stop: function () {
-                      a.stop();
-                    },
-                  });
-                })(a.anims[c]);
-            return b;
-          }),
-          (a.animate = function (a, d, e, f, g, h) {
-            "function" != typeof g || g.length || ((h = g), (g = c.linear));
-            var i = c.time(),
-              j = c(a, d, i, i + f, c.time, e, g);
-            return h && b.once("mina.finish." + j.id, h), j;
-          }),
-          (i.stop = function () {
-            for (var a = this.inAnim(), b = 0, c = a.length; c > b; b++) a[b].stop();
-            return this;
-          }),
-          (i.animate = function (a, d, e, f) {
-            "function" != typeof e || e.length || ((f = e), (e = c.linear)),
-              a instanceof m && ((f = a.callback), (e = a.easing), (d = a.dur), (a = a.attr));
-            var g,
-              i,
-              n,
-              o,
-              p = [],
-              q = [],
-              r = {},
-              s = this;
-            for (var t in a)
-              if (a[l](t)) {
-                s.equal
-                  ? ((o = s.equal(t, k(a[t]))), (g = o.from), (i = o.to), (n = o.f))
-                  : ((g = +s.attr(t)), (i = +a[t]));
-                var u = j(g, "array") ? g.length : 1;
-                (r[t] = h(p.length, p.length + u, n)), (p = p.concat(g)), (q = q.concat(i));
-              }
-            var v = c.time(),
-              w = c(
-                p,
-                q,
-                v,
-                v + d,
-                c.time,
-                function (a) {
-                  var b = {};
-                  for (var c in r) r[l](c) && (b[c] = r[c](a));
-                  s.attr(b);
-                },
-                e
-              );
-            return (
-              (s.anims[w.id] = w),
-              (w._attrs = a),
-              (w._callback = f),
-              b("snap.animcreated." + s.id, w),
-              b.once("mina.finish." + w.id, function () {
-                b.off("mina.*." + w.id), delete s.anims[w.id], f && f.call(s);
-              }),
-              b.once("mina.stop." + w.id, function () {
-                b.off("mina.*." + w.id), delete s.anims[w.id];
-              }),
-              s
-            );
-          });
-      }),
-      d.plugin(function (a, b, c, d, e) {
-        function f(a, b, c, d, e, f) {
-          return null == b && "[object SVGMatrix]" == g.call(a)
-            ? ((this.a = a.a),
-              (this.b = a.b),
-              (this.c = a.c),
-              (this.d = a.d),
-              (this.e = a.e),
-              void (this.f = a.f))
-            : void (null != a
-                ? ((this.a = +a),
-                  (this.b = +b),
-                  (this.c = +c),
-                  (this.d = +d),
-                  (this.e = +e),
-                  (this.f = +f))
-                : ((this.a = 1),
-                  (this.b = 0),
-                  (this.c = 0),
-                  (this.d = 1),
-                  (this.e = 0),
-                  (this.f = 0)));
-        }
-        var g = Object.prototype.toString,
-          h = String,
-          i = Math,
-          j = "";
-        !(function (b) {
-          function c(a) {
-            return a[0] * a[0] + a[1] * a[1];
-          }
-          function d(a) {
-            var b = i.sqrt(c(a));
-            a[0] && (a[0] /= b), a[1] && (a[1] /= b);
-          }
-          (b.add = function (a, b, c, d, e, g) {
-            if (a && a instanceof f) return this.add(a.a, a.b, a.c, a.d, a.e, a.f);
-            var h = a * this.a + b * this.c,
-              i = a * this.b + b * this.d;
-            return (
-              (this.e += e * this.a + g * this.c),
-              (this.f += e * this.b + g * this.d),
-              (this.c = c * this.a + d * this.c),
-              (this.d = c * this.b + d * this.d),
-              (this.a = h),
-              (this.b = i),
-              this
-            );
-          }),
-            (f.prototype.multLeft = function (a, b, c, d, e, g) {
-              if (a && a instanceof f) return this.multLeft(a.a, a.b, a.c, a.d, a.e, a.f);
-              var h = a * this.a + c * this.b,
-                i = a * this.c + c * this.d,
-                j = a * this.e + c * this.f + e;
-              return (
-                (this.b = b * this.a + d * this.b),
-                (this.d = b * this.c + d * this.d),
-                (this.f = b * this.e + d * this.f + g),
-                (this.a = h),
-                (this.c = i),
-                (this.e = j),
-                this
-              );
-            }),
-            (b.invert = function () {
-              var a = this,
-                b = a.a * a.d - a.b * a.c;
-              return new f(
-                a.d / b,
-                -a.b / b,
-                -a.c / b,
-                a.a / b,
-                (a.c * a.f - a.d * a.e) / b,
-                (a.b * a.e - a.a * a.f) / b
-              );
-            }),
-            (b.clone = function () {
-              return new f(this.a, this.b, this.c, this.d, this.e, this.f);
-            }),
-            (b.translate = function (a, b) {
-              return (this.e += a * this.a + b * this.c), (this.f += a * this.b + b * this.d), this;
-            }),
-            (b.scale = function (a, b, c, d) {
-              return (
-                null == b && (b = a),
-                (c || d) && this.translate(c, d),
-                (this.a *= a),
-                (this.b *= a),
-                (this.c *= b),
-                (this.d *= b),
-                (c || d) && this.translate(-c, -d),
-                this
-              );
-            }),
-            (b.rotate = function (b, c, d) {
-              (b = a.rad(b)), (c = c || 0), (d = d || 0);
-              var e = +i.cos(b).toFixed(9),
-                f = +i.sin(b).toFixed(9);
-              return this.add(e, f, -f, e, c, d), this.add(1, 0, 0, 1, -c, -d);
-            }),
-            (b.skewX = function (a) {
-              return this.skew(a, 0);
-            }),
-            (b.skewY = function (a) {
-              return this.skew(0, a);
-            }),
-            (b.skew = function (b, c) {
-              (b = b || 0), (c = c || 0), (b = a.rad(b)), (c = a.rad(c));
-              var d = i.tan(b).toFixed(9),
-                e = i.tan(c).toFixed(9);
-              return this.add(1, e, d, 1, 0, 0);
-            }),
-            (b.x = function (a, b) {
-              return a * this.a + b * this.c + this.e;
-            }),
-            (b.y = function (a, b) {
-              return a * this.b + b * this.d + this.f;
-            }),
-            (b.get = function (a) {
-              return +this[h.fromCharCode(97 + a)].toFixed(4);
-            }),
-            (b.toString = function () {
-              return (
-                "matrix(" +
-                [
-                  this.get(0),
-                  this.get(1),
-                  this.get(2),
-                  this.get(3),
-                  this.get(4),
-                  this.get(5),
-                ].join() +
-                ")"
-              );
-            }),
-            (b.offset = function () {
-              return [this.e.toFixed(4), this.f.toFixed(4)];
-            }),
-            (b.determinant = function () {
-              return this.a * this.d - this.b * this.c;
-            }),
-            (b.split = function () {
-              var b = {};
-              (b.dx = this.e), (b.dy = this.f);
-              var e = [
-                [this.a, this.b],
-                [this.c, this.d],
-              ];
-              (b.scalex = i.sqrt(c(e[0]))),
-                d(e[0]),
-                (b.shear = e[0][0] * e[1][0] + e[0][1] * e[1][1]),
-                (e[1] = [e[1][0] - e[0][0] * b.shear, e[1][1] - e[0][1] * b.shear]),
-                (b.scaley = i.sqrt(c(e[1]))),
-                d(e[1]),
-                (b.shear /= b.scaley),
-                this.determinant() < 0 && (b.scalex = -b.scalex);
-              var f = e[0][1],
-                g = e[1][1];
-              return (
-                0 > g
-                  ? ((b.rotate = a.deg(i.acos(g))), 0 > f && (b.rotate = 360 - b.rotate))
-                  : (b.rotate = a.deg(i.asin(f))),
-                (b.isSimple = !(
-                  +b.shear.toFixed(9) ||
-                  (b.scalex.toFixed(9) != b.scaley.toFixed(9) && b.rotate)
-                )),
-                (b.isSuperSimple =
-                  !+b.shear.toFixed(9) && b.scalex.toFixed(9) == b.scaley.toFixed(9) && !b.rotate),
-                (b.noRotation = !+b.shear.toFixed(9) && !b.rotate),
-                b
-              );
-            }),
-            (b.toTransformString = function (a) {
-              var b = a || this.split();
-              return +b.shear.toFixed(9)
-                ? "m" +
-                    [this.get(0), this.get(1), this.get(2), this.get(3), this.get(4), this.get(5)]
-                : ((b.scalex = +b.scalex.toFixed(4)),
-                  (b.scaley = +b.scaley.toFixed(4)),
-                  (b.rotate = +b.rotate.toFixed(4)),
-                  (b.dx || b.dy ? "t" + [+b.dx.toFixed(4), +b.dy.toFixed(4)] : j) +
-                    (b.rotate ? "r" + [+b.rotate.toFixed(4), 0, 0] : j) +
-                    (1 != b.scalex || 1 != b.scaley ? "s" + [b.scalex, b.scaley, 0, 0] : j));
-            });
-        })(f.prototype),
-          (a.Matrix = f),
-          (a.matrix = function (a, b, c, d, e, g) {
-            return new f(a, b, c, d, e, g);
-          });
-      }),
-      d.plugin(function (a, c, d, e, f) {
-        function g(d) {
-          return function (e) {
-            if (
-              (b.stop(),
-              e instanceof f &&
-                1 == e.node.childNodes.length &&
-                ("radialGradient" == e.node.firstChild.tagName ||
-                  "linearGradient" == e.node.firstChild.tagName ||
-                  "pattern" == e.node.firstChild.tagName) &&
-                ((e = e.node.firstChild), n(this).appendChild(e), (e = l(e))),
-              e instanceof c)
-            )
-              if ("radialGradient" == e.type || "linearGradient" == e.type || "pattern" == e.type) {
-                e.node.id || p(e.node, { id: e.id });
-                var g = q(e.node.id);
-              } else g = e.attr(d);
-            else if (((g = a.color(e)), g.error)) {
-              var h = a(n(this).ownerSVGElement).gradient(e);
-              h ? (h.node.id || p(h.node, { id: h.id }), (g = q(h.node.id))) : (g = e);
-            } else g = r(g);
-            var i = {};
-            (i[d] = g), p(this.node, i), (this.node.style[d] = t);
-          };
-        }
-        function h(a) {
-          b.stop(), a == +a && (a += "px"), (this.node.style.fontSize = a);
-        }
-        function i(a) {
-          for (var b = [], c = a.childNodes, d = 0, e = c.length; e > d; d++) {
-            var f = c[d];
-            3 == f.nodeType && b.push(f.nodeValue),
-              "tspan" == f.tagName &&
-                (1 == f.childNodes.length && 3 == f.firstChild.nodeType
-                  ? b.push(f.firstChild.nodeValue)
-                  : b.push(i(f)));
-          }
-          return b;
-        }
-        function j() {
-          return b.stop(), this.node.style.fontSize;
-        }
-        var k = a._.make,
-          l = a._.wrap,
-          m = a.is,
-          n = a._.getSomeDefs,
-          o = /^url\((['"]?)([^)]+)\1\)$/,
-          p = a._.$,
-          q = a.url,
-          r = String,
-          s = a._.separator,
-          t = "";
-        (a.deurl = function (a) {
-          var b = String(a).match(o);
-          return b ? b[2] : a;
-        }),
-          b.on("snap.util.attr.mask", function (a) {
-            if (a instanceof c || a instanceof f) {
-              if (
-                (b.stop(),
-                a instanceof f &&
-                  1 == a.node.childNodes.length &&
-                  ((a = a.node.firstChild), n(this).appendChild(a), (a = l(a))),
-                "mask" == a.type)
-              )
-                var d = a;
-              else (d = k("mask", n(this))), d.node.appendChild(a.node);
-              !d.node.id && p(d.node, { id: d.id }), p(this.node, { mask: q(d.id) });
-            }
-          }),
-          (function (a) {
-            b.on("snap.util.attr.clip", a),
-              b.on("snap.util.attr.clip-path", a),
-              b.on("snap.util.attr.clipPath", a);
-          })(function (a) {
-            if (a instanceof c || a instanceof f) {
-              b.stop();
-              for (var d, e = a.node; e; ) {
-                if ("clipPath" === e.nodeName) {
-                  d = new c(e);
-                  break;
-                }
-                if ("svg" === e.nodeName) {
-                  d = void 0;
-                  break;
-                }
-                e = e.parentNode;
-              }
-              d ||
-                ((d = k("clipPath", n(this))),
-                d.node.appendChild(a.node),
-                !d.node.id && p(d.node, { id: d.id })),
-                p(this.node, { "clip-path": q(d.node.id || d.id) });
-            }
-          }),
-          b.on("snap.util.attr.fill", g("fill")),
-          b.on("snap.util.attr.stroke", g("stroke"));
-        var u = /^([lr])(?:\(([^)]*)\))?(.*)$/i;
-        b.on("snap.util.grad.parse", function (a) {
-          function b(a, b) {
-            for (var c = (b - h) / (a - i), d = i; a > d; d++)
-              f[d].offset = +(+h + c * (d - i)).toFixed(2);
-            (i = a), (h = b);
-          }
-          a = r(a);
-          var c = a.match(u);
-          if (!c) return null;
-          var d = c[1],
-            e = c[2],
-            f = c[3];
-          (e = e.split(/\s*,\s*/).map(function (a) {
-            return +a == a ? +a : a;
-          })),
-            1 == e.length && 0 == e[0] && (e = []),
-            (f = f.split("-")),
-            (f = f.map(function (a) {
-              a = a.split(":");
-              var b = { color: a[0] };
-              return a[1] && (b.offset = parseFloat(a[1])), b;
-            }));
-          var g = f.length,
-            h = 0,
-            i = 0;
-          g--;
-          for (var j = 0; g > j; j++) "offset" in f[j] && b(j, f[j].offset);
-          return (
-            (f[g].offset = f[g].offset || 100), b(g, f[g].offset), { type: d, params: e, stops: f }
-          );
-        }),
-          b.on("snap.util.attr.d", function (c) {
-            b.stop(),
-              m(c, "array") && m(c[0], "array") && (c = a.path.toString.call(c)),
-              (c = r(c)),
-              c.match(/[ruo]/i) && (c = a.path.toAbsolute(c)),
-              p(this.node, { d: c });
-          })(-1),
-          b.on("snap.util.attr.#text", function (a) {
-            b.stop(), (a = r(a));
-            for (var c = e.doc.createTextNode(a); this.node.firstChild; )
-              this.node.removeChild(this.node.firstChild);
-            this.node.appendChild(c);
-          })(-1),
-          b.on("snap.util.attr.path", function (a) {
-            b.stop(), this.attr({ d: a });
-          })(-1),
-          b.on("snap.util.attr.class", function (a) {
-            b.stop(), (this.node.className.baseVal = a);
-          })(-1),
-          b.on("snap.util.attr.viewBox", function (a) {
-            var c;
-            (c =
-              m(a, "object") && "x" in a
-                ? [a.x, a.y, a.width, a.height].join(" ")
-                : m(a, "array")
-                ? a.join(" ")
-                : a),
-              p(this.node, { viewBox: c }),
-              b.stop();
-          })(-1),
-          b.on("snap.util.attr.transform", function (a) {
-            this.transform(a), b.stop();
-          })(-1),
-          b.on("snap.util.attr.r", function (a) {
-            "rect" == this.type && (b.stop(), p(this.node, { rx: a, ry: a }));
-          })(-1),
-          b.on("snap.util.attr.textpath", function (a) {
-            if ((b.stop(), "text" == this.type)) {
-              var d, e, f;
-              if (!a && this.textPath) {
-                for (e = this.textPath; e.node.firstChild; )
-                  this.node.appendChild(e.node.firstChild);
-                return e.remove(), void delete this.textPath;
-              }
-              if (m(a, "string")) {
-                var g = n(this),
-                  h = l(g.parentNode).path(a);
-                g.appendChild(h.node), (d = h.id), h.attr({ id: d });
-              } else
-                (a = l(a)),
-                  a instanceof c && ((d = a.attr("id")), d || ((d = a.id), a.attr({ id: d })));
-              if (d)
-                if (((e = this.textPath), (f = this.node), e)) e.attr({ "xlink:href": "#" + d });
-                else {
-                  for (e = p("textPath", { "xlink:href": "#" + d }); f.firstChild; )
-                    e.appendChild(f.firstChild);
-                  f.appendChild(e), (this.textPath = l(e));
-                }
-            }
-          })(-1),
-          b.on("snap.util.attr.text", function (a) {
-            if ("text" == this.type) {
-              for (
-                var c = this.node,
-                  d = function (a) {
-                    var b = p("tspan");
-                    if (m(a, "array")) for (var c = 0; c < a.length; c++) b.appendChild(d(a[c]));
-                    else b.appendChild(e.doc.createTextNode(a));
-                    return b.normalize && b.normalize(), b;
-                  };
-                c.firstChild;
-
-              )
-                c.removeChild(c.firstChild);
-              for (var f = d(a); f.firstChild; ) c.appendChild(f.firstChild);
-            }
-            b.stop();
-          })(-1),
-          b.on("snap.util.attr.fontSize", h)(-1),
-          b.on("snap.util.attr.font-size", h)(-1),
-          b.on("snap.util.getattr.transform", function () {
-            return b.stop(), this.transform();
-          })(-1),
-          b.on("snap.util.getattr.textpath", function () {
-            return b.stop(), this.textPath;
-          })(-1),
-          (function () {
-            function c(c) {
-              return function () {
-                b.stop();
-                var d = e.doc.defaultView
-                  .getComputedStyle(this.node, null)
-                  .getPropertyValue("marker-" + c);
-                return "none" == d ? d : a(e.doc.getElementById(d.match(o)[1]));
-              };
-            }
-            function d(a) {
-              return function (c) {
-                b.stop();
-                var d = "marker" + a.charAt(0).toUpperCase() + a.substring(1);
-                if ("" == c || !c) return void (this.node.style[d] = "none");
-                if ("marker" == c.type) {
-                  var e = c.node.id;
-                  return e || p(c.node, { id: c.id }), void (this.node.style[d] = q(e));
-                }
-              };
-            }
-            b.on("snap.util.getattr.marker-end", c("end"))(-1),
-              b.on("snap.util.getattr.markerEnd", c("end"))(-1),
-              b.on("snap.util.getattr.marker-start", c("start"))(-1),
-              b.on("snap.util.getattr.markerStart", c("start"))(-1),
-              b.on("snap.util.getattr.marker-mid", c("mid"))(-1),
-              b.on("snap.util.getattr.markerMid", c("mid"))(-1),
-              b.on("snap.util.attr.marker-end", d("end"))(-1),
-              b.on("snap.util.attr.markerEnd", d("end"))(-1),
-              b.on("snap.util.attr.marker-start", d("start"))(-1),
-              b.on("snap.util.attr.markerStart", d("start"))(-1),
-              b.on("snap.util.attr.marker-mid", d("mid"))(-1),
-              b.on("snap.util.attr.markerMid", d("mid"))(-1);
-          })(),
-          b.on("snap.util.getattr.r", function () {
-            return "rect" == this.type && p(this.node, "rx") == p(this.node, "ry")
-              ? (b.stop(), p(this.node, "rx"))
-              : void 0;
-          })(-1),
-          b.on("snap.util.getattr.text", function () {
-            if ("text" == this.type || "tspan" == this.type) {
-              b.stop();
-              var a = i(this.node);
-              return 1 == a.length ? a[0] : a;
-            }
-          })(-1),
-          b.on("snap.util.getattr.#text", function () {
-            return this.node.textContent;
-          })(-1),
-          b.on("snap.util.getattr.fill", function (c) {
-            if (!c) {
-              b.stop();
-              var d = b("snap.util.getattr.fill", this, !0).firstDefined();
-              return a(a.deurl(d)) || d;
-            }
-          })(-1),
-          b.on("snap.util.getattr.stroke", function (c) {
-            if (!c) {
-              b.stop();
-              var d = b("snap.util.getattr.stroke", this, !0).firstDefined();
-              return a(a.deurl(d)) || d;
-            }
-          })(-1),
-          b.on("snap.util.getattr.viewBox", function () {
-            b.stop();
-            var c = p(this.node, "viewBox");
-            return c ? ((c = c.split(s)), a._.box(+c[0], +c[1], +c[2], +c[3])) : void 0;
-          })(-1),
-          b.on("snap.util.getattr.points", function () {
-            var a = p(this.node, "points");
-            return b.stop(), a ? a.split(s) : void 0;
-          })(-1),
-          b.on("snap.util.getattr.path", function () {
-            var a = p(this.node, "d");
-            return b.stop(), a;
-          })(-1),
-          b.on("snap.util.getattr.class", function () {
-            return this.node.className.baseVal;
-          })(-1),
-          b.on("snap.util.getattr.fontSize", j)(-1),
-          b.on("snap.util.getattr.font-size", j)(-1);
-      }),
-      d.plugin(function (a, b, c, d, e) {
-        var f = /\S+/g,
-          g = String,
-          h = b.prototype;
-        (h.addClass = function (a) {
-          var b,
-            c,
-            d,
-            e,
-            h = g(a || "").match(f) || [],
-            i = this.node,
-            j = i.className.baseVal,
-            k = j.match(f) || [];
-          if (h.length) {
-            for (b = 0; (d = h[b++]); ) (c = k.indexOf(d)), ~c || k.push(d);
-            (e = k.join(" ")), j != e && (i.className.baseVal = e);
-          }
-          return this;
-        }),
-          (h.removeClass = function (a) {
-            var b,
-              c,
-              d,
-              e,
-              h = g(a || "").match(f) || [],
-              i = this.node,
-              j = i.className.baseVal,
-              k = j.match(f) || [];
-            if (k.length) {
-              for (b = 0; (d = h[b++]); ) (c = k.indexOf(d)), ~c && k.splice(c, 1);
-              (e = k.join(" ")), j != e && (i.className.baseVal = e);
-            }
-            return this;
-          }),
-          (h.hasClass = function (a) {
-            var b = this.node,
-              c = b.className.baseVal,
-              d = c.match(f) || [];
-            return !!~d.indexOf(a);
-          }),
-          (h.toggleClass = function (a, b) {
-            if (null != b) return b ? this.addClass(a) : this.removeClass(a);
-            var c,
-              d,
-              e,
-              g,
-              h = (a || "").match(f) || [],
-              i = this.node,
-              j = i.className.baseVal,
-              k = j.match(f) || [];
-            for (c = 0; (e = h[c++]); ) (d = k.indexOf(e)), ~d ? k.splice(d, 1) : k.push(e);
-            return (g = k.join(" ")), j != g && (i.className.baseVal = g), this;
-          });
-      }),
-      d.plugin(function (a, c, d, e, f) {
-        function g(a) {
-          return a;
-        }
-        function h(a) {
-          return function (b) {
-            return +b.toFixed(3) + a;
-          };
-        }
-        var i = {
-            "+": function (a, b) {
-              return a + b;
-            },
-            "-": function (a, b) {
-              return a - b;
-            },
-            "/": function (a, b) {
-              return a / b;
-            },
-            "*": function (a, b) {
-              return a * b;
-            },
-          },
-          j = String,
-          k = /[a-z]+$/i,
-          l = /^\s*([+\-\/*])\s*=\s*([\d.eE+\-]+)\s*([^\d\s]+)?\s*$/;
-        b.on("snap.util.attr", function (a) {
-          var c = j(a).match(l);
-          if (c) {
-            var d = b.nt(),
-              e = d.substring(d.lastIndexOf(".") + 1),
-              f = this.attr(e),
-              g = {};
-            b.stop();
-            var h = c[3] || "",
-              m = f.match(k),
-              n = i[c[1]];
-            if (
-              (m && m == h
-                ? (a = n(parseFloat(f), +c[2]))
-                : ((f = this.asPX(e)), (a = n(this.asPX(e), this.asPX(e, c[2] + h)))),
-              isNaN(f) || isNaN(a))
-            )
-              return;
-            (g[e] = a), this.attr(g);
-          }
-        })(-10),
-          b.on("snap.util.equal", function (a, c) {
-            var d = j(this.attr(a) || ""),
-              e = j(c).match(l);
-            if (e) {
-              b.stop();
-              var f = e[3] || "",
-                m = d.match(k),
-                n = i[e[1]];
-              return m && m == f
-                ? { from: parseFloat(d), to: n(parseFloat(d), +e[2]), f: h(m) }
-                : ((d = this.asPX(a)), { from: d, to: n(d, this.asPX(a, e[2] + f)), f: g });
-            }
-          })(-10);
-      }),
-      d.plugin(function (c, d, e, f, g) {
-        var h = e.prototype,
-          i = c.is;
-        (h.rect = function (a, b, c, d, e, f) {
-          var g;
-          return (
-            null == f && (f = e),
-            i(a, "object") && "[object Object]" == a
-              ? (g = a)
-              : null != a &&
-                ((g = { x: a, y: b, width: c, height: d }), null != e && ((g.rx = e), (g.ry = f))),
-            this.el("rect", g)
-          );
-        }),
-          (h.circle = function (a, b, c) {
-            var d;
-            return (
-              i(a, "object") && "[object Object]" == a
-                ? (d = a)
-                : null != a && (d = { cx: a, cy: b, r: c }),
-              this.el("circle", d)
-            );
-          });
-        var j = (function () {
-          function a() {
-            this.parentNode.removeChild(this);
-          }
-          return function (b, c) {
-            var d = f.doc.createElement("img"),
-              e = f.doc.body;
-            (d.style.cssText = "position:absolute;left:-9999em;top:-9999em"),
-              (d.onload = function () {
-                c.call(d), (d.onload = d.onerror = null), e.removeChild(d);
-              }),
-              (d.onerror = a),
-              e.appendChild(d),
-              (d.src = b);
-          };
-        })();
-        (h.image = function (a, b, d, e, f) {
-          var g = this.el("image");
-          if (i(a, "object") && "src" in a) g.attr(a);
-          else if (null != a) {
-            var h = { "xlink:href": a, preserveAspectRatio: "none" };
-            null != b && null != d && ((h.x = b), (h.y = d)),
-              null != e && null != f
-                ? ((h.width = e), (h.height = f))
-                : j(a, function () {
-                    c._.$(g.node, { width: this.offsetWidth, height: this.offsetHeight });
-                  }),
-              c._.$(g.node, h);
-          }
-          return g;
-        }),
-          (h.ellipse = function (a, b, c, d) {
-            var e;
-            return (
-              i(a, "object") && "[object Object]" == a
-                ? (e = a)
-                : null != a && (e = { cx: a, cy: b, rx: c, ry: d }),
-              this.el("ellipse", e)
-            );
-          }),
-          (h.path = function (a) {
-            var b;
-            return (
-              i(a, "object") && !i(a, "array") ? (b = a) : a && (b = { d: a }), this.el("path", b)
-            );
-          }),
-          (h.group = h.g =
-            function (a) {
-              var b = this.el("g");
-              return (
-                1 == arguments.length && a && !a.type
-                  ? b.attr(a)
-                  : arguments.length && b.add(Array.prototype.slice.call(arguments, 0)),
-                b
-              );
-            }),
-          (h.svg = function (a, b, c, d, e, f, g, h) {
-            var j = {};
-            return (
-              i(a, "object") && null == b
-                ? (j = a)
-                : (null != a && (j.x = a),
-                  null != b && (j.y = b),
-                  null != c && (j.width = c),
-                  null != d && (j.height = d),
-                  null != e && null != f && null != g && null != h && (j.viewBox = [e, f, g, h])),
-              this.el("svg", j)
-            );
-          }),
-          (h.mask = function (a) {
-            var b = this.el("mask");
-            return (
-              1 == arguments.length && a && !a.type
-                ? b.attr(a)
-                : arguments.length && b.add(Array.prototype.slice.call(arguments, 0)),
-              b
-            );
-          }),
-          (h.ptrn = function (a, b, c, d, e, f, g, h) {
-            if (i(a, "object")) var j = a;
-            else
-              (j = { patternUnits: "userSpaceOnUse" }),
-                a && (j.x = a),
-                b && (j.y = b),
-                null != c && (j.width = c),
-                null != d && (j.height = d),
-                null != e && null != f && null != g && null != h
-                  ? (j.viewBox = [e, f, g, h])
-                  : (j.viewBox = [a || 0, b || 0, c || 0, d || 0]);
-            return this.el("pattern", j);
-          }),
-          (h.use = function (a) {
-            return null != a
-              ? (a instanceof d && (a.attr("id") || a.attr({ id: c._.id(a) }), (a = a.attr("id"))),
-                "#" == String(a).charAt() && (a = a.substring(1)),
-                this.el("use", { "xlink:href": "#" + a }))
-              : d.prototype.use.call(this);
-          }),
-          (h.symbol = function (a, b, c, d) {
-            var e = {};
-            return (
-              null != a && null != b && null != c && null != d && (e.viewBox = [a, b, c, d]),
-              this.el("symbol", e)
-            );
-          }),
-          (h.text = function (a, b, c) {
-            var d = {};
-            return (
-              i(a, "object") ? (d = a) : null != a && (d = { x: a, y: b, text: c || "" }),
-              this.el("text", d)
-            );
-          }),
-          (h.line = function (a, b, c, d) {
-            var e = {};
-            return (
-              i(a, "object") ? (e = a) : null != a && (e = { x1: a, x2: c, y1: b, y2: d }),
-              this.el("line", e)
-            );
-          }),
-          (h.polyline = function (a) {
-            arguments.length > 1 && (a = Array.prototype.slice.call(arguments, 0));
-            var b = {};
-            return (
-              i(a, "object") && !i(a, "array") ? (b = a) : null != a && (b = { points: a }),
-              this.el("polyline", b)
-            );
-          }),
-          (h.polygon = function (a) {
-            arguments.length > 1 && (a = Array.prototype.slice.call(arguments, 0));
-            var b = {};
-            return (
-              i(a, "object") && !i(a, "array") ? (b = a) : null != a && (b = { points: a }),
-              this.el("polygon", b)
-            );
-          }),
-          (function () {
-            function d() {
-              return this.selectAll("stop");
-            }
-            function e(a, b) {
-              var d = l("stop"),
-                e = { offset: +b + "%" };
-              (a = c.color(a)),
-                (e["stop-color"] = a.hex),
-                a.opacity < 1 && (e["stop-opacity"] = a.opacity),
-                l(d, e);
-              for (var f, g = this.stops(), h = 0; h < g.length; h++) {
-                var i = parseFloat(g[h].attr("offset"));
-                if (i > b) {
-                  this.node.insertBefore(d, g[h].node), (f = !0);
-                  break;
-                }
-              }
-              return f || this.node.appendChild(d), this;
-            }
-            function f() {
-              if ("linearGradient" == this.type) {
-                var a = l(this.node, "x1") || 0,
-                  b = l(this.node, "x2") || 1,
-                  d = l(this.node, "y1") || 0,
-                  e = l(this.node, "y2") || 0;
-                return c._.box(a, d, math.abs(b - a), math.abs(e - d));
-              }
-              var f = this.node.cx || 0.5,
-                g = this.node.cy || 0.5,
-                h = this.node.r || 0;
-              return c._.box(f - h, g - h, 2 * h, 2 * h);
-            }
-            function g(a) {
-              var d = a,
-                e = this.stops();
-              if (
-                ("string" == typeof a &&
-                  (d = b("snap.util.grad.parse", null, "l(0,0,0,1)" + a).firstDefined().stops),
-                c.is(d, "array"))
-              ) {
-                for (var f = 0; f < e.length; f++)
-                  if (d[f]) {
-                    var g = c.color(d[f].color),
-                      h = { offset: d[f].offset + "%" };
-                    (h["stop-color"] = g.hex),
-                      g.opacity < 1 && (h["stop-opacity"] = g.opacity),
-                      e[f].attr(h);
-                  } else e[f].remove();
-                for (f = e.length; f < d.length; f++) this.addStop(d[f].color, d[f].offset);
-                return this;
-              }
-            }
-            function i(a, c) {
-              var d,
-                e = b("snap.util.grad.parse", null, c).firstDefined();
-              if (!e) return null;
-              e.params.unshift(a),
-                (d = "l" == e.type.toLowerCase() ? j.apply(0, e.params) : k.apply(0, e.params)),
-                e.type != e.type.toLowerCase() && l(d.node, { gradientUnits: "userSpaceOnUse" });
-              for (var f = e.stops, g = f.length, h = 0; g > h; h++) {
-                var i = f[h];
-                d.addStop(i.color, i.offset);
-              }
-              return d;
-            }
-            function j(a, b, h, i, j) {
-              var k = c._.make("linearGradient", a);
-              return (
-                (k.stops = d),
-                (k.addStop = e),
-                (k.getBBox = f),
-                (k.setStops = g),
-                null != b && l(k.node, { x1: b, y1: h, x2: i, y2: j }),
-                k
-              );
-            }
-            function k(a, b, g, h, i, j) {
-              var k = c._.make("radialGradient", a);
-              return (
-                (k.stops = d),
-                (k.addStop = e),
-                (k.getBBox = f),
-                null != b && l(k.node, { cx: b, cy: g, r: h }),
-                null != i && null != j && l(k.node, { fx: i, fy: j }),
-                k
-              );
-            }
-            var l = c._.$;
-            (h.gradient = function (a) {
-              return i(this.defs, a);
-            }),
-              (h.gradientLinear = function (a, b, c, d) {
-                return j(this.defs, a, b, c, d);
-              }),
-              (h.gradientRadial = function (a, b, c, d, e) {
-                return k(this.defs, a, b, c, d, e);
-              }),
-              (h.toString = function () {
-                var a,
-                  b = this.node.ownerDocument,
-                  d = b.createDocumentFragment(),
-                  e = b.createElement("div"),
-                  f = this.node.cloneNode(!0);
-                return (
-                  d.appendChild(e),
-                  e.appendChild(f),
-                  c._.$(f, { xmlns: "http://www.w3.org/2000/svg" }),
-                  (a = e.innerHTML),
-                  d.removeChild(d.firstChild),
-                  a
-                );
-              }),
-              (h.toDataURL = function () {
-                return a && a.btoa
-                  ? "data:image/svg+xml;base64," + btoa(unescape(encodeURIComponent(this)))
-                  : void 0;
-              }),
-              (h.clear = function () {
-                for (var a, b = this.node.firstChild; b; )
-                  (a = b.nextSibling),
-                    "defs" != b.tagName ? b.parentNode.removeChild(b) : h.clear.call({ node: b }),
-                    (b = a);
-              });
-          })();
-      }),
-      d.plugin(function (a, b, c, d) {
-        function e(a) {
-          var b = (e.ps = e.ps || {});
-          return (
-            b[a] ? (b[a].sleep = 100) : (b[a] = { sleep: 100 }),
-            setTimeout(function () {
-              for (var c in b) b[M](c) && c != a && (b[c].sleep--, !b[c].sleep && delete b[c]);
-            }),
-            b[a]
-          );
-        }
-        function f(a, b, c, d) {
-          return (
-            null == a && (a = b = c = d = 0),
-            null == b && ((b = a.y), (c = a.width), (d = a.height), (a = a.x)),
-            {
-              x: a,
-              y: b,
-              width: c,
-              w: c,
-              height: d,
-              h: d,
-              x2: a + c,
-              y2: b + d,
-              cx: a + c / 2,
-              cy: b + d / 2,
-              r1: P.min(c, d) / 2,
-              r2: P.max(c, d) / 2,
-              r0: P.sqrt(c * c + d * d) / 2,
-              path: y(a, b, c, d),
-              vb: [a, b, c, d].join(" "),
-            }
-          );
-        }
-        function g() {
-          return this.join(",").replace(N, "$1");
-        }
-        function h(a) {
-          var b = L(a);
-          return (b.toString = g), b;
-        }
-        function i(a, b, c, d, e, f, g, h, i) {
-          return null == i
-            ? p(a, b, c, d, e, f, g, h)
-            : k(a, b, c, d, e, f, g, h, q(a, b, c, d, e, f, g, h, i));
-        }
-        function j(c, d) {
-          function e(a) {
-            return +(+a).toFixed(3);
-          }
-          return a._.cacher(
-            function (a, f, g) {
-              a instanceof b && (a = a.attr("d")), (a = G(a));
-              for (var h, j, l, m, n, o = "", p = {}, q = 0, r = 0, s = a.length; s > r; r++) {
-                if (((l = a[r]), "M" == l[0])) (h = +l[1]), (j = +l[2]);
-                else {
-                  if (((m = i(h, j, l[1], l[2], l[3], l[4], l[5], l[6])), q + m > f)) {
-                    if (d && !p.start) {
-                      if (
-                        ((n = i(h, j, l[1], l[2], l[3], l[4], l[5], l[6], f - q)),
-                        (o += [
-                          "C" + e(n.start.x),
-                          e(n.start.y),
-                          e(n.m.x),
-                          e(n.m.y),
-                          e(n.x),
-                          e(n.y),
-                        ]),
-                        g)
-                      )
-                        return o;
-                      (p.start = o),
-                        (o = [
-                          "M" + e(n.x),
-                          e(n.y) + "C" + e(n.n.x),
-                          e(n.n.y),
-                          e(n.end.x),
-                          e(n.end.y),
-                          e(l[5]),
-                          e(l[6]),
-                        ].join()),
-                        (q += m),
-                        (h = +l[5]),
-                        (j = +l[6]);
-                      continue;
-                    }
-                    if (!c && !d) return (n = i(h, j, l[1], l[2], l[3], l[4], l[5], l[6], f - q));
-                  }
-                  (q += m), (h = +l[5]), (j = +l[6]);
-                }
-                o += l.shift() + l;
-              }
-              return (
-                (p.end = o), (n = c ? q : d ? p : k(h, j, l[0], l[1], l[2], l[3], l[4], l[5], 1))
-              );
-            },
-            null,
-            a._.clone
-          );
-        }
-        function k(a, b, c, d, e, f, g, h, i) {
-          var j = 1 - i,
-            k = T(j, 3),
-            l = T(j, 2),
-            m = i * i,
-            n = m * i,
-            o = k * a + 3 * l * i * c + 3 * j * i * i * e + n * g,
-            p = k * b + 3 * l * i * d + 3 * j * i * i * f + n * h,
-            q = a + 2 * i * (c - a) + m * (e - 2 * c + a),
-            r = b + 2 * i * (d - b) + m * (f - 2 * d + b),
-            s = c + 2 * i * (e - c) + m * (g - 2 * e + c),
-            t = d + 2 * i * (f - d) + m * (h - 2 * f + d),
-            u = j * a + i * c,
-            v = j * b + i * d,
-            w = j * e + i * g,
-            x = j * f + i * h,
-            y = 90 - (180 * P.atan2(q - s, r - t)) / Q;
-          return {
-            x: o,
-            y: p,
-            m: { x: q, y: r },
-            n: { x: s, y: t },
-            start: { x: u, y: v },
-            end: { x: w, y: x },
-            alpha: y,
-          };
-        }
-        function l(b, c, d, e, g, h, i, j) {
-          a.is(b, "array") || (b = [b, c, d, e, g, h, i, j]);
-          var k = F.apply(null, b);
-          return f(k.min.x, k.min.y, k.max.x - k.min.x, k.max.y - k.min.y);
-        }
-        function m(a, b, c) {
-          return b >= a.x && b <= a.x + a.width && c >= a.y && c <= a.y + a.height;
-        }
-        function n(a, b) {
-          return (
-            (a = f(a)),
-            (b = f(b)),
-            m(b, a.x, a.y) ||
-              m(b, a.x2, a.y) ||
-              m(b, a.x, a.y2) ||
-              m(b, a.x2, a.y2) ||
-              m(a, b.x, b.y) ||
-              m(a, b.x2, b.y) ||
-              m(a, b.x, b.y2) ||
-              m(a, b.x2, b.y2) ||
-              (((a.x < b.x2 && a.x > b.x) || (b.x < a.x2 && b.x > a.x)) &&
-                ((a.y < b.y2 && a.y > b.y) || (b.y < a.y2 && b.y > a.y)))
-          );
-        }
-        function o(a, b, c, d, e) {
-          var f = -3 * b + 9 * c - 9 * d + 3 * e,
-            g = a * f + 6 * b - 12 * c + 6 * d;
-          return a * g - 3 * b + 3 * c;
-        }
-        function p(a, b, c, d, e, f, g, h, i) {
-          null == i && (i = 1), (i = i > 1 ? 1 : 0 > i ? 0 : i);
-          for (
-            var j = i / 2,
-              k = 12,
-              l = [
-                -0.1252, 0.1252, -0.3678, 0.3678, -0.5873, 0.5873, -0.7699, 0.7699, -0.9041, 0.9041,
-                -0.9816, 0.9816,
-              ],
-              m = [
-                0.2491, 0.2491, 0.2335, 0.2335, 0.2032, 0.2032, 0.1601, 0.1601, 0.1069, 0.1069,
-                0.0472, 0.0472,
-              ],
-              n = 0,
-              p = 0;
-            k > p;
-            p++
-          ) {
-            var q = j * l[p] + j,
-              r = o(q, a, c, e, g),
-              s = o(q, b, d, f, h),
-              t = r * r + s * s;
-            n += m[p] * P.sqrt(t);
-          }
-          return j * n;
-        }
-        function q(a, b, c, d, e, f, g, h, i) {
-          if (!(0 > i || p(a, b, c, d, e, f, g, h) < i)) {
-            var j,
-              k = 1,
-              l = k / 2,
-              m = k - l,
-              n = 0.01;
-            for (j = p(a, b, c, d, e, f, g, h, m); U(j - i) > n; )
-              (l /= 2), (m += (i > j ? 1 : -1) * l), (j = p(a, b, c, d, e, f, g, h, m));
-            return m;
-          }
-        }
-        function r(a, b, c, d, e, f, g, h) {
-          if (!(S(a, c) < R(e, g) || R(a, c) > S(e, g) || S(b, d) < R(f, h) || R(b, d) > S(f, h))) {
-            var i = (a * d - b * c) * (e - g) - (a - c) * (e * h - f * g),
-              j = (a * d - b * c) * (f - h) - (b - d) * (e * h - f * g),
-              k = (a - c) * (f - h) - (b - d) * (e - g);
-            if (k) {
-              var l = i / k,
-                m = j / k,
-                n = +l.toFixed(2),
-                o = +m.toFixed(2);
-              if (
-                !(
-                  n < +R(a, c).toFixed(2) ||
-                  n > +S(a, c).toFixed(2) ||
-                  n < +R(e, g).toFixed(2) ||
-                  n > +S(e, g).toFixed(2) ||
-                  o < +R(b, d).toFixed(2) ||
-                  o > +S(b, d).toFixed(2) ||
-                  o < +R(f, h).toFixed(2) ||
-                  o > +S(f, h).toFixed(2)
-                )
-              )
-                return { x: l, y: m };
-            }
-          }
-        }
-        function s(a, b, c) {
-          var d = l(a),
-            e = l(b);
-          if (!n(d, e)) return c ? 0 : [];
-          for (
-            var f = p.apply(0, a),
-              g = p.apply(0, b),
-              h = ~~(f / 8),
-              i = ~~(g / 8),
-              j = [],
-              m = [],
-              o = {},
-              q = c ? 0 : [],
-              s = 0;
-            h + 1 > s;
-            s++
-          ) {
-            var t = k.apply(0, a.concat(s / h));
-            j.push({ x: t.x, y: t.y, t: s / h });
-          }
-          for (s = 0; i + 1 > s; s++)
-            (t = k.apply(0, b.concat(s / i))), m.push({ x: t.x, y: t.y, t: s / i });
-          for (s = 0; h > s; s++)
-            for (var u = 0; i > u; u++) {
-              var v = j[s],
-                w = j[s + 1],
-                x = m[u],
-                y = m[u + 1],
-                z = U(w.x - v.x) < 0.001 ? "y" : "x",
-                A = U(y.x - x.x) < 0.001 ? "y" : "x",
-                B = r(v.x, v.y, w.x, w.y, x.x, x.y, y.x, y.y);
-              if (B) {
-                if (o[B.x.toFixed(4)] == B.y.toFixed(4)) continue;
-                o[B.x.toFixed(4)] = B.y.toFixed(4);
-                var C = v.t + U((B[z] - v[z]) / (w[z] - v[z])) * (w.t - v.t),
-                  D = x.t + U((B[A] - x[A]) / (y[A] - x[A])) * (y.t - x.t);
-                C >= 0 &&
-                  1 >= C &&
-                  D >= 0 &&
-                  1 >= D &&
-                  (c ? q++ : q.push({ x: B.x, y: B.y, t1: C, t2: D }));
-              }
-            }
-          return q;
-        }
-        function t(a, b) {
-          return v(a, b);
-        }
-        function u(a, b) {
-          return v(a, b, 1);
-        }
-        function v(a, b, c) {
-          (a = G(a)), (b = G(b));
-          for (var d, e, f, g, h, i, j, k, l, m, n = c ? 0 : [], o = 0, p = a.length; p > o; o++) {
-            var q = a[o];
-            if ("M" == q[0]) (d = h = q[1]), (e = i = q[2]);
-            else {
-              "C" == q[0]
-                ? ((l = [d, e].concat(q.slice(1))), (d = l[6]), (e = l[7]))
-                : ((l = [d, e, d, e, h, i, h, i]), (d = h), (e = i));
-              for (var r = 0, t = b.length; t > r; r++) {
-                var u = b[r];
-                if ("M" == u[0]) (f = j = u[1]), (g = k = u[2]);
-                else {
-                  "C" == u[0]
-                    ? ((m = [f, g].concat(u.slice(1))), (f = m[6]), (g = m[7]))
-                    : ((m = [f, g, f, g, j, k, j, k]), (f = j), (g = k));
-                  var v = s(l, m, c);
-                  if (c) n += v;
-                  else {
-                    for (var w = 0, x = v.length; x > w; w++)
-                      (v[w].segment1 = o), (v[w].segment2 = r), (v[w].bez1 = l), (v[w].bez2 = m);
-                    n = n.concat(v);
-                  }
-                }
-              }
-            }
-          }
-          return n;
-        }
-        function w(a, b, c) {
-          var d = x(a);
-          return (
-            m(d, b, c) &&
-            v(
-              a,
-              [
-                ["M", b, c],
-                ["H", d.x2 + 10],
-              ],
-              1
-            ) %
-              2 ==
-              1
-          );
-        }
-        function x(a) {
-          var b = e(a);
-          if (b.bbox) return L(b.bbox);
-          if (!a) return f();
-          a = G(a);
-          for (var c, d = 0, g = 0, h = [], i = [], j = 0, k = a.length; k > j; j++)
-            if (((c = a[j]), "M" == c[0])) (d = c[1]), (g = c[2]), h.push(d), i.push(g);
-            else {
-              var l = F(d, g, c[1], c[2], c[3], c[4], c[5], c[6]);
-              (h = h.concat(l.min.x, l.max.x)),
-                (i = i.concat(l.min.y, l.max.y)),
-                (d = c[5]),
-                (g = c[6]);
-            }
-          var m = R.apply(0, h),
-            n = R.apply(0, i),
-            o = S.apply(0, h),
-            p = S.apply(0, i),
-            q = f(m, n, o - m, p - n);
-          return (b.bbox = L(q)), q;
-        }
-        function y(a, b, c, d, e) {
-          if (e)
-            return [
-              ["M", +a + +e, b],
-              ["l", c - 2 * e, 0],
-              ["a", e, e, 0, 0, 1, e, e],
-              ["l", 0, d - 2 * e],
-              ["a", e, e, 0, 0, 1, -e, e],
-              ["l", 2 * e - c, 0],
-              ["a", e, e, 0, 0, 1, -e, -e],
-              ["l", 0, 2 * e - d],
-              ["a", e, e, 0, 0, 1, e, -e],
-              ["z"],
-            ];
-          var f = [["M", a, b], ["l", c, 0], ["l", 0, d], ["l", -c, 0], ["z"]];
-          return (f.toString = g), f;
-        }
-        function z(a, b, c, d, e) {
-          if (
-            (null == e && null == d && (d = c), (a = +a), (b = +b), (c = +c), (d = +d), null != e)
-          )
-            var f = Math.PI / 180,
-              h = a + c * Math.cos(-d * f),
-              i = a + c * Math.cos(-e * f),
-              j = b + c * Math.sin(-d * f),
-              k = b + c * Math.sin(-e * f),
-              l = [
-                ["M", h, j],
-                ["A", c, c, 0, +(e - d > 180), 0, i, k],
-              ];
-          else
-            l = [
-              ["M", a, b],
-              ["m", 0, -d],
-              ["a", c, d, 0, 1, 1, 0, 2 * d],
-              ["a", c, d, 0, 1, 1, 0, -2 * d],
-              ["z"],
-            ];
-          return (l.toString = g), l;
-        }
-        function A(b) {
-          var c = e(b),
-            d = String.prototype.toLowerCase;
-          if (c.rel) return h(c.rel);
-          (a.is(b, "array") && a.is(b && b[0], "array")) || (b = a.parsePathString(b));
-          var f = [],
-            i = 0,
-            j = 0,
-            k = 0,
-            l = 0,
-            m = 0;
-          "M" == b[0][0] &&
-            ((i = b[0][1]), (j = b[0][2]), (k = i), (l = j), m++, f.push(["M", i, j]));
-          for (var n = m, o = b.length; o > n; n++) {
-            var p = (f[n] = []),
-              q = b[n];
-            if (q[0] != d.call(q[0]))
-              switch (((p[0] = d.call(q[0])), p[0])) {
-                case "a":
-                  (p[1] = q[1]),
-                    (p[2] = q[2]),
-                    (p[3] = q[3]),
-                    (p[4] = q[4]),
-                    (p[5] = q[5]),
-                    (p[6] = +(q[6] - i).toFixed(3)),
-                    (p[7] = +(q[7] - j).toFixed(3));
-                  break;
-                case "v":
-                  p[1] = +(q[1] - j).toFixed(3);
-                  break;
-                case "m":
-                  (k = q[1]), (l = q[2]);
-                default:
-                  for (var r = 1, s = q.length; s > r; r++)
-                    p[r] = +(q[r] - (r % 2 ? i : j)).toFixed(3);
-              }
-            else {
-              (p = f[n] = []), "m" == q[0] && ((k = q[1] + i), (l = q[2] + j));
-              for (var t = 0, u = q.length; u > t; t++) f[n][t] = q[t];
-            }
-            var v = f[n].length;
-            switch (f[n][0]) {
-              case "z":
-                (i = k), (j = l);
-                break;
-              case "h":
-                i += +f[n][v - 1];
-                break;
-              case "v":
-                j += +f[n][v - 1];
-                break;
-              default:
-                (i += +f[n][v - 2]), (j += +f[n][v - 1]);
-            }
-          }
-          return (f.toString = g), (c.rel = h(f)), f;
-        }
-        function B(b) {
-          var c = e(b);
-          if (c.abs) return h(c.abs);
-          if (
-            ((K(b, "array") && K(b && b[0], "array")) || (b = a.parsePathString(b)),
-            !b || !b.length)
-          )
-            return [["M", 0, 0]];
-          var d,
-            f = [],
-            i = 0,
-            j = 0,
-            k = 0,
-            l = 0,
-            m = 0;
-          "M" == b[0][0] &&
-            ((i = +b[0][1]), (j = +b[0][2]), (k = i), (l = j), m++, (f[0] = ["M", i, j]));
-          for (
-            var n,
-              o,
-              p =
-                3 == b.length &&
-                "M" == b[0][0] &&
-                "R" == b[1][0].toUpperCase() &&
-                "Z" == b[2][0].toUpperCase(),
-              q = m,
-              r = b.length;
-            r > q;
-            q++
-          ) {
-            if ((f.push((n = [])), (o = b[q]), (d = o[0]), d != d.toUpperCase()))
-              switch (((n[0] = d.toUpperCase()), n[0])) {
-                case "A":
-                  (n[1] = o[1]),
-                    (n[2] = o[2]),
-                    (n[3] = o[3]),
-                    (n[4] = o[4]),
-                    (n[5] = o[5]),
-                    (n[6] = +o[6] + i),
-                    (n[7] = +o[7] + j);
-                  break;
-                case "V":
-                  n[1] = +o[1] + j;
-                  break;
-                case "H":
-                  n[1] = +o[1] + i;
-                  break;
-                case "R":
-                  for (var s = [i, j].concat(o.slice(1)), t = 2, u = s.length; u > t; t++)
-                    (s[t] = +s[t] + i), (s[++t] = +s[t] + j);
-                  f.pop(), (f = f.concat(I(s, p)));
-                  break;
-                case "O":
-                  f.pop(), (s = z(i, j, o[1], o[2])), s.push(s[0]), (f = f.concat(s));
-                  break;
-                case "U":
-                  f.pop(),
-                    (f = f.concat(z(i, j, o[1], o[2], o[3]))),
-                    (n = ["U"].concat(f[f.length - 1].slice(-2)));
-                  break;
-                case "M":
-                  (k = +o[1] + i), (l = +o[2] + j);
-                default:
-                  for (t = 1, u = o.length; u > t; t++) n[t] = +o[t] + (t % 2 ? i : j);
-              }
-            else if ("R" == d)
-              (s = [i, j].concat(o.slice(1))),
-                f.pop(),
-                (f = f.concat(I(s, p))),
-                (n = ["R"].concat(o.slice(-2)));
-            else if ("O" == d) f.pop(), (s = z(i, j, o[1], o[2])), s.push(s[0]), (f = f.concat(s));
-            else if ("U" == d)
-              f.pop(),
-                (f = f.concat(z(i, j, o[1], o[2], o[3]))),
-                (n = ["U"].concat(f[f.length - 1].slice(-2)));
-            else for (var v = 0, w = o.length; w > v; v++) n[v] = o[v];
-            if (((d = d.toUpperCase()), "O" != d))
-              switch (n[0]) {
-                case "Z":
-                  (i = +k), (j = +l);
-                  break;
-                case "H":
-                  i = n[1];
-                  break;
-                case "V":
-                  j = n[1];
-                  break;
-                case "M":
-                  (k = n[n.length - 2]), (l = n[n.length - 1]);
-                default:
-                  (i = n[n.length - 2]), (j = n[n.length - 1]);
-              }
-          }
-          return (f.toString = g), (c.abs = h(f)), f;
-        }
-        function C(a, b, c, d) {
-          return [a, b, c, d, c, d];
-        }
-        function D(a, b, c, d, e, f) {
-          var g = 1 / 3,
-            h = 2 / 3;
-          return [g * a + h * c, g * b + h * d, g * e + h * c, g * f + h * d, e, f];
-        }
-        function E(b, c, d, e, f, g, h, i, j, k) {
-          var l,
-            m = (120 * Q) / 180,
-            n = (Q / 180) * (+f || 0),
-            o = [],
-            p = a._.cacher(function (a, b, c) {
-              var d = a * P.cos(c) - b * P.sin(c),
-                e = a * P.sin(c) + b * P.cos(c);
-              return { x: d, y: e };
-            });
-          if (!d || !e) return [b, c, i, j, i, j];
-          if (k) (y = k[0]), (z = k[1]), (w = k[2]), (x = k[3]);
-          else {
-            (l = p(b, c, -n)), (b = l.x), (c = l.y), (l = p(i, j, -n)), (i = l.x), (j = l.y);
-            var q = (P.cos((Q / 180) * f), P.sin((Q / 180) * f), (b - i) / 2),
-              r = (c - j) / 2,
-              s = (q * q) / (d * d) + (r * r) / (e * e);
-            s > 1 && ((s = P.sqrt(s)), (d = s * d), (e = s * e));
-            var t = d * d,
-              u = e * e,
-              v =
-                (g == h ? -1 : 1) *
-                P.sqrt(U((t * u - t * r * r - u * q * q) / (t * r * r + u * q * q))),
-              w = (v * d * r) / e + (b + i) / 2,
-              x = (v * -e * q) / d + (c + j) / 2,
-              y = P.asin(((c - x) / e).toFixed(9)),
-              z = P.asin(((j - x) / e).toFixed(9));
-            (y = w > b ? Q - y : y),
-              (z = w > i ? Q - z : z),
-              0 > y && (y = 2 * Q + y),
-              0 > z && (z = 2 * Q + z),
-              h && y > z && (y -= 2 * Q),
-              !h && z > y && (z -= 2 * Q);
-          }
-          var A = z - y;
-          if (U(A) > m) {
-            var B = z,
-              C = i,
-              D = j;
-            (z = y + m * (h && z > y ? 1 : -1)),
-              (i = w + d * P.cos(z)),
-              (j = x + e * P.sin(z)),
-              (o = E(i, j, d, e, f, 0, h, C, D, [z, B, w, x]));
-          }
-          A = z - y;
-          var F = P.cos(y),
-            G = P.sin(y),
-            H = P.cos(z),
-            I = P.sin(z),
-            J = P.tan(A / 4),
-            K = (4 / 3) * d * J,
-            L = (4 / 3) * e * J,
-            M = [b, c],
-            N = [b + K * G, c - L * F],
-            O = [i + K * I, j - L * H],
-            R = [i, j];
-          if (((N[0] = 2 * M[0] - N[0]), (N[1] = 2 * M[1] - N[1]), k)) return [N, O, R].concat(o);
-          o = [N, O, R].concat(o).join().split(",");
-          for (var S = [], T = 0, V = o.length; V > T; T++)
-            S[T] = T % 2 ? p(o[T - 1], o[T], n).y : p(o[T], o[T + 1], n).x;
-          return S;
-        }
-        function F(a, b, c, d, e, f, g, h) {
-          for (var i, j, k, l, m, n, o, p, q = [], r = [[], []], s = 0; 2 > s; ++s)
-            if (
-              (0 == s
-                ? ((j = 6 * a - 12 * c + 6 * e),
-                  (i = -3 * a + 9 * c - 9 * e + 3 * g),
-                  (k = 3 * c - 3 * a))
-                : ((j = 6 * b - 12 * d + 6 * f),
-                  (i = -3 * b + 9 * d - 9 * f + 3 * h),
-                  (k = 3 * d - 3 * b)),
-              U(i) < 1e-12)
-            ) {
-              if (U(j) < 1e-12) continue;
-              (l = -k / j), l > 0 && 1 > l && q.push(l);
-            } else
-              (o = j * j - 4 * k * i),
-                (p = P.sqrt(o)),
-                0 > o ||
-                  ((m = (-j + p) / (2 * i)),
-                  m > 0 && 1 > m && q.push(m),
-                  (n = (-j - p) / (2 * i)),
-                  n > 0 && 1 > n && q.push(n));
-          for (var t, u = q.length, v = u; u--; )
-            (l = q[u]),
-              (t = 1 - l),
-              (r[0][u] = t * t * t * a + 3 * t * t * l * c + 3 * t * l * l * e + l * l * l * g),
-              (r[1][u] = t * t * t * b + 3 * t * t * l * d + 3 * t * l * l * f + l * l * l * h);
-          return (
-            (r[0][v] = a),
-            (r[1][v] = b),
-            (r[0][v + 1] = g),
-            (r[1][v + 1] = h),
-            (r[0].length = r[1].length = v + 2),
-            {
-              min: { x: R.apply(0, r[0]), y: R.apply(0, r[1]) },
-              max: { x: S.apply(0, r[0]), y: S.apply(0, r[1]) },
-            }
-          );
-        }
-        function G(a, b) {
-          var c = !b && e(a);
-          if (!b && c.curve) return h(c.curve);
-          for (
-            var d = B(a),
-              f = b && B(b),
-              g = { x: 0, y: 0, bx: 0, by: 0, X: 0, Y: 0, qx: null, qy: null },
-              i = { x: 0, y: 0, bx: 0, by: 0, X: 0, Y: 0, qx: null, qy: null },
-              j = function (a, b, c) {
-                var d, e;
-                if (!a) return ["C", b.x, b.y, b.x, b.y, b.x, b.y];
-                switch ((!(a[0] in { T: 1, Q: 1 }) && (b.qx = b.qy = null), a[0])) {
-                  case "M":
-                    (b.X = a[1]), (b.Y = a[2]);
-                    break;
-                  case "A":
-                    a = ["C"].concat(E.apply(0, [b.x, b.y].concat(a.slice(1))));
-                    break;
-                  case "S":
-                    "C" == c || "S" == c
-                      ? ((d = 2 * b.x - b.bx), (e = 2 * b.y - b.by))
-                      : ((d = b.x), (e = b.y)),
-                      (a = ["C", d, e].concat(a.slice(1)));
-                    break;
-                  case "T":
-                    "Q" == c || "T" == c
-                      ? ((b.qx = 2 * b.x - b.qx), (b.qy = 2 * b.y - b.qy))
-                      : ((b.qx = b.x), (b.qy = b.y)),
-                      (a = ["C"].concat(D(b.x, b.y, b.qx, b.qy, a[1], a[2])));
-                    break;
-                  case "Q":
-                    (b.qx = a[1]),
-                      (b.qy = a[2]),
-                      (a = ["C"].concat(D(b.x, b.y, a[1], a[2], a[3], a[4])));
-                    break;
-                  case "L":
-                    a = ["C"].concat(C(b.x, b.y, a[1], a[2]));
-                    break;
-                  case "H":
-                    a = ["C"].concat(C(b.x, b.y, a[1], b.y));
-                    break;
-                  case "V":
-                    a = ["C"].concat(C(b.x, b.y, b.x, a[1]));
-                    break;
-                  case "Z":
-                    a = ["C"].concat(C(b.x, b.y, b.X, b.Y));
-                }
-                return a;
-              },
-              k = function (a, b) {
-                if (a[b].length > 7) {
-                  a[b].shift();
-                  for (var c = a[b]; c.length; )
-                    (m[b] = "A"), f && (n[b] = "A"), a.splice(b++, 0, ["C"].concat(c.splice(0, 6)));
-                  a.splice(b, 1), (r = S(d.length, (f && f.length) || 0));
-                }
-              },
-              l = function (a, b, c, e, g) {
-                a &&
-                  b &&
-                  "M" == a[g][0] &&
-                  "M" != b[g][0] &&
-                  (b.splice(g, 0, ["M", e.x, e.y]),
-                  (c.bx = 0),
-                  (c.by = 0),
-                  (c.x = a[g][1]),
-                  (c.y = a[g][2]),
-                  (r = S(d.length, (f && f.length) || 0)));
-              },
-              m = [],
-              n = [],
-              o = "",
-              p = "",
-              q = 0,
-              r = S(d.length, (f && f.length) || 0);
-            r > q;
-            q++
-          ) {
-            d[q] && (o = d[q][0]),
-              "C" != o && ((m[q] = o), q && (p = m[q - 1])),
-              (d[q] = j(d[q], g, p)),
-              "A" != m[q] && "C" == o && (m[q] = "C"),
-              k(d, q),
-              f &&
-                (f[q] && (o = f[q][0]),
-                "C" != o && ((n[q] = o), q && (p = n[q - 1])),
-                (f[q] = j(f[q], i, p)),
-                "A" != n[q] && "C" == o && (n[q] = "C"),
-                k(f, q)),
-              l(d, f, g, i, q),
-              l(f, d, i, g, q);
-            var s = d[q],
-              t = f && f[q],
-              u = s.length,
-              v = f && t.length;
-            (g.x = s[u - 2]),
-              (g.y = s[u - 1]),
-              (g.bx = O(s[u - 4]) || g.x),
-              (g.by = O(s[u - 3]) || g.y),
-              (i.bx = f && (O(t[v - 4]) || i.x)),
-              (i.by = f && (O(t[v - 3]) || i.y)),
-              (i.x = f && t[v - 2]),
-              (i.y = f && t[v - 1]);
-          }
-          return f || (c.curve = h(d)), f ? [d, f] : d;
-        }
-        function H(a, b) {
-          if (!b) return a;
-          var c, d, e, f, g, h, i;
-          for (a = G(a), e = 0, g = a.length; g > e; e++)
-            for (i = a[e], f = 1, h = i.length; h > f; f += 2)
-              (c = b.x(i[f], i[f + 1])), (d = b.y(i[f], i[f + 1])), (i[f] = c), (i[f + 1] = d);
-          return a;
-        }
-        function I(a, b) {
-          for (var c = [], d = 0, e = a.length; e - 2 * !b > d; d += 2) {
-            var f = [
-              { x: +a[d - 2], y: +a[d - 1] },
-              { x: +a[d], y: +a[d + 1] },
-              { x: +a[d + 2], y: +a[d + 3] },
-              { x: +a[d + 4], y: +a[d + 5] },
-            ];
-            b
-              ? d
-                ? e - 4 == d
-                  ? (f[3] = { x: +a[0], y: +a[1] })
-                  : e - 2 == d && ((f[2] = { x: +a[0], y: +a[1] }), (f[3] = { x: +a[2], y: +a[3] }))
-                : (f[0] = { x: +a[e - 2], y: +a[e - 1] })
-              : e - 4 == d
-              ? (f[3] = f[2])
-              : d || (f[0] = { x: +a[d], y: +a[d + 1] }),
-              c.push([
-                "C",
-                (-f[0].x + 6 * f[1].x + f[2].x) / 6,
-                (-f[0].y + 6 * f[1].y + f[2].y) / 6,
-                (f[1].x + 6 * f[2].x - f[3].x) / 6,
-                (f[1].y + 6 * f[2].y - f[3].y) / 6,
-                f[2].x,
-                f[2].y,
-              ]);
-          }
-          return c;
-        }
-        var J = b.prototype,
-          K = a.is,
-          L = a._.clone,
-          M = "hasOwnProperty",
-          N = /,?([a-z]),?/gi,
-          O = parseFloat,
-          P = Math,
-          Q = P.PI,
-          R = P.min,
-          S = P.max,
-          T = P.pow,
-          U = P.abs,
-          V = j(1),
-          W = j(),
-          X = j(0, 1),
-          Y = a._unit2px,
-          Z = {
-            path: function (a) {
-              return a.attr("path");
-            },
-            circle: function (a) {
-              var b = Y(a);
-              return z(b.cx, b.cy, b.r);
-            },
-            ellipse: function (a) {
-              var b = Y(a);
-              return z(b.cx || 0, b.cy || 0, b.rx, b.ry);
-            },
-            rect: function (a) {
-              var b = Y(a);
-              return y(b.x || 0, b.y || 0, b.width, b.height, b.rx, b.ry);
-            },
-            image: function (a) {
-              var b = Y(a);
-              return y(b.x || 0, b.y || 0, b.width, b.height);
-            },
-            line: function (a) {
-              return "M" + [a.attr("x1") || 0, a.attr("y1") || 0, a.attr("x2"), a.attr("y2")];
-            },
-            polyline: function (a) {
-              return "M" + a.attr("points");
-            },
-            polygon: function (a) {
-              return "M" + a.attr("points") + "z";
-            },
-            deflt: function (a) {
-              var b = a.node.getBBox();
-              return y(b.x, b.y, b.width, b.height);
-            },
-          };
-        (a.path = e),
-          (a.path.getTotalLength = V),
-          (a.path.getPointAtLength = W),
-          (a.path.getSubpath = function (a, b, c) {
-            if (this.getTotalLength(a) - c < 1e-6) return X(a, b).end;
-            var d = X(a, c, 1);
-            return b ? X(d, b).end : d;
-          }),
-          (J.getTotalLength = function () {
-            return this.node.getTotalLength ? this.node.getTotalLength() : void 0;
-          }),
-          (J.getPointAtLength = function (a) {
-            return W(this.attr("d"), a);
-          }),
-          (J.getSubpath = function (b, c) {
-            return a.path.getSubpath(this.attr("d"), b, c);
-          }),
-          (a._.box = f),
-          (a.path.findDotsAtSegment = k),
-          (a.path.bezierBBox = l),
-          (a.path.isPointInsideBBox = m),
-          (a.closest = function (b, c, d, e) {
-            for (
-              var g = 100,
-                h = f(b - g / 2, c - g / 2, g, g),
-                i = [],
-                j = d[0].hasOwnProperty("x")
-                  ? function (a) {
-                      return { x: d[a].x, y: d[a].y };
-                    }
-                  : function (a) {
-                      return { x: d[a], y: e[a] };
-                    },
-                k = 0;
-              1e6 >= g && !k;
-
-            ) {
-              for (var l = 0, n = d.length; n > l; l++) {
-                var o = j(l);
-                if (m(h, o.x, o.y)) {
-                  k++, i.push(o);
-                  break;
-                }
-              }
-              k || ((g *= 2), (h = f(b - g / 2, c - g / 2, g, g)));
-            }
-            if (1e6 != g) {
-              var p,
-                q = 1 / 0;
-              for (l = 0, n = i.length; n > l; l++) {
-                var r = a.len(b, c, i[l].x, i[l].y);
-                q > r && ((q = r), (i[l].len = r), (p = i[l]));
-              }
-              return p;
-            }
-          }),
-          (a.path.isBBoxIntersect = n),
-          (a.path.intersection = t),
-          (a.path.intersectionNumber = u),
-          (a.path.isPointInside = w),
-          (a.path.getBBox = x),
-          (a.path.get = Z),
-          (a.path.toRelative = A),
-          (a.path.toAbsolute = B),
-          (a.path.toCubic = G),
-          (a.path.map = H),
-          (a.path.toString = g),
-          (a.path.clone = h);
-      }),
-      d.plugin(function (a, d, e, f) {
-        var g = Math.max,
-          h = Math.min,
-          i = function (a) {
-            if (
-              ((this.items = []), (this.bindings = {}), (this.length = 0), (this.type = "set"), a)
-            )
-              for (var b = 0, c = a.length; c > b; b++)
-                a[b] &&
-                  ((this[this.items.length] = this.items[this.items.length] = a[b]), this.length++);
-          },
-          j = i.prototype;
-        (j.push = function () {
-          for (var a, b, c = 0, d = arguments.length; d > c; c++)
-            (a = arguments[c]),
-              a && ((b = this.items.length), (this[b] = this.items[b] = a), this.length++);
-          return this;
-        }),
-          (j.pop = function () {
-            return this.length && delete this[this.length--], this.items.pop();
-          }),
-          (j.forEach = function (a, b) {
-            for (var c = 0, d = this.items.length; d > c; c++)
-              if (a.call(b, this.items[c], c) === !1) return this;
-            return this;
-          }),
-          (j.animate = function (d, e, f, g) {
-            "function" != typeof f || f.length || ((g = f), (f = c.linear)),
-              d instanceof a._.Animation &&
-                ((g = d.callback), (f = d.easing), (e = f.dur), (d = d.attr));
-            var h = arguments;
-            if (a.is(d, "array") && a.is(h[h.length - 1], "array")) var i = !0;
-            var j,
-              k = function () {
-                j ? (this.b = j) : (j = this.b);
-              },
-              l = 0,
-              m = this,
-              n =
-                g &&
-                function () {
-                  ++l == m.length && g.call(this);
-                };
-            return this.forEach(function (a, c) {
-              b.once("snap.animcreated." + a.id, k),
-                i ? h[c] && a.animate.apply(a, h[c]) : a.animate(d, e, f, n);
-            });
-          }),
-          (j.remove = function () {
-            for (; this.length; ) this.pop().remove();
-            return this;
-          }),
-          (j.bind = function (a, b, c) {
-            var d = {};
-            if ("function" == typeof b) this.bindings[a] = b;
-            else {
-              var e = c || a;
-              this.bindings[a] = function (a) {
-                (d[e] = a), b.attr(d);
-              };
-            }
-            return this;
-          }),
-          (j.attr = function (a) {
-            var b = {};
-            for (var c in a) this.bindings[c] ? this.bindings[c](a[c]) : (b[c] = a[c]);
-            for (var d = 0, e = this.items.length; e > d; d++) this.items[d].attr(b);
-            return this;
-          }),
-          (j.clear = function () {
-            for (; this.length; ) this.pop();
-          }),
-          (j.splice = function (a, b, c) {
-            (a = 0 > a ? g(this.length + a, 0) : a), (b = g(0, h(this.length - a, b)));
-            var d,
-              e = [],
-              f = [],
-              j = [];
-            for (d = 2; d < arguments.length; d++) j.push(arguments[d]);
-            for (d = 0; b > d; d++) f.push(this[a + d]);
-            for (; d < this.length - a; d++) e.push(this[a + d]);
-            var k = j.length;
-            for (d = 0; d < k + e.length; d++)
-              this.items[a + d] = this[a + d] = k > d ? j[d] : e[d - k];
-            for (d = this.items.length = this.length -= b - k; this[d]; ) delete this[d++];
-            return new i(f);
-          }),
-          (j.exclude = function (a) {
-            for (var b = 0, c = this.length; c > b; b++)
-              if (this[b] == a) return this.splice(b, 1), !0;
-            return !1;
-          }),
-          (j.insertAfter = function (a) {
-            for (var b = this.items.length; b--; ) this.items[b].insertAfter(a);
-            return this;
-          }),
-          (j.getBBox = function () {
-            for (var a = [], b = [], c = [], d = [], e = this.items.length; e--; )
-              if (!this.items[e].removed) {
-                var f = this.items[e].getBBox();
-                a.push(f.x), b.push(f.y), c.push(f.x + f.width), d.push(f.y + f.height);
-              }
-            return (
-              (a = h.apply(0, a)),
-              (b = h.apply(0, b)),
-              (c = g.apply(0, c)),
-              (d = g.apply(0, d)),
-              {
-                x: a,
-                y: b,
-                x2: c,
-                y2: d,
-                width: c - a,
-                height: d - b,
-                cx: a + (c - a) / 2,
-                cy: b + (d - b) / 2,
-              }
-            );
-          }),
-          (j.clone = function (a) {
-            a = new i();
-            for (var b = 0, c = this.items.length; c > b; b++) a.push(this.items[b].clone());
-            return a;
-          }),
-          (j.toString = function () {
-            return "Snap‘s set";
-          }),
-          (j.type = "set"),
-          (a.Set = i),
-          (a.set = function () {
-            var a = new i();
-            return arguments.length && a.push.apply(a, Array.prototype.slice.call(arguments, 0)), a;
-          });
-      }),
-      d.plugin(function (a, c, d, e) {
-        function f(a) {
-          var b = a[0];
-          switch (b.toLowerCase()) {
-            case "t":
-              return [b, 0, 0];
-            case "m":
-              return [b, 1, 0, 0, 1, 0, 0];
-            case "r":
-              return 4 == a.length ? [b, 0, a[2], a[3]] : [b, 0];
-            case "s":
-              return 5 == a.length ? [b, 1, 1, a[3], a[4]] : 3 == a.length ? [b, 1, 1] : [b, 1];
-          }
-        }
-        function g(b, c, d) {
-          (b = b || new a.Matrix()),
-            (c = c || new a.Matrix()),
-            (b = a.parseTransformString(b.toTransformString()) || []),
-            (c = a.parseTransformString(c.toTransformString()) || []);
-          for (
-            var e, g, h, i, j = Math.max(b.length, c.length), k = [], n = [], o = 0;
-            j > o;
-            o++
-          ) {
-            if (
-              ((h = b[o] || f(c[o])),
-              (i = c[o] || f(h)),
-              h[0] != i[0] ||
-                ("r" == h[0].toLowerCase() && (h[2] != i[2] || h[3] != i[3])) ||
-                ("s" == h[0].toLowerCase() && (h[3] != i[3] || h[4] != i[4])))
-            ) {
-              (b = a._.transform2matrix(b, d())),
-                (c = a._.transform2matrix(c, d())),
-                (k = [["m", b.a, b.b, b.c, b.d, b.e, b.f]]),
-                (n = [["m", c.a, c.b, c.c, c.d, c.e, c.f]]);
-              break;
-            }
-            for (k[o] = [], n[o] = [], e = 0, g = Math.max(h.length, i.length); g > e; e++)
-              e in h && (k[o][e] = h[e]), e in i && (n[o][e] = i[e]);
-          }
-          return { from: m(k), to: m(n), f: l(k) };
-        }
-        function h(a) {
-          return a;
-        }
-        function i(a) {
-          return function (b) {
-            return +b.toFixed(3) + a;
-          };
-        }
-        function j(a) {
-          return a.join(" ");
-        }
-        function k(b) {
-          return a.rgb(b[0], b[1], b[2], b[3]);
-        }
-        function l(a) {
-          var b,
-            c,
-            d,
-            e,
-            f,
-            g,
-            h = 0,
-            i = [];
-          for (b = 0, c = a.length; c > b; b++) {
-            for (f = "[", g = ['"' + a[b][0] + '"'], d = 1, e = a[b].length; e > d; d++)
-              g[d] = "val[" + h++ + "]";
-            (f += g + "]"), (i[b] = f);
-          }
-          return Function("val", "return Snap.path.toString.call([" + i + "])");
-        }
-        function m(a) {
-          for (var b = [], c = 0, d = a.length; d > c; c++)
-            for (var e = 1, f = a[c].length; f > e; e++) b.push(a[c][e]);
-          return b;
-        }
-        function n(a) {
-          return isFinite(a);
-        }
-        function o(b, c) {
-          return a.is(b, "array") && a.is(c, "array") ? b.toString() == c.toString() : !1;
-        }
-        var p = {},
-          q = /[%a-z]+$/i,
-          r = String;
-        (p.stroke = p.fill = "colour"),
-          (c.prototype.equal = function (a, c) {
-            return b("snap.util.equal", this, a, c).firstDefined();
-          }),
-          b.on("snap.util.equal", function (b, c) {
-            var d,
-              e,
-              f = r(this.attr(b) || ""),
-              s = this;
-            if ("colour" == p[b])
-              return (
-                (d = a.color(f)),
-                (e = a.color(c)),
-                { from: [d.r, d.g, d.b, d.opacity], to: [e.r, e.g, e.b, e.opacity], f: k }
-              );
-            if ("viewBox" == b)
-              return (
-                (d = this.attr(b).vb.split(" ").map(Number)),
-                (e = c.split(" ").map(Number)),
-                { from: d, to: e, f: j }
-              );
-            if ("transform" == b || "gradientTransform" == b || "patternTransform" == b)
-              return (
-                "string" == typeof c && (c = r(c).replace(/\.{3}|\u2026/g, f)),
-                (f = this.matrix),
-                (c = a._.rgTransform.test(c)
-                  ? a._.transform2matrix(c, this.getBBox())
-                  : a._.transform2matrix(a._.svgTransform2string(c), this.getBBox())),
-                g(f, c, function () {
-                  return s.getBBox(1);
-                })
-              );
-            if ("d" == b || "path" == b)
-              return (d = a.path.toCubic(f, c)), { from: m(d[0]), to: m(d[1]), f: l(d[0]) };
-            if ("points" == b)
-              return (
-                (d = r(f).split(a._.separator)),
-                (e = r(c).split(a._.separator)),
-                {
-                  from: d,
-                  to: e,
-                  f: function (a) {
-                    return a;
-                  },
-                }
-              );
-            if (n(f) && n(c)) return { from: parseFloat(f), to: parseFloat(c), f: h };
-            var t = f.match(q),
-              u = r(c).match(q);
-            return t && o(t, u)
-              ? { from: parseFloat(f), to: parseFloat(c), f: i(t) }
-              : { from: this.asPX(b), to: this.asPX(b, c), f: h };
-          });
-      }),
-      d.plugin(function (a, c, d, e) {
-        for (
-          var f = c.prototype,
-            g = "hasOwnProperty",
-            h = ("createTouch" in e.doc),
-            i = [
-              "click",
-              "dblclick",
-              "mousedown",
-              "mousemove",
-              "mouseout",
-              "mouseover",
-              "mouseup",
-              "touchstart",
-              "touchmove",
-              "touchend",
-              "touchcancel",
-            ],
-            j = { mousedown: "touchstart", mousemove: "touchmove", mouseup: "touchend" },
-            k = function (a, b) {
-              var c = "y" == a ? "scrollTop" : "scrollLeft",
-                d = b && b.node ? b.node.ownerDocument : e.doc;
-              return d[(c in d.documentElement) ? "documentElement" : "body"][c];
-            },
-            l = function () {
-              return this.originalEvent.preventDefault();
-            },
-            m = function () {
-              return this.originalEvent.stopPropagation();
-            },
-            n = function (a, b, c, d) {
-              var e = h && j[b] ? j[b] : b,
-                f = function (e) {
-                  var f = k("y", d),
-                    i = k("x", d);
-                  if (h && j[g](b))
-                    for (var n = 0, o = e.targetTouches && e.targetTouches.length; o > n; n++)
-                      if (e.targetTouches[n].target == a || a.contains(e.targetTouches[n].target)) {
-                        var p = e;
-                        (e = e.targetTouches[n]),
-                          (e.originalEvent = p),
-                          (e.preventDefault = l),
-                          (e.stopPropagation = m);
-                        break;
-                      }
-                  var q = e.clientX + i,
-                    r = e.clientY + f;
-                  return c.call(d, e, q, r);
-                };
-              return (
-                b !== e && a.addEventListener(b, f, !1),
-                a.addEventListener(e, f, !1),
-                function () {
-                  return (
-                    b !== e && a.removeEventListener(b, f, !1), a.removeEventListener(e, f, !1), !0
-                  );
-                }
-              );
-            },
-            o = [],
-            p = function (a) {
-              for (
-                var c, d = a.clientX, e = a.clientY, f = k("y"), g = k("x"), i = o.length;
-                i--;
-
-              ) {
-                if (((c = o[i]), h)) {
-                  for (var j, l = a.touches && a.touches.length; l--; )
-                    if (
-                      ((j = a.touches[l]),
-                      j.identifier == c.el._drag.id || c.el.node.contains(j.target))
-                    ) {
-                      (d = j.clientX),
-                        (e = j.clientY),
-                        (a.originalEvent ? a.originalEvent : a).preventDefault();
-                      break;
-                    }
-                } else a.preventDefault();
-                var m = c.el.node;
-                m.nextSibling, m.parentNode, m.style.display;
-                (d += g),
-                  (e += f),
-                  b(
-                    "snap.drag.move." + c.el.id,
-                    c.move_scope || c.el,
-                    d - c.el._drag.x,
-                    e - c.el._drag.y,
-                    d,
-                    e,
-                    a
-                  );
-              }
-            },
-            q = function (c) {
-              a.unmousemove(p).unmouseup(q);
-              for (var d, e = o.length; e--; )
-                (d = o[e]),
-                  (d.el._drag = {}),
-                  b(
-                    "snap.drag.end." + d.el.id,
-                    d.end_scope || d.start_scope || d.move_scope || d.el,
-                    c
-                  ),
-                  b.off("snap.drag.*." + d.el.id);
-              o = [];
-            },
-            r = i.length;
-          r--;
-
-        )
-          !(function (b) {
-            (a[b] = f[b] =
-              function (c, d) {
-                if (a.is(c, "function"))
-                  (this.events = this.events || []),
-                    this.events.push({
-                      name: b,
-                      f: c,
-                      unbind: n(this.node || document, b, c, d || this),
-                    });
-                else
-                  for (var e = 0, f = this.events.length; f > e; e++)
-                    if (this.events[e].name == b)
-                      try {
-                        this.events[e].f.call(this);
-                      } catch (g) {}
-                return this;
-              }),
-              (a["un" + b] = f["un" + b] =
-                function (a) {
-                  for (var c = this.events || [], d = c.length; d--; )
-                    if (c[d].name == b && (c[d].f == a || !a))
-                      return c[d].unbind(), c.splice(d, 1), !c.length && delete this.events, this;
-                  return this;
-                });
-          })(i[r]);
-        (f.hover = function (a, b, c, d) {
-          return this.mouseover(a, c).mouseout(b, d || c);
-        }),
-          (f.unhover = function (a, b) {
-            return this.unmouseover(a).unmouseout(b);
-          });
-        var s = [];
-        (f.drag = function (c, d, e, f, g, h) {
-          function i(i, j, l) {
-            (i.originalEvent || i).preventDefault(),
-              (k._drag.x = j),
-              (k._drag.y = l),
-              (k._drag.id = i.identifier),
-              !o.length && a.mousemove(p).mouseup(q),
-              o.push({ el: k, move_scope: f, start_scope: g, end_scope: h }),
-              d && b.on("snap.drag.start." + k.id, d),
-              c && b.on("snap.drag.move." + k.id, c),
-              e && b.on("snap.drag.end." + k.id, e),
-              b("snap.drag.start." + k.id, g || f || k, j, l, i);
-          }
-          function j(a, c, d) {
-            b("snap.draginit." + k.id, k, a, c, d);
-          }
-          var k = this;
-          if (!arguments.length) {
-            var l;
-            return k.drag(
-              function (a, b) {
-                this.attr({ transform: l + (l ? "T" : "t") + [a, b] });
-              },
-              function () {
-                l = this.transform().local;
-              }
-            );
-          }
-          return (
-            b.on("snap.draginit." + k.id, i),
-            (k._drag = {}),
-            s.push({ el: k, start: i, init: j }),
-            k.mousedown(j),
-            k
-          );
-        }),
-          (f.undrag = function () {
-            for (var c = s.length; c--; )
-              s[c].el == this &&
-                (this.unmousedown(s[c].init),
-                s.splice(c, 1),
-                b.unbind("snap.drag.*." + this.id),
-                b.unbind("snap.draginit." + this.id));
-            return !s.length && a.unmousemove(p).unmouseup(q), this;
-          });
-      }),
-      d.plugin(function (a, c, d, e) {
-        var f = (c.prototype, d.prototype),
-          g = /^\s*url\((.+)\)/,
-          h = String,
-          i = a._.$;
-        (a.filter = {}),
-          (f.filter = function (b) {
-            var d = this;
-            "svg" != d.type && (d = d.paper);
-            var e = a.parse(h(b)),
-              f = a._.id(),
-              g = (d.node.offsetWidth, d.node.offsetHeight, i("filter"));
-            return (
-              i(g, { id: f, filterUnits: "userSpaceOnUse" }),
-              g.appendChild(e.node),
-              d.defs.appendChild(g),
-              new c(g)
-            );
-          }),
-          b.on("snap.util.getattr.filter", function () {
-            b.stop();
-            var c = i(this.node, "filter");
-            if (c) {
-              var d = h(c).match(g);
-              return d && a.select(d[1]);
-            }
-          }),
-          b.on("snap.util.attr.filter", function (d) {
-            if (d instanceof c && "filter" == d.type) {
-              b.stop();
-              var e = d.node.id;
-              e || (i(d.node, { id: d.id }), (e = d.id)), i(this.node, { filter: a.url(e) });
-            }
-            (d && "none" != d) || (b.stop(), this.node.removeAttribute("filter"));
-          }),
-          (a.filter.blur = function (b, c) {
-            null == b && (b = 2);
-            var d = null == c ? b : [b, c];
-            return a.format('<feGaussianBlur stdDeviation="{def}"/>', { def: d });
-          }),
-          (a.filter.blur.toString = function () {
-            return this();
-          }),
-          (a.filter.shadow = function (b, c, d, e, f) {
-            return (
-              null == f &&
-                (null == e ? ((f = d), (d = 4), (e = "#000")) : ((f = e), (e = d), (d = 4))),
-              null == d && (d = 4),
-              null == f && (f = 1),
-              null == b && ((b = 0), (c = 2)),
-              null == c && (c = b),
-              (e = a.color(e)),
-              a.format(
-                '<feGaussianBlur in="SourceAlpha" stdDeviation="{blur}"/><feOffset dx="{dx}" dy="{dy}" result="offsetblur"/><feFlood flood-color="{color}"/><feComposite in2="offsetblur" operator="in"/><feComponentTransfer><feFuncA type="linear" slope="{opacity}"/></feComponentTransfer><feMerge><feMergeNode/><feMergeNode in="SourceGraphic"/></feMerge>',
-                { color: e, dx: b, dy: c, blur: d, opacity: f }
-              )
-            );
-          }),
-          (a.filter.shadow.toString = function () {
-            return this();
-          }),
-          (a.filter.grayscale = function (b) {
-            return (
-              null == b && (b = 1),
-              a.format(
-                '<feColorMatrix type="matrix" values="{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {b} {h} 0 0 0 0 0 1 0"/>',
-                {
-                  a: 0.2126 + 0.7874 * (1 - b),
-                  b: 0.7152 - 0.7152 * (1 - b),
-                  c: 0.0722 - 0.0722 * (1 - b),
-                  d: 0.2126 - 0.2126 * (1 - b),
-                  e: 0.7152 + 0.2848 * (1 - b),
-                  f: 0.0722 - 0.0722 * (1 - b),
-                  g: 0.2126 - 0.2126 * (1 - b),
-                  h: 0.0722 + 0.9278 * (1 - b),
-                }
-              )
-            );
-          }),
-          (a.filter.grayscale.toString = function () {
-            return this();
-          }),
-          (a.filter.sepia = function (b) {
-            return (
-              null == b && (b = 1),
-              a.format(
-                '<feColorMatrix type="matrix" values="{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {h} {i} 0 0 0 0 0 1 0"/>',
-                {
-                  a: 0.393 + 0.607 * (1 - b),
-                  b: 0.769 - 0.769 * (1 - b),
-                  c: 0.189 - 0.189 * (1 - b),
-                  d: 0.349 - 0.349 * (1 - b),
-                  e: 0.686 + 0.314 * (1 - b),
-                  f: 0.168 - 0.168 * (1 - b),
-                  g: 0.272 - 0.272 * (1 - b),
-                  h: 0.534 - 0.534 * (1 - b),
-                  i: 0.131 + 0.869 * (1 - b),
-                }
-              )
-            );
-          }),
-          (a.filter.sepia.toString = function () {
-            return this();
-          }),
-          (a.filter.saturate = function (b) {
-            return (
-              null == b && (b = 1),
-              a.format('<feColorMatrix type="saturate" values="{amount}"/>', { amount: 1 - b })
-            );
-          }),
-          (a.filter.saturate.toString = function () {
-            return this();
-          }),
-          (a.filter.hueRotate = function (b) {
-            return (
-              (b = b || 0),
-              a.format('<feColorMatrix type="hueRotate" values="{angle}"/>', { angle: b })
-            );
-          }),
-          (a.filter.hueRotate.toString = function () {
-            return this();
-          }),
-          (a.filter.invert = function (b) {
-            return (
-              null == b && (b = 1),
-              a.format(
-                '<feComponentTransfer><feFuncR type="table" tableValues="{amount} {amount2}"/><feFuncG type="table" tableValues="{amount} {amount2}"/><feFuncB type="table" tableValues="{amount} {amount2}"/></feComponentTransfer>',
-                { amount: b, amount2: 1 - b }
-              )
-            );
-          }),
-          (a.filter.invert.toString = function () {
-            return this();
-          }),
-          (a.filter.brightness = function (b) {
-            return (
-              null == b && (b = 1),
-              a.format(
-                '<feComponentTransfer><feFuncR type="linear" slope="{amount}"/><feFuncG type="linear" slope="{amount}"/><feFuncB type="linear" slope="{amount}"/></feComponentTransfer>',
-                { amount: b }
-              )
-            );
-          }),
-          (a.filter.brightness.toString = function () {
-            return this();
-          }),
-          (a.filter.contrast = function (b) {
-            return (
-              null == b && (b = 1),
-              a.format(
-                '<feComponentTransfer><feFuncR type="linear" slope="{amount}" intercept="{amount2}"/><feFuncG type="linear" slope="{amount}" intercept="{amount2}"/><feFuncB type="linear" slope="{amount}" intercept="{amount2}"/></feComponentTransfer>',
-                { amount: b, amount2: 0.5 - b / 2 }
-              )
-            );
-          }),
-          (a.filter.contrast.toString = function () {
-            return this();
-          });
-      }),
-      d.plugin(function (a, b, c, d, e) {
-        var f = a._.box,
-          g = a.is,
-          h = /^[^a-z]*([tbmlrc])/i,
-          i = function () {
-            return "T" + this.dx + "," + this.dy;
-          };
-        (b.prototype.getAlign = function (a, b) {
-          null == b && g(a, "string") && ((b = a), (a = null)), (a = a || this.paper);
-          var c = a.getBBox ? a.getBBox() : f(a),
-            d = this.getBBox(),
-            e = {};
-          switch (((b = b && b.match(h)), (b = b ? b[1].toLowerCase() : "c"))) {
-            case "t":
-              (e.dx = 0), (e.dy = c.y - d.y);
-              break;
-            case "b":
-              (e.dx = 0), (e.dy = c.y2 - d.y2);
-              break;
-            case "m":
-              (e.dx = 0), (e.dy = c.cy - d.cy);
-              break;
-            case "l":
-              (e.dx = c.x - d.x), (e.dy = 0);
-              break;
-            case "r":
-              (e.dx = c.x2 - d.x2), (e.dy = 0);
-              break;
-            default:
-              (e.dx = c.cx - d.cx), (e.dy = 0);
-          }
-          return (e.toString = i), e;
-        }),
-          (b.prototype.align = function (a, b) {
-            return this.transform("..." + this.getAlign(a, b));
-          });
-      }),
-      d.plugin(function (b, c, d, e) {
-        function f(a) {
-          a = a.split(/(?=#)/);
-          var b = new String(a[5]);
-          return (
-            (b[50] = a[0]),
-            (b[100] = a[1]),
-            (b[200] = a[2]),
-            (b[300] = a[3]),
-            (b[400] = a[4]),
-            (b[500] = a[5]),
-            (b[600] = a[6]),
-            (b[700] = a[7]),
-            (b[800] = a[8]),
-            (b[900] = a[9]),
-            a[10] && ((b.A100 = a[10]), (b.A200 = a[11]), (b.A400 = a[12]), (b.A700 = a[13])),
-            b
-          );
-        }
-        var g =
-            "#ffebee#ffcdd2#ef9a9a#e57373#ef5350#f44336#e53935#d32f2f#c62828#b71c1c#ff8a80#ff5252#ff1744#d50000",
-          h =
-            "#FCE4EC#F8BBD0#F48FB1#F06292#EC407A#E91E63#D81B60#C2185B#AD1457#880E4F#FF80AB#FF4081#F50057#C51162",
-          i =
-            "#F3E5F5#E1BEE7#CE93D8#BA68C8#AB47BC#9C27B0#8E24AA#7B1FA2#6A1B9A#4A148C#EA80FC#E040FB#D500F9#AA00FF",
-          j =
-            "#EDE7F6#D1C4E9#B39DDB#9575CD#7E57C2#673AB7#5E35B1#512DA8#4527A0#311B92#B388FF#7C4DFF#651FFF#6200EA",
-          k =
-            "#E8EAF6#C5CAE9#9FA8DA#7986CB#5C6BC0#3F51B5#3949AB#303F9F#283593#1A237E#8C9EFF#536DFE#3D5AFE#304FFE",
-          l =
-            "#E3F2FD#BBDEFB#90CAF9#64B5F6#64B5F6#2196F3#1E88E5#1976D2#1565C0#0D47A1#82B1FF#448AFF#2979FF#2962FF",
-          m =
-            "#E1F5FE#B3E5FC#81D4FA#4FC3F7#29B6F6#03A9F4#039BE5#0288D1#0277BD#01579B#80D8FF#40C4FF#00B0FF#0091EA",
-          n =
-            "#E0F7FA#B2EBF2#80DEEA#4DD0E1#26C6DA#00BCD4#00ACC1#0097A7#00838F#006064#84FFFF#18FFFF#00E5FF#00B8D4",
-          o =
-            "#E0F2F1#B2DFDB#80CBC4#4DB6AC#26A69A#009688#00897B#00796B#00695C#004D40#A7FFEB#64FFDA#1DE9B6#00BFA5",
-          p =
-            "#E8F5E9#C8E6C9#A5D6A7#81C784#66BB6A#4CAF50#43A047#388E3C#2E7D32#1B5E20#B9F6CA#69F0AE#00E676#00C853",
-          q =
-            "#F1F8E9#DCEDC8#C5E1A5#AED581#9CCC65#8BC34A#7CB342#689F38#558B2F#33691E#CCFF90#B2FF59#76FF03#64DD17",
-          r =
-            "#F9FBE7#F0F4C3#E6EE9C#DCE775#D4E157#CDDC39#C0CA33#AFB42B#9E9D24#827717#F4FF81#EEFF41#C6FF00#AEEA00",
-          s =
-            "#FFFDE7#FFF9C4#FFF59D#FFF176#FFEE58#FFEB3B#FDD835#FBC02D#F9A825#F57F17#FFFF8D#FFFF00#FFEA00#FFD600",
-          t =
-            "#FFF8E1#FFECB3#FFE082#FFD54F#FFCA28#FFC107#FFB300#FFA000#FF8F00#FF6F00#FFE57F#FFD740#FFC400#FFAB00",
-          u =
-            "#FFF3E0#FFE0B2#FFCC80#FFB74D#FFA726#FF9800#FB8C00#F57C00#EF6C00#E65100#FFD180#FFAB40#FF9100#FF6D00",
-          v =
-            "#FBE9E7#FFCCBC#FFAB91#FF8A65#FF7043#FF5722#F4511E#E64A19#D84315#BF360C#FF9E80#FF6E40#FF3D00#DD2C00",
-          w = "#EFEBE9#D7CCC8#BCAAA4#A1887F#8D6E63#795548#6D4C41#5D4037#4E342E#3E2723",
-          x = "#FAFAFA#F5F5F5#EEEEEE#E0E0E0#BDBDBD#9E9E9E#757575#616161#424242#212121",
-          y = "#ECEFF1#CFD8DC#B0BEC5#90A4AE#78909C#607D8B#546E7A#455A64#37474F#263238";
-        (b.mui = {}),
-          (b.flat = {}),
-          (b.mui.red = f(g)),
-          (b.mui.pink = f(h)),
-          (b.mui.purple = f(i)),
-          (b.mui.deeppurple = f(j)),
-          (b.mui.indigo = f(k)),
-          (b.mui.blue = f(l)),
-          (b.mui.lightblue = f(m)),
-          (b.mui.cyan = f(n)),
-          (b.mui.teal = f(o)),
-          (b.mui.green = f(p)),
-          (b.mui.lightgreen = f(q)),
-          (b.mui.lime = f(r)),
-          (b.mui.yellow = f(s)),
-          (b.mui.amber = f(t)),
-          (b.mui.orange = f(u)),
-          (b.mui.deeporange = f(v)),
-          (b.mui.brown = f(w)),
-          (b.mui.grey = f(x)),
-          (b.mui.bluegrey = f(y)),
-          (b.flat.turquoise = "#1abc9c"),
-          (b.flat.greensea = "#16a085"),
-          (b.flat.sunflower = "#f1c40f"),
-          (b.flat.orange = "#f39c12"),
-          (b.flat.emerland = "#2ecc71"),
-          (b.flat.nephritis = "#27ae60"),
-          (b.flat.carrot = "#e67e22"),
-          (b.flat.pumpkin = "#d35400"),
-          (b.flat.peterriver = "#3498db"),
-          (b.flat.belizehole = "#2980b9"),
-          (b.flat.alizarin = "#e74c3c"),
-          (b.flat.pomegranate = "#c0392b"),
-          (b.flat.amethyst = "#9b59b6"),
-          (b.flat.wisteria = "#8e44ad"),
-          (b.flat.clouds = "#ecf0f1"),
-          (b.flat.silver = "#bdc3c7"),
-          (b.flat.wetasphalt = "#34495e"),
-          (b.flat.midnightblue = "#2c3e50"),
-          (b.flat.concrete = "#95a5a6"),
-          (b.flat.asbestos = "#7f8c8d"),
-          (b.importMUIColors = function () {
-            for (var c in b.mui) b.mui.hasOwnProperty(c) && (a[c] = b.mui[c]);
-          });
-      }),
-      d
-    );
-  });
+// Snap.svg 0.5.1
+//
+// Copyright (c) 2013 – 2017 Adobe Systems Incorporated. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+// build: 2017-02-07
+
+!(function (a) {
+  var b,
+    c,
+    d = "0.5.0",
+    e = "hasOwnProperty",
+    f = /[\.\/]/,
+    g = /\s*,\s*/,
+    h = "*",
+    i = function (a, b) {
+      return a - b;
+    },
+    j = { n: {} },
+    k = function () {
+      for (var a = 0, b = this.length; b > a; a++)
+        if ("undefined" != typeof this[a]) return this[a];
+    },
+    l = function () {
+      for (var a = this.length; --a; ) if ("undefined" != typeof this[a]) return this[a];
+    },
+    m = Object.prototype.toString,
+    n = String,
+    o =
+      Array.isArray ||
+      function (a) {
+        return a instanceof Array || "[object Array]" == m.call(a);
+      };
+  (eve = function (a, d) {
+    var e,
+      f = c,
+      g = Array.prototype.slice.call(arguments, 2),
+      h = eve.listeners(a),
+      j = 0,
+      m = [],
+      n = {},
+      o = [],
+      p = b;
+    (o.firstDefined = k), (o.lastDefined = l), (b = a), (c = 0);
+    for (var q = 0, r = h.length; r > q; q++)
+      "zIndex" in h[q] && (m.push(h[q].zIndex), h[q].zIndex < 0 && (n[h[q].zIndex] = h[q]));
+    for (m.sort(i); m[j] < 0; ) if (((e = n[m[j++]]), o.push(e.apply(d, g)), c)) return (c = f), o;
+    for (q = 0; r > q; q++)
+      if (((e = h[q]), "zIndex" in e))
+        if (e.zIndex == m[j]) {
+          if ((o.push(e.apply(d, g)), c)) break;
+          do if ((j++, (e = n[m[j]]), e && o.push(e.apply(d, g)), c)) break;
+          while (e);
+        } else n[e.zIndex] = e;
+      else if ((o.push(e.apply(d, g)), c)) break;
+    return (c = f), (b = p), o;
+  }),
+    (eve._events = j),
+    (eve.listeners = function (a) {
+      var b,
+        c,
+        d,
+        e,
+        g,
+        i,
+        k,
+        l,
+        m = o(a) ? a : a.split(f),
+        n = j,
+        p = [n],
+        q = [];
+      for (e = 0, g = m.length; g > e; e++) {
+        for (l = [], i = 0, k = p.length; k > i; i++)
+          for (n = p[i].n, c = [n[m[e]], n[h]], d = 2; d--; )
+            (b = c[d]), b && (l.push(b), (q = q.concat(b.f || [])));
+        p = l;
+      }
+      return q;
+    }),
+    (eve.separator = function (a) {
+      a
+        ? ((a = n(a).replace(/(?=[\.\^\]\[\-])/g, "\\")), (a = "[" + a + "]"), (f = new RegExp(a)))
+        : (f = /[\.\/]/);
+    }),
+    (eve.on = function (a, b) {
+      if ("function" != typeof b) return function () {};
+      for (var c = o(a) ? (o(a[0]) ? a : [a]) : n(a).split(g), d = 0, e = c.length; e > d; d++)
+        !(function (a) {
+          for (var c, d = o(a) ? a : n(a).split(f), e = j, g = 0, h = d.length; h > g; g++)
+            (e = e.n), (e = (e.hasOwnProperty(d[g]) && e[d[g]]) || (e[d[g]] = { n: {} }));
+          for (e.f = e.f || [], g = 0, h = e.f.length; h > g; g++)
+            if (e.f[g] == b) {
+              c = !0;
+              break;
+            }
+          !c && e.f.push(b);
+        })(c[d]);
+      return function (a) {
+        +a == +a && (b.zIndex = +a);
+      };
+    }),
+    (eve.f = function (a) {
+      var b = [].slice.call(arguments, 1);
+      return function () {
+        eve.apply(null, [a, null].concat(b).concat([].slice.call(arguments, 0)));
+      };
+    }),
+    (eve.stop = function () {
+      c = 1;
+    }),
+    (eve.nt = function (a) {
+      var c = o(b) ? b.join(".") : b;
+      return a ? new RegExp("(?:\\.|\\/|^)" + a + "(?:\\.|\\/|$)").test(c) : c;
+    }),
+    (eve.nts = function () {
+      return o(b) ? b : b.split(f);
+    }),
+    (eve.off = eve.unbind =
+      function (a, b) {
+        if (!a) return void (eve._events = j = { n: {} });
+        var c = o(a) ? (o(a[0]) ? a : [a]) : n(a).split(g);
+        if (c.length > 1) for (var d = 0, i = c.length; i > d; d++) eve.off(c[d], b);
+        else {
+          c = o(a) ? a : n(a).split(f);
+          var k,
+            l,
+            m,
+            d,
+            i,
+            p,
+            q,
+            r = [j],
+            s = [];
+          for (d = 0, i = c.length; i > d; d++)
+            for (p = 0; p < r.length; p += m.length - 2) {
+              if (((m = [p, 1]), (k = r[p].n), c[d] != h))
+                k[c[d]] && (m.push(k[c[d]]), s.unshift({ n: k, name: c[d] }));
+              else for (l in k) k[e](l) && (m.push(k[l]), s.unshift({ n: k, name: l }));
+              r.splice.apply(r, m);
+            }
+          for (d = 0, i = r.length; i > d; d++)
+            for (k = r[d]; k.n; ) {
+              if (b) {
+                if (k.f) {
+                  for (p = 0, q = k.f.length; q > p; p++)
+                    if (k.f[p] == b) {
+                      k.f.splice(p, 1);
+                      break;
+                    }
+                  !k.f.length && delete k.f;
+                }
+                for (l in k.n)
+                  if (k.n[e](l) && k.n[l].f) {
+                    var t = k.n[l].f;
+                    for (p = 0, q = t.length; q > p; p++)
+                      if (t[p] == b) {
+                        t.splice(p, 1);
+                        break;
+                      }
+                    !t.length && delete k.n[l].f;
+                  }
+              } else {
+                delete k.f;
+                for (l in k.n) k.n[e](l) && k.n[l].f && delete k.n[l].f;
+              }
+              k = k.n;
+            }
+          a: for (d = 0, i = s.length; i > d; d++) {
+            k = s[d];
+            for (l in k.n[k.name].f) continue a;
+            for (l in k.n[k.name].n) continue a;
+            delete k.n[k.name];
+          }
+        }
+      }),
+    (eve.once = function (a, b) {
+      var c = function () {
+        return eve.off(a, c), b.apply(this, arguments);
+      };
+      return eve.on(a, c);
+    }),
+    (eve.version = d),
+    (eve.toString = function () {
+      return "You are running Eve " + d;
+    }),
+    "undefined" != typeof module && module.exports
+      ? (module.exports = eve)
+      : "function" == typeof define && define.amd
+      ? define("eve", [], function () {
+          return eve;
+        })
+      : (a.eve = eve);
+})(this),
+  (function (a, b) {
+    if ("function" == typeof define && define.amd)
+      define(["eve"], function (c) {
+        return b(a, c);
+      });
+    else if ("undefined" != typeof exports) {
+      var c = require("eve");
+      module.exports = b(a, c);
+    } else b(a, a.eve);
+  })(window || this, function (a, b) {
+    var c = (function (b) {
+        var c,
+          d = {},
+          e =
+            a.requestAnimationFrame ||
+            a.webkitRequestAnimationFrame ||
+            a.mozRequestAnimationFrame ||
+            a.oRequestAnimationFrame ||
+            a.msRequestAnimationFrame ||
+            function (a) {
+              return setTimeout(a, 16, new Date().getTime()), !0;
+            },
+          f =
+            Array.isArray ||
+            function (a) {
+              return a instanceof Array || "[object Array]" == Object.prototype.toString.call(a);
+            },
+          g = 0,
+          h = "M" + (+new Date()).toString(36),
+          i = function () {
+            return h + (g++).toString(36);
+          },
+          j =
+            Date.now ||
+            function () {
+              return +new Date();
+            },
+          k = function (a) {
+            var b = this;
+            if (null == a) return b.s;
+            var c = b.s - a;
+            (b.b += b.dur * c), (b.B += b.dur * c), (b.s = a);
+          },
+          l = function (a) {
+            var b = this;
+            return null == a ? b.spd : void (b.spd = a);
+          },
+          m = function (a) {
+            var b = this;
+            return null == a ? b.dur : ((b.s = (b.s * a) / b.dur), void (b.dur = a));
+          },
+          n = function () {
+            var a = this;
+            delete d[a.id], a.update(), b("mina.stop." + a.id, a);
+          },
+          o = function () {
+            var a = this;
+            a.pdif || (delete d[a.id], a.update(), (a.pdif = a.get() - a.b));
+          },
+          p = function () {
+            var a = this;
+            a.pdif && ((a.b = a.get() - a.pdif), delete a.pdif, (d[a.id] = a), r());
+          },
+          q = function () {
+            var a,
+              b = this;
+            if (f(b.start)) {
+              a = [];
+              for (var c = 0, d = b.start.length; d > c; c++)
+                a[c] = +b.start[c] + (b.end[c] - b.start[c]) * b.easing(b.s);
+            } else a = +b.start + (b.end - b.start) * b.easing(b.s);
+            b.set(a);
+          },
+          r = function (a) {
+            if (!a) return void (c || (c = e(r)));
+            var f = 0;
+            for (var g in d)
+              if (d.hasOwnProperty(g)) {
+                var h = d[g],
+                  i = h.get();
+                f++,
+                  (h.s = (i - h.b) / (h.dur / h.spd)),
+                  h.s >= 1 &&
+                    (delete d[g],
+                    (h.s = 1),
+                    f--,
+                    (function (a) {
+                      setTimeout(function () {
+                        b("mina.finish." + a.id, a);
+                      });
+                    })(h)),
+                  h.update();
+              }
+            c = f ? e(r) : !1;
+          },
+          s = function (a, b, c, e, f, g, h) {
+            var j = {
+              id: i(),
+              start: a,
+              end: b,
+              b: c,
+              s: 0,
+              dur: e - c,
+              spd: 1,
+              get: f,
+              set: g,
+              easing: h || s.linear,
+              status: k,
+              speed: l,
+              duration: m,
+              stop: n,
+              pause: o,
+              resume: p,
+              update: q,
+            };
+            d[j.id] = j;
+            var t,
+              u = 0;
+            for (t in d) if (d.hasOwnProperty(t) && (u++, 2 == u)) break;
+            return 1 == u && r(), j;
+          };
+        return (
+          (s.time = j),
+          (s.getById = function (a) {
+            return d[a] || null;
+          }),
+          (s.linear = function (a) {
+            return a;
+          }),
+          (s.easeout = function (a) {
+            return Math.pow(a, 1.7);
+          }),
+          (s.easein = function (a) {
+            return Math.pow(a, 0.48);
+          }),
+          (s.easeinout = function (a) {
+            if (1 == a) return 1;
+            if (0 == a) return 0;
+            var b = 0.48 - a / 1.04,
+              c = Math.sqrt(0.1734 + b * b),
+              d = c - b,
+              e = Math.pow(Math.abs(d), 1 / 3) * (0 > d ? -1 : 1),
+              f = -c - b,
+              g = Math.pow(Math.abs(f), 1 / 3) * (0 > f ? -1 : 1),
+              h = e + g + 0.5;
+            return 3 * (1 - h) * h * h + h * h * h;
+          }),
+          (s.backin = function (a) {
+            if (1 == a) return 1;
+            var b = 1.70158;
+            return a * a * ((b + 1) * a - b);
+          }),
+          (s.backout = function (a) {
+            if (0 == a) return 0;
+            a -= 1;
+            var b = 1.70158;
+            return a * a * ((b + 1) * a + b) + 1;
+          }),
+          (s.elastic = function (a) {
+            return a == !!a
+              ? a
+              : Math.pow(2, -10 * a) * Math.sin(((a - 0.075) * (2 * Math.PI)) / 0.3) + 1;
+          }),
+          (s.bounce = function (a) {
+            var b,
+              c = 7.5625,
+              d = 2.75;
+            return (
+              1 / d > a
+                ? (b = c * a * a)
+                : 2 / d > a
+                ? ((a -= 1.5 / d), (b = c * a * a + 0.75))
+                : 2.5 / d > a
+                ? ((a -= 2.25 / d), (b = c * a * a + 0.9375))
+                : ((a -= 2.625 / d), (b = c * a * a + 0.984375)),
+              b
+            );
+          }),
+          (a.mina = s),
+          s
+        );
+      })("undefined" == typeof b ? function () {} : b),
+      d = (function (a) {
+        function c(a, b) {
+          if (a) {
+            if (a.nodeType) return w(a);
+            if (e(a, "array") && c.set) return c.set.apply(c, a);
+            if (a instanceof s) return a;
+            if (null == b)
+              try {
+                return (a = y.doc.querySelector(String(a))), w(a);
+              } catch (d) {
+                return null;
+              }
+          }
+          return (a = null == a ? "100%" : a), (b = null == b ? "100%" : b), new v(a, b);
+        }
+        function d(a, b) {
+          if (b) {
+            if (
+              ("#text" == a && (a = y.doc.createTextNode(b.text || b["#text"] || "")),
+              "#comment" == a && (a = y.doc.createComment(b.text || b["#text"] || "")),
+              "string" == typeof a && (a = d(a)),
+              "string" == typeof b)
+            )
+              return 1 == a.nodeType
+                ? "xlink:" == b.substring(0, 6)
+                  ? a.getAttributeNS(T, b.substring(6))
+                  : "xml:" == b.substring(0, 4)
+                  ? a.getAttributeNS(U, b.substring(4))
+                  : a.getAttribute(b)
+                : "text" == b
+                ? a.nodeValue
+                : null;
+            if (1 == a.nodeType) {
+              for (var c in b)
+                if (b[z](c)) {
+                  var e = A(b[c]);
+                  e
+                    ? "xlink:" == c.substring(0, 6)
+                      ? a.setAttributeNS(T, c.substring(6), e)
+                      : "xml:" == c.substring(0, 4)
+                      ? a.setAttributeNS(U, c.substring(4), e)
+                      : a.setAttribute(c, e)
+                    : a.removeAttribute(c);
+                }
+            } else "text" in b && (a.nodeValue = b.text);
+          } else a = y.doc.createElementNS(U, a);
+          return a;
+        }
+        function e(a, b) {
+          return (
+            (b = A.prototype.toLowerCase.call(b)),
+            "finite" == b
+              ? isFinite(a)
+              : "array" == b && (a instanceof Array || (Array.isArray && Array.isArray(a)))
+              ? !0
+              : ("null" == b && null === a) ||
+                (b == typeof a && null !== a) ||
+                ("object" == b && a === Object(a)) ||
+                J.call(a).slice(8, -1).toLowerCase() == b
+          );
+        }
+        function f(a) {
+          if ("function" == typeof a || Object(a) !== a) return a;
+          var b = new a.constructor();
+          for (var c in a) a[z](c) && (b[c] = f(a[c]));
+          return b;
+        }
+        function h(a, b) {
+          for (var c = 0, d = a.length; d > c; c++)
+            if (a[c] === b) return a.push(a.splice(c, 1)[0]);
+        }
+        function i(a, b, c) {
+          function d() {
+            var e = Array.prototype.slice.call(arguments, 0),
+              f = e.join("␀"),
+              g = (d.cache = d.cache || {}),
+              i = (d.count = d.count || []);
+            return g[z](f)
+              ? (h(i, f), c ? c(g[f]) : g[f])
+              : (i.length >= 1e3 && delete g[i.shift()],
+                i.push(f),
+                (g[f] = a.apply(b, e)),
+                c ? c(g[f]) : g[f]);
+          }
+          return d;
+        }
+        function j(a, b, c, d, e, f) {
+          if (null == e) {
+            var g = a - c,
+              h = b - d;
+            return g || h ? (180 + (180 * D.atan2(-h, -g)) / H + 360) % 360 : 0;
+          }
+          return j(a, b, e, f) - j(c, d, e, f);
+        }
+        function k(a) {
+          return ((a % 360) * H) / 180;
+        }
+        function l(a) {
+          return ((180 * a) / H) % 360;
+        }
+        function m(a) {
+          var b = [];
+          return (
+            (a = a.replace(/(?:^|\s)(\w+)\(([^)]+)\)/g, function (a, c, d) {
+              return (
+                (d = d.split(/\s*,\s*|\s+/)),
+                "rotate" == c && 1 == d.length && d.push(0, 0),
+                "scale" == c &&
+                  (d.length > 2 ? (d = d.slice(0, 2)) : 2 == d.length && d.push(0, 0),
+                  1 == d.length && d.push(d[0], 0, 0)),
+                "skewX" == c
+                  ? b.push(["m", 1, 0, D.tan(k(d[0])), 1, 0, 0])
+                  : "skewY" == c
+                  ? b.push(["m", 1, D.tan(k(d[0])), 0, 1, 0, 0])
+                  : b.push([c.charAt(0)].concat(d)),
+                a
+              );
+            })),
+            b
+          );
+        }
+        function n(a, b) {
+          var d = aa(a),
+            e = new c.Matrix();
+          if (d)
+            for (var f = 0, g = d.length; g > f; f++) {
+              var h,
+                i,
+                j,
+                k,
+                l,
+                m = d[f],
+                n = m.length,
+                o = A(m[0]).toLowerCase(),
+                p = m[0] != o,
+                q = p ? e.invert() : 0;
+              "t" == o && 2 == n
+                ? e.translate(m[1], 0)
+                : "t" == o && 3 == n
+                ? p
+                  ? ((h = q.x(0, 0)),
+                    (i = q.y(0, 0)),
+                    (j = q.x(m[1], m[2])),
+                    (k = q.y(m[1], m[2])),
+                    e.translate(j - h, k - i))
+                  : e.translate(m[1], m[2])
+                : "r" == o
+                ? 2 == n
+                  ? ((l = l || b), e.rotate(m[1], l.x + l.width / 2, l.y + l.height / 2))
+                  : 4 == n &&
+                    (p
+                      ? ((j = q.x(m[2], m[3])), (k = q.y(m[2], m[3])), e.rotate(m[1], j, k))
+                      : e.rotate(m[1], m[2], m[3]))
+                : "s" == o
+                ? 2 == n || 3 == n
+                  ? ((l = l || b), e.scale(m[1], m[n - 1], l.x + l.width / 2, l.y + l.height / 2))
+                  : 4 == n
+                  ? p
+                    ? ((j = q.x(m[2], m[3])), (k = q.y(m[2], m[3])), e.scale(m[1], m[1], j, k))
+                    : e.scale(m[1], m[1], m[2], m[3])
+                  : 5 == n &&
+                    (p
+                      ? ((j = q.x(m[3], m[4])), (k = q.y(m[3], m[4])), e.scale(m[1], m[2], j, k))
+                      : e.scale(m[1], m[2], m[3], m[4]))
+                : "m" == o && 7 == n && e.add(m[1], m[2], m[3], m[4], m[5], m[6]);
+            }
+          return e;
+        }
+        function o(a) {
+          var b =
+              (a.node.ownerSVGElement && w(a.node.ownerSVGElement)) ||
+              (a.node.parentNode && w(a.node.parentNode)) ||
+              c.select("svg") ||
+              c(0, 0),
+            d = b.select("defs"),
+            e = null == d ? !1 : d.node;
+          return e || (e = u("defs", b.node).node), e;
+        }
+        function p(a) {
+          return (a.node.ownerSVGElement && w(a.node.ownerSVGElement)) || c.select("svg");
+        }
+        function q(a, b, c) {
+          function e(a) {
+            if (null == a) return I;
+            if (a == +a) return a;
+            d(j, { width: a });
+            try {
+              return j.getBBox().width;
+            } catch (b) {
+              return 0;
+            }
+          }
+          function f(a) {
+            if (null == a) return I;
+            if (a == +a) return a;
+            d(j, { height: a });
+            try {
+              return j.getBBox().height;
+            } catch (b) {
+              return 0;
+            }
+          }
+          function g(d, e) {
+            null == b
+              ? (i[d] = e(a.attr(d) || 0))
+              : d == b && (i = e(null == c ? a.attr(d) || 0 : c));
+          }
+          var h = p(a).node,
+            i = {},
+            j = h.querySelector(".svg---mgr");
+          switch (
+            (j ||
+              ((j = d("rect")),
+              d(j, { x: -9e9, y: -9e9, width: 10, height: 10, class: "svg---mgr", fill: "none" }),
+              h.appendChild(j)),
+            a.type)
+          ) {
+            case "rect":
+              g("rx", e), g("ry", f);
+            case "image":
+              g("width", e), g("height", f);
+            case "text":
+              g("x", e), g("y", f);
+              break;
+            case "circle":
+              g("cx", e), g("cy", f), g("r", e);
+              break;
+            case "ellipse":
+              g("cx", e), g("cy", f), g("rx", e), g("ry", f);
+              break;
+            case "line":
+              g("x1", e), g("x2", e), g("y1", f), g("y2", f);
+              break;
+            case "marker":
+              g("refX", e), g("markerWidth", e), g("refY", f), g("markerHeight", f);
+              break;
+            case "radialGradient":
+              g("fx", e), g("fy", f);
+              break;
+            case "tspan":
+              g("dx", e), g("dy", f);
+              break;
+            default:
+              g(b, e);
+          }
+          return h.removeChild(j), i;
+        }
+        function r(a) {
+          e(a, "array") || (a = Array.prototype.slice.call(arguments, 0));
+          for (var b = 0, c = 0, d = this.node; this[b]; ) delete this[b++];
+          for (b = 0; b < a.length; b++)
+            "set" == a[b].type
+              ? a[b].forEach(function (a) {
+                  d.appendChild(a.node);
+                })
+              : d.appendChild(a[b].node);
+          var f = d.childNodes;
+          for (b = 0; b < f.length; b++) this[c++] = w(f[b]);
+          return this;
+        }
+        function s(a) {
+          if (a.snap in V) return V[a.snap];
+          var b;
+          try {
+            b = a.ownerSVGElement;
+          } catch (c) {}
+          (this.node = a), b && (this.paper = new v(b)), (this.type = a.tagName || a.nodeName);
+          var d = (this.id = S(this));
+          if (
+            ((this.anims = {}),
+            (this._ = { transform: [] }),
+            (a.snap = d),
+            (V[d] = this),
+            "g" == this.type && (this.add = r),
+            this.type in { g: 1, mask: 1, pattern: 1, symbol: 1 })
+          )
+            for (var e in v.prototype) v.prototype[z](e) && (this[e] = v.prototype[e]);
+        }
+        function t(a) {
+          this.node = a;
+        }
+        function u(a, b) {
+          var c = d(a);
+          b.appendChild(c);
+          var e = w(c);
+          return e;
+        }
+        function v(a, b) {
+          var c,
+            e,
+            f,
+            g = v.prototype;
+          if (a && a.tagName && "svg" == a.tagName.toLowerCase()) {
+            if (a.snap in V) return V[a.snap];
+            var h = a.ownerDocument;
+            (c = new s(a)),
+              (e = a.getElementsByTagName("desc")[0]),
+              (f = a.getElementsByTagName("defs")[0]),
+              e ||
+                ((e = d("desc")),
+                e.appendChild(h.createTextNode("Created with Snap")),
+                c.node.appendChild(e)),
+              f || ((f = d("defs")), c.node.appendChild(f)),
+              (c.defs = f);
+            for (var i in g) g[z](i) && (c[i] = g[i]);
+            c.paper = c.root = c;
+          } else
+            (c = u("svg", y.doc.body)), d(c.node, { height: b, version: 1.1, width: a, xmlns: U });
+          return c;
+        }
+        function w(a) {
+          return a
+            ? a instanceof s || a instanceof t
+              ? a
+              : a.tagName && "svg" == a.tagName.toLowerCase()
+              ? new v(a)
+              : a.tagName && "object" == a.tagName.toLowerCase() && "image/svg+xml" == a.type
+              ? new v(a.contentDocument.getElementsByTagName("svg")[0])
+              : new s(a)
+            : a;
+        }
+        function x(a, b) {
+          for (var c = 0, d = a.length; d > c; c++) {
+            var e = { type: a[c].type, attr: a[c].attr() },
+              f = a[c].children();
+            b.push(e), f.length && x(f, (e.childNodes = []));
+          }
+        }
+        (c.version = "0.5.1"),
+          (c.toString = function () {
+            return "Snap v" + this.version;
+          }),
+          (c._ = {});
+        var y = { win: a.window, doc: a.window.document };
+        c._.glob = y;
+        var z = "hasOwnProperty",
+          A = String,
+          B = parseFloat,
+          C = parseInt,
+          D = Math,
+          E = D.max,
+          F = D.min,
+          G = D.abs,
+          H = (D.pow, D.PI),
+          I = (D.round, ""),
+          J = Object.prototype.toString,
+          K =
+            /^\s*((#[a-f\d]{6})|(#[a-f\d]{3})|rgba?\(\s*([\d\.]+%?\s*,\s*[\d\.]+%?\s*,\s*[\d\.]+%?(?:\s*,\s*[\d\.]+%?)?)\s*\)|hsba?\(\s*([\d\.]+(?:deg|\xb0|%)?\s*,\s*[\d\.]+%?\s*,\s*[\d\.]+(?:%?\s*,\s*[\d\.]+)?%?)\s*\)|hsla?\(\s*([\d\.]+(?:deg|\xb0|%)?\s*,\s*[\d\.]+%?\s*,\s*[\d\.]+(?:%?\s*,\s*[\d\.]+)?%?)\s*\))\s*$/i,
+          L = ((c._.separator = /[,\s]+/), /[\s]*,[\s]*/),
+          M = { hs: 1, rg: 1 },
+          N = /([a-z])[\s,]*((-?\d*\.?\d*(?:e[\-+]?\d+)?[\s]*,?[\s]*)+)/gi,
+          O = /([rstm])[\s,]*((-?\d*\.?\d*(?:e[\-+]?\d+)?[\s]*,?[\s]*)+)/gi,
+          P = /(-?\d*\.?\d*(?:e[\-+]?\d+)?)[\s]*,?[\s]*/gi,
+          Q = 0,
+          R = "S" + (+new Date()).toString(36),
+          S = function (a) {
+            return (a && a.type ? a.type : I) + R + (Q++).toString(36);
+          },
+          T = "http://www.w3.org/1999/xlink",
+          U = "http://www.w3.org/2000/svg",
+          V = {};
+        c.url = function (a) {
+          return "url('#" + a + "')";
+        };
+        (c._.$ = d),
+          (c._.id = S),
+          (c.format = (function () {
+            var a = /\{([^\}]+)\}/g,
+              b = /(?:(?:^|\.)(.+?)(?=\[|\.|$|\()|\[('|")(.+?)\2\])(\(\))?/g,
+              c = function (a, c, d) {
+                var e = d;
+                return (
+                  c.replace(b, function (a, b, c, d, f) {
+                    (b = b || d),
+                      e && (b in e && (e = e[b]), "function" == typeof e && f && (e = e()));
+                  }),
+                  (e = (null == e || e == d ? a : e) + "")
+                );
+              };
+            return function (b, d) {
+              return A(b).replace(a, function (a, b) {
+                return c(a, b, d);
+              });
+            };
+          })()),
+          (c._.clone = f),
+          (c._.cacher = i),
+          (c.rad = k),
+          (c.deg = l),
+          (c.sin = function (a) {
+            return D.sin(c.rad(a));
+          }),
+          (c.tan = function (a) {
+            return D.tan(c.rad(a));
+          }),
+          (c.cos = function (a) {
+            return D.cos(c.rad(a));
+          }),
+          (c.asin = function (a) {
+            return c.deg(D.asin(a));
+          }),
+          (c.acos = function (a) {
+            return c.deg(D.acos(a));
+          }),
+          (c.atan = function (a) {
+            return c.deg(D.atan(a));
+          }),
+          (c.atan2 = function (a) {
+            return c.deg(D.atan2(a));
+          }),
+          (c.angle = j),
+          (c.len = function (a, b, d, e) {
+            return Math.sqrt(c.len2(a, b, d, e));
+          }),
+          (c.len2 = function (a, b, c, d) {
+            return (a - c) * (a - c) + (b - d) * (b - d);
+          }),
+          (c.closestPoint = function (a, b, c) {
+            function d(a) {
+              var d = a.x - b,
+                e = a.y - c;
+              return d * d + e * e;
+            }
+            for (
+              var e,
+                f,
+                g,
+                h,
+                i = a.node,
+                j = i.getTotalLength(),
+                k = (j / i.pathSegList.numberOfItems) * 0.125,
+                l = 1 / 0,
+                m = 0;
+              j >= m;
+              m += k
+            )
+              (h = d((g = i.getPointAtLength(m)))) < l && ((e = g), (f = m), (l = h));
+            for (k *= 0.5; k > 0.5; ) {
+              var n, o, p, q, r, s;
+              (p = f - k) >= 0 && (r = d((n = i.getPointAtLength(p)))) < l
+                ? ((e = n), (f = p), (l = r))
+                : (q = f + k) <= j && (s = d((o = i.getPointAtLength(q)))) < l
+                ? ((e = o), (f = q), (l = s))
+                : (k *= 0.5);
+            }
+            return (e = { x: e.x, y: e.y, length: f, distance: Math.sqrt(l) });
+          }),
+          (c.is = e),
+          (c.snapTo = function (a, b, c) {
+            if (((c = e(c, "finite") ? c : 10), e(a, "array"))) {
+              for (var d = a.length; d--; ) if (G(a[d] - b) <= c) return a[d];
+            } else {
+              a = +a;
+              var f = b % a;
+              if (c > f) return b - f;
+              if (f > a - c) return b - f + a;
+            }
+            return b;
+          }),
+          (c.getRGB = i(function (a) {
+            if (!a || (a = A(a)).indexOf("-") + 1)
+              return { r: -1, g: -1, b: -1, hex: "none", error: 1, toString: Z };
+            if ("none" == a) return { r: -1, g: -1, b: -1, hex: "none", toString: Z };
+            if ((!(M[z](a.toLowerCase().substring(0, 2)) || "#" == a.charAt()) && (a = W(a)), !a))
+              return { r: -1, g: -1, b: -1, hex: "none", error: 1, toString: Z };
+            var b,
+              d,
+              f,
+              g,
+              h,
+              i,
+              j = a.match(K);
+            return j
+              ? (j[2] &&
+                  ((f = C(j[2].substring(5), 16)),
+                  (d = C(j[2].substring(3, 5), 16)),
+                  (b = C(j[2].substring(1, 3), 16))),
+                j[3] &&
+                  ((f = C((h = j[3].charAt(3)) + h, 16)),
+                  (d = C((h = j[3].charAt(2)) + h, 16)),
+                  (b = C((h = j[3].charAt(1)) + h, 16))),
+                j[4] &&
+                  ((i = j[4].split(L)),
+                  (b = B(i[0])),
+                  "%" == i[0].slice(-1) && (b *= 2.55),
+                  (d = B(i[1])),
+                  "%" == i[1].slice(-1) && (d *= 2.55),
+                  (f = B(i[2])),
+                  "%" == i[2].slice(-1) && (f *= 2.55),
+                  "rgba" == j[1].toLowerCase().slice(0, 4) && (g = B(i[3])),
+                  i[3] && "%" == i[3].slice(-1) && (g /= 100)),
+                j[5]
+                  ? ((i = j[5].split(L)),
+                    (b = B(i[0])),
+                    "%" == i[0].slice(-1) && (b /= 100),
+                    (d = B(i[1])),
+                    "%" == i[1].slice(-1) && (d /= 100),
+                    (f = B(i[2])),
+                    "%" == i[2].slice(-1) && (f /= 100),
+                    ("deg" == i[0].slice(-3) || "°" == i[0].slice(-1)) && (b /= 360),
+                    "hsba" == j[1].toLowerCase().slice(0, 4) && (g = B(i[3])),
+                    i[3] && "%" == i[3].slice(-1) && (g /= 100),
+                    c.hsb2rgb(b, d, f, g))
+                  : j[6]
+                  ? ((i = j[6].split(L)),
+                    (b = B(i[0])),
+                    "%" == i[0].slice(-1) && (b /= 100),
+                    (d = B(i[1])),
+                    "%" == i[1].slice(-1) && (d /= 100),
+                    (f = B(i[2])),
+                    "%" == i[2].slice(-1) && (f /= 100),
+                    ("deg" == i[0].slice(-3) || "°" == i[0].slice(-1)) && (b /= 360),
+                    "hsla" == j[1].toLowerCase().slice(0, 4) && (g = B(i[3])),
+                    i[3] && "%" == i[3].slice(-1) && (g /= 100),
+                    c.hsl2rgb(b, d, f, g))
+                  : ((b = F(D.round(b), 255)),
+                    (d = F(D.round(d), 255)),
+                    (f = F(D.round(f), 255)),
+                    (g = F(E(g, 0), 1)),
+                    (j = { r: b, g: d, b: f, toString: Z }),
+                    (j.hex = "#" + (16777216 | f | (d << 8) | (b << 16)).toString(16).slice(1)),
+                    (j.opacity = e(g, "finite") ? g : 1),
+                    j))
+              : { r: -1, g: -1, b: -1, hex: "none", error: 1, toString: Z };
+          }, c)),
+          (c.hsb = i(function (a, b, d) {
+            return c.hsb2rgb(a, b, d).hex;
+          })),
+          (c.hsl = i(function (a, b, d) {
+            return c.hsl2rgb(a, b, d).hex;
+          })),
+          (c.rgb = i(function (a, b, c, d) {
+            if (e(d, "finite")) {
+              var f = D.round;
+              return "rgba(" + [f(a), f(b), f(c), +d.toFixed(2)] + ")";
+            }
+            return "#" + (16777216 | c | (b << 8) | (a << 16)).toString(16).slice(1);
+          }));
+        var W = function (a) {
+            var b = y.doc.getElementsByTagName("head")[0] || y.doc.getElementsByTagName("svg")[0],
+              c = "rgb(255, 0, 0)";
+            return (W = i(function (a) {
+              if ("red" == a.toLowerCase()) return c;
+              (b.style.color = c), (b.style.color = a);
+              var d = y.doc.defaultView.getComputedStyle(b, I).getPropertyValue("color");
+              return d == c ? null : d;
+            }))(a);
+          },
+          X = function () {
+            return "hsb(" + [this.h, this.s, this.b] + ")";
+          },
+          Y = function () {
+            return "hsl(" + [this.h, this.s, this.l] + ")";
+          },
+          Z = function () {
+            return 1 == this.opacity || null == this.opacity
+              ? this.hex
+              : "rgba(" + [this.r, this.g, this.b, this.opacity] + ")";
+          },
+          $ = function (a, b, d) {
+            if (
+              (null == b &&
+                e(a, "object") &&
+                "r" in a &&
+                "g" in a &&
+                "b" in a &&
+                ((d = a.b), (b = a.g), (a = a.r)),
+              null == b && e(a, string))
+            ) {
+              var f = c.getRGB(a);
+              (a = f.r), (b = f.g), (d = f.b);
+            }
+            return (a > 1 || b > 1 || d > 1) && ((a /= 255), (b /= 255), (d /= 255)), [a, b, d];
+          },
+          _ = function (a, b, d, f) {
+            (a = D.round(255 * a)), (b = D.round(255 * b)), (d = D.round(255 * d));
+            var g = {
+              r: a,
+              g: b,
+              b: d,
+              opacity: e(f, "finite") ? f : 1,
+              hex: c.rgb(a, b, d),
+              toString: Z,
+            };
+            return e(f, "finite") && (g.opacity = f), g;
+          };
+        (c.color = function (a) {
+          var b;
+          return (
+            e(a, "object") && "h" in a && "s" in a && "b" in a
+              ? ((b = c.hsb2rgb(a)),
+                (a.r = b.r),
+                (a.g = b.g),
+                (a.b = b.b),
+                (a.opacity = 1),
+                (a.hex = b.hex))
+              : e(a, "object") && "h" in a && "s" in a && "l" in a
+              ? ((b = c.hsl2rgb(a)),
+                (a.r = b.r),
+                (a.g = b.g),
+                (a.b = b.b),
+                (a.opacity = 1),
+                (a.hex = b.hex))
+              : (e(a, "string") && (a = c.getRGB(a)),
+                e(a, "object") && "r" in a && "g" in a && "b" in a && !("error" in a)
+                  ? ((b = c.rgb2hsl(a)),
+                    (a.h = b.h),
+                    (a.s = b.s),
+                    (a.l = b.l),
+                    (b = c.rgb2hsb(a)),
+                    (a.v = b.b))
+                  : ((a = { hex: "none" }),
+                    (a.r = a.g = a.b = a.h = a.s = a.v = a.l = -1),
+                    (a.error = 1))),
+            (a.toString = Z),
+            a
+          );
+        }),
+          (c.hsb2rgb = function (a, b, c, d) {
+            e(a, "object") &&
+              "h" in a &&
+              "s" in a &&
+              "b" in a &&
+              ((c = a.b), (b = a.s), (d = a.o), (a = a.h)),
+              (a *= 360);
+            var f, g, h, i, j;
+            return (
+              (a = (a % 360) / 60),
+              (j = c * b),
+              (i = j * (1 - G((a % 2) - 1))),
+              (f = g = h = c - j),
+              (a = ~~a),
+              (f += [j, i, 0, 0, i, j][a]),
+              (g += [i, j, j, i, 0, 0][a]),
+              (h += [0, 0, i, j, j, i][a]),
+              _(f, g, h, d)
+            );
+          }),
+          (c.hsl2rgb = function (a, b, c, d) {
+            e(a, "object") && "h" in a && "s" in a && "l" in a && ((c = a.l), (b = a.s), (a = a.h)),
+              (a > 1 || b > 1 || c > 1) && ((a /= 360), (b /= 100), (c /= 100)),
+              (a *= 360);
+            var f, g, h, i, j;
+            return (
+              (a = (a % 360) / 60),
+              (j = 2 * b * (0.5 > c ? c : 1 - c)),
+              (i = j * (1 - G((a % 2) - 1))),
+              (f = g = h = c - j / 2),
+              (a = ~~a),
+              (f += [j, i, 0, 0, i, j][a]),
+              (g += [i, j, j, i, 0, 0][a]),
+              (h += [0, 0, i, j, j, i][a]),
+              _(f, g, h, d)
+            );
+          }),
+          (c.rgb2hsb = function (a, b, c) {
+            (c = $(a, b, c)), (a = c[0]), (b = c[1]), (c = c[2]);
+            var d, e, f, g;
+            return (
+              (f = E(a, b, c)),
+              (g = f - F(a, b, c)),
+              (d =
+                0 == g ? null : f == a ? (b - c) / g : f == b ? (c - a) / g + 2 : (a - b) / g + 4),
+              (d = (((d + 360) % 6) * 60) / 360),
+              (e = 0 == g ? 0 : g / f),
+              { h: d, s: e, b: f, toString: X }
+            );
+          }),
+          (c.rgb2hsl = function (a, b, c) {
+            (c = $(a, b, c)), (a = c[0]), (b = c[1]), (c = c[2]);
+            var d, e, f, g, h, i;
+            return (
+              (g = E(a, b, c)),
+              (h = F(a, b, c)),
+              (i = g - h),
+              (d =
+                0 == i ? null : g == a ? (b - c) / i : g == b ? (c - a) / i + 2 : (a - b) / i + 4),
+              (d = (((d + 360) % 6) * 60) / 360),
+              (f = (g + h) / 2),
+              (e = 0 == i ? 0 : 0.5 > f ? i / (2 * f) : i / (2 - 2 * f)),
+              { h: d, s: e, l: f, toString: Y }
+            );
+          }),
+          (c.parsePathString = function (a) {
+            if (!a) return null;
+            var b = c.path(a);
+            if (b.arr) return c.path.clone(b.arr);
+            var d = {
+                a: 7,
+                c: 6,
+                o: 2,
+                h: 1,
+                l: 2,
+                m: 2,
+                r: 4,
+                q: 4,
+                s: 4,
+                t: 2,
+                v: 1,
+                u: 3,
+                z: 0,
+              },
+              f = [];
+            return (
+              e(a, "array") && e(a[0], "array") && (f = c.path.clone(a)),
+              f.length ||
+                A(a).replace(N, function (a, b, c) {
+                  var e = [],
+                    g = b.toLowerCase();
+                  if (
+                    (c.replace(P, function (a, b) {
+                      b && e.push(+b);
+                    }),
+                    "m" == g &&
+                      e.length > 2 &&
+                      (f.push([b].concat(e.splice(0, 2))), (g = "l"), (b = "m" == b ? "l" : "L")),
+                    "o" == g && 1 == e.length && f.push([b, e[0]]),
+                    "r" == g)
+                  )
+                    f.push([b].concat(e));
+                  else for (; e.length >= d[g] && (f.push([b].concat(e.splice(0, d[g]))), d[g]); );
+                }),
+              (f.toString = c.path.toString),
+              (b.arr = c.path.clone(f)),
+              f
+            );
+          });
+        var aa = (c.parseTransformString = function (a) {
+          if (!a) return null;
+          var b = [];
+          return (
+            e(a, "array") && e(a[0], "array") && (b = c.path.clone(a)),
+            b.length ||
+              A(a).replace(O, function (a, c, d) {
+                var e = [];
+                c.toLowerCase();
+                d.replace(P, function (a, b) {
+                  b && e.push(+b);
+                }),
+                  b.push([c].concat(e));
+              }),
+            (b.toString = c.path.toString),
+            b
+          );
+        });
+        (c._.svgTransform2string = m),
+          (c._.rgTransform = /^[a-z][\s]*-?\.?\d/i),
+          (c._.transform2matrix = n),
+          (c._unit2px = q);
+        y.doc.contains || y.doc.compareDocumentPosition
+          ? function (a, b) {
+              var c = 9 == a.nodeType ? a.documentElement : a,
+                d = b && b.parentNode;
+              return (
+                a == d ||
+                !(
+                  !d ||
+                  1 != d.nodeType ||
+                  !(c.contains
+                    ? c.contains(d)
+                    : a.compareDocumentPosition && 16 & a.compareDocumentPosition(d))
+                )
+              );
+            }
+          : function (a, b) {
+              if (b) for (; b; ) if (((b = b.parentNode), b == a)) return !0;
+              return !1;
+            };
+        (c._.getSomeDefs = o),
+          (c._.getSomeSVG = p),
+          (c.select = function (a) {
+            return (a = A(a).replace(/([^\\]):/g, "$1\\:")), w(y.doc.querySelector(a));
+          }),
+          (c.selectAll = function (a) {
+            for (
+              var b = y.doc.querySelectorAll(a), d = (c.set || Array)(), e = 0;
+              e < b.length;
+              e++
+            )
+              d.push(w(b[e]));
+            return d;
+          }),
+          setInterval(function () {
+            for (var a in V)
+              if (V[z](a)) {
+                var b = V[a],
+                  c = b.node;
+                (("svg" != b.type && !c.ownerSVGElement) ||
+                  ("svg" == b.type &&
+                    (!c.parentNode ||
+                      ("ownerSVGElement" in c.parentNode && !c.ownerSVGElement)))) &&
+                  delete V[a];
+              }
+          }, 1e4),
+          (s.prototype.attr = function (a, c) {
+            var d = this,
+              f = d.node;
+            if (!a) {
+              if (1 != f.nodeType) return { text: f.nodeValue };
+              for (var g = f.attributes, h = {}, i = 0, j = g.length; j > i; i++)
+                h[g[i].nodeName] = g[i].nodeValue;
+              return h;
+            }
+            if (e(a, "string")) {
+              if (!(arguments.length > 1)) return b("snap.util.getattr." + a, d).firstDefined();
+              var k = {};
+              (k[a] = c), (a = k);
+            }
+            for (var l in a) a[z](l) && b("snap.util.attr." + l, d, a[l]);
+            return d;
+          }),
+          (c.parse = function (a) {
+            var b = y.doc.createDocumentFragment(),
+              c = !0,
+              d = y.doc.createElement("div");
+            if (
+              ((a = A(a)),
+              a.match(/^\s*<\s*svg(?:\s|>)/) || ((a = "<svg>" + a + "</svg>"), (c = !1)),
+              (d.innerHTML = a),
+              (a = d.getElementsByTagName("svg")[0]))
+            )
+              if (c) b = a;
+              else for (; a.firstChild; ) b.appendChild(a.firstChild);
+            return new t(b);
+          }),
+          (c.fragment = function () {
+            for (
+              var a = Array.prototype.slice.call(arguments, 0),
+                b = y.doc.createDocumentFragment(),
+                d = 0,
+                e = a.length;
+              e > d;
+              d++
+            ) {
+              var f = a[d];
+              f.node && f.node.nodeType && b.appendChild(f.node),
+                f.nodeType && b.appendChild(f),
+                "string" == typeof f && b.appendChild(c.parse(f).node);
+            }
+            return new t(b);
+          }),
+          (c._.make = u),
+          (c._.wrap = w),
+          (v.prototype.el = function (a, b) {
+            var c = u(a, this.node);
+            return b && c.attr(b), c;
+          }),
+          (s.prototype.children = function () {
+            for (var a = [], b = this.node.childNodes, d = 0, e = b.length; e > d; d++)
+              a[d] = c(b[d]);
+            return a;
+          }),
+          (s.prototype.toJSON = function () {
+            var a = [];
+            return x([this], a), a[0];
+          }),
+          b.on("snap.util.getattr", function () {
+            var a = b.nt();
+            a = a.substring(a.lastIndexOf(".") + 1);
+            var c = a.replace(/[A-Z]/g, function (a) {
+              return "-" + a.toLowerCase();
+            });
+            return ba[z](c)
+              ? this.node.ownerDocument.defaultView
+                  .getComputedStyle(this.node, null)
+                  .getPropertyValue(c)
+              : d(this.node, a);
+          });
+        var ba = {
+          "alignment-baseline": 0,
+          "baseline-shift": 0,
+          clip: 0,
+          "clip-path": 0,
+          "clip-rule": 0,
+          color: 0,
+          "color-interpolation": 0,
+          "color-interpolation-filters": 0,
+          "color-profile": 0,
+          "color-rendering": 0,
+          cursor: 0,
+          direction: 0,
+          display: 0,
+          "dominant-baseline": 0,
+          "enable-background": 0,
+          fill: 0,
+          "fill-opacity": 0,
+          "fill-rule": 0,
+          filter: 0,
+          "flood-color": 0,
+          "flood-opacity": 0,
+          font: 0,
+          "font-family": 0,
+          "font-size": 0,
+          "font-size-adjust": 0,
+          "font-stretch": 0,
+          "font-style": 0,
+          "font-variant": 0,
+          "font-weight": 0,
+          "glyph-orientation-horizontal": 0,
+          "glyph-orientation-vertical": 0,
+          "image-rendering": 0,
+          kerning: 0,
+          "letter-spacing": 0,
+          "lighting-color": 0,
+          marker: 0,
+          "marker-end": 0,
+          "marker-mid": 0,
+          "marker-start": 0,
+          mask: 0,
+          opacity: 0,
+          overflow: 0,
+          "pointer-events": 0,
+          "shape-rendering": 0,
+          "stop-color": 0,
+          "stop-opacity": 0,
+          stroke: 0,
+          "stroke-dasharray": 0,
+          "stroke-dashoffset": 0,
+          "stroke-linecap": 0,
+          "stroke-linejoin": 0,
+          "stroke-miterlimit": 0,
+          "stroke-opacity": 0,
+          "stroke-width": 0,
+          "text-anchor": 0,
+          "text-decoration": 0,
+          "text-rendering": 0,
+          "unicode-bidi": 0,
+          visibility: 0,
+          "word-spacing": 0,
+          "writing-mode": 0,
+        };
+        b.on("snap.util.attr", function (a) {
+          var c = b.nt(),
+            e = {};
+          (c = c.substring(c.lastIndexOf(".") + 1)), (e[c] = a);
+          var f = c.replace(/-(\w)/gi, function (a, b) {
+              return b.toUpperCase();
+            }),
+            g = c.replace(/[A-Z]/g, function (a) {
+              return "-" + a.toLowerCase();
+            });
+          ba[z](g) ? (this.node.style[f] = null == a ? I : a) : d(this.node, e);
+        }),
+          (function (a) {})(v.prototype),
+          (c.ajax = function (a, c, d, f) {
+            var g = new XMLHttpRequest(),
+              h = S();
+            if (g) {
+              if (e(c, "function")) (f = d), (d = c), (c = null);
+              else if (e(c, "object")) {
+                var i = [];
+                for (var j in c)
+                  c.hasOwnProperty(j) &&
+                    i.push(encodeURIComponent(j) + "=" + encodeURIComponent(c[j]));
+                c = i.join("&");
+              }
+              return (
+                g.open(c ? "POST" : "GET", a, !0),
+                c &&
+                  (g.setRequestHeader("X-Requested-With", "XMLHttpRequest"),
+                  g.setRequestHeader("Content-type", "application/x-www-form-urlencoded")),
+                d &&
+                  (b.once("snap.ajax." + h + ".0", d),
+                  b.once("snap.ajax." + h + ".200", d),
+                  b.once("snap.ajax." + h + ".304", d)),
+                (g.onreadystatechange = function () {
+                  4 == g.readyState && b("snap.ajax." + h + "." + g.status, f, g);
+                }),
+                4 == g.readyState ? g : (g.send(c), g)
+              );
+            }
+          }),
+          (c.load = function (a, b, d) {
+            c.ajax(a, function (a) {
+              var e = c.parse(a.responseText);
+              d ? b.call(d, e) : b(e);
+            });
+          });
+        var ca = function (a) {
+          var b = a.getBoundingClientRect(),
+            c = a.ownerDocument,
+            d = c.body,
+            e = c.documentElement,
+            f = e.clientTop || d.clientTop || 0,
+            h = e.clientLeft || d.clientLeft || 0,
+            i = b.top + (g.win.pageYOffset || e.scrollTop || d.scrollTop) - f,
+            j = b.left + (g.win.pageXOffset || e.scrollLeft || d.scrollLeft) - h;
+          return { y: i, x: j };
+        };
+        return (
+          (c.getElementByPoint = function (a, b) {
+            var c = this,
+              d = (c.canvas, y.doc.elementFromPoint(a, b));
+            if (y.win.opera && "svg" == d.tagName) {
+              var e = ca(d),
+                f = d.createSVGRect();
+              (f.x = a - e.x), (f.y = b - e.y), (f.width = f.height = 1);
+              var g = d.getIntersectionList(f, null);
+              g.length && (d = g[g.length - 1]);
+            }
+            return d ? w(d) : null;
+          }),
+          (c.plugin = function (a) {
+            a(c, s, v, y, t);
+          }),
+          (y.win.Snap = c),
+          c
+        );
+      })(a || this);
+    return (
+      d.plugin(function (c, d, e, f, g) {
+        function h(a, b) {
+          if (null == b) {
+            var d = !0;
+            if (
+              ((b =
+                "linearGradient" == a.type || "radialGradient" == a.type
+                  ? a.node.getAttribute("gradientTransform")
+                  : "pattern" == a.type
+                  ? a.node.getAttribute("patternTransform")
+                  : a.node.getAttribute("transform")),
+              !b)
+            )
+              return new c.Matrix();
+            b = c._.svgTransform2string(b);
+          } else (b = c._.rgTransform.test(b) ? m(b).replace(/\.{3}|\u2026/g, a._.transform || "") : c._.svgTransform2string(b)), l(b, "array") && (b = c.path ? c.path.toString.call(b) : m(b)), (a._.transform = b);
+          var e = c._.transform2matrix(b, a.getBBox(1));
+          return d ? e : void (a.matrix = e);
+        }
+        function i(a) {
+          function b(a, b) {
+            var d = o(a.node, b);
+            (d = d && d.match(g)),
+              (d = d && d[2]),
+              d &&
+                "#" == d.charAt() &&
+                ((d = d.substring(1)),
+                d &&
+                  (i[d] = (i[d] || []).concat(function (d) {
+                    var e = {};
+                    (e[b] = c.url(d)), o(a.node, e);
+                  })));
+          }
+          function d(a) {
+            var b = o(a.node, "xlink:href");
+            b &&
+              "#" == b.charAt() &&
+              ((b = b.substring(1)),
+              b &&
+                (i[b] = (i[b] || []).concat(function (b) {
+                  a.attr("xlink:href", "#" + b);
+                })));
+          }
+          for (
+            var e,
+              f = a.selectAll("*"),
+              g = /^\s*url\(("|'|)(.*)\1\)\s*$/,
+              h = [],
+              i = {},
+              j = 0,
+              k = f.length;
+            k > j;
+            j++
+          ) {
+            (e = f[j]),
+              b(e, "fill"),
+              b(e, "stroke"),
+              b(e, "filter"),
+              b(e, "mask"),
+              b(e, "clip-path"),
+              d(e);
+            var l = o(e.node, "id");
+            l && (o(e.node, { id: e.id }), h.push({ old: l, id: e.id }));
+          }
+          for (j = 0, k = h.length; k > j; j++) {
+            var m = i[h[j].old];
+            if (m) for (var n = 0, p = m.length; p > n; n++) m[n](h[j].id);
+          }
+        }
+        function j(a) {
+          return function () {
+            var b = a ? "<" + this.type : "",
+              c = this.node.attributes,
+              d = this.node.childNodes;
+            if (a)
+              for (var e = 0, f = c.length; f > e; e++)
+                b += " " + c[e].name + '="' + c[e].value.replace(/"/g, '\\"') + '"';
+            if (d.length) {
+              for (a && (b += ">"), e = 0, f = d.length; f > e; e++)
+                3 == d[e].nodeType
+                  ? (b += d[e].nodeValue)
+                  : 1 == d[e].nodeType && (b += s(d[e]).toString());
+              a && (b += "</" + this.type + ">");
+            } else a && (b += "/>");
+            return b;
+          };
+        }
+        var k = d.prototype,
+          l = c.is,
+          m = String,
+          n = c._unit2px,
+          o = c._.$,
+          p = c._.make,
+          q = c._.getSomeDefs,
+          r = "hasOwnProperty",
+          s = c._.wrap;
+        k.getBBox = function (a) {
+          if ("tspan" == this.type) return c._.box(this.node.getClientRects().item(0));
+          if (!c.Matrix || !c.path) return this.node.getBBox();
+          var b = this,
+            d = new c.Matrix();
+          if (b.removed) return c._.box();
+          for (; "use" == b.type; )
+            if (
+              (a ||
+                (d = d.add(
+                  b.transform().localMatrix.translate(b.attr("x") || 0, b.attr("y") || 0)
+                )),
+              b.original)
+            )
+              b = b.original;
+            else {
+              var e = b.attr("xlink:href");
+              b = b.original = b.node.ownerDocument.getElementById(e.substring(e.indexOf("#") + 1));
+            }
+          var f = b._,
+            g = c.path.get[b.type] || c.path.get.deflt;
+          try {
+            return a
+              ? ((f.bboxwt = g ? c.path.getBBox((b.realPath = g(b))) : c._.box(b.node.getBBox())),
+                c._.box(f.bboxwt))
+              : ((b.realPath = g(b)),
+                (b.matrix = b.transform().localMatrix),
+                (f.bbox = c.path.getBBox(c.path.map(b.realPath, d.add(b.matrix)))),
+                c._.box(f.bbox));
+          } catch (h) {
+            return c._.box();
+          }
+        };
+        var t = function () {
+          return this.string;
+        };
+        (k.transform = function (a) {
+          var b = this._;
+          if (null == a) {
+            for (
+              var d,
+                e = this,
+                f = new c.Matrix(this.node.getCTM()),
+                g = h(this),
+                i = [g],
+                j = new c.Matrix(),
+                k = g.toTransformString(),
+                l = m(g) == m(this.matrix) ? m(b.transform) : k;
+              "svg" != e.type && (e = e.parent());
+
+            )
+              i.push(h(e));
+            for (d = i.length; d--; ) j.add(i[d]);
+            return {
+              string: l,
+              globalMatrix: f,
+              totalMatrix: j,
+              localMatrix: g,
+              diffMatrix: f.clone().add(g.invert()),
+              global: f.toTransformString(),
+              total: j.toTransformString(),
+              local: k,
+              toString: t,
+            };
+          }
+          return (
+            a instanceof c.Matrix
+              ? ((this.matrix = a), (this._.transform = a.toTransformString()))
+              : h(this, a),
+            this.node &&
+              ("linearGradient" == this.type || "radialGradient" == this.type
+                ? o(this.node, { gradientTransform: this.matrix })
+                : "pattern" == this.type
+                ? o(this.node, { patternTransform: this.matrix })
+                : o(this.node, { transform: this.matrix })),
+            this
+          );
+        }),
+          (k.parent = function () {
+            return s(this.node.parentNode);
+          }),
+          (k.append = k.add =
+            function (a) {
+              if (a) {
+                if ("set" == a.type) {
+                  var b = this;
+                  return (
+                    a.forEach(function (a) {
+                      b.add(a);
+                    }),
+                    this
+                  );
+                }
+                (a = s(a)), this.node.appendChild(a.node), (a.paper = this.paper);
+              }
+              return this;
+            }),
+          (k.appendTo = function (a) {
+            return a && ((a = s(a)), a.append(this)), this;
+          }),
+          (k.prepend = function (a) {
+            if (a) {
+              if ("set" == a.type) {
+                var b,
+                  c = this;
+                return (
+                  a.forEach(function (a) {
+                    b ? b.after(a) : c.prepend(a), (b = a);
+                  }),
+                  this
+                );
+              }
+              a = s(a);
+              var d = a.parent();
+              this.node.insertBefore(a.node, this.node.firstChild),
+                this.add && this.add(),
+                (a.paper = this.paper),
+                this.parent() && this.parent().add(),
+                d && d.add();
+            }
+            return this;
+          }),
+          (k.prependTo = function (a) {
+            return (a = s(a)), a.prepend(this), this;
+          }),
+          (k.before = function (a) {
+            if ("set" == a.type) {
+              var b = this;
+              return (
+                a.forEach(function (a) {
+                  var c = a.parent();
+                  b.node.parentNode.insertBefore(a.node, b.node), c && c.add();
+                }),
+                this.parent().add(),
+                this
+              );
+            }
+            a = s(a);
+            var c = a.parent();
+            return (
+              this.node.parentNode.insertBefore(a.node, this.node),
+              this.parent() && this.parent().add(),
+              c && c.add(),
+              (a.paper = this.paper),
+              this
+            );
+          }),
+          (k.after = function (a) {
+            a = s(a);
+            var b = a.parent();
+            return (
+              this.node.nextSibling
+                ? this.node.parentNode.insertBefore(a.node, this.node.nextSibling)
+                : this.node.parentNode.appendChild(a.node),
+              this.parent() && this.parent().add(),
+              b && b.add(),
+              (a.paper = this.paper),
+              this
+            );
+          }),
+          (k.insertBefore = function (a) {
+            a = s(a);
+            var b = this.parent();
+            return (
+              a.node.parentNode.insertBefore(this.node, a.node),
+              (this.paper = a.paper),
+              b && b.add(),
+              a.parent() && a.parent().add(),
+              this
+            );
+          }),
+          (k.insertAfter = function (a) {
+            a = s(a);
+            var b = this.parent();
+            return (
+              a.node.parentNode.insertBefore(this.node, a.node.nextSibling),
+              (this.paper = a.paper),
+              b && b.add(),
+              a.parent() && a.parent().add(),
+              this
+            );
+          }),
+          (k.remove = function () {
+            var a = this.parent();
+            return (
+              this.node.parentNode && this.node.parentNode.removeChild(this.node),
+              delete this.paper,
+              (this.removed = !0),
+              a && a.add(),
+              this
+            );
+          }),
+          (k.select = function (a) {
+            return s(this.node.querySelector(a));
+          }),
+          (k.selectAll = function (a) {
+            for (
+              var b = this.node.querySelectorAll(a), d = (c.set || Array)(), e = 0;
+              e < b.length;
+              e++
+            )
+              d.push(s(b[e]));
+            return d;
+          }),
+          (k.asPX = function (a, b) {
+            return null == b && (b = this.attr(a)), +n(this, a, b);
+          }),
+          (k.use = function () {
+            var a,
+              b = this.node.id;
+            return (
+              b || ((b = this.id), o(this.node, { id: b })),
+              (a =
+                "linearGradient" == this.type ||
+                "radialGradient" == this.type ||
+                "pattern" == this.type
+                  ? p(this.type, this.node.parentNode)
+                  : p("use", this.node.parentNode)),
+              o(a.node, { "xlink:href": "#" + b }),
+              (a.original = this),
+              a
+            );
+          }),
+          (k.clone = function () {
+            var a = s(this.node.cloneNode(!0));
+            return o(a.node, "id") && o(a.node, { id: a.id }), i(a), a.insertAfter(this), a;
+          }),
+          (k.toDefs = function () {
+            var a = q(this);
+            return a.appendChild(this.node), this;
+          }),
+          (k.pattern = k.toPattern =
+            function (a, b, c, d) {
+              var e = p("pattern", q(this));
+              return (
+                null == a && (a = this.getBBox()),
+                l(a, "object") && "x" in a && ((b = a.y), (c = a.width), (d = a.height), (a = a.x)),
+                o(e.node, {
+                  x: a,
+                  y: b,
+                  width: c,
+                  height: d,
+                  patternUnits: "userSpaceOnUse",
+                  id: e.id,
+                  viewBox: [a, b, c, d].join(" "),
+                }),
+                e.node.appendChild(this.node),
+                e
+              );
+            }),
+          (k.marker = function (a, b, c, d, e, f) {
+            var g = p("marker", q(this));
+            return (
+              null == a && (a = this.getBBox()),
+              l(a, "object") &&
+                "x" in a &&
+                ((b = a.y),
+                (c = a.width),
+                (d = a.height),
+                (e = a.refX || a.cx),
+                (f = a.refY || a.cy),
+                (a = a.x)),
+              o(g.node, {
+                viewBox: [a, b, c, d].join(" "),
+                markerWidth: c,
+                markerHeight: d,
+                orient: "auto",
+                refX: e || 0,
+                refY: f || 0,
+                id: g.id,
+              }),
+              g.node.appendChild(this.node),
+              g
+            );
+          });
+        var u = {};
+        (k.data = function (a, d) {
+          var e = (u[this.id] = u[this.id] || {});
+          if (0 == arguments.length) return b("snap.data.get." + this.id, this, e, null), e;
+          if (1 == arguments.length) {
+            if (c.is(a, "object")) {
+              for (var f in a) a[r](f) && this.data(f, a[f]);
+              return this;
+            }
+            return b("snap.data.get." + this.id, this, e[a], a), e[a];
+          }
+          return (e[a] = d), b("snap.data.set." + this.id, this, d, a), this;
+        }),
+          (k.removeData = function (a) {
+            return null == a ? (u[this.id] = {}) : u[this.id] && delete u[this.id][a], this;
+          }),
+          (k.outerSVG = k.toString = j(1)),
+          (k.innerSVG = j()),
+          (k.toDataURL = function () {
+            if (a && a.btoa) {
+              var b = this.getBBox(),
+                d = c.format(
+                  '<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="{width}" height="{height}" viewBox="{x} {y} {width} {height}">{contents}</svg>',
+                  {
+                    x: +b.x.toFixed(3),
+                    y: +b.y.toFixed(3),
+                    width: +b.width.toFixed(3),
+                    height: +b.height.toFixed(3),
+                    contents: this.outerSVG(),
+                  }
+                );
+              return "data:image/svg+xml;base64," + btoa(unescape(encodeURIComponent(d)));
+            }
+          }),
+          (g.prototype.select = k.select),
+          (g.prototype.selectAll = k.selectAll);
+      }),
+      d.plugin(function (a, d, e, f, g) {
+        function h(a, b, c) {
+          return function (d) {
+            var e = d.slice(a, b);
+            return 1 == e.length && (e = e[0]), c ? c(e) : e;
+          };
+        }
+        var i = d.prototype,
+          j = a.is,
+          k = String,
+          l = "hasOwnProperty",
+          m = function (a, b, d, e) {
+            "function" != typeof d || d.length || ((e = d), (d = c.linear)),
+              (this.attr = a),
+              (this.dur = b),
+              d && (this.easing = d),
+              e && (this.callback = e);
+          };
+        (a._.Animation = m),
+          (a.animation = function (a, b, c, d) {
+            return new m(a, b, c, d);
+          }),
+          (i.inAnim = function () {
+            var a = this,
+              b = [];
+            for (var c in a.anims)
+              a.anims[l](c) &&
+                !(function (a) {
+                  b.push({
+                    anim: new m(a._attrs, a.dur, a.easing, a._callback),
+                    mina: a,
+                    curStatus: a.status(),
+                    status: function (b) {
+                      return a.status(b);
+                    },
+                    stop: function () {
+                      a.stop();
+                    },
+                  });
+                })(a.anims[c]);
+            return b;
+          }),
+          (a.animate = function (a, d, e, f, g, h) {
+            "function" != typeof g || g.length || ((h = g), (g = c.linear));
+            var i = c.time(),
+              j = c(a, d, i, i + f, c.time, e, g);
+            return h && b.once("mina.finish." + j.id, h), j;
+          }),
+          (i.stop = function () {
+            for (var a = this.inAnim(), b = 0, c = a.length; c > b; b++) a[b].stop();
+            return this;
+          }),
+          (i.animate = function (a, d, e, f) {
+            "function" != typeof e || e.length || ((f = e), (e = c.linear)),
+              a instanceof m && ((f = a.callback), (e = a.easing), (d = a.dur), (a = a.attr));
+            var g,
+              i,
+              n,
+              o,
+              p = [],
+              q = [],
+              r = {},
+              s = this;
+            for (var t in a)
+              if (a[l](t)) {
+                s.equal
+                  ? ((o = s.equal(t, k(a[t]))), (g = o.from), (i = o.to), (n = o.f))
+                  : ((g = +s.attr(t)), (i = +a[t]));
+                var u = j(g, "array") ? g.length : 1;
+                (r[t] = h(p.length, p.length + u, n)), (p = p.concat(g)), (q = q.concat(i));
+              }
+            var v = c.time(),
+              w = c(
+                p,
+                q,
+                v,
+                v + d,
+                c.time,
+                function (a) {
+                  var b = {};
+                  for (var c in r) r[l](c) && (b[c] = r[c](a));
+                  s.attr(b);
+                },
+                e
+              );
+            return (
+              (s.anims[w.id] = w),
+              (w._attrs = a),
+              (w._callback = f),
+              b("snap.animcreated." + s.id, w),
+              b.once("mina.finish." + w.id, function () {
+                b.off("mina.*." + w.id), delete s.anims[w.id], f && f.call(s);
+              }),
+              b.once("mina.stop." + w.id, function () {
+                b.off("mina.*." + w.id), delete s.anims[w.id];
+              }),
+              s
+            );
+          });
+      }),
+      d.plugin(function (a, b, c, d, e) {
+        function f(a, b, c, d, e, f) {
+          return null == b && "[object SVGMatrix]" == g.call(a)
+            ? ((this.a = a.a),
+              (this.b = a.b),
+              (this.c = a.c),
+              (this.d = a.d),
+              (this.e = a.e),
+              void (this.f = a.f))
+            : void (null != a
+                ? ((this.a = +a),
+                  (this.b = +b),
+                  (this.c = +c),
+                  (this.d = +d),
+                  (this.e = +e),
+                  (this.f = +f))
+                : ((this.a = 1),
+                  (this.b = 0),
+                  (this.c = 0),
+                  (this.d = 1),
+                  (this.e = 0),
+                  (this.f = 0)));
+        }
+        var g = Object.prototype.toString,
+          h = String,
+          i = Math,
+          j = "";
+        !(function (b) {
+          function c(a) {
+            return a[0] * a[0] + a[1] * a[1];
+          }
+          function d(a) {
+            var b = i.sqrt(c(a));
+            a[0] && (a[0] /= b), a[1] && (a[1] /= b);
+          }
+          (b.add = function (a, b, c, d, e, g) {
+            if (a && a instanceof f) return this.add(a.a, a.b, a.c, a.d, a.e, a.f);
+            var h = a * this.a + b * this.c,
+              i = a * this.b + b * this.d;
+            return (
+              (this.e += e * this.a + g * this.c),
+              (this.f += e * this.b + g * this.d),
+              (this.c = c * this.a + d * this.c),
+              (this.d = c * this.b + d * this.d),
+              (this.a = h),
+              (this.b = i),
+              this
+            );
+          }),
+            (f.prototype.multLeft = function (a, b, c, d, e, g) {
+              if (a && a instanceof f) return this.multLeft(a.a, a.b, a.c, a.d, a.e, a.f);
+              var h = a * this.a + c * this.b,
+                i = a * this.c + c * this.d,
+                j = a * this.e + c * this.f + e;
+              return (
+                (this.b = b * this.a + d * this.b),
+                (this.d = b * this.c + d * this.d),
+                (this.f = b * this.e + d * this.f + g),
+                (this.a = h),
+                (this.c = i),
+                (this.e = j),
+                this
+              );
+            }),
+            (b.invert = function () {
+              var a = this,
+                b = a.a * a.d - a.b * a.c;
+              return new f(
+                a.d / b,
+                -a.b / b,
+                -a.c / b,
+                a.a / b,
+                (a.c * a.f - a.d * a.e) / b,
+                (a.b * a.e - a.a * a.f) / b
+              );
+            }),
+            (b.clone = function () {
+              return new f(this.a, this.b, this.c, this.d, this.e, this.f);
+            }),
+            (b.translate = function (a, b) {
+              return (this.e += a * this.a + b * this.c), (this.f += a * this.b + b * this.d), this;
+            }),
+            (b.scale = function (a, b, c, d) {
+              return (
+                null == b && (b = a),
+                (c || d) && this.translate(c, d),
+                (this.a *= a),
+                (this.b *= a),
+                (this.c *= b),
+                (this.d *= b),
+                (c || d) && this.translate(-c, -d),
+                this
+              );
+            }),
+            (b.rotate = function (b, c, d) {
+              (b = a.rad(b)), (c = c || 0), (d = d || 0);
+              var e = +i.cos(b).toFixed(9),
+                f = +i.sin(b).toFixed(9);
+              return this.add(e, f, -f, e, c, d), this.add(1, 0, 0, 1, -c, -d);
+            }),
+            (b.skewX = function (a) {
+              return this.skew(a, 0);
+            }),
+            (b.skewY = function (a) {
+              return this.skew(0, a);
+            }),
+            (b.skew = function (b, c) {
+              (b = b || 0), (c = c || 0), (b = a.rad(b)), (c = a.rad(c));
+              var d = i.tan(b).toFixed(9),
+                e = i.tan(c).toFixed(9);
+              return this.add(1, e, d, 1, 0, 0);
+            }),
+            (b.x = function (a, b) {
+              return a * this.a + b * this.c + this.e;
+            }),
+            (b.y = function (a, b) {
+              return a * this.b + b * this.d + this.f;
+            }),
+            (b.get = function (a) {
+              return +this[h.fromCharCode(97 + a)].toFixed(4);
+            }),
+            (b.toString = function () {
+              return (
+                "matrix(" +
+                [
+                  this.get(0),
+                  this.get(1),
+                  this.get(2),
+                  this.get(3),
+                  this.get(4),
+                  this.get(5),
+                ].join() +
+                ")"
+              );
+            }),
+            (b.offset = function () {
+              return [this.e.toFixed(4), this.f.toFixed(4)];
+            }),
+            (b.determinant = function () {
+              return this.a * this.d - this.b * this.c;
+            }),
+            (b.split = function () {
+              var b = {};
+              (b.dx = this.e), (b.dy = this.f);
+              var e = [
+                [this.a, this.b],
+                [this.c, this.d],
+              ];
+              (b.scalex = i.sqrt(c(e[0]))),
+                d(e[0]),
+                (b.shear = e[0][0] * e[1][0] + e[0][1] * e[1][1]),
+                (e[1] = [e[1][0] - e[0][0] * b.shear, e[1][1] - e[0][1] * b.shear]),
+                (b.scaley = i.sqrt(c(e[1]))),
+                d(e[1]),
+                (b.shear /= b.scaley),
+                this.determinant() < 0 && (b.scalex = -b.scalex);
+              var f = e[0][1],
+                g = e[1][1];
+              return (
+                0 > g
+                  ? ((b.rotate = a.deg(i.acos(g))), 0 > f && (b.rotate = 360 - b.rotate))
+                  : (b.rotate = a.deg(i.asin(f))),
+                (b.isSimple = !(
+                  +b.shear.toFixed(9) ||
+                  (b.scalex.toFixed(9) != b.scaley.toFixed(9) && b.rotate)
+                )),
+                (b.isSuperSimple =
+                  !+b.shear.toFixed(9) && b.scalex.toFixed(9) == b.scaley.toFixed(9) && !b.rotate),
+                (b.noRotation = !+b.shear.toFixed(9) && !b.rotate),
+                b
+              );
+            }),
+            (b.toTransformString = function (a) {
+              var b = a || this.split();
+              return +b.shear.toFixed(9)
+                ? "m" +
+                    [this.get(0), this.get(1), this.get(2), this.get(3), this.get(4), this.get(5)]
+                : ((b.scalex = +b.scalex.toFixed(4)),
+                  (b.scaley = +b.scaley.toFixed(4)),
+                  (b.rotate = +b.rotate.toFixed(4)),
+                  (b.dx || b.dy ? "t" + [+b.dx.toFixed(4), +b.dy.toFixed(4)] : j) +
+                    (b.rotate ? "r" + [+b.rotate.toFixed(4), 0, 0] : j) +
+                    (1 != b.scalex || 1 != b.scaley ? "s" + [b.scalex, b.scaley, 0, 0] : j));
+            });
+        })(f.prototype),
+          (a.Matrix = f),
+          (a.matrix = function (a, b, c, d, e, g) {
+            return new f(a, b, c, d, e, g);
+          });
+      }),
+      d.plugin(function (a, c, d, e, f) {
+        function g(d) {
+          return function (e) {
+            if (
+              (b.stop(),
+              e instanceof f &&
+                1 == e.node.childNodes.length &&
+                ("radialGradient" == e.node.firstChild.tagName ||
+                  "linearGradient" == e.node.firstChild.tagName ||
+                  "pattern" == e.node.firstChild.tagName) &&
+                ((e = e.node.firstChild), n(this).appendChild(e), (e = l(e))),
+              e instanceof c)
+            )
+              if ("radialGradient" == e.type || "linearGradient" == e.type || "pattern" == e.type) {
+                e.node.id || p(e.node, { id: e.id });
+                var g = q(e.node.id);
+              } else g = e.attr(d);
+            else if (((g = a.color(e)), g.error)) {
+              var h = a(n(this).ownerSVGElement).gradient(e);
+              h ? (h.node.id || p(h.node, { id: h.id }), (g = q(h.node.id))) : (g = e);
+            } else g = r(g);
+            var i = {};
+            (i[d] = g), p(this.node, i), (this.node.style[d] = t);
+          };
+        }
+        function h(a) {
+          b.stop(), a == +a && (a += "px"), (this.node.style.fontSize = a);
+        }
+        function i(a) {
+          for (var b = [], c = a.childNodes, d = 0, e = c.length; e > d; d++) {
+            var f = c[d];
+            3 == f.nodeType && b.push(f.nodeValue),
+              "tspan" == f.tagName &&
+                (1 == f.childNodes.length && 3 == f.firstChild.nodeType
+                  ? b.push(f.firstChild.nodeValue)
+                  : b.push(i(f)));
+          }
+          return b;
+        }
+        function j() {
+          return b.stop(), this.node.style.fontSize;
+        }
+        var k = a._.make,
+          l = a._.wrap,
+          m = a.is,
+          n = a._.getSomeDefs,
+          o = /^url\((['"]?)([^)]+)\1\)$/,
+          p = a._.$,
+          q = a.url,
+          r = String,
+          s = a._.separator,
+          t = "";
+        (a.deurl = function (a) {
+          var b = String(a).match(o);
+          return b ? b[2] : a;
+        }),
+          b.on("snap.util.attr.mask", function (a) {
+            if (a instanceof c || a instanceof f) {
+              if (
+                (b.stop(),
+                a instanceof f &&
+                  1 == a.node.childNodes.length &&
+                  ((a = a.node.firstChild), n(this).appendChild(a), (a = l(a))),
+                "mask" == a.type)
+              )
+                var d = a;
+              else (d = k("mask", n(this))), d.node.appendChild(a.node);
+              !d.node.id && p(d.node, { id: d.id }), p(this.node, { mask: q(d.id) });
+            }
+          }),
+          (function (a) {
+            b.on("snap.util.attr.clip", a),
+              b.on("snap.util.attr.clip-path", a),
+              b.on("snap.util.attr.clipPath", a);
+          })(function (a) {
+            if (a instanceof c || a instanceof f) {
+              b.stop();
+              for (var d, e = a.node; e; ) {
+                if ("clipPath" === e.nodeName) {
+                  d = new c(e);
+                  break;
+                }
+                if ("svg" === e.nodeName) {
+                  d = void 0;
+                  break;
+                }
+                e = e.parentNode;
+              }
+              d ||
+                ((d = k("clipPath", n(this))),
+                d.node.appendChild(a.node),
+                !d.node.id && p(d.node, { id: d.id })),
+                p(this.node, { "clip-path": q(d.node.id || d.id) });
+            }
+          }),
+          b.on("snap.util.attr.fill", g("fill")),
+          b.on("snap.util.attr.stroke", g("stroke"));
+        var u = /^([lr])(?:\(([^)]*)\))?(.*)$/i;
+        b.on("snap.util.grad.parse", function (a) {
+          function b(a, b) {
+            for (var c = (b - h) / (a - i), d = i; a > d; d++)
+              f[d].offset = +(+h + c * (d - i)).toFixed(2);
+            (i = a), (h = b);
+          }
+          a = r(a);
+          var c = a.match(u);
+          if (!c) return null;
+          var d = c[1],
+            e = c[2],
+            f = c[3];
+          (e = e.split(/\s*,\s*/).map(function (a) {
+            return +a == a ? +a : a;
+          })),
+            1 == e.length && 0 == e[0] && (e = []),
+            (f = f.split("-")),
+            (f = f.map(function (a) {
+              a = a.split(":");
+              var b = { color: a[0] };
+              return a[1] && (b.offset = parseFloat(a[1])), b;
+            }));
+          var g = f.length,
+            h = 0,
+            i = 0;
+          g--;
+          for (var j = 0; g > j; j++) "offset" in f[j] && b(j, f[j].offset);
+          return (
+            (f[g].offset = f[g].offset || 100), b(g, f[g].offset), { type: d, params: e, stops: f }
+          );
+        }),
+          b.on("snap.util.attr.d", function (c) {
+            b.stop(),
+              m(c, "array") && m(c[0], "array") && (c = a.path.toString.call(c)),
+              (c = r(c)),
+              c.match(/[ruo]/i) && (c = a.path.toAbsolute(c)),
+              p(this.node, { d: c });
+          })(-1),
+          b.on("snap.util.attr.#text", function (a) {
+            b.stop(), (a = r(a));
+            for (var c = e.doc.createTextNode(a); this.node.firstChild; )
+              this.node.removeChild(this.node.firstChild);
+            this.node.appendChild(c);
+          })(-1),
+          b.on("snap.util.attr.path", function (a) {
+            b.stop(), this.attr({ d: a });
+          })(-1),
+          b.on("snap.util.attr.class", function (a) {
+            b.stop(), (this.node.className.baseVal = a);
+          })(-1),
+          b.on("snap.util.attr.viewBox", function (a) {
+            var c;
+            (c =
+              m(a, "object") && "x" in a
+                ? [a.x, a.y, a.width, a.height].join(" ")
+                : m(a, "array")
+                ? a.join(" ")
+                : a),
+              p(this.node, { viewBox: c }),
+              b.stop();
+          })(-1),
+          b.on("snap.util.attr.transform", function (a) {
+            this.transform(a), b.stop();
+          })(-1),
+          b.on("snap.util.attr.r", function (a) {
+            "rect" == this.type && (b.stop(), p(this.node, { rx: a, ry: a }));
+          })(-1),
+          b.on("snap.util.attr.textpath", function (a) {
+            if ((b.stop(), "text" == this.type)) {
+              var d, e, f;
+              if (!a && this.textPath) {
+                for (e = this.textPath; e.node.firstChild; )
+                  this.node.appendChild(e.node.firstChild);
+                return e.remove(), void delete this.textPath;
+              }
+              if (m(a, "string")) {
+                var g = n(this),
+                  h = l(g.parentNode).path(a);
+                g.appendChild(h.node), (d = h.id), h.attr({ id: d });
+              } else
+                (a = l(a)),
+                  a instanceof c && ((d = a.attr("id")), d || ((d = a.id), a.attr({ id: d })));
+              if (d)
+                if (((e = this.textPath), (f = this.node), e)) e.attr({ "xlink:href": "#" + d });
+                else {
+                  for (e = p("textPath", { "xlink:href": "#" + d }); f.firstChild; )
+                    e.appendChild(f.firstChild);
+                  f.appendChild(e), (this.textPath = l(e));
+                }
+            }
+          })(-1),
+          b.on("snap.util.attr.text", function (a) {
+            if ("text" == this.type) {
+              for (
+                var c = this.node,
+                  d = function (a) {
+                    var b = p("tspan");
+                    if (m(a, "array")) for (var c = 0; c < a.length; c++) b.appendChild(d(a[c]));
+                    else b.appendChild(e.doc.createTextNode(a));
+                    return b.normalize && b.normalize(), b;
+                  };
+                c.firstChild;
+
+              )
+                c.removeChild(c.firstChild);
+              for (var f = d(a); f.firstChild; ) c.appendChild(f.firstChild);
+            }
+            b.stop();
+          })(-1),
+          b.on("snap.util.attr.fontSize", h)(-1),
+          b.on("snap.util.attr.font-size", h)(-1),
+          b.on("snap.util.getattr.transform", function () {
+            return b.stop(), this.transform();
+          })(-1),
+          b.on("snap.util.getattr.textpath", function () {
+            return b.stop(), this.textPath;
+          })(-1),
+          (function () {
+            function c(c) {
+              return function () {
+                b.stop();
+                var d = e.doc.defaultView
+                  .getComputedStyle(this.node, null)
+                  .getPropertyValue("marker-" + c);
+                return "none" == d ? d : a(e.doc.getElementById(d.match(o)[1]));
+              };
+            }
+            function d(a) {
+              return function (c) {
+                b.stop();
+                var d = "marker" + a.charAt(0).toUpperCase() + a.substring(1);
+                if ("" == c || !c) return void (this.node.style[d] = "none");
+                if ("marker" == c.type) {
+                  var e = c.node.id;
+                  return e || p(c.node, { id: c.id }), void (this.node.style[d] = q(e));
+                }
+              };
+            }
+            b.on("snap.util.getattr.marker-end", c("end"))(-1),
+              b.on("snap.util.getattr.markerEnd", c("end"))(-1),
+              b.on("snap.util.getattr.marker-start", c("start"))(-1),
+              b.on("snap.util.getattr.markerStart", c("start"))(-1),
+              b.on("snap.util.getattr.marker-mid", c("mid"))(-1),
+              b.on("snap.util.getattr.markerMid", c("mid"))(-1),
+              b.on("snap.util.attr.marker-end", d("end"))(-1),
+              b.on("snap.util.attr.markerEnd", d("end"))(-1),
+              b.on("snap.util.attr.marker-start", d("start"))(-1),
+              b.on("snap.util.attr.markerStart", d("start"))(-1),
+              b.on("snap.util.attr.marker-mid", d("mid"))(-1),
+              b.on("snap.util.attr.markerMid", d("mid"))(-1);
+          })(),
+          b.on("snap.util.getattr.r", function () {
+            return "rect" == this.type && p(this.node, "rx") == p(this.node, "ry")
+              ? (b.stop(), p(this.node, "rx"))
+              : void 0;
+          })(-1),
+          b.on("snap.util.getattr.text", function () {
+            if ("text" == this.type || "tspan" == this.type) {
+              b.stop();
+              var a = i(this.node);
+              return 1 == a.length ? a[0] : a;
+            }
+          })(-1),
+          b.on("snap.util.getattr.#text", function () {
+            return this.node.textContent;
+          })(-1),
+          b.on("snap.util.getattr.fill", function (c) {
+            if (!c) {
+              b.stop();
+              var d = b("snap.util.getattr.fill", this, !0).firstDefined();
+              return a(a.deurl(d)) || d;
+            }
+          })(-1),
+          b.on("snap.util.getattr.stroke", function (c) {
+            if (!c) {
+              b.stop();
+              var d = b("snap.util.getattr.stroke", this, !0).firstDefined();
+              return a(a.deurl(d)) || d;
+            }
+          })(-1),
+          b.on("snap.util.getattr.viewBox", function () {
+            b.stop();
+            var c = p(this.node, "viewBox");
+            return c ? ((c = c.split(s)), a._.box(+c[0], +c[1], +c[2], +c[3])) : void 0;
+          })(-1),
+          b.on("snap.util.getattr.points", function () {
+            var a = p(this.node, "points");
+            return b.stop(), a ? a.split(s) : void 0;
+          })(-1),
+          b.on("snap.util.getattr.path", function () {
+            var a = p(this.node, "d");
+            return b.stop(), a;
+          })(-1),
+          b.on("snap.util.getattr.class", function () {
+            return this.node.className.baseVal;
+          })(-1),
+          b.on("snap.util.getattr.fontSize", j)(-1),
+          b.on("snap.util.getattr.font-size", j)(-1);
+      }),
+      d.plugin(function (a, b, c, d, e) {
+        var f = /\S+/g,
+          g = String,
+          h = b.prototype;
+        (h.addClass = function (a) {
+          var b,
+            c,
+            d,
+            e,
+            h = g(a || "").match(f) || [],
+            i = this.node,
+            j = i.className.baseVal,
+            k = j.match(f) || [];
+          if (h.length) {
+            for (b = 0; (d = h[b++]); ) (c = k.indexOf(d)), ~c || k.push(d);
+            (e = k.join(" ")), j != e && (i.className.baseVal = e);
+          }
+          return this;
+        }),
+          (h.removeClass = function (a) {
+            var b,
+              c,
+              d,
+              e,
+              h = g(a || "").match(f) || [],
+              i = this.node,
+              j = i.className.baseVal,
+              k = j.match(f) || [];
+            if (k.length) {
+              for (b = 0; (d = h[b++]); ) (c = k.indexOf(d)), ~c && k.splice(c, 1);
+              (e = k.join(" ")), j != e && (i.className.baseVal = e);
+            }
+            return this;
+          }),
+          (h.hasClass = function (a) {
+            var b = this.node,
+              c = b.className.baseVal,
+              d = c.match(f) || [];
+            return !!~d.indexOf(a);
+          }),
+          (h.toggleClass = function (a, b) {
+            if (null != b) return b ? this.addClass(a) : this.removeClass(a);
+            var c,
+              d,
+              e,
+              g,
+              h = (a || "").match(f) || [],
+              i = this.node,
+              j = i.className.baseVal,
+              k = j.match(f) || [];
+            for (c = 0; (e = h[c++]); ) (d = k.indexOf(e)), ~d ? k.splice(d, 1) : k.push(e);
+            return (g = k.join(" ")), j != g && (i.className.baseVal = g), this;
+          });
+      }),
+      d.plugin(function (a, c, d, e, f) {
+        function g(a) {
+          return a;
+        }
+        function h(a) {
+          return function (b) {
+            return +b.toFixed(3) + a;
+          };
+        }
+        var i = {
+            "+": function (a, b) {
+              return a + b;
+            },
+            "-": function (a, b) {
+              return a - b;
+            },
+            "/": function (a, b) {
+              return a / b;
+            },
+            "*": function (a, b) {
+              return a * b;
+            },
+          },
+          j = String,
+          k = /[a-z]+$/i,
+          l = /^\s*([+\-\/*])\s*=\s*([\d.eE+\-]+)\s*([^\d\s]+)?\s*$/;
+        b.on("snap.util.attr", function (a) {
+          var c = j(a).match(l);
+          if (c) {
+            var d = b.nt(),
+              e = d.substring(d.lastIndexOf(".") + 1),
+              f = this.attr(e),
+              g = {};
+            b.stop();
+            var h = c[3] || "",
+              m = f.match(k),
+              n = i[c[1]];
+            if (
+              (m && m == h
+                ? (a = n(parseFloat(f), +c[2]))
+                : ((f = this.asPX(e)), (a = n(this.asPX(e), this.asPX(e, c[2] + h)))),
+              isNaN(f) || isNaN(a))
+            )
+              return;
+            (g[e] = a), this.attr(g);
+          }
+        })(-10),
+          b.on("snap.util.equal", function (a, c) {
+            var d = j(this.attr(a) || ""),
+              e = j(c).match(l);
+            if (e) {
+              b.stop();
+              var f = e[3] || "",
+                m = d.match(k),
+                n = i[e[1]];
+              return m && m == f
+                ? { from: parseFloat(d), to: n(parseFloat(d), +e[2]), f: h(m) }
+                : ((d = this.asPX(a)), { from: d, to: n(d, this.asPX(a, e[2] + f)), f: g });
+            }
+          })(-10);
+      }),
+      d.plugin(function (c, d, e, f, g) {
+        var h = e.prototype,
+          i = c.is;
+        (h.rect = function (a, b, c, d, e, f) {
+          var g;
+          return (
+            null == f && (f = e),
+            i(a, "object") && "[object Object]" == a
+              ? (g = a)
+              : null != a &&
+                ((g = { x: a, y: b, width: c, height: d }), null != e && ((g.rx = e), (g.ry = f))),
+            this.el("rect", g)
+          );
+        }),
+          (h.circle = function (a, b, c) {
+            var d;
+            return (
+              i(a, "object") && "[object Object]" == a
+                ? (d = a)
+                : null != a && (d = { cx: a, cy: b, r: c }),
+              this.el("circle", d)
+            );
+          });
+        var j = (function () {
+          function a() {
+            this.parentNode.removeChild(this);
+          }
+          return function (b, c) {
+            var d = f.doc.createElement("img"),
+              e = f.doc.body;
+            (d.style.cssText = "position:absolute;left:-9999em;top:-9999em"),
+              (d.onload = function () {
+                c.call(d), (d.onload = d.onerror = null), e.removeChild(d);
+              }),
+              (d.onerror = a),
+              e.appendChild(d),
+              (d.src = b);
+          };
+        })();
+        (h.image = function (a, b, d, e, f) {
+          var g = this.el("image");
+          if (i(a, "object") && "src" in a) g.attr(a);
+          else if (null != a) {
+            var h = { "xlink:href": a, preserveAspectRatio: "none" };
+            null != b && null != d && ((h.x = b), (h.y = d)),
+              null != e && null != f
+                ? ((h.width = e), (h.height = f))
+                : j(a, function () {
+                    c._.$(g.node, { width: this.offsetWidth, height: this.offsetHeight });
+                  }),
+              c._.$(g.node, h);
+          }
+          return g;
+        }),
+          (h.ellipse = function (a, b, c, d) {
+            var e;
+            return (
+              i(a, "object") && "[object Object]" == a
+                ? (e = a)
+                : null != a && (e = { cx: a, cy: b, rx: c, ry: d }),
+              this.el("ellipse", e)
+            );
+          }),
+          (h.path = function (a) {
+            var b;
+            return (
+              i(a, "object") && !i(a, "array") ? (b = a) : a && (b = { d: a }), this.el("path", b)
+            );
+          }),
+          (h.group = h.g =
+            function (a) {
+              var b = this.el("g");
+              return (
+                1 == arguments.length && a && !a.type
+                  ? b.attr(a)
+                  : arguments.length && b.add(Array.prototype.slice.call(arguments, 0)),
+                b
+              );
+            }),
+          (h.svg = function (a, b, c, d, e, f, g, h) {
+            var j = {};
+            return (
+              i(a, "object") && null == b
+                ? (j = a)
+                : (null != a && (j.x = a),
+                  null != b && (j.y = b),
+                  null != c && (j.width = c),
+                  null != d && (j.height = d),
+                  null != e && null != f && null != g && null != h && (j.viewBox = [e, f, g, h])),
+              this.el("svg", j)
+            );
+          }),
+          (h.mask = function (a) {
+            var b = this.el("mask");
+            return (
+              1 == arguments.length && a && !a.type
+                ? b.attr(a)
+                : arguments.length && b.add(Array.prototype.slice.call(arguments, 0)),
+              b
+            );
+          }),
+          (h.ptrn = function (a, b, c, d, e, f, g, h) {
+            if (i(a, "object")) var j = a;
+            else
+              (j = { patternUnits: "userSpaceOnUse" }),
+                a && (j.x = a),
+                b && (j.y = b),
+                null != c && (j.width = c),
+                null != d && (j.height = d),
+                null != e && null != f && null != g && null != h
+                  ? (j.viewBox = [e, f, g, h])
+                  : (j.viewBox = [a || 0, b || 0, c || 0, d || 0]);
+            return this.el("pattern", j);
+          }),
+          (h.use = function (a) {
+            return null != a
+              ? (a instanceof d && (a.attr("id") || a.attr({ id: c._.id(a) }), (a = a.attr("id"))),
+                "#" == String(a).charAt() && (a = a.substring(1)),
+                this.el("use", { "xlink:href": "#" + a }))
+              : d.prototype.use.call(this);
+          }),
+          (h.symbol = function (a, b, c, d) {
+            var e = {};
+            return (
+              null != a && null != b && null != c && null != d && (e.viewBox = [a, b, c, d]),
+              this.el("symbol", e)
+            );
+          }),
+          (h.text = function (a, b, c) {
+            var d = {};
+            return (
+              i(a, "object") ? (d = a) : null != a && (d = { x: a, y: b, text: c || "" }),
+              this.el("text", d)
+            );
+          }),
+          (h.line = function (a, b, c, d) {
+            var e = {};
+            return (
+              i(a, "object") ? (e = a) : null != a && (e = { x1: a, x2: c, y1: b, y2: d }),
+              this.el("line", e)
+            );
+          }),
+          (h.polyline = function (a) {
+            arguments.length > 1 && (a = Array.prototype.slice.call(arguments, 0));
+            var b = {};
+            return (
+              i(a, "object") && !i(a, "array") ? (b = a) : null != a && (b = { points: a }),
+              this.el("polyline", b)
+            );
+          }),
+          (h.polygon = function (a) {
+            arguments.length > 1 && (a = Array.prototype.slice.call(arguments, 0));
+            var b = {};
+            return (
+              i(a, "object") && !i(a, "array") ? (b = a) : null != a && (b = { points: a }),
+              this.el("polygon", b)
+            );
+          }),
+          (function () {
+            function d() {
+              return this.selectAll("stop");
+            }
+            function e(a, b) {
+              var d = l("stop"),
+                e = { offset: +b + "%" };
+              (a = c.color(a)),
+                (e["stop-color"] = a.hex),
+                a.opacity < 1 && (e["stop-opacity"] = a.opacity),
+                l(d, e);
+              for (var f, g = this.stops(), h = 0; h < g.length; h++) {
+                var i = parseFloat(g[h].attr("offset"));
+                if (i > b) {
+                  this.node.insertBefore(d, g[h].node), (f = !0);
+                  break;
+                }
+              }
+              return f || this.node.appendChild(d), this;
+            }
+            function f() {
+              if ("linearGradient" == this.type) {
+                var a = l(this.node, "x1") || 0,
+                  b = l(this.node, "x2") || 1,
+                  d = l(this.node, "y1") || 0,
+                  e = l(this.node, "y2") || 0;
+                return c._.box(a, d, math.abs(b - a), math.abs(e - d));
+              }
+              var f = this.node.cx || 0.5,
+                g = this.node.cy || 0.5,
+                h = this.node.r || 0;
+              return c._.box(f - h, g - h, 2 * h, 2 * h);
+            }
+            function g(a) {
+              var d = a,
+                e = this.stops();
+              if (
+                ("string" == typeof a &&
+                  (d = b("snap.util.grad.parse", null, "l(0,0,0,1)" + a).firstDefined().stops),
+                c.is(d, "array"))
+              ) {
+                for (var f = 0; f < e.length; f++)
+                  if (d[f]) {
+                    var g = c.color(d[f].color),
+                      h = { offset: d[f].offset + "%" };
+                    (h["stop-color"] = g.hex),
+                      g.opacity < 1 && (h["stop-opacity"] = g.opacity),
+                      e[f].attr(h);
+                  } else e[f].remove();
+                for (f = e.length; f < d.length; f++) this.addStop(d[f].color, d[f].offset);
+                return this;
+              }
+            }
+            function i(a, c) {
+              var d,
+                e = b("snap.util.grad.parse", null, c).firstDefined();
+              if (!e) return null;
+              e.params.unshift(a),
+                (d = "l" == e.type.toLowerCase() ? j.apply(0, e.params) : k.apply(0, e.params)),
+                e.type != e.type.toLowerCase() && l(d.node, { gradientUnits: "userSpaceOnUse" });
+              for (var f = e.stops, g = f.length, h = 0; g > h; h++) {
+                var i = f[h];
+                d.addStop(i.color, i.offset);
+              }
+              return d;
+            }
+            function j(a, b, h, i, j) {
+              var k = c._.make("linearGradient", a);
+              return (
+                (k.stops = d),
+                (k.addStop = e),
+                (k.getBBox = f),
+                (k.setStops = g),
+                null != b && l(k.node, { x1: b, y1: h, x2: i, y2: j }),
+                k
+              );
+            }
+            function k(a, b, g, h, i, j) {
+              var k = c._.make("radialGradient", a);
+              return (
+                (k.stops = d),
+                (k.addStop = e),
+                (k.getBBox = f),
+                null != b && l(k.node, { cx: b, cy: g, r: h }),
+                null != i && null != j && l(k.node, { fx: i, fy: j }),
+                k
+              );
+            }
+            var l = c._.$;
+            (h.gradient = function (a) {
+              return i(this.defs, a);
+            }),
+              (h.gradientLinear = function (a, b, c, d) {
+                return j(this.defs, a, b, c, d);
+              }),
+              (h.gradientRadial = function (a, b, c, d, e) {
+                return k(this.defs, a, b, c, d, e);
+              }),
+              (h.toString = function () {
+                var a,
+                  b = this.node.ownerDocument,
+                  d = b.createDocumentFragment(),
+                  e = b.createElement("div"),
+                  f = this.node.cloneNode(!0);
+                return (
+                  d.appendChild(e),
+                  e.appendChild(f),
+                  c._.$(f, { xmlns: "http://www.w3.org/2000/svg" }),
+                  (a = e.innerHTML),
+                  d.removeChild(d.firstChild),
+                  a
+                );
+              }),
+              (h.toDataURL = function () {
+                return a && a.btoa
+                  ? "data:image/svg+xml;base64," + btoa(unescape(encodeURIComponent(this)))
+                  : void 0;
+              }),
+              (h.clear = function () {
+                for (var a, b = this.node.firstChild; b; )
+                  (a = b.nextSibling),
+                    "defs" != b.tagName ? b.parentNode.removeChild(b) : h.clear.call({ node: b }),
+                    (b = a);
+              });
+          })();
+      }),
+      d.plugin(function (a, b, c, d) {
+        function e(a) {
+          var b = (e.ps = e.ps || {});
+          return (
+            b[a] ? (b[a].sleep = 100) : (b[a] = { sleep: 100 }),
+            setTimeout(function () {
+              for (var c in b) b[M](c) && c != a && (b[c].sleep--, !b[c].sleep && delete b[c]);
+            }),
+            b[a]
+          );
+        }
+        function f(a, b, c, d) {
+          return (
+            null == a && (a = b = c = d = 0),
+            null == b && ((b = a.y), (c = a.width), (d = a.height), (a = a.x)),
+            {
+              x: a,
+              y: b,
+              width: c,
+              w: c,
+              height: d,
+              h: d,
+              x2: a + c,
+              y2: b + d,
+              cx: a + c / 2,
+              cy: b + d / 2,
+              r1: P.min(c, d) / 2,
+              r2: P.max(c, d) / 2,
+              r0: P.sqrt(c * c + d * d) / 2,
+              path: y(a, b, c, d),
+              vb: [a, b, c, d].join(" "),
+            }
+          );
+        }
+        function g() {
+          return this.join(",").replace(N, "$1");
+        }
+        function h(a) {
+          var b = L(a);
+          return (b.toString = g), b;
+        }
+        function i(a, b, c, d, e, f, g, h, i) {
+          return null == i
+            ? p(a, b, c, d, e, f, g, h)
+            : k(a, b, c, d, e, f, g, h, q(a, b, c, d, e, f, g, h, i));
+        }
+        function j(c, d) {
+          function e(a) {
+            return +(+a).toFixed(3);
+          }
+          return a._.cacher(
+            function (a, f, g) {
+              a instanceof b && (a = a.attr("d")), (a = G(a));
+              for (var h, j, l, m, n, o = "", p = {}, q = 0, r = 0, s = a.length; s > r; r++) {
+                if (((l = a[r]), "M" == l[0])) (h = +l[1]), (j = +l[2]);
+                else {
+                  if (((m = i(h, j, l[1], l[2], l[3], l[4], l[5], l[6])), q + m > f)) {
+                    if (d && !p.start) {
+                      if (
+                        ((n = i(h, j, l[1], l[2], l[3], l[4], l[5], l[6], f - q)),
+                        (o += [
+                          "C" + e(n.start.x),
+                          e(n.start.y),
+                          e(n.m.x),
+                          e(n.m.y),
+                          e(n.x),
+                          e(n.y),
+                        ]),
+                        g)
+                      )
+                        return o;
+                      (p.start = o),
+                        (o = [
+                          "M" + e(n.x),
+                          e(n.y) + "C" + e(n.n.x),
+                          e(n.n.y),
+                          e(n.end.x),
+                          e(n.end.y),
+                          e(l[5]),
+                          e(l[6]),
+                        ].join()),
+                        (q += m),
+                        (h = +l[5]),
+                        (j = +l[6]);
+                      continue;
+                    }
+                    if (!c && !d) return (n = i(h, j, l[1], l[2], l[3], l[4], l[5], l[6], f - q));
+                  }
+                  (q += m), (h = +l[5]), (j = +l[6]);
+                }
+                o += l.shift() + l;
+              }
+              return (
+                (p.end = o), (n = c ? q : d ? p : k(h, j, l[0], l[1], l[2], l[3], l[4], l[5], 1))
+              );
+            },
+            null,
+            a._.clone
+          );
+        }
+        function k(a, b, c, d, e, f, g, h, i) {
+          var j = 1 - i,
+            k = T(j, 3),
+            l = T(j, 2),
+            m = i * i,
+            n = m * i,
+            o = k * a + 3 * l * i * c + 3 * j * i * i * e + n * g,
+            p = k * b + 3 * l * i * d + 3 * j * i * i * f + n * h,
+            q = a + 2 * i * (c - a) + m * (e - 2 * c + a),
+            r = b + 2 * i * (d - b) + m * (f - 2 * d + b),
+            s = c + 2 * i * (e - c) + m * (g - 2 * e + c),
+            t = d + 2 * i * (f - d) + m * (h - 2 * f + d),
+            u = j * a + i * c,
+            v = j * b + i * d,
+            w = j * e + i * g,
+            x = j * f + i * h,
+            y = 90 - (180 * P.atan2(q - s, r - t)) / Q;
+          return {
+            x: o,
+            y: p,
+            m: { x: q, y: r },
+            n: { x: s, y: t },
+            start: { x: u, y: v },
+            end: { x: w, y: x },
+            alpha: y,
+          };
+        }
+        function l(b, c, d, e, g, h, i, j) {
+          a.is(b, "array") || (b = [b, c, d, e, g, h, i, j]);
+          var k = F.apply(null, b);
+          return f(k.min.x, k.min.y, k.max.x - k.min.x, k.max.y - k.min.y);
+        }
+        function m(a, b, c) {
+          return b >= a.x && b <= a.x + a.width && c >= a.y && c <= a.y + a.height;
+        }
+        function n(a, b) {
+          return (
+            (a = f(a)),
+            (b = f(b)),
+            m(b, a.x, a.y) ||
+              m(b, a.x2, a.y) ||
+              m(b, a.x, a.y2) ||
+              m(b, a.x2, a.y2) ||
+              m(a, b.x, b.y) ||
+              m(a, b.x2, b.y) ||
+              m(a, b.x, b.y2) ||
+              m(a, b.x2, b.y2) ||
+              (((a.x < b.x2 && a.x > b.x) || (b.x < a.x2 && b.x > a.x)) &&
+                ((a.y < b.y2 && a.y > b.y) || (b.y < a.y2 && b.y > a.y)))
+          );
+        }
+        function o(a, b, c, d, e) {
+          var f = -3 * b + 9 * c - 9 * d + 3 * e,
+            g = a * f + 6 * b - 12 * c + 6 * d;
+          return a * g - 3 * b + 3 * c;
+        }
+        function p(a, b, c, d, e, f, g, h, i) {
+          null == i && (i = 1), (i = i > 1 ? 1 : 0 > i ? 0 : i);
+          for (
+            var j = i / 2,
+              k = 12,
+              l = [
+                -0.1252, 0.1252, -0.3678, 0.3678, -0.5873, 0.5873, -0.7699, 0.7699, -0.9041, 0.9041,
+                -0.9816, 0.9816,
+              ],
+              m = [
+                0.2491, 0.2491, 0.2335, 0.2335, 0.2032, 0.2032, 0.1601, 0.1601, 0.1069, 0.1069,
+                0.0472, 0.0472,
+              ],
+              n = 0,
+              p = 0;
+            k > p;
+            p++
+          ) {
+            var q = j * l[p] + j,
+              r = o(q, a, c, e, g),
+              s = o(q, b, d, f, h),
+              t = r * r + s * s;
+            n += m[p] * P.sqrt(t);
+          }
+          return j * n;
+        }
+        function q(a, b, c, d, e, f, g, h, i) {
+          if (!(0 > i || p(a, b, c, d, e, f, g, h) < i)) {
+            var j,
+              k = 1,
+              l = k / 2,
+              m = k - l,
+              n = 0.01;
+            for (j = p(a, b, c, d, e, f, g, h, m); U(j - i) > n; )
+              (l /= 2), (m += (i > j ? 1 : -1) * l), (j = p(a, b, c, d, e, f, g, h, m));
+            return m;
+          }
+        }
+        function r(a, b, c, d, e, f, g, h) {
+          if (!(S(a, c) < R(e, g) || R(a, c) > S(e, g) || S(b, d) < R(f, h) || R(b, d) > S(f, h))) {
+            var i = (a * d - b * c) * (e - g) - (a - c) * (e * h - f * g),
+              j = (a * d - b * c) * (f - h) - (b - d) * (e * h - f * g),
+              k = (a - c) * (f - h) - (b - d) * (e - g);
+            if (k) {
+              var l = i / k,
+                m = j / k,
+                n = +l.toFixed(2),
+                o = +m.toFixed(2);
+              if (
+                !(
+                  n < +R(a, c).toFixed(2) ||
+                  n > +S(a, c).toFixed(2) ||
+                  n < +R(e, g).toFixed(2) ||
+                  n > +S(e, g).toFixed(2) ||
+                  o < +R(b, d).toFixed(2) ||
+                  o > +S(b, d).toFixed(2) ||
+                  o < +R(f, h).toFixed(2) ||
+                  o > +S(f, h).toFixed(2)
+                )
+              )
+                return { x: l, y: m };
+            }
+          }
+        }
+        function s(a, b, c) {
+          var d = l(a),
+            e = l(b);
+          if (!n(d, e)) return c ? 0 : [];
+          for (
+            var f = p.apply(0, a),
+              g = p.apply(0, b),
+              h = ~~(f / 8),
+              i = ~~(g / 8),
+              j = [],
+              m = [],
+              o = {},
+              q = c ? 0 : [],
+              s = 0;
+            h + 1 > s;
+            s++
+          ) {
+            var t = k.apply(0, a.concat(s / h));
+            j.push({ x: t.x, y: t.y, t: s / h });
+          }
+          for (s = 0; i + 1 > s; s++)
+            (t = k.apply(0, b.concat(s / i))), m.push({ x: t.x, y: t.y, t: s / i });
+          for (s = 0; h > s; s++)
+            for (var u = 0; i > u; u++) {
+              var v = j[s],
+                w = j[s + 1],
+                x = m[u],
+                y = m[u + 1],
+                z = U(w.x - v.x) < 0.001 ? "y" : "x",
+                A = U(y.x - x.x) < 0.001 ? "y" : "x",
+                B = r(v.x, v.y, w.x, w.y, x.x, x.y, y.x, y.y);
+              if (B) {
+                if (o[B.x.toFixed(4)] == B.y.toFixed(4)) continue;
+                o[B.x.toFixed(4)] = B.y.toFixed(4);
+                var C = v.t + U((B[z] - v[z]) / (w[z] - v[z])) * (w.t - v.t),
+                  D = x.t + U((B[A] - x[A]) / (y[A] - x[A])) * (y.t - x.t);
+                C >= 0 &&
+                  1 >= C &&
+                  D >= 0 &&
+                  1 >= D &&
+                  (c ? q++ : q.push({ x: B.x, y: B.y, t1: C, t2: D }));
+              }
+            }
+          return q;
+        }
+        function t(a, b) {
+          return v(a, b);
+        }
+        function u(a, b) {
+          return v(a, b, 1);
+        }
+        function v(a, b, c) {
+          (a = G(a)), (b = G(b));
+          for (var d, e, f, g, h, i, j, k, l, m, n = c ? 0 : [], o = 0, p = a.length; p > o; o++) {
+            var q = a[o];
+            if ("M" == q[0]) (d = h = q[1]), (e = i = q[2]);
+            else {
+              "C" == q[0]
+                ? ((l = [d, e].concat(q.slice(1))), (d = l[6]), (e = l[7]))
+                : ((l = [d, e, d, e, h, i, h, i]), (d = h), (e = i));
+              for (var r = 0, t = b.length; t > r; r++) {
+                var u = b[r];
+                if ("M" == u[0]) (f = j = u[1]), (g = k = u[2]);
+                else {
+                  "C" == u[0]
+                    ? ((m = [f, g].concat(u.slice(1))), (f = m[6]), (g = m[7]))
+                    : ((m = [f, g, f, g, j, k, j, k]), (f = j), (g = k));
+                  var v = s(l, m, c);
+                  if (c) n += v;
+                  else {
+                    for (var w = 0, x = v.length; x > w; w++)
+                      (v[w].segment1 = o), (v[w].segment2 = r), (v[w].bez1 = l), (v[w].bez2 = m);
+                    n = n.concat(v);
+                  }
+                }
+              }
+            }
+          }
+          return n;
+        }
+        function w(a, b, c) {
+          var d = x(a);
+          return (
+            m(d, b, c) &&
+            v(
+              a,
+              [
+                ["M", b, c],
+                ["H", d.x2 + 10],
+              ],
+              1
+            ) %
+              2 ==
+              1
+          );
+        }
+        function x(a) {
+          var b = e(a);
+          if (b.bbox) return L(b.bbox);
+          if (!a) return f();
+          a = G(a);
+          for (var c, d = 0, g = 0, h = [], i = [], j = 0, k = a.length; k > j; j++)
+            if (((c = a[j]), "M" == c[0])) (d = c[1]), (g = c[2]), h.push(d), i.push(g);
+            else {
+              var l = F(d, g, c[1], c[2], c[3], c[4], c[5], c[6]);
+              (h = h.concat(l.min.x, l.max.x)),
+                (i = i.concat(l.min.y, l.max.y)),
+                (d = c[5]),
+                (g = c[6]);
+            }
+          var m = R.apply(0, h),
+            n = R.apply(0, i),
+            o = S.apply(0, h),
+            p = S.apply(0, i),
+            q = f(m, n, o - m, p - n);
+          return (b.bbox = L(q)), q;
+        }
+        function y(a, b, c, d, e) {
+          if (e)
+            return [
+              ["M", +a + +e, b],
+              ["l", c - 2 * e, 0],
+              ["a", e, e, 0, 0, 1, e, e],
+              ["l", 0, d - 2 * e],
+              ["a", e, e, 0, 0, 1, -e, e],
+              ["l", 2 * e - c, 0],
+              ["a", e, e, 0, 0, 1, -e, -e],
+              ["l", 0, 2 * e - d],
+              ["a", e, e, 0, 0, 1, e, -e],
+              ["z"],
+            ];
+          var f = [["M", a, b], ["l", c, 0], ["l", 0, d], ["l", -c, 0], ["z"]];
+          return (f.toString = g), f;
+        }
+        function z(a, b, c, d, e) {
+          if (
+            (null == e && null == d && (d = c), (a = +a), (b = +b), (c = +c), (d = +d), null != e)
+          )
+            var f = Math.PI / 180,
+              h = a + c * Math.cos(-d * f),
+              i = a + c * Math.cos(-e * f),
+              j = b + c * Math.sin(-d * f),
+              k = b + c * Math.sin(-e * f),
+              l = [
+                ["M", h, j],
+                ["A", c, c, 0, +(e - d > 180), 0, i, k],
+              ];
+          else
+            l = [
+              ["M", a, b],
+              ["m", 0, -d],
+              ["a", c, d, 0, 1, 1, 0, 2 * d],
+              ["a", c, d, 0, 1, 1, 0, -2 * d],
+              ["z"],
+            ];
+          return (l.toString = g), l;
+        }
+        function A(b) {
+          var c = e(b),
+            d = String.prototype.toLowerCase;
+          if (c.rel) return h(c.rel);
+          (a.is(b, "array") && a.is(b && b[0], "array")) || (b = a.parsePathString(b));
+          var f = [],
+            i = 0,
+            j = 0,
+            k = 0,
+            l = 0,
+            m = 0;
+          "M" == b[0][0] &&
+            ((i = b[0][1]), (j = b[0][2]), (k = i), (l = j), m++, f.push(["M", i, j]));
+          for (var n = m, o = b.length; o > n; n++) {
+            var p = (f[n] = []),
+              q = b[n];
+            if (q[0] != d.call(q[0]))
+              switch (((p[0] = d.call(q[0])), p[0])) {
+                case "a":
+                  (p[1] = q[1]),
+                    (p[2] = q[2]),
+                    (p[3] = q[3]),
+                    (p[4] = q[4]),
+                    (p[5] = q[5]),
+                    (p[6] = +(q[6] - i).toFixed(3)),
+                    (p[7] = +(q[7] - j).toFixed(3));
+                  break;
+                case "v":
+                  p[1] = +(q[1] - j).toFixed(3);
+                  break;
+                case "m":
+                  (k = q[1]), (l = q[2]);
+                default:
+                  for (var r = 1, s = q.length; s > r; r++)
+                    p[r] = +(q[r] - (r % 2 ? i : j)).toFixed(3);
+              }
+            else {
+              (p = f[n] = []), "m" == q[0] && ((k = q[1] + i), (l = q[2] + j));
+              for (var t = 0, u = q.length; u > t; t++) f[n][t] = q[t];
+            }
+            var v = f[n].length;
+            switch (f[n][0]) {
+              case "z":
+                (i = k), (j = l);
+                break;
+              case "h":
+                i += +f[n][v - 1];
+                break;
+              case "v":
+                j += +f[n][v - 1];
+                break;
+              default:
+                (i += +f[n][v - 2]), (j += +f[n][v - 1]);
+            }
+          }
+          return (f.toString = g), (c.rel = h(f)), f;
+        }
+        function B(b) {
+          var c = e(b);
+          if (c.abs) return h(c.abs);
+          if (
+            ((K(b, "array") && K(b && b[0], "array")) || (b = a.parsePathString(b)),
+            !b || !b.length)
+          )
+            return [["M", 0, 0]];
+          var d,
+            f = [],
+            i = 0,
+            j = 0,
+            k = 0,
+            l = 0,
+            m = 0;
+          "M" == b[0][0] &&
+            ((i = +b[0][1]), (j = +b[0][2]), (k = i), (l = j), m++, (f[0] = ["M", i, j]));
+          for (
+            var n,
+              o,
+              p =
+                3 == b.length &&
+                "M" == b[0][0] &&
+                "R" == b[1][0].toUpperCase() &&
+                "Z" == b[2][0].toUpperCase(),
+              q = m,
+              r = b.length;
+            r > q;
+            q++
+          ) {
+            if ((f.push((n = [])), (o = b[q]), (d = o[0]), d != d.toUpperCase()))
+              switch (((n[0] = d.toUpperCase()), n[0])) {
+                case "A":
+                  (n[1] = o[1]),
+                    (n[2] = o[2]),
+                    (n[3] = o[3]),
+                    (n[4] = o[4]),
+                    (n[5] = o[5]),
+                    (n[6] = +o[6] + i),
+                    (n[7] = +o[7] + j);
+                  break;
+                case "V":
+                  n[1] = +o[1] + j;
+                  break;
+                case "H":
+                  n[1] = +o[1] + i;
+                  break;
+                case "R":
+                  for (var s = [i, j].concat(o.slice(1)), t = 2, u = s.length; u > t; t++)
+                    (s[t] = +s[t] + i), (s[++t] = +s[t] + j);
+                  f.pop(), (f = f.concat(I(s, p)));
+                  break;
+                case "O":
+                  f.pop(), (s = z(i, j, o[1], o[2])), s.push(s[0]), (f = f.concat(s));
+                  break;
+                case "U":
+                  f.pop(),
+                    (f = f.concat(z(i, j, o[1], o[2], o[3]))),
+                    (n = ["U"].concat(f[f.length - 1].slice(-2)));
+                  break;
+                case "M":
+                  (k = +o[1] + i), (l = +o[2] + j);
+                default:
+                  for (t = 1, u = o.length; u > t; t++) n[t] = +o[t] + (t % 2 ? i : j);
+              }
+            else if ("R" == d)
+              (s = [i, j].concat(o.slice(1))),
+                f.pop(),
+                (f = f.concat(I(s, p))),
+                (n = ["R"].concat(o.slice(-2)));
+            else if ("O" == d) f.pop(), (s = z(i, j, o[1], o[2])), s.push(s[0]), (f = f.concat(s));
+            else if ("U" == d)
+              f.pop(),
+                (f = f.concat(z(i, j, o[1], o[2], o[3]))),
+                (n = ["U"].concat(f[f.length - 1].slice(-2)));
+            else for (var v = 0, w = o.length; w > v; v++) n[v] = o[v];
+            if (((d = d.toUpperCase()), "O" != d))
+              switch (n[0]) {
+                case "Z":
+                  (i = +k), (j = +l);
+                  break;
+                case "H":
+                  i = n[1];
+                  break;
+                case "V":
+                  j = n[1];
+                  break;
+                case "M":
+                  (k = n[n.length - 2]), (l = n[n.length - 1]);
+                default:
+                  (i = n[n.length - 2]), (j = n[n.length - 1]);
+              }
+          }
+          return (f.toString = g), (c.abs = h(f)), f;
+        }
+        function C(a, b, c, d) {
+          return [a, b, c, d, c, d];
+        }
+        function D(a, b, c, d, e, f) {
+          var g = 1 / 3,
+            h = 2 / 3;
+          return [g * a + h * c, g * b + h * d, g * e + h * c, g * f + h * d, e, f];
+        }
+        function E(b, c, d, e, f, g, h, i, j, k) {
+          var l,
+            m = (120 * Q) / 180,
+            n = (Q / 180) * (+f || 0),
+            o = [],
+            p = a._.cacher(function (a, b, c) {
+              var d = a * P.cos(c) - b * P.sin(c),
+                e = a * P.sin(c) + b * P.cos(c);
+              return { x: d, y: e };
+            });
+          if (!d || !e) return [b, c, i, j, i, j];
+          if (k) (y = k[0]), (z = k[1]), (w = k[2]), (x = k[3]);
+          else {
+            (l = p(b, c, -n)), (b = l.x), (c = l.y), (l = p(i, j, -n)), (i = l.x), (j = l.y);
+            var q = (P.cos((Q / 180) * f), P.sin((Q / 180) * f), (b - i) / 2),
+              r = (c - j) / 2,
+              s = (q * q) / (d * d) + (r * r) / (e * e);
+            s > 1 && ((s = P.sqrt(s)), (d = s * d), (e = s * e));
+            var t = d * d,
+              u = e * e,
+              v =
+                (g == h ? -1 : 1) *
+                P.sqrt(U((t * u - t * r * r - u * q * q) / (t * r * r + u * q * q))),
+              w = (v * d * r) / e + (b + i) / 2,
+              x = (v * -e * q) / d + (c + j) / 2,
+              y = P.asin(((c - x) / e).toFixed(9)),
+              z = P.asin(((j - x) / e).toFixed(9));
+            (y = w > b ? Q - y : y),
+              (z = w > i ? Q - z : z),
+              0 > y && (y = 2 * Q + y),
+              0 > z && (z = 2 * Q + z),
+              h && y > z && (y -= 2 * Q),
+              !h && z > y && (z -= 2 * Q);
+          }
+          var A = z - y;
+          if (U(A) > m) {
+            var B = z,
+              C = i,
+              D = j;
+            (z = y + m * (h && z > y ? 1 : -1)),
+              (i = w + d * P.cos(z)),
+              (j = x + e * P.sin(z)),
+              (o = E(i, j, d, e, f, 0, h, C, D, [z, B, w, x]));
+          }
+          A = z - y;
+          var F = P.cos(y),
+            G = P.sin(y),
+            H = P.cos(z),
+            I = P.sin(z),
+            J = P.tan(A / 4),
+            K = (4 / 3) * d * J,
+            L = (4 / 3) * e * J,
+            M = [b, c],
+            N = [b + K * G, c - L * F],
+            O = [i + K * I, j - L * H],
+            R = [i, j];
+          if (((N[0] = 2 * M[0] - N[0]), (N[1] = 2 * M[1] - N[1]), k)) return [N, O, R].concat(o);
+          o = [N, O, R].concat(o).join().split(",");
+          for (var S = [], T = 0, V = o.length; V > T; T++)
+            S[T] = T % 2 ? p(o[T - 1], o[T], n).y : p(o[T], o[T + 1], n).x;
+          return S;
+        }
+        function F(a, b, c, d, e, f, g, h) {
+          for (var i, j, k, l, m, n, o, p, q = [], r = [[], []], s = 0; 2 > s; ++s)
+            if (
+              (0 == s
+                ? ((j = 6 * a - 12 * c + 6 * e),
+                  (i = -3 * a + 9 * c - 9 * e + 3 * g),
+                  (k = 3 * c - 3 * a))
+                : ((j = 6 * b - 12 * d + 6 * f),
+                  (i = -3 * b + 9 * d - 9 * f + 3 * h),
+                  (k = 3 * d - 3 * b)),
+              U(i) < 1e-12)
+            ) {
+              if (U(j) < 1e-12) continue;
+              (l = -k / j), l > 0 && 1 > l && q.push(l);
+            } else
+              (o = j * j - 4 * k * i),
+                (p = P.sqrt(o)),
+                0 > o ||
+                  ((m = (-j + p) / (2 * i)),
+                  m > 0 && 1 > m && q.push(m),
+                  (n = (-j - p) / (2 * i)),
+                  n > 0 && 1 > n && q.push(n));
+          for (var t, u = q.length, v = u; u--; )
+            (l = q[u]),
+              (t = 1 - l),
+              (r[0][u] = t * t * t * a + 3 * t * t * l * c + 3 * t * l * l * e + l * l * l * g),
+              (r[1][u] = t * t * t * b + 3 * t * t * l * d + 3 * t * l * l * f + l * l * l * h);
+          return (
+            (r[0][v] = a),
+            (r[1][v] = b),
+            (r[0][v + 1] = g),
+            (r[1][v + 1] = h),
+            (r[0].length = r[1].length = v + 2),
+            {
+              min: { x: R.apply(0, r[0]), y: R.apply(0, r[1]) },
+              max: { x: S.apply(0, r[0]), y: S.apply(0, r[1]) },
+            }
+          );
+        }
+        function G(a, b) {
+          var c = !b && e(a);
+          if (!b && c.curve) return h(c.curve);
+          for (
+            var d = B(a),
+              f = b && B(b),
+              g = { x: 0, y: 0, bx: 0, by: 0, X: 0, Y: 0, qx: null, qy: null },
+              i = { x: 0, y: 0, bx: 0, by: 0, X: 0, Y: 0, qx: null, qy: null },
+              j = function (a, b, c) {
+                var d, e;
+                if (!a) return ["C", b.x, b.y, b.x, b.y, b.x, b.y];
+                switch ((!(a[0] in { T: 1, Q: 1 }) && (b.qx = b.qy = null), a[0])) {
+                  case "M":
+                    (b.X = a[1]), (b.Y = a[2]);
+                    break;
+                  case "A":
+                    a = ["C"].concat(E.apply(0, [b.x, b.y].concat(a.slice(1))));
+                    break;
+                  case "S":
+                    "C" == c || "S" == c
+                      ? ((d = 2 * b.x - b.bx), (e = 2 * b.y - b.by))
+                      : ((d = b.x), (e = b.y)),
+                      (a = ["C", d, e].concat(a.slice(1)));
+                    break;
+                  case "T":
+                    "Q" == c || "T" == c
+                      ? ((b.qx = 2 * b.x - b.qx), (b.qy = 2 * b.y - b.qy))
+                      : ((b.qx = b.x), (b.qy = b.y)),
+                      (a = ["C"].concat(D(b.x, b.y, b.qx, b.qy, a[1], a[2])));
+                    break;
+                  case "Q":
+                    (b.qx = a[1]),
+                      (b.qy = a[2]),
+                      (a = ["C"].concat(D(b.x, b.y, a[1], a[2], a[3], a[4])));
+                    break;
+                  case "L":
+                    a = ["C"].concat(C(b.x, b.y, a[1], a[2]));
+                    break;
+                  case "H":
+                    a = ["C"].concat(C(b.x, b.y, a[1], b.y));
+                    break;
+                  case "V":
+                    a = ["C"].concat(C(b.x, b.y, b.x, a[1]));
+                    break;
+                  case "Z":
+                    a = ["C"].concat(C(b.x, b.y, b.X, b.Y));
+                }
+                return a;
+              },
+              k = function (a, b) {
+                if (a[b].length > 7) {
+                  a[b].shift();
+                  for (var c = a[b]; c.length; )
+                    (m[b] = "A"), f && (n[b] = "A"), a.splice(b++, 0, ["C"].concat(c.splice(0, 6)));
+                  a.splice(b, 1), (r = S(d.length, (f && f.length) || 0));
+                }
+              },
+              l = function (a, b, c, e, g) {
+                a &&
+                  b &&
+                  "M" == a[g][0] &&
+                  "M" != b[g][0] &&
+                  (b.splice(g, 0, ["M", e.x, e.y]),
+                  (c.bx = 0),
+                  (c.by = 0),
+                  (c.x = a[g][1]),
+                  (c.y = a[g][2]),
+                  (r = S(d.length, (f && f.length) || 0)));
+              },
+              m = [],
+              n = [],
+              o = "",
+              p = "",
+              q = 0,
+              r = S(d.length, (f && f.length) || 0);
+            r > q;
+            q++
+          ) {
+            d[q] && (o = d[q][0]),
+              "C" != o && ((m[q] = o), q && (p = m[q - 1])),
+              (d[q] = j(d[q], g, p)),
+              "A" != m[q] && "C" == o && (m[q] = "C"),
+              k(d, q),
+              f &&
+                (f[q] && (o = f[q][0]),
+                "C" != o && ((n[q] = o), q && (p = n[q - 1])),
+                (f[q] = j(f[q], i, p)),
+                "A" != n[q] && "C" == o && (n[q] = "C"),
+                k(f, q)),
+              l(d, f, g, i, q),
+              l(f, d, i, g, q);
+            var s = d[q],
+              t = f && f[q],
+              u = s.length,
+              v = f && t.length;
+            (g.x = s[u - 2]),
+              (g.y = s[u - 1]),
+              (g.bx = O(s[u - 4]) || g.x),
+              (g.by = O(s[u - 3]) || g.y),
+              (i.bx = f && (O(t[v - 4]) || i.x)),
+              (i.by = f && (O(t[v - 3]) || i.y)),
+              (i.x = f && t[v - 2]),
+              (i.y = f && t[v - 1]);
+          }
+          return f || (c.curve = h(d)), f ? [d, f] : d;
+        }
+        function H(a, b) {
+          if (!b) return a;
+          var c, d, e, f, g, h, i;
+          for (a = G(a), e = 0, g = a.length; g > e; e++)
+            for (i = a[e], f = 1, h = i.length; h > f; f += 2)
+              (c = b.x(i[f], i[f + 1])), (d = b.y(i[f], i[f + 1])), (i[f] = c), (i[f + 1] = d);
+          return a;
+        }
+        function I(a, b) {
+          for (var c = [], d = 0, e = a.length; e - 2 * !b > d; d += 2) {
+            var f = [
+              { x: +a[d - 2], y: +a[d - 1] },
+              { x: +a[d], y: +a[d + 1] },
+              { x: +a[d + 2], y: +a[d + 3] },
+              { x: +a[d + 4], y: +a[d + 5] },
+            ];
+            b
+              ? d
+                ? e - 4 == d
+                  ? (f[3] = { x: +a[0], y: +a[1] })
+                  : e - 2 == d && ((f[2] = { x: +a[0], y: +a[1] }), (f[3] = { x: +a[2], y: +a[3] }))
+                : (f[0] = { x: +a[e - 2], y: +a[e - 1] })
+              : e - 4 == d
+              ? (f[3] = f[2])
+              : d || (f[0] = { x: +a[d], y: +a[d + 1] }),
+              c.push([
+                "C",
+                (-f[0].x + 6 * f[1].x + f[2].x) / 6,
+                (-f[0].y + 6 * f[1].y + f[2].y) / 6,
+                (f[1].x + 6 * f[2].x - f[3].x) / 6,
+                (f[1].y + 6 * f[2].y - f[3].y) / 6,
+                f[2].x,
+                f[2].y,
+              ]);
+          }
+          return c;
+        }
+        var J = b.prototype,
+          K = a.is,
+          L = a._.clone,
+          M = "hasOwnProperty",
+          N = /,?([a-z]),?/gi,
+          O = parseFloat,
+          P = Math,
+          Q = P.PI,
+          R = P.min,
+          S = P.max,
+          T = P.pow,
+          U = P.abs,
+          V = j(1),
+          W = j(),
+          X = j(0, 1),
+          Y = a._unit2px,
+          Z = {
+            path: function (a) {
+              return a.attr("path");
+            },
+            circle: function (a) {
+              var b = Y(a);
+              return z(b.cx, b.cy, b.r);
+            },
+            ellipse: function (a) {
+              var b = Y(a);
+              return z(b.cx || 0, b.cy || 0, b.rx, b.ry);
+            },
+            rect: function (a) {
+              var b = Y(a);
+              return y(b.x || 0, b.y || 0, b.width, b.height, b.rx, b.ry);
+            },
+            image: function (a) {
+              var b = Y(a);
+              return y(b.x || 0, b.y || 0, b.width, b.height);
+            },
+            line: function (a) {
+              return "M" + [a.attr("x1") || 0, a.attr("y1") || 0, a.attr("x2"), a.attr("y2")];
+            },
+            polyline: function (a) {
+              return "M" + a.attr("points");
+            },
+            polygon: function (a) {
+              return "M" + a.attr("points") + "z";
+            },
+            deflt: function (a) {
+              var b = a.node.getBBox();
+              return y(b.x, b.y, b.width, b.height);
+            },
+          };
+        (a.path = e),
+          (a.path.getTotalLength = V),
+          (a.path.getPointAtLength = W),
+          (a.path.getSubpath = function (a, b, c) {
+            if (this.getTotalLength(a) - c < 1e-6) return X(a, b).end;
+            var d = X(a, c, 1);
+            return b ? X(d, b).end : d;
+          }),
+          (J.getTotalLength = function () {
+            return this.node.getTotalLength ? this.node.getTotalLength() : void 0;
+          }),
+          (J.getPointAtLength = function (a) {
+            return W(this.attr("d"), a);
+          }),
+          (J.getSubpath = function (b, c) {
+            return a.path.getSubpath(this.attr("d"), b, c);
+          }),
+          (a._.box = f),
+          (a.path.findDotsAtSegment = k),
+          (a.path.bezierBBox = l),
+          (a.path.isPointInsideBBox = m),
+          (a.closest = function (b, c, d, e) {
+            for (
+              var g = 100,
+                h = f(b - g / 2, c - g / 2, g, g),
+                i = [],
+                j = d[0].hasOwnProperty("x")
+                  ? function (a) {
+                      return { x: d[a].x, y: d[a].y };
+                    }
+                  : function (a) {
+                      return { x: d[a], y: e[a] };
+                    },
+                k = 0;
+              1e6 >= g && !k;
+
+            ) {
+              for (var l = 0, n = d.length; n > l; l++) {
+                var o = j(l);
+                if (m(h, o.x, o.y)) {
+                  k++, i.push(o);
+                  break;
+                }
+              }
+              k || ((g *= 2), (h = f(b - g / 2, c - g / 2, g, g)));
+            }
+            if (1e6 != g) {
+              var p,
+                q = 1 / 0;
+              for (l = 0, n = i.length; n > l; l++) {
+                var r = a.len(b, c, i[l].x, i[l].y);
+                q > r && ((q = r), (i[l].len = r), (p = i[l]));
+              }
+              return p;
+            }
+          }),
+          (a.path.isBBoxIntersect = n),
+          (a.path.intersection = t),
+          (a.path.intersectionNumber = u),
+          (a.path.isPointInside = w),
+          (a.path.getBBox = x),
+          (a.path.get = Z),
+          (a.path.toRelative = A),
+          (a.path.toAbsolute = B),
+          (a.path.toCubic = G),
+          (a.path.map = H),
+          (a.path.toString = g),
+          (a.path.clone = h);
+      }),
+      d.plugin(function (a, d, e, f) {
+        var g = Math.max,
+          h = Math.min,
+          i = function (a) {
+            if (
+              ((this.items = []), (this.bindings = {}), (this.length = 0), (this.type = "set"), a)
+            )
+              for (var b = 0, c = a.length; c > b; b++)
+                a[b] &&
+                  ((this[this.items.length] = this.items[this.items.length] = a[b]), this.length++);
+          },
+          j = i.prototype;
+        (j.push = function () {
+          for (var a, b, c = 0, d = arguments.length; d > c; c++)
+            (a = arguments[c]),
+              a && ((b = this.items.length), (this[b] = this.items[b] = a), this.length++);
+          return this;
+        }),
+          (j.pop = function () {
+            return this.length && delete this[this.length--], this.items.pop();
+          }),
+          (j.forEach = function (a, b) {
+            for (var c = 0, d = this.items.length; d > c; c++)
+              if (a.call(b, this.items[c], c) === !1) return this;
+            return this;
+          }),
+          (j.animate = function (d, e, f, g) {
+            "function" != typeof f || f.length || ((g = f), (f = c.linear)),
+              d instanceof a._.Animation &&
+                ((g = d.callback), (f = d.easing), (e = f.dur), (d = d.attr));
+            var h = arguments;
+            if (a.is(d, "array") && a.is(h[h.length - 1], "array")) var i = !0;
+            var j,
+              k = function () {
+                j ? (this.b = j) : (j = this.b);
+              },
+              l = 0,
+              m = this,
+              n =
+                g &&
+                function () {
+                  ++l == m.length && g.call(this);
+                };
+            return this.forEach(function (a, c) {
+              b.once("snap.animcreated." + a.id, k),
+                i ? h[c] && a.animate.apply(a, h[c]) : a.animate(d, e, f, n);
+            });
+          }),
+          (j.remove = function () {
+            for (; this.length; ) this.pop().remove();
+            return this;
+          }),
+          (j.bind = function (a, b, c) {
+            var d = {};
+            if ("function" == typeof b) this.bindings[a] = b;
+            else {
+              var e = c || a;
+              this.bindings[a] = function (a) {
+                (d[e] = a), b.attr(d);
+              };
+            }
+            return this;
+          }),
+          (j.attr = function (a) {
+            var b = {};
+            for (var c in a) this.bindings[c] ? this.bindings[c](a[c]) : (b[c] = a[c]);
+            for (var d = 0, e = this.items.length; e > d; d++) this.items[d].attr(b);
+            return this;
+          }),
+          (j.clear = function () {
+            for (; this.length; ) this.pop();
+          }),
+          (j.splice = function (a, b, c) {
+            (a = 0 > a ? g(this.length + a, 0) : a), (b = g(0, h(this.length - a, b)));
+            var d,
+              e = [],
+              f = [],
+              j = [];
+            for (d = 2; d < arguments.length; d++) j.push(arguments[d]);
+            for (d = 0; b > d; d++) f.push(this[a + d]);
+            for (; d < this.length - a; d++) e.push(this[a + d]);
+            var k = j.length;
+            for (d = 0; d < k + e.length; d++)
+              this.items[a + d] = this[a + d] = k > d ? j[d] : e[d - k];
+            for (d = this.items.length = this.length -= b - k; this[d]; ) delete this[d++];
+            return new i(f);
+          }),
+          (j.exclude = function (a) {
+            for (var b = 0, c = this.length; c > b; b++)
+              if (this[b] == a) return this.splice(b, 1), !0;
+            return !1;
+          }),
+          (j.insertAfter = function (a) {
+            for (var b = this.items.length; b--; ) this.items[b].insertAfter(a);
+            return this;
+          }),
+          (j.getBBox = function () {
+            for (var a = [], b = [], c = [], d = [], e = this.items.length; e--; )
+              if (!this.items[e].removed) {
+                var f = this.items[e].getBBox();
+                a.push(f.x), b.push(f.y), c.push(f.x + f.width), d.push(f.y + f.height);
+              }
+            return (
+              (a = h.apply(0, a)),
+              (b = h.apply(0, b)),
+              (c = g.apply(0, c)),
+              (d = g.apply(0, d)),
+              {
+                x: a,
+                y: b,
+                x2: c,
+                y2: d,
+                width: c - a,
+                height: d - b,
+                cx: a + (c - a) / 2,
+                cy: b + (d - b) / 2,
+              }
+            );
+          }),
+          (j.clone = function (a) {
+            a = new i();
+            for (var b = 0, c = this.items.length; c > b; b++) a.push(this.items[b].clone());
+            return a;
+          }),
+          (j.toString = function () {
+            return "Snap‘s set";
+          }),
+          (j.type = "set"),
+          (a.Set = i),
+          (a.set = function () {
+            var a = new i();
+            return arguments.length && a.push.apply(a, Array.prototype.slice.call(arguments, 0)), a;
+          });
+      }),
+      d.plugin(function (a, c, d, e) {
+        function f(a) {
+          var b = a[0];
+          switch (b.toLowerCase()) {
+            case "t":
+              return [b, 0, 0];
+            case "m":
+              return [b, 1, 0, 0, 1, 0, 0];
+            case "r":
+              return 4 == a.length ? [b, 0, a[2], a[3]] : [b, 0];
+            case "s":
+              return 5 == a.length ? [b, 1, 1, a[3], a[4]] : 3 == a.length ? [b, 1, 1] : [b, 1];
+          }
+        }
+        function g(b, c, d) {
+          (b = b || new a.Matrix()),
+            (c = c || new a.Matrix()),
+            (b = a.parseTransformString(b.toTransformString()) || []),
+            (c = a.parseTransformString(c.toTransformString()) || []);
+          for (
+            var e, g, h, i, j = Math.max(b.length, c.length), k = [], n = [], o = 0;
+            j > o;
+            o++
+          ) {
+            if (
+              ((h = b[o] || f(c[o])),
+              (i = c[o] || f(h)),
+              h[0] != i[0] ||
+                ("r" == h[0].toLowerCase() && (h[2] != i[2] || h[3] != i[3])) ||
+                ("s" == h[0].toLowerCase() && (h[3] != i[3] || h[4] != i[4])))
+            ) {
+              (b = a._.transform2matrix(b, d())),
+                (c = a._.transform2matrix(c, d())),
+                (k = [["m", b.a, b.b, b.c, b.d, b.e, b.f]]),
+                (n = [["m", c.a, c.b, c.c, c.d, c.e, c.f]]);
+              break;
+            }
+            for (k[o] = [], n[o] = [], e = 0, g = Math.max(h.length, i.length); g > e; e++)
+              e in h && (k[o][e] = h[e]), e in i && (n[o][e] = i[e]);
+          }
+          return { from: m(k), to: m(n), f: l(k) };
+        }
+        function h(a) {
+          return a;
+        }
+        function i(a) {
+          return function (b) {
+            return +b.toFixed(3) + a;
+          };
+        }
+        function j(a) {
+          return a.join(" ");
+        }
+        function k(b) {
+          return a.rgb(b[0], b[1], b[2], b[3]);
+        }
+        function l(a) {
+          var b,
+            c,
+            d,
+            e,
+            f,
+            g,
+            h = 0,
+            i = [];
+          for (b = 0, c = a.length; c > b; b++) {
+            for (f = "[", g = ['"' + a[b][0] + '"'], d = 1, e = a[b].length; e > d; d++)
+              g[d] = "val[" + h++ + "]";
+            (f += g + "]"), (i[b] = f);
+          }
+          return Function("val", "return Snap.path.toString.call([" + i + "])");
+        }
+        function m(a) {
+          for (var b = [], c = 0, d = a.length; d > c; c++)
+            for (var e = 1, f = a[c].length; f > e; e++) b.push(a[c][e]);
+          return b;
+        }
+        function n(a) {
+          return isFinite(a);
+        }
+        function o(b, c) {
+          return a.is(b, "array") && a.is(c, "array") ? b.toString() == c.toString() : !1;
+        }
+        var p = {},
+          q = /[%a-z]+$/i,
+          r = String;
+        (p.stroke = p.fill = "colour"),
+          (c.prototype.equal = function (a, c) {
+            return b("snap.util.equal", this, a, c).firstDefined();
+          }),
+          b.on("snap.util.equal", function (b, c) {
+            var d,
+              e,
+              f = r(this.attr(b) || ""),
+              s = this;
+            if ("colour" == p[b])
+              return (
+                (d = a.color(f)),
+                (e = a.color(c)),
+                { from: [d.r, d.g, d.b, d.opacity], to: [e.r, e.g, e.b, e.opacity], f: k }
+              );
+            if ("viewBox" == b)
+              return (
+                (d = this.attr(b).vb.split(" ").map(Number)),
+                (e = c.split(" ").map(Number)),
+                { from: d, to: e, f: j }
+              );
+            if ("transform" == b || "gradientTransform" == b || "patternTransform" == b)
+              return (
+                "string" == typeof c && (c = r(c).replace(/\.{3}|\u2026/g, f)),
+                (f = this.matrix),
+                (c = a._.rgTransform.test(c)
+                  ? a._.transform2matrix(c, this.getBBox())
+                  : a._.transform2matrix(a._.svgTransform2string(c), this.getBBox())),
+                g(f, c, function () {
+                  return s.getBBox(1);
+                })
+              );
+            if ("d" == b || "path" == b)
+              return (d = a.path.toCubic(f, c)), { from: m(d[0]), to: m(d[1]), f: l(d[0]) };
+            if ("points" == b)
+              return (
+                (d = r(f).split(a._.separator)),
+                (e = r(c).split(a._.separator)),
+                {
+                  from: d,
+                  to: e,
+                  f: function (a) {
+                    return a;
+                  },
+                }
+              );
+            if (n(f) && n(c)) return { from: parseFloat(f), to: parseFloat(c), f: h };
+            var t = f.match(q),
+              u = r(c).match(q);
+            return t && o(t, u)
+              ? { from: parseFloat(f), to: parseFloat(c), f: i(t) }
+              : { from: this.asPX(b), to: this.asPX(b, c), f: h };
+          });
+      }),
+      d.plugin(function (a, c, d, e) {
+        for (
+          var f = c.prototype,
+            g = "hasOwnProperty",
+            h = ("createTouch" in e.doc),
+            i = [
+              "click",
+              "dblclick",
+              "mousedown",
+              "mousemove",
+              "mouseout",
+              "mouseover",
+              "mouseup",
+              "touchstart",
+              "touchmove",
+              "touchend",
+              "touchcancel",
+            ],
+            j = { mousedown: "touchstart", mousemove: "touchmove", mouseup: "touchend" },
+            k = function (a, b) {
+              var c = "y" == a ? "scrollTop" : "scrollLeft",
+                d = b && b.node ? b.node.ownerDocument : e.doc;
+              return d[(c in d.documentElement) ? "documentElement" : "body"][c];
+            },
+            l = function () {
+              return this.originalEvent.preventDefault();
+            },
+            m = function () {
+              return this.originalEvent.stopPropagation();
+            },
+            n = function (a, b, c, d) {
+              var e = h && j[b] ? j[b] : b,
+                f = function (e) {
+                  var f = k("y", d),
+                    i = k("x", d);
+                  if (h && j[g](b))
+                    for (var n = 0, o = e.targetTouches && e.targetTouches.length; o > n; n++)
+                      if (e.targetTouches[n].target == a || a.contains(e.targetTouches[n].target)) {
+                        var p = e;
+                        (e = e.targetTouches[n]),
+                          (e.originalEvent = p),
+                          (e.preventDefault = l),
+                          (e.stopPropagation = m);
+                        break;
+                      }
+                  var q = e.clientX + i,
+                    r = e.clientY + f;
+                  return c.call(d, e, q, r);
+                };
+              return (
+                b !== e && a.addEventListener(b, f, !1),
+                a.addEventListener(e, f, !1),
+                function () {
+                  return (
+                    b !== e && a.removeEventListener(b, f, !1), a.removeEventListener(e, f, !1), !0
+                  );
+                }
+              );
+            },
+            o = [],
+            p = function (a) {
+              for (
+                var c, d = a.clientX, e = a.clientY, f = k("y"), g = k("x"), i = o.length;
+                i--;
+
+              ) {
+                if (((c = o[i]), h)) {
+                  for (var j, l = a.touches && a.touches.length; l--; )
+                    if (
+                      ((j = a.touches[l]),
+                      j.identifier == c.el._drag.id || c.el.node.contains(j.target))
+                    ) {
+                      (d = j.clientX),
+                        (e = j.clientY),
+                        (a.originalEvent ? a.originalEvent : a).preventDefault();
+                      break;
+                    }
+                } else a.preventDefault();
+                var m = c.el.node;
+                m.nextSibling, m.parentNode, m.style.display;
+                (d += g),
+                  (e += f),
+                  b(
+                    "snap.drag.move." + c.el.id,
+                    c.move_scope || c.el,
+                    d - c.el._drag.x,
+                    e - c.el._drag.y,
+                    d,
+                    e,
+                    a
+                  );
+              }
+            },
+            q = function (c) {
+              a.unmousemove(p).unmouseup(q);
+              for (var d, e = o.length; e--; )
+                (d = o[e]),
+                  (d.el._drag = {}),
+                  b(
+                    "snap.drag.end." + d.el.id,
+                    d.end_scope || d.start_scope || d.move_scope || d.el,
+                    c
+                  ),
+                  b.off("snap.drag.*." + d.el.id);
+              o = [];
+            },
+            r = i.length;
+          r--;
+
+        )
+          !(function (b) {
+            (a[b] = f[b] =
+              function (c, d) {
+                if (a.is(c, "function"))
+                  (this.events = this.events || []),
+                    this.events.push({
+                      name: b,
+                      f: c,
+                      unbind: n(this.node || document, b, c, d || this),
+                    });
+                else
+                  for (var e = 0, f = this.events.length; f > e; e++)
+                    if (this.events[e].name == b)
+                      try {
+                        this.events[e].f.call(this);
+                      } catch (g) {}
+                return this;
+              }),
+              (a["un" + b] = f["un" + b] =
+                function (a) {
+                  for (var c = this.events || [], d = c.length; d--; )
+                    if (c[d].name == b && (c[d].f == a || !a))
+                      return c[d].unbind(), c.splice(d, 1), !c.length && delete this.events, this;
+                  return this;
+                });
+          })(i[r]);
+        (f.hover = function (a, b, c, d) {
+          return this.mouseover(a, c).mouseout(b, d || c);
+        }),
+          (f.unhover = function (a, b) {
+            return this.unmouseover(a).unmouseout(b);
+          });
+        var s = [];
+        (f.drag = function (c, d, e, f, g, h) {
+          function i(i, j, l) {
+            (i.originalEvent || i).preventDefault(),
+              (k._drag.x = j),
+              (k._drag.y = l),
+              (k._drag.id = i.identifier),
+              !o.length && a.mousemove(p).mouseup(q),
+              o.push({ el: k, move_scope: f, start_scope: g, end_scope: h }),
+              d && b.on("snap.drag.start." + k.id, d),
+              c && b.on("snap.drag.move." + k.id, c),
+              e && b.on("snap.drag.end." + k.id, e),
+              b("snap.drag.start." + k.id, g || f || k, j, l, i);
+          }
+          function j(a, c, d) {
+            b("snap.draginit." + k.id, k, a, c, d);
+          }
+          var k = this;
+          if (!arguments.length) {
+            var l;
+            return k.drag(
+              function (a, b) {
+                this.attr({ transform: l + (l ? "T" : "t") + [a, b] });
+              },
+              function () {
+                l = this.transform().local;
+              }
+            );
+          }
+          return (
+            b.on("snap.draginit." + k.id, i),
+            (k._drag = {}),
+            s.push({ el: k, start: i, init: j }),
+            k.mousedown(j),
+            k
+          );
+        }),
+          (f.undrag = function () {
+            for (var c = s.length; c--; )
+              s[c].el == this &&
+                (this.unmousedown(s[c].init),
+                s.splice(c, 1),
+                b.unbind("snap.drag.*." + this.id),
+                b.unbind("snap.draginit." + this.id));
+            return !s.length && a.unmousemove(p).unmouseup(q), this;
+          });
+      }),
+      d.plugin(function (a, c, d, e) {
+        var f = (c.prototype, d.prototype),
+          g = /^\s*url\((.+)\)/,
+          h = String,
+          i = a._.$;
+        (a.filter = {}),
+          (f.filter = function (b) {
+            var d = this;
+            "svg" != d.type && (d = d.paper);
+            var e = a.parse(h(b)),
+              f = a._.id(),
+              g = (d.node.offsetWidth, d.node.offsetHeight, i("filter"));
+            return (
+              i(g, { id: f, filterUnits: "userSpaceOnUse" }),
+              g.appendChild(e.node),
+              d.defs.appendChild(g),
+              new c(g)
+            );
+          }),
+          b.on("snap.util.getattr.filter", function () {
+            b.stop();
+            var c = i(this.node, "filter");
+            if (c) {
+              var d = h(c).match(g);
+              return d && a.select(d[1]);
+            }
+          }),
+          b.on("snap.util.attr.filter", function (d) {
+            if (d instanceof c && "filter" == d.type) {
+              b.stop();
+              var e = d.node.id;
+              e || (i(d.node, { id: d.id }), (e = d.id)), i(this.node, { filter: a.url(e) });
+            }
+            (d && "none" != d) || (b.stop(), this.node.removeAttribute("filter"));
+          }),
+          (a.filter.blur = function (b, c) {
+            null == b && (b = 2);
+            var d = null == c ? b : [b, c];
+            return a.format('<feGaussianBlur stdDeviation="{def}"/>', { def: d });
+          }),
+          (a.filter.blur.toString = function () {
+            return this();
+          }),
+          (a.filter.shadow = function (b, c, d, e, f) {
+            return (
+              null == f &&
+                (null == e ? ((f = d), (d = 4), (e = "#000")) : ((f = e), (e = d), (d = 4))),
+              null == d && (d = 4),
+              null == f && (f = 1),
+              null == b && ((b = 0), (c = 2)),
+              null == c && (c = b),
+              (e = a.color(e)),
+              a.format(
+                '<feGaussianBlur in="SourceAlpha" stdDeviation="{blur}"/><feOffset dx="{dx}" dy="{dy}" result="offsetblur"/><feFlood flood-color="{color}"/><feComposite in2="offsetblur" operator="in"/><feComponentTransfer><feFuncA type="linear" slope="{opacity}"/></feComponentTransfer><feMerge><feMergeNode/><feMergeNode in="SourceGraphic"/></feMerge>',
+                { color: e, dx: b, dy: c, blur: d, opacity: f }
+              )
+            );
+          }),
+          (a.filter.shadow.toString = function () {
+            return this();
+          }),
+          (a.filter.grayscale = function (b) {
+            return (
+              null == b && (b = 1),
+              a.format(
+                '<feColorMatrix type="matrix" values="{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {b} {h} 0 0 0 0 0 1 0"/>',
+                {
+                  a: 0.2126 + 0.7874 * (1 - b),
+                  b: 0.7152 - 0.7152 * (1 - b),
+                  c: 0.0722 - 0.0722 * (1 - b),
+                  d: 0.2126 - 0.2126 * (1 - b),
+                  e: 0.7152 + 0.2848 * (1 - b),
+                  f: 0.0722 - 0.0722 * (1 - b),
+                  g: 0.2126 - 0.2126 * (1 - b),
+                  h: 0.0722 + 0.9278 * (1 - b),
+                }
+              )
+            );
+          }),
+          (a.filter.grayscale.toString = function () {
+            return this();
+          }),
+          (a.filter.sepia = function (b) {
+            return (
+              null == b && (b = 1),
+              a.format(
+                '<feColorMatrix type="matrix" values="{a} {b} {c} 0 0 {d} {e} {f} 0 0 {g} {h} {i} 0 0 0 0 0 1 0"/>',
+                {
+                  a: 0.393 + 0.607 * (1 - b),
+                  b: 0.769 - 0.769 * (1 - b),
+                  c: 0.189 - 0.189 * (1 - b),
+                  d: 0.349 - 0.349 * (1 - b),
+                  e: 0.686 + 0.314 * (1 - b),
+                  f: 0.168 - 0.168 * (1 - b),
+                  g: 0.272 - 0.272 * (1 - b),
+                  h: 0.534 - 0.534 * (1 - b),
+                  i: 0.131 + 0.869 * (1 - b),
+                }
+              )
+            );
+          }),
+          (a.filter.sepia.toString = function () {
+            return this();
+          }),
+          (a.filter.saturate = function (b) {
+            return (
+              null == b && (b = 1),
+              a.format('<feColorMatrix type="saturate" values="{amount}"/>', { amount: 1 - b })
+            );
+          }),
+          (a.filter.saturate.toString = function () {
+            return this();
+          }),
+          (a.filter.hueRotate = function (b) {
+            return (
+              (b = b || 0),
+              a.format('<feColorMatrix type="hueRotate" values="{angle}"/>', { angle: b })
+            );
+          }),
+          (a.filter.hueRotate.toString = function () {
+            return this();
+          }),
+          (a.filter.invert = function (b) {
+            return (
+              null == b && (b = 1),
+              a.format(
+                '<feComponentTransfer><feFuncR type="table" tableValues="{amount} {amount2}"/><feFuncG type="table" tableValues="{amount} {amount2}"/><feFuncB type="table" tableValues="{amount} {amount2}"/></feComponentTransfer>',
+                { amount: b, amount2: 1 - b }
+              )
+            );
+          }),
+          (a.filter.invert.toString = function () {
+            return this();
+          }),
+          (a.filter.brightness = function (b) {
+            return (
+              null == b && (b = 1),
+              a.format(
+                '<feComponentTransfer><feFuncR type="linear" slope="{amount}"/><feFuncG type="linear" slope="{amount}"/><feFuncB type="linear" slope="{amount}"/></feComponentTransfer>',
+                { amount: b }
+              )
+            );
+          }),
+          (a.filter.brightness.toString = function () {
+            return this();
+          }),
+          (a.filter.contrast = function (b) {
+            return (
+              null == b && (b = 1),
+              a.format(
+                '<feComponentTransfer><feFuncR type="linear" slope="{amount}" intercept="{amount2}"/><feFuncG type="linear" slope="{amount}" intercept="{amount2}"/><feFuncB type="linear" slope="{amount}" intercept="{amount2}"/></feComponentTransfer>',
+                { amount: b, amount2: 0.5 - b / 2 }
+              )
+            );
+          }),
+          (a.filter.contrast.toString = function () {
+            return this();
+          });
+      }),
+      d.plugin(function (a, b, c, d, e) {
+        var f = a._.box,
+          g = a.is,
+          h = /^[^a-z]*([tbmlrc])/i,
+          i = function () {
+            return "T" + this.dx + "," + this.dy;
+          };
+        (b.prototype.getAlign = function (a, b) {
+          null == b && g(a, "string") && ((b = a), (a = null)), (a = a || this.paper);
+          var c = a.getBBox ? a.getBBox() : f(a),
+            d = this.getBBox(),
+            e = {};
+          switch (((b = b && b.match(h)), (b = b ? b[1].toLowerCase() : "c"))) {
+            case "t":
+              (e.dx = 0), (e.dy = c.y - d.y);
+              break;
+            case "b":
+              (e.dx = 0), (e.dy = c.y2 - d.y2);
+              break;
+            case "m":
+              (e.dx = 0), (e.dy = c.cy - d.cy);
+              break;
+            case "l":
+              (e.dx = c.x - d.x), (e.dy = 0);
+              break;
+            case "r":
+              (e.dx = c.x2 - d.x2), (e.dy = 0);
+              break;
+            default:
+              (e.dx = c.cx - d.cx), (e.dy = 0);
+          }
+          return (e.toString = i), e;
+        }),
+          (b.prototype.align = function (a, b) {
+            return this.transform("..." + this.getAlign(a, b));
+          });
+      }),
+      d.plugin(function (b, c, d, e) {
+        function f(a) {
+          a = a.split(/(?=#)/);
+          var b = new String(a[5]);
+          return (
+            (b[50] = a[0]),
+            (b[100] = a[1]),
+            (b[200] = a[2]),
+            (b[300] = a[3]),
+            (b[400] = a[4]),
+            (b[500] = a[5]),
+            (b[600] = a[6]),
+            (b[700] = a[7]),
+            (b[800] = a[8]),
+            (b[900] = a[9]),
+            a[10] && ((b.A100 = a[10]), (b.A200 = a[11]), (b.A400 = a[12]), (b.A700 = a[13])),
+            b
+          );
+        }
+        var g =
+            "#ffebee#ffcdd2#ef9a9a#e57373#ef5350#f44336#e53935#d32f2f#c62828#b71c1c#ff8a80#ff5252#ff1744#d50000",
+          h =
+            "#FCE4EC#F8BBD0#F48FB1#F06292#EC407A#E91E63#D81B60#C2185B#AD1457#880E4F#FF80AB#FF4081#F50057#C51162",
+          i =
+            "#F3E5F5#E1BEE7#CE93D8#BA68C8#AB47BC#9C27B0#8E24AA#7B1FA2#6A1B9A#4A148C#EA80FC#E040FB#D500F9#AA00FF",
+          j =
+            "#EDE7F6#D1C4E9#B39DDB#9575CD#7E57C2#673AB7#5E35B1#512DA8#4527A0#311B92#B388FF#7C4DFF#651FFF#6200EA",
+          k =
+            "#E8EAF6#C5CAE9#9FA8DA#7986CB#5C6BC0#3F51B5#3949AB#303F9F#283593#1A237E#8C9EFF#536DFE#3D5AFE#304FFE",
+          l =
+            "#E3F2FD#BBDEFB#90CAF9#64B5F6#64B5F6#2196F3#1E88E5#1976D2#1565C0#0D47A1#82B1FF#448AFF#2979FF#2962FF",
+          m =
+            "#E1F5FE#B3E5FC#81D4FA#4FC3F7#29B6F6#03A9F4#039BE5#0288D1#0277BD#01579B#80D8FF#40C4FF#00B0FF#0091EA",
+          n =
+            "#E0F7FA#B2EBF2#80DEEA#4DD0E1#26C6DA#00BCD4#00ACC1#0097A7#00838F#006064#84FFFF#18FFFF#00E5FF#00B8D4",
+          o =
+            "#E0F2F1#B2DFDB#80CBC4#4DB6AC#26A69A#009688#00897B#00796B#00695C#004D40#A7FFEB#64FFDA#1DE9B6#00BFA5",
+          p =
+            "#E8F5E9#C8E6C9#A5D6A7#81C784#66BB6A#4CAF50#43A047#388E3C#2E7D32#1B5E20#B9F6CA#69F0AE#00E676#00C853",
+          q =
+            "#F1F8E9#DCEDC8#C5E1A5#AED581#9CCC65#8BC34A#7CB342#689F38#558B2F#33691E#CCFF90#B2FF59#76FF03#64DD17",
+          r =
+            "#F9FBE7#F0F4C3#E6EE9C#DCE775#D4E157#CDDC39#C0CA33#AFB42B#9E9D24#827717#F4FF81#EEFF41#C6FF00#AEEA00",
+          s =
+            "#FFFDE7#FFF9C4#FFF59D#FFF176#FFEE58#FFEB3B#FDD835#FBC02D#F9A825#F57F17#FFFF8D#FFFF00#FFEA00#FFD600",
+          t =
+            "#FFF8E1#FFECB3#FFE082#FFD54F#FFCA28#FFC107#FFB300#FFA000#FF8F00#FF6F00#FFE57F#FFD740#FFC400#FFAB00",
+          u =
+            "#FFF3E0#FFE0B2#FFCC80#FFB74D#FFA726#FF9800#FB8C00#F57C00#EF6C00#E65100#FFD180#FFAB40#FF9100#FF6D00",
+          v =
+            "#FBE9E7#FFCCBC#FFAB91#FF8A65#FF7043#FF5722#F4511E#E64A19#D84315#BF360C#FF9E80#FF6E40#FF3D00#DD2C00",
+          w = "#EFEBE9#D7CCC8#BCAAA4#A1887F#8D6E63#795548#6D4C41#5D4037#4E342E#3E2723",
+          x = "#FAFAFA#F5F5F5#EEEEEE#E0E0E0#BDBDBD#9E9E9E#757575#616161#424242#212121",
+          y = "#ECEFF1#CFD8DC#B0BEC5#90A4AE#78909C#607D8B#546E7A#455A64#37474F#263238";
+        (b.mui = {}),
+          (b.flat = {}),
+          (b.mui.red = f(g)),
+          (b.mui.pink = f(h)),
+          (b.mui.purple = f(i)),
+          (b.mui.deeppurple = f(j)),
+          (b.mui.indigo = f(k)),
+          (b.mui.blue = f(l)),
+          (b.mui.lightblue = f(m)),
+          (b.mui.cyan = f(n)),
+          (b.mui.teal = f(o)),
+          (b.mui.green = f(p)),
+          (b.mui.lightgreen = f(q)),
+          (b.mui.lime = f(r)),
+          (b.mui.yellow = f(s)),
+          (b.mui.amber = f(t)),
+          (b.mui.orange = f(u)),
+          (b.mui.deeporange = f(v)),
+          (b.mui.brown = f(w)),
+          (b.mui.grey = f(x)),
+          (b.mui.bluegrey = f(y)),
+          (b.flat.turquoise = "#1abc9c"),
+          (b.flat.greensea = "#16a085"),
+          (b.flat.sunflower = "#f1c40f"),
+          (b.flat.orange = "#f39c12"),
+          (b.flat.emerland = "#2ecc71"),
+          (b.flat.nephritis = "#27ae60"),
+          (b.flat.carrot = "#e67e22"),
+          (b.flat.pumpkin = "#d35400"),
+          (b.flat.peterriver = "#3498db"),
+          (b.flat.belizehole = "#2980b9"),
+          (b.flat.alizarin = "#e74c3c"),
+          (b.flat.pomegranate = "#c0392b"),
+          (b.flat.amethyst = "#9b59b6"),
+          (b.flat.wisteria = "#8e44ad"),
+          (b.flat.clouds = "#ecf0f1"),
+          (b.flat.silver = "#bdc3c7"),
+          (b.flat.wetasphalt = "#34495e"),
+          (b.flat.midnightblue = "#2c3e50"),
+          (b.flat.concrete = "#95a5a6"),
+          (b.flat.asbestos = "#7f8c8d"),
+          (b.importMUIColors = function () {
+            for (var c in b.mui) b.mui.hasOwnProperty(c) && (a[c] = b.mui[c]);
+          });
+      }),
+      d
+    );
+  });
diff --git a/7.3/demos/js/webgazer/ridgeWorker.mjs b/7.3/demos/js/webgazer/ridgeWorker.mjs
old mode 100755
new mode 100644
index a9da0d0683..8e5f57c442
--- a/7.3/demos/js/webgazer/ridgeWorker.mjs
+++ b/7.3/demos/js/webgazer/ridgeWorker.mjs
@@ -1,136 +1,136 @@
-"use strict";
-
-console.log("thread starting");
-
-// Add src/util.mjs and src/mat.mjs to the same directory as your html file
-importScripts("./worker_scripts/util.js", "./worker_scripts/mat.js"); // [20200708] Figure out how to make all of this wrap up neatly
-var ridgeParameter = Math.pow(10, -5);
-var resizeWidth = 10;
-var resizeHeight = 6;
-var dataWindow = 700;
-var trailDataWindow = 10;
-var trainInterval = 500;
-
-var screenXClicksArray = new self.webgazer.util.DataWindow(dataWindow);
-var screenYClicksArray = new self.webgazer.util.DataWindow(dataWindow);
-var eyeFeaturesClicks = new self.webgazer.util.DataWindow(dataWindow);
-var dataClicks = new self.webgazer.util.DataWindow(dataWindow);
-
-var screenXTrailArray = new self.webgazer.util.DataWindow(trailDataWindow);
-var screenYTrailArray = new self.webgazer.util.DataWindow(trailDataWindow);
-var eyeFeaturesTrail = new self.webgazer.util.DataWindow(trailDataWindow);
-var dataTrail = new self.webgazer.util.DataWindow(trailDataWindow);
-
-/**
- * Performs ridge regression, according to the Weka code.
- * @param {Array} y - corresponds to screen coordinates (either x or y) for each of n click events
- * @param {Array.<Array.<Number>>} X - corresponds to gray pixel features (120 pixels for both eyes) for each of n clicks
- * @param {Array} k - ridge parameter
- * @return{Array} regression coefficients
- */
-function ridge(y, X, k) {
-  var nc = X[0].length;
-  var m_Coefficients = new Array(nc);
-  var xt = self.webgazer.mat.transpose(X);
-  var solution = new Array();
-  var success = true;
-  do {
-    var ss = self.webgazer.mat.mult(xt, X);
-    // Set ridge regression adjustment
-    for (var i = 0; i < nc; i++) {
-      ss[i][i] = ss[i][i] + k;
-    }
-
-    // Carry out the regression
-    var bb = self.webgazer.mat.mult(xt, y);
-    for (var i = 0; i < nc; i++) {
-      m_Coefficients[i] = bb[i][0];
-    }
-    try {
-      var n = m_Coefficients.length !== 0 ? m_Coefficients.length / m_Coefficients.length : 0;
-      if (m_Coefficients.length * n !== m_Coefficients.length) {
-        console.log("Array length must be a multiple of m");
-      }
-      solution =
-        ss.length === ss[0].length
-          ? self.webgazer.mat.LUDecomposition(ss, bb)
-          : self.webgazer.mat.QRDecomposition(ss, bb);
-
-      for (var i = 0; i < nc; i++) {
-        m_Coefficients[i] = solution[i][0];
-      }
-      success = true;
-    } catch (ex) {
-      k *= 10;
-      console.log(ex);
-      success = false;
-    }
-  } while (!success);
-  return m_Coefficients;
-}
-
-//TODO: still usefull ???
-/**
- *
- * @returns {Number}
- */
-function getCurrentFixationIndex() {
-  var index = 0;
-  var recentX = this.screenXTrailArray.get(0);
-  var recentY = this.screenYTrailArray.get(0);
-  for (var i = this.screenXTrailArray.length - 1; i >= 0; i--) {
-    var currX = this.screenXTrailArray.get(i);
-    var currY = this.screenYTrailArray.get(i);
-    var euclideanDistance = Math.sqrt(Math.pow(currX - recentX, 2) + Math.pow(currY - recentY, 2));
-    if (euclideanDistance > 72) {
-      return i + 1;
-    }
-  }
-  return i;
-}
-
-/**
- * Event handler, it store screen position to allow training
- * @param {Event} event - the receive event
- */
-self.onmessage = function (event) {
-  var data = event.data;
-  var screenPos = data["screenPos"];
-  var eyes = data["eyes"];
-  var type = data["type"];
-  if (type === "click") {
-    self.screenXClicksArray.push([screenPos[0]]);
-    self.screenYClicksArray.push([screenPos[1]]);
-
-    self.eyeFeaturesClicks.push(eyes);
-  } else if (type === "move") {
-    self.screenXTrailArray.push([screenPos[0]]);
-    self.screenYTrailArray.push([screenPos[1]]);
-
-    self.eyeFeaturesTrail.push(eyes);
-    self.dataTrail.push({ eyes: eyes, screenPos: screenPos, type: type });
-  }
-  self.needsTraining = true;
-};
-
-/**
- * Compute coefficient from training data
- */
-function retrain() {
-  if (self.screenXClicksArray.length === 0) {
-    return;
-  }
-  if (!self.needsTraining) {
-    return;
-  }
-  var screenXArray = self.screenXClicksArray.data.concat(self.screenXTrailArray.data);
-  var screenYArray = self.screenYClicksArray.data.concat(self.screenYTrailArray.data);
-  var eyeFeatures = self.eyeFeaturesClicks.data.concat(self.eyeFeaturesTrail.data);
-
-  var coefficientsX = ridge(screenXArray, eyeFeatures, ridgeParameter);
-  var coefficientsY = ridge(screenYArray, eyeFeatures, ridgeParameter);
-  self.postMessage({ X: coefficientsX, Y: coefficientsY });
-  self.needsTraining = false;
-}
-
-setInterval(retrain, trainInterval);
+"use strict";
+
+console.log("thread starting");
+
+// Add src/util.mjs and src/mat.mjs to the same directory as your html file
+importScripts("./worker_scripts/util.js", "./worker_scripts/mat.js"); // [20200708] Figure out how to make all of this wrap up neatly
+var ridgeParameter = Math.pow(10, -5);
+var resizeWidth = 10;
+var resizeHeight = 6;
+var dataWindow = 700;
+var trailDataWindow = 10;
+var trainInterval = 500;
+
+var screenXClicksArray = new self.webgazer.util.DataWindow(dataWindow);
+var screenYClicksArray = new self.webgazer.util.DataWindow(dataWindow);
+var eyeFeaturesClicks = new self.webgazer.util.DataWindow(dataWindow);
+var dataClicks = new self.webgazer.util.DataWindow(dataWindow);
+
+var screenXTrailArray = new self.webgazer.util.DataWindow(trailDataWindow);
+var screenYTrailArray = new self.webgazer.util.DataWindow(trailDataWindow);
+var eyeFeaturesTrail = new self.webgazer.util.DataWindow(trailDataWindow);
+var dataTrail = new self.webgazer.util.DataWindow(trailDataWindow);
+
+/**
+ * Performs ridge regression, according to the Weka code.
+ * @param {Array} y - corresponds to screen coordinates (either x or y) for each of n click events
+ * @param {Array.<Array.<Number>>} X - corresponds to gray pixel features (120 pixels for both eyes) for each of n clicks
+ * @param {Array} k - ridge parameter
+ * @return{Array} regression coefficients
+ */
+function ridge(y, X, k) {
+  var nc = X[0].length;
+  var m_Coefficients = new Array(nc);
+  var xt = self.webgazer.mat.transpose(X);
+  var solution = new Array();
+  var success = true;
+  do {
+    var ss = self.webgazer.mat.mult(xt, X);
+    // Set ridge regression adjustment
+    for (var i = 0; i < nc; i++) {
+      ss[i][i] = ss[i][i] + k;
+    }
+
+    // Carry out the regression
+    var bb = self.webgazer.mat.mult(xt, y);
+    for (var i = 0; i < nc; i++) {
+      m_Coefficients[i] = bb[i][0];
+    }
+    try {
+      var n = m_Coefficients.length !== 0 ? m_Coefficients.length / m_Coefficients.length : 0;
+      if (m_Coefficients.length * n !== m_Coefficients.length) {
+        console.log("Array length must be a multiple of m");
+      }
+      solution =
+        ss.length === ss[0].length
+          ? self.webgazer.mat.LUDecomposition(ss, bb)
+          : self.webgazer.mat.QRDecomposition(ss, bb);
+
+      for (var i = 0; i < nc; i++) {
+        m_Coefficients[i] = solution[i][0];
+      }
+      success = true;
+    } catch (ex) {
+      k *= 10;
+      console.log(ex);
+      success = false;
+    }
+  } while (!success);
+  return m_Coefficients;
+}
+
+//TODO: still usefull ???
+/**
+ *
+ * @returns {Number}
+ */
+function getCurrentFixationIndex() {
+  var index = 0;
+  var recentX = this.screenXTrailArray.get(0);
+  var recentY = this.screenYTrailArray.get(0);
+  for (var i = this.screenXTrailArray.length - 1; i >= 0; i--) {
+    var currX = this.screenXTrailArray.get(i);
+    var currY = this.screenYTrailArray.get(i);
+    var euclideanDistance = Math.sqrt(Math.pow(currX - recentX, 2) + Math.pow(currY - recentY, 2));
+    if (euclideanDistance > 72) {
+      return i + 1;
+    }
+  }
+  return i;
+}
+
+/**
+ * Event handler, it store screen position to allow training
+ * @param {Event} event - the receive event
+ */
+self.onmessage = function (event) {
+  var data = event.data;
+  var screenPos = data["screenPos"];
+  var eyes = data["eyes"];
+  var type = data["type"];
+  if (type === "click") {
+    self.screenXClicksArray.push([screenPos[0]]);
+    self.screenYClicksArray.push([screenPos[1]]);
+
+    self.eyeFeaturesClicks.push(eyes);
+  } else if (type === "move") {
+    self.screenXTrailArray.push([screenPos[0]]);
+    self.screenYTrailArray.push([screenPos[1]]);
+
+    self.eyeFeaturesTrail.push(eyes);
+    self.dataTrail.push({ eyes: eyes, screenPos: screenPos, type: type });
+  }
+  self.needsTraining = true;
+};
+
+/**
+ * Compute coefficient from training data
+ */
+function retrain() {
+  if (self.screenXClicksArray.length === 0) {
+    return;
+  }
+  if (!self.needsTraining) {
+    return;
+  }
+  var screenXArray = self.screenXClicksArray.data.concat(self.screenXTrailArray.data);
+  var screenYArray = self.screenYClicksArray.data.concat(self.screenYTrailArray.data);
+  var eyeFeatures = self.eyeFeaturesClicks.data.concat(self.eyeFeaturesTrail.data);
+
+  var coefficientsX = ridge(screenXArray, eyeFeatures, ridgeParameter);
+  var coefficientsY = ridge(screenYArray, eyeFeatures, ridgeParameter);
+  self.postMessage({ X: coefficientsX, Y: coefficientsY });
+  self.needsTraining = false;
+}
+
+setInterval(retrain, trainInterval);
diff --git a/7.3/demos/js/webgazer/webgazer.js b/7.3/demos/js/webgazer/webgazer.js
old mode 100755
new mode 100644
index f421f2c80d..71835befff
--- a/7.3/demos/js/webgazer/webgazer.js
+++ b/7.3/demos/js/webgazer/webgazer.js
@@ -1,99912 +1,99912 @@
-/*!
- *
- *  WebGazer.js: Scalable Webcam EyeTracking Using User Interactions
- *  Copyright (c) 2016-2020, Brown HCI Group
- *  Licensed under GPLv3. Companies with a valuation of less than $1M can use WebGazer.js under LGPLv3.
- *
- */
-var webgazer = /******/ (function (modules) {
-  // webpackBootstrap
-  /******/ // The module cache
-  /******/ var installedModules = {};
-  /******/
-  /******/ // The require function
-  /******/ function __webpack_require__(moduleId) {
-    /******/
-    /******/ // Check if module is in cache
-    /******/ if (installedModules[moduleId]) {
-      /******/ return installedModules[moduleId].exports;
-      /******/
-    }
-    /******/ // Create a new module (and put it into the cache)
-    /******/ var module = (installedModules[moduleId] = {
-      /******/ i: moduleId,
-      /******/ l: false,
-      /******/ exports: {},
-      /******/
-    });
-    /******/
-    /******/ // Execute the module function
-    /******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__);
-    /******/
-    /******/ // Flag the module as loaded
-    /******/ module.l = true;
-    /******/
-    /******/ // Return the exports of the module
-    /******/ return module.exports;
-    /******/
-  }
-  /******/
-  /******/
-  /******/ // expose the modules object (__webpack_modules__)
-  /******/ __webpack_require__.m = modules;
-  /******/
-  /******/ // expose the module cache
-  /******/ __webpack_require__.c = installedModules;
-  /******/
-  /******/ // define getter function for harmony exports
-  /******/ __webpack_require__.d = function (exports, name, getter) {
-    /******/ if (!__webpack_require__.o(exports, name)) {
-      /******/ Object.defineProperty(exports, name, { enumerable: true, get: getter });
-      /******/
-    }
-    /******/
-  };
-  /******/
-  /******/ // define __esModule on exports
-  /******/ __webpack_require__.r = function (exports) {
-    /******/ if (typeof Symbol !== "undefined" && Symbol.toStringTag) {
-      /******/ Object.defineProperty(exports, Symbol.toStringTag, { value: "Module" });
-      /******/
-    }
-    /******/ Object.defineProperty(exports, "__esModule", { value: true });
-    /******/
-  };
-  /******/
-  /******/ // create a fake namespace object
-  /******/ // mode & 1: value is a module id, require it
-  /******/ // mode & 2: merge all properties of value into the ns
-  /******/ // mode & 4: return value when already ns object
-  /******/ // mode & 8|1: behave like require
-  /******/ __webpack_require__.t = function (value, mode) {
-    /******/ if (mode & 1) value = __webpack_require__(value);
-    /******/ if (mode & 8) return value;
-    /******/ if (mode & 4 && typeof value === "object" && value && value.__esModule) return value;
-    /******/ var ns = Object.create(null);
-    /******/ __webpack_require__.r(ns);
-    /******/ Object.defineProperty(ns, "default", { enumerable: true, value: value });
-    /******/ if (mode & 2 && typeof value != "string")
-      for (var key in value)
-        __webpack_require__.d(
-          ns,
-          key,
-          function (key) {
-            return value[key];
-          }.bind(null, key)
-        );
-    /******/ return ns;
-    /******/
-  };
-  /******/
-  /******/ // getDefaultExport function for compatibility with non-harmony modules
-  /******/ __webpack_require__.n = function (module) {
-    /******/ var getter =
-      module && module.__esModule
-        ? /******/ function getDefault() {
-            return module["default"];
-          }
-        : /******/ function getModuleExports() {
-            return module;
-          };
-    /******/ __webpack_require__.d(getter, "a", getter);
-    /******/ return getter;
-    /******/
-  };
-  /******/
-  /******/ // Object.prototype.hasOwnProperty.call
-  /******/ __webpack_require__.o = function (object, property) {
-    return Object.prototype.hasOwnProperty.call(object, property);
-  };
-  /******/
-  /******/ // __webpack_public_path__
-  /******/ __webpack_require__.p = "";
-  /******/
-  /******/
-  /******/ // Load entry module and return exports
-  /******/ return __webpack_require__((__webpack_require__.s = 90));
-  /******/
-})(
-  /************************************************************************/
-  /******/ [
-    /* 0 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      // ESM COMPAT FLAG
-      __webpack_require__.r(__webpack_exports__);
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "AdadeltaOptimizer", function () {
-        return /* reexport */ adadelta_optimizer_AdadeltaOptimizer;
-      });
-      __webpack_require__.d(__webpack_exports__, "AdagradOptimizer", function () {
-        return /* reexport */ adagrad_optimizer_AdagradOptimizer;
-      });
-      __webpack_require__.d(__webpack_exports__, "AdamOptimizer", function () {
-        return /* reexport */ adam_optimizer_AdamOptimizer;
-      });
-      __webpack_require__.d(__webpack_exports__, "AdamaxOptimizer", function () {
-        return /* reexport */ adamax_optimizer_AdamaxOptimizer;
-      });
-      __webpack_require__.d(__webpack_exports__, "MomentumOptimizer", function () {
-        return /* reexport */ momentum_optimizer_MomentumOptimizer;
-      });
-      __webpack_require__.d(__webpack_exports__, "Optimizer", function () {
-        return /* reexport */ optimizer_Optimizer;
-      });
-      __webpack_require__.d(__webpack_exports__, "RMSPropOptimizer", function () {
-        return /* reexport */ rmsprop_optimizer_RMSPropOptimizer;
-      });
-      __webpack_require__.d(__webpack_exports__, "SGDOptimizer", function () {
-        return /* reexport */ sgd_optimizer_SGDOptimizer;
-      });
-      __webpack_require__.d(__webpack_exports__, "Tensor", function () {
-        return /* reexport */ dist_tensor["a" /* Tensor */];
-      });
-      __webpack_require__.d(__webpack_exports__, "TensorBuffer", function () {
-        return /* reexport */ dist_tensor["b" /* TensorBuffer */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Variable", function () {
-        return /* reexport */ dist_tensor["c" /* Variable */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Rank", function () {
-        return /* reexport */ dist_types["a" /* Rank */];
-      });
-      __webpack_require__.d(__webpack_exports__, "sumOutType", function () {
-        return /* reexport */ dist_types["b" /* sumOutType */];
-      });
-      __webpack_require__.d(__webpack_exports__, "upcastType", function () {
-        return /* reexport */ dist_types["c" /* upcastType */];
-      });
-      __webpack_require__.d(__webpack_exports__, "add", function () {
-        return /* reexport */ add;
-      });
-      __webpack_require__.d(__webpack_exports__, "addN", function () {
-        return /* reexport */ addN;
-      });
-      __webpack_require__.d(__webpack_exports__, "atan2", function () {
-        return /* reexport */ atan2;
-      });
-      __webpack_require__.d(__webpack_exports__, "avgPool", function () {
-        return /* reexport */ avgPool;
-      });
-      __webpack_require__.d(__webpack_exports__, "avgPool3d", function () {
-        return /* reexport */ avgPool3d;
-      });
-      __webpack_require__.d(__webpack_exports__, "batchToSpaceND", function () {
-        return /* reexport */ batchToSpaceND;
-      });
-      __webpack_require__.d(__webpack_exports__, "batchNorm", function () {
-        return /* reexport */ batchNorm;
-      });
-      __webpack_require__.d(__webpack_exports__, "batchNorm2d", function () {
-        return /* reexport */ batchNorm2d;
-      });
-      __webpack_require__.d(__webpack_exports__, "batchNorm3d", function () {
-        return /* reexport */ batchNorm3d;
-      });
-      __webpack_require__.d(__webpack_exports__, "batchNorm4d", function () {
-        return /* reexport */ batchNorm4d;
-      });
-      __webpack_require__.d(__webpack_exports__, "broadcastTo", function () {
-        return /* reexport */ broadcastTo;
-      });
-      __webpack_require__.d(__webpack_exports__, "clone", function () {
-        return /* reexport */ clone;
-      });
-      __webpack_require__.d(__webpack_exports__, "complex", function () {
-        return /* reexport */ complex["a" /* complex */];
-      });
-      __webpack_require__.d(__webpack_exports__, "concat", function () {
-        return /* reexport */ concat;
-      });
-      __webpack_require__.d(__webpack_exports__, "concat1d", function () {
-        return /* reexport */ concat1d;
-      });
-      __webpack_require__.d(__webpack_exports__, "concat2d", function () {
-        return /* reexport */ concat2d;
-      });
-      __webpack_require__.d(__webpack_exports__, "concat3d", function () {
-        return /* reexport */ concat3d;
-      });
-      __webpack_require__.d(__webpack_exports__, "concat4d", function () {
-        return /* reexport */ concat4d;
-      });
-      __webpack_require__.d(__webpack_exports__, "conv1d", function () {
-        return /* reexport */ conv1d;
-      });
-      __webpack_require__.d(__webpack_exports__, "conv2d", function () {
-        return /* reexport */ conv2d;
-      });
-      __webpack_require__.d(__webpack_exports__, "conv2dTranspose", function () {
-        return /* reexport */ conv2dTranspose;
-      });
-      __webpack_require__.d(__webpack_exports__, "conv3d", function () {
-        return /* reexport */ conv3d;
-      });
-      __webpack_require__.d(__webpack_exports__, "conv3dTranspose", function () {
-        return /* reexport */ conv3dTranspose;
-      });
-      __webpack_require__.d(__webpack_exports__, "cumsum", function () {
-        return /* reexport */ cumsum;
-      });
-      __webpack_require__.d(__webpack_exports__, "depthToSpace", function () {
-        return /* reexport */ depthToSpace;
-      });
-      __webpack_require__.d(__webpack_exports__, "depthwiseConv2d", function () {
-        return /* reexport */ depthwiseConv2d;
-      });
-      __webpack_require__.d(__webpack_exports__, "diag", function () {
-        return /* reexport */ diag;
-      });
-      __webpack_require__.d(__webpack_exports__, "div", function () {
-        return /* reexport */ div;
-      });
-      __webpack_require__.d(__webpack_exports__, "divNoNan", function () {
-        return /* reexport */ divNoNan;
-      });
-      __webpack_require__.d(__webpack_exports__, "dot", function () {
-        return /* reexport */ dot;
-      });
-      __webpack_require__.d(__webpack_exports__, "elu", function () {
-        return /* reexport */ elu;
-      });
-      __webpack_require__.d(__webpack_exports__, "equal", function () {
-        return /* reexport */ equal;
-      });
-      __webpack_require__.d(__webpack_exports__, "eye", function () {
-        return /* reexport */ eye;
-      });
-      __webpack_require__.d(__webpack_exports__, "fill", function () {
-        return /* reexport */ fill;
-      });
-      __webpack_require__.d(__webpack_exports__, "floorDiv", function () {
-        return /* reexport */ floorDiv;
-      });
-      __webpack_require__.d(__webpack_exports__, "greater", function () {
-        return /* reexport */ greater;
-      });
-      __webpack_require__.d(__webpack_exports__, "greaterEqual", function () {
-        return /* reexport */ greaterEqual;
-      });
-      __webpack_require__.d(__webpack_exports__, "imag", function () {
-        return /* reexport */ imag["a" /* imag */];
-      });
-      __webpack_require__.d(__webpack_exports__, "leakyRelu", function () {
-        return /* reexport */ leakyRelu;
-      });
-      __webpack_require__.d(__webpack_exports__, "less", function () {
-        return /* reexport */ less;
-      });
-      __webpack_require__.d(__webpack_exports__, "lessEqual", function () {
-        return /* reexport */ lessEqual;
-      });
-      __webpack_require__.d(__webpack_exports__, "localResponseNormalization", function () {
-        return /* reexport */ localResponseNormalization;
-      });
-      __webpack_require__.d(__webpack_exports__, "matMul", function () {
-        return /* reexport */ matMul;
-      });
-      __webpack_require__.d(__webpack_exports__, "max", function () {
-        return /* reexport */ max_max;
-      });
-      __webpack_require__.d(__webpack_exports__, "maxPool", function () {
-        return /* reexport */ maxPool;
-      });
-      __webpack_require__.d(__webpack_exports__, "maxPool3d", function () {
-        return /* reexport */ maxPool3d;
-      });
-      __webpack_require__.d(__webpack_exports__, "maxPoolWithArgmax", function () {
-        return /* reexport */ maxPoolWithArgmax;
-      });
-      __webpack_require__.d(__webpack_exports__, "maximum", function () {
-        return /* reexport */ maximum;
-      });
-      __webpack_require__.d(__webpack_exports__, "minimum", function () {
-        return /* reexport */ minimum;
-      });
-      __webpack_require__.d(__webpack_exports__, "mod", function () {
-        return /* reexport */ mod;
-      });
-      __webpack_require__.d(__webpack_exports__, "mul", function () {
-        return /* reexport */ mul;
-      });
-      __webpack_require__.d(__webpack_exports__, "multinomial", function () {
-        return /* reexport */ multinomial;
-      });
-      __webpack_require__.d(__webpack_exports__, "notEqual", function () {
-        return /* reexport */ notEqual;
-      });
-      __webpack_require__.d(__webpack_exports__, "oneHot", function () {
-        return /* reexport */ oneHot;
-      });
-      __webpack_require__.d(__webpack_exports__, "outerProduct", function () {
-        return /* reexport */ outerProduct;
-      });
-      __webpack_require__.d(__webpack_exports__, "pad", function () {
-        return /* reexport */ pad_pad;
-      });
-      __webpack_require__.d(__webpack_exports__, "pad1d", function () {
-        return /* reexport */ pad1d;
-      });
-      __webpack_require__.d(__webpack_exports__, "pad2d", function () {
-        return /* reexport */ pad2d;
-      });
-      __webpack_require__.d(__webpack_exports__, "pad3d", function () {
-        return /* reexport */ pad3d;
-      });
-      __webpack_require__.d(__webpack_exports__, "pad4d", function () {
-        return /* reexport */ pad4d;
-      });
-      __webpack_require__.d(__webpack_exports__, "pool", function () {
-        return /* reexport */ pool;
-      });
-      __webpack_require__.d(__webpack_exports__, "pow", function () {
-        return /* reexport */ pow;
-      });
-      __webpack_require__.d(__webpack_exports__, "prelu", function () {
-        return /* reexport */ prelu;
-      });
-      __webpack_require__.d(__webpack_exports__, "rand", function () {
-        return /* reexport */ rand;
-      });
-      __webpack_require__.d(__webpack_exports__, "randomGamma", function () {
-        return /* reexport */ randomGamma;
-      });
-      __webpack_require__.d(__webpack_exports__, "randomNormal", function () {
-        return /* reexport */ randomNormal;
-      });
-      __webpack_require__.d(__webpack_exports__, "randomUniform", function () {
-        return /* reexport */ randomUniform;
-      });
-      __webpack_require__.d(__webpack_exports__, "real", function () {
-        return /* reexport */ real["a" /* real */];
-      });
-      __webpack_require__.d(__webpack_exports__, "relu", function () {
-        return /* reexport */ relu;
-      });
-      __webpack_require__.d(__webpack_exports__, "relu6", function () {
-        return /* reexport */ relu6;
-      });
-      __webpack_require__.d(__webpack_exports__, "selu", function () {
-        return /* reexport */ selu;
-      });
-      __webpack_require__.d(__webpack_exports__, "separableConv2d", function () {
-        return /* reexport */ separableConv2d;
-      });
-      __webpack_require__.d(__webpack_exports__, "spaceToBatchND", function () {
-        return /* reexport */ spaceToBatchND;
-      });
-      __webpack_require__.d(__webpack_exports__, "split", function () {
-        return /* reexport */ split;
-      });
-      __webpack_require__.d(__webpack_exports__, "square", function () {
-        return /* reexport */ square;
-      });
-      __webpack_require__.d(__webpack_exports__, "squaredDifference", function () {
-        return /* reexport */ squaredDifference;
-      });
-      __webpack_require__.d(__webpack_exports__, "sub", function () {
-        return /* reexport */ sub;
-      });
-      __webpack_require__.d(__webpack_exports__, "tile", function () {
-        return /* reexport */ tile;
-      });
-      __webpack_require__.d(__webpack_exports__, "truncatedNormal", function () {
-        return /* reexport */ truncatedNormal;
-      });
-      __webpack_require__.d(__webpack_exports__, "booleanMaskAsync", function () {
-        return /* reexport */ booleanMaskAsync;
-      });
-      __webpack_require__.d(__webpack_exports__, "reverse", function () {
-        return /* reexport */ reverse_reverse;
-      });
-      __webpack_require__.d(__webpack_exports__, "reverse1d", function () {
-        return /* reexport */ reverse1d;
-      });
-      __webpack_require__.d(__webpack_exports__, "reverse2d", function () {
-        return /* reexport */ reverse2d;
-      });
-      __webpack_require__.d(__webpack_exports__, "reverse3d", function () {
-        return /* reexport */ reverse3d;
-      });
-      __webpack_require__.d(__webpack_exports__, "reverse4d", function () {
-        return /* reexport */ reverse4d;
-      });
-      __webpack_require__.d(__webpack_exports__, "slice", function () {
-        return /* reexport */ slice;
-      });
-      __webpack_require__.d(__webpack_exports__, "slice1d", function () {
-        return /* reexport */ slice1d;
-      });
-      __webpack_require__.d(__webpack_exports__, "slice2d", function () {
-        return /* reexport */ slice2d;
-      });
-      __webpack_require__.d(__webpack_exports__, "slice3d", function () {
-        return /* reexport */ slice3d;
-      });
-      __webpack_require__.d(__webpack_exports__, "slice4d", function () {
-        return /* reexport */ slice4d;
-      });
-      __webpack_require__.d(__webpack_exports__, "abs", function () {
-        return /* reexport */ abs;
-      });
-      __webpack_require__.d(__webpack_exports__, "acos", function () {
-        return /* reexport */ acos;
-      });
-      __webpack_require__.d(__webpack_exports__, "acosh", function () {
-        return /* reexport */ acosh;
-      });
-      __webpack_require__.d(__webpack_exports__, "asin", function () {
-        return /* reexport */ asin;
-      });
-      __webpack_require__.d(__webpack_exports__, "asinh", function () {
-        return /* reexport */ asinh;
-      });
-      __webpack_require__.d(__webpack_exports__, "atan", function () {
-        return /* reexport */ atan;
-      });
-      __webpack_require__.d(__webpack_exports__, "atanh", function () {
-        return /* reexport */ atanh;
-      });
-      __webpack_require__.d(__webpack_exports__, "ceil", function () {
-        return /* reexport */ ceil;
-      });
-      __webpack_require__.d(__webpack_exports__, "clipByValue", function () {
-        return /* reexport */ clipByValue;
-      });
-      __webpack_require__.d(__webpack_exports__, "cos", function () {
-        return /* reexport */ cos;
-      });
-      __webpack_require__.d(__webpack_exports__, "cosh", function () {
-        return /* reexport */ cosh;
-      });
-      __webpack_require__.d(__webpack_exports__, "erf", function () {
-        return /* reexport */ erf;
-      });
-      __webpack_require__.d(__webpack_exports__, "exp", function () {
-        return /* reexport */ unary_ops_exp;
-      });
-      __webpack_require__.d(__webpack_exports__, "expm1", function () {
-        return /* reexport */ expm1;
-      });
-      __webpack_require__.d(__webpack_exports__, "floor", function () {
-        return /* reexport */ floor;
-      });
-      __webpack_require__.d(__webpack_exports__, "log", function () {
-        return /* reexport */ log;
-      });
-      __webpack_require__.d(__webpack_exports__, "log1p", function () {
-        return /* reexport */ log1p;
-      });
-      __webpack_require__.d(__webpack_exports__, "logSigmoid", function () {
-        return /* reexport */ logSigmoid;
-      });
-      __webpack_require__.d(__webpack_exports__, "neg", function () {
-        return /* reexport */ neg;
-      });
-      __webpack_require__.d(__webpack_exports__, "reciprocal", function () {
-        return /* reexport */ reciprocal;
-      });
-      __webpack_require__.d(__webpack_exports__, "round", function () {
-        return /* reexport */ round;
-      });
-      __webpack_require__.d(__webpack_exports__, "rsqrt", function () {
-        return /* reexport */ rsqrt;
-      });
-      __webpack_require__.d(__webpack_exports__, "sigmoid", function () {
-        return /* reexport */ sigmoid;
-      });
-      __webpack_require__.d(__webpack_exports__, "sign", function () {
-        return /* reexport */ sign;
-      });
-      __webpack_require__.d(__webpack_exports__, "isNaN", function () {
-        return /* reexport */ unary_ops_isNaN;
-      });
-      __webpack_require__.d(__webpack_exports__, "isInf", function () {
-        return /* reexport */ isInf;
-      });
-      __webpack_require__.d(__webpack_exports__, "isFinite", function () {
-        return /* reexport */ unary_ops_isFinite;
-      });
-      __webpack_require__.d(__webpack_exports__, "sin", function () {
-        return /* reexport */ sin;
-      });
-      __webpack_require__.d(__webpack_exports__, "sinh", function () {
-        return /* reexport */ sinh;
-      });
-      __webpack_require__.d(__webpack_exports__, "softplus", function () {
-        return /* reexport */ softplus;
-      });
-      __webpack_require__.d(__webpack_exports__, "sqrt", function () {
-        return /* reexport */ sqrt;
-      });
-      __webpack_require__.d(__webpack_exports__, "step", function () {
-        return /* reexport */ unary_ops_step;
-      });
-      __webpack_require__.d(__webpack_exports__, "tan", function () {
-        return /* reexport */ tan;
-      });
-      __webpack_require__.d(__webpack_exports__, "tanh", function () {
-        return /* reexport */ tanh;
-      });
-      __webpack_require__.d(__webpack_exports__, "all", function () {
-        return /* reexport */ reduction_ops_all;
-      });
-      __webpack_require__.d(__webpack_exports__, "any", function () {
-        return /* reexport */ any;
-      });
-      __webpack_require__.d(__webpack_exports__, "argMax", function () {
-        return /* reexport */ argMax;
-      });
-      __webpack_require__.d(__webpack_exports__, "argMin", function () {
-        return /* reexport */ argMin;
-      });
-      __webpack_require__.d(__webpack_exports__, "logSumExp", function () {
-        return /* reexport */ logSumExp;
-      });
-      __webpack_require__.d(__webpack_exports__, "mean", function () {
-        return /* reexport */ reduction_ops_mean;
-      });
-      __webpack_require__.d(__webpack_exports__, "min", function () {
-        return /* reexport */ reduction_ops_min;
-      });
-      __webpack_require__.d(__webpack_exports__, "moments", function () {
-        return /* reexport */ moments;
-      });
-      __webpack_require__.d(__webpack_exports__, "sum", function () {
-        return /* reexport */ sum;
-      });
-      __webpack_require__.d(__webpack_exports__, "prod", function () {
-        return /* reexport */ reduction_ops_prod;
-      });
-      __webpack_require__.d(__webpack_exports__, "equalStrict", function () {
-        return /* reexport */ equalStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "greaterEqualStrict", function () {
-        return /* reexport */ greaterEqualStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "greaterStrict", function () {
-        return /* reexport */ greaterStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "lessEqualStrict", function () {
-        return /* reexport */ lessEqualStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "lessStrict", function () {
-        return /* reexport */ lessStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "notEqualStrict", function () {
-        return /* reexport */ notEqualStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "addStrict", function () {
-        return /* reexport */ addStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "divStrict", function () {
-        return /* reexport */ divStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "maximumStrict", function () {
-        return /* reexport */ maximumStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "minimumStrict", function () {
-        return /* reexport */ minimumStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "modStrict", function () {
-        return /* reexport */ modStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "mulStrict", function () {
-        return /* reexport */ mulStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "powStrict", function () {
-        return /* reexport */ powStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "squaredDifferenceStrict", function () {
-        return /* reexport */ squaredDifferenceStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "subStrict", function () {
-        return /* reexport */ subStrict;
-      });
-      __webpack_require__.d(__webpack_exports__, "logicalAnd", function () {
-        return /* reexport */ logicalAnd;
-      });
-      __webpack_require__.d(__webpack_exports__, "logicalNot", function () {
-        return /* reexport */ logicalNot;
-      });
-      __webpack_require__.d(__webpack_exports__, "logicalOr", function () {
-        return /* reexport */ logicalOr;
-      });
-      __webpack_require__.d(__webpack_exports__, "logicalXor", function () {
-        return /* reexport */ logicalXor;
-      });
-      __webpack_require__.d(__webpack_exports__, "where", function () {
-        return /* reexport */ where;
-      });
-      __webpack_require__.d(__webpack_exports__, "whereAsync", function () {
-        return /* reexport */ whereAsync;
-      });
-      __webpack_require__.d(__webpack_exports__, "buffer", function () {
-        return /* reexport */ array_ops_buffer;
-      });
-      __webpack_require__.d(__webpack_exports__, "print", function () {
-        return /* reexport */ print;
-      });
-      __webpack_require__.d(__webpack_exports__, "cast", function () {
-        return /* reexport */ cast;
-      });
-      __webpack_require__.d(__webpack_exports__, "expandDims", function () {
-        return /* reexport */ expandDims;
-      });
-      __webpack_require__.d(__webpack_exports__, "reshape", function () {
-        return /* reexport */ reshape;
-      });
-      __webpack_require__.d(__webpack_exports__, "squeeze", function () {
-        return /* reexport */ squeeze;
-      });
-      __webpack_require__.d(__webpack_exports__, "stack", function () {
-        return /* reexport */ stack;
-      });
-      __webpack_require__.d(__webpack_exports__, "unstack", function () {
-        return /* reexport */ unstack;
-      });
-      __webpack_require__.d(__webpack_exports__, "setdiff1dAsync", function () {
-        return /* reexport */ setdiff1dAsync;
-      });
-      __webpack_require__.d(__webpack_exports__, "linspace", function () {
-        return /* reexport */ tensor_ops["a" /* linspace */];
-      });
-      __webpack_require__.d(__webpack_exports__, "ones", function () {
-        return /* reexport */ tensor_ops["b" /* ones */];
-      });
-      __webpack_require__.d(__webpack_exports__, "range", function () {
-        return /* reexport */ tensor_ops["d" /* range */];
-      });
-      __webpack_require__.d(__webpack_exports__, "scalar", function () {
-        return /* reexport */ tensor_ops["e" /* scalar */];
-      });
-      __webpack_require__.d(__webpack_exports__, "tensor", function () {
-        return /* reexport */ tensor_ops["f" /* tensor */];
-      });
-      __webpack_require__.d(__webpack_exports__, "tensor1d", function () {
-        return /* reexport */ tensor_ops["g" /* tensor1d */];
-      });
-      __webpack_require__.d(__webpack_exports__, "tensor2d", function () {
-        return /* reexport */ tensor_ops["h" /* tensor2d */];
-      });
-      __webpack_require__.d(__webpack_exports__, "tensor3d", function () {
-        return /* reexport */ tensor_ops["i" /* tensor3d */];
-      });
-      __webpack_require__.d(__webpack_exports__, "tensor4d", function () {
-        return /* reexport */ tensor_ops["j" /* tensor4d */];
-      });
-      __webpack_require__.d(__webpack_exports__, "tensor5d", function () {
-        return /* reexport */ tensor_ops["k" /* tensor5d */];
-      });
-      __webpack_require__.d(__webpack_exports__, "tensor6d", function () {
-        return /* reexport */ tensor_ops["l" /* tensor6d */];
-      });
-      __webpack_require__.d(__webpack_exports__, "variable", function () {
-        return /* reexport */ tensor_ops["m" /* variable */];
-      });
-      __webpack_require__.d(__webpack_exports__, "zeros", function () {
-        return /* reexport */ tensor_ops["n" /* zeros */];
-      });
-      __webpack_require__.d(__webpack_exports__, "onesLike", function () {
-        return /* reexport */ tensor_ops["c" /* onesLike */];
-      });
-      __webpack_require__.d(__webpack_exports__, "zerosLike", function () {
-        return /* reexport */ tensor_ops["o" /* zerosLike */];
-      });
-      __webpack_require__.d(__webpack_exports__, "transpose", function () {
-        return /* reexport */ transpose;
-      });
-      __webpack_require__.d(__webpack_exports__, "softmax", function () {
-        return /* reexport */ softmax;
-      });
-      __webpack_require__.d(__webpack_exports__, "logSoftmax", function () {
-        return /* reexport */ logSoftmax;
-      });
-      __webpack_require__.d(__webpack_exports__, "norm", function () {
-        return /* reexport */ norm_norm;
-      });
-      __webpack_require__.d(__webpack_exports__, "gather", function () {
-        return /* reexport */ gather;
-      });
-      __webpack_require__.d(__webpack_exports__, "unsortedSegmentSum", function () {
-        return /* reexport */ unsortedSegmentSum;
-      });
-      __webpack_require__.d(__webpack_exports__, "basicLSTMCell", function () {
-        return /* reexport */ basicLSTMCell;
-      });
-      __webpack_require__.d(__webpack_exports__, "multiRNNCell", function () {
-        return /* reexport */ multiRNNCell;
-      });
-      __webpack_require__.d(__webpack_exports__, "movingAverage", function () {
-        return /* reexport */ movingAverage;
-      });
-      __webpack_require__.d(__webpack_exports__, "stridedSlice", function () {
-        return /* reexport */ stridedSlice;
-      });
-      __webpack_require__.d(__webpack_exports__, "topk", function () {
-        return /* reexport */ topk;
-      });
-      __webpack_require__.d(__webpack_exports__, "scatterND", function () {
-        return /* reexport */ scatterND;
-      });
-      __webpack_require__.d(__webpack_exports__, "fft", function () {
-        return /* reexport */ fft;
-      });
-      __webpack_require__.d(__webpack_exports__, "ifft", function () {
-        return /* reexport */ ifft;
-      });
-      __webpack_require__.d(__webpack_exports__, "rfft", function () {
-        return /* reexport */ rfft;
-      });
-      __webpack_require__.d(__webpack_exports__, "irfft", function () {
-        return /* reexport */ irfft;
-      });
-      __webpack_require__.d(__webpack_exports__, "sparseToDense", function () {
-        return /* reexport */ sparseToDense;
-      });
-      __webpack_require__.d(__webpack_exports__, "gatherND", function () {
-        return /* reexport */ gatherND;
-      });
-      __webpack_require__.d(__webpack_exports__, "dropout", function () {
-        return /* reexport */ dropout;
-      });
-      __webpack_require__.d(__webpack_exports__, "hannWindow", function () {
-        return /* reexport */ hannWindow;
-      });
-      __webpack_require__.d(__webpack_exports__, "hammingWindow", function () {
-        return /* reexport */ hammingWindow;
-      });
-      __webpack_require__.d(__webpack_exports__, "frame", function () {
-        return /* reexport */ signal_ops_frame;
-      });
-      __webpack_require__.d(__webpack_exports__, "stft", function () {
-        return /* reexport */ stft;
-      });
-      __webpack_require__.d(__webpack_exports__, "inTopKAsync", function () {
-        return /* reexport */ inTopKAsync;
-      });
-      __webpack_require__.d(__webpack_exports__, "op", function () {
-        return /* reexport */ operation["a" /* op */];
-      });
-      __webpack_require__.d(__webpack_exports__, "image", function () {
-        return /* reexport */ image_ops_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "linalg", function () {
-        return /* reexport */ linalg_ops_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "losses", function () {
-        return /* reexport */ loss_ops_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "spectral", function () {
-        return /* reexport */ spectral_ops_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "fused", function () {
-        return /* reexport */ fused_ops_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "signal", function () {
-        return /* reexport */ signal_ops_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "Reduction", function () {
-        return /* reexport */ Reduction;
-      });
-      __webpack_require__.d(__webpack_exports__, "train", function () {
-        return /* reexport */ train;
-      });
-      __webpack_require__.d(__webpack_exports__, "enableProdMode", function () {
-        return /* reexport */ enableProdMode;
-      });
-      __webpack_require__.d(__webpack_exports__, "enableDebugMode", function () {
-        return /* reexport */ enableDebugMode;
-      });
-      __webpack_require__.d(__webpack_exports__, "disableDeprecationWarnings", function () {
-        return /* reexport */ disableDeprecationWarnings;
-      });
-      __webpack_require__.d(__webpack_exports__, "deprecationWarn", function () {
-        return /* reexport */ deprecationWarn;
-      });
-      __webpack_require__.d(__webpack_exports__, "disposeVariables", function () {
-        return /* reexport */ disposeVariables;
-      });
-      __webpack_require__.d(__webpack_exports__, "engine", function () {
-        return /* reexport */ globals_engine;
-      });
-      __webpack_require__.d(__webpack_exports__, "memory", function () {
-        return /* reexport */ memory;
-      });
-      __webpack_require__.d(__webpack_exports__, "profile", function () {
-        return /* reexport */ profile;
-      });
-      __webpack_require__.d(__webpack_exports__, "tidy", function () {
-        return /* reexport */ tidy;
-      });
-      __webpack_require__.d(__webpack_exports__, "dispose", function () {
-        return /* reexport */ dispose;
-      });
-      __webpack_require__.d(__webpack_exports__, "keep", function () {
-        return /* reexport */ keep;
-      });
-      __webpack_require__.d(__webpack_exports__, "time", function () {
-        return /* reexport */ time;
-      });
-      __webpack_require__.d(__webpack_exports__, "setBackend", function () {
-        return /* reexport */ setBackend;
-      });
-      __webpack_require__.d(__webpack_exports__, "ready", function () {
-        return /* reexport */ ready;
-      });
-      __webpack_require__.d(__webpack_exports__, "getBackend", function () {
-        return /* reexport */ getBackend;
-      });
-      __webpack_require__.d(__webpack_exports__, "removeBackend", function () {
-        return /* reexport */ removeBackend;
-      });
-      __webpack_require__.d(__webpack_exports__, "findBackend", function () {
-        return /* reexport */ findBackend;
-      });
-      __webpack_require__.d(__webpack_exports__, "findBackendFactory", function () {
-        return /* reexport */ findBackendFactory;
-      });
-      __webpack_require__.d(__webpack_exports__, "registerBackend", function () {
-        return /* reexport */ registerBackend;
-      });
-      __webpack_require__.d(__webpack_exports__, "backend", function () {
-        return /* reexport */ globals_backend;
-      });
-      __webpack_require__.d(__webpack_exports__, "setPlatform", function () {
-        return /* reexport */ setPlatform;
-      });
-      __webpack_require__.d(__webpack_exports__, "getKernel", function () {
-        return /* reexport */ kernel_registry["b" /* getKernel */];
-      });
-      __webpack_require__.d(__webpack_exports__, "getGradient", function () {
-        return /* reexport */ kernel_registry["a" /* getGradient */];
-      });
-      __webpack_require__.d(__webpack_exports__, "getKernelsForBackend", function () {
-        return /* reexport */ kernel_registry["c" /* getKernelsForBackend */];
-      });
-      __webpack_require__.d(__webpack_exports__, "registerKernel", function () {
-        return /* reexport */ kernel_registry["e" /* registerKernel */];
-      });
-      __webpack_require__.d(__webpack_exports__, "registerGradient", function () {
-        return /* reexport */ kernel_registry["d" /* registerGradient */];
-      });
-      __webpack_require__.d(__webpack_exports__, "unregisterKernel", function () {
-        return /* reexport */ kernel_registry["g" /* unregisterKernel */];
-      });
-      __webpack_require__.d(__webpack_exports__, "unregisterGradient", function () {
-        return /* reexport */ kernel_registry["f" /* unregisterGradient */];
-      });
-      __webpack_require__.d(__webpack_exports__, "customGrad", function () {
-        return /* reexport */ customGrad;
-      });
-      __webpack_require__.d(__webpack_exports__, "grad", function () {
-        return /* reexport */ gradients_grad;
-      });
-      __webpack_require__.d(__webpack_exports__, "grads", function () {
-        return /* reexport */ gradients_grads;
-      });
-      __webpack_require__.d(__webpack_exports__, "valueAndGrad", function () {
-        return /* reexport */ valueAndGrad;
-      });
-      __webpack_require__.d(__webpack_exports__, "valueAndGrads", function () {
-        return /* reexport */ valueAndGrads;
-      });
-      __webpack_require__.d(__webpack_exports__, "variableGrads", function () {
-        return /* reexport */ variableGrads;
-      });
-      __webpack_require__.d(__webpack_exports__, "Environment", function () {
-        return /* reexport */ environment["b" /* Environment */];
-      });
-      __webpack_require__.d(__webpack_exports__, "env", function () {
-        return /* reexport */ environment["c" /* env */];
-      });
-      __webpack_require__.d(__webpack_exports__, "ENV", function () {
-        return /* reexport */ environment["a" /* ENV */];
-      });
-      __webpack_require__.d(__webpack_exports__, "version_core", function () {
-        return /* reexport */ version;
-      });
-      __webpack_require__.d(__webpack_exports__, "nextFrame", function () {
-        return /* reexport */ browser_util["a" /* nextFrame */];
-      });
-      __webpack_require__.d(__webpack_exports__, "browser", function () {
-        return /* reexport */ browser_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "io", function () {
-        return /* reexport */ io_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "math", function () {
-        return /* reexport */ math_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "serialization", function () {
-        return /* reexport */ serialization_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "test_util", function () {
-        return /* reexport */ test_util_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "util", function () {
-        return /* reexport */ util;
-      });
-      __webpack_require__.d(__webpack_exports__, "backend_util", function () {
-        return /* reexport */ backend_util_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "tensor_util", function () {
-        return /* reexport */ tensor_util;
-      });
-      __webpack_require__.d(__webpack_exports__, "slice_util", function () {
-        return /* reexport */ slice_util_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "gather_util", function () {
-        return /* reexport */ gather_nd_util_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "scatter_util", function () {
-        return /* reexport */ scatter_nd_util_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "device_util", function () {
-        return /* reexport */ device_util;
-      });
-      __webpack_require__.d(__webpack_exports__, "kernel_impls", function () {
-        return /* reexport */ kernel_impls_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "KernelBackend", function () {
-        return /* reexport */ KernelBackend;
-      });
-      __webpack_require__.d(__webpack_exports__, "DataStorage", function () {
-        return /* reexport */ DataStorage;
-      });
-      __webpack_require__.d(__webpack_exports__, "Add", function () {
-        return /* reexport */ kernel_names["a" /* Add */];
-      });
-      __webpack_require__.d(__webpack_exports__, "AddN", function () {
-        return /* reexport */ kernel_names["b" /* AddN */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Atan2", function () {
-        return /* reexport */ kernel_names["c" /* Atan2 */];
-      });
-      __webpack_require__.d(__webpack_exports__, "AvgPool", function () {
-        return /* reexport */ kernel_names["d" /* AvgPool */];
-      });
-      __webpack_require__.d(__webpack_exports__, "AvgPoolBackprop", function () {
-        return /* reexport */ kernel_names["g" /* AvgPoolBackprop */];
-      });
-      __webpack_require__.d(__webpack_exports__, "AvgPool3D", function () {
-        return /* reexport */ kernel_names["e" /* AvgPool3D */];
-      });
-      __webpack_require__.d(__webpack_exports__, "AvgPool3DBackprop", function () {
-        return /* reexport */ kernel_names["f" /* AvgPool3DBackprop */];
-      });
-      __webpack_require__.d(__webpack_exports__, "BatchMatMul", function () {
-        return /* reexport */ kernel_names["h" /* BatchMatMul */];
-      });
-      __webpack_require__.d(__webpack_exports__, "BatchToSpaceND", function () {
-        return /* reexport */ kernel_names["i" /* BatchToSpaceND */];
-      });
-      __webpack_require__.d(__webpack_exports__, "BroadcastTo", function () {
-        return /* reexport */ kernel_names["j" /* BroadcastTo */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Complex", function () {
-        return /* reexport */ kernel_names["k" /* Complex */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Concat", function () {
-        return /* reexport */ kernel_names["l" /* Concat */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Conv2D", function () {
-        return /* reexport */ kernel_names["m" /* Conv2D */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Conv2DBackpropFilter", function () {
-        return /* reexport */ kernel_names["n" /* Conv2DBackpropFilter */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Conv2DBackpropInput", function () {
-        return /* reexport */ kernel_names["o" /* Conv2DBackpropInput */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Conv3D", function () {
-        return /* reexport */ kernel_names["p" /* Conv3D */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Conv3DBackpropFilterV2", function () {
-        return /* reexport */ kernel_names["q" /* Conv3DBackpropFilterV2 */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Conv3DBackpropInputV2", function () {
-        return /* reexport */ kernel_names["r" /* Conv3DBackpropInputV2 */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Cumsum", function () {
-        return /* reexport */ kernel_names["s" /* Cumsum */];
-      });
-      __webpack_require__.d(__webpack_exports__, "DepthToSpace", function () {
-        return /* reexport */ kernel_names["t" /* DepthToSpace */];
-      });
-      __webpack_require__.d(__webpack_exports__, "DepthwiseConv2dNative", function () {
-        return /* reexport */ kernel_names["u" /* DepthwiseConv2dNative */];
-      });
-      __webpack_require__.d(
-        __webpack_exports__,
-        "DepthwiseConv2dNativeBackpropFilter",
-        function () {
-          return /* reexport */ kernel_names["v" /* DepthwiseConv2dNativeBackpropFilter */];
-        }
-      );
-      __webpack_require__.d(__webpack_exports__, "DepthwiseConv2dNativeBackpropInput", function () {
-        return /* reexport */ kernel_names["w" /* DepthwiseConv2dNativeBackpropInput */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Diag", function () {
-        return /* reexport */ kernel_names["x" /* Diag */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Div", function () {
-        return /* reexport */ kernel_names["y" /* Div */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Elu", function () {
-        return /* reexport */ kernel_names["z" /* Elu */];
-      });
-      __webpack_require__.d(__webpack_exports__, "EluGrad", function () {
-        return /* reexport */ kernel_names["A" /* EluGrad */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Equal", function () {
-        return /* reexport */ kernel_names["B" /* Equal */];
-      });
-      __webpack_require__.d(__webpack_exports__, "FloorDiv", function () {
-        return /* reexport */ kernel_names["D" /* FloorDiv */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Fill", function () {
-        return /* reexport */ kernel_names["C" /* Fill */];
-      });
-      __webpack_require__.d(__webpack_exports__, "FusedBatchNorm", function () {
-        return /* reexport */ kernel_names["F" /* FusedBatchNorm */];
-      });
-      __webpack_require__.d(__webpack_exports__, "GatherNd", function () {
-        return /* reexport */ kernel_names["G" /* GatherNd */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Greater", function () {
-        return /* reexport */ kernel_names["H" /* Greater */];
-      });
-      __webpack_require__.d(__webpack_exports__, "GreaterEqual", function () {
-        return /* reexport */ kernel_names["I" /* GreaterEqual */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Identity", function () {
-        return /* reexport */ kernel_names["J" /* Identity */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Imag", function () {
-        return /* reexport */ kernel_names["K" /* Imag */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Less", function () {
-        return /* reexport */ kernel_names["N" /* Less */];
-      });
-      __webpack_require__.d(__webpack_exports__, "LessEqual", function () {
-        return /* reexport */ kernel_names["O" /* LessEqual */];
-      });
-      __webpack_require__.d(__webpack_exports__, "LRN", function () {
-        return /* reexport */ kernel_names["L" /* LRN */];
-      });
-      __webpack_require__.d(__webpack_exports__, "LRNBackprop", function () {
-        return /* reexport */ kernel_names["M" /* LRNBackprop */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Max", function () {
-        return /* reexport */ kernel_names["P" /* Max */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Maximum", function () {
-        return /* reexport */ kernel_names["V" /* Maximum */];
-      });
-      __webpack_require__.d(__webpack_exports__, "MaxPool", function () {
-        return /* reexport */ kernel_names["Q" /* MaxPool */];
-      });
-      __webpack_require__.d(__webpack_exports__, "MaxPoolBackprop", function () {
-        return /* reexport */ kernel_names["T" /* MaxPoolBackprop */];
-      });
-      __webpack_require__.d(__webpack_exports__, "MaxPool3D", function () {
-        return /* reexport */ kernel_names["R" /* MaxPool3D */];
-      });
-      __webpack_require__.d(__webpack_exports__, "MaxPool3DBackprop", function () {
-        return /* reexport */ kernel_names["S" /* MaxPool3DBackprop */];
-      });
-      __webpack_require__.d(__webpack_exports__, "MaxPoolWithArgmax", function () {
-        return /* reexport */ kernel_names["U" /* MaxPoolWithArgmax */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Minimum", function () {
-        return /* reexport */ kernel_names["W" /* Minimum */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Mod", function () {
-        return /* reexport */ kernel_names["X" /* Mod */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Multiply", function () {
-        return /* reexport */ kernel_names["Y" /* Multiply */];
-      });
-      __webpack_require__.d(__webpack_exports__, "NotEqual", function () {
-        return /* reexport */ kernel_names["bb" /* NotEqual */];
-      });
-      __webpack_require__.d(__webpack_exports__, "NonMaxSuppressionV3", function () {
-        return /* reexport */ kernel_names["Z" /* NonMaxSuppressionV3 */];
-      });
-      __webpack_require__.d(__webpack_exports__, "NonMaxSuppressionV5", function () {
-        return /* reexport */ kernel_names["ab" /* NonMaxSuppressionV5 */];
-      });
-      __webpack_require__.d(__webpack_exports__, "OneHot", function () {
-        return /* reexport */ kernel_names["cb" /* OneHot */];
-      });
-      __webpack_require__.d(__webpack_exports__, "PadV2", function () {
-        return /* reexport */ kernel_names["db" /* PadV2 */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Pool", function () {
-        return /* reexport */ kernel_names["eb" /* Pool */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Pow", function () {
-        return /* reexport */ kernel_names["fb" /* Pow */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Prelu", function () {
-        return /* reexport */ kernel_names["gb" /* Prelu */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Real", function () {
-        return /* reexport */ kernel_names["hb" /* Real */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Relu", function () {
-        return /* reexport */ kernel_names["ib" /* Relu */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Relu6", function () {
-        return /* reexport */ kernel_names["jb" /* Relu6 */];
-      });
-      __webpack_require__.d(__webpack_exports__, "SelectV2", function () {
-        return /* reexport */ kernel_names["kb" /* SelectV2 */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Selu", function () {
-        return /* reexport */ kernel_names["lb" /* Selu */];
-      });
-      __webpack_require__.d(__webpack_exports__, "SpaceToBatchND", function () {
-        return /* reexport */ kernel_names["mb" /* SpaceToBatchND */];
-      });
-      __webpack_require__.d(__webpack_exports__, "SplitV", function () {
-        return /* reexport */ kernel_names["nb" /* SplitV */];
-      });
-      __webpack_require__.d(__webpack_exports__, "SquaredDifference", function () {
-        return /* reexport */ kernel_names["pb" /* SquaredDifference */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Square", function () {
-        return /* reexport */ kernel_names["ob" /* Square */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Sub", function () {
-        return /* reexport */ kernel_names["qb" /* Sub */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Tile", function () {
-        return /* reexport */ kernel_names["rb" /* Tile */];
-      });
-      __webpack_require__.d(__webpack_exports__, "Transpose", function () {
-        return /* reexport */ kernel_names["sb" /* Transpose */];
-      });
-      __webpack_require__.d(__webpack_exports__, "FromPixels", function () {
-        return /* reexport */ kernel_names["E" /* FromPixels */];
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/slice_util.js
-      var slice_util_namespaceObject = {};
-      __webpack_require__.r(slice_util_namespaceObject);
-      __webpack_require__.d(slice_util_namespaceObject, "assertParamsValid", function () {
-        return assertParamsValid;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "maskToAxes", function () {
-        return maskToAxes;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "computeOutShape", function () {
-        return slice_util_computeOutShape;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "stridesWithElidedDims", function () {
-        return stridesWithElidedDims;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "startIndicesWithElidedDims", function () {
-        return startIndicesWithElidedDims;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "stopIndicesWithElidedDims", function () {
-        return stopIndicesWithElidedDims;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "stridesForAxis", function () {
-        return stridesForAxis;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "startForAxis", function () {
-        return startForAxis;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "stopForAxis", function () {
-        return stopForAxis;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "isSliceContinous", function () {
-        return isSliceContinous;
-      });
-      __webpack_require__.d(slice_util_namespaceObject, "computeFlatOffset", function () {
-        return computeFlatOffset;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/io/io.js
-      var io_namespaceObject = {};
-      __webpack_require__.r(io_namespaceObject);
-      __webpack_require__.d(io_namespaceObject, "copyModel", function () {
-        return copyModel;
-      });
-      __webpack_require__.d(io_namespaceObject, "listModels", function () {
-        return listModels;
-      });
-      __webpack_require__.d(io_namespaceObject, "moveModel", function () {
-        return moveModel;
-      });
-      __webpack_require__.d(io_namespaceObject, "removeModel", function () {
-        return removeModel;
-      });
-      __webpack_require__.d(io_namespaceObject, "browserFiles", function () {
-        return browserFiles;
-      });
-      __webpack_require__.d(io_namespaceObject, "browserHTTPRequest", function () {
-        return browserHTTPRequest;
-      });
-      __webpack_require__.d(io_namespaceObject, "concatenateArrayBuffers", function () {
-        return io_utils["d" /* concatenateArrayBuffers */];
-      });
-      __webpack_require__.d(io_namespaceObject, "decodeWeights", function () {
-        return io_utils["e" /* decodeWeights */];
-      });
-      __webpack_require__.d(io_namespaceObject, "encodeWeights", function () {
-        return io_utils["f" /* encodeWeights */];
-      });
-      __webpack_require__.d(io_namespaceObject, "fromMemory", function () {
-        return fromMemory;
-      });
-      __webpack_require__.d(io_namespaceObject, "getLoadHandlers", function () {
-        return getLoadHandlers;
-      });
-      __webpack_require__.d(io_namespaceObject, "getModelArtifactsInfoForJSON", function () {
-        return io_utils["g" /* getModelArtifactsInfoForJSON */];
-      });
-      __webpack_require__.d(io_namespaceObject, "getSaveHandlers", function () {
-        return getSaveHandlers;
-      });
-      __webpack_require__.d(io_namespaceObject, "http", function () {
-        return http;
-      });
-      __webpack_require__.d(io_namespaceObject, "isHTTPScheme", function () {
-        return isHTTPScheme;
-      });
-      __webpack_require__.d(io_namespaceObject, "loadWeights", function () {
-        return loadWeights;
-      });
-      __webpack_require__.d(io_namespaceObject, "registerLoadRouter", function () {
-        return registerLoadRouter;
-      });
-      __webpack_require__.d(io_namespaceObject, "registerSaveRouter", function () {
-        return registerSaveRouter;
-      });
-      __webpack_require__.d(io_namespaceObject, "weightsLoaderFactory", function () {
-        return weightsLoaderFactory;
-      });
-      __webpack_require__.d(io_namespaceObject, "withSaveHandler", function () {
-        return withSaveHandler;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/math.js
-      var math_namespaceObject = {};
-      __webpack_require__.r(math_namespaceObject);
-      __webpack_require__.d(math_namespaceObject, "confusionMatrix", function () {
-        return confusionMatrix;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/browser.js
-      var browser_namespaceObject = {};
-      __webpack_require__.r(browser_namespaceObject);
-      __webpack_require__.d(browser_namespaceObject, "toPixels", function () {
-        return toPixels;
-      });
-      __webpack_require__.d(browser_namespaceObject, "fromPixels", function () {
-        return fromPixels;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd_util.js
-      var gather_nd_util_namespaceObject = {};
-      __webpack_require__.r(gather_nd_util_namespaceObject);
-      __webpack_require__.d(gather_nd_util_namespaceObject, "prepareAndValidate", function () {
-        return prepareAndValidate;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd_util.js
-      var scatter_nd_util_namespaceObject = {};
-      __webpack_require__.r(scatter_nd_util_namespaceObject);
-      __webpack_require__.d(scatter_nd_util_namespaceObject, "validateUpdateShape", function () {
-        return validateUpdateShape;
-      });
-      __webpack_require__.d(scatter_nd_util_namespaceObject, "validateInput", function () {
-        return validateInput;
-      });
-      __webpack_require__.d(scatter_nd_util_namespaceObject, "calculateShapes", function () {
-        return calculateShapes;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/serialization.js
-      var serialization_namespaceObject = {};
-      __webpack_require__.r(serialization_namespaceObject);
-      __webpack_require__.d(serialization_namespaceObject, "Serializable", function () {
-        return Serializable;
-      });
-      __webpack_require__.d(serialization_namespaceObject, "SerializationMap", function () {
-        return SerializationMap;
-      });
-      __webpack_require__.d(serialization_namespaceObject, "registerClass", function () {
-        return registerClass;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/test_util.js
-      var test_util_namespaceObject = {};
-      __webpack_require__.r(test_util_namespaceObject);
-      __webpack_require__.d(test_util_namespaceObject, "TEST_EPSILON_FLOAT16", function () {
-        return TEST_EPSILON_FLOAT16;
-      });
-      __webpack_require__.d(test_util_namespaceObject, "expectArraysClose", function () {
-        return expectArraysClose;
-      });
-      __webpack_require__.d(test_util_namespaceObject, "testEpsilon", function () {
-        return testEpsilon;
-      });
-      __webpack_require__.d(test_util_namespaceObject, "expectPromiseToFail", function () {
-        return expectPromiseToFail;
-      });
-      __webpack_require__.d(test_util_namespaceObject, "expectArraysEqual", function () {
-        return expectArraysEqual;
-      });
-      __webpack_require__.d(test_util_namespaceObject, "expectNumbersClose", function () {
-        return expectNumbersClose;
-      });
-      __webpack_require__.d(test_util_namespaceObject, "expectValuesInRange", function () {
-        return expectValuesInRange;
-      });
-      __webpack_require__.d(test_util_namespaceObject, "expectArrayBuffersEqual", function () {
-        return expectArrayBuffersEqual;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/segment_util.js
-      var segment_util_namespaceObject = {};
-      __webpack_require__.r(segment_util_namespaceObject);
-      __webpack_require__.d(
-        segment_util_namespaceObject,
-        "segOpComputeOptimalWindowSize",
-        function () {
-          return segOpComputeOptimalWindowSize;
-        }
-      );
-      __webpack_require__.d(segment_util_namespaceObject, "computeOutShape", function () {
-        return segment_util_computeOutShape;
-      });
-      __webpack_require__.d(segment_util_namespaceObject, "collectGatherOpShapeInfo", function () {
-        return collectGatherOpShapeInfo;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/spectral_ops.js
-      var spectral_ops_namespaceObject = {};
-      __webpack_require__.r(spectral_ops_namespaceObject);
-      __webpack_require__.d(spectral_ops_namespaceObject, "fft", function () {
-        return fft;
-      });
-      __webpack_require__.d(spectral_ops_namespaceObject, "ifft", function () {
-        return ifft;
-      });
-      __webpack_require__.d(spectral_ops_namespaceObject, "rfft", function () {
-        return rfft;
-      });
-      __webpack_require__.d(spectral_ops_namespaceObject, "irfft", function () {
-        return irfft;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/signal_ops.js
-      var signal_ops_namespaceObject = {};
-      __webpack_require__.r(signal_ops_namespaceObject);
-      __webpack_require__.d(signal_ops_namespaceObject, "hannWindow", function () {
-        return hannWindow;
-      });
-      __webpack_require__.d(signal_ops_namespaceObject, "hammingWindow", function () {
-        return hammingWindow;
-      });
-      __webpack_require__.d(signal_ops_namespaceObject, "frame", function () {
-        return signal_ops_frame;
-      });
-      __webpack_require__.d(signal_ops_namespaceObject, "stft", function () {
-        return stft;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/loss_ops.js
-      var loss_ops_namespaceObject = {};
-      __webpack_require__.r(loss_ops_namespaceObject);
-      __webpack_require__.d(loss_ops_namespaceObject, "Reduction", function () {
-        return Reduction;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "absoluteDifference", function () {
-        return absoluteDifference;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "computeWeightedLoss", function () {
-        return computeWeightedLoss;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "cosineDistance", function () {
-        return cosineDistance;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "hingeLoss", function () {
-        return hingeLoss;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "huberLoss", function () {
-        return huberLoss;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "logLoss", function () {
-        return logLoss;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "meanSquaredError", function () {
-        return meanSquaredError;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "sigmoidCrossEntropy", function () {
-        return sigmoidCrossEntropy;
-      });
-      __webpack_require__.d(loss_ops_namespaceObject, "softmaxCrossEntropy", function () {
-        return softmaxCrossEntropy;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/linalg_ops.js
-      var linalg_ops_namespaceObject = {};
-      __webpack_require__.r(linalg_ops_namespaceObject);
-      __webpack_require__.d(linalg_ops_namespaceObject, "bandPart", function () {
-        return bandPart;
-      });
-      __webpack_require__.d(linalg_ops_namespaceObject, "gramSchmidt", function () {
-        return gramSchmidt;
-      });
-      __webpack_require__.d(linalg_ops_namespaceObject, "qr", function () {
-        return qr;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/image_ops.js
-      var image_ops_namespaceObject = {};
-      __webpack_require__.r(image_ops_namespaceObject);
-      __webpack_require__.d(image_ops_namespaceObject, "nonMaxSuppression", function () {
-        return nonMaxSuppression;
-      });
-      __webpack_require__.d(image_ops_namespaceObject, "resizeBilinear", function () {
-        return resizeBilinear;
-      });
-      __webpack_require__.d(image_ops_namespaceObject, "resizeNearestNeighbor", function () {
-        return resizeNearestNeighbor;
-      });
-      __webpack_require__.d(image_ops_namespaceObject, "nonMaxSuppressionAsync", function () {
-        return nonMaxSuppressionAsync;
-      });
-      __webpack_require__.d(image_ops_namespaceObject, "nonMaxSuppressionWithScore", function () {
-        return nonMaxSuppressionWithScore;
-      });
-      __webpack_require__.d(
-        image_ops_namespaceObject,
-        "nonMaxSuppressionWithScoreAsync",
-        function () {
-          return nonMaxSuppressionWithScoreAsync;
-        }
-      );
-      __webpack_require__.d(image_ops_namespaceObject, "cropAndResize", function () {
-        return cropAndResize;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/fused_ops.js
-      var fused_ops_namespaceObject = {};
-      __webpack_require__.r(fused_ops_namespaceObject);
-      __webpack_require__.d(fused_ops_namespaceObject, "matMul", function () {
-        return fused_ops_matMul;
-      });
-      __webpack_require__.d(fused_ops_namespaceObject, "conv2d", function () {
-        return fused_ops_conv2d;
-      });
-      __webpack_require__.d(fused_ops_namespaceObject, "depthwiseConv2d", function () {
-        return fused_ops_depthwiseConv2d;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/ops.js
-      var ops_namespaceObject = {};
-      __webpack_require__.r(ops_namespaceObject);
-      __webpack_require__.d(ops_namespaceObject, "add", function () {
-        return add;
-      });
-      __webpack_require__.d(ops_namespaceObject, "addN", function () {
-        return addN;
-      });
-      __webpack_require__.d(ops_namespaceObject, "atan2", function () {
-        return atan2;
-      });
-      __webpack_require__.d(ops_namespaceObject, "avgPool", function () {
-        return avgPool;
-      });
-      __webpack_require__.d(ops_namespaceObject, "avgPool3d", function () {
-        return avgPool3d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "batchToSpaceND", function () {
-        return batchToSpaceND;
-      });
-      __webpack_require__.d(ops_namespaceObject, "batchNorm", function () {
-        return batchNorm;
-      });
-      __webpack_require__.d(ops_namespaceObject, "batchNorm2d", function () {
-        return batchNorm2d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "batchNorm3d", function () {
-        return batchNorm3d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "batchNorm4d", function () {
-        return batchNorm4d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "broadcastTo", function () {
-        return broadcastTo;
-      });
-      __webpack_require__.d(ops_namespaceObject, "clone", function () {
-        return clone;
-      });
-      __webpack_require__.d(ops_namespaceObject, "complex", function () {
-        return complex["a" /* complex */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "concat", function () {
-        return concat;
-      });
-      __webpack_require__.d(ops_namespaceObject, "concat1d", function () {
-        return concat1d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "concat2d", function () {
-        return concat2d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "concat3d", function () {
-        return concat3d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "concat4d", function () {
-        return concat4d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "conv1d", function () {
-        return conv1d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "conv2d", function () {
-        return conv2d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "conv2dTranspose", function () {
-        return conv2dTranspose;
-      });
-      __webpack_require__.d(ops_namespaceObject, "conv3d", function () {
-        return conv3d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "conv3dTranspose", function () {
-        return conv3dTranspose;
-      });
-      __webpack_require__.d(ops_namespaceObject, "cumsum", function () {
-        return cumsum;
-      });
-      __webpack_require__.d(ops_namespaceObject, "depthToSpace", function () {
-        return depthToSpace;
-      });
-      __webpack_require__.d(ops_namespaceObject, "depthwiseConv2d", function () {
-        return depthwiseConv2d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "diag", function () {
-        return diag;
-      });
-      __webpack_require__.d(ops_namespaceObject, "div", function () {
-        return div;
-      });
-      __webpack_require__.d(ops_namespaceObject, "divNoNan", function () {
-        return divNoNan;
-      });
-      __webpack_require__.d(ops_namespaceObject, "dot", function () {
-        return dot;
-      });
-      __webpack_require__.d(ops_namespaceObject, "elu", function () {
-        return elu;
-      });
-      __webpack_require__.d(ops_namespaceObject, "equal", function () {
-        return equal;
-      });
-      __webpack_require__.d(ops_namespaceObject, "eye", function () {
-        return eye;
-      });
-      __webpack_require__.d(ops_namespaceObject, "fill", function () {
-        return fill;
-      });
-      __webpack_require__.d(ops_namespaceObject, "floorDiv", function () {
-        return floorDiv;
-      });
-      __webpack_require__.d(ops_namespaceObject, "greater", function () {
-        return greater;
-      });
-      __webpack_require__.d(ops_namespaceObject, "greaterEqual", function () {
-        return greaterEqual;
-      });
-      __webpack_require__.d(ops_namespaceObject, "imag", function () {
-        return imag["a" /* imag */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "leakyRelu", function () {
-        return leakyRelu;
-      });
-      __webpack_require__.d(ops_namespaceObject, "less", function () {
-        return less;
-      });
-      __webpack_require__.d(ops_namespaceObject, "lessEqual", function () {
-        return lessEqual;
-      });
-      __webpack_require__.d(ops_namespaceObject, "localResponseNormalization", function () {
-        return localResponseNormalization;
-      });
-      __webpack_require__.d(ops_namespaceObject, "matMul", function () {
-        return matMul;
-      });
-      __webpack_require__.d(ops_namespaceObject, "max", function () {
-        return max_max;
-      });
-      __webpack_require__.d(ops_namespaceObject, "maxPool", function () {
-        return maxPool;
-      });
-      __webpack_require__.d(ops_namespaceObject, "maxPool3d", function () {
-        return maxPool3d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "maxPoolWithArgmax", function () {
-        return maxPoolWithArgmax;
-      });
-      __webpack_require__.d(ops_namespaceObject, "maximum", function () {
-        return maximum;
-      });
-      __webpack_require__.d(ops_namespaceObject, "minimum", function () {
-        return minimum;
-      });
-      __webpack_require__.d(ops_namespaceObject, "mod", function () {
-        return mod;
-      });
-      __webpack_require__.d(ops_namespaceObject, "mul", function () {
-        return mul;
-      });
-      __webpack_require__.d(ops_namespaceObject, "multinomial", function () {
-        return multinomial;
-      });
-      __webpack_require__.d(ops_namespaceObject, "notEqual", function () {
-        return notEqual;
-      });
-      __webpack_require__.d(ops_namespaceObject, "oneHot", function () {
-        return oneHot;
-      });
-      __webpack_require__.d(ops_namespaceObject, "outerProduct", function () {
-        return outerProduct;
-      });
-      __webpack_require__.d(ops_namespaceObject, "pad", function () {
-        return pad_pad;
-      });
-      __webpack_require__.d(ops_namespaceObject, "pad1d", function () {
-        return pad1d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "pad2d", function () {
-        return pad2d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "pad3d", function () {
-        return pad3d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "pad4d", function () {
-        return pad4d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "pool", function () {
-        return pool;
-      });
-      __webpack_require__.d(ops_namespaceObject, "pow", function () {
-        return pow;
-      });
-      __webpack_require__.d(ops_namespaceObject, "prelu", function () {
-        return prelu;
-      });
-      __webpack_require__.d(ops_namespaceObject, "rand", function () {
-        return rand;
-      });
-      __webpack_require__.d(ops_namespaceObject, "randomGamma", function () {
-        return randomGamma;
-      });
-      __webpack_require__.d(ops_namespaceObject, "randomNormal", function () {
-        return randomNormal;
-      });
-      __webpack_require__.d(ops_namespaceObject, "randomUniform", function () {
-        return randomUniform;
-      });
-      __webpack_require__.d(ops_namespaceObject, "real", function () {
-        return real["a" /* real */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "relu", function () {
-        return relu;
-      });
-      __webpack_require__.d(ops_namespaceObject, "relu6", function () {
-        return relu6;
-      });
-      __webpack_require__.d(ops_namespaceObject, "selu", function () {
-        return selu;
-      });
-      __webpack_require__.d(ops_namespaceObject, "separableConv2d", function () {
-        return separableConv2d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "spaceToBatchND", function () {
-        return spaceToBatchND;
-      });
-      __webpack_require__.d(ops_namespaceObject, "split", function () {
-        return split;
-      });
-      __webpack_require__.d(ops_namespaceObject, "square", function () {
-        return square;
-      });
-      __webpack_require__.d(ops_namespaceObject, "squaredDifference", function () {
-        return squaredDifference;
-      });
-      __webpack_require__.d(ops_namespaceObject, "sub", function () {
-        return sub;
-      });
-      __webpack_require__.d(ops_namespaceObject, "tile", function () {
-        return tile;
-      });
-      __webpack_require__.d(ops_namespaceObject, "truncatedNormal", function () {
-        return truncatedNormal;
-      });
-      __webpack_require__.d(ops_namespaceObject, "booleanMaskAsync", function () {
-        return booleanMaskAsync;
-      });
-      __webpack_require__.d(ops_namespaceObject, "reverse", function () {
-        return reverse_reverse;
-      });
-      __webpack_require__.d(ops_namespaceObject, "reverse1d", function () {
-        return reverse1d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "reverse2d", function () {
-        return reverse2d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "reverse3d", function () {
-        return reverse3d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "reverse4d", function () {
-        return reverse4d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "slice", function () {
-        return slice;
-      });
-      __webpack_require__.d(ops_namespaceObject, "slice1d", function () {
-        return slice1d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "slice2d", function () {
-        return slice2d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "slice3d", function () {
-        return slice3d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "slice4d", function () {
-        return slice4d;
-      });
-      __webpack_require__.d(ops_namespaceObject, "abs", function () {
-        return abs;
-      });
-      __webpack_require__.d(ops_namespaceObject, "acos", function () {
-        return acos;
-      });
-      __webpack_require__.d(ops_namespaceObject, "acosh", function () {
-        return acosh;
-      });
-      __webpack_require__.d(ops_namespaceObject, "asin", function () {
-        return asin;
-      });
-      __webpack_require__.d(ops_namespaceObject, "asinh", function () {
-        return asinh;
-      });
-      __webpack_require__.d(ops_namespaceObject, "atan", function () {
-        return atan;
-      });
-      __webpack_require__.d(ops_namespaceObject, "atanh", function () {
-        return atanh;
-      });
-      __webpack_require__.d(ops_namespaceObject, "ceil", function () {
-        return ceil;
-      });
-      __webpack_require__.d(ops_namespaceObject, "clipByValue", function () {
-        return clipByValue;
-      });
-      __webpack_require__.d(ops_namespaceObject, "cos", function () {
-        return cos;
-      });
-      __webpack_require__.d(ops_namespaceObject, "cosh", function () {
-        return cosh;
-      });
-      __webpack_require__.d(ops_namespaceObject, "erf", function () {
-        return erf;
-      });
-      __webpack_require__.d(ops_namespaceObject, "exp", function () {
-        return unary_ops_exp;
-      });
-      __webpack_require__.d(ops_namespaceObject, "expm1", function () {
-        return expm1;
-      });
-      __webpack_require__.d(ops_namespaceObject, "floor", function () {
-        return floor;
-      });
-      __webpack_require__.d(ops_namespaceObject, "log", function () {
-        return log;
-      });
-      __webpack_require__.d(ops_namespaceObject, "log1p", function () {
-        return log1p;
-      });
-      __webpack_require__.d(ops_namespaceObject, "logSigmoid", function () {
-        return logSigmoid;
-      });
-      __webpack_require__.d(ops_namespaceObject, "neg", function () {
-        return neg;
-      });
-      __webpack_require__.d(ops_namespaceObject, "reciprocal", function () {
-        return reciprocal;
-      });
-      __webpack_require__.d(ops_namespaceObject, "round", function () {
-        return round;
-      });
-      __webpack_require__.d(ops_namespaceObject, "rsqrt", function () {
-        return rsqrt;
-      });
-      __webpack_require__.d(ops_namespaceObject, "sigmoid", function () {
-        return sigmoid;
-      });
-      __webpack_require__.d(ops_namespaceObject, "sign", function () {
-        return sign;
-      });
-      __webpack_require__.d(ops_namespaceObject, "isNaN", function () {
-        return unary_ops_isNaN;
-      });
-      __webpack_require__.d(ops_namespaceObject, "isInf", function () {
-        return isInf;
-      });
-      __webpack_require__.d(ops_namespaceObject, "isFinite", function () {
-        return unary_ops_isFinite;
-      });
-      __webpack_require__.d(ops_namespaceObject, "sin", function () {
-        return sin;
-      });
-      __webpack_require__.d(ops_namespaceObject, "sinh", function () {
-        return sinh;
-      });
-      __webpack_require__.d(ops_namespaceObject, "softplus", function () {
-        return softplus;
-      });
-      __webpack_require__.d(ops_namespaceObject, "sqrt", function () {
-        return sqrt;
-      });
-      __webpack_require__.d(ops_namespaceObject, "step", function () {
-        return unary_ops_step;
-      });
-      __webpack_require__.d(ops_namespaceObject, "tan", function () {
-        return tan;
-      });
-      __webpack_require__.d(ops_namespaceObject, "tanh", function () {
-        return tanh;
-      });
-      __webpack_require__.d(ops_namespaceObject, "all", function () {
-        return reduction_ops_all;
-      });
-      __webpack_require__.d(ops_namespaceObject, "any", function () {
-        return any;
-      });
-      __webpack_require__.d(ops_namespaceObject, "argMax", function () {
-        return argMax;
-      });
-      __webpack_require__.d(ops_namespaceObject, "argMin", function () {
-        return argMin;
-      });
-      __webpack_require__.d(ops_namespaceObject, "logSumExp", function () {
-        return logSumExp;
-      });
-      __webpack_require__.d(ops_namespaceObject, "mean", function () {
-        return reduction_ops_mean;
-      });
-      __webpack_require__.d(ops_namespaceObject, "min", function () {
-        return reduction_ops_min;
-      });
-      __webpack_require__.d(ops_namespaceObject, "moments", function () {
-        return moments;
-      });
-      __webpack_require__.d(ops_namespaceObject, "sum", function () {
-        return sum;
-      });
-      __webpack_require__.d(ops_namespaceObject, "prod", function () {
-        return reduction_ops_prod;
-      });
-      __webpack_require__.d(ops_namespaceObject, "equalStrict", function () {
-        return equalStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "greaterEqualStrict", function () {
-        return greaterEqualStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "greaterStrict", function () {
-        return greaterStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "lessEqualStrict", function () {
-        return lessEqualStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "lessStrict", function () {
-        return lessStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "notEqualStrict", function () {
-        return notEqualStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "addStrict", function () {
-        return addStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "divStrict", function () {
-        return divStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "maximumStrict", function () {
-        return maximumStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "minimumStrict", function () {
-        return minimumStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "modStrict", function () {
-        return modStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "mulStrict", function () {
-        return mulStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "powStrict", function () {
-        return powStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "squaredDifferenceStrict", function () {
-        return squaredDifferenceStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "subStrict", function () {
-        return subStrict;
-      });
-      __webpack_require__.d(ops_namespaceObject, "logicalAnd", function () {
-        return logicalAnd;
-      });
-      __webpack_require__.d(ops_namespaceObject, "logicalNot", function () {
-        return logicalNot;
-      });
-      __webpack_require__.d(ops_namespaceObject, "logicalOr", function () {
-        return logicalOr;
-      });
-      __webpack_require__.d(ops_namespaceObject, "logicalXor", function () {
-        return logicalXor;
-      });
-      __webpack_require__.d(ops_namespaceObject, "where", function () {
-        return where;
-      });
-      __webpack_require__.d(ops_namespaceObject, "whereAsync", function () {
-        return whereAsync;
-      });
-      __webpack_require__.d(ops_namespaceObject, "buffer", function () {
-        return array_ops_buffer;
-      });
-      __webpack_require__.d(ops_namespaceObject, "print", function () {
-        return print;
-      });
-      __webpack_require__.d(ops_namespaceObject, "cast", function () {
-        return cast;
-      });
-      __webpack_require__.d(ops_namespaceObject, "expandDims", function () {
-        return expandDims;
-      });
-      __webpack_require__.d(ops_namespaceObject, "reshape", function () {
-        return reshape;
-      });
-      __webpack_require__.d(ops_namespaceObject, "squeeze", function () {
-        return squeeze;
-      });
-      __webpack_require__.d(ops_namespaceObject, "stack", function () {
-        return stack;
-      });
-      __webpack_require__.d(ops_namespaceObject, "unstack", function () {
-        return unstack;
-      });
-      __webpack_require__.d(ops_namespaceObject, "setdiff1dAsync", function () {
-        return setdiff1dAsync;
-      });
-      __webpack_require__.d(ops_namespaceObject, "linspace", function () {
-        return tensor_ops["a" /* linspace */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "ones", function () {
-        return tensor_ops["b" /* ones */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "range", function () {
-        return tensor_ops["d" /* range */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "scalar", function () {
-        return tensor_ops["e" /* scalar */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "tensor", function () {
-        return tensor_ops["f" /* tensor */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "tensor1d", function () {
-        return tensor_ops["g" /* tensor1d */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "tensor2d", function () {
-        return tensor_ops["h" /* tensor2d */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "tensor3d", function () {
-        return tensor_ops["i" /* tensor3d */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "tensor4d", function () {
-        return tensor_ops["j" /* tensor4d */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "tensor5d", function () {
-        return tensor_ops["k" /* tensor5d */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "tensor6d", function () {
-        return tensor_ops["l" /* tensor6d */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "variable", function () {
-        return tensor_ops["m" /* variable */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "zeros", function () {
-        return tensor_ops["n" /* zeros */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "onesLike", function () {
-        return tensor_ops["c" /* onesLike */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "zerosLike", function () {
-        return tensor_ops["o" /* zerosLike */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "transpose", function () {
-        return transpose;
-      });
-      __webpack_require__.d(ops_namespaceObject, "softmax", function () {
-        return softmax;
-      });
-      __webpack_require__.d(ops_namespaceObject, "logSoftmax", function () {
-        return logSoftmax;
-      });
-      __webpack_require__.d(ops_namespaceObject, "norm", function () {
-        return norm_norm;
-      });
-      __webpack_require__.d(ops_namespaceObject, "gather", function () {
-        return gather;
-      });
-      __webpack_require__.d(ops_namespaceObject, "unsortedSegmentSum", function () {
-        return unsortedSegmentSum;
-      });
-      __webpack_require__.d(ops_namespaceObject, "basicLSTMCell", function () {
-        return basicLSTMCell;
-      });
-      __webpack_require__.d(ops_namespaceObject, "multiRNNCell", function () {
-        return multiRNNCell;
-      });
-      __webpack_require__.d(ops_namespaceObject, "movingAverage", function () {
-        return movingAverage;
-      });
-      __webpack_require__.d(ops_namespaceObject, "stridedSlice", function () {
-        return stridedSlice;
-      });
-      __webpack_require__.d(ops_namespaceObject, "topk", function () {
-        return topk;
-      });
-      __webpack_require__.d(ops_namespaceObject, "scatterND", function () {
-        return scatterND;
-      });
-      __webpack_require__.d(ops_namespaceObject, "fft", function () {
-        return fft;
-      });
-      __webpack_require__.d(ops_namespaceObject, "ifft", function () {
-        return ifft;
-      });
-      __webpack_require__.d(ops_namespaceObject, "rfft", function () {
-        return rfft;
-      });
-      __webpack_require__.d(ops_namespaceObject, "irfft", function () {
-        return irfft;
-      });
-      __webpack_require__.d(ops_namespaceObject, "sparseToDense", function () {
-        return sparseToDense;
-      });
-      __webpack_require__.d(ops_namespaceObject, "gatherND", function () {
-        return gatherND;
-      });
-      __webpack_require__.d(ops_namespaceObject, "dropout", function () {
-        return dropout;
-      });
-      __webpack_require__.d(ops_namespaceObject, "hannWindow", function () {
-        return hannWindow;
-      });
-      __webpack_require__.d(ops_namespaceObject, "hammingWindow", function () {
-        return hammingWindow;
-      });
-      __webpack_require__.d(ops_namespaceObject, "frame", function () {
-        return signal_ops_frame;
-      });
-      __webpack_require__.d(ops_namespaceObject, "stft", function () {
-        return stft;
-      });
-      __webpack_require__.d(ops_namespaceObject, "inTopKAsync", function () {
-        return inTopKAsync;
-      });
-      __webpack_require__.d(ops_namespaceObject, "op", function () {
-        return operation["a" /* op */];
-      });
-      __webpack_require__.d(ops_namespaceObject, "image", function () {
-        return image_ops_namespaceObject;
-      });
-      __webpack_require__.d(ops_namespaceObject, "linalg", function () {
-        return linalg_ops_namespaceObject;
-      });
-      __webpack_require__.d(ops_namespaceObject, "losses", function () {
-        return loss_ops_namespaceObject;
-      });
-      __webpack_require__.d(ops_namespaceObject, "spectral", function () {
-        return spectral_ops_namespaceObject;
-      });
-      __webpack_require__.d(ops_namespaceObject, "fused", function () {
-        return fused_ops_namespaceObject;
-      });
-      __webpack_require__.d(ops_namespaceObject, "signal", function () {
-        return signal_ops_namespaceObject;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/backends/backend_util.js
-      var backend_util_namespaceObject = {};
-      __webpack_require__.r(backend_util_namespaceObject);
-      __webpack_require__.d(backend_util_namespaceObject, "axesAreInnerMostDims", function () {
-        return axesAreInnerMostDims;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "combineLocations", function () {
-        return combineLocations;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "computeOutAndReduceShapes", function () {
-        return computeOutAndReduceShapes;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "expandShapeToKeepDim", function () {
-        return expandShapeToKeepDim;
-      });
-      __webpack_require__.d(
-        backend_util_namespaceObject,
-        "assertAxesAreInnerMostDims",
-        function () {
-          return assertAxesAreInnerMostDims;
-        }
-      );
-      __webpack_require__.d(backend_util_namespaceObject, "getAxesPermutation", function () {
-        return getAxesPermutation;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getUndoAxesPermutation", function () {
-        return getUndoAxesPermutation;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getInnerMostAxes", function () {
-        return getInnerMostAxes;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getBroadcastDims", function () {
-        return getBroadcastDims;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getReductionAxes", function () {
-        return getReductionAxes;
-      });
-      __webpack_require__.d(
-        backend_util_namespaceObject,
-        "assertAndGetBroadcastShape",
-        function () {
-          return assertAndGetBroadcastShape;
-        }
-      );
-      __webpack_require__.d(backend_util_namespaceObject, "assertParamsConsistent", function () {
-        return assertParamsConsistent;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "computeOutShape", function () {
-        return computeOutShape;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "computePool2DInfo", function () {
-        return computePool2DInfo;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "computePool3DInfo", function () {
-        return computePool3DInfo;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "computeConv2DInfo", function () {
-        return computeConv2DInfo;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "computeConv3DInfo", function () {
-        return computeConv3DInfo;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "computeDefaultPad", function () {
-        return computeDefaultPad;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "tupleValuesAreOne", function () {
-        return tupleValuesAreOne;
-      });
-      __webpack_require__.d(
-        backend_util_namespaceObject,
-        "eitherStridesOrDilationsAreOne",
-        function () {
-          return eitherStridesOrDilationsAreOne;
-        }
-      );
-      __webpack_require__.d(backend_util_namespaceObject, "convertConv2DDataFormat", function () {
-        return convertConv2DDataFormat;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "PARALLELIZE_THRESHOLD", function () {
-        return PARALLELIZE_THRESHOLD;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "computeOptimalWindowSize", function () {
-        return computeOptimalWindowSize;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "nonMaxSuppressionV3", function () {
-        return nonMaxSuppressionV3;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "nonMaxSuppressionV5", function () {
-        return nonMaxSuppressionV5;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "upcastType", function () {
-        return dist_types["c" /* upcastType */];
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getReshaped", function () {
-        return getReshaped;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getPermuted", function () {
-        return getPermuted;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getReshapedPermuted", function () {
-        return getReshapedPermuted;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getSliceBeginCoords", function () {
-        return getSliceBeginCoords;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getSliceSize", function () {
-        return getSliceSize;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "prepareAndValidate", function () {
-        return prepareAndValidate;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "validateUpdateShape", function () {
-        return validateUpdateShape;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "validateInput", function () {
-        return validateInput;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "calculateShapes", function () {
-        return calculateShapes;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "SELU_SCALEALPHA", function () {
-        return SELU_SCALEALPHA;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "SELU_SCALE", function () {
-        return SELU_SCALE;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "shouldFuse", function () {
-        return shouldFuse;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "ERF_P", function () {
-        return ERF_P;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "ERF_A1", function () {
-        return ERF_A1;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "ERF_A2", function () {
-        return ERF_A2;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "ERF_A3", function () {
-        return ERF_A3;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "ERF_A4", function () {
-        return ERF_A4;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "ERF_A5", function () {
-        return ERF_A5;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "warn", function () {
-        return warn;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "log", function () {
-        return log_log;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "mergeRealAndImagArrays", function () {
-        return mergeRealAndImagArrays;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "splitRealAndImagArrays", function () {
-        return splitRealAndImagArrays;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "complexWithEvenIndex", function () {
-        return complexWithEvenIndex;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "complexWithOddIndex", function () {
-        return complexWithOddIndex;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "getComplexWithIndex", function () {
-        return getComplexWithIndex;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "assignToTypedArray", function () {
-        return assignToTypedArray;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "exponents", function () {
-        return exponents;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "exponent", function () {
-        return exponent;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "segment_util", function () {
-        return segment_util_namespaceObject;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "castTensor", function () {
-        return castTensor;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "reshapeTensor", function () {
-        return reshapeTensor;
-      });
-      __webpack_require__.d(backend_util_namespaceObject, "linspaceImpl", function () {
-        return linspaceImpl;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/backends/kernel_impls.js
-      var kernel_impls_namespaceObject = {};
-      __webpack_require__.r(kernel_impls_namespaceObject);
-      __webpack_require__.d(kernel_impls_namespaceObject, "nonMaxSuppressionV3", function () {
-        return nonMaxSuppressionV3;
-      });
-      __webpack_require__.d(kernel_impls_namespaceObject, "nonMaxSuppressionV5", function () {
-        return nonMaxSuppressionV5;
-      });
-      __webpack_require__.d(kernel_impls_namespaceObject, "split", function () {
-        return split_shared_split;
-      });
-      __webpack_require__.d(kernel_impls_namespaceObject, "tile", function () {
-        return tile_impl_tile;
-      });
-      __webpack_require__.d(kernel_impls_namespaceObject, "topkImpl", function () {
-        return topkImpl;
-      });
-      __webpack_require__.d(kernel_impls_namespaceObject, "whereImpl", function () {
-        return whereImpl;
-      });
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/engine.js + 2 modules
-      var engine = __webpack_require__(5);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/flags.js
-      var flags = __webpack_require__(61);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/kernel_names.js
-      var kernel_names = __webpack_require__(6);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Returns the dimensions in the input shape that are broadcasted to
-       * produce the provided output shape.
-       *
-       * The returned dimensions are 0-indexed and sorted. An example:
-       * inShape = [4, 1, 3]
-       * outShape = [5, 4, 3, 3]
-       * result = [1]. Dimension 1 (2nd dimension of input) gets broadcasted 1 => 3.
-       */
-      function getBroadcastDims(inShape, outShape) {
-        const inRank = inShape.length;
-        const dims = [];
-        for (let i = 0; i < inRank; i++) {
-          const dim = inRank - 1 - i;
-          const a = inShape[dim] || 1;
-          const b = outShape[outShape.length - 1 - i] || 1;
-          if (b > 1 && a === 1) {
-            dims.unshift(dim);
-          }
-        }
-        return dims;
-      }
-      /**
-       * Returns the axes in the output space that should be reduced to produce
-       * the input space.
-       */
-      function getReductionAxes(inShape, outShape) {
-        const result = [];
-        for (let i = 0; i < outShape.length; i++) {
-          const inDim = inShape[inShape.length - i - 1];
-          const outAxis = outShape.length - i - 1;
-          const outDim = outShape[outAxis];
-          if (inDim == null || (inDim === 1 && outDim > 1)) {
-            result.unshift(outAxis);
-          }
-        }
-        return result;
-      }
-      function assertAndGetBroadcastShape(shapeA, shapeB) {
-        const result = [];
-        const l = Math.max(shapeA.length, shapeB.length);
-        for (let i = 0; i < l; i++) {
-          let a = shapeA[shapeA.length - i - 1];
-          if (a == null) {
-            a = 1;
-          }
-          let b = shapeB[shapeB.length - i - 1];
-          if (b == null) {
-            b = 1;
-          }
-          if (a === 1) {
-            result.unshift(b);
-          } else if (b === 1) {
-            result.unshift(a);
-          } else if (a !== b) {
-            const errMsg =
-              `Operands could not be broadcast together with shapes ` + `${shapeA} and ${shapeB}.`;
-            throw Error(errMsg);
-          } else {
-            result.unshift(a);
-          }
-        }
-        return result;
-      }
-      //# sourceMappingURL=broadcast_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Add_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const addGradConfig = {
-        kernelName: kernel_names["a" /* Add */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
-          const derA = () => {
-            let res = dy;
-            const reduceAxes = getReductionAxes(a.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = res.sum(reduceAxes);
-            }
-            return res.reshape(a.shape);
-          };
-          const derB = () => {
-            let res = dy;
-            const reduceAxes = getReductionAxes(b.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = res.sum(reduceAxes);
-            }
-            return res.reshape(b.shape);
-          };
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=Add_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/AddN_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const addNGradConfig = {
-        kernelName: kernel_names["b" /* AddN */],
-        saveAllInputs: true,
-        gradFunc: (dy, saved) => {
-          const ders = {};
-          saved.forEach((_, i) => {
-            ders[i] = () => dy.clone();
-          });
-          return ders;
-        },
-      };
-      //# sourceMappingURL=AddN_grad.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor_util.js
-      var tensor_util = __webpack_require__(11);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor_util_env.js
-      var tensor_util_env = __webpack_require__(3);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/operation.js
-      var operation = __webpack_require__(4);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/add.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Adds two `tf.Tensor`s element-wise, A + B. Supports broadcasting.
-       *
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3, 4]);
-       * const b = tf.tensor1d([10, 20, 30, 40]);
-       *
-       * a.add(b).print();  // or tf.add(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast add a with b.
-       * const a = tf.scalar(5);
-       * const b = tf.tensor1d([10, 20, 30, 40]);
-       *
-       * a.add(b).print();  // or tf.add(a, b)
-       * ```
-       * @param a The first `tf.Tensor` to add.
-       * @param b The second `tf.Tensor` to add. Must have the same type as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function add_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "add");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "add");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        const forward = (backend, save) => {
-          const res = backend.add($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["a" /* Add */]
-        );
-      }
-      const add = Object(operation["a" /* op */])({ add_ });
-      //# sourceMappingURL=add.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor.js + 1 modules
-      var dist_tensor = __webpack_require__(7);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/util.js
-      var util = __webpack_require__(1);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function assertParamsConsistent(shapes, axis) {
-        const rank = shapes[0].length;
-        shapes.forEach((shape, i) => {
-          util["assert"](
-            shape.length === rank,
-            () =>
-              `Error in concat${rank}D: rank of tensors[${i}] must be the same ` +
-              `as the rank of the rest (${rank})`
-          );
-        });
-        util["assert"](
-          axis >= 0 && axis < rank,
-          () => `Error in concat${rank}D: axis must be between 0 and ${rank - 1}.`
-        );
-        const firstShape = shapes[0];
-        shapes.forEach((shape, i) => {
-          for (let r = 0; r < rank; r++) {
-            util["assert"](
-              r === axis || shape[r] === firstShape[r],
-              () =>
-                `Error in concat${rank}D: Shape of tensors[${i}] (${shape}) ` +
-                `does not match the shape of the rest (${firstShape}) ` +
-                `along the non-concatenated axis ${i}.`
-            );
-          }
-        });
-      }
-      function computeOutShape(shapes, axis) {
-        const outputShape = shapes[0].slice();
-        for (let i = 1; i < shapes.length; i++) {
-          outputShape[axis] += shapes[i][axis];
-        }
-        return outputShape;
-      }
-      //# sourceMappingURL=concat_util.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/tensor_ops.js
-      var tensor_ops = __webpack_require__(8);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Concatenates a list of `tf.Tensor`s along a given axis.
-       *
-       * The tensors ranks and types must match, and their sizes must match in all
-       * dimensions except `axis`.
-       *
-       * Also available are stricter rank-specific methods that assert that
-       * `tensors` are of the given rank:
-       *   - `tf.concat1d`
-       *   - `tf.concat2d`
-       *   - `tf.concat3d`
-       *   - `tf.concat4d`
-       *
-       * Except `tf.concat1d` (which does not have axis param), all methods have
-       * same signature as this method.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2]);
-       * const b = tf.tensor1d([3, 4]);
-       * a.concat(b).print();  // or a.concat(b)
-       * ```
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2]);
-       * const b = tf.tensor1d([3, 4]);
-       * const c = tf.tensor1d([5, 6]);
-       * tf.concat([a, b, c]).print();
-       * ```
-       *
-       * ```js
-       * const a = tf.tensor2d([[1, 2], [10, 20]]);
-       * const b = tf.tensor2d([[3, 4], [30, 40]]);
-       * const axis = 1;
-       * tf.concat([a, b], axis).print();
-       * ```
-       * @param tensors A list of tensors to concatenate.
-       * @param axis The axis to concate along. Defaults to 0 (the first dim).
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      function concat_(tensors, axis = 0) {
-        Object(util["assert"])(tensors.length >= 1, () => "Pass at least one tensor to concat");
-        let $tensors = Object(tensor_util_env["b" /* convertToTensorArray */])(
-          tensors,
-          "tensors",
-          "concat"
-        );
-        if ($tensors[0].dtype === "complex64") {
-          $tensors.forEach((tensor) => {
-            if (tensor.dtype !== "complex64") {
-              throw new Error(`Cannot concatenate complex64 tensors with a tensor
-          with dtype ${tensor.dtype}. `);
-            }
-          });
-        }
-        const $axis = Object(util["parseAxisParam"])(axis, $tensors[0].shape)[0];
-        const outShape = computeOutShape(
-          $tensors.map((t) => t.shape),
-          $axis
-        );
-        if (Object(util["sizeFromShape"])(outShape) === 0) {
-          return Object(tensor_ops["f" /* tensor */])([], outShape);
-        }
-        // Keep only non-empty tensors (ignore tensors with 0 in their shape).
-        $tensors = $tensors.filter((t) => t.size > 0);
-        if ($tensors.length === 1) {
-          return $tensors[0];
-        }
-        const shapes = $tensors.map((t) => t.shape);
-        assertParamsConsistent(shapes, $axis);
-        const forward = (backend, save) => {
-          const res = backend.concat($tensors, $axis);
-          save($tensors);
-          return res;
-        };
-        const inputs = $tensors;
-        const attr = { axis };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["l" /* Concat */],
-          attr
-        );
-      }
-      const concat = Object(operation["a" /* op */])({ concat_ });
-      //# sourceMappingURL=concat.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/array_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Reshapes a `tf.Tensor` to a given shape.
-       *
-       * Given an input tensor, returns a new tensor with the same values as the
-       * input tensor with shape `shape`.
-       *
-       * If one component of shape is the special value -1, the size of that
-       * dimension is computed so that the total size remains constant. In
-       * particular, a shape of [-1] flattens into 1-D. At most one component of
-       * shape can be -1.
-       *
-       * If shape is 1-D or higher, then the operation returns a tensor with shape
-       * shape filled with the values of tensor. In this case, the number of
-       * elements implied by shape must be the same as the number of elements in
-       * tensor.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       * x.reshape([2, 2]).print();
-       * ```
-       *
-       * @param x The input tensor to be reshaped.
-       * @param shape An array of integers defining the output tensor shape.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function reshape_(x, shape) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reshape", null);
-        shape = util["inferFromImplicitShape"](shape, $x.size);
-        util["assert"](
-          $x.size === util["sizeFromShape"](shape),
-          () => "new shape and old shape must have the same number of elements."
-        );
-        const grad = (dy) => {
-          return { x: () => dy.reshape($x.shape) };
-        };
-        const attrs = { shape };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.reshape($x, shape),
-          { x: $x },
-          grad,
-          "Reshape",
-          attrs
-        );
-      }
-      /**
-       * Removes dimensions of size 1 from the shape of a `tf.Tensor`.
-       *
-       * ```js
-       * const x = tf.tensor([1, 2, 3, 4], [1, 1, 4]);
-       * x.squeeze().print();
-       * ```
-       *
-       * @param x The input tensor to be squeezed.
-       * @param axis An optional list of numbers. If specified, only
-       *     squeezes the dimensions listed. The dimension index starts at 0. It
-       * is an error to squeeze a dimension that is not 1.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function squeeze_(x, axis) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "squeeze");
-        return reshape($x, util["squeezeShape"]($x.shape, axis).newShape);
-      }
-      /**
-       * Casts a `tf.Tensor` to a new dtype.
-       *
-       * ```js
-       * const x = tf.tensor1d([1.5, 2.5, 3]);
-       * tf.cast(x, 'int32').print();
-       * ```
-       * @param x The input tensor to be casted.
-       * @param dtype The dtype to cast the input tensor to.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function cast_(x, dtype) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "cast");
-        // Sanity checks.
-        if (!util["isValidDtype"](dtype)) {
-          throw new Error(`Failed to cast to unknown dtype ${dtype}`);
-        }
-        if (
-          (dtype === "string" && $x.dtype !== "string") ||
-          (dtype !== "string" && $x.dtype === "string")
-        ) {
-          throw new Error("Only strings can be casted to strings");
-        }
-        const grad = (dy) => {
-          return { x: () => dy.clone() };
-        };
-        const attrs = { dtype };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.cast($x, dtype),
-          { x: $x },
-          grad,
-          "Cast",
-          attrs
-        );
-      }
-      /**
-       * Stacks a list of rank-`R` `tf.Tensor`s into one rank-`(R+1)` `tf.Tensor`.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2]);
-       * const b = tf.tensor1d([3, 4]);
-       * const c = tf.tensor1d([5, 6]);
-       * tf.stack([a, b, c]).print();
-       * ```
-       *
-       * @param tensors A list of tensor objects with the same shape and dtype.
-       * @param axis The axis to stack along. Defaults to 0 (the first dim).
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      function stack_(tensors, axis = 0) {
-        const $tensors = Object(tensor_util_env["b" /* convertToTensorArray */])(
-          tensors,
-          "tensors",
-          "stack"
-        );
-        util["assert"]($tensors.length >= 1, () => "Pass at least one tensor to tf.stack");
-        if ($tensors.length === 1) {
-          return $tensors[0].expandDims(axis);
-        }
-        const rank = $tensors[0].rank;
-        const shape = $tensors[0].shape;
-        const dtype = $tensors[0].dtype;
-        util["assert"](axis <= rank, () => "Axis must be <= rank of the tensor");
-        $tensors.forEach((t) => {
-          util["assertShapesMatch"](
-            shape,
-            t.shape,
-            "All tensors passed to stack must have matching shapes"
-          );
-        });
-        $tensors.forEach((t) => {
-          util["assert"](
-            dtype === t.dtype,
-            () => "All tensors passed to stack must have matching dtypes"
-          );
-        });
-        const expandedTensors = $tensors.map((t) => t.expandDims(axis));
-        return concat(expandedTensors, axis);
-      }
-      /**
-       * Unstacks a `tf.Tensor` of rank-`R` into a list of rank-`(R-1)` `tf.Tensor`s.
-       *
-       * ```js
-       * const a = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * tf.unstack(a).forEach(tensor => tensor.print());
-       * ```
-       *
-       * @param x A tensor object.
-       * @param axis The axis to unstack along. Defaults to 0 (the first dim).
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      function unstack_(x, axis = 0) {
-        axis = axis || 0;
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "unstack");
-        util["assert"](
-          axis >= -$x.shape.length && axis < $x.shape.length,
-          () => `Axis = ${axis} is not in [-${$x.shape.length}, ${$x.shape.length})`
-        );
-        if (axis < 0) {
-          axis += $x.shape.length;
-        }
-        const grad = (dy) => {
-          return { x: () => stack(dy, axis) };
-        };
-        const attrs = { axis };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.unstack($x, axis),
-          { x: $x },
-          grad,
-          "Unpack",
-          attrs
-        );
-      }
-      /**
-       * Returns a `tf.Tensor` that has expanded rank, by inserting a dimension
-       * into the tensor's shape.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       * const axis = 1;
-       * x.expandDims(axis).print();
-       * ```
-       *
-       * @param x The input tensor whose dimensions to be expanded.
-       * @param axis The dimension index at which to insert shape of `1`. Defaults
-       *     to 0 (the first dimension).
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function expandDims_(x, axis = 0) {
-        const parseAs = null;
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(
-          x,
-          "x",
-          "expandDims",
-          parseAs
-        );
-        util["assert"](axis <= $x.rank, () => "Axis must be <= rank of the tensor");
-        const newShape = $x.shape.slice();
-        if (axis < 0) {
-          // Negative value is counted from the tail of rank.
-          util["assert"](
-            -($x.rank + 1) <= axis,
-            () => `Axis must be in the interval [${-($x.rank + 1)}, ${$x.rank}]`
-          );
-          axis = $x.rank + axis + 1;
-        }
-        newShape.splice(axis, 0, 1);
-        return reshape($x, newShape);
-      }
-      /**
-       * Computes the difference between two lists of numbers.
-       *
-       * Given a Tensor `x` and a Tensor `y`, this operation returns a Tensor `out`
-       * that represents all values that are in `x` but not in `y`. The returned
-       * Tensor `out` is sorted in the same order that the numbers appear in `x`
-       * (duplicates are preserved). This operation also returns a Tensor indices that
-       * represents the position of each out element in `x`. In other words:
-       *
-       * `out[i] = x[idx[i]] for i in [0, 1, ..., out.length - 1]`
-       *
-       * ```js
-       * const x = [1, 2, 3, 4, 5, 6];
-       * const y = [1, 3, 5];
-       *
-       * const [out, indices] = await tf.setdiff1dAsync(x, y);
-       * out.print(); // [2, 4, 6]
-       * indices.print(); // [1, 3, 5]
-       * ```
-       *
-       * @param x 1-D Tensor. Values to keep.
-       * @param y 1-D Tensor. Must have the same type as x. Values to exclude in the
-       *     output.
-       * @returns Promise of Tensor tuple [out, indices].
-       *  out: Tensor with the same type as x.
-       *  indices: A Tensor of type int32.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      async function setdiff1dAsync_(x, y) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "setdiff1d");
-        const $y = Object(tensor_util_env["a" /* convertToTensor */])(y, "y", "setdiff1d");
-        util["assert"](
-          $x.dtype === $y.dtype,
-          () => `x and y should have the same dtype, but got x (${$x.dtype}) and y (${$y.dtype}).`
-        );
-        util["assert"]($x.rank === 1, () => `x should be 1D tensor, but got x (${$x.shape}).`);
-        util["assert"]($y.rank === 1, () => `y should be 1D tensor, but got y (${$y.shape}).`);
-        const xVals = await $x.data();
-        const yVals = await $y.data();
-        const ySet = new Set(yVals);
-        let outputSize = 0;
-        for (let i = 0; i < xVals.length; i++) {
-          if (!ySet.has(xVals[i])) {
-            outputSize++;
-          }
-        }
-        const buffer = new dist_tensor["b" /* TensorBuffer */]([outputSize], $x.dtype);
-        const indices = new dist_tensor["b" /* TensorBuffer */]([outputSize], "int32");
-        for (let i = 0, p = 0; i < xVals.length; i++) {
-          if (!ySet.has(xVals[i])) {
-            buffer.values[p] = xVals[i];
-            indices.values[p] = i;
-            p++;
-          }
-        }
-        return [buffer.toTensor(), indices.toTensor()];
-      }
-      /**
-       * Creates an empty `tf.TensorBuffer` with the specified `shape` and `dtype`.
-       *
-       * The values are stored in CPU as `TypedArray`. Fill the buffer using
-       * `buffer.set()`, or by modifying directly `buffer.values`.
-       *
-       * When done, call `buffer.toTensor()` to get an immutable `tf.Tensor` with
-       * those values.
-       *
-       * ```js
-       * // Create a buffer and set values at particular indices.
-       * const buffer = tf.buffer([2, 2]);
-       * buffer.set(3, 0, 0);
-       * buffer.set(5, 1, 0);
-       *
-       * // Convert the buffer back to a tensor.
-       * buffer.toTensor().print();
-       * ```
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param dtype The dtype of the buffer. Defaults to 'float32'.
-       * @param values The values of the buffer as `TypedArray`. Defaults to
-       * zeros.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function array_ops_buffer(shape, dtype = "float32", values) {
-        dtype = dtype || "float32";
-        util["assertNonNegativeIntegerDimensions"](shape);
-        return new dist_tensor["b" /* TensorBuffer */](shape, dtype, values);
-      }
-      /**
-       * Prints information about the `tf.Tensor` including its data.
-       *
-       * ```js
-       * const verbose = true;
-       * tf.tensor2d([1, 2, 3, 4], [2, 2]).print(verbose);
-       * ```
-       * @param x The tensor to be printed.
-       * @param verbose Whether to print verbose information about the ` Tensor`,
-       * including dtype and size.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function print(x, verbose = false) {
-        console.log(x.toString(verbose));
-      }
-
-      const cast = Object(operation["a" /* op */])({ cast_ });
-      const expandDims = Object(operation["a" /* op */])({ expandDims_ });
-      const reshape = Object(operation["a" /* op */])({ reshape_ });
-      const squeeze = Object(operation["a" /* op */])({ squeeze_ });
-      const stack = Object(operation["a" /* op */])({ stack_ });
-      const unstack = Object(operation["a" /* op */])({ unstack_ });
-      const setdiff1dAsync = setdiff1dAsync_;
-      //# sourceMappingURL=array_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/floorDiv.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Divides two `tf.Tensor`s element-wise, A / B. Supports broadcasting.
-       * The result is rounded with floor function.
-       *
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 4, 9, 16]);
-       * const b = tf.tensor1d([1, 2, 3, 4]);
-       *
-       * a.floorDiv(b).print();  // or tf.div(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast div a with b.
-       * const a = tf.tensor1d([2, 4, 6, 8]);
-       * const b = tf.scalar(2);
-       *
-       * a.floorDiv(b).print();  // or tf.floorDiv(a, b)
-       * ```
-       *
-       * @param a The first tensor as the numerator.
-       * @param b The second tensor as the denominator. Must have the same dtype as
-       * `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function floorDiv_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "floorDiv");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "floorDiv");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        const forward = (backend, save) => {
-          const res = backend.floorDiv($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["D" /* FloorDiv */]
-        );
-      }
-      const floorDiv = Object(operation["a" /* op */])({ floorDiv_ });
-      //# sourceMappingURL=floorDiv.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/div.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Divides two `tf.Tensor`s element-wise, A / B. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 4, 9, 16]);
-       * const b = tf.tensor1d([1, 2, 3, 4]);
-       *
-       * a.div(b).print();  // or tf.div(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast div a with b.
-       * const a = tf.tensor1d([2, 4, 6, 8]);
-       * const b = tf.scalar(2);
-       *
-       * a.div(b).print();  // or tf.div(a, b)
-       * ```
-       *
-       * @param a The first tensor as the numerator.
-       * @param b The second tensor as the denominator. Must have the same dtype as
-       * `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function div_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "div");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "div");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        if ($a.dtype === "int32" && $b.dtype === "int32") {
-          return floorDiv($a, $b);
-        }
-        const forward = (backend, save) => {
-          const res = backend.realDivide($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        const attrs = {};
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["y" /* Div */],
-          attrs
-        );
-      }
-      const div = Object(operation["a" /* op */])({ div_ });
-      //# sourceMappingURL=div.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/mul.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Multiplies two `tf.Tensor`s element-wise, A * B. Supports broadcasting.
-       *
-       * We also expose `tf.mulStrict` which has the same signature as this op and
-       * asserts that `a` and `b` are the same shape (does not broadcast).
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3, 4]);
-       * const b = tf.tensor1d([2, 3, 4, 5]);
-       *
-       * a.mul(b).print();  // or tf.mul(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast mul a with b.
-       * const a = tf.tensor1d([1, 2, 3, 4]);
-       * const b = tf.scalar(5);
-       *
-       * a.mul(b).print();  // or tf.mul(a, b)
-       * ```
-       * @param a The first tensor to multiply.
-       * @param b The second tensor to multiply. Must have the same dtype as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function mul_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "mul");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "mul");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        const forward = (backend, save) => {
-          const res = backend.multiply($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["Y" /* Multiply */]
-        );
-      }
-      const mul = Object(operation["a" /* op */])({ mul_ });
-      //# sourceMappingURL=mul.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Provided `f(x)`, returns another function `g(x, dy?)`, which gives the
-       * gradient of `f(x)` with respect to `x`.
-       *
-       * If `dy` is provided, the gradient of `f(x).mul(dy).sum()` with respect to
-       * `x` is computed instead. `f(x)` must take a single tensor `x` and return a
-       * single tensor `y`. If `f()` takes multiple inputs, use `tf.grads` instead.
-       *
-       * ```js
-       * // f(x) = x ^ 2
-       * const f = x => x.square();
-       * // f'(x) = 2x
-       * const g = tf.grad(f);
-       *
-       * const x = tf.tensor1d([2, 3]);
-       * g(x).print();
-       * ```
-       *
-       * ```js
-       * // f(x) = x ^ 3
-       * const f = x => x.pow(tf.scalar(3, 'int32'));
-       * // f'(x) = 3x ^ 2
-       * const g = tf.grad(f);
-       * // f''(x) = 6x
-       * const gg = tf.grad(g);
-       *
-       * const x = tf.tensor1d([2, 3]);
-       * gg(x).print();
-       * ```
-       *
-       * @param f The function f(x), to compute gradient for.
-       */
-      /** @doc {heading: 'Training', subheading: 'Gradients'} */
-      function gradients_grad(f) {
-        util["assert"](util["isFunction"](f), () => "The f passed in grad(f) must be a function");
-        return (x, dy) => {
-          // x can be of any dtype, thus null as the last argument.
-          const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "tf.grad", null);
-          const $dy =
-            dy != null
-              ? Object(tensor_util_env["a" /* convertToTensor */])(dy, "dy", "tf.grad")
-              : null;
-          return engine["a" /* ENGINE */].tidy(() => {
-            const { value, grads } = engine["a" /* ENGINE */].gradients(() => f($x), [$x], $dy);
-            if ($dy != null) {
-              util["assertShapesMatch"](
-                value.shape,
-                $dy.shape,
-                "The shape of dy passed in grad(f)(x, dy) must match the shape " +
-                  "returned by f(x)"
-              );
-            }
-            checkGrads(grads);
-            return grads[0];
-          });
-        };
-      }
-      /**
-       * Provided `f(x1, x2,...)`, returns another function `g([x1, x2,...], dy?)`,
-       * which gives an array of gradients of `f()` with respect to each input
-       * [`x1`,`x2`,...].
-       *
-       * If `dy` is passed when calling `g()`, the gradient of
-       * `f(x1,...).mul(dy).sum()` with respect to each input is computed instead.
-       * The provided `f` must take one or more tensors and return a single tensor
-       * `y`. If `f()` takes a single input, we recommend using `tf.grad` instead.
-       *
-       * ```js
-       * // f(a, b) = a * b
-       * const f = (a, b) => a.mul(b);
-       * // df / da = b, df / db = a
-       * const g = tf.grads(f);
-       *
-       * const a = tf.tensor1d([2, 3]);
-       * const b = tf.tensor1d([-2, -3]);
-       * const [da, db] = g([a, b]);
-       * console.log('da');
-       * da.print();
-       * console.log('db');
-       * db.print();
-       * ```
-       *
-       * @param f The function `f(x1, x2,...)` to compute gradients for.
-       */
-      /** @doc {heading: 'Training', subheading: 'Gradients'} */
-      function gradients_grads(f) {
-        util["assert"](util["isFunction"](f), () => "The f passed in grads(f) must be a function");
-        return (args, dy) => {
-          util["assert"](
-            Array.isArray(args),
-            () =>
-              "The args passed in grads(f)(args) must be an array " +
-              "of `Tensor`s or `TensorLike`s"
-          );
-          // args can be of any dtype, thus null as the last argument.
-          const $args = Object(tensor_util_env["b" /* convertToTensorArray */])(
-            args,
-            "args",
-            "tf.grads",
-            null
-          );
-          const $dy =
-            dy != null
-              ? Object(tensor_util_env["a" /* convertToTensor */])(dy, "dy", "tf.grads")
-              : null;
-          return engine["a" /* ENGINE */].tidy(() => {
-            const { value, grads } = engine["a" /* ENGINE */].gradients(
-              () => f(...$args),
-              $args,
-              $dy
-            );
-            if ($dy != null) {
-              util["assertShapesMatch"](
-                value.shape,
-                $dy.shape,
-                "The shape of dy passed in grads(f)([x1,...], dy) must " +
-                  "match the shape returned by f([x1,...])"
-              );
-            }
-            checkGrads(grads);
-            return grads;
-          });
-        };
-      }
-      /**
-       * Like `tf.grad`, but also returns the value of `f()`. Useful when `f()`
-       * returns a metric you want to show.
-       *
-       * The result is a rich object with the following properties:
-       * - grad: The gradient of `f(x)` w.r.t `x` (result of `tf.grad`).
-       * - value: The value returned by `f(x)`.
-       *
-       * ```js
-       * // f(x) = x ^ 2
-       * const f = x => x.square();
-       * // f'(x) = 2x
-       * const g = tf.valueAndGrad(f);
-       *
-       * const x = tf.tensor1d([2, 3]);
-       * const {value, grad} = g(x);
-       *
-       * console.log('value');
-       * value.print();
-       * console.log('grad');
-       * grad.print();
-       * ```
-       */
-      /** @doc {heading: 'Training', subheading: 'Gradients'} */
-      function valueAndGrad(f) {
-        util["assert"](
-          util["isFunction"](f),
-          () => "The f passed in valueAndGrad(f) must be a function"
-        );
-        return (x, dy) => {
-          util["assert"](
-            x instanceof dist_tensor["a" /* Tensor */],
-            () => "The x passed in valueAndGrad(f)(x) must be a tensor"
-          );
-          util["assert"](
-            dy == null || dy instanceof dist_tensor["a" /* Tensor */],
-            () => "The dy passed in valueAndGrad(f)(x, dy) must be a tensor"
-          );
-          const { grads, value } = engine["a" /* ENGINE */].gradients(() => f(x), [x], dy);
-          checkGrads(grads);
-          return { grad: grads[0], value };
-        };
-      }
-      /**
-       * Like `tf.grads`, but returns also the value of `f()`. Useful when `f()`
-       * returns a metric you want to show.
-       *
-       * The result is a rich object with the following properties:
-       * - grads: The gradients of `f()` w.r.t each input (result of `tf.grads`).
-       * - value: The value returned by `f(x)`.
-       *
-       * ```js
-       * // f(a, b) = a * b
-       * const f = (a, b) => a.mul(b);
-       * // df/da = b, df/db = a
-       * const g = tf.valueAndGrads(f);
-       *
-       * const a = tf.tensor1d([2, 3]);
-       * const b = tf.tensor1d([-2, -3]);
-       * const {value, grads} = g([a, b]);
-       *
-       * const [da, db] = grads;
-       *
-       * console.log('value');
-       * value.print();
-       *
-       * console.log('da');
-       * da.print();
-       * console.log('db');
-       * db.print();
-       * ```
-       */
-      /** @doc {heading: 'Training', subheading: 'Gradients'} */
-      function valueAndGrads(f) {
-        util["assert"](
-          util["isFunction"](f),
-          () => "The f passed in valueAndGrads(f) must be a function"
-        );
-        return (args, dy) => {
-          util["assert"](
-            Array.isArray(args) &&
-              args.every((arg) => arg instanceof dist_tensor["a" /* Tensor */]),
-            () => "The args passed in valueAndGrads(f)(args) must be array of " + "tensors"
-          );
-          util["assert"](
-            dy == null || dy instanceof dist_tensor["a" /* Tensor */],
-            () => "The dy passed in valueAndGrads(f)(args, dy) must be a tensor"
-          );
-          const res = engine["a" /* ENGINE */].gradients(() => f(...args), args, dy);
-          if (dy != null) {
-            util["assertShapesMatch"](
-              res.value.shape,
-              dy.shape,
-              "The shape of dy passed in valueAndGrads(f)([x1,...], dy) must " +
-                "match the shape returned by f([x1,...])"
-            );
-          }
-          checkGrads(res.grads);
-          return res;
-        };
-      }
-      /**
-       * Computes and returns the gradient of f(x) with respect to the list of
-       * trainable variables provided by `varList`. If no list is provided, it
-       * defaults to all trainable variables.
-       *
-       * ```js
-       * const a = tf.variable(tf.tensor1d([3, 4]));
-       * const b = tf.variable(tf.tensor1d([5, 6]));
-       * const x = tf.tensor1d([1, 2]);
-       *
-       * // f(a, b) = a * x ^ 2 + b * x
-       * const f = () => a.mul(x.square()).add(b.mul(x)).sum();
-       * // df/da = x ^ 2, df/db = x
-       * const {value, grads} = tf.variableGrads(f);
-       *
-       * Object.keys(grads).forEach(varName => grads[varName].print());
-       * ```
-       *
-       * @param f The function to execute. f() should return a scalar.
-       * @param varList The list of variables to compute the gradients with respect
-       *     to. Defaults to all trainable variables.
-       * @returns An object with the following keys and values:
-       *   - `value`: The value of the function `f`.
-       *   - `grads`: A map from the names of the variables to the gradients.
-       *     If the `varList` argument is provided explicitly and contains a subset of
-       *     non-trainable variables, this map in the return value will contain keys
-       *     that map the names of the non-trainable variables to `null`.
-       */
-      /** @doc {heading: 'Training', subheading: 'Gradients'} */
-      function variableGrads(f, varList) {
-        util["assert"](
-          util["isFunction"](f),
-          () => "The f passed in variableGrads(f) must be a function"
-        );
-        util["assert"](
-          varList == null ||
-            (Array.isArray(varList) &&
-              varList.every((v) => v instanceof dist_tensor["c" /* Variable */])),
-          () => "The varList passed in variableGrads(f, varList) must be an array " + "of variables"
-        );
-        const specifiedVarList = varList != null;
-        if (!specifiedVarList) {
-          // Get all of the trainable variables.
-          varList = [];
-          for (const varName in engine["a" /* ENGINE */].registeredVariables) {
-            varList.push(engine["a" /* ENGINE */].registeredVariables[varName]);
-          }
-        }
-        const specifiedNonTrainable = specifiedVarList
-          ? varList.filter((variable) => !variable.trainable)
-          : null;
-        // Prune non-trainable variables.
-        const originalVarCount = varList.length;
-        varList = varList.filter((variable) => variable.trainable);
-        util["assert"](
-          varList.length > 0,
-          () =>
-            `variableGrads() expects at least one of the input variables to ` +
-            `be trainable, but none of the ${originalVarCount} variables is ` +
-            `trainable.`
-        );
-        const allowNoGradients = true;
-        const { value, grads } = engine["a" /* ENGINE */].gradients(
-          f,
-          varList,
-          null,
-          allowNoGradients
-        );
-        util["assert"](
-          grads.some((g) => g != null),
-          () =>
-            "Cannot find a connection between any variable and the result of " +
-            "the loss function y=f(x). Please make sure the operations that " +
-            "use variables are inside the function f passed to minimize()."
-        );
-        util["assert"](
-          value.rank === 0,
-          () =>
-            `The f passed in variableGrads(f) must return a scalar, but it ` +
-            `returned a rank-${value.rank} tensor`
-        );
-        const namedGrads = {};
-        varList.forEach((v, i) => {
-          if (grads[i] != null) {
-            namedGrads[v.name] = grads[i];
-          }
-        });
-        if (specifiedNonTrainable != null) {
-          // If varList is explicitly provided and contains non-trainable values,
-          // add them to the returned gradients with `null` values.
-          specifiedNonTrainable.forEach((v) => (namedGrads[v.name] = null));
-        }
-        return { value, grads: namedGrads };
-      }
-      /**
-       * Overrides the gradient computation of a function `f`.
-       *
-       * Takes a function
-       * `f(...inputs, save) => {value: Tensor, gradFunc: (dy, saved) => Tensor[]}`
-       * and returns another function `g(...inputs)` which takes the same inputs as
-       * `f`. When called, `g` returns `f().value`. In backward mode, custom gradients
-       * with respect to each input of `f` are computed using `f().gradFunc`.
-       *
-       * The `save` function passsed to `f` should be used for saving tensors needed
-       * in the gradient. And the `saved` passed to the `gradFunc` is a
-       * `NamedTensorMap`, which contains those saved tensor.
-       *
-       * ```js
-       * const customOp = tf.customGrad((x, save) => {
-       *   // Save x to make sure it's available later for the gradient.
-       *   save([x]);
-       *   // Override gradient of our custom x ^ 2 op to be dy * abs(x);
-       *   return {
-       *     value: x.square(),
-       *     // Note `saved.x` which points to the `x` we saved earlier.
-       *     gradFunc: (dy, saved) => [dy.mul(saved[0].abs())]
-       *   };
-       * });
-       *
-       * const x = tf.tensor1d([-1, -2, 3]);
-       * const dx = tf.grad(x => customOp(x));
-       *
-       * console.log(`f(x):`);
-       * customOp(x).print();
-       * console.log(`f'(x):`);
-       * dx(x).print();
-       * ```
-       *
-       * @param f The function to evaluate in forward mode, which should return
-       *     `{value: Tensor, gradFunc: (dy, saved) => Tensor[]}`, where `gradFunc`
-       *     returns the custom gradients of `f` with respect to its inputs.
-       */
-      /** @doc {heading: 'Training', subheading: 'Gradients'} */
-      function customGrad(f) {
-        return engine["a" /* ENGINE */].customGrad(f);
-      }
-      function checkGrads(grads) {
-        const numNullGradients = grads.filter((g) => g == null).length;
-        if (numNullGradients > 0) {
-          throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that
-    the f you passed encloses all operations that lead from x to y.`);
-        }
-      }
-
-      //# sourceMappingURL=gradients.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/axis_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns true if the axis specifies the inner most dimensions of the
-       * array.
-       */
-      function axesAreInnerMostDims(axes, rank) {
-        for (let i = 0; i < axes.length; ++i) {
-          if (axes[axes.length - i - 1] !== rank - 1 - i) {
-            return false;
-          }
-        }
-        return true;
-      }
-      function combineLocations(outputLoc, reduceLoc, axes) {
-        const rank = outputLoc.length + reduceLoc.length;
-        const loc = [];
-        let outIdx = 0;
-        let reduceIdx = 0;
-        for (let dim = 0; dim < rank; dim++) {
-          if (axes.indexOf(dim) === -1) {
-            loc.push(outputLoc[outIdx++]);
-          } else {
-            loc.push(reduceLoc[reduceIdx++]);
-          }
-        }
-        return loc;
-      }
-      function computeOutAndReduceShapes(aShape, axes) {
-        const outShape = [];
-        const rank = aShape.length;
-        for (let dim = 0; dim < rank; dim++) {
-          if (axes.indexOf(dim) === -1) {
-            outShape.push(aShape[dim]);
-          }
-        }
-        const reduceShape = axes.map((dim) => aShape[dim]);
-        return [outShape, reduceShape];
-      }
-      function expandShapeToKeepDim(shape, axes) {
-        const reduceSubShape = axes.map((x) => 1);
-        return combineLocations(shape, reduceSubShape, axes);
-      }
-      function assertAxesAreInnerMostDims(msg, axes, rank) {
-        util["assert"](
-          axesAreInnerMostDims(axes, rank),
-          () =>
-            `${msg} supports only inner-most axes for now. ` +
-            `Got axes ${axes} and rank-${rank} input.`
-        );
-      }
-      /**
-       * Returns the axes permutation to be used with `tf.transpose`, if such
-       * permutation is necessary. Otherwise it returns null. This method is used by
-       * operations that operate only on inner-most axes.
-       */
-      function getAxesPermutation(axes, rank) {
-        if (axesAreInnerMostDims(axes, rank)) {
-          return null;
-        }
-        const result = [];
-        for (let i = 0; i < rank; ++i) {
-          if (axes.indexOf(i) === -1) {
-            result.push(i);
-          }
-        }
-        axes.forEach((axis) => result.push(axis));
-        return result;
-      }
-      /** Returns the axes permutation that undoes the original permutation. */
-      function getUndoAxesPermutation(axes) {
-        return axes
-          .map((axis, i) => [i, axis])
-          .sort((a, b) => a[1] - b[1])
-          .map((x) => x[0]);
-      }
-      function getInnerMostAxes(numAxes, rank) {
-        const res = [];
-        for (let i = rank - numAxes; i < rank; ++i) {
-          res.push(i);
-        }
-        return res;
-      }
-      //# sourceMappingURL=axis_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/reduction_ops_util.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Gradient helper function for the min and max operations.
-       */
-      function gradForMinAndMax(dy, y, xOrig, origAxes, permutedAxes) {
-        if (y.rank < xOrig.rank) {
-          y = y.reshape(expandShapeToKeepDim(y.shape, origAxes));
-        }
-        if (dy.rank < xOrig.rank) {
-          dy = dy.reshape(expandShapeToKeepDim(dy.shape, origAxes));
-        }
-        return {
-          x: () => {
-            const dx = dy.mul(xOrig.equal(y).cast(dy.dtype));
-            return permutedAxes == null ? dx : dx.transpose(permutedAxes);
-          },
-        };
-      }
-      //# sourceMappingURL=reduction_ops_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/reduction_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the log(sum(exp(elements across the reduction dimensions)).
-       *
-       * Reduces the input along the dimensions given in `axis`. Unless `keepDims`
-       * is true, the rank of the array is reduced by 1 for each entry in `axis`.
-       * If `keepDims` is true, the reduced dimensions are retained with length 1.
-       * If `axis` has no entries, all dimensions are reduced, and an array with a
-       * single element is returned.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3]);
-       *
-       * x.logSumExp().print();  // or tf.logSumExp(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * const axis = 1;
-       * x.logSumExp(axis).print();  // or tf.logSumExp(a, axis)
-       * ```
-       * @param x The input tensor.
-       * @param axis The dimension(s) to reduce. If null (the default),
-       *     reduces all dimensions.
-       * @param keepDims If true, retains reduced dimensions with length
-       *     of 1. Defaults to false.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function logSumExp_(x, axis = null, keepDims = false) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "logSumExp");
-        const axes = util["parseAxisParam"](axis, $x.shape);
-        const xMax = $x.max(axes, true /* keepDims */);
-        const a = $x.sub(xMax);
-        const b = a.exp();
-        const c = b.sum(axes);
-        const d = c.log();
-        const res = xMax.reshape(d.shape).add(d);
-        if (keepDims) {
-          const newShape = expandShapeToKeepDim(res.shape, axes);
-          return res.reshape(newShape);
-        }
-        return res;
-      }
-      /**
-       * Computes the sum of elements across dimensions of a `tf.Tensor`.
-       *
-       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
-       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
-       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
-       * length 1. If axes has no entries, all dimensions are reduced, and a
-       * `tf.Tensor` with a single element is returned.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3]);
-       *
-       * x.sum().print();  // or tf.sum(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * const axis = 1;
-       * x.sum(axis).print();  // or tf.sum(x, axis)
-       * ```
-       *
-       * @param x The input tensor to compute the sum over. If the dtype is `bool`
-       *   it will be converted to `int32` and the output dtype will be `int32`.
-       * @param axis The dimension(s) to reduce. By default it reduces
-       *     all dimensions.
-       * @param keepDims If true, retains reduced dimensions with size 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function sum_(x, axis = null, keepDims = false) {
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sum");
-        if ($x.dtype === "bool") {
-          $x = $x.toInt();
-        }
-        const axes = util["parseAxisParam"](axis, $x.shape);
-        // Use a custom gradient to bypass 2 gradient backprops since sum is used
-        // extremely often.
-        const customOp = customGrad((x) => {
-          const permutation = getAxesPermutation(axes, x.rank);
-          let reductionAxes = axes;
-          let permutedX = x;
-          if (permutation != null) {
-            permutedX = x.transpose(permutation);
-            reductionAxes = getInnerMostAxes(reductionAxes.length, x.rank);
-          }
-          const gradFunc = (dy) => {
-            const expandedDyShape = x.shape.slice();
-            axes.forEach((axis) => {
-              expandedDyShape[axis] = 1;
-            });
-            const expandedDy = dy.reshape(expandedDyShape);
-            const derX = expandedDy.mul(Object(tensor_ops["b" /* ones */])(x.shape, "float32"));
-            return derX;
-          };
-          const gradInputs = (dy) => {
-            return { x: () => gradFunc(dy) };
-          };
-          const attrs = { axes: reductionAxes };
-          let value = engine["a" /* ENGINE */].runKernelFunc(
-            (backend) => backend.sum(permutedX, reductionAxes),
-            { x: permutedX },
-            gradInputs,
-            "Sum",
-            attrs
-          );
-          if (keepDims) {
-            const newShape = expandShapeToKeepDim(value.shape, axes);
-            value = value.reshape(newShape);
-          }
-          return { value, gradFunc };
-        });
-        return customOp($x);
-      }
-      /**
-       * Computes the product of elements across dimensions of a `tf.Tensor`.
-       *
-       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
-       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
-       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
-       * length 1. If `axes` has no entries, all dimensions are reduced, and a
-       * `tf.Tensor` with a single element is returned.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3]);
-       *
-       * x.prod().print();  // or tf.prod(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * const axis = 1;
-       * x.prod(axis).print();  // or tf.prod(x, axis)
-       * ```
-       *
-       * @param x The input tensor to compute the product over. If the dtype is `bool`
-       *   it will be converted to `int32` and the output dtype will be `int32`.
-       * @param axis The dimension(s) to reduce. By default it reduces
-       *     all dimensions.
-       * @param keepDims If true, retains reduced dimensions with size 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function prod_(x, axis = null, keepDims = false) {
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "prod");
-        if ($x.dtype === "bool") {
-          $x = $x.toInt();
-        }
-        const axes = util["parseAxisParam"](axis, $x.shape);
-        const permutation = getAxesPermutation(axes, $x.rank);
-        let reductionAxes = axes;
-        let permutedX = $x;
-        if (permutation != null) {
-          permutedX = $x.transpose(permutation);
-          reductionAxes = getInnerMostAxes(reductionAxes.length, $x.rank);
-        }
-        let value = engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.prod(permutedX, reductionAxes),
-          { permutedX }
-        );
-        if (keepDims) {
-          const newShape = expandShapeToKeepDim(value.shape, axes);
-          value = value.reshape(newShape);
-        }
-        return value;
-      }
-      /**
-       * Computes the mean of elements across dimensions of a `tf.Tensor`.
-       *
-       * Reduces `x` along the dimensions given in `axis`. Unless `keepDims` is
-       * true, the rank of the `tf.Tensor` is reduced by 1 for each entry in `axis`.
-       * If `keepDims` is true, the reduced dimensions are retained with length 1.
-       * If `axis` has no entries, all dimensions are reduced, and a `tf.Tensor` with
-       * a single element is returned.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3]);
-       *
-       * x.mean().print();  // or tf.mean(a)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * const axis = 1;
-       * x.mean(axis).print();  // or tf.mean(x, axis)
-       * ```
-       *
-       * @param x The input tensor.
-       * @param axis The dimension(s) to reduce. By default it reduces
-       *     all dimensions.
-       * @param keepDims If true, retains reduced dimensions with size 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function mean_(x, axis = null, keepDims = false) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "mean");
-        const axes = util["parseAxisParam"](axis, $x.shape);
-        const shapes = computeOutAndReduceShapes($x.shape, axes);
-        const reduceShape = shapes[1];
-        const reduceSize = util["sizeFromShape"](reduceShape);
-        // Use a custom gradient to bypass 2 gradient backprops since mean is used
-        // extremely often.
-        const customOp = customGrad((x) => {
-          const reduceSizeScalar = Object(tensor_ops["e" /* scalar */])(reduceSize);
-          // Cast if needed.
-          const xReduce = reduceSizeScalar.dtype === x.dtype ? x : x.cast(reduceSizeScalar.dtype);
-          const res = xReduce.div(reduceSizeScalar);
-          const value = res.sum(axis, keepDims);
-          const gradFunc = (dy) => {
-            const expandedDyShape = x.shape.slice();
-            axes.forEach((axis) => {
-              expandedDyShape[axis] = 1;
-            });
-            const expandedDy = dy.reshape(expandedDyShape);
-            const derX = expandedDy
-              .mul(Object(tensor_ops["b" /* ones */])(x.shape, "float32"))
-              .div(reduceSize);
-            return derX;
-          };
-          return { value, gradFunc };
-        });
-        return customOp($x);
-      }
-      /**
-       * Computes the minimum value from the input.
-       *
-       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
-       * is true, the rank of the array is reduced by 1 for each entry in `axes`.
-       * If `keepDims` is true, the reduced dimensions are retained with length 1.
-       * If `axes` has no entries, all dimensions are reduced, and an array with a
-       * single element is returned.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3]);
-       *
-       * x.min().print();  // or tf.min(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * const axis = 1;
-       * x.min(axis).print();  // or tf.min(x, axis)
-       * ```
-       *
-       * @param x The input Tensor.
-       * @param axis The dimension(s) to reduce. By default it reduces
-       *     all dimensions.
-       * @param keepDims If true, retains reduced dimensions with size 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function min_(x, axis = null, keepDims = false) {
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "min");
-        const xOrig = $x;
-        const origAxes = util["parseAxisParam"](axis, $x.shape);
-        let axes = origAxes;
-        const permutedAxes = getAxesPermutation(axes, $x.rank);
-        if (permutedAxes != null) {
-          $x = $x.transpose(permutedAxes);
-          axes = getInnerMostAxes(axes.length, $x.rank);
-        }
-        const grad = (dy, saved) =>
-          gradForMinAndMax(dy, saved[1], saved[0], origAxes, permutedAxes);
-        const inputsToSave = [$x];
-        const outputsToSave = [true];
-        let res = engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const y = backend.min($x, axes);
-            save([xOrig, y]);
-            return y;
-          },
-          { x: $x },
-          grad,
-          "Min",
-          { axes },
-          inputsToSave,
-          outputsToSave
-        );
-        if (keepDims) {
-          const newShape = expandShapeToKeepDim(res.shape, origAxes);
-          res = res.reshape(newShape);
-        }
-        return res;
-      }
-      /**
-       * Returns the indices of the minimum values along an `axis`.
-       *
-       * The result has the same shape as `input` with the dimension along `axis`
-       * removed.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3]);
-       *
-       * x.argMin().print();  // or tf.argMin(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 4, 3], [2, 2]);
-       *
-       * const axis = 1;
-       * x.argMin(axis).print();  // or tf.argMin(x, axis)
-       * ```
-       *
-       * @param x The input tensor.
-       * @param axis The dimension to reduce. Defaults to 0 (outer-most dimension).
-       *
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function argMin_(x, axis = 0) {
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "argMin");
-        if (axis == null) {
-          axis = 0;
-        }
-        let axes = util["parseAxisParam"](axis, $x.shape);
-        const permutedAxes = getAxesPermutation(axes, $x.rank);
-        if (permutedAxes != null) {
-          $x = $x.transpose(permutedAxes);
-          axes = getInnerMostAxes(axes.length, $x.rank);
-        }
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])($x) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.argMin($x, axes[0]);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Returns the indices of the maximum values along an `axis`.
-       *
-       * The result has the same shape as `input` with the dimension along `axis`
-       * removed.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3]);
-       *
-       * x.argMax().print();  // or tf.argMax(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 4, 3], [2, 2]);
-       *
-       * const axis = 1;
-       * x.argMax(axis).print();  // or tf.argMax(x, axis)
-       * ```
-       *
-       * @param x The input tensor.
-       * @param axis The dimension to reduce. Defaults to 0 (outer-most dimension).
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function argMax_(x, axis = 0) {
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "argMax");
-        if (axis == null) {
-          axis = 0;
-        }
-        let axes = util["parseAxisParam"](axis, $x.shape);
-        const permutedAxes = getAxesPermutation(axes, $x.rank);
-        if (permutedAxes != null) {
-          $x = $x.transpose(permutedAxes);
-          axes = getInnerMostAxes(axes.length, $x.rank);
-        }
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { x: () => Object(tensor_ops["o" /* zerosLike */])($x) };
-        };
-        const attrs = { axis: axes[0] };
-        const inputsToSave = [$x];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.argMax($x, axes[0]);
-            save([$x]);
-            return res;
-          },
-          { x: $x },
-          grad,
-          "ArgMax",
-          attrs,
-          inputsToSave
-        );
-      }
-      /**
-       * Computes the logical and of elements across dimensions of a `tf.Tensor`.
-       *
-       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
-       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
-       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
-       * length 1. If `axes` has no entries, all dimensions are reduced, and an
-       * `tf.Tensor` with a single element is returned.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 1, 1], 'bool');
-       *
-       * x.all().print();  // or tf.all(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 1, 0, 0], [2, 2], 'bool');
-       *
-       * const axis = 1;
-       * x.all(axis).print();  // or tf.all(x, axis)
-       * ```
-       *
-       * @param x The input tensor. Must be of dtype bool.
-       * @param axis The dimension(s) to reduce. By default it reduces
-       *     all dimensions.
-       * @param keepDims If true, retains reduced dimensions with size 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function all_(x, axis = null, keepDims = false) {
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "all", "bool");
-        const origAxes = util["parseAxisParam"](axis, $x.shape);
-        let axes = origAxes;
-        const permutedAxes = getAxesPermutation(axes, $x.rank);
-        if (permutedAxes != null) {
-          $x = $x.transpose(permutedAxes);
-          axes = getInnerMostAxes(axes.length, $x.rank);
-        }
-        const res = engine["a" /* ENGINE */].runKernelFunc((backend) => backend.all($x, axes), {
-          $x,
-        });
-        if (keepDims) {
-          const newShape = expandShapeToKeepDim(res.shape, origAxes);
-          return res.reshape(newShape);
-        }
-        return res;
-      }
-      /**
-       * Computes the logical or of elements across dimensions of a `tf.Tensor`.
-       *
-       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
-       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
-       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
-       * length 1. If `axes` has no entries, all dimensions are reduced, and an
-       * `tf.Tensor` with a single element is returned.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 1, 1], 'bool');
-       *
-       * x.any().print();  // or tf.any(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 1, 0, 0], [2, 2], 'bool');
-       *
-       * const axis = 1;
-       * x.any(axis).print();  // or tf.any(x, axis)
-       * ```
-       *
-       * @param x The input tensor. Must be of dtype bool.
-       * @param axis The dimension(s) to reduce. By default it reduces
-       *     all dimensions.
-       * @param keepDims If true, retains reduced dimensions with size 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function any_(x, axis = null, keepDims = false) {
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "any", "bool");
-        const origAxes = util["parseAxisParam"](axis, $x.shape);
-        let axes = origAxes;
-        const permutedAxes = getAxesPermutation(axes, $x.rank);
-        if (permutedAxes != null) {
-          $x = $x.transpose(permutedAxes);
-          axes = getInnerMostAxes(axes.length, $x.rank);
-        }
-        const res = engine["a" /* ENGINE */].runKernelFunc((backend) => backend.any($x, axes), {
-          $x,
-        });
-        if (keepDims) {
-          const newShape = expandShapeToKeepDim(res.shape, origAxes);
-          return res.reshape(newShape);
-        }
-        return res;
-      }
-      /**
-       * Calculates the mean and variance of `x`. The mean and variance are
-       * calculated by aggregating the contents of `x` across `axes`. If `x` is
-       * 1-D and `axes = [0]` this is just the mean and variance of a vector.
-       *
-       * @param x The input tensor.
-       * @param axis The dimension(s) along with to compute mean and
-       *     variance. By default it reduces all dimensions.
-       * @param keepDims If true, the moments have the same dimensionality as the
-       *     input.
-       * @return An object with two keys: `mean` and `variance`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
-      function moments_(x, axis = null, keepDims = false) {
-        x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "moments");
-        const axes = util["parseAxisParam"](axis, x.shape);
-        const mean = x.mean(axes, keepDims);
-        let keepDimsShape = mean.shape;
-        if (!keepDims) {
-          keepDimsShape = expandShapeToKeepDim(mean.shape, axes);
-        }
-        const devSquared = x.toFloat().sub(mean.reshape(keepDimsShape)).square();
-        const variance = devSquared.mean(axes, keepDims);
-        return { mean, variance };
-      }
-      const reduction_ops_all = Object(operation["a" /* op */])({ all_ });
-      // tslint:disable-next-line:variable-name
-      const any = Object(operation["a" /* op */])({ any_ });
-      const argMax = Object(operation["a" /* op */])({ argMax_ });
-      const argMin = Object(operation["a" /* op */])({ argMin_ });
-      const logSumExp = Object(operation["a" /* op */])({ logSumExp_ });
-      const reduction_ops_mean = Object(operation["a" /* op */])({ mean_ });
-      const reduction_ops_min = Object(operation["a" /* op */])({ min_ });
-      const moments = Object(operation["a" /* op */])({ moments_ });
-      const sum = Object(operation["a" /* op */])({ sum_ });
-      const reduction_ops_prod = Object(operation["a" /* op */])({ prod_ });
-      //# sourceMappingURL=reduction_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/square.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes square of `x` element-wise: `x ^ 2`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, Math.sqrt(2), -1]);
-       *
-       * x.square().print();  // or tf.square(x)
-       * ```
-       * @param x The input Tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function square_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "square");
-        const attrs = {};
-        const inputsToSave = [$x];
-        const outputsToSave = [];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            save([$x]);
-            return backend.square($x);
-          },
-          { x: $x },
-          null /* grad */,
-          "Square",
-          attrs,
-          inputsToSave,
-          outputsToSave
-        );
-      }
-      const square = Object(operation["a" /* op */])({ square_ });
-      //# sourceMappingURL=square.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/unary_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes `-1 * x` element-wise.
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, -2, 0], [2, 2]);
-       *
-       * x.neg().print();  // or tf.neg(x)
-       * ```
-       *
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function neg_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "neg");
-        const grad = (dy) => {
-          return { x: () => dy.neg() };
-        };
-        const attrs = {};
-        const inputsToSave = [$x];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.neg($x),
-          { x: $x },
-          grad,
-          "Neg",
-          attrs,
-          inputsToSave
-        );
-      }
-      /**
-       * Computes ceiling of input `tf.Tensor` element-wise: `ceil(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([.6, 1.1, -3.3]);
-       *
-       * x.ceil().print();  // or tf.ceil(x)
-       * ```
-       * @param x The input Tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function ceil_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "ceil");
-        // TODO(manrajgrover): Return null for gradients when backprop supports it.
-        const grad = (dy) => {
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.ceil($x), { $x }, grad);
-      }
-      /**
-       * Computes floor of input `tf.Tensor` element-wise: `floor(x)`.
-       *
-       * ```js
-       * const x = tf.tensor1d([.6, 1.1, -3.3]);
-       *
-       * x.floor().print();  // or tf.floor(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function floor_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "floor");
-        // TODO(nsthorat): Let gradients be null for cases where we want to stop
-        // backpropgation.
-        const grad = (dy) => {
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.floor($x), { $x }, grad);
-      }
-      /**
-       * Returns an element-wise indication of the sign of a number.
-       *
-       * ```js
-       * const x = tf.tensor1d([.6, 1.1, -3.3, NaN, 0]);
-       *
-       * x.sign().print();  // or tf.sign(x)
-       * ```
-       * @param x The input Tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function sign_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sign");
-        const grad = (dy) => {
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.sign($x), { $x }, grad);
-      }
-      /**
-       * RReturns which elements of x are NaN.
-       *
-       * ```js
-       * const x = tf.tensor1d([NaN, Infinity, -Infinity, 0, 1]);
-       *
-       * x.isNaN().print();  // or tf.isNaN(x)
-       * ```
-       * @param x The input Tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function isNaN_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "isNaN");
-        // TODO(nsthorat): Let gradients be null for cases where we want to stop
-        // backpropgation.
-        const grad = (dy) => {
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.isNaN($x), { $x }, grad);
-      }
-      /**
-       * Returns which elements of x are Infinity or -Infinity.
-       *
-       * ```js
-       * const x = tf.tensor1d([NaN, Infinity, -Infinity, 0, 1]);
-       *
-       * x.isInf().print();  // or tf.isNaN(x)
-       * ```
-       * @param x The input Tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function isInf_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "isInf");
-        // TODO(nsthorat): Let gradients be null for cases where we want to stop
-        // backpropgation.
-        const grad = (dy) => {
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.isInf($x), { $x }, grad);
-      }
-      /**
-       * Returns which elements of x are finite.
-       *
-       * ```js
-       * const x = tf.tensor1d([NaN, Infinity, -Infinity, 0, 1]);
-       *
-       * x.isFinite().print();  // or tf.isNaN(x)
-       * ```
-       * @param x The input Tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function isFinite_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "isFinite");
-        // TODO(nsthorat): Let gradients be null for cases where we want to stop
-        // backpropgation.
-        const grad = (dy) => {
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.isFinite($x),
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes round of input `tf.Tensor` element-wise: `round(x)`.
-       * It implements banker's rounding.
-       *
-       * ```js
-       * const x = tf.tensor1d([.6, 1.1, -3.3]);
-       *
-       * x.round().print();  // or tf.round(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function round_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "round");
-        // TODO(nsthorat): Let gradients be null for cases where we want to stop
-        // backpropgation.
-        const grad = (dy) => {
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.round($x), { $x }, grad);
-      }
-      /**
-       * Computes exponential of the input `tf.Tensor` element-wise. `e ^ x`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, -3]);
-       *
-       * x.exp().print();  // or tf.exp(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function exp_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "exp");
-        const bck = (dy, saved) => {
-          // tslint:disable-next-line: no-unnecessary-type-assertion
-          return { x: () => dy.mul(saved[0]) };
-        };
-        const attrs = {};
-        const inputsToSave = [];
-        const outputsToSave = [true];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const y = backend.exp($x);
-            save([y]);
-            return y;
-          },
-          { x: $x },
-          bck,
-          "Exp",
-          attrs,
-          inputsToSave,
-          outputsToSave
-        );
-      }
-      /**
-       * Computes exponential of the input `tf.Tensor` minus one element-wise.
-       * `e ^ x - 1`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, -3]);
-       *
-       * x.expm1().print();  // or tf.expm1(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function expm1_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "expm1");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { $x: () => dy.mul($x.exp()) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.expm1($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes natural logarithm of the input `tf.Tensor` element-wise: `ln(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, Math.E]);
-       *
-       * x.log().print();  // or tf.log(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function log_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "log");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { x: () => dy.div($x.toFloat()) };
-        };
-        const attrs = {};
-        const inputsToSave = [$x];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.log($x);
-            save([$x]);
-            return res;
-          },
-          { x: $x },
-          grad,
-          "Log",
-          attrs,
-          inputsToSave
-        );
-      }
-      /**
-       * Computes natural logarithm of the input `tf.Tensor` plus one
-       * element-wise: `ln(1 + x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, Math.E - 1]);
-       *
-       * x.log1p().print();  // or tf.log1p(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function log1p_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "log1p");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { $x: () => dy.div($x.add(1)) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.log1p($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes square root of the input `tf.Tensor` element-wise: `y = sqrt(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 4, -1]);
-       *
-       * x.sqrt().print();  // or tf.sqrt(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function sqrt_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sqrt");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { x: () => dy.div($x.toFloat().sqrt().mul(2)) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.sqrt($x);
-            save([$x]);
-            return res;
-          },
-          { x: $x },
-          grad,
-          "Sqrt",
-          {}
-        );
-      }
-      /**
-       * Computes reciprocal of square root of the input `tf.Tensor` element-wise:
-       * `y = 1 / sqrt(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 4, -1]);
-       *
-       * x.rsqrt().print();  // or tf.rsqrt(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function rsqrt_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "rsqrt");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { x: () => dy.div($x.pow(1.5).mul(2)).neg() };
-        };
-        const inputsToSave = [$x];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.rsqrt($x);
-            save([$x]);
-            return res;
-          },
-          { x: $x },
-          grad,
-          "Rsqrt",
-          {} /* attrs */,
-          inputsToSave
-        );
-      }
-      /**
-       * Computes reciprocal of x element-wise: `1 / x`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, 2]);
-       *
-       * x.reciprocal().print();  // or tf.reciprocal(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function reciprocal_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reciprocal");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { $x: () => dy.div($x.square().neg()) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.reciprocal($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes absolute value element-wise: `abs(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([-1, 2, -3, 4]);
-       *
-       * x.abs().print();  // or tf.abs(x)
-       * ```
-       * @param x The input `tf.Tensor`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function abs_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "abs");
-        if ($x.dtype === "complex64") {
-          return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.complexAbs($x), {
-            $x,
-          });
-        }
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { x: () => dy.mul($x.toFloat().step(-1)) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.abs($x);
-            save([$x]);
-            return res;
-          },
-          { x: $x },
-          grad,
-          "Abs"
-        );
-      }
-      /**
-       * Clips values element-wise. `max(min(x, clipValueMax), clipValueMin)`
-       *
-       * ```js
-       * const x = tf.tensor1d([-1, 2, -3, 4]);
-       *
-       * x.clipByValue(-2, 3).print();  // or tf.clipByValue(x, -2, 3)
-       * ```
-       * @param x The input tensor.
-       * @param clipValueMin Lower-bound of range to be clipped to.
-       * @param clipValueMax Upper-bound of range to be clipped to.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function clipByValue_(x, clipValueMin, clipValueMax) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "clipByValue");
-        util["assert"](
-          clipValueMin <= clipValueMax,
-          () =>
-            `Error in clip: min (${clipValueMin}) must be ` +
-            `less than or equal to max (${clipValueMax}).`
-        );
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return {
-            x: () =>
-              dy.where(
-                $x.greaterEqual(clipValueMin).logicalAnd($x.lessEqual(clipValueMax)),
-                Object(tensor_ops["o" /* zerosLike */])(dy)
-              ),
-          };
-        };
-        const inputsToSave = [$x];
-        const attr = { min: clipValueMin, max: clipValueMax };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.clip($x, clipValueMin, clipValueMax);
-            save([$x]);
-            return res;
-          },
-          { x: $x },
-          grad,
-          "ClipByValue",
-          attr,
-          inputsToSave
-        );
-      }
-      /**
-       * Computes sigmoid element-wise, `1 / (1 + exp(-x))`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, -1, 2, -3]);
-       *
-       * x.sigmoid().print();  // or tf.sigmoid(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function sigmoid_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sigmoid");
-        const grad = (dy, saved) => {
-          const [y] = saved;
-          return { x: () => dy.mul(y.mul(Object(tensor_ops["e" /* scalar */])(1).sub(y))) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const y = backend.sigmoid($x);
-            save([y]);
-            return y;
-          },
-          { x: $x },
-          grad,
-          "Sigmoid"
-        );
-      }
-      /**
-       * Computes log sigmoid of the input `tf.Tensor` element-wise:
-       * `logSigmoid(x)`. For numerical stability, we use `-tf.softplus(-x)`.
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, .7]);
-       *
-       * x.logSigmoid().print();  // or tf.logSigmoid(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function logSigmoid_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "logSigmoid");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { $x: () => dy.mul($x.neg().sigmoid()) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.softplus($x.neg()).neg();
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes softplus of the input `tf.Tensor` element-wise: `log(exp(x) + 1)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, .7]);
-       *
-       * x.softplus().print();  // or tf.softplus(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function softplus_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "softplus");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { $x: () => dy.mul($x.sigmoid()) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.softplus($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes sin of the input Tensor element-wise: `sin(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, Math.PI / 2, Math.PI * 3 / 4]);
-       *
-       * x.sin().print();  // or tf.sin(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function sin_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sin");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { x: () => $x.toFloat().cos().mul(dy) };
-        };
-        const inputsToSave = [$x];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.sin($x);
-            save([$x]);
-            return res;
-          },
-          { x: $x },
-          grad,
-          "Sin",
-          {} /* attrs */,
-          inputsToSave
-        );
-      }
-      /**
-       * Computes cos of the input `tf.Tensor` element-wise: `cos(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, Math.PI / 2, Math.PI * 3 / 4]);
-       *
-       * x.cos().print();  // or tf.cos(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function cos_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "cos");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { x: () => $x.toFloat().sin().neg().mul(dy) };
-        };
-        const inputsToSave = [$x];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.cos($x);
-            save([$x]);
-            return res;
-          },
-          { x: $x },
-          grad,
-          "Cos",
-          {} /* attrs */,
-          inputsToSave
-        );
-      }
-      /**
-       * Computes tan of the input `tf.Tensor` element-wise, `tan(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, Math.PI / 2, Math.PI * 3 / 4]);
-       *
-       * x.tan().print();  // or tf.tan(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function tan_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "tan");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { $x: () => dy.div($x.cos().square()) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.tan($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes asin of the input `tf.Tensor` element-wise: `asin(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, .7]);
-       *
-       * x.asin().print();  // or tf.asin(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function asin_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "asin");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return {
-            // tslint:disable-next-line: no-unnecessary-type-assertion
-            $x: () =>
-              dy.div(Object(tensor_ops["e" /* scalar */])(1).sub($x.toFloat().square()).sqrt()),
-          };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.asin($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes acos of the input `tf.Tensor` element-wise: `acos(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, .7]);
-       *
-       * x.acos().print();  // or tf.acos(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function acos_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "acos");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return {
-            $x: () => {
-              const a = $x.toFloat().square();
-              const b = Object(tensor_ops["e" /* scalar */])(1).sub(a).sqrt();
-              // tslint:disable-next-line: no-unnecessary-type-assertion
-              return dy.div(b).neg();
-            },
-          };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.acos($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes atan of the input `tf.Tensor` element-wise: `atan(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, .7]);
-       *
-       * x.atan().print();  // or tf.atan(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function atan_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "atan");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return { $x: () => dy.div($x.toFloat().square().add(1)) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.atan($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes hyperbolic sin of the input `tf.Tensor` element-wise: `sinh(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, .7]);
-       *
-       * x.sinh().print();  // or tf.sinh(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function sinh_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sinh");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          // tslint:disable-next-line: no-unnecessary-type-assertion
-          return { $x: () => $x.toFloat().cosh().mul(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.sinh($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes hyperbolic cos of the input `tf.Tensor` element-wise: `cosh(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, .7]);
-       *
-       * x.cosh().print();  // or tf.cosh(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function cosh_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "cosh");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          // tslint:disable-next-line: no-unnecessary-type-assertion
-          return { $x: () => $x.toFloat().sinh().mul(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.cosh($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes hyperbolic tangent of the input `tf.Tensor` element-wise: `tanh(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, 70]);
-       *
-       * x.tanh().print();  // or tf.tanh(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function tanh_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "tanh");
-        const grad = (dy, saved) => {
-          const [y] = saved;
-          // tslint:disable-next-line: no-unnecessary-type-assertion
-          return { x: () => Object(tensor_ops["e" /* scalar */])(1).sub(y.square()).mul(dy) };
-        };
-        const outputsToSave = [true];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const y = backend.tanh($x);
-            save([y]);
-            return y;
-          },
-          { x: $x },
-          grad,
-          "Tanh",
-          {} /* attrs */,
-          null /* inputsToSave */,
-          outputsToSave
-        );
-      }
-      /**
-       * Computes inverse hyperbolic sin of the input `tf.Tensor` element-wise:
-       * `asinh(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 1, -1, .7]);
-       *
-       * x.asinh().print();  // or tf.asinh(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function asinh_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "asinh");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return {
-            $x: () => {
-              const a = Object(tensor_ops["e" /* scalar */])(1).add($x.toFloat().square()).sqrt();
-              // tslint:disable-next-line: no-unnecessary-type-assertion
-              return dy.div(a);
-            },
-          };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.asinh($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes the inverse hyperbolic cos of the input `tf.Tensor` element-wise:
-       * `acosh(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([10, 1, 3, 5.7]);
-       *
-       * x.acosh().print();  // or tf.acosh(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function acosh_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "acosh");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return {
-            $x: () => {
-              const a = $x.toFloat().square().sub(1).sqrt();
-              // tslint:disable-next-line: no-unnecessary-type-assertion
-              return dy.div(a);
-            },
-          };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.acosh($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes inverse hyperbolic tan of the input `tf.Tensor` element-wise:
-       * `atanh(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, .1, -.1, .7]);
-       *
-       * x.atanh().print();  // or tf.atanh(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function atanh_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "atanh");
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return {
-            $x: () => dy.div(Object(tensor_ops["e" /* scalar */])(1).sub($x.toFloat().square())),
-          };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.atanh($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes gause error function of the input `tf.Tensor` element-wise:
-       * `erf(x)`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, .1, -.1, .7]);
-       *
-       * x.erf().print(); // or tf.erf(x);
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function erf_(x) {
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "erf");
-        util["assert"](
-          $x.dtype === "int32" || $x.dtype === "float32",
-          () => "Input dtype must be `int32` or `float32`."
-        );
-        if ($x.dtype === "int32") {
-          $x = $x.toFloat();
-        }
-        const grad = (dy, saved) => {
-          const [$x] = saved;
-          return {
-            $x: () =>
-              dy.mul(
-                $x
-                  .square()
-                  .neg()
-                  .exp()
-                  .mul(2 / Math.sqrt(Math.PI))
-              ),
-          };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.erf($x);
-            save([$x]);
-            return res;
-          },
-          { $x },
-          grad
-        );
-      }
-      /**
-       * Computes step of the input `tf.Tensor` element-wise: `x > 0 ? 1 : alpha * x`
-       *
-       * ```js
-       * const x = tf.tensor1d([0, 2, -1, -3]);
-       *
-       * x.step(.5).print();  // or tf.step(x, .5)
-       * ```
-       * @param x The input tensor.
-       * @param alpha The gradient when input is negative.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function step_(x, alpha = 0.0) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "step");
-        // TODO(manrajgrover): Return null for gradients when backprop supports
-        // it.
-        const grad = (dy) => {
-          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.step($x, alpha),
-          { $x },
-          grad
-        );
-      }
-      const abs = Object(operation["a" /* op */])({ abs_ });
-      const acos = Object(operation["a" /* op */])({ acos_ });
-      const acosh = Object(operation["a" /* op */])({ acosh_ });
-      const asin = Object(operation["a" /* op */])({ asin_ });
-      const asinh = Object(operation["a" /* op */])({ asinh_ });
-      const atan = Object(operation["a" /* op */])({ atan_ });
-      const atanh = Object(operation["a" /* op */])({ atanh_ });
-      const ceil = Object(operation["a" /* op */])({ ceil_ });
-      const clipByValue = Object(operation["a" /* op */])({ clipByValue_ });
-      const cos = Object(operation["a" /* op */])({ cos_ });
-      const cosh = Object(operation["a" /* op */])({ cosh_ });
-      const erf = Object(operation["a" /* op */])({ erf_ });
-      const unary_ops_exp = Object(operation["a" /* op */])({ exp_ });
-      const expm1 = Object(operation["a" /* op */])({ expm1_ });
-      const floor = Object(operation["a" /* op */])({ floor_ });
-      const log = Object(operation["a" /* op */])({ log_ });
-      const log1p = Object(operation["a" /* op */])({ log1p_ });
-      const logSigmoid = Object(operation["a" /* op */])({ logSigmoid_ });
-      const neg = Object(operation["a" /* op */])({ neg_ });
-      const reciprocal = Object(operation["a" /* op */])({ reciprocal_ });
-      const round = Object(operation["a" /* op */])({ round_ });
-      const rsqrt = Object(operation["a" /* op */])({ rsqrt_ });
-      const sigmoid = Object(operation["a" /* op */])({ sigmoid_ });
-      const sign = Object(operation["a" /* op */])({ sign_ });
-      const unary_ops_isNaN = Object(operation["a" /* op */])({ isNaN_ });
-      const isInf = Object(operation["a" /* op */])({ isInf_ });
-      const unary_ops_isFinite = Object(operation["a" /* op */])({ isFinite_ });
-      const sin = Object(operation["a" /* op */])({ sin_ });
-      const sinh = Object(operation["a" /* op */])({ sinh_ });
-      const softplus = Object(operation["a" /* op */])({ softplus_ });
-      const sqrt = Object(operation["a" /* op */])({ sqrt_ });
-      const unary_ops_step = Object(operation["a" /* op */])({ step_ });
-      const tan = Object(operation["a" /* op */])({ tan_ });
-      const tanh = Object(operation["a" /* op */])({ tanh_ });
-      //# sourceMappingURL=unary_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Atan2_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const atan2GradConfig = {
-        kernelName: kernel_names["c" /* Atan2 */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
-          const derA = () => {
-            const d = add(square(a), square(b));
-            let res = mul(dy, div(b, d));
-            const reduceAxes = getReductionAxes(a.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = sum(res, reduceAxes);
-            }
-            return reshape(res, a.shape);
-          };
-          const derB = () => {
-            const d = add(square(a), square(b));
-            let res = neg(mul(dy, div(a, d)));
-            const reduceAxes = getReductionAxes(b.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = sum(res, reduceAxes);
-            }
-            return reshape(res, b.shape);
-          };
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=Atan2_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function computePool2DInfo(
-        inShape,
-        filterSize,
-        strides,
-        dilations,
-        pad,
-        roundingMode,
-        dataFormat = "channelsLast"
-      ) {
-        const [filterHeight, filterWidth] = parseTupleParam(filterSize);
-        let filterShape;
-        if (dataFormat === "channelsLast") {
-          filterShape = [filterHeight, filterWidth, inShape[3], inShape[3]];
-        } else if (dataFormat === "channelsFirst") {
-          filterShape = [filterHeight, filterWidth, inShape[1], inShape[1]];
-        } else {
-          throw new Error(`Unknown dataFormat ${dataFormat}`);
-        }
-        return computeConv2DInfo(
-          inShape,
-          filterShape,
-          strides,
-          dilations,
-          pad,
-          roundingMode,
-          false,
-          dataFormat
-        );
-      }
-      /**
-       * Computes the information for a forward pass of a pooling3D operation.
-       */
-      function computePool3DInfo(
-        inShape,
-        filterSize,
-        strides,
-        dilations,
-        pad,
-        roundingMode,
-        dataFormat = "NDHWC"
-      ) {
-        const [filterDepth, filterHeight, filterWidth] = parse3TupleParam(filterSize);
-        let filterShape;
-        let $dataFormat;
-        if (dataFormat === "NDHWC") {
-          $dataFormat = "channelsLast";
-          filterShape = [filterDepth, filterHeight, filterWidth, inShape[4], inShape[4]];
-        } else if (dataFormat === "NCDHW") {
-          $dataFormat = "channelsFirst";
-          filterShape = [filterDepth, filterHeight, filterWidth, inShape[1], inShape[1]];
-        } else {
-          throw new Error(`Unknown dataFormat ${dataFormat}`);
-        }
-        return computeConv3DInfo(
-          inShape,
-          filterShape,
-          strides,
-          dilations,
-          pad,
-          false,
-          $dataFormat,
-          roundingMode
-        );
-      }
-      /**
-       * Computes the information for a forward pass of a convolution/pooling
-       * operation.
-       */
-      function computeConv2DInfo(
-        inShape,
-        filterShape,
-        strides,
-        dilations,
-        pad,
-        roundingMode,
-        depthwise = false,
-        dataFormat = "channelsLast"
-      ) {
-        let [batchSize, inHeight, inWidth, inChannels] = [-1, -1, -1, -1];
-        if (dataFormat === "channelsLast") {
-          [batchSize, inHeight, inWidth, inChannels] = inShape;
-        } else if (dataFormat === "channelsFirst") {
-          [batchSize, inChannels, inHeight, inWidth] = inShape;
-        } else {
-          throw new Error(`Unknown dataFormat ${dataFormat}`);
-        }
-        const [filterHeight, filterWidth, , filterChannels] = filterShape;
-        const [strideHeight, strideWidth] = parseTupleParam(strides);
-        const [dilationHeight, dilationWidth] = parseTupleParam(dilations);
-        const effectiveFilterHeight = getEffectiveFilterSize(filterHeight, dilationHeight);
-        const effectiveFilterWidth = getEffectiveFilterSize(filterWidth, dilationWidth);
-        const { padInfo, outHeight, outWidth } = getPadAndOutInfo(
-          pad,
-          inHeight,
-          inWidth,
-          strideHeight,
-          strideWidth,
-          effectiveFilterHeight,
-          effectiveFilterWidth,
-          roundingMode,
-          dataFormat
-        );
-        const outChannels = depthwise ? filterChannels * inChannels : filterChannels;
-        let outShape;
-        if (dataFormat === "channelsFirst") {
-          outShape = [batchSize, outChannels, outHeight, outWidth];
-        } else if (dataFormat === "channelsLast") {
-          outShape = [batchSize, outHeight, outWidth, outChannels];
-        }
-        return {
-          batchSize,
-          dataFormat,
-          inHeight,
-          inWidth,
-          inChannels,
-          outHeight,
-          outWidth,
-          outChannels,
-          padInfo,
-          strideHeight,
-          strideWidth,
-          filterHeight,
-          filterWidth,
-          effectiveFilterHeight,
-          effectiveFilterWidth,
-          dilationHeight,
-          dilationWidth,
-          inShape,
-          outShape,
-          filterShape,
-        };
-      }
-      /**
-       * Computes the information for a forward pass of a 3D convolution/pooling
-       * operation.
-       */
-      function computeConv3DInfo(
-        inShape,
-        filterShape,
-        strides,
-        dilations,
-        pad,
-        depthwise = false,
-        dataFormat = "channelsLast",
-        roundingMode
-      ) {
-        let [batchSize, inDepth, inHeight, inWidth, inChannels] = [-1, -1, -1, -1, -1];
-        if (dataFormat === "channelsLast") {
-          [batchSize, inDepth, inHeight, inWidth, inChannels] = inShape;
-        } else if (dataFormat === "channelsFirst") {
-          [batchSize, inChannels, inDepth, inHeight, inWidth] = inShape;
-        } else {
-          throw new Error(`Unknown dataFormat ${dataFormat}`);
-        }
-        const [filterDepth, filterHeight, filterWidth, , filterChannels] = filterShape;
-        const [strideDepth, strideHeight, strideWidth] = parse3TupleParam(strides);
-        const [dilationDepth, dilationHeight, dilationWidth] = parse3TupleParam(dilations);
-        const effectiveFilterDepth = getEffectiveFilterSize(filterDepth, dilationDepth);
-        const effectiveFilterHeight = getEffectiveFilterSize(filterHeight, dilationHeight);
-        const effectiveFilterWidth = getEffectiveFilterSize(filterWidth, dilationWidth);
-        const { padInfo, outDepth, outHeight, outWidth } = get3DPadAndOutInfo(
-          pad,
-          inDepth,
-          inHeight,
-          inWidth,
-          strideDepth,
-          strideHeight,
-          strideWidth,
-          effectiveFilterDepth,
-          effectiveFilterHeight,
-          effectiveFilterWidth,
-          roundingMode
-        );
-        const outChannels = depthwise ? filterChannels * inChannels : filterChannels;
-        let outShape;
-        if (dataFormat === "channelsFirst") {
-          outShape = [batchSize, outChannels, outDepth, outHeight, outWidth];
-        } else if (dataFormat === "channelsLast") {
-          outShape = [batchSize, outDepth, outHeight, outWidth, outChannels];
-        }
-        return {
-          batchSize,
-          dataFormat,
-          inDepth,
-          inHeight,
-          inWidth,
-          inChannels,
-          outDepth,
-          outHeight,
-          outWidth,
-          outChannels,
-          padInfo,
-          strideDepth,
-          strideHeight,
-          strideWidth,
-          filterDepth,
-          filterHeight,
-          filterWidth,
-          effectiveFilterDepth,
-          effectiveFilterHeight,
-          effectiveFilterWidth,
-          dilationDepth,
-          dilationHeight,
-          dilationWidth,
-          inShape,
-          outShape,
-          filterShape,
-        };
-      }
-      function computeOutputShape2D(inShape, fieldSize, stride, zeroPad, roundingMode) {
-        if (zeroPad == null) {
-          zeroPad = computeDefaultPad(inShape, fieldSize, stride);
-        }
-        const inputRows = inShape[0];
-        const inputCols = inShape[1];
-        const outputRows = conditionalRound(
-          (inputRows - fieldSize + 2 * zeroPad) / stride + 1,
-          roundingMode
-        );
-        util["assert"](
-          util["isInt"](outputRows),
-          () =>
-            `The output # of rows (${outputRows}) must be an integer. ` +
-            `Change the stride and/or zero pad parameters`
-        );
-        const outputCols = conditionalRound(
-          (inputCols - fieldSize + 2 * zeroPad) / stride + 1,
-          roundingMode
-        );
-        util["assert"](
-          util["isInt"](outputCols),
-          () =>
-            `The output # of columns (${outputCols}) must be an integer. ` +
-            `Change the stride and/or zero pad parameters`
-        );
-        return [outputRows, outputCols];
-      }
-      function computeOutputShape4D(
-        inShape,
-        fieldSize,
-        outChannels,
-        stride,
-        zeroPad,
-        roundingMode
-      ) {
-        if (zeroPad == null) {
-          zeroPad = computeDefaultPad(inShape, fieldSize, stride);
-        }
-        const inputDepth = inShape[0];
-        const inputRows = inShape[1];
-        const inputCols = inShape[2];
-        const outputDepths = conditionalRound(
-          (inputDepth - fieldSize + 2 * zeroPad) / stride + 1,
-          roundingMode
-        );
-        util["assert"](
-          util["isInt"](outputDepths),
-          () =>
-            `The output # of depths (${outputDepths}) must be an integer. ` +
-            `Change the stride and/or zero pad parameters`
-        );
-        const outputRows = conditionalRound(
-          (inputRows - fieldSize + 2 * zeroPad) / stride + 1,
-          roundingMode
-        );
-        util["assert"](
-          util["isInt"](outputRows),
-          () =>
-            `The output # of rows (${outputRows}) must be an integer. ` +
-            `Change the stride and/or zero pad parameters`
-        );
-        const outputCols = conditionalRound(
-          (inputCols - fieldSize + 2 * zeroPad) / stride + 1,
-          roundingMode
-        );
-        util["assert"](
-          util["isInt"](outputCols),
-          () =>
-            `The output # of columns (${outputCols}) must be an integer. ` +
-            `Change the stride and/or zero pad parameters`
-        );
-        return [outputDepths, outputRows, outputCols, outChannels];
-      }
-      function computeDefaultPad(inputShape, fieldSize, stride, dilation = 1) {
-        const effectiveFieldSize = getEffectiveFilterSize(fieldSize, dilation);
-        return Math.floor((inputShape[0] * (stride - 1) - stride + effectiveFieldSize) / 2);
-      }
-      function parseTupleParam(param) {
-        if (typeof param === "number") {
-          return [param, param, param];
-        }
-        if (param.length === 2) {
-          return [param[0], param[1], 1];
-        }
-        return param;
-      }
-      function parse3TupleParam(param) {
-        return typeof param === "number" ? [param, param, param] : param;
-      }
-      /* See https://www.tensorflow.org/api_docs/python/tf/nn/atrous_conv2d
-       * Atrous convolution is equivalent to standard convolution with upsampled
-       * filters with effective_filter_height =
-       * filter_height + (filter_height - 1) * (dilation - 1)
-       * and effective_filter_width =
-       * filter_width + (filter_width - 1) * (dilation - 1),
-       * produced by inserting dilation - 1 zeros along consecutive elements across
-       * the filters' spatial dimensions.
-       * When there is a dilation, this converts a filter dimension to the
-       * effective filter dimension, so it can be used in a standard convolution.
-       */
-      function getEffectiveFilterSize(filterSize, dilation) {
-        if (dilation <= 1) {
-          return filterSize;
-        }
-        return filterSize + (filterSize - 1) * (dilation - 1);
-      }
-      function getPadAndOutInfo(
-        pad,
-        inHeight,
-        inWidth,
-        strideHeight,
-        strideWidth,
-        filterHeight,
-        filterWidth,
-        roundingMode,
-        dataFormat
-      ) {
-        let padInfo;
-        let outHeight;
-        let outWidth;
-        if (typeof pad === "number") {
-          const padType = pad === 0 ? "VALID" : "NUMBER";
-          padInfo = { top: pad, bottom: pad, left: pad, right: pad, type: padType };
-          const outShape = computeOutputShape2D(
-            [inHeight, inWidth],
-            filterHeight,
-            strideHeight,
-            pad,
-            roundingMode
-          );
-          outHeight = outShape[0];
-          outWidth = outShape[1];
-        } else if (pad === "same") {
-          outHeight = Math.ceil(inHeight / strideHeight);
-          outWidth = Math.ceil(inWidth / strideWidth);
-          const padAlongHeight = Math.max(
-            0,
-            (outHeight - 1) * strideHeight + filterHeight - inHeight
-          );
-          const padAlongWidth = Math.max(0, (outWidth - 1) * strideWidth + filterWidth - inWidth);
-          const top = Math.floor(padAlongHeight / 2);
-          const bottom = padAlongHeight - top;
-          const left = Math.floor(padAlongWidth / 2);
-          const right = padAlongWidth - left;
-          padInfo = { top, bottom, left, right, type: "SAME" };
-        } else if (pad === "valid") {
-          padInfo = { top: 0, bottom: 0, left: 0, right: 0, type: "VALID" };
-          outHeight = Math.ceil((inHeight - filterHeight + 1) / strideHeight);
-          outWidth = Math.ceil((inWidth - filterWidth + 1) / strideWidth);
-        } else if (typeof pad === "object") {
-          const top = dataFormat === "channelsLast" ? pad[1][0] : pad[2][0];
-          const bottom = dataFormat === "channelsLast" ? pad[1][1] : pad[2][1];
-          const left = dataFormat === "channelsLast" ? pad[2][0] : pad[3][0];
-          const right = dataFormat === "channelsLast" ? pad[2][1] : pad[3][1];
-          const padType =
-            top === 0 && bottom === 0 && left === 0 && right === 0 ? "VALID" : "EXPLICIT";
-          padInfo = { top, bottom, left, right, type: padType };
-          outHeight = conditionalRound(
-            (inHeight - filterHeight + top + bottom) / strideHeight + 1,
-            roundingMode
-          );
-          outWidth = conditionalRound(
-            (inWidth - filterWidth + left + right) / strideWidth + 1,
-            roundingMode
-          );
-        } else {
-          throw Error(`Unknown padding parameter: ${pad}`);
-        }
-        return { padInfo, outHeight, outWidth };
-      }
-      function get3DPadAndOutInfo(
-        pad,
-        inDepth,
-        inHeight,
-        inWidth,
-        strideDepth,
-        strideHeight,
-        strideWidth,
-        filterDepth,
-        filterHeight,
-        filterWidth,
-        roundingMode
-      ) {
-        let padInfo;
-        let outDepth;
-        let outHeight;
-        let outWidth;
-        if (typeof pad === "number") {
-          const padType = pad === 0 ? "VALID" : "NUMBER";
-          padInfo = {
-            top: pad,
-            bottom: pad,
-            left: pad,
-            right: pad,
-            front: pad,
-            back: pad,
-            type: padType,
-          };
-          const outShape = computeOutputShape4D(
-            [inDepth, inHeight, inWidth, 1],
-            filterDepth,
-            1,
-            strideDepth,
-            pad,
-            roundingMode
-          );
-          outDepth = outShape[0];
-          outHeight = outShape[1];
-          outWidth = outShape[2];
-        } else if (pad === "same") {
-          outDepth = Math.ceil(inDepth / strideDepth);
-          outHeight = Math.ceil(inHeight / strideHeight);
-          outWidth = Math.ceil(inWidth / strideWidth);
-          const padAlongDepth = (outDepth - 1) * strideDepth + filterDepth - inDepth;
-          const padAlongHeight = (outHeight - 1) * strideHeight + filterHeight - inHeight;
-          const padAlongWidth = (outWidth - 1) * strideWidth + filterWidth - inWidth;
-          const front = Math.floor(padAlongDepth / 2);
-          const back = padAlongDepth - front;
-          const top = Math.floor(padAlongHeight / 2);
-          const bottom = padAlongHeight - top;
-          const left = Math.floor(padAlongWidth / 2);
-          const right = padAlongWidth - left;
-          padInfo = { top, bottom, left, right, front, back, type: "SAME" };
-        } else if (pad === "valid") {
-          padInfo = {
-            top: 0,
-            bottom: 0,
-            left: 0,
-            right: 0,
-            front: 0,
-            back: 0,
-            type: "VALID",
-          };
-          outDepth = Math.ceil((inDepth - filterDepth + 1) / strideDepth);
-          outHeight = Math.ceil((inHeight - filterHeight + 1) / strideHeight);
-          outWidth = Math.ceil((inWidth - filterWidth + 1) / strideWidth);
-        } else {
-          throw Error(`Unknown padding parameter: ${pad}`);
-        }
-        return { padInfo, outDepth, outHeight, outWidth };
-      }
-      /**
-       * Rounds a value depending on the rounding mode
-       * @param value
-       * @param roundingMode
-       */
-      function conditionalRound(value, roundingMode) {
-        if (!roundingMode) {
-          return value;
-        }
-        switch (roundingMode) {
-          case "round":
-            // used for Caffe Conv
-            return Math.round(value);
-          case "ceil":
-            // used for Caffe Pool
-            return Math.ceil(value);
-          case "floor":
-            return Math.floor(value);
-          default:
-            throw new Error(`Unknown roundingMode ${roundingMode}`);
-        }
-      }
-      function tupleValuesAreOne(param) {
-        const [dimA, dimB, dimC] = parseTupleParam(param);
-        return dimA === 1 && dimB === 1 && dimC === 1;
-      }
-      function eitherStridesOrDilationsAreOne(strides, dilations) {
-        return tupleValuesAreOne(strides) || tupleValuesAreOne(dilations);
-      }
-      /**
-       * Convert Conv2D dataFormat from 'NHWC'|'NCHW' to
-       *    'channelsLast'|'channelsFirst'
-       * @param dataFormat in 'NHWC'|'NCHW' mode
-       * @return dataFormat in 'channelsLast'|'channelsFirst' mode
-       * @throws unknown dataFormat
-       */
-      function convertConv2DDataFormat(dataFormat) {
-        if (dataFormat === "NHWC") {
-          return "channelsLast";
-        } else if (dataFormat === "NCHW") {
-          return "channelsFirst";
-        } else {
-          throw new Error(`Unknown dataFormat ${dataFormat}`);
-        }
-      }
-      //# sourceMappingURL=conv_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_3d_backprop.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the backprop of a 3d avg pool.
-       *
-       * @param dy The dy error, of rank 5 of shape
-       *     [batchSize, depth, height, width, channels].
-       * assumed.
-       * @param input The original input image, of rank 5 or rank4 of shape
-       *     [batchSize, depth, height, width, channels].
-       * @param filterSize The filter size:
-       *     `[filterDepth, filterHeight, filterWidth]`.
-       *     `filterSize` is a single number,
-       *     then `filterDepth == filterHeight == filterWidth`.
-       * @param strides The strides of the pooling:
-       *     `[strideDepth, strideHeight, strideWidth]`. If
-       *     `strides` is a single number, then `strideHeight == strideWidth`.
-       * @param dilations Deprecated, this field will be gone in v3.0.0. The dilation
-       *     rates: `[dilationDepth, dilationHeight, dilationWidth]`
-       *     in which we sample input values across the depth, height and width
-       *     dimensions in dilated pooling.
-       *     Defaults to `[1, 1, 1]`. If `dilations` is a single number,
-       *     then `dilationDepth == dilationHeight == dilationWidth`.
-       *     If it is greater than 1, then all values of `strides` must be 1.
-       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
-       *     used in the forward prop of the op.
-       * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. The
-       *     rounding mode used when computing output dimensions if pad is a
-       *     number. If none is provided, it will not round and error if the output
-       *     is of fractional size.
-       */
-      function avgPool3dBackprop_(
-        dy,
-        input,
-        filterSize,
-        strides,
-        dilations = [1, 1, 1],
-        pad,
-        dimRoundingMode
-      ) {
-        const $dy = Object(tensor_util_env["a" /* convertToTensor */])(
-          dy,
-          "dy",
-          "avgPool3dBackprop"
-        );
-        const $input = Object(tensor_util_env["a" /* convertToTensor */])(
-          input,
-          "input",
-          "avgPool3dBackprop"
-        );
-        let dy5D = $dy;
-        let input5D = $input;
-        let reshapedTo5D = false;
-        if ($input.rank === 4) {
-          reshapedTo5D = true;
-          dy5D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]);
-          input5D = reshape($input, [
-            1,
-            $input.shape[0],
-            $input.shape[1],
-            $input.shape[2],
-            $input.shape[3],
-          ]);
-        }
-        util["assert"](
-          dy5D.rank === 5,
-          () => `Error in avgPool3dBackprop: dy must be rank 5 but got rank ` + `${dy5D.rank}.`
-        );
-        util["assert"](
-          input5D.rank === 5,
-          () =>
-            `Error in avgPool3dBackprop: input must be rank 5 but got rank ` + `${input5D.rank}.`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in avgPool3dBackprop: Either strides or dilations " +
-            `must be 1. Got strides ${strides} and dilations '${dilations}'`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in maxPool3dBackprop: pad must be an integer when ` +
-              `using, dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend) => {
-          const convInfo = computePool3DInfo(
-            input5D.shape,
-            filterSize,
-            strides,
-            dilations,
-            pad,
-            dimRoundingMode
-          );
-          return backend.avgPool3dBackprop(dy5D, input5D, convInfo);
-        };
-        const inputs = { dy: dy5D, input: input5D };
-        const attrs = { filterSize, strides, dilations, pad, dimRoundingMode };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["f" /* AvgPool3DBackprop */],
-          attrs
-        );
-        if (reshapedTo5D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);
-        }
-        return res;
-      }
-      const avgPool3dBackprop = Object(operation["a" /* op */])({ avgPool3dBackprop_ });
-      //# sourceMappingURL=avg_pool_3d_backprop.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/AvgPool3D_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const avgPool3DGradConfig = {
-        kernelName: kernel_names["e" /* AvgPool3D */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved, attrs) => {
-          const [x] = saved;
-          const { filterSize, strides, dilations, pad, dimRoundingMode } = attrs;
-          const $dilations = dilations == null ? [1, 1, 1] : dilations;
-          return {
-            x: () =>
-              avgPool3dBackprop(dy, x, filterSize, strides, $dilations, pad, dimRoundingMode),
-          };
-        },
-      };
-      //# sourceMappingURL=AvgPool3D_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_backprop.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the backprop of an 2D avg pool.
-       *
-       * @param dy The dy error, of rank 4 or rank 3 of shape
-       *     [batchSize, height, width, channels]. If rank 3, batch of 1 is
-       * assumed.
-       * @param input The input image, of rank 4 or rank 3 of shape
-       *     [batchSize, height, width, channels]. If rank 3, batch of 1 is
-       * assumed.
-       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
-       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
-       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
-       *     `strides` is a single number, then `strideHeight == strideWidth`.
-       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
-       *     used in the forward prop of the op.
-       */
-      function avgPoolBackprop_(dy, input, filterSize, strides, pad) {
-        const $dy = Object(tensor_util_env["a" /* convertToTensor */])(dy, "dy", "avgPoolBackprop");
-        const $input = Object(tensor_util_env["a" /* convertToTensor */])(
-          input,
-          "input",
-          "avgPoolBackprop"
-        );
-        util["assert"](
-          $input.rank === $dy.rank,
-          () => `Rank of input (${$input.rank}) does not match rank of dy (${$dy.rank})`
-        );
-        let input4D = $input;
-        let dy4D = $dy;
-        let reshapedTo4D = false;
-        if ($input.rank === 3) {
-          reshapedTo4D = true;
-          input4D = reshape($input, [1, $input.shape[0], $input.shape[1], $input.shape[2]]);
-          dy4D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2]]);
-        }
-        util["assert"](
-          dy4D.rank === 4,
-          () => `Error in avgPoolBackprop: dy must be rank 4 but got rank ` + `${dy4D.rank}.`
-        );
-        util["assert"](
-          input4D.rank === 4,
-          () => `Error in avgPoolBackprop: input must be rank 4 but got rank ` + `${input4D.rank}.`
-        );
-        const forward = (backend) => {
-          const convInfo = computePool2DInfo(
-            input4D.shape,
-            filterSize,
-            strides,
-            1 /* dilations */,
-            pad
-          );
-          return backend.avgPoolBackprop(dy4D, input4D, convInfo);
-        };
-        const inputs = { dy: dy4D, input: input4D };
-        const attrs = { filterSize, strides, pad };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null,
-          kernel_names["g" /* AvgPoolBackprop */],
-          attrs
-        );
-        if (reshapedTo4D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
-        }
-        return res;
-      }
-      const avgPoolBackprop = Object(operation["a" /* op */])({ avgPoolBackprop_ });
-      //# sourceMappingURL=avg_pool_backprop.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/AvgPool_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const avgPoolGradConfig = {
-        kernelName: kernel_names["d" /* AvgPool */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved, attrs) => {
-          const [x] = saved;
-          const { filterSize, strides, pad } = attrs;
-          return {
-            x: () => avgPoolBackprop(dy, x, filterSize, strides, pad),
-          };
-        },
-      };
-      //# sourceMappingURL=AvgPool_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/mat_mul.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the dot product of two matrices, A * B. These must be matrices.
-       *
-       * ```js
-       * const a = tf.tensor2d([1, 2], [1, 2]);
-       * const b = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * a.matMul(b).print();  // or tf.matMul(a, b)
-       * ```
-       * @param a First matrix in dot product operation.
-       * @param b Second matrix in dot product operation.
-       * @param transposeA If true, `a` is transposed before multiplication.
-       * @param transposeB If true, `b` is transposed before multiplication.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
-      function matMul_(a, b, transposeA = false, transposeB = false) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "matMul");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "matMul");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        util["assert"](
-          $a.rank >= 2 && $b.rank >= 2 && $a.rank === $b.rank,
-          () =>
-            `Error in matMul: inputs must have the same rank of at least 2, ` +
-            `got ranks ${$a.rank} and ${$b.rank}.`
-        );
-        const innerShapeA = transposeA ? $a.shape[$a.rank - 2] : $a.shape[$a.rank - 1];
-        const innerShapeB = transposeB ? $b.shape[$b.rank - 1] : $b.shape[$b.rank - 2];
-        const outerShapeA = transposeA ? $a.shape[$a.rank - 1] : $a.shape[$a.rank - 2];
-        const outerShapeB = transposeB ? $b.shape[$b.rank - 2] : $b.shape[$b.rank - 1];
-        const outerDimsA = $a.shape.slice(0, -2);
-        const outerDimsB = $b.shape.slice(0, -2);
-        const batchDimA = util["sizeFromShape"](outerDimsA);
-        const batchDimB = util["sizeFromShape"](outerDimsB);
-        util["assert"](
-          util["arraysEqual"](outerDimsA, outerDimsB),
-          () =>
-            `Error in matMul: outer dimensions (${outerDimsA}) and (` +
-            `${outerDimsB}) of Tensors with shapes ${$a.shape} and ` +
-            `${$b.shape} must match.`
-        );
-        util["assert"](
-          innerShapeA === innerShapeB,
-          () =>
-            `Error in matMul: inner shapes (${innerShapeA}) and (` +
-            `${innerShapeB}) of Tensors with shapes ${$a.shape} and ` +
-            `${$b.shape} and transposeA=${transposeA}` +
-            ` and transposeB=${transposeB} must match.`
-        );
-        const outShape = $a.shape.slice(0, -2).concat([outerShapeA, outerShapeB]);
-        const a3D = transposeA
-          ? reshape($a, [batchDimA, innerShapeA, outerShapeA])
-          : reshape($a, [batchDimA, outerShapeA, innerShapeA]);
-        const b3D = transposeB
-          ? reshape($b, [batchDimB, outerShapeB, innerShapeB])
-          : reshape($b, [batchDimB, innerShapeB, outerShapeB]);
-        const forward = (backend, save) => {
-          save([a3D, b3D]);
-          return backend.batchMatMul(a3D, b3D, transposeA, transposeB);
-        };
-        const inputs = { a: a3D, b: b3D };
-        const attrs = { transposeA, transposeB };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["h" /* BatchMatMul */],
-          attrs
-        );
-        return reshape(res, outShape);
-      }
-      const matMul = Object(operation["a" /* op */])({ matMul_ });
-      //# sourceMappingURL=mat_mul.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/BatchMatMul_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const batchMatMulGradConfig = {
-        kernelName: kernel_names["h" /* BatchMatMul */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved, attrs) => {
-          const [a, b] = saved;
-          const { transposeA, transposeB } = attrs;
-          if (!transposeA && !transposeB) {
-            return {
-              a: () => matMul(dy, b, false, true),
-              b: () => matMul(a, dy, true, false),
-            };
-          } else if (!transposeA && transposeB) {
-            return {
-              a: () => matMul(dy, b, false, false),
-              b: () => matMul(dy, a, true, false),
-            };
-          } else if (transposeA && !transposeB) {
-            return {
-              a: () => matMul(b, dy, false, true),
-              b: () => matMul(a, dy, false, false),
-            };
-          } else {
-            return {
-              a: () => matMul(b, dy, true, true),
-              b: () => matMul(dy, a, true, true),
-            };
-          }
-        },
-      };
-      //# sourceMappingURL=BatchMatMul_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/space_to_batch_nd.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * This operation divides "spatial" dimensions `[1, ..., M]` of the input into
-       * a grid of blocks of shape `blockShape`, and interleaves these blocks with
-       * the "batch" dimension (0) such that in the output, the spatial
-       * dimensions `[1, ..., M]` correspond to the position within the grid,
-       * and the batch dimension combines both the position within a spatial block
-       * and the original batch position. Prior to division into blocks,
-       * the spatial dimensions of the input are optionally zero padded
-       * according to `paddings`. See below for a precise description.
-       *
-       * ```js
-       * const x = tf.tensor4d([1, 2, 3, 4], [1, 2, 2, 1]);
-       * const blockShape = [2, 2];
-       * const paddings = [[0, 0], [0, 0]];
-       *
-       * x.spaceToBatchND(blockShape, paddings).print();
-       * ```
-       *
-       * @param x A `tf.Tensor`. N-D with `x.shape` = `[batch] + spatialShape +
-       * remainingShape`, where spatialShape has `M` dimensions.
-       * @param blockShape A 1-D array. Must have shape `[M]`, all values must
-       * be >= 1.
-       * @param paddings A 2-D array. Must have shape `[M, 2]`, all values must be >=
-       *     0. `paddings[i] = [padStart, padEnd]` specifies the amount to zero-pad
-       * from input dimension `i + 1`, which corresponds to spatial dimension `i`. It
-       * is required that
-       * `(inputShape[i + 1] + padStart + padEnd) % blockShape[i] === 0`
-       *
-       * This operation is equivalent to the following steps:
-       *
-       * 1. Zero-pad the start and end of dimensions `[1, ..., M]` of the input
-       * according to `paddings` to produce `padded` of shape paddedShape.
-       *
-       * 2. Reshape `padded` to `reshapedPadded` of shape:
-       * `[batch] + [paddedShape[1] / blockShape[0], blockShape[0], ...,
-       * paddedShape[M] / blockShape[M-1], blockShape[M-1]] + remainingShape`
-       *
-       * 3. Permute dimensions of `reshapedPadded` to produce `permutedReshapedPadded`
-       * of shape: `blockShape + [batch] + [paddedShape[1] / blockShape[0], ...,
-       * paddedShape[M] / blockShape[M-1]] + remainingShape`
-       *
-       * 4. Reshape `permutedReshapedPadded` to flatten `blockShape` into the
-       * batch dimension, producing an output tensor of shape:
-       * `[batch * prod(blockShape)] + [paddedShape[1] / blockShape[0], ...,
-       * paddedShape[M] / blockShape[M-1]] + remainingShape`
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function spaceToBatchND_(x, blockShape, paddings) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "spaceToBatchND");
-        util["assert"](
-          $x.rank >= 1 + blockShape.length,
-          () => `input rank ${$x.rank} should be > than [blockShape] ${blockShape.length}`
-        );
-        util["assert"](
-          paddings.length === blockShape.length,
-          () =>
-            `paddings.shape[0] ${paddings.length} must be equal to [blockShape] ${blockShape.length}`
-        );
-        util["assert"](
-          $x.shape.reduce((a, b, i) => {
-            if (i > 0 && i <= blockShape.length) {
-              return a && (b + paddings[i - 1][0] + paddings[i - 1][1]) % blockShape[i - 1] === 0;
-            }
-            return a;
-          }, true),
-          () =>
-            `input spatial dimensions ${$x.shape.slice(
-              1
-            )} with paddings ${paddings.toString()} must be divisible by blockShapes ${blockShape.toString()}`
-        );
-        const forward = (backend) => backend.spaceToBatchND($x, blockShape, paddings);
-        const inputs = { x: $x };
-        const attrs = { blockShape, paddings };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["mb" /* SpaceToBatchND */],
-          attrs
-        );
-      }
-      const spaceToBatchND = Object(operation["a" /* op */])({ spaceToBatchND_ });
-      //# sourceMappingURL=space_to_batch_nd.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/BatchToSpaceND_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const batchToSpaceNDGradConfig = {
-        kernelName: kernel_names["i" /* BatchToSpaceND */],
-        gradFunc: (dy, saved, attrs) => {
-          const { blockShape, crops } = attrs;
-          return { x: () => spaceToBatchND(dy, blockShape, crops) };
-        },
-      };
-      //# sourceMappingURL=BatchToSpaceND_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/BroadcastTo_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const broadcastToGradConfig = {
-        kernelName: kernel_names["j" /* BroadcastTo */],
-        gradFunc: (dy, saved, attrs) => {
-          const broadCastToAttrs = attrs;
-          const inputShape = broadCastToAttrs.inputShape;
-          const outputShape = broadCastToAttrs.shape;
-          const reps = Array.from(outputShape);
-          for (let i = inputShape.length - 1; i >= 0; i--) {
-            if (inputShape[i] === outputShape[i]) {
-              reps[i] = 1;
-            } else if (inputShape[i] !== 1) {
-              throw new Error(
-                `broadcastTo(): [${inputShape}] cannot be broadcast to [${outputShape}].`
-              );
-            }
-          }
-          const axes = [];
-          for (let i = 0; i < reps.length; i++) {
-            if (reps[i] > 1) {
-              axes.push(i);
-            }
-          }
-          return { x: () => sum(dy, axes, true /* keepDims */) };
-        },
-      };
-      //# sourceMappingURL=BroadcastTo_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/split.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Splits a `tf.Tensor` into sub tensors.
-       *
-       * If `numOrSizeSplits` is a number, splits `x` along dimension `axis`
-       * into `numOrSizeSplits` smaller tensors.
-       * Requires that `numOrSizeSplits` evenly divides `x.shape[axis]`.
-       *
-       * If `numOrSizeSplits` is a number array, splits `x` into
-       * `numOrSizeSplits.length` pieces. The shape of the `i`-th piece has the
-       * same size as `x` except along dimension `axis` where the size is
-       * `numOrSizeSplits[i]`.
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);
-       * const [a, b] = tf.split(x, 2, 1);
-       * a.print();
-       * b.print();
-       *
-       * const [c, d, e] = tf.split(x, [1, 2, 1], 1);
-       * c.print();
-       * d.print();
-       * e.print();
-       * ```
-       *
-       * @param x The input tensor to split.
-       * @param numOrSizeSplits Either an integer indicating the number of
-       * splits along the axis or an array of integers containing the sizes of
-       * each output tensor along the axis. If a number then it must evenly divide
-       * `x.shape[axis]`; otherwise the sum of sizes must match `x.shape[axis]`.
-       * @param axis The dimension along which to split. Defaults to 0 (the first
-       * dim).
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      function split_(x, numOrSizeSplits, axis = 0) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "split");
-        const $axis = Object(util["parseAxisParam"])(axis, $x.shape)[0];
-        let splitSizes;
-        if (typeof numOrSizeSplits === "number") {
-          Object(util["assert"])(
-            $x.shape[$axis] % numOrSizeSplits === 0,
-            () => "Number of splits must evenly divide the axis."
-          );
-          splitSizes = new Array(numOrSizeSplits).fill($x.shape[$axis] / numOrSizeSplits);
-        } else {
-          Object(util["assert"])(
-            $x.shape[$axis] === numOrSizeSplits.reduce((a, b) => a + b),
-            () => "The sum of sizes must match the size of the axis dimension."
-          );
-          splitSizes = numOrSizeSplits;
-        }
-        const forward = (backend, _) => {
-          return backend.split($x, splitSizes, $axis);
-        };
-        const inputs = { x: $x };
-        const attr = { numOrSizeSplits, axis };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["nb" /* SplitV */],
-          attr
-        );
-      }
-      const split = Object(operation["a" /* op */])({ split_ });
-      //# sourceMappingURL=split.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Concat_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const concatGradConfig = {
-        kernelName: kernel_names["l" /* Concat */],
-        saveAllInputs: true,
-        gradFunc: (dy, saved, attrs) => {
-          const shapes = saved.map((t) => t.shape);
-          const { axis } = attrs;
-          const $axis = Object(util["parseAxisParam"])(axis, saved[0].shape)[0];
-          const sizeSplits = shapes.map((s) => s[$axis]);
-          const derTensors = split(dy, sizeSplits, $axis);
-          return derTensors.map((t) => () => t);
-        },
-      };
-      //# sourceMappingURL=Concat_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_backprop_filter.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the derivative of the filter of a 2D convolution.
-       *
-       * @param x The input tensor, of rank 4 or rank 3 of shape
-       *     [batch, height, width, inChannels]. If rank 3, batch of 1 is assumed.
-       * @param dy The dy image, of rank 4 or rank 3, of shape
-       *     [batch, height, width, outDepth]. If rank 3, batch of 1 is assumed.
-       * @param filterShape The shape of the filter, length 4,
-       *     [filterHeight, filterWidth, inDepth, outDepth].
-       * @param strides The strides of the convolution: [strideHeight,
-       * strideWidth].
-       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
-       *     used in the forward prop of the op.
-       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
-       *     "NHWC". Specify the data format of the input and output data. With the
-       *     default format "NHWC", the data is stored in the order of: [batch,
-       *     height, width, channels].
-       * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. The
-       *     rounding mode used when computing output dimensions if pad is a
-       *     number. If none is provided, it will not round and error if the output
-       *     is of fractional size.
-       */
-      function conv2DBackpropFilter_(
-        x,
-        dy,
-        filterShape,
-        strides,
-        pad,
-        dataFormat = "NHWC",
-        dimRoundingMode
-      ) {
-        let x4D = x;
-        if (x.rank === 3) {
-          x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);
-        }
-        let dy4D = dy;
-        if (dy4D.rank === 3) {
-          dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
-        }
-        util["assert"](
-          x4D.rank === 4,
-          () => `Error in conv2dDerFilter: input must be rank 4, but got shape ` + `${x4D.shape}.`
-        );
-        util["assert"](
-          dy4D.rank === 4,
-          () => `Error in conv2dDerFilter: dy must be rank 4, but got shape ` + `${dy4D.shape}.`
-        );
-        util["assert"](
-          filterShape.length === 4,
-          () =>
-            `Error in conv2dDerFilter: filterShape must be length 4, but got ` + `${filterShape}.`
-        );
-        const inDepth = dataFormat === "NHWC" ? x4D.shape[3] : x4D.shape[1];
-        const outDepth = dataFormat === "NHWC" ? dy4D.shape[3] : dy4D.shape[1];
-        util["assert"](
-          inDepth === filterShape[2],
-          () =>
-            `Error in conv2dDerFilter: depth of input ${inDepth}) must ` +
-            `match input depth in filter (${filterShape[2]}.`
-        );
-        util["assert"](
-          outDepth === filterShape[3],
-          () =>
-            `Error in conv2dDerFilter: depth of dy (${outDepth}) must ` +
-            `match output depth for filter (${filterShape[3]}).`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in conv2dDerFilter: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend) => {
-          const dilations = 1;
-          const $dataFormat = convertConv2DDataFormat(dataFormat);
-          const convInfo = computeConv2DInfo(
-            x4D.shape,
-            filterShape,
-            strides,
-            dilations,
-            pad,
-            dimRoundingMode,
-            false,
-            $dataFormat
-          );
-          return backend.conv2dDerFilter(x4D, dy4D, convInfo);
-        };
-        const inputs = { x: x4D, dy: dy4D };
-        const attrs = { strides, pad, dataFormat, dimRoundingMode };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null,
-          kernel_names["n" /* Conv2DBackpropFilter */],
-          attrs
-        );
-      }
-      const conv2DBackpropFilter = Object(operation["a" /* op */])({ conv2DBackpropFilter_ });
-      //# sourceMappingURL=conv2d_backprop_filter.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_backprop_input.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the derivative of the input of a 2D convolution.
-       *
-       * @param xShape The shape of the input: [batch, height, width, inDepth].
-       * If length of 3, batch of 1 is assumed.
-       * @param dy The derivative of the output, of rank 4 or rank 3 of shape
-       *   `[batch, outHeight, outWidth, outDepth]`. If rank 3, batch of 1 is
-       * assumed.
-       * @param filter The filter, rank 4, of shape
-       *     `[filterHeight, filterWidth, inDepth, outDepth]`.
-       * @param strides The strides of the convolution: `[strideHeight,
-       * strideWidth]`.
-       * @param pad The type of padding algorithm used:
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
-       *     "NHWC". Specify the data format of the input and output data. With the
-       *     default format "NHWC", the data is stored in the order of: [batch,
-       *     height, width, channels].
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       */
-      function conv2DBackpropInput_(
-        xShape,
-        dy,
-        filter,
-        strides,
-        pad,
-        dataFormat = "NHWC",
-        dimRoundingMode
-      ) {
-        util["assert"](
-          xShape.length === dy.rank,
-          () => `Length of inShape ` + `(${xShape.length}) and rank of dy (${dy.rank}) must match`
-        );
-        let xShape4D = xShape;
-        let dy4D = dy;
-        let reshapedTo4D = false;
-        if (dy.rank === 3) {
-          reshapedTo4D = true;
-          dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
-          xShape4D = [1, xShape[0], xShape[1], xShape[2]];
-        }
-        util["assert"](
-          xShape4D.length === 4,
-          () =>
-            `Error in conv2dDerInput: inShape must be length 4, but got length ` +
-            `${xShape4D.length}.`
-        );
-        util["assert"](
-          dy4D.rank === 4,
-          () => `Error in conv2dDerInput: dy must be rank 4, but got ` + `rank ${dy4D.rank}`
-        );
-        util["assert"](
-          filter.rank === 4,
-          () => `Error in conv2dDerInput: filter must be rank 4, but got ` + `rank ${filter.rank}`
-        );
-        const inDepth = dataFormat === "NHWC" ? xShape4D[3] : xShape4D[1];
-        const outDepth = dataFormat === "NHWC" ? dy4D.shape[3] : dy4D.shape[1];
-        util["assert"](
-          inDepth === filter.shape[2],
-          () =>
-            `Error in conv2dDerInput: depth of input (${inDepth}) must ` +
-            `match input depth for filter ${filter.shape[2]}.`
-        );
-        util["assert"](
-          outDepth === filter.shape[3],
-          () =>
-            `Error in conv2dDerInput: depth of output (${outDepth}) must ` +
-            `match output depth for filter ${filter.shape[3]}.`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in conv2dDerInput: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend, save) => {
-          const dilations = 1;
-          const $dataFormat = convertConv2DDataFormat(dataFormat);
-          const convInfo = computeConv2DInfo(
-            xShape4D,
-            filter.shape,
-            strides,
-            dilations,
-            pad,
-            dimRoundingMode,
-            false,
-            $dataFormat
-          );
-          const res = backend.conv2dDerInput(dy4D, filter, convInfo);
-          save([dy4D, filter]);
-          return res;
-        };
-        const inputs = { dy: dy4D, filter };
-        const attrs = { strides, pad, dataFormat, dimRoundingMode };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["o" /* Conv2DBackpropInput */],
-          attrs
-        );
-        if (reshapedTo4D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
-        }
-        return res;
-      }
-      const conv2DBackpropInput = Object(operation["a" /* op */])({ conv2DBackpropInput_ });
-      //# sourceMappingURL=conv2d_backprop_input.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Conv2D_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const conv2DGradConfig = {
-        kernelName: kernel_names["m" /* Conv2D */],
-        inputsToSave: ["x", "filter"],
-        gradFunc: (dy, saved, attrs) => {
-          const [x4D, $filter] = saved;
-          const { dilations, strides, pad, dataFormat } = attrs;
-          util["assert"](
-            tupleValuesAreOne(dilations),
-            () =>
-              "Error in gradient of conv2D: dilation rates greater than 1 " +
-              `are not yet supported in gradients. Got dilations '${dilations}'`
-          );
-          return {
-            x: () => conv2DBackpropInput(x4D.shape, dy, $filter, strides, pad, dataFormat),
-            filter: () => conv2DBackpropFilter(x4D, dy, $filter.shape, strides, pad, dataFormat),
-          };
-        },
-      };
-      //# sourceMappingURL=Conv2D_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv2d.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes a 2D convolution over the input x.
-       *
-       * @param x The input tensor, of rank 4 or rank 3, of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
-       * assumed.
-       * @param filter The filter, rank 4, of shape
-       *     `[filterHeight, filterWidth, inDepth, outDepth]`.
-       * @param strides The strides of the convolution: `[strideHeight,
-       * strideWidth]`.
-       * @param pad The type of padding algorithm.
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *   - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
-       *     "NHWC". Specify the data format of the input and output data. With the
-       *     default format "NHWC", the data is stored in the order of: [batch,
-       *     height, width, channels].
-       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
-       *     in which we sample input values across the height and width dimensions
-       *     in atrous convolution. Defaults to `[1, 1]`. If `dilations` is a single
-       *     number, then `dilationHeight == dilationWidth`. If it is greater than
-       *     1, then all values of `strides` must be 1.
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function conv2d_(
-        x,
-        filter,
-        strides,
-        pad,
-        dataFormat = "NHWC",
-        dilations = [1, 1],
-        dimRoundingMode
-      ) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv2d");
-        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
-          filter,
-          "filter",
-          "conv2d"
-        );
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
-        }
-        util["assert"](
-          x4D.rank === 4,
-          () => `Error in conv2d: input must be rank 4, but got rank ${x4D.rank}.`
-        );
-        util["assert"](
-          $filter.rank === 4,
-          () => `Error in conv2d: filter must be rank 4, but got rank ` + `${$filter.rank}.`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in conv2d: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const inDepth = dataFormat === "NHWC" ? x4D.shape[3] : x4D.shape[1];
-        util["assert"](
-          inDepth === $filter.shape[2],
-          () =>
-            `Error in conv2d: depth of input (${inDepth}) must match ` +
-            `input depth for filter ${$filter.shape[2]}.`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in conv2D: Either strides or dilations must be 1. " +
-            `Got strides ${strides} and dilations '${dilations}'`
-        );
-        const forward = (backend, save) => {
-          const $dataFormat = convertConv2DDataFormat(dataFormat);
-          const convInfo = computeConv2DInfo(
-            x4D.shape,
-            $filter.shape,
-            strides,
-            dilations,
-            pad,
-            dimRoundingMode,
-            false,
-            $dataFormat
-          );
-          const res = backend.conv2d(x4D, $filter, convInfo);
-          save([x4D, $filter]);
-          return res;
-        };
-        const inputs = { x: x4D, filter: $filter };
-        const attrs = { strides, pad, dataFormat, dilations, dimRoundingMode };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["m" /* Conv2D */],
-          attrs
-        );
-        if (reshapedTo4D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
-        }
-        return res;
-      }
-      const conv2d = Object(operation["a" /* op */])({ conv2d_ });
-      //# sourceMappingURL=conv2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Conv2DBackpropInput_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const conv2DBackpropInputGradConfig = {
-        kernelName: kernel_names["o" /* Conv2DBackpropInput */],
-        inputsToSave: ["dy", "filter"],
-        gradFunc: (ddx, saved, attrs) => {
-          const [dy, filter] = saved;
-          const { strides, pad, dataFormat, dimRoundingMode } = attrs;
-          return {
-            dy: () =>
-              conv2d(ddx, filter, strides, pad, dataFormat, 1 /* dilations */, dimRoundingMode),
-            filter: () =>
-              conv2DBackpropFilter(
-                ddx,
-                dy,
-                filter.shape,
-                strides,
-                pad,
-                dataFormat,
-                dimRoundingMode
-              ),
-          };
-        },
-      };
-      //# sourceMappingURL=Conv2DBackpropInput_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_backprop_filter.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the derivative of the filter of a 3D convolution.
-       *
-       * @param x The input tensor, of rank 5 or rank 4 of shape
-       *     [batch, depth, height, width, inChannels]. If rank 4, batch of 1 is
-       *     assumed.
-       * @param dy The dy image, of rank 5 or rank 4, of shape
-       *     [batch, depth, height, width, outDepth]. If rank 4, batch of 1 is
-       *     assumed.
-       * @param filterShape The shape of the filter, length 5,
-       *     [filterDepth, filterHeight, filterWidth, inDepth, outDepth].
-       * @param strides The strides of the convolution: [strideDepth, strideHeight,
-       * strideWidth].
-       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
-       *     used in the forward prop of the op.
-       */
-      function conv3DBackpropFilter_(x, dy, filterShape, strides, pad) {
-        let x5D = x;
-        if (x.rank === 4) {
-          x5D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2], x.shape[3]]);
-        }
-        let dy5D = dy;
-        if (dy5D.rank === 4) {
-          dy5D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2], dy.shape[3]]);
-        }
-        util["assert"](
-          x5D.rank === 5,
-          () => `Error in conv3dDerFilter: input must be rank 5, but got shape ` + `${x5D.shape}.`
-        );
-        util["assert"](
-          dy5D.rank === 5,
-          () => `Error in conv3dDerFilter: dy must be rank 5, but got shape ` + `${dy5D.shape}.`
-        );
-        util["assert"](
-          filterShape.length === 5,
-          () =>
-            `Error in conv3dDerFilter: filterShape must be length 5, but got ` + `${filterShape}.`
-        );
-        util["assert"](
-          x5D.shape[4] === filterShape[3],
-          () =>
-            `Error in conv3dDerFilter: depth of input ${x5D.shape[4]}) must ` +
-            `match input depth in filter (${filterShape[3]}.`
-        );
-        util["assert"](
-          dy5D.shape[4] === filterShape[4],
-          () =>
-            `Error in conv3dDerFilter: depth of dy (${dy5D.shape[4]}) must ` +
-            `match output depth for filter (${filterShape[4]}).`
-        );
-        const forward = (backend) => {
-          const dilations = 1;
-          const convInfo = computeConv3DInfo(x5D.shape, filterShape, strides, dilations, pad);
-          return backend.conv3dDerFilter(x5D, dy5D, convInfo);
-        };
-        const inputs = { x: x5D, y: dy5D };
-        const attrs = { strides, pad };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null,
-          kernel_names["q" /* Conv3DBackpropFilterV2 */],
-          attrs
-        );
-      }
-      const conv3DBackpropFilter = Object(operation["a" /* op */])({ conv3DBackpropFilter_ });
-      //# sourceMappingURL=conv3d_backprop_filter.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_backprop_input.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the derivative of the input of a 3D convolution.
-       *
-       * @param xShape The shape of the input: [batch, depth, height, width,
-       * in_channels]. If length of 4, batch of 1 is assumed.
-       * @param dy The derivative of the output, of rank 5 or rank 4 of shape
-       *   `[batch, outDepth, outHeight, outWidth, in_channels]`.
-       * If rank 4, batch of 1 is assumed.
-       * @param filter The filter, rank 5, of shape
-       *     `[filterDepth, filterHeight, filterWidth, inDepth, outDepth]`.
-       * @param strides The strides of the convolution: `[strideDepth, strideHeight,
-       * strideWidth]`.
-       * @param pad The type of padding algorithm used:
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       */
-      function conv3DBackpropInput_(xShape, dy, filter, strides, pad) {
-        util["assert"](
-          xShape.length === dy.rank,
-          () => `Length of inShape ` + `(${xShape.length}) and rank of dy (${dy.rank}) must match`
-        );
-        let xShape5D = xShape;
-        let dy5D = dy;
-        let reshapedTo5D = false;
-        if (dy.rank === 4) {
-          reshapedTo5D = true;
-          dy5D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2], dy.shape[3]]);
-          xShape5D = [1, xShape[0], xShape[1], xShape[2], xShape[3]];
-        }
-        const inDepth = xShape5D[4];
-        const outDepth = dy5D.shape[4];
-        util["assert"](
-          xShape5D.length === 5,
-          () =>
-            `Error in conv3dDerInput: inShape must be length 5, but got length ` +
-            `${xShape5D.length}.`
-        );
-        util["assert"](
-          dy5D.rank === 5,
-          () => `Error in conv3dDerInput: dy must be rank 5, but got ` + `rank ${dy5D.rank}`
-        );
-        util["assert"](
-          filter.rank === 5,
-          () => `Error in conv3dDerInput: filter must be rank 5, but got ` + `rank ${filter.rank}`
-        );
-        util["assert"](
-          inDepth === filter.shape[3],
-          () =>
-            `Error in conv3dDerInput: depth of input (${inDepth}) must ` +
-            `match input depth for filter ${filter.shape[3]}.`
-        );
-        util["assert"](
-          outDepth === filter.shape[4],
-          () =>
-            `Error in conv3dDerInput: depth of output (${outDepth}) must ` +
-            `match output depth for filter ${filter.shape[4]}.`
-        );
-        const forward = (backend) => {
-          const dilations = 1;
-          const convInfo = computeConv3DInfo(xShape5D, filter.shape, strides, dilations, pad);
-          return backend.conv3dDerInput(dy5D, filter, convInfo);
-        };
-        const inputs = { dy: dy5D };
-        const attrs = { pad };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null,
-          kernel_names["r" /* Conv3DBackpropInputV2 */],
-          attrs
-        );
-        if (reshapedTo5D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);
-        }
-        return res;
-      }
-      const conv3DBackpropInput = Object(operation["a" /* op */])({ conv3DBackpropInput_ });
-      //# sourceMappingURL=conv3d_backprop_input.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Conv3D_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const conv3DGradConfig = {
-        kernelName: kernel_names["p" /* Conv3D */],
-        inputsToSave: ["x", "filter"],
-        gradFunc: (dy, saved, attrs) => {
-          const { dilations, strides, pad } = attrs;
-          util["assert"](
-            tupleValuesAreOne(dilations),
-            () =>
-              "Error in gradient of conv3D: dilation rates greater than 1 are " +
-              `not yet supported in gradients. Got dilations '${dilations}'`
-          );
-          const [x5D, $filter] = saved;
-          return {
-            x: () => conv3DBackpropInput(x5D.shape, dy, $filter, strides, pad),
-            filter: () => conv3DBackpropFilter(x5D, dy, $filter.shape, strides, pad),
-          };
-        },
-      };
-      //# sourceMappingURL=Conv3D_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/transpose.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Transposes the `tf.Tensor`. Permutes the dimensions according to `perm`.
-       *
-       * The returned `tf.Tensor`'s dimension `i` will correspond to the input
-       * dimension `perm[i]`. If `perm` is not given, it is set to `[n-1...0]`,
-       * where `n` is the rank of the input `tf.Tensor`. Hence by default, this
-       * operation performs a regular matrix transpose on 2-D input `tf.Tensor`s.
-       *
-       * ```js
-       * const a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
-       *
-       * a.transpose().print();  // or tf.transpose(a)
-       * ```
-       *
-       * @param x The tensor to transpose.
-       * @param perm The permutation of the dimensions of a.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
-      function transpose_(x, perm) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "transpose");
-        if (perm == null) {
-          perm = $x.shape.map((s, i) => i).reverse();
-        }
-        util["assert"](
-          $x.rank === perm.length,
-          () =>
-            `Error in transpose: rank of input ${$x.rank} ` + `must match length of perm ${perm}.`
-        );
-        perm.forEach((axis) => {
-          util["assert"](
-            axis >= 0 && axis < $x.rank,
-            () => `All entries in 'perm' must be between 0 and ${$x.rank - 1}` + ` but got ${perm}`
-          );
-        });
-        if ($x.rank <= 1) {
-          return $x.clone();
-        }
-        const attrs = { perm };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.transpose($x, perm),
-          { x: $x },
-          null /* gradient */,
-          "Transpose",
-          attrs
-        );
-      }
-      const transpose = Object(operation["a" /* op */])({ transpose_ });
-      //# sourceMappingURL=transpose.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/cumsum.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the cumulative sum of a `tf.Tensor` along `axis`.
-       *
-       * ```js
-       * const x = tf.tensor([1, 2, 3, 4]);
-       * x.cumsum().print();
-       * ```
-       * ```js
-       * const x = tf.tensor([[1, 2], [3, 4]]);
-       * x.cumsum().print();
-       * ```
-       *
-       * @param x The input tensor to be summed.
-       * @param axis The axis along which to sum. Optional. Defaults to 0.
-       * @param exclusive Whether to perform exclusive cumulative sum. Optional.
-       *     Defaults to false. If set to true then the sum of each tensor entry
-       *     does not include its own value, but only the values previous to it
-       *     along the specified axis.
-       * @param reverse Whether to sum in the opposite direction. Optional.
-       *     Defaults to false.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Scan'} */
-      function cumsum_(x, axis = 0, exclusive = false, reverse = false) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "cumsum");
-        const forward = (backend, save) => {
-          const permutation = getAxesPermutation([axis], $x.rank);
-          let permutedX = $x;
-          if (permutation != null) {
-            permutedX = transpose($x, permutation);
-          }
-          const permutedAxis = getInnerMostAxes(1, $x.rank)[0];
-          let value = backend.cumsum(permutedX, permutedAxis, exclusive, reverse);
-          save([$x]);
-          if (permutation != null) {
-            value = transpose(value, permutation);
-          }
-          return value;
-        };
-        const inputs = { x: $x };
-        const attrs = { axis, exclusive, reverse };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["s" /* Cumsum */],
-          attrs
-        );
-      }
-      const cumsum = Object(operation["a" /* op */])({ cumsum_ });
-      //# sourceMappingURL=cumsum.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Cumsum_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const cumsumGradConfig = {
-        kernelName: kernel_names["s" /* Cumsum */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved, attrs) => {
-          const [x] = saved;
-          const { axis, exclusive, reverse } = attrs;
-          return {
-            x: () => {
-              const permutation = getAxesPermutation([axis], x.rank);
-              let out = cumsum(dy, axis, exclusive, !reverse);
-              if (permutation != null) {
-                out = transpose(out, permutation);
-              }
-              return out;
-            },
-          };
-        },
-      };
-      //# sourceMappingURL=Cumsum_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d_native_backprop_filter.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function depthwiseConv2dNativeBackpropFilter_(x, dy, filterShape, convInfo) {
-        let x4D = x;
-        if (x.rank === 3) {
-          x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);
-        }
-        let dy4D = dy;
-        if (dy4D.rank === 3) {
-          dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
-        }
-        const forward = (backend) => backend.depthwiseConv2DDerFilter(x4D, dy4D, convInfo);
-        const inputs = { x: x4D, dy: dy4D };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null,
-          kernel_names["v" /* DepthwiseConv2dNativeBackpropFilter */]
-        );
-      }
-      const depthwiseConv2dNativeBackpropFilter = Object(operation["a" /* op */])({
-        depthwiseConv2dNativeBackpropFilter_,
-      });
-      //# sourceMappingURL=depthwise_conv2d_native_backprop_filter.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d_native_backprop_input.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function depthwiseConv2dNativeBackpropInput_(xShape, dy, filter, convInfo) {
-        let dy4D = dy;
-        let reshapedTo4D = false;
-        if (dy.rank === 3) {
-          reshapedTo4D = true;
-          dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
-        }
-        const forward = (backend) => backend.depthwiseConv2DDerInput(dy4D, filter, convInfo);
-        const inputs = { dy: dy4D };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null,
-          kernel_names["w" /* DepthwiseConv2dNativeBackpropInput */]
-        );
-        if (reshapedTo4D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
-        }
-        return res;
-      }
-      const depthwiseConv2dNativeBackpropInput = Object(operation["a" /* op */])({
-        depthwiseConv2dNativeBackpropInput_,
-      });
-      //# sourceMappingURL=depthwise_conv2d_native_backprop_input.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/DepthwiseConv2dNative_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const depthwiseConv2dNativeGradConfig = {
-        kernelName: kernel_names["u" /* DepthwiseConv2dNative */],
-        inputsToSave: ["x", "filter"],
-        gradFunc: (dy, saved, attrs) => {
-          const { dilations, strides, pad, dimRoundingMode } = attrs;
-          const $dilations = dilations == null ? [1, 1] : dilations;
-          util["assert"](
-            tupleValuesAreOne($dilations),
-            () =>
-              "Error in gradient of depthwiseConv2dNative: dilation rates " +
-              `greater than 1 are not yet supported. Got dilations ` +
-              `'${$dilations}'`
-          );
-          const [x, filter] = saved;
-          util["assert"](
-            x.rank === 4,
-            () =>
-              `Error in gradient of depthwiseConv2dNative: input must be ` +
-              `rank 4, but got rank ${x.rank}.`
-          );
-          util["assert"](
-            filter.rank === 4,
-            () =>
-              `Error in gradient of depthwiseConv2dNative: filter must be ` +
-              `rank 4, but got rank ${filter.rank}.`
-          );
-          util["assert"](
-            x.shape[3] === filter.shape[2],
-            () =>
-              `Error in gradient of depthwiseConv2d: number of input ` +
-              `channels (${x.shape[3]}) must match the inChannels dimension ` +
-              `in filter ${filter.shape[2]}.`
-          );
-          util["assert"](
-            eitherStridesOrDilationsAreOne(strides, $dilations),
-            () =>
-              "Error in gradient of depthwiseConv2d: Either strides or " +
-              `dilations must be  1. Got strides ${strides} and dilations ` +
-              `'${$dilations}'.`
-          );
-          if (dimRoundingMode != null) {
-            util["assert"](
-              util["isInt"](pad),
-              () =>
-                `Error in depthwiseConv2d: pad must be an integer when using, ` +
-                `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-            );
-          }
-          const convInfo = computeConv2DInfo(
-            x.shape,
-            filter.shape,
-            strides,
-            $dilations,
-            pad,
-            dimRoundingMode,
-            true /* depthwise */
-          );
-          return {
-            x: () => depthwiseConv2dNativeBackpropInput(x.shape, dy, filter, convInfo),
-            filter: () => depthwiseConv2dNativeBackpropFilter(x, dy, filter.shape, convInfo),
-          };
-        },
-      };
-      //# sourceMappingURL=DepthwiseConv2dNative_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Div_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const divGradConfig = {
-        kernelName: kernel_names["y" /* Div */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
-          const derA = () => {
-            const res = div(dy, b.toFloat());
-            const reduceAxes = getReductionAxes(a.shape, outShape);
-            if (reduceAxes.length > 0) {
-              return sum(res, reduceAxes).reshape(a.shape);
-            }
-            return res;
-          };
-          const derB = () => {
-            let res = mul(dy, a.toFloat());
-            const reduceAxes = getReductionAxes(b.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = reshape(sum(res, reduceAxes), b.shape);
-            }
-            const tmp = square(b);
-            return neg(div(res, tmp.toFloat()));
-          };
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=Div_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Elu_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const eluGradConfig = {
-        kernelName: kernel_names["z" /* Elu */],
-        outputsToSave: [true],
-        gradFunc: (dy, saved) => {
-          const [y] = saved;
-          const backPropKernelFunc = (backend) => {
-            return backend.eluDer(dy, y);
-          };
-          const inputs = { dy, y };
-          return {
-            x: () =>
-              engine["a" /* ENGINE */].runKernelFunc(
-                backPropKernelFunc,
-                inputs,
-                null /* grad */,
-                kernel_names["A" /* EluGrad */]
-              ),
-          };
-        },
-      };
-      //# sourceMappingURL=Elu_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/FloorDiv_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const floorDivGradConfig = {
-        kernelName: kernel_names["D" /* FloorDiv */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
-          const derA = () => {
-            const res = dy.div(b.toFloat());
-            const reduceAxes = getReductionAxes(a.shape, outShape);
-            if (reduceAxes.length > 0) {
-              return res.sum(reduceAxes).reshape(a.shape);
-            }
-            return res;
-          };
-          const derB = () => {
-            let res = dy.mul(a.toFloat());
-            const reduceAxes = getReductionAxes(b.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = res.sum(reduceAxes).reshape(b.shape);
-            }
-            const tmp = b.square();
-            return res.div(tmp.toFloat()).neg();
-          };
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=FloorDiv_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/sub.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Subtracts two `tf.Tensor`s element-wise, A - B. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([10, 20, 30, 40]);
-       * const b = tf.tensor1d([1, 2, 3, 4]);
-       *
-       * a.sub(b).print();  // or tf.sub(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast subtract a with b.
-       * const a = tf.tensor1d([10, 20, 30, 40]);
-       * const b = tf.scalar(5);
-       *
-       * a.sub(b).print();  // or tf.sub(a, b)
-       * ```
-       * @param a The first `tf.Tensor` to subtract from.
-       * @param b The second `tf.Tensor` to be subtracted. Must have the same dtype as
-       * `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function sub_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "sub");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "sub");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        const forward = (backend, save) => {
-          const res = backend.subtract($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["qb" /* Sub */]
-        );
-      }
-      const sub = Object(operation["a" /* op */])({ sub_ });
-      //# sourceMappingURL=sub.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/tile.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Construct a tensor by repeating it the number of times given by reps.
-       *
-       * This operation creates a new tensor by replicating `input` `reps`
-       * times. The output tensor's i'th dimension has `input.shape[i] *
-       * reps[i]` elements, and the values of `input` are replicated
-       * `reps[i]` times along the i'th dimension. For example, tiling
-       * `[a, b, c, d]` by `[2]` produces `[a, b, c, d, a, b, c, d]`.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2]);
-       *
-       * a.tile([2]).print();    // or a.tile([2])
-       * ```
-       *
-       * ```js
-       * const a = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * a.tile([1, 2]).print();  // or a.tile([1, 2])
-       * ```
-       * @param x The tensor to tile.
-       * @param reps Determines the number of replications per dimension.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      function tile_(x, reps) {
-        const parseAs = null;
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "tile", parseAs);
-        util["assert"](
-          $x.rank === reps.length,
-          () =>
-            `Error in transpose: rank of input ${$x.rank} ` + `must match length of reps ${reps}.`
-        );
-        const forward = (backend, save) => {
-          const res = backend.tile($x, reps);
-          save([$x]);
-          return res;
-        };
-        const inputsToSave = [$x];
-        const inputs = { x: $x };
-        const attrs = { reps };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["rb" /* Tile */],
-          attrs,
-          inputsToSave
-        );
-      }
-      const tile = Object(operation["a" /* op */])({ tile_ });
-      //# sourceMappingURL=tile.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/FusedBatchNorm_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const fusedBatchNormGradConfig = {
-        kernelName: kernel_names["F" /* FusedBatchNorm */],
-        inputsToSave: ["x", "mean", "variance", "scale"],
-        gradFunc: (dy, saved, attrs) => {
-          const { varianceEpsilon } = attrs;
-          const [x, mean, variance, scale] = saved;
-          const scaleValue = scale == null ? Object(tensor_ops["e" /* scalar */])(1) : scale;
-          const reductionAxes = getReductionAxes(mean.shape, x.shape);
-          const tileShape = [];
-          if (mean.rank === 1) {
-            for (let i = 0; i < x.shape.length - 1; ++i) {
-              tileShape.push(x.shape[i]);
-            }
-            tileShape.push(1);
-          }
-          const xMinusMean = sub(x, mean);
-          const dyTimesScaleValue = mul(dy, scaleValue);
-          const oneOverSqrtVariance = rsqrt(
-            add(variance, Object(tensor_ops["e" /* scalar */])(varianceEpsilon))
-          );
-          const minusHalfRCube = mul(
-            mul(mul(oneOverSqrtVariance, oneOverSqrtVariance), oneOverSqrtVariance),
-            Object(tensor_ops["e" /* scalar */])(-0.5)
-          );
-          const derX = () => {
-            if (mean.rank === 1) {
-              return reshape(
-                mul(
-                  mul(dy, tile(oneOverSqrtVariance.as4D(1, 1, 1, mean.shape[0]), tileShape)),
-                  scaleValue
-                ),
-                x.shape
-              );
-            } else {
-              return reshape(mul(mul(dy, oneOverSqrtVariance), scaleValue), x.shape);
-            }
-          };
-          const derMean = () => {
-            let meanDer = mul(
-              mul(oneOverSqrtVariance, Object(tensor_ops["e" /* scalar */])(-1)),
-              dyTimesScaleValue
-            );
-            if (mean.rank === 1) {
-              meanDer = sum(meanDer, reductionAxes);
-            }
-            return reshape(meanDer, mean.shape);
-          };
-          const derVariance = () => {
-            let varianceDer = mul(mul(minusHalfRCube, xMinusMean), dyTimesScaleValue);
-            if (mean.rank === 1) {
-              varianceDer = sum(varianceDer, reductionAxes);
-            }
-            return reshape(varianceDer, mean.shape);
-          };
-          const derScale = () => {
-            const xMinusMean2TimesRsqrt = mul(xMinusMean, oneOverSqrtVariance);
-            let scaleDer = mul(dy, xMinusMean2TimesRsqrt);
-            if (mean.rank === 1) {
-              scaleDer = sum(scaleDer, reductionAxes);
-            }
-            return reshape(scaleDer, mean.shape);
-          };
-          const derOffset = () => {
-            let offsetDer = dy;
-            if (mean.rank === 1) {
-              offsetDer = sum(offsetDer, reductionAxes);
-            }
-            return reshape(offsetDer, mean.shape);
-          };
-          return {
-            x: derX,
-            mean: derMean,
-            variance: derVariance,
-            scale: derScale,
-            offset: derOffset,
-          };
-        },
-      };
-      //# sourceMappingURL=FusedBatchNorm_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/GreaterEqual_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const greaterEqualGradConfig = {
-        kernelName: kernel_names["I" /* GreaterEqual */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          return {
-            a: () => Object(tensor_ops["o" /* zerosLike */])(a),
-            b: () => Object(tensor_ops["o" /* zerosLike */])(b),
-          };
-        },
-      };
-      //# sourceMappingURL=GreaterEqual_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Identity_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const identityGradConfig = {
-        kernelName: kernel_names["J" /* Identity */],
-        gradFunc: (dy) => {
-          return { x: () => dy.toFloat() };
-        },
-      };
-      //# sourceMappingURL=Identity_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/local_response_normalization_backprop.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function localResponseNormalizationBackprop_(
-        x,
-        y,
-        dy,
-        depthRadius = 5,
-        bias = 1,
-        alpha = 1,
-        beta = 0.5
-      ) {
-        const forward = (backend) => backend.LRNGrad(dy, x, y, depthRadius, bias, alpha, beta);
-        const inputs = { x, y, dy };
-        const attrs = { depthRadius, bias, alpha, beta };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["M" /* LRNBackprop */],
-          attrs
-        );
-      }
-      const localResponseNormalizationBackprop = Object(operation["a" /* op */])({
-        localResponseNormalizationBackprop_,
-      });
-      //# sourceMappingURL=local_response_normalization_backprop.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/LRN_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const lrnGradConfig = {
-        kernelName: kernel_names["L" /* LRN */],
-        inputsToSave: ["x"],
-        outputsToSave: [true],
-        gradFunc: (dy, saved, attrs) => {
-          const [x, y] = saved;
-          const { depthRadius, bias, alpha, beta } = attrs;
-          return {
-            x: () => localResponseNormalizationBackprop(x, y, dy, depthRadius, bias, alpha, beta),
-          };
-        },
-      };
-      //# sourceMappingURL=LRN_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Max_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const maxGradConfig = {
-        kernelName: kernel_names["P" /* Max */],
-        inputsToSave: ["x"],
-        outputsToSave: [true],
-        gradFunc: (dy, saved, attrs) => {
-          const maxAttrs = attrs;
-          const { reductionIndices } = maxAttrs;
-          const [x, y] = saved;
-          const origAxes = util["parseAxisParam"](reductionIndices, x.shape);
-          const permutedAxes = getAxesPermutation(origAxes, x.rank);
-          const maxGrad = gradForMinAndMax(dy, y, x, origAxes, permutedAxes);
-          return {
-            x: () => {
-              let out = maxGrad["x"]();
-              if (permutedAxes != null) {
-                out = transpose(out);
-              }
-              return out;
-            },
-          };
-        },
-      };
-      //# sourceMappingURL=Max_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/greater_equal.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the truth value of (a >= b) element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       * const b = tf.tensor1d([2, 2, 2]);
-       *
-       * a.greaterEqual(b).print();
-       * ```
-       *
-       * @param a The first input tensor.
-       * @param b The second input tensor. Must have the same dtype as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function greaterEqual_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "greaterEqual");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "greaterEqual");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend, save) => {
-          const res = backend.greaterEqual($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["I" /* GreaterEqual */]
-        );
-      }
-      const greaterEqual = Object(operation["a" /* op */])({ greaterEqual_ });
-      //# sourceMappingURL=greater_equal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/less.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the truth value of (a < b) element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       * const b = tf.tensor1d([2, 2, 2]);
-       *
-       * a.less(b).print();
-       * ```
-       * @param a The first input tensor.
-       * @param b The second input tensor. Must have the same dtype as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function less_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "less");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "less");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend) => backend.less($a, $b);
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["N" /* Less */]
-        );
-      }
-      const less = Object(operation["a" /* op */])({ less_ });
-      //# sourceMappingURL=less.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Maximum_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const maximumGradConfig = {
-        kernelName: kernel_names["V" /* Maximum */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const derA = () => mul(dy, cast(greaterEqual(a, b), "float32"));
-          const derB = () => mul(dy, cast(less(a, b), "float32"));
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=Maximum_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_3d_backprop.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the backprop of a 3d max pool.
-       *
-       * @param dy The dy error, of rank 5 of shape
-       *     [batchSize, depth, height, width, channels].
-       * assumed.
-       * @param input The original input image, of rank 5 or rank 4 of shape
-       *     [batchSize, depth, height, width, channels].
-       * @param output The original output image, of rank 5 of shape
-       *     [batchSize, outDepth, outHeight, outWidth, channels].
-       * @param filterSize The filter size:
-       *     `[filterDepth, filterHeight, filterWidth]`.
-       *     `filterSize` is a single number,
-       *     then `filterDepth == filterHeight == filterWidth`.
-       * @param strides The strides of the pooling:
-       *     `[strideDepth, strideHeight, strideWidth]`. If
-       *     `strides` is a single number, then `strideHeight == strideWidth`.
-       * @param dilations Deprecated, this field will be gone in v3.0.0.
-       *     The dilation rates: `[dilationDepth, dilationHeight, dilationWidth]`
-       *     in which we sample input values across the depth, height and width
-       *     dimensions in dilated pooling.
-       *     Defaults to `[1, 1, 1]`. If `dilations` is a single number,
-       *     then `dilationDepth == dilationHeight == dilationWidth`.
-       *     If it is greater than 1, then all values of `strides` must be 1.
-       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
-       *     used in the forward prop of the op.
-       * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. The
-       *     rounding mode used when computing output dimensions if pad is a
-       *     number. If none is provided, it will not round and error if the output
-       *     is of fractional size.
-       */
-      function maxPool3dBackprop_(
-        dy,
-        input,
-        output,
-        filterSize,
-        strides,
-        dilations = [1, 1, 1],
-        pad,
-        dimRoundingMode
-      ) {
-        const $dy = Object(tensor_util_env["a" /* convertToTensor */])(
-          dy,
-          "dy",
-          "maxPool3dBackprop"
-        );
-        const $input = Object(tensor_util_env["a" /* convertToTensor */])(
-          input,
-          "input",
-          "maxPool3dBackprop"
-        );
-        const $output = Object(tensor_util_env["a" /* convertToTensor */])(
-          output,
-          "output",
-          "maxPool3dBackprop"
-        );
-        let dy5D = $dy;
-        let input5D = $input;
-        let output5D = $output;
-        let reshapedTo5D = false;
-        if ($input.rank === 4) {
-          reshapedTo5D = true;
-          dy5D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]);
-          input5D = reshape($input, [
-            1,
-            $input.shape[0],
-            $input.shape[1],
-            $input.shape[2],
-            $input.shape[3],
-          ]);
-          output5D = reshape($output, [
-            1,
-            $output.shape[0],
-            $output.shape[1],
-            $output.shape[2],
-            $output.shape[3],
-          ]);
-        }
-        util["assert"](
-          dy5D.rank === 5,
-          () => `Error in maxPool3dBackprop: dy must be rank 5 but got rank ` + `${dy5D.rank}.`
-        );
-        util["assert"](
-          input5D.rank === 5,
-          () =>
-            `Error in maxPool3dBackprop: input must be rank 5 but got rank ` + `${input5D.rank}.`
-        );
-        util["assert"](
-          output5D.rank === 5,
-          () =>
-            `Error in maxPool3dBackprop: output must be rank 5 but got rank ` + `${output5D.rank}.`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in maxPool3dBackprop: Either strides or dilations " +
-            `must be 1. Got strides ${strides} and dilations '${dilations}'`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in maxPool3dBackprop: pad must be an integer when ` +
-              `using, dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend) => {
-          const convInfo = computePool3DInfo(
-            input5D.shape,
-            filterSize,
-            strides,
-            dilations,
-            pad,
-            dimRoundingMode
-          );
-          return backend.maxPool3dBackprop(dy5D, input5D, output5D, convInfo);
-        };
-        const inputs = { dy: dy5D, input: input5D, output: output5D };
-        const attrs = { filterSize, strides, dilations, pad, dimRoundingMode };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["S" /* MaxPool3DBackprop */],
-          attrs
-        );
-        if (reshapedTo5D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);
-        }
-        return res;
-      }
-      const maxPool3dBackprop = Object(operation["a" /* op */])({ maxPool3dBackprop_ });
-      //# sourceMappingURL=max_pool_3d_backprop.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/MaxPool3D_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const maxPool3DGradConfig = {
-        kernelName: kernel_names["R" /* MaxPool3D */],
-        inputsToSave: ["x"],
-        outputsToSave: [true],
-        gradFunc: (dy, saved, attrs) => {
-          const [x, y] = saved;
-          const { filterSize, strides, dilations, pad, dimRoundingMode } = attrs;
-          const $dilations = dilations == null ? [1, 1, 1] : dilations;
-          return {
-            x: () =>
-              maxPool3dBackprop(dy, x, y, filterSize, strides, $dilations, pad, dimRoundingMode),
-          };
-        },
-      };
-      //# sourceMappingURL=MaxPool3D_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_backprop.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the backprop of a 2D max pool.
-       *
-       * @param dy The dy error, of rank 4 or rank 3 of shape
-       *     [batchSize, height, width, channels]. If rank 3, batch of 1 is
-       * assumed.
-       * @param input The original input image, of rank 4, of shape
-       *     [batchSize, height, width, channels].
-       * @param output The original output image, of rank 4, of shape
-       *     [batchSize, outHeight, outWidth, channels].
-       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
-       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
-       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
-       *     `strides` is a single number, then `strideHeight == strideWidth`.
-       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
-       *     used in the forward prop of the op.
-       * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. The
-       *     rounding mode used when computing output dimensions if pad is a
-       *     number. If none is provided, it will not round and error if the output
-       *     is of fractional size.
-       */
-      function maxPoolBackprop_(dy, input, output, filterSize, strides, pad, dimRoundingMode) {
-        const $dy = Object(tensor_util_env["a" /* convertToTensor */])(dy, "dy", "maxPoolBackprop");
-        const $input = Object(tensor_util_env["a" /* convertToTensor */])(
-          input,
-          "input",
-          "maxPoolBackprop"
-        );
-        const $output = Object(tensor_util_env["a" /* convertToTensor */])(
-          output,
-          "output",
-          "maxPoolBackprop"
-        );
-        util["assert"](
-          $input.rank === $dy.rank,
-          () => `Rank of input (${$input.rank}) does not match rank of dy ` + `(${$dy.rank})`
-        );
-        util["assert"](
-          $dy.rank === 4,
-          () => `Error in maxPoolBackprop: dy must be rank 4 but got rank ` + `${$dy.rank}.`
-        );
-        util["assert"](
-          $input.rank === 4,
-          () => `Error in maxPoolBackprop: input must be rank 4 but got rank ` + `${$input.rank}.`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in maxPoolBackprop: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend) => {
-          const convInfo = computePool2DInfo(
-            $input.shape,
-            filterSize,
-            strides,
-            1 /* dilations */,
-            pad,
-            dimRoundingMode
-          );
-          return backend.maxPoolBackprop($dy, $input, $output, convInfo);
-        };
-        const inputs = { dy: $dy, input: $input, output: $output };
-        const attrs = { filterSize, strides, pad, dimRoundingMode };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null,
-          kernel_names["T" /* MaxPoolBackprop */],
-          attrs
-        );
-      }
-      const maxPoolBackprop = Object(operation["a" /* op */])({ maxPoolBackprop_ });
-      //# sourceMappingURL=max_pool_backprop.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/MaxPool_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const maxPoolGradConfig = {
-        kernelName: kernel_names["Q" /* MaxPool */],
-        inputsToSave: ["x"],
-        outputsToSave: [true],
-        gradFunc: (dy, saved, attrs) => {
-          const [x, y] = saved;
-          const { filterSize, strides, pad } = attrs;
-          return {
-            x: () => maxPoolBackprop(dy, x, y, filterSize, strides, pad),
-          };
-        },
-      };
-      //# sourceMappingURL=MaxPool_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/greater.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the truth value of (a > b) element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       * const b = tf.tensor1d([2, 2, 2]);
-       *
-       * a.greater(b).print();
-       * ```
-       *
-       * @param a The first input tensor.
-       * @param b The second input tensor. Must have the same dtype as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function greater_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "greater");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "greater");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend) => backend.greater($a, $b);
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["H" /* Greater */]
-        );
-      }
-      const greater = Object(operation["a" /* op */])({ greater_ });
-      //# sourceMappingURL=greater.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/less_equal.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the truth value of (a <= b) element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       * const b = tf.tensor1d([2, 2, 2]);
-       *
-       * a.lessEqual(b).print();
-       * ```
-       *
-       * @param a The first input tensor.
-       * @param b The second input tensor. Must have the same dtype as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function lessEqual_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "lessEqual");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "lessEqual");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend, save) => {
-          const res = backend.lessEqual($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["O" /* LessEqual */]
-        );
-      }
-      const lessEqual = Object(operation["a" /* op */])({ lessEqual_ });
-      //# sourceMappingURL=less_equal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Minimum_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const minimumGradConfig = {
-        kernelName: kernel_names["W" /* Minimum */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const derA = () => mul(dy, cast(lessEqual(a, b), "float32"));
-          const derB = () => mul(dy, cast(greater(a, b), "float32"));
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=Minimum_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Mod_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const modGradConfig = {
-        kernelName: kernel_names["X" /* Mod */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
-          const derA = () => {
-            const reduceAxes = getReductionAxes(a.shape, outShape);
-            if (reduceAxes.length > 0) {
-              return reshape(sum(dy, reduceAxes), a.shape);
-            }
-            return dy;
-          };
-          const derB = () => {
-            const res = mul(dy, neg(floor(div(a, b))));
-            const reduceAxes = getReductionAxes(b.shape, outShape);
-            if (reduceAxes.length > 0) {
-              return reshape(sum(res, reduceAxes), b.shape);
-            }
-            return res;
-          };
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=Mod_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Multiply_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const multiplyGradConfig = {
-        kernelName: kernel_names["Y" /* Multiply */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
-          const derA = () => {
-            const res = mul(dy, cast(b, "float32"));
-            const reduceAxes = getReductionAxes(a.shape, outShape);
-            if (reduceAxes.length > 0) {
-              return reshape(sum(res, reduceAxes), a.shape);
-            }
-            return res;
-          };
-          const derB = () => {
-            const res = mul(dy, cast(a, "float32"));
-            const reduceAxes = getReductionAxes(b.shape, outShape);
-            if (reduceAxes.length > 0) {
-              return reshape(sum(res, reduceAxes), b.shape);
-            }
-            return res;
-          };
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=Multiply_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/OneHot_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const oneHotGradConfig = {
-        kernelName: kernel_names["cb" /* OneHot */],
-        inputsToSave: ["indices"],
-        gradFunc: (dy, saved) => {
-          const indices = saved[0];
-          return { indices: () => Object(tensor_ops["n" /* zeros */])(indices.shape, "float32") };
-        },
-      };
-      //# sourceMappingURL=OneHot_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/PadV2_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const padV2GradConfig = {
-        kernelName: kernel_names["db" /* PadV2 */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved, attrs) => {
-          // Pad introduces values around the original tensor, so the gradient
-          // slices the original shape out of the gradient.
-          const x = saved[0];
-          const { paddings } = attrs;
-          const begin = paddings.map((p) => p[0]);
-          return { x: () => dy.slice(begin, x.shape) };
-        },
-      };
-      //# sourceMappingURL=PadV2_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/where_impl.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /** An implementation of the Where kernel shared between cpu and webgl */
-
-      function whereImpl(condShape, condVals) {
-        const indices = [];
-        for (let i = 0; i < condVals.length; i++) {
-          if (condVals[i]) {
-            indices.push(i);
-          }
-        }
-        const inBuffer = array_ops_buffer(condShape, "int32");
-        const out = array_ops_buffer([indices.length, condShape.length], "int32");
-        for (let i = 0; i < indices.length; i++) {
-          const loc = inBuffer.indexToLoc(indices[i]);
-          const offset = i * condShape.length;
-          out.values.set(loc, offset);
-        }
-        return out.toTensor();
-      }
-      //# sourceMappingURL=where_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/logical_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the truth value of `NOT x` element-wise.
-       *
-       * ```js
-       * const a = tf.tensor1d([false, true], 'bool');
-       *
-       * a.logicalNot().print();
-       * ```
-       *
-       * @param x The input tensor. Must be of dtype 'bool'.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function logicalNot_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "logicalNot", "bool");
-        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.logicalNot($x), { $x });
-      }
-      /**
-       * Returns the truth value of `a AND b` element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([false, false, true, true], 'bool');
-       * const b = tf.tensor1d([false, true, false, true], 'bool');
-       *
-       * a.logicalAnd(b).print();
-       * ```
-       *
-       * @param a The first input tensor. Must be of dtype bool.
-       * @param b The second input tensor. Must be of dtype bool.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function logicalAnd_(a, b) {
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "logicalAnd", "bool");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "logicalAnd", "bool");
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.logicalAnd($a, $b),
-          { a: $a, b: $b },
-          null /* grad */,
-          "LogicalAnd"
-        );
-      }
-      /**
-       * Returns the truth value of `a OR b` element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([false, false, true, true], 'bool');
-       * const b = tf.tensor1d([false, true, false, true], 'bool');
-       *
-       * a.logicalOr(b).print();
-       * ```
-       * @param a The first input tensor. Must be of dtype bool.
-       * @param b The second input tensor. Must be of dtype bool.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function logicalOr_(a, b) {
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "logicalOr", "bool");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "logicalOr", "bool");
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.logicalOr($a, $b), {
-          $a,
-          $b,
-        });
-      }
-      /**
-       * Returns the truth value of `a XOR b` element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([false, false, true, true], 'bool');
-       * const b = tf.tensor1d([false, true, false, true], 'bool');
-       *
-       * a.logicalXor(b).print();
-       * ```
-       *
-       * @param a The first input tensor. Must be of dtype bool.
-       * @param b The second input tensor. Must be of dtype bool.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function logicalXor_(a, b) {
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "logicalXor", "bool");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "logicalXor", "bool");
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        // x ^ y = (x | y) & ~(x & y)
-        return logicalOr(a, b).logicalAnd(logicalAnd(a, b).logicalNot());
-      }
-      /**
-       * Returns the elements, either `a` or `b` depending on the `condition`.
-       *
-       * If the condition is true, select from `a`, otherwise select from `b`.
-       *
-       * ```js
-       * const cond = tf.tensor1d([false, false, true], 'bool');
-       * const a = tf.tensor1d([1 , 2, 3]);
-       * const b = tf.tensor1d([-1, -2, -3]);
-       *
-       * a.where(cond, b).print();
-       * ```
-       *
-       * @param condition The input condition. Must be of dtype bool.
-       * @param a If `condition` is rank 1, `a` may have a higher rank but
-       *     its first dimension must match the size of `condition`.
-       * @param b A tensor with the same shape and type as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function where_(condition, a, b) {
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "where");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "where");
-        const $condition = Object(tensor_util_env["a" /* convertToTensor */])(
-          condition,
-          "condition",
-          "where",
-          "bool"
-        );
-        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in where: ");
-        if ($condition.rank === 1) {
-          // If condition rank is 1, then the first dimension must match the size of
-          // condition.
-          Object(util["assert"])(
-            $condition.shape[0] === $a.shape[0],
-            () => "The first dimension of `a` must match the size of `condition`."
-          );
-        } else {
-          // A must have the same shape as condition.
-          Object(util["assertShapesMatch"])($condition.shape, $b.shape, "Error in where: ");
-        }
-        // TODO(julianoks): Return null for condition gradient
-        // when backprop supports it.
-        const grad = (dy, saved) => {
-          const [$condition] = saved;
-          return {
-            condition: () => Object(tensor_ops["o" /* zerosLike */])($condition).toFloat(),
-            t: () => dy.mul($condition.cast(dy.dtype)),
-            e: () => dy.mul($condition.logicalNot().cast(dy.dtype)),
-          };
-        };
-        const inputs = { condition: $condition, t: $a, e: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.select($condition, $a, $b);
-            save([$condition]);
-            return res;
-          },
-          inputs,
-          grad,
-          kernel_names["kb" /* SelectV2 */]
-        );
-      }
-      /**
-       * Returns the coordinates of true elements of condition.
-       *
-       * The coordinates are returned in a 2-D tensor where the first dimension (rows)
-       * represents the number of true elements, and the second dimension (columns)
-       * represents the coordinates of the true elements. Keep in mind, the shape of
-       * the output tensor can vary depending on how many true values there are in
-       * input. Indices are output in row-major order. The resulting tensor has the
-       * shape `[numTrueElems, condition.rank]`.
-       *
-       * This is analogous to calling the python `tf.where(cond)` without an x or y.
-       *
-       * ```js
-       * const cond = tf.tensor1d([false, false, true], 'bool');
-       * const result = await tf.whereAsync(cond);
-       * result.print();
-       * ```
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      async function whereAsync_(condition) {
-        const $condition = Object(tensor_util_env["a" /* convertToTensor */])(
-          condition,
-          "condition",
-          "whereAsync",
-          "bool"
-        );
-        const vals = await $condition.data();
-        const res = whereImpl($condition.shape, vals);
-        if (condition !== $condition) {
-          $condition.dispose();
-        }
-        return res;
-      }
-      const logicalAnd = Object(operation["a" /* op */])({ logicalAnd_ });
-      const logicalNot = Object(operation["a" /* op */])({ logicalNot_ });
-      const logicalOr = Object(operation["a" /* op */])({ logicalOr_ });
-      const logicalXor = Object(operation["a" /* op */])({ logicalXor_ });
-      const where = Object(operation["a" /* op */])({ where_ });
-      const whereAsync = whereAsync_;
-      //# sourceMappingURL=logical_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pow.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the power of one `tf.Tensor` to another. Supports broadcasting.
-       *
-       * Given a `tf.Tensor` x and a `tf.Tensor` y, this operation computes x^y for
-       * corresponding elements in x and y. The result's dtype will be the upcasted
-       * type of the `base` and `exp` dtypes.
-       *
-       * ```js
-       * const a = tf.tensor([[2, 3], [4, 5]])
-       * const b = tf.tensor([[1, 2], [3, 0]]).toInt();
-       *
-       * a.pow(b).print();  // or tf.pow(a, b)
-       * ```
-       *
-       * ```js
-       * const a = tf.tensor([[1, 2], [3, 4]])
-       * const b = tf.tensor(2).toInt();
-       *
-       * a.pow(b).print();  // or tf.pow(a, b)
-       * ```
-       * We also expose `powStrict` which has the same signature as this op and
-       * asserts that `base` and `exp` are the same shape (does not broadcast).
-       *
-       * @param base The base `tf.Tensor` to pow element-wise.
-       * @param exp The exponent `tf.Tensor` to pow element-wise.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function pow_(base, exp) {
-        let $base = Object(tensor_util_env["a" /* convertToTensor */])(base, "base", "pow");
-        let $exp = Object(tensor_util_env["a" /* convertToTensor */])(exp, "exp", "pow");
-        [$base, $exp] = Object(tensor_util["makeTypesMatch"])($base, $exp);
-        const inputs = { a: $base, b: $exp };
-        const forward = (backend, save) => {
-          const y = backend.pow($base, $exp);
-          save([$base, $exp, y]);
-          return y;
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["fb" /* Pow */]
-        );
-      }
-      const pow = Object(operation["a" /* op */])({ pow_ });
-      //# sourceMappingURL=pow.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Pow_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const powGradConfig = {
-        kernelName: kernel_names["fb" /* Pow */],
-        inputsToSave: ["a", "b"],
-        outputsToSave: [true],
-        gradFunc: (dy, saved) => {
-          const [a, b, y] = saved;
-          const base = a;
-          const exp = b;
-          const outShape = assertAndGetBroadcastShape(base.shape, exp.shape);
-          const derBase = () => {
-            const expFloat = cast(exp, "float32");
-            let res = mul(
-              dy,
-              mul(expFloat, pow(base, sub(expFloat, Object(tensor_ops["e" /* scalar */])(1))))
-            );
-            const reduceAxes = getReductionAxes(base.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = sum(res, reduceAxes);
-            }
-            return reshape(res, base.shape);
-          };
-          const derExp = () => {
-            const condition = greater(base, 0);
-            const logBase = where(
-              condition,
-              log(base),
-              Object(tensor_ops["o" /* zerosLike */])(base)
-            );
-            let res = mul(dy, mul(y, logBase));
-            const reduceAxes = getReductionAxes(exp.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = sum(res, reduceAxes);
-            }
-            return reshape(res, exp.shape);
-          };
-          return { a: derBase, b: derExp };
-        },
-      };
-      //# sourceMappingURL=Pow_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Prelu_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const preluGradConfig = {
-        kernelName: kernel_names["gb" /* Prelu */],
-        inputsToSave: ["x", "alpha"],
-        gradFunc: (dy, saved) => {
-          const [x, alpha] = saved;
-          const mask = greater(x, 0);
-          return {
-            x: () => where(mask, dy, mul(dy, alpha)),
-            alpha: () => {
-              let res = where(mask, Object(tensor_ops["o" /* zerosLike */])(dy), mul(dy, x));
-              const reduceAxes = getReductionAxes(alpha.shape, dy.shape);
-              if (reduceAxes.length > 0) {
-                res = sum(res, reduceAxes);
-              }
-              return reshape(res, alpha.shape);
-            },
-          };
-        },
-      };
-      //# sourceMappingURL=Prelu_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Relu6_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const relu6GradConfig = {
-        kernelName: kernel_names["jb" /* Relu6 */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved) => {
-          const [x] = saved;
-          const mask = mul(lessEqual(x, 6), unary_ops_step(x));
-          return { x: () => mul(dy, cast(mask, "float32")) };
-        },
-      };
-      //# sourceMappingURL=Relu6_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Relu_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const reluGradConfig = {
-        kernelName: kernel_names["ib" /* Relu */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved) => {
-          const [x] = saved;
-          return { x: () => mul(dy, cast(unary_ops_step(x), "float32")) };
-        },
-      };
-      //# sourceMappingURL=Relu_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/selu_util.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const SELU_SCALEALPHA = 1.7580993408473768599402175208123;
-      const SELU_SCALE = 1.0507009873554804934193349852946;
-      //# sourceMappingURL=selu_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Selu_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const seluGradConfig = {
-        kernelName: kernel_names["lb" /* Selu */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved) => {
-          const [x] = saved;
-          return {
-            x: () => {
-              const mask = greater(x, Object(tensor_ops["e" /* scalar */])(0));
-              const scaleAlpha = Object(tensor_ops["e" /* scalar */])(SELU_SCALEALPHA);
-              const scale = Object(tensor_ops["e" /* scalar */])(SELU_SCALE);
-              const greaterThanZeroDer = mul(dy, scale);
-              const lessEqualZeroDer = mul(mul(dy, scaleAlpha), unary_ops_exp(cast(x, "float32")));
-              return where(mask, greaterThanZeroDer, lessEqualZeroDer);
-            },
-          };
-        },
-      };
-      //# sourceMappingURL=Selu_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batch_to_space_nd.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * This operation reshapes the "batch" dimension 0 into `M + 1` dimensions of
-       * shape `blockShape + [batch]`, interleaves these blocks back into the grid
-       * defined by the spatial dimensions `[1, ..., M]`, to obtain a result with
-       * the same rank as the input. The spatial dimensions of this intermediate
-       * result are then optionally cropped according to `crops` to produce the
-       * output. This is the reverse of `tf.spaceToBatchND`. See below for a precise
-       * description.
-       *
-       * ```js
-       * const x = tf.tensor4d([1, 2, 3, 4], [4, 1, 1, 1]);
-       * const blockShape = [2, 2];
-       * const crops = [[0, 0], [0, 0]];
-       *
-       * x.batchToSpaceND(blockShape, crops).print();
-       * ```
-       *
-       * @param x A `tf.Tensor`. N-D with `x.shape` = `[batch] + spatialShape +
-       * remainingShape`, where spatialShape has `M` dimensions.
-       * @param blockShape A 1-D array. Must have shape `[M]`, all values must
-       * be >= 1.
-       * @param crops A 2-D array.  Must have shape `[M, 2]`, all values must be >= 0.
-       * `crops[i] = [cropStart, cropEnd]` specifies the amount to crop from input
-       * dimension `i + 1`, which corresponds to spatial dimension `i`. It is required
-       * that `cropStart[i] + cropEnd[i] <= blockShape[i] * inputShape[i + 1]`
-       *
-       * This operation is equivalent to the following steps:
-       *
-       * 1. Reshape `x` to `reshaped` of shape: `[blockShape[0], ...,
-       * blockShape[M-1], batch / prod(blockShape), x.shape[1], ...,
-       * x.shape[N-1]]`
-       *
-       * 2. Permute dimensions of `reshaped`to produce `permuted` of shape `[batch /
-       * prod(blockShape),x.shape[1], blockShape[0], ..., x.shape[M],
-       * blockShape[M-1],x.shape[M+1], ..., x.shape[N-1]]`
-       *
-       * 3. Reshape `permuted` to produce `reshapedPermuted` of shape `[batch /
-       * prod(blockShape),x.shape[1] * blockShape[0], ..., x.shape[M] *
-       * blockShape[M-1],x.shape[M+1], ..., x.shape[N-1]]`
-       *
-       * 4. Crop the start and end of dimensions `[1, ..., M]` of `reshapedPermuted`
-       * according to `crops` to produce the output of shape: `[batch /
-       * prod(blockShape),x.shape[1] * blockShape[0] - crops[0,0] - crops[0,1],
-       * ..., x.shape[M] * blockShape[M-1] - crops[M-1,0] -
-       * crops[M-1,1],x.shape[M+1], ..., x.shape[N-1]]`
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function batchToSpaceND_(x, blockShape, crops) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchToSpaceND");
-        const prod = blockShape.reduce((a, b) => a * b);
-        util["assert"](
-          $x.rank >= 1 + blockShape.length,
-          () =>
-            `input rank is ${$x.rank} but should be > than blockShape.length ${blockShape.length}`
-        );
-        util["assert"](
-          crops.length === blockShape.length,
-          () =>
-            `crops.length is ${crops.length} but should be equal to blockShape.length  ${blockShape.length}`
-        );
-        util["assert"](
-          $x.shape[0] % prod === 0,
-          () =>
-            `input tensor batch is ${$x.shape[0]} but is not divisible by the product of ` +
-            `the elements of blockShape ${blockShape.join(" * ")} === ${prod}`
-        );
-        const forward = (backend) => {
-          return backend.batchToSpaceND($x, blockShape, crops);
-        };
-        const inputs = { x: $x };
-        const attrs = { blockShape, crops };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["i" /* BatchToSpaceND */],
-          attrs
-        );
-      }
-      const batchToSpaceND = Object(operation["a" /* op */])({ batchToSpaceND_ });
-      //# sourceMappingURL=batch_to_space_nd.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/SpaceToBatchND_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const spaceToBatchNDGradConfig = {
-        kernelName: kernel_names["mb" /* SpaceToBatchND */],
-        gradFunc: (dy, saved, attrs) => {
-          const { blockShape, paddings } = attrs;
-          return { x: () => batchToSpaceND(dy, blockShape, paddings) };
-        },
-      };
-      //# sourceMappingURL=SpaceToBatchND_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/SplitV_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const splitVGradConfig = {
-        kernelName: kernel_names["nb" /* SplitV */],
-        gradFunc: (dy, saved, attrs) => {
-          const { axis } = attrs;
-          return { x: () => concat(dy, axis) };
-        },
-      };
-      //# sourceMappingURL=SplitV_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Square_grad.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const squareGradConfig = {
-        kernelName: kernel_names["ob" /* Square */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved) => {
-          const [x] = saved;
-          return { x: () => mul(dy, mul(x.toFloat(), 2)) };
-        },
-      };
-      //# sourceMappingURL=Square_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/SquaredDifference_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const squaredDifferenceGradConfig = {
-        kernelName: kernel_names["pb" /* SquaredDifference */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const two = Object(tensor_ops["e" /* scalar */])(2);
-          const derA = () => mul(dy, mul(two, sub(a, b)));
-          const derB = () => mul(dy, mul(two, sub(b, a)));
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=SquaredDifference_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Sub_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const subGradConfig = {
-        kernelName: kernel_names["qb" /* Sub */],
-        inputsToSave: ["a", "b"],
-        gradFunc: (dy, saved) => {
-          const [a, b] = saved;
-          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
-          const derA = () => {
-            let res = dy;
-            const reduceAxes = getReductionAxes(a.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = sum(res, reduceAxes);
-            }
-            return reshape(res, a.shape);
-          };
-          const derB = () => {
-            let res = dy;
-            const reduceAxes = getReductionAxes(b.shape, outShape);
-            if (reduceAxes.length > 0) {
-              res = sum(res, reduceAxes);
-            }
-            return reshape(neg(res), b.shape);
-          };
-          return { a: derA, b: derB };
-        },
-      };
-      //# sourceMappingURL=Sub_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Pads a `tf.Tensor` with a given value and paddings.
-       *
-       * This operation currently only implements the `CONSTANT` mode.
-       *
-       * Also available are stricter rank-specific methods with the same signature
-       * as this method that assert that `paddings` is of given length.
-       *   - `tf.pad1d`
-       *   - `tf.pad2d`
-       *   - `tf.pad3d`
-       *   - `tf.pad4d`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       * x.pad([[1, 2]]).print();
-       * ```
-       * @param x The tensor to pad.
-       * @param paddings An array of length `R` (the rank of the tensor), where
-       * each element is a length-2 tuple of ints `[padBefore, padAfter]`,
-       * specifying how much to pad along each dimension of the tensor.
-       * @param constantValue The pad value to use. Defaults to 0.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function pad_(x, paddings, constantValue = 0) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "pad");
-        if ($x.rank === 0) {
-          throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");
-        }
-        const forward = (backend, save) => {
-          save([$x]);
-          return backend.pad($x, paddings, constantValue);
-        };
-        const attrs = { paddings, constantValue };
-        const inputs = { x: $x };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["db" /* PadV2 */],
-          attrs
-        );
-      }
-      const pad_pad = Object(operation["a" /* op */])({ pad_ });
-      //# sourceMappingURL=pad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/slice_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function assertParamsValid(input, begin, size) {
-        util["assert"](
-          input.rank === begin.length,
-          () =>
-            `Error in slice${input.rank}D: Length of begin ${begin} must ` +
-            `match the rank of the array (${input.rank}).`
-        );
-        util["assert"](
-          input.rank === size.length,
-          () =>
-            `Error in slice${input.rank}D: Length of size ${size} must ` +
-            `match the rank of the array (${input.rank}).`
-        );
-        for (let i = 0; i < input.rank; ++i) {
-          util["assert"](
-            begin[i] + size[i] <= input.shape[i],
-            () =>
-              `Error in slice${input.rank}D: begin[${i}] + size[${i}] ` +
-              `(${begin[i] + size[i]}) would overflow input.shape[${i}] (${input.shape[i]})`
-          );
-        }
-      }
-      /** Converts a binary mask to an array of axes. Used in stridedSlice(). */
-      function maskToAxes(mask) {
-        const axes = [];
-        let axis = 0;
-        while (mask > 0) {
-          if (mask & 1) {
-            axes.push(axis);
-          }
-          mask /= 2;
-          axis++;
-        }
-        return axes;
-      }
-      /** Computes the output shape given the strided slice params. */
-      function slice_util_computeOutShape(begin, end, strides) {
-        const size = [];
-        for (let axis = 0; axis < begin.length; axis++) {
-          size[axis] = Math.ceil((end[axis] - begin[axis]) / strides[axis]);
-        }
-        return size;
-      }
-      // Creates full selection at the elided dimensions. If the dimension matches
-      // the ellipsis mask, override the current stride value. Otherwise, insert.
-      function stridesWithElidedDims(strides, ellipsisInsertionIndex, numElidedAxes) {
-        const newStrides = [...strides];
-        for (let i = 0; i < numElidedAxes; i++) {
-          if (i === 0) {
-            newStrides[ellipsisInsertionIndex] = 1;
-          } else {
-            newStrides.splice(
-              ellipsisInsertionIndex,
-              0 /* num elements to delete */,
-              1 /* element to add */
-            );
-            newStrides.pop();
-          }
-        }
-        return newStrides;
-      }
-      // Creates full selection at the elided dimensions. If the dimension matches
-      // the ellipsis mask, override the current start value. Otherwise, insert.
-      function startIndicesWithElidedDims(startIndices, ellipsisInsertionIndex, numElidedAxes) {
-        const newIndices = [...startIndices];
-        for (let i = 0; i < numElidedAxes; i++) {
-          if (i === 0) {
-            newIndices[ellipsisInsertionIndex] = 0;
-          } else {
-            newIndices.splice(
-              ellipsisInsertionIndex,
-              0 /* num elements to delete */,
-              0 /* element to add */
-            );
-            newIndices.pop();
-          }
-        }
-        return newIndices;
-      }
-      // Creates full selection at the elided dimensions. If the dimension matches
-      // the ellipsis mask, override the current stop value. Otherwise, insert.
-      function stopIndicesWithElidedDims(
-        stopIndices,
-        ellipsisInsertionIndex,
-        numElidedAxes,
-        inputShape
-      ) {
-        const newIndices = [...stopIndices];
-        for (let i = 0; i < numElidedAxes; i++) {
-          if (i === 0) {
-            newIndices[ellipsisInsertionIndex] = Number.MAX_SAFE_INTEGER;
-          } else {
-            newIndices.splice(
-              ellipsisInsertionIndex,
-              0 /* num elements to delete */,
-              Number.MAX_SAFE_INTEGER /* element to add */
-            );
-            newIndices.pop();
-          }
-        }
-        for (let i = 0; i < newIndices.length; i++) {
-          newIndices[i] = util["clamp"](0, newIndices[i], inputShape[i]);
-        }
-        return newIndices;
-      }
-      function stridesForAxis(strides, axis, ellipsisMask) {
-        let stride = strides[axis];
-        if (ellipsisMask & (1 << axis) || stride == null) {
-          stride = 1;
-        }
-        return stride;
-      }
-      function startForAxis(beginMask, startIndices, strides, inputShape, axis, ellipsisMask) {
-        // Begin with the specified index
-        let start = startIndices[axis];
-        const stride = strides[axis] || 1;
-        // Check the axis bit from right of masked axes, or the begin index is not set
-        // for the axis.
-        if (beginMask & (1 << axis) || ellipsisMask & (1 << axis) || start == null) {
-          if (stride > 0) {
-            // Forward iteration - use the first element. These values will get
-            // clamped below (Note: We could have set them to 0 and axis_size-1, but
-            // use lowest() and max() to maintain symmetry with StopForAxis())
-            start = Number.MIN_SAFE_INTEGER;
-          } else {
-            // Backward iteration - use the last element.
-            start = Number.MAX_SAFE_INTEGER;
-          }
-        }
-        // Handle negative indices
-        const axisSize = inputShape[axis];
-        if (start < 0) {
-          start += axisSize;
-        }
-        // Clamping
-        start = util["clamp"](0, start, axisSize - 1);
-        return start;
-      }
-      function stopForAxis(endMask, stopIndices, strides, inputShape, axis, ellipsisMask) {
-        // Begin with the specified index
-        let stop = stopIndices[axis];
-        const stride = strides[axis] || 1;
-        // Check the axis bit from right of masked axes, or if the stop index is not
-        // set for this axis.
-        if (endMask & (1 << axis) || ellipsisMask & (1 << axis) || stop == null) {
-          if (stride > 0) {
-            // Forward iteration - use the last element. These values will get
-            // clamped below
-            stop = Number.MAX_SAFE_INTEGER;
-          } else {
-            // Backward iteration - use the first element.
-            stop = Number.MIN_SAFE_INTEGER;
-          }
-        }
-        // Handle negative indices
-        const axisSize = inputShape[axis];
-        if (stop < 0) {
-          stop += axisSize;
-        }
-        // Clamping
-        // Because the end index points one past the last element, we need slightly
-        // different clamping ranges depending on the direction.
-        if (stride > 0) {
-          // Forward iteration
-          stop = util["clamp"](0, stop, axisSize);
-        } else {
-          // Backward iteration
-          stop = util["clamp"](-1, stop, axisSize - 1);
-        }
-        return stop;
-      }
-      /**
-       * Returns true if the slice occupies a continous set of elements in the
-       * 'flat' space.
-       */
-      function isSliceContinous(shape, begin, size) {
-        // Index of the first axis that has size > 1.
-        let firstNonOneAxis = size.length;
-        for (let i = 0; i < size.length; i++) {
-          if (size[i] > 1) {
-            firstNonOneAxis = i;
-            break;
-          }
-        }
-        for (let i = firstNonOneAxis + 1; i < size.length; i++) {
-          if (begin[i] > 0 || size[i] !== shape[i]) {
-            return false;
-          }
-        }
-        return true;
-      }
-      function computeFlatOffset(begin, strides) {
-        let flatOffset = begin.length > 0 ? begin[begin.length - 1] : 1;
-        for (let i = 0; i < begin.length - 1; i++) {
-          flatOffset += begin[i] * strides[i];
-        }
-        return flatOffset;
-      }
-      //# sourceMappingURL=slice_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/slice.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Extracts a 1D slice from 1D array starting at coordinates `begin` and is
-       * of length `size`. See `slice` for details.
-       */
-      function slice1d_(x, begin, size) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice1d");
-        util["assert"](
-          $x.rank === 1,
-          () => `slice1d expects a rank-1 tensor, but got a rank-${$x.rank} tensor`
-        );
-        return slice($x, [begin], [size]);
-      }
-      /**
-       * Extracts a 2D slice from a 2D array starting at coordinates `begin` and
-       * is of size `size`. See `slice` for details.
-       */
-      function slice2d_(x, begin, size) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice2d");
-        util["assert"](
-          $x.rank === 2,
-          () => `slice2d expects a rank-2 tensor, but got a rank-${$x.rank} tensor`
-        );
-        return slice($x, begin, size);
-      }
-      /**
-       * Extracts a 3D slice from a 3D array starting at coordinates `begin` and
-       * is of size `size`. See `slice` for details.
-       */
-      function slice3d_(x, begin, size) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice3d");
-        util["assert"](
-          $x.rank === 3,
-          () => `slice3d expects a rank-3 tensor, but got a rank-${$x.rank} tensor`
-        );
-        return slice($x, begin, size);
-      }
-      /**
-       * Extracts a 4D slice from a 4D array starting at coordinates `begin` and
-       * is of size `size`. See `slice` for details.
-       */
-      function slice4d_(x, begin, size) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice4d");
-        util["assert"](
-          $x.rank === 4,
-          () => `slice4d expects a rank-4 tensor, but got a rank-${$x.rank} tensor`
-        );
-        return slice($x, begin, size);
-      }
-      /**
-       * Extracts a slice from a `tf.Tensor` starting at coordinates `begin`
-       * and is of size `size`.
-       *
-       * Also available are stricter rank-specific methods with the same signature
-       * as this method that assert that `x` is of the given rank:
-       *   - `tf.slice1d`
-       *   - `tf.slice2d`
-       *   - `tf.slice3d`
-       *   - `tf.slice4d`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       *
-       * x.slice([1], [2]).print();
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * x.slice([1, 0], [1, 2]).print();
-       * ```
-       * @param x The input `tf.Tensor` to slice from.
-       * @param begin The coordinates to start the slice from. The length can be
-       *     less than the rank of x - the rest of the axes will have implicit 0 as
-       *     start. Can also be a single number, in which case it specifies the
-       *     first axis.
-       * @param size The size of the slice. The length can be less than the rank of
-       *     x - the rest of the axes will have implicit -1. A value of -1 requests
-       *     the rest of the dimensions in the axis. Can also be a single number,
-       *     in which case it specifies the size of the first axis.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      function slice_(x, begin, size) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice");
-        if ($x.rank === 0) {
-          throw new Error("Slicing scalar is not possible");
-        }
-        // The following logic allows for more ergonomic calls.
-        let begin_;
-        if (typeof begin === "number") {
-          begin_ = [begin, ...new Array($x.rank - 1).fill(0)];
-        } else if (begin.length < $x.rank) {
-          begin_ = begin.concat(new Array($x.rank - begin.length).fill(0));
-        } else {
-          begin_ = begin.slice();
-        }
-        begin_.forEach((d) => {
-          util["assert"](d !== -1, () => "slice() does not support negative begin indexing.");
-        });
-        let size_;
-        if (size == null) {
-          size_ = new Array($x.rank).fill(-1);
-        } else if (typeof size === "number") {
-          size_ = [size, ...new Array($x.rank - 1).fill(-1)];
-        } else if (size.length < $x.rank) {
-          size_ = size.concat(new Array($x.rank - size.length).fill(-1));
-        } else {
-          size_ = size;
-        }
-        size_ = size_.map((d, i) => {
-          if (d >= 0) {
-            return d;
-          } else {
-            util["assert"](
-              d === -1,
-              () =>
-                `Negative size values should be exactly -1 but got ` +
-                `${d} for the slice() size at index ${i}.`
-            );
-            return $x.shape[i] - begin_[i];
-          }
-        });
-        assertParamsValid($x, begin_, size_);
-        const inputShape = $x.shape;
-        const grad = (dy) => {
-          // Create an Nx2 padding where the first column represents how many
-          // zeros are prepended (at start) for each dimension, and the second
-          // column indicates how many zeros are appended (at end).
-          // The number of zeros to append is the shape of the input
-          // elementwise-subtracted by both the begin vector and sizes vector.
-          const paddings = [];
-          for (let i = 0; i < dy.rank; i++) {
-            paddings.push([begin_[i], inputShape[i] - begin_[i] - size_[i]]);
-          }
-          return { x: () => pad_pad(dy, paddings) };
-        };
-        const attrs = { begin: begin_, size: size_ };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.slice($x, begin_, size_),
-          { x: $x },
-          grad,
-          "Slice",
-          attrs
-        );
-      }
-      const slice = Object(operation["a" /* op */])({ slice_ });
-      const slice1d = Object(operation["a" /* op */])({ slice1d_ });
-      const slice2d = Object(operation["a" /* op */])({ slice2d_ });
-      const slice3d = Object(operation["a" /* op */])({ slice3d_ });
-      const slice4d = Object(operation["a" /* op */])({ slice4d_ });
-      //# sourceMappingURL=slice.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Tile_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const tileGradConfig = {
-        kernelName: kernel_names["rb" /* Tile */],
-        inputsToSave: ["x"],
-        gradFunc: (dy, saved, attrs) => {
-          const [x] = saved;
-          const { reps } = attrs;
-          const derX = () => {
-            let xGrad = Object(tensor_ops["o" /* zerosLike */])(x);
-            // TODO(cais): Maybe reduce memory footprint by avoiding repeated
-            // slicing.
-            if (x.rank === 1) {
-              for (let i = 0; i < reps[0]; ++i) {
-                xGrad = add(xGrad, slice(dy, [i * x.shape[0]], [x.shape[0]]));
-              }
-            } else if (x.rank === 2) {
-              for (let i = 0; i < reps[0]; ++i) {
-                for (let j = 0; j < reps[1]; ++j) {
-                  xGrad = add(
-                    xGrad,
-                    slice(dy, [i * x.shape[0], j * x.shape[1]], [x.shape[0], x.shape[1]])
-                  );
-                }
-              }
-            } else if (x.rank === 3) {
-              for (let i = 0; i < reps[0]; ++i) {
-                for (let j = 0; j < reps[1]; ++j) {
-                  for (let k = 0; k < reps[2]; ++k) {
-                    xGrad = add(
-                      xGrad,
-                      slice(
-                        dy,
-                        [i * x.shape[0], j * x.shape[1], k * x.shape[2]],
-                        [x.shape[0], x.shape[1], x.shape[2]]
-                      )
-                    );
-                  }
-                }
-              }
-            } else if (x.rank === 4) {
-              for (let i = 0; i < reps[0]; ++i) {
-                for (let j = 0; j < reps[1]; ++j) {
-                  for (let k = 0; k < reps[2]; ++k) {
-                    for (let l = 0; l < reps[3]; ++l) {
-                      xGrad = add(
-                        xGrad,
-                        slice(
-                          dy,
-                          [i * x.shape[0], j * x.shape[1], k * x.shape[2], l * x.shape[3]],
-                          [x.shape[0], x.shape[1], x.shape[2], x.shape[3]]
-                        )
-                      );
-                    }
-                  }
-                }
-              }
-            } else {
-              throw new Error(
-                `Gradient for tile operation is not implemented for rank-` +
-                  `${x.rank} tensors yet.`
-              );
-            }
-            return xGrad;
-          };
-          return { x: derX };
-        },
-      };
-      //# sourceMappingURL=Tile_grad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Transpose_grad.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const transposeGradConfig = {
-        kernelName: kernel_names["sb" /* Transpose */],
-        gradFunc: (dy, saved, attrs) => {
-          const transposeAttrs = attrs;
-          const { perm } = transposeAttrs;
-          const undoPerm = getUndoAxesPermutation(perm);
-          return { x: () => transpose(dy, undoPerm) };
-        },
-      };
-      //# sourceMappingURL=Transpose_grad.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/kernel_registry.js
-      var kernel_registry = __webpack_require__(17);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/register_all_gradients.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // Export all kernel configs here so that the package can auto register them
-      const gradConfigs = [
-        addGradConfig,
-        addNGradConfig,
-        atan2GradConfig,
-        avgPoolGradConfig,
-        avgPool3DGradConfig,
-        batchMatMulGradConfig,
-        batchToSpaceNDGradConfig,
-        broadcastToGradConfig,
-        concatGradConfig,
-        conv2DGradConfig,
-        conv2DBackpropInputGradConfig,
-        conv3DGradConfig,
-        cumsumGradConfig,
-        depthwiseConv2dNativeGradConfig,
-        divGradConfig,
-        eluGradConfig,
-        floorDivGradConfig,
-        fusedBatchNormGradConfig,
-        greaterEqualGradConfig,
-        identityGradConfig,
-        lrnGradConfig,
-        oneHotGradConfig,
-        padV2GradConfig,
-        splitVGradConfig,
-        maxGradConfig,
-        spaceToBatchNDGradConfig,
-        maxGradConfig,
-        maximumGradConfig,
-        maxPoolGradConfig,
-        maxPool3DGradConfig,
-        minimumGradConfig,
-        modGradConfig,
-        multiplyGradConfig,
-        oneHotGradConfig,
-        padV2GradConfig,
-        powGradConfig,
-        preluGradConfig,
-        reluGradConfig,
-        relu6GradConfig,
-        seluGradConfig,
-        spaceToBatchNDGradConfig,
-        splitVGradConfig,
-        squareGradConfig,
-        squaredDifferenceGradConfig,
-        tileGradConfig,
-        transposeGradConfig,
-        subGradConfig,
-      ];
-      for (const gradientConfig of gradConfigs) {
-        Object(kernel_registry["d" /* registerGradient */])(gradientConfig);
-      }
-      //# sourceMappingURL=register_all_gradients.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/environment.js
-      var environment = __webpack_require__(10);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/platforms/platform_browser.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class PlatformBrowser {
-        fetch(path, init) {
-          return fetch(path, init);
-        }
-        now() {
-          return performance.now();
-        }
-        encode(text, encoding) {
-          if (encoding !== "utf-8" && encoding !== "utf8") {
-            throw new Error(`Browser's encoder only supports utf-8, but got ${encoding}`);
-          }
-          if (this.textEncoder == null) {
-            this.textEncoder = new TextEncoder();
-          }
-          return this.textEncoder.encode(text);
-        }
-        decode(bytes, encoding) {
-          return new TextDecoder(encoding).decode(bytes);
-        }
-      }
-      if (Object(environment["c" /* env */])().get("IS_BROWSER")) {
-        Object(environment["c" /* env */])().setPlatform("browser", new PlatformBrowser());
-      }
-      //# sourceMappingURL=platform_browser.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/platforms/platform_node.js
-      var platform_node = __webpack_require__(62);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/io_utils.js
-      var io_utils = __webpack_require__(13);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/router_registry.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class IORouterRegistry {
-        constructor() {
-          this.saveRouters = [];
-          this.loadRouters = [];
-        }
-        static getInstance() {
-          if (IORouterRegistry.instance == null) {
-            IORouterRegistry.instance = new IORouterRegistry();
-          }
-          return IORouterRegistry.instance;
-        }
-        /**
-         * Register a save-handler router.
-         *
-         * @param saveRouter A function that maps a URL-like string onto an instance
-         * of `IOHandler` with the `save` method defined or `null`.
-         */
-        static registerSaveRouter(saveRouter) {
-          IORouterRegistry.getInstance().saveRouters.push(saveRouter);
-        }
-        /**
-         * Register a load-handler router.
-         *
-         * @param loadRouter A function that maps a URL-like string onto an instance
-         * of `IOHandler` with the `load` method defined or `null`.
-         */
-        static registerLoadRouter(loadRouter) {
-          IORouterRegistry.getInstance().loadRouters.push(loadRouter);
-        }
-        /**
-         * Look up IOHandler for saving, given a URL-like string.
-         *
-         * @param url
-         * @returns If only one match is found, an instance of IOHandler with the
-         * `save` method defined. If no match is found, `null`.
-         * @throws Error, if more than one match is found.
-         */
-        static getSaveHandlers(url) {
-          return IORouterRegistry.getHandlers(url, "save");
-        }
-        /**
-         * Look up IOHandler for loading, given a URL-like string.
-         *
-         * @param url
-         * @param loadOptions Optional, custom load options.
-         * @returns All valid handlers for `url`, given the currently registered
-         *   handler routers.
-         */
-        static getLoadHandlers(url, loadOptions) {
-          return IORouterRegistry.getHandlers(url, "load", loadOptions);
-        }
-        static getHandlers(url, handlerType, loadOptions) {
-          const validHandlers = [];
-          const routers =
-            handlerType === "load"
-              ? IORouterRegistry.getInstance().loadRouters
-              : IORouterRegistry.getInstance().saveRouters;
-          routers.forEach((router) => {
-            const handler = router(url, loadOptions);
-            if (handler !== null) {
-              validHandlers.push(handler);
-            }
-          });
-          return validHandlers;
-        }
-      }
-      const registerSaveRouter = (loudRouter) => IORouterRegistry.registerSaveRouter(loudRouter);
-      const registerLoadRouter = (loudRouter) => IORouterRegistry.registerLoadRouter(loudRouter);
-      const getSaveHandlers = (url) => IORouterRegistry.getSaveHandlers(url);
-      const getLoadHandlers = (url, loadOptions) =>
-        IORouterRegistry.getLoadHandlers(url, loadOptions);
-      //# sourceMappingURL=router_registry.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/model_management.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Classes and functions for model management across multiple storage mediums.
-       *
-       * Supported client actions:
-       * - Listing models on all registered storage mediums.
-       * - Remove model by URL from any registered storage mediums, by using URL
-       *   string.
-       * - Moving or copying model from one path to another in the same medium or from
-       *   one medium to another, by using URL strings.
-       */
-
-      const URL_SCHEME_SUFFIX = "://";
-      class model_management_ModelStoreManagerRegistry {
-        constructor() {
-          this.managers = {};
-        }
-        static getInstance() {
-          if (model_management_ModelStoreManagerRegistry.instance == null) {
-            model_management_ModelStoreManagerRegistry.instance =
-              new model_management_ModelStoreManagerRegistry();
-          }
-          return model_management_ModelStoreManagerRegistry.instance;
-        }
-        /**
-         * Register a save-handler router.
-         *
-         * @param saveRouter A function that maps a URL-like string onto an instance
-         * of `IOHandler` with the `save` method defined or `null`.
-         */
-        static registerManager(scheme, manager) {
-          Object(util["assert"])(scheme != null, () => "scheme must not be undefined or null.");
-          if (scheme.endsWith(URL_SCHEME_SUFFIX)) {
-            scheme = scheme.slice(0, scheme.indexOf(URL_SCHEME_SUFFIX));
-          }
-          Object(util["assert"])(scheme.length > 0, () => "scheme must not be an empty string.");
-          const registry = model_management_ModelStoreManagerRegistry.getInstance();
-          Object(util["assert"])(
-            registry.managers[scheme] == null,
-            () => `A model store manager is already registered for scheme '${scheme}'.`
-          );
-          registry.managers[scheme] = manager;
-        }
-        static getManager(scheme) {
-          const manager = this.getInstance().managers[scheme];
-          if (manager == null) {
-            throw new Error(`Cannot find model manager for scheme '${scheme}'`);
-          }
-          return manager;
-        }
-        static getSchemes() {
-          return Object.keys(this.getInstance().managers);
-        }
-      }
-      /**
-       * Helper method for parsing a URL string into a scheme and a path.
-       *
-       * @param url E.g., 'localstorage://my-model'
-       * @returns A dictionary with two fields: scheme and path.
-       *   Scheme: e.g., 'localstorage' in the example above.
-       *   Path: e.g., 'my-model' in the example above.
-       */
-      function parseURL(url) {
-        if (url.indexOf(URL_SCHEME_SUFFIX) === -1) {
-          throw new Error(
-            `The url string provided does not contain a scheme. ` +
-              `Supported schemes are: ` +
-              `${model_management_ModelStoreManagerRegistry.getSchemes().join(",")}`
-          );
-        }
-        return {
-          scheme: url.split(URL_SCHEME_SUFFIX)[0],
-          path: url.split(URL_SCHEME_SUFFIX)[1],
-        };
-      }
-      async function cloneModelInternal(sourceURL, destURL, deleteSource = false) {
-        Object(util["assert"])(
-          sourceURL !== destURL,
-          () => `Old path and new path are the same: '${sourceURL}'`
-        );
-        const loadHandlers = IORouterRegistry.getLoadHandlers(sourceURL);
-        Object(util["assert"])(
-          loadHandlers.length > 0,
-          () => `Copying failed because no load handler is found for source URL ${sourceURL}.`
-        );
-        Object(util["assert"])(
-          loadHandlers.length < 2,
-          () =>
-            `Copying failed because more than one (${loadHandlers.length}) ` +
-            `load handlers for source URL ${sourceURL}.`
-        );
-        const loadHandler = loadHandlers[0];
-        const saveHandlers = IORouterRegistry.getSaveHandlers(destURL);
-        Object(util["assert"])(
-          saveHandlers.length > 0,
-          () =>
-            `Copying failed because no save handler is found for destination ` + `URL ${destURL}.`
-        );
-        Object(util["assert"])(
-          saveHandlers.length < 2,
-          () =>
-            `Copying failed because more than one (${loadHandlers.length}) ` +
-            `save handlers for destination URL ${destURL}.`
-        );
-        const saveHandler = saveHandlers[0];
-        const sourceScheme = parseURL(sourceURL).scheme;
-        const sourcePath = parseURL(sourceURL).path;
-        const sameMedium = sourceScheme === parseURL(sourceURL).scheme;
-        const modelArtifacts = await loadHandler.load();
-        // If moving within the same storage medium, remove the old model as soon as
-        // the loading is done. Without doing this, it is possible that the combined
-        // size of the two models will cause the cloning to fail.
-        if (deleteSource && sameMedium) {
-          await model_management_ModelStoreManagerRegistry
-            .getManager(sourceScheme)
-            .removeModel(sourcePath);
-        }
-        const saveResult = await saveHandler.save(modelArtifacts);
-        // If moving between mediums, the deletion is done after the save succeeds.
-        // This guards against the case in which saving to the destination medium
-        // fails.
-        if (deleteSource && !sameMedium) {
-          await model_management_ModelStoreManagerRegistry
-            .getManager(sourceScheme)
-            .removeModel(sourcePath);
-        }
-        return saveResult.modelArtifactsInfo;
-      }
-      /**
-       * List all models stored in registered storage mediums.
-       *
-       * For a web browser environment, the registered mediums are Local Storage and
-       * IndexedDB.
-       *
-       * ```js
-       * // First create and save a model.
-       * const model = tf.sequential();
-       * model.add(tf.layers.dense(
-       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
-       * await model.save('localstorage://demo/management/model1');
-       *
-       * // Then list existing models.
-       * console.log(JSON.stringify(await tf.io.listModels()));
-       *
-       * // Delete the model.
-       * await tf.io.removeModel('localstorage://demo/management/model1');
-       *
-       * // List models again.
-       * console.log(JSON.stringify(await tf.io.listModels()));
-       * ```
-       *
-       * @returns A `Promise` of a dictionary mapping URLs of existing models to
-       * their model artifacts info. URLs include medium-specific schemes, e.g.,
-       *   'indexeddb://my/model/1'. Model artifacts info include type of the
-       * model's topology, byte sizes of the topology, weights, etc.
-       */
-      /**
-       * @doc {
-       *   heading: 'Models',
-       *   subheading: 'Management',
-       *   namespace: 'io',
-       *   ignoreCI: true
-       * }
-       */
-      async function listModels() {
-        const schemes = model_management_ModelStoreManagerRegistry.getSchemes();
-        const out = {};
-        for (const scheme of schemes) {
-          const schemeOut = await model_management_ModelStoreManagerRegistry
-            .getManager(scheme)
-            .listModels();
-          for (const path in schemeOut) {
-            const url = scheme + URL_SCHEME_SUFFIX + path;
-            out[url] = schemeOut[path];
-          }
-        }
-        return out;
-      }
-      /**
-       * Remove a model specified by URL from a reigstered storage medium.
-       *
-       * ```js
-       * // First create and save a model.
-       * const model = tf.sequential();
-       * model.add(tf.layers.dense(
-       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
-       * await model.save('localstorage://demo/management/model1');
-       *
-       * // Then list existing models.
-       * console.log(JSON.stringify(await tf.io.listModels()));
-       *
-       * // Delete the model.
-       * await tf.io.removeModel('localstorage://demo/management/model1');
-       *
-       * // List models again.
-       * console.log(JSON.stringify(await tf.io.listModels()));
-       * ```
-       *
-       * @param url A URL to a stored model, with a scheme prefix, e.g.,
-       *   'localstorage://my-model-1', 'indexeddb://my/model/2'.
-       * @returns ModelArtifactsInfo of the deleted model (if and only if deletion
-       *   is successful).
-       * @throws Error if deletion fails, e.g., if no model exists at `path`.
-       */
-      /**
-       * @doc {
-       *   heading: 'Models',
-       *   subheading: 'Management',
-       *   namespace: 'io',
-       *   ignoreCI: true
-       * }
-       */
-      async function removeModel(url) {
-        const schemeAndPath = parseURL(url);
-        const manager = model_management_ModelStoreManagerRegistry.getManager(schemeAndPath.scheme);
-        return manager.removeModel(schemeAndPath.path);
-      }
-      /**
-       * Copy a model from one URL to another.
-       *
-       * This function supports:
-       *
-       * 1. Copying within a storage medium, e.g.,
-       *    `tf.io.copyModel('localstorage://model-1', 'localstorage://model-2')`
-       * 2. Copying between two storage mediums, e.g.,
-       *    `tf.io.copyModel('localstorage://model-1', 'indexeddb://model-1')`
-       *
-       * ```js
-       * // First create and save a model.
-       * const model = tf.sequential();
-       * model.add(tf.layers.dense(
-       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
-       * await model.save('localstorage://demo/management/model1');
-       *
-       * // Then list existing models.
-       * console.log(JSON.stringify(await tf.io.listModels()));
-       *
-       * // Copy the model, from Local Storage to IndexedDB.
-       * await tf.io.copyModel(
-       *     'localstorage://demo/management/model1',
-       *     'indexeddb://demo/management/model1');
-       *
-       * // List models again.
-       * console.log(JSON.stringify(await tf.io.listModels()));
-       *
-       * // Remove both models.
-       * await tf.io.removeModel('localstorage://demo/management/model1');
-       * await tf.io.removeModel('indexeddb://demo/management/model1');
-       * ```
-       *
-       * @param sourceURL Source URL of copying.
-       * @param destURL Destination URL of copying.
-       * @returns ModelArtifactsInfo of the copied model (if and only if copying
-       *   is successful).
-       * @throws Error if copying fails, e.g., if no model exists at `sourceURL`, or
-       *   if `oldPath` and `newPath` are identical.
-       */
-      /**
-       * @doc {
-       *   heading: 'Models',
-       *   subheading: 'Management',
-       *   namespace: 'io',
-       *   ignoreCI: true
-       * }
-       */
-      async function copyModel(sourceURL, destURL) {
-        const deleteSource = false;
-        return cloneModelInternal(sourceURL, destURL, deleteSource);
-      }
-      /**
-       * Move a model from one URL to another.
-       *
-       * This function supports:
-       *
-       * 1. Moving within a storage medium, e.g.,
-       *    `tf.io.moveModel('localstorage://model-1', 'localstorage://model-2')`
-       * 2. Moving between two storage mediums, e.g.,
-       *    `tf.io.moveModel('localstorage://model-1', 'indexeddb://model-1')`
-       *
-       * ```js
-       * // First create and save a model.
-       * const model = tf.sequential();
-       * model.add(tf.layers.dense(
-       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
-       * await model.save('localstorage://demo/management/model1');
-       *
-       * // Then list existing models.
-       * console.log(JSON.stringify(await tf.io.listModels()));
-       *
-       * // Move the model, from Local Storage to IndexedDB.
-       * await tf.io.moveModel(
-       *     'localstorage://demo/management/model1',
-       *     'indexeddb://demo/management/model1');
-       *
-       * // List models again.
-       * console.log(JSON.stringify(await tf.io.listModels()));
-       *
-       * // Remove the moved model.
-       * await tf.io.removeModel('indexeddb://demo/management/model1');
-       * ```
-       *
-       * @param sourceURL Source URL of moving.
-       * @param destURL Destination URL of moving.
-       * @returns ModelArtifactsInfo of the copied model (if and only if copying
-       *   is successful).
-       * @throws Error if moving fails, e.g., if no model exists at `sourceURL`, or
-       *   if `oldPath` and `newPath` are identical.
-       */
-      /**
-       * @doc {
-       *   heading: 'Models',
-       *   subheading: 'Management',
-       *   namespace: 'io',
-       *   ignoreCI: true
-       * }
-       */
-      async function moveModel(sourceURL, destURL) {
-        const deleteSource = true;
-        return cloneModelInternal(sourceURL, destURL, deleteSource);
-      }
-
-      //# sourceMappingURL=model_management.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/indexed_db.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const DATABASE_NAME = "tensorflowjs";
-      const DATABASE_VERSION = 1;
-      // Model data and ModelArtifactsInfo (metadata) are stored in two separate
-      // stores for efficient access of the list of stored models and their metadata.
-      // 1. The object store for model data: topology, weights and weight manifests.
-      const MODEL_STORE_NAME = "models_store";
-      // 2. The object store for ModelArtifactsInfo, including meta-information such
-      //    as the type of topology (JSON vs binary), byte size of the topology, byte
-      //    size of the weights, etc.
-      const INFO_STORE_NAME = "model_info_store";
-      /**
-       * Delete the entire database for tensorflow.js, including the models store.
-       */
-      async function deleteDatabase() {
-        const idbFactory = getIndexedDBFactory();
-        return new Promise((resolve, reject) => {
-          const deleteRequest = idbFactory.deleteDatabase(DATABASE_NAME);
-          deleteRequest.onsuccess = () => resolve();
-          deleteRequest.onerror = (error) => reject(error);
-        });
-      }
-      function getIndexedDBFactory() {
-        if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
-          // TODO(cais): Add more info about what IOHandler subtypes are available.
-          //   Maybe point to a doc page on the web and/or automatically determine
-          //   the available IOHandlers and print them in the error message.
-          throw new Error(
-            "Failed to obtain IndexedDB factory because the current environment" +
-              "is not a web browser."
-          );
-        }
-        // tslint:disable-next-line:no-any
-        const theWindow = typeof window === "undefined" ? self : window;
-        const factory =
-          theWindow.indexedDB ||
-          theWindow.mozIndexedDB ||
-          theWindow.webkitIndexedDB ||
-          theWindow.msIndexedDB ||
-          theWindow.shimIndexedDB;
-        if (factory == null) {
-          throw new Error("The current browser does not appear to support IndexedDB.");
-        }
-        return factory;
-      }
-      function setUpDatabase(openRequest) {
-        const db = openRequest.result;
-        db.createObjectStore(MODEL_STORE_NAME, { keyPath: "modelPath" });
-        db.createObjectStore(INFO_STORE_NAME, { keyPath: "modelPath" });
-      }
-      /**
-       * IOHandler subclass: Browser IndexedDB.
-       *
-       * See the doc string of `browserIndexedDB` for more details.
-       */
-      class indexed_db_BrowserIndexedDB {
-        constructor(modelPath) {
-          this.indexedDB = getIndexedDBFactory();
-          if (modelPath == null || !modelPath) {
-            throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");
-          }
-          this.modelPath = modelPath;
-        }
-        async save(modelArtifacts) {
-          // TODO(cais): Support saving GraphDef models.
-          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
-            throw new Error(
-              "BrowserLocalStorage.save() does not support saving model topology " +
-                "in binary formats yet."
-            );
-          }
-          return this.databaseAction(this.modelPath, modelArtifacts);
-        }
-        async load() {
-          return this.databaseAction(this.modelPath);
-        }
-        /**
-         * Perform database action to put model artifacts into or read model artifacts
-         * from IndexedDB object store.
-         *
-         * Whether the action is put or get depends on whether `modelArtifacts` is
-         * specified. If it is specified, the action will be put; otherwise the action
-         * will be get.
-         *
-         * @param modelPath A unique string path for the model.
-         * @param modelArtifacts If specified, it will be the model artifacts to be
-         *   stored in IndexedDB.
-         * @returns A `Promise` of `SaveResult`, if the action is put, or a `Promise`
-         *   of `ModelArtifacts`, if the action is get.
-         */
-        databaseAction(modelPath, modelArtifacts) {
-          return new Promise((resolve, reject) => {
-            const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);
-            openRequest.onupgradeneeded = () => setUpDatabase(openRequest);
-            openRequest.onsuccess = () => {
-              const db = openRequest.result;
-              if (modelArtifacts == null) {
-                // Read model out from object store.
-                const modelTx = db.transaction(MODEL_STORE_NAME, "readonly");
-                const modelStore = modelTx.objectStore(MODEL_STORE_NAME);
-                const getRequest = modelStore.get(this.modelPath);
-                getRequest.onsuccess = () => {
-                  if (getRequest.result == null) {
-                    db.close();
-                    return reject(
-                      new Error(
-                        `Cannot find model with path '${this.modelPath}' ` + `in IndexedDB.`
-                      )
-                    );
-                  } else {
-                    resolve(getRequest.result.modelArtifacts);
-                  }
-                };
-                getRequest.onerror = (error) => {
-                  db.close();
-                  return reject(getRequest.error);
-                };
-                modelTx.oncomplete = () => db.close();
-              } else {
-                // Put model into object store.
-                const modelArtifactsInfo = Object(io_utils["g" /* getModelArtifactsInfoForJSON */])(
-                  modelArtifacts
-                );
-                // First, put ModelArtifactsInfo into info store.
-                const infoTx = db.transaction(INFO_STORE_NAME, "readwrite");
-                let infoStore = infoTx.objectStore(INFO_STORE_NAME);
-                const putInfoRequest = infoStore.put({
-                  modelPath: this.modelPath,
-                  modelArtifactsInfo,
-                });
-                let modelTx;
-                putInfoRequest.onsuccess = () => {
-                  // Second, put model data into model store.
-                  modelTx = db.transaction(MODEL_STORE_NAME, "readwrite");
-                  const modelStore = modelTx.objectStore(MODEL_STORE_NAME);
-                  const putModelRequest = modelStore.put({
-                    modelPath: this.modelPath,
-                    modelArtifacts,
-                    modelArtifactsInfo,
-                  });
-                  putModelRequest.onsuccess = () => resolve({ modelArtifactsInfo });
-                  putModelRequest.onerror = (error) => {
-                    // If the put-model request fails, roll back the info entry as
-                    // well.
-                    infoStore = infoTx.objectStore(INFO_STORE_NAME);
-                    const deleteInfoRequest = infoStore.delete(this.modelPath);
-                    deleteInfoRequest.onsuccess = () => {
-                      db.close();
-                      return reject(putModelRequest.error);
-                    };
-                    deleteInfoRequest.onerror = (error) => {
-                      db.close();
-                      return reject(putModelRequest.error);
-                    };
-                  };
-                };
-                putInfoRequest.onerror = (error) => {
-                  db.close();
-                  return reject(putInfoRequest.error);
-                };
-                infoTx.oncomplete = () => {
-                  if (modelTx == null) {
-                    db.close();
-                  } else {
-                    modelTx.oncomplete = () => db.close();
-                  }
-                };
-              }
-            };
-            openRequest.onerror = (error) => reject(openRequest.error);
-          });
-        }
-      }
-      indexed_db_BrowserIndexedDB.URL_SCHEME = "indexeddb://";
-      const indexedDBRouter = (url) => {
-        if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
-          return null;
-        } else {
-          if (!Array.isArray(url) && url.startsWith(indexed_db_BrowserIndexedDB.URL_SCHEME)) {
-            return browserIndexedDB(url.slice(indexed_db_BrowserIndexedDB.URL_SCHEME.length));
-          } else {
-            return null;
-          }
-        }
-      };
-      IORouterRegistry.registerSaveRouter(indexedDBRouter);
-      IORouterRegistry.registerLoadRouter(indexedDBRouter);
-      /**
-       * Creates a browser IndexedDB IOHandler for saving and loading models.
-       *
-       * ```js
-       * const model = tf.sequential();
-       * model.add(
-       *     tf.layers.dense({units: 1, inputShape: [100], activation: 'sigmoid'}));
-       *
-       * const saveResult = await model.save('indexeddb://MyModel'));
-       * console.log(saveResult);
-       * ```
-       *
-       * @param modelPath A unique identifier for the model to be saved. Must be a
-       *   non-empty string.
-       * @returns An instance of `BrowserIndexedDB` (sublcass of `IOHandler`),
-       *   which can be used with, e.g., `tf.Model.save`.
-       */
-      function browserIndexedDB(modelPath) {
-        return new indexed_db_BrowserIndexedDB(modelPath);
-      }
-      function maybeStripScheme(key) {
-        return key.startsWith(indexed_db_BrowserIndexedDB.URL_SCHEME)
-          ? key.slice(indexed_db_BrowserIndexedDB.URL_SCHEME.length)
-          : key;
-      }
-      class BrowserIndexedDBManager {
-        constructor() {
-          this.indexedDB = getIndexedDBFactory();
-        }
-        async listModels() {
-          return new Promise((resolve, reject) => {
-            const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);
-            openRequest.onupgradeneeded = () => setUpDatabase(openRequest);
-            openRequest.onsuccess = () => {
-              const db = openRequest.result;
-              const tx = db.transaction(INFO_STORE_NAME, "readonly");
-              const store = tx.objectStore(INFO_STORE_NAME);
-              // tslint:disable:max-line-length
-              // Need to cast `store` as `any` here because TypeScript's DOM
-              // library does not have the `getAll()` method even though the
-              // method is supported in the latest version of most mainstream
-              // browsers:
-              // https://developer.mozilla.org/en-US/docs/Web/API/IDBObjectStore/getAll
-              // tslint:enable:max-line-length
-              // tslint:disable-next-line:no-any
-              const getAllInfoRequest = store.getAll();
-              getAllInfoRequest.onsuccess = () => {
-                const out = {};
-                for (const item of getAllInfoRequest.result) {
-                  out[item.modelPath] = item.modelArtifactsInfo;
-                }
-                resolve(out);
-              };
-              getAllInfoRequest.onerror = (error) => {
-                db.close();
-                return reject(getAllInfoRequest.error);
-              };
-              tx.oncomplete = () => db.close();
-            };
-            openRequest.onerror = (error) => reject(openRequest.error);
-          });
-        }
-        async removeModel(path) {
-          path = maybeStripScheme(path);
-          return new Promise((resolve, reject) => {
-            const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);
-            openRequest.onupgradeneeded = () => setUpDatabase(openRequest);
-            openRequest.onsuccess = () => {
-              const db = openRequest.result;
-              const infoTx = db.transaction(INFO_STORE_NAME, "readwrite");
-              const infoStore = infoTx.objectStore(INFO_STORE_NAME);
-              const getInfoRequest = infoStore.get(path);
-              let modelTx;
-              getInfoRequest.onsuccess = () => {
-                if (getInfoRequest.result == null) {
-                  db.close();
-                  return reject(
-                    new Error(`Cannot find model with path '${path}' ` + `in IndexedDB.`)
-                  );
-                } else {
-                  // First, delete the entry in the info store.
-                  const deleteInfoRequest = infoStore.delete(path);
-                  const deleteModelData = () => {
-                    // Second, delete the entry in the model store.
-                    modelTx = db.transaction(MODEL_STORE_NAME, "readwrite");
-                    const modelStore = modelTx.objectStore(MODEL_STORE_NAME);
-                    const deleteModelRequest = modelStore.delete(path);
-                    deleteModelRequest.onsuccess = () =>
-                      resolve(getInfoRequest.result.modelArtifactsInfo);
-                    deleteModelRequest.onerror = (error) => reject(getInfoRequest.error);
-                  };
-                  // Proceed with deleting model data regardless of whether deletion
-                  // of info data succeeds or not.
-                  deleteInfoRequest.onsuccess = deleteModelData;
-                  deleteInfoRequest.onerror = (error) => {
-                    deleteModelData();
-                    db.close();
-                    return reject(getInfoRequest.error);
-                  };
-                }
-              };
-              getInfoRequest.onerror = (error) => {
-                db.close();
-                return reject(getInfoRequest.error);
-              };
-              infoTx.oncomplete = () => {
-                if (modelTx == null) {
-                  db.close();
-                } else {
-                  modelTx.oncomplete = () => db.close();
-                }
-              };
-            };
-            openRequest.onerror = (error) => reject(openRequest.error);
-          });
-        }
-      }
-      if (Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
-        // Wrap the construction and registration, to guard against browsers that
-        // don't support Local Storage.
-        try {
-          model_management_ModelStoreManagerRegistry.registerManager(
-            indexed_db_BrowserIndexedDB.URL_SCHEME,
-            new BrowserIndexedDBManager()
-          );
-        } catch (err) {}
-      }
-      //# sourceMappingURL=indexed_db.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/local_storage.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const PATH_SEPARATOR = "/";
-      const PATH_PREFIX = "tensorflowjs_models";
-      const INFO_SUFFIX = "info";
-      const MODEL_TOPOLOGY_SUFFIX = "model_topology";
-      const WEIGHT_SPECS_SUFFIX = "weight_specs";
-      const WEIGHT_DATA_SUFFIX = "weight_data";
-      const MODEL_METADATA_SUFFIX = "model_metadata";
-      /**
-       * Purge all tensorflow.js-saved model artifacts from local storage.
-       *
-       * @returns Paths of the models purged.
-       */
-      function purgeLocalStorageArtifacts() {
-        if (
-          !Object(environment["c" /* env */])().getBool("IS_BROWSER") ||
-          typeof window === "undefined" ||
-          typeof window.localStorage === "undefined"
-        ) {
-          throw new Error(
-            "purgeLocalStorageModels() cannot proceed because local storage is " +
-              "unavailable in the current environment."
-          );
-        }
-        const LS = window.localStorage;
-        const purgedModelPaths = [];
-        for (let i = 0; i < LS.length; ++i) {
-          const key = LS.key(i);
-          const prefix = PATH_PREFIX + PATH_SEPARATOR;
-          if (key.startsWith(prefix) && key.length > prefix.length) {
-            LS.removeItem(key);
-            const modelName = getModelPathFromKey(key);
-            if (purgedModelPaths.indexOf(modelName) === -1) {
-              purgedModelPaths.push(modelName);
-            }
-          }
-        }
-        return purgedModelPaths;
-      }
-      function getModelKeys(path) {
-        return {
-          info: [PATH_PREFIX, path, INFO_SUFFIX].join(PATH_SEPARATOR),
-          topology: [PATH_PREFIX, path, MODEL_TOPOLOGY_SUFFIX].join(PATH_SEPARATOR),
-          weightSpecs: [PATH_PREFIX, path, WEIGHT_SPECS_SUFFIX].join(PATH_SEPARATOR),
-          weightData: [PATH_PREFIX, path, WEIGHT_DATA_SUFFIX].join(PATH_SEPARATOR),
-          modelMetadata: [PATH_PREFIX, path, MODEL_METADATA_SUFFIX].join(PATH_SEPARATOR),
-        };
-      }
-      /**
-       * Get model path from a local-storage key.
-       *
-       * E.g., 'tensorflowjs_models/my/model/1/info' --> 'my/model/1'
-       *
-       * @param key
-       */
-      function getModelPathFromKey(key) {
-        const items = key.split(PATH_SEPARATOR);
-        if (items.length < 3) {
-          throw new Error(`Invalid key format: ${key}`);
-        }
-        return items.slice(1, items.length - 1).join(PATH_SEPARATOR);
-      }
-      function local_storage_maybeStripScheme(key) {
-        return key.startsWith(local_storage_BrowserLocalStorage.URL_SCHEME)
-          ? key.slice(local_storage_BrowserLocalStorage.URL_SCHEME.length)
-          : key;
-      }
-      /**
-       * IOHandler subclass: Browser Local Storage.
-       *
-       * See the doc string to `browserLocalStorage` for more details.
-       */
-      class local_storage_BrowserLocalStorage {
-        constructor(modelPath) {
-          if (
-            !Object(environment["c" /* env */])().getBool("IS_BROWSER") ||
-            typeof window === "undefined" ||
-            typeof window.localStorage === "undefined"
-          ) {
-            // TODO(cais): Add more info about what IOHandler subtypes are
-            // available.
-            //   Maybe point to a doc page on the web and/or automatically determine
-            //   the available IOHandlers and print them in the error message.
-            throw new Error("The current environment does not support local storage.");
-          }
-          this.LS = window.localStorage;
-          if (modelPath == null || !modelPath) {
-            throw new Error("For local storage, modelPath must not be null, undefined or empty.");
-          }
-          this.modelPath = modelPath;
-          this.keys = getModelKeys(this.modelPath);
-        }
-        /**
-         * Save model artifacts to browser local storage.
-         *
-         * See the documentation to `browserLocalStorage` for details on the saved
-         * artifacts.
-         *
-         * @param modelArtifacts The model artifacts to be stored.
-         * @returns An instance of SaveResult.
-         */
-        async save(modelArtifacts) {
-          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
-            throw new Error(
-              "BrowserLocalStorage.save() does not support saving model topology " +
-                "in binary formats yet."
-            );
-          } else {
-            const topology = JSON.stringify(modelArtifacts.modelTopology);
-            const weightSpecs = JSON.stringify(modelArtifacts.weightSpecs);
-            const modelArtifactsInfo = Object(io_utils["g" /* getModelArtifactsInfoForJSON */])(
-              modelArtifacts
-            );
-            try {
-              this.LS.setItem(this.keys.info, JSON.stringify(modelArtifactsInfo));
-              this.LS.setItem(this.keys.topology, topology);
-              this.LS.setItem(this.keys.weightSpecs, weightSpecs);
-              this.LS.setItem(
-                this.keys.weightData,
-                Object(io_utils["a" /* arrayBufferToBase64String */])(modelArtifacts.weightData)
-              );
-              this.LS.setItem(
-                this.keys.modelMetadata,
-                JSON.stringify({
-                  format: modelArtifacts.format,
-                  generatedBy: modelArtifacts.generatedBy,
-                  convertedBy: modelArtifacts.convertedBy,
-                  userDefinedMetadata: modelArtifacts.userDefinedMetadata,
-                })
-              );
-              return { modelArtifactsInfo };
-            } catch (err) {
-              // If saving failed, clean up all items saved so far.
-              this.LS.removeItem(this.keys.info);
-              this.LS.removeItem(this.keys.topology);
-              this.LS.removeItem(this.keys.weightSpecs);
-              this.LS.removeItem(this.keys.weightData);
-              this.LS.removeItem(this.keys.modelMetadata);
-              throw new Error(
-                `Failed to save model '${this.modelPath}' to local storage: ` +
-                  `size quota being exceeded is a possible cause of this failure: ` +
-                  `modelTopologyBytes=${modelArtifactsInfo.modelTopologyBytes}, ` +
-                  `weightSpecsBytes=${modelArtifactsInfo.weightSpecsBytes}, ` +
-                  `weightDataBytes=${modelArtifactsInfo.weightDataBytes}.`
-              );
-            }
-          }
-        }
-        /**
-         * Load a model from local storage.
-         *
-         * See the documentation to `browserLocalStorage` for details on the saved
-         * artifacts.
-         *
-         * @returns The loaded model (if loading succeeds).
-         */
-        async load() {
-          const info = JSON.parse(this.LS.getItem(this.keys.info));
-          if (info == null) {
-            throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);
-          }
-          if (info.modelTopologyType !== "JSON") {
-            throw new Error(
-              "BrowserLocalStorage does not support loading non-JSON model " + "topology yet."
-            );
-          }
-          const out = {};
-          // Load topology.
-          const topology = JSON.parse(this.LS.getItem(this.keys.topology));
-          if (topology == null) {
-            throw new Error(
-              `In local storage, the topology of model '${this.modelPath}' ` + `is missing.`
-            );
-          }
-          out.modelTopology = topology;
-          // Load weight specs.
-          const weightSpecs = JSON.parse(this.LS.getItem(this.keys.weightSpecs));
-          if (weightSpecs == null) {
-            throw new Error(
-              `In local storage, the weight specs of model '${this.modelPath}' ` + `are missing.`
-            );
-          }
-          out.weightSpecs = weightSpecs;
-          // Load meta-data fields.
-          const metadataString = this.LS.getItem(this.keys.modelMetadata);
-          if (metadataString != null) {
-            const metadata = JSON.parse(metadataString);
-            out.format = metadata["format"];
-            out.generatedBy = metadata["generatedBy"];
-            out.convertedBy = metadata["convertedBy"];
-            out.userDefinedMetadata = metadata["userDefinedMetadata"];
-          }
-          // Load weight data.
-          const weightDataBase64 = this.LS.getItem(this.keys.weightData);
-          if (weightDataBase64 == null) {
-            throw new Error(
-              `In local storage, the binary weight values of model ` +
-                `'${this.modelPath}' are missing.`
-            );
-          }
-          out.weightData = Object(io_utils["b" /* base64StringToArrayBuffer */])(weightDataBase64);
-          return out;
-        }
-      }
-      local_storage_BrowserLocalStorage.URL_SCHEME = "localstorage://";
-      const localStorageRouter = (url) => {
-        if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
-          return null;
-        } else {
-          if (!Array.isArray(url) && url.startsWith(local_storage_BrowserLocalStorage.URL_SCHEME)) {
-            return browserLocalStorage(
-              url.slice(local_storage_BrowserLocalStorage.URL_SCHEME.length)
-            );
-          } else {
-            return null;
-          }
-        }
-      };
-      IORouterRegistry.registerSaveRouter(localStorageRouter);
-      IORouterRegistry.registerLoadRouter(localStorageRouter);
-      /**
-       * Factory function for local storage IOHandler.
-       *
-       * This `IOHandler` supports both `save` and `load`.
-       *
-       * For each model's saved artifacts, four items are saved to local storage.
-       *   - `${PATH_SEPARATOR}/${modelPath}/info`: Contains meta-info about the
-       *     model, such as date saved, type of the topology, size in bytes, etc.
-       *   - `${PATH_SEPARATOR}/${modelPath}/topology`: Model topology. For Keras-
-       *     style models, this is a stringized JSON.
-       *   - `${PATH_SEPARATOR}/${modelPath}/weight_specs`: Weight specs of the
-       *     model, can be used to decode the saved binary weight values (see
-       *     item below).
-       *   - `${PATH_SEPARATOR}/${modelPath}/weight_data`: Concatenated binary
-       *     weight values, stored as a base64-encoded string.
-       *
-       * Saving may throw an `Error` if the total size of the artifacts exceed the
-       * browser-specific quota.
-       *
-       * @param modelPath A unique identifier for the model to be saved. Must be a
-       *   non-empty string.
-       * @returns An instance of `IOHandler`, which can be used with, e.g.,
-       *   `tf.Model.save`.
-       */
-      function browserLocalStorage(modelPath) {
-        return new local_storage_BrowserLocalStorage(modelPath);
-      }
-      class local_storage_BrowserLocalStorageManager {
-        constructor() {
-          Object(util["assert"])(
-            Object(environment["c" /* env */])().getBool("IS_BROWSER"),
-            () => "Current environment is not a web browser"
-          );
-          Object(util["assert"])(
-            typeof window === "undefined" || typeof window.localStorage !== "undefined",
-            () => "Current browser does not appear to support localStorage"
-          );
-          this.LS = window.localStorage;
-        }
-        async listModels() {
-          const out = {};
-          const prefix = PATH_PREFIX + PATH_SEPARATOR;
-          const suffix = PATH_SEPARATOR + INFO_SUFFIX;
-          for (let i = 0; i < this.LS.length; ++i) {
-            const key = this.LS.key(i);
-            if (key.startsWith(prefix) && key.endsWith(suffix)) {
-              const modelPath = getModelPathFromKey(key);
-              out[modelPath] = JSON.parse(this.LS.getItem(key));
-            }
-          }
-          return out;
-        }
-        async removeModel(path) {
-          path = local_storage_maybeStripScheme(path);
-          const keys = getModelKeys(path);
-          if (this.LS.getItem(keys.info) == null) {
-            throw new Error(`Cannot find model at path '${path}'`);
-          }
-          const info = JSON.parse(this.LS.getItem(keys.info));
-          this.LS.removeItem(keys.info);
-          this.LS.removeItem(keys.topology);
-          this.LS.removeItem(keys.weightSpecs);
-          this.LS.removeItem(keys.weightData);
-          return info;
-        }
-      }
-      if (Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
-        // Wrap the construction and registration, to guard against browsers that
-        // don't support Local Storage.
-        try {
-          model_management_ModelStoreManagerRegistry.registerManager(
-            local_storage_BrowserLocalStorage.URL_SCHEME,
-            new local_storage_BrowserLocalStorageManager()
-          );
-        } catch (err) {}
-      }
-      //# sourceMappingURL=local_storage.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/browser_files.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * IOHandlers related to files, such as browser-triggered file downloads,
-       * user-selected files in browser.
-       */
-
-      const DEFAULT_FILE_NAME_PREFIX = "model";
-      const DEFAULT_JSON_EXTENSION_NAME = ".json";
-      const DEFAULT_WEIGHT_DATA_EXTENSION_NAME = ".weights.bin";
-      function defer(f) {
-        return new Promise((resolve) => setTimeout(resolve)).then(f);
-      }
-      class browser_files_BrowserDownloads {
-        constructor(fileNamePrefix) {
-          if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
-            // TODO(cais): Provide info on what IOHandlers are available under the
-            //   current environment.
-            throw new Error(
-              "browserDownloads() cannot proceed because the current environment " +
-                "is not a browser."
-            );
-          }
-          if (fileNamePrefix.startsWith(browser_files_BrowserDownloads.URL_SCHEME)) {
-            fileNamePrefix = fileNamePrefix.slice(browser_files_BrowserDownloads.URL_SCHEME.length);
-          }
-          if (fileNamePrefix == null || fileNamePrefix.length === 0) {
-            fileNamePrefix = DEFAULT_FILE_NAME_PREFIX;
-          }
-          this.modelTopologyFileName = fileNamePrefix + DEFAULT_JSON_EXTENSION_NAME;
-          this.weightDataFileName = fileNamePrefix + DEFAULT_WEIGHT_DATA_EXTENSION_NAME;
-        }
-        async save(modelArtifacts) {
-          if (typeof document === "undefined") {
-            throw new Error(
-              "Browser downloads are not supported in " +
-                "this environment since `document` is not present"
-            );
-          }
-          const weightsURL = window.URL.createObjectURL(
-            new Blob([modelArtifacts.weightData], { type: "application/octet-stream" })
-          );
-          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
-            throw new Error(
-              "BrowserDownloads.save() does not support saving model topology " +
-                "in binary formats yet."
-            );
-          } else {
-            const weightsManifest = [
-              {
-                paths: ["./" + this.weightDataFileName],
-                weights: modelArtifacts.weightSpecs,
-              },
-            ];
-            const modelTopologyAndWeightManifest = {
-              modelTopology: modelArtifacts.modelTopology,
-              format: modelArtifacts.format,
-              generatedBy: modelArtifacts.generatedBy,
-              convertedBy: modelArtifacts.convertedBy,
-              weightsManifest,
-            };
-            const modelTopologyAndWeightManifestURL = window.URL.createObjectURL(
-              new Blob([JSON.stringify(modelTopologyAndWeightManifest)], {
-                type: "application/json",
-              })
-            );
-            // If anchor elements are not provided, create them without attaching them
-            // to parents, so that the downloaded file names can be controlled.
-            const jsonAnchor =
-              this.jsonAnchor == null ? document.createElement("a") : this.jsonAnchor;
-            jsonAnchor.download = this.modelTopologyFileName;
-            jsonAnchor.href = modelTopologyAndWeightManifestURL;
-            // Trigger downloads by evoking a click event on the download anchors.
-            // When multiple downloads are started synchronously, Firefox will only
-            // save the last one.
-            await defer(() => jsonAnchor.dispatchEvent(new MouseEvent("click")));
-            if (modelArtifacts.weightData != null) {
-              const weightDataAnchor =
-                this.weightDataAnchor == null ? document.createElement("a") : this.weightDataAnchor;
-              weightDataAnchor.download = this.weightDataFileName;
-              weightDataAnchor.href = weightsURL;
-              await defer(() => weightDataAnchor.dispatchEvent(new MouseEvent("click")));
-            }
-            return {
-              modelArtifactsInfo: Object(io_utils["g" /* getModelArtifactsInfoForJSON */])(
-                modelArtifacts
-              ),
-            };
-          }
-        }
-      }
-      browser_files_BrowserDownloads.URL_SCHEME = "downloads://";
-      class browser_files_BrowserFiles {
-        constructor(files) {
-          if (files == null || files.length < 1) {
-            throw new Error(
-              `When calling browserFiles, at least 1 file is required, ` + `but received ${files}`
-            );
-          }
-          this.files = files;
-        }
-        async load() {
-          const jsonFile = this.files[0];
-          const weightFiles = this.files.slice(1);
-          return new Promise((resolve, reject) => {
-            const jsonReader = new FileReader();
-            jsonReader.onload = (event) => {
-              // tslint:disable-next-line:no-any
-              const modelJSON = JSON.parse(event.target.result);
-              const modelTopology = modelJSON.modelTopology;
-              if (modelTopology == null) {
-                reject(new Error(`modelTopology field is missing from file ${jsonFile.name}`));
-                return;
-              }
-              if (weightFiles.length === 0) {
-                resolve({ modelTopology });
-              }
-              const weightsManifest = modelJSON.weightsManifest;
-              if (weightsManifest == null) {
-                reject(new Error(`weightManifest field is missing from file ${jsonFile.name}`));
-                return;
-              }
-              let pathToFile;
-              try {
-                pathToFile = this.checkManifestAndWeightFiles(weightsManifest, weightFiles);
-              } catch (err) {
-                reject(err);
-                return;
-              }
-              const weightSpecs = [];
-              const paths = [];
-              const perFileBuffers = [];
-              weightsManifest.forEach((weightsGroup) => {
-                weightsGroup.paths.forEach((path) => {
-                  paths.push(path);
-                  perFileBuffers.push(null);
-                });
-                weightSpecs.push(...weightsGroup.weights);
-              });
-              weightsManifest.forEach((weightsGroup) => {
-                weightsGroup.paths.forEach((path) => {
-                  const weightFileReader = new FileReader();
-                  weightFileReader.onload = (event) => {
-                    // tslint:disable-next-line:no-any
-                    const weightData = event.target.result;
-                    const index = paths.indexOf(path);
-                    perFileBuffers[index] = weightData;
-                    if (perFileBuffers.indexOf(null) === -1) {
-                      resolve({
-                        modelTopology,
-                        weightSpecs,
-                        weightData: Object(io_utils["d" /* concatenateArrayBuffers */])(
-                          perFileBuffers
-                        ),
-                        format: modelJSON.format,
-                        generatedBy: modelJSON.generatedBy,
-                        convertedBy: modelJSON.convertedBy,
-                        userDefinedMetadata: modelJSON.userDefinedMetadata,
-                      });
-                    }
-                  };
-                  weightFileReader.onerror = (error) =>
-                    reject(`Failed to weights data from file of path '${path}'.`);
-                  weightFileReader.readAsArrayBuffer(pathToFile[path]);
-                });
-              });
-            };
-            jsonReader.onerror = (error) =>
-              reject(
-                `Failed to read model topology and weights manifest JSON ` +
-                  `from file '${jsonFile.name}'. BrowserFiles supports loading ` +
-                  `Keras-style tf.Model artifacts only.`
-              );
-            jsonReader.readAsText(jsonFile);
-          });
-        }
-        /**
-         * Check the compatibility between weights manifest and weight files.
-         */
-        checkManifestAndWeightFiles(manifest, files) {
-          const basenames = [];
-          const fileNames = files.map((file) => Object(io_utils["c" /* basename */])(file.name));
-          const pathToFile = {};
-          for (const group of manifest) {
-            group.paths.forEach((path) => {
-              const pathBasename = Object(io_utils["c" /* basename */])(path);
-              if (basenames.indexOf(pathBasename) !== -1) {
-                throw new Error(
-                  `Duplicate file basename found in weights manifest: ` + `'${pathBasename}'`
-                );
-              }
-              basenames.push(pathBasename);
-              if (fileNames.indexOf(pathBasename) === -1) {
-                throw new Error(`Weight file with basename '${pathBasename}' is not provided.`);
-              } else {
-                pathToFile[path] = files[fileNames.indexOf(pathBasename)];
-              }
-            });
-          }
-          if (basenames.length !== files.length) {
-            throw new Error(
-              `Mismatch in the number of files in weights manifest ` +
-                `(${basenames.length}) and the number of weight files provided ` +
-                `(${files.length}).`
-            );
-          }
-          return pathToFile;
-        }
-      }
-      const browserDownloadsRouter = (url) => {
-        if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
-          return null;
-        } else {
-          if (!Array.isArray(url) && url.startsWith(browser_files_BrowserDownloads.URL_SCHEME)) {
-            return browserDownloads(url.slice(browser_files_BrowserDownloads.URL_SCHEME.length));
-          } else {
-            return null;
-          }
-        }
-      };
-      IORouterRegistry.registerSaveRouter(browserDownloadsRouter);
-      /**
-       * Creates an IOHandler that triggers file downloads from the browser.
-       *
-       * The returned `IOHandler` instance can be used as model exporting methods such
-       * as `tf.Model.save` and supports only saving.
-       *
-       * ```js
-       * const model = tf.sequential();
-       * model.add(tf.layers.dense(
-       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
-       * const saveResult = await model.save('downloads://mymodel');
-       * // This will trigger downloading of two files:
-       * //   'mymodel.json' and 'mymodel.weights.bin'.
-       * console.log(saveResult);
-       * ```
-       *
-       * @param fileNamePrefix Prefix name of the files to be downloaded. For use with
-       *   `tf.Model`, `fileNamePrefix` should follow either of the following two
-       *   formats:
-       *   1. `null` or `undefined`, in which case the default file
-       *      names will be used:
-       *      - 'model.json' for the JSON file containing the model topology and
-       *        weights manifest.
-       *      - 'model.weights.bin' for the binary file containing the binary weight
-       *        values.
-       *   2. A single string or an Array of a single string, as the file name prefix.
-       *      For example, if `'foo'` is provided, the downloaded JSON
-       *      file and binary weights file will be named 'foo.json' and
-       *      'foo.weights.bin', respectively.
-       * @param config Additional configuration for triggering downloads.
-       * @returns An instance of `BrowserDownloads` `IOHandler`.
-       */
-      /**
-       * @doc {
-       *   heading: 'Models',
-       *   subheading: 'Loading',
-       *   namespace: 'io',
-       *   ignoreCI: true
-       * }
-       */
-      function browserDownloads(fileNamePrefix = "model") {
-        return new browser_files_BrowserDownloads(fileNamePrefix);
-      }
-      /**
-       * Creates an IOHandler that loads model artifacts from user-selected files.
-       *
-       * This method can be used for loading from files such as user-selected files
-       * in the browser.
-       * When used in conjunction with `tf.loadLayersModel`, an instance of
-       * `tf.LayersModel` (Keras-style) can be constructed from the loaded artifacts.
-       *
-       * ```js
-       * // Note: This code snippet won't run properly without the actual file input
-       * //   elements in the HTML DOM.
-       *
-       * // Suppose there are two HTML file input (`<input type="file" ...>`)
-       * // elements.
-       * const uploadJSONInput = document.getElementById('upload-json');
-       * const uploadWeightsInput = document.getElementById('upload-weights');
-       * const model = await tf.loadLayersModel(tf.io.browserFiles(
-       *     [uploadJSONInput.files[0], uploadWeightsInput.files[0]]));
-       * ```
-       *
-       * @param files `File`s to load from. Currently, this function supports only
-       *   loading from files that contain Keras-style models (i.e., `tf.Model`s), for
-       *   which an `Array` of `File`s is expected (in that order):
-       *   - A JSON file containing the model topology and weight manifest.
-       *   - Optionally, One or more binary files containing the binary weights.
-       *     These files must have names that match the paths in the `weightsManifest`
-       *     contained by the aforementioned JSON file, or errors will be thrown
-       *     during loading. These weights files have the same format as the ones
-       *     generated by `tensorflowjs_converter` that comes with the `tensorflowjs`
-       *     Python PIP package. If no weights files are provided, only the model
-       *     topology will be loaded from the JSON file above.
-       * @returns An instance of `Files` `IOHandler`.
-       */
-      /**
-       * @doc {
-       *   heading: 'Models',
-       *   subheading: 'Loading',
-       *   namespace: 'io',
-       *   ignoreCI: true
-       * }
-       */
-      function browserFiles(files) {
-        return new browser_files_BrowserFiles(files);
-      }
-      //# sourceMappingURL=browser_files.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/progress.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Monitor Promise.all progress, fire onProgress callback function.
-       *
-       * @param promises Promise list going to be monitored
-       * @param onProgress Callback function. Fired when a promise resolved.
-       * @param startFraction Optional fraction start. Default to 0.
-       * @param endFraction Optional fraction end. Default to 1.
-       */
-      function monitorPromisesProgress(promises, onProgress, startFraction, endFraction) {
-        checkPromises(promises);
-        startFraction = startFraction == null ? 0 : startFraction;
-        endFraction = endFraction == null ? 1 : endFraction;
-        checkFraction(startFraction, endFraction);
-        let resolvedPromise = 0;
-        const registerMonitor = (promise) => {
-          promise.then((value) => {
-            const fraction =
-              startFraction + (++resolvedPromise / promises.length) * (endFraction - startFraction);
-            // pass fraction as parameter to callback function.
-            onProgress(fraction);
-            return value;
-          });
-          return promise;
-        };
-        function checkPromises(promises) {
-          Object(util["assert"])(
-            promises != null && Array.isArray(promises) && promises.length > 0,
-            () => "promises must be a none empty array"
-          );
-        }
-        function checkFraction(startFraction, endFraction) {
-          Object(util["assert"])(
-            startFraction >= 0 && startFraction <= 1,
-            () =>
-              `Progress fraction must be in range [0, 1], but ` +
-              `got startFraction ${startFraction}`
-          );
-          Object(util["assert"])(
-            endFraction >= 0 && endFraction <= 1,
-            () =>
-              `Progress fraction must be in range [0, 1], but ` + `got endFraction ${endFraction}`
-          );
-          Object(util["assert"])(
-            endFraction >= startFraction,
-            () =>
-              `startFraction must be no more than endFraction, but ` +
-              `got startFraction ${startFraction} and endFraction ` +
-              `${endFraction}`
-          );
-        }
-        return Promise.all(promises.map(registerMonitor));
-      }
-      //# sourceMappingURL=progress.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/types.js
-      var types = __webpack_require__(34);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/weights_loader.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Reads binary weights data from a number of URLs.
-       *
-       * @param fetchURLs URLs to send the HTTP requests at, using `fetch` calls.
-       * @param requestOptions RequestInit (options) for the HTTP requests.
-       * @param fetchFunc Optional overriding value for the `window.fetch` function.
-       * @param onProgress Optional, progress callback function, fired periodically
-       *   before the load is completed.
-       * @returns A `Promise` of an Array of `ArrayBuffer`. The Array has the same
-       *   length as `fetchURLs`.
-       */
-      async function loadWeightsAsArrayBuffer(fetchURLs, loadOptions) {
-        if (loadOptions == null) {
-          loadOptions = {};
-        }
-        const fetchFunc =
-          loadOptions.fetchFunc == null
-            ? Object(environment["c" /* env */])().platform.fetch
-            : loadOptions.fetchFunc;
-        // Create the requests for all of the weights in parallel.
-        const requests = fetchURLs.map((fetchURL) =>
-          fetchFunc(fetchURL, loadOptions.requestInit, { isBinary: true })
-        );
-        const fetchStartFraction = 0;
-        const fetchEndFraction = 0.5;
-        const responses =
-          loadOptions.onProgress == null
-            ? await Promise.all(requests)
-            : await monitorPromisesProgress(
-                requests,
-                loadOptions.onProgress,
-                fetchStartFraction,
-                fetchEndFraction
-              );
-        const bufferPromises = responses.map((response) => response.arrayBuffer());
-        const bufferStartFraction = 0.5;
-        const bufferEndFraction = 1;
-        const buffers =
-          loadOptions.onProgress == null
-            ? await Promise.all(bufferPromises)
-            : await monitorPromisesProgress(
-                bufferPromises,
-                loadOptions.onProgress,
-                bufferStartFraction,
-                bufferEndFraction
-              );
-        return buffers;
-      }
-      /**
-       * Reads a weights manifest JSON configuration, fetches the weights and
-       * returns them as `Tensor`s.
-       *
-       * @param manifest The weights manifest JSON.
-       * @param filePathPrefix The path prefix for filenames given in the manifest.
-       *     Defaults to the empty string.
-       * @param weightNames The names of the weights to be fetched.
-       */
-      async function loadWeights(manifest, filePathPrefix = "", weightNames, requestInit) {
-        // TODO(nsthorat): Groups are currently fetched atomically. If you need a
-        // single weight from a group, the whole group will be fetched. At a future
-        // date, we should support fetching only the individual shards within a
-        // group that are needed to reconstruct the requested weight.
-        // TODO(cais): Use `decodeWeights` for implementation.
-        const fetchWeights = (fetchUrls) => loadWeightsAsArrayBuffer(fetchUrls, { requestInit });
-        const loadWeights = weightsLoaderFactory(fetchWeights);
-        return loadWeights(manifest, filePathPrefix, weightNames);
-      }
-      /**
-       * Creates a function, which reads a weights manifest JSON configuration,
-       * fetches the weight files using the specified function and returns them as
-       * `Tensor`s.
-       *
-       * ```js
-       * // example for creating a nodejs weight loader, which reads the weight files
-       * // from disk using fs.readFileSync
-       *
-       * import * as fs from 'fs'
-       *
-       * const fetchWeightsFromDisk = (filePaths: string[]) =>
-       *   filePaths.map(filePath => fs.readFileSync(filePath).buffer)
-       *
-       * const loadWeights = tf.io.weightsLoaderFactory(fetchWeightsFromDisk)
-       *
-       * const manifest = JSON.parse(
-       *   fs.readFileSync('./my_model-weights_manifest').toString()
-       * )
-       * const weightMap = await loadWeights(manifest, './')
-       * ```
-       * @param fetchWeightsFunction The function used for fetching the weight files.
-       * @returns Weight loading function.
-       */
-      function weightsLoaderFactory(fetchWeightsFunction) {
-        return async (manifest, filePathPrefix = "", weightNames) => {
-          // Collect all the groups, weights, and their relative offsets to be
-          // fetched.
-          const groupIndicesToFetchMap = manifest.map(() => false);
-          const groupWeightsToFetch = {};
-          const weightsFound = weightNames != null ? weightNames.map(() => false) : [];
-          const allManifestWeightNames = [];
-          manifest.forEach((manifestGroupConfig, groupIndex) => {
-            let groupOffset = 0;
-            manifestGroupConfig.weights.forEach((weightsEntry) => {
-              const rawDtype =
-                "quantization" in weightsEntry
-                  ? weightsEntry.quantization.dtype
-                  : weightsEntry.dtype;
-              const weightsBytes =
-                types["a" /* DTYPE_VALUE_SIZE_MAP */][rawDtype] *
-                util["sizeFromShape"](weightsEntry.shape);
-              const enqueueWeightsForFetchingFn = () => {
-                groupIndicesToFetchMap[groupIndex] = true;
-                if (groupWeightsToFetch[groupIndex] == null) {
-                  groupWeightsToFetch[groupIndex] = [];
-                }
-                groupWeightsToFetch[groupIndex].push({
-                  manifestEntry: weightsEntry,
-                  groupOffset,
-                  sizeBytes: weightsBytes,
-                });
-              };
-              if (weightNames != null) {
-                weightNames.forEach((weightName, weightIndex) => {
-                  if (weightName === weightsEntry.name) {
-                    enqueueWeightsForFetchingFn();
-                    weightsFound[weightIndex] = true;
-                  }
-                });
-              } else {
-                enqueueWeightsForFetchingFn();
-              }
-              allManifestWeightNames.push(weightsEntry.name);
-              groupOffset += weightsBytes;
-            });
-          });
-          if (!weightsFound.every((found) => found)) {
-            const weightsNotFound = weightNames.filter((_, i) => !weightsFound[i]);
-            throw new Error(
-              `Could not find weights in manifest with names: ` +
-                `${weightsNotFound.join(", ")}. \n` +
-                `Manifest JSON has weights with names: ` +
-                `${allManifestWeightNames.join(", ")}.`
-            );
-          }
-          // Convert the one-hot boolean groupId => shouldFetch map to a list of group
-          // IDs.
-          const groupIndicesToFetch = groupIndicesToFetchMap.reduce(
-            (accumulator, shouldFetch, i) => {
-              if (shouldFetch) {
-                accumulator.push(i);
-              }
-              return accumulator;
-            },
-            []
-          );
-          const fetchUrls = [];
-          groupIndicesToFetch.forEach((i) => {
-            manifest[i].paths.forEach((filepath) => {
-              const fetchUrl =
-                filePathPrefix + (!filePathPrefix.endsWith("/") ? "/" : "") + filepath;
-              fetchUrls.push(fetchUrl);
-            });
-          });
-          const buffers = await fetchWeightsFunction(fetchUrls);
-          const weightsTensorMap = {};
-          let bufferIndexOffset = 0;
-          groupIndicesToFetch.forEach((i) => {
-            const numBuffers = manifest[i].paths.length;
-            let groupBytes = 0;
-            for (let i = 0; i < numBuffers; i++) {
-              groupBytes += buffers[bufferIndexOffset + i].byteLength;
-            }
-            // Create a buffer for the whole group.
-            const groupBuffer = new ArrayBuffer(groupBytes);
-            const groupByteBuffer = new Uint8Array(groupBuffer);
-            let groupBufferOffset = 0;
-            for (let i = 0; i < numBuffers; i++) {
-              const buffer = new Uint8Array(buffers[bufferIndexOffset + i]);
-              groupByteBuffer.set(buffer, groupBufferOffset);
-              groupBufferOffset += buffer.byteLength;
-            }
-            const weightsEntries = groupWeightsToFetch[i];
-            weightsEntries.forEach((weightsEntry) => {
-              const byteBuffer = groupBuffer.slice(
-                weightsEntry.groupOffset,
-                weightsEntry.groupOffset + weightsEntry.sizeBytes
-              );
-              const nameToTensorMap = Object(io_utils["e" /* decodeWeights */])(byteBuffer, [
-                weightsEntry.manifestEntry,
-              ]);
-              for (const name in nameToTensorMap) {
-                weightsTensorMap[name] = nameToTensorMap[name];
-              }
-            });
-            bufferIndexOffset += numBuffers;
-          });
-          return weightsTensorMap;
-        };
-      }
-      //# sourceMappingURL=weights_loader.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/http.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * IOHandler implementations based on HTTP requests in the web browser.
-       *
-       * Uses [`fetch`](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API).
-       */
-
-      const OCTET_STREAM_MIME_TYPE = "application/octet-stream";
-      const JSON_TYPE = "application/json";
-      class http_HTTPRequest {
-        constructor(path, loadOptions) {
-          this.DEFAULT_METHOD = "POST";
-          if (loadOptions == null) {
-            loadOptions = {};
-          }
-          this.weightPathPrefix = loadOptions.weightPathPrefix;
-          this.onProgress = loadOptions.onProgress;
-          if (loadOptions.fetchFunc != null) {
-            Object(util["assert"])(
-              typeof loadOptions.fetchFunc === "function",
-              () =>
-                "Must pass a function that matches the signature of " +
-                "`fetch` (see " +
-                "https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"
-            );
-            this.fetch = loadOptions.fetchFunc;
-          } else {
-            this.fetch = Object(environment["c" /* env */])().platform.fetch;
-          }
-          Object(util["assert"])(
-            path != null && path.length > 0,
-            () => "URL path for http must not be null, undefined or " + "empty."
-          );
-          if (Array.isArray(path)) {
-            Object(util["assert"])(
-              path.length === 2,
-              () =>
-                "URL paths for http must have a length of 2, " +
-                `(actual length is ${path.length}).`
-            );
-          }
-          this.path = path;
-          if (loadOptions.requestInit != null && loadOptions.requestInit.body != null) {
-            throw new Error("requestInit is expected to have no pre-existing body, but has one.");
-          }
-          this.requestInit = loadOptions.requestInit || {};
-        }
-        async save(modelArtifacts) {
-          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
-            throw new Error(
-              "BrowserHTTPRequest.save() does not support saving model topology " +
-                "in binary formats yet."
-            );
-          }
-          const init = Object.assign({ method: this.DEFAULT_METHOD }, this.requestInit);
-          init.body = new FormData();
-          const weightsManifest = [
-            {
-              paths: ["./model.weights.bin"],
-              weights: modelArtifacts.weightSpecs,
-            },
-          ];
-          const modelTopologyAndWeightManifest = {
-            modelTopology: modelArtifacts.modelTopology,
-            format: modelArtifacts.format,
-            generatedBy: modelArtifacts.generatedBy,
-            convertedBy: modelArtifacts.convertedBy,
-            userDefinedMetadata: modelArtifacts.userDefinedMetadata,
-            weightsManifest,
-          };
-          init.body.append(
-            "model.json",
-            new Blob([JSON.stringify(modelTopologyAndWeightManifest)], { type: JSON_TYPE }),
-            "model.json"
-          );
-          if (modelArtifacts.weightData != null) {
-            init.body.append(
-              "model.weights.bin",
-              new Blob([modelArtifacts.weightData], { type: OCTET_STREAM_MIME_TYPE }),
-              "model.weights.bin"
-            );
-          }
-          const response = await this.fetch(this.path, init);
-          if (response.ok) {
-            return {
-              modelArtifactsInfo: Object(io_utils["g" /* getModelArtifactsInfoForJSON */])(
-                modelArtifacts
-              ),
-              responses: [response],
-            };
-          } else {
-            throw new Error(
-              `BrowserHTTPRequest.save() failed due to HTTP response status ` +
-                `${response.status}.`
-            );
-          }
-        }
-        /**
-         * Load model artifacts via HTTP request(s).
-         *
-         * See the documentation to `tf.io.http` for details on the saved
-         * artifacts.
-         *
-         * @returns The loaded model artifacts (if loading succeeds).
-         */
-        async load() {
-          const modelConfigRequest = await this.fetch(this.path, this.requestInit);
-          if (!modelConfigRequest.ok) {
-            throw new Error(
-              `Request to ${this.path} failed with status code ` +
-                `${modelConfigRequest.status}. Please verify this URL points to ` +
-                `the model JSON of the model to load.`
-            );
-          }
-          let modelConfig;
-          try {
-            modelConfig = await modelConfigRequest.json();
-          } catch (e) {
-            let message = `Failed to parse model JSON of response from ${this.path}.`;
-            // TODO(nsthorat): Remove this after some time when we're comfortable that
-            // .pb files are mostly gone.
-            if (this.path.endsWith(".pb")) {
-              message +=
-                " Your path contains a .pb file extension. " +
-                "Support for .pb models have been removed in TensorFlow.js 1.0 " +
-                "in favor of .json models. You can re-convert your Python " +
-                "TensorFlow model using the TensorFlow.js 1.0 conversion scripts " +
-                "or you can convert your.pb models with the 'pb2json'" +
-                "NPM script in the tensorflow/tfjs-converter repository.";
-            } else {
-              message +=
-                " Please make sure the server is serving valid " + "JSON for this request.";
-            }
-            throw new Error(message);
-          }
-          const modelTopology = modelConfig.modelTopology;
-          const weightsManifest = modelConfig.weightsManifest;
-          const generatedBy = modelConfig.generatedBy;
-          const convertedBy = modelConfig.convertedBy;
-          const format = modelConfig.format;
-          const userDefinedMetadata = modelConfig.userDefinedMetadata;
-          // We do not allow both modelTopology and weightsManifest to be missing.
-          if (modelTopology == null && weightsManifest == null) {
-            throw new Error(
-              `The JSON from HTTP path ${this.path} contains neither model ` +
-                `topology or manifest for weights.`
-            );
-          }
-          let weightSpecs;
-          let weightData;
-          if (weightsManifest != null) {
-            const results = await this.loadWeights(weightsManifest);
-            [weightSpecs, weightData] = results;
-          }
-          return {
-            modelTopology,
-            weightSpecs,
-            weightData,
-            userDefinedMetadata,
-            generatedBy,
-            convertedBy,
-            format,
-          };
-        }
-        async loadWeights(weightsManifest) {
-          const weightPath = Array.isArray(this.path) ? this.path[1] : this.path;
-          const [prefix, suffix] = parseUrl(weightPath);
-          const pathPrefix = this.weightPathPrefix || prefix;
-          const weightSpecs = [];
-          for (const entry of weightsManifest) {
-            weightSpecs.push(...entry.weights);
-          }
-          const fetchURLs = [];
-          weightsManifest.forEach((weightsGroup) => {
-            weightsGroup.paths.forEach((path) => {
-              fetchURLs.push(pathPrefix + path + suffix);
-            });
-          });
-          const buffers = await loadWeightsAsArrayBuffer(fetchURLs, {
-            requestInit: this.requestInit,
-            fetchFunc: this.fetch,
-            onProgress: this.onProgress,
-          });
-          return [weightSpecs, Object(io_utils["d" /* concatenateArrayBuffers */])(buffers)];
-        }
-      }
-      http_HTTPRequest.URL_SCHEME_REGEX = /^https?:\/\//;
-      /**
-       * Extract the prefix and suffix of the url, where the prefix is the path before
-       * the last file, and suffix is the search params after the last file.
-       * ```
-       * const url = 'http://tfhub.dev/model/1/tensorflowjs_model.pb?tfjs-format=file'
-       * [prefix, suffix] = parseUrl(url)
-       * // prefix = 'http://tfhub.dev/model/1/'
-       * // suffix = '?tfjs-format=file'
-       * ```
-       * @param url the model url to be parsed.
-       */
-      function parseUrl(url) {
-        const lastSlash = url.lastIndexOf("/");
-        const lastSearchParam = url.lastIndexOf("?");
-        const prefix = url.substring(0, lastSlash);
-        const suffix = lastSearchParam > lastSlash ? url.substring(lastSearchParam) : "";
-        return [prefix + "/", suffix];
-      }
-      function isHTTPScheme(url) {
-        return url.match(http_HTTPRequest.URL_SCHEME_REGEX) != null;
-      }
-      const httpRouter = (url, loadOptions) => {
-        if (
-          typeof fetch === "undefined" &&
-          (loadOptions == null || loadOptions.fetchFunc == null)
-        ) {
-          // `http` uses `fetch` or `node-fetch`, if one wants to use it in
-          // an environment that is not the browser or node they have to setup a
-          // global fetch polyfill.
-          return null;
-        } else {
-          let isHTTP = true;
-          if (Array.isArray(url)) {
-            isHTTP = url.every((urlItem) => isHTTPScheme(urlItem));
-          } else {
-            isHTTP = isHTTPScheme(url);
-          }
-          if (isHTTP) {
-            return http(url, loadOptions);
-          }
-        }
-        return null;
-      };
-      IORouterRegistry.registerSaveRouter(httpRouter);
-      IORouterRegistry.registerLoadRouter(httpRouter);
-      /**
-       * Creates an IOHandler subtype that sends model artifacts to HTTP server.
-       *
-       * An HTTP request of the `multipart/form-data` mime type will be sent to the
-       * `path` URL. The form data includes artifacts that represent the topology
-       * and/or weights of the model. In the case of Keras-style `tf.Model`, two
-       * blobs (files) exist in form-data:
-       *   - A JSON file consisting of `modelTopology` and `weightsManifest`.
-       *   - A binary weights file consisting of the concatenated weight values.
-       * These files are in the same format as the one generated by
-       * [tfjs_converter](https://js.tensorflow.org/tutorials/import-keras.html).
-       *
-       * The following code snippet exemplifies the client-side code that uses this
-       * function:
-       *
-       * ```js
-       * const model = tf.sequential();
-       * model.add(
-       *     tf.layers.dense({units: 1, inputShape: [100], activation: 'sigmoid'}));
-       *
-       * const saveResult = await model.save(tf.io.http(
-       *     'http://model-server:5000/upload', {requestInit: {method: 'PUT'}}));
-       * console.log(saveResult);
-       * ```
-       *
-       * If the default `POST` method is to be used, without any custom parameters
-       * such as headers, you can simply pass an HTTP or HTTPS URL to `model.save`:
-       *
-       * ```js
-       * const saveResult = await model.save('http://model-server:5000/upload');
-       * ```
-       *
-       * The following GitHub Gist
-       * https://gist.github.com/dsmilkov/1b6046fd6132d7408d5257b0976f7864
-       * implements a server based on [flask](https://github.com/pallets/flask) that
-       * can receive the request. Upon receiving the model artifacts via the requst,
-       * this particular server reconsistutes instances of [Keras
-       * Models](https://keras.io/models/model/) in memory.
-       *
-       *
-       * @param path A URL path to the model.
-       *   Can be an absolute HTTP path (e.g.,
-       *   'http://localhost:8000/model-upload)') or a relative path (e.g.,
-       *   './model-upload').
-       * @param requestInit Request configurations to be used when sending
-       *    HTTP request to server using `fetch`. It can contain fields such as
-       *    `method`, `credentials`, `headers`, `mode`, etc. See
-       *    https://developer.mozilla.org/en-US/docs/Web/API/Request/Request
-       *    for more information. `requestInit` must not have a body, because the
-       * body will be set by TensorFlow.js. File blobs representing the model
-       * topology (filename: 'model.json') and the weights of the model (filename:
-       * 'model.weights.bin') will be appended to the body. If `requestInit` has a
-       * `body`, an Error will be thrown.
-       * @param loadOptions Optional configuration for the loading. It includes the
-       *   following fields:
-       *   - weightPathPrefix Optional, this specifies the path prefix for weight
-       *     files, by default this is calculated from the path param.
-       *   - fetchFunc Optional, custom `fetch` function. E.g., in Node.js,
-       *     the `fetch` from node-fetch can be used here.
-       *   - onProgress Optional, progress callback function, fired periodically
-       *     before the load is completed.
-       * @returns An instance of `IOHandler`.
-       */
-      /**
-       * @doc {
-       *   heading: 'Models',
-       *   subheading: 'Loading',
-       *   namespace: 'io',
-       *   ignoreCI: true
-       * }
-       */
-      function http(path, loadOptions) {
-        return new http_HTTPRequest(path, loadOptions);
-      }
-      /**
-       * Deprecated. Use `tf.io.http`.
-       * @param path
-       * @param loadOptions
-       */
-      function browserHTTPRequest(path, loadOptions) {
-        return http(path, loadOptions);
-      }
-      //# sourceMappingURL=http.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/passthrough.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class PassthroughLoader {
-        constructor(modelArtifacts) {
-          this.modelArtifacts = modelArtifacts;
-        }
-        async load() {
-          return this.modelArtifacts;
-        }
-      }
-      class PassthroughSaver {
-        constructor(saveHandler) {
-          this.saveHandler = saveHandler;
-        }
-        async save(modelArtifacts) {
-          return this.saveHandler(modelArtifacts);
-        }
-      }
-      /**
-       * Creates an IOHandler that loads model artifacts from memory.
-       *
-       * When used in conjunction with `tf.loadLayersModel`, an instance of
-       * `tf.LayersModel` (Keras-style) can be constructed from the loaded artifacts.
-       *
-       * ```js
-       * const model = await tf.loadLayersModel(tf.io.fromMemory(
-       *     modelTopology, weightSpecs, weightData));
-       * ```
-       *
-       * @param modelArtifacts a object containing model topology (i.e., parsed from
-       *   the JSON format).
-       * @param weightSpecs An array of `WeightsManifestEntry` objects describing the
-       *   names, shapes, types, and quantization of the weight data.
-       * @param weightData A single `ArrayBuffer` containing the weight data,
-       *   concatenated in the order described by the weightSpecs.
-       * @param trainingConfig Model training configuration. Optional.
-       *
-       * @returns A passthrough `IOHandler` that simply loads the provided data.
-       */
-      function fromMemory(modelArtifacts, weightSpecs, weightData, trainingConfig) {
-        if (arguments.length === 1) {
-          const isModelArtifacts =
-            modelArtifacts.modelTopology != null || modelArtifacts.weightSpecs != null;
-          if (isModelArtifacts) {
-            return new PassthroughLoader(modelArtifacts);
-          } else {
-            // Legacy support: with only modelTopology.
-            // TODO(cais): Remove this deprecated API.
-            console.warn(
-              "Please call tf.io.fromMemory() with only one argument. " +
-                "The argument should be of type ModelArtifacts. " +
-                "The multi-argument signature of tf.io.fromMemory() has been " +
-                "deprecated and will be removed in a future release."
-            );
-            return new PassthroughLoader({ modelTopology: modelArtifacts });
-          }
-        } else {
-          // Legacy support.
-          // TODO(cais): Remove this deprecated API.
-          console.warn(
-            "Please call tf.io.fromMemory() with only one argument. " +
-              "The argument should be of type ModelArtifacts. " +
-              "The multi-argument signature of tf.io.fromMemory() has been " +
-              "deprecated and will be removed in a future release."
-          );
-          return new PassthroughLoader({
-            modelTopology: modelArtifacts,
-            weightSpecs,
-            weightData,
-            trainingConfig,
-          });
-        }
-      }
-      /**
-       * Creates an IOHandler that passes saved model artifacts to a callback.
-       *
-       * ```js
-       * function handleSave(artifacts) {
-       *   // ... do something with the artifacts ...
-       *   return {modelArtifactsInfo: {...}, ...};
-       * }
-       *
-       * const saveResult = model.save(tf.io.withSaveHandler(handleSave));
-       * ```
-       *
-       * @param saveHandler A function that accepts a `ModelArtifacts` and returns a
-       *     `SaveResult`.
-       */
-      function withSaveHandler(saveHandler) {
-        return new PassthroughSaver(saveHandler);
-      }
-      //# sourceMappingURL=passthrough.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/io.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // Importing local_storage and indexed_db is necessary for the routers to be
-      // registered.
-
-      //# sourceMappingURL=io.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/one_hot.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a one-hot `tf.Tensor`. The locations represented by `indices` take
-       * value `onValue` (defaults to 1), while all other locations take value
-       * `offValue` (defaults to 0). If `indices` is rank `R`, the output has rank
-       * `R+1` with the last axis of size `depth`.
-       *
-       * ```js
-       * tf.oneHot(tf.tensor1d([0, 1], 'int32'), 3).print();
-       * ```
-       *
-       * @param indices `tf.Tensor` of indices with dtype `int32`.
-       * @param depth The depth of the one hot dimension.
-       * @param onValue A number used to fill in the output when the index matches
-       * the location.
-       * @param offValue A number used to fill in the output when the index does
-       *     not match the location.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function oneHot_(indices, depth, onValue = 1, offValue = 0) {
-        if (depth < 2) {
-          throw new Error(`Error in oneHot: depth must be >=2, but it is ${depth}`);
-        }
-        let $indices = Object(tensor_util_env["a" /* convertToTensor */])(
-          indices,
-          "indices",
-          "oneHot",
-          "int32"
-        );
-        const outShape = [...$indices.shape, depth];
-        $indices = $indices.flatten();
-        const forward = (backend, save) => {
-          save([$indices]);
-          return reshape(backend.oneHot($indices, depth, onValue, offValue), outShape);
-        };
-        const inputs = { indices: $indices };
-        const attrs = { depth, onValue, offValue };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["cb" /* OneHot */],
-          attrs
-        );
-      }
-      const oneHot = Object(operation["a" /* op */])({ oneHot_ });
-      //# sourceMappingURL=one_hot.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/confusion_matrix.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the confusion matrix from true labels and predicted labels.
-       *
-       * ```js
-       * const labels = tf.tensor1d([0, 1, 2, 1, 0], 'int32');
-       * const predictions = tf.tensor1d([0, 2, 2, 1, 0], 'int32');
-       * const numClasses = 3;
-       * const out = tf.math.confusionMatrix(labels, predictions, numClasses);
-       * out.print();
-       * // Expected output matrix:
-       * // [[2, 0, 0],
-       * //  [0, 1, 1],
-       * //  [0, 0, 1]]
-       * ```
-       *
-       * @param labels The target labels, assumed to be 0-based integers
-       *   for the classes. The shape is `[numExamples]`, where
-       *   `numExamples` is the number of examples included.
-       * @param predictions The predicted classes, assumed to be
-       *   0-based integers for the classes. Must have the same shape as `labels`.
-       * @param numClasses Number of all classes, as an integer.
-       *   Its value must be larger than the largest element in `labels` and
-       *   `predictions`.
-       * @returns The confusion matrix as a int32-type 2D tensor. The value at
-       *   row `r` and column `c` is the number of times examples of actual class
-       *   `r` were predicted as class `c`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Evaluation'} */
-      function confusionMatrix_(labels, predictions, numClasses) {
-        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
-          labels,
-          "labels",
-          "confusionMatrix"
-        );
-        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
-          predictions,
-          "predictions",
-          "confusionMatrix"
-        );
-        util["assert"](
-          numClasses == null || (numClasses > 0 && Number.isInteger(numClasses)),
-          () => `If provided, numClasses must be a positive integer, ` + `but got ${numClasses}`
-        );
-        util["assert"](
-          $labels.rank === 1,
-          () => `Expected the rank of labels to be 1, but got ${$labels.rank}`
-        );
-        util["assert"](
-          $predictions.rank === 1,
-          () => `Expected the rank of predictions to be 1, ` + `but got ${$predictions.rank}`
-        );
-        util["assert"](
-          $labels.shape[0] === $predictions.shape[0],
-          () =>
-            `Mismatch in the number of examples: ` +
-            `${$labels.shape[0]} vs. ${$predictions.shape[0]}. ` +
-            `Labels and predictions should have the same number of elements.`
-        );
-        util["assert"](
-          numClasses > 0 && Number.isInteger(numClasses),
-          () => `numClasses is required to be a positive integer, but got ` + `${numClasses}`
-        );
-        // TODO(cais): In the future, if oneHot supports tensors inputs for
-        //   `numClasses`, `confusionMatrix` can make `numClasses` optional.
-        const oneHotLabels = oneHot($labels.asType("int32"), numClasses);
-        const oneHotPredictions = oneHot($predictions.asType("int32"), numClasses);
-        const oneHotLabelsT = oneHotLabels.transpose();
-        return oneHotLabelsT.matMul(oneHotPredictions).asType("int32");
-      }
-      const confusionMatrix = Object(operation["a" /* op */])({ confusionMatrix_ });
-      //# sourceMappingURL=confusion_matrix.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/math.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Exports under the tf.math.* namespace.
-       */
-
-      //# sourceMappingURL=math.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/browser.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      let fromPixels2DContext;
-      /**
-       * Creates a `tf.Tensor` from an image.
-       *
-       * ```js
-       * const image = new ImageData(1, 1);
-       * image.data[0] = 100;
-       * image.data[1] = 150;
-       * image.data[2] = 200;
-       * image.data[3] = 255;
-       *
-       * tf.browser.fromPixels(image).print();
-       * ```
-       *
-       * @param pixels The input image to construct the tensor from. The
-       * supported image types are all 4-channel. You can also pass in an image
-       * object with following attributes:
-       * `{data: Uint8Array; width: number; height: number}`
-       * @param numChannels The number of channels of the output tensor. A
-       * numChannels value less than 4 allows you to ignore channels. Defaults to
-       * 3 (ignores alpha channel of input image).
-       */
-      /** @doc {heading: 'Browser', namespace: 'browser', ignoreCI: true} */
-      function fromPixels_(pixels, numChannels = 3) {
-        // Sanity checks.
-        if (numChannels > 4) {
-          throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");
-        }
-        if (pixels == null) {
-          throw new Error("pixels passed to tf.browser.fromPixels() can not be null");
-        }
-        let isPixelData = false;
-        let isImageData = false;
-        let isVideo = false;
-        let isImage = false;
-        let isCanvasLike = false;
-        if (pixels.data instanceof Uint8Array) {
-          isPixelData = true;
-        } else if (typeof ImageData !== "undefined" && pixels instanceof ImageData) {
-          isImageData = true;
-        } else if (typeof HTMLVideoElement !== "undefined" && pixels instanceof HTMLVideoElement) {
-          isVideo = true;
-        } else if (typeof HTMLImageElement !== "undefined" && pixels instanceof HTMLImageElement) {
-          isImage = true;
-          // tslint:disable-next-line: no-any
-        } else if (pixels.getContext != null) {
-          isCanvasLike = true;
-        } else {
-          throw new Error(
-            "pixels passed to tf.browser.fromPixels() must be either an " +
-              `HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData ` +
-              `in browser, or OffscreenCanvas, ImageData in webworker` +
-              ` or {data: Uint32Array, width: number, height: number}, ` +
-              `but was ${pixels.constructor.name}`
-          );
-        }
-        if (isVideo) {
-          const HAVE_CURRENT_DATA_READY_STATE = 2;
-          if (isVideo && pixels.readyState < HAVE_CURRENT_DATA_READY_STATE) {
-            throw new Error(
-              "The video element has not loaded data yet. Please wait for " +
-                "`loadeddata` event on the <video> element."
-            );
-          }
-        }
-        // If the current backend has 'FromPixels' registered, it has a more
-        // efficient way of handling pixel uploads, so we call that.
-        const kernel = Object(kernel_registry["b" /* getKernel */])(
-          kernel_names["E" /* FromPixels */],
-          engine["a" /* ENGINE */].backendName
-        );
-        if (kernel != null) {
-          const inputs = { pixels };
-          const attrs = { numChannels };
-          return engine["a" /* ENGINE */].runKernel(
-            kernel_names["E" /* FromPixels */],
-            inputs,
-            attrs
-          );
-        }
-        const [width, height] = isVideo
-          ? [pixels.videoWidth, pixels.videoHeight]
-          : [pixels.width, pixels.height];
-        let vals;
-        if (isCanvasLike) {
-          vals =
-            // tslint:disable-next-line:no-any
-            pixels.getContext("2d").getImageData(0, 0, width, height).data;
-        } else if (isImageData || isPixelData) {
-          vals = pixels.data;
-        } else if (isImage || isVideo) {
-          if (fromPixels2DContext == null) {
-            fromPixels2DContext = document.createElement("canvas").getContext("2d");
-          }
-          fromPixels2DContext.canvas.width = width;
-          fromPixels2DContext.canvas.height = height;
-          fromPixels2DContext.drawImage(pixels, 0, 0, width, height);
-          vals = fromPixels2DContext.getImageData(0, 0, width, height).data;
-        }
-        let values;
-        if (numChannels === 4) {
-          values = new Int32Array(vals);
-        } else {
-          const numPixels = width * height;
-          values = new Int32Array(numPixels * numChannels);
-          for (let i = 0; i < numPixels; i++) {
-            for (let channel = 0; channel < numChannels; ++channel) {
-              values[i * numChannels + channel] = vals[i * 4 + channel];
-            }
-          }
-        }
-        const outShape = [height, width, numChannels];
-        return Object(tensor_ops["i" /* tensor3d */])(values, outShape, "int32");
-      }
-      /**
-       * Draws a `tf.Tensor` of pixel values to a byte array or optionally a
-       * canvas.
-       *
-       * When the dtype of the input is 'float32', we assume values in the range
-       * [0-1]. Otherwise, when input is 'int32', we assume values in the range
-       * [0-255].
-       *
-       * Returns a promise that resolves when the canvas has been drawn to.
-       *
-       * @param img A rank-2 or rank-3 tensor. If rank-2, draws grayscale. If
-       *     rank-3, must have depth of 1, 3 or 4. When depth of 1, draws
-       * grayscale. When depth of 3, we draw with the first three components of
-       * the depth dimension corresponding to r, g, b and alpha = 1. When depth of
-       * 4, all four components of the depth dimension correspond to r, g, b, a.
-       * @param canvas The canvas to draw to.
-       */
-      /** @doc {heading: 'Browser', namespace: 'browser'} */
-      async function toPixels(img, canvas) {
-        let $img = Object(tensor_util_env["a" /* convertToTensor */])(img, "img", "toPixels");
-        if (!(img instanceof dist_tensor["a" /* Tensor */])) {
-          // Assume int32 if user passed a native array.
-          const originalImgTensor = $img;
-          $img = originalImgTensor.toInt();
-          originalImgTensor.dispose();
-        }
-        if ($img.rank !== 2 && $img.rank !== 3) {
-          throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${$img.rank}.`);
-        }
-        const [height, width] = $img.shape.slice(0, 2);
-        const depth = $img.rank === 2 ? 1 : $img.shape[2];
-        if (depth > 4 || depth === 2) {
-          throw new Error(`toPixels only supports depth of size ` + `1, 3 or 4 but got ${depth}`);
-        }
-        const data = await $img.data();
-        const minTensor = $img.min();
-        const maxTensor = $img.max();
-        const vals = await Promise.all([minTensor.data(), maxTensor.data()]);
-        const minVals = vals[0];
-        const maxVals = vals[1];
-        const min = minVals[0];
-        const max = maxVals[0];
-        minTensor.dispose();
-        maxTensor.dispose();
-        if ($img.dtype === "float32") {
-          if (min < 0 || max > 1) {
-            throw new Error(
-              `Tensor values for a float32 Tensor must be in the ` +
-                `range [0 - 1] but got range [${min} - ${max}].`
-            );
-          }
-        } else if ($img.dtype === "int32") {
-          if (min < 0 || max > 255) {
-            throw new Error(
-              `Tensor values for a int32 Tensor must be in the ` +
-                `range [0 - 255] but got range [${min} - ${max}].`
-            );
-          }
-        } else {
-          throw new Error(
-            `Unsupported type for toPixels: ${$img.dtype}.` +
-              ` Please use float32 or int32 tensors.`
-          );
-        }
-        const multiplier = $img.dtype === "float32" ? 255 : 1;
-        const bytes = new Uint8ClampedArray(width * height * 4);
-        for (let i = 0; i < height * width; ++i) {
-          let r, g, b, a;
-          if (depth === 1) {
-            r = data[i] * multiplier;
-            g = data[i] * multiplier;
-            b = data[i] * multiplier;
-            a = 255;
-          } else if (depth === 3) {
-            r = data[i * 3] * multiplier;
-            g = data[i * 3 + 1] * multiplier;
-            b = data[i * 3 + 2] * multiplier;
-            a = 255;
-          } else if (depth === 4) {
-            r = data[i * 4] * multiplier;
-            g = data[i * 4 + 1] * multiplier;
-            b = data[i * 4 + 2] * multiplier;
-            a = data[i * 4 + 3] * multiplier;
-          }
-          const j = i * 4;
-          bytes[j + 0] = Math.round(r);
-          bytes[j + 1] = Math.round(g);
-          bytes[j + 2] = Math.round(b);
-          bytes[j + 3] = Math.round(a);
-        }
-        if (canvas != null) {
-          canvas.width = width;
-          canvas.height = height;
-          const ctx = canvas.getContext("2d");
-          const imageData = new ImageData(bytes, width, height);
-          ctx.putImageData(imageData, 0, 0);
-        }
-        if ($img !== img) {
-          $img.dispose();
-        }
-        return bytes;
-      }
-      const fromPixels = Object(operation["a" /* op */])({ fromPixels_ });
-      //# sourceMappingURL=browser.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd_util.js
-
-      /**
-       * Validate gather nd inputs.
-       *
-       * @param tensor The tensor contains the source values.
-       * @param indices The tensor contains the indices to slice the source.
-       *
-       * @returns [resultShape, numUpdates, sliceSize, strides]
-       */
-      function prepareAndValidate(tensor, indices) {
-        if (tensor.rank < 1) {
-          throw new Error(
-            "tf.gatherND() expects the input to be rank 1 or higher," +
-              ` but the rank was ${tensor.rank}.`
-          );
-        }
-        if (indices.rank < 1) {
-          throw new Error(
-            "tf.gatherND() expects the indices to be rank 1 or higher," +
-              ` but the rank was ${indices.rank}.`
-          );
-        }
-        if (indices.dtype !== "int32") {
-          throw new Error(
-            "tf.gatherND() expects the indices to be int32 type," +
-              ` but the dtype was ${indices.dtype}.`
-          );
-        }
-        if (indices.shape[indices.rank - 1] > tensor.rank) {
-          throw new Error(
-            "index innermost dimension length must be <= tensor rank; saw: " +
-              `${indices.shape[indices.rank - 1]} vs. ${tensor.rank}`
-          );
-        }
-        if (tensor.size === 0) {
-          throw new Error(
-            "Requested more than 0 entries, but input is empty." + ` Input shape: ${tensor.shape}.`
-          );
-        }
-        const indicesShape = indices.shape;
-        const sliceRank = indicesShape[indicesShape.length - 1];
-        // The result shape is
-        //   indices.shape[:-1] + params.shape[indices.shape[-1]:]
-        let nResult = 1;
-        for (let i = 0; i < indicesShape.length - 1; ++i) {
-          nResult *= indicesShape[i];
-        }
-        const inputShape = tensor.shape;
-        const resultShape = indicesShape.slice();
-        resultShape.pop();
-        let sliceSize = 1;
-        for (let i = sliceRank; i < tensor.rank; ++i) {
-          sliceSize *= inputShape[i];
-          resultShape.push(inputShape[i]);
-        }
-        const strides = [
-          ...Object(util["computeStrides"])(tensor.shape).map((stride) => stride / sliceSize),
-          1,
-        ].slice(0, sliceRank);
-        return [resultShape, nResult, sliceSize, strides];
-      }
-      //# sourceMappingURL=gather_nd_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd_util.js
-
-      /**
-       * Check whether updates.shape = indices.shape[:batchDim] +
-       * shape[sliceDim:]
-       *
-       * @param x The input tensor.
-       */
-      function validateUpdateShape(shape, indices, updates) {
-        const sliceDim = indices.rank > 1 ? indices.shape[indices.rank - 1] : 1;
-        const batchDim = indices.rank > 1 ? indices.rank - 1 : 1;
-        const shapeError =
-          "Must have updates.shape = indices.shape[:batchDim] + " +
-          `shape[sliceDim:], got updates.shape: ${updates.shape}` +
-          `, indices.shape: ${indices.shape}, shape: ${shape}` +
-          `, sliceDim: ${sliceDim}, and batchDim: ${batchDim}.`;
-        if (updates.rank < batchDim) {
-          throw new Error(shapeError + ` update.rank < ${batchDim}. `);
-        }
-        if (shape.length < sliceDim + (updates.rank - batchDim)) {
-          throw new Error(
-            shapeError + ` Output shape length < ${sliceDim + (updates.rank - batchDim)}`
-          );
-        }
-        if (updates.rank !== batchDim + shape.length - sliceDim) {
-          throw new Error(shapeError + ` update.rank != ${batchDim + shape.length - sliceDim}`);
-        }
-        for (let d = 0; d < batchDim; ++d) {
-          if (updates.shape[d] !== indices.shape[d]) {
-            throw new Error(
-              shapeError +
-                ` updates.shape[${d}] (${updates.shape[d]}) != indices.shape[${d}] (${indices.shape[d]}).`
-            );
-          }
-        }
-        for (let d = 0; d < updates.rank - batchDim; ++d) {
-          if (updates.shape[d + batchDim] !== shape[d + sliceDim]) {
-            throw new Error(
-              shapeError +
-                ` updates.shape[${d + batchDim}] (${updates.shape[d + batchDim]}) != shape[${
-                  d + batchDim
-                }] (${shape[d + batchDim]})`
-            );
-          }
-        }
-      }
-      /**
-       * Validate scatter nd inputs.
-       *
-       * @param update The tensor contains the update values.
-       * @param indices The tensor contains the indices for the update values.
-       * @param shape The shape of the output tensor.
-       */
-      function validateInput(updates, indices, shape) {
-        if (indices.rank < 1) {
-          throw new Error(
-            "tf.scatterND() expects the indices to be rank 1 or higher," +
-              ` but the rank was ${indices.rank}.`
-          );
-        }
-        if (updates.rank < 1) {
-          throw new Error(
-            "tf.scatterND() expects the updates to be rank 1 or higher," +
-              ` but the rank was ${updates.rank}.`
-          );
-        }
-        if (indices.dtype !== "int32") {
-          throw new Error(
-            `The dtype of 'indices' should be int32, but got dtype: ${indices.dtype}`
-          );
-        }
-        if (shape.length < 1) {
-          throw new Error(`Output rank must be greater or equal to 1, but got shape: ${shape}`);
-        }
-        if (shape.length === 0) {
-          if (indices.size === 0) {
-            throw new Error(`Indices specified for empty output. indices shape: ${indices.shape}`);
-          }
-          if (updates.size === 0) {
-            throw new Error(`Updates specified for empty output. updates shape: ${updates.shape}`);
-          }
-        }
-        validateUpdateShape(shape, indices, updates);
-      }
-      /**
-       * Calculate the shape information for the output.
-       *
-       * @param update The tensor contains the update values.
-       * @param indices The tensor contains the indices for the update values.
-       * @param shape The shape of the output tensor.
-       *
-       * @returns ScatterShapeInfo
-       */
-      function calculateShapes(updates, indices, shape) {
-        // Calculate the number of dimensions in indices
-        const indicesRank = indices.shape.length;
-        const sliceRank = indicesRank > 1 ? indices.shape[indicesRank - 1] : 1;
-        // Calculate the number of elements that make up each slice of our updated
-        // tensor. This allows us to work with flattened tensors and copy over whole
-        // slices at a time.
-        const totalNd = shape.length;
-        let sliceSize = 1;
-        for (let i = sliceRank; i < totalNd; ++i) {
-          sliceSize *= shape[i];
-        }
-        const safeSliceDim = sliceRank < 1 ? 1 : sliceRank;
-        const numUpdates = Object(util["sizeFromShape"])(indices.shape) / safeSliceDim;
-        const strides = [...Object(util["computeStrides"])(shape.slice(0, sliceRank)), 1];
-        const outputSize = Object(util["sizeFromShape"])(shape);
-        return { sliceRank, numUpdates, sliceSize, strides, outputSize };
-      }
-      //# sourceMappingURL=scatter_nd_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/serialization.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Serializable defines the serialization contract.
-       *
-       * TFJS requires serializable classes to return their className when asked
-       * to avoid issues with minification.
-       */
-      class Serializable {
-        /**
-         * Return the class name for this class to use in serialization contexts.
-         *
-         * Generally speaking this will be the same thing that constructor.name
-         * would have returned.  However, the class name needs to be robust
-         * against minification for serialization/deserialization to work properly.
-         *
-         * There's also places such as initializers.VarianceScaling, where
-         * implementation details between different languages led to different
-         * class hierarchies and a non-leaf node is used for serialization purposes.
-         */
-        getClassName() {
-          return this.constructor.className;
-        }
-        /**
-         * Creates an instance of T from a ConfigDict.
-         *
-         * This works for most descendants of serializable.  A few need to
-         * provide special handling.
-         * @param cls A Constructor for the class to instantiate.
-         * @param config The Configuration for the object.
-         */
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(config);
-        }
-      }
-      /**
-       * Maps string keys to class constructors.
-       *
-       * Used during (de)serialization from the cross-language JSON format, which
-       * requires the class name in the serialization format matches the class
-       * names as used in Python, should it exist.
-       */
-      class SerializationMap {
-        constructor() {
-          this.classNameMap = {};
-        }
-        /**
-         * Returns the singleton instance of the map.
-         */
-        static getMap() {
-          if (SerializationMap.instance == null) {
-            SerializationMap.instance = new SerializationMap();
-          }
-          return SerializationMap.instance;
-        }
-        /**
-         * Registers the class as serializable.
-         */
-        static register(cls) {
-          SerializationMap.getMap().classNameMap[cls.className] = [cls, cls.fromConfig];
-        }
-      }
-      /**
-       * Register a class with the serialization map of TensorFlow.js.
-       *
-       * This is often used for registering custom Layers, so they can be
-       * serialized and deserialized.
-       *
-       * Example:
-       *
-       * ```js
-       * class MyCustomLayer extends tf.layers.Layer {
-       *   static className = 'MyCustomLayer';
-       *
-       *   constructor(config) {
-       *     super(config);
-       *   }
-       * }
-       * tf.serialization.registerClass(MyCustomLayer);
-       * ```
-       *
-       * @param cls The class to be registered. It must have a public static member
-       *   called `className` defined and the value must be a non-empty string.
-       */
-      /** @doc {heading: 'Models', subheading: 'Serialization', ignoreCI: true} */
-      function registerClass(cls) {
-        Object(util["assert"])(
-          cls.className != null,
-          () => `Class being registered does not have the static className ` + `property defined.`
-        );
-        Object(util["assert"])(
-          typeof cls.className === "string",
-          () => `className is required to be a string, but got type ` + typeof cls.className
-        );
-        Object(util["assert"])(
-          cls.className.length > 0,
-          () =>
-            `Class being registered has an empty-string as its className, ` + `which is disallowed.`
-        );
-        SerializationMap.register(cls);
-      }
-      //# sourceMappingURL=serialization.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/test_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const TEST_EPSILON_FLOAT32 = 1e-3;
-      const TEST_EPSILON_FLOAT16 = 1e-1;
-      function expectArraysClose(actual, expected, epsilon) {
-        if (epsilon == null) {
-          epsilon = testEpsilon();
-        }
-        return expectArraysPredicate(actual, expected, (a, b) => areClose(a, b, epsilon));
-      }
-      function testEpsilon() {
-        return engine["a" /* ENGINE */].backend.floatPrecision() === 32
-          ? TEST_EPSILON_FLOAT32
-          : TEST_EPSILON_FLOAT16;
-      }
-      function expectArraysPredicate(actual, expected, predicate) {
-        let checkClassType = true;
-        if (Object(util["isTypedArray"])(actual) || Object(util["isTypedArray"])(expected)) {
-          checkClassType = false;
-        }
-        if (Object(util["isTypedArray"])(actual) && Object(util["isTypedArray"])(expected)) {
-          checkClassType = true;
-        }
-        if (checkClassType) {
-          const aType = actual.constructor.name;
-          const bType = expected.constructor.name;
-          if (aType !== bType) {
-            throw new Error(
-              `Arrays are of different type. Actual: ${aType}. ` + `Expected: ${bType}`
-            );
-          }
-        }
-        if (Array.isArray(actual) && Array.isArray(expected)) {
-          const actualShape = Object(tensor_util_env["c" /* inferShape */])(actual);
-          const expectedShape = Object(tensor_util_env["c" /* inferShape */])(expected);
-          if (!Object(util["arraysEqual"])(actualShape, expectedShape)) {
-            throw new Error(
-              `Arrays have different shapes. ` +
-                `Actual: [${actualShape}]. Expected: [${expectedShape}]`
-            );
-          }
-        }
-        const actualFlat = Object(util["isTypedArray"])(actual)
-          ? actual
-          : Object(util["flatten"])(actual);
-        const expectedFlat = Object(util["isTypedArray"])(expected)
-          ? expected
-          : Object(util["flatten"])(expected);
-        if (actualFlat.length !== expectedFlat.length) {
-          throw new Error(
-            `Arrays have different lengths actual: ${actualFlat.length} vs ` +
-              `expected: ${expectedFlat.length}.\n` +
-              `Actual:   ${actualFlat}.\n` +
-              `Expected: ${expectedFlat}.`
-          );
-        }
-        for (let i = 0; i < expectedFlat.length; ++i) {
-          const a = actualFlat[i];
-          const e = expectedFlat[i];
-          if (!predicate(a, e)) {
-            throw new Error(
-              `Arrays differ: actual[${i}] = ${a}, expected[${i}] = ${e}.\n` +
-                `Actual:   ${actualFlat}.\n` +
-                `Expected: ${expectedFlat}.`
-            );
-          }
-        }
-      }
-      function expectPromiseToFail(fn, done) {
-        fn().then(
-          () => done.fail(),
-          () => done()
-        );
-      }
-      function expectArraysEqual(actual, expected) {
-        const exp =
-          typeof expected === "string" ||
-          typeof expected === "number" ||
-          typeof expected === "boolean"
-            ? [expected]
-            : expected;
-        if (
-          Object(util["isString"])(actual) ||
-          Object(util["isString"])(actual[0]) ||
-          Object(util["isString"])(expected) ||
-          Object(util["isString"])(expected[0])
-        ) {
-          // tslint:disable-next-line: triple-equals
-          return expectArraysPredicate(actual, exp, (a, b) => a == b);
-        }
-        return expectArraysPredicate(actual, expected, (a, b) => areClose(a, b, 0));
-      }
-      function expectNumbersClose(a, e, epsilon) {
-        if (epsilon == null) {
-          epsilon = testEpsilon();
-        }
-        if (!areClose(a, e, epsilon)) {
-          throw new Error(`Numbers differ: actual === ${a}, expected === ${e}`);
-        }
-      }
-      function areClose(a, e, epsilon) {
-        if (!isFinite(a) && !isFinite(e)) {
-          return true;
-        }
-        if (isNaN(a) || isNaN(e) || Math.abs(a - e) > epsilon) {
-          return false;
-        }
-        return true;
-      }
-      function expectValuesInRange(actual, low, high) {
-        for (let i = 0; i < actual.length; i++) {
-          if (actual[i] < low || actual[i] > high) {
-            throw new Error(`Value out of range:${actual[i]} low: ${low}, high: ${high}`);
-          }
-        }
-      }
-      function expectArrayBuffersEqual(actual, expected) {
-        // Safari & Jasmine don't like comparing ArrayBuffers directly. Wrapping in
-        // a Float32Array solves this issue.
-        expect(new Float32Array(actual)).toEqual(new Float32Array(expected));
-      }
-      //# sourceMappingURL=test_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/version.js
-      /** @license See the LICENSE file. */
-      // This code is auto-generated, do not modify this file!
-      const version = "2.0.1";
-
-      //# sourceMappingURL=version.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/globals.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Enables production mode which disables correctness checks in favor of
-       * performance.
-       */
-      /** @doc {heading: 'Environment'} */
-      function enableProdMode() {
-        Object(environment["c" /* env */])().set("PROD", true);
-      }
-      /**
-       * Enables debug mode which will log information about all executed kernels:
-       * the elapsed time of the kernel execution, as well as the rank, shape, and
-       * size of the output tensor.
-       *
-       * Debug mode will significantly slow down your application as it will
-       * download the result of every operation to the CPU. This should not be used in
-       * production. Debug mode does not affect the timing information of the kernel
-       * execution as we do not measure download time in the kernel execution time.
-       *
-       * See also: `tf.profile`, `tf.memory`.
-       */
-      /** @doc {heading: 'Environment'} */
-      function enableDebugMode() {
-        Object(environment["c" /* env */])().set("DEBUG", true);
-      }
-      /** Globally disables deprecation warnings */
-      function disableDeprecationWarnings() {
-        Object(environment["c" /* env */])().set("DEPRECATION_WARNINGS_ENABLED", false);
-        console.warn(`TensorFlow.js deprecation warnings have been disabled.`);
-      }
-      /** Warn users about deprecated functionality. */
-      function deprecationWarn(msg) {
-        if (Object(environment["c" /* env */])().getBool("DEPRECATION_WARNINGS_ENABLED")) {
-          console.warn(
-            msg + " You can disable deprecation warnings with " + "tf.disableDeprecationWarnings()."
-          );
-        }
-      }
-      Object(dist_tensor["d" /* setDeprecationWarningFn */])(deprecationWarn);
-      /**
-       * Dispose all variables kept in backend engine.
-       */
-      /** @doc {heading: 'Environment'} */
-      function disposeVariables() {
-        engine["a" /* ENGINE */].disposeVariables();
-      }
-      /**
-       * It returns the global engine that keeps track of all tensors and backends.
-       */
-      /** @doc {heading: 'Environment'} */
-      function globals_engine() {
-        return engine["a" /* ENGINE */];
-      }
-      /**
-       * Returns memory info at the current time in the program. The result is an
-       * object with the following properties:
-       *
-       * - `numBytes`: Number of bytes allocated (undisposed) at this time.
-       * - `numTensors`: Number of unique tensors allocated.
-       * - `numDataBuffers`: Number of unique data buffers allocated
-       *   (undisposed) at this time, which is ≤ the number of tensors
-       *   (e.g. `a.reshape(newShape)` makes a new Tensor that shares the same
-       *   data buffer with `a`).
-       * - `unreliable`: True if the memory usage is unreliable. See `reasons` when
-       *    `unreliable` is true.
-       * - `reasons`: `string[]`, reasons why the memory is unreliable, present if
-       *    `unreliable` is true.
-       *
-       * WebGL Properties:
-       * - `numBytesInGPU`: Number of bytes allocated (undisposed) in the GPU only at
-       *     this time.
-       */
-      /** @doc {heading: 'Performance', subheading: 'Memory'} */
-      function memory() {
-        return engine["a" /* ENGINE */].memory();
-      }
-      /**
-       * Executes the provided function `f()` and returns a promise that resolves
-       * with information about the function's memory use:
-       * - `newBytes`: the number of new bytes allocated
-       * - `newTensors`: the number of new tensors created
-       * - `peakBytes`: the peak number of bytes allocated
-       * - `kernels`: an array of objects for each kernel involved that reports
-       * their input and output shapes, number of bytes used, and number of new
-       * tensors created.
-       *
-       * ```js
-       * const profile = await tf.profile(() => {
-       *   const x = tf.tensor1d([1, 2, 3]);
-       *   let x2 = x.square();
-       *   x2.dispose();
-       *   x2 = x.square();
-       *   x2.dispose();
-       *   return x;
-       * });
-       *
-       * console.log(`newBytes: ${profile.newBytes}`);
-       * console.log(`newTensors: ${profile.newTensors}`);
-       * console.log(`byte usage over all kernels: ${profile.kernels.map(k =>
-       * k.totalBytesSnapshot)}`);
-       * ```
-       *
-       */
-      /** @doc {heading: 'Performance', subheading: 'Profile'} */
-      function profile(f) {
-        return engine["a" /* ENGINE */].profile(f);
-      }
-      /**
-       * Executes the provided function `fn` and after it is executed, cleans up all
-       * intermediate tensors allocated by `fn` except those returned by `fn`.
-       * `fn` must not return a Promise (async functions not allowed). The returned
-       * result can be a complex object.
-       *
-       * Using this method helps avoid memory leaks. In general, wrap calls to
-       * operations in `tf.tidy` for automatic memory cleanup.
-       *
-       * NOTE: Variables do *not* get cleaned up when inside a tidy(). If you want to
-       * dispose variables, please use `tf.disposeVariables` or call dispose()
-       * directly on variables.
-       *
-       * ```js
-       * // y = 2 ^ 2 + 1
-       * const y = tf.tidy(() => {
-       *   // a, b, and one will be cleaned up when the tidy ends.
-       *   const one = tf.scalar(1);
-       *   const a = tf.scalar(2);
-       *   const b = a.square();
-       *
-       *   console.log('numTensors (in tidy): ' + tf.memory().numTensors);
-       *
-       *   // The value returned inside the tidy function will return
-       *   // through the tidy, in this case to the variable y.
-       *   return b.add(one);
-       * });
-       *
-       * console.log('numTensors (outside tidy): ' + tf.memory().numTensors);
-       * y.print();
-       * ```
-       *
-       * @param nameOrFn The name of the closure, or the function to execute.
-       *     If a name is provided, the 2nd argument should be the function.
-       *     If debug mode is on, the timing and the memory usage of the function
-       *     will be tracked and displayed on the console using the provided name.
-       * @param fn The function to execute.
-       */
-      /** @doc {heading: 'Performance', subheading: 'Memory'} */
-      function tidy(nameOrFn, fn) {
-        return engine["a" /* ENGINE */].tidy(nameOrFn, fn);
-      }
-      /**
-       * Disposes any `tf.Tensor`s found within the provided object.
-       *
-       * @param container an object that may be a `tf.Tensor` or may directly
-       *     contain `tf.Tensor`s, such as a `Tensor[]` or `{key: Tensor, ...}`. If
-       *     the object is not a `tf.Tensor` or does not contain `Tensors`, nothing
-       *     happens. In general it is safe to pass any object here, except that
-       *     `Promise`s are not supported.
-       */
-      /** @doc {heading: 'Performance', subheading: 'Memory'} */
-      function dispose(container) {
-        const tensors = Object(tensor_util["getTensorsInContainer"])(container);
-        tensors.forEach((tensor) => tensor.dispose());
-      }
-      /**
-       * Keeps a `tf.Tensor` generated inside a `tf.tidy` from being disposed
-       * automatically.
-       *
-       * ```js
-       * let b;
-       * const y = tf.tidy(() => {
-       *   const one = tf.scalar(1);
-       *   const a = tf.scalar(2);
-       *
-       *   // b will not be cleaned up by the tidy. a and one will be cleaned up
-       *   // when the tidy ends.
-       *   b = tf.keep(a.square());
-       *
-       *   console.log('numTensors (in tidy): ' + tf.memory().numTensors);
-       *
-       *   // The value returned inside the tidy function will return
-       *   // through the tidy, in this case to the variable y.
-       *   return b.add(one);
-       * });
-       *
-       * console.log('numTensors (outside tidy): ' + tf.memory().numTensors);
-       * console.log('y:');
-       * y.print();
-       * console.log('b:');
-       * b.print();
-       * ```
-       *
-       * @param result The tensor to keep from being disposed.
-       */
-      /** @doc {heading: 'Performance', subheading: 'Memory'} */
-      function keep(result) {
-        return engine["a" /* ENGINE */].keep(result);
-      }
-      /**
-       * Executes `f()` and returns a promise that resolves with timing
-       * information.
-       *
-       * The result is an object with the following properties:
-       *
-       * - `wallMs`: Wall execution time.
-       * - `kernelMs`: Kernel execution time, ignoring data transfer. If using the
-       * WebGL backend and the query timer extension is not available, this will
-       * return an error object.
-       * - On `WebGL` The following additional properties exist:
-       *   - `uploadWaitMs`: CPU blocking time on texture uploads.
-       *   - `downloadWaitMs`: CPU blocking time on texture downloads (readPixels).
-       *
-       * ```js
-       * const x = tf.randomNormal([20, 20]);
-       * const time = await tf.time(() => x.matMul(x));
-       *
-       * console.log(`kernelMs: ${time.kernelMs}, wallTimeMs: ${time.wallMs}`);
-       * ```
-       *
-       * @param f The function to execute and time.
-       */
-      /** @doc {heading: 'Performance', subheading: 'Timing'} */
-      function time(f) {
-        return engine["a" /* ENGINE */].time(f);
-      }
-      /**
-       * Sets the backend (cpu, webgl, wasm, etc) responsible for creating tensors and
-       * executing operations on those tensors. Returns a promise that resolves
-       * to a boolean if the backend initialization was successful.
-       *
-       * Note this disposes the current backend, if any, as well as any tensors
-       * associated with it. A new backend is initialized, even if it is of the
-       * same type as the previous one.
-       *
-       * @param backendName The name of the backend. Currently supports
-       *     `'webgl'|'cpu'` in the browser, `'tensorflow'` under node.js
-       *     (requires tfjs-node), and `'wasm'` (requires tfjs-backend-wasm).
-       */
-      /** @doc {heading: 'Backends'} */
-      function setBackend(backendName) {
-        return engine["a" /* ENGINE */].setBackend(backendName);
-      }
-      /**
-       * Returns a promise that resolves when the currently selected backend (or the
-       * highest priority one) has initialized. Await this promise when you are using
-       * a backend that has async initialization.
-       */
-      /** @doc {heading: 'Backends'} */
-      function ready() {
-        return engine["a" /* ENGINE */].ready();
-      }
-      /**
-       * Returns the current backend name (cpu, webgl, etc). The backend is
-       * responsible for creating tensors and executing operations on those tensors.
-       */
-      /** @doc {heading: 'Backends'} */
-      function getBackend() {
-        return engine["a" /* ENGINE */].backendName;
-      }
-      /**
-       * Removes a backend and the registered factory.
-       */
-      /** @doc {heading: 'Backends'} */
-      function removeBackend(name) {
-        engine["a" /* ENGINE */].removeBackend(name);
-      }
-      /**
-       * Finds the backend registered under the provided name. Returns null if the
-       * name is not in the registry, or the registration hasn't finished yet.
-       */
-      function findBackend(name) {
-        return engine["a" /* ENGINE */].findBackend(name);
-      }
-      /**
-       * Finds the backend factory registered under the provided name. Returns a
-       * function that produces a new backend when called. Returns null if the name
-       * is not in the registry.
-       */
-      function findBackendFactory(name) {
-        return engine["a" /* ENGINE */].findBackendFactory(name);
-      }
-      /**
-       * Registers a global backend. The registration should happen when importing
-       * a module file (e.g. when importing `backend_webgl.ts`), and is used for
-       * modular builds (e.g. custom tfjs bundle with only webgl support).
-       *
-       * @param factory The backend factory function. When called, it should
-       * return a backend instance, or a promise of an instance.
-       * @param priority The priority of the backend (higher = more important).
-       *     In case multiple backends are registered, the priority is used to find
-       *     the best backend. Defaults to 1.
-       * @return False if there is already a registered backend under this name, true
-       *     if not.
-       */
-      /** @doc {heading: 'Backends'} */
-      function registerBackend(name, factory, priority = 1) {
-        return engine["a" /* ENGINE */].registerBackend(name, factory, priority);
-      }
-      /**
-       * Gets the current backend. If no backends have been initialized, this will
-       * attempt to initialize the best backend. Will throw an error if the highest
-       * priority backend has async initialization, in which case, you should call
-       * 'await tf.ready()' before running other code.
-       */
-      /** @doc {heading: 'Backends'} */
-      function globals_backend() {
-        return engine["a" /* ENGINE */].backend;
-      }
-      /**
-       * Sets the global platform.
-       *
-       * @param platformName The name of this platform.
-       * @param platform A platform implementation.
-       */
-      function setPlatform(platformName, platform) {
-        Object(environment["c" /* env */])().setPlatform(platformName, platform);
-      }
-      //# sourceMappingURL=globals.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/add_n.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Adds a list of `tf.Tensor`s element-wise, each with the same shape and dtype.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2]);
-       * const b = tf.tensor1d([3, 4]);
-       * const c = tf.tensor1d([5, 6]);
-       *
-       * tf.addN([a, b, c]).print();
-       * ```
-       * @param tensors A list of tensors with the same shape and dtype.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function addN_(tensors) {
-        util["assert"](
-          Array.isArray(tensors),
-          () => "The argument passed to tf.addN() must be a list of tensors"
-        );
-        util["assert"](
-          tensors.length >= 1,
-          () => `Must pass at least one tensor to tf.addN(), but got ` + `${tensors.length}`
-        );
-        const $tensors = tensors.map((t, i) =>
-          Object(tensor_util_env["a" /* convertToTensor */])(t, `tensors${i}`, "addN")
-        );
-        const firstTensor = $tensors[0];
-        $tensors.forEach((t) => {
-          if (t.dtype !== firstTensor.dtype) {
-            throw new Error("All tensors passed to tf.addN() must have the same dtype");
-          }
-        });
-        $tensors.forEach((t) => {
-          if (!util["arraysEqual"](t.shape, firstTensor.shape)) {
-            throw new Error("All tensors passed to tf.addN() must have the same shape");
-          }
-        });
-        const forward = (backend, save) => {
-          const res = backend.addN($tensors);
-          save($tensors);
-          return res;
-        };
-        const inputs = $tensors;
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["b" /* AddN */]
-        );
-      }
-      const addN = Object(operation["a" /* op */])({ addN_ });
-      //# sourceMappingURL=add_n.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/atan2.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes arctangent of `tf.Tensor`s a / b element-wise: `atan2(a, b)`.
-       * Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1.0, 1.0, -1.0, .7]);
-       * const b = tf.tensor1d([2.0, 13.0, 3.5, .21]);
-       *
-       * tf.atan2(a, b).print()
-       * ```
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same dtype as `a`.
-       *
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function atan2_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "atan2");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "atan2");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        const forward = (backend, save) => {
-          const res = backend.atan2($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["c" /* Atan2 */]
-        );
-      }
-      const atan2 = Object(operation["a" /* op */])({ atan2_ });
-      //# sourceMappingURL=atan2.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the 2D average pooling of an image.
-       *
-       * @param x The input tensor, of rank 4 or rank 3 of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
-       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
-       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
-       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
-       *     `strides` is a single number, then `strideHeight == strideWidth`.
-       * @param pad The type of padding algorithm:
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *    - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *         https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       */
-      function avgPool_(x, filterSize, strides, pad, dimRoundingMode) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "avgPool", "float32");
-        const dilations = 1;
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in avgPool: Either strides or dilations must be 1. " +
-            `Got strides ${strides} and dilations '${dilations}'`
-        );
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
-        }
-        util["assert"](
-          x4D.rank === 4,
-          () => `Error in avgPool: x must be rank 4 but got rank ${x4D.rank}.`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in avgPool: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend, save) => {
-          const convInfo = computePool2DInfo(
-            x4D.shape,
-            filterSize,
-            strides,
-            1 /* dilations */,
-            pad,
-            dimRoundingMode
-          );
-          save([x4D]);
-          if (
-            convInfo.filterWidth === 1 &&
-            convInfo.filterHeight === 1 &&
-            util["arraysEqual"](convInfo.inShape, convInfo.outShape)
-          ) {
-            return x4D.clone();
-          }
-          return backend.avgPool(x4D, convInfo);
-        };
-        const inputs = { x: x4D };
-        const attrs = { filterSize, strides, pad, dimRoundingMode };
-        let res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["d" /* AvgPool */],
-          attrs
-        );
-        res = cast(res, $x.dtype);
-        if (reshapedTo4D) {
-          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
-        }
-        return res;
-      }
-      const avgPool = Object(operation["a" /* op */])({ avgPool_ });
-      //# sourceMappingURL=avg_pool.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_3d.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the 3D average pooling.
-       *
-       * ```js
-       * const x = tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]);
-       * const result = tf.avgPool3d(x, 2, 1, 'valid');
-       * result.print();
-       * ```
-       *
-       * @param x The input tensor, of rank 5 or rank 4 of shape
-       *     `[batch, depth, height, width, inChannels]`.
-       * @param filterSize The filter size:
-       *     `[filterDepth, filterHeight, filterWidth]`.
-       *     If `filterSize` is a single number,
-       *     then `filterDepth == filterHeight == filterWidth`.
-       * @param strides The strides of the pooling:
-       *     `[strideDepth, strideHeight, strideWidth]`.
-       *     If `strides` is a single number,
-       *     then `strideDepth == strideHeight == strideWidth`.
-       * @param pad The type of padding algorithm.
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1*1x1.
-       *    - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       * @param dataFormat An optional string from: "NDHWC", "NCDHW". Defaults to
-       *     "NDHWC". Specify the data format of the input and output data. With the
-       *     default format "NDHWC", the data is stored in the order of: [batch,
-       *     depth, height, width, channels]. Only "NDHWC" is currently supported.
-       * @param dilations Deprecated, this field will be gone in v3.0.0.
-       *     The dilation rates:
-       *     `[dilationDepth, dilationHeight, dilationWidth]`
-       *     in which we sample input values across the depth, height and width
-       *     dimensions in dilated pooling.
-       *     Defaults to `[1, 1, 1]`. If `dilations` is a single number,
-       *     then `dilationDepth == dilationHeight == dilationWidth`.
-       *     If it is greater than 1, then all values of `strides` must be 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function avgPool3d_(
-        x,
-        filterSize,
-        strides,
-        pad,
-        dimRoundingMode,
-        dataFormat = "NDHWC",
-        dilations
-      ) {
-        if (dilations == null) {
-          dilations = [1, 1, 1];
-        } else {
-          deprecationWarn("dilations is deprecated, this field will be gone in " + "v3.0.0.");
-        }
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(
-          x,
-          "x",
-          "avgPool3d",
-          "float32"
-        );
-        let x5D = $x;
-        let reshapedTo5D = false;
-        if ($x.rank === 4) {
-          reshapedTo5D = true;
-          x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);
-        }
-        util["assert"](
-          x5D.rank === 5,
-          () => `Error in avgPool3d: x must be rank 5 but got rank ${x5D.rank}.`
-        );
-        util["assert"](
-          dataFormat === "NDHWC",
-          () =>
-            `Error in avgPool3d: Only NDHWC is currently supported, ` +
-            `but got dataFormat of ${dataFormat}`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in avgPool3d: Either strides or dilations must be 1. " +
-            `Got strides ${strides} and dilations '${dilations}'`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in avgPool3d: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend, save) => {
-          if (dilations == null) {
-            dilations = [1, 1, 1];
-          }
-          const convInfo = computePool3DInfo(
-            x5D.shape,
-            filterSize,
-            strides,
-            dilations,
-            pad,
-            dimRoundingMode,
-            dataFormat
-          );
-          save([x5D]);
-          return backend.avgPool3d(x5D, convInfo);
-        };
-        const inputs = { x: x5D };
-        const attrs = { filterSize, strides, pad, dimRoundingMode, dataFormat, dilations };
-        let res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["e" /* AvgPool3D */],
-          attrs
-        );
-        res = cast(res, x5D.dtype);
-        if (reshapedTo5D) {
-          return res.as4D(res.shape[1], res.shape[2], res.shape[3], res.shape[4]);
-        }
-        return res;
-      }
-      const avgPool3d = Object(operation["a" /* op */])({ avgPool3d_ });
-      //# sourceMappingURL=avg_pool_3d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm_util.js
-      function xAs4D(x) {
-        let x4D;
-        if (x.rank === 0 || x.rank === 1) {
-          x4D = x.as4D(1, 1, 1, x.size);
-        } else if (x.rank === 2) {
-          x4D = x.as4D(1, 1, x.shape[0], x.shape[1]);
-        } else if (x.rank === 3) {
-          x4D = x.as4D(1, x.shape[0], x.shape[1], x.shape[2]);
-        } else {
-          x4D = x;
-        }
-        return x4D;
-      }
-      //# sourceMappingURL=batchnorm_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Batch normalization.
-       *
-       * As described in
-       * [http://arxiv.org/abs/1502.03167](http://arxiv.org/abs/1502.03167).
-       *
-       * Mean, variance, scale, and offset can be of two shapes:
-       *   - The same shape as the input.
-       *   - In the common case, the depth dimension is the last dimension of x, so
-       *     the values would be an `tf.Tensor1D` of shape [depth].
-       *
-       * Also available are stricter rank-specific methods with the same signature
-       * as this method that assert that parameters passed are of given rank
-       *   - `tf.batchNorm2d`
-       *   - `tf.batchNorm3d`
-       *   - `tf.batchNorm4d`
-       *
-       * @param x The input Tensor.
-       * @param mean A mean Tensor.
-       * @param variance A variance Tensor.
-       * @param offset An offset Tensor.
-       * @param scale A scale Tensor.
-       * @param varianceEpsilon A small float number to avoid dividing by 0.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
-      function batchNorm_(x, mean, variance, offset, scale, varianceEpsilon) {
-        if (varianceEpsilon == null) {
-          varianceEpsilon = 0.001;
-        }
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchNorm");
-        const $mean = Object(tensor_util_env["a" /* convertToTensor */])(mean, "mean", "batchNorm");
-        const $variance = Object(tensor_util_env["a" /* convertToTensor */])(
-          variance,
-          "variance",
-          "batchNorm"
-        );
-        let $scale;
-        if (scale != null) {
-          $scale = Object(tensor_util_env["a" /* convertToTensor */])(scale, "scale", "batchNorm");
-        }
-        let $offset;
-        if (offset != null) {
-          $offset = Object(tensor_util_env["a" /* convertToTensor */])(
-            offset,
-            "offset",
-            "batchNorm"
-          );
-        }
-        util["assert"](
-          $mean.rank === $variance.rank,
-          () => "Batch normalization gradient requires mean and variance to have " + "equal ranks."
-        );
-        util["assert"](
-          $offset == null || $mean.rank === $offset.rank,
-          () => "Batch normalization gradient requires mean and offset to have " + "equal ranks."
-        );
-        util["assert"](
-          $scale == null || $mean.rank === $scale.rank,
-          () => "Batch normalization gradient requires mean and scale to have " + "equal ranks."
-        );
-        const x4D = xAs4D($x);
-        const forward = (backend, save) => {
-          save([x4D, $mean, $variance, $scale]);
-          return backend.batchNorm(
-            x4D,
-            as1DOr4D($mean),
-            as1DOr4D($variance),
-            as1DOr4D($offset),
-            as1DOr4D($scale),
-            varianceEpsilon
-          );
-        };
-        const inputs = {
-          x: x4D,
-          scale: $scale,
-          offset: $offset,
-          mean: $mean,
-          variance: $variance,
-        };
-        const attrs = { varianceEpsilon };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["F" /* FusedBatchNorm */],
-          attrs
-        );
-        return reshape(res, $x.shape);
-      }
-      function as1DOr4D(x) {
-        if (x == null) {
-          return null;
-        }
-        if (x.rank === 0) {
-          return x.as1D();
-        } else if (x.rank === 1) {
-          return x;
-        } else if (x.rank === 2) {
-          return x.as4D(1, 1, x.shape[0], x.shape[1]);
-        } else if (x.rank === 3) {
-          return x.as4D(1, x.shape[0], x.shape[1], x.shape[2]);
-        }
-        return x;
-      }
-      const batchNorm = Object(operation["a" /* op */])({ batchNorm_ });
-      //# sourceMappingURL=batchnorm.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm2d.js
-
-      /**
-       * Batch normalization, strictly for 2D. For the more relaxed version, see
-       * `tf.batchNorm`.
-       *
-       * @param x The input Tensor.
-       * @param mean A mean Tensor.
-       * @param variance A variance Tensor.
-       * @param offset An offset Tensor.
-       * @param scale A scale Tensor.
-       * @param varianceEpsilon A small float number to avoid dividing by 0.
-       */
-      function batchNorm2d_(x, mean, variance, offset, scale, varianceEpsilon) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchNorm");
-        const $mean = Object(tensor_util_env["a" /* convertToTensor */])(mean, "mean", "batchNorm");
-        const $variance = Object(tensor_util_env["a" /* convertToTensor */])(
-          variance,
-          "variance",
-          "batchNorm"
-        );
-        let $scale;
-        if (scale != null) {
-          $scale = Object(tensor_util_env["a" /* convertToTensor */])(scale, "scale", "batchNorm");
-        }
-        let $offset;
-        if (offset != null) {
-          $offset = Object(tensor_util_env["a" /* convertToTensor */])(
-            offset,
-            "offset",
-            "batchNorm"
-          );
-        }
-        util["assert"](
-          $x.rank === 2,
-          () => `Error in batchNorm3D: x must be rank 3 but got rank ` + `${$x.rank}.`
-        );
-        util["assert"](
-          $mean.rank === 2 || $mean.rank === 1,
-          () =>
-            `Error in batchNorm2D: mean must be rank 2 or rank 1 but ` + `got rank ${$mean.rank}.`
-        );
-        util["assert"](
-          $variance.rank === 2 || $variance.rank === 1,
-          () =>
-            `Error in batchNorm2D: variance must be rank 2 or rank 1 ` +
-            `but got rank ${$variance.rank}.`
-        );
-        if ($scale != null) {
-          util["assert"](
-            $scale.rank === 2 || $scale.rank === 1,
-            () =>
-              `Error in batchNorm2D: scale must be rank 2 or rank 1 ` +
-              `but got rank ${$scale.rank}.`
-          );
-        }
-        if ($offset != null) {
-          util["assert"](
-            $offset.rank === 2 || $offset.rank === 1,
-            () =>
-              `Error in batchNorm2D: offset must be rank 2 or rank 1 ` +
-              `but got rank ${$offset.rank}.`
-          );
-        }
-        return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);
-      }
-      const batchNorm2d = Object(operation["a" /* op */])({ batchNorm2d_ });
-      //# sourceMappingURL=batchnorm2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm3d.js
-
-      /**
-       * Batch normalization, strictly for 3D. For the more relaxed version, see
-       * `tf.batchNorm`.
-       *
-       * @param x The input Tensor.
-       * @param mean A mean Tensor.
-       * @param variance A variance Tensor.
-       * @param offset An offset Tensor.
-       * @param scale A scale Tensor.
-       * @param varianceEpsilon A small float number to avoid dividing by 0.
-       */
-      function batchNorm3d_(x, mean, variance, offset, scale, varianceEpsilon) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchNorm");
-        const $mean = Object(tensor_util_env["a" /* convertToTensor */])(mean, "mean", "batchNorm");
-        const $variance = Object(tensor_util_env["a" /* convertToTensor */])(
-          variance,
-          "variance",
-          "batchNorm"
-        );
-        let $scale;
-        if (scale != null) {
-          $scale = Object(tensor_util_env["a" /* convertToTensor */])(scale, "scale", "batchNorm");
-        }
-        let $offset;
-        if (offset != null) {
-          $offset = Object(tensor_util_env["a" /* convertToTensor */])(
-            offset,
-            "offset",
-            "batchNorm"
-          );
-        }
-        util["assert"](
-          $x.rank === 3,
-          () => `Error in batchNorm3D: x must be rank 3 but got rank ` + `${$x.rank}.`
-        );
-        util["assert"](
-          $mean.rank === 3 || $mean.rank === 1,
-          () =>
-            `Error in batchNorm3D: mean must be rank 3 or rank 1 but ` + `got rank ${$mean.rank}.`
-        );
-        util["assert"](
-          $variance.rank === 3 || $variance.rank === 1,
-          () =>
-            `Error in batchNorm3D: variance must be rank 3 or rank 1 ` +
-            `but got rank ${$variance.rank}.`
-        );
-        if ($scale != null) {
-          util["assert"](
-            $scale.rank === 3 || $scale.rank === 1,
-            () =>
-              `Error in batchNorm3D: scale must be rank 3 or rank 1 ` +
-              `but got rank ${$scale.rank}.`
-          );
-        }
-        if ($offset != null) {
-          util["assert"](
-            $offset.rank === 3 || $offset.rank === 1,
-            () =>
-              `Error in batchNorm3D: offset must be rank 3 or rank 1 ` +
-              `but got rank ${$offset.rank}.`
-          );
-        }
-        return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);
-      }
-      const batchNorm3d = Object(operation["a" /* op */])({ batchNorm3d_ });
-      //# sourceMappingURL=batchnorm3d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm4d.js
-
-      /**
-       * Batch normalization, strictly for 4D. For the more relaxed version, see
-       * `tf.batchNorm`.
-       *
-       * @param x The input Tensor.
-       * @param mean A mean Tensor.
-       * @param variance A variance Tensor.
-       * @param offset An offset Tensor.
-       * @param scale A scale Tensor.
-       * @param varianceEpsilon A small float number to avoid dividing by 0.
-       */
-      function batchNorm4d_(x, mean, variance, offset, scale, varianceEpsilon) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchNorm");
-        const $mean = Object(tensor_util_env["a" /* convertToTensor */])(mean, "mean", "batchNorm");
-        const $variance = Object(tensor_util_env["a" /* convertToTensor */])(
-          variance,
-          "variance",
-          "batchNorm"
-        );
-        let $scale;
-        if (scale != null) {
-          $scale = Object(tensor_util_env["a" /* convertToTensor */])(scale, "scale", "batchNorm");
-        }
-        let $offset;
-        if (offset != null) {
-          $offset = Object(tensor_util_env["a" /* convertToTensor */])(
-            offset,
-            "offset",
-            "batchNorm"
-          );
-        }
-        util["assert"](
-          $x.rank === 4,
-          () => `Error in batchNorm4D: x must be rank 4 but got rank ` + `${$x.rank}.`
-        );
-        util["assert"](
-          $mean.rank === 4 || $mean.rank === 1,
-          () =>
-            `Error in batchNorm4D: mean must be rank 4 or rank 1 but ` + `got rank ${$mean.rank}.`
-        );
-        util["assert"](
-          $variance.rank === 4 || $variance.rank === 1,
-          () =>
-            `Error in batchNorm4D: variance must be rank 4 or rank 1 ` +
-            `but got rank ${$variance.rank}.`
-        );
-        if ($scale != null) {
-          util["assert"](
-            $scale.rank === 4 || $scale.rank === 1,
-            () =>
-              `Error in batchNorm4D: scale must be rank 4 or rank 1 ` +
-              `but got rank ${$scale.rank}.`
-          );
-        }
-        if ($offset != null) {
-          util["assert"](
-            $offset.rank === 4 || $offset.rank === 1,
-            () =>
-              `Error in batchNorm4D: offset must be rank 4 or rank 1 ` +
-              `but got rank ${$offset.rank}.`
-          );
-        }
-        return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);
-      }
-      const batchNorm4d = Object(operation["a" /* op */])({ batchNorm4d_ });
-      //# sourceMappingURL=batchnorm4d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/clone.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a new tensor with the same values and shape as the specified
-       * tensor.
-       *
-       * ```js
-       * const x = tf.tensor([1, 2]);
-       *
-       * x.clone().print();
-       * ```
-       *
-       * @param x The tensor to clone.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function clone_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "clone", null);
-        const forward = () =>
-          engine["a" /* ENGINE */].makeTensorFromDataId($x.dataId, $x.shape, $x.dtype);
-        // Note this op is called tf.identity in python. Hence the kernel name used
-        // here.
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          { x: $x },
-          null /* grad */,
-          kernel_names["J" /* Identity */]
-        );
-      }
-      const clone = Object(operation["a" /* op */])({ clone_ });
-      //# sourceMappingURL=clone.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_to.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Broadcast an array to a compatible shape NumPy-style.
-       *
-       * The tensor's shape is compared to the broadcast shape from end to beginning.
-       * Ones are prepended to the tensor's shape until is has the same length as
-       * the broadcast shape. If input.shape[i]==shape[i], the (i+1)-th axis is
-       * already broadcast-compatible. If input.shape[i]==1 and shape[i]==N, then
-       * the input tensor is tiled N times along that axis (using tf.tile).
-       *
-       * @param input The tensor that is to be broadcasted.
-       * @param shape The input is to be broadcast to this shape.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function broadcastTo_(x, shape) {
-        let input = Object(tensor_util_env["a" /* convertToTensor */])(x, "broadcastTo", "x");
-        const xShape = input.shape;
-        if (shape.some((d) => !(d > 0) || d % 1 !== 0)) {
-          throw new Error(`broadcastTo(): Invalid broadcast shape [${shape}].`);
-        }
-        if (shape.length < input.rank) {
-          throw new Error(
-            `broadcastTo(): shape.length=${shape.length} < input.rank=${input.rank}.`
-          );
-        }
-        if (shape.length > input.rank) {
-          const newShape = input.shape.slice();
-          while (newShape.length < shape.length) {
-            newShape.unshift(1);
-          }
-          input = reshape(input, newShape);
-        }
-        const inputShape = input.shape;
-        const reps = Array.from(shape);
-        for (let i = shape.length - 1; i >= 0; i--) {
-          if (inputShape[i] === shape[i]) {
-            reps[i] = 1;
-          } else if (input.shape[i] !== 1) {
-            throw new Error(`broadcastTo(): [${xShape}] cannot be broadcast to [${shape}].`);
-          }
-        }
-        const axes = reps.map((n, i) => (n > 1 ? i : -1)).filter((i) => i >= 0);
-        if (axes.length === 0) {
-          return clone(input);
-        }
-        const forward = (backend) => backend.tile(input, reps);
-        const inputs = { x: input };
-        const attrs = { shape, inputShape };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["j" /* BroadcastTo */],
-          attrs
-        );
-      }
-      const broadcastTo = Object(operation["a" /* op */])({ broadcastTo_ });
-      //# sourceMappingURL=broadcast_to.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/complex.js
-      var complex = __webpack_require__(18);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_1d.js
-
-      /**
-       * Concatenates a list of`tf.Tensor1D`s along an axis. See `concat` for details.
-       *
-       * For example, if:
-       * A: shape(3) = |r1, g1, b1|
-       * B: shape(2) = |r2, g2|
-       * C = tf.concat1d([A, B]) == |r1, g1, b1, r2, g2|
-       *
-       * @param tensors A list of`tf.Tensor`s to concatenate.
-       * @return The concatenated array.
-       */
-      function concat1d_(tensors) {
-        return concat(tensors, 0 /* axis */);
-      }
-      const concat1d = Object(operation["a" /* op */])({ concat1d_ });
-      //# sourceMappingURL=concat_1d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_2d.js
-
-      /**
-       * Concatenates a list of`tf.Tensor2D`s along an axis. See `concat` for details.
-       *
-       * For example, if:
-       * A: shape(2, 3) = | r1, g1, b1 |
-       *                  | r2, g2, b2 |
-       *
-       * B: shape(2, 3) = | r3, g3, b3 |
-       *                  | r4, g4, b4 |
-       *
-       * C = tf.concat2d([A, B], axis)
-       *
-       * if axis = 0:
-       * C: shape(4, 3) = | r1, g1, b1 |
-       *                  | r2, g2, b2 |
-       *                  | r3, g3, b3 |
-       *                  | r4, g4, b4 |
-       *
-       * if axis = 1:
-       * C = shape(2, 6) = | r1, g1, b1, r3, g3, b3 |
-       *                   | r2, g2, b2, r4, g4, b4 |
-       *
-       *
-       * @param tensors A list of `tf.Tensor`s to concatenate.
-       * @param axis The axis to concatenate along.
-       * @return The concatenated array.
-       */
-      function concat2d_(tensors, axis) {
-        return concat(tensors, axis);
-      }
-      const concat2d = Object(operation["a" /* op */])({ concat2d_ });
-      //# sourceMappingURL=concat_2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_3d.js
-
-      /**
-       * Concatenates a list of `tf.Tensor3D`s along an axis.
-       * See `concat` for details.
-       *
-       * For example, if:
-       * A: shape(2, 1, 3) = | r1, g1, b1 |
-       *                     | r2, g2, b2 |
-       *
-       * B: shape(2, 1, 3) = | r3, g3, b3 |
-       *                     | r4, g4, b4 |
-       *
-       * C = tf.concat3d([A, B], axis)
-       *
-       * if axis = 0:
-       * C: shape(4, 1, 3) = | r1, g1, b1 |
-       *                     | r2, g2, b2 |
-       *                     | r3, g3, b3 |
-       *                     | r4, g4, b4 |
-       *
-       * if axis = 1:
-       * C: shape(2, 2, 3) = | r1, g1, b1, r3, g3, b3 |
-       *                     | r2, g2, b2, r4, g4, b4 |
-       *
-       * if axis = 2:
-       * C = shape(2, 1, 6) = | r1, g1, b1, r3, g3, b3 |
-       *                      | r2, g2, b2, r4, g4, b4 |
-       *
-       * @param tensors A list of`tf.Tensor`s to concatenate.
-       * @param axis The axis to concate along.
-       * @return The concatenated array.
-       */
-      function concat3d_(tensors, axis) {
-        return concat(tensors, axis);
-      }
-      const concat3d = Object(operation["a" /* op */])({ concat3d_ });
-      //# sourceMappingURL=concat_3d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_4d.js
-
-      /**
-       * Concatenates a list of `tf.Tensor4D`s along an axis.
-       * See `concat` for details.
-       *
-       * @param tensors A list of `tf.Tensor`s to concatenate.
-       * @param axis The axis to concate along.
-       * @return The concatenated array.
-       */
-      function concat4d_(tensors, axis) {
-        return concat(tensors, axis);
-      }
-      const concat4d = Object(operation["a" /* op */])({ concat4d_ });
-      //# sourceMappingURL=concat_4d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv1d.js
-
-      /**
-       * Computes a 1D convolution over the input x.
-       *
-       * @param x The input tensor, of rank 3 or rank 2, of shape
-       *     `[batch, width, inChannels]`. If rank 2, batch of 1 is assumed.
-       * @param filter The filter, rank 3, of shape
-       *     `[filterWidth, inDepth, outDepth]`.
-       * @param stride The number of entries by which the filter is moved right at
-       *     each step.
-       * @param pad The type of padding algorithm.
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *   - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dataFormat An optional string from "NWC", "NCW". Defaults to "NWC",
-       *     the data is stored in the order of [batch, in_width, in_channels]. Only
-       *     "NWC" is currently supported.
-       * @param dilation The dilation rate in which we sample input values in
-       *     atrous convolution. Defaults to `1`. If it is greater than 1, then
-       *     stride must be `1`.
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function conv1d_(x, filter, stride, pad, dataFormat = "NWC", dilation = 1, dimRoundingMode) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv1d");
-        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
-          filter,
-          "filter",
-          "conv1d"
-        );
-        let x3D = $x;
-        let reshapedTo3D = false;
-        if ($x.rank === 2) {
-          reshapedTo3D = true;
-          x3D = reshape($x, [1, $x.shape[0], $x.shape[1]]);
-        }
-        util["assert"](
-          x3D.rank === 3,
-          () => `Error in conv1d: input must be rank 3, but got rank ${x3D.rank}.`
-        );
-        util["assert"](
-          $filter.rank === 3,
-          () => `Error in conv1d: filter must be rank 3, but got rank ` + `${$filter.rank}.`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in conv1d: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        util["assert"](
-          x3D.shape[2] === $filter.shape[1],
-          () =>
-            `Error in conv1d: depth of input (${x3D.shape[2]}) must match ` +
-            `input depth for filter ${$filter.shape[1]}.`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(stride, dilation),
-          () =>
-            "Error in conv1D: Either stride or dilation must be 1. " +
-            `Got stride ${stride} and dilation '${dilation}'`
-        );
-        util["assert"](
-          dataFormat === "NWC",
-          () =>
-            `Error in conv1d: got dataFormat of ${dataFormat} but only NWC is currently supported.`
-        );
-        const filter4D = reshape($filter, [
-          1,
-          $filter.shape[0],
-          $filter.shape[1],
-          $filter.shape[2],
-        ]);
-        const input4D = reshape(x3D, [x3D.shape[0], 1, x3D.shape[1], x3D.shape[2]]);
-        const strides = [1, stride];
-        const dilations = [1, dilation];
-        const conv2dDataFormat = "NHWC";
-        const res = conv2d(
-          input4D,
-          filter4D,
-          strides,
-          pad,
-          conv2dDataFormat,
-          dilations,
-          dimRoundingMode
-        );
-        if (reshapedTo3D) {
-          return reshape(res, [res.shape[2], res.shape[3]]);
-        }
-        return reshape(res, [res.shape[0], res.shape[2], res.shape[3]]);
-      }
-      const conv1d = Object(operation["a" /* op */])({ conv1d_ });
-      //# sourceMappingURL=conv1d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_transpose.js
-
-      /**
-       * Computes the transposed 2D convolution of an image, also known as a
-       * deconvolution.
-       *
-       * @param x The input image, of rank 4 or rank 3, of shape
-       *   `[batch, height, width, inDepth]`. If rank 3, batch of 1 is assumed.
-       * @param filter The filter, rank 4, of shape
-       *     `[filterHeight, filterWidth, outDepth, inDepth]`.
-       *     `inDepth` must match `inDepth` in `x`.
-       * @param outputShape Output shape, of rank 4 or rank 3:
-       *     `[batch, height, width, outDepth]`. If rank 3, batch of 1 is assumed.
-       * @param strides The strides of the original convolution:
-       *     `[strideHeight, strideWidth]`.
-       * @param pad  The type of padding algorithm used in the non-transpose version
-       *    of the op.
-       * @param dimRoundingMode The rounding mode used when computing output
-       *    dimensions if pad is a number. If none is provided, it will not round
-       *    and error if the output is of fractional size.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function conv2dTranspose_(x, filter, outputShape, strides, pad, dimRoundingMode) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv2dTranspose");
-        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
-          filter,
-          "filter",
-          "conv2dTranspose"
-        );
-        return conv2DBackpropInput(outputShape, $x, $filter, strides, pad, "NHWC", dimRoundingMode);
-      }
-      const conv2dTranspose = Object(operation["a" /* op */])({ conv2dTranspose_ });
-      //# sourceMappingURL=conv2d_transpose.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv3d.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes a 3D convolution over the input x.
-       *
-       * @param x The input tensor, of rank 5 or rank 4, of shape
-       *     `[batch, depth, height, width, channels]`. If rank 4,
-       * batch of 1 is assumed.
-       * @param filter The filter, rank 5, of shape
-       *     `[filterDepth, filterHeight, filterWidth, inChannels, outChannels]`.
-       *      inChannels must match between input and filter.
-       * @param strides The strides of the convolution: `[strideDepth, strideHeight,
-       * strideWidth]`.
-       * @param pad The type of padding algorithm.
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *   - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dataFormat: An optional string from: "NDHWC", "NCDHW". Defaults to
-       *     "NDHWC". Specify the data format of the input and output data. With the
-       *     default format "NDHWC", the data is stored in the order of: [batch,
-       *     depth, height, width, channels]. Only "NDHWC" is currently supported.
-       * @param dilations The dilation rates: `[dilationDepth, dilationHeight,
-       *     dilationWidth]` in which we sample input values across the height
-       *     and width dimensions in atrous convolution. Defaults to `[1, 1, 1]`.
-       *     If `dilations` is a single number, then
-       *     `dilationDepth == dilationHeight == dilationWidth`. If it is greater
-       *     than 1, then all values of `strides` must be 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function conv3d_(x, filter, strides, pad, dataFormat = "NDHWC", dilations = [1, 1, 1]) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv3d");
-        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
-          filter,
-          "filter",
-          "conv3d"
-        );
-        let x5D = $x;
-        let reshapedTo5D = false;
-        if ($x.rank === 4) {
-          reshapedTo5D = true;
-          x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);
-        }
-        util["assert"](
-          x5D.rank === 5,
-          () => `Error in conv3d: input must be rank 5, but got rank ${x5D.rank}.`
-        );
-        util["assert"](
-          $filter.rank === 5,
-          () => `Error in conv3d: filter must be rank 5, but got rank ` + `${$filter.rank}.`
-        );
-        util["assert"](
-          x5D.shape[4] === $filter.shape[3],
-          () =>
-            `Error in conv3d: depth of input (${x5D.shape[4]}) must match ` +
-            `input depth for filter ${$filter.shape[3]}.`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in conv3D: Either strides or dilations must be 1. " +
-            `Got strides ${strides} and dilations '${dilations}'`
-        );
-        util["assert"](
-          dataFormat === "NDHWC",
-          () =>
-            `Error in conv3d: got dataFormat of ${dataFormat} but only NDHWC is currently supported.`
-        );
-        const forward = (backend, save) => {
-          const convInfo = computeConv3DInfo(x5D.shape, $filter.shape, strides, dilations, pad);
-          const res = backend.conv3d(x5D, $filter, convInfo);
-          save([x5D, $filter]);
-          return res;
-        };
-        const inputs = { x: x5D, filter: $filter };
-        const attrs = { strides, pad, dataFormat, dilations };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["p" /* Conv3D */],
-          attrs
-        );
-        if (reshapedTo5D) {
-          return res.as4D(res.shape[1], res.shape[2], res.shape[3], res.shape[4]);
-        }
-        return res;
-      }
-      const conv3d = Object(operation["a" /* op */])({ conv3d_ });
-      //# sourceMappingURL=conv3d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_transpose.js
-
-      /**
-       * Computes the transposed 3D convolution of a volume, also known as a
-       * deconvolution.
-       *
-       * @param x The input image, of rank 5 or rank 4, of shape
-       *   `[batch, depth, height, width, inDepth]`. If rank 4, batch of 1 is assumed.
-       * @param filter The filter, rank 4, of shape
-       *     `[depth, filterHeight, filterWidth, outDepth, inDepth]`.
-       *     `inDepth` must match `inDepth` in `x`.
-       * @param outputShape Output shape, of rank 5 or rank 4:
-       *     `[batch, depth, height, width, outDepth]`. If rank 3, batch of 1 is
-       *    assumed.
-       * @param strides The strides of the original convolution:
-       *     `[strideDepth, strideHeight, strideWidth]`.
-       * @param pad  The type of padding algorithm used in the non-transpose version
-       *    of the op.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function conv3dTranspose_(x, filter, outputShape, strides, pad) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv3dTranspose");
-        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
-          filter,
-          "filter",
-          "conv3dTranspose"
-        );
-        return conv3DBackpropInput(outputShape, $x, $filter, strides, pad);
-      }
-      const conv3dTranspose = Object(operation["a" /* op */])({ conv3dTranspose_ });
-      //# sourceMappingURL=conv3d_transpose.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/depth_to_space.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Rearranges data from depth into blocks of spatial data. More specifically,
-       * this op outputs a copy of the input tensor where values from the `depth`
-       * dimension are moved in spatial blocks to the `height` and `width` dimensions.
-       * The attr `blockSize` indicates the input block size and how the data is
-       * moved.
-       *
-       *  - Chunks of data of size `blockSize * blockSize` from depth are rearranged
-       * into non-overlapping blocks of size `blockSize x blockSize`
-       *
-       *  - The width the output tensor is `inputWidth * blockSize`, whereas the
-       * height is `inputHeight * blockSize`
-       *
-       *  - The Y, X coordinates within each block of the output image are determined
-       * by the high order component of the input channel index
-       *
-       *  - The depth of the input tensor must be divisible by `blockSize *
-       * blockSize`
-       *
-       * The `dataFormat` attr specifies the layout of the input and output tensors
-       * with the following options: "NHWC": [ `batch, height, width, channels` ]
-       * "NCHW": [ `batch, channels, height, width` ]
-       *
-       * ```js
-       * const x = tf.tensor4d([1, 2, 3, 4], [1, 1, 1, 4]);
-       * const blockSize = 2;
-       * const dataFormat = "NHWC";
-       *
-       * tf.depthToSpace(x, blockSize, dataFormat).print();
-       * ```
-       *
-       * @param x The input tensor of rank 4
-       * @param blockSIze  An `int` that is `>= 2`. The size of the spatial block
-       * @param dataFormat An optional string from: "NHWC", "NCHW". Defaults to "NHWC"
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
-      function depthToSpace_(x, blockSize, dataFormat = "NHWC") {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "depthToSpace");
-        const inputHeight = dataFormat === "NHWC" ? $x.shape[1] : $x.shape[2];
-        const inputWidth = dataFormat === "NHWC" ? $x.shape[2] : $x.shape[3];
-        const inputDepth = dataFormat === "NHWC" ? $x.shape[3] : $x.shape[1];
-        util["assert"](
-          inputHeight * blockSize >= 0,
-          () => `Negative dimension size caused by overflow when multiplying
-    ${inputHeight} and ${blockSize}  for depthToSpace with input shape
-    ${$x.shape}`
-        );
-        util["assert"](
-          inputWidth * blockSize >= 0,
-          () => `Negative dimension size caused by overflow when multiplying
-    ${inputWidth} and ${blockSize} for depthToSpace with input shape
-        ${$x.shape}`
-        );
-        util["assert"](
-          inputDepth % (blockSize * blockSize) === 0,
-          () =>
-            `Dimension size must be evenly divisible by ${
-              blockSize * blockSize
-            } but is ${inputDepth} for depthToSpace with input shape ${$x.shape}`
-        );
-        const forward = (backend) => backend.depthToSpace($x, blockSize, dataFormat);
-        const inputs = { x: $x };
-        const attrs = { blockSize, dataFormat };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["t" /* DepthToSpace */],
-          attrs
-        );
-      }
-      const depthToSpace = Object(operation["a" /* op */])({ depthToSpace_ });
-      //# sourceMappingURL=depth_to_space.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Depthwise 2D convolution.
-       *
-       * Given a 4D `input` array and a `filter` array of shape
-       * `[filterHeight, filterWidth, inChannels, channelMultiplier]` containing
-       * `inChannels` convolutional filters of depth 1, this op applies a
-       * different filter to each input channel (expanding from 1 channel to
-       * `channelMultiplier` channels for each), then concatenates the results
-       * together. The output has `inChannels * channelMultiplier` channels.
-       *
-       * See
-       * [https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d](
-       *     https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d)
-       * for more details.
-       *
-       * @param x The input tensor, of rank 4 or rank 3, of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
-       * assumed.
-       * @param filter The filter tensor, rank 4, of shape
-       *     `[filterHeight, filterWidth, inChannels, channelMultiplier]`.
-       * @param strides The strides of the convolution: `[strideHeight,
-       * strideWidth]`. If strides is a single number, then `strideHeight ==
-       * strideWidth`.
-       * @param pad The type of padding algorithm.
-       *   - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *   - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *   - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
-       *     in which we sample input values across the height and width dimensions
-       *     in atrous convolution. Defaults to `[1, 1]`. If `rate` is a single
-       *     number, then `dilationHeight == dilationWidth`. If it is greater than
-       *     1, then all values of `strides` must be 1.
-       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
-       *     "NHWC". Specify the data format of the input and output data. With the
-       *     default format "NHWC", the data is stored in the order of: [batch,
-       *     height, width, channels]. Only "NHWC" is currently supported.
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function depthwiseConv2d_(
-        x,
-        filter,
-        strides,
-        pad,
-        dataFormat = "NHWC",
-        dilations = [1, 1],
-        dimRoundingMode
-      ) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "depthwiseConv2d");
-        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
-          filter,
-          "filter",
-          "depthwiseConv2d"
-        );
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
-        }
-        util["assert"](
-          x4D.rank === 4,
-          () => `Error in depthwiseConv2d: input must be rank 4, but got ` + `rank ${x4D.rank}.`
-        );
-        util["assert"](
-          $filter.rank === 4,
-          () =>
-            `Error in depthwiseConv2d: filter must be rank 4, but got rank ` + `${$filter.rank}.`
-        );
-        util["assert"](
-          x4D.shape[3] === $filter.shape[2],
-          () =>
-            `Error in depthwiseConv2d: number of input channels ` +
-            `(${x4D.shape[3]}) must match the inChannels dimension in ` +
-            `filter ${$filter.shape[2]}.`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in depthwiseConv2d: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend, save) => {
-          if (dilations == null) {
-            dilations = [1, 1];
-          }
-          util["assert"](
-            eitherStridesOrDilationsAreOne(strides, dilations),
-            () =>
-              "Error in depthwiseConv2d: Either strides or dilations must be " +
-              `1. Got strides ${strides} and dilations '${dilations}'`
-          );
-          const convInfo = computeConv2DInfo(
-            x4D.shape,
-            $filter.shape,
-            strides,
-            dilations,
-            pad,
-            dimRoundingMode,
-            true /* depthwise */
-          );
-          const res = backend.depthwiseConv2D(x4D, $filter, convInfo);
-          save([x4D, $filter]);
-          return res;
-        };
-        const inputs = { x: x4D, filter: $filter };
-        const attrs = { strides, pad, dataFormat, dilations, dimRoundingMode };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["u" /* DepthwiseConv2dNative */],
-          attrs
-        );
-        if (reshapedTo4D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
-        }
-        return res;
-      }
-      const depthwiseConv2d = Object(operation["a" /* op */])({ depthwiseConv2d_ });
-      //# sourceMappingURL=depthwise_conv2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/diag.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns a diagonal tensor with a given diagonal values.
-       *
-       * Given a diagonal, this operation returns a tensor with the diagonal and
-       * everything else padded with zeros.
-       *
-       * Assume the input has dimensions `[D1,..., Dk]`, then the output is a tensor
-       * of rank 2k with dimensions `[D1,..., Dk, D1,..., Dk]`
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       *
-       * tf.diag(x).print()
-       * ```
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4, 5, 6, 6, 8], [4, 2])
-       *
-       * tf.diag(x).print()
-       * ```
-       * @param x The input tensor.
-       */
-      function diag_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "diag").flatten();
-        const forward = (backend) => {
-          const result = backend.diag($x);
-          const outShape = [...x.shape, ...x.shape];
-          return reshape(result, outShape);
-        };
-        const inputs = { x: $x };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["x" /* Diag */]
-        );
-      }
-      const diag = Object(operation["a" /* op */])({ diag_ });
-      //# sourceMappingURL=diag.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/div_no_nan.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Divides two `tf.Tensor`s element-wise, A / B. Supports broadcasting. Return 0
-       * if denominator is 0.
-       *
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 4, 9, 16]);
-       * const b = tf.tensor1d([1, 2, 3, 4]);
-       * const c = tf.tensor1d([0, 0, 0, 0]);
-       *
-       * a.divNoNan(b).print();  // or tf.divNoNan(a, b)
-       * a.divNoNan(c).print();  // or tf.divNoNan(a, c)
-       * ```
-       *
-       * ```js
-       * // Broadcast div a with b.
-       * const a = tf.tensor1d([2, 4, 6, 8]);
-       * const b = tf.scalar(2);
-       * const c = tf.scalar(0);
-       *
-       * a.divNoNan(b).print();  // or tf.divNoNan(a, b)
-       * a.divNoNan(c).print();  // or tf.divNoNan(a, c)
-       * ```
-       *
-       * @param a The first tensor as the numerator.
-       * @param b The second tensor as the denominator. Must have the same dtype as
-       * `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function divNoNan_(a, b) {
-        // TODO: Make this into its own kernel.
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "div");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "div");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        const divResult = div($a, $b);
-        const zeros = Object(tensor_ops["o" /* zerosLike */])(divResult);
-        const bEqualsZero = $b.equal(zeros);
-        return where(bEqualsZero, zeros, divResult);
-      }
-      const divNoNan = Object(operation["a" /* op */])({ divNoNan_ });
-      //# sourceMappingURL=div_no_nan.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/dot.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the dot product of two matrices and/or vectors, `t1` and `t2`.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2]);
-       * const b = tf.tensor2d([[1, 2], [3, 4]]);
-       * const c = tf.tensor2d([[1, 2, 3], [4, 5, 6]]);
-       *
-       * a.dot(b).print();  // or tf.dot(a, b)
-       * b.dot(a).print();
-       * b.dot(c).print();
-       * ```
-       * @param t1 The first tensor in the dot operation.
-       * @param t2 The second tensor in the dot operation.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
-      function dot_(t1, t2) {
-        const $t1 = Object(tensor_util_env["a" /* convertToTensor */])(t1, "t1", "dot");
-        const $t2 = Object(tensor_util_env["a" /* convertToTensor */])(t2, "t2", "dot");
-        util["assert"](
-          ($t1.rank === 1 || $t1.rank === 2) && ($t2.rank === 1 || $t2.rank === 2),
-          () =>
-            `Error in dot: inputs must all be rank 1 or 2, but got ranks ` +
-            `${$t1.rank} and ${$t2.rank}.`
-        );
-        const t1Inner = $t1.rank === 1 ? $t1.size : $t1.shape[1];
-        const t2Inner = $t2.rank === 1 ? $t2.size : $t2.shape[0];
-        util["assert"](
-          t1Inner === t2Inner,
-          () =>
-            `Error in dot: inner dimensions of inputs must match, but got ` +
-            `${t1Inner} and ${t2Inner}.`
-        );
-        if ($t1.rank === 1 && $t2.rank === 1) {
-          const t12D = reshape($t1, [1, -1]);
-          const t22D = reshape($t2, [-1, 1]);
-          const t1t2 = matMul(t12D, t22D);
-          return reshape(t1t2, []);
-        } else if ($t1.rank === 1 && $t2.rank === 2) {
-          const t12D = reshape($t1, [1, -1]);
-          const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);
-          const t1t2 = matMul(t12D, t22D);
-          return reshape(t1t2, [t1t2.size]);
-        } else if ($t1.rank === 2 && $t2.rank === 1) {
-          const t22D = reshape($t2, [-1, 1]);
-          const t1t2 = matMul($t1, t22D);
-          return reshape(t1t2, [t1t2.size]);
-        } else {
-          const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);
-          const t1t2 = matMul($t1, t22D);
-          return t1t2;
-        }
-      }
-      const dot = Object(operation["a" /* op */])({ dot_ });
-      //# sourceMappingURL=dot.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/elu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes exponential linear element-wise: `x > 0 ? e ^ x - 1 : 0`.
-       *
-       * ```js
-       * const x = tf.tensor1d([-1, 1, -3, 2]);
-       *
-       * x.elu().print();  // or tf.elu(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function elu_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "elu");
-        const forward = (backend, save) => {
-          const y = backend.elu($x);
-          save([y]);
-          return y;
-        };
-        const inputs = { x: $x };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["z" /* Elu */]
-        );
-      }
-      const elu = Object(operation["a" /* op */])({ elu_ });
-      //# sourceMappingURL=elu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/equal.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the truth value of (a == b) element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       * const b = tf.tensor1d([2, 2, 2]);
-       *
-       * a.equal(b).print();
-       * ```
-       *
-       * @param a The first input tensor.
-       * @param b The second input tensor. Must have the same dtype as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function equal_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "equal");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "equal");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend) => backend.equal($a, $b);
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null,
-          kernel_names["B" /* Equal */]
-        );
-      }
-      const equal = Object(operation["a" /* op */])({ equal_ });
-      //# sourceMappingURL=equal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/eye.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Create an identity matrix.
-       *
-       * @param numRows Number of rows.
-       * @param numColumns Number of columns. Defaults to `numRows`.
-       * @param batchShape If provided, will add the batch shape to the beginning
-       *   of the shape of the returned `tf.Tensor` by repeating the identity
-       *   matrix.
-       * @param dtype Data type.
-       * @returns Identity matrix of the specified size and data type, possibly
-       *   with batch repetition if `batchShape` is specified.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function eye_(numRows, numColumns, batchShape, dtype = "float32") {
-        if (numColumns == null) {
-          numColumns = numRows;
-        }
-        const buff = array_ops_buffer([numRows, numColumns], dtype);
-        const n = numRows <= numColumns ? numRows : numColumns;
-        for (let i = 0; i < n; ++i) {
-          buff.set(1, i, i);
-        }
-        const out = buff.toTensor().as2D(numRows, numColumns);
-        if (batchShape == null) {
-          return out;
-        } else {
-          if (batchShape.length === 1) {
-            return tile(expandDims(out, 0), [batchShape[0], 1, 1]);
-          } else if (batchShape.length === 2) {
-            return tile(expandDims(expandDims(out, 0), 0), [batchShape[0], batchShape[1], 1, 1]);
-          } else if (batchShape.length === 3) {
-            return tile(expandDims(expandDims(expandDims(out, 0), 0), 0), [
-              batchShape[0],
-              batchShape[1],
-              batchShape[2],
-              1,
-              1,
-            ]);
-          } else {
-            throw new Error(
-              `eye() currently supports only 1D and 2D ` +
-                // tslint:disable-next-line:no-any
-                `batchShapes, but received ${batchShape.length}D.`
-            );
-          }
-        }
-      }
-      const eye = Object(operation["a" /* op */])({ eye_ });
-      //# sourceMappingURL=eye.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/fill.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a `tf.Tensor` filled with a scalar value.
-       *
-       * ```js
-       * tf.fill([2, 2], 4).print();
-       * ```
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param value The scalar value to fill the tensor with.
-       * @param dtype The type of an element in the resulting tensor. Defaults to
-       * 'float'.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function fill(shape, value, dtype) {
-        const attrs = { shape, value, dtype };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.fill(shape, value, dtype),
-          {},
-          null,
-          kernel_names["C" /* Fill */],
-          attrs
-        );
-      }
-
-      //# sourceMappingURL=fill.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/imag.js
-      var imag = __webpack_require__(25);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/maximum.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the max of a and b (`a > b ? a : b`) element-wise.
-       * Supports broadcasting.
-       *
-       * We also expose `tf.maximumStrict` which has the same signature as this op and
-       * asserts that `a` and `b` are the same shape (does not broadcast).
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 4, 3, 16]);
-       * const b = tf.tensor1d([1, 2, 9, 4]);
-       *
-       * a.maximum(b).print();  // or tf.maximum(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast maximum a with b.
-       * const a = tf.tensor1d([2, 4, 6, 8]);
-       * const b = tf.scalar(5);
-       *
-       * a.maximum(b).print();  // or tf.maximum(a, b)
-       * ```
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same type as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function maximum_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "maximum");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "maximum");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        if ($a.dtype === "bool") {
-          $a = cast($a, "int32");
-          $b = cast($b, "int32");
-        }
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend, save) => {
-          const res = backend.maximum($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["V" /* Maximum */]
-        );
-      }
-      const maximum = Object(operation["a" /* op */])({ maximum_ });
-      //# sourceMappingURL=maximum.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/leaky_relu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes leaky rectified linear element-wise.
-       *
-       * See
-       * [http://web.stanford.edu/~awni/papers/relu_hybrid_icml2013_final.pdf](
-       *     http://web.stanford.edu/~awni/papers/relu_hybrid_icml2013_final.pdf)
-       *
-       * ```js
-       * const x = tf.tensor1d([-1, 2, -3, 4]);
-       *
-       * x.leakyRelu(0.1).print();  // or tf.leakyRelu(x, 0.1)
-       * ```
-       * @param x The input tensor.
-       * @param alpha The scaling factor for negative values, defaults to 0.2.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function leakyRelu_(x, alpha = 0.2) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "leakyRelu");
-        return maximum(mul(Object(tensor_ops["e" /* scalar */])(alpha), $x), $x);
-      }
-      const leakyRelu = Object(operation["a" /* op */])({ leakyRelu_ });
-      //# sourceMappingURL=leaky_relu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/local_response_normalization.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Normalizes the activation of a local neighborhood across or within
-       * channels.
-       *
-       * @param x The input tensor. The 4-D input tensor is treated as a 3-D array
-       *     of 1D vectors (along the last dimension), and each vector is
-       *     normalized independently.
-       * @param depthRadius The number of adjacent channels in the 1D normalization
-       *     window.
-       * @param bias A constant bias term for the basis.
-       * @param alpha A scale factor, usually positive.
-       * @param beta An exponent.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
-      function localResponseNormalization_(x, depthRadius = 5, bias = 1, alpha = 1, beta = 0.5) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(
-          x,
-          "x",
-          "localResponseNormalization"
-        );
-        util["assert"](
-          $x.rank === 4 || $x.rank === 3,
-          () => `Error in localResponseNormalization: x must be rank 3 or 4 but got
-               rank ${$x.rank}.`
-        );
-        util["assert"](
-          util["isInt"](depthRadius),
-          () =>
-            `Error in localResponseNormalization: depthRadius must be an ` +
-            `integer but got depthRadius ${depthRadius}.`
-        );
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
-        }
-        const forward = (backend, save) => {
-          const y = backend.localResponseNormalization4D(x4D, depthRadius, bias, alpha, beta);
-          save([x4D, y]);
-          return y;
-        };
-        const inputs = { x: x4D };
-        const attrs = { depthRadius, bias, alpha, beta };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["L" /* LRN */],
-          attrs
-        );
-        if (reshapedTo4D) {
-          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
-        } else {
-          return res;
-        }
-      }
-      const localResponseNormalization = Object(operation["a" /* op */])({
-        localResponseNormalization_,
-      });
-      //# sourceMappingURL=local_response_normalization.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the maximum of elements across dimensions of a `tf.Tensor`.
-       *
-       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
-       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
-       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
-       * length 1. If `axes` has no entries, all dimensions are reduced, and an
-       * `tf.Tensor` with a single element is returned.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3]);
-       *
-       * x.max().print();  // or tf.max(x)
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * const axis = 1;
-       * x.max(axis).print();  // or tf.max(x, axis)
-       * ```
-       *
-       * @param x The input tensor.
-       * @param axis The dimension(s) to reduce. By default it reduces
-       *     all dimensions.
-       * @param keepDims If true, retains reduced dimensions with size 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
-      function max_(x, axis = null, keepDims = false) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "max");
-        const forward = (backend, save) => {
-          const origAxes = util["parseAxisParam"](axis, $x.shape);
-          let axes = origAxes;
-          const permutedAxes = getAxesPermutation(axes, $x.rank);
-          let maxInput = $x;
-          if (permutedAxes != null) {
-            maxInput = transpose($x, permutedAxes);
-            axes = getInnerMostAxes(axes.length, maxInput.rank);
-          }
-          const y = backend.max(maxInput, axes);
-          save([$x, y]);
-          if (permutedAxes != null) {
-            backend.disposeData(maxInput.dataId);
-          }
-          return y;
-        };
-        const inputs = { x: $x };
-        const attrs = { reductionIndices: axis, keepDims };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["P" /* Max */],
-          attrs
-        );
-        if (keepDims) {
-          return reshape(
-            res,
-            expandShapeToKeepDim(res.shape, util["parseAxisParam"](axis, $x.shape))
-          );
-        }
-        return res;
-      }
-      const max_max = Object(operation["a" /* op */])({ max_ });
-      //# sourceMappingURL=max.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the 2D max pooling of an image.
-       *
-       * @param x The input tensor, of rank 4 or rank 3 of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
-       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
-       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
-       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
-       *     `strides` is a single number, then `strideHeight == strideWidth`.
-       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
-       *     in which we sample input values across the height and width dimensions
-       *     in dilated pooling. Defaults to `[1, 1]`. If `dilations` is a single
-       *     number, then `dilationHeight == dilationWidth`. If it is greater than
-       *     1, then all values of `strides` must be 1.
-       * @param pad The type of padding algorithm.
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *    - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       */
-      function maxPool_(x, filterSize, strides, pad, dimRoundingMode) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "maxPool");
-        const dilations = 1;
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
-        }
-        util["assert"](
-          x4D.rank === 4,
-          () => `Error in maxPool: input must be rank 4 but got rank ${x4D.rank}.`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in maxPool: Either strides or dilations must be 1. " +
-            `Got strides ${strides} and dilations '${dilations}'`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in maxPool: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend, save) => {
-          const convInfo = computePool2DInfo(
-            x4D.shape,
-            filterSize,
-            strides,
-            1 /* dilations */,
-            pad,
-            dimRoundingMode
-          );
-          let y;
-          if (
-            convInfo.filterWidth === 1 &&
-            convInfo.filterHeight === 1 &&
-            util["arraysEqual"](convInfo.inShape, convInfo.outShape)
-          ) {
-            y = x4D.clone();
-          } else {
-            y = backend.maxPool(x4D, convInfo);
-          }
-          save([x4D, y]);
-          return y;
-        };
-        const inputs = { x: x4D };
-        const attrs = { filterSize, strides, pad, dimRoundingMode };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["Q" /* MaxPool */],
-          attrs
-        );
-        if (reshapedTo4D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
-        }
-        return res;
-      }
-      const maxPool = Object(operation["a" /* op */])({ maxPool_ });
-      //# sourceMappingURL=max_pool.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_3d.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the 3D max pooling.
-       *
-       * ```js
-       * const x = tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]);
-       * const result = tf.maxPool3d(x, 2, 1, 'valid');
-       * result.print();
-       * ```
-       *
-       * @param x The input tensor, of rank 5 or rank 4 of shape
-       *     `[batch, depth, height, width, inChannels]`.
-       * @param filterSize The filter size:
-       *     `[filterDepth, filterHeight, filterWidth]`.
-       *     If `filterSize` is a single number,
-       *     then `filterDepth == filterHeight == filterWidth`.
-       * @param strides The strides of the pooling:
-       *     `[strideDepth, strideHeight, strideWidth]`.
-       *     If `strides` is a single number,
-       *     then `strideDepth == strideHeight == strideWidth`.
-       * @param pad The type of padding algorithm.
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1*1x1.
-       *    - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       * @param dataFormat An optional string from: "NDHWC", "NCDHW". Defaults to
-       *     "NDHWC". Specify the data format of the input and output data. With the
-       *     default format "NDHWC", the data is stored in the order of: [batch,
-       *     depth, height, width, channels]. Only "NDHWC" is currently supported.
-       * @param dilations Deprecated, this field will be gone in v3.0.0.
-       *     The dilation rates: `[dilationDepth, dilationHeight, dilationWidth]`
-       *     in which we sample input values across the depth, height and width
-       *     dimensions in dilated pooling.
-       *     Defaults to `[1, 1, 1]`. If `dilations` is a single number,
-       *     then `dilationDepth == dilationHeight == dilationWidth`.
-       *     If it is greater than 1, then all values of `strides` must be 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function maxPool3d_(
-        x,
-        filterSize = [1, 1, 1],
-        strides,
-        pad,
-        dimRoundingMode,
-        dataFormat = "NDHWC",
-        dilations
-      ) {
-        if (dilations == null) {
-          dilations = [1, 1, 1];
-        } else {
-          deprecationWarn("dilations is deprecated, this field will be gone in " + "v3.0.0.");
-        }
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "maxPool3d");
-        let x5D = $x;
-        let reshapedTo5D = false;
-        if ($x.rank === 4) {
-          reshapedTo5D = true;
-          x5D = $x.as5D(1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]);
-        }
-        util["assert"](
-          x5D.rank === 5,
-          () => `Error in maxPool3d: x must be rank 5 but got rank ${x5D.rank}.`
-        );
-        util["assert"](
-          dataFormat === "NDHWC",
-          () =>
-            `Error in maxPool3d: Only NDHWC is currently supported, ` +
-            `but got dataFormat of ${dataFormat}`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in maxPool3d: Either strides or dilations must be 1. " +
-            `Got strides ${strides} and dilations '${dilations}'`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in maxPool3d: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const forward = (backend, save) => {
-          if (dilations == null) {
-            dilations = [1, 1, 1];
-          }
-          const convInfo = computePool3DInfo(
-            x5D.shape,
-            filterSize,
-            strides,
-            dilations,
-            pad,
-            dimRoundingMode,
-            dataFormat
-          );
-          const y = backend.maxPool3d(x5D, convInfo);
-          save([x5D, y]);
-          return y;
-        };
-        const inputs = { x: x5D };
-        const attrs = { filterSize, strides, pad, dimRoundingMode, dataFormat, dilations };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["R" /* MaxPool3D */],
-          attrs
-        );
-        if (reshapedTo5D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);
-        }
-        return res;
-      }
-      const maxPool3d = Object(operation["a" /* op */])({ maxPool3d_ });
-      //# sourceMappingURL=max_pool_3d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_with_argmax.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the 2D max pooling of an image with Argmax index.
-       * The indices in argmax are flattened, so that a maximum value at position `[b,
-       * y, x, c]` becomes flattened index: `(y * width + x) * channels + c` if
-       * include_batch_in_index is False; `((b * height + y) * width + x) * channels
-       * +c` if include_batch_in_index is True.
-       *
-       * The indices returned are always in `[0, height) x [0, width)` before
-       * flattening.
-       *
-       * @param x The input tensor, of rank 4 or rank 3 of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
-       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
-       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
-       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
-       *     `strides` is a single number, then `strideHeight == strideWidth`.
-       * @param dataFormat An optional string from: "NDHWC", "NCDHW". Defaults to
-       *     "NDHWC". Specify the data format of the input and output data. With the
-       *     default format "NDHWC", the data is stored in the order of: [batch,
-       *     depth, height, width, channels]. Only "NDHWC" is currently supported.
-       * @param pad The type of padding algorithm.
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *    - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param includeBatchIndex Defaults to False. Whether to include batch
-       *    dimension in flattened index of argmax.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function maxPoolWithArgmax_(x, filterSize, strides, pad, includeBatchInIndex = false) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "maxPoolWithArgmax");
-        const inputs = { x: $x };
-        const attrs = { filterSize, strides, pad, includeBatchInIndex };
-        const result = engine["a" /* ENGINE */].runKernel(
-          kernel_names["U" /* MaxPoolWithArgmax */],
-          inputs,
-          attrs
-        );
-        return { result: result[0], indexes: result[1] };
-      }
-      const maxPoolWithArgmax = Object(operation["a" /* op */])({ maxPoolWithArgmax_ });
-      //# sourceMappingURL=max_pool_with_argmax.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/minimum.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the min of a and b (`a < b ? a : b`) element-wise.
-       * Supports broadcasting.
-       *
-       * We also expose `minimumStrict` which has the same signature as this op and
-       * asserts that `a` and `b` are the same shape (does not broadcast).
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 4, 3, 16]);
-       * const b = tf.tensor1d([1, 2, 9, 4]);
-       *
-       * a.minimum(b).print();  // or tf.minimum(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast minimum a with b.
-       * const a = tf.tensor1d([2, 4, 6, 8]);
-       * const b = tf.scalar(5);
-       *
-       * a.minimum(b).print();  // or tf.minimum(a, b)
-       * ```
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same type as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function minimum_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "minimum");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "minimum");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        if ($a.dtype === "bool") {
-          $a = cast($a, "int32");
-          $b = cast($b, "int32");
-        }
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend, save) => {
-          const res = backend.minimum($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["W" /* Minimum */]
-        );
-      }
-      const minimum = Object(operation["a" /* op */])({ minimum_ });
-      //# sourceMappingURL=minimum.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/mod.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the mod of a and b element-wise.
-       * `floor(x / y) * y + mod(x, y) = x`
-       * Supports broadcasting.
-       *
-       * We also expose `tf.modStrict` which has the same signature as this op and
-       * asserts that `a` and `b` are the same shape (does not broadcast).
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 4, 3, 16]);
-       * const b = tf.tensor1d([1, 2, 9, 4]);
-       *
-       * a.mod(b).print();  // or tf.mod(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast a mod b.
-       * const a = tf.tensor1d([2, 4, 6, 8]);
-       * const b = tf.scalar(5);
-       *
-       * a.mod(b).print();  // or tf.mod(a, b)
-       * ```
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same type as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function mod_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "mod");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "mod");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        const forward = (backend, save) => {
-          const res = backend.mod($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["X" /* Mod */]
-        );
-      }
-      const mod = Object(operation["a" /* op */])({ mod_ });
-      //# sourceMappingURL=mod.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/multinomial.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a `tf.Tensor` with values drawn from a multinomial distribution.
-       *
-       * ```js
-       * const probs = tf.tensor([.75, .25]);
-       * tf.multinomial(probs, 3).print();
-       * ```
-       *
-       * @param logits 1D array with unnormalized log-probabilities, or
-       *     2D array of shape `[batchSize, numOutcomes]`. See the `normalized`
-       *     parameter.
-       * @param numSamples Number of samples to draw for each row slice.
-       * @param seed The seed number.
-       * @param normalized Whether the provided `logits` are normalized true
-       *     probabilities (sum to 1). Defaults to false.
-       * @return 1D array of shape `[numSamples]`, or 2D array of shape
-       *     `[batchSize, numSamples]`, depending on the rank of the input.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Random'} */
-      function multinomial_(logits, numSamples, seed, normalized = false) {
-        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
-          logits,
-          "logits",
-          "multinomial"
-        );
-        const numOutcomes = $logits.size;
-        const origRank = $logits.rank;
-        if (numOutcomes < 2) {
-          throw new Error(
-            `Error in multinomial: you need at least 2 outcomes, but got ` + `${numOutcomes}.`
-          );
-        }
-        if (origRank > 2) {
-          throw new Error(`Rank of probabilities must be 1 or 2, but is ${origRank}`);
-        }
-        seed = seed || Math.random();
-        const logits2D = origRank === 1 ? $logits.as2D(1, -1) : $logits;
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.multinomial(logits2D, normalized, numSamples, seed),
-          { logits2D }
-        );
-        return origRank === 1 ? res.as1D() : res;
-      }
-      const multinomial = Object(operation["a" /* op */])({ multinomial_ });
-      //# sourceMappingURL=multinomial.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/not_equal.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the truth value of (a != b) element-wise. Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       * const b = tf.tensor1d([0, 2, 3]);
-       *
-       * a.notEqual(b).print();
-       * ```
-       * @param a The first input tensor.
-       * @param b The second input tensor. Must have the same dtype as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Logical'} */
-      function notEqual_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "notEqual");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "notEqual");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend) => backend.notEqual($a, $b);
-        const inputs = { a: $a, b: $b };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["bb" /* NotEqual */]
-        );
-      }
-      const notEqual = Object(operation["a" /* op */])({ notEqual_ });
-      //# sourceMappingURL=not_equal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/outer_product.js
-
-      /**
-       * Computes the outer product of two vectors, `v1` and `v2`.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       * const b = tf.tensor1d([3, 4, 5]);
-       *
-       * tf.outerProduct(a, b).print();
-       * ```
-       * @param v1 The first vector in the outer product operation.
-       * @param v2 The second vector in the outer product operation.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
-      function outerProduct_(v1, v2) {
-        const $v1 = Object(tensor_util_env["a" /* convertToTensor */])(v1, "v1", "outerProduct");
-        const $v2 = Object(tensor_util_env["a" /* convertToTensor */])(v2, "v2", "outerProduct");
-        util["assert"](
-          $v1.rank === 1 && $v2.rank === 1,
-          () =>
-            `Error in outerProduct: inputs must be rank 1, but got ranks ` +
-            `${$v1.rank} and ${$v2.rank}.`
-        );
-        const v12D = reshape($v1, [-1, 1]);
-        const v22D = reshape($v2, [1, -1]);
-        return matMul(v12D, v22D);
-      }
-      const outerProduct = Object(operation["a" /* op */])({ outerProduct_ });
-      //# sourceMappingURL=outer_product.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad1d.js
-
-      /**
-       * Pads a `tf.Tensor1D` with a given value and paddings. See `pad` for details.
-       */
-      function pad1d_(x, paddings, constantValue = 0) {
-        Object(util["assert"])(
-          paddings.length === 2,
-          () => "Invalid number of paddings. Must be length of 2."
-        );
-        return pad_pad(x, [paddings], constantValue);
-      }
-      const pad1d = Object(operation["a" /* op */])({ pad1d_ });
-      //# sourceMappingURL=pad1d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad2d.js
-
-      /**
-       * Pads a `tf.Tensor2D` with a given value and paddings. See `pad` for details.
-       */
-      function pad2d_(x, paddings, constantValue = 0) {
-        Object(util["assert"])(
-          paddings.length === 2 && paddings[0].length === 2 && paddings[1].length === 2,
-          () => "Invalid number of paddings. Must be length of 2 each."
-        );
-        return pad_pad(x, paddings, constantValue);
-      }
-      const pad2d = Object(operation["a" /* op */])({ pad2d_ });
-      //# sourceMappingURL=pad2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad3d.js
-
-      /**
-       * Pads a `tf.Tensor3D` with a given value and paddings. See `pad` for details.
-       */
-      function pad3d_(x, paddings, constantValue = 0) {
-        Object(util["assert"])(
-          paddings.length === 3 &&
-            paddings[0].length === 2 &&
-            paddings[1].length === 2 &&
-            paddings[2].length === 2,
-          () => "Invalid number of paddings. Must be length of 2 each."
-        );
-        return pad_pad(x, paddings, constantValue);
-      }
-      const pad3d = Object(operation["a" /* op */])({ pad3d_ });
-      //# sourceMappingURL=pad3d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad4d.js
-
-      /**
-       * Pads a `tf.Tensor4D` with a given value and paddings. See `pad` for details.
-       */
-      function pad4d_(x, paddings, constantValue = 0) {
-        Object(util["assert"])(
-          paddings.length === 4 &&
-            paddings[0].length === 2 &&
-            paddings[1].length === 2 &&
-            paddings[2].length === 2 &&
-            paddings[3].length === 2,
-          () => "Invalid number of paddings. Must be length of 2 each."
-        );
-        return pad_pad(x, paddings, constantValue);
-      }
-      const pad4d = Object(operation["a" /* op */])({ pad4d_ });
-      //# sourceMappingURL=pad4d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pool.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Performs an N-D pooling operation
-       *
-       * @param input The input tensor, of rank 4 or rank 3 of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
-       * @param windowShape The filter size: `[filterHeight, filterWidth]`. If
-       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
-       * @param poolingType The type of pooling, either 'max' or 'avg'.
-       * @param pad The type of padding algorithm:
-       *    - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *    - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *    - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *         https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
-       *     in which we sample input values across the height and width dimensions
-       *     in dilated pooling. Defaults to `[1, 1]`. If `dilationRate` is a single
-       *     number, then `dilationHeight == dilationWidth`. If it is greater than
-       *     1, then all values of `strides` must be 1.
-       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
-       *     `strides` is a single number, then `strideHeight == strideWidth`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function pool_(input, windowShape, poolingType, pad, dilations, strides) {
-        if (dilations == null) {
-          dilations = [1, 1];
-        }
-        if (strides == null) {
-          strides = 1;
-        }
-        if (pad === 0) {
-          pad = "valid";
-        }
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(input, "x", "maxPool");
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
-        }
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in pool: Either strides or dilations must be 1. " +
-            `Got strides ${strides} and dilations '${dilations}'`
-        );
-        const convInfo = computePool2DInfo(x4D.shape, windowShape, strides, dilations, pad);
-        const dilation = [convInfo.dilationHeight, convInfo.dilationWidth];
-        // The following implementation does batchToSpace(pool(spaceToBatch(x)))
-        // whenever dilation > 1 since the TF kernels do not support dilation > 1.
-        // tslint:disable-next-line:max-line-length
-        // https://github.com/tensorflow/tensorflow/blob/50f6bb67dc98c9b74630b6047aae7a4f8a40fd02/tensorflow/python/ops/nn_ops.py#L1037
-        let basePadding;
-        if (pad === "same") {
-          basePadding = withSpaceToBatchBasePaddings(
-            [convInfo.filterHeight, convInfo.filterWidth],
-            dilation
-          );
-        } else {
-          basePadding = [
-            [0, 0],
-            [0, 0],
-          ];
-        }
-        const isDilationOne = dilation[0] === 1 && dilation[1] === 1;
-        const [adjustedPadding, adjustedCrops] = requiredSpaceToBatchPaddings(
-          [convInfo.inHeight, convInfo.inWidth],
-          dilation,
-          basePadding
-        );
-        const convertedPad = isDilationOne ? pad : "valid";
-        const convertedX = isDilationOne ? x4D : spaceToBatchND(x4D, dilation, adjustedPadding);
-        const forwardOp =
-          poolingType === "avg"
-            ? () => avgPool(convertedX, windowShape, strides, convertedPad)
-            : () => maxPool(convertedX, windowShape, strides, convertedPad);
-        const y = forwardOp();
-        const res = isDilationOne ? y : batchToSpaceND(y, dilation, adjustedCrops);
-        if (reshapedTo4D) {
-          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
-        }
-        return res;
-      }
-      // Helper function to compute crops and paddings for pool with dilation > 1.
-      // tslint:disable-next-line:max-line-length
-      // https://github.com/tensorflow/tensorflow/blob/50f6bb67dc98c9b74630b6047aae7a4f8a40fd02/tensorflow/python/ops/array_ops.py#L2184
-      function requiredSpaceToBatchPaddings(inputShape, blockShape, basePadding) {
-        const padStart = basePadding.map((b) => b[0]);
-        const origPadEnd = basePadding.map((b) => b[1]);
-        const fullInputShape = inputShape.concat(padStart, origPadEnd);
-        const padEndExtra = blockShape.map((b, i) => (b - (fullInputShape[i] % b)) % b);
-        const padEnd = origPadEnd.map((s, i) => s + padEndExtra[i]);
-        const paddings = blockShape.map((_, i) => [padStart[i], padEnd[i]]);
-        const crops = blockShape.map((_, i) => [0, padEndExtra[i]]);
-        return [paddings, crops];
-      }
-      // Helper function to compute base paddings for pool with dilation > 1.
-      // tslint:disable-next-line:max-line-length
-      // https://github.com/tensorflow/tensorflow/blob/50f6bb67dc98c9b74630b6047aae7a4f8a40fd02/tensorflow/python/ops/nn_ops.py#L524
-      function withSpaceToBatchBasePaddings(filterShape, dilation) {
-        // Spatial dimensions of the filters and the upsampled filters in which we
-        // introduce (rate - 1) zeros between consecutive filter values.
-        const dilatedFilterShape = filterShape.map((s, i) => {
-          return s + (s - 1) * (dilation[i] - 1);
-        });
-        const padExtraShape = dilatedFilterShape.map((s) => s - 1);
-        // When padding is odd, we pad more at end, following the same
-        // convention as conv2d.
-        const padExtraStart = padExtraShape.map((s) => Math.floor(s / 2));
-        const padExtraEnd = padExtraShape.map((s, i) => s - padExtraStart[i]);
-        return padExtraShape.map((_, i) => {
-          return [padExtraStart[i], padExtraEnd[i]];
-        });
-      }
-      const pool = Object(operation["a" /* op */])({ pool_ });
-      //# sourceMappingURL=pool.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/prelu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes leaky rectified linear element-wise with parametric alphas.
-       *
-       * `x < 0 ? alpha * x : f(x) = x`
-       *
-       * ```js
-       * const x = tf.tensor1d([-1, 2, -3, 4]);
-       * const alpha = tf.scalar(0.1);
-       *
-       * x.prelu(alpha).print();  // or tf.prelu(x, alpha)
-       * ```
-       * @param x The input tensor.
-       * @param alpha Scaling factor for negative values.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function prelu_(x, alpha) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "prelu");
-        const $alpha = Object(tensor_util_env["a" /* convertToTensor */])(alpha, "alpha", "prelu");
-        const forward = (backend, save) => {
-          const res = backend.prelu($x, $alpha);
-          save([$x, $alpha]);
-          return res;
-        };
-        const inputs = { x: $x, alpha: $alpha };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["gb" /* Prelu */]
-        );
-      }
-      const prelu = Object(operation["a" /* op */])({ prelu_ });
-      //# sourceMappingURL=prelu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/rand.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a `tf.Tensor` with values sampled from a random number generator
-       * function defined by the user.
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param randFunction A random number generator function which is called
-       * for each element in the output tensor.
-       * @param dtype The data type of the output tensor. Defaults to 'float32'.
-       */
-      function rand_(shape, randFunction, dtype) {
-        const size = Object(util["sizeFromShape"])(shape);
-        let values = null;
-        if (dtype == null || dtype === "float32") {
-          values = new Float32Array(size);
-        } else if (dtype === "int32") {
-          values = new Int32Array(size);
-        } else if (dtype === "bool") {
-          values = new Uint8Array(size);
-        } else {
-          throw new Error(`Unknown data type ${dtype}`);
-        }
-        for (let i = 0; i < size; i++) {
-          values[i] = randFunction();
-        }
-        return engine["a" /* ENGINE */].makeTensor(values, shape, dtype);
-      }
-      const rand = Object(operation["a" /* op */])({ rand_ });
-      //# sourceMappingURL=rand.js.map
-      // EXTERNAL MODULE: ./node_modules/seedrandom/index.js
-      var seedrandom = __webpack_require__(20);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/rand_util.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // https://en.wikipedia.org/wiki/Marsaglia_polar_method
-      class rand_util_MPRandGauss {
-        constructor(mean, stdDeviation, dtype, truncated, seed) {
-          this.mean = mean;
-          this.stdDev = stdDeviation;
-          this.dtype = dtype;
-          this.nextVal = NaN;
-          this.truncated = truncated;
-          if (this.truncated) {
-            this.upper = this.mean + this.stdDev * 2;
-            this.lower = this.mean - this.stdDev * 2;
-          }
-          const seedValue = seed ? seed : Math.random();
-          this.random = seedrandom["alea"](seedValue.toString());
-        }
-        /** Returns next sample from a Gaussian distribution. */
-        nextValue() {
-          if (!isNaN(this.nextVal)) {
-            const value = this.nextVal;
-            this.nextVal = NaN;
-            return value;
-          }
-          let resultX, resultY;
-          let isValid = false;
-          while (!isValid) {
-            let v1, v2, s;
-            do {
-              v1 = 2 * this.random() - 1;
-              v2 = 2 * this.random() - 1;
-              s = v1 * v1 + v2 * v2;
-            } while (s >= 1 || s === 0);
-            const mul = Math.sqrt((-2.0 * Math.log(s)) / s);
-            resultX = this.mean + this.stdDev * v1 * mul;
-            resultY = this.mean + this.stdDev * v2 * mul;
-            if (!this.truncated || this.isValidTruncated(resultX)) {
-              isValid = true;
-            }
-          }
-          if (!this.truncated || this.isValidTruncated(resultY)) {
-            this.nextVal = this.convertValue(resultY);
-          }
-          return this.convertValue(resultX);
-        }
-        /** Handles proper rounding for non-floating-point numbers. */
-        convertValue(value) {
-          if (this.dtype == null || this.dtype === "float32") {
-            return value;
-          }
-          return Math.round(value);
-        }
-        /** Returns true if less than 2-standard-deviations from the mean. */
-        isValidTruncated(value) {
-          return value <= this.upper && value >= this.lower;
-        }
-      }
-      // Marsaglia, George, and Wai Wan Tsang. 2000. "A Simple Method for Generating
-      // Gamma Variables."
-      class rand_util_RandGamma {
-        constructor(alpha, beta, dtype, seed) {
-          this.alpha = alpha;
-          this.beta = 1 / beta; // convert rate to scale parameter
-          this.dtype = dtype;
-          const seedValue = seed ? seed : Math.random();
-          this.randu = seedrandom["alea"](seedValue.toString());
-          this.randn = new rand_util_MPRandGauss(0, 1, dtype, false, this.randu());
-          if (alpha < 1) {
-            this.d = alpha + 2 / 3;
-          } else {
-            this.d = alpha - 1 / 3;
-          }
-          this.c = 1 / Math.sqrt(9 * this.d);
-        }
-        /** Returns next sample from a gamma distribution. */
-        nextValue() {
-          let x2, v0, v1, x, u, v;
-          while (true) {
-            do {
-              x = this.randn.nextValue();
-              v = 1 + this.c * x;
-            } while (v <= 0);
-            v *= v * v;
-            x2 = x * x;
-            v0 = 1 - 0.331 * x2 * x2;
-            v1 = 0.5 * x2 + this.d * (1 - v + Math.log(v));
-            u = this.randu();
-            if (u < v0 || Math.log(u) < v1) {
-              break;
-            }
-          }
-          v = (1 / this.beta) * this.d * v;
-          if (this.alpha < 1) {
-            v *= Math.pow(this.randu(), 1 / this.alpha);
-          }
-          return this.convertValue(v);
-        }
-        /** Handles proper rounding for non-floating-point numbers. */
-        convertValue(value) {
-          if (this.dtype === "float32") {
-            return value;
-          }
-          return Math.round(value);
-        }
-      }
-      class rand_util_UniformRandom {
-        constructor(min = 0, max = 1, dtype, seed) {
-          /** Handles proper rounding for non floating point numbers. */
-          this.canReturnFloat = () => this.dtype == null || this.dtype === "float32";
-          this.min = min;
-          this.range = max - min;
-          this.dtype = dtype;
-          if (seed == null) {
-            seed = Math.random();
-          }
-          if (typeof seed === "number") {
-            seed = seed.toString();
-          }
-          if (!this.canReturnFloat() && this.range <= 1) {
-            throw new Error(`The difference between ${min} - ${max} <= 1 and dtype is not float`);
-          }
-          this.random = seedrandom["alea"](seed);
-        }
-        convertValue(value) {
-          if (this.canReturnFloat()) {
-            return value;
-          }
-          return Math.round(value);
-        }
-        nextValue() {
-          return this.convertValue(this.min + this.range * this.random());
-        }
-      }
-      function jarqueBeraNormalityTest(values) {
-        // https://en.wikipedia.org/wiki/Jarque%E2%80%93Bera_test
-        const n = values.length;
-        const s = skewness(values);
-        const k = kurtosis(values);
-        const jb = (n / 6) * (Math.pow(s, 2) + 0.25 * Math.pow(k - 3, 2));
-        // JB test requires 2-degress of freedom from Chi-Square @ 0.95:
-        // http://www.itl.nist.gov/div898/handbook/eda/section3/eda3674.htm
-        const CHI_SQUARE_2DEG = 5.991;
-        if (jb > CHI_SQUARE_2DEG) {
-          throw new Error(`Invalid p-value for JB: ${jb}`);
-        }
-      }
-      function expectArrayInMeanStdRange(actual, expectedMean, expectedStdDev, epsilon) {
-        if (epsilon == null) {
-          epsilon = testEpsilon();
-        }
-        const actualMean = rand_util_mean(actual);
-        expectNumbersClose(actualMean, expectedMean, epsilon);
-        expectNumbersClose(standardDeviation(actual, actualMean), expectedStdDev, epsilon);
-      }
-      function rand_util_mean(values) {
-        let sum = 0;
-        for (let i = 0; i < values.length; i++) {
-          sum += values[i];
-        }
-        return sum / values.length;
-      }
-      function standardDeviation(values, mean) {
-        let squareDiffSum = 0;
-        for (let i = 0; i < values.length; i++) {
-          const diff = values[i] - mean;
-          squareDiffSum += diff * diff;
-        }
-        return Math.sqrt(squareDiffSum / values.length);
-      }
-      function kurtosis(values) {
-        // https://en.wikipedia.org/wiki/Kurtosis
-        const valuesMean = rand_util_mean(values);
-        const n = values.length;
-        let sum2 = 0;
-        let sum4 = 0;
-        for (let i = 0; i < n; i++) {
-          const v = values[i] - valuesMean;
-          sum2 += Math.pow(v, 2);
-          sum4 += Math.pow(v, 4);
-        }
-        return ((1 / n) * sum4) / Math.pow((1 / n) * sum2, 2);
-      }
-      function skewness(values) {
-        // https://en.wikipedia.org/wiki/Skewness
-        const valuesMean = rand_util_mean(values);
-        const n = values.length;
-        let sum2 = 0;
-        let sum3 = 0;
-        for (let i = 0; i < n; i++) {
-          const v = values[i] - valuesMean;
-          sum2 += Math.pow(v, 2);
-          sum3 += Math.pow(v, 3);
-        }
-        return ((1 / n) * sum3) / Math.pow((1 / (n - 1)) * sum2, 3 / 2);
-      }
-      //# sourceMappingURL=rand_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/random_gamma.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a `tf.Tensor` with values sampled from a gamma distribution.
-       *
-       * ```js
-       * tf.randomGamma([2, 2], 1).print();
-       * ```
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param alpha The shape parameter of the gamma distribution.
-       * @param beta The inverse scale parameter of the gamma distribution. Defaults
-       *     to 1.
-       * @param dtype The data type of the output. Defaults to float32.
-       * @param seed The seed for the random number generator.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Random'} */
-      function randomGamma_(shape, alpha, beta = 1, dtype = "float32", seed) {
-        if (beta == null) {
-          beta = 1;
-        }
-        if (dtype == null) {
-          dtype = "float32";
-        }
-        if (dtype !== "float32" && dtype !== "int32") {
-          throw new Error(`Unsupported data type ${dtype}`);
-        }
-        const rgamma = new rand_util_RandGamma(alpha, beta, dtype, seed);
-        const res = array_ops_buffer(shape, dtype);
-        for (let i = 0; i < res.values.length; i++) {
-          res.values[i] = rgamma.nextValue();
-        }
-        return res.toTensor();
-      }
-      const randomGamma = Object(operation["a" /* op */])({ randomGamma_ });
-      //# sourceMappingURL=random_gamma.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/random_normal.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a `tf.Tensor` with values sampled from a normal distribution.
-       *
-       * ```js
-       * tf.randomNormal([2, 2]).print();
-       * ```
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param mean The mean of the normal distribution.
-       * @param stdDev The standard deviation of the normal distribution.
-       * @param dtype The data type of the output.
-       * @param seed The seed for the random number generator.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Random'} */
-      function randomNormal_(shape, mean = 0, stdDev = 1, dtype, seed) {
-        if (dtype != null && dtype === "bool") {
-          throw new Error(`Unsupported data type ${dtype}`);
-        }
-        const randGauss = new rand_util_MPRandGauss(
-          mean,
-          stdDev,
-          dtype,
-          false /* truncated */,
-          seed
-        );
-        const res = array_ops_buffer(shape, dtype);
-        for (let i = 0; i < res.values.length; i++) {
-          res.values[i] = randGauss.nextValue();
-        }
-        return res.toTensor();
-      }
-      const randomNormal = Object(operation["a" /* op */])({ randomNormal_ });
-      //# sourceMappingURL=random_normal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/random_uniform.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a `tf.Tensor` with values sampled from a uniform distribution.
-       *
-       * The generated values follow a uniform distribution in the range [minval,
-       * maxval). The lower bound minval is included in the range, while the upper
-       * bound maxval is excluded.
-       *
-       * ```js
-       * tf.randomUniform([2, 2]).print();
-       * ```
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param minval The lower bound on the range of random values to generate.
-       *   Defaults to 0.
-       * @param maxval The upper bound on the range of random values to generate.
-       *   Defaults to 1.
-       * @param dtype The data type of the output tensor. Defaults to 'float32'.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Random'} */
-      function randomUniform_(shape, minval = 0, maxval = 1, dtype = "float32", seed) {
-        const res = array_ops_buffer(shape, dtype);
-        const random = new rand_util_UniformRandom(minval, maxval, null, seed);
-        for (let i = 0; i < res.values.length; i++) {
-          res.values[i] = random.nextValue();
-        }
-        return res.toTensor();
-      }
-      const randomUniform = Object(operation["a" /* op */])({ randomUniform_ });
-      //# sourceMappingURL=random_uniform.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/real.js
-      var real = __webpack_require__(22);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/relu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes rectified linear element-wise: `max(x, 0)`.
-       *
-       * ```js
-       * const x = tf.tensor1d([-1, 2, -3, 4]);
-       *
-       * x.relu().print();  // or tf.relu(x)
-       * ```
-       * @param x The input tensor. If the dtype is `bool`, the output dtype will be
-       *     `int32'.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function relu_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "relu");
-        const forward = (backend, save) => {
-          save([$x]);
-          if ($x.dtype === "bool") {
-            return $x.toInt();
-          }
-          return backend.relu($x);
-        };
-        const inputs = { x: $x };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["ib" /* Relu */]
-        );
-      }
-      const relu = Object(operation["a" /* op */])({ relu_ });
-      //# sourceMappingURL=relu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/relu6.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes rectified linear 6 element-wise: `min(max(x, 0), 6)`.
-       *
-       * ```js
-       * const x = tf.tensor1d([-1, 2, -3, 8]);
-       *
-       * x.relu6().print();  // or tf.relu6(x)
-       * ```
-       * @param x The input tensor. If the dtype is `bool`, the output dtype will be
-       *     `int32'.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function relu6_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "relu6");
-        const forward = (backend, save) => {
-          save([$x]);
-          if ($x.dtype === "bool") {
-            return cast($x, "int32");
-          }
-          return backend.relu6($x);
-        };
-        const inputs = { x: $x };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["jb" /* Relu6 */]
-        );
-      }
-      const relu6 = Object(operation["a" /* op */])({ relu6_ });
-      //# sourceMappingURL=relu6.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/selu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes scaled exponential linear element-wise.
-       *
-       * `x < 0 ? scale * alpha * (exp(x) - 1) : x`
-       *
-       * ```js
-       * const x = tf.tensor1d([-1, 2, -3, 4]);
-       *
-       * x.selu().print();  // or tf.selu(x)
-       * ```
-       * @param x The input tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
-      function selu_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "selu");
-        const forward = (backend, save) => {
-          const res = backend.selu($x);
-          save([$x]);
-          return res;
-        };
-        const inputs = { x: $x };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["lb" /* Selu */]
-        );
-      }
-      const selu = Object(operation["a" /* op */])({ selu_ });
-      //# sourceMappingURL=selu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/separable_conv2d.js
-
-      /**
-       * 2-D convolution with separable filters.
-       *
-       * Performs a depthwise convolution that acts separately on channels followed
-       * by a pointwise convolution that mixes channels. Note that this is
-       * separability between dimensions [1, 2] and 3, not spatial separability
-       * between dimensions 1 and 2.
-       *
-       * See
-       * [https://www.tensorflow.org/api_docs/python/tf/nn/separable_conv2d](
-       *     https://www.tensorflow.org/api_docs/python/tf/nn/separable_conv2d)
-       * for more details.
-       *
-       * @param x The input tensor, of rank 4 or rank 3, of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
-       * assumed.
-       * @param depthwiseFilter The depthwise filter tensor, rank 4, of shape
-       *     `[filterHeight, filterWidth, inChannels, channelMultiplier]`. This is
-       *     the filter used in the first step.
-       * @param pointwiseFilter The pointwise filter tensor, rank 4, of shape
-       *     `[1, 1, inChannels * channelMultiplier, outChannels]`. This is
-       *     the filter used in the second step.
-       * @param strides The strides of the convolution: `[strideHeight,
-       * strideWidth]`. If strides is a single number, then `strideHeight ==
-       * strideWidth`.
-       * @param pad The type of padding algorithm.
-       *   - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *   - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *   - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
-       *     in which we sample input values across the height and width dimensions
-       *     in atrous convolution. Defaults to `[1, 1]`. If `rate` is a single
-       *     number, then `dilationHeight == dilationWidth`. If it is greater than
-       *     1, then all values of `strides` must be 1.
-       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
-       *     "NHWC". Specify the data format of the input and output data. With the
-       *     default format "NHWC", the data is stored in the order of: [batch,
-       *     height, width, channels]. Only "NHWC" is currently supported.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
-      function separableConv2d_(
-        x,
-        depthwiseFilter,
-        pointwiseFilter,
-        strides,
-        pad,
-        dilation = [1, 1],
-        dataFormat = "NHWC"
-      ) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "separableConv2d");
-        const $depthwiseFilter = Object(tensor_util_env["a" /* convertToTensor */])(
-          depthwiseFilter,
-          "depthwiseFilter",
-          "separableConv2d"
-        );
-        const $pointwiseFilter = Object(tensor_util_env["a" /* convertToTensor */])(
-          pointwiseFilter,
-          "pointwiseFilter",
-          "separableConv2d"
-        );
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = $x.as4D(1, $x.shape[0], $x.shape[1], $x.shape[2]);
-        }
-        if (dataFormat === "NCHW") {
-          throw new Error(
-            "separableConv2d currently does not support dataFormat NCHW; only " +
-              "NHWC is supported"
-          );
-        }
-        util["assert"](
-          x4D.rank === 4,
-          () => `Error in separableConv2d: input must be rank 4, but got ` + `rank ${x4D.rank}.`
-        );
-        util["assert"](
-          $depthwiseFilter.rank === 4,
-          () =>
-            `Error in separableConv2d: depthwise filter must be rank 4, but ` +
-            `got rank ${$depthwiseFilter.rank}.`
-        );
-        util["assert"](
-          $pointwiseFilter.rank === 4,
-          () =>
-            `Error in separableConv2d: pointwise filter must be rank 4, but ` +
-            `got rank ${$depthwiseFilter.rank}.`
-        );
-        util["assert"](
-          $pointwiseFilter.shape[0] === 1,
-          () =>
-            `Error in separableConv2d: the first dimension of pointwise filter ` +
-            ` must be 1, but got ${$pointwiseFilter.shape[0]}.`
-        );
-        util["assert"](
-          $pointwiseFilter.shape[1] === 1,
-          () =>
-            `Error in separableConv2d: the second dimension of pointwise ` +
-            `filter must be 1, but got ${$pointwiseFilter.shape[1]}.`
-        );
-        const inChannels = $depthwiseFilter.shape[2];
-        const channelMultiplier = $depthwiseFilter.shape[3];
-        util["assert"](
-          $pointwiseFilter.shape[2] === inChannels * channelMultiplier,
-          () =>
-            `Error in separableConv2d: the third dimension of pointwise filter ` +
-            `must be ${inChannels * channelMultiplier}, ` +
-            `but got ${$pointwiseFilter.shape[2]}.`
-        );
-        const depthwise = depthwiseConv2d(
-          x4D,
-          $depthwiseFilter,
-          strides,
-          pad,
-          dataFormat,
-          dilation
-        );
-        const pointwiseStride = 1;
-        const res = conv2d(depthwise, $pointwiseFilter, pointwiseStride, "valid", dataFormat);
-        if (reshapedTo4D) {
-          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
-        }
-        return res;
-      }
-      const separableConv2d = Object(operation["a" /* op */])({ separableConv2d_ });
-      //# sourceMappingURL=separable_conv2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/squared_difference.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns (a - b) * (a - b) element-wise.
-       * Supports broadcasting.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 4, 3, 16]);
-       * const b = tf.tensor1d([1, 2, 9, 4]);
-       *
-       * a.squaredDifference(b).print();  // or tf.squaredDifference(a, b)
-       * ```
-       *
-       * ```js
-       * // Broadcast squared difference  a with b.
-       * const a = tf.tensor1d([2, 4, 6, 8]);
-       * const b = tf.scalar(5);
-       *
-       * a.squaredDifference(b).print();  // or tf.squaredDifference(a, b)
-       * ```
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same type as `a`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
-      function squaredDifference_(a, b) {
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "squaredDifference");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "squaredDifference");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        assertAndGetBroadcastShape($a.shape, $b.shape);
-        const forward = (backend, save) => {
-          const res = backend.squaredDifference($a, $b);
-          save([$a, $b]);
-          return res;
-        };
-        const inputs = { a: $a, b: $b };
-        const attrs = {};
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* grad */,
-          kernel_names["pb" /* SquaredDifference */],
-          attrs
-        );
-      }
-      const squaredDifference = Object(operation["a" /* op */])({ squaredDifference_ });
-      //# sourceMappingURL=squared_difference.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/truncated_normal.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a `tf.Tensor` with values sampled from a truncated normal
-       * distribution.
-       *
-       * ```js
-       * tf.truncatedNormal([2, 2]).print();
-       * ```
-       *
-       * The generated values follow a normal distribution with specified mean and
-       * standard deviation, except that values whose magnitude is more than 2
-       * standard deviations from the mean are dropped and re-picked.
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param mean The mean of the normal distribution.
-       * @param stdDev The standard deviation of the normal distribution.
-       * @param dtype The data type of the output tensor.
-       * @param seed The seed for the random number generator.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function truncatedNormal_(shape, mean = 0, stdDev = 1, dtype, seed) {
-        if (dtype != null && dtype === "bool") {
-          throw new Error(`Unsupported data type $ { dtype }`);
-        }
-        const randGauss = new rand_util_MPRandGauss(
-          mean,
-          stdDev,
-          dtype,
-          true /* truncated */,
-          seed
-        );
-        const res = array_ops_buffer(shape, dtype);
-        for (let i = 0; i < res.values.length; i++) {
-          res.values[i] = randGauss.nextValue();
-        }
-        return res.toTensor();
-      }
-      const truncatedNormal = Object(operation["a" /* op */])({ truncatedNormal_ });
-      //# sourceMappingURL=truncated_normal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/reduce_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Inputs of size above this threshold will be parallelized by calling multiple
-       * shader programs.
-       */
-
-      const PARALLELIZE_THRESHOLD = 30;
-      function computeOptimalWindowSize(inSize) {
-        if (inSize <= PARALLELIZE_THRESHOLD) {
-          return inSize;
-        }
-        return Object(util["nearestDivisor"])(inSize, Math.floor(Math.sqrt(inSize)));
-      }
-      //# sourceMappingURL=reduce_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/segment_util.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function segOpComputeOptimalWindowSize(inSize, numSegments) {
-        let done = false;
-        let res;
-        if (inSize <= PARALLELIZE_THRESHOLD) {
-          res = inSize;
-          done = true;
-        } else {
-          res = Object(util["nearestDivisor"])(inSize, Math.floor(Math.sqrt(inSize)));
-        }
-        while (!done) {
-          if (res > numSegments || res === inSize) {
-            done = true;
-          } else {
-            res = Object(util["nearestDivisor"])(inSize, res + 1);
-          }
-        }
-        return res;
-      }
-      function segment_util_computeOutShape(aShape, axis, numSegments) {
-        const outShape = [];
-        const rank = aShape.length;
-        for (let dim = 0; dim < rank; dim++) {
-          if (dim !== axis) {
-            outShape.push(aShape[dim]);
-          } else {
-            outShape.push(numSegments);
-          }
-        }
-        return outShape;
-      }
-      function collectGatherOpShapeInfo(x, indices, axis) {
-        const dimSize = x.shape[axis];
-        const outputShape = [];
-        let batchSize = 1;
-        let sliceSize = 1;
-        for (let i = 0; i < axis; i++) {
-          outputShape.push(x.shape[i]);
-          batchSize *= x.shape[i];
-        }
-        for (let i = 0; i < indices.rank; i++) {
-          outputShape.push(indices.shape[i]);
-        }
-        for (let i = axis + 1; i < x.rank; i++) {
-          outputShape.push(x.shape[i]);
-          sliceSize *= x.shape[i];
-        }
-        return { batchSize, sliceSize, dimSize, outputShape };
-      }
-      //# sourceMappingURL=segment_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/segment_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the sum along segments of a `tf.Tensor`.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       * const segmentIds = tf.tensor1d([1, 2, 0, 1], 'int32');
-       * const numSegments = 3;
-       *
-       * x.unsortedSegmentSum(segmentIds, numSegments).print()
-       * //or tf.unsortedSegmentSum(x, segmentIds, numSegments)
-       * ```
-       * @param x The `tf.Tensor` that will be summed along its segments.
-       * @param segmentIds A `tf.Tensor1D` whose rank is equal to the rank of `x`'s
-       * dimension along the `axis`.  Maps each element of `x` to a segment.
-       * @param numSegments The number of distinct `segmentIds`.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Segment'} */
-      function unsortedSegmentSum_(x, segmentIds, numSegments) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "unsortedSegmentSum");
-        const $segmentIds = Object(tensor_util_env["a" /* convertToTensor */])(
-          segmentIds,
-          "segmentIds",
-          "unsortedSegmentSum",
-          "int32"
-        );
-        Object(util["assert"])(
-          Object(util["isInt"])(numSegments),
-          () => "numSegments must be of dtype int"
-        );
-        const gradFunc = (dy, saved) => {
-          const [$segmentIds] = saved;
-          const derX = () => {
-            return gatherDropNegatives(dy, $segmentIds);
-          };
-          return { $x: derX };
-        };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.unsortedSegmentSum($x, $segmentIds, numSegments);
-            save([$segmentIds]);
-            return res;
-          },
-          { $x },
-          gradFunc
-        );
-      }
-      /**
-       * Gather slices from tensor `x`'s axis `axis` according to `indices`.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       * const indices = tf.tensor1d([1, 3, 3], 'int32');
-       *
-       * x.gather(indices).print();
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       * const indices = tf.tensor1d([1, 1, 0], 'int32');
-       *
-       * x.gather(indices).print();
-       * ```
-       * @param x The input tensor whose slices to be gathered.
-       * @param indices The indices of the values to extract.
-       * @param axis The axis over which to select values. Defaults to 0.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      function gather_(x, indices, axis = 0) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "gather");
-        const $indices = Object(tensor_util_env["a" /* convertToTensor */])(
-          indices,
-          "indices",
-          "gather",
-          "int32"
-        );
-        axis = Object(util["parseAxisParam"])(axis, $x.shape)[0];
-        const shapeInfo = collectGatherOpShapeInfo($x, $indices, axis);
-        const grad = (dy, saved) => {
-          const [$indices] = saved;
-          const derX = () => {
-            const paramsShape = $x.shape;
-            const indicesSize = $indices.size;
-            const outerShape = paramsShape.slice(0, axis);
-            const outerDims = outerShape.length;
-            const innerShape = paramsShape.slice(axis, paramsShape.length).slice(1);
-            const innerDims = innerShape.length;
-            const outerAxesIndices = arrayRange(0, outerDims);
-            const innerAxesIndices = arrayRange(outerDims + 1, outerDims + 1 + innerDims);
-            const valuesShape = arrayConcat([outerShape, [indicesSize], innerShape]);
-            const values = dy.reshape(valuesShape);
-            const reshapedIndices = $indices.reshape([indicesSize]);
-            const transposeDims = arrayConcat([[outerDims], outerAxesIndices, innerAxesIndices]);
-            const valuesTranspose = values.transpose(transposeDims);
-            let paramsGrad = unsortedSegmentSum(valuesTranspose, reshapedIndices, $x.shape[axis]);
-            const invertTransposeDims = getUndoAxesPermutation(transposeDims);
-            paramsGrad = paramsGrad.transpose(invertTransposeDims);
-            return paramsGrad;
-          };
-          return { x: derX, indices: () => $indices };
-        };
-        return engine["a" /* ENGINE */]
-          .runKernelFunc(
-            (backend, save) => {
-              const res = backend.gather($x, $indices.flatten(), axis);
-              save([$indices]);
-              return res;
-            },
-            { x: $x, indices: $indices },
-            grad,
-            "Gather",
-            { axis }
-          )
-          .reshape(shapeInfo.outputShape);
-      }
-      function arrayRange(start, stop) {
-        const result = [];
-        for (let i = start; i < stop; ++i) {
-          result.push(i);
-        }
-        return result;
-      }
-      function arrayConcat(arrays) {
-        const result = [];
-        for (let i = 0; i < arrays.length; ++i) {
-          for (let j = 0; j < arrays[i].length; ++j) {
-            result.push(arrays[i][j]);
-          }
-        }
-        return result;
-      }
-      function gatherDropNegatives(x, indices) {
-        // Helper function for unsorted segment ops. Gathers params for
-        // positive segment ids and gathers 0 for inputs with negative segment id.
-        // Mirrors _GatherDropNegatives from tensorflow/python/ops/math_grad.py
-        const zeroClippedIndices = maximum(
-          indices,
-          Object(tensor_ops["o" /* zerosLike */])(indices)
-        );
-        const gathered = gather(x, zeroClippedIndices);
-        let isPositive = greaterEqual(indices, Object(tensor_ops["e" /* scalar */])(0, "int32"));
-        const numIters = gathered.rank - isPositive.rank;
-        for (let i = 0; i < numIters; ++i) {
-          isPositive = expandDims(isPositive, i + 1);
-        }
-        isPositive = logicalAnd(
-          isPositive,
-          Object(tensor_ops["b" /* ones */])(gathered.shape, "bool")
-        );
-        const zeroSlice = Object(tensor_ops["o" /* zerosLike */])(gathered);
-        return where(isPositive, gathered, zeroSlice);
-      }
-      const gather = Object(operation["a" /* op */])({ gather_ });
-      const unsortedSegmentSum = Object(operation["a" /* op */])({ unsortedSegmentSum_ });
-      //# sourceMappingURL=segment_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/boolean_mask.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Apply boolean mask to tensor.
-       *
-       * ```js
-       * const tensor = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
-       * const mask = tf.tensor1d([1, 0, 1], 'bool');
-       * const result = await tf.booleanMaskAsync(tensor, mask);
-       * result.print();
-       * ```
-       *
-       * @param tensor N-D tensor.
-       * @param mask K-D boolean tensor, K <= N and K must be known statically.
-       * @param axis A 0-D int Tensor representing the axis in tensor to mask from.
-       *     By default, axis is 0 which will mask from the first dimension.
-       *     Otherwise K + axis <= N.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      async function booleanMaskAsync_(tensor, mask, axis) {
-        const $tensor = Object(tensor_util_env["a" /* convertToTensor */])(
-          tensor,
-          "tensor",
-          "boolMask"
-        );
-        const $mask = Object(tensor_util_env["a" /* convertToTensor */])(
-          mask,
-          "mask",
-          "boolMask",
-          "bool"
-        );
-        const axisFrom = axis == null ? 0 : axis;
-        const maskDim = $mask.rank;
-        const tensorShape = $tensor.shape;
-        util["assert"](maskDim > 0, () => "mask cannot be scalar");
-        util["assertShapesMatch"](
-          tensorShape.slice(axisFrom, axisFrom + maskDim),
-          $mask.shape,
-          `mask's shape must match the first K dimensions of tensor's shape,`
-        );
-        let leadingSize = 1;
-        for (let i = axisFrom; i < axisFrom + maskDim; i++) {
-          leadingSize *= tensorShape[i];
-        }
-        const targetTensorShape = tensorShape
-          .slice(0, axisFrom)
-          .concat([leadingSize], tensorShape.slice(axisFrom + maskDim));
-        const reshapedTensor = $tensor.reshape(targetTensorShape);
-        const reshapedMask = $mask.reshape([-1]);
-        const positivePositions = await whereAsync(reshapedMask);
-        const indices = positivePositions.squeeze([1]);
-        const res = gather(reshapedTensor, indices, axisFrom);
-        // Ensure no memory leak.
-        if (tensor !== $tensor) {
-          $tensor.dispose();
-        }
-        if (mask !== $mask) {
-          $mask.dispose();
-        }
-        indices.dispose();
-        reshapedTensor.dispose();
-        reshapedMask.dispose();
-        positivePositions.dispose();
-        return res;
-      }
-      const booleanMaskAsync = booleanMaskAsync_;
-      //# sourceMappingURL=boolean_mask.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/reverse.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Reverses a `tf.Tensor1D`.
-       *
-       * @param x The input tensor.
-       */
-      function reverse1d_(x) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
-        util["assert"](
-          $x.rank === 1,
-          () => `Error in reverse1D: x must be rank 1 but got rank ${$x.rank}.`
-        );
-        return reverse_reverse($x, 0);
-      }
-      /**
-       * Reverses a `tf.Tensor2D` along a specified axis.
-       *
-       * @param x The input tensor.
-       * @param axis The set of dimensions to reverse. Must be in the
-       *     range [-rank(x), rank(x)). Defaults to all axes.
-       */
-      function reverse2d_(x, axis) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
-        util["assert"](
-          $x.rank === 2,
-          () => `Error in reverse2D: x must be rank 2 but got rank ${$x.rank}.`
-        );
-        return reverse_reverse($x, axis);
-      }
-      /**
-       * Reverses a `tf.Tensor3D` along a specified axis.
-       *
-       * @param x The input tensor.
-       * @param axis The set of dimensions to reverse. Must be in the
-       *     range [-rank(x), rank(x)). Defaults to all axes.
-       */
-      function reverse3d_(x, axis) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
-        util["assert"](
-          $x.rank === 3,
-          () => `Error in reverse3D: x must be rank 3 but got rank ${$x.rank}.`
-        );
-        return reverse_reverse($x, axis);
-      }
-      /**
-       * Reverses a `tf.Tensor4D` along a specified axis.
-       *
-       * @param x The input tensor.
-       * @param axis The set of dimensions to reverse. Must be in the
-       *     range [-rank(x), rank(x)). Defaults to all axes.
-       */
-      function reverse4d_(x, axis) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
-        util["assert"](
-          $x.rank === 4,
-          () => `Error in reverse4D: x must be rank 4 but got rank ${$x.rank}.`
-        );
-        return reverse_reverse($x, axis);
-      }
-      /**
-       * Reverses a `tf.Tensor` along a specified axis.
-       *
-       * Also available are stricter rank-specific methods that assert that `x` is
-       * of the given rank:
-       *   - `tf.reverse1d`
-       *   - `tf.reverse2d`
-       *   - `tf.reverse3d`
-       *   - `tf.reverse4d`
-       *
-       * Except `tf.reverse1d` (which does not have axis param), all methods have
-       * same signature as this method.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       *
-       * x.reverse().print();
-       * ```
-       *
-       * ```js
-       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       *
-       * const axis = 1;
-       * x.reverse(axis).print();
-       * ```
-       * @param x The input tensor to be reversed.
-       * @param axis The set of dimensions to reverse. Must be in the
-       *     range [-rank(x), rank(x)). Defaults to all axes.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
-      function reverse_(x, axis) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
-        if ($x.rank === 0) {
-          return $x.clone();
-        }
-        const axes = util["parseAxisParam"](axis, $x.shape);
-        const grad = (dy) => {
-          return { $x: () => dy.reverse(axes) };
-        };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.reverse($x, axes),
-          { $x },
-          grad
-        );
-        return res.reshapeAs($x);
-      }
-      const reverse_reverse = Object(operation["a" /* op */])({ reverse_ });
-      const reverse1d = Object(operation["a" /* op */])({ reverse1d_ });
-      const reverse2d = Object(operation["a" /* op */])({ reverse2d_ });
-      const reverse3d = Object(operation["a" /* op */])({ reverse3d_ });
-      const reverse4d = Object(operation["a" /* op */])({ reverse4d_ });
-      //# sourceMappingURL=reverse.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/compare.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * @deprecated
-       * Strict version of `tf.notEqual` that forces `a` and `b` to be of the same
-       * shape.
-       *
-       * @param a The first input tensor.
-       * @param b The second input tensor. Must have the same shape and dtype as
-       *     `a`.
-       */
-      function notEqualStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "notEqualStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "notEqualStrict");
-        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in notEqualStrict: ");
-        return $a.notEqual($b);
-      }
-      /**
-       * @deprecated
-       * Strict version of `tf.less` that forces `a` and `b` to be of the same
-       * shape.
-       *
-       * @param a The first input tensor.
-       * @param b The second input tensor. Must have the same shape and dtype as
-       *     `a`.
-       */
-      function lessStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "lessStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "lessStrict");
-        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in lessStrict: ");
-        return $a.less($b);
-      }
-      function equalStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "equalStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "equalStrict");
-        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in equalStrict: ");
-        return $a.equal($b);
-      }
-      function lessEqualStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "lessEqualStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "lessEqualStrict");
-        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in lessEqualStrict: ");
-        return $a.lessEqual($b);
-      }
-      function greaterStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "greaterStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "greaterStrict");
-        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in greaterStrict: ");
-        return $a.greater($b);
-      }
-      function greaterEqualStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "greaterEqualStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "greaterEqualStrict");
-        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in greaterEqualStrict: ");
-        return $a.greaterEqual($b);
-      }
-      const equalStrict = Object(operation["a" /* op */])({ equalStrict_ });
-      const greaterEqualStrict = Object(operation["a" /* op */])({ greaterEqualStrict_ });
-      const greaterStrict = Object(operation["a" /* op */])({ greaterStrict_ });
-      const lessEqualStrict = Object(operation["a" /* op */])({ lessEqualStrict_ });
-      const lessStrict = Object(operation["a" /* op */])({ lessStrict_ });
-      const notEqualStrict = Object(operation["a" /* op */])({ notEqualStrict_ });
-      //# sourceMappingURL=compare.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/binary_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * @deprecated
-       * Adds two `tf.Tensor`s element-wise, A + B.
-       *
-       * Inputs must be the same shape. For broadcasting support, use add() instead.
-       *
-       * @param a The first Tensor to add element-wise.
-       * @param b The second Tensor to add element-wise.
-       */
-      function addStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "addStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "addStrict");
-        util["assertShapesMatch"]($a.shape, $b.shape, "Error in addStrict: ");
-        return $a.add($b);
-      }
-      /**
-       * @deprecated
-       * Subtracts two `tf.Tensor`s element-wise, A - B. Inputs must
-       * be the same shape.
-       *
-       * For broadcasting support, use `tf.sub` instead.
-       *
-       * @param a The first Tensor to subtract element-wise.
-       * @param b The second Tensor to subtract element-wise.
-       */
-      function subStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "subStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "subStrict");
-        util["assertShapesMatch"]($a.shape, $b.shape, "Error in subStrict: ");
-        return $a.sub($b);
-      }
-      /**
-       * @deprecated
-       * Computes the power of one `tf.Tensor` to another. Inputs must
-       * be the same shape.
-       *
-       * For broadcasting support, use `tf.pow` instead.
-       *
-       * @param base The base tensor to pow element-wise.
-       * @param exp The exponent tensor to pow element-wise.
-       */
-      function powStrict_(base, exp) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        util["assertShapesMatch"](base.shape, exp.shape, "Error in powStrict: ");
-        return base.pow(exp);
-      }
-      /**
-       * @deprecated
-       * Multiplies two `tf.Tensor`s element-wise, A * B.
-       *
-       * Inputs must be the same shape. For broadcasting support, use `tf.mul`.
-       *
-       * @param a The first tensor to multiply.
-       * @param b The first tensor to multiply. Must have the same
-       *    dtype as `a`.
-       */
-      function mulStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "mul");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "mul");
-        util["assertShapesMatch"]($a.shape, $b.shape, "Error in multiplyStrict: ");
-        return $a.mul($b);
-      }
-      /**
-       * @deprecated
-       * Divides two `tf.Tensor`s element-wise, A / B. Inputs must
-       * be the same shape.
-       *
-       * @param a The first tensor as the numerator for element-wise division.
-       * @param b The second tensor as the denominator for element-wise division.
-       */
-      function divStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "div");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "div");
-        util["assertShapesMatch"]($a.shape, $b.shape, "Error in divideStrict: ");
-        return $a.div($b);
-      }
-      /**
-       * @deprecated
-       * Returns the mod of a and b (`a < b ? a : b`) element-wise. Inputs must
-       * be the same shape. For broadcasting support, use mod().
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same dtype as `a`.
-       */
-      function modStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "modStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "modStrict");
-        util["assertShapesMatch"]($a.shape, $b.shape, "Error in modStrict: ");
-        return $a.mod($b);
-      }
-      /**
-       * @deprecated
-       * Returns the min of a and b (`a < b ? a : b`) element-wise. Inputs must
-       * be the same shape. For broadcasting support, use minimum().
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same dtype as `a`.
-       */
-      function minimumStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "minimumStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "minimumStrict");
-        util["assertShapesMatch"]($a.shape, $b.shape, "Error in minimumStrict: ");
-        return $a.minimum($b);
-      }
-      /**
-       * @deprecated
-       * Returns the max of a and b (`a > b ? a : b`) element-wise. Inputs must
-       * be the same shape. For broadcasting support, use maximum().
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same dtype as `a`.
-       */
-      function maximumStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "maximumStrict");
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "maximumStrict");
-        util["assertShapesMatch"]($a.shape, $b.shape, "Error in maximumStrict: ");
-        return $a.maximum($b);
-      }
-      /**
-       * @deprecated
-       * Returns (a - b) * (a - b) element-wise.
-       *
-       * Inputs must be the same shape. For broadcasting support, use
-       * `tf.squaredDifference` instead.
-       *
-       * @param a The first tensor.
-       * @param b The second tensor. Must have the same type as `a`.
-       */
-      function squaredDifferenceStrict_(a, b) {
-        deprecationWarn(
-          "strict variants of ops have been deprecated " + "and will be removed in future"
-        );
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(
-          a,
-          "a",
-          "squaredDifferenceStrict"
-        );
-        const $b = Object(tensor_util_env["a" /* convertToTensor */])(
-          b,
-          "b",
-          "squaredDifferenceStrict"
-        );
-        util["assertShapesMatch"]($a.shape, $b.shape, "Error in squaredDifferenceStrict: ");
-        return $a.squaredDifference($b);
-      }
-      const addStrict = Object(operation["a" /* op */])({ addStrict_ });
-      const divStrict = Object(operation["a" /* op */])({ divStrict_ });
-      const maximumStrict = Object(operation["a" /* op */])({ maximumStrict_ });
-      const minimumStrict = Object(operation["a" /* op */])({ minimumStrict_ });
-      const modStrict = Object(operation["a" /* op */])({ modStrict_ });
-      const mulStrict = Object(operation["a" /* op */])({ mulStrict_ });
-      const powStrict = Object(operation["a" /* op */])({ powStrict_ });
-      const squaredDifferenceStrict = Object(operation["a" /* op */])({ squaredDifferenceStrict_ });
-      const subStrict = Object(operation["a" /* op */])({ subStrict_ });
-      //# sourceMappingURL=binary_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/softmax.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the softmax normalized vector given the logits.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       *
-       * a.softmax().print();  // or tf.softmax(a)
-       * ```
-       *
-       * ```js
-       * const a = tf.tensor2d([2, 4, 6, 1, 2, 3], [2, 3]);
-       *
-       * a.softmax().print();  // or tf.softmax(a)
-       * ```
-       *
-       * @param logits The logits array.
-       * @param dim The dimension softmax would be performed on. Defaults to `-1`
-       *     which indicates the last dimension.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
-      function softmax_(logits, dim = -1) {
-        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
-          logits,
-          "logits",
-          "softmax",
-          "float32"
-        );
-        if (dim === -1) {
-          dim = $logits.rank - 1;
-        }
-        if (dim !== $logits.rank - 1) {
-          throw Error(
-            "Softmax along a non-last dimension is not yet supported. " +
-              `Logits was rank ${$logits.rank} and dim was ${dim}`
-          );
-        }
-        const inputsToSave = [];
-        const outputsToSave = [true];
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const y = backend.softmax($logits, dim);
-            save([y]);
-            return y;
-          },
-          { logits: $logits },
-          (dy, saved) => {
-            const [y] = saved;
-            const dyTimesY = dy.mul(y);
-            const keepDims = true;
-            return {
-              logits: () => dyTimesY.sub(dyTimesY.sum([dim], keepDims).mul(y)),
-            };
-          },
-          "Softmax",
-          { dim },
-          inputsToSave,
-          outputsToSave
-        );
-      }
-      /**
-       * Computes the log softmax.
-       *
-       * ```js
-       * const a = tf.tensor1d([1, 2, 3]);
-       *
-       * a.logSoftmax().print();  // or tf.logSoftmax(a)
-       * ```
-       *
-       * ```js
-       * const a = tf.tensor2d([2, 4, 6, 1, 2, 3], [2, 3]);
-       *
-       * a.logSoftmax().print();  // or tf.logSoftmax(a)
-       * ```
-       *
-       * @param logits The logits array.
-       * @param axis The dimension softmax would be performed on. Defaults to `-1`
-       *     which indicates the last dimension.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
-      function logSoftmax_(logits, axis = -1) {
-        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
-          logits,
-          "logits",
-          "logSoftmax"
-        );
-        if (axis === -1) {
-          axis = $logits.rank - 1;
-        }
-        if (axis !== $logits.rank - 1) {
-          throw Error(
-            "Log Softmax along a non-last dimension is not yet supported. " +
-              `Logits was rank ${$logits.rank} and axis was ${axis}`
-          );
-        }
-        const customOp = customGrad((logits, save) => {
-          const keepDims = true;
-          const xMax = logits.max(axis, true);
-          const shifted = logits.sub(xMax);
-          const value = shifted.toFloat().sub(shifted.exp().sum(axis, keepDims).log());
-          save([value]);
-          const gradFunc = (dy, saved) => {
-            const [value] = saved;
-            const softmax = value.exp();
-            return dy.sub(dy.sum(axis, keepDims).mul(softmax));
-          };
-          return { value, gradFunc };
-        });
-        return customOp($logits);
-      }
-      const softmax = Object(operation["a" /* op */])({ softmax_ });
-      const logSoftmax = Object(operation["a" /* op */])({ logSoftmax_ });
-      //# sourceMappingURL=softmax.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/norm.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the norm of scalar, vectors, and matrices.
-       * This function can compute several different vector norms (the 1-norm, the
-       * Euclidean or 2-norm, the inf-norm, and in general the p-norm for p > 0)
-       * and matrix norms (Frobenius, 1-norm, and inf-norm).
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 3, 4]);
-       *
-       * x.norm().print();  // or tf.norm(x)
-       * ```
-       *
-       * @param x The input array.
-       * @param ord Optional. Order of the norm. Supported norm types are
-       * following:
-       *
-       *  | ord        | norm for matrices         | norm for vectors
-       *  |------------|---------------------------|---------------------
-       *  |'euclidean' |Frobenius norm             |2-norm
-       *  |'fro'       |Frobenius norm	           |
-       *  |Infinity    |max(sum(abs(x), axis=1))   |max(abs(x))
-       *  |-Infinity   |min(sum(abs(x), axis=1))   |min(abs(x))
-       *  |1           |max(sum(abs(x), axis=0))   |sum(abs(x))
-       *  |2           |                           |sum(abs(x)^2)^1/2*
-       *
-       * @param axis Optional. If axis is null (the default), the input is
-       * considered a vector and a single vector norm is computed over the entire
-       * set of values in the Tensor, i.e. norm(x, ord) is equivalent
-       * to norm(x.reshape([-1]), ord). If axis is a integer, the input
-       * is considered a batch of vectors, and axis determines the axis in x
-       * over which to compute vector norms. If axis is a 2-tuple of integer it is
-       * considered a batch of matrices and axis determines the axes in NDArray
-       * over which to compute a matrix norm.
-       * @param keepDims Optional. If true, the norm have the same dimensionality
-       * as the input.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
-      function norm_(x, ord = "euclidean", axis = null, keepDims = false) {
-        x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "norm");
-        const norm = normImpl(x, ord, axis);
-        let keepDimsShape = norm.shape;
-        if (keepDims) {
-          const axes = Object(util["parseAxisParam"])(axis, x.shape);
-          keepDimsShape = expandShapeToKeepDim(norm.shape, axes);
-        }
-        return norm.reshape(keepDimsShape);
-      }
-      function normImpl(x, p, axis = null) {
-        if (x.rank === 0) {
-          return x.abs();
-        }
-        // consider vector when no axis is specified
-        if (x.rank !== 1 && axis === null) {
-          return normImpl(x.reshape([-1]), p, axis);
-        }
-        // vector
-        if (
-          x.rank === 1 ||
-          typeof axis === "number" ||
-          (Array.isArray(axis) && axis.length === 1)
-        ) {
-          if (p === 1) {
-            return x.abs().sum(axis);
-          }
-          if (p === Infinity) {
-            return x.abs().max(axis);
-          }
-          if (p === -Infinity) {
-            return x.abs().min(axis);
-          }
-          if (p === "euclidean" || p === 2) {
-            // norm(x, 2) = sum(abs(xi) ^ 2) ^ 1/2
-            return x.abs().pow(Object(tensor_ops["e" /* scalar */])(2, "int32")).sum(axis).sqrt();
-          }
-          throw new Error(`Error in norm: invalid ord value: ${p}`);
-        }
-        // matrix (assumption axis[0] < axis[1])
-        if (Array.isArray(axis) && axis.length === 2) {
-          if (p === 1) {
-            return x
-              .abs()
-              .sum(axis[0])
-              .max(axis[1] - 1);
-          }
-          if (p === Infinity) {
-            return x.abs().sum(axis[1]).max(axis[0]);
-          }
-          if (p === -Infinity) {
-            return x.abs().sum(axis[1]).min(axis[0]);
-          }
-          if (p === "fro" || p === "euclidean") {
-            // norm(x) = sqrt(sum(pow(x, 2)))
-            return x.square().sum(axis).sqrt();
-          }
-          throw new Error(`Error in norm: invalid ord value: ${p}`);
-        }
-        throw new Error(`Error in norm: invalid axis: ${axis}`);
-      }
-      const norm_norm = Object(operation["a" /* op */])({ norm_ });
-      //# sourceMappingURL=norm.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/lstm.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes the next states and outputs of a stack of LSTMCells.
-       *
-       * Each cell output is used as input to the next cell.
-       *
-       * Returns `[cellState, cellOutput]`.
-       *
-       * Derived from tf.contrib.rn.MultiRNNCell.
-       *
-       * @param lstmCells Array of LSTMCell functions.
-       * @param data The input to the cell.
-       * @param c Array of previous cell states.
-       * @param h Array of previous cell outputs.
-       */
-      /** @doc {heading: 'Operations', subheading: 'RNN'} */
-      function multiRNNCell_(lstmCells, data, c, h) {
-        const $data = Object(tensor_util_env["a" /* convertToTensor */])(
-          data,
-          "data",
-          "multiRNNCell"
-        );
-        const $c = Object(tensor_util_env["b" /* convertToTensorArray */])(c, "c", "multiRNNCell");
-        const $h = Object(tensor_util_env["b" /* convertToTensorArray */])(h, "h", "multiRNNCell");
-        let input = $data;
-        const newStates = [];
-        for (let i = 0; i < lstmCells.length; i++) {
-          const output = lstmCells[i](input, $c[i], $h[i]);
-          newStates.push(output[0]);
-          newStates.push(output[1]);
-          input = output[1];
-        }
-        const newC = [];
-        const newH = [];
-        for (let i = 0; i < newStates.length; i += 2) {
-          newC.push(newStates[i]);
-          newH.push(newStates[i + 1]);
-        }
-        return [newC, newH];
-      }
-      /**
-       * Computes the next state and output of a BasicLSTMCell.
-       *
-       * Returns `[newC, newH]`.
-       *
-       * Derived from tf.contrib.rnn.BasicLSTMCell.
-       *
-       * @param forgetBias Forget bias for the cell.
-       * @param lstmKernel The weights for the cell.
-       * @param lstmBias The bias for the cell.
-       * @param data The input to the cell.
-       * @param c Previous cell state.
-       * @param h Previous cell output.
-       */
-      /** @doc {heading: 'Operations', subheading: 'RNN'} */
-      function basicLSTMCell_(forgetBias, lstmKernel, lstmBias, data, c, h) {
-        const $forgetBias = Object(tensor_util_env["a" /* convertToTensor */])(
-          forgetBias,
-          "forgetBias",
-          "basicLSTMCell"
-        );
-        const $lstmKernel = Object(tensor_util_env["a" /* convertToTensor */])(
-          lstmKernel,
-          "lstmKernel",
-          "basicLSTMCell"
-        );
-        const $lstmBias = Object(tensor_util_env["a" /* convertToTensor */])(
-          lstmBias,
-          "lstmBias",
-          "basicLSTMCell"
-        );
-        const $data = Object(tensor_util_env["a" /* convertToTensor */])(
-          data,
-          "data",
-          "basicLSTMCell"
-        );
-        const $c = Object(tensor_util_env["a" /* convertToTensor */])(c, "c", "basicLSTMCell");
-        const $h = Object(tensor_util_env["a" /* convertToTensor */])(h, "h", "basicLSTMCell");
-        const combined = $data.concat($h, 1);
-        const weighted = combined.matMul($lstmKernel);
-        const res = weighted.add($lstmBias);
-        // i = input_gate, j = new_input, f = forget_gate, o = output_gate
-        const batchSize = res.shape[0];
-        const sliceCols = res.shape[1] / 4;
-        const sliceSize = [batchSize, sliceCols];
-        const i = res.slice([0, 0], sliceSize);
-        const j = res.slice([0, sliceCols], sliceSize);
-        const f = res.slice([0, sliceCols * 2], sliceSize);
-        const o = res.slice([0, sliceCols * 3], sliceSize);
-        const newC = i
-          .sigmoid()
-          .mul(j.tanh())
-          .add($c.mul($forgetBias.add(f).sigmoid()));
-        const newH = newC.tanh().mul(o.sigmoid());
-        return [newC, newH];
-      }
-      const basicLSTMCell = Object(operation["a" /* op */])({ basicLSTMCell_ });
-      const multiRNNCell = Object(operation["a" /* op */])({ multiRNNCell_ });
-      //# sourceMappingURL=lstm.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/moving_average.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Compute the moving average of a variable.
-       *
-       * Without zeroDebias, the moving average operation is defined by:
-       *   `v += delta`
-       * where
-       *   `delta = (1 - decay) * (x - v)`
-       *
-       * With zeroDebias (default), the `delta` term is scaled to debias the
-       * effect of the (assumed) zero-initialization of `v`.
-       *   `delta /= (1 - decay ^ step)`
-       *
-       * For more details on the zero-debiasing algorithm, see:
-       *   https://arxiv.org/abs/1412.6980
-       *
-       * Note that this function is completely stateless and does not keep track of
-       * step count. The step count needs to be maintained by the caller and passed
-       * in as `step`.
-       *
-       * @param v The current moving average value.
-       * @param x New input value, must have the same shape and dtype as `v`.
-       * @param decay The decay factor. Typical values are 0.95 and 0.99.
-       * @param step Step count.
-       * @param zeroDebias: Whether zeroDebias is to be performed (default: `true`).
-       * @returns The new moving average value.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Moving Average'} */
-      function movingAverage_(v, x, decay, step, zeroDebias = true) {
-        const $v = Object(tensor_util_env["a" /* convertToTensor */])(v, "v", "movingAverage");
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "movingAverage");
-        const $decay = Object(tensor_util_env["a" /* convertToTensor */])(
-          decay,
-          "decay",
-          "movingAverage"
-        );
-        Object(tensor_util["assertTypesMatch"])($v, $x);
-        util["assert"](util["arraysEqual"]($v.shape, $x.shape), () => "Shape mismatch in v and x");
-        const one = Object(tensor_ops["e" /* scalar */])(1);
-        const oneMinusDecay = one.sub($decay);
-        let update = $x.sub($v).mul(oneMinusDecay);
-        if (zeroDebias) {
-          util["assert"](step != null, () => "When using zeroDebias: true, step is required.");
-          const $step = Object(tensor_util_env["a" /* convertToTensor */])(
-            step,
-            "step",
-            "movingAverage"
-          );
-          update = update.div(one.sub(pow($decay, $step)));
-        }
-        return $v.add(update);
-      }
-      const movingAverage = Object(operation["a" /* op */])({ movingAverage_ });
-      //# sourceMappingURL=moving_average.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/strided_slice.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Extracts a strided slice of a tensor.
-       *
-       * Roughly speaking, this op extracts a slice of size (end-begin)/stride from
-       * the given input tensor (x). Starting at the location specified by begin the
-       * slice continues by adding stride to the index until all dimensions are not
-       * less than end. Note that a stride can be negative, which causes a reverse
-       * slice.
-       *
-       * ```js
-       * const t = tf.tensor3d([1, 1, 1 ,2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6],
-       *    [3, 2, 3]);
-       * t.stridedSlice([1, 0, 0], [2, 1, 3], [1, 1, 1]).print()  // [[[3, 3, 3]]]
-       * t.stridedSlice([1, 0, 0], [2, 2, 3], [1, 1, 1]).print()  // [[[3, 3, 3],
-       *                                                     // [4, 4, 4]]]
-       * t.stridedSlice([1, -1, 0], [2, -3, 3], [1, -1, 1]).print() // [[[4, 4, 4],
-       *                                                     // [3, 3, 3]]]
-       * ```
-       *
-       * @param x The tensor to stride slice.
-       * @param begin The coordinates to start the slice from.
-       * @param end: The coordinates to end the slice at.
-       * @param strides: The size of the slice.
-       * @param beginMask: If the ith bit of beginMask is set, begin[i] is ignored
-       *      and the fullest possible range in that dimension is used instead.
-       * @param endMask: If the ith bit of endMask is set, end[i] is ignored
-       *      and the fullest possible range in that dimension is used instead.
-       * @param shrinkAxisMask: a bitmask where bit i implies that
-       * the ith specification should shrink the dimensionality. begin and end must
-       * imply a slice of size 1 in the dimension.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Slicing and Joining'} */
-      function stridedSlice_(
-        x,
-        begin,
-        end,
-        strides,
-        beginMask = 0,
-        endMask = 0,
-        ellipsisMask = 0,
-        newAxisMask = 0,
-        shrinkAxisMask = 0
-      ) {
-        if (strides == null) {
-          strides = new Array(begin.length);
-        }
-        const ellipsisAxes = maskToAxes(ellipsisMask);
-        if (ellipsisAxes.length > 1) {
-          throw new Error("Multiple ellipses in slice is not allowed.");
-        }
-        if (ellipsisMask !== 0 && newAxisMask !== 0) {
-          throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");
-        }
-        if (ellipsisMask !== 0 && shrinkAxisMask !== 0) {
-          throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");
-        }
-        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "stridedSlice");
-        const numInterpolatedAxes = $x.rank - begin.length;
-        // Expand the dims of x based on the newAxisMask.
-        const expandAxes = maskToAxes(newAxisMask);
-        const newShape = $x.shape.slice();
-        expandAxes.forEach((axis) => {
-          begin[axis] = 0;
-          end[axis] = 1;
-          newShape.splice(axis, 0, 1);
-        });
-        $x = $x.reshape(newShape);
-        // Normalize the start, end and strides.
-        for (let axis = 0; axis < $x.rank; axis++) {
-          begin[axis] = startForAxis(beginMask, begin, strides, $x.shape, axis, ellipsisMask);
-          end[axis] = stopForAxis(endMask, end, strides, $x.shape, axis, ellipsisMask);
-          strides[axis] = stridesForAxis(strides, axis, ellipsisMask);
-        }
-        if (ellipsisAxes.length && numInterpolatedAxes > 0) {
-          const fullIndex = ellipsisAxes[0];
-          // The ellipsis applies to the masked index as well as any dimensions that
-          // were interpolated as full selection.
-          const numElidedAxes = numInterpolatedAxes + 1;
-          begin = startIndicesWithElidedDims(begin, fullIndex, numElidedAxes);
-          end = stopIndicesWithElidedDims(end, fullIndex, numElidedAxes, $x.shape);
-          strides = stridesWithElidedDims(strides, fullIndex, numElidedAxes);
-        }
-        const shrinkAxes = maskToAxes(shrinkAxisMask);
-        // Adjust the ends based on the shrink mask.
-        shrinkAxes.forEach((axis) => {
-          end[axis] = begin[axis] + 1;
-          strides[axis] = 1;
-        });
-        // Figure out the output shape.
-        const size = slice_util_computeOutShape(begin, end, strides);
-        // Remove the axes based on shrinkMask.
-        const outShape = size.filter((_, axis) => shrinkAxes.indexOf(axis) === -1);
-        const nonStrided = strides.every((v) => v === 1);
-        if (nonStrided) {
-          return slice($x, begin, size).reshape(outShape);
-        }
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.stridedSlice($x, begin, end, strides),
-          { $x }
-        );
-        return res.reshape(outShape);
-      }
-      const stridedSlice = Object(operation["a" /* op */])({ stridedSlice_ });
-      //# sourceMappingURL=strided_slice.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/topk.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Finds the values and indices of the `k` largest entries along the last
-       * dimension.
-       *
-       * If the input is a vector (rank=1), finds the k largest entries in the vector
-       * and outputs their values and indices as vectors. Thus values[j] is the j-th
-       * largest entry in input, and its index is indices[j].
-       * For higher rank inputs, computes the top k entries along the last dimension.
-       *
-       * If two elements are equal, the lower-index element appears first.
-       *
-       * ```js
-       * const a = tf.tensor2d([[1, 5], [4, 3]]);
-       * const {values, indices} = tf.topk(a);
-       * values.print();
-       * indices.print();
-       * ```
-       * @param x 1-D or higher `tf.Tensor` with last dimension being at least `k`.
-       * @param k Number of top elements to look for along the last dimension.
-       * @param sorted If true, the resulting `k` elements will be sorted by the
-       *     values in descending order.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Evaluation'} */
-      function topk_(x, k = 1, sorted = true) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "topk");
-        if ($x.rank === 0) {
-          throw new Error("topk() expects the input to be of rank 1 or higher");
-        }
-        const lastDim = $x.shape[$x.shape.length - 1];
-        if (k > lastDim) {
-          throw new Error(
-            `'k' passed to topk() must be <= the last dimension (${lastDim}) ` + `but got ${k}`
-          );
-        }
-        const [values, indices] = engine["a" /* ENGINE */].runKernelFunc(
-          (b) => b.topk($x, k, sorted),
-          { $x }
-        );
-        return { values, indices };
-      }
-      const topk = Object(operation["a" /* op */])({ topk_ });
-      //# sourceMappingURL=topk.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a new tensor by applying sparse updates to individual
-       * values or slices within a zero tensor of the given shape tensor according to
-       * indices. This operator is the inverse of the `tf.gatherND` operator which
-       * extracts values or slices from a given tensor.
-       *
-       * ```js
-       * const indices = tf.tensor2d([4, 3, 1, 7], [4, 1], 'int32');
-       * const updates = tf.tensor1d([9, 10, 11, 12]);
-       * const shape = [8];
-       * tf.scatterND(indices, updates, shape).print() //[0, 11, 0, 10, 9, 0, 0, 12]
-       * ```
-       *
-       * @param indices The tensor contains the indices into the output tensor.
-       * @param updates The tensor contains the value for the indices.
-       * @param shape: The shape of the output tensor.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Slicing and Joining'} */
-      function scatterND_(indices, updates, shape) {
-        const $indices = Object(tensor_util_env["a" /* convertToTensor */])(
-          indices,
-          "indices",
-          "scatterND",
-          "int32"
-        );
-        const $updates = Object(tensor_util_env["a" /* convertToTensor */])(
-          updates,
-          "updates",
-          "scatterND"
-        );
-        validateInput($updates, $indices, shape);
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) => backend.scatterND($indices, $updates, shape),
-          { indices: $indices, updates: $updates },
-          null /* backward */,
-          "ScatterNd",
-          { shape }
-        );
-      }
-      const scatterND = Object(operation["a" /* op */])({ scatterND_ });
-      //# sourceMappingURL=scatter_nd.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/spectral_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Fast Fourier transform.
-       *
-       * Computes the 1-dimensional discrete Fourier transform over the inner-most
-       * dimension of input.
-       *
-       * ```js
-       * const real = tf.tensor1d([1, 2, 3]);
-       * const imag = tf.tensor1d([1, 2, 3]);
-       * const x = tf.complex(real, imag);
-       *
-       * x.fft().print();  // tf.spectral.fft(x).print();
-       * ```
-       * @param input The complex input to compute an fft over.
-       */
-      /**
-       * @doc {heading: 'Operations', subheading: 'Spectral', namespace: 'spectral'}
-       */
-      function fft_(input) {
-        Object(util["assert"])(
-          input.dtype === "complex64",
-          () => `The dtype for tf.spectral.fft() must be complex64 ` + `but got ${input.dtype}.`
-        );
-        // Collapse all outer dimensions to a single batch dimension.
-        const innerDimensionSize = input.shape[input.shape.length - 1];
-        const batch = input.size / innerDimensionSize;
-        const input2D = input.as2D(batch, innerDimensionSize);
-        const ret = engine["a" /* ENGINE */].runKernelFunc((backend) => backend.fft(input2D), {
-          input,
-        });
-        return ret.reshape(input.shape);
-      }
-      /**
-       * Inverse fast Fourier transform.
-       *
-       * Computes the inverse 1-dimensional discrete Fourier transform over the
-       * inner-most dimension of input.
-       *
-       * ```js
-       * const real = tf.tensor1d([1, 2, 3]);
-       * const imag = tf.tensor1d([1, 2, 3]);
-       * const x = tf.complex(real, imag);
-       *
-       * x.ifft().print();  // tf.spectral.ifft(x).print();
-       * ```
-       * @param input The complex input to compute an ifft over.
-       */
-      /**
-       * @doc {heading: 'Operations', subheading: 'Spectral', namespace: 'spectral'}
-       */
-      function ifft_(input) {
-        Object(util["assert"])(
-          input.dtype === "complex64",
-          () => `The dtype for tf.spectral.ifft() must be complex64 ` + `but got ${input.dtype}.`
-        );
-        // Collapse all outer dimensions to a single batch dimension.
-        const innerDimensionSize = input.shape[input.shape.length - 1];
-        const batch = input.size / innerDimensionSize;
-        const input2D = input.as2D(batch, innerDimensionSize);
-        const ret = engine["a" /* ENGINE */].runKernelFunc((backend) => backend.ifft(input2D), {
-          input,
-        });
-        return ret.reshape(input.shape);
-      }
-      /**
-       * Real value input fast Fourier transform.
-       *
-       * Computes the 1-dimensional discrete Fourier transform over the
-       * inner-most dimension of the real input.
-       *
-       * ```js
-       * const real = tf.tensor1d([1, 2, 3]);
-       *
-       * real.rfft().print();
-       * ```
-       * @param input The real value input to compute an rfft over.
-       */
-      /**
-       * @doc {heading: 'Operations', subheading: 'Spectral', namespace: 'spectral'}
-       */
-      function rfft_(input, fftLength) {
-        Object(util["assert"])(
-          input.dtype === "float32",
-          () => `The dtype for rfft() must be real value but got ${input.dtype}`
-        );
-        let innerDimensionSize = input.shape[input.shape.length - 1];
-        const batch = input.size / innerDimensionSize;
-        let adjustedInput;
-        if (fftLength != null && fftLength < innerDimensionSize) {
-          // Need to crop
-          const begin = input.shape.map((v) => 0);
-          const size = input.shape.map((v) => v);
-          size[input.shape.length - 1] = fftLength;
-          adjustedInput = input.slice(begin, size);
-          innerDimensionSize = fftLength;
-        } else if (fftLength != null && fftLength > innerDimensionSize) {
-          // Need to pad with zeros
-          const zerosShape = input.shape.map((v) => v);
-          zerosShape[input.shape.length - 1] = fftLength - innerDimensionSize;
-          adjustedInput = input.concat(
-            Object(tensor_ops["n" /* zeros */])(zerosShape),
-            input.shape.length - 1
-          );
-          innerDimensionSize = fftLength;
-        } else {
-          adjustedInput = input;
-        }
-        // Complement the input with zero imaginary numbers.
-        const zerosInput = adjustedInput.zerosLike();
-        const complexInput = Object(complex["a" /* complex */])(adjustedInput, zerosInput).as2D(
-          batch,
-          innerDimensionSize
-        );
-        const ret = fft(complexInput);
-        // Exclude complex conjugations. These conjugations are put symmetrically.
-        const half = Math.floor(innerDimensionSize / 2) + 1;
-        const realValues = Object(real["a" /* real */])(ret);
-        const imagValues = Object(imag["a" /* imag */])(ret);
-        const realComplexConjugate = realValues.split(
-          [half, innerDimensionSize - half],
-          realValues.shape.length - 1
-        );
-        const imagComplexConjugate = imagValues.split(
-          [half, innerDimensionSize - half],
-          imagValues.shape.length - 1
-        );
-        const outputShape = adjustedInput.shape.slice();
-        outputShape[adjustedInput.shape.length - 1] = half;
-        return Object(complex["a" /* complex */])(
-          realComplexConjugate[0],
-          imagComplexConjugate[0]
-        ).reshape(outputShape);
-      }
-      /**
-       * Inversed real value input fast Fourier transform.
-       *
-       * Computes the 1-dimensional inversed discrete Fourier transform over the
-       * inner-most dimension of the real input.
-       *
-       * ```js
-       * const real = tf.tensor1d([1, 2, 3]);
-       * const imag = tf.tensor1d([0, 0, 0]);
-       * const x = tf.complex(real, imag);
-       *
-       * x.irfft().print();
-       * ```
-       * @param input The real value input to compute an irfft over.
-       */
-      /**
-       * @doc {heading: 'Operations', subheading: 'Spectral', namespace: 'spectral'}
-       */
-      function irfft_(input) {
-        const innerDimensionSize = input.shape[input.shape.length - 1];
-        const batch = input.size / innerDimensionSize;
-        if (innerDimensionSize <= 2) {
-          const complexInput = input.as2D(batch, innerDimensionSize);
-          const ret = ifft(complexInput);
-          return Object(real["a" /* real */])(ret);
-        } else {
-          // The length of unique components of the DFT of a real-valued signal
-          // is 2 * (input_len - 1)
-          const outputShape = [batch, 2 * (innerDimensionSize - 1)];
-          const realInput = Object(real["a" /* real */])(input).as2D(batch, innerDimensionSize);
-          const imagInput = Object(imag["a" /* imag */])(input).as2D(batch, innerDimensionSize);
-          const realConjugate = realInput.slice([0, 1], [batch, innerDimensionSize - 2]).reverse(1);
-          const imagConjugate = imagInput
-            .slice([0, 1], [batch, innerDimensionSize - 2])
-            .reverse(1)
-            .mul(Object(tensor_ops["e" /* scalar */])(-1));
-          const r = realInput.concat(realConjugate, 1);
-          const i = imagInput.concat(imagConjugate, 1);
-          const complexInput = Object(complex["a" /* complex */])(r, i).as2D(
-            outputShape[0],
-            outputShape[1]
-          );
-          const ret = ifft(complexInput);
-          return Object(real["a" /* real */])(ret);
-        }
-      }
-      const fft = Object(operation["a" /* op */])({ fft_ });
-      const ifft = Object(operation["a" /* op */])({ ifft_ });
-      const rfft = Object(operation["a" /* op */])({ rfft_ });
-      const irfft = Object(operation["a" /* op */])({ irfft_ });
-      //# sourceMappingURL=spectral_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/sparse_to_dense_util.js
-      /**
-       * Validate sparseToDense inputs.
-       *
-       * @param sparseIndices A 0-D, 1-D, or 2-D Tensor of type int32.
-       * sparseIndices[i] contains the complete index where sparseValues[i] will be
-       * placed.
-       * @param sparseValues A 0-D or 1-D Tensor. Values
-       * corresponding to each row of sparseIndices, or a scalar value to be used for
-       * all sparse indices.
-       * @param outputShape number[]. Shape of the dense output tensor.
-       * @param validateIndices boolean. indice validation is not supported, error
-       * will be thrown if it is set.
-       */
-      function sparse_to_dense_util_validateInput(
-        sparseIndices,
-        sparseValues,
-        outputShape,
-        defaultValues
-      ) {
-        if (sparseIndices.dtype !== "int32") {
-          throw new Error(
-            "tf.sparseToDense() expects the indices to be int32 type," +
-              ` but the dtype was ${sparseIndices.dtype}.`
-          );
-        }
-        if (sparseIndices.rank > 2) {
-          throw new Error(
-            "sparseIndices should be a scalar, vector, or matrix," +
-              ` but got shape ${sparseIndices.shape}.`
-          );
-        }
-        const numElems = sparseIndices.rank > 0 ? sparseIndices.shape[0] : 1;
-        const numDims = sparseIndices.rank > 1 ? sparseIndices.shape[1] : 1;
-        if (outputShape.length !== numDims) {
-          throw new Error(
-            "outputShape has incorrect number of elements:," +
-              ` ${outputShape.length}, should be: ${numDims}.`
-          );
-        }
-        const numValues = sparseValues.size;
-        if (!(sparseValues.rank === 0 || (sparseValues.rank === 1 && numValues === numElems))) {
-          throw new Error(
-            "sparseValues has incorrect shape " +
-              `${sparseValues.shape}, should be [] or [${numElems}]`
-          );
-        }
-        if (sparseValues.dtype !== defaultValues.dtype) {
-          throw new Error("sparseValues.dtype must match defaultValues.dtype");
-        }
-      }
-      //# sourceMappingURL=sparse_to_dense_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/sparse_to_dense.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Converts a sparse representation into a dense tensor.
-       *
-       * Builds an array dense with shape outputShape such that:
-       *
-       * // If sparseIndices is scalar
-       * dense[i] = (i == sparseIndices ? sparseValues : defaultValue)
-       *
-       * // If sparseIndices is a vector, then for each i
-       * dense[sparseIndices[i]] = sparseValues[i]
-       *
-       * // If sparseIndices is an n by d matrix, then for each i in [0, n)
-       * dense[sparseIndices[i][0], ..., sparseIndices[i][d-1]] = sparseValues[i]
-       * All other values in dense are set to defaultValue. If sparseValues is a
-       * scalar, all sparse indices are set to this single value.
-       *
-       * If indices are repeated the final value is summed over all values for those
-       * indices.
-       *
-       * ```js
-       * const indices = tf.tensor1d([4, 5, 6, 1, 2, 3], 'int32');
-       * const values = tf.tensor1d([10, 11, 12, 13, 14, 15], 'float32');
-       * const shape = [8];
-       * tf.sparseToDense(indices, values, shape).print();
-       * ```
-       *
-       * @param sparseIndices A 0-D, 1-D, or 2-D Tensor of type int32.
-       * sparseIndices[i] contains the complete index where sparseValues[i] will be
-       * placed.
-       * @param sparseValues A 0-D or 1-D Tensor. Values
-       * corresponding to each row of sparseIndices, or a scalar value to be used for
-       * all sparse indices.
-       * @param outputShape Shape of the dense output tensor. the type is inferred.
-       * @param defaultValue Scalar. Value to set for indices not specified in
-       * sparseIndices. Defaults to zero.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
-      function sparseToDense_(sparseIndices, sparseValues, outputShape, defaultValue = 0) {
-        const $sparseIndices = Object(tensor_util_env["a" /* convertToTensor */])(
-          sparseIndices,
-          "sparseIndices",
-          "sparseToDense",
-          "int32"
-        );
-        const $sparseValues = Object(tensor_util_env["a" /* convertToTensor */])(
-          sparseValues,
-          "sparseValues",
-          "sparseToDense"
-        );
-        const $defaultValue = Object(tensor_util_env["a" /* convertToTensor */])(
-          defaultValue,
-          "defaultValue",
-          "sparseToDense",
-          $sparseValues.dtype
-        );
-        sparse_to_dense_util_validateInput(
-          $sparseIndices,
-          $sparseValues,
-          outputShape,
-          $defaultValue
-        );
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (backend) =>
-            backend.sparseToDense($sparseIndices, $sparseValues, outputShape, $defaultValue),
-          { $sparseIndices, $sparseValues, $defaultValue }
-        );
-      }
-      const sparseToDense = Object(operation["a" /* op */])({ sparseToDense_ });
-      //# sourceMappingURL=sparse_to_dense.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Gather slices from input tensor into a Tensor with shape specified by
-       * `indices`.
-       *
-       * `indices` is an K-dimensional integer tensor, best thought of as a
-       * (K-1)-dimensional tensor of indices into input, where each element defines a
-       * slice of input:
-       * output[\\(i_0, ..., i_{K-2}\\)] = input[indices[\\(i_0, ..., i_{K-2}\\)]]
-       *
-       * Whereas in `tf.gather`, `indices` defines slices into the first dimension of
-       * input, in `tf.gatherND`, `indices` defines slices into the first N dimensions
-       * of input, where N = indices.shape[-1].
-       *
-       * The last dimension of indices can be at most the rank of input:
-       * indices.shape[-1] <= input.rank
-       *
-       * The last dimension of `indices` corresponds to elements
-       * (if indices.shape[-1] == input.rank) or slices
-       * (if indices.shape[-1] < input.rank) along dimension indices.shape[-1] of
-       * input.
-       * The output tensor has shape
-       * indices.shape[:-1] + input.shape[indices.shape[-1]:]
-       *
-       * Note that on CPU, if an out of bound index is found, an error is returned. On
-       * GPU, if an out of bound index is found, a 0 is stored in the corresponding
-       * output value.
-       *
-       * ```js
-       * const indices = tf.tensor2d([0, 1, 1, 0], [2,2], 'int32');
-       * const input = tf.tensor2d([9, 10, 11, 12], [2, 2]);
-       * tf.gatherND(input, indices).print() // [10, 11]
-       * ```
-       *
-       * @param x The tensor from which to gather values.
-       * @param indices Index tensor, must be of type int32.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Slicing and Joining'} */
-      function gatherND_(x, indices) {
-        const $indices = Object(tensor_util_env["a" /* convertToTensor */])(
-          indices,
-          "indices",
-          "gatherND",
-          "int32"
-        );
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "gatherND");
-        const forward = (backend) => {
-          return backend.gatherND($x, $indices);
-        };
-        const inputs = { params: $x, indices: $indices };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          kernel_names["G" /* GatherNd */]
-        );
-      }
-      const gatherND = Object(operation["a" /* op */])({ gatherND_ });
-      //# sourceMappingURL=gather_nd.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/dropout_util.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Normalize noise shape based on provided tensor and noise shape.
-       *
-       * @param x Tensor.
-       * @param noiseShape The shape for the randomly generated keep/drop flags, as
-       *   an array of numbers. Optional.
-       * @returns Normalized noise shape.
-       */
-      function getNoiseShape(x, noiseShape) {
-        if (noiseShape == null) {
-          return x.shape.slice();
-        }
-        if (util["arraysEqual"](x.shape, noiseShape)) {
-          return noiseShape;
-        }
-        if (x.shape.length === noiseShape.length) {
-          const newDimension = [];
-          for (let i = 0; i < x.shape.length; i++) {
-            if (noiseShape[i] == null && x.shape[i] != null) {
-              newDimension.push(x.shape[i]);
-            } else {
-              newDimension.push(noiseShape[i]);
-            }
-          }
-          return newDimension;
-        }
-        return noiseShape;
-      }
-      //# sourceMappingURL=dropout_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/dropout.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes dropout.
-       *
-       * ```js
-       * const x = tf.tensor1d([1, 2, 2, 1]);
-       * const rate = 0.75;
-       * const output = tf.dropout(x, rate);
-       * output.print();
-       * ```
-       *
-       * @param x A floating point Tensor or TensorLike.
-       * @param rate A float in the range [0, 1). The probability that each element
-       *   of x is discarded.
-       * @param noiseShape An array of numbers of type int32, representing the
-       * shape for randomly generated keep/drop flags. If the noiseShape has null
-       * value, it will be automatically replaced with the x's relative dimension
-       * size. Optional.
-       * @param seed Used to create random seeds. Optional.
-       * @returns A Tensor of the same shape of x.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Dropout'} */
-      function dropout_(x, rate, noiseShape, seed) {
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "dropout");
-        util["assert"](
-          $x.dtype === "float32",
-          () =>
-            `x has to be a floating point tensor since it's going to be ` +
-            `scaled, but got a ${$x.dtype} tensor instead.`
-        );
-        util["assert"](
-          rate >= 0 && rate < 1,
-          () => `rate must be a float in the range [0, 1), but got ${rate}.`
-        );
-        if (rate === 0) {
-          return x instanceof dist_tensor["a" /* Tensor */] ? $x.clone() : $x;
-        }
-        const $noiseShape = getNoiseShape($x, noiseShape);
-        const keepProb = 1 - rate;
-        const multiplier = randomUniform($noiseShape, 0, 1, "float32", seed)
-          .add(keepProb)
-          .floor()
-          .div(keepProb);
-        return $x.mul(multiplier);
-      }
-      const dropout = Object(operation["a" /* op */])({ dropout_ });
-      //# sourceMappingURL=dropout.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/signal_ops.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Generate a Hann window.
-       *
-       * See: https://en.wikipedia.org/wiki/Window_function#Hann_and_Hamming_windows
-       *
-       * ```js
-       * tf.signal.hannWindow(10).print();
-       * ```
-       * @param The length of window
-       */
-      /**
-       * @doc {heading: 'Operations', subheading: 'Signal', namespace: 'signal'}
-       */
-      function hannWindow_(windowLength) {
-        return cosineWindow(windowLength, 0.5, 0.5);
-      }
-      /**
-       * Generate a hamming window.
-       *
-       * See: https://en.wikipedia.org/wiki/Window_function#Hann_and_Hamming_windows
-       *
-       * ```js
-       * tf.signal.hammingWindow(10).print();
-       * ```
-       * @param The length of window
-       */
-      /**
-       * @doc {heading: 'Operations', subheading: 'Signal', namespace: 'signal'}
-       */
-      function hammingWindow_(windowLength) {
-        return cosineWindow(windowLength, 0.54, 0.46);
-      }
-      /**
-       * Expands input into frames of frameLength.
-       * Slides a window size with frameStep.
-       *
-       * ```js
-       * tf.signal.frame([1, 2, 3], 2, 1).print();
-       * ```
-       * @param signal The input tensor to be expanded
-       * @param frameLength Length of each frame
-       * @param frameStep The frame hop size in samples.
-       * @param padEnd Whether to pad the end of signal with padValue.
-       * @param padValue An number to use where the input signal does
-       *     not exist when padEnd is True.
-       */
-      /**
-       * @doc {heading: 'Operations', subheading: 'Signal', namespace: 'signal'}
-       */
-      function frame_(signal, frameLength, frameStep, padEnd = false, padValue = 0) {
-        let start = 0;
-        const output = [];
-        while (start + frameLength <= signal.size) {
-          output.push(slice(signal, start, frameLength));
-          start += frameStep;
-        }
-        if (padEnd) {
-          while (start < signal.size) {
-            const padLen = start + frameLength - signal.size;
-            const pad = concat([
-              slice(signal, start, frameLength - padLen),
-              fill([padLen], padValue),
-            ]);
-            output.push(pad);
-            start += frameStep;
-          }
-        }
-        if (output.length === 0) {
-          return Object(tensor_ops["h" /* tensor2d */])([], [0, frameLength]);
-        }
-        return concat(output).as2D(output.length, frameLength);
-      }
-      /**
-       * Computes the Short-time Fourier Transform of signals
-       * See: https://en.wikipedia.org/wiki/Short-time_Fourier_transform
-       *
-       * ```js
-       * const input = tf.tensor1d([1, 1, 1, 1, 1])
-       * tf.signal.stft(input, 3, 1).print();
-       * ```
-       * @param signal 1-dimensional real value tensor.
-       * @param frameLength The window length of samples.
-       * @param frameStep The number of samples to step.
-       * @param fftLength The size of the FFT to apply.
-       * @param windowFn A callable that takes a window length and returns 1-d tensor.
-       */
-      /**
-       * @doc {heading: 'Operations', subheading: 'Signal', namespace: 'signal'}
-       */
-      function stft_(signal, frameLength, frameStep, fftLength, windowFn = hannWindow) {
-        if (fftLength == null) {
-          fftLength = enclosingPowerOfTwo(frameLength);
-        }
-        const framedSignal = signal_ops_frame(signal, frameLength, frameStep);
-        const windowedSignal = mul(framedSignal, windowFn(frameLength));
-        const output = [];
-        for (let i = 0; i < framedSignal.shape[0]; i++) {
-          output.push(rfft(windowedSignal.slice([i, 0], [1, frameLength]), fftLength));
-        }
-        return concat(output);
-      }
-      function enclosingPowerOfTwo(value) {
-        // Return 2**N for integer N such that 2**N >= value.
-        return Math.floor(Math.pow(2, Math.ceil(Math.log(value) / Math.log(2.0))));
-      }
-      function cosineWindow(windowLength, a, b) {
-        const even = 1 - (windowLength % 2);
-        const newValues = new Float32Array(windowLength);
-        for (let i = 0; i < windowLength; ++i) {
-          const cosArg = (2.0 * Math.PI * i) / (windowLength + even - 1);
-          newValues[i] = a - b * Math.cos(cosArg);
-        }
-        return Object(tensor_ops["g" /* tensor1d */])(newValues, "float32");
-      }
-      const hannWindow = Object(operation["a" /* op */])({ hannWindow_ });
-      const hammingWindow = Object(operation["a" /* op */])({ hammingWindow_ });
-      const signal_ops_frame = Object(operation["a" /* op */])({ frame_ });
-      const stft = Object(operation["a" /* op */])({ stft_ });
-      //# sourceMappingURL=signal_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/in_top_k.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns whether the targets are in the top K predictions.
-       *
-       * ```js
-       * const predictions = tf.tensor2d([[20, 10, 40, 30], [30, 50, -20, 10]]);
-       * const targets = tf.tensor1d([2, 0]);
-       * const precision = await tf.inTopKAsync(predictions, targets);
-       * precision.print();
-       * ```
-       * @param predictions 2-D or higher `tf.Tensor` with last dimension being
-       *     at least `k`.
-       * @param targets 1-D or higher `tf.Tensor`.
-       * @param k Optional Number of top elements to look at for computing precision,
-       *     default to 1.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Evaluation'} */
-      async function inTopKAsync_(predictions, targets, k = 1) {
-        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
-          predictions,
-          "predictions",
-          "inTopK"
-        );
-        const $targets = Object(tensor_util_env["a" /* convertToTensor */])(
-          targets,
-          "targets",
-          "inTopK"
-        );
-        Object(util["assert"])(
-          $predictions.rank > 1,
-          () =>
-            "inTopK() expects the predictions to be of rank 2 or higher, " +
-            `but got ${$predictions.rank}`
-        );
-        Object(util["assert"])(
-          $predictions.rank - 1 === $targets.rank,
-          () =>
-            `predictions rank should be 1 larger than ` +
-            `targets rank, but got predictions rank ` +
-            `${$predictions.rank} and targets rank ${$targets.rank}`
-        );
-        Object(util["assertShapesMatch"])(
-          $predictions.shape.slice(0, $predictions.shape.length - 1),
-          $targets.shape,
-          `predictions's shape should be align with the targets' shape, ` +
-            "except the last dimension."
-        );
-        const lastDim = $predictions.shape[$predictions.shape.length - 1];
-        Object(util["assert"])(
-          k > 0 && k <= lastDim,
-          () =>
-            `'k' passed to inTopK() must be > 0 && <= the predictions last ` +
-            `dimension (${lastDim}), but got ${k}`
-        );
-        const predictionsVals = await $predictions.data();
-        const targetsVals = await $targets.data();
-        // Reshape predictionsVals into a 2d tensor [batch, lastDim]
-        // and look up topK along lastDim.
-        const [batch, size] = [predictionsVals.length / lastDim, lastDim];
-        const precision = Object(util["getTypedArrayFromDType"])("bool", batch);
-        for (let b = 0; b < batch; b++) {
-          const offset = b * size;
-          const vals = predictionsVals.subarray(offset, offset + size);
-          const valAndInd = [];
-          for (let i = 0; i < vals.length; i++) {
-            valAndInd.push({ value: vals[i], index: i });
-          }
-          valAndInd.sort((a, b) => b.value - a.value);
-          precision[b] = 0;
-          for (let i = 0; i < k; i++) {
-            if (valAndInd[i].index === targetsVals[b]) {
-              precision[b] = 1;
-              break;
-            }
-          }
-        }
-        if (predictions !== $predictions) {
-          $predictions.dispose();
-        }
-        if (targets !== $targets) {
-          $targets.dispose();
-        }
-        // Output precision has the same shape as targets.
-        return Object(tensor_ops["f" /* tensor */])(precision, $targets.shape, "bool");
-      }
-      const inTopKAsync = inTopKAsync_;
-      //# sourceMappingURL=in_top_k.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/loss_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      var Reduction;
-      (function (Reduction) {
-        Reduction[(Reduction["NONE"] = 0)] = "NONE";
-        Reduction[(Reduction["MEAN"] = 1)] = "MEAN";
-        Reduction[(Reduction["SUM"] = 2)] = "SUM";
-        Reduction[(Reduction["SUM_BY_NONZERO_WEIGHTS"] = 3)] = "SUM_BY_NONZERO_WEIGHTS";
-      })(Reduction || (Reduction = {}));
-      /**
-       * Computes the weighted loss between two tensors.
-       *
-       * @param losses Tensor of shape `[batch_size, d1, ... dN]`.
-       * @param weights Tensor whose rank is either 0, or the same rank as
-       *    `losses`, and must be broadcastable to `losses` (i.e., all
-       *    dimensions must be either `1`, or the same as the corresponding
-       *    `losses` dimension).
-       */
-      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
-      function computeWeightedLoss_(losses, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {
-        const $losses = Object(tensor_util_env["a" /* convertToTensor */])(
-          losses,
-          "losses",
-          "computeWeightedLoss"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "computeWeightedLoss"
-          );
-        }
-        const weightedLoss = $weights == null ? $losses : $losses.mul($weights);
-        if (reduction === Reduction.NONE) {
-          return weightedLoss;
-        }
-        if (reduction === Reduction.SUM) {
-          return weightedLoss.sum();
-        }
-        if (reduction === Reduction.MEAN) {
-          if ($weights == null) {
-            return weightedLoss.mean();
-          } else {
-            const broadcastFactor = $losses.size / $weights.size;
-            const result = weightedLoss.sum().div($weights.sum());
-            return broadcastFactor > 1
-              ? result.div(Object(tensor_ops["e" /* scalar */])(broadcastFactor))
-              : result;
-          }
-        }
-        if (reduction === Reduction.SUM_BY_NONZERO_WEIGHTS) {
-          if ($weights == null) {
-            return weightedLoss.sum().div(Object(tensor_ops["e" /* scalar */])($losses.size));
-          } else {
-            const broadcastedWeights = $weights.mul(
-              Object(tensor_ops["b" /* ones */])($losses.shape)
-            );
-            const numNonZeros = broadcastedWeights
-              .notEqual(Object(tensor_ops["e" /* scalar */])(0))
-              .sum()
-              .toFloat();
-            return weightedLoss.sum().div(numNonZeros);
-          }
-        }
-        throw Error(`Unknown reduction: ${reduction}`);
-      }
-      /**
-       * Computes the absolute difference loss between two tensors.
-       *
-       * @param labels The ground truth output tensor, same dimensions as
-       *    'predictions'.
-       * @param predictions The predicted outputs.
-       * @param weights Tensor whose rank is either 0, or the same rank as
-       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
-       *    must be either `1`, or the same as the corresponding `losses`
-       *    dimension).
-       * @param reduction Type of reduction to apply to loss. Should be of type
-       *    `Reduction`
-       */
-      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
-      function absoluteDifference_(
-        labels,
-        predictions,
-        weights,
-        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
-      ) {
-        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
-          labels,
-          "labels",
-          "absoluteDifference"
-        );
-        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
-          predictions,
-          "predictions",
-          "absoluteDifference"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "absoluteDifference"
-          );
-        }
-        Object(util["assertShapesMatch"])(
-          $labels.shape,
-          $predictions.shape,
-          "Error in absoluteDifference: "
-        );
-        const losses = $labels.sub($predictions).abs();
-        return computeWeightedLoss(losses, $weights, reduction);
-      }
-      /**
-       * Computes the mean squared error between two tensors.
-       *
-       * @param labels The ground truth output tensor, same dimensions as
-       *    'predictions'.
-       * @param predictions The predicted outputs.
-       * @param weights Tensor whose rank is either 0, or the same rank as
-       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
-       *    must be either `1`, or the same as the corresponding `losses`
-       *    dimension).
-       * @param reduction Type of reduction to apply to loss. Should be of type
-       *    `Reduction`
-       */
-      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
-      function meanSquaredError_(
-        labels,
-        predictions,
-        weights,
-        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
-      ) {
-        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
-          labels,
-          "labels",
-          "meanSquaredError"
-        );
-        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
-          predictions,
-          "predictions",
-          "meanSquaredError"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "meanSquaredError"
-          );
-        }
-        Object(util["assertShapesMatch"])(
-          $labels.shape,
-          $predictions.shape,
-          "Error in meanSquaredError: "
-        );
-        const losses = $labels.squaredDifference($predictions);
-        return computeWeightedLoss(losses, $weights, reduction);
-      }
-      /**
-       * Computes the cosine distance loss between two tensors.
-       *
-       * @param labels The ground truth output tensor, same dimensions as
-       *    'predictions'.
-       * @param predictions The predicted outputs.
-       * @param axis The dimension along which the cosine distance is computed.
-       * @param weights Tensor whose rank is either 0, or the same rank as
-       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
-       *    must be either `1`, or the same as the corresponding `losses`
-       *    dimension).
-       * @param reduction Type of reduction to apply to loss. Should be of type
-       *    `Reduction`
-       */
-      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
-      function cosineDistance_(
-        labels,
-        predictions,
-        axis,
-        weights,
-        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
-      ) {
-        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
-          labels,
-          "labels",
-          "cosineDistance"
-        );
-        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
-          predictions,
-          "predictions",
-          "cosineDistance"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "cosineDistance"
-          );
-        }
-        Object(util["assertShapesMatch"])(
-          $labels.shape,
-          $predictions.shape,
-          "Error in cosineDistance: "
-        );
-        const one = Object(tensor_ops["e" /* scalar */])(1);
-        const losses = one.sub($labels.mul($predictions).sum(axis, true));
-        return computeWeightedLoss(losses, $weights, reduction);
-      }
-      /**
-       * Computes the Hinge loss between two tensors.
-       *
-       * @param labels The ground truth output tensor, same dimensions as
-       *    'predictions'.
-       * @param predictions The predicted outputs.
-       * @param weights Tensor whose rank is either 0, or the same rank as
-       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
-       *    must be either `1`, or the same as the corresponding `losses`
-       *    dimension).
-       * @param reduction Type of reduction to apply to loss. Should be of type
-       *    `Reduction`
-       */
-      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
-      function hingeLoss_(
-        labels,
-        predictions,
-        weights,
-        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
-      ) {
-        let $labels = Object(tensor_util_env["a" /* convertToTensor */])(
-          labels,
-          "labels",
-          "hingeLoss"
-        );
-        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
-          predictions,
-          "predictions",
-          "hingeLoss"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "hingeLoss"
-          );
-        }
-        Object(util["assertShapesMatch"])(
-          $labels.shape,
-          $predictions.shape,
-          "Error in hingeLoss: "
-        );
-        const one = Object(tensor_ops["e" /* scalar */])(1);
-        // Convert binary labels to (-1, 1)
-        $labels = Object(tensor_ops["e" /* scalar */])(2).mul($labels).sub(one);
-        const losses = one.sub($labels.mul($predictions)).relu();
-        return computeWeightedLoss(losses, $weights, reduction);
-      }
-      /**
-       * Computes the log loss between two tensors.
-       *
-       * @param labels The ground truth output tensor, same dimensions as
-       *    'predictions'.
-       * @param predictions The predicted outputs.
-       * @param weights Tensor whose rank is either 0, or the same rank as
-       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
-       *    must be either `1`, or the same as the corresponding `losses`
-       *    dimension).
-       * @param epsilon A small increment to avoid taking log of zero
-       * @param reduction Type of reduction to apply to loss. Should be of type
-       *    `Reduction`
-       */
-      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
-      function logLoss_(
-        labels,
-        predictions,
-        weights,
-        epsilon = 1e-7,
-        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
-      ) {
-        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
-          labels,
-          "labels",
-          "logLoss"
-        );
-        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
-          predictions,
-          "predictions",
-          "logLoss"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "logLoss"
-          );
-        }
-        Object(util["assertShapesMatch"])($labels.shape, $predictions.shape, "Error in logLoss: ");
-        const one = Object(tensor_ops["e" /* scalar */])(1);
-        const epsilonScalar = Object(tensor_ops["e" /* scalar */])(epsilon);
-        const losses = $labels
-          .mul($predictions.add(epsilonScalar).log())
-          .neg()
-          .sub(one.sub($labels).mul(one.sub($predictions).add(epsilonScalar).log()));
-        return computeWeightedLoss(losses, $weights, reduction);
-      }
-      function sigmoidCrossEntropyWithLogits_(labels, logits) {
-        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
-          labels,
-          "labels",
-          "sigmoidCrossEntropyWithLogits"
-        );
-        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
-          logits,
-          "logits",
-          "sigmoidCrossEntropyWithLogits"
-        );
-        Object(util["assertShapesMatch"])(
-          $labels.shape,
-          $logits.shape,
-          "Error in sigmoidCrossEntropyWithLogits: "
-        );
-        /**
-         * Implementation Details:
-         *
-         * For brevity, let `x = logits`, `z = labels`.  The logistic loss is
-         *     z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
-         *   = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
-         *   = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
-         *   = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
-         *   = (1 - z) * x + log(1 + exp(-x))
-         *   = x - x * z + log(1 + exp(-x))
-         *
-         *   For x < 0, to avoid overflow in exp(-x), we reformulate the above
-         *     x - x * z + log(1 + exp(-x))
-         *   = log(exp(x)) - x * z + log(1 + exp(-x))
-         *   = - x * z + log(1 + exp(x))
-         *
-         * Hence, to ensure stability and avoid overflow, the implementation uses
-         * this equivalent formulation:
-         *     max(x, 0) - x * z + log(1 + exp(-abs(x)))
-         */
-        const maxOutput = $logits.relu();
-        const outputXTarget = $logits.mul($labels);
-        const sigmoidOutput = $logits.abs().neg().exp().log1p();
-        return maxOutput.sub(outputXTarget).add(sigmoidOutput);
-      }
-      /**
-       * Computes the sigmoid cross entropy loss between two tensors.
-       *
-       * If labelSmoothing is nonzero, smooth the labels towards 1/2:
-       *
-       *   newMulticlassLabels = multiclassLabels * (1 - labelSmoothing)
-       *                         + 0.5 * labelSmoothing
-       *
-       * @param multiClassLabels The ground truth output tensor of shape
-       * [batch_size, num_classes], same dimensions as 'predictions'.
-       * @param logits The predicted outputs.
-       * @param weights Tensor whose rank is either 0, or the same rank as
-       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
-       *    must be either `1`, or the same as the corresponding `losses`
-       *    dimension).
-       * @param labelSmoothing If greater than 0, then smooth the labels.
-       * @param reduction Type of reduction to apply to loss. Should be of type
-       *    `Reduction`
-       */
-      /** @doc { heading: 'Training', subheading: 'Losses', namespace: 'losses' } */
-      function sigmoidCrossEntropy_(
-        multiClassLabels,
-        logits,
-        weights,
-        labelSmoothing = 0,
-        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
-      ) {
-        let $multiClassLabels = Object(tensor_util_env["a" /* convertToTensor */])(
-          multiClassLabels,
-          "multiClassLabels",
-          "sigmoidCrossEntropy"
-        );
-        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
-          logits,
-          "logits",
-          "sigmoidCrossEntropy"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "sigmoidCrossEntropy"
-          );
-        }
-        Object(util["assertShapesMatch"])(
-          $multiClassLabels.shape,
-          $logits.shape,
-          "Error in sigmoidCrossEntropy: "
-        );
-        if (labelSmoothing > 0) {
-          const labelSmoothingScalar = Object(tensor_ops["e" /* scalar */])(labelSmoothing);
-          const one = Object(tensor_ops["e" /* scalar */])(1);
-          const half = Object(tensor_ops["e" /* scalar */])(0.5);
-          $multiClassLabels = $multiClassLabels
-            .mul(one.sub(labelSmoothingScalar))
-            .add(half.mul(labelSmoothingScalar));
-        }
-        const losses = sigmoidCrossEntropyWithLogits_($multiClassLabels, $logits);
-        return computeWeightedLoss(losses, $weights, reduction);
-      }
-      /**
-       * Computes the huber loss between two tensors.
-       *
-       * @param labels The ground truth output tensor, same dimensions as
-       *    'predictions'.
-       * @param predictions The predicted outputs.
-       * @param weights Tensor whose rank is either 0, or the same rank as
-       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
-       *    must be either `1`, or the same as the corresponding `losses`
-       *    dimension).
-       * @param delta Point where huber loss changes from quadratic to linear.
-       * @param reduction Type of reduction to apply to loss. Should be of type
-       *    `Reduction`.
-       */
-      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
-      function huberLoss_(
-        labels,
-        predictions,
-        weights,
-        delta = 1.0,
-        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
-      ) {
-        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
-          labels,
-          "labels",
-          "huberLoss"
-        );
-        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
-          predictions,
-          "predictions",
-          "huberLoss"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "huberLoss"
-          );
-        }
-        Object(util["assertShapesMatch"])(
-          $labels.shape,
-          $predictions.shape,
-          "Error in huberLoss: "
-        );
-        const deltaScalar = Object(tensor_ops["e" /* scalar */])(delta);
-        const error = $predictions.sub($labels).abs();
-        const quadratic = minimum(error, deltaScalar);
-        const linear = error.sub(quadratic);
-        const losses = Object(tensor_ops["e" /* scalar */])(0.5)
-          .mul(quadratic.square())
-          .add(deltaScalar.mul(linear));
-        return computeWeightedLoss(losses, $weights, reduction);
-      }
-      /**
-       * Computes softmax cross entropy between logits and labels.
-       *
-       * Measures the probability error in discrete classification tasks in which
-       * the classes are mutually exclusive (each entry is in exactly one class).
-       * For example, each CIFAR-10 image is labeled with one and only one label: an
-       * image can be a dog or a truck, but not both.
-       *
-       * `NOTE`: While the classes are mutually exclusive, their probabilities need
-       * not be. All that is required is that each row of labels is a valid
-       * probability distribution. If they are not, the computation of the gradient
-       * will be incorrect.
-       *
-       * `WARNING`: This op expects unscaled logits, since it performs a softmax on
-       * logits internally for efficiency. Do not call this op with the output of
-       * softmax, as it will produce incorrect results.
-       *
-       * logits and labels must have the same shape, e.g. [batch_size, num_classes]
-       * and the same dtype.
-       * @param labels The labels array.
-       * @param logits The logits array.
-       * @param dim The dimension softmax would be performed on. Defaults to `-1`
-       *     which indicates the last dimension.
-       */
-      function softmaxCrossEntropyWithLogits_(labels, logits, dim = -1) {
-        if (dim === -1) {
-          dim = logits.rank - 1;
-        }
-        if (dim !== logits.rank - 1) {
-          throw Error(
-            `Softmax cross entropy along a non-last dimension is not yet ` +
-              `supported. Labels / logits was rank ${logits.rank} ` +
-              `and dim was ${dim}`
-          );
-        }
-        // Use a custom gradient for numerical stability.
-        const customOp = customGrad((labels, logits, save) => {
-          // Reference:
-          //   1. http://cs231n.github.io/linear-classify/#softmax
-          //   2. https://blog.feedly.com/tricks-of-the-trade-logsumexp/
-          const keepDims = true;
-          const lse = logits.logSumExp([dim], keepDims);
-          const logResult = logits.toFloat().sub(lse);
-          save([labels, logResult]);
-          const costVector = logResult.mul(labels).neg();
-          const value = costVector.sum([dim]);
-          const gradFunc = (dy, saved) => {
-            const [labels, logResult] = saved;
-            const dyShape = expandShapeToKeepDim(dy.shape, [dim]);
-            return [
-              dy.reshape(dyShape).mul(labels.toFloat().sub(logResult.exp())),
-              dy.reshape(dyShape).mul(logResult.exp().sub(labels.toFloat())),
-            ];
-          };
-          return { value, gradFunc };
-        });
-        return customOp(labels, logits);
-      }
-      /**
-       * Computes the softmax cross entropy loss between two tensors.
-       *
-       * If labelSmoothing is nonzero, smooth the labels towards 1/2:
-       *
-       *   newOnehotLabels = onehotLabels * (1 - labelSmoothing)
-       *                         + labelSmoothing / numClasses
-       *
-       * @param onehotLabels One hot encoded labels
-       *    [batch_size, num_classes], same dimensions as 'predictions'.
-       * @param logits The predicted outputs.
-       * @param weights Tensor whose rank is either 0, or 1, and must be
-       *    broadcastable to `loss`  of shape [batch_size]
-       * @param labelSmoothing If greater than 0, then smooth the labels.
-       * @param reduction Type of reduction to apply to loss. Should be of type
-       *    `Reduction`
-       */
-      /** @doc { heading: 'Training', subheading: 'Losses', namespace: 'losses' } */
-      function softmaxCrossEntropy_(
-        onehotLabels,
-        logits,
-        weights,
-        labelSmoothing = 0,
-        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
-      ) {
-        let $onehotLabels = Object(tensor_util_env["a" /* convertToTensor */])(
-          onehotLabels,
-          "onehotLabels",
-          "softmaxCrossEntropy"
-        );
-        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
-          logits,
-          "logits",
-          "softmaxCrossEntropy"
-        );
-        let $weights = null;
-        if (weights != null) {
-          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
-            weights,
-            "weights",
-            "softmaxCrossEntropy"
-          );
-        }
-        Object(util["assertShapesMatch"])(
-          $onehotLabels.shape,
-          $logits.shape,
-          "Error in softmaxCrossEntropy: "
-        );
-        if (labelSmoothing > 0) {
-          const labelSmoothingScalar = Object(tensor_ops["e" /* scalar */])(labelSmoothing);
-          const one = Object(tensor_ops["e" /* scalar */])(1);
-          const numClasses = Object(tensor_ops["e" /* scalar */])($onehotLabels.shape[1]);
-          $onehotLabels = $onehotLabels
-            .mul(one.sub(labelSmoothingScalar))
-            .add(labelSmoothingScalar.div(numClasses));
-        }
-        const losses = softmaxCrossEntropyWithLogits_($onehotLabels, $logits);
-        return computeWeightedLoss(losses, $weights, reduction);
-      }
-      const absoluteDifference = Object(operation["a" /* op */])({ absoluteDifference_ });
-      const computeWeightedLoss = Object(operation["a" /* op */])({ computeWeightedLoss_ });
-      const cosineDistance = Object(operation["a" /* op */])({ cosineDistance_ });
-      const hingeLoss = Object(operation["a" /* op */])({ hingeLoss_ });
-      const huberLoss = Object(operation["a" /* op */])({ huberLoss_ });
-      const logLoss = Object(operation["a" /* op */])({ logLoss_ });
-      const meanSquaredError = Object(operation["a" /* op */])({ meanSquaredError_ });
-      const sigmoidCrossEntropy = Object(operation["a" /* op */])({ sigmoidCrossEntropy_ });
-      const softmaxCrossEntropy = Object(operation["a" /* op */])({ softmaxCrossEntropy_ });
-      //# sourceMappingURL=loss_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/linalg_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Linear algebra ops.
-       */
-
-      /**
-       * Copy a tensor setting everything outside a central band in each innermost
-       * matrix to zero.
-       *
-       * The band part is computed as follows: Assume input has `k` dimensions
-       * `[I, J, K, ..., M, N]`, then the output is a tensor with the same shape where
-       * `band[i, j, k, ..., m, n] = in_band(m, n) * input[i, j, k, ..., m, n]`.
-       * The indicator function
-       * `in_band(m, n) = (num_lower < 0 || (m-n) <= num_lower))`
-       * `&& (num_upper < 0 || (n-m) <= num_upper)`
-       *
-       * ```js
-       * const x = tf.tensor2d([[ 0,  1,  2, 3],
-       *                        [-1,  0,  1, 2],
-       *                        [-2, -1,  0, 1],
-       *                        [-3, -2, -1, 0]]);
-       * let y = tf.linalg.bandPart(x, 1, -1);
-       * y.print(); // [[ 0,  1,  2, 3],
-       *            //  [-1,  0,  1, 2],
-       *            //  [ 0, -1,  0, 1],
-       *            //  [ 0, 0 , -1, 0]]
-       * let z = tf.linalg.bandPart(x, 2, 1);
-       * z.print(); // [[ 0,  1,  0, 0],
-       *            //  [-1,  0,  1, 0],
-       *            //  [-2, -1,  0, 1],
-       *            //  [ 0, -2, -1, 0]]
-       * ```
-       *
-       * @param x Rank `k` tensor
-       * @param numLower Number of subdiagonals to keep.
-       *   If negative, keep entire lower triangle.
-       * @param numUpper Number of subdiagonals to keep.
-       *   If negative, keep entire upper triangle.
-       * @returns Rank `k` tensor of the same shape as input.
-       *   The extracted banded tensor.
-       */
-      /**
-       * @doc {heading:'Operations',
-       *       subheading:'Linear Algebra',
-       *       namespace:'linalg'}
-       */
-      function bandPart_(a, numLower, numUpper) {
-        if (numLower % 1 !== 0) {
-          throw new Error(`bandPart(): numLower must be an integer, got ${numLower}.`);
-        }
-        if (numUpper % 1 !== 0) {
-          throw new Error(`bandPart(): numUpper must be an integer, got ${numUpper}.`);
-        }
-        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "bandPart");
-        if ($a.rank < 2) {
-          throw new Error(`bandPart(): Rank must be at least 2, got ${$a.rank}.`);
-        }
-        const shape = $a.shape,
-          [M, N] = $a.shape.slice(-2);
-        if (!(numLower <= M)) {
-          throw new Error(
-            `bandPart(): numLower (${numLower})` +
-              ` must not be greater than the number of rows (${M}).`
-          );
-        }
-        if (!(numUpper <= N)) {
-          throw new Error(
-            `bandPart(): numUpper (${numUpper})` +
-              ` must not be greater than the number of columns (${N}).`
-          );
-        }
-        if (numLower < 0) {
-          numLower = M;
-        }
-        if (numUpper < 0) {
-          numUpper = N;
-        }
-        const i = Object(tensor_ops["d" /* range */])(0, M, 1, "int32").reshape([-1, 1]),
-          j = Object(tensor_ops["d" /* range */])(0, N, 1, "int32"),
-          ij = sub(i, j);
-        const inBand = logicalAnd(
-          ij.lessEqual(Object(tensor_ops["e" /* scalar */])(+numLower, "int32")),
-          ij.greaterEqual(Object(tensor_ops["e" /* scalar */])(-numUpper, "int32"))
-        );
-        const zero = Object(tensor_ops["n" /* zeros */])([M, N], $a.dtype);
-        return stack(
-          unstack($a.reshape([-1, M, N])).map((mat) => where(inBand, mat, zero))
-        ).reshape(shape);
-      }
-      /**
-       * Gram-Schmidt orthogonalization.
-       *
-       * ```js
-       * const x = tf.tensor2d([[1, 2], [3, 4]]);
-       * let y = tf.linalg.gramSchmidt(x);
-       * y.print();
-       * console.log('Othogonalized:');
-       * y.dot(y.transpose()).print();  // should be nearly the identity matrix.
-       * console.log('First row direction maintained:');
-       * const data = await y.array();
-       * console.log(data[0][1] / data[0][0]);  // should be nearly 2.
-       * ```
-       *
-       * @param xs The vectors to be orthogonalized, in one of the two following
-       *   formats:
-       *   - An Array of `tf.Tensor1D`.
-       *   - A `tf.Tensor2D`, i.e., a matrix, in which case the vectors are the rows
-       *     of `xs`.
-       *   In each case, all the vectors must have the same length and the length
-       *   must be greater than or equal to the number of vectors.
-       * @returns The orthogonalized and normalized vectors or matrix.
-       *   Orthogonalization means that the vectors or the rows of the matrix
-       *   are orthogonal (zero inner products). Normalization means that each
-       *   vector or each row of the matrix has an L2 norm that equals `1`.
-       */
-      /**
-       * @doc {heading:'Operations',
-       *       subheading:'Linear Algebra',
-       *       namespace:'linalg'}
-       */
-      function gramSchmidt_(xs) {
-        let inputIsTensor2D;
-        if (Array.isArray(xs)) {
-          inputIsTensor2D = false;
-          Object(util["assert"])(
-            xs != null && xs.length > 0,
-            () => "Gram-Schmidt process: input must not be null, undefined, or " + "empty"
-          );
-          const dim = xs[0].shape[0];
-          for (let i = 1; i < xs.length; ++i) {
-            Object(util["assert"])(
-              xs[i].shape[0] === dim,
-              () =>
-                "Gram-Schmidt: Non-unique lengths found in the input vectors: " +
-                `(${xs[i].shape[0]} vs. ${dim})`
-            );
-          }
-        } else {
-          inputIsTensor2D = true;
-          xs = split(xs, xs.shape[0], 0).map((x) => squeeze(x, [0]));
-        }
-        Object(util["assert"])(
-          xs.length <= xs[0].shape[0],
-          () =>
-            `Gram-Schmidt: Number of vectors (${xs.length}) exceeds ` +
-            `number of dimensions (${xs[0].shape[0]}).`
-        );
-        const ys = [];
-        const xs1d = xs;
-        for (let i = 0; i < xs.length; ++i) {
-          ys.push(
-            engine["a" /* ENGINE */].tidy(() => {
-              let x = xs1d[i];
-              if (i > 0) {
-                for (let j = 0; j < i; ++j) {
-                  const proj = sum(ys[j].mul(x)).mul(ys[j]);
-                  x = x.sub(proj);
-                }
-              }
-              return x.div(norm_norm(x, "euclidean"));
-            })
-          );
-        }
-        if (inputIsTensor2D) {
-          return stack(ys, 0);
-        } else {
-          return ys;
-        }
-      }
-      /**
-       * Compute QR decomposition of m-by-n matrix using Householder transformation.
-       *
-       * Implementation based on
-       *   [http://www.cs.cornell.edu/~bindel/class/cs6210-f09/lec18.pdf]
-       * (http://www.cs.cornell.edu/~bindel/class/cs6210-f09/lec18.pdf)
-       *
-       * ```js
-       * const a = tf.tensor2d([[1, 2], [3, 4]]);
-       * let [q, r] = tf.linalg.qr(a);
-       * console.log('Q');
-       * q.print();
-       * console.log('R');
-       * r.print();
-       * console.log('Orthogonalized');
-       * q.dot(q.transpose()).print()  // should be nearly the identity matrix.
-       * console.log('Reconstructed');
-       * q.dot(r).print(); // should be nearly [[1, 2], [3, 4]];
-       * ```
-       *
-       * @param x The `tf.Tensor` to be QR-decomposed. Must have rank >= 2. Suppose
-       *   it has the shape `[..., M, N]`.
-       * @param fullMatrices An optional boolean parameter. Defaults to `false`.
-       *   If `true`, compute full-sized `Q`. If `false` (the default),
-       *   compute only the leading N columns of `Q` and `R`.
-       * @returns An `Array` of two `tf.Tensor`s: `[Q, R]`. `Q` is a unitary matrix,
-       *   i.e., its columns all have unit norm and are mutually orthogonal.
-       *   If `M >= N`,
-       *     If `fullMatrices` is `false` (default),
-       *       - `Q` has a shape of `[..., M, N]`,
-       *       - `R` has a shape of `[..., N, N]`.
-       *     If `fullMatrices` is `true` (default),
-       *       - `Q` has a shape of `[..., M, M]`,
-       *       - `R` has a shape of `[..., M, N]`.
-       *   If `M < N`,
-       *     - `Q` has a shape of `[..., M, M]`,
-       *     - `R` has a shape of `[..., M, N]`.
-       * @throws If the rank of `x` is less than 2.
-       */
-      /**
-       * @doc {heading:'Operations',
-       *       subheading:'Linear Algebra',
-       *       namespace:'linalg'}
-       */
-      function qr_(x, fullMatrices = false) {
-        if (x.rank < 2) {
-          throw new Error(`qr() requires input tensor to have a rank >= 2, but got rank ${x.rank}`);
-        } else if (x.rank === 2) {
-          return qr2d(x, fullMatrices);
-        } else {
-          // Rank > 2.
-          // TODO(cais): Below we split the input into individual 2D tensors,
-          //   perform QR decomposition on them and then stack the results back
-          //   together. We should explore whether this can be parallelized.
-          const outerDimsProd = x.shape
-            .slice(0, x.shape.length - 2)
-            .reduce((value, prev) => value * prev);
-          const x2ds = unstack(
-            x.reshape([outerDimsProd, x.shape[x.shape.length - 2], x.shape[x.shape.length - 1]]),
-            0
-          );
-          const q2ds = [];
-          const r2ds = [];
-          x2ds.forEach((x2d) => {
-            const [q2d, r2d] = qr2d(x2d, fullMatrices);
-            q2ds.push(q2d);
-            r2ds.push(r2d);
-          });
-          const q = stack(q2ds, 0).reshape(x.shape);
-          const r = stack(r2ds, 0).reshape(x.shape);
-          return [q, r];
-        }
-      }
-      function qr2d(x, fullMatrices = false) {
-        return engine["a" /* ENGINE */].tidy(() => {
-          if (x.shape.length !== 2) {
-            throw new Error(`qr2d() requires a 2D Tensor, but got a ${x.shape.length}D Tensor.`);
-          }
-          const m = x.shape[0];
-          const n = x.shape[1];
-          let q = eye(m); // Orthogonal transform so far.
-          let r = x.clone(); // Transformed matrix so far.
-          const one2D = Object(tensor_ops["h" /* tensor2d */])([[1]], [1, 1]);
-          let w = one2D.clone();
-          const iters = m >= n ? n : m;
-          for (let j = 0; j < iters; ++j) {
-            // This tidy within the for-loop ensures we clean up temporary
-            // tensors as soon as they are no longer needed.
-            const rTemp = r;
-            const wTemp = w;
-            const qTemp = q;
-            [w, r, q] = engine["a" /* ENGINE */].tidy(() => {
-              // Find H = I - tau * w * w', to put zeros below R(j, j).
-              const rjEnd1 = r.slice([j, j], [m - j, 1]);
-              const normX = rjEnd1.norm();
-              const rjj = r.slice([j, j], [1, 1]);
-              // The sign() function returns 0 on 0, which causes division by zero.
-              const s = Object(tensor_ops["h" /* tensor2d */])([[-1]]).where(
-                rjj.greater(0),
-                Object(tensor_ops["h" /* tensor2d */])([[1]])
-              );
-              const u1 = rjj.sub(s.mul(normX));
-              const wPre = rjEnd1.div(u1);
-              if (wPre.shape[0] === 1) {
-                w = one2D.clone();
-              } else {
-                w = one2D.concat(wPre.slice([1, 0], [wPre.shape[0] - 1, wPre.shape[1]]), 0);
-              }
-              const tau = s.matMul(u1).div(normX).neg();
-              // -- R := HR, Q := QH.
-              const rjEndAll = r.slice([j, 0], [m - j, n]);
-              const tauTimesW = tau.mul(w);
-              const wT = w.transpose();
-              if (j === 0) {
-                r = rjEndAll.sub(tauTimesW.matMul(wT.matMul(rjEndAll)));
-              } else {
-                const rTimesTau = rjEndAll.sub(tauTimesW.matMul(wT.matMul(rjEndAll)));
-                r = r.slice([0, 0], [j, n]).concat(rTimesTau, 0);
-              }
-              const tawTimesWT = tauTimesW.transpose();
-              const qAllJEnd = q.slice([0, j], [m, q.shape[1] - j]);
-              if (j === 0) {
-                q = qAllJEnd.sub(qAllJEnd.matMul(w).matMul(tawTimesWT));
-              } else {
-                const qTimesTau = qAllJEnd.sub(qAllJEnd.matMul(w).matMul(tawTimesWT));
-                q = q.slice([0, 0], [m, j]).concat(qTimesTau, 1);
-              }
-              return [w, r, q];
-            });
-            dispose([rTemp, wTemp, qTemp]);
-          }
-          if (!fullMatrices && m > n) {
-            q = q.slice([0, 0], [m, n]);
-            r = r.slice([0, 0], [n, n]);
-          }
-          return [q, r];
-        });
-      }
-      const bandPart = Object(operation["a" /* op */])({ bandPart_ });
-      const gramSchmidt = Object(operation["a" /* op */])({ gramSchmidt_ });
-      const qr = Object(operation["a" /* op */])({ qr_ });
-      //# sourceMappingURL=linalg_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/array_util.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Inserts a value into a sorted array. This method allows duplicate, meaning it
-       * allows inserting duplicate value, in which case, the element will be inserted
-       * at the lowest index of the value.
-       * @param arr The array to modify.
-       * @param element The element to insert.
-       * @param comparator Optional. If no comparator is specified, elements are
-       * compared using array_util.defaultComparator, which is suitable for Strings
-       * and Numbers in ascending arrays. If the array contains multiple instances of
-       * the target value, the left-most instance will be returned. To provide a
-       * comparator, it should take 2 arguments to compare and return a negative,
-       * zero, or a positive number.
-       */
-      function binaryInsert(arr, element, comparator) {
-        const index = binarySearch(arr, element, comparator);
-        const insertionPoint = index < 0 ? -(index + 1) : index;
-        arr.splice(insertionPoint, 0, element);
-      }
-      /**
-       * Searches the array for the target using binary search, returns the index
-       * of the found element, or position to insert if element not found. If no
-       * comparator is specified, elements are compared using array_
-       * util.defaultComparator, which is suitable for Strings and Numbers in
-       * ascending arrays. If the array contains multiple instances of the target
-       * value, the left-most instance will be returned.
-       * @param arr The array to be searched in.
-       * @param target The target to be searched for.
-       * @param comparator Should take 2 arguments to compare and return a negative,
-       *    zero, or a positive number.
-       * @return Lowest index of the target value if found, otherwise the insertion
-       *    point where the target should be inserted, in the form of
-       *    (-insertionPoint - 1).
-       */
-      function binarySearch(arr, target, comparator) {
-        return binarySearch_(arr, target, comparator || defaultComparator);
-      }
-      /**
-       * Compares its two arguments for order.
-       * @param a The first element to be compared.
-       * @param b The second element to be compared.
-       * @return A negative number, zero, or a positive number as the first
-       *     argument is less than, equal to, or greater than the second.
-       */
-      function defaultComparator(a, b) {
-        return a > b ? 1 : a < b ? -1 : 0;
-      }
-      function binarySearch_(arr, target, comparator) {
-        let left = 0;
-        let right = arr.length;
-        let middle = 0;
-        let found = false;
-        while (left < right) {
-          middle = left + ((right - left) >>> 1);
-          const compareResult = comparator(target, arr[middle]);
-          if (compareResult > 0) {
-            left = middle + 1;
-          } else {
-            right = middle;
-            // If compareResult is 0, the value is found. We record it is found,
-            // and then keep looking because there may be duplicate.
-            found = !compareResult;
-          }
-        }
-        return found ? left : -left - 1;
-      }
-      //# sourceMappingURL=array_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/non_max_suppression_impl.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Implementation of the NonMaxSuppression kernel shared between webgl and cpu.
-       */
-
-      function nonMaxSuppressionV3(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold) {
-        const dummySoftNmsSigma = 0.0;
-        const result = nonMaxSuppressionImpl_(
-          boxes,
-          scores,
-          maxOutputSize,
-          iouThreshold,
-          scoreThreshold,
-          dummySoftNmsSigma
-        );
-        result.selectedScores.dispose();
-        result.numValidOutputs.dispose();
-        return result.selectedIndices;
-      }
-      function nonMaxSuppressionV5(
-        boxes,
-        scores,
-        maxOutputSize,
-        iouThreshold,
-        scoreThreshold,
-        softNmsSigma
-      ) {
-        // For NonMaxSuppressionV5Op, we always return a second output holding
-        // corresponding scores.
-        const returnScoresTensor = true;
-        const result = nonMaxSuppressionImpl_(
-          boxes,
-          scores,
-          maxOutputSize,
-          iouThreshold,
-          scoreThreshold,
-          softNmsSigma,
-          returnScoresTensor
-        );
-        result.numValidOutputs.dispose();
-        return {
-          selectedIndices: result.selectedIndices,
-          selectedScores: result.selectedScores,
-        };
-      }
-      function nonMaxSuppressionImpl_(
-        boxes,
-        scores,
-        maxOutputSize,
-        iouThreshold,
-        scoreThreshold,
-        softNmsSigma,
-        returnScoresTensor = false,
-        padToMaxOutputSize = false
-      ) {
-        // The list is sorted in ascending order, so that we can always pop the
-        // candidate with the largest score in O(1) time.
-        const candidates = [];
-        for (let i = 0; i < scores.length; i++) {
-          if (scores[i] > scoreThreshold) {
-            candidates.push({ score: scores[i], boxIndex: i, suppressBeginIndex: 0 });
-          }
-        }
-        candidates.sort(ascendingComparator);
-        // If softNmsSigma is 0, the outcome of this algorithm is exactly same as
-        // before.
-        const scale = softNmsSigma > 0 ? -0.5 / softNmsSigma : 0.0;
-        const selectedIndices = [];
-        const selectedScores = [];
-        while (selectedIndices.length < maxOutputSize && candidates.length > 0) {
-          const candidate = candidates.pop();
-          const { score: originalScore, boxIndex, suppressBeginIndex } = candidate;
-          if (originalScore < scoreThreshold) {
-            break;
-          }
-          // Overlapping boxes are likely to have similar scores, therefore we
-          // iterate through the previously selected boxes backwards in order to
-          // see if candidate's score should be suppressed. We use
-          // suppressBeginIndex to track and ensure a candidate can be suppressed
-          // by a selected box no more than once. Also, if the overlap exceeds
-          // iouThreshold, we simply ignore the candidate.
-          let ignoreCandidate = false;
-          for (let j = selectedIndices.length - 1; j >= suppressBeginIndex; --j) {
-            const iou = intersectionOverUnion(boxes, boxIndex, selectedIndices[j]);
-            if (iou >= iouThreshold) {
-              ignoreCandidate = true;
-              break;
-            }
-            candidate.score = candidate.score * suppressWeight(iouThreshold, scale, iou);
-            if (candidate.score <= scoreThreshold) {
-              break;
-            }
-          }
-          // At this point, if `candidate.score` has not dropped below
-          // `scoreThreshold`, then we know that we went through all of the
-          // previous selections and can safely update `suppressBeginIndex` to the
-          // end of the selected array. Then we can re-insert the candidate with
-          // the updated score and suppressBeginIndex back in the candidate list.
-          // If on the other hand, `candidate.score` has dropped below the score
-          // threshold, we will not add it back to the candidates list.
-          candidate.suppressBeginIndex = selectedIndices.length;
-          if (!ignoreCandidate) {
-            // Candidate has passed all the tests, and is not suppressed, so
-            // select the candidate.
-            if (candidate.score === originalScore) {
-              selectedIndices.push(boxIndex);
-              selectedScores.push(candidate.score);
-            } else if (candidate.score > scoreThreshold) {
-              // Candidate's score is suppressed but is still high enough to be
-              // considered, so add back to the candidates list.
-              binaryInsert(candidates, candidate, ascendingComparator);
-            }
-          }
-        }
-        // NonMaxSuppressionV4 feature: padding output to maxOutputSize.
-        const numValidOutputs = selectedIndices.length;
-        if (padToMaxOutputSize) {
-          selectedIndices.fill(0, numValidOutputs);
-          selectedScores.fill(0.0, numValidOutputs);
-        }
-        return {
-          selectedIndices: Object(tensor_ops["g" /* tensor1d */])(selectedIndices, "int32"),
-          selectedScores: Object(tensor_ops["g" /* tensor1d */])(selectedScores, "float32"),
-          numValidOutputs: Object(tensor_ops["e" /* scalar */])(numValidOutputs, "int32"),
-        };
-      }
-      function intersectionOverUnion(boxes, i, j) {
-        const iCoord = boxes.subarray(i * 4, i * 4 + 4);
-        const jCoord = boxes.subarray(j * 4, j * 4 + 4);
-        const yminI = Math.min(iCoord[0], iCoord[2]);
-        const xminI = Math.min(iCoord[1], iCoord[3]);
-        const ymaxI = Math.max(iCoord[0], iCoord[2]);
-        const xmaxI = Math.max(iCoord[1], iCoord[3]);
-        const yminJ = Math.min(jCoord[0], jCoord[2]);
-        const xminJ = Math.min(jCoord[1], jCoord[3]);
-        const ymaxJ = Math.max(jCoord[0], jCoord[2]);
-        const xmaxJ = Math.max(jCoord[1], jCoord[3]);
-        const areaI = (ymaxI - yminI) * (xmaxI - xminI);
-        const areaJ = (ymaxJ - yminJ) * (xmaxJ - xminJ);
-        if (areaI <= 0 || areaJ <= 0) {
-          return 0.0;
-        }
-        const intersectionYmin = Math.max(yminI, yminJ);
-        const intersectionXmin = Math.max(xminI, xminJ);
-        const intersectionYmax = Math.min(ymaxI, ymaxJ);
-        const intersectionXmax = Math.min(xmaxI, xmaxJ);
-        const intersectionArea =
-          Math.max(intersectionYmax - intersectionYmin, 0.0) *
-          Math.max(intersectionXmax - intersectionXmin, 0.0);
-        return intersectionArea / (areaI + areaJ - intersectionArea);
-      }
-      // A Gaussian penalty function, this method always returns values in [0, 1].
-      // The weight is a function of similarity, the more overlap two boxes are, the
-      // smaller the weight is, meaning highly overlapping boxe will be significantly
-      // penalized. On the other hand, a non-overlapping box will not be penalized.
-      function suppressWeight(iouThreshold, scale, iou) {
-        const weight = Math.exp(scale * iou * iou);
-        return iou <= iouThreshold ? weight : 0.0;
-      }
-      function ascendingComparator(c1, c2) {
-        // For objects with same scores, we make the object with the larger index go
-        // first. In an array that pops from the end, this means that the object with
-        // the smaller index will be popped first. This ensures the same output as
-        // the TensorFlow python version.
-        return c1.score - c2.score || (c1.score === c2.score && c2.boxIndex - c1.boxIndex);
-      }
-      //# sourceMappingURL=non_max_suppression_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/nonmax_util.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function nonMaxSuppSanityCheck(
-        boxes,
-        scores,
-        maxOutputSize,
-        iouThreshold,
-        scoreThreshold,
-        softNmsSigma
-      ) {
-        if (iouThreshold == null) {
-          iouThreshold = 0.5;
-        }
-        if (scoreThreshold == null) {
-          scoreThreshold = Number.NEGATIVE_INFINITY;
-        }
-        if (softNmsSigma == null) {
-          softNmsSigma = 0.0;
-        }
-        const numBoxes = boxes.shape[0];
-        maxOutputSize = Math.min(maxOutputSize, numBoxes);
-        util["assert"](
-          0 <= iouThreshold && iouThreshold <= 1,
-          () => `iouThreshold must be in [0, 1], but was '${iouThreshold}'`
-        );
-        util["assert"](
-          boxes.rank === 2,
-          () => `boxes must be a 2D tensor, but was of rank '${boxes.rank}'`
-        );
-        util["assert"](
-          boxes.shape[1] === 4,
-          () => `boxes must have 4 columns, but 2nd dimension was ${boxes.shape[1]}`
-        );
-        util["assert"](scores.rank === 1, () => "scores must be a 1D tensor");
-        util["assert"](
-          scores.shape[0] === numBoxes,
-          () =>
-            `scores has incompatible shape with boxes. Expected ${numBoxes}, ` +
-            `but was ${scores.shape[0]}`
-        );
-        util["assert"](
-          0 <= softNmsSigma && softNmsSigma <= 1,
-          () => `softNmsSigma must be in [0, 1], but was '${softNmsSigma}'`
-        );
-        return { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };
-      }
-
-      //# sourceMappingURL=nonmax_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/non_max_suppression.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function nonMaxSuppression_(
-        boxes,
-        scores,
-        maxOutputSize,
-        iouThreshold = 0.5,
-        scoreThreshold = Number.NEGATIVE_INFINITY
-      ) {
-        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
-          boxes,
-          "boxes",
-          "nonMaxSuppression"
-        );
-        const $scores = Object(tensor_util_env["a" /* convertToTensor */])(
-          scores,
-          "scores",
-          "nonMaxSuppression"
-        );
-        const inputs = nonMaxSuppSanityCheck(
-          $boxes,
-          $scores,
-          maxOutputSize,
-          iouThreshold,
-          scoreThreshold
-        );
-        maxOutputSize = inputs.maxOutputSize;
-        iouThreshold = inputs.iouThreshold;
-        scoreThreshold = inputs.scoreThreshold;
-        const attrs = { maxOutputSize, iouThreshold, scoreThreshold };
-        return engine["a" /* ENGINE */].runKernelFunc(
-          (b) => b.nonMaxSuppression($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold),
-          { boxes: $boxes, scores: $scores },
-          null /* grad */,
-          kernel_names["Z" /* NonMaxSuppressionV3 */],
-          attrs
-        );
-      }
-      const nonMaxSuppression = Object(operation["a" /* op */])({ nonMaxSuppression_ });
-      //# sourceMappingURL=non_max_suppression.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/image_ops.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Bilinear resize a batch of 3D images to a new shape.
-       *
-       * @param images The images, of rank 4 or rank 3, of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
-       * @param size The new shape `[newHeight, newWidth]` to resize the
-       *     images to. Each channel is resized individually.
-       * @param alignCorners Defaults to False. If true, rescale
-       *     input by `(new_height - 1) / (height - 1)`, which exactly aligns the 4
-       *     corners of images and resized images. If false, rescale by
-       *     `new_height / height`. Treat similarly the width dimension.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
-      function resizeBilinear_(images, size, alignCorners = false) {
-        const $images = Object(tensor_util_env["a" /* convertToTensor */])(
-          images,
-          "images",
-          "resizeBilinear"
-        );
-        util["assert"](
-          $images.rank === 3 || $images.rank === 4,
-          () => `Error in resizeBilinear: x must be rank 3 or 4, but got ` + `rank ${$images.rank}.`
-        );
-        util["assert"](
-          size.length === 2,
-          () => `Error in resizeBilinear: new shape must 2D, but got shape ` + `${size}.`
-        );
-        let batchImages = $images;
-        let reshapedTo4D = false;
-        if ($images.rank === 3) {
-          reshapedTo4D = true;
-          batchImages = $images.as4D(1, $images.shape[0], $images.shape[1], $images.shape[2]);
-        }
-        const [newHeight, newWidth] = size;
-        const forward = (backend, save) => {
-          save([batchImages]);
-          return backend.resizeBilinear(batchImages, newHeight, newWidth, alignCorners);
-        };
-        const backward = (dy, saved) => {
-          return {
-            x: () =>
-              engine["a" /* ENGINE */].runKernelFunc(
-                (backend) => backend.resizeBilinearBackprop(dy, saved[0], alignCorners),
-                {}
-              ),
-          };
-        };
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          { x: batchImages },
-          backward,
-          "ResizeBilinear",
-          { alignCorners, newHeight, newWidth }
-        );
-        if (reshapedTo4D) {
-          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
-        }
-        return res;
-      }
-      /**
-       * NearestNeighbor resize a batch of 3D images to a new shape.
-       *
-       * @param images The images, of rank 4 or rank 3, of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
-       * @param size The new shape `[newHeight, newWidth]` to resize the
-       *     images to. Each channel is resized individually.
-       * @param alignCorners Defaults to False. If true, rescale
-       *     input by `(new_height - 1) / (height - 1)`, which exactly aligns the 4
-       *     corners of images and resized images. If false, rescale by
-       *     `new_height / height`. Treat similarly the width dimension.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
-      function resizeNearestNeighbor_(images, size, alignCorners = false) {
-        const $images = Object(tensor_util_env["a" /* convertToTensor */])(
-          images,
-          "images",
-          "resizeNearestNeighbor"
-        );
-        util["assert"](
-          $images.rank === 3 || $images.rank === 4,
-          () =>
-            `Error in resizeNearestNeighbor: x must be rank 3 or 4, but got ` +
-            `rank ${$images.rank}.`
-        );
-        util["assert"](
-          size.length === 2,
-          () => `Error in resizeNearestNeighbor: new shape must 2D, but got shape ` + `${size}.`
-        );
-        util["assert"](
-          $images.dtype === "float32" || $images.dtype === "int32",
-          () => "`images` must have `int32` or `float32` as dtype"
-        );
-        let batchImages = $images;
-        let reshapedTo4D = false;
-        if ($images.rank === 3) {
-          reshapedTo4D = true;
-          batchImages = $images.as4D(1, $images.shape[0], $images.shape[1], $images.shape[2]);
-        }
-        const [newHeight, newWidth] = size;
-        const forward = (backend, save) => {
-          save([batchImages]);
-          return backend.resizeNearestNeighbor(batchImages, newHeight, newWidth, alignCorners);
-        };
-        const backward = (dy, saved) => {
-          return {
-            batchImages: () =>
-              engine["a" /* ENGINE */].runKernelFunc(
-                (backend) => backend.resizeNearestNeighborBackprop(dy, saved[0], alignCorners),
-                {}
-              ),
-          };
-        };
-        const res = engine["a" /* ENGINE */].runKernelFunc(forward, { batchImages }, backward);
-        if (reshapedTo4D) {
-          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
-        }
-        return res;
-      }
-      /**
-       * Performs non maximum suppression of bounding boxes based on
-       * iou (intersection over union).
-       *
-       * @param boxes a 2d tensor of shape `[numBoxes, 4]`. Each entry is
-       *     `[y1, x1, y2, x2]`, where `(y1, x1)` and `(y2, x2)` are the corners of
-       *     the bounding box.
-       * @param scores a 1d tensor providing the box scores of shape `[numBoxes]`.
-       * @param maxOutputSize The maximum number of boxes to be selected.
-       * @param iouThreshold A float representing the threshold for deciding whether
-       *     boxes overlap too much with respect to IOU. Must be between [0, 1].
-       *     Defaults to 0.5 (50% box overlap).
-       * @param scoreThreshold A threshold for deciding when to remove boxes based
-       *     on score. Defaults to -inf, which means any score is accepted.
-       * @return A 1D tensor with the selected box indices.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
-      /** This is the async version of `nonMaxSuppression` */
-      async function nonMaxSuppressionAsync_(
-        boxes,
-        scores,
-        maxOutputSize,
-        iouThreshold = 0.5,
-        scoreThreshold = Number.NEGATIVE_INFINITY
-      ) {
-        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
-          boxes,
-          "boxes",
-          "nonMaxSuppressionAsync"
-        );
-        const $scores = Object(tensor_util_env["a" /* convertToTensor */])(
-          scores,
-          "scores",
-          "nonMaxSuppressionAsync"
-        );
-        const inputs = nonMaxSuppSanityCheck(
-          $boxes,
-          $scores,
-          maxOutputSize,
-          iouThreshold,
-          scoreThreshold
-        );
-        maxOutputSize = inputs.maxOutputSize;
-        iouThreshold = inputs.iouThreshold;
-        scoreThreshold = inputs.scoreThreshold;
-        const boxesAndScores = await Promise.all([$boxes.data(), $scores.data()]);
-        const boxesVals = boxesAndScores[0];
-        const scoresVals = boxesAndScores[1];
-        const res = nonMaxSuppressionV3(
-          boxesVals,
-          scoresVals,
-          maxOutputSize,
-          iouThreshold,
-          scoreThreshold
-        );
-        if ($boxes !== boxes) {
-          $boxes.dispose();
-        }
-        if ($scores !== scores) {
-          $scores.dispose();
-        }
-        return res;
-      }
-      /**
-       * Performs non maximum suppression of bounding boxes based on
-       * iou (intersection over union).
-       *
-       * This op also supports a Soft-NMS mode (c.f.
-       * Bodla et al, https://arxiv.org/abs/1704.04503) where boxes reduce the score
-       * of other overlapping boxes, therefore favoring different regions of the image
-       * with high scores. To enable this Soft-NMS mode, set the `softNmsSigma`
-       * parameter to be larger than 0.
-       *
-       * @param boxes a 2d tensor of shape `[numBoxes, 4]`. Each entry is
-       *     `[y1, x1, y2, x2]`, where `(y1, x1)` and `(y2, x2)` are the corners of
-       *     the bounding box.
-       * @param scores a 1d tensor providing the box scores of shape `[numBoxes]`.
-       * @param maxOutputSize The maximum number of boxes to be selected.
-       * @param iouThreshold A float representing the threshold for deciding whether
-       *     boxes overlap too much with respect to IOU. Must be between [0, 1].
-       *     Defaults to 0.5 (50% box overlap).
-       * @param scoreThreshold A threshold for deciding when to remove boxes based
-       *     on score. Defaults to -inf, which means any score is accepted.
-       * @param softNmsSigma A float representing the sigma parameter for Soft NMS.
-       *     When sigma is 0, it falls back to nonMaxSuppression.
-       * @return A map with the following properties:
-       *     - selectedIndices: A 1D tensor with the selected box indices.
-       *     - selectedScores: A 1D tensor with the corresponding scores for each
-       *       selected box.
-       */
-      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
-      function nonMaxSuppressionWithScore_(
-        boxes,
-        scores,
-        maxOutputSize,
-        iouThreshold = 0.5,
-        scoreThreshold = Number.NEGATIVE_INFINITY,
-        softNmsSigma = 0.0
-      ) {
-        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
-          boxes,
-          "boxes",
-          "nonMaxSuppression"
-        );
-        const $scores = Object(tensor_util_env["a" /* convertToTensor */])(
-          scores,
-          "scores",
-          "nonMaxSuppression"
-        );
-        const inputs = nonMaxSuppSanityCheck(
-          $boxes,
-          $scores,
-          maxOutputSize,
-          iouThreshold,
-          scoreThreshold,
-          softNmsSigma
-        );
-        maxOutputSize = inputs.maxOutputSize;
-        iouThreshold = inputs.iouThreshold;
-        scoreThreshold = inputs.scoreThreshold;
-        softNmsSigma = inputs.softNmsSigma;
-        const attrs = { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };
-        const result = engine["a" /* ENGINE */].runKernel(
-          "NonMaxSuppressionV5",
-          { boxes: $boxes, scores: $scores },
-          attrs
-        );
-        return { selectedIndices: result[0], selectedScores: result[1] };
-      }
-      /** This is the async version of `nonMaxSuppressionWithScore` */
-      async function nonMaxSuppressionWithScoreAsync_(
-        boxes,
-        scores,
-        maxOutputSize,
-        iouThreshold = 0.5,
-        scoreThreshold = Number.NEGATIVE_INFINITY,
-        softNmsSigma = 0.0
-      ) {
-        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
-          boxes,
-          "boxes",
-          "nonMaxSuppressionAsync"
-        );
-        const $scores = Object(tensor_util_env["a" /* convertToTensor */])(
-          scores,
-          "scores",
-          "nonMaxSuppressionAsync"
-        );
-        const inputs = nonMaxSuppSanityCheck(
-          $boxes,
-          $scores,
-          maxOutputSize,
-          iouThreshold,
-          scoreThreshold,
-          softNmsSigma
-        );
-        maxOutputSize = inputs.maxOutputSize;
-        iouThreshold = inputs.iouThreshold;
-        scoreThreshold = inputs.scoreThreshold;
-        softNmsSigma = inputs.softNmsSigma;
-        const boxesAndScores = await Promise.all([$boxes.data(), $scores.data()]);
-        const boxesVals = boxesAndScores[0];
-        const scoresVals = boxesAndScores[1];
-        const res = nonMaxSuppressionV5(
-          boxesVals,
-          scoresVals,
-          maxOutputSize,
-          iouThreshold,
-          scoreThreshold,
-          softNmsSigma
-        );
-        if ($boxes !== boxes) {
-          $boxes.dispose();
-        }
-        if ($scores !== scores) {
-          $scores.dispose();
-        }
-        return res;
-      }
-      /**
-       * Extracts crops from the input image tensor and resizes them using bilinear
-       * sampling or nearest neighbor sampling (possibly with aspect ratio change)
-       * to a common output size specified by crop_size.
-       *
-       * @param image 4d tensor of shape `[batch,imageHeight,imageWidth, depth]`,
-       *     where imageHeight and imageWidth must be positive, specifying the
-       *     batch of images from which to take crops
-       * @param boxes 2d float32 tensor of shape `[numBoxes, 4]`. Each entry is
-       *     `[y1, x1, y2, x2]`, where `(y1, x1)` and `(y2, x2)` are the normalized
-       *     coordinates of the box in the boxInd[i]'th image in the batch
-       * @param boxInd 1d int32 tensor of shape `[numBoxes]` with values in range
-       *     `[0, batch)` that specifies the image that the `i`-th box refers to.
-       * @param cropSize 1d int32 tensor of 2 elements `[cropHeigh, cropWidth]`
-       *     specifying the size to which all crops are resized to.
-       * @param method Optional string from `'bilinear' | 'nearest'`,
-       *     defaults to bilinear, which specifies the sampling method for resizing
-       * @param extrapolationValue A threshold for deciding when to remove boxes based
-       *     on score. Defaults to 0.
-       * @return A 4D tensor of the shape `[numBoxes,cropHeight,cropWidth,depth]`
-       */
-      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
-      function cropAndResize_(image, boxes, boxInd, cropSize, method, extrapolationValue) {
-        const $image = Object(tensor_util_env["a" /* convertToTensor */])(
-          image,
-          "image",
-          "cropAndResize"
-        );
-        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
-          boxes,
-          "boxes",
-          "cropAndResize",
-          "float32"
-        );
-        const $boxInd = Object(tensor_util_env["a" /* convertToTensor */])(
-          boxInd,
-          "boxInd",
-          "cropAndResize",
-          "int32"
-        );
-        method = method || "bilinear";
-        extrapolationValue = extrapolationValue || 0;
-        const numBoxes = $boxes.shape[0];
-        util["assert"](
-          $image.rank === 4,
-          () => "Error in cropAndResize: image must be rank 4," + `but got rank ${$image.rank}.`
-        );
-        util["assert"](
-          $boxes.rank === 2 && $boxes.shape[1] === 4,
-          () =>
-            `Error in cropAndResize: boxes must be have size [${numBoxes},4] ` +
-            `but had shape ${$boxes.shape}.`
-        );
-        util["assert"](
-          $boxInd.rank === 1 && $boxInd.shape[0] === numBoxes,
-          () =>
-            `Error in cropAndResize: boxInd must be have size [${numBoxes}] ` +
-            `but had shape ${$boxes.shape}.`
-        );
-        util["assert"](
-          cropSize.length === 2,
-          () =>
-            `Error in cropAndResize: cropSize must be of length 2, but got ` +
-            `length ${cropSize.length}.`
-        );
-        util["assert"](
-          cropSize[0] >= 1 && cropSize[1] >= 1,
-          () => `cropSize must be atleast [1,1], but was ${cropSize}`
-        );
-        util["assert"](
-          method === "bilinear" || method === "nearest",
-          () => `method must be bilinear or nearest, but was ${method}`
-        );
-        const forward = (backend, save) =>
-          backend.cropAndResize($image, $boxes, $boxInd, cropSize, method, extrapolationValue);
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          forward,
-          { images: $image, boxes: $boxes, boxInd: $boxInd },
-          null /* der */,
-          "CropAndResize",
-          { method, extrapolationValue, cropSize }
-        );
-        return res;
-      }
-      const resizeBilinear = Object(operation["a" /* op */])({ resizeBilinear_ });
-      const resizeNearestNeighbor = Object(operation["a" /* op */])({ resizeNearestNeighbor_ });
-      const nonMaxSuppressionAsync = nonMaxSuppressionAsync_;
-      const nonMaxSuppressionWithScore = Object(operation["a" /* op */])({
-        nonMaxSuppressionWithScore_,
-      });
-      const nonMaxSuppressionWithScoreAsync = nonMaxSuppressionWithScoreAsync_;
-      const cropAndResize = Object(operation["a" /* op */])({ cropAndResize_ });
-      //# sourceMappingURL=image_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/fused_util.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // Whether we should call fused ops.
-      const shouldFuse = (gradientDepth, activation) => {
-        const gradientMode = gradientDepth > 0;
-        return !gradientMode || activation === "linear";
-      };
-      //# sourceMappingURL=fused_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/fused_ops.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // Returns gradient for fused activation.
-      const getFusedDyActivation = (dy, y, activation) => {
-        if (activation == null || activation === "linear") {
-          return dy;
-        }
-        if (activation === "relu") {
-          return dy.mul(y.step());
-        }
-        throw new Error(`Gradient for activation ${activation} has not been ` + `implemented yet.`);
-      };
-      // Returns gradient for fused bias.
-      const getFusedBiasGradient = (bias, dyActivation) => {
-        let res = dyActivation;
-        const reduceAxes = getReductionAxes(bias.shape, dyActivation.shape);
-        if (reduceAxes.length > 0) {
-          res = res.sum(reduceAxes);
-        }
-        return res.reshape(bias.shape);
-      };
-      const applyActivation = (x, activation, preluActivationWeights) => {
-        if (activation === "linear") {
-          return x;
-        } else if (activation === "relu") {
-          return relu(x);
-        } else if (activation === "elu") {
-          return elu(x);
-        } else if (activation === "relu6") {
-          return relu6(x);
-        } else if (activation === "prelu") {
-          return prelu(x, preluActivationWeights);
-        }
-        throw new Error(`Unknown fused activation ${activation}.`);
-      };
-      /**
-       * Computes the dot product of two matrices with optional activation and bias.
-       *
-       * ```js
-       * const a = tf.tensor2d([-1, -2], [1, 2]);
-       * const b = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       * const bias = tf.tensor2d([1, 2], [1, 2]);
-       *
-       * tf.fused.matMul({a, b, bias, activation: 'relu'}).print();
-       * ```
-       *
-       * @param obj An object with the following properties:
-       * - `a` First matrix in dot product operation.
-       * - `b` Second matrix in dot product operation.
-       * - `transposeA` If true, `a` is transposed before multiplication.
-       * - `transposeB` If true, `b` is transposed before multiplication.
-       * - `bias` Matrix to be added to the result.
-       * - `activation` Name of activation kernel (defaults to `linear`).
-       * - `preluActivationWeights` Tensor of prelu weights.
-       */
-      function fusedMatMul_({
-        a,
-        b,
-        transposeA = false,
-        transposeB = false,
-        bias,
-        activation = "linear",
-        preluActivationWeights,
-      }) {
-        if (shouldFuse(engine["a" /* ENGINE */].state.gradientDepth, activation) === false) {
-          let result = matMul(a, b, transposeA, transposeB);
-          if (bias != null) {
-            result = add(result, bias);
-          }
-          return applyActivation(result, activation, preluActivationWeights);
-        }
-        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "fused matMul");
-        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "fused matMul");
-        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
-        const innerShapeA = transposeA ? $a.shape[$a.rank - 2] : $a.shape[$a.rank - 1];
-        const innerShapeB = transposeB ? $b.shape[$b.rank - 1] : $b.shape[$b.rank - 2];
-        const outerShapeA = transposeA ? $a.shape[$a.rank - 1] : $a.shape[$a.rank - 2];
-        const outerShapeB = transposeB ? $b.shape[$b.rank - 2] : $b.shape[$b.rank - 1];
-        const outerDimsA = $a.shape.slice(0, -2);
-        const outerDimsB = $b.shape.slice(0, -2);
-        const batchDimA = util["sizeFromShape"](outerDimsA);
-        const batchDimB = util["sizeFromShape"](outerDimsB);
-        util["assert"](
-          $a.rank >= 2 && $b.rank >= 2 && $a.rank === $b.rank,
-          () =>
-            `Error in fused matMul: inputs must have the same rank of at least ` +
-            `2, got ranks ${$a.rank} and ${$b.rank}.`
-        );
-        util["assert"](
-          util["arraysEqual"](outerDimsA, outerDimsB),
-          () =>
-            `Error in fused matMul: outer dimensions (${outerDimsA}) and (` +
-            `${outerDimsB}) of Tensors with shapes ${$a.shape} and ` +
-            `${$b.shape} must match.`
-        );
-        util["assert"](
-          innerShapeA === innerShapeB,
-          () =>
-            `Error in fused matMul: inner shapes (${innerShapeA}) and (` +
-            `${innerShapeB}) of Tensors with shapes ${$a.shape} and ` +
-            `${$b.shape} and transposeA=${transposeA}` +
-            ` and transposeB=${transposeB} must match.`
-        );
-        const outShape = $a.shape.slice(0, -2).concat([outerShapeA, outerShapeB]);
-        const a3D = transposeA
-          ? $a.as3D(batchDimA, innerShapeA, outerShapeA)
-          : $a.as3D(batchDimA, outerShapeA, innerShapeA);
-        const b3D = transposeB
-          ? $b.as3D(batchDimB, outerShapeB, innerShapeB)
-          : $b.as3D(batchDimB, innerShapeB, outerShapeB);
-        let $bias;
-        if (bias != null) {
-          $bias = Object(tensor_util_env["a" /* convertToTensor */])(bias, "bias", "fused matMul");
-          [$bias] = Object(tensor_util["makeTypesMatch"])($bias, $a);
-          assertAndGetBroadcastShape(outShape, $bias.shape);
-        }
-        let $preluActivationWeights;
-        if (preluActivationWeights != null) {
-          $preluActivationWeights = Object(tensor_util_env["a" /* convertToTensor */])(
-            preluActivationWeights,
-            "prelu weights",
-            "fused matMul"
-          );
-        }
-        const grad = (dy, saved) => {
-          const [a3D, b3D, y] = saved;
-          const dyActivation = getFusedDyActivation(dy, y, activation);
-          let biasGradient = {};
-          if (bias != null) {
-            biasGradient = { bias: () => getFusedBiasGradient($bias, dyActivation) };
-          }
-          if (!transposeA && !transposeB) {
-            return Object.assign(
-              {
-                a: () => dyActivation.matMul(b3D, false, true),
-                b: () => a3D.matMul(dyActivation, true, false),
-              },
-              biasGradient
-            );
-          } else if (!transposeA && transposeB) {
-            return Object.assign(
-              {
-                a: () => dyActivation.matMul(b3D, false, false),
-                b: () => dyActivation.matMul(a3D, true, false),
-              },
-              biasGradient
-            );
-          } else if (transposeA && !transposeB) {
-            return Object.assign(
-              {
-                a: () => b3D.matMul(dyActivation, false, true),
-                b: () => a3D.matMul(dyActivation, false, false),
-              },
-              biasGradient
-            );
-          } else {
-            return Object.assign(
-              {
-                a: () => b3D.matMul(dyActivation, true, true),
-                b: () => dyActivation.matMul(a3D, true, true),
-              },
-              biasGradient
-            );
-          }
-        };
-        const inputs = { a: a3D, b: b3D };
-        if (bias != null) {
-          inputs.bias = $bias;
-        }
-        if (preluActivationWeights != null) {
-          inputs.preluActivationWeights = $preluActivationWeights;
-        }
-        const inputsToSave = [a3D, b3D];
-        const outputsToSave = [true];
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const y = backend.fusedBatchMatMul({
-              a: a3D,
-              b: b3D,
-              transposeA,
-              transposeB,
-              bias: $bias,
-              activation,
-              preluActivationWeights: $preluActivationWeights,
-            });
-            save([a3D, b3D, y]);
-            return y;
-          },
-          inputs,
-          grad,
-          "_FusedMatMul",
-          { transposeA, transposeB, activation },
-          inputsToSave,
-          outputsToSave
-        );
-        return res.reshape(outShape);
-      }
-      /**
-       * Computes a 2D convolution over the input x, optionally fused with adding a
-       * bias and applying an activation.
-       *
-       * ```js
-       * const inputDepth = 2;
-       * const inShape = [2, 2, 2, inputDepth];
-       * const outputDepth = 2;
-       * const fSize = 1;
-       * const pad = 0;
-       * const strides = 1;
-       *
-       * const x = tf.tensor4d( [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-       * 16], inShape);
-       * const w = tf.tensor4d([-1, 1, -2, 0.5], [fSize, fSize, inputDepth,
-       * outputDepth]);
-       *
-       * tf.fused.conv2d({ x, filter: w, strides, pad, dataFormat: 'NHWC',
-       * dilations: [1, 1], bias: tf.scalar(5), activation: 'relu' }).print();
-       * ```
-       *
-       * @param obj An object with the following properties:
-       * @param x The input tensor, of rank 4 or rank 3, of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
-       * assumed.
-       * @param filter The filter, rank 4, of shape
-       *     `[filterHeight, filterWidth, inDepth, outDepth]`.
-       * @param strides The strides of the convolution: `[strideHeight,
-       * strideWidth]`.
-       * @param pad The type of padding algorithm.
-       *   - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *   - `valid` output will be smaller than input if filter is larger
-       *       than 1x1.
-       *   - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dataFormat An optional string from: "NHWC", "NCHW". Defaults to
-       *     "NHWC". Specify the data format of the input and output data. With the
-       *     default format "NHWC", the data is stored in the order of: [batch,
-       *     height, width, channels]. Only "NHWC" is currently supported.
-       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
-       *     in which we sample input values across the height and width dimensions
-       *     in atrous convolution. Defaults to `[1, 1]`. If `dilations` is a single
-       *     number, then `dilationHeight == dilationWidth`. If it is greater than
-       *     1, then all values of `strides` must be 1.
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       * @param bias Tensor to be added to the result.
-       * @param activation Name of activation kernel (defaults to `linear`) to be
-       *     applied
-       *      after biasAdd.
-       * @param preluActivationWeights Tensor of prelu weights to be applied as part
-       *     of a `prelu` activation, typically the same shape as `x`.
-       */
-      function fusedConv2d_({
-        x,
-        filter,
-        strides,
-        pad,
-        dataFormat = "NHWC",
-        dilations = [1, 1],
-        dimRoundingMode,
-        bias,
-        activation = "linear",
-        preluActivationWeights,
-      }) {
-        activation = activation || "linear";
-        if (shouldFuse(engine["a" /* ENGINE */].state.gradientDepth, activation) === false) {
-          let result = conv2d(x, filter, strides, pad, dataFormat, dilations, dimRoundingMode);
-          if (bias != null) {
-            result = add(result, bias);
-          }
-          return applyActivation(result, activation, preluActivationWeights);
-        }
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv2d");
-        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
-          filter,
-          "filter",
-          "conv2d"
-        );
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = $x.as4D(1, $x.shape[0], $x.shape[1], $x.shape[2]);
-        }
-        util["assert"](
-          x4D.rank === 4,
-          () => `Error in fused conv2d: input must be rank 4, but got rank ` + `${x4D.rank}.`
-        );
-        util["assert"](
-          $filter.rank === 4,
-          () => `Error in fused conv2d: filter must be rank 4, but got rank ` + `${$filter.rank}.`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in fused conv2d: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        util["assert"](
-          x4D.shape[3] === $filter.shape[2],
-          () =>
-            `Error in conv2d: depth of input (${x4D.shape[3]}) must match ` +
-            `input depth for filter ${$filter.shape[2]}.`
-        );
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in conv2D: Either strides or dilations must be 1. " +
-            `Got strides ${strides} and dilations '${dilations}'`
-        );
-        util["assert"](
-          dataFormat === "NHWC",
-          () =>
-            `Error in conv2d: got dataFormat of ${dataFormat} but only NHWC is currently supported.`
-        );
-        const convInfo = computeConv2DInfo(
-          x4D.shape,
-          $filter.shape,
-          strides,
-          dilations,
-          pad,
-          dimRoundingMode
-        );
-        let $bias;
-        if (bias != null) {
-          $bias = Object(tensor_util_env["a" /* convertToTensor */])(bias, "bias", "fused conv2d");
-          [$bias] = Object(tensor_util["makeTypesMatch"])($bias, $x);
-          assertAndGetBroadcastShape(convInfo.outShape, $bias.shape);
-        }
-        let $preluActivationWeights;
-        if (preluActivationWeights != null) {
-          $preluActivationWeights = Object(tensor_util_env["a" /* convertToTensor */])(
-            preluActivationWeights,
-            "prelu weights",
-            "fused conv2d"
-          );
-        }
-        const grad = (dy, saved) => {
-          const [$filter, x4D, y] = saved;
-          const dyActivation = getFusedDyActivation(dy, y, activation);
-          util["assert"](
-            tupleValuesAreOne(dilations),
-            () =>
-              "Error in gradient of fused conv2D: " +
-              `dilation rates greater than 1 ` +
-              `are not yet supported in gradients. Got dilations '${dilations}'`
-          );
-          let biasGradient = {};
-          if (bias != null) {
-            biasGradient = { bias: () => getFusedBiasGradient($bias, dyActivation) };
-          }
-          return Object.assign(
-            {
-              x: () => conv2DBackpropInput(x4D.shape, dyActivation, $filter, strides, pad),
-              filter: () => conv2DBackpropFilter(x4D, dyActivation, $filter.shape, strides, pad),
-            },
-            biasGradient
-          );
-        };
-        const inputs = { x: x4D, filter: $filter };
-        if (bias != null) {
-          inputs.bias = $bias;
-        }
-        if (preluActivationWeights != null) {
-          inputs.preluActivationWeights = $preluActivationWeights;
-        }
-        const inputsToSave = [$filter, x4D];
-        const outputsToSave = [true]; // Save the only output.
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.fusedConv2d({
-              input: x4D,
-              filter: $filter,
-              convInfo,
-              bias: $bias,
-              activation,
-              preluActivationWeights: $preluActivationWeights,
-            });
-            save([$filter, x4D, res]);
-            return res;
-          },
-          inputs,
-          grad,
-          "FusedConv2D",
-          { convInfo, activation },
-          inputsToSave,
-          outputsToSave
-        );
-        if (reshapedTo4D) {
-          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
-        }
-        return res;
-      }
-      /**
-       * Computes depthwise 2D convolution, optionally fused with adding a
-       * bias and applying an activation.
-       *
-       * Given a 4D `input` array and a `filter` array of shape
-       * `[filterHeight, filterWidth, inChannels, channelMultiplier]` containing
-       * `inChannels` convolutional filters of depth 1, this op applies a
-       * different filter to each input channel (expanding from 1 channel to
-       * `channelMultiplier` channels for each), then concatenates the results
-       * together. The output has `inChannels * channelMultiplier` channels.
-       *
-       * See
-       * [https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d](
-       *     https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d)
-       * for more details.
-       *
-       * @param obj An object with the following properties:
-       * @param x The input tensor, of rank 4 or rank 3, of shape
-       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
-       * assumed.
-       * @param filter The filter tensor, rank 4, of shape
-       *     `[filterHeight, filterWidth, inChannels, channelMultiplier]`.
-       * @param strides The strides of the convolution: `[strideHeight,
-       * strideWidth]`. If strides is a single number, then `strideHeight ==
-       * strideWidth`.
-       * @param pad The type of padding algorithm.
-       *   - `same` and stride 1: output will be of same size as input,
-       *       regardless of filter size.
-       *   - `valid`: output will be smaller than input if filter is larger
-       *       than 1x1.
-       *   - For more info, see this guide:
-       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
-       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
-       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
-       *     in which we sample input values across the height and width dimensions
-       *     in atrous convolution. Defaults to `[1, 1]`. If `rate` is a single
-       *     number, then `dilationHeight == dilationWidth`. If it is greater than
-       *     1, then all values of `strides` must be 1.
-       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
-       *     "NHWC". Specify the data format of the input and output data. With the
-       *     default format "NHWC", the data is stored in the order of: [batch,
-       *     height, width, channels]. Only "NHWC" is currently supported.
-       * @param dimRoundingMode The rounding mode used when computing output
-       *     dimensions if pad is a number. If none is provided, it will not round
-       *     and error if the output is of fractional size.
-       * @param bias Tensor to be added to the result.
-       * @param activation Name of activation kernel (defaults to `linear`).
-       * @param preluActivationWeights Tensor of prelu weights to be applied as part
-       *     of a `prelu` activation, typically the same shape as `x`.
-       */
-      function fusedDepthwiseConv2d_({
-        x,
-        filter,
-        strides,
-        pad,
-        dataFormat = "NHWC",
-        dilations = [1, 1],
-        dimRoundingMode,
-        bias,
-        activation = "linear",
-        preluActivationWeights,
-      }) {
-        if (shouldFuse(engine["a" /* ENGINE */].state.gradientDepth, activation) === false) {
-          let result = depthwiseConv2d(
-            x,
-            filter,
-            strides,
-            pad,
-            dataFormat,
-            dilations,
-            dimRoundingMode
-          );
-          if (bias != null) {
-            result = add(result, bias);
-          }
-          return applyActivation(result, activation, preluActivationWeights);
-        }
-        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "depthwiseConv2d");
-        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
-          filter,
-          "filter",
-          "depthwiseConv2d"
-        );
-        let x4D = $x;
-        let reshapedTo4D = false;
-        if ($x.rank === 3) {
-          reshapedTo4D = true;
-          x4D = $x.as4D(1, $x.shape[0], $x.shape[1], $x.shape[2]);
-        }
-        util["assert"](
-          x4D.rank === 4,
-          () =>
-            `Error in fused depthwiseConv2d: input must be rank 4, but got ` + `rank ${x4D.rank}.`
-        );
-        util["assert"](
-          $filter.rank === 4,
-          () =>
-            `Error in fused depthwiseConv2d: filter must be rank 4, ` +
-            `but got rank ${$filter.rank}.`
-        );
-        util["assert"](
-          x4D.shape[3] === $filter.shape[2],
-          () =>
-            `Error in fused depthwiseConv2d: number of input channels ` +
-            `(${x4D.shape[3]}) must match the inChannels dimension in ` +
-            `filter ${$filter.shape[2]}.`
-        );
-        if (dilations == null) {
-          dilations = [1, 1];
-        }
-        util["assert"](
-          eitherStridesOrDilationsAreOne(strides, dilations),
-          () =>
-            "Error in fused depthwiseConv2d: Either strides or dilations must " +
-            `be 1. Got strides ${strides} and dilations '${dilations}'`
-        );
-        if (dimRoundingMode != null) {
-          util["assert"](
-            util["isInt"](pad),
-            () =>
-              `Error in fused depthwiseConv2d: pad must be an integer when ` +
-              `using dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
-          );
-        }
-        const convInfo = computeConv2DInfo(
-          x4D.shape,
-          $filter.shape,
-          strides,
-          dilations,
-          pad,
-          dimRoundingMode,
-          true /* depthwise */
-        );
-        let $bias;
-        if (bias != null) {
-          $bias = Object(tensor_util_env["a" /* convertToTensor */])(bias, "bias", "fused conv2d");
-          [$bias] = Object(tensor_util["makeTypesMatch"])($bias, $x);
-          assertAndGetBroadcastShape(convInfo.outShape, $bias.shape);
-        }
-        let $preluActivationWeights;
-        if (preluActivationWeights != null) {
-          $preluActivationWeights = Object(tensor_util_env["a" /* convertToTensor */])(
-            preluActivationWeights,
-            "prelu weights",
-            "fused depthwiseConv2d"
-          );
-        }
-        const grad = (dy, saved) => {
-          util["assert"](
-            tupleValuesAreOne(dilations),
-            () =>
-              "Error in gradient of fused depthwiseConv2d: dilation rates " +
-              `greater than 1 are not yet supported. Got dilations ` +
-              `'${dilations}'`
-          );
-          const [$filter, x4D, y] = saved;
-          const dyActivation = getFusedDyActivation(dy, y, activation);
-          let biasGradient = {};
-          if (bias != null) {
-            biasGradient = { bias: () => getFusedBiasGradient($bias, dyActivation) };
-          }
-          return Object.assign(
-            {
-              x: () =>
-                depthwiseConv2dNativeBackpropInput(x4D.shape, dyActivation, $filter, convInfo),
-              filter: () =>
-                depthwiseConv2dNativeBackpropFilter(x4D, dyActivation, $filter.shape, convInfo),
-            },
-            biasGradient
-          );
-        };
-        const inputs = { x: x4D, filter: $filter };
-        if (bias != null) {
-          inputs.bias = $bias;
-        }
-        if (preluActivationWeights != null) {
-          inputs.preluActivationWeights = $preluActivationWeights;
-        }
-        const inputsToSave = [$filter, x4D];
-        const outputsToSave = [true];
-        const res = engine["a" /* ENGINE */].runKernelFunc(
-          (backend, save) => {
-            const res = backend.fusedDepthwiseConv2D({
-              input: x4D,
-              filter: $filter,
-              convInfo,
-              bias: $bias,
-              activation,
-              preluActivationWeights: $preluActivationWeights,
-            });
-            save([$filter, x4D, res]);
-            return res;
-          },
-          inputs,
-          grad,
-          "FusedDepthwiseConv2D",
-          { convInfo, activation },
-          inputsToSave,
-          outputsToSave
-        );
-        if (reshapedTo4D) {
-          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
-        }
-        return res;
-      }
-      const fused_ops_matMul = Object(operation["a" /* op */])({ fusedMatMul_ });
-      const fused_ops_conv2d = Object(operation["a" /* op */])({ fusedConv2d_ });
-      const fused_ops_depthwiseConv2d = Object(operation["a" /* op */])({ fusedDepthwiseConv2d_ });
-      //# sourceMappingURL=fused_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/ops.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // Modularized ops.
-
-      // Second level exports.
-
-      //# sourceMappingURL=ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/optimizer.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /** @doc {heading: 'Training', subheading: 'Classes', namespace: 'train'} */
-      class optimizer_Optimizer extends Serializable {
-        /**
-         * Executes `f()` and minimizes the scalar output of `f()` by computing
-         * gradients of y with respect to the list of trainable variables provided by
-         * `varList`. If no list is provided, it defaults to all trainable variables.
-         *
-         * @param f The function to execute and whose output to minimize.
-         * @param returnCost Whether to return the scalar cost value produced by
-         * executing `f()`.
-         * @param varList An optional list of variables to update. If specified, only
-         * the trainable variables in varList will be updated by minimize. Defaults to
-         * all trainable variables.
-         */
-        /** @doc {heading: 'Training', subheading: 'Optimizers'} */
-        minimize(f, returnCost = false, varList) {
-          const { value, grads } = this.computeGradients(f, varList);
-          if (varList != null) {
-            const gradArray = varList.map((v) => ({ name: v.name, tensor: grads[v.name] }));
-            this.applyGradients(gradArray);
-          } else {
-            this.applyGradients(grads);
-          }
-          // Dispose gradients.
-          dispose(grads);
-          if (returnCost) {
-            return value;
-          } else {
-            value.dispose();
-            return null;
-          }
-        }
-        /**
-         * The number of iterations that this optimizer instance has been invoked for.
-         */
-        get iterations() {
-          if (this.iterations_ == null) {
-            this.iterations_ = 0;
-          }
-          return this.iterations_;
-        }
-        incrementIterations() {
-          this.iterations_ = this.iterations + 1;
-        }
-        /**
-         * Executes f() and computes the gradient of the scalar output of f() with
-         * respect to the list of trainable variables provided by `varList`. If no
-         * list is provided, it defaults to all trainable variables.
-         *
-         * @param f The function to execute and whose output to use for computing
-         * gradients with respect to variables.
-         * @param varList An optional list of variables to compute gradients with
-         * respect to. If specified, only the trainable variables in varList will have
-         * gradients computed with respect to. Defaults to all trainable variables.
-         */
-        computeGradients(f, varList) {
-          return variableGrads(f, varList);
-        }
-        /**
-         * Dispose the variables (if any) owned by this optimizer instance.
-         */
-        dispose() {
-          if (this.iterations_ != null) {
-            dispose(this.iterations_);
-          }
-        }
-        async saveIterations() {
-          if (this.iterations_ == null) {
-            this.iterations_ = 0;
-          }
-          return {
-            name: "iter",
-            // TODO(cais): Use 'int64' type when available.
-            tensor: Object(tensor_ops["e" /* scalar */])(this.iterations_, "int32"),
-          };
-        }
-        async getWeights() {
-          throw new Error("getWeights() is not implemented for this optimizer yet.");
-        }
-        async setWeights(weightValues) {
-          throw new Error(
-            `setWeights() is not implemented for this optimizer class ` + `${this.getClassName()}`
-          );
-        }
-        /**
-         * Extract the first element of the weight values and set it
-         * as the iterations counter variable of this instance of optimizer.
-         *
-         * @param weightValues
-         * @returns Weight values with the first element consumed and excluded.
-         */
-        async extractIterations(weightValues) {
-          this.iterations_ = (await weightValues[0].tensor.data())[0];
-          return weightValues.slice(1);
-        }
-      }
-      Object.defineProperty(optimizer_Optimizer, Symbol.hasInstance, {
-        value: (instance) => {
-          return (
-            instance.minimize != null &&
-            instance.computeGradients != null &&
-            instance.applyGradients != null
-          );
-        },
-      });
-      //# sourceMappingURL=optimizer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/adadelta_optimizer.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /** @doclink Optimizer */
-      class adadelta_optimizer_AdadeltaOptimizer extends optimizer_Optimizer {
-        constructor(learningRate, rho, epsilon = null) {
-          super();
-          this.learningRate = learningRate;
-          this.rho = rho;
-          this.epsilon = epsilon;
-          this.accumulatedGrads = [];
-          this.accumulatedUpdates = [];
-          if (epsilon == null) {
-            this.epsilon = engine["a" /* ENGINE */].backend.epsilon();
-          }
-        }
-        applyGradients(variableGradients) {
-          const variableNames = Array.isArray(variableGradients)
-            ? variableGradients.map((item) => item.name)
-            : Object.keys(variableGradients);
-          variableNames.forEach((name, i) => {
-            const value = engine["a" /* ENGINE */].registeredVariables[name];
-            const trainable = false;
-            if (this.accumulatedGrads[i] == null) {
-              this.accumulatedGrads[i] = {
-                originalName: `${name}/accum_grad`,
-                variable: tidy(() =>
-                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
-                ),
-              };
-            }
-            if (this.accumulatedUpdates[i] == null) {
-              this.accumulatedUpdates[i] = {
-                originalName: `${name}/accum_var`,
-                variable: tidy(() =>
-                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
-                ),
-              };
-            }
-            const gradient = Array.isArray(variableGradients)
-              ? variableGradients[i].tensor
-              : variableGradients[name];
-            if (gradient == null) {
-              return;
-            }
-            const accumulatedGrad = this.accumulatedGrads[i].variable;
-            const accumulatedUpdate = this.accumulatedUpdates[i].variable;
-            tidy(() => {
-              const newAccumulatedGrad = accumulatedGrad
-                .mul(this.rho)
-                .add(gradient.square().mul(1 - this.rho));
-              const updates = accumulatedUpdate
-                .add(this.epsilon)
-                .sqrt()
-                .div(accumulatedGrad.add(this.epsilon).sqrt())
-                .mul(gradient);
-              const newAccumulatedUpdate = accumulatedUpdate
-                .mul(this.rho)
-                .add(updates.square().mul(1 - this.rho));
-              accumulatedGrad.assign(newAccumulatedGrad);
-              accumulatedUpdate.assign(newAccumulatedUpdate);
-              const newValue = updates.mul(-this.learningRate).add(value);
-              value.assign(newValue);
-            });
-          });
-          this.incrementIterations();
-        }
-        dispose() {
-          if (this.accumulatedUpdates != null) {
-            dispose(this.accumulatedGrads.map((v) => v.variable));
-            dispose(this.accumulatedUpdates.map((v) => v.variable));
-          }
-        }
-        async getWeights() {
-          // Order matters for Python compatibility.
-          const variables = [...this.accumulatedGrads, ...this.accumulatedUpdates];
-          return [await this.saveIterations()].concat(
-            variables.map((v) => ({ name: v.originalName, tensor: v.variable }))
-          );
-        }
-        async setWeights(weightValues) {
-          weightValues = await this.extractIterations(weightValues);
-          const variableCount = weightValues.length / 2;
-          const trainable = false;
-          this.accumulatedGrads = weightValues.slice(0, variableCount).map((v) => ({
-            originalName: v.name,
-            variable: v.tensor.variable(trainable),
-          }));
-          this.accumulatedUpdates = weightValues
-            .slice(variableCount, variableCount * 2)
-            .map((v) => ({
-              originalName: v.name,
-              variable: v.tensor.variable(trainable),
-            }));
-        }
-        getConfig() {
-          return {
-            learningRate: this.learningRate,
-            rho: this.rho,
-            epsilon: this.epsilon,
-          };
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(config["learningRate"], config["rho"], config["epsilon"]);
-        }
-      }
-      /** @nocollapse */
-      adadelta_optimizer_AdadeltaOptimizer.className = "Adadelta"; // Name matters for Python compatibility.
-      registerClass(adadelta_optimizer_AdadeltaOptimizer);
-      //# sourceMappingURL=adadelta_optimizer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/adagrad_optimizer.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /** @doclink Optimizer */
-      class adagrad_optimizer_AdagradOptimizer extends optimizer_Optimizer {
-        constructor(learningRate, initialAccumulatorValue = 0.1) {
-          super();
-          this.learningRate = learningRate;
-          this.initialAccumulatorValue = initialAccumulatorValue;
-          this.accumulatedGrads = [];
-        }
-        applyGradients(variableGradients) {
-          const variableNames = Array.isArray(variableGradients)
-            ? variableGradients.map((item) => item.name)
-            : Object.keys(variableGradients);
-          variableNames.forEach((name, i) => {
-            const value = engine["a" /* ENGINE */].registeredVariables[name];
-            if (this.accumulatedGrads[i] == null) {
-              const trainable = false;
-              this.accumulatedGrads[i] = {
-                originalName: `${name}/accumulator`,
-                variable: tidy(() =>
-                  fill(value.shape, this.initialAccumulatorValue).variable(trainable)
-                ),
-              };
-            }
-            const gradient = Array.isArray(variableGradients)
-              ? variableGradients[i].tensor
-              : variableGradients[name];
-            if (gradient == null) {
-              return;
-            }
-            const accumulatedGrad = this.accumulatedGrads[i].variable;
-            tidy(() => {
-              const newAccumulatedGrad = accumulatedGrad.add(gradient.square());
-              accumulatedGrad.assign(newAccumulatedGrad);
-              const newValue = gradient
-                .div(newAccumulatedGrad.add(engine["a" /* ENGINE */].backend.epsilon()).sqrt())
-                .mul(-this.learningRate)
-                .add(value);
-              value.assign(newValue);
-            });
-          });
-          this.incrementIterations();
-        }
-        dispose() {
-          if (this.accumulatedGrads != null) {
-            dispose(this.accumulatedGrads.map((v) => v.variable));
-          }
-        }
-        async getWeights() {
-          // Order matters for Python compatibility.
-          return [await this.saveIterations()].concat(
-            this.accumulatedGrads.map((v) => ({ name: v.originalName, tensor: v.variable }))
-          );
-        }
-        async setWeights(weightValues) {
-          weightValues = await this.extractIterations(weightValues);
-          const trainable = false;
-          this.accumulatedGrads = weightValues.map((v) => ({
-            originalName: v.name,
-            variable: v.tensor.variable(trainable),
-          }));
-        }
-        getConfig() {
-          return {
-            learningRate: this.learningRate,
-            initialAccumulatorValue: this.initialAccumulatorValue,
-          };
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(config["learningRate"], config["initialAccumulatorValue"]);
-        }
-      }
-      /** @nocollapse */
-      adagrad_optimizer_AdagradOptimizer.className = "Adagrad"; // Note: Name matters for Python compatibility.
-      registerClass(adagrad_optimizer_AdagradOptimizer);
-      //# sourceMappingURL=adagrad_optimizer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/adam_optimizer.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class adam_optimizer_AdamOptimizer extends optimizer_Optimizer {
-        constructor(learningRate, beta1, beta2, epsilon = null) {
-          super();
-          this.learningRate = learningRate;
-          this.beta1 = beta1;
-          this.beta2 = beta2;
-          this.epsilon = epsilon;
-          this.accumulatedFirstMoment = [];
-          this.accumulatedSecondMoment = [];
-          tidy(() => {
-            // accB* will be updated by batch.
-            this.accBeta1 = Object(tensor_ops["e" /* scalar */])(beta1).variable();
-            this.accBeta2 = Object(tensor_ops["e" /* scalar */])(beta2).variable();
-          });
-          if (epsilon == null) {
-            this.epsilon = engine["a" /* ENGINE */].backend.epsilon();
-          }
-        }
-        applyGradients(variableGradients) {
-          const varNames = Array.isArray(variableGradients)
-            ? variableGradients.map((v) => v.name)
-            : Object.keys(variableGradients);
-          tidy(() => {
-            const oneMinusAccBeta1 = sub(1, this.accBeta1);
-            const oneMinusAccBeta2 = sub(1, this.accBeta2);
-            varNames.forEach((name, i) => {
-              const value = engine["a" /* ENGINE */].registeredVariables[name];
-              const trainable = false;
-              if (this.accumulatedFirstMoment[i] == null) {
-                this.accumulatedFirstMoment[i] = {
-                  originalName: `${name}/m`,
-                  variable: tidy(() =>
-                    Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
-                  ),
-                };
-              }
-              if (this.accumulatedSecondMoment[i] == null) {
-                this.accumulatedSecondMoment[i] = {
-                  originalName: `${name}/v`,
-                  variable: tidy(() =>
-                    Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
-                  ),
-                };
-              }
-              const gradient = Array.isArray(variableGradients)
-                ? variableGradients[i].tensor
-                : variableGradients[name];
-              if (gradient == null) {
-                return;
-              }
-              const firstMoment = this.accumulatedFirstMoment[i].variable;
-              const secondMoment = this.accumulatedSecondMoment[i].variable;
-              const newFirstMoment = firstMoment.mul(this.beta1).add(gradient.mul(1 - this.beta1));
-              const newSecondMoment = secondMoment
-                .mul(this.beta2)
-                .add(gradient.square().mul(1 - this.beta2));
-              const biasCorrectedFirstMoment = newFirstMoment.div(oneMinusAccBeta1);
-              const biasCorrectedSecondMoment = newSecondMoment.div(oneMinusAccBeta2);
-              firstMoment.assign(newFirstMoment);
-              secondMoment.assign(newSecondMoment);
-              const newValue = biasCorrectedFirstMoment
-                .div(biasCorrectedSecondMoment.sqrt().add(this.epsilon))
-                .mul(-this.learningRate)
-                .add(value);
-              value.assign(newValue);
-            });
-            this.accBeta1.assign(this.accBeta1.mul(this.beta1));
-            this.accBeta2.assign(this.accBeta2.mul(this.beta2));
-          });
-          this.incrementIterations();
-        }
-        dispose() {
-          this.accBeta1.dispose();
-          this.accBeta2.dispose();
-          if (this.accumulatedFirstMoment != null) {
-            dispose(this.accumulatedFirstMoment.map((v) => v.variable));
-          }
-          if (this.accumulatedSecondMoment != null) {
-            dispose(this.accumulatedSecondMoment.map((v) => v.variable));
-          }
-        }
-        async getWeights() {
-          // Order matters for Python compatibility.
-          const variables = [...this.accumulatedFirstMoment, ...this.accumulatedSecondMoment];
-          return [await this.saveIterations()].concat(
-            variables.map((v) => ({ name: v.originalName, tensor: v.variable }))
-          );
-        }
-        async setWeights(weightValues) {
-          weightValues = await this.extractIterations(weightValues);
-          tidy(() => {
-            this.accBeta1.assign(pow(this.beta1, this.iterations_ + 1));
-            this.accBeta2.assign(pow(this.beta2, this.iterations_ + 1));
-          });
-          const variableCount = weightValues.length / 2;
-          const trainable = false;
-          this.accumulatedFirstMoment = weightValues.slice(0, variableCount).map((v) => ({
-            originalName: v.name,
-            variable: v.tensor.variable(trainable),
-          }));
-          this.accumulatedSecondMoment = weightValues
-            .slice(variableCount, variableCount * 2)
-            .map((v) => ({
-              originalName: v.name,
-              variable: v.tensor.variable(trainable),
-            }));
-        }
-        getConfig() {
-          return {
-            learningRate: this.learningRate,
-            beta1: this.beta1,
-            beta2: this.beta2,
-            epsilon: this.epsilon,
-          };
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(
-            config["learningRate"],
-            config["beta1"],
-            config["beta2"],
-            config["epsilon"]
-          );
-        }
-      }
-      /** @nocollapse */
-      adam_optimizer_AdamOptimizer.className = "Adam"; // Note: Name matters for Python compatibility.
-      registerClass(adam_optimizer_AdamOptimizer);
-      //# sourceMappingURL=adam_optimizer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/adamax_optimizer.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class adamax_optimizer_AdamaxOptimizer extends optimizer_Optimizer {
-        constructor(learningRate, beta1, beta2, epsilon = null, decay = 0.0) {
-          super();
-          this.learningRate = learningRate;
-          this.beta1 = beta1;
-          this.beta2 = beta2;
-          this.epsilon = epsilon;
-          this.decay = decay;
-          this.accumulatedFirstMoment = [];
-          this.accumulatedWeightedInfNorm = [];
-          tidy(() => {
-            this.iteration = Object(tensor_ops["e" /* scalar */])(0).variable();
-            this.accBeta1 = Object(tensor_ops["e" /* scalar */])(beta1).variable();
-          });
-          if (epsilon == null) {
-            this.epsilon = engine["a" /* ENGINE */].backend.epsilon();
-          }
-        }
-        applyGradients(variableGradients) {
-          const variableNames = Array.isArray(variableGradients)
-            ? variableGradients.map((item) => item.name)
-            : Object.keys(variableGradients);
-          tidy(() => {
-            const oneMinusAccBeta1 = sub(1, this.accBeta1);
-            const lr = div(-this.learningRate, this.iteration.mul(this.decay).add(1));
-            variableNames.forEach((name, i) => {
-              const value = engine["a" /* ENGINE */].registeredVariables[name];
-              const trainable = false;
-              if (this.accumulatedFirstMoment[i] == null) {
-                this.accumulatedFirstMoment[i] = {
-                  originalName: `${name}/m`,
-                  variable: Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable),
-                };
-              }
-              if (this.accumulatedWeightedInfNorm[i] == null) {
-                this.accumulatedWeightedInfNorm[i] = {
-                  originalName: `${name}/v`,
-                  variable: Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable),
-                };
-              }
-              const gradient = Array.isArray(variableGradients)
-                ? variableGradients[i].tensor
-                : variableGradients[name];
-              if (gradient == null) {
-                return;
-              }
-              const firstMoment = this.accumulatedFirstMoment[i].variable;
-              const weightedInfNorm = this.accumulatedWeightedInfNorm[i].variable;
-              const newFirstMoment = firstMoment.mul(this.beta1).add(gradient.mul(1 - this.beta1));
-              const ut0 = weightedInfNorm.mul(this.beta2);
-              const ut1 = gradient.abs();
-              const newWeightedInfNorm = ut0.maximum(ut1);
-              firstMoment.assign(newFirstMoment);
-              weightedInfNorm.assign(newWeightedInfNorm);
-              const newValue = lr
-                .div(oneMinusAccBeta1)
-                .mul(newFirstMoment.div(newWeightedInfNorm.add(this.epsilon)))
-                .add(value);
-              value.assign(newValue);
-            });
-            this.iteration.assign(this.iteration.add(1));
-            this.accBeta1.assign(this.accBeta1.mul(this.beta1));
-          });
-          this.incrementIterations();
-        }
-        dispose() {
-          this.accBeta1.dispose();
-          this.iteration.dispose();
-          if (this.accumulatedFirstMoment != null) {
-            dispose(this.accumulatedFirstMoment.map((v) => v.variable));
-          }
-          if (this.accumulatedWeightedInfNorm != null) {
-            dispose(this.accumulatedWeightedInfNorm.map((v) => v.variable));
-          }
-        }
-        async getWeights() {
-          throw new Error("getWeights() is not implemented for Adamax yet.");
-        }
-        async setWeights(weightValues) {
-          throw new Error("setWeights() is not implemented for Adamax yet.");
-        }
-        getConfig() {
-          return {
-            learningRate: this.learningRate,
-            beta1: this.beta1,
-            beta2: this.beta2,
-            epsilon: this.epsilon,
-            decay: this.decay,
-          };
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(
-            config["learningRate"],
-            config["beta1"],
-            config["beta2"],
-            config["epsilon"],
-            config["decay"]
-          );
-        }
-      }
-      /** @nocollapse */
-      adamax_optimizer_AdamaxOptimizer.className = "Adamax"; // Note: Name matters for Python compatbility.
-      registerClass(adamax_optimizer_AdamaxOptimizer);
-      //# sourceMappingURL=adamax_optimizer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/sgd_optimizer.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /** @doclink Optimizer */
-      class sgd_optimizer_SGDOptimizer extends optimizer_Optimizer {
-        constructor(learningRate) {
-          super();
-          this.learningRate = learningRate;
-          this.setLearningRate(learningRate);
-        }
-        applyGradients(variableGradients) {
-          const varNames = Array.isArray(variableGradients)
-            ? variableGradients.map((v) => v.name)
-            : Object.keys(variableGradients);
-          varNames.forEach((name, i) => {
-            const gradient = Array.isArray(variableGradients)
-              ? variableGradients[i].tensor
-              : variableGradients[name];
-            if (gradient == null) {
-              return;
-            }
-            const value = engine["a" /* ENGINE */].registeredVariables[name];
-            tidy(() => {
-              const newValue = this.c.mul(gradient).add(value);
-              value.assign(newValue);
-            });
-          });
-          this.incrementIterations();
-        }
-        /**
-         * Sets the learning rate of the optimizer.
-         */
-        setLearningRate(learningRate) {
-          this.learningRate = learningRate;
-          if (this.c != null) {
-            this.c.dispose();
-          }
-          this.c = keep(Object(tensor_ops["e" /* scalar */])(-learningRate));
-        }
-        dispose() {
-          this.c.dispose();
-        }
-        async getWeights() {
-          return [await this.saveIterations()];
-        }
-        async setWeights(weightValues) {
-          weightValues = await this.extractIterations(weightValues);
-          if (weightValues.length !== 0) {
-            throw new Error("SGD optimizer does not have settable weights.");
-          }
-        }
-        getConfig() {
-          return { learningRate: this.learningRate };
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(config["learningRate"]);
-        }
-      }
-      /** @nocollapse */
-      sgd_optimizer_SGDOptimizer.className = "SGD"; // Note: Name matters for Python compatibility.
-      registerClass(sgd_optimizer_SGDOptimizer);
-      //# sourceMappingURL=sgd_optimizer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/momentum_optimizer.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /** @doclink Optimizer */
-      class momentum_optimizer_MomentumOptimizer extends sgd_optimizer_SGDOptimizer {
-        constructor(learningRate, momentum, useNesterov = false) {
-          super(learningRate);
-          this.learningRate = learningRate;
-          this.momentum = momentum;
-          this.useNesterov = useNesterov;
-          this.accumulations = [];
-          this.m = Object(tensor_ops["e" /* scalar */])(this.momentum);
-        }
-        applyGradients(variableGradients) {
-          const variableNames = Array.isArray(variableGradients)
-            ? variableGradients.map((item) => item.name)
-            : Object.keys(variableGradients);
-          variableNames.forEach((name, i) => {
-            const value = engine["a" /* ENGINE */].registeredVariables[name];
-            if (this.accumulations[i] == null) {
-              const trainable = false;
-              this.accumulations[i] = {
-                originalName: `${name}/momentum`,
-                variable: tidy(() =>
-                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
-                ),
-              };
-            }
-            const accumulation = this.accumulations[i].variable;
-            const gradient = Array.isArray(variableGradients)
-              ? variableGradients[i].tensor
-              : variableGradients[name];
-            if (gradient == null) {
-              return;
-            }
-            tidy(() => {
-              let newValue;
-              const newAccumulation = this.m.mul(accumulation).add(gradient);
-              if (this.useNesterov) {
-                newValue = this.c.mul(gradient.add(newAccumulation.mul(this.m))).add(value);
-              } else {
-                newValue = this.c.mul(newAccumulation).add(value);
-              }
-              accumulation.assign(newAccumulation);
-              value.assign(newValue);
-            });
-          });
-          this.incrementIterations();
-        }
-        dispose() {
-          this.m.dispose();
-          if (this.accumulations != null) {
-            dispose(this.accumulations.map((v) => v.variable));
-          }
-        }
-        /**
-         * Sets the momentum of the optimizer.
-         *
-         * @param momentum
-         */
-        setMomentum(momentum) {
-          this.momentum = momentum;
-        }
-        async getWeights() {
-          // Order matters for Python compatibility.
-          return [await this.saveIterations()].concat(
-            this.accumulations.map((v) => ({ name: v.originalName, tensor: v.variable }))
-          );
-        }
-        async setWeights(weightValues) {
-          weightValues = await this.extractIterations(weightValues);
-          const trainable = false;
-          this.accumulations = weightValues.map((v) => ({
-            originalName: v.name,
-            variable: v.tensor.variable(trainable),
-          }));
-        }
-        getConfig() {
-          return {
-            learningRate: this.learningRate,
-            momentum: this.momentum,
-            useNesterov: this.useNesterov,
-          };
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(config["learningRate"], config["momentum"], config["useNesterov"]);
-        }
-      }
-      /** @nocollapse */
-      momentum_optimizer_MomentumOptimizer.className = "Momentum"; // Name matters for Python compatibility.
-      registerClass(momentum_optimizer_MomentumOptimizer);
-      //# sourceMappingURL=momentum_optimizer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/rmsprop_optimizer.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /** @doclink Optimizer */
-      class rmsprop_optimizer_RMSPropOptimizer extends optimizer_Optimizer {
-        constructor(learningRate, decay = 0.9, momentum = 0.0, epsilon = null, centered = false) {
-          super();
-          this.learningRate = learningRate;
-          this.decay = decay;
-          this.momentum = momentum;
-          this.epsilon = epsilon;
-          this.accumulatedMeanSquares = [];
-          this.accumulatedMoments = [];
-          this.accumulatedMeanGrads = [];
-          this.centered = centered;
-          if (epsilon == null) {
-            this.epsilon = engine["a" /* ENGINE */].backend.epsilon();
-          }
-          if (learningRate == null) {
-            throw new Error(`learningRate for RMSPropOptimizer must be defined.`);
-          }
-        }
-        applyGradients(variableGradients) {
-          const variableNames = Array.isArray(variableGradients)
-            ? variableGradients.map((item) => item.name)
-            : Object.keys(variableGradients);
-          variableNames.forEach((name, i) => {
-            const value = engine["a" /* ENGINE */].registeredVariables[name];
-            const trainable = false;
-            if (this.accumulatedMeanSquares[i] == null) {
-              this.accumulatedMeanSquares[i] = {
-                originalName: `${name}/rms`,
-                variable: tidy(() =>
-                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
-                ),
-              };
-            }
-            if (this.accumulatedMoments[i] == null) {
-              this.accumulatedMoments[i] = {
-                originalName: `${name}/momentum`,
-                variable: tidy(() =>
-                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
-                ),
-              };
-            }
-            if (this.accumulatedMeanGrads[i] == null && this.centered) {
-              this.accumulatedMeanGrads[i] = {
-                originalName: `${name}/mg`,
-                variable: tidy(() =>
-                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
-                ),
-              };
-            }
-            const gradient = Array.isArray(variableGradients)
-              ? variableGradients[i].tensor
-              : variableGradients[name];
-            if (gradient == null) {
-              return;
-            }
-            const accumulatedMeanSquare = this.accumulatedMeanSquares[i].variable;
-            const accumulatedMoments = this.accumulatedMoments[i].variable;
-            tidy(() => {
-              const newAccumulatedMeanSquare = accumulatedMeanSquare
-                .mul(this.decay)
-                .add(gradient.square().mul(1 - this.decay));
-              if (this.centered) {
-                const accumulatedMeanGrad = this.accumulatedMeanGrads[i].variable;
-                // Centered gradient
-                const newAccumulatedMeanGrad = accumulatedMeanGrad
-                  .mul(this.decay)
-                  .add(gradient.mul(1 - this.decay));
-                const newAccumulatedMoments = accumulatedMoments
-                  .mul(this.momentum)
-                  .add(
-                    gradient
-                      .mul(this.learningRate)
-                      .div(
-                        newAccumulatedMeanSquare
-                          .sub(newAccumulatedMeanGrad.square().add(this.epsilon))
-                          .sqrt()
-                      )
-                  );
-                accumulatedMeanSquare.assign(newAccumulatedMeanSquare);
-                accumulatedMeanGrad.assign(newAccumulatedMeanGrad);
-                accumulatedMoments.assign(newAccumulatedMoments);
-                const newValue = value.sub(newAccumulatedMoments);
-                value.assign(newValue);
-              } else {
-                // Plain gradient
-                const newAccumulatedMeanSquare = accumulatedMeanSquare
-                  .mul(this.decay)
-                  .add(gradient.square().mul(1 - this.decay));
-                const newAccumulatedMoments = accumulatedMoments
-                  .mul(this.momentum)
-                  .add(
-                    gradient
-                      .mul(this.learningRate)
-                      .div(newAccumulatedMeanSquare.add(this.epsilon).sqrt())
-                  );
-                accumulatedMeanSquare.assign(newAccumulatedMeanSquare);
-                accumulatedMoments.assign(newAccumulatedMoments);
-                const newValue = value.sub(newAccumulatedMoments);
-                value.assign(newValue);
-              }
-            });
-          });
-          this.incrementIterations();
-        }
-        dispose() {
-          if (this.accumulatedMeanSquares != null) {
-            dispose(this.accumulatedMeanSquares.map((v) => v.variable));
-          }
-          if (this.accumulatedMeanGrads != null && this.centered) {
-            dispose(this.accumulatedMeanGrads.map((v) => v.variable));
-          }
-          if (this.accumulatedMoments != null) {
-            dispose(this.accumulatedMoments.map((v) => v.variable));
-          }
-        }
-        async getWeights() {
-          // Order matters for Python compatibility.
-          const variables = [...this.accumulatedMeanSquares, ...this.accumulatedMoments];
-          if (this.centered) {
-            variables.push(...this.accumulatedMeanGrads);
-          }
-          return [await this.saveIterations()].concat(
-            variables.map((v) => ({ name: v.originalName, tensor: v.variable }))
-          );
-        }
-        async setWeights(weightValues) {
-          weightValues = await this.extractIterations(weightValues);
-          const variableCount = this.centered ? weightValues.length / 3 : weightValues.length / 2;
-          const trainable = false;
-          this.accumulatedMeanSquares = weightValues.slice(0, variableCount).map((v) => ({
-            originalName: v.name,
-            variable: v.tensor.variable(trainable),
-          }));
-          this.accumulatedMoments = weightValues
-            .slice(variableCount, variableCount * 2)
-            .map((v) => ({
-              originalName: v.name,
-              variable: v.tensor.variable(trainable),
-            }));
-          if (this.centered) {
-            this.accumulatedMeanGrads = weightValues
-              .slice(variableCount * 2, variableCount * 3)
-              .map((v) => ({
-                originalName: v.name,
-                variable: v.tensor.variable(trainable),
-              }));
-          }
-        }
-        getConfig() {
-          return {
-            learningRate: this.learningRate,
-            decay: this.decay,
-            momentum: this.momentum,
-            epsilon: this.epsilon,
-            centered: this.centered,
-          };
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(
-            config["learningRate"],
-            config["decay"],
-            config["momentum"],
-            config["epsilon"],
-            config["centered"]
-          );
-        }
-      }
-      /** @nocollapse */
-      rmsprop_optimizer_RMSPropOptimizer.className = "RMSProp"; // Note: Name matters for Python compatibility.
-      registerClass(rmsprop_optimizer_RMSPropOptimizer);
-      //# sourceMappingURL=rmsprop_optimizer.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/types.js
-      var dist_types = __webpack_require__(23);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/optimizer_constructors.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class optimizer_constructors_OptimizerConstructors {
-        /**
-         * Constructs a `tf.SGDOptimizer` that uses stochastic gradient descent.
-         *
-         * ```js
-         * // Fit a quadratic function by learning the coefficients a, b, c.
-         * const xs = tf.tensor1d([0, 1, 2, 3]);
-         * const ys = tf.tensor1d([1.1, 5.9, 16.8, 33.9]);
-         *
-         * const a = tf.scalar(Math.random()).variable();
-         * const b = tf.scalar(Math.random()).variable();
-         * const c = tf.scalar(Math.random()).variable();
-         *
-         * // y = a * x^2 + b * x + c.
-         * const f = x => a.mul(x.square()).add(b.mul(x)).add(c);
-         * const loss = (pred, label) => pred.sub(label).square().mean();
-         *
-         * const learningRate = 0.01;
-         * const optimizer = tf.train.sgd(learningRate);
-         *
-         * // Train the model.
-         * for (let i = 0; i < 10; i++) {
-         *   optimizer.minimize(() => loss(f(xs), ys));
-         * }
-         *
-         * // Make predictions.
-         * console.log(
-         *     `a: ${a.dataSync()}, b: ${b.dataSync()}, c: ${c.dataSync()}`);
-         * const preds = f(xs).dataSync();
-         * preds.forEach((pred, i) => {
-         *   console.log(`x: ${i}, pred: ${pred}`);
-         * });
-         * ```
-         *
-         * @param learningRate The learning rate to use for the SGD algorithm.
-         */
-        /**
-         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
-         */
-        static sgd(learningRate) {
-          return new sgd_optimizer_SGDOptimizer(learningRate);
-        }
-        /**
-         * Constructs a `tf.MomentumOptimizer` that uses momentum gradient
-         * descent.
-         *
-         * See
-         * [http://proceedings.mlr.press/v28/sutskever13.pdf](
-         * http://proceedings.mlr.press/v28/sutskever13.pdf)
-         *
-         * @param learningRate The learning rate to use for the Momentum gradient
-         * descent algorithm.
-         * @param momentum The momentum to use for the momentum gradient descent
-         * algorithm.
-         */
-        /**
-         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
-         */
-        static momentum(learningRate, momentum, useNesterov = false) {
-          return new momentum_optimizer_MomentumOptimizer(learningRate, momentum, useNesterov);
-        }
-        /**
-         * Constructs a `tf.RMSPropOptimizer` that uses RMSProp gradient
-         * descent. This implementation uses plain momentum and is not centered
-         * version of RMSProp.
-         *
-         * See
-         * [http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf](
-         * http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf)
-         *
-         * @param learningRate The learning rate to use for the RMSProp gradient
-         * descent algorithm.
-         * @param decay The discounting factor for the history/coming gradient.
-         * @param momentum The momentum to use for the RMSProp gradient descent
-         * algorithm.
-         * @param epsilon Small value to avoid zero denominator.
-         * @param centered If true, gradients are normalized by the estimated
-         * variance of the gradient.
-         */
-        /**
-         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
-         */
-        static rmsprop(
-          learningRate,
-          decay = 0.9,
-          momentum = 0.0,
-          epsilon = null,
-          centered = false
-        ) {
-          return new rmsprop_optimizer_RMSPropOptimizer(
-            learningRate,
-            decay,
-            momentum,
-            epsilon,
-            centered
-          );
-        }
-        /**
-         * Constructs a `tf.AdamOptimizer` that uses the Adam algorithm.
-         * See [https://arxiv.org/abs/1412.6980](https://arxiv.org/abs/1412.6980)
-         *
-         * @param learningRate The learning rate to use for the Adam gradient
-         * descent algorithm.
-         * @param beta1 The exponential decay rate for the 1st moment estimates.
-         * @param beta2 The exponential decay rate for the 2nd moment estimates.
-         * @param epsilon A small constant for numerical stability.
-         */
-        /**
-         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
-         */
-        static adam(learningRate = 0.001, beta1 = 0.9, beta2 = 0.999, epsilon = null) {
-          return new adam_optimizer_AdamOptimizer(learningRate, beta1, beta2, epsilon);
-        }
-        /**
-         * Constructs a `tf.AdadeltaOptimizer` that uses the Adadelta algorithm.
-         * See [https://arxiv.org/abs/1212.5701](https://arxiv.org/abs/1212.5701)
-         *
-         * @param learningRate The learning rate to use for the Adadelta gradient
-         * descent algorithm.
-         * @param rho The learning rate decay over each update.
-         * @param epsilon A constant epsilon used to better condition the grad
-         * update.
-         */
-        /**
-         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
-         */
-        static adadelta(learningRate = 0.001, rho = 0.95, epsilon = null) {
-          return new adadelta_optimizer_AdadeltaOptimizer(learningRate, rho, epsilon);
-        }
-        /**
-         * Constructs a `tf.AdamaxOptimizer` that uses the Adamax algorithm.
-         * See [https://arxiv.org/abs/1412.6980](https://arxiv.org/abs/1412.6980)
-         *
-         * @param learningRate The learning rate to use for the Adamax gradient
-         * descent algorithm.
-         * @param beta1 The exponential decay rate for the 1st moment estimates.
-         * @param beta2 The exponential decay rate for the 2nd moment estimates.
-         * @param epsilon A small constant for numerical stability.
-         * @param decay The learning rate decay over each update.
-         */
-        /**
-         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
-         */
-        static adamax(
-          learningRate = 0.002,
-          beta1 = 0.9,
-          beta2 = 0.999,
-          epsilon = null,
-          decay = 0.0
-        ) {
-          return new adamax_optimizer_AdamaxOptimizer(learningRate, beta1, beta2, epsilon, decay);
-        }
-        /**
-         * Constructs a `tf.AdagradOptimizer` that uses the Adagrad algorithm.
-         * See
-         * [http://www.jmlr.org/papers/volume12/duchi11a/duchi11a.pdf](
-         * http://www.jmlr.org/papers/volume12/duchi11a/duchi11a.pdf)
-         * or
-         * [http://ruder.io/optimizing-gradient-descent/index.html#adagrad](
-         * http://ruder.io/optimizing-gradient-descent/index.html#adagrad)
-         *
-         * @param learningRate The learning rate to use for the Adagrad gradient
-         * descent algorithm.
-         * @param initialAccumulatorValue Starting value for the accumulators, must be
-         * positive.
-         */
-        /**
-         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
-         */
-        static adagrad(learningRate, initialAccumulatorValue = 0.1) {
-          return new adagrad_optimizer_AdagradOptimizer(learningRate, initialAccumulatorValue);
-        }
-      }
-      //# sourceMappingURL=optimizer_constructors.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/train.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // So typings can propagate.
-
-      // tslint:disable-next-line:no-unused-expression
-      [
-        momentum_optimizer_MomentumOptimizer,
-        sgd_optimizer_SGDOptimizer,
-        adadelta_optimizer_AdadeltaOptimizer,
-        adagrad_optimizer_AdagradOptimizer,
-        rmsprop_optimizer_RMSPropOptimizer,
-        adamax_optimizer_AdamaxOptimizer,
-        adam_optimizer_AdamOptimizer,
-      ];
-      const train = {
-        sgd: optimizer_constructors_OptimizerConstructors.sgd,
-        momentum: optimizer_constructors_OptimizerConstructors.momentum,
-        adadelta: optimizer_constructors_OptimizerConstructors.adadelta,
-        adagrad: optimizer_constructors_OptimizerConstructors.adagrad,
-        rmsprop: optimizer_constructors_OptimizerConstructors.rmsprop,
-        adamax: optimizer_constructors_OptimizerConstructors.adamax,
-        adam: optimizer_constructors_OptimizerConstructors.adam,
-      };
-      //# sourceMappingURL=train.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/browser_util.js
-      var browser_util = __webpack_require__(40);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/array_ops_util.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Gets the new shape of the input Tensor after it's been reshaped
-       * to:
-       * [blockShape[0], ..., blockShape[M-1], batch / prod(blockShape),
-       * inputShape[1], ..., inputShape[N-1]]
-       *
-       * See step 1: https://www.tensorflow.org/api_docs/python/tf/batch_to_space_nd
-       */
-      function getReshaped(inputShape, blockShape, prod, batchToSpace = true) {
-        let reshaped = [];
-        if (batchToSpace) {
-          reshaped = reshaped.concat(blockShape.slice(0));
-          reshaped.push(inputShape[0] / prod);
-          reshaped = reshaped.concat(inputShape.slice(1));
-        } else {
-          reshaped = reshaped.concat(inputShape[0]);
-          const spatialLength = blockShape.length;
-          for (let i = 0; i < spatialLength; ++i) {
-            reshaped = reshaped.concat([inputShape[i + 1] / blockShape[i], blockShape[i]]);
-          }
-          reshaped = reshaped.concat(inputShape.slice(spatialLength + 1));
-        }
-        return reshaped;
-      }
-      /**
-       * Gets the permutation that will transpose the dimensions of the
-       * reshaped tensor to shape:
-       *
-       * [batch / prod(block_shape),inputShape[1], blockShape[0], ...,
-       * inputShape[M], blockShape[M-1],inputShape[M+1], ..., inputShape[N-1]]
-       *
-       * see step 2: https://www.tensorflow.org/api_docs/python/tf/batch_to_space_nd
-       */
-      function getPermuted(reshapedRank, blockShapeRank, batchToSpace = true) {
-        const permuted = [];
-        if (batchToSpace) {
-          permuted.push(blockShapeRank);
-          for (let i = blockShapeRank + 1; i < reshapedRank; ++i) {
-            if (i <= 2 * blockShapeRank) {
-              permuted.push(i);
-              permuted.push(i - (blockShapeRank + 1));
-            } else {
-              permuted.push(i);
-            }
-          }
-        } else {
-          const permutedBeforeBatch = [];
-          const permutedAfterBatch = [];
-          for (let i = 1; i < reshapedRank; ++i) {
-            if (i >= blockShapeRank * 2 + 1 || i % 2 === 1) {
-              permutedAfterBatch.push(i);
-            } else {
-              permutedBeforeBatch.push(i);
-            }
-          }
-          permuted.push(...permutedBeforeBatch);
-          permuted.push(0);
-          permuted.push(...permutedAfterBatch);
-        }
-        return permuted;
-      }
-      /**
-       * Gets the shape of the reshaped and permuted input Tensor before any cropping
-       * is applied.  The new shape will be:
-       *
-       * [batch / prod(blockShape),inputShape[1] * blockShape[0], ...,
-       * inputShape[M] * blockShape[M-1],inputShape[M+1], ..., inputShape[N-1]]
-       *
-       * See step 3: https://www.tensorflow.org/api_docs/python/tf/batch_to_space_nd
-       */
-      function getReshapedPermuted(inputShape, blockShape, prod, batchToSpace = true) {
-        const reshapedPermuted = [];
-        if (batchToSpace) {
-          reshapedPermuted.push(inputShape[0] / prod);
-        } else {
-          reshapedPermuted.push(inputShape[0] * prod);
-        }
-        for (let i = 1; i < inputShape.length; ++i) {
-          if (i <= blockShape.length) {
-            if (batchToSpace) {
-              reshapedPermuted.push(blockShape[i - 1] * inputShape[i]);
-            } else {
-              reshapedPermuted.push(inputShape[i] / blockShape[i - 1]);
-            }
-          } else {
-            reshapedPermuted.push(inputShape[i]);
-          }
-        }
-        return reshapedPermuted;
-      }
-      /**
-       * Converts the crops argument into the beginning coordinates of a slice
-       * operation.
-       */
-      function getSliceBeginCoords(crops, blockShape) {
-        const sliceBeginCoords = [0];
-        for (let i = 0; i < blockShape; ++i) {
-          sliceBeginCoords.push(crops[i][0]);
-        }
-        return sliceBeginCoords;
-      }
-      /**
-       * Converts the crops argument into the size of a slice operation.  When
-       * combined with getSliceBeginCoords this function allows the reshaped and
-       * permuted Tensor to be cropped to its final output shape of:
-       *
-       * inputShape[1] * blockShape[0] - crops[0,0] - crops[0,1], ...,
-       * inputShape[M] * blockShape[M-1] -crops[M-1,0] -
-       * crops[M-1,1],inputShape[M+1], ..., inputShape[N-1]]
-       *
-       * See step 4: https://www.tensorflow.org/api_docs/python/tf/batch_to_space_nd
-       */
-      function getSliceSize(uncroppedShape, crops, blockShape) {
-        const sliceSize = uncroppedShape.slice(0, 1);
-        for (let i = 0; i < blockShape; ++i) {
-          sliceSize.push(uncroppedShape[i + 1] - crops[i][0] - crops[i][1]);
-        }
-        return sliceSize;
-      }
-      //# sourceMappingURL=array_ops_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/erf_util.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const ERF_P = 0.3275911;
-      const ERF_A1 = 0.254829592;
-      const ERF_A2 = -0.284496736;
-      const ERF_A3 = 1.421413741;
-      const ERF_A4 = -1.453152027;
-      const ERF_A5 = 1.061405429;
-      //# sourceMappingURL=erf_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/log.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function warn(...msg) {
-        if (!Object(environment["c" /* env */])().getBool("IS_TEST")) {
-          console.warn(...msg);
-        }
-      }
-      function log_log(...msg) {
-        if (!Object(environment["c" /* env */])().getBool("IS_TEST")) {
-          console.log(...msg);
-        }
-      }
-      //# sourceMappingURL=log.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/complex_util.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * Merges real and imaginary Float32Arrays into a single complex Float32Array.
-       *
-       * The memory layout is interleaved as follows:
-       * real: [r0, r1, r2]
-       * imag: [i0, i1, i2]
-       * complex: [r0, i0, r1, i1, r2, i2]
-       *
-       * This is the inverse of splitRealAndImagArrays.
-       *
-       * @param real The real values of the complex tensor values.
-       * @param imag The imag values of the complex tensor values.
-       * @returns A complex tensor as a Float32Array with merged values.
-       */
-      function mergeRealAndImagArrays(real, imag) {
-        if (real.length !== imag.length) {
-          throw new Error(
-            `Cannot merge real and imag arrays of different lengths. real:` +
-              `${real.length}, imag: ${imag.length}.`
-          );
-        }
-        const result = new Float32Array(real.length * 2);
-        for (let i = 0; i < result.length; i += 2) {
-          result[i] = real[i / 2];
-          result[i + 1] = imag[i / 2];
-        }
-        return result;
-      }
-      /**
-       * Splits a complex Float32Array into real and imag parts.
-       *
-       * The memory layout is interleaved as follows:
-       * complex: [r0, i0, r1, i1, r2, i2]
-       * real: [r0, r1, r2]
-       * imag: [i0, i1, i2]
-       *
-       * This is the inverse of mergeRealAndImagArrays.
-       *
-       * @param complex The complex tensor values.
-       * @returns An object with real and imag Float32Array components of the complex
-       *     tensor.
-       */
-      function splitRealAndImagArrays(complex) {
-        const real = new Float32Array(complex.length / 2);
-        const imag = new Float32Array(complex.length / 2);
-        for (let i = 0; i < complex.length; i += 2) {
-          real[i / 2] = complex[i];
-          imag[i / 2] = complex[i + 1];
-        }
-        return { real, imag };
-      }
-      /**
-       * Extracts even indexed complex values in the given array.
-       * @param complex The complex tensor values
-       */
-      function complexWithEvenIndex(complex) {
-        const len = Math.ceil(complex.length / 4);
-        const real = new Float32Array(len);
-        const imag = new Float32Array(len);
-        for (let i = 0; i < complex.length; i += 4) {
-          real[Math.floor(i / 4)] = complex[i];
-          imag[Math.floor(i / 4)] = complex[i + 1];
-        }
-        return { real, imag };
-      }
-      /**
-       * Extracts odd indexed comple values in the given array.
-       * @param complex The complex tensor values
-       */
-      function complexWithOddIndex(complex) {
-        const len = Math.floor(complex.length / 4);
-        const real = new Float32Array(len);
-        const imag = new Float32Array(len);
-        for (let i = 2; i < complex.length; i += 4) {
-          real[Math.floor(i / 4)] = complex[i];
-          imag[Math.floor(i / 4)] = complex[i + 1];
-        }
-        return { real, imag };
-      }
-      /**
-       * Get the map representing a complex value in the given array.
-       * @param complex The complex tensor values.
-       * @param index An index of the target complex value.
-       */
-      function getComplexWithIndex(complex, index) {
-        const real = complex[index * 2];
-        const imag = complex[index * 2 + 1];
-        return { real, imag };
-      }
-      /**
-       * Insert a given complex value into the TypedArray.
-       * @param data The array in which the complex value is inserted.
-       * @param c The complex value to be inserted.
-       * @param index An index of the target complex value.
-       */
-      function assignToTypedArray(data, real, imag, index) {
-        data[index * 2] = real;
-        data[index * 2 + 1] = imag;
-      }
-      /**
-       * Make the list of exponent terms used by FFT.
-       */
-      function exponents(n, inverse) {
-        const real = new Float32Array(n / 2);
-        const imag = new Float32Array(n / 2);
-        for (let i = 0; i < Math.ceil(n / 2); i++) {
-          const x = (inverse ? 2 : -2) * Math.PI * (i / n);
-          real[i] = Math.cos(x);
-          imag[i] = Math.sin(x);
-        }
-        return { real, imag };
-      }
-      /**
-       * Make the exponent term used by FFT.
-       */
-      function exponent(k, n, inverse) {
-        const x = (inverse ? 2 : -2) * Math.PI * (k / n);
-        const real = Math.cos(x);
-        const imag = Math.sin(x);
-        return { real, imag };
-      }
-      //# sourceMappingURL=complex_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/backend_util.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // Utilities needed by backend consumers of tf-core.
-
-      function castTensor(x, dtype, backend) {
-        if (dtype === "complex64") {
-          if (x.dtype === "complex64") {
-            return x.clone();
-          }
-          const zerosTensor = Object(tensor_ops["n" /* zeros */])(x.shape);
-          const floatX = x.toFloat();
-          const result = backend.complex(floatX, zerosTensor);
-          zerosTensor.dispose();
-          floatX.dispose();
-          return result;
-        }
-        if (!Object(util["hasEncodingLoss"])(x.dtype, dtype)) {
-          // We don't change the underlying data, since we cast to higher
-          // precision.
-          return engine["a" /* ENGINE */].makeTensorFromDataId(x.dataId, x.shape, dtype);
-        }
-        if (x.dtype === "complex64") {
-          const real = backend.real(x);
-          const result = real.cast(dtype);
-          real.dispose();
-          return result;
-        }
-        if (dtype === "int32") {
-          return backend.int(x);
-        } else if (dtype === "bool") {
-          const zero = Object(tensor_ops["e" /* scalar */])(0, x.dtype);
-          const result = backend.notEqual(x, zero);
-          zero.dispose();
-          return result;
-        } else {
-          throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`);
-        }
-      }
-      function reshapeTensor(x, shape) {
-        return engine["a" /* ENGINE */].makeTensorFromDataId(x.dataId, shape, x.dtype);
-      }
-      function linspaceImpl(start, stop, num) {
-        const step = (stop - start) / (num - 1);
-        const values = Object(util["makeZerosTypedArray"])(num, "float32");
-        values[0] = start;
-        for (let i = 1; i < values.length; i++) {
-          values[i] = values[i - 1] + step;
-        }
-        return Object(tensor_ops["g" /* tensor1d */])(values, "float32");
-      }
-      //# sourceMappingURL=backend_util.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/device_util.js
-      var device_util = __webpack_require__(36);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/split_shared.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // TODO(annxingyuan): Use this helper in WASM Split kernel once intermediate
-      // kernels have been modularized in WebGL and CPU
-      // https://github.com/tensorflow/tfjs/issues/2822.
-      /** Shared implementation of the split kernel across WebGL and CPU. */
-      function split_shared_split(x, sizeSplits, axis) {
-        const begin = new Array(x.rank).fill(0);
-        const size = x.shape.slice();
-        return sizeSplits.map((s) => {
-          const sliceSize = [...size];
-          sliceSize[axis] = s;
-          const slice = x.slice(begin, sliceSize);
-          begin[axis] += s;
-          return slice;
-        });
-      }
-      //# sourceMappingURL=split_shared.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/tile_impl.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * An implementation of the tile kernel shared between webgl and cpu for string
-       * tensors only.
-       */
-
-      function tile_impl_tile(xBuf, reps) {
-        const newShape = new Array(xBuf.rank);
-        for (let i = 0; i < newShape.length; i++) {
-          newShape[i] = xBuf.shape[i] * reps[i];
-        }
-        const result = array_ops_buffer(newShape, xBuf.dtype);
-        for (let i = 0; i < result.values.length; ++i) {
-          const newLoc = result.indexToLoc(i);
-          const originalLoc = new Array(xBuf.rank);
-          for (let j = 0; j < originalLoc.length; j++) {
-            originalLoc[j] = newLoc[j] % xBuf.shape[j];
-          }
-          const originalIndex = xBuf.locToIndex(originalLoc);
-          result.values[i] = xBuf.values[originalIndex];
-        }
-        return result.toTensor();
-      }
-      //# sourceMappingURL=tile_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/topk_impl.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /** An implementation of the TopK kernel shared between webgl and cpu. */
-
-      function topkImpl(x, xShape, xDtype, k, sorted) {
-        // Reshape into a 2d tensor [batch, lastDim] and compute topk along lastDim.
-        const lastDim = xShape[xShape.length - 1];
-        const [batch, size] = [x.length / lastDim, lastDim];
-        const allTopKVals = Object(util["getTypedArrayFromDType"])(xDtype, batch * k);
-        const allTopKIndices = Object(util["getTypedArrayFromDType"])("int32", batch * k);
-        for (let b = 0; b < batch; b++) {
-          const offset = b * size;
-          const vals = x.subarray(offset, offset + size);
-          const valAndInd = [];
-          for (let i = 0; i < vals.length; i++) {
-            valAndInd.push({ value: vals[i], index: i });
-          }
-          valAndInd.sort((a, b) => b.value - a.value);
-          const outOffset = b * k;
-          const topKVals = allTopKVals.subarray(outOffset, outOffset + k);
-          const topKIndices = allTopKIndices.subarray(outOffset, outOffset + k);
-          for (let i = 0; i < k; i++) {
-            topKVals[i] = valAndInd[i].value;
-            topKIndices[i] = valAndInd[i].index;
-          }
-        }
-        // Reshape back to the original input shape, except that the last
-        // dimension is k.
-        const outputShape = xShape.slice();
-        outputShape[outputShape.length - 1] = k;
-        return [
-          Object(tensor_ops["f" /* tensor */])(allTopKVals, outputShape, xDtype),
-          Object(tensor_ops["f" /* tensor */])(allTopKIndices, outputShape, "int32"),
-        ];
-      }
-      //# sourceMappingURL=topk_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/kernel_impls.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      //# sourceMappingURL=kernel_impls.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/backend.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const EPSILON_FLOAT32 = 1e-7;
-      const EPSILON_FLOAT16 = 1e-4;
-      /** Convenient class for storing tensor-related data. */
-      class DataStorage {
-        constructor(backend, dataMover) {
-          this.backend = backend;
-          this.dataMover = dataMover;
-          this.data = new WeakMap();
-          this.dataIdsCount = 0;
-        }
-        get(dataId) {
-          if (!this.data.has(dataId)) {
-            this.dataMover.moveData(this.backend, dataId);
-          }
-          return this.data.get(dataId);
-        }
-        set(dataId, value) {
-          this.dataIdsCount++;
-          this.data.set(dataId, value);
-        }
-        has(dataId) {
-          return this.data.has(dataId);
-        }
-        delete(dataId) {
-          this.dataIdsCount--;
-          return this.data.delete(dataId);
-        }
-        numDataIds() {
-          return this.dataIdsCount;
-        }
-      }
-      /**
-       * The interface that defines the kernels that should be implemented when
-       * adding a new backend. New backends don't need to implement every one of the
-       * methods, this can be done gradually (throw an error for unimplemented
-       * methods).
-       */
-      class KernelBackend {
-        time(f) {
-          return notYetImplemented("time");
-        }
-        read(dataId) {
-          return notYetImplemented("read");
-        }
-        readSync(dataId) {
-          return notYetImplemented("readSync");
-        }
-        numDataIds() {
-          return notYetImplemented("numDataIds");
-        }
-        disposeData(dataId) {
-          return notYetImplemented("disposeData");
-        }
-        write(values, shape, dtype) {
-          return notYetImplemented("write");
-        }
-        move(dataId, values, shape, dtype) {
-          return notYetImplemented("move");
-        }
-        memory() {
-          return notYetImplemented("memory");
-        }
-        /** Returns the highest precision for floats in bits (e.g. 16 or 32) */
-        floatPrecision() {
-          return notYetImplemented("floatPrecision");
-        }
-        /** Returns the smallest representable number.  */
-        epsilon() {
-          return this.floatPrecision() === 32 ? EPSILON_FLOAT32 : EPSILON_FLOAT16;
-        }
-        batchMatMul(a, b, transposeA, transposeB) {
-          return notYetImplemented("batchMatMul");
-        }
-        fusedBatchMatMul({
-          a,
-          b,
-          transposeA,
-          transposeB,
-          bias,
-          activation,
-          preluActivationWeights,
-        }) {
-          return notYetImplemented("fusedBatchMatMul");
-        }
-        slice(x, begin, size) {
-          return notYetImplemented("slice");
-        }
-        stridedSlice(x, begin, end, strides) {
-          return notYetImplemented("stridedSlice");
-        }
-        unstack(x, axis) {
-          return notYetImplemented("unstack");
-        }
-        reverse(a, axis) {
-          return notYetImplemented("reverse");
-        }
-        concat(tensors, axis) {
-          return notYetImplemented("concat");
-        }
-        neg(a) {
-          return notYetImplemented("neg");
-        }
-        add(a, b) {
-          return notYetImplemented("add");
-        }
-        addN(tensors) {
-          return notYetImplemented("addN");
-        }
-        subtract(a, b) {
-          return notYetImplemented("subtract");
-        }
-        multiply(a, b) {
-          return notYetImplemented("multiply");
-        }
-        realDivide(a, b) {
-          return notYetImplemented("realDivide");
-        }
-        floorDiv(a, b) {
-          return notYetImplemented("floorDiv");
-        }
-        sum(x, axes) {
-          return notYetImplemented("sum");
-        }
-        prod(x, axes) {
-          return notYetImplemented("prod");
-        }
-        unsortedSegmentSum(x, segmentIds, numSegments) {
-          return notYetImplemented("unsortedSegmentSum");
-        }
-        argMin(x, axis) {
-          return notYetImplemented("argMin");
-        }
-        argMax(x, axis) {
-          return notYetImplemented("argMax");
-        }
-        equal(a, b) {
-          return notYetImplemented("equal");
-        }
-        notEqual(a, b) {
-          return notYetImplemented("notEqual");
-        }
-        less(a, b) {
-          return notYetImplemented("less");
-        }
-        lessEqual(a, b) {
-          return notYetImplemented("lessEqual");
-        }
-        greater(a, b) {
-          return notYetImplemented("greater");
-        }
-        greaterEqual(a, b) {
-          return notYetImplemented("greaterEqual");
-        }
-        logicalNot(a) {
-          return notYetImplemented("logicalNot");
-        }
-        logicalAnd(a, b) {
-          return notYetImplemented("logicalAnd");
-        }
-        logicalOr(a, b) {
-          return notYetImplemented("logicalOr");
-        }
-        where(condition) {
-          return notYetImplemented("where");
-        }
-        select(condition, a, b) {
-          return notYetImplemented("select");
-        }
-        topk(x, k, sorted) {
-          return notYetImplemented("topk");
-        }
-        min(x, axes) {
-          return notYetImplemented("min");
-        }
-        minimum(a, b) {
-          return notYetImplemented("minimum");
-        }
-        mod(a, b) {
-          return notYetImplemented("mod");
-        }
-        max(x, axes) {
-          return notYetImplemented("max");
-        }
-        maximum(a, b) {
-          return notYetImplemented("maximum");
-        }
-        all(x, axes) {
-          return notYetImplemented("all");
-        }
-        any(x, axes) {
-          return notYetImplemented("any");
-        }
-        squaredDifference(a, b) {
-          return notYetImplemented("squaredDifference");
-        }
-        ceil(x) {
-          return notYetImplemented("ceil");
-        }
-        floor(x) {
-          return notYetImplemented("floor");
-        }
-        round(x) {
-          return notYetImplemented("round");
-        }
-        sign(x) {
-          return notYetImplemented("sign");
-        }
-        isNaN(x) {
-          return notYetImplemented("isNaN");
-        }
-        isInf(x) {
-          return notYetImplemented("isInf");
-        }
-        isFinite(x) {
-          return notYetImplemented("isFinite");
-        }
-        pow(a, b) {
-          return notYetImplemented("pow");
-        }
-        exp(x) {
-          return notYetImplemented("exp");
-        }
-        expm1(x) {
-          return notYetImplemented("expm1");
-        }
-        softmax(x, dim) {
-          return notYetImplemented("softmax");
-        }
-        log(x) {
-          return notYetImplemented("log");
-        }
-        log1p(x) {
-          return notYetImplemented("log1p");
-        }
-        sqrt(x) {
-          return notYetImplemented("sqrt");
-        }
-        rsqrt(x) {
-          return notYetImplemented("rsqrt");
-        }
-        square(x) {
-          return notYetImplemented("square");
-        }
-        reciprocal(x) {
-          return notYetImplemented("reciprocal");
-        }
-        relu(x) {
-          return notYetImplemented("relu");
-        }
-        relu6(x) {
-          return notYetImplemented("relu6");
-        }
-        prelu(x, a) {
-          return notYetImplemented("prelu");
-        }
-        elu(x) {
-          return notYetImplemented("elu");
-        }
-        eluDer(dy, y) {
-          return notYetImplemented("eluDer");
-        }
-        selu(x) {
-          return notYetImplemented("selu");
-        }
-        int(x) {
-          return notYetImplemented("int");
-        }
-        clip(x, min, max) {
-          return notYetImplemented("clip");
-        }
-        abs(x) {
-          return notYetImplemented("abs");
-        }
-        complexAbs(x) {
-          return notYetImplemented("complexAbs");
-        }
-        sigmoid(x) {
-          return notYetImplemented("sigmoid");
-        }
-        softplus(x) {
-          return notYetImplemented("softplus");
-        }
-        sin(x) {
-          return notYetImplemented("sin");
-        }
-        cos(x) {
-          return notYetImplemented("cos");
-        }
-        tan(x) {
-          return notYetImplemented("tan");
-        }
-        asin(x) {
-          return notYetImplemented("asin");
-        }
-        acos(x) {
-          return notYetImplemented("acos");
-        }
-        atan(x) {
-          return notYetImplemented("atan");
-        }
-        atan2(a, b) {
-          return notYetImplemented("atan2");
-        }
-        sinh(x) {
-          return notYetImplemented("sinh");
-        }
-        cosh(x) {
-          return notYetImplemented("cosh");
-        }
-        tanh(x) {
-          return notYetImplemented("tanh");
-        }
-        asinh(x) {
-          return notYetImplemented("asinh");
-        }
-        acosh(x) {
-          return notYetImplemented("acosh");
-        }
-        atanh(x) {
-          return notYetImplemented("atanh");
-        }
-        erf(x) {
-          return notYetImplemented("erf");
-        }
-        step(x, alpha) {
-          return notYetImplemented("step");
-        }
-        fusedConv2d({ input, filter, convInfo, bias, activation, preluActivationWeights }) {
-          return notYetImplemented("fusedConv2d");
-        }
-        conv2d(x, filter, convInfo) {
-          return notYetImplemented("conv2d");
-        }
-        conv2dDerInput(dy, filter, convInfo) {
-          return notYetImplemented("conv2dDerInput");
-        }
-        conv2dDerFilter(x, dY, convInfo) {
-          return notYetImplemented("conv2dDerFilter");
-        }
-        fusedDepthwiseConv2D({
-          input,
-          filter,
-          convInfo,
-          bias,
-          activation,
-          preluActivationWeights,
-        }) {
-          return notYetImplemented("fusedDepthwiseConv2D");
-        }
-        depthwiseConv2D(input, filter, convInfo) {
-          return notYetImplemented("depthwiseConv2D");
-        }
-        depthwiseConv2DDerInput(dy, filter, convInfo) {
-          return notYetImplemented("depthwiseConv2DDerInput");
-        }
-        depthwiseConv2DDerFilter(x, dY, convInfo) {
-          return notYetImplemented("depthwiseConv2DDerFilter");
-        }
-        conv3d(x, filter, convInfo) {
-          return notYetImplemented("conv3d");
-        }
-        conv3dDerInput(dy, filter, convInfo) {
-          return notYetImplemented("conv3dDerInput");
-        }
-        conv3dDerFilter(x, dY, convInfo) {
-          return notYetImplemented("conv3dDerFilter");
-        }
-        maxPool(x, convInfo) {
-          return notYetImplemented("maxPool");
-        }
-        maxPoolBackprop(dy, x, y, convInfo) {
-          return notYetImplemented("maxPoolBackprop");
-        }
-        avgPool(x, convInfo) {
-          return notYetImplemented("avgPool");
-        }
-        avgPoolBackprop(dy, x, convInfo) {
-          return notYetImplemented("avgPoolBackprop");
-        }
-        avgPool3d(x, convInfo) {
-          return notYetImplemented("avgPool3d");
-        }
-        avgPool3dBackprop(dy, x, convInfo) {
-          return notYetImplemented("avgPool3dBackprop");
-        }
-        maxPool3d(x, convInfo) {
-          return notYetImplemented("maxPool3d");
-        }
-        maxPool3dBackprop(dy, x, y, convInfo) {
-          return notYetImplemented("maxPool3dBackprop");
-        }
-        reshape(x, shape) {
-          return notYetImplemented("reshape");
-        }
-        cast(x, dtype) {
-          return notYetImplemented("cast");
-        }
-        tile(x, reps) {
-          return notYetImplemented("tile");
-        }
-        pad(x, paddings, constantValue) {
-          return notYetImplemented("pad");
-        }
-        transpose(x, perm) {
-          return notYetImplemented("transpose");
-        }
-        gather(x, indices, axis) {
-          return notYetImplemented("gather");
-        }
-        gatherND(x, indices) {
-          return notYetImplemented("gatherND");
-        }
-        scatterND(indices, updates, shape) {
-          return notYetImplemented("scatterND");
-        }
-        batchToSpaceND(x, blockShape, crops) {
-          return notYetImplemented("batchToSpaceND");
-        }
-        spaceToBatchND(x, blockShape, paddings) {
-          return notYetImplemented("spaceToBatchND");
-        }
-        resizeBilinear(x, newHeight, newWidth, alignCorners) {
-          return notYetImplemented("resizeBilinear");
-        }
-        resizeBilinearBackprop(dy, x, alignCorners) {
-          return notYetImplemented("resizeBilinearBackprop");
-        }
-        resizeNearestNeighbor(x, newHEight, newWidth, alignCorners) {
-          return notYetImplemented("resizeNearestNeighbor");
-        }
-        resizeNearestNeighborBackprop(dy, x, alignCorners) {
-          return notYetImplemented("resizeNearestNeighborBackprop");
-        }
-        batchNorm(x, mean, variance, offset, scale, varianceEpsilon) {
-          return notYetImplemented("batchNorm");
-        }
-        localResponseNormalization4D(x, radius, bias, alpha, beta) {
-          return notYetImplemented("localResponseNormalization4D");
-        }
-        LRNGrad(dy, inputImage, outputImage, radius, bias, alpha, beta) {
-          return notYetImplemented("LRNGrad");
-        }
-        multinomial(logits, normalized, numSamples, seed) {
-          return notYetImplemented("multinomial");
-        }
-        oneHot(indices, depth, onValue, offValue) {
-          return notYetImplemented("oneHot");
-        }
-        cumsum(x, axis, exclusive, reverse) {
-          return notYetImplemented("cumsum");
-        }
-        nonMaxSuppression(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold) {
-          return notYetImplemented("nonMaxSuppression");
-        }
-        fft(x) {
-          return notYetImplemented("fft");
-        }
-        ifft(x) {
-          return notYetImplemented("ifft");
-        }
-        complex(real, imag) {
-          return notYetImplemented("complex");
-        }
-        real(input) {
-          return notYetImplemented("real");
-        }
-        imag(input) {
-          return notYetImplemented("imag");
-        }
-        cropAndResize(image, boxes, boxIndex, cropSize, method, extrapolationValue) {
-          return notYetImplemented("cropAndResize");
-        }
-        depthToSpace(x, blockSize, dataFormat) {
-          return notYetImplemented("depthToSpace");
-        }
-        // Aligns with the "SplitV" kernel in TensorFlow.
-        split(value, sizeSplits, axis) {
-          return notYetImplemented("split");
-        }
-        sparseToDense(sparseIndices, sparseValues, outputShape, defaultValue) {
-          return notYetImplemented("sparseToDense");
-        }
-        diag(x) {
-          return notYetImplemented("diag");
-        }
-        fill(shape, value, dtype) {
-          return notYetImplemented("fill");
-        }
-        onesLike(x) {
-          return notYetImplemented("onesLike");
-        }
-        zerosLike(x) {
-          return notYetImplemented("zerosLike");
-        }
-        linspace(start, stop, num) {
-          return notYetImplemented("linspace");
-        }
-        dispose() {
-          return notYetImplemented("dispose");
-        }
-      }
-      function notYetImplemented(kernelName) {
-        throw new Error(
-          `'${kernelName}' not yet implemented or not found in the registry. ` +
-            `Did you forget to import the kernel?`
-        );
-      }
-      //# sourceMappingURL=backend.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/add.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.add = function (b) {
-        this.throwIfDisposed();
-        return add(this, b);
-      };
-      //# sourceMappingURL=add.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/atan2.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.atan2 = function (b) {
-        this.throwIfDisposed();
-        return atan2(this, b);
-      };
-      //# sourceMappingURL=atan2.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/avg_pool.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.avgPool = function (
-        filterSize,
-        strides,
-        pad,
-        dimRoundingMode
-      ) {
-        this.throwIfDisposed();
-        return avgPool(this, filterSize, strides, pad, dimRoundingMode);
-      };
-      //# sourceMappingURL=avg_pool.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/batchnorm.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.batchNorm = function (
-        mean,
-        variance,
-        offset,
-        scale,
-        varianceEpsilon
-      ) {
-        this.throwIfDisposed();
-        return batchNorm(this, mean, variance, offset, scale, varianceEpsilon);
-      };
-      //# sourceMappingURL=batchnorm.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/broadcast_to.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.broadcastTo = function (shape) {
-        this.throwIfDisposed();
-        return broadcastTo(this, shape);
-      };
-      //# sourceMappingURL=broadcast_to.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/batch_to_space_nd.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.batchToSpaceND = function (blockShape, crops) {
-        this.throwIfDisposed();
-        return batchToSpaceND(this, blockShape, crops);
-      };
-      //# sourceMappingURL=batch_to_space_nd.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/concat.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.concat = function (x, axis) {
-        this.throwIfDisposed();
-        if (x instanceof dist_tensor["a" /* Tensor */]) {
-          x = [x];
-        }
-        return concat([this, ...x], axis);
-      };
-      //# sourceMappingURL=concat.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv1d.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.conv1d = function (
-        filter,
-        stride,
-        pad,
-        dataFormat,
-        dilation,
-        dimRoundingMode
-      ) {
-        this.throwIfDisposed();
-        return conv1d(this, filter, stride, pad, dataFormat, dilation, dimRoundingMode);
-      };
-      //# sourceMappingURL=conv1d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv2d.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.conv2d = function (
-        filter,
-        strides,
-        pad,
-        dataFormat,
-        dilations,
-        dimRoundingMode
-      ) {
-        this.throwIfDisposed();
-        return conv2d(this, filter, strides, pad, dataFormat, dilations, dimRoundingMode);
-      };
-      //# sourceMappingURL=conv2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv2d_transpose.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.conv2dTranspose = function (
-        filter,
-        outputShape,
-        strides,
-        pad,
-        dimRoundingMode
-      ) {
-        this.throwIfDisposed();
-        return conv2dTranspose(this, filter, outputShape, strides, pad, dimRoundingMode);
-      };
-      //# sourceMappingURL=conv2d_transpose.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cumsum.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.cumsum = function (axis, exclusive, reverse) {
-        this.throwIfDisposed();
-        return cumsum(this, axis, exclusive, reverse);
-      };
-      //# sourceMappingURL=cumsum.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depth_to_space.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.depthToSpace = function (blockSize, dataFormat) {
-        this.throwIfDisposed();
-        return depthToSpace(this, blockSize, dataFormat);
-      };
-      //# sourceMappingURL=depth_to_space.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depthwise_conv2d.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.depthwiseConv2d = function (
-        filter,
-        strides,
-        pad,
-        dataFormat,
-        dilations,
-        dimRoundingMode
-      ) {
-        this.throwIfDisposed();
-        return depthwiseConv2d(this, filter, strides, pad, dataFormat, dilations, dimRoundingMode);
-      };
-      //# sourceMappingURL=depthwise_conv2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depthwise_conv2D_deprecated.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * @deprecated Use `depthwiseConv2d` instead.
-       */
-      dist_tensor["a" /* Tensor */].prototype.depthwiseConv2D = function (
-        filter,
-        strides,
-        pad,
-        dataFormat,
-        dilations,
-        dimRoundingMode
-      ) {
-        deprecationWarn("depthwiseConv2D is deprecated, use depthwiseConv2d instead");
-        this.throwIfDisposed();
-        return depthwiseConv2d(this, filter, strides, pad, dataFormat, dilations, dimRoundingMode);
-      };
-      //# sourceMappingURL=depthwise_conv2D_deprecated.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/div.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.div = function (b) {
-        this.throwIfDisposed();
-        return div(this, b);
-      };
-      //# sourceMappingURL=div.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/div_no_nan.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.divNoNan = function (b) {
-        this.throwIfDisposed();
-        return divNoNan(this, b);
-      };
-      //# sourceMappingURL=div_no_nan.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/dot.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.dot = function (b) {
-        this.throwIfDisposed();
-        return dot(this, b);
-      };
-      //# sourceMappingURL=dot.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/elu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.elu = function () {
-        this.throwIfDisposed();
-        return elu(this);
-      };
-      //# sourceMappingURL=elu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/equal.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.equal = function (b) {
-        this.throwIfDisposed();
-        return equal(this, b);
-      };
-      //# sourceMappingURL=equal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/floorDiv.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.floorDiv = function (b) {
-        this.throwIfDisposed();
-        return floorDiv(this, b);
-      };
-      //# sourceMappingURL=floorDiv.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/greater.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.greater = function (b) {
-        this.throwIfDisposed();
-        return greater(this, b);
-      };
-      //# sourceMappingURL=greater.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/greater_equal.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.greaterEqual = function (b) {
-        this.throwIfDisposed();
-        return greaterEqual(this, b);
-      };
-      //# sourceMappingURL=greater_equal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/leaky_relu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.leakyRelu = function (alpha) {
-        this.throwIfDisposed();
-        return leakyRelu(this, alpha);
-      };
-      //# sourceMappingURL=leaky_relu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/less.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.less = function (b) {
-        this.throwIfDisposed();
-        return less(this, b);
-      };
-      //# sourceMappingURL=less.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/less_equal.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.lessEqual = function (b) {
-        this.throwIfDisposed();
-        return lessEqual(this, b);
-      };
-      //# sourceMappingURL=less_equal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/local_response_normalization.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.localResponseNormalization = function (
-        depthRadius,
-        bias,
-        alpha,
-        beta
-      ) {
-        this.throwIfDisposed();
-        return localResponseNormalization(this, depthRadius, bias, alpha, beta);
-      };
-      //# sourceMappingURL=local_response_normalization.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mat_mul.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.matMul = function (b, transposeA, transposeB) {
-        this.throwIfDisposed();
-        return matMul(this, b, transposeA, transposeB);
-      };
-      //# sourceMappingURL=mat_mul.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/max.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.max = function (axis, keepDims) {
-        this.throwIfDisposed();
-        return max_max(this, axis, keepDims);
-      };
-      //# sourceMappingURL=max.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/max_pool.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.maxPool = function (
-        filterSize,
-        strides,
-        pad,
-        dimRoundingMode
-      ) {
-        this.throwIfDisposed();
-        return maxPool(this, filterSize, strides, pad, dimRoundingMode);
-      };
-      //# sourceMappingURL=max_pool.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/maximum.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.maximum = function (b) {
-        this.throwIfDisposed();
-        return maximum(this, b);
-      };
-      //# sourceMappingURL=maximum.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/minimum.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.minimum = function (b) {
-        this.throwIfDisposed();
-        return minimum(this, b);
-      };
-      //# sourceMappingURL=minimum.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mod.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.mod = function (b) {
-        this.throwIfDisposed();
-        return mod(this, b);
-      };
-      //# sourceMappingURL=mod.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mul.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.mul = function (b) {
-        this.throwIfDisposed();
-        return mul(this, b);
-      };
-      //# sourceMappingURL=mul.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/not_equal.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.notEqual = function (b) {
-        this.throwIfDisposed();
-        return notEqual(this, b);
-      };
-      //# sourceMappingURL=not_equal.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/one_hot.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.oneHot = function (depth, onValue = 1, offValue = 0) {
-        this.throwIfDisposed();
-        return oneHot(this, depth, onValue, offValue);
-      };
-      //# sourceMappingURL=one_hot.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pad.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.pad = function (paddings, constantValue) {
-        this.throwIfDisposed();
-        return pad_pad(this, paddings, constantValue);
-      };
-      //# sourceMappingURL=pad.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pool.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.pool = function (
-        windowShape,
-        poolingType,
-        padding,
-        dilationRate,
-        strides
-      ) {
-        this.throwIfDisposed();
-        return pool(this, windowShape, poolingType, padding, dilationRate, strides);
-      };
-      //# sourceMappingURL=pool.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pow.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.pow = function (exp) {
-        this.throwIfDisposed();
-        return pow(this, exp);
-      };
-      //# sourceMappingURL=pow.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/prelu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.prelu = function (alpha) {
-        this.throwIfDisposed();
-        return prelu(this, alpha);
-      };
-      //# sourceMappingURL=prelu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/relu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.relu = function () {
-        this.throwIfDisposed();
-        return relu(this);
-      };
-      //# sourceMappingURL=relu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/relu6.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.relu6 = function () {
-        this.throwIfDisposed();
-        return relu6(this);
-      };
-      //# sourceMappingURL=relu6.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/selu.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.selu = function () {
-        this.throwIfDisposed();
-        return selu(this);
-      };
-      //# sourceMappingURL=selu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/separable_conv2d.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.separableConv2d = function (
-        depthwiseFilter,
-        pointwiseFilter,
-        strides,
-        pad,
-        dilation,
-        dataFormat
-      ) {
-        this.throwIfDisposed();
-        return separableConv2d(
-          this,
-          depthwiseFilter,
-          pointwiseFilter,
-          strides,
-          pad,
-          dilation,
-          dataFormat
-        );
-      };
-      //# sourceMappingURL=separable_conv2d.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/split.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.split = function (numOrSizeSplits, axis) {
-        this.throwIfDisposed();
-        return split(this, numOrSizeSplits, axis);
-      };
-      //# sourceMappingURL=split.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/squared_difference.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.squaredDifference = function (b) {
-        this.throwIfDisposed();
-        return squaredDifference(this, b);
-      };
-      //# sourceMappingURL=squared_difference.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/space_to_batch_nd.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.spaceToBatchND = function (blockShape, paddings) {
-        this.throwIfDisposed();
-        return spaceToBatchND(this, blockShape, paddings);
-      };
-      //# sourceMappingURL=space_to_batch_nd.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sub.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.sub = function (b) {
-        this.throwIfDisposed();
-        return sub(this, b);
-      };
-      //# sourceMappingURL=sub.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/tile.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.tile = function (reps) {
-        this.throwIfDisposed();
-        return tile(this, reps);
-      };
-      //# sourceMappingURL=tile.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/transpose.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      dist_tensor["a" /* Tensor */].prototype.transpose = function (perm) {
-        this.throwIfDisposed();
-        return transpose(this, perm);
-      };
-      //# sourceMappingURL=transpose.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/register_all_chained_ops.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      //# sourceMappingURL=register_all_chained_ops.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * @fileoverview
-       * @suppress {partialAlias} Optimization disabled due to passing the module
-       * object into a function below:
-       *
-       *   import * as ops from './ops/ops';
-       *   setOpHandler(ops);
-       */
-      // Engine is the global singleton that needs to be initialized before the rest
-      // of the app.
-
-      // Register backend-agnostic flags.
-
-      // Register all the gradients.
-
-      // Serialization.
-
-      // Optimizers.
-
-      // Top-level method exports.
-
-      // Second level exports.
-
-      // Backend specific.
-
-      Object(dist_tensor["e" /* setOpHandler */])(ops_namespaceObject);
-      // Export all kernel names / info.
-
-      // Import all op chainers and add type info to Tensor.
-
-      //# sourceMappingURL=index.js.map
-
-      /***/
-    },
-    /* 1 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "shuffle",
-        function () {
-          return shuffle;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "clamp",
-        function () {
-          return clamp;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "nearestLargerEven",
-        function () {
-          return nearestLargerEven;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "sum", function () {
-        return sum;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "randUniform",
-        function () {
-          return randUniform;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "distSquared",
-        function () {
-          return distSquared;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "assert",
-        function () {
-          return assert;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "assertShapesMatch",
-        function () {
-          return assertShapesMatch;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "assertNonNull",
-        function () {
-          return assertNonNull;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "flatten",
-        function () {
-          return flatten;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "sizeFromShape",
-        function () {
-          return sizeFromShape;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isScalarShape",
-        function () {
-          return isScalarShape;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "arraysEqual",
-        function () {
-          return arraysEqual;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isInt",
-        function () {
-          return isInt;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "tanh",
-        function () {
-          return tanh;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "sizeToSquarishShape",
-        function () {
-          return sizeToSquarishShape;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "createShuffledIndices",
-        function () {
-          return createShuffledIndices;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "rightPad",
-        function () {
-          return rightPad;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "repeatedTry",
-        function () {
-          return repeatedTry;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "inferFromImplicitShape",
-        function () {
-          return inferFromImplicitShape;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "parseAxisParam",
-        function () {
-          return parseAxisParam;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "squeezeShape",
-        function () {
-          return squeezeShape;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "getTypedArrayFromDType",
-        function () {
-          return getTypedArrayFromDType;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "getArrayFromDType",
-        function () {
-          return getArrayFromDType;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "checkConversionForErrors",
-        function () {
-          return checkConversionForErrors;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isValidDtype",
-        function () {
-          return isValidDtype;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "hasEncodingLoss",
-        function () {
-          return hasEncodingLoss;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isTypedArray",
-        function () {
-          return isTypedArray;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "bytesPerElement",
-        function () {
-          return bytesPerElement;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "bytesFromStringArray",
-        function () {
-          return bytesFromStringArray;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isString",
-        function () {
-          return isString;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isBoolean",
-        function () {
-          return isBoolean;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isNumber",
-        function () {
-          return isNumber;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "inferDtype",
-        function () {
-          return inferDtype;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isFunction",
-        function () {
-          return isFunction;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "nearestDivisor",
-        function () {
-          return nearestDivisor;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "computeStrides",
-        function () {
-          return computeStrides;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "toTypedArray",
-        function () {
-          return toTypedArray;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "toNestedArray",
-        function () {
-          return toNestedArray;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "makeOnesTypedArray",
-        function () {
-          return makeOnesTypedArray;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "makeZerosTypedArray",
-        function () {
-          return makeZerosTypedArray;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "now", function () {
-        return now;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "assertNonNegativeIntegerDimensions",
-        function () {
-          return assertNonNegativeIntegerDimensions;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "fetch",
-        function () {
-          return fetch;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "encodeString",
-        function () {
-          return encodeString;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "decodeString",
-        function () {
-          return decodeString;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "locToIndex",
-        function () {
-          return locToIndex;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "indexToLoc",
-        function () {
-          return indexToLoc;
-        }
-      );
-      /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(10);
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Shuffles the array in-place using Fisher-Yates algorithm.
-       *
-       * ```js
-       * const a = [1, 2, 3, 4, 5];
-       * tf.util.shuffle(a);
-       * console.log(a);
-       * ```
-       *
-       * @param array The array to shuffle in-place.
-       */
-      /** @doc {heading: 'Util', namespace: 'util'} */
-      // tslint:disable-next-line:no-any
-      function shuffle(array) {
-        let counter = array.length;
-        let temp = 0;
-        let index = 0;
-        // While there are elements in the array
-        while (counter > 0) {
-          // Pick a random index
-          index = (Math.random() * counter) | 0;
-          // Decrease counter by 1
-          counter--;
-          // And swap the last element with it
-          temp = array[counter];
-          array[counter] = array[index];
-          array[index] = temp;
-        }
-      }
-      /** Clamps a value to a specified range. */
-      function clamp(min, x, max) {
-        return Math.max(min, Math.min(x, max));
-      }
-      function nearestLargerEven(val) {
-        return val % 2 === 0 ? val : val + 1;
-      }
-      function sum(arr) {
-        let sum = 0;
-        for (let i = 0; i < arr.length; i++) {
-          sum += arr[i];
-        }
-        return sum;
-      }
-      /**
-       * Returns a sample from a uniform [a, b) distribution.
-       *
-       * @param a The minimum support (inclusive).
-       * @param b The maximum support (exclusive).
-       * @return A pseudorandom number on the half-open interval [a,b).
-       */
-      function randUniform(a, b) {
-        const r = Math.random();
-        return b * r + (1 - r) * a;
-      }
-      /** Returns the squared Euclidean distance between two vectors. */
-      function distSquared(a, b) {
-        let result = 0;
-        for (let i = 0; i < a.length; i++) {
-          const diff = Number(a[i]) - Number(b[i]);
-          result += diff * diff;
-        }
-        return result;
-      }
-      /**
-       * Asserts that the expression is true. Otherwise throws an error with the
-       * provided message.
-       *
-       * ```js
-       * const x = 2;
-       * tf.util.assert(x === 2, 'x is not 2');
-       * ```
-       *
-       * @param expr The expression to assert (as a boolean).
-       * @param msg A function that returns the message to report when throwing an
-       *     error. We use a function for performance reasons.
-       */
-      /** @doc {heading: 'Util', namespace: 'util'} */
-      function assert(expr, msg) {
-        if (!expr) {
-          throw new Error(typeof msg === "string" ? msg : msg());
-        }
-      }
-      function assertShapesMatch(shapeA, shapeB, errorMessagePrefix = "") {
-        assert(
-          arraysEqual(shapeA, shapeB),
-          () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`
-        );
-      }
-      function assertNonNull(a) {
-        assert(a != null, () => `The input to the tensor constructor must be a non-null value.`);
-      }
-      // NOTE: We explicitly type out what T extends instead of any so that
-      // util.flatten on a nested array of number doesn't try to infer T as a
-      // number[][], causing us to explicitly type util.flatten<number>().
-      /**
-       *  Flattens an arbitrarily nested array.
-       *
-       * ```js
-       * const a = [[1, 2], [3, 4], [5, [6, [7]]]];
-       * const flat = tf.util.flatten(a);
-       * console.log(flat);
-       * ```
-       *
-       *  @param arr The nested array to flatten.
-       *  @param result The destination array which holds the elements.
-       *  @param skipTypedArray If true, avoids flattening the typed arrays. Defaults
-       *      to false.
-       */
-      /** @doc {heading: 'Util', namespace: 'util'} */
-      function flatten(arr, result = [], skipTypedArray = false) {
-        if (result == null) {
-          result = [];
-        }
-        if (Array.isArray(arr) || (isTypedArray(arr) && !skipTypedArray)) {
-          for (let i = 0; i < arr.length; ++i) {
-            flatten(arr[i], result, skipTypedArray);
-          }
-        } else {
-          result.push(arr);
-        }
-        return result;
-      }
-      /**
-       * Returns the size (number of elements) of the tensor given its shape.
-       *
-       * ```js
-       * const shape = [3, 4, 2];
-       * const size = tf.util.sizeFromShape(shape);
-       * console.log(size);
-       * ```
-       */
-      /** @doc {heading: 'Util', namespace: 'util'} */
-      function sizeFromShape(shape) {
-        if (shape.length === 0) {
-          // Scalar.
-          return 1;
-        }
-        let size = shape[0];
-        for (let i = 1; i < shape.length; i++) {
-          size *= shape[i];
-        }
-        return size;
-      }
-      function isScalarShape(shape) {
-        return shape.length === 0;
-      }
-      function arraysEqual(n1, n2) {
-        if (n1 === n2) {
-          return true;
-        }
-        if (n1 == null || n2 == null) {
-          return false;
-        }
-        if (n1.length !== n2.length) {
-          return false;
-        }
-        for (let i = 0; i < n1.length; i++) {
-          if (n1[i] !== n2[i]) {
-            return false;
-          }
-        }
-        return true;
-      }
-      function isInt(a) {
-        return a % 1 === 0;
-      }
-      function tanh(x) {
-        // tslint:disable-next-line:no-any
-        if (Math.tanh != null) {
-          // tslint:disable-next-line:no-any
-          return Math.tanh(x);
-        }
-        if (x === Infinity) {
-          return 1;
-        } else if (x === -Infinity) {
-          return -1;
-        } else {
-          const e2x = Math.exp(2 * x);
-          return (e2x - 1) / (e2x + 1);
-        }
-      }
-      function sizeToSquarishShape(size) {
-        const width = Math.ceil(Math.sqrt(size));
-        return [width, Math.ceil(size / width)];
-      }
-      /**
-       * Creates a new array with randomized indicies to a given quantity.
-       *
-       * ```js
-       * const randomTen = tf.util.createShuffledIndices(10);
-       * console.log(randomTen);
-       * ```
-       *
-       * @param number Quantity of how many shuffled indicies to create.
-       */
-      /** @doc {heading: 'Util', namespace: 'util'} */
-      function createShuffledIndices(n) {
-        const shuffledIndices = new Uint32Array(n);
-        for (let i = 0; i < n; ++i) {
-          shuffledIndices[i] = i;
-        }
-        shuffle(shuffledIndices);
-        return shuffledIndices;
-      }
-      function rightPad(a, size) {
-        if (size <= a.length) {
-          return a;
-        }
-        return a + " ".repeat(size - a.length);
-      }
-      function repeatedTry(checkFn, delayFn = (counter) => 0, maxCounter) {
-        return new Promise((resolve, reject) => {
-          let tryCount = 0;
-          const tryFn = () => {
-            if (checkFn()) {
-              resolve();
-              return;
-            }
-            tryCount++;
-            const nextBackoff = delayFn(tryCount);
-            if (maxCounter != null && tryCount >= maxCounter) {
-              reject();
-              return;
-            }
-            setTimeout(tryFn, nextBackoff);
-          };
-          tryFn();
-        });
-      }
-      /**
-       * Given the full size of the array and a shape that may contain -1 as the
-       * implicit dimension, returns the inferred shape where -1 is replaced.
-       * E.g. For shape=[2, -1, 3] and size=24, it will return [2, 4, 3].
-       *
-       * @param shape The shape, which may contain -1 in some dimension.
-       * @param size The full size (number of elements) of the array.
-       * @return The inferred shape where -1 is replaced with the inferred size.
-       */
-      function inferFromImplicitShape(shape, size) {
-        let shapeProd = 1;
-        let implicitIdx = -1;
-        for (let i = 0; i < shape.length; ++i) {
-          if (shape[i] >= 0) {
-            shapeProd *= shape[i];
-          } else if (shape[i] === -1) {
-            if (implicitIdx !== -1) {
-              throw Error(
-                `Shapes can only have 1 implicit size. ` +
-                  `Found -1 at dim ${implicitIdx} and dim ${i}`
-              );
-            }
-            implicitIdx = i;
-          } else if (shape[i] < 0) {
-            throw Error(`Shapes can not be < 0. Found ${shape[i]} at dim ${i}`);
-          }
-        }
-        if (implicitIdx === -1) {
-          if (size > 0 && size !== shapeProd) {
-            throw Error(`Size(${size}) must match the product of shape ${shape}`);
-          }
-          return shape;
-        }
-        if (shapeProd === 0) {
-          throw Error(`Cannot infer the missing size in [${shape}] when ` + `there are 0 elements`);
-        }
-        if (size % shapeProd !== 0) {
-          throw Error(
-            `The implicit shape can't be a fractional number. ` + `Got ${size} / ${shapeProd}`
-          );
-        }
-        const newShape = shape.slice();
-        newShape[implicitIdx] = size / shapeProd;
-        return newShape;
-      }
-      function parseAxisParam(axis, shape) {
-        const rank = shape.length;
-        // Normalize input
-        axis = axis == null ? shape.map((s, i) => i) : [].concat(axis);
-        // Check for valid range
-        assert(
-          axis.every((ax) => ax >= -rank && ax < rank),
-          () =>
-            `All values in axis param must be in range [-${rank}, ${rank}) but ` +
-            `got axis ${axis}`
-        );
-        // Check for only integers
-        assert(
-          axis.every((ax) => isInt(ax)),
-          () => `All values in axis param must be integers but ` + `got axis ${axis}`
-        );
-        // Handle negative axis.
-        return axis.map((a) => (a < 0 ? rank + a : a));
-      }
-      /** Reduces the shape by removing all dimensions of shape 1. */
-      function squeezeShape(shape, axis) {
-        const newShape = [];
-        const keptDims = [];
-        const isEmptyArray = axis != null && Array.isArray(axis) && axis.length === 0;
-        const axes = axis == null || isEmptyArray ? null : parseAxisParam(axis, shape).sort();
-        let j = 0;
-        for (let i = 0; i < shape.length; ++i) {
-          if (axes != null) {
-            if (axes[j] === i && shape[i] !== 1) {
-              throw new Error(`Can't squeeze axis ${i} since its dim '${shape[i]}' is not 1`);
-            }
-            if ((axes[j] == null || axes[j] > i) && shape[i] === 1) {
-              newShape.push(shape[i]);
-              keptDims.push(i);
-            }
-            if (axes[j] <= i) {
-              j++;
-            }
-          }
-          if (shape[i] !== 1) {
-            newShape.push(shape[i]);
-            keptDims.push(i);
-          }
-        }
-        return { newShape, keptDims };
-      }
-      function getTypedArrayFromDType(dtype, size) {
-        let values = null;
-        if (dtype == null || dtype === "float32") {
-          values = new Float32Array(size);
-        } else if (dtype === "int32") {
-          values = new Int32Array(size);
-        } else if (dtype === "bool") {
-          values = new Uint8Array(size);
-        } else {
-          throw new Error(`Unknown data type ${dtype}`);
-        }
-        return values;
-      }
-      function getArrayFromDType(dtype, size) {
-        let values = null;
-        if (dtype == null || dtype === "float32") {
-          values = new Float32Array(size);
-        } else if (dtype === "int32") {
-          values = new Int32Array(size);
-        } else if (dtype === "bool") {
-          values = new Uint8Array(size);
-        } else if (dtype === "string") {
-          values = new Array(size);
-        } else {
-          throw new Error(`Unknown data type ${dtype}`);
-        }
-        return values;
-      }
-      function checkConversionForErrors(vals, dtype) {
-        for (let i = 0; i < vals.length; i++) {
-          const num = vals[i];
-          if (isNaN(num) || !isFinite(num)) {
-            throw Error(`A tensor of type ${dtype} being uploaded contains ${num}.`);
-          }
-        }
-      }
-      /** Returns true if the dtype is valid. */
-      function isValidDtype(dtype) {
-        return (
-          dtype === "bool" ||
-          dtype === "complex64" ||
-          dtype === "float32" ||
-          dtype === "int32" ||
-          dtype === "string"
-        );
-      }
-      /**
-       * Returns true if the new type can't encode the old type without loss of
-       * precision.
-       */
-      function hasEncodingLoss(oldType, newType) {
-        if (newType === "complex64") {
-          return false;
-        }
-        if (newType === "float32" && oldType !== "complex64") {
-          return false;
-        }
-        if (newType === "int32" && oldType !== "float32" && oldType !== "complex64") {
-          return false;
-        }
-        if (newType === "bool" && oldType === "bool") {
-          return false;
-        }
-        return true;
-      }
-      function isTypedArray(a) {
-        return a instanceof Float32Array || a instanceof Int32Array || a instanceof Uint8Array;
-      }
-      function bytesPerElement(dtype) {
-        if (dtype === "float32" || dtype === "int32") {
-          return 4;
-        } else if (dtype === "complex64") {
-          return 8;
-        } else if (dtype === "bool") {
-          return 1;
-        } else {
-          throw new Error(`Unknown dtype ${dtype}`);
-        }
-      }
-      /**
-       * Returns the approximate number of bytes allocated in the string array - 2
-       * bytes per character. Computing the exact bytes for a native string in JS is
-       * not possible since it depends on the encoding of the html page that serves
-       * the website.
-       */
-      function bytesFromStringArray(arr) {
-        if (arr == null) {
-          return 0;
-        }
-        let bytes = 0;
-        arr.forEach((x) => (bytes += x.length));
-        return bytes;
-      }
-      /** Returns true if the value is a string. */
-      function isString(value) {
-        return typeof value === "string" || value instanceof String;
-      }
-      function isBoolean(value) {
-        return typeof value === "boolean";
-      }
-      function isNumber(value) {
-        return typeof value === "number";
-      }
-      function inferDtype(values) {
-        if (Array.isArray(values)) {
-          return inferDtype(values[0]);
-        }
-        if (values instanceof Float32Array) {
-          return "float32";
-        } else if (values instanceof Int32Array || values instanceof Uint8Array) {
-          return "int32";
-        } else if (isNumber(values)) {
-          return "float32";
-        } else if (isString(values)) {
-          return "string";
-        } else if (isBoolean(values)) {
-          return "bool";
-        }
-        return "float32";
-      }
-      function isFunction(f) {
-        return !!(f && f.constructor && f.call && f.apply);
-      }
-      function nearestDivisor(size, start) {
-        for (let i = start; i < size; ++i) {
-          if (size % i === 0) {
-            return i;
-          }
-        }
-        return size;
-      }
-      function computeStrides(shape) {
-        const rank = shape.length;
-        if (rank < 2) {
-          return [];
-        }
-        // Last dimension has implicit stride of 1, thus having D-1 (instead of D)
-        // strides.
-        const strides = new Array(rank - 1);
-        strides[rank - 2] = shape[rank - 1];
-        for (let i = rank - 3; i >= 0; --i) {
-          strides[i] = strides[i + 1] * shape[i + 1];
-        }
-        return strides;
-      }
-      function toTypedArray(a, dtype, debugMode) {
-        if (dtype === "string") {
-          throw new Error("Cannot convert a string[] to a TypedArray");
-        }
-        if (Array.isArray(a)) {
-          a = flatten(a);
-        }
-        if (debugMode) {
-          checkConversionForErrors(a, dtype);
-        }
-        if (noConversionNeeded(a, dtype)) {
-          return a;
-        }
-        if (dtype == null || dtype === "float32" || dtype === "complex64") {
-          return new Float32Array(a);
-        } else if (dtype === "int32") {
-          return new Int32Array(a);
-        } else if (dtype === "bool") {
-          const bool = new Uint8Array(a.length);
-          for (let i = 0; i < bool.length; ++i) {
-            if (Math.round(a[i]) !== 0) {
-              bool[i] = 1;
-            }
-          }
-          return bool;
-        } else {
-          throw new Error(`Unknown data type ${dtype}`);
-        }
-      }
-      function createNestedArray(offset, shape, a) {
-        const ret = new Array();
-        if (shape.length === 1) {
-          const d = shape[0];
-          for (let i = 0; i < d; i++) {
-            ret[i] = a[offset + i];
-          }
-        } else {
-          const d = shape[0];
-          const rest = shape.slice(1);
-          const len = rest.reduce((acc, c) => acc * c);
-          for (let i = 0; i < d; i++) {
-            ret[i] = createNestedArray(offset + i * len, rest, a);
-          }
-        }
-        return ret;
-      }
-      // Provide a nested array of TypedArray in given shape.
-      function toNestedArray(shape, a) {
-        if (shape.length === 0) {
-          // Scalar type should return a single number.
-          return a[0];
-        }
-        const size = shape.reduce((acc, c) => acc * c);
-        if (size === 0) {
-          // A tensor with shape zero should be turned into empty list.
-          return [];
-        }
-        if (size !== a.length) {
-          throw new Error(`[${shape}] does not match the input size.`);
-        }
-        return createNestedArray(0, shape, a);
-      }
-      function noConversionNeeded(a, dtype) {
-        return (
-          (a instanceof Float32Array && dtype === "float32") ||
-          (a instanceof Int32Array && dtype === "int32") ||
-          (a instanceof Uint8Array && dtype === "bool")
-        );
-      }
-      function makeOnesTypedArray(size, dtype) {
-        const array = makeZerosTypedArray(size, dtype);
-        for (let i = 0; i < array.length; i++) {
-          array[i] = 1;
-        }
-        return array;
-      }
-      function makeZerosTypedArray(size, dtype) {
-        if (dtype == null || dtype === "float32" || dtype === "complex64") {
-          return new Float32Array(size);
-        } else if (dtype === "int32") {
-          return new Int32Array(size);
-        } else if (dtype === "bool") {
-          return new Uint8Array(size);
-        } else {
-          throw new Error(`Unknown data type ${dtype}`);
-        }
-      }
-      /**
-       * Returns the current high-resolution time in milliseconds relative to an
-       * arbitrary time in the past. It works across different platforms (node.js,
-       * browsers).
-       *
-       * ```js
-       * console.log(tf.util.now());
-       * ```
-       */
-      /** @doc {heading: 'Util', namespace: 'util'} */
-      function now() {
-        return Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().platform.now();
-      }
-      function assertNonNegativeIntegerDimensions(shape) {
-        shape.forEach((dimSize) => {
-          assert(
-            Number.isInteger(dimSize) && dimSize >= 0,
-            () =>
-              `Tensor must have a shape comprised of positive integers but got ` +
-              `shape [${shape}].`
-          );
-        });
-      }
-      /**
-       * Returns a platform-specific implementation of
-       * [`fetch`](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API).
-       *
-       * If `fetch` is defined on the global object (`window`, `process`, etc.),
-       * `tf.util.fetch` returns that function.
-       *
-       * If not, `tf.util.fetch` returns a platform-specific solution.
-       *
-       * ```js
-       * const resource = await tf.util.fetch('https://unpkg.com/@tensorflow/tfjs');
-       * // handle response
-       * ```
-       */
-      /** @doc {heading: 'Util'} */
-      function fetch(path, requestInits) {
-        return Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().platform.fetch(
-          path,
-          requestInits
-        );
-      }
-      /**
-       * Encodes the provided string into bytes using the provided encoding scheme.
-       *
-       * @param s The string to encode.
-       * @param encoding The encoding scheme. Defaults to utf-8.
-       *
-       */
-      /** @doc {heading: 'Util'} */
-      function encodeString(s, encoding = "utf-8") {
-        encoding = encoding || "utf-8";
-        return Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().platform.encode(
-          s,
-          encoding
-        );
-      }
-      /**
-       * Decodes the provided bytes into a string using the provided encoding scheme.
-       * @param bytes The bytes to decode.
-       *
-       * @param encoding The encoding scheme. Defaults to utf-8.
-       */
-      /** @doc {heading: 'Util'} */
-      function decodeString(bytes, encoding = "utf-8") {
-        encoding = encoding || "utf-8";
-        return Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().platform.decode(
-          bytes,
-          encoding
-        );
-      }
-      /**
-       * Computes flat index for a given location (multidimentionsal index) in a
-       * Tensor/multidimensional array.
-       *
-       * @param locs Location in the tensor.
-       * @param rank Rank of the tensor.
-       * @param strides Tensor strides.
-       */
-      function locToIndex(locs, rank, strides) {
-        if (rank === 0) {
-          return 0;
-        } else if (rank === 1) {
-          return locs[0];
-        }
-        let index = locs[locs.length - 1];
-        for (let i = 0; i < locs.length - 1; ++i) {
-          index += strides[i] * locs[i];
-        }
-        return index;
-      }
-      /**
-       * Computes the location (multidimensional index) in a tensor/multidimentional
-       * array for a given flat index.
-       *
-       * @param index Index in flat array.
-       * @param rank Rank of tensor.
-       * @param strides Strides of tensor.
-       */
-      function indexToLoc(index, rank, strides) {
-        if (rank === 0) {
-          return [];
-        } else if (rank === 1) {
-          return [index];
-        }
-        const locs = new Array(rank);
-        for (let i = 0; i < locs.length - 1; ++i) {
-          locs[i] = Math.floor(index / strides[i]);
-          index -= locs[i] * strides[i];
-        }
-        locs[locs.length - 1] = index;
-        return locs;
-      }
-      //# sourceMappingURL=util.js.map
-
-      /***/
-    },
-    /* 2 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return getParamValue;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return getTensor;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
-        return getTensorsForCurrentContenxt;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return getNodeNameAndIndex;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
-        return parseNodeName;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
-        return split;
-      });
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      function getParamValue(paramName, node, tensorMap, context) {
-        const inputParam = node.inputParams[paramName];
-        if (inputParam && inputParam.inputIndexStart !== undefined) {
-          const start = inputParam.inputIndexStart;
-          const end =
-            inputParam.inputIndexEnd === 0
-              ? undefined
-              : inputParam.inputIndexEnd === undefined
-              ? start + 1
-              : inputParam.inputIndexEnd;
-          if (inputParam.type === "tensor") {
-            return getTensor(node.inputNames[inputParam.inputIndexStart], tensorMap, context);
-          }
-          if (inputParam.type === "tensors") {
-            const inputs = node.inputNames.slice(start, end);
-            return inputs.map((name) => getTensor(name, tensorMap, context));
-          }
-          const data = Array.prototype.slice.call(
-            getTensor(node.inputNames.slice(start)[0], tensorMap, context).dataSync()
-          );
-          return inputParam.type === "number" ? data[0] : data;
-        }
-        const attrParam = node.attrParams[paramName];
-        return attrParam && attrParam.value;
-      }
-      /**
-       * Retrieve the tensor based on input name by extracting the node name and
-       * output index information.
-       * @param name Node input name
-       * @param tensorsMap Tensors map keyed by the node
-       */
-      function getTensor(name, tensorsMap, context) {
-        const [nodeName, index] = parseNodeName(name);
-        const contextId = context.currentContextIds.find((contextId) => {
-          return !!tensorsMap[getNodeNameWithContextId(nodeName, contextId)];
-        });
-        return contextId !== undefined
-          ? tensorsMap[getNodeNameWithContextId(nodeName, contextId)][index]
-          : undefined;
-      }
-      /**
-       * Retrieve the tensors based on input name for current context.
-       * @param name Node input name
-       * @param tensorsMap Tensors map keyed by the node
-       */
-      function getTensorsForCurrentContenxt(name, tensorsMap, context) {
-        return tensorsMap[getNodeNameWithContextId(name, context.currentContextId)];
-      }
-      /**
-       * Returns the node name and index from the Node input name.
-       * @param inputName The input name of the node, in format of
-       * node_name:output_index, i.e. MatMul:0, if the output_index is not set, it is
-       * default to 0.
-       */
-      function getNodeNameAndIndex(inputName, context) {
-        const [nodeName, index] = parseNodeName(inputName);
-        return [getNodeNameWithContextId(nodeName, context && context.currentContextId), index];
-      }
-      function getNodeNameWithContextId(name, contextId) {
-        return !!contextId ? `${name}-${contextId}` : name;
-      }
-      function parseNodeName(name) {
-        const parts = name.split(":");
-        if (parts.length === 1) {
-          return [name, 0];
-        }
-        const nodeName = parts[0];
-        return [nodeName, Number(parts[parts.length - 1])];
-      }
-      function split(arr, size) {
-        const res = [];
-        for (let i = 0; i < arr.length; i += size) {
-          res.push(arr.slice(i, i + size));
-        }
-        return res;
-      }
-      //# sourceMappingURL=utils.js.map
-
-      /***/
-    },
-    /* 3 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return inferShape;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return convertToTensor;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return convertToTensorArray;
-      });
-      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
-      /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(10);
-      /* harmony import */ var _tensor__WEBPACK_IMPORTED_MODULE_2__ = __webpack_require__(7);
-      /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(1);
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function inferShape(val, dtype) {
-        let firstElem = val;
-        if (Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(val)) {
-          return dtype === "string" ? [] : [val.length];
-        }
-        if (!Array.isArray(val)) {
-          return []; // Scalar.
-        }
-        const shape = [];
-        while (
-          Array.isArray(firstElem) ||
-          (Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(firstElem) &&
-            dtype !== "string")
-        ) {
-          shape.push(firstElem.length);
-          firstElem = firstElem[0];
-        }
-        if (
-          Array.isArray(val) &&
-          Object(_environment__WEBPACK_IMPORTED_MODULE_1__[/* env */ "c"])().getBool(
-            "TENSORLIKE_CHECK_SHAPE_CONSISTENCY"
-          )
-        ) {
-          deepAssertShapeConsistency(val, shape, []);
-        }
-        return shape;
-      }
-      function deepAssertShapeConsistency(val, shape, indices) {
-        indices = indices || [];
-        if (
-          !Array.isArray(val) &&
-          !Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(val)
-        ) {
-          Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
-            shape.length === 0,
-            () =>
-              `Element arr[${indices.join("][")}] is a primitive, ` +
-              `but should be an array/TypedArray of ${shape[0]} elements`
-          );
-          return;
-        }
-        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
-          shape.length > 0,
-          () =>
-            `Element arr[${indices.join("][")}] should be a primitive, ` +
-            `but is an array of ${val.length} elements`
-        );
-        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
-          val.length === shape[0],
-          () =>
-            `Element arr[${indices.join("][")}] should have ${shape[0]} ` +
-            `elements, but has ${val.length} elements`
-        );
-        const subShape = shape.slice(1);
-        for (let i = 0; i < val.length; ++i) {
-          deepAssertShapeConsistency(val[i], subShape, indices.concat(i));
-        }
-      }
-      function assertDtype(expectedDtype, actualDType, argName, functionName) {
-        if (expectedDtype == null) {
-          return;
-        }
-        if (
-          (expectedDtype !== "numeric" && expectedDtype !== actualDType) ||
-          (expectedDtype === "numeric" && actualDType === "string")
-        ) {
-          throw new Error(
-            `Argument '${argName}' passed to '${functionName}' must ` +
-              `be ${expectedDtype} tensor, but got ${actualDType} tensor`
-          );
-        }
-      }
-      function convertToTensor(x, argName, functionName, parseAsDtype = "numeric") {
-        if (x instanceof _tensor__WEBPACK_IMPORTED_MODULE_2__[/* Tensor */ "a"]) {
-          assertDtype(parseAsDtype, x.dtype, argName, functionName);
-          return x;
-        }
-        let inferredDtype = Object(_util__WEBPACK_IMPORTED_MODULE_3__["inferDtype"])(x);
-        // If the user expects a bool/int/float, use that info to update the
-        // inferredDtype when it is not a string.
-        if (inferredDtype !== "string" && ["bool", "int32", "float32"].indexOf(parseAsDtype) >= 0) {
-          inferredDtype = parseAsDtype;
-        }
-        assertDtype(parseAsDtype, inferredDtype, argName, functionName);
-        if (
-          x == null ||
-          (!Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(x) &&
-            !Array.isArray(x) &&
-            typeof x !== "number" &&
-            typeof x !== "boolean" &&
-            typeof x !== "string")
-        ) {
-          const type = x == null ? "null" : x.constructor.name;
-          throw new Error(
-            `Argument '${argName}' passed to '${functionName}' must be a ` +
-              `Tensor or TensorLike, but got '${type}'`
-          );
-        }
-        const inferredShape = inferShape(x, inferredDtype);
-        if (!Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(x) && !Array.isArray(x)) {
-          x = [x];
-        }
-        const skipTypedArray = true;
-        const values =
-          inferredDtype !== "string"
-            ? Object(_util__WEBPACK_IMPORTED_MODULE_3__["toTypedArray"])(
-                x,
-                inferredDtype,
-                Object(_environment__WEBPACK_IMPORTED_MODULE_1__[/* env */ "c"])().getBool("DEBUG")
-              )
-            : Object(_util__WEBPACK_IMPORTED_MODULE_3__["flatten"])(x, [], skipTypedArray);
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeTensor(
-          values,
-          inferredShape,
-          inferredDtype
-        );
-      }
-      function convertToTensorArray(arg, argName, functionName, parseAsDtype = "numeric") {
-        if (!Array.isArray(arg)) {
-          throw new Error(
-            `Argument ${argName} passed to ${functionName} must be a ` +
-              "`Tensor[]` or `TensorLike[]`"
-          );
-        }
-        const tensors = arg;
-        return tensors.map(
-          (t, i) => convertToTensor(t, `${argName}[${i}]`, functionName),
-          parseAsDtype
-        );
-      }
-      //# sourceMappingURL=tensor_util_env.js.map
-
-      /***/
-    },
-    /* 4 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return op;
-      });
-      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Used for wrapping functions that perform math operations on
-       * Tensors. The function will be wrapped in a named scope that cleans all
-       * memory usage after the function is done.
-       */
-      function op(f) {
-        const keys = Object.keys(f);
-        if (keys.length !== 1) {
-          throw new Error(
-            `Please provide an object with a single key ` +
-              `(operation name) mapping to a function. Got an object with ` +
-              `${keys.length} keys.`
-          );
-        }
-        let opName = keys[0];
-        const fn = f[opName];
-        // Strip the underscore from the end of the function name.
-        if (opName.endsWith("_")) {
-          opName = opName.substring(0, opName.length - 1);
-        }
-        // tslint:disable-next-line:no-any
-        const f2 = (...args) => {
-          _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].startScope(opName);
-          try {
-            const result = fn(...args);
-            if (result instanceof Promise) {
-              console.error("Cannot return a Promise inside of tidy.");
-            }
-            _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].endScope(result);
-            return result;
-          } catch (ex) {
-            _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].endScope(null);
-            throw ex;
-          }
-        };
-        Object.defineProperty(f2, "name", { value: opName, configurable: true });
-        // tslint:disable-next-line:no-any
-        return f2;
-      }
-      //# sourceMappingURL=operation.js.map
-
-      /***/
-    },
-    /* 5 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "a", function () {
-        return /* binding */ ENGINE;
-      });
-
-      // UNUSED EXPORTS: Engine
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/environment.js
-      var dist_environment = __webpack_require__(10);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/global_util.js
-      var global_util = __webpack_require__(33);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/kernel_registry.js
-      var kernel_registry = __webpack_require__(17);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/util.js
-      var util = __webpack_require__(1);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/profiler.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class Profiler {
-        constructor(backendTimer, logger) {
-          this.backendTimer = backendTimer;
-          this.logger = logger;
-          if (logger == null) {
-            this.logger = new profiler_Logger();
-          }
-        }
-        profileKernel(kernelName, inputs, f) {
-          let outputs;
-          const holdResultWrapperFn = () => {
-            outputs = f();
-          };
-          const timer = this.backendTimer.time(holdResultWrapperFn);
-          outputs.forEach((r) => {
-            // Dangling promise here because we don't want to propagate up
-            // asynchronicity.
-            r.data().then((vals) => {
-              checkComputationForErrors(vals, r.dtype, kernelName);
-              timer.then((timing) => {
-                let extraInfo = "";
-                if (timing.getExtraProfileInfo != null) {
-                  extraInfo = timing.getExtraProfileInfo();
-                }
-                this.logger.logKernelProfile(
-                  kernelName,
-                  r,
-                  vals,
-                  timing.kernelMs,
-                  inputs,
-                  extraInfo
-                );
-              });
-            });
-          });
-          return outputs;
-        }
-      }
-      function checkComputationForErrors(vals, dtype, kernelName) {
-        if (dtype !== "float32") {
-          // Only floating point computations will generate NaN values
-          return false;
-        }
-        for (let i = 0; i < vals.length; i++) {
-          const num = vals[i];
-          if (isNaN(num) || !isFinite(num)) {
-            // Throwing custom exception so behavior is testable.
-            console.warn(`Found ${num} in the result of '${kernelName}'`);
-            return true;
-          }
-        }
-        return false;
-      }
-      class profiler_Logger {
-        logKernelProfile(name, result, vals, timeMs, inputs, extraInfo) {
-          const time =
-            typeof timeMs === "number" ? util["rightPad"](`${timeMs}ms`, 9) : timeMs["error"];
-          const paddedName = util["rightPad"](name, 25);
-          const rank = result.rank;
-          const size = result.size;
-          const shape = util["rightPad"](result.shape.toString(), 14);
-          let inputShapesDescription = "";
-          for (const name in inputs) {
-            const input = inputs[name];
-            // The input might be a non-tensor (e.g HTMLImageElement), in which case
-            // we claim the output shape as input shape.
-            const inputShape = input.shape || result.shape;
-            const inputRank = inputShape.length;
-            inputShapesDescription += `${name}: ${inputRank}D ${inputRank > 0 ? inputShape : ""} `;
-          }
-          console.log(
-            `%c${paddedName}\t%c${time}\t%c${rank}D ${shape}\t%c${size}\t%c${inputShapesDescription}\t%c${extraInfo}`,
-            "font-weight:bold",
-            "color:red",
-            "color:blue",
-            "color: orange",
-            "color: green",
-            "color: steelblue"
-          );
-        }
-      }
-      //# sourceMappingURL=profiler.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tape.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Computes a list of TapeNodes that connect x to y, filtering everything else
-       * out and preserving the order of the original tape elements.
-       *
-       * @param tape The tape elements to filter.
-       * @param xs The input Tensors.
-       * @param y The output Tensor.
-       */
-      function getFilteredNodesXToY(tape, xs, y) {
-        // Forward pass to compute all the nodes and Tensors that are transitively a
-        // function of x.
-        const tensorsFromX = {};
-        const nodesFromX = {};
-        for (let i = 0; i < xs.length; i++) {
-          tensorsFromX[xs[i].id] = true;
-        }
-        for (let i = 0; i < tape.length; i++) {
-          const node = tape[i];
-          const nodeInputs = node.inputs;
-          for (const inputName in nodeInputs) {
-            const input = nodeInputs[inputName];
-            let anyInputFromX = false;
-            for (let j = 0; j < xs.length; j++) {
-              if (tensorsFromX[input.id]) {
-                node.outputs.forEach((output) => (tensorsFromX[output.id] = true));
-                anyInputFromX = true;
-                nodesFromX[node.id] = true;
-                break;
-              }
-            }
-            if (anyInputFromX) {
-              break;
-            }
-          }
-        }
-        // Backward pass to find all of the nodes and Tensors that lead to y.
-        const tensorsLeadToY = {};
-        tensorsLeadToY[y.id] = true;
-        const nodesToY = {};
-        for (let i = tape.length - 1; i >= 0; i--) {
-          const node = tape[i];
-          const nodeInputs = node.inputs;
-          // If any of the outputs lead to y, mark all of the inputs as leading to y.
-          for (let j = 0; j < node.outputs.length; j++) {
-            if (tensorsLeadToY[node.outputs[j].id]) {
-              for (const inputName in nodeInputs) {
-                tensorsLeadToY[nodeInputs[inputName].id] = true;
-                nodesToY[node.id] = true;
-              }
-              break;
-            }
-          }
-        }
-        // Return the paths that come from x and lead to y.
-        const filteredTape = [];
-        for (let i = 0; i < tape.length; i++) {
-          const node = tape[i];
-          if (nodesFromX[node.id] && nodesToY[node.id]) {
-            // Prune the inputs from the node that aren't a function of x.
-            const prunedInputs = {};
-            for (const inputName in node.inputs) {
-              const nodeInput = node.inputs[inputName];
-              if (tensorsFromX[nodeInput.id]) {
-                prunedInputs[inputName] = nodeInput;
-              }
-            }
-            // Copy the node and overwrite inputsAndArgs to the pruned version.
-            const prunedNode = Object.assign({}, node);
-            prunedNode.inputs = prunedInputs;
-            prunedNode.outputs = node.outputs;
-            filteredTape.push(prunedNode);
-          }
-        }
-        return filteredTape;
-      }
-      /**
-       * Backpropagate gradients through the filtered TapeNodes.
-       *
-       * @param tensorAccumulatedGradientMap A map of Tensor to its gradient. This map
-       * is mutated by this method.
-       * @param filteredTape The filtered TapeNodes to backprop through.
-       */
-      function backpropagateGradients(tensorAccumulatedGradientMap, filteredTape, tidy) {
-        // Walk the tape backward and keep a map of Tensor to its gradient.
-        for (let i = filteredTape.length - 1; i >= 0; i--) {
-          const node = filteredTape[i];
-          const dys = [];
-          node.outputs.forEach((o) => {
-            const gradTensor = tensorAccumulatedGradientMap[o.id];
-            if (gradTensor != null) {
-              dys.push(gradTensor);
-            } else {
-              // This particular output is not in the back-propagation subgraph, so it
-              // does not affect the final output, thus we put null for its dy.
-              dys.push(null);
-            }
-          });
-          if (node.gradient == null) {
-            throw new Error(
-              `Cannot compute gradient: gradient function not found ` + `for ${node.kernelName}.`
-            );
-          }
-          // Backprop dy through this node and accumulate gradients over the inputs.
-          const inputGradients = node.gradient(dys);
-          for (const inputName in node.inputs) {
-            if (!(inputName in inputGradients)) {
-              throw new Error(
-                `Cannot backprop through input ${inputName}. ` +
-                  `Available gradients found: ${Object.keys(inputGradients)}.`
-              );
-            }
-            // Call the gradient function.
-            const dx = tidy(() => inputGradients[inputName]());
-            if (dx.dtype !== "float32") {
-              throw new Error(
-                `Error in gradient for op ${node.kernelName}. The gradient of input ` +
-                  `${inputName} must have 'float32' dtype, but has '${dx.dtype}'`
-              );
-            }
-            const x = node.inputs[inputName];
-            if (!util["arraysEqual"](dx.shape, x.shape)) {
-              throw new Error(
-                `Error in gradient for op ${node.kernelName}. The gradient of input ` +
-                  `'${inputName}' has shape '${dx.shape}', which does not match ` +
-                  `the shape of the input '${x.shape}'`
-              );
-            }
-            if (tensorAccumulatedGradientMap[x.id] == null) {
-              tensorAccumulatedGradientMap[x.id] = dx;
-            } else {
-              const curGradient = tensorAccumulatedGradientMap[x.id];
-              tensorAccumulatedGradientMap[x.id] = curGradient.add(dx);
-              curGradient.dispose();
-            }
-          }
-        }
-      }
-      //# sourceMappingURL=tape.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor.js + 1 modules
-      var tensor = __webpack_require__(7);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor_util.js
-      var tensor_util = __webpack_require__(11);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/engine.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class EngineState {
-        constructor() {
-          // Public since optimizers will use it.
-          this.registeredVariables = {};
-          this.nextTapeNodeId = 0;
-          this.numBytes = 0;
-          this.numTensors = 0;
-          this.numStringTensors = 0;
-          this.numDataBuffers = 0;
-          // Number of nested tf.grad() statements when computing higher-order
-          // gradients. E.g. `1` for first-order gradients and `2` for second-order
-          // gradients. Used to track if the tape should be removed after a backprop.
-          this.gradientDepth = 0;
-          // Number of nested kernel calls. When kernel depth is greater than 1, we turn
-          // off the tape.
-          this.kernelDepth = 0;
-          this.scopeStack = [];
-          /**
-           * Keeps track of the number of data moves during a kernel execution. We
-           * maintain a stack since kernels can call other kernels, recursively.
-           */
-          this.numDataMovesStack = [];
-          this.nextScopeId = 0;
-          this.tensorInfo = new WeakMap();
-          this.profiling = false;
-          this.activeProfile = {
-            newBytes: 0,
-            newTensors: 0,
-            peakBytes: 0,
-            kernels: [],
-            result: null,
-          };
-        }
-        dispose() {
-          for (const variableName in this.registeredVariables) {
-            this.registeredVariables[variableName].dispose();
-          }
-        }
-      }
-      class engine_Engine {
-        constructor(ENV) {
-          this.ENV = ENV;
-          this.registry = {};
-          this.registryFactory = {};
-          this.pendingBackendInitId = 0;
-          this.state = new EngineState();
-        }
-        async ready() {
-          if (this.pendingBackendInit != null) {
-            return this.pendingBackendInit.then(() => {});
-          }
-          if (this.backendInstance != null) {
-            return;
-          }
-          const sortedBackends = this.getSortedBackends();
-          for (let i = 0; i < sortedBackends.length; i++) {
-            const backendName = sortedBackends[i];
-            const success = await this.initializeBackend(backendName).success;
-            if (success) {
-              await this.setBackend(backendName);
-              return;
-            }
-          }
-          throw new Error(
-            `Could not initialize any backends, all backend initializations ` + `failed.`
-          );
-        }
-        get backend() {
-          if (this.pendingBackendInit != null) {
-            throw new Error(
-              `Backend '${this.backendName}' has not yet been initialized. Make ` +
-                `sure to await tf.ready() or await tf.setBackend() before calling ` +
-                `other methods`
-            );
-          }
-          if (this.backendInstance == null) {
-            const { name, asyncInit } = this.initializeBackendsAndReturnBest();
-            if (asyncInit) {
-              throw new Error(
-                `The highest priority backend '${name}' has not yet been ` +
-                  `initialized. Make sure to await tf.ready() or ` +
-                  `await tf.setBackend() before calling other methods`
-              );
-            }
-            this.setBackend(name);
-          }
-          return this.backendInstance;
-        }
-        backendNames() {
-          return Object.keys(this.registryFactory);
-        }
-        findBackend(backendName) {
-          if (!(backendName in this.registry)) {
-            // If the backend hasn't been initialized but we have a registry entry for
-            // it, initialize it and return it.
-            if (backendName in this.registryFactory) {
-              const { asyncInit } = this.initializeBackend(backendName);
-              if (asyncInit) {
-                // Backend is not ready yet.
-                return null;
-              }
-            } else {
-              return null;
-            }
-          }
-          return this.registry[backendName];
-        }
-        findBackendFactory(backendName) {
-          if (!(backendName in this.registryFactory)) {
-            return null;
-          }
-          return this.registryFactory[backendName].factory;
-        }
-        registerBackend(backendName, factory, priority = 1) {
-          if (backendName in this.registryFactory) {
-            console.warn(
-              `${backendName} backend was already registered. ` +
-                `Reusing existing backend factory.`
-            );
-            return false;
-          }
-          this.registryFactory[backendName] = { factory, priority };
-          return true;
-        }
-        async setBackend(backendName) {
-          if (this.registryFactory[backendName] == null) {
-            throw new Error(`Backend name '${backendName}' not found in registry`);
-          }
-          this.backendName = backendName;
-          if (this.registry[backendName] == null) {
-            this.backendInstance = null;
-            const { success, asyncInit } = this.initializeBackend(backendName);
-            const result = asyncInit ? await success : success;
-            if (!result) {
-              return false;
-            }
-          }
-          this.backendInstance = this.registry[backendName];
-          this.setupRegisteredKernels();
-          // Reset the profiler.
-          this.profiler = new Profiler(this.backendInstance);
-          return true;
-        }
-        setupRegisteredKernels() {
-          const kernels = Object(kernel_registry["c" /* getKernelsForBackend */])(this.backendName);
-          kernels.forEach((kernel) => {
-            if (kernel.setupFunc != null) {
-              kernel.setupFunc(this.backendInstance);
-            }
-          });
-        }
-        disposeRegisteredKernels(backendName) {
-          const kernels = Object(kernel_registry["c" /* getKernelsForBackend */])(backendName);
-          kernels.forEach((kernel) => {
-            if (kernel.disposeFunc != null) {
-              kernel.disposeFunc(this.registry[backendName]);
-            }
-          });
-        }
-        /**
-         * Initializes a backend by looking up the backend name in the factory
-         * registry and calling the factory method. Returns a boolean representing
-         * whether the initialization of the backend suceeded. Throws an error if
-         * there is no backend in the factory registry.
-         */
-        initializeBackend(backendName) {
-          const registryFactoryEntry = this.registryFactory[backendName];
-          if (registryFactoryEntry == null) {
-            throw new Error(`Cannot initialize backend ${backendName}, no registration found.`);
-          }
-          try {
-            const backend = registryFactoryEntry.factory();
-            // Test if the factory returns a promise.
-            if (Promise.resolve(backend) === backend) {
-              const promiseId = ++this.pendingBackendInitId;
-              const success = backend
-                .then((backendInstance) => {
-                  // Outdated promise. Another backend was set in the meantime.
-                  if (promiseId < this.pendingBackendInitId) {
-                    return false;
-                  }
-                  this.registry[backendName] = backendInstance;
-                  this.pendingBackendInit = null;
-                  return true;
-                })
-                .catch((err) => {
-                  // Outdated promise. Another backend was set in the meantime.
-                  if (promiseId < this.pendingBackendInitId) {
-                    return false;
-                  }
-                  this.pendingBackendInit = null;
-                  console.warn(`Initialization of backend ${backendName} failed`);
-                  console.warn(err.stack || err.message);
-                  return false;
-                });
-              this.pendingBackendInit = success;
-              return { success, asyncInit: true };
-            } else {
-              this.registry[backendName] = backend;
-              return { success: true, asyncInit: false };
-            }
-          } catch (err) {
-            console.warn(`Initialization of backend ${backendName} failed`);
-            console.warn(err.stack || err.message);
-            return { success: false, asyncInit: false };
-          }
-        }
-        removeBackend(backendName) {
-          if (!(backendName in this.registryFactory)) {
-            throw new Error(`${backendName} backend not found in registry`);
-          }
-          if (this.backendName === backendName && this.pendingBackendInit != null) {
-            // There is a pending promise of the backend we want to remove. Make it
-            // obsolete.
-            this.pendingBackendInitId++;
-          }
-          if (backendName in this.registry) {
-            this.disposeRegisteredKernels(backendName);
-            this.registry[backendName].dispose();
-            delete this.registry[backendName];
-          }
-          delete this.registryFactory[backendName];
-          // Unset the backend if it is active.
-          if (this.backendName === backendName) {
-            this.pendingBackendInit = null;
-            this.backendName = null;
-            this.backendInstance = null;
-          }
-        }
-        getSortedBackends() {
-          if (Object.keys(this.registryFactory).length === 0) {
-            throw new Error("No backend found in registry.");
-          }
-          return Object.keys(this.registryFactory).sort((a, b) => {
-            // Highest priority comes first.
-            return this.registryFactory[b].priority - this.registryFactory[a].priority;
-          });
-        }
-        initializeBackendsAndReturnBest() {
-          const sortedBackends = this.getSortedBackends();
-          for (let i = 0; i < sortedBackends.length; i++) {
-            const backendName = sortedBackends[i];
-            const { success, asyncInit } = this.initializeBackend(backendName);
-            if (asyncInit || success) {
-              return { name: backendName, asyncInit };
-            }
-          }
-          throw new Error(
-            `Could not initialize any backends, all backend initializations ` + `failed.`
-          );
-        }
-        moveData(backend, dataId) {
-          const info = this.state.tensorInfo.get(dataId);
-          const srcBackend = info.backend;
-          const values = this.readSync(dataId);
-          // Delete the tensor from the old backend and move it to the new
-          // backend.
-          srcBackend.disposeData(dataId);
-          info.backend = backend;
-          backend.move(dataId, values, info.shape, info.dtype);
-          if (this.shouldCheckForMemLeaks()) {
-            // Track the number of moves during a kernel execution to correctly
-            // detect memory leaks.
-            this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1]++;
-          }
-        }
-        tidy(nameOrFn, fn) {
-          let name = null;
-          if (fn == null) {
-            // Called with only 1 argument.
-            if (typeof nameOrFn !== "function") {
-              throw new Error("Please provide a function to tidy()");
-            }
-            fn = nameOrFn;
-          } else {
-            // Called with 2 arguments.
-            if (typeof nameOrFn !== "string" && !(nameOrFn instanceof String)) {
-              throw new Error(
-                "When calling with two arguments, the first argument " +
-                  "to tidy() must be a string"
-              );
-            }
-            if (typeof fn !== "function") {
-              throw new Error(
-                "When calling with two arguments, the 2nd argument " +
-                  "to tidy() must be a function"
-              );
-            }
-            name = nameOrFn;
-            // TODO(nsthorat,smilkov): Do operation logging and performance
-            // profiling.
-          }
-          let result;
-          return this.scopedRun(
-            () => this.startScope(name),
-            () => this.endScope(result),
-            () => {
-              result = fn();
-              if (result instanceof Promise) {
-                console.error("Cannot return a Promise inside of tidy.");
-              }
-              return result;
-            }
-          );
-        }
-        scopedRun(start, end, f) {
-          start();
-          try {
-            const res = f();
-            end();
-            return res;
-          } catch (ex) {
-            end();
-            throw ex;
-          }
-        }
-        nextTensorId() {
-          return engine_Engine.nextTensorId++;
-        }
-        nextVariableId() {
-          return engine_Engine.nextVariableId++;
-        }
-        /**
-         * This method is called instead of the public-facing tensor.clone() when
-         * saving a tensor for backwards pass. It makes sure to add the clone
-         * operation to the tape regardless of being called inside a kernel
-         * execution.
-         *
-         * This method will go away once all kernels are modularized since we won't
-         * need to turn off the tape inside runKernel().
-         */
-        clone(x) {
-          const y = this.makeTensorFromDataId(x.dataId, x.shape, x.dtype);
-          const inputs = { x };
-          const grad = (dy) => ({ x: () => dy.toFloat() });
-          const saved = [];
-          this.addTapeNode(this.state.activeScope.name, inputs, [y], grad, saved, {});
-          return y;
-        }
-        /**
-         * Execute a kernel with the given name and return the output tensor.
-         *
-         * @param kernelName The name of the kernel to execute.
-         * @param inputs A map of input names to tensors.
-         * @param attrs A map of attribute names to their values. An attribute is a
-         *     primitive (non-tensor) input to the kernel.
-         * @param inputsToSave A list of tensors, inputs to save for the backprop
-         *     computation.
-         * @param outputsToSave A list of booleans, specifying which output to save
-         *     for the backprop computation. These are booleans since the output
-         * tensors are not visible to the user.
-         */
-        runKernel(kernelName, inputs, attrs, inputsToSave, outputsToSave) {
-          const forwardFunc = null;
-          const backwardsFunc = null;
-          // Call runKernel as a stop-gap until we modularize all kernels.
-          // Once we modularize all kernels, we will remove the existing
-          // `runKernelFunc`.
-          return this.runKernelFunc(
-            forwardFunc,
-            inputs,
-            backwardsFunc,
-            kernelName,
-            attrs,
-            inputsToSave,
-            outputsToSave
-          );
-        }
-        shouldCheckForMemLeaks() {
-          return this.ENV.getBool("IS_TEST");
-        }
-        checkKernelForMemLeak(kernelName, numDataIdsBefore, outInfos) {
-          const numDataIdsAfter = this.backend.numDataIds();
-          // Count the number of data ids associated with the result of the kernel.
-          let numOutputDataIds = 0;
-          outInfos.forEach((info) => {
-            // Complex numbers allocate 3 data ids, one for 'real', one for
-            // 'imaginary', and one for the container that holds the former two.
-            numOutputDataIds += info.dtype === "complex64" ? 3 : 1;
-          });
-          // Account for the number of moves during kernel execution. A "data move"
-          // can happen in the middle of a kernel execution, placing a new (key,value)
-          // pair in the data storage. Since data moves have net zero effect (we
-          // always remove the data from the old backend), we have to cancel them out
-          // when detecting memory leaks.
-          const numMoves = this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1];
-          const dataIdsLeaked = numDataIdsAfter - numDataIdsBefore - numOutputDataIds - numMoves;
-          if (dataIdsLeaked > 0) {
-            throw new Error(
-              `Backend '${this.backendName}' has an internal memory leak ` +
-                `(${dataIdsLeaked} data ids) after running '${kernelName}'`
-            );
-          }
-        }
-        /**
-         * @deprecated Use `runKernel` for newly added kernels. Keep using this method
-         *     only for kernels that are not yet fully modularized.
-         */
-        runKernelFunc(
-          forwardFunc,
-          inputs,
-          backwardsFunc,
-          kernelName,
-          attrs,
-          inputsToSave,
-          outputsToSave
-        ) {
-          let outputs;
-          let saved = [];
-          const isTapeOn = this.isTapeOn();
-          if (kernelName == null) {
-            kernelName = this.state.activeScope != null ? this.state.activeScope.name : "";
-          }
-          const startingBytecount = this.state.numBytes;
-          const startingNumTensors = this.state.numTensors;
-          if (this.shouldCheckForMemLeaks()) {
-            this.state.numDataMovesStack.push(0);
-          }
-          let kernelFunc;
-          const kernel = Object(kernel_registry["b" /* getKernel */])(kernelName, this.backendName);
-          let out;
-          if (kernel != null) {
-            kernelFunc = () => {
-              const numDataIdsBefore = this.backend.numDataIds();
-              out = kernel.kernelFunc({ inputs, attrs, backend: this.backend });
-              const outInfos = Array.isArray(out) ? out : [out];
-              if (this.shouldCheckForMemLeaks()) {
-                this.checkKernelForMemLeak(kernelName, numDataIdsBefore, outInfos);
-              }
-              const outTensors = outInfos.map(({ dataId, shape, dtype }) =>
-                this.makeTensorFromDataId(dataId, shape, dtype)
-              );
-              // Save the inputs and outputs.
-              // Do not save unless we are recording to the tape. Otherwise it would
-              // cause a mem leak since we would never run backprop, which disposes
-              // the kept tensors.
-              if (isTapeOn) {
-                let tensorsToSave = this.getTensorsForGradient(kernelName, inputs, outTensors);
-                if (tensorsToSave == null) {
-                  // Fallback for ops that call runKernelFunc and pass in
-                  // inputsToSave and outputsToSave. Currently this is the set of ops
-                  // with kernel support in the WASM backend. Once those ops and
-                  // respective gradients are modularised we can remove this path.
-                  if (outputsToSave == null) {
-                    outputsToSave = [];
-                  }
-                  const outsToSave = outTensors.filter((_, i) => outputsToSave[i]);
-                  tensorsToSave = (inputsToSave || []).slice().concat(outsToSave);
-                }
-                saved = this.saveTensorsForBackwardMode(tensorsToSave);
-              }
-              return outTensors;
-            };
-          } else {
-            const saveFunc = (tensors) => {
-              // Do not save unless we are recording to the tape. Otherwise it would
-              // cause a mem leak since we would never run backprop, which disposes
-              // the kept tensors.
-              if (!isTapeOn) {
-                return;
-              }
-              saved = tensors.map((tensor) => this.keep(this.clone(tensor)));
-            };
-            kernelFunc = () => {
-              const numDataIdsBefore = this.backend.numDataIds();
-              out = this.tidy(() => forwardFunc(this.backend, saveFunc));
-              const outs = Array.isArray(out) ? out : [out];
-              if (this.shouldCheckForMemLeaks()) {
-                this.checkKernelForMemLeak(kernelName, numDataIdsBefore, outs);
-              }
-              return outs;
-            };
-          }
-          // Stop recording to a tape when running a kernel.
-          this.scopedRun(
-            () => this.state.kernelDepth++,
-            () => this.state.kernelDepth--,
-            () => {
-              if (!this.ENV.getBool("DEBUG")) {
-                outputs = kernelFunc();
-              } else {
-                outputs = this.profiler.profileKernel(kernelName, inputs, () => kernelFunc());
-              }
-            }
-          );
-          if (isTapeOn) {
-            this.addTapeNode(kernelName, inputs, outputs, backwardsFunc, saved, attrs);
-          }
-          if (this.state.profiling) {
-            this.state.activeProfile.kernels.push({
-              name: kernelName,
-              bytesAdded: this.state.numBytes - startingBytecount,
-              totalBytesSnapshot: this.state.numBytes,
-              tensorsAdded: this.state.numTensors - startingNumTensors,
-              totalTensorsSnapshot: this.state.numTensors,
-              inputShapes: Object.keys(inputs).map((key) => inputs[key].shape),
-              outputShapes: outputs.map((item) => item.shape),
-            });
-          }
-          return Array.isArray(out) ? outputs : outputs[0];
-        }
-        /**
-         * Saves tensors used in forward mode for use in backward mode.
-         *
-         * @param tensors the list of tensors to save.
-         */
-        saveTensorsForBackwardMode(tensors) {
-          const saved = tensors.map((tensor) => this.keep(this.clone(tensor)));
-          return saved;
-        }
-        /**
-         * Returns a list of tensors to save for a given gradient calculation.
-         *
-         * Returns undefined if their is no registered gradient for this kernel in the
-         * gradient registry.
-         *
-         * @param kernelName name of kernel to look up gradient for.
-         * @param inputs a map of input tensors.
-         * @param outputs an array of output tensors from forward mode of kernel.
-         */
-        getTensorsForGradient(kernelName, inputs, outputs) {
-          const gradConfig = Object(kernel_registry["a" /* getGradient */])(kernelName);
-          if (gradConfig != null) {
-            const inputsToSave = gradConfig.inputsToSave || [];
-            const outputsToSave = gradConfig.outputsToSave || [];
-            // If saveAllInputs is true, all inputs will be saved. Otherwise, inputs
-            // specified in inputsToSave will be saved.
-            let inputTensorsToSave;
-            if (gradConfig.saveAllInputs) {
-              util["assert"](
-                Array.isArray(inputs),
-                () => "saveAllInputs is true, expected inputs to be an array."
-              );
-              inputTensorsToSave = Object.keys(inputs).map((key) => inputs[key]);
-            } else {
-              inputTensorsToSave = inputsToSave.map((inputName) => inputs[inputName]);
-            }
-            const outputTensorsToSave = outputs.filter((_, i) => outputsToSave[i]);
-            return inputTensorsToSave.concat(outputTensorsToSave);
-          }
-          // TODO(yassogba) throw exception here once all runkernelFunc calls with
-          // inputsToSave/outputsToSave are removed
-          return null;
-        }
-        /**
-         * Internal method used by public APIs for tensor creation. Makes a new
-         * tensor with the provided shape, dtype and values. It always
-         * creates a new data id and writes the values to the underlying backend.
-         */
-        makeTensor(values, shape, dtype, backend) {
-          if (values == null) {
-            throw new Error("Values passed to engine.makeTensor() are null");
-          }
-          dtype = dtype || "float32";
-          backend = backend || this.backend;
-          let backendVals = values;
-          if (dtype === "string" && util["isString"](values[0])) {
-            backendVals = values.map((d) => util["encodeString"](d));
-          }
-          const dataId = backend.write(backendVals, shape, dtype);
-          const t = new tensor["a" /* Tensor */](shape, dtype, dataId, this.nextTensorId());
-          this.incRef(t, backend);
-          // Count bytes for string tensors.
-          if (dtype === "string") {
-            const info = this.state.tensorInfo.get(dataId);
-            const newBytes = Object(util["bytesFromStringArray"])(backendVals);
-            this.state.numBytes += newBytes - info.bytes;
-            info.bytes = newBytes;
-          }
-          return t;
-        }
-        /**
-         * Internal method used by backends. Makes a new tensor
-         * that is a wrapper around an existing data id. It doesn't create
-         * a new data id, only increments the ref count used in memory tracking.
-         */
-        makeTensorFromDataId(dataId, shape, dtype, backend) {
-          dtype = dtype || "float32";
-          const t = new tensor["a" /* Tensor */](shape, dtype, dataId, this.nextTensorId());
-          this.incRef(t, backend);
-          return t;
-        }
-        makeVariable(initialValue, trainable = true, name, dtype) {
-          name = name || this.nextVariableId().toString();
-          if (dtype != null && dtype !== initialValue.dtype) {
-            initialValue = initialValue.asType(dtype);
-          }
-          const v = new tensor["c" /* Variable */](
-            initialValue,
-            trainable,
-            name,
-            this.nextTensorId()
-          );
-          if (this.state.registeredVariables[v.name] != null) {
-            throw new Error(`Variable with name ${v.name} was already registered`);
-          }
-          this.state.registeredVariables[v.name] = v;
-          this.incRef(v, this.backend);
-          return v;
-        }
-        incRef(a, backend) {
-          const refCount = this.state.tensorInfo.has(a.dataId)
-            ? this.state.tensorInfo.get(a.dataId).refCount
-            : 0;
-          this.state.numTensors++;
-          if (a.dtype === "string") {
-            this.state.numStringTensors++;
-          }
-          if (refCount === 0) {
-            this.state.numDataBuffers++;
-            // Bytes for complex numbers are counted by their components. Bytes for
-            // string tensors are counted when writing values.
-            let bytes = 0;
-            if (a.dtype !== "complex64" && a.dtype !== "string") {
-              bytes = a.size * util["bytesPerElement"](a.dtype);
-            }
-            this.state.tensorInfo.set(a.dataId, {
-              backend: backend || this.backend,
-              dtype: a.dtype,
-              shape: a.shape,
-              bytes,
-              refCount: 0,
-            });
-            this.state.numBytes += bytes;
-          }
-          this.state.tensorInfo.get(a.dataId).refCount++;
-          if (!(a instanceof tensor["c" /* Variable */])) {
-            this.track(a);
-          }
-        }
-        disposeTensor(a) {
-          if (!this.state.tensorInfo.has(a.dataId)) {
-            return;
-          }
-          this.state.numTensors--;
-          if (a.dtype === "string") {
-            this.state.numStringTensors--;
-          }
-          const info = this.state.tensorInfo.get(a.dataId);
-          const refCount = info.refCount;
-          if (refCount <= 1) {
-            // Don't count bytes for complex numbers as they are counted by their
-            // components.
-            if (a.dtype !== "complex64") {
-              this.state.numBytes -= info.bytes;
-            }
-            this.state.numDataBuffers--;
-            info.backend.disposeData(a.dataId);
-            this.state.tensorInfo.delete(a.dataId);
-          } else {
-            this.state.tensorInfo.get(a.dataId).refCount--;
-          }
-          // TODO(nsthorat): Construct an error and save the stack trace for
-          // debugging when in debug mode. Creating a stack trace is too expensive
-          // to do unconditionally.
-        }
-        disposeVariables() {
-          for (const varName in this.state.registeredVariables) {
-            const v = this.state.registeredVariables[varName];
-            this.disposeVariable(v);
-          }
-        }
-        disposeVariable(v) {
-          this.disposeTensor(v);
-          if (this.state.registeredVariables[v.name] != null) {
-            delete this.state.registeredVariables[v.name];
-          }
-        }
-        memory() {
-          const info = this.backend.memory();
-          info.numTensors = this.state.numTensors;
-          info.numDataBuffers = this.state.numDataBuffers;
-          info.numBytes = this.state.numBytes;
-          if (this.state.numStringTensors > 0) {
-            info.unreliable = true;
-            if (info.reasons == null) {
-              info.reasons = [];
-            }
-            info.reasons.push(
-              "Memory usage by string tensors is approximate " + "(2 bytes per character)"
-            );
-          }
-          return info;
-        }
-        async profile(query) {
-          this.state.profiling = true;
-          const startBytes = this.state.numBytes;
-          const startNumTensors = this.state.numTensors;
-          this.state.activeProfile.kernels = [];
-          this.state.activeProfile.result = query();
-          this.state.profiling = false;
-          this.state.activeProfile.peakBytes = Math.max(
-            ...this.state.activeProfile.kernels.map((d) => d.totalBytesSnapshot)
-          );
-          this.state.activeProfile.newBytes = this.state.numBytes - startBytes;
-          this.state.activeProfile.newTensors = this.state.numTensors - startNumTensors;
-          return this.state.activeProfile;
-        }
-        isTapeOn() {
-          return this.state.gradientDepth > 0 && this.state.kernelDepth === 0;
-        }
-        addTapeNode(kernelName, inputs, outputs, gradientsFunc, saved, attrs) {
-          const tapeNode = { id: this.state.nextTapeNodeId++, kernelName, inputs, outputs, saved };
-          const gradConfig = Object(kernel_registry["a" /* getGradient */])(kernelName);
-          if (gradConfig != null) {
-            gradientsFunc = gradConfig.gradFunc;
-          }
-          if (gradientsFunc != null) {
-            tapeNode.gradient = (dys) => {
-              // TODO(smilkov): To optimize back-prop, pass dys that are not used in
-              // the backprop graph to the user as null instead of zeros
-              dys = dys.map((dy, i) => {
-                if (dy == null) {
-                  const output = outputs[i];
-                  const vals = util["makeZerosTypedArray"](output.size, output.dtype);
-                  return this.makeTensor(vals, output.shape, output.dtype);
-                }
-                return dy;
-              });
-              // Grad functions of ops with single outputs expect a dy, while ops
-              // with multiple outputs expect dys (array of dy).
-              return gradientsFunc(dys.length > 1 ? dys : dys[0], saved, attrs);
-            };
-          }
-          this.state.activeTape.push(tapeNode);
-        }
-        keep(result) {
-          result.kept = true;
-          return result;
-        }
-        startTape() {
-          if (this.state.gradientDepth === 0) {
-            this.state.activeTape = [];
-          }
-          this.state.gradientDepth++;
-        }
-        endTape() {
-          this.state.gradientDepth--;
-        }
-        /**
-         * Start a scope. Use this with endScope() to achieve the same functionality
-         * as scope() without the need for a function closure.
-         */
-        startScope(name) {
-          const scopeInfo = {
-            track: [],
-            name: "unnamed scope",
-            id: this.state.nextScopeId++,
-          };
-          if (name) {
-            scopeInfo.name = name;
-          }
-          this.state.scopeStack.push(scopeInfo);
-          this.state.activeScope = scopeInfo;
-        }
-        /**
-         * End a scope. Use this with startScope() to achieve the same functionality
-         * as scope() without the need for a function closure.
-         */
-        endScope(result) {
-          const tensorsToTrackInParent = Object(tensor_util["getTensorsInContainer"])(result);
-          const tensorsToTrackInParentSet = new Set(tensorsToTrackInParent.map((t) => t.id));
-          // Dispose the arrays tracked in this scope.
-          for (let i = 0; i < this.state.activeScope.track.length; i++) {
-            const tensor = this.state.activeScope.track[i];
-            if (!tensor.kept && !tensorsToTrackInParentSet.has(tensor.id)) {
-              tensor.dispose();
-            }
-          }
-          const oldScope = this.state.scopeStack.pop();
-          this.state.activeScope =
-            this.state.scopeStack.length === 0
-              ? null
-              : this.state.scopeStack[this.state.scopeStack.length - 1];
-          // Track the current result in the parent scope.
-          tensorsToTrackInParent.forEach((tensor) => {
-            // Only track the tensor if was allocated in the inner scope and is not
-            // globally kept.
-            if (!tensor.kept && tensor.scopeId === oldScope.id) {
-              this.track(tensor);
-            }
-          });
-        }
-        /**
-         * Returns gradients of `f` with respect to each of the `xs`. The gradients
-         * returned are of the same length as `xs`, but some might be null if `f`
-         * was not a function of that `x`. It also takes optional dy to multiply the
-         * gradient, which defaults to `1`.
-         */
-        gradients(f, xs, dy, allowNoGradients = false) {
-          util["assert"](xs.length > 0, () => "gradients() received an empty list of xs.");
-          if (dy != null && dy.dtype !== "float32") {
-            throw new Error(`dy must have 'float32' dtype, but has '${dy.dtype}'`);
-          }
-          const y = this.scopedRun(
-            () => this.startTape(),
-            () => this.endTape(),
-            () => this.tidy("forward", f)
-          );
-          util["assert"](
-            y instanceof tensor["a" /* Tensor */],
-            () => "The result y returned by f() must be a tensor."
-          );
-          // Filter out the nodes that don't connect x => y.
-          const filteredTape = getFilteredNodesXToY(this.state.activeTape, xs, y);
-          if (!allowNoGradients && filteredTape.length === 0 && xs.length > 0) {
-            throw new Error(
-              "Cannot compute gradient of y=f(x) with respect to x. Make sure " +
-                "that the f you passed encloses all operations that lead from x " +
-                "to y."
-            );
-          }
-          return this.tidy("backward", () => {
-            const accumulatedGradientMap = {};
-            accumulatedGradientMap[y.id] = dy == null ? ones(y.shape) : dy;
-            // Backprop gradients through the filtered nodes.
-            backpropagateGradients(
-              accumulatedGradientMap,
-              filteredTape,
-              // Pass the tidy function to avoid circular dep with `tape.ts`.
-              (f) => this.tidy(f)
-            );
-            const grads = xs.map((x) => accumulatedGradientMap[x.id]);
-            if (this.state.gradientDepth === 0) {
-              // This means that we are not computing higher-order gradients
-              // and can clean up the tape.
-              this.state.activeTape.forEach((node) => {
-                for (const tensor of node.saved) {
-                  tensor.dispose();
-                }
-              });
-              this.state.activeTape = null;
-            }
-            return { value: y, grads };
-          });
-        }
-        customGrad(f) {
-          util["assert"](
-            util["isFunction"](f),
-            () => "The f passed in customGrad(f) must be a function."
-          );
-          return (...inputs) => {
-            util["assert"](
-              inputs.every((t) => t instanceof tensor["a" /* Tensor */]),
-              () => "The args passed in customGrad(f)(x1, x2,...) must all be " + "tensors"
-            );
-            let res;
-            const inputMap = {};
-            inputs.forEach((input, i) => {
-              inputMap[i] = input;
-            });
-            return this.runKernelFunc(
-              (_, save) => {
-                res = f(...[...inputs, save]);
-                util["assert"](
-                  res.value instanceof tensor["a" /* Tensor */],
-                  () =>
-                    "The function f passed in customGrad(f) must return an " +
-                    "object where `obj.value` is a tensor"
-                );
-                util["assert"](
-                  util["isFunction"](res.gradFunc),
-                  () =>
-                    "The function f passed in customGrad(f) must return an " +
-                    "object where `obj.gradFunc` is a function."
-                );
-                return res.value;
-              },
-              inputMap,
-              (dy, saved) => {
-                const gradRes = res.gradFunc(dy, saved);
-                const grads = Array.isArray(gradRes) ? gradRes : [gradRes];
-                util["assert"](
-                  grads.length === inputs.length,
-                  () =>
-                    "The function f passed in customGrad(f) must return an " +
-                    "object where `obj.gradFunc` is a function that returns " +
-                    "the same number of tensors as inputs passed to f(...)."
-                );
-                util["assert"](
-                  grads.every((t) => t instanceof tensor["a" /* Tensor */]),
-                  () =>
-                    "The function f passed in customGrad(f) must return an " +
-                    "object where `obj.gradFunc` is a function that returns " +
-                    "a list of only tensors."
-                );
-                const gradMap = {};
-                grads.forEach((grad, i) => {
-                  gradMap[i] = () => grad;
-                });
-                return gradMap;
-              }
-            );
-          };
-        }
-        readSync(dataId) {
-          // Route the read to the correct backend.
-          const info = this.state.tensorInfo.get(dataId);
-          return info.backend.readSync(dataId);
-        }
-        read(dataId) {
-          // Route the read to the correct backend.
-          const info = this.state.tensorInfo.get(dataId);
-          return info.backend.read(dataId);
-        }
-        async time(query) {
-          const start = Object(util["now"])();
-          const timingInfo = await this.backend.time(query);
-          timingInfo.wallMs = Object(util["now"])() - start;
-          return timingInfo;
-        }
-        /**
-         * Tracks a Tensor in the current scope to be automatically cleaned up
-         * when the current scope ends, and returns the value.
-         *
-         * @param result The Tensor to track in the current scope.
-         */
-        track(result) {
-          if (this.state.activeScope != null) {
-            result.scopeId = this.state.activeScope.id;
-            this.state.activeScope.track.push(result);
-          }
-          return result;
-        }
-        get registeredVariables() {
-          return this.state.registeredVariables;
-        }
-        /**
-         * Resets the engine state. Removes all backends but does not remove
-         * registered backend factories.
-         */
-        reset() {
-          // Make any pending promise obsolete.
-          this.pendingBackendInitId++;
-          this.state.dispose();
-          this.ENV.reset();
-          this.state = new EngineState();
-          for (const backendName in this.registry) {
-            this.disposeRegisteredKernels(backendName);
-            this.registry[backendName].dispose();
-            delete this.registry[backendName];
-          }
-          this.backendName = null;
-          this.backendInstance = null;
-          this.pendingBackendInit = null;
-        }
-      }
-      engine_Engine.nextTensorId = 0;
-      engine_Engine.nextVariableId = 0;
-      function ones(shape) {
-        const values = Object(util["makeOnesTypedArray"])(
-          Object(util["sizeFromShape"])(shape),
-          "float32"
-        );
-        return ENGINE.makeTensor(values, shape, "float32");
-      }
-      function getOrMakeEngine() {
-        const ns = Object(global_util["b" /* getGlobalNamespace */])();
-        if (ns._tfengine == null) {
-          const environment = new dist_environment["b" /* Environment */](ns);
-          ns._tfengine = new engine_Engine(environment);
-        }
-        Object(dist_environment["d" /* setEnvironmentGlobal */])(ns._tfengine.ENV);
-        // Tell the current tensor interface that the global engine is responsible
-        // for tracking.
-        Object(tensor["f" /* setTensorTracker */])(() => ns._tfengine);
-        return ns._tfengine;
-      }
-      const ENGINE = getOrMakeEngine();
-      //# sourceMappingURL=engine.js.map
-
-      /***/
-    },
-    /* 6 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return Add;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return AddN;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return Atan2;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
-        return AvgPool;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
-        return AvgPoolBackprop;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
-        return AvgPool3D;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
-        return AvgPool3DBackprop;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "h", function () {
-        return BatchMatMul;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "i", function () {
-        return BatchToSpaceND;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "j", function () {
-        return BroadcastTo;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "k", function () {
-        return Complex;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "l", function () {
-        return Concat;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "m", function () {
-        return Conv2D;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "n", function () {
-        return Conv2DBackpropFilter;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "o", function () {
-        return Conv2DBackpropInput;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "p", function () {
-        return Conv3D;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "q", function () {
-        return Conv3DBackpropFilterV2;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "r", function () {
-        return Conv3DBackpropInputV2;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "s", function () {
-        return Cumsum;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "t", function () {
-        return DepthToSpace;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "u", function () {
-        return DepthwiseConv2dNative;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "v", function () {
-        return DepthwiseConv2dNativeBackpropFilter;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "w", function () {
-        return DepthwiseConv2dNativeBackpropInput;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "x", function () {
-        return Diag;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "y", function () {
-        return Div;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "z", function () {
-        return Elu;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "A", function () {
-        return EluGrad;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "B", function () {
-        return Equal;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "D", function () {
-        return FloorDiv;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "C", function () {
-        return Fill;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "F", function () {
-        return FusedBatchNorm;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "G", function () {
-        return GatherNd;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "H", function () {
-        return Greater;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "I", function () {
-        return GreaterEqual;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "J", function () {
-        return Identity;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "K", function () {
-        return Imag;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "N", function () {
-        return Less;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "O", function () {
-        return LessEqual;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "L", function () {
-        return LRN;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "M", function () {
-        return LRNBackprop;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "P", function () {
-        return Max;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "V", function () {
-        return Maximum;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "Q", function () {
-        return MaxPool;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "T", function () {
-        return MaxPoolBackprop;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "R", function () {
-        return MaxPool3D;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "S", function () {
-        return MaxPool3DBackprop;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "U", function () {
-        return MaxPoolWithArgmax;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "W", function () {
-        return Minimum;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "X", function () {
-        return Mod;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "Y", function () {
-        return Multiply;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "bb", function () {
-        return NotEqual;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "Z", function () {
-        return NonMaxSuppressionV3;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "ab", function () {
-        return NonMaxSuppressionV5;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "cb", function () {
-        return OneHot;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "db", function () {
-        return PadV2;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "eb", function () {
-        return Pool;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "fb", function () {
-        return Pow;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "gb", function () {
-        return Prelu;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "hb", function () {
-        return Real;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "ib", function () {
-        return Relu;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "jb", function () {
-        return Relu6;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "kb", function () {
-        return SelectV2;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "lb", function () {
-        return Selu;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "mb", function () {
-        return SpaceToBatchND;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "nb", function () {
-        return SplitV;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "pb", function () {
-        return SquaredDifference;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "ob", function () {
-        return Square;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "qb", function () {
-        return Sub;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "rb", function () {
-        return Tile;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "sb", function () {
-        return Transpose;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "E", function () {
-        return FromPixels;
-      });
-      const Add = "Add";
-      const AddN = "AddN";
-      const Atan2 = "Atan2";
-      const AvgPool = "AvgPool";
-      const AvgPoolBackprop = "AvgPoolBackprop";
-      const AvgPool3D = "AvgPool3D";
-      const AvgPool3DBackprop = "AvgPool3DBackprop";
-      const BatchMatMul = "BatchMatMul";
-      const BatchToSpaceND = "BatchToSpaceND";
-      const BroadcastTo = "BroadcastTo";
-      const Complex = "Complex";
-      const Concat = "Concat";
-      const Conv2D = "Conv2D";
-      const Conv2DBackpropFilter = "Conv2DBackpropFilter";
-      const Conv2DBackpropInput = "Conv2DBackpropInput";
-      const Conv3D = "Conv3D";
-      const Conv3DBackpropFilterV2 = "Conv3DBackpropFilterV2";
-      const Conv3DBackpropInputV2 = "Conv3DBackpropInputV2";
-      const Cumsum = "Cumsum";
-      const DepthToSpace = "DepthToSpace";
-      const DepthwiseConv2dNative = "DepthwiseConv2dNative";
-      const DepthwiseConv2dNativeBackpropFilter = "DepthwiseConv2dNativeBackpropFilter";
-      const DepthwiseConv2dNativeBackpropInput = "DepthwiseConv2dNativeBackpropInput";
-      const Diag = "Diag";
-      const Div = "Div";
-      const Elu = "Elu";
-      const EluGrad = "EluGrad";
-      const Equal = "Equal";
-      const FloorDiv = "FloorDiv";
-      const Fill = "Fill";
-      const FusedBatchNorm = "FusedBatchNorm";
-      const GatherNd = "GatherNd";
-      const Greater = "Greater";
-      const GreaterEqual = "GreaterEqual";
-      const Identity = "Identity";
-      const Imag = "Imag";
-      const Less = "Less";
-      const LessEqual = "LessEqual";
-      const LRN = "LRN";
-      const LRNBackprop = "LRNBackprop";
-      const Max = "Max";
-      const Maximum = "Maximum";
-      const MaxPool = "MaxPool";
-      const MaxPoolBackprop = "MaxPoolBackprop";
-      const MaxPool3D = "MaxPool3D";
-      const MaxPool3DBackprop = "MaxPool3DBackprop";
-      const MaxPoolWithArgmax = "MaxPoolWithArgmax";
-      const Minimum = "Minimum";
-      const Mod = "Mod";
-      const Multiply = "Multiply";
-      const NotEqual = "NotEqual";
-      const NonMaxSuppressionV3 = "NonMaxSuppressionV3";
-      const NonMaxSuppressionV5 = "NonMaxSuppressionV5";
-      const OneHot = "OneHot";
-      const PadV2 = "PadV2";
-      const Pool = "Pool";
-      const Pow = "Pow";
-      const Prelu = "Prelu";
-      const Real = "Real";
-      const Relu = "Relu";
-      const Relu6 = "Relu6";
-      const SelectV2 = "SelectV2";
-      const Selu = "Selu";
-      const SpaceToBatchND = "SpaceToBatchND";
-      const SplitV = "SplitV";
-      const SquaredDifference = "SquaredDifference";
-      const Square = "Square";
-      const Sub = "Sub";
-      const Tile = "Tile";
-      const Transpose = "Transpose";
-      /**
-       * TensorFlow.js-only kernels
-       */
-      const FromPixels = "FromPixels";
-      //# sourceMappingURL=kernel_names.js.map
-
-      /***/
-    },
-    /* 7 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "b", function () {
-        return /* binding */ tensor_TensorBuffer;
-      });
-      __webpack_require__.d(__webpack_exports__, "f", function () {
-        return /* binding */ setTensorTracker;
-      });
-      __webpack_require__.d(__webpack_exports__, "e", function () {
-        return /* binding */ setOpHandler;
-      });
-      __webpack_require__.d(__webpack_exports__, "d", function () {
-        return /* binding */ setDeprecationWarningFn;
-      });
-      __webpack_require__.d(__webpack_exports__, "a", function () {
-        return /* binding */ tensor_Tensor;
-      });
-      __webpack_require__.d(__webpack_exports__, "c", function () {
-        return /* binding */ tensor_Variable;
-      });
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/util.js
-      var util = __webpack_require__(1);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor_format.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // Maximum number of values before we decide to show ellipsis.
-      const FORMAT_LIMIT_NUM_VALS = 20;
-      // Number of first and last values to show when displaying a, b,...,y, z.
-      const FORMAT_NUM_FIRST_LAST_VALS = 3;
-      // Number of significant digits to show.
-      const FORMAT_NUM_SIG_DIGITS = 7;
-      function tensorToString(vals, shape, dtype, verbose) {
-        const strides = Object(util["computeStrides"])(shape);
-        const padPerCol = computeMaxSizePerColumn(vals, shape, dtype, strides);
-        const rank = shape.length;
-        const valsLines = subTensorToString(vals, shape, dtype, strides, padPerCol);
-        const lines = ["Tensor"];
-        if (verbose) {
-          lines.push(`  dtype: ${dtype}`);
-          lines.push(`  rank: ${rank}`);
-          lines.push(`  shape: [${shape}]`);
-          lines.push(`  values:`);
-        }
-        lines.push(valsLines.map((l) => "    " + l).join("\n"));
-        return lines.join("\n");
-      }
-      function computeMaxSizePerColumn(vals, shape, dtype, strides) {
-        const n = Object(util["sizeFromShape"])(shape);
-        const numCols = strides[strides.length - 1];
-        const padPerCol = new Array(numCols).fill(0);
-        const rank = shape.length;
-        const valuesOrTuples = dtype === "complex64" ? createComplexTuples(vals) : vals;
-        if (rank > 1) {
-          for (let row = 0; row < n / numCols; row++) {
-            const offset = row * numCols;
-            for (let j = 0; j < numCols; j++) {
-              padPerCol[j] = Math.max(
-                padPerCol[j],
-                valToString(valuesOrTuples[offset + j], 0, dtype).length
-              );
-            }
-          }
-        }
-        return padPerCol;
-      }
-      function valToString(val, pad, dtype) {
-        let valStr;
-        if (Array.isArray(val)) {
-          valStr =
-            `${parseFloat(val[0].toFixed(FORMAT_NUM_SIG_DIGITS))} + ` +
-            `${parseFloat(val[1].toFixed(FORMAT_NUM_SIG_DIGITS))}j`;
-        } else if (Object(util["isString"])(val)) {
-          valStr = `'${val}'`;
-        } else if (dtype === "bool") {
-          valStr = boolNumToString(val);
-        } else {
-          valStr = parseFloat(val.toFixed(FORMAT_NUM_SIG_DIGITS)).toString();
-        }
-        return Object(util["rightPad"])(valStr, pad);
-      }
-      function boolNumToString(v) {
-        return v === 0 ? "false" : "true";
-      }
-      function subTensorToString(vals, shape, dtype, strides, padPerCol, isLast = true) {
-        const storagePerElement = dtype === "complex64" ? 2 : 1;
-        const size = shape[0];
-        const rank = shape.length;
-        if (rank === 0) {
-          if (dtype === "complex64") {
-            const complexTuple = createComplexTuples(vals);
-            return [valToString(complexTuple[0], 0, dtype)];
-          }
-          if (dtype === "bool") {
-            return [boolNumToString(vals[0])];
-          }
-          return [vals[0].toString()];
-        }
-        if (rank === 1) {
-          if (size > FORMAT_LIMIT_NUM_VALS) {
-            const firstValsSize = FORMAT_NUM_FIRST_LAST_VALS * storagePerElement;
-            let firstVals = Array.from(vals.slice(0, firstValsSize));
-            let lastVals = Array.from(
-              vals.slice(
-                (size - FORMAT_NUM_FIRST_LAST_VALS) * storagePerElement,
-                size * storagePerElement
-              )
-            );
-            if (dtype === "complex64") {
-              firstVals = createComplexTuples(firstVals);
-              lastVals = createComplexTuples(lastVals);
-            }
-            return [
-              "[" +
-                firstVals.map((x, i) => valToString(x, padPerCol[i], dtype)).join(", ") +
-                ", ..., " +
-                lastVals
-                  .map((x, i) =>
-                    valToString(x, padPerCol[size - FORMAT_NUM_FIRST_LAST_VALS + i], dtype)
-                  )
-                  .join(", ") +
-                "]",
-            ];
-          }
-          const displayVals = dtype === "complex64" ? createComplexTuples(vals) : Array.from(vals);
-          return [
-            "[" + displayVals.map((x, i) => valToString(x, padPerCol[i], dtype)).join(", ") + "]",
-          ];
-        }
-        // The array is rank 2 or more.
-        const subshape = shape.slice(1);
-        const substrides = strides.slice(1);
-        const stride = strides[0] * storagePerElement;
-        const lines = [];
-        if (size > FORMAT_LIMIT_NUM_VALS) {
-          for (let i = 0; i < FORMAT_NUM_FIRST_LAST_VALS; i++) {
-            const start = i * stride;
-            const end = start + stride;
-            lines.push(
-              ...subTensorToString(
-                vals.slice(start, end),
-                subshape,
-                dtype,
-                substrides,
-                padPerCol,
-                false /* isLast */
-              )
-            );
-          }
-          lines.push("...");
-          for (let i = size - FORMAT_NUM_FIRST_LAST_VALS; i < size; i++) {
-            const start = i * stride;
-            const end = start + stride;
-            lines.push(
-              ...subTensorToString(
-                vals.slice(start, end),
-                subshape,
-                dtype,
-                substrides,
-                padPerCol,
-                i === size - 1 /* isLast */
-              )
-            );
-          }
-        } else {
-          for (let i = 0; i < size; i++) {
-            const start = i * stride;
-            const end = start + stride;
-            lines.push(
-              ...subTensorToString(
-                vals.slice(start, end),
-                subshape,
-                dtype,
-                substrides,
-                padPerCol,
-                i === size - 1 /* isLast */
-              )
-            );
-          }
-        }
-        const sep = rank === 2 ? "," : "";
-        lines[0] = "[" + lines[0] + sep;
-        for (let i = 1; i < lines.length - 1; i++) {
-          lines[i] = " " + lines[i] + sep;
-        }
-        let newLineSep = ",\n";
-        for (let i = 2; i < rank; i++) {
-          newLineSep += "\n";
-        }
-        lines[lines.length - 1] = " " + lines[lines.length - 1] + "]" + (isLast ? "" : newLineSep);
-        return lines;
-      }
-      function createComplexTuples(vals) {
-        const complexTuples = [];
-        for (let i = 0; i < vals.length; i += 2) {
-          complexTuples.push([vals[i], vals[i + 1]]);
-        }
-        return complexTuples;
-      }
-      //# sourceMappingURL=tensor_format.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * A mutable object, similar to `tf.Tensor`, that allows users to set values
-       * at locations before converting to an immutable `tf.Tensor`.
-       *
-       * See `tf.buffer` for creating a tensor buffer.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-      class tensor_TensorBuffer {
-        constructor(shape, dtype, values) {
-          this.dtype = dtype;
-          this.shape = shape.slice();
-          this.size = util["sizeFromShape"](shape);
-          if (values != null) {
-            const n = values.length;
-            util["assert"](
-              n === this.size,
-              () =>
-                `Length of values '${n}' does not match the size ` +
-                `inferred by the shape '${this.size}'.`
-            );
-          }
-          if (dtype === "complex64") {
-            throw new Error(
-              `complex64 dtype TensorBuffers are not supported. Please create ` +
-                `a TensorBuffer for the real and imaginary parts separately and ` +
-                `call tf.complex(real, imag).`
-            );
-          }
-          this.values = values || util["getArrayFromDType"](dtype, this.size);
-          this.strides = Object(util["computeStrides"])(shape);
-        }
-        /**
-         * Sets a value in the buffer at a given location.
-         *
-         * @param value The value to set.
-         * @param locs  The location indices.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-        set(value, ...locs) {
-          if (locs.length === 0) {
-            locs = [0];
-          }
-          util["assert"](
-            locs.length === this.rank,
-            () =>
-              `The number of provided coordinates (${locs.length}) must ` +
-              `match the rank (${this.rank})`
-          );
-          const index = this.locToIndex(locs);
-          this.values[index] = value;
-        }
-        /**
-         * Returns the value in the buffer at the provided location.
-         *
-         * @param locs The location indices.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-        get(...locs) {
-          if (locs.length === 0) {
-            locs = [0];
-          }
-          let i = 0;
-          for (const loc of locs) {
-            if (loc < 0 || loc >= this.shape[i]) {
-              const msg =
-                `Requested out of range element at ${locs}. ` + `  Buffer shape=${this.shape}`;
-              throw new Error(msg);
-            }
-            i++;
-          }
-          let index = locs[locs.length - 1];
-          for (let i = 0; i < locs.length - 1; ++i) {
-            index += this.strides[i] * locs[i];
-          }
-          return this.values[index];
-        }
-        locToIndex(locs) {
-          if (this.rank === 0) {
-            return 0;
-          } else if (this.rank === 1) {
-            return locs[0];
-          }
-          let index = locs[locs.length - 1];
-          for (let i = 0; i < locs.length - 1; ++i) {
-            index += this.strides[i] * locs[i];
-          }
-          return index;
-        }
-        indexToLoc(index) {
-          if (this.rank === 0) {
-            return [];
-          } else if (this.rank === 1) {
-            return [index];
-          }
-          const locs = new Array(this.shape.length);
-          for (let i = 0; i < locs.length - 1; ++i) {
-            locs[i] = Math.floor(index / this.strides[i]);
-            index -= locs[i] * this.strides[i];
-          }
-          locs[locs.length - 1] = index;
-          return locs;
-        }
-        get rank() {
-          return this.shape.length;
-        }
-        /**
-         * Creates an immutable `tf.Tensor` object from the buffer.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-        toTensor() {
-          return trackerFn().makeTensor(this.values, this.shape, this.dtype);
-        }
-      }
-      // For tracking tensor creation and disposal.
-      let trackerFn = null;
-      // Used by chaining methods to call into ops.
-      let opHandler = null;
-      // Used to warn about deprecated methods.
-      let deprecationWarningFn = null;
-      // This here so that we can use this method on dev branches and keep the
-      // functionality at master.
-      // tslint:disable-next-line:no-unused-expression
-      [deprecationWarningFn];
-      /**
-       * An external consumer can register itself as the tensor tracker. This way
-       * the Tensor class can notify the tracker for every tensor created and
-       * disposed.
-       */
-      function setTensorTracker(fn) {
-        trackerFn = fn;
-      }
-      /**
-       * An external consumer can register itself as the op handler. This way the
-       * Tensor class can have chaining methods that call into ops via the op
-       * handler.
-       */
-      function setOpHandler(handler) {
-        opHandler = handler;
-      }
-      /**
-       * Sets the deprecation warning function to be used by this file. This way the
-       * Tensor class can be a leaf but still use the environment.
-       */
-      function setDeprecationWarningFn(fn) {
-        deprecationWarningFn = fn;
-      }
-      /**
-       * A `tf.Tensor` object represents an immutable, multidimensional array of
-       * numbers that has a shape and a data type.
-       *
-       * See `tf.tensor` for details on how to create a `tf.Tensor`.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-      class tensor_Tensor {
-        constructor(shape, dtype, dataId, id) {
-          /** Whether this tensor has been globally kept. */
-          this.kept = false;
-          this.isDisposedInternal = false;
-          this.shape = shape.slice();
-          this.dtype = dtype || "float32";
-          this.size = util["sizeFromShape"](shape);
-          this.strides = Object(util["computeStrides"])(shape);
-          this.dataId = dataId;
-          this.id = id;
-          this.rankType = this.rank < 5 ? this.rank.toString() : "higher";
-        }
-        /** Flatten a Tensor to a 1D array. */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        flatten() {
-          this.throwIfDisposed();
-          return this.as1D();
-        }
-        /** Converts a size-1 `tf.Tensor` to a `tf.Scalar`. */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        asScalar() {
-          this.throwIfDisposed();
-          util["assert"](this.size === 1, () => "The array must have only 1 element.");
-          return this.reshape([]);
-        }
-        /** Converts a `tf.Tensor` to a `tf.Tensor1D`. */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        as1D() {
-          this.throwIfDisposed();
-          return this.reshape([this.size]);
-        }
-        /**
-         * Converts a `tf.Tensor` to a `tf.Tensor2D`.
-         *
-         * @param rows Number of rows in `tf.Tensor2D`.
-         * @param columns Number of columns in `tf.Tensor2D`.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        as2D(rows, columns) {
-          this.throwIfDisposed();
-          return this.reshape([rows, columns]);
-        }
-        /**
-         * Converts a `tf.Tensor` to a `tf.Tensor3D`.
-         *
-         * @param rows Number of rows in `tf.Tensor3D`.
-         * @param columns Number of columns in `tf.Tensor3D`.
-         * @param depth Depth of `tf.Tensor3D`.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        as3D(rows, columns, depth) {
-          this.throwIfDisposed();
-          return this.reshape([rows, columns, depth]);
-        }
-        /**
-         * Converts a `tf.Tensor` to a `tf.Tensor4D`.
-         *
-         * @param rows Number of rows in `tf.Tensor4D`.
-         * @param columns Number of columns in `tf.Tensor4D`.
-         * @param depth Depth of `tf.Tensor4D`.
-         * @param depth2 4th dimension of `tf.Tensor4D`.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        as4D(rows, columns, depth, depth2) {
-          this.throwIfDisposed();
-          return this.reshape([rows, columns, depth, depth2]);
-        }
-        /**
-         * Converts a `tf.Tensor` to a `tf.Tensor5D`.
-         *
-         * @param rows Number of rows in `tf.Tensor5D`.
-         * @param columns Number of columns in `tf.Tensor5D`.
-         * @param depth Depth of `tf.Tensor5D`.
-         * @param depth2 4th dimension of `tf.Tensor5D`.
-         * @param depth3 5th dimension of 'tf.Tensor5D'
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        as5D(rows, columns, depth, depth2, depth3) {
-          this.throwIfDisposed();
-          return this.reshape([rows, columns, depth, depth2, depth3]);
-        }
-        /**
-         * Casts a `tf.Tensor` to a specified dtype.
-         *
-         * @param dtype Data-type to cast the tensor to.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        asType(dtype) {
-          this.throwIfDisposed();
-          return opHandler.cast(this, dtype);
-        }
-        get rank() {
-          return this.shape.length;
-        }
-        /**
-         * Returns a promise of `tf.TensorBuffer` that holds the underlying data.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        async buffer() {
-          const vals = await this.data();
-          return opHandler.buffer(this.shape, this.dtype, vals);
-        }
-        /** Returns a `tf.TensorBuffer` that holds the underlying data. */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        bufferSync() {
-          return opHandler.buffer(this.shape, this.dtype, this.dataSync());
-        }
-        /**
-         * Returns the tensor data as a nested array. The transfer of data is done
-         * asynchronously.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        async array() {
-          const vals = await this.data();
-          return Object(util["toNestedArray"])(this.shape, vals);
-        }
-        /**
-         * Returns the tensor data as a nested array. The transfer of data is done
-         * synchronously.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        arraySync() {
-          return Object(util["toNestedArray"])(this.shape, this.dataSync());
-        }
-        /**
-         * Asynchronously downloads the values from the `tf.Tensor`. Returns a
-         * promise of `TypedArray` that resolves when the computation has finished.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        async data() {
-          this.throwIfDisposed();
-          const data = trackerFn().read(this.dataId);
-          if (this.dtype === "string") {
-            const bytes = await data;
-            try {
-              return bytes.map((b) => util["decodeString"](b));
-            } catch (_a) {
-              throw new Error(
-                "Failed to decode the string bytes into utf-8. " +
-                  "To get the original bytes, call tensor.bytes()."
-              );
-            }
-          }
-          return data;
-        }
-        /**
-         * Synchronously downloads the values from the `tf.Tensor`. This blocks the
-         * UI thread until the values are ready, which can cause performance issues.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        dataSync() {
-          this.throwIfDisposed();
-          const data = trackerFn().readSync(this.dataId);
-          if (this.dtype === "string") {
-            try {
-              return data.map((b) => util["decodeString"](b));
-            } catch (_a) {
-              throw new Error(
-                "Failed to decode the string bytes into utf-8. " +
-                  "To get the original bytes, call tensor.bytes()."
-              );
-            }
-          }
-          return data;
-        }
-        /** Returns the underlying bytes of the tensor's data. */
-        async bytes() {
-          this.throwIfDisposed();
-          const data = await trackerFn().read(this.dataId);
-          if (this.dtype === "string") {
-            return data;
-          } else {
-            return new Uint8Array(data.buffer);
-          }
-        }
-        /**
-         * Disposes `tf.Tensor` from memory.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        dispose() {
-          if (this.isDisposed) {
-            return;
-          }
-          trackerFn().disposeTensor(this);
-          this.isDisposedInternal = true;
-        }
-        get isDisposed() {
-          return this.isDisposedInternal;
-        }
-        throwIfDisposed() {
-          if (this.isDisposed) {
-            throw new Error(`Tensor is disposed.`);
-          }
-        }
-        /** Casts the array to type `float32` */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        toFloat() {
-          return this.asType("float32");
-        }
-        /** Casts the array to type `int32` */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        toInt() {
-          return this.asType("int32");
-        }
-        /** Casts the array to type `bool` */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        toBool() {
-          return this.asType("bool");
-        }
-        /**
-         * Prints the `tf.Tensor`. See `tf.print` for details.
-         *
-         * @param verbose Whether to print verbose information about the tensor,
-         *    including dtype and size.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        print(verbose = false) {
-          return opHandler.print(this, verbose);
-        }
-        /**
-         * Reshapes the tensor into the provided shape.
-         * See `tf.reshape` for more details.
-         *
-         * @param newShape An array of integers defining the output tensor shape.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        reshape(newShape) {
-          this.throwIfDisposed();
-          return opHandler.reshape(this, newShape);
-        }
-        /**
-         * Reshapes the tensor into the shape of the provided tensor.
-         *
-         * @param x The tensor of required shape.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        reshapeAs(x) {
-          this.throwIfDisposed();
-          return this.reshape(x.shape);
-        }
-        /**
-         * Returns a `tf.Tensor` that has expanded rank, by inserting a dimension
-         * into the tensor's shape. See `tf.expandDims` for details.
-         *
-         * @param axis The dimension index at which to insert shape of 1. Defaults to
-         *     0 (the first dimension).
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        expandDims(axis = 0) {
-          return opHandler.expandDims(this, axis);
-        }
-        /**
-         * Returns a `tf.Tensor` with dimensions of size 1 removed from the shape.
-         * See `tf.squeeze` for more details.
-         *
-         * @param axis A list of numbers. If specified, only squeezes the
-         *    dimensions listed. The dimension index starts at 0. It is an error to
-         *    squeeze a dimension that is not 1.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        squeeze(axis) {
-          this.throwIfDisposed();
-          return opHandler.squeeze(this, axis);
-        }
-        /** Returns a copy of the tensor. See `tf.clone` for details. */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        clone() {
-          this.throwIfDisposed();
-          return opHandler.clone(this);
-        }
-        /**
-         * Returns a human-readable description of the tensor. Useful for logging.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        toString(verbose = false) {
-          const vals = this.dataSync();
-          return tensorToString(vals, this.shape, this.dtype, verbose);
-        }
-        // Below is chain API that is not exposed to docs to avoid repetition. To
-        // expose a method, move it above this comment and add @doc and jsdoc.
-        gather(indices, axis = 0) {
-          this.throwIfDisposed();
-          return opHandler.gather(this, indices, axis);
-        }
-        norm(ord = "euclidean", axis = null, keepDims = false) {
-          this.throwIfDisposed();
-          return opHandler.norm(this, ord, axis, keepDims);
-        }
-        slice(begin, size) {
-          this.throwIfDisposed();
-          return opHandler.slice(this, begin, size);
-        }
-        reverse(axis) {
-          this.throwIfDisposed();
-          return opHandler.reverse(this, axis);
-        }
-        stack(x, axis = 0) {
-          return opHandler.stack([this, x], axis);
-        }
-        unstack(axis = 0) {
-          return opHandler.unstack(this, axis);
-        }
-        // Reduction ops.
-        all(axis = null, keepDims = false) {
-          this.throwIfDisposed();
-          return opHandler.all(this, axis, keepDims);
-        }
-        any(axis = null, keepDims = false) {
-          this.throwIfDisposed();
-          return opHandler.any(this, axis, keepDims);
-        }
-        logSumExp(axis = null, keepDims = false) {
-          this.throwIfDisposed();
-          return opHandler.logSumExp(this, axis, keepDims);
-        }
-        sum(axis = null, keepDims = false) {
-          this.throwIfDisposed();
-          return opHandler.sum(this, axis, keepDims);
-        }
-        prod(axis = null, keepDims = false) {
-          this.throwIfDisposed();
-          return opHandler.prod(this, axis, keepDims);
-        }
-        mean(axis = null, keepDims = false) {
-          this.throwIfDisposed();
-          return opHandler.mean(this, axis, keepDims);
-        }
-        min(axis = null, keepDims = false) {
-          this.throwIfDisposed();
-          return opHandler.min(this, axis, keepDims);
-        }
-        argMin(axis = null) {
-          this.throwIfDisposed();
-          return opHandler.argMin(this, axis);
-        }
-        argMax(axis = null) {
-          this.throwIfDisposed();
-          return opHandler.argMax(this, axis);
-        }
-        // Transformations
-        cast(dtype) {
-          this.throwIfDisposed();
-          return opHandler.cast(this, dtype);
-        }
-        // Binary ops.
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        addStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.addStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        subStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.subStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        powStrict(exp) {
-          this.throwIfDisposed();
-          return opHandler.powStrict(this, exp);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        mulStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.mulStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        divStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.divStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        minimumStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.minimumStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        maximumStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.maximumStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        modStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.modStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        squaredDifferenceStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.squaredDifferenceStrict(this, x);
-        }
-        // Compare ops.
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        notEqualStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.notEqualStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        lessStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.lessStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        equalStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.equalStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        lessEqualStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.lessEqualStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        greaterStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.greaterStrict(this, x);
-        }
-        /**
-         * @deprecated strict variants of ops have been deprecated
-         */
-        greaterEqualStrict(x) {
-          this.throwIfDisposed();
-          return opHandler.greaterEqualStrict(this, x);
-        }
-        // Compare ops.
-        logicalAnd(x) {
-          this.throwIfDisposed();
-          return opHandler.logicalAnd(this, x);
-        }
-        logicalOr(x) {
-          this.throwIfDisposed();
-          return opHandler.logicalOr(this, x);
-        }
-        logicalNot() {
-          this.throwIfDisposed();
-          return opHandler.logicalNot(this);
-        }
-        logicalXor(x) {
-          this.throwIfDisposed();
-          return opHandler.logicalXor(this, x);
-        }
-        where(condition, x) {
-          this.throwIfDisposed();
-          return opHandler.where(condition, this, x);
-        }
-        // Unary ops.
-        neg() {
-          this.throwIfDisposed();
-          return opHandler.neg(this);
-        }
-        ceil() {
-          this.throwIfDisposed();
-          return opHandler.ceil(this);
-        }
-        floor() {
-          this.throwIfDisposed();
-          return opHandler.floor(this);
-        }
-        sign() {
-          this.throwIfDisposed();
-          return opHandler.sign(this);
-        }
-        isNaN() {
-          this.throwIfDisposed();
-          return opHandler.isNaN(this);
-        }
-        isInf() {
-          this.throwIfDisposed();
-          return opHandler.isInf(this);
-        }
-        isFinite() {
-          this.throwIfDisposed();
-          return opHandler.isFinite(this);
-        }
-        exp() {
-          this.throwIfDisposed();
-          return opHandler.exp(this);
-        }
-        expm1() {
-          this.throwIfDisposed();
-          return opHandler.expm1(this);
-        }
-        log() {
-          this.throwIfDisposed();
-          return opHandler.log(this);
-        }
-        log1p() {
-          this.throwIfDisposed();
-          return opHandler.log1p(this);
-        }
-        sqrt() {
-          this.throwIfDisposed();
-          return opHandler.sqrt(this);
-        }
-        rsqrt() {
-          this.throwIfDisposed();
-          return opHandler.rsqrt(this);
-        }
-        square() {
-          this.throwIfDisposed();
-          return opHandler.square(this);
-        }
-        reciprocal() {
-          this.throwIfDisposed();
-          return opHandler.reciprocal(this);
-        }
-        abs() {
-          this.throwIfDisposed();
-          return opHandler.abs(this);
-        }
-        clipByValue(min, max) {
-          this.throwIfDisposed();
-          return opHandler.clipByValue(this, min, max);
-        }
-        sigmoid() {
-          this.throwIfDisposed();
-          return opHandler.sigmoid(this);
-        }
-        logSigmoid() {
-          this.throwIfDisposed();
-          return opHandler.logSigmoid(this);
-        }
-        softplus() {
-          this.throwIfDisposed();
-          return opHandler.softplus(this);
-        }
-        zerosLike() {
-          this.throwIfDisposed();
-          return opHandler.zerosLike(this);
-        }
-        onesLike() {
-          this.throwIfDisposed();
-          return opHandler.onesLike(this);
-        }
-        sin() {
-          this.throwIfDisposed();
-          return opHandler.sin(this);
-        }
-        cos() {
-          this.throwIfDisposed();
-          return opHandler.cos(this);
-        }
-        tan() {
-          this.throwIfDisposed();
-          return opHandler.tan(this);
-        }
-        asin() {
-          this.throwIfDisposed();
-          return opHandler.asin(this);
-        }
-        acos() {
-          this.throwIfDisposed();
-          return opHandler.acos(this);
-        }
-        atan() {
-          this.throwIfDisposed();
-          return opHandler.atan(this);
-        }
-        sinh() {
-          this.throwIfDisposed();
-          return opHandler.sinh(this);
-        }
-        cosh() {
-          this.throwIfDisposed();
-          return opHandler.cosh(this);
-        }
-        tanh() {
-          this.throwIfDisposed();
-          return opHandler.tanh(this);
-        }
-        asinh() {
-          this.throwIfDisposed();
-          return opHandler.asinh(this);
-        }
-        acosh() {
-          this.throwIfDisposed();
-          return opHandler.acosh(this);
-        }
-        atanh() {
-          this.throwIfDisposed();
-          return opHandler.atanh(this);
-        }
-        erf() {
-          this.throwIfDisposed();
-          return opHandler.erf(this);
-        }
-        round() {
-          this.throwIfDisposed();
-          return opHandler.round(this);
-        }
-        step(alpha = 0.0) {
-          this.throwIfDisposed();
-          return opHandler.step(this, alpha);
-        }
-        softmax(dim = -1) {
-          this.throwIfDisposed();
-          return opHandler.softmax(this, dim);
-        }
-        logSoftmax(axis = -1) {
-          this.throwIfDisposed();
-          return opHandler.logSoftmax(this, axis);
-        }
-        // Image ops.
-        resizeBilinear(newShape2D, alignCorners = false) {
-          this.throwIfDisposed();
-          return opHandler.image.resizeBilinear(this, newShape2D, alignCorners);
-        }
-        resizeNearestNeighbor(newShape2D, alignCorners = false) {
-          this.throwIfDisposed();
-          return opHandler.image.resizeNearestNeighbor(this, newShape2D, alignCorners);
-        }
-        // Pooling.
-        variable(trainable = true, name, dtype) {
-          this.throwIfDisposed();
-          return trackerFn().makeVariable(this, trainable, name, dtype);
-        }
-        unsortedSegmentSum(segmentIds, numSegments) {
-          this.throwIfDisposed();
-          return opHandler.unsortedSegmentSum(this, segmentIds, numSegments);
-        }
-        topk(k = 1, sorted = true) {
-          this.throwIfDisposed();
-          return opHandler.topk(this, k, sorted);
-        }
-        stridedSlice(
-          begin,
-          end,
-          strides,
-          beginMask = 0,
-          endMask = 0,
-          ellipsisMask = 0,
-          newAxisMask = 0,
-          shrinkAxisMask = 0
-        ) {
-          this.throwIfDisposed();
-          return opHandler.stridedSlice(
-            this,
-            begin,
-            end,
-            strides,
-            beginMask,
-            endMask,
-            ellipsisMask,
-            newAxisMask,
-            shrinkAxisMask
-          );
-        }
-        fft() {
-          this.throwIfDisposed();
-          return opHandler.spectral.fft(this);
-        }
-        ifft() {
-          this.throwIfDisposed();
-          return opHandler.spectral.ifft(this);
-        }
-        rfft() {
-          this.throwIfDisposed();
-          return opHandler.spectral.rfft(this);
-        }
-        irfft() {
-          this.throwIfDisposed();
-          return opHandler.spectral.irfft(this);
-        }
-      }
-      Object.defineProperty(tensor_Tensor, Symbol.hasInstance, {
-        value: (instance) => {
-          return (
-            !!instance &&
-            instance.dataId != null &&
-            instance.shape != null &&
-            instance.dtype != null
-          );
-        },
-      });
-      /**
-       * A mutable `tf.Tensor`, useful for persisting state, e.g. for training.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-      class tensor_Variable extends tensor_Tensor {
-        constructor(initialValue, trainable, name, tensorId) {
-          super(initialValue.shape, initialValue.dtype, initialValue.dataId, tensorId);
-          this.trainable = trainable;
-          this.name = name;
-        }
-        /**
-         * Assign a new `tf.Tensor` to this variable. The new `tf.Tensor` must have
-         * the same shape and dtype as the old `tf.Tensor`.
-         *
-         * @param newValue New tensor to be assigned to this variable.
-         */
-        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
-        assign(newValue) {
-          if (newValue.dtype !== this.dtype) {
-            throw new Error(
-              `dtype of the new value (${newValue.dtype}) and ` +
-                `previous value (${this.dtype}) must match`
-            );
-          }
-          if (!util["arraysEqual"](newValue.shape, this.shape)) {
-            throw new Error(
-              `shape of the new value (${newValue.shape}) and ` +
-                `previous value (${this.shape}) must match`
-            );
-          }
-          trackerFn().disposeTensor(this);
-          this.dataId = newValue.dataId;
-          trackerFn().incRef(this, null /* backend */);
-        }
-        dispose() {
-          trackerFn().disposeVariable(this);
-          this.isDisposedInternal = true;
-        }
-      }
-      Object.defineProperty(tensor_Variable, Symbol.hasInstance, {
-        value: (instance) => {
-          return (
-            instance instanceof tensor_Tensor &&
-            instance.assign != null &&
-            instance.assign instanceof Function
-          );
-        },
-      });
-      //# sourceMappingURL=tensor.js.map
-
-      /***/
-    },
-    /* 8 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return linspace;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return ones;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
-        return range;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
-        return scalar;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
-        return tensor;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
-        return tensor1d;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "h", function () {
-        return tensor2d;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "i", function () {
-        return tensor3d;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "j", function () {
-        return tensor4d;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "k", function () {
-        return tensor5d;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "l", function () {
-        return tensor6d;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "m", function () {
-        return variable;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "n", function () {
-        return zeros;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return onesLike;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "o", function () {
-        return zerosLike;
-      });
-      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
-      /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(10);
-      /* harmony import */ var _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__ =
-        __webpack_require__(3);
-      /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(1);
-      /* harmony import */ var _complex__WEBPACK_IMPORTED_MODULE_4__ = __webpack_require__(18);
-      /* harmony import */ var _imag__WEBPACK_IMPORTED_MODULE_5__ = __webpack_require__(25);
-      /* harmony import */ var _operation__WEBPACK_IMPORTED_MODULE_6__ = __webpack_require__(4);
-      /* harmony import */ var _real__WEBPACK_IMPORTED_MODULE_7__ = __webpack_require__(22);
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Creates a `tf.Tensor` with the provided values, shape and dtype.
-       *
-       * ```js
-       * // Pass an array of values to create a vector.
-       * tf.tensor([1, 2, 3, 4]).print();
-       * ```
-       *
-       * ```js
-       * // Pass a nested array of values to make a matrix or a higher
-       * // dimensional tensor.
-       * tf.tensor([[1, 2], [3, 4]]).print();
-       * ```
-       *
-       * ```js
-       * // Pass a flat array and specify a shape yourself.
-       * tf.tensor([1, 2, 3, 4], [2, 2]).print();
-       * ```
-       *
-       * @param values The values of the tensor. Can be nested array of numbers,
-       *     or a flat array, or a `TypedArray`. If the values are strings,
-       *     they will be encoded as utf-8 and kept as `Uint8Array[]`.
-       * @param shape The shape of the tensor. Optional. If not provided,
-       *   it is inferred from `values`.
-       * @param dtype The data type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function tensor(values, shape, dtype) {
-        const inferredShape = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
-        )(values, dtype);
-        return makeTensor(values, shape, inferredShape, dtype);
-      }
-      /** This is shared code across all tensor creation methods. */
-      function makeTensor(values, shape, inferredShape, dtype) {
-        if (dtype == null) {
-          dtype = Object(_util__WEBPACK_IMPORTED_MODULE_3__["inferDtype"])(values);
-        }
-        if (dtype === "complex64") {
-          throw new Error(
-            `Cannot construct a complex64 tensor directly. ` + `Please use tf.complex(real, imag).`
-          );
-        }
-        if (
-          !Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(values) &&
-          !Array.isArray(values) &&
-          typeof values !== "number" &&
-          typeof values !== "boolean" &&
-          typeof values !== "string"
-        ) {
-          throw new Error(
-            "values passed to tensor(values) must be a number/boolean/string or " +
-              "an array of numbers/booleans/strings, or a TypedArray"
-          );
-        }
-        if (shape != null) {
-          Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNegativeIntegerDimensions"])(shape);
-          const providedSize = Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(shape);
-          const inferredSize = Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(
-            inferredShape
-          );
-          Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
-            providedSize === inferredSize,
-            () =>
-              `Based on the provided shape, [${shape}], the tensor should have ` +
-              `${providedSize} values but has ${inferredSize}`
-          );
-          for (let i = 0; i < inferredShape.length; ++i) {
-            const inferred = inferredShape[i];
-            const flatDimsDontMatch =
-              i === inferredShape.length - 1
-                ? inferred !==
-                  Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(shape.slice(i))
-                : true;
-            Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
-              inferredShape[i] === shape[i] || !flatDimsDontMatch,
-              () =>
-                `Error creating a new Tensor. Inferred shape ` +
-                `(${inferredShape}) does not match the provided ` +
-                `shape (${shape}). `
-            );
-          }
-        }
-        if (
-          !Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(values) &&
-          !Array.isArray(values)
-        ) {
-          values = [values];
-        }
-        shape = shape || inferredShape;
-        values =
-          dtype !== "string"
-            ? Object(_util__WEBPACK_IMPORTED_MODULE_3__["toTypedArray"])(
-                values,
-                dtype,
-                Object(_environment__WEBPACK_IMPORTED_MODULE_1__[/* env */ "c"])().getBool("DEBUG")
-              )
-            : Object(_util__WEBPACK_IMPORTED_MODULE_3__["flatten"])(values, [], true);
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeTensor(
-          values,
-          shape,
-          dtype
-        );
-      }
-      /**
-       * Creates rank-0 `tf.Tensor` (scalar) with the provided value and dtype.
-       *
-       * The same functionality can be achieved with `tf.tensor`, but in general
-       * we recommend using `tf.scalar` as it makes the code more readable.
-       *
-       * ```js
-       * tf.scalar(3.14).print();
-       * ```
-       *
-       * @param value The value of the scalar.
-       * @param dtype The data type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function scalar(value, dtype) {
-        if (
-          ((Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(value) &&
-            dtype !== "string") ||
-            Array.isArray(value)) &&
-          dtype !== "complex64"
-        ) {
-          throw new Error(
-            "Error creating a new Scalar: value must be a primitive " + "(number|boolean|string)"
-          );
-        }
-        if (
-          dtype === "string" &&
-          Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(value) &&
-          !(value instanceof Uint8Array)
-        ) {
-          throw new Error(
-            "When making a scalar from encoded string, " + "the value must be `Uint8Array`."
-          );
-        }
-        const shape = [];
-        const inferredShape = [];
-        return makeTensor(value, shape, inferredShape, dtype);
-      }
-      /**
-       * Creates rank-1 `tf.Tensor` with the provided values, shape and dtype.
-       *
-       * The same functionality can be achieved with `tf.tensor`, but in general
-       * we recommend using `tf.tensor1d` as it makes the code more readable.
-       *
-       * ```js
-       * tf.tensor1d([1, 2, 3]).print();
-       * ```
-       *
-       * @param values The values of the tensor. Can be array of numbers,
-       *     or a `TypedArray`.
-       * @param dtype The data type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function tensor1d(values, dtype) {
-        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
-        const inferredShape = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
-        )(values, dtype);
-        if (inferredShape.length !== 1) {
-          throw new Error("tensor1d() requires values to be a flat/TypedArray");
-        }
-        const shape = null;
-        return makeTensor(values, shape, inferredShape, dtype);
-      }
-      /**
-       * Creates rank-2 `tf.Tensor` with the provided values, shape and dtype.
-       *
-       * The same functionality can be achieved with `tf.tensor`, but in general
-       * we recommend using `tf.tensor2d` as it makes the code more readable.
-       *
-       *  ```js
-       * // Pass a nested array.
-       * tf.tensor2d([[1, 2], [3, 4]]).print();
-       * ```
-       * ```js
-       * // Pass a flat array and specify a shape.
-       * tf.tensor2d([1, 2, 3, 4], [2, 2]).print();
-       * ```
-       *
-       * @param values The values of the tensor. Can be nested array of numbers,
-       *     or a flat array, or a `TypedArray`.
-       * @param shape The shape of the tensor. If not provided, it is inferred from
-       *     `values`.
-       * @param dtype The data type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function tensor2d(values, shape, dtype) {
-        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
-        if (shape != null && shape.length !== 2) {
-          throw new Error("tensor2d() requires shape to have two numbers");
-        }
-        const inferredShape = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
-        )(values, dtype);
-        if (inferredShape.length !== 2 && inferredShape.length !== 1) {
-          throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");
-        }
-        if (inferredShape.length === 1 && shape == null) {
-          throw new Error(
-            "tensor2d() requires shape to be provided when `values` " + "are a flat/TypedArray"
-          );
-        }
-        return makeTensor(values, shape, inferredShape, dtype);
-      }
-      /**
-       * Creates rank-3 `tf.Tensor` with the provided values, shape and dtype.
-       *
-       * The same functionality can be achieved with `tf.tensor`, but in general
-       * we recommend using `tf.tensor3d` as it makes the code more readable.
-       *
-       *  ```js
-       * // Pass a nested array.
-       * tf.tensor3d([[[1], [2]], [[3], [4]]]).print();
-       * ```
-       * ```js
-       * // Pass a flat array and specify a shape.
-       * tf.tensor3d([1, 2, 3, 4], [2, 2, 1]).print();
-       * ```
-       *
-       * @param values The values of the tensor. Can be nested array of numbers,
-       *     or a flat array, or a `TypedArray`.
-       * @param shape The shape of the tensor. If not provided,  it is inferred from
-       *     `values`.
-       * @param dtype The data type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function tensor3d(values, shape, dtype) {
-        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
-        if (shape != null && shape.length !== 3) {
-          throw new Error("tensor3d() requires shape to have three numbers");
-        }
-        const inferredShape = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
-        )(values, dtype);
-        if (inferredShape.length !== 3 && inferredShape.length !== 1) {
-          throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");
-        }
-        if (inferredShape.length === 1 && shape == null) {
-          throw new Error(
-            "tensor3d() requires shape to be provided when `values` " + "are a flat array"
-          );
-        }
-        return makeTensor(values, shape, inferredShape, dtype);
-      }
-      /**
-       * Creates rank-4 `tf.Tensor` with the provided values, shape and dtype.
-       *
-       * The same functionality can be achieved with `tf.tensor`, but in general
-       * we recommend using `tf.tensor4d` as it makes the code more readable.
-       *
-       *  ```js
-       * // Pass a nested array.
-       * tf.tensor4d([[[[1], [2]], [[3], [4]]]]).print();
-       * ```
-       * ```js
-       * // Pass a flat array and specify a shape.
-       * tf.tensor4d([1, 2, 3, 4], [1, 2, 2, 1]).print();
-       * ```
-       *
-       * @param values The values of the tensor. Can be nested array of numbers,
-       *     or a flat array, or a `TypedArray`.
-       * @param shape The shape of the tensor. Optional. If not provided,
-       *   it is inferred from `values`.
-       * @param dtype The data type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function tensor4d(values, shape, dtype) {
-        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
-        if (shape != null && shape.length !== 4) {
-          throw new Error("tensor4d() requires shape to have four numbers");
-        }
-        const inferredShape = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
-        )(values, dtype);
-        if (inferredShape.length !== 4 && inferredShape.length !== 1) {
-          throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");
-        }
-        if (inferredShape.length === 1 && shape == null) {
-          throw new Error(
-            "tensor4d() requires shape to be provided when `values` " + "are a flat array"
-          );
-        }
-        return makeTensor(values, shape, inferredShape, dtype);
-      }
-      /**
-       * Creates rank-5 `tf.Tensor` with the provided values, shape and dtype.
-       *
-       * The same functionality can be achieved with `tf.tensor`, but in general
-       * we recommend using `tf.tensor5d` as it makes the code more readable.
-       *
-       *  ```js
-       * // Pass a nested array.
-       * tf.tensor5d([[[[[1], [2]], [[3], [4]]]]]).print();
-       * ```
-       * ```js
-       * // Pass a flat array and specify a shape.
-       * tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]).print();
-       * ```
-       *
-       * @param values The values of the tensor. Can be nested array of numbers,
-       *     or a flat array, or a `TypedArray`.
-       * @param shape The shape of the tensor. Optional. If not provided,
-       *   it is inferred from `values`.
-       * @param dtype The data type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function tensor5d(values, shape, dtype) {
-        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
-        if (shape != null && shape.length !== 5) {
-          throw new Error("tensor5d() requires shape to have five numbers");
-        }
-        const inferredShape = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
-        )(values, dtype);
-        if (inferredShape.length !== 5 && inferredShape.length !== 1) {
-          throw new Error(
-            "tensor5d() requires values to be " + "number[][][][][] or flat/TypedArray"
-          );
-        }
-        if (inferredShape.length === 1 && shape == null) {
-          throw new Error(
-            "tensor5d() requires shape to be provided when `values` " + "are a flat array"
-          );
-        }
-        return makeTensor(values, shape, inferredShape, dtype);
-      }
-      /**
-       * Creates rank-6 `tf.Tensor` with the provided values, shape and dtype.
-       *
-       * The same functionality can be achieved with `tf.tensor`, but in general
-       * we recommend using `tf.tensor6d` as it makes the code more readable.
-       *
-       *  ```js
-       * // Pass a nested array.
-       * tf.tensor6d([[[[[[1],[2]],[[3],[4]]],[[[5],[6]],[[7],[8]]]]]]).print();
-       * ```
-       * ```js
-       * // Pass a flat array and specify a shape.
-       * tf.tensor6d([1, 2, 3, 4, 5, 6, 7, 8], [1, 1, 2, 2, 2, 1]).print();
-       * ```
-       *
-       * @param values The values of the tensor. Can be nested array of numbers,
-       *     or a flat array, or a `TypedArray`.
-       * @param shape The shape of the tensor. Optional. If not provided,
-       *   it is inferred from `values`.
-       * @param dtype The data type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function tensor6d(values, shape, dtype) {
-        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
-        if (shape != null && shape.length !== 6) {
-          throw new Error("tensor6d() requires shape to have six numbers");
-        }
-        const inferredShape = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
-        )(values, dtype);
-        if (inferredShape.length !== 6 && inferredShape.length !== 1) {
-          throw new Error(
-            "tensor6d() requires values to be number[][][][][][] or " + "flat/TypedArray"
-          );
-        }
-        if (inferredShape.length === 1 && shape == null) {
-          throw new Error(
-            "tensor6d() requires shape to be provided when `values` " + "are a flat array"
-          );
-        }
-        shape = shape || inferredShape;
-        return makeTensor(values, shape, inferredShape, dtype);
-      }
-      /**
-       * Creates a new variable with the provided initial value.
-       * ```js
-       * const x = tf.variable(tf.tensor([1, 2, 3]));
-       * x.assign(tf.tensor([4, 5, 6]));
-       *
-       * x.print();
-       * ```
-       *
-       * @param initialValue Initial value for the tensor.
-       * @param trainable If true, optimizers are allowed to update it.
-       * @param name Name of the variable. Defaults to a unique id.
-       * @param dtype If set, initialValue will be converted to the given type.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function variable(initialValue, trainable = true, name, dtype) {
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeVariable(
-          initialValue,
-          trainable,
-          name,
-          dtype
-        );
-      }
-      /**
-       * Creates a `tf.Tensor` with all elements set to 1.
-       *
-       * ```js
-       * tf.ones([2, 2]).print();
-       * ```
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param dtype The type of an element in the resulting tensor. Defaults to
-       *     'float'.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function ones(shape, dtype = "float32") {
-        if (dtype === "complex64") {
-          const real = ones(shape, "float32");
-          const imag = zeros(shape, "float32");
-          return Object(_complex__WEBPACK_IMPORTED_MODULE_4__[/* complex */ "a"])(real, imag);
-        }
-        const values = Object(_util__WEBPACK_IMPORTED_MODULE_3__["makeOnesTypedArray"])(
-          Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(shape),
-          dtype
-        );
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeTensor(
-          values,
-          shape,
-          dtype
-        );
-      }
-      /**
-       * Creates a `tf.Tensor` with all elements set to 0.
-       *
-       * ```js
-       * tf.zeros([2, 2]).print();
-       * ```
-       *
-       * @param shape An array of integers defining the output tensor shape.
-       * @param dtype The type of an element in the resulting tensor. Can
-       *     be 'float32', 'int32' or 'bool'. Defaults to 'float'.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function zeros(shape, dtype = "float32") {
-        if (dtype === "complex64") {
-          const real = zeros(shape, "float32");
-          const imag = zeros(shape, "float32");
-          return Object(_complex__WEBPACK_IMPORTED_MODULE_4__[/* complex */ "a"])(real, imag);
-        }
-        const values = Object(_util__WEBPACK_IMPORTED_MODULE_3__["makeZerosTypedArray"])(
-          Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(shape),
-          dtype
-        );
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeTensor(
-          values,
-          shape,
-          dtype
-        );
-      }
-      /**
-       * Creates a `tf.Tensor` with all elements set to 1 with the same shape as the
-       * given tensor.
-       *
-       * ```js
-       * const x = tf.tensor([1, 2]);
-       * tf.onesLike(x).print();
-       * ```
-       * @param x A tensor.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function onesLike_(x) {
-        const $x = Object(_tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"])(
-          x,
-          "x",
-          "onesLike"
-        );
-        if ($x.dtype === "complex64") {
-          const r = onesLike(Object(_real__WEBPACK_IMPORTED_MODULE_7__[/* real */ "a"])($x));
-          const i = zerosLike(Object(_imag__WEBPACK_IMPORTED_MODULE_5__[/* imag */ "a"])($x));
-          return Object(_complex__WEBPACK_IMPORTED_MODULE_4__[/* complex */ "a"])(r, i);
-        }
-        const der = (dy, saved) => ({ x: () => zerosLike(dy) });
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
-          (backend) => backend.onesLike($x),
-          { x: $x },
-          der,
-          "OnesLike"
-        );
-      }
-      /**
-       * Creates a `tf.Tensor` with all elements set to 0 with the same shape as the
-       * given tensor.
-       *
-       * ```js
-       * const x = tf.tensor([1, 2]);
-       * tf.zerosLike(x).print();
-       * ```
-       *
-       * @param x The tensor of required shape.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function zerosLike_(x) {
-        const $x = Object(_tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"])(
-          x,
-          "x",
-          "zerosLike"
-        );
-        const der = (dy, saved) => ({ x: () => zerosLike(dy) });
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
-          (backend) => backend.zerosLike($x),
-          { x: $x },
-          der,
-          "ZerosLike"
-        );
-      }
-      /**
-       * Return an evenly spaced sequence of numbers over the given interval.
-       *
-       * ```js
-       * tf.linspace(0, 9, 10).print();
-       * ```
-       * @param start The start value of the sequence.
-       * @param stop The end value of the sequence.
-       * @param num The number of values to generate.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function linspace(start, stop, num) {
-        if (num <= 0) {
-          throw new Error("The number of values should be positive.");
-        }
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
-          (backend) => backend.linspace(start, stop, num),
-          {}
-        );
-      }
-      /**
-       * Creates a new `tf.Tensor1D` filled with the numbers in the range provided.
-       *
-       * The tensor is a is half-open interval meaning it includes start, but
-       * excludes stop. Decrementing ranges and negative step values are also
-       * supported.
-       *
-       * ```js
-       * tf.range(0, 9, 2).print();
-       * ```
-       *
-       * @param start An integer start value
-       * @param stop An integer stop value
-       * @param step An integer increment (will default to 1 or -1)
-       * @param dtype The data type of the output tensor. Defaults to 'float32'.
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function range(start, stop, step = 1, dtype = "float32") {
-        if (step === 0) {
-          throw new Error("Cannot have a step of zero");
-        }
-        const sameStartStop = start === stop;
-        const increasingRangeNegativeStep = start < stop && step < 0;
-        const decreasingRangePositiveStep = stop < start && step > 1;
-        if (sameStartStop || increasingRangeNegativeStep || decreasingRangePositiveStep) {
-          return zeros([0], dtype);
-        }
-        const numElements = Math.abs(Math.ceil((stop - start) / step));
-        const values = Object(_util__WEBPACK_IMPORTED_MODULE_3__["makeZerosTypedArray"])(
-          numElements,
-          dtype
-        );
-        if (stop < start && step === 1) {
-          // Auto adjust the step's sign if it hasn't been set
-          // (or was set to 1)
-          step = -1;
-        }
-        values[0] = start;
-        for (let i = 1; i < values.length; i++) {
-          values[i] = values[i - 1] + step;
-        }
-        return tensor1d(values, dtype);
-      }
-
-      const onesLike = Object(_operation__WEBPACK_IMPORTED_MODULE_6__[/* op */ "a"])({ onesLike_ });
-      const zerosLike = Object(_operation__WEBPACK_IMPORTED_MODULE_6__[/* op */ "a"])({
-        zerosLike_,
-      });
-      //# sourceMappingURL=tensor_ops.js.map
-
-      /***/
-    },
-    /* 9 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return assertNotComplex;
-      });
-      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
-        __webpack_require__(0);
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function assertNotComplex(tensor, opName) {
-        if (!Array.isArray(tensor)) {
-          tensor = [tensor];
-        }
-        tensor.forEach((t) => {
-          if (t != null) {
-            _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].assert(
-              t.dtype !== "complex64",
-              () => `${opName} does not support complex64 tensors in the CPU backend.`
-            );
-          }
-        });
-      }
-      //# sourceMappingURL=cpu_util.js.map
-
-      /***/
-    },
-    /* 10 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return Environment;
-      });
-      /* unused harmony export getQueryParams */
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return env;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return ENV;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
-        return setEnvironmentGlobal;
-      });
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // Expects flags from URL in the format ?tfjsflags=FLAG1:1,FLAG2:true.
-      const TENSORFLOWJS_FLAGS_PREFIX = "tfjsflags";
-      /**
-       * The environment contains evaluated flags as well as the registered platform.
-       * This is always used as a global singleton and can be retrieved with
-       * `tf.env()`.
-       */
-      /** @doc {heading: 'Environment'} */
-      class Environment {
-        // tslint:disable-next-line: no-any
-        constructor(global) {
-          this.global = global;
-          this.flags = {};
-          this.flagRegistry = {};
-          this.urlFlags = {};
-          this.populateURLFlags();
-        }
-        setPlatform(platformName, platform) {
-          if (this.platform != null) {
-            console.warn(
-              `Platform ${this.platformName} has already been set. ` +
-                `Overwriting the platform with ${platform}.`
-            );
-          }
-          this.platformName = platformName;
-          this.platform = platform;
-        }
-        registerFlag(flagName, evaluationFn, setHook) {
-          this.flagRegistry[flagName] = { evaluationFn, setHook };
-          // Override the flag value from the URL. This has to happen here because the
-          // environment is initialized before flags get registered.
-          if (this.urlFlags[flagName] != null) {
-            const flagValue = this.urlFlags[flagName];
-            console.warn(`Setting feature override from URL ${flagName}: ${flagValue}.`);
-            this.set(flagName, flagValue);
-          }
-        }
-        async getAsync(flagName) {
-          if (flagName in this.flags) {
-            return this.flags[flagName];
-          }
-          this.flags[flagName] = await this.evaluateFlag(flagName);
-          return this.flags[flagName];
-        }
-        get(flagName) {
-          if (flagName in this.flags) {
-            return this.flags[flagName];
-          }
-          const flagValue = this.evaluateFlag(flagName);
-          if (flagValue instanceof Promise) {
-            throw new Error(
-              `Flag ${flagName} cannot be synchronously evaluated. ` +
-                `Please use getAsync() instead.`
-            );
-          }
-          this.flags[flagName] = flagValue;
-          return this.flags[flagName];
-        }
-        getNumber(flagName) {
-          return this.get(flagName);
-        }
-        getBool(flagName) {
-          return this.get(flagName);
-        }
-        getFlags() {
-          return this.flags;
-        }
-        // For backwards compatibility.
-        get features() {
-          return this.flags;
-        }
-        set(flagName, value) {
-          if (this.flagRegistry[flagName] == null) {
-            throw new Error(`Cannot set flag ${flagName} as it has not been registered.`);
-          }
-          this.flags[flagName] = value;
-          if (this.flagRegistry[flagName].setHook != null) {
-            this.flagRegistry[flagName].setHook(value);
-          }
-        }
-        evaluateFlag(flagName) {
-          if (this.flagRegistry[flagName] == null) {
-            throw new Error(`Cannot evaluate flag '${flagName}': no evaluation function found.`);
-          }
-          return this.flagRegistry[flagName].evaluationFn();
-        }
-        setFlags(flags) {
-          this.flags = Object.assign({}, flags);
-        }
-        reset() {
-          this.flags = {};
-          this.urlFlags = {};
-          this.populateURLFlags();
-        }
-        populateURLFlags() {
-          if (
-            typeof this.global === "undefined" ||
-            typeof this.global.location === "undefined" ||
-            typeof this.global.location.search === "undefined"
-          ) {
-            return;
-          }
-          const urlParams = getQueryParams(this.global.location.search);
-          if (TENSORFLOWJS_FLAGS_PREFIX in urlParams) {
-            const keyValues = urlParams[TENSORFLOWJS_FLAGS_PREFIX].split(",");
-            keyValues.forEach((keyValue) => {
-              const [key, value] = keyValue.split(":");
-              this.urlFlags[key] = parseValue(key, value);
-            });
-          }
-        }
-      }
-      function getQueryParams(queryString) {
-        const params = {};
-        queryString.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g, (s, ...t) => {
-          decodeParam(params, t[0], t[1]);
-          return t.join("=");
-        });
-        return params;
-      }
-      function decodeParam(params, name, value) {
-        params[decodeURIComponent(name)] = decodeURIComponent(value || "");
-      }
-      function parseValue(flagName, value) {
-        value = value.toLowerCase();
-        if (value === "true" || value === "false") {
-          return value === "true";
-        } else if (`${+value}` === value) {
-          return +value;
-        }
-        throw new Error(`Could not parse value flag value ${value} for flag ${flagName}.`);
-      }
-      /**
-       * Returns the current environment (a global singleton).
-       *
-       * The environment object contains the evaluated feature values as well as the
-       * active platform.
-       */
-      /** @doc {heading: 'Environment'} */
-      function env() {
-        return ENV;
-      }
-      let ENV = null;
-      function setEnvironmentGlobal(environment) {
-        ENV = environment;
-      }
-      //# sourceMappingURL=environment.js.map
-
-      /***/
-    },
-    /* 11 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "makeTypesMatch",
-        function () {
-          return makeTypesMatch;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "assertTypesMatch",
-        function () {
-          return assertTypesMatch;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isTensorInList",
-        function () {
-          return isTensorInList;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "getTensorsInContainer",
-        function () {
-          return getTensorsInContainer;
-        }
-      );
-      /* harmony import */ var _tensor__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(7);
-      /* harmony import */ var _types__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(23);
-      /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_2__ = __webpack_require__(1);
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function makeTypesMatch(a, b) {
-        if (a.dtype === b.dtype) {
-          return [a, b];
-        }
-        const dtype = Object(_types__WEBPACK_IMPORTED_MODULE_1__[/* upcastType */ "c"])(
-          a.dtype,
-          b.dtype
-        );
-        return [a.cast(dtype), b.cast(dtype)];
-      }
-      function assertTypesMatch(a, b) {
-        Object(_util__WEBPACK_IMPORTED_MODULE_2__["assert"])(
-          a.dtype === b.dtype,
-          () => `The dtypes of the first(${a.dtype}) and` + ` second(${b.dtype}) input must match`
-        );
-      }
-      function isTensorInList(tensor, tensorList) {
-        return tensorList.some((x) => x.id === tensor.id);
-      }
-      /**
-       * Extracts any `Tensor`s found within the provided object.
-       *
-       * @param container an object that may be a `Tensor` or may directly contain
-       *   `Tensor`s, such as a `Tensor[]` or `{key: Tensor, ...}`. In general it
-       *   is safe to pass any object here, except that `Promise`s are not
-       *   supported.
-       * @returns An array of `Tensors` found within the passed object. If the
-       *   argument is simply a `Tensor', a list containing that `Tensor` is
-       *   returned. If the object is not a `Tensor` or does not
-       *   contain `Tensors`, an empty list is returned.
-       */
-      function getTensorsInContainer(result) {
-        const list = [];
-        const seen = new Set();
-        walkTensorContainer(result, list, seen);
-        return list;
-      }
-      function walkTensorContainer(container, list, seen) {
-        if (container == null) {
-          return;
-        }
-        if (container instanceof _tensor__WEBPACK_IMPORTED_MODULE_0__[/* Tensor */ "a"]) {
-          list.push(container);
-          return;
-        }
-        if (!isIterable(container)) {
-          return;
-        }
-        // Iteration over keys works also for arrays.
-        const iterable = container;
-        for (const k in iterable) {
-          const val = iterable[k];
-          if (!seen.has(val)) {
-            seen.add(val);
-            walkTensorContainer(val, list, seen);
-          }
-        }
-      }
-      // tslint:disable-next-line:no-any
-      function isIterable(obj) {
-        return Array.isArray(obj) || typeof obj === "object";
-      }
-      //# sourceMappingURL=tensor_util.js.map
-
-      /***/
-    },
-    /* 12 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (global) {
-        var numeric = false ? undefined : exports;
-        if (typeof global !== "undefined") {
-          global.numeric = numeric;
-        }
-
-        numeric.version = "1.2.6";
-
-        // 1. Utility functions
-        numeric.bench = function bench(f, interval) {
-          var t1, t2, n, i;
-          if (typeof interval === "undefined") {
-            interval = 15;
-          }
-          n = 0.5;
-          t1 = new Date();
-          while (1) {
-            n *= 2;
-            for (i = n; i > 3; i -= 4) {
-              f();
-              f();
-              f();
-              f();
-            }
-            while (i > 0) {
-              f();
-              i--;
-            }
-            t2 = new Date();
-            if (t2 - t1 > interval) break;
-          }
-          for (i = n; i > 3; i -= 4) {
-            f();
-            f();
-            f();
-            f();
-          }
-          while (i > 0) {
-            f();
-            i--;
-          }
-          t2 = new Date();
-          return (1000 * (3 * n - 1)) / (t2 - t1);
-        };
-
-        numeric._myIndexOf = function _myIndexOf(w) {
-          var n = this.length,
-            k;
-          for (k = 0; k < n; ++k) if (this[k] === w) return k;
-          return -1;
-        };
-        numeric.myIndexOf = Array.prototype.indexOf ? Array.prototype.indexOf : numeric._myIndexOf;
-
-        numeric.Function = Function;
-        numeric.precision = 4;
-        numeric.largeArray = 50;
-
-        numeric.prettyPrint = function prettyPrint(x) {
-          function fmtnum(x) {
-            if (x === 0) {
-              return "0";
-            }
-            if (isNaN(x)) {
-              return "NaN";
-            }
-            if (x < 0) {
-              return "-" + fmtnum(-x);
-            }
-            if (isFinite(x)) {
-              var scale = Math.floor(Math.log(x) / Math.log(10));
-              var normalized = x / Math.pow(10, scale);
-              var basic = normalized.toPrecision(numeric.precision);
-              if (parseFloat(basic) === 10) {
-                scale++;
-                normalized = 1;
-                basic = normalized.toPrecision(numeric.precision);
-              }
-              return parseFloat(basic).toString() + "e" + scale.toString();
-            }
-            return "Infinity";
-          }
-          var ret = [];
-          function foo(x) {
-            var k;
-            if (typeof x === "undefined") {
-              ret.push(Array(numeric.precision + 8).join(" "));
-              return false;
-            }
-            if (typeof x === "string") {
-              ret.push('"' + x + '"');
-              return false;
-            }
-            if (typeof x === "boolean") {
-              ret.push(x.toString());
-              return false;
-            }
-            if (typeof x === "number") {
-              var a = fmtnum(x);
-              var b = x.toPrecision(numeric.precision);
-              var c = parseFloat(x.toString()).toString();
-              var d = [a, b, c, parseFloat(b).toString(), parseFloat(c).toString()];
-              for (k = 1; k < d.length; k++) {
-                if (d[k].length < a.length) a = d[k];
-              }
-              ret.push(Array(numeric.precision + 8 - a.length).join(" ") + a);
-              return false;
-            }
-            if (x === null) {
-              ret.push("null");
-              return false;
-            }
-            if (typeof x === "function") {
-              ret.push(x.toString());
-              var flag = false;
-              for (k in x) {
-                if (x.hasOwnProperty(k)) {
-                  if (flag) ret.push(",\n");
-                  else ret.push("\n{");
-                  flag = true;
-                  ret.push(k);
-                  ret.push(": \n");
-                  foo(x[k]);
-                }
-              }
-              if (flag) ret.push("}\n");
-              return true;
-            }
-            if (x instanceof Array) {
-              if (x.length > numeric.largeArray) {
-                ret.push("...Large Array...");
-                return true;
-              }
-              var flag = false;
-              ret.push("[");
-              for (k = 0; k < x.length; k++) {
-                if (k > 0) {
-                  ret.push(",");
-                  if (flag) ret.push("\n ");
-                }
-                flag = foo(x[k]);
-              }
-              ret.push("]");
-              return true;
-            }
-            ret.push("{");
-            var flag = false;
-            for (k in x) {
-              if (x.hasOwnProperty(k)) {
-                if (flag) ret.push(",\n");
-                flag = true;
-                ret.push(k);
-                ret.push(": \n");
-                foo(x[k]);
-              }
-            }
-            ret.push("}");
-            return true;
-          }
-          foo(x);
-          return ret.join("");
-        };
-
-        numeric.parseDate = function parseDate(d) {
-          function foo(d) {
-            if (typeof d === "string") {
-              return Date.parse(d.replace(/-/g, "/"));
-            }
-            if (!(d instanceof Array)) {
-              throw new Error("parseDate: parameter must be arrays of strings");
-            }
-            var ret = [],
-              k;
-            for (k = 0; k < d.length; k++) {
-              ret[k] = foo(d[k]);
-            }
-            return ret;
-          }
-          return foo(d);
-        };
-
-        numeric.parseFloat = function parseFloat_(d) {
-          function foo(d) {
-            if (typeof d === "string") {
-              return parseFloat(d);
-            }
-            if (!(d instanceof Array)) {
-              throw new Error("parseFloat: parameter must be arrays of strings");
-            }
-            var ret = [],
-              k;
-            for (k = 0; k < d.length; k++) {
-              ret[k] = foo(d[k]);
-            }
-            return ret;
-          }
-          return foo(d);
-        };
-
-        numeric.parseCSV = function parseCSV(t) {
-          var foo = t.split("\n");
-          var j, k;
-          var ret = [];
-          var pat = /(([^'",]*)|('[^']*')|("[^"]*")),/g;
-          var patnum =
-            /^\s*(([+-]?[0-9]+(\.[0-9]*)?(e[+-]?[0-9]+)?)|([+-]?[0-9]*(\.[0-9]+)?(e[+-]?[0-9]+)?))\s*$/;
-          var stripper = function (n) {
-            return n.substr(0, n.length - 1);
-          };
-          var count = 0;
-          for (k = 0; k < foo.length; k++) {
-            var bar = (foo[k] + ",").match(pat),
-              baz;
-            if (bar.length > 0) {
-              ret[count] = [];
-              for (j = 0; j < bar.length; j++) {
-                baz = stripper(bar[j]);
-                if (patnum.test(baz)) {
-                  ret[count][j] = parseFloat(baz);
-                } else ret[count][j] = baz;
-              }
-              count++;
-            }
-          }
-          return ret;
-        };
-
-        numeric.toCSV = function toCSV(A) {
-          var s = numeric.dim(A);
-          var i, j, m, n, row, ret;
-          m = s[0];
-          n = s[1];
-          ret = [];
-          for (i = 0; i < m; i++) {
-            row = [];
-            for (j = 0; j < m; j++) {
-              row[j] = A[i][j].toString();
-            }
-            ret[i] = row.join(", ");
-          }
-          return ret.join("\n") + "\n";
-        };
-
-        numeric.getURL = function getURL(url) {
-          var client = new XMLHttpRequest();
-          client.open("GET", url, false);
-          client.send();
-          return client;
-        };
-
-        numeric.imageURL = function imageURL(img) {
-          function base64(A) {
-            var n = A.length,
-              i,
-              x,
-              y,
-              z,
-              p,
-              q,
-              r,
-              s;
-            var key = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=";
-            var ret = "";
-            for (i = 0; i < n; i += 3) {
-              x = A[i];
-              y = A[i + 1];
-              z = A[i + 2];
-              p = x >> 2;
-              q = ((x & 3) << 4) + (y >> 4);
-              r = ((y & 15) << 2) + (z >> 6);
-              s = z & 63;
-              if (i + 1 >= n) {
-                r = s = 64;
-              } else if (i + 2 >= n) {
-                s = 64;
-              }
-              ret += key.charAt(p) + key.charAt(q) + key.charAt(r) + key.charAt(s);
-            }
-            return ret;
-          }
-          function crc32Array(a, from, to) {
-            if (typeof from === "undefined") {
-              from = 0;
-            }
-            if (typeof to === "undefined") {
-              to = a.length;
-            }
-            var table = [
-              0x00000000, 0x77073096, 0xee0e612c, 0x990951ba, 0x076dc419, 0x706af48f, 0xe963a535,
-              0x9e6495a3, 0x0edb8832, 0x79dcb8a4, 0xe0d5e91e, 0x97d2d988, 0x09b64c2b, 0x7eb17cbd,
-              0xe7b82d07, 0x90bf1d91, 0x1db71064, 0x6ab020f2, 0xf3b97148, 0x84be41de, 0x1adad47d,
-              0x6ddde4eb, 0xf4d4b551, 0x83d385c7, 0x136c9856, 0x646ba8c0, 0xfd62f97a, 0x8a65c9ec,
-              0x14015c4f, 0x63066cd9, 0xfa0f3d63, 0x8d080df5, 0x3b6e20c8, 0x4c69105e, 0xd56041e4,
-              0xa2677172, 0x3c03e4d1, 0x4b04d447, 0xd20d85fd, 0xa50ab56b, 0x35b5a8fa, 0x42b2986c,
-              0xdbbbc9d6, 0xacbcf940, 0x32d86ce3, 0x45df5c75, 0xdcd60dcf, 0xabd13d59, 0x26d930ac,
-              0x51de003a, 0xc8d75180, 0xbfd06116, 0x21b4f4b5, 0x56b3c423, 0xcfba9599, 0xb8bda50f,
-              0x2802b89e, 0x5f058808, 0xc60cd9b2, 0xb10be924, 0x2f6f7c87, 0x58684c11, 0xc1611dab,
-              0xb6662d3d, 0x76dc4190, 0x01db7106, 0x98d220bc, 0xefd5102a, 0x71b18589, 0x06b6b51f,
-              0x9fbfe4a5, 0xe8b8d433, 0x7807c9a2, 0x0f00f934, 0x9609a88e, 0xe10e9818, 0x7f6a0dbb,
-              0x086d3d2d, 0x91646c97, 0xe6635c01, 0x6b6b51f4, 0x1c6c6162, 0x856530d8, 0xf262004e,
-              0x6c0695ed, 0x1b01a57b, 0x8208f4c1, 0xf50fc457, 0x65b0d9c6, 0x12b7e950, 0x8bbeb8ea,
-              0xfcb9887c, 0x62dd1ddf, 0x15da2d49, 0x8cd37cf3, 0xfbd44c65, 0x4db26158, 0x3ab551ce,
-              0xa3bc0074, 0xd4bb30e2, 0x4adfa541, 0x3dd895d7, 0xa4d1c46d, 0xd3d6f4fb, 0x4369e96a,
-              0x346ed9fc, 0xad678846, 0xda60b8d0, 0x44042d73, 0x33031de5, 0xaa0a4c5f, 0xdd0d7cc9,
-              0x5005713c, 0x270241aa, 0xbe0b1010, 0xc90c2086, 0x5768b525, 0x206f85b3, 0xb966d409,
-              0xce61e49f, 0x5edef90e, 0x29d9c998, 0xb0d09822, 0xc7d7a8b4, 0x59b33d17, 0x2eb40d81,
-              0xb7bd5c3b, 0xc0ba6cad, 0xedb88320, 0x9abfb3b6, 0x03b6e20c, 0x74b1d29a, 0xead54739,
-              0x9dd277af, 0x04db2615, 0x73dc1683, 0xe3630b12, 0x94643b84, 0x0d6d6a3e, 0x7a6a5aa8,
-              0xe40ecf0b, 0x9309ff9d, 0x0a00ae27, 0x7d079eb1, 0xf00f9344, 0x8708a3d2, 0x1e01f268,
-              0x6906c2fe, 0xf762575d, 0x806567cb, 0x196c3671, 0x6e6b06e7, 0xfed41b76, 0x89d32be0,
-              0x10da7a5a, 0x67dd4acc, 0xf9b9df6f, 0x8ebeeff9, 0x17b7be43, 0x60b08ed5, 0xd6d6a3e8,
-              0xa1d1937e, 0x38d8c2c4, 0x4fdff252, 0xd1bb67f1, 0xa6bc5767, 0x3fb506dd, 0x48b2364b,
-              0xd80d2bda, 0xaf0a1b4c, 0x36034af6, 0x41047a60, 0xdf60efc3, 0xa867df55, 0x316e8eef,
-              0x4669be79, 0xcb61b38c, 0xbc66831a, 0x256fd2a0, 0x5268e236, 0xcc0c7795, 0xbb0b4703,
-              0x220216b9, 0x5505262f, 0xc5ba3bbe, 0xb2bd0b28, 0x2bb45a92, 0x5cb36a04, 0xc2d7ffa7,
-              0xb5d0cf31, 0x2cd99e8b, 0x5bdeae1d, 0x9b64c2b0, 0xec63f226, 0x756aa39c, 0x026d930a,
-              0x9c0906a9, 0xeb0e363f, 0x72076785, 0x05005713, 0x95bf4a82, 0xe2b87a14, 0x7bb12bae,
-              0x0cb61b38, 0x92d28e9b, 0xe5d5be0d, 0x7cdcefb7, 0x0bdbdf21, 0x86d3d2d4, 0xf1d4e242,
-              0x68ddb3f8, 0x1fda836e, 0x81be16cd, 0xf6b9265b, 0x6fb077e1, 0x18b74777, 0x88085ae6,
-              0xff0f6a70, 0x66063bca, 0x11010b5c, 0x8f659eff, 0xf862ae69, 0x616bffd3, 0x166ccf45,
-              0xa00ae278, 0xd70dd2ee, 0x4e048354, 0x3903b3c2, 0xa7672661, 0xd06016f7, 0x4969474d,
-              0x3e6e77db, 0xaed16a4a, 0xd9d65adc, 0x40df0b66, 0x37d83bf0, 0xa9bcae53, 0xdebb9ec5,
-              0x47b2cf7f, 0x30b5ffe9, 0xbdbdf21c, 0xcabac28a, 0x53b39330, 0x24b4a3a6, 0xbad03605,
-              0xcdd70693, 0x54de5729, 0x23d967bf, 0xb3667a2e, 0xc4614ab8, 0x5d681b02, 0x2a6f2b94,
-              0xb40bbe37, 0xc30c8ea1, 0x5a05df1b, 0x2d02ef8d,
-            ];
-
-            var crc = -1,
-              y = 0,
-              n = a.length,
-              i;
-
-            for (i = from; i < to; i++) {
-              y = (crc ^ a[i]) & 0xff;
-              crc = (crc >>> 8) ^ table[y];
-            }
-
-            return crc ^ -1;
-          }
-
-          var h = img[0].length,
-            w = img[0][0].length,
-            s1,
-            s2,
-            next,
-            k,
-            length,
-            a,
-            b,
-            i,
-            j,
-            adler32,
-            crc32;
-          var stream = [
-            137,
-            80,
-            78,
-            71,
-            13,
-            10,
-            26,
-            10, //  0: PNG signature
-            0,
-            0,
-            0,
-            13, //  8: IHDR Chunk length
-            73,
-            72,
-            68,
-            82, // 12: "IHDR"
-            (w >> 24) & 255,
-            (w >> 16) & 255,
-            (w >> 8) & 255,
-            w & 255, // 16: Width
-            (h >> 24) & 255,
-            (h >> 16) & 255,
-            (h >> 8) & 255,
-            h & 255, // 20: Height
-            8, // 24: bit depth
-            2, // 25: RGB
-            0, // 26: deflate
-            0, // 27: no filter
-            0, // 28: no interlace
-            -1,
-            -2,
-            -3,
-            -4, // 29: CRC
-            -5,
-            -6,
-            -7,
-            -8, // 33: IDAT Chunk length
-            73,
-            68,
-            65,
-            84, // 37: "IDAT"
-            // RFC 1950 header starts here
-            8, // 41: RFC1950 CMF
-            29, // 42: RFC1950 FLG
-          ];
-          crc32 = crc32Array(stream, 12, 29);
-          stream[29] = (crc32 >> 24) & 255;
-          stream[30] = (crc32 >> 16) & 255;
-          stream[31] = (crc32 >> 8) & 255;
-          stream[32] = crc32 & 255;
-          s1 = 1;
-          s2 = 0;
-          for (i = 0; i < h; i++) {
-            if (i < h - 1) {
-              stream.push(0);
-            } else {
-              stream.push(1);
-            }
-            a = (3 * w + 1 + (i === 0)) & 255;
-            b = ((3 * w + 1 + (i === 0)) >> 8) & 255;
-            stream.push(a);
-            stream.push(b);
-            stream.push(~a & 255);
-            stream.push(~b & 255);
-            if (i === 0) stream.push(0);
-            for (j = 0; j < w; j++) {
-              for (k = 0; k < 3; k++) {
-                a = img[k][i][j];
-                if (a > 255) a = 255;
-                else if (a < 0) a = 0;
-                else a = Math.round(a);
-                s1 = (s1 + a) % 65521;
-                s2 = (s2 + s1) % 65521;
-                stream.push(a);
-              }
-            }
-            stream.push(0);
-          }
-          adler32 = (s2 << 16) + s1;
-          stream.push((adler32 >> 24) & 255);
-          stream.push((adler32 >> 16) & 255);
-          stream.push((adler32 >> 8) & 255);
-          stream.push(adler32 & 255);
-          length = stream.length - 41;
-          stream[33] = (length >> 24) & 255;
-          stream[34] = (length >> 16) & 255;
-          stream[35] = (length >> 8) & 255;
-          stream[36] = length & 255;
-          crc32 = crc32Array(stream, 37);
-          stream.push((crc32 >> 24) & 255);
-          stream.push((crc32 >> 16) & 255);
-          stream.push((crc32 >> 8) & 255);
-          stream.push(crc32 & 255);
-          stream.push(0);
-          stream.push(0);
-          stream.push(0);
-          stream.push(0);
-          //    a = stream.length;
-          stream.push(73); // I
-          stream.push(69); // E
-          stream.push(78); // N
-          stream.push(68); // D
-          stream.push(174); // CRC1
-          stream.push(66); // CRC2
-          stream.push(96); // CRC3
-          stream.push(130); // CRC4
-          return "data:image/png;base64," + base64(stream);
-        };
-
-        // 2. Linear algebra with Arrays.
-        numeric._dim = function _dim(x) {
-          var ret = [];
-          while (typeof x === "object") {
-            ret.push(x.length);
-            x = x[0];
-          }
-          return ret;
-        };
-
-        numeric.dim = function dim(x) {
-          var y, z;
-          if (typeof x === "object") {
-            y = x[0];
-            if (typeof y === "object") {
-              z = y[0];
-              if (typeof z === "object") {
-                return numeric._dim(x);
-              }
-              return [x.length, y.length];
-            }
-            return [x.length];
-          }
-          return [];
-        };
-
-        numeric.mapreduce = function mapreduce(body, init) {
-          return Function(
-            "x",
-            "accum",
-            "_s",
-            "_k",
-            'if(typeof accum === "undefined") accum = ' +
-              init +
-              ";\n" +
-              'if(typeof x === "number") { var xi = x; ' +
-              body +
-              "; return accum; }\n" +
-              'if(typeof _s === "undefined") _s = numeric.dim(x);\n' +
-              'if(typeof _k === "undefined") _k = 0;\n' +
-              "var _n = _s[_k];\n" +
-              "var i,xi;\n" +
-              "if(_k < _s.length-1) {\n" +
-              "    for(i=_n-1;i>=0;i--) {\n" +
-              "        accum = arguments.callee(x[i],accum,_s,_k+1);\n" +
-              "    }" +
-              "    return accum;\n" +
-              "}\n" +
-              "for(i=_n-1;i>=1;i-=2) { \n" +
-              "    xi = x[i];\n" +
-              "    " +
-              body +
-              ";\n" +
-              "    xi = x[i-1];\n" +
-              "    " +
-              body +
-              ";\n" +
-              "}\n" +
-              "if(i === 0) {\n" +
-              "    xi = x[i];\n" +
-              "    " +
-              body +
-              "\n" +
-              "}\n" +
-              "return accum;"
-          );
-        };
-        numeric.mapreduce2 = function mapreduce2(body, setup) {
-          return Function(
-            "x",
-            "var n = x.length;\n" +
-              "var i,xi;\n" +
-              setup +
-              ";\n" +
-              "for(i=n-1;i!==-1;--i) { \n" +
-              "    xi = x[i];\n" +
-              "    " +
-              body +
-              ";\n" +
-              "}\n" +
-              "return accum;"
-          );
-        };
-
-        numeric.same = function same(x, y) {
-          var i, n;
-          if (!(x instanceof Array) || !(y instanceof Array)) {
-            return false;
-          }
-          n = x.length;
-          if (n !== y.length) {
-            return false;
-          }
-          for (i = 0; i < n; i++) {
-            if (x[i] === y[i]) {
-              continue;
-            }
-            if (typeof x[i] === "object") {
-              if (!same(x[i], y[i])) return false;
-            } else {
-              return false;
-            }
-          }
-          return true;
-        };
-
-        numeric.rep = function rep(s, v, k) {
-          if (typeof k === "undefined") {
-            k = 0;
-          }
-          var n = s[k],
-            ret = Array(n),
-            i;
-          if (k === s.length - 1) {
-            for (i = n - 2; i >= 0; i -= 2) {
-              ret[i + 1] = v;
-              ret[i] = v;
-            }
-            if (i === -1) {
-              ret[0] = v;
-            }
-            return ret;
-          }
-          for (i = n - 1; i >= 0; i--) {
-            ret[i] = numeric.rep(s, v, k + 1);
-          }
-          return ret;
-        };
-
-        numeric.dotMMsmall = function dotMMsmall(x, y) {
-          var i, j, k, p, q, r, ret, foo, bar, woo, i0, k0, p0, r0;
-          p = x.length;
-          q = y.length;
-          r = y[0].length;
-          ret = Array(p);
-          for (i = p - 1; i >= 0; i--) {
-            foo = Array(r);
-            bar = x[i];
-            for (k = r - 1; k >= 0; k--) {
-              woo = bar[q - 1] * y[q - 1][k];
-              for (j = q - 2; j >= 1; j -= 2) {
-                i0 = j - 1;
-                woo += bar[j] * y[j][k] + bar[i0] * y[i0][k];
-              }
-              if (j === 0) {
-                woo += bar[0] * y[0][k];
-              }
-              foo[k] = woo;
-            }
-            ret[i] = foo;
-          }
-          return ret;
-        };
-        numeric._getCol = function _getCol(A, j, x) {
-          var n = A.length,
-            i;
-          for (i = n - 1; i > 0; --i) {
-            x[i] = A[i][j];
-            --i;
-            x[i] = A[i][j];
-          }
-          if (i === 0) x[0] = A[0][j];
-        };
-        numeric.dotMMbig = function dotMMbig(x, y) {
-          var gc = numeric._getCol,
-            p = y.length,
-            v = Array(p);
-          var m = x.length,
-            n = y[0].length,
-            A = new Array(m),
-            xj;
-          var VV = numeric.dotVV;
-          var i, j, k, z;
-          --p;
-          --m;
-          for (i = m; i !== -1; --i) A[i] = Array(n);
-          --n;
-          for (i = n; i !== -1; --i) {
-            gc(y, i, v);
-            for (j = m; j !== -1; --j) {
-              z = 0;
-              xj = x[j];
-              A[j][i] = VV(xj, v);
-            }
-          }
-          return A;
-        };
-
-        numeric.dotMV = function dotMV(x, y) {
-          var p = x.length,
-            q = y.length,
-            i;
-          var ret = Array(p),
-            dotVV = numeric.dotVV;
-          for (i = p - 1; i >= 0; i--) {
-            ret[i] = dotVV(x[i], y);
-          }
-          return ret;
-        };
-
-        numeric.dotVM = function dotVM(x, y) {
-          var i, j, k, p, q, r, ret, foo, bar, woo, i0, k0, p0, r0, s1, s2, s3, baz, accum;
-          p = x.length;
-          q = y[0].length;
-          ret = Array(q);
-          for (k = q - 1; k >= 0; k--) {
-            woo = x[p - 1] * y[p - 1][k];
-            for (j = p - 2; j >= 1; j -= 2) {
-              i0 = j - 1;
-              woo += x[j] * y[j][k] + x[i0] * y[i0][k];
-            }
-            if (j === 0) {
-              woo += x[0] * y[0][k];
-            }
-            ret[k] = woo;
-          }
-          return ret;
-        };
-
-        numeric.dotVV = function dotVV(x, y) {
-          var i,
-            n = x.length,
-            i1,
-            ret = x[n - 1] * y[n - 1];
-          for (i = n - 2; i >= 1; i -= 2) {
-            i1 = i - 1;
-            ret += x[i] * y[i] + x[i1] * y[i1];
-          }
-          if (i === 0) {
-            ret += x[0] * y[0];
-          }
-          return ret;
-        };
-
-        numeric.dot = function dot(x, y) {
-          var d = numeric.dim;
-          switch (d(x).length * 1000 + d(y).length) {
-            case 2002:
-              if (y.length < 10) return numeric.dotMMsmall(x, y);
-              else return numeric.dotMMbig(x, y);
-            case 2001:
-              return numeric.dotMV(x, y);
-            case 1002:
-              return numeric.dotVM(x, y);
-            case 1001:
-              return numeric.dotVV(x, y);
-            case 1000:
-              return numeric.mulVS(x, y);
-            case 1:
-              return numeric.mulSV(x, y);
-            case 0:
-              return x * y;
-            default:
-              throw new Error("numeric.dot only works on vectors and matrices");
-          }
-        };
-
-        numeric.diag = function diag(d) {
-          var i,
-            i1,
-            j,
-            n = d.length,
-            A = Array(n),
-            Ai;
-          for (i = n - 1; i >= 0; i--) {
-            Ai = Array(n);
-            i1 = i + 2;
-            for (j = n - 1; j >= i1; j -= 2) {
-              Ai[j] = 0;
-              Ai[j - 1] = 0;
-            }
-            if (j > i) {
-              Ai[j] = 0;
-            }
-            Ai[i] = d[i];
-            for (j = i - 1; j >= 1; j -= 2) {
-              Ai[j] = 0;
-              Ai[j - 1] = 0;
-            }
-            if (j === 0) {
-              Ai[0] = 0;
-            }
-            A[i] = Ai;
-          }
-          return A;
-        };
-        numeric.getDiag = function (A) {
-          var n = Math.min(A.length, A[0].length),
-            i,
-            ret = Array(n);
-          for (i = n - 1; i >= 1; --i) {
-            ret[i] = A[i][i];
-            --i;
-            ret[i] = A[i][i];
-          }
-          if (i === 0) {
-            ret[0] = A[0][0];
-          }
-          return ret;
-        };
-
-        numeric.identity = function identity(n) {
-          return numeric.diag(numeric.rep([n], 1));
-        };
-        numeric.pointwise = function pointwise(params, body, setup) {
-          if (typeof setup === "undefined") {
-            setup = "";
-          }
-          var fun = [];
-          var k;
-          var avec = /\[i\]$/,
-            p,
-            thevec = "";
-          var haveret = false;
-          for (k = 0; k < params.length; k++) {
-            if (avec.test(params[k])) {
-              p = params[k].substring(0, params[k].length - 3);
-              thevec = p;
-            } else {
-              p = params[k];
-            }
-            if (p === "ret") haveret = true;
-            fun.push(p);
-          }
-          fun[params.length] = "_s";
-          fun[params.length + 1] = "_k";
-          fun[params.length + 2] =
-            'if(typeof _s === "undefined") _s = numeric.dim(' +
-            thevec +
-            ");\n" +
-            'if(typeof _k === "undefined") _k = 0;\n' +
-            "var _n = _s[_k];\n" +
-            "var i" +
-            (haveret ? "" : ", ret = Array(_n)") +
-            ";\n" +
-            "if(_k < _s.length-1) {\n" +
-            "    for(i=_n-1;i>=0;i--) ret[i] = arguments.callee(" +
-            params.join(",") +
-            ",_s,_k+1);\n" +
-            "    return ret;\n" +
-            "}\n" +
-            setup +
-            "\n" +
-            "for(i=_n-1;i!==-1;--i) {\n" +
-            "    " +
-            body +
-            "\n" +
-            "}\n" +
-            "return ret;";
-          return Function.apply(null, fun);
-        };
-        numeric.pointwise2 = function pointwise2(params, body, setup) {
-          if (typeof setup === "undefined") {
-            setup = "";
-          }
-          var fun = [];
-          var k;
-          var avec = /\[i\]$/,
-            p,
-            thevec = "";
-          var haveret = false;
-          for (k = 0; k < params.length; k++) {
-            if (avec.test(params[k])) {
-              p = params[k].substring(0, params[k].length - 3);
-              thevec = p;
-            } else {
-              p = params[k];
-            }
-            if (p === "ret") haveret = true;
-            fun.push(p);
-          }
-          fun[params.length] =
-            "var _n = " +
-            thevec +
-            ".length;\n" +
-            "var i" +
-            (haveret ? "" : ", ret = Array(_n)") +
-            ";\n" +
-            setup +
-            "\n" +
-            "for(i=_n-1;i!==-1;--i) {\n" +
-            body +
-            "\n" +
-            "}\n" +
-            "return ret;";
-          return Function.apply(null, fun);
-        };
-        numeric._biforeach = function _biforeach(x, y, s, k, f) {
-          if (k === s.length - 1) {
-            f(x, y);
-            return;
-          }
-          var i,
-            n = s[k];
-          for (i = n - 1; i >= 0; i--) {
-            _biforeach(
-              typeof x === "object" ? x[i] : x,
-              typeof y === "object" ? y[i] : y,
-              s,
-              k + 1,
-              f
-            );
-          }
-        };
-        numeric._biforeach2 = function _biforeach2(x, y, s, k, f) {
-          if (k === s.length - 1) {
-            return f(x, y);
-          }
-          var i,
-            n = s[k],
-            ret = Array(n);
-          for (i = n - 1; i >= 0; --i) {
-            ret[i] = _biforeach2(
-              typeof x === "object" ? x[i] : x,
-              typeof y === "object" ? y[i] : y,
-              s,
-              k + 1,
-              f
-            );
-          }
-          return ret;
-        };
-        numeric._foreach = function _foreach(x, s, k, f) {
-          if (k === s.length - 1) {
-            f(x);
-            return;
-          }
-          var i,
-            n = s[k];
-          for (i = n - 1; i >= 0; i--) {
-            _foreach(x[i], s, k + 1, f);
-          }
-        };
-        numeric._foreach2 = function _foreach2(x, s, k, f) {
-          if (k === s.length - 1) {
-            return f(x);
-          }
-          var i,
-            n = s[k],
-            ret = Array(n);
-          for (i = n - 1; i >= 0; i--) {
-            ret[i] = _foreach2(x[i], s, k + 1, f);
-          }
-          return ret;
-        };
-
-        /*numeric.anyV = numeric.mapreduce('if(xi) return true;','false');
-numeric.allV = numeric.mapreduce('if(!xi) return false;','true');
-numeric.any = function(x) { if(typeof x.length === "undefined") return x; return numeric.anyV(x); }
-numeric.all = function(x) { if(typeof x.length === "undefined") return x; return numeric.allV(x); }*/
-
-        numeric.ops2 = {
-          add: "+",
-          sub: "-",
-          mul: "*",
-          div: "/",
-          mod: "%",
-          and: "&&",
-          or: "||",
-          eq: "===",
-          neq: "!==",
-          lt: "<",
-          gt: ">",
-          leq: "<=",
-          geq: ">=",
-          band: "&",
-          bor: "|",
-          bxor: "^",
-          lshift: "<<",
-          rshift: ">>",
-          rrshift: ">>>",
-        };
-        numeric.opseq = {
-          addeq: "+=",
-          subeq: "-=",
-          muleq: "*=",
-          diveq: "/=",
-          modeq: "%=",
-          lshifteq: "<<=",
-          rshifteq: ">>=",
-          rrshifteq: ">>>=",
-          bandeq: "&=",
-          boreq: "|=",
-          bxoreq: "^=",
-        };
-        numeric.mathfuns = [
-          "abs",
-          "acos",
-          "asin",
-          "atan",
-          "ceil",
-          "cos",
-          "exp",
-          "floor",
-          "log",
-          "round",
-          "sin",
-          "sqrt",
-          "tan",
-          "isNaN",
-          "isFinite",
-        ];
-        numeric.mathfuns2 = ["atan2", "pow", "max", "min"];
-        numeric.ops1 = {
-          neg: "-",
-          not: "!",
-          bnot: "~",
-          clone: "",
-        };
-        numeric.mapreducers = {
-          any: ["if(xi) return true;", "var accum = false;"],
-          all: ["if(!xi) return false;", "var accum = true;"],
-          sum: ["accum += xi;", "var accum = 0;"],
-          prod: ["accum *= xi;", "var accum = 1;"],
-          norm2Squared: ["accum += xi*xi;", "var accum = 0;"],
-          norminf: [
-            "accum = max(accum,abs(xi));",
-            "var accum = 0, max = Math.max, abs = Math.abs;",
-          ],
-          norm1: ["accum += abs(xi)", "var accum = 0, abs = Math.abs;"],
-          sup: ["accum = max(accum,xi);", "var accum = -Infinity, max = Math.max;"],
-          inf: ["accum = min(accum,xi);", "var accum = Infinity, min = Math.min;"],
-        };
-
-        (function () {
-          var i, o;
-          for (i = 0; i < numeric.mathfuns2.length; ++i) {
-            o = numeric.mathfuns2[i];
-            numeric.ops2[o] = o;
-          }
-          for (i in numeric.ops2) {
-            if (numeric.ops2.hasOwnProperty(i)) {
-              o = numeric.ops2[i];
-              var code,
-                codeeq,
-                setup = "";
-              if (numeric.myIndexOf.call(numeric.mathfuns2, i) !== -1) {
-                setup = "var " + o + " = Math." + o + ";\n";
-                code = function (r, x, y) {
-                  return r + " = " + o + "(" + x + "," + y + ")";
-                };
-                codeeq = function (x, y) {
-                  return x + " = " + o + "(" + x + "," + y + ")";
-                };
-              } else {
-                code = function (r, x, y) {
-                  return r + " = " + x + " " + o + " " + y;
-                };
-                if (numeric.opseq.hasOwnProperty(i + "eq")) {
-                  codeeq = function (x, y) {
-                    return x + " " + o + "= " + y;
-                  };
-                } else {
-                  codeeq = function (x, y) {
-                    return x + " = " + x + " " + o + " " + y;
-                  };
-                }
-              }
-              numeric[i + "VV"] = numeric.pointwise2(
-                ["x[i]", "y[i]"],
-                code("ret[i]", "x[i]", "y[i]"),
-                setup
-              );
-              numeric[i + "SV"] = numeric.pointwise2(
-                ["x", "y[i]"],
-                code("ret[i]", "x", "y[i]"),
-                setup
-              );
-              numeric[i + "VS"] = numeric.pointwise2(
-                ["x[i]", "y"],
-                code("ret[i]", "x[i]", "y"),
-                setup
-              );
-              numeric[i] = Function(
-                "var n = arguments.length, i, x = arguments[0], y;\n" +
-                  "var VV = numeric." +
-                  i +
-                  "VV, VS = numeric." +
-                  i +
-                  "VS, SV = numeric." +
-                  i +
-                  "SV;\n" +
-                  "var dim = numeric.dim;\n" +
-                  "for(i=1;i!==n;++i) { \n" +
-                  "  y = arguments[i];\n" +
-                  '  if(typeof x === "object") {\n' +
-                  '      if(typeof y === "object") x = numeric._biforeach2(x,y,dim(x),0,VV);\n' +
-                  "      else x = numeric._biforeach2(x,y,dim(x),0,VS);\n" +
-                  '  } else if(typeof y === "object") x = numeric._biforeach2(x,y,dim(y),0,SV);\n' +
-                  "  else " +
-                  codeeq("x", "y") +
-                  "\n" +
-                  "}\nreturn x;\n"
-              );
-              numeric[o] = numeric[i];
-              numeric[i + "eqV"] = numeric.pointwise2(
-                ["ret[i]", "x[i]"],
-                codeeq("ret[i]", "x[i]"),
-                setup
-              );
-              numeric[i + "eqS"] = numeric.pointwise2(
-                ["ret[i]", "x"],
-                codeeq("ret[i]", "x"),
-                setup
-              );
-              numeric[i + "eq"] = Function(
-                "var n = arguments.length, i, x = arguments[0], y;\n" +
-                  "var V = numeric." +
-                  i +
-                  "eqV, S = numeric." +
-                  i +
-                  "eqS\n" +
-                  "var s = numeric.dim(x);\n" +
-                  "for(i=1;i!==n;++i) { \n" +
-                  "  y = arguments[i];\n" +
-                  '  if(typeof y === "object") numeric._biforeach(x,y,s,0,V);\n' +
-                  "  else numeric._biforeach(x,y,s,0,S);\n" +
-                  "}\nreturn x;\n"
-              );
-            }
-          }
-          for (i = 0; i < numeric.mathfuns2.length; ++i) {
-            o = numeric.mathfuns2[i];
-            delete numeric.ops2[o];
-          }
-          for (i = 0; i < numeric.mathfuns.length; ++i) {
-            o = numeric.mathfuns[i];
-            numeric.ops1[o] = o;
-          }
-          for (i in numeric.ops1) {
-            if (numeric.ops1.hasOwnProperty(i)) {
-              setup = "";
-              o = numeric.ops1[i];
-              if (numeric.myIndexOf.call(numeric.mathfuns, i) !== -1) {
-                if (Math.hasOwnProperty(o)) setup = "var " + o + " = Math." + o + ";\n";
-              }
-              numeric[i + "eqV"] = numeric.pointwise2(
-                ["ret[i]"],
-                "ret[i] = " + o + "(ret[i]);",
-                setup
-              );
-              numeric[i + "eq"] = Function(
-                "x",
-                'if(typeof x !== "object") return ' +
-                  o +
-                  "x\n" +
-                  "var i;\n" +
-                  "var V = numeric." +
-                  i +
-                  "eqV;\n" +
-                  "var s = numeric.dim(x);\n" +
-                  "numeric._foreach(x,s,0,V);\n" +
-                  "return x;\n"
-              );
-              numeric[i + "V"] = numeric.pointwise2(["x[i]"], "ret[i] = " + o + "(x[i]);", setup);
-              numeric[i] = Function(
-                "x",
-                'if(typeof x !== "object") return ' +
-                  o +
-                  "(x)\n" +
-                  "var i;\n" +
-                  "var V = numeric." +
-                  i +
-                  "V;\n" +
-                  "var s = numeric.dim(x);\n" +
-                  "return numeric._foreach2(x,s,0,V);\n"
-              );
-            }
-          }
-          for (i = 0; i < numeric.mathfuns.length; ++i) {
-            o = numeric.mathfuns[i];
-            delete numeric.ops1[o];
-          }
-          for (i in numeric.mapreducers) {
-            if (numeric.mapreducers.hasOwnProperty(i)) {
-              o = numeric.mapreducers[i];
-              numeric[i + "V"] = numeric.mapreduce2(o[0], o[1]);
-              numeric[i] = Function(
-                "x",
-                "s",
-                "k",
-                o[1] +
-                  'if(typeof x !== "object") {' +
-                  "    xi = x;\n" +
-                  o[0] +
-                  ";\n" +
-                  "    return accum;\n" +
-                  "}" +
-                  'if(typeof s === "undefined") s = numeric.dim(x);\n' +
-                  'if(typeof k === "undefined") k = 0;\n' +
-                  "if(k === s.length-1) return numeric." +
-                  i +
-                  "V(x);\n" +
-                  "var xi;\n" +
-                  "var n = x.length, i;\n" +
-                  "for(i=n-1;i!==-1;--i) {\n" +
-                  "   xi = arguments.callee(x[i]);\n" +
-                  o[0] +
-                  ";\n" +
-                  "}\n" +
-                  "return accum;\n"
-              );
-            }
-          }
-        })();
-
-        numeric.truncVV = numeric.pointwise(
-          ["x[i]", "y[i]"],
-          "ret[i] = round(x[i]/y[i])*y[i];",
-          "var round = Math.round;"
-        );
-        numeric.truncVS = numeric.pointwise(
-          ["x[i]", "y"],
-          "ret[i] = round(x[i]/y)*y;",
-          "var round = Math.round;"
-        );
-        numeric.truncSV = numeric.pointwise(
-          ["x", "y[i]"],
-          "ret[i] = round(x/y[i])*y[i];",
-          "var round = Math.round;"
-        );
-        numeric.trunc = function trunc(x, y) {
-          if (typeof x === "object") {
-            if (typeof y === "object") return numeric.truncVV(x, y);
-            return numeric.truncVS(x, y);
-          }
-          if (typeof y === "object") return numeric.truncSV(x, y);
-          return Math.round(x / y) * y;
-        };
-
-        numeric.inv = function inv(x) {
-          var s = numeric.dim(x),
-            abs = Math.abs,
-            m = s[0],
-            n = s[1];
-          var A = numeric.clone(x),
-            Ai,
-            Aj;
-          var I = numeric.identity(m),
-            Ii,
-            Ij;
-          var i, j, k, x;
-          for (j = 0; j < n; ++j) {
-            var i0 = -1;
-            var v0 = -1;
-            for (i = j; i !== m; ++i) {
-              k = abs(A[i][j]);
-              if (k > v0) {
-                i0 = i;
-                v0 = k;
-              }
-            }
-            Aj = A[i0];
-            A[i0] = A[j];
-            A[j] = Aj;
-            Ij = I[i0];
-            I[i0] = I[j];
-            I[j] = Ij;
-            x = Aj[j];
-            for (k = j; k !== n; ++k) Aj[k] /= x;
-            for (k = n - 1; k !== -1; --k) Ij[k] /= x;
-            for (i = m - 1; i !== -1; --i) {
-              if (i !== j) {
-                Ai = A[i];
-                Ii = I[i];
-                x = Ai[j];
-                for (k = j + 1; k !== n; ++k) Ai[k] -= Aj[k] * x;
-                for (k = n - 1; k > 0; --k) {
-                  Ii[k] -= Ij[k] * x;
-                  --k;
-                  Ii[k] -= Ij[k] * x;
-                }
-                if (k === 0) Ii[0] -= Ij[0] * x;
-              }
-            }
-          }
-          return I;
-        };
-
-        numeric.det = function det(x) {
-          var s = numeric.dim(x);
-          if (s.length !== 2 || s[0] !== s[1]) {
-            throw new Error("numeric: det() only works on square matrices");
-          }
-          var n = s[0],
-            ret = 1,
-            i,
-            j,
-            k,
-            A = numeric.clone(x),
-            Aj,
-            Ai,
-            alpha,
-            temp,
-            k1,
-            k2,
-            k3;
-          for (j = 0; j < n - 1; j++) {
-            k = j;
-            for (i = j + 1; i < n; i++) {
-              if (Math.abs(A[i][j]) > Math.abs(A[k][j])) {
-                k = i;
-              }
-            }
-            if (k !== j) {
-              temp = A[k];
-              A[k] = A[j];
-              A[j] = temp;
-              ret *= -1;
-            }
-            Aj = A[j];
-            for (i = j + 1; i < n; i++) {
-              Ai = A[i];
-              alpha = Ai[j] / Aj[j];
-              for (k = j + 1; k < n - 1; k += 2) {
-                k1 = k + 1;
-                Ai[k] -= Aj[k] * alpha;
-                Ai[k1] -= Aj[k1] * alpha;
-              }
-              if (k !== n) {
-                Ai[k] -= Aj[k] * alpha;
-              }
-            }
-            if (Aj[j] === 0) {
-              return 0;
-            }
-            ret *= Aj[j];
-          }
-          return ret * A[j][j];
-        };
-
-        numeric.transpose = function transpose(x) {
-          var i,
-            j,
-            m = x.length,
-            n = x[0].length,
-            ret = Array(n),
-            A0,
-            A1,
-            Bj;
-          for (j = 0; j < n; j++) ret[j] = Array(m);
-          for (i = m - 1; i >= 1; i -= 2) {
-            A1 = x[i];
-            A0 = x[i - 1];
-            for (j = n - 1; j >= 1; --j) {
-              Bj = ret[j];
-              Bj[i] = A1[j];
-              Bj[i - 1] = A0[j];
-              --j;
-              Bj = ret[j];
-              Bj[i] = A1[j];
-              Bj[i - 1] = A0[j];
-            }
-            if (j === 0) {
-              Bj = ret[0];
-              Bj[i] = A1[0];
-              Bj[i - 1] = A0[0];
-            }
-          }
-          if (i === 0) {
-            A0 = x[0];
-            for (j = n - 1; j >= 1; --j) {
-              ret[j][0] = A0[j];
-              --j;
-              ret[j][0] = A0[j];
-            }
-            if (j === 0) {
-              ret[0][0] = A0[0];
-            }
-          }
-          return ret;
-        };
-        numeric.negtranspose = function negtranspose(x) {
-          var i,
-            j,
-            m = x.length,
-            n = x[0].length,
-            ret = Array(n),
-            A0,
-            A1,
-            Bj;
-          for (j = 0; j < n; j++) ret[j] = Array(m);
-          for (i = m - 1; i >= 1; i -= 2) {
-            A1 = x[i];
-            A0 = x[i - 1];
-            for (j = n - 1; j >= 1; --j) {
-              Bj = ret[j];
-              Bj[i] = -A1[j];
-              Bj[i - 1] = -A0[j];
-              --j;
-              Bj = ret[j];
-              Bj[i] = -A1[j];
-              Bj[i - 1] = -A0[j];
-            }
-            if (j === 0) {
-              Bj = ret[0];
-              Bj[i] = -A1[0];
-              Bj[i - 1] = -A0[0];
-            }
-          }
-          if (i === 0) {
-            A0 = x[0];
-            for (j = n - 1; j >= 1; --j) {
-              ret[j][0] = -A0[j];
-              --j;
-              ret[j][0] = -A0[j];
-            }
-            if (j === 0) {
-              ret[0][0] = -A0[0];
-            }
-          }
-          return ret;
-        };
-
-        numeric._random = function _random(s, k) {
-          var i,
-            n = s[k],
-            ret = Array(n),
-            rnd;
-          if (k === s.length - 1) {
-            rnd = Math.random;
-            for (i = n - 1; i >= 1; i -= 2) {
-              ret[i] = rnd();
-              ret[i - 1] = rnd();
-            }
-            if (i === 0) {
-              ret[0] = rnd();
-            }
-            return ret;
-          }
-          for (i = n - 1; i >= 0; i--) ret[i] = _random(s, k + 1);
-          return ret;
-        };
-        numeric.random = function random(s) {
-          return numeric._random(s, 0);
-        };
-
-        numeric.norm2 = function norm2(x) {
-          return Math.sqrt(numeric.norm2Squared(x));
-        };
-
-        numeric.linspace = function linspace(a, b, n) {
-          if (typeof n === "undefined") n = Math.max(Math.round(b - a) + 1, 1);
-          if (n < 2) {
-            return n === 1 ? [a] : [];
-          }
-          var i,
-            ret = Array(n);
-          n--;
-          for (i = n; i >= 0; i--) {
-            ret[i] = (i * b + (n - i) * a) / n;
-          }
-          return ret;
-        };
-
-        numeric.getBlock = function getBlock(x, from, to) {
-          var s = numeric.dim(x);
-          function foo(x, k) {
-            var i,
-              a = from[k],
-              n = to[k] - a,
-              ret = Array(n);
-            if (k === s.length - 1) {
-              for (i = n; i >= 0; i--) {
-                ret[i] = x[i + a];
-              }
-              return ret;
-            }
-            for (i = n; i >= 0; i--) {
-              ret[i] = foo(x[i + a], k + 1);
-            }
-            return ret;
-          }
-          return foo(x, 0);
-        };
-
-        numeric.setBlock = function setBlock(x, from, to, B) {
-          var s = numeric.dim(x);
-          function foo(x, y, k) {
-            var i,
-              a = from[k],
-              n = to[k] - a;
-            if (k === s.length - 1) {
-              for (i = n; i >= 0; i--) {
-                x[i + a] = y[i];
-              }
-            }
-            for (i = n; i >= 0; i--) {
-              foo(x[i + a], y[i], k + 1);
-            }
-          }
-          foo(x, B, 0);
-          return x;
-        };
-
-        numeric.getRange = function getRange(A, I, J) {
-          var m = I.length,
-            n = J.length;
-          var i, j;
-          var B = Array(m),
-            Bi,
-            AI;
-          for (i = m - 1; i !== -1; --i) {
-            B[i] = Array(n);
-            Bi = B[i];
-            AI = A[I[i]];
-            for (j = n - 1; j !== -1; --j) Bi[j] = AI[J[j]];
-          }
-          return B;
-        };
-
-        numeric.blockMatrix = function blockMatrix(X) {
-          var s = numeric.dim(X);
-          if (s.length < 4) return numeric.blockMatrix([X]);
-          var m = s[0],
-            n = s[1],
-            M,
-            N,
-            i,
-            j,
-            Xij;
-          M = 0;
-          N = 0;
-          for (i = 0; i < m; ++i) M += X[i][0].length;
-          for (j = 0; j < n; ++j) N += X[0][j][0].length;
-          var Z = Array(M);
-          for (i = 0; i < M; ++i) Z[i] = Array(N);
-          var I = 0,
-            J,
-            ZI,
-            k,
-            l,
-            Xijk;
-          for (i = 0; i < m; ++i) {
-            J = N;
-            for (j = n - 1; j !== -1; --j) {
-              Xij = X[i][j];
-              J -= Xij[0].length;
-              for (k = Xij.length - 1; k !== -1; --k) {
-                Xijk = Xij[k];
-                ZI = Z[I + k];
-                for (l = Xijk.length - 1; l !== -1; --l) ZI[J + l] = Xijk[l];
-              }
-            }
-            I += X[i][0].length;
-          }
-          return Z;
-        };
-
-        numeric.tensor = function tensor(x, y) {
-          if (typeof x === "number" || typeof y === "number") return numeric.mul(x, y);
-          var s1 = numeric.dim(x),
-            s2 = numeric.dim(y);
-          if (s1.length !== 1 || s2.length !== 1) {
-            throw new Error("numeric: tensor product is only defined for vectors");
-          }
-          var m = s1[0],
-            n = s2[0],
-            A = Array(m),
-            Ai,
-            i,
-            j,
-            xi;
-          for (i = m - 1; i >= 0; i--) {
-            Ai = Array(n);
-            xi = x[i];
-            for (j = n - 1; j >= 3; --j) {
-              Ai[j] = xi * y[j];
-              --j;
-              Ai[j] = xi * y[j];
-              --j;
-              Ai[j] = xi * y[j];
-              --j;
-              Ai[j] = xi * y[j];
-            }
-            while (j >= 0) {
-              Ai[j] = xi * y[j];
-              --j;
-            }
-            A[i] = Ai;
-          }
-          return A;
-        };
-
-        // 3. The Tensor type T
-        numeric.T = function T(x, y) {
-          this.x = x;
-          this.y = y;
-        };
-        numeric.t = function t(x, y) {
-          return new numeric.T(x, y);
-        };
-
-        numeric.Tbinop = function Tbinop(rr, rc, cr, cc, setup) {
-          var io = numeric.indexOf;
-          if (typeof setup !== "string") {
-            var k;
-            setup = "";
-            for (k in numeric) {
-              if (
-                numeric.hasOwnProperty(k) &&
-                (rr.indexOf(k) >= 0 ||
-                  rc.indexOf(k) >= 0 ||
-                  cr.indexOf(k) >= 0 ||
-                  cc.indexOf(k) >= 0) &&
-                k.length > 1
-              ) {
-                setup += "var " + k + " = numeric." + k + ";\n";
-              }
-            }
-          }
-          return Function(
-            ["y"],
-            "var x = this;\n" +
-              "if(!(y instanceof numeric.T)) { y = new numeric.T(y); }\n" +
-              setup +
-              "\n" +
-              "if(x.y) {" +
-              "  if(y.y) {" +
-              "    return new numeric.T(" +
-              cc +
-              ");\n" +
-              "  }\n" +
-              "  return new numeric.T(" +
-              cr +
-              ");\n" +
-              "}\n" +
-              "if(y.y) {\n" +
-              "  return new numeric.T(" +
-              rc +
-              ");\n" +
-              "}\n" +
-              "return new numeric.T(" +
-              rr +
-              ");\n"
-          );
-        };
-
-        numeric.T.prototype.add = numeric.Tbinop(
-          "add(x.x,y.x)",
-          "add(x.x,y.x),y.y",
-          "add(x.x,y.x),x.y",
-          "add(x.x,y.x),add(x.y,y.y)"
-        );
-        numeric.T.prototype.sub = numeric.Tbinop(
-          "sub(x.x,y.x)",
-          "sub(x.x,y.x),neg(y.y)",
-          "sub(x.x,y.x),x.y",
-          "sub(x.x,y.x),sub(x.y,y.y)"
-        );
-        numeric.T.prototype.mul = numeric.Tbinop(
-          "mul(x.x,y.x)",
-          "mul(x.x,y.x),mul(x.x,y.y)",
-          "mul(x.x,y.x),mul(x.y,y.x)",
-          "sub(mul(x.x,y.x),mul(x.y,y.y)),add(mul(x.x,y.y),mul(x.y,y.x))"
-        );
-
-        numeric.T.prototype.reciprocal = function reciprocal() {
-          var mul = numeric.mul,
-            div = numeric.div;
-          if (this.y) {
-            var d = numeric.add(mul(this.x, this.x), mul(this.y, this.y));
-            return new numeric.T(div(this.x, d), div(numeric.neg(this.y), d));
-          }
-          return new T(div(1, this.x));
-        };
-        numeric.T.prototype.div = function div(y) {
-          if (!(y instanceof numeric.T)) y = new numeric.T(y);
-          if (y.y) {
-            return this.mul(y.reciprocal());
-          }
-          var div = numeric.div;
-          if (this.y) {
-            return new numeric.T(div(this.x, y.x), div(this.y, y.x));
-          }
-          return new numeric.T(div(this.x, y.x));
-        };
-        numeric.T.prototype.dot = numeric.Tbinop(
-          "dot(x.x,y.x)",
-          "dot(x.x,y.x),dot(x.x,y.y)",
-          "dot(x.x,y.x),dot(x.y,y.x)",
-          "sub(dot(x.x,y.x),dot(x.y,y.y)),add(dot(x.x,y.y),dot(x.y,y.x))"
-        );
-        numeric.T.prototype.transpose = function transpose() {
-          var t = numeric.transpose,
-            x = this.x,
-            y = this.y;
-          if (y) {
-            return new numeric.T(t(x), t(y));
-          }
-          return new numeric.T(t(x));
-        };
-        numeric.T.prototype.transjugate = function transjugate() {
-          var t = numeric.transpose,
-            x = this.x,
-            y = this.y;
-          if (y) {
-            return new numeric.T(t(x), numeric.negtranspose(y));
-          }
-          return new numeric.T(t(x));
-        };
-        numeric.Tunop = function Tunop(r, c, s) {
-          if (typeof s !== "string") {
-            s = "";
-          }
-          return Function(
-            "var x = this;\n" + s + "\n" + "if(x.y) {" + "  " + c + ";\n" + "}\n" + r + ";\n"
-          );
-        };
-
-        numeric.T.prototype.exp = numeric.Tunop(
-          "return new numeric.T(ex)",
-          "return new numeric.T(mul(cos(x.y),ex),mul(sin(x.y),ex))",
-          "var ex = numeric.exp(x.x), cos = numeric.cos, sin = numeric.sin, mul = numeric.mul;"
-        );
-        numeric.T.prototype.conj = numeric.Tunop(
-          "return new numeric.T(x.x);",
-          "return new numeric.T(x.x,numeric.neg(x.y));"
-        );
-        numeric.T.prototype.neg = numeric.Tunop(
-          "return new numeric.T(neg(x.x));",
-          "return new numeric.T(neg(x.x),neg(x.y));",
-          "var neg = numeric.neg;"
-        );
-        numeric.T.prototype.sin = numeric.Tunop(
-          "return new numeric.T(numeric.sin(x.x))",
-          "return x.exp().sub(x.neg().exp()).div(new numeric.T(0,2));"
-        );
-        numeric.T.prototype.cos = numeric.Tunop(
-          "return new numeric.T(numeric.cos(x.x))",
-          "return x.exp().add(x.neg().exp()).div(2);"
-        );
-        numeric.T.prototype.abs = numeric.Tunop(
-          "return new numeric.T(numeric.abs(x.x));",
-          "return new numeric.T(numeric.sqrt(numeric.add(mul(x.x,x.x),mul(x.y,x.y))));",
-          "var mul = numeric.mul;"
-        );
-        numeric.T.prototype.log = numeric.Tunop(
-          "return new numeric.T(numeric.log(x.x));",
-          "var theta = new numeric.T(numeric.atan2(x.y,x.x)), r = x.abs();\n" +
-            "return new numeric.T(numeric.log(r.x),theta.x);"
-        );
-        numeric.T.prototype.norm2 = numeric.Tunop(
-          "return numeric.norm2(x.x);",
-          "var f = numeric.norm2Squared;\n" + "return Math.sqrt(f(x.x)+f(x.y));"
-        );
-        numeric.T.prototype.inv = function inv() {
-          var A = this;
-          if (typeof A.y === "undefined") {
-            return new numeric.T(numeric.inv(A.x));
-          }
-          var n = A.x.length,
-            i,
-            j,
-            k;
-          var Rx = numeric.identity(n),
-            Ry = numeric.rep([n, n], 0);
-          var Ax = numeric.clone(A.x),
-            Ay = numeric.clone(A.y);
-          var Aix, Aiy, Ajx, Ajy, Rix, Riy, Rjx, Rjy;
-          var i, j, k, d, d1, ax, ay, bx, by, temp;
-          for (i = 0; i < n; i++) {
-            ax = Ax[i][i];
-            ay = Ay[i][i];
-            d = ax * ax + ay * ay;
-            k = i;
-            for (j = i + 1; j < n; j++) {
-              ax = Ax[j][i];
-              ay = Ay[j][i];
-              d1 = ax * ax + ay * ay;
-              if (d1 > d) {
-                k = j;
-                d = d1;
-              }
-            }
-            if (k !== i) {
-              temp = Ax[i];
-              Ax[i] = Ax[k];
-              Ax[k] = temp;
-              temp = Ay[i];
-              Ay[i] = Ay[k];
-              Ay[k] = temp;
-              temp = Rx[i];
-              Rx[i] = Rx[k];
-              Rx[k] = temp;
-              temp = Ry[i];
-              Ry[i] = Ry[k];
-              Ry[k] = temp;
-            }
-            Aix = Ax[i];
-            Aiy = Ay[i];
-            Rix = Rx[i];
-            Riy = Ry[i];
-            ax = Aix[i];
-            ay = Aiy[i];
-            for (j = i + 1; j < n; j++) {
-              bx = Aix[j];
-              by = Aiy[j];
-              Aix[j] = (bx * ax + by * ay) / d;
-              Aiy[j] = (by * ax - bx * ay) / d;
-            }
-            for (j = 0; j < n; j++) {
-              bx = Rix[j];
-              by = Riy[j];
-              Rix[j] = (bx * ax + by * ay) / d;
-              Riy[j] = (by * ax - bx * ay) / d;
-            }
-            for (j = i + 1; j < n; j++) {
-              Ajx = Ax[j];
-              Ajy = Ay[j];
-              Rjx = Rx[j];
-              Rjy = Ry[j];
-              ax = Ajx[i];
-              ay = Ajy[i];
-              for (k = i + 1; k < n; k++) {
-                bx = Aix[k];
-                by = Aiy[k];
-                Ajx[k] -= bx * ax - by * ay;
-                Ajy[k] -= by * ax + bx * ay;
-              }
-              for (k = 0; k < n; k++) {
-                bx = Rix[k];
-                by = Riy[k];
-                Rjx[k] -= bx * ax - by * ay;
-                Rjy[k] -= by * ax + bx * ay;
-              }
-            }
-          }
-          for (i = n - 1; i > 0; i--) {
-            Rix = Rx[i];
-            Riy = Ry[i];
-            for (j = i - 1; j >= 0; j--) {
-              Rjx = Rx[j];
-              Rjy = Ry[j];
-              ax = Ax[j][i];
-              ay = Ay[j][i];
-              for (k = n - 1; k >= 0; k--) {
-                bx = Rix[k];
-                by = Riy[k];
-                Rjx[k] -= ax * bx - ay * by;
-                Rjy[k] -= ax * by + ay * bx;
-              }
-            }
-          }
-          return new numeric.T(Rx, Ry);
-        };
-        numeric.T.prototype.get = function get(i) {
-          var x = this.x,
-            y = this.y,
-            k = 0,
-            ik,
-            n = i.length;
-          if (y) {
-            while (k < n) {
-              ik = i[k];
-              x = x[ik];
-              y = y[ik];
-              k++;
-            }
-            return new numeric.T(x, y);
-          }
-          while (k < n) {
-            ik = i[k];
-            x = x[ik];
-            k++;
-          }
-          return new numeric.T(x);
-        };
-        numeric.T.prototype.set = function set(i, v) {
-          var x = this.x,
-            y = this.y,
-            k = 0,
-            ik,
-            n = i.length,
-            vx = v.x,
-            vy = v.y;
-          if (n === 0) {
-            if (vy) {
-              this.y = vy;
-            } else if (y) {
-              this.y = undefined;
-            }
-            this.x = x;
-            return this;
-          }
-          if (vy) {
-            if (y) {
-              /* ok */
-            } else {
-              y = numeric.rep(numeric.dim(x), 0);
-              this.y = y;
-            }
-            while (k < n - 1) {
-              ik = i[k];
-              x = x[ik];
-              y = y[ik];
-              k++;
-            }
-            ik = i[k];
-            x[ik] = vx;
-            y[ik] = vy;
-            return this;
-          }
-          if (y) {
-            while (k < n - 1) {
-              ik = i[k];
-              x = x[ik];
-              y = y[ik];
-              k++;
-            }
-            ik = i[k];
-            x[ik] = vx;
-            if (vx instanceof Array) y[ik] = numeric.rep(numeric.dim(vx), 0);
-            else y[ik] = 0;
-            return this;
-          }
-          while (k < n - 1) {
-            ik = i[k];
-            x = x[ik];
-            k++;
-          }
-          ik = i[k];
-          x[ik] = vx;
-          return this;
-        };
-        numeric.T.prototype.getRows = function getRows(i0, i1) {
-          var n = i1 - i0 + 1,
-            j;
-          var rx = Array(n),
-            ry,
-            x = this.x,
-            y = this.y;
-          for (j = i0; j <= i1; j++) {
-            rx[j - i0] = x[j];
-          }
-          if (y) {
-            ry = Array(n);
-            for (j = i0; j <= i1; j++) {
-              ry[j - i0] = y[j];
-            }
-            return new numeric.T(rx, ry);
-          }
-          return new numeric.T(rx);
-        };
-        numeric.T.prototype.setRows = function setRows(i0, i1, A) {
-          var j;
-          var rx = this.x,
-            ry = this.y,
-            x = A.x,
-            y = A.y;
-          for (j = i0; j <= i1; j++) {
-            rx[j] = x[j - i0];
-          }
-          if (y) {
-            if (!ry) {
-              ry = numeric.rep(numeric.dim(rx), 0);
-              this.y = ry;
-            }
-            for (j = i0; j <= i1; j++) {
-              ry[j] = y[j - i0];
-            }
-          } else if (ry) {
-            for (j = i0; j <= i1; j++) {
-              ry[j] = numeric.rep([x[j - i0].length], 0);
-            }
-          }
-          return this;
-        };
-        numeric.T.prototype.getRow = function getRow(k) {
-          var x = this.x,
-            y = this.y;
-          if (y) {
-            return new numeric.T(x[k], y[k]);
-          }
-          return new numeric.T(x[k]);
-        };
-        numeric.T.prototype.setRow = function setRow(i, v) {
-          var rx = this.x,
-            ry = this.y,
-            x = v.x,
-            y = v.y;
-          rx[i] = x;
-          if (y) {
-            if (!ry) {
-              ry = numeric.rep(numeric.dim(rx), 0);
-              this.y = ry;
-            }
-            ry[i] = y;
-          } else if (ry) {
-            ry = numeric.rep([x.length], 0);
-          }
-          return this;
-        };
-
-        numeric.T.prototype.getBlock = function getBlock(from, to) {
-          var x = this.x,
-            y = this.y,
-            b = numeric.getBlock;
-          if (y) {
-            return new numeric.T(b(x, from, to), b(y, from, to));
-          }
-          return new numeric.T(b(x, from, to));
-        };
-        numeric.T.prototype.setBlock = function setBlock(from, to, A) {
-          if (!(A instanceof numeric.T)) A = new numeric.T(A);
-          var x = this.x,
-            y = this.y,
-            b = numeric.setBlock,
-            Ax = A.x,
-            Ay = A.y;
-          if (Ay) {
-            if (!y) {
-              this.y = numeric.rep(numeric.dim(this), 0);
-              y = this.y;
-            }
-            b(x, from, to, Ax);
-            b(y, from, to, Ay);
-            return this;
-          }
-          b(x, from, to, Ax);
-          if (y) b(y, from, to, numeric.rep(numeric.dim(Ax), 0));
-        };
-        numeric.T.rep = function rep(s, v) {
-          var T = numeric.T;
-          if (!(v instanceof T)) v = new T(v);
-          var x = v.x,
-            y = v.y,
-            r = numeric.rep;
-          if (y) return new T(r(s, x), r(s, y));
-          return new T(r(s, x));
-        };
-        numeric.T.diag = function diag(d) {
-          if (!(d instanceof numeric.T)) d = new numeric.T(d);
-          var x = d.x,
-            y = d.y,
-            diag = numeric.diag;
-          if (y) return new numeric.T(diag(x), diag(y));
-          return new numeric.T(diag(x));
-        };
-        numeric.T.eig = function eig() {
-          if (this.y) {
-            throw new Error("eig: not implemented for complex matrices.");
-          }
-          return numeric.eig(this.x);
-        };
-        numeric.T.identity = function identity(n) {
-          return new numeric.T(numeric.identity(n));
-        };
-        numeric.T.prototype.getDiag = function getDiag() {
-          var n = numeric;
-          var x = this.x,
-            y = this.y;
-          if (y) {
-            return new n.T(n.getDiag(x), n.getDiag(y));
-          }
-          return new n.T(n.getDiag(x));
-        };
-
-        // 4. Eigenvalues of real matrices
-
-        numeric.house = function house(x) {
-          var v = numeric.clone(x);
-          var s = x[0] >= 0 ? 1 : -1;
-          var alpha = s * numeric.norm2(x);
-          v[0] += alpha;
-          var foo = numeric.norm2(v);
-          if (foo === 0) {
-            /* this should not happen */ throw new Error("eig: internal error");
-          }
-          return numeric.div(v, foo);
-        };
-
-        numeric.toUpperHessenberg = function toUpperHessenberg(me) {
-          var s = numeric.dim(me);
-          if (s.length !== 2 || s[0] !== s[1]) {
-            throw new Error("numeric: toUpperHessenberg() only works on square matrices");
-          }
-          var m = s[0],
-            i,
-            j,
-            k,
-            x,
-            v,
-            A = numeric.clone(me),
-            B,
-            C,
-            Ai,
-            Ci,
-            Q = numeric.identity(m),
-            Qi;
-          for (j = 0; j < m - 2; j++) {
-            x = Array(m - j - 1);
-            for (i = j + 1; i < m; i++) {
-              x[i - j - 1] = A[i][j];
-            }
-            if (numeric.norm2(x) > 0) {
-              v = numeric.house(x);
-              B = numeric.getBlock(A, [j + 1, j], [m - 1, m - 1]);
-              C = numeric.tensor(v, numeric.dot(v, B));
-              for (i = j + 1; i < m; i++) {
-                Ai = A[i];
-                Ci = C[i - j - 1];
-                for (k = j; k < m; k++) Ai[k] -= 2 * Ci[k - j];
-              }
-              B = numeric.getBlock(A, [0, j + 1], [m - 1, m - 1]);
-              C = numeric.tensor(numeric.dot(B, v), v);
-              for (i = 0; i < m; i++) {
-                Ai = A[i];
-                Ci = C[i];
-                for (k = j + 1; k < m; k++) Ai[k] -= 2 * Ci[k - j - 1];
-              }
-              B = Array(m - j - 1);
-              for (i = j + 1; i < m; i++) B[i - j - 1] = Q[i];
-              C = numeric.tensor(v, numeric.dot(v, B));
-              for (i = j + 1; i < m; i++) {
-                Qi = Q[i];
-                Ci = C[i - j - 1];
-                for (k = 0; k < m; k++) Qi[k] -= 2 * Ci[k];
-              }
-            }
-          }
-          return { H: A, Q: Q };
-        };
-
-        numeric.epsilon = 2.220446049250313e-16;
-
-        numeric.QRFrancis = function (H, maxiter) {
-          if (typeof maxiter === "undefined") {
-            maxiter = 10000;
-          }
-          H = numeric.clone(H);
-          var H0 = numeric.clone(H);
-          var s = numeric.dim(H),
-            m = s[0],
-            x,
-            v,
-            a,
-            b,
-            c,
-            d,
-            det,
-            tr,
-            Hloc,
-            Q = numeric.identity(m),
-            Qi,
-            Hi,
-            B,
-            C,
-            Ci,
-            i,
-            j,
-            k,
-            iter;
-          if (m < 3) {
-            return { Q: Q, B: [[0, m - 1]] };
-          }
-          var epsilon = numeric.epsilon;
-          for (iter = 0; iter < maxiter; iter++) {
-            for (j = 0; j < m - 1; j++) {
-              if (
-                Math.abs(H[j + 1][j]) <
-                epsilon * (Math.abs(H[j][j]) + Math.abs(H[j + 1][j + 1]))
-              ) {
-                var QH1 = numeric.QRFrancis(numeric.getBlock(H, [0, 0], [j, j]), maxiter);
-                var QH2 = numeric.QRFrancis(
-                  numeric.getBlock(H, [j + 1, j + 1], [m - 1, m - 1]),
-                  maxiter
-                );
-                B = Array(j + 1);
-                for (i = 0; i <= j; i++) {
-                  B[i] = Q[i];
-                }
-                C = numeric.dot(QH1.Q, B);
-                for (i = 0; i <= j; i++) {
-                  Q[i] = C[i];
-                }
-                B = Array(m - j - 1);
-                for (i = j + 1; i < m; i++) {
-                  B[i - j - 1] = Q[i];
-                }
-                C = numeric.dot(QH2.Q, B);
-                for (i = j + 1; i < m; i++) {
-                  Q[i] = C[i - j - 1];
-                }
-                return { Q: Q, B: QH1.B.concat(numeric.add(QH2.B, j + 1)) };
-              }
-            }
-            a = H[m - 2][m - 2];
-            b = H[m - 2][m - 1];
-            c = H[m - 1][m - 2];
-            d = H[m - 1][m - 1];
-            tr = a + d;
-            det = a * d - b * c;
-            Hloc = numeric.getBlock(H, [0, 0], [2, 2]);
-            if (tr * tr >= 4 * det) {
-              var s1, s2;
-              s1 = 0.5 * (tr + Math.sqrt(tr * tr - 4 * det));
-              s2 = 0.5 * (tr - Math.sqrt(tr * tr - 4 * det));
-              Hloc = numeric.add(
-                numeric.sub(numeric.dot(Hloc, Hloc), numeric.mul(Hloc, s1 + s2)),
-                numeric.diag(numeric.rep([3], s1 * s2))
-              );
-            } else {
-              Hloc = numeric.add(
-                numeric.sub(numeric.dot(Hloc, Hloc), numeric.mul(Hloc, tr)),
-                numeric.diag(numeric.rep([3], det))
-              );
-            }
-            x = [Hloc[0][0], Hloc[1][0], Hloc[2][0]];
-            v = numeric.house(x);
-            B = [H[0], H[1], H[2]];
-            C = numeric.tensor(v, numeric.dot(v, B));
-            for (i = 0; i < 3; i++) {
-              Hi = H[i];
-              Ci = C[i];
-              for (k = 0; k < m; k++) Hi[k] -= 2 * Ci[k];
-            }
-            B = numeric.getBlock(H, [0, 0], [m - 1, 2]);
-            C = numeric.tensor(numeric.dot(B, v), v);
-            for (i = 0; i < m; i++) {
-              Hi = H[i];
-              Ci = C[i];
-              for (k = 0; k < 3; k++) Hi[k] -= 2 * Ci[k];
-            }
-            B = [Q[0], Q[1], Q[2]];
-            C = numeric.tensor(v, numeric.dot(v, B));
-            for (i = 0; i < 3; i++) {
-              Qi = Q[i];
-              Ci = C[i];
-              for (k = 0; k < m; k++) Qi[k] -= 2 * Ci[k];
-            }
-            var J;
-            for (j = 0; j < m - 2; j++) {
-              for (k = j; k <= j + 1; k++) {
-                if (
-                  Math.abs(H[k + 1][k]) <
-                  epsilon * (Math.abs(H[k][k]) + Math.abs(H[k + 1][k + 1]))
-                ) {
-                  var QH1 = numeric.QRFrancis(numeric.getBlock(H, [0, 0], [k, k]), maxiter);
-                  var QH2 = numeric.QRFrancis(
-                    numeric.getBlock(H, [k + 1, k + 1], [m - 1, m - 1]),
-                    maxiter
-                  );
-                  B = Array(k + 1);
-                  for (i = 0; i <= k; i++) {
-                    B[i] = Q[i];
-                  }
-                  C = numeric.dot(QH1.Q, B);
-                  for (i = 0; i <= k; i++) {
-                    Q[i] = C[i];
-                  }
-                  B = Array(m - k - 1);
-                  for (i = k + 1; i < m; i++) {
-                    B[i - k - 1] = Q[i];
-                  }
-                  C = numeric.dot(QH2.Q, B);
-                  for (i = k + 1; i < m; i++) {
-                    Q[i] = C[i - k - 1];
-                  }
-                  return { Q: Q, B: QH1.B.concat(numeric.add(QH2.B, k + 1)) };
-                }
-              }
-              J = Math.min(m - 1, j + 3);
-              x = Array(J - j);
-              for (i = j + 1; i <= J; i++) {
-                x[i - j - 1] = H[i][j];
-              }
-              v = numeric.house(x);
-              B = numeric.getBlock(H, [j + 1, j], [J, m - 1]);
-              C = numeric.tensor(v, numeric.dot(v, B));
-              for (i = j + 1; i <= J; i++) {
-                Hi = H[i];
-                Ci = C[i - j - 1];
-                for (k = j; k < m; k++) Hi[k] -= 2 * Ci[k - j];
-              }
-              B = numeric.getBlock(H, [0, j + 1], [m - 1, J]);
-              C = numeric.tensor(numeric.dot(B, v), v);
-              for (i = 0; i < m; i++) {
-                Hi = H[i];
-                Ci = C[i];
-                for (k = j + 1; k <= J; k++) Hi[k] -= 2 * Ci[k - j - 1];
-              }
-              B = Array(J - j);
-              for (i = j + 1; i <= J; i++) B[i - j - 1] = Q[i];
-              C = numeric.tensor(v, numeric.dot(v, B));
-              for (i = j + 1; i <= J; i++) {
-                Qi = Q[i];
-                Ci = C[i - j - 1];
-                for (k = 0; k < m; k++) Qi[k] -= 2 * Ci[k];
-              }
-            }
-          }
-          throw new Error("numeric: eigenvalue iteration does not converge -- increase maxiter?");
-        };
-
-        numeric.eig = function eig(A, maxiter) {
-          var QH = numeric.toUpperHessenberg(A);
-          var QB = numeric.QRFrancis(QH.H, maxiter);
-          var T = numeric.T;
-          var n = A.length,
-            i,
-            k,
-            flag = false,
-            B = QB.B,
-            H = numeric.dot(QB.Q, numeric.dot(QH.H, numeric.transpose(QB.Q)));
-          var Q = new T(numeric.dot(QB.Q, QH.Q)),
-            Q0;
-          var m = B.length,
-            j;
-          var a, b, c, d, p1, p2, disc, x, y, p, q, n1, n2;
-          var sqrt = Math.sqrt;
-          for (k = 0; k < m; k++) {
-            i = B[k][0];
-            if (i === B[k][1]) {
-              // nothing
-            } else {
-              j = i + 1;
-              a = H[i][i];
-              b = H[i][j];
-              c = H[j][i];
-              d = H[j][j];
-              if (b === 0 && c === 0) continue;
-              p1 = -a - d;
-              p2 = a * d - b * c;
-              disc = p1 * p1 - 4 * p2;
-              if (disc >= 0) {
-                if (p1 < 0) x = -0.5 * (p1 - sqrt(disc));
-                else x = -0.5 * (p1 + sqrt(disc));
-                n1 = (a - x) * (a - x) + b * b;
-                n2 = c * c + (d - x) * (d - x);
-                if (n1 > n2) {
-                  n1 = sqrt(n1);
-                  p = (a - x) / n1;
-                  q = b / n1;
-                } else {
-                  n2 = sqrt(n2);
-                  p = c / n2;
-                  q = (d - x) / n2;
-                }
-                Q0 = new T([
-                  [q, -p],
-                  [p, q],
-                ]);
-                Q.setRows(i, j, Q0.dot(Q.getRows(i, j)));
-              } else {
-                x = -0.5 * p1;
-                y = 0.5 * sqrt(-disc);
-                n1 = (a - x) * (a - x) + b * b;
-                n2 = c * c + (d - x) * (d - x);
-                if (n1 > n2) {
-                  n1 = sqrt(n1 + y * y);
-                  p = (a - x) / n1;
-                  q = b / n1;
-                  x = 0;
-                  y /= n1;
-                } else {
-                  n2 = sqrt(n2 + y * y);
-                  p = c / n2;
-                  q = (d - x) / n2;
-                  x = y / n2;
-                  y = 0;
-                }
-                Q0 = new T(
-                  [
-                    [q, -p],
-                    [p, q],
-                  ],
-                  [
-                    [x, y],
-                    [y, -x],
-                  ]
-                );
-                Q.setRows(i, j, Q0.dot(Q.getRows(i, j)));
-              }
-            }
-          }
-          var R = Q.dot(A).dot(Q.transjugate()),
-            n = A.length,
-            E = numeric.T.identity(n);
-          for (j = 0; j < n; j++) {
-            if (j > 0) {
-              for (k = j - 1; k >= 0; k--) {
-                var Rk = R.get([k, k]),
-                  Rj = R.get([j, j]);
-                if (numeric.neq(Rk.x, Rj.x) || numeric.neq(Rk.y, Rj.y)) {
-                  x = R.getRow(k).getBlock([k], [j - 1]);
-                  y = E.getRow(j).getBlock([k], [j - 1]);
-                  E.set([j, k], R.get([k, j]).neg().sub(x.dot(y)).div(Rk.sub(Rj)));
-                } else {
-                  E.setRow(j, E.getRow(k));
-                  continue;
-                }
-              }
-            }
-          }
-          for (j = 0; j < n; j++) {
-            x = E.getRow(j);
-            E.setRow(j, x.div(x.norm2()));
-          }
-          E = E.transpose();
-          E = Q.transjugate().dot(E);
-          return { lambda: R.getDiag(), E: E };
-        };
-
-        // 5. Compressed Column Storage matrices
-        numeric.ccsSparse = function ccsSparse(A) {
-          var m = A.length,
-            n,
-            foo,
-            i,
-            j,
-            counts = [];
-          for (i = m - 1; i !== -1; --i) {
-            foo = A[i];
-            for (j in foo) {
-              j = parseInt(j);
-              while (j >= counts.length) counts[counts.length] = 0;
-              if (foo[j] !== 0) counts[j]++;
-            }
-          }
-          var n = counts.length;
-          var Ai = Array(n + 1);
-          Ai[0] = 0;
-          for (i = 0; i < n; ++i) Ai[i + 1] = Ai[i] + counts[i];
-          var Aj = Array(Ai[n]),
-            Av = Array(Ai[n]);
-          for (i = m - 1; i !== -1; --i) {
-            foo = A[i];
-            for (j in foo) {
-              if (foo[j] !== 0) {
-                counts[j]--;
-                Aj[Ai[j] + counts[j]] = i;
-                Av[Ai[j] + counts[j]] = foo[j];
-              }
-            }
-          }
-          return [Ai, Aj, Av];
-        };
-        numeric.ccsFull = function ccsFull(A) {
-          var Ai = A[0],
-            Aj = A[1],
-            Av = A[2],
-            s = numeric.ccsDim(A),
-            m = s[0],
-            n = s[1],
-            i,
-            j,
-            j0,
-            j1,
-            k;
-          var B = numeric.rep([m, n], 0);
-          for (i = 0; i < n; i++) {
-            j0 = Ai[i];
-            j1 = Ai[i + 1];
-            for (j = j0; j < j1; ++j) {
-              B[Aj[j]][i] = Av[j];
-            }
-          }
-          return B;
-        };
-        numeric.ccsTSolve = function ccsTSolve(A, b, x, bj, xj) {
-          var Ai = A[0],
-            Aj = A[1],
-            Av = A[2],
-            m = Ai.length - 1,
-            max = Math.max,
-            n = 0;
-          if (typeof bj === "undefined") x = numeric.rep([m], 0);
-          if (typeof bj === "undefined") bj = numeric.linspace(0, x.length - 1);
-          if (typeof xj === "undefined") xj = [];
-          function dfs(j) {
-            var k;
-            if (x[j] !== 0) return;
-            x[j] = 1;
-            for (k = Ai[j]; k < Ai[j + 1]; ++k) dfs(Aj[k]);
-            xj[n] = j;
-            ++n;
-          }
-          var i, j, j0, j1, k, l, l0, l1, a;
-          for (i = bj.length - 1; i !== -1; --i) {
-            dfs(bj[i]);
-          }
-          xj.length = n;
-          for (i = xj.length - 1; i !== -1; --i) {
-            x[xj[i]] = 0;
-          }
-          for (i = bj.length - 1; i !== -1; --i) {
-            j = bj[i];
-            x[j] = b[j];
-          }
-          for (i = xj.length - 1; i !== -1; --i) {
-            j = xj[i];
-            j0 = Ai[j];
-            j1 = max(Ai[j + 1], j0);
-            for (k = j0; k !== j1; ++k) {
-              if (Aj[k] === j) {
-                x[j] /= Av[k];
-                break;
-              }
-            }
-            a = x[j];
-            for (k = j0; k !== j1; ++k) {
-              l = Aj[k];
-              if (l !== j) x[l] -= a * Av[k];
-            }
-          }
-          return x;
-        };
-        numeric.ccsDFS = function ccsDFS(n) {
-          this.k = Array(n);
-          this.k1 = Array(n);
-          this.j = Array(n);
-        };
-        numeric.ccsDFS.prototype.dfs = function dfs(J, Ai, Aj, x, xj, Pinv) {
-          var m = 0,
-            foo,
-            n = xj.length;
-          var k = this.k,
-            k1 = this.k1,
-            j = this.j,
-            km,
-            k11;
-          if (x[J] !== 0) return;
-          x[J] = 1;
-          j[0] = J;
-          k[0] = km = Ai[J];
-          k1[0] = k11 = Ai[J + 1];
-          while (1) {
-            if (km >= k11) {
-              xj[n] = j[m];
-              if (m === 0) return;
-              ++n;
-              --m;
-              km = k[m];
-              k11 = k1[m];
-            } else {
-              foo = Pinv[Aj[km]];
-              if (x[foo] === 0) {
-                x[foo] = 1;
-                k[m] = km;
-                ++m;
-                j[m] = foo;
-                km = Ai[foo];
-                k1[m] = k11 = Ai[foo + 1];
-              } else ++km;
-            }
-          }
-        };
-        numeric.ccsLPSolve = function ccsLPSolve(A, B, x, xj, I, Pinv, dfs) {
-          var Ai = A[0],
-            Aj = A[1],
-            Av = A[2],
-            m = Ai.length - 1,
-            n = 0;
-          var Bi = B[0],
-            Bj = B[1],
-            Bv = B[2];
-
-          var i, i0, i1, j, J, j0, j1, k, l, l0, l1, a;
-          i0 = Bi[I];
-          i1 = Bi[I + 1];
-          xj.length = 0;
-          for (i = i0; i < i1; ++i) {
-            dfs.dfs(Pinv[Bj[i]], Ai, Aj, x, xj, Pinv);
-          }
-          for (i = xj.length - 1; i !== -1; --i) {
-            x[xj[i]] = 0;
-          }
-          for (i = i0; i !== i1; ++i) {
-            j = Pinv[Bj[i]];
-            x[j] = Bv[i];
-          }
-          for (i = xj.length - 1; i !== -1; --i) {
-            j = xj[i];
-            j0 = Ai[j];
-            j1 = Ai[j + 1];
-            for (k = j0; k < j1; ++k) {
-              if (Pinv[Aj[k]] === j) {
-                x[j] /= Av[k];
-                break;
-              }
-            }
-            a = x[j];
-            for (k = j0; k < j1; ++k) {
-              l = Pinv[Aj[k]];
-              if (l !== j) x[l] -= a * Av[k];
-            }
-          }
-          return x;
-        };
-        numeric.ccsLUP1 = function ccsLUP1(A, threshold) {
-          var m = A[0].length - 1;
-          var L = [numeric.rep([m + 1], 0), [], []],
-            U = [numeric.rep([m + 1], 0), [], []];
-          var Li = L[0],
-            Lj = L[1],
-            Lv = L[2],
-            Ui = U[0],
-            Uj = U[1],
-            Uv = U[2];
-          var x = numeric.rep([m], 0),
-            xj = numeric.rep([m], 0);
-          var i, j, k, j0, j1, a, e, c, d, K;
-          var sol = numeric.ccsLPSolve,
-            max = Math.max,
-            abs = Math.abs;
-          var P = numeric.linspace(0, m - 1),
-            Pinv = numeric.linspace(0, m - 1);
-          var dfs = new numeric.ccsDFS(m);
-          if (typeof threshold === "undefined") {
-            threshold = 1;
-          }
-          for (i = 0; i < m; ++i) {
-            sol(L, A, x, xj, i, Pinv, dfs);
-            a = -1;
-            e = -1;
-            for (j = xj.length - 1; j !== -1; --j) {
-              k = xj[j];
-              if (k <= i) continue;
-              c = abs(x[k]);
-              if (c > a) {
-                e = k;
-                a = c;
-              }
-            }
-            if (abs(x[i]) < threshold * a) {
-              j = P[i];
-              a = P[e];
-              P[i] = a;
-              Pinv[a] = i;
-              P[e] = j;
-              Pinv[j] = e;
-              a = x[i];
-              x[i] = x[e];
-              x[e] = a;
-            }
-            a = Li[i];
-            e = Ui[i];
-            d = x[i];
-            Lj[a] = P[i];
-            Lv[a] = 1;
-            ++a;
-            for (j = xj.length - 1; j !== -1; --j) {
-              k = xj[j];
-              c = x[k];
-              xj[j] = 0;
-              x[k] = 0;
-              if (k <= i) {
-                Uj[e] = k;
-                Uv[e] = c;
-                ++e;
-              } else {
-                Lj[a] = P[k];
-                Lv[a] = c / d;
-                ++a;
-              }
-            }
-            Li[i + 1] = a;
-            Ui[i + 1] = e;
-          }
-          for (j = Lj.length - 1; j !== -1; --j) {
-            Lj[j] = Pinv[Lj[j]];
-          }
-          return { L: L, U: U, P: P, Pinv: Pinv };
-        };
-        numeric.ccsDFS0 = function ccsDFS0(n) {
-          this.k = Array(n);
-          this.k1 = Array(n);
-          this.j = Array(n);
-        };
-        numeric.ccsDFS0.prototype.dfs = function dfs(J, Ai, Aj, x, xj, Pinv, P) {
-          var m = 0,
-            foo,
-            n = xj.length;
-          var k = this.k,
-            k1 = this.k1,
-            j = this.j,
-            km,
-            k11;
-          if (x[J] !== 0) return;
-          x[J] = 1;
-          j[0] = J;
-          k[0] = km = Ai[Pinv[J]];
-          k1[0] = k11 = Ai[Pinv[J] + 1];
-          while (1) {
-            if (isNaN(km)) throw new Error("Ow!");
-            if (km >= k11) {
-              xj[n] = Pinv[j[m]];
-              if (m === 0) return;
-              ++n;
-              --m;
-              km = k[m];
-              k11 = k1[m];
-            } else {
-              foo = Aj[km];
-              if (x[foo] === 0) {
-                x[foo] = 1;
-                k[m] = km;
-                ++m;
-                j[m] = foo;
-                foo = Pinv[foo];
-                km = Ai[foo];
-                k1[m] = k11 = Ai[foo + 1];
-              } else ++km;
-            }
-          }
-        };
-        numeric.ccsLPSolve0 = function ccsLPSolve0(A, B, y, xj, I, Pinv, P, dfs) {
-          var Ai = A[0],
-            Aj = A[1],
-            Av = A[2],
-            m = Ai.length - 1,
-            n = 0;
-          var Bi = B[0],
-            Bj = B[1],
-            Bv = B[2];
-
-          var i, i0, i1, j, J, j0, j1, k, l, l0, l1, a;
-          i0 = Bi[I];
-          i1 = Bi[I + 1];
-          xj.length = 0;
-          for (i = i0; i < i1; ++i) {
-            dfs.dfs(Bj[i], Ai, Aj, y, xj, Pinv, P);
-          }
-          for (i = xj.length - 1; i !== -1; --i) {
-            j = xj[i];
-            y[P[j]] = 0;
-          }
-          for (i = i0; i !== i1; ++i) {
-            j = Bj[i];
-            y[j] = Bv[i];
-          }
-          for (i = xj.length - 1; i !== -1; --i) {
-            j = xj[i];
-            l = P[j];
-            j0 = Ai[j];
-            j1 = Ai[j + 1];
-            for (k = j0; k < j1; ++k) {
-              if (Aj[k] === l) {
-                y[l] /= Av[k];
-                break;
-              }
-            }
-            a = y[l];
-            for (k = j0; k < j1; ++k) y[Aj[k]] -= a * Av[k];
-            y[l] = a;
-          }
-        };
-        numeric.ccsLUP0 = function ccsLUP0(A, threshold) {
-          var m = A[0].length - 1;
-          var L = [numeric.rep([m + 1], 0), [], []],
-            U = [numeric.rep([m + 1], 0), [], []];
-          var Li = L[0],
-            Lj = L[1],
-            Lv = L[2],
-            Ui = U[0],
-            Uj = U[1],
-            Uv = U[2];
-          var y = numeric.rep([m], 0),
-            xj = numeric.rep([m], 0);
-          var i, j, k, j0, j1, a, e, c, d, K;
-          var sol = numeric.ccsLPSolve0,
-            max = Math.max,
-            abs = Math.abs;
-          var P = numeric.linspace(0, m - 1),
-            Pinv = numeric.linspace(0, m - 1);
-          var dfs = new numeric.ccsDFS0(m);
-          if (typeof threshold === "undefined") {
-            threshold = 1;
-          }
-          for (i = 0; i < m; ++i) {
-            sol(L, A, y, xj, i, Pinv, P, dfs);
-            a = -1;
-            e = -1;
-            for (j = xj.length - 1; j !== -1; --j) {
-              k = xj[j];
-              if (k <= i) continue;
-              c = abs(y[P[k]]);
-              if (c > a) {
-                e = k;
-                a = c;
-              }
-            }
-            if (abs(y[P[i]]) < threshold * a) {
-              j = P[i];
-              a = P[e];
-              P[i] = a;
-              Pinv[a] = i;
-              P[e] = j;
-              Pinv[j] = e;
-            }
-            a = Li[i];
-            e = Ui[i];
-            d = y[P[i]];
-            Lj[a] = P[i];
-            Lv[a] = 1;
-            ++a;
-            for (j = xj.length - 1; j !== -1; --j) {
-              k = xj[j];
-              c = y[P[k]];
-              xj[j] = 0;
-              y[P[k]] = 0;
-              if (k <= i) {
-                Uj[e] = k;
-                Uv[e] = c;
-                ++e;
-              } else {
-                Lj[a] = P[k];
-                Lv[a] = c / d;
-                ++a;
-              }
-            }
-            Li[i + 1] = a;
-            Ui[i + 1] = e;
-          }
-          for (j = Lj.length - 1; j !== -1; --j) {
-            Lj[j] = Pinv[Lj[j]];
-          }
-          return { L: L, U: U, P: P, Pinv: Pinv };
-        };
-        numeric.ccsLUP = numeric.ccsLUP0;
-
-        numeric.ccsDim = function ccsDim(A) {
-          return [numeric.sup(A[1]) + 1, A[0].length - 1];
-        };
-        numeric.ccsGetBlock = function ccsGetBlock(A, i, j) {
-          var s = numeric.ccsDim(A),
-            m = s[0],
-            n = s[1];
-          if (typeof i === "undefined") {
-            i = numeric.linspace(0, m - 1);
-          } else if (typeof i === "number") {
-            i = [i];
-          }
-          if (typeof j === "undefined") {
-            j = numeric.linspace(0, n - 1);
-          } else if (typeof j === "number") {
-            j = [j];
-          }
-          var p,
-            p0,
-            p1,
-            P = i.length,
-            q,
-            Q = j.length,
-            r,
-            jq,
-            ip;
-          var Bi = numeric.rep([n], 0),
-            Bj = [],
-            Bv = [],
-            B = [Bi, Bj, Bv];
-          var Ai = A[0],
-            Aj = A[1],
-            Av = A[2];
-          var x = numeric.rep([m], 0),
-            count = 0,
-            flags = numeric.rep([m], 0);
-          for (q = 0; q < Q; ++q) {
-            jq = j[q];
-            var q0 = Ai[jq];
-            var q1 = Ai[jq + 1];
-            for (p = q0; p < q1; ++p) {
-              r = Aj[p];
-              flags[r] = 1;
-              x[r] = Av[p];
-            }
-            for (p = 0; p < P; ++p) {
-              ip = i[p];
-              if (flags[ip]) {
-                Bj[count] = p;
-                Bv[count] = x[i[p]];
-                ++count;
-              }
-            }
-            for (p = q0; p < q1; ++p) {
-              r = Aj[p];
-              flags[r] = 0;
-            }
-            Bi[q + 1] = count;
-          }
-          return B;
-        };
-
-        numeric.ccsDot = function ccsDot(A, B) {
-          var Ai = A[0],
-            Aj = A[1],
-            Av = A[2];
-          var Bi = B[0],
-            Bj = B[1],
-            Bv = B[2];
-          var sA = numeric.ccsDim(A),
-            sB = numeric.ccsDim(B);
-          var m = sA[0],
-            n = sA[1],
-            o = sB[1];
-          var x = numeric.rep([m], 0),
-            flags = numeric.rep([m], 0),
-            xj = Array(m);
-          var Ci = numeric.rep([o], 0),
-            Cj = [],
-            Cv = [],
-            C = [Ci, Cj, Cv];
-          var i, j, k, j0, j1, i0, i1, l, p, a, b;
-          for (k = 0; k !== o; ++k) {
-            j0 = Bi[k];
-            j1 = Bi[k + 1];
-            p = 0;
-            for (j = j0; j < j1; ++j) {
-              a = Bj[j];
-              b = Bv[j];
-              i0 = Ai[a];
-              i1 = Ai[a + 1];
-              for (i = i0; i < i1; ++i) {
-                l = Aj[i];
-                if (flags[l] === 0) {
-                  xj[p] = l;
-                  flags[l] = 1;
-                  p = p + 1;
-                }
-                x[l] = x[l] + Av[i] * b;
-              }
-            }
-            j0 = Ci[k];
-            j1 = j0 + p;
-            Ci[k + 1] = j1;
-            for (j = p - 1; j !== -1; --j) {
-              b = j0 + j;
-              i = xj[j];
-              Cj[b] = i;
-              Cv[b] = x[i];
-              flags[i] = 0;
-              x[i] = 0;
-            }
-            Ci[k + 1] = Ci[k] + p;
-          }
-          return C;
-        };
-
-        numeric.ccsLUPSolve = function ccsLUPSolve(LUP, B) {
-          var L = LUP.L,
-            U = LUP.U,
-            P = LUP.P;
-          var Bi = B[0];
-          var flag = false;
-          if (typeof Bi !== "object") {
-            B = [[0, B.length], numeric.linspace(0, B.length - 1), B];
-            Bi = B[0];
-            flag = true;
-          }
-          var Bj = B[1],
-            Bv = B[2];
-          var n = L[0].length - 1,
-            m = Bi.length - 1;
-          var x = numeric.rep([n], 0),
-            xj = Array(n);
-          var b = numeric.rep([n], 0),
-            bj = Array(n);
-          var Xi = numeric.rep([m + 1], 0),
-            Xj = [],
-            Xv = [];
-          var sol = numeric.ccsTSolve;
-          var i,
-            j,
-            j0,
-            j1,
-            k,
-            J,
-            N = 0;
-          for (i = 0; i < m; ++i) {
-            k = 0;
-            j0 = Bi[i];
-            j1 = Bi[i + 1];
-            for (j = j0; j < j1; ++j) {
-              J = LUP.Pinv[Bj[j]];
-              bj[k] = J;
-              b[J] = Bv[j];
-              ++k;
-            }
-            bj.length = k;
-            sol(L, b, x, bj, xj);
-            for (j = bj.length - 1; j !== -1; --j) b[bj[j]] = 0;
-            sol(U, x, b, xj, bj);
-            if (flag) return b;
-            for (j = xj.length - 1; j !== -1; --j) x[xj[j]] = 0;
-            for (j = bj.length - 1; j !== -1; --j) {
-              J = bj[j];
-              Xj[N] = J;
-              Xv[N] = b[J];
-              b[J] = 0;
-              ++N;
-            }
-            Xi[i + 1] = N;
-          }
-          return [Xi, Xj, Xv];
-        };
-
-        numeric.ccsbinop = function ccsbinop(body, setup) {
-          if (typeof setup === "undefined") setup = "";
-          return Function(
-            "X",
-            "Y",
-            "var Xi = X[0], Xj = X[1], Xv = X[2];\n" +
-              "var Yi = Y[0], Yj = Y[1], Yv = Y[2];\n" +
-              "var n = Xi.length-1,m = Math.max(numeric.sup(Xj),numeric.sup(Yj))+1;\n" +
-              "var Zi = numeric.rep([n+1],0), Zj = [], Zv = [];\n" +
-              "var x = numeric.rep([m],0),y = numeric.rep([m],0);\n" +
-              "var xk,yk,zk;\n" +
-              "var i,j,j0,j1,k,p=0;\n" +
-              setup +
-              "for(i=0;i<n;++i) {\n" +
-              "  j0 = Xi[i]; j1 = Xi[i+1];\n" +
-              "  for(j=j0;j!==j1;++j) {\n" +
-              "    k = Xj[j];\n" +
-              "    x[k] = 1;\n" +
-              "    Zj[p] = k;\n" +
-              "    ++p;\n" +
-              "  }\n" +
-              "  j0 = Yi[i]; j1 = Yi[i+1];\n" +
-              "  for(j=j0;j!==j1;++j) {\n" +
-              "    k = Yj[j];\n" +
-              "    y[k] = Yv[j];\n" +
-              "    if(x[k] === 0) {\n" +
-              "      Zj[p] = k;\n" +
-              "      ++p;\n" +
-              "    }\n" +
-              "  }\n" +
-              "  Zi[i+1] = p;\n" +
-              "  j0 = Xi[i]; j1 = Xi[i+1];\n" +
-              "  for(j=j0;j!==j1;++j) x[Xj[j]] = Xv[j];\n" +
-              "  j0 = Zi[i]; j1 = Zi[i+1];\n" +
-              "  for(j=j0;j!==j1;++j) {\n" +
-              "    k = Zj[j];\n" +
-              "    xk = x[k];\n" +
-              "    yk = y[k];\n" +
-              body +
-              "\n" +
-              "    Zv[j] = zk;\n" +
-              "  }\n" +
-              "  j0 = Xi[i]; j1 = Xi[i+1];\n" +
-              "  for(j=j0;j!==j1;++j) x[Xj[j]] = 0;\n" +
-              "  j0 = Yi[i]; j1 = Yi[i+1];\n" +
-              "  for(j=j0;j!==j1;++j) y[Yj[j]] = 0;\n" +
-              "}\n" +
-              "return [Zi,Zj,Zv];"
-          );
-        };
-
-        (function () {
-          var k, A, B, C;
-          for (k in numeric.ops2) {
-            if (isFinite(eval("1" + numeric.ops2[k] + "0")))
-              A = "[Y[0],Y[1],numeric." + k + "(X,Y[2])]";
-            else A = "NaN";
-            if (isFinite(eval("0" + numeric.ops2[k] + "1")))
-              B = "[X[0],X[1],numeric." + k + "(X[2],Y)]";
-            else B = "NaN";
-            if (
-              isFinite(eval("1" + numeric.ops2[k] + "0")) &&
-              isFinite(eval("0" + numeric.ops2[k] + "1"))
-            )
-              C = "numeric.ccs" + k + "MM(X,Y)";
-            else C = "NaN";
-            numeric["ccs" + k + "MM"] = numeric.ccsbinop("zk = xk " + numeric.ops2[k] + "yk;");
-            numeric["ccs" + k] = Function(
-              "X",
-              "Y",
-              'if(typeof X === "number") return ' +
-                A +
-                ";\n" +
-                'if(typeof Y === "number") return ' +
-                B +
-                ";\n" +
-                "return " +
-                C +
-                ";\n"
-            );
-          }
-        })();
-
-        numeric.ccsScatter = function ccsScatter(A) {
-          var Ai = A[0],
-            Aj = A[1],
-            Av = A[2];
-          var n = numeric.sup(Aj) + 1,
-            m = Ai.length;
-          var Ri = numeric.rep([n], 0),
-            Rj = Array(m),
-            Rv = Array(m);
-          var counts = numeric.rep([n], 0),
-            i;
-          for (i = 0; i < m; ++i) counts[Aj[i]]++;
-          for (i = 0; i < n; ++i) Ri[i + 1] = Ri[i] + counts[i];
-          var ptr = Ri.slice(0),
-            k,
-            Aii;
-          for (i = 0; i < m; ++i) {
-            Aii = Aj[i];
-            k = ptr[Aii];
-            Rj[k] = Ai[i];
-            Rv[k] = Av[i];
-            ptr[Aii] = ptr[Aii] + 1;
-          }
-          return [Ri, Rj, Rv];
-        };
-
-        numeric.ccsGather = function ccsGather(A) {
-          var Ai = A[0],
-            Aj = A[1],
-            Av = A[2];
-          var n = Ai.length - 1,
-            m = Aj.length;
-          var Ri = Array(m),
-            Rj = Array(m),
-            Rv = Array(m);
-          var i, j, j0, j1, p;
-          p = 0;
-          for (i = 0; i < n; ++i) {
-            j0 = Ai[i];
-            j1 = Ai[i + 1];
-            for (j = j0; j !== j1; ++j) {
-              Rj[p] = i;
-              Ri[p] = Aj[j];
-              Rv[p] = Av[j];
-              ++p;
-            }
-          }
-          return [Ri, Rj, Rv];
-        };
-
-        // The following sparse linear algebra routines are deprecated.
-
-        numeric.sdim = function dim(A, ret, k) {
-          if (typeof ret === "undefined") {
-            ret = [];
-          }
-          if (typeof A !== "object") return ret;
-          if (typeof k === "undefined") {
-            k = 0;
-          }
-          if (!(k in ret)) {
-            ret[k] = 0;
-          }
-          if (A.length > ret[k]) ret[k] = A.length;
-          var i;
-          for (i in A) {
-            if (A.hasOwnProperty(i)) dim(A[i], ret, k + 1);
-          }
-          return ret;
-        };
-
-        numeric.sclone = function clone(A, k, n) {
-          if (typeof k === "undefined") {
-            k = 0;
-          }
-          if (typeof n === "undefined") {
-            n = numeric.sdim(A).length;
-          }
-          var i,
-            ret = Array(A.length);
-          if (k === n - 1) {
-            for (i in A) {
-              if (A.hasOwnProperty(i)) ret[i] = A[i];
-            }
-            return ret;
-          }
-          for (i in A) {
-            if (A.hasOwnProperty(i)) ret[i] = clone(A[i], k + 1, n);
-          }
-          return ret;
-        };
-
-        numeric.sdiag = function diag(d) {
-          var n = d.length,
-            i,
-            ret = Array(n),
-            i1,
-            i2,
-            i3;
-          for (i = n - 1; i >= 1; i -= 2) {
-            i1 = i - 1;
-            ret[i] = [];
-            ret[i][i] = d[i];
-            ret[i1] = [];
-            ret[i1][i1] = d[i1];
-          }
-          if (i === 0) {
-            ret[0] = [];
-            ret[0][0] = d[i];
-          }
-          return ret;
-        };
-
-        numeric.sidentity = function identity(n) {
-          return numeric.sdiag(numeric.rep([n], 1));
-        };
-
-        numeric.stranspose = function transpose(A) {
-          var ret = [],
-            n = A.length,
-            i,
-            j,
-            Ai;
-          for (i in A) {
-            if (!A.hasOwnProperty(i)) continue;
-            Ai = A[i];
-            for (j in Ai) {
-              if (!Ai.hasOwnProperty(j)) continue;
-              if (typeof ret[j] !== "object") {
-                ret[j] = [];
-              }
-              ret[j][i] = Ai[j];
-            }
-          }
-          return ret;
-        };
-
-        numeric.sLUP = function LUP(A, tol) {
-          throw new Error(
-            "The function numeric.sLUP had a bug in it and has been removed. Please use the new numeric.ccsLUP function instead."
-          );
-        };
-
-        numeric.sdotMM = function dotMM(A, B) {
-          var p = A.length,
-            q = B.length,
-            BT = numeric.stranspose(B),
-            r = BT.length,
-            Ai,
-            BTk;
-          var i, j, k, accum;
-          var ret = Array(p),
-            reti;
-          for (i = p - 1; i >= 0; i--) {
-            reti = [];
-            Ai = A[i];
-            for (k = r - 1; k >= 0; k--) {
-              accum = 0;
-              BTk = BT[k];
-              for (j in Ai) {
-                if (!Ai.hasOwnProperty(j)) continue;
-                if (j in BTk) {
-                  accum += Ai[j] * BTk[j];
-                }
-              }
-              if (accum) reti[k] = accum;
-            }
-            ret[i] = reti;
-          }
-          return ret;
-        };
-
-        numeric.sdotMV = function dotMV(A, x) {
-          var p = A.length,
-            Ai,
-            i,
-            j;
-          var ret = Array(p),
-            accum;
-          for (i = p - 1; i >= 0; i--) {
-            Ai = A[i];
-            accum = 0;
-            for (j in Ai) {
-              if (!Ai.hasOwnProperty(j)) continue;
-              if (x[j]) accum += Ai[j] * x[j];
-            }
-            if (accum) ret[i] = accum;
-          }
-          return ret;
-        };
-
-        numeric.sdotVM = function dotMV(x, A) {
-          var i, j, Ai, alpha;
-          var ret = [],
-            accum;
-          for (i in x) {
-            if (!x.hasOwnProperty(i)) continue;
-            Ai = A[i];
-            alpha = x[i];
-            for (j in Ai) {
-              if (!Ai.hasOwnProperty(j)) continue;
-              if (!ret[j]) {
-                ret[j] = 0;
-              }
-              ret[j] += alpha * Ai[j];
-            }
-          }
-          return ret;
-        };
-
-        numeric.sdotVV = function dotVV(x, y) {
-          var i,
-            ret = 0;
-          for (i in x) {
-            if (x[i] && y[i]) ret += x[i] * y[i];
-          }
-          return ret;
-        };
-
-        numeric.sdot = function dot(A, B) {
-          var m = numeric.sdim(A).length,
-            n = numeric.sdim(B).length;
-          var k = m * 1000 + n;
-          switch (k) {
-            case 0:
-              return A * B;
-            case 1001:
-              return numeric.sdotVV(A, B);
-            case 2001:
-              return numeric.sdotMV(A, B);
-            case 1002:
-              return numeric.sdotVM(A, B);
-            case 2002:
-              return numeric.sdotMM(A, B);
-            default:
-              throw new Error(
-                "numeric.sdot not implemented for tensors of order " + m + " and " + n
-              );
-          }
-        };
-
-        numeric.sscatter = function scatter(V) {
-          var n = V[0].length,
-            Vij,
-            i,
-            j,
-            m = V.length,
-            A = [],
-            Aj;
-          for (i = n - 1; i >= 0; --i) {
-            if (!V[m - 1][i]) continue;
-            Aj = A;
-            for (j = 0; j < m - 2; j++) {
-              Vij = V[j][i];
-              if (!Aj[Vij]) Aj[Vij] = [];
-              Aj = Aj[Vij];
-            }
-            Aj[V[j][i]] = V[j + 1][i];
-          }
-          return A;
-        };
-
-        numeric.sgather = function gather(A, ret, k) {
-          if (typeof ret === "undefined") ret = [];
-          if (typeof k === "undefined") k = [];
-          var n, i, Ai;
-          n = k.length;
-          for (i in A) {
-            if (A.hasOwnProperty(i)) {
-              k[n] = parseInt(i);
-              Ai = A[i];
-              if (typeof Ai === "number") {
-                if (Ai) {
-                  if (ret.length === 0) {
-                    for (i = n + 1; i >= 0; --i) ret[i] = [];
-                  }
-                  for (i = n; i >= 0; --i) ret[i].push(k[i]);
-                  ret[n + 1].push(Ai);
-                }
-              } else gather(Ai, ret, k);
-            }
-          }
-          if (k.length > n) k.pop();
-          return ret;
-        };
-
-        // 6. Coordinate matrices
-        numeric.cLU = function LU(A) {
-          var I = A[0],
-            J = A[1],
-            V = A[2];
-          var p = I.length,
-            m = 0,
-            i,
-            j,
-            k,
-            a,
-            b,
-            c;
-          for (i = 0; i < p; i++) if (I[i] > m) m = I[i];
-          m++;
-          var L = Array(m),
-            U = Array(m),
-            left = numeric.rep([m], Infinity),
-            right = numeric.rep([m], -Infinity);
-          var Ui, Uj, alpha;
-          for (k = 0; k < p; k++) {
-            i = I[k];
-            j = J[k];
-            if (j < left[i]) left[i] = j;
-            if (j > right[i]) right[i] = j;
-          }
-          for (i = 0; i < m - 1; i++) {
-            if (right[i] > right[i + 1]) right[i + 1] = right[i];
-          }
-          for (i = m - 1; i >= 1; i--) {
-            if (left[i] < left[i - 1]) left[i - 1] = left[i];
-          }
-          var countL = 0,
-            countU = 0;
-          for (i = 0; i < m; i++) {
-            U[i] = numeric.rep([right[i] - left[i] + 1], 0);
-            L[i] = numeric.rep([i - left[i]], 0);
-            countL += i - left[i] + 1;
-            countU += right[i] - i + 1;
-          }
-          for (k = 0; k < p; k++) {
-            i = I[k];
-            U[i][J[k] - left[i]] = V[k];
-          }
-          for (i = 0; i < m - 1; i++) {
-            a = i - left[i];
-            Ui = U[i];
-            for (j = i + 1; left[j] <= i && j < m; j++) {
-              b = i - left[j];
-              c = right[i] - i;
-              Uj = U[j];
-              alpha = Uj[b] / Ui[a];
-              if (alpha) {
-                for (k = 1; k <= c; k++) {
-                  Uj[k + b] -= alpha * Ui[k + a];
-                }
-                L[j][i - left[j]] = alpha;
-              }
-            }
-          }
-          var Ui = [],
-            Uj = [],
-            Uv = [],
-            Li = [],
-            Lj = [],
-            Lv = [];
-          var p, q, foo;
-          p = 0;
-          q = 0;
-          for (i = 0; i < m; i++) {
-            a = left[i];
-            b = right[i];
-            foo = U[i];
-            for (j = i; j <= b; j++) {
-              if (foo[j - a]) {
-                Ui[p] = i;
-                Uj[p] = j;
-                Uv[p] = foo[j - a];
-                p++;
-              }
-            }
-            foo = L[i];
-            for (j = a; j < i; j++) {
-              if (foo[j - a]) {
-                Li[q] = i;
-                Lj[q] = j;
-                Lv[q] = foo[j - a];
-                q++;
-              }
-            }
-            Li[q] = i;
-            Lj[q] = i;
-            Lv[q] = 1;
-            q++;
-          }
-          return { U: [Ui, Uj, Uv], L: [Li, Lj, Lv] };
-        };
-
-        numeric.cLUsolve = function LUsolve(lu, b) {
-          var L = lu.L,
-            U = lu.U,
-            ret = numeric.clone(b);
-          var Li = L[0],
-            Lj = L[1],
-            Lv = L[2];
-          var Ui = U[0],
-            Uj = U[1],
-            Uv = U[2];
-          var p = Ui.length,
-            q = Li.length;
-          var m = ret.length,
-            i,
-            j,
-            k;
-          k = 0;
-          for (i = 0; i < m; i++) {
-            while (Lj[k] < i) {
-              ret[i] -= Lv[k] * ret[Lj[k]];
-              k++;
-            }
-            k++;
-          }
-          k = p - 1;
-          for (i = m - 1; i >= 0; i--) {
-            while (Uj[k] > i) {
-              ret[i] -= Uv[k] * ret[Uj[k]];
-              k--;
-            }
-            ret[i] /= Uv[k];
-            k--;
-          }
-          return ret;
-        };
-
-        numeric.cgrid = function grid(n, shape) {
-          if (typeof n === "number") n = [n, n];
-          var ret = numeric.rep(n, -1);
-          var i, j, count;
-          if (typeof shape !== "function") {
-            switch (shape) {
-              case "L":
-                shape = function (i, j) {
-                  return i >= n[0] / 2 || j < n[1] / 2;
-                };
-                break;
-              default:
-                shape = function (i, j) {
-                  return true;
-                };
-                break;
-            }
-          }
-          count = 0;
-          for (i = 1; i < n[0] - 1; i++)
-            for (j = 1; j < n[1] - 1; j++)
-              if (shape(i, j)) {
-                ret[i][j] = count;
-                count++;
-              }
-          return ret;
-        };
-
-        numeric.cdelsq = function delsq(g) {
-          var dir = [
-            [-1, 0],
-            [0, -1],
-            [0, 1],
-            [1, 0],
-          ];
-          var s = numeric.dim(g),
-            m = s[0],
-            n = s[1],
-            i,
-            j,
-            k,
-            p,
-            q;
-          var Li = [],
-            Lj = [],
-            Lv = [];
-          for (i = 1; i < m - 1; i++)
-            for (j = 1; j < n - 1; j++) {
-              if (g[i][j] < 0) continue;
-              for (k = 0; k < 4; k++) {
-                p = i + dir[k][0];
-                q = j + dir[k][1];
-                if (g[p][q] < 0) continue;
-                Li.push(g[i][j]);
-                Lj.push(g[p][q]);
-                Lv.push(-1);
-              }
-              Li.push(g[i][j]);
-              Lj.push(g[i][j]);
-              Lv.push(4);
-            }
-          return [Li, Lj, Lv];
-        };
-
-        numeric.cdotMV = function dotMV(A, x) {
-          var ret,
-            Ai = A[0],
-            Aj = A[1],
-            Av = A[2],
-            k,
-            p = Ai.length,
-            N;
-          N = 0;
-          for (k = 0; k < p; k++) {
-            if (Ai[k] > N) N = Ai[k];
-          }
-          N++;
-          ret = numeric.rep([N], 0);
-          for (k = 0; k < p; k++) {
-            ret[Ai[k]] += Av[k] * x[Aj[k]];
-          }
-          return ret;
-        };
-
-        // 7. Splines
-
-        numeric.Spline = function Spline(x, yl, yr, kl, kr) {
-          this.x = x;
-          this.yl = yl;
-          this.yr = yr;
-          this.kl = kl;
-          this.kr = kr;
-        };
-        numeric.Spline.prototype._at = function _at(x1, p) {
-          var x = this.x;
-          var yl = this.yl;
-          var yr = this.yr;
-          var kl = this.kl;
-          var kr = this.kr;
-          var x1, a, b, t;
-          var add = numeric.add,
-            sub = numeric.sub,
-            mul = numeric.mul;
-          a = sub(mul(kl[p], x[p + 1] - x[p]), sub(yr[p + 1], yl[p]));
-          b = add(mul(kr[p + 1], x[p] - x[p + 1]), sub(yr[p + 1], yl[p]));
-          t = (x1 - x[p]) / (x[p + 1] - x[p]);
-          var s = t * (1 - t);
-          return add(
-            add(add(mul(1 - t, yl[p]), mul(t, yr[p + 1])), mul(a, s * (1 - t))),
-            mul(b, s * t)
-          );
-        };
-        numeric.Spline.prototype.at = function at(x0) {
-          if (typeof x0 === "number") {
-            var x = this.x;
-            var n = x.length;
-            var p,
-              q,
-              mid,
-              floor = Math.floor,
-              a,
-              b,
-              t;
-            p = 0;
-            q = n - 1;
-            while (q - p > 1) {
-              mid = floor((p + q) / 2);
-              if (x[mid] <= x0) p = mid;
-              else q = mid;
-            }
-            return this._at(x0, p);
-          }
-          var n = x0.length,
-            i,
-            ret = Array(n);
-          for (i = n - 1; i !== -1; --i) ret[i] = this.at(x0[i]);
-          return ret;
-        };
-        numeric.Spline.prototype.diff = function diff() {
-          var x = this.x;
-          var yl = this.yl;
-          var yr = this.yr;
-          var kl = this.kl;
-          var kr = this.kr;
-          var n = yl.length;
-          var i, dx, dy;
-          var zl = kl,
-            zr = kr,
-            pl = Array(n),
-            pr = Array(n);
-          var add = numeric.add,
-            mul = numeric.mul,
-            div = numeric.div,
-            sub = numeric.sub;
-          for (i = n - 1; i !== -1; --i) {
-            dx = x[i + 1] - x[i];
-            dy = sub(yr[i + 1], yl[i]);
-            pl[i] = div(add(mul(dy, 6), mul(kl[i], -4 * dx), mul(kr[i + 1], -2 * dx)), dx * dx);
-            pr[i + 1] = div(add(mul(dy, -6), mul(kl[i], 2 * dx), mul(kr[i + 1], 4 * dx)), dx * dx);
-          }
-          return new numeric.Spline(x, zl, zr, pl, pr);
-        };
-        numeric.Spline.prototype.roots = function roots() {
-          function sqr(x) {
-            return x * x;
-          }
-          function heval(y0, y1, k0, k1, x) {
-            var A = k0 * 2 - (y1 - y0);
-            var B = -k1 * 2 + (y1 - y0);
-            var t = (x + 1) * 0.5;
-            var s = t * (1 - t);
-            return (1 - t) * y0 + t * y1 + A * s * (1 - t) + B * s * t;
-          }
-          var ret = [];
-          var x = this.x,
-            yl = this.yl,
-            yr = this.yr,
-            kl = this.kl,
-            kr = this.kr;
-          if (typeof yl[0] === "number") {
-            yl = [yl];
-            yr = [yr];
-            kl = [kl];
-            kr = [kr];
-          }
-          var m = yl.length,
-            n = x.length - 1,
-            i,
-            j,
-            k,
-            y,
-            s,
-            t;
-          var ai,
-            bi,
-            ci,
-            di,
-            ret = Array(m),
-            ri,
-            k0,
-            k1,
-            y0,
-            y1,
-            A,
-            B,
-            D,
-            dx,
-            cx,
-            stops,
-            z0,
-            z1,
-            zm,
-            t0,
-            t1,
-            tm;
-          var sqrt = Math.sqrt;
-          for (i = 0; i !== m; ++i) {
-            ai = yl[i];
-            bi = yr[i];
-            ci = kl[i];
-            di = kr[i];
-            ri = [];
-            for (j = 0; j !== n; j++) {
-              if (j > 0 && bi[j] * ai[j] < 0) ri.push(x[j]);
-              dx = x[j + 1] - x[j];
-              cx = x[j];
-              y0 = ai[j];
-              y1 = bi[j + 1];
-              k0 = ci[j] / dx;
-              k1 = di[j + 1] / dx;
-              D = sqr(k0 - k1 + 3 * (y0 - y1)) + 12 * k1 * y0;
-              A = k1 + 3 * y0 + 2 * k0 - 3 * y1;
-              B = 3 * (k1 + k0 + 2 * (y0 - y1));
-              if (D <= 0) {
-                z0 = A / B;
-                if (z0 > x[j] && z0 < x[j + 1]) stops = [x[j], z0, x[j + 1]];
-                else stops = [x[j], x[j + 1]];
-              } else {
-                z0 = (A - sqrt(D)) / B;
-                z1 = (A + sqrt(D)) / B;
-                stops = [x[j]];
-                if (z0 > x[j] && z0 < x[j + 1]) stops.push(z0);
-                if (z1 > x[j] && z1 < x[j + 1]) stops.push(z1);
-                stops.push(x[j + 1]);
-              }
-              t0 = stops[0];
-              z0 = this._at(t0, j);
-              for (k = 0; k < stops.length - 1; k++) {
-                t1 = stops[k + 1];
-                z1 = this._at(t1, j);
-                if (z0 === 0) {
-                  ri.push(t0);
-                  t0 = t1;
-                  z0 = z1;
-                  continue;
-                }
-                if (z1 === 0 || z0 * z1 > 0) {
-                  t0 = t1;
-                  z0 = z1;
-                  continue;
-                }
-                var side = 0;
-                while (1) {
-                  tm = (z0 * t1 - z1 * t0) / (z0 - z1);
-                  if (tm <= t0 || tm >= t1) {
-                    break;
-                  }
-                  zm = this._at(tm, j);
-                  if (zm * z1 > 0) {
-                    t1 = tm;
-                    z1 = zm;
-                    if (side === -1) z0 *= 0.5;
-                    side = -1;
-                  } else if (zm * z0 > 0) {
-                    t0 = tm;
-                    z0 = zm;
-                    if (side === 1) z1 *= 0.5;
-                    side = 1;
-                  } else break;
-                }
-                ri.push(tm);
-                t0 = stops[k + 1];
-                z0 = this._at(t0, j);
-              }
-              if (z1 === 0) ri.push(t1);
-            }
-            ret[i] = ri;
-          }
-          if (typeof this.yl[0] === "number") return ret[0];
-          return ret;
-        };
-        numeric.spline = function spline(x, y, k1, kn) {
-          var n = x.length,
-            b = [],
-            dx = [],
-            dy = [];
-          var i;
-          var sub = numeric.sub,
-            mul = numeric.mul,
-            add = numeric.add;
-          for (i = n - 2; i >= 0; i--) {
-            dx[i] = x[i + 1] - x[i];
-            dy[i] = sub(y[i + 1], y[i]);
-          }
-          if (typeof k1 === "string" || typeof kn === "string") {
-            k1 = kn = "periodic";
-          }
-          // Build sparse tridiagonal system
-          var T = [[], [], []];
-          switch (typeof k1) {
-            case "undefined":
-              b[0] = mul(3 / (dx[0] * dx[0]), dy[0]);
-              T[0].push(0, 0);
-              T[1].push(0, 1);
-              T[2].push(2 / dx[0], 1 / dx[0]);
-              break;
-            case "string":
-              b[0] = add(
-                mul(3 / (dx[n - 2] * dx[n - 2]), dy[n - 2]),
-                mul(3 / (dx[0] * dx[0]), dy[0])
-              );
-              T[0].push(0, 0, 0);
-              T[1].push(n - 2, 0, 1);
-              T[2].push(1 / dx[n - 2], 2 / dx[n - 2] + 2 / dx[0], 1 / dx[0]);
-              break;
-            default:
-              b[0] = k1;
-              T[0].push(0);
-              T[1].push(0);
-              T[2].push(1);
-              break;
-          }
-          for (i = 1; i < n - 1; i++) {
-            b[i] = add(
-              mul(3 / (dx[i - 1] * dx[i - 1]), dy[i - 1]),
-              mul(3 / (dx[i] * dx[i]), dy[i])
-            );
-            T[0].push(i, i, i);
-            T[1].push(i - 1, i, i + 1);
-            T[2].push(1 / dx[i - 1], 2 / dx[i - 1] + 2 / dx[i], 1 / dx[i]);
-          }
-          switch (typeof kn) {
-            case "undefined":
-              b[n - 1] = mul(3 / (dx[n - 2] * dx[n - 2]), dy[n - 2]);
-              T[0].push(n - 1, n - 1);
-              T[1].push(n - 2, n - 1);
-              T[2].push(1 / dx[n - 2], 2 / dx[n - 2]);
-              break;
-            case "string":
-              T[1][T[1].length - 1] = 0;
-              break;
-            default:
-              b[n - 1] = kn;
-              T[0].push(n - 1);
-              T[1].push(n - 1);
-              T[2].push(1);
-              break;
-          }
-          if (typeof b[0] !== "number") b = numeric.transpose(b);
-          else b = [b];
-          var k = Array(b.length);
-          if (typeof k1 === "string") {
-            for (i = k.length - 1; i !== -1; --i) {
-              k[i] = numeric.ccsLUPSolve(numeric.ccsLUP(numeric.ccsScatter(T)), b[i]);
-              k[i][n - 1] = k[i][0];
-            }
-          } else {
-            for (i = k.length - 1; i !== -1; --i) {
-              k[i] = numeric.cLUsolve(numeric.cLU(T), b[i]);
-            }
-          }
-          if (typeof y[0] === "number") k = k[0];
-          else k = numeric.transpose(k);
-          return new numeric.Spline(x, y, y, k, k);
-        };
-
-        // 8. FFT
-        numeric.fftpow2 = function fftpow2(x, y) {
-          var n = x.length;
-          if (n === 1) return;
-          var cos = Math.cos,
-            sin = Math.sin,
-            i,
-            j;
-          var xe = Array(n / 2),
-            ye = Array(n / 2),
-            xo = Array(n / 2),
-            yo = Array(n / 2);
-          j = n / 2;
-          for (i = n - 1; i !== -1; --i) {
-            --j;
-            xo[j] = x[i];
-            yo[j] = y[i];
-            --i;
-            xe[j] = x[i];
-            ye[j] = y[i];
-          }
-          fftpow2(xe, ye);
-          fftpow2(xo, yo);
-          j = n / 2;
-          var t,
-            k = -6.2831853071795864769252867665590057683943387987502116419 / n,
-            ci,
-            si;
-          for (i = n - 1; i !== -1; --i) {
-            --j;
-            if (j === -1) j = n / 2 - 1;
-            t = k * i;
-            ci = cos(t);
-            si = sin(t);
-            x[i] = xe[j] + ci * xo[j] - si * yo[j];
-            y[i] = ye[j] + ci * yo[j] + si * xo[j];
-          }
-        };
-        numeric._ifftpow2 = function _ifftpow2(x, y) {
-          var n = x.length;
-          if (n === 1) return;
-          var cos = Math.cos,
-            sin = Math.sin,
-            i,
-            j;
-          var xe = Array(n / 2),
-            ye = Array(n / 2),
-            xo = Array(n / 2),
-            yo = Array(n / 2);
-          j = n / 2;
-          for (i = n - 1; i !== -1; --i) {
-            --j;
-            xo[j] = x[i];
-            yo[j] = y[i];
-            --i;
-            xe[j] = x[i];
-            ye[j] = y[i];
-          }
-          _ifftpow2(xe, ye);
-          _ifftpow2(xo, yo);
-          j = n / 2;
-          var t,
-            k = 6.2831853071795864769252867665590057683943387987502116419 / n,
-            ci,
-            si;
-          for (i = n - 1; i !== -1; --i) {
-            --j;
-            if (j === -1) j = n / 2 - 1;
-            t = k * i;
-            ci = cos(t);
-            si = sin(t);
-            x[i] = xe[j] + ci * xo[j] - si * yo[j];
-            y[i] = ye[j] + ci * yo[j] + si * xo[j];
-          }
-        };
-        numeric.ifftpow2 = function ifftpow2(x, y) {
-          numeric._ifftpow2(x, y);
-          numeric.diveq(x, x.length);
-          numeric.diveq(y, y.length);
-        };
-        numeric.convpow2 = function convpow2(ax, ay, bx, by) {
-          numeric.fftpow2(ax, ay);
-          numeric.fftpow2(bx, by);
-          var i,
-            n = ax.length,
-            axi,
-            bxi,
-            ayi,
-            byi;
-          for (i = n - 1; i !== -1; --i) {
-            axi = ax[i];
-            ayi = ay[i];
-            bxi = bx[i];
-            byi = by[i];
-            ax[i] = axi * bxi - ayi * byi;
-            ay[i] = axi * byi + ayi * bxi;
-          }
-          numeric.ifftpow2(ax, ay);
-        };
-        numeric.T.prototype.fft = function fft() {
-          var x = this.x,
-            y = this.y;
-          var n = x.length,
-            log = Math.log,
-            log2 = log(2),
-            p = Math.ceil(log(2 * n - 1) / log2),
-            m = Math.pow(2, p);
-          var cx = numeric.rep([m], 0),
-            cy = numeric.rep([m], 0),
-            cos = Math.cos,
-            sin = Math.sin;
-          var k,
-            c = -3.14159265358979323846264338327950288419716939937510582 / n,
-            t;
-          var a = numeric.rep([m], 0),
-            b = numeric.rep([m], 0),
-            nhalf = Math.floor(n / 2);
-          for (k = 0; k < n; k++) a[k] = x[k];
-          if (typeof y !== "undefined") for (k = 0; k < n; k++) b[k] = y[k];
-          cx[0] = 1;
-          for (k = 1; k <= m / 2; k++) {
-            t = c * k * k;
-            cx[k] = cos(t);
-            cy[k] = sin(t);
-            cx[m - k] = cos(t);
-            cy[m - k] = sin(t);
-          }
-          var X = new numeric.T(a, b),
-            Y = new numeric.T(cx, cy);
-          X = X.mul(Y);
-          numeric.convpow2(X.x, X.y, numeric.clone(Y.x), numeric.neg(Y.y));
-          X = X.mul(Y);
-          X.x.length = n;
-          X.y.length = n;
-          return X;
-        };
-        numeric.T.prototype.ifft = function ifft() {
-          var x = this.x,
-            y = this.y;
-          var n = x.length,
-            log = Math.log,
-            log2 = log(2),
-            p = Math.ceil(log(2 * n - 1) / log2),
-            m = Math.pow(2, p);
-          var cx = numeric.rep([m], 0),
-            cy = numeric.rep([m], 0),
-            cos = Math.cos,
-            sin = Math.sin;
-          var k,
-            c = 3.14159265358979323846264338327950288419716939937510582 / n,
-            t;
-          var a = numeric.rep([m], 0),
-            b = numeric.rep([m], 0),
-            nhalf = Math.floor(n / 2);
-          for (k = 0; k < n; k++) a[k] = x[k];
-          if (typeof y !== "undefined") for (k = 0; k < n; k++) b[k] = y[k];
-          cx[0] = 1;
-          for (k = 1; k <= m / 2; k++) {
-            t = c * k * k;
-            cx[k] = cos(t);
-            cy[k] = sin(t);
-            cx[m - k] = cos(t);
-            cy[m - k] = sin(t);
-          }
-          var X = new numeric.T(a, b),
-            Y = new numeric.T(cx, cy);
-          X = X.mul(Y);
-          numeric.convpow2(X.x, X.y, numeric.clone(Y.x), numeric.neg(Y.y));
-          X = X.mul(Y);
-          X.x.length = n;
-          X.y.length = n;
-          return X.div(n);
-        };
-
-        //9. Unconstrained optimization
-        numeric.gradient = function gradient(f, x) {
-          var n = x.length;
-          var f0 = f(x);
-          if (isNaN(f0)) throw new Error("gradient: f(x) is a NaN!");
-          var max = Math.max;
-          var i,
-            x0 = numeric.clone(x),
-            f1,
-            f2,
-            J = Array(n);
-          var div = numeric.div,
-            sub = numeric.sub,
-            errest,
-            roundoff,
-            max = Math.max,
-            eps = 1e-3,
-            abs = Math.abs,
-            min = Math.min;
-          var t0,
-            t1,
-            t2,
-            it = 0,
-            d1,
-            d2,
-            N;
-          for (i = 0; i < n; i++) {
-            var h = max(1e-6 * f0, 1e-8);
-            while (1) {
-              ++it;
-              if (it > 20) {
-                throw new Error("Numerical gradient fails");
-              }
-              x0[i] = x[i] + h;
-              f1 = f(x0);
-              x0[i] = x[i] - h;
-              f2 = f(x0);
-              x0[i] = x[i];
-              if (isNaN(f1) || isNaN(f2)) {
-                h /= 16;
-                continue;
-              }
-              J[i] = (f1 - f2) / (2 * h);
-              t0 = x[i] - h;
-              t1 = x[i];
-              t2 = x[i] + h;
-              d1 = (f1 - f0) / h;
-              d2 = (f0 - f2) / h;
-              N = max(abs(J[i]), abs(f0), abs(f1), abs(f2), abs(t0), abs(t1), abs(t2), 1e-8);
-              errest = min(max(abs(d1 - J[i]), abs(d2 - J[i]), abs(d1 - d2)) / N, h / N);
-              if (errest > eps) {
-                h /= 16;
-              } else break;
-            }
-          }
-          return J;
-        };
-
-        numeric.uncmin = function uncmin(f, x0, tol, gradient, maxit, callback, options) {
-          var grad = numeric.gradient;
-          if (typeof options === "undefined") {
-            options = {};
-          }
-          if (typeof tol === "undefined") {
-            tol = 1e-8;
-          }
-          if (typeof gradient === "undefined") {
-            gradient = function (x) {
-              return grad(f, x);
-            };
-          }
-          if (typeof maxit === "undefined") maxit = 1000;
-          x0 = numeric.clone(x0);
-          var n = x0.length;
-          var f0 = f(x0),
-            f1,
-            df0;
-          if (isNaN(f0)) throw new Error("uncmin: f(x0) is a NaN!");
-          var max = Math.max,
-            norm2 = numeric.norm2;
-          tol = max(tol, numeric.epsilon);
-          var step,
-            g0,
-            g1,
-            H1 = options.Hinv || numeric.identity(n);
-          var dot = numeric.dot,
-            inv = numeric.inv,
-            sub = numeric.sub,
-            add = numeric.add,
-            ten = numeric.tensor,
-            div = numeric.div,
-            mul = numeric.mul;
-          var all = numeric.all,
-            isfinite = numeric.isFinite,
-            neg = numeric.neg;
-          var it = 0,
-            i,
-            s,
-            x1,
-            y,
-            Hy,
-            Hs,
-            ys,
-            i0,
-            t,
-            nstep,
-            t1,
-            t2;
-          var msg = "";
-          g0 = gradient(x0);
-          while (it < maxit) {
-            if (typeof callback === "function") {
-              if (callback(it, x0, f0, g0, H1)) {
-                msg = "Callback returned true";
-                break;
-              }
-            }
-            if (!all(isfinite(g0))) {
-              msg = "Gradient has Infinity or NaN";
-              break;
-            }
-            step = neg(dot(H1, g0));
-            if (!all(isfinite(step))) {
-              msg = "Search direction has Infinity or NaN";
-              break;
-            }
-            nstep = norm2(step);
-            if (nstep < tol) {
-              msg = "Newton step smaller than tol";
-              break;
-            }
-            t = 1;
-            df0 = dot(g0, step);
-            // line search
-            x1 = x0;
-            while (it < maxit) {
-              if (t * nstep < tol) {
-                break;
-              }
-              s = mul(step, t);
-              x1 = add(x0, s);
-              f1 = f(x1);
-              if (f1 - f0 >= 0.1 * t * df0 || isNaN(f1)) {
-                t *= 0.5;
-                ++it;
-                continue;
-              }
-              break;
-            }
-            if (t * nstep < tol) {
-              msg = "Line search step size smaller than tol";
-              break;
-            }
-            if (it === maxit) {
-              msg = "maxit reached during line search";
-              break;
-            }
-            g1 = gradient(x1);
-            y = sub(g1, g0);
-            ys = dot(y, s);
-            Hy = dot(H1, y);
-            H1 = sub(
-              add(H1, mul((ys + dot(y, Hy)) / (ys * ys), ten(s, s))),
-              div(add(ten(Hy, s), ten(s, Hy)), ys)
-            );
-            x0 = x1;
-            f0 = f1;
-            g0 = g1;
-            ++it;
-          }
-          return {
-            solution: x0,
-            f: f0,
-            gradient: g0,
-            invHessian: H1,
-            iterations: it,
-            message: msg,
-          };
-        };
-
-        // 10. Ode solver (Dormand-Prince)
-        numeric.Dopri = function Dopri(x, y, f, ymid, iterations, msg, events) {
-          this.x = x;
-          this.y = y;
-          this.f = f;
-          this.ymid = ymid;
-          this.iterations = iterations;
-          this.events = events;
-          this.message = msg;
-        };
-        numeric.Dopri.prototype._at = function _at(xi, j) {
-          function sqr(x) {
-            return x * x;
-          }
-          var sol = this;
-          var xs = sol.x;
-          var ys = sol.y;
-          var k1 = sol.f;
-          var ymid = sol.ymid;
-          var n = xs.length;
-          var x0, x1, xh, y0, y1, yh, xi;
-          var floor = Math.floor,
-            h;
-          var c = 0.5;
-          var add = numeric.add,
-            mul = numeric.mul,
-            sub = numeric.sub,
-            p,
-            q,
-            w;
-          x0 = xs[j];
-          x1 = xs[j + 1];
-          y0 = ys[j];
-          y1 = ys[j + 1];
-          h = x1 - x0;
-          xh = x0 + c * h;
-          yh = ymid[j];
-          p = sub(k1[j], mul(y0, 1 / (x0 - xh) + 2 / (x0 - x1)));
-          q = sub(k1[j + 1], mul(y1, 1 / (x1 - xh) + 2 / (x1 - x0)));
-          w = [
-            (sqr(xi - x1) * (xi - xh)) / sqr(x0 - x1) / (x0 - xh),
-            (sqr(xi - x0) * sqr(xi - x1)) / sqr(x0 - xh) / sqr(x1 - xh),
-            (sqr(xi - x0) * (xi - xh)) / sqr(x1 - x0) / (x1 - xh),
-            ((xi - x0) * sqr(xi - x1) * (xi - xh)) / sqr(x0 - x1) / (x0 - xh),
-            ((xi - x1) * sqr(xi - x0) * (xi - xh)) / sqr(x0 - x1) / (x1 - xh),
-          ];
-          return add(
-            add(add(add(mul(y0, w[0]), mul(yh, w[1])), mul(y1, w[2])), mul(p, w[3])),
-            mul(q, w[4])
-          );
-        };
-        numeric.Dopri.prototype.at = function at(x) {
-          var i,
-            j,
-            k,
-            floor = Math.floor;
-          if (typeof x !== "number") {
-            var n = x.length,
-              ret = Array(n);
-            for (i = n - 1; i !== -1; --i) {
-              ret[i] = this.at(x[i]);
-            }
-            return ret;
-          }
-          var x0 = this.x;
-          i = 0;
-          j = x0.length - 1;
-          while (j - i > 1) {
-            k = floor(0.5 * (i + j));
-            if (x0[k] <= x) i = k;
-            else j = k;
-          }
-          return this._at(x, i);
-        };
-
-        numeric.dopri = function dopri(x0, x1, y0, f, tol, maxit, event) {
-          if (typeof tol === "undefined") {
-            tol = 1e-6;
-          }
-          if (typeof maxit === "undefined") {
-            maxit = 1000;
-          }
-          var xs = [x0],
-            ys = [y0],
-            k1 = [f(x0, y0)],
-            k2,
-            k3,
-            k4,
-            k5,
-            k6,
-            k7,
-            ymid = [];
-          var A2 = 1 / 5;
-          var A3 = [3 / 40, 9 / 40];
-          var A4 = [44 / 45, -56 / 15, 32 / 9];
-          var A5 = [19372 / 6561, -25360 / 2187, 64448 / 6561, -212 / 729];
-          var A6 = [9017 / 3168, -355 / 33, 46732 / 5247, 49 / 176, -5103 / 18656];
-          var b = [35 / 384, 0, 500 / 1113, 125 / 192, -2187 / 6784, 11 / 84];
-          var bm = [
-            (0.5 * 6025192743) / 30085553152,
-            0,
-            (0.5 * 51252292925) / 65400821598,
-            (0.5 * -2691868925) / 45128329728,
-            (0.5 * 187940372067) / 1594534317056,
-            (0.5 * -1776094331) / 19743644256,
-            (0.5 * 11237099) / 235043384,
-          ];
-          var c = [1 / 5, 3 / 10, 4 / 5, 8 / 9, 1, 1];
-          var e = [-71 / 57600, 0, 71 / 16695, -71 / 1920, 17253 / 339200, -22 / 525, 1 / 40];
-          var i = 0,
-            er,
-            j;
-          var h = (x1 - x0) / 10;
-          var it = 0;
-          var add = numeric.add,
-            mul = numeric.mul,
-            y1,
-            erinf;
-          var max = Math.max,
-            min = Math.min,
-            abs = Math.abs,
-            norminf = numeric.norminf,
-            pow = Math.pow;
-          var any = numeric.any,
-            lt = numeric.lt,
-            and = numeric.and,
-            sub = numeric.sub;
-          var e0, e1, ev;
-          var ret = new numeric.Dopri(xs, ys, k1, ymid, -1, "");
-          if (typeof event === "function") e0 = event(x0, y0);
-          while (x0 < x1 && it < maxit) {
-            ++it;
-            if (x0 + h > x1) h = x1 - x0;
-            k2 = f(x0 + c[0] * h, add(y0, mul(A2 * h, k1[i])));
-            k3 = f(x0 + c[1] * h, add(add(y0, mul(A3[0] * h, k1[i])), mul(A3[1] * h, k2)));
-            k4 = f(
-              x0 + c[2] * h,
-              add(add(add(y0, mul(A4[0] * h, k1[i])), mul(A4[1] * h, k2)), mul(A4[2] * h, k3))
-            );
-            k5 = f(
-              x0 + c[3] * h,
-              add(
-                add(add(add(y0, mul(A5[0] * h, k1[i])), mul(A5[1] * h, k2)), mul(A5[2] * h, k3)),
-                mul(A5[3] * h, k4)
-              )
-            );
-            k6 = f(
-              x0 + c[4] * h,
-              add(
-                add(
-                  add(add(add(y0, mul(A6[0] * h, k1[i])), mul(A6[1] * h, k2)), mul(A6[2] * h, k3)),
-                  mul(A6[3] * h, k4)
-                ),
-                mul(A6[4] * h, k5)
-              )
-            );
-            y1 = add(
-              add(
-                add(add(add(y0, mul(k1[i], h * b[0])), mul(k3, h * b[2])), mul(k4, h * b[3])),
-                mul(k5, h * b[4])
-              ),
-              mul(k6, h * b[5])
-            );
-            k7 = f(x0 + h, y1);
-            er = add(
-              add(
-                add(
-                  add(add(mul(k1[i], h * e[0]), mul(k3, h * e[2])), mul(k4, h * e[3])),
-                  mul(k5, h * e[4])
-                ),
-                mul(k6, h * e[5])
-              ),
-              mul(k7, h * e[6])
-            );
-            if (typeof er === "number") erinf = abs(er);
-            else erinf = norminf(er);
-            if (erinf > tol) {
-              // reject
-              h = 0.2 * h * pow(tol / erinf, 0.25);
-              if (x0 + h === x0) {
-                ret.msg = "Step size became too small";
-                break;
-              }
-              continue;
-            }
-            ymid[i] = add(
-              add(
-                add(
-                  add(add(add(y0, mul(k1[i], h * bm[0])), mul(k3, h * bm[2])), mul(k4, h * bm[3])),
-                  mul(k5, h * bm[4])
-                ),
-                mul(k6, h * bm[5])
-              ),
-              mul(k7, h * bm[6])
-            );
-            ++i;
-            xs[i] = x0 + h;
-            ys[i] = y1;
-            k1[i] = k7;
-            if (typeof event === "function") {
-              var yi,
-                xl = x0,
-                xr = x0 + 0.5 * h,
-                xi;
-              e1 = event(xr, ymid[i - 1]);
-              ev = and(lt(e0, 0), lt(0, e1));
-              if (!any(ev)) {
-                xl = xr;
-                xr = x0 + h;
-                e0 = e1;
-                e1 = event(xr, y1);
-                ev = and(lt(e0, 0), lt(0, e1));
-              }
-              if (any(ev)) {
-                var xc, yc, en, ei;
-                var side = 0,
-                  sl = 1.0,
-                  sr = 1.0;
-                while (1) {
-                  if (typeof e0 === "number")
-                    xi = (sr * e1 * xl - sl * e0 * xr) / (sr * e1 - sl * e0);
-                  else {
-                    xi = xr;
-                    for (j = e0.length - 1; j !== -1; --j) {
-                      if (e0[j] < 0 && e1[j] > 0)
-                        xi = min(
-                          xi,
-                          (sr * e1[j] * xl - sl * e0[j] * xr) / (sr * e1[j] - sl * e0[j])
-                        );
-                    }
-                  }
-                  if (xi <= xl || xi >= xr) break;
-                  yi = ret._at(xi, i - 1);
-                  ei = event(xi, yi);
-                  en = and(lt(e0, 0), lt(0, ei));
-                  if (any(en)) {
-                    xr = xi;
-                    e1 = ei;
-                    ev = en;
-                    sr = 1.0;
-                    if (side === -1) sl *= 0.5;
-                    else sl = 1.0;
-                    side = -1;
-                  } else {
-                    xl = xi;
-                    e0 = ei;
-                    sl = 1.0;
-                    if (side === 1) sr *= 0.5;
-                    else sr = 1.0;
-                    side = 1;
-                  }
-                }
-                y1 = ret._at(0.5 * (x0 + xi), i - 1);
-                ret.f[i] = f(xi, yi);
-                ret.x[i] = xi;
-                ret.y[i] = yi;
-                ret.ymid[i - 1] = y1;
-                ret.events = ev;
-                ret.iterations = it;
-                return ret;
-              }
-            }
-            x0 += h;
-            y0 = y1;
-            e0 = e1;
-            h = min(0.8 * h * pow(tol / erinf, 0.25), 4 * h);
-          }
-          ret.iterations = it;
-          return ret;
-        };
-
-        // 11. Ax = b
-        numeric.LU = function (A, fast) {
-          fast = fast || false;
-
-          var abs = Math.abs;
-          var i, j, k, absAjk, Akk, Ak, Pk, Ai;
-          var max;
-          var n = A.length,
-            n1 = n - 1;
-          var P = new Array(n);
-          if (!fast) A = numeric.clone(A);
-
-          for (k = 0; k < n; ++k) {
-            Pk = k;
-            Ak = A[k];
-            max = abs(Ak[k]);
-            for (j = k + 1; j < n; ++j) {
-              absAjk = abs(A[j][k]);
-              if (max < absAjk) {
-                max = absAjk;
-                Pk = j;
-              }
-            }
-            P[k] = Pk;
-
-            if (Pk != k) {
-              A[k] = A[Pk];
-              A[Pk] = Ak;
-              Ak = A[k];
-            }
-
-            Akk = Ak[k];
-
-            for (i = k + 1; i < n; ++i) {
-              A[i][k] /= Akk;
-            }
-
-            for (i = k + 1; i < n; ++i) {
-              Ai = A[i];
-              for (j = k + 1; j < n1; ++j) {
-                Ai[j] -= Ai[k] * Ak[j];
-                ++j;
-                Ai[j] -= Ai[k] * Ak[j];
-              }
-              if (j === n1) Ai[j] -= Ai[k] * Ak[j];
-            }
-          }
-
-          return {
-            LU: A,
-            P: P,
-          };
-        };
-
-        numeric.LUsolve = function LUsolve(LUP, b) {
-          var i, j;
-          var LU = LUP.LU;
-          var n = LU.length;
-          var x = numeric.clone(b);
-          var P = LUP.P;
-          var Pi, LUi, LUii, tmp;
-
-          for (i = n - 1; i !== -1; --i) x[i] = b[i];
-          for (i = 0; i < n; ++i) {
-            Pi = P[i];
-            if (P[i] !== i) {
-              tmp = x[i];
-              x[i] = x[Pi];
-              x[Pi] = tmp;
-            }
-
-            LUi = LU[i];
-            for (j = 0; j < i; ++j) {
-              x[i] -= x[j] * LUi[j];
-            }
-          }
-
-          for (i = n - 1; i >= 0; --i) {
-            LUi = LU[i];
-            for (j = i + 1; j < n; ++j) {
-              x[i] -= x[j] * LUi[j];
-            }
-
-            x[i] /= LUi[i];
-          }
-
-          return x;
-        };
-
-        numeric.solve = function solve(A, b, fast) {
-          return numeric.LUsolve(numeric.LU(A, fast), b);
-        };
-
-        // 12. Linear programming
-        numeric.echelonize = function echelonize(A) {
-          var s = numeric.dim(A),
-            m = s[0],
-            n = s[1];
-          var I = numeric.identity(m);
-          var P = Array(m);
-          var i, j, k, l, Ai, Ii, Z, a;
-          var abs = Math.abs;
-          var diveq = numeric.diveq;
-          A = numeric.clone(A);
-          for (i = 0; i < m; ++i) {
-            k = 0;
-            Ai = A[i];
-            Ii = I[i];
-            for (j = 1; j < n; ++j) if (abs(Ai[k]) < abs(Ai[j])) k = j;
-            P[i] = k;
-            diveq(Ii, Ai[k]);
-            diveq(Ai, Ai[k]);
-            for (j = 0; j < m; ++j)
-              if (j !== i) {
-                Z = A[j];
-                a = Z[k];
-                for (l = n - 1; l !== -1; --l) Z[l] -= Ai[l] * a;
-                Z = I[j];
-                for (l = m - 1; l !== -1; --l) Z[l] -= Ii[l] * a;
-              }
-          }
-          return { I: I, A: A, P: P };
-        };
-
-        numeric.__solveLP = function __solveLP(c, A, b, tol, maxit, x, flag) {
-          var sum = numeric.sum,
-            log = numeric.log,
-            mul = numeric.mul,
-            sub = numeric.sub,
-            dot = numeric.dot,
-            div = numeric.div,
-            add = numeric.add;
-          var m = c.length,
-            n = b.length,
-            y;
-          var unbounded = false,
-            cb,
-            i0 = 0;
-          var alpha = 1.0;
-          var f0,
-            df0,
-            AT = numeric.transpose(A),
-            svd = numeric.svd,
-            transpose = numeric.transpose,
-            leq = numeric.leq,
-            sqrt = Math.sqrt,
-            abs = Math.abs;
-          var muleq = numeric.muleq;
-          var norm = numeric.norminf,
-            any = numeric.any,
-            min = Math.min;
-          var all = numeric.all,
-            gt = numeric.gt;
-          var p = Array(m),
-            A0 = Array(n),
-            e = numeric.rep([n], 1),
-            H;
-          var solve = numeric.solve,
-            z = sub(b, dot(A, x)),
-            count;
-          var dotcc = dot(c, c);
-          var g;
-          for (count = i0; count < maxit; ++count) {
-            var i, j, d;
-            for (i = n - 1; i !== -1; --i) A0[i] = div(A[i], z[i]);
-            var A1 = transpose(A0);
-            for (i = m - 1; i !== -1; --i) p[i] = /*x[i]+*/ sum(A1[i]);
-            alpha = 0.25 * abs(dotcc / dot(c, p));
-            var a1 = 100 * sqrt(dotcc / dot(p, p));
-            if (!isFinite(alpha) || alpha > a1) alpha = a1;
-            g = add(c, mul(alpha, p));
-            H = dot(A1, A0);
-            for (i = m - 1; i !== -1; --i) H[i][i] += 1;
-            d = solve(H, div(g, alpha), true);
-            var t0 = div(z, dot(A, d));
-            var t = 1.0;
-            for (i = n - 1; i !== -1; --i) if (t0[i] < 0) t = min(t, -0.999 * t0[i]);
-            y = sub(x, mul(d, t));
-            z = sub(b, dot(A, y));
-            if (!all(gt(z, 0))) return { solution: x, message: "", iterations: count };
-            x = y;
-            if (alpha < tol) return { solution: y, message: "", iterations: count };
-            if (flag) {
-              var s = dot(c, g),
-                Ag = dot(A, g);
-              unbounded = true;
-              for (i = n - 1; i !== -1; --i)
-                if (s * Ag[i] < 0) {
-                  unbounded = false;
-                  break;
-                }
-            } else {
-              if (x[m - 1] >= 0) unbounded = false;
-              else unbounded = true;
-            }
-            if (unbounded) return { solution: y, message: "Unbounded", iterations: count };
-          }
-          return { solution: x, message: "maximum iteration count exceeded", iterations: count };
-        };
-
-        numeric._solveLP = function _solveLP(c, A, b, tol, maxit) {
-          var m = c.length,
-            n = b.length,
-            y;
-          var sum = numeric.sum,
-            log = numeric.log,
-            mul = numeric.mul,
-            sub = numeric.sub,
-            dot = numeric.dot,
-            div = numeric.div,
-            add = numeric.add;
-          var c0 = numeric.rep([m], 0).concat([1]);
-          var J = numeric.rep([n, 1], -1);
-          var A0 = numeric.blockMatrix([[A, J]]);
-          var b0 = b;
-          var y = numeric.rep([m], 0).concat(Math.max(0, numeric.sup(numeric.neg(b))) + 1);
-          var x0 = numeric.__solveLP(c0, A0, b0, tol, maxit, y, false);
-          var x = numeric.clone(x0.solution);
-          x.length = m;
-          var foo = numeric.inf(sub(b, dot(A, x)));
-          if (foo < 0) {
-            return { solution: NaN, message: "Infeasible", iterations: x0.iterations };
-          }
-          var ret = numeric.__solveLP(c, A, b, tol, maxit - x0.iterations, x, true);
-          ret.iterations += x0.iterations;
-          return ret;
-        };
-
-        numeric.solveLP = function solveLP(c, A, b, Aeq, beq, tol, maxit) {
-          if (typeof maxit === "undefined") maxit = 1000;
-          if (typeof tol === "undefined") tol = numeric.epsilon;
-          if (typeof Aeq === "undefined") return numeric._solveLP(c, A, b, tol, maxit);
-          var m = Aeq.length,
-            n = Aeq[0].length,
-            o = A.length;
-          var B = numeric.echelonize(Aeq);
-          var flags = numeric.rep([n], 0);
-          var P = B.P;
-          var Q = [];
-          var i;
-          for (i = P.length - 1; i !== -1; --i) flags[P[i]] = 1;
-          for (i = n - 1; i !== -1; --i) if (flags[i] === 0) Q.push(i);
-          var g = numeric.getRange;
-          var I = numeric.linspace(0, m - 1),
-            J = numeric.linspace(0, o - 1);
-          var Aeq2 = g(Aeq, I, Q),
-            A1 = g(A, J, P),
-            A2 = g(A, J, Q),
-            dot = numeric.dot,
-            sub = numeric.sub;
-          var A3 = dot(A1, B.I);
-          var A4 = sub(A2, dot(A3, Aeq2)),
-            b4 = sub(b, dot(A3, beq));
-          var c1 = Array(P.length),
-            c2 = Array(Q.length);
-          for (i = P.length - 1; i !== -1; --i) c1[i] = c[P[i]];
-          for (i = Q.length - 1; i !== -1; --i) c2[i] = c[Q[i]];
-          var c4 = sub(c2, dot(c1, dot(B.I, Aeq2)));
-          var S = numeric._solveLP(c4, A4, b4, tol, maxit);
-          var x2 = S.solution;
-          if (x2 !== x2) return S;
-          var x1 = dot(B.I, sub(beq, dot(Aeq2, x2)));
-          var x = Array(c.length);
-          for (i = P.length - 1; i !== -1; --i) x[P[i]] = x1[i];
-          for (i = Q.length - 1; i !== -1; --i) x[Q[i]] = x2[i];
-          return { solution: x, message: S.message, iterations: S.iterations };
-        };
-
-        numeric.MPStoLP = function MPStoLP(MPS) {
-          if (MPS instanceof String) {
-            MPS.split("\n");
-          }
-          var state = 0;
-          var states = ["Initial state", "NAME", "ROWS", "COLUMNS", "RHS", "BOUNDS", "ENDATA"];
-          var n = MPS.length;
-          var i,
-            j,
-            z,
-            N = 0,
-            rows = {},
-            sign = [],
-            rl = 0,
-            vars = {},
-            nv = 0;
-          var name;
-          var c = [],
-            A = [],
-            b = [];
-          function err(e) {
-            throw new Error(
-              "MPStoLP: " +
-                e +
-                "\nLine " +
-                i +
-                ": " +
-                MPS[i] +
-                "\nCurrent state: " +
-                states[state] +
-                "\n"
-            );
-          }
-          for (i = 0; i < n; ++i) {
-            z = MPS[i];
-            var w0 = z.match(/\S*/g);
-            var w = [];
-            for (j = 0; j < w0.length; ++j) if (w0[j] !== "") w.push(w0[j]);
-            if (w.length === 0) continue;
-            for (j = 0; j < states.length; ++j)
-              if (z.substr(0, states[j].length) === states[j]) break;
-            if (j < states.length) {
-              state = j;
-              if (j === 1) {
-                name = w[1];
-              }
-              if (j === 6)
-                return { name: name, c: c, A: numeric.transpose(A), b: b, rows: rows, vars: vars };
-              continue;
-            }
-            switch (state) {
-              case 0:
-              case 1:
-                err("Unexpected line");
-              case 2:
-                switch (w[0]) {
-                  case "N":
-                    if (N === 0) N = w[1];
-                    else err("Two or more N rows");
-                    break;
-                  case "L":
-                    rows[w[1]] = rl;
-                    sign[rl] = 1;
-                    b[rl] = 0;
-                    ++rl;
-                    break;
-                  case "G":
-                    rows[w[1]] = rl;
-                    sign[rl] = -1;
-                    b[rl] = 0;
-                    ++rl;
-                    break;
-                  case "E":
-                    rows[w[1]] = rl;
-                    sign[rl] = 0;
-                    b[rl] = 0;
-                    ++rl;
-                    break;
-                  default:
-                    err("Parse error " + numeric.prettyPrint(w));
-                }
-                break;
-              case 3:
-                if (!vars.hasOwnProperty(w[0])) {
-                  vars[w[0]] = nv;
-                  c[nv] = 0;
-                  A[nv] = numeric.rep([rl], 0);
-                  ++nv;
-                }
-                var p = vars[w[0]];
-                for (j = 1; j < w.length; j += 2) {
-                  if (w[j] === N) {
-                    c[p] = parseFloat(w[j + 1]);
-                    continue;
-                  }
-                  var q = rows[w[j]];
-                  A[p][q] = (sign[q] < 0 ? -1 : 1) * parseFloat(w[j + 1]);
-                }
-                break;
-              case 4:
-                for (j = 1; j < w.length; j += 2)
-                  b[rows[w[j]]] = (sign[rows[w[j]]] < 0 ? -1 : 1) * parseFloat(w[j + 1]);
-                break;
-              case 5:
-                /*FIXME*/ break;
-              case 6:
-                err("Internal error");
-            }
-          }
-          err("Reached end of file without ENDATA");
-        };
-        // seedrandom.js version 2.0.
-        // Author: David Bau 4/2/2011
-        //
-        // Defines a method Math.seedrandom() that, when called, substitutes
-        // an explicitly seeded RC4-based algorithm for Math.random().  Also
-        // supports automatic seeding from local or network sources of entropy.
-        //
-        // Usage:
-        //
-        //   <script src=http://davidbau.com/encode/seedrandom-min.js></script>
-        //
-        //   Math.seedrandom('yipee'); Sets Math.random to a function that is
-        //                             initialized using the given explicit seed.
-        //
-        //   Math.seedrandom();        Sets Math.random to a function that is
-        //                             seeded using the current time, dom state,
-        //                             and other accumulated local entropy.
-        //                             The generated seed string is returned.
-        //
-        //   Math.seedrandom('yowza', true);
-        //                             Seeds using the given explicit seed mixed
-        //                             together with accumulated entropy.
-        //
-        //   <script src="http://bit.ly/srandom-512"></script>
-        //                             Seeds using physical random bits downloaded
-        //                             from random.org.
-        //
-        //   <script src="https://jsonlib.appspot.com/urandom?callback=Math.seedrandom">
-        //   </script>                 Seeds using urandom bits from call.jsonlib.com,
-        //                             which is faster than random.org.
-        //
-        // Examples:
-        //
-        //   Math.seedrandom("hello");            // Use "hello" as the seed.
-        //   document.write(Math.random());       // Always 0.5463663768140734
-        //   document.write(Math.random());       // Always 0.43973793770592234
-        //   var rng1 = Math.random;              // Remember the current prng.
-        //
-        //   var autoseed = Math.seedrandom();    // New prng with an automatic seed.
-        //   document.write(Math.random());       // Pretty much unpredictable.
-        //
-        //   Math.random = rng1;                  // Continue "hello" prng sequence.
-        //   document.write(Math.random());       // Always 0.554769432473455
-        //
-        //   Math.seedrandom(autoseed);           // Restart at the previous seed.
-        //   document.write(Math.random());       // Repeat the 'unpredictable' value.
-        //
-        // Notes:
-        //
-        // Each time seedrandom('arg') is called, entropy from the passed seed
-        // is accumulated in a pool to help generate future seeds for the
-        // zero-argument form of Math.seedrandom, so entropy can be injected over
-        // time by calling seedrandom with explicit data repeatedly.
-        //
-        // On speed - This javascript implementation of Math.random() is about
-        // 3-10x slower than the built-in Math.random() because it is not native
-        // code, but this is typically fast enough anyway.  Seeding is more expensive,
-        // especially if you use auto-seeding.  Some details (timings on Chrome 4):
-        //
-        // Our Math.random()            - avg less than 0.002 milliseconds per call
-        // seedrandom('explicit')       - avg less than 0.5 milliseconds per call
-        // seedrandom('explicit', true) - avg less than 2 milliseconds per call
-        // seedrandom()                 - avg about 38 milliseconds per call
-        //
-        // LICENSE (BSD):
-        //
-        // Copyright 2010 David Bau, all rights reserved.
-        //
-        // Redistribution and use in source and binary forms, with or without
-        // modification, are permitted provided that the following conditions are met:
-        //
-        //   1. Redistributions of source code must retain the above copyright
-        //      notice, this list of conditions and the following disclaimer.
-        //
-        //   2. Redistributions in binary form must reproduce the above copyright
-        //      notice, this list of conditions and the following disclaimer in the
-        //      documentation and/or other materials provided with the distribution.
-        //
-        //   3. Neither the name of this module nor the names of its contributors may
-        //      be used to endorse or promote products derived from this software
-        //      without specific prior written permission.
-        //
-        // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-        // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-        // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
-        // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
-        // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
-        // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
-        // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
-        // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
-        // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
-        // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
-        // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-        //
-        /**
-         * All code is in an anonymous closure to keep the global namespace clean.
-         *
-         * @param {number=} overflow
-         * @param {number=} startdenom
-         */
-
-        // Patched by Seb so that seedrandom.js does not pollute the Math object.
-        // My tests suggest that doing Math.trouble = 1 makes Math lookups about 5%
-        // slower.
-        numeric.seedrandom = { pow: Math.pow, random: Math.random };
-
-        (function (pool, math, width, chunks, significance, overflow, startdenom) {
-          //
-          // seedrandom()
-          // This is the seedrandom function described above.
-          //
-          math["seedrandom"] = function seedrandom(seed, use_entropy) {
-            var key = [];
-            var arc4;
-
-            // Flatten the seed string or build one from local entropy if needed.
-            seed = mixkey(
-              flatten(
-                use_entropy
-                  ? [seed, pool]
-                  : arguments.length
-                  ? seed
-                  : [new Date().getTime(), pool, window],
-                3
-              ),
-              key
-            );
-
-            // Use the seed to initialize an ARC4 generator.
-            arc4 = new ARC4(key);
-
-            // Mix the randomness into accumulated entropy.
-            mixkey(arc4.S, pool);
-
-            // Override Math.random
-
-            // This function returns a random double in [0, 1) that contains
-            // randomness in every bit of the mantissa of the IEEE 754 value.
-
-            math["random"] = function random() {
-              // Closure to return a random double:
-              var n = arc4.g(chunks); // Start with a numerator n < 2 ^ 48
-              var d = startdenom; //   and denominator d = 2 ^ 48.
-              var x = 0; //   and no 'extra last byte'.
-              while (n < significance) {
-                // Fill up all significant digits by
-                n = (n + x) * width; //   shifting numerator and
-                d *= width; //   denominator and generating a
-                x = arc4.g(1); //   new least-significant-byte.
-              }
-              while (n >= overflow) {
-                // To avoid rounding up, before adding
-                n /= 2; //   last byte, shift everything
-                d /= 2; //   right using integer math until
-                x >>>= 1; //   we have exactly the desired bits.
-              }
-              return (n + x) / d; // Form the number within [0, 1).
-            };
-
-            // Return the seed that was used
-            return seed;
-          };
-
-          //
-          // ARC4
-          //
-          // An ARC4 implementation.  The constructor takes a key in the form of
-          // an array of at most (width) integers that should be 0 <= x < (width).
-          //
-          // The g(count) method returns a pseudorandom integer that concatenates
-          // the next (count) outputs from ARC4.  Its return value is a number x
-          // that is in the range 0 <= x < (width ^ count).
-          //
-          /** @constructor */
-          function ARC4(key) {
-            var t,
-              u,
-              me = this,
-              keylen = key.length;
-            var i = 0,
-              j = (me.i = me.j = me.m = 0);
-            me.S = [];
-            me.c = [];
-
-            // The empty key [] is treated as [0].
-            if (!keylen) {
-              key = [keylen++];
-            }
-
-            // Set up S using the standard key scheduling algorithm.
-            while (i < width) {
-              me.S[i] = i++;
-            }
-            for (i = 0; i < width; i++) {
-              t = me.S[i];
-              j = lowbits(j + t + key[i % keylen]);
-              u = me.S[j];
-              me.S[i] = u;
-              me.S[j] = t;
-            }
-
-            // The "g" method returns the next (count) outputs as one number.
-            me.g = function getnext(count) {
-              var s = me.S;
-              var i = lowbits(me.i + 1);
-              var t = s[i];
-              var j = lowbits(me.j + t);
-              var u = s[j];
-              s[i] = u;
-              s[j] = t;
-              var r = s[lowbits(t + u)];
-              while (--count) {
-                i = lowbits(i + 1);
-                t = s[i];
-                j = lowbits(j + t);
-                u = s[j];
-                s[i] = u;
-                s[j] = t;
-                r = r * width + s[lowbits(t + u)];
-              }
-              me.i = i;
-              me.j = j;
-              return r;
-            };
-            // For robust unpredictability discard an initial batch of values.
-            // See http://www.rsa.com/rsalabs/node.asp?id=2009
-            me.g(width);
-          }
-
-          //
-          // flatten()
-          // Converts an object tree to nested arrays of strings.
-          //
-          /** @param {Object=} result
-           * @param {string=} prop
-           * @param {string=} typ */
-          function flatten(obj, depth, result, prop, typ) {
-            result = [];
-            typ = typeof obj;
-            if (depth && typ == "object") {
-              for (prop in obj) {
-                if (prop.indexOf("S") < 5) {
-                  // Avoid FF3 bug (local/sessionStorage)
-                  try {
-                    result.push(flatten(obj[prop], depth - 1));
-                  } catch (e) {}
-                }
-              }
-            }
-            return result.length ? result : obj + (typ != "string" ? "\0" : "");
-          }
-
-          //
-          // mixkey()
-          // Mixes a string seed into a key that is an array of integers, and
-          // returns a shortened string seed that is equivalent to the result key.
-          //
-          /** @param {number=} smear
-           * @param {number=} j */
-          function mixkey(seed, key, smear, j) {
-            seed += ""; // Ensure the seed is a string
-            smear = 0;
-            for (j = 0; j < seed.length; j++) {
-              key[lowbits(j)] = lowbits((smear ^= key[lowbits(j)] * 19) + seed.charCodeAt(j));
-            }
-            seed = "";
-            for (j in key) {
-              seed += String.fromCharCode(key[j]);
-            }
-            return seed;
-          }
-
-          //
-          // lowbits()
-          // A quick "n mod width" for width a power of 2.
-          //
-          function lowbits(n) {
-            return n & (width - 1);
-          }
-
-          //
-          // The following constants are related to IEEE 754 limits.
-          //
-          startdenom = math.pow(width, chunks);
-          significance = math.pow(2, significance);
-          overflow = significance * 2;
-
-          //
-          // When seedrandom.js is loaded, we immediately mix a few bits
-          // from the built-in RNG into the entropy pool.  Because we do
-          // not want to intefere with determinstic PRNG state later,
-          // seedrandom will not call math.random on its own again after
-          // initialization.
-          //
-          mixkey(math.random(), pool);
-
-          // End anonymous scope, and pass initial values.
-        })(
-          [], // pool: entropy pool starts empty
-          numeric.seedrandom, // math: package containing random, pow, and seedrandom
-          256, // width: each RC4 output is 0 <= x < 256
-          6, // chunks: at least six RC4 outputs for each double
-          52 // significance: there are 52 significant digits in a double
-        );
-        /* This file is a slightly modified version of quadprog.js from Alberto Santini.
-         * It has been slightly modified by Sébastien Loisel to make sure that it handles
-         * 0-based Arrays instead of 1-based Arrays.
-         * License is in resources/LICENSE.quadprog */
-        (function (exports) {
-          function base0to1(A) {
-            if (typeof A !== "object") {
-              return A;
-            }
-            var ret = [],
-              i,
-              n = A.length;
-            for (i = 0; i < n; i++) ret[i + 1] = base0to1(A[i]);
-            return ret;
-          }
-          function base1to0(A) {
-            if (typeof A !== "object") {
-              return A;
-            }
-            var ret = [],
-              i,
-              n = A.length;
-            for (i = 1; i < n; i++) ret[i - 1] = base1to0(A[i]);
-            return ret;
-          }
-
-          function dpori(a, lda, n) {
-            var i, j, k, kp1, t;
-
-            for (k = 1; k <= n; k = k + 1) {
-              a[k][k] = 1 / a[k][k];
-              t = -a[k][k];
-              //~ dscal(k - 1, t, a[1][k], 1);
-              for (i = 1; i < k; i = i + 1) {
-                a[i][k] = t * a[i][k];
-              }
-
-              kp1 = k + 1;
-              if (n < kp1) {
-                break;
-              }
-              for (j = kp1; j <= n; j = j + 1) {
-                t = a[k][j];
-                a[k][j] = 0;
-                //~ daxpy(k, t, a[1][k], 1, a[1][j], 1);
-                for (i = 1; i <= k; i = i + 1) {
-                  a[i][j] = a[i][j] + t * a[i][k];
-                }
-              }
-            }
-          }
-
-          function dposl(a, lda, n, b) {
-            var i, k, kb, t;
-
-            for (k = 1; k <= n; k = k + 1) {
-              //~ t = ddot(k - 1, a[1][k], 1, b[1], 1);
-              t = 0;
-              for (i = 1; i < k; i = i + 1) {
-                t = t + a[i][k] * b[i];
-              }
-
-              b[k] = (b[k] - t) / a[k][k];
-            }
-
-            for (kb = 1; kb <= n; kb = kb + 1) {
-              k = n + 1 - kb;
-              b[k] = b[k] / a[k][k];
-              t = -b[k];
-              //~ daxpy(k - 1, t, a[1][k], 1, b[1], 1);
-              for (i = 1; i < k; i = i + 1) {
-                b[i] = b[i] + t * a[i][k];
-              }
-            }
-          }
-
-          function dpofa(a, lda, n, info) {
-            var i, j, jm1, k, t, s;
-
-            for (j = 1; j <= n; j = j + 1) {
-              info[1] = j;
-              s = 0;
-              jm1 = j - 1;
-              if (jm1 < 1) {
-                s = a[j][j] - s;
-                if (s <= 0) {
-                  break;
-                }
-                a[j][j] = Math.sqrt(s);
-              } else {
-                for (k = 1; k <= jm1; k = k + 1) {
-                  //~ t = a[k][j] - ddot(k - 1, a[1][k], 1, a[1][j], 1);
-                  t = a[k][j];
-                  for (i = 1; i < k; i = i + 1) {
-                    t = t - a[i][j] * a[i][k];
-                  }
-                  t = t / a[k][k];
-                  a[k][j] = t;
-                  s = s + t * t;
-                }
-                s = a[j][j] - s;
-                if (s <= 0) {
-                  break;
-                }
-                a[j][j] = Math.sqrt(s);
-              }
-              info[1] = 0;
-            }
-          }
-
-          function qpgen2(
-            dmat,
-            dvec,
-            fddmat,
-            n,
-            sol,
-            crval,
-            amat,
-            bvec,
-            fdamat,
-            q,
-            meq,
-            iact,
-            nact,
-            iter,
-            work,
-            ierr
-          ) {
-            var i,
-              j,
-              l,
-              l1,
-              info,
-              it1,
-              iwzv,
-              iwrv,
-              iwrm,
-              iwsv,
-              iwuv,
-              nvl,
-              r,
-              iwnbv,
-              temp,
-              sum,
-              t1,
-              tt,
-              gc,
-              gs,
-              nu,
-              t1inf,
-              t2min,
-              vsmall,
-              tmpa,
-              tmpb,
-              go;
-
-            r = Math.min(n, q);
-            l = 2 * n + (r * (r + 5)) / 2 + 2 * q + 1;
-
-            vsmall = 1.0e-60;
-            do {
-              vsmall = vsmall + vsmall;
-              tmpa = 1 + 0.1 * vsmall;
-              tmpb = 1 + 0.2 * vsmall;
-            } while (tmpa <= 1 || tmpb <= 1);
-
-            for (i = 1; i <= n; i = i + 1) {
-              work[i] = dvec[i];
-            }
-            for (i = n + 1; i <= l; i = i + 1) {
-              work[i] = 0;
-            }
-            for (i = 1; i <= q; i = i + 1) {
-              iact[i] = 0;
-            }
-
-            info = [];
-
-            if (ierr[1] === 0) {
-              dpofa(dmat, fddmat, n, info);
-              if (info[1] !== 0) {
-                ierr[1] = 2;
-                return;
-              }
-              dposl(dmat, fddmat, n, dvec);
-              dpori(dmat, fddmat, n);
-            } else {
-              for (j = 1; j <= n; j = j + 1) {
-                sol[j] = 0;
-                for (i = 1; i <= j; i = i + 1) {
-                  sol[j] = sol[j] + dmat[i][j] * dvec[i];
-                }
-              }
-              for (j = 1; j <= n; j = j + 1) {
-                dvec[j] = 0;
-                for (i = j; i <= n; i = i + 1) {
-                  dvec[j] = dvec[j] + dmat[j][i] * sol[i];
-                }
-              }
-            }
-
-            crval[1] = 0;
-            for (j = 1; j <= n; j = j + 1) {
-              sol[j] = dvec[j];
-              crval[1] = crval[1] + work[j] * sol[j];
-              work[j] = 0;
-              for (i = j + 1; i <= n; i = i + 1) {
-                dmat[i][j] = 0;
-              }
-            }
-            crval[1] = -crval[1] / 2;
-            ierr[1] = 0;
-
-            iwzv = n;
-            iwrv = iwzv + n;
-            iwuv = iwrv + r;
-            iwrm = iwuv + r + 1;
-            iwsv = iwrm + (r * (r + 1)) / 2;
-            iwnbv = iwsv + q;
-
-            for (i = 1; i <= q; i = i + 1) {
-              sum = 0;
-              for (j = 1; j <= n; j = j + 1) {
-                sum = sum + amat[j][i] * amat[j][i];
-              }
-              work[iwnbv + i] = Math.sqrt(sum);
-            }
-            nact = 0;
-            iter[1] = 0;
-            iter[2] = 0;
-
-            function fn_goto_50() {
-              iter[1] = iter[1] + 1;
-
-              l = iwsv;
-              for (i = 1; i <= q; i = i + 1) {
-                l = l + 1;
-                sum = -bvec[i];
-                for (j = 1; j <= n; j = j + 1) {
-                  sum = sum + amat[j][i] * sol[j];
-                }
-                if (Math.abs(sum) < vsmall) {
-                  sum = 0;
-                }
-                if (i > meq) {
-                  work[l] = sum;
-                } else {
-                  work[l] = -Math.abs(sum);
-                  if (sum > 0) {
-                    for (j = 1; j <= n; j = j + 1) {
-                      amat[j][i] = -amat[j][i];
-                    }
-                    bvec[i] = -bvec[i];
-                  }
-                }
-              }
-
-              for (i = 1; i <= nact; i = i + 1) {
-                work[iwsv + iact[i]] = 0;
-              }
-
-              nvl = 0;
-              temp = 0;
-              for (i = 1; i <= q; i = i + 1) {
-                if (work[iwsv + i] < temp * work[iwnbv + i]) {
-                  nvl = i;
-                  temp = work[iwsv + i] / work[iwnbv + i];
-                }
-              }
-              if (nvl === 0) {
-                return 999;
-              }
-
-              return 0;
-            }
-
-            function fn_goto_55() {
-              for (i = 1; i <= n; i = i + 1) {
-                sum = 0;
-                for (j = 1; j <= n; j = j + 1) {
-                  sum = sum + dmat[j][i] * amat[j][nvl];
-                }
-                work[i] = sum;
-              }
-
-              l1 = iwzv;
-              for (i = 1; i <= n; i = i + 1) {
-                work[l1 + i] = 0;
-              }
-              for (j = nact + 1; j <= n; j = j + 1) {
-                for (i = 1; i <= n; i = i + 1) {
-                  work[l1 + i] = work[l1 + i] + dmat[i][j] * work[j];
-                }
-              }
-
-              t1inf = true;
-              for (i = nact; i >= 1; i = i - 1) {
-                sum = work[i];
-                l = iwrm + (i * (i + 3)) / 2;
-                l1 = l - i;
-                for (j = i + 1; j <= nact; j = j + 1) {
-                  sum = sum - work[l] * work[iwrv + j];
-                  l = l + j;
-                }
-                sum = sum / work[l1];
-                work[iwrv + i] = sum;
-                if (iact[i] < meq) {
-                  // continue;
-                  break;
-                }
-                if (sum < 0) {
-                  // continue;
-                  break;
-                }
-                t1inf = false;
-                it1 = i;
-              }
-
-              if (!t1inf) {
-                t1 = work[iwuv + it1] / work[iwrv + it1];
-                for (i = 1; i <= nact; i = i + 1) {
-                  if (iact[i] < meq) {
-                    // continue;
-                    break;
-                  }
-                  if (work[iwrv + i] < 0) {
-                    // continue;
-                    break;
-                  }
-                  temp = work[iwuv + i] / work[iwrv + i];
-                  if (temp < t1) {
-                    t1 = temp;
-                    it1 = i;
-                  }
-                }
-              }
-
-              sum = 0;
-              for (i = iwzv + 1; i <= iwzv + n; i = i + 1) {
-                sum = sum + work[i] * work[i];
-              }
-              if (Math.abs(sum) <= vsmall) {
-                if (t1inf) {
-                  ierr[1] = 1;
-                  // GOTO 999
-                  return 999;
-                } else {
-                  for (i = 1; i <= nact; i = i + 1) {
-                    work[iwuv + i] = work[iwuv + i] - t1 * work[iwrv + i];
-                  }
-                  work[iwuv + nact + 1] = work[iwuv + nact + 1] + t1;
-                  // GOTO 700
-                  return 700;
-                }
-              } else {
-                sum = 0;
-                for (i = 1; i <= n; i = i + 1) {
-                  sum = sum + work[iwzv + i] * amat[i][nvl];
-                }
-                tt = -work[iwsv + nvl] / sum;
-                t2min = true;
-                if (!t1inf) {
-                  if (t1 < tt) {
-                    tt = t1;
-                    t2min = false;
-                  }
-                }
-
-                for (i = 1; i <= n; i = i + 1) {
-                  sol[i] = sol[i] + tt * work[iwzv + i];
-                  if (Math.abs(sol[i]) < vsmall) {
-                    sol[i] = 0;
-                  }
-                }
-
-                crval[1] = crval[1] + tt * sum * (tt / 2 + work[iwuv + nact + 1]);
-                for (i = 1; i <= nact; i = i + 1) {
-                  work[iwuv + i] = work[iwuv + i] - tt * work[iwrv + i];
-                }
-                work[iwuv + nact + 1] = work[iwuv + nact + 1] + tt;
-
-                if (t2min) {
-                  nact = nact + 1;
-                  iact[nact] = nvl;
-
-                  l = iwrm + ((nact - 1) * nact) / 2 + 1;
-                  for (i = 1; i <= nact - 1; i = i + 1) {
-                    work[l] = work[i];
-                    l = l + 1;
-                  }
-
-                  if (nact === n) {
-                    work[l] = work[n];
-                  } else {
-                    for (i = n; i >= nact + 1; i = i - 1) {
-                      if (work[i] === 0) {
-                        // continue;
-                        break;
-                      }
-                      gc = Math.max(Math.abs(work[i - 1]), Math.abs(work[i]));
-                      gs = Math.min(Math.abs(work[i - 1]), Math.abs(work[i]));
-                      if (work[i - 1] >= 0) {
-                        temp = Math.abs(gc * Math.sqrt(1 + (gs * gs) / (gc * gc)));
-                      } else {
-                        temp = -Math.abs(gc * Math.sqrt(1 + (gs * gs) / (gc * gc)));
-                      }
-                      gc = work[i - 1] / temp;
-                      gs = work[i] / temp;
-
-                      if (gc === 1) {
-                        // continue;
-                        break;
-                      }
-                      if (gc === 0) {
-                        work[i - 1] = gs * temp;
-                        for (j = 1; j <= n; j = j + 1) {
-                          temp = dmat[j][i - 1];
-                          dmat[j][i - 1] = dmat[j][i];
-                          dmat[j][i] = temp;
-                        }
-                      } else {
-                        work[i - 1] = temp;
-                        nu = gs / (1 + gc);
-                        for (j = 1; j <= n; j = j + 1) {
-                          temp = gc * dmat[j][i - 1] + gs * dmat[j][i];
-                          dmat[j][i] = nu * (dmat[j][i - 1] + temp) - dmat[j][i];
-                          dmat[j][i - 1] = temp;
-                        }
-                      }
-                    }
-                    work[l] = work[nact];
-                  }
-                } else {
-                  sum = -bvec[nvl];
-                  for (j = 1; j <= n; j = j + 1) {
-                    sum = sum + sol[j] * amat[j][nvl];
-                  }
-                  if (nvl > meq) {
-                    work[iwsv + nvl] = sum;
-                  } else {
-                    work[iwsv + nvl] = -Math.abs(sum);
-                    if (sum > 0) {
-                      for (j = 1; j <= n; j = j + 1) {
-                        amat[j][nvl] = -amat[j][nvl];
-                      }
-                      bvec[nvl] = -bvec[nvl];
-                    }
-                  }
-                  // GOTO 700
-                  return 700;
-                }
-              }
-
-              return 0;
-            }
-
-            function fn_goto_797() {
-              l = iwrm + (it1 * (it1 + 1)) / 2 + 1;
-              l1 = l + it1;
-              if (work[l1] === 0) {
-                // GOTO 798
-                return 798;
-              }
-              gc = Math.max(Math.abs(work[l1 - 1]), Math.abs(work[l1]));
-              gs = Math.min(Math.abs(work[l1 - 1]), Math.abs(work[l1]));
-              if (work[l1 - 1] >= 0) {
-                temp = Math.abs(gc * Math.sqrt(1 + (gs * gs) / (gc * gc)));
-              } else {
-                temp = -Math.abs(gc * Math.sqrt(1 + (gs * gs) / (gc * gc)));
-              }
-              gc = work[l1 - 1] / temp;
-              gs = work[l1] / temp;
-
-              if (gc === 1) {
-                // GOTO 798
-                return 798;
-              }
-              if (gc === 0) {
-                for (i = it1 + 1; i <= nact; i = i + 1) {
-                  temp = work[l1 - 1];
-                  work[l1 - 1] = work[l1];
-                  work[l1] = temp;
-                  l1 = l1 + i;
-                }
-                for (i = 1; i <= n; i = i + 1) {
-                  temp = dmat[i][it1];
-                  dmat[i][it1] = dmat[i][it1 + 1];
-                  dmat[i][it1 + 1] = temp;
-                }
-              } else {
-                nu = gs / (1 + gc);
-                for (i = it1 + 1; i <= nact; i = i + 1) {
-                  temp = gc * work[l1 - 1] + gs * work[l1];
-                  work[l1] = nu * (work[l1 - 1] + temp) - work[l1];
-                  work[l1 - 1] = temp;
-                  l1 = l1 + i;
-                }
-                for (i = 1; i <= n; i = i + 1) {
-                  temp = gc * dmat[i][it1] + gs * dmat[i][it1 + 1];
-                  dmat[i][it1 + 1] = nu * (dmat[i][it1] + temp) - dmat[i][it1 + 1];
-                  dmat[i][it1] = temp;
-                }
-              }
-
-              return 0;
-            }
-
-            function fn_goto_798() {
-              l1 = l - it1;
-              for (i = 1; i <= it1; i = i + 1) {
-                work[l1] = work[l];
-                l = l + 1;
-                l1 = l1 + 1;
-              }
-
-              work[iwuv + it1] = work[iwuv + it1 + 1];
-              iact[it1] = iact[it1 + 1];
-              it1 = it1 + 1;
-              if (it1 < nact) {
-                // GOTO 797
-                return 797;
-              }
-
-              return 0;
-            }
-
-            function fn_goto_799() {
-              work[iwuv + nact] = work[iwuv + nact + 1];
-              work[iwuv + nact + 1] = 0;
-              iact[nact] = 0;
-              nact = nact - 1;
-              iter[2] = iter[2] + 1;
-
-              return 0;
-            }
-
-            go = 0;
-            while (true) {
-              go = fn_goto_50();
-              if (go === 999) {
-                return;
-              }
-              while (true) {
-                go = fn_goto_55();
-                if (go === 0) {
-                  break;
-                }
-                if (go === 999) {
-                  return;
-                }
-                if (go === 700) {
-                  if (it1 === nact) {
-                    fn_goto_799();
-                  } else {
-                    while (true) {
-                      fn_goto_797();
-                      go = fn_goto_798();
-                      if (go !== 797) {
-                        break;
-                      }
-                    }
-                    fn_goto_799();
-                  }
-                }
-              }
-            }
-          }
-
-          function solveQP(Dmat, dvec, Amat, bvec, meq, factorized) {
-            Dmat = base0to1(Dmat);
-            dvec = base0to1(dvec);
-            Amat = base0to1(Amat);
-            var i,
-              n,
-              q,
-              nact,
-              r,
-              crval = [],
-              iact = [],
-              sol = [],
-              work = [],
-              iter = [],
-              message;
-
-            meq = meq || 0;
-            factorized = factorized ? base0to1(factorized) : [undefined, 0];
-            bvec = bvec ? base0to1(bvec) : [];
-
-            // In Fortran the array index starts from 1
-            n = Dmat.length - 1;
-            q = Amat[1].length - 1;
-
-            if (!bvec) {
-              for (i = 1; i <= q; i = i + 1) {
-                bvec[i] = 0;
-              }
-            }
-            for (i = 1; i <= q; i = i + 1) {
-              iact[i] = 0;
-            }
-            nact = 0;
-            r = Math.min(n, q);
-            for (i = 1; i <= n; i = i + 1) {
-              sol[i] = 0;
-            }
-            crval[1] = 0;
-            for (i = 1; i <= 2 * n + (r * (r + 5)) / 2 + 2 * q + 1; i = i + 1) {
-              work[i] = 0;
-            }
-            for (i = 1; i <= 2; i = i + 1) {
-              iter[i] = 0;
-            }
-
-            qpgen2(
-              Dmat,
-              dvec,
-              n,
-              n,
-              sol,
-              crval,
-              Amat,
-              bvec,
-              n,
-              q,
-              meq,
-              iact,
-              nact,
-              iter,
-              work,
-              factorized
-            );
-
-            message = "";
-            if (factorized[1] === 1) {
-              message = "constraints are inconsistent, no solution!";
-            }
-            if (factorized[1] === 2) {
-              message = "matrix D in quadratic function is not positive definite!";
-            }
-
-            return {
-              solution: base1to0(sol),
-              value: base1to0(crval),
-              unconstrained_solution: base1to0(dvec),
-              iterations: base1to0(iter),
-              iact: base1to0(iact),
-              message: message,
-            };
-          }
-          exports.solveQP = solveQP;
-        })(numeric);
-        /*
-Shanti Rao sent me this routine by private email. I had to modify it
-slightly to work on Arrays instead of using a Matrix object.
-It is apparently translated from http://stitchpanorama.sourceforge.net/Python/svd.py
-*/
-
-        numeric.svd = function svd(A) {
-          var temp;
-          //Compute the thin SVD from G. H. Golub and C. Reinsch, Numer. Math. 14, 403-420 (1970)
-          var prec = numeric.epsilon; //Math.pow(2,-52) // assumes double prec
-          var tolerance = 1e-64 / prec;
-          var itmax = 50;
-          var c = 0;
-          var i = 0;
-          var j = 0;
-          var k = 0;
-          var l = 0;
-
-          var u = numeric.clone(A);
-          var m = u.length;
-
-          var n = u[0].length;
-
-          if (m < n) throw "Need more rows than columns";
-
-          var e = new Array(n);
-          var q = new Array(n);
-          for (i = 0; i < n; i++) e[i] = q[i] = 0.0;
-          var v = numeric.rep([n, n], 0);
-          //	v.zero();
-
-          function pythag(a, b) {
-            a = Math.abs(a);
-            b = Math.abs(b);
-            if (a > b) return a * Math.sqrt(1.0 + (b * b) / a / a);
-            else if (b == 0.0) return a;
-            return b * Math.sqrt(1.0 + (a * a) / b / b);
-          }
-
-          //Householder's reduction to bidiagonal form
-
-          var f = 0.0;
-          var g = 0.0;
-          var h = 0.0;
-          var x = 0.0;
-          var y = 0.0;
-          var z = 0.0;
-          var s = 0.0;
-
-          for (i = 0; i < n; i++) {
-            e[i] = g;
-            s = 0.0;
-            l = i + 1;
-            for (j = i; j < m; j++) s += u[j][i] * u[j][i];
-            if (s <= tolerance) g = 0.0;
-            else {
-              f = u[i][i];
-              g = Math.sqrt(s);
-              if (f >= 0.0) g = -g;
-              h = f * g - s;
-              u[i][i] = f - g;
-              for (j = l; j < n; j++) {
-                s = 0.0;
-                for (k = i; k < m; k++) s += u[k][i] * u[k][j];
-                f = s / h;
-                for (k = i; k < m; k++) u[k][j] += f * u[k][i];
-              }
-            }
-            q[i] = g;
-            s = 0.0;
-            for (j = l; j < n; j++) s = s + u[i][j] * u[i][j];
-            if (s <= tolerance) g = 0.0;
-            else {
-              f = u[i][i + 1];
-              g = Math.sqrt(s);
-              if (f >= 0.0) g = -g;
-              h = f * g - s;
-              u[i][i + 1] = f - g;
-              for (j = l; j < n; j++) e[j] = u[i][j] / h;
-              for (j = l; j < m; j++) {
-                s = 0.0;
-                for (k = l; k < n; k++) s += u[j][k] * u[i][k];
-                for (k = l; k < n; k++) u[j][k] += s * e[k];
-              }
-            }
-            y = Math.abs(q[i]) + Math.abs(e[i]);
-            if (y > x) x = y;
-          }
-
-          // accumulation of right hand gtransformations
-          for (i = n - 1; i != -1; i += -1) {
-            if (g != 0.0) {
-              h = g * u[i][i + 1];
-              for (j = l; j < n; j++) v[j][i] = u[i][j] / h;
-              for (j = l; j < n; j++) {
-                s = 0.0;
-                for (k = l; k < n; k++) s += u[i][k] * v[k][j];
-                for (k = l; k < n; k++) v[k][j] += s * v[k][i];
-              }
-            }
-            for (j = l; j < n; j++) {
-              v[i][j] = 0;
-              v[j][i] = 0;
-            }
-            v[i][i] = 1;
-            g = e[i];
-            l = i;
-          }
-
-          // accumulation of left hand transformations
-          for (i = n - 1; i != -1; i += -1) {
-            l = i + 1;
-            g = q[i];
-            for (j = l; j < n; j++) u[i][j] = 0;
-            if (g != 0.0) {
-              h = u[i][i] * g;
-              for (j = l; j < n; j++) {
-                s = 0.0;
-                for (k = l; k < m; k++) s += u[k][i] * u[k][j];
-                f = s / h;
-                for (k = i; k < m; k++) u[k][j] += f * u[k][i];
-              }
-              for (j = i; j < m; j++) u[j][i] = u[j][i] / g;
-            } else for (j = i; j < m; j++) u[j][i] = 0;
-            u[i][i] += 1;
-          }
-
-          // diagonalization of the bidiagonal form
-          prec = prec * x;
-          for (k = n - 1; k != -1; k += -1) {
-            for (var iteration = 0; iteration < itmax; iteration++) {
-              // test f splitting
-              var test_convergence = false;
-              for (l = k; l != -1; l += -1) {
-                if (Math.abs(e[l]) <= prec) {
-                  test_convergence = true;
-                  break;
-                }
-                if (Math.abs(q[l - 1]) <= prec) break;
-              }
-              if (!test_convergence) {
-                // cancellation of e[l] if l>0
-                c = 0.0;
-                s = 1.0;
-                var l1 = l - 1;
-                for (i = l; i < k + 1; i++) {
-                  f = s * e[i];
-                  e[i] = c * e[i];
-                  if (Math.abs(f) <= prec) break;
-                  g = q[i];
-                  h = pythag(f, g);
-                  q[i] = h;
-                  c = g / h;
-                  s = -f / h;
-                  for (j = 0; j < m; j++) {
-                    y = u[j][l1];
-                    z = u[j][i];
-                    u[j][l1] = y * c + z * s;
-                    u[j][i] = -y * s + z * c;
-                  }
-                }
-              }
-              // test f convergence
-              z = q[k];
-              if (l == k) {
-                //convergence
-                if (z < 0.0) {
-                  //q[k] is made non-negative
-                  q[k] = -z;
-                  for (j = 0; j < n; j++) v[j][k] = -v[j][k];
-                }
-                break; //break out of iteration loop and move on to next k value
-              }
-              if (iteration >= itmax - 1) throw "Error: no convergence.";
-              // shift from bottom 2x2 minor
-              x = q[l];
-              y = q[k - 1];
-              g = e[k - 1];
-              h = e[k];
-              f = ((y - z) * (y + z) + (g - h) * (g + h)) / (2.0 * h * y);
-              g = pythag(f, 1.0);
-              if (f < 0.0) f = ((x - z) * (x + z) + h * (y / (f - g) - h)) / x;
-              else f = ((x - z) * (x + z) + h * (y / (f + g) - h)) / x;
-              // next QR transformation
-              c = 1.0;
-              s = 1.0;
-              for (i = l + 1; i < k + 1; i++) {
-                g = e[i];
-                y = q[i];
-                h = s * g;
-                g = c * g;
-                z = pythag(f, h);
-                e[i - 1] = z;
-                c = f / z;
-                s = h / z;
-                f = x * c + g * s;
-                g = -x * s + g * c;
-                h = y * s;
-                y = y * c;
-                for (j = 0; j < n; j++) {
-                  x = v[j][i - 1];
-                  z = v[j][i];
-                  v[j][i - 1] = x * c + z * s;
-                  v[j][i] = -x * s + z * c;
-                }
-                z = pythag(f, h);
-                q[i - 1] = z;
-                c = f / z;
-                s = h / z;
-                f = c * g + s * y;
-                x = -s * g + c * y;
-                for (j = 0; j < m; j++) {
-                  y = u[j][i - 1];
-                  z = u[j][i];
-                  u[j][i - 1] = y * c + z * s;
-                  u[j][i] = -y * s + z * c;
-                }
-              }
-              e[l] = 0.0;
-              e[k] = f;
-              q[k] = x;
-            }
-          }
-
-          //vt= transpose(v)
-          //return (u,q,vt)
-          for (i = 0; i < q.length; i++) if (q[i] < prec) q[i] = 0;
-
-          //sort eigenvalues
-          for (i = 0; i < n; i++) {
-            //writeln(q)
-            for (j = i - 1; j >= 0; j--) {
-              if (q[j] < q[i]) {
-                //  writeln(i,'-',j)
-                c = q[j];
-                q[j] = q[i];
-                q[i] = c;
-                for (k = 0; k < u.length; k++) {
-                  temp = u[k][i];
-                  u[k][i] = u[k][j];
-                  u[k][j] = temp;
-                }
-                for (k = 0; k < v.length; k++) {
-                  temp = v[k][i];
-                  v[k][i] = v[k][j];
-                  v[k][j] = temp;
-                }
-                //	   u.swapCols(i,j)
-                //	   v.swapCols(i,j)
-                i = j;
-              }
-            }
-          }
-
-          return { U: u, S: q, V: v };
-        };
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(27)));
-
-      /***/
-    },
-    /* 13 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (Buffer) {
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
-          return encodeWeights;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
-          return decodeWeights;
-        });
-        /* unused harmony export concatenateTypedArrays */
-        /* unused harmony export stringByteLength */
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-          return arrayBufferToBase64String;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-          return base64StringToArrayBuffer;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
-          return concatenateArrayBuffers;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-          return basename;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
-          return getModelArtifactsInfoForJSON;
-        });
-        /* unused harmony export getFloat16Decoder */
-        /* harmony import */ var _ops_complex__WEBPACK_IMPORTED_MODULE_0__ =
-          __webpack_require__(18);
-        /* harmony import */ var _ops_tensor_ops__WEBPACK_IMPORTED_MODULE_1__ =
-          __webpack_require__(8);
-        /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_2__ = __webpack_require__(1);
-        /* harmony import */ var _types__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(34);
-        /**
-         * @license
-         * Copyright 2018 Google LLC. All Rights Reserved.
-         * Licensed under the Apache License, Version 2.0 (the "License");
-         * you may not use this file except in compliance with the License.
-         * You may obtain a copy of the License at
-         *
-         * http://www.apache.org/licenses/LICENSE-2.0
-         *
-         * Unless required by applicable law or agreed to in writing, software
-         * distributed under the License is distributed on an "AS IS" BASIS,
-         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-         * See the License for the specific language governing permissions and
-         * limitations under the License.
-         * =============================================================================
-         */
-
-        /** Number of bytes reserved for the length of the string. (32bit integer). */
-        const NUM_BYTES_STRING_LENGTH = 4;
-        /**
-         * Encode a map from names to weight values as an ArrayBuffer, along with an
-         * `Array` of `WeightsManifestEntry` as specification of the encoded weights.
-         *
-         * This function does not perform sharding.
-         *
-         * This function is the reverse of `decodeWeights`.
-         *
-         * @param tensors A map ("dict") from names to tensors.
-         * @param group Group to which the weights belong (optional).
-         * @returns A `Promise` of
-         *   - A flat `ArrayBuffer` with all the binary values of the `Tensor`s
-         *     concatenated.
-         *   - An `Array` of `WeightManifestEntry`s, carrying information including
-         *     tensor names, `dtype`s and shapes.
-         * @throws Error: on unsupported tensor `dtype`.
-         */
-        async function encodeWeights(tensors, group) {
-          // TODO(adarob, cais): Support quantization.
-          const specs = [];
-          const dataPromises = [];
-          const names = Array.isArray(tensors)
-            ? tensors.map((tensor) => tensor.name)
-            : Object.keys(tensors);
-          for (let i = 0; i < names.length; ++i) {
-            const name = names[i];
-            const t = Array.isArray(tensors) ? tensors[i].tensor : tensors[name];
-            if (
-              t.dtype !== "float32" &&
-              t.dtype !== "int32" &&
-              t.dtype !== "bool" &&
-              t.dtype !== "string" &&
-              t.dtype !== "complex64"
-            ) {
-              throw new Error(`Unsupported dtype in weight '${name}': ${t.dtype}`);
-            }
-            const spec = { name, shape: t.shape, dtype: t.dtype };
-            if (t.dtype === "string") {
-              const utf8bytes = new Promise(async (resolve) => {
-                const vals = await t.bytes();
-                const totalNumBytes =
-                  vals.reduce((p, c) => p + c.length, 0) + NUM_BYTES_STRING_LENGTH * vals.length;
-                const bytes = new Uint8Array(totalNumBytes);
-                let offset = 0;
-                for (let i = 0; i < vals.length; i++) {
-                  const val = vals[i];
-                  const bytesOfLength = new Uint8Array(new Uint32Array([val.length]).buffer);
-                  bytes.set(bytesOfLength, offset);
-                  offset += NUM_BYTES_STRING_LENGTH;
-                  bytes.set(val, offset);
-                  offset += val.length;
-                }
-                resolve(bytes);
-              });
-              dataPromises.push(utf8bytes);
-            } else {
-              dataPromises.push(t.data());
-            }
-            if (group != null) {
-              spec.group = group;
-            }
-            specs.push(spec);
-          }
-          const tensorValues = await Promise.all(dataPromises);
-          return { data: concatenateTypedArrays(tensorValues), specs };
-        }
-        /**
-         * Decode flat ArrayBuffer as weights.
-         *
-         * This function does not handle sharding.
-         *
-         * This function is the reverse of `encodeWeights`.
-         *
-         * @param buffer A flat ArrayBuffer carrying the binary values of the tensors
-         *   concatenated in the order specified in `specs`.
-         * @param specs Specifications of the names, dtypes and shapes of the tensors
-         *   whose value are encoded by `buffer`.
-         * @return A map from tensor name to tensor value, with the names corresponding
-         *   to names in `specs`.
-         * @throws Error, if any of the tensors has unsupported dtype.
-         */
-        function decodeWeights(buffer, specs) {
-          // TODO(adarob, cais): Support quantization.
-          const out = {};
-          let float16Decode;
-          let offset = 0;
-          for (const spec of specs) {
-            const name = spec.name;
-            const dtype = spec.dtype;
-            const shape = spec.shape;
-            const size = Object(_util__WEBPACK_IMPORTED_MODULE_2__["sizeFromShape"])(shape);
-            let values;
-            if ("quantization" in spec) {
-              const quantization = spec.quantization;
-              if (quantization.dtype === "uint8" || quantization.dtype === "uint16") {
-                if (!("min" in quantization && "scale" in quantization)) {
-                  throw new Error(
-                    `Weight ${spec.name} with quantization ${quantization.dtype} ` +
-                      `doesn't have corresponding metadata min and scale.`
-                  );
-                }
-              } else if (quantization.dtype === "float16") {
-                if (dtype !== "float32") {
-                  throw new Error(
-                    `Weight ${spec.name} is quantized with ${quantization.dtype} ` +
-                      `which only supports weights of type float32 not ${dtype}.`
-                  );
-                }
-              } else {
-                throw new Error(
-                  `Weight ${spec.name} has unknown ` +
-                    `quantization dtype ${quantization.dtype}. ` +
-                    `Supported quantization dtypes are: ` +
-                    `'uint8', 'uint16', and 'float16'.`
-                );
-              }
-              const quantizationSizeFactor =
-                _types__WEBPACK_IMPORTED_MODULE_3__[/* DTYPE_VALUE_SIZE_MAP */ "a"][
-                  quantization.dtype
-                ];
-              const byteBuffer = buffer.slice(offset, offset + size * quantizationSizeFactor);
-              const quantizedArray =
-                quantization.dtype === "uint8"
-                  ? new Uint8Array(byteBuffer)
-                  : new Uint16Array(byteBuffer);
-              if (dtype === "float32") {
-                if (quantization.dtype === "uint8" || quantization.dtype === "uint16") {
-                  values = new Float32Array(quantizedArray.length);
-                  for (let i = 0; i < quantizedArray.length; i++) {
-                    const v = quantizedArray[i];
-                    values[i] = v * quantization.scale + quantization.min;
-                  }
-                } else if (quantization.dtype === "float16") {
-                  if (float16Decode === undefined) {
-                    float16Decode = getFloat16Decoder();
-                  }
-                  values = float16Decode(quantizedArray);
-                } else {
-                  throw new Error(
-                    `Unsupported quantization type ${quantization.dtype} ` +
-                      `for weight type float32.`
-                  );
-                }
-              } else if (dtype === "int32") {
-                if (quantization.dtype !== "uint8" && quantization.dtype !== "uint16") {
-                  throw new Error(
-                    `Unsupported quantization type ${quantization.dtype} ` +
-                      `for weight type int32.`
-                  );
-                }
-                values = new Int32Array(quantizedArray.length);
-                for (let i = 0; i < quantizedArray.length; i++) {
-                  const v = quantizedArray[i];
-                  values[i] = Math.round(v * quantization.scale + quantization.min);
-                }
-              } else {
-                throw new Error(`Unsupported dtype in weight '${name}': ${dtype}`);
-              }
-              offset += size * quantizationSizeFactor;
-            } else if (dtype === "string") {
-              const size = Object(_util__WEBPACK_IMPORTED_MODULE_2__["sizeFromShape"])(spec.shape);
-              values = [];
-              for (let i = 0; i < size; i++) {
-                const byteLength = new Uint32Array(
-                  buffer.slice(offset, offset + NUM_BYTES_STRING_LENGTH)
-                )[0];
-                offset += NUM_BYTES_STRING_LENGTH;
-                const bytes = new Uint8Array(buffer.slice(offset, offset + byteLength));
-                values.push(bytes);
-                offset += byteLength;
-              }
-            } else {
-              const dtypeFactor =
-                _types__WEBPACK_IMPORTED_MODULE_3__[/* DTYPE_VALUE_SIZE_MAP */ "a"][dtype];
-              const byteBuffer = buffer.slice(offset, offset + size * dtypeFactor);
-              if (dtype === "float32") {
-                values = new Float32Array(byteBuffer);
-              } else if (dtype === "int32") {
-                values = new Int32Array(byteBuffer);
-              } else if (dtype === "bool") {
-                values = new Uint8Array(byteBuffer);
-              } else if (dtype === "complex64") {
-                values = new Float32Array(byteBuffer);
-                const real = new Float32Array(values.length / 2);
-                const image = new Float32Array(values.length / 2);
-                for (let i = 0; i < real.length; i++) {
-                  real[i] = values[i * 2];
-                  image[i] = values[i * 2 + 1];
-                }
-                const realTensor = Object(
-                  _ops_tensor_ops__WEBPACK_IMPORTED_MODULE_1__[/* tensor */ "f"]
-                )(real, shape, "float32");
-                const imageTensor = Object(
-                  _ops_tensor_ops__WEBPACK_IMPORTED_MODULE_1__[/* tensor */ "f"]
-                )(image, shape, "float32");
-                out[name] = Object(_ops_complex__WEBPACK_IMPORTED_MODULE_0__[/* complex */ "a"])(
-                  realTensor,
-                  imageTensor
-                );
-              } else {
-                throw new Error(`Unsupported dtype in weight '${name}': ${dtype}`);
-              }
-              offset += size * dtypeFactor;
-            }
-            if (dtype !== "complex64") {
-              out[name] = Object(_ops_tensor_ops__WEBPACK_IMPORTED_MODULE_1__[/* tensor */ "f"])(
-                values,
-                shape,
-                dtype
-              );
-            }
-          }
-          return out;
-        }
-        /**
-         * Concatenate TypedArrays into an ArrayBuffer.
-         */
-        function concatenateTypedArrays(xs) {
-          // TODO(adarob, cais): Support quantization.
-          if (xs === null) {
-            throw new Error(`Invalid input value: ${JSON.stringify(xs)}`);
-          }
-          let totalByteLength = 0;
-          // `normalizedXs` is here for this reason: a `TypedArray`'s `buffer'
-          // can have a different byte length from that of the `TypedArray` itself,
-          // for example, when the `TypedArray` is created from an offset in an
-          // `ArrayBuffer`. `normliazedXs` holds `TypedArray`s whose `buffer`s match
-          // the `TypedArray` in byte length. If an element of `xs` does not show
-          // this property, a new `TypedArray` that satisfy this property will be
-          // constructed and pushed into `normalizedXs`.
-          const normalizedXs = [];
-          xs.forEach((x) => {
-            totalByteLength += x.byteLength;
-            // tslint:disable:no-any
-            normalizedXs.push(x.byteLength === x.buffer.byteLength ? x : new x.constructor(x));
-            if (
-              !(x instanceof Float32Array || x instanceof Int32Array || x instanceof Uint8Array)
-            ) {
-              throw new Error(`Unsupported TypedArray subtype: ${x.constructor.name}`);
-            }
-            // tslint:enable:no-any
-          });
-          const y = new Uint8Array(totalByteLength);
-          let offset = 0;
-          normalizedXs.forEach((x) => {
-            y.set(new Uint8Array(x.buffer), offset);
-            offset += x.byteLength;
-          });
-          return y.buffer;
-        }
-        // Use Buffer on Node.js instead of Blob/atob/btoa
-        const useNodeBuffer =
-          typeof Buffer !== "undefined" &&
-          (typeof Blob === "undefined" ||
-            typeof atob === "undefined" ||
-            typeof btoa === "undefined");
-        /**
-         * Calculate the byte length of a JavaScript string.
-         *
-         * Note that a JavaScript string can contain wide characters, therefore the
-         * length of the string is not necessarily equal to the byte length.
-         *
-         * @param str Input string.
-         * @returns Byte length.
-         */
-        function stringByteLength(str) {
-          if (useNodeBuffer) {
-            return Buffer.byteLength(str);
-          }
-          return new Blob([str]).size;
-        }
-        /**
-         * Encode an ArrayBuffer as a base64 encoded string.
-         *
-         * @param buffer `ArrayBuffer` to be converted.
-         * @returns A string that base64-encodes `buffer`.
-         */
-        function arrayBufferToBase64String(buffer) {
-          if (useNodeBuffer) {
-            return Buffer.from(buffer).toString("base64");
-          }
-          const buf = new Uint8Array(buffer);
-          let s = "";
-          for (let i = 0, l = buf.length; i < l; i++) {
-            s += String.fromCharCode(buf[i]);
-          }
-          return btoa(s);
-        }
-        /**
-         * Decode a base64 string as an ArrayBuffer.
-         *
-         * @param str Base64 string.
-         * @returns Decoded `ArrayBuffer`.
-         */
-        function base64StringToArrayBuffer(str) {
-          if (useNodeBuffer) {
-            const buf = Buffer.from(str, "base64");
-            return buf.buffer.slice(buf.byteOffset, buf.byteOffset + buf.byteLength);
-          }
-          const s = atob(str);
-          const buffer = new Uint8Array(s.length);
-          for (let i = 0; i < s.length; ++i) {
-            buffer.set([s.charCodeAt(i)], i);
-          }
-          return buffer.buffer;
-        }
-        /**
-         * Concatenate a number of ArrayBuffers into one.
-         *
-         * @param buffers A number of array buffers to concatenate.
-         * @returns Result of concatenating `buffers` in order.
-         */
-        function concatenateArrayBuffers(buffers) {
-          if (buffers.length === 1) {
-            return buffers[0];
-          }
-          let totalByteLength = 0;
-          buffers.forEach((buffer) => {
-            totalByteLength += buffer.byteLength;
-          });
-          const temp = new Uint8Array(totalByteLength);
-          let offset = 0;
-          buffers.forEach((buffer) => {
-            temp.set(new Uint8Array(buffer), offset);
-            offset += buffer.byteLength;
-          });
-          return temp.buffer;
-        }
-        /**
-         * Get the basename of a path.
-         *
-         * Behaves in a way analogous to Linux's basename command.
-         *
-         * @param path
-         */
-        function basename(path) {
-          const SEPARATOR = "/";
-          path = path.trim();
-          while (path.endsWith(SEPARATOR)) {
-            path = path.slice(0, path.length - 1);
-          }
-          const items = path.split(SEPARATOR);
-          return items[items.length - 1];
-        }
-        /**
-         * Populate ModelArtifactsInfo fields for a model with JSON topology.
-         * @param modelArtifacts
-         * @returns A ModelArtifactsInfo object.
-         */
-        function getModelArtifactsInfoForJSON(modelArtifacts) {
-          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
-            throw new Error("Expected JSON model topology, received ArrayBuffer.");
-          }
-          return {
-            dateSaved: new Date(),
-            modelTopologyType: "JSON",
-            modelTopologyBytes:
-              modelArtifacts.modelTopology == null
-                ? 0
-                : stringByteLength(JSON.stringify(modelArtifacts.modelTopology)),
-            weightSpecsBytes:
-              modelArtifacts.weightSpecs == null
-                ? 0
-                : stringByteLength(JSON.stringify(modelArtifacts.weightSpecs)),
-            weightDataBytes:
-              modelArtifacts.weightData == null ? 0 : modelArtifacts.weightData.byteLength,
-          };
-        }
-        /**
-         * Computes mantisa table for casting Float16 to Float32
-         * See http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf
-         *
-         * @returns Uint32Array, 2048 mantissa lookup values.
-         */
-        function computeFloat16MantisaTable() {
-          const convertMantissa = (i) => {
-            let m = i << 13;
-            let e = 0;
-            while ((m & 0x00800000) === 0) {
-              e -= 0x00800000;
-              m <<= 1;
-            }
-            m &= ~0x00800000;
-            e += 0x38800000;
-            return m | e;
-          };
-          const mantisaTable = new Uint32Array(2048);
-          mantisaTable[0] = 0;
-          for (let i = 1; i < 1024; i++) {
-            mantisaTable[i] = convertMantissa(i);
-          }
-          for (let i = 1024; i < 2048; i++) {
-            mantisaTable[i] = 0x38000000 + ((i - 1024) << 13);
-          }
-          return mantisaTable;
-        }
-        /**
-         * Computes exponent table for casting Float16 to Float32
-         * See http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf
-         *
-         * @returns Uint32Array, 64 exponent lookup values.
-         */
-        function computeFloat16ExponentTable() {
-          const exponentTable = new Uint32Array(64);
-          exponentTable[0] = 0;
-          exponentTable[31] = 0x47800000;
-          exponentTable[32] = 0x80000000;
-          exponentTable[63] = 0xc7800000;
-          for (let i = 1; i < 31; i++) {
-            exponentTable[i] = i << 23;
-          }
-          for (let i = 33; i < 63; i++) {
-            exponentTable[i] = 0x80000000 + ((i - 32) << 23);
-          }
-          return exponentTable;
-        }
-        /**
-         * Computes offset table for casting Float16 to Float32
-         * See http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf
-         *
-         * @returns Uint32Array, 6d offset values.
-         */
-        function computeFloat16OffsetTable() {
-          const offsetTable = new Uint32Array(64);
-          for (let i = 0; i < 64; i++) {
-            offsetTable[i] = 1024;
-          }
-          offsetTable[0] = offsetTable[32] = 0;
-          return offsetTable;
-        }
-        /**
-         * Retrieve a Float16 decoder which will decode a ByteArray of Float16 values
-         * to a Float32Array.
-         *
-         * @returns Function (buffer: Uint16Array) => Float32Array which decodes
-         *          the Uint16Array of Float16 bytes to a Float32Array.
-         */
-        function getFloat16Decoder() {
-          // Algorithm is based off of http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf
-          // Cache lookup tables
-          const mantisaTable = computeFloat16MantisaTable();
-          const exponentTable = computeFloat16ExponentTable();
-          const offsetTable = computeFloat16OffsetTable();
-          return (quantizedArray) => {
-            const buffer = new ArrayBuffer(4 * quantizedArray.length);
-            const bufferUint32View = new Uint32Array(buffer);
-            for (let index = 0; index < quantizedArray.length; index++) {
-              const float16Bits = quantizedArray[index];
-              const float32Bits =
-                mantisaTable[offsetTable[float16Bits >> 10] + (float16Bits & 0x3ff)] +
-                exponentTable[float16Bits >> 10];
-              bufferUint32View[index] = float32Bits;
-            }
-            return new Float32Array(buffer);
-          };
-        }
-        //# sourceMappingURL=io_utils.js.map
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(39).Buffer));
-
-      /***/
-    },
-    /* 14 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "f", function () {
-        return /* binding */ iteratorFromItems;
-      });
-      __webpack_require__.d(__webpack_exports__, "e", function () {
-        return /* binding */ iteratorFromFunction;
-      });
-      __webpack_require__.d(__webpack_exports__, "d", function () {
-        return /* binding */ iteratorFromConcatenated;
-      });
-      __webpack_require__.d(__webpack_exports__, "g", function () {
-        return /* binding */ iteratorFromZipped;
-      });
-      __webpack_require__.d(__webpack_exports__, "a", function () {
-        return /* binding */ lazy_iterator_LazyIterator;
-      });
-      __webpack_require__.d(__webpack_exports__, "b", function () {
-        return /* binding */ lazy_iterator_OneToManyIterator;
-      });
-      __webpack_require__.d(__webpack_exports__, "c", function () {
-        return /* binding */ ZipMismatchMode;
-      });
-
-      // UNUSED EXPORTS: iteratorFromIncrementing, iteratorFromConcatenatedFunction, ChainedIterator, PrefetchIterator, ShuffleIterator
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
-      var dist = __webpack_require__(0);
-
-      // EXTERNAL MODULE: ./node_modules/seedrandom/index.js
-      var seedrandom = __webpack_require__(20);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/deep_map.js
-      var deep_map = __webpack_require__(19);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/deep_clone.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      function deepClone(container) {
-        return Object(deep_map["b" /* deepMap */])(container, cloneIfTensor);
-      }
-      // tslint:disable-next-line: no-any
-      function cloneIfTensor(item) {
-        if (item instanceof dist["Tensor"]) {
-          return { value: item.clone(), recurse: false };
-        } else if (Object(deep_map["e" /* isIterable */])(item)) {
-          return { value: null, recurse: true };
-        } else {
-          return { value: item, recurse: false };
-        }
-      }
-      //# sourceMappingURL=deep_clone.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/ring_buffer.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-      /**
-       * A ring buffer, providing O(1) FIFO, LIFO, and related operations.
-       */
-      class RingBuffer {
-        /**
-         * Constructs a `RingBuffer`.
-         * @param capacity The number of items that the buffer can accomodate.
-         */
-        constructor(capacity) {
-          this.capacity = capacity;
-          // Note we store the indices in the range 0 <= index < 2*capacity.
-          // This allows us to distinguish the full from the empty case.
-          // See https://www.snellman.net/blog/archive/2016-12-13-ring-buffers/
-          this.begin = 0; // inclusive
-          this.end = 0; // exclusive
-          if (capacity == null) {
-            throw new RangeError("Can't create a ring buffer of unknown capacity.");
-          }
-          if (capacity < 1) {
-            throw new RangeError("Can't create ring buffer of capacity < 1.");
-          }
-          this.data = new Array(capacity);
-          this.doubledCapacity = 2 * capacity;
-        }
-        /**
-         * Map any index into the range 0 <= index < 2*capacity.
-         */
-        wrap(index) {
-          // don't trust % on negative numbers
-          while (index < 0) {
-            index += this.doubledCapacity;
-          }
-          return index % this.doubledCapacity;
-        }
-        get(index) {
-          if (index < 0) {
-            throw new RangeError("Can't get item at a negative index.");
-          }
-          return this.data[index % this.capacity];
-        }
-        set(index, value) {
-          if (index < 0) {
-            throw new RangeError("Can't set item at a negative index.");
-          }
-          this.data[index % this.capacity] = value;
-        }
-        /**
-         * Returns the current number of items in the buffer.
-         */
-        length() {
-          let length = this.end - this.begin;
-          if (length < 0) {
-            length = this.doubledCapacity + length;
-          }
-          return length;
-        }
-        /**
-         * Reports whether the buffer is full.
-         * @returns true if the number of items in the buffer equals its capacity, and
-         *   false otherwise.
-         */
-        isFull() {
-          return this.length() === this.capacity;
-        }
-        /**
-         * Reports whether the buffer is empty.
-         * @returns true if the number of items in the buffer equals zero, and
-         *   false otherwise.
-         */
-        isEmpty() {
-          return this.length() === 0;
-        }
-        /**
-         * Adds an item to the end of the buffer.
-         */
-        push(value) {
-          if (this.isFull()) {
-            throw new RangeError("Ring buffer is full.");
-          }
-          this.set(this.end, value);
-          this.end = this.wrap(this.end + 1);
-        }
-        /**
-         * Adds many items to the end of the buffer, in order.
-         */
-        pushAll(values) {
-          for (const value of values) {
-            this.push(value);
-          }
-        }
-        /**
-         * Removes and returns the last item in the buffer.
-         */
-        pop() {
-          if (this.isEmpty()) {
-            throw new RangeError("Ring buffer is empty.");
-          }
-          this.end = this.wrap(this.end - 1);
-          const result = this.get(this.end);
-          this.set(this.end, undefined);
-          return result;
-        }
-        /**
-         * Adds an item to the beginning of the buffer.
-         */
-        unshift(value) {
-          if (this.isFull()) {
-            throw new RangeError("Ring buffer is full.");
-          }
-          this.begin = this.wrap(this.begin - 1);
-          this.set(this.begin, value);
-        }
-        /**
-         * Removes and returns the first item in the buffer.
-         */
-        shift() {
-          if (this.isEmpty()) {
-            throw new RangeError("Ring buffer is empty.");
-          }
-          const result = this.get(this.begin);
-          this.set(this.begin, undefined);
-          this.begin = this.wrap(this.begin + 1);
-          return result;
-        }
-        /**
-         * Removes and returns a specific item in the buffer, and moves the last item
-         * to the vacated slot.  This is useful for implementing a shuffling stream.
-         * Note that this operation necessarily scrambles the original order.
-         *
-         * @param relativeIndex: the index of the item to remove, relative to the
-         *   first item in the buffer (e.g., hiding the ring nature of the underlying
-         *   storage).
-         */
-        shuffleExcise(relativeIndex) {
-          if (this.isEmpty()) {
-            throw new RangeError("Ring buffer is empty.");
-          }
-          const index = this.wrap(this.begin + relativeIndex);
-          const result = this.get(index);
-          this.set(index, this.pop());
-          return result;
-        }
-      }
-      //# sourceMappingURL=ring_buffer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/growing_ring_buffer.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      class growing_ring_buffer_GrowingRingBuffer extends RingBuffer {
-        /**
-         * Constructs a `GrowingRingBuffer`.
-         */
-        constructor() {
-          super(growing_ring_buffer_GrowingRingBuffer.INITIAL_CAPACITY);
-        }
-        isFull() {
-          return false;
-        }
-        push(value) {
-          if (super.isFull()) {
-            this.expand();
-          }
-          super.push(value);
-        }
-        unshift(value) {
-          if (super.isFull()) {
-            this.expand();
-          }
-          super.unshift(value);
-        }
-        /**
-         * Doubles the capacity of the buffer.
-         */
-        expand() {
-          const newCapacity = this.capacity * 2;
-          const newData = new Array(newCapacity);
-          const len = this.length();
-          // Rotate the buffer to start at index 0 again, since we can't just
-          // allocate more space at the end.
-          for (let i = 0; i < len; i++) {
-            newData[i] = this.get(this.wrap(this.begin + i));
-          }
-          this.data = newData;
-          this.capacity = newCapacity;
-          this.doubledCapacity = 2 * this.capacity;
-          this.begin = 0;
-          this.end = len;
-        }
-      }
-      growing_ring_buffer_GrowingRingBuffer.INITIAL_CAPACITY = 32;
-      //# sourceMappingURL=growing_ring_buffer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/lazy_iterator.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      // Here we implement a simple asynchronous iterator.
-      // This lets us avoid using either third-party stream libraries or
-      // recent TypeScript language support requiring polyfills.
-      /**
-       * Create a `LazyIterator` from an array of items.
-       */
-      function iteratorFromItems(items) {
-        return new lazy_iterator_ArrayIterator(items);
-      }
-      /**
-       * Create a `LazyIterator` of incrementing integers.
-       */
-      function iteratorFromIncrementing(start) {
-        let i = start;
-        return iteratorFromFunction(() => ({ value: i++, done: false }));
-      }
-      /**
-       * Create a `LazyIterator` from a function.
-       *
-       * ```js
-       * let i = -1;
-       * const func = () =>
-       *    ++i < 5 ? {value: i, done: false} : {value: null, done: true};
-       * const iter = tf.data.iteratorFromFunction(func);
-       * await iter.forEachAsync(e => console.log(e));
-       * ```
-       *
-       * @param func A function that produces data on each call.
-       */
-      function iteratorFromFunction(func) {
-        return new FunctionCallIterator(func);
-      }
-      /**
-       * Create a `LazyIterator` by concatenating underlying streams, which are
-       * themselves provided as a stream.
-       *
-       * This can also be thought of as a "stream flatten" operation.
-       *
-       * @param baseIterators A stream of streams to be concatenated.
-       * @param baseErrorHandler An optional function that can intercept `Error`s
-       *   raised during a `next()` call on the base stream.  This function can decide
-       *   whether the error should be propagated, whether the error should be
-       *   ignored, or whether the base stream should be terminated.
-       */
-      function iteratorFromConcatenated(baseIterators, baseErrorHandler) {
-        return new ChainedIterator(baseIterators, baseErrorHandler);
-      }
-      /**
-       * Create a `LazyIterator` by concatenating streams produced by calling a
-       * stream-generating function a given number of times.
-       *
-       * Since a `LazyIterator` is read-once, it cannot be repeated, but this
-       * function can be used to achieve a similar effect:
-       *
-       *   LazyIterator.ofConcatenatedFunction(() => new MyIterator(), 6);
-       *
-       * @param iteratorFunc: A function that produces a new stream on each call.
-       * @param count: The number of times to call the function.
-       * @param baseErrorHandler An optional function that can intercept `Error`s
-       *   raised during a `next()` call on the base stream.  This function can decide
-       *   whether the error should be propagated, whether the error should be
-       *   ignored, or whether the base stream should be terminated.
-       */
-      function iteratorFromConcatenatedFunction(iteratorFunc, count, baseErrorHandler) {
-        return iteratorFromConcatenated(
-          iteratorFromFunction(iteratorFunc).take(count),
-          baseErrorHandler
-        );
-      }
-      /**
-       * Create a `LazyIterator` by zipping together an array, dict, or nested
-       * structure of `LazyIterator`s (and perhaps additional constants).
-       *
-       * The underlying streams must provide elements in a consistent order such
-       * that they correspond.
-       *
-       * Typically, the underlying streams should have the same number of
-       * elements. If they do not, the behavior is determined by the
-       * `mismatchMode` argument.
-       *
-       * The nested structure of the `iterators` argument determines the
-       * structure of elements in the resulting iterator.
-       *
-       * @param iterators: An array or object containing LazyIterators at the
-       * leaves.
-       * @param mismatchMode: Determines what to do when one underlying iterator
-       * is exhausted before the others.  `ZipMismatchMode.FAIL` (the default)
-       * causes an error to be thrown in this case.  `ZipMismatchMode.SHORTEST`
-       * causes the zipped iterator to terminate with the furst underlying
-       * streams, so elements remaining on the longer streams are ignored.
-       * `ZipMismatchMode.LONGEST` causes the zipped stream to continue, filling
-       * in nulls for the exhausted streams, until all streams are exhausted.
-       */
-      function iteratorFromZipped(iterators, mismatchMode = ZipMismatchMode.FAIL) {
-        return new lazy_iterator_ZipIterator(iterators, mismatchMode);
-      }
-      /**
-       * An asynchronous iterator, providing lazy access to a potentially
-       * unbounded stream of elements.
-       *
-       * Iterator can be obtained from a dataset:
-       * `const iter = await dataset.iterator();`
-       */
-      class lazy_iterator_LazyIterator {
-        /**
-         * Collect all remaining elements of a bounded stream into an array.
-         * Obviously this will succeed only for small streams that fit in memory.
-         * Useful for testing.
-         *
-         * @returns A Promise for an array of stream elements, which will resolve
-         *   when the stream is exhausted.
-         */
-        async toArray() {
-          const result = [];
-          let x = await this.next();
-          while (!x.done) {
-            result.push(x.value);
-            x = await this.next();
-          }
-          return result;
-        }
-        /**
-         * Collect all elements of this dataset into an array with prefetching 100
-         * elements. This is useful for testing, because the prefetch changes the
-         * order in which the Promises are resolved along the processing pipeline.
-         * This may help expose bugs where results are dependent on the order of
-         * Promise resolution rather than on the logical order of the stream (i.e.,
-         * due to hidden mutable state).
-         *
-         * @returns A Promise for an array of stream elements, which will resolve
-         *   when the stream is exhausted.
-         */
-        async toArrayForTest() {
-          const stream = this.prefetch(100);
-          const result = [];
-          let x = await stream.next();
-          while (!x.done) {
-            result.push(x.value);
-            x = await stream.next();
-          }
-          return result;
-        }
-        /**
-         * Draw items from the stream until it is exhausted.
-         *
-         * This can be useful when the stream has side effects but no output.  In
-         * that case, calling this function guarantees that the stream will be
-         * fully processed.
-         */
-        async resolveFully() {
-          let x = await this.next();
-          while (!x.done) {
-            x = await this.next();
-          }
-        }
-        /**
-         * Draw items from the stream until it is exhausted, or a predicate fails.
-         *
-         * This can be useful when the stream has side effects but no output.  In
-         * that case, calling this function guarantees that the stream will be
-         * fully processed.
-         */
-        async resolveWhile(predicate) {
-          let x = await this.next();
-          let shouldContinue = predicate(x.value);
-          while (!x.done && shouldContinue) {
-            x = await this.next();
-            shouldContinue = predicate(x.value);
-          }
-        }
-        /**
-         * Handles errors thrown on this stream using a provided handler function.
-         *
-         * @param handler A function that handles any `Error` thrown during a `next()`
-         *   call and returns true if the stream should continue (dropping the failed
-         *   call) or false if the stream should quietly terminate.  If the handler
-         *   itself throws (or rethrows) an `Error`, that will be propagated.
-         *
-         * @returns A `LazyIterator` of elements passed through from upstream,
-         *   possibly filtering or terminating on upstream `next()` calls that
-         *   throw an `Error`.
-         */
-        handleErrors(handler) {
-          return new ErrorHandlingLazyIterator(this, handler);
-        }
-        // TODO(soergel): Implement reduce() etc.
-        /**
-         * Filters this stream according to `predicate`.
-         *
-         * @param predicate A function mapping a stream element to a boolean or a
-         * `Promise` for one.
-         *
-         * @returns A `LazyIterator` of elements for which the predicate was true.
-         */
-        filter(predicate) {
-          return new lazy_iterator_FilterIterator(this, predicate);
-        }
-        /**
-         * Maps this stream through a 1-to-1 transform.
-         *
-         * @param transform A function mapping a stream element to a transformed
-         *   element.
-         *
-         * @returns A `LazyIterator` of transformed elements.
-         */
-        map(transform) {
-          return new lazy_iterator_MapIterator(this, transform);
-        }
-        /**
-         * Maps this stream through an async 1-to-1 transform.
-         *
-         * @param transform A function mapping a stream element to a `Promise` for a
-         *   transformed stream element.
-         *
-         * @returns A `LazyIterator` of transformed elements.
-         */
-        mapAsync(transform) {
-          return new lazy_iterator_AsyncMapIterator(this, transform);
-        }
-        /**
-         * Maps this stream through a 1-to-1 transform, forcing serial execution.
-         *
-         * @param transform A function mapping a stream element to a transformed
-         *   element.
-         *
-         * @returns A `LazyIterator` of transformed elements.
-         */
-        serialMapAsync(transform) {
-          return new lazy_iterator_AsyncMapIterator(this, transform).serial();
-        }
-        /**
-         * Maps this stream through a 1-to-many transform.
-         *
-         * @param transform A function mapping a stream element to an array of
-         *   transformed elements.
-         *
-         * @returns A `DataStream` of transformed elements.
-         */
-        flatmap(transform) {
-          return new lazy_iterator_FlatmapIterator(this, transform);
-        }
-        /**
-         * Apply a function to every element of the stream.
-         *
-         * @param f A function to apply to each stream element.
-         */
-        async forEachAsync(f) {
-          return this.map(f).resolveFully();
-        }
-        /**
-         * Apply a function to every element of the stream, forcing serial execution.
-         *
-         * @param f A function to apply to each stream element.  Should return 'true'
-         *   to indicate that the stream should continue, or 'false' to cause it to
-         *   terminate.
-         */
-        async serialForEach(f) {
-          return this.serialMapAsync(f).resolveWhile((x) => x === true);
-        }
-        /**
-         * Groups elements into batches, represented as arrays of elements.
-         *
-         * We can think of the elements of this iterator as 'rows' (even if they are
-         * nested structures).  By the same token, consecutive values for a given
-         * key within the elements form a 'column'.  This matches the usual sense of
-         * 'row' and 'column' when processing tabular data (e.g., parsing a CSV).
-         *
-         * Thus, "Row-major" means that the resulting batch is simply a collection of
-         * rows: `[row1, row2, row3, ...]`.  This is contrast to the column-major
-         * form, which is needed for vectorized computation.
-         *
-         * @param batchSize The number of elements desired per batch.
-         * @param smallLastBatch Whether to emit the final batch when it has fewer
-         *   than batchSize elements. Default true.
-         * @returns A `LazyIterator` of batches of elements, represented as arrays
-         *   of the original element type.
-         */
-        rowMajorBatch(batchSize, smallLastBatch = true) {
-          return new RowMajorBatchIterator(this, batchSize, smallLastBatch);
-        }
-        /**
-         * Groups elements into batches, represented in column-major form.
-         *
-         * We can think of the elements of this iterator as 'rows' (even if they are
-         * nested structures).  By the same token, consecutive values for a given
-         * key within the elements form a 'column'.  This matches the usual sense of
-         * 'row' and 'column' when processing tabular data (e.g., parsing a CSV).
-         *
-         * Thus, "column-major" means that the resulting batch is a (potentially
-         * nested) structure representing the columns.  Each column entry, then,
-         * contains a collection of the values found in that column for a range of
-         * input elements.  This representation allows for vectorized computation, in
-         * contrast to the row-major form.
-         *
-         * The inputs should all have the same nested structure (i.e., of arrays and
-         * dicts).  The result is a single object with the same nested structure,
-         * where the leaves are arrays collecting the values of the inputs at that
-         * location (or, optionally, the result of a custom function applied to those
-         * arrays).
-         *
-         * @param batchSize The number of elements desired per batch.
-         * @param smallLastBatch Whether to emit the final batch when it has fewer
-         *   than batchSize elements. Default true.
-         * @param zipFn: (optional) A function that expects an array of elements at a
-         *   single node of the object tree, and returns a `DeepMapResult`.  The
-         *   `DeepMapResult` either provides a result value for that node (i.e.,
-         *   representing the subtree), or indicates that the node should be processed
-         *   recursively.  The default zipFn recurses as far as possible and places
-         *   arrays at the leaves.
-         * @returns A `LazyIterator` of batches of elements, represented as an object
-         *   with collections at the leaves.
-         */
-        columnMajorBatch(
-          batchSize,
-          smallLastBatch = true,
-          // tslint:disable-next-line:no-any
-          zipFn = deep_map["f" /* zipToList */]
-        ) {
-          // First collect the desired number of input elements as a row-major batch.
-          const rowBatches = this.rowMajorBatch(batchSize, smallLastBatch);
-          // Now 'rotate' or 'pivot' the data, collecting all values from each column
-          // in the batch (i.e., for each key within the elements) into an array.
-          return rowBatches.map((x) => Object(deep_map["d" /* deepZip */])(x, zipFn));
-        }
-        /**
-         * Concatenate this `LazyIterator` with another.
-         *
-         * @param iterator A `LazyIterator` to be concatenated onto this one.
-         * @param baseErrorHandler An optional function that can intercept `Error`s
-         *   raised during a `next()` call on the base stream.  This function can
-         *   decide whether the error should be propagated, whether the error should
-         *   be ignored, or whether the base stream should be terminated.
-         * @returns A `LazyIterator`.
-         */
-        concatenate(iterator, baseErrorHandler) {
-          return new ChainedIterator(iteratorFromItems([this, iterator]), baseErrorHandler);
-        }
-        /**
-         * Limits this stream to return at most `count` items.
-         *
-         * @param count The maximum number of items to provide from the stream. If
-         * a negative or undefined value is given, the entire stream is returned
-         *   unaltered.
-         */
-        take(count) {
-          if (count < 0 || count == null) {
-            return this;
-          }
-          return new TakeIterator(this, count);
-        }
-        /**
-         * Skips the first `count` items in this stream.
-         *
-         * @param count The number of items to skip.  If a negative or undefined
-         * value is given, the entire stream is returned unaltered.
-         */
-        skip(count) {
-          if (count < 0 || count == null) {
-            return this;
-          }
-          return new lazy_iterator_SkipIterator(this, count);
-        }
-        /**
-         * Prefetch the first `bufferSize` items in this stream.
-         *
-         * Note this prefetches Promises, but makes no guarantees about when those
-         * Promises resolve.
-         *
-         * @param bufferSize: An integer specifying the number of elements to be
-         *   prefetched.
-         */
-        prefetch(bufferSize) {
-          return new lazy_iterator_PrefetchIterator(this, bufferSize);
-        }
-        // TODO(soergel): deep sharded shuffle, where supported
-        /**
-         * Randomly shuffles the elements of this stream.
-         *
-         * @param bufferSize: An integer specifying the number of elements from
-         * this stream from which the new stream will sample.
-         * @param seed: (Optional.) An integer specifying the random seed that
-         * will be used to create the distribution.
-         */
-        shuffle(windowSize, seed) {
-          return new lazy_iterator_ShuffleIterator(this, windowSize, seed);
-        }
-        /**
-         * Force an iterator to execute serially: each next() call will await the
-         * prior one, so that they cannot execute concurrently.
-         */
-        serial() {
-          return new SerialIterator(this);
-        }
-      }
-      // ============================================================================
-      // The following private classes serve to implement the chainable methods
-      // on LazyIterator.  Unfortunately they can't be placed in separate files,
-      // due to resulting trouble with circular imports.
-      // ============================================================================
-      // Iterators that just extend LazyIterator directly
-      // ============================================================================
-      class lazy_iterator_ArrayIterator extends lazy_iterator_LazyIterator {
-        constructor(items) {
-          super();
-          this.items = items;
-          this.trav = 0;
-        }
-        summary() {
-          return `Array of ${this.items.length} items`;
-        }
-        async next() {
-          if (this.trav >= this.items.length) {
-            return { value: null, done: true };
-          }
-          const item = this.items[this.trav];
-          this.trav++;
-          return { value: deepClone(item), done: false };
-        }
-      }
-      class FunctionCallIterator extends lazy_iterator_LazyIterator {
-        constructor(nextFn) {
-          super();
-          this.nextFn = nextFn;
-        }
-        summary() {
-          return `Function call`;
-        }
-        async next() {
-          try {
-            return this.nextFn();
-          } catch (e) {
-            // Modify the error message but leave the stack trace intact
-            e.message = `Error thrown while iterating through a dataset: ${e.message}`;
-            throw e;
-          }
-        }
-      }
-      class SerialIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream) {
-          super();
-          this.upstream = upstream;
-          this.lastRead = Promise.resolve({ value: null, done: false });
-        }
-        summary() {
-          return `${this.upstream.summary()} -> Serial`;
-        }
-        async next() {
-          // This sets this.lastRead to a new Promise right away, as opposed to
-          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
-          // would not work because this.nextRead would be updated only after the
-          // promise resolves.
-          this.lastRead = this.lastRead.then(() => this.serialNext());
-          return this.lastRead;
-        }
-        async serialNext() {
-          return this.upstream.next();
-        }
-      }
-      class lazy_iterator_SkipIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream, maxCount) {
-          super();
-          this.upstream = upstream;
-          this.maxCount = maxCount;
-          // Local state that should not be clobbered by out-of-order execution.
-          this.count = 0;
-          this.lastRead = Promise.resolve({ value: null, done: false });
-        }
-        summary() {
-          return `${this.upstream.summary()} -> Skip`;
-        }
-        async next() {
-          // This sets this.lastRead to a new Promise right away, as opposed to
-          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
-          // would not work because this.nextRead would be updated only after the
-          // promise resolves.
-          this.lastRead = this.lastRead.then(() => this.serialNext());
-          return this.lastRead;
-        }
-        async serialNext() {
-          // TODO(soergel): consider tradeoffs of reading in parallel, eg.
-          // collecting next() promises in an Array and then waiting for
-          // Promise.all() of those. Benefit: pseudo-parallel execution.  Drawback:
-          // maybe delayed GC.
-          while (this.count++ < this.maxCount) {
-            const skipped = await this.upstream.next();
-            // short-circuit if upstream is already empty
-            if (skipped.done) {
-              return skipped;
-            }
-            dist["dispose"](skipped.value);
-          }
-          return this.upstream.next();
-        }
-      }
-      class TakeIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream, maxCount) {
-          super();
-          this.upstream = upstream;
-          this.maxCount = maxCount;
-          this.count = 0;
-        }
-        summary() {
-          return `${this.upstream.summary()} -> Take`;
-        }
-        async next() {
-          if (this.count++ >= this.maxCount) {
-            return { value: null, done: true };
-          }
-          return this.upstream.next();
-        }
-      }
-      // Note this batch just groups items into row-wise element arrays.
-      // Rotating these to a column-wise representation happens only at the dataset
-      // level.
-      class RowMajorBatchIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream, batchSize, enableSmallLastBatch = true) {
-          super();
-          this.upstream = upstream;
-          this.batchSize = batchSize;
-          this.enableSmallLastBatch = enableSmallLastBatch;
-          this.lastRead = Promise.resolve({ value: null, done: false });
-        }
-        summary() {
-          return `${this.upstream.summary()} -> RowMajorBatch`;
-        }
-        async next() {
-          // This sets this.lastRead to a new Promise right away, as opposed to
-          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
-          // would not work because this.nextRead would be updated only after the
-          // promise resolves.
-          this.lastRead = this.lastRead.then(() => this.serialNext());
-          return this.lastRead;
-        }
-        async serialNext() {
-          const batch = [];
-          while (batch.length < this.batchSize) {
-            const item = await this.upstream.next();
-            if (item.done) {
-              if (this.enableSmallLastBatch && batch.length > 0) {
-                return { value: batch, done: false };
-              }
-              return { value: null, done: true };
-            }
-            batch.push(item.value);
-          }
-          return { value: batch, done: false };
-        }
-      }
-      class lazy_iterator_FilterIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream, predicate) {
-          super();
-          this.upstream = upstream;
-          this.predicate = predicate;
-          this.lastRead = Promise.resolve({ value: null, done: false });
-        }
-        summary() {
-          return `${this.upstream.summary()} -> Filter`;
-        }
-        async next() {
-          // This sets this.lastRead to a new Promise right away, as opposed to
-          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
-          // would not work because this.nextRead would be updated only after the
-          // promise resolves.
-          this.lastRead = this.lastRead.then(() => this.serialNext());
-          return this.lastRead;
-        }
-        async serialNext() {
-          while (true) {
-            const item = await this.upstream.next();
-            if (item.done || this.predicate(item.value)) {
-              return item;
-            }
-            dist["dispose"](item.value);
-          }
-        }
-      }
-      class lazy_iterator_MapIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream, transform) {
-          super();
-          this.upstream = upstream;
-          this.transform = transform;
-        }
-        summary() {
-          return `${this.upstream.summary()} -> Map`;
-        }
-        async next() {
-          const item = await this.upstream.next();
-          if (item.done) {
-            return { value: null, done: true };
-          }
-          const inputTensors = dist["tensor_util"].getTensorsInContainer(item.value);
-          // Careful: the transform may mutate the item in place.
-          // That's why we have to remember the input Tensors above, and then
-          // below dispose only those that were not passed through to the output.
-          // Note too that the transform function is responsible for tidying
-          // any intermediate Tensors.  Here we are concerned only about the
-          // inputs.
-          const mapped = this.transform(item.value);
-          const outputTensors = dist["tensor_util"].getTensorsInContainer(mapped);
-          // TODO(soergel) faster intersection
-          // TODO(soergel) move to tf.disposeExcept(in, out)?
-          for (const t of inputTensors) {
-            if (!dist["tensor_util"].isTensorInList(t, outputTensors)) {
-              t.dispose();
-            }
-          }
-          return { value: mapped, done: false };
-        }
-      }
-      class ErrorHandlingLazyIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream, handler) {
-          super();
-          this.upstream = upstream;
-          this.handler = handler;
-          this.count = 0;
-          this.lastRead = Promise.resolve({ value: null, done: false });
-        }
-        summary() {
-          return `${this.upstream.summary()} -> handleErrors`;
-        }
-        async next() {
-          // This sets this.lastRead to a new Promise right away, as opposed to
-          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
-          // would not work because this.nextRead would be updated only after the
-          // promise resolves.
-          this.lastRead = this.lastRead.then(() => this.serialNext());
-          return this.lastRead;
-        }
-        async serialNext() {
-          while (true) {
-            try {
-              return await this.upstream.next();
-            } catch (e) {
-              if (!this.handler(e)) {
-                return { value: null, done: true };
-              }
-              // If the handler returns true, loop and fetch the next upstream item.
-              // If the upstream iterator throws an endless stream of errors, and if
-              // the handler says to ignore them, then we loop forever here.  That is
-              // the correct behavior-- it's up to the handler to decide when to stop.
-            }
-          }
-        }
-      }
-      class lazy_iterator_AsyncMapIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream, transform) {
-          super();
-          this.upstream = upstream;
-          this.transform = transform;
-        }
-        summary() {
-          return `${this.upstream.summary()} -> AsyncMap`;
-        }
-        async next() {
-          const item = await this.upstream.next();
-          if (item.done) {
-            return { value: null, done: true };
-          }
-          const inputTensors = dist["tensor_util"].getTensorsInContainer(item.value);
-          // Careful: the transform may mutate the item in place.
-          // That's why we have to remember the input Tensors above, and then
-          // below dispose only those that were not passed through to the output.
-          // Note too that the transform function is responsible for tidying
-          // any intermediate Tensors.  Here we are concerned only about the
-          // inputs.
-          const mapped = await this.transform(item.value);
-          const outputTensors = dist["tensor_util"].getTensorsInContainer(mapped);
-          // TODO(soergel) faster intersection
-          // TODO(soergel) move to tf.disposeExcept(in, out)?
-          for (const t of inputTensors) {
-            if (!dist["tensor_util"].isTensorInList(t, outputTensors)) {
-              t.dispose();
-            }
-          }
-          return { value: mapped, done: false };
-        }
-      }
-      // Iterators that maintain a queue of pending items
-      // ============================================================================
-      /**
-       * A base class for transforming streams that operate by maintaining an
-       * output queue of elements that are ready to return via next().  This is
-       * commonly required when the transformation is 1-to-many:  A call to next()
-       * may trigger a call to the underlying stream, which will produce many
-       * mapped elements of this stream-- of which we need to return only one, so
-       * we have to queue the rest.
-       */
-      class lazy_iterator_OneToManyIterator extends lazy_iterator_LazyIterator {
-        constructor() {
-          super();
-          this.outputQueue = new growing_ring_buffer_GrowingRingBuffer();
-          this.lastRead = Promise.resolve({ value: null, done: false });
-        }
-        async next() {
-          // This sets this.lastRead to a new Promise right away, as opposed to
-          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
-          // would not work because this.nextRead would be updated only after the
-          // promise resolves.
-          this.lastRead = this.lastRead.then(() => this.serialNext());
-          return this.lastRead;
-        }
-        async serialNext() {
-          // Fetch so that the queue contains at least one item if possible.
-          // If the upstream source is exhausted, AND there are no items left in
-          // the output queue, then this stream is also exhausted.
-          while (this.outputQueue.length() === 0) {
-            // TODO(soergel): consider parallel reads.
-            if (!(await this.pump())) {
-              return { value: null, done: true };
-            }
-          }
-          return { value: this.outputQueue.shift(), done: false };
-        }
-      }
-      class lazy_iterator_FlatmapIterator extends lazy_iterator_OneToManyIterator {
-        constructor(upstream, transform) {
-          super();
-          this.upstream = upstream;
-          this.transform = transform;
-        }
-        summary() {
-          return `${this.upstream.summary()} -> Flatmap`;
-        }
-        async pump() {
-          const item = await this.upstream.next();
-          if (item.done) {
-            return false;
-          }
-          const inputTensors = dist["tensor_util"].getTensorsInContainer(item.value);
-          // Careful: the transform may mutate the item in place.
-          // that's why we have to remember the input Tensors above, and then
-          // below dispose only those that were not passed through to the output.
-          // Note too that the transform function is responsible for tidying any
-          // intermediate Tensors.  Here we are concerned only about the inputs.
-          const mappedArray = this.transform(item.value);
-          const outputTensors = dist["tensor_util"].getTensorsInContainer(mappedArray);
-          this.outputQueue.pushAll(mappedArray);
-          // TODO(soergel) faster intersection, and deduplicate outputTensors
-          // TODO(soergel) move to tf.disposeExcept(in, out)?
-          for (const t of inputTensors) {
-            if (!dist["tensor_util"].isTensorInList(t, outputTensors)) {
-              t.dispose();
-            }
-          }
-          return true;
-        }
-      }
-      /**
-       * Provides a `LazyIterator` that concatenates a stream of underlying
-       * streams.
-       *
-       * Doing this in a concurrency-safe way requires some trickery.  In
-       * particular, we want this stream to return the elements from the
-       * underlying streams in the correct order according to when next() was
-       * called, even if the resulting Promises resolve in a different order.
-       */
-      class ChainedIterator extends lazy_iterator_LazyIterator {
-        constructor(iterators, baseErrorHandler) {
-          super();
-          this.baseErrorHandler = baseErrorHandler;
-          // Strict Promise execution order:
-          // a next() call may not even begin until the previous one completes.
-          this.lastRead = null;
-          // Local state that should not be clobbered by out-of-order execution.
-          this.iterator = null;
-          this.moreIterators = iterators;
-        }
-        summary() {
-          const upstreamSummaries = "TODO: fill in upstream of chained summaries";
-          return `${upstreamSummaries} -> Chained`;
-        }
-        async next() {
-          this.lastRead = this.readFromChain(this.lastRead);
-          return this.lastRead;
-        }
-        async readFromChain(lastRead) {
-          // Must await on the previous read since the previous read may have advanced
-          // the stream of streams, from which we need to read.
-          // This is unfortunate since we can't parallelize reads. Which means
-          // prefetching of chained streams is a no-op.
-          // One solution is to prefetch immediately upstream of this.
-          await lastRead;
-          if (this.iterator == null) {
-            const iteratorResult = await this.moreIterators.next();
-            if (iteratorResult.done) {
-              // No more streams to stream from.
-              return { value: null, done: true };
-            }
-            this.iterator = iteratorResult.value;
-            if (this.baseErrorHandler != null) {
-              this.iterator = this.iterator.handleErrors(this.baseErrorHandler);
-            }
-          }
-          const itemResult = await this.iterator.next();
-          if (itemResult.done) {
-            this.iterator = null;
-            return this.readFromChain(lastRead);
-          }
-          return itemResult;
-        }
-      }
-      var ZipMismatchMode;
-      (function (ZipMismatchMode) {
-        ZipMismatchMode[(ZipMismatchMode["FAIL"] = 0)] = "FAIL";
-        ZipMismatchMode[(ZipMismatchMode["SHORTEST"] = 1)] = "SHORTEST";
-        ZipMismatchMode[(ZipMismatchMode["LONGEST"] = 2)] = "LONGEST"; // use nulls for exhausted streams; use up the longest stream.
-      })(ZipMismatchMode || (ZipMismatchMode = {}));
-      /**
-       * Provides a `LazyIterator` that zips together an array, dict, or nested
-       * structure of `LazyIterator`s (and perhaps additional constants).
-       *
-       * The underlying streams must provide elements in a consistent order such
-       * that they correspond.
-       *
-       * Typically, the underlying streams should have the same number of
-       * elements. If they do not, the behavior is determined by the
-       * `mismatchMode` argument.
-       *
-       * The nested structure of the `iterators` argument determines the
-       * structure of elements in the resulting iterator.
-       *
-       * Doing this in a concurrency-safe way requires some trickery.  In
-       * particular, we want this stream to return the elements from the
-       * underlying streams in the correct order according to when next() was
-       * called, even if the resulting Promises resolve in a different order.
-       *
-       * @param iterators: An array or object containing LazyIterators at the
-       * leaves.
-       * @param mismatchMode: Determines what to do when one underlying iterator
-       * is exhausted before the others.  `ZipMismatchMode.FAIL` (the default)
-       * causes an error to be thrown in this case.  `ZipMismatchMode.SHORTEST`
-       * causes the zipped iterator to terminate with the furst underlying
-       * streams, so elements remaining on the longer streams are ignored.
-       * `ZipMismatchMode.LONGEST` causes the zipped stream to continue, filling
-       * in nulls for the exhausted streams, until all streams are exhausted.
-       */
-      class lazy_iterator_ZipIterator extends lazy_iterator_LazyIterator {
-        constructor(iterators, mismatchMode = ZipMismatchMode.FAIL) {
-          super();
-          this.iterators = iterators;
-          this.mismatchMode = mismatchMode;
-          this.count = 0;
-          this.currentPromise = null;
-        }
-        summary() {
-          const upstreamSummaries = "TODO: fill in upstream of zip summaries";
-          return `{${upstreamSummaries}} -> Zip`;
-        }
-        async nextState(afterState) {
-          // This chaining ensures that the underlying next() are not even called
-          // before the previous ones have resolved.
-          await afterState;
-          // Collect underlying iterator "done" signals as a side effect in
-          // getNext()
-          let numIterators = 0;
-          let iteratorsDone = 0;
-          function getNext(container) {
-            if (container instanceof lazy_iterator_LazyIterator) {
-              const result = container.next();
-              return {
-                value: result.then((x) => {
-                  numIterators++;
-                  if (x.done) {
-                    iteratorsDone++;
-                  }
-                  return x.value;
-                }),
-                recurse: false,
-              };
-            } else {
-              return { value: null, recurse: true };
-            }
-          }
-          const mapped = await Object(deep_map["c" /* deepMapAndAwaitAll */])(
-            this.iterators,
-            getNext
-          );
-          if (numIterators === iteratorsDone) {
-            // The streams have all ended.
-            return { value: null, done: true };
-          }
-          if (iteratorsDone > 0) {
-            switch (this.mismatchMode) {
-              case ZipMismatchMode.FAIL:
-                throw new Error(
-                  "Zipped streams should have the same length. " +
-                    `Mismatched at element ${this.count}.`
-                );
-              case ZipMismatchMode.SHORTEST:
-                return { value: null, done: true };
-              case ZipMismatchMode.LONGEST:
-              default:
-              // Continue.  The exhausted streams already produced value: null.
-            }
-          }
-          this.count++;
-          return { value: mapped, done: false };
-        }
-        async next() {
-          this.currentPromise = this.nextState(this.currentPromise);
-          return this.currentPromise;
-        }
-      }
-      // Iterators that maintain a ring buffer of pending promises
-      // ============================================================================
-      /**
-       * A stream that prefetches a given number of items from an upstream source,
-       * returning them in FIFO order.
-       *
-       * Note this prefetches Promises, but makes no guarantees about when those
-       * Promises resolve.
-       */
-      class lazy_iterator_PrefetchIterator extends lazy_iterator_LazyIterator {
-        constructor(upstream, bufferSize) {
-          super();
-          this.upstream = upstream;
-          this.bufferSize = bufferSize;
-          this.buffer = new RingBuffer(bufferSize);
-        }
-        summary() {
-          return `${this.upstream.summary()} -> Prefetch`;
-        }
-        /**
-         * Refill the prefetch buffer.  Returns only after the buffer is full, or
-         * the upstream source is exhausted.
-         */
-        refill() {
-          while (!this.buffer.isFull()) {
-            const v = this.upstream.next();
-            this.buffer.push(v);
-          }
-        }
-        next() {
-          this.refill();
-          // This shift will never throw an error because the buffer is always
-          // full after a refill. If the stream is exhausted, the buffer will be
-          // full of Promises that will resolve to the end-of-stream signal.
-          return this.buffer.shift();
-        }
-      }
-      /**
-       * A stream that performs a sliding-window random shuffle on an upstream
-       * source. This is like a `PrefetchIterator` except that the items are
-       * returned in randomized order.  Mixing naturally improves as the buffer
-       * size increases.
-       */
-      class lazy_iterator_ShuffleIterator extends lazy_iterator_PrefetchIterator {
-        constructor(upstream, windowSize, seed) {
-          super(upstream, windowSize);
-          this.upstream = upstream;
-          this.windowSize = windowSize;
-          // Local state that should not be clobbered by out-of-order execution.
-          this.upstreamExhausted = false;
-          this.random = seedrandom["alea"](seed || dist["util"].now().toString());
-          this.lastRead = Promise.resolve({ value: null, done: false });
-        }
-        async next() {
-          // This sets this.lastRead to a new Promise right away, as opposed to
-          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
-          // would not work because this.nextRead would be updated only after the
-          // promise resolves.
-          this.lastRead = this.lastRead.then(() => this.serialNext());
-          return this.lastRead;
-        }
-        randomInt(max) {
-          return Math.floor(this.random() * max);
-        }
-        chooseIndex() {
-          return this.randomInt(this.buffer.length());
-        }
-        async serialNext() {
-          // TODO(soergel): consider performance
-          if (!this.upstreamExhausted) {
-            this.refill();
-          }
-          while (!this.buffer.isEmpty()) {
-            const chosenIndex = this.chooseIndex();
-            const result = await this.buffer.shuffleExcise(chosenIndex);
-            if (result.done) {
-              this.upstreamExhausted = true;
-            } else {
-              this.refill();
-              return result;
-            }
-          }
-          return { value: null, done: true };
-        }
-      }
-      //# sourceMappingURL=lazy_iterator.js.map
-
-      /***/
-    },
-    /* 15 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (Buffer) {
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-          return OperationMapper;
-        });
-        /* unused harmony export decodeBase64 */
-        /* unused harmony export parseStringParam */
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "i", function () {
-          return getStringParam;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-          return getBoolParam;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
-          return getNumberParam;
-        });
-        /* unused harmony export parseDtypeParam */
-        /* unused harmony export getFuncParam */
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
-          return getDtypeParam;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
-          return getDtypeArrayParam;
-        });
-        /* unused harmony export parseTensorShapeParam */
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "k", function () {
-          return getTensorShapeParam;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
-          return getNumericArrayParam;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "h", function () {
-          return getStringArrayParam;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "j", function () {
-          return getTensorShapeArrayParam;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-          return getBoolArrayParam;
-        });
-        /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
-          __webpack_require__(0);
-        /* harmony import */ var _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__ =
-          __webpack_require__(21);
-        /* harmony import */ var _custom_op_register__WEBPACK_IMPORTED_MODULE_2__ =
-          __webpack_require__(24);
-        /* harmony import */ var _executors_utils__WEBPACK_IMPORTED_MODULE_3__ =
-          __webpack_require__(2);
-        /* harmony import */ var _op_list_arithmetic__WEBPACK_IMPORTED_MODULE_4__ =
-          __webpack_require__(41);
-        /* harmony import */ var _op_list_basic_math__WEBPACK_IMPORTED_MODULE_5__ =
-          __webpack_require__(42);
-        /* harmony import */ var _op_list_control__WEBPACK_IMPORTED_MODULE_6__ =
-          __webpack_require__(43);
-        /* harmony import */ var _op_list_convolution__WEBPACK_IMPORTED_MODULE_7__ =
-          __webpack_require__(44);
-        /* harmony import */ var _op_list_creation__WEBPACK_IMPORTED_MODULE_8__ =
-          __webpack_require__(45);
-        /* harmony import */ var _op_list_dynamic__WEBPACK_IMPORTED_MODULE_9__ =
-          __webpack_require__(46);
-        /* harmony import */ var _op_list_evaluation__WEBPACK_IMPORTED_MODULE_10__ =
-          __webpack_require__(47);
-        /* harmony import */ var _op_list_graph__WEBPACK_IMPORTED_MODULE_11__ =
-          __webpack_require__(48);
-        /* harmony import */ var _op_list_image__WEBPACK_IMPORTED_MODULE_12__ =
-          __webpack_require__(49);
-        /* harmony import */ var _op_list_logical__WEBPACK_IMPORTED_MODULE_13__ =
-          __webpack_require__(50);
-        /* harmony import */ var _op_list_matrices__WEBPACK_IMPORTED_MODULE_14__ =
-          __webpack_require__(51);
-        /* harmony import */ var _op_list_normalization__WEBPACK_IMPORTED_MODULE_15__ =
-          __webpack_require__(52);
-        /* harmony import */ var _op_list_reduction__WEBPACK_IMPORTED_MODULE_16__ =
-          __webpack_require__(53);
-        /* harmony import */ var _op_list_slice_join__WEBPACK_IMPORTED_MODULE_17__ =
-          __webpack_require__(54);
-        /* harmony import */ var _op_list_spectral__WEBPACK_IMPORTED_MODULE_18__ =
-          __webpack_require__(55);
-        /* harmony import */ var _op_list_transformation__WEBPACK_IMPORTED_MODULE_19__ =
-          __webpack_require__(56);
-        /**
-         * @license
-         * Copyright 2018 Google LLC. All Rights Reserved.
-         * Licensed under the Apache License, Version 2.0 (the "License");
-         * you may not use this file except in compliance with the License.
-         * You may obtain a copy of the License at
-         *
-         * http://www.apache.org/licenses/LICENSE-2.0
-         *
-         * Unless required by applicable law or agreed to in writing, software
-         * distributed under the License is distributed on an "AS IS" BASIS,
-         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-         * See the License for the specific language governing permissions and
-         * limitations under the License.
-         * =============================================================================
-         */
-
-        class OperationMapper {
-          // Singleton instance for the mapper
-          static get Instance() {
-            return this._instance || (this._instance = new this());
-          }
-          // Loads the op mapping from the JSON file.
-          constructor() {
-            const ops = [
-              _op_list_arithmetic__WEBPACK_IMPORTED_MODULE_4__,
-              _op_list_basic_math__WEBPACK_IMPORTED_MODULE_5__,
-              _op_list_control__WEBPACK_IMPORTED_MODULE_6__,
-              _op_list_convolution__WEBPACK_IMPORTED_MODULE_7__,
-              _op_list_creation__WEBPACK_IMPORTED_MODULE_8__,
-              _op_list_dynamic__WEBPACK_IMPORTED_MODULE_9__,
-              _op_list_evaluation__WEBPACK_IMPORTED_MODULE_10__,
-              _op_list_logical__WEBPACK_IMPORTED_MODULE_13__,
-              _op_list_image__WEBPACK_IMPORTED_MODULE_12__,
-              _op_list_graph__WEBPACK_IMPORTED_MODULE_11__,
-              _op_list_matrices__WEBPACK_IMPORTED_MODULE_14__,
-              _op_list_normalization__WEBPACK_IMPORTED_MODULE_15__,
-              _op_list_reduction__WEBPACK_IMPORTED_MODULE_16__,
-              _op_list_slice_join__WEBPACK_IMPORTED_MODULE_17__,
-              _op_list_spectral__WEBPACK_IMPORTED_MODULE_18__,
-              _op_list_transformation__WEBPACK_IMPORTED_MODULE_19__,
-            ];
-            const mappersJson = [].concat(...ops.map((op) => op.json));
-            this.opMappers = mappersJson.reduce((map, mapper) => {
-              map[mapper.tfOpName] = mapper;
-              return map;
-            }, {});
-          }
-          // Converts the model from Tensorflow GraphDef to local representation for
-          // TensorFlow.js API
-          transformGraph(graph, signature = {}) {
-            const tfNodes = graph.node;
-            const placeholders = [];
-            const weights = [];
-            const nodes = tfNodes.reduce((map, node) => {
-              map[node.name] = this.mapNode(node);
-              if (node.op.startsWith("Placeholder")) {
-                placeholders.push(map[node.name]);
-              }
-              if (node.op === "Const") {
-                weights.push(map[node.name]);
-              }
-              return map;
-            }, {});
-            let inputs = [];
-            const outputs = [];
-            let inputNodeNameToKey = {};
-            let outputNodeNameToKey = {};
-            if (signature != null) {
-              inputNodeNameToKey = this.mapSignatureEntries(signature.inputs);
-              outputNodeNameToKey = this.mapSignatureEntries(signature.outputs);
-            }
-            const allNodes = Object.keys(nodes);
-            allNodes.forEach((key) => {
-              const node = nodes[key];
-              node.inputNames.forEach((name) => {
-                const [nodeName] = Object(
-                  _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
-                )(name);
-                node.inputs.push(nodes[nodeName]);
-                nodes[nodeName].children.push(node);
-              });
-            });
-            // if signature has not outputs set, add any node that does not have
-            // outputs.
-            if (Object.keys(outputNodeNameToKey).length === 0) {
-              allNodes.forEach((key) => {
-                const node = nodes[key];
-                if (node.children.length === 0) {
-                  outputs.push(node);
-                }
-              });
-            } else {
-              Object.keys(outputNodeNameToKey).forEach((name) => {
-                const [nodeName] = Object(
-                  _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
-                )(name);
-                const node = nodes[nodeName];
-                if (node != null) {
-                  node.signatureKey = outputNodeNameToKey[name];
-                  outputs.push(node);
-                }
-              });
-            }
-            if (Object.keys(inputNodeNameToKey).length > 0) {
-              Object.keys(inputNodeNameToKey).forEach((name) => {
-                const [nodeName] = Object(
-                  _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
-                )(name);
-                const node = nodes[nodeName];
-                if (node) {
-                  node.signatureKey = inputNodeNameToKey[name];
-                  inputs.push(node);
-                }
-              });
-            } else {
-              inputs = placeholders;
-            }
-            let functions = {};
-            if (graph.library != null && graph.library.function != null) {
-              functions = graph.library.function.reduce((functions, func) => {
-                functions[func.signature.name] = this.mapFunction(func);
-                return functions;
-              }, {});
-            }
-            return {
-              nodes,
-              inputs,
-              outputs,
-              weights,
-              placeholders,
-              signature,
-              functions,
-            };
-          }
-          mapSignatureEntries(entries) {
-            return Object.keys(entries || {}).reduce((prev, curr) => {
-              prev[entries[curr].name] = curr;
-              return prev;
-            }, {});
-          }
-          mapNode(node) {
-            // Unsupported ops will cause an error at run-time (not parse time), since
-            // they may not be used by the actual execution subgraph.
-            const mapper =
-              Object(_custom_op_register__WEBPACK_IMPORTED_MODULE_2__[/* getRegisteredOp */ "b"])(
-                node.op
-              ) ||
-              this.opMappers[node.op] ||
-              {};
-            if (node.attr == null) {
-              node.attr = {};
-            }
-            const newNode = {
-              name: node.name,
-              op: node.op,
-              category: mapper.category,
-              inputNames: (node.input || []).map((input) =>
-                input.startsWith("^") ? input.substr(1) : input
-              ),
-              inputs: [],
-              children: [],
-              inputParams: {},
-              attrParams: {},
-              rawAttrs: node.attr,
-            };
-            if (mapper.inputs != null) {
-              newNode.inputParams = mapper.inputs.reduce((map, param) => {
-                map[param.name] = {
-                  type: param.type,
-                  inputIndexStart: param.start,
-                  inputIndexEnd: param.end,
-                };
-                return map;
-              }, {});
-            }
-            if (mapper.attrs != null) {
-              newNode.attrParams = mapper.attrs.reduce((map, param) => {
-                const type = param.type;
-                let value = undefined;
-                switch (param.type) {
-                  case "string":
-                    value = getStringParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getStringParam(node.attr, param.tfDeprecatedName, param.defaultValue);
-                    }
-                    break;
-                  case "string[]":
-                    value = getStringArrayParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getStringArrayParam(
-                        node.attr,
-                        param.tfDeprecatedName,
-                        param.defaultValue
-                      );
-                    }
-                    break;
-                  case "number":
-                    value = getNumberParam(node.attr, param.tfName, param.defaultValue || 0);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getNumberParam(node.attr, param.tfDeprecatedName, param.defaultValue);
-                    }
-                    break;
-                  case "number[]":
-                    value = getNumericArrayParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getNumericArrayParam(
-                        node.attr,
-                        param.tfDeprecatedName,
-                        param.defaultValue
-                      );
-                    }
-                    break;
-                  case "bool":
-                    value = getBoolParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getBoolParam(node.attr, param.tfDeprecatedName, param.defaultValue);
-                    }
-                    break;
-                  case "bool[]":
-                    value = getBoolArrayParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getBoolArrayParam(
-                        node.attr,
-                        param.tfDeprecatedName,
-                        param.defaultValue
-                      );
-                    }
-                    break;
-                  case "shape":
-                    value = getTensorShapeParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getTensorShapeParam(
-                        node.attr,
-                        param.tfDeprecatedName,
-                        param.defaultValue
-                      );
-                    }
-                    break;
-                  case "shape[]":
-                    value = getTensorShapeArrayParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getTensorShapeArrayParam(
-                        node.attr,
-                        param.tfDeprecatedName,
-                        param.defaultValue
-                      );
-                    }
-                    break;
-                  case "dtype":
-                    value = getDtypeParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getDtypeParam(node.attr, param.tfDeprecatedName, param.defaultValue);
-                    }
-                    break;
-                  case "dtype[]":
-                    value = getDtypeArrayParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getDtypeArrayParam(
-                        node.attr,
-                        param.tfDeprecatedName,
-                        param.defaultValue
-                      );
-                    }
-                    break;
-                  case "func":
-                    value = getFuncParam(node.attr, param.tfName, param.defaultValue);
-                    if (value === undefined && !!param.tfDeprecatedName) {
-                      value = getFuncParam(node.attr, param.tfDeprecatedName, param.defaultValue);
-                    }
-                    break;
-                  case "tensor":
-                  case "tensors":
-                    break;
-                  default:
-                    throw new Error(`Unsupported param type: ${param.type} for op: ${node.op}`);
-                }
-                map[param.name] = { value, type };
-                return map;
-              }, {});
-            }
-            return newNode;
-          }
-          // map the TFunctionDef to TFJS graph object
-          mapFunction(functionDef) {
-            const tfNodes = functionDef.nodeDef;
-            const placeholders = [];
-            const weights = [];
-            let nodes = {};
-            if (tfNodes != null) {
-              nodes = tfNodes.reduce((map, node) => {
-                map[node.name] = this.mapNode(node);
-                if (node.op === "Const") {
-                  weights.push(map[node.name]);
-                }
-                return map;
-              }, {});
-            }
-            const inputs = [];
-            const outputs = [];
-            functionDef.signature.inputArg.forEach((arg) => {
-              const [nodeName] = Object(
-                _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
-              )(arg.name);
-              const node = {
-                name: nodeName,
-                op: "Placeholder",
-                inputs: [],
-                inputNames: [],
-                category: "graph",
-                inputParams: {},
-                attrParams: { dtype: { value: parseDtypeParam(arg.type), type: "dtype" } },
-                children: [],
-              };
-              node.signatureKey = arg.name;
-              inputs.push(node);
-              nodes[nodeName] = node;
-            });
-            const allNodes = Object.keys(nodes);
-            allNodes.forEach((key) => {
-              const node = nodes[key];
-              node.inputNames.forEach((name) => {
-                const [nodeName] = Object(
-                  _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
-                )(name);
-                node.inputs.push(nodes[nodeName]);
-                nodes[nodeName].children.push(node);
-              });
-            });
-            const returnNodeMap = functionDef.ret;
-            functionDef.signature.outputArg.forEach((output) => {
-              const [nodeName, index] = Object(
-                _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
-              )(returnNodeMap[output.name]);
-              const node = nodes[nodeName];
-              if (node != null) {
-                node.defaultOutput = index;
-                outputs.push(node);
-              }
-            });
-            const signature = this.mapArgsToSignature(functionDef);
-            return { nodes, inputs, outputs, weights, placeholders, signature };
-          }
-          mapArgsToSignature(functionDef) {
-            return {
-              methodName: functionDef.signature.name,
-              inputs: functionDef.signature.inputArg.reduce((map, arg) => {
-                map[arg.name] = this.mapArgToTensorInfo(arg);
-                return map;
-              }, {}),
-              outputs: functionDef.signature.outputArg.reduce((map, arg) => {
-                map[arg.name] = this.mapArgToTensorInfo(arg, functionDef.ret);
-                return map;
-              }, {}),
-            };
-          }
-          mapArgToTensorInfo(arg, nameMap) {
-            let name = arg.name;
-            if (nameMap != null) {
-              name = nameMap[name];
-            }
-            return { name, dtype: arg.type };
-          }
-        }
-        function decodeBase64(text) {
-          const global = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["env"])().global;
-          if (typeof global.atob !== "undefined") {
-            return global.atob(text);
-          } else if (typeof Buffer !== "undefined") {
-            return new Buffer(text, "base64").toString();
-          } else {
-            throw new Error(
-              "Unable to decode base64 in this environment. " +
-                "Missing built-in atob() or Buffer()"
-            );
-          }
-        }
-        function parseStringParam(s, keepCase) {
-          const value = Array.isArray(s) ? String.fromCharCode.apply(null, s) : decodeBase64(s);
-          return keepCase ? value : value.toLowerCase();
-        }
-        function getStringParam(attrs, name, def, keepCase = false) {
-          const param = attrs[name];
-          if (param != null) {
-            return parseStringParam(param.s, keepCase);
-          }
-          return def;
-        }
-        function getBoolParam(attrs, name, def) {
-          const param = attrs[name];
-          return param ? param.b : def;
-        }
-        function getNumberParam(attrs, name, def) {
-          const param = attrs[name] || {};
-          const value = param["i"] != null ? param["i"] : param["f"] != null ? param["f"] : def;
-          return typeof value === "number" ? value : parseInt(value, 10);
-        }
-        function parseDtypeParam(value) {
-          if (typeof value === "string") {
-            // tslint:disable-next-line:no-any
-            value = _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"][value];
-          }
-          switch (value) {
-            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_FLOAT:
-              return "float32";
-            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_INT32:
-            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_INT64:
-            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_INT8:
-            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_UINT8:
-              return "int32";
-            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_BOOL:
-              return "bool";
-            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_DOUBLE:
-              return "float32";
-            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_STRING:
-              return "string";
-            default:
-              // Unknown dtype error will happen at runtime (instead of parse time),
-              // since these nodes might not be used by the actual subgraph execution.
-              return null;
-          }
-        }
-        function getFuncParam(attrs, name, def) {
-          const param = attrs[name];
-          if (param && param.func) {
-            return param.func.name;
-          }
-          return def;
-        }
-        function getDtypeParam(attrs, name, def) {
-          const param = attrs[name];
-          if (param && param.type) {
-            return parseDtypeParam(param.type);
-          }
-          return def;
-        }
-        function getDtypeArrayParam(attrs, name, def) {
-          const param = attrs[name];
-          if (param && param.list && param.list.type) {
-            return param.list.type.map((v) => parseDtypeParam(v));
-          }
-          return def;
-        }
-        function parseTensorShapeParam(shape) {
-          if (shape.unknownRank) {
-            return undefined;
-          }
-          if (shape.dim != null) {
-            return shape.dim.map((dim) =>
-              typeof dim.size === "number" ? dim.size : parseInt(dim.size, 10)
-            );
-          }
-          return [];
-        }
-        function getTensorShapeParam(attrs, name, def) {
-          const param = attrs[name];
-          if (param && param.shape) {
-            return parseTensorShapeParam(param.shape);
-          }
-          return def;
-        }
-        function getNumericArrayParam(attrs, name, def) {
-          const param = attrs[name];
-          if (param) {
-            return ((param.list.f && param.list.f.length ? param.list.f : param.list.i) || []).map(
-              (v) => (typeof v === "number" ? v : parseInt(v, 10))
-            );
-          }
-          return def;
-        }
-        function getStringArrayParam(attrs, name, def, keepCase = false) {
-          const param = attrs[name];
-          if (param && param.list && param.list.s) {
-            return param.list.s.map((v) => {
-              return parseStringParam(v, keepCase);
-            });
-          }
-          return def;
-        }
-        function getTensorShapeArrayParam(attrs, name, def) {
-          const param = attrs[name];
-          if (param && param.list && param.list.shape) {
-            return param.list.shape.map((v) => {
-              return parseTensorShapeParam(v);
-            });
-          }
-          return def;
-        }
-        function getBoolArrayParam(attrs, name, def) {
-          const param = attrs[name];
-          if (param && param.list && param.list.b) {
-            return param.list.b;
-          }
-          return def;
-        }
-        //# sourceMappingURL=operation_mapper.js.map
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(39).Buffer));
-
-      /***/
-    },
-    /* 16 */
-    /***/ function (module, exports) {
-      module.exports = function () {
-        throw new Error("define cannot be used indirect");
-      };
-
-      /***/
-    },
-    /* 17 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return getKernel;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return getGradient;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return getKernelsForBackend;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
-        return registerKernel;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
-        return registerGradient;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
-        return unregisterKernel;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
-        return unregisterGradient;
-      });
-      /* harmony import */ var _global_util__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(33);
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const kernelRegistry = Object(_global_util__WEBPACK_IMPORTED_MODULE_0__[/* getGlobal */ "a"])(
-        "kernelRegistry",
-        () => new Map()
-      );
-      const gradRegistry = Object(_global_util__WEBPACK_IMPORTED_MODULE_0__[/* getGlobal */ "a"])(
-        "gradRegistry",
-        () => new Map()
-      );
-      /**
-       * Returns the kernel function (code) associated with the provided names.
-       *
-       * @param kernelName The official name of the kernel.
-       * @param backendName The official name of the backend.
-       */
-      function getKernel(kernelName, backendName) {
-        const key = makeKey(kernelName, backendName);
-        return kernelRegistry.get(key);
-      }
-      /**
-       * Returns the registered gradient info associated with the provided kernel.
-       * @param kernelName The official TF kernel name.
-       */
-      function getGradient(kernelName) {
-        return gradRegistry.get(kernelName);
-      }
-      function getKernelsForBackend(backendName) {
-        const it = kernelRegistry.entries();
-        const result = [];
-        while (true) {
-          const { done, value } = it.next();
-          if (done) {
-            break;
-          }
-          const [key, config] = value;
-          const [backend] = key.split("_");
-          if (backend === backendName) {
-            result.push(config);
-          }
-        }
-        return result;
-      }
-      /**
-       * Registers the function (forward pass) for the kernel in a global registry.
-       *
-       * @param config A config object with the following properties:
-       * - `kernelName` The official name of the kernel.
-       * - `backendName` The official name of the backend.
-       * - `kernelFunc` The function to run during the forward pass of the kernel.
-       * - `setupFunc` Optional. Gets called once, after the backend initializes.
-       * - `disposeFunc` Optional. Gets called once, right before the backend is
-       * disposed.
-       */
-      function registerKernel(config) {
-        const { kernelName, backendName } = config;
-        const key = makeKey(kernelName, backendName);
-        if (kernelRegistry.has(key)) {
-          console.warn(
-            `The kernel '${kernelName}' for backend ` + `'${backendName}' is already registered`
-          );
-        }
-        kernelRegistry.set(key, config);
-      }
-      /**
-       * Registers a gradient function for a given kernel in the global registry,
-       * to be used during the back-propagation of that kernel.
-       *
-       * @param config An object with the following properties:
-       * - `kernelName` The name of the kernel that the gradient function is for.
-       * - `gradFunc` The function to run during back-propagation.
-       */
-      function registerGradient(config) {
-        const { kernelName } = config;
-        if (gradRegistry.has(kernelName)) {
-          console.warn(`Overriding the gradient for '${kernelName}'`);
-        }
-        gradRegistry.set(kernelName, config);
-      }
-      /**
-       * Removes the kernel function from the registry.
-       *
-       * @param kernelName The official name of the kernel.
-       * @param backendName The official name of the backend.
-       *
-       */
-      function unregisterKernel(kernelName, backendName) {
-        const key = makeKey(kernelName, backendName);
-        if (!kernelRegistry.has(key)) {
-          throw new Error(
-            `The kernel '${kernelName}' for backend ` + `'${backendName}' is not registered`
-          );
-        }
-        kernelRegistry.delete(key);
-      }
-      /** Removes the registered gradient from the global registry. */
-      function unregisterGradient(kernelName) {
-        if (!gradRegistry.has(kernelName)) {
-          throw new Error(`The gradient '${kernelName}' for backend is not registered`);
-        }
-        gradRegistry.delete(kernelName);
-      }
-      function makeKey(kernelName, backendName) {
-        return `${backendName}_${kernelName}`;
-      }
-      //# sourceMappingURL=kernel_registry.js.map
-
-      /***/
-    },
-    /* 18 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return complex;
-      });
-      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
-      /* harmony import */ var _kernel_names__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(6);
-      /* harmony import */ var _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__ =
-        __webpack_require__(3);
-      /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(1);
-      /* harmony import */ var _operation__WEBPACK_IMPORTED_MODULE_4__ = __webpack_require__(4);
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Converts two real numbers to a complex number.
-       *
-       * Given a tensor `real` representing the real part of a complex number, and a
-       * tensor `imag` representing the imaginary part of a complex number, this
-       * operation returns complex numbers elementwise of the form [r0, i0, r1, i1],
-       * where r represents the real part and i represents the imag part.
-       *
-       * The input tensors real and imag must have the same shape.
-       *
-       * ```js
-       * const real = tf.tensor1d([2.25, 3.25]);
-       * const imag = tf.tensor1d([4.75, 5.75]);
-       * const complex = tf.complex(real, imag);
-       *
-       * complex.print();
-       * ```
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function complex_(real, imag) {
-        const $real = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"]
-        )(real, "real", "complex");
-        const $imag = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"]
-        )(imag, "imag", "complex");
-        _util__WEBPACK_IMPORTED_MODULE_3__["assertShapesMatch"](
-          $real.shape,
-          $imag.shape,
-          `real and imag shapes, ${$real.shape} and ${$imag.shape}, ` +
-            `must match in call to tf.complex().`
-        );
-        const forward = (backend) => {
-          return backend.complex($real, $imag);
-        };
-        const inputs = { real: $real, imag: $imag };
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          _kernel_names__WEBPACK_IMPORTED_MODULE_1__[/* Complex */ "k"]
-        );
-      }
-      const complex = Object(_operation__WEBPACK_IMPORTED_MODULE_4__[/* op */ "a"])({ complex_ });
-      //# sourceMappingURL=complex.js.map
-
-      /***/
-    },
-    /* 19 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return deepMap;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
-        return deepZip;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
-        return zipToList;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return deepMapAndAwaitAll;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
-        return isIterable;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return canTensorify;
-      });
-      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
-        __webpack_require__(0);
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      /**
-       * Apply a mapping function to a nested structure in a recursive manner.
-       *
-       * The result of the mapping is an object with the same nested structure (i.e.,
-       * of arrays and dicts) as the input, except that some subtrees are replaced,
-       * according to the results of the mapping function.
-       *
-       * Mappings are memoized.  Thus, if the nested structure contains the same
-       * object in multiple positions, the output will contain the same mapped object
-       * in those positions.  Cycles are not supported, however.
-       *
-       * @param input: The object to which to apply the mapping function.
-       * @param mapFn: A function that expects a single node of the object tree, and
-       *   returns a `DeepMapResult`.  The `DeepMapResult` either provides a
-       *   replacement value for that node (i.e., replacing the subtree), or indicates
-       *   that the node should be processed recursively.
-       */
-      function deepMap(input, mapFn) {
-        return deepMapInternal(input, mapFn);
-      }
-      /**
-       * @param seen: A Map of known object mappings (i.e., memoized results of
-       *   `mapFn()`)
-       * @param containedIn: An set containing objects on the reference path currently
-       *   being processed (used to detect cycles).
-       */
-      function deepMapInternal(input, mapFn, seen = new Map(), containedIn = new Set()) {
-        if (input == null) {
-          return null;
-        }
-        if (containedIn.has(input)) {
-          throw new Error("Circular references are not supported.");
-        }
-        if (seen.has(input)) {
-          return seen.get(input);
-        }
-        const result = mapFn(input);
-        if (result.recurse && result.value !== null) {
-          throw new Error("A deep map function may not return both a value and recurse=true.");
-        }
-        if (!result.recurse) {
-          seen.set(input, result.value);
-          return result.value;
-        } else if (isIterable(input)) {
-          // tslint:disable-next-line:no-any
-          const mappedIterable = Array.isArray(input) ? [] : {};
-          containedIn.add(input);
-          for (const k in input) {
-            const child = input[k];
-            const childResult = deepMapInternal(child, mapFn, seen, containedIn);
-            mappedIterable[k] = childResult;
-          }
-          containedIn.delete(input);
-          return mappedIterable;
-        } else {
-          throw new Error(`Can't recurse into non-iterable type: ${input}`);
-        }
-      }
-      // TODO(soergel, kangyizhang) Reconsider naming of deepZip() to avoid confusion
-      // with zip()
-      /**
-       * Zip nested structures together in a recursive manner.
-       *
-       * This has the effect of transposing or pivoting data, e.g. converting it from
-       * a row-major representation to a column-major representation.
-       *
-       * For example, `deepZip([{a: 1, b: 2}, {a: 3, b: 4}])` returns
-       * `{a: [1, 3], b: [2, 4]}`.
-       *
-       * The inputs should all have the same nested structure (i.e., of arrays and
-       * dicts).  The result is a single object with the same nested structure, where
-       * the leaves are arrays collecting the values of the inputs at that location
-       * (or, optionally, the result of a custom function applied to those arrays).
-       *
-       * @param inputs: An array of the objects to zip together.
-       * @param zipFn: (optional) A function that expects an array of elements at a
-       *   single node of the object tree, and returns a `DeepMapResult`.  The
-       *   `DeepMapResult` either provides a result value for that node (i.e.,
-       *   representing the subtree), or indicates that the node should be processed
-       *   recursively.  The default zipFn recurses as far as possible and places
-       *   arrays at the leaves.
-       */
-      function deepZip(inputs, zipFn = zipToList) {
-        return deepZipInternal(inputs, zipFn);
-      }
-      /**
-       * @param containedIn: An set containing objects on the reference path currently
-       *   being processed (used to detect cycles).
-       */
-      function deepZipInternal(inputs, zipFn, containedIn = new Set()) {
-        // The recursion follows the structure of input 0; it's assumed that all the
-        // other inputs have the same structure.
-        const input = inputs[0];
-        if (containedIn.has(input)) {
-          throw new Error("Circular references are not supported.");
-        }
-        const result = zipFn(inputs);
-        if (result.recurse && result.value !== null) {
-          throw new Error("A deep zip function may not return both a value and recurse=true.");
-        }
-        if (!result.recurse) {
-          return result.value;
-        } else if (isIterable(input)) {
-          // tslint:disable-next-line:no-any
-          const mappedIterable = Array.isArray(input) ? [] : {};
-          containedIn.add(input);
-          for (const k in input) {
-            const children = inputs.map((x) => x[k]);
-            const childResult = deepZipInternal(children, zipFn, containedIn);
-            mappedIterable[k] = childResult;
-          }
-          containedIn.delete(input);
-          return mappedIterable;
-        } else {
-          throw new Error(`Can't recurse into non-iterable type: ${input}`);
-        }
-      }
-      // tslint:disable-next-line:no-any
-      function zipToList(x) {
-        if (x === null) {
-          return null;
-        }
-        // TODO(soergel): validate array type?
-        if (isIterable(x[0])) {
-          return { value: null, recurse: true };
-        } else {
-          return { value: x, recurse: false };
-        }
-      }
-      /**
-       * Apply an async mapping function to a nested structure in a recursive manner.
-       *
-       * This first creates a nested structure of Promises, and then awaits all of
-       * those, resulting in a single Promise for a resolved nested structure.
-       *
-       * The result of the mapping is an object with the same nested structure (i.e.,
-       * of arrays and dicts) as the input, except that some subtrees are replaced,
-       * according to the results of the mapping function.
-       *
-       * Mappings are memoized.  Thus, if the nested structure contains the same
-       * object in multiple positions, the output will contain the same mapped object
-       * in those positions.  Cycles are not supported, however.
-       *
-       * @param input: The object to which to apply the mapping function.
-       * @param mapFn: A function that expects a single node of the object tree, and
-       *   returns a `DeepMapAsyncResult`.  The `DeepMapAsyncResult` either provides
-       *   a `Promise` for a replacement value for that node (i.e., replacing the
-       *   subtree), or indicates that the node should be processed recursively.  Note
-       *   that the decision whether or not to recurse must be made immediately; only
-       *   the mapped value may be promised.
-       */
-      async function deepMapAndAwaitAll(input, mapFn) {
-        const seen = new Map();
-        // First do a normal deepMap, collecting Promises in 'seen' as a side effect.
-        deepMapInternal(input, mapFn, seen);
-        // Replace the Promises in 'seen' in place.
-        // Note TypeScript provides no async map iteration, and regular map iteration
-        // is broken too, so sadly we have to do Array.from() to make it work.
-        // (There's no advantage to Promise.all(), and that would be tricky anyway.)
-        for (const key of Array.from(seen.keys())) {
-          const value = seen.get(key);
-          if (value instanceof Promise) {
-            const mappedValue = await value;
-            seen.set(key, mappedValue);
-          }
-        }
-        // Normal deepMap again, this time filling in the resolved values.
-        // It's unfortunate that we have to do two passes.
-        // TODO(soergel): test performance and think harder about a fast solution.
-        const result = deepMapInternal(input, mapFn, seen);
-        return result;
-      }
-      /**
-       * Determine whether the argument is iterable.
-       *
-       * @returns true if the argument is an array or any non-Tensor object.
-       */
-      // tslint:disable-next-line:no-any
-      function isIterable(obj) {
-        return (
-          obj != null &&
-          !ArrayBuffer.isView(obj) &&
-          (Array.isArray(obj) ||
-            (typeof obj === "object" &&
-              !(obj instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"])))
-        );
-      }
-      /**
-       * Determine whether the argument can be converted to Tensor.
-       *
-       * Tensors, primitives, arrays, and TypedArrays all qualify; anything else does
-       * not.
-       *
-       * @returns true if the argument can be converted to Tensor.
-       */
-      // tslint:disable-next-line:no-any
-      function canTensorify(obj) {
-        return (
-          obj == null ||
-          isPrimitive(obj) ||
-          Array.isArray(obj) ||
-          (typeof obj === "object" &&
-            obj instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]) ||
-          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].isTypedArray(obj)
-        );
-      }
-      /**
-       * Returns true if the given `value` is a primitive type. Otherwise returns
-       * false. This is equivalant to node util.isPrimitive
-       */
-      function isPrimitive(value) {
-        return value === null || (typeof value !== "object" && typeof value !== "function");
-      }
-      //# sourceMappingURL=deep_map.js.map
-
-      /***/
-    },
-    /* 20 */
-    /***/ function (module, exports, __webpack_require__) {
-      // A library of seedable RNGs implemented in Javascript.
-      //
-      // Usage:
-      //
-      // var seedrandom = require('seedrandom');
-      // var random = seedrandom(1); // or any seed.
-      // var x = random();       // 0 <= x < 1.  Every bit is random.
-      // var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.
-
-      // alea, a 53-bit multiply-with-carry generator by Johannes Baagøe.
-      // Period: ~2^116
-      // Reported to pass all BigCrush tests.
-      var alea = __webpack_require__(68);
-
-      // xor128, a pure xor-shift generator by George Marsaglia.
-      // Period: 2^128-1.
-      // Reported to fail: MatrixRank and LinearComp.
-      var xor128 = __webpack_require__(69);
-
-      // xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.
-      // Period: 2^192-2^32
-      // Reported to fail: CollisionOver, SimpPoker, and LinearComp.
-      var xorwow = __webpack_require__(70);
-
-      // xorshift7, by François Panneton and Pierre L'ecuyer, takes
-      // a different approach: it adds robustness by allowing more shifts
-      // than Marsaglia's original three.  It is a 7-shift generator
-      // with 256 bits, that passes BigCrush with no systmatic failures.
-      // Period 2^256-1.
-      // No systematic BigCrush failures reported.
-      var xorshift7 = __webpack_require__(71);
-
-      // xor4096, by Richard Brent, is a 4096-bit xor-shift with a
-      // very long period that also adds a Weyl generator. It also passes
-      // BigCrush with no systematic failures.  Its long period may
-      // be useful if you have many generators and need to avoid
-      // collisions.
-      // Period: 2^4128-2^32.
-      // No systematic BigCrush failures reported.
-      var xor4096 = __webpack_require__(72);
-
-      // Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random
-      // number generator derived from ChaCha, a modern stream cipher.
-      // https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf
-      // Period: ~2^127
-      // No systematic BigCrush failures reported.
-      var tychei = __webpack_require__(73);
-
-      // The original ARC4-based prng included in this library.
-      // Period: ~2^1600
-      var sr = __webpack_require__(74);
-
-      sr.alea = alea;
-      sr.xor128 = xor128;
-      sr.xorwow = xorwow;
-      sr.xorshift7 = xorshift7;
-      sr.xor4096 = xor4096;
-      sr.tychei = tychei;
-
-      module.exports = sr;
-
-      /***/
-    },
-    /* 21 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return DataType;
-      });
-      /* unused harmony export SaverDef */
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-      /** DataType enum. */
-      var DataType;
-      (function (DataType) {
-        DataType[(DataType["DT_INVALID"] = 0)] = "DT_INVALID";
-        DataType[(DataType["DT_FLOAT"] = 1)] = "DT_FLOAT";
-        DataType[(DataType["DT_DOUBLE"] = 2)] = "DT_DOUBLE";
-        DataType[(DataType["DT_INT32"] = 3)] = "DT_INT32";
-        DataType[(DataType["DT_UINT8"] = 4)] = "DT_UINT8";
-        DataType[(DataType["DT_INT16"] = 5)] = "DT_INT16";
-        DataType[(DataType["DT_INT8"] = 6)] = "DT_INT8";
-        DataType[(DataType["DT_STRING"] = 7)] = "DT_STRING";
-        DataType[(DataType["DT_COMPLEX64"] = 8)] = "DT_COMPLEX64";
-        DataType[(DataType["DT_INT64"] = 9)] = "DT_INT64";
-        DataType[(DataType["DT_BOOL"] = 10)] = "DT_BOOL";
-        DataType[(DataType["DT_QINT8"] = 11)] = "DT_QINT8";
-        DataType[(DataType["DT_QUINT8"] = 12)] = "DT_QUINT8";
-        DataType[(DataType["DT_QINT32"] = 13)] = "DT_QINT32";
-        DataType[(DataType["DT_BFLOAT16"] = 14)] = "DT_BFLOAT16";
-        DataType[(DataType["DT_FLOAT_REF"] = 101)] = "DT_FLOAT_REF";
-        DataType[(DataType["DT_DOUBLE_REF"] = 102)] = "DT_DOUBLE_REF";
-        DataType[(DataType["DT_INT32_REF"] = 103)] = "DT_INT32_REF";
-        DataType[(DataType["DT_UINT8_REF"] = 104)] = "DT_UINT8_REF";
-        DataType[(DataType["DT_INT16_REF"] = 105)] = "DT_INT16_REF";
-        DataType[(DataType["DT_INT8_REF"] = 106)] = "DT_INT8_REF";
-        DataType[(DataType["DT_STRING_REF"] = 107)] = "DT_STRING_REF";
-        DataType[(DataType["DT_COMPLEX64_REF"] = 108)] = "DT_COMPLEX64_REF";
-        DataType[(DataType["DT_INT64_REF"] = 109)] = "DT_INT64_REF";
-        DataType[(DataType["DT_BOOL_REF"] = 110)] = "DT_BOOL_REF";
-        DataType[(DataType["DT_QINT8_REF"] = 111)] = "DT_QINT8_REF";
-        DataType[(DataType["DT_QUINT8_REF"] = 112)] = "DT_QUINT8_REF";
-        DataType[(DataType["DT_QINT32_REF"] = 113)] = "DT_QINT32_REF";
-        DataType[(DataType["DT_BFLOAT16_REF"] = 114)] = "DT_BFLOAT16_REF";
-      })(DataType || (DataType = {}));
-      var SaverDef;
-      (function (SaverDef) {
-        /** CheckpointFormatVersion enum. */
-        let CheckpointFormatVersion;
-        (function (CheckpointFormatVersion) {
-          CheckpointFormatVersion[(CheckpointFormatVersion["LEGACY"] = 0)] = "LEGACY";
-          CheckpointFormatVersion[(CheckpointFormatVersion["V1"] = 1)] = "V1";
-          CheckpointFormatVersion[(CheckpointFormatVersion["V2"] = 2)] = "V2";
-        })(
-          (CheckpointFormatVersion =
-            SaverDef.CheckpointFormatVersion || (SaverDef.CheckpointFormatVersion = {}))
-        );
-      })(SaverDef || (SaverDef = {}));
-      //# sourceMappingURL=compiled_api.js.map
-
-      /***/
-    },
-    /* 22 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return real;
-      });
-      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
-      /* harmony import */ var _kernel_names__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(6);
-      /* harmony import */ var _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__ =
-        __webpack_require__(3);
-      /* harmony import */ var _operation__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(4);
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the real part of a complex (or real) tensor.
-       *
-       * Given a tensor input, this operation returns a tensor of type float that is
-       * the real part of each element in input considered as a complex number.
-       *
-       * If the input is real, it simply makes a clone.
-       *
-       * ```js
-       * const x = tf.complex([-2.25, 3.25], [4.75, 5.75]);
-       * tf.real(x).print();
-       * ```
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function real_(input) {
-        const $input = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"]
-        )(input, "input", "real");
-        const forward = (backend) => {
-          return backend.real($input);
-        };
-        const inputs = { input: $input };
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          _kernel_names__WEBPACK_IMPORTED_MODULE_1__[/* Real */ "hb"]
-        );
-      }
-      const real = Object(_operation__WEBPACK_IMPORTED_MODULE_3__[/* op */ "a"])({ real_ });
-      //# sourceMappingURL=real.js.map
-
-      /***/
-    },
-    /* 23 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return Rank;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return upcastType;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return sumOutType;
-      });
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      var Rank;
-      (function (Rank) {
-        Rank["R0"] = "R0";
-        Rank["R1"] = "R1";
-        Rank["R2"] = "R2";
-        Rank["R3"] = "R3";
-        Rank["R4"] = "R4";
-        Rank["R5"] = "R5";
-        Rank["R6"] = "R6";
-      })(Rank || (Rank = {}));
-      // Looks for upcasting types. Used, for example, in operations with mixed dtype
-      // inputs.
-      var UpcastInt32AndMap;
-      (function (UpcastInt32AndMap) {
-        UpcastInt32AndMap["float32"] = "float32";
-        UpcastInt32AndMap["int32"] = "int32";
-        UpcastInt32AndMap["bool"] = "int32";
-        UpcastInt32AndMap["complex64"] = "complex64";
-      })(UpcastInt32AndMap || (UpcastInt32AndMap = {}));
-      var UpcastBoolAndMap;
-      (function (UpcastBoolAndMap) {
-        UpcastBoolAndMap["float32"] = "float32";
-        UpcastBoolAndMap["int32"] = "int32";
-        UpcastBoolAndMap["bool"] = "bool";
-        UpcastBoolAndMap["complex64"] = "complex64";
-      })(UpcastBoolAndMap || (UpcastBoolAndMap = {}));
-      var UpcastFloat32AndMap;
-      (function (UpcastFloat32AndMap) {
-        UpcastFloat32AndMap["float32"] = "float32";
-        UpcastFloat32AndMap["int32"] = "float32";
-        UpcastFloat32AndMap["bool"] = "float32";
-        UpcastFloat32AndMap["complex64"] = "complex64";
-      })(UpcastFloat32AndMap || (UpcastFloat32AndMap = {}));
-      var UpcastComplex64AndMap;
-      (function (UpcastComplex64AndMap) {
-        UpcastComplex64AndMap["float32"] = "complex64";
-        UpcastComplex64AndMap["int32"] = "complex64";
-        UpcastComplex64AndMap["bool"] = "complex64";
-        UpcastComplex64AndMap["complex64"] = "complex64";
-      })(UpcastComplex64AndMap || (UpcastComplex64AndMap = {}));
-      const upcastTypeMap = {
-        float32: UpcastFloat32AndMap,
-        int32: UpcastInt32AndMap,
-        bool: UpcastBoolAndMap,
-        complex64: UpcastComplex64AndMap,
-      };
-      function upcastType(typeA, typeB) {
-        if (typeA === "string" || typeB === "string") {
-          if (typeA === "string" && typeB === "string") {
-            return "string";
-          }
-          throw new Error(`Can not upcast ${typeA} with ${typeB}`);
-        }
-        return upcastTypeMap[typeA][typeB];
-      }
-      /** Returns the output type after summation. */
-      function sumOutType(type) {
-        return upcastType(type, "int32");
-      }
-      //# sourceMappingURL=types.js.map
-
-      /***/
-    },
-    /* 24 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
-        return registerOp;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return getRegisteredOp;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return deregisterOp;
-      });
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const CUSTOM_OPS = {};
-      /**
-       * Register an Op for graph model executor. This allow you to register
-       * TensorFlow custom op or override existing op.
-       *
-       * Here is an example of registering a new MatMul Op.
-       * ```js
-       * const customMatmul = (node) =>
-       *    tf.matMul(
-       *        node.inputs[0], node.inputs[1],
-       *        node.attrs['transpose_a'], node.attrs['transpose_b']);
-       *
-       * tf.registerOp('MatMul', customMatmul);
-       * ```
-       * The inputs and attrs of the node object is based on the TensorFlow op
-       * registry.
-       *
-       * @param name The Tensorflow Op name.
-       * @param opFunc An op function which is called with the current graph node
-       * during execution and needs to return a tensor or a list of tensors. The node
-       * has the following attributes:
-       *    - attr: A map from attribute name to its value
-       *    - inputs: A list of input tensors
-       */
-      /** @doc {heading: 'Models', subheading: 'Op Registry'} */
-      function registerOp(name, opFunc) {
-        const opMapper = {
-          tfOpName: name,
-          category: "custom",
-          inputs: [],
-          attrs: [],
-          customExecutor: opFunc,
-        };
-        CUSTOM_OPS[name] = opMapper;
-      }
-      /**
-       * Retrieve the OpMapper object for the registered op.
-       *
-       * @param name The Tensorflow Op name.
-       */
-      /** @doc {heading: 'Models', subheading: 'Op Registry'} */
-      function getRegisteredOp(name) {
-        return CUSTOM_OPS[name];
-      }
-      /**
-       * Deregister the Op for graph model executor.
-       *
-       * @param name The Tensorflow Op name.
-       */
-      /** @doc {heading: 'Models', subheading: 'Op Registry'} */
-      function deregisterOp(name) {
-        delete CUSTOM_OPS[name];
-      }
-      //# sourceMappingURL=register.js.map
-
-      /***/
-    },
-    /* 25 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return imag;
-      });
-      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
-      /* harmony import */ var _kernel_names__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(6);
-      /* harmony import */ var _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__ =
-        __webpack_require__(3);
-      /* harmony import */ var _operation__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(4);
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Returns the imaginary part of a complex (or real) tensor.
-       *
-       * Given a tensor input, this operation returns a tensor of type float that is
-       * the imaginary part of each element in input considered as a complex number.
-       * If input is real, a tensor of all zeros is returned.
-       *
-       * ```js
-       * const x = tf.complex([-2.25, 3.25], [4.75, 5.75]);
-       * tf.imag(x).print();
-       * ```
-       */
-      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
-      function imag_(input) {
-        const $input = Object(
-          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"]
-        )(input, "input", "imag");
-        const forward = (backend) => {
-          return backend.imag($input);
-        };
-        const inputs = { input: $input };
-        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
-          forward,
-          inputs,
-          null /* gradient */,
-          _kernel_names__WEBPACK_IMPORTED_MODULE_1__[/* Imag */ "K"]
-        );
-      }
-      const imag = Object(_operation__WEBPACK_IMPORTED_MODULE_3__[/* op */ "a"])({ imag_ });
-      //# sourceMappingURL=imag.js.map
-
-      /***/
-    },
-    /* 26 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-        return pool;
-      });
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return maxPoolPositions;
-      });
-      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
-        __webpack_require__(0);
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function pool(xValues, xShape, dtype, strides, convInfo, poolType) {
-        const strideHeight = convInfo.strideHeight;
-        const strideWidth = convInfo.strideWidth;
-        const dilationHeight = convInfo.dilationHeight;
-        const dilationWidth = convInfo.dilationWidth;
-        const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-        const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-        const padTop = convInfo.padInfo.top;
-        const padLeft = convInfo.padInfo.left;
-        const initialValue =
-          poolType === "max" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY;
-        const output = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["buffer"])(
-          convInfo.outShape,
-          dtype
-        );
-        const outputVals = output.values;
-        const outputBatchStrides =
-          convInfo.outShape[1] * convInfo.outShape[2] * convInfo.outShape[3];
-        const outputRowStrides = convInfo.outShape[2] * convInfo.outShape[3];
-        const outputColStrides = convInfo.outShape[3];
-        for (let b = 0; b < convInfo.batchSize; ++b) {
-          const outputBatchOffset = b * outputBatchStrides;
-          const inputBatchOffset = b * strides[0];
-          for (let d = 0; d < convInfo.inChannels; ++d) {
-            for (let yR = 0; yR < convInfo.outHeight; ++yR) {
-              const xRCorner = yR * strideHeight - padTop;
-              const xRMin = Math.max(0, xRCorner);
-              const xRMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRCorner);
-              const outputRowOffset = outputBatchOffset + yR * outputRowStrides;
-              for (let yC = 0; yC < convInfo.outWidth; ++yC) {
-                const xCCorner = yC * strideWidth - padLeft;
-                const xCMin = Math.max(0, xCCorner);
-                const xCMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xCCorner);
-                let minMaxValue = initialValue;
-                let avgValue = 0;
-                let count = 0;
-                for (let xR = xRMin; xR < xRMax; xR += dilationHeight) {
-                  const xROffset = inputBatchOffset + xR * strides[1];
-                  for (let xC = xCMin; xC < xCMax; xC += dilationWidth) {
-                    const xCOffset = xROffset + xC * strides[2];
-                    const pixel = xValues[xCOffset + d];
-                    if (poolType === "max" && pixel > minMaxValue) {
-                      minMaxValue = pixel;
-                    } else if (poolType === "avg") {
-                      avgValue += pixel;
-                      count++;
-                    }
-                  }
-                  if (isNaN(minMaxValue)) {
-                    break;
-                  }
-                }
-                const outputOffset = outputRowOffset + yC * outputColStrides + d;
-                outputVals[outputOffset] = poolType === "avg" ? avgValue / count : minMaxValue;
-              }
-            }
-          }
-        }
-        return output;
-      }
-      function maxPoolPositions(
-        xValues,
-        xShape,
-        dtype,
-        convInfo,
-        flattenPositions = false,
-        includeBatchInIndex = false
-      ) {
-        const maxPositions = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["buffer"])(
-          convInfo.outShape,
-          "int32"
-        );
-        const strideHeight = convInfo.strideHeight;
-        const strideWidth = convInfo.strideWidth;
-        const dilationHeight = convInfo.dilationHeight;
-        const dilationWidth = convInfo.dilationWidth;
-        const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-        const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-        const padTop = convInfo.padInfo.top;
-        const padLeft = convInfo.padInfo.left;
-        const xBuf = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["buffer"])(
-          xShape,
-          dtype,
-          xValues
-        );
-        for (let b = 0; b < convInfo.batchSize; ++b) {
-          for (let d = 0; d < convInfo.inChannels; ++d) {
-            for (let yR = 0; yR < convInfo.outHeight; ++yR) {
-              const xRCorner = yR * strideHeight - padTop;
-              let xRMin = xRCorner;
-              while (xRMin < 0) {
-                xRMin += dilationHeight;
-              }
-              // const xRMin = Math.max(0, xRCorner);
-              const xRMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRCorner);
-              for (let yC = 0; yC < convInfo.outWidth; ++yC) {
-                const xCCorner = yC * strideWidth - padLeft;
-                let xCMin = xCCorner;
-                while (xCMin < 0) {
-                  xCMin += dilationWidth;
-                }
-                const xCMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xCCorner);
-                let maxValue = Number.NEGATIVE_INFINITY;
-                let maxPosition = -1;
-                for (let xR = xRMin; xR < xRMax; xR += dilationHeight) {
-                  const wR = xR - xRCorner;
-                  for (let xC = xCMin; xC < xCMax; xC += dilationWidth) {
-                    const wC = xC - xCCorner;
-                    const pixel = xBuf.get(b, xR, xC, d);
-                    if (pixel > maxValue) {
-                      maxValue = pixel;
-                      if (flattenPositions) {
-                        maxPosition = includeBatchInIndex
-                          ? ((b * convInfo.inHeight + xR) * convInfo.inWidth + xC) *
-                              convInfo.inChannels +
-                            d
-                          : (xR * convInfo.inWidth + xC) * convInfo.inChannels + d;
-                      } else {
-                        maxPosition = wR * effectiveFilterWidth + wC;
-                      }
-                    }
-                  }
-                }
-                maxPositions.set(maxPosition, b, yR, yC, d);
-              }
-            }
-          }
-        }
-        return maxPositions;
-      }
-      //# sourceMappingURL=pool_utils.js.map
-
-      /***/
-    },
-    /* 27 */
-    /***/ function (module, exports) {
-      var g;
-
-      // This works in non-strict mode
-      g = (function () {
-        return this;
-      })();
-
-      try {
-        // This works if eval is allowed (see CSP)
-        g = g || new Function("return this")();
-      } catch (e) {
-        // This works if the window reference is available
-        if (typeof window === "object") g = window;
-      }
-
-      // g can still be undefined, but nothing to do about it...
-      // We return undefined, instead of nothing here, so it's
-      // easier to handle this case. if(!global) { ...}
-
-      module.exports = g;
-
-      /***/
-    },
-    /* 28 */
-    /***/ function (module, exports) {
-      module.exports = function (module) {
-        if (!module.webpackPolyfill) {
-          module.deprecate = function () {};
-          module.paths = [];
-          // module.parent = undefined by default
-          if (!module.children) module.children = [];
-          Object.defineProperty(module, "loaded", {
-            enumerable: true,
-            get: function () {
-              return module.l;
-            },
-          });
-          Object.defineProperty(module, "id", {
-            enumerable: true,
-            get: function () {
-              return module.i;
-            },
-          });
-          module.webpackPolyfill = 1;
-        }
-        return module;
-      };
-
-      /***/
-    },
-    /* 29 */
-    /***/ function (module, exports) {
-      /* WEBPACK VAR INJECTION */ (function (__webpack_amd_options__) {
-        /* globals __webpack_amd_options__ */
-        module.exports = __webpack_amd_options__;
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, {}));
-
-      /***/
-    },
-    /* 30 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return transposeImpl;
-      });
-      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
-        __webpack_require__(0);
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function transposeImpl(xVals, xShape, dtype, perm, newShape) {
-        const xRank = xShape.length;
-        const xSize =
-          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].sizeFromShape(xShape);
-        const xStrides =
-          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].computeStrides(xShape);
-        const newStrides =
-          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].computeStrides(newShape);
-        const result = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__[
-          "util"
-        ].getTypedArrayFromDType(
-          dtype,
-          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].sizeFromShape(newShape)
-        );
-        for (let i = 0; i < xSize; ++i) {
-          const loc = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].indexToLoc(
-            i,
-            xRank,
-            xStrides
-          );
-          // Permute location.
-          const newLoc = new Array(loc.length);
-          for (let i = 0; i < newLoc.length; i++) {
-            newLoc[i] = loc[perm[i]];
-          }
-          const newIndex = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].locToIndex(
-            newLoc,
-            xRank,
-            newStrides
-          );
-          result[newIndex] = xVals[i];
-        }
-        return result;
-      }
-      //# sourceMappingURL=Transpose_impl.js.map
-
-      /***/
-    },
-    /* 31 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "a", function () {
-        return /* reexport */ backend_cpu_MathBackendCPU;
-      });
-      __webpack_require__.d(__webpack_exports__, "c", function () {
-        return /* reexport */ version;
-      });
-      __webpack_require__.d(__webpack_exports__, "b", function () {
-        return /* reexport */ shared_namespaceObject;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/shared.js
-      var shared_namespaceObject = {};
-      __webpack_require__.r(shared_namespaceObject);
-      __webpack_require__.d(shared_namespaceObject, "maxImpl", function () {
-        return Max_impl["a" /* maxImpl */];
-      });
-      __webpack_require__.d(shared_namespaceObject, "transposeImpl", function () {
-        return Transpose_impl["a" /* transposeImpl */];
-      });
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max_impl.js
-      var Max_impl = __webpack_require__(37);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose_impl.js
-      var Transpose_impl = __webpack_require__(30);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/shared.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // Shared kernel impls for use in other backends.
-
-      //# sourceMappingURL=shared.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
-      var dist = __webpack_require__(0);
-
-      // EXTERNAL MODULE: ./node_modules/seedrandom/index.js
-      var seedrandom = __webpack_require__(20);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/cpu_util.js
-      var cpu_util = __webpack_require__(9);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/pool_utils.js
-      var pool_utils = __webpack_require__(26);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/backend_cpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const nonMaxSuppressionV3 = dist["kernel_impls"].nonMaxSuppressionV3;
-      const split = dist["kernel_impls"].split;
-      const tile = dist["kernel_impls"].tile;
-      const topkImpl = dist["kernel_impls"].topkImpl;
-      const whereImpl = dist["kernel_impls"].whereImpl;
-
-      function mapActivation(backend, x, activation, preluActivationWeights) {
-        if (activation === "linear") {
-          return backend.linear(x);
-        } else if (activation === "relu") {
-          return backend.relu(x);
-        } else if (activation === "elu") {
-          return backend.elu(x);
-        } else if (activation === "relu6") {
-          return backend.relu6(x);
-        } else if (activation === "prelu") {
-          return backend.prelu(x, preluActivationWeights);
-        }
-        throw new Error(`Activation ${activation} has not been implemented for the CPU backend.`);
-      }
-      class backend_cpu_MathBackendCPU extends dist["KernelBackend"] {
-        constructor() {
-          super();
-          this.blockSize = 48;
-          this.firstUse = true;
-          this.data = new dist["DataStorage"](this, Object(dist["engine"])());
-        }
-        write(values, shape, dtype) {
-          if (this.firstUse) {
-            this.firstUse = false;
-            if (Object(dist["env"])().get("IS_NODE")) {
-              dist["backend_util"].warn(
-                "\n============================\n" +
-                  "Hi there 👋. Looks like you are running TensorFlow.js in " +
-                  "Node.js. To speed things up dramatically, install our node " +
-                  "backend, which binds to TensorFlow C++, by running " +
-                  "npm i @tensorflow/tfjs-node, " +
-                  "or npm i @tensorflow/tfjs-node-gpu if you have CUDA. " +
-                  "Then call require('@tensorflow/tfjs-node'); (-gpu " +
-                  "suffix for CUDA) at the start of your program. " +
-                  "Visit https://github.com/tensorflow/tfjs-node for more details." +
-                  "\n============================"
-              );
-            }
-          }
-          const dataId = {};
-          this.data.set(dataId, { values, dtype });
-          return dataId;
-        }
-        move(dataId, values, shape, dtype) {
-          this.data.set(dataId, { values, dtype });
-        }
-        numDataIds() {
-          return this.data.numDataIds();
-        }
-        async read(dataId) {
-          return this.readSync(dataId);
-        }
-        readSync(dataId) {
-          const { dtype, complexTensors } = this.data.get(dataId);
-          if (dtype === "complex64") {
-            const realValues = this.readSync(complexTensors.real.dataId);
-            const imagValues = this.readSync(complexTensors.imag.dataId);
-            return dist["backend_util"].mergeRealAndImagArrays(realValues, imagValues);
-          }
-          return this.data.get(dataId).values;
-        }
-        bufferSync(t) {
-          const data = this.readSync(t.dataId);
-          let decodedData = data;
-          if (t.dtype === "string") {
-            try {
-              // Decode the bytes into string.
-              decodedData = data.map((d) => dist["util"].decodeString(d));
-            } catch (_a) {
-              throw new Error("Failed to decode encoded string bytes into utf-8");
-            }
-          }
-          return dist["buffer"](t.shape, t.dtype, decodedData);
-        }
-        makeOutput(values, shape, dtype) {
-          const dataId = this.write(values, shape, dtype);
-          return Object(dist["engine"])().makeTensorFromDataId(dataId, shape, dtype, this);
-        }
-        disposeData(dataId) {
-          if (this.data.has(dataId)) {
-            const { complexTensors } = this.data.get(dataId);
-            if (complexTensors != null) {
-              complexTensors.real.dispose();
-              complexTensors.imag.dispose();
-            }
-            this.data.delete(dataId);
-          }
-        }
-        async time(f) {
-          const start = dist["util"].now();
-          f();
-          const kernelMs = dist["util"].now() - start;
-          return { kernelMs };
-        }
-        memory() {
-          return {
-            // Unreliable due to automatic gc. The numbers above are cumulative.
-            unreliable: true,
-            reasons: [
-              "The reported memory is an upper bound. Due to automatic garbage " +
-                "collection, the true allocated memory may be less.",
-            ],
-          };
-        }
-        complex(real, imag) {
-          const result = this.makeOutput(null, real.shape, "complex64");
-          const resultData = this.data.get(result.dataId);
-          // The backend owns the reference to the underlying real and imaginary
-          // clones. These will explicitly get disposed when the complex tensor is
-          // disposed.
-          resultData.complexTensors = {
-            real: Object(dist["engine"])().keep(real.clone()),
-            imag: Object(dist["engine"])().keep(imag.clone()),
-          };
-          return result;
-        }
-        real(input) {
-          const resultData = this.data.get(input.dataId);
-          return resultData.complexTensors.real.clone();
-        }
-        imag(input) {
-          const resultData = this.data.get(input.dataId);
-          return resultData.complexTensors.imag.clone();
-        }
-        slice(x, begin, size) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "slice");
-          const isContinous = dist["slice_util"].isSliceContinous(x.shape, begin, size);
-          if (isContinous) {
-            const flatOffset = dist["slice_util"].computeFlatOffset(begin, x.strides);
-            const length = dist["util"].sizeFromShape(size);
-            const vals = this.readSync(x.dataId);
-            return dist["tensor"](vals.subarray(flatOffset, flatOffset + length), size, x.dtype);
-          }
-          const buffer = dist["buffer"](size, x.dtype);
-          const xBuf = this.bufferSync(x);
-          for (let i = 0; i < buffer.size; ++i) {
-            const loc = buffer.indexToLoc(i);
-            const xLoc = loc.map((idx, j) => idx + begin[j]);
-            buffer.values[i] = xBuf.get(...xLoc);
-          }
-          return buffer.toTensor();
-        }
-        stridedSlice(x, begin, end, strides) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "stridedSlice");
-          const outShape = dist["slice_util"].computeOutShape(begin, end, strides);
-          if (outShape.some((axis) => axis === 0)) {
-            return dist["tensor"]([], outShape);
-          }
-          const buffer = dist["buffer"](outShape, x.dtype);
-          const xBuf = this.bufferSync(x);
-          for (let i = 0; i < buffer.size; i++) {
-            const loc = buffer.indexToLoc(i);
-            const newLoc = new Array(loc.length);
-            for (let j = 0; j < newLoc.length; j++) {
-              newLoc[j] = loc[j] * strides[j] + begin[j];
-            }
-            buffer.set(xBuf.get(...newLoc), ...loc);
-          }
-          return buffer.toTensor();
-        }
-        diag(x) {
-          const xVals = this.readSync(x.dataId);
-          const buffer = dist["buffer"]([x.size, x.size], x.dtype);
-          const vals = buffer.values;
-          for (let i = 0; i < xVals.length; i++) {
-            vals[i * x.size + i] = xVals[i];
-          }
-          return buffer.toTensor();
-        }
-        unstack(x, axis) {
-          const num = x.shape[axis];
-          const outShape = new Array(x.rank - 1);
-          let outIndex = 0;
-          for (let i = 0; i < x.rank; i++) {
-            if (i !== axis) {
-              outShape[outIndex++] = x.shape[i];
-            }
-          }
-          const begin = new Array(x.rank).fill(0);
-          const size = x.shape.slice();
-          size[axis] = 1;
-          const res = new Array(num);
-          for (let i = 0; i < res.length; i++) {
-            begin[axis] = i;
-            res[i] = this.slice(x, begin, size).reshape(outShape);
-          }
-          return res;
-        }
-        reverse(x, axis) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "reverse");
-          const buffer = dist["buffer"](x.shape, x.dtype);
-          const xBuf = this.bufferSync(x);
-          for (let i = 0; i < buffer.size; i++) {
-            const outLoc = buffer.indexToLoc(i);
-            const inLoc = outLoc.slice();
-            axis.forEach((ax) => (inLoc[ax] = x.shape[ax] - 1 - inLoc[ax]));
-            buffer.set(xBuf.get(...inLoc), ...outLoc);
-          }
-          return buffer.toTensor();
-        }
-        concat(tensors, axis) {
-          if (tensors[0].dtype === "complex64") {
-            const reals = tensors.map((t) => dist["real"](t));
-            const imags = tensors.map((t) => dist["imag"](t));
-            return dist["complex"](this.concat(reals, axis), this.concat(imags, axis));
-          }
-          const tensors2D = tensors.map((t) => {
-            const innerSize = dist["util"].sizeFromShape(t.shape.slice(axis));
-            return t.as2D(-1, innerSize);
-          });
-          const outShape = dist["backend_util"].computeOutShape(
-            tensors2D.map((t) => t.shape),
-            1
-            /* axis
-             */
-          );
-          const values = dist["buffer"](outShape, tensors[0].dtype).values;
-          if (tensors2D[0].shape[0] === 1) {
-            // Use built-in TypedArray.set() method for speed.
-            let offset = 0;
-            tensors2D.forEach((t) => {
-              values.set(this.readSync(t.dataId), offset);
-              offset += t.size;
-            });
-          } else {
-            let colOffset = 0;
-            tensors2D.forEach((t) => {
-              const tVals = this.readSync(t.dataId);
-              let tIdx = 0;
-              for (let row = 0; row < t.shape[0]; ++row) {
-                const resIdx = row * outShape[1] + colOffset;
-                for (let col = 0; col < t.shape[1]; ++col) {
-                  values[resIdx + col] = tVals[tIdx++];
-                }
-              }
-              colOffset += t.shape[1];
-            });
-          }
-          const finalOutShape = dist["backend_util"].computeOutShape(
-            tensors.map((t) => t.shape),
-            axis
-          );
-          return dist["tensor"](values, finalOutShape, tensors[0].dtype);
-        }
-        neg(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "neg");
-          return this.multiply(dist["scalar"](-1), x);
-        }
-        add(a, b) {
-          if (a.dtype === "complex64" || b.dtype === "complex64") {
-            return this.broadcastedBinaryComplexOp(
-              a.cast("complex64"),
-              b.cast("complex64"),
-              (aReal, aImag, bReal, bImag) => {
-                return { real: aReal + bReal, imag: aImag + bImag };
-              }
-            );
-          }
-          return this.broadcastedBinaryOp(
-            a,
-            b,
-            Object(dist["upcastType"])(a.dtype, b.dtype),
-            (aValue, bValue) => aValue + bValue
-          );
-        }
-        addN(tensors) {
-          Object(cpu_util["a" /* assertNotComplex */])(tensors, "addN");
-          const vals = tensors.map((t) => this.readSync(t.dataId));
-          const result = dist["buffer"](tensors[0].shape, tensors[0].dtype);
-          const resultVals = result.values;
-          for (let i = 0; i < tensors.length; i++) {
-            const currVals = vals[i];
-            for (let j = 0; j < resultVals.length; j++) {
-              resultVals[j] += currVals[j];
-            }
-          }
-          return result.toTensor();
-        }
-        softmax(logits, dim) {
-          const axes = dist["util"].parseAxisParam([dim], logits.shape);
-          // TODO(annxingyuan): Call maxImpl rather than op as part of softmax kernel
-          // modularization.
-          const maxLogit = Object(dist["max"])(logits, axes);
-          const expandedShape = dist["backend_util"].expandShapeToKeepDim(maxLogit.shape, axes);
-          const a = this.subtract(logits, maxLogit.reshape(expandedShape));
-          const b = this.exp(a);
-          const sumExp = this.sum(b, axes).reshape(expandedShape);
-          // TODO(annxingyuan): Call divImpl rather than op as part of softmax
-          // kernel modularization.
-          return dist["div"](b, sumExp);
-        }
-        subtract(a, b) {
-          if (a.dtype === "complex64" || b.dtype === "complex64") {
-            return this.broadcastedBinaryComplexOp(
-              a.cast("complex64"),
-              b.cast("complex64"),
-              (aReal, aImag, bReal, bImag) => {
-                return { real: aReal - bReal, imag: aImag - bImag };
-              }
-            );
-          }
-          return this.broadcastedBinaryOp(
-            a,
-            b,
-            Object(dist["upcastType"])(a.dtype, b.dtype),
-            (aValue, bValue) => aValue - bValue
-          );
-        }
-        pow(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "pow");
-          return this.broadcastedBinaryOp(a, b, a.dtype, (aValue, bValue) =>
-            Math.pow(aValue, bValue)
-          );
-        }
-        batchMatMul(a, b, transposeA, transposeB) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "matMul");
-          const sharedDim = transposeA ? a.shape[1] : a.shape[2];
-          const leftDim = transposeA ? a.shape[2] : a.shape[1];
-          const rightDim = transposeB ? b.shape[1] : b.shape[2];
-          const batchDim = a.shape[0];
-          const aValues = this.readSync(a.dataId);
-          const bValues = this.readSync(b.dataId);
-          const [aBatch, aOuterStep, aInnerStep] = transposeA
-            ? [a.strides[0], 1, a.strides[1]]
-            : [a.strides[0], a.strides[1], 1];
-          const [bInnerStep, bOuterStep, bBatch] = transposeB
-            ? [1, b.strides[1], b.strides[0]]
-            : [b.strides[1], 1, b.strides[0]];
-          const size = leftDim * rightDim;
-          const result = dist["buffer"]([batchDim, leftDim, rightDim], a.dtype);
-          const resVals = result.values;
-          const blockSize = this.blockSize;
-          for (let b = 0; b < batchDim; b++) {
-            for (let i0 = 0; i0 < leftDim; i0 += blockSize) {
-              for (let j0 = 0; j0 < rightDim; j0 += blockSize) {
-                for (let k0 = 0; k0 < sharedDim; k0 += blockSize) {
-                  // for when blockSize doesn't evenly divide the input
-                  const iBlock = Math.min(i0 + blockSize, leftDim);
-                  const jBlock = Math.min(j0 + blockSize, rightDim);
-                  const kBlock = Math.min(k0 + blockSize, sharedDim);
-                  for (let i = i0; i < iBlock; i++) {
-                    for (let j = j0; j < jBlock; j++) {
-                      let sum = 0.0;
-                      for (let k = k0; k < kBlock; k++) {
-                        sum +=
-                          aValues[b * aBatch + i * aOuterStep + k * aInnerStep] *
-                          bValues[k * bInnerStep + j * bOuterStep + b * bBatch];
-                      }
-                      resVals[b * size + (i * rightDim + j)] += sum;
-                    }
-                  }
-                }
-              }
-            }
-          }
-          return result.toTensor();
-        }
-        fusedBatchMatMul({
-          a,
-          b,
-          transposeA,
-          transposeB,
-          bias,
-          activation,
-          preluActivationWeights,
-        }) {
-          let result = this.batchMatMul(a, b, transposeA, transposeB);
-          if (bias) {
-            result = this.add(result, bias);
-          }
-          if (activation) {
-            result = mapActivation(this, result, activation, preluActivationWeights);
-          }
-          return result;
-        }
-        multiply(a, b) {
-          if (a.dtype === "complex64" || b.dtype === "complex64") {
-            return this.broadcastedBinaryComplexOp(
-              a.cast("complex64"),
-              b.cast("complex64"),
-              (aReal, aImag, bReal, bImag) => {
-                return {
-                  real: aReal * bReal - aImag * bImag,
-                  imag: aReal * bImag + aImag * bReal,
-                };
-              }
-            );
-          }
-          return this.broadcastedBinaryOp(
-            a,
-            b,
-            Object(dist["upcastType"])(a.dtype, b.dtype),
-            (aValue, bValue) => aValue * bValue
-          );
-        }
-        floorDiv(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "floorDiv");
-          const op = (a, b) => Math.floor(a / b);
-          const outputDtype = "int32";
-          return this.broadcastedBinaryOp(a, b, outputDtype, op);
-        }
-        sum(x, axes) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "sum");
-          dist["backend_util"].assertAxesAreInnerMostDims("sum", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const resultDtype = Object(dist["upcastType"])(x.dtype, "int32");
-          const result = dist["zeros"](outShape, resultDtype);
-          const reduceSize = dist["util"].sizeFromShape(reduceShape);
-          const vals = this.readSync(result.dataId);
-          const aVals = this.readSync(x.dataId);
-          for (let i = 0; i < vals.length; ++i) {
-            const offset = i * reduceSize;
-            let sum = 0;
-            for (let j = 0; j < reduceSize; ++j) {
-              sum += aVals[offset + j];
-            }
-            vals[i] = sum;
-          }
-          return result;
-        }
-        prod(x, axes) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "sum");
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const resultDtype = Object(dist["upcastType"])(x.dtype, "int32");
-          const result = dist["zeros"](outShape, resultDtype);
-          const reduceSize = dist["util"].sizeFromShape(reduceShape);
-          const vals = this.readSync(result.dataId);
-          const aVals = this.readSync(x.dataId);
-          for (let i = 0; i < vals.length; ++i) {
-            const offset = i * reduceSize;
-            let prod = 1;
-            for (let j = 0; j < reduceSize; ++j) {
-              prod *= aVals[offset + j];
-            }
-            vals[i] = prod;
-          }
-          return result;
-        }
-        unsortedSegmentSum(x, segmentIds, numSegments) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "unsortedSegmentSum");
-          const res = [];
-          // Reshape the segment id's so that they can be broadcast with
-          // x. The new shape should be [segmentIds.shape, 1, ..., 1]
-          const numIters = x.rank - segmentIds.rank;
-          for (let i = 0; i < numIters; ++i) {
-            segmentIds = segmentIds.expandDims(i + 1);
-          }
-          for (let i = 0; i < numSegments; ++i) {
-            const segmentId = dist["scalar"](i, "int32");
-            const mask = dist["equal"](segmentId, segmentIds).asType("float32");
-            const sum = mask.mul(x).sum(0);
-            res.push(sum);
-          }
-          return dist["stack"](res);
-        }
-        argMin(x, axis) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "argMin");
-          const axes = [axis];
-          dist["backend_util"].assertAxesAreInnerMostDims("argMin", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const result = dist["zeros"](outShape, "int32");
-          const reduceSize = dist["util"].sizeFromShape(reduceShape);
-          const vals = this.readSync(result.dataId);
-          const aVals = this.readSync(x.dataId);
-          for (let i = 0; i < vals.length; ++i) {
-            const offset = i * reduceSize;
-            let min = aVals[offset];
-            let minIndex = 0;
-            for (let j = 0; j < reduceSize; ++j) {
-              const value = aVals[offset + j];
-              if (value < min) {
-                min = value;
-                minIndex = j;
-              }
-            }
-            vals[i] = minIndex;
-          }
-          return result;
-        }
-        argMax(x, axis) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "argMax");
-          const axes = [axis];
-          dist["backend_util"].assertAxesAreInnerMostDims("argMax", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const result = dist["zeros"](outShape, "int32");
-          const reduceSize = dist["util"].sizeFromShape(reduceShape);
-          const vals = this.readSync(result.dataId);
-          const aVals = this.readSync(x.dataId);
-          for (let i = 0; i < vals.length; ++i) {
-            const offset = i * reduceSize;
-            let max = aVals[offset];
-            let maxIndex = 0;
-            for (let j = 0; j < reduceSize; ++j) {
-              const value = aVals[offset + j];
-              if (value > max) {
-                max = value;
-                maxIndex = j;
-              }
-            }
-            vals[i] = maxIndex;
-          }
-          return result;
-        }
-        cumsum(x, axis, exclusive, reverse) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "cumsum");
-          if (axis !== x.rank - 1) {
-            throw new Error(
-              `backend.cumsum in CPU expects an inner-most axis=${x.rank - 1} ` +
-                `but got axis=${axis}`
-            );
-          }
-          const resultDtype = Object(dist["upcastType"])(x.dtype, "int32");
-          const result = dist["zeros"](x.shape, resultDtype);
-          const vals = this.readSync(result.dataId);
-          const aVals = this.readSync(x.dataId);
-          const finalDim = x.shape[x.rank - 1];
-          const indexAdjuster = reverse ? (i, j) => i + finalDim - j - 1 : (i, j) => i + j;
-          for (let i = 0; i < aVals.length; i += finalDim) {
-            for (let j = 0; j < finalDim; j++) {
-              const idx = indexAdjuster(i, j);
-              if (j === 0) {
-                vals[idx] = exclusive ? 0 : aVals[idx];
-              } else {
-                const prevIdx = indexAdjuster(i, j - 1);
-                vals[idx] = exclusive ? aVals[prevIdx] + vals[prevIdx] : aVals[idx] + vals[prevIdx];
-              }
-            }
-          }
-          return result;
-        }
-        equal(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "equal");
-          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
-            return aVal === bVal ? 1 : 0;
-          });
-        }
-        notEqual(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "notEqual");
-          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
-            return aVal !== bVal ? 1 : 0;
-          });
-        }
-        less(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "less");
-          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
-            return aVal < bVal ? 1 : 0;
-          });
-        }
-        lessEqual(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "lessEqual");
-          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
-            return aVal <= bVal ? 1 : 0;
-          });
-        }
-        greater(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "greater");
-          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
-            return aVal > bVal ? 1 : 0;
-          });
-        }
-        greaterEqual(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "greaterEqual");
-          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
-            return aVal >= bVal ? 1 : 0;
-          });
-        }
-        logicalNot(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "logicalNot");
-          const values = this.readSync(x.dataId);
-          const newValues = new Uint8Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            newValues[i] = values[i] ? 0 : 1;
-          }
-          return this.makeOutput(newValues, x.shape, "bool");
-        }
-        logicalAnd(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "logicalAnd");
-          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
-            return aVal && bVal;
-          });
-        }
-        logicalOr(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "logicalOr");
-          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
-            return aVal || bVal;
-          });
-        }
-        select(condition, a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([condition, a, b], "select");
-          const values = this.readSync(condition.dataId);
-          const aValues = this.readSync(a.dataId);
-          const bValues = this.readSync(b.dataId);
-          const result = dist["zeros"](a.shape, Object(dist["upcastType"])(a.dtype, b.dtype));
-          const newValues = this.readSync(result.dataId);
-          let index = 0;
-          const offset =
-            condition.rank === 0 || condition.rank > 1 || a.rank === 1
-              ? 1
-              : dist["util"].sizeFromShape(a.shape.slice(1));
-          for (let i = 0; i < values.length; i++) {
-            for (let j = 0; j < offset; j++) {
-              if (values[i] === 1) {
-                newValues[index++] = aValues[i];
-              } else {
-                newValues[index++] = bValues[i];
-              }
-            }
-          }
-          return result;
-        }
-        where(condition) {
-          Object(cpu_util["a" /* assertNotComplex */])([condition], "where");
-          const condVals = this.readSync(condition.dataId);
-          return whereImpl(condition.shape, condVals);
-        }
-        topk(x, k, sorted) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "topk");
-          const xVals = this.readSync(x.dataId);
-          return topkImpl(xVals, x.shape, x.dtype, k, sorted);
-        }
-        min(x, axes) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "min");
-          dist["backend_util"].assertAxesAreInnerMostDims("min", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const result = dist["zeros"](outShape, x.dtype);
-          const reduceSize = dist["util"].sizeFromShape(reduceShape);
-          const vals = this.readSync(result.dataId);
-          const aVals = this.readSync(x.dataId);
-          for (let i = 0; i < vals.length; ++i) {
-            const offset = i * reduceSize;
-            let min = aVals[offset];
-            for (let j = 0; j < reduceSize; ++j) {
-              const value = aVals[offset + j];
-              if (value < min) {
-                min = value;
-              }
-            }
-            vals[i] = min;
-          }
-          return result;
-        }
-        minimum(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "minimum");
-          return this.broadcastedBinaryOp(a, b, a.dtype, (aVal, bVal) => Math.min(aVal, bVal));
-        }
-        mod(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "mod");
-          return this.broadcastedBinaryOp(a, b, a.dtype, (aVal, bVal) => {
-            const rem = aVal % bVal;
-            if ((aVal < 0 && bVal < 0) || (aVal >= 0 && bVal >= 0)) {
-              return rem;
-            } else {
-              return (rem + bVal) % bVal;
-            }
-          });
-        }
-        maximum(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "maximum");
-          return this.broadcastedBinaryOp(a, b, a.dtype, (aVal, bVal) => Math.max(aVal, bVal));
-        }
-        all(x, axes) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "all");
-          dist["backend_util"].assertAxesAreInnerMostDims("all", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const result = dist["zeros"](outShape, x.dtype);
-          const reduceSize = dist["util"].sizeFromShape(reduceShape);
-          const vals = this.readSync(result.dataId);
-          const aVals = this.readSync(x.dataId);
-          for (let i = 0; i < vals.length; ++i) {
-            const offset = i * reduceSize;
-            let all = aVals[offset];
-            for (let j = 0; j < reduceSize; ++j) {
-              const value = aVals[offset + j];
-              all = all && value;
-            }
-            vals[i] = all;
-          }
-          return result;
-        }
-        any(x, axes) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "any");
-          dist["backend_util"].assertAxesAreInnerMostDims("any", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const result = dist["zeros"](outShape, x.dtype);
-          const reduceSize = dist["util"].sizeFromShape(reduceShape);
-          const vals = this.readSync(result.dataId);
-          const aVals = this.readSync(x.dataId);
-          for (let i = 0; i < vals.length; ++i) {
-            const offset = i * reduceSize;
-            let anyVal = aVals[offset];
-            for (let j = 0; j < reduceSize; ++j) {
-              const value = aVals[offset + j];
-              anyVal = anyVal || value;
-            }
-            vals[i] = anyVal;
-          }
-          return result;
-        }
-        squaredDifference(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "squaredDifference");
-          return this.broadcastedBinaryOp(a, b, a.dtype, (aVal, bVal) => {
-            const diff = aVal - bVal;
-            return diff * diff;
-          });
-        }
-        ceil(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "ceil");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            newValues[i] = Math.ceil(values[i]);
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        floor(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "floor");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            newValues[i] = Math.floor(values[i]);
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        sign(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "x");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            if (values[i] < 0) {
-              newValues[i] = -1;
-            } else if (values[i] > 0) {
-              newValues[i] = 1;
-            } else {
-              newValues[i] = 0;
-            }
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        isNaN(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "x");
-          const values = this.readSync(x.dataId);
-          const newValues = new Uint8Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            if (Number.isNaN(values[i])) {
-              newValues[i] = 1;
-            }
-          }
-          return this.makeOutput(newValues, x.shape, "bool");
-        }
-        isInf(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "x");
-          const values = this.readSync(x.dataId);
-          const newValues = new Uint8Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            if (Math.abs(values[i]) === Infinity) {
-              newValues[i] = 1;
-            }
-          }
-          return this.makeOutput(newValues, x.shape, "bool");
-        }
-        isFinite(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "x");
-          const values = this.readSync(x.dataId);
-          const newValues = new Uint8Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            if (Number.isFinite(values[i])) {
-              newValues[i] = 1;
-            }
-          }
-          return this.makeOutput(newValues, x.shape, "bool");
-        }
-        round(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "round");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            // The algorithm is based on banker's rounding.
-            const base = Math.floor(values[i]);
-            if (values[i] - base < 0.5) {
-              newValues[i] = Math.floor(values[i]);
-            } else if (values[i] - base > 0.5) {
-              newValues[i] = Math.ceil(values[i]);
-            } else {
-              if (base % 2.0 === 0.0) {
-                newValues[i] = base;
-              } else {
-                newValues[i] = base + 1.0;
-              }
-            }
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        exp(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "exp");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            newValues[i] = Math.exp(values[i]);
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        expm1(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "expm1");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            newValues[i] = Math.expm1(values[i]);
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        log(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "log");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            const value = values[i];
-            newValues[i] = Math.log(value);
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        log1p(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "log1p");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            const value = values[i];
-            newValues[i] = Math.log1p(value);
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        sqrt(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "sqrt");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            const value = values[i];
-            newValues[i] = Math.sqrt(value);
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        rsqrt(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "rsqrt");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            const value = values[i];
-            newValues[i] = 1 / Math.sqrt(value);
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        reciprocal(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "reciprocal");
-          const values = this.readSync(x.dataId);
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            newValues[i] = 1 / values[i];
-          }
-          return this.makeOutput(newValues, x.shape, "float32");
-        }
-        linear(x) {
-          return x;
-        }
-        relu(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "relu");
-          const res = dist["zeros"](x.shape, x.dtype);
-          const resVals = this.readSync(res.dataId);
-          const inVals = this.readSync(x.dataId);
-          for (let i = 0; i < inVals.length; ++i) {
-            resVals[i] = Math.max(0, inVals[i]);
-          }
-          return res;
-        }
-        relu6(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "relu");
-          const res = dist["zeros"](x.shape, x.dtype);
-          const resVals = this.readSync(res.dataId);
-          const inVals = this.readSync(x.dataId);
-          for (let i = 0; i < inVals.length; ++i) {
-            resVals[i] = Math.min(Math.max(0, inVals[i]), 6);
-          }
-          return res;
-        }
-        prelu(x, a) {
-          Object(cpu_util["a" /* assertNotComplex */])([x, a], "prelu");
-          return this.broadcastedBinaryOp(x, a, x.dtype, (xValue, aValue) =>
-            xValue < 0 ? aValue * xValue : xValue
-          );
-        }
-        elu(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "elu");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            const v = values[i];
-            if (v >= 0) {
-              resultValues[i] = v;
-            } else {
-              resultValues[i] = Math.exp(v) - 1;
-            }
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        eluDer(dy, y) {
-          Object(cpu_util["a" /* assertNotComplex */])([dy, y], "eluDer");
-          const resultValues = new Float32Array(y.size);
-          const values = this.readSync(y.dataId);
-          const dyValues = this.readSync(dy.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            const v = values[i];
-            if (v >= 1) {
-              resultValues[i] = dyValues[i];
-            } else {
-              resultValues[i] = dyValues[i] * (v + 1);
-            }
-          }
-          return this.makeOutput(resultValues, y.shape, "float32");
-        }
-        selu(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "selu");
-          // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
-          // see: https://arxiv.org/abs/1706.02515
-          const scaleAlpha = dist["backend_util"].SELU_SCALEALPHA;
-          const scale = dist["backend_util"].SELU_SCALE;
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            const v = values[i];
-            if (v >= 0) {
-              resultValues[i] = scale * v;
-            } else {
-              resultValues[i] = scaleAlpha * (Math.exp(v) - 1);
-            }
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        clip(x, min, max) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "clip");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            const v = values[i];
-            resultValues[i] = v > max ? max : v < min ? min : v;
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        abs(x) {
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.abs(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        complexAbs(x) {
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < x.size; ++i) {
-            const real = values[i * 2];
-            const imag = values[i * 2 + 1];
-            resultValues[i] = Math.hypot(real, imag);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        int(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "int");
-          const resultValues = new Int32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = values[i];
-          }
-          return this.makeOutput(resultValues, x.shape, "int32");
-        }
-        sigmoid(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "sigmoid");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = 1 / (1 + Math.exp(-values[i]));
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        softplus(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "softplus");
-          // mirrors the implementation of tf.nn.softplus: https://goo.gl/vkcvwX
-          // epsilon is the difference between 1.0 and the next representable float.
-          // For a single precision 32 bit float this should be 2^-23, see:
-          // https://math.byu.edu/~schow/work/IEEEFloatingPoint.htm
-          const epsilon = 1.1920928955078125e-7;
-          const threshold = Math.log(epsilon) + 2.0;
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            // Value above which exp(x) may overflow, but softplus(x) == x
-            // is within machine epsilon.
-            const tooLarge = values[i] > -threshold;
-            // Value below which exp(x) may underflow, but softplus(x) == exp(x)
-            // is within machine epsilon.
-            const tooSmall = values[i] < threshold;
-            const expX = Math.exp(values[i]);
-            let result;
-            if (tooSmall) {
-              result = expX;
-            } else if (tooLarge) {
-              result = values[i];
-            } else {
-              result = Math.log(1.0 + expX);
-            }
-            resultValues[i] = result;
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        sin(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "sin");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.sin(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        cos(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "cos");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.cos(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        tan(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "tan");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.tan(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        asin(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "asin");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.asin(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        acos(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "acos");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.acos(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        atan(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "atan");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.atan(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        atan2(a, b) {
-          Object(cpu_util["a" /* assertNotComplex */])([a, b], "atan2");
-          return this.broadcastedBinaryOp(a, b, a.dtype, (aValue, bValue) =>
-            Math.atan2(aValue, bValue)
-          );
-        }
-        sinh(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "sinh");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.sinh(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        cosh(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "cosh");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.cosh(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        tanh(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "tanh");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = dist["util"].tanh(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        asinh(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "asinh");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.asinh(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        acosh(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "acosh");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.acosh(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        atanh(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "atanh");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            resultValues[i] = Math.atanh(values[i]);
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        erf(x) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "erf");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          const p = dist["backend_util"].ERF_P;
-          const a1 = dist["backend_util"].ERF_A1;
-          const a2 = dist["backend_util"].ERF_A2;
-          const a3 = dist["backend_util"].ERF_A3;
-          const a4 = dist["backend_util"].ERF_A4;
-          const a5 = dist["backend_util"].ERF_A5;
-          for (let i = 0; i < values.length; ++i) {
-            const sign = Math.sign(values[i]);
-            const v = Math.abs(values[i]);
-            const t = 1.0 / (1.0 + p * v);
-            resultValues[i] =
-              sign * (1.0 - ((((a5 * t + a4) * t + a3) * t + a2) * t + a1) * t * Math.exp(-v * v));
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        step(x, alpha = 0) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "step");
-          const resultValues = new Float32Array(x.size);
-          const values = this.readSync(x.dataId);
-          for (let i = 0; i < values.length; ++i) {
-            const value = values[i];
-            if (isNaN(value)) {
-              resultValues[i] = NaN;
-            } else {
-              resultValues[i] = value > 0 ? 1 : alpha;
-            }
-          }
-          return this.makeOutput(resultValues, x.shape, "float32");
-        }
-        fusedConv2d({ input, filter, convInfo, bias, activation, preluActivationWeights }) {
-          let result = this.conv2d(input, filter, convInfo);
-          if (bias) {
-            result = this.add(result, bias);
-          }
-          if (activation) {
-            result = mapActivation(this, result, activation, preluActivationWeights);
-          }
-          return result;
-        }
-        conv2d(x, filter, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([x, filter], "conv2d");
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const padLeft = convInfo.padInfo.left;
-          const padTop = convInfo.padInfo.top;
-          const isChannelsLast = convInfo.dataFormat === "channelsLast";
-          const y = dist["buffer"](convInfo.outShape, x.dtype);
-          const xBatchStride = x.strides[0];
-          const xRowStride = isChannelsLast ? x.strides[1] : x.strides[2];
-          const xColStride = isChannelsLast ? x.strides[2] : 1;
-          const xChannelStride = isChannelsLast ? 1 : x.strides[1];
-          const yBatchStride = y.strides[0];
-          const yRowStride = isChannelsLast ? y.strides[1] : y.strides[2];
-          const yColStride = isChannelsLast ? y.strides[2] : 1;
-          const yChannelStride = isChannelsLast ? 1 : y.strides[1];
-          const xVals = this.readSync(x.dataId);
-          const wVals = this.readSync(filter.dataId);
-          const yVals = y.values;
-          for (let b = 0; b < convInfo.batchSize; ++b) {
-            const xOffset1 = b * xBatchStride;
-            const yOffset1 = b * yBatchStride;
-            for (let yR = 0; yR < convInfo.outHeight; ++yR) {
-              const yOffset2 = yOffset1 + yR * yRowStride;
-              const xRCorner = yR * convInfo.strideHeight - padTop;
-              for (let wR = 0; wR < filterHeight; wR++) {
-                const xR = xRCorner + wR * dilationHeight;
-                if (xR < 0 || xR >= convInfo.inHeight) {
-                  continue;
-                }
-                const wOffset1 = wR * filter.strides[0];
-                const xOffset2 = xOffset1 + xR * xRowStride;
-                for (let yC = 0; yC < convInfo.outWidth; ++yC) {
-                  const yOffset3 = yOffset2 + yC * yColStride;
-                  const xCCorner = yC * convInfo.strideWidth - padLeft;
-                  for (let wC = 0; wC < filterWidth; wC++) {
-                    const xC = xCCorner + wC * dilationWidth;
-                    if (xC < 0 || xC >= convInfo.inWidth) {
-                      continue;
-                    }
-                    const wOffset2 = wOffset1 + wC * filter.strides[1];
-                    const xOffset3 = xOffset2 + xC * xColStride;
-                    let wOffset3 = wOffset2;
-                    for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
-                      const xVal = xVals[xOffset3 + d1 * xChannelStride];
-                      for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
-                        yVals[yOffset3 + d2 * yChannelStride] += xVal * wVals[wOffset3 + d2];
-                      }
-                      wOffset3 += convInfo.outChannels;
-                    }
-                  }
-                }
-              }
-            }
-          }
-          return y.toTensor();
-        }
-        conv3d(x, filter, convInfo) {
-          const filterDepth = convInfo.filterDepth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const padFront = convInfo.padInfo.front;
-          const padLeft = convInfo.padInfo.left;
-          const padTop = convInfo.padInfo.top;
-          const y = dist["buffer"](convInfo.outShape, x.dtype);
-          const xVals = this.readSync(x.dataId);
-          const wVals = this.readSync(filter.dataId);
-          const yVals = y.values;
-          for (let b = 0; b < convInfo.batchSize; ++b) {
-            const xOffset1 = b * x.strides[0];
-            const yOffset1 = b * y.strides[0];
-            for (let yF = 0; yF < convInfo.outDepth; ++yF) {
-              const yOffset2 = yOffset1 + yF * y.strides[1];
-              const xFCorner = yF * convInfo.strideDepth - padFront;
-              for (let wF = 0; wF < filterDepth; wF++) {
-                const xF = xFCorner + wF * dilationDepth;
-                if (xF < 0 || xF >= convInfo.inDepth) {
-                  continue;
-                }
-                const wOffset1 = wF * filter.strides[0];
-                const xOffset2 = xOffset1 + xF * x.strides[1];
-                for (let yR = 0; yR < convInfo.outHeight; ++yR) {
-                  const yOffset3 = yOffset2 + yR * y.strides[2];
-                  const xRCorner = yR * convInfo.strideHeight - padTop;
-                  for (let wR = 0; wR < filterHeight; wR++) {
-                    const xR = xRCorner + wR * dilationHeight;
-                    if (xR < 0 || xR >= convInfo.inHeight) {
-                      continue;
-                    }
-                    const wOffset2 = wOffset1 + wR * filter.strides[1];
-                    const xOffset3 = xOffset2 + xR * x.strides[2];
-                    for (let yC = 0; yC < convInfo.outWidth; ++yC) {
-                      const yOffset4 = yOffset3 + yC * convInfo.outChannels;
-                      const xCCorner = yC * convInfo.strideWidth - padLeft;
-                      for (let wC = 0; wC < filterWidth; wC++) {
-                        const xC = xCCorner + wC * dilationWidth;
-                        if (xC < 0 || xC >= convInfo.inWidth) {
-                          continue;
-                        }
-                        const wOffset3 = wOffset2 + wC * filter.strides[2];
-                        const xOffset4 = xOffset3 + xC * convInfo.inChannels;
-                        let wOffset4 = wOffset3;
-                        for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
-                          const xVal = xVals[xOffset4 + d1];
-                          for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
-                            yVals[yOffset4 + d2] += xVal * wVals[wOffset4 + d2];
-                          }
-                          wOffset4 += convInfo.outChannels;
-                        }
-                      }
-                    }
-                  }
-                }
-              }
-            }
-          }
-          return y.toTensor();
-        }
-        conv2dDerInput(dy, filter, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([dy, filter], "conv2dDerInput");
-          const dx = dist["buffer"](convInfo.inShape, "float32");
-          const dxValues = dx.values;
-          const dyValues = this.readSync(dy.dataId);
-          const fltValues = this.readSync(filter.dataId);
-          const [fltS0, fltS1, fltS2] = filter.strides;
-          const {
-            batchSize,
-            filterHeight,
-            filterWidth,
-            inChannels,
-            inHeight,
-            inWidth,
-            outChannels,
-            outHeight,
-            outWidth,
-            strideHeight,
-            strideWidth,
-            dataFormat,
-          } = convInfo;
-          const topPad = filterHeight - 1 - convInfo.padInfo.top;
-          const leftPad = filterWidth - 1 - convInfo.padInfo.left;
-          const isChannelsLast = dataFormat === "channelsLast";
-          const xBatchStride = dx.strides[0];
-          const xRowStride = isChannelsLast ? dx.strides[1] : dx.strides[2];
-          const xColStride = isChannelsLast ? dx.strides[2] : 1;
-          const xChannelStride = isChannelsLast ? 1 : dx.strides[1];
-          const yBatchStride = dy.strides[0];
-          const yRowStride = isChannelsLast ? dy.strides[1] : dy.strides[2];
-          const yColStride = isChannelsLast ? dy.strides[2] : 1;
-          const yChannelStride = isChannelsLast ? 1 : dy.strides[1];
-          for (let b = 0; b < batchSize; ++b) {
-            for (let d1 = 0; d1 < inChannels; ++d1) {
-              for (let xR = 0; xR < inHeight; ++xR) {
-                const xRCorner = xR - topPad;
-                const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));
-                const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);
-                for (let xC = 0; xC < inWidth; ++xC) {
-                  const xCCorner = xC - leftPad;
-                  const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));
-                  const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);
-                  let dotProd = 0;
-                  for (let yR = xRMin; yR < yRMax; ++yR) {
-                    const wR = yR * strideHeight - xRCorner;
-                    for (let yC = xCMin; yC < yCMax; ++yC) {
-                      const wC = yC * strideWidth - xCCorner;
-                      const dyOffset = yBatchStride * b + yRowStride * yR + yColStride * yC;
-                      const fltOffset =
-                        fltS0 * (filterHeight - 1 - wR) +
-                        fltS1 * (filterWidth - 1 - wC) +
-                        fltS2 * d1;
-                      for (let d2 = 0; d2 < outChannels; ++d2) {
-                        const pixel = dyValues[dyOffset + yChannelStride * d2];
-                        const weight = fltValues[fltOffset + d2];
-                        dotProd += pixel * weight;
-                      }
-                    }
-                  }
-                  const dxOffset =
-                    xBatchStride * b + xRowStride * xR + xColStride * xC + xChannelStride * d1;
-                  dxValues[dxOffset] = dotProd;
-                }
-              }
-            }
-          }
-          return dx.toTensor();
-        }
-        conv3dDerInput(dy, filter, convInfo) {
-          const dx = dist["buffer"](convInfo.inShape, "float32");
-          const dxValues = dx.values;
-          const [dxS0, dxS1, dxS2, dxS3] = dx.strides;
-          const dyValues = this.readSync(dy.dataId);
-          const [dyS0, dyS1, dyS2, dyS3] = dy.strides;
-          const fltValues = this.readSync(filter.dataId);
-          const [fltS0, fltS1, fltS2, fltS3] = filter.strides;
-          const {
-            batchSize,
-            filterDepth,
-            filterHeight,
-            filterWidth,
-            inChannels,
-            inDepth,
-            inHeight,
-            inWidth,
-            outChannels,
-            outDepth,
-            outHeight,
-            outWidth,
-            strideDepth,
-            strideHeight,
-            strideWidth,
-          } = convInfo;
-          const frontPad = filterDepth - 1 - convInfo.padInfo.front;
-          const topPad = filterHeight - 1 - convInfo.padInfo.top;
-          const leftPad = filterWidth - 1 - convInfo.padInfo.left;
-          for (let b = 0; b < batchSize; ++b) {
-            for (let d1 = 0; d1 < inChannels; ++d1) {
-              // Frames of depth
-              for (let xF = 0; xF < inDepth; ++xF) {
-                const xFCorner = xF - frontPad;
-                const xFMin = Math.max(0, Math.ceil(xFCorner / strideDepth));
-                const yFMax = Math.min(outDepth, (filterDepth + xFCorner) / strideDepth);
-                // Rows as per standard 2d matrix notation
-                for (let xR = 0; xR < inHeight; ++xR) {
-                  const xRCorner = xR - topPad;
-                  const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));
-                  const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);
-                  // Columns as per standard 2d matrix notation
-                  for (let xC = 0; xC < inWidth; ++xC) {
-                    const xCCorner = xC - leftPad;
-                    const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));
-                    const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);
-                    let dotProd = 0;
-                    for (let yF = xFMin; yF < yFMax; ++yF) {
-                      const wF = yF * strideDepth - xFCorner;
-                      for (let yR = xRMin; yR < yRMax; ++yR) {
-                        const wR = yR * strideHeight - xRCorner;
-                        for (let yC = xCMin; yC < yCMax; ++yC) {
-                          const wC = yC * strideWidth - xCCorner;
-                          const dyOffset = dyS0 * b + dyS1 * yF + dyS2 * yR + dyS3 * yC;
-                          const fltOffset =
-                            fltS0 * (filterDepth - 1 - wF) +
-                            fltS1 * (filterHeight - 1 - wR) +
-                            fltS2 * (filterWidth - 1 - wC) +
-                            fltS3 * d1;
-                          for (let d2 = 0; d2 < outChannels; ++d2) {
-                            const pixel = dyValues[dyOffset + d2];
-                            const weight = fltValues[fltOffset + d2];
-                            dotProd += pixel * weight;
-                          }
-                        }
-                      }
-                    }
-                    dxValues[dxS0 * b + dxS1 * xF + dxS2 * xR + dxS3 * xC + d1] = dotProd;
-                  }
-                }
-              }
-            }
-          }
-          return dx.toTensor();
-        }
-        conv2dDerFilter(x, dy, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([x, dy], "conv2dDerFilter");
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const isChannelsLast = convInfo.dataFormat === "channelsLast";
-          const dW = dist["buffer"](convInfo.filterShape, "float32");
-          const leftPad = convInfo.padInfo.left;
-          const topPad = convInfo.padInfo.top;
-          const xBuf = this.bufferSync(x);
-          const dyBuf = this.bufferSync(dy);
-          for (let wR = 0; wR < filterHeight; ++wR) {
-            const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));
-            const yRMax = Math.min(
-              convInfo.outHeight,
-              (convInfo.inHeight + topPad - wR) / strideHeight
-            );
-            for (let wC = 0; wC < filterWidth; ++wC) {
-              const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));
-              const yCMax = Math.min(
-                convInfo.outWidth,
-                (convInfo.inWidth + leftPad - wC) / strideWidth
-              );
-              for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
-                for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
-                  // Need to convolve.
-                  let dotProd = 0;
-                  for (let b = 0; b < convInfo.batchSize; ++b) {
-                    for (let yR = yRMin; yR < yRMax; ++yR) {
-                      const xR = wR + yR * strideHeight - topPad;
-                      for (let yC = yCMin; yC < yCMax; ++yC) {
-                        const xC = wC + yC * strideWidth - leftPad;
-                        if (isChannelsLast) {
-                          dotProd += xBuf.get(b, xR, xC, d1) * dyBuf.get(b, yR, yC, d2);
-                        } else {
-                          dotProd += xBuf.get(b, d1, xR, xC) * dyBuf.get(b, d2, yR, yC);
-                        }
-                      }
-                    }
-                  }
-                  dW.set(dotProd, wR, wC, d1, d2);
-                }
-              }
-            }
-          }
-          return dW.toTensor();
-        }
-        conv3dDerFilter(x, dy, convInfo) {
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const filterDepth = convInfo.filterDepth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const dw = dist["buffer"](convInfo.filterShape, "float32");
-          const dwValues = dw.values;
-          const [dwS0, dwS1, dwS2, dwS3] = dw.strides;
-          const dyValues = this.readSync(dy.dataId);
-          const [dyS0, dyS1, dyS2, dyS3] = dy.strides;
-          const xValues = this.readSync(x.dataId);
-          const [xS0, xS1, xS2, xS3] = x.strides;
-          const frontPad = convInfo.padInfo.front;
-          const leftPad = convInfo.padInfo.left;
-          const topPad = convInfo.padInfo.top;
-          for (let wF = 0; wF < filterDepth; ++wF) {
-            const yFMin = Math.max(0, Math.ceil((frontPad - wF) / strideDepth));
-            const yFMax = Math.min(
-              convInfo.outDepth,
-              (convInfo.inDepth + frontPad - wF) / strideDepth
-            );
-            const wOffset1 = wF * dwS0;
-            for (let wR = 0; wR < filterHeight; ++wR) {
-              const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));
-              const yRMax = Math.min(
-                convInfo.outHeight,
-                (convInfo.inHeight + topPad - wR) / strideHeight
-              );
-              const wOffset2 = wR * dwS1 + wOffset1;
-              for (let wC = 0; wC < filterWidth; ++wC) {
-                const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));
-                const yCMax = Math.min(
-                  convInfo.outWidth,
-                  (convInfo.inWidth + leftPad - wC) / strideWidth
-                );
-                const wOffset3 = wC * dwS2 + wOffset2;
-                for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
-                  const wOffset4 = d1 * dwS3 + wOffset3;
-                  for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
-                    let dotProd = 0;
-                    for (let b = 0; b < convInfo.batchSize; ++b) {
-                      const xOffset1 = b * xS0;
-                      const yOffset1 = b * dyS0;
-                      for (let yF = yFMin; yF < yFMax; ++yF) {
-                        const xF = wF + yF * strideDepth - frontPad;
-                        const xOffset2 = xF * xS1 + xOffset1;
-                        const yOffset2 = yF * dyS1 + yOffset1;
-                        for (let yR = yRMin; yR < yRMax; ++yR) {
-                          const xR = wR + yR * strideHeight - topPad;
-                          const xOffset3 = xR * xS2 + xOffset2;
-                          const yOffset3 = yR * dyS2 + yOffset2;
-                          for (let yC = yCMin; yC < yCMax; ++yC) {
-                            const xC = wC + yC * strideWidth - leftPad;
-                            const xOffset4 = xC * xS3 + xOffset3;
-                            const yOffset4 = yC * dyS3 + yOffset3;
-                            dotProd += xValues[xOffset4 + d1] * dyValues[yOffset4 + d2];
-                          }
-                        }
-                      }
-                    }
-                    dwValues[wOffset4 + d2] = dotProd;
-                  }
-                }
-              }
-            }
-          }
-          return dw.toTensor();
-        }
-        fusedDepthwiseConv2D({
-          input,
-          filter,
-          convInfo,
-          bias,
-          activation,
-          preluActivationWeights,
-        }) {
-          let result = this.depthwiseConv2D(input, filter, convInfo);
-          if (bias) {
-            result = this.add(result, bias);
-          }
-          if (activation) {
-            result = mapActivation(this, result, activation, preluActivationWeights);
-          }
-          return result;
-        }
-        depthwiseConv2D(x, filter, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([x, filter], "depthwiseConv2D");
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const padLeft = convInfo.padInfo.left;
-          const padTop = convInfo.padInfo.top;
-          const chMul = convInfo.outChannels / convInfo.inChannels;
-          const y = dist["buffer"](convInfo.outShape, x.dtype);
-          const xVals = this.readSync(x.dataId);
-          const wVals = this.readSync(filter.dataId);
-          const yVals = y.values;
-          for (let b = 0; b < convInfo.batchSize; ++b) {
-            const xOffset1 = b * x.strides[0];
-            const yOffset1 = b * y.strides[0];
-            for (let yR = 0; yR < convInfo.outHeight; ++yR) {
-              const yOffset2 = yOffset1 + yR * y.strides[1];
-              const xRCorner = yR * convInfo.strideHeight - padLeft;
-              for (let wR = 0; wR < filterHeight; ++wR) {
-                const xR = xRCorner + wR * dilationHeight;
-                if (xR < 0 || xR >= convInfo.inHeight) {
-                  continue;
-                }
-                const wOffset1 = wR * filter.strides[0];
-                const xOffset2 = xOffset1 + xR * x.strides[1];
-                for (let yC = 0; yC < convInfo.outWidth; ++yC) {
-                  const yOffset3 = yOffset2 + yC * y.strides[2];
-                  const xCCorner = yC * convInfo.strideWidth - padTop;
-                  for (let wC = 0; wC < filterWidth; ++wC) {
-                    const xC = xCCorner + wC * dilationWidth;
-                    if (xC < 0 || xC >= convInfo.inWidth) {
-                      continue;
-                    }
-                    const wOffset2 = wOffset1 + wC * filter.strides[1];
-                    const xOffset3 = xOffset2 + xC * convInfo.inChannels;
-                    let yOffset4 = yOffset3;
-                    let wOffset3 = wOffset2;
-                    for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
-                      const xVal = xVals[xOffset3 + d1];
-                      for (let q = 0; q < chMul; ++q) {
-                        yVals[yOffset4 + q] += xVal * wVals[wOffset3 + q];
-                      }
-                      yOffset4 += chMul;
-                      wOffset3 += chMul;
-                    }
-                  }
-                }
-              }
-            }
-          }
-          return y.toTensor();
-        }
-        depthwiseConv2DDerInput(dy, filter, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([dy, filter], "depthwiseConv2DDerInput");
-          const dx = dist["buffer"](convInfo.inShape, "float32");
-          const dxValues = dx.values;
-          const [dxS0, dxS1, dxS2] = dx.strides;
-          const dyValues = this.readSync(dy.dataId);
-          const [dyS0, dyS1, dyS2] = dy.strides;
-          const fltValues = this.readSync(filter.dataId);
-          const [fltS0, fltS1, fltS2] = filter.strides;
-          const {
-            batchSize,
-            filterHeight,
-            filterWidth,
-            inChannels,
-            inHeight,
-            inWidth,
-            outChannels,
-            outHeight,
-            outWidth,
-            strideHeight,
-            strideWidth,
-          } = convInfo;
-          const topPad = filterHeight - 1 - convInfo.padInfo.top;
-          const leftPad = filterWidth - 1 - convInfo.padInfo.left;
-          const chMul = outChannels / inChannels;
-          for (let b = 0; b < batchSize; ++b) {
-            for (let d1 = 0; d1 < inChannels; ++d1) {
-              for (let xR = 0; xR < inHeight; ++xR) {
-                const xRCorner = xR - topPad;
-                const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));
-                const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);
-                for (let xC = 0; xC < inWidth; ++xC) {
-                  const xCCorner = xC - leftPad;
-                  const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));
-                  const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);
-                  let dotProd = 0;
-                  for (let yR = xRMin; yR < yRMax; ++yR) {
-                    const wR = yR * strideHeight - xRCorner;
-                    for (let yC = xCMin; yC < yCMax; ++yC) {
-                      const wC = yC * strideWidth - xCCorner;
-                      const dyOffset = dyS0 * b + dyS1 * yR + dyS2 * yC;
-                      const fltOffset =
-                        fltS0 * (filterHeight - 1 - wR) +
-                        fltS1 * (filterWidth - 1 - wC) +
-                        fltS2 * d1;
-                      for (let dm = 0; dm < chMul; ++dm) {
-                        const d2 = d1 * chMul + dm;
-                        const pixel = dyValues[dyOffset + d2];
-                        const weight = fltValues[fltOffset + dm];
-                        dotProd += pixel * weight;
-                      }
-                    }
-                  }
-                  dxValues[dxS0 * b + dxS1 * xR + dxS2 * xC + d1] = dotProd;
-                }
-              }
-            }
-          }
-          return dx.toTensor();
-        }
-        depthwiseConv2DDerFilter(x, dy, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([x, dy], "depthwiseConv2DDerFilter");
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const dW = dist["buffer"](convInfo.filterShape, "float32");
-          const leftPad = convInfo.padInfo.left;
-          const topPad = convInfo.padInfo.top;
-          const chMul = convInfo.outChannels / convInfo.inChannels;
-          const xBuf = this.bufferSync(x);
-          const dyBuf = this.bufferSync(dy);
-          for (let wR = 0; wR < filterHeight; ++wR) {
-            const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));
-            const yRMax = Math.min(
-              convInfo.outHeight,
-              (convInfo.inHeight + topPad - wR) / strideHeight
-            );
-            for (let wC = 0; wC < filterWidth; ++wC) {
-              const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));
-              const yCMax = Math.min(
-                convInfo.outWidth,
-                (convInfo.inWidth + leftPad - wC) / strideWidth
-              );
-              for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
-                const d1 = Math.trunc(d2 / chMul);
-                const dm = d2 % chMul;
-                let dotProd = 0;
-                for (let b = 0; b < convInfo.batchSize; ++b) {
-                  for (let yR = yRMin; yR < yRMax; ++yR) {
-                    const xR = wR + yR * strideHeight - topPad;
-                    for (let yC = yCMin; yC < yCMax; ++yC) {
-                      const xC = wC + yC * strideWidth - leftPad;
-                      dotProd += xBuf.get(b, xR, xC, d1) * dyBuf.get(b, yR, yC, d2);
-                    }
-                  }
-                }
-                dW.set(dotProd, wR, wC, d1, dm);
-              }
-            }
-          }
-          return dW.toTensor();
-        }
-        tile(x, reps) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "tile");
-          return tile(this.bufferSync(x), reps);
-        }
-        pad(x, paddings, constantValue) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "pad");
-          const outShape = paddings.map(
-            (p, i) => p[0] /* beforePad */ + x.shape[i] + p[1] /* afterPad */
-          );
-          const start = paddings.map((p) => p[0]);
-          const xBuffer = this.bufferSync(x);
-          const buffer = dist["buffer"](outShape, x.dtype);
-          if (constantValue !== 0) {
-            buffer.values.fill(constantValue);
-          }
-          for (let i = 0; i < x.size; i++) {
-            const coords = xBuffer.indexToLoc(i);
-            const outCoords = coords.map((c, i) => c + start[i]);
-            buffer.set(xBuffer.get(...coords), ...outCoords);
-          }
-          return buffer.toTensor();
-        }
-        gather(x, indices, axis) {
-          Object(cpu_util["a" /* assertNotComplex */])([x, indices], "gather");
-          const newShape = x.shape.slice();
-          const indicesValues = this.readSync(indices.dataId);
-          newShape[axis] = indicesValues.length;
-          const result = dist["buffer"](newShape, x.dtype);
-          const xBuf = this.bufferSync(x);
-          for (let i = 0; i < result.size; ++i) {
-            const newLoc = result.indexToLoc(i);
-            const originalLoc = newLoc.slice();
-            originalLoc[axis] = indicesValues[newLoc[axis]];
-            const originalIndex = xBuf.locToIndex(originalLoc);
-            result.values[i] = xBuf.values[originalIndex];
-          }
-          return result.toTensor();
-        }
-        batchToSpaceND(x, blockShape, crops) {
-          Object(cpu_util["a" /* assertNotComplex */])([x], "batchToSpaceND");
-          const prod = blockShape.reduce((a, b) => a * b);
-          const reshaped = dist["backend_util"].getReshaped(x.shape, blockShape, prod);
-          const permuted = dist["backend_util"].getPermuted(reshaped.length, blockShape.length);
-          const reshapedPermuted = dist["backend_util"].getReshapedPermuted(
-            x.shape,
-            blockShape,
-            prod
-          );
-          const sliceBeginCoords = dist["backend_util"].getSliceBeginCoords(
-            crops,
-            blockShape.length
-          );
-          const sliceSize = dist["backend_util"].getSliceSize(
-            reshapedPermuted,
-            crops,
-            blockShape.length
-          );
-          return dist["transpose"](x.reshape(reshaped), permuted)
-            .reshape(reshapedPermuted)
-            .slice(sliceBeginCoords, sliceSize);
-        }
-        spaceToBatchND(x, blockShape, paddings) {
-          Object(cpu_util["a" /* assertNotComplex */])([x], "spaceToBatchND");
-          const prod = blockShape.reduce((a, b) => a * b);
-          const completePaddings = [[0, 0]];
-          completePaddings.push(...paddings);
-          for (let i = 1 + blockShape.length; i < x.shape.length; ++i) {
-            completePaddings.push([0, 0]);
-          }
-          const paddedX = x.pad(completePaddings);
-          const reshapedPaddedShape = dist["backend_util"].getReshaped(
-            paddedX.shape,
-            blockShape,
-            prod,
-            false
-          );
-          const permutedReshapedPaddedPermutation = dist["backend_util"].getPermuted(
-            reshapedPaddedShape.length,
-            blockShape.length,
-            false
-          );
-          const flattenShape = dist["backend_util"].getReshapedPermuted(
-            paddedX.shape,
-            blockShape,
-            prod,
-            false
-          );
-          return dist["transpose"](
-            paddedX.reshape(reshapedPaddedShape),
-            permutedReshapedPaddedPermutation
-          ).reshape(flattenShape);
-        }
-        maxPool(x, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "maxPool");
-          const xValues = this.readSync(x.dataId);
-          return Object(pool_utils["b" /* pool */])(
-            xValues,
-            x.shape,
-            x.dtype,
-            x.strides,
-            convInfo,
-            "max"
-          ).toTensor();
-        }
-        maxPoolBackprop(dy, x, y, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([x, y], "maxPoolBackprop");
-          const xValues = this.readSync(x.dataId);
-          const maxPosBuf = Object(dist["buffer"])(
-            convInfo.outShape,
-            x.dtype,
-            Object(pool_utils["a" /* maxPoolPositions */])(xValues, x.shape, x.dtype, convInfo)
-              .values
-          );
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
-          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
-          const dx = dist["buffer"](x.shape, "float32");
-          const dyBuf = this.bufferSync(dy);
-          for (let b = 0; b < convInfo.batchSize; ++b) {
-            for (let d = 0; d < convInfo.inChannels; ++d) {
-              for (let dxR = 0; dxR < convInfo.inHeight; ++dxR) {
-                for (let dxC = 0; dxC < convInfo.inWidth; ++dxC) {
-                  // Shader code begins.
-                  const dyRCorner = dxR - padTop;
-                  const dyCCorner = dxC - padLeft;
-                  let dotProd = 0;
-                  for (let wR = 0; wR < effectiveFilterHeight; wR += dilationHeight) {
-                    const dyR = (dyRCorner + wR) / strideHeight;
-                    if (dyR < 0 || dyR >= convInfo.outHeight || Math.floor(dyR) !== dyR) {
-                      continue;
-                    }
-                    for (let wC = 0; wC < effectiveFilterWidth; wC += dilationWidth) {
-                      const dyC = (dyCCorner + wC) / strideWidth;
-                      if (dyC < 0 || dyC >= convInfo.outWidth || Math.floor(dyC) !== dyC) {
-                        continue;
-                      }
-                      const maxPos =
-                        effectiveFilterHeight * effectiveFilterWidth -
-                        1 -
-                        maxPosBuf.get(b, dyR, dyC, d);
-                      const curPos = wR * effectiveFilterWidth + wC;
-                      const mask = maxPos === curPos ? 1 : 0;
-                      if (mask === 0) {
-                        continue;
-                      }
-                      const pixel = dyBuf.get(b, dyR, dyC, d);
-                      dotProd += pixel * mask;
-                    }
-                  }
-                  dx.set(dotProd, b, dxR, dxC, d);
-                }
-              }
-            }
-          }
-          return dx.toTensor();
-        }
-        avgPoolBackprop(dy, x, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([dy, x], "avgPoolBackprop");
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
-          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
-          const dx = dist["buffer"](x.shape, "float32");
-          const avgMultiplier = 1 / (filterHeight * filterWidth);
-          const dyBuf = this.bufferSync(dy);
-          for (let b = 0; b < convInfo.batchSize; ++b) {
-            for (let d = 0; d < convInfo.inChannels; ++d) {
-              for (let dxR = 0; dxR < convInfo.inHeight; ++dxR) {
-                for (let dxC = 0; dxC < convInfo.inWidth; ++dxC) {
-                  // Shader code begins.
-                  const dyRCorner = dxR - padTop;
-                  const dyCCorner = dxC - padLeft;
-                  let dotProd = 0;
-                  for (let wR = 0; wR < effectiveFilterHeight; wR += dilationHeight) {
-                    const dyR = (dyRCorner + wR) / strideHeight;
-                    if (dyR < 0 || dyR >= convInfo.outHeight || Math.floor(dyR) !== dyR) {
-                      continue;
-                    }
-                    for (let wC = 0; wC < effectiveFilterWidth; wC += dilationWidth) {
-                      const dyC = (dyCCorner + wC) / strideWidth;
-                      if (dyC < 0 || dyC >= convInfo.outWidth || Math.floor(dyC) !== dyC) {
-                        continue;
-                      }
-                      const pixel = dyBuf.get(b, dyR, dyC, d);
-                      dotProd += pixel;
-                    }
-                  }
-                  dx.set(dotProd * avgMultiplier, b, dxR, dxC, d);
-                }
-              }
-            }
-          }
-          return dx.toTensor();
-        }
-        pool3d(x, convInfo, poolType) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "pool3d");
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padFront = convInfo.padInfo.front;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          const initialValue =
-            poolType === "max" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY;
-          const xValues = this.readSync(x.dataId);
-          const output = dist["buffer"](convInfo.outShape, x.dtype);
-          const outputVals = output.values;
-          const outputBatchStrides =
-            convInfo.outShape[1] *
-            convInfo.outShape[2] *
-            convInfo.outShape[3] *
-            convInfo.outShape[4];
-          const outputDepthStrides =
-            convInfo.outShape[2] * convInfo.outShape[3] * convInfo.outShape[4];
-          const outputRowStrides = convInfo.outShape[3] * convInfo.outShape[4];
-          const outputColStrides = convInfo.outShape[4];
-          for (let batch = 0; batch < convInfo.batchSize; ++batch) {
-            const outputBatchOffset = batch * outputBatchStrides;
-            const inputBatchOffset = batch * x.strides[0];
-            for (let channel = 0; channel < convInfo.inChannels; ++channel) {
-              for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {
-                const xDepthCorner = yDepth * strideDepth - padFront;
-                let xDepthMin = xDepthCorner;
-                while (xDepthMin < 0) {
-                  xDepthMin += dilationDepth;
-                }
-                const xDepthMax = Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);
-                const outputDepthOffset = outputBatchOffset + yDepth * outputDepthStrides;
-                for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {
-                  const xRowCorner = yRow * strideHeight - padTop;
-                  let xRowMin = xRowCorner;
-                  while (xRowMin < 0) {
-                    xRowMin += dilationHeight;
-                  }
-                  const xRowMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);
-                  const outputRowOffset = outputDepthOffset + yRow * outputRowStrides;
-                  for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {
-                    const xColCorner = yCol * strideWidth - padLeft;
-                    let xColMin = xColCorner;
-                    while (xColMin < 0) {
-                      xColMin += dilationWidth;
-                    }
-                    const xColMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);
-                    // Shader code begins
-                    const outputColOffset = outputRowOffset + yCol * outputColStrides;
-                    let minMaxValue = initialValue;
-                    let avgValue = 0;
-                    let count = 0;
-                    for (let xDepth = xDepthMin; xDepth < xDepthMax; xDepth += dilationDepth) {
-                      const xDepthOffset = inputBatchOffset + xDepth * x.strides[1];
-                      for (let xRow = xRowMin; xRow < xRowMax; xRow += dilationHeight) {
-                        const xRowOffset = xDepthOffset + xRow * x.strides[2];
-                        for (let xCol = xColMin; xCol < xColMax; xCol += dilationWidth) {
-                          const xColOffset = xRowOffset + xCol * x.strides[3];
-                          const pixel = xValues[xColOffset + channel];
-                          if (poolType === "max" && pixel > minMaxValue) {
-                            minMaxValue = pixel;
-                          } else if (poolType === "avg") {
-                            avgValue += pixel;
-                            count++;
-                          }
-                          if (isNaN(minMaxValue)) {
-                            break;
-                          }
-                        }
-                        if (isNaN(minMaxValue)) {
-                          break;
-                        }
-                      }
-                      if (isNaN(minMaxValue)) {
-                        break;
-                      }
-                    }
-                    const outputOffset = outputColOffset + channel;
-                    outputVals[outputOffset] = poolType === "avg" ? avgValue / count : minMaxValue;
-                  }
-                }
-              }
-            }
-          }
-          return output.toTensor();
-        }
-        avgPool3d(x, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "avgPool3d");
-          return this.pool3d(x, convInfo, "avg").toFloat();
-        }
-        avgPool3dBackprop(dy, x, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([dy, x], "avgPool3dBackprop");
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const filterDepth = convInfo.filterDepth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
-          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
-          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
-          const dx = dist["buffer"](x.shape, "float32");
-          const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);
-          const dyBuf = this.bufferSync(dy);
-          for (let batch = 0; batch < convInfo.batchSize; ++batch) {
-            for (let channel = 0; channel < convInfo.inChannels; ++channel) {
-              for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {
-                for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {
-                  for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {
-                    // Shader code begins.
-                    const dyDepthCorner = dxDepth - padFront;
-                    const dyRowCorner = dxRow - padTop;
-                    const dyColCorner = dxCol - padLeft;
-                    let dotProd = 0;
-                    for (let wDepth = 0; wDepth < effectiveFilterDepth; wDepth += dilationDepth) {
-                      const dyDepth = (dyDepthCorner + wDepth) / strideDepth;
-                      if (
-                        dyDepth < 0 ||
-                        dyDepth >= convInfo.outDepth ||
-                        Math.floor(dyDepth) !== dyDepth
-                      ) {
-                        continue;
-                      }
-                      for (let wRow = 0; wRow < effectiveFilterHeight; wRow += dilationHeight) {
-                        const dyRow = (dyRowCorner + wRow) / strideHeight;
-                        if (
-                          dyRow < 0 ||
-                          dyRow >= convInfo.outHeight ||
-                          Math.floor(dyRow) !== dyRow
-                        ) {
-                          continue;
-                        }
-                        for (let wCol = 0; wCol < effectiveFilterWidth; wCol += dilationWidth) {
-                          const dyCol = (dyColCorner + wCol) / strideWidth;
-                          if (
-                            dyCol < 0 ||
-                            dyCol >= convInfo.outWidth ||
-                            Math.floor(dyCol) !== dyCol
-                          ) {
-                            continue;
-                          }
-                          const pixel = dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);
-                          dotProd += pixel;
-                        }
-                      }
-                    }
-                    dx.set(dotProd * avgMultiplier, batch, dxDepth, dxRow, dxCol, channel);
-                  }
-                }
-              }
-            }
-          }
-          return dx.toTensor();
-        }
-        maxPool3d(x, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "maxPool3d");
-          return this.pool3d(x, convInfo, "max").toFloat();
-        }
-        maxPool3dPositions(x, convInfo) {
-          const maxPositions = dist["buffer"](convInfo.outShape, "int32");
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padFront = convInfo.padInfo.front;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          const xBuf = this.bufferSync(x);
-          for (let batch = 0; batch < convInfo.batchSize; ++batch) {
-            for (let channel = 0; channel < convInfo.inChannels; ++channel) {
-              for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {
-                const xDepthCorner = yDepth * strideDepth - padFront;
-                let xDepthMin = xDepthCorner;
-                while (xDepthMin < 0) {
-                  xDepthMin += dilationDepth;
-                }
-                const xDepthMax = Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);
-                for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {
-                  const xRowCorner = yRow * strideHeight - padTop;
-                  let xRowMin = xRowCorner;
-                  while (xRowMin < 0) {
-                    xRowMin += dilationHeight;
-                  }
-                  const xRowMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);
-                  for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {
-                    const xColCorner = yCol * strideWidth - padLeft;
-                    let xColMin = xColCorner;
-                    while (xColMin < 0) {
-                      xColMin += dilationWidth;
-                    }
-                    const xColMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);
-                    // Shader code begins
-                    let maxValue = Number.NEGATIVE_INFINITY;
-                    let maxPosition = -1;
-                    for (let xDepth = xDepthMin; xDepth < xDepthMax; xDepth += dilationDepth) {
-                      const wDepth = xDepth - xDepthCorner;
-                      for (let xRow = xRowMin; xRow < xRowMax; xRow += dilationHeight) {
-                        const wRow = xRow - xRowCorner;
-                        for (let xCol = xColMin; xCol < xColMax; xCol += dilationWidth) {
-                          const wCol = xCol - xColCorner;
-                          const pixel = xBuf.get(batch, xDepth, xRow, xCol, channel);
-                          if (pixel >= maxValue) {
-                            maxValue = pixel;
-                            maxPosition =
-                              wDepth * effectiveFilterHeight * effectiveFilterWidth +
-                              wRow * effectiveFilterHeight +
-                              wCol;
-                          }
-                        }
-                      }
-                    }
-                    maxPositions.set(maxPosition, batch, yDepth, yRow, yCol, channel);
-                  }
-                }
-              }
-            }
-          }
-          return maxPositions.toTensor();
-        }
-        maxPool3dBackprop(dy, x, y, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])([x, y], "maxPool3dBackprop");
-          const maxPositions = this.maxPool3dPositions(x, convInfo);
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
-          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
-          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
-          const dx = dist["buffer"](x.shape, "float32");
-          const maxPosBuf = this.bufferSync(maxPositions);
-          const dyBuf = this.bufferSync(dy);
-          for (let batch = 0; batch < convInfo.batchSize; ++batch) {
-            for (let channel = 0; channel < convInfo.inChannels; ++channel) {
-              for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {
-                for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {
-                  for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {
-                    // Shader code begins
-                    const dyDepthCorner = dxDepth - padFront;
-                    const dyRowCorner = dxRow - padTop;
-                    const dyColCorner = dxCol - padLeft;
-                    let dotProd = 0;
-                    for (let wDepth = 0; wDepth < effectiveFilterDepth; wDepth += dilationDepth) {
-                      const dyDepth = (dyDepthCorner + wDepth) / strideDepth;
-                      if (
-                        dyDepth < 0 ||
-                        dyDepth >= convInfo.outDepth ||
-                        Math.floor(dyDepth) !== dyDepth
-                      ) {
-                        continue;
-                      }
-                      for (let wRow = 0; wRow < effectiveFilterHeight; wRow += dilationHeight) {
-                        const dyRow = (dyRowCorner + wRow) / strideHeight;
-                        if (
-                          dyRow < 0 ||
-                          dyRow >= convInfo.outHeight ||
-                          Math.floor(dyRow) !== dyRow
-                        ) {
-                          continue;
-                        }
-                        for (let wCol = 0; wCol < effectiveFilterWidth; wCol += dilationWidth) {
-                          const dyCol = (dyColCorner + wCol) / strideWidth;
-                          if (
-                            dyCol < 0 ||
-                            dyCol >= convInfo.outWidth ||
-                            Math.floor(dyCol) !== dyCol
-                          ) {
-                            continue;
-                          }
-                          const maxPos =
-                            effectiveFilterDepth * effectiveFilterHeight * effectiveFilterWidth -
-                            1 -
-                            maxPosBuf.get(batch, dyDepth, dyRow, dyCol, channel);
-                          const curPos =
-                            wDepth * effectiveFilterHeight * effectiveFilterWidth +
-                            wRow * effectiveFilterWidth +
-                            wCol;
-                          const mask = maxPos === curPos ? 1 : 0;
-                          if (mask === 0) {
-                            continue;
-                          }
-                          const pixel = dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);
-                          dotProd += pixel * mask;
-                        }
-                      }
-                    }
-                    dx.set(dotProd, batch, dxDepth, dxRow, dxCol, channel);
-                  }
-                }
-              }
-            }
-          }
-          return dx.toTensor();
-        }
-        cast(x, dtype) {
-          return dist["backend_util"].castTensor(x, dtype, this);
-        }
-        reshape(x, shape) {
-          return dist["backend_util"].reshapeTensor(x, shape);
-        }
-        avgPool(x, convInfo) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "avgPool");
-          Object(cpu_util["a" /* assertNotComplex */])(x, "maxPool");
-          const xValues = this.readSync(x.dataId);
-          return Object(pool_utils["b" /* pool */])(
-            xValues,
-            x.shape,
-            x.dtype,
-            x.strides,
-            convInfo,
-            "avg"
-          )
-            .toTensor()
-            .toFloat();
-        }
-        resizeBilinear(x, newHeight, newWidth, alignCorners) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "resizeBilinear");
-          const [batch, oldHeight, oldWidth, numChannels] = x.shape;
-          const xValues = this.readSync(x.dataId);
-          const result = new Float32Array(
-            dist["util"].sizeFromShape([batch, newHeight, newWidth, numChannels])
-          );
-          const effectiveInputSize = [
-            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
-            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
-          ];
-          const effectiveOutputSize = [
-            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
-            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
-          ];
-          let outputIdx = 0;
-          const effectiveRowSizeRatio = effectiveInputSize[0] / effectiveOutputSize[0];
-          const effectiveColSizeRatio = effectiveInputSize[1] / effectiveOutputSize[1];
-          for (let b = 0; b < batch; b++) {
-            for (let r = 0; r < newHeight; r++) {
-              const sourceFracRow = effectiveRowSizeRatio * r;
-              const sourceRowFloor = Math.floor(sourceFracRow);
-              const rowFrac = sourceFracRow - sourceRowFloor;
-              const sourceRowCeil = Math.min(oldHeight - 1, Math.ceil(sourceFracRow));
-              const topRowOffset = b * x.strides[0] + sourceRowFloor * x.strides[1];
-              const botRowOffset = b * x.strides[0] + sourceRowCeil * x.strides[1];
-              for (let c = 0; c < newWidth; c++) {
-                const sourceFracCol = effectiveColSizeRatio * c;
-                const sourceColFloor = Math.floor(sourceFracCol);
-                const colFrac = sourceFracCol - sourceColFloor;
-                const sourceColCeil = Math.min(oldWidth - 1, Math.ceil(sourceFracCol));
-                const topLeftOffest = topRowOffset + sourceColFloor * x.strides[2];
-                const botLeftOffset = botRowOffset + sourceColFloor * x.strides[2];
-                const topRightOffset = topRowOffset + sourceColCeil * x.strides[2];
-                const botRightOffest = botRowOffset + sourceColCeil * x.strides[2];
-                for (let d = 0; d < numChannels; d++) {
-                  // Begin shader.
-                  // Compute the fractional index of the source.
-                  const topLeft = xValues[topLeftOffest + d];
-                  const bottomLeft = xValues[botLeftOffset + d];
-                  const topRight = xValues[topRightOffset + d];
-                  const bottomRight = xValues[botRightOffest + d];
-                  const top = topLeft + (topRight - topLeft) * colFrac;
-                  const bottom = bottomLeft + (bottomRight - bottomLeft) * colFrac;
-                  const newValue = top + (bottom - top) * rowFrac;
-                  result[outputIdx++] = newValue;
-                }
-              }
-            }
-          }
-          return dist["tensor"](result, [batch, newHeight, newWidth, numChannels]);
-        }
-        resizeBilinearBackprop(dy, x, alignCorners) {
-          Object(cpu_util["a" /* assertNotComplex */])([dy, x], "resizeBilinearBackprop");
-          const [batch, xHeight, xWidth, depth] = x.shape;
-          const [, yHeight, yWidth] = dy.shape;
-          const output = new Float32Array(batch * xHeight * xWidth * depth);
-          // In the backwards pass, we want to find the pixels that were generated
-          // for each pixel in the input image the forward pass and add the
-          // corresponding coefficient from dy to the gradient (with some
-          // interpolation).
-          const effectiveXSize = [
-            alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,
-            alignCorners && yWidth > 1 ? xWidth - 1 : xWidth,
-          ];
-          const effectiveYSize = [
-            alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,
-            alignCorners && yWidth > 1 ? yWidth - 1 : yWidth,
-          ];
-          const heightScale = effectiveXSize[0] / effectiveYSize[0];
-          const widthScale = effectiveXSize[1] / effectiveYSize[1];
-          // Reference implementation
-          // tslint:disable-next-line:max-line-length
-          // https://github.com/tensorflow/tensorflow/blob/3039375c86a5bbc9610c7725dcaa95d635f87ba2/tensorflow/core/kernels/resize_bilinear_op.cc#L275
-          const dyValues = this.readSync(dy.dataId);
-          let offset = 0;
-          for (let b = 0; b < batch; b++) {
-            const bOffset = b * x.strides[0];
-            for (let r = 0; r < yHeight; r++) {
-              const dxR = r * heightScale;
-              const topDxRIndex = Math.floor(dxR);
-              const bottomDxRIndex = Math.min(Math.ceil(dxR), xHeight - 1);
-              const topDxROffset = bOffset + topDxRIndex * x.strides[1];
-              const bottomDxROffset = bOffset + bottomDxRIndex * x.strides[1];
-              const dxRLerp = dxR - topDxRIndex;
-              const inverseDxRLerp = 1.0 - dxRLerp;
-              for (let c = 0; c < yWidth; c++) {
-                const dxC = c * widthScale;
-                const leftDxCIndex = Math.floor(dxC);
-                const rightDxCIndex = Math.min(Math.ceil(dxC), xWidth - 1);
-                const dxCLerp = dxC - leftDxCIndex;
-                const inverseDxCLerp = 1.0 - dxCLerp;
-                const topLeftRCOffset = topDxROffset + leftDxCIndex * x.strides[2];
-                const topRightRCOffset = topDxROffset + rightDxCIndex * x.strides[2];
-                const bottomLeftRCOffset = bottomDxROffset + leftDxCIndex * x.strides[2];
-                const bottomRightRCOffset = bottomDxROffset + rightDxCIndex * x.strides[2];
-                const inverseDxRLerpTimesInverseDxCLerp = inverseDxRLerp * inverseDxCLerp;
-                const inverseDxRLerpTimesDxCLerp = inverseDxRLerp * dxCLerp;
-                const dxRLerpTimesInverseDxCLerp = dxRLerp * inverseDxCLerp;
-                const dxRLerpTimesDxCLerp = dxRLerp * dxCLerp;
-                for (let d = 0; d < depth; d++) {
-                  const dyVal = dyValues[offset++];
-                  output[topLeftRCOffset + d] += dyVal * inverseDxRLerpTimesInverseDxCLerp;
-                  output[topRightRCOffset + d] += dyVal * inverseDxRLerpTimesDxCLerp;
-                  output[bottomLeftRCOffset + d] += dyVal * dxRLerpTimesInverseDxCLerp;
-                  output[bottomRightRCOffset + d] += dyVal * dxRLerpTimesDxCLerp;
-                }
-              }
-            }
-          }
-          return dist["tensor4d"](output, [batch, xWidth, xHeight, depth], x.dtype);
-        }
-        resizeNearestNeighbor(x, newHeight, newWidth, alignCorners) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "resizeNearestNeighbor");
-          const [batch, oldHeight, oldWidth, numChannels] = x.shape;
-          const xValues = this.readSync(x.dataId);
-          const output = new Float32Array(batch * newHeight * newWidth * numChannels);
-          const effectiveInputSize = [
-            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
-            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
-          ];
-          const effectiveOutputSize = [
-            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
-            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
-          ];
-          const effectiveRowSizeRatio = effectiveInputSize[0] / effectiveOutputSize[0];
-          const effectiveColSizeRatio = effectiveInputSize[1] / effectiveOutputSize[1];
-          let outputOffset = 0;
-          for (let b = 0; b < batch; b++) {
-            const batchOffset = b * x.strides[0];
-            for (let r = 0; r < newHeight; r++) {
-              const sourceFracRow = effectiveRowSizeRatio * r;
-              const sourceNearestRow = Math.min(
-                oldHeight - 1,
-                alignCorners ? Math.round(sourceFracRow) : Math.floor(sourceFracRow)
-              );
-              const rowOffset = batchOffset + sourceNearestRow * x.strides[1];
-              for (let c = 0; c < newWidth; c++) {
-                const sourceFracCol = effectiveColSizeRatio * c;
-                const sourceNearestCol = Math.min(
-                  oldWidth - 1,
-                  alignCorners ? Math.round(sourceFracCol) : Math.floor(sourceFracCol)
-                );
-                const colOffset = rowOffset + sourceNearestCol * x.strides[2];
-                for (let d = 0; d < numChannels; d++) {
-                  // Begin shader.
-                  // Compute the fractional index of the source.
-                  const newVal = xValues[colOffset + d];
-                  output[outputOffset++] = newVal;
-                }
-              }
-            }
-          }
-          return dist["tensor"](output, [batch, newHeight, newWidth, numChannels], x.dtype);
-        }
-        resizeNearestNeighborBackprop(dy, x, alignCorners) {
-          Object(cpu_util["a" /* assertNotComplex */])([dy, x], "resizeNearestNeighborBackprop");
-          const [batch, xHeight, xWidth, depth] = x.shape;
-          const [, yHeight, yWidth] = dy.shape;
-          const output = new Float32Array(batch * xHeight * xWidth * depth);
-          const dyValues = this.readSync(dy.dataId);
-          // In the backwards pass, we want to find the pixels that were generated
-          // for each pixel in the input image the forward pass
-          const effectiveXSize = [
-            alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,
-            alignCorners && yWidth > 1 ? xWidth - 1 : xWidth,
-          ];
-          const effectiveYSize = [
-            alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,
-            alignCorners && yWidth > 1 ? yWidth - 1 : yWidth,
-          ];
-          const heightScale = effectiveXSize[0] / effectiveYSize[0];
-          const widthScale = effectiveXSize[1] / effectiveYSize[1];
-          const invHeightScale = 1 / heightScale;
-          const invWidthScale = 1 / widthScale;
-          // This defines the size of the window of values around a particular
-          // index in dy that we want to search for contributions to dx.
-          const winHeight = Math.ceil(invHeightScale) * 2 + 2;
-          const winWidth = Math.ceil(invWidthScale) * 2 + 2;
-          // Loop over the output space.
-          for (let b = 0; b < batch; b++) {
-            const batchOffset = b * x.strides[0];
-            for (let r = 0; r < xHeight; r++) {
-              const rowOffset = batchOffset + r * x.strides[1];
-              // Compute bounds for where in dy we will look
-              const startRLerp = Math.floor(r * invHeightScale);
-              const startDyR = Math.floor(startRLerp - winHeight / 2);
-              for (let c = 0; c < xWidth; c++) {
-                const colOffset = rowOffset + c * x.strides[2];
-                // Compute bounds for where in dy we will look
-                const startCLerp = Math.floor(c * invWidthScale);
-                const startDyC = Math.floor(startCLerp - winWidth / 2);
-                for (let d = 0; d < depth; d++) {
-                  let accum = 0;
-                  // loop over dy
-                  for (let dyRIndex = 0; dyRIndex < winHeight; dyRIndex++) {
-                    const dyR = dyRIndex + startDyR;
-                    // Guard against the window exceeding the bounds of dy
-                    if (dyR < 0 || dyR >= yHeight) {
-                      continue;
-                    }
-                    const dyROffset = batchOffset + dyR * dy.strides[1];
-                    const sourceFracRow = dyR * heightScale;
-                    const sourceNearestRow = Math.min(
-                      xHeight - 1,
-                      alignCorners ? Math.round(sourceFracRow) : Math.floor(sourceFracRow)
-                    );
-                    if (r !== sourceNearestRow) {
-                      continue;
-                    }
-                    for (let dyCIndex = 0; dyCIndex < winWidth; dyCIndex++) {
-                      const dyC = dyCIndex + startDyC;
-                      // Guard against the window exceeding the bounds of dy
-                      if (dyC < 0 || dyC >= yWidth) {
-                        continue;
-                      }
-                      const dyCOffset = dyROffset + dyC * dy.strides[2];
-                      const sourceFracCol = dyC * widthScale;
-                      const sourceNearestCol = Math.min(
-                        xWidth - 1,
-                        alignCorners ? Math.round(sourceFracCol) : Math.floor(sourceFracCol)
-                      );
-                      if (c === sourceNearestCol) {
-                        accum += dyValues[dyCOffset + d];
-                      }
-                    }
-                  }
-                  output[colOffset + d] = accum;
-                }
-              }
-            }
-          }
-          return dist["tensor4d"](output, x.shape, x.dtype);
-        }
-        batchNorm(x, mean, variance, offset, scale, varianceEpsilon) {
-          Object(cpu_util["a" /* assertNotComplex */])(
-            [x, mean, variance, scale, offset],
-            "batchNorm"
-          );
-          const xVals = this.readSync(x.dataId);
-          const mVals = this.readSync(mean.dataId);
-          const varVals = this.readSync(variance.dataId);
-          const sVals = scale ? this.readSync(scale.dataId) : new Float32Array([1]);
-          const offVals = offset ? this.readSync(offset.dataId) : new Float32Array([0]);
-          const outVals = new Float32Array(xVals.length);
-          const offValsLength = offVals.length;
-          const sValsLength = sVals.length;
-          const varValsLength = varVals.length;
-          const mValsLength = mVals.length;
-          let offi = 0;
-          let mi = 0;
-          let si = 0;
-          let vi = 0;
-          for (let i = 0; i < xVals.length; ++i) {
-            outVals[i] =
-              offVals[offi++] +
-              ((xVals[i] - mVals[mi++]) * sVals[si++]) / Math.sqrt(varVals[vi++] + varianceEpsilon);
-            if (offi >= offValsLength) {
-              offi = 0;
-            }
-            if (mi >= mValsLength) {
-              mi = 0;
-            }
-            if (si >= sValsLength) {
-              si = 0;
-            }
-            if (vi >= varValsLength) {
-              vi = 0;
-            }
-          }
-          return dist["tensor4d"](outVals, x.shape);
-        }
-        localResponseNormalization4D(x, depthRadius, bias, alpha, beta) {
-          Object(cpu_util["a" /* assertNotComplex */])(x, "localResponseNormalization4D");
-          const channels = x.shape[3];
-          const maxD = channels - 1;
-          const xValues = this.readSync(x.dataId);
-          const size = x.size;
-          const result = new Float32Array(size);
-          function sumAcrossChannels(offset) {
-            const currentChannel = offset % channels;
-            let beginSumOffset =
-              offset - currentChannel + Math.max(0, currentChannel - depthRadius);
-            const endSumOffset =
-              offset - currentChannel + Math.min(currentChannel + depthRadius, maxD);
-            let sum = 0.0;
-            for (; beginSumOffset <= endSumOffset; beginSumOffset++) {
-              const z = xValues[beginSumOffset];
-              sum += z * z;
-            }
-            return sum;
-          }
-          for (let offset = 0; offset < size; offset++) {
-            const sum = sumAcrossChannels(offset);
-            const val = xValues[offset] * Math.pow(bias + alpha * sum, -beta);
-            result[offset] = val;
-          }
-          return dist["tensor4d"](result, x.shape);
-        }
-        LRNGrad(dy, inputImage, outputImage, depthRadius, bias, alpha, beta) {
-          Object(cpu_util["a" /* assertNotComplex */])(dy, "LRNGrad");
-          const channels = dy.shape[3];
-          const dyValues = this.readSync(dy.dataId);
-          const inputImageValues = this.readSync(inputImage.dataId);
-          const outputImageValues = this.readSync(outputImage.dataId);
-          const result = new Float32Array(dy.size);
-          const size = dy.size;
-          for (let offset = 0; offset < size; offset++) {
-            const currentChannel = offset % channels;
-            const depthBegin = offset - currentChannel + Math.max(0, currentChannel - depthRadius);
-            const depthEnd =
-              offset - currentChannel + Math.min(channels, currentChannel + depthRadius + 1);
-            let norm = 0;
-            for (let k = depthBegin; k < depthEnd; k++) {
-              norm += Math.pow(inputImageValues[k], 2);
-            }
-            norm = alpha * norm + bias;
-            for (let k = depthBegin; k < depthEnd; k++) {
-              let dyi =
-                (-2 * alpha * beta * inputImageValues[k] * outputImageValues[offset]) / norm;
-              if (offset === k) {
-                dyi += Math.pow(norm, -beta);
-              }
-              dyi *= dyValues[offset];
-              result[k] += dyi;
-            }
-          }
-          return dist["tensor4d"](result, dy.shape);
-        }
-        multinomial(logits, normalized, numSamples, seed) {
-          Object(cpu_util["a" /* assertNotComplex */])(logits, "multinomial");
-          const probabilities = normalized ? logits : dist["softmax"](logits);
-          const batchSize = probabilities.shape[0];
-          const numEvents = probabilities.shape[1];
-          const res = dist["zeros"]([batchSize, numSamples], "int32");
-          const resVals = this.readSync(res.dataId);
-          const probVals = this.readSync(probabilities.dataId);
-          for (let b = 0; b < batchSize; ++b) {
-            const offset = b * numEvents;
-            // The cdf won't include the last event. It will be implicit if no other
-            // event happened.
-            const cdf = new Float32Array(numEvents - 1);
-            cdf[0] = probVals[offset];
-            for (let event = 1; event < cdf.length; ++event) {
-              cdf[event] = cdf[event - 1] + probVals[offset + event];
-            }
-            const random = seedrandom["alea"](seed.toString());
-            const outOffset = b * numSamples;
-            for (let sampleId = 0; sampleId < numSamples; ++sampleId) {
-              const r = random();
-              // Assume last event happened by default.
-              resVals[outOffset + sampleId] = cdf.length;
-              for (let event = 0; event < cdf.length; event++) {
-                if (r < cdf[event]) {
-                  resVals[outOffset + sampleId] = event;
-                  break;
-                }
-              }
-            }
-          }
-          return res;
-        }
-        oneHot(indices, depth, onValue, offValue) {
-          Object(cpu_util["a" /* assertNotComplex */])(indices, "oneHot");
-          const res = new Float32Array(indices.size * depth);
-          res.fill(offValue);
-          const indicesVal = this.readSync(indices.dataId);
-          for (let event = 0; event < indices.size; ++event) {
-            if (indicesVal[event] >= 0 && indicesVal[event] < depth) {
-              res[event * depth + indicesVal[event]] = onValue;
-            }
-          }
-          return dist["tensor2d"](res, [indices.size, depth], "int32");
-        }
-        nonMaxSuppression(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold) {
-          Object(cpu_util["a" /* assertNotComplex */])(boxes, "nonMaxSuppression");
-          const boxesVals = this.readSync(boxes.dataId);
-          const scoresVals = this.readSync(scores.dataId);
-          return nonMaxSuppressionV3(
-            boxesVals,
-            scoresVals,
-            maxOutputSize,
-            iouThreshold,
-            scoreThreshold
-          );
-        }
-        fft(x) {
-          return this.fftBatch(x, false);
-        }
-        ifft(x) {
-          return this.fftBatch(x, true);
-        }
-        /**
-         * Calculate FFT of inner most elements of batch tensor.
-         */
-        fftBatch(x, inverse) {
-          const batch = x.shape[0];
-          const innerDim = x.shape[1];
-          // Collects real and imaginary values separately.
-          const realResult = dist["buffer"](x.shape, "float32");
-          const imagResult = dist["buffer"](x.shape, "float32");
-          const real = dist["real"](x).as2D(batch, innerDim);
-          const imag = dist["imag"](x).as2D(batch, innerDim);
-          for (let b = 0; b < batch; b++) {
-            // TODO: Support slice ops for complex type.
-            const r = real.slice([b, 0], [1, innerDim]);
-            const i = imag.slice([b, 0], [1, innerDim]);
-            const input = dist["complex"](r, i);
-            // Run FFT by batch element.
-            const res = this.readSync(this.fftImpl(input, inverse).dataId);
-            for (let d = 0; d < innerDim; d++) {
-              const c = dist["backend_util"].getComplexWithIndex(res, d);
-              realResult.values[b * innerDim + d] = c.real;
-              imagResult.values[b * innerDim + d] = c.imag;
-            }
-          }
-          const t = dist["complex"](realResult.toTensor(), imagResult.toTensor());
-          return t.as2D(batch, innerDim);
-        }
-        fftImpl(x, inverse) {
-          const x1D = x.as1D();
-          const n = x1D.size;
-          if (this.isExponentOf2(n)) {
-            let result = this.fftRadix2(x1D, n, inverse).as2D(x.shape[0], x.shape[1]);
-            if (inverse) {
-              result = dist["complex"](
-                dist["real"](result).div(dist["scalar"](n)),
-                dist["imag"](result).div(dist["scalar"](n))
-              );
-            }
-            return result;
-          } else {
-            const data = this.readSync(x.dataId);
-            const rawOutput = this.fourierTransformByMatmul(data, n, inverse);
-            const output = dist["backend_util"].splitRealAndImagArrays(rawOutput);
-            return dist["complex"](output.real, output.imag).as2D(x.shape[0], x.shape[1]);
-          }
-        }
-        isExponentOf2(size) {
-          return (size & (size - 1)) === 0;
-        }
-        // FFT using Cooley-Tukey algorithm on radix 2 dimensional input.
-        fftRadix2(input, size, inverse) {
-          if (size === 1) {
-            return input;
-          }
-          const data = this.readSync(input.dataId);
-          const half = size / 2;
-          const evenComplex = dist["backend_util"].complexWithEvenIndex(data);
-          let evenTensor = dist["complex"](evenComplex.real, evenComplex.imag).as1D();
-          const oddComplex = dist["backend_util"].complexWithOddIndex(data);
-          let oddTensor = dist["complex"](oddComplex.real, oddComplex.imag).as1D();
-          // Recursive call for half part of original input.
-          evenTensor = this.fftRadix2(evenTensor, half, inverse);
-          oddTensor = this.fftRadix2(oddTensor, half, inverse);
-          const e = dist["backend_util"].exponents(size, inverse);
-          const exponent = dist["complex"](e.real, e.imag).mul(oddTensor);
-          const addPart = evenTensor.add(exponent);
-          const subPart = evenTensor.sub(exponent);
-          const realTensor = dist["real"](addPart).concat(dist["real"](subPart));
-          const imagTensor = dist["imag"](addPart).concat(dist["imag"](subPart));
-          return dist["complex"](realTensor, imagTensor).as1D();
-        }
-        // Calculate fourier transform by multplying sinusoid matrix.
-        fourierTransformByMatmul(data, size, inverse) {
-          const ret = new Float32Array(size * 2);
-          // TODO: Use matmul instead once it supports complex64 type.
-          for (let r = 0; r < size; r++) {
-            let real = 0.0;
-            let imag = 0.0;
-            for (let c = 0; c < size; c++) {
-              const e = dist["backend_util"].exponent(r * c, size, inverse);
-              const term = dist["backend_util"].getComplexWithIndex(data, c);
-              real += term.real * e.real - term.imag * e.imag;
-              imag += term.real * e.imag + term.imag * e.real;
-            }
-            if (inverse) {
-              real /= size;
-              imag /= size;
-            }
-            dist["backend_util"].assignToTypedArray(ret, real, imag, r);
-          }
-          return ret;
-        }
-        depthToSpace(x, blockSize, dataFormat) {
-          dist["util"].assert(
-            dataFormat === "NHWC",
-            () => `Only NHWC dataFormat supported on CPU for depthToSpace. Got ${dataFormat}`
-          );
-          dist["util"].assert(
-            blockSize > 1,
-            () => `blockSize should be > 1 for depthToSpace, but was: ${blockSize}`
-          );
-          const batchSize = x.shape[0];
-          const inputHeight = x.shape[1];
-          const inputWidth = x.shape[2];
-          const inputDepth = x.shape[3];
-          const outputHeight = inputHeight * blockSize;
-          const outputWidth = inputWidth * blockSize;
-          const outputDepth = inputDepth / (blockSize * blockSize);
-          const xValues = this.readSync(x.dataId);
-          const result = new Float32Array(batchSize * outputHeight * outputWidth * outputDepth);
-          let outputIdx = 0;
-          for (let b = 0; b < batchSize; ++b) {
-            for (let h = 0; h < outputHeight; ++h) {
-              const inH = Math.floor(h / blockSize);
-              const offsetH = h % blockSize;
-              for (let w = 0; w < outputWidth; ++w) {
-                const inW = Math.floor(w / blockSize);
-                const offsetW = w % blockSize;
-                const offsetD = (offsetH * blockSize + offsetW) * outputDepth;
-                for (let d = 0; d < outputDepth; ++d) {
-                  const inD = d + offsetD;
-                  const inputIdx = inD + inputDepth * (inW + inputWidth * (inH + inputHeight * b));
-                  result[outputIdx++] = xValues[inputIdx];
-                }
-              }
-            }
-          }
-          return dist["tensor4d"](result, [batchSize, outputHeight, outputWidth, outputDepth]);
-        }
-        broadcastedBinaryOp(a, b, dtype, op) {
-          const newShape = dist["backend_util"].assertAndGetBroadcastShape(a.shape, b.shape);
-          const result = dist["buffer"](newShape, dtype);
-          const aVals = this.readSync(a.dataId);
-          const bVals = this.readSync(b.dataId);
-          const aBroadcastDims = dist["backend_util"].getBroadcastDims(a.shape, newShape);
-          const bBroadcastDims = dist["backend_util"].getBroadcastDims(b.shape, newShape);
-          const resVals = result.values;
-          if (aBroadcastDims.length + bBroadcastDims.length === 0) {
-            for (let i = 0; i < resVals.length; ++i) {
-              resVals[i] = op(aVals[i % aVals.length], bVals[i % bVals.length]);
-            }
-          } else {
-            const aBuf = this.bufferSync(a);
-            const bBuf = this.bufferSync(b);
-            for (let i = 0; i < resVals.length; ++i) {
-              const loc = result.indexToLoc(i);
-              const aLoc = loc.slice(-a.rank);
-              aBroadcastDims.forEach((d) => (aLoc[d] = 0));
-              const aIndex = aBuf.locToIndex(aLoc);
-              const bLoc = loc.slice(-b.rank);
-              bBroadcastDims.forEach((d) => (bLoc[d] = 0));
-              const bIndex = bBuf.locToIndex(bLoc);
-              resVals[i] = op(aVals[aIndex], bVals[bIndex]);
-            }
-          }
-          return result.toTensor();
-        }
-        broadcastedBinaryComplexOp(a, b, op) {
-          const newShape = dist["backend_util"].assertAndGetBroadcastShape(a.shape, b.shape);
-          const realResult = dist["buffer"](newShape, "float32");
-          const imagResult = dist["buffer"](newShape, "float32");
-          const aVals = this.readSync(a.dataId);
-          const bVals = this.readSync(b.dataId);
-          const aBroadcastDims = dist["backend_util"].getBroadcastDims(a.shape, newShape);
-          const bBroadcastDims = dist["backend_util"].getBroadcastDims(b.shape, newShape);
-          const realVals = realResult.values;
-          const imagVals = imagResult.values;
-          if (aBroadcastDims.length + bBroadcastDims.length === 0) {
-            for (let i = 0; i < realVals.length; i++) {
-              const aIdx = i % aVals.length;
-              const bIdx = i % bVals.length;
-              const result = op(
-                aVals[aIdx * 2],
-                aVals[aIdx * 2 + 1],
-                bVals[bIdx * 2],
-                bVals[bIdx * 2 + 1]
-              );
-              realVals[i] = result.real;
-              imagVals[i] = result.imag;
-            }
-          } else {
-            const aRealBuf = this.bufferSync(this.data.get(a.dataId).complexTensors.real);
-            const bRealBuf = this.bufferSync(this.data.get(b.dataId).complexTensors.real);
-            for (let i = 0; i < realVals.length; i++) {
-              const loc = realResult.indexToLoc(i);
-              const aLoc = loc.slice(-a.rank);
-              aBroadcastDims.forEach((d) => (aLoc[d] = 0));
-              const aIndex = aRealBuf.locToIndex(aLoc);
-              const bLoc = loc.slice(-b.rank);
-              bBroadcastDims.forEach((d) => (bLoc[d] = 0));
-              const bIndex = bRealBuf.locToIndex(bLoc);
-              const opResult = op(
-                aVals[aIndex * 2],
-                aVals[aIndex * 2 + 1],
-                bVals[bIndex * 2],
-                bVals[bIndex * 2 + 1]
-              );
-              realVals[i] = opResult.real;
-              imagVals[i] = opResult.imag;
-            }
-          }
-          return this.complex(realResult.toTensor(), imagResult.toTensor());
-        }
-        split(x, sizeSplits, axis) {
-          return split(x, sizeSplits, axis);
-        }
-        dispose() {}
-        floatPrecision() {
-          return 32;
-        }
-        /** Returns the smallest representable number.  */
-        epsilon() {
-          return super.epsilon();
-        }
-        cropAndResize(images, boxes, boxIndex, cropSize, method, extrapolationValue) {
-          const [batch, imageHeight, imageWidth, numChannels] = images.shape;
-          const numBoxes = boxes.shape[0];
-          const [cropHeight, cropWidth] = cropSize;
-          const output = dist["buffer"]([numBoxes, cropHeight, cropWidth, numChannels], "float32");
-          const boxVals = this.readSync(boxes.dataId);
-          const boxIndVals = this.readSync(boxIndex.dataId);
-          const imageVals = this.readSync(images.dataId);
-          const inStride = images.strides; // to calculate flat indexes into image
-          const outStride = output.strides; // to calculate flat indexes into output
-          // Reference implementation
-          // tslint:disable-next-line:max-line-length
-          // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/crop_and_resize_op.cc
-          for (let b = 0; b < numBoxes; b++) {
-            const startInd = b * 4;
-            const y1 = boxVals[startInd];
-            const x1 = boxVals[startInd + 1];
-            const y2 = boxVals[startInd + 2];
-            const x2 = boxVals[startInd + 3];
-            const bInd = boxIndVals[b];
-            if (bInd >= batch) {
-              continue;
-            }
-            const heightScale =
-              cropHeight > 1 ? ((y2 - y1) * (imageHeight - 1)) / (cropHeight - 1) : 0;
-            const widthScale = cropWidth > 1 ? ((x2 - x1) * (imageWidth - 1)) / (cropWidth - 1) : 0;
-            for (let y = 0; y < cropHeight; y++) {
-              const yInd =
-                cropHeight > 1
-                  ? y1 * (imageHeight - 1) + y * heightScale
-                  : 0.5 * (y1 + y2) * (imageHeight - 1);
-              if (yInd < 0 || yInd > imageHeight - 1) {
-                for (let x = 0; x < cropWidth; x++) {
-                  for (let c = 0; c < numChannels; c++) {
-                    const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
-                    output.values[ind] = extrapolationValue;
-                  }
-                }
-                continue;
-              }
-              if (method === "bilinear") {
-                const topInd = Math.floor(yInd);
-                const bottomInd = Math.ceil(yInd);
-                const yLerp = yInd - topInd;
-                for (let x = 0; x < cropWidth; x++) {
-                  const xInd =
-                    cropWidth > 1
-                      ? x1 * (imageWidth - 1) + x * widthScale
-                      : 0.5 * (x1 + x2) * (imageWidth - 1);
-                  if (xInd < 0 || xInd > imageWidth - 1) {
-                    for (let c = 0; c < numChannels; c++) {
-                      const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
-                      output.values[ind] = extrapolationValue;
-                    }
-                    continue;
-                  }
-                  const leftInd = Math.floor(xInd);
-                  const rightInd = Math.ceil(xInd);
-                  const xLerp = xInd - leftInd;
-                  for (let c = 0; c < numChannels; c++) {
-                    let ind = c + leftInd * inStride[2] + topInd * inStride[1] + bInd * inStride[0];
-                    const topLeft = imageVals[ind];
-                    ind = c + rightInd * inStride[2] + topInd * inStride[1] + bInd * inStride[0];
-                    const topRight = imageVals[ind];
-                    ind = c + leftInd * inStride[2] + bottomInd * inStride[1] + bInd * inStride[0];
-                    const bottomLeft = imageVals[ind];
-                    ind = c + rightInd * inStride[2] + bottomInd * inStride[1] + bInd * inStride[0];
-                    const bottomRight = imageVals[ind];
-                    const top = topLeft + (topRight - topLeft) * xLerp;
-                    const bottom = bottomLeft + (bottomRight - bottomLeft) * xLerp;
-                    ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
-                    output.values[ind] = top + (bottom - top) * yLerp;
-                  }
-                }
-              } else {
-                // method == "nearest"
-                for (let x = 0; x < cropWidth; ++x) {
-                  const xInd =
-                    cropWidth > 1
-                      ? x1 * (imageWidth - 1) + x * widthScale
-                      : 0.5 * (x1 + x2) * (imageWidth - 1);
-                  if (xInd < 0 || xInd > imageWidth - 1) {
-                    for (let c = 0; c < numChannels; c++) {
-                      const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
-                      output.values[ind] = extrapolationValue;
-                    }
-                    continue;
-                  }
-                  const closestX = Math.round(xInd);
-                  const closestY = Math.round(yInd);
-                  for (let c = 0; c < numChannels; c++) {
-                    const inInd =
-                      c + closestX * inStride[2] + closestY * inStride[1] + bInd * inStride[0];
-                    const outInd = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
-                    output.values[outInd] = imageVals[inInd];
-                  }
-                }
-              }
-            }
-          }
-          return output.toTensor();
-        }
-        sparseToDense(sparseIndices, sparseValues, outputShape, defaultValue) {
-          const { sliceRank, numUpdates, sliceSize, strides, outputSize } = dist[
-            "backend_util"
-          ].calculateShapes(sparseValues, sparseIndices, outputShape);
-          const sumDupeIndices = false;
-          return this.scatter(
-            sparseIndices,
-            sparseValues,
-            outputShape,
-            outputSize,
-            sliceSize,
-            numUpdates,
-            sliceRank,
-            strides,
-            defaultValue,
-            sumDupeIndices
-          );
-        }
-        gatherND(x, indices) {
-          const indicesShape = indices.shape;
-          const sliceRank = indicesShape[indicesShape.length - 1];
-          const [resultShape, numSlices, sliceSize, strides] = dist[
-            "backend_util"
-          ].prepareAndValidate(x, indices);
-          if (numSlices === 0) {
-            return dist["tensor"]([], resultShape, x.dtype);
-          }
-          const buffer = new dist["TensorBuffer"]([numSlices, sliceSize], x.dtype);
-          const indicesData = this.readSync(indices.dataId);
-          const xData = this.readSync(x.dataId);
-          for (let i = 0; i < numSlices; i++) {
-            const index = [];
-            let flattenIndex = 0;
-            for (let j = 0; j < sliceRank; j++) {
-              const dim = indicesData[i * sliceRank + j];
-              flattenIndex += dim * strides[j];
-              index.push(dim);
-            }
-            if (flattenIndex < 0 || flattenIndex >= x.size / sliceSize) {
-              throw new Error(`Invalid indices: ${index} does not index into ${x.shape}`);
-            }
-            for (let k = 0; k < sliceSize; k++) {
-              buffer.values[i * sliceSize + k] = xData[flattenIndex * sliceSize + k];
-            }
-          }
-          return buffer.toTensor().reshape(resultShape);
-        }
-        scatterND(indices, updates, shape) {
-          const { sliceRank, numUpdates, sliceSize, strides, outputSize } = dist[
-            "backend_util"
-          ].calculateShapes(updates, indices, shape);
-          const defaultValue = dist["scalar"](0);
-          const sumDupeIndices = true;
-          return this.scatter(
-            indices,
-            updates,
-            shape,
-            outputSize,
-            sliceSize,
-            numUpdates,
-            sliceRank,
-            strides,
-            defaultValue,
-            sumDupeIndices
-          );
-        }
-        fill(shape, value, dtype) {
-          dtype = dtype || dist["util"].inferDtype(value);
-          const values = dist["util"].getArrayFromDType(dtype, dist["util"].sizeFromShape(shape));
-          values.fill(value);
-          return Object(dist["engine"])().makeTensor(values, shape, dtype, this);
-        }
-        onesLike(x) {
-          if (x.dtype === "string") {
-            throw new Error("onesLike is not supported for string tensors");
-          } else {
-            return this.fill(x.shape, 1, x.dtype);
-          }
-        }
-        zerosLike(x) {
-          const values = dist["util"].getArrayFromDType(
-            x.dtype,
-            dist["util"].sizeFromShape(x.shape)
-          );
-          return this.makeOutput(values, x.shape, x.dtype);
-        }
-        linspace(start, stop, num) {
-          return dist["backend_util"].linspaceImpl(start, stop, num);
-        }
-        scatter(
-          indices,
-          updates,
-          shape,
-          outputSize,
-          sliceSize,
-          numUpdates,
-          sliceRank,
-          strides,
-          defaultValue,
-          sumDupeIndices
-        ) {
-          const flattenShape = [outputSize / sliceSize, sliceSize];
-          const indicesData = this.readSync(indices.dataId);
-          const updatesData = this.readSync(updates.dataId);
-          if (outputSize === 0) {
-            return dist["tensor"]([], shape, updates.dtype);
-          }
-          const buffer = new dist["TensorBuffer"](flattenShape, updates.dtype);
-          buffer.values.fill(this.readSync(defaultValue.dataId)[0]);
-          for (let i = 0; i < numUpdates; i++) {
-            const index = [];
-            let flattenIndex = 0;
-            for (let j = 0; j < sliceRank; j++) {
-              const dim = indicesData[i * sliceRank + j];
-              index.push(dim);
-              flattenIndex += dim * strides[j];
-            }
-            if (flattenIndex < 0 || flattenIndex >= outputSize / sliceSize) {
-              throw new Error(`Invalid indices: ${index} does not index into ${shape}`);
-            }
-            for (let k = 0; k < sliceSize; k++) {
-              if (sumDupeIndices) {
-                buffer.values[flattenIndex * sliceSize + k] += updatesData[i * sliceSize + k];
-              } else {
-                buffer.values[flattenIndex * sliceSize + k] =
-                  updates.rank === 0 ? updatesData[0] : updatesData[i * sliceSize + k];
-              }
-            }
-          }
-          return buffer.toTensor().reshape(shape);
-        }
-      }
-      //# sourceMappingURL=backend_cpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/version.js
-      /** @license See the LICENSE file. */
-      // This code is auto-generated, do not modify this file!
-      const version = "2.0.1";
-
-      //# sourceMappingURL=version.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/base.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /*
-       * base.ts contains all the exports from tfjs-backend-cpu
-       * that do not trigger side effects.
-       */
-
-      //# sourceMappingURL=base.js.map
-
-      /***/
-    },
-    /* 32 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (global) {
-        var require;
-        var require; /*!
-    localForage -- Offline Storage, Improved
-    Version 1.7.3
-    https://localforage.github.io/localForage
-    (c) 2013-2017 Mozilla, Apache License 2.0
-*/
-        (function (f) {
-          if (true) {
-            module.exports = f();
-          } else {
-            var g;
-          }
-        })(function () {
-          var define, module, exports;
-          return (function e(t, n, r) {
-            function s(o, u) {
-              if (!n[o]) {
-                if (!t[o]) {
-                  var a = typeof require == "function" && require;
-                  if (!u && a) return require(o, !0);
-                  if (i) return i(o, !0);
-                  var f = new Error("Cannot find module '" + o + "'");
-                  throw ((f.code = "MODULE_NOT_FOUND"), f);
-                }
-                var l = (n[o] = { exports: {} });
-                t[o][0].call(
-                  l.exports,
-                  function (e) {
-                    var n = t[o][1][e];
-                    return s(n ? n : e);
-                  },
-                  l,
-                  l.exports,
-                  e,
-                  t,
-                  n,
-                  r
-                );
-              }
-              return n[o].exports;
-            }
-            var i = typeof require == "function" && require;
-            for (var o = 0; o < r.length; o++) s(r[o]);
-            return s;
-          })(
-            {
-              1: [
-                function (_dereq_, module, exports) {
-                  (function (global) {
-                    "use strict";
-                    var Mutation = global.MutationObserver || global.WebKitMutationObserver;
-
-                    var scheduleDrain;
-
-                    {
-                      if (Mutation) {
-                        var called = 0;
-                        var observer = new Mutation(nextTick);
-                        var element = global.document.createTextNode("");
-                        observer.observe(element, {
-                          characterData: true,
-                        });
-                        scheduleDrain = function () {
-                          element.data = called = ++called % 2;
-                        };
-                      } else if (
-                        !global.setImmediate &&
-                        typeof global.MessageChannel !== "undefined"
-                      ) {
-                        var channel = new global.MessageChannel();
-                        channel.port1.onmessage = nextTick;
-                        scheduleDrain = function () {
-                          channel.port2.postMessage(0);
-                        };
-                      } else if (
-                        "document" in global &&
-                        "onreadystatechange" in global.document.createElement("script")
-                      ) {
-                        scheduleDrain = function () {
-                          // Create a <script> element; its readystatechange event will be fired asynchronously once it is inserted
-                          // into the document. Do so, thus queuing up the task. Remember to clean up once it's been called.
-                          var scriptEl = global.document.createElement("script");
-                          scriptEl.onreadystatechange = function () {
-                            nextTick();
-
-                            scriptEl.onreadystatechange = null;
-                            scriptEl.parentNode.removeChild(scriptEl);
-                            scriptEl = null;
-                          };
-                          global.document.documentElement.appendChild(scriptEl);
-                        };
-                      } else {
-                        scheduleDrain = function () {
-                          setTimeout(nextTick, 0);
-                        };
-                      }
-                    }
-
-                    var draining;
-                    var queue = [];
-                    //named nextTick for less confusing stack traces
-                    function nextTick() {
-                      draining = true;
-                      var i, oldQueue;
-                      var len = queue.length;
-                      while (len) {
-                        oldQueue = queue;
-                        queue = [];
-                        i = -1;
-                        while (++i < len) {
-                          oldQueue[i]();
-                        }
-                        len = queue.length;
-                      }
-                      draining = false;
-                    }
-
-                    module.exports = immediate;
-                    function immediate(task) {
-                      if (queue.push(task) === 1 && !draining) {
-                        scheduleDrain();
-                      }
-                    }
-                  }.call(
-                    this,
-                    typeof global !== "undefined"
-                      ? global
-                      : typeof self !== "undefined"
-                      ? self
-                      : typeof window !== "undefined"
-                      ? window
-                      : {}
-                  ));
-                },
-                {},
-              ],
-              2: [
-                function (_dereq_, module, exports) {
-                  "use strict";
-                  var immediate = _dereq_(1);
-
-                  /* istanbul ignore next */
-                  function INTERNAL() {}
-
-                  var handlers = {};
-
-                  var REJECTED = ["REJECTED"];
-                  var FULFILLED = ["FULFILLED"];
-                  var PENDING = ["PENDING"];
-
-                  module.exports = Promise;
-
-                  function Promise(resolver) {
-                    if (typeof resolver !== "function") {
-                      throw new TypeError("resolver must be a function");
-                    }
-                    this.state = PENDING;
-                    this.queue = [];
-                    this.outcome = void 0;
-                    if (resolver !== INTERNAL) {
-                      safelyResolveThenable(this, resolver);
-                    }
-                  }
-
-                  Promise.prototype["catch"] = function (onRejected) {
-                    return this.then(null, onRejected);
-                  };
-                  Promise.prototype.then = function (onFulfilled, onRejected) {
-                    if (
-                      (typeof onFulfilled !== "function" && this.state === FULFILLED) ||
-                      (typeof onRejected !== "function" && this.state === REJECTED)
-                    ) {
-                      return this;
-                    }
-                    var promise = new this.constructor(INTERNAL);
-                    if (this.state !== PENDING) {
-                      var resolver = this.state === FULFILLED ? onFulfilled : onRejected;
-                      unwrap(promise, resolver, this.outcome);
-                    } else {
-                      this.queue.push(new QueueItem(promise, onFulfilled, onRejected));
-                    }
-
-                    return promise;
-                  };
-                  function QueueItem(promise, onFulfilled, onRejected) {
-                    this.promise = promise;
-                    if (typeof onFulfilled === "function") {
-                      this.onFulfilled = onFulfilled;
-                      this.callFulfilled = this.otherCallFulfilled;
-                    }
-                    if (typeof onRejected === "function") {
-                      this.onRejected = onRejected;
-                      this.callRejected = this.otherCallRejected;
-                    }
-                  }
-                  QueueItem.prototype.callFulfilled = function (value) {
-                    handlers.resolve(this.promise, value);
-                  };
-                  QueueItem.prototype.otherCallFulfilled = function (value) {
-                    unwrap(this.promise, this.onFulfilled, value);
-                  };
-                  QueueItem.prototype.callRejected = function (value) {
-                    handlers.reject(this.promise, value);
-                  };
-                  QueueItem.prototype.otherCallRejected = function (value) {
-                    unwrap(this.promise, this.onRejected, value);
-                  };
-
-                  function unwrap(promise, func, value) {
-                    immediate(function () {
-                      var returnValue;
-                      try {
-                        returnValue = func(value);
-                      } catch (e) {
-                        return handlers.reject(promise, e);
-                      }
-                      if (returnValue === promise) {
-                        handlers.reject(
-                          promise,
-                          new TypeError("Cannot resolve promise with itself")
-                        );
-                      } else {
-                        handlers.resolve(promise, returnValue);
-                      }
-                    });
-                  }
-
-                  handlers.resolve = function (self, value) {
-                    var result = tryCatch(getThen, value);
-                    if (result.status === "error") {
-                      return handlers.reject(self, result.value);
-                    }
-                    var thenable = result.value;
-
-                    if (thenable) {
-                      safelyResolveThenable(self, thenable);
-                    } else {
-                      self.state = FULFILLED;
-                      self.outcome = value;
-                      var i = -1;
-                      var len = self.queue.length;
-                      while (++i < len) {
-                        self.queue[i].callFulfilled(value);
-                      }
-                    }
-                    return self;
-                  };
-                  handlers.reject = function (self, error) {
-                    self.state = REJECTED;
-                    self.outcome = error;
-                    var i = -1;
-                    var len = self.queue.length;
-                    while (++i < len) {
-                      self.queue[i].callRejected(error);
-                    }
-                    return self;
-                  };
-
-                  function getThen(obj) {
-                    // Make sure we only access the accessor once as required by the spec
-                    var then = obj && obj.then;
-                    if (
-                      obj &&
-                      (typeof obj === "object" || typeof obj === "function") &&
-                      typeof then === "function"
-                    ) {
-                      return function appyThen() {
-                        then.apply(obj, arguments);
-                      };
-                    }
-                  }
-
-                  function safelyResolveThenable(self, thenable) {
-                    // Either fulfill, reject or reject with error
-                    var called = false;
-                    function onError(value) {
-                      if (called) {
-                        return;
-                      }
-                      called = true;
-                      handlers.reject(self, value);
-                    }
-
-                    function onSuccess(value) {
-                      if (called) {
-                        return;
-                      }
-                      called = true;
-                      handlers.resolve(self, value);
-                    }
-
-                    function tryToUnwrap() {
-                      thenable(onSuccess, onError);
-                    }
-
-                    var result = tryCatch(tryToUnwrap);
-                    if (result.status === "error") {
-                      onError(result.value);
-                    }
-                  }
-
-                  function tryCatch(func, value) {
-                    var out = {};
-                    try {
-                      out.value = func(value);
-                      out.status = "success";
-                    } catch (e) {
-                      out.status = "error";
-                      out.value = e;
-                    }
-                    return out;
-                  }
-
-                  Promise.resolve = resolve;
-                  function resolve(value) {
-                    if (value instanceof this) {
-                      return value;
-                    }
-                    return handlers.resolve(new this(INTERNAL), value);
-                  }
-
-                  Promise.reject = reject;
-                  function reject(reason) {
-                    var promise = new this(INTERNAL);
-                    return handlers.reject(promise, reason);
-                  }
-
-                  Promise.all = all;
-                  function all(iterable) {
-                    var self = this;
-                    if (Object.prototype.toString.call(iterable) !== "[object Array]") {
-                      return this.reject(new TypeError("must be an array"));
-                    }
-
-                    var len = iterable.length;
-                    var called = false;
-                    if (!len) {
-                      return this.resolve([]);
-                    }
-
-                    var values = new Array(len);
-                    var resolved = 0;
-                    var i = -1;
-                    var promise = new this(INTERNAL);
-
-                    while (++i < len) {
-                      allResolver(iterable[i], i);
-                    }
-                    return promise;
-                    function allResolver(value, i) {
-                      self.resolve(value).then(resolveFromAll, function (error) {
-                        if (!called) {
-                          called = true;
-                          handlers.reject(promise, error);
-                        }
-                      });
-                      function resolveFromAll(outValue) {
-                        values[i] = outValue;
-                        if (++resolved === len && !called) {
-                          called = true;
-                          handlers.resolve(promise, values);
-                        }
-                      }
-                    }
-                  }
-
-                  Promise.race = race;
-                  function race(iterable) {
-                    var self = this;
-                    if (Object.prototype.toString.call(iterable) !== "[object Array]") {
-                      return this.reject(new TypeError("must be an array"));
-                    }
-
-                    var len = iterable.length;
-                    var called = false;
-                    if (!len) {
-                      return this.resolve([]);
-                    }
-
-                    var i = -1;
-                    var promise = new this(INTERNAL);
-
-                    while (++i < len) {
-                      resolver(iterable[i]);
-                    }
-                    return promise;
-                    function resolver(value) {
-                      self.resolve(value).then(
-                        function (response) {
-                          if (!called) {
-                            called = true;
-                            handlers.resolve(promise, response);
-                          }
-                        },
-                        function (error) {
-                          if (!called) {
-                            called = true;
-                            handlers.reject(promise, error);
-                          }
-                        }
-                      );
-                    }
-                  }
-                },
-                { 1: 1 },
-              ],
-              3: [
-                function (_dereq_, module, exports) {
-                  (function (global) {
-                    "use strict";
-                    if (typeof global.Promise !== "function") {
-                      global.Promise = _dereq_(2);
-                    }
-                  }.call(
-                    this,
-                    typeof global !== "undefined"
-                      ? global
-                      : typeof self !== "undefined"
-                      ? self
-                      : typeof window !== "undefined"
-                      ? window
-                      : {}
-                  ));
-                },
-                { 2: 2 },
-              ],
-              4: [
-                function (_dereq_, module, exports) {
-                  "use strict";
-
-                  var _typeof =
-                    typeof Symbol === "function" && typeof Symbol.iterator === "symbol"
-                      ? function (obj) {
-                          return typeof obj;
-                        }
-                      : function (obj) {
-                          return obj &&
-                            typeof Symbol === "function" &&
-                            obj.constructor === Symbol &&
-                            obj !== Symbol.prototype
-                            ? "symbol"
-                            : typeof obj;
-                        };
-
-                  function _classCallCheck(instance, Constructor) {
-                    if (!(instance instanceof Constructor)) {
-                      throw new TypeError("Cannot call a class as a function");
-                    }
-                  }
-
-                  function getIDB() {
-                    /* global indexedDB,webkitIndexedDB,mozIndexedDB,OIndexedDB,msIndexedDB */
-                    try {
-                      if (typeof indexedDB !== "undefined") {
-                        return indexedDB;
-                      }
-                      if (typeof webkitIndexedDB !== "undefined") {
-                        return webkitIndexedDB;
-                      }
-                      if (typeof mozIndexedDB !== "undefined") {
-                        return mozIndexedDB;
-                      }
-                      if (typeof OIndexedDB !== "undefined") {
-                        return OIndexedDB;
-                      }
-                      if (typeof msIndexedDB !== "undefined") {
-                        return msIndexedDB;
-                      }
-                    } catch (e) {
-                      return;
-                    }
-                  }
-
-                  var idb = getIDB();
-
-                  function isIndexedDBValid() {
-                    try {
-                      // Initialize IndexedDB; fall back to vendor-prefixed versions
-                      // if needed.
-                      if (!idb) {
-                        return false;
-                      }
-                      // We mimic PouchDB here;
-                      //
-                      // We test for openDatabase because IE Mobile identifies itself
-                      // as Safari. Oh the lulz...
-                      var isSafari =
-                        typeof openDatabase !== "undefined" &&
-                        /(Safari|iPhone|iPad|iPod)/.test(navigator.userAgent) &&
-                        !/Chrome/.test(navigator.userAgent) &&
-                        !/BlackBerry/.test(navigator.platform);
-
-                      var hasFetch =
-                        typeof fetch === "function" &&
-                        fetch.toString().indexOf("[native code") !== -1;
-
-                      // Safari <10.1 does not meet our requirements for IDB support (#5572)
-                      // since Safari 10.1 shipped with fetch, we can use that to detect it
-                      return (
-                        (!isSafari || hasFetch) &&
-                        typeof indexedDB !== "undefined" &&
-                        // some outdated implementations of IDB that appear on Samsung
-                        // and HTC Android devices <4.4 are missing IDBKeyRange
-                        // See: https://github.com/mozilla/localForage/issues/128
-                        // See: https://github.com/mozilla/localForage/issues/272
-                        typeof IDBKeyRange !== "undefined"
-                      );
-                    } catch (e) {
-                      return false;
-                    }
-                  }
-
-                  // Abstracts constructing a Blob object, so it also works in older
-                  // browsers that don't support the native Blob constructor. (i.e.
-                  // old QtWebKit versions, at least).
-                  // Abstracts constructing a Blob object, so it also works in older
-                  // browsers that don't support the native Blob constructor. (i.e.
-                  // old QtWebKit versions, at least).
-                  function createBlob(parts, properties) {
-                    /* global BlobBuilder,MSBlobBuilder,MozBlobBuilder,WebKitBlobBuilder */
-                    parts = parts || [];
-                    properties = properties || {};
-                    try {
-                      return new Blob(parts, properties);
-                    } catch (e) {
-                      if (e.name !== "TypeError") {
-                        throw e;
-                      }
-                      var Builder =
-                        typeof BlobBuilder !== "undefined"
-                          ? BlobBuilder
-                          : typeof MSBlobBuilder !== "undefined"
-                          ? MSBlobBuilder
-                          : typeof MozBlobBuilder !== "undefined"
-                          ? MozBlobBuilder
-                          : WebKitBlobBuilder;
-                      var builder = new Builder();
-                      for (var i = 0; i < parts.length; i += 1) {
-                        builder.append(parts[i]);
-                      }
-                      return builder.getBlob(properties.type);
-                    }
-                  }
-
-                  // This is CommonJS because lie is an external dependency, so Rollup
-                  // can just ignore it.
-                  if (typeof Promise === "undefined") {
-                    // In the "nopromises" build this will just throw if you don't have
-                    // a global promise object, but it would throw anyway later.
-                    _dereq_(3);
-                  }
-                  var Promise$1 = Promise;
-
-                  function executeCallback(promise, callback) {
-                    if (callback) {
-                      promise.then(
-                        function (result) {
-                          callback(null, result);
-                        },
-                        function (error) {
-                          callback(error);
-                        }
-                      );
-                    }
-                  }
-
-                  function executeTwoCallbacks(promise, callback, errorCallback) {
-                    if (typeof callback === "function") {
-                      promise.then(callback);
-                    }
-
-                    if (typeof errorCallback === "function") {
-                      promise["catch"](errorCallback);
-                    }
-                  }
-
-                  function normalizeKey(key) {
-                    // Cast the key to a string, as that's all we can set as a key.
-                    if (typeof key !== "string") {
-                      console.warn(key + " used as a key, but it is not a string.");
-                      key = String(key);
-                    }
-
-                    return key;
-                  }
-
-                  function getCallback() {
-                    if (arguments.length && typeof arguments[arguments.length - 1] === "function") {
-                      return arguments[arguments.length - 1];
-                    }
-                  }
-
-                  // Some code originally from async_storage.js in
-                  // [Gaia](https://github.com/mozilla-b2g/gaia).
-
-                  var DETECT_BLOB_SUPPORT_STORE = "local-forage-detect-blob-support";
-                  var supportsBlobs = void 0;
-                  var dbContexts = {};
-                  var toString = Object.prototype.toString;
-
-                  // Transaction Modes
-                  var READ_ONLY = "readonly";
-                  var READ_WRITE = "readwrite";
-
-                  // Transform a binary string to an array buffer, because otherwise
-                  // weird stuff happens when you try to work with the binary string directly.
-                  // It is known.
-                  // From http://stackoverflow.com/questions/14967647/ (continues on next line)
-                  // encode-decode-image-with-base64-breaks-image (2013-04-21)
-                  function _binStringToArrayBuffer(bin) {
-                    var length = bin.length;
-                    var buf = new ArrayBuffer(length);
-                    var arr = new Uint8Array(buf);
-                    for (var i = 0; i < length; i++) {
-                      arr[i] = bin.charCodeAt(i);
-                    }
-                    return buf;
-                  }
-
-                  //
-                  // Blobs are not supported in all versions of IndexedDB, notably
-                  // Chrome <37 and Android <5. In those versions, storing a blob will throw.
-                  //
-                  // Various other blob bugs exist in Chrome v37-42 (inclusive).
-                  // Detecting them is expensive and confusing to users, and Chrome 37-42
-                  // is at very low usage worldwide, so we do a hacky userAgent check instead.
-                  //
-                  // content-type bug: https://code.google.com/p/chromium/issues/detail?id=408120
-                  // 404 bug: https://code.google.com/p/chromium/issues/detail?id=447916
-                  // FileReader bug: https://code.google.com/p/chromium/issues/detail?id=447836
-                  //
-                  // Code borrowed from PouchDB. See:
-                  // https://github.com/pouchdb/pouchdb/blob/master/packages/node_modules/pouchdb-adapter-idb/src/blobSupport.js
-                  //
-                  function _checkBlobSupportWithoutCaching(idb) {
-                    return new Promise$1(function (resolve) {
-                      var txn = idb.transaction(DETECT_BLOB_SUPPORT_STORE, READ_WRITE);
-                      var blob = createBlob([""]);
-                      txn.objectStore(DETECT_BLOB_SUPPORT_STORE).put(blob, "key");
-
-                      txn.onabort = function (e) {
-                        // If the transaction aborts now its due to not being able to
-                        // write to the database, likely due to the disk being full
-                        e.preventDefault();
-                        e.stopPropagation();
-                        resolve(false);
-                      };
-
-                      txn.oncomplete = function () {
-                        var matchedChrome = navigator.userAgent.match(/Chrome\/(\d+)/);
-                        var matchedEdge = navigator.userAgent.match(/Edge\//);
-                        // MS Edge pretends to be Chrome 42:
-                        // https://msdn.microsoft.com/en-us/library/hh869301%28v=vs.85%29.aspx
-                        resolve(
-                          matchedEdge || !matchedChrome || parseInt(matchedChrome[1], 10) >= 43
-                        );
-                      };
-                    })["catch"](function () {
-                      return false; // error, so assume unsupported
-                    });
-                  }
-
-                  function _checkBlobSupport(idb) {
-                    if (typeof supportsBlobs === "boolean") {
-                      return Promise$1.resolve(supportsBlobs);
-                    }
-                    return _checkBlobSupportWithoutCaching(idb).then(function (value) {
-                      supportsBlobs = value;
-                      return supportsBlobs;
-                    });
-                  }
-
-                  function _deferReadiness(dbInfo) {
-                    var dbContext = dbContexts[dbInfo.name];
-
-                    // Create a deferred object representing the current database operation.
-                    var deferredOperation = {};
-
-                    deferredOperation.promise = new Promise$1(function (resolve, reject) {
-                      deferredOperation.resolve = resolve;
-                      deferredOperation.reject = reject;
-                    });
-
-                    // Enqueue the deferred operation.
-                    dbContext.deferredOperations.push(deferredOperation);
-
-                    // Chain its promise to the database readiness.
-                    if (!dbContext.dbReady) {
-                      dbContext.dbReady = deferredOperation.promise;
-                    } else {
-                      dbContext.dbReady = dbContext.dbReady.then(function () {
-                        return deferredOperation.promise;
-                      });
-                    }
-                  }
-
-                  function _advanceReadiness(dbInfo) {
-                    var dbContext = dbContexts[dbInfo.name];
-
-                    // Dequeue a deferred operation.
-                    var deferredOperation = dbContext.deferredOperations.pop();
-
-                    // Resolve its promise (which is part of the database readiness
-                    // chain of promises).
-                    if (deferredOperation) {
-                      deferredOperation.resolve();
-                      return deferredOperation.promise;
-                    }
-                  }
-
-                  function _rejectReadiness(dbInfo, err) {
-                    var dbContext = dbContexts[dbInfo.name];
-
-                    // Dequeue a deferred operation.
-                    var deferredOperation = dbContext.deferredOperations.pop();
-
-                    // Reject its promise (which is part of the database readiness
-                    // chain of promises).
-                    if (deferredOperation) {
-                      deferredOperation.reject(err);
-                      return deferredOperation.promise;
-                    }
-                  }
-
-                  function _getConnection(dbInfo, upgradeNeeded) {
-                    return new Promise$1(function (resolve, reject) {
-                      dbContexts[dbInfo.name] = dbContexts[dbInfo.name] || createDbContext();
-
-                      if (dbInfo.db) {
-                        if (upgradeNeeded) {
-                          _deferReadiness(dbInfo);
-                          dbInfo.db.close();
-                        } else {
-                          return resolve(dbInfo.db);
-                        }
-                      }
-
-                      var dbArgs = [dbInfo.name];
-
-                      if (upgradeNeeded) {
-                        dbArgs.push(dbInfo.version);
-                      }
-
-                      var openreq = idb.open.apply(idb, dbArgs);
-
-                      if (upgradeNeeded) {
-                        openreq.onupgradeneeded = function (e) {
-                          var db = openreq.result;
-                          try {
-                            db.createObjectStore(dbInfo.storeName);
-                            if (e.oldVersion <= 1) {
-                              // Added when support for blob shims was added
-                              db.createObjectStore(DETECT_BLOB_SUPPORT_STORE);
-                            }
-                          } catch (ex) {
-                            if (ex.name === "ConstraintError") {
-                              console.warn(
-                                'The database "' +
-                                  dbInfo.name +
-                                  '"' +
-                                  " has been upgraded from version " +
-                                  e.oldVersion +
-                                  " to version " +
-                                  e.newVersion +
-                                  ', but the storage "' +
-                                  dbInfo.storeName +
-                                  '" already exists.'
-                              );
-                            } else {
-                              throw ex;
-                            }
-                          }
-                        };
-                      }
-
-                      openreq.onerror = function (e) {
-                        e.preventDefault();
-                        reject(openreq.error);
-                      };
-
-                      openreq.onsuccess = function () {
-                        resolve(openreq.result);
-                        _advanceReadiness(dbInfo);
-                      };
-                    });
-                  }
-
-                  function _getOriginalConnection(dbInfo) {
-                    return _getConnection(dbInfo, false);
-                  }
-
-                  function _getUpgradedConnection(dbInfo) {
-                    return _getConnection(dbInfo, true);
-                  }
-
-                  function _isUpgradeNeeded(dbInfo, defaultVersion) {
-                    if (!dbInfo.db) {
-                      return true;
-                    }
-
-                    var isNewStore = !dbInfo.db.objectStoreNames.contains(dbInfo.storeName);
-                    var isDowngrade = dbInfo.version < dbInfo.db.version;
-                    var isUpgrade = dbInfo.version > dbInfo.db.version;
-
-                    if (isDowngrade) {
-                      // If the version is not the default one
-                      // then warn for impossible downgrade.
-                      if (dbInfo.version !== defaultVersion) {
-                        console.warn(
-                          'The database "' +
-                            dbInfo.name +
-                            '"' +
-                            " can't be downgraded from version " +
-                            dbInfo.db.version +
-                            " to version " +
-                            dbInfo.version +
-                            "."
-                        );
-                      }
-                      // Align the versions to prevent errors.
-                      dbInfo.version = dbInfo.db.version;
-                    }
-
-                    if (isUpgrade || isNewStore) {
-                      // If the store is new then increment the version (if needed).
-                      // This will trigger an "upgradeneeded" event which is required
-                      // for creating a store.
-                      if (isNewStore) {
-                        var incVersion = dbInfo.db.version + 1;
-                        if (incVersion > dbInfo.version) {
-                          dbInfo.version = incVersion;
-                        }
-                      }
-
-                      return true;
-                    }
-
-                    return false;
-                  }
-
-                  // encode a blob for indexeddb engines that don't support blobs
-                  function _encodeBlob(blob) {
-                    return new Promise$1(function (resolve, reject) {
-                      var reader = new FileReader();
-                      reader.onerror = reject;
-                      reader.onloadend = function (e) {
-                        var base64 = btoa(e.target.result || "");
-                        resolve({
-                          __local_forage_encoded_blob: true,
-                          data: base64,
-                          type: blob.type,
-                        });
-                      };
-                      reader.readAsBinaryString(blob);
-                    });
-                  }
-
-                  // decode an encoded blob
-                  function _decodeBlob(encodedBlob) {
-                    var arrayBuff = _binStringToArrayBuffer(atob(encodedBlob.data));
-                    return createBlob([arrayBuff], { type: encodedBlob.type });
-                  }
-
-                  // is this one of our fancy encoded blobs?
-                  function _isEncodedBlob(value) {
-                    return value && value.__local_forage_encoded_blob;
-                  }
-
-                  // Specialize the default `ready()` function by making it dependent
-                  // on the current database operations. Thus, the driver will be actually
-                  // ready when it's been initialized (default) *and* there are no pending
-                  // operations on the database (initiated by some other instances).
-                  function _fullyReady(callback) {
-                    var self = this;
-
-                    var promise = self._initReady().then(function () {
-                      var dbContext = dbContexts[self._dbInfo.name];
-
-                      if (dbContext && dbContext.dbReady) {
-                        return dbContext.dbReady;
-                      }
-                    });
-
-                    executeTwoCallbacks(promise, callback, callback);
-                    return promise;
-                  }
-
-                  // Try to establish a new db connection to replace the
-                  // current one which is broken (i.e. experiencing
-                  // InvalidStateError while creating a transaction).
-                  function _tryReconnect(dbInfo) {
-                    _deferReadiness(dbInfo);
-
-                    var dbContext = dbContexts[dbInfo.name];
-                    var forages = dbContext.forages;
-
-                    for (var i = 0; i < forages.length; i++) {
-                      var forage = forages[i];
-                      if (forage._dbInfo.db) {
-                        forage._dbInfo.db.close();
-                        forage._dbInfo.db = null;
-                      }
-                    }
-                    dbInfo.db = null;
-
-                    return _getOriginalConnection(dbInfo)
-                      .then(function (db) {
-                        dbInfo.db = db;
-                        if (_isUpgradeNeeded(dbInfo)) {
-                          // Reopen the database for upgrading.
-                          return _getUpgradedConnection(dbInfo);
-                        }
-                        return db;
-                      })
-                      .then(function (db) {
-                        // store the latest db reference
-                        // in case the db was upgraded
-                        dbInfo.db = dbContext.db = db;
-                        for (var i = 0; i < forages.length; i++) {
-                          forages[i]._dbInfo.db = db;
-                        }
-                      })
-                      ["catch"](function (err) {
-                        _rejectReadiness(dbInfo, err);
-                        throw err;
-                      });
-                  }
-
-                  // FF doesn't like Promises (micro-tasks) and IDDB store operations,
-                  // so we have to do it with callbacks
-                  function createTransaction(dbInfo, mode, callback, retries) {
-                    if (retries === undefined) {
-                      retries = 1;
-                    }
-
-                    try {
-                      var tx = dbInfo.db.transaction(dbInfo.storeName, mode);
-                      callback(null, tx);
-                    } catch (err) {
-                      if (
-                        retries > 0 &&
-                        (!dbInfo.db ||
-                          err.name === "InvalidStateError" ||
-                          err.name === "NotFoundError")
-                      ) {
-                        return Promise$1.resolve()
-                          .then(function () {
-                            if (
-                              !dbInfo.db ||
-                              (err.name === "NotFoundError" &&
-                                !dbInfo.db.objectStoreNames.contains(dbInfo.storeName) &&
-                                dbInfo.version <= dbInfo.db.version)
-                            ) {
-                              // increase the db version, to create the new ObjectStore
-                              if (dbInfo.db) {
-                                dbInfo.version = dbInfo.db.version + 1;
-                              }
-                              // Reopen the database for upgrading.
-                              return _getUpgradedConnection(dbInfo);
-                            }
-                          })
-                          .then(function () {
-                            return _tryReconnect(dbInfo).then(function () {
-                              createTransaction(dbInfo, mode, callback, retries - 1);
-                            });
-                          })
-                          ["catch"](callback);
-                      }
-
-                      callback(err);
-                    }
-                  }
-
-                  function createDbContext() {
-                    return {
-                      // Running localForages sharing a database.
-                      forages: [],
-                      // Shared database.
-                      db: null,
-                      // Database readiness (promise).
-                      dbReady: null,
-                      // Deferred operations on the database.
-                      deferredOperations: [],
-                    };
-                  }
-
-                  // Open the IndexedDB database (automatically creates one if one didn't
-                  // previously exist), using any options set in the config.
-                  function _initStorage(options) {
-                    var self = this;
-                    var dbInfo = {
-                      db: null,
-                    };
-
-                    if (options) {
-                      for (var i in options) {
-                        dbInfo[i] = options[i];
-                      }
-                    }
-
-                    // Get the current context of the database;
-                    var dbContext = dbContexts[dbInfo.name];
-
-                    // ...or create a new context.
-                    if (!dbContext) {
-                      dbContext = createDbContext();
-                      // Register the new context in the global container.
-                      dbContexts[dbInfo.name] = dbContext;
-                    }
-
-                    // Register itself as a running localForage in the current context.
-                    dbContext.forages.push(self);
-
-                    // Replace the default `ready()` function with the specialized one.
-                    if (!self._initReady) {
-                      self._initReady = self.ready;
-                      self.ready = _fullyReady;
-                    }
-
-                    // Create an array of initialization states of the related localForages.
-                    var initPromises = [];
-
-                    function ignoreErrors() {
-                      // Don't handle errors here,
-                      // just makes sure related localForages aren't pending.
-                      return Promise$1.resolve();
-                    }
-
-                    for (var j = 0; j < dbContext.forages.length; j++) {
-                      var forage = dbContext.forages[j];
-                      if (forage !== self) {
-                        // Don't wait for itself...
-                        initPromises.push(forage._initReady()["catch"](ignoreErrors));
-                      }
-                    }
-
-                    // Take a snapshot of the related localForages.
-                    var forages = dbContext.forages.slice(0);
-
-                    // Initialize the connection process only when
-                    // all the related localForages aren't pending.
-                    return Promise$1.all(initPromises)
-                      .then(function () {
-                        dbInfo.db = dbContext.db;
-                        // Get the connection or open a new one without upgrade.
-                        return _getOriginalConnection(dbInfo);
-                      })
-                      .then(function (db) {
-                        dbInfo.db = db;
-                        if (_isUpgradeNeeded(dbInfo, self._defaultConfig.version)) {
-                          // Reopen the database for upgrading.
-                          return _getUpgradedConnection(dbInfo);
-                        }
-                        return db;
-                      })
-                      .then(function (db) {
-                        dbInfo.db = dbContext.db = db;
-                        self._dbInfo = dbInfo;
-                        // Share the final connection amongst related localForages.
-                        for (var k = 0; k < forages.length; k++) {
-                          var forage = forages[k];
-                          if (forage !== self) {
-                            // Self is already up-to-date.
-                            forage._dbInfo.db = dbInfo.db;
-                            forage._dbInfo.version = dbInfo.version;
-                          }
-                        }
-                      });
-                  }
-
-                  function getItem(key, callback) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
-                            if (err) {
-                              return reject(err);
-                            }
-
-                            try {
-                              var store = transaction.objectStore(self._dbInfo.storeName);
-                              var req = store.get(key);
-
-                              req.onsuccess = function () {
-                                var value = req.result;
-                                if (value === undefined) {
-                                  value = null;
-                                }
-                                if (_isEncodedBlob(value)) {
-                                  value = _decodeBlob(value);
-                                }
-                                resolve(value);
-                              };
-
-                              req.onerror = function () {
-                                reject(req.error);
-                              };
-                            } catch (e) {
-                              reject(e);
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Iterate over all items stored in database.
-                  function iterate(iterator, callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
-                            if (err) {
-                              return reject(err);
-                            }
-
-                            try {
-                              var store = transaction.objectStore(self._dbInfo.storeName);
-                              var req = store.openCursor();
-                              var iterationNumber = 1;
-
-                              req.onsuccess = function () {
-                                var cursor = req.result;
-
-                                if (cursor) {
-                                  var value = cursor.value;
-                                  if (_isEncodedBlob(value)) {
-                                    value = _decodeBlob(value);
-                                  }
-                                  var result = iterator(value, cursor.key, iterationNumber++);
-
-                                  // when the iterator callback retuns any
-                                  // (non-`undefined`) value, then we stop
-                                  // the iteration immediately
-                                  if (result !== void 0) {
-                                    resolve(result);
-                                  } else {
-                                    cursor["continue"]();
-                                  }
-                                } else {
-                                  resolve();
-                                }
-                              };
-
-                              req.onerror = function () {
-                                reject(req.error);
-                              };
-                            } catch (e) {
-                              reject(e);
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-
-                    return promise;
-                  }
-
-                  function setItem(key, value, callback) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      var dbInfo;
-                      self
-                        .ready()
-                        .then(function () {
-                          dbInfo = self._dbInfo;
-                          if (toString.call(value) === "[object Blob]") {
-                            return _checkBlobSupport(dbInfo.db).then(function (blobSupport) {
-                              if (blobSupport) {
-                                return value;
-                              }
-                              return _encodeBlob(value);
-                            });
-                          }
-                          return value;
-                        })
-                        .then(function (value) {
-                          createTransaction(self._dbInfo, READ_WRITE, function (err, transaction) {
-                            if (err) {
-                              return reject(err);
-                            }
-
-                            try {
-                              var store = transaction.objectStore(self._dbInfo.storeName);
-
-                              // The reason we don't _save_ null is because IE 10 does
-                              // not support saving the `null` type in IndexedDB. How
-                              // ironic, given the bug below!
-                              // See: https://github.com/mozilla/localForage/issues/161
-                              if (value === null) {
-                                value = undefined;
-                              }
-
-                              var req = store.put(value, key);
-
-                              transaction.oncomplete = function () {
-                                // Cast to undefined so the value passed to
-                                // callback/promise is the same as what one would get out
-                                // of `getItem()` later. This leads to some weirdness
-                                // (setItem('foo', undefined) will return `null`), but
-                                // it's not my fault localStorage is our baseline and that
-                                // it's weird.
-                                if (value === undefined) {
-                                  value = null;
-                                }
-
-                                resolve(value);
-                              };
-                              transaction.onabort = transaction.onerror = function () {
-                                var err = req.error ? req.error : req.transaction.error;
-                                reject(err);
-                              };
-                            } catch (e) {
-                              reject(e);
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function removeItem(key, callback) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          createTransaction(self._dbInfo, READ_WRITE, function (err, transaction) {
-                            if (err) {
-                              return reject(err);
-                            }
-
-                            try {
-                              var store = transaction.objectStore(self._dbInfo.storeName);
-                              // We use a Grunt task to make this safe for IE and some
-                              // versions of Android (including those used by Cordova).
-                              // Normally IE won't like `.delete()` and will insist on
-                              // using `['delete']()`, but we have a build step that
-                              // fixes this for us now.
-                              var req = store["delete"](key);
-                              transaction.oncomplete = function () {
-                                resolve();
-                              };
-
-                              transaction.onerror = function () {
-                                reject(req.error);
-                              };
-
-                              // The request will be also be aborted if we've exceeded our storage
-                              // space.
-                              transaction.onabort = function () {
-                                var err = req.error ? req.error : req.transaction.error;
-                                reject(err);
-                              };
-                            } catch (e) {
-                              reject(e);
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function clear(callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          createTransaction(self._dbInfo, READ_WRITE, function (err, transaction) {
-                            if (err) {
-                              return reject(err);
-                            }
-
-                            try {
-                              var store = transaction.objectStore(self._dbInfo.storeName);
-                              var req = store.clear();
-
-                              transaction.oncomplete = function () {
-                                resolve();
-                              };
-
-                              transaction.onabort = transaction.onerror = function () {
-                                var err = req.error ? req.error : req.transaction.error;
-                                reject(err);
-                              };
-                            } catch (e) {
-                              reject(e);
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function length(callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
-                            if (err) {
-                              return reject(err);
-                            }
-
-                            try {
-                              var store = transaction.objectStore(self._dbInfo.storeName);
-                              var req = store.count();
-
-                              req.onsuccess = function () {
-                                resolve(req.result);
-                              };
-
-                              req.onerror = function () {
-                                reject(req.error);
-                              };
-                            } catch (e) {
-                              reject(e);
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function key(n, callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      if (n < 0) {
-                        resolve(null);
-
-                        return;
-                      }
-
-                      self
-                        .ready()
-                        .then(function () {
-                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
-                            if (err) {
-                              return reject(err);
-                            }
-
-                            try {
-                              var store = transaction.objectStore(self._dbInfo.storeName);
-                              var advanced = false;
-                              var req = store.openCursor();
-
-                              req.onsuccess = function () {
-                                var cursor = req.result;
-                                if (!cursor) {
-                                  // this means there weren't enough keys
-                                  resolve(null);
-
-                                  return;
-                                }
-
-                                if (n === 0) {
-                                  // We have the first key, return it if that's what they
-                                  // wanted.
-                                  resolve(cursor.key);
-                                } else {
-                                  if (!advanced) {
-                                    // Otherwise, ask the cursor to skip ahead n
-                                    // records.
-                                    advanced = true;
-                                    cursor.advance(n);
-                                  } else {
-                                    // When we get here, we've got the nth key.
-                                    resolve(cursor.key);
-                                  }
-                                }
-                              };
-
-                              req.onerror = function () {
-                                reject(req.error);
-                              };
-                            } catch (e) {
-                              reject(e);
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function keys(callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
-                            if (err) {
-                              return reject(err);
-                            }
-
-                            try {
-                              var store = transaction.objectStore(self._dbInfo.storeName);
-                              var req = store.openCursor();
-                              var keys = [];
-
-                              req.onsuccess = function () {
-                                var cursor = req.result;
-
-                                if (!cursor) {
-                                  resolve(keys);
-                                  return;
-                                }
-
-                                keys.push(cursor.key);
-                                cursor["continue"]();
-                              };
-
-                              req.onerror = function () {
-                                reject(req.error);
-                              };
-                            } catch (e) {
-                              reject(e);
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function dropInstance(options, callback) {
-                    callback = getCallback.apply(this, arguments);
-
-                    var currentConfig = this.config();
-                    options = (typeof options !== "function" && options) || {};
-                    if (!options.name) {
-                      options.name = options.name || currentConfig.name;
-                      options.storeName = options.storeName || currentConfig.storeName;
-                    }
-
-                    var self = this;
-                    var promise;
-                    if (!options.name) {
-                      promise = Promise$1.reject("Invalid arguments");
-                    } else {
-                      var isCurrentDb = options.name === currentConfig.name && self._dbInfo.db;
-
-                      var dbPromise = isCurrentDb
-                        ? Promise$1.resolve(self._dbInfo.db)
-                        : _getOriginalConnection(options).then(function (db) {
-                            var dbContext = dbContexts[options.name];
-                            var forages = dbContext.forages;
-                            dbContext.db = db;
-                            for (var i = 0; i < forages.length; i++) {
-                              forages[i]._dbInfo.db = db;
-                            }
-                            return db;
-                          });
-
-                      if (!options.storeName) {
-                        promise = dbPromise.then(function (db) {
-                          _deferReadiness(options);
-
-                          var dbContext = dbContexts[options.name];
-                          var forages = dbContext.forages;
-
-                          db.close();
-                          for (var i = 0; i < forages.length; i++) {
-                            var forage = forages[i];
-                            forage._dbInfo.db = null;
-                          }
-
-                          var dropDBPromise = new Promise$1(function (resolve, reject) {
-                            var req = idb.deleteDatabase(options.name);
-
-                            req.onerror = req.onblocked = function (err) {
-                              var db = req.result;
-                              if (db) {
-                                db.close();
-                              }
-                              reject(err);
-                            };
-
-                            req.onsuccess = function () {
-                              var db = req.result;
-                              if (db) {
-                                db.close();
-                              }
-                              resolve(db);
-                            };
-                          });
-
-                          return dropDBPromise
-                            .then(function (db) {
-                              dbContext.db = db;
-                              for (var i = 0; i < forages.length; i++) {
-                                var _forage = forages[i];
-                                _advanceReadiness(_forage._dbInfo);
-                              }
-                            })
-                            ["catch"](function (err) {
-                              (_rejectReadiness(options, err) || Promise$1.resolve())["catch"](
-                                function () {}
-                              );
-                              throw err;
-                            });
-                        });
-                      } else {
-                        promise = dbPromise.then(function (db) {
-                          if (!db.objectStoreNames.contains(options.storeName)) {
-                            return;
-                          }
-
-                          var newVersion = db.version + 1;
-
-                          _deferReadiness(options);
-
-                          var dbContext = dbContexts[options.name];
-                          var forages = dbContext.forages;
-
-                          db.close();
-                          for (var i = 0; i < forages.length; i++) {
-                            var forage = forages[i];
-                            forage._dbInfo.db = null;
-                            forage._dbInfo.version = newVersion;
-                          }
-
-                          var dropObjectPromise = new Promise$1(function (resolve, reject) {
-                            var req = idb.open(options.name, newVersion);
-
-                            req.onerror = function (err) {
-                              var db = req.result;
-                              db.close();
-                              reject(err);
-                            };
-
-                            req.onupgradeneeded = function () {
-                              var db = req.result;
-                              db.deleteObjectStore(options.storeName);
-                            };
-
-                            req.onsuccess = function () {
-                              var db = req.result;
-                              db.close();
-                              resolve(db);
-                            };
-                          });
-
-                          return dropObjectPromise
-                            .then(function (db) {
-                              dbContext.db = db;
-                              for (var j = 0; j < forages.length; j++) {
-                                var _forage2 = forages[j];
-                                _forage2._dbInfo.db = db;
-                                _advanceReadiness(_forage2._dbInfo);
-                              }
-                            })
-                            ["catch"](function (err) {
-                              (_rejectReadiness(options, err) || Promise$1.resolve())["catch"](
-                                function () {}
-                              );
-                              throw err;
-                            });
-                        });
-                      }
-                    }
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  var asyncStorage = {
-                    _driver: "asyncStorage",
-                    _initStorage: _initStorage,
-                    _support: isIndexedDBValid(),
-                    iterate: iterate,
-                    getItem: getItem,
-                    setItem: setItem,
-                    removeItem: removeItem,
-                    clear: clear,
-                    length: length,
-                    key: key,
-                    keys: keys,
-                    dropInstance: dropInstance,
-                  };
-
-                  function isWebSQLValid() {
-                    return typeof openDatabase === "function";
-                  }
-
-                  // Sadly, the best way to save binary data in WebSQL/localStorage is serializing
-                  // it to Base64, so this is how we store it to prevent very strange errors with less
-                  // verbose ways of binary <-> string data storage.
-                  var BASE_CHARS =
-                    "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
-
-                  var BLOB_TYPE_PREFIX = "~~local_forage_type~";
-                  var BLOB_TYPE_PREFIX_REGEX = /^~~local_forage_type~([^~]+)~/;
-
-                  var SERIALIZED_MARKER = "__lfsc__:";
-                  var SERIALIZED_MARKER_LENGTH = SERIALIZED_MARKER.length;
-
-                  // OMG the serializations!
-                  var TYPE_ARRAYBUFFER = "arbf";
-                  var TYPE_BLOB = "blob";
-                  var TYPE_INT8ARRAY = "si08";
-                  var TYPE_UINT8ARRAY = "ui08";
-                  var TYPE_UINT8CLAMPEDARRAY = "uic8";
-                  var TYPE_INT16ARRAY = "si16";
-                  var TYPE_INT32ARRAY = "si32";
-                  var TYPE_UINT16ARRAY = "ur16";
-                  var TYPE_UINT32ARRAY = "ui32";
-                  var TYPE_FLOAT32ARRAY = "fl32";
-                  var TYPE_FLOAT64ARRAY = "fl64";
-                  var TYPE_SERIALIZED_MARKER_LENGTH =
-                    SERIALIZED_MARKER_LENGTH + TYPE_ARRAYBUFFER.length;
-
-                  var toString$1 = Object.prototype.toString;
-
-                  function stringToBuffer(serializedString) {
-                    // Fill the string into a ArrayBuffer.
-                    var bufferLength = serializedString.length * 0.75;
-                    var len = serializedString.length;
-                    var i;
-                    var p = 0;
-                    var encoded1, encoded2, encoded3, encoded4;
-
-                    if (serializedString[serializedString.length - 1] === "=") {
-                      bufferLength--;
-                      if (serializedString[serializedString.length - 2] === "=") {
-                        bufferLength--;
-                      }
-                    }
-
-                    var buffer = new ArrayBuffer(bufferLength);
-                    var bytes = new Uint8Array(buffer);
-
-                    for (i = 0; i < len; i += 4) {
-                      encoded1 = BASE_CHARS.indexOf(serializedString[i]);
-                      encoded2 = BASE_CHARS.indexOf(serializedString[i + 1]);
-                      encoded3 = BASE_CHARS.indexOf(serializedString[i + 2]);
-                      encoded4 = BASE_CHARS.indexOf(serializedString[i + 3]);
-
-                      /*jslint bitwise: true */
-                      bytes[p++] = (encoded1 << 2) | (encoded2 >> 4);
-                      bytes[p++] = ((encoded2 & 15) << 4) | (encoded3 >> 2);
-                      bytes[p++] = ((encoded3 & 3) << 6) | (encoded4 & 63);
-                    }
-                    return buffer;
-                  }
-
-                  // Converts a buffer to a string to store, serialized, in the backend
-                  // storage library.
-                  function bufferToString(buffer) {
-                    // base64-arraybuffer
-                    var bytes = new Uint8Array(buffer);
-                    var base64String = "";
-                    var i;
-
-                    for (i = 0; i < bytes.length; i += 3) {
-                      /*jslint bitwise: true */
-                      base64String += BASE_CHARS[bytes[i] >> 2];
-                      base64String += BASE_CHARS[((bytes[i] & 3) << 4) | (bytes[i + 1] >> 4)];
-                      base64String += BASE_CHARS[((bytes[i + 1] & 15) << 2) | (bytes[i + 2] >> 6)];
-                      base64String += BASE_CHARS[bytes[i + 2] & 63];
-                    }
-
-                    if (bytes.length % 3 === 2) {
-                      base64String = base64String.substring(0, base64String.length - 1) + "=";
-                    } else if (bytes.length % 3 === 1) {
-                      base64String = base64String.substring(0, base64String.length - 2) + "==";
-                    }
-
-                    return base64String;
-                  }
-
-                  // Serialize a value, afterwards executing a callback (which usually
-                  // instructs the `setItem()` callback/promise to be executed). This is how
-                  // we store binary data with localStorage.
-                  function serialize(value, callback) {
-                    var valueType = "";
-                    if (value) {
-                      valueType = toString$1.call(value);
-                    }
-
-                    // Cannot use `value instanceof ArrayBuffer` or such here, as these
-                    // checks fail when running the tests using casper.js...
-                    //
-                    // TODO: See why those tests fail and use a better solution.
-                    if (
-                      value &&
-                      (valueType === "[object ArrayBuffer]" ||
-                        (value.buffer && toString$1.call(value.buffer) === "[object ArrayBuffer]"))
-                    ) {
-                      // Convert binary arrays to a string and prefix the string with
-                      // a special marker.
-                      var buffer;
-                      var marker = SERIALIZED_MARKER;
-
-                      if (value instanceof ArrayBuffer) {
-                        buffer = value;
-                        marker += TYPE_ARRAYBUFFER;
-                      } else {
-                        buffer = value.buffer;
-
-                        if (valueType === "[object Int8Array]") {
-                          marker += TYPE_INT8ARRAY;
-                        } else if (valueType === "[object Uint8Array]") {
-                          marker += TYPE_UINT8ARRAY;
-                        } else if (valueType === "[object Uint8ClampedArray]") {
-                          marker += TYPE_UINT8CLAMPEDARRAY;
-                        } else if (valueType === "[object Int16Array]") {
-                          marker += TYPE_INT16ARRAY;
-                        } else if (valueType === "[object Uint16Array]") {
-                          marker += TYPE_UINT16ARRAY;
-                        } else if (valueType === "[object Int32Array]") {
-                          marker += TYPE_INT32ARRAY;
-                        } else if (valueType === "[object Uint32Array]") {
-                          marker += TYPE_UINT32ARRAY;
-                        } else if (valueType === "[object Float32Array]") {
-                          marker += TYPE_FLOAT32ARRAY;
-                        } else if (valueType === "[object Float64Array]") {
-                          marker += TYPE_FLOAT64ARRAY;
-                        } else {
-                          callback(new Error("Failed to get type for BinaryArray"));
-                        }
-                      }
-
-                      callback(marker + bufferToString(buffer));
-                    } else if (valueType === "[object Blob]") {
-                      // Conver the blob to a binaryArray and then to a string.
-                      var fileReader = new FileReader();
-
-                      fileReader.onload = function () {
-                        // Backwards-compatible prefix for the blob type.
-                        var str = BLOB_TYPE_PREFIX + value.type + "~" + bufferToString(this.result);
-
-                        callback(SERIALIZED_MARKER + TYPE_BLOB + str);
-                      };
-
-                      fileReader.readAsArrayBuffer(value);
-                    } else {
-                      try {
-                        callback(JSON.stringify(value));
-                      } catch (e) {
-                        console.error("Couldn't convert value into a JSON string: ", value);
-
-                        callback(null, e);
-                      }
-                    }
-                  }
-
-                  // Deserialize data we've inserted into a value column/field. We place
-                  // special markers into our strings to mark them as encoded; this isn't
-                  // as nice as a meta field, but it's the only sane thing we can do whilst
-                  // keeping localStorage support intact.
-                  //
-                  // Oftentimes this will just deserialize JSON content, but if we have a
-                  // special marker (SERIALIZED_MARKER, defined above), we will extract
-                  // some kind of arraybuffer/binary data/typed array out of the string.
-                  function deserialize(value) {
-                    // If we haven't marked this string as being specially serialized (i.e.
-                    // something other than serialized JSON), we can just return it and be
-                    // done with it.
-                    if (value.substring(0, SERIALIZED_MARKER_LENGTH) !== SERIALIZED_MARKER) {
-                      return JSON.parse(value);
-                    }
-
-                    // The following code deals with deserializing some kind of Blob or
-                    // TypedArray. First we separate out the type of data we're dealing
-                    // with from the data itself.
-                    var serializedString = value.substring(TYPE_SERIALIZED_MARKER_LENGTH);
-                    var type = value.substring(
-                      SERIALIZED_MARKER_LENGTH,
-                      TYPE_SERIALIZED_MARKER_LENGTH
-                    );
-
-                    var blobType;
-                    // Backwards-compatible blob type serialization strategy.
-                    // DBs created with older versions of localForage will simply not have the blob type.
-                    if (type === TYPE_BLOB && BLOB_TYPE_PREFIX_REGEX.test(serializedString)) {
-                      var matcher = serializedString.match(BLOB_TYPE_PREFIX_REGEX);
-                      blobType = matcher[1];
-                      serializedString = serializedString.substring(matcher[0].length);
-                    }
-                    var buffer = stringToBuffer(serializedString);
-
-                    // Return the right type based on the code/type set during
-                    // serialization.
-                    switch (type) {
-                      case TYPE_ARRAYBUFFER:
-                        return buffer;
-                      case TYPE_BLOB:
-                        return createBlob([buffer], { type: blobType });
-                      case TYPE_INT8ARRAY:
-                        return new Int8Array(buffer);
-                      case TYPE_UINT8ARRAY:
-                        return new Uint8Array(buffer);
-                      case TYPE_UINT8CLAMPEDARRAY:
-                        return new Uint8ClampedArray(buffer);
-                      case TYPE_INT16ARRAY:
-                        return new Int16Array(buffer);
-                      case TYPE_UINT16ARRAY:
-                        return new Uint16Array(buffer);
-                      case TYPE_INT32ARRAY:
-                        return new Int32Array(buffer);
-                      case TYPE_UINT32ARRAY:
-                        return new Uint32Array(buffer);
-                      case TYPE_FLOAT32ARRAY:
-                        return new Float32Array(buffer);
-                      case TYPE_FLOAT64ARRAY:
-                        return new Float64Array(buffer);
-                      default:
-                        throw new Error("Unkown type: " + type);
-                    }
-                  }
-
-                  var localforageSerializer = {
-                    serialize: serialize,
-                    deserialize: deserialize,
-                    stringToBuffer: stringToBuffer,
-                    bufferToString: bufferToString,
-                  };
-
-                  /*
-                   * Includes code from:
-                   *
-                   * base64-arraybuffer
-                   * https://github.com/niklasvh/base64-arraybuffer
-                   *
-                   * Copyright (c) 2012 Niklas von Hertzen
-                   * Licensed under the MIT license.
-                   */
-
-                  function createDbTable(t, dbInfo, callback, errorCallback) {
-                    t.executeSql(
-                      "CREATE TABLE IF NOT EXISTS " +
-                        dbInfo.storeName +
-                        " " +
-                        "(id INTEGER PRIMARY KEY, key unique, value)",
-                      [],
-                      callback,
-                      errorCallback
-                    );
-                  }
-
-                  // Open the WebSQL database (automatically creates one if one didn't
-                  // previously exist), using any options set in the config.
-                  function _initStorage$1(options) {
-                    var self = this;
-                    var dbInfo = {
-                      db: null,
-                    };
-
-                    if (options) {
-                      for (var i in options) {
-                        dbInfo[i] =
-                          typeof options[i] !== "string" ? options[i].toString() : options[i];
-                      }
-                    }
-
-                    var dbInfoPromise = new Promise$1(function (resolve, reject) {
-                      // Open the database; the openDatabase API will automatically
-                      // create it for us if it doesn't exist.
-                      try {
-                        dbInfo.db = openDatabase(
-                          dbInfo.name,
-                          String(dbInfo.version),
-                          dbInfo.description,
-                          dbInfo.size
-                        );
-                      } catch (e) {
-                        return reject(e);
-                      }
-
-                      // Create our key/value table if it doesn't exist.
-                      dbInfo.db.transaction(function (t) {
-                        createDbTable(
-                          t,
-                          dbInfo,
-                          function () {
-                            self._dbInfo = dbInfo;
-                            resolve();
-                          },
-                          function (t, error) {
-                            reject(error);
-                          }
-                        );
-                      }, reject);
-                    });
-
-                    dbInfo.serializer = localforageSerializer;
-                    return dbInfoPromise;
-                  }
-
-                  function tryExecuteSql(t, dbInfo, sqlStatement, args, callback, errorCallback) {
-                    t.executeSql(
-                      sqlStatement,
-                      args,
-                      callback,
-                      function (t, error) {
-                        if (error.code === error.SYNTAX_ERR) {
-                          t.executeSql(
-                            "SELECT name FROM sqlite_master " + "WHERE type='table' AND name = ?",
-                            [dbInfo.storeName],
-                            function (t, results) {
-                              if (!results.rows.length) {
-                                // if the table is missing (was deleted)
-                                // re-create it table and retry
-                                createDbTable(
-                                  t,
-                                  dbInfo,
-                                  function () {
-                                    t.executeSql(sqlStatement, args, callback, errorCallback);
-                                  },
-                                  errorCallback
-                                );
-                              } else {
-                                errorCallback(t, error);
-                              }
-                            },
-                            errorCallback
-                          );
-                        } else {
-                          errorCallback(t, error);
-                        }
-                      },
-                      errorCallback
-                    );
-                  }
-
-                  function getItem$1(key, callback) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          var dbInfo = self._dbInfo;
-                          dbInfo.db.transaction(function (t) {
-                            tryExecuteSql(
-                              t,
-                              dbInfo,
-                              "SELECT * FROM " + dbInfo.storeName + " WHERE key = ? LIMIT 1",
-                              [key],
-                              function (t, results) {
-                                var result = results.rows.length
-                                  ? results.rows.item(0).value
-                                  : null;
-
-                                // Check to see if this is serialized content we need to
-                                // unpack.
-                                if (result) {
-                                  result = dbInfo.serializer.deserialize(result);
-                                }
-
-                                resolve(result);
-                              },
-                              function (t, error) {
-                                reject(error);
-                              }
-                            );
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function iterate$1(iterator, callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          var dbInfo = self._dbInfo;
-
-                          dbInfo.db.transaction(function (t) {
-                            tryExecuteSql(
-                              t,
-                              dbInfo,
-                              "SELECT * FROM " + dbInfo.storeName,
-                              [],
-                              function (t, results) {
-                                var rows = results.rows;
-                                var length = rows.length;
-
-                                for (var i = 0; i < length; i++) {
-                                  var item = rows.item(i);
-                                  var result = item.value;
-
-                                  // Check to see if this is serialized content
-                                  // we need to unpack.
-                                  if (result) {
-                                    result = dbInfo.serializer.deserialize(result);
-                                  }
-
-                                  result = iterator(result, item.key, i + 1);
-
-                                  // void(0) prevents problems with redefinition
-                                  // of `undefined`.
-                                  if (result !== void 0) {
-                                    resolve(result);
-                                    return;
-                                  }
-                                }
-
-                                resolve();
-                              },
-                              function (t, error) {
-                                reject(error);
-                              }
-                            );
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function _setItem(key, value, callback, retriesLeft) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          // The localStorage API doesn't return undefined values in an
-                          // "expected" way, so undefined is always cast to null in all
-                          // drivers. See: https://github.com/mozilla/localForage/pull/42
-                          if (value === undefined) {
-                            value = null;
-                          }
-
-                          // Save the original value to pass to the callback.
-                          var originalValue = value;
-
-                          var dbInfo = self._dbInfo;
-                          dbInfo.serializer.serialize(value, function (value, error) {
-                            if (error) {
-                              reject(error);
-                            } else {
-                              dbInfo.db.transaction(
-                                function (t) {
-                                  tryExecuteSql(
-                                    t,
-                                    dbInfo,
-                                    "INSERT OR REPLACE INTO " +
-                                      dbInfo.storeName +
-                                      " " +
-                                      "(key, value) VALUES (?, ?)",
-                                    [key, value],
-                                    function () {
-                                      resolve(originalValue);
-                                    },
-                                    function (t, error) {
-                                      reject(error);
-                                    }
-                                  );
-                                },
-                                function (sqlError) {
-                                  // The transaction failed; check
-                                  // to see if it's a quota error.
-                                  if (sqlError.code === sqlError.QUOTA_ERR) {
-                                    // We reject the callback outright for now, but
-                                    // it's worth trying to re-run the transaction.
-                                    // Even if the user accepts the prompt to use
-                                    // more storage on Safari, this error will
-                                    // be called.
-                                    //
-                                    // Try to re-run the transaction.
-                                    if (retriesLeft > 0) {
-                                      resolve(
-                                        _setItem.apply(self, [
-                                          key,
-                                          originalValue,
-                                          callback,
-                                          retriesLeft - 1,
-                                        ])
-                                      );
-                                      return;
-                                    }
-                                    reject(sqlError);
-                                  }
-                                }
-                              );
-                            }
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function setItem$1(key, value, callback) {
-                    return _setItem.apply(this, [key, value, callback, 1]);
-                  }
-
-                  function removeItem$1(key, callback) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          var dbInfo = self._dbInfo;
-                          dbInfo.db.transaction(function (t) {
-                            tryExecuteSql(
-                              t,
-                              dbInfo,
-                              "DELETE FROM " + dbInfo.storeName + " WHERE key = ?",
-                              [key],
-                              function () {
-                                resolve();
-                              },
-                              function (t, error) {
-                                reject(error);
-                              }
-                            );
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Deletes every item in the table.
-                  // TODO: Find out if this resets the AUTO_INCREMENT number.
-                  function clear$1(callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          var dbInfo = self._dbInfo;
-                          dbInfo.db.transaction(function (t) {
-                            tryExecuteSql(
-                              t,
-                              dbInfo,
-                              "DELETE FROM " + dbInfo.storeName,
-                              [],
-                              function () {
-                                resolve();
-                              },
-                              function (t, error) {
-                                reject(error);
-                              }
-                            );
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Does a simple `COUNT(key)` to get the number of items stored in
-                  // localForage.
-                  function length$1(callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          var dbInfo = self._dbInfo;
-                          dbInfo.db.transaction(function (t) {
-                            // Ahhh, SQL makes this one soooooo easy.
-                            tryExecuteSql(
-                              t,
-                              dbInfo,
-                              "SELECT COUNT(key) as c FROM " + dbInfo.storeName,
-                              [],
-                              function (t, results) {
-                                var result = results.rows.item(0).c;
-                                resolve(result);
-                              },
-                              function (t, error) {
-                                reject(error);
-                              }
-                            );
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Return the key located at key index X; essentially gets the key from a
-                  // `WHERE id = ?`. This is the most efficient way I can think to implement
-                  // this rarely-used (in my experience) part of the API, but it can seem
-                  // inconsistent, because we do `INSERT OR REPLACE INTO` on `setItem()`, so
-                  // the ID of each key will change every time it's updated. Perhaps a stored
-                  // procedure for the `setItem()` SQL would solve this problem?
-                  // TODO: Don't change ID on `setItem()`.
-                  function key$1(n, callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          var dbInfo = self._dbInfo;
-                          dbInfo.db.transaction(function (t) {
-                            tryExecuteSql(
-                              t,
-                              dbInfo,
-                              "SELECT key FROM " + dbInfo.storeName + " WHERE id = ? LIMIT 1",
-                              [n + 1],
-                              function (t, results) {
-                                var result = results.rows.length ? results.rows.item(0).key : null;
-                                resolve(result);
-                              },
-                              function (t, error) {
-                                reject(error);
-                              }
-                            );
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function keys$1(callback) {
-                    var self = this;
-
-                    var promise = new Promise$1(function (resolve, reject) {
-                      self
-                        .ready()
-                        .then(function () {
-                          var dbInfo = self._dbInfo;
-                          dbInfo.db.transaction(function (t) {
-                            tryExecuteSql(
-                              t,
-                              dbInfo,
-                              "SELECT key FROM " + dbInfo.storeName,
-                              [],
-                              function (t, results) {
-                                var keys = [];
-
-                                for (var i = 0; i < results.rows.length; i++) {
-                                  keys.push(results.rows.item(i).key);
-                                }
-
-                                resolve(keys);
-                              },
-                              function (t, error) {
-                                reject(error);
-                              }
-                            );
-                          });
-                        })
-                        ["catch"](reject);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // https://www.w3.org/TR/webdatabase/#databases
-                  // > There is no way to enumerate or delete the databases available for an origin from this API.
-                  function getAllStoreNames(db) {
-                    return new Promise$1(function (resolve, reject) {
-                      db.transaction(
-                        function (t) {
-                          t.executeSql(
-                            "SELECT name FROM sqlite_master " +
-                              "WHERE type='table' AND name <> '__WebKitDatabaseInfoTable__'",
-                            [],
-                            function (t, results) {
-                              var storeNames = [];
-
-                              for (var i = 0; i < results.rows.length; i++) {
-                                storeNames.push(results.rows.item(i).name);
-                              }
-
-                              resolve({
-                                db: db,
-                                storeNames: storeNames,
-                              });
-                            },
-                            function (t, error) {
-                              reject(error);
-                            }
-                          );
-                        },
-                        function (sqlError) {
-                          reject(sqlError);
-                        }
-                      );
-                    });
-                  }
-
-                  function dropInstance$1(options, callback) {
-                    callback = getCallback.apply(this, arguments);
-
-                    var currentConfig = this.config();
-                    options = (typeof options !== "function" && options) || {};
-                    if (!options.name) {
-                      options.name = options.name || currentConfig.name;
-                      options.storeName = options.storeName || currentConfig.storeName;
-                    }
-
-                    var self = this;
-                    var promise;
-                    if (!options.name) {
-                      promise = Promise$1.reject("Invalid arguments");
-                    } else {
-                      promise = new Promise$1(function (resolve) {
-                        var db;
-                        if (options.name === currentConfig.name) {
-                          // use the db reference of the current instance
-                          db = self._dbInfo.db;
-                        } else {
-                          db = openDatabase(options.name, "", "", 0);
-                        }
-
-                        if (!options.storeName) {
-                          // drop all database tables
-                          resolve(getAllStoreNames(db));
-                        } else {
-                          resolve({
-                            db: db,
-                            storeNames: [options.storeName],
-                          });
-                        }
-                      }).then(function (operationInfo) {
-                        return new Promise$1(function (resolve, reject) {
-                          operationInfo.db.transaction(
-                            function (t) {
-                              function dropTable(storeName) {
-                                return new Promise$1(function (resolve, reject) {
-                                  t.executeSql(
-                                    "DROP TABLE IF EXISTS " + storeName,
-                                    [],
-                                    function () {
-                                      resolve();
-                                    },
-                                    function (t, error) {
-                                      reject(error);
-                                    }
-                                  );
-                                });
-                              }
-
-                              var operations = [];
-                              for (var i = 0, len = operationInfo.storeNames.length; i < len; i++) {
-                                operations.push(dropTable(operationInfo.storeNames[i]));
-                              }
-
-                              Promise$1.all(operations)
-                                .then(function () {
-                                  resolve();
-                                })
-                                ["catch"](function (e) {
-                                  reject(e);
-                                });
-                            },
-                            function (sqlError) {
-                              reject(sqlError);
-                            }
-                          );
-                        });
-                      });
-                    }
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  var webSQLStorage = {
-                    _driver: "webSQLStorage",
-                    _initStorage: _initStorage$1,
-                    _support: isWebSQLValid(),
-                    iterate: iterate$1,
-                    getItem: getItem$1,
-                    setItem: setItem$1,
-                    removeItem: removeItem$1,
-                    clear: clear$1,
-                    length: length$1,
-                    key: key$1,
-                    keys: keys$1,
-                    dropInstance: dropInstance$1,
-                  };
-
-                  function isLocalStorageValid() {
-                    try {
-                      return (
-                        typeof localStorage !== "undefined" &&
-                        "setItem" in localStorage &&
-                        // in IE8 typeof localStorage.setItem === 'object'
-                        !!localStorage.setItem
-                      );
-                    } catch (e) {
-                      return false;
-                    }
-                  }
-
-                  function _getKeyPrefix(options, defaultConfig) {
-                    var keyPrefix = options.name + "/";
-
-                    if (options.storeName !== defaultConfig.storeName) {
-                      keyPrefix += options.storeName + "/";
-                    }
-                    return keyPrefix;
-                  }
-
-                  // Check if localStorage throws when saving an item
-                  function checkIfLocalStorageThrows() {
-                    var localStorageTestKey = "_localforage_support_test";
-
-                    try {
-                      localStorage.setItem(localStorageTestKey, true);
-                      localStorage.removeItem(localStorageTestKey);
-
-                      return false;
-                    } catch (e) {
-                      return true;
-                    }
-                  }
-
-                  // Check if localStorage is usable and allows to save an item
-                  // This method checks if localStorage is usable in Safari Private Browsing
-                  // mode, or in any other case where the available quota for localStorage
-                  // is 0 and there wasn't any saved items yet.
-                  function _isLocalStorageUsable() {
-                    return !checkIfLocalStorageThrows() || localStorage.length > 0;
-                  }
-
-                  // Config the localStorage backend, using options set in the config.
-                  function _initStorage$2(options) {
-                    var self = this;
-                    var dbInfo = {};
-                    if (options) {
-                      for (var i in options) {
-                        dbInfo[i] = options[i];
-                      }
-                    }
-
-                    dbInfo.keyPrefix = _getKeyPrefix(options, self._defaultConfig);
-
-                    if (!_isLocalStorageUsable()) {
-                      return Promise$1.reject();
-                    }
-
-                    self._dbInfo = dbInfo;
-                    dbInfo.serializer = localforageSerializer;
-
-                    return Promise$1.resolve();
-                  }
-
-                  // Remove all keys from the datastore, effectively destroying all data in
-                  // the app's key/value store!
-                  function clear$2(callback) {
-                    var self = this;
-                    var promise = self.ready().then(function () {
-                      var keyPrefix = self._dbInfo.keyPrefix;
-
-                      for (var i = localStorage.length - 1; i >= 0; i--) {
-                        var key = localStorage.key(i);
-
-                        if (key.indexOf(keyPrefix) === 0) {
-                          localStorage.removeItem(key);
-                        }
-                      }
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Retrieve an item from the store. Unlike the original async_storage
-                  // library in Gaia, we don't modify return values at all. If a key's value
-                  // is `undefined`, we pass that value to the callback function.
-                  function getItem$2(key, callback) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = self.ready().then(function () {
-                      var dbInfo = self._dbInfo;
-                      var result = localStorage.getItem(dbInfo.keyPrefix + key);
-
-                      // If a result was found, parse it from the serialized
-                      // string into a JS object. If result isn't truthy, the key
-                      // is likely undefined and we'll pass it straight to the
-                      // callback.
-                      if (result) {
-                        result = dbInfo.serializer.deserialize(result);
-                      }
-
-                      return result;
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Iterate over all items in the store.
-                  function iterate$2(iterator, callback) {
-                    var self = this;
-
-                    var promise = self.ready().then(function () {
-                      var dbInfo = self._dbInfo;
-                      var keyPrefix = dbInfo.keyPrefix;
-                      var keyPrefixLength = keyPrefix.length;
-                      var length = localStorage.length;
-
-                      // We use a dedicated iterator instead of the `i` variable below
-                      // so other keys we fetch in localStorage aren't counted in
-                      // the `iterationNumber` argument passed to the `iterate()`
-                      // callback.
-                      //
-                      // See: github.com/mozilla/localForage/pull/435#discussion_r38061530
-                      var iterationNumber = 1;
-
-                      for (var i = 0; i < length; i++) {
-                        var key = localStorage.key(i);
-                        if (key.indexOf(keyPrefix) !== 0) {
-                          continue;
-                        }
-                        var value = localStorage.getItem(key);
-
-                        // If a result was found, parse it from the serialized
-                        // string into a JS object. If result isn't truthy, the
-                        // key is likely undefined and we'll pass it straight
-                        // to the iterator.
-                        if (value) {
-                          value = dbInfo.serializer.deserialize(value);
-                        }
-
-                        value = iterator(value, key.substring(keyPrefixLength), iterationNumber++);
-
-                        if (value !== void 0) {
-                          return value;
-                        }
-                      }
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Same as localStorage's key() method, except takes a callback.
-                  function key$2(n, callback) {
-                    var self = this;
-                    var promise = self.ready().then(function () {
-                      var dbInfo = self._dbInfo;
-                      var result;
-                      try {
-                        result = localStorage.key(n);
-                      } catch (error) {
-                        result = null;
-                      }
-
-                      // Remove the prefix from the key, if a key is found.
-                      if (result) {
-                        result = result.substring(dbInfo.keyPrefix.length);
-                      }
-
-                      return result;
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function keys$2(callback) {
-                    var self = this;
-                    var promise = self.ready().then(function () {
-                      var dbInfo = self._dbInfo;
-                      var length = localStorage.length;
-                      var keys = [];
-
-                      for (var i = 0; i < length; i++) {
-                        var itemKey = localStorage.key(i);
-                        if (itemKey.indexOf(dbInfo.keyPrefix) === 0) {
-                          keys.push(itemKey.substring(dbInfo.keyPrefix.length));
-                        }
-                      }
-
-                      return keys;
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Supply the number of keys in the datastore to the callback function.
-                  function length$2(callback) {
-                    var self = this;
-                    var promise = self.keys().then(function (keys) {
-                      return keys.length;
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Remove an item from the store, nice and simple.
-                  function removeItem$2(key, callback) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = self.ready().then(function () {
-                      var dbInfo = self._dbInfo;
-                      localStorage.removeItem(dbInfo.keyPrefix + key);
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  // Set a key's value and run an optional callback once the value is set.
-                  // Unlike Gaia's implementation, the callback function is passed the value,
-                  // in case you want to operate on that value only after you're sure it
-                  // saved, or something like that.
-                  function setItem$2(key, value, callback) {
-                    var self = this;
-
-                    key = normalizeKey(key);
-
-                    var promise = self.ready().then(function () {
-                      // Convert undefined values to null.
-                      // https://github.com/mozilla/localForage/pull/42
-                      if (value === undefined) {
-                        value = null;
-                      }
-
-                      // Save the original value to pass to the callback.
-                      var originalValue = value;
-
-                      return new Promise$1(function (resolve, reject) {
-                        var dbInfo = self._dbInfo;
-                        dbInfo.serializer.serialize(value, function (value, error) {
-                          if (error) {
-                            reject(error);
-                          } else {
-                            try {
-                              localStorage.setItem(dbInfo.keyPrefix + key, value);
-                              resolve(originalValue);
-                            } catch (e) {
-                              // localStorage capacity exceeded.
-                              // TODO: Make this a specific error/event.
-                              if (
-                                e.name === "QuotaExceededError" ||
-                                e.name === "NS_ERROR_DOM_QUOTA_REACHED"
-                              ) {
-                                reject(e);
-                              }
-                              reject(e);
-                            }
-                          }
-                        });
-                      });
-                    });
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  function dropInstance$2(options, callback) {
-                    callback = getCallback.apply(this, arguments);
-
-                    options = (typeof options !== "function" && options) || {};
-                    if (!options.name) {
-                      var currentConfig = this.config();
-                      options.name = options.name || currentConfig.name;
-                      options.storeName = options.storeName || currentConfig.storeName;
-                    }
-
-                    var self = this;
-                    var promise;
-                    if (!options.name) {
-                      promise = Promise$1.reject("Invalid arguments");
-                    } else {
-                      promise = new Promise$1(function (resolve) {
-                        if (!options.storeName) {
-                          resolve(options.name + "/");
-                        } else {
-                          resolve(_getKeyPrefix(options, self._defaultConfig));
-                        }
-                      }).then(function (keyPrefix) {
-                        for (var i = localStorage.length - 1; i >= 0; i--) {
-                          var key = localStorage.key(i);
-
-                          if (key.indexOf(keyPrefix) === 0) {
-                            localStorage.removeItem(key);
-                          }
-                        }
-                      });
-                    }
-
-                    executeCallback(promise, callback);
-                    return promise;
-                  }
-
-                  var localStorageWrapper = {
-                    _driver: "localStorageWrapper",
-                    _initStorage: _initStorage$2,
-                    _support: isLocalStorageValid(),
-                    iterate: iterate$2,
-                    getItem: getItem$2,
-                    setItem: setItem$2,
-                    removeItem: removeItem$2,
-                    clear: clear$2,
-                    length: length$2,
-                    key: key$2,
-                    keys: keys$2,
-                    dropInstance: dropInstance$2,
-                  };
-
-                  var sameValue = function sameValue(x, y) {
-                    return (
-                      x === y ||
-                      (typeof x === "number" && typeof y === "number" && isNaN(x) && isNaN(y))
-                    );
-                  };
-
-                  var includes = function includes(array, searchElement) {
-                    var len = array.length;
-                    var i = 0;
-                    while (i < len) {
-                      if (sameValue(array[i], searchElement)) {
-                        return true;
-                      }
-                      i++;
-                    }
-
-                    return false;
-                  };
-
-                  var isArray =
-                    Array.isArray ||
-                    function (arg) {
-                      return Object.prototype.toString.call(arg) === "[object Array]";
-                    };
-
-                  // Drivers are stored here when `defineDriver()` is called.
-                  // They are shared across all instances of localForage.
-                  var DefinedDrivers = {};
-
-                  var DriverSupport = {};
-
-                  var DefaultDrivers = {
-                    INDEXEDDB: asyncStorage,
-                    WEBSQL: webSQLStorage,
-                    LOCALSTORAGE: localStorageWrapper,
-                  };
-
-                  var DefaultDriverOrder = [
-                    DefaultDrivers.INDEXEDDB._driver,
-                    DefaultDrivers.WEBSQL._driver,
-                    DefaultDrivers.LOCALSTORAGE._driver,
-                  ];
-
-                  var OptionalDriverMethods = ["dropInstance"];
-
-                  var LibraryMethods = [
-                    "clear",
-                    "getItem",
-                    "iterate",
-                    "key",
-                    "keys",
-                    "length",
-                    "removeItem",
-                    "setItem",
-                  ].concat(OptionalDriverMethods);
-
-                  var DefaultConfig = {
-                    description: "",
-                    driver: DefaultDriverOrder.slice(),
-                    name: "localforage",
-                    // Default DB size is _JUST UNDER_ 5MB, as it's the highest size
-                    // we can use without a prompt.
-                    size: 4980736,
-                    storeName: "keyvaluepairs",
-                    version: 1.0,
-                  };
-
-                  function callWhenReady(localForageInstance, libraryMethod) {
-                    localForageInstance[libraryMethod] = function () {
-                      var _args = arguments;
-                      return localForageInstance.ready().then(function () {
-                        return localForageInstance[libraryMethod].apply(localForageInstance, _args);
-                      });
-                    };
-                  }
-
-                  function extend() {
-                    for (var i = 1; i < arguments.length; i++) {
-                      var arg = arguments[i];
-
-                      if (arg) {
-                        for (var _key in arg) {
-                          if (arg.hasOwnProperty(_key)) {
-                            if (isArray(arg[_key])) {
-                              arguments[0][_key] = arg[_key].slice();
-                            } else {
-                              arguments[0][_key] = arg[_key];
-                            }
-                          }
-                        }
-                      }
-                    }
-
-                    return arguments[0];
-                  }
-
-                  var LocalForage = (function () {
-                    function LocalForage(options) {
-                      _classCallCheck(this, LocalForage);
-
-                      for (var driverTypeKey in DefaultDrivers) {
-                        if (DefaultDrivers.hasOwnProperty(driverTypeKey)) {
-                          var driver = DefaultDrivers[driverTypeKey];
-                          var driverName = driver._driver;
-                          this[driverTypeKey] = driverName;
-
-                          if (!DefinedDrivers[driverName]) {
-                            // we don't need to wait for the promise,
-                            // since the default drivers can be defined
-                            // in a blocking manner
-                            this.defineDriver(driver);
-                          }
-                        }
-                      }
-
-                      this._defaultConfig = extend({}, DefaultConfig);
-                      this._config = extend({}, this._defaultConfig, options);
-                      this._driverSet = null;
-                      this._initDriver = null;
-                      this._ready = false;
-                      this._dbInfo = null;
-
-                      this._wrapLibraryMethodsWithReady();
-                      this.setDriver(this._config.driver)["catch"](function () {});
-                    }
-
-                    // Set any config values for localForage; can be called anytime before
-                    // the first API call (e.g. `getItem`, `setItem`).
-                    // We loop through options so we don't overwrite existing config
-                    // values.
-
-                    LocalForage.prototype.config = function config(options) {
-                      // If the options argument is an object, we use it to set values.
-                      // Otherwise, we return either a specified config value or all
-                      // config values.
-                      if (
-                        (typeof options === "undefined" ? "undefined" : _typeof(options)) ===
-                        "object"
-                      ) {
-                        // If localforage is ready and fully initialized, we can't set
-                        // any new configuration values. Instead, we return an error.
-                        if (this._ready) {
-                          return new Error(
-                            "Can't call config() after localforage " + "has been used."
-                          );
-                        }
-
-                        for (var i in options) {
-                          if (i === "storeName") {
-                            options[i] = options[i].replace(/\W/g, "_");
-                          }
-
-                          if (i === "version" && typeof options[i] !== "number") {
-                            return new Error("Database version must be a number.");
-                          }
-
-                          this._config[i] = options[i];
-                        }
-
-                        // after all config options are set and
-                        // the driver option is used, try setting it
-                        if ("driver" in options && options.driver) {
-                          return this.setDriver(this._config.driver);
-                        }
-
-                        return true;
-                      } else if (typeof options === "string") {
-                        return this._config[options];
-                      } else {
-                        return this._config;
-                      }
-                    };
-
-                    // Used to define a custom driver, shared across all instances of
-                    // localForage.
-
-                    LocalForage.prototype.defineDriver = function defineDriver(
-                      driverObject,
-                      callback,
-                      errorCallback
-                    ) {
-                      var promise = new Promise$1(function (resolve, reject) {
-                        try {
-                          var driverName = driverObject._driver;
-                          var complianceError = new Error(
-                            "Custom driver not compliant; see " +
-                              "https://mozilla.github.io/localForage/#definedriver"
-                          );
-
-                          // A driver name should be defined and not overlap with the
-                          // library-defined, default drivers.
-                          if (!driverObject._driver) {
-                            reject(complianceError);
-                            return;
-                          }
-
-                          var driverMethods = LibraryMethods.concat("_initStorage");
-                          for (var i = 0, len = driverMethods.length; i < len; i++) {
-                            var driverMethodName = driverMethods[i];
-
-                            // when the property is there,
-                            // it should be a method even when optional
-                            var isRequired = !includes(OptionalDriverMethods, driverMethodName);
-                            if (
-                              (isRequired || driverObject[driverMethodName]) &&
-                              typeof driverObject[driverMethodName] !== "function"
-                            ) {
-                              reject(complianceError);
-                              return;
-                            }
-                          }
-
-                          var configureMissingMethods = function configureMissingMethods() {
-                            var methodNotImplementedFactory = function methodNotImplementedFactory(
-                              methodName
-                            ) {
-                              return function () {
-                                var error = new Error(
-                                  "Method " +
-                                    methodName +
-                                    " is not implemented by the current driver"
-                                );
-                                var promise = Promise$1.reject(error);
-                                executeCallback(promise, arguments[arguments.length - 1]);
-                                return promise;
-                              };
-                            };
-
-                            for (var _i = 0, _len = OptionalDriverMethods.length; _i < _len; _i++) {
-                              var optionalDriverMethod = OptionalDriverMethods[_i];
-                              if (!driverObject[optionalDriverMethod]) {
-                                driverObject[optionalDriverMethod] =
-                                  methodNotImplementedFactory(optionalDriverMethod);
-                              }
-                            }
-                          };
-
-                          configureMissingMethods();
-
-                          var setDriverSupport = function setDriverSupport(support) {
-                            if (DefinedDrivers[driverName]) {
-                              console.info("Redefining LocalForage driver: " + driverName);
-                            }
-                            DefinedDrivers[driverName] = driverObject;
-                            DriverSupport[driverName] = support;
-                            // don't use a then, so that we can define
-                            // drivers that have simple _support methods
-                            // in a blocking manner
-                            resolve();
-                          };
-
-                          if ("_support" in driverObject) {
-                            if (
-                              driverObject._support &&
-                              typeof driverObject._support === "function"
-                            ) {
-                              driverObject._support().then(setDriverSupport, reject);
-                            } else {
-                              setDriverSupport(!!driverObject._support);
-                            }
-                          } else {
-                            setDriverSupport(true);
-                          }
-                        } catch (e) {
-                          reject(e);
-                        }
-                      });
-
-                      executeTwoCallbacks(promise, callback, errorCallback);
-                      return promise;
-                    };
-
-                    LocalForage.prototype.driver = function driver() {
-                      return this._driver || null;
-                    };
-
-                    LocalForage.prototype.getDriver = function getDriver(
-                      driverName,
-                      callback,
-                      errorCallback
-                    ) {
-                      var getDriverPromise = DefinedDrivers[driverName]
-                        ? Promise$1.resolve(DefinedDrivers[driverName])
-                        : Promise$1.reject(new Error("Driver not found."));
-
-                      executeTwoCallbacks(getDriverPromise, callback, errorCallback);
-                      return getDriverPromise;
-                    };
-
-                    LocalForage.prototype.getSerializer = function getSerializer(callback) {
-                      var serializerPromise = Promise$1.resolve(localforageSerializer);
-                      executeTwoCallbacks(serializerPromise, callback);
-                      return serializerPromise;
-                    };
-
-                    LocalForage.prototype.ready = function ready(callback) {
-                      var self = this;
-
-                      var promise = self._driverSet.then(function () {
-                        if (self._ready === null) {
-                          self._ready = self._initDriver();
-                        }
-
-                        return self._ready;
-                      });
-
-                      executeTwoCallbacks(promise, callback, callback);
-                      return promise;
-                    };
-
-                    LocalForage.prototype.setDriver = function setDriver(
-                      drivers,
-                      callback,
-                      errorCallback
-                    ) {
-                      var self = this;
-
-                      if (!isArray(drivers)) {
-                        drivers = [drivers];
-                      }
-
-                      var supportedDrivers = this._getSupportedDrivers(drivers);
-
-                      function setDriverToConfig() {
-                        self._config.driver = self.driver();
-                      }
-
-                      function extendSelfWithDriver(driver) {
-                        self._extend(driver);
-                        setDriverToConfig();
-
-                        self._ready = self._initStorage(self._config);
-                        return self._ready;
-                      }
-
-                      function initDriver(supportedDrivers) {
-                        return function () {
-                          var currentDriverIndex = 0;
-
-                          function driverPromiseLoop() {
-                            while (currentDriverIndex < supportedDrivers.length) {
-                              var driverName = supportedDrivers[currentDriverIndex];
-                              currentDriverIndex++;
-
-                              self._dbInfo = null;
-                              self._ready = null;
-
-                              return self
-                                .getDriver(driverName)
-                                .then(extendSelfWithDriver)
-                                ["catch"](driverPromiseLoop);
-                            }
-
-                            setDriverToConfig();
-                            var error = new Error("No available storage method found.");
-                            self._driverSet = Promise$1.reject(error);
-                            return self._driverSet;
-                          }
-
-                          return driverPromiseLoop();
-                        };
-                      }
-
-                      // There might be a driver initialization in progress
-                      // so wait for it to finish in order to avoid a possible
-                      // race condition to set _dbInfo
-                      var oldDriverSetDone =
-                        this._driverSet !== null
-                          ? this._driverSet["catch"](function () {
-                              return Promise$1.resolve();
-                            })
-                          : Promise$1.resolve();
-
-                      this._driverSet = oldDriverSetDone
-                        .then(function () {
-                          var driverName = supportedDrivers[0];
-                          self._dbInfo = null;
-                          self._ready = null;
-
-                          return self.getDriver(driverName).then(function (driver) {
-                            self._driver = driver._driver;
-                            setDriverToConfig();
-                            self._wrapLibraryMethodsWithReady();
-                            self._initDriver = initDriver(supportedDrivers);
-                          });
-                        })
-                        ["catch"](function () {
-                          setDriverToConfig();
-                          var error = new Error("No available storage method found.");
-                          self._driverSet = Promise$1.reject(error);
-                          return self._driverSet;
-                        });
-
-                      executeTwoCallbacks(this._driverSet, callback, errorCallback);
-                      return this._driverSet;
-                    };
-
-                    LocalForage.prototype.supports = function supports(driverName) {
-                      return !!DriverSupport[driverName];
-                    };
-
-                    LocalForage.prototype._extend = function _extend(libraryMethodsAndProperties) {
-                      extend(this, libraryMethodsAndProperties);
-                    };
-
-                    LocalForage.prototype._getSupportedDrivers = function _getSupportedDrivers(
-                      drivers
-                    ) {
-                      var supportedDrivers = [];
-                      for (var i = 0, len = drivers.length; i < len; i++) {
-                        var driverName = drivers[i];
-                        if (this.supports(driverName)) {
-                          supportedDrivers.push(driverName);
-                        }
-                      }
-                      return supportedDrivers;
-                    };
-
-                    LocalForage.prototype._wrapLibraryMethodsWithReady =
-                      function _wrapLibraryMethodsWithReady() {
-                        // Add a stub for each driver API method that delays the call to the
-                        // corresponding driver method until localForage is ready. These stubs
-                        // will be replaced by the driver methods as soon as the driver is
-                        // loaded, so there is no performance impact.
-                        for (var i = 0, len = LibraryMethods.length; i < len; i++) {
-                          callWhenReady(this, LibraryMethods[i]);
-                        }
-                      };
-
-                    LocalForage.prototype.createInstance = function createInstance(options) {
-                      return new LocalForage(options);
-                    };
-
-                    return LocalForage;
-                  })();
-
-                  // The actual localForage object that we expose as a module or via a
-                  // global. It's extended by pulling in one of our other libraries.
-
-                  var localforage_js = new LocalForage();
-
-                  module.exports = localforage_js;
-                },
-                { 3: 3 },
-              ],
-            },
-            {},
-            [4]
-          )(4);
-        });
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(27)));
-
-      /***/
-    },
-    /* 33 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (global, process) {
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
-          return getGlobalNamespace;
-        });
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-          return getGlobal;
-        });
-        /**
-         * @license
-         * Copyright 2020 Google Inc. All Rights Reserved.
-         * Licensed under the Apache License, Version 2.0 (the "License");
-         * you may not use this file except in compliance with the License.
-         * You may obtain a copy of the License at
-         *
-         * http://www.apache.org/licenses/LICENSE-2.0
-         *
-         * Unless required by applicable law or agreed to in writing, software
-         * distributed under the License is distributed on an "AS IS" BASIS,
-         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-         * See the License for the specific language governing permissions and
-         * limitations under the License.
-         * =============================================================================
-         */
-        // Note that the identifier globalNameSpace is scoped to this module, but will
-        // always resolve to the same global object regardless of how the module is
-        // resolved.
-        // tslint:disable-next-line:no-any
-        let globalNameSpace;
-        // tslint:disable-next-line:no-any
-        function getGlobalNamespace() {
-          if (globalNameSpace == null) {
-            // tslint:disable-next-line:no-any
-            let ns;
-            if (typeof window !== "undefined") {
-              ns = window;
-            } else if (typeof global !== "undefined") {
-              ns = global;
-            } else if (typeof process !== "undefined") {
-              ns = process;
-            } else if (typeof self !== "undefined") {
-              ns = self;
-            } else {
-              throw new Error("Could not find a global object");
-            }
-            globalNameSpace = ns;
-          }
-          return globalNameSpace;
-        }
-        // tslint:disable-next-line:no-any
-        function getGlobalMap() {
-          const ns = getGlobalNamespace();
-          if (ns._tfGlobals == null) {
-            ns._tfGlobals = new Map();
-          }
-          return ns._tfGlobals;
-        }
-        /**
-         * Returns a globally accessible 'singleton' object.
-         *
-         * @param key the name of the object
-         * @param init a function to initialize to initialize this object
-         *             the first time it is fetched.
-         */
-        function getGlobal(key, init) {
-          const globalMap = getGlobalMap();
-          if (globalMap.has(key)) {
-            return globalMap.get(key);
-          } else {
-            const singleton = init();
-            globalMap.set(key, singleton);
-            return globalMap.get(key);
-          }
-        }
-        //# sourceMappingURL=global_util.js.map
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(27), __webpack_require__(35)));
-
-      /***/
-    },
-    /* 34 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return DTYPE_VALUE_SIZE_MAP;
-      });
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /* Type definitions for exporting and importing of models. */
-      /**
-       * A map from Tensor dtype to number of bytes per element of the Tensor.
-       */
-      const DTYPE_VALUE_SIZE_MAP = {
-        float32: 4,
-        float16: 2,
-        int32: 4,
-        uint16: 2,
-        uint8: 1,
-        bool: 1,
-        complex64: 8,
-      };
-      //# sourceMappingURL=types.js.map
-
-      /***/
-    },
-    /* 35 */
-    /***/ function (module, exports) {
-      // shim for using process in browser
-      var process = (module.exports = {});
-
-      // cached from whatever global is present so that test runners that stub it
-      // don't break things.  But we need to wrap it in a try catch in case it is
-      // wrapped in strict mode code which doesn't define any globals.  It's inside a
-      // function because try/catches deoptimize in certain engines.
-
-      var cachedSetTimeout;
-      var cachedClearTimeout;
-
-      function defaultSetTimout() {
-        throw new Error("setTimeout has not been defined");
-      }
-      function defaultClearTimeout() {
-        throw new Error("clearTimeout has not been defined");
-      }
-      (function () {
-        try {
-          if (typeof setTimeout === "function") {
-            cachedSetTimeout = setTimeout;
-          } else {
-            cachedSetTimeout = defaultSetTimout;
-          }
-        } catch (e) {
-          cachedSetTimeout = defaultSetTimout;
-        }
-        try {
-          if (typeof clearTimeout === "function") {
-            cachedClearTimeout = clearTimeout;
-          } else {
-            cachedClearTimeout = defaultClearTimeout;
-          }
-        } catch (e) {
-          cachedClearTimeout = defaultClearTimeout;
-        }
-      })();
-      function runTimeout(fun) {
-        if (cachedSetTimeout === setTimeout) {
-          //normal enviroments in sane situations
-          return setTimeout(fun, 0);
-        }
-        // if setTimeout wasn't available but was latter defined
-        if ((cachedSetTimeout === defaultSetTimout || !cachedSetTimeout) && setTimeout) {
-          cachedSetTimeout = setTimeout;
-          return setTimeout(fun, 0);
-        }
-        try {
-          // when when somebody has screwed with setTimeout but no I.E. maddness
-          return cachedSetTimeout(fun, 0);
-        } catch (e) {
-          try {
-            // When we are in I.E. but the script has been evaled so I.E. doesn't trust the global object when called normally
-            return cachedSetTimeout.call(null, fun, 0);
-          } catch (e) {
-            // same as above but when it's a version of I.E. that must have the global object for 'this', hopfully our context correct otherwise it will throw a global error
-            return cachedSetTimeout.call(this, fun, 0);
-          }
-        }
-      }
-      function runClearTimeout(marker) {
-        if (cachedClearTimeout === clearTimeout) {
-          //normal enviroments in sane situations
-          return clearTimeout(marker);
-        }
-        // if clearTimeout wasn't available but was latter defined
-        if ((cachedClearTimeout === defaultClearTimeout || !cachedClearTimeout) && clearTimeout) {
-          cachedClearTimeout = clearTimeout;
-          return clearTimeout(marker);
-        }
-        try {
-          // when when somebody has screwed with setTimeout but no I.E. maddness
-          return cachedClearTimeout(marker);
-        } catch (e) {
-          try {
-            // When we are in I.E. but the script has been evaled so I.E. doesn't  trust the global object when called normally
-            return cachedClearTimeout.call(null, marker);
-          } catch (e) {
-            // same as above but when it's a version of I.E. that must have the global object for 'this', hopfully our context correct otherwise it will throw a global error.
-            // Some versions of I.E. have different rules for clearTimeout vs setTimeout
-            return cachedClearTimeout.call(this, marker);
-          }
-        }
-      }
-      var queue = [];
-      var draining = false;
-      var currentQueue;
-      var queueIndex = -1;
-
-      function cleanUpNextTick() {
-        if (!draining || !currentQueue) {
-          return;
-        }
-        draining = false;
-        if (currentQueue.length) {
-          queue = currentQueue.concat(queue);
-        } else {
-          queueIndex = -1;
-        }
-        if (queue.length) {
-          drainQueue();
-        }
-      }
-
-      function drainQueue() {
-        if (draining) {
-          return;
-        }
-        var timeout = runTimeout(cleanUpNextTick);
-        draining = true;
-
-        var len = queue.length;
-        while (len) {
-          currentQueue = queue;
-          queue = [];
-          while (++queueIndex < len) {
-            if (currentQueue) {
-              currentQueue[queueIndex].run();
-            }
-          }
-          queueIndex = -1;
-          len = queue.length;
-        }
-        currentQueue = null;
-        draining = false;
-        runClearTimeout(timeout);
-      }
-
-      process.nextTick = function (fun) {
-        var args = new Array(arguments.length - 1);
-        if (arguments.length > 1) {
-          for (var i = 1; i < arguments.length; i++) {
-            args[i - 1] = arguments[i];
-          }
-        }
-        queue.push(new Item(fun, args));
-        if (queue.length === 1 && !draining) {
-          runTimeout(drainQueue);
-        }
-      };
-
-      // v8 likes predictible objects
-      function Item(fun, array) {
-        this.fun = fun;
-        this.array = array;
-      }
-      Item.prototype.run = function () {
-        this.fun.apply(null, this.array);
-      };
-      process.title = "browser";
-      process.browser = true;
-      process.env = {};
-      process.argv = [];
-      process.version = ""; // empty string to avoid regexp issues
-      process.versions = {};
-
-      function noop() {}
-
-      process.on = noop;
-      process.addListener = noop;
-      process.once = noop;
-      process.off = noop;
-      process.removeListener = noop;
-      process.removeAllListeners = noop;
-      process.emit = noop;
-      process.prependListener = noop;
-      process.prependOnceListener = noop;
-
-      process.listeners = function (name) {
-        return [];
-      };
-
-      process.binding = function (name) {
-        throw new Error("process.binding is not supported");
-      };
-
-      process.cwd = function () {
-        return "/";
-      };
-      process.chdir = function (dir) {
-        throw new Error("process.chdir is not supported");
-      };
-      process.umask = function () {
-        return 0;
-      };
-
-      /***/
-    },
-    /* 36 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isMobile",
-        function () {
-          return isMobile;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "isBrowser",
-        function () {
-          return isBrowser;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // tslint:disable-next-line:no-any
-      function _isNavigatorDefined() {
-        return typeof navigator !== "undefined" && navigator != null;
-      }
-      function isMobile() {
-        if (_isNavigatorDefined()) {
-          // tslint:disable-next-line:no-any
-          const a = navigator.userAgent || navigator.vendor || window.opera;
-          // tslint:disable-next-line:max-line-length
-          return (
-            /(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(
-              a
-            ) ||
-            // tslint:disable-next-line:max-line-length
-            /1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(
-              a.substr(0, 4)
-            )
-          );
-        }
-        return false;
-      }
-      function isBrowser() {
-        return (
-          (typeof window !== "undefined" && window.document != null) ||
-          //@ts-ignore
-          typeof WorkerGlobalScope !== "undefined"
-        );
-      }
-      //# sourceMappingURL=device_util.js.map
-
-      /***/
-    },
-    /* 37 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return maxImpl;
-      });
-      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
-        __webpack_require__(0);
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function maxImpl(aVals, reduceSize, outShape, dtype) {
-        const vals = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__[
-          "util"
-        ].getTypedArrayFromDType(
-          dtype,
-          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].sizeFromShape(outShape)
-        );
-        for (let i = 0; i < vals.length; ++i) {
-          const offset = i * reduceSize;
-          let max = aVals[offset];
-          for (let j = 0; j < reduceSize; ++j) {
-            const value = aVals[offset + j];
-            if (value > max) {
-              max = value;
-            }
-          }
-          vals[i] = max;
-        }
-        return vals;
-      }
-      //# sourceMappingURL=Max_impl.js.map
-
-      /***/
-    },
-    /* 38 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      // ESM COMPAT FLAG
-      __webpack_require__.r(__webpack_exports__);
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "GraphModel", function () {
-        return /* reexport */ graph_model_GraphModel;
-      });
-      __webpack_require__.d(__webpack_exports__, "loadGraphModel", function () {
-        return /* reexport */ loadGraphModel;
-      });
-      __webpack_require__.d(__webpack_exports__, "deregisterOp", function () {
-        return /* reexport */ register["a" /* deregisterOp */];
-      });
-      __webpack_require__.d(__webpack_exports__, "registerOp", function () {
-        return /* reexport */ register["c" /* registerOp */];
-      });
-      __webpack_require__.d(__webpack_exports__, "version_converter", function () {
-        return /* reexport */ version;
-      });
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
-      var dist = __webpack_require__(0);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/operation_mapper.js
-      var operation_mapper = __webpack_require__(15);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/utils.js
-      var utils = __webpack_require__(2);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/custom_op/node_value_impl.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Helper class for lookup inputs and params for nodes in the model graph.
-       */
-      class node_value_impl_NodeValueImpl {
-        constructor(node, tensorMap, context) {
-          this.node = node;
-          this.tensorMap = tensorMap;
-          this.context = context;
-          this.inputs = [];
-          this.attrs = {};
-          this.inputs = node.inputNames.map((name) => this.getInput(name));
-          if (node.rawAttrs != null) {
-            this.attrs = Object.keys(node.rawAttrs).reduce((attrs, key) => {
-              attrs[key] = this.getAttr(key);
-              return attrs;
-            }, {});
-          }
-        }
-        /**
-         * Return the value of the attribute or input param.
-         * @param name String: name of attribute or input param.
-         */
-        getInput(name) {
-          return Object(utils["c" /* getTensor */])(name, this.tensorMap, this.context);
-        }
-        /**
-         * Return the value of the attribute or input param.
-         * @param name String: name of attribute or input param.
-         */
-        getAttr(name, defaultValue) {
-          const value = this.node.rawAttrs[name];
-          if (value.tensor != null) {
-            return Object(utils["c" /* getTensor */])(name, this.tensorMap, this.context);
-          }
-          if (value.i != null || value.f != null) {
-            return Object(operation_mapper["f" /* getNumberParam */])(
-              this.node.rawAttrs,
-              name,
-              defaultValue
-            );
-          }
-          if (value.s != null) {
-            return Object(operation_mapper["i" /* getStringParam */])(
-              this.node.rawAttrs,
-              name,
-              defaultValue
-            );
-          }
-          if (value.b != null) {
-            return Object(operation_mapper["c" /* getBoolParam */])(
-              this.node.rawAttrs,
-              name,
-              defaultValue
-            );
-          }
-          if (value.shape != null) {
-            return Object(operation_mapper["k" /* getTensorShapeParam */])(
-              this.node.rawAttrs,
-              name,
-              defaultValue
-            );
-          }
-          if (value.type != null) {
-            return Object(operation_mapper["e" /* getDtypeParam */])(
-              this.node.rawAttrs,
-              name,
-              defaultValue
-            );
-          }
-          if (value.list != null) {
-            if (value.list.i != null || value.list.f != null) {
-              return Object(operation_mapper["g" /* getNumericArrayParam */])(
-                this.node.rawAttrs,
-                name,
-                defaultValue
-              );
-            }
-            if (value.list.s != null) {
-              return Object(operation_mapper["h" /* getStringArrayParam */])(
-                this.node.rawAttrs,
-                name,
-                defaultValue
-              );
-            }
-            if (value.list.shape != null) {
-              return Object(operation_mapper["j" /* getTensorShapeArrayParam */])(
-                this.node.rawAttrs,
-                name,
-                defaultValue
-              );
-            }
-            if (value.list.b != null) {
-              return Object(operation_mapper["b" /* getBoolArrayParam */])(
-                this.node.rawAttrs,
-                name,
-                defaultValue
-              );
-            }
-            if (value.list.type != null) {
-              return Object(operation_mapper["d" /* getDtypeArrayParam */])(
-                this.node.rawAttrs,
-                name,
-                defaultValue
-              );
-            }
-          }
-          return defaultValue;
-        }
-      }
-      //# sourceMappingURL=node_value_impl.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/custom_op/register.js
-      var register = __webpack_require__(24);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/arithmetic_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "BiasAdd":
-          case "AddV2":
-          case "Add": {
-            return [
-              dist["add"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "AddN": {
-            return [
-              dist["addN"](
-                Object(utils["b" /* getParamValue */])("tensors", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "FloorMod":
-          case "Mod":
-            return [
-              dist["mod"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          case "Mul":
-            return [
-              dist["mul"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          case "RealDiv":
-          case "Div": {
-            return [
-              dist["div"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "DivNoNan": {
-            return [
-              dist["divNoNan"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "FloorDiv": {
-            return [
-              dist["floorDiv"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Sub": {
-            return [
-              dist["sub"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Minimum": {
-            return [
-              dist["minimum"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Maximum": {
-            return [
-              dist["maximum"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Pow": {
-            return [
-              dist["pow"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "SquaredDifference": {
-            return [
-              dist["squaredDifference"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const CATEGORY = "arithmetic";
-      //# sourceMappingURL=arithmetic_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/basic_math_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const basic_math_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "Abs":
-          case "ComplexAbs":
-            return [
-              dist["abs"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Acos":
-            return [
-              dist["acos"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Acosh":
-            return [
-              dist["acosh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Asin":
-            return [
-              dist["asin"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Asinh":
-            return [
-              dist["asinh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Atan":
-            return [
-              dist["atan"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Atan2":
-            return [
-              dist["atan2"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("y", node, tensorMap, context)
-              ),
-            ];
-          case "Atanh":
-            return [
-              dist["atanh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Ceil":
-            return [
-              dist["ceil"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Complex":
-            return [
-              dist["complex"](
-                Object(utils["b" /* getParamValue */])("real", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("imag", node, tensorMap, context)
-              ),
-            ];
-          case "Cos":
-            return [
-              dist["cos"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Cosh":
-            return [
-              dist["cosh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Elu":
-            return [
-              dist["elu"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Erf":
-            return [
-              dist["erf"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Exp":
-            return [
-              dist["exp"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Expm1": {
-            return [
-              dist["expm1"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "Floor":
-            return [
-              dist["floor"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Log":
-            return [
-              dist["log"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Log1p": {
-            return [
-              dist["log1p"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "Imag":
-            return [
-              dist["imag"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Neg":
-            return [
-              dist["neg"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Reciprocal": {
-            return [
-              dist["reciprocal"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Real":
-            return [
-              dist["real"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Relu":
-            return [
-              dist["relu"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Round": {
-            return [
-              dist["round"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "Selu":
-            return [
-              dist["selu"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Sigmoid":
-            return [
-              dist["sigmoid"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
-              ),
-            ];
-          case "Sin":
-            return [
-              dist["sin"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Sign": {
-            return [
-              dist["sign"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "Sinh": {
-            return [
-              dist["sinh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "Softplus": {
-            return [
-              dist["softplus"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Sqrt": {
-            return [
-              dist["sqrt"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "Square": {
-            return [
-              dist["square"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "Tanh": {
-            return [
-              dist["tanh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "Tan":
-            return [
-              dist["tan"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          case "Relu6":
-          case "ClipByValue":
-            return [
-              dist["clipByValue"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("clipValueMin", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("clipValueMax", node, tensorMap, context)
-              ),
-            ];
-          case "Rsqrt":
-            return [
-              dist["rsqrt"](
-                Object(utils["c" /* getTensor */])(node.inputNames[0], tensorMap, context)
-              ),
-            ];
-          case "Prod":
-            return [
-              dist["prod"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("axes", node, tensorMap, context)
-              ),
-            ];
-          case "LeakyRelu":
-            return [
-              dist["leakyRelu"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("alpha", node, tensorMap, context)
-              ),
-            ];
-          case "Prelu":
-            return [
-              dist["prelu"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("alpha", node, tensorMap, context)
-              ),
-            ];
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const basic_math_executor_CATEGORY = "basic_math";
-      //# sourceMappingURL=basic_math_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_utils.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      /**
-       * This differs from util.assertShapesMatch in that it allows values of
-       * negative one, an undefined size of a dimensinon, in a shape to match
-       * anything.
-       */
-
-      function assertShapesMatchAllowUndefinedSize(shapeA, shapeB, errorMessagePrefix = "") {
-        dist["util"].assert(
-          shapesEqualAllowUndefinedSize(shapeA, shapeB),
-          () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`
-        );
-      }
-      function shapesEqualAllowUndefinedSize(n1, n2) {
-        if (n1.length !== n2.length) {
-          return false;
-        }
-        for (let i = 0; i < n1.length; i++) {
-          if (n1[i] !== -1 && n2[i] !== -1 && n1[i] !== n2[i]) {
-            return false;
-          }
-        }
-        return true;
-      }
-      //# sourceMappingURL=tensor_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_array.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * The TensorArray object keeps an array of Tensors.  It
-       * allows reading from the array and writing to the array.
-       */
-      class tensor_array_TensorArray {
-        constructor(
-          name,
-          dtype,
-          maxSize,
-          elementShape,
-          identicalElementShapes,
-          dynamicSize,
-          clearAfterRead
-        ) {
-          this.name = name;
-          this.dtype = dtype;
-          this.maxSize = maxSize;
-          this.elementShape = elementShape;
-          this.identicalElementShapes = identicalElementShapes;
-          this.dynamicSize = dynamicSize;
-          this.clearAfterRead = clearAfterRead;
-          this.tensors = [];
-          this.closed_ = false;
-          this.id = tensor_array_TensorArray.nextId++;
-        }
-        get closed() {
-          return this.closed_;
-        }
-        /**
-         * Close the current TensorArray.
-         */
-        clearAndClose() {
-          this.tensors.forEach((tensor) => tensor.tensor.dispose());
-          this.tensors = [];
-          this.closed_ = true;
-        }
-        size() {
-          return this.tensors.length;
-        }
-        /**
-         * Read the value at location index in the TensorArray.
-         * @param index Number the index to read from.
-         */
-        read(index) {
-          if (this.closed_) {
-            throw new Error(`TensorArray ${this.name} has already been closed.`);
-          }
-          if (index < 0 || index >= this.size()) {
-            throw new Error(`Tried to read from index ${index}, but array size is: ${this.size()}`);
-          }
-          const tensorWithState = this.tensors[index];
-          if (tensorWithState.cleared) {
-            throw new Error(
-              `TensorArray ${this.name}: Could not read index ${index} twice because it was cleared after a previous read ` +
-                `(perhaps try setting clear_after_read = false?).`
-            );
-          }
-          if (this.clearAfterRead) {
-            tensorWithState.cleared = true;
-          }
-          tensorWithState.read = true;
-          return tensorWithState.tensor;
-        }
-        /**
-         * Helper method to read multiple tensors from the specified indices.
-         */
-        readMany(indices) {
-          return indices.map((index) => this.read(index));
-        }
-        /**
-         * Write value into the index of the TensorArray.
-         * @param index number the index to write to.
-         * @param tensor
-         */
-        write(index, tensor) {
-          if (this.closed_) {
-            throw new Error(`TensorArray ${this.name} has already been closed.`);
-          }
-          if (index < 0 || (!this.dynamicSize && index >= this.maxSize)) {
-            throw new Error(
-              `Tried to write to index ${index}, but array is not resizeable and size is: ${this.maxSize}`
-            );
-          }
-          const t = this.tensors[index] || {};
-          if (tensor.dtype !== this.dtype) {
-            throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index},
-          because the value dtype is ${tensor.dtype}, but TensorArray dtype is ${this.dtype}.`);
-          }
-          // Set the shape for the first time write to unknow shape tensor array
-          if (this.size() === 0 && (this.elementShape == null || this.elementShape.length === 0)) {
-            this.elementShape = tensor.shape;
-          }
-          assertShapesMatchAllowUndefinedSize(
-            this.elementShape,
-            tensor.shape,
-            `TensorArray ${this.name}: Could not write to TensorArray index ${index}.`
-          );
-          if (t && t.read) {
-            throw new Error(
-              `TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been read.`
-            );
-          }
-          if (t && t.written) {
-            throw new Error(
-              `TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been written.`
-            );
-          }
-          t.tensor = tensor;
-          t.written = true;
-          this.tensors[index] = t;
-        }
-        /**
-         * Helper method to write multiple tensors to the specified indices.
-         */
-        writeMany(indices, tensors) {
-          if (indices.length !== tensors.length) {
-            throw new Error(
-              `TensorArray ${this.name}: could not write multiple tensors,` +
-                `because the index size: ${indices.length} is not the same as tensors size: ${tensors.length}.`
-            );
-          }
-          indices.forEach((i, index) => this.write(i, tensors[index]));
-        }
-        /**
-         * Return selected values in the TensorArray as a packed Tensor. All of
-         * selected values must have been written and their shapes must all match.
-         * @param [indices] number[] Optional. Taking values in [0, max_value). If the
-         *    TensorArray is not dynamic, max_value=size(). If not specified returns
-         *    all tensors in the original order.
-         * @param [dtype]
-         */
-        gather(indices, dtype) {
-          if (!!dtype && dtype !== this.dtype) {
-            throw new Error(
-              `TensorArray dtype is ${this.dtype} but gather requested dtype ${dtype}`
-            );
-          }
-          if (!indices) {
-            indices = [];
-            for (let i = 0; i < this.size(); i++) {
-              indices.push(i);
-            }
-          } else {
-            indices = indices.slice(0, this.size());
-          }
-          if (indices.length === 0) {
-            return Object(dist["tensor"])([], [0].concat(this.elementShape));
-          }
-          // Read all the PersistentTensors into a vector to keep track of
-          // their memory.
-          const tensors = this.readMany(indices);
-          assertShapesMatchAllowUndefinedSize(
-            this.elementShape,
-            tensors[0].shape,
-            "TensorArray shape mismatch: "
-          );
-          return Object(dist["stack"])(tensors, 0);
-        }
-        /**
-         * Return the values in the TensorArray as a concatenated Tensor.
-         */
-        concat(dtype) {
-          if (!!dtype && dtype !== this.dtype) {
-            throw new Error(
-              `TensorArray dtype is ${this.dtype} but concat requested dtype ${dtype}`
-            );
-          }
-          if (this.size() === 0) {
-            return Object(dist["tensor"])([], [0].concat(this.elementShape));
-          }
-          const indices = [];
-          for (let i = 0; i < this.size(); i++) {
-            indices.push(i);
-          }
-          // Collect all the tensors from the tensors array.
-          const tensors = this.readMany(indices);
-          assertShapesMatchAllowUndefinedSize(
-            this.elementShape,
-            tensors[0].shape,
-            `TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${tensors[0].shape})`
-          );
-          return Object(dist["concat"])(tensors, 0);
-        }
-        /**
-         * Scatter the values of a Tensor in specific indices of a TensorArray.
-         * @param indices nummber[] values in [0, max_value). If the
-         *    TensorArray is not dynamic, max_value=size().
-         * @param tensor Tensor input tensor.
-         */
-        scatter(indices, tensor) {
-          if (tensor.dtype !== this.dtype) {
-            throw new Error(
-              `TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor.dtype}`
-            );
-          }
-          if (indices.length !== tensor.shape[0]) {
-            throw new Error(
-              `Expected len(indices) == tensor.shape[0], but saw: ${indices.length} vs. ${tensor.shape[0]}`
-            );
-          }
-          const maxIndex = Math.max(...indices);
-          if (!this.dynamicSize && maxIndex >= this.maxSize) {
-            throw new Error(`Max index must be < array size (${maxIndex}  vs. ${this.maxSize})`);
-          }
-          this.writeMany(indices, Object(dist["unstack"])(tensor, 0));
-        }
-        /**
-         * Split the values of a Tensor into the TensorArray.
-         * @param length number[] with the lengths to use when splitting value along
-         *    its first dimension.
-         * @param tensor Tensor, the tensor to split.
-         */
-        split(length, tensor) {
-          if (tensor.dtype !== this.dtype) {
-            throw new Error(
-              `TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor.dtype}`
-            );
-          }
-          let totalLength = 0;
-          const cumulativeLengths = length.map((len) => {
-            totalLength += len;
-            return totalLength;
-          });
-          if (totalLength !== tensor.shape[0]) {
-            throw new Error(`Expected sum of lengths to be equal to
-          tensor.shape[0], but sum of lengths is
-        ${totalLength}, and tensor's shape is: ${tensor.shape}`);
-          }
-          if (!this.dynamicSize && length.length !== this.maxSize) {
-            throw new Error(
-              `TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${length.length}), ` +
-                "and the TensorArray is not marked as dynamically resizeable"
-            );
-          }
-          const elementPerRow = totalLength === 0 ? 0 : tensor.size / totalLength;
-          const tensors = [];
-          Object(dist["tidy"])(() => {
-            tensor = tensor.reshape([1, totalLength, elementPerRow]);
-            for (let i = 0; i < length.length; ++i) {
-              const previousLength = i === 0 ? 0 : cumulativeLengths[i - 1];
-              const indices = [0, previousLength, 0];
-              const sizes = [1, length[i], elementPerRow];
-              tensors[i] = Object(dist["slice"])(tensor, indices, sizes).reshape(this.elementShape);
-            }
-            return tensors;
-          });
-          const indices = [];
-          for (let i = 0; i < length.length; i++) {
-            indices[i] = i;
-          }
-          this.writeMany(indices, tensors);
-        }
-      }
-      tensor_array_TensorArray.nextId = 0;
-      //# sourceMappingURL=tensor_array.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/control_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const control_executor_executeOp = async (node, tensorMap, context) => {
-        switch (node.op) {
-          case "If":
-          case "StatelessIf": {
-            const thenFunc = Object(utils["b" /* getParamValue */])(
-              "thenBranch",
-              node,
-              tensorMap,
-              context
-            );
-            const elseFunc = Object(utils["b" /* getParamValue */])(
-              "elseBranch",
-              node,
-              tensorMap,
-              context
-            );
-            const cond = Object(utils["b" /* getParamValue */])("cond", node, tensorMap, context);
-            const args = Object(utils["b" /* getParamValue */])("args", node, tensorMap, context);
-            const condValue = await cond.data();
-            if (condValue[0]) {
-              return context.functionMap[thenFunc].executeFunctionAsync(args);
-            } else {
-              return context.functionMap[elseFunc].executeFunctionAsync(args);
-            }
-          }
-          case "While":
-          case "StatelessWhile": {
-            const bodyFunc = Object(utils["b" /* getParamValue */])(
-              "body",
-              node,
-              tensorMap,
-              context
-            );
-            const condFunc = Object(utils["b" /* getParamValue */])(
-              "cond",
-              node,
-              tensorMap,
-              context
-            );
-            const args = Object(utils["b" /* getParamValue */])("args", node, tensorMap, context);
-            const condTensor = (await context.functionMap[condFunc].executeFunctionAsync(args))[0];
-            let condValue = await condTensor.data();
-            let result = args;
-            while (condValue[0]) {
-              result = await context.functionMap[bodyFunc].executeFunctionAsync(result);
-              const condTensor = (
-                await context.functionMap[condFunc].executeFunctionAsync(result)
-              )[0];
-              condValue = await condTensor.data();
-            }
-            return result;
-          }
-          case "LoopCond":
-            return [
-              Object(utils["b" /* getParamValue */])("pred", node, tensorMap, context).clone(),
-            ];
-          case "Switch": {
-            const pred = Object(utils["b" /* getParamValue */])("pred", node, tensorMap, context);
-            const data = Object(utils["b" /* getParamValue */])("data", node, tensorMap, context);
-            // Outputs nodes :0 => false, :1 => true
-            return (await pred.data())[0] ? [undefined, data.clone()] : [data.clone(), undefined];
-          }
-          case "Merge":
-            const inputName = node.inputNames.find(
-              (name) => Object(utils["c" /* getTensor */])(name, tensorMap, context) !== undefined
-            );
-            return inputName
-              ? [Object(utils["c" /* getTensor */])(inputName, tensorMap, context).clone()]
-              : undefined;
-          case "Enter":
-            const frameId = Object(utils["b" /* getParamValue */])(
-              "frameName",
-              node,
-              tensorMap,
-              context
-            );
-            const data = Object(utils["b" /* getParamValue */])("tensor", node, tensorMap, context);
-            context.enterFrame(frameId);
-            return [data.clone()];
-          case "Exit":
-            const tensor = Object(utils["b" /* getParamValue */])(
-              "tensor",
-              node,
-              tensorMap,
-              context
-            );
-            context.exitFrame();
-            return [tensor.clone()];
-          case "NextIteration":
-            const input = Object(utils["b" /* getParamValue */])(
-              "tensor",
-              node,
-              tensorMap,
-              context
-            );
-            context.nextIteration();
-            return [input.clone()];
-          case "TensorArrayV3":
-            const size = Object(utils["b" /* getParamValue */])("size", node, tensorMap, context);
-            const dtype = Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context);
-            const elementShape = Object(utils["b" /* getParamValue */])(
-              "elementShape",
-              node,
-              tensorMap,
-              context
-            );
-            const dynamicSize = Object(utils["b" /* getParamValue */])(
-              "dynamicSize",
-              node,
-              tensorMap,
-              context
-            );
-            const clearAfterRead = Object(utils["b" /* getParamValue */])(
-              "clearAfterRead",
-              node,
-              tensorMap,
-              context
-            );
-            const identicalElementShapes = Object(utils["b" /* getParamValue */])(
-              "identicalElementShapes",
-              node,
-              tensorMap,
-              context
-            );
-            const name = Object(utils["b" /* getParamValue */])("name", node, tensorMap, context);
-            const tensorArray = new tensor_array_TensorArray(
-              name,
-              dtype,
-              size,
-              elementShape,
-              identicalElementShapes,
-              dynamicSize,
-              clearAfterRead
-            );
-            context.addTensorArray(tensorArray);
-            return [Object(dist["scalar"])(tensorArray.id), Object(dist["scalar"])(1.0)];
-          case "TensorArrayWriteV3":
-            const id = Object(utils["b" /* getParamValue */])(
-              "tensorArrayId",
-              node,
-              tensorMap,
-              context
-            );
-            const index = Object(utils["b" /* getParamValue */])("index", node, tensorMap, context);
-            const writeTensor = Object(utils["b" /* getParamValue */])(
-              "tensor",
-              node,
-              tensorMap,
-              context
-            );
-            const writeTensorArray = context.getTensorArray(id);
-            writeTensorArray.write(index, writeTensor);
-            return [Object(dist["scalar"])(1.0)];
-          case "TensorArrayReadV3":
-            const readId = Object(utils["b" /* getParamValue */])(
-              "tensorArrayId",
-              node,
-              tensorMap,
-              context
-            );
-            const readIndex = Object(utils["b" /* getParamValue */])(
-              "index",
-              node,
-              tensorMap,
-              context
-            );
-            const readTensorArray = context.getTensorArray(readId);
-            return [readTensorArray.read(readIndex)];
-          case "TensorArrayGatherV3":
-            const gatherId = Object(utils["b" /* getParamValue */])(
-              "tensorArrayId",
-              node,
-              tensorMap,
-              context
-            );
-            const gatherIndices = Object(utils["b" /* getParamValue */])(
-              "indices",
-              node,
-              tensorMap,
-              context
-            );
-            const gatherDtype = Object(utils["b" /* getParamValue */])(
-              "dtype",
-              node,
-              tensorMap,
-              context
-            );
-            const gatherTensorArray = context.getTensorArray(gatherId);
-            return [gatherTensorArray.gather(gatherIndices, gatherDtype)];
-          case "TensorArrayScatterV3":
-            const scatterId = Object(utils["b" /* getParamValue */])(
-              "tensorArrayId",
-              node,
-              tensorMap,
-              context
-            );
-            const scatterIndices = Object(utils["b" /* getParamValue */])(
-              "indices",
-              node,
-              tensorMap,
-              context
-            );
-            const scatterTensor = Object(utils["b" /* getParamValue */])(
-              "tensor",
-              node,
-              tensorMap,
-              context
-            );
-            const scatterTensorArray = context.getTensorArray(scatterId);
-            scatterTensorArray.scatter(scatterIndices, scatterTensor);
-            return [Object(dist["scalar"])(1.0)];
-          case "TensorArrayConcatV3":
-            const concatId = Object(utils["b" /* getParamValue */])(
-              "tensorArrayId",
-              node,
-              tensorMap,
-              context
-            );
-            const concatTensorArray = context.getTensorArray(concatId);
-            const concatDtype = Object(utils["b" /* getParamValue */])(
-              "dtype",
-              node,
-              tensorMap,
-              context
-            );
-            return [concatTensorArray.concat(concatDtype)];
-          case "TensorArraySplitV3":
-            const splitId = Object(utils["b" /* getParamValue */])(
-              "tensorArrayId",
-              node,
-              tensorMap,
-              context
-            );
-            const splitTensor = Object(utils["b" /* getParamValue */])(
-              "tensor",
-              node,
-              tensorMap,
-              context
-            );
-            const lengths = Object(utils["b" /* getParamValue */])(
-              "lengths",
-              node,
-              tensorMap,
-              context
-            );
-            const splitTensorArray = context.getTensorArray(splitId);
-            splitTensorArray.split(lengths, splitTensor);
-            return [Object(dist["scalar"])(1.0)];
-          case "TensorArraySizeV3":
-            const sizeId = Object(utils["b" /* getParamValue */])(
-              "tensorArrayId",
-              node,
-              tensorMap,
-              context
-            );
-            const sizeTensorArray = context.getTensorArray(sizeId);
-            return [Object(dist["scalar"])(sizeTensorArray.size(), "int32")];
-          case "TensorArrayCloseV3":
-            const closeId = Object(utils["b" /* getParamValue */])(
-              "tensorArrayId",
-              node,
-              tensorMap,
-              context
-            );
-            const closeTensorArray = context.getTensorArray(closeId);
-            closeTensorArray.clearAndClose();
-            return [Object(dist["scalar"])(0)];
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const control_executor_CATEGORY = "control";
-      //# sourceMappingURL=control_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/convolution_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const convolution_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "Conv1D": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "stride",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const dataFormat = Object(utils["b" /* getParamValue */])(
-              "dataFormat",
-              node,
-              tensorMap,
-              context
-            ).toUpperCase();
-            const dilation = Object(utils["b" /* getParamValue */])(
-              "dilation",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["conv1d"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
-                stride,
-                pad,
-                dataFormat,
-                dilation
-              ),
-            ];
-          }
-          case "Conv2D": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const dataFormat = Object(utils["b" /* getParamValue */])(
-              "dataFormat",
-              node,
-              tensorMap,
-              context
-            ).toUpperCase();
-            const dilations = Object(utils["b" /* getParamValue */])(
-              "dilations",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["conv2d"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
-                [stride[1], stride[2]],
-                pad,
-                dataFormat,
-                [dilations[1], dilations[2]]
-              ),
-            ];
-          }
-          case "_FusedConv2D":
-          case "FusedDepthwiseConv2dNative": {
-            const [extraOp, activationFunc] = Object(utils["b" /* getParamValue */])(
-              "fusedOps",
-              node,
-              tensorMap,
-              context
-            );
-            const isBiasAdd = extraOp === "biasadd";
-            const isPrelu = activationFunc === "prelu";
-            const isBatchNorm = extraOp === "fusedbatchnorm";
-            const numArgs = Object(utils["b" /* getParamValue */])(
-              "numArgs",
-              node,
-              tensorMap,
-              context
-            );
-            if (isBiasAdd) {
-              if (isPrelu && numArgs !== 2) {
-                throw new Error(
-                  "FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu " +
-                    "must have two extra arguments: bias and alpha."
-                );
-              }
-              if (!isPrelu && numArgs !== 1) {
-                throw new Error(
-                  "FusedConv2d and DepthwiseConv2d with BiasAdd must have " +
-                    "one extra argument: bias."
-                );
-              }
-            }
-            if (isBatchNorm) {
-              throw new Error(
-                "FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported."
-              );
-            }
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const dataFormat = Object(utils["b" /* getParamValue */])(
-              "dataFormat",
-              node,
-              tensorMap,
-              context
-            ).toUpperCase();
-            const dilations = Object(utils["b" /* getParamValue */])(
-              "dilations",
-              node,
-              tensorMap,
-              context
-            );
-            const [biasArg, preluArg] = Object(utils["b" /* getParamValue */])(
-              "args",
-              node,
-              tensorMap,
-              context
-            );
-            const kernelMethod =
-              node.op === "_FusedConv2D" ? dist["fused"].conv2d : dist["fused"].depthwiseConv2d;
-            return [
-              kernelMethod({
-                x: Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                filter: Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
-                strides: [stride[1], stride[2]],
-                pad: pad,
-                dataFormat: dataFormat,
-                dilations: [dilations[1], dilations[2]],
-                bias: biasArg,
-                activation: activationFunc,
-                preluActivationWeights: preluArg,
-              }),
-            ];
-          }
-          case "Conv2DBackpropInput":
-          case "Conv2dTranspose": {
-            const shape = Object(utils["b" /* getParamValue */])(
-              "outputShape",
-              node,
-              tensorMap,
-              context
-            );
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            return [
-              dist["conv2dTranspose"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
-                shape,
-                [stride[1], stride[2]],
-                pad
-              ),
-            ];
-          }
-          case "DepthwiseConv2dNative":
-          case "DepthwiseConv2d": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const dilations = Object(utils["b" /* getParamValue */])(
-              "dilations",
-              node,
-              tensorMap,
-              context
-            );
-            const dataFormat = Object(utils["b" /* getParamValue */])(
-              "dataFormat",
-              node,
-              tensorMap,
-              context
-            ).toUpperCase();
-            return [
-              dist["depthwiseConv2d"](
-                Object(utils["b" /* getParamValue */])("input", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
-                [stride[1], stride[2]],
-                pad,
-                dataFormat,
-                [dilations[1], dilations[2]]
-              ),
-            ];
-          }
-          case "Conv3D": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const dataFormat = Object(utils["b" /* getParamValue */])(
-              "dataFormat",
-              node,
-              tensorMap,
-              context
-            ).toUpperCase();
-            const dilations = Object(utils["b" /* getParamValue */])(
-              "dilations",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["conv3d"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
-                [stride[1], stride[2], stride[3]],
-                pad,
-                dataFormat,
-                [dilations[1], dilations[2], dilations[3]]
-              ),
-            ];
-          }
-          case "AvgPool": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const kernelSize = Object(utils["b" /* getParamValue */])(
-              "kernelSize",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["avgPool"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                [kernelSize[1], kernelSize[2]],
-                [stride[1], stride[2]],
-                pad
-              ),
-            ];
-          }
-          case "MaxPool": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const kernelSize = Object(utils["b" /* getParamValue */])(
-              "kernelSize",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["maxPool"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                [kernelSize[1], kernelSize[2]],
-                [stride[1], stride[2]],
-                pad
-              ),
-            ];
-          }
-          case "MaxPoolWithArgmax": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const kernelSize = Object(utils["b" /* getParamValue */])(
-              "kernelSize",
-              node,
-              tensorMap,
-              context
-            );
-            const includeBatchInIndex = Object(utils["b" /* getParamValue */])(
-              "includeBatchInIndex",
-              node,
-              tensorMap,
-              context
-            );
-            const { result, indexes } = dist["maxPoolWithArgmax"](
-              Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-              [kernelSize[1], kernelSize[2]],
-              [stride[1], stride[2]],
-              pad,
-              includeBatchInIndex
-            );
-            return [result, indexes];
-          }
-          case "AvgPool3D": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const kernelSize = Object(utils["b" /* getParamValue */])(
-              "kernelSize",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["avgPool3d"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                [kernelSize[1], kernelSize[2], kernelSize[3]],
-                [stride[1], stride[2], stride[3]],
-                pad
-              ),
-            ];
-          }
-          case "MaxPool3D": {
-            const stride = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
-            const kernelSize = Object(utils["b" /* getParamValue */])(
-              "kernelSize",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["maxPool3d"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                [kernelSize[1], kernelSize[2], kernelSize[3]],
-                [stride[1], stride[2], stride[3]],
-                pad
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const convolution_executor_CATEGORY = "convolution";
-      //# sourceMappingURL=convolution_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/creation_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const creation_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "Fill": {
-            const shape = Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context);
-            const dtype = Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context);
-            const value = Object(utils["b" /* getParamValue */])("value", node, tensorMap, context);
-            return [dist["fill"](shape, value, dtype)];
-          }
-          case "LinSpace": {
-            const start = Object(utils["b" /* getParamValue */])("start", node, tensorMap, context);
-            const stop = Object(utils["b" /* getParamValue */])("stop", node, tensorMap, context);
-            const num = Object(utils["b" /* getParamValue */])("num", node, tensorMap, context);
-            return [dist["linspace"](start, stop, num)];
-          }
-          case "Multinomial": {
-            const logits = Object(utils["b" /* getParamValue */])(
-              "logits",
-              node,
-              tensorMap,
-              context
-            );
-            const numSamples = Object(utils["b" /* getParamValue */])(
-              "numSamples",
-              node,
-              tensorMap,
-              context
-            );
-            const seed = Object(utils["b" /* getParamValue */])("seed", node, tensorMap, context);
-            return [dist["multinomial"](logits, numSamples, seed)];
-          }
-          case "OneHot": {
-            const indices = Object(utils["b" /* getParamValue */])(
-              "indices",
-              node,
-              tensorMap,
-              context
-            );
-            const depth = Object(utils["b" /* getParamValue */])("depth", node, tensorMap, context);
-            const onValue = Object(utils["b" /* getParamValue */])(
-              "onValue",
-              node,
-              tensorMap,
-              context
-            );
-            const offValue = Object(utils["b" /* getParamValue */])(
-              "offValue",
-              node,
-              tensorMap,
-              context
-            );
-            return [dist["oneHot"](indices, depth, onValue, offValue)];
-          }
-          case "Ones": {
-            return [
-              dist["ones"](
-                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "OnesLike": {
-            return [
-              dist["onesLike"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "RandomUniform": {
-            return [
-              dist["randomUniform"](
-                // tslint:disable-next-line:no-any
-                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("minval", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("maxval", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Range": {
-            const start = Object(utils["b" /* getParamValue */])("start", node, tensorMap, context);
-            const stop = Object(utils["b" /* getParamValue */])("stop", node, tensorMap, context);
-            const step = Object(utils["b" /* getParamValue */])("step", node, tensorMap, context);
-            return [
-              dist["range"](
-                start,
-                stop,
-                step,
-                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "TruncatedNormal": {
-            const shape = Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context);
-            const mean = Object(utils["b" /* getParamValue */])("mean", node, tensorMap, context);
-            const stdDev = Object(utils["b" /* getParamValue */])(
-              "stdDev",
-              node,
-              tensorMap,
-              context
-            );
-            const seed = Object(utils["b" /* getParamValue */])("seed", node, tensorMap, context);
-            return [
-              dist["truncatedNormal"](
-                shape,
-                mean,
-                stdDev,
-                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context),
-                seed
-              ),
-            ];
-          }
-          case "Zeros": {
-            return [
-              dist["zeros"](
-                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "ZerosLike": {
-            return [
-              dist["zerosLike"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const creation_executor_CATEGORY = "creation";
-      //# sourceMappingURL=creation_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/dynamic_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const dynamic_executor_executeOp = async (node, tensorMap, context) => {
-        switch (node.op) {
-          case "NonMaxSuppressionV5":
-          case "NonMaxSuppressionV3":
-          case "NonMaxSuppressionV2": {
-            const boxes = Object(utils["b" /* getParamValue */])("boxes", node, tensorMap, context);
-            const scores = Object(utils["b" /* getParamValue */])(
-              "scores",
-              node,
-              tensorMap,
-              context
-            );
-            const maxOutputSize = Object(utils["b" /* getParamValue */])(
-              "maxOutputSize",
-              node,
-              tensorMap,
-              context
-            );
-            const iouThreshold = Object(utils["b" /* getParamValue */])(
-              "iouThreshold",
-              node,
-              tensorMap,
-              context
-            );
-            const scoreThreshold = Object(utils["b" /* getParamValue */])(
-              "scoreThreshold",
-              node,
-              tensorMap,
-              context
-            );
-            if (node.op === "NonMaxSuppressionV5") {
-              const softNmsSigma = Object(utils["b" /* getParamValue */])(
-                "softNmsSigma",
-                node,
-                tensorMap,
-                context
-              );
-              const result = await dist["image"].nonMaxSuppressionWithScoreAsync(
-                boxes,
-                scores,
-                maxOutputSize,
-                iouThreshold,
-                scoreThreshold,
-                softNmsSigma
-              );
-              return [result.selectedIndices, result.selectedScores];
-            }
-            return [
-              await dist["image"].nonMaxSuppressionAsync(
-                boxes,
-                scores,
-                maxOutputSize,
-                iouThreshold,
-                scoreThreshold
-              ),
-            ];
-          }
-          case "Where": {
-            const condition = Object(utils["b" /* getParamValue */])(
-              "condition",
-              node,
-              tensorMap,
-              context
-            ).asType("bool");
-            const result = [await dist["whereAsync"](condition)];
-            condition.dispose();
-            return result;
-          }
-          case "ListDiff": {
-            return dist["setdiff1dAsync"](
-              Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-              Object(utils["b" /* getParamValue */])("y", node, tensorMap, context)
-            );
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const dynamic_executor_CATEGORY = "dynamic";
-      //# sourceMappingURL=dynamic_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/evaluation_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const evaluation_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "TopKV2": {
-            const x = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
-            const k = Object(utils["b" /* getParamValue */])("k", node, tensorMap, context);
-            const sorted = Object(utils["b" /* getParamValue */])(
-              "sorted",
-              node,
-              tensorMap,
-              context
-            );
-            const result = dist["topk"](x, k, sorted);
-            return [result.values, result.indices];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const evaluation_executor_CATEGORY = "evaluation";
-      //# sourceMappingURL=evaluation_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/graph_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const graph_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "Const": {
-            return tensorMap[node.name];
-          }
-          case "PlaceholderWithDefault":
-            const def = Object(utils["b" /* getParamValue */])("default", node, tensorMap, context);
-            return [Object(utils["c" /* getTensor */])(node.name, tensorMap, context) || def];
-          case "Placeholder":
-            return [Object(utils["c" /* getTensor */])(node.name, tensorMap, context)];
-          case "Identity":
-          case "StopGradient":
-          case "FakeQuantWithMinMaxVars": // This op is currently ignored.
-            return [Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).clone()];
-          case "IdentityN":
-            return Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).map((t) =>
-              t.clone()
-            );
-          case "Snapshot":
-            const snapshot = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
-            return [snapshot.clone()];
-          case "Shape":
-            return [
-              dist["tensor1d"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).shape,
-                "int32"
-              ),
-            ];
-          case "ShapeN":
-            return Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).map((t) =>
-              dist["tensor1d"](t.shape)
-            );
-          case "Size":
-            return [
-              dist["scalar"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).size,
-                "int32"
-              ),
-            ];
-          case "Rank":
-            return [
-              dist["scalar"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).rank,
-                "int32"
-              ),
-            ];
-          case "NoOp":
-            return [dist["scalar"](1)];
-          case "Print":
-            const input = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
-            const data = Object(utils["b" /* getParamValue */])("data", node, tensorMap, context);
-            const message = Object(utils["b" /* getParamValue */])(
-              "message",
-              node,
-              tensorMap,
-              context
-            );
-            const summarize = Object(utils["b" /* getParamValue */])(
-              "summarize",
-              node,
-              tensorMap,
-              context
-            );
-            console.warn(
-              "The graph has a tf.print() operation," +
-                "usually used for debugging, which slows down performance."
-            );
-            console.log(message);
-            for (let i = 0; i < data.length; i++) {
-              console.log(Array.prototype.slice.call(data[i].dataSync()).slice(0, summarize));
-            }
-            return [input];
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const graph_executor_CATEGORY = "graph";
-      //# sourceMappingURL=graph_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/image_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const image_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "ResizeBilinear": {
-            const images = Object(utils["b" /* getParamValue */])(
-              "images",
-              node,
-              tensorMap,
-              context
-            );
-            const size = Object(utils["b" /* getParamValue */])("size", node, tensorMap, context);
-            const alignCorners = Object(utils["b" /* getParamValue */])(
-              "alignCorners",
-              node,
-              tensorMap,
-              context
-            );
-            return [dist["image"].resizeBilinear(images, [size[0], size[1]], alignCorners)];
-          }
-          case "ResizeNearestNeighbor": {
-            const images = Object(utils["b" /* getParamValue */])(
-              "images",
-              node,
-              tensorMap,
-              context
-            );
-            const size = Object(utils["b" /* getParamValue */])("size", node, tensorMap, context);
-            const alignCorners = Object(utils["b" /* getParamValue */])(
-              "alignCorners",
-              node,
-              tensorMap,
-              context
-            );
-            return [dist["image"].resizeNearestNeighbor(images, [size[0], size[1]], alignCorners)];
-          }
-          case "CropAndResize": {
-            const image = Object(utils["b" /* getParamValue */])("image", node, tensorMap, context);
-            const boxes = Object(utils["b" /* getParamValue */])("boxes", node, tensorMap, context);
-            const boxInd = Object(utils["b" /* getParamValue */])(
-              "boxInd",
-              node,
-              tensorMap,
-              context
-            );
-            const cropSize = Object(utils["b" /* getParamValue */])(
-              "cropSize",
-              node,
-              tensorMap,
-              context
-            );
-            const method = Object(utils["b" /* getParamValue */])(
-              "method",
-              node,
-              tensorMap,
-              context
-            );
-            const extrapolationValue = Object(utils["b" /* getParamValue */])(
-              "extrapolationValue",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["image"].cropAndResize(
-                image,
-                boxes,
-                boxInd,
-                cropSize,
-                method,
-                extrapolationValue
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const image_executor_CATEGORY = "image";
-      //# sourceMappingURL=image_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/logical_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const logical_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "Equal": {
-            return [
-              dist["equal"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "NotEqual": {
-            return [
-              dist["notEqual"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Greater": {
-            return [
-              dist["greater"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "GreaterEqual": {
-            return [
-              dist["greaterEqual"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Less": {
-            return [
-              dist["less"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "LessEqual": {
-            return [
-              dist["lessEqual"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "LogicalAnd": {
-            return [
-              dist["logicalAnd"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "LogicalNot": {
-            return [
-              dist["logicalNot"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "LogicalOr": {
-            return [
-              dist["logicalOr"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Select":
-          case "SelectV2": {
-            return [
-              dist["where"](
-                Object(utils["b" /* getParamValue */])("condition", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const logical_executor_CATEGORY = "logical";
-      //# sourceMappingURL=logical_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/matrices_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const matrices_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "BatchMatMul":
-          case "BatchMatMulV2":
-          case "MatMul":
-            return [
-              dist["matMul"](
-                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("transposeA", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("transposeB", node, tensorMap, context)
-              ),
-            ];
-          case "Transpose":
-            return [
-              dist["transpose"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("perm", node, tensorMap, context)
-              ),
-            ];
-          case "_FusedMatMul":
-            const [extraOp, activationFunc] = Object(utils["b" /* getParamValue */])(
-              "fusedOps",
-              node,
-              tensorMap,
-              context
-            );
-            const isBiasAdd = extraOp === "biasadd";
-            const isPrelu = activationFunc === "prelu";
-            const numArgs = Object(utils["b" /* getParamValue */])(
-              "numArgs",
-              node,
-              tensorMap,
-              context
-            );
-            if (isBiasAdd) {
-              if (isPrelu && numArgs !== 2) {
-                throw new Error(
-                  "Fused MatMul with BiasAdd and Prelu must have two " +
-                    "extra arguments: bias and alpha."
-                );
-              }
-              if (!isPrelu && numArgs !== 1) {
-                throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.");
-              }
-            }
-            const [biasArg, preluArg] = Object(utils["b" /* getParamValue */])(
-              "args",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["fused"].matMul({
-                a: Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
-                b: Object(utils["b" /* getParamValue */])("b", node, tensorMap, context),
-                transposeA: Object(utils["b" /* getParamValue */])(
-                  "transposeA",
-                  node,
-                  tensorMap,
-                  context
-                ),
-                transposeB: Object(utils["b" /* getParamValue */])(
-                  "transposeB",
-                  node,
-                  tensorMap,
-                  context
-                ),
-                bias: biasArg,
-                activation: activationFunc,
-                preluActivationWeights: preluArg,
-              }),
-            ];
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const matrices_executor_CATEGORY = "matrices";
-      //# sourceMappingURL=matrices_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/normalization_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const normalization_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "FusedBatchNorm":
-          case "FusedBatchNormV2": {
-            return [
-              dist["batchNorm"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("mean", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("variance", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("offset", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("scale", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("epsilon", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "FusedBatchNormV3": {
-            return [
-              dist["batchNorm"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("mean", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("variance", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("offset", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("scale", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("epsilon", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "LRN": {
-            return [
-              dist["localResponseNormalization"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("radius", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("bias", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("alpha", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("beta", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "Softmax": {
-            return [
-              dist["softmax"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "LogSoftmax": {
-            return [
-              dist["logSoftmax"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "SparseToDense": {
-            return [
-              dist["sparseToDense"](
-                Object(utils["b" /* getParamValue */])("sparseIndices", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("outputShape", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("sparseValues", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("defaultValue", node, tensorMap, context)
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const normalization_executor_CATEGORY = "normalization";
-      //# sourceMappingURL=normalization_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/reduction_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const reduction_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "Max": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const keepDims = Object(utils["b" /* getParamValue */])(
-              "keepDims",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["max"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis,
-                keepDims
-              ),
-            ];
-          }
-          case "Mean": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const keepDims = Object(utils["b" /* getParamValue */])(
-              "keepDims",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["mean"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis,
-                keepDims
-              ),
-            ];
-          }
-          case "Min": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const keepDims = Object(utils["b" /* getParamValue */])(
-              "keepDims",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["min"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis,
-                keepDims
-              ),
-            ];
-          }
-          case "Sum": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const keepDims = Object(utils["b" /* getParamValue */])(
-              "keepDims",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["sum"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis,
-                keepDims
-              ),
-            ];
-          }
-          case "All": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const keepDims = Object(utils["b" /* getParamValue */])(
-              "keepDims",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["all"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis,
-                keepDims
-              ),
-            ];
-          }
-          case "Any": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const keepDims = Object(utils["b" /* getParamValue */])(
-              "keepDims",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["any"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis,
-                keepDims
-              ),
-            ];
-          }
-          case "ArgMax": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            return [
-              dist["argMax"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis
-              ),
-            ];
-          }
-          case "ArgMin": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            return [
-              dist["argMin"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis
-              ),
-            ];
-          }
-          case "Prod": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const keepDims = Object(utils["b" /* getParamValue */])(
-              "keepDims",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["prod"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis,
-                keepDims
-              ),
-            ];
-          }
-          case "Cumsum": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const exclusive = Object(utils["b" /* getParamValue */])(
-              "exclusive",
-              node,
-              tensorMap,
-              context
-            );
-            const reverse = Object(utils["b" /* getParamValue */])(
-              "reverse",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["cumsum"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis,
-                exclusive,
-                reverse
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const reduction_executor_CATEGORY = "reduction";
-      //# sourceMappingURL=reduction_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/slice_join_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const slice_join_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "ConcatV2":
-          case "Concat": {
-            const n = Object(utils["b" /* getParamValue */])("n", node, tensorMap, context);
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            let inputs = Object(utils["b" /* getParamValue */])(
-              "tensors",
-              node,
-              tensorMap,
-              context
-            );
-            inputs = inputs.slice(0, n);
-            return [dist["concat"](inputs, axis)];
-          }
-          case "GatherV2":
-          case "Gather": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const input = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
-            const indices = Object(utils["b" /* getParamValue */])(
-              "indices",
-              node,
-              tensorMap,
-              context
-            );
-            return [dist["gather"](input, indices.asType("int32"), axis)];
-          }
-          case "ReverseV2":
-          case "Reverse": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const input = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
-            return [dist["reverse"](input, axis)];
-          }
-          case "Slice": {
-            // tslint:disable-next-line:no-any
-            const begin = Object(utils["b" /* getParamValue */])("begin", node, tensorMap, context);
-            // tslint:disable-next-line:no-any
-            const size = Object(utils["b" /* getParamValue */])("size", node, tensorMap, context);
-            return [
-              dist["slice"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                begin,
-                size
-              ),
-            ];
-          }
-          case "StridedSlice": {
-            const begin = Object(utils["b" /* getParamValue */])("begin", node, tensorMap, context);
-            const end = Object(utils["b" /* getParamValue */])("end", node, tensorMap, context);
-            const strides = Object(utils["b" /* getParamValue */])(
-              "strides",
-              node,
-              tensorMap,
-              context
-            );
-            const beginMask = Object(utils["b" /* getParamValue */])(
-              "beginMask",
-              node,
-              tensorMap,
-              context
-            );
-            const endMask = Object(utils["b" /* getParamValue */])(
-              "endMask",
-              node,
-              tensorMap,
-              context
-            );
-            const ellipsisMask = Object(utils["b" /* getParamValue */])(
-              "ellipsisMask",
-              node,
-              tensorMap,
-              context
-            );
-            const newAxisMask = Object(utils["b" /* getParamValue */])(
-              "newAxisMask",
-              node,
-              tensorMap,
-              context
-            );
-            const shrinkAxisMask = Object(utils["b" /* getParamValue */])(
-              "shrinkAxisMask",
-              node,
-              tensorMap,
-              context
-            );
-            const tensor = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
-            if (begin.length === 1 && tensor.shape.length > 1) {
-              for (let i = 1; i < tensor.shape.length; i++) {
-                begin.push(0);
-                end.push(tensor.shape[i]);
-                strides.push(strides[0]);
-              }
-            }
-            return [
-              dist["stridedSlice"](
-                tensor,
-                begin,
-                end,
-                strides,
-                beginMask,
-                endMask,
-                ellipsisMask,
-                newAxisMask,
-                shrinkAxisMask
-              ),
-            ];
-          }
-          case "Pack": {
-            return dist["tidy"](() => {
-              const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-              const tensors = Object(utils["b" /* getParamValue */])(
-                "tensors",
-                node,
-                tensorMap,
-                context
-              );
-              // Reshape the tensors to the first tensor's shape if they don't match.
-              const shape = tensors[0].shape;
-              const squeezedShape = tensors[0].squeeze().shape;
-              const mapped = tensors.map((tensor) => {
-                const sameShape = dist["util"].arraysEqual(tensor.shape, shape);
-                if (
-                  !sameShape &&
-                  !dist["util"].arraysEqual(tensor.squeeze().shape, squeezedShape)
-                ) {
-                  throw new Error("the input tensors shape does not match");
-                }
-                return sameShape ? tensor : tensor.reshape(shape);
-              });
-              return [dist["stack"](mapped, axis)];
-            });
-          }
-          case "Unpack": {
-            return dist["tidy"](() => {
-              const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-              const tensor = Object(utils["b" /* getParamValue */])(
-                "tensor",
-                node,
-                tensorMap,
-                context
-              );
-              return dist["unstack"](tensor, axis);
-            });
-          }
-          case "Tile": {
-            const reps = Object(utils["b" /* getParamValue */])("reps", node, tensorMap, context);
-            return [
-              dist["tile"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                reps
-              ),
-            ];
-          }
-          case "Split":
-          case "SplitV": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            const numOrSizeSplits = Object(utils["b" /* getParamValue */])(
-              "numOrSizeSplits",
-              node,
-              tensorMap,
-              context
-            );
-            return dist["split"](
-              Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-              numOrSizeSplits,
-              axis
-            );
-          }
-          case "ScatterNd": {
-            const indices = Object(utils["b" /* getParamValue */])(
-              "indices",
-              node,
-              tensorMap,
-              context
-            );
-            const values = Object(utils["b" /* getParamValue */])(
-              "values",
-              node,
-              tensorMap,
-              context
-            );
-            const shape = Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context);
-            return [dist["scatterND"](indices, values, shape)];
-          }
-          case "GatherNd": {
-            const x = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
-            const indices = Object(utils["b" /* getParamValue */])(
-              "indices",
-              node,
-              tensorMap,
-              context
-            );
-            return [dist["gatherND"](x, indices)];
-          }
-          case "SparseToDense": {
-            const indices = Object(utils["b" /* getParamValue */])(
-              "sparseIndices",
-              node,
-              tensorMap,
-              context
-            );
-            const shape = Object(utils["b" /* getParamValue */])(
-              "outputShape",
-              node,
-              tensorMap,
-              context
-            );
-            const sparseValues = Object(utils["b" /* getParamValue */])(
-              "sparseValues",
-              node,
-              tensorMap,
-              context
-            );
-            const defaultValue = Object(utils["b" /* getParamValue */])(
-              "defaultValue",
-              node,
-              tensorMap,
-              context
-            );
-            return [
-              dist["sparseToDense"](
-                indices,
-                sparseValues,
-                shape,
-                sparseValues.dtype === defaultValue.dtype
-                  ? defaultValue
-                  : defaultValue.asType(sparseValues.dtype)
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const slice_join_executor_CATEGORY = "slice_join";
-      //# sourceMappingURL=slice_join_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/spectral_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const spectral_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "FFT": {
-            return [
-              dist["fft"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "IFFT": {
-            return [
-              dist["ifft"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "RFFT": {
-            return [
-              dist["rfft"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          case "IRFFT": {
-            return [
-              dist["irfft"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const spectral_executor_CATEGORY = "spectral";
-      //# sourceMappingURL=spectral_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/transformation_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const transformation_executor_executeOp = (node, tensorMap, context) => {
-        switch (node.op) {
-          case "Cast": {
-            return [
-              dist["cast"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "ExpandDims": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            return [
-              dist["expandDims"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis
-              ),
-            ];
-          }
-          case "Squeeze": {
-            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
-            return [
-              dist["squeeze"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                axis
-              ),
-            ];
-          }
-          case "Reshape": {
-            return [
-              dist["reshape"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "PadV2":
-          case "Pad": {
-            return [
-              dist["pad"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["f" /* split */])(
-                  Object(utils["b" /* getParamValue */])("padding", node, tensorMap, context),
-                  2
-                ),
-                Object(utils["b" /* getParamValue */])("constantValue", node, tensorMap, context)
-              ),
-            ];
-          }
-          case "SpaceToBatchND": {
-            const blockShape = Object(utils["b" /* getParamValue */])(
-              "blockShape",
-              node,
-              tensorMap,
-              context
-            );
-            const paddings = Object(utils["f" /* split */])(
-              Object(utils["b" /* getParamValue */])("paddings", node, tensorMap, context),
-              2
-            );
-            return [
-              dist["spaceToBatchND"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                blockShape,
-                paddings
-              ),
-            ];
-          }
-          case "BatchToSpaceND": {
-            const blockShape = Object(utils["b" /* getParamValue */])(
-              "blockShape",
-              node,
-              tensorMap,
-              context
-            );
-            const crops = Object(utils["f" /* split */])(
-              Object(utils["b" /* getParamValue */])("crops", node, tensorMap, context),
-              2
-            );
-            return [
-              dist["batchToSpaceND"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                blockShape,
-                crops
-              ),
-            ];
-          }
-          case "DepthToSpace": {
-            const blockSize = Object(utils["b" /* getParamValue */])(
-              "blockSize",
-              node,
-              tensorMap,
-              context
-            );
-            const dataFormat = Object(utils["b" /* getParamValue */])(
-              "dataFormat",
-              node,
-              tensorMap,
-              context
-            ).toUpperCase();
-            return [
-              dist["depthToSpace"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                blockSize,
-                dataFormat
-              ),
-            ];
-          }
-          case "BroadcastTo": {
-            return [
-              dist["broadcastTo"](
-                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
-                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context)
-              ),
-            ];
-          }
-          default:
-            throw TypeError(`Node type ${node.op} is not implemented`);
-        }
-      };
-      const transformation_executor_CATEGORY = "transformation";
-      //# sourceMappingURL=transformation_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/operation_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Executes the op defined by the node object.
-       * @param node
-       * @param tensorMap contains tensors for executed nodes and weights
-       */
-      function operation_executor_executeOp(node, tensorMap, context) {
-        const value = ((node, tensorMap, context) => {
-          switch (node.category) {
-            case "arithmetic":
-              return dist["tidy"](() => executeOp(node, tensorMap, context));
-            case "basic_math":
-              return dist["tidy"](() => basic_math_executor_executeOp(node, tensorMap, context));
-            case "control":
-              return control_executor_executeOp(node, tensorMap, context);
-            case "convolution":
-              return dist["tidy"](() => convolution_executor_executeOp(node, tensorMap, context));
-            case "creation":
-              return dist["tidy"](() => creation_executor_executeOp(node, tensorMap, context));
-            case "dynamic":
-              return dynamic_executor_executeOp(node, tensorMap, context);
-            case "evaluation":
-              return dist["tidy"](() => evaluation_executor_executeOp(node, tensorMap, context));
-            case "image":
-              return dist["tidy"](() => image_executor_executeOp(node, tensorMap, context));
-            case "graph":
-              return dist["tidy"](() => graph_executor_executeOp(node, tensorMap, context));
-            case "logical":
-              return dist["tidy"](() => logical_executor_executeOp(node, tensorMap, context));
-            case "matrices":
-              return dist["tidy"](() => matrices_executor_executeOp(node, tensorMap, context));
-            case "normalization":
-              return dist["tidy"](() => normalization_executor_executeOp(node, tensorMap, context));
-            case "reduction":
-              return dist["tidy"](() => reduction_executor_executeOp(node, tensorMap, context));
-            case "slice_join":
-              return dist["tidy"](() => slice_join_executor_executeOp(node, tensorMap, context));
-            case "spectral":
-              return dist["tidy"](() => spectral_executor_executeOp(node, tensorMap, context));
-            case "transformation":
-              return dist["tidy"](() =>
-                transformation_executor_executeOp(node, tensorMap, context)
-              );
-            case "custom":
-              const opMapper = Object(register["b" /* getRegisteredOp */])(node.op);
-              if (opMapper && opMapper.customExecutor) {
-                return opMapper.customExecutor(
-                  new node_value_impl_NodeValueImpl(node, tensorMap, context)
-                );
-              } else {
-                throw TypeError(`Custom op ${node.op} is not registered.`);
-              }
-            default:
-              throw TypeError(
-                `Unknown op '${node.op}'. File an issue at ` +
-                  `https://github.com/tensorflow/tfjs/issues so we can add it` +
-                  `, or register a custom execution with tf.registerOp()`
-              );
-          }
-        })(node, tensorMap, context);
-        if (value instanceof Promise) {
-          return value.then((data) => [].concat(data));
-        }
-        return [].concat(value);
-      }
-      //# sourceMappingURL=operation_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/execution_context.js
-      /**
-       * ExecutionContext captures the runtime environment of the node. It keeps
-       * track of the current frame and iteration for the control flow ops.
-       *
-       * For example, typical Dynamic RNN model may contain loops, for which
-       * TensorFlow will generate graphs with Enter/Exit nodes to control the
-       * current execution frame, and NextIteration Nodes for iteration id increment.
-       * For model with branch logic, TensorFLow will generate Switch/Merge ops.
-       */
-      class ExecutionContext {
-        constructor(weightMap, tensorArrayMap, functionMap = {}) {
-          this.weightMap = weightMap;
-          this.tensorArrayMap = tensorArrayMap;
-          this.functionMap = functionMap;
-          this.rootContext = { id: 0, frameName: "", iterationId: 0 };
-          this.contexts = [this.rootContext];
-          this.lastId = 0;
-          this.generateCurrentContextIds();
-        }
-        newFrame(id, frameName) {
-          return { id, frameName, iterationId: 0 };
-        }
-        /**
-         * Set the current context
-         * @param contexts: ExecutionContextInfo[] the current path of execution
-         * frames
-         */
-        set currentContext(contexts) {
-          if (this.contexts !== contexts) {
-            this.contexts = contexts;
-            this.generateCurrentContextIds();
-          }
-        }
-        get currentContext() {
-          return this.contexts;
-        }
-        /**
-         * Returns the current context in string format.
-         */
-        get currentContextId() {
-          return this._currentContextIds[0];
-        }
-        /**
-         * Returns the current context and all parent contexts in string format.
-         * This allow access to the nodes in the current and parent frames.
-         */
-        get currentContextIds() {
-          return this._currentContextIds;
-        }
-        generateCurrentContextIds() {
-          const names = [];
-          for (let i = 0; i < this.contexts.length - 1; i++) {
-            const contexts = this.contexts.slice(0, this.contexts.length - i);
-            names.push(this.contextIdforContexts(contexts));
-          }
-          names.push("");
-          this._currentContextIds = names;
-        }
-        contextIdforContexts(contexts) {
-          return contexts
-            ? contexts
-                .map((context) =>
-                  context.id === 0 && context.iterationId === 0
-                    ? ""
-                    : `${context.frameName}-${context.iterationId}`
-                )
-                .join("/")
-            : "";
-        }
-        /**
-         * Enter a new frame, a new context is pushed on the current context list.
-         * @param frameId new frame id
-         */
-        enterFrame(frameId) {
-          if (this.contexts) {
-            this.lastId++;
-            this.contexts = this.contexts.slice();
-            this.contexts.push(this.newFrame(this.lastId, frameId));
-            this._currentContextIds.unshift(this.contextIdforContexts(this.contexts));
-          }
-        }
-        /**
-         * Exit the current frame, the last context is removed from the current
-         * context list.
-         */
-        exitFrame() {
-          if (this.contexts && this.contexts.length > 1) {
-            this.contexts = this.contexts.slice();
-            this.contexts.splice(-1);
-            this.currentContextIds.shift();
-          } else {
-            throw new Error("Cannot exit frame, the context is empty");
-          }
-        }
-        /**
-         * Enter the next iteration of a loop, the iteration id of last context is
-         * increased.
-         */
-        nextIteration() {
-          if (this.contexts && this.contexts.length > 0) {
-            this.contexts = this.contexts.slice();
-            this.lastId++;
-            const context = Object.assign({}, this.contexts[this.contexts.length - 1]);
-            context.iterationId += 1;
-            context.id = this.lastId;
-            this.contexts.splice(-1, 1, context);
-            this._currentContextIds.splice(0, 1, this.contextIdforContexts(this.contexts));
-          } else {
-            throw new Error("Cannot increase frame iteration, the context is empty");
-          }
-        }
-        getWeight(name) {
-          return this.weightMap[name];
-        }
-        addTensorArray(tensorArray) {
-          this.tensorArrayMap[tensorArray.id] = tensorArray;
-        }
-        getTensorArray(id) {
-          return this.tensorArrayMap[id];
-        }
-      }
-      //# sourceMappingURL=execution_context.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/model_analysis.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Given graph inputs and desired outputs, find the minimal set of nodes
-       * to execute in order to compute the outputs. In addition return other useful
-       * info such:
-       * - Missing inputs needed to compute the output.
-       * - Whether the subgraph contains dynamic ops (control flow, dynamic shape).
-       * - Alternative inputs in order to avoid async (dynamic op) execution.
-       */
-      function getExecutionSubgraph(inputs, outputs, weightMap) {
-        const usedNodes = new Set();
-        const missingInputs = [];
-        let dynamicNode = null;
-        let syncInputs = null;
-        // Start with the outputs, going backwards and find all the nodes that are
-        // needed to compute those outputs.
-        const seen = new Set();
-        const inputNodeNames = Object.keys(inputs).map(
-          (name) => Object(utils["e" /* parseNodeName */])(name)[0]
-        );
-        const frontier = [...outputs];
-        while (frontier.length > 0) {
-          const node = frontier.pop();
-          if (isControlFlow(node) || isDynamicShape(node)) {
-            if (dynamicNode == null) {
-              dynamicNode = node;
-              syncInputs = dynamicNode.children
-                .map((child) => child.name)
-                .filter((name) => usedNodes.has(name));
-            }
-          }
-          usedNodes.add(node.name);
-          // Weights are dead end since we already have their values.
-          if (weightMap[node.name] != null) {
-            continue;
-          }
-          // This node is a dead end since it's one of the user-provided inputs.
-          if (inputNodeNames.indexOf(node.name) !== -1) {
-            continue;
-          }
-          if (node.inputs.length === 0) {
-            missingInputs.push(node.name);
-            continue;
-          }
-          node.inputs.forEach((input) => {
-            // Don't add to the frontier if it is already there.
-            if (seen.has(input.name)) {
-              return;
-            }
-            seen.add(input.name);
-            frontier.push(input);
-          });
-        }
-        return { inputs, outputs, usedNodes, missingInputs, dynamicNode, syncInputs };
-      }
-      /**
-       * Given the execution info, return a list of nodes in topological order that
-       * need to be executed to compute the output.
-       */
-      function getNodesInTopologicalOrder(graph, weightMap, executionInfo) {
-        const { usedNodes, inputs } = executionInfo;
-        const frontier = [];
-        const inputNodes = Object.keys(inputs)
-          .map((name) => Object(utils["e" /* parseNodeName */])(name)[0])
-          .map((name) => graph.nodes[name]);
-        inputNodes.forEach((input) => {
-          if (usedNodes.has(input.name)) {
-            frontier.push(input);
-          }
-        });
-        graph.weights.forEach((weight) => {
-          if (usedNodes.has(weight.name)) {
-            frontier.push(weight);
-          }
-        });
-        const seen = new Set();
-        const orderedNodes = [];
-        while (frontier.length > 0) {
-          const node = frontier.pop();
-          seen.add(node.name);
-          if (!weightMap[node.name]) {
-            orderedNodes.push(node);
-          }
-          node.children.forEach((child) => {
-            if (
-              !seen.has(child.name) &&
-              usedNodes.has(child.name) &&
-              child.inputs.every((input) => seen.has(input.name))
-            ) {
-              frontier.push(child);
-            }
-          });
-        }
-        return orderedNodes;
-      }
-      const CONTROL_FLOW_OPS = [
-        "Switch",
-        "Merge",
-        "Enter",
-        "Exit",
-        "NextIteration",
-        "StatelessIf",
-        "StatelessWhile",
-      ];
-      const DYNAMIC_SHAPE_OPS = [
-        "NonMaxSuppressionV2",
-        "NonMaxSuppressionV3",
-        "NonMaxSuppressionV5",
-        "Where",
-      ];
-      function isControlFlow(node) {
-        return CONTROL_FLOW_OPS.indexOf(node.op) >= 0;
-      }
-      function isDynamicShape(node) {
-        return DYNAMIC_SHAPE_OPS.indexOf(node.op) >= 0;
-      }
-      //# sourceMappingURL=model_analysis.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/graph_executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class graph_executor_GraphExecutor {
-        /**
-         *
-         * @param graph Graph the model or function graph to be executed.
-         * @param parent When building function exector you need to set the parent
-         * executor. Since the weights and function executor maps are set at parant
-         * level, that function executor can access the function maps and weight maps
-         * through the parent.
-         */
-        constructor(graph, parent) {
-          this.graph = graph;
-          this.parent = parent;
-          this.compiledMap = new Map();
-          this._weightMap = {};
-          this.SEPERATOR = ",";
-          this._functions = {};
-          this._functionExecutorMap = {};
-          this._outputs = graph.outputs;
-          this._inputs = graph.inputs;
-          this._signature = graph.signature;
-          this._functions = graph.functions;
-          // create sub-graph executors
-          if (graph.functions != null) {
-            Object.keys(graph.functions).forEach((name) => {
-              this._functionExecutorMap[name] = new graph_executor_GraphExecutor(
-                graph.functions[name],
-                this
-              );
-            });
-          }
-        }
-        get weightIds() {
-          return this.parent ? this.parent.weightIds : this._weightIds;
-        }
-        get functionExecutorMap() {
-          return this.parent ? this.parent.functionExecutorMap : this._functionExecutorMap;
-        }
-        get weightMap() {
-          return this.parent ? this.parent.weightMap : this._weightMap;
-        }
-        set weightMap(weightMap) {
-          const weightIds = Object.keys(weightMap).map((key) =>
-            weightMap[key].map((tensor) => tensor.id)
-          );
-          this._weightIds = [].concat(...weightIds);
-          this._weightMap = weightMap;
-        }
-        get inputs() {
-          return this._inputs.map((node) => {
-            return {
-              name: node.name,
-              shape: node.attrParams["shape"] ? node.attrParams["shape"].value : undefined,
-              dtype: node.attrParams["dtype"] ? node.attrParams["dtype"].value : undefined,
-            };
-          });
-        }
-        get outputs() {
-          return this._outputs.map((node) => {
-            return {
-              name: node.name,
-              shape: node.attrParams["shape"] ? node.attrParams["shape"].value : undefined,
-              dtype: node.attrParams["dtype"] ? node.attrParams["dtype"].value : undefined,
-            };
-          });
-        }
-        get inputNodes() {
-          return this._inputs.map((node) => node.signatureKey || node.name);
-        }
-        get outputNodes() {
-          return this._outputs.map((node) => {
-            const name = node.signatureKey || node.name;
-            return node.defaultOutput ? `${name}:${node.defaultOutput}` : name;
-          });
-        }
-        get functions() {
-          return Object.keys(this._functions).reduce((map, key) => {
-            map[key] = this._functions[key].signature;
-            return map;
-          }, {});
-        }
-        getCompilationKey(inputs, outputs) {
-          const sortedInputs = inputs.map((node) => node.name).sort();
-          const sortedOutputs = outputs.map((node) => node.name).sort();
-          return sortedInputs.join(this.SEPERATOR) + "--" + sortedOutputs.join(this.SEPERATOR);
-        }
-        /**
-         * Compiles the inference graph and returns the minimal set of nodes that are
-         * required for execution, in the correct execution order.
-         */
-        compile(inputs, outputs) {
-          const executionInfo = getExecutionSubgraph(inputs, outputs, this.weightMap);
-          const { missingInputs, dynamicNode, syncInputs } = executionInfo;
-          if (dynamicNode != null) {
-            throw new Error(
-              `This execution contains the node '${dynamicNode.name}', which has ` +
-                `the dynamic op '${dynamicNode.op}'. Please use ` +
-                `model.executeAsync() instead. Alternatively, to avoid the ` +
-                `dynamic ops, specify the inputs [${syncInputs}]`
-            );
-          }
-          if (missingInputs.length > 0) {
-            const outNames = outputs.map((n) => n.name);
-            const inNames = Object.keys(inputs);
-            throw new Error(
-              `Cannot compute the outputs [${outNames}] from the provided inputs ` +
-                `[${inNames}]. Missing the following inputs: [${missingInputs}]`
-            );
-          }
-          return getNodesInTopologicalOrder(this.graph, this.weightMap, executionInfo);
-        }
-        /**
-         * Executes the inference for given input tensors.
-         * @param inputs Tensor map for the model inputs, keyed by the input node
-         * names.
-         * @param outputs output node name from the Tensorflow model, if no outputs
-         * are specified, the default outputs of the model would be used. You can
-         * inspect intermediate nodes of the model by adding them to the outputs
-         * array.
-         */
-        execute(inputs, outputs) {
-          inputs = this.mapInputs(inputs);
-          const names = Object.keys(inputs).sort();
-          this.checkInputs(inputs);
-          this.checkInputShapeAndType(inputs);
-          outputs = this.mapOutputs(outputs);
-          this.checkOutputs(outputs);
-          const inputNodes = names.map(
-            (name) => this.graph.nodes[Object(utils["e" /* parseNodeName */])(name)[0]]
-          );
-          const outputNodes = outputs.map(
-            (name) => this.graph.nodes[Object(utils["e" /* parseNodeName */])(name)[0]]
-          );
-          const compilationKey = this.getCompilationKey(inputNodes, outputNodes);
-          // Do nothing if the compiled graph cache contains the input.
-          let orderedNodes = this.compiledMap.get(compilationKey);
-          if (orderedNodes == null) {
-            orderedNodes = this.compile(inputs, outputNodes);
-            this.compiledMap.set(compilationKey, orderedNodes);
-          }
-          const tensorArrayMap = {};
-          return Object(dist["tidy"])(() => {
-            const context = new ExecutionContext(
-              this.weightMap,
-              tensorArrayMap,
-              this.functionExecutorMap
-            );
-            const tensorsMap = Object.assign({}, this.weightMap);
-            Object.keys(inputs).forEach((name) => {
-              const [nodeName, index] = Object(utils["e" /* parseNodeName */])(name);
-              const tensors = [];
-              tensors[index] = inputs[name];
-              tensorsMap[nodeName] = tensors;
-            });
-            const tensorsToKeep = this.getFrozenTensorIds(tensorsMap);
-            const intermediateTensorConsumerCount = {};
-            for (let i = 0; i < orderedNodes.length; i++) {
-              const node = orderedNodes[i];
-              if (!tensorsMap[node.name]) {
-                const tensors = operation_executor_executeOp(node, tensorsMap, context);
-                if (tensors instanceof Promise) {
-                  throw new Error(
-                    `The execution of the op '${node.op}' returned a promise. ` +
-                      `Please use model.executeAsync() instead.`
-                  );
-                }
-                tensorsMap[node.name] = tensors;
-                this.checkTensorForDisposal(
-                  node.name,
-                  node,
-                  tensorsMap,
-                  context,
-                  tensorsToKeep,
-                  outputs,
-                  intermediateTensorConsumerCount
-                );
-              }
-            }
-            return outputs.map((name) =>
-              Object(utils["c" /* getTensor */])(name, tensorsMap, context)
-            );
-          });
-        }
-        getFrozenTensorIds(tensorMap) {
-          const ids = [].concat.apply(
-            [],
-            Object.keys(tensorMap)
-              .map((key) => tensorMap[key])
-              .map((tensors) => tensors.map((tensor) => tensor.id))
-          );
-          return new Set(ids);
-        }
-        checkTensorForDisposal(
-          nodeName,
-          node,
-          tensorMap,
-          context,
-          tensorsToKeep,
-          outputNames,
-          intermediateTensorConsumerCount
-        ) {
-          // Skip output nodes and any control flow nodes, since its dependency is
-          // tricky to track correctly.
-          if (node.category === "control" || outputNames.indexOf(nodeName) !== -1) {
-            return;
-          }
-          tensorMap[nodeName].forEach((tensor) => {
-            if (tensor != null) {
-              intermediateTensorConsumerCount[tensor.id] =
-                (intermediateTensorConsumerCount[tensor.id] || 0) + node.children.length;
-            }
-          });
-          node.inputs.forEach((input) => {
-            // Skip any control flow nodes, since its dependency is tricky to track
-            // correctly.
-            if (input.category !== "control") {
-              const tensors = Object(utils["d" /* getTensorsForCurrentContenxt */])(
-                input.name,
-                tensorMap,
-                context
-              );
-              if (tensors != null) {
-                tensors.forEach((tensor) => {
-                  if (tensor && !tensorsToKeep.has(tensor.id)) {
-                    const count = intermediateTensorConsumerCount[tensor.id];
-                    if (count === 1) {
-                      tensor.dispose();
-                      delete intermediateTensorConsumerCount[tensor.id];
-                    } else if (count != null) {
-                      // only intermediate nodes has count set, inputs and weights are
-                      // not.
-                      intermediateTensorConsumerCount[tensor.id]--;
-                    }
-                  }
-                });
-              }
-            }
-          });
-        }
-        /**
-         * Executes the inference for given input tensors in Async fashion.
-         * @param inputs Tensor map for the model inputs, keyed by the input node
-         * names.
-         * @param outputs output node name from the Tensorflow model, if no outputs
-         * are specified, the default outputs of the model would be used. You can
-         * inspect intermediate nodes of the model by adding them to the outputs
-         * array.
-         * @param disableWarning disable the no dynamic ops warning message, default
-         * to false
-         */
-        async executeAsync(inputs, outputs, disableWarning = false) {
-          inputs = this.mapInputs(inputs);
-          this.checkInputs(inputs);
-          this.checkInputShapeAndType(inputs);
-          outputs = this.mapOutputs(outputs);
-          this.checkOutputs(outputs);
-          const tensorArrayMap = {};
-          const context = new ExecutionContext(
-            this.weightMap,
-            tensorArrayMap,
-            this.functionExecutorMap
-          );
-          // Graph with control flow op requires runtime evaluation of the execution
-          // order, while without control flow the execution order is pre-determined
-          // in the compile method.
-          const tensorMap = await this.executeWithControlFlow(
-            inputs,
-            context,
-            outputs,
-            disableWarning
-          );
-          const results = outputs.map((name) =>
-            Object(utils["c" /* getTensor */])(name, tensorMap, context)
-          );
-          // dispose all the intermediate tensors
-          const outputIds = new Set(results.map((t) => t.id));
-          const inputIds = new Set(Object.keys(inputs).map((name) => inputs[name].id));
-          Object.keys(tensorMap).forEach((key) => {
-            const tensorArray = tensorMap[key];
-            tensorArray.forEach((tensor) => {
-              if (
-                tensor &&
-                !tensor.isDisposed &&
-                !outputIds.has(tensor.id) &&
-                !inputIds.has(tensor.id) &&
-                this.weightIds.indexOf(tensor.id) === -1
-              ) {
-                tensor.dispose();
-              }
-            });
-          });
-          return results;
-        }
-        async executeFunctionAsync(inputs) {
-          const mappedInputs = inputs.reduce((map, tensor, index) => {
-            map[this.inputs[index].name] = tensor;
-            return map;
-          }, {});
-          return this.executeAsync(mappedInputs, this.outputNodes, true);
-        }
-        /**
-         * When there are control flow nodes in the graph, the graph execution use
-         * ExecutionContext to keep track of the frames and loop iterators.
-         * @param inputs placeholder tensors for the graph.
-         * @param context the execution context object for current execution.
-         * @param disableWarning disable no async op warning
-         */
-        async executeWithControlFlow(inputs, context, outputNames, disableWarning) {
-          const names = Object.keys(inputs);
-          const inputNodes = names.map(
-            (name) => this.graph.nodes[Object(utils["e" /* parseNodeName */])(name)[0]]
-          );
-          const outputNodes = outputNames.map(
-            (name) => this.graph.nodes[Object(utils["e" /* parseNodeName */])(name)[0]]
-          );
-          const { usedNodes, missingInputs, dynamicNode, syncInputs } = getExecutionSubgraph(
-            inputs,
-            outputNodes,
-            this.weightMap
-          );
-          const stack = [...inputNodes, ...this.graph.weights].map((node) => {
-            return { node, contexts: context.currentContext };
-          });
-          const tensorsMap = Object.assign({}, this.weightMap);
-          Object.keys(inputs).forEach((name) => {
-            const [nodeName, index] = Object(utils["e" /* parseNodeName */])(name);
-            const tensors = [];
-            tensors[index] = inputs[name];
-            tensorsMap[nodeName] = tensors;
-          });
-          const intermediateTensorConsumerCount = {};
-          const tensorsToKeep = this.getFrozenTensorIds(tensorsMap);
-          const added = {};
-          while (stack.length > 0) {
-            const promises = this.processStack(
-              inputNodes,
-              stack,
-              context,
-              tensorsMap,
-              added,
-              tensorsToKeep,
-              outputNames,
-              intermediateTensorConsumerCount,
-              usedNodes
-            );
-            await Promise.all(promises);
-          }
-          if (dynamicNode == null && !disableWarning) {
-            console.warn(
-              `This model execution did not contain any nodes with control flow ` +
-                `or dynamic output shapes. You can use model.execute() instead.`
-            );
-          }
-          const missingOutputs = outputNodes
-            .filter(
-              (node) =>
-                !isControlFlow(node) &&
-                !Object(utils["c" /* getTensor */])(node.name, tensorsMap, context)
-            )
-            .map((node) => node.name);
-          if (missingOutputs.length > 0) {
-            let alternativeMsg = "";
-            if (dynamicNode != null) {
-              alternativeMsg =
-                `Alternatively, to avoid the dynamic ops, use model.execute() ` +
-                `and specify the inputs [${syncInputs}]`;
-            }
-            throw new Error(
-              `Cannot compute the outputs [${missingOutputs}] from the provided ` +
-                `inputs [${names}]. Consider providing the following inputs: ` +
-                `[${missingInputs}]. ${alternativeMsg}`
-            );
-          }
-          return tensorsMap;
-        }
-        processStack(
-          inputNodes,
-          stack,
-          context,
-          tensorMap,
-          added,
-          tensorsToKeep,
-          outputNames,
-          intermediateTensorConsumerCount,
-          usedNodes
-        ) {
-          const promises = [];
-          while (stack.length > 0) {
-            const item = stack.pop();
-            context.currentContext = item.contexts;
-            let nodeName = "";
-            // The tensor of the Enter op with isConstant set should be set
-            // in the parent scope, so it will be available as constant for the
-            // whole loop.
-            if (
-              item.node.op === "Enter" &&
-              Object(utils["b" /* getParamValue */])("isConstant", item.node, tensorMap, context)
-            ) {
-              [nodeName] = Object(utils["a" /* getNodeNameAndIndex */])(item.node.name, context);
-            }
-            // only process nodes that are not provided as input nodes.
-            if (inputNodes.indexOf(item.node) === -1) {
-              const tensors = operation_executor_executeOp(item.node, tensorMap, context);
-              if (!nodeName) {
-                [nodeName] = Object(utils["a" /* getNodeNameAndIndex */])(item.node.name, context);
-              }
-              const currentContext = context.currentContext;
-              if (tensors instanceof Promise) {
-                promises.push(
-                  tensors.then((t) => {
-                    tensorMap[nodeName] = t;
-                    context.currentContext = currentContext;
-                    this.checkTensorForDisposal(
-                      nodeName,
-                      item.node,
-                      tensorMap,
-                      context,
-                      tensorsToKeep,
-                      outputNames,
-                      intermediateTensorConsumerCount
-                    );
-                    this.processChildNodes(item.node, stack, context, tensorMap, added, usedNodes);
-                    return t;
-                  })
-                );
-              } else {
-                tensorMap[nodeName] = tensors;
-                this.checkTensorForDisposal(
-                  nodeName,
-                  item.node,
-                  tensorMap,
-                  context,
-                  tensorsToKeep,
-                  outputNames,
-                  intermediateTensorConsumerCount
-                );
-                this.processChildNodes(item.node, stack, context, tensorMap, added, usedNodes);
-              }
-            } else {
-              this.processChildNodes(item.node, stack, context, tensorMap, added, usedNodes);
-            }
-          }
-          return promises;
-        }
-        processChildNodes(node, stack, context, tensorMap, added, usedNodes) {
-          node.children.forEach((childNode) => {
-            const [nodeName] = Object(utils["a" /* getNodeNameAndIndex */])(
-              childNode.name,
-              context
-            );
-            if (added[nodeName] || !usedNodes.has(childNode.name)) {
-              return;
-            }
-            // Merge op can be pushed if any of its inputs has value.
-            if (childNode.op === "Merge") {
-              if (
-                childNode.inputNames.some((name) => {
-                  return !!Object(utils["c" /* getTensor */])(name, tensorMap, context);
-                })
-              ) {
-                added[nodeName] = true;
-                stack.push({ contexts: context.currentContext, node: childNode });
-              }
-            } // Otherwise all inputs must to have value.
-            else if (
-              childNode.inputNames.every((name) => {
-                return !!Object(utils["c" /* getTensor */])(name, tensorMap, context);
-              })
-            ) {
-              added[nodeName] = true;
-              stack.push({ contexts: context.currentContext, node: childNode });
-            }
-          });
-        }
-        /**
-         * Releases the memory used by the weight tensors.
-         */
-        dispose() {
-          Object.keys(this.weightMap).forEach((key) =>
-            this.weightMap[key].forEach((tensor) => tensor.dispose())
-          );
-        }
-        checkInputShapeAndType(inputs) {
-          Object.keys(inputs).forEach((name) => {
-            const input = inputs[name];
-            const [nodeName] = Object(utils["e" /* parseNodeName */])(name);
-            const node = this.graph.nodes[nodeName];
-            if (node.attrParams["shape"] && node.attrParams["shape"].value) {
-              const shape = node.attrParams["shape"].value;
-              const match =
-                shape.length === input.shape.length &&
-                input.shape.every((dim, index) => shape[index] === -1 || shape[index] === dim);
-              dist["util"].assert(
-                match,
-                () =>
-                  `The shape of dict['${node.name}'] provided in ` +
-                  `model.execute(dict) must be [${shape}], but was ` +
-                  `[${input.shape}]`
-              );
-            }
-            if (node.attrParams["dtype"] && node.attrParams["dtype"].value) {
-              dist["util"].assert(
-                input.dtype === node.attrParams["dtype"].value,
-                () =>
-                  `The dtype of dict['${node.name}'] provided in ` +
-                  `model.execute(dict) must be ` +
-                  `${node.attrParams["dtype"].value}, but was ${input.dtype}`
-              );
-            }
-          });
-        }
-        mapInputs(inputs) {
-          const result = {};
-          for (const inputName in inputs) {
-            if (
-              this._signature != null &&
-              this._signature.inputs != null &&
-              this._signature.inputs[inputName] != null
-            ) {
-              const tensor = this._signature.inputs[inputName];
-              result[tensor.name] = inputs[inputName];
-            } else {
-              result[inputName] = inputs[inputName];
-            }
-          }
-          return result;
-        }
-        checkInputs(inputs) {
-          const notInGraph = Object.keys(inputs).filter((name) => {
-            const [nodeName] = Object(utils["e" /* parseNodeName */])(name);
-            return this.graph.nodes[nodeName] == null;
-          });
-          if (notInGraph.length > 0) {
-            throw new Error(
-              `The dict provided in model.execute(dict) has ` +
-                `keys: [${notInGraph}] that are not part of graph`
-            );
-          }
-        }
-        mapOutputs(outputs) {
-          return outputs.map((name) => {
-            if (
-              this._signature != null &&
-              this._signature.outputs != null &&
-              this._signature.outputs[name] != null
-            ) {
-              const tensor = this._signature.outputs[name];
-              return tensor.name;
-            }
-            return name;
-          }, {});
-        }
-        checkOutputs(outputs) {
-          outputs.forEach((name) => {
-            const [normalizedName] = Object(utils["e" /* parseNodeName */])(name);
-            if (!this.graph.nodes[normalizedName]) {
-              throw new Error(`The output '${name}' is not found in the graph`);
-            }
-          });
-        }
-      }
-      //# sourceMappingURL=graph_executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/graph_model.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const TFHUB_SEARCH_PARAM = "?tfjs-format=file";
-      const DEFAULT_MODEL_NAME = "model.json";
-      /**
-       * A `tf.GraphModel` is a directed, acyclic graph built from a
-       * SavedModel GraphDef and allows inference execution.
-       *
-       * A `tf.GraphModel` can only be created by loading from a model converted from
-       * a [TensorFlow SavedModel](https://www.tensorflow.org/guide/saved_model) using
-       * the command line converter tool and loaded via `tf.loadGraphModel`.
-       */
-      /** @doc {heading: 'Models', subheading: 'Classes'} */
-      class graph_model_GraphModel {
-        /**
-         * @param modelUrl url for the model, or an `io.IOHandler`.
-         * @param weightManifestUrl url for the weight file generated by
-         * scripts/convert.py script.
-         * @param requestOption options for Request, which allows to send credentials
-         * and custom headers.
-         * @param onProgress Optional, progress callback function, fired periodically
-         * before the load is completed.
-         */
-        constructor(modelUrl, loadOptions = {}) {
-          this.modelUrl = modelUrl;
-          this.loadOptions = loadOptions;
-          this.version = "n/a";
-          if (loadOptions == null) {
-            this.loadOptions = {};
-          }
-        }
-        // Returns the version information for the tensorflow model GraphDef.
-        get modelVersion() {
-          return this.version;
-        }
-        get inputNodes() {
-          return this.executor.inputNodes;
-        }
-        get outputNodes() {
-          return this.executor.outputNodes;
-        }
-        get inputs() {
-          return this.executor.inputs;
-        }
-        get outputs() {
-          return this.executor.outputs;
-        }
-        get weights() {
-          return this.executor.weightMap;
-        }
-        findIOHandler() {
-          const path = this.modelUrl;
-          if (path.load != null) {
-            // Path is an IO Handler.
-            this.handler = path;
-          } else if (this.loadOptions.requestInit != null) {
-            this.handler = dist["io"].browserHTTPRequest(path, this.loadOptions);
-          } else {
-            const handlers = dist["io"].getLoadHandlers(path, this.loadOptions);
-            if (handlers.length === 0) {
-              // For backward compatibility: if no load handler can be found,
-              // assume it is a relative http path.
-              handlers.push(dist["io"].browserHTTPRequest(path, this.loadOptions));
-            } else if (handlers.length > 1) {
-              throw new Error(
-                `Found more than one (${handlers.length}) load handlers for ` + `URL '${[path]}'`
-              );
-            }
-            this.handler = handlers[0];
-          }
-        }
-        /**
-         * Loads the model and weight files, construct the in memory weight map and
-         * compile the inference graph.
-         */
-        async load() {
-          this.findIOHandler();
-          if (this.handler.load == null) {
-            throw new Error(
-              "Cannot proceed with model loading because the IOHandler provided " +
-                "does not have the `load` method implemented."
-            );
-          }
-          const artifacts = await this.handler.load();
-          return this.loadSync(artifacts);
-        }
-        /**
-         * Synchronously construct the in memory weight map and
-         * compile the inference graph.
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes', ignoreCI: true} */
-        loadSync(artifacts) {
-          this.artifacts = artifacts;
-          const graph = this.artifacts.modelTopology;
-          let signature = {};
-          if (this.artifacts.userDefinedMetadata != null) {
-            signature = this.artifacts.userDefinedMetadata.signature; // tslint:disable-next-line:no-any
-          }
-          this.version = `${graph.versions.producer}.${graph.versions.minConsumer}`;
-          const weightMap = dist["io"].decodeWeights(
-            this.artifacts.weightData,
-            this.artifacts.weightSpecs
-          );
-          this.executor = new graph_executor_GraphExecutor(
-            operation_mapper["a" /* OperationMapper */].Instance.transformGraph(graph, signature)
-          );
-          this.executor.weightMap = this.convertTensorMapToTensorsMap(weightMap);
-          return true;
-        }
-        /**
-         * Save the configuration and/or weights of the GraphModel.
-         *
-         * An `IOHandler` is an object that has a `save` method of the proper
-         * signature defined. The `save` method manages the storing or
-         * transmission of serialized data ("artifacts") that represent the
-         * model's topology and weights onto or via a specific medium, such as
-         * file downloads, local storage, IndexedDB in the web browser and HTTP
-         * requests to a server. TensorFlow.js provides `IOHandler`
-         * implementations for a number of frequently used saving mediums, such as
-         * `tf.io.browserDownloads` and `tf.io.browserLocalStorage`. See `tf.io`
-         * for more details.
-         *
-         * This method also allows you to refer to certain types of `IOHandler`s
-         * as URL-like string shortcuts, such as 'localstorage://' and
-         * 'indexeddb://'.
-         *
-         * Example 1: Save `model`'s topology and weights to browser [local
-         * storage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage);
-         * then load it back.
-         *
-         * ```js
-         * const modelUrl =
-         *    'https://storage.googleapis.com/tfjs-models/savedmodel/mobilenet_v2_1.0_224/model.json';
-         * const model = await tf.loadGraphModel(modelUrl);
-         * const zeros = tf.zeros([1, 224, 224, 3]);
-         * model.predict(zeros).print();
-         *
-         * const saveResults = await model.save('localstorage://my-model-1');
-         *
-         * const loadedModel = await tf.loadGraphModel('localstorage://my-model-1');
-         * console.log('Prediction from loaded model:');
-         * model.predict(zeros).print();
-         * ```
-         *
-         * @param handlerOrURL An instance of `IOHandler` or a URL-like,
-         * scheme-based string shortcut for `IOHandler`.
-         * @param config Options for saving the model.
-         * @returns A `Promise` of `SaveResult`, which summarizes the result of
-         * the saving, such as byte sizes of the saved artifacts for the model's
-         *   topology and weight values.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes', ignoreCI: true}
-         */
-        async save(handlerOrURL, config) {
-          if (typeof handlerOrURL === "string") {
-            const handlers = dist["io"].getSaveHandlers(handlerOrURL);
-            if (handlers.length === 0) {
-              throw new Error(`Cannot find any save handlers for URL '${handlerOrURL}'`);
-            } else if (handlers.length > 1) {
-              throw new Error(
-                `Found more than one (${handlers.length}) save handlers for ` +
-                  `URL '${handlerOrURL}'`
-              );
-            }
-            handlerOrURL = handlers[0];
-          }
-          if (handlerOrURL.save == null) {
-            throw new Error(
-              "GraphModel.save() cannot proceed because the IOHandler " +
-                "provided does not have the `save` attribute defined."
-            );
-          }
-          return handlerOrURL.save(this.artifacts);
-        }
-        /**
-         * Execute the inference for the input tensors.
-         *
-         * @param input The input tensors, when there is single input for the model,
-         * inputs param should be a `tf.Tensor`. For models with mutliple inputs,
-         * inputs params should be in either `tf.Tensor`[] if the input order is
-         * fixed, or otherwise NamedTensorMap format.
-         *
-         * For model with multiple inputs, we recommend you use NamedTensorMap as the
-         * input type, if you use `tf.Tensor`[], the order of the array needs to
-         * follow the
-         * order of inputNodes array. @see {@link GraphModel.inputNodes}
-         *
-         * You can also feed any intermediate nodes using the NamedTensorMap as the
-         * input type. For example, given the graph
-         *    InputNode => Intermediate => OutputNode,
-         * you can execute the subgraph Intermediate => OutputNode by calling
-         *    model.execute('IntermediateNode' : tf.tensor(...));
-         *
-         * This is useful for models that uses tf.dynamic_rnn, where the intermediate
-         * state needs to be fed manually.
-         *
-         * For batch inference execution, the tensors for each input need to be
-         * concatenated together. For example with mobilenet, the required input shape
-         * is [1, 244, 244, 3], which represents the [batch, height, width, channel].
-         * If we are provide a batched data of 100 images, the input tensor should be
-         * in the shape of [100, 244, 244, 3].
-         *
-         * @param config Prediction configuration for specifying the batch size and
-         * output node names. Currently the batch size option is ignored for graph
-         * model.
-         *
-         * @returns Inference result tensors. The output would be single `tf.Tensor`
-         * if model has single output node, otherwise Tensor[] or NamedTensorMap[]
-         * will be returned for model with multiple outputs.
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes'} */
-        predict(inputs, config) {
-          return this.execute(inputs, this.outputNodes);
-        }
-        normalizeInputs(inputs) {
-          if (!(inputs instanceof dist["Tensor"]) && !Array.isArray(inputs)) {
-            // The input is already a NamedTensorMap.
-            return inputs;
-          }
-          inputs = Array.isArray(inputs) ? inputs : [inputs];
-          if (inputs.length !== this.inputNodes.length) {
-            throw new Error(
-              "Input tensor count mismatch," +
-                `the graph model has ${this.inputNodes.length} placeholders, ` +
-                `while there are ${inputs.length} input tensors.`
-            );
-          }
-          return this.inputNodes.reduce((map, inputName, i) => {
-            map[inputName] = inputs[i];
-            return map;
-          }, {});
-        }
-        normalizeOutputs(outputs) {
-          outputs = outputs || this.outputNodes;
-          return !Array.isArray(outputs) ? [outputs] : outputs;
-        }
-        /**
-         * Executes inference for the model for given input tensors.
-         * @param inputs tensor, tensor array or tensor map of the inputs for the
-         * model, keyed by the input node names.
-         * @param outputs output node name from the Tensorflow model, if no
-         * outputs are specified, the default outputs of the model would be used.
-         * You can inspect intermediate nodes of the model by adding them to the
-         * outputs array.
-         *
-         * @returns A single tensor if provided with a single output or no outputs
-         * are provided and there is only one default output, otherwise return a
-         * tensor array. The order of the tensor array is the same as the outputs
-         * if provided, otherwise the order of outputNodes attribute of the model.
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes'} */
-        execute(inputs, outputs) {
-          inputs = this.normalizeInputs(inputs);
-          outputs = this.normalizeOutputs(outputs);
-          const result = this.executor.execute(inputs, outputs);
-          return result.length > 1 ? result : result[0];
-        }
-        /**
-         * Executes inference for the model for given input tensors in async
-         * fashion, use this method when your model contains control flow ops.
-         * @param inputs tensor, tensor array or tensor map of the inputs for the
-         * model, keyed by the input node names.
-         * @param outputs output node name from the Tensorflow model, if no outputs
-         * are specified, the default outputs of the model would be used. You can
-         * inspect intermediate nodes of the model by adding them to the outputs
-         * array.
-         *
-         * @returns A Promise of single tensor if provided with a single output or
-         * no outputs are provided and there is only one default output, otherwise
-         * return a tensor map.
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes'} */
-        async executeAsync(inputs, outputs) {
-          inputs = this.normalizeInputs(inputs);
-          outputs = this.normalizeOutputs(outputs);
-          const result = await this.executor.executeAsync(inputs, outputs);
-          return result.length > 1 ? result : result[0];
-        }
-        convertTensorMapToTensorsMap(map) {
-          return Object.keys(map).reduce((newMap, key) => {
-            newMap[key] = [map[key]];
-            return newMap;
-          }, {});
-        }
-        /**
-         * Releases the memory used by the weight tensors.
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes'} */
-        dispose() {
-          this.executor.dispose();
-        }
-      }
-      /**
-       * Load a graph model given a URL to the model definition.
-       *
-       * Example of loading MobileNetV2 from a URL and making a prediction with a
-       * zeros input:
-       *
-       * ```js
-       * const modelUrl =
-       *    'https://storage.googleapis.com/tfjs-models/savedmodel/mobilenet_v2_1.0_224/model.json';
-       * const model = await tf.loadGraphModel(modelUrl);
-       * const zeros = tf.zeros([1, 224, 224, 3]);
-       * model.predict(zeros).print();
-       * ```
-       *
-       * Example of loading MobileNetV2 from a TF Hub URL and making a prediction with
-       * a zeros input:
-       *
-       * ```js
-       * const modelUrl =
-       *    'https://tfhub.dev/google/imagenet/mobilenet_v2_140_224/classification/2';
-       * const model = await tf.loadGraphModel(modelUrl, {fromTFHub: true});
-       * const zeros = tf.zeros([1, 224, 224, 3]);
-       * model.predict(zeros).print();
-       * ```
-       * @param modelUrl The url or an `io.IOHandler` that loads the model.
-       * @param options Options for the HTTP request, which allows to send credentials
-       *    and custom headers.
-       */
-      /** @doc {heading: 'Models', subheading: 'Loading'} */
-      async function loadGraphModel(modelUrl, options = {}) {
-        if (modelUrl == null) {
-          throw new Error(
-            "modelUrl in loadGraphModel() cannot be null. Please provide a url " +
-              "or an IOHandler that loads the model"
-          );
-        }
-        if (options == null) {
-          options = {};
-        }
-        if (options.fromTFHub) {
-          if (modelUrl.load == null) {
-            if (!modelUrl.endsWith("/")) {
-              modelUrl = modelUrl + "/";
-            }
-            modelUrl = `${modelUrl}${DEFAULT_MODEL_NAME}${TFHUB_SEARCH_PARAM}`;
-          }
-        }
-        const model = new graph_model_GraphModel(modelUrl, options);
-        await model.load();
-        return model;
-      }
-      //# sourceMappingURL=graph_model.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/version.js
-      /** @license See the LICENSE file. */
-      // This code is auto-generated, do not modify this file!
-      const version = "2.0.1";
-
-      //# sourceMappingURL=version.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/index.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      //# sourceMappingURL=index.js.map
-
-      /***/
-    },
-    /* 39 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (global) {
-        /*!
-         * The buffer module from node.js, for the browser.
-         *
-         * @author   Feross Aboukhadijeh <http://feross.org>
-         * @license  MIT
-         */
-        /* eslint-disable no-proto */
-
-        var base64 = __webpack_require__(65);
-        var ieee754 = __webpack_require__(66);
-        var isArray = __webpack_require__(67);
-
-        exports.Buffer = Buffer;
-        exports.SlowBuffer = SlowBuffer;
-        exports.INSPECT_MAX_BYTES = 50;
-
-        /**
- * If `Buffer.TYPED_ARRAY_SUPPORT`:
- *   === true    Use Uint8Array implementation (fastest)
- *   === false   Use Object implementation (most compatible, even IE6)
- *
- * Browsers that support typed arrays are IE 10+, Firefox 4+, Chrome 7+, Safari 5.1+,
- * Opera 11.6+, iOS 4.2+.
- *
- * Due to various browser bugs, sometimes the Object implementation will be used even
- * when the browser supports typed arrays.
- *
- * Note:
- *
- *   - Firefox 4-29 lacks support for adding new properties to `Uint8Array` instances,
- *     See: https://bugzilla.mozilla.org/show_bug.cgi?id=695438.
- *
- *   - Chrome 9-10 is missing the `TypedArray.prototype.subarray` function.
- *
- *   - IE10 has a broken `TypedArray.prototype.subarray` function which returns arrays of
- *     incorrect length in some situations.
-
- * We detect these buggy browsers and set `Buffer.TYPED_ARRAY_SUPPORT` to `false` so they
- * get the Object implementation, which is slower but behaves correctly.
- */
-        Buffer.TYPED_ARRAY_SUPPORT =
-          global.TYPED_ARRAY_SUPPORT !== undefined
-            ? global.TYPED_ARRAY_SUPPORT
-            : typedArraySupport();
-
-        /*
-         * Export kMaxLength after typed array support is determined.
-         */
-        exports.kMaxLength = kMaxLength();
-
-        function typedArraySupport() {
-          try {
-            var arr = new Uint8Array(1);
-            arr.__proto__ = {
-              __proto__: Uint8Array.prototype,
-              foo: function () {
-                return 42;
-              },
-            };
-            return (
-              arr.foo() === 42 && // typed array instances can be augmented
-              typeof arr.subarray === "function" && // chrome 9-10 lack `subarray`
-              arr.subarray(1, 1).byteLength === 0
-            ); // ie10 has broken `subarray`
-          } catch (e) {
-            return false;
-          }
-        }
-
-        function kMaxLength() {
-          return Buffer.TYPED_ARRAY_SUPPORT ? 0x7fffffff : 0x3fffffff;
-        }
-
-        function createBuffer(that, length) {
-          if (kMaxLength() < length) {
-            throw new RangeError("Invalid typed array length");
-          }
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            // Return an augmented `Uint8Array` instance, for best performance
-            that = new Uint8Array(length);
-            that.__proto__ = Buffer.prototype;
-          } else {
-            // Fallback: Return an object instance of the Buffer class
-            if (that === null) {
-              that = new Buffer(length);
-            }
-            that.length = length;
-          }
-
-          return that;
-        }
-
-        /**
-         * The Buffer constructor returns instances of `Uint8Array` that have their
-         * prototype changed to `Buffer.prototype`. Furthermore, `Buffer` is a subclass of
-         * `Uint8Array`, so the returned instances will have all the node `Buffer` methods
-         * and the `Uint8Array` methods. Square bracket notation works as expected -- it
-         * returns a single octet.
-         *
-         * The `Uint8Array` prototype remains unmodified.
-         */
-
-        function Buffer(arg, encodingOrOffset, length) {
-          if (!Buffer.TYPED_ARRAY_SUPPORT && !(this instanceof Buffer)) {
-            return new Buffer(arg, encodingOrOffset, length);
-          }
-
-          // Common case.
-          if (typeof arg === "number") {
-            if (typeof encodingOrOffset === "string") {
-              throw new Error("If encoding is specified then the first argument must be a string");
-            }
-            return allocUnsafe(this, arg);
-          }
-          return from(this, arg, encodingOrOffset, length);
-        }
-
-        Buffer.poolSize = 8192; // not used by this implementation
-
-        // TODO: Legacy, not needed anymore. Remove in next major version.
-        Buffer._augment = function (arr) {
-          arr.__proto__ = Buffer.prototype;
-          return arr;
-        };
-
-        function from(that, value, encodingOrOffset, length) {
-          if (typeof value === "number") {
-            throw new TypeError('"value" argument must not be a number');
-          }
-
-          if (typeof ArrayBuffer !== "undefined" && value instanceof ArrayBuffer) {
-            return fromArrayBuffer(that, value, encodingOrOffset, length);
-          }
-
-          if (typeof value === "string") {
-            return fromString(that, value, encodingOrOffset);
-          }
-
-          return fromObject(that, value);
-        }
-
-        /**
-         * Functionally equivalent to Buffer(arg, encoding) but throws a TypeError
-         * if value is a number.
-         * Buffer.from(str[, encoding])
-         * Buffer.from(array)
-         * Buffer.from(buffer)
-         * Buffer.from(arrayBuffer[, byteOffset[, length]])
-         **/
-        Buffer.from = function (value, encodingOrOffset, length) {
-          return from(null, value, encodingOrOffset, length);
-        };
-
-        if (Buffer.TYPED_ARRAY_SUPPORT) {
-          Buffer.prototype.__proto__ = Uint8Array.prototype;
-          Buffer.__proto__ = Uint8Array;
-          if (
-            typeof Symbol !== "undefined" &&
-            Symbol.species &&
-            Buffer[Symbol.species] === Buffer
-          ) {
-            // Fix subarray() in ES2016. See: https://github.com/feross/buffer/pull/97
-            Object.defineProperty(Buffer, Symbol.species, {
-              value: null,
-              configurable: true,
-            });
-          }
-        }
-
-        function assertSize(size) {
-          if (typeof size !== "number") {
-            throw new TypeError('"size" argument must be a number');
-          } else if (size < 0) {
-            throw new RangeError('"size" argument must not be negative');
-          }
-        }
-
-        function alloc(that, size, fill, encoding) {
-          assertSize(size);
-          if (size <= 0) {
-            return createBuffer(that, size);
-          }
-          if (fill !== undefined) {
-            // Only pay attention to encoding if it's a string. This
-            // prevents accidentally sending in a number that would
-            // be interpretted as a start offset.
-            return typeof encoding === "string"
-              ? createBuffer(that, size).fill(fill, encoding)
-              : createBuffer(that, size).fill(fill);
-          }
-          return createBuffer(that, size);
-        }
-
-        /**
-         * Creates a new filled Buffer instance.
-         * alloc(size[, fill[, encoding]])
-         **/
-        Buffer.alloc = function (size, fill, encoding) {
-          return alloc(null, size, fill, encoding);
-        };
-
-        function allocUnsafe(that, size) {
-          assertSize(size);
-          that = createBuffer(that, size < 0 ? 0 : checked(size) | 0);
-          if (!Buffer.TYPED_ARRAY_SUPPORT) {
-            for (var i = 0; i < size; ++i) {
-              that[i] = 0;
-            }
-          }
-          return that;
-        }
-
-        /**
-         * Equivalent to Buffer(num), by default creates a non-zero-filled Buffer instance.
-         * */
-        Buffer.allocUnsafe = function (size) {
-          return allocUnsafe(null, size);
-        };
-        /**
-         * Equivalent to SlowBuffer(num), by default creates a non-zero-filled Buffer instance.
-         */
-        Buffer.allocUnsafeSlow = function (size) {
-          return allocUnsafe(null, size);
-        };
-
-        function fromString(that, string, encoding) {
-          if (typeof encoding !== "string" || encoding === "") {
-            encoding = "utf8";
-          }
-
-          if (!Buffer.isEncoding(encoding)) {
-            throw new TypeError('"encoding" must be a valid string encoding');
-          }
-
-          var length = byteLength(string, encoding) | 0;
-          that = createBuffer(that, length);
-
-          var actual = that.write(string, encoding);
-
-          if (actual !== length) {
-            // Writing a hex string, for example, that contains invalid characters will
-            // cause everything after the first invalid character to be ignored. (e.g.
-            // 'abxxcd' will be treated as 'ab')
-            that = that.slice(0, actual);
-          }
-
-          return that;
-        }
-
-        function fromArrayLike(that, array) {
-          var length = array.length < 0 ? 0 : checked(array.length) | 0;
-          that = createBuffer(that, length);
-          for (var i = 0; i < length; i += 1) {
-            that[i] = array[i] & 255;
-          }
-          return that;
-        }
-
-        function fromArrayBuffer(that, array, byteOffset, length) {
-          array.byteLength; // this throws if `array` is not a valid ArrayBuffer
-
-          if (byteOffset < 0 || array.byteLength < byteOffset) {
-            throw new RangeError("'offset' is out of bounds");
-          }
-
-          if (array.byteLength < byteOffset + (length || 0)) {
-            throw new RangeError("'length' is out of bounds");
-          }
-
-          if (byteOffset === undefined && length === undefined) {
-            array = new Uint8Array(array);
-          } else if (length === undefined) {
-            array = new Uint8Array(array, byteOffset);
-          } else {
-            array = new Uint8Array(array, byteOffset, length);
-          }
-
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            // Return an augmented `Uint8Array` instance, for best performance
-            that = array;
-            that.__proto__ = Buffer.prototype;
-          } else {
-            // Fallback: Return an object instance of the Buffer class
-            that = fromArrayLike(that, array);
-          }
-          return that;
-        }
-
-        function fromObject(that, obj) {
-          if (Buffer.isBuffer(obj)) {
-            var len = checked(obj.length) | 0;
-            that = createBuffer(that, len);
-
-            if (that.length === 0) {
-              return that;
-            }
-
-            obj.copy(that, 0, 0, len);
-            return that;
-          }
-
-          if (obj) {
-            if (
-              (typeof ArrayBuffer !== "undefined" && obj.buffer instanceof ArrayBuffer) ||
-              "length" in obj
-            ) {
-              if (typeof obj.length !== "number" || isnan(obj.length)) {
-                return createBuffer(that, 0);
-              }
-              return fromArrayLike(that, obj);
-            }
-
-            if (obj.type === "Buffer" && isArray(obj.data)) {
-              return fromArrayLike(that, obj.data);
-            }
-          }
-
-          throw new TypeError(
-            "First argument must be a string, Buffer, ArrayBuffer, Array, or array-like object."
-          );
-        }
-
-        function checked(length) {
-          // Note: cannot use `length < kMaxLength()` here because that fails when
-          // length is NaN (which is otherwise coerced to zero.)
-          if (length >= kMaxLength()) {
-            throw new RangeError(
-              "Attempt to allocate Buffer larger than maximum " +
-                "size: 0x" +
-                kMaxLength().toString(16) +
-                " bytes"
-            );
-          }
-          return length | 0;
-        }
-
-        function SlowBuffer(length) {
-          if (+length != length) {
-            // eslint-disable-line eqeqeq
-            length = 0;
-          }
-          return Buffer.alloc(+length);
-        }
-
-        Buffer.isBuffer = function isBuffer(b) {
-          return !!(b != null && b._isBuffer);
-        };
-
-        Buffer.compare = function compare(a, b) {
-          if (!Buffer.isBuffer(a) || !Buffer.isBuffer(b)) {
-            throw new TypeError("Arguments must be Buffers");
-          }
-
-          if (a === b) return 0;
-
-          var x = a.length;
-          var y = b.length;
-
-          for (var i = 0, len = Math.min(x, y); i < len; ++i) {
-            if (a[i] !== b[i]) {
-              x = a[i];
-              y = b[i];
-              break;
-            }
-          }
-
-          if (x < y) return -1;
-          if (y < x) return 1;
-          return 0;
-        };
-
-        Buffer.isEncoding = function isEncoding(encoding) {
-          switch (String(encoding).toLowerCase()) {
-            case "hex":
-            case "utf8":
-            case "utf-8":
-            case "ascii":
-            case "latin1":
-            case "binary":
-            case "base64":
-            case "ucs2":
-            case "ucs-2":
-            case "utf16le":
-            case "utf-16le":
-              return true;
-            default:
-              return false;
-          }
-        };
-
-        Buffer.concat = function concat(list, length) {
-          if (!isArray(list)) {
-            throw new TypeError('"list" argument must be an Array of Buffers');
-          }
-
-          if (list.length === 0) {
-            return Buffer.alloc(0);
-          }
-
-          var i;
-          if (length === undefined) {
-            length = 0;
-            for (i = 0; i < list.length; ++i) {
-              length += list[i].length;
-            }
-          }
-
-          var buffer = Buffer.allocUnsafe(length);
-          var pos = 0;
-          for (i = 0; i < list.length; ++i) {
-            var buf = list[i];
-            if (!Buffer.isBuffer(buf)) {
-              throw new TypeError('"list" argument must be an Array of Buffers');
-            }
-            buf.copy(buffer, pos);
-            pos += buf.length;
-          }
-          return buffer;
-        };
-
-        function byteLength(string, encoding) {
-          if (Buffer.isBuffer(string)) {
-            return string.length;
-          }
-          if (
-            typeof ArrayBuffer !== "undefined" &&
-            typeof ArrayBuffer.isView === "function" &&
-            (ArrayBuffer.isView(string) || string instanceof ArrayBuffer)
-          ) {
-            return string.byteLength;
-          }
-          if (typeof string !== "string") {
-            string = "" + string;
-          }
-
-          var len = string.length;
-          if (len === 0) return 0;
-
-          // Use a for loop to avoid recursion
-          var loweredCase = false;
-          for (;;) {
-            switch (encoding) {
-              case "ascii":
-              case "latin1":
-              case "binary":
-                return len;
-              case "utf8":
-              case "utf-8":
-              case undefined:
-                return utf8ToBytes(string).length;
-              case "ucs2":
-              case "ucs-2":
-              case "utf16le":
-              case "utf-16le":
-                return len * 2;
-              case "hex":
-                return len >>> 1;
-              case "base64":
-                return base64ToBytes(string).length;
-              default:
-                if (loweredCase) return utf8ToBytes(string).length; // assume utf8
-                encoding = ("" + encoding).toLowerCase();
-                loweredCase = true;
-            }
-          }
-        }
-        Buffer.byteLength = byteLength;
-
-        function slowToString(encoding, start, end) {
-          var loweredCase = false;
-
-          // No need to verify that "this.length <= MAX_UINT32" since it's a read-only
-          // property of a typed array.
-
-          // This behaves neither like String nor Uint8Array in that we set start/end
-          // to their upper/lower bounds if the value passed is out of range.
-          // undefined is handled specially as per ECMA-262 6th Edition,
-          // Section 13.3.3.7 Runtime Semantics: KeyedBindingInitialization.
-          if (start === undefined || start < 0) {
-            start = 0;
-          }
-          // Return early if start > this.length. Done here to prevent potential uint32
-          // coercion fail below.
-          if (start > this.length) {
-            return "";
-          }
-
-          if (end === undefined || end > this.length) {
-            end = this.length;
-          }
-
-          if (end <= 0) {
-            return "";
-          }
-
-          // Force coersion to uint32. This will also coerce falsey/NaN values to 0.
-          end >>>= 0;
-          start >>>= 0;
-
-          if (end <= start) {
-            return "";
-          }
-
-          if (!encoding) encoding = "utf8";
-
-          while (true) {
-            switch (encoding) {
-              case "hex":
-                return hexSlice(this, start, end);
-
-              case "utf8":
-              case "utf-8":
-                return utf8Slice(this, start, end);
-
-              case "ascii":
-                return asciiSlice(this, start, end);
-
-              case "latin1":
-              case "binary":
-                return latin1Slice(this, start, end);
-
-              case "base64":
-                return base64Slice(this, start, end);
-
-              case "ucs2":
-              case "ucs-2":
-              case "utf16le":
-              case "utf-16le":
-                return utf16leSlice(this, start, end);
-
-              default:
-                if (loweredCase) throw new TypeError("Unknown encoding: " + encoding);
-                encoding = (encoding + "").toLowerCase();
-                loweredCase = true;
-            }
-          }
-        }
-
-        // The property is used by `Buffer.isBuffer` and `is-buffer` (in Safari 5-7) to detect
-        // Buffer instances.
-        Buffer.prototype._isBuffer = true;
-
-        function swap(b, n, m) {
-          var i = b[n];
-          b[n] = b[m];
-          b[m] = i;
-        }
-
-        Buffer.prototype.swap16 = function swap16() {
-          var len = this.length;
-          if (len % 2 !== 0) {
-            throw new RangeError("Buffer size must be a multiple of 16-bits");
-          }
-          for (var i = 0; i < len; i += 2) {
-            swap(this, i, i + 1);
-          }
-          return this;
-        };
-
-        Buffer.prototype.swap32 = function swap32() {
-          var len = this.length;
-          if (len % 4 !== 0) {
-            throw new RangeError("Buffer size must be a multiple of 32-bits");
-          }
-          for (var i = 0; i < len; i += 4) {
-            swap(this, i, i + 3);
-            swap(this, i + 1, i + 2);
-          }
-          return this;
-        };
-
-        Buffer.prototype.swap64 = function swap64() {
-          var len = this.length;
-          if (len % 8 !== 0) {
-            throw new RangeError("Buffer size must be a multiple of 64-bits");
-          }
-          for (var i = 0; i < len; i += 8) {
-            swap(this, i, i + 7);
-            swap(this, i + 1, i + 6);
-            swap(this, i + 2, i + 5);
-            swap(this, i + 3, i + 4);
-          }
-          return this;
-        };
-
-        Buffer.prototype.toString = function toString() {
-          var length = this.length | 0;
-          if (length === 0) return "";
-          if (arguments.length === 0) return utf8Slice(this, 0, length);
-          return slowToString.apply(this, arguments);
-        };
-
-        Buffer.prototype.equals = function equals(b) {
-          if (!Buffer.isBuffer(b)) throw new TypeError("Argument must be a Buffer");
-          if (this === b) return true;
-          return Buffer.compare(this, b) === 0;
-        };
-
-        Buffer.prototype.inspect = function inspect() {
-          var str = "";
-          var max = exports.INSPECT_MAX_BYTES;
-          if (this.length > 0) {
-            str = this.toString("hex", 0, max).match(/.{2}/g).join(" ");
-            if (this.length > max) str += " ... ";
-          }
-          return "<Buffer " + str + ">";
-        };
-
-        Buffer.prototype.compare = function compare(target, start, end, thisStart, thisEnd) {
-          if (!Buffer.isBuffer(target)) {
-            throw new TypeError("Argument must be a Buffer");
-          }
-
-          if (start === undefined) {
-            start = 0;
-          }
-          if (end === undefined) {
-            end = target ? target.length : 0;
-          }
-          if (thisStart === undefined) {
-            thisStart = 0;
-          }
-          if (thisEnd === undefined) {
-            thisEnd = this.length;
-          }
-
-          if (start < 0 || end > target.length || thisStart < 0 || thisEnd > this.length) {
-            throw new RangeError("out of range index");
-          }
-
-          if (thisStart >= thisEnd && start >= end) {
-            return 0;
-          }
-          if (thisStart >= thisEnd) {
-            return -1;
-          }
-          if (start >= end) {
-            return 1;
-          }
-
-          start >>>= 0;
-          end >>>= 0;
-          thisStart >>>= 0;
-          thisEnd >>>= 0;
-
-          if (this === target) return 0;
-
-          var x = thisEnd - thisStart;
-          var y = end - start;
-          var len = Math.min(x, y);
-
-          var thisCopy = this.slice(thisStart, thisEnd);
-          var targetCopy = target.slice(start, end);
-
-          for (var i = 0; i < len; ++i) {
-            if (thisCopy[i] !== targetCopy[i]) {
-              x = thisCopy[i];
-              y = targetCopy[i];
-              break;
-            }
-          }
-
-          if (x < y) return -1;
-          if (y < x) return 1;
-          return 0;
-        };
-
-        // Finds either the first index of `val` in `buffer` at offset >= `byteOffset`,
-        // OR the last index of `val` in `buffer` at offset <= `byteOffset`.
-        //
-        // Arguments:
-        // - buffer - a Buffer to search
-        // - val - a string, Buffer, or number
-        // - byteOffset - an index into `buffer`; will be clamped to an int32
-        // - encoding - an optional encoding, relevant is val is a string
-        // - dir - true for indexOf, false for lastIndexOf
-        function bidirectionalIndexOf(buffer, val, byteOffset, encoding, dir) {
-          // Empty buffer means no match
-          if (buffer.length === 0) return -1;
-
-          // Normalize byteOffset
-          if (typeof byteOffset === "string") {
-            encoding = byteOffset;
-            byteOffset = 0;
-          } else if (byteOffset > 0x7fffffff) {
-            byteOffset = 0x7fffffff;
-          } else if (byteOffset < -0x80000000) {
-            byteOffset = -0x80000000;
-          }
-          byteOffset = +byteOffset; // Coerce to Number.
-          if (isNaN(byteOffset)) {
-            // byteOffset: it it's undefined, null, NaN, "foo", etc, search whole buffer
-            byteOffset = dir ? 0 : buffer.length - 1;
-          }
-
-          // Normalize byteOffset: negative offsets start from the end of the buffer
-          if (byteOffset < 0) byteOffset = buffer.length + byteOffset;
-          if (byteOffset >= buffer.length) {
-            if (dir) return -1;
-            else byteOffset = buffer.length - 1;
-          } else if (byteOffset < 0) {
-            if (dir) byteOffset = 0;
-            else return -1;
-          }
-
-          // Normalize val
-          if (typeof val === "string") {
-            val = Buffer.from(val, encoding);
-          }
-
-          // Finally, search either indexOf (if dir is true) or lastIndexOf
-          if (Buffer.isBuffer(val)) {
-            // Special case: looking for empty string/buffer always fails
-            if (val.length === 0) {
-              return -1;
-            }
-            return arrayIndexOf(buffer, val, byteOffset, encoding, dir);
-          } else if (typeof val === "number") {
-            val = val & 0xff; // Search for a byte value [0-255]
-            if (Buffer.TYPED_ARRAY_SUPPORT && typeof Uint8Array.prototype.indexOf === "function") {
-              if (dir) {
-                return Uint8Array.prototype.indexOf.call(buffer, val, byteOffset);
-              } else {
-                return Uint8Array.prototype.lastIndexOf.call(buffer, val, byteOffset);
-              }
-            }
-            return arrayIndexOf(buffer, [val], byteOffset, encoding, dir);
-          }
-
-          throw new TypeError("val must be string, number or Buffer");
-        }
-
-        function arrayIndexOf(arr, val, byteOffset, encoding, dir) {
-          var indexSize = 1;
-          var arrLength = arr.length;
-          var valLength = val.length;
-
-          if (encoding !== undefined) {
-            encoding = String(encoding).toLowerCase();
-            if (
-              encoding === "ucs2" ||
-              encoding === "ucs-2" ||
-              encoding === "utf16le" ||
-              encoding === "utf-16le"
-            ) {
-              if (arr.length < 2 || val.length < 2) {
-                return -1;
-              }
-              indexSize = 2;
-              arrLength /= 2;
-              valLength /= 2;
-              byteOffset /= 2;
-            }
-          }
-
-          function read(buf, i) {
-            if (indexSize === 1) {
-              return buf[i];
-            } else {
-              return buf.readUInt16BE(i * indexSize);
-            }
-          }
-
-          var i;
-          if (dir) {
-            var foundIndex = -1;
-            for (i = byteOffset; i < arrLength; i++) {
-              if (read(arr, i) === read(val, foundIndex === -1 ? 0 : i - foundIndex)) {
-                if (foundIndex === -1) foundIndex = i;
-                if (i - foundIndex + 1 === valLength) return foundIndex * indexSize;
-              } else {
-                if (foundIndex !== -1) i -= i - foundIndex;
-                foundIndex = -1;
-              }
-            }
-          } else {
-            if (byteOffset + valLength > arrLength) byteOffset = arrLength - valLength;
-            for (i = byteOffset; i >= 0; i--) {
-              var found = true;
-              for (var j = 0; j < valLength; j++) {
-                if (read(arr, i + j) !== read(val, j)) {
-                  found = false;
-                  break;
-                }
-              }
-              if (found) return i;
-            }
-          }
-
-          return -1;
-        }
-
-        Buffer.prototype.includes = function includes(val, byteOffset, encoding) {
-          return this.indexOf(val, byteOffset, encoding) !== -1;
-        };
-
-        Buffer.prototype.indexOf = function indexOf(val, byteOffset, encoding) {
-          return bidirectionalIndexOf(this, val, byteOffset, encoding, true);
-        };
-
-        Buffer.prototype.lastIndexOf = function lastIndexOf(val, byteOffset, encoding) {
-          return bidirectionalIndexOf(this, val, byteOffset, encoding, false);
-        };
-
-        function hexWrite(buf, string, offset, length) {
-          offset = Number(offset) || 0;
-          var remaining = buf.length - offset;
-          if (!length) {
-            length = remaining;
-          } else {
-            length = Number(length);
-            if (length > remaining) {
-              length = remaining;
-            }
-          }
-
-          // must be an even number of digits
-          var strLen = string.length;
-          if (strLen % 2 !== 0) throw new TypeError("Invalid hex string");
-
-          if (length > strLen / 2) {
-            length = strLen / 2;
-          }
-          for (var i = 0; i < length; ++i) {
-            var parsed = parseInt(string.substr(i * 2, 2), 16);
-            if (isNaN(parsed)) return i;
-            buf[offset + i] = parsed;
-          }
-          return i;
-        }
-
-        function utf8Write(buf, string, offset, length) {
-          return blitBuffer(utf8ToBytes(string, buf.length - offset), buf, offset, length);
-        }
-
-        function asciiWrite(buf, string, offset, length) {
-          return blitBuffer(asciiToBytes(string), buf, offset, length);
-        }
-
-        function latin1Write(buf, string, offset, length) {
-          return asciiWrite(buf, string, offset, length);
-        }
-
-        function base64Write(buf, string, offset, length) {
-          return blitBuffer(base64ToBytes(string), buf, offset, length);
-        }
-
-        function ucs2Write(buf, string, offset, length) {
-          return blitBuffer(utf16leToBytes(string, buf.length - offset), buf, offset, length);
-        }
-
-        Buffer.prototype.write = function write(string, offset, length, encoding) {
-          // Buffer#write(string)
-          if (offset === undefined) {
-            encoding = "utf8";
-            length = this.length;
-            offset = 0;
-            // Buffer#write(string, encoding)
-          } else if (length === undefined && typeof offset === "string") {
-            encoding = offset;
-            length = this.length;
-            offset = 0;
-            // Buffer#write(string, offset[, length][, encoding])
-          } else if (isFinite(offset)) {
-            offset = offset | 0;
-            if (isFinite(length)) {
-              length = length | 0;
-              if (encoding === undefined) encoding = "utf8";
-            } else {
-              encoding = length;
-              length = undefined;
-            }
-            // legacy write(string, encoding, offset, length) - remove in v0.13
-          } else {
-            throw new Error(
-              "Buffer.write(string, encoding, offset[, length]) is no longer supported"
-            );
-          }
-
-          var remaining = this.length - offset;
-          if (length === undefined || length > remaining) length = remaining;
-
-          if ((string.length > 0 && (length < 0 || offset < 0)) || offset > this.length) {
-            throw new RangeError("Attempt to write outside buffer bounds");
-          }
-
-          if (!encoding) encoding = "utf8";
-
-          var loweredCase = false;
-          for (;;) {
-            switch (encoding) {
-              case "hex":
-                return hexWrite(this, string, offset, length);
-
-              case "utf8":
-              case "utf-8":
-                return utf8Write(this, string, offset, length);
-
-              case "ascii":
-                return asciiWrite(this, string, offset, length);
-
-              case "latin1":
-              case "binary":
-                return latin1Write(this, string, offset, length);
-
-              case "base64":
-                // Warning: maxLength not taken into account in base64Write
-                return base64Write(this, string, offset, length);
-
-              case "ucs2":
-              case "ucs-2":
-              case "utf16le":
-              case "utf-16le":
-                return ucs2Write(this, string, offset, length);
-
-              default:
-                if (loweredCase) throw new TypeError("Unknown encoding: " + encoding);
-                encoding = ("" + encoding).toLowerCase();
-                loweredCase = true;
-            }
-          }
-        };
-
-        Buffer.prototype.toJSON = function toJSON() {
-          return {
-            type: "Buffer",
-            data: Array.prototype.slice.call(this._arr || this, 0),
-          };
-        };
-
-        function base64Slice(buf, start, end) {
-          if (start === 0 && end === buf.length) {
-            return base64.fromByteArray(buf);
-          } else {
-            return base64.fromByteArray(buf.slice(start, end));
-          }
-        }
-
-        function utf8Slice(buf, start, end) {
-          end = Math.min(buf.length, end);
-          var res = [];
-
-          var i = start;
-          while (i < end) {
-            var firstByte = buf[i];
-            var codePoint = null;
-            var bytesPerSequence =
-              firstByte > 0xef ? 4 : firstByte > 0xdf ? 3 : firstByte > 0xbf ? 2 : 1;
-
-            if (i + bytesPerSequence <= end) {
-              var secondByte, thirdByte, fourthByte, tempCodePoint;
-
-              switch (bytesPerSequence) {
-                case 1:
-                  if (firstByte < 0x80) {
-                    codePoint = firstByte;
-                  }
-                  break;
-                case 2:
-                  secondByte = buf[i + 1];
-                  if ((secondByte & 0xc0) === 0x80) {
-                    tempCodePoint = ((firstByte & 0x1f) << 0x6) | (secondByte & 0x3f);
-                    if (tempCodePoint > 0x7f) {
-                      codePoint = tempCodePoint;
-                    }
-                  }
-                  break;
-                case 3:
-                  secondByte = buf[i + 1];
-                  thirdByte = buf[i + 2];
-                  if ((secondByte & 0xc0) === 0x80 && (thirdByte & 0xc0) === 0x80) {
-                    tempCodePoint =
-                      ((firstByte & 0xf) << 0xc) |
-                      ((secondByte & 0x3f) << 0x6) |
-                      (thirdByte & 0x3f);
-                    if (
-                      tempCodePoint > 0x7ff &&
-                      (tempCodePoint < 0xd800 || tempCodePoint > 0xdfff)
-                    ) {
-                      codePoint = tempCodePoint;
-                    }
-                  }
-                  break;
-                case 4:
-                  secondByte = buf[i + 1];
-                  thirdByte = buf[i + 2];
-                  fourthByte = buf[i + 3];
-                  if (
-                    (secondByte & 0xc0) === 0x80 &&
-                    (thirdByte & 0xc0) === 0x80 &&
-                    (fourthByte & 0xc0) === 0x80
-                  ) {
-                    tempCodePoint =
-                      ((firstByte & 0xf) << 0x12) |
-                      ((secondByte & 0x3f) << 0xc) |
-                      ((thirdByte & 0x3f) << 0x6) |
-                      (fourthByte & 0x3f);
-                    if (tempCodePoint > 0xffff && tempCodePoint < 0x110000) {
-                      codePoint = tempCodePoint;
-                    }
-                  }
-              }
-            }
-
-            if (codePoint === null) {
-              // we did not generate a valid codePoint so insert a
-              // replacement char (U+FFFD) and advance only 1 byte
-              codePoint = 0xfffd;
-              bytesPerSequence = 1;
-            } else if (codePoint > 0xffff) {
-              // encode to utf16 (surrogate pair dance)
-              codePoint -= 0x10000;
-              res.push(((codePoint >>> 10) & 0x3ff) | 0xd800);
-              codePoint = 0xdc00 | (codePoint & 0x3ff);
-            }
-
-            res.push(codePoint);
-            i += bytesPerSequence;
-          }
-
-          return decodeCodePointsArray(res);
-        }
-
-        // Based on http://stackoverflow.com/a/22747272/680742, the browser with
-        // the lowest limit is Chrome, with 0x10000 args.
-        // We go 1 magnitude less, for safety
-        var MAX_ARGUMENTS_LENGTH = 0x1000;
-
-        function decodeCodePointsArray(codePoints) {
-          var len = codePoints.length;
-          if (len <= MAX_ARGUMENTS_LENGTH) {
-            return String.fromCharCode.apply(String, codePoints); // avoid extra slice()
-          }
-
-          // Decode in chunks to avoid "call stack size exceeded".
-          var res = "";
-          var i = 0;
-          while (i < len) {
-            res += String.fromCharCode.apply(
-              String,
-              codePoints.slice(i, (i += MAX_ARGUMENTS_LENGTH))
-            );
-          }
-          return res;
-        }
-
-        function asciiSlice(buf, start, end) {
-          var ret = "";
-          end = Math.min(buf.length, end);
-
-          for (var i = start; i < end; ++i) {
-            ret += String.fromCharCode(buf[i] & 0x7f);
-          }
-          return ret;
-        }
-
-        function latin1Slice(buf, start, end) {
-          var ret = "";
-          end = Math.min(buf.length, end);
-
-          for (var i = start; i < end; ++i) {
-            ret += String.fromCharCode(buf[i]);
-          }
-          return ret;
-        }
-
-        function hexSlice(buf, start, end) {
-          var len = buf.length;
-
-          if (!start || start < 0) start = 0;
-          if (!end || end < 0 || end > len) end = len;
-
-          var out = "";
-          for (var i = start; i < end; ++i) {
-            out += toHex(buf[i]);
-          }
-          return out;
-        }
-
-        function utf16leSlice(buf, start, end) {
-          var bytes = buf.slice(start, end);
-          var res = "";
-          for (var i = 0; i < bytes.length; i += 2) {
-            res += String.fromCharCode(bytes[i] + bytes[i + 1] * 256);
-          }
-          return res;
-        }
-
-        Buffer.prototype.slice = function slice(start, end) {
-          var len = this.length;
-          start = ~~start;
-          end = end === undefined ? len : ~~end;
-
-          if (start < 0) {
-            start += len;
-            if (start < 0) start = 0;
-          } else if (start > len) {
-            start = len;
-          }
-
-          if (end < 0) {
-            end += len;
-            if (end < 0) end = 0;
-          } else if (end > len) {
-            end = len;
-          }
-
-          if (end < start) end = start;
-
-          var newBuf;
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            newBuf = this.subarray(start, end);
-            newBuf.__proto__ = Buffer.prototype;
-          } else {
-            var sliceLen = end - start;
-            newBuf = new Buffer(sliceLen, undefined);
-            for (var i = 0; i < sliceLen; ++i) {
-              newBuf[i] = this[i + start];
-            }
-          }
-
-          return newBuf;
-        };
-
-        /*
-         * Need to make sure that buffer isn't trying to write out of bounds.
-         */
-        function checkOffset(offset, ext, length) {
-          if (offset % 1 !== 0 || offset < 0) throw new RangeError("offset is not uint");
-          if (offset + ext > length) throw new RangeError("Trying to access beyond buffer length");
-        }
-
-        Buffer.prototype.readUIntLE = function readUIntLE(offset, byteLength, noAssert) {
-          offset = offset | 0;
-          byteLength = byteLength | 0;
-          if (!noAssert) checkOffset(offset, byteLength, this.length);
-
-          var val = this[offset];
-          var mul = 1;
-          var i = 0;
-          while (++i < byteLength && (mul *= 0x100)) {
-            val += this[offset + i] * mul;
-          }
-
-          return val;
-        };
-
-        Buffer.prototype.readUIntBE = function readUIntBE(offset, byteLength, noAssert) {
-          offset = offset | 0;
-          byteLength = byteLength | 0;
-          if (!noAssert) {
-            checkOffset(offset, byteLength, this.length);
-          }
-
-          var val = this[offset + --byteLength];
-          var mul = 1;
-          while (byteLength > 0 && (mul *= 0x100)) {
-            val += this[offset + --byteLength] * mul;
-          }
-
-          return val;
-        };
-
-        Buffer.prototype.readUInt8 = function readUInt8(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 1, this.length);
-          return this[offset];
-        };
-
-        Buffer.prototype.readUInt16LE = function readUInt16LE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 2, this.length);
-          return this[offset] | (this[offset + 1] << 8);
-        };
-
-        Buffer.prototype.readUInt16BE = function readUInt16BE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 2, this.length);
-          return (this[offset] << 8) | this[offset + 1];
-        };
-
-        Buffer.prototype.readUInt32LE = function readUInt32LE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 4, this.length);
-
-          return (
-            (this[offset] | (this[offset + 1] << 8) | (this[offset + 2] << 16)) +
-            this[offset + 3] * 0x1000000
-          );
-        };
-
-        Buffer.prototype.readUInt32BE = function readUInt32BE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 4, this.length);
-
-          return (
-            this[offset] * 0x1000000 +
-            ((this[offset + 1] << 16) | (this[offset + 2] << 8) | this[offset + 3])
-          );
-        };
-
-        Buffer.prototype.readIntLE = function readIntLE(offset, byteLength, noAssert) {
-          offset = offset | 0;
-          byteLength = byteLength | 0;
-          if (!noAssert) checkOffset(offset, byteLength, this.length);
-
-          var val = this[offset];
-          var mul = 1;
-          var i = 0;
-          while (++i < byteLength && (mul *= 0x100)) {
-            val += this[offset + i] * mul;
-          }
-          mul *= 0x80;
-
-          if (val >= mul) val -= Math.pow(2, 8 * byteLength);
-
-          return val;
-        };
-
-        Buffer.prototype.readIntBE = function readIntBE(offset, byteLength, noAssert) {
-          offset = offset | 0;
-          byteLength = byteLength | 0;
-          if (!noAssert) checkOffset(offset, byteLength, this.length);
-
-          var i = byteLength;
-          var mul = 1;
-          var val = this[offset + --i];
-          while (i > 0 && (mul *= 0x100)) {
-            val += this[offset + --i] * mul;
-          }
-          mul *= 0x80;
-
-          if (val >= mul) val -= Math.pow(2, 8 * byteLength);
-
-          return val;
-        };
-
-        Buffer.prototype.readInt8 = function readInt8(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 1, this.length);
-          if (!(this[offset] & 0x80)) return this[offset];
-          return (0xff - this[offset] + 1) * -1;
-        };
-
-        Buffer.prototype.readInt16LE = function readInt16LE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 2, this.length);
-          var val = this[offset] | (this[offset + 1] << 8);
-          return val & 0x8000 ? val | 0xffff0000 : val;
-        };
-
-        Buffer.prototype.readInt16BE = function readInt16BE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 2, this.length);
-          var val = this[offset + 1] | (this[offset] << 8);
-          return val & 0x8000 ? val | 0xffff0000 : val;
-        };
-
-        Buffer.prototype.readInt32LE = function readInt32LE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 4, this.length);
-
-          return (
-            this[offset] |
-            (this[offset + 1] << 8) |
-            (this[offset + 2] << 16) |
-            (this[offset + 3] << 24)
-          );
-        };
-
-        Buffer.prototype.readInt32BE = function readInt32BE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 4, this.length);
-
-          return (
-            (this[offset] << 24) |
-            (this[offset + 1] << 16) |
-            (this[offset + 2] << 8) |
-            this[offset + 3]
-          );
-        };
-
-        Buffer.prototype.readFloatLE = function readFloatLE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 4, this.length);
-          return ieee754.read(this, offset, true, 23, 4);
-        };
-
-        Buffer.prototype.readFloatBE = function readFloatBE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 4, this.length);
-          return ieee754.read(this, offset, false, 23, 4);
-        };
-
-        Buffer.prototype.readDoubleLE = function readDoubleLE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 8, this.length);
-          return ieee754.read(this, offset, true, 52, 8);
-        };
-
-        Buffer.prototype.readDoubleBE = function readDoubleBE(offset, noAssert) {
-          if (!noAssert) checkOffset(offset, 8, this.length);
-          return ieee754.read(this, offset, false, 52, 8);
-        };
-
-        function checkInt(buf, value, offset, ext, max, min) {
-          if (!Buffer.isBuffer(buf))
-            throw new TypeError('"buffer" argument must be a Buffer instance');
-          if (value > max || value < min) throw new RangeError('"value" argument is out of bounds');
-          if (offset + ext > buf.length) throw new RangeError("Index out of range");
-        }
-
-        Buffer.prototype.writeUIntLE = function writeUIntLE(value, offset, byteLength, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          byteLength = byteLength | 0;
-          if (!noAssert) {
-            var maxBytes = Math.pow(2, 8 * byteLength) - 1;
-            checkInt(this, value, offset, byteLength, maxBytes, 0);
-          }
-
-          var mul = 1;
-          var i = 0;
-          this[offset] = value & 0xff;
-          while (++i < byteLength && (mul *= 0x100)) {
-            this[offset + i] = (value / mul) & 0xff;
-          }
-
-          return offset + byteLength;
-        };
-
-        Buffer.prototype.writeUIntBE = function writeUIntBE(value, offset, byteLength, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          byteLength = byteLength | 0;
-          if (!noAssert) {
-            var maxBytes = Math.pow(2, 8 * byteLength) - 1;
-            checkInt(this, value, offset, byteLength, maxBytes, 0);
-          }
-
-          var i = byteLength - 1;
-          var mul = 1;
-          this[offset + i] = value & 0xff;
-          while (--i >= 0 && (mul *= 0x100)) {
-            this[offset + i] = (value / mul) & 0xff;
-          }
-
-          return offset + byteLength;
-        };
-
-        Buffer.prototype.writeUInt8 = function writeUInt8(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 1, 0xff, 0);
-          if (!Buffer.TYPED_ARRAY_SUPPORT) value = Math.floor(value);
-          this[offset] = value & 0xff;
-          return offset + 1;
-        };
-
-        function objectWriteUInt16(buf, value, offset, littleEndian) {
-          if (value < 0) value = 0xffff + value + 1;
-          for (var i = 0, j = Math.min(buf.length - offset, 2); i < j; ++i) {
-            buf[offset + i] =
-              (value & (0xff << (8 * (littleEndian ? i : 1 - i)))) >>>
-              ((littleEndian ? i : 1 - i) * 8);
-          }
-        }
-
-        Buffer.prototype.writeUInt16LE = function writeUInt16LE(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 2, 0xffff, 0);
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            this[offset] = value & 0xff;
-            this[offset + 1] = value >>> 8;
-          } else {
-            objectWriteUInt16(this, value, offset, true);
-          }
-          return offset + 2;
-        };
-
-        Buffer.prototype.writeUInt16BE = function writeUInt16BE(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 2, 0xffff, 0);
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            this[offset] = value >>> 8;
-            this[offset + 1] = value & 0xff;
-          } else {
-            objectWriteUInt16(this, value, offset, false);
-          }
-          return offset + 2;
-        };
-
-        function objectWriteUInt32(buf, value, offset, littleEndian) {
-          if (value < 0) value = 0xffffffff + value + 1;
-          for (var i = 0, j = Math.min(buf.length - offset, 4); i < j; ++i) {
-            buf[offset + i] = (value >>> ((littleEndian ? i : 3 - i) * 8)) & 0xff;
-          }
-        }
-
-        Buffer.prototype.writeUInt32LE = function writeUInt32LE(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 4, 0xffffffff, 0);
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            this[offset + 3] = value >>> 24;
-            this[offset + 2] = value >>> 16;
-            this[offset + 1] = value >>> 8;
-            this[offset] = value & 0xff;
-          } else {
-            objectWriteUInt32(this, value, offset, true);
-          }
-          return offset + 4;
-        };
-
-        Buffer.prototype.writeUInt32BE = function writeUInt32BE(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 4, 0xffffffff, 0);
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            this[offset] = value >>> 24;
-            this[offset + 1] = value >>> 16;
-            this[offset + 2] = value >>> 8;
-            this[offset + 3] = value & 0xff;
-          } else {
-            objectWriteUInt32(this, value, offset, false);
-          }
-          return offset + 4;
-        };
-
-        Buffer.prototype.writeIntLE = function writeIntLE(value, offset, byteLength, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) {
-            var limit = Math.pow(2, 8 * byteLength - 1);
-
-            checkInt(this, value, offset, byteLength, limit - 1, -limit);
-          }
-
-          var i = 0;
-          var mul = 1;
-          var sub = 0;
-          this[offset] = value & 0xff;
-          while (++i < byteLength && (mul *= 0x100)) {
-            if (value < 0 && sub === 0 && this[offset + i - 1] !== 0) {
-              sub = 1;
-            }
-            this[offset + i] = (((value / mul) >> 0) - sub) & 0xff;
-          }
-
-          return offset + byteLength;
-        };
-
-        Buffer.prototype.writeIntBE = function writeIntBE(value, offset, byteLength, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) {
-            var limit = Math.pow(2, 8 * byteLength - 1);
-
-            checkInt(this, value, offset, byteLength, limit - 1, -limit);
-          }
-
-          var i = byteLength - 1;
-          var mul = 1;
-          var sub = 0;
-          this[offset + i] = value & 0xff;
-          while (--i >= 0 && (mul *= 0x100)) {
-            if (value < 0 && sub === 0 && this[offset + i + 1] !== 0) {
-              sub = 1;
-            }
-            this[offset + i] = (((value / mul) >> 0) - sub) & 0xff;
-          }
-
-          return offset + byteLength;
-        };
-
-        Buffer.prototype.writeInt8 = function writeInt8(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 1, 0x7f, -0x80);
-          if (!Buffer.TYPED_ARRAY_SUPPORT) value = Math.floor(value);
-          if (value < 0) value = 0xff + value + 1;
-          this[offset] = value & 0xff;
-          return offset + 1;
-        };
-
-        Buffer.prototype.writeInt16LE = function writeInt16LE(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 2, 0x7fff, -0x8000);
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            this[offset] = value & 0xff;
-            this[offset + 1] = value >>> 8;
-          } else {
-            objectWriteUInt16(this, value, offset, true);
-          }
-          return offset + 2;
-        };
-
-        Buffer.prototype.writeInt16BE = function writeInt16BE(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 2, 0x7fff, -0x8000);
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            this[offset] = value >>> 8;
-            this[offset + 1] = value & 0xff;
-          } else {
-            objectWriteUInt16(this, value, offset, false);
-          }
-          return offset + 2;
-        };
-
-        Buffer.prototype.writeInt32LE = function writeInt32LE(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 4, 0x7fffffff, -0x80000000);
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            this[offset] = value & 0xff;
-            this[offset + 1] = value >>> 8;
-            this[offset + 2] = value >>> 16;
-            this[offset + 3] = value >>> 24;
-          } else {
-            objectWriteUInt32(this, value, offset, true);
-          }
-          return offset + 4;
-        };
-
-        Buffer.prototype.writeInt32BE = function writeInt32BE(value, offset, noAssert) {
-          value = +value;
-          offset = offset | 0;
-          if (!noAssert) checkInt(this, value, offset, 4, 0x7fffffff, -0x80000000);
-          if (value < 0) value = 0xffffffff + value + 1;
-          if (Buffer.TYPED_ARRAY_SUPPORT) {
-            this[offset] = value >>> 24;
-            this[offset + 1] = value >>> 16;
-            this[offset + 2] = value >>> 8;
-            this[offset + 3] = value & 0xff;
-          } else {
-            objectWriteUInt32(this, value, offset, false);
-          }
-          return offset + 4;
-        };
-
-        function checkIEEE754(buf, value, offset, ext, max, min) {
-          if (offset + ext > buf.length) throw new RangeError("Index out of range");
-          if (offset < 0) throw new RangeError("Index out of range");
-        }
-
-        function writeFloat(buf, value, offset, littleEndian, noAssert) {
-          if (!noAssert) {
-            checkIEEE754(buf, value, offset, 4, 3.4028234663852886e38, -3.4028234663852886e38);
-          }
-          ieee754.write(buf, value, offset, littleEndian, 23, 4);
-          return offset + 4;
-        }
-
-        Buffer.prototype.writeFloatLE = function writeFloatLE(value, offset, noAssert) {
-          return writeFloat(this, value, offset, true, noAssert);
-        };
-
-        Buffer.prototype.writeFloatBE = function writeFloatBE(value, offset, noAssert) {
-          return writeFloat(this, value, offset, false, noAssert);
-        };
-
-        function writeDouble(buf, value, offset, littleEndian, noAssert) {
-          if (!noAssert) {
-            checkIEEE754(buf, value, offset, 8, 1.7976931348623157e308, -1.7976931348623157e308);
-          }
-          ieee754.write(buf, value, offset, littleEndian, 52, 8);
-          return offset + 8;
-        }
-
-        Buffer.prototype.writeDoubleLE = function writeDoubleLE(value, offset, noAssert) {
-          return writeDouble(this, value, offset, true, noAssert);
-        };
-
-        Buffer.prototype.writeDoubleBE = function writeDoubleBE(value, offset, noAssert) {
-          return writeDouble(this, value, offset, false, noAssert);
-        };
-
-        // copy(targetBuffer, targetStart=0, sourceStart=0, sourceEnd=buffer.length)
-        Buffer.prototype.copy = function copy(target, targetStart, start, end) {
-          if (!start) start = 0;
-          if (!end && end !== 0) end = this.length;
-          if (targetStart >= target.length) targetStart = target.length;
-          if (!targetStart) targetStart = 0;
-          if (end > 0 && end < start) end = start;
-
-          // Copy 0 bytes; we're done
-          if (end === start) return 0;
-          if (target.length === 0 || this.length === 0) return 0;
-
-          // Fatal error conditions
-          if (targetStart < 0) {
-            throw new RangeError("targetStart out of bounds");
-          }
-          if (start < 0 || start >= this.length) throw new RangeError("sourceStart out of bounds");
-          if (end < 0) throw new RangeError("sourceEnd out of bounds");
-
-          // Are we oob?
-          if (end > this.length) end = this.length;
-          if (target.length - targetStart < end - start) {
-            end = target.length - targetStart + start;
-          }
-
-          var len = end - start;
-          var i;
-
-          if (this === target && start < targetStart && targetStart < end) {
-            // descending copy from end
-            for (i = len - 1; i >= 0; --i) {
-              target[i + targetStart] = this[i + start];
-            }
-          } else if (len < 1000 || !Buffer.TYPED_ARRAY_SUPPORT) {
-            // ascending copy from start
-            for (i = 0; i < len; ++i) {
-              target[i + targetStart] = this[i + start];
-            }
-          } else {
-            Uint8Array.prototype.set.call(target, this.subarray(start, start + len), targetStart);
-          }
-
-          return len;
-        };
-
-        // Usage:
-        //    buffer.fill(number[, offset[, end]])
-        //    buffer.fill(buffer[, offset[, end]])
-        //    buffer.fill(string[, offset[, end]][, encoding])
-        Buffer.prototype.fill = function fill(val, start, end, encoding) {
-          // Handle string cases:
-          if (typeof val === "string") {
-            if (typeof start === "string") {
-              encoding = start;
-              start = 0;
-              end = this.length;
-            } else if (typeof end === "string") {
-              encoding = end;
-              end = this.length;
-            }
-            if (val.length === 1) {
-              var code = val.charCodeAt(0);
-              if (code < 256) {
-                val = code;
-              }
-            }
-            if (encoding !== undefined && typeof encoding !== "string") {
-              throw new TypeError("encoding must be a string");
-            }
-            if (typeof encoding === "string" && !Buffer.isEncoding(encoding)) {
-              throw new TypeError("Unknown encoding: " + encoding);
-            }
-          } else if (typeof val === "number") {
-            val = val & 255;
-          }
-
-          // Invalid ranges are not set to a default, so can range check early.
-          if (start < 0 || this.length < start || this.length < end) {
-            throw new RangeError("Out of range index");
-          }
-
-          if (end <= start) {
-            return this;
-          }
-
-          start = start >>> 0;
-          end = end === undefined ? this.length : end >>> 0;
-
-          if (!val) val = 0;
-
-          var i;
-          if (typeof val === "number") {
-            for (i = start; i < end; ++i) {
-              this[i] = val;
-            }
-          } else {
-            var bytes = Buffer.isBuffer(val)
-              ? val
-              : utf8ToBytes(new Buffer(val, encoding).toString());
-            var len = bytes.length;
-            for (i = 0; i < end - start; ++i) {
-              this[i + start] = bytes[i % len];
-            }
-          }
-
-          return this;
-        };
-
-        // HELPER FUNCTIONS
-        // ================
-
-        var INVALID_BASE64_RE = /[^+\/0-9A-Za-z-_]/g;
-
-        function base64clean(str) {
-          // Node strips out invalid characters like \n and \t from the string, base64-js does not
-          str = stringtrim(str).replace(INVALID_BASE64_RE, "");
-          // Node converts strings with length < 2 to ''
-          if (str.length < 2) return "";
-          // Node allows for non-padded base64 strings (missing trailing ===), base64-js does not
-          while (str.length % 4 !== 0) {
-            str = str + "=";
-          }
-          return str;
-        }
-
-        function stringtrim(str) {
-          if (str.trim) return str.trim();
-          return str.replace(/^\s+|\s+$/g, "");
-        }
-
-        function toHex(n) {
-          if (n < 16) return "0" + n.toString(16);
-          return n.toString(16);
-        }
-
-        function utf8ToBytes(string, units) {
-          units = units || Infinity;
-          var codePoint;
-          var length = string.length;
-          var leadSurrogate = null;
-          var bytes = [];
-
-          for (var i = 0; i < length; ++i) {
-            codePoint = string.charCodeAt(i);
-
-            // is surrogate component
-            if (codePoint > 0xd7ff && codePoint < 0xe000) {
-              // last char was a lead
-              if (!leadSurrogate) {
-                // no lead yet
-                if (codePoint > 0xdbff) {
-                  // unexpected trail
-                  if ((units -= 3) > -1) bytes.push(0xef, 0xbf, 0xbd);
-                  continue;
-                } else if (i + 1 === length) {
-                  // unpaired lead
-                  if ((units -= 3) > -1) bytes.push(0xef, 0xbf, 0xbd);
-                  continue;
-                }
-
-                // valid lead
-                leadSurrogate = codePoint;
-
-                continue;
-              }
-
-              // 2 leads in a row
-              if (codePoint < 0xdc00) {
-                if ((units -= 3) > -1) bytes.push(0xef, 0xbf, 0xbd);
-                leadSurrogate = codePoint;
-                continue;
-              }
-
-              // valid surrogate pair
-              codePoint = (((leadSurrogate - 0xd800) << 10) | (codePoint - 0xdc00)) + 0x10000;
-            } else if (leadSurrogate) {
-              // valid bmp char, but last char was a lead
-              if ((units -= 3) > -1) bytes.push(0xef, 0xbf, 0xbd);
-            }
-
-            leadSurrogate = null;
-
-            // encode utf8
-            if (codePoint < 0x80) {
-              if ((units -= 1) < 0) break;
-              bytes.push(codePoint);
-            } else if (codePoint < 0x800) {
-              if ((units -= 2) < 0) break;
-              bytes.push((codePoint >> 0x6) | 0xc0, (codePoint & 0x3f) | 0x80);
-            } else if (codePoint < 0x10000) {
-              if ((units -= 3) < 0) break;
-              bytes.push(
-                (codePoint >> 0xc) | 0xe0,
-                ((codePoint >> 0x6) & 0x3f) | 0x80,
-                (codePoint & 0x3f) | 0x80
-              );
-            } else if (codePoint < 0x110000) {
-              if ((units -= 4) < 0) break;
-              bytes.push(
-                (codePoint >> 0x12) | 0xf0,
-                ((codePoint >> 0xc) & 0x3f) | 0x80,
-                ((codePoint >> 0x6) & 0x3f) | 0x80,
-                (codePoint & 0x3f) | 0x80
-              );
-            } else {
-              throw new Error("Invalid code point");
-            }
-          }
-
-          return bytes;
-        }
-
-        function asciiToBytes(str) {
-          var byteArray = [];
-          for (var i = 0; i < str.length; ++i) {
-            // Node's code seems to be doing this and not & 0x7F..
-            byteArray.push(str.charCodeAt(i) & 0xff);
-          }
-          return byteArray;
-        }
-
-        function utf16leToBytes(str, units) {
-          var c, hi, lo;
-          var byteArray = [];
-          for (var i = 0; i < str.length; ++i) {
-            if ((units -= 2) < 0) break;
-
-            c = str.charCodeAt(i);
-            hi = c >> 8;
-            lo = c % 256;
-            byteArray.push(lo);
-            byteArray.push(hi);
-          }
-
-          return byteArray;
-        }
-
-        function base64ToBytes(str) {
-          return base64.toByteArray(base64clean(str));
-        }
-
-        function blitBuffer(src, dst, offset, length) {
-          for (var i = 0; i < length; ++i) {
-            if (i + offset >= dst.length || i >= src.length) break;
-            dst[i + offset] = src[i];
-          }
-          return i;
-        }
-
-        function isnan(val) {
-          return val !== val; // eslint-disable-line no-self-compare
-        }
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(27)));
-
-      /***/
-    },
-    /* 40 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (setImmediate) {
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-          return nextFrame;
-        });
-        /**
-         * @license
-         * Copyright 2017 Google Inc. All Rights Reserved.
-         * Licensed under the Apache License, Version 2.0 (the "License");
-         * you may not use this file except in compliance with the License.
-         * You may obtain a copy of the License at
-         *
-         * http://www.apache.org/licenses/LICENSE-2.0
-         *
-         * Unless required by applicable law or agreed to in writing, software
-         * distributed under the License is distributed on an "AS IS" BASIS,
-         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-         * See the License for the specific language governing permissions and
-         * limitations under the License.
-         * =============================================================================
-         */
-        const delayCallback = (() => {
-          if (typeof requestAnimationFrame !== "undefined") {
-            return requestAnimationFrame;
-          } else if (typeof setImmediate !== "undefined") {
-            return setImmediate;
-          }
-          return (f) => f(); // no delays
-        })();
-        /**
-         * Returns a promise that resolve when a requestAnimationFrame has completed.
-         *
-         * On Node.js this uses setImmediate instead of requestAnimationFrame.
-         *
-         * This is simply a sugar method so that users can do the following:
-         * `await tf.nextFrame();`
-         */
-        /** @doc {heading: 'Performance', subheading: 'Timing'} */
-        function nextFrame() {
-          return new Promise((resolve) => delayCallback(() => resolve()));
-        }
-
-        //# sourceMappingURL=browser_util.js.map
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(76).setImmediate));
-
-      /***/
-    },
-    /* 41 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "Add",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "AddV2",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "AddN",
-          category: "arithmetic",
-          inputs: [{ start: 0, end: 0, name: "tensors", type: "tensors" }],
-        },
-        {
-          tfOpName: "BiasAdd",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Sub",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "RealDiv",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Div",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "DivNoNan",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "FloorDiv",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Mul",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Maximum",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-        },
-        {
-          tfOpName: "Minimum",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-        },
-        {
-          tfOpName: "Pow",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "SquaredDifference",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Mod",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "FloorMod",
-          category: "arithmetic",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-      ];
-      //# sourceMappingURL=arithmetic.js.map
-
-      /***/
-    },
-    /* 42 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "Abs",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Acos",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Asin",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Atan",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Atan2",
-          category: "basic_math",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "y", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Ceil",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "ClipByValue",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "clip_value_min", name: "clipValueMin", type: "number" },
-            { tfName: "clip_value_max", name: "clipValueMax", type: "number" },
-          ],
-        },
-        {
-          tfOpName: "Complex",
-          category: "basic_math",
-          inputs: [
-            { start: 0, name: "real", type: "tensor" },
-            { start: 1, name: "imag", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "ComplexAbs",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Cos",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Cosh",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Elu",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Exp",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Floor",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Log",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Imag",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-            {
-              tfName: "Tout",
-              name: "outputType",
-              type: "dtype",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "Neg",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Real",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-            {
-              tfName: "Tout",
-              name: "outputType",
-              type: "dtype",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "Prelu",
-          category: "basic_math",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "alpha", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Relu",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Relu6",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-            {
-              tfName: "clipValueMin",
-              name: "clipValueMin",
-              type: "number",
-              defaultValue: 0,
-            },
-            {
-              tfName: "clipValueMax",
-              name: "clipValueMax",
-              type: "number",
-              defaultValue: 6,
-            },
-          ],
-        },
-        {
-          tfOpName: "Selu",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Sigmoid",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Sin",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Sinh",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Sqrt",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Rsqrt",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Square",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Tan",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Tanh",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Sign",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Round",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Expm1",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Log1p",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Reciprocal",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Softplus",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Asinh",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Acosh",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Atanh",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Erf",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Prod",
-          category: "basic_math",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axes", type: "number[]" },
-          ],
-          attrs: [
-            {
-              tfName: "keep_dims",
-              name: "keepDims",
-              type: "bool",
-              notSupported: true,
-            },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "LeakyRelu",
-          category: "basic_math",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            {
-              tfName: "alpha",
-              name: "alpha",
-              type: "number",
-              defaultValue: 0.2,
-            },
-            {
-              tfName: "T",
-              name: "dtype",
-              type: "dtype",
-              notSupported: true,
-            },
-          ],
-        },
-      ];
-      //# sourceMappingURL=basic_math.js.map
-
-      /***/
-    },
-    /* 43 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "LoopCond",
-          category: "control",
-          inputs: [{ start: 0, name: "pred", type: "tensor" }],
-        },
-        {
-          tfOpName: "Switch",
-          category: "control",
-          inputs: [
-            { start: 0, name: "data", type: "tensor" },
-            { start: 1, name: "pred", type: "tensor" },
-          ],
-        },
-        {
-          tfOpName: "Merge",
-          category: "control",
-          inputs: [{ start: 0, end: 0, name: "tensors", type: "tensors" }],
-        },
-        {
-          tfOpName: "Enter",
-          category: "control",
-          inputs: [{ start: 0, name: "tensor", type: "tensor" }],
-          attrs: [
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-            { tfName: "frame_name", name: "frameName", type: "string" },
-            { tfName: "is_constant", name: "isConstant", type: "bool" },
-          ],
-        },
-        {
-          tfOpName: "Exit",
-          category: "control",
-          inputs: [{ start: 0, name: "tensor", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "NextIteration",
-          category: "control",
-          inputs: [{ start: 0, name: "tensor", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "TensorArrayV3",
-          category: "control",
-          inputs: [{ start: 0, name: "size", type: "number" }],
-          attrs: [
-            { tfName: "dtype", name: "dtype", type: "dtype" },
-            { tfName: "element_shape", name: "elementShape", type: "shape" },
-            { tfName: "dynamic_size", name: "dynamicSize", type: "bool" },
-            { tfName: "clear_after_read", name: "clearAfterRead", type: "bool" },
-            {
-              tfName: "identical_element_shapes",
-              name: "identicalElementShapes",
-              type: "bool",
-            },
-            { tfName: "tensor_array_name", name: "name", type: "string" },
-          ],
-        },
-        {
-          tfOpName: "TensorArrayWriteV3",
-          category: "control",
-          inputs: [
-            { start: 0, name: "tensorArrayId", type: "number" },
-            { start: 1, name: "index", type: "number" },
-            { start: 2, name: "tensor", type: "tensor" },
-            { start: 3, name: "flowIn", type: "number" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "TensorArrayReadV3",
-          category: "control",
-          inputs: [
-            { start: 0, name: "tensorArrayId", type: "number" },
-            { start: 1, name: "index", type: "number" },
-            { start: 2, name: "flowIn", type: "number" },
-          ],
-          attrs: [
-            {
-              tfName: "dtype",
-              name: "dtype",
-              type: "dtype",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "TensorArrayGatherV3",
-          category: "control",
-          inputs: [
-            { start: 0, name: "tensorArrayId", type: "number" },
-            { start: 1, name: "indices", type: "number[]" },
-            { start: 2, name: "flowIn", type: "number" },
-          ],
-          attrs: [
-            { tfName: "dtype", name: "dtype", type: "dtype" },
-            { tfName: "element_shape", name: "elementShape", type: "shape" },
-          ],
-        },
-        {
-          tfOpName: "TensorArrayScatterV3",
-          category: "control",
-          inputs: [
-            { start: 0, name: "tensorArrayId", type: "number" },
-            { start: 1, name: "indices", type: "number[]" },
-            { start: 2, name: "tensor", type: "tensor" },
-            { start: 3, name: "flowIn", type: "number" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
-        },
-        {
-          tfOpName: "TensorArrayConcatV3",
-          category: "control",
-          inputs: [
-            { start: 0, name: "tensorArrayId", type: "number" },
-            { start: 1, name: "flowIn", type: "number" },
-          ],
-          attrs: [
-            { tfName: "dtype", name: "dtype", type: "dtype" },
-            {
-              tfName: "element_shape_except0",
-              name: "elementShapeExcept0",
-              type: "shape",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "TensorArraySplitV3",
-          category: "control",
-          inputs: [
-            { start: 0, name: "tensorArrayId", type: "number" },
-            { start: 1, name: "tensor", type: "tensor" },
-            { start: 2, name: "lengths", type: "number[]" },
-            { start: 3, name: "flowIn", type: "number" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
-        },
-        {
-          tfOpName: "TensorArraySizeV3",
-          category: "control",
-          inputs: [
-            { start: 0, name: "tensorArrayId", type: "number" },
-            { start: 1, name: "flowIn", type: "number" },
-          ],
-        },
-        {
-          tfOpName: "TensorArrayCloseV3",
-          category: "control",
-          inputs: [{ start: 0, name: "tensorArrayId", type: "number" }],
-        },
-        {
-          tfOpName: "StatelessIf",
-          category: "control",
-          inputs: [
-            { start: 0, name: "cond", type: "tensor" },
-            { start: 1, end: 0, name: "args", type: "tensors" },
-          ],
-          attrs: [
-            { tfName: "then_branch", name: "thenBranch", type: "func" },
-            { tfName: "else_branch", name: "elseBranch", type: "func" },
-          ],
-        },
-        {
-          tfOpName: "If",
-          category: "control",
-          inputs: [
-            { start: 0, name: "cond", type: "tensor" },
-            { start: 1, end: 0, name: "args", type: "tensors" },
-          ],
-          attrs: [
-            { tfName: "then_branch", name: "thenBranch", type: "func" },
-            { tfName: "else_branch", name: "elseBranch", type: "func" },
-          ],
-        },
-        {
-          tfOpName: "StatelessWhile",
-          category: "control",
-          inputs: [{ start: 0, end: 0, name: "args", type: "tensors" }],
-          attrs: [
-            { tfName: "cond", name: "cond", type: "func" },
-            { tfName: "body", name: "body", type: "func" },
-          ],
-        },
-        {
-          tfOpName: "While",
-          category: "control",
-          inputs: [{ start: 0, end: 0, name: "args", type: "tensors" }],
-          attrs: [
-            { tfName: "cond", name: "cond", type: "func" },
-            { tfName: "body", name: "body", type: "func" },
-          ],
-        },
-      ];
-      //# sourceMappingURL=control.js.map
-
-      /***/
-    },
-    /* 44 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "AvgPool",
-          category: "convolution",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              notSupported: true,
-            },
-            { tfName: "ksize", name: "kernelSize", type: "number[]" },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "MaxPool",
-          category: "convolution",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              notSupported: true,
-            },
-            { tfName: "ksize", name: "kernelSize", type: "number[]" },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "MaxPoolWithArgmax",
-          category: "convolution",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            { tfName: "ksize", name: "kernelSize", type: "number[]" },
-            {
-              tfName: "include_batch_in_index",
-              name: "includeBatchInIndex",
-              type: "bool",
-            },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "AvgPool3D",
-          category: "convolution",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              notSupported: true,
-            },
-            { tfName: "ksize", name: "kernelSize", type: "number[]" },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "MaxPool3D",
-          category: "convolution",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              notSupported: true,
-            },
-            { tfName: "ksize", name: "kernelSize", type: "number[]" },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "Conv1D",
-          category: "convolution",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "filter", type: "tensor" },
-          ],
-          attrs: [
-            { tfName: "stride", name: "stride", type: "number" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              defaultValue: "NWC",
-            },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-            {
-              tfName: "dilation",
-              name: "dilation",
-              type: "number",
-              defaultValue: 1,
-            },
-          ],
-        },
-        {
-          tfOpName: "Conv2D",
-          category: "convolution",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "filter", type: "tensor" },
-          ],
-          attrs: [
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            { tfName: "useCudnnOnGpu", name: "useCudnnOnGpu", type: "bool" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              defaultValue: "NHWC",
-            },
-            {
-              tfName: "explicit_paddings",
-              name: "explicitPaddings",
-              type: "number[]",
-              defaultValue: [],
-            },
-            { tfName: "dilations", name: "dilations", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "_FusedConv2D",
-          category: "convolution",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "filter", type: "tensor" },
-            { start: 2, end: 0, name: "args", type: "tensors" },
-          ],
-          attrs: [
-            { tfName: "num_args", name: "numArgs", type: "number" },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "explicit_paddings",
-              name: "explicitPaddings",
-              type: "number[]",
-              defaultValue: [],
-            },
-            {
-              tfName: "use_cudnn_on_gpu",
-              name: "useCudnnOnGpu",
-              type: "bool",
-              defaultValue: true,
-            },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              defaultValue: "NHWC",
-            },
-            {
-              tfName: "dilations",
-              name: "dilations",
-              type: "number[]",
-              defaultValue: [1, 1, 1, 1],
-            },
-            {
-              tfName: "fused_ops",
-              name: "fusedOps",
-              type: "string[]",
-              defaultValue: [],
-            },
-            {
-              tfName: "epsilon",
-              name: "epsilon",
-              type: "number",
-              defaultValue: 0.0001,
-            },
-          ],
-        },
-        {
-          tfOpName: "Conv2DBackpropInput",
-          category: "convolution",
-          inputs: [
-            { start: 2, name: "x", type: "tensor" },
-            { start: 1, name: "filter", type: "tensor" },
-            { start: 0, name: "outputShape", type: "number[]" },
-          ],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              notSupported: true,
-            },
-            {
-              tfName: "explicit_paddings",
-              name: "explicitPaddings",
-              type: "number[]",
-              defaultValue: [],
-            },
-          ],
-        },
-        {
-          tfOpName: "DepthwiseConv2d",
-          category: "convolution",
-          inputs: [
-            { start: 0, name: "input", type: "tensor" },
-            { start: 1, name: "filter", type: "tensor" },
-          ],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              defaultValue: "NHWC",
-            },
-            {
-              tfName: "explicit_paddings",
-              name: "explicitPaddings",
-              type: "number[]",
-              defaultValue: [],
-            },
-            { tfName: "dilations", name: "dilations", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "DepthwiseConv2dNative",
-          category: "convolution",
-          inputs: [
-            { start: 0, name: "input", type: "tensor" },
-            { start: 1, name: "filter", type: "tensor" },
-          ],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              defaultValue: "NHWC",
-            },
-            {
-              tfName: "explicit_paddings",
-              name: "explicitPaddings",
-              type: "number[]",
-              defaultValue: [],
-            },
-            { tfName: "dilations", name: "dilations", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "FusedDepthwiseConv2dNative",
-          category: "convolution",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "filter", type: "tensor" },
-            { start: 2, end: 0, name: "args", type: "tensors" },
-          ],
-          attrs: [
-            { tfName: "num_args", name: "numArgs", type: "number" },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              defaultValue: "NHWC",
-            },
-            {
-              tfName: "dilations",
-              name: "dilations",
-              type: "number[]",
-              defaultValue: [1, 1, 1, 1],
-            },
-            {
-              tfName: "fused_ops",
-              name: "fusedOps",
-              type: "string[]",
-              defaultValue: [],
-            },
-          ],
-        },
-        {
-          tfOpName: "Conv3D",
-          category: "convolution",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "filter", type: "tensor" },
-          ],
-          attrs: [
-            { tfName: "strides", name: "strides", type: "number[]" },
-            { tfName: "padding", name: "pad", type: "string" },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              defaultValue: "NHWC",
-            },
-            { tfName: "dilations", name: "dilations", type: "number[]" },
-          ],
-        },
-      ];
-      //# sourceMappingURL=convolution.js.map
-
-      /***/
-    },
-    /* 45 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "Fill",
-          category: "creation",
-          inputs: [
-            { start: 0, name: "shape", type: "number[]" },
-            { start: 1, name: "value", type: "number" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
-        },
-        {
-          tfOpName: "LinSpace",
-          category: "creation",
-          inputs: [
-            { start: 0, name: "start", type: "number" },
-            { start: 1, name: "stop", type: "number" },
-            { start: 2, name: "num", type: "number" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "OneHot",
-          category: "creation",
-          inputs: [
-            { start: 0, name: "indices", type: "tensor" },
-            { start: 1, name: "depth", type: "number" },
-            { start: 2, name: "onValue", type: "number", defaultValue: 1 },
-            { start: 3, name: "offValue", type: "number", defaultValue: 0 },
-          ],
-          attrs: [
-            {
-              tfName: "axis",
-              name: "axis",
-              type: "number",
-              notSupported: true,
-            },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "Ones",
-          category: "creation",
-          inputs: [{ start: 0, name: "shape", type: "number[]" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
-        },
-        {
-          tfOpName: "OnesLike",
-          category: "creation",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "dtype", name: "dtype", type: "dtype" }],
-        },
-        {
-          tfOpName: "RandomUniform",
-          category: "creation",
-          inputs: [{ start: 0, name: "shape", type: "number[]" }],
-          attrs: [
-            {
-              tfName: "minval",
-              name: "minval",
-              type: "number",
-              defaultValue: 0,
-            },
-            {
-              tfName: "maxval",
-              name: "maxval",
-              type: "number",
-              defaultValue: 1,
-            },
-            { tfName: "dtype", name: "dtype", type: "dtype" },
-            { tfName: "seed", name: "seed", type: "number", defaultValue: 0 },
-            {
-              tfName: "seed2",
-              name: "seed2",
-              type: "number",
-              defaultValue: 0,
-              notSupported: true,
-            },
-            { tfName: "T", name: "T", type: "number", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "Range",
-          category: "creation",
-          inputs: [
-            { start: 0, name: "start", type: "number" },
-            { start: 1, name: "stop", type: "number" },
-            { start: 2, name: "step", type: "number", defaultValue: 0 },
-          ],
-          attrs: [{ tfName: "Tidx", name: "dtype", type: "dtype" }],
-        },
-        {
-          tfOpName: "TruncatedNormal",
-          category: "creation",
-          inputs: [{ start: 0, name: "shape", type: "number[]" }],
-          attrs: [
-            {
-              tfName: "means",
-              name: "mean",
-              type: "number",
-              defaultValue: 0.0,
-            },
-            {
-              tfName: "stddev",
-              name: "stdDev",
-              type: "number",
-              defaultValue: 1.0,
-            },
-            { tfName: "seed", name: "seed", type: "number" },
-            {
-              tfName: "seed2",
-              name: "seed2",
-              type: "number",
-              defaultValue: 0,
-              notSupported: true,
-            },
-            { tfName: "dtype", name: "dtype", type: "dtype" },
-            { tfName: "T", name: "T", type: "number", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "Zeros",
-          category: "creation",
-          inputs: [{ start: 0, name: "shape", type: "number[]" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
-        },
-        {
-          tfOpName: "ZerosLike",
-          category: "creation",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
-        },
-        {
-          tfOpName: "Multinomial",
-          category: "creation",
-          inputs: [
-            { start: 0, name: "logits", type: "tensor" },
-            { start: 1, name: "numSamples", type: "number" },
-          ],
-          attrs: [
-            { tfName: "seed", name: "seed", type: "number" },
-            { tfName: "seed2", name: "seed2", type: "number" },
-            { tfName: "T", name: "dtype", type: "dtype" },
-            { tfName: "output_dtype", name: "output_dtype", type: "dtype" },
-          ],
-        },
-      ];
-      //# sourceMappingURL=creation.js.map
-
-      /***/
-    },
-    /* 46 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "NonMaxSuppressionV2",
-          category: "dynamic",
-          inputs: [
-            { start: 0, name: "boxes", type: "tensor" },
-            { start: 1, name: "scores", type: "tensor" },
-            { start: 2, name: "maxOutputSize", type: "number" },
-            { start: 3, name: "iouThreshold", type: "number" },
-          ],
-        },
-        {
-          tfOpName: "NonMaxSuppressionV3",
-          category: "dynamic",
-          inputs: [
-            { start: 0, name: "boxes", type: "tensor" },
-            { start: 1, name: "scores", type: "tensor" },
-            { start: 2, name: "maxOutputSize", type: "number" },
-            { start: 3, name: "iouThreshold", type: "number" },
-            { start: 4, name: "scoreThreshold", type: "number" },
-          ],
-        },
-        {
-          tfOpName: "NonMaxSuppressionV5",
-          category: "dynamic",
-          inputs: [
-            { start: 0, name: "boxes", type: "tensor" },
-            { start: 1, name: "scores", type: "tensor" },
-            { start: 2, name: "maxOutputSize", type: "number" },
-            { start: 3, name: "iouThreshold", type: "number" },
-            { start: 4, name: "scoreThreshold", type: "number" },
-            { start: 5, name: "softNmsSigma", type: "number" },
-          ],
-        },
-        {
-          tfOpName: "Where",
-          category: "dynamic",
-          inputs: [{ start: 0, name: "condition", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "ListDiff",
-          category: "dynamic",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "y", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "T",
-              name: "dtype",
-              type: "dtype",
-              notSupported: true,
-            },
-          ],
-        },
-      ];
-      //# sourceMappingURL=dynamic.js.map
-
-      /***/
-    },
-    /* 47 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "TopKV2",
-          category: "evaluation",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "k", type: "number" },
-          ],
-          attrs: [{ tfName: "sorted", name: "sorted", type: "bool" }],
-        },
-      ];
-      //# sourceMappingURL=evaluation.js.map
-
-      /***/
-    },
-    /* 48 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "PlaceholderWithDefault",
-          category: "graph",
-          inputs: [{ start: 0, name: "default", type: "tensor" }],
-          attrs: [
-            { tfName: "shape", name: "shape", type: "shape" },
-            { tfName: "dtype", name: "dtype", type: "dtype" },
-          ],
-        },
-        {
-          tfOpName: "Placeholder",
-          category: "graph",
-          attrs: [
-            { tfName: "shape", name: "shape", type: "shape" },
-            { tfName: "dtype", name: "dtype", type: "dtype" },
-          ],
-        },
-        { tfOpName: "Const", category: "graph" },
-        {
-          tfOpName: "Identity",
-          category: "graph",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "IdentityN",
-          category: "graph",
-          inputs: [{ start: 0, end: 0, name: "x", type: "tensors" }],
-        },
-        {
-          tfOpName: "Snapshot",
-          category: "graph",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "Rank",
-          category: "graph",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "Size",
-          category: "graph",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "Shape",
-          category: "graph",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "ShapeN",
-          category: "graph",
-          inputs: [{ start: 0, end: 0, name: "x", type: "tensors" }],
-        },
-        {
-          tfOpName: "Print",
-          category: "graph",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "data", type: "tensors" },
-          ],
-          attrs: [
-            { tfName: "message", name: "message", type: "string" },
-            {
-              tfName: "first_n",
-              name: "firstN",
-              type: "number",
-              notSupported: true,
-            },
-            {
-              tfName: "summarize",
-              name: "summarize",
-              type: "number",
-              defaultValue: 3,
-            },
-          ],
-        },
-        { tfOpName: "NoOp", category: "graph", inputs: [] },
-        {
-          tfOpName: "StopGradient",
-          category: "graph",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "FakeQuantWithMinMaxVars",
-          category: "graph",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "min", name: "min", type: "number" },
-            { tfName: "max", name: "max", type: "number" },
-          ],
-        },
-      ];
-      //# sourceMappingURL=graph.js.map
-
-      /***/
-    },
-    /* 49 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "ResizeBilinear",
-          category: "image",
-          inputs: [
-            { start: 0, name: "images", type: "tensor" },
-            { start: 1, name: "size", type: "number[]" },
-          ],
-          attrs: [
-            { tfName: "align_corners", name: "alignCorners", type: "bool" },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "ResizeNearestNeighbor",
-          category: "image",
-          inputs: [
-            { start: 0, name: "images", type: "tensor" },
-            { start: 1, name: "size", type: "number[]" },
-          ],
-          attrs: [
-            { tfName: "align_corners", name: "alignCorners", type: "bool" },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "CropAndResize",
-          category: "image",
-          inputs: [
-            { start: 0, name: "image", type: "tensor" },
-            { start: 1, name: "boxes", type: "tensor" },
-            { start: 2, name: "boxInd", type: "tensor" },
-            { start: 3, name: "cropSize", type: "number[]" },
-          ],
-          attrs: [
-            { tfName: "method", name: "method", type: "string" },
-            {
-              tfName: "extrapolation_value",
-              name: "extrapolationValue",
-              type: "number",
-            },
-          ],
-        },
-      ];
-      //# sourceMappingURL=image.js.map
-
-      /***/
-    },
-    /* 50 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "Equal",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "NotEqual",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Greater",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "GreaterEqual",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Less",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "LessEqual",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "LogicalAnd",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "LogicalNot",
-          category: "logical",
-          inputs: [{ start: 0, name: "a", type: "tensor" }],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "LogicalOr",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "Select",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "condition", type: "tensor" },
-            { start: 1, name: "a", type: "tensor" },
-            { start: 2, name: "b", type: "tensor" },
-          ],
-          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
-        },
-        {
-          tfOpName: "SelectV2",
-          category: "logical",
-          inputs: [
-            { start: 0, name: "condition", type: "tensor" },
-            { start: 1, name: "a", type: "tensor" },
-            { start: 2, name: "b", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "T",
-              name: "dtype",
-              type: "dtype",
-              notSupported: true,
-            },
-          ],
-        },
-      ];
-      //# sourceMappingURL=logical.js.map
-
-      /***/
-    },
-    /* 51 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "_FusedMatMul",
-          category: "matrices",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-            { start: 2, end: 0, name: "args", type: "tensors" },
-          ],
-          attrs: [
-            { tfName: "num_args", name: "numArgs", type: "number" },
-            {
-              tfName: "fused_ops",
-              name: "fusedOps",
-              type: "string[]",
-              defaultValue: [],
-            },
-            {
-              tfName: "epsilon",
-              name: "epsilon",
-              type: "number",
-              defaultValue: 0.0001,
-            },
-            {
-              tfName: "transpose_a",
-              name: "transposeA",
-              type: "bool",
-              defaultValue: false,
-            },
-            {
-              tfName: "transpose_b",
-              name: "transposeB",
-              type: "bool",
-              defaultValue: false,
-            },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "MatMul",
-          category: "matrices",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "transpose_a",
-              name: "transposeA",
-              type: "bool",
-              defaultValue: false,
-            },
-            {
-              tfName: "transpose_b",
-              name: "transposeB",
-              type: "bool",
-              defaultValue: false,
-            },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "BatchMatMul",
-          category: "matrices",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "adj_x",
-              name: "transposeA",
-              type: "bool",
-              defaultValue: false,
-            },
-            {
-              tfName: "adj_y",
-              name: "transposeB",
-              type: "bool",
-              defaultValue: false,
-            },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "BatchMatMulV2",
-          category: "matrices",
-          inputs: [
-            { start: 0, name: "a", type: "tensor" },
-            { start: 1, name: "b", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "adj_x",
-              name: "transposeA",
-              type: "bool",
-              defaultValue: false,
-            },
-            {
-              tfName: "adj_y",
-              name: "transposeB",
-              type: "bool",
-              defaultValue: false,
-            },
-            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "Transpose",
-          category: "matrices",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "perm", type: "number[]" },
-          ],
-          attrs: [
-            {
-              tfName: "T",
-              name: "dtype",
-              type: "dtype",
-              notSupported: true,
-            },
-          ],
-        },
-      ];
-      //# sourceMappingURL=matrices.js.map
-
-      /***/
-    },
-    /* 52 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "FusedBatchNorm",
-          category: "normalization",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "scale", type: "tensor" },
-            { start: 2, name: "offset", type: "tensor" },
-            { start: 3, name: "mean", type: "tensor" },
-            { start: 4, name: "variance", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "epsilon",
-              name: "epsilon",
-              type: "number",
-              defaultValue: 0.001,
-            },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "FusedBatchNormV2",
-          category: "normalization",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "scale", type: "tensor" },
-            { start: 2, name: "offset", type: "tensor" },
-            { start: 3, name: "mean", type: "tensor" },
-            { start: 4, name: "variance", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "epsilon",
-              name: "epsilon",
-              type: "number",
-              defaultValue: 0.001,
-            },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "FusedBatchNormV3",
-          category: "normalization",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "scale", type: "tensor" },
-            { start: 2, name: "offset", type: "tensor" },
-            { start: 3, name: "mean", type: "tensor" },
-            { start: 4, name: "variance", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "epsilon",
-              name: "epsilon",
-              type: "number",
-              defaultValue: 0.001,
-            },
-            {
-              tfName: "data_format",
-              name: "dataFormat",
-              type: "string",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "LRN",
-          category: "normalization",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            {
-              tfName: "depth_radius",
-              name: "radius",
-              type: "number",
-              defaultValue: 5,
-            },
-            { tfName: "bias", name: "bias", type: "number", defaultValue: 1.0 },
-            {
-              tfName: "alpha",
-              name: "alpha",
-              type: "number",
-              defaultValue: 1.0,
-            },
-            {
-              tfName: "beta",
-              name: "beta",
-              type: "number",
-              defaultValue: 0.5,
-            },
-          ],
-        },
-        {
-          tfOpName: "Softmax",
-          category: "normalization",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "LogSoftmax",
-          category: "normalization",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "SparseToDense",
-          category: "normalization",
-          inputs: [
-            { start: 0, name: "sparseIndices", type: "tensor" },
-            { start: 1, name: "outputShape", type: "number[]" },
-            { start: 2, name: "sparseValues", type: "tensor" },
-            { start: 3, name: "defaultValue", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "validate_indices",
-              name: "validateIndices",
-              type: "bool",
-              defaultValue: true,
-              notSupported: true,
-            },
-          ],
-        },
-      ];
-      //# sourceMappingURL=normalization.js.map
-
-      /***/
-    },
-    /* 53 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "Max",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number[]" },
-          ],
-          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
-        },
-        {
-          tfOpName: "Mean",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number[]" },
-          ],
-          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
-        },
-        {
-          tfOpName: "Min",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number[]" },
-          ],
-          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
-        },
-        {
-          tfOpName: "Sum",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number[]" },
-          ],
-          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
-        },
-        {
-          tfOpName: "All",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number[]" },
-          ],
-          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
-        },
-        {
-          tfOpName: "Any",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number[]" },
-          ],
-          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
-        },
-        {
-          tfOpName: "ArgMax",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number" },
-          ],
-        },
-        {
-          tfOpName: "ArgMin",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number" },
-          ],
-        },
-        {
-          tfOpName: "Prod",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number[]" },
-          ],
-          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
-        },
-        {
-          tfOpName: "Cumsum",
-          category: "reduction",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number" },
-          ],
-          attrs: [
-            { tfName: "exclusive", name: "exclusive", type: "bool" },
-            { tfName: "reverse", name: "reverse", type: "bool" },
-          ],
-        },
-      ];
-      //# sourceMappingURL=reduction.js.map
-
-      /***/
-    },
-    /* 54 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "ConcatV2",
-          category: "slice_join",
-          inputs: [
-            { start: 0, end: -1, name: "tensors", type: "tensors" },
-            { start: -1, name: "axis", type: "number" },
-          ],
-          attrs: [{ tfName: "N", name: "n", type: "number", defaultValue: 2 }],
-        },
-        {
-          tfOpName: "Concat",
-          category: "slice_join",
-          inputs: [
-            { start: 1, end: 0, name: "tensors", type: "tensors" },
-            { start: 0, name: "axis", type: "number" },
-          ],
-          attrs: [{ tfName: "N", name: "n", type: "number", defaultValue: 2 }],
-        },
-        {
-          tfOpName: "GatherV2",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "indices", type: "tensor" },
-            { start: 2, name: "axis", type: "number", defaultValue: 0 },
-          ],
-        },
-        {
-          tfOpName: "Gather",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "indices", type: "tensor" },
-          ],
-          attrs: [
-            { tfName: "axis", name: "axis", type: "number", defaultValue: 0 },
-            {
-              tfName: "validate_indices",
-              name: "validateIndices",
-              type: "bool",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "Reverse",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "dims", type: "bool", notSupported: true },
-          ],
-        },
-        {
-          tfOpName: "ReverseV2",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "Slice",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "begin", type: "number[]" },
-            { start: 2, name: "size", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "StridedSlice",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "begin", type: "number[]" },
-            { start: 2, name: "end", type: "number[]" },
-            { start: 3, name: "strides", type: "number[]" },
-          ],
-          attrs: [
-            {
-              tfName: "begin_mask",
-              name: "beginMask",
-              type: "number",
-              defaultValue: 0,
-            },
-            {
-              tfName: "end_mask",
-              name: "endMask",
-              type: "number",
-              defaultValue: 0,
-            },
-            {
-              tfName: "new_axis_mask",
-              name: "newAxisMask",
-              type: "number",
-              defaultValue: 0,
-            },
-            {
-              tfName: "ellipsis_mask",
-              name: "ellipsisMask",
-              type: "number",
-              defaultValue: 0,
-            },
-            {
-              tfName: "shrink_axis_mask",
-              name: "shrinkAxisMask",
-              type: "number",
-              defaultValue: 0,
-            },
-          ],
-        },
-        {
-          tfOpName: "Pack",
-          category: "slice_join",
-          inputs: [{ start: 0, end: 0, name: "tensors", type: "tensors" }],
-          attrs: [{ tfName: "axis", name: "axis", type: "number", defaultValue: 0 }],
-        },
-        {
-          tfOpName: "Unpack",
-          category: "slice_join",
-          inputs: [{ start: 0, name: "tensor", type: "tensor" }],
-          attrs: [
-            { tfName: "axis", name: "axis", type: "number", defaultValue: 0 },
-            {
-              tfName: "num",
-              name: "num",
-              type: "number",
-              defaultValue: 0,
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "Tile",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "reps", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "Split",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "axis", type: "number", defaultValue: 0 },
-            { start: 1, name: "x", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "num_split",
-              name: "numOrSizeSplits",
-              type: "number",
-              defaultValue: 1,
-            },
-          ],
-        },
-        {
-          tfOpName: "SplitV",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "numOrSizeSplits", type: "number[]" },
-            { start: 2, name: "axis", type: "number", defaultValue: 0 },
-          ],
-        },
-        {
-          tfOpName: "ScatterNd",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "indices", type: "tensor" },
-            { start: 1, name: "values", type: "tensor" },
-            { start: 2, name: "shape", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "GatherNd",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "indices", type: "tensor" },
-          ],
-        },
-        {
-          tfOpName: "SparseToDense",
-          category: "slice_join",
-          inputs: [
-            { start: 0, name: "sparseIndices", type: "tensor" },
-            { start: 1, name: "outputShape", type: "number[]" },
-            { start: 2, name: "sparseValues", type: "tensor" },
-            { start: 3, name: "defaultValue", type: "tensor" },
-          ],
-          attrs: [
-            {
-              tfName: "validate_indices",
-              name: "validateIndices",
-              type: "bool",
-              defaultValue: false,
-              notSupported: true,
-            },
-          ],
-        },
-      ];
-      //# sourceMappingURL=slice_join.js.map
-
-      /***/
-    },
-    /* 55 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "FFT",
-          category: "spectral",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "IFFT",
-          category: "spectral",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-        },
-        {
-          tfOpName: "RFFT",
-          category: "spectral",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            {
-              start: 1,
-              name: "fft_length",
-              type: "number",
-              notSupported: true,
-            },
-          ],
-        },
-        {
-          tfOpName: "IRFFT",
-          category: "spectral",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            {
-              start: 1,
-              name: "fft_length",
-              type: "number",
-              notSupported: true,
-            },
-          ],
-        },
-      ];
-      //# sourceMappingURL=spectral.js.map
-
-      /***/
-    },
-    /* 56 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "json",
-        function () {
-          return json;
-        }
-      );
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const json = [
-        {
-          tfOpName: "Cast",
-          category: "transformation",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            {
-              tfName: "SrcT",
-              name: "sdtype",
-              type: "dtype",
-              notSupported: true,
-            },
-            { tfName: "DstT", name: "dtype", type: "dtype" },
-          ],
-        },
-        {
-          tfOpName: "ExpandDims",
-          category: "transformation",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "axis", type: "number" },
-          ],
-        },
-        {
-          tfOpName: "Pad",
-          category: "transformation",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "padding", type: "number[]" },
-          ],
-          attrs: [
-            {
-              tfName: "constant_value",
-              name: "constantValue",
-              type: "number",
-              defaultValue: 0,
-            },
-          ],
-        },
-        {
-          tfOpName: "PadV2",
-          category: "transformation",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "padding", type: "number[]" },
-            {
-              start: 2,
-              name: "constantValue",
-              type: "number",
-              defaultValue: 0,
-            },
-          ],
-        },
-        {
-          tfOpName: "Reshape",
-          category: "transformation",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "shape", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "Squeeze",
-          category: "transformation",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            {
-              tfName: "axis",
-              tfDeprecatedName: "squeeze_dims",
-              name: "axis",
-              type: "number[]",
-            },
-          ],
-        },
-        {
-          tfOpName: "SpaceToBatchND",
-          category: "transformation",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "blockShape", type: "number[]" },
-            { start: 2, name: "paddings", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "BatchToSpaceND",
-          category: "transformation",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "blockShape", type: "number[]" },
-            { start: 2, name: "crops", type: "number[]" },
-          ],
-        },
-        {
-          tfOpName: "DepthToSpace",
-          category: "transformation",
-          inputs: [{ start: 0, name: "x", type: "tensor" }],
-          attrs: [
-            { tfName: "block_size", name: "blockSize", type: "number" },
-            { tfName: "data_format", name: "dataFormat", type: "string" },
-          ],
-        },
-        {
-          tfOpName: "BroadcastTo",
-          category: "transformation",
-          inputs: [
-            { start: 0, name: "x", type: "tensor" },
-            { start: 1, name: "shape", type: "number[]" },
-          ],
-          attrs: [],
-        },
-      ];
-      //# sourceMappingURL=transformation.js.map
-
-      /***/
-    },
-    /* 57 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (Buffer) {
-        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-          return ByteChunkIterator;
-        });
-        /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
-          __webpack_require__(0);
-        /* harmony import */ var _lazy_iterator__WEBPACK_IMPORTED_MODULE_1__ =
-          __webpack_require__(14);
-        /* harmony import */ var _string_iterator__WEBPACK_IMPORTED_MODULE_2__ =
-          __webpack_require__(58);
-        /**
-         * @license
-         * Copyright 2018 Google LLC. All Rights Reserved.
-         * Licensed under the Apache License, Version 2.0 (the "License");
-         * you may not use this file except in compliance with the License.
-         * You may obtain a copy of the License at
-         *
-         * http://www.apache.org/licenses/LICENSE-2.0
-         *
-         * Unless required by applicable law or agreed to in writing, software
-         * distributed under the License is distributed on an "AS IS" BASIS,
-         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-         * See the License for the specific language governing permissions and
-         * limitations under the License.
-         *
-         * =============================================================================
-         */
-
-        class ByteChunkIterator extends _lazy_iterator__WEBPACK_IMPORTED_MODULE_1__[
-          /* LazyIterator */ "a"
-        ] {
-          /**
-           * Decode a stream of UTF8-encoded byte arrays to a stream of strings.
-           *
-           * The byte arrays producetd from the ByteChunkIterator on which this is
-           * called will be interpreted as concatenated.  No assumptions are made about
-           * the boundaries of the incoming chunks, so a multi-byte UTF8 encoding of a
-           * character may span the boundary between chunks.  This naturally happens,
-           * for instance, when reading fixed-size byte arrays from a file.
-           */
-          decodeUTF8() {
-            return new Utf8Iterator(this);
-          }
-        }
-        // ============================================================================
-        // The following private classes serve to implement the chainable methods
-        // on ByteChunkIterator.  Unfortunately they can't be placed in separate files,
-        // due to resulting trouble with circular imports.
-        // ============================================================================
-        // We wanted multiple inheritance, e.g.
-        //   class Utf8Iterator extends QueueIterator<string>, StringIterator
-        // but the TypeScript mixin approach is a bit hacky, so we take this adapter
-        // approach instead.
-        class Utf8Iterator extends _string_iterator__WEBPACK_IMPORTED_MODULE_2__[
-          /* StringIterator */ "a"
-        ] {
-          constructor(upstream) {
-            super();
-            this.upstream = upstream;
-            this.impl = new Utf8IteratorImpl(upstream);
-          }
-          summary() {
-            return this.impl.summary();
-          }
-          async next() {
-            return this.impl.next();
-          }
-        }
-        /**
-         * Decode a stream of UTF8-encoded byte arrays to a stream of strings.
-         *
-         * This is tricky because the incoming byte array boundaries may disrupt a
-         * multi-byte UTF8 character. Thus any incomplete character data at the end of
-         * a chunk must be carried over and prepended to the next chunk before
-         * decoding. Luckily with native decoder, TextDecoder in browser and
-         * string_decoder in node, byte array boundaries are handled automatically.
-         *
-         * In the context of an input pipeline for machine learning, UTF8 decoding is
-         * needed to parse text files containing training examples or prediction
-         * requests (e.g., formatted as CSV or JSON). We cannot use the built-in
-         * decoding provided by FileReader.readAsText() because here we are in a
-         * streaming context, which FileReader does not support.
-         *
-         * @param upstream A `LazyIterator` of `Uint8Arrays` containing UTF8-encoded
-         *   text, which should be interpreted as concatenated.  No assumptions are
-         *   made about the boundaries of the incoming chunks, so a multi-byte UTF8
-         *   encoding of a character may span the boundary between chunks.  This
-         *   naturally happens, for instance, when reading fixed-size byte arrays from a
-         *   file.
-         */
-        class Utf8IteratorImpl extends _lazy_iterator__WEBPACK_IMPORTED_MODULE_1__[
-          /* OneToManyIterator */ "b"
-        ] {
-          constructor(upstream) {
-            super();
-            this.upstream = upstream;
-            if (
-              Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["env"])().get("IS_BROWSER")
-            ) {
-              this.decoder = new TextDecoder("utf-8");
-            } else {
-              // tslint:disable-next-line:no-require-imports
-              const { StringDecoder } = __webpack_require__(78);
-              this.decoder = new StringDecoder("utf8");
-            }
-          }
-          summary() {
-            return `${this.upstream.summary()} -> Utf8`;
-          }
-          async pump() {
-            const chunkResult = await this.upstream.next();
-            let chunk;
-            if (chunkResult.done) {
-              return false;
-            } else {
-              chunk = chunkResult.value;
-            }
-            let text;
-            if (
-              Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["env"])().get("IS_BROWSER")
-            ) {
-              text = this.decoder.decode(chunk, { stream: true });
-            } else {
-              text = this.decoder.write(Buffer.from(chunk.buffer));
-            }
-            this.outputQueue.push(text);
-            return true;
-          }
-        }
-        //# sourceMappingURL=byte_chunk_iterator.js.map
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(39).Buffer));
-
-      /***/
-    },
-    /* 58 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
-        return StringIterator;
-      });
-      /* harmony import */ var _lazy_iterator__WEBPACK_IMPORTED_MODULE_0__ =
-        __webpack_require__(14);
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      class StringIterator extends _lazy_iterator__WEBPACK_IMPORTED_MODULE_0__[
-        /* LazyIterator */ "a"
-      ] {
-        /**
-         * Splits a string stream on a given separator.
-         *
-         * It is assumed that the incoming chunk boundaries have no semantic meaning,
-         * so conceptually the incoming stream is treated simply as the concatenation
-         * of its elements.
-         *
-         * The outgoing stream provides chunks corresponding to the results of the
-         * standard string split() operation (even if such a chunk spanned incoming
-         * chunks).  The separators are not included.
-         *
-         * A typical usage is to split a text file (represented as a stream with
-         * arbitrary chunk boundaries) into lines.
-         *
-         * @param upstream A readable stream of strings that can be treated as
-         *   concatenated.
-         * @param separator A character to split on.
-         */
-        split(separator) {
-          return new SplitIterator(this, separator);
-        }
-      }
-      // ============================================================================
-      // The following private classes serve to implement the chainable methods
-      // on StringIterator.  Unfortunately they can't be placed in separate files, due
-      // to resulting trouble with circular imports.
-      // ============================================================================
-      // We wanted multiple inheritance, e.g.
-      //   class SplitIterator extends QueueIterator<string>, StringIterator
-      // but the TypeScript mixin approach is a bit hacky, so we take this adapter
-      // approach instead.
-      class SplitIterator extends StringIterator {
-        constructor(upstream, separator) {
-          super();
-          this.upstream = upstream;
-          this.impl = new SplitIteratorImpl(upstream, separator);
-        }
-        summary() {
-          return this.impl.summary();
-        }
-        async next() {
-          return this.impl.next();
-        }
-      }
-      class SplitIteratorImpl extends _lazy_iterator__WEBPACK_IMPORTED_MODULE_0__[
-        /* OneToManyIterator */ "b"
-      ] {
-        constructor(upstream, separator) {
-          super();
-          this.upstream = upstream;
-          this.separator = separator;
-          // A partial string at the end of an upstream chunk
-          this.carryover = "";
-        }
-        summary() {
-          return `${this.upstream.summary()} -> Split('${this.separator}')`;
-        }
-        async pump() {
-          const chunkResult = await this.upstream.next();
-          if (chunkResult.done) {
-            if (this.carryover === "") {
-              return false;
-            }
-            // Pretend that the pump succeeded in order to emit the small last batch.
-            // The next pump() call will actually fail.
-            this.outputQueue.push(this.carryover);
-            this.carryover = "";
-            return true;
-          }
-          const lines = chunkResult.value.split(this.separator);
-          // Note the behavior: " ab ".split(' ') === ['', 'ab', '']
-          // Thus the carryover may be '' if the separator falls on a chunk
-          // boundary; this produces the correct result.
-          lines[0] = this.carryover + lines[0];
-          for (const line of lines.slice(0, -1)) {
-            this.outputQueue.push(line);
-          }
-          this.carryover = lines[lines.length - 1];
-          return true;
-        }
-      }
-      //# sourceMappingURL=string_iterator.js.map
-
-      /***/
-    },
-    /* 59 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-
-      Object.defineProperty(exports, "__esModule", { value: true });
-      const blazeface = __webpack_require__(81);
-      const tfconv = __webpack_require__(38);
-      const tf = __webpack_require__(0);
-      const keypoints_1 = __webpack_require__(82);
-      const pipeline_1 = __webpack_require__(83);
-      const uv_coords_1 = __webpack_require__(85);
-      const FACEMESH_GRAPHMODEL_PATH =
-        "https://tfhub.dev/mediapipe/tfjs-model/facemesh/1/default/1";
-      const MESH_MODEL_INPUT_WIDTH = 192;
-      const MESH_MODEL_INPUT_HEIGHT = 192;
-      async function load({
-        maxContinuousChecks = 5,
-        detectionConfidence = 0.9,
-        maxFaces = 10,
-        iouThreshold = 0.3,
-        scoreThreshold = 0.75,
-      } = {}) {
-        const [blazeFace, blazeMeshModel] = await Promise.all([
-          loadDetectorModel(maxFaces, iouThreshold, scoreThreshold),
-          loadMeshModel(),
-        ]);
-        const faceMesh = new FaceMesh(
-          blazeFace,
-          blazeMeshModel,
-          maxContinuousChecks,
-          detectionConfidence,
-          maxFaces
-        );
-        return faceMesh;
-      }
-      exports.load = load;
-      async function loadDetectorModel(maxFaces, iouThreshold, scoreThreshold) {
-        return blazeface.load({ maxFaces, iouThreshold, scoreThreshold });
-      }
-      async function loadMeshModel() {
-        return tfconv.loadGraphModel(FACEMESH_GRAPHMODEL_PATH, { fromTFHub: true });
-      }
-      function getInputTensorDimensions(input) {
-        return input instanceof tf.Tensor
-          ? [input.shape[0], input.shape[1]]
-          : [input.height, input.width];
-      }
-      function flipFaceHorizontal(face, imageWidth) {
-        if (face.mesh instanceof tf.Tensor) {
-          const [topLeft, bottomRight, mesh, scaledMesh] = tf.tidy(() => {
-            const subtractBasis = tf.tensor1d([imageWidth - 1, 0, 0]);
-            const multiplyBasis = tf.tensor1d([1, -1, 1]);
-            return tf.tidy(() => {
-              return [
-                tf.concat([
-                  tf.sub(imageWidth - 1, face.boundingBox.topLeft.slice(0, 1)),
-                  face.boundingBox.topLeft.slice(1, 1),
-                ]),
-                tf.concat([
-                  tf.sub(imageWidth - 1, face.boundingBox.bottomRight.slice(0, 1)),
-                  face.boundingBox.bottomRight.slice(1, 1),
-                ]),
-                tf.sub(subtractBasis, face.mesh).mul(multiplyBasis),
-                tf.sub(subtractBasis, face.scaledMesh).mul(multiplyBasis),
-              ];
-            });
-          });
-          return Object.assign({}, face, {
-            boundingBox: { topLeft, bottomRight },
-            mesh,
-            scaledMesh,
-          });
-        }
-        return Object.assign({}, face, {
-          boundingBox: {
-            topLeft: [imageWidth - 1 - face.boundingBox.topLeft[0], face.boundingBox.topLeft[1]],
-            bottomRight: [
-              imageWidth - 1 - face.boundingBox.bottomRight[0],
-              face.boundingBox.bottomRight[1],
-            ],
-          },
-          mesh: face.mesh.map((coord) => {
-            const flippedCoord = coord.slice(0);
-            flippedCoord[0] = imageWidth - 1 - coord[0];
-            return flippedCoord;
-          }),
-          scaledMesh: face.scaledMesh.map((coord) => {
-            const flippedCoord = coord.slice(0);
-            flippedCoord[0] = imageWidth - 1 - coord[0];
-            return flippedCoord;
-          }),
-        });
-      }
-      class FaceMesh {
-        constructor(blazeFace, blazeMeshModel, maxContinuousChecks, detectionConfidence, maxFaces) {
-          this.pipeline = new pipeline_1.Pipeline(
-            blazeFace,
-            blazeMeshModel,
-            MESH_MODEL_INPUT_WIDTH,
-            MESH_MODEL_INPUT_HEIGHT,
-            maxContinuousChecks,
-            maxFaces
-          );
-          this.detectionConfidence = detectionConfidence;
-        }
-        static getAnnotations() {
-          return keypoints_1.MESH_ANNOTATIONS;
-        }
-        static getUVCoords() {
-          return uv_coords_1.UV_COORDS;
-        }
-        async estimateFaces(input, returnTensors = false, flipHorizontal = false) {
-          const [, width] = getInputTensorDimensions(input);
-          const image = tf.tidy(() => {
-            if (!(input instanceof tf.Tensor)) {
-              input = tf.browser.fromPixels(input);
-            }
-            return input.toFloat().expandDims(0);
-          });
-          const savedWebglPackDepthwiseConvFlag = tf.env().get("WEBGL_PACK_DEPTHWISECONV");
-          tf.env().set("WEBGL_PACK_DEPTHWISECONV", true);
-          const predictions = await this.pipeline.predict(image);
-          tf.env().set("WEBGL_PACK_DEPTHWISECONV", savedWebglPackDepthwiseConvFlag);
-          image.dispose();
-          if (predictions != null && predictions.length > 0) {
-            return Promise.all(
-              predictions.map(async (prediction, i) => {
-                const { coords, scaledCoords, box, flag } = prediction;
-                let tensorsToRead = [flag];
-                if (!returnTensors) {
-                  tensorsToRead = tensorsToRead.concat([
-                    coords,
-                    scaledCoords,
-                    box.startPoint,
-                    box.endPoint,
-                  ]);
-                }
-                const tensorValues = await Promise.all(tensorsToRead.map(async (d) => d.array()));
-                const flagValue = tensorValues[0];
-                flag.dispose();
-                if (flagValue < this.detectionConfidence) {
-                  this.pipeline.clearRegionOfInterest(i);
-                }
-                if (returnTensors) {
-                  const annotatedPrediction = {
-                    faceInViewConfidence: flagValue,
-                    mesh: coords,
-                    scaledMesh: scaledCoords,
-                    boundingBox: {
-                      topLeft: box.startPoint.squeeze(),
-                      bottomRight: box.endPoint.squeeze(),
-                    },
-                  };
-                  if (flipHorizontal) {
-                    return flipFaceHorizontal(annotatedPrediction, width);
-                  }
-                  return annotatedPrediction;
-                }
-                const [coordsArr, coordsArrScaled, topLeft, bottomRight] = tensorValues.slice(1);
-                scaledCoords.dispose();
-                coords.dispose();
-                let annotatedPrediction = {
-                  faceInViewConfidence: flagValue,
-                  boundingBox: { topLeft, bottomRight },
-                  mesh: coordsArr,
-                  scaledMesh: coordsArrScaled,
-                };
-                if (flipHorizontal) {
-                  annotatedPrediction = flipFaceHorizontal(annotatedPrediction, width);
-                }
-                const annotations = {};
-                for (const key in keypoints_1.MESH_ANNOTATIONS) {
-                  annotations[key] = keypoints_1.MESH_ANNOTATIONS[key].map(
-                    (index) => annotatedPrediction.scaledMesh[index]
-                  );
-                }
-                annotatedPrediction["annotations"] = annotations;
-                return annotatedPrediction;
-              })
-            );
-          }
-          return [];
-        }
-      }
-      exports.FaceMesh = FaceMesh;
-      //# sourceMappingURL=index.js.map
-
-      /***/
-    },
-    /* 60 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      Object.defineProperty(exports, "__esModule", { value: true });
-
-      var tfjsCore = __webpack_require__(0);
-      var tfjsLayers = __webpack_require__(87);
-      var tfjsConverter = __webpack_require__(38);
-      var tfjsData = __webpack_require__(88);
-      var tfjsBackendCpu = __webpack_require__(89);
-      var tfjsBackendWebgl = __webpack_require__(86);
-
-      /** @license See the LICENSE file. */
-      // This code is auto-generated, do not modify this file!
-      var version = "2.0.1";
-
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      var version$1 = {
-        "tfjs-core": tfjsCore.version_core,
-        "tfjs-backend-cpu": tfjsBackendCpu.version_cpu,
-        "tfjs-backend-webgl": tfjsBackendWebgl.version_webgl,
-        "tfjs-data": tfjsData.version_data,
-        "tfjs-layers": tfjsLayers.version_layers,
-        "tfjs-converter": tfjsConverter.version_converter,
-        tfjs: version,
-      };
-
-      Object.keys(tfjsCore).forEach(function (k) {
-        if (k !== "default")
-          Object.defineProperty(exports, k, {
-            enumerable: true,
-            get: function () {
-              return tfjsCore[k];
-            },
-          });
-      });
-      Object.keys(tfjsLayers).forEach(function (k) {
-        if (k !== "default")
-          Object.defineProperty(exports, k, {
-            enumerable: true,
-            get: function () {
-              return tfjsLayers[k];
-            },
-          });
-      });
-      Object.keys(tfjsConverter).forEach(function (k) {
-        if (k !== "default")
-          Object.defineProperty(exports, k, {
-            enumerable: true,
-            get: function () {
-              return tfjsConverter[k];
-            },
-          });
-      });
-      exports.data = tfjsData;
-      exports.version = version$1;
-      //# sourceMappingURL=tf.node.js.map
-
-      /***/
-    },
-    /* 61 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (process) {
-        /* harmony import */ var _device_util__WEBPACK_IMPORTED_MODULE_0__ =
-          __webpack_require__(36);
-        /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_1__ =
-          __webpack_require__(10);
-        /**
-         * @license
-         * Copyright 2019 Google Inc. All Rights Reserved.
-         * Licensed under the Apache License, Version 2.0 (the "License");
-         * you may not use this file except in compliance with the License.
-         * You may obtain a copy of the License at
-         *
-         * http://www.apache.org/licenses/LICENSE-2.0
-         *
-         * Unless required by applicable law or agreed to in writing, software
-         * distributed under the License is distributed on an "AS IS" BASIS,
-         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-         * See the License for the specific language governing permissions and
-         * limitations under the License.
-         * =============================================================================
-         */
-
-        const ENV = Object(_environment__WEBPACK_IMPORTED_MODULE_1__[/* env */ "c"])();
-        /**
-         * This file contains environment-related flag registrations.
-         */
-        /** Whether to enable debug mode. */
-        ENV.registerFlag(
-          "DEBUG",
-          () => false,
-          (debugValue) => {
-            if (debugValue) {
-              console.warn(
-                "Debugging mode is ON. The output of every math call will " +
-                  "be downloaded to CPU and checked for NaNs. " +
-                  "This significantly impacts performance."
-              );
-            }
-          }
-        );
-        /** Whether we are in a browser (as versus, say, node.js) environment. */
-        ENV.registerFlag("IS_BROWSER", () =>
-          _device_util__WEBPACK_IMPORTED_MODULE_0__["isBrowser"]()
-        );
-        /** Whether we are in a browser (as versus, say, node.js) environment. */
-        ENV.registerFlag(
-          "IS_NODE",
-          () =>
-            typeof process !== "undefined" &&
-            typeof process.versions !== "undefined" &&
-            typeof process.versions.node !== "undefined"
-        );
-        /** Whether this browser is Chrome. */
-        ENV.registerFlag(
-          "IS_CHROME",
-          () =>
-            typeof navigator !== "undefined" &&
-            navigator != null &&
-            navigator.userAgent != null &&
-            /Chrome/.test(navigator.userAgent) &&
-            /Google Inc/.test(navigator.vendor)
-        );
-        /**
-         * True when the environment is "production" where we disable safety checks
-         * to gain performance.
-         */
-        ENV.registerFlag("PROD", () => false);
-        /**
-         * Whether to do sanity checks when inferring a shape from user-provided
-         * values, used when creating a new tensor.
-         */
-        ENV.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY", () => ENV.getBool("DEBUG"));
-        /** Whether deprecation warnings are enabled. */
-        ENV.registerFlag("DEPRECATION_WARNINGS_ENABLED", () => true);
-        /** True if running unit tests. */
-        ENV.registerFlag("IS_TEST", () => false);
-        //# sourceMappingURL=flags.js.map
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(35)));
-
-      /***/
-    },
-    /* 62 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      /* WEBPACK VAR INJECTION */ (function (process) {
-        /* unused harmony export getNodeFetch */
-        /* unused harmony export resetSystemFetch */
-        /* unused harmony export setSystemFetch */
-        /* unused harmony export getSystemFetch */
-        /* unused harmony export PlatformNode */
-        /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_0__ =
-          __webpack_require__(10);
-        /**
-         * @license
-         * Copyright 2019 Google LLC. All Rights Reserved.
-         * Licensed under the Apache License, Version 2.0 (the "License");
-         * you may not use this file except in compliance with the License.
-         * You may obtain a copy of the License at
-         *
-         * http://www.apache.org/licenses/LICENSE-2.0
-         *
-         * Unless required by applicable law or agreed to in writing, software
-         * distributed under the License is distributed on an "AS IS" BASIS,
-         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-         * See the License for the specific language governing permissions and
-         * limitations under the License.
-         * =============================================================================
-         */
-
-        // We are wrapping this within an object so it can be stubbed by Jasmine.
-        const getNodeFetch = {
-          // tslint:disable-next-line:no-require-imports
-          importFetch: () => __webpack_require__(63),
-        };
-        let systemFetch;
-        // These getters and setters are for testing so we don't export a mutable
-        // variable.
-        function resetSystemFetch() {
-          systemFetch = null;
-        }
-        function setSystemFetch(fetchFn) {
-          systemFetch = fetchFn;
-        }
-        function getSystemFetch() {
-          return systemFetch;
-        }
-        class PlatformNode {
-          constructor() {
-            // tslint:disable-next-line:no-require-imports
-            this.util = __webpack_require__(64);
-            // According to the spec, the built-in encoder can do only UTF-8 encoding.
-            // https://developer.mozilla.org/en-US/docs/Web/API/TextEncoder/TextEncoder
-            this.textEncoder = new this.util.TextEncoder();
-          }
-          fetch(path, requestInits) {
-            if (
-              Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().global.fetch !=
-              null
-            ) {
-              return Object(
-                _environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"]
-              )().global.fetch(path, requestInits);
-            }
-            if (systemFetch == null) {
-              systemFetch = getNodeFetch.importFetch();
-            }
-            return systemFetch(path, requestInits);
-          }
-          now() {
-            const time = process.hrtime();
-            return time[0] * 1000 + time[1] / 1000000;
-          }
-          encode(text, encoding) {
-            if (encoding !== "utf-8" && encoding !== "utf8") {
-              throw new Error(`Node built-in encoder only supports utf-8, but got ${encoding}`);
-            }
-            return this.textEncoder.encode(text);
-          }
-          decode(bytes, encoding) {
-            if (bytes.length === 0) {
-              return "";
-            }
-            return new this.util.TextDecoder(encoding).decode(bytes);
-          }
-        }
-        if (Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().get("IS_NODE")) {
-          Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().setPlatform(
-            "node",
-            new PlatformNode()
-          );
-        }
-        //# sourceMappingURL=platform_node.js.map
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(35)));
-
-      /***/
-    },
-    /* 63 */
-    /***/ function (module, exports) {
-      /* (ignored) */
-      /***/
-    },
-    /* 64 */
-    /***/ function (module, exports) {
-      /* (ignored) */
-      /***/
-    },
-    /* 65 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-
-      exports.byteLength = byteLength;
-      exports.toByteArray = toByteArray;
-      exports.fromByteArray = fromByteArray;
-
-      var lookup = [];
-      var revLookup = [];
-      var Arr = typeof Uint8Array !== "undefined" ? Uint8Array : Array;
-
-      var code = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
-      for (var i = 0, len = code.length; i < len; ++i) {
-        lookup[i] = code[i];
-        revLookup[code.charCodeAt(i)] = i;
-      }
-
-      // Support decoding URL-safe base64 strings, as Node.js does.
-      // See: https://en.wikipedia.org/wiki/Base64#URL_applications
-      revLookup["-".charCodeAt(0)] = 62;
-      revLookup["_".charCodeAt(0)] = 63;
-
-      function getLens(b64) {
-        var len = b64.length;
-
-        if (len % 4 > 0) {
-          throw new Error("Invalid string. Length must be a multiple of 4");
-        }
-
-        // Trim off extra bytes after placeholder bytes are found
-        // See: https://github.com/beatgammit/base64-js/issues/42
-        var validLen = b64.indexOf("=");
-        if (validLen === -1) validLen = len;
-
-        var placeHoldersLen = validLen === len ? 0 : 4 - (validLen % 4);
-
-        return [validLen, placeHoldersLen];
-      }
-
-      // base64 is 4/3 + up to two characters of the original data
-      function byteLength(b64) {
-        var lens = getLens(b64);
-        var validLen = lens[0];
-        var placeHoldersLen = lens[1];
-        return ((validLen + placeHoldersLen) * 3) / 4 - placeHoldersLen;
-      }
-
-      function _byteLength(b64, validLen, placeHoldersLen) {
-        return ((validLen + placeHoldersLen) * 3) / 4 - placeHoldersLen;
-      }
-
-      function toByteArray(b64) {
-        var tmp;
-        var lens = getLens(b64);
-        var validLen = lens[0];
-        var placeHoldersLen = lens[1];
-
-        var arr = new Arr(_byteLength(b64, validLen, placeHoldersLen));
-
-        var curByte = 0;
-
-        // if there are placeholders, only get up to the last complete 4 chars
-        var len = placeHoldersLen > 0 ? validLen - 4 : validLen;
-
-        var i;
-        for (i = 0; i < len; i += 4) {
-          tmp =
-            (revLookup[b64.charCodeAt(i)] << 18) |
-            (revLookup[b64.charCodeAt(i + 1)] << 12) |
-            (revLookup[b64.charCodeAt(i + 2)] << 6) |
-            revLookup[b64.charCodeAt(i + 3)];
-          arr[curByte++] = (tmp >> 16) & 0xff;
-          arr[curByte++] = (tmp >> 8) & 0xff;
-          arr[curByte++] = tmp & 0xff;
-        }
-
-        if (placeHoldersLen === 2) {
-          tmp = (revLookup[b64.charCodeAt(i)] << 2) | (revLookup[b64.charCodeAt(i + 1)] >> 4);
-          arr[curByte++] = tmp & 0xff;
-        }
-
-        if (placeHoldersLen === 1) {
-          tmp =
-            (revLookup[b64.charCodeAt(i)] << 10) |
-            (revLookup[b64.charCodeAt(i + 1)] << 4) |
-            (revLookup[b64.charCodeAt(i + 2)] >> 2);
-          arr[curByte++] = (tmp >> 8) & 0xff;
-          arr[curByte++] = tmp & 0xff;
-        }
-
-        return arr;
-      }
-
-      function tripletToBase64(num) {
-        return (
-          lookup[(num >> 18) & 0x3f] +
-          lookup[(num >> 12) & 0x3f] +
-          lookup[(num >> 6) & 0x3f] +
-          lookup[num & 0x3f]
-        );
-      }
-
-      function encodeChunk(uint8, start, end) {
-        var tmp;
-        var output = [];
-        for (var i = start; i < end; i += 3) {
-          tmp =
-            ((uint8[i] << 16) & 0xff0000) + ((uint8[i + 1] << 8) & 0xff00) + (uint8[i + 2] & 0xff);
-          output.push(tripletToBase64(tmp));
-        }
-        return output.join("");
-      }
-
-      function fromByteArray(uint8) {
-        var tmp;
-        var len = uint8.length;
-        var extraBytes = len % 3; // if we have 1 byte left, pad 2 bytes
-        var parts = [];
-        var maxChunkLength = 16383; // must be multiple of 3
-
-        // go through the array every three bytes, we'll deal with trailing stuff later
-        for (var i = 0, len2 = len - extraBytes; i < len2; i += maxChunkLength) {
-          parts.push(encodeChunk(uint8, i, i + maxChunkLength > len2 ? len2 : i + maxChunkLength));
-        }
-
-        // pad the end with zeros, but make sure to not forget the extra bytes
-        if (extraBytes === 1) {
-          tmp = uint8[len - 1];
-          parts.push(lookup[tmp >> 2] + lookup[(tmp << 4) & 0x3f] + "==");
-        } else if (extraBytes === 2) {
-          tmp = (uint8[len - 2] << 8) + uint8[len - 1];
-          parts.push(
-            lookup[tmp >> 10] + lookup[(tmp >> 4) & 0x3f] + lookup[(tmp << 2) & 0x3f] + "="
-          );
-        }
-
-        return parts.join("");
-      }
-
-      /***/
-    },
-    /* 66 */
-    /***/ function (module, exports) {
-      exports.read = function (buffer, offset, isLE, mLen, nBytes) {
-        var e, m;
-        var eLen = nBytes * 8 - mLen - 1;
-        var eMax = (1 << eLen) - 1;
-        var eBias = eMax >> 1;
-        var nBits = -7;
-        var i = isLE ? nBytes - 1 : 0;
-        var d = isLE ? -1 : 1;
-        var s = buffer[offset + i];
-
-        i += d;
-
-        e = s & ((1 << -nBits) - 1);
-        s >>= -nBits;
-        nBits += eLen;
-        for (; nBits > 0; e = e * 256 + buffer[offset + i], i += d, nBits -= 8) {}
-
-        m = e & ((1 << -nBits) - 1);
-        e >>= -nBits;
-        nBits += mLen;
-        for (; nBits > 0; m = m * 256 + buffer[offset + i], i += d, nBits -= 8) {}
-
-        if (e === 0) {
-          e = 1 - eBias;
-        } else if (e === eMax) {
-          return m ? NaN : (s ? -1 : 1) * Infinity;
-        } else {
-          m = m + Math.pow(2, mLen);
-          e = e - eBias;
-        }
-        return (s ? -1 : 1) * m * Math.pow(2, e - mLen);
-      };
-
-      exports.write = function (buffer, value, offset, isLE, mLen, nBytes) {
-        var e, m, c;
-        var eLen = nBytes * 8 - mLen - 1;
-        var eMax = (1 << eLen) - 1;
-        var eBias = eMax >> 1;
-        var rt = mLen === 23 ? Math.pow(2, -24) - Math.pow(2, -77) : 0;
-        var i = isLE ? 0 : nBytes - 1;
-        var d = isLE ? 1 : -1;
-        var s = value < 0 || (value === 0 && 1 / value < 0) ? 1 : 0;
-
-        value = Math.abs(value);
-
-        if (isNaN(value) || value === Infinity) {
-          m = isNaN(value) ? 1 : 0;
-          e = eMax;
-        } else {
-          e = Math.floor(Math.log(value) / Math.LN2);
-          if (value * (c = Math.pow(2, -e)) < 1) {
-            e--;
-            c *= 2;
-          }
-          if (e + eBias >= 1) {
-            value += rt / c;
-          } else {
-            value += rt * Math.pow(2, 1 - eBias);
-          }
-          if (value * c >= 2) {
-            e++;
-            c /= 2;
-          }
-
-          if (e + eBias >= eMax) {
-            m = 0;
-            e = eMax;
-          } else if (e + eBias >= 1) {
-            m = (value * c - 1) * Math.pow(2, mLen);
-            e = e + eBias;
-          } else {
-            m = value * Math.pow(2, eBias - 1) * Math.pow(2, mLen);
-            e = 0;
-          }
-        }
-
-        for (; mLen >= 8; buffer[offset + i] = m & 0xff, i += d, m /= 256, mLen -= 8) {}
-
-        e = (e << mLen) | m;
-        eLen += mLen;
-        for (; eLen > 0; buffer[offset + i] = e & 0xff, i += d, e /= 256, eLen -= 8) {}
-
-        buffer[offset + i - d] |= s * 128;
-      };
-
-      /***/
-    },
-    /* 67 */
-    /***/ function (module, exports) {
-      var toString = {}.toString;
-
-      module.exports =
-        Array.isArray ||
-        function (arr) {
-          return toString.call(arr) == "[object Array]";
-        };
-
-      /***/
-    },
-    /* 68 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (module) {
-        var __WEBPACK_AMD_DEFINE_RESULT__; // A port of an algorithm by Johannes Baagøe <baagoe@baagoe.com>, 2010
-        // http://baagoe.com/en/RandomMusings/javascript/
-        // https://github.com/nquinlan/better-random-numbers-for-javascript-mirror
-        // Original work is under MIT license -
-
-        // Copyright (C) 2010 by Johannes Baagøe <baagoe@baagoe.org>
-        //
-        // Permission is hereby granted, free of charge, to any person obtaining a copy
-        // of this software and associated documentation files (the "Software"), to deal
-        // in the Software without restriction, including without limitation the rights
-        // to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-        // copies of the Software, and to permit persons to whom the Software is
-        // furnished to do so, subject to the following conditions:
-        //
-        // The above copyright notice and this permission notice shall be included in
-        // all copies or substantial portions of the Software.
-        //
-        // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-        // IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-        // FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-        // AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-        // LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-        // OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
-        // THE SOFTWARE.
-
-        (function (global, module, define) {
-          function Alea(seed) {
-            var me = this,
-              mash = Mash();
-
-            me.next = function () {
-              var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32
-              me.s0 = me.s1;
-              me.s1 = me.s2;
-              return (me.s2 = t - (me.c = t | 0));
-            };
-
-            // Apply the seeding algorithm from Baagoe.
-            me.c = 1;
-            me.s0 = mash(" ");
-            me.s1 = mash(" ");
-            me.s2 = mash(" ");
-            me.s0 -= mash(seed);
-            if (me.s0 < 0) {
-              me.s0 += 1;
-            }
-            me.s1 -= mash(seed);
-            if (me.s1 < 0) {
-              me.s1 += 1;
-            }
-            me.s2 -= mash(seed);
-            if (me.s2 < 0) {
-              me.s2 += 1;
-            }
-            mash = null;
-          }
-
-          function copy(f, t) {
-            t.c = f.c;
-            t.s0 = f.s0;
-            t.s1 = f.s1;
-            t.s2 = f.s2;
-            return t;
-          }
-
-          function impl(seed, opts) {
-            var xg = new Alea(seed),
-              state = opts && opts.state,
-              prng = xg.next;
-            prng.int32 = function () {
-              return (xg.next() * 0x100000000) | 0;
-            };
-            prng.double = function () {
-              return prng() + ((prng() * 0x200000) | 0) * 1.1102230246251565e-16; // 2^-53
-            };
-            prng.quick = prng;
-            if (state) {
-              if (typeof state == "object") copy(state, xg);
-              prng.state = function () {
-                return copy(xg, {});
-              };
-            }
-            return prng;
-          }
-
-          function Mash() {
-            var n = 0xefc8249d;
-
-            var mash = function (data) {
-              data = data.toString();
-              for (var i = 0; i < data.length; i++) {
-                n += data.charCodeAt(i);
-                var h = 0.02519603282416938 * n;
-                n = h >>> 0;
-                h -= n;
-                h *= n;
-                n = h >>> 0;
-                h -= n;
-                n += h * 0x100000000; // 2^32
-              }
-              return (n >>> 0) * 2.3283064365386963e-10; // 2^-32
-            };
-
-            return mash;
-          }
-
-          if (module && module.exports) {
-            module.exports = impl;
-          } else if (__webpack_require__(16) && __webpack_require__(29)) {
-            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
-              return impl;
-            }.call(exports, __webpack_require__, exports, module)),
-            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
-              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
-          } else {
-            this.alea = impl;
-          }
-        })(
-          this,
-          true && module, // present in node.js
-          __webpack_require__(16) // present with an AMD loader
-        );
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(28)(module)));
-
-      /***/
-    },
-    /* 69 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (module) {
-        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of the "xor128" prng algorithm by
-        // George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper
-
-        (function (global, module, define) {
-          function XorGen(seed) {
-            var me = this,
-              strseed = "";
-
-            me.x = 0;
-            me.y = 0;
-            me.z = 0;
-            me.w = 0;
-
-            // Set up generator function.
-            me.next = function () {
-              var t = me.x ^ (me.x << 11);
-              me.x = me.y;
-              me.y = me.z;
-              me.z = me.w;
-              return (me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8));
-            };
-
-            if (seed === (seed | 0)) {
-              // Integer seed.
-              me.x = seed;
-            } else {
-              // String seed.
-              strseed += seed;
-            }
-
-            // Mix in string seed, then discard an initial batch of 64 values.
-            for (var k = 0; k < strseed.length + 64; k++) {
-              me.x ^= strseed.charCodeAt(k) | 0;
-              me.next();
-            }
-          }
-
-          function copy(f, t) {
-            t.x = f.x;
-            t.y = f.y;
-            t.z = f.z;
-            t.w = f.w;
-            return t;
-          }
-
-          function impl(seed, opts) {
-            var xg = new XorGen(seed),
-              state = opts && opts.state,
-              prng = function () {
-                return (xg.next() >>> 0) / 0x100000000;
-              };
-            prng.double = function () {
-              do {
-                var top = xg.next() >>> 11,
-                  bot = (xg.next() >>> 0) / 0x100000000,
-                  result = (top + bot) / (1 << 21);
-              } while (result === 0);
-              return result;
-            };
-            prng.int32 = xg.next;
-            prng.quick = prng;
-            if (state) {
-              if (typeof state == "object") copy(state, xg);
-              prng.state = function () {
-                return copy(xg, {});
-              };
-            }
-            return prng;
-          }
-
-          if (module && module.exports) {
-            module.exports = impl;
-          } else if (__webpack_require__(16) && __webpack_require__(29)) {
-            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
-              return impl;
-            }.call(exports, __webpack_require__, exports, module)),
-            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
-              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
-          } else {
-            this.xor128 = impl;
-          }
-        })(
-          this,
-          true && module, // present in node.js
-          __webpack_require__(16) // present with an AMD loader
-        );
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(28)(module)));
-
-      /***/
-    },
-    /* 70 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (module) {
-        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of the "xorwow" prng algorithm by
-        // George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper
-
-        (function (global, module, define) {
-          function XorGen(seed) {
-            var me = this,
-              strseed = "";
-
-            // Set up generator function.
-            me.next = function () {
-              var t = me.x ^ (me.x >>> 2);
-              me.x = me.y;
-              me.y = me.z;
-              me.z = me.w;
-              me.w = me.v;
-              return (
-                ((me.d = (me.d + 362437) | 0) + (me.v = me.v ^ (me.v << 4) ^ (t ^ (t << 1)))) | 0
-              );
-            };
-
-            me.x = 0;
-            me.y = 0;
-            me.z = 0;
-            me.w = 0;
-            me.v = 0;
-
-            if (seed === (seed | 0)) {
-              // Integer seed.
-              me.x = seed;
-            } else {
-              // String seed.
-              strseed += seed;
-            }
-
-            // Mix in string seed, then discard an initial batch of 64 values.
-            for (var k = 0; k < strseed.length + 64; k++) {
-              me.x ^= strseed.charCodeAt(k) | 0;
-              if (k == strseed.length) {
-                me.d = (me.x << 10) ^ (me.x >>> 4);
-              }
-              me.next();
-            }
-          }
-
-          function copy(f, t) {
-            t.x = f.x;
-            t.y = f.y;
-            t.z = f.z;
-            t.w = f.w;
-            t.v = f.v;
-            t.d = f.d;
-            return t;
-          }
-
-          function impl(seed, opts) {
-            var xg = new XorGen(seed),
-              state = opts && opts.state,
-              prng = function () {
-                return (xg.next() >>> 0) / 0x100000000;
-              };
-            prng.double = function () {
-              do {
-                var top = xg.next() >>> 11,
-                  bot = (xg.next() >>> 0) / 0x100000000,
-                  result = (top + bot) / (1 << 21);
-              } while (result === 0);
-              return result;
-            };
-            prng.int32 = xg.next;
-            prng.quick = prng;
-            if (state) {
-              if (typeof state == "object") copy(state, xg);
-              prng.state = function () {
-                return copy(xg, {});
-              };
-            }
-            return prng;
-          }
-
-          if (module && module.exports) {
-            module.exports = impl;
-          } else if (__webpack_require__(16) && __webpack_require__(29)) {
-            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
-              return impl;
-            }.call(exports, __webpack_require__, exports, module)),
-            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
-              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
-          } else {
-            this.xorwow = impl;
-          }
-        })(
-          this,
-          true && module, // present in node.js
-          __webpack_require__(16) // present with an AMD loader
-        );
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(28)(module)));
-
-      /***/
-    },
-    /* 71 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (module) {
-        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of the "xorshift7" algorithm by
-        // François Panneton and Pierre L'ecuyer:
-        // "On the Xorgshift Random Number Generators"
-        // http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf
-
-        (function (global, module, define) {
-          function XorGen(seed) {
-            var me = this;
-
-            // Set up generator function.
-            me.next = function () {
-              // Update xor generator.
-              var X = me.x,
-                i = me.i,
-                t,
-                v,
-                w;
-              t = X[i];
-              t ^= t >>> 7;
-              v = t ^ (t << 24);
-              t = X[(i + 1) & 7];
-              v ^= t ^ (t >>> 10);
-              t = X[(i + 3) & 7];
-              v ^= t ^ (t >>> 3);
-              t = X[(i + 4) & 7];
-              v ^= t ^ (t << 7);
-              t = X[(i + 7) & 7];
-              t = t ^ (t << 13);
-              v ^= t ^ (t << 9);
-              X[i] = v;
-              me.i = (i + 1) & 7;
-              return v;
-            };
-
-            function init(me, seed) {
-              var j,
-                w,
-                X = [];
-
-              if (seed === (seed | 0)) {
-                // Seed state array using a 32-bit integer.
-                w = X[0] = seed;
-              } else {
-                // Seed state using a string.
-                seed = "" + seed;
-                for (j = 0; j < seed.length; ++j) {
-                  X[j & 7] = (X[j & 7] << 15) ^ ((seed.charCodeAt(j) + X[(j + 1) & 7]) << 13);
-                }
-              }
-              // Enforce an array length of 8, not all zeroes.
-              while (X.length < 8) X.push(0);
-              for (j = 0; j < 8 && X[j] === 0; ++j);
-              if (j == 8) w = X[7] = -1;
-              else w = X[j];
-
-              me.x = X;
-              me.i = 0;
-
-              // Discard an initial 256 values.
-              for (j = 256; j > 0; --j) {
-                me.next();
-              }
-            }
-
-            init(me, seed);
-          }
-
-          function copy(f, t) {
-            t.x = f.x.slice();
-            t.i = f.i;
-            return t;
-          }
-
-          function impl(seed, opts) {
-            if (seed == null) seed = +new Date();
-            var xg = new XorGen(seed),
-              state = opts && opts.state,
-              prng = function () {
-                return (xg.next() >>> 0) / 0x100000000;
-              };
-            prng.double = function () {
-              do {
-                var top = xg.next() >>> 11,
-                  bot = (xg.next() >>> 0) / 0x100000000,
-                  result = (top + bot) / (1 << 21);
-              } while (result === 0);
-              return result;
-            };
-            prng.int32 = xg.next;
-            prng.quick = prng;
-            if (state) {
-              if (state.x) copy(state, xg);
-              prng.state = function () {
-                return copy(xg, {});
-              };
-            }
-            return prng;
-          }
-
-          if (module && module.exports) {
-            module.exports = impl;
-          } else if (__webpack_require__(16) && __webpack_require__(29)) {
-            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
-              return impl;
-            }.call(exports, __webpack_require__, exports, module)),
-            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
-              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
-          } else {
-            this.xorshift7 = impl;
-          }
-        })(
-          this,
-          true && module, // present in node.js
-          __webpack_require__(16) // present with an AMD loader
-        );
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(28)(module)));
-
-      /***/
-    },
-    /* 72 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (module) {
-        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.
-        //
-        // This fast non-cryptographic random number generator is designed for
-        // use in Monte-Carlo algorithms. It combines a long-period xorshift
-        // generator with a Weyl generator, and it passes all common batteries
-        // of stasticial tests for randomness while consuming only a few nanoseconds
-        // for each prng generated.  For background on the generator, see Brent's
-        // paper: "Some long-period random number generators using shifts and xors."
-        // http://arxiv.org/pdf/1004.3115v1.pdf
-        //
-        // Usage:
-        //
-        // var xor4096 = require('xor4096');
-        // random = xor4096(1);                        // Seed with int32 or string.
-        // assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.
-        // assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.
-        //
-        // For nonzero numeric keys, this impelementation provides a sequence
-        // identical to that by Brent's xorgens 3 implementaion in C.  This
-        // implementation also provides for initalizing the generator with
-        // string seeds, or for saving and restoring the state of the generator.
-        //
-        // On Chrome, this prng benchmarks about 2.1 times slower than
-        // Javascript's built-in Math.random().
-
-        (function (global, module, define) {
-          function XorGen(seed) {
-            var me = this;
-
-            // Set up generator function.
-            me.next = function () {
-              var w = me.w,
-                X = me.X,
-                i = me.i,
-                t,
-                v;
-              // Update Weyl generator.
-              me.w = w = (w + 0x61c88647) | 0;
-              // Update xor generator.
-              v = X[(i + 34) & 127];
-              t = X[(i = (i + 1) & 127)];
-              v ^= v << 13;
-              t ^= t << 17;
-              v ^= v >>> 15;
-              t ^= t >>> 12;
-              // Update Xor generator array state.
-              v = X[i] = v ^ t;
-              me.i = i;
-              // Result is the combination.
-              return (v + (w ^ (w >>> 16))) | 0;
-            };
-
-            function init(me, seed) {
-              var t,
-                v,
-                i,
-                j,
-                w,
-                X = [],
-                limit = 128;
-              if (seed === (seed | 0)) {
-                // Numeric seeds initialize v, which is used to generates X.
-                v = seed;
-                seed = null;
-              } else {
-                // String seeds are mixed into v and X one character at a time.
-                seed = seed + "\0";
-                v = 0;
-                limit = Math.max(limit, seed.length);
-              }
-              // Initialize circular array and weyl value.
-              for (i = 0, j = -32; j < limit; ++j) {
-                // Put the unicode characters into the array, and shuffle them.
-                if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);
-                // After 32 shuffles, take v as the starting w value.
-                if (j === 0) w = v;
-                v ^= v << 10;
-                v ^= v >>> 15;
-                v ^= v << 4;
-                v ^= v >>> 13;
-                if (j >= 0) {
-                  w = (w + 0x61c88647) | 0; // Weyl.
-                  t = X[j & 127] ^= v + w; // Combine xor and weyl to init array.
-                  i = 0 == t ? i + 1 : 0; // Count zeroes.
-                }
-              }
-              // We have detected all zeroes; make the key nonzero.
-              if (i >= 128) {
-                X[((seed && seed.length) || 0) & 127] = -1;
-              }
-              // Run the generator 512 times to further mix the state before using it.
-              // Factoring this as a function slows the main generator, so it is just
-              // unrolled here.  The weyl generator is not advanced while warming up.
-              i = 127;
-              for (j = 4 * 128; j > 0; --j) {
-                v = X[(i + 34) & 127];
-                t = X[(i = (i + 1) & 127)];
-                v ^= v << 13;
-                t ^= t << 17;
-                v ^= v >>> 15;
-                t ^= t >>> 12;
-                X[i] = v ^ t;
-              }
-              // Storing state as object members is faster than using closure variables.
-              me.w = w;
-              me.X = X;
-              me.i = i;
-            }
-
-            init(me, seed);
-          }
-
-          function copy(f, t) {
-            t.i = f.i;
-            t.w = f.w;
-            t.X = f.X.slice();
-            return t;
-          }
-
-          function impl(seed, opts) {
-            if (seed == null) seed = +new Date();
-            var xg = new XorGen(seed),
-              state = opts && opts.state,
-              prng = function () {
-                return (xg.next() >>> 0) / 0x100000000;
-              };
-            prng.double = function () {
-              do {
-                var top = xg.next() >>> 11,
-                  bot = (xg.next() >>> 0) / 0x100000000,
-                  result = (top + bot) / (1 << 21);
-              } while (result === 0);
-              return result;
-            };
-            prng.int32 = xg.next;
-            prng.quick = prng;
-            if (state) {
-              if (state.X) copy(state, xg);
-              prng.state = function () {
-                return copy(xg, {});
-              };
-            }
-            return prng;
-          }
-
-          if (module && module.exports) {
-            module.exports = impl;
-          } else if (__webpack_require__(16) && __webpack_require__(29)) {
-            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
-              return impl;
-            }.call(exports, __webpack_require__, exports, module)),
-            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
-              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
-          } else {
-            this.xor4096 = impl;
-          }
-        })(
-          this, // window object or global
-          true && module, // present in node.js
-          __webpack_require__(16) // present with an AMD loader
-        );
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(28)(module)));
-
-      /***/
-    },
-    /* 73 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (module) {
-        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of the "Tyche-i" prng algorithm by
-        // Samuel Neves and Filipe Araujo.
-        // See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf
-
-        (function (global, module, define) {
-          function XorGen(seed) {
-            var me = this,
-              strseed = "";
-
-            // Set up generator function.
-            me.next = function () {
-              var b = me.b,
-                c = me.c,
-                d = me.d,
-                a = me.a;
-              b = (b << 25) ^ (b >>> 7) ^ c;
-              c = (c - d) | 0;
-              d = (d << 24) ^ (d >>> 8) ^ a;
-              a = (a - b) | 0;
-              me.b = b = (b << 20) ^ (b >>> 12) ^ c;
-              me.c = c = (c - d) | 0;
-              me.d = (d << 16) ^ (c >>> 16) ^ a;
-              return (me.a = (a - b) | 0);
-            };
-
-            /* The following is non-inverted tyche, which has better internal
-   * bit diffusion, but which is about 25% slower than tyche-i in JS.
-  me.next = function() {
-    var a = me.a, b = me.b, c = me.c, d = me.d;
-    a = (me.a + me.b | 0) >>> 0;
-    d = me.d ^ a; d = d << 16 ^ d >>> 16;
-    c = me.c + d | 0;
-    b = me.b ^ c; b = b << 12 ^ d >>> 20;
-    me.a = a = a + b | 0;
-    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;
-    me.c = c = c + d | 0;
-    b = b ^ c;
-    return me.b = (b << 7 ^ b >>> 25);
-  }
-  */
-
-            me.a = 0;
-            me.b = 0;
-            me.c = 2654435769 | 0;
-            me.d = 1367130551;
-
-            if (seed === Math.floor(seed)) {
-              // Integer seed.
-              me.a = (seed / 0x100000000) | 0;
-              me.b = seed | 0;
-            } else {
-              // String seed.
-              strseed += seed;
-            }
-
-            // Mix in string seed, then discard an initial batch of 64 values.
-            for (var k = 0; k < strseed.length + 20; k++) {
-              me.b ^= strseed.charCodeAt(k) | 0;
-              me.next();
-            }
-          }
-
-          function copy(f, t) {
-            t.a = f.a;
-            t.b = f.b;
-            t.c = f.c;
-            t.d = f.d;
-            return t;
-          }
-
-          function impl(seed, opts) {
-            var xg = new XorGen(seed),
-              state = opts && opts.state,
-              prng = function () {
-                return (xg.next() >>> 0) / 0x100000000;
-              };
-            prng.double = function () {
-              do {
-                var top = xg.next() >>> 11,
-                  bot = (xg.next() >>> 0) / 0x100000000,
-                  result = (top + bot) / (1 << 21);
-              } while (result === 0);
-              return result;
-            };
-            prng.int32 = xg.next;
-            prng.quick = prng;
-            if (state) {
-              if (typeof state == "object") copy(state, xg);
-              prng.state = function () {
-                return copy(xg, {});
-              };
-            }
-            return prng;
-          }
-
-          if (module && module.exports) {
-            module.exports = impl;
-          } else if (__webpack_require__(16) && __webpack_require__(29)) {
-            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
-              return impl;
-            }.call(exports, __webpack_require__, exports, module)),
-            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
-              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
-          } else {
-            this.tychei = impl;
-          }
-        })(
-          this,
-          true && module, // present in node.js
-          __webpack_require__(16) // present with an AMD loader
-        );
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(28)(module)));
-
-      /***/
-    },
-    /* 74 */
-    /***/ function (module, exports, __webpack_require__) {
-      var __WEBPACK_AMD_DEFINE_RESULT__; /*
-Copyright 2014 David Bau.
-
-Permission is hereby granted, free of charge, to any person obtaining
-a copy of this software and associated documentation files (the
-"Software"), to deal in the Software without restriction, including
-without limitation the rights to use, copy, modify, merge, publish,
-distribute, sublicense, and/or sell copies of the Software, and to
-permit persons to whom the Software is furnished to do so, subject to
-the following conditions:
-
-The above copyright notice and this permission notice shall be
-included in all copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
-EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
-MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
-IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
-TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
-SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
-
-*/
-
-      (function (pool, math) {
-        //
-        // The following constants are related to IEEE 754 limits.
-        //
-        var global = this,
-          width = 256, // each RC4 output is 0 <= x < 256
-          chunks = 6, // at least six RC4 outputs for each double
-          digits = 52, // there are 52 significant digits in a double
-          rngname = "random", // rngname: name for Math.random and Math.seedrandom
-          startdenom = math.pow(width, chunks),
-          significance = math.pow(2, digits),
-          overflow = significance * 2,
-          mask = width - 1,
-          nodecrypto; // node.js crypto module, initialized at the bottom.
-
-        //
-        // seedrandom()
-        // This is the seedrandom function described above.
-        //
-        function seedrandom(seed, options, callback) {
-          var key = [];
-          options = options == true ? { entropy: true } : options || {};
-
-          // Flatten the seed string or build one from local entropy if needed.
-          var shortseed = mixkey(
-            flatten(options.entropy ? [seed, tostring(pool)] : seed == null ? autoseed() : seed, 3),
-            key
-          );
-
-          // Use the seed to initialize an ARC4 generator.
-          var arc4 = new ARC4(key);
-
-          // This function returns a random double in [0, 1) that contains
-          // randomness in every bit of the mantissa of the IEEE 754 value.
-          var prng = function () {
-            var n = arc4.g(chunks), // Start with a numerator n < 2 ^ 48
-              d = startdenom, //   and denominator d = 2 ^ 48.
-              x = 0; //   and no 'extra last byte'.
-            while (n < significance) {
-              // Fill up all significant digits by
-              n = (n + x) * width; //   shifting numerator and
-              d *= width; //   denominator and generating a
-              x = arc4.g(1); //   new least-significant-byte.
-            }
-            while (n >= overflow) {
-              // To avoid rounding up, before adding
-              n /= 2; //   last byte, shift everything
-              d /= 2; //   right using integer math until
-              x >>>= 1; //   we have exactly the desired bits.
-            }
-            return (n + x) / d; // Form the number within [0, 1).
-          };
-
-          prng.int32 = function () {
-            return arc4.g(4) | 0;
-          };
-          prng.quick = function () {
-            return arc4.g(4) / 0x100000000;
-          };
-          prng.double = prng;
-
-          // Mix the randomness into accumulated entropy.
-          mixkey(tostring(arc4.S), pool);
-
-          // Calling convention: what to return as a function of prng, seed, is_math.
-          return (
-            options.pass ||
-            callback ||
-            function (prng, seed, is_math_call, state) {
-              if (state) {
-                // Load the arc4 state from the given state if it has an S array.
-                if (state.S) {
-                  copy(state, arc4);
-                }
-                // Only provide the .state method if requested via options.state.
-                prng.state = function () {
-                  return copy(arc4, {});
-                };
-              }
-
-              // If called as a method of Math (Math.seedrandom()), mutate
-              // Math.random because that is how seedrandom.js has worked since v1.0.
-              if (is_math_call) {
-                math[rngname] = prng;
-                return seed;
-              }
-
-              // Otherwise, it is a newer calling convention, so return the
-              // prng directly.
-              else return prng;
-            }
-          )(prng, shortseed, "global" in options ? options.global : this == math, options.state);
-        }
-        math["seed" + rngname] = seedrandom;
-
-        //
-        // ARC4
-        //
-        // An ARC4 implementation.  The constructor takes a key in the form of
-        // an array of at most (width) integers that should be 0 <= x < (width).
-        //
-        // The g(count) method returns a pseudorandom integer that concatenates
-        // the next (count) outputs from ARC4.  Its return value is a number x
-        // that is in the range 0 <= x < (width ^ count).
-        //
-        function ARC4(key) {
-          var t,
-            keylen = key.length,
-            me = this,
-            i = 0,
-            j = (me.i = me.j = 0),
-            s = (me.S = []);
-
-          // The empty key [] is treated as [0].
-          if (!keylen) {
-            key = [keylen++];
-          }
-
-          // Set up S using the standard key scheduling algorithm.
-          while (i < width) {
-            s[i] = i++;
-          }
-          for (i = 0; i < width; i++) {
-            s[i] = s[(j = mask & (j + key[i % keylen] + (t = s[i])))];
-            s[j] = t;
-          }
-
-          // The "g" method returns the next (count) outputs as one number.
-          (me.g = function (count) {
-            // Using instance members instead of closure state nearly doubles speed.
-            var t,
-              r = 0,
-              i = me.i,
-              j = me.j,
-              s = me.S;
-            while (count--) {
-              t = s[(i = mask & (i + 1))];
-              r = r * width + s[mask & ((s[i] = s[(j = mask & (j + t))]) + (s[j] = t))];
-            }
-            me.i = i;
-            me.j = j;
-            return r;
-            // For robust unpredictability, the function call below automatically
-            // discards an initial batch of values.  This is called RC4-drop[256].
-            // See http://google.com/search?q=rsa+fluhrer+response&btnI
-          })(width);
-        }
-
-        //
-        // copy()
-        // Copies internal state of ARC4 to or from a plain object.
-        //
-        function copy(f, t) {
-          t.i = f.i;
-          t.j = f.j;
-          t.S = f.S.slice();
-          return t;
-        }
-
-        //
-        // flatten()
-        // Converts an object tree to nested arrays of strings.
-        //
-        function flatten(obj, depth) {
-          var result = [],
-            typ = typeof obj,
-            prop;
-          if (depth && typ == "object") {
-            for (prop in obj) {
-              try {
-                result.push(flatten(obj[prop], depth - 1));
-              } catch (e) {}
-            }
-          }
-          return result.length ? result : typ == "string" ? obj : obj + "\0";
-        }
-
-        //
-        // mixkey()
-        // Mixes a string seed into a key that is an array of integers, and
-        // returns a shortened string seed that is equivalent to the result key.
-        //
-        function mixkey(seed, key) {
-          var stringseed = seed + "",
-            smear,
-            j = 0;
-          while (j < stringseed.length) {
-            key[mask & j] = mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));
-          }
-          return tostring(key);
-        }
-
-        //
-        // autoseed()
-        // Returns an object for autoseeding, using window.crypto and Node crypto
-        // module if available.
-        //
-        function autoseed() {
-          try {
-            var out;
-            if (nodecrypto && (out = nodecrypto.randomBytes)) {
-              // The use of 'out' to remember randomBytes makes tight minified code.
-              out = out(width);
-            } else {
-              out = new Uint8Array(width);
-              (global.crypto || global.msCrypto).getRandomValues(out);
-            }
-            return tostring(out);
-          } catch (e) {
-            var browser = global.navigator,
-              plugins = browser && browser.plugins;
-            return [+new Date(), global, plugins, global.screen, tostring(pool)];
-          }
-        }
-
-        //
-        // tostring()
-        // Converts an array of charcodes to a string
-        //
-        function tostring(a) {
-          return String.fromCharCode.apply(0, a);
-        }
-
-        //
-        // When seedrandom.js is loaded, we immediately mix a few bits
-        // from the built-in RNG into the entropy pool.  Because we do
-        // not want to interfere with deterministic PRNG state later,
-        // seedrandom will not call math.random on its own again after
-        // initialization.
-        //
-        mixkey(math.random(), pool);
-
-        //
-        // Nodejs and AMD support: export the implementation as a module using
-        // either convention.
-        //
-        if (true && module.exports) {
-          module.exports = seedrandom;
-          // When in node.js, try using crypto package for autoseeding.
-          try {
-            nodecrypto = __webpack_require__(75);
-          } catch (ex) {}
-        } else if (true) {
-          !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
-            return seedrandom;
-          }.call(exports, __webpack_require__, exports, module)),
-          __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
-            (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
-        }
-
-        // End anonymous scope, and pass initial values.
-      })(
-        [], // pool: entropy pool starts empty
-        Math // math: package containing random, pow, and seedrandom
-      );
-
-      /***/
-    },
-    /* 75 */
-    /***/ function (module, exports) {
-      /* (ignored) */
-      /***/
-    },
-    /* 76 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (global) {
-        var scope =
-          (typeof global !== "undefined" && global) ||
-          (typeof self !== "undefined" && self) ||
-          window;
-        var apply = Function.prototype.apply;
-
-        // DOM APIs, for completeness
-
-        exports.setTimeout = function () {
-          return new Timeout(apply.call(setTimeout, scope, arguments), clearTimeout);
-        };
-        exports.setInterval = function () {
-          return new Timeout(apply.call(setInterval, scope, arguments), clearInterval);
-        };
-        exports.clearTimeout = exports.clearInterval = function (timeout) {
-          if (timeout) {
-            timeout.close();
-          }
-        };
-
-        function Timeout(id, clearFn) {
-          this._id = id;
-          this._clearFn = clearFn;
-        }
-        Timeout.prototype.unref = Timeout.prototype.ref = function () {};
-        Timeout.prototype.close = function () {
-          this._clearFn.call(scope, this._id);
-        };
-
-        // Does not start the time, just sets up the members needed.
-        exports.enroll = function (item, msecs) {
-          clearTimeout(item._idleTimeoutId);
-          item._idleTimeout = msecs;
-        };
-
-        exports.unenroll = function (item) {
-          clearTimeout(item._idleTimeoutId);
-          item._idleTimeout = -1;
-        };
-
-        exports._unrefActive = exports.active = function (item) {
-          clearTimeout(item._idleTimeoutId);
-
-          var msecs = item._idleTimeout;
-          if (msecs >= 0) {
-            item._idleTimeoutId = setTimeout(function onTimeout() {
-              if (item._onTimeout) item._onTimeout();
-            }, msecs);
-          }
-        };
-
-        // setimmediate attaches itself to the global object
-        __webpack_require__(77);
-        // On some exotic environments, it's not clear which object `setimmediate` was
-        // able to install onto.  Search each possibility in the same order as the
-        // `setimmediate` library.
-        exports.setImmediate =
-          (typeof self !== "undefined" && self.setImmediate) ||
-          (typeof global !== "undefined" && global.setImmediate) ||
-          (this && this.setImmediate);
-        exports.clearImmediate =
-          (typeof self !== "undefined" && self.clearImmediate) ||
-          (typeof global !== "undefined" && global.clearImmediate) ||
-          (this && this.clearImmediate);
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(27)));
-
-      /***/
-    },
-    /* 77 */
-    /***/ function (module, exports, __webpack_require__) {
-      /* WEBPACK VAR INJECTION */ (function (global, process) {
-        (function (global, undefined) {
-          "use strict";
-
-          if (global.setImmediate) {
-            return;
-          }
-
-          var nextHandle = 1; // Spec says greater than zero
-          var tasksByHandle = {};
-          var currentlyRunningATask = false;
-          var doc = global.document;
-          var registerImmediate;
-
-          function setImmediate(callback) {
-            // Callback can either be a function or a string
-            if (typeof callback !== "function") {
-              callback = new Function("" + callback);
-            }
-            // Copy function arguments
-            var args = new Array(arguments.length - 1);
-            for (var i = 0; i < args.length; i++) {
-              args[i] = arguments[i + 1];
-            }
-            // Store and register the task
-            var task = { callback: callback, args: args };
-            tasksByHandle[nextHandle] = task;
-            registerImmediate(nextHandle);
-            return nextHandle++;
-          }
-
-          function clearImmediate(handle) {
-            delete tasksByHandle[handle];
-          }
-
-          function run(task) {
-            var callback = task.callback;
-            var args = task.args;
-            switch (args.length) {
-              case 0:
-                callback();
-                break;
-              case 1:
-                callback(args[0]);
-                break;
-              case 2:
-                callback(args[0], args[1]);
-                break;
-              case 3:
-                callback(args[0], args[1], args[2]);
-                break;
-              default:
-                callback.apply(undefined, args);
-                break;
-            }
-          }
-
-          function runIfPresent(handle) {
-            // From the spec: "Wait until any invocations of this algorithm started before this one have completed."
-            // So if we're currently running a task, we'll need to delay this invocation.
-            if (currentlyRunningATask) {
-              // Delay by doing a setTimeout. setImmediate was tried instead, but in Firefox 7 it generated a
-              // "too much recursion" error.
-              setTimeout(runIfPresent, 0, handle);
-            } else {
-              var task = tasksByHandle[handle];
-              if (task) {
-                currentlyRunningATask = true;
-                try {
-                  run(task);
-                } finally {
-                  clearImmediate(handle);
-                  currentlyRunningATask = false;
-                }
-              }
-            }
-          }
-
-          function installNextTickImplementation() {
-            registerImmediate = function (handle) {
-              process.nextTick(function () {
-                runIfPresent(handle);
-              });
-            };
-          }
-
-          function canUsePostMessage() {
-            // The test against `importScripts` prevents this implementation from being installed inside a web worker,
-            // where `global.postMessage` means something completely different and can't be used for this purpose.
-            if (global.postMessage && !global.importScripts) {
-              var postMessageIsAsynchronous = true;
-              var oldOnMessage = global.onmessage;
-              global.onmessage = function () {
-                postMessageIsAsynchronous = false;
-              };
-              global.postMessage("", "*");
-              global.onmessage = oldOnMessage;
-              return postMessageIsAsynchronous;
-            }
-          }
-
-          function installPostMessageImplementation() {
-            // Installs an event handler on `global` for the `message` event: see
-            // * https://developer.mozilla.org/en/DOM/window.postMessage
-            // * http://www.whatwg.org/specs/web-apps/current-work/multipage/comms.html#crossDocumentMessages
-
-            var messagePrefix = "setImmediate$" + Math.random() + "$";
-            var onGlobalMessage = function (event) {
-              if (
-                event.source === global &&
-                typeof event.data === "string" &&
-                event.data.indexOf(messagePrefix) === 0
-              ) {
-                runIfPresent(+event.data.slice(messagePrefix.length));
-              }
-            };
-
-            if (global.addEventListener) {
-              global.addEventListener("message", onGlobalMessage, false);
-            } else {
-              global.attachEvent("onmessage", onGlobalMessage);
-            }
-
-            registerImmediate = function (handle) {
-              global.postMessage(messagePrefix + handle, "*");
-            };
-          }
-
-          function installMessageChannelImplementation() {
-            var channel = new MessageChannel();
-            channel.port1.onmessage = function (event) {
-              var handle = event.data;
-              runIfPresent(handle);
-            };
-
-            registerImmediate = function (handle) {
-              channel.port2.postMessage(handle);
-            };
-          }
-
-          function installReadyStateChangeImplementation() {
-            var html = doc.documentElement;
-            registerImmediate = function (handle) {
-              // Create a <script> element; its readystatechange event will be fired asynchronously once it is inserted
-              // into the document. Do so, thus queuing up the task. Remember to clean up once it's been called.
-              var script = doc.createElement("script");
-              script.onreadystatechange = function () {
-                runIfPresent(handle);
-                script.onreadystatechange = null;
-                html.removeChild(script);
-                script = null;
-              };
-              html.appendChild(script);
-            };
-          }
-
-          function installSetTimeoutImplementation() {
-            registerImmediate = function (handle) {
-              setTimeout(runIfPresent, 0, handle);
-            };
-          }
-
-          // If supported, we should attach to the prototype of global, since that is where setTimeout et al. live.
-          var attachTo = Object.getPrototypeOf && Object.getPrototypeOf(global);
-          attachTo = attachTo && attachTo.setTimeout ? attachTo : global;
-
-          // Don't get fooled by e.g. browserify environments.
-          if ({}.toString.call(global.process) === "[object process]") {
-            // For Node.js before 0.9
-            installNextTickImplementation();
-          } else if (canUsePostMessage()) {
-            // For non-IE10 modern browsers
-            installPostMessageImplementation();
-          } else if (global.MessageChannel) {
-            // For web workers, where supported
-            installMessageChannelImplementation();
-          } else if (doc && "onreadystatechange" in doc.createElement("script")) {
-            // For IE 6–8
-            installReadyStateChangeImplementation();
-          } else {
-            // For older browsers
-            installSetTimeoutImplementation();
-          }
-
-          attachTo.setImmediate = setImmediate;
-          attachTo.clearImmediate = clearImmediate;
-        })(typeof self === "undefined" ? (typeof global === "undefined" ? this : global) : self);
-
-        /* WEBPACK VAR INJECTION */
-      }.call(this, __webpack_require__(27), __webpack_require__(35)));
-
-      /***/
-    },
-    /* 78 */
-    /***/ function (module, exports) {
-      /* (ignored) */
-      /***/
-    },
-    /* 79 */
-    /***/ function (module, exports) {
-      /* (ignored) */
-      /***/
-    },
-    /* 80 */
-    /***/ function (module, exports, __webpack_require__) {
-      var __WEBPACK_AMD_DEFINE_FACTORY__,
-        __WEBPACK_AMD_DEFINE_ARRAY__,
-        __WEBPACK_AMD_DEFINE_RESULT__;
-      (function (global, factory) {
-        if (true) {
-          !((__WEBPACK_AMD_DEFINE_ARRAY__ = [module]),
-          (__WEBPACK_AMD_DEFINE_FACTORY__ = factory),
-          (__WEBPACK_AMD_DEFINE_RESULT__ =
-            typeof __WEBPACK_AMD_DEFINE_FACTORY__ === "function"
-              ? __WEBPACK_AMD_DEFINE_FACTORY__.apply(exports, __WEBPACK_AMD_DEFINE_ARRAY__)
-              : __WEBPACK_AMD_DEFINE_FACTORY__),
-          __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
-            (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
-        } else {
-          var mod;
-        }
-      })(this, function (module) {
-        "use strict";
-
-        function _defineProperty(obj, key, value) {
-          if (key in obj) {
-            Object.defineProperty(obj, key, {
-              value: value,
-              enumerable: true,
-              configurable: true,
-              writable: true,
-            });
-          } else {
-            obj[key] = value;
-          }
-
-          return obj;
-        }
-
-        var _extends =
-          Object.assign ||
-          function (target) {
-            for (var i = 1; i < arguments.length; i++) {
-              var source = arguments[i];
-
-              for (var key in source) {
-                if (Object.prototype.hasOwnProperty.call(source, key)) {
-                  target[key] = source[key];
-                }
-              }
-            }
-
-            return target;
-          };
-
-        function _toConsumableArray(arr) {
-          if (Array.isArray(arr)) {
-            for (var i = 0, arr2 = Array(arr.length); i < arr.length; i++) {
-              arr2[i] = arr[i];
-            }
-
-            return arr2;
-          } else {
-            return Array.from(arr);
-          }
-        }
-
-        var DEFAULT_OPTIONS = { order: 2, precision: 2, period: null };
-
-        /**
-         * Determine the coefficient of determination (r^2) of a fit from the observations
-         * and predictions.
-         *
-         * @param {Array<Array<number>>} data - Pairs of observed x-y values
-         * @param {Array<Array<number>>} results - Pairs of observed predicted x-y values
-         *
-         * @return {number} - The r^2 value, or NaN if one cannot be calculated.
-         */
-        function determinationCoefficient(data, results) {
-          var predictions = [];
-          var observations = [];
-
-          data.forEach(function (d, i) {
-            if (d[1] !== null) {
-              observations.push(d);
-              predictions.push(results[i]);
-            }
-          });
-
-          var sum = observations.reduce(function (a, observation) {
-            return a + observation[1];
-          }, 0);
-          var mean = sum / observations.length;
-
-          var ssyy = observations.reduce(function (a, observation) {
-            var difference = observation[1] - mean;
-            return a + difference * difference;
-          }, 0);
-
-          var sse = observations.reduce(function (accum, observation, index) {
-            var prediction = predictions[index];
-            var residual = observation[1] - prediction[1];
-            return accum + residual * residual;
-          }, 0);
-
-          return 1 - sse / ssyy;
-        }
-
-        /**
-         * Determine the solution of a system of linear equations A * x = b using
-         * Gaussian elimination.
-         *
-         * @param {Array<Array<number>>} input - A 2-d matrix of data in row-major form [ A | b ]
-         * @param {number} order - How many degrees to solve for
-         *
-         * @return {Array<number>} - Vector of normalized solution coefficients matrix (x)
-         */
-        function gaussianElimination(input, order) {
-          var matrix = input;
-          var n = input.length - 1;
-          var coefficients = [order];
-
-          for (var i = 0; i < n; i++) {
-            var maxrow = i;
-            for (var j = i + 1; j < n; j++) {
-              if (Math.abs(matrix[i][j]) > Math.abs(matrix[i][maxrow])) {
-                maxrow = j;
-              }
-            }
-
-            for (var k = i; k < n + 1; k++) {
-              var tmp = matrix[k][i];
-              matrix[k][i] = matrix[k][maxrow];
-              matrix[k][maxrow] = tmp;
-            }
-
-            for (var _j = i + 1; _j < n; _j++) {
-              for (var _k = n; _k >= i; _k--) {
-                matrix[_k][_j] -= (matrix[_k][i] * matrix[i][_j]) / matrix[i][i];
-              }
-            }
-          }
-
-          for (var _j2 = n - 1; _j2 >= 0; _j2--) {
-            var total = 0;
-            for (var _k2 = _j2 + 1; _k2 < n; _k2++) {
-              total += matrix[_k2][_j2] * coefficients[_k2];
-            }
-
-            coefficients[_j2] = (matrix[n][_j2] - total) / matrix[_j2][_j2];
-          }
-
-          return coefficients;
-        }
-
-        /**
-         * Round a number to a precision, specificed in number of decimal places
-         *
-         * @param {number} number - The number to round
-         * @param {number} precision - The number of decimal places to round to:
-         *                             > 0 means decimals, < 0 means powers of 10
-         *
-         *
-         * @return {numbr} - The number, rounded
-         */
-        function round(number, precision) {
-          var factor = Math.pow(10, precision);
-          return Math.round(number * factor) / factor;
-        }
-
-        /**
-         * The set of all fitting methods
-         *
-         * @namespace
-         */
-        var methods = {
-          linear: function linear(data, options) {
-            var sum = [0, 0, 0, 0, 0];
-            var len = 0;
-
-            for (var n = 0; n < data.length; n++) {
-              if (data[n][1] !== null) {
-                len++;
-                sum[0] += data[n][0];
-                sum[1] += data[n][1];
-                sum[2] += data[n][0] * data[n][0];
-                sum[3] += data[n][0] * data[n][1];
-                sum[4] += data[n][1] * data[n][1];
-              }
-            }
-
-            var run = len * sum[2] - sum[0] * sum[0];
-            var rise = len * sum[3] - sum[0] * sum[1];
-            var gradient = run === 0 ? 0 : round(rise / run, options.precision);
-            var intercept = round(sum[1] / len - (gradient * sum[0]) / len, options.precision);
-
-            var predict = function predict(x) {
-              return [
-                round(x, options.precision),
-                round(gradient * x + intercept, options.precision),
-              ];
-            };
-
-            var points = data.map(function (point) {
-              return predict(point[0]);
-            });
-
-            return {
-              points: points,
-              predict: predict,
-              equation: [gradient, intercept],
-              r2: round(determinationCoefficient(data, points), options.precision),
-              string:
-                intercept === 0 ? "y = " + gradient + "x" : "y = " + gradient + "x + " + intercept,
-            };
-          },
-          exponential: function exponential(data, options) {
-            var sum = [0, 0, 0, 0, 0, 0];
-
-            for (var n = 0; n < data.length; n++) {
-              if (data[n][1] !== null) {
-                sum[0] += data[n][0];
-                sum[1] += data[n][1];
-                sum[2] += data[n][0] * data[n][0] * data[n][1];
-                sum[3] += data[n][1] * Math.log(data[n][1]);
-                sum[4] += data[n][0] * data[n][1] * Math.log(data[n][1]);
-                sum[5] += data[n][0] * data[n][1];
-              }
-            }
-
-            var denominator = sum[1] * sum[2] - sum[5] * sum[5];
-            var a = Math.exp((sum[2] * sum[3] - sum[5] * sum[4]) / denominator);
-            var b = (sum[1] * sum[4] - sum[5] * sum[3]) / denominator;
-            var coeffA = round(a, options.precision);
-            var coeffB = round(b, options.precision);
-            var predict = function predict(x) {
-              return [
-                round(x, options.precision),
-                round(coeffA * Math.exp(coeffB * x), options.precision),
-              ];
-            };
-
-            var points = data.map(function (point) {
-              return predict(point[0]);
-            });
-
-            return {
-              points: points,
-              predict: predict,
-              equation: [coeffA, coeffB],
-              string: "y = " + coeffA + "e^(" + coeffB + "x)",
-              r2: round(determinationCoefficient(data, points), options.precision),
-            };
-          },
-          logarithmic: function logarithmic(data, options) {
-            var sum = [0, 0, 0, 0];
-            var len = data.length;
-
-            for (var n = 0; n < len; n++) {
-              if (data[n][1] !== null) {
-                sum[0] += Math.log(data[n][0]);
-                sum[1] += data[n][1] * Math.log(data[n][0]);
-                sum[2] += data[n][1];
-                sum[3] += Math.pow(Math.log(data[n][0]), 2);
-              }
-            }
-
-            var a = (len * sum[1] - sum[2] * sum[0]) / (len * sum[3] - sum[0] * sum[0]);
-            var coeffB = round(a, options.precision);
-            var coeffA = round((sum[2] - coeffB * sum[0]) / len, options.precision);
-
-            var predict = function predict(x) {
-              return [
-                round(x, options.precision),
-                round(round(coeffA + coeffB * Math.log(x), options.precision), options.precision),
-              ];
-            };
-
-            var points = data.map(function (point) {
-              return predict(point[0]);
-            });
-
-            return {
-              points: points,
-              predict: predict,
-              equation: [coeffA, coeffB],
-              string: "y = " + coeffA + " + " + coeffB + " ln(x)",
-              r2: round(determinationCoefficient(data, points), options.precision),
-            };
-          },
-          power: function power(data, options) {
-            var sum = [0, 0, 0, 0, 0];
-            var len = data.length;
-
-            for (var n = 0; n < len; n++) {
-              if (data[n][1] !== null) {
-                sum[0] += Math.log(data[n][0]);
-                sum[1] += Math.log(data[n][1]) * Math.log(data[n][0]);
-                sum[2] += Math.log(data[n][1]);
-                sum[3] += Math.pow(Math.log(data[n][0]), 2);
-              }
-            }
-
-            var b = (len * sum[1] - sum[0] * sum[2]) / (len * sum[3] - Math.pow(sum[0], 2));
-            var a = (sum[2] - b * sum[0]) / len;
-            var coeffA = round(Math.exp(a), options.precision);
-            var coeffB = round(b, options.precision);
-
-            var predict = function predict(x) {
-              return [
-                round(x, options.precision),
-                round(round(coeffA * Math.pow(x, coeffB), options.precision), options.precision),
-              ];
-            };
-
-            var points = data.map(function (point) {
-              return predict(point[0]);
-            });
-
-            return {
-              points: points,
-              predict: predict,
-              equation: [coeffA, coeffB],
-              string: "y = " + coeffA + "x^" + coeffB,
-              r2: round(determinationCoefficient(data, points), options.precision),
-            };
-          },
-          polynomial: function polynomial(data, options) {
-            var lhs = [];
-            var rhs = [];
-            var a = 0;
-            var b = 0;
-            var len = data.length;
-            var k = options.order + 1;
-
-            for (var i = 0; i < k; i++) {
-              for (var l = 0; l < len; l++) {
-                if (data[l][1] !== null) {
-                  a += Math.pow(data[l][0], i) * data[l][1];
-                }
-              }
-
-              lhs.push(a);
-              a = 0;
-
-              var c = [];
-              for (var j = 0; j < k; j++) {
-                for (var _l = 0; _l < len; _l++) {
-                  if (data[_l][1] !== null) {
-                    b += Math.pow(data[_l][0], i + j);
-                  }
-                }
-                c.push(b);
-                b = 0;
-              }
-              rhs.push(c);
-            }
-            rhs.push(lhs);
-
-            var coefficients = gaussianElimination(rhs, k).map(function (v) {
-              return round(v, options.precision);
-            });
-
-            var predict = function predict(x) {
-              return [
-                round(x, options.precision),
-                round(
-                  coefficients.reduce(function (sum, coeff, power) {
-                    return sum + coeff * Math.pow(x, power);
-                  }, 0),
-                  options.precision
-                ),
-              ];
-            };
-
-            var points = data.map(function (point) {
-              return predict(point[0]);
-            });
-
-            var string = "y = ";
-            for (var _i = coefficients.length - 1; _i >= 0; _i--) {
-              if (_i > 1) {
-                string += coefficients[_i] + "x^" + _i + " + ";
-              } else if (_i === 1) {
-                string += coefficients[_i] + "x + ";
-              } else {
-                string += coefficients[_i];
-              }
-            }
-
-            return {
-              string: string,
-              points: points,
-              predict: predict,
-              equation: [].concat(_toConsumableArray(coefficients)).reverse(),
-              r2: round(determinationCoefficient(data, points), options.precision),
-            };
-          },
-        };
-
-        function createWrapper() {
-          var reduce = function reduce(accumulator, name) {
-            return _extends(
-              {
-                _round: round,
-              },
-              accumulator,
-              _defineProperty({}, name, function (data, supplied) {
-                return methods[name](data, _extends({}, DEFAULT_OPTIONS, supplied));
-              })
-            );
-          };
-
-          return Object.keys(methods).reduce(reduce, {});
-        }
-
-        module.exports = createWrapper();
-      });
-
-      /***/
-    },
-    /* 81 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      __webpack_require__.r(__webpack_exports__);
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "load",
-        function () {
-          return load;
-        }
-      );
-      /* harmony export (binding) */ __webpack_require__.d(
-        __webpack_exports__,
-        "BlazeFaceModel",
-        function () {
-          return BlazeFaceModel;
-        }
-      );
-      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
-        __webpack_require__(0);
-      /* harmony import */ var _tensorflow_tfjs_converter__WEBPACK_IMPORTED_MODULE_1__ =
-        __webpack_require__(38);
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const disposeBox = (t) => {
-          t.startEndTensor.dispose(), t.startPoint.dispose(), t.endPoint.dispose();
-        },
-        createBox = (t) => ({
-          startEndTensor: t,
-          startPoint: Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
-            t,
-            [0, 0],
-            [-1, 2]
-          ),
-          endPoint: Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
-            t,
-            [0, 2],
-            [-1, 2]
-          ),
-        }),
-        scaleBox = (t, o) => {
-          const s = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(
-              t.startPoint,
-              o
-            ),
-            e = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(t.endPoint, o),
-            i = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["concat2d"])([s, e], 1);
-          return createBox(i);
-        },
-        ANCHORS_CONFIG = { strides: [8, 16], anchors: [2, 6] },
-        NUM_LANDMARKS = 6;
-      function generateAnchors(t, o, s) {
-        const e = [];
-        for (let i = 0; i < s.strides.length; i++) {
-          const n = s.strides[i],
-            a = Math.floor((o + n - 1) / n),
-            r = Math.floor((t + n - 1) / n),
-            c = s.anchors[i];
-          for (let t = 0; t < a; t++) {
-            const o = n * (t + 0.5);
-            for (let t = 0; t < r; t++) {
-              const s = n * (t + 0.5);
-              for (let t = 0; t < c; t++) e.push([s, o]);
-            }
-          }
-        }
-        return e;
-      }
-      function decodeBounds(t, o, s) {
-        const e = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
-            t,
-            [0, 1],
-            [-1, 2]
-          ),
-          i = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["add"])(e, o),
-          n = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
-            t,
-            [0, 3],
-            [-1, 2]
-          ),
-          a = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["div"])(n, s),
-          r = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["div"])(i, s),
-          c = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["div"])(a, 2),
-          l = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(r, c),
-          d = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["add"])(r, c),
-          h = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(l, s),
-          p = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(d, s);
-        return Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["concat2d"])([h, p], 1);
-      }
-      function getInputTensorDimensions(t) {
-        return t instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]
-          ? [t.shape[0], t.shape[1]]
-          : [t.height, t.width];
-      }
-      function flipFaceHorizontal(t, o) {
-        let s, e, i;
-        if (
-          t.topLeft instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"] &&
-          t.bottomRight instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]
-        ) {
-          const [n, a] = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(() => [
-            Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["concat"])([
-              Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(
-                o - 1,
-                t.topLeft.slice(0, 1)
-              ),
-              t.topLeft.slice(1, 1),
-            ]),
-            Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["concat"])([
-              Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(
-                o - 1,
-                t.bottomRight.slice(0, 1)
-              ),
-              t.bottomRight.slice(1, 1),
-            ]),
-          ]);
-          (s = n),
-            (e = a),
-            null != t.landmarks &&
-              (i = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(() => {
-                const s = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(
-                    Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor1d"])([
-                      o - 1,
-                      0,
-                    ]),
-                    t.landmarks
-                  ),
-                  e = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor1d"])([
-                    1, -1,
-                  ]);
-                return Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(s, e);
-              }));
-        } else {
-          const [n, a] = t.topLeft,
-            [r, c] = t.bottomRight;
-          (s = [o - 1 - n, a]),
-            (e = [o - 1 - r, c]),
-            null != t.landmarks && (i = t.landmarks.map((t) => [o - 1 - t[0], t[1]]));
-        }
-        const n = { topLeft: s, bottomRight: e };
-        return (
-          null != i && (n.landmarks = i),
-          null != t.probability &&
-            (n.probability =
-              t.probability instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]
-                ? t.probability.clone()
-                : t.probability),
-          n
-        );
-      }
-      function scaleBoxFromPrediction(t, o) {
-        return Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(() => {
-          let s;
-          return (s = t.hasOwnProperty("box") ? t.box : t), scaleBox(s, o).startEndTensor.squeeze();
-        });
-      }
-      class BlazeFaceModel {
-        constructor(t, o, s, e, i, n) {
-          (this.blazeFaceModel = t),
-            (this.width = o),
-            (this.height = s),
-            (this.maxFaces = e),
-            (this.anchorsData = generateAnchors(o, s, ANCHORS_CONFIG)),
-            (this.anchors = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor2d"])(
-              this.anchorsData
-            )),
-            (this.inputSizeData = [o, s]),
-            (this.inputSize = Object(
-              _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor1d"]
-            )([o, s])),
-            (this.iouThreshold = i),
-            (this.scoreThreshold = n);
-        }
-        async getBoundingBoxes(t, o, s = !0) {
-          const [e, i, n] = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(
-              () => {
-                const o = t.resizeBilinear([this.width, this.height]),
-                  s = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(
-                    Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(
-                      o.div(255),
-                      0.5
-                    ),
-                    2
-                  ),
-                  e = this.blazeFaceModel.predict(s).squeeze(),
-                  i = decodeBounds(e, this.anchors, this.inputSize),
-                  n = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
-                    e,
-                    [0, 0],
-                    [-1, 1]
-                  );
-                return [
-                  e,
-                  i,
-                  Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sigmoid"])(
-                    n
-                  ).squeeze(),
-                ];
-              }
-            ),
-            a = console.warn;
-          console.warn = () => {};
-          const r = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["image"].nonMaxSuppression(
-            i,
-            n,
-            this.maxFaces,
-            this.iouThreshold,
-            this.scoreThreshold
-          );
-          console.warn = a;
-          const c = await r.array();
-          r.dispose();
-          let l = c.map((t) =>
-            Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(i, [t, 0], [1, -1])
-          );
-          o ||
-            (l = await Promise.all(
-              l.map(async (t) => {
-                const o = await t.array();
-                return t.dispose(), o;
-              })
-            ));
-          const d = t.shape[1],
-            h = t.shape[2];
-          let p;
-          p = o
-            ? Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["div"])(
-                [h, d],
-                this.inputSize
-              )
-            : [h / this.inputSizeData[0], d / this.inputSizeData[1]];
-          const u = [];
-          for (let t = 0; t < l.length; t++) {
-            const i = l[t],
-              a = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(() => {
-                const a = createBox(
-                  i instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]
-                    ? i
-                    : Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor2d"])(i)
-                );
-                if (!s) return a;
-                const r = c[t];
-                let l;
-                return (
-                  (l = o ? this.anchors.slice([r, 0], [1, 2]) : this.anchorsData[r]),
-                  {
-                    box: a,
-                    landmarks: Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
-                      e,
-                      [r, NUM_LANDMARKS - 1],
-                      [1, -1]
-                    )
-                      .squeeze()
-                      .reshape([NUM_LANDMARKS, -1]),
-                    probability: Object(
-                      _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"]
-                    )(n, [r], [1]),
-                    anchor: l,
-                  }
-                );
-              });
-            u.push(a);
-          }
-          return i.dispose(), n.dispose(), e.dispose(), { boxes: u, scaleFactor: p };
-        }
-        async estimateFaces(t, o = !1, s = !1, e = !0) {
-          const [, i] = getInputTensorDimensions(t),
-            n = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(
-              () => (
-                t instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"] ||
-                  (t = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["browser"].fromPixels(t)),
-                t.toFloat().expandDims(0)
-              )
-            ),
-            { boxes: a, scaleFactor: r } = await this.getBoundingBoxes(n, o, e);
-          return (
-            n.dispose(),
-            o
-              ? a.map((t) => {
-                  const o = scaleBoxFromPrediction(t, r);
-                  let n = { topLeft: o.slice([0], [2]), bottomRight: o.slice([2], [2]) };
-                  if (e) {
-                    const { landmarks: o, probability: s, anchor: e } = t,
-                      i = o.add(e).mul(r);
-                    (n.landmarks = i), (n.probability = s);
-                  }
-                  return s && (n = flipFaceHorizontal(n, i)), n;
-                })
-              : Promise.all(
-                  a.map(async (t) => {
-                    const o = scaleBoxFromPrediction(t, r);
-                    let n;
-                    if (e) {
-                      const [s, e, i] = await Promise.all(
-                          [t.landmarks, o, t.probability].map(async (t) => t.array())
-                        ),
-                        a = t.anchor,
-                        [c, l] = r,
-                        d = s.map((t) => [(t[0] + a[0]) * c, (t[1] + a[1]) * l]);
-                      (n = {
-                        topLeft: e.slice(0, 2),
-                        bottomRight: e.slice(2),
-                        landmarks: d,
-                        probability: i,
-                      }),
-                        disposeBox(t.box),
-                        t.landmarks.dispose(),
-                        t.probability.dispose();
-                    } else {
-                      const t = await o.array();
-                      n = { topLeft: t.slice(0, 2), bottomRight: t.slice(2) };
-                    }
-                    return o.dispose(), s && (n = flipFaceHorizontal(n, i)), n;
-                  })
-                )
-          );
-        }
-      }
-      const BLAZEFACE_MODEL_URL = "https://tfhub.dev/tensorflow/tfjs-model/blazeface/1/default/1";
-      async function load({
-        maxFaces: t = 10,
-        inputWidth: o = 128,
-        inputHeight: s = 128,
-        iouThreshold: e = 0.3,
-        scoreThreshold: i = 0.75,
-      } = {}) {
-        const n = await Object(
-          _tensorflow_tfjs_converter__WEBPACK_IMPORTED_MODULE_1__["loadGraphModel"]
-        )(BLAZEFACE_MODEL_URL, { fromTFHub: !0 });
-        return new BlazeFaceModel(n, o, s, t, e, i);
-      }
-
-      /***/
-    },
-    /* 82 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-
-      Object.defineProperty(exports, "__esModule", { value: true });
-      exports.MESH_ANNOTATIONS = {
-        silhouette: [
-          10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288, 397, 365, 379, 378, 400, 377,
-          152, 148, 176, 149, 150, 136, 172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,
-        ],
-        lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],
-        lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],
-        lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],
-        lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],
-        rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],
-        rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],
-        rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],
-        rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],
-        rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],
-        rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],
-        rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],
-        rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],
-        rightEyebrowLower: [35, 124, 46, 53, 52, 65],
-        leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],
-        leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],
-        leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],
-        leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],
-        leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],
-        leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],
-        leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],
-        leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],
-        leftEyebrowLower: [265, 353, 276, 283, 282, 295],
-        midwayBetweenEyes: [168],
-        noseTip: [1],
-        noseBottom: [2],
-        noseRightCorner: [98],
-        noseLeftCorner: [327],
-        rightCheek: [205],
-        leftCheek: [425],
-      };
-      //# sourceMappingURL=keypoints.js.map
-
-      /***/
-    },
-    /* 83 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-
-      Object.defineProperty(exports, "__esModule", { value: true });
-      const tf = __webpack_require__(0);
-      const box_1 = __webpack_require__(84);
-      const LANDMARKS_COUNT = 468;
-      const UPDATE_REGION_OF_INTEREST_IOU_THRESHOLD = 0.25;
-      class Pipeline {
-        constructor(
-          boundingBoxDetector,
-          meshDetector,
-          meshWidth,
-          meshHeight,
-          maxContinuousChecks,
-          maxFaces
-        ) {
-          this.regionsOfInterest = [];
-          this.runsWithoutFaceDetector = 0;
-          this.boundingBoxDetector = boundingBoxDetector;
-          this.meshDetector = meshDetector;
-          this.meshWidth = meshWidth;
-          this.meshHeight = meshHeight;
-          this.maxContinuousChecks = maxContinuousChecks;
-          this.maxFaces = maxFaces;
-        }
-        async predict(input) {
-          if (this.shouldUpdateRegionsOfInterest()) {
-            const returnTensors = true;
-            const annotateFace = false;
-            const { boxes, scaleFactor } = await this.boundingBoxDetector.getBoundingBoxes(
-              input,
-              returnTensors,
-              annotateFace
-            );
-            if (boxes.length === 0) {
-              scaleFactor.dispose();
-              this.clearAllRegionsOfInterest();
-              return null;
-            }
-            const scaledBoxes = boxes.map((prediction) =>
-              box_1.enlargeBox(box_1.scaleBoxCoordinates(prediction, scaleFactor))
-            );
-            boxes.forEach(box_1.disposeBox);
-            this.updateRegionsOfInterest(scaledBoxes);
-            this.runsWithoutFaceDetector = 0;
-          } else {
-            this.runsWithoutFaceDetector++;
-          }
-          return tf.tidy(() => {
-            return this.regionsOfInterest.map((box, i) => {
-              const face = box_1
-                .cutBoxFromImageAndResize(box, input, [this.meshHeight, this.meshWidth])
-                .div(255);
-              const [, flag, coords] = this.meshDetector.predict(face);
-              const coordsReshaped = tf.reshape(coords, [-1, 3]);
-              const normalizedBox = tf.div(box_1.getBoxSize(box), [
-                this.meshWidth,
-                this.meshHeight,
-              ]);
-              const scaledCoords = tf
-                .mul(coordsReshaped, normalizedBox.concat(tf.tensor2d([1], [1, 1]), 1))
-                .add(box.startPoint.concat(tf.tensor2d([0], [1, 1]), 1));
-              const landmarksBox = this.calculateLandmarksBoundingBox(scaledCoords);
-              const previousBox = this.regionsOfInterest[i];
-              box_1.disposeBox(previousBox);
-              this.regionsOfInterest[i] = landmarksBox;
-              const prediction = {
-                coords: coordsReshaped,
-                scaledCoords,
-                box: landmarksBox,
-                flag: flag.squeeze(),
-              };
-              return prediction;
-            });
-          });
-        }
-        updateRegionsOfInterest(boxes) {
-          for (let i = 0; i < boxes.length; i++) {
-            const box = boxes[i];
-            const previousBox = this.regionsOfInterest[i];
-            let iou = 0;
-            if (previousBox && previousBox.startPoint) {
-              const [boxStartX, boxStartY, boxEndX, boxEndY] = box.startEndTensor.arraySync()[0];
-              const [previousBoxStartX, previousBoxStartY, previousBoxEndX, previousBoxEndY] =
-                previousBox.startEndTensor.arraySync()[0];
-              const xStartMax = Math.max(boxStartX, previousBoxStartX);
-              const yStartMax = Math.max(boxStartY, previousBoxStartY);
-              const xEndMin = Math.min(boxEndX, previousBoxEndX);
-              const yEndMin = Math.min(boxEndY, previousBoxEndY);
-              const intersection = (xEndMin - xStartMax) * (yEndMin - yStartMax);
-              const boxArea = (boxEndX - boxStartX) * (boxEndY - boxStartY);
-              const previousBoxArea =
-                (previousBoxEndX - previousBoxStartX) * (previousBoxEndY - boxStartY);
-              iou = intersection / (boxArea + previousBoxArea - intersection);
-            }
-            if (iou > UPDATE_REGION_OF_INTEREST_IOU_THRESHOLD) {
-              box_1.disposeBox(box);
-            } else {
-              this.regionsOfInterest[i] = box;
-              box_1.disposeBox(previousBox);
-            }
-          }
-          for (let i = boxes.length; i < this.regionsOfInterest.length; i++) {
-            box_1.disposeBox(this.regionsOfInterest[i]);
-          }
-          this.regionsOfInterest = this.regionsOfInterest.slice(0, boxes.length);
-        }
-        clearRegionOfInterest(index) {
-          if (this.regionsOfInterest[index] != null) {
-            box_1.disposeBox(this.regionsOfInterest[index]);
-            this.regionsOfInterest = [
-              ...this.regionsOfInterest.slice(0, index),
-              ...this.regionsOfInterest.slice(index + 1),
-            ];
-          }
-        }
-        clearAllRegionsOfInterest() {
-          for (let i = 0; i < this.regionsOfInterest.length; i++) {
-            box_1.disposeBox(this.regionsOfInterest[i]);
-          }
-          this.regionsOfInterest = [];
-        }
-        shouldUpdateRegionsOfInterest() {
-          const roisCount = this.regionsOfInterest.length;
-          const noROIs = roisCount === 0;
-          if (this.maxFaces === 1 || noROIs) {
-            return noROIs;
-          }
-          return (
-            roisCount !== this.maxFaces && this.runsWithoutFaceDetector >= this.maxContinuousChecks
-          );
-        }
-        calculateLandmarksBoundingBox(landmarks) {
-          const xs = landmarks.slice([0, 0], [LANDMARKS_COUNT, 1]);
-          const ys = landmarks.slice([0, 1], [LANDMARKS_COUNT, 1]);
-          const boxMinMax = tf.stack([xs.min(), ys.min(), xs.max(), ys.max()]);
-          const box = box_1.createBox(boxMinMax.expandDims(0));
-          return box_1.enlargeBox(box);
-        }
-      }
-      exports.Pipeline = Pipeline;
-      //# sourceMappingURL=pipeline.js.map
-
-      /***/
-    },
-    /* 84 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-
-      Object.defineProperty(exports, "__esModule", { value: true });
-      const tf = __webpack_require__(0);
-      function disposeBox(box) {
-        if (box != null && box.startPoint != null) {
-          box.startEndTensor.dispose();
-          box.startPoint.dispose();
-          box.endPoint.dispose();
-        }
-      }
-      exports.disposeBox = disposeBox;
-      function createBox(startEndTensor, startPoint, endPoint) {
-        return {
-          startEndTensor,
-          startPoint: startPoint != null ? startPoint : tf.slice(startEndTensor, [0, 0], [-1, 2]),
-          endPoint: endPoint != null ? endPoint : tf.slice(startEndTensor, [0, 2], [-1, 2]),
-        };
-      }
-      exports.createBox = createBox;
-      function scaleBoxCoordinates(box, factor) {
-        const newStart = tf.mul(box.startPoint, factor);
-        const newEnd = tf.mul(box.endPoint, factor);
-        return createBox(tf.concat2d([newStart, newEnd], 1));
-      }
-      exports.scaleBoxCoordinates = scaleBoxCoordinates;
-      function getBoxSize(box) {
-        return tf.tidy(() => {
-          const diff = tf.sub(box.endPoint, box.startPoint);
-          return tf.abs(diff);
-        });
-      }
-      exports.getBoxSize = getBoxSize;
-      function getBoxCenter(box) {
-        return tf.tidy(() => {
-          const halfSize = tf.div(tf.sub(box.endPoint, box.startPoint), 2);
-          return tf.add(box.startPoint, halfSize);
-        });
-      }
-      exports.getBoxCenter = getBoxCenter;
-      function cutBoxFromImageAndResize(box, image, cropSize) {
-        const height = image.shape[1];
-        const width = image.shape[2];
-        const xyxy = box.startEndTensor;
-        return tf.tidy(() => {
-          const yxyx = tf.concat2d(
-            [
-              xyxy.slice([0, 1], [-1, 1]),
-              xyxy.slice([0, 0], [-1, 1]),
-              xyxy.slice([0, 3], [-1, 1]),
-              xyxy.slice([0, 2], [-1, 1]),
-            ],
-            0
-          );
-          const roundedCoords = tf.div(yxyx.transpose(), [height, width, height, width]);
-          return tf.image.cropAndResize(image, roundedCoords, [0], cropSize);
-        });
-      }
-      exports.cutBoxFromImageAndResize = cutBoxFromImageAndResize;
-      function enlargeBox(box, factor = 1.5) {
-        return tf.tidy(() => {
-          const center = getBoxCenter(box);
-          const size = getBoxSize(box);
-          const newSize = tf.mul(tf.div(size, 2), factor);
-          const newStart = tf.sub(center, newSize);
-          const newEnd = tf.add(center, newSize);
-          return createBox(tf.concat2d([newStart, newEnd], 1), newStart, newEnd);
-        });
-      }
-      exports.enlargeBox = enlargeBox;
-      //# sourceMappingURL=box.js.map
-
-      /***/
-    },
-    /* 85 */
-    /***/ function (module, exports, __webpack_require__) {
-      "use strict";
-
-      Object.defineProperty(exports, "__esModule", { value: true });
-      exports.UV_COORDS = [
-        [0.499976992607117, 0.652534008026123],
-        [0.500025987625122, 0.547487020492554],
-        [0.499974012374878, 0.602371990680695],
-        [0.482113003730774, 0.471979022026062],
-        [0.500150978565216, 0.527155995368958],
-        [0.499909996986389, 0.498252987861633],
-        [0.499523013830185, 0.40106201171875],
-        [0.289712011814117, 0.380764007568359],
-        [0.499954998493195, 0.312398016452789],
-        [0.499987006187439, 0.269918978214264],
-        [0.500023007392883, 0.107050001621246],
-        [0.500023007392883, 0.666234016418457],
-        [0.5000159740448, 0.679224014282227],
-        [0.500023007392883, 0.692348003387451],
-        [0.499976992607117, 0.695277988910675],
-        [0.499976992607117, 0.70593398809433],
-        [0.499976992607117, 0.719385027885437],
-        [0.499976992607117, 0.737019002437592],
-        [0.499967992305756, 0.781370997428894],
-        [0.499816000461578, 0.562981009483337],
-        [0.473773002624512, 0.573909997940063],
-        [0.104906998574734, 0.254140973091125],
-        [0.365929991006851, 0.409575998783112],
-        [0.338757991790771, 0.41302502155304],
-        [0.311120003461838, 0.409460008144379],
-        [0.274657994508743, 0.389131009578705],
-        [0.393361985683441, 0.403706014156342],
-        [0.345234006643295, 0.344011008739471],
-        [0.370094001293182, 0.346076011657715],
-        [0.319321990013123, 0.347265005111694],
-        [0.297903001308441, 0.353591024875641],
-        [0.24779200553894, 0.410809993743896],
-        [0.396889001131058, 0.842755019664764],
-        [0.280097991228104, 0.375599980354309],
-        [0.106310002505779, 0.399955987930298],
-        [0.2099249958992, 0.391353011131287],
-        [0.355807989835739, 0.534406006336212],
-        [0.471751004457474, 0.65040397644043],
-        [0.474155008792877, 0.680191993713379],
-        [0.439785003662109, 0.657229006290436],
-        [0.414617002010345, 0.66654098033905],
-        [0.450374007225037, 0.680860996246338],
-        [0.428770989179611, 0.682690978050232],
-        [0.374971002340317, 0.727805018424988],
-        [0.486716985702515, 0.547628998756409],
-        [0.485300987958908, 0.527395009994507],
-        [0.257764995098114, 0.314490020275116],
-        [0.401223003864288, 0.455172002315521],
-        [0.429818987846375, 0.548614978790283],
-        [0.421351999044418, 0.533740997314453],
-        [0.276895999908447, 0.532056987285614],
-        [0.483370006084442, 0.499586999416351],
-        [0.33721199631691, 0.282882988452911],
-        [0.296391993761063, 0.293242990970612],
-        [0.169294998049736, 0.193813979625702],
-        [0.447580009698868, 0.302609980106354],
-        [0.392390012741089, 0.353887975215912],
-        [0.354490011930466, 0.696784019470215],
-        [0.067304998636246, 0.730105042457581],
-        [0.442739009857178, 0.572826027870178],
-        [0.457098007202148, 0.584792017936707],
-        [0.381974011659622, 0.694710969924927],
-        [0.392388999462128, 0.694203019142151],
-        [0.277076005935669, 0.271932005882263],
-        [0.422551989555359, 0.563233017921448],
-        [0.385919004678726, 0.281364023685455],
-        [0.383103013038635, 0.255840003490448],
-        [0.331431001424789, 0.119714021682739],
-        [0.229923993349075, 0.232002973556519],
-        [0.364500999450684, 0.189113974571228],
-        [0.229622006416321, 0.299540996551514],
-        [0.173287004232407, 0.278747975826263],
-        [0.472878992557526, 0.666198015213013],
-        [0.446828007698059, 0.668527007102966],
-        [0.422762006521225, 0.673889994621277],
-        [0.445307999849319, 0.580065965652466],
-        [0.388103008270264, 0.693961024284363],
-        [0.403039008378983, 0.706539988517761],
-        [0.403629004955292, 0.693953037261963],
-        [0.460041999816895, 0.557139039039612],
-        [0.431158006191254, 0.692366003990173],
-        [0.452181994915009, 0.692366003990173],
-        [0.475387006998062, 0.692366003990173],
-        [0.465828001499176, 0.779190003871918],
-        [0.472328990697861, 0.736225962638855],
-        [0.473087012767792, 0.717857003211975],
-        [0.473122000694275, 0.704625964164734],
-        [0.473033010959625, 0.695277988910675],
-        [0.427942007780075, 0.695277988910675],
-        [0.426479011774063, 0.703539967536926],
-        [0.423162013292313, 0.711845993995667],
-        [0.4183090031147, 0.720062971115112],
-        [0.390094995498657, 0.639572978019714],
-        [0.013953999616206, 0.560034036636353],
-        [0.499913990497589, 0.58014702796936],
-        [0.413199990987778, 0.69539999961853],
-        [0.409626007080078, 0.701822996139526],
-        [0.468080013990402, 0.601534962654114],
-        [0.422728985548019, 0.585985004901886],
-        [0.463079988956451, 0.593783974647522],
-        [0.37211999297142, 0.47341400384903],
-        [0.334562003612518, 0.496073007583618],
-        [0.411671012639999, 0.546965003013611],
-        [0.242175996303558, 0.14767599105835],
-        [0.290776997804642, 0.201445996761322],
-        [0.327338010072708, 0.256527006626129],
-        [0.399509996175766, 0.748921036720276],
-        [0.441727995872498, 0.261676013469696],
-        [0.429764986038208, 0.187834024429321],
-        [0.412198007106781, 0.108901023864746],
-        [0.288955003023148, 0.398952007293701],
-        [0.218936994671822, 0.435410976409912],
-        [0.41278201341629, 0.398970007896423],
-        [0.257135003805161, 0.355440020561218],
-        [0.427684992551804, 0.437960982322693],
-        [0.448339998722076, 0.536936044692993],
-        [0.178560003638268, 0.45755398273468],
-        [0.247308000922203, 0.457193970680237],
-        [0.286267012357712, 0.467674970626831],
-        [0.332827985286713, 0.460712015628815],
-        [0.368755996227264, 0.447206974029541],
-        [0.398963987827301, 0.432654976844788],
-        [0.476410001516342, 0.405806005001068],
-        [0.189241006970406, 0.523923993110657],
-        [0.228962004184723, 0.348950982093811],
-        [0.490725994110107, 0.562400996685028],
-        [0.404670000076294, 0.485132992267609],
-        [0.019469000399113, 0.401564002037048],
-        [0.426243007183075, 0.420431017875671],
-        [0.396993011236191, 0.548797011375427],
-        [0.266469985246658, 0.376977026462555],
-        [0.439121007919312, 0.51895797252655],
-        [0.032313998788595, 0.644356966018677],
-        [0.419054001569748, 0.387154996395111],
-        [0.462783008813858, 0.505746960639954],
-        [0.238978996872902, 0.779744982719421],
-        [0.198220998048782, 0.831938028335571],
-        [0.107550002634525, 0.540755033493042],
-        [0.183610007166862, 0.740257024765015],
-        [0.134409993886948, 0.333683013916016],
-        [0.385764002799988, 0.883153975009918],
-        [0.490967005491257, 0.579378008842468],
-        [0.382384985685349, 0.508572995662689],
-        [0.174399003386497, 0.397670984268188],
-        [0.318785011768341, 0.39623498916626],
-        [0.343364000320435, 0.400596976280212],
-        [0.396100014448166, 0.710216999053955],
-        [0.187885001301765, 0.588537991046906],
-        [0.430987000465393, 0.944064974784851],
-        [0.318993002176285, 0.898285031318665],
-        [0.266247987747192, 0.869701027870178],
-        [0.500023007392883, 0.190576016902924],
-        [0.499976992607117, 0.954452991485596],
-        [0.366169989109039, 0.398822009563446],
-        [0.393207013607025, 0.39553701877594],
-        [0.410373002290726, 0.391080021858215],
-        [0.194993004202843, 0.342101991176605],
-        [0.388664990663528, 0.362284004688263],
-        [0.365961998701096, 0.355970978736877],
-        [0.343364000320435, 0.355356991291046],
-        [0.318785011768341, 0.35834002494812],
-        [0.301414996385574, 0.363156020641327],
-        [0.058132998645306, 0.319076001644135],
-        [0.301414996385574, 0.387449026107788],
-        [0.499987989664078, 0.618434011936188],
-        [0.415838003158569, 0.624195992946625],
-        [0.445681989192963, 0.566076993942261],
-        [0.465844005346298, 0.620640993118286],
-        [0.49992299079895, 0.351523995399475],
-        [0.288718998432159, 0.819945991039276],
-        [0.335278987884521, 0.852819979190826],
-        [0.440512001514435, 0.902418971061707],
-        [0.128294005990028, 0.791940987110138],
-        [0.408771991729736, 0.373893976211548],
-        [0.455606997013092, 0.451801002025604],
-        [0.499877005815506, 0.908990025520325],
-        [0.375436991453171, 0.924192011356354],
-        [0.11421000212431, 0.615022003650665],
-        [0.448662012815475, 0.695277988910675],
-        [0.4480200111866, 0.704632043838501],
-        [0.447111994028091, 0.715808033943176],
-        [0.444831997156143, 0.730794012546539],
-        [0.430011987686157, 0.766808986663818],
-        [0.406787008047104, 0.685672998428345],
-        [0.400738000869751, 0.681069016456604],
-        [0.392399996519089, 0.677703022956848],
-        [0.367855995893478, 0.663918972015381],
-        [0.247923001646996, 0.601333022117615],
-        [0.452769994735718, 0.420849978923798],
-        [0.43639200925827, 0.359887003898621],
-        [0.416164010763168, 0.368713974952698],
-        [0.413385987281799, 0.692366003990173],
-        [0.228018000721931, 0.683571994304657],
-        [0.468268007040024, 0.352671027183533],
-        [0.411361992359161, 0.804327011108398],
-        [0.499989002943039, 0.469825029373169],
-        [0.479153990745544, 0.442654013633728],
-        [0.499974012374878, 0.439637005329132],
-        [0.432112008333206, 0.493588984012604],
-        [0.499886006116867, 0.866917014122009],
-        [0.49991300702095, 0.821729004383087],
-        [0.456548988819122, 0.819200992584229],
-        [0.344549000263214, 0.745438992977142],
-        [0.37890899181366, 0.574010014533997],
-        [0.374292999505997, 0.780184984207153],
-        [0.319687992334366, 0.570737957954407],
-        [0.357154995203018, 0.604269981384277],
-        [0.295284003019333, 0.621580958366394],
-        [0.447750002145767, 0.862477004528046],
-        [0.410986006259918, 0.508723020553589],
-        [0.31395098567009, 0.775308012962341],
-        [0.354128003120422, 0.812552988529205],
-        [0.324548006057739, 0.703992962837219],
-        [0.189096003770828, 0.646299958229065],
-        [0.279776990413666, 0.71465802192688],
-        [0.1338230073452, 0.682700991630554],
-        [0.336768001317978, 0.644733011722565],
-        [0.429883986711502, 0.466521978378296],
-        [0.455527991056442, 0.548622965812683],
-        [0.437114000320435, 0.558896005153656],
-        [0.467287987470627, 0.529924988746643],
-        [0.414712011814117, 0.335219979286194],
-        [0.37704598903656, 0.322777986526489],
-        [0.344107985496521, 0.320150971412659],
-        [0.312875986099243, 0.32233202457428],
-        [0.283526003360748, 0.333190023899078],
-        [0.241245999932289, 0.382785975933075],
-        [0.102986000478268, 0.468762993812561],
-        [0.267612010240555, 0.424560010433197],
-        [0.297879010438919, 0.433175981044769],
-        [0.333433985710144, 0.433878004550934],
-        [0.366427004337311, 0.426115989685059],
-        [0.396012008190155, 0.416696012020111],
-        [0.420121014118195, 0.41022801399231],
-        [0.007561000064015, 0.480777025222778],
-        [0.432949006557465, 0.569517970085144],
-        [0.458638995885849, 0.479089021682739],
-        [0.473466008901596, 0.545744001865387],
-        [0.476087987422943, 0.563830018043518],
-        [0.468472003936768, 0.555056989192963],
-        [0.433990985155106, 0.582361996173859],
-        [0.483518004417419, 0.562983989715576],
-        [0.482482999563217, 0.57784903049469],
-        [0.42645001411438, 0.389798998832703],
-        [0.438998997211456, 0.39649498462677],
-        [0.450067013502121, 0.400434017181396],
-        [0.289712011814117, 0.368252992630005],
-        [0.276670008897781, 0.363372981548309],
-        [0.517862021923065, 0.471948027610779],
-        [0.710287988185883, 0.380764007568359],
-        [0.526226997375488, 0.573909997940063],
-        [0.895093023777008, 0.254140973091125],
-        [0.634069979190826, 0.409575998783112],
-        [0.661242008209229, 0.41302502155304],
-        [0.688880026340485, 0.409460008144379],
-        [0.725341975688934, 0.389131009578705],
-        [0.606630027294159, 0.40370500087738],
-        [0.654766023159027, 0.344011008739471],
-        [0.629905998706818, 0.346076011657715],
-        [0.680678009986877, 0.347265005111694],
-        [0.702096998691559, 0.353591024875641],
-        [0.75221198797226, 0.410804986953735],
-        [0.602918028831482, 0.842862963676453],
-        [0.719901978969574, 0.375599980354309],
-        [0.893692970275879, 0.399959981441498],
-        [0.790081977844238, 0.391354024410248],
-        [0.643998026847839, 0.534487962722778],
-        [0.528249025344849, 0.65040397644043],
-        [0.525849997997284, 0.680191040039062],
-        [0.560214996337891, 0.657229006290436],
-        [0.585384011268616, 0.66654098033905],
-        [0.549625992774963, 0.680860996246338],
-        [0.57122802734375, 0.682691991329193],
-        [0.624852001667023, 0.72809898853302],
-        [0.513050019741058, 0.547281980514526],
-        [0.51509702205658, 0.527251958847046],
-        [0.742246985435486, 0.314507007598877],
-        [0.598631024360657, 0.454979002475739],
-        [0.570338010787964, 0.548575043678284],
-        [0.578631997108459, 0.533622980117798],
-        [0.723087012767792, 0.532054007053375],
-        [0.516445994377136, 0.499638974666595],
-        [0.662801027297974, 0.282917976379395],
-        [0.70362401008606, 0.293271005153656],
-        [0.830704987049103, 0.193813979625702],
-        [0.552385985851288, 0.302568018436432],
-        [0.607609987258911, 0.353887975215912],
-        [0.645429015159607, 0.696707010269165],
-        [0.932694971561432, 0.730105042457581],
-        [0.557260990142822, 0.572826027870178],
-        [0.542901992797852, 0.584792017936707],
-        [0.6180260181427, 0.694710969924927],
-        [0.607590973377228, 0.694203019142151],
-        [0.722943007946014, 0.271963000297546],
-        [0.577413976192474, 0.563166975975037],
-        [0.614082992076874, 0.281386971473694],
-        [0.616907000541687, 0.255886018276215],
-        [0.668509006500244, 0.119913995265961],
-        [0.770092010498047, 0.232020974159241],
-        [0.635536015033722, 0.189248979091644],
-        [0.77039098739624, 0.299556016921997],
-        [0.826722025871277, 0.278755009174347],
-        [0.527121007442474, 0.666198015213013],
-        [0.553171992301941, 0.668527007102966],
-        [0.577238023281097, 0.673889994621277],
-        [0.554691970348358, 0.580065965652466],
-        [0.611896991729736, 0.693961024284363],
-        [0.59696102142334, 0.706539988517761],
-        [0.596370995044708, 0.693953037261963],
-        [0.539958000183105, 0.557139039039612],
-        [0.568841993808746, 0.692366003990173],
-        [0.547818005084991, 0.692366003990173],
-        [0.52461302280426, 0.692366003990173],
-        [0.534089982509613, 0.779141008853912],
-        [0.527670979499817, 0.736225962638855],
-        [0.526912987232208, 0.717857003211975],
-        [0.526877999305725, 0.704625964164734],
-        [0.526966989040375, 0.695277988910675],
-        [0.572058022022247, 0.695277988910675],
-        [0.573521018028259, 0.703539967536926],
-        [0.57683801651001, 0.711845993995667],
-        [0.581691026687622, 0.720062971115112],
-        [0.609944999217987, 0.639909982681274],
-        [0.986046016216278, 0.560034036636353],
-        [0.5867999792099, 0.69539999961853],
-        [0.590372025966644, 0.701822996139526],
-        [0.531915009021759, 0.601536989212036],
-        [0.577268004417419, 0.585934996604919],
-        [0.536915004253387, 0.593786001205444],
-        [0.627542972564697, 0.473352015018463],
-        [0.665585994720459, 0.495950996875763],
-        [0.588353991508484, 0.546862006187439],
-        [0.757824003696442, 0.14767599105835],
-        [0.709249973297119, 0.201507985591888],
-        [0.672684013843536, 0.256581008434296],
-        [0.600408971309662, 0.74900496006012],
-        [0.55826598405838, 0.261672019958496],
-        [0.570303976535797, 0.187870979309082],
-        [0.588165998458862, 0.109044015407562],
-        [0.711045026779175, 0.398952007293701],
-        [0.781069993972778, 0.435405015945435],
-        [0.587247014045715, 0.398931980133057],
-        [0.742869973182678, 0.355445981025696],
-        [0.572156012058258, 0.437651991844177],
-        [0.55186802148819, 0.536570012569427],
-        [0.821442008018494, 0.457556009292603],
-        [0.752701997756958, 0.457181990146637],
-        [0.71375697851181, 0.467626988887787],
-        [0.66711300611496, 0.460672974586487],
-        [0.631101012229919, 0.447153985500336],
-        [0.6008620262146, 0.432473003864288],
-        [0.523481011390686, 0.405627012252808],
-        [0.810747981071472, 0.523926019668579],
-        [0.771045982837677, 0.348959028720856],
-        [0.509127020835876, 0.562718033790588],
-        [0.595292985439301, 0.485023975372314],
-        [0.980530977249146, 0.401564002037048],
-        [0.573499977588654, 0.420000016689301],
-        [0.602994978427887, 0.548687994480133],
-        [0.733529984951019, 0.376977026462555],
-        [0.560611009597778, 0.519016981124878],
-        [0.967685997486115, 0.644356966018677],
-        [0.580985009670258, 0.387160003185272],
-        [0.537728011608124, 0.505385041236877],
-        [0.760966002941132, 0.779752969741821],
-        [0.801778972148895, 0.831938028335571],
-        [0.892440974712372, 0.54076099395752],
-        [0.816350996494293, 0.740260004997253],
-        [0.865594983100891, 0.333687007427216],
-        [0.614073991775513, 0.883246004581451],
-        [0.508952975273132, 0.579437971115112],
-        [0.617941975593567, 0.508316040039062],
-        [0.825608015060425, 0.397674977779388],
-        [0.681214988231659, 0.39623498916626],
-        [0.656635999679565, 0.400596976280212],
-        [0.603900015354156, 0.710216999053955],
-        [0.81208598613739, 0.588539004325867],
-        [0.56801301240921, 0.944564998149872],
-        [0.681007981300354, 0.898285031318665],
-        [0.733752012252808, 0.869701027870178],
-        [0.633830010890961, 0.398822009563446],
-        [0.606792986392975, 0.39553701877594],
-        [0.589659988880157, 0.391062021255493],
-        [0.805015981197357, 0.342108011245728],
-        [0.611334979534149, 0.362284004688263],
-        [0.634037971496582, 0.355970978736877],
-        [0.656635999679565, 0.355356991291046],
-        [0.681214988231659, 0.35834002494812],
-        [0.698584973812103, 0.363156020641327],
-        [0.941866993904114, 0.319076001644135],
-        [0.698584973812103, 0.387449026107788],
-        [0.584177017211914, 0.624107003211975],
-        [0.554318010807037, 0.566076993942261],
-        [0.534153997898102, 0.62064003944397],
-        [0.711217999458313, 0.819975018501282],
-        [0.664629995822906, 0.852871000766754],
-        [0.559099972248077, 0.902631998062134],
-        [0.871706008911133, 0.791940987110138],
-        [0.591234028339386, 0.373893976211548],
-        [0.544341027736664, 0.451583981513977],
-        [0.624562978744507, 0.924192011356354],
-        [0.88577002286911, 0.615028977394104],
-        [0.551338016986847, 0.695277988910675],
-        [0.551980018615723, 0.704632043838501],
-        [0.552887976169586, 0.715808033943176],
-        [0.555167973041534, 0.730794012546539],
-        [0.569944024085999, 0.767035007476807],
-        [0.593203008174896, 0.685675978660583],
-        [0.599261999130249, 0.681069016456604],
-        [0.607599973678589, 0.677703022956848],
-        [0.631937980651855, 0.663500010967255],
-        [0.752032995223999, 0.601315021514893],
-        [0.547226011753082, 0.420395016670227],
-        [0.563543975353241, 0.359827995300293],
-        [0.583841025829315, 0.368713974952698],
-        [0.586614012718201, 0.692366003990173],
-        [0.771915018558502, 0.683578014373779],
-        [0.531597018241882, 0.352482974529266],
-        [0.588370978832245, 0.804440975189209],
-        [0.52079701423645, 0.442565023899078],
-        [0.567984998226166, 0.493479013442993],
-        [0.543282985687256, 0.819254994392395],
-        [0.655317008495331, 0.745514988899231],
-        [0.621008992195129, 0.574018001556396],
-        [0.625559985637665, 0.78031200170517],
-        [0.680198013782501, 0.570719003677368],
-        [0.64276397228241, 0.604337990283966],
-        [0.704662978649139, 0.621529996395111],
-        [0.552012026309967, 0.862591981887817],
-        [0.589071989059448, 0.508637011051178],
-        [0.685944974422455, 0.775357007980347],
-        [0.645735025405884, 0.812640011310577],
-        [0.675342977046967, 0.703978002071381],
-        [0.810858011245728, 0.646304965019226],
-        [0.72012197971344, 0.714666962623596],
-        [0.866151988506317, 0.682704985141754],
-        [0.663187026977539, 0.644596993923187],
-        [0.570082008838654, 0.466325998306274],
-        [0.544561982154846, 0.548375964164734],
-        [0.562758982181549, 0.558784961700439],
-        [0.531987011432648, 0.530140042304993],
-        [0.585271000862122, 0.335177004337311],
-        [0.622952997684479, 0.32277899980545],
-        [0.655896008014679, 0.320163011550903],
-        [0.687132000923157, 0.322345972061157],
-        [0.716481983661652, 0.333200991153717],
-        [0.758756995201111, 0.382786989212036],
-        [0.897013008594513, 0.468769013881683],
-        [0.732392013072968, 0.424547016620636],
-        [0.70211398601532, 0.433162987232208],
-        [0.66652500629425, 0.433866024017334],
-        [0.633504986763, 0.426087975502014],
-        [0.603875994682312, 0.416586995124817],
-        [0.579657971858978, 0.409945011138916],
-        [0.992439985275269, 0.480777025222778],
-        [0.567192018032074, 0.569419980049133],
-        [0.54136598110199, 0.478899002075195],
-        [0.526564002037048, 0.546118021011353],
-        [0.523913025856018, 0.563830018043518],
-        [0.531529009342194, 0.555056989192963],
-        [0.566035985946655, 0.582329034805298],
-        [0.51631098985672, 0.563053965568542],
-        [0.5174720287323, 0.577877044677734],
-        [0.573594987392426, 0.389806985855103],
-        [0.560697972774506, 0.395331978797913],
-        [0.549755990505219, 0.399751007556915],
-        [0.710287988185883, 0.368252992630005],
-        [0.723330020904541, 0.363372981548309],
-      ];
-      //# sourceMappingURL=uv_coords.js.map
-
-      /***/
-    },
-    /* 86 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      // ESM COMPAT FLAG
-      __webpack_require__.r(__webpack_exports__);
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "version_webgl", function () {
-        return /* reexport */ version_version;
-      });
-      __webpack_require__.d(__webpack_exports__, "MathBackendWebGL", function () {
-        return /* reexport */ backend_webgl_MathBackendWebGL;
-      });
-      __webpack_require__.d(__webpack_exports__, "setWebGLContext", function () {
-        return /* reexport */ setWebGLContext;
-      });
-      __webpack_require__.d(__webpack_exports__, "GPGPUContext", function () {
-        return /* reexport */ gpgpu_context_GPGPUContext;
-      });
-      __webpack_require__.d(__webpack_exports__, "gpgpu_util", function () {
-        return /* reexport */ gpgpu_util_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "webgl_util", function () {
-        return /* reexport */ webgl_util_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "forceHalfFloat", function () {
-        return /* reexport */ forceHalfFloat;
-      });
-      __webpack_require__.d(__webpack_exports__, "webgl", function () {
-        return /* binding */ webgl;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl_util.js
-      var webgl_util_namespaceObject = {};
-      __webpack_require__.r(webgl_util_namespaceObject);
-      __webpack_require__.d(webgl_util_namespaceObject, "callAndCheck", function () {
-        return callAndCheck;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "canBeRepresented", function () {
-        return canBeRepresented;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getWebGLErrorMessage", function () {
-        return getWebGLErrorMessage;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getExtensionOrThrow", function () {
-        return getExtensionOrThrow;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "createVertexShader", function () {
-        return createVertexShader;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "createFragmentShader", function () {
-        return createFragmentShader;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "createProgram", function () {
-        return createProgram;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "linkProgram", function () {
-        return linkProgram;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "validateProgram", function () {
-        return validateProgram;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "createStaticVertexBuffer", function () {
-        return createStaticVertexBuffer;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "createStaticIndexBuffer", function () {
-        return createStaticIndexBuffer;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getNumChannels", function () {
-        return getNumChannels;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "createTexture", function () {
-        return createTexture;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "validateTextureSize", function () {
-        return validateTextureSize;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "createFramebuffer", function () {
-        return createFramebuffer;
-      });
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "bindVertexBufferToProgramAttribute",
-        function () {
-          return bindVertexBufferToProgramAttribute;
-        }
-      );
-      __webpack_require__.d(webgl_util_namespaceObject, "bindTextureUnit", function () {
-        return bindTextureUnit;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "unbindTextureUnit", function () {
-        return unbindTextureUnit;
-      });
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "getProgramUniformLocationOrThrow",
-        function () {
-          return getProgramUniformLocationOrThrow;
-        }
-      );
-      __webpack_require__.d(webgl_util_namespaceObject, "getProgramUniformLocation", function () {
-        return getProgramUniformLocation;
-      });
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "bindTextureToProgramUniformSampler",
-        function () {
-          return bindTextureToProgramUniformSampler;
-        }
-      );
-      __webpack_require__.d(webgl_util_namespaceObject, "bindCanvasToFramebuffer", function () {
-        return bindCanvasToFramebuffer;
-      });
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "bindColorTextureToFramebuffer",
-        function () {
-          return bindColorTextureToFramebuffer;
-        }
-      );
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "unbindColorTextureFromFramebuffer",
-        function () {
-          return unbindColorTextureFromFramebuffer;
-        }
-      );
-      __webpack_require__.d(webgl_util_namespaceObject, "validateFramebuffer", function () {
-        return validateFramebuffer;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getFramebufferErrorMessage", function () {
-        return getFramebufferErrorMessage;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getBatchDim", function () {
-        return getBatchDim;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getRowsCols", function () {
-        return getRowsCols;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getShapeAs3D", function () {
-        return getShapeAs3D;
-      });
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "getTextureShapeFromLogicalShape",
-        function () {
-          return getTextureShapeFromLogicalShape;
-        }
-      );
-      __webpack_require__.d(webgl_util_namespaceObject, "isReshapeFree", function () {
-        return isReshapeFree;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getWebGLMaxTextureSize", function () {
-        return getWebGLMaxTextureSize;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "resetMaxTextureSize", function () {
-        return resetMaxTextureSize;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "resetMaxTexturesInShader", function () {
-        return resetMaxTexturesInShader;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "getMaxTexturesInShader", function () {
-        return getMaxTexturesInShader;
-      });
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "getWebGLDisjointQueryTimerVersion",
-        function () {
-          return getWebGLDisjointQueryTimerVersion;
-        }
-      );
-      __webpack_require__.d(webgl_util_namespaceObject, "hasExtension", function () {
-        return hasExtension;
-      });
-      __webpack_require__.d(webgl_util_namespaceObject, "isWebGLVersionEnabled", function () {
-        return isWebGLVersionEnabled;
-      });
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "isCapableOfRenderingToFloatTexture",
-        function () {
-          return isCapableOfRenderingToFloatTexture;
-        }
-      );
-      __webpack_require__.d(
-        webgl_util_namespaceObject,
-        "isDownloadFloatTextureEnabled",
-        function () {
-          return isDownloadFloatTextureEnabled;
-        }
-      );
-      __webpack_require__.d(webgl_util_namespaceObject, "isWebGLFenceEnabled", function () {
-        return isWebGLFenceEnabled;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_util.js
-      var gpgpu_util_namespaceObject = {};
-      __webpack_require__.r(gpgpu_util_namespaceObject);
-      __webpack_require__.d(gpgpu_util_namespaceObject, "createVertexShader", function () {
-        return gpgpu_util_createVertexShader;
-      });
-      __webpack_require__.d(gpgpu_util_namespaceObject, "createVertexBuffer", function () {
-        return createVertexBuffer;
-      });
-      __webpack_require__.d(gpgpu_util_namespaceObject, "createIndexBuffer", function () {
-        return createIndexBuffer;
-      });
-      __webpack_require__.d(gpgpu_util_namespaceObject, "createFloat32MatrixTexture", function () {
-        return createFloat32MatrixTexture;
-      });
-      __webpack_require__.d(gpgpu_util_namespaceObject, "createFloat16MatrixTexture", function () {
-        return createFloat16MatrixTexture;
-      });
-      __webpack_require__.d(
-        gpgpu_util_namespaceObject,
-        "createUnsignedBytesMatrixTexture",
-        function () {
-          return createUnsignedBytesMatrixTexture;
-        }
-      );
-      __webpack_require__.d(gpgpu_util_namespaceObject, "createPackedMatrixTexture", function () {
-        return createPackedMatrixTexture;
-      });
-      __webpack_require__.d(
-        gpgpu_util_namespaceObject,
-        "createFloat16PackedMatrixTexture",
-        function () {
-          return createFloat16PackedMatrixTexture;
-        }
-      );
-      __webpack_require__.d(
-        gpgpu_util_namespaceObject,
-        "bindVertexProgramAttributeStreams",
-        function () {
-          return bindVertexProgramAttributeStreams;
-        }
-      );
-      __webpack_require__.d(gpgpu_util_namespaceObject, "uploadDenseMatrixToTexture", function () {
-        return uploadDenseMatrixToTexture;
-      });
-      __webpack_require__.d(gpgpu_util_namespaceObject, "uploadPixelDataToTexture", function () {
-        return uploadPixelDataToTexture;
-      });
-      __webpack_require__.d(
-        gpgpu_util_namespaceObject,
-        "createBufferFromOutputTexture",
-        function () {
-          return createBufferFromOutputTexture;
-        }
-      );
-      __webpack_require__.d(
-        gpgpu_util_namespaceObject,
-        "downloadFloat32MatrixFromBuffer",
-        function () {
-          return downloadFloat32MatrixFromBuffer;
-        }
-      );
-      __webpack_require__.d(
-        gpgpu_util_namespaceObject,
-        "downloadByteEncodedFloatMatrixFromOutputTexture",
-        function () {
-          return downloadByteEncodedFloatMatrixFromOutputTexture;
-        }
-      );
-      __webpack_require__.d(
-        gpgpu_util_namespaceObject,
-        "downloadPackedMatrixFromBuffer",
-        function () {
-          return downloadPackedMatrixFromBuffer;
-        }
-      );
-      __webpack_require__.d(
-        gpgpu_util_namespaceObject,
-        "downloadMatrixFromPackedOutputTexture",
-        function () {
-          return downloadMatrixFromPackedOutputTexture;
-        }
-      );
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
-      var dist = __webpack_require__(0);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/canvas_util.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const contexts = {};
-      const WEBGL_ATTRIBUTES = {
-        alpha: false,
-        antialias: false,
-        premultipliedAlpha: false,
-        preserveDrawingBuffer: false,
-        depth: false,
-        stencil: false,
-        failIfMajorPerformanceCaveat: true,
-      };
-      function setWebGLContext(webGLVersion, gl) {
-        contexts[webGLVersion] = gl;
-      }
-      function getWebGLContext(webGLVersion) {
-        if (!(webGLVersion in contexts)) {
-          contexts[webGLVersion] = getWebGLRenderingContext(webGLVersion);
-        }
-        const gl = contexts[webGLVersion];
-        if (gl.isContextLost()) {
-          delete contexts[webGLVersion];
-          return getWebGLContext(webGLVersion);
-        }
-        gl.disable(gl.DEPTH_TEST);
-        gl.disable(gl.STENCIL_TEST);
-        gl.disable(gl.BLEND);
-        gl.disable(gl.DITHER);
-        gl.disable(gl.POLYGON_OFFSET_FILL);
-        gl.disable(gl.SAMPLE_COVERAGE);
-        gl.enable(gl.SCISSOR_TEST);
-        gl.enable(gl.CULL_FACE);
-        gl.cullFace(gl.BACK);
-        return contexts[webGLVersion];
-      }
-      function createCanvas(webGLVersion) {
-        if (typeof OffscreenCanvas !== "undefined" && webGLVersion === 2) {
-          return new OffscreenCanvas(300, 150);
-        } else if (typeof document !== "undefined") {
-          return document.createElement("canvas");
-        } else {
-          throw new Error("Cannot create a canvas in this context");
-        }
-      }
-      function getWebGLRenderingContext(webGLVersion) {
-        if (webGLVersion !== 1 && webGLVersion !== 2) {
-          throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");
-        }
-        const canvas = createCanvas(webGLVersion);
-        canvas.addEventListener(
-          "webglcontextlost",
-          (ev) => {
-            ev.preventDefault();
-            delete contexts[webGLVersion];
-          },
-          false
-        );
-        if (webGLVersion === 1) {
-          return (
-            canvas.getContext("webgl", WEBGL_ATTRIBUTES) ||
-            canvas.getContext("experimental-webgl", WEBGL_ATTRIBUTES)
-          );
-        }
-        return canvas.getContext("webgl2", WEBGL_ATTRIBUTES);
-      }
-      //# sourceMappingURL=canvas_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/tex_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      var PackingScheme;
-      (function (PackingScheme) {
-        /**
-         * All values in a single texel are densely packed without any constraints.
-         *
-         * This is how the shader encodes a tensor with shape = [2, 3, 4]
-         * (indices are [batch, row, col]).
-         *
-         * 000|001   010|011   020|021
-         * -------   -------   -------
-         * 002|003   012|013   022|023
-         *
-         * 100|101   110|111   120|121
-         * -------   -------   -------
-         * 102|103   112|113   122|123
-         *
-         */
-        PackingScheme[(PackingScheme["DENSE"] = 0)] = "DENSE";
-        /**
-         * Single texels contain only values from the same batch, and from adjacent
-         * rows and columns.
-         *
-         * This is how the shader encodes a tensor with shape = [2, 3, 5]
-         * (indices are [batch, row, col]).
-         *
-         * 000|001   002|003   004|xxx   020|021   022|023   024|xxx
-         * -------   -------   -------   -------   -------   -------
-         * 010|011   012|013   014|xxx   xxx|xxx   xxx|xxx   xxx|xxx
-         *
-         * 100|101   102|103   104|xxx   120|121   122|123   124|xxx
-         * -------   -------   -------   -------   -------   -------
-         * 110|111   112|113   114|xxx   xxx|xxx   xxx|xxx   xxx|xxx
-         *
-         */
-        PackingScheme[(PackingScheme["SHARED_BATCH"] = 1)] = "SHARED_BATCH";
-      })(PackingScheme || (PackingScheme = {}));
-      var TextureUsage;
-      (function (TextureUsage) {
-        TextureUsage[(TextureUsage["RENDER"] = 0)] = "RENDER";
-        TextureUsage[(TextureUsage["UPLOAD"] = 1)] = "UPLOAD";
-        TextureUsage[(TextureUsage["PIXELS"] = 2)] = "PIXELS";
-        TextureUsage[(TextureUsage["DOWNLOAD"] = 3)] = "DOWNLOAD";
-      })(TextureUsage || (TextureUsage = {}));
-      var PhysicalTextureType;
-      (function (PhysicalTextureType) {
-        PhysicalTextureType[(PhysicalTextureType["UNPACKED_FLOAT16"] = 0)] = "UNPACKED_FLOAT16";
-        PhysicalTextureType[(PhysicalTextureType["UNPACKED_FLOAT32"] = 1)] = "UNPACKED_FLOAT32";
-        PhysicalTextureType[(PhysicalTextureType["PACKED_4X1_UNSIGNED_BYTE"] = 2)] =
-          "PACKED_4X1_UNSIGNED_BYTE";
-        PhysicalTextureType[(PhysicalTextureType["PACKED_2X2_FLOAT32"] = 3)] = "PACKED_2X2_FLOAT32";
-        PhysicalTextureType[(PhysicalTextureType["PACKED_2X2_FLOAT16"] = 4)] = "PACKED_2X2_FLOAT16";
-      })(PhysicalTextureType || (PhysicalTextureType = {}));
-      function getUnpackedMatrixTextureShapeWidthHeight(rows, columns) {
-        return [columns, rows];
-      }
-      function getUnpackedArraySizeFromMatrixSize(matrixSize, channelsPerTexture) {
-        return matrixSize * channelsPerTexture;
-      }
-      function getColorMatrixTextureShapeWidthHeight(rows, columns) {
-        return [columns * 4, rows];
-      }
-      /**
-       * Get shape for densely packed RGBA texture.
-       */
-      function getDenseTexShape(shape) {
-        const size = dist["util"].sizeFromShape(shape);
-        const texelsNeeded = Math.ceil(size / 4);
-        return dist["util"].sizeToSquarishShape(texelsNeeded);
-      }
-      function getMatrixSizeFromUnpackedArraySize(unpackedSize, channelsPerTexture) {
-        if (unpackedSize % channelsPerTexture !== 0) {
-          throw new Error(
-            `unpackedSize (${unpackedSize}) must be a multiple of ` + `${channelsPerTexture}`
-          );
-        }
-        return unpackedSize / channelsPerTexture;
-      }
-      function decodeMatrixFromUnpackedColorRGBAArray(unpackedArray, matrix, channels) {
-        const requiredSize = (unpackedArray.length * channels) / 4;
-        if (matrix.length < requiredSize) {
-          throw new Error(`matrix length (${matrix.length}) must be >= ${requiredSize}`);
-        }
-        let dst = 0;
-        for (let src = 0; src < unpackedArray.length; src += 4) {
-          for (let c = 0; c < channels; c++) {
-            matrix[dst++] = unpackedArray[src + c];
-          }
-        }
-      }
-      function getPackedMatrixTextureShapeWidthHeight(rows, columns) {
-        return [Math.max(1, Math.ceil(columns / 2)), Math.max(1, Math.ceil(rows / 2))];
-      }
-      function getPackedRGBAArraySizeFromMatrixShape(rows, columns) {
-        const [w, h] = getPackedMatrixTextureShapeWidthHeight(rows, columns);
-        return w * h * 4;
-      }
-      function getTextureConfig(
-        // tslint:disable-next-line:no-any
-        gl,
-        textureHalfFloatExtension
-      ) {
-        // tslint:disable-next-line:no-any
-        const glany = gl;
-        let internalFormatFloat;
-        let internalFormatHalfFloat;
-        let internalFormatPackedHalfFloat;
-        let internalFormatPackedFloat;
-        let textureFormatFloat;
-        let downloadTextureFormat;
-        let downloadUnpackNumChannels;
-        let defaultNumChannels;
-        let textureTypeHalfFloat;
-        let textureTypeFloat;
-        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 2) {
-          internalFormatFloat = glany.R32F;
-          internalFormatHalfFloat = glany.R16F;
-          internalFormatPackedHalfFloat = glany.RGBA16F;
-          internalFormatPackedFloat = glany.RGBA32F;
-          textureFormatFloat = glany.RED;
-          downloadUnpackNumChannels = 4;
-          defaultNumChannels = 1;
-          textureTypeHalfFloat = glany.HALF_FLOAT;
-          textureTypeFloat = glany.FLOAT;
-        } else {
-          internalFormatFloat = gl.RGBA;
-          internalFormatHalfFloat = gl.RGBA;
-          internalFormatPackedHalfFloat = gl.RGBA;
-          internalFormatPackedFloat = glany.RGBA;
-          textureFormatFloat = gl.RGBA;
-          downloadUnpackNumChannels = 4;
-          defaultNumChannels = 4;
-          textureTypeHalfFloat =
-            textureHalfFloatExtension != null ? textureHalfFloatExtension.HALF_FLOAT_OES : null;
-          textureTypeFloat = gl.FLOAT;
-        }
-        downloadTextureFormat = gl.RGBA;
-        return {
-          internalFormatFloat,
-          internalFormatHalfFloat,
-          internalFormatPackedHalfFloat,
-          internalFormatPackedFloat,
-          textureFormatFloat,
-          downloadTextureFormat,
-          downloadUnpackNumChannels,
-          defaultNumChannels,
-          textureTypeHalfFloat,
-          textureTypeFloat,
-        };
-      }
-      //# sourceMappingURL=tex_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function callAndCheck(gl, debugMode, func) {
-        const returnValue = func();
-        if (debugMode) {
-          checkWebGLError(gl);
-        }
-        return returnValue;
-      }
-      function checkWebGLError(gl) {
-        const error = gl.getError();
-        if (error !== gl.NO_ERROR) {
-          throw new Error("WebGL Error: " + getWebGLErrorMessage(gl, error));
-        }
-      }
-      // https://en.wikipedia.org/wiki/Half-precision_floating-point_format
-      const MIN_FLOAT16 = 5.96e-8;
-      const MAX_FLOAT16 = 65504;
-      function canBeRepresented(num) {
-        if (
-          Object(dist["env"])().getBool("WEBGL_RENDER_FLOAT32_ENABLED") ||
-          num === 0 ||
-          (MIN_FLOAT16 < Math.abs(num) && Math.abs(num) < MAX_FLOAT16)
-        ) {
-          return true;
-        }
-        return false;
-      }
-      function getWebGLErrorMessage(gl, status) {
-        switch (status) {
-          case gl.NO_ERROR:
-            return "NO_ERROR";
-          case gl.INVALID_ENUM:
-            return "INVALID_ENUM";
-          case gl.INVALID_VALUE:
-            return "INVALID_VALUE";
-          case gl.INVALID_OPERATION:
-            return "INVALID_OPERATION";
-          case gl.INVALID_FRAMEBUFFER_OPERATION:
-            return "INVALID_FRAMEBUFFER_OPERATION";
-          case gl.OUT_OF_MEMORY:
-            return "OUT_OF_MEMORY";
-          case gl.CONTEXT_LOST_WEBGL:
-            return "CONTEXT_LOST_WEBGL";
-          default:
-            return `Unknown error code ${status}`;
-        }
-      }
-      function getExtensionOrThrow(gl, debug, extensionName) {
-        return throwIfNull(
-          gl,
-          debug,
-          () => gl.getExtension(extensionName),
-          'Extension "' + extensionName + '" not supported on this browser.'
-        );
-      }
-      function createVertexShader(gl, debug, vertexShaderSource) {
-        const vertexShader = throwIfNull(
-          gl,
-          debug,
-          () => gl.createShader(gl.VERTEX_SHADER),
-          "Unable to create vertex WebGLShader."
-        );
-        callAndCheck(gl, debug, () => gl.shaderSource(vertexShader, vertexShaderSource));
-        callAndCheck(gl, debug, () => gl.compileShader(vertexShader));
-        if (gl.getShaderParameter(vertexShader, gl.COMPILE_STATUS) === false) {
-          console.log(gl.getShaderInfoLog(vertexShader));
-          throw new Error("Failed to compile vertex shader.");
-        }
-        return vertexShader;
-      }
-      function createFragmentShader(gl, debug, fragmentShaderSource) {
-        const fragmentShader = throwIfNull(
-          gl,
-          debug,
-          () => gl.createShader(gl.FRAGMENT_SHADER),
-          "Unable to create fragment WebGLShader."
-        );
-        callAndCheck(gl, debug, () => gl.shaderSource(fragmentShader, fragmentShaderSource));
-        callAndCheck(gl, debug, () => gl.compileShader(fragmentShader));
-        if (gl.getShaderParameter(fragmentShader, gl.COMPILE_STATUS) === false) {
-          logShaderSourceAndInfoLog(fragmentShaderSource, gl.getShaderInfoLog(fragmentShader));
-          throw new Error("Failed to compile fragment shader.");
-        }
-        return fragmentShader;
-      }
-      const lineNumberRegex = /ERROR: [0-9]+:([0-9]+):/g;
-      function logShaderSourceAndInfoLog(shaderSource, shaderInfoLog) {
-        const lineNumberRegexResult = lineNumberRegex.exec(shaderInfoLog);
-        if (lineNumberRegexResult == null) {
-          console.log(`Couldn't parse line number in error: ${shaderInfoLog}`);
-          console.log(shaderSource);
-          return;
-        }
-        const lineNumber = +lineNumberRegexResult[1];
-        const shaderLines = shaderSource.split("\n");
-        const pad = shaderLines.length.toString().length + 2;
-        const linesWithLineNumbers = shaderLines.map(
-          (line, lineNumber) => dist["util"].rightPad((lineNumber + 1).toString(), pad) + line
-        );
-        let maxLineLength = 0;
-        for (let i = 0; i < linesWithLineNumbers.length; i++) {
-          maxLineLength = Math.max(linesWithLineNumbers[i].length, maxLineLength);
-        }
-        const beforeErrorLines = linesWithLineNumbers.slice(0, lineNumber - 1);
-        const errorLine = linesWithLineNumbers.slice(lineNumber - 1, lineNumber);
-        const afterErrorLines = linesWithLineNumbers.slice(lineNumber);
-        console.log(beforeErrorLines.join("\n"));
-        console.log(shaderInfoLog.split("\n")[0]);
-        console.log(
-          `%c ${dist["util"].rightPad(errorLine[0], maxLineLength)}`,
-          "border:1px solid red; background-color:#e3d2d2; color:#a61717"
-        );
-        console.log(afterErrorLines.join("\n"));
-      }
-      function createProgram(gl, debug) {
-        return throwIfNull(gl, debug, () => gl.createProgram(), "Unable to create WebGLProgram.");
-      }
-      function linkProgram(gl, debug, program) {
-        callAndCheck(gl, debug, () => gl.linkProgram(program));
-        if (gl.getProgramParameter(program, gl.LINK_STATUS) === false) {
-          console.log(gl.getProgramInfoLog(program));
-          throw new Error("Failed to link vertex and fragment shaders.");
-        }
-      }
-      function validateProgram(gl, debug, program) {
-        callAndCheck(gl, debug, () => gl.validateProgram(program));
-        if (gl.getProgramParameter(program, gl.VALIDATE_STATUS) === false) {
-          console.log(gl.getProgramInfoLog(program));
-          throw new Error("Shader program validation failed.");
-        }
-      }
-      function createStaticVertexBuffer(gl, debug, data) {
-        const buffer = throwIfNull(
-          gl,
-          debug,
-          () => gl.createBuffer(),
-          "Unable to create WebGLBuffer"
-        );
-        callAndCheck(gl, debug, () => gl.bindBuffer(gl.ARRAY_BUFFER, buffer));
-        callAndCheck(gl, debug, () => gl.bufferData(gl.ARRAY_BUFFER, data, gl.STATIC_DRAW));
-        return buffer;
-      }
-      function createStaticIndexBuffer(gl, debug, data) {
-        const buffer = throwIfNull(
-          gl,
-          debug,
-          () => gl.createBuffer(),
-          "Unable to create WebGLBuffer"
-        );
-        callAndCheck(gl, debug, () => gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, buffer));
-        callAndCheck(gl, debug, () => gl.bufferData(gl.ELEMENT_ARRAY_BUFFER, data, gl.STATIC_DRAW));
-        return buffer;
-      }
-      function getNumChannels() {
-        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 2) {
-          return 1;
-        }
-        return 4;
-      }
-      function createTexture(gl, debug) {
-        return throwIfNull(gl, debug, () => gl.createTexture(), "Unable to create WebGLTexture.");
-      }
-      function validateTextureSize(width, height) {
-        const maxTextureSize = Object(dist["env"])().getNumber("WEBGL_MAX_TEXTURE_SIZE");
-        if (width <= 0 || height <= 0) {
-          const requested = `[${width}x${height}]`;
-          throw new Error("Requested texture size " + requested + " is invalid.");
-        }
-        if (width > maxTextureSize || height > maxTextureSize) {
-          const requested = `[${width}x${height}]`;
-          const max = `[${maxTextureSize}x${maxTextureSize}]`;
-          throw new Error(
-            "Requested texture size " +
-              requested +
-              " greater than WebGL maximum on this browser / GPU " +
-              max +
-              "."
-          );
-        }
-      }
-      function createFramebuffer(gl, debug) {
-        return throwIfNull(
-          gl,
-          debug,
-          () => gl.createFramebuffer(),
-          "Unable to create WebGLFramebuffer."
-        );
-      }
-      function bindVertexBufferToProgramAttribute(
-        gl,
-        debug,
-        program,
-        attribute,
-        buffer,
-        arrayEntriesPerItem,
-        itemStrideInBytes,
-        itemOffsetInBytes
-      ) {
-        const loc = gl.getAttribLocation(program, attribute);
-        if (loc === -1) {
-          // The GPU compiler decided to strip out this attribute because it's unused,
-          // thus no need to bind.
-          return false;
-        }
-        callAndCheck(gl, debug, () => gl.bindBuffer(gl.ARRAY_BUFFER, buffer));
-        callAndCheck(gl, debug, () =>
-          gl.vertexAttribPointer(
-            loc,
-            arrayEntriesPerItem,
-            gl.FLOAT,
-            false,
-            itemStrideInBytes,
-            itemOffsetInBytes
-          )
-        );
-        callAndCheck(gl, debug, () => gl.enableVertexAttribArray(loc));
-        return true;
-      }
-      function bindTextureUnit(gl, debug, texture, textureUnit) {
-        validateTextureUnit(gl, textureUnit);
-        callAndCheck(gl, debug, () => gl.activeTexture(gl.TEXTURE0 + textureUnit));
-        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, texture));
-      }
-      function unbindTextureUnit(gl, debug, textureUnit) {
-        validateTextureUnit(gl, textureUnit);
-        callAndCheck(gl, debug, () => gl.activeTexture(gl.TEXTURE0 + textureUnit));
-        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, null));
-      }
-      function getProgramUniformLocationOrThrow(gl, debug, program, uniformName) {
-        return throwIfNull(
-          gl,
-          debug,
-          () => gl.getUniformLocation(program, uniformName),
-          'uniform "' + uniformName + '" not present in program.'
-        );
-      }
-      function getProgramUniformLocation(gl, program, uniformName) {
-        return gl.getUniformLocation(program, uniformName);
-      }
-      function bindTextureToProgramUniformSampler(
-        gl,
-        debug,
-        program,
-        texture,
-        uniformSamplerLocation,
-        textureUnit
-      ) {
-        callAndCheck(gl, debug, () => bindTextureUnit(gl, debug, texture, textureUnit));
-        callAndCheck(gl, debug, () => gl.uniform1i(uniformSamplerLocation, textureUnit));
-      }
-      function bindCanvasToFramebuffer(gl, debug) {
-        callAndCheck(gl, debug, () => gl.bindFramebuffer(gl.FRAMEBUFFER, null));
-        callAndCheck(gl, debug, () => gl.viewport(0, 0, gl.canvas.width, gl.canvas.height));
-        callAndCheck(gl, debug, () => gl.scissor(0, 0, gl.canvas.width, gl.canvas.height));
-      }
-      function bindColorTextureToFramebuffer(gl, debug, texture, framebuffer) {
-        callAndCheck(gl, debug, () => gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer));
-        callAndCheck(gl, debug, () =>
-          gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0)
-        );
-      }
-      function unbindColorTextureFromFramebuffer(gl, debug, framebuffer) {
-        callAndCheck(gl, debug, () => gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer));
-        callAndCheck(gl, debug, () =>
-          gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, null, 0)
-        );
-      }
-      function validateFramebuffer(gl) {
-        const status = gl.checkFramebufferStatus(gl.FRAMEBUFFER);
-        if (status !== gl.FRAMEBUFFER_COMPLETE) {
-          throw new Error("Error binding framebuffer: " + getFramebufferErrorMessage(gl, status));
-        }
-      }
-      function getFramebufferErrorMessage(gl, status) {
-        switch (status) {
-          case gl.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:
-            return "FRAMEBUFFER_INCOMPLETE_ATTACHMENT";
-          case gl.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:
-            return "FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";
-          case gl.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:
-            return "FRAMEBUFFER_INCOMPLETE_DIMENSIONS";
-          case gl.FRAMEBUFFER_UNSUPPORTED:
-            return "FRAMEBUFFER_UNSUPPORTED";
-          default:
-            return `unknown error ${status}`;
-        }
-      }
-      function throwIfNull(gl, debug, returnTOrNull, failureMessage) {
-        const tOrNull = callAndCheck(gl, debug, () => returnTOrNull());
-        if (tOrNull == null) {
-          throw new Error(failureMessage);
-        }
-        return tOrNull;
-      }
-      function validateTextureUnit(gl, textureUnit) {
-        const maxTextureUnit = gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS - 1;
-        const glTextureUnit = textureUnit + gl.TEXTURE0;
-        if (glTextureUnit < gl.TEXTURE0 || glTextureUnit > maxTextureUnit) {
-          const textureUnitRange = `[gl.TEXTURE0, gl.TEXTURE${maxTextureUnit}]`;
-          throw new Error(`textureUnit must be in ${textureUnitRange}.`);
-        }
-      }
-      function getBatchDim(shape, dimsToSkip = 2) {
-        return dist["util"].sizeFromShape(shape.slice(0, shape.length - dimsToSkip));
-      }
-      function getRowsCols(shape) {
-        if (shape.length === 0) {
-          throw Error("Cannot get rows and columns of an empty shape array.");
-        }
-        return [shape.length > 1 ? shape[shape.length - 2] : 1, shape[shape.length - 1]];
-      }
-      function getShapeAs3D(shape) {
-        let shapeAs3D = [1, 1, 1];
-        const isScalar = shape.length === 0 || (shape.length === 1 && shape[0] === 1);
-        if (!isScalar) {
-          shapeAs3D = [getBatchDim(shape), ...getRowsCols(shape)];
-        }
-        return shapeAs3D;
-      }
-      function getTextureShapeFromLogicalShape(logShape, isPacked = false) {
-        let maxTexSize = Object(dist["env"])().getNumber("WEBGL_MAX_TEXTURE_SIZE");
-        if (isPacked) {
-          maxTexSize = maxTexSize * 2;
-          // This logic ensures we accurately count the number of packed texels needed
-          // to accommodate the tensor. We can only pack values in the same texel if
-          // they are from adjacent pairs of rows/cols within the same batch. So if a
-          // tensor has 3 rows, we pretend it has 4 rows in order to account for the
-          // fact that the texels containing the third row are half empty.
-          logShape = logShape.map((d, i) =>
-            i >= logShape.length - 2 ? dist["util"].nearestLargerEven(logShape[i]) : logShape[i]
-          );
-          // Packed texture height is at least 2 (the channel height of a single
-          // texel).
-          if (logShape.length === 1) {
-            logShape = [2, logShape[0]];
-          }
-        }
-        // If logical shape is 2, we don't squeeze, since we want to match physical.
-        if (logShape.length !== 2) {
-          const squeezeResult = dist["util"].squeezeShape(logShape);
-          logShape = squeezeResult.newShape;
-        }
-        let size = dist["util"].sizeFromShape(logShape);
-        if (logShape.length <= 1 && size <= maxTexSize) {
-          return [1, size];
-        } else if (
-          logShape.length === 2 &&
-          logShape[0] <= maxTexSize &&
-          logShape[1] <= maxTexSize
-        ) {
-          return logShape;
-        } else if (
-          logShape.length === 3 &&
-          logShape[0] * logShape[1] <= maxTexSize &&
-          logShape[2] <= maxTexSize
-        ) {
-          return [logShape[0] * logShape[1], logShape[2]];
-        } else if (
-          logShape.length === 3 &&
-          logShape[0] <= maxTexSize &&
-          logShape[1] * logShape[2] <= maxTexSize
-        ) {
-          return [logShape[0], logShape[1] * logShape[2]];
-        } else if (
-          logShape.length === 4 &&
-          logShape[0] * logShape[1] * logShape[2] <= maxTexSize &&
-          logShape[3] <= maxTexSize
-        ) {
-          return [logShape[0] * logShape[1] * logShape[2], logShape[3]];
-        } else if (
-          logShape.length === 4 &&
-          logShape[0] <= maxTexSize &&
-          logShape[1] * logShape[2] * logShape[3] <= maxTexSize
-        ) {
-          return [logShape[0], logShape[1] * logShape[2] * logShape[3]];
-        } else {
-          if (isPacked) {
-            // For packed textures size equals the number of channels required to
-            // accommodate the texture data. However in order to squarify such that
-            // inner dimensions stay even, we rewrite size to equal the number of
-            // texels. Then in the return statement we rehydrate the squarified
-            // dimensions to channel units.
-            const batchDim = getBatchDim(logShape);
-            let rows = 2,
-              cols = 2;
-            if (logShape.length) {
-              [rows, cols] = getRowsCols(logShape);
-            }
-            size = batchDim * (rows / 2) * (cols / 2);
-            return dist["util"].sizeToSquarishShape(size).map((d) => d * 2);
-          }
-          return dist["util"].sizeToSquarishShape(size);
-        }
-      }
-      function isEven(n) {
-        return n % 2 === 0;
-      }
-      /**
-       * This determines whether reshaping a packed texture requires rearranging
-       * the data within the texture, assuming 2x2 packing.
-       */
-      function isReshapeFree(shape1, shape2) {
-        shape1 = shape1.slice(-2);
-        shape2 = shape2.slice(-2);
-        if (dist["util"].arraysEqual(shape1, shape2)) {
-          return true;
-        }
-        if (!shape1.length || !shape2.length) {
-          // One of the shapes is a scalar.
-          return true;
-        }
-        if (shape1[0] === 0 || shape1[1] === 0 || shape2[0] === 0 || shape2[1] === 0) {
-          return true;
-        }
-        if (shape1.length !== shape2.length) {
-          // One of the shapes is a vector.
-          const shape1Cols = shape1.slice(-1)[0];
-          const shape2Cols = shape2.slice(-1)[0];
-          if (shape1Cols === shape2Cols) {
-            return true;
-          }
-          if (isEven(shape1Cols) && isEven(shape2Cols) && (shape1[0] === 1 || shape2[0] === 1)) {
-            return true;
-          }
-        }
-        return shape1[1] === shape2[1] && isEven(shape1[0]) && isEven(shape2[0]);
-      }
-      // We cache webgl params because the environment gets reset between
-      // unit tests and we don't want to constantly query the WebGLContext for
-      // MAX_TEXTURE_SIZE.
-      let MAX_TEXTURE_SIZE;
-      let MAX_TEXTURES_IN_SHADER;
-      function getWebGLMaxTextureSize(webGLVersion) {
-        if (MAX_TEXTURE_SIZE == null) {
-          const gl = getWebGLContext(webGLVersion);
-          MAX_TEXTURE_SIZE = gl.getParameter(gl.MAX_TEXTURE_SIZE);
-        }
-        return MAX_TEXTURE_SIZE;
-      }
-      function resetMaxTextureSize() {
-        MAX_TEXTURE_SIZE = null;
-      }
-      function resetMaxTexturesInShader() {
-        MAX_TEXTURES_IN_SHADER = null;
-      }
-      function getMaxTexturesInShader(webGLVersion) {
-        if (MAX_TEXTURES_IN_SHADER == null) {
-          const gl = getWebGLContext(webGLVersion);
-          MAX_TEXTURES_IN_SHADER = gl.getParameter(gl.MAX_TEXTURE_IMAGE_UNITS);
-        }
-        // We cap at 16 to avoid spurious runtime "memory exhausted" error.
-        return Math.min(16, MAX_TEXTURES_IN_SHADER);
-      }
-      function getWebGLDisjointQueryTimerVersion(webGLVersion) {
-        if (webGLVersion === 0) {
-          return 0;
-        }
-        let queryTimerVersion;
-        const gl = getWebGLContext(webGLVersion);
-        if (hasExtension(gl, "EXT_disjoint_timer_query_webgl2") && webGLVersion === 2) {
-          queryTimerVersion = 2;
-        } else if (hasExtension(gl, "EXT_disjoint_timer_query")) {
-          queryTimerVersion = 1;
-        } else {
-          queryTimerVersion = 0;
-        }
-        return queryTimerVersion;
-      }
-      function hasExtension(gl, extensionName) {
-        const ext = gl.getExtension(extensionName);
-        return ext != null;
-      }
-      function isWebGLVersionEnabled(webGLVersion) {
-        try {
-          const gl = getWebGLContext(webGLVersion);
-          if (gl != null) {
-            return true;
-          }
-        } catch (e) {
-          return false;
-        }
-        return false;
-      }
-      function isCapableOfRenderingToFloatTexture(webGLVersion) {
-        if (webGLVersion === 0) {
-          return false;
-        }
-        const gl = getWebGLContext(webGLVersion);
-        if (webGLVersion === 1) {
-          if (!hasExtension(gl, "OES_texture_float")) {
-            return false;
-          }
-        } else {
-          if (!hasExtension(gl, "EXT_color_buffer_float")) {
-            return false;
-          }
-        }
-        const isFrameBufferComplete = createFloatTextureAndBindToFramebuffer(gl);
-        return isFrameBufferComplete;
-      }
-      /**
-       * Check if we can download values from a float/half-float texture.
-       *
-       * Note that for performance reasons we use binding a texture to a framebuffer
-       * as a proxy for ability to download float values later using readPixels. The
-       * texture params of this texture will not match those in readPixels exactly
-       * but if we are unable to bind some kind of float texture to the frameBuffer
-       * then we definitely will not be able to read float values from it.
-       */
-      function isDownloadFloatTextureEnabled(webGLVersion) {
-        if (webGLVersion === 0) {
-          return false;
-        }
-        const gl = getWebGLContext(webGLVersion);
-        if (webGLVersion === 1) {
-          if (!hasExtension(gl, "OES_texture_float")) {
-            return false;
-          }
-          if (!hasExtension(gl, "WEBGL_color_buffer_float")) {
-            return false;
-          }
-        } else {
-          if (hasExtension(gl, "EXT_color_buffer_float")) {
-            return createFloatTextureAndBindToFramebuffer(gl);
-          }
-          const COLOR_BUFFER_HALF_FLOAT = "EXT_color_buffer_half_float";
-          if (hasExtension(gl, COLOR_BUFFER_HALF_FLOAT)) {
-            const textureHalfFloatExtension = gl.getExtension(COLOR_BUFFER_HALF_FLOAT);
-            return createHalfFloatTextureAndBindToFramebuffer(gl, textureHalfFloatExtension);
-          }
-          return false;
-        }
-        const isFrameBufferComplete = createFloatTextureAndBindToFramebuffer(gl);
-        return isFrameBufferComplete;
-      }
-      function createFloatTextureAndBindToFramebuffer(gl) {
-        const texConfig = getTextureConfig(gl);
-        const texture = gl.createTexture();
-        gl.bindTexture(gl.TEXTURE_2D, texture);
-        const width = 1;
-        const height = 1;
-        gl.texImage2D(
-          gl.TEXTURE_2D,
-          0,
-          texConfig.internalFormatFloat,
-          width,
-          height,
-          0,
-          texConfig.textureFormatFloat,
-          texConfig.textureTypeFloat,
-          null
-        );
-        const frameBuffer = gl.createFramebuffer();
-        gl.bindFramebuffer(gl.FRAMEBUFFER, frameBuffer);
-        gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);
-        const isFrameBufferComplete =
-          gl.checkFramebufferStatus(gl.FRAMEBUFFER) === gl.FRAMEBUFFER_COMPLETE;
-        gl.bindTexture(gl.TEXTURE_2D, null);
-        gl.bindFramebuffer(gl.FRAMEBUFFER, null);
-        gl.deleteTexture(texture);
-        gl.deleteFramebuffer(frameBuffer);
-        return isFrameBufferComplete;
-      }
-      function createHalfFloatTextureAndBindToFramebuffer(
-        // tslint:disable-next-line:no-any
-        gl,
-        textureHalfFloatExtension
-      ) {
-        const texConfig = getTextureConfig(gl, textureHalfFloatExtension);
-        const texture = gl.createTexture();
-        gl.bindTexture(gl.TEXTURE_2D, texture);
-        const width = 1;
-        const height = 1;
-        gl.texImage2D(
-          gl.TEXTURE_2D,
-          0,
-          texConfig.internalFormatHalfFloat,
-          width,
-          height,
-          0,
-          texConfig.textureFormatFloat,
-          texConfig.textureTypeHalfFloat,
-          null
-        );
-        const frameBuffer = gl.createFramebuffer();
-        gl.bindFramebuffer(gl.FRAMEBUFFER, frameBuffer);
-        gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);
-        const isFrameBufferComplete =
-          gl.checkFramebufferStatus(gl.FRAMEBUFFER) === gl.FRAMEBUFFER_COMPLETE;
-        gl.bindTexture(gl.TEXTURE_2D, null);
-        gl.bindFramebuffer(gl.FRAMEBUFFER, null);
-        gl.deleteTexture(texture);
-        gl.deleteFramebuffer(frameBuffer);
-        return isFrameBufferComplete;
-      }
-      function isWebGLFenceEnabled(webGLVersion) {
-        if (webGLVersion !== 2) {
-          return false;
-        }
-        const gl = getWebGLContext(webGLVersion);
-        // tslint:disable-next-line:no-any
-        const isEnabled = gl.fenceSync != null;
-        return isEnabled;
-      }
-      //# sourceMappingURL=webgl_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/flags_webgl.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const ENV = Object(dist["env"])();
-      /**
-       * This file contains WebGL-specific flag registrations.
-       */
-      /**
-       * True if WebGL is supported.
-       */
-      ENV.registerFlag("HAS_WEBGL", () => ENV.getNumber("WEBGL_VERSION") > 0);
-      /** 0: No WebGL, 1: WebGL 1.0, 2: WebGL 2.0. */
-      ENV.registerFlag("WEBGL_VERSION", () => {
-        if (isWebGLVersionEnabled(2)) {
-          return 2;
-        } else if (isWebGLVersionEnabled(1)) {
-          return 1;
-        }
-        return 0;
-      });
-      ENV.registerFlag("WEBGL_BUFFER_SUPPORTED", () => ENV.get("WEBGL_VERSION") === 2);
-      /** Whether the WebGL backend will sometimes forward ops to the CPU. */
-      ENV.registerFlag("WEBGL_CPU_FORWARD", () => true);
-      /** Whether the WebGL backend will always use f16 textures for rendering. */
-      ENV.registerFlag("WEBGL_FORCE_F16_TEXTURES", () => false);
-      /** Whether to turn all packing related flags on. */
-      ENV.registerFlag("WEBGL_PACK", () => ENV.getBool("HAS_WEBGL"));
-      /** Whether we will pack the batchnormalization op. */
-      ENV.registerFlag("WEBGL_PACK_NORMALIZATION", () => ENV.getBool("WEBGL_PACK"));
-      /** Whether we will pack the clip op. */
-      ENV.registerFlag("WEBGL_PACK_CLIP", () => ENV.getBool("WEBGL_PACK"));
-      /** Whether we will pack the depthwise conv op. */
-      // TODO: https://github.com/tensorflow/tfjs/issues/1679
-      ENV.registerFlag("WEBGL_PACK_DEPTHWISECONV", () => false);
-      /** Whether we will pack binary ops. */
-      ENV.registerFlag("WEBGL_PACK_BINARY_OPERATIONS", () => ENV.getBool("WEBGL_PACK"));
-      /** Whether we will pack unary ops. */
-      ENV.registerFlag("WEBGL_PACK_UNARY_OPERATIONS", () => ENV.getBool("WEBGL_PACK"));
-      /** Whether we will pack array ops. */
-      ENV.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS", () => ENV.getBool("WEBGL_PACK"));
-      /** Whether we will pack image ops. */
-      ENV.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS", () => ENV.getBool("WEBGL_PACK"));
-      /** Whether we will pack reduce ops. */
-      ENV.registerFlag("WEBGL_PACK_REDUCE", () => ENV.getBool("WEBGL_PACK"));
-      /** Whether packed WebGL kernels lazily unpack their outputs. */
-      ENV.registerFlag("WEBGL_LAZILY_UNPACK", () => ENV.getBool("WEBGL_PACK"));
-      /** Whether we will use the im2col algorithm to speed up convolutions. */
-      ENV.registerFlag("WEBGL_CONV_IM2COL", () => ENV.getBool("WEBGL_PACK"));
-      /** The maximum texture dimension. */
-      ENV.registerFlag("WEBGL_MAX_TEXTURE_SIZE", () =>
-        getWebGLMaxTextureSize(ENV.getNumber("WEBGL_VERSION"))
-      );
-      /** The maximum texture dimension. */
-      ENV.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER", () =>
-        getMaxTexturesInShader(ENV.getNumber("WEBGL_VERSION"))
-      );
-      /**
-       * The disjoint_query_timer extension version.
-       * 0: disabled, 1: EXT_disjoint_timer_query, 2:
-       * EXT_disjoint_timer_query_webgl2.
-       * In Firefox with WebGL 2.0,
-       * EXT_disjoint_timer_query_webgl2 is not available, so we must use the
-       * WebGL 1.0 extension.
-       */
-      ENV.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION", () => {
-        const webGLVersion = ENV.getNumber("WEBGL_VERSION");
-        if (webGLVersion === 0) {
-          return 0;
-        }
-        return getWebGLDisjointQueryTimerVersion(webGLVersion);
-      });
-      /**
-       * Whether the timer object from the disjoint_query_timer extension gives
-       * timing information that is reliable.
-       */
-      ENV.registerFlag(
-        "WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",
-        () =>
-          ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") > 0 &&
-          !dist["device_util"].isMobile()
-      );
-      /**
-       * Whether the device is physically capable of rendering to float32 textures.
-       */
-      ENV.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE", () =>
-        isCapableOfRenderingToFloatTexture(ENV.getNumber("WEBGL_VERSION"))
-      );
-      /**
-       * Whether rendering to float32 textures is enabled. If disabled, renders to
-       * float16 textures.
-       */
-      ENV.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED", () => {
-        return ENV.getBool("WEBGL_FORCE_F16_TEXTURES")
-          ? false
-          : ENV.getBool("WEBGL_RENDER_FLOAT32_CAPABLE");
-      });
-      /**
-       * Whether downloading float textures is enabled (16 or 32 bit). If disabled,
-       * uses IEEE 754 encoding of the float32 values to 4 uint8 when downloading.
-       */
-      ENV.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED", () =>
-        isDownloadFloatTextureEnabled(ENV.getNumber("WEBGL_VERSION"))
-      );
-      /** Whether the fence API is available. */
-      ENV.registerFlag("WEBGL_FENCE_API_ENABLED", () =>
-        isWebGLFenceEnabled(ENV.getNumber("WEBGL_VERSION"))
-      );
-      /**
-       * Tensors with size <= than this will be uploaded as uniforms, not textures.
-       */
-      ENV.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM", () => {
-        // Use uniform uploads only when 32bit floats are supported. In
-        // 16bit
-        // environments there are problems with comparing a 16bit texture value
-        // with a 32bit uniform value.
-        const useUniforms = ENV.getBool("WEBGL_RENDER_FLOAT32_ENABLED");
-        return useUniforms ? 4 : 0;
-      });
-      //# sourceMappingURL=flags_webgl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/addn_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class AddNProgram {
-        constructor(outputShape, shapes) {
-          this.outputShape = [];
-          this.outputShape = outputShape;
-          this.variableNames = shapes.map((_, i) => `T${i}`);
-          const snippets = [];
-          // Get target elements from every input tensor.
-          this.variableNames.forEach((variable) => {
-            snippets.push(`float v${variable} = get${variable}AtOutCoords();`);
-          });
-          // Calculate the sum of all elements.
-          const operation = this.variableNames
-            .map((variable) => {
-              return `v${variable}`;
-            })
-            .join(" + ");
-          this.userCode = `
-      void main() {
-        ${snippets.join("\n        ")}
-
-        float result = ${operation};
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=addn_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/addn_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class AddNPackedProgram {
-        constructor(outputShape, shapes) {
-          this.outputShape = [];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = outputShape;
-          this.variableNames = shapes.map((_, i) => `T${i}`);
-          const snippets = [];
-          // Get target elements from every input tensor.
-          this.variableNames.forEach((variable) => {
-            snippets.push(`vec4 v${variable} = get${variable}AtOutCoords();`);
-          });
-          // Calculate the sum of all elements.
-          const operation = this.variableNames
-            .map((variable) => {
-              return `v${variable}`;
-            })
-            .join(" + ");
-          this.userCode = `
-      void main() {
-        ${snippets.join("\n        ")}
-
-        vec4 result = ${operation};
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=addn_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/argminmax_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ArgMinMaxProgram {
-        constructor(reduceInfo, op, firstPass) {
-          this.variableNames = ["A"];
-          const windowSize = reduceInfo.windowSize;
-          const batchSize = reduceInfo.batchSize;
-          const inSize = reduceInfo.inSize;
-          const outSize = Math.ceil(inSize / windowSize);
-          if (!firstPass) {
-            this.variableNames.push("bestIndicesA");
-          }
-          this.outputShape = [batchSize, outSize];
-          const compOp = op === "max" ? ">" : "<";
-          const indexSnippet = firstPass
-            ? "inOffset + i;"
-            : "round(getBestIndicesA(batch, inOffset + i));";
-          this.userCode = `
-      void main() {
-        ivec2 coords = getOutputCoords();
-        int batch = coords[0];
-        int outIdx = coords[1];
-        int inOffset = outIdx * ${windowSize};
-
-        int bestIndex = inOffset;
-        float bestValue = getA(batch, bestIndex);
-
-        for (int i = 0; i < ${windowSize}; i++) {
-          int inIdx = ${indexSnippet};
-          float candidate = getA(batch, inIdx);
-          if (candidate ${compOp} bestValue) {
-            bestValue = candidate;
-            bestIndex = inIdx;
-          }
-        }
-        setOutput(float(bestIndex));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=argminmax_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/packing_util.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      function getVecChannels(name, rank) {
-        return ["x", "y", "z", "w", "u", "v"].slice(0, rank).map((d) => `${name}.${d}`);
-      }
-      function getChannels(name, rank) {
-        if (rank === 1) {
-          return [name];
-        }
-        return getVecChannels(name, rank);
-      }
-      function getSourceCoords(rank, dims) {
-        if (rank === 1) {
-          return "rc";
-        }
-        let coords = "";
-        for (let i = 0; i < rank; i++) {
-          coords += dims[i];
-          if (i < rank - 1) {
-            coords += ",";
-          }
-        }
-        return coords;
-      }
-      //# sourceMappingURL=packing_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/glsl_version.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function getGlslDifferences() {
-        let version;
-        let attribute;
-        let varyingVs;
-        let varyingFs;
-        let texture2D;
-        let output;
-        let defineOutput;
-        let defineSpecialNaN;
-        let defineSpecialInf;
-        let defineRound;
-        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 2) {
-          version = "#version 300 es";
-          attribute = "in";
-          varyingVs = "out";
-          varyingFs = "in";
-          texture2D = "texture";
-          output = "outputColor";
-          defineOutput = "out vec4 outputColor;";
-          // Use custom isnan definition to work across differences between
-          // implementations on various platforms. While this should happen in ANGLE
-          // we still see differences between android and windows (on chrome) when
-          // using isnan directly.
-          defineSpecialNaN = `
-      bool isnan_custom(float val) {
-        return (val > 0.0 || val < 0.0) ? false : val != 0.0;
-      }
-
-      bvec4 isnan_custom(vec4 val) {
-        return bvec4(isnan_custom(val.x),
-          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
-      }
-
-      #define isnan(value) isnan_custom(value)
-    `;
-          // In webgl 2 we do not need to specify a custom isinf so there is no
-          // need for a special INFINITY constant.
-          defineSpecialInf = ``;
-          defineRound = `
-      #define round(value) newRound(value)
-      int newRound(float value) {
-        return int(floor(value + 0.5));
-      }
-
-      ivec4 newRound(vec4 value) {
-        return ivec4(floor(value + vec4(0.5)));
-      }
-    `;
-        } else {
-          version = "";
-          attribute = "attribute";
-          varyingVs = "varying";
-          varyingFs = "varying";
-          texture2D = "texture2D";
-          output = "gl_FragColor";
-          defineOutput = "";
-          // WebGL1 has no built in isnan so we define one here.
-          defineSpecialNaN = `
-      #define isnan(value) isnan_custom(value)
-      bool isnan_custom(float val) {
-        return (val > 0. || val < 1. || val == 0.) ? false : true;
-      }
-      bvec4 isnan_custom(vec4 val) {
-        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
-      }
-    `;
-          defineSpecialInf = `
-      uniform float INFINITY;
-
-      bool isinf(float val) {
-        return abs(val) == INFINITY;
-      }
-      bvec4 isinf(vec4 val) {
-        return equal(abs(val), vec4(INFINITY));
-      }
-    `;
-          defineRound = `
-      int round(float value) {
-        return int(floor(value + 0.5));
-      }
-
-      ivec4 round(vec4 value) {
-        return ivec4(floor(value + vec4(0.5)));
-      }
-    `;
-        }
-        return {
-          version,
-          attribute,
-          varyingVs,
-          varyingFs,
-          texture2D,
-          output,
-          defineOutput,
-          defineSpecialNaN,
-          defineSpecialInf,
-          defineRound,
-        };
-      }
-      //# sourceMappingURL=glsl_version.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/shader_compiler_util.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /**
-       * Produces GLSL code that derives logical coordinates from a flat
-       * index. The code performs integer division with each stride and decrements
-       * the index until the index equals the final dimension coordinate.
-       */
-      function getLogicalCoordinatesFromFlatIndex(coords, shape, index = "index") {
-        const strides = dist["util"].computeStrides(shape);
-        return strides
-          .map((stride, i) => {
-            const line1 = `int ${coords[i]} = ${index} / ${stride}`;
-            const line2 =
-              i === strides.length - 1
-                ? `int ${coords[i + 1]} = ${index} - ${coords[i]} * ${stride}`
-                : `index -= ${coords[i]} * ${stride}`;
-            return `${line1}; ${line2};`;
-          })
-          .join("");
-      }
-      function buildVec(x) {
-        if (x.length === 1) {
-          return `${x[0]}`;
-        }
-        return `vec${x.length}(${x.join(",")})`;
-      }
-      /**
-       * Produces GLSL code that computes the dot product of the input x and y
-       * vectors. Handles splitting inputs into increments of vec4s when necessary.
-       */
-      function dotify(x, y) {
-        if (x.length !== y.length) {
-          throw new Error(
-            `Vectors to be dotted must be of the same length -` + `got ${x.length} and ${y.length}`
-          );
-        }
-        const slices = [];
-        const nearestVec4 = Math.floor(x.length / 4);
-        const nearestVec4Remainder = x.length % 4;
-        for (let i = 0; i < nearestVec4; i++) {
-          const xSlice = x.slice(i * 4, i * 4 + 4);
-          const ySlice = y.slice(i * 4, i * 4 + 4);
-          slices.push(`${buildVec(xSlice)}, ${buildVec(ySlice)}`);
-        }
-        if (nearestVec4Remainder !== 0) {
-          let xSlice = x.slice(nearestVec4 * 4);
-          let ySlice = y.slice(nearestVec4 * 4);
-          if (xSlice.length === 1) {
-            xSlice = xSlice.map((d) => `float(${d})`);
-            ySlice = ySlice.map((d) => `float(${d})`);
-          }
-          slices.push(`${buildVec(xSlice)}, ${buildVec(ySlice)}`);
-        }
-        return slices.map((d, i) => `dot(${d})`).join("+");
-      }
-      /**
-       * Produces GLSL that computes the flat index from 3D coordinates.
-       */
-      function getFlatIndexFrom3D(shape) {
-        const strides = dist["util"].computeStrides(shape).map((d) => d.toString());
-        return `
-  int getFlatIndex(ivec3 coords) {
-    return coords.x * ${strides[0]} + coords.y * ${strides[1]} + coords.z;
-  }
-`;
-      }
-      const ENCODE_FLOAT_SNIPPET = `
-  const float FLOAT_MAX = 1.70141184e38;
-  const float FLOAT_MIN = 1.17549435e-38;
-
-  lowp vec4 encode_float(highp float v) {
-    if (isnan(v)) {
-      return vec4(255, 255, 255, 255);
-    }
-
-    highp float av = abs(v);
-
-    if(av < FLOAT_MIN) {
-      return vec4(0.0, 0.0, 0.0, 0.0);
-    } else if(v > FLOAT_MAX) {
-      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
-    } else if(v < -FLOAT_MAX) {
-      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
-    }
-
-    highp vec4 c = vec4(0,0,0,0);
-
-    highp float e = floor(log2(av));
-    highp float m = exp2(fract(log2(av))) - 1.0;
-
-    c[2] = floor(128.0 * m);
-    m -= c[2] / 128.0;
-    c[1] = floor(32768.0 * m);
-    m -= c[1] / 32768.0;
-    c[0] = floor(8388608.0 * m);
-
-    highp float ebias = e + 127.0;
-    c[3] = floor(ebias / 2.0);
-    ebias -= c[3] * 2.0;
-    c[2] += floor(ebias) * 128.0;
-
-    c[3] += 128.0 * step(0.0, -v);
-
-    return c / 255.0;
-  }
-`;
-      //# sourceMappingURL=shader_compiler_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/shader_compiler.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const { getBroadcastDims } = dist["backend_util"];
-
-      function makeShader(inputsInfo, outputShape, userCode, usesPackedTextures) {
-        const prefixSnippets = [];
-        inputsInfo.forEach((x) => {
-          const size = dist["util"].sizeFromShape(x.shapeInfo.logicalShape);
-          // Snippet when we decided to upload the values as uniform.
-          if (x.shapeInfo.isUniform) {
-            prefixSnippets.push(`uniform float ${x.name}${size > 1 ? `[${size}]` : ""};`);
-          } else {
-            prefixSnippets.push(`uniform sampler2D ${x.name};`);
-            prefixSnippets.push(`uniform int offset${x.name};`);
-          }
-        });
-        const inputPrefixSnippet = prefixSnippets.join("\n");
-        const inputSamplingSnippet = inputsInfo
-          .map((x) => getInputSamplingSnippet(x, outputShape, usesPackedTextures))
-          .join("\n");
-        const outTexShape = outputShape.texShape;
-        const glsl = getGlslDifferences();
-        const floatTextureSampleSnippet = getFloatTextureSampleSnippet(glsl);
-        let outputSamplingSnippet;
-        let floatTextureSetOutputSnippet;
-        let shaderPrefix = getShaderPrefix(glsl);
-        if (outputShape.isPacked) {
-          outputSamplingSnippet = getPackedOutputSamplingSnippet(
-            outputShape.logicalShape,
-            outTexShape
-          );
-          floatTextureSetOutputSnippet = getFloatTextureSetRGBASnippet(glsl);
-        } else {
-          outputSamplingSnippet = getOutputSamplingSnippet(outputShape.logicalShape, outTexShape);
-          floatTextureSetOutputSnippet = getFloatTextureSetRSnippet(glsl);
-        }
-        if (usesPackedTextures) {
-          shaderPrefix += SHADER_PACKED_PREFIX;
-        }
-        const source = [
-          shaderPrefix,
-          floatTextureSampleSnippet,
-          floatTextureSetOutputSnippet,
-          inputPrefixSnippet,
-          outputSamplingSnippet,
-          inputSamplingSnippet,
-          userCode,
-        ].join("\n");
-        return source;
-      }
-      function getSamplerFromInInfo(inInfo) {
-        const shape = inInfo.shapeInfo.logicalShape;
-        switch (shape.length) {
-          case 0:
-            return getSamplerScalar(inInfo);
-          case 1:
-            return getSampler1D(inInfo);
-          case 2:
-            return getSampler2D(inInfo);
-          case 3:
-            return getSampler3D(inInfo);
-          case 4:
-            return getSampler4D(inInfo);
-          case 5:
-            return getSampler5D(inInfo);
-          case 6:
-            return getSampler6D(inInfo);
-          default:
-            throw new Error(`${shape.length}-D input sampling` + ` is not yet supported`);
-        }
-      }
-      function getPackedSamplerFromInInfo(inInfo) {
-        const shape = inInfo.shapeInfo.logicalShape;
-        switch (shape.length) {
-          case 0:
-            return getPackedSamplerScalar(inInfo);
-          case 1:
-            return getPackedSampler1D(inInfo);
-          case 2:
-            return getPackedSampler2D(inInfo);
-          case 3:
-            return getPackedSampler3D(inInfo);
-          default:
-            return getPackedSamplerND(inInfo);
-        }
-      }
-      function getInputSamplingSnippet(inInfo, outShapeInfo, usesPackedTextures = false) {
-        let res = "";
-        if (usesPackedTextures) {
-          res += getPackedSamplerFromInInfo(inInfo);
-        } else {
-          res += getSamplerFromInInfo(inInfo);
-        }
-        const inShape = inInfo.shapeInfo.logicalShape;
-        const outShape = outShapeInfo.logicalShape;
-        if (inShape.length <= outShape.length) {
-          if (usesPackedTextures) {
-            res += getPackedSamplerAtOutputCoords(inInfo, outShapeInfo);
-          } else {
-            res += getSamplerAtOutputCoords(inInfo, outShapeInfo);
-          }
-        }
-        return res;
-      }
-      function getPackedOutputSamplingSnippet(outShape, outTexShape) {
-        switch (outShape.length) {
-          case 0:
-            return getOutputScalarCoords();
-          case 1:
-            return getOutputPacked1DCoords(outShape, outTexShape);
-          case 2:
-            return getOutputPacked2DCoords(outShape, outTexShape);
-          case 3:
-            return getOutputPacked3DCoords(outShape, outTexShape);
-          default:
-            return getOutputPackedNDCoords(outShape, outTexShape);
-        }
-      }
-      function getOutputSamplingSnippet(outShape, outTexShape) {
-        switch (outShape.length) {
-          case 0:
-            return getOutputScalarCoords();
-          case 1:
-            return getOutput1DCoords(outShape, outTexShape);
-          case 2:
-            return getOutput2DCoords(outShape, outTexShape);
-          case 3:
-            return getOutput3DCoords(outShape, outTexShape);
-          case 4:
-            return getOutput4DCoords(outShape, outTexShape);
-          case 5:
-            return getOutput5DCoords(outShape, outTexShape);
-          case 6:
-            return getOutput6DCoords(outShape, outTexShape);
-          default:
-            throw new Error(`${outShape.length}-D output sampling is not yet supported`);
-        }
-      }
-      function getFloatTextureSampleSnippet(glsl) {
-        return `
-    float sampleTexture(sampler2D textureSampler, vec2 uv) {
-      return ${glsl.texture2D}(textureSampler, uv).r;
-    }
-  `;
-      }
-      function getFloatTextureSetRSnippet(glsl) {
-        return `
-    void setOutput(float val) {
-      ${glsl.output} = vec4(val, 0, 0, 0);
-    }
-  `;
-      }
-      function getFloatTextureSetRGBASnippet(glsl) {
-        return `
-    void setOutput(vec4 val) {
-      ${glsl.output} = val;
-    }
-  `;
-      }
-      function getShaderPrefix(glsl) {
-        const SHADER_PREFIX = `${glsl.version}
-    precision highp float;
-    precision highp int;
-    precision highp sampler2D;
-    ${glsl.varyingFs} vec2 resultUV;
-    ${glsl.defineOutput}
-    const vec2 halfCR = vec2(0.5, 0.5);
-
-    struct ivec5
-    {
-      int x;
-      int y;
-      int z;
-      int w;
-      int u;
-    };
-
-    struct ivec6
-    {
-      int x;
-      int y;
-      int z;
-      int w;
-      int u;
-      int v;
-    };
-
-    uniform float NAN;
-    ${glsl.defineSpecialNaN}
-    ${glsl.defineSpecialInf}
-    ${glsl.defineRound}
-
-    int imod(int x, int y) {
-      return x - y * (x / y);
-    }
-
-    int idiv(int a, int b, float sign) {
-      int res = a / b;
-      int mod = imod(a, b);
-      if (sign < 0. && mod != 0) {
-        res -= 1;
-      }
-      return res;
-    }
-
-    //Based on the work of Dave Hoskins
-    //https://www.shadertoy.com/view/4djSRW
-    #define HASHSCALE1 443.8975
-    float random(float seed){
-      vec2 p = resultUV * seed;
-      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);
-      p3 += dot(p3, p3.yzx + 19.19);
-      return fract((p3.x + p3.y) * p3.z);
-    }
-
-    ${SAMPLE_1D_SNIPPET}
-    ${SAMPLE_2D_SNIPPET}
-    ${SAMPLE_3D_SNIPPET}
-  `;
-        return SHADER_PREFIX;
-      }
-      const SAMPLE_1D_SNIPPET = `
-vec2 uvFromFlat(int texNumR, int texNumC, int index) {
-  int texR = index / texNumC;
-  int texC = index - texR * texNumC;
-  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
-}
-vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
-  int texelIndex = index / 2;
-  int texR = texelIndex / texNumC;
-  int texC = texelIndex - texR * texNumC;
-  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
-}
-`;
-      const SAMPLE_2D_SNIPPET = `
-vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
-  int texNumC, int row, int col) {
-  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
-  int texR = texelIndex / texNumC;
-  int texC = texelIndex - texR * texNumC;
-  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
-}
-`;
-      const SAMPLE_3D_SNIPPET = `
-vec2 packedUVfrom3D(int texNumR, int texNumC,
-    int texelsInBatch, int texelsInLogicalRow, int b,
-    int row, int col) {
-  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
-  int texR = index / texNumC;
-  int texC = index - texR * texNumC;
-  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
-}
-`;
-      const SHADER_PACKED_PREFIX = `
-  float getChannel(vec4 frag, vec2 innerDims) {
-    vec2 modCoord = mod(innerDims, 2.);
-    return modCoord.x == 0. ?
-      (modCoord.y == 0. ? frag.r : frag.g) :
-      (modCoord.y == 0. ? frag.b : frag.a);
-  }
-  float getChannel(vec4 frag, int dim) {
-    float modCoord = mod(float(dim), 2.);
-    return modCoord == 0. ? frag.r : frag.g;
-  }
-`;
-      function getOutputScalarCoords() {
-        return `
-    int getOutputCoords() {
-      return 0;
-    }
-  `;
-      }
-      function getOutputPacked1DCoords(shape, texShape) {
-        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
-        if (packedTexShape[0] === 1) {
-          return `
-      int getOutputCoords() {
-        return 2 * int(resultUV.x * ${packedTexShape[1]}.0);
-      }
-    `;
-        }
-        if (packedTexShape[1] === 1) {
-          return `
-      int getOutputCoords() {
-        return 2 * int(resultUV.y * ${packedTexShape[0]}.0);
-      }
-    `;
-        }
-        return `
-    int getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
-      return 2 * (resTexRC.x * ${packedTexShape[1]} + resTexRC.y);
-    }
-  `;
-      }
-      function getOutput1DCoords(shape, texShape) {
-        if (texShape[0] === 1) {
-          return `
-      int getOutputCoords() {
-        return int(resultUV.x * ${texShape[1]}.0);
-      }
-    `;
-        }
-        if (texShape[1] === 1) {
-          return `
-      int getOutputCoords() {
-        return int(resultUV.y * ${texShape[0]}.0);
-      }
-    `;
-        }
-        return `
-    int getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-                             vec2(${texShape[0]}, ${texShape[1]}));
-      return resTexRC.x * ${texShape[1]} + resTexRC.y;
-    }
-  `;
-      }
-      function getOutputPacked3DCoords(shape, texShape) {
-        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
-        const texelsInLogicalRow = Math.ceil(shape[2] / 2);
-        const texelsInBatch = texelsInLogicalRow * Math.ceil(shape[1] / 2);
-        return `
-    ivec3 getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
-      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;
-
-      int b = index / ${texelsInBatch};
-      index -= b * ${texelsInBatch};
-
-      int r = 2 * (index / ${texelsInLogicalRow});
-      int c = imod(index, ${texelsInLogicalRow}) * 2;
-
-      return ivec3(b, r, c);
-    }
-  `;
-      }
-      function getOutput3DCoords(shape, texShape) {
-        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(["r", "c", "d"], shape);
-        return `
-    ivec3 getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-                             vec2(${texShape[0]}, ${texShape[1]}));
-      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
-      ${coordsFromIndexSnippet}
-      return ivec3(r, c, d);
-    }
-  `;
-      }
-      function getOutputPackedNDCoords(shape, texShape) {
-        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
-        const texelsInLogicalRow = Math.ceil(shape[shape.length - 1] / 2);
-        const texelsInBatch = texelsInLogicalRow * Math.ceil(shape[shape.length - 2] / 2);
-        let texelsInBatchN = texelsInBatch;
-        let batches = ``;
-        let coords = "b, r, c";
-        for (let b = 2; b < shape.length - 1; b++) {
-          texelsInBatchN *= shape[shape.length - b - 1];
-          batches =
-            `
-      int b${b} = index / ${texelsInBatchN};
-      index -= b${b} * ${texelsInBatchN};
-    ` + batches;
-          coords = `b${b}, ` + coords;
-        }
-        return `
-    ivec${shape.length} getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
-      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;
-
-      ${batches}
-
-      int b = index / ${texelsInBatch};
-      index -= b * ${texelsInBatch};
-
-      int r = 2 * (index / ${texelsInLogicalRow});
-      int c = imod(index, ${texelsInLogicalRow}) * 2;
-
-      return ivec${shape.length}(${coords});
-    }
-  `;
-      }
-      function getOutput4DCoords(shape, texShape) {
-        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(
-          ["r", "c", "d", "d2"],
-          shape
-        );
-        return `
-    ivec4 getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-        vec2(${texShape[0]}, ${texShape[1]}));
-      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
-      ${coordsFromIndexSnippet}
-      return ivec4(r, c, d, d2);
-    }
-  `;
-      }
-      function getOutput5DCoords(shape, texShape) {
-        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(
-          ["r", "c", "d", "d2", "d3"],
-          shape
-        );
-        return `
-    ivec5 getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${texShape[0]},
-                             ${texShape[1]}));
-
-      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
-
-      ${coordsFromIndexSnippet}
-
-      ivec5 outShape = ivec5(r, c, d, d2, d3);
-      return outShape;
-    }
-  `;
-      }
-      function getOutput6DCoords(shape, texShape) {
-        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(
-          ["r", "c", "d", "d2", "d3", "d4"],
-          shape
-        );
-        return `
-    ivec6 getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-        vec2(${texShape[0]}, ${texShape[1]}));
-      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
-
-      ${coordsFromIndexSnippet}
-
-      ivec6 result = ivec6(r, c, d, d2, d3, d4);
-      return result;
-    }
-  `;
-      }
-      function getOutputPacked2DCoords(shape, texShape) {
-        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
-        if (dist["util"].arraysEqual(shape, texShape)) {
-          return `
-      ivec2 getOutputCoords() {
-        return 2 * ivec2(resultUV.yx * vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
-      }
-    `;
-        }
-        // texels needed to accommodate a logical row
-        const texelsInLogicalRow = Math.ceil(shape[1] / 2);
-        /**
-         * getOutputCoords
-         *
-         * resTexRC: The rows and columns of the texels. If you move over one
-         * texel to the right in the packed texture, you are moving over one column
-         * (not two).
-         *
-         * index: The texel index
-         */
-        return `
-    ivec2 getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
-
-      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;
-      int r = 2 * (index / ${texelsInLogicalRow});
-      int c = imod(index, ${texelsInLogicalRow}) * 2;
-
-      return ivec2(r, c);
-    }
-  `;
-      }
-      function getOutput2DCoords(shape, texShape) {
-        if (dist["util"].arraysEqual(shape, texShape)) {
-          return `
-      ivec2 getOutputCoords() {
-        return ivec2(resultUV.yx * vec2(${texShape[0]}, ${texShape[1]}));
-      }
-    `;
-        }
-        if (shape[1] === 1) {
-          return `
-      ivec2 getOutputCoords() {
-        ivec2 resTexRC = ivec2(resultUV.yx *
-                               vec2(${texShape[0]}, ${texShape[1]}));
-        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
-        return ivec2(index, 0);
-      }
-    `;
-        }
-        if (shape[0] === 1) {
-          return `
-      ivec2 getOutputCoords() {
-        ivec2 resTexRC = ivec2(resultUV.yx *
-                               vec2(${texShape[0]}, ${texShape[1]}));
-        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
-        return ivec2(0, index);
-      }
-    `;
-        }
-        return `
-    ivec2 getOutputCoords() {
-      ivec2 resTexRC = ivec2(resultUV.yx *
-                             vec2(${texShape[0]}, ${texShape[1]}));
-      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
-      int r = index / ${shape[1]};
-      int c = index - r * ${shape[1]};
-      return ivec2(r, c);
-    }
-  `;
-      }
-      function getFlatOffsetUniformName(texName) {
-        return `offset${texName}`;
-      }
-      function getPackedSamplerScalar(inputInfo) {
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const glsl = getGlslDifferences();
-        return `
-    vec4 ${funcName}() {
-      return ${glsl.texture2D}(${texName}, halfCR);
-    }
-  `;
-      }
-      function getSamplerScalar(inputInfo) {
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        if (inputInfo.shapeInfo.isUniform) {
-          return `float ${funcName}() {return ${texName};}`;
-        }
-        const [texNumR, texNumC] = inputInfo.shapeInfo.texShape;
-        if (texNumR === 1 && texNumC === 1) {
-          return `
-      float ${funcName}() {
-        return sampleTexture(${texName}, halfCR);
-      }
-    `;
-        }
-        const [tNumR, tNumC] = inputInfo.shapeInfo.texShape;
-        const offset = getFlatOffsetUniformName(texName);
-        return `
-    float ${funcName}() {
-      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, ${offset});
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-      }
-      function getPackedSampler1D(inputInfo) {
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const texShape = inputInfo.shapeInfo.texShape;
-        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
-        const glsl = getGlslDifferences();
-        return `
-    vec4 ${funcName}(int index) {
-      vec2 uv = packedUVfrom1D(
-        ${packedTexShape[0]}, ${packedTexShape[1]}, index);
-      return ${glsl.texture2D}(${texName}, uv);
-    }
-  `;
-      }
-      function getSampler1D(inputInfo) {
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        if (inputInfo.shapeInfo.isUniform) {
-          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
-          return `
-      float ${funcName}(int index) {
-        ${getUniformSampler(inputInfo)}
-      }
-    `;
-        }
-        const texShape = inputInfo.shapeInfo.texShape;
-        const tNumR = texShape[0];
-        const tNumC = texShape[1];
-        if (tNumC === 1 && tNumR === 1) {
-          return `
-      float ${funcName}(int index) {
-        return sampleTexture(${texName}, halfCR);
-      }
-    `;
-        }
-        const offset = getFlatOffsetUniformName(texName);
-        if (tNumC === 1) {
-          return `
-      float ${funcName}(int index) {
-        vec2 uv = vec2(0.5, (float(index + ${offset}) + 0.5) / ${tNumR}.0);
-        return sampleTexture(${texName}, uv);
-      }
-    `;
-        }
-        if (tNumR === 1) {
-          return `
-      float ${funcName}(int index) {
-        vec2 uv = vec2((float(index + ${offset}) + 0.5) / ${tNumC}.0, 0.5);
-        return sampleTexture(${texName}, uv);
-      }
-    `;
-        }
-        return `
-    float ${funcName}(int index) {
-      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, index + ${offset});
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-      }
-      function getPackedSampler2D(inputInfo) {
-        const shape = inputInfo.shapeInfo.logicalShape;
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const texShape = inputInfo.shapeInfo.texShape;
-        const texNumR = texShape[0];
-        const texNumC = texShape[1];
-        const glsl = getGlslDifferences();
-        if (texShape != null && dist["util"].arraysEqual(shape, texShape)) {
-          return `
-      vec4 ${funcName}(int row, int col) {
-        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);
-
-        return ${glsl.texture2D}(${texName}, uv);
-      }
-    `;
-        }
-        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
-        const valuesPerRow = Math.ceil(shape[1] / 2);
-        return `
-    vec4 ${funcName}(int row, int col) {
-      vec2 uv = packedUVfrom2D(${valuesPerRow}, ${packedTexShape[0]}, ${packedTexShape[1]}, row, col);
-      return ${glsl.texture2D}(${texName}, uv);
-    }
-  `;
-      }
-      function getSampler2D(inputInfo) {
-        const shape = inputInfo.shapeInfo.logicalShape;
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const texShape = inputInfo.shapeInfo.texShape;
-        if (texShape != null && dist["util"].arraysEqual(shape, texShape)) {
-          const texNumR = texShape[0];
-          const texNumC = texShape[1];
-          return `
-    float ${funcName}(int row, int col) {
-      vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-        }
-        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
-        const squeezedShape = newShape;
-        if (squeezedShape.length < shape.length) {
-          const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);
-          const params = ["row", "col"];
-          return `
-      ${getSamplerFromInInfo(newInputInfo)}
-      float ${funcName}(int row, int col) {
-        return ${funcName}(${getSqueezedParams(params, keptDims)});
-      }
-    `;
-        }
-        if (inputInfo.shapeInfo.isUniform) {
-          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col) {
-        int index = round(dot(vec2(row, col), vec2(${shape[1]}, 1)));
-        ${getUniformSampler(inputInfo)}
-      }
-    `;
-        }
-        const texNumR = texShape[0];
-        const texNumC = texShape[1];
-        const offset = getFlatOffsetUniformName(texName);
-        if (texNumC === 1) {
-          // index is used directly as physical (no risk of float16 overflow).
-          return `
-    float ${funcName}(int row, int col) {
-      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));
-      vec2 uv = vec2(0.5, (index + 0.5) / ${texNumR}.0);
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-        }
-        if (texNumR === 1) {
-          // index is used directly as physical (no risk of float16 overflow).
-          return `
-    float ${funcName}(int row, int col) {
-      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));
-      vec2 uv = vec2((index + 0.5) / ${texNumC}.0, 0.5);
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-        }
-        return `
-  float ${funcName}(int row, int col) {
-    // Explicitly use integer operations as dot() only works on floats.
-    int index = row * ${shape[1]} + col + ${offset};
-    vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
-    return sampleTexture(${texName}, uv);
-  }
-`;
-      }
-      function getPackedSampler3D(inputInfo) {
-        const shape = inputInfo.shapeInfo.logicalShape;
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const texShape = inputInfo.shapeInfo.texShape;
-        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
-        if (shape[0] === 1) {
-          const squeezedShape = shape.slice(1);
-          const keptDims = [1, 2];
-          const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);
-          const params = ["b", "row", "col"];
-          return `
-        ${getPackedSamplerFromInInfo(newInputInfo)}
-        vec4 ${funcName}(int b, int row, int col) {
-          return ${funcName}(${getSqueezedParams(params, keptDims)});
-        }
-      `;
-        }
-        const texNumR = packedTexShape[0];
-        const texNumC = packedTexShape[1];
-        const valuesPerRow = Math.ceil(shape[2] / 2);
-        const texelsInBatch = valuesPerRow * Math.ceil(shape[1] / 2);
-        const glsl = getGlslDifferences();
-        return `
-    vec4 ${funcName}(int b, int row, int col) {
-      vec2 uv = packedUVfrom3D(
-        ${texNumR}, ${texNumC}, ${texelsInBatch}, ${valuesPerRow}, b, row, col);
-      return ${glsl.texture2D}(${texName}, uv);
-    }
-  `;
-      }
-      function getSampler3D(inputInfo) {
-        const shape = inputInfo.shapeInfo.logicalShape;
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const stride0 = shape[1] * shape[2];
-        const stride1 = shape[2];
-        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
-        const squeezedShape = newShape;
-        if (squeezedShape.length < shape.length) {
-          const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);
-          const params = ["row", "col", "depth"];
-          return `
-        ${getSamplerFromInInfo(newInputInfo)}
-        float ${funcName}(int row, int col, int depth) {
-          return ${funcName}(${getSqueezedParams(params, keptDims)});
-        }
-      `;
-        }
-        if (inputInfo.shapeInfo.isUniform) {
-          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth) {
-        int index = round(dot(vec3(row, col, depth),
-                          vec3(${stride0}, ${stride1}, 1)));
-        ${getUniformSampler(inputInfo)}
-      }
-    `;
-        }
-        const texShape = inputInfo.shapeInfo.texShape;
-        const texNumR = texShape[0];
-        const texNumC = texShape[1];
-        const flatOffset = inputInfo.shapeInfo.flatOffset;
-        if (texNumC === stride0 && flatOffset == null) {
-          // texC is used directly as physical (no risk of float16 overflow).
-          return `
-        float ${funcName}(int row, int col, int depth) {
-          float texR = float(row);
-          float texC = dot(vec2(col, depth), vec2(${stride1}, 1));
-          vec2 uv = (vec2(texC, texR) + halfCR) /
-                     vec2(${texNumC}.0, ${texNumR}.0);
-          return sampleTexture(${texName}, uv);
-        }
-      `;
-        }
-        if (texNumC === stride1 && flatOffset == null) {
-          // texR is used directly as physical (no risk of float16 overflow).
-          return `
-    float ${funcName}(int row, int col, int depth) {
-      float texR = dot(vec2(row, col), vec2(${shape[1]}, 1));
-      float texC = float(depth);
-      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-        }
-        const offset = getFlatOffsetUniformName(texName);
-        return `
-      float ${funcName}(int row, int col, int depth) {
-        // Explicitly use integer operations as dot() only works on floats.
-        int index = row * ${stride0} + col * ${stride1} + depth + ${offset};
-        vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
-        return sampleTexture(${texName}, uv);
-      }
-  `;
-      }
-      function getPackedSamplerND(inputInfo) {
-        const shape = inputInfo.shapeInfo.logicalShape;
-        const rank = shape.length;
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const texShape = inputInfo.shapeInfo.texShape;
-        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
-        const texNumR = packedTexShape[0];
-        const texNumC = packedTexShape[1];
-        const valuesPerRow = Math.ceil(shape[rank - 1] / 2);
-        let texelsInBatch = valuesPerRow * Math.ceil(shape[rank - 2] / 2);
-        let params = `int b, int row, int col`;
-        let index = `b * ${texelsInBatch} + (row / 2) * ${valuesPerRow} + (col / 2)`;
-        for (let b = 2; b < rank - 1; b++) {
-          params = `int b${b}, ` + params;
-          texelsInBatch *= shape[rank - b - 1];
-          index = `b${b} * ${texelsInBatch} + ` + index;
-        }
-        const glsl = getGlslDifferences();
-        return `
-    vec4 ${funcName}(${params}) {
-      int index = ${index};
-      int texR = index / ${texNumC};
-      int texC = index - texR * ${texNumC};
-      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}, ${texNumR});
-      return ${glsl.texture2D}(${texName}, uv);
-    }
-  `;
-      }
-      function getSampler4D(inputInfo) {
-        const shape = inputInfo.shapeInfo.logicalShape;
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const stride2 = shape[3];
-        const stride1 = shape[2] * stride2;
-        const stride0 = shape[1] * stride1;
-        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
-        if (newShape.length < shape.length) {
-          const newInputInfo = squeezeInputInfo(inputInfo, newShape);
-          const params = ["row", "col", "depth", "depth2"];
-          return `
-      ${getSamplerFromInInfo(newInputInfo)}
-      float ${funcName}(int row, int col, int depth, int depth2) {
-        return ${funcName}(${getSqueezedParams(params, keptDims)});
-      }
-    `;
-        }
-        if (inputInfo.shapeInfo.isUniform) {
-          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth, int depth2) {
-        int index = round(dot(vec4(row, col, depth, depth2),
-                          vec4(${stride0}, ${stride1}, ${stride2}, 1)));
-        ${getUniformSampler(inputInfo)}
-      }
-    `;
-        }
-        const flatOffset = inputInfo.shapeInfo.flatOffset;
-        const texShape = inputInfo.shapeInfo.texShape;
-        const texNumR = texShape[0];
-        const texNumC = texShape[1];
-        if (texNumC === stride0 && flatOffset == null) {
-          // texC is used directly as physical (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth, int depth2) {
-        float texR = float(row);
-        float texC =
-            dot(vec3(col, depth, depth2),
-                vec3(${stride1}, ${stride2}, 1));
-        vec2 uv = (vec2(texC, texR) + halfCR) /
-                   vec2(${texNumC}.0, ${texNumR}.0);
-        return sampleTexture(${texName}, uv);
-      }
-    `;
-        }
-        if (texNumC === stride2 && flatOffset == null) {
-          // texR is used directly as physical (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth, int depth2) {
-        float texR = dot(vec3(row, col, depth),
-                         vec3(${shape[1] * shape[2]}, ${shape[2]}, 1));
-        float texC = float(depth2);
-        vec2 uv = (vec2(texC, texR) + halfCR) /
-                  vec2(${texNumC}.0, ${texNumR}.0);
-        return sampleTexture(${texName}, uv);
-      }
-    `;
-        }
-        const offset = getFlatOffsetUniformName(texName);
-        return `
-    float ${funcName}(int row, int col, int depth, int depth2) {
-      // Explicitly use integer operations as dot() only works on floats.
-      int index = row * ${stride0} + col * ${stride1} +
-          depth * ${stride2} + depth2;
-      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index + ${offset});
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-      }
-      function getSampler5D(inputInfo) {
-        const shape = inputInfo.shapeInfo.logicalShape;
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const stride3 = shape[4];
-        const stride2 = shape[3] * stride3;
-        const stride1 = shape[2] * stride2;
-        const stride0 = shape[1] * stride1;
-        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
-        if (newShape.length < shape.length) {
-          const newInputInfo = squeezeInputInfo(inputInfo, newShape);
-          const params = ["row", "col", "depth", "depth2", "depth3"];
-          return `
-      ${getSamplerFromInInfo(newInputInfo)}
-      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
-        return ${funcName}(${getSqueezedParams(params, keptDims)});
-      }
-    `;
-        }
-        if (inputInfo.shapeInfo.isUniform) {
-          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
-        float index = dot(
-          vec4(row, col, depth, depth2),
-          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +
-          depth3;
-        ${getUniformSampler(inputInfo)}
-      }
-    `;
-        }
-        const flatOffset = inputInfo.shapeInfo.flatOffset;
-        const texShape = inputInfo.shapeInfo.texShape;
-        const texNumR = texShape[0];
-        const texNumC = texShape[1];
-        if (texNumC === stride0 && flatOffset == null) {
-          // texC is used directly as physical (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
-        int texR = row;
-        float texC = dot(vec4(col, depth, depth2, depth3),
-                         vec4(${stride1}, ${stride2}, ${stride3}, 1));
-        vec2 uv = (vec2(texC, texR) + halfCR) /
-                   vec2(${texNumC}.0, ${texNumR}.0);
-        return sampleTexture(${texName}, uv);
-      }
-    `;
-        }
-        if (texNumC === stride3 && flatOffset == null) {
-          // texR is used directly as physical (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
-        float texR = dot(
-          vec4(row, col, depth, depth2),
-          vec4(${shape[1] * shape[2] * shape[3]},
-               ${shape[2] * shape[3]}, ${shape[3]}, 1));
-        int texC = depth3;
-        vec2 uv = (vec2(texC, texR) + halfCR) /
-                  vec2(${texNumC}.0, ${texNumR}.0);
-        return sampleTexture(${texName}, uv);
-      }
-    `;
-        }
-        const offset = getFlatOffsetUniformName(texName);
-        return `
-    float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
-      // Explicitly use integer operations as dot() only works on floats.
-      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +
-          depth2 * ${stride3} + depth3 + ${offset};
-      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-      }
-      function getSampler6D(inputInfo) {
-        const shape = inputInfo.shapeInfo.logicalShape;
-        const texName = inputInfo.name;
-        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
-        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
-        if (newShape.length < shape.length) {
-          const newInputInfo = squeezeInputInfo(inputInfo, newShape);
-          const params = ["row", "col", "depth", "depth2", "depth3", "depth4"];
-          return `
-      ${getSamplerFromInInfo(newInputInfo)}
-      float ${funcName}(int row, int col, int depth,
-                    int depth2, int depth3, int depth4) {
-        return ${funcName}(${getSqueezedParams(params, keptDims)});
-      }
-    `;
-        }
-        const stride4 = shape[5];
-        const stride3 = shape[4] * stride4;
-        const stride2 = shape[3] * stride3;
-        const stride1 = shape[2] * stride2;
-        const stride0 = shape[1] * stride1;
-        if (inputInfo.shapeInfo.isUniform) {
-          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth,
-                  int depth2, int depth3, int depth4) {
-        int index = round(dot(
-          vec4(row, col, depth, depth2),
-          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +
-          dot(
-            vec2(depth3, depth4),
-            vec2(${stride4}, 1)));
-        ${getUniformSampler(inputInfo)}
-      }
-    `;
-        }
-        const flatOffset = inputInfo.shapeInfo.flatOffset;
-        const texShape = inputInfo.shapeInfo.texShape;
-        const texNumR = texShape[0];
-        const texNumC = texShape[1];
-        if (texNumC === stride0 && flatOffset == null) {
-          // texC is used directly as physical (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth,
-                    int depth2, int depth3, int depth4) {
-        int texR = row;
-        float texC = dot(vec4(col, depth, depth2, depth3),
-          vec4(${stride1}, ${stride2}, ${stride3}, ${stride4})) +
-               float(depth4);
-        vec2 uv = (vec2(texC, texR) + halfCR) /
-                   vec2(${texNumC}.0, ${texNumR}.0);
-        return sampleTexture(${texName}, uv);
-      }
-    `;
-        }
-        if (texNumC === stride4 && flatOffset == null) {
-          // texR is used directly as physical (no risk of float16 overflow).
-          return `
-      float ${funcName}(int row, int col, int depth,
-                    int depth2, int depth3, int depth4) {
-        float texR = dot(vec4(row, col, depth, depth2),
-          vec4(${shape[1] * shape[2] * shape[3] * shape[4]},
-               ${shape[2] * shape[3] * shape[4]},
-               ${shape[3] * shape[4]},
-               ${shape[4]})) + float(depth3);
-        int texC = depth4;
-        vec2 uv = (vec2(texC, texR) + halfCR) /
-                  vec2(${texNumC}.0, ${texNumR}.0);
-        return sampleTexture(${texName}, uv);
-      }
-    `;
-        }
-        const offset = getFlatOffsetUniformName(texName);
-        return `
-    float ${funcName}(int row, int col, int depth,
-                  int depth2, int depth3, int depth4) {
-      // Explicitly use integer operations as dot() only works on floats.
-      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +
-          depth2 * ${stride3} + depth3 * ${stride4} + depth4 + ${offset};
-      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
-      return sampleTexture(${texName}, uv);
-    }
-  `;
-      }
-      function getUniformSampler(inputInfo) {
-        const texName = inputInfo.name;
-        const inSize = dist["util"].sizeFromShape(inputInfo.shapeInfo.logicalShape);
-        if (inSize < 2) {
-          return `return ${texName};`;
-        }
-        return `
-    for (int i = 0; i < ${inSize}; i++) {
-      if (i == index) {
-        return ${texName}[i];
-      }
-    }
-  `;
-      }
-      function getPackedSamplerAtOutputCoords(inputInfo, outShapeInfo) {
-        const texName = inputInfo.name;
-        const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);
-        const funcName = "get" + texFuncSnippet + "AtOutCoords";
-        const inRank = inputInfo.shapeInfo.logicalShape.length;
-        const outRank = outShapeInfo.logicalShape.length;
-        const broadcastDims = getBroadcastDims(
-          inputInfo.shapeInfo.logicalShape,
-          outShapeInfo.logicalShape
-        );
-        const type = getCoordsDataType(outRank);
-        const rankDiff = outRank - inRank;
-        let coordsSnippet;
-        const fields = ["x", "y", "z", "w", "u", "v"];
-        if (inRank === 0) {
-          coordsSnippet = "";
-        } else if (outRank < 2 && broadcastDims.length >= 1) {
-          coordsSnippet = "coords = 0;";
-        } else {
-          coordsSnippet = broadcastDims
-            .map((d) => `coords.${fields[d + rankDiff]} = 0;`)
-            .join("\n");
-        }
-        let unpackedCoordsSnippet = "";
-        if (outRank < 2 && inRank > 0) {
-          unpackedCoordsSnippet = "coords";
-        } else {
-          unpackedCoordsSnippet = inputInfo.shapeInfo.logicalShape
-            .map((s, i) => `coords.${fields[i + rankDiff]}`)
-            .join(", ");
-        }
-        let output = `return outputValue;`;
-        const inSize = dist["util"].sizeFromShape(inputInfo.shapeInfo.logicalShape);
-        const isInputScalar = inSize === 1;
-        const outSize = dist["util"].sizeFromShape(outShapeInfo.logicalShape);
-        const isOutputScalar = outSize === 1;
-        if (inRank === 1 && !isInputScalar && !isOutputScalar) {
-          output = `
-      return vec4(outputValue.xy, outputValue.xy);
-    `;
-        } else if (isInputScalar && !isOutputScalar) {
-          if (outRank === 1) {
-            output = `
-        return vec4(outputValue.x, outputValue.x, 0., 0.);
-      `;
-          } else {
-            output = `
-        return vec4(outputValue.x);
-      `;
-          }
-        } else if (broadcastDims.length) {
-          const rows = inRank - 2;
-          const cols = inRank - 1;
-          if (broadcastDims.indexOf(rows) > -1 && broadcastDims.indexOf(cols) > -1) {
-            output = `return vec4(outputValue.x);`;
-          } else if (broadcastDims.indexOf(rows) > -1) {
-            output =
-              `return vec4(outputValue.x, outputValue.y, ` + `outputValue.x, outputValue.y);`;
-          } else if (broadcastDims.indexOf(cols) > -1) {
-            output = `return vec4(outputValue.xx, outputValue.zz);`;
-          }
-        }
-        return `
-    vec4 ${funcName}() {
-      ${type} coords = getOutputCoords();
-      ${coordsSnippet}
-      vec4 outputValue = get${texFuncSnippet}(${unpackedCoordsSnippet});
-      ${output}
-    }
-  `;
-      }
-      function getSamplerAtOutputCoords(inputInfo, outShapeInfo) {
-        const texName = inputInfo.name;
-        const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);
-        const funcName = "get" + texFuncSnippet + "AtOutCoords";
-        const outTexShape = outShapeInfo.texShape;
-        const inTexShape = inputInfo.shapeInfo.texShape;
-        const inRank = inputInfo.shapeInfo.logicalShape.length;
-        const outRank = outShapeInfo.logicalShape.length;
-        if (
-          !inputInfo.shapeInfo.isUniform &&
-          inRank === outRank &&
-          inputInfo.shapeInfo.flatOffset == null &&
-          dist["util"].arraysEqual(inTexShape, outTexShape)
-        ) {
-          return `
-      float ${funcName}() {
-        return sampleTexture(${texName}, resultUV);
-      }
-    `;
-        }
-        const type = getCoordsDataType(outRank);
-        const broadcastDims = getBroadcastDims(
-          inputInfo.shapeInfo.logicalShape,
-          outShapeInfo.logicalShape
-        );
-        const rankDiff = outRank - inRank;
-        let coordsSnippet;
-        const fields = ["x", "y", "z", "w", "u", "v"];
-        if (inRank === 0) {
-          coordsSnippet = "";
-        } else if (outRank < 2 && broadcastDims.length >= 1) {
-          coordsSnippet = "coords = 0;";
-        } else {
-          coordsSnippet = broadcastDims
-            .map((d) => `coords.${fields[d + rankDiff]} = 0;`)
-            .join("\n");
-        }
-        let unpackedCoordsSnippet = "";
-        if (outRank < 2 && inRank > 0) {
-          unpackedCoordsSnippet = "coords";
-        } else {
-          unpackedCoordsSnippet = inputInfo.shapeInfo.logicalShape
-            .map((s, i) => `coords.${fields[i + rankDiff]}`)
-            .join(", ");
-        }
-        return `
-    float ${funcName}() {
-      ${type} coords = getOutputCoords();
-      ${coordsSnippet}
-      return get${texFuncSnippet}(${unpackedCoordsSnippet});
-    }
-  `;
-      }
-      function getCoordsDataType(rank) {
-        if (rank <= 1) {
-          return "int";
-        } else if (rank === 2) {
-          return "ivec2";
-        } else if (rank === 3) {
-          return "ivec3";
-        } else if (rank === 4) {
-          return "ivec4";
-        } else if (rank === 5) {
-          return "ivec5";
-        } else if (rank === 6) {
-          return "ivec6";
-        } else {
-          throw Error(`GPU for rank ${rank} is not yet supported`);
-        }
-      }
-      /** Returns a new input info (a copy) that has a squeezed logical shape. */
-      function squeezeInputInfo(inInfo, squeezedShape) {
-        // Deep copy.
-        const newInputInfo = JSON.parse(JSON.stringify(inInfo));
-        newInputInfo.shapeInfo.logicalShape = squeezedShape;
-        return newInputInfo;
-      }
-      function getSqueezedParams(params, keptDims) {
-        return keptDims.map((d) => params[d]).join(", ");
-      }
-      //# sourceMappingURL=shader_compiler.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/argminmax_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class argminmax_packed_gpu_ArgMinMaxPackedProgram {
-        constructor(shape, windowSize, op, firstPass) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          dist["util"].assert(
-            shape.length > 2,
-            () =>
-              `Packed arg${
-                op.charAt(0).toUpperCase() + op.slice(1)
-              } supports only inputs with rank above 2.`
-          );
-          const inSize = shape[shape.length - 1];
-          const outSize = Math.ceil(inSize / windowSize);
-          this.outputShape = shape.slice(0, -1);
-          if (outSize > 1) {
-            this.outputShape.push(outSize);
-          }
-          if (!firstPass) {
-            this.variableNames.push("bestIndicesA");
-          }
-          const outShape = this.outputShape;
-          const rank = outShape.length;
-          const dtype = getCoordsDataType(rank);
-          const coords = getChannels("coords", rank);
-          let sourceLocSetup;
-          let sourceRank;
-          if (outSize === 1) {
-            sourceRank = rank + 1;
-            const sourceLocDType = getCoordsDataType(sourceRank);
-            sourceLocSetup = `
-        ${sourceLocDType} sourceLocR = ${sourceLocDType}(${coords.join()}, 0);
-        ++${coords[rank - 1]};
-        ${sourceLocDType} sourceLocG = ${sourceLocDType}(${coords.join()}, 0);
-        ++${coords[rank - 2]};
-        ${sourceLocDType} sourceLocA = ${sourceLocDType}(${coords.join()}, 0);
-        --${coords[rank - 1]};
-        ${sourceLocDType} sourceLocB = ${sourceLocDType}(${coords.join()}, 0);
-        --${coords[rank - 2]};`;
-          } else {
-            sourceRank = rank;
-            sourceLocSetup = `
-        ${dtype} sourceLocR = coords;
-        ++${coords[rank - 1]};
-        ${dtype} sourceLocG = coords;
-        ++${coords[rank - 2]};
-        ${dtype} sourceLocA = coords;
-        --${coords[rank - 1]};
-        ${dtype} sourceLocB = coords;
-        --${coords[rank - 2]};`;
-          }
-          const channels = ["x", "y", "z", "w", "u", "v"].slice(0, sourceRank);
-          const inChannel = "." + channels[sourceRank - 1]; // e.g. ".b" for rank 3.
-          const intChannels = channels.map((x) => "int " + x);
-          const srcRCoords = getChannels("sourceLocR", sourceRank - 1).concat("inIdx.r");
-          const srcGCoords = getChannels("sourceLocG", sourceRank - 1).concat("inIdx.g");
-          const srcBCoords = getChannels("sourceLocB", sourceRank - 1).concat("inIdx.b");
-          const srcACoords = getChannels("sourceLocA", sourceRank - 1).concat("inIdx.a");
-          const compOp = op === "max" ? "greaterThan" : "lessThan";
-          const fetchCandidateIdx = firstPass
-            ? ""
-            : `
-          inIdx = round(vec4(getBestIndicesAChannel(${srcRCoords.join()}),
-                             getBestIndicesAChannel(${srcGCoords.join()}),
-                             getBestIndicesAChannel(${srcBCoords.join()}),
-                             getBestIndicesAChannel(${srcACoords.join()})));`;
-          const fetchValue = `vec4(
-            getAChannel(${srcRCoords.join()}),
-            hasNextCol ? getAChannel(${srcGCoords.join()}) : 0.,
-            hasNextRow ? getAChannel(${srcBCoords.join()}) : 0.,
-            hasNextRow && hasNextCol ? getAChannel(${srcACoords.join()}) : 0.)`;
-          const getBestIndicesAChannelSnippet = firstPass
-            ? ""
-            : `
-      float getBestIndicesAChannel(${intChannels.join()}) {
-        return getChannel(getBestIndicesA(${channels.join()}),
-                                          vec2(${channels.slice(-2).join()}));
-      }`;
-          this.userCode = `
-      float getAChannel(${intChannels.join()}) {
-        return getChannel(getA(${channels.join()}),
-                               vec2(${channels.slice(-2).join()}));
-      }
-      ${getBestIndicesAChannelSnippet}
-      void main() {
-        ${dtype} coords = getOutputCoords();
-        bool hasNextCol = ${coords[rank - 1]} < ${outShape[rank - 1] - 1};
-        bool hasNextRow = ${coords[rank - 2]} < ${outShape[rank - 2] - 1};
-        ${sourceLocSetup}
-        ivec4 srcIdx = ivec4(sourceLocR${inChannel}, sourceLocG${inChannel},
-          sourceLocB${inChannel}, sourceLocA${inChannel}) * ${windowSize};
-        ivec4 inIdx = srcIdx;
-        vec4 bestIndex = vec4(inIdx);
-        vec4 bestValue = ${fetchValue};
-
-        for (int i = 0; i < ${windowSize}; i++) {
-          inIdx = srcIdx;
-          ${fetchCandidateIdx}
-          vec4 candidate = ${fetchValue};
-          bvec4 nan = isnan(candidate);
-          bvec4 replace = bvec4(
-            vec4(${compOp}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
-
-          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
-                           replace.y  ? candidate.y : bestValue.y,
-                           replace.z  ? candidate.z : bestValue.z,
-                           replace.w  ? candidate.w : bestValue.w);
-          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
-          srcIdx++;
-        }
-        setOutput(bestIndex);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=argminmax_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/avg_pool_backprop_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class AvgPool2DBackpropProgram {
-        constructor(convInfo) {
-          this.variableNames = ["dy"];
-          this.outputShape = convInfo.inShape;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
-          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
-          const avgMultiplier = 1 / (filterHeight * filterWidth);
-          this.userCode = `
-      const ivec2 pads = ivec2(${padTop}, ${padLeft});
-      const float avgMultiplier = float(${avgMultiplier});
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int d = coords[3];
-
-        ivec2 dyRCCorner = coords.yz - pads;
-        int dyRCorner = dyRCCorner.x;
-        int dyCCorner = dyRCCorner.y;
-
-        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
-        // ? = to be determined. : = across all values in that axis.
-        float dotProd = 0.0;
-        for (int wR = 0; wR < ${effectiveFilterHeight};
-            wR += ${dilationHeight}) {
-          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
-
-          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {
-            continue;
-          }
-          int idyR = int(dyR);
-
-          for (int wC = 0; wC < ${effectiveFilterWidth};
-            wC+= ${dilationWidth}) {
-            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
-
-            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
-                fract(dyC) > 0.0) {
-              continue;
-            }
-            int idyC = int(dyC);
-
-            float dyValue = getDy(b, idyR, idyC, d);
-
-            dotProd += dyValue * avgMultiplier;
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      class AvgPool3DBackpropProgram {
-        constructor(convInfo) {
-          this.variableNames = ["dy"];
-          this.outputShape = convInfo.inShape;
-          const filterDepth = convInfo.filterDepth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
-          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
-          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
-          const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);
-          this.userCode = `
-      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
-      const float avgMultiplier = float(${avgMultiplier});
-
-      void main() {
-        ivec5 coords = getOutputCoords();
-        int batch = coords.x;
-        int ch = coords.u;
-
-        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
-        int dyDCorner = dyCorner.x;
-        int dyRCorner = dyCorner.y;
-        int dyCCorner = dyCorner.z;
-
-        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
-        // dx(xD, xR, xC, ch).
-        // ? = to be determined. : = across all values in that axis.
-        float dotProd = 0.0;
-
-        for (int wD = 0; wD < ${effectiveFilterDepth};
-            wD += ${dilationDepth}) {
-          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;
-
-          if (dyD < 0.0 || dyD >= ${convInfo.outDepth}.0 || fract(dyD) > 0.0) {
-            continue;
-          }
-          int idyD = int(dyD);
-
-          for (int wR = 0; wR < ${effectiveFilterHeight};
-              wR += ${dilationHeight}) {
-            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
-
-            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||
-                fract(dyR) > 0.0) {
-              continue;
-            }
-            int idyR = int(dyR);
-
-            for (int wC = 0; wC < ${effectiveFilterWidth};
-                wC += ${dilationWidth}) {
-              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
-
-              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
-                  fract(dyC) > 0.0) {
-                continue;
-              }
-              int idyC = int(dyC);
-
-              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
-
-              dotProd += dyValue * avgMultiplier;
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=avg_pool_backprop_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/batchnorm_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class batchnorm_gpu_BatchNormProgram {
-        constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {
-          this.outputShape = [];
-          this.variableNames = ["x", "mean", "variance"];
-          dist["backend_util"].assertAndGetBroadcastShape(xShape, meanShape);
-          dist["backend_util"].assertAndGetBroadcastShape(xShape, varianceShape);
-          let offsetSnippet = "0.0";
-          if (offsetShape != null) {
-            dist["backend_util"].assertAndGetBroadcastShape(xShape, offsetShape);
-            this.variableNames.push("offset");
-            offsetSnippet = "getOffsetAtOutCoords()";
-          }
-          let scaleSnippet = "1.0";
-          if (scaleShape != null) {
-            dist["backend_util"].assertAndGetBroadcastShape(xShape, scaleShape);
-            this.variableNames.push("scale");
-            scaleSnippet = "getScaleAtOutCoords()";
-          }
-          this.outputShape = xShape;
-          this.userCode = `
-      void main() {
-        float x = getXAtOutCoords();
-        float mean = getMeanAtOutCoords();
-        float variance = getVarianceAtOutCoords();
-        float offset = ${offsetSnippet};
-        float scale = ${scaleSnippet};
-        float inv = scale * inversesqrt(variance + float(${varianceEpsilon}));
-        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=batchnorm_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/batchnorm_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class batchnorm_packed_gpu_BatchNormPackedProgram {
-        constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.variableNames = ["x", "mean", "variance"];
-          dist["backend_util"].assertAndGetBroadcastShape(xShape, meanShape);
-          dist["backend_util"].assertAndGetBroadcastShape(xShape, varianceShape);
-          let offsetSnippet = "vec4(0.0)";
-          if (offsetShape != null) {
-            dist["backend_util"].assertAndGetBroadcastShape(xShape, offsetShape);
-            this.variableNames.push("offset");
-            offsetSnippet = "getOffsetAtOutCoords()";
-          }
-          let scaleSnippet = "vec4(1.0)";
-          if (scaleShape != null) {
-            dist["backend_util"].assertAndGetBroadcastShape(xShape, scaleShape);
-            this.variableNames.push("scale");
-            scaleSnippet = "getScaleAtOutCoords()";
-          }
-          this.outputShape = xShape;
-          this.userCode = `
-      void main() {
-        vec4 offset = ${offsetSnippet};
-        vec4 scale = ${scaleSnippet};
-
-        vec4 x = getXAtOutCoords();
-        vec4 mean = getMeanAtOutCoords();
-        vec4 variance = getVarianceAtOutCoords();
-
-        vec4 inv = scale * inversesqrt(variance + vec4(${varianceEpsilon}));
-
-        setOutput((x - mean) * inv + offset);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=batchnorm_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_complex_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // (Ar + Ai)(Br + Bi) =
-      // ArBr + ArBi + AiBr + AiBi = ArBr - AB + ArBi + AiBr
-      // Yr = ArBr - AB
-      // Yi = ArBi + AiBr
-      const COMPLEX_MULTIPLY = {
-        REAL: "return areal * breal - aimag * bimag;",
-        IMAG: "return areal * bimag + aimag * breal;",
-      };
-      class binaryop_complex_gpu_BinaryOpComplexProgram {
-        constructor(op, aShape, bShape) {
-          this.variableNames = ["AReal", "AImag", "BReal", "BImag"];
-          this.outputShape = dist["backend_util"].assertAndGetBroadcastShape(aShape, bShape);
-          this.userCode = `
-      float binaryOpComplex(
-          float areal, float aimag, float breal, float bimag) {
-        ${op}
-      }
-
-      void main() {
-        float areal = getARealAtOutCoords();
-        float aimag = getAImagAtOutCoords();
-        float breal = getBRealAtOutCoords();
-        float bimag = getBImagAtOutCoords();
-        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=binaryop_complex_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const CHECK_NAN_SNIPPET = `
-  if (isnan(a)) return a;
-  if (isnan(b)) return b;
-`;
-      const ADD = "return a + b;";
-      const SUB = "return a - b;";
-      const MUL = "return a * b;";
-      // Without the equality check div produces 0.9999 for a = b, which when
-      // floored can cause errors.
-      const DIV = `
-if (a == b) {
-  return 1.0;
-};
-return a / b;`;
-      // We use native integer division to deal with floating point imprecision. Since
-      // we implement floor division and glsl implements truncated division, we
-      // correct for this by subtracting 1 from result when the result is negative and
-      // there is a remainder.
-      const INT_DIV = `
-  float s = sign(a) * sign(b);
-  int ia = round(a);
-  int ib = round(b);
-  if (ib != 0) {
-    // Windows (D3D) wants guaranteed non-zero int division at compile-time.
-    return float(idiv(ia, ib, s));
-  } else {
-    return NAN;
-  }
-`;
-      const POW = `
-if(a < 0.0 && floor(b) < b){
-  return NAN;
-}
-if (b == 0.0) {
-  return 1.0;
-}
-return (round(mod(b, 2.0)) != 1) ?
-    pow(abs(a), b) : sign(a) * pow(abs(a), b);
-`;
-      const binaryop_gpu_SQUARED_DIFFERENCE = "return (a - b) * (a - b);";
-      const EQUAL = `return float(a == b);`;
-      const NOT_EQUAL = `return float(a != b);`;
-      const LESS = `return float(a < b);`;
-      const LESS_EQUAL = `return float(a <= b);`;
-      const GREATER = `return float(a > b);`;
-      const GREATER_EQUAL = `return float(a >= b);`;
-      const LOGICAL_AND = `return float(a >= 1.0 && b >= 1.0);`;
-      const LOGICAL_OR = `return float(a >= 1.0 || b >= 1.0);`;
-      const MAX =
-        CHECK_NAN_SNIPPET +
-        `
-  return max(a, b);
-`;
-      const MIN =
-        CHECK_NAN_SNIPPET +
-        `
-  return min(a, b);
-`;
-      const MOD = `if (b == 0.0) return NAN;
-  return mod(a, b);`;
-      const ATAN2 =
-        CHECK_NAN_SNIPPET +
-        `
-  return atan(a, b);
-`;
-      const ELU_DER = `return (b >= 1.0) ? a : a * (b + 1.0);`;
-      const PRELU = `return (a < 0.) ? b * a : a;`;
-      class binaryop_gpu_BinaryOpProgram {
-        constructor(op, aShape, bShape) {
-          this.variableNames = ["A", "B"];
-          this.outputShape = dist["backend_util"].assertAndGetBroadcastShape(aShape, bShape);
-          this.userCode = `
-      float binaryOperation(float a, float b) {
-        ${op}
-      }
-
-      void main() {
-        float a = getAAtOutCoords();
-        float b = getBAtOutCoords();
-        setOutput(binaryOperation(a, b));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=binaryop_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const binaryop_packed_gpu_CHECK_NAN_SNIPPET = `
-  result.r = isNaN.r > 0. ? NAN : result.r;
-  result.g = isNaN.g > 0. ? NAN : result.g;
-  result.b = isNaN.b > 0. ? NAN : result.b;
-  result.a = isNaN.a > 0. ? NAN : result.a;
-`;
-      // We do the same as in ./binaryop_gpu, with vec4 and ivec4.
-      // On Linux, the vectorized implementation produces NaNs when a and b are 0.
-      const binaryop_packed_gpu_DIV = `
-  // vec4 one = vec4(equal(a, b));
-  // return one + (vec4(1.0) - one) * a / b;
-  vec4 result = a / b;
-  if(a.x == b.x) {
-    result.x = 1.;
-  }
-  if(a.y == b.y) {
-    result.y = 1.;
-  }
-  if(a.z == b.z) {
-    result.z = 1.;
-  }
-  if(a.w == b.w) {
-    result.w = 1.;
-  }
-
-  return result;
-`;
-      const binaryop_packed_gpu_INT_DIV = `
-  ivec4 ia = round(a);
-  ivec4 ib = round(b);
-  bvec4 cond = notEqual(ib, ivec4(0));
-  ivec4 result = ivec4(0);
-  vec4 s = sign(a) * sign(b);
-
-  // Windows (D3D) wants guaranteed non-zero int division at compile-time.
-  if (cond[0]) {
-    result[0] = idiv(ia[0], ib[0], s[0]);
-  }
-  if (cond[1]) {
-    result[1] = idiv(ia[1], ib[1], s[1]);
-  }
-  if (cond[2]) {
-    result[2] = idiv(ia[2], ib[2], s[2]);
-  }
-  if (cond[3]) {
-    result[3] = idiv(ia[3], ib[3], s[3]);
-  }
-  return vec4(result);
-`;
-      const binaryop_packed_gpu_POW =
-        `
-  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
-  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
-  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
-  vec4 result = multiplier * pow(abs(a), b);
-
-  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
-  bvec4 isExpZero = equal(b, vec4(0.0));
-  result.r = isExpZero.r ? 1.0 : result.r;
-  result.g = isExpZero.g ? 1.0 : result.g;
-  result.b = isExpZero.b ? 1.0 : result.b;
-  result.a = isExpZero.a ? 1.0 : result.a;
-
-  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
-  ` +
-        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
-        `
-  return result;
-`;
-      const binaryop_packed_gpu_PRELU = `
-  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
-  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;
-      const binaryop_packed_gpu_ELU_DER = `
-  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
-  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`;
-      const binaryop_packed_gpu_ATAN2 =
-        `
-  vec4 result = atan(a, b);
-  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  ` +
-        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
-        `
-  return result;
-`;
-      const binaryop_packed_gpu_EQUAL = `
-  return vec4(equal(a, b));
-`;
-      const binaryop_packed_gpu_NOT_EQUAL = `
-  return vec4(notEqual(a, b));
-`;
-      const binaryop_packed_gpu_LESS = `
-  return vec4(lessThan(a, b));
-`;
-      const binaryop_packed_gpu_LESS_EQUAL = `
-  return vec4(lessThanEqual(a, b));
-`;
-      const binaryop_packed_gpu_GREATER = `
-  return vec4(greaterThan(a, b));
-`;
-      const binaryop_packed_gpu_GREATER_EQUAL = `
-  return vec4(greaterThanEqual(a, b));
-`;
-      const binaryop_packed_gpu_LOGICAL_AND = `
-  return vec4(
-    vec4(greaterThanEqual(a, vec4(1.0))) *
-    vec4(greaterThanEqual(b, vec4(1.0))));
-`;
-      const binaryop_packed_gpu_LOGICAL_OR = `
-  return min(
-    vec4(greaterThanEqual(a, vec4(1.0))) +
-    vec4(greaterThanEqual(b, vec4(1.0))),
-    vec4(1.0));
-`;
-      const binaryop_packed_gpu_MAX =
-        `
-  vec4 result = vec4(max(a, b));
-  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  ` +
-        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
-        `
-  return result;
-`;
-      const binaryop_packed_gpu_MIN =
-        `
-  vec4 result = vec4(min(a, b));
-  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  ` +
-        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
-        `
-  return result;
-`;
-      const binaryop_packed_gpu_MOD =
-        `
-  vec4 result = mod(a, b);
-  vec4 isNaN = vec4(equal(b, vec4(0.0)));
-  ` +
-        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
-        `
-  return result;
-`;
-      class binaryop_packed_gpu_BinaryOpPackedProgram {
-        constructor(op, aShape, bShape, checkOutOfBounds = false) {
-          this.variableNames = ["A", "B"];
-          this.supportsBroadcasting = true;
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = dist["backend_util"].assertAndGetBroadcastShape(aShape, bShape);
-          const rank = this.outputShape.length;
-          let checkOutOfBoundsString = "";
-          if (checkOutOfBounds) {
-            if (rank === 0 || dist["util"].sizeFromShape(this.outputShape) === 1) {
-              checkOutOfBoundsString = `
-          result.y = 0.;
-          result.z = 0.;
-          result.w = 0.;
-        `;
-            } else {
-              const dtype = getCoordsDataType(rank);
-              checkOutOfBoundsString = `
-          ${dtype} coords = getOutputCoords();
-        `;
-              if (rank === 1) {
-                checkOutOfBoundsString += `
-            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
-            result.z = 0.;
-            result.w = 0.;
-          `;
-              } else {
-                const channels = getChannels("coords", rank);
-                checkOutOfBoundsString += `
-            bool nextRowOutOfBounds =
-              (${channels[rank - 2]} + 1) >= ${this.outputShape[rank - 2]};
-            bool nextColOutOfBounds =
-              (${channels[rank - 1]} + 1) >= ${this.outputShape[rank - 1]};
-            result.y = nextColOutOfBounds ? 0. : result.y;
-            result.z = nextRowOutOfBounds ? 0. : result.z;
-            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
-          `;
-              }
-            }
-          }
-          this.userCode = `
-      vec4 binaryOperation(vec4 a, vec4 b) {
-        ${op}
-      }
-
-      void main() {
-        vec4 a = getAAtOutCoords();
-        vec4 b = getBAtOutCoords();
-
-        vec4 result = binaryOperation(a, b);
-        ${checkOutOfBoundsString}
-
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=binaryop_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/clip_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ClipProgram {
-        constructor(aShape) {
-          this.variableNames = ["A"];
-          this.outputShape = aShape;
-          this.userCode = `
-      uniform float minVal;
-      uniform float maxVal;
-
-      void main() {
-        float value = getAAtOutCoords();
-        if (isnan(value)) {
-          setOutput(value);
-          return;
-        }
-
-        setOutput(clamp(value, minVal, maxVal));
-      }
-    `;
-        }
-        getCustomSetupFunc(min, max) {
-          return (gpgpu, webGLProgram) => {
-            if (this.minLoc == null) {
-              this.minLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "minVal");
-              this.maxLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "maxVal");
-            }
-            gpgpu.gl.uniform1f(this.minLoc, min);
-            gpgpu.gl.uniform1f(this.maxLoc, max);
-          };
-        }
-      }
-      //# sourceMappingURL=clip_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/clip_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ClipPackedProgram {
-        constructor(aShape) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = aShape;
-          this.userCode = `
-      uniform float minVal;
-      uniform float maxVal;
-
-      void main() {
-        vec4 value = getAAtOutCoords();
-
-        if (any(isnan(value))) {
-          setOutput(value);
-          return;
-        }
-
-        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
-      }
-    `;
-        }
-        getCustomSetupFunc(min, max) {
-          return (gpgpu, webGLProgram) => {
-            if (this.minLoc == null) {
-              this.minLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "minVal");
-              this.maxLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "maxVal");
-            }
-            gpgpu.gl.uniform1f(this.minLoc, min);
-            gpgpu.gl.uniform1f(this.maxLoc, max);
-          };
-        }
-      }
-      //# sourceMappingURL=clip_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/complex_abs_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ComplexAbsProgram {
-        constructor(shape) {
-          this.variableNames = ["real", "imag"];
-          this.outputShape = shape;
-          this.userCode = `
-      void main() {
-        float re = abs(getRealAtOutCoords());
-        float im = abs(getImagAtOutCoords());
-        float mx = max(re, im);
-
-        // sadly the length function in glsl is not underflow-safe
-        // (at least not on Intel GPUs). So the safe solution is
-        // to ensure underflow-safety in all cases.
-        setOutput(
-          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
-        );
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=complex_abs_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/concat_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class concat_gpu_ConcatProgram {
-        // Concats 2d tensors along axis=1. See comments in MathBackendWebGL.concat().
-        constructor(shapes) {
-          this.outputShape = [];
-          this.outputShape = dist["backend_util"].computeOutShape(shapes, 1 /* axis */);
-          this.variableNames = shapes.map((_, i) => `T${i}`);
-          const offsets = new Array(shapes.length - 1);
-          offsets[0] = shapes[0][1];
-          for (let i = 1; i < offsets.length; i++) {
-            offsets[i] = offsets[i - 1] + shapes[i][1];
-          }
-          const snippets = [`if (yC < ${offsets[0]}) setOutput(getT0(yR, yC));`];
-          for (let i = 1; i < offsets.length; i++) {
-            const shift = offsets[i - 1];
-            snippets.push(
-              `else if (yC < ${offsets[i]}) ` + `setOutput(getT${i}(yR, yC-${shift}));`
-            );
-          }
-          const lastIndex = offsets.length;
-          const lastShift = offsets[offsets.length - 1];
-          snippets.push(`else setOutput(getT${lastIndex}(yR, yC-${lastShift}));`);
-          this.userCode = `
-      void main() {
-        ivec2 coords = getOutputCoords();
-        int yR = coords.x;
-        int yC = coords.y;
-
-        ${snippets.join("\n        ")}
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=concat_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/concat_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class concat_packed_gpu_ConcatPackedProgram {
-        constructor(shapes, axis) {
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = [];
-          this.outputShape = dist["backend_util"].computeOutShape(shapes, axis);
-          const shape = this.outputShape;
-          const rank = shape.length;
-          const dtype = getCoordsDataType(rank);
-          const coords = getChannels("coords", rank);
-          const channels = ["x", "y", "z", "w", "u", "v"].slice(0, rank);
-          this.variableNames = shapes.map((_, i) => `T${i}`);
-          const offsets = new Array(shapes.length - 1);
-          offsets[0] = shapes[0][axis];
-          for (let i = 1; i < offsets.length; i++) {
-            offsets[i] = offsets[i - 1] + shapes[i][axis];
-          }
-          const channel = channels[axis];
-          const lastChannels = channels.slice(-2);
-          const allChannels = channels.join();
-          let getValueSnippet = `if (${channel} < ${offsets[0]}) {
-        return getChannel(
-            getT0(${allChannels}), vec2(${lastChannels.join()}));
-        }`;
-          for (let i = 1; i < offsets.length; i++) {
-            const shift = offsets[i - 1];
-            // Note: the >= comparison below may seem unnecessary given the check
-            // above but is needed to workaround branch execution issues on some
-            // devices. It makes all the conditions exclusive without relying on
-            // execution order.
-            getValueSnippet += `
-        if (${channel} < ${offsets[i]}  && ${channel} >= ${offsets[i - 1]}) {
-          return getChannel(
-            getT${i}(${shiftedChannels(channels, channel, shift)}),
-            vec2(${shiftedChannels(lastChannels, channel, shift)}));
-        }`;
-          }
-          const lastIndex = offsets.length;
-          const shift = offsets[offsets.length - 1];
-          getValueSnippet += `
-        return getChannel(
-          getT${lastIndex}(${shiftedChannels(channels, channel, shift)}),
-          vec2(${shiftedChannels(lastChannels, channel, shift)}));`;
-          this.userCode = `
-      float getValue(${channels.map((x) => "int " + x)}) {
-        ${getValueSnippet}
-      }
-
-      void main() {
-        ${dtype} coords = getOutputCoords();
-        vec4 result = vec4(getValue(${coords}), 0., 0., 0.);
-
-        ${coords[rank - 1]} = ${coords[rank - 1]} + 1;
-        if (${coords[rank - 1]} < ${shape[rank - 1]}) {
-          result.g = getValue(${coords});
-        }
-
-        ${coords[rank - 2]} = ${coords[rank - 2]} + 1;
-        if (${coords[rank - 2]} < ${shape[rank - 2]}) {
-          result.a = getValue(${coords});
-        }
-
-        ${coords[rank - 1]} = ${coords[rank - 1]} - 1;
-        if (${coords[rank - 2]} < ${shape[rank - 2]} &&
-            ${coords[rank - 1]} < ${shape[rank - 1]}) {
-          result.b = getValue(${coords});
-        }
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      /**
-       * Return an expression for coordinates into a vector where a given channel
-       * will be offset by [shift].
-       *
-       * @param channels the channels to consider
-       * @param channel the channel we want shifted
-       * @param shift  the amount to subtract from the channel.
-       *
-       * @returns a string of the form 'x, y-[shift], z' where any one channel can
-       * have the shift applied.
-       */
-      function shiftedChannels(channels, channel, shift) {
-        const channelIdx = channels.indexOf(channel);
-        const res = channels.map((c, idx) => {
-          if (idx === channelIdx) {
-            return `${c} - ${shift}`;
-          } else {
-            return c;
-          }
-        });
-        return res.join();
-      }
-      //# sourceMappingURL=concat_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_backprop_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class Conv2DDerFilterProgram {
-        constructor(convInfo) {
-          this.variableNames = ["x", "dy"];
-          this.outputShape = convInfo.filterShape;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          const isChannelsLast = convInfo.dataFormat === "channelsLast";
-          this.userCode = `
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int wR = coords.x;
-        int wC = coords.y;
-        int d1 = coords.z;
-        int d2 = coords.w;
-
-        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
-        // ? = to be determined. : = across all values in that axis.
-        float dotProd = 0.0;
-
-        for (int b = 0; b < ${convInfo.batchSize}; b++) {
-          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {
-            int xR = wR + yR * ${strideHeight} - ${padTop};
-
-            if (xR < 0 || xR >= ${convInfo.inHeight}) {
-              continue;
-            }
-
-            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
-              int xC = wC + yC * ${strideWidth} - ${padLeft};
-
-              if (xC < 0 || xC >= ${convInfo.inWidth}) {
-                continue;
-              }
-
-              if (${isChannelsLast}) {
-                float dyValue = getDy(b, yR, yC, d2);
-                float xValue = getX(b, xR, xC, d1);
-                dotProd += (xValue * dyValue);
-              } else {
-                float dyValue = getDy(b, d2, yR, yC);
-                float xValue = getX(b, d1, xR, xC);
-                dotProd += (xValue * dyValue);
-              }
-
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      class Conv2DDerInputProgram {
-        constructor(convInfo) {
-          this.variableNames = ["dy", "W"];
-          this.outputShape = convInfo.inShape;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const isChannelsLast = convInfo.dataFormat === "channelsLast";
-          const padTop = filterHeight - 1 - convInfo.padInfo.top;
-          const padLeft = filterWidth - 1 - convInfo.padInfo.left;
-          const rowDim = isChannelsLast ? 1 : 2;
-          const colDim = isChannelsLast ? 2 : 3;
-          const channelDim = isChannelsLast ? 3 : 1;
-          this.userCode = `
-      const ivec2 pads = ivec2(${padTop}, ${padLeft});
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int batch = coords[0];
-        int d1 = coords[${channelDim}];
-
-        ivec2 dyCorner = ivec2(coords[${rowDim}], coords[${colDim}]) - pads;
-        int dyRCorner = dyCorner.x;
-        int dyCCorner = dyCorner.y;
-
-        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
-        // ? = to be determined. : = across all values in that axis.
-        float dotProd = 0.0;
-        for (int wR = 0; wR < ${filterHeight}; wR++) {
-          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
-
-          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {
-            continue;
-          }
-          int idyR = int(dyR);
-
-          int wRPerm = ${filterHeight} - 1 - wR;
-
-          for (int wC = 0; wC < ${filterWidth}; wC++) {
-            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
-
-            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
-                fract(dyC) > 0.0) {
-              continue;
-            }
-            int idyC = int(dyC);
-
-            int wCPerm = ${filterWidth} - 1 - wC;
-
-            for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {
-
-              if (${isChannelsLast}) {
-                float xValue = getDy(batch, idyR, idyC, d2);
-                float wValue = getW(wRPerm, wCPerm, d1, d2);
-                dotProd += xValue * wValue;
-              } else {
-                float xValue = getDy(batch, d2, idyR, idyC);
-                float wValue = getW(wRPerm, wCPerm, d1, d2);
-                dotProd += xValue * wValue;
-              }
-
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      class Conv3DDerFilterProgram {
-        constructor(convInfo) {
-          this.variableNames = ["x", "dy"];
-          this.outputShape = convInfo.filterShape;
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const padFront = convInfo.padInfo.front;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          this.userCode = `
-      void main() {
-        ivec5 coords = getOutputCoords();
-        int wF = coords.x;
-        int wR = coords.y;
-        int wC = coords.z;
-        int d1 = coords.w;
-        int d2 = coords.u;
-
-        float dotProd = 0.0;
-
-        for (int b = 0; b < ${convInfo.batchSize}; b++) {
-          for (int yF = 0; yF < ${convInfo.outDepth}; yF++) {
-            int xF = wF + yF * ${strideDepth} - ${padFront};
-
-            if (xF < 0 || xF >= ${convInfo.inDepth}) {
-              continue;
-            }
-
-            for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {
-              int xR = wR + yR * ${strideHeight} - ${padTop};
-
-              if (xR < 0 || xR >= ${convInfo.inHeight}) {
-                continue;
-              }
-
-              for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
-                int xC = wC + yC * ${strideWidth} - ${padLeft};
-
-                if (xC < 0 || xC >= ${convInfo.inWidth}) {
-                  continue;
-                }
-
-                float dyValue = getDy(b, yF, yR, yC, d2);
-                float xValue = getX(b, xF, xR, xC, d1);
-                dotProd += (xValue * dyValue);
-              }
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      class Conv3DDerInputProgram {
-        constructor(convInfo) {
-          this.variableNames = ["dy", "W"];
-          this.outputShape = convInfo.inShape;
-          const filterDepth = convInfo.filterDepth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const padFront = filterDepth - 1 - convInfo.padInfo.front;
-          const padTop = filterHeight - 1 - convInfo.padInfo.top;
-          const padLeft = filterWidth - 1 - convInfo.padInfo.left;
-          this.userCode = `
-      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
-
-      void main() {
-        ivec5 coords = getOutputCoords();
-        int batch = coords.x;
-        int d1 = coords.u;
-
-
-        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
-        int dyFCorner = dyCorner.x;
-        int dyRCorner = dyCorner.y;
-        int dyCCorner = dyCorner.z;
-
-        float dotProd = 0.0;
-        for (int wF = 0; wF < ${filterDepth}; wF++) {
-          float dyF = float(dyFCorner + wF) / ${strideDepth}.0;
-
-          if (dyF < 0.0 || dyF >= ${convInfo.outDepth}.0 || fract(dyF) > 0.0) {
-            continue;
-          }
-          int idyF = int(dyF);
-
-          int wFPerm = ${filterDepth} - 1 - wF;
-
-          for (int wR = 0; wR < ${filterHeight}; wR++) {
-            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
-
-            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||
-              fract(dyR) > 0.0) {
-              continue;
-            }
-            int idyR = int(dyR);
-
-            int wRPerm = ${filterHeight} - 1 - wR;
-
-            for (int wC = 0; wC < ${filterWidth}; wC++) {
-              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
-
-              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
-                  fract(dyC) > 0.0) {
-                continue;
-              }
-              int idyC = int(dyC);
-
-              int wCPerm = ${filterWidth} - 1 - wC;
-
-              for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {
-                float xValue = getDy(batch, idyF, idyR, idyC, d2);
-                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
-                dotProd += xValue * wValue;
-              }
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=conv_backprop_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_backprop_gpu_depthwise.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class DepthwiseConv2DDerFilterProgram {
-        constructor(convInfo) {
-          this.variableNames = ["x", "dy"];
-          this.outputShape = convInfo.filterShape;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          const channelMul = convInfo.outChannels / convInfo.inChannels;
-          this.userCode = `
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int wR = coords.x;
-        int wC = coords.y;
-        int d1 = coords.z;
-        int dm = coords.w;
-        int d2 = d1 * ${channelMul} + dm;
-
-        float dotProd = 0.0;
-
-        // TO DO: Vec4 over the batch size
-        for (int b = 0; b < ${convInfo.batchSize}; b++) {
-          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {
-            int xR = wR + yR * ${strideHeight} - ${padTop};
-
-            if (xR < 0 || xR >= ${convInfo.inHeight}) {
-              continue;
-            }
-
-            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
-              int xC = wC + yC * ${strideWidth} - ${padLeft};
-
-              if (xC < 0 || xC >= ${convInfo.inWidth}) {
-                continue;
-              }
-
-              float dyValue = getDy(b, yR, yC, d2);
-              float xValue = getX(b, xR, xC, d1);
-              dotProd += (xValue * dyValue);
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      class DepthwiseConv2DDerInputProgram {
-        constructor(convInfo) {
-          this.variableNames = ["dy", "W"];
-          this.outputShape = convInfo.inShape;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const padTop = filterHeight - 1 - convInfo.padInfo.top;
-          const padLeft = filterWidth - 1 - convInfo.padInfo.left;
-          const channelMul = convInfo.outChannels / convInfo.inChannels;
-          this.userCode = `
-      const ivec2 pads = ivec2(${padTop}, ${padLeft});
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int batch = coords[0];
-        int d1 = coords[3];
-        ivec2 dyCorner = coords.yz - pads;
-        int dyRCorner = dyCorner.x;
-        int dyCCorner = dyCorner.y;
-
-        float dotProd = 0.0;
-
-        for (int wR = 0; wR < ${filterHeight}; wR++) {
-          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
-
-          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {
-            continue;
-          }
-          int idyR = int(dyR);
-
-          int wRPerm = ${filterHeight} - 1 - wR;
-
-          for (int wC = 0; wC < ${filterWidth}; wC++) {
-            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
-
-            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
-                fract(dyC) > 0.0) {
-              continue;
-            }
-            int idyC = int(dyC);
-
-            int wCPerm = ${filterWidth} - 1 - wC;
-
-            // TO DO: Vec4 over the channelMul
-            for (int dm = 0; dm < ${channelMul}; dm++) {
-              int d2 = d1 * ${channelMul} + dm;
-              float xValue = getDy(batch, idyR, idyC, d2);
-              float wValue = getW(wRPerm, wCPerm, d1, dm);
-              dotProd += xValue * wValue;
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=conv_backprop_gpu_depthwise.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class Conv2DProgram {
-        constructor(
-          convInfo,
-          addBias = false,
-          activation = null,
-          hasPreluActivationWeights = false
-        ) {
-          this.variableNames = ["x", "W"];
-          this.outputShape = convInfo.outShape;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const inputDepthNearestVec4 = Math.floor(convInfo.inChannels / 4) * 4;
-          const inputDepthVec4Remainder = convInfo.inChannels % 4;
-          const isChannelsLast = convInfo.dataFormat === "channelsLast";
-          const rowDim = isChannelsLast ? 1 : 2;
-          const colDim = isChannelsLast ? 2 : 3;
-          const channelDim = isChannelsLast ? 3 : 1;
-          let activationSnippet = "",
-            applyActivationSnippet = "";
-          if (activation) {
-            if (hasPreluActivationWeights) {
-              activationSnippet = `float activation(float a) {
-          float b = getPreluActivationWeightsAtOutCoords();
-          ${activation}
-        }`;
-            } else {
-              activationSnippet = `
-          float activation(float x) {
-            ${activation}
-          }
-        `;
-            }
-            applyActivationSnippet = `result = activation(result);`;
-          }
-          const addBiasSnippet = addBias ? "result += getBiasAtOutCoords();" : "";
-          if (addBias) {
-            this.variableNames.push("bias");
-          }
-          if (hasPreluActivationWeights) {
-            this.variableNames.push("preluActivationWeights");
-          }
-          this.userCode = `
-      ${activationSnippet}
-
-      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
-      const ivec2 pads = ivec2(${padTop}, ${padLeft});
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int batch = coords[0];
-        int d2 = coords[${channelDim}];
-
-        ivec2 xRCCorner =
-            ivec2(coords[${rowDim}], coords[${colDim}]) * strides - pads;
-        int xRCorner = xRCCorner.x;
-        int xCCorner = xRCCorner.y;
-
-        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
-        // ? = to be determined. : = across all values in that axis.
-        float dotProd = 0.0;
-        for (int wR = 0; wR < ${filterHeight}; wR++) {
-          int xR = xRCorner + wR * ${dilationHeight};
-
-          if (xR < 0 || xR >= ${convInfo.inHeight}) {
-            continue;
-          }
-
-          for (int wC = 0; wC < ${filterWidth}; wC++) {
-            int xC = xCCorner + wC * ${dilationWidth};
-
-            if (xC < 0 || xC >= ${convInfo.inWidth}) {
-              continue;
-            }
-
-            for (int d1 = 0; d1 < ${inputDepthNearestVec4}; d1 += 4) {
-              vec4 wValues = vec4(
-                getW(wR, wC, d1, d2),
-                getW(wR, wC, d1 + 1, d2),
-                getW(wR, wC, d1 + 2, d2),
-                getW(wR, wC, d1 + 3, d2)
-              );
-
-              if (${isChannelsLast}) {
-                vec4 xValues = vec4(
-                  getX(batch, xR, xC, d1),
-                  getX(batch, xR, xC, d1 + 1),
-                  getX(batch, xR, xC, d1 + 2),
-                  getX(batch, xR, xC, d1 + 3)
-                );
-                dotProd += dot(xValues, wValues);
-              } else {
-                vec4 xValues = vec4(
-                  getX(batch, d1, xR, xC),
-                  getX(batch, d1 + 1, xR, xC),
-                  getX(batch, d1 + 2, xR, xC),
-                  getX(batch, d1 + 3, xR, xC)
-                );
-                dotProd += dot(xValues, wValues);
-              }
-            }
-
-            if (${inputDepthVec4Remainder === 1}) {
-
-              if (${isChannelsLast}) {
-                dotProd +=
-                    getX(batch, xR, xC, ${inputDepthNearestVec4}) *
-                    getW(wR, wC, ${inputDepthNearestVec4}, d2);
-              } else {
-                dotProd +=
-                    getX(batch, ${inputDepthNearestVec4}, xR, xC) *
-                    getW(wR, wC, ${inputDepthNearestVec4}, d2);
-              }
-
-            } else if (${inputDepthVec4Remainder === 2}) {
-              vec2 wValues = vec2(
-                getW(wR, wC, ${inputDepthNearestVec4}, d2),
-                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2)
-              );
-
-              if (${isChannelsLast}) {
-                vec2 xValues = vec2(
-                  getX(batch, xR, xC, ${inputDepthNearestVec4}),
-                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1)
-                );
-                dotProd += dot(xValues, wValues);
-              } else {
-                vec2 xValues = vec2(
-                  getX(batch, ${inputDepthNearestVec4}, xR, xC),
-                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC)
-                );
-                dotProd += dot(xValues, wValues);
-              }
-
-            } else if (${inputDepthVec4Remainder === 3}) {
-              vec3 wValues = vec3(
-                getW(wR, wC, ${inputDepthNearestVec4}, d2),
-                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2),
-                getW(wR, wC, ${inputDepthNearestVec4} + 2, d2)
-              );
-
-              if (${isChannelsLast}) {
-                vec3 xValues = vec3(
-                  getX(batch, xR, xC, ${inputDepthNearestVec4}),
-                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1),
-                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 2)
-                );
-                dotProd += dot(xValues, wValues);
-              } else {
-                vec3 xValues = vec3(
-                  getX(batch, ${inputDepthNearestVec4}, xR, xC),
-                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC),
-                  getX(batch, ${inputDepthNearestVec4} + 2, xR, xC)
-                );
-                dotProd += dot(xValues, wValues);
-              }
-
-            }
-          }
-        }
-
-        float result = dotProd;
-        ${addBiasSnippet}
-        ${applyActivationSnippet}
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      class Conv3DProgram {
-        constructor(convInfo) {
-          this.variableNames = ["x", "W"];
-          this.outputShape = convInfo.outShape;
-          const padFront = convInfo.padInfo.front;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const filterDepth = convInfo.filterDepth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const inputDepthNearestVec4 = Math.floor(convInfo.inChannels / 4) * 4;
-          const inputDepthVec4Remainder = convInfo.inChannels % 4;
-          this.userCode = `
-      const ivec3 strides = ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
-      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
-
-      void main() {
-        ivec5 coords = getOutputCoords();
-        int batch = coords.x;
-        int d2 = coords.u;
-
-        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
-        int xFCorner = xFRCCorner.x;
-        int xRCorner = xFRCCorner.y;
-        int xCCorner = xFRCCorner.z;
-
-        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
-        // y(yF, yR, yC, d2). ? = to be determined. : = across all
-        // values in that axis.
-        float dotProd = 0.0;
-        for (int wF = 0; wF < ${filterDepth}; wF++) {
-          int xF = xFCorner + wF * ${dilationDepth};
-
-          if (xF < 0 || xF >= ${convInfo.inDepth}) {
-            continue;
-          }
-
-          for (int wR = 0; wR < ${filterHeight}; wR++) {
-            int xR = xRCorner + wR * ${dilationHeight};
-
-            if (xR < 0 || xR >= ${convInfo.inHeight}) {
-              continue;
-            }
-
-            for (int wC = 0; wC < ${filterWidth}; wC++) {
-              int xC = xCCorner + wC * ${dilationWidth};
-
-              if (xC < 0 || xC >= ${convInfo.inWidth}) {
-                continue;
-              }
-
-              for (int d1 = 0; d1 < ${inputDepthNearestVec4}; d1 += 4) {
-                vec4 xValues = vec4(
-                  getX(batch, xF, xR, xC, d1),
-                  getX(batch, xF, xR, xC, d1 + 1),
-                  getX(batch, xF, xR, xC, d1 + 2),
-                  getX(batch, xF, xR, xC, d1 + 3)
-                );
-                vec4 wValues = vec4(
-                  getW(wF, wR, wC, d1, d2),
-                  getW(wF, wR, wC, d1 + 1, d2),
-                  getW(wF, wR, wC, d1 + 2, d2),
-                  getW(wF, wR, wC, d1 + 3, d2)
-                );
-
-                dotProd += dot(xValues, wValues);
-              }
-
-              if (${inputDepthVec4Remainder === 1}) {
-                dotProd +=
-                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}) *
-                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2);
-              } else if (${inputDepthVec4Remainder === 2}) {
-                vec2 xValues = vec2(
-                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),
-                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1)
-                );
-                vec2 wValues = vec2(
-                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),
-                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2)
-                );
-                dotProd += dot(xValues, wValues);
-              } else if (${inputDepthVec4Remainder === 3}) {
-                vec3 xValues = vec3(
-                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),
-                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1),
-                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 2)
-                );
-                vec3 wValues = vec3(
-                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),
-                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2),
-                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 2, d2)
-                );
-                dotProd += dot(xValues, wValues);
-              }
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=conv_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_gpu_depthwise.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class DepthwiseConv2DProgram {
-        constructor(convInfo, addBias = false, activation = null, hasPreluActivation = false) {
-          this.variableNames = ["x", "W"];
-          this.outputShape = convInfo.outShape;
-          const xNumRows = convInfo.inHeight;
-          const xNumCols = convInfo.inWidth;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const channelMul = convInfo.outChannels / convInfo.inChannels;
-          let activationSnippet = "",
-            applyActivationSnippet = "";
-          if (activation) {
-            if (hasPreluActivation) {
-              activationSnippet = `float activation(float a) {
-          float b = getPreluActivationWeightsAtOutCoords();
-          ${activation}
-        }`;
-            } else {
-              activationSnippet = `
-          float activation(float x) {
-            ${activation}
-          }
-        `;
-            }
-            applyActivationSnippet = `result = activation(result);`;
-          }
-          const addBiasSnippet = addBias ? "result += getBiasAtOutCoords();" : "";
-          if (addBias) {
-            this.variableNames.push("bias");
-          }
-          if (hasPreluActivation) {
-            this.variableNames.push("preluActivationWeights");
-          }
-          this.userCode = `
-      ${activationSnippet}
-
-      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
-      const ivec2 pads = ivec2(${padTop}, ${padLeft});
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int batch = coords.x;
-        ivec2 xRCCorner = coords.yz * strides - pads;
-        int d2 = coords.w;
-        int d1 = d2 / ${channelMul};
-        int q = d2 - d1 * ${channelMul};
-
-        int xRCorner = xRCCorner.x;
-        int xCCorner = xRCCorner.y;
-
-        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
-        // ? = to be determined. : = across all values in that axis.
-        float dotProd = 0.0;
-        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
-        for (int wR = 0; wR < ${filterHeight}; wR++) {
-          int xR = xRCorner + wR * ${dilationHeight};
-
-          if (xR < 0 || xR >= ${xNumRows}) {
-            continue;
-          }
-
-          for (int wC = 0; wC < ${filterWidth}; wC++) {
-            int xC = xCCorner + wC * ${dilationWidth};
-
-            if (xC < 0 || xC >= ${xNumCols}) {
-              continue;
-            }
-
-            float xVal = getX(batch, xR, xC, d1);
-            float wVal = getW(wR, wC, d1, q);
-            dotProd += xVal * wVal;
-          }
-        }
-
-        float result = dotProd;
-        ${addBiasSnippet}
-        ${applyActivationSnippet}
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=conv_gpu_depthwise.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_packed_gpu_depthwise.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class conv_packed_gpu_depthwise_DepthwiseConvPacked2DProgram {
-        constructor(convInfo, addBias = false, activation = null, hasPreluActivation = false) {
-          this.variableNames = ["x", "W"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = convInfo.outShape;
-          const xNumRows = convInfo.inHeight;
-          const xNumCols = convInfo.inWidth;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const filterHeight = convInfo.filterHeight;
-          const filterWidth = convInfo.filterWidth;
-          const texelsAcross = filterWidth;
-          let mainLoop = `int xR; int xC; int xCOffset;`;
-          for (let r = 0; r < filterHeight; r++) {
-            for (let c = 0; c < filterWidth; c++) {
-              mainLoop += `
-          vec4 xTexelR${r}C${c * 2} = vec4(0.);
-          vec4 wR${r}C${c} = vec4(0.);
-          vec4 xR${r}C${c} = vec4(0.);`;
-            }
-          }
-          /**
-           * This vectorized implementation works by gathering the values needed for
-           * each output channel's dot product into vec4's and then multiplying them
-           * all together (this happens in the final double for-loop below). Most of
-           * the main loop consists of constructing these vec4's with the minimum
-           * number of texture2D calls, which means making use of all four returned
-           * values from a texture2D call at once.
-           */
-          for (let r = 0; r < filterHeight; r++) {
-            for (let texelC = 0; texelC < texelsAcross; texelC++) {
-              const c = texelC * 2;
-              mainLoop += `
-          xR = xRCorner + ${r * dilationHeight};
-          xC = xCCorner + ${c * dilationWidth};
-        `;
-              if (strideWidth === 1) {
-                if (c < filterWidth) {
-                  // If padding is odd, the outer texels have to be composed.
-                  if (padLeft % 2 === 1) {
-                    // TODO: Ensure vec4 previous does not result in redundant sample,
-                    // and avoid setting xTexelRC's that exceed the boundary in the
-                    // first place rather than resetting them to vec4(0)).
-                    // To compute xCOffset:
-                    // - If padding is odd, we must add 1 to ensure we ask for an
-                    // even-numbered row.
-                    // - We subtract 2 to access the previous texel.
-                    mainLoop += `
-                xCOffset = xC + 1;
-                if(xR >= 0 && xR < ${xNumRows} && xCOffset >= 0 && xCOffset < ${xNumCols}) {
-                  xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);
-
-                  // Need to manually clear unused channels in case
-                  // we're reading from recycled texture.
-                  if(xCOffset + 1 >= ${xNumCols}) {
-                    xTexelR${r}C${c}.zw = vec2(0.);
-                  }
-                } else {
-                  xTexelR${r}C${c} = vec4(0.);
-                }
-
-                xCOffset = xC + 1 - 2;
-                if(xR >= 0 && xR < ${xNumRows} && xCOffset >= 0 && xCOffset < ${xNumCols}) {
-                  vec4 previous = getX(batch, xR, xCOffset, d1);
-
-                  // Need to manually clear unused channels in case
-                  // we're reading from recycled texture.
-                  if(xCOffset + 1 >= ${xNumCols}) {
-                    previous.zw = vec2(0.);
-                  }
-
-                  xR${r}C${c} = vec4(previous.zw, xTexelR${r}C${c}.xy);
-                } else {
-                  xR${r}C${c} = vec4(0, 0, xTexelR${r}C${c}.xy);
-                }
-              `;
-                  } else {
-                    // Padding is even, so xRC corresponds to a single texel.
-                    mainLoop += `
-                if(xR >= 0 && xR < ${xNumRows} && xC >= 0 && xC < ${xNumCols}) {
-                  xTexelR${r}C${c} = getX(batch, xR, xC, d1);
-                } else {
-                  xTexelR${r}C${c} = vec4(0.);
-                }
-
-                xR${r}C${c} = xTexelR${r}C${c};
-              `;
-                  }
-                  if (c + 1 < filterWidth) {
-                    // If dilation is even, the second entry should match the first
-                    // (either both are composed or both are single samples). But if
-                    // dilation is odd, then the second entry should be the opposite
-                    // of the first (if the first is composed, the second is a single
-                    // sample, and vice versa.)
-                    const nextTexelOffset =
-                      padLeft % 2 === 0
-                        ? dist["util"].nearestLargerEven(dilationWidth)
-                        : dilationWidth;
-                    if (
-                      (dilationWidth % 2 === 0 && padLeft % 2 === 1) ||
-                      (dilationWidth % 2 !== 0 && padLeft % 2 !== 1)
-                    ) {
-                      mainLoop += `
-                  xCOffset = xC + ${padLeft % 2} + ${nextTexelOffset};
-
-                  if(xR >= 0 && xR < ${xNumRows} &&
-                    xCOffset >= 0 && xCOffset < ${xNumCols}) {
-                    xTexelR${r}C${c + 2} = getX(batch, xR, xCOffset, d1);
-                  }
-                `;
-                      // If dilation > 1 then the xRC's will not be able to share any
-                      // values, so each xRC will require two unique calls to getX.
-                      if (dilationWidth > 1) {
-                        mainLoop += `
-                    xCOffset -= 2;
-                    if(xR >= 0 && xR < ${xNumRows} &&
-                      xCOffset >= 0 && xCOffset < ${xNumCols}) {
-                      xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);
-                    } else {
-                      xTexelR${r}C${c} = vec4(0.);
-                    }
-                  `;
-                      }
-                      mainLoop += `
-                  xR${r}C${c + 1} = vec4(
-                    xTexelR${r}C${c}.zw, xTexelR${r}C${c + 2}.xy);
-                `;
-                    } else {
-                      mainLoop += `
-                  xCOffset = xC + ${nextTexelOffset};
-
-                  if(xR >= 0 && xR < ${xNumRows} &&
-                    xCOffset >= 0 && xCOffset < ${xNumCols}) {
-                    xTexelR${r}C${c + 2} = getX(batch, xR, xCOffset, d1);
-                  }
-
-                  xR${r}C${c + 1} = xTexelR${r}C${c + 2};
-                `;
-                    }
-                  }
-                }
-              } else {
-                // stride > 1
-                if (c < filterWidth) {
-                  mainLoop += `
-              if(xR >= 0 && xR < ${xNumRows}) {
-            `;
-                  // Depending on whether padLeft is even or odd, we want either the
-                  // xy or zw channels from X texels for xR${r}C${c}. If padLeft is
-                  // even, xR${r}C${c + 1} is simply the zw channels of texels we've
-                  // already sampled. But if padLeft is odd, xR${r}C{$c + 1}.zw will
-                  // need to come from the xy channels of a new texel, hence the `vec4
-                  // final` initialized below.
-                  if (padLeft % 2 === 1) {
-                    mainLoop += `
-                xCOffset = xC + 1 - ${strideWidth};
-                if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
-                  xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);
-                } else {
-                  xTexelR${r}C${c} = vec4(0.);
-                }
-
-                if(xC + 1 >= 0 && xC + 1 < ${xNumCols}) {
-                  xTexelR${r}C${c + 2} = getX(batch, xR, xC + 1, d1);
-                } else {
-                  xTexelR${r}C${c + 2} = vec4(0.);
-                }
-
-                xR${r}C${c} = vec4(
-                  xTexelR${r}C${c}.zw, xTexelR${r}C${c + 2}.zw);
-              `;
-                    if (c + 1 < filterWidth) {
-                      mainLoop += `
-                  vec4 final = vec4(0.);
-                  xCOffset = xC + 1 + ${strideWidth};
-                  if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
-                    final = getX(batch, xR, xCOffset, d1);
-                  }
-                  xR${r}C${c + 1} = vec4(xTexelR${r}C${c + 2}.xy, final.xy);
-                `;
-                    }
-                  } else {
-                    mainLoop += `
-                if(xC >= 0 && xC < ${xNumCols}) {
-                  xTexelR${r}C${c} = getX(batch, xR, xC, d1);
-                } else {
-                  xTexelR${r}C${c} = vec4(0.);
-                }
-
-                xCOffset = xC + ${strideWidth};
-                if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
-                  xTexelR${r}C${c + 2} = getX(batch, xR, xCOffset, d1);
-                } else {
-                  xTexelR${r}C${c + 2} = vec4(0.);
-                }
-
-                xR${r}C${c} = vec4(
-                  xTexelR${r}C${c}.xy, xTexelR${r}C${c + 2}.xy);
-              `;
-                    if (c + 1 < filterWidth) {
-                      mainLoop += `
-                  xR${r}C${c + 1} = vec4(
-                    xTexelR${r}C${c}.zw, xTexelR${r}C${c + 2}.zw);
-                `;
-                    }
-                  }
-                  mainLoop += `}`;
-                }
-              }
-              if (c < filterWidth) {
-                mainLoop += `
-            vec4 wTexelR${r}C${c} = getW(${r}, ${c}, d1, q);
-            wR${r}C${c} = vec4(wTexelR${r}C${c}.xz, wTexelR${r}C${c}.xz);
-          `;
-                if (c + 1 < filterWidth) {
-                  mainLoop += `
-              vec4 wTexelR${r}C${c + 1} = getW(${r}, ${c + 1}, d1, q);
-              wR${r}C${c + 1} =
-                vec4(wTexelR${r}C${c + 1}.xz, wTexelR${r}C${c + 1}.xz);`;
-                }
-              }
-            }
-          }
-          for (let r = 0; r < filterHeight; r++) {
-            for (let c = 0; c < filterWidth; c++) {
-              mainLoop += `dotProd += xR${r}C${c} * wR${r}C${c};`;
-            }
-          }
-          let activationSnippet = "",
-            applyActivationSnippet = "";
-          if (activation) {
-            if (hasPreluActivation) {
-              activationSnippet = `vec4 activation(vec4 a) {
-          vec4 b = getPreluActivationWeightsAtOutCoords();
-          ${activation}
-        }`;
-            } else {
-              activationSnippet = `vec4 activation(vec4 x) {
-          ${activation}
-        }`;
-            }
-            applyActivationSnippet = `result = activation(result);`;
-          }
-          const addBiasSnippet = addBias ? "result += getBiasAtOutCoords();" : "";
-          if (addBias) {
-            this.variableNames.push("bias");
-          }
-          if (hasPreluActivation) {
-            this.variableNames.push("preluActivationWeights");
-          }
-          this.userCode = `
-      ${activationSnippet}
-
-      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
-      const ivec2 pads = ivec2(${padTop}, ${padLeft});
-
-      void main() {
-
-        ivec4 coords = getOutputCoords();
-        int batch = coords.x;
-        ivec2 xRCCorner = coords.yz * strides - pads;
-        int d2 = coords.w;
-        int d1 = d2;
-        int q = 0;
-        int xRCorner = xRCCorner.x;
-        int xCCorner = xRCCorner.y;
-
-        vec4 dotProd = vec4(0.);
-
-        ${mainLoop}
-
-        vec4 result = dotProd;
-        ${addBiasSnippet}
-        ${applyActivationSnippet}
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=conv_packed_gpu_depthwise.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/crop_and_resize_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class CropAndResizeProgram {
-        constructor(imageShape, boxShape, cropSize, method, extrapolationValue) {
-          this.variableNames = ["Image", "Boxes", "BoxInd"];
-          this.outputShape = [];
-          const [batch, imageHeight, imageWidth, depth] = imageShape;
-          const [numBoxes] = boxShape;
-          const [cropHeight, cropWidth] = cropSize;
-          this.outputShape = [numBoxes, cropHeight, cropWidth, depth];
-          const methodId = method === "bilinear" ? 1 : 0;
-          const [inputHeightFloat, inputWidthFloat] = [
-            `${imageHeight - 1}.0`,
-            `${imageWidth - 1}.0`,
-          ];
-          const [heightRatio, heightScale, inY] =
-            cropHeight > 1
-              ? [
-                  `${(imageHeight - 1) / (cropHeight - 1)}`,
-                  "(y2-y1) * height_ratio",
-                  `y1*${inputHeightFloat} + float(y)*(height_scale)`,
-                ]
-              : ["0.0", "0.0", `0.5 * (y1+y2) * ${inputHeightFloat}`];
-          const [widthRatio, widthScale, inX] =
-            cropWidth > 1
-              ? [
-                  `${(imageWidth - 1) / (cropWidth - 1)}`,
-                  "(x2-x1) * width_ratio",
-                  `x1*${inputWidthFloat} + float(x)*(width_scale)`,
-                ]
-              : ["0.0", "0.0", `0.5 * (x1+x2) * ${inputWidthFloat}`];
-          // Reference implementation
-          // tslint:disable-next-line:max-line-length
-          // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/crop_and_resize_op_gpu.cu.cc
-          this.userCode = `
-      const float height_ratio = float(${heightRatio});
-      const float width_ratio = float(${widthRatio});
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int y = coords[1];
-        int x = coords[2];
-        int d = coords[3];
-
-        // get box vals
-        float y1 = getBoxes(b,0);
-        float x1 = getBoxes(b,1);
-        float y2 = getBoxes(b,2);
-        float x2 = getBoxes(b,3);
-
-        // get image in batch index
-        int bInd = round(getBoxInd(b));
-        if(bInd < 0 || bInd >= ${batch}) {
-          return;
-        }
-
-        float height_scale = ${heightScale};
-        float width_scale = ${widthScale};
-
-        float in_y = ${inY};
-        if( in_y < 0.0 || in_y > ${inputHeightFloat} ) {
-          setOutput(float(${extrapolationValue}));
-          return;
-        }
-        float in_x = ${inX};
-        if( in_x < 0.0 || in_x > ${inputWidthFloat} ) {
-          setOutput(float(${extrapolationValue}));
-          return;
-        }
-
-        vec2 sourceFracIndexCR = vec2(in_x,in_y);
-        if(${methodId} == 1) {
-          // Compute the four integer indices.
-          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
-          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
-
-          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
-          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
-          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
-          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
-
-          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
-
-          float top = topLeft + (topRight - topLeft) * fracCR.x;
-          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
-          float newValue = top + (bottom - top) * fracCR.y;
-          setOutput(newValue);
-        } else {
-          // Compute the coordinators of nearest neighbor point.
-          ivec2 sourceNearestCR = ivec2(floor(
-            sourceFracIndexCR + vec2(0.5,0.5)));
-          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
-          setOutput(newValue);
-        }
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=crop_and_resize_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/cumsum_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class cumsum_gpu_CumSumProgram {
-        constructor(shape, exclusive, reverse) {
-          this.variableNames = ["x"];
-          this.outputShape = shape;
-          const rank = shape.length;
-          const finalDim = shape[shape.length - 1];
-          const comparator = reverse ? "<" : ">";
-          this.userCode = `
-      int getIndex(int i) {
-        ${reverse ? `return ${finalDim} -i - 1;` : "return i;"}
-      }
-
-      void main() {
-        ${getCoordsDataType(rank)} coords = getOutputCoords();
-        int end = ${getFinalCoord(rank, "coords")};
-        float val = 0.0;
-        for (int i = ${finalDim} - 1; i >= 0; i -= 1) {
-          int idx = getIndex(i);
-          if (idx ${comparator} end) {
-            continue;
-          }
-          if (idx == end && ${exclusive}) {
-            continue;
-          }
-          ${getFinalCoord(rank, "coords")} = idx;
-          val += getX(${getCoords(rank, "coords")});
-        }
-        setOutput(val);
-      }
-    `;
-        }
-      }
-      function getCoords(rank, name) {
-        if (rank === 1) {
-          return `${name}`;
-        } else if (rank === 2) {
-          return `${name}.x, ${name}.y`;
-        } else if (rank === 3) {
-          return `${name}.x, ${name}.y, ${name}.z`;
-        } else if (rank === 4) {
-          return `${name}.x, ${name}.y, ${name}.z, ${name}.w`;
-        } else {
-          throw Error(`Cumulative sum for rank ${rank} is not yet supported`);
-        }
-      }
-      function getFinalCoord(rank, name) {
-        if (rank === 1) {
-          return `${name}`;
-        } else if (rank === 2) {
-          return `${name}.y`;
-        } else if (rank === 3) {
-          return `${name}.z`;
-        } else if (rank === 4) {
-          return `${name}.w`;
-        } else {
-          throw Error(`Cumulative sum for rank ${rank} is not yet supported`);
-        }
-      }
-      //# sourceMappingURL=cumsum_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/decode_matrix_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class decode_matrix_gpu_DecodeMatrixProgram {
-        constructor(outputShape) {
-          this.variableNames = ["A"];
-          this.packedInputs = false;
-          this.packedOutput = true;
-          this.outPackingScheme = PackingScheme.DENSE;
-          const texShape = getDenseTexShape(outputShape);
-          const glsl = getGlslDifferences();
-          this.outputShape = outputShape;
-          this.userCode = `
-      ivec3 outCoordsFromFlatIndex(int index) {
-        ${getLogicalCoordinatesFromFlatIndex(["r", "c", "d"], outputShape)}
-        return ivec3(r, c, d);
-      }
-
-      void main() {
-        ivec2 resTexRC = ivec2(resultUV.yx *
-          vec2(${texShape[0]}, ${texShape[1]}));
-        int index = 4 * (resTexRC.x * ${texShape[1]} + resTexRC.y);
-
-        vec4 result = vec4(0.);
-
-        for (int i=0; i<4; i++) {
-          int flatIndex = index + i;
-          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
-          result[i] = getA(rc.x, rc.y, rc.z);
-        }
-
-        ${glsl.output} = result;
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=decode_matrix_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/decode_matrix_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class decode_matrix_packed_gpu_DecodeMatrixPackedProgram {
-        constructor(outputShape) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outPackingScheme = PackingScheme.DENSE;
-          const texShape = getDenseTexShape(outputShape);
-          const glsl = getGlslDifferences();
-          this.outputShape = outputShape;
-          this.userCode = `
-      ivec3 outCoordsFromFlatIndex(int index) {
-        ${getLogicalCoordinatesFromFlatIndex(["r", "c", "d"], outputShape)}
-        return ivec3(r, c, d);
-      }
-
-      void main() {
-        ivec2 resTexRC = ivec2(resultUV.yx *
-          vec2(${texShape[0]}, ${texShape[1]}));
-        int index = 4 * (resTexRC.x * ${texShape[1]} + resTexRC.y);
-
-        vec4 result = vec4(0.);
-
-        for (int i=0; i<4; i++) {
-          int flatIndex = index + i;
-          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
-          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
-        }
-
-        ${glsl.output} = result;
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=decode_matrix_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/depth_to_space_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class DepthToSpaceProgram {
-        constructor(outputShape, blockSize, dataFormat) {
-          this.variableNames = ["x"];
-          this.outputShape = [];
-          this.outputShape = outputShape;
-          this.blockSize = blockSize;
-          this.dataFormat = dataFormat;
-          this.userCode = `
-    void main() {
-      ivec4 coords = getOutputCoords();
-      int b = coords[0];
-      int h = ${this.getHeightCoordString()};
-      int w = ${this.getWidthCoordString()};
-      int d = ${this.getDepthCoordString()};
-
-      int in_h = h / ${blockSize};
-      int offset_h = imod(h, ${blockSize});
-      int in_w = w / ${blockSize};
-      int offset_w = imod(w, ${blockSize});
-      int offset_d = (offset_h * ${blockSize} + offset_w) *
-        ${this.getOutputDepthSize()};
-      int in_d = d + offset_d;
-
-      float result = ${this.getInputSamplingString()};
-      setOutput(result);
-    }
-  `;
-        }
-        getHeightCoordString() {
-          if (this.dataFormat === "NHWC") {
-            return `coords[1]`;
-          } else {
-            return `coords[2]`;
-          }
-        }
-        getWidthCoordString() {
-          if (this.dataFormat === "NHWC") {
-            return `coords[2]`;
-          } else {
-            return `coords[3]`;
-          }
-        }
-        getDepthCoordString() {
-          if (this.dataFormat === "NHWC") {
-            return `coords[3]`;
-          } else {
-            return `coords[1]`;
-          }
-        }
-        getOutputDepthSize() {
-          if (this.dataFormat === "NHWC") {
-            return this.outputShape[3];
-          } else {
-            return this.outputShape[1];
-          }
-        }
-        getInputSamplingString() {
-          if (this.dataFormat === "NHWC") {
-            return `getX(b, in_h, in_w, in_d)`;
-          } else {
-            return `getX(b, in_d, in_h, in_w)`;
-          }
-        }
-      }
-      //# sourceMappingURL=depth_to_space_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/diag_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class DiagProgram {
-        constructor(size) {
-          this.variableNames = ["X"];
-          this.outputShape = [size, size];
-          this.userCode = `
-      void main() {
-          ivec2 coords = getOutputCoords();
-          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
-          setOutput(val);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=diag_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_float_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class encode_float_gpu_EncodeFloatProgram {
-        constructor(outputShape) {
-          this.variableNames = ["A"];
-          this.outTexUsage = TextureUsage.DOWNLOAD;
-          const glsl = getGlslDifferences();
-          this.outputShape = outputShape;
-          this.userCode = `
-      ${ENCODE_FLOAT_SNIPPET}
-
-      void main() {
-        float x = getAAtOutCoords();
-        ${glsl.output} = encode_float(x);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=encode_float_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_float_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class encode_float_packed_gpu_EncodeFloatPackedProgram {
-        constructor(outputShape) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = false;
-          this.outTexUsage = TextureUsage.DOWNLOAD;
-          const glsl = getGlslDifferences();
-          this.outputShape = outputShape;
-          this.userCode = `
-      ${ENCODE_FLOAT_SNIPPET}
-
-      void main() {
-        ivec3 coords = getOutputCoords();
-        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
-        ${glsl.output} = encode_float(x);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=encode_float_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_matrix_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class encode_matrix_gpu_EncodeMatrixProgram {
-        constructor(outputShape, texShape, inputIsUnsignedByte = false) {
-          this.variableNames = ["A"];
-          const glsl = getGlslDifferences();
-          const [height, width] = texShape;
-          this.outputShape = outputShape;
-          let output = `result`;
-          if (inputIsUnsignedByte) {
-            output = `floor(result * 255. + 0.5)`;
-          }
-          this.userCode = `
-      ${getFlatIndexFrom3D(outputShape)}
-
-      void main() {
-        ivec3 coords = getOutputCoords();
-
-        int flatIndex = getFlatIndex(coords);
-        int offset = imod(flatIndex, 4);
-
-        flatIndex = idiv(flatIndex, 4, 1.);
-        
-        int r = flatIndex / ${width};
-        int c = imod(flatIndex, ${width});
-        vec2 uv = (vec2(c, r) + halfCR) / vec2(${width}.0, ${height}.0);
-        vec4 values = ${glsl.texture2D}(A, uv);
-
-        float result;
-
-        if(offset == 0) {
-          result = values[0];
-        } else if(offset == 1) {
-          result = values[1];
-        } else if(offset == 2) {
-          result = values[2];
-        } else {
-          result = values[3];
-        }
-
-        ${glsl.output} = vec4(${output}, 0., 0., 0.);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=encode_matrix_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_matrix_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      /*
-This is how the shader encodes a tensor with shape = [2, 3, 5]
-(indices are [batch, row, col]).
-
-000|001   002|003   004|xxx   020|021   022|023   024|xxx
--------   -------   -------   -------   -------   -------
-010|011   012|013   014|xxx   xxx|xxx   xxx|xxx   xxx|xxx
-
-100|101   102|103   104|xxx   120|121   122|123   124|xxx
--------   -------   -------   -------   -------   -------
-110|111   112|113   114|xxx   xxx|xxx   xxx|xxx   xxx|xxx
-
-Single texels contain only values from the same batch, and from adjacent rows
-and columns.
- */
-      class encode_matrix_packed_gpu_EncodeMatrixPackedProgram {
-        constructor(outputShape, texShape, inputIsUnsignedByte = false) {
-          this.variableNames = ["A"];
-          this.packedInputs = false;
-          this.packedOutput = true;
-          const glsl = getGlslDifferences();
-          const [height, width] = texShape;
-          this.outputShape = outputShape;
-          let mainLoop = "";
-          let output = "result";
-          if (inputIsUnsignedByte) {
-            output = "floor(result * 255. + 0.5)";
-          }
-          for (let row = 0; row <= 1; row++) {
-            for (let col = 0; col <= 1; col++) {
-              const channel = row * 2 + col;
-              mainLoop += `
-          localCoords = coords;
-          if(localCoords[2] + ${col} < ${outputShape[2]}) {
-            localCoords[2] += ${col};
-            if(localCoords[1] + ${row} < ${outputShape[1]}) {
-              localCoords[1] += ${row};
-
-              flatIndex = getFlatIndex(localCoords);
-              offset = imod(flatIndex, 4);
-
-              flatIndex = idiv(flatIndex, 4, 1.);
-
-              r = flatIndex / ${width};
-              c = imod(flatIndex, ${width});
-              uv = (vec2(c, r) + halfCR) / vec2(${width}.0, ${height}.0);
-              values = ${glsl.texture2D}(A, uv);
-
-              if(offset == 0) {
-                result[${channel}] = values[0];
-              } else if(offset == 1) {
-                result[${channel}] = values[1];
-              } else if(offset == 2) {
-                result[${channel}] = values[2];
-              } else {
-                result[${channel}] = values[3];
-              }
-            }
-          }
-        `;
-            }
-          }
-          this.userCode = `
-      ${getFlatIndexFrom3D(outputShape)}
-
-      void main() {
-        ivec3 coords = getOutputCoords();
-
-        vec4 result = vec4(0.);
-        int flatIndex, r, c, offset;
-        ivec3 localCoords;
-        vec2 uv;
-        vec4 values;
-
-        ${mainLoop}
-
-        ${glsl.output} = ${output};
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=encode_matrix_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/fft_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const COMPLEX_FFT = {
-        REAL: "return real * expR - imag * expI;",
-        IMAG: "return real * expI + imag * expR;",
-      };
-      class FFTProgram {
-        constructor(op, inputShape, inverse) {
-          this.variableNames = ["real", "imag"];
-          const innerDim = inputShape[1];
-          this.outputShape = inputShape;
-          const exponentMultiplierSnippet = inverse ? `2.0 * ${Math.PI}` : `-2.0 * ${Math.PI}`;
-          const resultDenominator = inverse ? `${innerDim}.0` : "1.0";
-          this.userCode = `
-      const float exponentMultiplier = ${exponentMultiplierSnippet};
-
-      float unaryOpComplex(float real, float expR, float imag, float expI) {
-        ${op}
-      }
-
-      float mulMatDFT(int batch, int index) {
-        float indexRatio = float(index) / float(${innerDim});
-        float exponentMultiplierTimesIndexRatio =
-            exponentMultiplier * indexRatio;
-
-        float result = 0.0;
-
-        for (int i = 0; i < ${innerDim}; i++) {
-          // x = (-2|2 * PI / N) * index * i;
-          float x = exponentMultiplierTimesIndexRatio * float(i);
-          float expR = cos(x);
-          float expI = sin(x);
-          float real = getReal(batch, i);
-          float imag = getImag(batch, i);
-
-          result +=
-              unaryOpComplex(real, expR, imag, expI) / ${resultDenominator};
-        }
-
-        return result;
-      }
-
-      void main() {
-        ivec2 coords = getOutputCoords();
-        setOutput(mulMatDFT(coords[0], coords[1]));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=fft_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/fill_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class FillProgram {
-        constructor(shape, value) {
-          this.outputShape = [];
-          this.variableNames = ["x"];
-          this.outputShape = shape;
-          this.userCode = `
-      uniform float value;
-      void main() {
-        // Input can be obtained from uniform value.
-        setOutput(value);
-      }
-    `;
-        }
-        getCustomSetupFunc(value) {
-          return (gpgpu, webGLProgram) => {
-            if (this.valueLoc == null) {
-              this.valueLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "value");
-            }
-            gpgpu.gl.uniform1f(this.valueLoc, value);
-          };
-        }
-      }
-      //# sourceMappingURL=fill_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gather_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class gather_gpu_GatherProgram {
-        constructor(aShape, indicesLength, axis) {
-          this.variableNames = ["A", "indices"];
-          const outputShape = aShape.slice();
-          outputShape[axis] = indicesLength;
-          this.outputShape = outputShape;
-          this.rank = outputShape.length;
-          const dtype = getCoordsDataType(this.rank);
-          const sourceCoords = gather_gpu_getSourceCoords(aShape, axis);
-          this.userCode = `
-      void main() {
-        ${dtype} resRC = getOutputCoords();
-        setOutput(getA(${sourceCoords}));
-      }
-    `;
-        }
-      }
-      function gather_gpu_getSourceCoords(aShape, axis) {
-        const rank = aShape.length;
-        if (rank > 4) {
-          throw Error(`Gather for rank ${rank} is not yet supported`);
-        }
-        if (rank === 1) {
-          return `int(getIndices(resRC))`;
-        }
-        const currentCoords = ["resRC.x", "resRC.y", "resRC.z", "resRC.w"];
-        const sourceCoords = [];
-        for (let i = 0; i < aShape.length; i++) {
-          if (i === axis) {
-            sourceCoords.push(`int(getIndices(${currentCoords[i]}))`);
-          } else {
-            sourceCoords.push(`${currentCoords[i]}`);
-          }
-        }
-        return sourceCoords.join();
-      }
-      //# sourceMappingURL=gather_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gather_nd_gpu.js
-
-      class gather_nd_gpu_GatherNDProgram {
-        constructor(sliceDim, strides, shape) {
-          this.sliceDim = sliceDim;
-          this.strides = strides;
-          this.variableNames = ["x", "indices"];
-          this.outputShape = shape;
-          const stridesType = getCoordsDataType(strides.length);
-          const dtype = getCoordsDataType(shape.length);
-          const strideString = this.sliceDim > 1 ? "strides[j]" : "strides";
-          this.userCode = `
-        ${stridesType} strides = ${stridesType}(${this.strides});
-         void main() {
-          ${dtype} coords = getOutputCoords();
-          int flattenIndex = 0;
-          for (int j = 0; j < ${this.sliceDim}; j++) {
-            int index = round(getIndices(coords[0], j));
-            flattenIndex += index * ${strideString};
-          }
-          setOutput(getX(flattenIndex, coords[1]));
-        }
-      `;
-        }
-      }
-      //# sourceMappingURL=gather_nd_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_util.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function gpgpu_util_createVertexShader(gl, debug) {
-        const glsl = getGlslDifferences();
-        const vertexShaderSource = `${glsl.version}
-    precision highp float;
-    ${glsl.attribute} vec3 clipSpacePos;
-    ${glsl.attribute} vec2 uv;
-    ${glsl.varyingVs} vec2 resultUV;
-
-    void main() {
-      gl_Position = vec4(clipSpacePos, 1);
-      resultUV = uv;
-    }`;
-        return createVertexShader(gl, debug, vertexShaderSource);
-      }
-      function createVertexBuffer(gl, debug) {
-        // [x y z u v] * [upper-left, lower-left, upper-right, lower-right]
-        const vertexArray = new Float32Array([
-          -1, 1, 0, 0, 1, -1, -1, 0, 0, 0, 1, 1, 0, 1, 1, 1, -1, 0, 1, 0,
-        ]);
-        return createStaticVertexBuffer(gl, debug, vertexArray);
-      }
-      function createIndexBuffer(gl, debug) {
-        // OpenGL (and WebGL) have "CCW == front" winding
-        const triangleVertexIndices = new Uint16Array([0, 1, 2, 2, 1, 3]);
-        return createStaticIndexBuffer(gl, debug, triangleVertexIndices);
-      }
-      function createAndConfigureTexture(
-        gl,
-        debug,
-        width,
-        height,
-        internalFormat,
-        textureFormat,
-        textureType
-      ) {
-        validateTextureSize(width, height);
-        const texture = createTexture(gl, debug);
-        const tex2d = gl.TEXTURE_2D;
-        callAndCheck(gl, debug, () => gl.bindTexture(tex2d, texture));
-        callAndCheck(gl, debug, () => gl.texParameteri(tex2d, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE));
-        callAndCheck(gl, debug, () => gl.texParameteri(tex2d, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE));
-        callAndCheck(gl, debug, () => gl.texParameteri(tex2d, gl.TEXTURE_MIN_FILTER, gl.NEAREST));
-        callAndCheck(gl, debug, () => gl.texParameteri(tex2d, gl.TEXTURE_MAG_FILTER, gl.NEAREST));
-        callAndCheck(gl, debug, () =>
-          gl.texImage2D(
-            tex2d,
-            0,
-            internalFormat,
-            width,
-            height,
-            0,
-            textureFormat,
-            textureType,
-            null
-          )
-        );
-        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, null));
-        return texture;
-      }
-      function createFloat32MatrixTexture(gl, debug, rows, columns, textureConfig) {
-        const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);
-        return createAndConfigureTexture(
-          gl,
-          debug,
-          width,
-          height,
-          textureConfig.internalFormatFloat,
-          textureConfig.textureFormatFloat,
-          gl.FLOAT
-        );
-      }
-      function createFloat16MatrixTexture(gl, debug, rows, columns, textureConfig) {
-        const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);
-        return createAndConfigureTexture(
-          gl,
-          debug,
-          width,
-          height,
-          textureConfig.internalFormatHalfFloat,
-          textureConfig.textureFormatFloat,
-          textureConfig.textureTypeHalfFloat
-        );
-      }
-      function createUnsignedBytesMatrixTexture(gl, debug, rows, columns, textureConfig) {
-        const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);
-        return createAndConfigureTexture(
-          gl,
-          debug,
-          width,
-          height,
-          gl.RGBA,
-          gl.RGBA,
-          gl.UNSIGNED_BYTE
-        );
-      }
-      function createPackedMatrixTexture(gl, debug, rows, columns, textureConfig) {
-        const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);
-        return createAndConfigureTexture(
-          gl,
-          debug,
-          width,
-          height,
-          textureConfig.internalFormatPackedFloat,
-          gl.RGBA,
-          gl.FLOAT
-        );
-      }
-      function createFloat16PackedMatrixTexture(gl, debug, rows, columns, textureConfig) {
-        const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);
-        return createAndConfigureTexture(
-          gl,
-          debug,
-          width,
-          height,
-          textureConfig.internalFormatPackedHalfFloat,
-          gl.RGBA,
-          textureConfig.textureTypeHalfFloat
-        );
-      }
-      function bindVertexProgramAttributeStreams(gl, debug, program, vertexBuffer) {
-        const posOffset = 0; // x is the first buffer element
-        const uvOffset = 3 * 4; // uv comes after [x y z]
-        const stride = 3 * 4 + 2 * 4; // xyz + uv, each entry is 4-byte float.
-        callAndCheck(gl, debug, () => gl.bindBuffer(gl.ARRAY_BUFFER, vertexBuffer));
-        const success = bindVertexBufferToProgramAttribute(
-          gl,
-          debug,
-          program,
-          "clipSpacePos",
-          vertexBuffer,
-          3,
-          stride,
-          posOffset
-        );
-        return (
-          success &&
-          bindVertexBufferToProgramAttribute(
-            gl,
-            debug,
-            program,
-            "uv",
-            vertexBuffer,
-            2,
-            stride,
-            uvOffset
-          )
-        );
-      }
-      function uploadDenseMatrixToTexture(gl, debug, texture, width, height, data, textureConfig) {
-        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, texture));
-        let dataForUpload, texelDataType, internalFormat;
-        if (data instanceof Uint8Array) {
-          dataForUpload = new Uint8Array(width * height * 4);
-          texelDataType = gl.UNSIGNED_BYTE;
-          internalFormat = gl.RGBA;
-        } else {
-          dataForUpload = new Float32Array(width * height * 4);
-          texelDataType = gl.FLOAT;
-          internalFormat = textureConfig.internalFormatPackedFloat;
-        }
-        dataForUpload.set(data);
-        callAndCheck(gl, debug, () =>
-          gl.texImage2D(
-            gl.TEXTURE_2D,
-            0,
-            internalFormat,
-            width,
-            height,
-            0,
-            gl.RGBA,
-            texelDataType,
-            dataForUpload
-          )
-        );
-        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, null));
-      }
-      function uploadPixelDataToTexture(gl, debug, texture, pixels) {
-        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, texture));
-        if (pixels.data instanceof Uint8Array) {
-          callAndCheck(gl, debug, () =>
-            gl.texImage2D(
-              gl.TEXTURE_2D,
-              0,
-              gl.RGBA,
-              pixels.width,
-              pixels.height,
-              0,
-              gl.RGBA,
-              gl.UNSIGNED_BYTE,
-              pixels.data
-            )
-          );
-        } else {
-          callAndCheck(gl, debug, () =>
-            gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, pixels)
-          );
-        }
-        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, null));
-      }
-      function createBufferFromOutputTexture(gl2, debug, rows, columns, textureConfig) {
-        // Create and bind the buffer.
-        const buffer = gl2.createBuffer();
-        callAndCheck(gl2, debug, () => gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer));
-        // Initialize the buffer to the size of the texture in bytes.
-        const bytesPerFloat = 4;
-        const valuesPerTexel = 4;
-        const bufferSizeBytes = bytesPerFloat * valuesPerTexel * rows * columns;
-        callAndCheck(gl2, debug, () =>
-          gl2.bufferData(gl2.PIXEL_PACK_BUFFER, bufferSizeBytes, gl2.STREAM_READ)
-        );
-        // Enqueue a command on the GPU command queue to copy of texture into the
-        // buffer.
-        callAndCheck(gl2, debug, () => gl2.readPixels(0, 0, columns, rows, gl2.RGBA, gl2.FLOAT, 0));
-        callAndCheck(gl2, debug, () => gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null));
-        return buffer;
-      }
-      function downloadFloat32MatrixFromBuffer(gl, buffer, size) {
-        const gl2 = gl;
-        const downloadTarget = new Float32Array(size);
-        gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer);
-        gl2.getBufferSubData(gl2.PIXEL_PACK_BUFFER, 0, downloadTarget);
-        gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null);
-        return downloadTarget;
-      }
-      function downloadByteEncodedFloatMatrixFromOutputTexture(
-        gl,
-        debug,
-        rows,
-        columns,
-        textureConfig
-      ) {
-        const [w, h] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);
-        const numChannels = 4;
-        const downloadTarget = new Uint8Array(
-          getUnpackedArraySizeFromMatrixSize(rows * columns, numChannels)
-        );
-        callAndCheck(gl, debug, () =>
-          gl.readPixels(
-            0,
-            0,
-            w,
-            h,
-            textureConfig.downloadTextureFormat,
-            gl.UNSIGNED_BYTE,
-            downloadTarget
-          )
-        );
-        // By wrapping the buffer in a Float32Array, we use native browser IEEE 754
-        // decoding of the 4 bytes that back each 32 bit float.
-        return new Float32Array(downloadTarget.buffer);
-      }
-      function downloadPackedMatrixFromBuffer(
-        gl,
-        buffer,
-        batch,
-        rows,
-        cols,
-        physicalRows,
-        physicalCols,
-        textureConfig
-      ) {
-        const gl2 = gl;
-        const downloadTarget = new Float32Array(
-          getPackedRGBAArraySizeFromMatrixShape(physicalRows, physicalCols)
-        );
-        gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer);
-        gl2.getBufferSubData(gl2.PIXEL_PACK_BUFFER, 0, downloadTarget);
-        gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null);
-        return downloadTarget;
-      }
-      function downloadMatrixFromPackedOutputTexture(gl, debug, physicalRows, physicalCols) {
-        const packedRGBA = new Float32Array(physicalRows * physicalCols * 4);
-        callAndCheck(gl, debug, () =>
-          gl.readPixels(0, 0, physicalCols, physicalRows, gl.RGBA, gl.FLOAT, packedRGBA)
-        );
-        return packedRGBA;
-      }
-      //# sourceMappingURL=gpgpu_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_context.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class gpgpu_context_GPGPUContext {
-        constructor(gl) {
-          this.outputTexture = null;
-          this.program = null;
-          this.disposed = false;
-          this.vertexAttrsAreBound = false;
-          this.itemsToPoll = [];
-          const glVersion = Object(dist["env"])().getNumber("WEBGL_VERSION");
-          if (gl != null) {
-            this.gl = gl;
-            setWebGLContext(glVersion, gl);
-          } else {
-            this.gl = getWebGLContext(glVersion);
-          }
-          // WebGL 2.0 enables texture floats without an extension.
-          let COLOR_BUFFER_FLOAT = "WEBGL_color_buffer_float";
-          const COLOR_BUFFER_HALF_FLOAT = "EXT_color_buffer_half_float";
-          if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 1) {
-            const TEXTURE_FLOAT = "OES_texture_float";
-            const TEXTURE_HALF_FLOAT = "OES_texture_half_float";
-            this.textureFloatExtension = getExtensionOrThrow(this.gl, this.debug, TEXTURE_FLOAT);
-            if (hasExtension(this.gl, TEXTURE_HALF_FLOAT)) {
-              this.textureHalfFloatExtension = getExtensionOrThrow(
-                this.gl,
-                this.debug,
-                TEXTURE_HALF_FLOAT
-              );
-            } else if (Object(dist["env"])().get("WEBGL_FORCE_F16_TEXTURES")) {
-              throw new Error(
-                "GL context does not support half float textures, yet the " +
-                  "environment flag WEBGL_FORCE_F16_TEXTURES is set to true."
-              );
-            }
-            this.colorBufferFloatExtension = this.gl.getExtension(COLOR_BUFFER_FLOAT);
-            if (hasExtension(this.gl, COLOR_BUFFER_HALF_FLOAT)) {
-              this.colorBufferHalfFloatExtension = getExtensionOrThrow(
-                this.gl,
-                this.debug,
-                COLOR_BUFFER_HALF_FLOAT
-              );
-            } else if (Object(dist["env"])().get("WEBGL_FORCE_F16_TEXTURES")) {
-              throw new Error(
-                "GL context does not support color renderable half floats, yet " +
-                  "the environment flag WEBGL_FORCE_F16_TEXTURES is set to true."
-              );
-            }
-          } else {
-            COLOR_BUFFER_FLOAT = "EXT_color_buffer_float";
-            if (hasExtension(this.gl, COLOR_BUFFER_FLOAT)) {
-              this.colorBufferFloatExtension = this.gl.getExtension(COLOR_BUFFER_FLOAT);
-            } else if (hasExtension(this.gl, COLOR_BUFFER_HALF_FLOAT)) {
-              this.colorBufferHalfFloatExtension = this.gl.getExtension(COLOR_BUFFER_HALF_FLOAT);
-            } else {
-              throw new Error("GL context does not support color renderable floats");
-            }
-          }
-          this.vertexBuffer = createVertexBuffer(this.gl, this.debug);
-          this.indexBuffer = createIndexBuffer(this.gl, this.debug);
-          this.framebuffer = createFramebuffer(this.gl, this.debug);
-          this.textureConfig = getTextureConfig(this.gl, this.textureHalfFloatExtension);
-        }
-        get debug() {
-          return Object(dist["env"])().getBool("DEBUG");
-        }
-        dispose() {
-          if (this.disposed) {
-            return;
-          }
-          if (this.program != null) {
-            console.warn(
-              "Disposing a GPGPUContext that still has a bound WebGLProgram." +
-                " This is probably a resource leak, delete the program with " +
-                "GPGPUContext.deleteProgram before disposing."
-            );
-          }
-          if (this.outputTexture != null) {
-            console.warn(
-              "Disposing a GPGPUContext that still has a bound output matrix " +
-                "texture.  This is probably a resource leak, delete the output " +
-                "matrix texture with GPGPUContext.deleteMatrixTexture before " +
-                "disposing."
-            );
-          }
-          const gl = this.gl;
-          callAndCheck(gl, this.debug, () => gl.finish());
-          callAndCheck(gl, this.debug, () => gl.bindFramebuffer(gl.FRAMEBUFFER, null));
-          callAndCheck(gl, this.debug, () => gl.deleteFramebuffer(this.framebuffer));
-          callAndCheck(gl, this.debug, () => gl.bindBuffer(gl.ARRAY_BUFFER, null));
-          callAndCheck(gl, this.debug, () => gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, null));
-          callAndCheck(gl, this.debug, () => gl.deleteBuffer(this.indexBuffer));
-          this.disposed = true;
-        }
-        createFloat32MatrixTexture(rows, columns) {
-          this.throwIfDisposed();
-          return createFloat32MatrixTexture(this.gl, this.debug, rows, columns, this.textureConfig);
-        }
-        createFloat16MatrixTexture(rows, columns) {
-          this.throwIfDisposed();
-          return createFloat16MatrixTexture(this.gl, this.debug, rows, columns, this.textureConfig);
-        }
-        createUnsignedBytesMatrixTexture(rows, columns) {
-          this.throwIfDisposed();
-          return createUnsignedBytesMatrixTexture(
-            this.gl,
-            this.debug,
-            rows,
-            columns,
-            this.textureConfig
-          );
-        }
-        uploadPixelDataToTexture(texture, pixels) {
-          this.throwIfDisposed();
-          uploadPixelDataToTexture(this.gl, this.debug, texture, pixels);
-        }
-        uploadDenseMatrixToTexture(texture, width, height, data) {
-          this.throwIfDisposed();
-          uploadDenseMatrixToTexture(
-            this.gl,
-            this.debug,
-            texture,
-            width,
-            height,
-            data,
-            this.textureConfig
-          );
-        }
-        createFloat16PackedMatrixTexture(rows, columns) {
-          this.throwIfDisposed();
-          return createFloat16PackedMatrixTexture(
-            this.gl,
-            this.debug,
-            rows,
-            columns,
-            this.textureConfig
-          );
-        }
-        createPackedMatrixTexture(rows, columns) {
-          this.throwIfDisposed();
-          return createPackedMatrixTexture(this.gl, this.debug, rows, columns, this.textureConfig);
-        }
-        deleteMatrixTexture(texture) {
-          this.throwIfDisposed();
-          if (this.outputTexture === texture) {
-            unbindColorTextureFromFramebuffer(this.gl, this.debug, this.framebuffer);
-            this.outputTexture = null;
-          }
-          callAndCheck(this.gl, this.debug, () => this.gl.deleteTexture(texture));
-        }
-        downloadByteEncodedFloatMatrixFromOutputTexture(texture, rows, columns) {
-          return this.downloadMatrixDriver(texture, () =>
-            downloadByteEncodedFloatMatrixFromOutputTexture(
-              this.gl,
-              this.debug,
-              rows,
-              columns,
-              this.textureConfig
-            )
-          );
-        }
-        downloadPackedMatrixFromBuffer(buffer, batch, rows, columns, physicalRows, physicalCols) {
-          return downloadPackedMatrixFromBuffer(
-            this.gl,
-            buffer,
-            batch,
-            rows,
-            columns,
-            physicalRows,
-            physicalCols,
-            this.textureConfig
-          );
-        }
-        downloadFloat32MatrixFromBuffer(buffer, size) {
-          return downloadFloat32MatrixFromBuffer(this.gl, buffer, size);
-        }
-        createBufferFromTexture(texture, rows, columns) {
-          this.bindTextureToFrameBuffer(texture);
-          const result = createBufferFromOutputTexture(
-            this.gl,
-            this.debug,
-            rows,
-            columns,
-            this.textureConfig
-          );
-          this.unbindTextureToFrameBuffer();
-          return result;
-        }
-        createAndWaitForFence() {
-          const fenceContext = this.createFence(this.gl);
-          return this.pollFence(fenceContext);
-        }
-        createFence(gl) {
-          let query;
-          let isFencePassed;
-          if (Object(dist["env"])().getBool("WEBGL_FENCE_API_ENABLED")) {
-            const gl2 = gl;
-            const sync = gl2.fenceSync(gl2.SYNC_GPU_COMMANDS_COMPLETE, 0);
-            gl.flush();
-            isFencePassed = () => {
-              const status = gl2.clientWaitSync(sync, 0, 0);
-              return status === gl2.ALREADY_SIGNALED || status === gl2.CONDITION_SATISFIED;
-            };
-            query = sync;
-          } else if (
-            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") > 0
-          ) {
-            query = this.beginQuery();
-            this.endQuery();
-            isFencePassed = () =>
-              this.isQueryAvailable(
-                query,
-                Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")
-              );
-          } else {
-            // If we have no way to fence, return true immediately. This will fire in
-            // WebGL 1.0 when there is no disjoint query timer. In this case, because
-            // the fence passes immediately, we'll immediately ask for a download of
-            // the texture, which will cause the UI thread to hang.
-            isFencePassed = () => true;
-          }
-          return { query, isFencePassed };
-        }
-        downloadMatrixFromPackedTexture(texture, physicalRows, physicalCols) {
-          return this.downloadMatrixDriver(texture, () =>
-            downloadMatrixFromPackedOutputTexture(this.gl, this.debug, physicalRows, physicalCols)
-          );
-        }
-        createProgram(fragmentShaderSource) {
-          this.throwIfDisposed();
-          const gl = this.gl;
-          const fragmentShader = createFragmentShader(gl, this.debug, fragmentShaderSource);
-          const vertexShader = gpgpu_util_createVertexShader(gl, this.debug);
-          const program = createProgram(gl, this.debug);
-          callAndCheck(gl, this.debug, () => gl.attachShader(program, vertexShader));
-          callAndCheck(gl, this.debug, () => gl.attachShader(program, fragmentShader));
-          linkProgram(gl, this.debug, program);
-          if (this.debug) {
-            validateProgram(gl, this.debug, program);
-          }
-          if (!this.vertexAttrsAreBound) {
-            this.setProgram(program);
-            this.vertexAttrsAreBound = bindVertexProgramAttributeStreams(
-              gl,
-              this.debug,
-              this.program,
-              this.vertexBuffer
-            );
-          }
-          return program;
-        }
-        deleteProgram(program) {
-          this.throwIfDisposed();
-          if (program === this.program) {
-            this.program = null;
-          }
-          if (program != null) {
-            callAndCheck(this.gl, this.debug, () => this.gl.deleteProgram(program));
-          }
-        }
-        setProgram(program) {
-          this.throwIfDisposed();
-          this.program = program;
-          if (this.program != null && this.debug) {
-            validateProgram(this.gl, this.debug, this.program);
-          }
-          callAndCheck(this.gl, this.debug, () => this.gl.useProgram(program));
-        }
-        getUniformLocation(program, uniformName, shouldThrow = true) {
-          this.throwIfDisposed();
-          if (shouldThrow) {
-            return getProgramUniformLocationOrThrow(this.gl, this.debug, program, uniformName);
-          } else {
-            return getProgramUniformLocation(this.gl, program, uniformName);
-          }
-        }
-        getAttributeLocation(program, attribute) {
-          this.throwIfDisposed();
-          return callAndCheck(this.gl, this.debug, () =>
-            this.gl.getAttribLocation(program, attribute)
-          );
-        }
-        getUniformLocationNoThrow(program, uniformName) {
-          this.throwIfDisposed();
-          return this.gl.getUniformLocation(program, uniformName);
-        }
-        setInputMatrixTexture(inputMatrixTexture, uniformLocation, textureUnit) {
-          this.throwIfDisposed();
-          this.throwIfNoProgram();
-          bindTextureToProgramUniformSampler(
-            this.gl,
-            this.debug,
-            this.program,
-            inputMatrixTexture,
-            uniformLocation,
-            textureUnit
-          );
-        }
-        setOutputMatrixTexture(outputMatrixTexture, rows, columns) {
-          this.setOutputMatrixTextureDriver(outputMatrixTexture, columns, rows);
-        }
-        setOutputPackedMatrixTexture(outputPackedMatrixTexture, rows, columns) {
-          this.throwIfDisposed();
-          const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);
-          this.setOutputMatrixTextureDriver(outputPackedMatrixTexture, width, height);
-        }
-        setOutputMatrixWriteRegion(startRow, numRows, startColumn, numColumns) {
-          this.setOutputMatrixWriteRegionDriver(startColumn, startRow, numColumns, numRows);
-        }
-        setOutputPackedMatrixWriteRegion(startRow, numRows, startColumn, numColumns) {
-          throw new Error("setOutputPackedMatrixWriteRegion not implemented.");
-        }
-        debugValidate() {
-          if (this.program != null) {
-            validateProgram(this.gl, this.debug, this.program);
-          }
-          validateFramebuffer(this.gl);
-        }
-        executeProgram() {
-          this.throwIfDisposed();
-          this.throwIfNoProgram();
-          const gl = this.gl;
-          if (this.debug) {
-            this.debugValidate();
-          }
-          callAndCheck(gl, this.debug, () =>
-            gl.drawElements(gl.TRIANGLES, 6, gl.UNSIGNED_SHORT, 0)
-          );
-        }
-        blockUntilAllProgramsCompleted() {
-          this.throwIfDisposed();
-          callAndCheck(this.gl, this.debug, () => this.gl.finish());
-        }
-        getQueryTimerExtension() {
-          if (this.disjointQueryTimerExtension == null) {
-            this.disjointQueryTimerExtension = getExtensionOrThrow(
-              this.gl,
-              this.debug,
-              Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2
-                ? "EXT_disjoint_timer_query_webgl2"
-                : "EXT_disjoint_timer_query"
-            );
-          }
-          return this.disjointQueryTimerExtension;
-        }
-        getQueryTimerExtensionWebGL2() {
-          return this.getQueryTimerExtension();
-        }
-        getQueryTimerExtensionWebGL1() {
-          return this.getQueryTimerExtension();
-        }
-        beginQuery() {
-          if (
-            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2
-          ) {
-            const gl2 = this.gl;
-            const ext = this.getQueryTimerExtensionWebGL2();
-            const query = gl2.createQuery();
-            gl2.beginQuery(ext.TIME_ELAPSED_EXT, query);
-            return query;
-          }
-          const ext = this.getQueryTimerExtensionWebGL1();
-          const query = ext.createQueryEXT();
-          ext.beginQueryEXT(ext.TIME_ELAPSED_EXT, query);
-          return query;
-        }
-        endQuery() {
-          if (
-            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2
-          ) {
-            const gl2 = this.gl;
-            const ext = this.getQueryTimerExtensionWebGL2();
-            gl2.endQuery(ext.TIME_ELAPSED_EXT);
-            return;
-          }
-          const ext = this.getQueryTimerExtensionWebGL1();
-          ext.endQueryEXT(ext.TIME_ELAPSED_EXT);
-        }
-        async waitForQueryAndGetTime(query) {
-          await dist["util"].repeatedTry(
-            () =>
-              this.disposed || // while testing contexts are created / disposed
-              // in rapid succession, so without this check we
-              // may poll for the query timer indefinitely
-              this.isQueryAvailable(
-                query,
-                Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")
-              )
-          );
-          return this.getQueryTime(
-            query,
-            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")
-          );
-        }
-        getQueryTime(query, queryTimerVersion) {
-          if (queryTimerVersion === 0) {
-            return null;
-          }
-          if (queryTimerVersion === 2) {
-            const gl2 = this.gl;
-            const timeElapsedNanos = gl2.getQueryParameter(query, gl2.QUERY_RESULT);
-            // Return milliseconds.
-            return timeElapsedNanos / 1000000;
-          } else {
-            const ext = this.getQueryTimerExtensionWebGL1();
-            const timeElapsedNanos = ext.getQueryObjectEXT(query, ext.QUERY_RESULT_EXT);
-            // Return milliseconds.
-            return timeElapsedNanos / 1000000;
-          }
-        }
-        isQueryAvailable(query, queryTimerVersion) {
-          if (queryTimerVersion === 0) {
-            return true;
-          }
-          if (queryTimerVersion === 2) {
-            const gl2 = this.gl;
-            const ext = this.getQueryTimerExtensionWebGL2();
-            const available = gl2.getQueryParameter(query, gl2.QUERY_RESULT_AVAILABLE);
-            if (this.disjoint == null) {
-              this.disjoint = this.gl.getParameter(ext.GPU_DISJOINT_EXT);
-            }
-            return available && !this.disjoint;
-          } else {
-            const ext = this.getQueryTimerExtensionWebGL1();
-            const available = ext.getQueryObjectEXT(query, ext.QUERY_RESULT_AVAILABLE_EXT);
-            if (this.disjoint == null) {
-              this.disjoint = this.gl.getParameter(ext.GPU_DISJOINT_EXT);
-            }
-            return available && !this.disjoint;
-          }
-        }
-        pollFence(fenceContext) {
-          return new Promise((resolve) => {
-            this.addItemToPoll(
-              () => fenceContext.isFencePassed(),
-              () => resolve()
-            );
-          });
-        }
-        pollItems() {
-          // Find the last query that has finished.
-          const index = linearSearchLastTrue(this.itemsToPoll.map((x) => x.isDoneFn));
-          for (let i = 0; i <= index; ++i) {
-            const { resolveFn } = this.itemsToPoll[i];
-            resolveFn();
-          }
-          this.itemsToPoll = this.itemsToPoll.slice(index + 1);
-        }
-        addItemToPoll(isDoneFn, resolveFn) {
-          this.itemsToPoll.push({ isDoneFn, resolveFn });
-          if (this.itemsToPoll.length > 1) {
-            // We already have a running loop that polls.
-            return;
-          }
-          // Start a new loop that polls.
-          dist["util"].repeatedTry(() => {
-            this.pollItems();
-            // End the loop if no more items to poll.
-            return this.itemsToPoll.length === 0;
-          });
-        }
-        bindTextureToFrameBuffer(texture) {
-          this.throwIfDisposed();
-          bindColorTextureToFramebuffer(this.gl, this.debug, texture, this.framebuffer);
-          if (this.debug) {
-            validateFramebuffer(this.gl);
-          }
-        }
-        unbindTextureToFrameBuffer() {
-          if (this.outputTexture != null) {
-            bindColorTextureToFramebuffer(
-              this.gl,
-              this.debug,
-              this.outputTexture,
-              this.framebuffer
-            );
-            if (this.debug) {
-              validateFramebuffer(this.gl);
-            }
-          } else {
-            unbindColorTextureFromFramebuffer(this.gl, this.debug, this.framebuffer);
-          }
-        }
-        downloadMatrixDriver(texture, downloadAndDecode) {
-          this.bindTextureToFrameBuffer(texture);
-          const result = downloadAndDecode();
-          this.unbindTextureToFrameBuffer();
-          return result;
-        }
-        setOutputMatrixTextureDriver(outputMatrixTextureMaybePacked, width, height) {
-          this.throwIfDisposed();
-          const gl = this.gl;
-          bindColorTextureToFramebuffer(
-            gl,
-            this.debug,
-            outputMatrixTextureMaybePacked,
-            this.framebuffer
-          );
-          if (this.debug) {
-            validateFramebuffer(gl);
-          }
-          this.outputTexture = outputMatrixTextureMaybePacked;
-          callAndCheck(gl, this.debug, () => gl.viewport(0, 0, width, height));
-          callAndCheck(gl, this.debug, () => gl.scissor(0, 0, width, height));
-        }
-        setOutputMatrixWriteRegionDriver(x, y, width, height) {
-          this.throwIfDisposed();
-          callAndCheck(this.gl, this.debug, () => this.gl.scissor(x, y, width, height));
-        }
-        throwIfDisposed() {
-          if (this.disposed) {
-            throw new Error("Attempted to use disposed GPGPUContext.");
-          }
-        }
-        throwIfNoProgram() {
-          if (this.program == null) {
-            throw new Error("No GPU program is currently set.");
-          }
-        }
-      }
-      /**
-       * Finds the index of the last true element using linear search.
-       * Note: We can't do binary search because Chrome expects us to explicitly
-       * test all fences before download:
-       * https://github.com/tensorflow/tfjs/issues/1145
-       */
-      function linearSearchLastTrue(arr) {
-        let i = 0;
-        for (; i < arr.length; ++i) {
-          const isDone = arr[i]();
-          if (!isDone) {
-            break;
-          }
-        }
-        return i - 1;
-      }
-      //# sourceMappingURL=gpgpu_context.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_math.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function compileProgram(gpgpu, program, inputs, output) {
-        const userCode = program.userCode;
-        const inputInfos = inputs.map((input, i) => {
-          const shapeInfo = {
-            logicalShape: input.shape,
-            texShape: input.isUniform ? null : input.texData.texShape,
-            isUniform: input.isUniform,
-            isPacked: input.isUniform ? false : input.texData.isPacked,
-            flatOffset: null,
-          };
-          if (
-            input.texData != null &&
-            input.texData.slice != null &&
-            input.texData.slice.flatOffset > 0
-          ) {
-            shapeInfo.flatOffset = input.texData.slice.flatOffset;
-          }
-          return { name: program.variableNames[i], shapeInfo };
-        });
-        const inShapeInfos = inputInfos.map((x) => x.shapeInfo);
-        const outShapeInfo = {
-          logicalShape: output.shape,
-          texShape: output.texData.texShape,
-          isUniform: false,
-          isPacked: output.texData.isPacked,
-          flatOffset: null,
-        };
-        const source = makeShader(inputInfos, outShapeInfo, userCode, program.packedInputs);
-        const webGLProgram = gpgpu.createProgram(source);
-        // Add special uniforms (NAN, INFINITY)
-        let infLoc = null;
-        const nanLoc = gpgpu.getUniformLocation(webGLProgram, "NAN", false);
-        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 1) {
-          infLoc = gpgpu.getUniformLocation(webGLProgram, "INFINITY", false);
-        }
-        // Add user-defined uniforms
-        const uniformLocations = {};
-        for (let i = 0; i < program.variableNames.length; i++) {
-          const varName = program.variableNames[i];
-          const shouldThrow = false;
-          uniformLocations[varName] = gpgpu.getUniformLocation(webGLProgram, varName, shouldThrow);
-          uniformLocations[`offset${varName}`] = gpgpu.getUniformLocation(
-            webGLProgram,
-            `offset${varName}`,
-            shouldThrow
-          );
-        }
-        return {
-          program,
-          source,
-          webGLProgram,
-          uniformLocations,
-          inShapeInfos,
-          outShapeInfo,
-          infLoc,
-          nanLoc,
-        };
-      }
-      function validateBinaryAndProgram(shapeInfos, inputs) {
-        if (shapeInfos.length !== inputs.length) {
-          throw Error(
-            `Binary was compiled with ${shapeInfos.length} inputs, but ` +
-              `was executed with ${inputs.length} inputs`
-          );
-        }
-        shapeInfos.forEach((s, i) => {
-          const shapeA = s.logicalShape;
-          const input = inputs[i];
-          const shapeB = input.shape;
-          if (!dist["util"].arraysEqual(shapeA, shapeB)) {
-            throw Error(
-              `Binary was compiled with different shapes than ` +
-                `the current args. Shapes ${shapeA} and ${shapeB} must match`
-            );
-          }
-          // The input is uploaded as uniform.
-          if (s.isUniform && input.isUniform) {
-            return;
-          }
-          const texShapeA = s.texShape;
-          const texShapeB = input.isUniform ? null : input.texData.texShape;
-          if (!dist["util"].arraysEqual(texShapeA, texShapeB)) {
-            throw Error(
-              `Binary was compiled with different texture shapes than the` +
-                ` current args. Shape ${texShapeA} and ${texShapeB} must match`
-            );
-          }
-        });
-      }
-      function runProgram(gpgpu, binary, inputs, output, customSetup) {
-        validateBinaryAndProgram(binary.inShapeInfos, inputs);
-        validateBinaryAndProgram([binary.outShapeInfo], [output]);
-        const outTex = output.texData.texture;
-        const outTexShape = output.texData.texShape;
-        if (output.texData.isPacked) {
-          gpgpu.setOutputPackedMatrixTexture(outTex, outTexShape[0], outTexShape[1]);
-        } else {
-          gpgpu.setOutputMatrixTexture(outTex, outTexShape[0], outTexShape[1]);
-        }
-        gpgpu.setProgram(binary.webGLProgram);
-        // Set special uniforms (NAN, INFINITY)
-        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 1) {
-          if (binary.infLoc !== null) {
-            gpgpu.gl.uniform1f(binary.infLoc, Infinity);
-          }
-        }
-        if (binary.nanLoc !== null) {
-          gpgpu.gl.uniform1f(binary.nanLoc, NaN);
-        }
-        // Set user-defined inputs
-        inputs.forEach((input, i) => {
-          const varName = binary.program.variableNames[i];
-          const varLoc = binary.uniformLocations[varName];
-          const varOffsetLoc = binary.uniformLocations[`offset${varName}`];
-          if (varLoc == null) {
-            // The compiler inferred that this variable is not used in this shader.
-            return;
-          }
-          if (input.isUniform) {
-            // Upload the values of the tensor as uniform.
-            if (dist["util"].sizeFromShape(input.shape) < 2) {
-              gpgpu.gl.uniform1f(varLoc, input.uniformValues[0]);
-            } else {
-              let vals = input.uniformValues;
-              if (!(vals instanceof Float32Array)) {
-                vals = new Float32Array(vals);
-              }
-              gpgpu.gl.uniform1fv(varLoc, vals);
-            }
-            return;
-          }
-          // If the input was sliced, upload the flat offset index.
-          if (input.texData.slice != null && varOffsetLoc != null) {
-            gpgpu.gl.uniform1i(varOffsetLoc, input.texData.slice.flatOffset);
-          }
-          gpgpu.setInputMatrixTexture(input.texData.texture, varLoc, i);
-        });
-        if (customSetup != null) {
-          customSetup(gpgpu, binary.webGLProgram);
-        }
-        gpgpu.executeProgram();
-      }
-      function makeShaderKey(program, inputs, output) {
-        let keyInputs = "";
-        inputs.concat(output).forEach((x) => {
-          const hasOffset =
-            x.texData != null && x.texData.slice != null && x.texData.slice.flatOffset > 0;
-          const texShape = x.isUniform ? "uniform" : x.texData.texShape;
-          keyInputs += `${x.shape}_${texShape}_${hasOffset}`;
-        });
-        const keyUserCode = program.userCode;
-        let key = program.constructor.name;
-        // Fast string concat. See https://jsperf.com/string-concatenation/14.
-        key += "_" + keyInputs + "_" + keyUserCode;
-        return key;
-      }
-      //# sourceMappingURL=gpgpu_math.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/im2col_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class im2col_packed_gpu_Im2ColPackedProgram {
-        constructor(outputShape, inputShape, convInfo) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = outputShape;
-          const {
-            filterWidth,
-            inChannels,
-            strideWidth,
-            strideHeight,
-            padInfo,
-            outWidth,
-            dilationWidth,
-            dilationHeight,
-            dataFormat,
-          } = convInfo;
-          const { left, top } = padInfo;
-          const itemsPerBlockRow = inChannels * filterWidth;
-          const glsl = getGlslDifferences();
-          const isChannelsLast = dataFormat === "channelsLast";
-          const rowDim = isChannelsLast ? 0 : 1;
-          const colDim = isChannelsLast ? 1 : 2;
-          let unrolled = ``;
-          for (let row = 0; row <= 1; row++) {
-            for (let col = 0; col <= 1; col++) {
-              unrolled += `
-          blockIndex = rc.y + ${col};
-          pos = rc.x + ${row};
-
-          if(blockIndex < ${outputShape[1]} && pos < ${outputShape[0]}) {
-            offsetY = int(blockIndex / (${outWidth})) * ${strideHeight} - ${top};
-            d0 = offsetY + ${dilationHeight} * (pos / ${itemsPerBlockRow});
-
-            if(d0 < ${inputShape[rowDim]} && d0 >= 0) {
-
-              offsetX = int(mod(float(blockIndex), ${outWidth}.) * ${strideWidth}. - ${left}.);
-              d1 = offsetX + ${dilationWidth} * (int(mod(float(pos), ${itemsPerBlockRow}.) / ${inChannels}.));
-
-              if(d1 < ${inputShape[colDim]} && d1 >= 0) {
-
-                ch = int(mod(float(pos), ${inChannels}.));
-
-                if (${isChannelsLast}) {
-                  innerDims = vec2(d1, ch);
-                  result[${row * 2 + col}] = getChannel(
-                    getA(d0, int(innerDims.x),
-                    int(innerDims.y)), innerDims);
-                } else {
-                  innerDims = vec2(d0, d1);
-                  result[${row * 2 + col}] = getChannel(
-                    getA(ch, int(innerDims.x),
-                    int(innerDims.y)), innerDims);
-                }
-              }
-            }
-          }
-        `;
-            }
-          }
-          this.userCode = `
-      void main() {
-        ivec2 rc = getOutputCoords();
-
-        vec4 result = vec4(0);
-
-        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
-        vec2 innerDims;
-
-        ${unrolled}
-
-        ${glsl.output} = result;
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=im2col_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class LRNProgram {
-        constructor(xShape, radius, bias, alpha, beta) {
-          this.variableNames = ["x"];
-          this.outputShape = [];
-          const rad = radius;
-          const maxD = xShape[3] - 1;
-          this.outputShape = xShape;
-          // optimize pow(bias + alpha * sum, -beta)
-          // src: https://github.com/tensorflow/tensorflow/..
-          // blob/26033a1644a9c4a5fbe3170ab2e864b6a4ccd4ca/..
-          // tensorflow/core/kernels/mkl_lrn_op.cc#L320
-          let powOperator;
-          const basis = `float(${bias}) + float(${alpha}) * sum`;
-          if (beta === 0.5) {
-            powOperator = `inversesqrt(${basis})`;
-          } else if (beta === 1.0) {
-            powOperator = `1.0/(${basis})`;
-          } else {
-            powOperator = `exp(log(${basis}) * float(-${beta}));`;
-          }
-          this.userCode = `
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int r = coords[1];
-        int c = coords[2];
-        int d = coords[3];
-        float x = getX(b, r, c, d);
-        float sum = 0.0;
-        for (int j = -${rad}; j <= ${rad}; j++) {
-          int idx = d + j;
-          if (idx >= 0 && idx <=  ${maxD}) {
-            float z = getX(b, r, c, idx);
-            sum += z * z;
-          }
-        }
-        float val = x * ${powOperator};
-        setOutput(val);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=lrn_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_grad_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class LRNGradProgram {
-        constructor(inputShape, depthRadius, bias, alpha, beta) {
-          this.variableNames = ["inputImage", "outputImage", "dy"];
-          this.outputShape = [];
-          this.outputShape = inputShape;
-          this.depth = inputShape[3];
-          this.depthRadius = depthRadius;
-          this.bias = bias;
-          this.alpha = alpha;
-          this.beta = beta;
-          this.userCode = `
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int r = coords[1];
-        int c = coords[2];
-
-        float result = 0.0;
-        for (int d = 0; d < ${this.depth}; ++d) {
-          int depthBegin = int(max(0.0, float(d - ${depthRadius})));
-          int depthEnd = int(min(float(${this.depth}),
-              float(d + ${depthRadius} + 1)));
-
-          const int MIN_DEPTH_BEGIN = 0;
-          const int MAX_DEPTH_END = ${this.depth};
-
-          float norm = 0.0;
-          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
-            if (k < depthBegin){
-              continue;
-            }
-            else if (k >= depthBegin && k < depthEnd) {
-              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
-            }
-            else {
-              break;
-            }
-          }
-
-          norm = float(${alpha}) * norm + float(${bias});
-
-          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
-            if (k < depthBegin){
-              continue;
-            }
-            else if (k >= depthBegin && k < depthEnd){
-              float dyi = -2.0 * float(${alpha})
-                * float(${beta})
-                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
-                / norm;
-              if (k == d) {
-                dyi += pow(norm, -1.0 * ${beta});
-              }
-              if (k == coords[3]) {
-                dyi *= getDy(b, r, c, d);
-                result += dyi;
-              }
-            }
-            else {
-              break;
-            }
-          }
-      }
-      setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=lrn_grad_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class LRNPackedProgram {
-        constructor(xShape, radius, bias, alpha, beta) {
-          this.variableNames = ["x"];
-          this.outputShape = [];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          const rad = radius;
-          const maxD = xShape[3] - 1;
-          this.outputShape = xShape;
-          // optimize pow(bias + alpha * sum, -beta)
-          // src: https://github.com/tensorflow/tensorflow/..
-          // blob/26033a1644a9c4a5fbe3170ab2e864b6a4ccd4ca/..
-          // tensorflow/core/kernels/mkl_lrn_op.cc#L320
-          let powOperator;
-          const basis = `float(${bias}) + float(${alpha}) * sum`;
-          if (beta === 0.5) {
-            powOperator = `inversesqrt(${basis})`;
-          } else if (beta === 1.0) {
-            powOperator = `1.0/(${basis})`;
-          } else {
-            powOperator = `exp(log(${basis}) * float(-${beta}));`;
-          }
-          this.userCode = `
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords.x;
-        int r = coords.y;
-        int c = coords.z;
-        int d = coords.w;
-
-        bool hasNextCol = d < ${this.outputShape[3]};
-        bool hasNextRow = c < ${this.outputShape[2]};
-
-        vec4 sum = vec4(0.);
-        vec4 xFragAtOutputCoords = getX(b, r, c, d);
-
-        vec4 xAtOutputCoords = vec4(
-          getChannel(xFragAtOutputCoords, vec2(c, d)),
-          hasNextCol ?
-            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
-          hasNextRow ?
-            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
-          (hasNextRow && hasNextCol) ?
-            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
-        );
-
-        int firstChannel = d - ${rad};
-        vec2 cache = vec2(0.);
-        if(firstChannel >= 0){
-          vec4 firstChannelFrag = getX(b, r, c, firstChannel);
-          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
-            if(hasNextRow){
-              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
-            }
-        }
-
-        ivec2 depth = ivec2(d, d + 1);
-        for (int j = - ${rad}; j <= ${rad}; j++) {
-          ivec2 idx = depth + j;
-          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
-          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${maxD}));
-
-          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
-          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;
-
-          if(depthInRange || depthPlusOneInRange){
-            vec4 z = vec4(0.);
-            vec4 xFragAtCurrentDepth;
-            z.xz = cache.xy;
-            if(depthPlusOneInRange && hasNextCol){
-              xFragAtCurrentDepth = idx.y != d ?
-                getX(b, r, c, idx.y) : xFragAtOutputCoords;
-              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
-              if(hasNextRow){
-                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
-              }
-            }
-            cache.xy = z.yw;
-            sum += z * z;
-          }
-        }
-        vec4 result = xAtOutputCoords * ${powOperator};
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=lrn_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/max_pool_backprop_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class MaxPool2DBackpropProgram {
-        constructor(convInfo) {
-          this.variableNames = ["dy", "maxPos"];
-          this.outputShape = convInfo.inShape;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
-          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
-          const lastIndex = effectiveFilterHeight * effectiveFilterWidth - 1;
-          this.userCode = `
-      const ivec2 pads = ivec2(${padTop}, ${padLeft});
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int d = coords[3];
-
-        ivec2 dyRCCorner = coords.yz - pads;
-        int dyRCorner = dyRCCorner.x;
-        int dyCCorner = dyRCCorner.y;
-
-        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
-        // ? = to be determined. : = across all values in that axis.
-        float dotProd = 0.0;
-        for (int wR = 0; wR < ${effectiveFilterHeight};
-          wR += ${dilationHeight}) {
-          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
-
-          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {
-            continue;
-          }
-          int idyR = int(dyR);
-
-          for (int wC = 0; wC < ${effectiveFilterWidth}; wC++) {
-            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
-
-            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
-                fract(dyC) > 0.0) {
-              continue;
-            }
-            int idyC = int(dyC);
-
-            float dyValue = getDy(b, idyR, idyC, d);
-            int maxPosValue = ${lastIndex} - int(getMaxPos(b, idyR, idyC, d));
-
-            // Get the current value, check it against the value from the
-            // position matrix.
-            int curPosValue = wR * ${effectiveFilterWidth} + wC;
-            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
-
-            dotProd += dyValue * mask;
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      class MaxPool3DBackpropProgram {
-        constructor(convInfo) {
-          this.variableNames = ["dy", "maxPos"];
-          this.outputShape = convInfo.inShape;
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
-          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
-          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
-          const lastIndex = effectiveFilterDepth * effectiveFilterHeight * effectiveFilterWidth - 1;
-          this.userCode = `
-      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
-
-      void main() {
-        ivec5 coords = getOutputCoords();
-        int batch = coords.x;
-        int ch = coords.u;
-
-        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
-        int dyDCorner = dyCorner.x;
-        int dyRCorner = dyCorner.y;
-        int dyCCorner = dyCorner.z;
-
-        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
-        // dx(xD, xR, xC, ch).
-        // ? = to be determined. : = across all values in that axis.
-        float dotProd = 0.0;
-
-        for (int wD = 0; wD < ${effectiveFilterDepth};
-           wD += ${dilationDepth}) {
-          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;
-
-          if (dyD < 0.0 || dyD >= ${convInfo.outDepth}.0 || fract(dyD) > 0.0) {
-            continue;
-          }
-          int idyD = int(dyD);
-
-          for (int wR = 0; wR < ${effectiveFilterHeight};
-              wR += ${dilationHeight}) {
-            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
-
-            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||
-                fract(dyR) > 0.0) {
-              continue;
-            }
-            int idyR = int(dyR);
-
-            for (int wC = 0; wC < ${effectiveFilterWidth};
-                wC += ${dilationWidth}) {
-              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
-
-              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
-                  fract(dyC) > 0.0) {
-                continue;
-              }
-              int idyC = int(dyC);
-
-              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
-              int maxPosValue = ${lastIndex} -
-                  int(getMaxPos(batch, idyD, idyR, idyC, ch));
-
-              // Get the current value, check it against the value from the
-              // position matrix.
-              int curPosValue =
-                  wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +
-                  wR * ${effectiveFilterWidth} + wC;
-              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
-
-              dotProd += dyValue * mask;
-            }
-          }
-        }
-        setOutput(dotProd);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=max_pool_backprop_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/mulmat_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class MatMulPackedProgram {
-        constructor(
-          aShape,
-          outputShape,
-          transposeA = false,
-          transposeB = false,
-          addBias = false,
-          activation = null,
-          hasPreluActivation = false
-        ) {
-          this.variableNames = ["matrixA", "matrixB"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = outputShape;
-          const sharedDim = transposeA ? aShape[1] : aShape[2];
-          const sharedDimensionPacked = Math.ceil(sharedDim / 2);
-          const aSample = transposeA ? "i * 2, rc.y" : "rc.y, i * 2";
-          const bSample = transposeB ? "rc.z, i * 2" : "i * 2, rc.z";
-          const aSwizzle = transposeA ? ["a.xxyy", "a.zzww"] : ["a.xxzz", "a.yyww"];
-          const bSwizzle = transposeB ? ["b.xzxz", "b.ywyw"] : ["b.xyxy", "b.zwzw"];
-          let activationSnippet = "",
-            applyActivationSnippet = "";
-          if (activation) {
-            if (hasPreluActivation) {
-              activationSnippet = `vec4 activation(vec4 a) {
-          vec4 b = getPreluActivationWeightsAtOutCoords();
-          ${activation}
-        }`;
-            } else {
-              activationSnippet = `vec4 activation(vec4 x) {
-          ${activation}
-        }`;
-            }
-            applyActivationSnippet = `result = activation(result);`;
-          }
-          const addBiasSnippet = addBias ? "result += getBiasAtOutCoords();" : "";
-          if (addBias) {
-            this.variableNames.push("bias");
-          }
-          if (hasPreluActivation) {
-            this.variableNames.push("preluActivationWeights");
-          }
-          this.userCode = `
-      ${activationSnippet}
-
-      const float sharedDimension = ${sharedDimensionPacked}.0;
-
-      vec4 dot2x2ARowBCol(ivec3 rc) {
-        vec4 result = vec4(0);
-        for (int i = 0; i < ${sharedDimensionPacked}; i++) {
-          vec4 a = getMatrixA(rc.x, ${aSample});
-          vec4 b = getMatrixB(rc.x, ${bSample});
-
-          // These swizzled products need to be separately added.
-          // See: https://github.com/tensorflow/tfjs/issues/1735
-          result += (${aSwizzle[0]} * ${bSwizzle[0]});
-          result += (${aSwizzle[1]} * ${bSwizzle[1]});
-        }
-        return result;
-      }
-
-      void main() {
-        ivec3 rc = getOutputCoords();
-        vec4 result = dot2x2ARowBCol(rc);
-
-        ${addBiasSnippet}
-
-        ${applyActivationSnippet}
-
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=mulmat_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/multinomial_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class MultinomialProgram {
-        constructor(batchSize, numOutcomes, numSamples) {
-          this.variableNames = ["probs"];
-          this.outputShape = [batchSize, numSamples];
-          this.userCode = `
-      uniform float seed;
-
-      void main() {
-        ivec2 coords = getOutputCoords();
-        int batch = coords[0];
-
-        float r = random(seed);
-        float cdf = 0.0;
-
-        for (int i = 0; i < ${numOutcomes - 1}; i++) {
-          cdf += getProbs(batch, i);
-
-          if (r < cdf) {
-            setOutput(float(i));
-            return;
-          }
-        }
-
-        // If no other event happened, last event happened.
-        setOutput(float(${numOutcomes - 1}));
-      }
-    `;
-        }
-        getCustomSetupFunc(seed) {
-          return (gpgpu, webGLProgram) => {
-            if (this.seedLoc == null) {
-              this.seedLoc = gpgpu.getUniformLocation(webGLProgram, "seed");
-            }
-            gpgpu.gl.uniform1f(this.seedLoc, seed);
-          };
-        }
-      }
-      //# sourceMappingURL=multinomial_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/onehot_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class OneHotProgram {
-        constructor(numIndices, depth, onValue, offValue) {
-          this.variableNames = ["indices"];
-          this.outputShape = [numIndices, depth];
-          this.userCode = `
-      void main() {
-        ivec2 coords = getOutputCoords();
-        int index = round(getIndices(coords.x));
-        setOutput(mix(float(${offValue}), float(${onValue}),
-                      float(index == coords.y)));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=onehot_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/pack_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class pack_gpu_PackProgram {
-        constructor(outputShape) {
-          this.variableNames = ["A"];
-          this.packedInputs = false;
-          this.packedOutput = true;
-          // Only input / output 3D tensors.
-          this.outputShape = outputShape;
-          const rank = outputShape.length;
-          if (rank === 0) {
-            this.userCode = `
-        void main() {
-          setOutput(vec4(getA(), 0., 0., 0.));
-        }
-      `;
-          } else {
-            const channels = getChannels("rc", rank);
-            const dtype = getCoordsDataType(rank);
-            const outOfBoundsCondition = getOutOfBoundsCondition(rank, outputShape, channels);
-            const setup = getSetup(
-              rank,
-              outputShape[outputShape.length - 1],
-              outputShape[outputShape.length - 2],
-              channels
-            );
-            const output = getOutput(outputShape, channels);
-            this.userCode = `
-        void main() {
-          ${dtype} rc = getOutputCoords();
-
-          if(${outOfBoundsCondition}) {
-            setOutput(vec4(0));
-          } else {
-            ${setup}
-
-            setOutput(vec4(${output}));
-          }
-        }
-      `;
-          }
-        }
-      }
-      function getSourceCoordsArr(rank, dims) {
-        const coords = [];
-        for (let row = 0; row <= 1; row++) {
-          for (let col = 0; col <= 1; col++) {
-            let coord = `${row === 0 ? "r" : "rp1"}, ${col === 0 ? "c" : "cp1"}`;
-            for (let d = 2; d < rank; d++) {
-              coord = `${dims[dims.length - 1 - d]},` + coord;
-            }
-            coords.push(coord);
-          }
-        }
-        return coords;
-      }
-      function getOutOfBoundsCondition(rank, shape, dims) {
-        if (rank === 1) {
-          return `rc > ${shape[0]}`;
-        }
-        let cond = "";
-        for (let i = rank - 2; i < rank; i++) {
-          cond += `${dims[i]} >= ${shape[i]}`;
-          if (i < rank - 1) {
-            cond += "||";
-          }
-        }
-        return cond;
-      }
-      function getSetup(rank, cols, rows, dims) {
-        if (rank === 1) {
-          return "";
-        }
-        const innerDims = dims.slice(-2);
-        return `
-    int r = ${innerDims[0]};
-    int c = ${innerDims[1]};
-    int rp1 = r + 1;
-    int cp1 = c + 1;
-
-    bool cEdge = cp1 >= ${cols};
-    bool rEdge = rp1 >= ${rows};
-  `;
-      }
-      function getOutput(shape, dims) {
-        const rank = shape.length;
-        const sourceCoords = getSourceCoordsArr(rank, dims);
-        if (rank === 1) {
-          return `getA(rc),
-            rc + 1 >= ${shape[0]} ? 0. : getA(rc + 1),
-            0, 0`;
-        }
-        return `getA(${sourceCoords[0]}),
-          cEdge ? 0. : getA(${sourceCoords[1]}),
-          rEdge ? 0. : getA(${sourceCoords[2]}),
-          rEdge || cEdge ? 0. : getA(${sourceCoords[3]})`;
-      }
-      //# sourceMappingURL=pack_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/pad_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class pad_gpu_PadProgram {
-        constructor(xShape, paddings, constantValue) {
-          this.variableNames = ["x"];
-          this.outputShape = paddings.map(
-            (p, i) => p[0] /* beforePad */ + xShape[i] + p[1] /* afterPad */
-          );
-          const rank = xShape.length;
-          const type = getCoordsDataType(rank);
-          const start = paddings.map((p) => p[0]).join(",");
-          const end = paddings.map((p, i) => p[0] + xShape[i]).join(",");
-          const unpackedCoords = ["coords[0]", "coords[1]", "coords[2]", "coords[3]"].slice(
-            0,
-            rank
-          );
-          if (rank === 1) {
-            this.userCode = `
-        int start = ${start};
-        int end = ${end};
-
-        void main() {
-          int outC = getOutputCoords();
-          if (outC < start || outC >= end) {
-            setOutput(float(${constantValue}));
-          } else {
-            setOutput(getX(outC - start));
-          }
-        }
-      `;
-            return;
-          }
-          this.userCode = `
-      ${type} start = ${type}(${start});
-      ${type} end = ${type}(${end});
-
-      void main() {
-        ${type} outC = getOutputCoords();
-        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
-          setOutput(float(${constantValue}));
-        } else {
-          ${type} coords = outC - start;
-          setOutput(getX(${unpackedCoords}));
-        }
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=pad_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/pad_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class pad_packed_gpu_PadPackedProgram {
-        constructor(xShape, paddings, constantValue) {
-          this.variableNames = ["x"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = paddings.map(
-            (p, i) => p[0] /* beforePad */ + xShape[i] + p[1] /* afterPad */
-          );
-          const rank = xShape.length;
-          const dtype = getCoordsDataType(rank);
-          const start = paddings.map((p) => p[0]).join(",");
-          const end = paddings.map((p, i) => p[0] + xShape[i]).join(",");
-          const coords = getChannels("rc", rank);
-          const source = getChannels("source", rank);
-          const cLimit = `${coords[rank - 1]} < ${this.outputShape[rank - 1]}`;
-          const innerDims = rank === 1 ? "source" : `vec2(${source.slice(-2).join()})`;
-          const componentSetup = [
-            `${dtype} rc = outputLoc;`,
-            `${coords[rank - 1]} += 1;
-       if(${cLimit}) {
-      `,
-            rank === 1
-              ? ""
-              : `}
-       rc = outputLoc;
-       ${coords[rank - 2]} += 1;
-       if(${coords[rank - 2]} < ${this.outputShape[rank - 2]}) {`,
-            rank === 1
-              ? ""
-              : `  ${coords[rank - 1]} += 1;
-         if(${cLimit}) {`,
-          ];
-          const paddingArea =
-            rank === 1
-              ? "rc < start || rc >= end"
-              : "any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))";
-          let mainLoop = "";
-          for (let i = 0, j = rank === 1 ? 2 : 4; i < j; i++) {
-            mainLoop += `
-        ${componentSetup[i]}
-        if (${paddingArea}) {
-          result[${i}] = float(${constantValue});
-        } else {
-          ${dtype} source = rc - start;
-          result[${i}] = getChannel(getX(${source.join()}), ${innerDims});
-        }
-      `;
-          }
-          mainLoop += rank === 1 ? `} ` : `}}`;
-          this.userCode = `
-      const ${dtype} start = ${dtype}(${start});
-      const ${dtype} end = ${dtype}(${end});
-
-      void main() {
-        ${dtype} outputLoc = getOutputCoords();
-        vec4 result = vec4(0.);
-        ${mainLoop}
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=pad_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/pool_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class Pool2DProgram {
-        constructor(
-          convInfo,
-          poolType,
-          computePositions,
-          flattenPositions = false,
-          includeBatchInIndex = false
-        ) {
-          this.variableNames = ["x"];
-          if (poolType === "avg" && computePositions) {
-            throw new Error("Cannot compute positions for average pool.");
-          }
-          const filterWidth = convInfo.filterWidth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          this.outputShape = convInfo.outShape;
-          const isAvgPool = poolType === "avg";
-          const batchFlattenPositionStr = `((batch  * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`;
-          const flattenPositionStr = `(xR * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`;
-          let initializationValue = "0.0";
-          if (!isAvgPool) {
-            // WebGL on Firefox Linux can't compile 1/0 so we do 1/eps.
-            initializationValue = "-1.0 / 1e-20";
-          }
-          if (computePositions) {
-            const compareOp = ">=";
-            this.userCode = `
-        const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
-        const ivec2 pads = ivec2(${padTop}, ${padLeft});
-
-        void main() {
-          ivec4 coords = getOutputCoords();
-          int batch = coords[0];
-          int d = coords[3];
-
-          ivec2 xRCCorner = coords.yz * strides - pads;
-          int xRCorner = xRCCorner.x;
-          int xCCorner = xRCCorner.y;
-
-          // max/min x(?, ?, d) to get y(yR, yC, d).
-          // ? = to be determined
-          float minMaxValue = 0.0;
-          float minMaxValueFound = 0.0;
-          int minMaxPosition = 0;
-          float avgValue = 0.0;
-
-          for (int wR = 0; wR < ${effectiveFilterHeight};
-              wR += ${dilationHeight}) {
-            int xR = xRCorner + wR;
-
-            if (xR < 0 || xR >= ${convInfo.inHeight}) {
-              continue;
-            }
-
-            for (int wC = 0; wC < ${effectiveFilterWidth};
-                wC += ${dilationWidth}) {
-              int xC = xCCorner + wC;
-
-              if (xC < 0 || xC >= ${convInfo.inWidth}) {
-                continue;
-              }
-
-              float value = getX(batch, xR, xC, d);
-
-              // If a min / max value has already been found, use it. If not,
-              // use the current value.
-              float currMinMaxValue = mix(
-                  value, minMaxValue, minMaxValueFound);
-              if (value ${compareOp} currMinMaxValue) {
-                minMaxValue = value;
-                minMaxValueFound = 1.0;
-                minMaxPosition = ${
-                  flattenPositions
-                    ? includeBatchInIndex
-                      ? batchFlattenPositionStr
-                      : flattenPositionStr
-                    : `wR * ${effectiveFilterWidth} + wC`
-                };
-              }
-            }
-          }
-          setOutput(float(minMaxPosition));
-        }
-      `;
-            return;
-          }
-          const compareOp = "max";
-          let returnValue =
-            `${poolType}(${poolType}(${poolType}(` +
-            "minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
-          if (poolType === "avg") {
-            returnValue = `avgValue / count`;
-          }
-          const filterWidthNearestVec4 = Math.floor(filterWidth / 4) * 4;
-          const filterWidthVec4Remainder = filterWidth % 4;
-          const updateSnippet = `
-      if (${isAvgPool}) {
-        avgValue += dot(values, ones);
-      } else {
-        minMaxValue = ${compareOp}(values, minMaxValue);
-      }
-    `;
-          this.userCode = `
-      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
-      const ivec2 pads = ivec2(${padTop}, ${padLeft});
-      const float initializationValue = ${initializationValue};
-      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
-
-      float count = 0.0;
-
-      float getValue(int batch, int xR, int xC, int d) {
-        if (xC < 0 || xC >= ${convInfo.inWidth}) {
-          return initializationValue;
-        }
-        count += 1.0;
-        return getX(batch, xR, xC, d);
-      }
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int batch = coords[0];
-        int d = coords[3];
-
-        ivec2 xRCCorner = coords.yz * strides - pads;
-        int xRCorner = xRCCorner.x;
-        int xCCorner = xRCCorner.y;
-
-        // max/min x(?, ?, d) to get y(yR, yC, d).
-        // ? = to be determined
-        vec4 minMaxValue = vec4(${initializationValue});
-        float avgValue = 0.0;
-        count = 0.0;
-
-        for (int wR = 0; wR < ${effectiveFilterHeight};
-            wR += ${dilationHeight}) {
-          int xR = xRCorner + wR;
-
-          if (xR < 0 || xR >= ${convInfo.inHeight}) {
-            continue;
-          }
-
-          for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {
-            int xC = xCCorner + wC * ${dilationWidth};
-
-            vec4 values = vec4(
-              getValue(batch, xR, xC, d),
-              getValue(batch, xR, xC + ${dilationWidth}, d),
-              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),
-              getValue(batch, xR, xC + 3 * ${dilationWidth}, d)
-            );
-
-            ${updateSnippet}
-          }
-
-          int xC = xCCorner + ${filterWidthNearestVec4};
-          if (${filterWidthVec4Remainder === 1}) {
-            vec4 values = vec4(
-              getValue(batch, xR, xC, d),
-              initializationValue,
-              initializationValue,
-              initializationValue
-            );
-
-            ${updateSnippet}
-          } else if (${filterWidthVec4Remainder === 2}) {
-            vec4 values = vec4(
-              getValue(batch, xR, xC, d),
-              getValue(batch, xR, xC + ${dilationWidth}, d),
-              initializationValue,
-              initializationValue
-            );
-
-            ${updateSnippet}
-          } else if (${filterWidthVec4Remainder === 3}) {
-            vec4 values = vec4(
-              getValue(batch, xR, xC, d),
-              getValue(batch, xR, xC + ${dilationWidth}, d),
-              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),
-              initializationValue
-            );
-
-            ${updateSnippet}
-          }
-        }
-        setOutput(${returnValue});
-      }
-    `;
-        }
-      }
-      class Pool3DProgram {
-        constructor(
-          convInfo,
-          poolType,
-          computePositions,
-          flattenPositions = false,
-          includeBatchInIndex = false
-        ) {
-          this.variableNames = ["x"];
-          if (poolType === "avg" && computePositions) {
-            throw new Error("Cannot compute positions for average pool.");
-          }
-          const filterWidth = convInfo.filterWidth;
-          const strideDepth = convInfo.strideDepth;
-          const strideHeight = convInfo.strideHeight;
-          const strideWidth = convInfo.strideWidth;
-          const dilationDepth = convInfo.dilationDepth;
-          const dilationHeight = convInfo.dilationHeight;
-          const dilationWidth = convInfo.dilationWidth;
-          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
-          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
-          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
-          const padFront = convInfo.padInfo.front;
-          const padTop = convInfo.padInfo.top;
-          const padLeft = convInfo.padInfo.left;
-          this.outputShape = convInfo.outShape;
-          const isAvgPool = poolType === "avg";
-          let initializationValue = "0.0";
-          if (!isAvgPool) {
-            // WebGL on Firefox Linux can't compile 1/0 so we do 1/eps.
-            initializationValue = "-1.0 / 1e-20";
-          }
-          if (computePositions) {
-            const compareOp = ">=";
-            this.userCode = `
-        const ivec3 strides =
-            ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
-        const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
-
-        void main() {
-          ivec5 coords = getOutputCoords();
-          int batch = coords.x;
-          int ch = coords.u;
-
-          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
-          int xDCorner = xCorner.x;
-          int xRCorner = xCorner.y;
-          int xCCorner = xCorner.z;
-
-          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
-          // ? = to be determined
-          float minMaxValue = 0.0;
-          float minMaxValueFound = 0.0;
-          int minMaxPosition = 0;
-
-          for (int wD = 0; wD < ${effectiveFilterDepth};
-              wD += ${dilationDepth}) {
-            int xD = xDCorner + wD;
-
-            if (xD < 0 || xD >= ${convInfo.inDepth}) {
-              continue;
-            }
-
-            for (int wR = 0; wR < ${effectiveFilterHeight};
-                wR += ${dilationHeight}) {
-              int xR = xRCorner + wR;
-
-              if (xR < 0 || xR >= ${convInfo.inHeight}) {
-                continue;
-              }
-
-              for (int wC = 0; wC < ${effectiveFilterWidth};
-                  wC += ${dilationWidth}) {
-                int xC = xCCorner + wC;
-
-                if (xC < 0 || xC >= ${convInfo.inWidth}) {
-                  continue;
-                }
-
-                float value = getX(batch, xD, xR, xC, ch);
-
-                // If a min / max value has already been found, use it. If not,
-                // use the current value.
-                float currMinMaxValue = mix(
-                    value, minMaxValue, minMaxValueFound);
-                if (value ${compareOp} currMinMaxValue) {
-                  minMaxValue = value;
-                  minMaxValueFound = 1.0;
-                  minMaxPosition = ${
-                    flattenPositions
-                      ? includeBatchInIndex
-                        ? `(((batch * ${convInfo.inDepth} + xD) * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch`
-                        : `((xD * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch`
-                      : `wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +
-                      wR * ${effectiveFilterWidth} + wC`
-                  };
-                }
-              }
-            }
-          }
-          setOutput(float(minMaxPosition));
-        }
-      `;
-            return;
-          }
-          const compareOp = "max";
-          let returnValue =
-            `${poolType}(${poolType}(${poolType}(` +
-            "minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
-          if (poolType === "avg") {
-            returnValue = `avgValue / count`;
-          }
-          const filterWidthNearestVec4 = Math.floor(filterWidth / 4) * 4;
-          const filterWidthVec4Remainder = filterWidth % 4;
-          const updateSnippet = `
-      if (${isAvgPool}) {
-        avgValue += dot(values, ones);
-      } else {
-        minMaxValue = ${compareOp}(values, minMaxValue);
-      }
-    `;
-          this.userCode = `
-      const ivec3 strides =
-        ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
-      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
-      const float initializationValue = ${initializationValue};
-      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
-
-      float count = 0.0;
-
-      float getValue(int batch, int xD, int xR, int xC, int ch) {
-        if (xC < 0 || xC >= ${convInfo.inWidth}) {
-          return initializationValue;
-        }
-        count += 1.0;
-        return getX(batch, xD, xR, xC, ch);
-      }
-
-      void main() {
-        ivec5 coords = getOutputCoords();
-        int batch = coords.x;
-        int ch = coords.u;
-
-        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
-        int xDCorner = xCorner.x;
-        int xRCorner = xCorner.y;
-        int xCCorner = xCorner.z;
-
-        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
-        // ? = to be determined
-        vec4 minMaxValue = vec4(${initializationValue});
-        float avgValue = 0.0;
-        count = 0.0;
-
-        for (int wD = 0; wD < ${effectiveFilterDepth};
-            wD += ${dilationDepth}) {
-          int xD = xDCorner + wD;
-
-          if (xD < 0 || xD >= ${convInfo.inDepth}) {
-            continue;
-          }
-
-          for (int wR = 0; wR < ${effectiveFilterHeight};
-            wR += ${dilationHeight}) {
-            int xR = xRCorner + wR;
-
-            if (xR < 0 || xR >= ${convInfo.inHeight}) {
-              continue;
-            }
-
-            for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {
-              int xC = xCCorner + wC * ${dilationWidth};
-
-              vec4 values = vec4(
-                getValue(batch, xD, xR, xC, ch),
-                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),
-                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),
-                getValue(batch, xD, xR, xC + 3 * ${dilationWidth}, ch)
-              );
-
-              ${updateSnippet}
-            }
-
-            int xC = xCCorner + ${filterWidthNearestVec4};
-            if (${filterWidthVec4Remainder === 1}) {
-              vec4 values = vec4(
-                getValue(batch, xD, xR, xC, ch),
-                initializationValue,
-                initializationValue,
-                initializationValue
-              );
-
-              ${updateSnippet}
-            } else if (${filterWidthVec4Remainder === 2}) {
-              vec4 values = vec4(
-                getValue(batch, xD, xR, xC, ch),
-                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),
-                initializationValue,
-                initializationValue
-              );
-
-              ${updateSnippet}
-            } else if (${filterWidthVec4Remainder === 3}) {
-              vec4 values = vec4(
-                getValue(batch, xD, xR, xC, ch),
-                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),
-                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),
-                initializationValue
-              );
-
-              ${updateSnippet}
-            }
-          }
-          setOutput(${returnValue});
-        }
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=pool_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/reduce_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ReduceProgram {
-        constructor(reduceInfo, reduceType) {
-          this.variableNames = ["x"];
-          const windowSize = reduceInfo.windowSize;
-          const batchSize = reduceInfo.batchSize;
-          const inSize = reduceInfo.inSize;
-          const outSize = Math.ceil(inSize / windowSize);
-          this.outputShape = [batchSize, outSize];
-          let initializationValue = "0.0";
-          let compareOp = ``;
-          if (reduceType === "prod") {
-            initializationValue = "1.0";
-          } else if (reduceType === "min") {
-            // WebGL on Firefox Linux can't compile 1/0 so we do 1/eps.
-            initializationValue = "1.0 / 1e-20";
-            compareOp = `min`;
-          } else if (reduceType === "max") {
-            // WebGL on Firefox Linux can't compile 1/0 so we do 1/eps.
-            initializationValue = "-1.0 / 1e-20";
-            compareOp = `max`;
-          }
-          let returnValue =
-            `${reduceType}(${reduceType}(${reduceType}(` +
-            "minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
-          if (reduceType === "sum") {
-            returnValue = `sumValue`;
-          } else if (reduceType === "prod") {
-            returnValue = `prodValue`;
-          } else if (reduceType === "all") {
-            returnValue = `allValue`;
-          } else if (reduceType === "any") {
-            returnValue = `anyValue`;
-          }
-          const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;
-          const windowSizeVec4Remainder = windowSize % 4;
-          let updateSnippet = `
-      if (${reduceType === "sum"}) {
-        sumValue += dot(values, ones);
-      } else if (${reduceType === "prod"}) {
-        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
-        prodValue *= tmp[0] * tmp[1];
-      } else {
-        minMaxValue = ${compareOp}(values, minMaxValue);
-      }
-    `;
-          let vecType = `vec4`;
-          if (reduceType === "all") {
-            initializationValue = "1.0";
-            updateSnippet = `
-        bool reducedAllValue = all(values);
-        float floatedReducedAllValue = float(reducedAllValue);
-        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
-      `;
-            vecType = `bvec4`;
-          } else if (reduceType === "any") {
-            initializationValue = "0.0";
-            updateSnippet = `
-        bool reducedAnyValue = any(values);
-        float floatedReducedAnyValue = float(reducedAnyValue);
-        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
-      `;
-            vecType = `bvec4`;
-          }
-          let checkOutOfBounds = "";
-          if (inSize % windowSize > 0) {
-            checkOutOfBounds = `
-        if (inIdx < 0 || inIdx >= ${inSize}) {
-          return initializationValue;
-        }
-      `;
-          }
-          this.userCode = `
-      const float initializationValue = ${initializationValue};
-      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
-
-      float getValue(int batch, int inIdx) {
-        ${checkOutOfBounds}
-        return getX(batch, inIdx);
-      }
-
-      void main() {
-        ivec2 coords = getOutputCoords();
-        int batch = coords[0];
-        int outIdx = coords[1];
-        int inOffset = outIdx * ${windowSize};
-
-        vec4 minMaxValue = vec4(${initializationValue});
-        float prodValue = 1.0;
-        float sumValue = 0.0;
-        float allValue = 1.0;
-        float anyValue = 0.0;
-
-        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {
-          int inIdx = inOffset + i;
-          ${vecType} values = ${vecType}(
-            getValue(batch, inIdx),
-            getValue(batch, inIdx + 1),
-            getValue(batch, inIdx + 2),
-            getValue(batch, inIdx + 3)
-          );
-
-          ${updateSnippet}
-        }
-
-        int inIdx = inOffset + ${windowSizeNearestVec4};
-        if (${windowSizeVec4Remainder === 1}) {
-          ${vecType} values = ${vecType}(
-            getValue(batch, inIdx),
-            initializationValue,
-            initializationValue,
-            initializationValue
-          );
-
-          ${updateSnippet}
-        } else if (${windowSizeVec4Remainder === 2}) {
-          ${vecType} values = ${vecType}(
-            getValue(batch, inIdx),
-            getValue(batch, inIdx + 1),
-            initializationValue,
-            initializationValue
-          );
-
-          ${updateSnippet}
-        } else if (${windowSizeVec4Remainder === 3}) {
-          ${vecType} values = ${vecType}(
-            getValue(batch, inIdx),
-            getValue(batch, inIdx + 1),
-            getValue(batch, inIdx + 2),
-            initializationValue
-          );
-
-          ${updateSnippet}
-        }
-        setOutput(${returnValue});
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=reduce_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/reshape_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class reshape_packed_gpu_ReshapePackedProgram {
-        constructor(outputShape, inputShape) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = outputShape;
-          let mainLoop = ``;
-          for (let i = 0; i < 4; i++) {
-            let thisRC = `thisRC = rc;`;
-            if (i % 2 === 1) {
-              thisRC += `thisRC.z += 1;`;
-            }
-            if (i > 1) {
-              thisRC += `thisRC.y += 1;`;
-            }
-            mainLoop += `
-        ${thisRC}
-        ${i > 0 ? `if(thisRC.y < rows && thisRC.z < cols){` : ""}
-          int flatIndex = getFlatIndex(thisRC);
-
-          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
-          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
-
-          result[${i}] =
-            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
-        ${i > 0 ? "}" : ""}
-      `;
-          }
-          this.userCode = `
-      ${getReshapedInputCoords(inputShape)}
-      ${getFlatIndexFrom3D(outputShape)}
-
-      void main() {
-        ivec3 rc = getOutputCoords();
-
-        vec4 result = vec4(0.);
-
-        ivec3 thisRC;
-        int rows = ${outputShape[1]};
-        int cols = ${outputShape[2]};
-
-        ${mainLoop}
-
-        setOutput(result);
-      }
-    `;
-        }
-      }
-      function getReshapedInputCoords(shape) {
-        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(["r", "c", "d"], shape);
-        return `
-    ivec3 inputCoordsFromReshapedOutCoords(int index) {
-      ${coordsFromIndexSnippet}
-      return ivec3(r, c, d);
-    }
-  `;
-      }
-      //# sourceMappingURL=reshape_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_backprop_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ResizeBilinearBackpropProgram {
-        constructor(dy, x, alignCorners) {
-          this.variableNames = ["dy"];
-          this.outputShape = [];
-          this.outputShape = x.shape;
-          const [, xHeight, xWidth] = x.shape;
-          const [, yHeight, yWidth] = dy.shape;
-          // In the backwards pass, we want to find the pixels that were generated for
-          // each pixel in the input image the forward pass and add the corresponding
-          // coefficient from dy to the gradient (with some interpolation).
-          const effectiveXSize = [
-            alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,
-            alignCorners && yWidth > 1 ? xWidth - 1 : xWidth,
-          ];
-          const effectiveYSize = [
-            alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,
-            alignCorners && yWidth > 1 ? yWidth - 1 : yWidth,
-          ];
-          const heightScale = effectiveXSize[0] / effectiveYSize[0];
-          const widthScale = effectiveXSize[1] / effectiveYSize[1];
-          const invHeightScale = 1 / heightScale;
-          const invWidthScale = 1 / widthScale;
-          // This defines the size of the window of values around a particular
-          // index in dy that we want to search for contributions to dx.
-          const winHeight = Math.ceil(invHeightScale) * 2 + 2;
-          const winWidth = Math.ceil(invWidthScale) * 2 + 2;
-          this.userCode = `
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int d = coords[3];
-        int r = coords[1];
-        int c = coords[2];
-
-        float accumulator = 0.0;
-
-        const float heightScale = float(${heightScale});
-        const float widthScale = float(${widthScale});
-
-        const float invHeightScale = float(${invHeightScale});
-        const float invWidthScale = float(${invWidthScale});
-
-        const int winHeight = int(${winHeight});
-        const int winWidth = int(${winWidth});
-
-        // Compute bounds for where in dy we will look
-        float startRLerp = floor(float(r) * invHeightScale);
-        int startDyR = int(startRLerp - float(winHeight / 2));
-
-        float startCLerp = floor(float(c) * invWidthScale);
-        int startDyC = int(startCLerp - float(winWidth / 2));
-
-        // Loop over dy
-        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
-          int dyR = dyROffset + startDyR;
-
-          // Guard against the window exceeding the bounds of dy
-          if (dyR < 0 || dyR >= ${yHeight}) {
-            continue;
-          }
-
-          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
-            int dyC = dyCOffset + startDyC;
-
-            // Guard against the window exceeding the bounds of dy
-            if (dyC < 0 || dyC >= ${yWidth}) {
-              continue;
-            }
-
-            float dxR = float(dyR) * heightScale;
-            int topDxRIndex = int(floor(dxR));
-            int bottomDxRIndex = int(min(ceil(dxR), ${xHeight - 1}.0));
-            float dxRLerp = dxR - float(topDxRIndex);
-            float inverseDxRLerp = 1.0 - dxRLerp;
-
-            float dxC = float(dyC) * widthScale;
-            int leftDxCIndex = int(floor(dxC));
-            int rightDxCIndex = int(min(ceil(dxC), ${xWidth - 1}.0));
-            float dxCLerp = dxC - float(leftDxCIndex);
-            float inverseDxCLerp = 1.0 - dxCLerp;
-
-            if (r == topDxRIndex && c == leftDxCIndex) {
-              // topLeft
-              accumulator +=
-                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
-            }
-
-            if (r == topDxRIndex && c == rightDxCIndex) {
-              // topRight
-              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
-            }
-
-            if (r == bottomDxRIndex && c == leftDxCIndex) {
-              // bottomLeft
-              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
-            }
-
-            if (r == bottomDxRIndex && c == rightDxCIndex) {
-              // bottomRight
-              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
-            }
-          }
-        }
-        // End loop over dy
-
-        setOutput(accumulator);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=resize_bilinear_backprop_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ResizeBilinearProgram {
-        constructor(inputShape, newHeight, newWidth, alignCorners) {
-          this.variableNames = ["A"];
-          this.outputShape = [];
-          const [batch, oldHeight, oldWidth, depth] = inputShape;
-          this.outputShape = [batch, newHeight, newWidth, depth];
-          const effectiveInSize = [
-            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
-            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
-          ];
-          const effectiveOutSize = [
-            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
-            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
-          ];
-          this.userCode = `
-      const vec2 effectiveInputOverOutputRatioRC = vec2(
-          ${effectiveInSize[0] / effectiveOutSize[0]},
-          ${effectiveInSize[1] / effectiveOutSize[1]});
-      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int d = coords[3];
-        ivec2 yRC = coords.yz;
-
-        // Fractional source index.
-        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;
-
-        // Compute the four integer indices.
-        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);
-        ivec2 sourceCeilRC = ivec2(
-          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
-
-        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);
-        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);
-        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);
-        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);
-
-        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);
-
-        float top = topLeft + (topRight - topLeft) * fracRC.y;
-        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
-        float newValue = top + (bottom - top) * fracRC.x;
-
-        setOutput(newValue);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=resize_bilinear_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ResizeBilinearPackedProgram {
-        constructor(inputShape, newHeight, newWidth, alignCorners) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = [];
-          const [batch, oldHeight, oldWidth, depth] = inputShape;
-          this.outputShape = [batch, newHeight, newWidth, depth];
-          const effectiveInSize = [
-            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
-            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
-          ];
-          const effectiveOutSize = [
-            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
-            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
-          ];
-          this.userCode = `
-      const vec3 effectiveInputOverOutputRatioRC = vec3(
-          ${effectiveInSize[0] / effectiveOutSize[0]},
-          ${effectiveInSize[1] / effectiveOutSize[1]},
-          ${effectiveInSize[1] / effectiveOutSize[1]});
-      const vec3 inputShapeRC = vec3(${oldHeight}.0, ${oldWidth}.0,
-                                     ${oldWidth}.0);
-
-      float getAValue(int b, int r, int c, int d) {
-        return getChannel(getA(b, r, c, d), vec2(c, d));
-      }
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int d = coords[3];
-        // Calculate values for next column in yRC.z.
-        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
-
-        // Fractional source index.
-        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;
-
-        // Compute the four integer indices.
-        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);
-        ivec3 sourceCeilRC = ivec3(
-          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
-
-        // Should we calculate next column and row elements in 2x2 packed cell.
-        bool hasNextCol = d < ${depth - 1};
-        bool hasNextRow = coords.z < ${newWidth - 1};
-
-        // In parallel, construct four corners for all four components in
-        // packed 2x2 cell.
-        vec4 topLeft = vec4(
-          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
-          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
-                     : 0.0,
-          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
-                     : 0.0,
-          (hasNextRow && hasNextCol) ?
-            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);
-
-        vec4 bottomLeft = vec4(
-          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
-          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
-                     : 0.0,
-          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
-                     : 0.0,
-          (hasNextRow && hasNextCol) ?
-            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);
-
-        vec4 topRight = vec4(
-          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
-          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
-                     : 0.0,
-          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
-                     : 0.0,
-          (hasNextRow && hasNextCol) ?
-            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);
-
-        vec4 bottomRight = vec4(
-          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
-          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
-                     : 0.0,
-          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
-                     : 0.0,
-          (hasNextRow && hasNextCol) ?
-            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);
-
-        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);
-
-        vec4 top = mix(topLeft, topRight, fracRC.yyzz);
-        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
-        vec4 newValue = mix(top, bottom, fracRC.x);
-
-        setOutput(newValue);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=resize_bilinear_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_backprop_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ResizeNearestNeigborBackpropProgram {
-        constructor(dy, x, alignCorners) {
-          this.variableNames = ["dy"];
-          this.outputShape = [];
-          this.outputShape = x.shape;
-          const [, xHeight, xWidth] = x.shape;
-          const [, yHeight, yWidth] = dy.shape;
-          // In the backwards pass, we want to find the pixels that were generated for
-          // each pixel in the input image the forward pass and add the corresponding
-          // coefficient from dy to the gradient (with some interpolation).
-          const effectiveXSize = [
-            alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,
-            alignCorners && yWidth > 1 ? xWidth - 1 : xWidth,
-          ];
-          const effectiveYSize = [
-            alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,
-            alignCorners && yWidth > 1 ? yWidth - 1 : yWidth,
-          ];
-          const heightScale = effectiveXSize[0] / effectiveYSize[0];
-          const widthScale = effectiveXSize[1] / effectiveYSize[1];
-          const invHeightScale = 1 / heightScale;
-          const invWidthScale = 1 / widthScale;
-          // This defines the size of the window of values around a particular
-          // index in dy that we want to search for contributions to dx.
-          const winHeight = Math.ceil(invHeightScale) * 2 + 2;
-          const winWidth = Math.ceil(invWidthScale) * 2 + 2;
-          this.userCode = `
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int d = coords[3];
-        int r = coords[1];
-        int c = coords[2];
-
-        float accumulator = 0.0;
-
-        const float heightScale = float(${heightScale});
-        const float widthScale = float(${widthScale});
-
-        const float invHeightScale = float(${invHeightScale});
-        const float invWidthScale = float(${invWidthScale});
-
-        const int winHeight = int(${winHeight});
-        const int winWidth = int(${winWidth});
-
-        // Compute bounds for where in dy we will look
-        float startRLerp = floor(float(r) * invHeightScale);
-        int startDyR = int(floor(startRLerp - float(winHeight / 2)));
-
-        float startCLerp = floor(float(c) * invWidthScale);
-        int startDyC = int(floor(startCLerp - float(winWidth / 2)));
-
-        // Loop over dy
-        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
-          int dyR = dyROffset + startDyR;
-
-          // Guard against the window exceeding the bounds of dy
-          if (dyR < 0 || dyR >= ${yHeight}) {
-            continue;
-          }
-
-          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
-            int dyC = dyCOffset + startDyC;
-
-            // Guard against the window exceeding the bounds of dy
-            if (dyC < 0 || dyC >= ${yWidth}) {
-              continue;
-            }
-
-            float sourceFracRow =
-              float(${effectiveXSize[0]}) *
-                (float(dyR) / float(${effectiveYSize[0]}));
-
-            float sourceFracCol =
-                float(${effectiveXSize[1]}) *
-                  (float(dyC) / float(${effectiveYSize[1]}));
-
-            int sourceNearestRow = int(min(
-                float(int(${xHeight}) - 1),
-                ${alignCorners} ? float(round(sourceFracRow)) :
-                                  float(floor(sourceFracRow))));
-
-            int sourceNearestCol = int(min(
-                float(int(${xWidth}) - 1),
-                ${alignCorners} ? float(round(sourceFracCol)) :
-                                  float(floor(sourceFracCol))));
-
-            if (r == sourceNearestRow && c == sourceNearestCol) {
-              accumulator += getDy(b, dyR, dyC, d);
-            }
-          }
-        }
-        // End loop over dy
-
-        setOutput(accumulator);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=resize_nearest_neighbor_backprop_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class ResizeNearestNeighborProgram {
-        constructor(inputShape, newHeight, newWidth, alignCorners) {
-          this.variableNames = ["A"];
-          this.outputShape = [];
-          const [batch, oldHeight, oldWidth, depth] = inputShape;
-          this.outputShape = [batch, newHeight, newWidth, depth];
-          const effectiveInSize = [
-            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
-            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
-          ];
-          const effectiveOutSize = [
-            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
-            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
-          ];
-          // When align corners is false, we rounds the value with floor.
-          const roundBase = alignCorners ? "0.5" : "0.0";
-          this.userCode = `
-      const vec2 effectiveInputOverOutputRatioRC = vec2(
-          ${effectiveInSize[0] / effectiveOutSize[0]},
-          ${effectiveInSize[1] / effectiveOutSize[1]});
-      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);
-
-      void main() {
-        ivec4 coords = getOutputCoords();
-        int b = coords[0];
-        int d = coords[3];
-        ivec2 yRC = coords.yz;
-
-        // Fractional source index.
-        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;
-
-        // Compute the coordinators of nearest neighbor point.
-        ivec2 sourceNearestRC = ivec2(
-          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${roundBase})));
-
-        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
-
-        setOutput(newValue);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=resize_nearest_neighbor_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/reverse_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class reverse_gpu_ReverseProgram {
-        constructor(xShape, axis) {
-          this.variableNames = ["x"];
-          const rank = xShape.length;
-          if (rank > 4) {
-            throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);
-          }
-          this.outputShape = xShape;
-          if (rank === 1) {
-            this.userCode = `
-        void main() {
-          int coord = getOutputCoords();
-          setOutput(getX(${xShape[0]} - coord - 1));
-        }
-      `;
-            return;
-          }
-          const getInCoord = (i) => {
-            if (axis.indexOf(i) !== -1 && xShape[i] !== 1) {
-              return `${xShape[i]} - coords[${i}] - 1`;
-            }
-            return `coords[${i}]`;
-          };
-          const inCoords = xShape.map((_, i) => getInCoord(i)).join(",");
-          const type = getCoordsDataType(rank);
-          this.userCode = `
-      void main() {
-        ${type} coords = getOutputCoords();
-        setOutput(getX(${inCoords}));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=reverse_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/reverse_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class reverse_packed_gpu_ReversePackedProgram {
-        constructor(xShape, axis) {
-          this.variableNames = ["x"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          const rank = xShape.length;
-          if (rank > 4) {
-            throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);
-          }
-          this.outputShape = xShape;
-          const channels = getChannels("rc", rank);
-          const nextColumn = `${channels[rank - 1]} + 1 < ${this.outputShape[rank - 1]}`;
-          const nextRow = `${channels[rank - 2]} + 1 < ${this.outputShape[rank - 2]}`;
-          const type = getCoordsDataType(rank);
-          if (rank === 1) {
-            this.userCode = `
-        void main(){
-          int rc = getOutputCoords();
-          vec4 result = vec4(0.);
-          result.r = getChannel(getX(${xShape[0]} - rc - 1),
-            ${xShape[0]} - rc - 1);
-          if(${nextColumn}){
-              result.g = getChannel(getX(${xShape[0]} - (rc  + 1) - 1),
-                ${xShape[0]} - (rc  + 1) - 1);
-          }
-          setOutput(result);
-        }
-      `;
-          } else {
-            this.userCode = `
-        void main() {
-          ${type} rc = getOutputCoords();
-          vec4 result = vec4(0.);
-          result.r = ${getR(channels.slice())};
-          if(${nextColumn}){
-            result.g = ${getG(channels.slice())};
-          }
-          if(${nextRow}) {
-            result.b = ${getB(channels.slice())};
-            if(${nextColumn}) {
-              result.a = ${getA(channels.slice())};
-            }
-          }
-          setOutput(result);
-        }
-    `;
-          }
-          function getR(channels) {
-            return getChannel(channels);
-          }
-          function getG(channels) {
-            channels[rank - 1] = "(" + channels[rank - 1] + ` + 1)`;
-            return getChannel(channels);
-          }
-          function getB(channels) {
-            channels[rank - 2] = "(" + channels[rank - 2] + ` + 1)`;
-            return getChannel(channels);
-          }
-          function getA(channels) {
-            channels[rank - 1] = "(" + channels[rank - 1] + ` + 1)`;
-            channels[rank - 2] = "(" + channels[rank - 2] + ` + 1)`;
-            return getChannel(channels);
-          }
-          function getChannel(channels) {
-            const inCoordsArray = xShape.map((_, i) => getInCoord(i, channels));
-            const inCoords = inCoordsArray.join(",");
-            const innerDims = inCoordsArray.slice(-2).join(",");
-            return `getChannel(getX(${inCoords}), vec2(${innerDims}))`;
-          }
-          function getInCoord(i, channels1) {
-            if (axis.indexOf(i) !== -1 && xShape[i] !== 1) {
-              return `${xShape[i]} - ${channels1[i]} - 1`;
-            } else {
-              return `${channels1[i]}`;
-            }
-          }
-        }
-      }
-      //# sourceMappingURL=reverse_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/scatter_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class scatter_gpu_ScatterProgram {
-        constructor(
-          updateSize,
-          sliceDim,
-          indicesRank,
-          updatesRank,
-          strides,
-          shape,
-          summingDupeIndex = true
-        ) {
-          this.variableNames = ["updates", "indices", "defaultValue"];
-          this.outputShape = shape;
-          const stridesType = getCoordsDataType(strides.length);
-          const dtype = getCoordsDataType(shape.length);
-          let indicesString = "";
-          if (indicesRank === 1) {
-            indicesString = "i";
-          } else if (indicesRank === 2) {
-            indicesString = "i, j";
-          }
-          const indicesSnippet = `getIndices(${indicesString})`;
-          let updatesString = "";
-          if (updatesRank === 1) {
-            updatesString = "i";
-          } else if (updatesRank === 2) {
-            updatesString = "i, coords[1]";
-          }
-          const updatesSnippet = `getUpdates(${updatesString})`;
-          const strideString = sliceDim > 1 ? "strides[j]" : "strides";
-          this.userCode = `
-        ${stridesType} strides = ${stridesType}(${strides});
-
-        void main() {
-          ${dtype} coords = getOutputCoords();
-          float sum = 0.0;
-          bool found = false;
-          for (int i = 0; i < ${updateSize}; i++) {
-            int flattenedIndex = 0;
-            for (int j = 0; j < ${sliceDim}; j++) {
-              int index = round(${indicesSnippet});
-              flattenedIndex += index * ${strideString};
-            }
-            if (flattenedIndex == coords[0]) {
-              sum += ${updatesSnippet};
-              found = true;
-            }
-          }
-          setOutput(mix(getDefaultValue(), sum, float(found)));
-        }
-      `;
-        }
-      }
-      //# sourceMappingURL=scatter_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/segment_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      class SegmentOpProgram {
-        constructor(segOpInfo, segOpType) {
-          this.variableNames = ["x", "segmentIds"];
-          const windowSize = segOpInfo.windowSize;
-          const batchSize = segOpInfo.batchSize;
-          const inSize = segOpInfo.inSize;
-          const numSegments = segOpInfo.numSegments;
-          const outSize = numSegments * Math.ceil(inSize / windowSize);
-          this.outputShape = [batchSize, outSize];
-          const initializationValue = "0.0";
-          const returnValue = `sumValue`;
-          const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;
-          const windowSizeVec4Remainder = windowSize % 4;
-          const updateSnippet = `
-        sumValue += dot(values, segFilter);
-    `;
-          let checkValueOutOfBounds = "";
-          if (inSize % windowSize > 0) {
-            checkValueOutOfBounds = `
-        if (inIdx < 0 || inIdx >= ${inSize}) {
-          return initializationValue;
-        }
-      `;
-          }
-          let checkSegmentIdOutOfBounds = "";
-          if (inSize % windowSize > 0) {
-            checkSegmentIdOutOfBounds = `
-        if (inIdx < 0 || inIdx >= ${inSize}) {
-          return -1.0;
-        }
-      `;
-          }
-          this.userCode = `
-      const float initializationValue = ${initializationValue};
-
-      float getValue(int batch, int inIdx) {
-        ${checkValueOutOfBounds}
-        return getX(batch, inIdx);
-      }
-
-      float getSegmentIdAtIndex(int inIdx) {
-        ${checkSegmentIdOutOfBounds}
-        return getSegmentIds(inIdx);
-      }
-
-      void main() {
-        ivec2 coords = getOutputCoords();
-        int batch = coords[0];
-        int outIdx = coords[1];
-        int inOffset = int(floor(float(outIdx) / float(
-          ${numSegments})) * float(${windowSize}));
-        int currentSeg = int(mod(float(outIdx), float(${numSegments})));
-
-        float sumValue = 0.0;
-
-        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {
-          int inIdx = inOffset + i;
-          vec4 values = vec4(
-            getValue(batch, inIdx),
-            getValue(batch, inIdx + 1),
-            getValue(batch, inIdx + 2),
-            getValue(batch, inIdx + 3)
-          );
-
-          vec4 segFilter = vec4(
-            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
-            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
-            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
-            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
-          );
-
-          ${updateSnippet}
-        }
-
-        int inIdx = inOffset + ${windowSizeNearestVec4};
-        if (${windowSizeVec4Remainder === 1}) {
-          vec4 values = vec4(
-            getValue(batch, inIdx),
-            initializationValue,
-            initializationValue,
-            initializationValue
-          );
-
-          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));
-
-          vec4 segFilter = vec4(
-            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
-            0,
-            0,
-            0
-          );
-
-          ${updateSnippet}
-        } else if (${windowSizeVec4Remainder === 2}) {
-          vec4 values = vec4(
-            getValue(batch, inIdx),
-            getValue(batch, inIdx + 1),
-            initializationValue,
-            initializationValue
-          );
-
-          vec4 segFilter = vec4(
-            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
-            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
-              0,
-              0
-          );
-
-          ${updateSnippet}
-        } else if (${windowSizeVec4Remainder === 3}) {
-          vec4 values = vec4(
-            getValue(batch, inIdx),
-            getValue(batch, inIdx + 1),
-            getValue(batch, inIdx + 2),
-            initializationValue
-          );
-
-          vec4 segFilter = vec4(
-            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
-            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
-            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
-            0
-          );
-
-          ${updateSnippet}
-        }
-        setOutput(${returnValue});
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=segment_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/select_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class select_gpu_SelectProgram {
-        constructor(cRank, shape, rank) {
-          this.variableNames = ["c", "a", "b"];
-          this.outputShape = shape;
-          let cCoords;
-          let abCoords;
-          if (rank > 4) {
-            throw Error(`Where for rank ${rank} is not yet supported`);
-          }
-          if (rank === 1) {
-            abCoords = `resRC`;
-            cCoords = `resRC`;
-          } else {
-            const currentCoords = ["resRC.x", "resRC.y", "resRC.z", "resRC.w"];
-            const cCoordVars = [];
-            const abCoordVars = [];
-            for (let i = 0; i < shape.length; i++) {
-              abCoordVars.push(`${currentCoords[i]}`);
-              if (i < cRank) {
-                cCoordVars.push(`${currentCoords[i]}`);
-              }
-            }
-            cCoords = cCoordVars.join();
-            abCoords = abCoordVars.join();
-          }
-          const dtype = getCoordsDataType(rank);
-          this.userCode = `
-      void main() {
-        ${dtype} resRC = getOutputCoords();
-        float cVal = getC(${cCoords});
-        if (cVal >= 1.0) {
-          setOutput(getA(${abCoords}));
-        } else {
-          setOutput(getB(${abCoords}));
-        }
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=select_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/slice_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class slice_gpu_SliceProgram {
-        constructor(destSize) {
-          this.variableNames = ["source"];
-          this.outputShape = destSize;
-          this.rank = destSize.length;
-          const dtype = getCoordsDataType(this.rank);
-          const uniformPart = `uniform int start[${this.rank}];`;
-          const sourceCoords = slice_gpu_getCoords(this.rank);
-          let body;
-          const coordSum = destSize.map((_, i) => {
-            return `sourceLoc.${slice_gpu_coords[i]} = start[${i}] + coords.${slice_gpu_coords[i]};`;
-          });
-          body = `
-        ${dtype} sourceLoc;
-        ${dtype} coords = getOutputCoords();
-        ${coordSum.join("\n")}
-      `;
-          this.userCode = `
-      ${uniformPart}
-      void main() {
-        ${body}
-        setOutput(getSource(${sourceCoords}));
-      }
-    `;
-        }
-        getCustomSetupFunc(start) {
-          if (start.length !== this.rank) {
-            throw Error(
-              `The rank (${this.rank}) of the program must match the ` +
-                `length of start (${start.length})`
-            );
-          }
-          return (gpgpu, webGLProgram) => {
-            if (this.startLoc == null) {
-              this.startLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "start");
-              if (this.startLoc == null) {
-                // This means the compiler has optimized and realized it doesn't need
-                // the uniform.
-                return;
-              }
-            }
-            gpgpu.gl.uniform1iv(this.startLoc, start);
-          };
-        }
-      }
-      const slice_gpu_coords = ["x", "y", "z", "w", "u", "v"];
-      function slice_gpu_getCoords(rank) {
-        if (rank === 1) {
-          return "sourceLoc";
-        } else if (rank <= 6) {
-          return slice_gpu_coords
-            .slice(0, rank)
-            .map((x) => "sourceLoc." + x)
-            .join(",");
-        } else {
-          throw Error(`Slicing for rank ${rank} is not yet supported`);
-        }
-      }
-      //# sourceMappingURL=slice_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/slice_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class slice_packed_gpu_SlicePackedProgram {
-        constructor(destSize) {
-          this.variableNames = ["source"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = destSize;
-          this.rank = destSize.length;
-          const dtype = getCoordsDataType(this.rank);
-          const coords = getChannels("coords", this.rank);
-          const sourceLoc = getChannels("sourceLoc", this.rank);
-          const innerDims = this.rank === 1 ? "sourceLoc" : `vec2(${sourceLoc.slice(-2).join()})`;
-          const getChannel = `getChannel(getSource(${sourceLoc.join()}), ${innerDims})`;
-          const upperRow = `
-      result.x = ${getChannel};
-      if (++${coords[this.rank - 1]} < ${destSize[this.rank - 1]}) {
-        ++${sourceLoc[this.rank - 1]};
-        result.y = ${getChannel};
-        --${sourceLoc[this.rank - 1]};
-      }
-    `;
-          const lowerRow =
-            this.rank === 1
-              ? ""
-              : `
-      --${coords[this.rank - 1]};
-      if (++${coords[this.rank - 2]} < ${destSize[this.rank - 2]}) {
-        ++${sourceLoc[this.rank - 2]};
-        result.z = ${getChannel};
-        if (++${coords[this.rank - 1]} < ${destSize[this.rank - 1]}) {
-          ++${sourceLoc[this.rank - 1]};
-          result.w = ${getChannel};
-        }
-      }
-    `;
-          const sourceLocSetup =
-            this.rank <= 4
-              ? `sourceLoc = coords +
-            ${dtype}(${destSize.map((_, i) => `start[${i}]`).join()});`
-              : destSize.map((_, i) => `${sourceLoc[i]} = ${coords[i]} + start[${i}];`).join("\n");
-          this.userCode = `
-      uniform int start[${this.rank}];
-      void main() {
-        ${dtype} coords = getOutputCoords();
-        ${dtype} sourceLoc;
-        ${sourceLocSetup}
-        vec4 result = vec4(0.);
-        ${upperRow}
-        ${lowerRow}
-        setOutput(result);
-      }
-    `;
-        }
-        getCustomSetupFunc(start) {
-          if (start.length !== this.rank) {
-            throw Error(
-              `The rank (${this.rank}) of the program must match the ` +
-                `length of start (${start.length})`
-            );
-          }
-          return (gpgpu, webGLProgram) => {
-            if (this.startLoc == null) {
-              this.startLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "start");
-              if (this.startLoc == null) {
-                // This means the compiler has optimized and realized it doesn't need
-                // the uniform.
-                return;
-              }
-            }
-            gpgpu.gl.uniform1iv(this.startLoc, start);
-          };
-        }
-      }
-      //# sourceMappingURL=slice_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/strided_slice_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class strided_slice_gpu_StridedSliceProgram {
-        constructor(begin, strides, size) {
-          this.variableNames = ["x"];
-          this.outputShape = size;
-          const rank = size.length;
-          const inputDtype = getCoordsDataType(size.length);
-          const dtype = getCoordsDataType(size.length);
-          let newCoords = "";
-          if (rank === 1) {
-            newCoords = "coords * strides + begin";
-          } else {
-            let outputAxis = 0;
-            newCoords = size
-              .map((_, i) => {
-                outputAxis++;
-                return size.length === 1
-                  ? `coords * strides[${i}] + begin[${i}]`
-                  : `coords[${outputAxis - 1}] * strides[${i}] + begin[${i}]`;
-              })
-              .join(",");
-          }
-          this.userCode = `
-      ${inputDtype} begin = ${inputDtype}(${begin});
-      ${inputDtype} strides = ${inputDtype}(${strides});
-
-      void main() {
-        ${dtype} coords = getOutputCoords();
-        setOutput(getX(${newCoords}));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=strided_slice_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/texture_manager.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class texture_manager_TextureManager {
-        constructor(gpgpu) {
-          this.gpgpu = gpgpu;
-          this.numUsedTextures = 0;
-          this.numFreeTextures = 0;
-          this.freeTextures = {};
-          this.logEnabled = false;
-          this.usedTextures = {};
-        }
-        acquireTexture(shapeRC, usage, isPacked) {
-          const physicalTexType = getPhysicalFromLogicalTextureType(usage, isPacked);
-          const shapeKey = getKeyFromTextureShape(shapeRC, physicalTexType, isPacked);
-          if (!(shapeKey in this.freeTextures)) {
-            this.freeTextures[shapeKey] = [];
-          }
-          if (!(shapeKey in this.usedTextures)) {
-            this.usedTextures[shapeKey] = [];
-          }
-          if (this.freeTextures[shapeKey].length > 0) {
-            this.numFreeTextures--;
-            this.numUsedTextures++;
-            this.log();
-            const newTexture = this.freeTextures[shapeKey].shift();
-            this.usedTextures[shapeKey].push(newTexture);
-            return newTexture;
-          }
-          this.numUsedTextures++;
-          this.log();
-          let newTexture;
-          if (physicalTexType === PhysicalTextureType.PACKED_2X2_FLOAT32) {
-            newTexture = this.gpgpu.createPackedMatrixTexture(shapeRC[0], shapeRC[1]);
-          } else if (physicalTexType === PhysicalTextureType.PACKED_2X2_FLOAT16) {
-            newTexture = this.gpgpu.createFloat16PackedMatrixTexture(shapeRC[0], shapeRC[1]);
-          } else if (physicalTexType === PhysicalTextureType.UNPACKED_FLOAT32) {
-            newTexture = this.gpgpu.createFloat32MatrixTexture(shapeRC[0], shapeRC[1]);
-          } else if (physicalTexType === PhysicalTextureType.UNPACKED_FLOAT16) {
-            newTexture = this.gpgpu.createFloat16MatrixTexture(shapeRC[0], shapeRC[1]);
-          } else if (physicalTexType === PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE) {
-            newTexture = this.gpgpu.createUnsignedBytesMatrixTexture(shapeRC[0], shapeRC[1]);
-          }
-          this.usedTextures[shapeKey].push(newTexture);
-          return newTexture;
-        }
-        releaseTexture(texture, shape, logicalTexType, isPacked) {
-          if (this.freeTextures == null) {
-            // Already disposed.
-            return;
-          }
-          const physicalTexType = getPhysicalFromLogicalTextureType(logicalTexType, isPacked);
-          const shapeKey = getKeyFromTextureShape(shape, physicalTexType, isPacked);
-          if (!(shapeKey in this.freeTextures)) {
-            this.freeTextures[shapeKey] = [];
-          }
-          this.freeTextures[shapeKey].push(texture);
-          this.numFreeTextures++;
-          this.numUsedTextures--;
-          const texList = this.usedTextures[shapeKey];
-          const texIndex = texList.indexOf(texture);
-          if (texIndex < 0) {
-            throw new Error(
-              "Cannot release a texture that was never provided by this " + "texture manager"
-            );
-          }
-          texList.splice(texIndex, 1);
-          this.log();
-        }
-        log() {
-          if (!this.logEnabled) {
-            return;
-          }
-          const total = this.numFreeTextures + this.numUsedTextures;
-          console.log(
-            "Free/Used",
-            `${this.numFreeTextures} / ${this.numUsedTextures}`,
-            `(${total})`
-          );
-        }
-        getNumUsedTextures() {
-          return this.numUsedTextures;
-        }
-        getNumFreeTextures() {
-          return this.numFreeTextures;
-        }
-        dispose() {
-          if (this.freeTextures == null) {
-            // Already disposed.
-            return;
-          }
-          for (const texShape in this.freeTextures) {
-            this.freeTextures[texShape].forEach((tex) => {
-              this.gpgpu.deleteMatrixTexture(tex);
-            });
-          }
-          for (const texShape in this.usedTextures) {
-            this.usedTextures[texShape].forEach((tex) => {
-              this.gpgpu.deleteMatrixTexture(tex);
-            });
-          }
-          this.freeTextures = null;
-          this.usedTextures = null;
-          this.numUsedTextures = 0;
-          this.numFreeTextures = 0;
-        }
-      }
-      function getPhysicalTextureForRendering(isPacked) {
-        if (Object(dist["env"])().getBool("WEBGL_RENDER_FLOAT32_ENABLED")) {
-          if (isPacked) {
-            return PhysicalTextureType.PACKED_2X2_FLOAT32;
-          }
-          return PhysicalTextureType.UNPACKED_FLOAT32;
-        }
-        if (isPacked) {
-          return PhysicalTextureType.PACKED_2X2_FLOAT16;
-        }
-        return PhysicalTextureType.UNPACKED_FLOAT16;
-      }
-      function getPhysicalFromLogicalTextureType(logicalTexType, isPacked) {
-        if (logicalTexType === TextureUsage.UPLOAD) {
-          return PhysicalTextureType.PACKED_2X2_FLOAT32;
-        } else if (logicalTexType === TextureUsage.RENDER || logicalTexType == null) {
-          return getPhysicalTextureForRendering(isPacked);
-        } else if (
-          logicalTexType === TextureUsage.DOWNLOAD ||
-          logicalTexType === TextureUsage.PIXELS
-        ) {
-          return PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE;
-        }
-        throw new Error(`Unknown logical texture type ${logicalTexType}`);
-      }
-      function getKeyFromTextureShape(shapeRowsCol, physicalTexType, isPacked) {
-        return `${shapeRowsCol[0]}_${shapeRowsCol[1]}_${physicalTexType}_${isPacked}`;
-      }
-      //# sourceMappingURL=texture_manager.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/tile_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class tile_gpu_TileProgram {
-        constructor(aShape, reps) {
-          this.variableNames = ["A"];
-          const outputShape = new Array(aShape.length);
-          for (let i = 0; i < outputShape.length; i++) {
-            outputShape[i] = aShape[i] * reps[i];
-          }
-          this.outputShape = outputShape;
-          this.rank = outputShape.length;
-          const dtype = getCoordsDataType(this.rank);
-          const sourceCoords = tile_gpu_getSourceCoords(aShape);
-          this.userCode = `
-      void main() {
-        ${dtype} resRC = getOutputCoords();
-        setOutput(getA(${sourceCoords}));
-      }
-    `;
-        }
-      }
-      function tile_gpu_getSourceCoords(aShape) {
-        const rank = aShape.length;
-        if (rank > 5) {
-          throw Error(`Tile for rank ${rank} is not yet supported`);
-        }
-        if (rank === 1) {
-          return `imod(resRC, ${aShape[0]})`;
-        }
-        const currentCoords = ["resRC.x", "resRC.y", "resRC.z", "resRC.w", "resRC.u"];
-        const sourceCoords = [];
-        for (let i = 0; i < aShape.length; i++) {
-          sourceCoords.push(`imod(${currentCoords[i]}, ${aShape[i]})`);
-        }
-        return sourceCoords.join();
-      }
-      //# sourceMappingURL=tile_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/unaryop_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class UnaryOpProgram {
-        constructor(aShape, opSnippet) {
-          this.variableNames = ["A"];
-          this.outputShape = aShape;
-          this.userCode = `
-      float unaryOperation(float x) {
-        ${opSnippet}
-      }
-
-      void main() {
-        float x = getAAtOutCoords();
-        float y = unaryOperation(x);
-
-        setOutput(y);
-      }
-    `;
-        }
-      }
-      const unaryop_gpu_CHECK_NAN_SNIPPET = `if (isnan(x)) return x;`;
-      const LINEAR = `return x;`;
-      const ABS = `return abs(x);`;
-      const RELU =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  return (x < 0.0) ? 0.0 : x;
-`;
-      const RELU6 =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  return (x < 0.0) ? 0.0 : min(6.0, x);
-`;
-      const ELU = `return (x >= 0.0) ? x : (exp(x) - 1.0);`;
-      const SELU = `
-  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
-  // see: https://arxiv.org/abs/1706.02515
-  float scaleAlpha = ${dist["backend_util"].SELU_SCALEALPHA};
-  float scale = ${dist["backend_util"].SELU_SCALE};
-  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`;
-      function STEP(alpha = 0.0) {
-        return (
-          unaryop_gpu_CHECK_NAN_SNIPPET +
-          `
-    return x > 0.0 ? 1.0 : float(${alpha});
-  `
-        );
-      }
-      const NEG = `return -x;`;
-      const CEIL = `return ceil(x);`;
-      const FLOOR = `return floor(x);`;
-      const SIGN = `
-  if (isnan(x)) { return 0.0; }
-  return sign(x);
-`;
-      const IS_NAN = `return float(isnan(x));`;
-      const IS_INF = `return float(isinf(x));`;
-      const IS_FINITE = `return float(!isnan(x) && !isinf(x));`;
-      const ROUND = `
-  // OpenGL ES does not support round function.
-  // The algorithm is based on banker's rounding.
-  float base = floor(x);
-  if ((x - base) < 0.5) {
-    return floor(x);
-  } else if ((x - base) > 0.5) {
-    return ceil(x);
-  } else {
-    if (mod(base, 2.0) == 0.0) {
-      return base;
-    } else {
-      return base + 1.0;
-    }
-  }
-`;
-      const EXP = `return exp(x);`;
-      const EXPM1 = `return exp(x) - 1.0;`;
-      const LOG = `if (x < 0.0) return NAN;
-  return log(x);`;
-      const LOG1P = `return log(1.0 + x);`;
-      const SQRT = `return sqrt(x);`;
-      const RSQRT = `return inversesqrt(x);`;
-      const SIGMOID = `return 1.0 / (1.0 + exp(-1.0 * x));`;
-      /**
-       * mirrors the implementation of tf.nn.softplus: https://goo.gl/vkcvwX
-       *
-       * epsilon is the difference between 1.0 and the next representable
-       * float. For a single precision 32 bit float this should be 2^-23, see:
-       * https://math.byu.edu/~schow/work/IEEEFloatingPoint.htm
-       *
-       * too_large = (x > -threshold) is value above which exp(x) may overflow
-       * but softplus(x) == x is within machine epsilon
-       *
-       * too_small = (x < threshold) is value below which exp(x) may underflow,
-       * but softplus(x) == exp(x) is within machine epsilon.
-       */
-      const SOFTPLUS = `
-  float epsilon = 1.1920928955078125e-7;
-  float threshold = log(epsilon) + 2.0;
-
-  bool too_large = x > -threshold;
-  bool too_small = x < threshold;
-
-  float result;
-  float exp_x = exp(x);
-
-  if (too_large){
-    result = x;
-  }
-  else if (too_small){
-    result = exp_x;
-  }
-  else{
-    result = log(exp_x + 1.0);
-  }
-  return result;
-`;
-      const SIN =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  return sin(x);
-`;
-      const COS =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  return cos(x);
-`;
-      const TAN = `return tan(x);`;
-      const ASIN =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  if (abs(x) > 1.) {
-    return NAN;
-  }
-  return asin(x);
-`;
-      const ACOS =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  if (abs(x) > 1.) {
-    return NAN;
-  }
-  return acos(x);
-`;
-      const ATAN =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  return atan(x);
-`;
-      const SINH = `
-  float e2x = exp(x);
-  return (e2x - 1.0 / e2x) / 2.0;
-`;
-      const COSH = `
-  float e2x = exp(-x);
-  return (e2x + 1.0 / e2x) / 2.0;
-`;
-      const TANH = `
-  float e2x = exp(-2.0 * abs(x));
-  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
-`;
-      const ASINH = unaryop_gpu_CHECK_NAN_SNIPPET + `return log(x + sqrt(x * x + 1.0));`;
-      const ACOSH =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  if (x < 1.0) return NAN;
-  return log(x + sqrt(x * x - 1.0));`;
-      const ATANH =
-        unaryop_gpu_CHECK_NAN_SNIPPET +
-        `
-  if ((x < -1.0) || (x > 1.0)) return NAN;
-  return (log(1.0 + x) - log(1.0 - x)) / 2.0;`;
-      const ERF = `
-  // Error function is calculated approximately with elementary function.
-  // See "Handbook of Mathematical Functions with Formulas,
-  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
-  float p = ${dist["backend_util"].ERF_P};
-  float a1 = ${dist["backend_util"].ERF_A1};
-  float a2 = ${dist["backend_util"].ERF_A2};
-  float a3 = ${dist["backend_util"].ERF_A3};
-  float a4 = ${dist["backend_util"].ERF_A4};
-  float a5 = ${dist["backend_util"].ERF_A5};
-
-  float sign = sign(x);
-  x = abs(x);
-  float t = 1.0 / (1.0 + p * x);
-  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
-`;
-      const SQUARE = `return x * x;`;
-      const RECIPROCAL = `return 1.0 / x;`;
-      const LOGICAL_NOT = `return float(!(x >= 1.0));`;
-      const TO_INT = `return float(int(x));`;
-      const CLONE = "return x;";
-      //# sourceMappingURL=unaryop_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/unaryop_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      const unaryop_packed_gpu_LINEAR = `return x;`;
-      const unaryop_packed_gpu_LOG = `
-  vec4 result = log(x);
-  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
-  result.r = isNaN.r == 1.0 ? NAN : result.r;
-  result.g = isNaN.g == 1.0 ? NAN : result.g;
-  result.b = isNaN.b == 1.0 ? NAN : result.b;
-  result.a = isNaN.a == 1.0 ? NAN : result.a;
-
-  return result;
-`;
-      const unaryop_packed_gpu_RELU = `
-  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
-  bvec4 isNaN = isnan(x);
-
-  result.r = isNaN.r ? x.r : result.r;
-  result.g = isNaN.g ? x.g : result.g;
-  result.b = isNaN.b ? x.b : result.b;
-  result.a = isNaN.a ? x.a : result.a;
-
-  return result;
-`;
-      const unaryop_packed_gpu_RELU6 = `
-  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
-  bvec4 isNaN = isnan(x);
-
-  result.r = isNaN.r ? x.r : result.r;
-  result.g = isNaN.g ? x.g : result.g;
-  result.b = isNaN.b ? x.b : result.b;
-  result.a = isNaN.a ? x.a : result.a;
-
-  return result;
-`;
-      const unaryop_packed_gpu_ELU = `
-  vec4 result;
-
-  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
-  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
-  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
-  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
-
-  return result;
-`;
-      class UnaryOpPackedProgram {
-        constructor(aShape, opSnippet) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          this.outputShape = aShape;
-          this.userCode = `
-      vec4 unaryOperation(vec4 x) {
-        ${opSnippet}
-      }
-
-      void main() {
-        vec4 x = getAAtOutCoords();
-        vec4 y = unaryOperation(x);
-
-        setOutput(y);
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=unaryop_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/unpack_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class unpack_gpu_UnpackProgram {
-        constructor(outputShape) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = false;
-          this.outputShape = outputShape;
-          const rank = outputShape.length;
-          const channels = getChannels("rc", rank);
-          const dtype = getCoordsDataType(rank);
-          const sourceCoords = getSourceCoords(rank, channels);
-          const innerDims = channels.slice(-2);
-          const coords = rank <= 1 ? "rc" : `vec2(${innerDims.join(",")})`;
-          this.userCode = `
-      void main() {
-        ${dtype} rc = getOutputCoords();
-        vec4 packedInput = getA(${sourceCoords});
-
-        setOutput(getChannel(packedInput, ${coords}));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=unpack_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/backend_webgl.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // Import webgl flags.
-
-      const { segment_util } = dist["backend_util"];
-      const split = dist["kernel_impls"].split;
-      const tile = dist["kernel_impls"].tile;
-      const topkImpl = dist["kernel_impls"].topkImpl;
-      const whereImpl = dist["kernel_impls"].whereImpl;
-
-      const EPSILON_FLOAT32 = 1e-7;
-      const EPSILON_FLOAT16 = 1e-4;
-      const binaryCaches = {};
-      function getBinaryCache(webGLVersion) {
-        if (webGLVersion in binaryCaches) {
-          return binaryCaches[webGLVersion];
-        }
-        binaryCaches[webGLVersion] = {};
-        return binaryCaches[webGLVersion];
-      }
-      function mapActivationToShaderProgram(activation, packed = false) {
-        if (activation === "linear") {
-          if (packed) {
-            return unaryop_packed_gpu_LINEAR;
-          }
-          return LINEAR;
-        } else if (activation === "relu") {
-          if (packed) {
-            return unaryop_packed_gpu_RELU;
-          }
-          return RELU;
-        } else if (activation === "elu") {
-          if (packed) {
-            return unaryop_packed_gpu_ELU;
-          }
-          return ELU;
-        } else if (activation === "relu6") {
-          if (packed) {
-            return unaryop_packed_gpu_RELU6;
-          }
-          return RELU6;
-        } else if (activation === "prelu") {
-          if (packed) {
-            return binaryop_packed_gpu_PRELU;
-          }
-          return PRELU;
-        }
-        throw new Error(`Activation ${activation} has not been implemented for the WebGL backend.`);
-      }
-      // Empirically determined constant used to determine size threshold for handing
-      // off execution to the CPU.
-      const CPU_HANDOFF_SIZE_THRESHOLD = 128;
-      // Empirically determined constant used to decide the number of MB on GPU
-      // before we warn about high memory use. The MB are this constant * screen area
-      // * dpi / 1024 / 1024.
-      const BEFORE_PAGING_CONSTANT = 600;
-      function numMBBeforeWarning() {
-        if (Object(dist["env"])().global.screen == null) {
-          return 1024; // 1 GB.
-        }
-        return (
-          (Object(dist["env"])().global.screen.height *
-            Object(dist["env"])().global.screen.width *
-            window.devicePixelRatio *
-            BEFORE_PAGING_CONSTANT) /
-          1024 /
-          1024
-        );
-      }
-      // Empirically determined minimal shared dimension in matmul before we forward
-      // to a.mul(b).sum() in order to take advantage of GPU parallelism. See
-      // https://github.com/tensorflow/tfjs-core/pull/1379 for benchmarks.
-      const MATMUL_SHARED_DIM_THRESHOLD = 1000;
-      class backend_webgl_MathBackendWebGL extends dist["KernelBackend"] {
-        constructor(gpgpu) {
-          super();
-          // Maps data ids that have a pending read operation, to list of subscribers.
-          this.pendingRead = new WeakMap();
-          // List of data ids that are scheduled for disposal, but are waiting on a
-          // pending read operation.
-          this.pendingDisposal = new WeakSet();
-          // Used to count the number of 'shallow' sliced tensors that point to the
-          // same data id.
-          this.dataRefCount = new WeakMap();
-          this.numBytesInGPU = 0;
-          // Accumulated time spent (including blocking) in uploading data to webgl.
-          this.uploadWaitMs = 0;
-          // Accumulated time spent (including blocking in downloading data from webgl.
-          this.downloadWaitMs = 0;
-          this.warnedAboutMemory = false;
-          this.pendingDeletes = 0;
-          this.disposed = false;
-          if (!Object(dist["env"])().getBool("HAS_WEBGL")) {
-            throw new Error("WebGL is not supported on this device");
-          }
-          if (gpgpu == null) {
-            const gl = getWebGLContext(Object(dist["env"])().getNumber("WEBGL_VERSION"));
-            this.binaryCache = getBinaryCache(Object(dist["env"])().getNumber("WEBGL_VERSION"));
-            this.gpgpu = new gpgpu_context_GPGPUContext(gl);
-            this.canvas = gl.canvas;
-            this.gpgpuCreatedLocally = true;
-          } else {
-            this.gpgpu = gpgpu;
-            this.binaryCache = {};
-            this.gpgpuCreatedLocally = false;
-            this.canvas = gpgpu.gl.canvas;
-          }
-          this.textureManager = new texture_manager_TextureManager(this.gpgpu);
-          this.numMBBeforeWarning = numMBBeforeWarning();
-          this.texData = new dist["DataStorage"](this, Object(dist["engine"])());
-        }
-        numDataIds() {
-          return (
-            this.texData.numDataIds() +
-            (this.cpuBackend ? this.cpuBackend.numDataIds() : 0) -
-            this.pendingDeletes
-          );
-        }
-        write(values, shape, dtype) {
-          if (Object(dist["env"])().getBool("DEBUG")) {
-            this.checkNumericalProblems(values);
-          }
-          if (dtype === "complex64" && values != null) {
-            throw new Error(
-              `Cannot write to a complex64 dtype. ` + `Please use tf.complex(real, imag).`
-            );
-          }
-          const dataId = {};
-          this.texData.set(dataId, { shape, dtype, values, usage: TextureUsage.UPLOAD });
-          return dataId;
-        }
-        move(dataId, values, shape, dtype) {
-          if (Object(dist["env"])().getBool("DEBUG")) {
-            this.checkNumericalProblems(values);
-          }
-          if (dtype === "complex64") {
-            throw new Error(
-              `Cannot write to a complex64 dtype. ` + `Please use tf.complex(real, imag).`
-            );
-          }
-          this.texData.set(dataId, { shape, dtype, values, usage: TextureUsage.UPLOAD });
-        }
-        readSync(dataId) {
-          const texData = this.texData.get(dataId);
-          const { values, dtype, complexTensors, slice, shape, isPacked } = texData;
-          if (slice != null) {
-            let program;
-            if (isPacked) {
-              program = new UnaryOpPackedProgram(shape, CLONE);
-            } else {
-              program = new UnaryOpProgram(shape, CLONE);
-            }
-            const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);
-            const data = this.readSync(res.dataId);
-            this.disposeData(res.dataId);
-            return data;
-          }
-          if (values != null) {
-            return this.convertAndCacheOnCPU(dataId);
-          }
-          if (dtype === "string") {
-            return values;
-          }
-          const shouldTimeProgram = this.activeTimers != null;
-          let start;
-          if (shouldTimeProgram) {
-            start = dist["util"].now();
-          }
-          let result;
-          if (dtype === "complex64") {
-            const realValues = complexTensors.real.dataSync();
-            const imagValues = complexTensors.imag.dataSync();
-            result = dist["backend_util"].mergeRealAndImagArrays(realValues, imagValues);
-          } else {
-            result = this.getValuesFromTexture(dataId);
-          }
-          if (shouldTimeProgram) {
-            this.downloadWaitMs += dist["util"].now() - start;
-          }
-          return this.convertAndCacheOnCPU(dataId, result);
-        }
-        async read(dataId) {
-          if (this.pendingRead.has(dataId)) {
-            const subscribers = this.pendingRead.get(dataId);
-            return new Promise((resolve) => subscribers.push(resolve));
-          }
-          const texData = this.texData.get(dataId);
-          const { values, shape, slice, dtype, complexTensors, isPacked } = texData;
-          if (slice != null) {
-            let program;
-            if (isPacked) {
-              program = new UnaryOpPackedProgram(shape, CLONE);
-            } else {
-              program = new UnaryOpProgram(shape, CLONE);
-            }
-            const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);
-            const data = this.read(res.dataId);
-            this.disposeData(res.dataId);
-            return data;
-          }
-          if (values != null) {
-            return this.convertAndCacheOnCPU(dataId);
-          }
-          if (
-            !Object(dist["env"])().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED") &&
-            Object(dist["env"])().getNumber("WEBGL_VERSION") === 2
-          ) {
-            throw new Error(
-              `tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and ` +
-                `WEBGL_VERSION=2 not yet supported.`
-            );
-          }
-          let buffer = null;
-          let tmpDownloadTarget;
-          if (dtype !== "complex64" && Object(dist["env"])().get("WEBGL_BUFFER_SUPPORTED")) {
-            // Possibly copy the texture into a buffer before inserting a fence.
-            tmpDownloadTarget = this.decode(dataId);
-            const tmpData = this.texData.get(tmpDownloadTarget.dataId);
-            buffer = this.gpgpu.createBufferFromTexture(
-              tmpData.texture,
-              ...getDenseTexShape(shape)
-            );
-          }
-          this.pendingRead.set(dataId, []);
-          if (dtype !== "complex64") {
-            // Create a fence and wait for it to resolve.
-            await this.gpgpu.createAndWaitForFence();
-          }
-          // Download the values from the GPU.
-          let vals;
-          if (dtype === "complex64") {
-            const ps = await Promise.all([complexTensors.real.data(), complexTensors.imag.data()]);
-            const realValues = ps[0];
-            const imagValues = ps[1];
-            vals = dist["backend_util"].mergeRealAndImagArrays(realValues, imagValues);
-          } else if (buffer == null) {
-            vals = this.getValuesFromTexture(dataId);
-          } else {
-            const size = dist["util"].sizeFromShape(shape);
-            vals = this.gpgpu.downloadFloat32MatrixFromBuffer(buffer, size);
-          }
-          if (tmpDownloadTarget != null) {
-            this.disposeData(tmpDownloadTarget.dataId);
-          }
-          const dTypeVals = this.convertAndCacheOnCPU(dataId, vals);
-          const subscribers = this.pendingRead.get(dataId);
-          this.pendingRead.delete(dataId);
-          // Notify all pending reads.
-          subscribers.forEach((resolve) => resolve(dTypeVals));
-          if (this.pendingDisposal.has(dataId)) {
-            this.pendingDisposal.delete(dataId);
-            this.disposeData(dataId);
-            this.pendingDeletes--;
-          }
-          return dTypeVals;
-        }
-        checkNumericalProblems(values) {
-          if (values == null) {
-            return;
-          }
-          for (let i = 0; i < values.length; i++) {
-            const num = values[i];
-            if (!canBeRepresented(num)) {
-              if (Object(dist["env"])().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")) {
-                throw Error(
-                  `The value ${num} cannot be represented with your ` +
-                    `current settings. Consider enabling float32 rendering: ` +
-                    `'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`
-                );
-              }
-              throw Error(`The value ${num} cannot be represented on this device.`);
-            }
-          }
-        }
-        getValuesFromTexture(dataId) {
-          const { shape, dtype, isPacked } = this.texData.get(dataId);
-          const size = dist["util"].sizeFromShape(shape);
-          if (Object(dist["env"])().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")) {
-            const tmpTarget = this.decode(dataId);
-            const tmpData = this.texData.get(tmpTarget.dataId);
-            const vals = this.gpgpu
-              .downloadMatrixFromPackedTexture(tmpData.texture, ...getDenseTexShape(shape))
-              .subarray(0, size);
-            this.disposeData(tmpTarget.dataId);
-            return vals;
-          }
-          const shouldUsePackedProgram =
-            Object(dist["env"])().getBool("WEBGL_PACK") && isPacked === true;
-          const outputShape = shouldUsePackedProgram ? getShapeAs3D(shape) : shape;
-          const program = shouldUsePackedProgram
-            ? new encode_float_packed_gpu_EncodeFloatPackedProgram(outputShape)
-            : new encode_float_gpu_EncodeFloatProgram(outputShape);
-          const output = this.runWebGLProgram(
-            program,
-            [{ shape: outputShape, dtype, dataId }],
-            "float32"
-          );
-          const tmpData = this.texData.get(output.dataId);
-          const vals = this.gpgpu
-            .downloadByteEncodedFloatMatrixFromOutputTexture(
-              tmpData.texture,
-              tmpData.texShape[0],
-              tmpData.texShape[1]
-            )
-            .subarray(0, size);
-          this.disposeData(output.dataId);
-          return vals;
-        }
-        async time(f) {
-          const oldActiveTimers = this.activeTimers;
-          const newActiveTimers = [];
-          let outerMostTime = false;
-          if (this.programTimersStack == null) {
-            this.programTimersStack = newActiveTimers;
-            outerMostTime = true;
-          } else {
-            this.activeTimers.push(newActiveTimers);
-          }
-          this.activeTimers = newActiveTimers;
-          f();
-          // needing to split these up because util.flatten only accepts certain types
-          const flattenedActiveTimerQueries = dist["util"]
-            .flatten(this.activeTimers.map((d) => d.query))
-            .filter((d) => d != null);
-          const flattenedActiveTimerNames = dist["util"]
-            .flatten(this.activeTimers.map((d) => d.name))
-            .filter((d) => d != null);
-          this.activeTimers = oldActiveTimers;
-          if (outerMostTime) {
-            this.programTimersStack = null;
-          }
-          const res = {
-            uploadWaitMs: this.uploadWaitMs,
-            downloadWaitMs: this.downloadWaitMs,
-            kernelMs: null,
-            wallMs: null, // will be filled by the engine
-          };
-          if (
-            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0
-          ) {
-            const kernelMs = await Promise.all(flattenedActiveTimerQueries);
-            res["kernelMs"] = dist["util"].sum(kernelMs);
-            res["getExtraProfileInfo"] = () =>
-              kernelMs
-                .map((d, i) => ({ name: flattenedActiveTimerNames[i], ms: d }))
-                .map((d) => `${d.name}: ${d.ms}`)
-                .join(", ");
-          } else {
-            res["kernelMs"] = {
-              error: "WebGL query timers are not supported in this environment.",
-            };
-          }
-          this.uploadWaitMs = 0;
-          this.downloadWaitMs = 0;
-          return res;
-        }
-        memory() {
-          return { unreliable: false, numBytesInGPU: this.numBytesInGPU };
-        }
-        startTimer() {
-          if (
-            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0
-          ) {
-            return this.gpgpu.beginQuery();
-          }
-          return { startMs: dist["util"].now(), endMs: null };
-        }
-        endTimer(query) {
-          if (
-            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0
-          ) {
-            this.gpgpu.endQuery();
-            return query;
-          }
-          query.endMs = dist["util"].now();
-          return query;
-        }
-        async getQueryTime(query) {
-          if (
-            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0
-          ) {
-            return this.gpgpu.waitForQueryAndGetTime(query);
-          }
-          const timerQuery = query;
-          return timerQuery.endMs - timerQuery.startMs;
-        }
-        disposeData(dataId) {
-          if (this.pendingDisposal.has(dataId)) {
-            return;
-          }
-          if (this.pendingRead.has(dataId)) {
-            this.pendingDisposal.add(dataId);
-            this.pendingDeletes++;
-            return;
-          }
-          // No-op if already disposed.
-          if (!this.texData.has(dataId)) {
-            return;
-          }
-          this.releaseGPUData(dataId);
-          const { complexTensors } = this.texData.get(dataId);
-          if (complexTensors != null) {
-            complexTensors.real.dispose();
-            complexTensors.imag.dispose();
-          }
-          this.texData.delete(dataId);
-        }
-        releaseGPUData(dataId) {
-          const { texture, dtype, texShape, usage, isPacked, slice } = this.texData.get(dataId);
-          const key = (slice && slice.origDataId) || dataId;
-          const refCount = this.dataRefCount.get(key);
-          if (refCount > 1) {
-            this.dataRefCount.set(key, refCount - 1);
-          } else {
-            this.dataRefCount.delete(key);
-            if (texture != null) {
-              this.numBytesInGPU -= this.computeBytes(texShape, dtype);
-              this.textureManager.releaseTexture(texture, texShape, usage, isPacked);
-            }
-          }
-          const texData = this.texData.get(dataId);
-          texData.texture = null;
-          texData.texShape = null;
-          texData.isPacked = false;
-          texData.slice = null;
-        }
-        getTexture(dataId) {
-          this.uploadToGPU(dataId);
-          return this.texData.get(dataId).texture;
-        }
-        /**
-         * Returns internal information for the specific data bucket. Used in unit
-         * tests.
-         */
-        getDataInfo(dataId) {
-          return this.texData.get(dataId);
-        }
-        getCPUBackend() {
-          if (!Object(dist["env"])().getBool("WEBGL_CPU_FORWARD")) {
-            return null;
-          }
-          if (this.cpuBackend == null) {
-            this.cpuBackend = Object(dist["engine"])().findBackend("cpu");
-          }
-          return this.cpuBackend;
-        }
-        /*
-    Tests whether all the inputs to an op are small and on the CPU. This heuristic
-    determines when it would be faster to execute a kernel on the CPU. WebGL
-    kernels opt into running this check and forwarding when appropriate.
-    TODO(https://github.com/tensorflow/tfjs/issues/872): Develop a more
-    sustainable strategy for optimizing backend execution of ops.
-     */
-        shouldExecuteOnCPU(inputs, sizeThreshold = CPU_HANDOFF_SIZE_THRESHOLD) {
-          return (
-            this.getCPUBackend() != null &&
-            inputs.every(
-              (input) =>
-                this.texData.get(input.dataId).texture == null &&
-                dist["util"].sizeFromShape(input.shape) < sizeThreshold
-            )
-          );
-        }
-        getGPGPUContext() {
-          return this.gpgpu;
-        }
-        complex(real, imag) {
-          const result = this.makeOutput(real.shape, "complex64");
-          const resultData = this.texData.get(result.dataId);
-          // The backend owns the reference to the underlying real and imaginary
-          // clones. These will explicitly get disposed when the complex tensor is
-          // disposed.
-          resultData.complexTensors = {
-            real: Object(dist["engine"])().keep(real.clone()),
-            imag: Object(dist["engine"])().keep(imag.clone()),
-          };
-          return result;
-        }
-        real(input) {
-          const resultData = this.texData.get(input.dataId);
-          return resultData.complexTensors.real.clone();
-        }
-        imag(input) {
-          const resultData = this.texData.get(input.dataId);
-          return resultData.complexTensors.imag.clone();
-        }
-        slice(x, begin, size) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.slice(x, begin, size);
-          }
-          // Short-circuit computation if the slice is zero-sized.
-          if (dist["util"].sizeFromShape(size) === 0) {
-            return Object(dist["tensor"])([], size, x.dtype);
-          }
-          const { isPacked } = this.texData.get(x.dataId);
-          const isContinous = dist["slice_util"].isSliceContinous(x.shape, begin, size);
-          if (isPacked || !isContinous) {
-            const program = Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS")
-              ? new slice_packed_gpu_SlicePackedProgram(size)
-              : new slice_gpu_SliceProgram(size);
-            const customSetup = program.getCustomSetupFunc(begin);
-            return this.compileAndRun(program, [x], null, customSetup);
-          }
-          this.uploadToGPU(x.dataId);
-          return this.shallowSlice(x, begin, size);
-        }
-        shallowSlice(x, begin, size) {
-          const xTexData = this.texData.get(x.dataId);
-          const t = this.makeOutput(size, x.dtype);
-          const newTexData = this.texData.get(t.dataId);
-          // Copy texture data from the original tensor.
-          Object.assign(newTexData, xTexData);
-          newTexData.shape = size;
-          newTexData.dtype = x.dtype;
-          let flatOffset = dist["slice_util"].computeFlatOffset(begin, x.strides);
-          if (xTexData.slice) {
-            // We are slicing an already sliced tensor, so we have to accumulate
-            // the offset.
-            flatOffset += xTexData.slice.flatOffset;
-          }
-          newTexData.slice = {
-            flatOffset,
-            // Point to the original dataId, which is used to do ref counting.
-            origDataId: (xTexData.slice && xTexData.slice.origDataId) || x.dataId,
-          };
-          // Increase the ref count for that data bucket.
-          const refCount = this.dataRefCount.get(newTexData.slice.origDataId) || 1;
-          this.dataRefCount.set(newTexData.slice.origDataId, refCount + 1);
-          return t;
-        }
-        stridedSlice(x, begin, end, strides) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.stridedSlice(x, begin, end, strides);
-          }
-          const outShape = dist["slice_util"].computeOutShape(begin, end, strides);
-          if (outShape.some((axis) => axis === 0)) {
-            return Object(dist["tensor"])([], outShape);
-          }
-          const program = new strided_slice_gpu_StridedSliceProgram(begin, strides, outShape);
-          return this.compileAndRun(program, [x]);
-        }
-        reverse(x, axis) {
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS")
-            ? new reverse_packed_gpu_ReversePackedProgram(x.shape, axis)
-            : new reverse_gpu_ReverseProgram(x.shape, axis);
-          return this.compileAndRun(program, [x]);
-        }
-        concat(tensors, axis) {
-          if (tensors[0].dtype === "complex64") {
-            const reals = tensors.map((t) => Object(dist["real"])(t));
-            const imags = tensors.map((t) => Object(dist["imag"])(t));
-            return Object(dist["complex"])(this.concat(reals, axis), this.concat(imags, axis));
-          }
-          if (this.shouldExecuteOnCPU(tensors)) {
-            return this.cpuBackend.concat(tensors, axis);
-          }
-          if (tensors.length === 1) {
-            return tensors[0];
-          }
-          if (tensors.length > Object(dist["env"])().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")) {
-            const midIndex = Math.floor(tensors.length / 2);
-            const leftSide = this.concat(tensors.slice(0, midIndex), axis);
-            const rightSide = this.concat(tensors.slice(midIndex), axis);
-            return this.concat([leftSide, rightSide], axis);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS") && tensors[0].rank > 1) {
-            const program = new concat_packed_gpu_ConcatPackedProgram(
-              tensors.map((t) => t.shape),
-              axis
-            );
-            return this.compileAndRun(program, tensors);
-          }
-          // Any concat of n-dimensional tensors across any axis can be reduced to
-          // a concatenation of two-dimensional tensors across the axis 1 by first
-          // partitioning the axes of the original tensors into those less than the
-          // axis to be concatenated and the rest. Then reshape the tensors
-          // into a two-dimensional tensor by collapsing these two sets of axes and
-          // concatenate the resulting matrices across the axis 1, finally reshaping
-          // the result to have the proper shape.
-          const outShape = dist["backend_util"].computeOutShape(
-            tensors.map((t) => t.shape),
-            axis
-          );
-          const tensors2D = tensors.map((t) =>
-            t.as2D(-1, dist["util"].sizeFromShape(t.shape.slice(axis)))
-          );
-          const program = new concat_gpu_ConcatProgram(tensors2D.map((t) => t.shape));
-          const res = this.compileAndRun(program, tensors2D);
-          return res.reshape(outShape);
-        }
-        neg(x) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.neg(x);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
-            return this.packedUnaryOp(x, NEG, x.dtype);
-          }
-          const program = new UnaryOpProgram(x.shape, NEG);
-          return this.compileAndRun(program, [x]);
-        }
-        batchMatMul(a, b, transposeA, transposeB) {
-          const outerShapeA = transposeA ? a.shape[2] : a.shape[1];
-          const outerShapeB = transposeB ? b.shape[1] : b.shape[2];
-          const sharedDim = transposeA ? a.shape[1] : a.shape[2];
-          const [batch, ,] = a.shape;
-          // Since the matrices are vectors, it is faster to call mul().sum()
-          // because sum() is O(sqrt(N)) due to divide-and-conquer.
-          if ((outerShapeA === 1 || outerShapeB === 1) && sharedDim > MATMUL_SHARED_DIM_THRESHOLD) {
-            if (transposeA) {
-              a = Object(dist["transpose"])(a, [0, 2, 1]);
-            }
-            if (transposeB) {
-              b = Object(dist["transpose"])(b, [0, 2, 1]);
-            }
-            const a3D = outerShapeB === 1 ? a : a.as3D(batch, sharedDim, 1);
-            const axis = outerShapeB === 1 ? 2 : 1;
-            const b3D = outerShapeB === 1 ? b.as3D(batch, 1, sharedDim) : b;
-            return this.multiply(a3D, b3D).sum(axis, true /* keepDims */);
-          }
-          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
-          const program = new MatMulPackedProgram(
-            a.shape,
-            [batch, outerShapeA, outerShapeB],
-            transposeA,
-            transposeB
-          );
-          return this.compileAndRun(program, [a, b], dtype);
-        }
-        fusedBatchMatMul({
-          a,
-          b,
-          transposeA,
-          transposeB,
-          bias,
-          activation,
-          preluActivationWeights,
-        }) {
-          const outerShapeA = transposeA ? a.shape[2] : a.shape[1];
-          const outerShapeB = transposeB ? b.shape[1] : b.shape[2];
-          const [batch, ,] = a.shape;
-          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
-          const hasBias = bias != null;
-          const hasPreluActivationWeights = preluActivationWeights != null;
-          const fusedActivation = activation
-            ? mapActivationToShaderProgram(activation, true)
-            : null;
-          const program = new MatMulPackedProgram(
-            a.shape,
-            [batch, outerShapeA, outerShapeB],
-            transposeA,
-            transposeB,
-            hasBias,
-            fusedActivation,
-            hasPreluActivationWeights
-          );
-          const inputs = [a, b];
-          if (bias) {
-            inputs.push(bias);
-          }
-          if (preluActivationWeights) {
-            inputs.push(preluActivationWeights);
-          }
-          return this.compileAndRun(program, inputs, dtype);
-        }
-        multiply(a, b) {
-          if (a.dtype === "complex64") {
-            const aData = this.texData.get(a.dataId);
-            const bData = this.texData.get(b.dataId);
-            const realProgram = new binaryop_complex_gpu_BinaryOpComplexProgram(
-              COMPLEX_MULTIPLY.REAL,
-              a.shape,
-              b.shape
-            );
-            const imagProgram = new binaryop_complex_gpu_BinaryOpComplexProgram(
-              COMPLEX_MULTIPLY.IMAG,
-              a.shape,
-              b.shape
-            );
-            const inputs = [
-              this.makeComplexComponentTensorInfo(a, aData.complexTensors.real),
-              this.makeComplexComponentTensorInfo(a, aData.complexTensors.imag),
-              this.makeComplexComponentTensorInfo(b, bData.complexTensors.real),
-              this.makeComplexComponentTensorInfo(b, bData.complexTensors.imag),
-            ];
-            const real = this.compileAndRun(realProgram, inputs);
-            const imag = this.compileAndRun(imagProgram, inputs);
-            const complex = this.complex(real, imag);
-            real.dispose();
-            imag.dispose();
-            return complex;
-          }
-          if (this.shouldExecuteOnCPU([a, b])) {
-            return this.cpuBackend.multiply(a, b);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, MUL, a.dtype);
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(MUL, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], a.dtype);
-        }
-        batchNorm(x, mean, variance, offset, scale, varianceEpsilon) {
-          const inputs = [x, mean, variance];
-          let offsetShape = null;
-          if (offset != null) {
-            offsetShape = offset.shape;
-            inputs.push(offset);
-          }
-          let scaleShape = null;
-          if (scale != null) {
-            scaleShape = scale.shape;
-            inputs.push(scale);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_NORMALIZATION")) {
-            const batchNormPackedProgram = new batchnorm_packed_gpu_BatchNormPackedProgram(
-              x.shape,
-              mean.shape,
-              variance.shape,
-              offsetShape,
-              scaleShape,
-              varianceEpsilon
-            );
-            return this.compileAndRun(batchNormPackedProgram, inputs);
-          }
-          const batchNormProgram = new batchnorm_gpu_BatchNormProgram(
-            x.shape,
-            mean.shape,
-            variance.shape,
-            offsetShape,
-            scaleShape,
-            varianceEpsilon
-          );
-          return this.compileAndRun(batchNormProgram, inputs);
-        }
-        localResponseNormalization4D(x, radius, bias, alpha, beta) {
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_NORMALIZATION")
-            ? new LRNPackedProgram(x.shape, radius, bias, alpha, beta)
-            : new LRNProgram(x.shape, radius, bias, alpha, beta);
-          return this.compileAndRun(program, [x]);
-        }
-        LRNGrad(dy, inputImage, outputImage, depthRadius, bias, alpha, beta) {
-          const program = new LRNGradProgram(inputImage.shape, depthRadius, bias, alpha, beta);
-          return this.compileAndRun(program, [inputImage, outputImage, dy]);
-        }
-        tile(x, reps) {
-          if (x.dtype === "string") {
-            const data = this.readSync(x.dataId);
-            const decodedData = data.map((d) => dist["util"].decodeString(d));
-            const buf = Object(dist["buffer"])(x.shape, x.dtype, decodedData);
-            return tile(buf, reps);
-          }
-          const program = new tile_gpu_TileProgram(x.shape, reps);
-          return this.compileAndRun(program, [x]);
-        }
-        pad(x, paddings, constantValue) {
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS")
-            ? new pad_packed_gpu_PadPackedProgram(x.shape, paddings, constantValue)
-            : new pad_gpu_PadProgram(x.shape, paddings, constantValue);
-          return this.compileAndRun(program, [x]);
-        }
-        gather(x, indices, axis) {
-          if (this.shouldExecuteOnCPU([x, indices])) {
-            return this.cpuBackend.gather(x, indices, axis);
-          }
-          const program = new gather_gpu_GatherProgram(x.shape, indices.size, axis);
-          return this.compileAndRun(program, [x, indices]);
-        }
-        batchToSpaceND(x, blockShape, crops) {
-          dist["util"].assert(
-            x.rank <= 4,
-            () => "batchToSpaceND for rank > 4 with a WebGL backend not " + "implemented yet"
-          );
-          const prod = blockShape.reduce((a, b) => a * b);
-          const reshaped = dist["backend_util"].getReshaped(x.shape, blockShape, prod);
-          const permuted = dist["backend_util"].getPermuted(reshaped.length, blockShape.length);
-          const reshapedPermuted = dist["backend_util"].getReshapedPermuted(
-            x.shape,
-            blockShape,
-            prod
-          );
-          const sliceBeginCoords = dist["backend_util"].getSliceBeginCoords(
-            crops,
-            blockShape.length
-          );
-          const sliceSize = dist["backend_util"].getSliceSize(
-            reshapedPermuted,
-            crops,
-            blockShape.length
-          );
-          return Object(dist["transpose"])(x.reshape(reshaped), permuted)
-            .reshape(reshapedPermuted)
-            .slice(sliceBeginCoords, sliceSize);
-        }
-        spaceToBatchND(x, blockShape, paddings) {
-          dist["util"].assert(
-            x.rank <= 4,
-            () => "spaceToBatchND for rank > 4 with a WebGL backend not " + "implemented yet"
-          );
-          const prod = blockShape.reduce((a, b) => a * b);
-          const completePaddings = [[0, 0]];
-          completePaddings.push(...paddings);
-          for (let i = 1 + blockShape.length; i < x.shape.length; ++i) {
-            completePaddings.push([0, 0]);
-          }
-          const paddedX = x.pad(completePaddings);
-          const reshapedPaddedShape = dist["backend_util"].getReshaped(
-            paddedX.shape,
-            blockShape,
-            prod,
-            false
-          );
-          const permutedReshapedPaddedPermutation = dist["backend_util"].getPermuted(
-            reshapedPaddedShape.length,
-            blockShape.length,
-            false
-          );
-          const flattenShape = dist["backend_util"].getReshapedPermuted(
-            paddedX.shape,
-            blockShape,
-            prod,
-            false
-          );
-          return Object(dist["transpose"])(
-            paddedX.reshape(reshapedPaddedShape),
-            permutedReshapedPaddedPermutation
-          ).reshape(flattenShape);
-        }
-        reduce(x, reduceType, dtype) {
-          const batchSize = x.shape[0];
-          const inSize = x.shape[1];
-          const windowSize = dist["backend_util"].computeOptimalWindowSize(inSize);
-          const reduceInfo = { windowSize, inSize, batchSize };
-          const program = new ReduceProgram(reduceInfo, reduceType);
-          const output = this.compileAndRun(program, [x], dtype);
-          // No need to run another GPGPU program.
-          if (output.shape[1] === 1) {
-            return output;
-          }
-          return this.reduce(output, reduceType, dtype);
-        }
-        argReduce(x, reduceType, bestIndicesA = null) {
-          let batchSize = x.shape[0];
-          let inSize = x.shape[1];
-          if (bestIndicesA != null) {
-            batchSize = bestIndicesA.shape[0];
-            inSize = bestIndicesA.shape[1];
-          }
-          const windowSize = dist["backend_util"].computeOptimalWindowSize(inSize);
-          const reduceInfo = { windowSize, inSize, batchSize };
-          const program = new ArgMinMaxProgram(reduceInfo, reduceType, bestIndicesA == null);
-          const inputs = [x];
-          if (bestIndicesA != null) {
-            inputs.push(bestIndicesA);
-          }
-          const output = this.compileAndRun(program, inputs, "int32");
-          // No need to run another GPGPU program.
-          if (output.shape[1] === 1) {
-            return output;
-          }
-          return this.argReduce(x, reduceType, output);
-        }
-        argReducePacked(x, reduceType, bestIndicesA = null) {
-          const inShape = bestIndicesA != null ? bestIndicesA.shape : x.shape;
-          const inSize = inShape[inShape.length - 1];
-          const windowSize = dist["backend_util"].computeOptimalWindowSize(inSize);
-          const program = new argminmax_packed_gpu_ArgMinMaxPackedProgram(
-            inShape,
-            windowSize,
-            reduceType,
-            bestIndicesA == null
-          );
-          const inputs = bestIndicesA == null ? [x] : [x, bestIndicesA];
-          const output = this.compileAndRun(program, inputs, "int32");
-          if (output.rank === x.rank) {
-            return this.argReducePacked(x, reduceType, output);
-          }
-          return output;
-        }
-        sum(x, axes) {
-          dist["backend_util"].assertAxesAreInnerMostDims("sum", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const inSize = dist["util"].sizeFromShape(reduceShape);
-          const a2D = x.as2D(-1, inSize);
-          const outputDType = dist["sumOutType"](x.dtype);
-          return this.reduce(a2D, "sum", outputDType).reshape(outShape);
-        }
-        prod(x, axes) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.prod(x, axes);
-          }
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const inSize = dist["util"].sizeFromShape(reduceShape);
-          const a2D = x.as2D(-1, inSize);
-          const outputDType = dist["sumOutType"](x.dtype);
-          return this.reduce(a2D, "prod", outputDType).reshape(outShape);
-        }
-        unsortedSegmentSum(x, segmentIds, numSegments) {
-          let axis = 0;
-          const permutation = dist["backend_util"].getAxesPermutation([axis], x.rank);
-          let permutedX = x;
-          if (permutation != null) {
-            permutedX = Object(dist["transpose"])(x, permutation);
-            axis = dist["backend_util"].getInnerMostAxes(1, x.rank)[0];
-          }
-          const outShape = segment_util.computeOutShape(permutedX.shape, axis, numSegments);
-          const inSize = dist["util"].sizeFromShape([permutedX.shape[axis]]);
-          const a2D = permutedX.as2D(-1, inSize);
-          const outputDType = dist["sumOutType"](x.dtype);
-          let result = this.segOpCompute(
-            a2D,
-            "unsortedSegmentSum",
-            segmentIds,
-            outputDType,
-            numSegments
-          ).reshape(outShape);
-          if (permutation != null) {
-            result = Object(dist["transpose"])(
-              result,
-              dist["backend_util"].getUndoAxesPermutation(permutation)
-            );
-          }
-          return result;
-        }
-        segOpCompute(x, segOpType, segmentIds, dtype, numSegments) {
-          const batchSize = x.shape[0];
-          const inSize = x.shape[1];
-          const windowSize = segment_util.segOpComputeOptimalWindowSize(inSize, numSegments);
-          const segOpInfo = { windowSize, inSize, batchSize, numSegments };
-          const program = new SegmentOpProgram(segOpInfo, segOpType);
-          const output = this.compileAndRun(program, [x, segmentIds], dtype);
-          // No need to run another GPGPU program.
-          if (output.shape[1] === numSegments) {
-            return output;
-          }
-          segmentIds = Object(dist["range"])(0, numSegments).tile([inSize / windowSize]);
-          return this.segOpCompute(output, segOpType, segmentIds, dtype, numSegments);
-        }
-        argMinMaxReduce(x, axis, reduceType) {
-          const axes = [axis];
-          dist["backend_util"].assertAxesAreInnerMostDims(
-            "arg" + reduceType.charAt(0).toUpperCase() + reduceType.slice(1),
-            axes,
-            x.rank
-          );
-          if (!Object(dist["env"])().getBool("WEBGL_PACK_REDUCE") || x.rank <= 2) {
-            const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-              x.shape,
-              axes
-            );
-            const inSize = dist["util"].sizeFromShape(reduceShape);
-            const a2D = x.as2D(-1, inSize);
-            return this.argReduce(a2D, reduceType).reshape(outShape);
-          }
-          return this.argReducePacked(x, reduceType);
-        }
-        argMin(x, axis) {
-          return this.argMinMaxReduce(x, axis, "min");
-        }
-        argMax(x, axis) {
-          return this.argMinMaxReduce(x, axis, "max");
-        }
-        cumsum(x, axis, exclusive, reverse) {
-          if (axis !== x.rank - 1) {
-            throw new Error(
-              `WebGL cumsum shader expects an inner-most axis=${x.rank - 1} ` +
-                `but got axis=${axis}`
-            );
-          }
-          const program = new cumsum_gpu_CumSumProgram(x.shape, exclusive, reverse);
-          return this.compileAndRun(program, [x]);
-        }
-        equal(a, b) {
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_EQUAL, "bool");
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(EQUAL, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], "bool");
-        }
-        notEqual(a, b) {
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_NOT_EQUAL, "bool");
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(NOT_EQUAL, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], "bool");
-        }
-        less(a, b) {
-          if (this.shouldExecuteOnCPU([a, b])) {
-            return this.cpuBackend.less(a, b);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_LESS, "bool");
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(LESS, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], "bool");
-        }
-        lessEqual(a, b) {
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_LESS_EQUAL, "bool");
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(LESS_EQUAL, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], "bool");
-        }
-        greater(a, b) {
-          if (this.shouldExecuteOnCPU([a, b])) {
-            return this.cpuBackend.greater(a, b);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_GREATER, "bool");
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(GREATER, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], "bool");
-        }
-        greaterEqual(a, b) {
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_GREATER_EQUAL, "bool");
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(GREATER_EQUAL, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], "bool");
-        }
-        logicalNot(x) {
-          const program = new UnaryOpProgram(x.shape, LOGICAL_NOT);
-          return this.compileAndRun(program, [x]);
-        }
-        logicalAnd(a, b) {
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_LOGICAL_AND, "bool");
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(LOGICAL_AND, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], "bool");
-        }
-        logicalOr(a, b) {
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_LOGICAL_OR, "bool");
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(LOGICAL_OR, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], "bool");
-        }
-        select(condition, a, b) {
-          const program = new select_gpu_SelectProgram(condition.rank, a.shape, a.rank);
-          return this.compileAndRun(
-            program,
-            [condition, a, b],
-            Object(dist["upcastType"])(a.dtype, b.dtype)
-          );
-        }
-        where(condition) {
-          dist["backend_util"].warn(
-            "tf.where() in webgl locks the UI thread. " + "Call tf.whereAsync() instead"
-          );
-          const condVals = condition.dataSync();
-          return whereImpl(condition.shape, condVals);
-        }
-        topk(x, k, sorted) {
-          const xVals = x.dataSync();
-          return topkImpl(xVals, x.shape, x.dtype, k, sorted);
-        }
-        min(x, axes) {
-          dist["backend_util"].assertAxesAreInnerMostDims("min", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const inSize = dist["util"].sizeFromShape(reduceShape);
-          const a2D = x.as2D(-1, inSize);
-          return this.reduce(a2D, "min", a2D.dtype).reshape(outShape);
-        }
-        minimum(a, b) {
-          if (this.shouldExecuteOnCPU([a, b])) {
-            return this.cpuBackend.minimum(a, b);
-          }
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
-            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
-                binaryop_packed_gpu_MIN,
-                a.shape,
-                b.shape
-              )
-            : new binaryop_gpu_BinaryOpProgram(MIN, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b]);
-        }
-        mod(a, b) {
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
-            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
-                binaryop_packed_gpu_MOD,
-                a.shape,
-                b.shape
-              )
-            : new binaryop_gpu_BinaryOpProgram(MOD, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b]);
-        }
-        maximum(a, b) {
-          if (this.shouldExecuteOnCPU([a, b])) {
-            return this.cpuBackend.maximum(a, b);
-          }
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
-            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
-                binaryop_packed_gpu_MAX,
-                a.shape,
-                b.shape
-              )
-            : new binaryop_gpu_BinaryOpProgram(MAX, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b]);
-        }
-        all(x, axes) {
-          dist["backend_util"].assertAxesAreInnerMostDims("all", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const inSize = dist["util"].sizeFromShape(reduceShape);
-          const a2D = x.as2D(-1, inSize);
-          return this.reduce(a2D, "all", a2D.dtype).reshape(outShape);
-        }
-        any(x, axes) {
-          dist["backend_util"].assertAxesAreInnerMostDims("any", axes, x.rank);
-          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            x.shape,
-            axes
-          );
-          const inSize = dist["util"].sizeFromShape(reduceShape);
-          const a2D = x.as2D(-1, inSize);
-          return this.reduce(a2D, "any", a2D.dtype).reshape(outShape);
-        }
-        floorDiv(a, b) {
-          const op = INT_DIV;
-          const outputDtype = "int32";
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, binaryop_packed_gpu_INT_DIV, outputDtype);
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(op, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], outputDtype);
-        }
-        add(a, b) {
-          if (a.dtype === "complex64" && b.dtype === "complex64") {
-            return this.complexSeparableBinaryOp(a, b, ADD);
-          }
-          if (this.shouldExecuteOnCPU([a, b])) {
-            return this.cpuBackend.add(a, b);
-          }
-          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, ADD, dtype);
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(ADD, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], dtype);
-        }
-        packedUnaryOp(x, op, dtype) {
-          const program = new UnaryOpPackedProgram(x.shape, op);
-          return this.compileAndRun(program, [x], dtype);
-        }
-        packedBinaryOp(a, b, op, dtype, checkOutOfBounds = false) {
-          const program = new binaryop_packed_gpu_BinaryOpPackedProgram(
-            op,
-            a.shape,
-            b.shape,
-            checkOutOfBounds
-          );
-          return this.compileAndRun(program, [a, b], dtype);
-        }
-        /**
-         * Computes a complex binary operation that can be decomposed into a simple
-         * binary operation on both the real and imagary parts.
-         */
-        complexSeparableBinaryOp(a, b, op) {
-          const aData = this.texData.get(a.dataId);
-          const bData = this.texData.get(b.dataId);
-          const [real, imag] = [
-            [aData.complexTensors.real, bData.complexTensors.real],
-            [aData.complexTensors.imag, bData.complexTensors.imag],
-          ].map((complexParts) => {
-            const [aPart, bPart] = complexParts;
-            const aHandle = this.makeComplexComponentTensorInfo(a, aPart);
-            const bHandle = this.makeComplexComponentTensorInfo(b, bPart);
-            const program = new binaryop_gpu_BinaryOpProgram(op, a.shape, b.shape);
-            return this.compileAndRun(
-              program,
-              [aHandle, bHandle],
-              Object(dist["upcastType"])(aPart.dtype, bPart.dtype)
-            );
-          });
-          const complex = this.complex(real, imag);
-          real.dispose();
-          imag.dispose();
-          return complex;
-        }
-        // Returns a TensorInfo with the complex shape and the dataId of the
-        // underlying part. We need to do this because a reshaped complex tensor is
-        // not reflected in its parts.
-        makeComplexComponentTensorInfo(complexTensor, complexPart) {
-          return {
-            dataId: complexPart.dataId,
-            dtype: complexPart.dtype,
-            shape: complexTensor.shape,
-          };
-        }
-        addN(tensors) {
-          if (tensors.length === 1) {
-            return tensors[0];
-          }
-          // Limit the number of uploaded textures for optimization.
-          if (tensors.length > Object(dist["env"])().get("WEBGL_MAX_TEXTURES_IN_SHADER")) {
-            const midIndex = Math.floor(tensors.length / 2);
-            const leftSide = this.addN(tensors.slice(0, midIndex));
-            const rightSide = this.addN(tensors.slice(midIndex));
-            return this.addN([leftSide, rightSide]);
-          }
-          const dtype = tensors
-            .map((t) => t.dtype)
-            .reduce((d1, d2) => Object(dist["upcastType"])(d1, d2));
-          const shapes = tensors.map((t) => t.shape);
-          // We can make sure shapes are identical in op level.
-          const usePackedOp = Object(dist["env"])().getBool("WEBGL_PACK");
-          const program = usePackedOp
-            ? new AddNPackedProgram(tensors[0].shape, shapes)
-            : new AddNProgram(tensors[0].shape, shapes);
-          return this.compileAndRun(program, tensors, dtype);
-        }
-        subtract(a, b) {
-          if (a.dtype === "complex64" && b.dtype === "complex64") {
-            return this.complexSeparableBinaryOp(a, b, SUB);
-          }
-          if (this.shouldExecuteOnCPU([a, b])) {
-            return this.cpuBackend.subtract(a, b);
-          }
-          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
-          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-            return this.packedBinaryOp(a, b, SUB, a.dtype);
-          }
-          const program = new binaryop_gpu_BinaryOpProgram(SUB, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b], dtype);
-        }
-        pow(a, b) {
-          const usePackedOp = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS");
-          const program = usePackedOp
-            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
-                binaryop_packed_gpu_POW,
-                a.shape,
-                b.shape
-              )
-            : new binaryop_gpu_BinaryOpProgram(POW, a.shape, b.shape);
-          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
-          return this.compileAndRun(program, [a, b], dtype);
-        }
-        ceil(x) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.ceil(x);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
-            return this.packedUnaryOp(x, CEIL, x.dtype);
-          }
-          const program = new UnaryOpProgram(x.shape, CEIL);
-          return this.compileAndRun(program, [x]);
-        }
-        floor(x) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.floor(x);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
-            return this.packedUnaryOp(x, FLOOR, x.dtype);
-          }
-          const program = new UnaryOpProgram(x.shape, FLOOR);
-          return this.compileAndRun(program, [x]);
-        }
-        sign(x) {
-          const program = new UnaryOpProgram(x.shape, SIGN);
-          return this.compileAndRun(program, [x]);
-        }
-        isNaN(x) {
-          const program = new UnaryOpProgram(x.shape, IS_NAN);
-          return this.compileAndRun(program, [x], "bool");
-        }
-        isInf(x) {
-          const program = new UnaryOpProgram(x.shape, IS_INF);
-          return this.compileAndRun(program, [x], "bool");
-        }
-        isFinite(x) {
-          const program = new UnaryOpProgram(x.shape, IS_FINITE);
-          return this.compileAndRun(program, [x], "bool");
-        }
-        round(x) {
-          const program = new UnaryOpProgram(x.shape, ROUND);
-          return this.compileAndRun(program, [x]);
-        }
-        exp(x) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.exp(x);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
-            return this.packedUnaryOp(x, EXP, x.dtype);
-          }
-          const program = new UnaryOpProgram(x.shape, EXP);
-          return this.compileAndRun(program, [x]);
-        }
-        expm1(x) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.expm1(x);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
-            return this.packedUnaryOp(x, EXPM1, x.dtype);
-          }
-          const program = new UnaryOpProgram(x.shape, EXPM1);
-          return this.compileAndRun(program, [x]);
-        }
-        softmax(logits, dim) {
-          const axes = dist["util"].parseAxisParam([dim], logits.shape);
-          // TODO(annxingyuan): Call maxImpl rather than op as part of softmax kernel
-          // modularization.
-          const maxLogit = Object(dist["max"])(logits, axes);
-          const expandedShape = dist["backend_util"].expandShapeToKeepDim(maxLogit.shape, axes);
-          const a = this.subtract(logits, maxLogit.reshape(expandedShape));
-          const b = this.exp(a);
-          const sumExp = this.sum(b, axes).reshape(expandedShape);
-          // TODO(annxingyuan): Call divImpl rather than op as part of softmax kernel
-          // modularization.
-          return Object(dist["div"])(b, sumExp);
-        }
-        log(x) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.log(x);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
-            return this.packedUnaryOp(x, unaryop_packed_gpu_LOG, x.dtype);
-          }
-          const program = new UnaryOpProgram(x.shape, LOG);
-          return this.compileAndRun(program, [x]);
-        }
-        log1p(x) {
-          const program = new UnaryOpProgram(x.shape, LOG1P);
-          return this.compileAndRun(program, [x]);
-        }
-        sqrt(x) {
-          const program = new UnaryOpProgram(x.shape, SQRT);
-          return this.compileAndRun(program, [x]);
-        }
-        rsqrt(x) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.rsqrt(x);
-          }
-          const program = new UnaryOpProgram(x.shape, RSQRT);
-          return this.compileAndRun(program, [x]);
-        }
-        reciprocal(x) {
-          const program = new UnaryOpProgram(x.shape, RECIPROCAL);
-          return this.compileAndRun(program, [x]);
-        }
-        relu(x) {
-          let program;
-          if (Object(dist["env"])().getBool("WEBGL_PACK")) {
-            program = new UnaryOpPackedProgram(x.shape, unaryop_packed_gpu_RELU);
-          } else {
-            program = new UnaryOpProgram(x.shape, RELU);
-          }
-          return this.compileAndRun(program, [x]);
-        }
-        relu6(x) {
-          let program;
-          if (Object(dist["env"])().getBool("WEBGL_PACK")) {
-            program = new UnaryOpPackedProgram(x.shape, unaryop_packed_gpu_RELU6);
-          } else {
-            program = new UnaryOpProgram(x.shape, RELU6);
-          }
-          return this.compileAndRun(program, [x]);
-        }
-        prelu(x, alpha) {
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
-            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
-                binaryop_packed_gpu_PRELU,
-                x.shape,
-                alpha.shape
-              )
-            : new binaryop_gpu_BinaryOpProgram(PRELU, x.shape, alpha.shape);
-          return this.compileAndRun(program, [x, alpha]);
-        }
-        elu(x) {
-          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
-            return this.packedUnaryOp(x, unaryop_packed_gpu_ELU, x.dtype);
-          }
-          const program = new UnaryOpProgram(x.shape, ELU);
-          return this.compileAndRun(program, [x]);
-        }
-        eluDer(dy, y) {
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
-            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
-                binaryop_packed_gpu_ELU_DER,
-                dy.shape,
-                y.shape
-              )
-            : new binaryop_gpu_BinaryOpProgram(ELU_DER, dy.shape, y.shape);
-          return this.compileAndRun(program, [dy, y]);
-        }
-        selu(x) {
-          const program = new UnaryOpProgram(x.shape, SELU);
-          return this.compileAndRun(program, [x]);
-        }
-        int(x) {
-          const program = new UnaryOpProgram(x.shape, TO_INT);
-          return this.compileAndRun(program, [x], "int32");
-        }
-        clip(x, min, max) {
-          let program;
-          if (Object(dist["env"])().getBool("WEBGL_PACK_CLIP")) {
-            program = new ClipPackedProgram(x.shape);
-          } else {
-            program = new ClipProgram(x.shape);
-          }
-          const customSetup = program.getCustomSetupFunc(min, max);
-          return this.compileAndRun(program, [x], null, customSetup);
-        }
-        abs(x) {
-          if (this.shouldExecuteOnCPU([x])) {
-            return this.cpuBackend.abs(x);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
-            return this.packedUnaryOp(x, ABS, x.dtype);
-          }
-          const program = new UnaryOpProgram(x.shape, ABS);
-          return this.compileAndRun(program, [x]);
-        }
-        complexAbs(x) {
-          const xData = this.texData.get(x.dataId);
-          const program = new ComplexAbsProgram(x.shape);
-          const inputs = [
-            this.makeComplexComponentTensorInfo(x, xData.complexTensors.real),
-            this.makeComplexComponentTensorInfo(x, xData.complexTensors.imag),
-          ];
-          return this.compileAndRun(program, inputs);
-        }
-        sigmoid(x) {
-          const program = new UnaryOpProgram(x.shape, SIGMOID);
-          return this.compileAndRun(program, [x]);
-        }
-        softplus(x) {
-          const program = new UnaryOpProgram(x.shape, SOFTPLUS);
-          return this.compileAndRun(program, [x]);
-        }
-        sin(x) {
-          const program = new UnaryOpProgram(x.shape, SIN);
-          return this.compileAndRun(program, [x]);
-        }
-        cos(x) {
-          const program = new UnaryOpProgram(x.shape, COS);
-          return this.compileAndRun(program, [x]);
-        }
-        tan(x) {
-          const program = new UnaryOpProgram(x.shape, TAN);
-          return this.compileAndRun(program, [x]);
-        }
-        asin(x) {
-          const program = new UnaryOpProgram(x.shape, ASIN);
-          return this.compileAndRun(program, [x]);
-        }
-        acos(x) {
-          const program = new UnaryOpProgram(x.shape, ACOS);
-          return this.compileAndRun(program, [x]);
-        }
-        atan(x) {
-          const program = new UnaryOpProgram(x.shape, ATAN);
-          return this.compileAndRun(program, [x]);
-        }
-        atan2(a, b) {
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
-            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
-                binaryop_packed_gpu_ATAN2,
-                a.shape,
-                b.shape
-              )
-            : new binaryop_gpu_BinaryOpProgram(ATAN2, a.shape, b.shape);
-          return this.compileAndRun(program, [a, b]);
-        }
-        sinh(x) {
-          const program = new UnaryOpProgram(x.shape, SINH);
-          return this.compileAndRun(program, [x]);
-        }
-        cosh(x) {
-          const program = new UnaryOpProgram(x.shape, COSH);
-          return this.compileAndRun(program, [x]);
-        }
-        tanh(x) {
-          const program = new UnaryOpProgram(x.shape, TANH);
-          return this.compileAndRun(program, [x]);
-        }
-        asinh(x) {
-          const program = new UnaryOpProgram(x.shape, ASINH);
-          return this.compileAndRun(program, [x]);
-        }
-        acosh(x) {
-          const program = new UnaryOpProgram(x.shape, ACOSH);
-          return this.compileAndRun(program, [x]);
-        }
-        atanh(x) {
-          const program = new UnaryOpProgram(x.shape, ATANH);
-          return this.compileAndRun(program, [x]);
-        }
-        erf(x) {
-          const program = new UnaryOpProgram(x.shape, ERF);
-          return this.compileAndRun(program, [x]);
-        }
-        step(x, alpha) {
-          const program = new UnaryOpProgram(x.shape, STEP(alpha));
-          return this.compileAndRun(program, [x]);
-        }
-        conv2dByMatMul(x, filter, convInfo, bias, activation, preluActivationWeights) {
-          // Reshapes conv2D input to 2D tensors, uses matMul and then reshape the
-          // result from 2D to 4D.
-          const xShape = x.shape;
-          const xTexData = this.texData.get(x.dataId);
-          const sharedMatMulDim = convInfo.inChannels;
-          const outerShapeX = xShape[0] * xShape[1] * xShape[2];
-          const outerShapeFilter = convInfo.outChannels;
-          const isChannelsLast = convInfo.dataFormat === "channelsLast";
-          const transposeA = false;
-          const transposeB = false;
-          // TODO: Once reduction ops are packed, batchMatMul will always be packed
-          // and we can remove this condition.
-          const batchMatMulWillBeUnpacked =
-            (outerShapeX === 1 || outerShapeFilter === 1) &&
-            sharedMatMulDim > MATMUL_SHARED_DIM_THRESHOLD;
-          const reshapeWillBeExpensive = xShape[2] % 2 !== 0 && !!xTexData.isPacked;
-          if (
-            batchMatMulWillBeUnpacked ||
-            !Object(dist["env"])().getBool("WEBGL_LAZILY_UNPACK") ||
-            !Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS") ||
-            !reshapeWillBeExpensive
-          ) {
-            const targetShape = isChannelsLast
-              ? xShape[0] * xShape[1] * xShape[2]
-              : xShape[0] * xShape[2] * xShape[3];
-            const xReshaped = this.reshape(x, [1, targetShape, convInfo.inChannels]);
-            const filterReshaped = this.reshape(filter, [
-              1,
-              convInfo.inChannels,
-              convInfo.outChannels,
-            ]);
-            return this.reshape(
-              this.fusedBatchMatMul({
-                a: xReshaped,
-                b: filterReshaped,
-                transposeA,
-                transposeB,
-                bias,
-                activation,
-                preluActivationWeights,
-              }),
-              convInfo.outShape
-            );
-          }
-          // Following optimization is specific to packed |x| with odd row count
-          // (For example, in channelLast mode, 'row count' refers to x.shape[2]):
-          // we avoid expensive packed 2x2 reshape by padding row count to next,
-          // even number. When x.shape[2] is odd, the result of packed batchMatMul is
-          // the same (has the same texture layout and and values in the texture) as
-          // it is for even x.shape[2] + 1. We make the odd-rows tensor to look like
-          // even-rows tensor before the operation and, after the batchMatMul,
-          // fix the even-rows result to have odd number of rows.
-          const targetShape = isChannelsLast
-            ? xShape[0] * xShape[1] * (xShape[2] + 1)
-            : xShape[0] * xShape[2] * (xShape[3] + 1);
-          const xReshaped = {
-            dataId: x.dataId,
-            shape: [1, targetShape, convInfo.inChannels],
-            dtype: x.dtype,
-          };
-          // xTexData.shape gets referenced from GPGPUBinary.inShapeInfos.
-          // Decrementing row count, after batchMatMul->...->compileProgram leads to
-          // invalid row count within the reference in GPGPUBinary.inShapeInfos.
-          // Alternative fix would be to provide a copy to GPGPUBinary.inShapeInfos
-          // in compileProgram method, but that would affect compilation of all
-          // programs - instead, provide a copy here, with even row count, before
-          // calling batchMatMul->...->compileProgram and after that, the original
-          // xTexData.shape is restored.
-          const originalXTexDataShape = xTexData.shape;
-          xTexData.shape = xTexData.shape.slice();
-          xTexData.shape[xTexData.shape.length - 2]++;
-          dist["util"].assert(
-            isReshapeFree(xTexData.shape, xReshaped.shape),
-            () => `packed reshape ${xTexData.shape} to ${xReshaped.shape} isn't free`
-          );
-          const filterReshaped = this.reshape(filter, [
-            1,
-            convInfo.inChannels,
-            convInfo.outChannels,
-          ]);
-          const pointwiseConv = this.fusedBatchMatMul({
-            a: xReshaped,
-            b: filterReshaped,
-            transposeA,
-            transposeB,
-            bias,
-            activation,
-            preluActivationWeights,
-          });
-          const pointwiseConvTexData = this.texData.get(pointwiseConv.dataId);
-          dist["util"].assert(
-            pointwiseConvTexData.isPacked,
-            () => "batchMatMul result is expected to be packed"
-          );
-          // Restore the input shape to original.
-          xTexData.shape = originalXTexDataShape;
-          // Set the output shape - there is no need for expensive reshape as data
-          // layout is already correct.
-          pointwiseConvTexData.shape = convInfo.outShape;
-          return Object(dist["engine"])().makeTensorFromDataId(
-            pointwiseConv.dataId,
-            convInfo.outShape,
-            pointwiseConv.dtype
-          );
-        }
-        conv2dWithIm2Row(x, filter, convInfo, bias, activation, preluActivationWeights) {
-          // Rearranges conv2d input so each block to be convolved over forms the
-          // column of a new matrix with shape [filterWidth * filterHeight *
-          // inChannels, outHeight * outWidth]. The filter is also rearranged so each
-          // output channel forms a row of a new matrix with shape [outChannels,
-          // filterWidth * filterHeight * inChannels]. The convolution is then
-          // computed by multiplying these matrices and reshaping the result.
-          const { filterWidth, filterHeight, inChannels, outWidth, outHeight, dataFormat } =
-            convInfo;
-          const isChannelsLast = dataFormat === "channelsLast";
-          const sharedDim = filterWidth * filterHeight * inChannels;
-          const numCols = outHeight * outWidth;
-          const x2ColShape = [sharedDim, numCols];
-          const transposeA = true;
-          const transposeB = false;
-          const xSqueezed = x.squeeze([0]);
-          const w2Row = filter.reshape([1, sharedDim, -1]);
-          const im2ColProgram = new im2col_packed_gpu_Im2ColPackedProgram(
-            x2ColShape,
-            xSqueezed.shape,
-            convInfo
-          );
-          const im2Col = this.compileAndRun(im2ColProgram, [xSqueezed]).reshape([
-            1,
-            x2ColShape[0],
-            x2ColShape[1],
-          ]);
-          const hasBias = bias != null;
-          const hasPreluActivationWeights = preluActivationWeights != null;
-          const fusedActivation = activation
-            ? mapActivationToShaderProgram(activation, true)
-            : null;
-          const matmulProgram = new MatMulPackedProgram(
-            im2Col.shape,
-            [1, numCols, convInfo.outChannels],
-            transposeA,
-            transposeB,
-            hasBias,
-            fusedActivation,
-            hasPreluActivationWeights
-          );
-          const inputs = [im2Col, w2Row];
-          if (bias) {
-            inputs.push(bias);
-          }
-          if (hasPreluActivationWeights) {
-            inputs.push(preluActivationWeights);
-          }
-          const product = this.compileAndRun(matmulProgram, inputs);
-          if (isChannelsLast) {
-            return product.reshape([1, outHeight, outWidth, convInfo.outChannels]);
-          } else {
-            return product.reshape([1, convInfo.outChannels, outHeight, outWidth]);
-          }
-        }
-        fusedConv2d({ input, filter, convInfo, bias, activation, preluActivationWeights }) {
-          if (
-            convInfo.filterHeight === 1 &&
-            convInfo.filterWidth === 1 &&
-            convInfo.dilationHeight === 1 &&
-            convInfo.dilationWidth === 1 &&
-            convInfo.strideHeight === 1 &&
-            convInfo.strideWidth === 1 &&
-            (convInfo.padInfo.type === "SAME" || convInfo.padInfo.type === "VALID")
-          ) {
-            return this.conv2dByMatMul(
-              input,
-              filter,
-              convInfo,
-              bias,
-              activation,
-              preluActivationWeights
-            );
-          }
-          if (Object(dist["env"])().getBool("WEBGL_CONV_IM2COL") && input.shape[0] === 1) {
-            return this.conv2dWithIm2Row(
-              input,
-              filter,
-              convInfo,
-              bias,
-              activation,
-              preluActivationWeights
-            );
-          }
-          const hasBias = bias != null;
-          const hasPreluActivationWeights = preluActivationWeights != null;
-          const fusedActivation = activation
-            ? mapActivationToShaderProgram(activation, false)
-            : null;
-          const program = new Conv2DProgram(
-            convInfo,
-            hasBias,
-            fusedActivation,
-            hasPreluActivationWeights
-          );
-          const inputs = [input, filter];
-          if (bias) {
-            inputs.push(bias);
-          }
-          if (preluActivationWeights) {
-            inputs.push(preluActivationWeights);
-          }
-          return this.compileAndRun(program, inputs);
-        }
-        conv2d(x, filter, convInfo) {
-          if (
-            convInfo.filterHeight === 1 &&
-            convInfo.filterWidth === 1 &&
-            convInfo.dilationHeight === 1 &&
-            convInfo.dilationWidth === 1 &&
-            convInfo.strideHeight === 1 &&
-            convInfo.strideWidth === 1 &&
-            (convInfo.padInfo.type === "SAME" || convInfo.padInfo.type === "VALID")
-          ) {
-            return this.conv2dByMatMul(x, filter, convInfo);
-          }
-          if (Object(dist["env"])().getBool("WEBGL_CONV_IM2COL") && x.shape[0] === 1) {
-            return this.conv2dWithIm2Row(x, filter, convInfo);
-          }
-          const program = new Conv2DProgram(convInfo);
-          return this.compileAndRun(program, [x, filter]);
-        }
-        conv2dDerInput(dy, filter, convInfo) {
-          const program = new Conv2DDerInputProgram(convInfo);
-          return this.compileAndRun(program, [dy, filter]);
-        }
-        conv2dDerFilter(x, dy, convInfo) {
-          const program = new Conv2DDerFilterProgram(convInfo);
-          return this.compileAndRun(program, [x, dy]);
-        }
-        fusedDepthwiseConv2D({
-          input,
-          filter,
-          convInfo,
-          bias,
-          activation,
-          preluActivationWeights,
-        }) {
-          const shouldPackDepthwiseConv =
-            Object(dist["env"])().getBool("WEBGL_PACK_DEPTHWISECONV") &&
-            convInfo.strideWidth <= 2 &&
-            convInfo.outChannels / convInfo.inChannels === 1;
-          const fusedActivation = activation
-            ? mapActivationToShaderProgram(activation, shouldPackDepthwiseConv)
-            : null;
-          const inputs = [input, filter];
-          const hasBias = bias != null;
-          const hasPreluActivationWeights = preluActivationWeights != null;
-          if (hasBias) {
-            inputs.push(bias);
-          }
-          if (hasPreluActivationWeights) {
-            inputs.push(preluActivationWeights);
-          }
-          let program;
-          if (shouldPackDepthwiseConv) {
-            program = new conv_packed_gpu_depthwise_DepthwiseConvPacked2DProgram(
-              convInfo,
-              hasBias,
-              fusedActivation,
-              hasPreluActivationWeights
-            );
-            return this.compileAndRun(program, inputs);
-          }
-          program = new DepthwiseConv2DProgram(
-            convInfo,
-            hasBias,
-            fusedActivation,
-            hasPreluActivationWeights
-          );
-          return this.compileAndRun(program, inputs);
-        }
-        depthwiseConv2D(x, filter, convInfo) {
-          let program;
-          if (
-            Object(dist["env"])().getBool("WEBGL_PACK_DEPTHWISECONV") &&
-            convInfo.strideWidth <= 2 &&
-            convInfo.outChannels / convInfo.inChannels === 1
-          ) {
-            program = new conv_packed_gpu_depthwise_DepthwiseConvPacked2DProgram(convInfo);
-            return this.compileAndRun(program, [x, filter]);
-          }
-          program = new DepthwiseConv2DProgram(convInfo);
-          return this.compileAndRun(program, [x, filter]);
-        }
-        depthwiseConv2DDerInput(dy, filter, convInfo) {
-          const program = new DepthwiseConv2DDerInputProgram(convInfo);
-          return this.compileAndRun(program, [dy, filter]);
-        }
-        depthwiseConv2DDerFilter(x, dy, convInfo) {
-          const program = new DepthwiseConv2DDerFilterProgram(convInfo);
-          return this.compileAndRun(program, [x, dy]);
-        }
-        conv3d(x, filter, convInfo) {
-          const program = new Conv3DProgram(convInfo);
-          return this.compileAndRun(program, [x, filter]);
-        }
-        conv3dDerInput(dy, filter, convInfo) {
-          const program = new Conv3DDerInputProgram(convInfo);
-          return this.compileAndRun(program, [dy, filter]);
-        }
-        conv3dDerFilter(x, dy, convInfo) {
-          const program = new Conv3DDerFilterProgram(convInfo);
-          return this.compileAndRun(program, [x, dy]);
-        }
-        maxPool(x, convInfo) {
-          const program = new Pool2DProgram(convInfo, "max", false);
-          return this.compileAndRun(program, [x]);
-        }
-        avgPool(x, convInfo) {
-          const program = new Pool2DProgram(convInfo, "avg", false);
-          return this.compileAndRun(program, [x], "float32");
-        }
-        maxPoolBackprop(dy, x, y, convInfo) {
-          const getPositions = true;
-          const maxPoolPositionsProgram = new Pool2DProgram(convInfo, "max", getPositions);
-          const maxPoolPositions = this.compileAndRun(maxPoolPositionsProgram, [x]);
-          const maxPoolBackPropProgram = new MaxPool2DBackpropProgram(convInfo);
-          const result = this.compileAndRun(
-            maxPoolBackPropProgram,
-            [dy, maxPoolPositions],
-            x.dtype
-          );
-          maxPoolPositions.dispose();
-          return result;
-        }
-        avgPoolBackprop(dy, x, convInfo) {
-          const avgPoolBackpropProgram = new AvgPool2DBackpropProgram(convInfo);
-          return this.compileAndRun(avgPoolBackpropProgram, [dy], x.dtype);
-        }
-        cast(x, dtype) {
-          return dist["backend_util"].castTensor(x, dtype, this);
-        }
-        unstack(x, axis) {
-          const num = x.shape[axis];
-          const outShape = new Array(x.rank - 1);
-          let outIndex = 0;
-          for (let i = 0; i < x.rank; i++) {
-            if (i !== axis) {
-              outShape[outIndex++] = x.shape[i];
-            }
-          }
-          const begin = new Array(x.rank).fill(0);
-          const size = x.shape.slice();
-          size[axis] = 1;
-          const res = new Array(num);
-          for (let i = 0; i < res.length; i++) {
-            begin[axis] = i;
-            res[i] = this.slice(x, begin, size).reshape(outShape);
-          }
-          return res;
-        }
-        avgPool3d(x, convInfo) {
-          const program = new Pool3DProgram(convInfo, "avg", false);
-          return this.compileAndRun(program, [x], "float32");
-        }
-        avgPool3dBackprop(dy, x, convInfo) {
-          const avgPool3dBackpropProgram = new AvgPool3DBackpropProgram(convInfo);
-          return this.compileAndRun(avgPool3dBackpropProgram, [dy], x.dtype);
-        }
-        maxPool3d(x, convInfo) {
-          const program = new Pool3DProgram(convInfo, "max", false);
-          return this.compileAndRun(program, [x], "float32");
-        }
-        maxPool3dBackprop(dy, x, y, convInfo) {
-          const getPositions = true;
-          const maxPool3dPositionsProgram = new Pool3DProgram(convInfo, "max", getPositions);
-          const maxPool3dPositions = this.compileAndRun(maxPool3dPositionsProgram, [x]);
-          const maxPool3dBackPropProgram = new MaxPool3DBackpropProgram(convInfo);
-          const result = this.compileAndRun(
-            maxPool3dBackPropProgram,
-            [dy, maxPool3dPositions],
-            x.dtype
-          );
-          maxPool3dPositions.dispose();
-          return result;
-        }
-        reshape(x, shape) {
-          const texData = this.texData.get(x.dataId);
-          if (
-            texData.isPacked &&
-            !isReshapeFree(x.shape, shape) &&
-            !(texData.texture !== null && isReshapeFree(texData.shape, shape))
-          ) {
-            const info = this.packedReshape(x, shape);
-            return Object(dist["engine"])().makeTensorFromDataId(
-              info.dataId,
-              info.shape,
-              info.dtype
-            );
-          }
-          return dist["backend_util"].reshapeTensor(x, shape);
-        }
-        resizeBilinear(x, newHeight, newWidth, alignCorners) {
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_IMAGE_OPERATIONS")
-            ? new ResizeBilinearPackedProgram(x.shape, newHeight, newWidth, alignCorners)
-            : new ResizeBilinearProgram(x.shape, newHeight, newWidth, alignCorners);
-          return this.compileAndRun(program, [x], "float32");
-        }
-        resizeBilinearBackprop(dy, x, alignCorners) {
-          const program = new ResizeBilinearBackpropProgram(dy, x, alignCorners);
-          return this.compileAndRun(program, [dy]);
-        }
-        resizeNearestNeighbor(x, newHeight, newWidth, alignCorners) {
-          const program = new ResizeNearestNeighborProgram(
-            x.shape,
-            newHeight,
-            newWidth,
-            alignCorners
-          );
-          return this.compileAndRun(program, [x]);
-        }
-        resizeNearestNeighborBackprop(dy, x, alignCorners) {
-          const program = new ResizeNearestNeigborBackpropProgram(dy, x, alignCorners);
-          return this.compileAndRun(program, [dy]);
-        }
-        multinomial(logits, normalized, numSamples, seed) {
-          const probs = normalized ? logits : Object(dist["softmax"])(logits);
-          const batchSize = probs.shape[0];
-          const numOutcomes = probs.shape[1];
-          const program = new MultinomialProgram(batchSize, numOutcomes, numSamples);
-          const customSetup = program.getCustomSetupFunc(seed);
-          return this.compileAndRun(program, [probs], "int32", customSetup);
-        }
-        oneHot(indices, depth, onValue, offValue) {
-          const program = new OneHotProgram(indices.size, depth, onValue, offValue);
-          return this.compileAndRun(program, [indices]);
-        }
-        diag(x) {
-          const program = new DiagProgram(x.size);
-          return this.compileAndRun(program, [x]);
-        }
-        cropAndResize(image, boxes, boxIndex, cropSize, method, extrapolationValue) {
-          const program = new CropAndResizeProgram(
-            image.shape,
-            boxes.shape,
-            cropSize,
-            method,
-            extrapolationValue
-          );
-          return this.compileAndRun(program, [image, boxes, boxIndex], "float32");
-        }
-        depthToSpace(x, blockSize, dataFormat) {
-          dist["util"].assert(
-            blockSize > 1,
-            () => `blockSize should be > 1 for depthToSpace, but was: ${blockSize}`
-          );
-          const batchSize = x.shape[0];
-          const inputHeight = dataFormat === "NHWC" ? x.shape[1] : x.shape[2];
-          const inputWidth = dataFormat === "NHWC" ? x.shape[2] : x.shape[3];
-          const inputDepth = dataFormat === "NHWC" ? x.shape[3] : x.shape[1];
-          const outputHeight = inputHeight * blockSize;
-          const outputWidth = inputWidth * blockSize;
-          const outputDepth = inputDepth / (blockSize * blockSize);
-          const outputShape =
-            dataFormat === "NHWC"
-              ? [batchSize, outputHeight, outputWidth, outputDepth]
-              : [batchSize, outputDepth, outputHeight, outputWidth];
-          const program = new DepthToSpaceProgram(outputShape, blockSize, dataFormat);
-          return this.compileAndRun(program, [x]);
-        }
-        split(x, sizeSplits, axis) {
-          return split(x, sizeSplits, axis);
-        }
-        scatterND(indices, updates, shape) {
-          const { sliceRank, numUpdates, sliceSize, strides, outputSize } = dist[
-            "backend_util"
-          ].calculateShapes(updates, indices, shape);
-          const flattenShape = [outputSize / sliceSize, sliceSize];
-          const flattenIndices = indices.reshape([numUpdates, sliceRank]);
-          const flattenX = updates.reshape([numUpdates, sliceSize]);
-          if (outputSize === 0) {
-            return dist["backend_util"].reshapeTensor(Object(dist["tensor"])([]), shape);
-          }
-          const defaultValue = Object(dist["scalar"])(0);
-          const program = new scatter_gpu_ScatterProgram(
-            numUpdates,
-            sliceRank,
-            flattenIndices.rank,
-            flattenX.rank,
-            strides,
-            flattenShape
-          );
-          const res = this.compileAndRun(program, [flattenX, flattenIndices, defaultValue]);
-          return res.reshape(shape);
-        }
-        sparseToDense(sparseIndices, sparseValues, outputShape, defaultValue) {
-          const { sliceRank, numUpdates, strides, outputSize } = dist[
-            "backend_util"
-          ].calculateShapes(sparseValues, sparseIndices, outputShape);
-          const sumDupeIndices = false;
-          const program = new scatter_gpu_ScatterProgram(
-            numUpdates,
-            sliceRank,
-            sparseIndices.rank,
-            sparseValues.rank,
-            strides,
-            [outputSize, 1],
-            sumDupeIndices
-          );
-          const res = this.compileAndRun(program, [sparseValues, sparseIndices, defaultValue]);
-          return res.reshape(outputShape);
-        }
-        fft(x) {
-          const inverse = false;
-          return this.fftImpl(x, inverse);
-        }
-        ifft(x) {
-          const inverse = true;
-          return this.fftImpl(x, inverse);
-        }
-        fftImpl(x, inverse) {
-          const xData = this.texData.get(x.dataId);
-          const realProgram = new FFTProgram(COMPLEX_FFT.REAL, x.shape, inverse);
-          const imagProgram = new FFTProgram(COMPLEX_FFT.IMAG, x.shape, inverse);
-          const inputs = [
-            this.makeComplexComponentTensorInfo(x, xData.complexTensors.real),
-            this.makeComplexComponentTensorInfo(x, xData.complexTensors.imag),
-          ];
-          const real = this.compileAndRun(realProgram, inputs);
-          const imag = this.compileAndRun(imagProgram, inputs);
-          const complex = this.complex(real, imag).as2D(x.shape[0], x.shape[1]);
-          real.dispose();
-          imag.dispose();
-          return complex;
-        }
-        gatherND(x, indices) {
-          const indicesShape = indices.shape;
-          const sliceRank = indicesShape[indicesShape.length - 1];
-          const [resultShape, numSlices, sliceSize, strides] = dist[
-            "backend_util"
-          ].prepareAndValidate(x, indices);
-          const flattenIndices = indices.reshape([numSlices, sliceRank]);
-          const flattenX = x.reshape([x.size / sliceSize, sliceSize]);
-          const program = new gather_nd_gpu_GatherNDProgram(sliceRank, strides, [
-            numSlices,
-            sliceSize,
-          ]);
-          const res = this.compileAndRun(program, [flattenX, flattenIndices]);
-          return res.reshape(resultShape);
-        }
-        fill(shape, value, dtype) {
-          dtype = dtype || dist["util"].inferDtype(value);
-          if (dtype === "string") {
-            // String type should be handled in CPU memory.
-            const values = dist["util"].getArrayFromDType(dtype, dist["util"].sizeFromShape(shape));
-            values.fill(value);
-            return Object(dist["engine"])().makeTensor(values, shape, dtype, this);
-          } else {
-            const program = new FillProgram(shape, value);
-            const customSetup = program.getCustomSetupFunc(value);
-            return this.compileAndRun(program, [], dtype, customSetup);
-          }
-        }
-        onesLike(x) {
-          if (x.dtype === "string") {
-            throw new Error("onesLike is not supported under string dtype");
-          } else {
-            // TODO(cais, smilkov): Add WebGL shader for onesLike:
-            //   https://github.com/tensorflow/tfjs/issues/1293
-            return this.fill(x.shape, 1, x.dtype);
-          }
-        }
-        zerosLike(x) {
-          return this.fill(x.shape, x.dtype === "string" ? "" : 0, x.dtype);
-        }
-        linspace(start, stop, num) {
-          // TODO: Use CPU implementation due to the precision problem in Safari.
-          return dist["backend_util"].linspaceImpl(start, stop, num);
-        }
-        makeTensorInfo(shape, dtype) {
-          const dataId = this.write(null /* values */, shape, dtype);
-          this.texData.get(dataId).usage = null;
-          return { dataId, shape, dtype };
-        }
-        makeOutput(shape, dtype) {
-          const { dataId } = this.makeTensorInfo(shape, dtype);
-          return Object(dist["engine"])().makeTensorFromDataId(dataId, shape, dtype, this);
-        }
-        unpackTensor(input) {
-          const program = new unpack_gpu_UnpackProgram(input.shape);
-          return this.runWebGLProgram(program, [input], input.dtype);
-        }
-        packTensor(input) {
-          const program = new pack_gpu_PackProgram(input.shape);
-          const preventEagerUnpackingOutput = true;
-          return this.runWebGLProgram(
-            program,
-            [input],
-            input.dtype,
-            null /* customSetup */,
-            preventEagerUnpackingOutput
-          );
-        }
-        packedReshape(input, afterShape) {
-          const input3DShape = [getBatchDim(input.shape), ...getRowsCols(input.shape)];
-          const input3D = {
-            dtype: input.dtype,
-            shape: input3DShape,
-            dataId: input.dataId,
-          };
-          const afterShapeAs3D = [getBatchDim(afterShape), ...getRowsCols(afterShape)];
-          const program = new reshape_packed_gpu_ReshapePackedProgram(afterShapeAs3D, input3DShape);
-          const preventEagerUnpackingOfOutput = true;
-          const output = this.runWebGLProgram(
-            program,
-            [input3D],
-            input.dtype,
-            null /* customSetup */,
-            preventEagerUnpackingOfOutput
-          );
-          return { dataId: output.dataId, shape: afterShape, dtype: output.dtype };
-        }
-        decode(dataId) {
-          const texData = this.texData.get(dataId);
-          const { isPacked, shape, dtype } = texData;
-          const shapeAs3D = getShapeAs3D(shape);
-          let program;
-          if (isPacked) {
-            program = new decode_matrix_packed_gpu_DecodeMatrixPackedProgram(shapeAs3D);
-          } else {
-            program = new decode_matrix_gpu_DecodeMatrixProgram(shapeAs3D);
-          }
-          const preventEagerUnpackingOfOutput = true;
-          const out = this.runWebGLProgram(
-            program,
-            [{ shape: shapeAs3D, dtype, dataId }],
-            dtype,
-            null /* customSetup */,
-            preventEagerUnpackingOfOutput
-          );
-          return { dtype, shape, dataId: out.dataId };
-        }
-        runWebGLProgram(
-          program,
-          inputs,
-          outputDtype,
-          customSetup,
-          preventEagerUnpackingOfOutput = false
-        ) {
-          const output = this.makeTensorInfo(program.outputShape, outputDtype);
-          const outData = this.texData.get(output.dataId);
-          if (program.packedOutput) {
-            outData.isPacked = true;
-          }
-          if (program.outPackingScheme === PackingScheme.DENSE) {
-            const texelShape = getDenseTexShape(program.outputShape);
-            // For a densely packed output, we explicitly set texShape
-            // so it doesn't get assigned later according to our typical packing
-            // scheme wherein a single texel can only contain values from adjacent
-            // rows/cols.
-            outData.texShape = texelShape.map((d) => d * 2);
-          }
-          if (program.outTexUsage != null) {
-            outData.usage = program.outTexUsage;
-          }
-          if (dist["util"].sizeFromShape(output.shape) === 0) {
-            // Short-circuit the computation since the result is empty (has 0 in its
-            // shape).
-            outData.values = dist["util"].getTypedArrayFromDType(output.dtype, 0);
-            return output;
-          }
-          const dataToDispose = [];
-          const inputsData = inputs.map((input) => {
-            if (input.dtype === "complex64") {
-              throw new Error(
-                `GPGPUProgram does not support complex64 input. For complex64 ` +
-                  `dtypes, please separate the program into real and imaginary ` +
-                  `parts.`
-              );
-            }
-            let texData = this.texData.get(input.dataId);
-            if (texData.texture == null) {
-              if (
-                !program.packedInputs &&
-                dist["util"].sizeFromShape(input.shape) <=
-                  Object(dist["env"])().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM")
-              ) {
-                // Upload small tensors that live on the CPU as uniforms, not as
-                // textures. Do this only when the environment supports 32bit floats
-                // due to problems when comparing 16bit floats with 32bit floats.
-                // TODO(https://github.com/tensorflow/tfjs/issues/821): Make it
-                // possible for packed shaders to sample from uniforms.
-                return {
-                  shape: input.shape,
-                  texData: null,
-                  isUniform: true,
-                  uniformValues: texData.values,
-                };
-              }
-              // This ensures that if a packed program's inputs have not yet been
-              // uploaded to the GPU, they get uploaded as packed right off the bat.
-              if (program.packedInputs) {
-                texData.isPacked = true;
-                texData.shape = input.shape;
-              }
-            } else if (!!texData.isPacked !== !!program.packedInputs) {
-              input = texData.isPacked ? this.unpackTensor(input) : this.packTensor(input);
-              dataToDispose.push(input);
-              texData = this.texData.get(input.dataId);
-            } else if (texData.isPacked && !isReshapeFree(texData.shape, input.shape)) {
-              // This is a special case where a texture exists for a tensor
-              // but the shapes are incompatible (due to packing constraints) because
-              // the tensor did not have a chance to go through the packed reshape
-              // shader. This only happens when we reshape the *same* tensor to form
-              // *distinct* inputs to an op, e.g. dotting a vector with itself. This
-              // case will disappear once packed uploading is the default.
-              const savedInput = input;
-              const targetShape = input.shape;
-              input.shape = texData.shape;
-              input = this.packedReshape(input, targetShape);
-              dataToDispose.push(input);
-              texData = this.texData.get(input.dataId);
-              savedInput.shape = targetShape;
-            }
-            this.uploadToGPU(input.dataId);
-            return { shape: input.shape, texData, isUniform: false };
-          });
-          this.uploadToGPU(output.dataId);
-          const outputData = { shape: output.shape, texData: outData, isUniform: false };
-          const key = makeShaderKey(program, inputsData, outputData);
-          const binary = this.getAndSaveBinary(key, () => {
-            return compileProgram(this.gpgpu, program, inputsData, outputData);
-          });
-          const shouldTimeProgram = this.activeTimers != null;
-          let query;
-          if (shouldTimeProgram) {
-            query = this.startTimer();
-          }
-          runProgram(this.gpgpu, binary, inputsData, outputData, customSetup);
-          dataToDispose.forEach((info) => this.disposeData(info.dataId));
-          if (shouldTimeProgram) {
-            query = this.endTimer(query);
-            this.activeTimers.push({
-              name: program.constructor.name,
-              query: this.getQueryTime(query),
-            });
-          }
-          if (
-            !Object(dist["env"])().getBool("WEBGL_LAZILY_UNPACK") &&
-            outData.isPacked &&
-            preventEagerUnpackingOfOutput === false
-          ) {
-            const unpacked = this.unpackTensor(output);
-            this.disposeData(output.dataId);
-            return unpacked;
-          }
-          return output;
-        }
-        compileAndRun(
-          program,
-          inputs,
-          outputDtype,
-          customSetup,
-          preventEagerUnpackingOfOutput = false
-        ) {
-          outputDtype = outputDtype || inputs[0].dtype;
-          const outInfo = this.runWebGLProgram(
-            program,
-            inputs,
-            outputDtype,
-            customSetup,
-            preventEagerUnpackingOfOutput
-          );
-          return Object(dist["engine"])().makeTensorFromDataId(
-            outInfo.dataId,
-            outInfo.shape,
-            outInfo.dtype
-          );
-        }
-        getAndSaveBinary(key, getBinary) {
-          if (!(key in this.binaryCache)) {
-            this.binaryCache[key] = getBinary();
-          }
-          return this.binaryCache[key];
-        }
-        getTextureManager() {
-          return this.textureManager;
-        }
-        dispose() {
-          if (this.disposed) {
-            return;
-          }
-          // Avoid disposing the compiled webgl programs during unit testing because
-          // it slows down test execution.
-          if (!Object(dist["env"])().getBool("IS_TEST")) {
-            const allKeys = Object.keys(this.binaryCache);
-            allKeys.forEach((key) => {
-              this.gpgpu.deleteProgram(this.binaryCache[key].webGLProgram);
-              delete this.binaryCache[key];
-            });
-          }
-          this.textureManager.dispose();
-          if (
-            this.canvas != null &&
-            typeof HTMLCanvasElement !== "undefined" &&
-            this.canvas instanceof HTMLCanvasElement
-          ) {
-            this.canvas.remove();
-          } else {
-            this.canvas = null;
-          }
-          if (this.gpgpuCreatedLocally) {
-            this.gpgpu.program = null;
-            this.gpgpu.dispose();
-          }
-          this.disposed = true;
-        }
-        floatPrecision() {
-          if (this.floatPrecisionValue == null) {
-            this.floatPrecisionValue = Object(dist["tidy"])(() => {
-              if (!Object(dist["env"])().get("WEBGL_RENDER_FLOAT32_ENABLED")) {
-                // Momentarily switching DEBUG flag to false so we don't throw an
-                // error trying to upload a small value.
-                const debugFlag = Object(dist["env"])().getBool("DEBUG");
-                Object(dist["env"])().set("DEBUG", false);
-                const underflowCheckValue = this.abs(Object(dist["scalar"])(1e-8)).dataSync()[0];
-                Object(dist["env"])().set("DEBUG", debugFlag);
-                if (underflowCheckValue > 0) {
-                  return 32;
-                }
-              }
-              return 16;
-            });
-          }
-          return this.floatPrecisionValue;
-        }
-        /** Returns the smallest representable number.  */
-        epsilon() {
-          return this.floatPrecision() === 32 ? EPSILON_FLOAT32 : EPSILON_FLOAT16;
-        }
-        uploadToGPU(dataId) {
-          const texData = this.texData.get(dataId);
-          const { shape, dtype, values, texture, usage, isPacked } = texData;
-          if (texture != null) {
-            // Array is already on GPU. No-op.
-            return;
-          }
-          const shouldTimeProgram = this.activeTimers != null;
-          let start;
-          if (shouldTimeProgram) {
-            start = dist["util"].now();
-          }
-          let texShape = texData.texShape;
-          if (texShape == null) {
-            texShape = getTextureShapeFromLogicalShape(shape, isPacked);
-            texData.texShape = texShape;
-          }
-          if (values != null) {
-            const shapeAs3D = getShapeAs3D(shape);
-            let program;
-            let width = texShape[1],
-              height = texShape[0];
-            const isByteArray = values instanceof Uint8Array;
-            if (isPacked) {
-              [width, height] = getPackedMatrixTextureShapeWidthHeight(texShape[0], texShape[1]);
-              program = new encode_matrix_packed_gpu_EncodeMatrixPackedProgram(
-                shapeAs3D,
-                [height, width],
-                isByteArray
-              );
-            } else {
-              program = new encode_matrix_gpu_EncodeMatrixProgram(
-                shapeAs3D,
-                [height, width],
-                isByteArray
-              );
-            }
-            const tempDenseInputHandle = this.makeTensorInfo([height, width], dtype);
-            if (isByteArray) {
-              this.texData.get(tempDenseInputHandle.dataId).usage = TextureUsage.PIXELS;
-            } else {
-              this.texData.get(tempDenseInputHandle.dataId).usage = TextureUsage.UPLOAD;
-            }
-            this.gpgpu.uploadDenseMatrixToTexture(
-              this.getTexture(tempDenseInputHandle.dataId),
-              width,
-              height,
-              values
-            );
-            // We want the output to remain packed regardless of the value of
-            // WEBGL_PACK.
-            const preventEagerUnpacking = true;
-            const encodedOutputTarget = this.runWebGLProgram(
-              program,
-              [tempDenseInputHandle],
-              dtype,
-              null,
-              preventEagerUnpacking
-            );
-            // Have the original texture assume the identity of the encoded output.
-            const outputTexData = this.texData.get(encodedOutputTarget.dataId);
-            texData.texture = outputTexData.texture;
-            texData.texShape = outputTexData.texShape;
-            texData.isPacked = outputTexData.isPacked;
-            texData.usage = outputTexData.usage;
-            this.disposeData(tempDenseInputHandle.dataId);
-            this.texData.delete(encodedOutputTarget.dataId);
-            // Once uploaded, don't store the values on cpu.
-            texData.values = null;
-            if (shouldTimeProgram) {
-              this.uploadWaitMs += dist["util"].now() - start;
-            }
-          } else {
-            const newTexture = this.acquireTexture(texShape, usage, dtype, isPacked);
-            texData.texture = newTexture;
-          }
-        }
-        convertAndCacheOnCPU(dataId, float32Values) {
-          const texData = this.texData.get(dataId);
-          const { dtype } = texData;
-          this.releaseGPUData(dataId);
-          if (float32Values != null) {
-            texData.values = float32ToTypedArray(float32Values, dtype);
-          }
-          return texData.values;
-        }
-        acquireTexture(texShape, texType, dtype, isPacked) {
-          this.numBytesInGPU += this.computeBytes(texShape, dtype);
-          if (
-            !this.warnedAboutMemory &&
-            this.numBytesInGPU > this.numMBBeforeWarning * 1024 * 1024
-          ) {
-            const mb = (this.numBytesInGPU / 1024 / 1024).toFixed(2);
-            this.warnedAboutMemory = true;
-            console.warn(
-              `High memory usage in GPU: ${mb} MB, ` + `most likely due to a memory leak`
-            );
-          }
-          return this.textureManager.acquireTexture(texShape, texType, isPacked);
-        }
-        computeBytes(shape, dtype) {
-          return shape[0] * shape[1] * dist["util"].bytesPerElement(dtype);
-        }
-      }
-      function float32ToTypedArray(a, dtype) {
-        if (dtype === "float32" || dtype === "complex64") {
-          return a;
-        } else if (dtype === "int32" || dtype === "bool") {
-          const result = dtype === "int32" ? new Int32Array(a.length) : new Uint8Array(a.length);
-          for (let i = 0; i < result.length; ++i) {
-            result[i] = Math.round(a[i]);
-          }
-          return result;
-        } else {
-          throw new Error(`Unknown dtype ${dtype}`);
-        }
-      }
-      //# sourceMappingURL=backend_webgl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/version.js
-      /** @license See the LICENSE file. */
-      // This code is auto-generated, do not modify this file!
-      const version_version = "2.0.1";
-
-      //# sourceMappingURL=version.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Div_impl.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function divImpl(a, b, backend) {
-        let program = new binaryop_gpu_BinaryOpProgram(DIV, a.shape, b.shape);
-        if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
-          program = new binaryop_packed_gpu_BinaryOpPackedProgram(
-            binaryop_packed_gpu_DIV,
-            a.shape,
-            b.shape,
-            true
-          );
-        }
-        const output = backend.runWebGLProgram(program, [a, b], "float32");
-        return output;
-      }
-      //# sourceMappingURL=Div_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Div.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const divConfig = {
-        kernelName: dist["Div"],
-        backendName: "webgl",
-        kernelFunc: ({ inputs, backend }) => {
-          const { a, b } = inputs;
-          const webglBackend = backend;
-          return divImpl(a, b, webglBackend);
-        },
-      };
-      //# sourceMappingURL=Div.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels_utils/from_pixels_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class from_pixels_gpu_FromPixelsProgram {
-        constructor(outputShape) {
-          this.variableNames = ["A"];
-          const glsl = getGlslDifferences();
-          const [height, width] = outputShape;
-          this.outputShape = outputShape;
-          this.userCode = `
-      void main() {
-        ivec3 coords = getOutputCoords();
-        int texR = coords[0];
-        int texC = coords[1];
-        int depth = coords[2];
-        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${width}.0, ${height}.0);
-
-        vec4 values = ${glsl.texture2D}(A, uv);
-        float value;
-        if (depth == 0) {
-          value = values.r;
-        } else if (depth == 1) {
-          value = values.g;
-        } else if (depth == 2) {
-          value = values.b;
-        } else if (depth == 3) {
-          value = values.a;
-        }
-
-        setOutput(floor(value * 255.0 + 0.5));
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=from_pixels_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels_utils/from_pixels_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2018 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class from_pixels_packed_gpu_FromPixelsPackedProgram {
-        constructor(outputShape) {
-          this.variableNames = ["A"];
-          this.packedInputs = false;
-          this.packedOutput = true;
-          const glsl = getGlslDifferences();
-          const [height, width] = outputShape;
-          this.outputShape = outputShape;
-          this.userCode = `
-      void main() {
-        ivec3 coords = getOutputCoords();
-        int texR = coords[0];
-        int texC = coords[1];
-        int depth = coords[2];
-
-        vec4 result = vec4(0.);
-
-        for(int row=0; row<=1; row++) {
-          for(int col=0; col<=1; col++) {
-            texC = coords[1] + row;
-            depth = coords[2] + col;
-
-            vec2 uv = (vec2(texC, texR) + halfCR) /
-                       vec2(${width}.0, ${height}.0);
-            vec4 values = ${glsl.texture2D}(A, uv);
-            float value;
-            if (depth == 0) {
-              value = values.r;
-            } else if (depth == 1) {
-              value = values.g;
-            } else if (depth == 2) {
-              value = values.b;
-            } else if (depth == 3) {
-              value = values.a;
-            }
-
-            result[row * 2 + col] = floor(value * 255.0 + 0.5);
-          }
-        }
-
-        ${glsl.output} = result;
-      }
-    `;
-        }
-      }
-      //# sourceMappingURL=from_pixels_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const fromPixelsConfig = {
-        kernelName: dist["FromPixels"],
-        backendName: "webgl",
-        kernelFunc: fromPixels,
-      };
-      let fromPixels2DContext;
-      function fromPixels(args) {
-        const { inputs, backend, attrs } = args;
-        let { pixels } = inputs;
-        const { numChannels } = attrs;
-        const isVideo =
-          typeof HTMLVideoElement !== "undefined" && pixels instanceof HTMLVideoElement;
-        const isImage =
-          typeof HTMLImageElement !== "undefined" && pixels instanceof HTMLImageElement;
-        const [width, height] = isVideo
-          ? [pixels.videoWidth, pixels.videoHeight]
-          : [pixels.width, pixels.height];
-        const texShape = [height, width];
-        const outShape = [height, width, numChannels];
-        if (isImage || isVideo) {
-          if (fromPixels2DContext == null) {
-            fromPixels2DContext = document.createElement("canvas").getContext("2d");
-          }
-          fromPixels2DContext.canvas.width = width;
-          fromPixels2DContext.canvas.height = height;
-          fromPixels2DContext.drawImage(pixels, 0, 0, width, height);
-          pixels = fromPixels2DContext.canvas;
-        }
-        const tempPixelHandle = backend.makeTensorInfo(texShape, "int32");
-        // This is a byte texture with pixels.
-        backend.texData.get(tempPixelHandle.dataId).usage = TextureUsage.PIXELS;
-        backend.gpgpu.uploadPixelDataToTexture(backend.getTexture(tempPixelHandle.dataId), pixels);
-        const program = Object(dist["env"])().getBool("WEBGL_PACK")
-          ? new from_pixels_packed_gpu_FromPixelsPackedProgram(outShape)
-          : new from_pixels_gpu_FromPixelsProgram(outShape);
-        const res = backend.runWebGLProgram(program, [tempPixelHandle], "int32");
-        backend.disposeData(tempPixelHandle.dataId);
-        return res;
-      }
-      //# sourceMappingURL=FromPixels.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/base.js + 3 modules
-      var base = __webpack_require__(31);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/shared.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // Import shared functionality from tfjs-backend-cpu without triggering
-      // side effects.
-      // tslint:disable-next-line: no-imports-from-dist
-
-      const { maxImpl: maxImplCPU, transposeImpl: transposeImplCPU } = base["b" /* shared */];
-
-      //# sourceMappingURL=shared.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/reduce.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function reduce(x, dtype, reductionType, backend) {
-        const [batchSize, inSize] = x.shape;
-        const windowSize = dist["backend_util"].computeOptimalWindowSize(inSize);
-        const reduceInfo = { windowSize, inSize, batchSize };
-        const program = new ReduceProgram(reduceInfo, reductionType);
-        const output = backend.runWebGLProgram(program, [x], dtype);
-        if (output.shape[1] === 1) {
-          return output;
-        }
-        return reduce(output, dtype, reductionType, backend);
-      }
-      //# sourceMappingURL=reduce.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/reshape.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function packedReshape(input, afterShape, backend) {
-        const input3DShape = [getBatchDim(input.shape), ...getRowsCols(input.shape)];
-        const input3D = {
-          dtype: input.dtype,
-          shape: input3DShape,
-          dataId: input.dataId,
-        };
-        const afterShapeAs3D = [getBatchDim(afterShape), ...getRowsCols(afterShape)];
-        const program = new reshape_packed_gpu_ReshapePackedProgram(afterShapeAs3D, input3DShape);
-        const preventEagerUnpackingOfOutput = true;
-        const output = backend.runWebGLProgram(
-          program,
-          [input3D],
-          input.dtype,
-          null /* customSetup */,
-          preventEagerUnpackingOfOutput
-        );
-        return { dataId: output.dataId, shape: afterShape, dtype: output.dtype };
-      }
-      function reshape(x, afterShape, backend) {
-        const xTexData = backend.texData.get(x.dataId);
-        if (
-          xTexData.isPacked &&
-          !isReshapeFree(x.shape, afterShape) &&
-          !(xTexData.texture !== null && isReshapeFree(xTexData.shape, afterShape))
-        ) {
-          return packedReshape(x, afterShape, backend);
-        }
-        return { dataId: x.dataId, shape: afterShape, dtype: x.dtype };
-      }
-      //# sourceMappingURL=reshape.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Max_impl.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function maxImpl(x, reduceShape, outShape, backend) {
-        const inSize = dist["util"].sizeFromShape(reduceShape);
-        const xSize = dist["util"].sizeFromShape(x.shape);
-        const batchSize = xSize / inSize;
-        const reshapedInput = reshape(x, [batchSize, inSize], backend);
-        const reduced = reduce(reshapedInput, x.dtype, "max", backend);
-        if (reshapedInput.dataId !== x.dataId) {
-          // dispose the output of the packed reshape.
-          backend.disposeData(reshapedInput.dataId);
-        }
-        return reshape(reduced, outShape, backend);
-      }
-      //# sourceMappingURL=Max_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/transpose_gpu.js
-      /**
-       * @license
-       * Copyright 2017 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class transpose_gpu_TransposeProgram {
-        constructor(aShape, newDim) {
-          this.variableNames = ["A"];
-          const outputShape = new Array(aShape.length);
-          for (let i = 0; i < outputShape.length; i++) {
-            outputShape[i] = aShape[newDim[i]];
-          }
-          this.outputShape = outputShape;
-          this.rank = outputShape.length;
-          const dtype = getCoordsDataType(this.rank);
-          const switched = getSwitchedCoords(newDim);
-          this.userCode = `
-    void main() {
-      ${dtype} resRC = getOutputCoords();
-      setOutput(getA(${switched}));
-    }
-    `;
-        }
-      }
-      function getSwitchedCoords(newDim) {
-        const rank = newDim.length;
-        if (rank > 6) {
-          throw Error(`Transpose for rank ${rank} is not yet supported`);
-        }
-        const originalOrder = ["resRC.x", "resRC.y", "resRC.z", "resRC.w", "resRC.u", "resRC.v"];
-        const switchedCoords = new Array(rank);
-        for (let i = 0; i < newDim.length; i++) {
-          switchedCoords[newDim[i]] = originalOrder[i];
-        }
-        return switchedCoords.join();
-      }
-      //# sourceMappingURL=transpose_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/transpose_packed_gpu.js
-      /**
-       * @license
-       * Copyright 2019 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      class transpose_packed_gpu_TransposePackedProgram {
-        constructor(aShape, newDim) {
-          this.variableNames = ["A"];
-          this.packedInputs = true;
-          this.packedOutput = true;
-          const outputShape = new Array(aShape.length);
-          for (let i = 0; i < outputShape.length; i++) {
-            outputShape[i] = aShape[newDim[i]];
-          }
-          this.outputShape = outputShape;
-          this.rank = outputShape.length;
-          if (this.rank > 6) {
-            throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);
-          }
-          const dtype = getCoordsDataType(this.rank);
-          const outputOrder = getVecChannels("rc", this.rank);
-          const switchedOrder = new Array(this.rank);
-          for (let i = 0; i < newDim.length; i++) {
-            switchedOrder[newDim[i]] = outputOrder[i];
-          }
-          const innerDims = `vec2(${switchedOrder.slice(-2).join()})`;
-          const nextColumn = `++${outputOrder[this.rank - 1]} < ${outputShape[this.rank - 1]}`;
-          const getc = `getChannel(getA(${switchedOrder.join()}), ${innerDims})`;
-          this.userCode = `
-    void main() {
-      ${dtype} rc = getOutputCoords();
-      vec4 result = vec4(0.);
-      result[0] = ${getc};
-      if(${nextColumn}) {
-        result[1] = ${getc};
-      }
-      --${outputOrder[this.rank - 1]};
-      if(++${outputOrder[this.rank - 2]} < ${outputShape[this.rank - 2]}) {
-        result[2] = ${getc};
-        if(${nextColumn}) {
-          result[3] = ${getc};
-        }
-      }
-      setOutput(result);
-    }
-    `;
-        }
-      }
-      //# sourceMappingURL=transpose_packed_gpu.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transpose_impl.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function transposeImpl(x, perm, backend) {
-        const program = Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS")
-          ? new transpose_packed_gpu_TransposePackedProgram(x.shape, perm)
-          : new transpose_gpu_TransposeProgram(x.shape, perm);
-        return backend.runWebGLProgram(program, [x], x.dtype);
-      }
-
-      //# sourceMappingURL=Transpose_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Max.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const maxConfig = {
-        kernelName: dist["Max"],
-        backendName: "webgl",
-        kernelFunc: ({ inputs, attrs, backend }) => {
-          const { x } = inputs;
-          const { reductionIndices } = attrs;
-          const webglBackend = backend;
-          const xRank = x.shape.length;
-          const origAxes = dist["util"].parseAxisParam(reductionIndices, x.shape);
-          let axes = origAxes;
-          const permutedAxes = dist["backend_util"].getAxesPermutation(axes, xRank);
-          const maxInputIsTransposed = permutedAxes != null;
-          const shouldExecuteOnCPU = webglBackend.shouldExecuteOnCPU([x]);
-          let maxInput = x;
-          if (maxInputIsTransposed) {
-            if (shouldExecuteOnCPU) {
-              const xTexData = webglBackend.texData.get(maxInput.dataId);
-              const values = xTexData.values;
-              const newShape = new Array(xRank);
-              for (let i = 0; i < newShape.length; i++) {
-                newShape[i] = x.shape[permutedAxes[i]];
-              }
-              const maxInputValues = transposeImplCPU(
-                values,
-                x.shape,
-                x.dtype,
-                permutedAxes,
-                newShape
-              );
-              maxInput = webglBackend.makeTensorInfo(newShape, x.dtype);
-              const maxInputData = webglBackend.texData.get(maxInput.dataId);
-              maxInputData.values = maxInputValues;
-            } else {
-              maxInput = transposeImpl(x, permutedAxes, webglBackend);
-            }
-            axes = dist["backend_util"].getInnerMostAxes(axes.length, xRank);
-          }
-          dist["backend_util"].assertAxesAreInnerMostDims("max", axes, xRank);
-          const [maxOutShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            maxInput.shape,
-            axes
-          );
-          let out;
-          if (shouldExecuteOnCPU) {
-            const xTexData = webglBackend.texData.get(maxInput.dataId);
-            const values = xTexData.values;
-            const outValues = maxImplCPU(
-              values,
-              dist["util"].sizeFromShape(reduceShape),
-              maxOutShape,
-              x.dtype
-            );
-            out = webglBackend.makeTensorInfo(maxOutShape, x.dtype);
-            const outData = webglBackend.texData.get(out.dataId);
-            outData.values = outValues;
-          } else {
-            out = maxImpl(maxInput, reduceShape, maxOutShape, webglBackend);
-          }
-          if (maxInputIsTransposed) {
-            webglBackend.disposeData(maxInput.dataId);
-          }
-          return out;
-        },
-      };
-      //# sourceMappingURL=Max.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolWithArgmax_impl.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function maxPoolWithArgmaxImpl(x, includeBatchInIndex, convInfo, backend) {
-        let program = new Pool2DProgram(convInfo, "max", false);
-        const poolOutput = backend.runWebGLProgram(program, [x], "float32");
-        program = new Pool2DProgram(convInfo, "max", true, true, includeBatchInIndex);
-        const indexOutput = backend.runWebGLProgram(program, [x], "float32");
-        return [poolOutput, indexOutput];
-      }
-      //# sourceMappingURL=MaxPoolWithArgmax_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolWithArgmax.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const maxPoolWithArgmaxConfig = {
-        kernelName: dist["MaxPoolWithArgmax"],
-        backendName: "webgl",
-        kernelFunc: ({ inputs, attrs, backend }) => {
-          const { x } = inputs;
-          const { filterSize, strides, pad, includeBatchInIndex } = attrs;
-          const webglBackend = backend;
-          dist["util"].assert(
-            x.shape.length === 4,
-            () => `Error in maxPool: input must be rank 4 but got rank ${x.shape.length}.`
-          );
-          const dilations = [1, 1];
-          dist["util"].assert(
-            dist["backend_util"].eitherStridesOrDilationsAreOne(strides, dilations),
-            () =>
-              "Error in maxPool: Either strides or dilations must be 1. " +
-              `Got strides ${strides} and dilations '${dilations}'`
-          );
-          const convInfo = dist["backend_util"].computePool2DInfo(
-            x.shape,
-            filterSize,
-            strides,
-            dilations,
-            pad
-          );
-          const [result, indexes] = maxPoolWithArgmaxImpl(
-            x,
-            includeBatchInIndex,
-            convInfo,
-            webglBackend
-          );
-          return [result, indexes];
-        },
-      };
-      //# sourceMappingURL=MaxPoolWithArgmax.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV3.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const nonMaxSuppressionV3Config = {
-        kernelName: dist["NonMaxSuppressionV3"],
-        backendName: "webgl",
-        kernelFunc: ({ inputs, backend, attrs }) => {
-          dist["backend_util"].warn(
-            "tf.nonMaxSuppression() in webgl locks the UI thread. " +
-              "Call tf.nonMaxSuppressionAsync() instead"
-          );
-          const { boxes, scores } = inputs;
-          const { maxOutputSize, iouThreshold, scoreThreshold } = attrs;
-          const gpuBackend = backend;
-          const boxesVals = gpuBackend.readSync(boxes.dataId);
-          const scoresVals = gpuBackend.readSync(scores.dataId);
-          const maxOutputSizeVal = maxOutputSize;
-          const iouThresholdVal = iouThreshold;
-          const scoreThresholdVal = scoreThreshold;
-          return dist["kernel_impls"].nonMaxSuppressionV3(
-            boxesVals,
-            scoresVals,
-            maxOutputSizeVal,
-            iouThresholdVal,
-            scoreThresholdVal
-          );
-        },
-      };
-      //# sourceMappingURL=NonMaxSuppressionV3.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV5.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const nonMaxSuppressionV5 = dist["kernel_impls"].nonMaxSuppressionV5;
-      const nonMaxSuppressionV5Config = {
-        kernelName: dist["NonMaxSuppressionV5"],
-        backendName: "webgl",
-        kernelFunc: ({ inputs, backend, attrs }) => {
-          dist["backend_util"].warn(
-            "tf.nonMaxSuppression() in webgl locks the UI thread. " +
-              "Call tf.nonMaxSuppressionAsync() instead"
-          );
-          const { boxes, scores } = inputs;
-          const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;
-          const gpuBackend = backend;
-          const boxesVals = gpuBackend.readSync(boxes.dataId);
-          const scoresVals = gpuBackend.readSync(scores.dataId);
-          const maxOutputSizeVal = maxOutputSize;
-          const iouThresholdVal = iouThreshold;
-          const scoreThresholdVal = scoreThreshold;
-          const softNmsSigmaVal = softNmsSigma;
-          const { selectedIndices, selectedScores } = nonMaxSuppressionV5(
-            boxesVals,
-            scoresVals,
-            maxOutputSizeVal,
-            iouThresholdVal,
-            scoreThresholdVal,
-            softNmsSigmaVal
-          );
-          return [selectedIndices, selectedScores];
-        },
-      };
-      //# sourceMappingURL=NonMaxSuppressionV5.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Square.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const squareConfig = {
-        kernelName: dist["Square"],
-        backendName: "webgl",
-        kernelFunc: ({ inputs, backend }) => {
-          const { x } = inputs;
-          const webglBackend = backend;
-          const program = new UnaryOpProgram(x.shape, SQUARE);
-          return webglBackend.runWebGLProgram(program, [x], x.dtype);
-        },
-      };
-      //# sourceMappingURL=Square.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SquaredDifference.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const squaredDifferenceConfig = {
-        kernelName: dist["SquaredDifference"],
-        backendName: "webgl",
-        kernelFunc: ({ inputs, backend }) => {
-          const { a, b } = inputs;
-          const SQUARED_DIFFERENCE = "return (a - b) * (a - b);";
-          const webGLBackend = backend;
-          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
-            ? new binaryop_packed_gpu_BinaryOpPackedProgram(SQUARED_DIFFERENCE, a.shape, b.shape)
-            : new binaryop_gpu_BinaryOpProgram(SQUARED_DIFFERENCE, a.shape, b.shape);
-          return webGLBackend.compileAndRun(program, [a, b]);
-        },
-      };
-      //# sourceMappingURL=SquaredDifference.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transpose.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const transposeConfig = {
-        kernelName: dist["Transpose"],
-        backendName: "webgl",
-        kernelFunc: ({ inputs, attrs, backend }) => {
-          const { x } = inputs;
-          const { perm } = attrs;
-          const webglBackend = backend;
-          const xRank = x.shape.length;
-          const newShape = new Array(xRank);
-          for (let i = 0; i < newShape.length; i++) {
-            newShape[i] = x.shape[perm[i]];
-          }
-          let out;
-          if (webglBackend.shouldExecuteOnCPU([x])) {
-            const xTexData = webglBackend.texData.get(x.dataId);
-            const values = xTexData.values;
-            const outValues = transposeImplCPU(values, x.shape, x.dtype, perm, newShape);
-            out = webglBackend.makeTensorInfo(newShape, x.dtype);
-            const outData = webglBackend.texData.get(out.dataId);
-            outData.values = outValues;
-          } else {
-            out = transposeImpl(x, perm, webglBackend);
-          }
-          return out;
-        },
-      };
-      //# sourceMappingURL=Transpose.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/register_all_kernels.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // List all kernel configs here
-      const kernelConfigs = [
-        maxConfig,
-        fromPixelsConfig,
-        divConfig,
-        nonMaxSuppressionV3Config,
-        nonMaxSuppressionV5Config,
-        squareConfig,
-        squaredDifferenceConfig,
-        transposeConfig,
-        maxPoolWithArgmaxConfig,
-      ];
-      for (const kernelConfig of kernelConfigs) {
-        Object(dist["registerKernel"])(kernelConfig);
-      }
-      //# sourceMappingURL=register_all_kernels.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // WebGL specific utils.
-
-      /**
-       * Enforce use of half precision textures if available on the platform.
-       */
-      /** @doc {heading: 'Environment', namespace: 'webgl'} */
-      function forceHalfFloat() {
-        Object(dist["env"])().set("WEBGL_FORCE_F16_TEXTURES", true);
-      }
-      //# sourceMappingURL=webgl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/index.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      if (dist["device_util"].isBrowser()) {
-        Object(dist["registerBackend"])(
-          "webgl",
-          () => new backend_webgl_MathBackendWebGL(),
-          2 /* priority */
-        );
-      }
-
-      // Export webgl utilities
-
-      // Export forceHalfFlost under webgl namespace for the union bundle.
-
-      const webgl = { forceHalfFloat: forceHalfFloat };
-      //# sourceMappingURL=index.js.map
-
-      /***/
-    },
-    /* 87 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      // ESM COMPAT FLAG
-      __webpack_require__.r(__webpack_exports__);
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "CallbackList", function () {
-        return /* reexport */ CallbackList;
-      });
-      __webpack_require__.d(__webpack_exports__, "CustomCallback", function () {
-        return /* reexport */ base_callbacks_CustomCallback;
-      });
-      __webpack_require__.d(__webpack_exports__, "History", function () {
-        return /* reexport */ History;
-      });
-      __webpack_require__.d(__webpack_exports__, "Callback", function () {
-        return /* reexport */ callbacks_Callback;
-      });
-      __webpack_require__.d(__webpack_exports__, "callbacks", function () {
-        return /* reexport */ callbacks_callbacks;
-      });
-      __webpack_require__.d(__webpack_exports__, "EarlyStopping", function () {
-        return /* reexport */ callbacks_EarlyStopping;
-      });
-      __webpack_require__.d(__webpack_exports__, "InputSpec", function () {
-        return /* reexport */ InputSpec;
-      });
-      __webpack_require__.d(__webpack_exports__, "SymbolicTensor", function () {
-        return /* reexport */ topology_SymbolicTensor;
-      });
-      __webpack_require__.d(__webpack_exports__, "LayersModel", function () {
-        return /* reexport */ training_LayersModel;
-      });
-      __webpack_require__.d(__webpack_exports__, "input", function () {
-        return /* reexport */ exports_input;
-      });
-      __webpack_require__.d(__webpack_exports__, "loadLayersModel", function () {
-        return /* reexport */ loadLayersModel;
-      });
-      __webpack_require__.d(__webpack_exports__, "model", function () {
-        return /* reexport */ exports_model;
-      });
-      __webpack_require__.d(__webpack_exports__, "registerCallbackConstructor", function () {
-        return /* reexport */ registerCallbackConstructor;
-      });
-      __webpack_require__.d(__webpack_exports__, "sequential", function () {
-        return /* reexport */ sequential;
-      });
-      __webpack_require__.d(__webpack_exports__, "RNN", function () {
-        return /* reexport */ recurrent_RNN;
-      });
-      __webpack_require__.d(__webpack_exports__, "Sequential", function () {
-        return /* reexport */ models_Sequential;
-      });
-      __webpack_require__.d(__webpack_exports__, "LayerVariable", function () {
-        return /* reexport */ variables_LayerVariable;
-      });
-      __webpack_require__.d(__webpack_exports__, "version_layers", function () {
-        return /* reexport */ version;
-      });
-      __webpack_require__.d(__webpack_exports__, "constraints", function () {
-        return /* reexport */ exports_constraints_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "initializers", function () {
-        return /* reexport */ exports_initializers_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "layers", function () {
-        return /* reexport */ exports_layers_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "metrics", function () {
-        return /* reexport */ exports_metrics_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "models", function () {
-        return /* reexport */ exports_models_namespaceObject;
-      });
-      __webpack_require__.d(__webpack_exports__, "regularizers", function () {
-        return /* reexport */ exports_regularizers_namespaceObject;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_constraints.js
-      var exports_constraints_namespaceObject = {};
-      __webpack_require__.r(exports_constraints_namespaceObject);
-      __webpack_require__.d(exports_constraints_namespaceObject, "maxNorm", function () {
-        return maxNorm;
-      });
-      __webpack_require__.d(exports_constraints_namespaceObject, "unitNorm", function () {
-        return unitNorm;
-      });
-      __webpack_require__.d(exports_constraints_namespaceObject, "nonNeg", function () {
-        return nonNeg;
-      });
-      __webpack_require__.d(exports_constraints_namespaceObject, "minMaxNorm", function () {
-        return minMaxNorm;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_initializers.js
-      var exports_initializers_namespaceObject = {};
-      __webpack_require__.r(exports_initializers_namespaceObject);
-      __webpack_require__.d(exports_initializers_namespaceObject, "zeros", function () {
-        return zeros;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "ones", function () {
-        return exports_initializers_ones;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "constant", function () {
-        return constant;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "randomUniform", function () {
-        return randomUniform;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "randomNormal", function () {
-        return exports_initializers_randomNormal;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "truncatedNormal", function () {
-        return truncatedNormal;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "identity", function () {
-        return identity;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "varianceScaling", function () {
-        return varianceScaling;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "glorotUniform", function () {
-        return glorotUniform;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "glorotNormal", function () {
-        return glorotNormal;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "heNormal", function () {
-        return heNormal;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "heUniform", function () {
-        return heUniform;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "leCunNormal", function () {
-        return leCunNormal;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "leCunUniform", function () {
-        return leCunUniform;
-      });
-      __webpack_require__.d(exports_initializers_namespaceObject, "orthogonal", function () {
-        return orthogonal;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_layers.js
-      var exports_layers_namespaceObject = {};
-      __webpack_require__.r(exports_layers_namespaceObject);
-      __webpack_require__.d(exports_layers_namespaceObject, "inputLayer", function () {
-        return exports_layers_inputLayer;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "elu", function () {
-        return exports_layers_elu;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "reLU", function () {
-        return reLU;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "leakyReLU", function () {
-        return leakyReLU;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "prelu", function () {
-        return prelu;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "softmax", function () {
-        return softmax;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "thresholdedReLU", function () {
-        return thresholdedReLU;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "conv1d", function () {
-        return exports_layers_conv1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "conv2d", function () {
-        return exports_layers_conv2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "conv2dTranspose", function () {
-        return conv2dTranspose;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "conv3d", function () {
-        return exports_layers_conv3d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "separableConv2d", function () {
-        return separableConv2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "cropping2D", function () {
-        return cropping2D;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "upSampling2d", function () {
-        return upSampling2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "depthwiseConv2d", function () {
-        return exports_layers_depthwiseConv2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "activation", function () {
-        return exports_layers_activation;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "dense", function () {
-        return dense;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "dropout", function () {
-        return exports_layers_dropout;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "spatialDropout1d", function () {
-        return spatialDropout1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "flatten", function () {
-        return exports_layers_flatten;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "repeatVector", function () {
-        return repeatVector;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "reshape", function () {
-        return reshape;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "permute", function () {
-        return permute;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "embedding", function () {
-        return embedding;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "add", function () {
-        return exports_layers_add;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "average", function () {
-        return exports_layers_average;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "concatenate", function () {
-        return exports_layers_concatenate;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "maximum", function () {
-        return exports_layers_maximum;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "minimum", function () {
-        return exports_layers_minimum;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "multiply", function () {
-        return exports_layers_multiply;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "dot", function () {
-        return exports_layers_dot;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "batchNormalization", function () {
-        return exports_layers_batchNormalization;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "layerNormalization", function () {
-        return layerNormalization;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "zeroPadding2d", function () {
-        return zeroPadding2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "averagePooling1d", function () {
-        return averagePooling1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "avgPool1d", function () {
-        return avgPool1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "avgPooling1d", function () {
-        return avgPooling1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "averagePooling2d", function () {
-        return averagePooling2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "avgPool2d", function () {
-        return avgPool2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "avgPooling2d", function () {
-        return avgPooling2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "averagePooling3d", function () {
-        return averagePooling3d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "avgPool3d", function () {
-        return avgPool3d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "avgPooling3d", function () {
-        return avgPooling3d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "globalAveragePooling1d", function () {
-        return globalAveragePooling1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "globalAveragePooling2d", function () {
-        return globalAveragePooling2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "globalMaxPooling1d", function () {
-        return globalMaxPooling1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "globalMaxPooling2d", function () {
-        return globalMaxPooling2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "maxPooling1d", function () {
-        return maxPooling1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "maxPooling2d", function () {
-        return maxPooling2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "maxPooling3d", function () {
-        return maxPooling3d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "gru", function () {
-        return gru;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "gruCell", function () {
-        return gruCell;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "lstm", function () {
-        return lstm;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "lstmCell", function () {
-        return lstmCell;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "simpleRNN", function () {
-        return simpleRNN;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "simpleRNNCell", function () {
-        return simpleRNNCell;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "rnn", function () {
-        return exports_layers_rnn;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "stackedRNNCells", function () {
-        return stackedRNNCells;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "bidirectional", function () {
-        return bidirectional;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "timeDistributed", function () {
-        return timeDistributed;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "globalMaxPool1d", function () {
-        return globalMaxPool1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "globalMaxPool2d", function () {
-        return globalMaxPool2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "maxPool1d", function () {
-        return maxPool1d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "maxPool2d", function () {
-        return maxPool2d;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "Layer", function () {
-        return topology_Layer;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "RNN", function () {
-        return recurrent_RNN;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "RNNCell", function () {
-        return recurrent_RNNCell;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "input", function () {
-        return exports_input;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "gaussianNoise", function () {
-        return gaussianNoise;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "gaussianDropout", function () {
-        return gaussianDropout;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "alphaDropout", function () {
-        return alphaDropout;
-      });
-      __webpack_require__.d(exports_layers_namespaceObject, "masking", function () {
-        return masking;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_metrics.js
-      var exports_metrics_namespaceObject = {};
-      __webpack_require__.r(exports_metrics_namespaceObject);
-      __webpack_require__.d(exports_metrics_namespaceObject, "binaryAccuracy", function () {
-        return exports_metrics_binaryAccuracy;
-      });
-      __webpack_require__.d(exports_metrics_namespaceObject, "binaryCrossentropy", function () {
-        return exports_metrics_binaryCrossentropy;
-      });
-      __webpack_require__.d(
-        exports_metrics_namespaceObject,
-        "sparseCategoricalAccuracy",
-        function () {
-          return exports_metrics_sparseCategoricalAccuracy;
-        }
-      );
-      __webpack_require__.d(exports_metrics_namespaceObject, "categoricalAccuracy", function () {
-        return exports_metrics_categoricalAccuracy;
-      });
-      __webpack_require__.d(
-        exports_metrics_namespaceObject,
-        "categoricalCrossentropy",
-        function () {
-          return exports_metrics_categoricalCrossentropy;
-        }
-      );
-      __webpack_require__.d(exports_metrics_namespaceObject, "precision", function () {
-        return exports_metrics_precision;
-      });
-      __webpack_require__.d(exports_metrics_namespaceObject, "recall", function () {
-        return exports_metrics_recall;
-      });
-      __webpack_require__.d(exports_metrics_namespaceObject, "cosineProximity", function () {
-        return exports_metrics_cosineProximity;
-      });
-      __webpack_require__.d(exports_metrics_namespaceObject, "meanAbsoluteError", function () {
-        return exports_metrics_meanAbsoluteError;
-      });
-      __webpack_require__.d(
-        exports_metrics_namespaceObject,
-        "meanAbsolutePercentageError",
-        function () {
-          return exports_metrics_meanAbsolutePercentageError;
-        }
-      );
-      __webpack_require__.d(exports_metrics_namespaceObject, "MAPE", function () {
-        return exports_metrics_MAPE;
-      });
-      __webpack_require__.d(exports_metrics_namespaceObject, "mape", function () {
-        return exports_metrics_mape;
-      });
-      __webpack_require__.d(exports_metrics_namespaceObject, "meanSquaredError", function () {
-        return exports_metrics_meanSquaredError;
-      });
-      __webpack_require__.d(exports_metrics_namespaceObject, "MSE", function () {
-        return exports_metrics_MSE;
-      });
-      __webpack_require__.d(exports_metrics_namespaceObject, "mse", function () {
-        return exports_metrics_mse;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_models.js
-      var exports_models_namespaceObject = {};
-      __webpack_require__.r(exports_models_namespaceObject);
-      __webpack_require__.d(exports_models_namespaceObject, "modelFromJSON", function () {
-        return modelFromJSON;
-      });
-
-      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_regularizers.js
-      var exports_regularizers_namespaceObject = {};
-      __webpack_require__.r(exports_regularizers_namespaceObject);
-      __webpack_require__.d(exports_regularizers_namespaceObject, "l1l2", function () {
-        return l1l2;
-      });
-      __webpack_require__.d(exports_regularizers_namespaceObject, "l1", function () {
-        return exports_regularizers_l1;
-      });
-      __webpack_require__.d(exports_regularizers_namespaceObject, "l2", function () {
-        return exports_regularizers_l2;
-      });
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
-      var dist = __webpack_require__(0);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/backend/common.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      let _epsilon;
-      /**
-       * Returns the value of the fuzz factor used in numeric expressions.
-       */
-      function common_epsilon() {
-        if (_epsilon == null) {
-          _epsilon = Object(dist["backend"])().epsilon();
-        }
-        return _epsilon;
-      }
-      /**
-       * Sets the value of the fuzz factor used in numeric expressions.
-       * @param e New value of epsilon.
-       */
-      function setEpsilon(e) {
-        _epsilon = e;
-      }
-      /**
-       * Returns the default image data format convention.
-       */
-      function imageDataFormat() {
-        return "channelsLast";
-      }
-      //# sourceMappingURL=common.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/errors.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Explicit error types.
-       *
-       * See the following link for more information about why the code includes
-       * calls to setPrototypeOf:
-       *
-       * https://github.com/Microsoft/TypeScript-wiki/blob/master/Breaking-Changes.md#extending-built-ins-like-error-array-and-map-may-no-longer-work
-       */
-      // tslint:enable
-      /**
-       * Equivalent of Python's AttributeError.
-       */
-      class AttributeError extends Error {
-        constructor(message) {
-          super(message);
-          // Set the prototype explicitly.
-          Object.setPrototypeOf(this, AttributeError.prototype);
-        }
-      }
-      /**
-       * Equivalent of Python's RuntimeError.
-       */
-      class RuntimeError extends Error {
-        constructor(message) {
-          super(message);
-          // Set the prototype explicitly.
-          Object.setPrototypeOf(this, RuntimeError.prototype);
-        }
-      }
-      /**
-       * Equivalent of Python's ValueError.
-       */
-      class ValueError extends Error {
-        constructor(message) {
-          super(message);
-          // Set the prototype explicitly.
-          Object.setPrototypeOf(this, ValueError.prototype);
-        }
-      }
-      /**
-       * Equivalent of Python's NotImplementedError.
-       */
-      class NotImplementedError extends Error {
-        constructor(message) {
-          super(message);
-          // Set the prototype explicitly.
-          Object.setPrototypeOf(this, NotImplementedError.prototype);
-        }
-      }
-      /**
-       * Equivalent of Python's AssertionError.
-       */
-      class AssertionError extends Error {
-        constructor(message) {
-          super(message);
-          // Set the prototype explicitly.
-          Object.setPrototypeOf(this, AssertionError.prototype);
-        }
-      }
-      /**
-       * Equivalent of Python's IndexError.
-       */
-      class IndexError extends Error {
-        constructor(message) {
-          super(message);
-          // Set the prototype explicitly.
-          Object.setPrototypeOf(this, IndexError.prototype);
-        }
-      }
-      //# sourceMappingURL=errors.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/generic_utils.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original source: utils/generic_utils.py */
-
-      // tslint:enable
-      /**
-       * If `value` is an Array, equivalent to Python's `value * numValues`.
-       * If `value` is not an Array, equivalent to Python's `[value] * numValues`
-       */
-      // tslint:disable-next-line:no-any
-      function pyListRepeat(value, numValues) {
-        if (Array.isArray(value)) {
-          // tslint:disable-next-line:no-any
-          let newArray = [];
-          for (let i = 0; i < numValues; i++) {
-            newArray = newArray.concat(value);
-          }
-          return newArray;
-        } else {
-          const newArray = new Array(numValues);
-          newArray.fill(value);
-          return newArray;
-        }
-      }
-      function assert(val, message) {
-        if (!val) {
-          throw new AssertionError(message);
-        }
-      }
-      /**
-       * Count the number of elements of the `array` that are equal to `reference`.
-       */
-      function generic_utils_count(array, refernce) {
-        let counter = 0;
-        for (const item of array) {
-          if (item === refernce) {
-            counter++;
-          }
-        }
-        return counter;
-      }
-      /**
-       * If an array is of length 1, just return the first element. Otherwise, return
-       * the full array.
-       * @param tensors
-       */
-      function singletonOrArray(xs) {
-        if (xs.length === 1) {
-          return xs[0];
-        }
-        return xs;
-      }
-      /**
-       * Normalizes a list/tensor into a list.
-       *
-       * If a tensor is passed, we return
-       * a list of size 1 containing the tensor.
-       *
-       * @param x target object to be normalized.
-       */
-      // tslint:disable-next-line:no-any
-      function toList(x) {
-        if (Array.isArray(x)) {
-          return x;
-        }
-        return [x];
-      }
-      /**
-       * Generate a UID for a list
-       */
-      // tslint:disable-next-line:no-any
-      function objectListUid(objs) {
-        const objectList = toList(objs);
-        let retVal = "";
-        for (const obj of objectList) {
-          if (obj.id == null) {
-            throw new ValueError(`Object ${obj} passed to objectListUid without an id`);
-          }
-          if (retVal !== "") {
-            retVal = retVal + ", ";
-          }
-          retVal = `${retVal}${Math.abs(obj.id)}`;
-        }
-        return retVal;
-      }
-      /**
-       * Converts string to snake-case.
-       * @param name
-       */
-      function toSnakeCase(name) {
-        const intermediate = name.replace(/(.)([A-Z][a-z0-9]+)/g, "$1_$2");
-        const insecure = intermediate.replace(/([a-z])([A-Z])/g, "$1_$2").toLowerCase();
-        /*
-     If the class is private the name starts with "_" which is not secure
-     for creating scopes. We prefix the name with "private" in this case.
-     */
-        if (insecure[0] !== "_") {
-          return insecure;
-        }
-        return "private" + insecure;
-      }
-      function toCamelCase(identifier) {
-        // quick return for empty string or single character strings
-        if (identifier.length <= 1) {
-          return identifier;
-        }
-        // Check for the underscore indicating snake_case
-        if (identifier.indexOf("_") === -1) {
-          return identifier;
-        }
-        return identifier.replace(/[_]+(\w|$)/g, (m, p1) => p1.toUpperCase());
-      }
-      // tslint:disable-next-line:no-any
-      let _GLOBAL_CUSTOM_OBJECTS = {};
-      function serializeKerasObject(instance) {
-        if (instance === null || instance === undefined) {
-          return null;
-        }
-        const dict = {};
-        dict["className"] = instance.getClassName();
-        dict["config"] = instance.getConfig();
-        return dict;
-      }
-      /**
-       * Replace ndarray-style scalar objects in serialization objects with numbers.
-       *
-       * Background: In some versions of tf.keras, certain scalar values in the HDF5
-       * model save file can be serialized as: `{'type': 'ndarray', 'value': num}`,
-       * where in `num` is a plain number. This method converts such serialization
-       * to a `number`.
-       *
-       * @param config The keras-format serialization object to be processed
-       *   (in place).
-       */
-      function convertNDArrayScalarsInConfig(config) {
-        if (config == null || typeof config !== "object") {
-          return;
-        } else if (Array.isArray(config)) {
-          config.forEach((configItem) => convertNDArrayScalarsInConfig(configItem));
-        } else {
-          const fields = Object.keys(config);
-          for (const field of fields) {
-            const value = config[field];
-            if (value != null && typeof value === "object") {
-              if (
-                !Array.isArray(value) &&
-                value["type"] === "ndarray" &&
-                typeof value["value"] === "number"
-              ) {
-                config[field] = value["value"];
-              } else {
-                convertNDArrayScalarsInConfig(value);
-              }
-            }
-          }
-        }
-      }
-      /**
-       * Deserialize a saved Keras Object
-       * @param identifier either a string ID or a saved Keras dictionary
-       * @param moduleObjects a list of Python class names to object constructors
-       * @param customObjects a list of Python class names to object constructors
-       * @param printableModuleName debug text for the object being reconstituted
-       * @param fastWeightInit Optional flag to use fast weight initialization
-       *   during deserialization. This is applicable to cases in which
-       *   the initialization will be immediately overwritten by loaded weight
-       *   values. Default: `false`.
-       * @returns a TensorFlow.js Layers object
-       */
-      // tslint:disable:no-any
-      function deserializeKerasObject(
-        identifier,
-        moduleObjects = {},
-        customObjects = {},
-        printableModuleName = "object",
-        fastWeightInit = false
-      ) {
-        // tslint:enable
-        if (typeof identifier === "string") {
-          const functionName = identifier;
-          let fn;
-          if (functionName in customObjects) {
-            fn = customObjects[functionName];
-          } else if (functionName in _GLOBAL_CUSTOM_OBJECTS) {
-            fn = _GLOBAL_CUSTOM_OBJECTS[functionName];
-          } else {
-            fn = moduleObjects[functionName];
-            if (fn == null) {
-              throw new ValueError(
-                `Unknown ${printableModuleName}: ${identifier}. ` +
-                  `This may be due to one of the following reasons:\n` +
-                  `1. The ${printableModuleName} is defined in Python, in which ` +
-                  `case it needs to be ported to TensorFlow.js or your JavaScript ` +
-                  `code.\n` +
-                  `2. The custom ${printableModuleName} is defined in JavaScript, ` +
-                  `but is not registered properly with ` +
-                  `tf.serialization.registerClass().`
-              );
-              // TODO(cais): Add link to tutorial page on custom layers.
-            }
-          }
-          return fn;
-        } else {
-          // In this case we are dealing with a Keras config dictionary.
-          const config = identifier;
-          if (config["className"] == null || config["config"] == null) {
-            throw new ValueError(
-              `${printableModuleName}: Improper config format: ` +
-                `${JSON.stringify(config)}.\n` +
-                `'className' and 'config' must set.`
-            );
-          }
-          const className = config["className"];
-          let cls, fromConfig;
-          if (className in customObjects) {
-            [cls, fromConfig] = customObjects[className];
-          } else if (className in _GLOBAL_CUSTOM_OBJECTS) {
-            [cls, fromConfig] = _GLOBAL_CUSTOM_OBJECTS["className"];
-          } else if (className in moduleObjects) {
-            [cls, fromConfig] = moduleObjects[className];
-          }
-          if (cls == null) {
-            throw new ValueError(
-              `Unknown ${printableModuleName}: ${className}. ` +
-                `This may be due to one of the following reasons:\n` +
-                `1. The ${printableModuleName} is defined in Python, in which ` +
-                `case it needs to be ported to TensorFlow.js or your JavaScript ` +
-                `code.\n` +
-                `2. The custom ${printableModuleName} is defined in JavaScript, ` +
-                `but is not registered properly with ` +
-                `tf.serialization.registerClass().`
-            );
-            // TODO(cais): Add link to tutorial page on custom layers.
-          }
-          if (fromConfig != null) {
-            // Porting notes: Instead of checking to see whether fromConfig accepts
-            // customObjects, we create a customObjects dictionary and tack it on to
-            // config['config'] as config['config'].customObjects. Objects can use it,
-            // if they want.
-            // tslint:disable-next-line:no-any
-            const customObjectsCombined = {};
-            for (const key of Object.keys(_GLOBAL_CUSTOM_OBJECTS)) {
-              customObjectsCombined[key] = _GLOBAL_CUSTOM_OBJECTS[key];
-            }
-            for (const key of Object.keys(customObjects)) {
-              customObjectsCombined[key] = customObjects[key];
-            }
-            // Add the customObjects to config
-            const nestedConfig = config["config"];
-            nestedConfig["customObjects"] = customObjectsCombined;
-            const backupCustomObjects = Object.assign({}, _GLOBAL_CUSTOM_OBJECTS);
-            for (const key of Object.keys(customObjects)) {
-              _GLOBAL_CUSTOM_OBJECTS[key] = customObjects[key];
-            }
-            convertNDArrayScalarsInConfig(config["config"]);
-            const returnObj = fromConfig(cls, config["config"], customObjects, fastWeightInit);
-            _GLOBAL_CUSTOM_OBJECTS = Object.assign({}, backupCustomObjects);
-            return returnObj;
-          } else {
-            // Then `cls` may be a function returning a class.
-            // In this case by convention `config` holds
-            // the kwargs of the function.
-            const backupCustomObjects = Object.assign({}, _GLOBAL_CUSTOM_OBJECTS);
-            for (const key of Object.keys(customObjects)) {
-              _GLOBAL_CUSTOM_OBJECTS[key] = customObjects[key];
-            }
-            // In python this is **config['config'], for tfjs-layers we require
-            // classes that use this fall-through construction method to take
-            // a config interface that mimics the expansion of named parameters.
-            const returnObj = new cls(config["config"]);
-            _GLOBAL_CUSTOM_OBJECTS = Object.assign({}, backupCustomObjects);
-            return returnObj;
-          }
-        }
-      }
-      /**
-       * Compares two numbers for sorting.
-       * @param a
-       * @param b
-       */
-      function numberCompare(a, b) {
-        return a < b ? -1 : a > b ? 1 : 0;
-      }
-      /**
-       * Comparison of two numbers for reverse sorting.
-       * @param a
-       * @param b
-       */
-      function reverseNumberCompare(a, b) {
-        return -1 * numberCompare(a, b);
-      }
-      /**
-       * Convert a string into the corresponding DType.
-       * @param dtype
-       * @returns An instance of DType.
-       */
-      function stringToDType(dtype) {
-        switch (dtype) {
-          case "float32":
-            return "float32";
-          default:
-            throw new ValueError(`Invalid dtype: ${dtype}`);
-        }
-      }
-      /**
-       * Test the element-by-element equality of two Arrays of strings.
-       * @param xs First array of strings.
-       * @param ys Second array of strings.
-       * @returns Wether the two arrays are all equal, element by element.
-       */
-      function stringsEqual(xs, ys) {
-        if (xs == null || ys == null) {
-          return xs === ys;
-        }
-        if (xs.length !== ys.length) {
-          return false;
-        }
-        for (let i = 0; i < xs.length; ++i) {
-          if (xs[i] !== ys[i]) {
-            return false;
-          }
-        }
-        return true;
-      }
-      /**
-       * Get the unique elements of an array.
-       * @param xs Array.
-       * @returns An Array consisting of the unique elements in `xs`.
-       */
-      function unique(xs) {
-        if (xs == null) {
-          return xs;
-        }
-        const out = [];
-        // TODO(cais): Maybe improve performance by sorting.
-        for (const x of xs) {
-          if (out.indexOf(x) === -1) {
-            out.push(x);
-          }
-        }
-        return out;
-      }
-      /**
-       * Determine if an Object is empty (i.e., does not have own properties).
-       * @param obj Object
-       * @returns Whether the Object is empty.
-       * @throws ValueError: If object is `null` or `undefined`.
-       */
-      function isObjectEmpty(obj) {
-        if (obj == null) {
-          throw new ValueError(`Invalid value in obj: ${JSON.stringify(obj)}`);
-        }
-        for (const key in obj) {
-          if (obj.hasOwnProperty(key)) {
-            return false;
-          }
-        }
-        return true;
-      }
-      /**
-       * Helper function used to build type union/enum run-time checkers.
-       * @param values The list of allowed values.
-       * @param label A string name for the type
-       * @param value The value to test.
-       * @throws ValueError: If the value is not in values nor `undefined`/`null`.
-       */
-      function checkStringTypeUnionValue(values, label, value) {
-        if (value == null) {
-          return;
-        }
-        if (values.indexOf(value) < 0) {
-          throw new ValueError(
-            `${value} is not a valid ${label}.  Valid values are ${values} or null/undefined.`
-          );
-        }
-      }
-      /**
-       * Helper function for verifying the types of inputs.
-       *
-       * Ensures that the elements of `x` are all of type `expectedType`.
-       * Also verifies that the length of `x` is within bounds.
-       *
-       * @param x Object to test.
-       * @param expectedType The string expected type of all of the elements in the
-       * Array.
-       * @param minLength Return false if x.length is less than this.
-       * @param maxLength Return false if x.length is greater than this.
-       * @returns true if and only if `x` is an `Array<expectedType>` with
-       * length >= `minLength` and <= `maxLength`.
-       */
-      // tslint:disable:no-any
-      function checkArrayTypeAndLength(x, expectedType, minLength = 0, maxLength = Infinity) {
-        assert(minLength >= 0);
-        assert(maxLength >= minLength);
-        return (
-          Array.isArray(x) &&
-          x.length >= minLength &&
-          x.length <= maxLength &&
-          x.every((e) => typeof e === expectedType)
-        );
-      }
-      // tslint:enable:no-any
-      /**
-       * Assert that a value or an array of value are positive integer.
-       *
-       * @param value The value being asserted on. May be a single number or an array
-       *   of numbers.
-       * @param name Name of the value, used to make the error message.
-       */
-      function assertPositiveInteger(value, name) {
-        if (Array.isArray(value)) {
-          dist["util"].assert(value.length > 0, () => `${name} is unexpectedly an empty array.`);
-          value.forEach((v, i) => assertPositiveInteger(v, `element ${i + 1} of ${name}`));
-        } else {
-          dist["util"].assert(
-            Number.isInteger(value) && value > 0,
-            () =>
-              `Expected ${name} to be a positive integer, but got ` +
-              `${formatAsFriendlyString(value)}.`
-          );
-        }
-      }
-      /**
-       * Format a value into a display-friendly, human-readable fashion.
-       *
-       * - `null` is formatted as `'null'`
-       * - Strings are formated with flanking pair of quotes.
-       * - Arrays are formatted with flanking pair of square brackets.
-       *
-       * @param value The value to display.
-       * @return Formatted string.
-       */
-      // tslint:disable-next-line:no-any
-      function formatAsFriendlyString(value) {
-        if (value === null) {
-          return "null";
-        } else if (Array.isArray(value)) {
-          return "[" + value.map((v) => formatAsFriendlyString(v)).join(",") + "]";
-        } else if (typeof value === "string") {
-          return `"${value}"`;
-        } else {
-          return `${value}`;
-        }
-      }
-      /**
-       * Returns a function `f2` (decorator) which wraps the original function
-       * `f`. `f2` guarantees that `f` can be called at most once
-       * every `waitMs` ms. If `f2` is called more often, it will return
-       * the last returned result of `f`.
-       *
-       * @param f The original function `f` to wrap.
-       * @param waitMs The time between two consecutive calls to `f` in ms.
-       */
-      function debounce(f, waitMs) {
-        let lastTime = dist["util"].now();
-        let lastResult;
-        const f2 = (...args) => {
-          const now = dist["util"].now();
-          if (now - lastTime < waitMs) {
-            return lastResult;
-          }
-          lastTime = now;
-          lastResult = f(...args);
-          return lastResult;
-        };
-        return f2;
-      }
-      /**
-       * Returns the fusable activation given a layers identifier.
-       *
-       * @param activationName The layers identifier string.
-       * @return The name of the fusable activation.
-       */
-      function mapActivationToFusedKernel(activationName) {
-        if (activationName === "relu") {
-          return "relu";
-        }
-        if (activationName === "linear") {
-          return "linear";
-        }
-        if (activationName === "elu") {
-          return "elu";
-        }
-        return null;
-      }
-      //# sourceMappingURL=generic_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/constraints.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original source: keras/contraints.py */
-
-      /**
-       * Helper function used by many of the Constraints to find the L2Norms.
-       */
-      function calcL2Norms(w, axis) {
-        return Object(dist["tidy"])(() => dist["sqrt"](dist["sum"](dist["mul"](w, w), axis, true)));
-      }
-      /**
-       * Base class for functions that impose constraints on weight values
-       */
-      /**
-       * @doc {
-       *   heading: 'Constraints',
-       *   subheading: 'Classes',
-       *   namespace: 'constraints'
-       * }
-       */
-      class constraints_Constraint extends dist["serialization"].Serializable {
-        getConfig() {
-          return {};
-        }
-      }
-      class constraints_MaxNorm extends constraints_Constraint {
-        constructor(args) {
-          super();
-          this.defaultMaxValue = 2;
-          this.defaultAxis = 0;
-          this.maxValue = args.maxValue != null ? args.maxValue : this.defaultMaxValue;
-          this.axis = args.axis != null ? args.axis : this.defaultAxis;
-        }
-        apply(w) {
-          return Object(dist["tidy"])(() => {
-            const norms = calcL2Norms(w, this.axis);
-            const desired = dist["clipByValue"](norms, 0, this.maxValue);
-            return dist["mul"](w, dist["div"](desired, dist["add"](common_epsilon(), norms)));
-          });
-        }
-        getConfig() {
-          return { maxValue: this.maxValue, axis: this.axis };
-        }
-      }
-      /** @nocollapse */
-      constraints_MaxNorm.className = "MaxNorm";
-      dist["serialization"].registerClass(constraints_MaxNorm);
-      class constraints_UnitNorm extends constraints_Constraint {
-        constructor(args) {
-          super();
-          this.defaultAxis = 0;
-          this.axis = args.axis != null ? args.axis : this.defaultAxis;
-        }
-        apply(w) {
-          return Object(dist["tidy"])(() =>
-            dist["div"](w, dist["add"](common_epsilon(), calcL2Norms(w, this.axis)))
-          );
-        }
-        getConfig() {
-          return { axis: this.axis };
-        }
-      }
-      /** @nocollapse */
-      constraints_UnitNorm.className = "UnitNorm";
-      dist["serialization"].registerClass(constraints_UnitNorm);
-      class constraints_NonNeg extends constraints_Constraint {
-        apply(w) {
-          return dist["relu"](w);
-        }
-      }
-      /** @nocollapse */
-      constraints_NonNeg.className = "NonNeg";
-      dist["serialization"].registerClass(constraints_NonNeg);
-      class constraints_MinMaxNorm extends constraints_Constraint {
-        constructor(args) {
-          super();
-          this.defaultMinValue = 0.0;
-          this.defaultMaxValue = 1.0;
-          this.defaultRate = 1.0;
-          this.defaultAxis = 0;
-          this.minValue = args.minValue != null ? args.minValue : this.defaultMinValue;
-          this.maxValue = args.maxValue != null ? args.maxValue : this.defaultMaxValue;
-          this.rate = args.rate != null ? args.rate : this.defaultRate;
-          this.axis = args.axis != null ? args.axis : this.defaultAxis;
-        }
-        apply(w) {
-          return Object(dist["tidy"])(() => {
-            const norms = calcL2Norms(w, this.axis);
-            const desired = dist["add"](
-              dist["mul"](this.rate, dist["clipByValue"](norms, this.minValue, this.maxValue)),
-              dist["mul"](1.0 - this.rate, norms)
-            );
-            return dist["mul"](w, dist["div"](desired, dist["add"](common_epsilon(), norms)));
-          });
-        }
-        getConfig() {
-          return {
-            minValue: this.minValue,
-            maxValue: this.maxValue,
-            rate: this.rate,
-            axis: this.axis,
-          };
-        }
-      }
-      /** @nocollapse */
-      constraints_MinMaxNorm.className = "MinMaxNorm";
-      dist["serialization"].registerClass(constraints_MinMaxNorm);
-      // Maps the JavaScript-like identifier keys to the corresponding registry
-      // symbols.
-      const CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP = {
-        maxNorm: "MaxNorm",
-        minMaxNorm: "MinMaxNorm",
-        nonNeg: "NonNeg",
-        unitNorm: "UnitNorm",
-      };
-      function serializeConstraint(constraint) {
-        return serializeKerasObject(constraint);
-      }
-      function deserializeConstraint(config, customObjects = {}) {
-        return deserializeKerasObject(
-          config,
-          dist["serialization"].SerializationMap.getMap().classNameMap,
-          customObjects,
-          "constraint"
-        );
-      }
-      function getConstraint(identifier) {
-        if (identifier == null) {
-          return null;
-        }
-        if (typeof identifier === "string") {
-          const className =
-            identifier in CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP
-              ? CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier]
-              : identifier;
-          const config = { className, config: {} };
-          return deserializeConstraint(config);
-        } else if (identifier instanceof constraints_Constraint) {
-          return identifier;
-        } else {
-          return deserializeConstraint(identifier);
-        }
-      }
-      //# sourceMappingURL=constraints.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_constraints.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      // tslint:disable-next-line:max-line-length
-
-      /**
-       * MaxNorm weight constraint.
-       *
-       * Constrains the weights incident to each hidden unit
-       * to have a norm less than or equal to a desired value.
-       *
-       * References
-       *       - [Dropout: A Simple Way to Prevent Neural Networks from Overfitting
-       * Srivastava, Hinton, et al.
-       * 2014](http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf)
-       */
-      /** @doc {heading: 'Constraints',namespace: 'constraints'} */
-      function maxNorm(args) {
-        return new constraints_MaxNorm(args);
-      }
-      /**
-       * Constrains the weights incident to each hidden unit to have unit norm.
-       */
-      /** @doc {heading: 'Constraints', namespace: 'constraints'} */
-      function unitNorm(args) {
-        return new constraints_UnitNorm(args);
-      }
-      /**
-       * Constains the weight to be non-negative.
-       */
-      /** @doc {heading: 'Constraints', namespace: 'constraints'} */
-      function nonNeg() {
-        return new constraints_NonNeg();
-      }
-      /** @doc {heading: 'Constraints', namespace: 'constraints'} */
-      function minMaxNorm(config) {
-        return new constraints_MinMaxNorm(config);
-      }
-      //# sourceMappingURL=exports_constraints.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/keras_format/common.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      const VALID_DATA_FORMAT_VALUES = ["channelsFirst", "channelsLast"];
-      const VALID_PADDING_MODE_VALUES = ["valid", "same", "causal"];
-      const VALID_POOL_MODE_VALUES = ["max", "avg"];
-      const VALID_BIDIRECTIONAL_MERGE_MODES = ["sum", "mul", "concat", "ave"];
-      const VALID_SAMPLE_WEIGHT_MODES = ["temporal"];
-      //# sourceMappingURL=common.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/common.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Common functions for TensorFlow.js Layers.
-       */
-
-      // A map from the requested scoped name of a Tensor to the number of Tensors
-      // wanting that name so far.  This allows enforcing name uniqueness by appending
-      // an incrementing index, e.g. scope/name, scope/name_1, scope/name_2, etc.
-      const nameMap = new Map();
-      function checkDataFormat(value) {
-        checkStringTypeUnionValue(VALID_DATA_FORMAT_VALUES, "DataFormat", value);
-      }
-      function checkPaddingMode(value) {
-        checkStringTypeUnionValue(VALID_PADDING_MODE_VALUES, "PaddingMode", value);
-      }
-      function checkPoolMode(value) {
-        checkStringTypeUnionValue(VALID_POOL_MODE_VALUES, "PoolMode", value);
-      }
-      const _nameScopeStack = [];
-      const _nameScopeDivider = "/";
-      /**
-       * Enter namescope, which can be nested.
-       */
-      function nameScope(name, fn) {
-        _nameScopeStack.push(name);
-        try {
-          const val = fn();
-          _nameScopeStack.pop();
-          return val;
-        } catch (e) {
-          _nameScopeStack.pop();
-          throw e;
-        }
-      }
-      /**
-       * Get the current namescope as a flat, concatenated string.
-       */
-      function currentNameScopePrefix() {
-        if (_nameScopeStack.length === 0) {
-          return "";
-        } else {
-          return _nameScopeStack.join(_nameScopeDivider) + _nameScopeDivider;
-        }
-      }
-      /**
-       * Get the name a Tensor (or Variable) would have if not uniqueified.
-       * @param tensorName
-       * @return Scoped name string.
-       */
-      function getScopedTensorName(tensorName) {
-        if (!isValidTensorName(tensorName)) {
-          throw new Error("Not a valid tensor name: '" + tensorName + "'");
-        }
-        return currentNameScopePrefix() + tensorName;
-      }
-      /**
-       * Get unique names for Tensors and Variables.
-       * @param scopedName The fully-qualified name of the Tensor, i.e. as produced by
-       *  `getScopedTensorName()`.
-       * @return A unique version of the given fully scoped name.
-       *   If this is the first time that the scoped name is seen in this session,
-       *   then the given `scopedName` is returned unaltered.  If the same name is
-       *   seen again (producing a collision), an incrementing suffix is added to the
-       *   end of the name, so it takes the form 'scope/name_1', 'scope/name_2', etc.
-       */
-      function getUniqueTensorName(scopedName) {
-        if (!isValidTensorName(scopedName)) {
-          throw new Error("Not a valid tensor name: '" + scopedName + "'");
-        }
-        if (!nameMap.has(scopedName)) {
-          nameMap.set(scopedName, 0);
-        }
-        const index = nameMap.get(scopedName);
-        nameMap.set(scopedName, nameMap.get(scopedName) + 1);
-        if (index > 0) {
-          const result = `${scopedName}_${index}`;
-          // Mark the composed name as used in case someone wants
-          // to call getUniqueTensorName("name_1").
-          nameMap.set(result, 1);
-          return result;
-        } else {
-          return scopedName;
-        }
-      }
-      const tensorNameRegex = new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);
-      /**
-       * Determine whether a string is a valid tensor name.
-       * @param name
-       * @returns A Boolean indicating whether `name` is a valid tensor name.
-       */
-      function isValidTensorName(name) {
-        return !!name.match(tensorNameRegex);
-      }
-      //# sourceMappingURL=common.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/math_utils.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Math utility functions.
-       *
-       * This file contains some frequently used math function that operates on
-       * number[] or Float32Array and return a number. Many of these functions are
-       * not-so-thick wrappers around TF.js Core functions. But they offer the
-       * convenience of
-       * 1) not having to convert the inputs into Tensors,
-       * 2) not having to convert the returned Tensors to numbers.
-       */
-
-      /**
-       * Determine if a number is an integer.
-       */
-      function isInteger(x) {
-        return x === parseInt(x.toString(), 10);
-      }
-      /**
-       * Calculate the product of an array of numbers.
-       * @param array The array to calculate the product over.
-       * @param begin Beginning index, inclusive.
-       * @param end Ending index, exclusive.
-       * @return The product.
-       */
-      function arrayProd(array, begin, end) {
-        if (begin == null) {
-          begin = 0;
-        }
-        if (end == null) {
-          end = array.length;
-        }
-        let prod = 1;
-        for (let i = begin; i < end; ++i) {
-          prod *= array[i];
-        }
-        return prod;
-      }
-      /**
-       * A helper function transforms the two input types to an instance of Tensor1D,
-       * so the return value can be fed directly into various TF.js Core functions.
-       * @param array
-       */
-      function toArray1D(array) {
-        array = Array.isArray(array) ? new Float32Array(array) : array;
-        return Object(dist["tensor1d"])(array);
-      }
-      /**
-       * Compute minimum value.
-       * @param array
-       * @return minimum value.
-       */
-      function min(array) {
-        return dist["min"](toArray1D(array)).dataSync()[0];
-      }
-      /**
-       * Compute maximum value.
-       * @param array
-       * @return maximum value
-       */
-      function max(array) {
-        return dist["max"](toArray1D(array)).dataSync()[0];
-      }
-      /**
-       * Compute sum of array.
-       * @param array
-       * @return The sum.
-       */
-      function sum(array) {
-        return dist["sum"](toArray1D(array)).dataSync()[0];
-      }
-      /**
-       * Compute mean of array.
-       * @param array
-       * @return The mean.
-       */
-      function math_utils_mean(array) {
-        return sum(array) / array.length;
-      }
-      /**
-       * Compute variance of array.
-       * @param array
-       * @return The variance.
-       */
-      function math_utils_variance(array) {
-        const demeaned = dist["sub"](
-          toArray1D(array),
-          Object(dist["scalar"])(math_utils_mean(array))
-        );
-        const sumSquare = dist["sum"](dist["mul"](demeaned, demeaned)).dataSync()[0];
-        return sumSquare / array.length;
-      }
-      /**
-       * Compute median of array.
-       * @param array
-       * @return The median value.
-       */
-      function median(array) {
-        const arraySorted = array.slice().sort((a, b) => a - b);
-        const lowIdx = Math.floor((arraySorted.length - 1) / 2);
-        const highIdx = Math.ceil((arraySorted.length - 1) / 2);
-        if (lowIdx === highIdx) {
-          return arraySorted[lowIdx];
-        }
-        return (arraySorted[lowIdx] + arraySorted[highIdx]) / 2;
-      }
-      /**
-       * Generate an array of integers in [begin, end).
-       * @param begin Beginning integer, inclusive.
-       * @param end Ending integer, exclusive.
-       * @returns Range array.
-       * @throws ValueError, iff `end` < `begin`.
-       */
-      function range(begin, end) {
-        if (end < begin) {
-          throw new ValueError(`end (${end}) < begin (${begin}) is forbidden.`);
-        }
-        const out = [];
-        for (let i = begin; i < end; ++i) {
-          out.push(i);
-        }
-        return out;
-      }
-      //# sourceMappingURL=math_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/backend/tfjs_backend.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * deeplearn.js backend.
-       */
-
-      // tslint:enable
-      /* Setting and getting backend from deeplearn.js. */
-      // Default deeplearn.js backend is WebGL (GPU).
-      let backend = "webgl";
-      function setBackend(requestedBackend) {
-        dist["setBackend"](requestedBackend);
-        backend = requestedBackend;
-      }
-      function getBackend() {
-        return backend;
-      }
-      /**
-       * Indicates whether the backend is operating symbolically.
-       *
-       * This function will be used to determine how to interpret user code. If
-       * it returns true, calls to the backend construct a symbolic graph; if
-       * it returns false, calls to the backend execute immediately.
-       */
-      function isBackendSymbolic() {
-        return false;
-      }
-      /**
-       * Get the number of elements in a Tensor.
-       * @param x The Tensor.
-       * @return Number of elements in `x`.
-       */
-      function countParams(x) {
-        const shape = x.shape;
-        if (shape.length > 0) {
-          return shape.reduce((a, b) => a * b);
-        } else {
-          // Scalar.
-          return 1;
-        }
-      }
-      /**
-       * Casts a tensor to a different dtype and returns it.
-       * @param x Input tensor.
-       * @param dtype String: 'float32'|'int32'|'bool'.
-       * @returns Tensor of the specified `dtype`.
-       */
-      function cast(x, dtype) {
-        return x.asType(dtype);
-      }
-      /**
-       * Adds a 1-sized dimension at index "axis".
-       * @param x Input tensor.
-       * @param axis Position where to add the new axis.
-       * @returns Result of the dimension expansion.
-       */
-      function expandDims(x, axis = -1) {
-        const outShape = x.shape.slice();
-        if (axis < 0) {
-          axis = outShape.length + axis + 1;
-        }
-        outShape.splice(axis, 0, 1);
-        return x.reshape(outShape);
-      }
-      /**
-       * Repeats a 2D tensor.
-       *
-       * If `x` has shape `[samples, dim]` and `n` is 2, for example, the output
-       * will have shape `[samples, 2, dim]`.
-       *
-       * @param x Input tensor.
-       * @param n Integer, number of times to repeat.
-       * @returns The result of the repeat operation.
-       * @throws ValueError: If input tensor is not 2D.
-       */
-      function repeat(x, n) {
-        return Object(dist["tidy"])(() => {
-          if (x.shape.length !== 2) {
-            throw new ValueError(
-              `repeat() expects a rank-2 tensor, but received a ` + `rank-${x.shape.length} tensor.`
-            );
-          }
-          const y = expandDims(x, 1);
-          return tile(y, [1, n, 1]);
-        });
-      }
-      /**
-       * Flatten a Tensor into 1D.
-       * @param x Input tensor.
-       * @return The result of the flattening `x`.
-       */
-      function flatten(x) {
-        const newShape = [arrayProd(x.shape)];
-        return x.reshape(newShape);
-      }
-      /**
-       * Turn a nD tensor into a 2D tensor with same 0th dimension.
-       * In other words, it flattens each data samples of a batch.
-       *
-       * @param x The tensor to flatten. The rank of this tensor is required to be 2
-       *   or higher.
-       * @return The result of the flattening.
-       */
-      function batchFlatten(x) {
-        if (x.rank <= 1) {
-          throw new ValueError(`batchFlatten requires a minimum rank of 2. Got rank: ${x.rank}.`);
-        }
-        const newShape = [x.shape[0], arrayProd(x.shape, 1)];
-        return x.reshape(newShape);
-      }
-      /**
-       * Do slicing along the first axis.
-       * @param array input `tf.Tensor`.
-       * @param start starting index, inclusive.
-       * @param size size of the slice along the first axis.
-       * @returns result of the slicing.
-       * @throws ValueError: If `array` is of an unsupported subtype of `tf.Tensor`.
-       */
-      function sliceAlongFirstAxis(array, start, size) {
-        return Object(dist["tidy"])(() => {
-          switch (array.rank) {
-            case 1:
-              return dist["slice1d"](array, start, size);
-            case 2:
-              return dist["slice2d"](array, [start, 0], [size, array.shape[1]]);
-            case 3:
-              return dist["slice3d"](array, [start, 0, 0], [size, array.shape[1], array.shape[2]]);
-            case 4:
-              return dist["slice4d"](
-                array,
-                [start, 0, 0, 0],
-                [size, array.shape[1], array.shape[2], array.shape[3]]
-              );
-            case 5:
-              return dist["slice"](
-                array,
-                [start, 0, 0, 0, 0],
-                [size, array.shape[1], array.shape[2], array.shape[3], array.shape[4]]
-              );
-            case 6:
-              return dist["slice"](
-                array,
-                [start, 0, 0, 0, 0, 0],
-                [
-                  size,
-                  array.shape[1],
-                  array.shape[2],
-                  array.shape[3],
-                  array.shape[4],
-                  array.shape[5],
-                ]
-              );
-            default:
-              throw new ValueError(
-                `sliceAlongFirstAxis() received an unsupported tensor rank: ` + `${array.rank}`
-              );
-          }
-        });
-      }
-      /**
-       * Do slicing along the last axis.
-       * @param array input `tf.Tensor`.
-       * @param start starting index, inclusive.
-       * @param size size of the slice along the last axis.
-       * @returns result of the slicing.
-       * @throws ValueError: If `array` is of an unsupported subtype of `tf.Tensor`.
-       */
-      function sliceAlongLastAxis(array, start, size) {
-        return Object(dist["tidy"])(() => {
-          switch (array.rank) {
-            case 1:
-              return dist["slice1d"](array, start, size);
-            case 2:
-              return dist["slice2d"](array, [0, start], [array.shape[0], size]);
-            case 3:
-              return dist["slice3d"](array, [0, 0, start], [array.shape[0], array.shape[1], size]);
-            case 4:
-              return dist["slice4d"](
-                array,
-                [0, 0, 0, start],
-                [array.shape[0], array.shape[1], array.shape[2], size]
-              );
-            default:
-              throw new ValueError(
-                `sliceAlongLastAxis() received an unsupported tensor rank: ` + `${array.rank}`
-              );
-          }
-        });
-      }
-      /**
-       * Do slicing along the sepcified axis.
-       * @param array input `tf.Tensor`.
-       * @param start starting index, inclusive.
-       * @param size of the slice along the chosen axis.
-       * @param choose an axis.
-       * @returns result of the slicing.
-       * @throws ValueError: If `array` is of an unsupported subtype of `tf.Tensor`.
-       */
-      function sliceAlongAxis(array, start, size, axis) {
-        return Object(dist["tidy"])(() => {
-          switch (array.rank) {
-            case 1:
-              return dist["slice1d"](array, start, size);
-            case 2:
-              switch (axis) {
-                case 1:
-                  return sliceAlongFirstAxis(array, start, size);
-                case 2:
-                  return sliceAlongLastAxis(array, start, size);
-                default:
-                  throw new ValueError(
-                    `The axis is not within the rank of the tensor ` + `${axis}`
-                  );
-              }
-            case 3:
-              switch (axis) {
-                case 1:
-                  return sliceAlongFirstAxis(array, start, size);
-                case 2:
-                  return dist["slice3d"](
-                    array,
-                    [0, start, 0],
-                    [array.shape[0], size, array.shape[2]]
-                  );
-                case 3:
-                  return sliceAlongLastAxis(array, start, size);
-                default:
-                  throw new ValueError(
-                    `The axis is not within the rank of the tensor ` + `${axis}`
-                  );
-              }
-            case 4:
-              switch (axis) {
-                case 1:
-                  return sliceAlongFirstAxis(array, start, size);
-                case 2:
-                  return dist["slice4d"](
-                    array,
-                    [0, start, 0, 0],
-                    [array.shape[0], size, array.shape[2], array.shape[3]]
-                  );
-                case 3:
-                  return dist["slice4d"](
-                    array,
-                    [0, 0, start, 0],
-                    [array.shape[0], array.shape[1], size, array.shape[3]]
-                  );
-                case 4:
-                  return sliceAlongLastAxis(array, start, size);
-                default:
-                  throw new ValueError(
-                    `The axis is not within the rank of the tensor ` + `${axis}`
-                  );
-              }
-            default:
-              throw new ValueError(
-                `sliceAlongLastAxis() received an unsupported tensor rank: ` + `${array.rank}`
-              );
-          }
-        });
-      }
-      /**
-       * Concatenates a list of tensors alongside the specified axis.
-       * @param tensors `Array` of tensors to concatenate.
-       * @param axis Concatenation axis.
-       * @returns The result of the concatenation.
-       */
-      function concatenate(tensors, axis = -1) {
-        let rank;
-        if (axis < 0) {
-          rank = tensors[0].rank;
-          if (rank !== 0) {
-            axis = rank;
-          } else {
-            axis = 0;
-          }
-        }
-        if (axis === tensors[0].rank) {
-          // Porting Note: This is necessary because tfc.concat() requires axis to be
-          //   in the interval [-rank, rank).
-          axis = -1;
-        }
-        // Porting Note: Sparse concat is not supported yet.
-        return dist["concat"](tensors, axis);
-      }
-      /**
-       * Concatenate two arrays along the first dimension.
-       * @param a The 1st `tf.Tensor` to concatenate.
-       * @param b The 2nd `tf.Tensor` to concatenate.
-       * @returns Result of the concatenation.
-       * @throws ValueError: If `a` is of an unsupported subtype of `tf.Tensor`.
-       */
-      function concatAlongFirstAxis(a, b) {
-        switch (a.rank) {
-          case 1:
-            return dist["concat1d"]([a, b]);
-          case 2:
-            return dist["concat2d"]([a, b], 0);
-          case 3:
-            return dist["concat3d"]([a, b], 0);
-          case 4:
-            return dist["concat4d"]([a, b], 0);
-          default:
-            throw new ValueError(
-              `concatAlongFirstAxis() received an unsupported ` + `tensor rank: ${a.rank}`
-            );
-        }
-      }
-      /**
-       * Creates a tensor by tiling `x` by `n`.
-       * @param x A tensor.
-       * @param n An Array of integers or a single integer. If an Array, the length
-       *   must be the same as the number of dimensions in `x`. If a single integer,
-       *   it will be treated as an Array of length 1.
-       */
-      function tile(x, n) {
-        if (!Array.isArray(n)) {
-          n = [n];
-        }
-        if (x.rank !== n.length) {
-          throw new ValueError(
-            `The length of input n (${n.length}) does not match ` +
-              `the number of dimensions in input x (${x.rank})`
-          );
-        }
-        return dist["tile"](x, n);
-      }
-      /* Creation of random tensors. */
-      /**
-       * Get a tensor with normal distribution of values.
-       *
-       * @param shape Shape of the tensor.
-       * @param mean mean value of the normal distribution.
-       * @param stddev standard deviation of the normal distribution.
-       * @param dtype
-       * @param seed
-       * @return The normal tensor.
-       */
-      function randomNormal(shape, mean = 0.0, stddev = 1.0, dtype, seed) {
-        return dist["randomNormal"](shape, mean, stddev, dtype, seed);
-      }
-      /* Linear Algebra */
-      /**
-       * Multiply two tensors and returns the result as a tensor.
-       *
-       * For 2D tensors, this is equivalent to matrix multiplication (matMul).
-       * For tensors of higher ranks, it follows the Theano behavior,
-       * (e.g. `(2, 3) * (4, 3, 5) -> (2, 4, 5)`).  From the Theano documentation:
-       *
-       * For N dimensions it is a sum product over the last axis of x and the
-       * second-to-last of y:
-       *
-       * @param a A tensor of at least rank 2.
-       * @param b A tensor of at least rank 2.
-       * @param activation (optional) A string identifying the activation
-       *   function.
-       * @return Result of the dot operation.
-       */
-      function dot(a, b, activation, bias) {
-        if (a.rank < 2 || b.rank < 2) {
-          throw new NotImplementedError(
-            `dot requires both inputs to be rank >= 2` +
-              ` but got x shape = ${a.shape} and y shape = ${b.shape}`
-          );
-        }
-        if (b.rank >= 3) {
-          const xLastDim = a.shape.slice(-1)[0];
-          const ySecondLastDim = b.shape.slice(-2)[0];
-          if (xLastDim !== ySecondLastDim) {
-            throw new NotImplementedError(
-              `If rank y >= 3, then the second last dim` +
-                ` of y must equal the last dim of x but got x shape = ${a.shape} and ` +
-                ` y shape = ${b.shape}`
-            );
-          }
-        }
-        // Handle basic 2D x 2D case.
-        if (a.rank === 2 && b.rank === 2) {
-          const transposeA = false;
-          const transposeB = false;
-          // tfc.fused.matMul only fuses certain activation functions. Unsupported
-          // activation functions are treated as 'linear' activations, which is
-          // equivalent to a no-op.
-          return dist["fused"].matMul({
-            a,
-            b: b,
-            transposeA,
-            transposeB,
-            bias: bias ? reshapeBias(a.rank, bias, imageDataFormat()) : null,
-            activation,
-          });
-        } else {
-          // Reshape x into the analogous 2D Tensor.
-          const aFirstDims = a.shape.slice(); // Holds all but the last dim of x.
-          const aLastDim = aFirstDims.pop();
-          a = a.reshape([-1, aLastDim]);
-          // Reshape y into the analogous 2D Tensor, and keep track of the
-          // required dimensions to reproduce the output shape.
-          const bShape = b.shape.slice();
-          const bLastDim = bShape.pop();
-          const ySecondLastDim = bShape.pop();
-          const yOtherDims = [...bShape, bLastDim];
-          // permutation should be like [r-2, 0, 1, 2, ... r-4, r-3, r-1]
-          // where r is the rank of y.
-          const perm = Array.from({ length: b.rank }, (_, i) => {
-            if (i === 0) {
-              return b.rank - 2;
-            } else if (i <= b.rank - 2) {
-              return i - 1;
-            }
-            return i;
-          });
-          b = b.transpose(perm).reshape([ySecondLastDim, -1]);
-          // Multiply x and y as 2D Tensors, and then reshape back to original.
-          const outputShape = [...aFirstDims, ...yOtherDims];
-          const transposeA = false;
-          const transposeB = false;
-          return dist["fused"]
-            .matMul({
-              a,
-              b,
-              transposeA,
-              transposeB,
-              bias: bias ? reshapeBias(a.rank, bias, imageDataFormat()) : null,
-              activation,
-            })
-            .reshape(outputShape);
-        }
-      }
-      /**
-       * Compute the sign Tensor of an input Tensor.
-       *
-       * Elements of the input `tf.Tensor` that are === 0 are mapped to 0.
-       * Elements of the input `tf.Tensor` that are > 0 are mapped to 1.
-       * Elements of the input `tf.Tensor` that are < 0 are mapped to -1.
-       *
-       * @param x Input `tf.Tensor`.
-       * @return The sign `tf.Tensor`.
-       */
-      function sign(x) {
-        // TODO(cais): Move to the core.
-        return Object(dist["tidy"])(() => {
-          const zerosLikeX = Object(dist["zerosLike"])(x);
-          const onesLikeX = Object(dist["onesLike"])(x);
-          return Object(dist["where"])(
-            dist["equal"](x, zerosLikeX),
-            zerosLikeX,
-            Object(dist["where"])(
-              dist["greater"](x, Object(dist["zerosLike"])(x)),
-              onesLikeX,
-              dist["mul"](-1, onesLikeX)
-            )
-          );
-        });
-      }
-      /**
-       * Computes the one-hot representation of an integer tensor.
-       * @param indices nD integer tensor of shape
-       *   `(batch_size, dim1, dim2, ... dim(n-1))`
-       * @param numClasses Integer, number of classes to consider.
-       * @returns (n + 1)D one hot representation of the input
-       *   with shape `(batch_size, dim1, dim2, ... dim(n-1), num_classes)`
-       */
-      function oneHot(indices, numClasses) {
-        return Object(dist["tidy"])(() => {
-          if (indices.rank !== 1) {
-            throw new Error(
-              "Only 1D one-hot tensors are supported in the " + "deeplearn backend, at present."
-            );
-          }
-          indices = indices.toInt();
-          return dist["oneHot"](indices, numClasses).toFloat();
-        });
-      }
-      /* Elementary math functions. */
-      /**
-       * Retrieves the elements of indices `indices` in the tensor `reference`.
-       * @param reference A tensor.
-       * @param indices An integer tensor of indices or an `Array` of integers.
-       * @param axis Axis along which to perform the gather operation.
-       * @returns The result of the gathering as a tensor.
-       */
-      function gather(reference, indices, axis) {
-        return Object(dist["tidy"])(() => {
-          if (Array.isArray(indices)) {
-            indices = Object(dist["tensor1d"])(indices, "int32");
-          } else {
-            indices = indices.toInt();
-          }
-          return dist["gather"](reference, indices, axis);
-        });
-      }
-      /**
-       * Element-wise square.
-       * @param x Input tensor.
-       * @return element-wise x^2
-       */
-      function square(x) {
-        return dist["mul"](x, x);
-      }
-      /**
-       * Element-wise exponentiation.
-       *
-       * Porting Note: In PyKeras, `a` (the exponent) is a Python integer, which
-       *   takes advatnage of the backend's (e.g., TensorFlow's) automatic
-       * conversion to tensor. Here we allow `a` to be either a number or a tensor.
-       *
-       * @param x The base tensor.
-       * @param a The exponent, tensor or number. If a number, it is rounded to the
-       *   nearest integer and converted to a tensor.
-       * @returns A tensor of the same shape as `x`.
-       */
-      function pow(x, a) {
-        return Object(dist["tidy"])(() => {
-          if (typeof a === "number") {
-            a = Object(dist["scalar"])(Math.round(a), "int32");
-          }
-          if (a.dtype !== "int32") {
-            throw new NotImplementedError(
-              `Non-int32 dtype (${a.dtype}) is not supported by pow() yet`
-            );
-          }
-          return dist["pow"](x, a);
-        });
-      }
-      /**
-       * Reshapes bias tensor according to rank of x.
-       */
-      function reshapeBias(xRank, bias, dataFormat) {
-        const biasShape = bias.shape;
-        if (bias.rank !== 1 && bias.rank !== xRank) {
-          throw new ValueError(
-            `Unexpected bias dimensions: ${bias.rank}` + `; expected it to be 1 or ${xRank}`
-          );
-        }
-        if (xRank === 5) {
-          if (dataFormat === "channelsFirst") {
-            if (biasShape.length === 1) {
-              return bias.reshape([1, biasShape[0], 1, 1, 1]);
-            } else {
-              return bias.reshape([1, biasShape[3], biasShape[0], biasShape[1], biasShape[2]]);
-            }
-          } else if (dataFormat === "channelsLast") {
-            if (biasShape.length === 1) {
-              return bias.reshape([1, 1, 1, 1, biasShape[0]]);
-            } else {
-              return bias.reshape([1].concat(biasShape));
-            }
-          }
-        } else if (xRank === 4) {
-          if (dataFormat === "channelsFirst") {
-            if (biasShape.length === 1) {
-              return bias.reshape([1, biasShape[0], 1, 1]);
-            } else {
-              return bias.reshape([1, biasShape[2], biasShape[0], biasShape[1]]);
-            }
-          } else if (dataFormat === "channelsLast") {
-            if (biasShape.length === 1) {
-              return bias.reshape([1, 1, 1, biasShape[0]]);
-            } else {
-              return bias.reshape([1].concat(biasShape));
-            }
-          }
-        } else if (xRank === 3) {
-          if (dataFormat === "channelsFirst") {
-            if (biasShape.length === 1) {
-              return bias.reshape([1, biasShape[0], 1]);
-            } else {
-              return bias.reshape([1, biasShape[1], biasShape[0]]);
-            }
-          } else if (dataFormat === "channelsLast") {
-            if (biasShape.length === 1) {
-              return bias.reshape([1, 1, biasShape[0]]);
-            } else {
-              return bias.reshape([1].concat(biasShape));
-            }
-          }
-        } else if (xRank < 3) {
-          return bias;
-        }
-        throw new ValueError(`Unsupported input rank by biasAdd: ${bias.rank}`);
-      }
-      /* Neural-network operations. */
-      /**
-       * Add a bias to a tensor.
-       *
-       * @param x The tensor to add the bias to.
-       * @param bias The bias to add to `x`. Must be 1D or the same rank as `x`.
-       * @return Result of the bias adding.
-       * @throws ValueError: If the rank of `bias` is incorrect.
-       */
-      function biasAdd(x, bias, dataFormat) {
-        return Object(dist["tidy"])(() => {
-          if (dataFormat == null) {
-            dataFormat = imageDataFormat();
-          }
-          checkDataFormat(dataFormat);
-          return x.add(reshapeBias(x.rank, bias, dataFormat));
-        });
-      }
-      /**
-       * Exponential linear unit (ELU).
-       * @param x A tensor or variable to compute the activation function for.
-       * @param alpha: A scalar, a scaling factor for the negative section.
-       * @return Output of the ELU operation.
-       */
-      function elu(x, alpha = 1) {
-        // TODO(cais): Add support for alpha values other than 1.
-        if (alpha !== 1) {
-          throw new NotImplementedError(
-            `Support for alpha values other than 1 (${alpha}) is not implemented ` + `yet.`
-          );
-        }
-        return dist["elu"](x);
-      }
-      /**
-       * Softsign of a tensor.
-       *
-       * Defined as x / (abs(x) + 1), element-wise.
-       *
-       * @param x: Input.
-       * @returns Output.
-       */
-      function softsign(x) {
-        return Object(dist["tidy"])(() => dist["div"](x, dist["abs"](x).add(1)));
-      }
-      /**
-       * Sets entries in `x` to zero at random, while scaling the entire tensor.
-       *
-       * @param x input tensor.
-       * @param level fraction of the entries in the tensor that will be set to 0.
-       * @param noiseShape shape of randomly generated keep/drop flags, must be
-       *   broadcastable to the shape of `x`. Optional.
-       * @param seed random seed to ensure determinism. Optional.
-       * @returns Result of the dropout operation.
-       */
-      function dropout(x, level, noiseShape, seed) {
-        return Object(dist["tidy"])(() => dist["dropout"](x, level, noiseShape, seed));
-      }
-      /**
-       * Element-wise, segment-wise linear approximation of sigmoid.
-       *
-       * Returns `0.` if `x < -2.5`, `1.` if `x > 2.5`.
-       * In `-2.5 <= x <= 2.5`, returns `0.2 * x + 0.5`.
-       *
-       * @param x Input tensor.
-       * @returns Output tensor.
-       */
-      function hardSigmoid(x) {
-        return Object(dist["tidy"])(() => {
-          const y = dist["add"](0.5, dist["mul"](0.2, x));
-          return dist["clipByValue"](y, 0, 1);
-        });
-      }
-      /**
-       * Invoke `x` in the training phase, and `alt` otherwise.
-       *
-       * Porting Note: We do not create placeholder tensors for the `training`
-       * boolean flag here, because there is no such thing in the TF.js imperative
-       * backend.
-       *
-       * @param x The function to invoke iff `training` is `true`.
-       * @param alt The function to invoke iff `training` is `false`.
-       * @param training Boolean flag for whether training phase is active.
-       * @returns The return value of `x()` if `training` is `true`, or the return
-       *   value of `alt()` if `training` is `false`.
-       */
-      function inTrainPhase(x, alt, training = false) {
-        return training ? x() : alt();
-      }
-      //# sourceMappingURL=tfjs_backend.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/keras_format/initializer_config.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      const VALID_FAN_MODE_VALUES = ["fanIn", "fanOut", "fanAvg"];
-      const VALID_DISTRIBUTION_VALUES = ["normal", "uniform", "truncatedNormal"];
-      // We can't easily extract a string[] from the string union type, but we can
-      // recapitulate the list, enforcing at compile time that the values are valid
-      // and that we have the right number of them.
-      /**
-       * A string array of valid Initializer class names.
-       *
-       * This is guaranteed to match the `InitializerClassName` union type.
-       */
-      const initializerClassNames = [
-        "Zeros",
-        "Ones",
-        "Constant",
-        "RandomNormal",
-        "RandomUniform",
-        "TruncatedNormal",
-        "VarianceScaling",
-        "Orthogonal",
-        "Identity",
-      ];
-      //# sourceMappingURL=initializer_config.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/initializers.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      function checkFanMode(value) {
-        checkStringTypeUnionValue(VALID_FAN_MODE_VALUES, "FanMode", value);
-      }
-      function checkDistribution(value) {
-        checkStringTypeUnionValue(VALID_DISTRIBUTION_VALUES, "Distribution", value);
-      }
-      /**
-       * Initializer base class.
-       *
-       * @doc {
-       *   heading: 'Initializers', subheading: 'Classes', namespace: 'initializers'}
-       */
-      class initializers_Initializer extends dist["serialization"].Serializable {
-        fromConfigUsesCustomObjects() {
-          return false;
-        }
-        getConfig() {
-          return {};
-        }
-      }
-      class initializers_Zeros extends initializers_Initializer {
-        apply(shape, dtype) {
-          return Object(dist["zeros"])(shape, dtype);
-        }
-      }
-      /** @nocollapse */
-      initializers_Zeros.className = "Zeros";
-      dist["serialization"].registerClass(initializers_Zeros);
-      class initializers_Ones extends initializers_Initializer {
-        apply(shape, dtype) {
-          return Object(dist["ones"])(shape, dtype);
-        }
-      }
-      /** @nocollapse */
-      initializers_Ones.className = "Ones";
-      dist["serialization"].registerClass(initializers_Ones);
-      class initializers_Constant extends initializers_Initializer {
-        constructor(args) {
-          super();
-          if (typeof args !== "object") {
-            throw new ValueError(`Expected argument of type ConstantConfig but got ${args}`);
-          }
-          if (args.value === undefined) {
-            throw new ValueError(`config must have value set but got ${args}`);
-          }
-          this.value = args.value;
-        }
-        apply(shape, dtype) {
-          return Object(dist["tidy"])(() =>
-            Object(dist["mul"])(
-              Object(dist["scalar"])(this.value),
-              Object(dist["ones"])(shape, dtype)
-            )
-          );
-        }
-        getConfig() {
-          return {
-            value: this.value,
-          };
-        }
-      }
-      /** @nocollapse */
-      initializers_Constant.className = "Constant";
-      dist["serialization"].registerClass(initializers_Constant);
-      class initializers_RandomUniform extends initializers_Initializer {
-        constructor(args) {
-          super();
-          this.DEFAULT_MINVAL = -0.05;
-          this.DEFAULT_MAXVAL = 0.05;
-          this.minval = args.minval || this.DEFAULT_MINVAL;
-          this.maxval = args.maxval || this.DEFAULT_MAXVAL;
-          this.seed = args.seed;
-        }
-        apply(shape, dtype) {
-          return Object(dist["randomUniform"])(shape, this.minval, this.maxval, dtype);
-        }
-        getConfig() {
-          return { minval: this.minval, maxval: this.maxval, seed: this.seed };
-        }
-      }
-      /** @nocollapse */
-      initializers_RandomUniform.className = "RandomUniform";
-      dist["serialization"].registerClass(initializers_RandomUniform);
-      class initializers_RandomNormal extends initializers_Initializer {
-        constructor(args) {
-          super();
-          this.DEFAULT_MEAN = 0;
-          this.DEFAULT_STDDEV = 0.05;
-          this.mean = args.mean || this.DEFAULT_MEAN;
-          this.stddev = args.stddev || this.DEFAULT_STDDEV;
-          this.seed = args.seed;
-        }
-        apply(shape, dtype) {
-          dtype = dtype || "float32";
-          if (dtype !== "float32" && dtype !== "int32") {
-            throw new NotImplementedError(`randomNormal does not support dType ${dtype}.`);
-          }
-          return randomNormal(shape, this.mean, this.stddev, dtype, this.seed);
-        }
-        getConfig() {
-          return { mean: this.mean, stddev: this.stddev, seed: this.seed };
-        }
-      }
-      /** @nocollapse */
-      initializers_RandomNormal.className = "RandomNormal";
-      dist["serialization"].registerClass(initializers_RandomNormal);
-      class initializers_TruncatedNormal extends initializers_Initializer {
-        constructor(args) {
-          super();
-          this.DEFAULT_MEAN = 0;
-          this.DEFAULT_STDDEV = 0.05;
-          this.mean = args.mean || this.DEFAULT_MEAN;
-          this.stddev = args.stddev || this.DEFAULT_STDDEV;
-          this.seed = args.seed;
-        }
-        apply(shape, dtype) {
-          dtype = dtype || "float32";
-          if (dtype !== "float32" && dtype !== "int32") {
-            throw new NotImplementedError(`truncatedNormal does not support dType ${dtype}.`);
-          }
-          return Object(dist["truncatedNormal"])(shape, this.mean, this.stddev, dtype, this.seed);
-        }
-        getConfig() {
-          return { mean: this.mean, stddev: this.stddev, seed: this.seed };
-        }
-      }
-      /** @nocollapse */
-      initializers_TruncatedNormal.className = "TruncatedNormal";
-      dist["serialization"].registerClass(initializers_TruncatedNormal);
-      class initializers_Identity extends initializers_Initializer {
-        constructor(args) {
-          super();
-          this.gain = args.gain != null ? args.gain : 1.0;
-        }
-        apply(shape, dtype) {
-          return Object(dist["tidy"])(() => {
-            if (shape.length !== 2 || shape[0] !== shape[1]) {
-              throw new ValueError(
-                "Identity matrix initializer can only be used for" + " 2D square matrices."
-              );
-            } else {
-              return Object(dist["mul"])(this.gain, Object(dist["eye"])(shape[0]));
-            }
-          });
-        }
-        getConfig() {
-          return { gain: this.gain };
-        }
-      }
-      /** @nocollapse */
-      initializers_Identity.className = "Identity";
-      dist["serialization"].registerClass(initializers_Identity);
-      /**
-       * Computes the number of input and output units for a weight shape.
-       * @param shape Shape of weight.
-       * @param dataFormat data format to use for convolution kernels.
-       *   Note that all kernels in Keras are standardized on the
-       *   CHANNEL_LAST ordering (even when inputs are set to CHANNEL_FIRST).
-       * @return An length-2 array: fanIn, fanOut.
-       */
-      function computeFans(shape, dataFormat = "channelsLast") {
-        let fanIn;
-        let fanOut;
-        checkDataFormat(dataFormat);
-        if (shape.length === 2) {
-          fanIn = shape[0];
-          fanOut = shape[1];
-        } else if ([3, 4, 5].indexOf(shape.length) !== -1) {
-          if (dataFormat === "channelsFirst") {
-            const receptiveFieldSize = arrayProd(shape, 2);
-            fanIn = shape[1] * receptiveFieldSize;
-            fanOut = shape[0] * receptiveFieldSize;
-          } else if (dataFormat === "channelsLast") {
-            const receptiveFieldSize = arrayProd(shape, 0, shape.length - 2);
-            fanIn = shape[shape.length - 2] * receptiveFieldSize;
-            fanOut = shape[shape.length - 1] * receptiveFieldSize;
-          }
-        } else {
-          const shapeProd = arrayProd(shape);
-          fanIn = Math.sqrt(shapeProd);
-          fanOut = Math.sqrt(shapeProd);
-        }
-        return [fanIn, fanOut];
-      }
-      class initializers_VarianceScaling extends initializers_Initializer {
-        /**
-         * Constructor of VarianceScaling.
-         * @throws ValueError for invalid value in scale.
-         */
-        constructor(args) {
-          super();
-          if (args.scale < 0.0) {
-            throw new ValueError(`scale must be a positive float. Got: ${args.scale}`);
-          }
-          this.scale = args.scale == null ? 1.0 : args.scale;
-          this.mode = args.mode == null ? "fanIn" : args.mode;
-          checkFanMode(this.mode);
-          this.distribution = args.distribution == null ? "normal" : args.distribution;
-          checkDistribution(this.distribution);
-          this.seed = args.seed;
-        }
-        apply(shape, dtype) {
-          const fans = computeFans(shape);
-          const fanIn = fans[0];
-          const fanOut = fans[1];
-          let scale = this.scale;
-          if (this.mode === "fanIn") {
-            scale /= Math.max(1, fanIn);
-          } else if (this.mode === "fanOut") {
-            scale /= Math.max(1, fanOut);
-          } else {
-            scale /= Math.max(1, (fanIn + fanOut) / 2);
-          }
-          if (this.distribution === "normal") {
-            const stddev = Math.sqrt(scale);
-            dtype = dtype || "float32";
-            if (dtype !== "float32" && dtype !== "int32") {
-              throw new NotImplementedError(
-                `${this.getClassName()} does not support dType ${dtype}.`
-              );
-            }
-            return Object(dist["truncatedNormal"])(shape, 0, stddev, dtype, this.seed);
-          } else {
-            const limit = Math.sqrt(3 * scale);
-            return Object(dist["randomUniform"])(shape, -limit, limit, dtype);
-          }
-        }
-        getConfig() {
-          return {
-            scale: this.scale,
-            mode: this.mode,
-            distribution: this.distribution,
-            seed: this.seed,
-          };
-        }
-      }
-      /** @nocollapse */
-      initializers_VarianceScaling.className = "VarianceScaling";
-      dist["serialization"].registerClass(initializers_VarianceScaling);
-      class GlorotUniform extends initializers_VarianceScaling {
-        /**
-         * Constructor of GlorotUniform
-         * @param scale
-         * @param mode
-         * @param distribution
-         * @param seed
-         */
-        constructor(args) {
-          super({
-            scale: 1.0,
-            mode: "fanAvg",
-            distribution: "uniform",
-            seed: args == null ? null : args.seed,
-          });
-        }
-        getClassName() {
-          // In Python Keras, GlorotUniform is not a class, but a helper method
-          // that creates a VarianceScaling object. Use 'VarianceScaling' as
-          // class name to be compatible with that.
-          return initializers_VarianceScaling.className;
-        }
-      }
-      /** @nocollapse */
-      GlorotUniform.className = "GlorotUniform";
-      dist["serialization"].registerClass(GlorotUniform);
-      class GlorotNormal extends initializers_VarianceScaling {
-        /**
-         * Constructor of GlorotNormal.
-         * @param scale
-         * @param mode
-         * @param distribution
-         * @param seed
-         */
-        constructor(args) {
-          super({
-            scale: 1.0,
-            mode: "fanAvg",
-            distribution: "normal",
-            seed: args == null ? null : args.seed,
-          });
-        }
-        getClassName() {
-          // In Python Keras, GlorotNormal is not a class, but a helper method
-          // that creates a VarianceScaling object. Use 'VarianceScaling' as
-          // class name to be compatible with that.
-          return initializers_VarianceScaling.className;
-        }
-      }
-      /** @nocollapse */
-      GlorotNormal.className = "GlorotNormal";
-      dist["serialization"].registerClass(GlorotNormal);
-      class HeNormal extends initializers_VarianceScaling {
-        constructor(args) {
-          super({
-            scale: 2.0,
-            mode: "fanIn",
-            distribution: "normal",
-            seed: args == null ? null : args.seed,
-          });
-        }
-        getClassName() {
-          // In Python Keras, HeNormal is not a class, but a helper method
-          // that creates a VarianceScaling object. Use 'VarianceScaling' as
-          // class name to be compatible with that.
-          return initializers_VarianceScaling.className;
-        }
-      }
-      /** @nocollapse */
-      HeNormal.className = "HeNormal";
-      dist["serialization"].registerClass(HeNormal);
-      class HeUniform extends initializers_VarianceScaling {
-        constructor(args) {
-          super({
-            scale: 2.0,
-            mode: "fanIn",
-            distribution: "uniform",
-            seed: args == null ? null : args.seed,
-          });
-        }
-        getClassName() {
-          // In Python Keras, HeUniform is not a class, but a helper method
-          // that creates a VarianceScaling object. Use 'VarianceScaling' as
-          // class name to be compatible with that.
-          return initializers_VarianceScaling.className;
-        }
-      }
-      /** @nocollapse */
-      HeUniform.className = "HeUniform";
-      dist["serialization"].registerClass(HeUniform);
-      class LeCunNormal extends initializers_VarianceScaling {
-        constructor(args) {
-          super({
-            scale: 1.0,
-            mode: "fanIn",
-            distribution: "normal",
-            seed: args == null ? null : args.seed,
-          });
-        }
-        getClassName() {
-          // In Python Keras, LeCunNormal is not a class, but a helper method
-          // that creates a VarianceScaling object. Use 'VarianceScaling' as
-          // class name to be compatible with that.
-          return initializers_VarianceScaling.className;
-        }
-      }
-      /** @nocollapse */
-      LeCunNormal.className = "LeCunNormal";
-      dist["serialization"].registerClass(LeCunNormal);
-      class LeCunUniform extends initializers_VarianceScaling {
-        constructor(args) {
-          super({
-            scale: 1.0,
-            mode: "fanIn",
-            distribution: "uniform",
-            seed: args == null ? null : args.seed,
-          });
-        }
-        getClassName() {
-          // In Python Keras, LeCunUniform is not a class, but a helper method
-          // that creates a VarianceScaling object. Use 'VarianceScaling' as
-          // class name to be compatible with that.
-          return initializers_VarianceScaling.className;
-        }
-      }
-      /** @nocollapse */
-      LeCunUniform.className = "LeCunNormal";
-      dist["serialization"].registerClass(LeCunUniform);
-      class initializers_Orthogonal extends initializers_Initializer {
-        constructor(args) {
-          super();
-          this.DEFAULT_GAIN = 1;
-          this.gain = args.gain == null ? this.DEFAULT_GAIN : args.gain;
-          this.seed = args.seed;
-          if (this.seed != null) {
-            throw new NotImplementedError(
-              "Random seed is not implemented for Orthogonal Initializer yet."
-            );
-          }
-        }
-        apply(shape, dtype) {
-          return Object(dist["tidy"])(() => {
-            if (shape.length !== 2) {
-              throw new NotImplementedError(
-                "The Orthogonal Initializer does not support non-2D shapes yet."
-              );
-            }
-            if (shape[0] * shape[1] > 2000) {
-              console.warn(
-                `Orthogonal initializer is being called on a matrix with more ` +
-                  `than 2000 (${shape[0] * shape[1]}) elements: ` +
-                  `Slowness may result.`
-              );
-            }
-            // TODO(cais): Add seed support.
-            const normalizedShape = shape[0] > shape[1] ? [shape[1], shape[0]] : shape;
-            const a = randomNormal(normalizedShape, 0, 1, "float32");
-            let q = dist["linalg"].gramSchmidt(a);
-            if (shape[0] > shape[1]) {
-              q = q.transpose();
-            }
-            return Object(dist["mul"])(this.gain, q);
-          });
-        }
-        getConfig() {
-          return {
-            gain: this.gain,
-            seed: this.seed,
-          };
-        }
-      }
-      /** @nocollapse */
-      initializers_Orthogonal.className = "Orthogonal";
-      dist["serialization"].registerClass(initializers_Orthogonal);
-      // Maps the JavaScript-like identifier keys to the corresponding registry
-      // symbols.
-      const INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP = {
-        constant: "Constant",
-        glorotNormal: "GlorotNormal",
-        glorotUniform: "GlorotUniform",
-        heNormal: "HeNormal",
-        heUniform: "HeUniform",
-        identity: "Identity",
-        leCunNormal: "LeCunNormal",
-        leCunUniform: "LeCunUniform",
-        ones: "Ones",
-        orthogonal: "Orthogonal",
-        randomNormal: "RandomNormal",
-        randomUniform: "RandomUniform",
-        truncatedNormal: "TruncatedNormal",
-        varianceScaling: "VarianceScaling",
-        zeros: "Zeros",
-      };
-      function deserializeInitializer(config, customObjects = {}) {
-        return deserializeKerasObject(
-          config,
-          dist["serialization"].SerializationMap.getMap().classNameMap,
-          customObjects,
-          "initializer"
-        );
-      }
-      function serializeInitializer(initializer) {
-        return serializeKerasObject(initializer);
-      }
-      function getInitializer(identifier) {
-        if (typeof identifier === "string") {
-          const className =
-            identifier in INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP
-              ? INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier]
-              : identifier;
-          /* We have four 'helper' classes for common initializers that
-        all get serialized as 'VarianceScaling' and shouldn't go through
-        the deserializeInitializer pathway. */
-          if (className === "GlorotNormal") {
-            return new GlorotNormal();
-          } else if (className === "GlorotUniform") {
-            return new GlorotUniform();
-          } else if (className === "HeNormal") {
-            return new HeNormal();
-          } else if (className === "HeUniform") {
-            return new HeUniform();
-          } else if (className === "LeCunNormal") {
-            return new LeCunNormal();
-          } else if (className === "LeCunUniform") {
-            return new LeCunUniform();
-          } else {
-            const config = {};
-            config["className"] = className;
-            config["config"] = {};
-            return deserializeInitializer(config);
-          }
-        } else if (identifier instanceof initializers_Initializer) {
-          return identifier;
-        } else {
-          return deserializeInitializer(identifier);
-        }
-      }
-      //# sourceMappingURL=initializers.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_initializers.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      // tslint:disable-next-line:max-line-length
-
-      /**
-       * Initializer that generates tensors initialized to 0.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function zeros() {
-        return new initializers_Zeros();
-      }
-      /**
-       * Initializer that generates tensors initialized to 1.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function exports_initializers_ones() {
-        return new initializers_Ones();
-      }
-      /**
-       * Initializer that generates values initialized to some constant.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function constant(args) {
-        return new initializers_Constant(args);
-      }
-      /**
-       * Initializer that generates random values initialized to a uniform
-       * distribution.
-       *
-       * Values will be distributed uniformly between the configured minval and
-       * maxval.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function randomUniform(args) {
-        return new initializers_RandomUniform(args);
-      }
-      /**
-       * Initializer that generates random values initialized to a normal
-       * distribution.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function exports_initializers_randomNormal(args) {
-        return new initializers_RandomNormal(args);
-      }
-      /**
-       * Initializer that generates random values initialized to a truncated normal.
-       * distribution.
-       *
-       * These values are similar to values from a `RandomNormal` except that values
-       * more than two standard deviations from the mean are discarded and re-drawn.
-       * This is the recommended initializer for neural network weights and filters.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function truncatedNormal(args) {
-        return new initializers_TruncatedNormal(args);
-      }
-      /**
-       * Initializer that generates the identity matrix.
-       * Only use for square 2D matrices.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function identity(args) {
-        return new initializers_Identity(args);
-      }
-      /**
-       * Initializer capable of adapting its scale to the shape of weights.
-       * With distribution=NORMAL, samples are drawn from a truncated normal
-       * distribution centered on zero, with `stddev = sqrt(scale / n)` where n is:
-       *   - number of input units in the weight tensor, if mode = FAN_IN.
-       *   - number of output units, if mode = FAN_OUT.
-       *   - average of the numbers of input and output units, if mode = FAN_AVG.
-       * With distribution=UNIFORM,
-       * samples are drawn from a uniform distribution
-       * within [-limit, limit], with `limit = sqrt(3 * scale / n)`.
-       */
-      /** @doc {heading: 'Initializers',namespace: 'initializers'} */
-      function varianceScaling(config) {
-        return new initializers_VarianceScaling(config);
-      }
-      /**
-       * Glorot uniform initializer, also called Xavier uniform initializer.
-       * It draws samples from a uniform distribution within [-limit, limit]
-       * where `limit` is `sqrt(6 / (fan_in + fan_out))`
-       * where `fan_in` is the number of input units in the weight tensor
-       * and `fan_out` is the number of output units in the weight tensor
-       *
-       * Reference:
-       *   Glorot & Bengio, AISTATS 2010
-       *       http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function glorotUniform(args) {
-        return new GlorotUniform(args);
-      }
-      /**
-       * Glorot normal initializer, also called Xavier normal initializer.
-       * It draws samples from a truncated normal distribution centered on 0
-       * with `stddev = sqrt(2 / (fan_in + fan_out))`
-       * where `fan_in` is the number of input units in the weight tensor
-       * and `fan_out` is the number of output units in the weight tensor.
-       *
-       * Reference:
-       *   Glorot & Bengio, AISTATS 2010
-       *       http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function glorotNormal(args) {
-        return new GlorotNormal(args);
-      }
-      /**
-       * He normal initializer.
-       *
-       * It draws samples from a truncated normal distribution centered on 0
-       * with `stddev = sqrt(2 / fanIn)`
-       * where `fanIn` is the number of input units in the weight tensor.
-       *
-       * Reference:
-       *     He et al., http://arxiv.org/abs/1502.01852
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function heNormal(args) {
-        return new HeNormal(args);
-      }
-      /**
-       * He uniform initializer.
-       *
-       * It draws samples from a uniform distribution within [-limit, limit]
-       * where `limit` is `sqrt(6 / fan_in)`
-       * where `fanIn` is the number of input units in the weight tensor.
-       *
-       * Reference:
-       *     He et al., http://arxiv.org/abs/1502.01852
-       */
-      /** @doc {heading: 'Initializers',namespace: 'initializers'} */
-      function heUniform(args) {
-        return new HeUniform(args);
-      }
-      /**
-       * LeCun normal initializer.
-       *
-       * It draws samples from a truncated normal distribution centered on 0
-       * with `stddev = sqrt(1 / fanIn)`
-       * where `fanIn` is the number of input units in the weight tensor.
-       *
-       * References:
-       *   [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)
-       *   [Efficient Backprop](http://yann.lecun.com/exdb/publis/pdf/lecun-98b.pdf)
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function leCunNormal(args) {
-        return new LeCunNormal(args);
-      }
-      /**
-       * LeCun uniform initializer.
-       *
-       * It draws samples from a uniform distribution in the interval
-       * `[-limit, limit]` with `limit = sqrt(3 / fanIn)`,
-       * where `fanIn` is the number of input units in the weight tensor.
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function leCunUniform(args) {
-        return new LeCunUniform(args);
-      }
-      /**
-       * Initializer that generates a random orthogonal matrix.
-       *
-       * Reference:
-       * [Saxe et al., http://arxiv.org/abs/1312.6120](http://arxiv.org/abs/1312.6120)
-       */
-      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
-      function orthogonal(args) {
-        return new initializers_Orthogonal(args);
-      }
-      //# sourceMappingURL=exports_initializers.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/backend/state.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Utilities related to persistent state in the backend.
-       */
-      /**
-       * An ID to track `tf.SymbolicTensor`s and derived classes.
-       * Required in different places in engine/topology.ts to identify unique
-       * tensors.
-       */
-      let _nextUniqueTensorId = 0;
-      function getNextUniqueTensorId() {
-        return _nextUniqueTensorId++;
-      }
-      const _uidPrefixes = {};
-      /**
-       * Provides a unique UID given a string prefix.
-       *
-       * @param prefix
-       */
-      function getUid(prefix = "") {
-        if (!(prefix in _uidPrefixes)) {
-          _uidPrefixes[prefix] = 0;
-        }
-        _uidPrefixes[prefix] += 1;
-        return prefix + _uidPrefixes[prefix].toString();
-      }
-      //# sourceMappingURL=state.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/types_utils.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      // tslint:enable
-      /**
-       * Determine whether the input is an Array of Shapes.
-       */
-      function isArrayOfShapes(x) {
-        return Array.isArray(x) && Array.isArray(x[0]);
-      }
-      /**
-       * Special case of normalizing shapes to lists.
-       *
-       * @param x A shape or list of shapes to normalize into a list of Shapes.
-       * @return A list of Shapes.
-       */
-      function normalizeShapeList(x) {
-        if (x.length === 0) {
-          return [];
-        }
-        if (!Array.isArray(x[0])) {
-          return [x];
-        }
-        return x;
-      }
-      /**
-       * Helper function to obtain exactly one Tensor.
-       * @param xs: A single `tf.Tensor` or an `Array` of `tf.Tensor`s.
-       * @return A single `tf.Tensor`. If `xs` is an `Array`, return the first one.
-       * @throws ValueError: If `xs` is an `Array` and its length is not 1.
-       */
-      function getExactlyOneTensor(xs) {
-        let x;
-        if (Array.isArray(xs)) {
-          if (xs.length !== 1) {
-            throw new ValueError(`Expected Tensor length to be 1; got ${xs.length}`);
-          }
-          x = xs[0];
-        } else {
-          x = xs;
-        }
-        return x;
-      }
-      /**
-       * Helper function to obtain exactly on instance of Shape.
-       *
-       * @param shapes Input single `Shape` or Array of `Shape`s.
-       * @returns If input is a single `Shape`, return it unchanged. If the input is
-       *   an `Array` containing exactly one instance of `Shape`, return the instance.
-       *   Otherwise, throw a `ValueError`.
-       * @throws ValueError: If input is an `Array` of `Shape`s, and its length is not
-       *   1.
-       */
-      function getExactlyOneShape(shapes) {
-        if (Array.isArray(shapes) && Array.isArray(shapes[0])) {
-          if (shapes.length === 1) {
-            shapes = shapes;
-            return shapes[0];
-          } else {
-            throw new ValueError(`Expected exactly 1 Shape; got ${shapes.length}`);
-          }
-        } else {
-          return shapes;
-        }
-      }
-      //# sourceMappingURL=types_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/variable_utils.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Count the elements in an Array of LayerVariables.
-       *
-       * @param weights: The LayerVariables of which the constituent numbers are to
-       *   be counted.
-       * @returns A count of the elements in all the LayerVariables
-       */
-      function countParamsInWeights(weights) {
-        let count = 0;
-        for (const weight of weights) {
-          if (weight.shape.length === 0) {
-            count += 1;
-          } else {
-            count += weight.shape.reduce((a, b) => a * b);
-          }
-        }
-        return count;
-      }
-      //# sourceMappingURL=variable_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/variables.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      const DEFAULT_VARIABLE_NAME_PREFIX = "Variable";
-      /**
-       * A `tf.layers.LayerVariable` is similar to a `tf.Tensor` in that it has a
-       * dtype and shape, but its value is mutable.  The value is itself represented
-       * as a`tf.Tensor`, and can be read with the `read()` method and updated with
-       * the `write()` method.
-       */
-      class variables_LayerVariable {
-        /**
-         * Construct Variable from a `tf.Tensor`.
-         *
-         * If not explicitly named, the Variable will be given a name with the
-         * prefix 'Variable'. Variable names are unique. In the case of name
-         * collision, suffixies '_<num>' will be added to the name.
-         *
-         * @param val Initial value of the Variable.
-         * @param name Name of the variable. If `null` or `undefined` is provided, it
-         *   will default a name with the prefix 'Variable'.
-         * @param constraint Optional, projection function to be applied to the
-         * variable after optimize updates
-         * @throws ValueError if `name` is `null` or `undefined`.
-         */
-        constructor(
-          val,
-          dtype = "float32",
-          name = DEFAULT_VARIABLE_NAME_PREFIX,
-          trainable = true,
-          constraint = null
-        ) {
-          this.dtype = dtype == null ? "float32" : dtype;
-          this.shape = val.shape;
-          this.id = getNextUniqueTensorId();
-          name = name == null ? DEFAULT_VARIABLE_NAME_PREFIX : name;
-          this.originalName = getScopedTensorName(name);
-          this.name = getUniqueTensorName(this.originalName);
-          this.trainable_ = trainable;
-          this.constraint = constraint;
-          this.val = dist["variable"](val, this.trainable_, this.name, this.dtype);
-        }
-        /**
-         * Get a snapshot of the Variable's value.
-         *
-         * The returned value is a snapshot of the Variable's value at the time of
-         * the invocation. Future mutations in the value of the tensor will only
-         * be reflected by future calls to this method.
-         */
-        read() {
-          this.assertNotDisposed();
-          return this.val;
-        }
-        /**
-         * Update the value of the Variable.
-         *
-         * @param newVal: The new value to update to. Must be consistent with the
-         *   dtype and shape of the Variable.
-         * @return This Variable.
-         */
-        write(newVal) {
-          // TODO(cais): Once  TF.js Core supports Tensor.dtype, check dtype match.
-          this.assertNotDisposed();
-          checkShapesMatch(this.val, newVal);
-          // Skip updating if this is the exact same tensor.
-          if (this.val.id !== newVal.id) {
-            this.val.assign(newVal);
-            if (this.constraint != null) {
-              this.val.assign(this.constraint.apply(this.val));
-            }
-          }
-          return this;
-        }
-        /**
-         * Dispose this LayersVariable instance from memory.
-         */
-        dispose() {
-          this.assertNotDisposed();
-          this.val.dispose();
-        }
-        assertNotDisposed() {
-          if (this.val.isDisposed) {
-            throw new Error(`LayersVariable ${this.name} is already disposed.`);
-          }
-        }
-        get trainable() {
-          return this.trainable_;
-        }
-        set trainable(trainable) {
-          this.trainable_ = trainable;
-          this.val.trainable = trainable;
-        }
-      }
-      function checkShapesMatch(x, y) {
-        if (x.shape.toString() !== y.shape.toString()) {
-          throw new Error(
-            "Shape mismatch: " + JSON.stringify(x.shape) + " vs. " + JSON.stringify(y.shape)
-          );
-        }
-      }
-      /**
-       * Create a Variable.
-       * @param x The initial value of the `Variable`.
-       * @param dtype optional, the type of the variable.
-       * @param name optional, the name of the variable, default provided by
-       * Variable.
-       * @param constraint optional, a constraint to be applied after every update.
-       * @return The newly instantiated `Variable`.
-       */
-      function variables_variable(x, dtype, name, constraint) {
-        return new variables_LayerVariable(x, dtype, name, true, constraint);
-      }
-      /**
-       * Instantiates an all-zeros Variable and returns it.
-       *
-       * @param shape Shape of the tensor.
-       * @param dtype DType of the tensor.
-       * @param name Name of the tensor.
-       * @return An all-zero Variable.
-       */
-      function zerosVariable(shape, dtype, name) {
-        // TODO(cais): Implement logic for dtype.
-        return new variables_LayerVariable(dist["zeros"](shape), dtype, name);
-      }
-      /**
-       * Instantiates an all-zeros tensor of the same shape as another tensor.
-       *
-       * @param x The other tensor.
-       * @param dtype DType of the tensor.
-       * @param name Name of the tensor.
-       * @return A newly instantiated Variable.
-       */
-      function zerosLike(x, dtype, name) {
-        return new variables_LayerVariable(dist["zerosLike"](x), dtype, name);
-      }
-      /**
-       * Instantiates an all-ones tensor and returns it.
-       *
-       * @param shape Shape of the tensor.
-       * @param dtype DType of the tensor.
-       * @param name Name of the tensor.
-       * @return An all-ones Variable.
-       */
-      function onesVariable(shape, dtype, name) {
-        // TODO(cais): Implement logic for dtype.
-        const allocated = dist["ones"](shape);
-        return new variables_LayerVariable(allocated, dtype, name);
-      }
-      /**
-       * Instantiates an all-ones tensor of the same shape as another tensor.
-       *
-       * @param x The other tensor.
-       * @param dtype DType of the tensor.
-       * @param name Name of the tensor.
-       * @return A newly instantiated Variable.
-       */
-      function onesLike(x, dtype, name) {
-        const allocated = dist["onesLike"](x);
-        return new variables_LayerVariable(allocated, dtype, name);
-      }
-      /**
-       * Instantiate an identity matrix and returns it, as a Variable
-       *
-       * @param size Number of rows/columns.
-       * @param dtype Data type of returned Variable.
-       * @param name Name of returned Variable.
-       * @return A Variable, an identity matrix.
-       */
-      function eyeVariable(size, dtype, name) {
-        return new variables_LayerVariable(dist["eye"](size), dtype, name);
-      }
-      /**
-       * Get a Variable with uniform distribution of values.
-       * @param shape Shape of the tensor.
-       * @param minval Lower bound of the uniform distribution.
-       * @param maxval Upper bound of the uniform distribution.
-       * @param dtype
-       * @param seed
-       * @param name Optional name.
-       * @return The uniform-random Variable.
-       */
-      function randomUniformVariable(shape, minval, maxval, dtype, seed, name = "randomUniform") {
-        return new variables_LayerVariable(
-          dist["randomUniform"](shape, minval, maxval, dtype),
-          dtype,
-          name
-        );
-      }
-      /**
-       * Get a Variable with truncated-normal distribution of values.
-       * @param shape Shape of the tensor.
-       * @param mean mean value of the normal distribution.
-       * @param stddev standard deviation of the normal distribution.
-       * @param dtype
-       * @param seed
-       * @param name Optional name.
-       * @return The truncated-normal-random Variable.
-       */
-      function truncatedNormalVariable(
-        shape,
-        mean = 0.0,
-        stddev = 1.0,
-        dtype,
-        seed,
-        name = "truncatedNormal"
-      ) {
-        // TODO(cais): Implement logic for dtype and seed once they are supported
-        // by deeplearn.js.
-        dtype = dtype || "float32";
-        if (dtype !== "float32" && dtype !== "int32") {
-          throw new NotImplementedError(`randomNormal does not support dType ${dtype}.`);
-        }
-        return new variables_LayerVariable(
-          dist["truncatedNormal"](shape, mean, stddev, dtype, seed),
-          dtype,
-          name
-        );
-      }
-      /**
-       * Get a Variable with normal distribution of values.
-       * @param shape Shape of the tensor.
-       * @param mean mean value of the normal distribution.
-       * @param stddev standard deviation of the normal distribution.
-       * @param dtype
-       * @param seed
-       * @param name Optional name.
-       * @return The truncated-normal-random Variable.
-       */
-      function randomNormalVariable(
-        shape,
-        mean = 0.0,
-        stddev = 1.0,
-        dtype,
-        seed,
-        name = "randomNormal"
-      ) {
-        dtype = dtype || "float32";
-        if (dtype !== "float32" && dtype !== "int32") {
-          throw new NotImplementedError(`randomNormalVariable does not support dType ${dtype}.`);
-        }
-        return new variables_LayerVariable(
-          dist["randomNormal"](shape, mean, stddev, dtype, seed),
-          dtype,
-          name
-        );
-      }
-      /**
-       * Update the value of a Variable.
-       * @param x The Variable to be updated.
-       * @param xNew The new value to update to.
-       * @return The Variable updated.
-       */
-      function update(x, xNew) {
-        return x.write(xNew);
-      }
-      /**
-       * Update the value of a Variable by adding an increment.
-       * @param x The Variable to be updated.
-       * @param increment The incrment to add to `x`.
-       * @return The Variable updated.
-       */
-      function updateAdd(x, increment) {
-        return x.write(dist["add"](x.read(), increment));
-      }
-      /**
-       * Update the value of a Variable by subtracting a decrement.
-       * @param x The Variable to be updated.
-       * @param decrement The decrement to subtract from `x`.
-       * @return The Variable updated.
-       */
-      function updateSub(x, decrement) {
-        return x.write(dist["sub"](x.read(), decrement));
-      }
-      /**
-       * Get the values of an array of Variables.
-       *
-       * @param tensors An `Array` of `Variable`s to get the values of.
-       * @return The values of the inputs, as an `Array` of`tf.Tensor`s.
-       */
-      function batchGetValue(xs) {
-        return xs.map((x) => x.read());
-      }
-      /**
-       * Update the value of multiple Variables at once.
-       *
-       * @param variablesAndValues An `Array`, each element is of type
-       *   [Variable, Tensor]. The first item is the
-       *   `Variable` of which the value is to be updated. The second item
-       *   carries the new value.
-       */
-      function batchSetValue(variablesAndValues) {
-        variablesAndValues.forEach((variableAndValue) => {
-          const variable = variableAndValue[0];
-          variable.write(variableAndValue[1]);
-        });
-      }
-      /**
-       * Returns the gradients of `variables` w.r.t. the return value of `lossFn`.
-       * @param lossFn A function which returns a Scalar to be used as the function
-       *   value (i.e., numerator) for differentiation.
-       * @param variables List of variables to be used as the independent variables
-       *   (i.e., denominator) for differentiation.
-       * @returns An Array of gradients tensors.
-       */
-      function gradients(lossFn, variables) {
-        // TODO(cais): The return type signature can be simplified if deeplearn makes
-        //   the corresponding type public.
-        const variableList = variables.map((variable) => variable.read());
-        const valudAndGrads = Object(dist["variableGrads"])(lossFn, variableList);
-        return variables.map((variable) => valudAndGrads.grads[variable.name]);
-      }
-      //# sourceMappingURL=variables.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/topology.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original source: keras/engine/topology.py */
-
-      /**
-       * Specifies the ndim, dtype and shape of every input to a layer.
-       *
-       * Every layer should expose (if appropriate) an `inputSpec` attribute:
-       * a list of instances of InputSpec (one per input tensor).
-       *
-       * A null entry in a shape is compatible with any dimension,
-       * a null shape is compatible with any shape.
-       */
-      class InputSpec {
-        constructor(args) {
-          this.dtype = args.dtype;
-          this.shape = args.shape;
-          /*
-          TODO(michaelterry): Could throw error if ndim and shape are both defined
-            (then backport).
-        */
-          if (args.shape != null) {
-            this.ndim = args.shape.length;
-          } else {
-            this.ndim = args.ndim;
-          }
-          this.maxNDim = args.maxNDim;
-          this.minNDim = args.minNDim;
-          this.axes = args.axes || {};
-        }
-      }
-      /**
-       * `tf.SymbolicTensor` is a placeholder for a Tensor without any concrete value.
-       *
-       * They are most often encountered when building a graph of `Layer`s for a
-       * a `tf.LayersModel` and the input data's shape, but not values are known.
-       */
-      /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-      class topology_SymbolicTensor {
-        /**
-         *
-         * @param dtype
-         * @param shape
-         * @param sourceLayer The Layer that produced this symbolic tensor.
-         * @param inputs The inputs passed to sourceLayer's __call__() method.
-         * @param nodeIndex
-         * @param tensorIndex
-         * @param callArgs The keyword arguments passed to the __call__() method.
-         * @param name
-         * @param outputTensorIndex The index of this tensor in the list of outputs
-         *   returned by apply().
-         */
-        constructor(dtype, shape, sourceLayer, inputs, callArgs, name, outputTensorIndex) {
-          this.dtype = dtype;
-          this.shape = shape;
-          this.sourceLayer = sourceLayer;
-          this.inputs = inputs;
-          this.callArgs = callArgs;
-          this.outputTensorIndex = outputTensorIndex;
-          this.id = getNextUniqueTensorId();
-          if (name != null) {
-            this.originalName = getScopedTensorName(name);
-            this.name = getUniqueTensorName(this.originalName);
-          }
-          this.rank = shape.length;
-        }
-      }
-      let _nextNodeID = 0;
-      /**
-       * A `Node` describes the connectivity between two layers.
-       *
-       * Each time a layer is connected to some new input,
-       * a node is added to `layer.inboundNodes`.
-       *
-       * Each time the output of a layer is used by another layer,
-       * a node is added to `layer.outboundNodes`.
-       *
-       * `nodeIndices` and `tensorIndices` are basically fine-grained coordinates
-       * describing the origin of the `inputTensors`, verifying the following:
-       *
-       * `inputTensors[i] ==
-       * inboundLayers[i].inboundNodes[nodeIndices[i]].outputTensors[
-       *   tensorIndices[i]]`
-       *
-       * A node from layer A to layer B is added to:
-       *     A.outboundNodes
-       *     B.inboundNodes
-       */
-      class Node {
-        constructor(
-          args,
-          // TODO(michaelterry): Define actual type for this.
-          callArgs
-        ) {
-          this.callArgs = callArgs;
-          this.id = _nextNodeID++;
-          /*
-          Layer instance (NOT a list).
-          this is the layer that takes a list of input tensors
-          and turns them into a list of output tensors.
-          the current node will be added to
-          the inboundNodes of outboundLayer.
-        */
-          this.outboundLayer = args.outboundLayer;
-          /*
-            The following 3 properties describe where
-            the input tensors come from: which layers,
-            and for each layer, which node and which
-            tensor output of each node.
-        */
-          // List of layer instances.
-          this.inboundLayers = args.inboundLayers;
-          // List of integers, 1:1 mapping with inboundLayers.
-          this.nodeIndices = args.nodeIndices;
-          // List of integers, 1:1 mapping with inboundLayers.
-          this.tensorIndices = args.tensorIndices;
-          /*
-            Following 2 properties:
-            tensor inputs and outputs of outboundLayer.
-        */
-          // List of tensors. 1:1 mapping with inboundLayers.
-          this.inputTensors = args.inputTensors;
-          // List of tensors, created by outboundLayer.call().
-          this.outputTensors = args.outputTensors;
-          /*
-            Following 2 properties: input and output masks.
-            List of tensors, 1:1 mapping with inputTensor.
-        */
-          this.inputMasks = args.inputMasks;
-          // List of tensors, created by outboundLayer.computeMask().
-          this.outputMasks = args.outputMasks;
-          // Following 2 properties: input and output shapes.
-          // List of shape tuples, shapes of inputTensors.
-          this.inputShapes = args.inputShapes;
-          // List of shape tuples, shapes of outputTensors.
-          this.outputShapes = args.outputShapes;
-          // Add nodes to all layers involved.
-          for (const layer of args.inboundLayers) {
-            if (layer != null) {
-              layer.outboundNodes.push(this);
-            }
-          }
-          args.outboundLayer.inboundNodes.push(this);
-        }
-        getConfig() {
-          const inboundNames = [];
-          for (const layer of this.inboundLayers) {
-            if (layer != null) {
-              inboundNames.push(layer.name);
-            } else {
-              inboundNames.push(null);
-            }
-          }
-          return {
-            outboundLayer: this.outboundLayer ? this.outboundLayer.name : null,
-            inboundLayers: inboundNames,
-            nodeIndices: this.nodeIndices,
-            tensorIndices: this.tensorIndices,
-          };
-        }
-      }
-      let _nextLayerID = 0;
-      /**
-       * A layer is a grouping of operations and weights that can be composed to
-       * create a `tf.LayersModel`.
-       *
-       * Layers are constructed by using the functions under the
-       * [tf.layers](#Layers-Basic) namespace.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Classes', namespace: 'layers'} */
-      class topology_Layer extends dist["serialization"].Serializable {
-        constructor(args = {}) {
-          super();
-          this._callHook = null;
-          this._addedWeightNames = [];
-          // Porting Notes: PyKeras does not have this property in this base Layer
-          //   class. Instead lets Layer subclass set it dynamically and checks the
-          //   value with `hasattr`. In tfjs-layers, we let this be a member of this
-          //   base class.
-          this._stateful = false;
-          this.id = _nextLayerID++;
-          this.activityRegularizer = null;
-          this.inputSpec = null;
-          this.supportsMasking = false;
-          // These properties will be set upon call of this.build()
-          this._trainableWeights = [];
-          this._nonTrainableWeights = [];
-          this._losses = [];
-          this._updates = [];
-          this._built = false;
-          /*
-          These lists will be filled via successive calls
-          to this.addInboundNode().
-         */
-          this.inboundNodes = [];
-          this.outboundNodes = [];
-          let name = args.name;
-          if (!name) {
-            const prefix = this.getClassName();
-            name = toSnakeCase(prefix) + "_" + getUid(prefix);
-          }
-          this.name = name;
-          this.trainable_ = args.trainable == null ? true : args.trainable;
-          if (args.inputShape != null || args.batchInputShape != null) {
-            /*
-              In this case we will later create an input layer
-              to insert before the current layer
-             */
-            let batchInputShape;
-            if (args.batchInputShape != null) {
-              batchInputShape = args.batchInputShape;
-            } else if (args.inputShape != null) {
-              let batchSize = null;
-              if (args.batchSize != null) {
-                batchSize = args.batchSize;
-              }
-              batchInputShape = [batchSize].concat(args.inputShape);
-            }
-            this.batchInputShape = batchInputShape;
-            // Set dtype.
-            let dtype = args.dtype;
-            if (dtype == null) {
-              dtype = args.inputDType;
-            }
-            if (dtype == null) {
-              dtype = "float32";
-            }
-            this.dtype = dtype;
-          }
-          if (args.weights != null) {
-            this.initialWeights = args.weights;
-          } else {
-            this.initialWeights = null;
-          }
-          // The value of `_refCount` is initialized to null. When the layer is used
-          // in a symbolic way for the first time, it will be set to 1.
-          this._refCount = null;
-          this.fastWeightInitDuringBuild = false;
-        }
-        /**
-         * Converts a layer and its index to a unique (immutable type) name.
-         * This function is used internally with `this.containerNodes`.
-         * @param layer The layer.
-         * @param nodeIndex The layer's position (e.g. via enumerate) in a list of
-         *   nodes.
-         *
-         * @returns The unique name.
-         */
-        static nodeKey(layer, nodeIndex) {
-          return layer.name + "_ib-" + nodeIndex.toString();
-        }
-        /**
-         * Returns this.inboundNode at index nodeIndex.
-         *
-         * Porting note: This is a replacement for _get_node_attribute_at_index()
-         * @param nodeIndex
-         * @param attrName The name of the attribute related to request for this node.
-         */
-        getNodeAtIndex(nodeIndex, attrName) {
-          if (this.inboundNodes.length === 0) {
-            throw new RuntimeError(
-              "The layer has never been called " + `and thus has no defined ${attrName}.`
-            );
-          }
-          if (this.inboundNodes.length <= nodeIndex) {
-            throw new ValueError(
-              `Asked to get ${attrName} at node ${nodeIndex}, ` +
-                `but the layer has only ${this.inboundNodes.length} inbound nodes.`
-            );
-          }
-          return this.inboundNodes[nodeIndex];
-        }
-        /**
-         * Retrieves the input tensor(s) of a layer at a given node.
-         *
-         * @param nodeIndex Integer, index of the node from which to retrieve the
-         *   attribute. E.g. `nodeIndex=0` will correspond to the first time the layer
-         *   was called.
-         *
-         * @return A tensor (or list of tensors if the layer has multiple inputs).
-         */
-        getInputAt(nodeIndex) {
-          return singletonOrArray(this.getNodeAtIndex(nodeIndex, "input").inputTensors);
-        }
-        /**
-         * Retrieves the output tensor(s) of a layer at a given node.
-         *
-         * @param nodeIndex Integer, index of the node from which to retrieve the
-         *   attribute. E.g. `nodeIndex=0` will correspond to the first time the layer
-         *   was called.
-         *
-         * @return A tensor (or list of tensors if the layer has multiple outputs).
-         */
-        getOutputAt(nodeIndex) {
-          return singletonOrArray(this.getNodeAtIndex(nodeIndex, "output").outputTensors);
-        }
-        // Properties
-        /**
-         * Retrieves the input tensor(s) of a layer.
-         *
-         * Only applicable if the layer has exactly one inbound node,
-         * i.e. if it is connected to one incoming layer.
-         *
-         * @return Input tensor or list of input tensors.
-         *
-         * @exception AttributeError if the layer is connected to more than one
-         *   incoming layers.
-         */
-        get input() {
-          if (this.inboundNodes.length > 1) {
-            throw new AttributeError(
-              `Layer ${this.name}` +
-                " has multiple inbound nodes, " +
-                'hence the notion of "layer input" ' +
-                "is ill-defined. " +
-                "Use `getInputAt(nodeIndex)` instead."
-            );
-          } else if (this.inboundNodes.length === 0) {
-            throw new AttributeError(
-              `Layer ${this.name}` + " is not connected, no input to return."
-            );
-          }
-          return singletonOrArray(this.getNodeAtIndex(0, "input").inputTensors);
-        }
-        /**
-         * Retrieves the output tensor(s) of a layer.
-         *
-         * Only applicable if the layer has exactly one inbound node,
-         * i.e. if it is connected to one incoming layer.
-         *
-         * @return Output tensor or list of output tensors.
-         *
-         * @exception AttributeError if the layer is connected to more than one
-         *   incoming layers.
-         */
-        get output() {
-          if (this.inboundNodes.length === 0) {
-            throw new AttributeError(`Layer ${this.name}` + " has no inbound nodes.");
-          }
-          if (this.inboundNodes.length > 1) {
-            throw new AttributeError(
-              `Layer ${this.name}` +
-                " has multiple inbound nodes, " +
-                'hence the notion of "layer output" ' +
-                "is ill-defined. " +
-                "Use `getOutputAt(nodeIndex)` instead."
-            );
-          }
-          return singletonOrArray(this.getNodeAtIndex(0, "output").outputTensors);
-        }
-        get losses() {
-          return this._losses;
-        }
-        /**
-         * Retrieves the Layer's current loss values.
-         *
-         * Used for regularizers during training.
-         */
-        calculateLosses() {
-          // Porting Node: This is an augmentation to Layer.loss in PyKeras.
-          //   In PyKeras, Layer.loss returns symbolic tensors. Here a concrete
-          //   Tensor (specifically Scalar) values are returned. This is due to the
-          //   imperative backend.
-          return this.losses.map((lossFn) => lossFn());
-        }
-        get updates() {
-          return this._updates;
-        }
-        get built() {
-          return this._built;
-        }
-        set built(built) {
-          this._built = built;
-        }
-        get trainable() {
-          return this.trainable_;
-        }
-        set trainable(trainable) {
-          this._trainableWeights.forEach((w) => (w.trainable = trainable));
-          this.trainable_ = trainable;
-        }
-        get trainableWeights() {
-          if (this.trainable_) {
-            return this._trainableWeights.filter((w) => w.trainable);
-          } else {
-            return [];
-          }
-        }
-        set trainableWeights(weights) {
-          this._trainableWeights = weights;
-        }
-        get nonTrainableWeights() {
-          if (this.trainable) {
-            return this._trainableWeights
-              .filter((w) => !w.trainable)
-              .concat(this._nonTrainableWeights);
-          } else {
-            return this._trainableWeights.concat(this._nonTrainableWeights);
-          }
-        }
-        set nonTrainableWeights(weights) {
-          this._nonTrainableWeights = weights;
-        }
-        /**
-         * The concatenation of the lists trainableWeights and nonTrainableWeights
-         * (in this order).
-         */
-        get weights() {
-          return this.trainableWeights.concat(this.nonTrainableWeights);
-        }
-        get stateful() {
-          return this._stateful;
-        }
-        /**
-         * Reset the states of the layer.
-         *
-         * This method of the base Layer class is essentially a no-op.
-         * Subclasses that are stateful (e.g., stateful RNNs) should override this
-         * method.
-         */
-        resetStates() {
-          if (!this.stateful) {
-            throw new Error(
-              "Cannot call the resetStates() method of a non-stateful Layer " + "object."
-            );
-          }
-        }
-        /**
-         * Checks compatibility between the layer and provided inputs.
-         *
-         * This checks that the tensor(s) `input`
-         * verify the input assumptions of the layer
-         * (if any). If not, exceptions are raised.
-         *
-         * @param inputs Input tensor or list of input tensors.
-         *
-         * @exception ValueError in case of mismatch between
-         *   the provided inputs and the expectations of the layer.
-         */
-        assertInputCompatibility(inputs) {
-          inputs = toList(inputs);
-          if (this.inputSpec == null || this.inputSpec.length === 0) {
-            return;
-          }
-          const inputSpec = toList(this.inputSpec);
-          if (inputs.length !== inputSpec.length) {
-            throw new ValueError(
-              `Layer ${this.name} expects ${inputSpec.length} inputs, ` +
-                `but it received ${inputs.length} input tensors. ` +
-                `Input received: ${inputs}`
-            );
-          }
-          for (let inputIndex = 0; inputIndex < inputs.length; inputIndex++) {
-            const x = inputs[inputIndex];
-            const spec = inputSpec[inputIndex];
-            if (spec == null) {
-              continue;
-            }
-            // Check ndim.
-            const ndim = x.rank;
-            if (spec.ndim != null) {
-              if (ndim !== spec.ndim) {
-                throw new ValueError(
-                  `Input ${inputIndex} is incompatible with layer ${this.name}: ` +
-                    `expected ndim=${spec.ndim}, found ndim=${ndim}`
-                );
-              }
-            }
-            if (spec.maxNDim != null) {
-              if (ndim > spec.maxNDim) {
-                throw new ValueError(
-                  `Input ${inputIndex} is incompatible with layer ${this.name}` +
-                    `: expected max_ndim=${spec.maxNDim}, found ndim=${ndim}`
-                );
-              }
-            }
-            if (spec.minNDim != null) {
-              if (ndim < spec.minNDim) {
-                throw new ValueError(
-                  `Input ${inputIndex} is incompatible with layer ${this.name}` +
-                    `: expected min_ndim=${spec.minNDim}, found ndim=${ndim}.`
-                );
-              }
-            }
-            // Check dtype.
-            if (spec.dtype != null) {
-              if (x.dtype !== spec.dtype) {
-                throw new ValueError(
-                  `Input ${inputIndex} is incompatible with layer ${this.name} ` +
-                    `: expected dtype=${spec.dtype}, found dtype=${x.dtype}.`
-                );
-              }
-            }
-            // Check specific shape axes.
-            if (spec.axes) {
-              const xShape = x.shape;
-              for (const key in spec.axes) {
-                const axis = Number(key);
-                const value = spec.axes[key];
-                // Perform Python-style slicing in case axis < 0;
-                // TODO(cais): Use https://github.com/alvivi/typescript-underscore to
-                // ensure type safety through Underscore calls.
-                const xShapeAtAxis = axis >= 0 ? xShape[axis] : xShape[xShape.length + axis];
-                if (value != null && [value, null].indexOf(xShapeAtAxis) === -1) {
-                  throw new ValueError(
-                    `Input ${inputIndex} is incompatible with layer ` +
-                      `${this.name}: expected axis ${axis} of input shape to ` +
-                      `have value ${value} but got shape ${xShape}.`
-                  );
-                }
-              }
-            }
-            // Check shape.
-            if (spec.shape != null) {
-              for (let i = 0; i < spec.shape.length; ++i) {
-                const specDim = spec.shape[i];
-                const dim = x.shape[i];
-                if (specDim != null && dim != null) {
-                  if (specDim !== dim) {
-                    throw new ValueError(
-                      `Input ${inputIndex} is incompatible with layer ` +
-                        `${this.name}: expected shape=${spec.shape}, ` +
-                        `found shape=${x.shape}.`
-                    );
-                  }
-                }
-              }
-            }
-          }
-        }
-        /**
-         * This is where the layer's logic lives.
-         *
-         * @param inputs Input tensor, or list/tuple of input tensors.
-         * @param kwargs Additional keyword arguments.
-         *
-         * @return A tensor or list/tuple of tensors.
-         */
-        call(inputs, kwargs) {
-          return inputs;
-        }
-        invokeCallHook(inputs, kwargs) {
-          if (this._callHook != null) {
-            this._callHook(inputs, kwargs);
-          }
-        }
-        /**
-         * Set call hook.
-         * This is currently used for testing only.
-         * @param callHook
-         */
-        setCallHook(callHook) {
-          this._callHook = callHook;
-        }
-        /**
-         * Clear call hook.
-         * This is currently used for testing only.
-         */
-        clearCallHook() {
-          this._callHook = null;
-        }
-        /**
-         * Builds or executes a `Layer's logic.
-         *
-         * When called with `tf.Tensor`(s), execute the `Layer`s computation and
-         * return Tensor(s). For example:
-         *
-         * ```js
-         * const denseLayer = tf.layers.dense({
-         *   units: 1,
-         *   kernelInitializer: 'zeros',
-         *   useBias: false
-         * });
-         *
-         * // Invoke the layer's apply() method with a `tf.Tensor` (with concrete
-         * // numeric values).
-         * const input = tf.ones([2, 2]);
-         * const output = denseLayer.apply(input);
-         *
-         * // The output's value is expected to be [[0], [0]], due to the fact that
-         * // the dense layer has a kernel initialized to all-zeros and does not have
-         * // a bias.
-         * output.print();
-         * ```
-         *
-         * When called with `tf.SymbolicTensor`(s), this will prepare the layer for
-         * future execution.  This entails internal book-keeping on shapes of
-         * expected Tensors, wiring layers together, and initializing weights.
-         *
-         * Calling `apply` with `tf.SymbolicTensor`s are typically used during the
-         * building of non-`tf.Sequential` models. For example:
-         *
-         * ```js
-         * const flattenLayer = tf.layers.flatten();
-         * const denseLayer = tf.layers.dense({units: 1});
-         *
-         * // Use tf.layers.input() to obtain a SymbolicTensor as input to apply().
-         * const input = tf.input({shape: [2, 2]});
-         * const output1 = flattenLayer.apply(input);
-         *
-         * // output1.shape is [null, 4]. The first dimension is the undetermined
-         * // batch size. The second dimension comes from flattening the [2, 2]
-         * // shape.
-         * console.log(JSON.stringify(output1.shape));
-         *
-         * // The output SymbolicTensor of the flatten layer can be used to call
-         * // the apply() of the dense layer:
-         * const output2 = denseLayer.apply(output1);
-         *
-         * // output2.shape is [null, 1]. The first dimension is the undetermined
-         * // batch size. The second dimension matches the number of units of the
-         * // dense layer.
-         * console.log(JSON.stringify(output2.shape));
-         *
-         * // The input and output and be used to construct a model that consists
-         * // of the flatten and dense layers.
-         * const model = tf.model({inputs: input, outputs: output2});
-         * ```
-         *
-         * @param inputs a `tf.Tensor` or `tf.SymbolicTensor` or an Array of them.
-         * @param kwargs Additional keyword arguments to be passed to `call()`.
-         *
-         * @return Output of the layer's `call` method.
-         *
-         * @exception ValueError error in case the layer is missing shape information
-         *   for its `build` call.
-         */
-        // Porting Note: This is a replacement for __call__() in Python.
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        apply(inputs, kwargs) {
-          kwargs = kwargs || {};
-          this.assertNotDisposed();
-          // Ensure inputs are all the same type.
-          const inputsList = toList(inputs);
-          let allAreSymbolic = true;
-          for (const input of inputsList) {
-            if (!(input instanceof topology_SymbolicTensor)) {
-              allAreSymbolic = false;
-              break;
-            }
-          }
-          let noneAreSymbolic = true;
-          for (const input of inputsList) {
-            if (input instanceof topology_SymbolicTensor) {
-              noneAreSymbolic = false;
-              break;
-            }
-          }
-          if (allAreSymbolic === noneAreSymbolic) {
-            throw new ValueError(
-              "Arguments to apply() must be all " + "SymbolicTensors or all Tensors"
-            );
-          }
-          // TODO(michaelterry): nameScope() may not be necessary.
-          return nameScope(this.name, () => {
-            // Handle laying building (weight creating, input spec locking).
-            if (!this.built) {
-              /*
-                  Throw exceptions in case the input is not compatible
-                  with the inputSpec specified in the layer constructor.
-                 */
-              this.assertInputCompatibility(inputs);
-              // Collect input shapes to build layer.
-              const inputShapes = [];
-              for (const xElem of toList(inputs)) {
-                inputShapes.push(xElem.shape);
-              }
-              this.build(singletonOrArray(inputShapes));
-              this.built = true;
-              // Load weights that were specified at layer instantiation.
-              if (this.initialWeights) {
-                this.setWeights(this.initialWeights);
-              }
-              if (this._refCount === null && noneAreSymbolic) {
-                // The first use of this layer is a non-symbolic call, set ref count
-                // to 1 so the Layer can be properly disposed if its dispose() method
-                // is called.
-                this._refCount = 1;
-              }
-            }
-            /*
-              Throw exceptions in case the input is not compatible
-              with the inputSpec set at build time.
-            */
-            this.assertInputCompatibility(inputs);
-            // Handle mask propagation.
-            // TODO(michaelterry): Mask propagation not currently implemented.
-            // Actually call the layer, collecting output(s), mask(s), and shape(s).
-            if (noneAreSymbolic) {
-              let output = this.call(inputs, kwargs);
-              // TODO(michaelterry): Compute the outputMask
-              // If the layer returns tensors from its inputs, unmodified,
-              // we copy them to avoid loss of tensor metadata.
-              const outputList = toList(output);
-              const outputListCopy = [];
-              // TODO(michaelterry): This copying may not be necessary given our eager
-              // backend.
-              for (let x of outputList) {
-                if (inputsList.indexOf(x) !== -1) {
-                  x = x.clone();
-                }
-                outputListCopy.push(x);
-              }
-              output = singletonOrArray(outputListCopy);
-              if (this.activityRegularizer != null) {
-                throw new NotImplementedError(
-                  "Layer invocation in the presence of activity " +
-                    "regularizer(s) is not supported yet."
-                );
-              }
-              // TODO(michaelterry): Call addInboundNode()?
-              return output;
-            } else {
-              const inputShape = collectInputShape(inputs);
-              const outputShape = this.computeOutputShape(inputShape);
-              let output;
-              const outputDType = guessOutputDType(inputs);
-              this.warnOnIncompatibleInputShape(Array.isArray(inputs) ? inputShape[0] : inputShape);
-              if (outputShape != null && outputShape.length > 0 && Array.isArray(outputShape[0])) {
-                // We have multiple output shapes. Create multiple output tensors.
-                output = outputShape.map(
-                  (shape, index) =>
-                    new topology_SymbolicTensor(
-                      outputDType,
-                      shape,
-                      this,
-                      toList(inputs),
-                      kwargs,
-                      this.name,
-                      index
-                    )
-                );
-              } else {
-                output = new topology_SymbolicTensor(
-                  outputDType,
-                  outputShape,
-                  this,
-                  toList(inputs),
-                  kwargs,
-                  this.name
-                );
-              }
-              /*
-                  Add an inbound node to the layer, so that it keeps track
-                  of the call and of all new variables created during the call.
-                  This also updates the layer history of the output tensor(s).
-                  If the input tensor(s) had no previous history,
-                  this does nothing.
-                */
-              this.addInboundNode(inputs, output, null, null, inputShape, outputShape, kwargs);
-              this._refCount++;
-              if (this.activityRegularizer != null) {
-                throw new NotImplementedError(
-                  "Layer invocation in the presence of activity " +
-                    "regularizer(s) is not supported yet."
-                );
-              }
-              return output;
-            }
-          });
-        }
-        /**
-         * Check compatibility between input shape and this layer's batchInputShape.
-         *
-         * Print warning if any incompatibility is found.
-         *
-         * @param inputShape Input shape to be checked.
-         */
-        warnOnIncompatibleInputShape(inputShape) {
-          if (this.batchInputShape == null) {
-            return;
-          } else if (inputShape.length !== this.batchInputShape.length) {
-            console.warn(
-              `The rank of the input tensor provided (shape: ` +
-                `${JSON.stringify(inputShape)}) does not match that of the ` +
-                `batchInputShape (${JSON.stringify(this.batchInputShape)}) ` +
-                `of the layer ${this.name}`
-            );
-          } else {
-            let dimMismatch = false;
-            this.batchInputShape.forEach((dimension, i) => {
-              if (dimension != null && inputShape[i] != null && inputShape[i] !== dimension) {
-                dimMismatch = true;
-              }
-            });
-            if (dimMismatch) {
-              console.warn(
-                `The shape of the input tensor ` +
-                  `(${JSON.stringify(inputShape)}) does not ` +
-                  `match the expectation of layer ${this.name}: ` +
-                  `${JSON.stringify(this.batchInputShape)}`
-              );
-            }
-          }
-        }
-        /**
-         * Retrieves the output shape(s) of a layer.
-         *
-         * Only applicable if the layer has only one inbound node, or if all inbound
-         * nodes have the same output shape.
-         *
-         * @returns Output shape or shapes.
-         * @throws AttributeError: if the layer is connected to more than one incoming
-         *   nodes.
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        get outputShape() {
-          if (this.inboundNodes == null || this.inboundNodes.length === 0) {
-            throw new AttributeError(
-              `The layer ${this.name} has never been called and thus has no ` +
-                `defined output shape.`
-            );
-          }
-          const allOutputShapes = [];
-          for (const node of this.inboundNodes) {
-            const shapeString = JSON.stringify(node.outputShapes);
-            if (allOutputShapes.indexOf(shapeString) === -1) {
-              allOutputShapes.push(shapeString);
-            }
-          }
-          if (allOutputShapes.length === 1) {
-            const outputShapes = this.inboundNodes[0].outputShapes;
-            if (
-              Array.isArray(outputShapes) &&
-              Array.isArray(outputShapes[0]) &&
-              outputShapes.length === 1
-            ) {
-              return outputShapes[0];
-            } else {
-              return outputShapes;
-            }
-          } else {
-            throw new AttributeError(
-              `The layer ${this.name} has multiple inbound nodes with different ` +
-                `output shapes. Hence the notion of "outut shape" is ill-defined ` +
-                `for the layer.`
-            );
-            // TODO(cais): Implement getOutputShapeAt().
-          }
-        }
-        /**
-         * Counts the total number of numbers (e.g., float32, int32) in the
-         * weights.
-         *
-         * @returns An integer count.
-         * @throws RuntimeError: If the layer is not built yet (in which case its
-         *   weights are not defined yet.)
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        countParams() {
-          if (!this.built) {
-            throw new RuntimeError(
-              `You tried to call countParams() on ${this.name}, ` +
-                `but the layer is not built yet. Build it first by calling ` +
-                `build(batchInputShape).`
-            );
-          }
-          return countParamsInWeights(this.weights);
-        }
-        /**
-         * Creates the layer weights.
-         *
-         * Must be implemented on all layers that have weights.
-         *
-         * Called when apply() is called to construct the weights.
-         *
-         * @param inputShape A `Shape` or array of `Shape` (unused).
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        build(inputShape) {
-          this.built = true;
-        }
-        /**
-         * Returns the current values of the weights of the layer.
-         *
-         * @param trainableOnly Whether to get the values of only trainable weights.
-         * @returns Weight values as an `Array` of `tf.Tensor`s.
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        getWeights(trainableOnly = false) {
-          return batchGetValue(trainableOnly ? this.trainableWeights : this.weights);
-        }
-        /**
-         * Sets the weights of the layer, from Tensors.
-         *
-         * @param weights a list of Tensors. The number of arrays and their shape
-         *   must match number of the dimensions of the weights of the layer (i.e.
-         *   it should match the output of `getWeights`).
-         *
-         * @exception ValueError If the provided weights list does not match the
-         *   layer's specifications.
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        setWeights(weights) {
-          Object(dist["tidy"])(() => {
-            const params = this.weights;
-            if (params.length !== weights.length) {
-              // TODO(cais): Restore the following and use `providedWeights`, instead
-              // of `weights` in the error message, once the deeplearn.js bug is
-              // fixed: https://github.com/PAIR-code/deeplearnjs/issues/498 const
-              // providedWeights = JSON.stringify(weights).substr(0, 50);
-              throw new ValueError(
-                `You called setWeights(weights) on layer "${this.name}" ` +
-                  `with a weight list of length ${weights.length}, ` +
-                  `but the layer was expecting ${params.length} weights. ` +
-                  `Provided weights: ${weights}...`
-              );
-            }
-            if (params.length === 0) {
-              return;
-            }
-            const weightValueTuples = [];
-            const paramValues = batchGetValue(params);
-            for (let i = 0; i < paramValues.length; ++i) {
-              const pv = paramValues[i];
-              const p = params[i];
-              const w = weights[i];
-              if (!dist["util"].arraysEqual(pv.shape, w.shape)) {
-                throw new ValueError(
-                  `Layer weight shape ${pv.shape} ` +
-                    `not compatible with provided weight shape ${w.shape}`
-                );
-              }
-              weightValueTuples.push([p, w]);
-            }
-            batchSetValue(weightValueTuples);
-          });
-        }
-        /**
-         * Adds a weight variable to the layer.
-         *
-         * @param name Name of the new weight variable.
-         * @param shape The shape of the weight.
-         * @param dtype The dtype of the weight.
-         * @param initializer An initializer instance.
-         * @param regularizer A regularizer instance.
-         * @param trainable Whether the weight should be trained via backprop or not
-         *   (assuming that the layer itself is also trainable).
-         * @param constraint An optional trainable.
-         * @return The created weight variable.
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        addWeight(name, shape, dtype, initializer, regularizer, trainable, constraint) {
-          // Reject duplicate weight names.
-          if (this._addedWeightNames.indexOf(name) !== -1) {
-            throw new ValueError(`Duplicate weight name ${name} for layer ${this.name}`);
-          }
-          this._addedWeightNames.push(name);
-          if (dtype == null) {
-            dtype = "float32";
-          }
-          if (this.fastWeightInitDuringBuild) {
-            initializer = getInitializer("zeros");
-          }
-          const initValue = initializer.apply(shape, dtype);
-          const weight = new variables_LayerVariable(initValue, dtype, name, trainable, constraint);
-          initValue.dispose();
-          // Request backend not to dispose the weights of the model on scope() exit.
-          if (regularizer != null) {
-            this.addLoss(() => regularizer.apply(weight.read()));
-          }
-          if (trainable == null) {
-            trainable = true;
-          }
-          if (trainable) {
-            this._trainableWeights.push(weight);
-          } else {
-            this._nonTrainableWeights.push(weight);
-          }
-          return weight;
-        }
-        /**
-         * Set the fast-weight-initialization flag.
-         *
-         * In cases where the initialized weight values will be immediately
-         * overwritten by loaded weight values during model loading, setting
-         * the flag to `true` saves unnecessary calls to potentially expensive
-         * initializers and speeds up the loading process.
-         *
-         * @param value Target value of the flag.
-         */
-        setFastWeightInitDuringBuild(value) {
-          this.fastWeightInitDuringBuild = value;
-        }
-        /**
-         * Add losses to the layer.
-         *
-         * The loss may potentionally be conditional on some inputs tensors,
-         * for instance activity losses are conditional on the layer's inputs.
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        addLoss(losses) {
-          if (losses == null || (Array.isArray(losses) && losses.length === 0)) {
-            return;
-          }
-          // Update this.losses
-          losses = toList(losses);
-          if (this._losses !== undefined && this._losses !== null) {
-            this.losses.push(...losses);
-          }
-        }
-        /**
-         * Computes the output shape of the layer.
-         *
-         * Assumes that the layer will be built to match that input shape provided.
-         *
-         * @param inputShape A shape (tuple of integers) or a list of shape tuples
-         *   (one per output tensor of the layer). Shape tuples can include null for
-         *   free dimensions, instead of an integer.
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        /**
-         * Computes an output mask tensor.
-         *
-         * @param inputs Tensor or list of tensors.
-         * @param mask Tensor or list of tensors.
-         *
-         * @return null or a tensor (or list of tensors, one per output tensor of the
-         * layer).
-         */
-        computeMask(inputs, mask) {
-          if (!this.supportsMasking) {
-            if (mask != null) {
-              if (Array.isArray(mask)) {
-                mask.forEach((maskElement) => {
-                  if (maskElement != null) {
-                    throw new TypeError(
-                      `Layer ${this.name} does not support masking, ` +
-                        "but was passed an inputMask."
-                    );
-                  }
-                });
-              } else {
-                throw new TypeError(
-                  `Layer ${this.name} does not support masking, ` + "but was passed an inputMask."
-                );
-              }
-            }
-            // masking not explicitly supported: return null as mask
-            return null;
-          }
-          // if masking is explictly supported, by default
-          // carry over the input mask
-          return mask;
-        }
-        /**
-         * Internal method to create an inbound node for the layer.
-         *
-         * @param inputTensors List of input tensors.
-         * @param outputTensors List of output tensors.
-         * @param inputMasks List of input masks (a mask can be a tensor, or null).
-         * @param outputMasks List of output masks (a mask can be a tensor, or null).
-         * @param inputShapes List of input shape tuples.
-         * @param outputShapes List of output shape tuples.
-         * @param kwargs Dictionary of keyword arguments that were passed to the
-         *   `call` method of the layer at the call that created the node.
-         */
-        addInboundNode(
-          inputTensors,
-          outputTensors,
-          inputMasks,
-          outputMasks,
-          inputShapes,
-          outputShapes,
-          kwargs = null
-        ) {
-          const inputTensorList = toList(inputTensors);
-          outputTensors = toList(outputTensors);
-          inputMasks = toList(inputMasks);
-          outputMasks = toList(outputMasks);
-          inputShapes = normalizeShapeList(inputShapes);
-          outputShapes = normalizeShapeList(outputShapes);
-          // Collect input tensor(s) coordinates.
-          const inboundLayers = [];
-          const nodeIndices = [];
-          const tensorIndices = [];
-          for (const x of inputTensorList) {
-            /*
-             * TODO(michaelterry): Keras adds this value to tensors; it's not
-             * clear whether we'll use this or not.
-             */
-            inboundLayers.push(x.sourceLayer);
-            nodeIndices.push(x.nodeIndex);
-            tensorIndices.push(x.tensorIndex);
-          }
-          // Create node, add it to inbound nodes.
-          // (This call has side effects.)
-          // tslint:disable-next-line:no-unused-expression
-          new Node(
-            {
-              outboundLayer: this,
-              inboundLayers,
-              nodeIndices,
-              tensorIndices,
-              inputTensors: inputTensorList,
-              outputTensors,
-              inputMasks,
-              outputMasks,
-              inputShapes,
-              outputShapes,
-            },
-            kwargs
-          );
-          // Update tensor history
-          for (let i = 0; i < outputTensors.length; i++) {
-            // TODO(michaelterry: _uses_learning_phase not tracked.
-            outputTensors[i].sourceLayer = this;
-            outputTensors[i].nodeIndex = this.inboundNodes.length - 1;
-            outputTensors[i].tensorIndex = i;
-          }
-        }
-        /**
-         * Returns the config of the layer.
-         *
-         * A layer config is a TS dictionary (serializable)
-         * containing the configuration of a layer.
-         * The same layer can be reinstantiated later
-         * (without its trained weights) from this configuration.
-         *
-         * The config of a layer does not include connectivity
-         * information, nor the layer class name.  These are handled
-         * by 'Container' (one layer of abstraction above).
-         *
-         * Porting Note: The TS dictionary follows TS naming standrds for
-         * keys, and uses tfjs-layers type-safe Enums.  Serialization methods
-         * should use a helper function to convert to the pythonic storage
-         * standard. (see serialization_utils.convertTsToPythonic)
-         *
-         * @returns TS dictionary of configuration.
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        getConfig() {
-          const config = { name: this.name, trainable: this.trainable };
-          if (this.batchInputShape != null) {
-            config["batchInputShape"] = this.batchInputShape;
-          }
-          if (this.dtype != null) {
-            config["dtype"] = this.dtype;
-          }
-          return config;
-        }
-        /**
-         * Dispose the weight variables that this Layer instance holds.
-         *
-         * @returns {number} Number of disposed variables.
-         */
-        disposeWeights() {
-          this.weights.forEach((weight) => weight.dispose());
-          return this.weights.length;
-        }
-        assertNotDisposed() {
-          if (this._refCount === 0) {
-            throw new Error(`Layer '${this.name}' is already disposed.`);
-          }
-        }
-        /**
-         * Attempt to dispose layer's weights.
-         *
-         * This method decrease the reference count of the Layer object by 1.
-         *
-         * A Layer is reference-counted. Its reference count is incremented by 1
-         * the first item its `apply()` method is called and when it becomes a part
-         * of a new `Node` (through calling the `apply()`) method on a
-         * `tf.SymbolicTensor`).
-         *
-         * If the reference count of a Layer becomes 0, all the weights will be
-         * disposed and the underlying memory (e.g., the textures allocated in WebGL)
-         * will be freed.
-         *
-         * Note: If the reference count is greater than 0 after the decrement, the
-         * weights of the Layer will *not* be disposed.
-         *
-         * After a Layer is disposed, it cannot be used in calls such as `apply()`,
-         * `getWeights()` or `setWeights()` anymore.
-         *
-         * @returns A DisposeResult Object with the following fields:
-         *   - refCountAfterDispose: The reference count of the Container after this
-         *     `dispose()` call.
-         *   - numDisposedVariables: Number of `tf.Variable`s (i.e., weights) disposed
-         *     during this `dispose()` call.
-         * @throws {Error} If the layer is not built yet, or if the layer has already
-         *   been disposed.
-         */
-        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
-        dispose() {
-          if (!this.built) {
-            throw new Error(
-              `Cannot dispose Layer ${this.name} because it has not been ` + `built yet.`
-            );
-          }
-          if (this._refCount === null) {
-            throw new Error(
-              `Cannot dispose Layer ${this.name} because it has not been used ` + `yet.`
-            );
-          }
-          this.assertNotDisposed();
-          let numDisposedVariables = 0;
-          if (--this._refCount === 0) {
-            numDisposedVariables = this.disposeWeights();
-          }
-          return { refCountAfterDispose: this._refCount, numDisposedVariables };
-        }
-      }
-      /**
-       * Collects the input shape(s) of a list of `tf.Tensor`s or
-       * `tf.SymbolicTensor`s.
-       *
-       * TODO(michaelterry): Update PyKeras docs (backport).
-       *
-       * @param inputTensors List of input tensors (or single input tensor).
-       *
-       * @return List of shape tuples (or single tuple), one tuple per input.
-       */
-      function collectInputShape(inputTensors) {
-        inputTensors = toList(inputTensors);
-        const shapes = [];
-        for (const x of inputTensors) {
-          shapes.push(x.shape);
-        }
-        return singletonOrArray(shapes);
-      }
-      /**
-       * Guesses output dtype based on inputs.
-       *
-       * At present, just returns 'float32' for any input.
-       *
-       * @param inputTensors List of input tensors (or single input tensor).
-       *
-       * @return The guessed DType. At present, always returns 'float32'.
-       */
-      function guessOutputDType(inputTensors) {
-        return "float32";
-      }
-      /**
-       * Returns the list of input tensors necessary to compute `tensor`.
-       *
-       * Output will always be a list of tensors (potentially with 1 element).
-       *
-       * @param tensor The tensor to start from.
-       * @param layer Origin layer of the tensor.
-       * @param nodeIndex Origin node index of the tensor.
-       *
-       * @return Array of input tensors.
-       */
-      function getSourceInputs(tensor, layer, nodeIndex) {
-        if (layer == null || (nodeIndex != null && nodeIndex > 0)) {
-          layer = tensor.sourceLayer;
-          nodeIndex = tensor.nodeIndex;
-        }
-        if (layer.inboundNodes.length === 0) {
-          return [tensor];
-        } else {
-          const node = layer.inboundNodes[nodeIndex];
-          if (node.inboundLayers.length === 0) {
-            return node.inputTensors;
-          } else {
-            const sourceTensors = [];
-            for (let i = 0; i < node.inboundLayers.length; i++) {
-              const x = node.inputTensors[i];
-              const layer = node.inboundLayers[i];
-              const nodeIndex = node.nodeIndices[i];
-              const previousSources = getSourceInputs(x, layer, nodeIndex);
-              // Avoid input redundancy.
-              for (const x of previousSources) {
-                if (sourceTensors.indexOf(x) === -1) {
-                  sourceTensors.push(x);
-                }
-              }
-            }
-            return sourceTensors;
-          }
-        }
-      }
-      //# sourceMappingURL=topology.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/input_layer.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      class input_layer_InputLayer extends topology_Layer {
-        constructor(args) {
-          super({
-            dtype: args.dtype,
-            name: args.name != null ? args.name : getUid("input").toString(),
-          });
-          // Normalize config.batchSize and config.sparse
-          if (args.batchSize == null) {
-            args.batchSize = null;
-          }
-          if (args.sparse == null) {
-            args.sparse = false;
-          }
-          this.trainable = false;
-          this.built = true;
-          this.sparse = args.sparse;
-          if (args.inputShape != null && args.batchInputShape != null) {
-            throw new ValueError(
-              "Only provide the inputShape OR " +
-                "batchInputShape argument to inputLayer, not both at the same time."
-            );
-          }
-          let batchInputShape = args.batchInputShape;
-          if (batchInputShape == null) {
-            if (args.inputShape == null) {
-              throw new ValueError(
-                "An InputLayer should be passed either a " + "`batchInputShape` or an `inputShape`."
-              );
-            } else {
-              batchInputShape = [args.batchSize].concat(args.inputShape);
-            }
-          } else {
-            // TODO(michaelterry): Backport to PyKeras
-            if (args.batchSize != null) {
-              throw new ValueError(
-                "Cannot specify batchSize if batchInputShape is " +
-                  "specified when creating an InputLayer."
-              );
-            }
-          }
-          const dtype = args.dtype || "float32";
-          this.batchInputShape = batchInputShape;
-          this.dtype = dtype;
-          // TODO(michaelterry): Backport this to PyKeras?
-          this.inputSpec = [{ shape: batchInputShape }];
-          const inputTensor = new topology_SymbolicTensor(
-            this.dtype,
-            this.batchInputShape,
-            this,
-            [],
-            {},
-            this.name
-          );
-          inputTensor.nodeIndex = 0;
-          inputTensor.tensorIndex = 0;
-          // Create an input node to add to this.outboundNode.
-          // (This call has side effects.)
-          // tslint:disable-next-line:no-unused-expression
-          new Node({
-            outboundLayer: this,
-            inboundLayers: [],
-            nodeIndices: [],
-            tensorIndices: [],
-            inputTensors: [inputTensor],
-            outputTensors: [inputTensor],
-            inputMasks: [null],
-            outputMasks: [null],
-            inputShapes: [batchInputShape],
-            outputShapes: [batchInputShape],
-          });
-        }
-        apply(inputs, kwargs) {
-          throw new ValueError(
-            "Cannot pass any input to an " +
-              `InputLayer's apply() method. InputLayer name: ${this.name}`
-          );
-        }
-        dispose() {
-          // dispose() for InputLayer is overridden as no-op.
-          return { refCountAfterDispose: this._refCount, numDisposedVariables: 0 };
-        }
-        getConfig() {
-          return {
-            batchInputShape: this.batchInputShape,
-            dtype: this.dtype,
-            sparse: this.sparse,
-            name: this.name,
-          };
-        }
-      }
-      /** @nocollapse */
-      input_layer_InputLayer.className = "InputLayer";
-      dist["serialization"].registerClass(input_layer_InputLayer);
-      function Input(config) {
-        if (config.batchShape == null && config.shape == null) {
-          throw new Error(
-            "Please provide to Input either a `shape`" +
-              " or a `batchShape` argument. Note that " +
-              "`shape` does not include the batch " +
-              "dimension."
-          );
-        }
-        if (config.batchShape != null && config.shape != null) {
-          // TODO(michaelterry): Backport to PyKeras.
-          throw new ValueError(
-            "Please provide either a `shape` or `batchShape` " + "argument to Input, but not both."
-          );
-        }
-        let batchShape = config.batchShape;
-        if (config.shape != null && batchShape == null) {
-          batchShape = [null].concat(config.shape);
-        }
-        let dtype = config.dtype;
-        if (dtype == null) {
-          dtype = "float32";
-        }
-        const inputLayer = new input_layer_InputLayer({
-          batchInputShape: batchShape,
-          name: config.name,
-          dtype,
-          sparse: config.sparse,
-        });
-        const outputs = inputLayer.inboundNodes[0].outputTensors;
-        return outputs[0];
-      }
-      //# sourceMappingURL=input_layer.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/logs.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      /**
-       * Turn any Scalar values in a Logs object into actual number values.
-       *
-       * @param logs The `Logs` object to be resolved in place.
-       */
-      async function resolveScalarsInLogs(logs) {
-        if (logs == null) {
-          return;
-        }
-        const promises = [];
-        const keys = [];
-        const scalarsToDispose = [];
-        for (const key in logs) {
-          const value = logs[key];
-          if (typeof value !== "number") {
-            const valueScalar = value;
-            promises.push(valueScalar.data());
-            keys.push(key);
-            scalarsToDispose.push(valueScalar);
-          }
-        }
-        if (promises.length > 0) {
-          const values = await Promise.all(promises);
-          for (let i = 0; i < values.length; ++i) {
-            logs[keys[i]] = values[i][0];
-          }
-          // Dispose the original scalar tensors.
-          Object(dist["dispose"])(scalarsToDispose);
-        }
-      }
-      /**
-       * Dispose all Tensors in an UnresolvedLogs object.
-       *
-       * @param logs An `UnresolvedLogs` object potentially containing `tf.Tensor`s in
-       *   places where the values can be `tf.Tensor` or `number`.
-       */
-      function disposeTensorsInLogs(logs) {
-        if (logs == null) {
-          return;
-        }
-        for (const key in logs) {
-          const value = logs[key];
-          if (typeof value !== "number") {
-            value.dispose();
-          }
-        }
-      }
-      //# sourceMappingURL=logs.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/base_callbacks.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original source: keras/callbacks.py */
-
-      /** Verbosity logging level when fitting a model. */
-      var ModelLoggingVerbosity;
-      (function (ModelLoggingVerbosity) {
-        ModelLoggingVerbosity[(ModelLoggingVerbosity["SILENT"] = 0)] = "SILENT";
-        ModelLoggingVerbosity[(ModelLoggingVerbosity["VERBOSE"] = 1)] = "VERBOSE";
-      })(ModelLoggingVerbosity || (ModelLoggingVerbosity = {}));
-      /** How often to yield to the main thread when training (in ms). */
-      const DEFAULT_YIELD_EVERY_MS = 125;
-      /**
-       * Abstract base class used to build new callbacks.
-       *
-       * The `logs` dictionary that callback methods take as argument will contain
-       * keys for quantities relevant to the current batch or epoch.
-       *
-       * Currently, the `.fit()` method of the `Sequential` model class
-       * will include the following quantities in the `logs` that
-       * it passes to its callbacks:
-       *
-       * onEpochEnd: Logs include `acc` and `loss`, and optionally include `valLoss`
-       *   (if validation is enabled in `fit`), and `valAcc` (if validation and
-       *   accuracy monitoring are enabled).
-       * onBatchBegin: Logs include `size`, the number of samples in the current
-       *   batch.
-       * onBatchEnd: Logs include `loss`, and optionally `acc` (if accuracy monitoring
-       *   is enabled).
-       */
-      class BaseCallback {
-        constructor() {
-          // TODO(michaelterry): This type is a best guess.
-          this.validationData = null;
-        }
-        setParams(params) {
-          this.params = params;
-        }
-        async onEpochBegin(epoch, logs) {}
-        async onEpochEnd(epoch, logs) {}
-        async onBatchBegin(batch, logs) {}
-        async onBatchEnd(batch, logs) {}
-        async onTrainBegin(logs) {}
-        async onTrainEnd(logs) {}
-        // LayersModel needs to call Callback.setModel(), but cannot actually depend
-        // on Callback because that creates a cyclic dependency.  Providing this no-op
-        // method on BaseCallback breaks the cycle: this way LayersModel can depend on
-        // BaseCallback but not on Callback.  The argument is typed as `Container`
-        // (the superclass of LayersModel) to avoid recapitulating the cycle. Callback
-        // overrides this method and enforces that the argument is really a
-        // LayersModel.
-        setModel(model) {
-          // Do nothing. Use Callback instead of BaseCallback to track the model.
-        }
-      }
-      /**
-       * Container abstracting a list of callbacks.
-       */
-      class CallbackList {
-        // TODO(cais): When the need arises, uncomment the following lines and
-        // implement the queue for time values.
-        // private deltaTBatch: number;
-        // private deltaTsBatchBegin: Array<number>;
-        // private deltaTsBatchEnd: Array<number>;
-        /**
-         * Constructor of CallbackList.
-         * @param callbacks Array of `Callback` instances.
-         * @param queueLength Queue length for keeping running statistics over
-         *   callback execution time.
-         */
-        constructor(callbacks, queueLength = 10) {
-          // TODO(cais): Make use of queueLength when implementing the queue for time
-          // values.
-          if (callbacks == null) {
-            callbacks = [];
-          }
-          this.callbacks = callbacks;
-          this.queueLength = queueLength;
-        }
-        append(callback) {
-          this.callbacks.push(callback);
-        }
-        setParams(params) {
-          for (const callback of this.callbacks) {
-            callback.setParams(params);
-          }
-        }
-        setModel(model) {
-          for (const callback of this.callbacks) {
-            callback.setModel(model);
-          }
-        }
-        /**
-         * Called at the start of an epoch.
-         * @param epoch Index of epoch.
-         * @param logs Dictionary of logs.
-         */
-        async onEpochBegin(epoch, logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          for (const callback of this.callbacks) {
-            await callback.onEpochBegin(epoch, logs);
-          }
-        }
-        /**
-         * Called at the end of an epoch.
-         * @param epoch Index of epoch.
-         * @param logs Dictionary of logs.
-         */
-        async onEpochEnd(epoch, logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          for (const callback of this.callbacks) {
-            await callback.onEpochEnd(epoch, logs);
-          }
-        }
-        /**
-         * Called  right before processing a batch.
-         * @param batch Index of batch within the current epoch.
-         * @param logs Dictionary of logs.
-         */
-        async onBatchBegin(batch, logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          for (const callback of this.callbacks) {
-            await callback.onBatchBegin(batch, logs);
-          }
-        }
-        /**
-         * Called at the end of a batch.
-         * @param batch Index of batch within the current epoch.
-         * @param logs Dictionary of logs.
-         */
-        async onBatchEnd(batch, logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          for (const callback of this.callbacks) {
-            await callback.onBatchEnd(batch, logs);
-          }
-        }
-        /**
-         * Called at the beginning of training.
-         * @param logs Dictionary of logs.
-         */
-        async onTrainBegin(logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          for (const callback of this.callbacks) {
-            await callback.onTrainBegin(logs);
-          }
-        }
-        /**
-         * Called at the end of training.
-         * @param logs Dictionary of logs.
-         */
-        async onTrainEnd(logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          for (const callback of this.callbacks) {
-            await callback.onTrainEnd(logs);
-          }
-        }
-      }
-      /**
-       * Callback that accumulates epoch averages of metrics.
-       *
-       * This callback is automatically applied to every LayersModel.
-       */
-      class base_callbacks_BaseLogger extends BaseCallback {
-        constructor() {
-          super();
-        }
-        async onEpochBegin(epoch) {
-          this.seen = 0;
-          this.totals = {};
-        }
-        async onBatchEnd(batch, logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          const batchSize = logs["size"] == null ? 0 : logs["size"];
-          this.seen += batchSize;
-          for (const key in logs) {
-            const value = logs[key];
-            if (typeof value === "number") {
-              if (!this.totals.hasOwnProperty(key)) {
-                this.totals[key] = 0;
-              }
-              this.totals[key] = this.totals[key] + value * batchSize;
-            } else {
-              let oldTotalsToDispose;
-              if (key in this.totals) {
-                oldTotalsToDispose = this.totals[key];
-              } else {
-                this.totals[key] = 0;
-              }
-              const total = Object(dist["tidy"])(() =>
-                Object(dist["add"])(this.totals[key], Object(dist["mul"])(value, batchSize))
-              );
-              this.totals[key] = total;
-              if (oldTotalsToDispose != null) {
-                oldTotalsToDispose.dispose();
-              }
-            }
-          }
-        }
-        async onEpochEnd(epoch, logs) {
-          if (logs != null) {
-            for (const key of this.params["metrics"]) {
-              if (this.totals[key] == null) {
-                continue;
-              }
-              if (typeof this.totals[key] === "number") {
-                logs[key] = this.totals[key] / this.seen;
-              } else {
-                Object(dist["tidy"])(() => {
-                  const log = Object(dist["mul"])(
-                    Object(dist["div"])(1, this.seen),
-                    this.totals[key]
-                  );
-                  logs[key] = log;
-                  this.totals[key].dispose();
-                  Object(dist["keep"])(logs[key]);
-                });
-              }
-            }
-          }
-        }
-      }
-      /**
-       * Callback that records events into a `History` object. This callback is
-       * automatically applied to every TF.js Layers model. The `History` object
-       * gets returned by the `fit` method of models.
-       */
-      class History extends BaseCallback {
-        async onTrainBegin(logs) {
-          this.epoch = [];
-          this.history = {};
-        }
-        async onEpochEnd(epoch, logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          this.epoch.push(epoch);
-          for (const key in logs) {
-            if (this.history[key] == null) {
-              this.history[key] = [];
-            }
-            this.history[key].push(logs[key]);
-          }
-        }
-        /**
-         * Await the values of all losses and metrics.
-         */
-        async syncData() {
-          const promises = [];
-          const keys = [];
-          const indices = [];
-          for (const key in this.history) {
-            const valueArray = this.history[key];
-            for (let i = 0; i < valueArray.length; ++i) {
-              if (typeof valueArray[i] !== "number") {
-                const valueScalar = valueArray[i];
-                promises.push(valueScalar.data());
-                keys.push(key);
-                indices.push(i);
-              }
-            }
-          }
-          const values = await Promise.all(promises);
-          for (let n = 0; n < values.length; ++n) {
-            const tensorToDispose = this.history[keys[n]][indices[n]];
-            tensorToDispose.dispose();
-            this.history[keys[n]][indices[n]] = values[n][0];
-          }
-        }
-      }
-      /**
-       * Custom callback for training.
-       */
-      class base_callbacks_CustomCallback extends BaseCallback {
-        constructor(args, yieldEvery) {
-          super();
-          this.currentEpoch = 0;
-          this.yieldEvery = yieldEvery || "auto";
-          if (this.yieldEvery === "auto") {
-            this.yieldEvery = DEFAULT_YIELD_EVERY_MS;
-          }
-          if (this.yieldEvery === "never" && args.onYield != null) {
-            throw new Error(
-              "yieldEvery is `never` but you provided an `onYield` callback. " +
-                "Either change `yieldEvery` or remove the callback"
-            );
-          }
-          if (dist["util"].isNumber(this.yieldEvery)) {
-            // Decorate `maybeWait` so it will be called at most once every
-            // `yieldEvery` ms.
-            this.maybeWait = debounce(this.maybeWait.bind(this), this.yieldEvery);
-          }
-          this.trainBegin = args.onTrainBegin;
-          this.trainEnd = args.onTrainEnd;
-          this.epochBegin = args.onEpochBegin;
-          this.epochEnd = args.onEpochEnd;
-          this.batchBegin = args.onBatchBegin;
-          this.batchEnd = args.onBatchEnd;
-          this.yield = args.onYield;
-        }
-        async maybeWait(epoch, batch, logs) {
-          const ps = [];
-          if (this.yield != null) {
-            await resolveScalarsInLogs(logs);
-            ps.push(this.yield(epoch, batch, logs));
-          }
-          ps.push(Object(dist["nextFrame"])());
-          await Promise.all(ps);
-        }
-        async onEpochBegin(epoch, logs) {
-          this.currentEpoch = epoch;
-          if (this.epochBegin != null) {
-            await resolveScalarsInLogs(logs);
-            await this.epochBegin(epoch, logs);
-          }
-        }
-        async onEpochEnd(epoch, logs) {
-          const ps = [];
-          if (this.epochEnd != null) {
-            await resolveScalarsInLogs(logs);
-            ps.push(this.epochEnd(epoch, logs));
-          }
-          if (this.yieldEvery === "epoch") {
-            ps.push(Object(dist["nextFrame"])());
-          }
-          await Promise.all(ps);
-        }
-        async onBatchBegin(batch, logs) {
-          if (this.batchBegin != null) {
-            await resolveScalarsInLogs(logs);
-            await this.batchBegin(batch, logs);
-          }
-        }
-        async onBatchEnd(batch, logs) {
-          const ps = [];
-          if (this.batchEnd != null) {
-            await resolveScalarsInLogs(logs);
-            ps.push(this.batchEnd(batch, logs));
-          }
-          if (this.yieldEvery === "batch") {
-            ps.push(Object(dist["nextFrame"])());
-          } else if (dist["util"].isNumber(this.yieldEvery)) {
-            ps.push(this.maybeWait(this.currentEpoch, batch, logs));
-          }
-          await Promise.all(ps);
-        }
-        async onTrainBegin(logs) {
-          if (this.trainBegin != null) {
-            await resolveScalarsInLogs(logs);
-            await this.trainBegin(logs);
-          }
-        }
-        async onTrainEnd(logs) {
-          if (this.trainEnd != null) {
-            await resolveScalarsInLogs(logs);
-            await this.trainEnd(logs);
-          }
-        }
-      }
-      /**
-       * Standardize callbacks or configurations of them to an Array of callbacks.
-       */
-      function standardizeCallbacks(callbacks, yieldEvery) {
-        if (callbacks == null) {
-          callbacks = {};
-        }
-        if (callbacks instanceof BaseCallback) {
-          return [callbacks];
-        }
-        if (Array.isArray(callbacks) && callbacks[0] instanceof BaseCallback) {
-          return callbacks;
-        }
-        // Convert custom callback configs to custom callback objects.
-        const callbackConfigs = toList(callbacks);
-        return callbackConfigs.map(
-          (callbackConfig) => new base_callbacks_CustomCallback(callbackConfig, yieldEvery)
-        );
-      }
-      /**
-       * A global registry for callback constructors to be used during
-       * LayersModel.fit().
-       */
-      class base_callbacks_CallbackConstructorRegistry {
-        /**
-         * Blocks public access to constructor.
-         */
-        constructor() {}
-        /**
-         * Register a tf.LayersModel.fit() callback constructor.
-         *
-         * The registered callback constructor will be used to instantiate
-         * callbacks for every tf.LayersModel.fit() call afterwards.
-         *
-         * @param verbosityLevel Level of verbosity at which the `callbackConstructor`
-         *   is to be reigstered.
-         * @param callbackConstructor A no-arg constructor for `tf.Callback`.
-         * @throws Error, if the same callbackConstructor has been registered before,
-         *   either at the same or a different `verbosityLevel`.
-         */
-        static registerCallbackConstructor(verbosityLevel, callbackConstructor) {
-          dist["util"].assert(
-            verbosityLevel >= 0 && Number.isInteger(verbosityLevel),
-            () =>
-              `Verbosity level is expected to be an integer >= 0, ` + `but got ${verbosityLevel}`
-          );
-          base_callbacks_CallbackConstructorRegistry.checkForDuplicate(callbackConstructor);
-          if (base_callbacks_CallbackConstructorRegistry.constructors[verbosityLevel] == null) {
-            base_callbacks_CallbackConstructorRegistry.constructors[verbosityLevel] = [];
-          }
-          base_callbacks_CallbackConstructorRegistry.constructors[verbosityLevel].push(
-            callbackConstructor
-          );
-        }
-        static checkForDuplicate(callbackConstructor) {
-          for (const levelName in base_callbacks_CallbackConstructorRegistry.constructors) {
-            const constructors =
-              base_callbacks_CallbackConstructorRegistry.constructors[+levelName];
-            constructors.forEach((ctor) => {
-              if (ctor === callbackConstructor) {
-                throw new ValueError("Duplicate callback constructor.");
-              }
-            });
-          }
-        }
-        /**
-         * Clear all registered callback constructors.
-         */
-        static clear() {
-          base_callbacks_CallbackConstructorRegistry.constructors = {};
-        }
-        /**
-         * Create callbacks using the registered callback constructors.
-         *
-         * Given `verbosityLevel`, all constructors registered at that level or above
-         * will be called and the instantiated callbacks will be used.
-         *
-         * @param verbosityLevel: Level of verbosity.
-         */
-        static createCallbacks(verbosityLevel) {
-          const constructors = [];
-          for (const levelName in base_callbacks_CallbackConstructorRegistry.constructors) {
-            const level = +levelName;
-            if (verbosityLevel >= level) {
-              constructors.push(...base_callbacks_CallbackConstructorRegistry.constructors[level]);
-            }
-          }
-          return constructors.map((ctor) => new ctor());
-        }
-      }
-      base_callbacks_CallbackConstructorRegistry.constructors = {};
-      function configureCallbacks(
-        callbacks,
-        verbose,
-        epochs,
-        initialEpoch,
-        numTrainSamples,
-        stepsPerEpoch,
-        batchSize,
-        doValidation,
-        callbackMetrics
-      ) {
-        const history = new History();
-        const actualCallbacks = [
-          new base_callbacks_BaseLogger(),
-          ...base_callbacks_CallbackConstructorRegistry.createCallbacks(verbose),
-        ];
-        if (callbacks != null) {
-          actualCallbacks.push(...callbacks);
-        }
-        actualCallbacks.push(history);
-        const callbackList = new CallbackList(actualCallbacks);
-        // TODO(cais): Figure out when this LayersModel instance can have a
-        // dynamically
-        //   set property called 'callback_model' as in PyKeras.
-        callbackList.setParams({
-          epochs,
-          initialEpoch,
-          samples: numTrainSamples,
-          steps: stepsPerEpoch,
-          batchSize,
-          verbose,
-          doValidation,
-          metrics: callbackMetrics,
-        });
-        return { callbackList, history };
-      }
-      //# sourceMappingURL=base_callbacks.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/serialization.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original Source layers/__init__.py */
-
-      /**
-       * Instantiate a layer from a config dictionary.
-       * @param config dict of the form {class_name: str, config: dict}
-       * @param customObjects dict mapping class names (or function names)
-       *   of custom (non-Keras) objects to class/functions
-       * @param fastWeightInit Optional flag to use fast weight initialization
-       *   during deserialization. This is applicable to cases in which
-       *   the initialization will be immediately overwritten by loaded weight
-       *   values. Default: `false`.
-       * @returns Layer instance (may be LayersModel, Sequential, Layer...)
-       */
-      function deserialize(config, customObjects = {}, fastWeightInit = false) {
-        return deserializeKerasObject(
-          config,
-          dist["serialization"].SerializationMap.getMap().classNameMap,
-          customObjects,
-          "layer",
-          fastWeightInit
-        );
-      }
-      //# sourceMappingURL=serialization.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/losses.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original Source: losses.py */
-
-      /**
-       * Normalizes a tensor wrt the L2 norm alongside the specified axis.
-       * @param x
-       * @param axis Axis along which to perform normalization.
-       */
-      function l2Normalize(x, axis) {
-        return Object(dist["tidy"])(() => {
-          if (x.dtype !== "float32") {
-            x = x.asType("float32");
-          }
-          const squareSum = dist["sum"](square(x), axis, true);
-          const epsilonTensor = dist["fill"](squareSum.shape, common_epsilon());
-          const norm = dist["sqrt"](dist["maximum"](squareSum, epsilonTensor));
-          return dist["div"](x, norm);
-        });
-      }
-      function meanSquaredError(yTrue, yPred) {
-        return Object(dist["tidy"])(() => dist["mean"](square(dist["sub"](yPred, yTrue)), -1));
-      }
-      function meanAbsoluteError(yTrue, yPred) {
-        return Object(dist["tidy"])(() => dist["mean"](dist["abs"](dist["sub"](yPred, yTrue)), -1));
-      }
-      function meanAbsolutePercentageError(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const diff = dist["sub"](yTrue, yPred);
-          const clippedTrue = dist["clipByValue"](
-            dist["abs"](yTrue),
-            common_epsilon(),
-            Number.MAX_VALUE
-          );
-          const absResult = dist["abs"](dist["div"](diff, clippedTrue));
-          return dist["mul"](100, dist["mean"](absResult, -1));
-        });
-      }
-      function meanSquaredLogarithmicError(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const clippedPred = dist["clipByValue"](yPred, common_epsilon(), Number.MAX_VALUE);
-          const firstLog = dist["log"](dist["add"](1, clippedPred));
-          const clippedTrue = dist["clipByValue"](yTrue, common_epsilon(), Number.MAX_VALUE);
-          const secondLog = dist["log"](dist["add"](1, clippedTrue));
-          return dist["mean"](square(dist["sub"](firstLog, secondLog)), -1);
-        });
-      }
-      function squaredHinge(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const maxResult = dist["maximum"](0, dist["sub"](1, dist["mul"](yTrue, yPred)));
-          return dist["mean"](square(maxResult), -1);
-        });
-      }
-      function hinge(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const maxResult = dist["maximum"](0, dist["sub"](1, dist["mul"](yTrue, yPred)));
-          return dist["mean"](maxResult, -1);
-        });
-      }
-      function categoricalHinge(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const pos = dist["sum"](dist["mul"](yTrue, yPred), -1);
-          const neg = dist["max"](dist["mul"](dist["sub"](1, yTrue), yPred), -1);
-          return dist["maximum"](0, dist["add"](1, dist["sub"](neg, pos)));
-        });
-      }
-      /**
-       * Logarithm of the hyperbolic cosine of the prediction error.
-       *
-       * `log(cosh(x))` is approximately equal to `(x ** 2) / 2` for small `x` and
-       * to `abs(x) - log(2)` for large `x`. This means that 'logcosh' works mostly
-       * like the mean squared error, but will not be so strongly affected by the
-       * occasional wildly incorrect prediction.
-       */
-      function logcosh(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const log2 = Math.log(2);
-          const predictionDiff = dist["sub"](yPred, yTrue);
-          const logcoshResult = dist["sub"](
-            dist["add"](predictionDiff, dist["softplus"](dist["mul"](-2, predictionDiff))),
-            log2
-          );
-          return dist["mean"](logcoshResult, -1);
-        });
-      }
-      function categoricalCrossentropy(target, output, fromLogits = false) {
-        return Object(dist["tidy"])(() => {
-          if (fromLogits) {
-            output = dist["softmax"](output);
-          } else {
-            // scale preds so that the class probabilities of each sample sum to 1.
-            const outputSum = dist["sum"](output, output.shape.length - 1, true);
-            output = dist["div"](output, outputSum);
-          }
-          output = dist["clipByValue"](output, common_epsilon(), 1 - common_epsilon());
-          return dist["neg"](
-            dist["sum"](dist["mul"](target.toFloat(), dist["log"](output)), output.shape.length - 1)
-          );
-        });
-      }
-      /**
-       * Categorical crossentropy with integer targets.
-       *
-       * @param target An integer tensor.
-       * @param output A tensor resulting from a softmax (unless `fromLogits` is
-       *  `true`, in which case `output` is expected to be the logits).
-       * @param fromLogits Boolean, whether `output` is the result of a softmax, or is
-       *   a tensor of logits.
-       */
-      function sparseCategoricalCrossentropy(target, output, fromLogits = false) {
-        return Object(dist["tidy"])(() => {
-          const flatTarget = dist["floor"](flatten(target)).toInt();
-          output = dist["clipByValue"](output, common_epsilon(), 1 - common_epsilon());
-          const outputShape = output.shape;
-          const oneHotTarget = dist["oneHot"](
-            flatTarget,
-            outputShape[outputShape.length - 1]
-          ).reshape(outputShape);
-          return categoricalCrossentropy(oneHotTarget, output, fromLogits);
-        });
-      }
-      /**
-       * From TensorFlow's implementation in nn_impl.py:
-       *
-       * For brevity, let `x = logits`, `z = labels`.  The logistic loss is
-       *      z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
-       *    = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
-       *    = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
-       *    = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
-       *    = (1 - z) * x + log(1 + exp(-x))
-       *    = x - x * z + log(1 + exp(-x))
-       * For x < 0, to avoid overflow in exp(-x), we reformulate the above
-       *      x - x * z + log(1 + exp(-x))
-       *    = log(exp(x)) - x * z + log(1 + exp(-x))
-       *    = - x * z + log(1 + exp(x))
-       * Hence, to ensure stability and avoid overflow, the implementation uses this
-       * equivalent formulation
-       *    max(x, 0) - x * z + log(1 + exp(-abs(x)))
-       *
-       * @param labels The labels.
-       * @param logits The logits.
-       */
-      function sigmoidCrossEntropyWithLogits(labels, logits) {
-        if (!dist["util"].arraysEqual(labels.shape, logits.shape)) {
-          throw new ValueError(
-            `logits and labels must have the same shape, but got shapes ` +
-              `${JSON.stringify(labels.shape)} and ${JSON.stringify(logits.shape)}`
-          );
-        }
-        return Object(dist["tidy"])(() => {
-          // The logistic loss formula from above is
-          //   x - x * z + log(1 + exp(-x))
-          // For x < 0, a more numerically stable formula is
-          //   -x * z + log(1 + exp(x))
-          // Note that these two expressions can be combined into the following:
-          //   max(x, 0) - x * z + log(1 + exp(-abs(x)))
-          const reluLogits = logits.relu();
-          const negAbsLogits = logits.abs().neg();
-          return reluLogits.sub(logits.mul(labels)).add(negAbsLogits.exp().log1p());
-        });
-      }
-      function binaryCrossentropy(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          let y;
-          y = dist["clipByValue"](yPred, common_epsilon(), 1 - common_epsilon());
-          y = dist["log"](dist["div"](y, dist["sub"](1, y)));
-          return dist["mean"](sigmoidCrossEntropyWithLogits(yTrue, y), -1);
-        });
-      }
-      function kullbackLeiblerDivergence(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const clippedTrue = dist["clipByValue"](yTrue, common_epsilon(), 1);
-          const clippedPred = dist["clipByValue"](yPred, common_epsilon(), 1);
-          return dist["sum"](
-            dist["mul"](yTrue, dist["log"](dist["div"](clippedTrue, clippedPred))),
-            -1
-          );
-        });
-      }
-      function poisson(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const logPred = dist["log"](dist["add"](common_epsilon(), yPred));
-          return dist["mean"](dist["sub"](yPred, dist["mul"](yTrue, logPred)), -1);
-        });
-      }
-      function cosineProximity(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const trueNormalized = l2Normalize(yTrue, -1);
-          const predNormalized = l2Normalize(yPred, -1);
-          const trueXPred = dist["mul"](trueNormalized, predNormalized);
-          return dist["neg"](dist["sum"](trueXPred, -1));
-        });
-      }
-      const mse = meanSquaredError;
-      const MSE = meanSquaredError;
-      const mae = meanAbsoluteError;
-      const MAE = meanAbsoluteError;
-      const mape = meanAbsolutePercentageError;
-      const MAPE = meanAbsolutePercentageError;
-      const msle = meanSquaredLogarithmicError;
-      const MSLE = meanSquaredLogarithmicError;
-      const kld = kullbackLeiblerDivergence;
-      const KLD = kullbackLeiblerDivergence;
-      const cosine = cosineProximity;
-      // TODO(michaelterry): Add deserialize() function.
-      const lossesMap = {
-        meanSquaredError,
-        meanAbsoluteError,
-        meanAbsolutePercentageError,
-        meanSquaredLogarithmicError,
-        squaredHinge,
-        hinge,
-        categoricalHinge,
-        logcosh,
-        categoricalCrossentropy,
-        sparseCategoricalCrossentropy,
-        binaryCrossentropy,
-        kullbackLeiblerDivergence,
-        poisson,
-        cosineProximity,
-      };
-      // Porting note: This diverges from the PyKeras implementation and may need to
-      // change based on (de)serialization requirements.
-      function get(identifierOrFn) {
-        if (typeof identifierOrFn === "string") {
-          if (identifierOrFn in lossesMap) {
-            return lossesMap[identifierOrFn];
-          }
-          let errMsg = `Unknown loss ${identifierOrFn}`;
-          if (identifierOrFn.toLowerCase().includes("softmaxcrossentropy")) {
-            errMsg =
-              `Unknown loss ${identifierOrFn}. ` +
-              'Use "categoricalCrossentropy" as the string name for ' +
-              "tf.losses.softmaxCrossEntropy";
-          }
-          throw new ValueError(errMsg);
-        } else {
-          return identifierOrFn;
-        }
-      }
-      //# sourceMappingURL=losses.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/metrics.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Built-in metrics.
-       */
-
-      function binaryAccuracy(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const threshold = dist["mul"](0.5, dist["onesLike"](yPred));
-          const yPredThresholded = cast(dist["greater"](yPred, threshold), yTrue.dtype);
-          return dist["mean"](dist["equal"](yTrue, yPredThresholded), -1);
-        });
-      }
-      function categoricalAccuracy(yTrue, yPred) {
-        return Object(dist["tidy"])(() =>
-          cast(dist["equal"](dist["argMax"](yTrue, -1), dist["argMax"](yPred, -1)), "float32")
-        );
-      }
-      function truePositives(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          return dist["logicalAnd"](yTrue.equal(1), yPred.equal(1)).sum().cast("float32");
-        });
-      }
-      function falseNegatives(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          return dist["logicalAnd"](yTrue.equal(1), yPred.equal(0)).sum().cast("float32");
-        });
-      }
-      function falsePositives(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          return dist["logicalAnd"](yTrue.equal(0), yPred.equal(1)).sum().cast("float32");
-        });
-      }
-      function precision(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const tp = truePositives(yTrue, yPred);
-          const fp = falsePositives(yTrue, yPred);
-          const denominator = tp.add(fp);
-          return dist["where"](dist["greater"](denominator, 0), tp.div(denominator), 0).cast(
-            "float32"
-          );
-        });
-      }
-      function recall(yTrue, yPred) {
-        return Object(dist["tidy"])(() => {
-          const tp = truePositives(yTrue, yPred);
-          const fn = falseNegatives(yTrue, yPred);
-          const denominator = tp.add(fn);
-          return dist["where"](dist["greater"](denominator, 0), tp.div(denominator), 0).cast(
-            "float32"
-          );
-        });
-      }
-      function metrics_binaryCrossentropy(yTrue, yPred) {
-        return binaryCrossentropy(yTrue, yPred);
-      }
-      function sparseCategoricalAccuracy(yTrue, yPred) {
-        if (yTrue.rank === yPred.rank) {
-          yTrue = yTrue.squeeze([yTrue.rank - 1]);
-        }
-        yPred = yPred.argMax(-1);
-        if (yPred.dtype !== yTrue.dtype) {
-          yPred = yPred.asType(yTrue.dtype);
-        }
-        return dist["equal"](yTrue, yPred).asType("float32");
-      }
-      function topKCategoricalAccuracy(yTrue, yPred) {
-        throw new NotImplementedError();
-      }
-      function sparseTopKCategoricalAccuracy(yTrue, yPred) {
-        throw new NotImplementedError();
-      }
-      // Aliases.
-      const metrics_mse = meanSquaredError;
-      const metrics_MSE = meanSquaredError;
-      const metrics_mae = meanAbsoluteError;
-      const metrics_MAE = meanAbsoluteError;
-      const metrics_mape = meanAbsolutePercentageError;
-      const metrics_MAPE = meanAbsolutePercentageError;
-      const metrics_categoricalCrossentropy = categoricalCrossentropy;
-      const metrics_cosine = cosineProximity;
-      const metrics_sparseCategoricalCrossentropy = sparseCategoricalCrossentropy;
-      // TODO(cais, nielsene): Add serialize().
-      const metricsMap = {
-        binaryAccuracy,
-        categoricalAccuracy,
-        precision,
-        categoricalCrossentropy: metrics_categoricalCrossentropy,
-        sparseCategoricalCrossentropy: metrics_sparseCategoricalCrossentropy,
-        mse: metrics_mse,
-        MSE: metrics_MSE,
-        mae: metrics_mae,
-        MAE: metrics_MAE,
-        mape: metrics_mape,
-        MAPE: metrics_MAPE,
-        cosine: metrics_cosine,
-      };
-      function metrics_get(identifier) {
-        if (typeof identifier === "string" && identifier in metricsMap) {
-          return metricsMap[identifier];
-        } else if (typeof identifier !== "string" && identifier != null) {
-          return identifier;
-        } else {
-          throw new ValueError(`Unknown metric ${identifier}`);
-        }
-      }
-      /**
-       * Get the shortcut function name.
-       *
-       * If the fn name is a string,
-       *   directly return the string name.
-       * If the function is included in metricsMap or lossesMap,
-       *   return key of the map.
-       *   - If the function relative to multiple keys,
-       *     return the first found key as the function name.
-       *   - If the function exists in both lossesMap and metricsMap,
-       *     search lossesMap first.
-       * If the function is not included in metricsMap or lossesMap,
-       *   return the function name.
-       *
-       * @param fn loss function, metric function, or short cut name.
-       * @returns Loss or Metric name in string.
-       */
-      function getLossOrMetricName(fn) {
-        assert(fn !== null, `Unknown LossOrMetricFn ${fn}`);
-        if (typeof fn === "string") {
-          return fn;
-        } else {
-          let fnName;
-          for (const key of Object.keys(lossesMap)) {
-            if (lossesMap[key] === fn) {
-              fnName = key;
-              break;
-            }
-          }
-          if (fnName !== undefined) {
-            return fnName;
-          }
-          for (const key of Object.keys(metricsMap)) {
-            if (metricsMap[key] === fn) {
-              fnName = key;
-              break;
-            }
-          }
-          if (fnName !== undefined) {
-            return fnName;
-          }
-          return fn.name;
-        }
-      }
-      //# sourceMappingURL=metrics.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/optimizers.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Optimizers.
-       */
-
-      // Add (de)serialize()
-      // Porting note: This diverges from the PyKeras implementation and may need to
-      // change based on (de)serialization requirements.
-      function getOptimizer(identifier) {
-        const optimizerMap = {
-          Adagrad: () => dist["train"].adagrad(0.01),
-          Adadelta: () => dist["train"].adadelta(1, 0.95, common_epsilon()),
-          Adam: () => dist["train"].adam(0.001, 0.9, 0.999, common_epsilon()),
-          Adamax: () => dist["train"].adamax(0.002, 0.9, 0.999, common_epsilon(), 0),
-          RMSProp: () => dist["train"].rmsprop(0.001, 0.9, 0, common_epsilon()),
-          SGD: () => dist["train"].sgd(0.01),
-        };
-        optimizerMap["adagrad"] = optimizerMap["Adagrad"];
-        optimizerMap["adadelta"] = optimizerMap["Adadelta"];
-        optimizerMap["adam"] = optimizerMap["Adam"];
-        optimizerMap["adamax"] = optimizerMap["Adamax"];
-        optimizerMap["rmsprop"] = optimizerMap["RMSProp"];
-        optimizerMap["sgd"] = optimizerMap["SGD"];
-        if (identifier in optimizerMap) {
-          return optimizerMap[identifier]();
-        }
-        throw new ValueError(`Unknown Optimizer ${identifier}`);
-      }
-      //# sourceMappingURL=optimizers.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/user_defined_metadata.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /** Utility functions related to user-defined metadata. */
-      // Maximum recommended serialized size for user-defined metadata.
-      // Beyond this limit, a warning message will be printed during model loading and
-      // saving.
-      const MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH = 1 * 1024 * 1024;
-      /**
-       * Check validity of user-defined metadata.
-       *
-       * @param userDefinedMetadata
-       * @param modelName Name of the model that the user-defined metadata belongs to.
-       *   Used during construction of error messages.
-       * @param checkSize Whether to check the size of the metadata is under
-       *   recommended limit. Default: `false`. If `true`, will try stringify the
-       *   JSON object and print a console warning if the serialzied size is above the
-       *   limit.
-       * @throws Error if `userDefinedMetadata` is not a plain JSON object.
-       */
-      function checkUserDefinedMetadata(userDefinedMetadata, modelName, checkSize = false) {
-        if (
-          userDefinedMetadata == null ||
-          typeof userDefinedMetadata !== "object" ||
-          Object.getPrototypeOf(userDefinedMetadata) !== Object.prototype ||
-          !plainObjectCheck(userDefinedMetadata)
-        ) {
-          throw new Error("User-defined metadata is expected to be a JSON object, but is not.");
-        }
-        if (checkSize) {
-          const out = JSON.stringify(userDefinedMetadata);
-          if (out.length > MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH) {
-            console.warn(
-              `User-defined metadata of model "${modelName}" is too large in ` +
-                `size (length=${out.length} when serialized). It is not ` +
-                `recommended to store such large objects in user-defined metadata. ` +
-                `Please make sure its serialized length is <= ` +
-                `${MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH}.`
-            );
-          }
-        }
-      }
-      /**
-       * Check if an input is plain JSON object or any valid subfield of it.
-       *
-       * @param x The input to be checked.
-       * @param assertObject Whether to assert `x` is a JSON object, i.e., reject
-       *   cases of arrays and primitives.
-       * @return Returns `true` if and only if `x` is a plain JSON object,
-       *   a JSON-valid primitive including string, number, boolean and null,
-       *   or an array of the said types.
-       */
-      // tslint:disable-next-line:no-any
-      function plainObjectCheck(x) {
-        if (x === null) {
-          // Note: typeof `null` is 'object', and `null` is valid in JSON.
-          return true;
-        } else if (typeof x === "object") {
-          if (Object.getPrototypeOf(x) === Object.prototype) {
-            // `x` is a JavaScript object and its prototype is Object.
-            const keys = Object.keys(x);
-            for (const key of keys) {
-              if (typeof key !== "string") {
-                // JSON keys must be strings.
-                return false;
-              }
-              if (!plainObjectCheck(x[key])) {
-                // Recursive call.
-                return false;
-              }
-            }
-            return true;
-          } else {
-            // `x` is a JavaScript object but its prototype is not Object.
-            if (Array.isArray(x)) {
-              // `x` is a JavaScript array.
-              for (const item of x) {
-                if (!plainObjectCheck(item)) {
-                  // Recursive call.
-                  return false;
-                }
-              }
-              return true;
-            } else {
-              // `x` is a JavaScript object and its prototype is not Object,
-              // and it's not an Array. I.e., it's a complex object such as
-              // `Error` and `Date`.
-              return false;
-            }
-          }
-        } else {
-          // `x` is not a JavaScript object or `null`.
-          const xType = typeof x;
-          return xType === "string" || xType === "number" || xType === "boolean";
-        }
-      }
-      //# sourceMappingURL=user_defined_metadata.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/layer_utils.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      /**
-       * Print the summary of a LayersModel object.
-       *
-       * @param model tf.LayersModel instance.
-       * @param lineLength Total length of printed lines. Set this to adapt to the
-       *   display to different terminal or console sizes.
-       * @param positions Relative or absolute positions of log elements in each
-       *   line. Each number corresponds to right-most (i.e., ending) position of a
-       *   column.
-       *   If not provided, defaults to `[0.45, 0.85, 1]` for sequential-like
-       *   models and `[0.33, 0.55, 0.67, 1]` for non-sequential like models.
-       * @param printFn Print function to use.
-       *   It will be called on each line of the summary. You can provide a custom
-       *   function in order to capture the string summary. Defaults to `console.log`.
-       */
-      function printSummary(
-        model,
-        lineLength,
-        positions,
-        // tslint:disable-next-line:no-any
-        printFn = console.log
-      ) {
-        const sequentialLike = isModelSequentialLike(model);
-        // Header names for different log elements.
-        const toDisplay = ["Layer (type)", "Output shape", "Param #"];
-        if (sequentialLike) {
-          lineLength = lineLength || 65;
-          positions = positions || [0.45, 0.85, 1];
-        } else {
-          lineLength = lineLength || 98;
-          positions = positions || [0.33, 0.55, 0.67, 1];
-          // Header names for different log elements.
-        }
-        if (positions[positions.length - 1] <= 1) {
-          // `positions` is relative. Convert it to absolute positioning.
-          positions = positions.map((p) => Math.floor(lineLength * p));
-        }
-        let relevantNodes;
-        if (!sequentialLike) {
-          toDisplay.push("Receives inputs");
-          relevantNodes = [];
-          for (const depth in model.nodesByDepth) {
-            relevantNodes.push(...model.nodesByDepth[depth]);
-          }
-        }
-        printFn("_".repeat(lineLength));
-        printRow(toDisplay, positions, printFn);
-        printFn("=".repeat(lineLength));
-        const layers = model.layers;
-        for (let i = 0; i < layers.length; ++i) {
-          if (sequentialLike) {
-            printLayerSummary(layers[i], positions, printFn);
-          } else {
-            printLayerSummaryWithConnections(layers[i], positions, relevantNodes, printFn);
-          }
-          printFn((i === layers.length - 1 ? "=" : "_").repeat(lineLength));
-        }
-        // tslint:disable-next-line:no-any
-        model.checkTrainableWeightsConsistency();
-        const trainableCount = countTrainableParams(model);
-        const nonTrainableCount = countParamsInWeights(model.nonTrainableWeights);
-        printFn(`Total params: ${trainableCount + nonTrainableCount}`);
-        printFn(`Trainable params: ${trainableCount}`);
-        printFn(`Non-trainable params: ${nonTrainableCount}`);
-        printFn("_".repeat(lineLength));
-      }
-      function countTrainableParams(model) {
-        let trainableCount;
-        // tslint:disable:no-any
-        if (model.collectedTrainableWeights != null) {
-          trainableCount = countParamsInWeights(model.collectedTrainableWeights);
-        } else {
-          trainableCount = countParamsInWeights(model.trainableWeights);
-        }
-        // tslint:enable:no-any
-        return trainableCount;
-      }
-      function isModelSequentialLike(model) {
-        let sequentialLike = true;
-        const nodesByDepth = [];
-        const nodes = [];
-        for (const depth in model.nodesByDepth) {
-          nodesByDepth.push(model.nodesByDepth[depth]);
-        }
-        for (const depthNodes of nodesByDepth) {
-          if (
-            depthNodes.length > 1 ||
-            (depthNodes.length === 1 && depthNodes[0].inboundLayers.length > 1)
-          ) {
-            sequentialLike = false;
-            break;
-          }
-          nodes.push(...depthNodes);
-        }
-        if (sequentialLike) {
-          // Search for shared layers.
-          for (const layer of model.layers) {
-            let flag = false;
-            for (const node of layer.inboundNodes) {
-              if (nodes.indexOf(node) !== -1) {
-                if (flag) {
-                  sequentialLike = false;
-                  break;
-                } else {
-                  flag = true;
-                }
-              }
-            }
-            if (!sequentialLike) {
-              break;
-            }
-          }
-        }
-        return sequentialLike;
-      }
-      function printRow(
-        fields,
-        positions,
-        // tslint:disable-next-line:no-any
-        printFn = console.log
-      ) {
-        let line = "";
-        for (let i = 0; i < fields.length; ++i) {
-          if (i > 0) {
-            line = line.slice(0, line.length - 1) + " ";
-          }
-          line += fields[i];
-          line = line.slice(0, positions[i]);
-          line += " ".repeat(positions[i] - line.length);
-        }
-        printFn(line);
-      }
-      /**
-       * Prints a summary for a single Layer, without connectivity information.
-       *
-       * @param layer: Layer instance to print.
-       */
-      function printLayerSummary(
-        layer,
-        positions,
-        // tslint:disable-next-line:no-any
-        printFn
-      ) {
-        let outputShape;
-        try {
-          outputShape = JSON.stringify(layer.outputShape);
-        } catch (err) {
-          outputShape = "multiple";
-        }
-        const name = layer.name;
-        const className = layer.getClassName();
-        const fields = [`${name} (${className})`, outputShape, layer.countParams().toString()];
-        printRow(fields, positions, printFn);
-      }
-      /**
-       * Prints a summary for a single Layer, with connectivity information.
-       */
-      function printLayerSummaryWithConnections(
-        layer,
-        positions,
-        relevantNodes,
-        // tslint:disable-next-line:no-any
-        printFn
-      ) {
-        let outputShape;
-        try {
-          outputShape = JSON.stringify(layer.outputShape);
-        } catch (err) {
-          outputShape = "multiple";
-        }
-        const connections = [];
-        for (const node of layer.inboundNodes) {
-          if (
-            relevantNodes != null &&
-            relevantNodes.length > 0 &&
-            relevantNodes.indexOf(node) === -1
-          ) {
-            continue;
-          }
-          for (let i = 0; i < node.inboundLayers.length; ++i) {
-            const inboundLayer = node.inboundLayers[i].name;
-            const inboundLayerIndex = node.nodeIndices[i];
-            const inboundTensorIndex = node.tensorIndices[i];
-            connections.push(`${inboundLayer}[${inboundLayerIndex}][${inboundTensorIndex}]`);
-          }
-        }
-        const name = layer.name;
-        const className = layer.getClassName();
-        const firstConnection = connections.length === 0 ? "" : connections[0];
-        const fields = [
-          `${name} (${className})`,
-          outputShape,
-          layer.countParams().toString(),
-          firstConnection,
-        ];
-        printRow(fields, positions, printFn);
-        for (let i = 1; i < connections.length; ++i) {
-          printRow(["", "", "", connections[i]], positions, printFn);
-        }
-      }
-      //# sourceMappingURL=layer_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/serialization_utils.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      // tslint:enable
-      /**
-       * Test whether a value in an array is the name of a LayersModel or Layer.
-       * @param key The key name that the value is found under. Note that the key
-       *   may not be at the level immediately above the value, if the value is in a
-       *   nested array.
-       * @param index Index of the value in the Array that it is found in.
-       * @param value The value object.
-       * @returns A boolean indicating whether value is a name.
-       */
-      function isArrayItemInputOrOutputName(key, index, value) {
-        return (
-          (key === "inboundNodes" || key === "outputLayers" || key === "inputLayers") &&
-          index === 0 &&
-          typeof value === "string"
-        );
-      }
-      /**
-       * Convert a Pythonic config object to TypeScript config object.
-       * @param pythonicConfig The config object to convert.
-       * @param key Optional key name of the object being converted.
-       * @returns Result of the conversion.
-       */
-      function convertPythonicToTs(pythonicConfig, key) {
-        if (pythonicConfig === null) {
-          return null;
-        } else if (typeof pythonicConfig === "string") {
-          return toCamelCase(pythonicConfig);
-        } else if (typeof pythonicConfig === "number" || typeof pythonicConfig === "boolean") {
-          return pythonicConfig;
-        } else if (pythonicConfig instanceof Array) {
-          const tsArray = [];
-          const arrayLength = pythonicConfig.length;
-          for (let i = 0; i < arrayLength; ++i) {
-            const item = pythonicConfig[i];
-            if (isArrayItemInputOrOutputName(key, i, item)) {
-              tsArray.push(item);
-            } else {
-              tsArray.push(convertPythonicToTs(item, key));
-            }
-          }
-          return tsArray;
-        } else {
-          const tsDict = {};
-          for (const pythonicKey of Object.keys(pythonicConfig)) {
-            const pythonicValue = pythonicConfig[pythonicKey];
-            if (pythonicKey === "name" && typeof pythonicValue === "string") {
-              // Special case the 'name' key with a string value. Name values, such as
-              // the names of LayersModel and Layer instances, should not undergo the
-              // camel-case conversion.
-              tsDict[pythonicKey] = pythonicValue;
-            } else {
-              const tsKey = toCamelCase(pythonicKey);
-              tsDict[tsKey] = convertPythonicToTs(pythonicValue, tsKey);
-            }
-          }
-          return tsDict;
-        }
-      }
-      /**
-       * Convert a TypeScript config object to Python config object.
-       * @param tsConfig The config object to convert.
-       * @param key Optional key name of the object being converted.
-       * @returns Result of the conversion.
-       */
-      function convertTsToPythonic(tsConfig, key) {
-        if (tsConfig === null || tsConfig === undefined) {
-          return null;
-        } else if (typeof tsConfig === "string") {
-          return toSnakeCase(tsConfig);
-        } else if (typeof tsConfig === "number" || typeof tsConfig === "boolean") {
-          return tsConfig;
-        } else if (tsConfig instanceof Array) {
-          const pyArray = [];
-          const arrayLength = tsConfig.length;
-          for (let i = 0; i < arrayLength; ++i) {
-            const item = tsConfig[i];
-            if (isArrayItemInputOrOutputName(key, i, item)) {
-              pyArray.push(item);
-            } else {
-              pyArray.push(convertTsToPythonic(item, key));
-            }
-          }
-          return pyArray;
-        } else {
-          const pyDict = {};
-          for (const tsKey of Object.keys(tsConfig)) {
-            const tsValue = tsConfig[tsKey];
-            const pyKey = toSnakeCase(tsKey);
-            if ((tsKey === "name" || tsKey === "className") && typeof tsValue === "string") {
-              // Special case the 'name' key with a string value. Name values, such as
-              // the names of LayersModel and Layer instances, should not undergo the
-              // snake-case conversion.
-              pyDict[pyKey] = tsValue;
-            } else {
-              pyDict[pyKey] = convertTsToPythonic(tsValue, tsKey);
-            }
-          }
-          return pyDict;
-        }
-      }
-      //# sourceMappingURL=serialization_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/version.js
-      /** @license See the LICENSE file. */
-      // This code is auto-generated, do not modify this file!
-      const version = "2.0.1";
-
-      //# sourceMappingURL=version.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/executor.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Executor: Evaluates SymbolicTensor based on feeds.
-       */
-
-      /**
-       * Helper function to check the dtype and shape compatibility of a feed value.
-       */
-      function assertFeedCompatibility(key, val) {
-        // Check dtype compatibility.
-        if (key.dtype == null || key.dtype === val.dtype) {
-          //  a.  If types match, return val tensor as is.
-          return val;
-        }
-        try {
-          //  b. Attempt to convert to expected type.
-          return Object(dist["cast"])(val, key.dtype);
-        } catch (err) {
-          //  c. If conversion fails, return helpful error.
-          throw new ValueError(
-            `The dtype of the feed (${val.dtype}) can not be cast to the dtype ` +
-              `of the key '${key.name}' (${key.dtype}).`
-          );
-        }
-      }
-      /**
-       * FeedDict: A mapping from unique SymbolicTensors to feed values for them.
-       * A feed value is a concrete value represented as an `Tensor`.
-       */
-      class executor_FeedDict {
-        /**
-         * Constructor, optionally does copy-construction.
-         * @param feeds An Array of `Feed`s, or another `FeedDict`, in which case
-         *   copy-construction will be performed.
-         */
-        constructor(feeds) {
-          this.id2Value = {};
-          this.id2Mask = {};
-          this.name2Id = {};
-          if (feeds instanceof executor_FeedDict) {
-            for (const id in feeds.id2Value) {
-              this.id2Value[id] = feeds.id2Value[id];
-              if (id in feeds.id2Mask) {
-                this.id2Mask[id] = feeds.id2Mask[id];
-              }
-            }
-          } else {
-            if (feeds == null) {
-              return;
-            }
-            for (const feed of feeds) {
-              this.add(feed.key, feed.value);
-            }
-          }
-        }
-        /**
-         * Add a key-value pair to the FeedDict.
-         *
-         * @param key The key of the feed.
-         * @param value The value of the tensor feed.
-         * @param mask The value of the mask feed (optional).
-         * @returns This `FeedDict`.
-         * @throws ValueError: If the key `SymbolicTensor` already exists in the
-         *   `FeedDict`.
-         */
-        add(key, value, mask) {
-          if (this.id2Value[key.id] == null) {
-            this.id2Value[key.id] = assertFeedCompatibility(key, value);
-            this.name2Id[key.name] = key.id;
-            if (mask != null) {
-              this.id2Mask[key.id] = mask;
-            }
-          } else {
-            throw new ValueError(`Duplicate key: name=${key.name}, id=${key.id}`);
-          }
-          return this;
-        }
-        /**
-         * Add a Feed to the FeedDict.
-         * @param feed The new `Feed` to add.
-         * @returns This `FeedDict`.
-         */
-        addFeed(feed) {
-          this.add(feed.key, feed.value);
-        }
-        /**
-         * Probe whether a key already exists in the FeedDict.
-         * @param key
-         */
-        hasKey(key) {
-          return this.id2Value[key.id] != null;
-        }
-        /**
-         * Get all the SymbolicTensor available in this FeedDict.
-         */
-        names() {
-          return Object.keys(this.name2Id);
-        }
-        /**
-         * Get the feed value for given key.
-         * @param key The SymbolicTensor, or its name (as a string), of which the
-         *     value is sought.
-         * @returns If `key` exists, the corresponding feed value.
-         * @throws ValueError: If `key` does not exist in this `FeedDict`.
-         */
-        getValue(key) {
-          if (key instanceof topology_SymbolicTensor) {
-            if (this.id2Value[key.id] == null) {
-              throw new ValueError(`Nonexistent key: ${key.name}`);
-            } else {
-              return this.id2Value[key.id];
-            }
-          } else {
-            const id = this.name2Id[key];
-            if (id == null) {
-              throw new ValueError(`Feed dict has no SymbolicTensor name: ${key}`);
-            }
-            return this.id2Value[id];
-          }
-        }
-        /**
-         * Get the feed mask for given key.
-         * @param key The SymbolicTensor, or its name (as a string), of which the
-         *     value is sought.
-         * @returns If `key` exists, the corresponding feed mask.
-         * @throws ValueError: If `key` does not exist in this `FeedDict`.
-         */
-        getMask(key) {
-          if (key instanceof topology_SymbolicTensor) {
-            if (this.id2Value[key.id] == null) {
-              throw new ValueError(`Nonexistent key: ${key.name}`);
-            } else {
-              return this.id2Mask[key.id];
-            }
-          } else {
-            const id = this.name2Id[key];
-            if (id == null) {
-              throw new ValueError(`Feed dict has no SymbolicTensor name: ${key}`);
-            }
-            return this.id2Mask[id];
-          }
-        }
-        /** Dispose all mask Tensors held by this object. */
-        disposeMasks() {
-          if (this.id2Mask != null) {
-            Object(dist["dispose"])(this.id2Mask);
-          }
-        }
-      }
-      // Cache for topologically sorted SymbolicTensors for given execution
-      // targets (i.e., fetches).
-      const cachedSorted = {};
-      // Cache for recipient count maps for given execution targets (i.e., fetches).
-      const cachedRecipientCounts = {};
-      /**
-       * Execute a SymbolicTensor by using concrete feed values.
-       *
-       * A `SymbolicTensor` object is a node in a computation graph of TF.js
-       * Layers. The object is backed by a source layer and input
-       * `SymbolicTensor`s to the source layer. This method evaluates
-       * the `call()` method of the source layer, using concrete values of the
-       * inputs obtained from either
-       * * `feedDict`, if the input key exists in `feedDict`, or else,
-       * * a recursive call to `execute()` itself.
-       *
-       * @param x: The `SymbolicTensor` to execute.
-       * @param feedDict: The feed values, as base condition of the recursion.
-       *   execution.
-       * @param kwargs: Optional keyword arguments.
-       * @param probe: A probe object (of interface `ExecutionProbe`) used for
-       *   testing memory footprint of `execute` calls.
-       * @returns Result of the execution.
-       * @throws ValueError: If any `SymbolicTensor`s from `InputLayer`s
-       *   encountered during the execution lacks a feed value in `feedDict`.
-       */
-      function execute(fetches, feedDict, kwargs, probe) {
-        const training = kwargs == null ? false : kwargs["training"];
-        const arrayFetches = Array.isArray(fetches);
-        const fetchArray = arrayFetches ? fetches : [fetches];
-        const outputNames = fetchArray.map((t) => t.name);
-        const finalOutputs = [];
-        const feedNames = feedDict.names();
-        for (const outputName of outputNames) {
-          if (feedNames.indexOf(outputName) !== -1) {
-            finalOutputs.push(feedDict.getValue(outputName));
-          } else {
-            finalOutputs.push(null);
-          }
-        }
-        if (probe != null) {
-          // For optional probing of memory footprint during execution.
-          probe.maxNumTensors = -Infinity;
-          probe.minNumTensors = Infinity;
-        }
-        // Check cache.
-        const fetchAndFeedKey = outputNames.join(",") + "|" + feedDict.names().join(",");
-        let sorted;
-        let recipientCounts;
-        if (cachedSorted[fetchAndFeedKey] == null) {
-          // Cache doesn't contain the desired combination of fetches. Compute
-          // topological sort for the combination for the first time.
-          const out = getTopologicalSortAndRecipientCounts(fetchArray, feedDict);
-          sorted = out.sorted;
-          recipientCounts = out.recipientCounts;
-          // Store results in cache for future use.
-          cachedSorted[fetchAndFeedKey] = sorted;
-          cachedRecipientCounts[fetchAndFeedKey] = recipientCounts;
-        }
-        sorted = cachedSorted[fetchAndFeedKey];
-        recipientCounts = {};
-        if (!training) {
-          Object.assign(recipientCounts, cachedRecipientCounts[fetchAndFeedKey]);
-        }
-        const internalFeedDict = new executor_FeedDict(feedDict);
-        // Start iterative execution on the topologically-sorted SymbolicTensors.
-        for (let i = 0; i < sorted.length; ++i) {
-          if (probe != null) {
-            // For optional probing of memory usage during execution.
-            const numTensors = Object(dist["memory"])().numTensors;
-            if (numTensors > probe.maxNumTensors) {
-              probe.maxNumTensors = numTensors;
-            }
-            if (numTensors < probe.minNumTensors) {
-              probe.minNumTensors = numTensors;
-            }
-          }
-          const symbolic = sorted[i];
-          const srcLayer = symbolic.sourceLayer;
-          if (srcLayer instanceof input_layer_InputLayer) {
-            continue;
-          }
-          const inputValues = [];
-          const inputMasks = [];
-          const tensorsToDispose = [];
-          let maskExists = false;
-          for (const input of symbolic.inputs) {
-            const value = internalFeedDict.getValue(input);
-            const mask = internalFeedDict.getMask(input);
-            inputValues.push(value);
-            inputMasks.push(mask);
-            if (mask != null) {
-              maskExists = true;
-            }
-            if (!training) {
-              recipientCounts[input.name]--;
-              if (
-                recipientCounts[input.name] === 0 &&
-                !feedDict.hasKey(input) &&
-                outputNames.indexOf(input.name) === -1 &&
-                !value.isDisposed &&
-                input.sourceLayer.stateful !== true
-              ) {
-                tensorsToDispose.push(value);
-              }
-            }
-          }
-          if (maskExists) {
-            kwargs = kwargs || {};
-            kwargs["mask"] = inputMasks[0];
-          }
-          const outputTensors = toList(srcLayer.apply(inputValues, kwargs));
-          let outputMask = null;
-          if (srcLayer.supportsMasking) {
-            outputMask = srcLayer.computeMask(inputValues, inputMasks);
-          }
-          const layerOutputs = getNodeOutputs(symbolic);
-          const outputSymbolicTensors = Array.isArray(layerOutputs) ? layerOutputs : [layerOutputs];
-          for (let i = 0; i < outputSymbolicTensors.length; ++i) {
-            if (!internalFeedDict.hasKey(outputSymbolicTensors[i])) {
-              internalFeedDict.add(
-                outputSymbolicTensors[i],
-                outputTensors[i],
-                Array.isArray(outputMask) ? outputMask[0] : outputMask
-              );
-            }
-            const index = outputNames.indexOf(outputSymbolicTensors[i].name);
-            if (index !== -1) {
-              finalOutputs[index] = outputTensors[i];
-            }
-          }
-          if (!training) {
-            // Clean up Tensors that are no longer needed.
-            Object(dist["dispose"])(tensorsToDispose);
-          }
-        }
-        // NOTE(cais): Unlike intermediate tensors, we don't discard mask
-        // tensors as we go, because these tensors are sometimes passed over a
-        // series of mutliple layers, i.e., not obeying the immediate input
-        // relations in the graph. If this becomes a memory-usage concern,
-        // we can improve this in the future.
-        internalFeedDict.disposeMasks();
-        return arrayFetches ? finalOutputs : finalOutputs[0];
-      }
-      /**
-       * Sort the `SymbolicTensor`s topologically, for an array of fetches.
-       *
-       * This function calls getTopologicalSortAndRecipientCountsForOneFetch and
-       * merges their results.
-       *
-       * @param fetch The array of fetches requested. Must be a non-empty array.
-       * @param feedDict The dictionary of fed values.
-       * @returns sorted: Topologically-sorted array of SymbolicTensors.
-       *   recipientCounts: Recipient counts for all SymbolicTensors in `sorted`.
-       */
-      function getTopologicalSortAndRecipientCounts(fetches, feedDict) {
-        dist["util"].assert(
-          fetches != null && fetches.length > 0,
-          () => `Expected at least one fetch, got none`
-        );
-        let finalSorted = [];
-        let finalRecipientMap = {};
-        if (fetches.length === 1) {
-          // Special-casing 1 fetch for efficiency.
-          const out = getTopologicalSortAndRecipientCountsForOneFetch(fetches[0], feedDict);
-          finalSorted = out.sorted;
-          finalRecipientMap = out.recipientMap;
-        } else {
-          const visited = new Set();
-          for (const fetch of fetches) {
-            const { sorted, recipientMap } = getTopologicalSortAndRecipientCountsForOneFetch(
-              fetch,
-              feedDict
-            );
-            // Merge sorted SymbolicTensor Arrays.
-            for (const symbolicTensor of sorted) {
-              if (!visited.has(symbolicTensor.name)) {
-                finalSorted.push(symbolicTensor);
-                visited.add(symbolicTensor.name);
-              }
-            }
-            // Merge recipient maps.
-            for (const name in recipientMap) {
-              if (finalRecipientMap[name] == null) {
-                finalRecipientMap[name] = new Set();
-              }
-              recipientMap[name].forEach((recipient) => finalRecipientMap[name].add(recipient));
-            }
-          }
-        }
-        return {
-          sorted: finalSorted,
-          recipientCounts: recipientMap2Counts(finalRecipientMap),
-        };
-      }
-      function recipientMap2Counts(recipientMap) {
-        const recipientCounts = {};
-        for (const name in recipientMap) {
-          recipientCounts[name] = recipientMap[name].size;
-        }
-        return recipientCounts;
-      }
-      /**
-       * Sort the `SymbolicTensor`s topologically, for a single fetch.
-       *
-       * This helper function processes the upstream SymbolicTensors of a single
-       * fetch.
-       *
-       * @param fetch The single fetch requested.
-       * @param feedDict The dictionary of fed values.
-       * @returns sorted: Topologically-sorted array of SymbolicTensors.
-       *   recipientMap: Recipient names for all SymbolicTensors in `sorted`.
-       */
-      function getTopologicalSortAndRecipientCountsForOneFetch(fetch, feedDict) {
-        const visited = new Set();
-        const sorted = [];
-        const recipientMap = {};
-        // Put keys of the feedDict into visited first, so they don't have to be
-        // walked. This is needed in case where there are feeds for intermediate
-        // SymbolicTensors of the graph.
-        for (const key of feedDict.names()) {
-          visited.add(key);
-        }
-        const stack = [];
-        const marks = [];
-        // Initial population of stack and marks.
-        stack.push(fetch);
-        while (stack.length > 0) {
-          const top = stack[stack.length - 1];
-          if (visited.has(top.name)) {
-            stack.pop();
-            continue;
-          }
-          const topIsMarked = marks[marks.length - 1] === stack.length - 1;
-          if (top.inputs.length === 0 || topIsMarked) {
-            // Input SymbolicTensor or all children have been visited.
-            stack.pop();
-            sorted.push(top);
-            visited.add(top.name);
-            if (topIsMarked) {
-              marks.pop();
-            }
-          } else {
-            // A non-input SymbolicTensor whose upstream SymbolicTensors haven't
-            // been visited yet. Push them onto the stack.
-            marks.push(stack.length - 1);
-            for (const input of top.inputs) {
-              // Increment the recipient count. Note that this needs to happen
-              // regardless of whether the SymbolicTensor has been visited before.
-              if (recipientMap[input.name] == null) {
-                recipientMap[input.name] = new Set();
-              }
-              recipientMap[input.name].add(top.name);
-              if (visited.has(input.name)) {
-                continue; // Avoid repeated visits to the same SymbolicTensor.
-              }
-              stack.push(input);
-            }
-          }
-        }
-        return { sorted, recipientMap };
-      }
-      /**
-       * Get the symbolic output tensors of the node to which a given fetch belongs.
-       * @param fetch The fetched symbolic tensor.
-       * @returns The Array of symbolic tensors output by the node to which `fetch`
-       *   belongs.
-       */
-      function getNodeOutputs(fetch) {
-        let layerOutputs;
-        if (fetch.sourceLayer.inboundNodes.length === 1) {
-          layerOutputs = fetch.sourceLayer.output;
-        } else {
-          let nodeIndex = null;
-          for (let i = 0; i < fetch.sourceLayer.inboundNodes.length; ++i) {
-            for (const outputTensor of fetch.sourceLayer.inboundNodes[i].outputTensors) {
-              if (outputTensor.id === fetch.id) {
-                nodeIndex = i;
-                break;
-              }
-            }
-          }
-          layerOutputs = fetch.sourceLayer.getOutputAt(nodeIndex);
-        }
-        return layerOutputs;
-      }
-      //# sourceMappingURL=executor.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/container.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original source: keras/engine/topology.py */
-
-      /**
-       * A Container is a directed acyclic graph of layers.
-       *
-       * It is the topological form of a "model". A LayersModel
-       * is simply a Container with added training routines.
-       *
-       */
-      class container_Container extends topology_Layer {
-        constructor(args) {
-          // No args passed to super's constructor.
-          super({});
-          this.containerNodes = new Set();
-          this.name = args.name;
-          if (this.name == null) {
-            const prefix = this.getClassName().toLowerCase();
-            this.name = getUid(prefix);
-          }
-          this.supportsMasking = false;
-          this.trainable_ = true;
-          // TODO(michaelterry): Initialize perInputLosses/Updates here.
-          // Container-specific properties.
-          if (Array.isArray(args.inputs)) {
-            this.inputs = args.inputs.slice();
-          } else {
-            this.inputs = [args.inputs];
-          }
-          if (Array.isArray(args.outputs)) {
-            this.outputs = args.outputs.slice();
-          } else {
-            this.outputs = [args.outputs];
-          }
-          // Check for redundancy in inputs.
-          if (unique(this.inputs).length !== this.inputs.length) {
-            throw new ValueError(
-              "The list of inputs passed to the model is " +
-                "redundant. All inputs should only appear once. Found: " +
-                `${this.inputs.map((x) => x.name)}`
-            );
-          }
-          // Check for redundancy in outputs.
-          if (unique(this.outputs).length !== this.outputs.length) {
-            console.warn(
-              "The list of outputs passed to the model is redundant. " +
-                "All outputs should only appear once. Found: " +
-                `${this.outputs.map((x) => x.name)}`
-            );
-          }
-          /*
-          List of initial layers (1 to 1 mapping with this.inputs, hence the same
-          layer might appear twice)
-        */
-          this.inputLayers = [];
-          this.inputLayersNodeIndices = [];
-          this.inputLayersTensorIndices = [];
-          /*
-          List of layers (1 to 1 mapping with this.outputs, hence the same layer
-          might appear twice)
-        */
-          this.outputLayers = [];
-          this.outputLayersNodeIndices = [];
-          this.outputLayersTensorIndices = [];
-          /*
-          All layers in order of horizontal graph traversal. Entries are unique.
-          Includes input and output layers.
-        */
-          this.layers = [];
-          /*
-          References to container layers that were constructed internally. We need
-          these to properly dispose of tensors from nested containers.
-        */
-          this.internalContainerRefs = [];
-          // TODO(michaelterry): Determine if caching still needed with eager
-          // backend.
-          /*
-          This is for performance optimization when calling the Container on new
-          inputs. Every time the Container is called on a set on input tensors,
-          we compute the output tensors, output masks and output shapes in one pass,
-          then cache them here. When one of these outputs is queried later,
-          we retrieve it from there instead of recomputing it.
-        */
-          // this.outputTensorCache = {};
-          // this.outputShapeCache = {};
-          // Build this.outputLayers:
-          for (const x of this.outputs) {
-            const layer = x.sourceLayer;
-            const nodeIndex = x.nodeIndex;
-            const tensorIndex = x.tensorIndex;
-            this.outputLayers.push(layer);
-            this.outputLayersNodeIndices.push(nodeIndex);
-            this.outputLayersTensorIndices.push(tensorIndex);
-          }
-          // TODO(michaelterry): Add output mask cache code.
-          // Build this.inputLayers:
-          for (const x of this.inputs) {
-            const layer = x.sourceLayer;
-            const nodeIndex = x.nodeIndex;
-            const tensorIndex = x.tensorIndex;
-            /*
-              It's supposed to be an input layer, so only one node
-              and one tensor output.
-            */
-            assert(nodeIndex === 0, "input layer has >1 nodes");
-            assert(tensorIndex === 0, "input layer has >1 tensors");
-            this.inputLayers.push(layer);
-            this.inputLayersNodeIndices.push(nodeIndex);
-            this.inputLayersTensorIndices.push(tensorIndex);
-          }
-          // Build this.inputNames and this.outputNames.
-          this.inputNames = [];
-          this.outputNames = [];
-          this.feedInputShapes = [];
-          this.feedInputNames = [];
-          this.feedOutputNames = [];
-          for (let i = 0; i < this.inputLayers.length; i++) {
-            const layer = this.inputLayers[i];
-            // Check that layer is an InputLayer.
-            if (!(layer instanceof input_layer_InputLayer)) {
-              throw new TypeError(
-                "Input layers to a LayersModel must be InputLayer objects. " +
-                  `Received inputs: ${args.inputs}. ` +
-                  `Input ${i} (0-based) originates ` +
-                  `from layer type ${layer.getClassName()}.`
-              );
-            }
-            this.inputNames.push(layer.name);
-            this.feedInputShapes.push(layer.batchInputShape);
-            this.feedInputNames.push(layer.name);
-          }
-          for (const layer of this.outputLayers) {
-            this.outputNames.push(layer.name);
-          }
-          this.internalInputShapes = this.inputs.map((x) => x.shape);
-          this.internalOutputShapes = this.outputs.map((x) => x.shape);
-          /*
-          Container_nodes: set of nodes included in the graph (not all nodes
-          included in the layers are relevant to the current graph).
-        */
-          // ids of all nodes relevant to the Container:
-          const nodesDepths = {};
-          // To recover nodes from their ID.
-          const nodeIDToNode = {};
-          const layersDepths = {};
-          // To layers from their ID.
-          const layerIDToLayer = {};
-          const layerIndices = {};
-          const nodesInDecreasingDepth = [];
-          /**
-           * Builds a map of the graph of layers.
-           *
-           * This recursively updates the map `layerIndices`,
-           * the list `nodesInDecreasingDepth` and the set `containerNodes`.
-           *
-           * @param tensor Some tensor in a graph.
-           * @param finishedNodes Set of nodes whose subgraphs have been traversed
-           *         completely. Useful to prevent duplicated work.
-           * @param nodesInProgress Set of nodes that are currently active on the
-           *         recursion stack. Useful to detect cycles.
-           * @param layer Layer from which `tensor` comes from. If not provided,
-           *   will be obtained from tensor.sourceLayer.
-           * @param nodeIndex Node index from which `tensor` comes from.
-           * @param tensorIndex TensorIndex from which `tensor` comes from.
-           *
-           * @exception RuntimeError if a cycle is detected.
-           */
-          const buildMapOfGraph = (
-            tensor,
-            finishedNodes,
-            nodesInProgress,
-            layer,
-            nodeIndex,
-            tensorIndex
-          ) => {
-            if (layer == null || nodeIndex == null || tensorIndex == null) {
-              layer = tensor.sourceLayer;
-              nodeIndex = tensor.nodeIndex;
-              tensorIndex = tensor.tensorIndex;
-            }
-            const node = layer.inboundNodes[nodeIndex];
-            // Prevent cycles.
-            if (nodesInProgress.indexOf(node) !== -1) {
-              throw new RuntimeError(
-                `The tensor ${tensor.name} at layer "${layer.name}" ` + "is part of a cycle."
-              );
-            }
-            // Don't repeat work for shared subgraphs
-            if (finishedNodes.indexOf(node) !== -1) {
-              return;
-            }
-            // Update containerNodes.
-            this.containerNodes.add(container_Container.nodeKey(layer, nodeIndex));
-            // Store the traversal order for layer sorting.
-            if (!(layer.id in layerIndices)) {
-              layerIndices[layer.id] = Object.keys(layerIndices).length;
-            }
-            if (nodesInProgress.indexOf(node) === -1) {
-              nodesInProgress.push(node);
-            }
-            // Propagate to all previous tensors connected to this node.
-            const numInboundLayers = node.inboundLayers.length;
-            for (let i = 0; i < numInboundLayers; i++) {
-              const x = node.inputTensors[i];
-              const layer = node.inboundLayers[i];
-              const nodeIndex = node.nodeIndices[i];
-              const tensorIndex = node.tensorIndices[i];
-              buildMapOfGraph(x, finishedNodes, nodesInProgress, layer, nodeIndex, tensorIndex);
-            }
-            finishedNodes.push(node);
-            while (nodesInProgress.indexOf(node) >= 0) {
-              nodesInProgress.splice(nodesInProgress.indexOf(node), 1);
-            }
-            nodesInDecreasingDepth.push(node);
-          };
-          const finishedNodes = [];
-          const nodesInProgress = [];
-          for (const x of this.outputs) {
-            buildMapOfGraph(x, finishedNodes, nodesInProgress);
-          }
-          const reversedNodesInDecreasingDepth = nodesInDecreasingDepth.slice().reverse();
-          for (const node of reversedNodesInDecreasingDepth) {
-            nodeIDToNode[node.id] = node;
-            // If the depth is not set, the node has no outbound nodes (depth 0).
-            if (!(node.id in nodesDepths)) {
-              nodesDepths[node.id] = 0;
-            }
-            let depth = nodesDepths[node.id];
-            // Update the depth of the corresponding layer
-            const previousDepth =
-              layersDepths[node.outboundLayer.id] == null ? 0 : layersDepths[node.outboundLayer.id];
-            /*
-              If we've seen this layer before at a higher depth, we should use that
-              depth instead of the node depth.  This is necessary for shared layers
-              that have inputs at different depth levels in the graph.
-            */
-            depth = Math.max(depth, previousDepth);
-            layersDepths[node.outboundLayer.id] = depth;
-            layerIDToLayer[node.outboundLayer.id] = node.outboundLayer;
-            nodesDepths[node.id] = depth;
-            // Update the depth of inbound nodes.
-            for (let i = 0; i < node.inboundLayers.length; i++) {
-              const inboundLayer = node.inboundLayers[i];
-              const nodeIndex = node.nodeIndices[i];
-              const inboundNode = inboundLayer.inboundNodes[nodeIndex];
-              const previousDepth =
-                nodesDepths[inboundNode.id] == null ? 0 : nodesDepths[inboundNode.id];
-              nodesDepths[inboundNode.id] = Math.max(depth + 1, previousDepth);
-              nodeIDToNode[inboundNode.id] = inboundNode;
-            }
-          }
-          // Build a dict {depth: list of nodes with this depth}
-          const nodesByDepth = {};
-          for (const nodeID in nodesDepths) {
-            const depth = nodesDepths[nodeID];
-            if (!(depth in nodesByDepth)) {
-              nodesByDepth[depth] = [];
-            }
-            nodesByDepth[depth].push(nodeIDToNode[nodeID]);
-          }
-          // Build a dict {depth: list of layers with this depth}
-          const layersByDepth = {};
-          for (const layerID in layersDepths) {
-            const depth = layersDepths[layerID];
-            if (!(depth in layersByDepth)) {
-              layersByDepth[depth] = [];
-            }
-            layersByDepth[depth].push(layerIDToLayer[layerID]);
-          }
-          // Get sorted list of layer depths.
-          let depthKeys = Object.keys(layersByDepth)
-            .map((x) => parseInt(x, 10))
-            .sort(reverseNumberCompare);
-          // Set this.layers and this.layersByDepth.
-          this.layers = [];
-          for (const depth of depthKeys) {
-            const layersForDepth = layersByDepth[depth];
-            // Container.layers needs to have a deterministic order:
-            // here we order them by traversal order.
-            layersForDepth.sort((a, b) => {
-              const aIndex = layerIndices[a.id];
-              const bIndex = layerIndices[b.id];
-              if (aIndex < bIndex) {
-                return -1;
-              }
-              if (aIndex > bIndex) {
-                return 1;
-              }
-              return 0;
-            });
-            for (const layer of layersForDepth) {
-              if (layer instanceof container_Container) {
-                this.internalContainerRefs.push(layer);
-              }
-              this.layers.push(layer);
-            }
-          }
-          this.layersByDepth = layersByDepth;
-          // Get sorted list of node depths;
-          depthKeys = Object.keys(nodesByDepth)
-            .map((x) => parseInt(x, 10))
-            .sort(reverseNumberCompare);
-          // Check that all tensors required are computable.
-          // computable_tensors: all tensors in the graph
-          // that can be computed from the inputs provided.
-          const computableTensors = this.inputs.slice();
-          // To provide a better error msg.
-          const layersWithCompleteInput = [];
-          for (const depth of depthKeys) {
-            for (const node of nodesByDepth[depth]) {
-              const layer = node.outboundLayer;
-              if (layer != null) {
-                for (const x of node.inputTensors) {
-                  if (computableTensors.indexOf(x) === -1) {
-                    throw new RuntimeError(
-                      `Graph disconnected: cannot obtain value for tensor ${x}` +
-                        ` at layer "${layer.name}". ` +
-                        "The following previous layers were accessed without " +
-                        `issue: ${layersWithCompleteInput}`
-                    );
-                  }
-                }
-                for (const x of node.outputTensors) {
-                  computableTensors.push(x);
-                }
-                layersWithCompleteInput.push(layer.name);
-              }
-            }
-          }
-          // Set this.containerNodes and this.nodesByDepth.
-          this.nodesByDepth = nodesByDepth;
-          // Ensure name unicity, which will be crucial for serialization
-          // (since serialized nodes refer to layers by their name).
-          const allNames = this.layers.map((x) => x.name);
-          for (const name of allNames) {
-            const numOccurrences = allNames.filter((x) => x === name).length;
-            if (numOccurrences !== 1) {
-              throw new RuntimeError(
-                `The name "${name}" is used ${numOccurrences} times ` +
-                  "in the model. All layer names should be unique. Layer names: " +
-                  JSON.stringify(allNames)
-              );
-            }
-          }
-          // Layer parameters.
-          // The new container starts with a single inbound node
-          // for its inputs, and no outbound nodes.
-          // Will be appended to by future calls to apply().
-          this.outboundNodes = [];
-          // Will be appended to below, and by future calls to apply().
-          this.inboundNodes = [];
-          // Create the node linking internal inputs to internal outputs.
-          // (This call has side effects.)
-          // tslint:disable-next-line:no-unused-expression
-          new Node({
-            outboundLayer: this,
-            inboundLayers: [],
-            nodeIndices: [],
-            tensorIndices: [],
-            inputTensors: this.inputs,
-            outputTensors: this.outputs,
-            inputMasks: this.inputs.map((x) => null),
-            outputMasks: this.outputs.map((x) => null),
-            inputShapes: this.inputs.map((x) => x.shape),
-            outputShapes: this.outputs.map((x) => x.shape),
-          });
-          this.built = true;
-          this._refCount = 1; // The ref count of a container always start at 1.
-        }
-        assertNotDisposed() {
-          if (this._refCount === 0) {
-            throw new Error(`Container '${this.name}' is already disposed.`);
-          }
-        }
-        /**
-         * Attempt to dispose a LayersModel's weights.
-         *
-         * This method decrease the reference count of the LayersModel object by 1.
-         *
-         * A LayersModel is reference-counted. Its reference count is incremented by 1
-         * when it is first constructed and when it is used as a Layer of another
-         * LayersModel.
-         *
-         * If the reference count of a LayersModel becomes 0, the `dispose` method of
-         * all its constituent `Layer`s will be called.
-         *
-         * Note: If the reference count is greater than 0 after the decrement, the
-         * `dispose` method of its constituent `Layer`s will *not* be called.
-         *
-         * After a LayersModel is disposed, it cannot be used in calls such as
-         * 'predict`, `evaluate` or `fit` anymore.
-         *
-         * @returns A DisposeResult Object with the following fields:
-         *   - refCountAfterDispose: The reference count of the LayersModel after this
-         *     `dispose()` call.
-         *   - numDisposedVariables: Number of `tf.Variable`s (i.e., weights) disposed
-         *     during this `dispose()` call.
-         * @throws {Error} If the layer is not built yet, or if the LayersModel has
-         *   already been disposed.
-         */
-        dispose() {
-          this.assertNotDisposed();
-          const result = { refCountAfterDispose: null, numDisposedVariables: 0 };
-          if (--this._refCount === 0) {
-            for (const layer of this.layers) {
-              result.numDisposedVariables += layer.dispose().numDisposedVariables;
-            }
-            // Call dispose on each internally created container layer again to ensure
-            // their refCounts hit zero and their tensors are subsequently deleted.
-            for (const container of this.internalContainerRefs) {
-              result.numDisposedVariables += container.dispose().numDisposedVariables;
-            }
-          }
-          result.refCountAfterDispose = this._refCount;
-          return result;
-        }
-        get trainable() {
-          return this.trainable_;
-        }
-        set trainable(trainable) {
-          this.layers.forEach((layer) => {
-            // tslint:disable-next-line:no-any
-            layer._trainableWeights.forEach((w) => (w.trainable = trainable));
-          });
-          this.trainable_ = trainable;
-        }
-        get trainableWeights() {
-          // Porting Note: This check below is to prevent errors where the
-          //   _trainableWeights inherited from the parent class (Layer) gets
-          //   inadvertently used.
-          if (this._trainableWeights.length > 0) {
-            throw new ValueError(
-              "Container instance unexpectedly contains _trainableWeights." +
-                "The trainable weights of a Container are a union of the " +
-                "trainable weights of its consituent Layers. Its own " +
-                "_trainableWeights must remain an empty Array."
-            );
-          }
-          if (!this.trainable) {
-            return [];
-          }
-          let weights = [];
-          for (const layer of this.layers) {
-            weights = weights.concat(layer.trainableWeights);
-          }
-          return weights;
-        }
-        get nonTrainableWeights() {
-          const weights = [];
-          for (const layer of this.layers) {
-            weights.push(...layer.nonTrainableWeights);
-          }
-          if (!this.trainable) {
-            const trainableWeights = [];
-            for (const layer of this.layers) {
-              trainableWeights.push(...layer.trainableWeights);
-            }
-            return trainableWeights.concat(weights);
-          }
-          return weights;
-        }
-        get weights() {
-          return this.trainableWeights.concat(this.nonTrainableWeights);
-        }
-        /**
-         * Loads all layer weights from a JSON object.
-         *
-         * Porting Note: HDF5 weight files cannot be directly loaded in JavaScript /
-         *   TypeScript. The utility script at `scripts/pykeras.py` offers means
-         *   to convert them into JSON strings compatible with this method.
-         * Porting Note: TensorFlow.js Layers supports only loading by name currently.
-         *
-         * @param weights A JSON mapping weight names to weight values as nested
-         *   arrays of numbers, or a `NamedTensorMap`, i.e., a JSON mapping weight
-         *   names to `tf.Tensor` objects.
-         * @param strict Require that the provided weights exactly match those
-         *   required by the container.  Default: `true`.  Passing `false` means that
-         *   extra weights and missing weights will be silently ignored.
-         */
-        loadWeights(weights, strict = true) {
-          const nameToWeight = {};
-          let totalWeightsCount = 0;
-          for (const layer of this.layers) {
-            for (const weight of layer.weights) {
-              if (nameToWeight[weight.originalName] != null) {
-                throw new ValueError(`Duplicate weight name: ${weight.originalName}`);
-              }
-              nameToWeight[weight.originalName] = weight;
-              totalWeightsCount++;
-            }
-          }
-          const weightValueTuples = [];
-          for (const name in weights) {
-            // TF 2.2.0 added cell name to the weight name in the format of
-            // layer_name/cell_name/weight_name, we need to remove
-            // the inner cell name.
-            let validatedName = name;
-            if (nameToWeight[name] == null) {
-              const tokens = name.split("/");
-              const shortenNameArray = tokens.slice(0, -2).concat([tokens[tokens.length - 1]]);
-              validatedName = shortenNameArray.join("/");
-            }
-            if (nameToWeight[validatedName] != null) {
-              weightValueTuples.push([nameToWeight[validatedName], weights[name]]);
-            } else if (strict) {
-              throw new ValueError(`Provided weight data has no target variable: ${name}`);
-            }
-            delete nameToWeight[validatedName];
-          }
-          if (strict) {
-            // Check that all weights are set.
-            const unsetNames = [];
-            for (const name in nameToWeight) {
-              unsetNames.push(name);
-            }
-            if (unsetNames.length > 0) {
-              throw new ValueError(
-                `${unsetNames.length} of ${totalWeightsCount} weights are not set: ` +
-                  `${unsetNames}`
-              );
-            }
-          }
-          batchSetValue(weightValueTuples);
-        }
-        /**
-         * Util shared between different serialization methods.
-         * @returns LayersModel config with Keras version information added.
-         */
-        updatedConfig() {
-          const theConfig = this.getConfig();
-          const modelConfig = {};
-          modelConfig["className"] = this.getClassName();
-          modelConfig["config"] = theConfig;
-          modelConfig["kerasVersion"] = `tfjs-layers ${version}`;
-          // TODO(nielsene): Replace something like K.backend() once
-          // possible.
-          modelConfig["backend"] = "TensorFlow.js";
-          return modelConfig;
-        }
-        /**
-         * Returns a JSON string containing the network configuration.
-         *
-         * To load a network from a JSON save file, use
-         * models.modelFromJSON(jsonString);
-         * @param extraJsonArgs Unused in tfjs-layers, maintained for PyKeras
-         * @param returnString Whether the return value should be stringified
-         *    (default: `true`).
-         * @returns a JSON string if `returnString` (default), or a JSON object if
-         *   `!returnString`.
-         */
-        // tslint:disable-next-line:no-any
-        toJSON(unused, returnString = true) {
-          const modelConfig = convertTsToPythonic(this.updatedConfig());
-          return returnString ? JSON.stringify(modelConfig) : modelConfig;
-        }
-        /**
-         * Call the model on new inputs.
-         *
-         * In this case `call` just reapplies all ops in the graph to the new inputs
-         * (e.g. build a new computational graph from the provided inputs).
-         *
-         * @param inputs A tensor or list of tensors.
-         * @param mask A mask or list of masks. A mask can be either a tensor or null
-         *   (no mask).
-         *
-         * @return A tensor if there is a single output, or a list of tensors if there
-         *   are more than one outputs.
-         */
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = toList(inputs);
-            const feedDict = new executor_FeedDict();
-            for (let i = 0; i < this.inputs.length; ++i) {
-              feedDict.add(this.inputs[i], inputs[i]);
-            }
-            return execute(this.outputs, feedDict, kwargs);
-          });
-        }
-        /**
-         * Computes an output mask tensor.
-         *
-         * @param inputs Tensor or list of tensors.
-         * @param mask Tensor or list of tensors.
-         *
-         * @return null or a tensor (or list of tensors, one per output tensor of the
-         * layer).
-         */
-        computeMask(inputs, mask) {
-          return Object(dist["tidy"])(() => {
-            inputs = toList(inputs);
-            let masks;
-            if (mask == null) {
-              masks = pyListRepeat(null, inputs.length);
-            } else {
-              masks = toList(mask);
-            }
-            // TODO(michaelterry): Add support for mask caching.
-            return this.runInternalGraph(inputs, masks)[1];
-          });
-        }
-        /**
-         * Computes the output shape of the layer.
-         *
-         * Assumes that the layer will be built to match that input shape provided.
-         *
-         * @param inputShape A shape (tuple of integers) or a list of shape tuples
-         *   (one per output tensor of the layer). Shape tuples can include null for
-         *   free dimensions, instead of an integer.
-         */
-        computeOutputShape(inputShape) {
-          const inputShapes = normalizeShapeList(inputShape);
-          if (inputShapes.length !== this.inputLayers.length) {
-            throw new ValueError(
-              `Invalid inputShape argument ${inputShape}: ` +
-                `model has ${this.inputLayers.length} tensor inputs.`
-            );
-          }
-          // TODO(michaelterry): Add caching
-          const layersToOutputShapes = {};
-          for (let i = 0; i < inputShapes.length; i++) {
-            const layer = this.inputLayers[i];
-            const inputShape = inputShapes[i];
-            // It's an input layer: computeOutputShape is identity,
-            // and there is only one node and one tensor output.
-            const shapeKey = layer.name + "_0_0";
-            layersToOutputShapes[shapeKey] = inputShape;
-          }
-          const depthKeys = Object.keys(this.nodesByDepth)
-            .map((x) => parseInt(x, 10))
-            .sort(reverseNumberCompare);
-          // Iterate over nodes, by depth level.
-          if (depthKeys.length > 1) {
-            for (const depth of depthKeys) {
-              const nodes = this.nodesByDepth[depth];
-              for (const node of nodes) {
-                // This is always a single layer, never a list.
-                const layer = node.outboundLayer;
-                if (this.inputLayers.map((x) => x.id).indexOf(layer.id) !== -1) {
-                  // We've already covered the input layers a few lines above.
-                  continue;
-                }
-                // Potentially redundant list, same size of node.inputTensors.
-                const inputShapes = [];
-                for (let j = 0; j < node.inboundLayers.length; j++) {
-                  const inboundLayer = node.inboundLayers[j];
-                  const nodeIndex = node.nodeIndices[j];
-                  const tensorIndex = node.tensorIndices[j];
-                  const shapeKey = `${inboundLayer.name}_${nodeIndex}_${tensorIndex}`;
-                  const inputShape = layersToOutputShapes[shapeKey];
-                  inputShapes.push(inputShape);
-                }
-                const outputShape = layer.computeOutputShape(singletonOrArray(inputShapes));
-                const outputShapes = normalizeShapeList(outputShape);
-                const nodeIndex = layer.inboundNodes.indexOf(node);
-                for (let j = 0; j < outputShapes.length; j++) {
-                  const shapeKey = `${layer.name}_${nodeIndex}_${j}`;
-                  layersToOutputShapes[shapeKey] = outputShapes[j];
-                }
-              }
-            }
-          }
-          // Read final output shapes from layersToOutputShapes.
-          const outputShapes = [];
-          const outputShapeKeys = [];
-          for (let i = 0; i < this.outputLayers.length; i++) {
-            const layer = this.outputLayers[i];
-            const nodeIndex = this.outputLayersNodeIndices[i];
-            const tensorIndex = this.outputLayersTensorIndices[i];
-            const shapeKey = `${layer.name}_${nodeIndex}_${tensorIndex}`;
-            outputShapeKeys.push(shapeKey);
-          }
-          for (let i = 0; i < outputShapeKeys.length; i++) {
-            const key = outputShapeKeys[i];
-            assert(key in layersToOutputShapes);
-            outputShapes.push(layersToOutputShapes[key]);
-          }
-          // TODO(michaelterry): Update cache
-          return singletonOrArray(outputShapes);
-        }
-        /**
-         * Computes output tensors for new inputs.
-         *
-         * Note:
-         *   - Expects `inputs` to be a list (potentially with 1 element).
-         *
-         * @param inputs List of tensors
-         * @param masks List of masks (tensors or null).
-         * @return Three lists: outputTensors, outputMasks, outputShapes
-         */
-        runInternalGraph(inputs, masks) {
-          if (masks == null) {
-            masks = pyListRepeat(null, inputs.length);
-          }
-          // Dictionary mapping reference tensors to tuples
-          // (computed tensor, compute mask)
-          // we assume a 1:1 mapping from tensor to mask
-          // TODO: raise exception when a `.computeMask()` call
-          // does not return a list the same size as `call`
-          const tensorMap = {};
-          for (let i = 0; i < this.inputs.length; ++i) {
-            const x = this.inputs[i];
-            const y = inputs[i];
-            const mask = masks[i];
-            tensorMap[x.id] = [y, mask];
-          }
-          const depthKeys = Object.keys(this.nodesByDepth)
-            .map((x) => parseInt(x, 10))
-            .sort(reverseNumberCompare);
-          for (const depth of depthKeys) {
-            const nodes = this.nodesByDepth[depth];
-            for (const node of nodes) {
-              // This is always a single layer, never a list.
-              const layer = node.outboundLayer;
-              const referenceInputTensors = node.inputTensors;
-              const referenceOutputTensors = node.outputTensors;
-              // If all previous input tensors are available in tensorMap,
-              // then call node.inboundLayer on them.
-              // List of tuples [input, mask]:
-              const computedData = new Array();
-              for (const x of referenceInputTensors) {
-                if (x.id in tensorMap) {
-                  computedData.push(tensorMap[x.id]);
-                }
-              }
-              if (computedData.length === referenceInputTensors.length) {
-                // TODO(michaelterry): Add K.name_scope here, if we need it.
-                let kwargs = {};
-                let computedTensors;
-                let computedMasks;
-                let outputTensors;
-                let outputMasks;
-                // call layer
-                if (node.callArgs != null) {
-                  kwargs = node.callArgs;
-                }
-                if (computedData.length === 1) {
-                  const [computedTensor, computedMask] = computedData[0];
-                  if (kwargs["mask"] == null) {
-                    kwargs["mask"] = computedMask;
-                  }
-                  outputTensors = toList(layer.call(computedTensor, kwargs));
-                  outputMasks = toList(layer.computeMask(computedTensor, computedMask));
-                  computedTensors = [computedTensor];
-                  computedMasks = [computedMask];
-                } else {
-                  computedTensors = computedData.map((x) => x[0]);
-                  computedMasks = computedData.map((x) => x[1]);
-                  if (kwargs["mask"] == null) {
-                    kwargs["mask"] = computedMasks;
-                  }
-                  outputTensors = toList(layer.call(computedTensors, kwargs));
-                  outputMasks = toList(layer.computeMask(computedTensors, computedMasks));
-                }
-                if (layer.activityRegularizer) {
-                  throw new NotImplementedError(
-                    "LayersModel invocation with concrete Tensor value(s) in the " +
-                      "presence of activity regularizer(s) is not supported yet."
-                  );
-                }
-                // TODO(michaelterry): Add model updates and losses
-                // Update tensor map.
-                for (let i = 0; i < referenceOutputTensors.length; ++i) {
-                  const x = referenceOutputTensors[i];
-                  const y = outputTensors[i];
-                  const mask = outputMasks[i];
-                  tensorMap[x.id] = [y, mask];
-                }
-              }
-            }
-          }
-          const outputTensors = [];
-          const outputMasks = [];
-          const outputShapes = [];
-          for (const x of this.outputs) {
-            assert(x.id in tensorMap, `Could not compute output ${x.name} : ${x.id}`);
-            const [tensor, mask] = tensorMap[x.id];
-            outputShapes.push(tensor.shape);
-            outputTensors.push(tensor);
-            outputMasks.push(mask);
-          }
-          // TODO(michaelterry): Add support for caches.
-          return [outputTensors, outputMasks, outputShapes];
-        }
-        /**
-         * Builds a map of internal node keys to node ordering.
-         * Used in serializaion a node orderings may change as unused nodes are
-         * dropped. Porting Note:  This helper method was pulled out of getConfig to
-         * improve readability.
-         * @param layers An array of Layers in the model.
-         * @returns Map of Node Keys to index order within the layer.
-         */
-        buildNodeConversionMap(layers) {
-          const nodeConversionMap = {};
-          let keptNodes;
-          for (const layer of this.layers) {
-            keptNodes = layer instanceof container_Container ? 1 : 0;
-            for (
-              let originalNodeIndex = 0;
-              originalNodeIndex < layer.inboundNodes.length;
-              originalNodeIndex++
-            ) {
-              const nodeKey = container_Container.nodeKey(layer, originalNodeIndex);
-              if (this.containerNodes.has(nodeKey)) {
-                // i.e. we mark it to be saved
-                nodeConversionMap[nodeKey] = keptNodes;
-                keptNodes += 1;
-              }
-            }
-          }
-          return nodeConversionMap;
-        }
-        /**
-         * Retrieves a layer based on either its name (unique) or index.
-         *
-         * Indices are based on order of horizontal graph traversal (bottom-up).
-         *
-         * If both `name` and `index` are specified, `index` takes precedence.
-         *
-         * @param name Name of layer.
-         * @param index Index of layer.
-         * @returns A Layer instance.
-         * @throws ValueError: In case of invalid layer name or index.
-         */
-        /**
-         * @doc {
-         *    heading: 'Layers',
-         *    subheading: 'Classes',
-         *    namespace: 'layers',
-         *    subclasses: ['LayersModel']
-         * }
-         */
-        getLayer(name, index) {
-          if (index != null) {
-            if (this.layers.length <= index) {
-              throw new ValueError(
-                `Was asked to retrieve layer at index ${index}, but model only ` +
-                  `has ${this.layers.length} layer(s).`
-              );
-            } else {
-              return this.layers[index];
-            }
-          } else {
-            if (name == null) {
-              throw new ValueError("Provide either a layer name or layer index");
-            }
-          }
-          for (const layer of this.layers) {
-            if (layer.name === name) {
-              return layer;
-            }
-          }
-          throw new ValueError(`No such layer: ${name}`);
-        }
-        /**
-         * Retrieves the Container's current loss values.
-         *
-         * Used for regularizers during training.
-         */
-        calculateLosses() {
-          // Porting Node: This is an augmentation to Container.loss in PyKeras.
-          //   In PyKeras, Container.loss returns symbolic tensors. Here a concrete
-          //   Tensor (specifically Scalar) values are returned. This is due to the
-          //   imperative backend.
-          return Object(dist["tidy"])(() => {
-            const losses = [];
-            for (const layer of this.layers) {
-              for (let nodeIndex = 0; nodeIndex < layer.inboundNodes.length; ++nodeIndex) {
-                const nodeKey = container_Container.nodeKey(layer, nodeIndex);
-                if (this.containerNodes.has(nodeKey)) {
-                  losses.push(...layer.calculateLosses());
-                }
-              }
-            }
-            // TODO(cais): Add any unconditional model-level losses?
-            return losses;
-          });
-        }
-        getConfig() {
-          const config = { name: this.name };
-          // Build a map from layer unique name (self._node_key)
-          // to the index of the nodes that are saved in the config.
-          // Only nodes in container_nodes are saved.
-          const nodeConversionMap = this.buildNodeConversionMap(this.layers);
-          // Serialize and save the layers in layerConfigs
-          const layerConfigs = [];
-          for (const layer of this.layers) {
-            const layerClassName = layer.getClassName();
-            const layerConfig = layer.getConfig();
-            const filteredInboundNodes = [];
-            for (
-              let originalNodeIndex = 0;
-              originalNodeIndex < layer.inboundNodes.length;
-              originalNodeIndex++
-            ) {
-              const node = layer.inboundNodes[originalNodeIndex];
-              const nodeKey = container_Container.nodeKey(layer, originalNodeIndex);
-              let kwargs = {};
-              if (this.containerNodes.has(nodeKey)) {
-                // The node is relevant to the model:
-                // add to filteredInboundNodes.
-                if (node.callArgs) {
-                  try {
-                    JSON.stringify(node.callArgs);
-                    kwargs = node.callArgs;
-                  } catch (err) {
-                    console.warn(
-                      `Layer ${layer.name} was passed ` +
-                        `non-serializable keyword arguments: ` +
-                        `${node.callArgs}. They will not be included ` +
-                        `in the serialized model (and thus will be ` +
-                        `missing at deserialization time).`
-                    );
-                    kwargs = {};
-                  }
-                }
-                if (node.inboundLayers.length > 0) {
-                  const nodeData = [];
-                  for (let i = 0; i < node.inboundLayers.length; i++) {
-                    const inboundLayer = node.inboundLayers[i];
-                    const nodeIndex = node.nodeIndices[i];
-                    const tensorIndex = node.tensorIndices[i];
-                    const nodeKey = container_Container.nodeKey(inboundLayer, nodeIndex);
-                    let newNodeIndex = nodeConversionMap[nodeKey];
-                    if (newNodeIndex == null) {
-                      newNodeIndex = 0;
-                    }
-                    nodeData.push([inboundLayer.name, newNodeIndex, tensorIndex, kwargs]);
-                  }
-                  filteredInboundNodes.push(nodeData);
-                }
-              }
-            }
-            const dict = {};
-            dict["name"] = layer.name;
-            dict["className"] = layerClassName;
-            dict["config"] = layerConfig;
-            dict["inboundNodes"] = filteredInboundNodes;
-            layerConfigs.push(dict);
-          }
-          config["layers"] = layerConfigs;
-          // Gather info about inputs and outputs
-          const modelInputs = [];
-          for (let i = 0; i < this.inputLayers.length; i++) {
-            const layer = this.inputLayers[i];
-            const nodeIndex = this.inputLayersNodeIndices[i];
-            const nodeKey = container_Container.nodeKey(layer, nodeIndex);
-            if (!this.containerNodes.has(nodeKey)) {
-              continue;
-            }
-            let newNodeIndex = nodeConversionMap[nodeKey];
-            if (newNodeIndex === null || newNodeIndex === undefined) {
-              newNodeIndex = 0;
-            }
-            const tensorIndex = this.inputLayersTensorIndices[i];
-            modelInputs.push([layer.name, newNodeIndex, tensorIndex]);
-          }
-          config["inputLayers"] = modelInputs;
-          const modelOutputs = [];
-          for (let i = 0; i < this.outputLayers.length; i++) {
-            const layer = this.outputLayers[i];
-            const nodeIndex = this.outputLayersNodeIndices[i];
-            const nodeKey = container_Container.nodeKey(layer, nodeIndex);
-            if (!this.containerNodes.has(nodeKey)) {
-              continue;
-            }
-            let newNodeIndex = nodeConversionMap[nodeKey];
-            if (newNodeIndex === null || newNodeIndex === undefined) {
-              newNodeIndex = 0;
-            }
-            const tensorIndex = this.outputLayersTensorIndices[i];
-            modelOutputs.push([layer.name, newNodeIndex, tensorIndex]);
-          }
-          config["outputLayers"] = modelOutputs;
-          return config;
-        }
-        /**
-         * Instantiates a LayersModel from its config (output of `get_config()`).
-         * @param cls the class to create
-         * @param config LayersModel config dictionary.
-         * @param customObjects An optional dictionary of custom objects.
-         * @param fastWeightInit Optional flag to use fast weight initialization
-         *   during deserialization. This is applicable to cases in which
-         *   the initialization will be immediately overwritten by loaded weight
-         *   values. Default: `false`.
-         * @returns A LayersModel instance.
-         * @throws ValueError: In case of improperly formatted config dict.
-         */
-        /** @nocollapse */
-        static fromConfig(cls, config, customObjects = {}, fastWeightInit = false) {
-          // Layer instances created during
-          // the graph reconstruction process
-          const createdLayers = {};
-          // Dictionary mapping layer instances to
-          // node data that specifies a layer call.
-          // It acts as a queue that maintains any unprocessed
-          // layer call until it becomes possible to process it
-          // (i.e. until the input tensors to the call all exist).
-          const unprocessedNodes = {};
-          function addUnprocessedNode(layer, nodeData) {
-            if (!(layer.name in unprocessedNodes)) {
-              unprocessedNodes[layer.name] = [nodeData];
-            } else {
-              unprocessedNodes[layer.name].push(nodeData);
-            }
-          }
-          function processNode(layer, nodeData) {
-            const inputTensors = [];
-            let kwargs;
-            for (const inputData of nodeData) {
-              const inboundLayerName = inputData[0];
-              const inboundNodeIndex = inputData[1];
-              const inboundTensorIndex = inputData[2];
-              kwargs = inputData[3] == null ? {} : inputData[3];
-              if (!(inboundLayerName in createdLayers)) {
-                addUnprocessedNode(layer, nodeData);
-                return;
-              }
-              const inboundLayer = createdLayers[inboundLayerName];
-              if (inboundLayer.inboundNodes.length <= inboundNodeIndex) {
-                addUnprocessedNode(layer, nodeData);
-                return;
-              }
-              const inboundNode = inboundLayer.inboundNodes[inboundNodeIndex];
-              inputTensors.push(inboundNode.outputTensors[inboundTensorIndex]);
-            }
-            // Call layer on its inputs, thus creating the node
-            // and building the layer if needed.
-            // Note: This has Eager vs Graph Implications.
-            if (inputTensors.length > 0) {
-              layer.apply(singletonOrArray(inputTensors), kwargs); // was ** kwargs
-            }
-          }
-          /**
-           * Deserialize a layer, then call it on appropriate inputs.
-           * @param layerData: layer config dict.
-           * @throws ValueError: In case of improperly formatted `layer_data`
-           * dict.
-           */
-          function processLayer(layerData) {
-            const layerName = layerData["name"];
-            // Instantiate layer.
-            const layer = deserialize(
-              layerData,
-              config["customObjects"] != null ? config["customObjects"] : {}
-            );
-            layer.setFastWeightInitDuringBuild(fastWeightInit);
-            createdLayers[layerName] = layer;
-            // Gather layer inputs.
-            const inboundNodesData = layerData["inboundNodes"];
-            inboundNodesData.forEach((nodeData) => {
-              if (!(nodeData instanceof Array)) {
-                throw new ValueError(
-                  `Corrupted configuration, expected array for nodeData: ${nodeData}`
-                );
-              }
-              // We don't process nodes (i.e. make layer calls)
-              // on the fly because the inbound node may not yet exist,
-              // in case of layer shared at different topological depths
-              // (e.g.a model such as A(B(A(B(x)))))
-              addUnprocessedNode(layer, nodeData);
-            });
-          }
-          // First, we create all layers and enqueue nodes to be processed.
-          const name = config["name"];
-          const layersFromConfig = config["layers"];
-          for (const layerData of layersFromConfig) {
-            processLayer(layerData);
-          }
-          // Then we process nodes in order of layer depth.
-          // Nodes that cannot yet be processed(if the inbound node
-          // does not yet exist) are re - enqueued, and the process
-          // is repeated until all nodes are processed.
-          while (!isObjectEmpty(unprocessedNodes)) {
-            for (const layerData of layersFromConfig) {
-              const layer = createdLayers[layerData["name"]];
-              if (layer.name in unprocessedNodes) {
-                const currentUnprocessedNodesForLayer = unprocessedNodes[layer.name];
-                delete unprocessedNodes[layer.name];
-                for (const nodeData of currentUnprocessedNodesForLayer) {
-                  processNode(layer, nodeData);
-                }
-              }
-            }
-          }
-          const inputTensors = [];
-          const outputTensors = [];
-          const inputLayersFromConfig = config["inputLayers"];
-          for (const layerData of inputLayersFromConfig) {
-            const layerName = layerData[0];
-            const nodeIndex = layerData[1];
-            const tensorIndex = layerData[2];
-            assert(layerName in createdLayers);
-            const layer = createdLayers[layerName];
-            const layerOutputTensors = layer.inboundNodes[nodeIndex].outputTensors;
-            inputTensors.push(layerOutputTensors[tensorIndex]);
-          }
-          const outputLayersFromConfig = config["outputLayers"];
-          for (const layerData of outputLayersFromConfig) {
-            const layerName = layerData[0];
-            const nodeIndex = layerData[1];
-            const tensorIndex = layerData[2];
-            assert(layerName in createdLayers);
-            const layer = createdLayers[layerName];
-            const layerOutputTensors = layer.inboundNodes[nodeIndex].outputTensors;
-            outputTensors.push(layerOutputTensors[tensorIndex]);
-          }
-          return new cls({ inputs: inputTensors, outputs: outputTensors, name });
-        }
-        /**
-         * Determine whether the container is stateful.
-         *
-         * Porting Note: this is the equivalent of the stateful @property of
-         *   the Container class in PyKeras.
-         */
-        get stateful() {
-          // Porting Note: This check is to prevent inadvertent setting of the
-          //   _stateful property of the Container instance.
-          if (this._stateful) {
-            throw new ValueError(
-              "Container instance unexpectedly has _stateful = true. The " +
-                "statefulness of a Container is determined by the Layers it " +
-                "contains. Its _stateful property must remain the default false."
-            );
-          }
-          for (const layer of this.layers) {
-            if (layer.stateful) {
-              return true;
-            }
-          }
-          return false;
-        }
-        /**
-         * Reset the state of all stateful constituent layers (if any).
-         *
-         * Examples of stateful layers include RNN layers whose `stateful` property
-         * is set as `true`.
-         */
-        resetStates() {
-          Object(dist["tidy"])(() => {
-            this.layers.forEach((layer) => {
-              // tslint:disable:no-any
-              if (layer.stateful) {
-                layer.resetStates();
-              }
-              // tslint:enable:no-any
-            });
-          });
-        }
-      }
-      //# sourceMappingURL=container.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/training_utils.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      function standardizeSampleOrClassWeights(xWeight, outputNames, weightType) {
-        const numOutputs = outputNames.length;
-        if (xWeight == null || (Array.isArray(xWeight) && xWeight.length === 0)) {
-          return outputNames.map((name) => null);
-        }
-        if (numOutputs === 1) {
-          if (Array.isArray(xWeight) && xWeight.length === 1) {
-            return xWeight;
-          } else if (typeof xWeight === "object" && outputNames[0] in xWeight) {
-            return [xWeight[outputNames[0]]];
-          } else {
-            return [xWeight];
-          }
-        }
-        if (Array.isArray(xWeight)) {
-          if (xWeight.length !== numOutputs) {
-            throw new Error(
-              `Provided ${weightType} is an array of ${xWeight.length} ` +
-                `element(s), but the model has ${numOutputs} outputs. ` +
-                `Make sure a set of weights is provided for each model output.`
-            );
-          }
-          return xWeight;
-        } else if (
-          typeof xWeight === "object" &&
-          Object.keys(xWeight).length > 0 &&
-          typeof xWeight[Object.keys(xWeight)[0]] === "object"
-        ) {
-          const output = [];
-          outputNames.forEach((outputName) => {
-            if (outputName in xWeight) {
-              output.push(xWeight[outputName]);
-            } else {
-              output.push(null);
-            }
-          });
-          return output;
-        } else {
-          throw new Error(
-            `The model has multiple (${numOutputs}) outputs, ` +
-              `so ${weightType} must be either an array with ` +
-              `${numOutputs} elements or an object with ${outputNames} keys. ` +
-              `Provided ${weightType} not understood: ${JSON.stringify(xWeight)}`
-          );
-        }
-      }
-      /**
-       * Standardize class weighting objects.
-       *
-       * This function takes a single class-weighting object, an array of them,
-       * or a map from output name to class-weighting object. It compares it to the
-       * output name(s) of the model, base on which it outputs an array of
-       * class-weighting objects of which the length matches the number of outputs.
-       *
-       * @param classWeight Input class-weighting object(s).
-       * @param outputNames All output name(s) of the model.
-       * @return An array of class-weighting objects. The length of the array matches
-       *   the model's number of outputs.
-       */
-      function standardizeClassWeights(classWeight, outputNames) {
-        return standardizeSampleOrClassWeights(classWeight, outputNames, "classWeight");
-      }
-      function standardizeSampleWeights(classWeight, outputNames) {
-        return standardizeSampleOrClassWeights(classWeight, outputNames, "sampleWeight");
-      }
-      /**
-       * Standardize by-sample and/or by-class weights for training.
-       *
-       * Note that this function operates on one model output at a time. For a model
-       * with multiple outputs, you must call this function multiple times.
-       *
-       * @param y The target tensor that the by-sample and/or by-class weight is for.
-       *     The values of y are assumed to encode the classes, either directly
-       *     as an integer index, or as one-hot encoding.
-       * @param sampleWeight By-sample weights.
-       * @param classWeight By-class weights: an object mapping class indices
-       *     (integers) to a weight (float) to apply to the model's loss for the
-       *     samples from this class during training. This can be useful to tell the
-       *     model to "pay more attention" to samples from an under-represented class.
-       * @param sampleWeightMode The mode for the sample weights.
-       * @return A Promise of weight tensor, of which the size of the first dimension
-       *     matches that of `y`.
-       */
-      async function standardizeWeights(y, sampleWeight, classWeight, sampleWeightMode) {
-        if (sampleWeight != null || sampleWeightMode != null) {
-          // TODO(cais): Once 'temporal' mode is implemented, document it in the doc
-          // string.
-          throw new Error("Support sampleWeight is not implemented yet");
-        }
-        if (classWeight != null) {
-          // Apply class weights per sample.
-          const yClasses = Object(dist["tidy"])(() => {
-            if (y.shape.length === 1) {
-              // Assume class indices.
-              return y.clone();
-            } else if (y.shape.length === 2) {
-              if (y.shape[1] > 1) {
-                // Assume one-hot encoding of classes.
-                const axis = 1;
-                return y.argMax(axis);
-              } else if (y.shape[1] === 1) {
-                // Class index.
-                return y.reshape([y.shape[0]]);
-              } else {
-                throw new Error(
-                  `Encountered unexpected last-dimension size (${y.shape[1]}) ` +
-                    `during handling of class weights. The size is expected to be ` +
-                    `>= 1.`
-                );
-              }
-            } else {
-              throw new Error(
-                `Unexpected rank of target (y) tensor (${y.rank}) during ` +
-                  `handling of class weights. The rank is expected to be 1 or 2.`
-              );
-            }
-          });
-          const yClassIndices = Array.from(await yClasses.data());
-          Object(dist["dispose"])(yClasses);
-          const classSampleWeight = [];
-          yClassIndices.forEach((classIndex) => {
-            if (classWeight[classIndex] == null) {
-              throw new Error(
-                `classWeight must contain all classes in the training data. ` +
-                  `The class ${classIndex} exists in the data but not in ` +
-                  `classWeight`
-              );
-            } else {
-              classSampleWeight.push(classWeight[classIndex]);
-            }
-          });
-          return Object(dist["tensor1d"])(classSampleWeight, "float32");
-        } else {
-          return null;
-        }
-      }
-      /**
-       * Apply per-sample weights on the loss values from a number of samples.
-       *
-       * @param losses Loss tensor of shape `[batchSize]`.
-       * @param sampleWeights Per-sample weight tensor of shape `[batchSize]`.
-       * @returns Tensor of the same shape as`losses`.
-       */
-      function computeWeightedLoss(losses, sampleWeights) {
-        return Object(dist["mul"])(losses, sampleWeights);
-      }
-      //# sourceMappingURL=training_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/training_dataset.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Interfaces and methods for training models using TensorFlow.js datasets.
-       */
-
-      // Default batch size used during tensor-based validation.
-      const DEFAULT_VALIDATION_BATCH_SIZE = 32;
-      /**
-       * Standardize the output of a dataset iterator for use by
-       * LayersModel.fitDataset().
-       *
-       * @param model: A `tf.LayersModel` object.
-       * @param iteratorOut The output of a dataset iterator. It is required to be
-       *   an object of the form `{xs: TensorOrArrayOrMap, ys:
-       * TensorOrArrayOrMap}`, where `TensorOrArrayOrMap` is a single `tf.Tensor`,
-       * a `tf.Tensor[]`, or a flat map from string names to `tf.Tensor`s.
-       * @returns A flat array of `tf.Tensor` objects: the input `tf.Tensor`s
-       *   followed by the target `tf.Tensor`s.  When `tf.Tensor`s are provided
-       *   as a map, the order in the resulting array is taken from the `inputNames`
-       *   and `outputNames` of the model.
-       */
-      function standardizeDataIteratorOutput(
-        // Type `model` as `any` here to avoid circular dependency w/
-        // training.ts.
-        // tslint:disable-next-line:no-any
-        model,
-        iteratorOut
-      ) {
-        let xs;
-        let ys;
-        const iteratorOutObj = iteratorOut;
-        xs = iteratorOutObj["xs"];
-        ys = iteratorOutObj["ys"];
-        dist["util"].assert(
-          xs != null && ys != null,
-          () =>
-            "A Dataset iterator for fitDataset() is expected to generate " +
-            "objects of the form `{xs: xVal, ys: yVal}`, where the two " +
-            "values may be `tf.Tensor`, an array of Tensors, or a map of " +
-            "string to Tensor.  The provided Dataset instead generates " +
-            `${iteratorOut}`
-        );
-        const flattenedXs = flattenTensorOrArrayOrMap("input", model.inputNames, xs);
-        const flattenedYs = flattenTensorOrArrayOrMap("output", model.outputNames, ys);
-        const batchSize = flattenedXs[0].shape[0];
-        dist["util"].assert(
-          flattenedXs.length === model.inputs.length,
-          () =>
-            `LayersModel has ${model.inputs.length} inputs, but the dataset ` +
-            `provides ${flattenedXs.length} inputs.  (Expected input keys: ` +
-            `${JSON.stringify(model.inputNames)})`
-        );
-        dist["util"].assert(
-          flattenedYs.length === model.outputs.length,
-          () =>
-            `LayersModel has ${model.outputs.length} outputs, but the dataset ` +
-            `provides ${flattenedYs.length} outputs.  (Expected output keys: ` +
-            `${JSON.stringify(model.outputNames)})`
-        );
-        for (let xIndex = 0; xIndex < flattenedXs.length; xIndex++) {
-          dist["util"].assert(
-            flattenedXs[xIndex].shape[0] === batchSize,
-            () =>
-              `Batch size mismatch: input ` +
-              `${model.inputNames[xIndex]} has ${flattenedXs[xIndex].shape[0]}; ` +
-              `expected  ${batchSize} based on input ${model.inputNames[0]}.`
-          );
-        }
-        for (let yIndex = 0; yIndex < flattenedYs.length; yIndex++) {
-          dist["util"].assert(
-            flattenedYs[yIndex].shape[0] === batchSize,
-            () =>
-              `Batch size mismatch: output ` +
-              `${model.outputNames[yIndex]} has ${flattenedYs[yIndex].shape[0]}; ` +
-              `expected  ${batchSize} based on input ${model.inputNames[0]}.`
-          );
-        }
-        return { xs: flattenedXs, ys: flattenedYs };
-      }
-      function flattenTensorOrArrayOrMap(inputOrOutput, names, values) {
-        if (values instanceof dist["Tensor"]) {
-          return [values];
-        } else if (Array.isArray(values)) {
-          dist["util"].assert(
-            values.length === names.length,
-            () =>
-              `Received an array of ${values.length} Tensors, but expected ${names.length} to match the ${inputOrOutput} keys ${names}.`
-          );
-          return values;
-        } else {
-          const result = [];
-          // Check that all the required keys are available.
-          for (const name of names) {
-            if (values[name] == null) {
-              throw new ValueError(
-                `The feature data generated by the dataset lacks the required ` +
-                  `${inputOrOutput} key '${name}'.`
-              );
-            }
-            result.push(values[name]);
-          }
-          return result;
-        }
-      }
-      function standardizeTensorValidationData(data) {
-        if (data.length === 3) {
-          throw new NotImplementedError("Validation with sample weights is not implemented yet.");
-        }
-        return { xs: data[0], ys: data[1] };
-      }
-      async function fitDataset(
-        // Type `model` as `any` here to avoid circular dependency w/
-        // training.ts.
-        // tslint:disable-next-line:no-any
-        model,
-        dataset,
-        args
-      ) {
-        const hasBatchesPerEpoch = args.batchesPerEpoch != null;
-        dist["util"].assert(
-          model.optimizer != null,
-          () =>
-            "You must compile a model before training/testing. Use " +
-            "LayersModel.compile(modelCompileConfig)."
-        );
-        dist["util"].assert(
-          args != null,
-          () =>
-            `For fitDataset(), the 2nd argument (config) is required, ` +
-            `but it is not provided in this call.`
-        );
-        dist["util"].assert(
-          args.epochs != null && args.epochs > 0 && Number.isInteger(args.epochs),
-          () =>
-            `For fitDataset(), config.epochs is expected to be a positive ` +
-            `integer, but got ${args.epochs}`
-        );
-        dist["util"].assert(
-          !hasBatchesPerEpoch ||
-            (args.batchesPerEpoch > 0 && Number.isInteger(args.batchesPerEpoch)),
-          () =>
-            `For fitDataset(), config.batchesPerEpoch is expected to be a ` +
-            `positive integer if specified, but got ${args.batchesPerEpoch}`
-        );
-        dist["util"].assert(
-          // tslint:disable-next-line:no-any
-          args["validationSplit"] == null,
-          () =>
-            "`validationSplit` is not supported by `fitDataset()`. " + "Use validationData instead."
-        );
-        if (model.isTraining) {
-          throw new Error("Cannot start training because another fit() call is ongoing.");
-        }
-        model.isTraining = true;
-        try {
-          const doValidation = args.validationData != null;
-          let valXs;
-          let valYs;
-          if (doValidation) {
-            if (isDatasetObject(args.validationData)) {
-              dist["util"].assert(
-                args.validationBatches == null ||
-                  (args.validationBatches > 0 && Number.isInteger(args.validationBatches)),
-                () =>
-                  `For fitDataset() with dataset-based validation, ` +
-                  `config.validationBatches is expected not to be provided, ` +
-                  `or to be a positive integer, ` +
-                  `but got ${args.validationBatches}`
-              );
-            } else {
-              const validationData = standardizeTensorValidationData(args.validationData);
-              valXs = validationData.xs;
-              valYs = validationData.ys;
-            }
-          }
-          const trainFunction = model.makeTrainFunction();
-          const outLabels = model.getDedupedMetricsNames();
-          let callbackMetrics;
-          if (doValidation) {
-            callbackMetrics = outLabels.slice().concat(outLabels.map((n) => "val_" + n));
-          } else {
-            callbackMetrics = outLabels.slice();
-          }
-          const callbacks = standardizeCallbacks(args.callbacks, args.yieldEvery);
-          const verbose = args.verbose == null ? 1 : args.verbose;
-          const { callbackList, history } = configureCallbacks(
-            callbacks,
-            verbose,
-            args.epochs,
-            null,
-            null,
-            getStepsPerEpoch(dataset, args),
-            null, // Batch size determined by the dataset itself.
-            doValidation,
-            callbackMetrics
-          );
-          callbackList.setModel(model);
-          model.history = history;
-          await callbackList.onTrainBegin();
-          model.stopTraining_ = false;
-          let epoch = args.initialEpoch == null ? 0 : args.initialEpoch;
-          let dataIterator = await dataset.iterator();
-          while (epoch < args.epochs) {
-            const epochLogs = {};
-            await callbackList.onEpochBegin(epoch);
-            let stepsDone = 0;
-            let batchIndex = 0;
-            if (!hasBatchesPerEpoch) {
-              dataIterator = await dataset.iterator();
-            }
-            while (hasBatchesPerEpoch ? stepsDone < args.batchesPerEpoch : true) {
-              const iteratorOut = await dataIterator.next();
-              // If `batchesPerEpoch` is specified, the dataset should not be
-              // exhausted until all epoches are done.
-              if (hasBatchesPerEpoch && iteratorOut.done) {
-                console.warn(
-                  "You provided `batchesPerEpoch` as " +
-                    `${args.batchesPerEpoch}, ` +
-                    "but your dataset iterator ran out of data after " +
-                    `${stepsDone} batches; ` +
-                    "interrupting training. Make sure that your " +
-                    "dataset can generate at least `batchesPerEpoch * epochs` " +
-                    "batches (in this case, " +
-                    `${args.batchesPerEpoch * args.epochs} batches). ` +
-                    "You may need to use the repeat() function when building " +
-                    "your dataset."
-                );
-                break;
-              }
-              if (iteratorOut.value != null) {
-                const { xs, ys } = standardizeDataIteratorOutput(model, iteratorOut.value);
-                const batchLogs = {};
-                batchLogs["batch"] = batchIndex;
-                batchLogs["size"] = xs[0].shape[0];
-                await callbackList.onBatchBegin(batchIndex, batchLogs);
-                const sampleWeights = [];
-                if (args.classWeight != null) {
-                  const standardClassWeights = standardizeClassWeights(
-                    args.classWeight,
-                    model.outputNames
-                  );
-                  for (let i = 0; i < standardClassWeights.length; ++i) {
-                    sampleWeights.push(
-                      await standardizeWeights(ys[i], null, standardClassWeights[i])
-                    );
-                  }
-                }
-                // Train on batch.
-                const ins = xs.concat(ys).concat(sampleWeights);
-                const outs = trainFunction(ins);
-                dist["dispose"](ins);
-                for (let i = 0; i < outLabels.length; ++i) {
-                  const label = outLabels[i];
-                  const out = outs[i];
-                  batchLogs[label] = out;
-                  dist["keep"](out);
-                }
-                await callbackList.onBatchEnd(batchIndex, batchLogs);
-                disposeTensorsInLogs(batchLogs);
-                batchIndex++;
-                stepsDone++;
-              }
-              if (hasBatchesPerEpoch ? stepsDone >= args.batchesPerEpoch : iteratorOut.done) {
-                // Epoch finished. Perform validation.
-                if (doValidation) {
-                  let valOuts;
-                  if (isDatasetObject(args.validationData)) {
-                    valOuts = toList(
-                      await model.evaluateDataset(args.validationData, {
-                        batches: args.validationBatches,
-                      })
-                    );
-                  } else {
-                    valOuts = toList(
-                      model.evaluate(valXs, valYs, {
-                        batchSize:
-                          args.validationBatchSize == null
-                            ? DEFAULT_VALIDATION_BATCH_SIZE
-                            : args.validationBatchSize,
-                        verbose: 0,
-                      })
-                    );
-                  }
-                  for (let i = 0; i < model.metricsNames.length; ++i) {
-                    epochLogs[`val_${model.metricsNames[i]}`] = valOuts[i];
-                  }
-                }
-                // Call `break` to exit one epoch lopp after validation is done. If
-                // config.batchesPerEpoch is specified, an epoch while loop will
-                // stop when `stepsDone >= config.batchesPerEpoch`. When
-                // config.batchesPerEpoch is not provided, the following `break` is
-                // required to exit the while lopp after dataset is exhausted.
-                break;
-              }
-              if (model.stopTraining_) {
-                break;
-              }
-            }
-            await callbackList.onEpochEnd(epoch, epochLogs);
-            epoch++;
-            if (model.stopTraining_) {
-              break;
-            }
-          }
-          await callbackList.onTrainEnd();
-          await model.history.syncData();
-          return model.history;
-        } finally {
-          model.isTraining = false;
-        }
-      }
-      /** Helper function that determines number of steps (batches) per epoch. */
-      function getStepsPerEpoch(dataset, args) {
-        // Attempt to determine # of batches in an epoch.
-        let stepsPerEpoch = null;
-        if (args.batchesPerEpoch != null) {
-          stepsPerEpoch = args.batchesPerEpoch;
-        } else if (Number.isFinite(dataset.size)) {
-          stepsPerEpoch = dataset.size;
-        }
-        return stepsPerEpoch;
-      }
-      // Check if provided object is a Dataset object by checking its .iterator
-      // element.
-      function isDatasetObject(dataset) {
-        return typeof dataset.iterator === "function";
-      }
-      // Check if provided object is a LazyIterator object by checking it's .next
-      // element.
-      function isLazyIteratorObject(iterator) {
-        return typeof iterator.next === "function";
-      }
-      async function evaluateDataset(
-        // Type `model` as `any` here to avoid circular dependency w/
-        // training.ts.
-        // tslint:disable-next-line:no-any
-        model,
-        dataset,
-        args
-      ) {
-        args = args || {};
-        const hasBatches = args.batches != null;
-        const f = model.testFunction;
-        let outs = [];
-        if (args.verbose > 0) {
-          throw new NotImplementedError("Verbose mode is not implemented yet.");
-        }
-        dist["util"].assert(
-          !hasBatches || (args.batches > 0 && Number.isInteger(args.batches)),
-          () =>
-            "Test loop expects `batches` to be a positive integer, but " +
-            `received ${JSON.stringify(args.batches)}`
-        );
-        const dataIterator = isLazyIteratorObject(dataset) ? dataset : await dataset.iterator();
-        // Keeps track of number of examples used in this evaluation.
-        let numExamples = 0;
-        let batch = 0;
-        while (hasBatches ? batch < args.batches : true) {
-          const iteratorOut = await dataIterator.next();
-          outs = dist["tidy"](() => {
-            if (iteratorOut.value) {
-              // TODO(cais): Once real dataset is available, use
-              //   `map(x => standardizeDataIteratorOutput(model, x).map(f)`.
-              const { xs, ys } = standardizeDataIteratorOutput(model, iteratorOut.value);
-              const xsAndYs = xs.concat(ys);
-              const batchOuts = dist["tidy"](() => f(xsAndYs));
-              dist["dispose"](xsAndYs);
-              if (batch === 0) {
-                for (let i = 0; i < batchOuts.length; ++i) {
-                  outs.push(Object(dist["scalar"])(0));
-                }
-              }
-              const batchSize = xsAndYs[0].shape[0];
-              for (let i = 0; i < batchOuts.length; ++i) {
-                const batchOut = batchOuts[i];
-                const oldScalar = outs[i];
-                outs[i] = dist["tidy"](() =>
-                  dist["add"](outs[i], dist["mul"](batchSize, batchOut))
-                );
-                if (batch > 0) {
-                  dist["dispose"](oldScalar);
-                }
-              }
-              dist["dispose"](batchOuts);
-              numExamples += batchSize;
-              ++batch;
-            }
-            return outs;
-          });
-          if (iteratorOut.done) {
-            if (hasBatches) {
-              console.warn(
-                "Your dataset iterator ran out of data during evaluateDataset(). " +
-                  "Interrupting evalution. Make sure that your " +
-                  "dataset can generate at least `batches` " +
-                  `batches (in this case, ${args.batches} batches). ` +
-                  "You may need to use the repeat() function when building " +
-                  "your dataset."
-              );
-            }
-            break;
-          }
-        }
-        for (let i = 0; i < outs.length; ++i) {
-          const oldScalar = outs[i];
-          outs[i] = dist["div"](outs[i], numExamples);
-          dist["dispose"](oldScalar);
-        }
-        return singletonOrArray(outs);
-      }
-      //# sourceMappingURL=training_dataset.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/training_tensors.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Interfaces and methods for training models using tf.Tensor objects.
-       */
-
-      function checkBatchSize(batchSize) {
-        dist["util"].assert(
-          batchSize > 0 && Number.isInteger(batchSize),
-          () => `batchSize is required to be a positive integer, but got ${batchSize}`
-        );
-      }
-      /**
-       * Slice a Tensor or an Array of Tensors, by start and stop indices.
-       *
-       * Porting Note: The `_slice_arrays` function in PyKeras is covered by this
-       *   function and `sliceArraysByIndices()` together.
-       *
-       * @param arrays: the input.
-       * @param start: the starting index (inclusive).
-       * @param stop: the stopping index (exclusive).
-       * @returns The result of the slicing. If `arrays` is an `Array` of
-       *   `tf.Tensor`s, the slicing will be applied to all elements of the `Array`
-       *   in the same way.
-       */
-      function sliceArrays(arrays, start, stop) {
-        if (arrays == null) {
-          return [null];
-        } else if (Array.isArray(arrays)) {
-          return arrays.map((array) => sliceAlongFirstAxis(array, start, stop - start));
-        } else {
-          // Tensor.
-          return sliceAlongFirstAxis(arrays, start, stop - start);
-        }
-      }
-      /**
-       * Slice a Tensor or an Array of Tensors, by random-order indices.
-       *
-       * Porting Note: The `_slice_arrays` function in PyKeras is covered by this
-       *   function and `sliceArrays()` together.
-       *
-       * @param arrays The input `tf.Tensor` or `Array` of `tf.Tensor`s to slice.
-       *   If an `Array` of `tf.Tensor`s, all `tf.Tensor`s will be sliced in the
-       *   same fashion.
-       * @param indices The indices to use for slicing along the first (batch)
-       *   dimension.
-       * @returns Result(s) of the slicing.
-       */
-      function sliceArraysByIndices(arrays, indices) {
-        return dist["tidy"](() => {
-          if (arrays == null) {
-            return null;
-          } else if (Array.isArray(arrays)) {
-            return arrays.map((array) => sliceArraysByIndices(array, indices));
-          } else {
-            // TODO(cais): indices should be a pre-constructed Tensor1D to avoid
-            //   tensor1d() calls.
-            return gather(arrays, indices.dtype === "int32" ? indices : indices.toInt());
-          }
-        });
-      }
-      /**
-       * Returns a list of batch indices (tuples of indices).
-       * @param size: Integer, total size of the data to slice into batches.
-       * @param batchSize: Integer, batch size.
-       * @returns An Array of [batchStart, batchEnd] tuples. batchStart is
-       *   inclusive; batchEnd is exclusive. I.e., each batch consists of indices x
-       *   that satisfy batchStart <= x < batchEnd.
-       */
-      function makeBatches(size, batchSize) {
-        const output = [];
-        let batchStart = 0;
-        let batchEnd = null;
-        while (batchStart < size) {
-          batchEnd = batchStart + batchSize;
-          if (batchEnd >= size) {
-            batchEnd = size;
-          }
-          output.push([batchStart, batchEnd]);
-          batchStart = batchEnd;
-        }
-        return output;
-      }
-      /**
-       * Abstract fit function for `f(ins)`.
-       * @param f A Function returning a list of tensors. For training, this
-       *   function is expected to perform the updates to the variables.
-       * @param ins List of tensors to be fed to `f`.
-       * @param outLabels List of strings, display names of the outputs of `f`.
-       * @param batchSize Integer batch size or `== null` if unknown. Default : 32.
-       * @param epochs Number of times to iterate over the data. Default : 1.
-       * @param verbose Verbosity mode: 0, 1, or 2. Default: 1.
-       * @param callbacks List of callbacks to be called during training.
-       * @param valF Function to call for validation.
-       * @param valIns List of tensors to be fed to `valF`.
-       * @param shuffle Whether to shuffle the data at the beginning of every
-       * epoch. Default : true.
-       * @param callbackMetrics List of strings, the display names of the metrics
-       *   passed to the callbacks. They should be the concatenation of the
-       *   display names of the outputs of `f` and the list of display names
-       *   of the outputs of `valF`.
-       * @param initialEpoch Epoch at which to start training (useful for
-       *   resuming a previous training run). Default : 0.
-       * @param stepsPerEpoch Total number of steps (batches on samples) before
-       *   declaring one epoch finished and starting the next epoch. Ignored with
-       *   the default value of `undefined` or `null`.
-       * @param validationSteps Number of steps to run validation for (only if
-       *   doing validation from data tensors). Not applicable for tfjs-layers.
-       * @returns A `History` object.
-       */
-      async function fitLoop(
-        // Type `model` as `any` here to avoid circular dependency w/ training.ts.
-        // tslint:disable-next-line:no-any
-        model,
-        f,
-        ins,
-        outLabels,
-        batchSize,
-        epochs,
-        verbose,
-        callbacks,
-        valF,
-        valIns,
-        shuffle,
-        callbackMetrics,
-        initialEpoch,
-        stepsPerEpoch,
-        validationSteps
-      ) {
-        if (batchSize == null) {
-          batchSize = 32;
-        }
-        if (epochs == null) {
-          epochs = 1;
-        }
-        if (shuffle == null) {
-          shuffle = true;
-        }
-        if (initialEpoch == null) {
-          initialEpoch = 0;
-        }
-        // TODO(cais): Change const to let below when implementing validation.
-        let doValidation = false;
-        if (valF != null && valIns != null) {
-          doValidation = true;
-          // TODO(cais): verbose message.
-        }
-        if (validationSteps != null) {
-          doValidation = true;
-          if (stepsPerEpoch == null) {
-            throw new ValueError(
-              "Can only use `validationSteps` when doing step-wise training, " +
-                "i.e., `stepsPerEpoch` must be set."
-            );
-          }
-        }
-        const numTrainSamples = model.checkNumSamples(
-          ins,
-          batchSize,
-          stepsPerEpoch,
-          "steps_per_epoch"
-        );
-        let indexArray;
-        if (numTrainSamples != null) {
-          indexArray = range(0, numTrainSamples);
-        }
-        if (verbose == null) {
-          verbose = 1;
-        }
-        const { callbackList, history } = configureCallbacks(
-          callbacks,
-          verbose,
-          epochs,
-          initialEpoch,
-          numTrainSamples,
-          stepsPerEpoch,
-          batchSize,
-          doValidation,
-          callbackMetrics
-        );
-        callbackList.setModel(model);
-        model.history = history;
-        await callbackList.onTrainBegin();
-        model.stopTraining_ = false;
-        // TODO(cais): Take care of callbacks.validation_data as in PyKeras.
-        // TODO(cais): Pre-convert feeds for performance as in PyKeras.
-        for (let epoch = initialEpoch; epoch < epochs; ++epoch) {
-          await callbackList.onEpochBegin(epoch);
-          const epochLogs = {};
-          if (stepsPerEpoch != null) {
-            throw new NotImplementedError("stepsPerEpoch mode is not implemented yet.");
-          } else {
-            if (shuffle === "batch") {
-              throw new NotImplementedError("batch shuffling is not implemneted yet");
-            } else if (shuffle) {
-              dist["util"].shuffle(indexArray);
-            }
-            // Convert the potentially shuffled indices to Tensor1D, to avoid the
-            // cost of repeated creation of Array1Ds later on.
-            const epochIndexArray1D = Object(dist["tensor1d"])(indexArray);
-            const batches = makeBatches(numTrainSamples, batchSize);
-            for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {
-              const batchLogs = {};
-              await callbackList.onBatchBegin(batchIndex, batchLogs);
-              dist["tidy"](() => {
-                const batchStart = batches[batchIndex][0];
-                const batchEnd = batches[batchIndex][1];
-                const batchIds = sliceAlongFirstAxis(
-                  epochIndexArray1D,
-                  batchStart,
-                  batchEnd - batchStart
-                );
-                batchLogs["batch"] = batchIndex;
-                batchLogs["size"] = batchEnd - batchStart;
-                // TODO(cais): In ins, train flag can be a number, instead of an
-                //   Tensor? Do we need to handle this in tfjs-layers?
-                const insBatch = sliceArraysByIndices(ins, batchIds);
-                const outs = f(insBatch);
-                for (let i = 0; i < outLabels.length; ++i) {
-                  const label = outLabels[i];
-                  const out = outs[i];
-                  batchLogs[label] = out;
-                  dist["keep"](out);
-                  // TODO(cais): Use scope() to avoid ownership.
-                }
-                if (batchIndex === batches.length - 1) {
-                  // Last batch.
-                  if (doValidation) {
-                    const valOuts = model.testLoop(valF, valIns, batchSize);
-                    // Porting Notes: In tfjs-layers, valOuts is always an Array.
-                    for (let i = 0; i < outLabels.length; ++i) {
-                      const label = outLabels[i];
-                      const out = valOuts[i];
-                      dist["keep"](out);
-                      // TODO(cais): Use scope() to avoid ownership.
-                      epochLogs["val_" + label] = out;
-                    }
-                  }
-                }
-              });
-              await callbackList.onBatchEnd(batchIndex, batchLogs);
-              disposeTensorsInLogs(batchLogs);
-              if (model.stopTraining_) {
-                break;
-              }
-              // TODO(cais): return outs as list of Tensor.
-            }
-            epochIndexArray1D.dispose();
-          }
-          // TODO(cais): Run validation at the end of the epoch.
-          await callbackList.onEpochEnd(epoch, epochLogs);
-          if (model.stopTraining_) {
-            break;
-          }
-        }
-        await callbackList.onTrainEnd();
-        await model.history.syncData();
-        return model.history;
-      }
-      async function fitTensors(
-        // Type `model` as `any` here to avoid circular dependency w/ training.ts.
-        // tslint:disable-next-line:no-any
-        model,
-        x,
-        y,
-        args = {}
-      ) {
-        if (model.isTraining) {
-          throw new Error("Cannot start training because another fit() call is ongoing.");
-        }
-        model.isTraining = true;
-        let inputs;
-        let targets;
-        let inputValX;
-        let inputValY;
-        let valX;
-        let valY;
-        let sampleWeights;
-        try {
-          const batchSize = args.batchSize == null ? 32 : args.batchSize;
-          checkBatchSize(batchSize);
-          // Validate user data.
-          // TODO(cais): Support sampleWeight.
-          const checkBatchAxis = false;
-          const standardizedOuts = await model.standardizeUserData(
-            x,
-            y,
-            args.sampleWeight,
-            args.classWeight,
-            checkBatchAxis,
-            batchSize
-          );
-          inputs = standardizedOuts[0];
-          targets = standardizedOuts[1];
-          sampleWeights = standardizedOuts[2];
-          // Prepare validation data.
-          let doValidation = false;
-          let valIns;
-          if (args.validationData != null && args.validationData.length > 0) {
-            doValidation = true;
-            if (args.validationData.length === 2) {
-              // config.validationData consists of valX and valY.
-              inputValX = args.validationData[0];
-              inputValY = args.validationData[1];
-            } else if (args.validationData.length === 3) {
-              throw new NotImplementedError(
-                "validationData including sample weights is not supported yet."
-              );
-            } else {
-              throw new ValueError(
-                `When passing validation data, it must contain 2 (valX, valY) ` +
-                  `or 3 (valX, valY, valSampleWeight) items; ` +
-                  `${args.validationData} is invalid.`
-              );
-            }
-            const checkBatchAxis = true;
-            const valStandardized = await model.standardizeUserData(
-              inputValX,
-              inputValY,
-              null,
-              /** Unused sample weights. */ null,
-              /** Unused class weights. */ checkBatchAxis,
-              batchSize
-            );
-            valX = valStandardized[0];
-            valY = valStandardized[1];
-            valIns = valX.concat(valY);
-            // TODO(cais): Add useLearningPhase data properly.
-          } else if (
-            args.validationSplit != null &&
-            args.validationSplit > 0 &&
-            args.validationSplit < 1
-          ) {
-            doValidation = true;
-            // Porting Note: In tfjs-layers, inputs[0] is always a Tensor.
-            const splitAt = Math.floor(inputs[0].shape[0] * (1 - args.validationSplit));
-            const originalBatchSize = inputs[0].shape[0];
-            valX = sliceArrays(inputs, splitAt, originalBatchSize);
-            inputs = sliceArrays(inputs, 0, splitAt);
-            valY = sliceArrays(targets, splitAt, originalBatchSize);
-            targets = sliceArrays(targets, 0, splitAt);
-            // TODO(cais): Once sampleWeights becomes available, slice it to get
-            //   valSampleWeights.
-            valIns = valX.concat(valY);
-            // TODO(cais): Add useLearningPhase data properly.
-          } else if (args.validationSteps != null) {
-            doValidation = true;
-            // TODO(cais): Add useLearningPhase.
-          }
-          const ins = inputs.concat(targets).concat(sampleWeights);
-          model.checkTrainableWeightsConsistency();
-          // TODO(cais): Handle use_learning_phase and learning_phase?
-          // Porting Note: Here we see a key deviation of tfjs-layers from
-          // Keras.
-          //  Due to the imperative nature of tfjs-layers' backend (tfjs-core),
-          //  we do not construct symbolic computation graphs to embody the
-          //  training process. Instead, we define a function that performs the
-          //  training action. In PyKeras, the data (inputs and targets) are fed
-          //  through graph placeholders. In tfjs-layers, the data are fed as
-          //  function arguments. Since the function are defined below in the
-          //  scope, we don't have equivalents of PyKeras's
-          //  `_make_train_funciton`.
-          const trainFunction = model.makeTrainFunction();
-          const outLabels = model.getDedupedMetricsNames();
-          let valFunction;
-          let callbackMetrics;
-          if (doValidation) {
-            model.makeTestFunction();
-            valFunction = model.testFunction;
-            callbackMetrics = outLabels.slice().concat(outLabels.map((n) => "val_" + n));
-          } else {
-            valFunction = null;
-            valIns = [];
-            callbackMetrics = outLabels.slice();
-          }
-          const callbacks = standardizeCallbacks(args.callbacks, args.yieldEvery);
-          const out = await fitLoop(
-            model,
-            trainFunction,
-            ins,
-            outLabels,
-            batchSize,
-            args.epochs,
-            args.verbose,
-            callbacks,
-            valFunction,
-            valIns,
-            args.shuffle,
-            callbackMetrics,
-            args.initialEpoch,
-            null,
-            null
-          );
-          return out;
-        } finally {
-          model.isTraining = false;
-          // Memory clean up.
-          disposeNewTensors(inputs, x);
-          disposeNewTensors(targets, y);
-          disposeNewTensors(valX, inputValX);
-          disposeNewTensors(valY, inputValY);
-          if (sampleWeights != null) {
-            dist["dispose"](sampleWeights);
-          }
-        }
-        // TODO(cais): Add value to outLabels.
-      }
-      /**
-       * Ensure tensors all have a rank of at least 2.
-       *
-       * If a tensor has a rank of 1, it is dimension-expanded to rank 2.
-       * If any tensor has a rank of 0 (i.e., is a scalar), an error will be thrown.
-       */
-      function ensureTensorsRank2OrHigher(tensors) {
-        const outs = [];
-        if (tensors instanceof dist["Tensor"]) {
-          tensors = [tensors];
-        }
-        // Make Tensors at least 2D.
-        for (let i = 0; i < tensors.length; ++i) {
-          const tensor = tensors[i];
-          if (tensor.rank === 1) {
-            outs.push(expandDims(tensor, 1));
-          } else if (tensor.rank === 0) {
-            throw new Error(
-              "Expected tensor to be at least 1D, but received a 0D tensor " + "(scalar)."
-            );
-          } else {
-            outs.push(tensor);
-          }
-        }
-        return outs;
-      }
-      /**
-       * Compare a set of tensors with a reference (old) set, discard the ones
-       * in the new set that are not present in the reference set.
-       *
-       * This method is used for memory clenaup during calls such as
-       * LayersModel.fit().
-       *
-       * @param tensors New set which may contain Tensors not present in
-       *   `refTensors`.
-       * @param refTensors Reference Tensor set.
-       */
-      // TODO(cais, kangyizhang): Deduplicate with tfjs-data.
-      function disposeNewTensors(tensors, refTensors) {
-        if (tensors == null) {
-          return;
-        }
-        const oldTensorIds = [];
-        if (refTensors instanceof dist["Tensor"]) {
-          oldTensorIds.push(refTensors.id);
-        } else if (Array.isArray(refTensors)) {
-          refTensors.forEach((t) => oldTensorIds.push(t.id));
-        } else if (refTensors != null) {
-          // `oldTensors` is a map from string name to Tensor.
-          for (const name in refTensors) {
-            const oldTensor = refTensors[name];
-            oldTensorIds.push(oldTensor.id);
-          }
-        }
-        const tensorsToDispose = [];
-        if (tensors instanceof dist["Tensor"]) {
-          if (oldTensorIds.indexOf(tensors.id) === -1) {
-            tensorsToDispose.push(tensors);
-          }
-        } else if (Array.isArray(tensors)) {
-          tensors.forEach((t) => {
-            if (oldTensorIds.indexOf(t.id) === -1) {
-              tensorsToDispose.push(t);
-            }
-          });
-        } else if (tensors != null) {
-          // `oldTensors` is a map from string name to Tensor.
-          for (const name in tensors) {
-            const tensor = tensors[name];
-            if (oldTensorIds.indexOf(tensor.id) === -1) {
-              tensorsToDispose.push(tensor);
-            }
-          }
-        }
-        tensorsToDispose.forEach((t) => {
-          if (!t.isDisposed) {
-            t.dispose();
-          }
-        });
-      }
-      //# sourceMappingURL=training_tensors.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/training.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original Source: engine/training.py */
-
-      /**
-       * Helper function for polymorphic input data: 1. singleton Tensor.
-       */
-      function isDataTensor(x) {
-        return x instanceof dist["Tensor"];
-      }
-      /**
-       * Helper function for polymorphic input data: 2. Array of Tensor.
-       */
-      function isDataArray(x) {
-        return Array.isArray(x);
-      }
-      /**
-       * Helper function for polymorphic input data: 3. "dict" of Tensor.
-       */
-      function isDataDict(x) {
-        return !isDataTensor(x) && !isDataArray(x);
-      }
-      /**
-       * Normalizes inputs and targets provided by users.
-       * @param data User-provided input data (polymorphic).
-       * @param names An Array of expected Tensor names.
-       * @param shapes Optional Array of expected Tensor shapes.
-       * @param checkBatchAxis Whether to check that the batch axis of the arrays
-       *   match  the expected value found in `shapes`.
-       * @param exceptionPrefix String prefix used for exception formatting.
-       * @returns List of standardized input Tensors (one Tensor per model input).
-       * @throws ValueError: in case of improperly formatted user data.
-       */
-      function standardizeInputData(
-        data,
-        names,
-        shapes,
-        checkBatchAxis = true,
-        exceptionPrefix = ""
-      ) {
-        if (names == null || names.length === 0) {
-          // Check for the case where the model expected no data, but some data got
-          // sent.
-          if (data != null) {
-            let gotUnexpectedData = false;
-            if (isDataArray(data) && data.length > 0) {
-              gotUnexpectedData = true;
-            } else if (isDataDict(data)) {
-              for (const key in data) {
-                if (data.hasOwnProperty(key)) {
-                  gotUnexpectedData = true;
-                  break;
-                }
-              }
-            } else {
-              // `data` is a singleton Tensor in this case.
-              gotUnexpectedData = true;
-            }
-            if (gotUnexpectedData) {
-              throw new ValueError(
-                `Error when checking model ${exceptionPrefix} expected no data, ` +
-                  `but got ${data}`
-              );
-            }
-          }
-          return [];
-        }
-        if (data == null) {
-          return names.map((name) => null);
-        }
-        let arrays;
-        if (isDataDict(data)) {
-          data = data;
-          arrays = [];
-          for (const name of names) {
-            if (data[name] == null) {
-              throw new ValueError(
-                `No data provided for "${name}". Need data for each key in: ` + `${names}`
-              );
-            }
-            arrays.push(data[name]);
-          }
-        } else if (isDataArray(data)) {
-          data = data;
-          if (data.length !== names.length) {
-            throw new ValueError(
-              `Error when checking model ${exceptionPrefix}: the Array of ` +
-                `Tensors that you are passing to your model is not the size the ` +
-                `model expected. Expected to see ${names.length} Tensor(s), but ` +
-                `instead got the following list of Tensor(s): ${data}`
-            );
-          }
-          arrays = data;
-        } else {
-          data = data;
-          if (names.length > 1) {
-            throw new ValueError(
-              `The model ${exceptionPrefix} expects ${names.length} Tensor(s), ` +
-                `but only received one Tensor. Found: Tensor with shape ${data.shape}`
-            );
-          }
-          arrays = [data];
-        }
-        arrays = ensureTensorsRank2OrHigher(arrays);
-        // Check shape compatibility.
-        if (shapes != null) {
-          for (let i = 0; i < names.length; ++i) {
-            if (shapes[i] == null) {
-              continue;
-            }
-            const array = arrays[i];
-            if (array.shape.length !== shapes[i].length) {
-              throw new ValueError(
-                `Error when checking ${exceptionPrefix}: expected ${names[i]} ` +
-                  `to have ${shapes[i].length} dimension(s). but got array with ` +
-                  `shape ${array.shape}`
-              );
-            }
-            for (let j = 0; j < shapes[i].length; ++j) {
-              if (j === 0 && !checkBatchAxis) {
-                // Skip the first (batch) axis.
-                continue;
-              }
-              const dim = array.shape[j];
-              const refDim = shapes[i][j];
-              if (refDim != null && refDim >= 0 && dim !== refDim) {
-                throw new ValueError(
-                  `Error when checking ${exceptionPrefix}: expected ${names[i]} ` +
-                    `to have shape [${shapes[i]}], but got array with shape ` +
-                    `[${array.shape}].`
-                );
-              }
-            }
-          }
-        }
-        return arrays;
-      }
-      /**
-       * User input validation for Tensors.
-       * @param inputs `Array` of `tf.Tensor`s for inputs.
-       * @param targets `Array` of `tf.Tensor`s for targets.
-       * @param weights Optional `Array` of `tf.Tensor`s for sample weights.
-       * @throws ValueError: in case of incorrectly formatted data.
-       */
-      function checkArrayLengths(inputs, targets, weights) {
-        const setX = unique(inputs.map((input) => input.shape[0]));
-        setX.sort();
-        const setY = unique(targets.map((target) => target.shape[0]));
-        setY.sort();
-        // TODO(cais): Check `weights` as well.
-        if (setX.length > 1) {
-          throw new ValueError(
-            `All input Tensors (x) should have the same number of samples. ` +
-              `Got array shapes: ` +
-              `${JSON.stringify(inputs.map((input) => input.shape))}`
-          );
-        }
-        if (setY.length > 1) {
-          throw new ValueError(
-            `All target Tensors (y) should have the same number of samples. ` +
-              `Got array shapes: ` +
-              `${JSON.stringify(targets.map((target) => target.shape))}`
-          );
-        }
-        if (setX.length > 0 && setY.length > 0 && !dist["util"].arraysEqual(setX, setY)) {
-          throw new ValueError(
-            `Input Tensors should have the same number of samples as target ` +
-              `Tensors. Found ${setX[0]} input sample(s) and ${setY[0]} target ` +
-              `sample(s).`
-          );
-        }
-      }
-      /**
-       * Validation on the compatibility of targes and loss functions.
-       *
-       * This helps prevent users from using loss functions incorrectly.
-       *
-       * @param targets `Array` of `tf.Tensor`s of targets.
-       * @param lossFns `Array` of loss functions.
-       * @param outputShapes `Array` of shapes of model outputs.
-       */
-      function checkLossAndTargetCompatibility(targets, lossFns, outputShapes) {
-        // TODO(cais): Dedicated test coverage?
-        const keyLosses = [meanSquaredError, binaryCrossentropy, categoricalCrossentropy];
-        for (let i = 0; i < targets.length; ++i) {
-          const y = targets[i];
-          const loss = lossFns[i];
-          const shape = outputShapes[i];
-          if (loss == null) {
-            continue;
-          }
-          if (loss === categoricalCrossentropy) {
-            if (y.shape[y.shape.length - 1] === 1) {
-              throw new ValueError(
-                `You are passing a target array of shape ${y.shape} while using ` +
-                  `a loss 'categorical_crossentropy'. 'categorical_crossentropy'` +
-                  `expects targets to be binary matrices (1s and 0s) of shape ` +
-                  `[samples, classes].`
-              );
-              // TODO(cais): Example code in error message.
-            }
-          }
-          if (keyLosses.indexOf(loss) !== -1) {
-            const slicedYShape = y.shape.slice(1);
-            const slicedShape = shape.slice(1);
-            for (let j = 0; j < slicedYShape.length; ++j) {
-              const targetDim = slicedYShape[j];
-              const outDim = slicedShape[j];
-              if (outDim != null && targetDim !== outDim) {
-                throw new ValueError(
-                  `A target Tensor with shape ${y.shape} was passed for an ` +
-                    `output of shape ${shape}, while using a loss function that ` +
-                    `expects targets to have the same shape as the output.`
-                );
-              }
-            }
-          }
-        }
-      }
-      /**
-       * Check inputs provided by the user.
-       *
-       * Porting Note: This corresponds to _standardize_input_data() in Python
-       *   Keras. Because of the strong typing in TF.js, we do not need to convert
-       *   the data. Specifically:
-       *   1) in PyKeras, `data` can be `DataFrame` instances from pandas, for
-       *      example. We don't need to worry about that here because there is no
-       *      widely popular javascript/typesdcript equivalent of pandas (so far).
-       *      If one becomes available in the future, we can add support.
-       *   2) in PyKeras, inputs can be Python dict. But here we are stipulating
-       * that the data is either a single `tf.Tensor` or an Array of `tf.Tensor`s. We
-       * may add support for `Object` data inputs in the future when the need
-       * arises.
-       *
-       * Instead, we perform basic checks for number of parameters and shapes.
-       *
-       * @param data: The input data.
-       * @param names: Name for the inputs, from the model.
-       * @param shapes: Expected shapes for the input data, from the model.
-       * @param checkBatchAxis: Whether the size along the batch axis (i.e., the
-       *   first dimension) will be checked for matching.
-       * @param exceptionPrefix: Execption prefix message, used in generating error
-       *   messages.
-       * @throws ValueError: on incorrect number of inputs or mismatches in shapes.
-       */
-      function checkInputData(data, names, shapes, checkBatchAxis = true, exceptionPrefix = "") {
-        let arrays;
-        if (Array.isArray(data)) {
-          if (data.length !== names.length) {
-            throw new ValueError(
-              `Error when checking model ${exceptionPrefix}: the Array of ` +
-                `Tensors that you are passing to your model is not the size the ` +
-                `the model expected. Expected to see ${names.length} Tensor(s),` +
-                ` but instead got ${data.length} Tensors(s).`
-            );
-          }
-          arrays = data;
-        } else {
-          if (names.length > 1) {
-            throw new ValueError(
-              `The model expects ${names.length} ${exceptionPrefix} Tensors, ` +
-                `but only received one Tensor. Found: array with shape ` +
-                `${JSON.stringify(data.shape)}.`
-            );
-          }
-          arrays = [data];
-        }
-        if (shapes != null) {
-          for (let i = 0; i < names.length; ++i) {
-            if (shapes[i] == null) {
-              continue;
-            }
-            const array = arrays[i];
-            if (array.shape.length !== shapes[i].length) {
-              throw new ValueError(
-                `Error when checking ${exceptionPrefix}: expected ${names[i]} ` +
-                  `to have ${shapes[i].length} dimension(s), but got array with ` +
-                  `shape ${JSON.stringify(array.shape)}`
-              );
-            }
-            for (let j = 0; j < shapes[i].length; ++j) {
-              if (j === 0 && !checkBatchAxis) {
-                continue;
-              }
-              const dim = array.shape[j];
-              const refDim = shapes[i][j];
-              if (refDim != null) {
-                if (refDim !== dim) {
-                  throw new ValueError(
-                    `Error when checking ${exceptionPrefix}: expected ` +
-                      `${names[i]} to have shape ${JSON.stringify(shapes[i])} but ` +
-                      `got array with shape ${JSON.stringify(array.shape)}.`
-                  );
-                }
-              }
-            }
-          }
-        }
-      }
-      /**
-       * Maps metric functions to model outputs.
-       * @param metrics An shortcut strings name, metric function, `Array` or dict
-       *   (`Object`) of metric functions.
-       * @param outputNames An `Array` of the names of model outputs.
-       * @returns An `Array` (one entry per model output) of `Array` of metric
-       *   functions. For instance, if the model has 2 outputs, and for the first
-       *   output we want to compute `binaryAccuracy` and `binaryCrossentropy`,
-       *   and just `binaryAccuracy` for the second output, the `Array` would look
-       *   like:
-       *     `[[binaryAccuracy, binaryCrossentropy],  [binaryAccuracy]]`
-       * @throws TypeError: incompatible metrics format.
-       */
-      function collectMetrics(metrics, outputNames) {
-        if (metrics == null || (Array.isArray(metrics) && metrics.length === 0)) {
-          return outputNames.map((name) => []);
-        }
-        let wrappedMetrics;
-        if (typeof metrics === "string" || typeof metrics === "function") {
-          wrappedMetrics = [metrics];
-        } else if (Array.isArray(metrics) || typeof metrics === "object") {
-          wrappedMetrics = metrics;
-        } else {
-          throw new TypeError(
-            "Type of metrics argument not understood. Expected an string," +
-              `function, Array, or Object, found: ${metrics}`
-          );
-        }
-        if (Array.isArray(wrappedMetrics)) {
-          // We then apply all metrics to all outputs.
-          return outputNames.map((name) => wrappedMetrics);
-        } else {
-          // In this case, metrics is a dict.
-          const nestedMetrics = [];
-          for (const name of outputNames) {
-            let outputMetrics = wrappedMetrics.hasOwnProperty(name) ? wrappedMetrics[name] : [];
-            if (!Array.isArray(outputMetrics)) {
-              outputMetrics = [outputMetrics];
-            }
-            nestedMetrics.push(outputMetrics);
-          }
-          return nestedMetrics;
-        }
-      }
-      const LAYERS_MODEL_FORMAT_NAME = "layers-model";
-      /**
-       * A `tf.LayersModel` is a directed, acyclic graph of `tf.Layer`s plus methods
-       * for training, evaluation, prediction and saving.
-       *
-       * `tf.LayersModel` is the basic unit of training, inference and evaluation in
-       * TensorFlow.js. To create a `tf.LayersModel`, use `tf.LayersModel`.
-       *
-       * See also:
-       *   `tf.Sequential`, `tf.loadLayersModel`.
-       */
-      /** @doc {heading: 'Models', subheading: 'Classes'} */
-      class training_LayersModel extends container_Container {
-        constructor(args) {
-          super(args);
-          this.isTraining = false;
-        }
-        /**
-         * Print a text summary of the model's layers.
-         *
-         * The summary includes
-         * - Name and type of all layers that comprise the model.
-         * - Output shape(s) of the layers
-         * - Number of weight parameters of each layer
-         * - If the model has non-sequential-like topology, the inputs each layer
-         *   receives
-         * - The total number of trainable and non-trainable parameters of the model.
-         *
-         * ```js
-         * const input1 = tf.input({shape: [10]});
-         * const input2 = tf.input({shape: [20]});
-         * const dense1 = tf.layers.dense({units: 4}).apply(input1);
-         * const dense2 = tf.layers.dense({units: 8}).apply(input2);
-         * const concat = tf.layers.concatenate().apply([dense1, dense2]);
-         * const output =
-         *     tf.layers.dense({units: 3, activation: 'softmax'}).apply(concat);
-         *
-         * const model = tf.model({inputs: [input1, input2], outputs: output});
-         * model.summary();
-         * ```
-         *
-         * @param lineLength Custom line length, in number of characters.
-         * @param positions Custom widths of each of the columns, as either
-         *   fractions of `lineLength` (e.g., `[0.5, 0.75, 1]`) or absolute number
-         *   of characters (e.g., `[30, 50, 65]`). Each number corresponds to
-         *   right-most (i.e., ending) position of a column.
-         * @param printFn Custom print function. Can be used to replace the default
-         *   `console.log`. For example, you can use `x => {}` to mute the printed
-         *   messages in the console.
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes'} */
-        summary(lineLength, positions, printFn = console.log) {
-          if (!this.built) {
-            throw new ValueError(
-              `This model has never been called, thus its weights have not been ` +
-                `created yet. So no summary can be displayed. Build the model ` +
-                `first (e.g., by calling it on some test data).`
-            );
-          }
-          printSummary(this, lineLength, positions, printFn);
-        }
-        /**
-         * Configures and prepares the model for training and evaluation.  Compiling
-         * outfits the model with an optimizer, loss, and/or metrics.  Calling `fit`
-         * or `evaluate` on an un-compiled model will throw an error.
-         *
-         * @param args a `ModelCompileArgs` specifying the loss, optimizer, and
-         * metrics to be used for fitting and evaluating this model.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        compile(args) {
-          if (args.loss == null) {
-            args.loss = [];
-          }
-          this.loss = args.loss;
-          if (typeof args.optimizer === "string") {
-            this.optimizer_ = getOptimizer(args.optimizer);
-            this.isOptimizerOwned = true;
-          } else {
-            if (!(args.optimizer instanceof dist["Optimizer"])) {
-              throw new ValueError(`User-defined optimizer must be an instance of tf.Optimizer.`);
-            }
-            this.optimizer_ = args.optimizer;
-            this.isOptimizerOwned = false;
-          }
-          // TODO(cais): Add lossWeights.
-          // TODO(cais): Add sampleWeightMode.
-          // Prepare loss functions.
-          let lossFunctions = [];
-          if (
-            !Array.isArray(args.loss) &&
-            typeof args.loss !== "string" &&
-            typeof args.loss !== "function"
-          ) {
-            args.loss = args.loss;
-            for (const name in args.loss) {
-              if (this.outputNames.indexOf(name) === -1) {
-                throw new ValueError(
-                  `Unknown entry in loss dictionary: "${name}". ` +
-                    `Only expected the following keys: ${this.outputNames}`
-                );
-              }
-            }
-            for (const name of this.outputNames) {
-              if (args.loss[name] == null) {
-                console.warn(
-                  `Output "${name}" is missing from loss dictionary. We assume ` +
-                    `this was done on purpose, and we will not be expecting data ` +
-                    `to be passed to ${name} during training`
-                );
-              }
-              lossFunctions.push(get(args.loss[name]));
-            }
-          } else if (Array.isArray(args.loss)) {
-            if (args.loss.length !== this.outputs.length) {
-              throw new ValueError(
-                `When passing an Array as loss, it should have one entry per ` +
-                  `model output. The model has ${this.outputs.length} output(s), ` +
-                  `but you passed loss=${args.loss}.`
-              );
-            }
-            const theLosses = args.loss;
-            lossFunctions = theLosses.map((l) => get(l));
-          } else {
-            const lossFunction = get(args.loss);
-            this.outputs.forEach((_) => {
-              lossFunctions.push(lossFunction);
-            });
-          }
-          this.lossFunctions = lossFunctions;
-          this.feedOutputNames = [];
-          this.feedOutputShapes = [];
-          this.feedLossFns = [];
-          for (let i = 0; i < this.outputs.length; ++i) {
-            // TODO(cais): Logic for skipping target(s).
-            const shape = this.internalOutputShapes[i];
-            const name = this.outputNames[i];
-            this.feedOutputNames.push(name);
-            this.feedOutputShapes.push(shape);
-            this.feedLossFns.push(this.lossFunctions[i]);
-          }
-          // TODO(cais): Add logic for output masks.
-          // TODO(cais): Add logic for sample weights.
-          const skipTargetIndices = [];
-          // Prepare metrics.
-          this.metrics = args.metrics;
-          // TODO(cais): Add weightedMetrics.
-          this.metricsNames = ["loss"];
-          this.metricsTensors = [];
-          // Compute total loss.
-          // Porting Note: In PyKeras, metrics_tensors are symbolic tensor objects.
-          //   Here, metricsTensors are TypeScript functions. This difference is due
-          //   to the difference in symbolic/imperative property of the backends.
-          nameScope("loss", () => {
-            for (let i = 0; i < this.outputs.length; ++i) {
-              if (skipTargetIndices.indexOf(i) !== -1) {
-                continue;
-              }
-              // TODO(cais): Add weightedLoss, sampleWeight and mask.
-              //   The following line should be weightedLoss
-              const weightedLoss = this.lossFunctions[i];
-              if (this.outputs.length > 1) {
-                this.metricsTensors.push([weightedLoss, i]);
-                this.metricsNames.push(this.outputNames[i] + "_loss");
-              }
-            }
-            // Porting Note: Due to the imperative nature of the backend, we calculate
-            //   the regularizer penalties in the totalLossFunction, instead of here.
-          });
-          const nestedMetrics = collectMetrics(args.metrics, this.outputNames);
-          // TODO(cais): Add nestedWeightedMetrics.
-          /**
-           * Helper function used in loop below.
-           */
-          const appendMetric = (outputIndex, metricName, metricTensor) => {
-            if (this.outputNames.length > 1) {
-              metricName = this.outputNames[outputIndex] + "_" + metricName;
-            }
-            this.metricsNames.push(metricName);
-            this.metricsTensors.push([metricTensor, outputIndex]);
-          };
-          nameScope("metric", () => {
-            for (let i = 0; i < this.outputs.length; ++i) {
-              if (skipTargetIndices.indexOf(i) !== -1) {
-                continue;
-              }
-              const outputMetrics = nestedMetrics[i];
-              // TODO(cais): Add weights and outputWeightedMetrics.
-              // TODO(cais): Add optional arg `weights` to the following function.
-              const handleMetrics = (metrics) => {
-                const metricNamePrefix = "";
-                let metricName;
-                let accFn;
-                let weightedMetricFn;
-                //  TODO(cais): Use 'weights_' for weighted metrics.
-                for (const metric of metrics) {
-                  if (
-                    typeof metric === "string" &&
-                    ["accuracy", "acc", "crossentropy", "ce"].indexOf(metric) !== -1
-                  ) {
-                    const outputShape = this.internalOutputShapes[i];
-                    if (
-                      outputShape[outputShape.length - 1] === 1 ||
-                      this.lossFunctions[i] === binaryCrossentropy
-                    ) {
-                      // case: binary accuracy/crossentropy.
-                      if (["accuracy", "acc"].indexOf(metric) !== -1) {
-                        accFn = binaryAccuracy;
-                      } else if (["crossentropy", "ce"].indexOf(metric) !== -1) {
-                        accFn = metrics_binaryCrossentropy;
-                      }
-                    } else if (this.lossFunctions[i] === sparseCategoricalCrossentropy) {
-                      // case: categorical accuracy / crossentropy with sparse
-                      // targets.
-                      if (["accuracy", "acc"].indexOf(metric) !== -1) {
-                        accFn = sparseCategoricalAccuracy;
-                      } else if (["crossentropy", "ce"].indexOf(metric) !== -1) {
-                        accFn = metrics_sparseCategoricalCrossentropy;
-                      }
-                    } else {
-                      // case: categorical accuracy / crossentropy.
-                      if (["accuracy", "acc"].indexOf(metric) !== -1) {
-                        accFn = categoricalAccuracy;
-                      } else if (["crossentropy", "ce"].indexOf(metric) !== -1) {
-                        accFn = metrics_categoricalCrossentropy;
-                      }
-                    }
-                    let suffix;
-                    if (["accuracy", "acc"].indexOf(metric) !== -1) {
-                      suffix = "acc";
-                    } else if (["crossentropy", "ce"].indexOf(metric) !== -1) {
-                      suffix = "ce";
-                    }
-                    // TODO(cais): Add weighting actually.
-                    weightedMetricFn = accFn;
-                    metricName = metricNamePrefix + suffix;
-                  } else {
-                    const metricFn = metrics_get(metric);
-                    // TODO(cais): Add weighting actually.
-                    weightedMetricFn = metricFn;
-                    metricName = metricNamePrefix + getLossOrMetricName(metric);
-                  }
-                  // TODO(cais): Add weighting and masking to metricResult.
-                  let metricResult;
-                  nameScope(metricName, () => {
-                    metricResult = weightedMetricFn;
-                  });
-                  appendMetric(i, metricName, metricResult);
-                }
-              };
-              handleMetrics(outputMetrics);
-              // TODO(cais): Call handleMetrics with weights.
-            }
-          });
-          // Porting Notes: Given the imperative backend of tfjs-core,
-          //   there is no need for constructing the symbolic graph and placeholders.
-          this.collectedTrainableWeights = this.trainableWeights;
-        }
-        /**
-         * Check trainable weights count consistency.
-         *
-         * This will raise a warning if `this.trainableWeights` and
-         * `this.collectedTrainableWeights` are inconsistent (i.e., have different
-         * numbers of parameters).
-         * Inconsistency will typically arise when one modifies `model.trainable`
-         * without calling `model.compile()` again.
-         */
-        checkTrainableWeightsConsistency() {
-          if (this.collectedTrainableWeights == null) {
-            return;
-          }
-          if (this.trainableWeights.length !== this.collectedTrainableWeights.length) {
-            console.warn(
-              "Discrepancy between trainableweights and collected trainable " +
-                "weights. Did you set `model.trainable` without calling " +
-                "`model.compile()` afterwards?"
-            );
-          }
-        }
-        /**
-         * Returns the loss value & metrics values for the model in test mode.
-         *
-         * Loss and metrics are specified during `compile()`, which needs to happen
-         * before calls to `evaluate()`.
-         *
-         * Computation is done in batches.
-         *
-         * ```js
-         * const model = tf.sequential({
-         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
-         * });
-         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
-         * const result = model.evaluate(
-         *     tf.ones([8, 10]), tf.ones([8, 1]), {batchSize: 4});
-         * result.print();
-         * ```
-         *
-         * @param x `tf.Tensor` of test data, or an `Array` of `tf.Tensor`s if the
-         * model has multiple inputs.
-         * @param y `tf.Tensor` of target data, or an `Array` of `tf.Tensor`s if the
-         * model has multiple outputs.
-         * @param args A `ModelEvaluateArgs`, containing optional fields.
-         *
-         * @return `Scalar` test loss (if the model has a single output and no
-         *   metrics) or `Array` of `Scalar`s (if the model has multiple outputs
-         *   and/or metrics). The attribute `model.metricsNames`
-         *   will give you the display labels for the scalar outputs.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        evaluate(x, y, args = {}) {
-          const batchSize = args.batchSize == null ? 32 : args.batchSize;
-          checkBatchSize(batchSize);
-          // TODO(cais): Standardize `config.sampleWeights` as well.
-          // Validate user data.
-          const checkBatchAxis = true;
-          const standardizedOuts = this.standardizeUserDataXY(x, y, checkBatchAxis, batchSize);
-          try {
-            // TODO(cais): If uses `useLearningPhase`, set the corresponding element
-            // of the input to 0.
-            const ins = standardizedOuts[0].concat(standardizedOuts[1]);
-            this.makeTestFunction();
-            const f = this.testFunction;
-            const testOuts = this.testLoop(f, ins, batchSize, args.verbose, args.steps);
-            return singletonOrArray(testOuts);
-          } finally {
-            disposeNewTensors(standardizedOuts[0], x);
-            disposeNewTensors(standardizedOuts[1], y);
-          }
-        }
-        // TODO(cais): Add code snippet below once real dataset objects are
-        //   available.
-        /**
-         * Evaluate model using a dataset object.
-         *
-         * Note: Unlike `evaluate()`, this method is asynchronous (`async`);
-         *
-         * @param dataset A dataset object. Its `iterator()` method is expected
-         *   to generate a dataset iterator object, the `next()` method of which
-         *   is expected to produce data batches for evaluation. The return value
-         *   of the `next()` call ought to contain a boolean `done` field and a
-         *   `value` field. The `value` field is expected to be an array of two
-         *   `tf.Tensor`s or an array of two nested `tf.Tensor` structures. The former
-         *   case is for models with exactly one input and one output (e.g..
-         *   a sequential model). The latter case is for models with multiple
-         *   inputs and/or multiple outputs. Of the two items in the array, the
-         *   first is the input feature(s) and the second is the output target(s).
-         * @param args A configuration object for the dataset-based evaluation.
-         * @returns Loss and metric values as an Array of `Scalar` objects.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        async evaluateDataset(dataset, args) {
-          this.makeTestFunction();
-          return evaluateDataset(this, dataset, args);
-        }
-        /**
-         * Get number of samples provided for training, evaluation or prediction.
-         *
-         * @param ins Input `tf.Tensor`.
-         * @param batchSize Integer batch size, optional.
-         * @param steps Total number of steps (batches of samples) before
-         * declaring loop finished. Optional.
-         * @param stepsName The public API's parameter name for `steps`.
-         * @returns Number of samples provided.
-         */
-        checkNumSamples(ins, batchSize, steps, stepsName = "steps") {
-          let numSamples;
-          if (steps != null) {
-            numSamples = null;
-            if (batchSize != null) {
-              throw new ValueError(
-                `If ${stepsName} is set, batchSize must be null or undefined.` +
-                  `Got batchSize = ${batchSize}`
-              );
-            }
-          } else if (ins != null) {
-            if (Array.isArray(ins)) {
-              numSamples = ins[0].shape[0];
-            } else {
-              numSamples = ins.shape[0];
-            }
-          } else {
-            throw new ValueError(
-              `Either the input data should have a defined shape, or ` +
-                `${stepsName} shoud be specified.`
-            );
-          }
-          return numSamples;
-        }
-        /**
-         * Execute internal tensors of the model with input data feed.
-         * @param inputs Input data feed. Must match the inputs of the model.
-         * @param outputs Names of the output tensors to be fetched. Must match
-         *   names of the SymbolicTensors that belong to the graph.
-         * @returns Fetched values for `outputs`.
-         */
-        execute(inputs, outputs) {
-          if (Array.isArray(outputs) && outputs.length === 0) {
-            throw new ValueError("`outputs` is an empty Array, which is not allowed.");
-          }
-          const outputsIsArray = Array.isArray(outputs);
-          const outputNames = outputsIsArray ? outputs : [outputs];
-          const outputSymbolicTensors = this.retrieveSymbolicTensors(outputNames);
-          // Format the input into a FeedDict.
-          const feedDict = new executor_FeedDict();
-          if (inputs instanceof dist["Tensor"]) {
-            inputs = [inputs];
-          }
-          if (Array.isArray(inputs)) {
-            if (inputs.length !== this.inputs.length) {
-              throw new ValueError(
-                `The number of inputs provided (${inputs.length}) ` +
-                  `does not match the number of inputs of this model ` +
-                  `(${this.inputs.length}).`
-              );
-            }
-            for (let i = 0; i < this.inputs.length; ++i) {
-              feedDict.add(this.inputs[i], inputs[i]);
-            }
-          } else {
-            for (const input of this.inputs) {
-              const tensorValue = inputs[input.name];
-              if (tensorValue == null) {
-                throw new ValueError(`No value is provided for the model's input ${input.name}`);
-              }
-              feedDict.add(input, tensorValue);
-            }
-          }
-          // Run execution.
-          const executeOutputs = execute(outputSymbolicTensors, feedDict);
-          return outputsIsArray ? executeOutputs : executeOutputs[0];
-        }
-        /**
-         * Retrieve the model's internal symbolic tensors from symbolic-tensor names.
-         */
-        retrieveSymbolicTensors(symbolicTensorNames) {
-          const outputSymbolicTensors = pyListRepeat(null, symbolicTensorNames.length);
-          let outputsRemaining = symbolicTensorNames.length;
-          for (const layer of this.layers) {
-            const layerOutputs = Array.isArray(layer.output) ? layer.output : [layer.output];
-            const layerOutputNames = layerOutputs.map((output) => output.name);
-            for (let i = 0; i < symbolicTensorNames.length; ++i) {
-              const index = layerOutputNames.indexOf(symbolicTensorNames[i]);
-              if (index !== -1) {
-                outputSymbolicTensors[i] = layerOutputs[index];
-                outputsRemaining--;
-              }
-              if (outputsRemaining === 0) {
-                break;
-              }
-            }
-            if (outputsRemaining === 0) {
-              break;
-            }
-          }
-          if (outputsRemaining > 0) {
-            const remainingNames = [];
-            outputSymbolicTensors.forEach((tensor, i) => {
-              if (tensor == null) {
-                remainingNames.push(symbolicTensorNames[i]);
-              }
-            });
-            throw new ValueError(
-              `Cannot find SymbolicTensors for output name(s): ` +
-                `${JSON.stringify(remainingNames)}`
-            );
-          }
-          return outputSymbolicTensors;
-        }
-        /**
-         * Helper method to loop over some data in batches.
-         *
-         * Porting Note: Not using the functional approach in the Python equivalent
-         *   due to the imperative backend.
-         * Porting Note: Does not support step mode currently.
-         *
-         * @param ins: input data
-         * @param batchSize: integer batch size.
-         * @param verbose: verbosity model
-         * @returns: Predictions as `tf.Tensor` (if a single output) or an `Array` of
-         *   `tf.Tensor` (if multipe outputs).
-         */
-        predictLoop(ins, batchSize = 32, verbose = false) {
-          return dist["tidy"](() => {
-            const numSamples = this.checkNumSamples(ins);
-            if (verbose) {
-              throw new NotImplementedError("Verbose predictLoop() is not implemented yet.");
-            }
-            // Sample-based predictions.
-            // Porting Note: Tensor currently does not support sliced assignments as
-            //   in numpy, e.g., x[1:3] = y. Therefore we use concatenation while
-            //   iterating over the batches.
-            const batches = makeBatches(numSamples, batchSize);
-            const outsBatches = this.outputs.map((output) => []);
-            // TODO(cais): Can the scope() be pushed down inside the for loop?
-            for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {
-              const batchOuts = dist["tidy"](() => {
-                const batchStart = batches[batchIndex][0];
-                const batchEnd = batches[batchIndex][1];
-                // TODO(cais): Take care of the case of the last element is a flag for
-                //   training/test.
-                const insBatch = sliceArrays(ins, batchStart, batchEnd);
-                // Construct the feeds for execute();
-                const feeds = [];
-                if (Array.isArray(insBatch)) {
-                  for (let i = 0; i < insBatch.length; ++i) {
-                    feeds.push({ key: this.inputs[i], value: insBatch[i] });
-                  }
-                } else {
-                  feeds.push({ key: this.inputs[0], value: insBatch });
-                }
-                const feedDict = new executor_FeedDict(feeds);
-                return execute(this.outputs, feedDict);
-              });
-              batchOuts.forEach((batchOut, i) => outsBatches[i].push(batchOut));
-            }
-            return singletonOrArray(outsBatches.map((batches) => dist["concat"](batches, 0)));
-          });
-        }
-        /**
-         * Generates output predictions for the input samples.
-         *
-         * Computation is done in batches.
-         *
-         * Note: the "step" mode of predict() is currently not supported.
-         *   This is because the TensorFlow.js core backend is imperative only.
-         *
-         * ```js
-         * const model = tf.sequential({
-         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
-         * });
-         * model.predict(tf.ones([8, 10]), {batchSize: 4}).print();
-         * ```
-         *
-         * @param x The input data, as a Tensor, or an `Array` of `tf.Tensor`s if
-         *   the model has multiple inputs.
-         * @param args A `ModelPredictArgs` object containing optional fields.
-         *
-         * @return Prediction results as a `tf.Tensor`(s).
-         *
-         * @exception ValueError In case of mismatch between the provided input data
-         *   and the model's expectations, or in case a stateful model receives a
-         *   number of samples that is not a multiple of the batch size.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        predict(x, args = {}) {
-          const xsRank2OrHigher = ensureTensorsRank2OrHigher(x);
-          checkInputData(xsRank2OrHigher, this.inputNames, this.feedInputShapes, false);
-          try {
-            // TODO(cais): Take care of stateful models.
-            //   if (this.stateful) ...
-            // TODO(cais): Take care of the learning_phase boolean flag.
-            //   if (this.useLearningPhase) ...
-            const batchSize = args.batchSize == null ? 32 : args.batchSize;
-            checkBatchSize(batchSize);
-            return this.predictLoop(xsRank2OrHigher, batchSize);
-          } finally {
-            disposeNewTensors(xsRank2OrHigher, x);
-          }
-        }
-        /**
-         * Returns predictions for a single batch of samples.
-         *
-         * ```js
-         * const model = tf.sequential({
-         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
-         * });
-         * model.predictOnBatch(tf.ones([8, 10])).print();
-         * ```
-         * @param x: Input samples, as a Tensor (for models with exactly one
-         *   input) or an array of Tensors (for models with more than one input).
-         * @return Tensor(s) of predictions
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes'} */
-        predictOnBatch(x) {
-          checkInputData(x, this.inputNames, this.feedInputShapes, true);
-          // TODO(cais): Take care of the learning_phase boolean flag.
-          //   if (this.useLearningPhase) ...
-          const batchSize = (Array.isArray(x) ? x[0] : x).shape[0];
-          return this.predictLoop(x, batchSize);
-        }
-        standardizeUserDataXY(x, y, checkBatchAxis = true, batchSize) {
-          // TODO(cais): Add sampleWeight, classWeight
-          if (this.optimizer_ == null) {
-            throw new RuntimeError(
-              "You must compile a model before training/testing. Use " +
-                "LayersModel.compile(modelCompileArgs)."
-            );
-          }
-          const outputShapes = [];
-          for (let i = 0; i < this.feedOutputShapes.length; ++i) {
-            const outputShape = this.feedOutputShapes[i];
-            const lossFn = this.feedLossFns[i];
-            if (lossFn === sparseCategoricalCrossentropy) {
-              outputShapes.push(outputShape.slice(0, outputShape.length - 1).concat([1]));
-            } else {
-              // Porting Note: Because of strong typing `lossFn` must be a function.
-              outputShapes.push(outputShape);
-            }
-          }
-          x = standardizeInputData(x, this.feedInputNames, this.feedInputShapes, false, "input");
-          y = standardizeInputData(y, this.feedOutputNames, outputShapes, false, "target");
-          // TODO(cais): Standardize sampleWeights & classWeights.
-          checkArrayLengths(x, y, null);
-          // TODO(cais): Check sampleWeights as well.
-          checkLossAndTargetCompatibility(y, this.feedLossFns, this.feedOutputShapes);
-          if (this.stateful && batchSize != null && batchSize > 0) {
-            if (x[0].shape[0] % batchSize !== 0) {
-              throw new ValueError(
-                `In a stateful network, you should only pass inputs with a ` +
-                  `number of samples that is divisible by the batch size ` +
-                  `${batchSize}. Found: ${x[0].shape[0]} sample(s).`
-              );
-            }
-          }
-          return [x, y];
-        }
-        async standardizeUserData(
-          x,
-          y,
-          sampleWeight,
-          classWeight,
-          checkBatchAxis = true,
-          batchSize
-        ) {
-          const [standardXs, standardYs] = this.standardizeUserDataXY(
-            x,
-            y,
-            checkBatchAxis,
-            batchSize
-          );
-          // TODO(cais): Handle sampleWeights.
-          if (sampleWeight != null) {
-            throw new Error("sample weight is not supported yet.");
-          }
-          let standardSampleWeights = null;
-          if (classWeight != null) {
-            const classWeights = standardizeClassWeights(classWeight, this.outputNames);
-            standardSampleWeights = [];
-            for (let i = 0; i < classWeights.length; ++i) {
-              standardSampleWeights.push(
-                await standardizeWeights(standardYs[i], null, classWeights[i])
-              );
-            }
-          }
-          // TODO(cais): Deal with the case of model.stateful == true.
-          return [standardXs, standardYs, standardSampleWeights];
-        }
-        /**
-         * Loop over some test data in batches.
-         * @param f A Function returning a list of tensors.
-         * @param ins Array of tensors to be fed to `f`.
-         * @param batchSize Integer batch size or `null` / `undefined`.
-         * @param verbose verbosity mode.
-         * @param steps Total number of steps (batches of samples) before
-         * declaring test finished. Ignored with the default value of `null` /
-         * `undefined`.
-         * @returns Array of Scalars.
-         */
-        testLoop(f, ins, batchSize, verbose = 0, steps) {
-          return dist["tidy"](() => {
-            const numSamples = this.checkNumSamples(ins, batchSize, steps, "steps");
-            const outs = [];
-            if (verbose > 0) {
-              throw new NotImplementedError("Verbose mode is not implemented yet.");
-            }
-            // TODO(cais): Use `indicesForConversionToDense' to prevent slow down.
-            if (steps != null) {
-              throw new NotImplementedError("steps mode in testLoop() is not implemented yet");
-            } else {
-              const batches = makeBatches(numSamples, batchSize);
-              const indexArray = Object(dist["tensor1d"])(range(0, numSamples));
-              for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {
-                const batchStart = batches[batchIndex][0];
-                const batchEnd = batches[batchIndex][1];
-                const batchIds = sliceAlongFirstAxis(indexArray, batchStart, batchEnd - batchStart);
-                // TODO(cais): In ins, train flag can be a number, instead of an
-                //   Tensor? Do we need to handle this in tfjs-layers?
-                const insBatch = sliceArraysByIndices(ins, batchIds);
-                const batchOuts = f(insBatch);
-                if (batchIndex === 0) {
-                  for (let i = 0; i < batchOuts.length; ++i) {
-                    outs.push(Object(dist["scalar"])(0));
-                  }
-                }
-                for (let i = 0; i < batchOuts.length; ++i) {
-                  const batchOut = batchOuts[i];
-                  outs[i] = dist["add"](outs[i], dist["mul"](batchEnd - batchStart, batchOut));
-                }
-              }
-              for (let i = 0; i < outs.length; ++i) {
-                outs[i] = dist["div"](outs[i], numSamples);
-              }
-            }
-            return outs;
-          });
-        }
-        getDedupedMetricsNames() {
-          const outLabels = this.metricsNames;
-          // Rename duplicated metrics names (can happen with an output layer
-          // shared among multiple dataflows).
-          const dedupedOutLabels = [];
-          for (let i = 0; i < outLabels.length; ++i) {
-            const label = outLabels[i];
-            let newLabel = label;
-            if (generic_utils_count(outLabels, label) > 1) {
-              const dupIndex = generic_utils_count(outLabels.slice(0, i), label);
-              newLabel += `_${dupIndex}`;
-            }
-            dedupedOutLabels.push(newLabel);
-          }
-          return dedupedOutLabels;
-        }
-        /**
-         * Creates a function that performs the following actions:
-         *
-         * 1. computes the losses
-         * 2. sums them to get the total loss
-         * 3. call the optimizer computes the gradients of the LayersModel's
-         *    trainable weights w.r.t. the total loss and update the variables
-         * 4. calculates the metrics
-         * 5. returns the values of the losses and metrics.
-         */
-        makeTrainFunction() {
-          return (data) => {
-            const lossValues = [];
-            const inputs = data.slice(0, this.inputs.length);
-            const targets = data.slice(
-              this.inputs.length,
-              this.inputs.length + this.outputs.length
-            );
-            const sampleWeights = data.slice(
-              this.inputs.length + this.outputs.length,
-              this.inputs.length + this.outputs.length * 2
-            );
-            const metricsValues = [];
-            // Create a function that computes the total loss based on the
-            // inputs. This function is used for obtaining gradients through
-            // backprop.
-            const totalLossFunction = () => {
-              const feeds = [];
-              for (let i = 0; i < this.inputs.length; ++i) {
-                feeds.push({ key: this.inputs[i], value: inputs[i] });
-              }
-              const feedDict = new executor_FeedDict(feeds);
-              const outputs = execute(this.outputs, feedDict, { training: true });
-              // TODO(cais): Take care of the case of multiple outputs from a
-              //   single layer?
-              let totalLoss;
-              for (let i = 0; i < this.lossFunctions.length; ++i) {
-                const lossFunction = this.lossFunctions[i];
-                let loss = lossFunction(targets[i], outputs[i]);
-                if (sampleWeights[i] != null) {
-                  loss = computeWeightedLoss(loss, sampleWeights[i]);
-                }
-                // TODO(cais): push Scalar instead.
-                const meanLoss = dist["mean"](loss);
-                // TODO(cais): Use a scope() instead, to avoid ownership.
-                lossValues.push(meanLoss);
-                if (i === 0) {
-                  totalLoss = loss;
-                } else {
-                  totalLoss = dist["add"](totalLoss, loss);
-                }
-              }
-              // Compute the metrics.
-              // TODO(cais): These should probably be calculated outside
-              //   totalLossFunction to benefit speed?
-              for (let i = 0; i < this.metricsTensors.length; ++i) {
-                let weightedMetric;
-                if (this.outputs.length > 1 && i < this.outputs.length) {
-                  weightedMetric = lossValues[i];
-                } else {
-                  const metric = this.metricsTensors[i][0];
-                  const outputIndex = this.metricsTensors[i][1];
-                  weightedMetric = dist["mean"](metric(targets[outputIndex], outputs[outputIndex]));
-                }
-                dist["keep"](weightedMetric);
-                // TODO(cais): Use a scope() instead, to avoid ownership.
-                metricsValues.push(weightedMetric);
-              }
-              totalLoss = dist["mean"](totalLoss);
-              // Add regularizer penalties.
-              this.calculateLosses().forEach((regularizerLoss) => {
-                totalLoss = dist["add"](totalLoss, regularizerLoss);
-              });
-              return totalLoss;
-            };
-            const variables = this.collectedTrainableWeights.map((param) => param.read());
-            const returnCost = true;
-            const totalLossValue = this.optimizer_.minimize(
-              totalLossFunction,
-              returnCost,
-              variables
-            );
-            return [totalLossValue].concat(metricsValues);
-          };
-        }
-        /**
-         * Create a function which, when invoked with an array of `tf.Tensor`s as a
-         * batch of inputs, returns the prespecified loss and metrics of the model
-         * under the batch of input data.
-         */
-        makeTestFunction() {
-          this.testFunction = (data) => {
-            return dist["tidy"](() => {
-              const valOutputs = [];
-              let totalLoss;
-              const inputs = data.slice(0, this.inputs.length);
-              const targets = data.slice(
-                this.inputs.length,
-                this.inputs.length + this.outputs.length
-              );
-              const feeds = [];
-              for (let i = 0; i < this.inputs.length; ++i) {
-                feeds.push({ key: this.inputs[i], value: inputs[i] });
-              }
-              const feedDict = new executor_FeedDict(feeds);
-              const outputs = execute(this.outputs, feedDict);
-              // Compute total loss.
-              for (let i = 0; i < this.lossFunctions.length; ++i) {
-                const lossFunction = this.lossFunctions[i];
-                // TODO(cais): Add sample weighting and replace the simple
-                // averaging.
-                const loss = dist["mean"](lossFunction(targets[i], outputs[i]));
-                if (i === 0) {
-                  totalLoss = loss;
-                } else {
-                  totalLoss = dist["add"](totalLoss, loss);
-                }
-                valOutputs.push(totalLoss);
-              }
-              // Compute the metrics.
-              for (let i = 0; i < this.metricsTensors.length; ++i) {
-                const metric = this.metricsTensors[i][0];
-                const outputIndex = this.metricsTensors[i][1];
-                // TODO(cais): Replace K.mean() with a proper weighting function.
-                const meanMetric = dist["mean"](metric(targets[outputIndex], outputs[outputIndex]));
-                valOutputs.push(meanMetric);
-              }
-              return valOutputs;
-            });
-          };
-        }
-        /**
-         * Trains the model for a fixed number of epochs (iterations on a
-         * dataset).
-         *
-         * ```js
-         * const model = tf.sequential({
-         *     layers: [tf.layers.dense({units: 1, inputShape: [10]})]
-         * });
-         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
-         * for (let i = 1; i < 5 ; ++i) {
-         *   const h = await model.fit(tf.ones([8, 10]), tf.ones([8, 1]), {
-         *       batchSize: 4,
-         *       epochs: 3
-         *   });
-         *   console.log("Loss after Epoch " + i + " : " + h.history.loss[0]);
-         * }
-         * ```
-         *
-         * @param x `tf.Tensor` of training data, or an array of `tf.Tensor`s if the
-         * model has multiple inputs. If all inputs in the model are named, you
-         * can also pass a dictionary mapping input names to `tf.Tensor`s.
-         * @param y `tf.Tensor` of target (label) data, or an array of `tf.Tensor`s if
-         * the model has multiple outputs. If all outputs in the model are named,
-         * you can also pass a dictionary mapping output names to `tf.Tensor`s.
-         * @param args A `ModelFitArgs`, containing optional fields.
-         *
-         * @return A `History` instance. Its `history` attribute contains all
-         *   information collected during training.
-         *
-         * @exception ValueError In case of mismatch between the provided input
-         * data and what the model expects.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        async fit(x, y, args = {}) {
-          return fitTensors(this, x, y, args);
-        }
-        // TODO(cais): Add code snippet below when it's possible to instantiate
-        //   actual dataset objects.
-        /**
-         * Trains the model using a dataset object.
-         *
-         * @param dataset A dataset object. Its `iterator()` method is expected
-         *   to generate a dataset iterator object, the `next()` method of which
-         *   is expected to produce data batches for training. The return value
-         *   of the `next()` call ought to contain a boolean `done` field and a
-         *   `value` field. The `value` field is expected to be an array of two
-         *   `tf.Tensor`s or an array of two nested `tf.Tensor` structures. The former
-         *   case is for models with exactly one input and one output (e.g..
-         *   a sequential model). The latter case is for models with multiple
-         *   inputs and/or multiple outputs.
-         *   Of the two items in the array, the first is the input feature(s) and
-         *   the second is the output target(s).
-         * @param args A `ModelFitDatasetArgs`, containing optional fields.
-         *
-         * @return A `History` instance. Its `history` attribute contains all
-         *   information collected during training.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        async fitDataset(dataset, args) {
-          return fitDataset(this, dataset, args);
-        }
-        /**
-         * Runs a single gradient update on a single batch of data.
-         *
-         * This method differs from `fit()` and `fitDataset()` in the following
-         * regards:
-         *   - It operates on exactly one batch of data.
-         *   - It returns only the loss and matric values, instead of
-         *     returning the batch-by-batch loss and metric values.
-         *   - It doesn't support fine-grained options such as verbosity and
-         *     callbacks.
-         *
-         * @param x Input data. It could be one of the following:
-         *   - A `tf.Tensor`, or an Array of `tf.Tensor`s (in case the model has
-         *     multiple inputs).
-         *   - An Object mapping input names to corresponding `tf.Tensor` (if the
-         *     model has named inputs).
-         * @param y Target darta. It could be either a `tf.Tensor` a multiple
-         *   `tf.Tensor`s. It should be consistent with `x`.
-         * @returns Training loss or losses (in case the model has
-         *   multiple outputs), along with metrics (if any), as numbers.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        async trainOnBatch(x, y) {
-          // TODO(cais): Support sampleWeight and classWeight.
-          // TODO(cais): Support Dataset objects.
-          const standardizeOut = await this.standardizeUserData(x, y);
-          const inputs = standardizeOut[0];
-          const targets = standardizeOut[1];
-          const trainFunction = this.makeTrainFunction();
-          const losses = trainFunction(inputs.concat(targets));
-          const lossValues = [];
-          for (const loss of losses) {
-            const v = await loss.data();
-            lossValues.push(v[0]);
-          }
-          dist["dispose"](losses);
-          return singletonOrArray(lossValues);
-        }
-        /**
-         * Extract weight values of the model.
-         *
-         * @param config: An instance of `io.SaveConfig`, which specifies
-         * model-saving options such as whether only trainable weights are to be
-         * saved.
-         * @returns A `NamedTensorMap` mapping original weight names (i.e.,
-         *   non-uniqueified weight names) to their values.
-         */
-        getNamedWeights(config) {
-          const namedWeights = [];
-          const trainableOnly = config != null && config.trainableOnly;
-          const weights = trainableOnly ? this.trainableWeights : this.weights;
-          const weightValues = this.getWeights(trainableOnly);
-          for (let i = 0; i < weights.length; ++i) {
-            if (trainableOnly && !weights[i].trainable) {
-              // Optionally skip non-trainable weights.
-              continue;
-            }
-            namedWeights.push({ name: weights[i].originalName, tensor: weightValues[i] });
-          }
-          return namedWeights;
-        }
-        /**
-         * Setter used for force stopping of LayersModel.fit() (i.e., training).
-         *
-         * Example:
-         *
-         * ```js
-         * const input = tf.input({shape: [10]});
-         * const output = tf.layers.dense({units: 1}).apply(input);
-         * const model = tf.model({inputs: [input], outputs: [output]});
-         * model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
-         * const xs = tf.ones([8, 10]);
-         * const ys = tf.zeros([8, 1]);
-         *
-         * const history = await model.fit(xs, ys, {
-         *   epochs: 10,
-         *   callbacks: {
-         *     onEpochEnd: async (epoch, logs) => {
-         *       if (epoch === 2) {
-         *         model.stopTraining = true;
-         *       }
-         *     }
-         *   }
-         * });
-         *
-         * // There should be only 3 values in the loss array, instead of 10
-         * values,
-         * // due to the stopping after 3 epochs.
-         * console.log(history.history.loss);
-         * ```
-         */
-        set stopTraining(stop) {
-          this.stopTraining_ = stop;
-        }
-        get stopTraining() {
-          return this.stopTraining_;
-        }
-        get optimizer() {
-          return this.optimizer_;
-        }
-        set optimizer(optimizer) {
-          if (this.optimizer_ !== optimizer) {
-            this.optimizer_ = optimizer;
-            this.isOptimizerOwned = false;
-          }
-        }
-        dispose() {
-          const result = super.dispose();
-          if (
-            result.refCountAfterDispose === 0 &&
-            this.optimizer != null &&
-            this.isOptimizerOwned
-          ) {
-            const numTensorsBeforeOptmizerDisposal = dist["memory"]().numTensors;
-            this.optimizer_.dispose();
-            result.numDisposedVariables +=
-              numTensorsBeforeOptmizerDisposal - dist["memory"]().numTensors;
-          }
-          return result;
-        }
-        getLossIdentifiers() {
-          let lossNames;
-          if (typeof this.loss === "string") {
-            lossNames = toSnakeCase(this.loss);
-          } else if (Array.isArray(this.loss)) {
-            for (const loss of this.loss) {
-              if (typeof loss !== "string") {
-                throw new Error("Serialization of non-string loss is not supported.");
-              }
-            }
-            lossNames = this.loss.map((name) => toSnakeCase(name));
-          } else {
-            const outputNames = Object.keys(this.loss);
-            lossNames = {};
-            const losses = this.loss;
-            for (const outputName of outputNames) {
-              if (typeof losses[outputName] === "string") {
-                lossNames[outputName] = toSnakeCase(losses[outputName]);
-              } else {
-                throw new Error("Serialization of non-string loss is not supported.");
-              }
-            }
-          }
-          return lossNames;
-        }
-        getMetricIdentifiers() {
-          if (typeof this.metrics === "string" || typeof this.metrics === "function") {
-            return [toSnakeCase(getLossOrMetricName(this.metrics))];
-          } else if (Array.isArray(this.metrics)) {
-            return this.metrics.map((metric) => toSnakeCase(getLossOrMetricName(metric)));
-          } else {
-            const metricsIdentifiers = {};
-            for (const key in this.metrics) {
-              metricsIdentifiers[key] = toSnakeCase(getLossOrMetricName(this.metrics[key]));
-            }
-            return metricsIdentifiers;
-          }
-        }
-        getTrainingConfig() {
-          return {
-            loss: this.getLossIdentifiers(),
-            metrics: this.getMetricIdentifiers(),
-            optimizer_config: {
-              class_name: this.optimizer.getClassName(),
-              config: this.optimizer.getConfig(),
-            },
-          };
-          // TODO(cais): Add weight_metrics when they are supported.
-          // TODO(cais): Add sample_weight_mode when it's supported.
-          // TODO(cais): Add loss_weights when it's supported.
-        }
-        loadTrainingConfig(trainingConfig) {
-          if (trainingConfig.weighted_metrics != null) {
-            throw new Error("Loading weight_metrics is not supported yet.");
-          }
-          if (trainingConfig.loss_weights != null) {
-            throw new Error("Loading loss_weights is not supported yet.");
-          }
-          if (trainingConfig.sample_weight_mode != null) {
-            throw new Error("Loading sample_weight_mode is not supported yet.");
-          }
-          const tsConfig = convertPythonicToTs(trainingConfig.optimizer_config);
-          const optimizer = deserialize(tsConfig);
-          let loss;
-          if (typeof trainingConfig.loss === "string") {
-            loss = toCamelCase(trainingConfig.loss);
-          } else if (Array.isArray(trainingConfig.loss)) {
-            loss = trainingConfig.loss.map((lossEntry) => toCamelCase(lossEntry));
-          } else if (trainingConfig.loss != null) {
-            loss = {};
-            for (const key in trainingConfig.loss) {
-              loss[key] = toCamelCase(trainingConfig.loss[key]);
-            }
-          }
-          let metrics;
-          if (Array.isArray(trainingConfig.metrics)) {
-            metrics = trainingConfig.metrics.map((metric) => toCamelCase(metric));
-          } else if (trainingConfig.metrics != null) {
-            metrics = {};
-            for (const key in trainingConfig.metrics) {
-              metrics[key] = toCamelCase(trainingConfig.metrics[key]);
-            }
-          }
-          this.compile({ loss, metrics, optimizer });
-        }
-        /**
-         * Save the configuration and/or weights of the LayersModel.
-         *
-         * An `IOHandler` is an object that has a `save` method of the proper
-         * signature defined. The `save` method manages the storing or
-         * transmission of serialized data ("artifacts") that represent the
-         * model's topology and weights onto or via a specific medium, such as
-         * file downloads, local storage, IndexedDB in the web browser and HTTP
-         * requests to a server. TensorFlow.js provides `IOHandler`
-         * implementations for a number of frequently used saving mediums, such as
-         * `tf.io.browserDownloads` and `tf.io.browserLocalStorage`. See `tf.io`
-         * for more details.
-         *
-         * This method also allows you to refer to certain types of `IOHandler`s
-         * as URL-like string shortcuts, such as 'localstorage://' and
-         * 'indexeddb://'.
-         *
-         * Example 1: Save `model`'s topology and weights to browser [local
-         * storage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage);
-         * then load it back.
-         *
-         * ```js
-         * const model = tf.sequential(
-         *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
-         * console.log('Prediction from original model:');
-         * model.predict(tf.ones([1, 3])).print();
-         *
-         * const saveResults = await model.save('localstorage://my-model-1');
-         *
-         * const loadedModel = await tf.loadLayersModel('localstorage://my-model-1');
-         * console.log('Prediction from loaded model:');
-         * loadedModel.predict(tf.ones([1, 3])).print();
-         * ```
-         *
-         * Example 2. Saving `model`'s topology and weights to browser
-         * [IndexedDB](https://developer.mozilla.org/en-US/docs/Web/API/IndexedDB_API);
-         * then load it back.
-         *
-         * ```js
-         * const model = tf.sequential(
-         *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
-         * console.log('Prediction from original model:');
-         * model.predict(tf.ones([1, 3])).print();
-         *
-         * const saveResults = await model.save('indexeddb://my-model-1');
-         *
-         * const loadedModel = await tf.loadLayersModel('indexeddb://my-model-1');
-         * console.log('Prediction from loaded model:');
-         * loadedModel.predict(tf.ones([1, 3])).print();
-         * ```
-         *
-         * Example 3. Saving `model`'s topology and weights as two files
-         * (`my-model-1.json` and `my-model-1.weights.bin`) downloaded from
-         * browser.
-         *
-         * ```js
-         * const model = tf.sequential(
-         *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
-         * const saveResults = await model.save('downloads://my-model-1');
-         * ```
-         *
-         * Example 4. Send  `model`'s topology and weights to an HTTP server.
-         * See the documentation of `tf.io.http` for more details
-         * including specifying request parameters and implementation of the
-         * server.
-         *
-         * ```js
-         * const model = tf.sequential(
-         *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
-         * const saveResults = await model.save('http://my-server/model/upload');
-         * ```
-         *
-         * @param handlerOrURL An instance of `IOHandler` or a URL-like,
-         * scheme-based string shortcut for `IOHandler`.
-         * @param config Options for saving the model.
-         * @returns A `Promise` of `SaveResult`, which summarizes the result of
-         * the saving, such as byte sizes of the saved artifacts for the model's
-         *   topology and weight values.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes', ignoreCI: true}
-         */
-        async save(handlerOrURL, config) {
-          if (typeof handlerOrURL === "string") {
-            const handlers = dist["io"].getSaveHandlers(handlerOrURL);
-            if (handlers.length === 0) {
-              throw new ValueError(`Cannot find any save handlers for URL '${handlerOrURL}'`);
-            } else if (handlers.length > 1) {
-              throw new ValueError(
-                `Found more than one (${handlers.length}) save handlers for ` +
-                  `URL '${handlerOrURL}'`
-              );
-            }
-            handlerOrURL = handlers[0];
-          }
-          if (handlerOrURL.save == null) {
-            throw new ValueError(
-              "LayersModel.save() cannot proceed because the IOHandler " +
-                "provided does not have the `save` attribute defined."
-            );
-          }
-          const weightDataAndSpecs = await dist["io"].encodeWeights(this.getNamedWeights(config));
-          const returnString = false;
-          const unusedArg = null;
-          const modelConfig = this.toJSON(unusedArg, returnString);
-          const modelArtifacts = {
-            modelTopology: modelConfig,
-            format: LAYERS_MODEL_FORMAT_NAME,
-            generatedBy: `TensorFlow.js tfjs-layers v${version}`,
-            convertedBy: null,
-          };
-          const includeOptimizer = config == null ? false : config.includeOptimizer;
-          if (includeOptimizer && this.optimizer != null) {
-            modelArtifacts.trainingConfig = this.getTrainingConfig();
-            const weightType = "optimizer";
-            const { data: optimizerWeightData, specs: optimizerWeightSpecs } = await dist[
-              "io"
-            ].encodeWeights(await this.optimizer.getWeights(), weightType);
-            weightDataAndSpecs.specs.push(...optimizerWeightSpecs);
-            weightDataAndSpecs.data = dist["io"].concatenateArrayBuffers([
-              weightDataAndSpecs.data,
-              optimizerWeightData,
-            ]);
-          }
-          if (this.userDefinedMetadata != null) {
-            // Check serialized size of user-defined metadata.
-            const checkSize = true;
-            checkUserDefinedMetadata(this.userDefinedMetadata, this.name, checkSize);
-            modelArtifacts.userDefinedMetadata = this.userDefinedMetadata;
-          }
-          modelArtifacts.weightData = weightDataAndSpecs.data;
-          modelArtifacts.weightSpecs = weightDataAndSpecs.specs;
-          return handlerOrURL.save(modelArtifacts);
-        }
-        /**
-         * Set user-defined metadata.
-         *
-         * The set metadata will be serialized together with the topology
-         * and weights of the model during `save()` calls.
-         *
-         * @param setUserDefinedMetadata
-         */
-        setUserDefinedMetadata(userDefinedMetadata) {
-          checkUserDefinedMetadata(userDefinedMetadata, this.name);
-          this.userDefinedMetadata = userDefinedMetadata;
-        }
-        /**
-         * Get user-defined metadata.
-         *
-         * The metadata is supplied via one of the two routes:
-         *   1. By calling `setUserDefinedMetadata()`.
-         *   2. Loaded during model loading (if the model is constructed
-         *      via `tf.loadLayersModel()`.)
-         *
-         * If no user-defined metadata is available from either of the
-         * two routes, this function will return `undefined`.
-         */
-        getUserDefinedMetadata() {
-          return this.userDefinedMetadata;
-        }
-      }
-      // The class name is 'Model' rather than 'LayersModel' for backwards
-      // compatibility since this class name shows up in the serialization format.
-      /** @nocollapse */
-      training_LayersModel.className = "Model";
-      dist["serialization"].registerClass(training_LayersModel);
-      //# sourceMappingURL=training.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/models.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original source keras/models.py */
-
-      /**
-       * Parses a JSON model configuration file and returns a model instance.
-       *
-       * ```js
-       * // This example shows how to serialize a model using `toJSON()` and
-       * // deserialize it as another model using `tf.models.modelFromJSON()`.
-       * // Note: this example serializes and deserializes only the topology
-       * // of the model; the weights of the loaded model will be different
-       * // from those of the the original model, due to random weight
-       * // initialization.
-       * // To load the topology and weights of a model, use `tf.loadLayersModel()`.
-       * const model1 = tf.sequential();
-       * model1.add(tf.layers.repeatVector({inputShape: [2], n: 4}));
-       * // Serialize `model1` as a JSON object.
-       * const model1JSON = model1.toJSON(null, false);
-       * model1.summary();
-       *
-       * const model2 = await tf.models.modelFromJSON(model1JSON);
-       * model2.summary();
-       * ```
-       *
-       *  @param modelAndWeightsConfig JSON object or string encoding a model and
-       *       weights configuration. It can also be only the topology JSON of the
-       *       model, in which case the weights will not be loaded.
-       *  @param custom_objects Optional dictionary mapping names
-       *       (strings) to custom classes or functions to be
-       *       considered during deserialization.
-       * @returns A TensorFlow.js Layers `tf.LayersModel` instance (uncompiled).
-       */
-      async function modelFromJSON(modelAndWeightsConfig, customObjects) {
-        if (!("modelTopology" in modelAndWeightsConfig)) {
-          modelAndWeightsConfig = { modelTopology: modelAndWeightsConfig };
-        }
-        modelAndWeightsConfig = modelAndWeightsConfig;
-        let modelTopology = modelAndWeightsConfig.modelTopology;
-        if (modelTopology["model_config"] != null) {
-          // If the model-topology JSON contains a 'model_config' field, then it is
-          // a full model JSON (e.g., from `keras.Model.save()`), which contains
-          // not only the model's architecture in its 'model_config' field, but
-          // additional information such as the model's optimizer. We use only the
-          // 'model_config' field currently.
-          modelTopology = modelTopology["model_config"];
-        }
-        const tsConfig = convertPythonicToTs(modelTopology);
-        const model = deserialize(tsConfig, customObjects);
-        if (modelAndWeightsConfig.weightsManifest != null) {
-          // Load the weight values keyed by the original tensor names in the model
-          // file that was loaded.  These should match the keys of the weight
-          // manifest.
-          const weightValues = await dist["io"].loadWeights(
-            modelAndWeightsConfig.weightsManifest,
-            modelAndWeightsConfig.pathPrefix,
-            model.weights.map((weight) => weight.originalName)
-          );
-          // Map the weights to the unique tensor names generated during model loading
-          const uniqueWeightValues = {};
-          for (const weight of model.weights) {
-            uniqueWeightValues[weight.originalName] = weightValues[weight.originalName];
-          }
-          model.loadWeights(uniqueWeightValues);
-          // Dispose temporary weight values.
-          Object(dist["dispose"])(weightValues);
-        }
-        return model;
-      }
-      /**
-       * Load a model, including its topology and optionally weights.  See the
-       * Tutorial named "How to import a Keras Model" for usage examples.
-       *
-       * Example 1: Save `model`'s topology and weights to browser [local
-       * storage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage);
-       * then load it back.
-       *
-       * ```js
-       * const model = tf.sequential(
-       *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
-       * console.log('Prediction from original model:');
-       * model.predict(tf.ones([1, 3])).print();
-       *
-       * const saveResults = await model.save('localstorage://my-model-1');
-       *
-       * const loadedModel = await tf.loadLayersModel('localstorage://my-model-1');
-       * console.log('Prediction from loaded model:');
-       * loadedModel.predict(tf.ones([1, 3])).print();
-       * ```
-       *
-       * Example 2. Saving `model`'s topology and weights to browser
-       * [IndexedDB](https://developer.mozilla.org/en-US/docs/Web/API/IndexedDB_API);
-       * then load it back.
-       *
-       * ```js
-       * const model = tf.sequential(
-       *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
-       * console.log('Prediction from original model:');
-       * model.predict(tf.ones([1, 3])).print();
-       *
-       * const saveResults = await model.save('indexeddb://my-model-1');
-       *
-       * const loadedModel = await tf.loadLayersModel('indexeddb://my-model-1');
-       * console.log('Prediction from loaded model:');
-       * loadedModel.predict(tf.ones([1, 3])).print();
-       * ```
-       *
-       * Example 3. Load a model from user-selected files from HTML
-       * [file input
-       * elements](https://developer.mozilla.org/en-US/docs/Web/HTML/Element/input/file).
-       *
-       * ```js
-       * // Note: this code snippet will not work without the HTML elements in the
-       * //   page
-       * const jsonUpload = document.getElementById('json-upload');
-       * const weightsUpload = document.getElementById('weights-upload');
-       *
-       * const model = await tf.loadLayersModel(
-       *     tf.io.browserFiles([jsonUpload.files[0], weightsUpload.files[0]]));
-       * ```
-       *
-       * Example 4. Load a model from an HTTP server.
-       *
-       * ```js
-       * const model = await
-       *     tf.loadLayersModel('https://storage.googleapis.com/tfjs-models/tfjs/iris_v1/model.json');
-       * model.summary();
-       * ```
-       *
-       * @param pathOrIOHandler Can be either of the two formats
-       *   1. A string path to the `ModelAndWeightsConfig` JSON describing
-       *      the model in the canonical TensorFlow.js format. This path will be
-       *      interpreted as a relative HTTP path, to which `fetch` will be used to
-       *      request the model topology and weight manifest JSON.
-       *      The content of the JSON file is assumed to be a JSON object with the
-       *      following fields and values:
-       *      - 'modelTopology': A JSON object that can be either of:
-       *        1. a model architecture JSON consistent with the format of the return
-       *            value of `keras.Model.to_json()`
-       *        2. a full model JSON in the format of `keras.models.save_model()`.
-       *      - 'weightsManifest': A TensorFlow.js weights manifest.
-       *      See the Python converter function `save_model()` for more details.
-       *      It is also assumed that model weights can be accessed from relative
-       *      paths described by the `paths` fields in weights manifest.
-       *   2. An `tf.io.IOHandler` object that loads model artifacts with its `load`
-       *      method.
-       * @param options Optional configuration arguments for the model loading,
-       *   including:
-       *   - `strict`: Require that the provided weights exactly match those required
-       *     by the layers.  Default true.  Passing false means that both extra
-       *     weights and missing weights will be silently ignored.
-       *   - `onProgress`: A progress callback of the form:
-       *     `(fraction: number) => void`. This callback can be used to monitor the
-       *     model-loading process.
-       * @returns A `Promise` of `tf.LayersModel`, with the topology and weights
-       *     loaded.
-       */
-      async function loadLayersModelInternal(pathOrIOHandler, options) {
-        if (options == null) {
-          options = {};
-        }
-        if (typeof pathOrIOHandler === "string") {
-          const handlers = dist["io"].getLoadHandlers(pathOrIOHandler, options);
-          if (handlers.length === 0) {
-            // For backward compatibility: if no load handler can be found,
-            // assume it is a relative http path.
-            // TODO(cais): Reformat the args into a single `LoadOptions` once the core
-            // is refactored.
-            handlers.push(dist["io"].browserHTTPRequest(pathOrIOHandler, options));
-          } else if (handlers.length > 1) {
-            throw new ValueError(
-              `Found more than one (${handlers.length}) load handlers for ` +
-                `URL '${pathOrIOHandler}'`
-            );
-          }
-          pathOrIOHandler = handlers[0];
-        }
-        return loadLayersModelFromIOHandler(pathOrIOHandler, undefined, options);
-      }
-      /**
-       * Load a model and optionally its weights, using an IOHandler object.
-       *
-       * @param handler The instance of `IOHandler` to be used during the model
-       *   loading.
-       * @param customObjects Any optional custom objects to be used during model
-       *   loading.
-       * @param strict Whether the weight loading will be done in strict mode.
-       *   Default: `true`.
-       */
-      async function loadLayersModelFromIOHandler(handler, customObjects, options) {
-        if (options == null) {
-          options = {};
-        }
-        if (handler.load == null) {
-          throw new ValueError(
-            "Cannot proceed with model loading because the IOHandler provided " +
-              "does not have the `load` method implemented."
-          );
-        }
-        const artifacts = await handler.load();
-        let modelTopology = artifacts.modelTopology;
-        if (modelTopology["model_config"] != null) {
-          modelTopology = modelTopology["model_config"];
-        }
-        const strict = options.strict == null ? true : options.strict;
-        // If weights are provided and the weight-loading mode is strict, use
-        // fast weight initialization. This skips costly initializers such as
-        // 'orthogonal' and saves unnecessary computation in cases where
-        // the initialized weight values will immediately be overwritten by
-        // loaded weight values.
-        const fastWeightInit =
-          artifacts.weightData != null && artifacts.weightSpecs != null && strict;
-        const model = deserialize(
-          convertPythonicToTs(modelTopology),
-          customObjects,
-          fastWeightInit
-        );
-        const trainingConfig = artifacts.trainingConfig;
-        if (trainingConfig != null) {
-          model.loadTrainingConfig(trainingConfig);
-        }
-        if (artifacts.userDefinedMetadata != null) {
-          model.setUserDefinedMetadata(artifacts.userDefinedMetadata);
-        }
-        // If weightData is present, load the weights into the model.
-        if (artifacts.weightData != null) {
-          // Loading weights requires weightSpecs.
-          if (artifacts.weightSpecs == null) {
-            throw new ValueError(
-              "LayersModel artifacts contains weight data, but not weight specs. " +
-                "Therefore loading of weights cannot proceed."
-            );
-          }
-          const { modelWeights, optimizerWeights } = decodeModelAndOptimizerWeights(
-            artifacts.weightData,
-            artifacts.weightSpecs
-          );
-          model.loadWeights(modelWeights, strict);
-          if (model.optimizer != null && optimizerWeights.length > 0) {
-            await model.optimizer.setWeights(optimizerWeights);
-          }
-          // Dispose temporary weight values.
-          Object(dist["dispose"])(modelWeights);
-          Object(dist["dispose"])(optimizerWeights.map((w) => w.tensor));
-        }
-        return model;
-      }
-      function decodeModelAndOptimizerWeights(buffer, specs) {
-        const name2Tensor = dist["io"].decodeWeights(buffer, specs);
-        const modelWeights = {};
-        const optimizerWeights = [];
-        specs.forEach((spec) => {
-          if (spec.group === "optimizer") {
-            optimizerWeights.push({ name: spec.name, tensor: name2Tensor[spec.name] });
-          } else {
-            modelWeights[spec.name] = name2Tensor[spec.name];
-          }
-        });
-        return { modelWeights, optimizerWeights };
-      }
-      /**
-       * A model with a stack of layers, feeding linearly from one to the next.
-       *
-       * `tf.sequential` is a factory function that creates an instance of
-       * `tf.Sequential`.
-       *
-       * ```js
-       *  // Define a model for linear regression.
-       *  const model = tf.sequential();
-       *  model.add(tf.layers.dense({units: 1, inputShape: [1]}));
-       *
-       *  // Prepare the model for training: Specify the loss and the optimizer.
-       *  model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
-       *
-       *  // Generate some synthetic data for training.
-       *  const xs = tf.tensor2d([1, 2, 3, 4], [4, 1]);
-       *  const ys = tf.tensor2d([1, 3, 5, 7], [4, 1]);
-       *
-       *  // Train the model using the data then do inference on a data point the
-       *  // model hasn't seen:
-       *  await model.fit(xs, ys);
-       *  model.predict(tf.tensor2d([5], [1, 1])).print();
-       * ```
-       */
-      /** @doc {heading: 'Models', subheading: 'Classes'} */
-      class models_Sequential extends training_LayersModel {
-        constructor(args) {
-          super({ inputs: [], outputs: [] });
-          args = args || {};
-          this.trainable = true;
-          this.built = false;
-          // Set model name.
-          this.name = args.name != null ? args.name : getUid("sequential_");
-          // Add to the model any layers passed to the constructor.
-          if (args.layers != null) {
-            for (const layer of args.layers) {
-              this.add(layer);
-            }
-          }
-        }
-        // Helper function to Sequential.add  Throws if the new output shape will be
-        // invalid.
-        checkShape(layer) {
-          const shape = layer.inboundNodes[0].outputTensors[0].shape;
-          if (shape.some((x) => x < 0)) {
-            throw new ValueError(
-              "Negative dimension size caused by adding layer " +
-                `${layer.name} with input shape [` +
-                `${layer.inboundNodes[0].inputTensors[0].shape}]`
-            );
-          }
-        }
-        /**
-         * Adds a layer instance on top of the layer stack.
-         *
-         * ```js
-         *  const model = tf.sequential();
-         *  model.add(tf.layers.dense({units: 8, inputShape: [1]}));
-         *  model.add(tf.layers.dense({units: 4, activation: 'relu6'}));
-         *  model.add(tf.layers.dense({units: 1, activation: 'relu6'}));
-         *  // Note that the untrained model is random at this point.
-         *  model.predict(tf.randomNormal([10, 1])).print();
-         * ```
-         * @param layer Layer instance.
-         *
-         * @exception ValueError In case the `layer` argument does not know its
-         * input shape.
-         * @exception ValueError In case the `layer` argument has multiple output
-         *   tensors, or is already connected somewhere else (forbidden in
-         *   `Sequential` models).
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes'} */
-        add(layer) {
-          const isLayerModelInstance =
-            layer instanceof models_Sequential || layer instanceof training_LayersModel;
-          let modelLayer;
-          if (isLayerModelInstance) {
-            modelLayer = layer;
-            if (modelLayer.outputs.length !== 1) {
-              throw new ValueError(
-                "All layers in a Sequential model " +
-                  "should have a single output tensor. " +
-                  "For multi-output layers, " +
-                  "use the functional API."
-              );
-            }
-            if (modelLayer.inputs.length !== 1) {
-              throw new ValueError(
-                "All layers in a Sequential model " +
-                  "should have a single input tensor. " +
-                  "For multi-input layers, " +
-                  "use the functional API."
-              );
-            }
-          }
-          if (this.outputs.length === 0) {
-            // first layer in model: check that it is an input layer
-            if (layer.inboundNodes.length === 0) {
-              // create an input layer
-              if (layer.batchInputShape == null) {
-                throw new ValueError(
-                  "The first layer in a Sequential model must " +
-                    "get an `inputShape` or `batchInputShape` argument."
-                );
-              }
-              // Instantiate the input layer.
-              const x = Input({
-                batchShape: layer.batchInputShape,
-                dtype: layer.dtype,
-                name: layer.name + "_input",
-              });
-              // This will build the current layer and create the node connecting
-              // the current layer to the input layer we just created.
-              layer.apply(x);
-            }
-            if (isLayerModelInstance) {
-              this.outputs = modelLayer.outputs;
-              this.inputs = modelLayer.inputs;
-            } else {
-              if (layer.inboundNodes.length !== 1) {
-                throw new ValueError(
-                  "A layer added to a Sequential model must not already be " +
-                    `connected somewhere else. LayersModel received layer ${layer.name} ` +
-                    `which has ${layer.inboundNodes.length} pre-existing inbound ` +
-                    "connections."
-                );
-              }
-              if (layer.inboundNodes[0].outputTensors.length !== 1) {
-                throw new ValueError(
-                  "All layers in a Sequential model " +
-                    "should have a single output tensor. " +
-                    "For multi-output layers, " +
-                    "use the functional API."
-                );
-              }
-              this.checkShape(layer);
-              this.outputs = [layer.inboundNodes[0].outputTensors[0]];
-              this.inputs = getSourceInputs(this.outputs[0]);
-            }
-            this.inboundNodes = [];
-            // We create an input node, which we will keep updated
-            // as we add more layers.
-            // (This call has side effects.)
-            // tslint:disable-next-line:no-unused-expression
-            new Node({
-              outboundLayer: this,
-              inboundLayers: [],
-              nodeIndices: [],
-              tensorIndices: [],
-              inputTensors: this.inputs,
-              outputTensors: this.outputs,
-              // no model-level masking for now
-              inputMasks: pyListRepeat(null, this.inputs.length),
-              outputMasks: [null],
-              inputShapes: this.inputs.map((x) => x.shape),
-              outputShapes: this.outputs[0].shape,
-            });
-          } else {
-            const outputTensor = layer.apply(this.outputs[0]);
-            if (Array.isArray(outputTensor)) {
-              throw new TypeError(
-                "All layers in a Sequential model " +
-                  "should have a single output tensor. " +
-                  "For multi-output layers, " +
-                  "use the functional API."
-              );
-            }
-            this.checkShape(layer);
-            this.outputs = [outputTensor];
-            // update self.inbound_nodes
-            this.inboundNodes[0].outputTensors = this.outputs;
-            this.inboundNodes[0].outputShapes = [this.outputs[0].shape];
-          }
-          this.layers.push(layer);
-          this.built = false;
-        }
-        /**
-         * Removes the last layer in the model.
-         *
-         * @exception TypeError if there are no layers in the model.
-         */
-        pop() {
-          if (this.layers.length === 0) {
-            throw new TypeError("There are no layers in the model.");
-          }
-          this.layers.pop();
-          if (this.layers.length === 0) {
-            this.outputs = [];
-            this.inboundNodes = [];
-            this.outboundNodes = [];
-          } else {
-            const lastLayerIndex = this.layers.length - 1;
-            this.layers[lastLayerIndex].outboundNodes = [];
-            this.outputs = [this.layers[lastLayerIndex].output];
-            // update self.inbound_nodes
-            this.inboundNodes[0].outputTensors = this.outputs;
-            this.inboundNodes[0].outputShapes = [this.outputs[0].shape];
-          }
-        }
-        call(inputs, kwargs) {
-          if (this.model == null) {
-            this.build();
-          }
-          return this.model.call(inputs, kwargs);
-        }
-        build(inputShape) {
-          // Call `getExactlyOneShape` without using its return value,
-          // to verify that exactly one input shape is provided.
-          getExactlyOneShape(inputShape);
-          if (this.inputs.length === 0 || this.outputs.length === 0) {
-            throw new TypeError(
-              "Sequential model cannot be built: model is empty." + " Add some layers first."
-            );
-          }
-          // actually create the model
-          this.model = new training_LayersModel({
-            inputs: this.inputs,
-            outputs: this.outputs[0],
-            name: this.name + "_model",
-          });
-          this.model.trainable = this.trainable;
-          // mirror model attributes
-          this.supportsMasking = this.model.supportsMasking;
-          // TODO(michaelterry): Add caches
-          this.inputLayers = this.model.inputLayers;
-          this.inputLayersNodeIndices = this.model.inputLayersNodeIndices;
-          this.inputLayersTensorIndices = this.model.inputLayersTensorIndices;
-          this.outputLayers = this.model.outputLayers;
-          this.outputLayersNodeIndices = this.model.outputLayersNodeIndices;
-          this.outputLayersTensorIndices = this.model.outputLayersTensorIndices;
-          this.nodesByDepth = this.model.nodesByDepth;
-          this.containerNodes = this.model.containerNodes;
-          this.outputNames = this.model.outputNames;
-          this.inputNames = this.model.inputNames;
-          // TODO(michaelterry): Add feedInputNames, feedInputs, if needed.
-          // TODO(michaelterry): Add callbackModel if needed.
-          this.built = true;
-        }
-        countParams() {
-          if (!this.built) {
-            this.build();
-          }
-          return super.countParams();
-        }
-        /**
-         * Print a text summary of the Sequential model's layers.
-         *
-         * The summary includes
-         * - Name and type of all layers that comprise the model.
-         * - Output shape(s) of the layers
-         * - Number of weight parameters of each layer
-         * - The total number of trainable and non-trainable parameters of the
-         * model.
-         *
-         * ```js
-         * const model = tf.sequential();
-         * model.add(
-         *     tf.layers.dense({units: 100, inputShape: [10], activation: 'relu'}));
-         * model.add(tf.layers.dense({units: 1, activation: 'sigmoid'}));
-         *
-         * model.summary();
-         * ```
-         *
-         * @param lineLength Custom line length, in number of characters.
-         * @param positions Custom widths of each of the columns, as either
-         *   fractions of `lineLength` (e.g., `[0.5, 0.75, 1]`) or absolute number
-         *   of characters (e.g., `[30, 50, 65]`). Each number corresponds to
-         *   right-most (i.e., ending) position of a column.
-         * @param printFn Custom print function. Can be used to replace the default
-         *   `console.log`. For example, you can use `x => {}` to mute the printed
-         *   messages in the console.
-         */
-        /** @doc {heading: 'Models', subheading: 'Classes'} */
-        summary(lineLength, positions, printFn = console.log) {
-          if (!this.built) {
-            this.build();
-          }
-          super.summary(lineLength, positions, printFn);
-        }
-        /**
-         * Sets the weights of the model.
-         *
-         * @param weights Should be a list of Tensors with shapes and types matching
-         *   the output of `model.getWeights()`.
-         */
-        setWeights(weights) {
-          if (this.model == null) {
-            this.build();
-          }
-          this.model.setWeights(weights);
-        }
-        /**
-         * Returns the loss value & metrics values for the model in test mode.
-         *
-         * Loss and metrics are specified during `compile()`, which needs to happen
-         * before calls to `evaluate()`.
-         *
-         * Computation is done in batches.
-         *
-         * ```js
-         * const model = tf.sequential({
-         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
-         * });
-         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
-         * const result = model.evaluate(tf.ones([8, 10]), tf.ones([8, 1]), {
-         *   batchSize: 4,
-         * });
-         * result.print();
-         * ```
-         *
-         * @param x `tf.Tensor` of test data, or an `Array` of `tf.Tensor`s if the
-         * model has multiple inputs.
-         * @param y `tf.Tensor` of target data, or an `Array` of `tf.Tensor`s if the
-         * model has multiple outputs.
-         * @param args A `ModelEvaluateConfig`, containing optional fields.
-         *
-         * @return `Scalar` test loss (if the model has a single output and no
-         *   metrics) or `Array` of `Scalar`s (if the model has multiple outputs
-         *   and/or metrics). The attribute `model.metricsNames`
-         *   will give you the display labels for the scalar outputs.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        evaluate(x, y, args = {}) {
-          if (!this.built) {
-            throw new RuntimeError("The model needs to be compiled before being used.");
-          }
-          return this.model.evaluate(x, y, args);
-        }
-        // TODO(cais): Add code snippet below once real dataset objects are
-        //   available.
-        /**
-         * Evaluate model using a dataset object.
-         *
-         * Note: Unlike `evaluate()`, this method is asynchronous (`async`);
-         *
-         * @param dataset A dataset object. Its `iterator()` method is expected
-         *   to generate a dataset iterator object, the `next()` method of which
-         *   is expected to produce data batches for evaluation. The return value
-         *   of the `next()` call ought to contain a boolean `done` field and a
-         *   `value` field. The `value` field is expected to be an array of two
-         *   `tf.Tensor`s or an array of two nested `tf.Tensor` structures. The former
-         *   case is for models with exactly one input and one output (e.g..
-         *   a sequential model). The latter case is for models with multiple
-         *   inputs and/or multiple outputs. Of the two items in the array, the
-         *   first is the input feature(s) and the second is the output target(s).
-         * @param args A configuration object for the dataset-based evaluation.
-         * @returns Loss and metric values as an Array of `Scalar` objects.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        async evaluateDataset(dataset, args) {
-          if (!this.built) {
-            throw new RuntimeError("The model needs to be compiled before being used.");
-          }
-          return this.model.evaluateDataset(dataset, args);
-        }
-        /**
-         * Generates output predictions for the input samples.
-         *
-         * Computation is done in batches.
-         *
-         * Note: the "step" mode of predict() is currently not supported.
-         *   This is because the TensorFow.js core backend is imperative only.
-         *
-         * ```js
-         * const model = tf.sequential({
-         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
-         * });
-         * model.predict(tf.ones([2, 10])).print();
-         * ```
-         *
-         * @param x The input data, as a Tensor, or an `Array` of `tf.Tensor`s if
-         *   the model has multiple inputs.
-         * @param conifg A `ModelPredictConfig` object containing optional fields.
-         *
-         * @return `tf.Tensor`(s) of predictions.
-         *
-         * @exception ValueError In case of mismatch between the provided input data
-         *   and the model's expectations, or in case a stateful model receives a
-         *   number of samples that is not a multiple of the batch size.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        predict(x, args = {}) {
-          if (this.model == null) {
-            this.build();
-          }
-          return this.model.predict(x, args);
-        }
-        /**
-         * Returns predictions for a single batch of samples.
-         *
-         * @param x: Input samples, as a Tensor, or list of Tensors (if the model
-         *   has multiple inputs).
-         * @return Tensor(s) of predictions
-         */
-        predictOnBatch(x) {
-          if (this.model == null) {
-            this.build();
-          }
-          return this.model.predictOnBatch(x);
-        }
-        /**
-         * See `LayersModel.compile`.
-         *
-         * @param args
-         */
-        compile(args) {
-          this.build();
-          this.model.compile(args);
-          this.optimizer_ = this.model.optimizer;
-          // tslint:disable-next-line:no-any
-          this.isOptimizerOwned = this.model.isOptimizerOwned;
-          this.loss = this.model.loss;
-          this.metrics = this.model.metrics;
-          // TODO(cais): Add this.lossWeights, this.sampleWeightMode,
-          //   this.weightedMetrics, this.targets.
-          this.metricsTensors = this.model.metricsTensors;
-          this.metricsNames = this.model.metricsNames;
-          // TODO(cais): Add sampleWeights.
-        }
-        get optimizer() {
-          return this.model == null ? undefined : this.model.optimizer;
-        }
-        set optimizer(optimizer) {
-          this.model.optimizer = optimizer;
-        }
-        /**
-         * Trains the model for a fixed number of epochs (iterations on a dataset).
-         *
-         * ```js
-         * const model = tf.sequential({
-         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
-         * });
-         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
-         * const history = await model.fit(tf.ones([8, 10]), tf.ones([8, 1]), {
-         *   batchSize: 4,
-         *   epochs: 3
-         * });
-         * console.log(history.history.loss[0]);
-         * ```
-         *
-         * @param x `tf.Tensor` of training data, or an array of `tf.Tensor`s if the
-         * model has multiple inputs. If all inputs in the model are named, you can
-         * also pass a dictionary mapping input names to `tf.Tensor`s.
-         * @param y `tf.Tensor` of target (label) data, or an array of `tf.Tensor`s if
-         * the model has multiple outputs. If all outputs in the model are named, you
-         *  can also pass a dictionary mapping output names to `tf.Tensor`s.
-         * @param args  A `ModelFitConfig`, containing optional fields.
-         *
-         * @return A `History` instance. Its `history` attribute contains all
-         *   information collected during training.
-         *
-         * @exception ValueError In case of mismatch between the provided input data
-         *   and what the model expects.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        async fit(x, y, args = {}) {
-          if (!this.built) {
-            throw new RuntimeError("The model needs to be compiled before " + "being used.");
-          }
-          return this.model.fit(x, y, args);
-        }
-        /**
-         * Trains the model using a dataset object.
-         *
-         * ```js
-         * const xArray = [
-         *   [1, 1, 1, 1, 1, 1, 1, 1, 1],
-         *   [1, 1, 1, 1, 1, 1, 1, 1, 1],
-         *   [1, 1, 1, 1, 1, 1, 1, 1, 1],
-         *   [1, 1, 1, 1, 1, 1, 1, 1, 1],
-         * ];
-         * const yArray = [1, 1, 1, 1];
-         * // Create a dataset from the JavaScript array.
-         * const xDataset = tf.data.array(xArray);
-         * const yDataset = tf.data.array(yArray);
-         * // Zip combines the `x` and `y` Datasets into a single Dataset, the
-         * // iterator of which will return an object containing of two tensors,
-         * // corresponding to `x` and `y`.  The call to `batch(4)` will bundle
-         * // four such samples into a single object, with the same keys now pointing
-         * // to tensors that hold 4 examples, organized along the batch dimension.
-         * // The call to `shuffle(4)` causes each iteration through the dataset to
-         * // happen in a different order.  The size of the shuffle window is 4.
-         * const xyDataset = tf.data.zip({xs: xDataset, ys: yDataset})
-         *     .batch(4)
-         *     .shuffle(4);
-         * const model = tf.sequential({
-         *   layers: [tf.layers.dense({units: 1, inputShape: [9]})]
-         * });
-         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
-         * const history = await model.fitDataset(xyDataset, {
-         *   epochs: 4,
-         *   callbacks: {onEpochEnd: (epoch, logs) => console.log(logs.loss)}
-         * });
-         * ```
-         *
-         * @param dataset A dataset object. Its `iterator()` method is expected to
-         *   generate a dataset iterator object, the `next()` method of which is
-         *   expected to produce data batches for evaluation. The return value of the
-         *   `next()` call ought to contain a boolean `done` field and a `value`
-         *   field.
-         *
-         *   The `value` field is expected to be an object of with fields
-         *   `xs` and `ys`, which point to the feature tensor and the target tensor,
-         *   respectively. This case is for models with exactly one input and one
-         *   output (e.g.. a sequential model). For example:
-         *   ```js
-         *   {value: {xs: xsTensor, ys: ysTensor}, done: false}
-         *   ```
-         *
-         *   If the model has multiple inputs, the `xs` field of `value` should
-         *   be an object mapping input names to their respective feature tensors.
-         *   For example:
-         *   ```js
-         *   {
-         *     value: {
-         *       xs: {
-         *         input_1: xsTensor1,
-         *         input_2: xsTensor2
-         *       },
-         *       ys: ysTensor
-         *     },
-         *     done: false
-         *   }
-         *   ```
-         *   If the model has multiple outputs, the `ys` field of `value` should
-         *   be an object mapping output names to their respective target tensors.
-         *   For example:
-         *   ```js
-         *   {
-         *     value: {
-         *       xs: xsTensor,
-         *       ys: {
-         *         output_1: ysTensor1,
-         *         output_2: ysTensor2
-         *       },
-         *     },
-         *     done: false
-         *   }
-         *   ```
-         * @param args A `ModelFitDatasetArgs`, containing optional fields.
-         *
-         * @return A `History` instance. Its `history` attribute contains all
-         *   information collected during training.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes', ignoreCI: true}
-         */
-        async fitDataset(dataset, args) {
-          if (!this.built) {
-            throw new RuntimeError("The model needs to be compiled before " + "being used.");
-          }
-          return this.model.fitDataset(dataset, args);
-        }
-        /**
-         * Runs a single gradient update on a single batch of data.
-         *
-         * This method differs from `fit()` and `fitDataset()` in the following
-         * regards:
-         *   - It operates on exactly one batch of data.
-         *   - It returns only the loss and matric values, instead of
-         *     returning the batch-by-batch loss and metric values.
-         *   - It doesn't support fine-grained options such as verbosity and
-         *     callbacks.
-         *
-         * @param x Input data. It could be one of the following:
-         *   - A `tf.Tensor`, or an Array of `tf.Tensor`s (in case the model has
-         *     multiple inputs).
-         *   - An Object mapping input names to corresponding `tf.Tensor` (if the
-         *     model has named inputs).
-         * @param y Target darta. It could be either a `tf.Tensor` a multiple
-         *   `tf.Tensor`s. It should be consistent with `x`.
-         * @returns Training loss or losses (in case the model has
-         *   multiple outputs), along with metrics (if any), as numbers.
-         */
-        /**
-         * @doc {heading: 'Models', subheading: 'Classes'}
-         */
-        async trainOnBatch(x, y) {
-          return this.model.trainOnBatch(x, y);
-        }
-        /* See parent class for JsDoc */
-        /** @nocollapse */
-        static fromConfig(cls, config, customObjects = {}, fastWeightInit = false) {
-          let configArray;
-          let extraModelConfig = {};
-          if (config instanceof Array) {
-            if (!(config[0].className != null) || config[0]["className"] === "Merge") {
-              throw new ValueError("Legacy serialization format not supported yet.");
-            }
-            configArray = config;
-          } else {
-            dist["util"].assert(
-              config["layers"] != null,
-              () =>
-                `When the config data for a Sequential model is not an Array, ` +
-                `it must be an Object that contains the 'layers' field.`
-            );
-            configArray = config["layers"];
-            delete config["layers"];
-            extraModelConfig = config;
-          }
-          const model = new cls(extraModelConfig);
-          if (!(model instanceof models_Sequential)) {
-            throw new NotImplementedError(
-              `Sequential.fromConfig called on non-Sequential input: ${model}`
-            );
-          }
-          for (const conf of configArray) {
-            const customObjects = undefined;
-            const layer = deserialize(conf, customObjects, fastWeightInit);
-            if (fastWeightInit) {
-              layer.setFastWeightInitDuringBuild(true);
-            }
-            model.add(layer);
-          }
-          return model;
-        }
-        /**
-         * Setter used for force stopping of LayersModel.fit() (i.e., training).
-         *
-         * Example:
-         *
-         * ```js
-         * const model = tf.sequential();
-         * model.add(tf.layers.dense({units: 1, inputShape: [10]}));
-         * model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
-         * const xs = tf.ones([8, 10]);
-         * const ys = tf.zeros([8, 1]);
-         *
-         * const history = await model.fit(xs, ys, {
-         *   epochs: 10,
-         *   callbacks: {
-         *     onEpochEnd: async (epoch, logs) => {
-         *       if (epoch === 2) {
-         *         model.stopTraining = true;
-         *       }
-         *     }
-         *   }
-         * });
-         *
-         * // There should be only 3 values in the loss array, instead of 10 values,
-         * // due to the stopping after 3 epochs.
-         * console.log(history.history.loss);
-         * ```
-         */
-        set stopTraining(stop) {
-          // TODO(cais): When refactoring to remove the composition pattern happens,
-          // remove this method overriding.
-          if (this.model == null) {
-            throw new ValueError(
-              "Cannot set the stopTraining property of a sequential model before " +
-                "it is compiled."
-            );
-          }
-          this.model.stopTraining = stop;
-        }
-        get stopTraining() {
-          if (this.model == null) {
-            throw new ValueError(
-              "Cannot get the stopTraining property of a sequential model before " +
-                "it is compiled."
-            );
-          }
-          return this.model.stopTraining;
-        }
-        // TODO(cais): Override get trainableWeights() here
-        // tslint:disable-next-line:no-any
-        getConfig() {
-          // NOTE(cais): We override the return type of getConfig() to `any` here,
-          //   because the `Sequential` class is a special case among `Container`
-          //   subtypes in that its getConfig() method returns an Array (not a
-          //   dict).
-          const layers = [];
-          for (const layer of this.layers) {
-            const dict = {};
-            dict["className"] = layer.getClassName();
-            dict["config"] = layer.getConfig();
-            layers.push(dict);
-          }
-          return { name: this.name, layers };
-        }
-      }
-      /** @nocollapse */
-      models_Sequential.className = "Sequential";
-      dist["serialization"].registerClass(models_Sequential);
-      //# sourceMappingURL=models.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      // TODO(cais): Add doc string to all the public static functions in this
-      //   class; include exectuable JavaScript code snippets where applicable
-      //   (b/74074458).
-      // LayersModel and related factory methods.
-      /**
-       * A model is a data structure that consists of `Layers` and defines inputs
-       * and outputs.
-       *
-       * The key difference between `tf.model` and `tf.sequential` is that
-       * `tf.model` is more generic, supporting an arbitrary graph (without
-       * cycles) of layers. `tf.sequential` is less generic and supports only a linear
-       * stack of layers.
-       *
-       * When creating a `tf.LayersModel`, specify its input(s) and output(s). Layers
-       * are used to wire input(s) to output(s).
-       *
-       * For example, the following code snippet defines a model consisting of
-       * two `dense` layers, with 10 and 4 units, respectively.
-       *
-       * ```js
-       * // Define input, which has a size of 5 (not including batch dimension).
-       * const input = tf.input({shape: [5]});
-       *
-       * // First dense layer uses relu activation.
-       * const denseLayer1 = tf.layers.dense({units: 10, activation: 'relu'});
-       * // Second dense layer uses softmax activation.
-       * const denseLayer2 = tf.layers.dense({units: 4, activation: 'softmax'});
-       *
-       * // Obtain the output symbolic tensor by applying the layers on the input.
-       * const output = denseLayer2.apply(denseLayer1.apply(input));
-       *
-       * // Create the model based on the inputs.
-       * const model = tf.model({inputs: input, outputs: output});
-       *
-       * // The model can be used for training, evaluation and prediction.
-       * // For example, the following line runs prediction with the model on
-       * // some fake data.
-       * model.predict(tf.ones([2, 5])).print();
-       * ```
-       * See also:
-       *   `tf.sequential`, `tf.loadLayersModel`.
-       */
-      /**
-       * @doc {heading: 'Models', subheading: 'Creation'}
-       */
-      function exports_model(args) {
-        return new training_LayersModel(args);
-      }
-      /**
-       * Creates a `tf.Sequential` model.  A sequential model is any model where the
-       * outputs of one layer are the inputs to the next layer, i.e. the model
-       * topology is a simple 'stack' of layers, with no branching or skipping.
-       *
-       * This means that the first layer passed to a `tf.Sequential` model should have
-       * a defined input shape. What that means is that it should have received an
-       * `inputShape` or `batchInputShape` argument, or for some type of layers
-       * (recurrent, Dense...) an `inputDim` argument.
-       *
-       * The key difference between `tf.model` and `tf.sequential` is that
-       * `tf.sequential` is less generic, supporting only a linear stack of layers.
-       * `tf.model` is more generic and supports an arbitrary graph (without
-       * cycles) of layers.
-       *
-       * Examples:
-       *
-       * ```js
-       * const model = tf.sequential();
-       *
-       * // First layer must have an input shape defined.
-       * model.add(tf.layers.dense({units: 32, inputShape: [50]}));
-       * // Afterwards, TF.js does automatic shape inference.
-       * model.add(tf.layers.dense({units: 4}));
-       *
-       * // Inspect the inferred shape of the model's output, which equals
-       * // `[null, 4]`. The 1st dimension is the undetermined batch dimension; the
-       * // 2nd is the output size of the model's last layer.
-       * console.log(JSON.stringify(model.outputs[0].shape));
-       * ```
-       *
-       * It is also possible to specify a batch size (with potentially undetermined
-       * batch dimension, denoted by "null") for the first layer using the
-       * `batchInputShape` key. The following example is equivalent to the above:
-       *
-       * ```js
-       * const model = tf.sequential();
-       *
-       * // First layer must have a defined input shape
-       * model.add(tf.layers.dense({units: 32, batchInputShape: [null, 50]}));
-       * // Afterwards, TF.js does automatic shape inference.
-       * model.add(tf.layers.dense({units: 4}));
-       *
-       * // Inspect the inferred shape of the model's output.
-       * console.log(JSON.stringify(model.outputs[0].shape));
-       * ```
-       *
-       * You can also use an `Array` of already-constructed `Layer`s to create
-       * a `tf.Sequential` model:
-       *
-       * ```js
-       * const model = tf.sequential({
-       *   layers: [tf.layers.dense({units: 32, inputShape: [50]}),
-       *            tf.layers.dense({units: 4})]
-       * });
-       * console.log(JSON.stringify(model.outputs[0].shape));
-       * ```
-       */
-      /**
-       * @doc {heading: 'Models', subheading: 'Creation'}
-       */
-      function sequential(config) {
-        return new models_Sequential(config);
-      }
-      /**
-       * Load a model composed of Layer objects, including its topology and optionally
-       * weights. See the Tutorial named "How to import a Keras Model" for usage
-       * examples.
-       *
-       * This method is applicable to:
-       *
-       * 1. Models created with the `tf.layers.*`, `tf.sequential`, and
-       * `tf.model` APIs of TensorFlow.js and later saved with the
-       * `tf.LayersModel.save` method.
-       * 2. Models converted from Keras or TensorFlow tf.keras using the
-       * [tensorflowjs_converter](https://github.com/tensorflow/tfjs/tree/master/tfjs-converter).
-       *
-       * This mode is *not* applicable to TensorFlow `SavedModel`s or their converted
-       * forms. For those models, use `tf.loadGraphModel`.
-       *
-       * Example 1. Load a model from an HTTP server.
-       *
-       * ```js
-       * const model = await tf.loadLayersModel(
-       *     'https://storage.googleapis.com/tfjs-models/tfjs/iris_v1/model.json');
-       * model.summary();
-       * ```
-       *
-       * Example 2: Save `model`'s topology and weights to browser [local
-       * storage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage);
-       * then load it back.
-       *
-       * ```js
-       * const model = tf.sequential(
-       *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
-       * console.log('Prediction from original model:');
-       * model.predict(tf.ones([1, 3])).print();
-       *
-       * const saveResults = await model.save('localstorage://my-model-1');
-       *
-       * const loadedModel = await tf.loadLayersModel('localstorage://my-model-1');
-       * console.log('Prediction from loaded model:');
-       * loadedModel.predict(tf.ones([1, 3])).print();
-       * ```
-       *
-       * Example 3. Saving `model`'s topology and weights to browser
-       * [IndexedDB](https://developer.mozilla.org/en-US/docs/Web/API/IndexedDB_API);
-       * then load it back.
-       *
-       * ```js
-       * const model = tf.sequential(
-       *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
-       * console.log('Prediction from original model:');
-       * model.predict(tf.ones([1, 3])).print();
-       *
-       * const saveResults = await model.save('indexeddb://my-model-1');
-       *
-       * const loadedModel = await tf.loadLayersModel('indexeddb://my-model-1');
-       * console.log('Prediction from loaded model:');
-       * loadedModel.predict(tf.ones([1, 3])).print();
-       * ```
-       *
-       * Example 4. Load a model from user-selected files from HTML
-       * [file input
-       * elements](https://developer.mozilla.org/en-US/docs/Web/HTML/Element/input/file).
-       *
-       * ```js
-       * // Note: this code snippet will not work without the HTML elements in the
-       * //   page
-       * const jsonUpload = document.getElementById('json-upload');
-       * const weightsUpload = document.getElementById('weights-upload');
-       *
-       * const model = await tf.loadLayersModel(
-       *     tf.io.browserFiles([jsonUpload.files[0], weightsUpload.files[0]]));
-       * ```
-       *
-       * @param pathOrIOHandler Can be either of the two formats
-       *   1. A string path to the `ModelAndWeightsConfig` JSON describing
-       *      the model in the canonical TensorFlow.js format. For file://
-       *      (tfjs-node-only), http:// and https:// schemas, the path can be
-       *      either absolute or relative.
-       *   2. An `tf.io.IOHandler` object that loads model artifacts with its `load`
-       *      method.
-       * @param options Optional configuration arguments for the model loading,
-       *   including:
-       *   - `strict`: Require that the provided weights exactly match those required
-       *     by the layers.  Default true.  Passing false means that both extra
-       *     weights and missing weights will be silently ignored.
-       *   - `onProgress`: A function of the signature `(fraction: number) => void',
-       *     that can be used as the progress callback for the model loading.
-       * @returns A `Promise` of `tf.LayersModel`, with the topology and weights
-       *     loaded.
-       */
-      /** @doc {heading: 'Models', subheading: 'Loading'} */
-      function loadLayersModel(pathOrIOHandler, options) {
-        if (options == null) {
-          options = {};
-        }
-        return loadLayersModelInternal(pathOrIOHandler, options);
-      }
-      /**
-       * Used to instantiate an input to a model as a `tf.SymbolicTensor`.
-       *
-       * Users should call the `input` factory function for
-       * consistency with other generator functions.
-       *
-       * Example:
-       *
-       * ```js
-       * // Defines a simple logistic regression model with 32 dimensional input
-       * // and 3 dimensional output.
-       * const x = tf.input({shape: [32]});
-       * const y = tf.layers.dense({units: 3, activation: 'softmax'}).apply(x);
-       * const model = tf.model({inputs: x, outputs: y});
-       * model.predict(tf.ones([2, 32])).print();
-       * ```
-       *
-       * Note: `input` is only necessary when using `model`. When using
-       * `sequential`, specify `inputShape` for the first layer or use `inputLayer`
-       * as the first layer.
-       */
-      /** @doc {heading: 'Models', subheading: 'Inputs'} */
-      function exports_input(config) {
-        return Input(config);
-      }
-      function registerCallbackConstructor(verbosityLevel, callbackConstructor) {
-        base_callbacks_CallbackConstructorRegistry.registerCallbackConstructor(
-          verbosityLevel,
-          callbackConstructor
-        );
-      }
-      //# sourceMappingURL=exports.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/activations.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      // Layer activation functions
-
-      /**
-       * Base class for Activations.
-       *
-       * Special note: due to cross-language compatibility reasons, the
-       * static readonly className field in this family of classes must be set to
-       * the initialLowerCamelCase name of the activation.
-       */
-      class activations_Activation extends dist["serialization"].Serializable {
-        getConfig() {
-          return {};
-        }
-      }
-      /**
-       * Exponential linear unit (ELU).
-       * Reference: https://arxiv.org/abs/1511.07289
-       */
-      class activations_Elu extends activations_Activation {
-        /**
-         * Calculate the activation function.
-         *
-         * @param x: Input.
-         * @param alpha: Scaling factor the negative section.
-         * @return Output of the ELU activation.
-         */
-        apply(x, alpha = 1) {
-          return elu(x, alpha);
-        }
-      }
-      /** @nocollapse */
-      activations_Elu.className = "elu";
-      dist["serialization"].registerClass(activations_Elu);
-      /**
-       * Scaled Exponential Linear Unit. (Klambauer et al., 2017).
-       * Reference: Self-Normalizing Neural Networks, https://arxiv.org/abs/1706.02515
-       * Notes:
-       *   - To be used together with the initialization "lecunNormal".
-       *   - To be used together with the dropout variant "AlphaDropout".
-       */
-      class activations_Selu extends activations_Activation {
-        apply(x) {
-          return dist["selu"](x);
-        }
-      }
-      /** @nocollapse */
-      activations_Selu.className = "selu";
-      dist["serialization"].registerClass(activations_Selu);
-      /**
-       *  Rectified linear unit
-       */
-      class activations_Relu extends activations_Activation {
-        apply(x) {
-          return dist["relu"](x);
-        }
-      }
-      /** @nocollapse */
-      activations_Relu.className = "relu";
-      dist["serialization"].registerClass(activations_Relu);
-      /**
-       * Rectified linear unit activation maxing out at 6.0.
-       */
-      class activations_Relu6 extends activations_Activation {
-        apply(x) {
-          return Object(dist["tidy"])(() => dist["minimum"](6.0, dist["relu"](x)));
-        }
-      }
-      /** @nocollapse */
-      activations_Relu6.className = "relu6";
-      dist["serialization"].registerClass(activations_Relu6);
-      //* Linear activation (no-op) */
-      class Linear extends activations_Activation {
-        apply(x) {
-          return x;
-        }
-      }
-      /** @nocollapse */
-      Linear.className = "linear";
-      dist["serialization"].registerClass(Linear);
-      /**
-       * Sigmoid activation function.
-       */
-      class activations_Sigmoid extends activations_Activation {
-        apply(x) {
-          return dist["sigmoid"](x);
-        }
-      }
-      /** @nocollapse */
-      activations_Sigmoid.className = "sigmoid";
-      dist["serialization"].registerClass(activations_Sigmoid);
-      /**
-       * Segment-wise linear approximation of sigmoid.
-       */
-      class activations_HardSigmoid extends activations_Activation {
-        apply(x) {
-          return hardSigmoid(x);
-        }
-      }
-      /** @nocollapse */
-      activations_HardSigmoid.className = "hardSigmoid";
-      dist["serialization"].registerClass(activations_HardSigmoid);
-      /**
-       * Softplus activation function.
-       */
-      class activations_Softplus extends activations_Activation {
-        apply(x) {
-          return dist["softplus"](x);
-        }
-      }
-      /** @nocollapse */
-      activations_Softplus.className = "softplus";
-      dist["serialization"].registerClass(activations_Softplus);
-      /**
-       * Softsign activation function.
-       */
-      class activations_Softsign extends activations_Activation {
-        apply(x) {
-          return softsign(x);
-        }
-      }
-      /** @nocollapse */
-      activations_Softsign.className = "softsign";
-      dist["serialization"].registerClass(activations_Softsign);
-      /**
-       * Hyperbolic tangent function.
-       */
-      class activations_Tanh extends activations_Activation {
-        apply(x) {
-          return dist["tanh"](x);
-        }
-      }
-      /** @nocollapse */
-      activations_Tanh.className = "tanh";
-      dist["serialization"].registerClass(activations_Tanh);
-      /**
-       * Softmax activation function
-       */
-      class activations_Softmax extends activations_Activation {
-        /**
-         * Calculate the activation function.
-         *
-         * @param x Tensor.
-         * @param axis Integer, axis along which the softmax normalization is applied.
-         * Invalid if < 2, as softmax across 1 (the batch dimension) is assumed to be
-         * an error.
-         *
-         * @returns a Tensor of the same shape as x
-         *
-         * @throws ValueError: In case `dim(x) < 2`.
-         */
-        apply(x, axis = -1) {
-          return dist["softmax"](x, axis);
-        }
-      }
-      /** @nocollapse */
-      activations_Softmax.className = "softmax";
-      dist["serialization"].registerClass(activations_Softmax);
-      /**
-       * Log softmax activation function
-       */
-      class activations_LogSoftmax extends activations_Activation {
-        /**
-         * Calculate the activation function of log softmax:
-         * log( exp(x_i) / sum(exp(x)) )
-         *
-         * @param x Tensor.
-         * @param axis Integer, axis along which the softmax normalization is applied.
-         * Invalid if < 2, as softmax across 1 (the batch dimension) is assumed to be
-         * an error.
-         *
-         * @returns a Tensor of the same shape as x
-         *
-         * @throws ValueError: In case `dim(x) < 2`.
-         */
-        apply(x, axis = -1) {
-          return dist["logSoftmax"](x, axis);
-        }
-      }
-      /** @nocollapse */
-      activations_LogSoftmax.className = "logSoftmax";
-      dist["serialization"].registerClass(activations_LogSoftmax);
-      function serializeActivation(activation) {
-        return activation.getClassName();
-      }
-      function deserializeActivation(config, customObjects = {}) {
-        return deserializeKerasObject(
-          config,
-          dist["serialization"].SerializationMap.getMap().classNameMap,
-          customObjects,
-          "activation"
-        );
-      }
-      function getActivation(identifier) {
-        if (identifier == null) {
-          const config = {};
-          config["className"] = "linear";
-          config["config"] = {};
-          return deserializeActivation(config);
-        }
-        if (typeof identifier === "string") {
-          const config = {};
-          config["className"] = identifier;
-          config["config"] = {};
-          return deserializeActivation(config);
-        } else if (identifier instanceof activations_Activation) {
-          return identifier;
-        } else {
-          return deserializeActivation(identifier);
-        }
-      }
-      //# sourceMappingURL=activations.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/regularizers.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* original source: keras/regularizers.py */
-
-      function assertObjectArgs(args) {
-        if (args != null && typeof args !== "object") {
-          throw new Error(
-            `Argument to L1L2 regularizer's constructor is expected to be an ` +
-              `object, but received: ${args}`
-          );
-        }
-      }
-      /**
-       * Regularizer base class.
-       */
-      class regularizers_Regularizer extends dist["serialization"].Serializable {}
-      class regularizers_L1L2 extends regularizers_Regularizer {
-        constructor(args) {
-          super();
-          assertObjectArgs(args);
-          this.l1 = args == null || args.l1 == null ? 0.01 : args.l1;
-          this.l2 = args == null || args.l2 == null ? 0.01 : args.l2;
-          this.hasL1 = this.l1 !== 0;
-          this.hasL2 = this.l2 !== 0;
-        }
-        /**
-         * Porting note: Renamed from __call__.
-         * @param x Variable of which to calculate the regularization score.
-         */
-        apply(x) {
-          return Object(dist["tidy"])(() => {
-            let regularization = Object(dist["zeros"])([1]);
-            if (this.hasL1) {
-              regularization = Object(dist["add"])(
-                regularization,
-                Object(dist["sum"])(dist["mul"](this.l1, Object(dist["abs"])(x)))
-              );
-            }
-            if (this.hasL2) {
-              regularization = Object(dist["add"])(
-                regularization,
-                Object(dist["sum"])(dist["mul"](this.l2, square(x)))
-              );
-            }
-            return regularization.asScalar();
-          });
-        }
-        getConfig() {
-          return { l1: this.l1, l2: this.l2 };
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls({ l1: config["l1"], l2: config["l2"] });
-        }
-      }
-      /** @nocollapse */
-      regularizers_L1L2.className = "L1L2";
-      dist["serialization"].registerClass(regularizers_L1L2);
-      function l1(args) {
-        assertObjectArgs(args);
-        return new regularizers_L1L2({ l1: args != null ? args.l1 : null, l2: 0 });
-      }
-      function l2(args) {
-        assertObjectArgs(args);
-        return new regularizers_L1L2({ l2: args != null ? args.l2 : null, l1: 0 });
-      }
-      // Maps the JavaScript-like identifier keys to the corresponding keras symbols.
-      const REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP = {
-        l1l2: "L1L2",
-      };
-      function serializeRegularizer(constraint) {
-        return serializeKerasObject(constraint);
-      }
-      function deserializeRegularizer(config, customObjects = {}) {
-        return deserializeKerasObject(
-          config,
-          dist["serialization"].SerializationMap.getMap().classNameMap,
-          customObjects,
-          "regularizer"
-        );
-      }
-      function getRegularizer(identifier) {
-        if (identifier == null) {
-          return null;
-        }
-        if (typeof identifier === "string") {
-          const className =
-            identifier in REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP
-              ? REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier]
-              : identifier;
-          const config = { className, config: {} };
-          return deserializeRegularizer(config);
-        } else if (identifier instanceof regularizers_Regularizer) {
-          return identifier;
-        } else {
-          return deserializeRegularizer(identifier);
-        }
-      }
-      //# sourceMappingURL=regularizers.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/advanced_activations.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       *  Advanced activation layers.
-       */
-
-      class advanced_activations_ReLU extends topology_Layer {
-        constructor(args) {
-          super(args == null ? {} : args);
-          this.supportsMasking = true;
-          if (args != null) {
-            this.maxValue = args.maxValue;
-          }
-        }
-        call(inputs, kwargs) {
-          inputs = getExactlyOneTensor(inputs);
-          let output = Object(dist["relu"])(inputs);
-          if (this.maxValue != null) {
-            output = Object(dist["clipByValue"])(output, 0, this.maxValue);
-          }
-          return output;
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const config = { maxValue: this.maxValue };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      advanced_activations_ReLU.className = "ReLU";
-      dist["serialization"].registerClass(advanced_activations_ReLU);
-      class advanced_activations_LeakyReLU extends topology_Layer {
-        constructor(args) {
-          super(args == null ? {} : args);
-          this.DEFAULT_ALPHA = 0.3;
-          if (args == null) {
-            args = {};
-          }
-          this.alpha = args.alpha == null ? this.DEFAULT_ALPHA : args.alpha;
-        }
-        call(inputs, kwargs) {
-          const x = getExactlyOneTensor(inputs);
-          return Object(dist["leakyRelu"])(x, this.alpha);
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const config = { alpha: this.alpha };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      advanced_activations_LeakyReLU.className = "LeakyReLU";
-      dist["serialization"].registerClass(advanced_activations_LeakyReLU);
-      class advanced_activations_PReLU extends topology_Layer {
-        constructor(args) {
-          super(args == null ? {} : args);
-          this.DEFAULT_ALPHA_INITIALIZER = "zeros";
-          if (args == null) {
-            args = {};
-          }
-          this.supportsMasking = true;
-          this.alphaInitializer = getInitializer(
-            args.alphaInitializer || this.DEFAULT_ALPHA_INITIALIZER
-          );
-          this.alphaRegularizer = getRegularizer(args.alphaRegularizer);
-          this.alphaConstraint = getConstraint(args.alphaConstraint);
-          if (args.sharedAxes == null) {
-            this.sharedAxes = null;
-          } else if (Array.isArray(args.sharedAxes)) {
-            this.sharedAxes = args.sharedAxes;
-          } else if (typeof args.sharedAxes === "number") {
-            this.sharedAxes = [args.sharedAxes];
-          } else {
-            throw new ValueError(
-              `Expected sharedAxes to be a number or an array of numbers, ` +
-                `but got ${args.sharedAxes}`
-            );
-          }
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const paramShape = inputShape.slice(1);
-          if (this.sharedAxes != null) {
-            for (const i of this.sharedAxes) {
-              paramShape[i - 1] = 1;
-            }
-          }
-          this.alpha = this.addWeight(
-            "alpha",
-            paramShape,
-            "float32",
-            this.alphaInitializer,
-            this.alphaRegularizer,
-            true,
-            this.alphaConstraint
-          );
-          // Set input spec.
-          const axes = {};
-          if (this.sharedAxes != null) {
-            for (let i = 1; i < inputShape.length; ++i) {
-              axes[i] = inputShape[i];
-            }
-          }
-          this.inputSpec = [
-            new InputSpec({
-              ndim: inputShape.length,
-              axes,
-            }),
-          ];
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          inputs = getExactlyOneTensor(inputs);
-          return Object(dist["prelu"])(inputs, this.alpha.read());
-        }
-        getConfig() {
-          const config = {
-            alphaInitializer: serializeInitializer(this.alphaInitializer),
-            alphaRegularizer: serializeRegularizer(this.alphaRegularizer),
-            alphaConstraint: serializeConstraint(this.alphaConstraint),
-            sharedAxes: this.sharedAxes,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      advanced_activations_PReLU.className = "PReLU";
-      dist["serialization"].registerClass(advanced_activations_PReLU);
-      class advanced_activations_ELU extends topology_Layer {
-        constructor(args) {
-          super(args == null ? {} : args);
-          this.DEFAULT_ALPHA = 1.0;
-          if (args == null) {
-            args = {};
-          }
-          if (args.alpha != null && args.alpha !== this.DEFAULT_ALPHA) {
-            throw new NotImplementedError(
-              `Non-default alpha value (${args.alpha}) is not supported by the ` + `ELU layer yet.`
-            );
-          }
-          this.alpha = args.alpha == null ? this.DEFAULT_ALPHA : args.alpha;
-        }
-        call(inputs, kwargs) {
-          const x = getExactlyOneTensor(inputs);
-          return Object(dist["elu"])(x);
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const config = { alpha: this.alpha };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      advanced_activations_ELU.className = "ELU";
-      dist["serialization"].registerClass(advanced_activations_ELU);
-      class advanced_activations_ThresholdedReLU extends topology_Layer {
-        constructor(args) {
-          super(args == null ? {} : args);
-          this.DEFAULT_THETA = 1.0;
-          if (args == null) {
-            args = {};
-          }
-          this.theta = args.theta == null ? this.DEFAULT_THETA : args.theta;
-        }
-        call(inputs, kwargs) {
-          const x = getExactlyOneTensor(inputs);
-          return x.mul(cast(x.greater(this.theta), "float32"));
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const config = { theta: this.theta };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      advanced_activations_ThresholdedReLU.className = "ThresholdedReLU";
-      dist["serialization"].registerClass(advanced_activations_ThresholdedReLU);
-      class advanced_activations_Softmax extends topology_Layer {
-        constructor(args) {
-          super(args == null ? {} : args);
-          this.DEFAULT_AXIS = 1.0;
-          if (args == null) {
-            args = {};
-          }
-          this.softmax = new activations_Softmax().apply;
-          this.axis = args.axis == null ? this.DEFAULT_AXIS : args.axis;
-        }
-        call(inputs, kwargs) {
-          const x = getExactlyOneTensor(inputs);
-          return this.softmax(x, this.axis);
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const config = { axis: this.axis };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      advanced_activations_Softmax.className = "Softmax";
-      dist["serialization"].registerClass(advanced_activations_Softmax);
-      //# sourceMappingURL=advanced_activations.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/conv_utils.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      /**
-       * Transforms a single number of array of numbers into an array of numbers.
-       * @param value
-       * @param n: The size of the tuple to be returned.
-       * @param name: Name of the parameter, used for generating error messages.
-       * @returns An array of numbers.
-       */
-      function normalizeArray(value, n, name) {
-        if (typeof value === "number") {
-          return pyListRepeat(value, n);
-        } else {
-          if (value.length !== n) {
-            throw new ValueError(
-              `The ${name} argument must be an integer or tuple of ${n} integers.` +
-                ` Received: ${value.length} elements.`
-            );
-          }
-          for (let i = 0; i < n; ++i) {
-            const singleValue = value[i];
-            if (!isInteger(singleValue)) {
-              throw new ValueError(
-                `The ${name} argument must be an integer or tuple of ${n}` +
-                  ` integers. Received: ${JSON.stringify(value)} including a` +
-                  ` non-integer number ${singleValue}`
-              );
-            }
-          }
-          return value;
-        }
-      }
-      /**
-       * Determines output length of a convolution given input length.
-       * @param inputLength
-       * @param filterSize
-       * @param padding
-       * @param stride
-       * @param dilation: dilation rate.
-       */
-      function convOutputLength(inputLength, filterSize, padding, stride, dilation = 1) {
-        if (inputLength == null) {
-          return inputLength;
-        }
-        const dilatedFilterSize = filterSize + (filterSize - 1) * (dilation - 1);
-        let outputLength;
-        if (padding === "same") {
-          outputLength = inputLength;
-        } else {
-          // VALID
-          outputLength = inputLength - dilatedFilterSize + 1;
-        }
-        return Math.floor((outputLength + stride - 1) / stride);
-      }
-      function deconvLength(dimSize, strideSize, kernelSize, padding) {
-        if (dimSize == null) {
-          return null;
-        }
-        if (padding === "valid") {
-          dimSize = dimSize * strideSize + max([kernelSize - strideSize, 0]);
-        } else if (padding === "same") {
-          dimSize = dimSize * strideSize;
-        } else {
-          throw new ValueError(`Unsupport padding mode: ${padding}.`);
-        }
-        return dimSize;
-      }
-      //# sourceMappingURL=conv_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * TensorFlow.js Layers: Convolutional Layers
-       */
-
-      /**
-       * Transpose and cast the input before the conv2d.
-       * @param x Input image tensor.
-       * @param dataFormat
-       */
-      function preprocessConv2DInput(x, dataFormat) {
-        // TODO(cais): Cast type to float32 if not.
-        return Object(dist["tidy"])(() => {
-          checkDataFormat(dataFormat);
-          if (dataFormat === "channelsFirst") {
-            return dist["transpose"](x, [0, 2, 3, 1]); // NCHW -> NHWC.
-          } else {
-            return x;
-          }
-        });
-      }
-      /**
-       * Transpose and cast the input before the conv3d.
-       * @param x Input image tensor.
-       * @param dataFormat
-       */
-      function preprocessConv3DInput(x, dataFormat) {
-        return Object(dist["tidy"])(() => {
-          checkDataFormat(dataFormat);
-          if (dataFormat === "channelsFirst") {
-            return dist["transpose"](x, [0, 2, 3, 4, 1]); // NCDHW -> NDHWC.
-          } else {
-            return x;
-          }
-        });
-      }
-      /**
-       * 1D-convolution with bias added.
-       *
-       * Porting Note: This function does not exist in the Python Keras backend.
-       *   It is exactly the same as `conv2d`, except the added `bias`.
-       *
-       * @param x Input tensor, rank-3, of shape `[batchSize, width, inChannels]`.
-       * @param kernel Kernel, rank-3, of shape `[filterWidth, inDepth, outDepth]`.
-       * @param bias Bias, rank-3, of shape `[outDepth]`.
-       * @param strides
-       * @param padding Padding mode.
-       * @param dataFormat Data format.
-       * @param dilationRate
-       * @returns The result of the 1D convolution.
-       * @throws ValueError, if `x`, `kernel` or `bias` is not of the correct rank.
-       */
-      function conv1dWithBias(
-        x,
-        kernel,
-        bias,
-        strides = 1,
-        padding = "valid",
-        dataFormat,
-        dilationRate = 1
-      ) {
-        return Object(dist["tidy"])(() => {
-          if (dataFormat == null) {
-            dataFormat = imageDataFormat();
-          }
-          checkDataFormat(dataFormat);
-          // Check the ranks of x, kernel and bias.
-          if (x.shape.length !== 3) {
-            throw new ValueError(
-              `The input of a conv1dWithBias operation should be 3, but is ` +
-                `${x.shape.length} instead.`
-            );
-          }
-          if (kernel.shape.length !== 3) {
-            throw new ValueError(
-              `The kernel for a conv1dWithBias operation should be 3, but is ` +
-                `${kernel.shape.length} instead`
-            );
-          }
-          if (bias != null && bias.shape.length !== 1) {
-            throw new ValueError(
-              `The bias for a conv1dWithBias operation should be 1, but is ` +
-                `${kernel.shape.length} instead`
-            );
-          }
-          // TODO(cais): Support CAUSAL padding mode.
-          if (dataFormat === "channelsFirst") {
-            x = dist["transpose"](x, [0, 2, 1]); // NCW -> NWC.
-          }
-          if (padding === "causal") {
-            throw new NotImplementedError(
-              "The support for CAUSAL padding mode in conv1dWithBias is not " + "implemented yet."
-            );
-          }
-          let y = dist["conv1d"](
-            x,
-            kernel,
-            strides,
-            padding === "same" ? "same" : "valid",
-            "NWC",
-            dilationRate
-          );
-          if (bias != null) {
-            y = biasAdd(y, bias);
-          }
-          return y;
-        });
-      }
-      /**
-       * 1D-convolution.
-       *
-       * @param x Input tensor, rank-3, of shape `[batchSize, width, inChannels]`.
-       * @param kernel Kernel, rank-3, of shape `[filterWidth, inDepth, outDepth]`.s
-       * @param strides
-       * @param padding Padding mode.
-       * @param dataFormat Data format.
-       * @param dilationRate
-       * @returns The result of the 1D convolution.
-       * @throws ValueError, if `x`, `kernel` or `bias` is not of the correct rank.
-       */
-      function conv1d(x, kernel, strides = 1, padding = "valid", dataFormat, dilationRate = 1) {
-        return Object(dist["tidy"])(() => {
-          checkDataFormat(dataFormat);
-          return conv1dWithBias(x, kernel, null, strides, padding, dataFormat, dilationRate);
-        });
-      }
-      /**
-       * 2D Convolution
-       * @param x
-       * @param kernel kernel of the convolution.
-       * @param strides strides array.
-       * @param padding padding mode. Default to 'valid'.
-       * @param dataFormat data format. Defaults to 'channelsLast'.
-       * @param dilationRate dilation rate array.
-       * @returns Result of the 2D pooling.
-       */
-      function conv2d(x, kernel, strides = [1, 1], padding = "valid", dataFormat, dilationRate) {
-        return Object(dist["tidy"])(() => {
-          checkDataFormat(dataFormat);
-          return conv2dWithBiasActivation(
-            x,
-            kernel,
-            null,
-            strides,
-            padding,
-            dataFormat,
-            dilationRate
-          );
-        });
-      }
-      /**
-       * 2D Convolution with an added bias and optional activation.
-       * Note: This function does not exist in the Python Keras Backend. This function
-       * is exactly the same as `conv2d`, except the added `bias`.
-       */
-      function conv2dWithBiasActivation(
-        x,
-        kernel,
-        bias,
-        strides = [1, 1],
-        padding = "valid",
-        dataFormat,
-        dilationRate,
-        activation = null
-      ) {
-        return Object(dist["tidy"])(() => {
-          if (dataFormat == null) {
-            dataFormat = imageDataFormat();
-          }
-          checkDataFormat(dataFormat);
-          if (x.rank !== 3 && x.rank !== 4) {
-            throw new ValueError(
-              `conv2dWithBiasActivation expects input to be of rank 3 or 4, ` +
-                `but received ${x.rank}.`
-            );
-          }
-          if (kernel.rank !== 3 && kernel.rank !== 4) {
-            throw new ValueError(
-              `conv2dWithBiasActivation expects kernel to be of rank 3 or 4, ` +
-                `but received ${x.rank}.`
-            );
-          }
-          let y = preprocessConv2DInput(x, dataFormat);
-          if (padding === "causal") {
-            throw new NotImplementedError(
-              "The support for CAUSAL padding mode in conv1dWithBias is not " + "implemented yet."
-            );
-          }
-          y = dist["fused"].conv2d({
-            x: y,
-            filter: kernel,
-            strides: strides,
-            pad: padding === "same" ? "same" : "valid",
-            dilations: dilationRate,
-            dataFormat: "NHWC",
-            bias,
-            activation,
-          });
-          if (dataFormat === "channelsFirst") {
-            y = dist["transpose"](y, [0, 3, 1, 2]);
-          }
-          return y;
-        });
-      }
-      /**
-       * 3D Convolution.
-       * @param x
-       * @param kernel kernel of the convolution.
-       * @param strides strides array.
-       * @param padding padding mode. Default to 'valid'.
-       * @param dataFormat data format. Defaults to 'channelsLast'.
-       * @param dilationRate dilation rate array.
-       * @returns Result of the 3D convolution.
-       */
-      function conv3d(x, kernel, strides = [1, 1, 1], padding = "valid", dataFormat, dilationRate) {
-        return Object(dist["tidy"])(() => {
-          checkDataFormat(dataFormat);
-          return conv3dWithBias(x, kernel, null, strides, padding, dataFormat, dilationRate);
-        });
-      }
-      /**
-       * 3D Convolution with an added bias.
-       * Note: This function does not exist in the Python Keras Backend. This function
-       * is exactly the same as `conv3d`, except the added `bias`.
-       */
-      function conv3dWithBias(
-        x,
-        kernel,
-        bias,
-        strides = [1, 1, 1],
-        padding = "valid",
-        dataFormat,
-        dilationRate
-      ) {
-        return Object(dist["tidy"])(() => {
-          if (dataFormat == null) {
-            dataFormat = imageDataFormat();
-          }
-          checkDataFormat(dataFormat);
-          if (x.rank !== 4 && x.rank !== 5) {
-            throw new ValueError(
-              `conv3dWithBias expects input to be of rank 4 or 5, but received ` + `${x.rank}.`
-            );
-          }
-          if (kernel.rank !== 4 && kernel.rank !== 5) {
-            throw new ValueError(
-              `conv3dWithBias expects kernel to be of rank 4 or 5, but received ` + `${x.rank}.`
-            );
-          }
-          let y = preprocessConv3DInput(x, dataFormat);
-          if (padding === "causal") {
-            throw new NotImplementedError(
-              "The support for CAUSAL padding mode in conv3dWithBias is not " + "implemented yet."
-            );
-          }
-          y = dist["conv3d"](
-            y,
-            kernel,
-            strides,
-            padding === "same" ? "same" : "valid",
-            "NDHWC",
-            dilationRate
-          );
-          if (bias != null) {
-            y = biasAdd(y, bias);
-          }
-          if (dataFormat === "channelsFirst") {
-            y = dist["transpose"](y, [0, 4, 1, 2, 3]);
-          }
-          return y;
-        });
-      }
-      /**
-       * Abstract convolution layer.
-       */
-      class convolutional_BaseConv extends topology_Layer {
-        constructor(rank, args) {
-          super(args);
-          this.bias = null;
-          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
-          this.DEFAULT_BIAS_INITIALIZER = "zeros";
-          convolutional_BaseConv.verifyArgs(args);
-          this.rank = rank;
-          assertPositiveInteger(this.rank, "rank");
-          if (this.rank !== 1 && this.rank !== 2 && this.rank !== 3) {
-            throw new NotImplementedError(
-              `Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is ` +
-                `not implemented yet.`
-            );
-          }
-          this.kernelSize = normalizeArray(args.kernelSize, rank, "kernelSize");
-          this.strides = normalizeArray(args.strides == null ? 1 : args.strides, rank, "strides");
-          this.padding = args.padding == null ? "valid" : args.padding;
-          checkPaddingMode(this.padding);
-          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
-          checkDataFormat(this.dataFormat);
-          this.activation = getActivation(args.activation);
-          this.useBias = args.useBias == null ? true : args.useBias;
-          this.biasInitializer = getInitializer(
-            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
-          );
-          this.biasConstraint = getConstraint(args.biasConstraint);
-          this.biasRegularizer = getRegularizer(args.biasRegularizer);
-          this.activityRegularizer = getRegularizer(args.activityRegularizer);
-          this.dilationRate = normalizeArray(
-            args.dilationRate == null ? 1 : args.dilationRate,
-            rank,
-            "dilationRate"
-          );
-          if (
-            this.rank === 1 &&
-            Array.isArray(this.dilationRate) &&
-            this.dilationRate.length !== 1
-          ) {
-            throw new ValueError(
-              `dilationRate must be a number or an array of a single number ` +
-                `for 1D convolution, but received ` +
-                `${JSON.stringify(this.dilationRate)}`
-            );
-          } else if (this.rank === 2) {
-            if (typeof this.dilationRate === "number") {
-              this.dilationRate = [this.dilationRate, this.dilationRate];
-            } else if (this.dilationRate.length !== 2) {
-              throw new ValueError(
-                `dilationRate must be a number or array of two numbers for 2D ` +
-                  `convolution, but received ${JSON.stringify(this.dilationRate)}`
-              );
-            }
-          } else if (this.rank === 3) {
-            if (typeof this.dilationRate === "number") {
-              this.dilationRate = [this.dilationRate, this.dilationRate, this.dilationRate];
-            } else if (this.dilationRate.length !== 3) {
-              throw new ValueError(
-                `dilationRate must be a number or array of three numbers for 3D ` +
-                  `convolution, but received ${JSON.stringify(this.dilationRate)}`
-              );
-            }
-          }
-        }
-        static verifyArgs(args) {
-          // Check config.kernelSize type and shape.
-          assert("kernelSize" in args, `required key 'kernelSize' not in config`);
-          if (
-            typeof args.kernelSize !== "number" &&
-            !checkArrayTypeAndLength(args.kernelSize, "number", 1, 3)
-          ) {
-            throw new ValueError(
-              `BaseConv expects config.kernelSize to be number or number[] with ` +
-                `length 1, 2, or 3, but received ${JSON.stringify(args.kernelSize)}.`
-            );
-          }
-        }
-        getConfig() {
-          const config = {
-            kernelSize: this.kernelSize,
-            strides: this.strides,
-            padding: this.padding,
-            dataFormat: this.dataFormat,
-            dilationRate: this.dilationRate,
-            activation: serializeActivation(this.activation),
-            useBias: this.useBias,
-            biasInitializer: serializeInitializer(this.biasInitializer),
-            biasRegularizer: serializeRegularizer(this.biasRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            biasConstraint: serializeConstraint(this.biasConstraint),
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /**
-       * Abstract nD convolution layer.  Ancestor of convolution layers which reduce
-       * across channels, i.e., Conv1D and Conv2D, but not DepthwiseConv2D.
-       */
-      class convolutional_Conv extends convolutional_BaseConv {
-        constructor(rank, args) {
-          super(rank, args);
-          this.kernel = null;
-          convolutional_Conv.verifyArgs(args);
-          this.filters = args.filters;
-          assertPositiveInteger(this.filters, "filters");
-          this.kernelInitializer = getInitializer(
-            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
-          );
-          this.kernelConstraint = getConstraint(args.kernelConstraint);
-          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const channelAxis = this.dataFormat === "channelsFirst" ? 1 : inputShape.length - 1;
-          if (inputShape[channelAxis] == null) {
-            throw new ValueError(
-              `The channel dimension of the input should be defined. ` +
-                `Found ${inputShape[channelAxis]}`
-            );
-          }
-          const inputDim = inputShape[channelAxis];
-          const kernelShape = this.kernelSize.concat([inputDim, this.filters]);
-          this.kernel = this.addWeight(
-            "kernel",
-            kernelShape,
-            null,
-            this.kernelInitializer,
-            this.kernelRegularizer,
-            true,
-            this.kernelConstraint
-          );
-          if (this.useBias) {
-            this.bias = this.addWeight(
-              "bias",
-              [this.filters],
-              null,
-              this.biasInitializer,
-              this.biasRegularizer,
-              true,
-              this.biasConstraint
-            );
-          }
-          this.inputSpec = [{ ndim: this.rank + 2, axes: { [channelAxis]: inputDim } }];
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = getExactlyOneTensor(inputs);
-            let outputs;
-            const biasValue = this.bias == null ? null : this.bias.read();
-            const fusedActivationName = mapActivationToFusedKernel(this.activation.getClassName());
-            if (fusedActivationName != null && this.rank === 2) {
-              outputs = conv2dWithBiasActivation(
-                inputs,
-                this.kernel.read(),
-                biasValue,
-                this.strides,
-                this.padding,
-                this.dataFormat,
-                this.dilationRate,
-                fusedActivationName
-              );
-            } else {
-              if (this.rank === 1) {
-                outputs = conv1dWithBias(
-                  inputs,
-                  this.kernel.read(),
-                  biasValue,
-                  this.strides[0],
-                  this.padding,
-                  this.dataFormat,
-                  this.dilationRate[0]
-                );
-              } else if (this.rank === 2) {
-                // TODO(cais): Move up to constructor.
-                outputs = conv2dWithBiasActivation(
-                  inputs,
-                  this.kernel.read(),
-                  biasValue,
-                  this.strides,
-                  this.padding,
-                  this.dataFormat,
-                  this.dilationRate
-                );
-              } else if (this.rank === 3) {
-                outputs = conv3dWithBias(
-                  inputs,
-                  this.kernel.read(),
-                  biasValue,
-                  this.strides,
-                  this.padding,
-                  this.dataFormat,
-                  this.dilationRate
-                );
-              } else {
-                throw new NotImplementedError(
-                  "convolutions greater than 3D are not implemented yet."
-                );
-              }
-              if (this.activation != null) {
-                outputs = this.activation.apply(outputs);
-              }
-            }
-            return outputs;
-          });
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const newSpace = [];
-          const space =
-            this.dataFormat === "channelsLast"
-              ? inputShape.slice(1, inputShape.length - 1)
-              : inputShape.slice(2);
-          for (let i = 0; i < space.length; ++i) {
-            const newDim = convOutputLength(
-              space[i],
-              this.kernelSize[i],
-              this.padding,
-              this.strides[i],
-              typeof this.dilationRate === "number" ? this.dilationRate : this.dilationRate[i]
-            );
-            newSpace.push(newDim);
-          }
-          let outputShape = [inputShape[0]];
-          if (this.dataFormat === "channelsLast") {
-            outputShape = outputShape.concat(newSpace);
-            outputShape.push(this.filters);
-          } else {
-            outputShape.push(this.filters);
-            outputShape = outputShape.concat(newSpace);
-          }
-          return outputShape;
-        }
-        getConfig() {
-          const config = {
-            filters: this.filters,
-            kernelInitializer: serializeInitializer(this.kernelInitializer),
-            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
-            kernelConstraint: serializeConstraint(this.kernelConstraint),
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        static verifyArgs(args) {
-          // Check config.filters type, shape, and value.
-          if (!("filters" in args) || typeof args.filters !== "number" || args.filters < 1) {
-            throw new ValueError(
-              `Convolution layer expected config.filters to be a 'number' > 0 ` +
-                `but got ${JSON.stringify(args.filters)}`
-            );
-          }
-        }
-      }
-      class convolutional_Conv2D extends convolutional_Conv {
-        constructor(args) {
-          super(2, args);
-          convolutional_Conv2D.verifyArgs(args);
-        }
-        getConfig() {
-          const config = super.getConfig();
-          delete config["rank"];
-          return config;
-        }
-        static verifyArgs(args) {
-          // config.kernelSize must be a number or array of numbers.
-          if (
-            typeof args.kernelSize !== "number" &&
-            !checkArrayTypeAndLength(args.kernelSize, "number", 1, 2)
-          ) {
-            throw new ValueError(
-              `Conv2D expects config.kernelSize to be number or number[] with ` +
-                `length 1 or 2, but received ${JSON.stringify(args.kernelSize)}.`
-            );
-          }
-        }
-      }
-      /** @nocollapse */
-      convolutional_Conv2D.className = "Conv2D";
-      dist["serialization"].registerClass(convolutional_Conv2D);
-      class convolutional_Conv3D extends convolutional_Conv {
-        constructor(args) {
-          super(3, args);
-          convolutional_Conv3D.verifyArgs(args);
-        }
-        getConfig() {
-          const config = super.getConfig();
-          delete config["rank"];
-          return config;
-        }
-        static verifyArgs(args) {
-          // config.kernelSize must be a number or array of numbers.
-          if (typeof args.kernelSize !== "number") {
-            if (
-              !(
-                Array.isArray(args.kernelSize) &&
-                (args.kernelSize.length === 1 || args.kernelSize.length === 3)
-              )
-            ) {
-              throw new ValueError(
-                `Conv3D expects config.kernelSize to be number or` +
-                  ` [number, number, number], but received ${JSON.stringify(args.kernelSize)}.`
-              );
-            }
-          }
-        }
-      }
-      /** @nocollapse */
-      convolutional_Conv3D.className = "Conv3D";
-      dist["serialization"].registerClass(convolutional_Conv3D);
-      class convolutional_Conv2DTranspose extends convolutional_Conv2D {
-        constructor(args) {
-          super(args);
-          this.inputSpec = [new InputSpec({ ndim: 4 })];
-          if (this.padding !== "same" && this.padding !== "valid") {
-            throw new ValueError(
-              `Conv2DTranspose currently supports only padding modes 'same' ` +
-                `and 'valid', but received padding mode ${this.padding}`
-            );
-          }
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          if (inputShape.length !== 4) {
-            throw new ValueError(
-              "Input should have rank 4; Received input shape: " + JSON.stringify(inputShape)
-            );
-          }
-          const channelAxis = this.dataFormat === "channelsFirst" ? 1 : inputShape.length - 1;
-          if (inputShape[channelAxis] == null) {
-            throw new ValueError(
-              "The channel dimension of the inputs should be defined. " + "Found `None`."
-            );
-          }
-          const inputDim = inputShape[channelAxis];
-          const kernelShape = this.kernelSize.concat([this.filters, inputDim]);
-          this.kernel = this.addWeight(
-            "kernel",
-            kernelShape,
-            "float32",
-            this.kernelInitializer,
-            this.kernelRegularizer,
-            true,
-            this.kernelConstraint
-          );
-          if (this.useBias) {
-            this.bias = this.addWeight(
-              "bias",
-              [this.filters],
-              "float32",
-              this.biasInitializer,
-              this.biasRegularizer,
-              true,
-              this.biasConstraint
-            );
-          }
-          // Set input spec.
-          this.inputSpec = [new InputSpec({ ndim: 4, axes: { [channelAxis]: inputDim } })];
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          return dist["tidy"](() => {
-            let input = getExactlyOneTensor(inputs);
-            if (input.shape.length !== 4) {
-              throw new ValueError(
-                `Conv2DTranspose.call() expects input tensor to be rank-4, but ` +
-                  `received a tensor of rank-${input.shape.length}`
-              );
-            }
-            const inputShape = input.shape;
-            const batchSize = inputShape[0];
-            let hAxis;
-            let wAxis;
-            if (this.dataFormat === "channelsFirst") {
-              hAxis = 2;
-              wAxis = 3;
-            } else {
-              hAxis = 1;
-              wAxis = 2;
-            }
-            const height = inputShape[hAxis];
-            const width = inputShape[wAxis];
-            const kernelH = this.kernelSize[0];
-            const kernelW = this.kernelSize[1];
-            const strideH = this.strides[0];
-            const strideW = this.strides[1];
-            // Infer the dynamic output shape.
-            const outHeight = deconvLength(height, strideH, kernelH, this.padding);
-            const outWidth = deconvLength(width, strideW, kernelW, this.padding);
-            // Porting Note: We don't branch based on `this.dataFormat` here,
-            // because
-            //   the tjfs-core function `conv2dTranspose` called below always
-            //   assumes channelsLast.
-            const outputShape = [batchSize, outHeight, outWidth, this.filters];
-            if (this.dataFormat !== "channelsLast") {
-              input = dist["transpose"](input, [0, 2, 3, 1]);
-            }
-            let outputs = dist["conv2dTranspose"](
-              input,
-              this.kernel.read(),
-              outputShape,
-              this.strides,
-              this.padding
-            );
-            if (this.dataFormat !== "channelsLast") {
-              outputs = dist["transpose"](outputs, [0, 3, 1, 2]);
-            }
-            if (this.bias != null) {
-              outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);
-            }
-            if (this.activation != null) {
-              outputs = this.activation.apply(outputs);
-            }
-            return outputs;
-          });
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const outputShape = inputShape.slice();
-          let channelAxis;
-          let heightAxis;
-          let widthAxis;
-          if (this.dataFormat === "channelsFirst") {
-            channelAxis = 1;
-            heightAxis = 2;
-            widthAxis = 3;
-          } else {
-            channelAxis = 3;
-            heightAxis = 1;
-            widthAxis = 2;
-          }
-          const kernelH = this.kernelSize[0];
-          const kernelW = this.kernelSize[1];
-          const strideH = this.strides[0];
-          const strideW = this.strides[1];
-          outputShape[channelAxis] = this.filters;
-          outputShape[heightAxis] = deconvLength(
-            outputShape[heightAxis],
-            strideH,
-            kernelH,
-            this.padding
-          );
-          outputShape[widthAxis] = deconvLength(
-            outputShape[widthAxis],
-            strideW,
-            kernelW,
-            this.padding
-          );
-          return outputShape;
-        }
-        getConfig() {
-          const config = super.getConfig();
-          delete config["dilationRate"];
-          return config;
-        }
-      }
-      /** @nocollapse */
-      convolutional_Conv2DTranspose.className = "Conv2DTranspose";
-      dist["serialization"].registerClass(convolutional_Conv2DTranspose);
-      class convolutional_SeparableConv extends convolutional_Conv {
-        constructor(rank, config) {
-          super(rank, config);
-          this.DEFAULT_DEPTHWISE_INITIALIZER = "glorotUniform";
-          this.DEFAULT_POINTWISE_INITIALIZER = "glorotUniform";
-          this.depthwiseKernel = null;
-          this.pointwiseKernel = null;
-          if (config.filters == null) {
-            throw new ValueError(
-              "The `filters` configuration field is required by SeparableConv, " +
-                "but is unspecified."
-            );
-          }
-          if (
-            config.kernelInitializer != null ||
-            config.kernelRegularizer != null ||
-            config.kernelConstraint != null
-          ) {
-            throw new ValueError(
-              "Fields kernelInitializer, kernelRegularizer and kernelConstraint " +
-                "are invalid for SeparableConv2D. Use depthwiseInitializer, " +
-                "depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, " +
-                "pointwiseRegularizer and pointwiseConstraint instead."
-            );
-          }
-          if (config.padding != null && config.padding !== "same" && config.padding !== "valid") {
-            throw new ValueError(
-              `SeparableConv${this.rank}D supports only padding modes: ` +
-                `'same' and 'valid', but received ${JSON.stringify(config.padding)}`
-            );
-          }
-          this.depthMultiplier = config.depthMultiplier == null ? 1 : config.depthMultiplier;
-          this.depthwiseInitializer = getInitializer(
-            config.depthwiseInitializer || this.DEFAULT_DEPTHWISE_INITIALIZER
-          );
-          this.depthwiseRegularizer = getRegularizer(config.depthwiseRegularizer);
-          this.depthwiseConstraint = getConstraint(config.depthwiseConstraint);
-          this.pointwiseInitializer = getInitializer(
-            config.depthwiseInitializer || this.DEFAULT_POINTWISE_INITIALIZER
-          );
-          this.pointwiseRegularizer = getRegularizer(config.pointwiseRegularizer);
-          this.pointwiseConstraint = getConstraint(config.pointwiseConstraint);
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          if (inputShape.length < this.rank + 2) {
-            throw new ValueError(
-              `Inputs to SeparableConv${this.rank}D should have rank ` +
-                `${this.rank + 2}, but received input shape: ` +
-                `${JSON.stringify(inputShape)}`
-            );
-          }
-          const channelAxis = this.dataFormat === "channelsFirst" ? 1 : inputShape.length - 1;
-          if (inputShape[channelAxis] == null || inputShape[channelAxis] < 0) {
-            throw new ValueError(
-              `The channel dimension of the inputs should be defined, ` +
-                `but found ${JSON.stringify(inputShape[channelAxis])}`
-            );
-          }
-          const inputDim = inputShape[channelAxis];
-          const depthwiseKernelShape = this.kernelSize.concat([inputDim, this.depthMultiplier]);
-          const pointwiseKernelShape = [];
-          for (let i = 0; i < this.rank; ++i) {
-            pointwiseKernelShape.push(1);
-          }
-          pointwiseKernelShape.push(inputDim * this.depthMultiplier, this.filters);
-          const trainable = true;
-          this.depthwiseKernel = this.addWeight(
-            "depthwise_kernel",
-            depthwiseKernelShape,
-            "float32",
-            this.depthwiseInitializer,
-            this.depthwiseRegularizer,
-            trainable,
-            this.depthwiseConstraint
-          );
-          this.pointwiseKernel = this.addWeight(
-            "pointwise_kernel",
-            pointwiseKernelShape,
-            "float32",
-            this.pointwiseInitializer,
-            this.pointwiseRegularizer,
-            trainable,
-            this.pointwiseConstraint
-          );
-          if (this.useBias) {
-            this.bias = this.addWeight(
-              "bias",
-              [this.filters],
-              "float32",
-              this.biasInitializer,
-              this.biasRegularizer,
-              trainable,
-              this.biasConstraint
-            );
-          } else {
-            this.bias = null;
-          }
-          this.inputSpec = [
-            new InputSpec({ ndim: this.rank + 2, axes: { [channelAxis]: inputDim } }),
-          ];
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = getExactlyOneTensor(inputs);
-            let output;
-            if (this.rank === 1) {
-              throw new NotImplementedError("1D separable convolution is not implemented yet.");
-            } else if (this.rank === 2) {
-              if (this.dataFormat === "channelsFirst") {
-                inputs = dist["transpose"](inputs, [0, 2, 3, 1]); // NCHW -> NHWC.
-              }
-              output = dist["separableConv2d"](
-                inputs,
-                this.depthwiseKernel.read(),
-                this.pointwiseKernel.read(),
-                this.strides,
-                this.padding,
-                this.dilationRate,
-                "NHWC"
-              );
-            }
-            if (this.useBias) {
-              output = biasAdd(output, this.bias.read(), this.dataFormat);
-            }
-            if (this.activation != null) {
-              output = this.activation.apply(output);
-            }
-            if (this.dataFormat === "channelsFirst") {
-              output = dist["transpose"](output, [0, 3, 1, 2]); // NHWC -> NCHW.
-            }
-            return output;
-          });
-        }
-        getConfig() {
-          const config = super.getConfig();
-          delete config["rank"];
-          delete config["kernelInitializer"];
-          delete config["kernelRegularizer"];
-          delete config["kernelConstraint"];
-          config["depthwiseInitializer"] = serializeInitializer(this.depthwiseInitializer);
-          config["pointwiseInitializer"] = serializeInitializer(this.pointwiseInitializer);
-          config["depthwiseRegularizer"] = serializeRegularizer(this.depthwiseRegularizer);
-          config["pointwiseRegularizer"] = serializeRegularizer(this.pointwiseRegularizer);
-          config["depthwiseConstraint"] = serializeConstraint(this.depthwiseConstraint);
-          config["pointwiseConstraint"] = serializeConstraint(this.pointwiseConstraint);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      convolutional_SeparableConv.className = "SeparableConv";
-      class SeparableConv2D extends convolutional_SeparableConv {
-        constructor(args) {
-          super(2, args);
-        }
-      }
-      /** @nocollapse */
-      SeparableConv2D.className = "SeparableConv2D";
-      dist["serialization"].registerClass(SeparableConv2D);
-      class convolutional_Conv1D extends convolutional_Conv {
-        constructor(args) {
-          super(1, args);
-          convolutional_Conv1D.verifyArgs(args);
-          this.inputSpec = [{ ndim: 3 }];
-        }
-        getConfig() {
-          const config = super.getConfig();
-          delete config["rank"];
-          delete config["dataFormat"];
-          return config;
-        }
-        static verifyArgs(args) {
-          // config.kernelSize must be a number or array of numbers.
-          if (
-            typeof args.kernelSize !== "number" &&
-            !checkArrayTypeAndLength(args.kernelSize, "number", 1, 1)
-          ) {
-            throw new ValueError(
-              `Conv1D expects config.kernelSize to be number or number[] with ` +
-                `length 1, but received ${JSON.stringify(args.kernelSize)}.`
-            );
-          }
-        }
-      }
-      /** @nocollapse */
-      convolutional_Conv1D.className = "Conv1D";
-      dist["serialization"].registerClass(convolutional_Conv1D);
-      class convolutional_Cropping2D extends topology_Layer {
-        constructor(args) {
-          super(args);
-          if (typeof args.cropping === "number") {
-            this.cropping = [
-              [args.cropping, args.cropping],
-              [args.cropping, args.cropping],
-            ];
-          } else if (typeof args.cropping[0] === "number") {
-            this.cropping = [
-              [args.cropping[0], args.cropping[0]],
-              [args.cropping[1], args.cropping[1]],
-            ];
-          } else {
-            this.cropping = args.cropping;
-          }
-          this.dataFormat = args.dataFormat === undefined ? "channelsLast" : args.dataFormat;
-          this.inputSpec = [{ ndim: 4 }];
-        }
-        computeOutputShape(inputShape) {
-          if (this.dataFormat === "channelsFirst") {
-            return [
-              inputShape[0],
-              inputShape[1],
-              inputShape[2] - this.cropping[0][0] - this.cropping[0][1],
-              inputShape[3] - this.cropping[1][0] - this.cropping[1][1],
-            ];
-          } else {
-            return [
-              inputShape[0],
-              inputShape[1] - this.cropping[0][0] - this.cropping[0][1],
-              inputShape[2] - this.cropping[1][0] - this.cropping[1][1],
-              inputShape[3],
-            ];
-          }
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = getExactlyOneTensor(inputs);
-            if (this.dataFormat === "channelsLast") {
-              const hSliced = sliceAlongAxis(
-                inputs,
-                this.cropping[0][0],
-                inputs.shape[1] - this.cropping[0][0] - this.cropping[0][1],
-                2
-              );
-              return sliceAlongAxis(
-                hSliced,
-                this.cropping[1][0],
-                inputs.shape[2] - this.cropping[1][1] - this.cropping[1][0],
-                3
-              );
-            } else {
-              const hSliced = sliceAlongAxis(
-                inputs,
-                this.cropping[0][0],
-                inputs.shape[2] - this.cropping[0][0] - this.cropping[0][1],
-                3
-              );
-              return sliceAlongAxis(
-                hSliced,
-                this.cropping[1][0],
-                inputs.shape[3] - this.cropping[1][1] - this.cropping[1][0],
-                4
-              );
-            }
-          });
-        }
-        getConfig() {
-          const config = { cropping: this.cropping, dataFormat: this.dataFormat };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      convolutional_Cropping2D.className = "Cropping2D";
-      dist["serialization"].registerClass(convolutional_Cropping2D);
-      class convolutional_UpSampling2D extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.DEFAULT_SIZE = [2, 2];
-          this.inputSpec = [{ ndim: 4 }];
-          this.size = args.size == null ? this.DEFAULT_SIZE : args.size;
-          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
-        }
-        computeOutputShape(inputShape) {
-          if (this.dataFormat === "channelsFirst") {
-            const height = inputShape[2] == null ? null : this.size[0] * inputShape[2];
-            const width = inputShape[3] == null ? null : this.size[1] * inputShape[3];
-            return [inputShape[0], inputShape[1], height, width];
-          } else {
-            const height = inputShape[1] == null ? null : this.size[0] * inputShape[1];
-            const width = inputShape[2] == null ? null : this.size[1] * inputShape[2];
-            return [inputShape[0], height, width, inputShape[3]];
-          }
-        }
-        call(inputs, kwargs) {
-          return dist["tidy"](() => {
-            let input = getExactlyOneTensor(inputs);
-            const inputShape = input.shape;
-            if (this.dataFormat === "channelsFirst") {
-              input = dist["transpose"](input, [0, 2, 3, 1]);
-              const height = this.size[0] * inputShape[2];
-              const width = this.size[1] * inputShape[3];
-              const resized = input.resizeNearestNeighbor([height, width]);
-              return dist["transpose"](resized, [0, 3, 1, 2]);
-            } else {
-              const height = this.size[0] * inputShape[1];
-              const width = this.size[1] * inputShape[2];
-              return input.resizeNearestNeighbor([height, width]);
-            }
-          });
-        }
-        getConfig() {
-          const config = { size: this.size, dataFormat: this.dataFormat };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      convolutional_UpSampling2D.className = "UpSampling2D";
-      dist["serialization"].registerClass(convolutional_UpSampling2D);
-      //# sourceMappingURL=convolutional.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional_depthwise.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * TensorFlow.js Layers: Depthwise Convolutional Layers
-       */
-
-      /**
-       * 2D convolution with separable filters.
-       * @param x Input tensor.
-       * @param depthwiseKernel Convolution kernel for depthwise convolution.
-       * @param strides Strides (Array of two integers).
-       * @param padding Padding model.
-       * @param dataFormat Data format.
-       * @param dilationRate Array of two integers, dilation rates for the separable
-       *   convolution.
-       * @returns Output tensor.
-       * @throws ValueError If depthwiseKernel is not a 4D array.
-       */
-      function depthwiseConv2d(
-        x,
-        depthwiseKernel,
-        strides = [1, 1],
-        padding = "valid",
-        dataFormat,
-        dilationRate
-      ) {
-        return Object(dist["tidy"])(() => {
-          if (dataFormat == null) {
-            dataFormat = imageDataFormat();
-          }
-          checkDataFormat(dataFormat);
-          let y = preprocessConv2DInput(x, dataFormat);
-          if (x.rank !== 4) {
-            throw new ValueError(
-              `Input for depthwiseConv2d is required to be 4-D, but is instead ` + `${x.rank}-D`
-            );
-          }
-          if (depthwiseKernel.rank !== 4) {
-            throw new ValueError(
-              `depthwiseKernel is required to be 4-D, but is instead ` + `${depthwiseKernel.rank}-D`
-            );
-          }
-          y = dist["depthwiseConv2d"](
-            y,
-            depthwiseKernel,
-            strides,
-            padding === "same" ? "same" : "valid",
-            "NHWC",
-            dilationRate
-          );
-          if (dataFormat === "channelsFirst") {
-            y = dist["transpose"](y, [0, 3, 1, 2]);
-          }
-          return y;
-        });
-      }
-      class convolutional_depthwise_DepthwiseConv2D extends convolutional_BaseConv {
-        constructor(args) {
-          super(2, args);
-          this.depthwiseKernel = null;
-          this.depthMultiplier = args.depthMultiplier == null ? 1 : args.depthMultiplier;
-          this.depthwiseInitializer = getInitializer(
-            args.depthwiseInitializer || this.DEFAULT_KERNEL_INITIALIZER
-          );
-          this.depthwiseConstraint = getConstraint(args.depthwiseConstraint);
-          this.depthwiseRegularizer = getRegularizer(args.depthwiseRegularizer);
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          if (inputShape.length < 4) {
-            throw new ValueError(
-              `Inputs to DepthwiseConv2D should have rank 4. ` +
-                `Received input shape: ${JSON.stringify(inputShape)}.`
-            );
-          }
-          const channelAxis = this.dataFormat === "channelsFirst" ? 1 : 3;
-          if (inputShape[channelAxis] == null || inputShape[channelAxis] < 0) {
-            throw new ValueError(
-              "The channel dimension of the inputs to DepthwiseConv2D should " +
-                `be defined, but is not (${inputShape[channelAxis]}).`
-            );
-          }
-          const inputDim = inputShape[channelAxis];
-          const depthwiseKernelShape = [
-            this.kernelSize[0],
-            this.kernelSize[1],
-            inputDim,
-            this.depthMultiplier,
-          ];
-          this.depthwiseKernel = this.addWeight(
-            "depthwise_kernel",
-            depthwiseKernelShape,
-            null,
-            this.depthwiseInitializer,
-            this.depthwiseRegularizer,
-            true,
-            this.depthwiseConstraint
-          );
-          if (this.useBias) {
-            this.bias = this.addWeight(
-              "bias",
-              [inputDim * this.depthMultiplier],
-              null,
-              this.biasInitializer,
-              this.biasRegularizer,
-              true,
-              this.biasConstraint
-            );
-          } else {
-            this.bias = null;
-          }
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = getExactlyOneTensor(inputs);
-            let outputs = depthwiseConv2d(
-              inputs,
-              this.depthwiseKernel.read(),
-              this.strides,
-              this.padding,
-              this.dataFormat,
-              null
-            );
-            // TODO(cais): Add support for dilation.
-            if (this.useBias) {
-              outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);
-            }
-            if (this.activation != null) {
-              outputs = this.activation.apply(outputs);
-            }
-            return outputs;
-          });
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const rows = this.dataFormat === "channelsFirst" ? inputShape[2] : inputShape[1];
-          const cols = this.dataFormat === "channelsFirst" ? inputShape[3] : inputShape[2];
-          const outFilters =
-            this.dataFormat === "channelsFirst"
-              ? inputShape[1] * this.depthMultiplier
-              : inputShape[3] * this.depthMultiplier;
-          const outRows = convOutputLength(rows, this.kernelSize[0], this.padding, this.strides[0]);
-          const outCols = convOutputLength(cols, this.kernelSize[1], this.padding, this.strides[1]);
-          if (this.dataFormat === "channelsFirst") {
-            return [inputShape[0], outFilters, outRows, outCols];
-          } else {
-            // In this case, assume 'channelsLast'.
-            return [inputShape[0], outRows, outCols, outFilters];
-          }
-        }
-        getConfig() {
-          const config = super.getConfig();
-          config["depthMultiplier"] = this.depthMultiplier;
-          config["depthwiseInitializer"] = serializeInitializer(this.depthwiseInitializer);
-          config["depthwiseRegularizer"] = serializeRegularizer(this.depthwiseRegularizer);
-          config["depthwiseConstraint"] = serializeConstraint(this.depthwiseRegularizer);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      convolutional_depthwise_DepthwiseConv2D.className = "DepthwiseConv2D";
-      dist["serialization"].registerClass(convolutional_depthwise_DepthwiseConv2D);
-      //# sourceMappingURL=convolutional_depthwise.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/core.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * TensorFlow.js Layers: Basic Layers.
-       */
-
-      class core_Dropout extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.rate = Math.max(Math.min(args.rate, 1), 0);
-          // So that the scalar doesn't get tidied up between executions.
-          this.noiseShape = args.noiseShape;
-          this.seed = args.seed;
-          this.supportsMasking = true;
-        }
-        getNoiseShape(input) {
-          if (this.noiseShape == null) {
-            return this.noiseShape;
-          }
-          const inputShape = input.shape;
-          const noiseShape = [];
-          for (let i = 0; i < this.noiseShape.length; ++i) {
-            noiseShape.push(this.noiseShape[i] == null ? inputShape[i] : this.noiseShape[i]);
-          }
-          return noiseShape;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            const input = getExactlyOneTensor(inputs);
-            if (0 < this.rate && this.rate < 1) {
-              const training = kwargs["training"] == null ? false : kwargs["training"];
-              const noiseShape = this.getNoiseShape(input);
-              const output = inTrainPhase(
-                () => dropout(input, this.rate, noiseShape, this.seed),
-                () => input,
-                training
-              );
-              return output;
-            }
-            return inputs;
-          });
-        }
-        getConfig() {
-          const config = {
-            rate: this.rate,
-            noiseShape: this.noiseShape,
-            seed: this.seed,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        dispose() {
-          return super.dispose();
-        }
-      }
-      /** @nocollapse */
-      core_Dropout.className = "Dropout";
-      dist["serialization"].registerClass(core_Dropout);
-      class SpatialDropout1D extends core_Dropout {
-        constructor(args) {
-          super(args);
-          this.inputSpec = [{ ndim: 3 }];
-        }
-        getNoiseShape(input) {
-          const inputShape = input.shape;
-          return [inputShape[0], 1, inputShape[2]];
-        }
-      }
-      /** @nocollapse */
-      SpatialDropout1D.className = "SpatialDropout1D";
-      dist["serialization"].registerClass(SpatialDropout1D);
-      class core_Dense extends topology_Layer {
-        constructor(args) {
-          super(args);
-          // Default activation: Linear (none).
-          this.activation = null;
-          this.useBias = true;
-          this.kernel = null;
-          this.bias = null;
-          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
-          this.DEFAULT_BIAS_INITIALIZER = "zeros";
-          if (args.batchInputShape == null && args.inputShape == null && args.inputDim != null) {
-            // This logic is copied from Layer's constructor, since we can't
-            // do exactly what the Python constructor does for Dense().
-            let batchSize = null;
-            if (args.batchSize != null) {
-              batchSize = args.batchSize;
-            }
-            this.batchInputShape = [batchSize, args.inputDim];
-          }
-          this.units = args.units;
-          assertPositiveInteger(this.units, "units");
-          this.activation = getActivation(args.activation);
-          if (args.useBias != null) {
-            this.useBias = args.useBias;
-          }
-          this.kernelInitializer = getInitializer(
-            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
-          );
-          this.biasInitializer = getInitializer(
-            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
-          );
-          this.kernelConstraint = getConstraint(args.kernelConstraint);
-          this.biasConstraint = getConstraint(args.biasConstraint);
-          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
-          this.biasRegularizer = getRegularizer(args.biasRegularizer);
-          this.activityRegularizer = getRegularizer(args.activityRegularizer);
-          this.supportsMasking = true;
-          this.inputSpec = [{ minNDim: 2 }];
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const inputLastDim = inputShape[inputShape.length - 1];
-          if (this.kernel == null) {
-            this.kernel = this.addWeight(
-              "kernel",
-              [inputLastDim, this.units],
-              null,
-              this.kernelInitializer,
-              this.kernelRegularizer,
-              true,
-              this.kernelConstraint
-            );
-            if (this.useBias) {
-              this.bias = this.addWeight(
-                "bias",
-                [this.units],
-                null,
-                this.biasInitializer,
-                this.biasRegularizer,
-                true,
-                this.biasConstraint
-              );
-            }
-          }
-          this.inputSpec = [{ minNDim: 2, axes: { [-1]: inputLastDim } }];
-          this.built = true;
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const outputShape = inputShape.slice();
-          outputShape[outputShape.length - 1] = this.units;
-          return outputShape;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            // Dense layer accepts only a single input.
-            const input = getExactlyOneTensor(inputs);
-            const fusedActivationName = mapActivationToFusedKernel(this.activation.getClassName());
-            let output;
-            if (fusedActivationName != null) {
-              output = dot(
-                input,
-                this.kernel.read(),
-                fusedActivationName,
-                this.bias ? this.bias.read() : null
-              );
-            } else {
-              output = dot(input, this.kernel.read());
-              if (this.bias != null) {
-                output = biasAdd(output, this.bias.read());
-              }
-              if (this.activation != null) {
-                output = this.activation.apply(output);
-              }
-            }
-            return output;
-          });
-        }
-        getConfig() {
-          const config = {
-            units: this.units,
-            activation: serializeActivation(this.activation),
-            useBias: this.useBias,
-            kernelInitializer: serializeInitializer(this.kernelInitializer),
-            biasInitializer: serializeInitializer(this.biasInitializer),
-            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
-            biasRegularizer: serializeRegularizer(this.biasRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            kernelConstraint: serializeConstraint(this.kernelConstraint),
-            biasConstraint: serializeConstraint(this.biasConstraint),
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      core_Dense.className = "Dense";
-      dist["serialization"].registerClass(core_Dense);
-      class core_Flatten extends topology_Layer {
-        constructor(args) {
-          args = args || {};
-          super(args);
-          this.inputSpec = [{ minNDim: 3 }];
-          this.dataFormat = args.dataFormat;
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          for (const dim of inputShape.slice(1)) {
-            if (dim == null) {
-              throw new ValueError(
-                `The shape of the input to "Flatten" is not fully defined ` +
-                  `(got ${inputShape.slice(1)}). Make sure to pass a complete ` +
-                  `"input_shape" or "batch_input_shape" argument to the first ` +
-                  `layer in your model.`
-              );
-            }
-          }
-          return [inputShape[0], arrayProd(inputShape, 1)];
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            let input = getExactlyOneTensor(inputs);
-            if (this.dataFormat === "channelsFirst" && input.rank > 1) {
-              const permutation = [0];
-              for (let i = 2; i < input.rank; ++i) {
-                permutation.push(i);
-              }
-              permutation.push(1);
-              input = input.transpose(permutation);
-            }
-            return batchFlatten(input);
-          });
-        }
-        getConfig() {
-          const config = {};
-          if (this.dataFormat != null) {
-            config["dataFormat"] = this.dataFormat;
-          }
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      core_Flatten.className = "Flatten";
-      dist["serialization"].registerClass(core_Flatten);
-      class core_Activation extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.supportsMasking = true;
-          this.activation = getActivation(args.activation);
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            const input = getExactlyOneTensor(inputs);
-            return this.activation.apply(input);
-          });
-        }
-        getConfig() {
-          const config = { activation: serializeActivation(this.activation) };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      core_Activation.className = "Activation";
-      dist["serialization"].registerClass(core_Activation);
-      class core_RepeatVector extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.n = args.n;
-          this.inputSpec = [{ ndim: 2 }];
-        }
-        computeOutputShape(inputShape) {
-          return [inputShape[0], this.n, inputShape[1]];
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = getExactlyOneTensor(inputs);
-            return repeat(inputs, this.n);
-          });
-        }
-        getConfig() {
-          const config = {
-            n: this.n,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      core_RepeatVector.className = "RepeatVector";
-      dist["serialization"].registerClass(core_RepeatVector);
-      class core_Reshape extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.targetShape = args.targetShape;
-          // Make sure that all unknown dimensions are represented as `null`.
-          for (let i = 0; i < this.targetShape.length; ++i) {
-            if (this.isUnknown(this.targetShape[i])) {
-              this.targetShape[i] = null;
-            }
-          }
-        }
-        isUnknown(dim) {
-          return dim < 0 || dim == null;
-        }
-        /**
-         * Finds and replaces a missing dimension in output shape.
-         *
-         * This is a near direct port of the internal Numpy function
-         * `_fix_unknown_dimension` in `numpy/core/src/multiarray/shape.c`.
-         *
-         * @param inputShape: Original shape of array begin reshape.
-         * @param outputShape: Target shape of the array, with at most a single
-         * `null` or negative number, which indicates an underdetermined dimension
-         * that should be derived from `inputShape` and the known dimensions of
-         *   `outputShape`.
-         * @returns: The output shape with `null` replaced with its computed value.
-         * @throws: ValueError: If `inputShape` and `outputShape` do not match.
-         */
-        fixUnknownDimension(inputShape, outputShape) {
-          const errorMsg = "Total size of new array must be unchanged.";
-          const finalShape = outputShape.slice();
-          let known = 1;
-          let unknown = null;
-          for (let i = 0; i < finalShape.length; ++i) {
-            const dim = finalShape[i];
-            if (this.isUnknown(dim)) {
-              if (unknown === null) {
-                unknown = i;
-              } else {
-                throw new ValueError("Can only specifiy one unknown dimension.");
-              }
-            } else {
-              known *= dim;
-            }
-          }
-          const originalSize = arrayProd(inputShape);
-          if (unknown !== null) {
-            if (known === 0 || originalSize % known !== 0) {
-              throw new ValueError(errorMsg);
-            }
-            finalShape[unknown] = originalSize / known;
-          } else if (originalSize !== known) {
-            throw new ValueError(errorMsg);
-          }
-          return finalShape;
-        }
-        computeOutputShape(inputShape) {
-          let anyUnknownDims = false;
-          for (let i = 0; i < inputShape.length; ++i) {
-            if (this.isUnknown(inputShape[i])) {
-              anyUnknownDims = true;
-              break;
-            }
-          }
-          if (anyUnknownDims) {
-            return inputShape.slice(0, 1).concat(this.targetShape);
-          } else {
-            return inputShape
-              .slice(0, 1)
-              .concat(this.fixUnknownDimension(inputShape.slice(1), this.targetShape));
-          }
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            const input = getExactlyOneTensor(inputs);
-            const inputShape = input.shape;
-            const outputShape = inputShape
-              .slice(0, 1)
-              .concat(this.fixUnknownDimension(inputShape.slice(1), this.targetShape));
-            return input.reshape(outputShape);
-          });
-        }
-        getConfig() {
-          const config = {
-            targetShape: this.targetShape,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      core_Reshape.className = "Reshape";
-      dist["serialization"].registerClass(core_Reshape);
-      class core_Permute extends topology_Layer {
-        constructor(args) {
-          super(args);
-          if (args.dims == null) {
-            throw new Error(
-              "Required configuration field `dims` is missing during Permute " + "constructor call."
-            );
-          }
-          if (!Array.isArray(args.dims)) {
-            throw new Error(
-              "Permute constructor requires `dims` to be an Array, but received " +
-                `${args.dims} instead.`
-            );
-          }
-          // Check the validity of the permutation indices.
-          const expectedSortedIndices = range(1, args.dims.length + 1);
-          if (!dist["util"].arraysEqual(args.dims.slice().sort(), expectedSortedIndices)) {
-            throw new Error(
-              "Invalid permutation `dims`: " +
-                JSON.stringify(args.dims) +
-                " `dims` must contain consecutive integers starting from 1."
-            );
-          }
-          this.dims = args.dims;
-          this.dimsIncludingBatch = [0].concat(this.dims);
-          this.inputSpec = [new InputSpec({ ndim: this.dims.length + 1 })];
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const outputShape = inputShape.slice();
-          this.dims.forEach((dim, i) => {
-            outputShape[i + 1] = inputShape[dim];
-          });
-          return outputShape;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["transpose"])(getExactlyOneTensor(inputs), this.dimsIncludingBatch);
-        }
-        getConfig() {
-          const config = {
-            dims: this.dims,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      core_Permute.className = "Permute";
-      dist["serialization"].registerClass(core_Permute);
-      class core_Masking extends topology_Layer {
-        constructor(args) {
-          super(args == null ? {} : args);
-          this.supportsMasking = true;
-          if (args != null) {
-            this.maskValue = args.maskValue == null ? 0 : args.maskValue;
-          } else {
-            this.maskValue = 0;
-          }
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const baseConfig = super.getConfig();
-          const config = { maskValue: this.maskValue };
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        computeMask(inputs, mask) {
-          const input = getExactlyOneTensor(inputs);
-          const axis = -1;
-          return Object(dist["any"])(Object(dist["notEqual"])(input, this.maskValue), axis);
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            const input = getExactlyOneTensor(inputs);
-            const axis = -1;
-            const keepDims = true;
-            const booleanMask = Object(dist["any"])(
-              Object(dist["notEqual"])(input, this.maskValue),
-              axis,
-              keepDims
-            );
-            const output = input.mul(booleanMask.asType(input.dtype));
-            return output;
-          });
-        }
-      }
-      /** @nocollapse */
-      core_Masking.className = "Masking";
-      dist["serialization"].registerClass(core_Masking);
-      //# sourceMappingURL=core.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/embeddings.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * TensorFlow.js Layers: Embedding Layer.
-       *
-       * Original source: keras/constraints.py
-       */
-
-      class embeddings_Embedding extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.embeddings = null;
-          this.DEFAULT_EMBEDDINGS_INITIALIZER = "randomUniform";
-          if (args.batchInputShape == null && args.inputShape == null) {
-            // Porting Note: This logic is copied from Layer's constructor, since we
-            // can't do exactly what the Python constructor does for Embedding().
-            // Specifically, the super constructor can not be called after the
-            // mutation of the `config` argument.
-            let batchSize = null;
-            if (args.batchSize != null) {
-              batchSize = args.batchSize;
-            }
-            if (args.inputLength == null) {
-              // Fix super-constructor to what it would have done if
-              // 'config.inputShape' were (None, )
-              this.batchInputShape = [batchSize, null];
-            } else {
-              // Fix super-constructor to what it would have done if
-              // 'config.inputShape' were (config.inputLength, )
-              this.batchInputShape = [batchSize].concat(toList(args.inputLength));
-            }
-          }
-          this.inputDim = args.inputDim;
-          assertPositiveInteger(this.inputDim, "inputDim");
-          this.outputDim = args.outputDim;
-          assertPositiveInteger(this.outputDim, "outputDim");
-          this.embeddingsInitializer = getInitializer(
-            args.embeddingsInitializer || this.DEFAULT_EMBEDDINGS_INITIALIZER
-          );
-          this.embeddingsRegularizer = getRegularizer(args.embeddingsRegularizer);
-          this.activityRegularizer = getRegularizer(args.activityRegularizer);
-          this.embeddingsConstraint = getConstraint(args.embeddingsConstraint);
-          this.maskZero = args.maskZero;
-          this.supportsMasking = args.maskZero;
-          this.inputLength = args.inputLength;
-        }
-        build(inputShape) {
-          this.embeddings = this.addWeight(
-            "embeddings",
-            [this.inputDim, this.outputDim],
-            this.dtype,
-            this.embeddingsInitializer,
-            this.embeddingsRegularizer,
-            true,
-            this.embeddingsConstraint
-          );
-          this.built = true;
-        }
-        // Override warnOnIncompatibleInputShape because an embedding layer allows
-        // the input to have varying ranks.
-        warnOnIncompatibleInputShape(inputShape) {}
-        computeMask(inputs, mask) {
-          return Object(dist["tidy"])(() => {
-            if (!this.maskZero) {
-              return null;
-            } else {
-              inputs = getExactlyOneTensor(inputs);
-              return Object(dist["notEqual"])(inputs, Object(dist["zerosLike"])(inputs));
-            }
-          });
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          if (this.inputLength == null) {
-            return [...inputShape, this.outputDim];
-          }
-          // inputLength can be an array if input is 3D or higher.
-          const inLens = toList(this.inputLength);
-          if (inLens.length !== inputShape.length - 1) {
-            throw new ValueError(
-              `"inputLength" is ${this.inputLength}, but received ` +
-                `input shape has shape ${inputShape}`
-            );
-          } else {
-            let i = 0;
-            for (let k = 0; k < inLens.length; ++k) {
-              const s1 = inLens[k];
-              const s2 = inputShape[k + 1];
-              if (s1 != null && s2 != null && s1 !== s2) {
-                throw new ValueError(
-                  `"inputLength" is ${this.inputLength}, but received ` +
-                    `input shape has shape ${inputShape}`
-                );
-              } else if (s1 == null) {
-                inLens[i] = s2;
-              }
-              i++;
-            }
-          }
-          return [inputShape[0], ...inLens, this.outputDim];
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            // Embedding layer accepts only a single input.
-            let input = getExactlyOneTensor(inputs);
-            if (input.dtype !== "int32") {
-              input = cast(input, "int32");
-            }
-            const output = gather(this.embeddings.read(), input.as1D());
-            return output.reshape(getExactlyOneShape(this.computeOutputShape(input.shape)));
-          });
-        }
-        getConfig() {
-          const config = {
-            inputDim: this.inputDim,
-            outputDim: this.outputDim,
-            embeddingsInitializer: serializeInitializer(this.embeddingsInitializer),
-            embeddingsRegularizer: serializeRegularizer(this.embeddingsRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            embeddingsConstraint: serializeConstraint(this.embeddingsConstraint),
-            maskZero: this.maskZero,
-            inputLength: this.inputLength,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      embeddings_Embedding.className = "Embedding";
-      dist["serialization"].registerClass(embeddings_Embedding);
-      //# sourceMappingURL=embeddings.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/merge.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * TensorFlow.js Layers: Merge Layers.
-       */
-
-      /**
-       * Generic Merge layer for element-wise merge functions.
-       *
-       * Used to implement `Sum`, `Average`, `Concatenate`, etc.
-       */
-      class merge_Merge extends topology_Layer {
-        constructor(args) {
-          super(args || {});
-          this.supportsMasking = true;
-        }
-        /**
-         * Logic for merging multiple tensors, to be overridden by subclasses.
-         * @param inputs
-         */
-        mergeFunction(inputs) {
-          throw new NotImplementedError();
-        }
-        /**
-         * Computes the shape of the result of an elementwise operation.
-         *
-         * @param shape1: Shape of the first tensor.
-         * @param shape2: Shape of the second tensor.
-         * @returns Expected output shape when an elementwise operation is carried
-         *   out on 2 tensors with shapes `shape1` and `shape2`.
-         * @throws ValueError: If `shape1` and `shape2` are not compatible for
-         *   element-wise operations.
-         */
-        computeElementwiseOpOutputShape(shape1, shape2) {
-          if (shape1 == null || shape2 == null) {
-            return null;
-          } else if (shape1.length < shape2.length) {
-            return this.computeElementwiseOpOutputShape(shape2, shape1);
-          } else if (shape2.length === 0) {
-            return shape1;
-          }
-          const outputShape = shape1.slice(0, shape1.length - shape2.length);
-          for (let k = 0; k < shape2.length; ++k) {
-            const i = shape1[shape1.length - shape2.length + k];
-            const j = shape2[k];
-            if (i == null || j == null || i < 0 || j < 0) {
-              outputShape.push(null);
-            } else if (i === 1) {
-              outputShape.push(j);
-            } else if (j === 1) {
-              outputShape.push(i);
-            } else {
-              if (i !== j) {
-                throw new ValueError(
-                  "Operands could not be broadcast together with shapes " +
-                    JSON.stringify(shape1) +
-                    " " +
-                    JSON.stringify(shape2)
-                );
-              }
-              outputShape.push(i);
-            }
-          }
-          return outputShape;
-        }
-        build(inputShape) {
-          // Used purely for shape validation.
-          if (Array.isArray(inputShape) && !Array.isArray(inputShape[0])) {
-            // Make sure that inputShape is an Array of shape.
-            inputShape = [getExactlyOneShape(inputShape)];
-          }
-          inputShape = inputShape;
-          if (inputShape.length < 2) {
-            throw new ValueError(
-              "A merge layer should be called on an Array of at least 2 inputs." +
-                ` Got ${inputShape.length} input(s).`
-            );
-          }
-          // Make sure that there is at most one unique batch size among the input
-          // shapes.
-          let batchSizes = [];
-          for (const shape of inputShape) {
-            if (shape != null && shape[0] !== null) {
-              batchSizes.push(shape[0]);
-            }
-          }
-          batchSizes = unique(batchSizes);
-          if (batchSizes.length > 1) {
-            throw new ValueError(
-              `Can not merge tensors with different batch sizes. ` +
-                `Got tensors with shapes: ${JSON.stringify(inputShape)}.`
-            );
-          }
-          let outputShape = inputShape[0] == null ? null : inputShape[0].slice(1);
-          for (let i = 1; i < inputShape.length; ++i) {
-            const shape = inputShape[i] == null ? null : inputShape[i].slice(1);
-            outputShape = this.computeElementwiseOpOutputShape(outputShape, shape);
-          }
-          // If the inputs have different ranks, we have to reshape them to make them
-          // broadcastable.
-          const allRanks = inputShape.map((shape) => shape.length);
-          if (inputShape.indexOf(null) === -1 && unique(allRanks).length === 1) {
-            this.reshapeRequired = false;
-          } else {
-            this.reshapeRequired = true;
-          }
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = inputs;
-            if (this.reshapeRequired) {
-              const reshapedInputs = [];
-              const inputDims = inputs.map((input) => input.rank);
-              if (inputDims.indexOf(null) === -1) {
-                // If ranks of all inputs are available, we simply expand each of them
-                // at axis=1 until all of them have the same rank.
-                const maxNDim = max(inputDims);
-                for (let x of inputs) {
-                  const xNDim = x.rank;
-                  for (let k = 0; k < maxNDim - xNDim; ++k) {
-                    x = expandDims(x, 1);
-                  }
-                  reshapedInputs.push(x);
-                }
-                return this.mergeFunction(reshapedInputs);
-              } else {
-                // Transpose all inputs so that batch size is the last dimension.
-                // [batchSize, dim1, dim2, ...] -> [dim1, dim2, ..., batchSize]
-                let transposed = false;
-                for (const x of inputs) {
-                  const xNDim = x.rank;
-                  if (xNDim == null) {
-                    const xShape = x.shape;
-                    const batchSize = xShape[0];
-                    const newShape = xShape.slice(1).concat([batchSize]);
-                    let xTransposed = x.reshape([batchSize].concat(arrayProd(xShape.slice(1))));
-                    xTransposed = dist["transpose"](xTransposed, [1, 0]);
-                    xTransposed = xTransposed.reshape(newShape);
-                    reshapedInputs.push(xTransposed);
-                    transposed = true;
-                  } else if (xNDim > 1) {
-                    const dims = range(1, xNDim).concat([0]);
-                    reshapedInputs.push(dist["transpose"](x, dims));
-                    transposed = true;
-                  } else {
-                    // We don't transpose inputs if they are 1D vectors or scalars.
-                    reshapedInputs.push(x);
-                  }
-                }
-                let y = this.mergeFunction(reshapedInputs);
-                const yNDim = y.rank;
-                if (transposed) {
-                  // If inputs have been transposed, we have to transpose the output
-                  // too.
-                  if (yNDim == null) {
-                    const yShape = y.shape;
-                    const yNDim = yShape.length;
-                    const batchSize = yShape[yNDim - 1];
-                    const newShape = [batchSize].concat(yShape.slice(0, yShape.length - 1));
-                    y = dist["transpose"](y.reshape([-1, batchSize]), [1, 0]).reshape(newShape);
-                  } else if (yNDim > 1) {
-                    const dims = [yNDim - 1].concat(range(0, yNDim - 1));
-                    y = dist["transpose"](y, dims);
-                  }
-                }
-                return y;
-              }
-            } else {
-              return this.mergeFunction(inputs);
-            }
-          });
-        }
-        computeOutputShape(inputShape) {
-          inputShape = inputShape;
-          let outputShape;
-          if (inputShape[0] == null) {
-            outputShape = null;
-          } else {
-            outputShape = inputShape[0].slice(1);
-          }
-          for (let i = 1; i < inputShape.length; ++i) {
-            const shape = inputShape[i] == null ? null : inputShape[i].slice(1);
-            outputShape = this.computeElementwiseOpOutputShape(outputShape, shape);
-          }
-          let batchSizes = [];
-          for (const shape of inputShape) {
-            if (shape != null && shape[0] !== null) {
-              batchSizes.push(shape[0]);
-            }
-          }
-          batchSizes = unique(batchSizes);
-          if (batchSizes.length === 1) {
-            outputShape = batchSizes.concat(outputShape);
-          } else {
-            outputShape = [null].concat(outputShape);
-          }
-          return outputShape;
-        }
-        computeMask(inputs, mask) {
-          return dist["tidy"](() => {
-            if (mask == null) {
-              return null;
-            }
-            if (!Array.isArray(mask)) {
-              throw new ValueError("`mask` should be an Array");
-            }
-            if (!Array.isArray(inputs)) {
-              throw new ValueError("`inputs` should be an Array");
-            }
-            if (mask.length !== inputs.length) {
-              throw new ValueError(
-                `The Array 'inputs' and 'mask' are expected to have the same ` +
-                  `length, but have different lengths ` +
-                  `(${inputs.length} vs ${mask.length})`
-              );
-            }
-            if (mask.every((m) => m == null)) {
-              return null;
-            }
-            mask = mask.map((m) => (m == null ? m : dist["expandDims"](m, 0)));
-            let output = mask[0];
-            for (let i = 1; i < mask.length - 1; ++i) {
-              output = dist["logicalAnd"](output, mask[i]);
-            }
-            return output;
-          });
-        }
-      }
-      class merge_Add extends merge_Merge {
-        constructor(args) {
-          super(args);
-        }
-        mergeFunction(inputs) {
-          return Object(dist["tidy"])(() => {
-            let output = inputs[0].clone();
-            for (let i = 1; i < inputs.length; ++i) {
-              output = dist["add"](output, inputs[i]);
-            }
-            return output;
-          });
-        }
-      }
-      /** @nocollapse */
-      merge_Add.className = "Add";
-      dist["serialization"].registerClass(merge_Add);
-      /**
-       * Calculate the element-wise sum of inputs, which all have the same shape.
-       *
-       * This function can be invoked in three ways.
-       *
-       * 1. Construct an instance of `Add` layer, by using no input argument
-       *    or a single configuration argument. The resultant `Add` layer can then
-       *    be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
-       *
-       * ```js
-       * const addLayer = tf.layers.add();
-       *
-       * // The layer can be applied to inputs.
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = addLayer.apply([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.SymbolicTensor`. For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = tf.layers.add([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.Tensor` as the result of the computation. For
-       * example:
-       *
-       * ```js
-       * const input1 = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       * const input2 = tf.tensor2d([10, 20, 30, 40], [2, 2]);
-       * tf.layers.add([input1, input2]).print();
-       * // Gives [[11, 22], [33, 44]].
-       *
-       */
-      function add(config) {
-        if (Array.isArray(config)) {
-          const layer = new merge_Add({});
-          return layer.apply(config);
-        } else {
-          return new merge_Add(config);
-        }
-      }
-      class merge_Multiply extends merge_Merge {
-        constructor(args) {
-          super(args);
-        }
-        mergeFunction(inputs) {
-          return Object(dist["tidy"])(() => {
-            let output = inputs[0].clone();
-            for (let i = 1; i < inputs.length; ++i) {
-              output = dist["mul"](output, inputs[i]);
-            }
-            return output;
-          });
-        }
-      }
-      /** @nocollapse */
-      merge_Multiply.className = "Multiply";
-      dist["serialization"].registerClass(merge_Multiply);
-      /**
-       * Calculate the element-wise product of inputs, which all have the same shape.
-       *
-       * This function can be invoked in three ways.
-       *
-       * 1. Construct an instance of `Multiply` layer, by using no input argument
-       *    or a single configuration argument. The resultant `Multiply` layer can
-       *    then be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
-       *
-       * ```js
-       * const multiplyLayer = tf.layers.multiply();
-       *
-       * // The layer can be applied to inputs.
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = multiplyLayer.apply([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.SymbolicTensor`. For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = tf.layers.multiply([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.Tensor` as the result of the computation. For
-       * example:
-       *
-       * ```js
-       * const input1 = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       * const input2 = tf.tensor2d([10, 20, 30, 40], [2, 2]);
-       * tf.layers.multiply([input1, input2]).print();
-       * // Gives [[10, 40], [90, 160]].
-       *
-       */
-      function multiply(config) {
-        if (Array.isArray(config)) {
-          const layer = new merge_Multiply({});
-          return layer.apply(config);
-        } else {
-          return new merge_Multiply(config);
-        }
-      }
-      class merge_Average extends merge_Merge {
-        constructor(args) {
-          super(args);
-        }
-        mergeFunction(inputs) {
-          return Object(dist["tidy"])(() => {
-            let output = inputs[0].clone();
-            for (let i = 1; i < inputs.length; ++i) {
-              output = dist["add"](output, inputs[i]);
-            }
-            return dist["mul"](1 / inputs.length, output);
-          });
-        }
-      }
-      /** @nocollapse */
-      merge_Average.className = "Average";
-      dist["serialization"].registerClass(merge_Average);
-      /**
-       * Calculate the element-wise arithmetic mean of inputs, which all have the same
-       * shape.
-       *
-       * This function can be invoked in three ways.
-       *
-       * 1. Construct an instance of `Average` layer, by using no input argument
-       *    or a single configuration argument. The resultant `Average` layer can then
-       *    be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
-       *
-       * ```js
-       * const averageLayer = tf.layers.average();
-       *
-       * // The layer can be applied to inputs.
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = averageLayer.apply([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.SymbolicTensor`. For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = tf.layers.average([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.Tensor` as the result of the computation. For
-       * example:
-       *
-       * ```js
-       * const input1 = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       * const input2 = tf.tensor2d([10, 20, 30, 40], [2, 2]);
-       * tf.layers.average([input1, input2]).print();
-       * // Gives [[5.5, 11], [16.5, 22]].
-       *
-       */
-      function average(config) {
-        if (Array.isArray(config)) {
-          const layer = new merge_Average({});
-          return layer.apply(config);
-        } else {
-          return new merge_Average(config);
-        }
-      }
-      class merge_Maximum extends merge_Merge {
-        constructor(args) {
-          super(args);
-        }
-        mergeFunction(inputs) {
-          return Object(dist["tidy"])(() => {
-            let output = inputs[0];
-            for (let i = 1; i < inputs.length; ++i) {
-              output = dist["maximum"](output, inputs[i]);
-            }
-            return output;
-          });
-        }
-      }
-      /** @nocollapse */
-      merge_Maximum.className = "Maximum";
-      dist["serialization"].registerClass(merge_Maximum);
-      /**
-       * Calculate the element-wise maximum of inputs, which all have the same shape.
-       *
-       * This function can be invoked in three ways.
-       *
-       * 1. Construct an instance of `Maximum` layer, by using no input argument
-       *    or a single configuration argument. The resultant `Maximum` layer can then
-       *    be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
-       *
-       * ```js
-       * const maximumLayer = tf.layers.maximum();
-       *
-       * // The layer can be applied to inputs.
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = maximumLayer.apply([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.SymbolicTensor`. For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = tf.layers.maximum([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.Tensor` as the result of the computation. For
-       * example:
-       *
-       * ```js
-       * const input1 = tf.tensor2d([1, 20, 3, 40], [2, 2]);
-       * const input2 = tf.tensor2d([10, 2, 30, 4], [2, 2]);
-       * tf.layers.maximum([input1, input2]).print();
-       * // Gives [[10, 20], [30, 40]].
-       *
-       */
-      function maximum(config) {
-        if (Array.isArray(config)) {
-          const layer = new merge_Maximum({});
-          return layer.apply(config);
-        } else {
-          return new merge_Maximum(config);
-        }
-      }
-      class merge_Minimum extends merge_Merge {
-        constructor(args) {
-          super(args);
-        }
-        mergeFunction(inputs) {
-          return Object(dist["tidy"])(() => {
-            let output = inputs[0];
-            for (let i = 1; i < inputs.length; ++i) {
-              output = dist["minimum"](output, inputs[i]);
-            }
-            return output;
-          });
-        }
-      }
-      /** @nocollapse */
-      merge_Minimum.className = "Minimum";
-      dist["serialization"].registerClass(merge_Minimum);
-      /**
-       * Calculate the element-wise minimum of inputs, which all have the same shape.
-       *
-       * This function can be invoked in three ways.
-       *
-       * 1. Construct an instance of `Minimum` layer, by using no input argument
-       *    or a single configuration argument. The resultant `Minimum` layer can then
-       *    be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
-       *
-       * ```js
-       * const minimumLayer = tf.layers.minimum();
-       *
-       * // The layer can be applied to inputs.
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = minimumLayer.apply([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.SymbolicTensor`. For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const output = tf.layers.minimum([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       *
-       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.Tensor` as the result of the computation. For
-       * example:
-       *
-       * ```js
-       * const input1 = tf.tensor2d([1, 20, 3, 40], [2, 2]);
-       * const input2 = tf.tensor2d([10, 2, 30, 4], [2, 2]);
-       * tf.layers.minimum([input1, input2]).print();
-       * // Gives [[1, 2], [3, 4]].
-       *
-       */
-      function minimum(config) {
-        if (Array.isArray(config)) {
-          const layer = new merge_Minimum({});
-          return layer.apply(config);
-        } else {
-          return new merge_Minimum(config);
-        }
-      }
-      class merge_Concatenate extends merge_Merge {
-        constructor(args) {
-          super(args);
-          this.DEFAULT_AXIS = -1;
-          if (args == null) {
-            args = {};
-          }
-          this.axis = args.axis == null ? this.DEFAULT_AXIS : args.axis;
-          this.supportsMasking = true;
-          this.reshapeRequired = false;
-        }
-        build(inputShape) {
-          // Used purely for shape validation.]
-          if (
-            !(Array.isArray(inputShape) && Array.isArray(inputShape[0])) ||
-            inputShape.length === 1
-          ) {
-            throw new ValueError(
-              "A `Concatenate` layer should be called on a list of at least 2 " + "inputs"
-            );
-          }
-          inputShape = inputShape;
-          let allNoneShape = true;
-          for (const shape of inputShape) {
-            if (shape != null) {
-              allNoneShape = false;
-              break;
-            }
-          }
-          if (allNoneShape) {
-            return;
-          }
-          const shapeSet = [];
-          for (let i = 0; i < inputShape.length; ++i) {
-            const shapeWithoutConcatAxis = inputShape[i].slice();
-            shapeWithoutConcatAxis.splice(this.axis, 1);
-            let exists = false;
-            for (const shape of shapeSet) {
-              if (dist["util"].arraysEqual(shape, shapeWithoutConcatAxis)) {
-                exists = true;
-                break;
-              }
-            }
-            if (!exists) {
-              shapeSet.push(shapeWithoutConcatAxis);
-            }
-          }
-          if (shapeSet.length > 1) {
-            throw new ValueError(
-              "A `Concatenate` layer requires inputs with matching shapes " +
-                "except for the concat axis. Got input shapes: " +
-                JSON.stringify(inputShape)
-            );
-          }
-        }
-        mergeFunction(inputs) {
-          return Object(dist["tidy"])(() => {
-            return concatenate(inputs, this.axis);
-          });
-        }
-        computeOutputShape(inputShape) {
-          if (!(Array.isArray(inputShape) && Array.isArray(inputShape[0]))) {
-            throw new ValueError("A `Concatenate` layer should be called on a list of inputs.");
-          }
-          const inputShapes = inputShape;
-          const outputShape = inputShapes[0].slice();
-          const axis = this.axis < 0 ? outputShape.length + this.axis : this.axis;
-          // Porting Note: the line above is because TypeScript doesn't support
-          //   negative indices.
-          for (const shape of inputShapes.slice(1)) {
-            if (outputShape[axis] == null || shape[axis] == null) {
-              outputShape[axis] = null;
-              break;
-            }
-            outputShape[axis] += shape[axis];
-          }
-          return outputShape;
-        }
-        computeMask(inputs, mask) {
-          if (mask == null) {
-            return null;
-          }
-          if (!Array.isArray(mask)) {
-            throw new ValueError("`mask` should be an array for Concatenate");
-          }
-          if (!Array.isArray(inputs)) {
-            throw new ValueError("`inputs` should be an array for Concatenate");
-          }
-          if (mask.length !== inputs.length) {
-            throw new ValueError(
-              `Mismatch in the length of mask (${mask.length}) ` +
-                `and the legnth of inputs (${inputs.length})`
-            );
-          }
-          return dist["tidy"](() => {
-            let allNullMasks = true;
-            mask.forEach((m) => {
-              if (m != null) {
-                allNullMasks = false;
-                return;
-              }
-            });
-            if (allNullMasks) {
-              return null;
-            }
-            const outputMasks = [];
-            for (let i = 0; i < inputs.length; ++i) {
-              if (mask[i] == null) {
-                // Input is unmasked. Append all 1's to masks.
-                outputMasks.push(dist["onesLike"](inputs[i]).asType("bool"));
-              } else if (mask[i].rank < inputs[i].rank) {
-                // Mask is smaller than the input, expand it.
-                outputMasks.push(dist["expandDims"](mask[i], -1));
-              } else {
-                outputMasks.push(mask[i]);
-              }
-            }
-            const concatenatedMasks = dist["concat"](outputMasks, this.axis);
-            return dist["all"](concatenatedMasks, -1, false);
-          });
-        }
-        getConfig() {
-          const config = {
-            axis: this.axis,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      merge_Concatenate.className = "Concatenate";
-      dist["serialization"].registerClass(merge_Concatenate);
-      /**
-       * Concatenate an `Array` of inputs.
-       *
-       * This function can be invoked in three ways.
-       *
-       * 1. Construct an instance of `Concatenate` layer, by using no input argument
-       *    or a single configuration argument. The resultant `Concatenate` layer can
-       *    then be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
-       *
-       * ```js
-       * const concatLayer = tf.layers.concatenate();
-       *
-       * // The layer can be applied to inputs.
-       * const input1 = tf.input({shape: [2, 3]});
-       * const input2 = tf.input({shape: [2, 4]});
-       * const output = concatLayer.apply([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 7], with the first dimension as the undetermined batch
-       * // dimension and the last dimension as the result of concatenating the
-       * // last dimensions of the two inputs.
-       * ```
-       *
-       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.SymbolicTensor`. For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 3]});
-       * const input2 = tf.input({shape: [2, 4]});
-       * const output = tf.layers.concatenate([input1, input2]);
-       * console.log(output.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension and the last dimension as the result of concatenating the
-       * // last dimensions of the two inputs.
-       * ```
-       *
-       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
-       *    an `Layer` object internally and calls its `apply` method on the inputs,
-       *    generating a new `tf.Tensor` as the result of the computation. For
-       * example:
-       *
-       * ```js
-       * const input1 = tf.tensor2d([[1, 2], [3, 4]], [2, 2]);
-       * const input2 = tf.tensor2d([[10, 20], [30, 40]], [2, 2]);
-       * tf.layers.concatenate([input1, input2]).print();
-       * // Gives [[1, 2, 10, 20], [3, 4, 30, 40]].
-       *
-       */
-      function merge_concatenate(config) {
-        if (Array.isArray(config)) {
-          const layer = new merge_Concatenate({});
-          return layer.apply(config);
-        } else {
-          return new merge_Concatenate(config);
-        }
-      }
-      /**
-       * Interpretable potentially negative axis index.
-       *
-       * For example, given axis = -1, and dim = 3, this function will return 2.
-       *
-       * @param axis The axis index, may be a positive, zero or negative integer.
-       * @param dim Total number of dimensions, a positive integer.
-       * @returns A non-negative axis index equivalent to the input `axis`.
-       */
-      function interpretAxis(axis, dim) {
-        while (axis < 0) {
-          axis += dim;
-        }
-        return axis;
-      }
-      function batchDot(x, y, axes) {
-        if (x.shape.length > 3 || y.shape.length > 3) {
-          throw new NotImplementedError(
-            "batchDot is not implemented for tensors of 4D or higher rank yet"
-          );
-        }
-        dist["util"].assert(
-          x.shape.length >= 2,
-          () => `batchDot requires the rank of x to be >= 2, ` + `but got ${x.shape.length}`
-        );
-        dist["util"].assert(
-          x.shape.length >= 2,
-          () => `batchDot requires the rank of y to be >= 2, ` + `but got ${y.shape.length}`
-        );
-        if (typeof axes === "number") {
-          axes = [axes, axes];
-        }
-        if (x.dtype === "complex64" || y.dtype === "complex64") {
-          throw new NotImplementedError(
-            "batchDot is not implemented for complex64-type Tensors yet."
-          );
-        }
-        const xNDim = x.shape.length;
-        const yNDim = y.shape.length;
-        if (axes == null) {
-          // Behave like batchMatmul by default.
-          axes = [xNDim - 1, yNDim - 2];
-        }
-        const axesArray = axes;
-        return dist["tidy"](() => {
-          let diff;
-          if (xNDim > yNDim) {
-            diff = xNDim - yNDim;
-            const diffShape = [];
-            for (let i = 0; i < diff; ++i) {
-              diffShape.push(1);
-            }
-            y = y.reshape(y.shape.concat(diffShape));
-          } else if (yNDim > xNDim) {
-            diff = yNDim - xNDim;
-            const diffShape = [];
-            for (let i = 0; i < diff; ++i) {
-              diffShape.push(1);
-            }
-            x = x.reshape(x.shape.concat(diffShape));
-          } else {
-            diff = 0;
-          }
-          let out;
-          if (x.shape.length === 2 && y.shape.length === 2) {
-            if (axesArray[0] === axesArray[1]) {
-              out = x.mul(y).sum(axesArray[0]);
-            } else {
-              out = x.transpose([1, 0]).mul(y).sum(axesArray[1]);
-            }
-          } else {
-            const adjX = axesArray[0] !== x.shape.length - 1;
-            const adjY = axesArray[1] === y.shape.length - 1;
-            out = x.matMul(y, adjX, adjY);
-          }
-          if (diff > 0) {
-            let idx;
-            if (xNDim > yNDim) {
-              idx = xNDim + yNDim - 3;
-            } else {
-              idx = xNDim - 1;
-            }
-            const squeezeAxes = [];
-            for (let i = idx; i < idx + diff; ++i) {
-              squeezeAxes.push(i);
-            }
-            out = out.squeeze(squeezeAxes);
-          }
-          if (out.shape.length === 1) {
-            out = out.expandDims(1);
-          }
-          return out;
-        });
-      }
-      class merge_Dot extends merge_Merge {
-        constructor(args) {
-          super(args);
-          this.axes = args.axes;
-          this.normalize = args.normalize == null ? false : args.normalize;
-          this.supportsMasking = true;
-          this.reshapeRequired = false;
-        }
-        build(inputShape) {
-          dist["util"].assert(
-            Array.isArray(inputShape) &&
-              inputShape.length === 2 &&
-              Array.isArray(inputShape[0]) &&
-              Array.isArray(inputShape[1]),
-            () => "A `Dot` layer should be called on a list of exactly 2 inputs."
-          );
-          const shape1 = inputShape[0];
-          const shape2 = inputShape[1];
-          if (shape1.length > 3 || shape2.length > 3) {
-            throw new NotImplementedError(
-              "Dot layer does not support tensors of 4D or higher rank yet."
-            );
-          }
-          const axes = this.interpretAxes(shape1, shape2);
-          if (shape1[axes[0]] !== shape2[axes[1]]) {
-            throw new ValueError(
-              `Dimension incompatibility: ` + `${shape1[axes[0]]} !== ${shape2[axes[1]]}`
-            );
-          }
-        }
-        mergeFunction(inputs) {
-          if (inputs.length !== 2) {
-            throw new ValueError(
-              "A `Dot` layer must be called on exactly 2 inputs, " +
-                `but received ${inputs.length} input(s).`
-            );
-          }
-          let x1 = inputs[0];
-          let x2 = inputs[1];
-          let axes;
-          if (!Array.isArray(this.axes)) {
-            axes = [
-              interpretAxis(this.axes, x1.shape.length),
-              interpretAxis(this.axes, x2.shape.length),
-            ];
-          } else {
-            axes = this.axes.map((axis, i) => interpretAxis(axis, inputs[i].shape.length));
-          }
-          if (this.normalize) {
-            x1 = l2Normalize(x1, axes[0]);
-            x2 = l2Normalize(x2, axes[1]);
-          }
-          return batchDot(x1, x2, axes);
-        }
-        interpretAxes(shape1, shape2) {
-          let axes;
-          if (!Array.isArray(this.axes)) {
-            // `this.axes` is a single integer.
-            axes = [
-              interpretAxis(this.axes, shape1.length),
-              interpretAxis(this.axes, shape2.length),
-            ];
-          } else {
-            // `this.axes` is an Array of integers.
-            axes = this.axes;
-          }
-          return axes;
-        }
-        computeOutputShape(inputShape) {
-          dist["util"].assert(
-            Array.isArray(inputShape) &&
-              inputShape.length === 2 &&
-              Array.isArray(inputShape[0]) &&
-              Array.isArray(inputShape[1]),
-            () => "A `Dot` layer should be called on a list of exactly 2 inputs."
-          );
-          const shape1 = inputShape[0].slice();
-          const shape2 = inputShape[1].slice();
-          if (shape1.length > 3 || shape2.length > 3) {
-            throw new NotImplementedError(
-              "Dot layer does not support tensors of 4D or higher rank yet."
-            );
-          }
-          const axes = this.interpretAxes(shape1, shape2);
-          shape1.splice(axes[0], 1);
-          shape2.splice(axes[1], 1);
-          shape2.splice(0, 1);
-          const outputShape = shape1.concat(shape2);
-          if (outputShape.length === 1) {
-            outputShape.push(1);
-          }
-          return outputShape;
-        }
-        computeMask(inputs, mask) {
-          return null;
-        }
-        getConfig() {
-          const config = {
-            axes: this.axes,
-            normalize: this.normalize,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      merge_Dot.className = "Dot";
-      dist["serialization"].registerClass(merge_Dot);
-      // TODO(cais): Add functional interfaces for the merge layers.
-      //# sourceMappingURL=merge.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/noise.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * TensorFlow.js Layers: Noise Layers.
-       */
-
-      class noise_GaussianNoise extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.supportsMasking = true;
-          this.stddev = args.stddev;
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const baseConfig = super.getConfig();
-          const config = { stddev: this.stddev };
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            const input = getExactlyOneTensor(inputs);
-            const noised = () => randomNormal(input.shape, 0, this.stddev).add(input);
-            const output = inTrainPhase(noised, () => input, kwargs["training"] || false);
-            return output;
-          });
-        }
-      }
-      /** @nocollapse */
-      noise_GaussianNoise.className = "GaussianNoise";
-      dist["serialization"].registerClass(noise_GaussianNoise);
-      class noise_GaussianDropout extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.supportsMasking = true;
-          this.rate = args.rate;
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const baseConfig = super.getConfig();
-          const config = { rate: this.rate };
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            const input = getExactlyOneTensor(inputs);
-            if (this.rate > 0 && this.rate < 1) {
-              const noised = () => {
-                const stddev = Math.sqrt(this.rate / (1 - this.rate));
-                return input.mul(randomNormal(input.shape, 1, stddev));
-              };
-              return inTrainPhase(noised, () => input, kwargs["training"] || false);
-            }
-            return input;
-          });
-        }
-      }
-      /** @nocollapse */
-      noise_GaussianDropout.className = "GaussianDropout";
-      dist["serialization"].registerClass(noise_GaussianDropout);
-      /**
-       * Applies Alpha Dropout to the input.
-       *
-       * As it is a regularization layer, it is only active at training time.
-       *
-       * Alpha Dropout is a `Dropout` that keeps mean and variance of inputs
-       * to their original values, in order to ensure the self-normalizing property
-       * even after this dropout.
-       * Alpha Dropout fits well to Scaled Exponential Linear Units
-       * by randomly setting activations to the negative saturation value.
-       *
-       * Arguments:
-       *   - `rate`: float, drop probability (as with `Dropout`).
-       *     The multiplicative noise will have
-       *     standard deviation `sqrt(rate / (1 - rate))`.
-       *   - `noise_shape`: A 1-D `Tensor` of type `int32`, representing the
-       *     shape for randomly generated keep/drop flags.
-       *
-       * Input shape:
-       *   Arbitrary. Use the keyword argument `inputShape`
-       *   (tuple of integers, does not include the samples axis)
-       *   when using this layer as the first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as input.
-       *
-       * References:
-       *   - [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)
-       */
-      class noise_AlphaDropout extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.supportsMasking = true;
-          this.rate = args.rate;
-          this.noiseShape = args.noiseShape;
-        }
-        _getNoiseShape(inputs) {
-          return this.noiseShape || getExactlyOneTensor(inputs).shape;
-        }
-        computeOutputShape(inputShape) {
-          return inputShape;
-        }
-        getConfig() {
-          const baseConfig = super.getConfig();
-          const config = { rate: this.rate };
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            if (this.rate < 1 && this.rate > 0) {
-              const noiseShape = this._getNoiseShape(inputs);
-              const droppedInputs = () => {
-                const input = getExactlyOneTensor(inputs);
-                const alpha = 1.6732632423543772848170429916717;
-                const scale = 1.0507009873554804934193349852946;
-                const alphaP = -alpha * scale;
-                let keptIdx = Object(dist["greaterEqual"])(
-                  Object(dist["randomUniform"])(noiseShape),
-                  this.rate
-                );
-                keptIdx = cast(keptIdx, "float32"); // get default dtype.
-                // Get affine transformation params.
-                const a = ((1 - this.rate) * (1 + this.rate * alphaP ** 2)) ** -0.5;
-                const b = -a * alphaP * this.rate;
-                // Apply mask.
-                const x = input.mul(keptIdx).add(keptIdx.add(-1).mul(alphaP));
-                return x.mul(a).add(b);
-              };
-              return inTrainPhase(
-                droppedInputs,
-                () => getExactlyOneTensor(inputs),
-                kwargs["training"] || false
-              );
-            }
-            return inputs;
-          });
-        }
-      }
-      /** @nocollapse */
-      noise_AlphaDropout.className = "AlphaDropout";
-      dist["serialization"].registerClass(noise_AlphaDropout);
-      //# sourceMappingURL=noise.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/normalization.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Normalization layers.
-       */
-
-      /**
-       * Applies batch normalization on x given mean, var, beta and gamma.
-       *
-       * I.e. returns:
-       *   `output = (x - mean) / (sqrt(var) + epsilon) * gamma + beta`
-       *
-       * @param x Input tensor.
-       * @param mean Mean of batch.
-       * @param variance Variance of batch.
-       * @param beta Tensor with which to center the input.
-       * @param gamma Tensor by which to scale the input.
-       * @param epsilon Fuzz factor.
-       * @returns The result of the batch normalization.
-       */
-      function batchNormalization(x, mean, variance, beta, gamma, epsilon = 1e-3) {
-        let out;
-        if (x.rank === 2) {
-          out = dist["batchNorm2d"](x, mean, variance, beta, gamma, epsilon);
-        } else if (x.rank === 3) {
-          // TODO(cais): Check rank; give proper error message.
-          out = dist["batchNorm3d"](x, mean, variance, beta, gamma, epsilon);
-        } else if (x.rank === 4) {
-          out = dist["batchNorm4d"](x, mean, variance, beta, gamma, epsilon);
-        } else {
-          throw new NotImplementedError(
-            `batchNormalization is not implemented for array of rank ${x.rank} ` + `yet`
-          );
-        }
-        return out;
-      }
-      /**
-       * Non-broadcasting batch normalization for use in training (not inference).
-       *
-       * The input is normalized to zero mean and unit variance along the
-       * `reductionAxes`, followed by scaling with `gamma` and shifted by `beta`.
-       * The result of that is returned as the first element
-       * of the returned `Array`. The other two elements are the mean and variance,
-       * respectively.
-       *
-       * @param x Input tensor to be normalized.
-       * @param gamma Tensor by which to scale the input.
-       * @param beta Tensor by which to center the input.
-       * @param reductionAxes Axes over which to normalize.
-       * @param epsilon Fuzz factor.
-       * @returns An `Array` of three `Tensors`:
-       *   [normalized tensor, mean of input, variance of input].
-       */
-      function regularNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon = 1e-3) {
-        return Object(dist["tidy"])(() => {
-          const meanAndVariance = dist["moments"](x, reductionAxes);
-          const mean = meanAndVariance.mean;
-          const variance = meanAndVariance.variance;
-          const normed = batchNormalization(x, mean, variance, beta, gamma, epsilon);
-          return [normed, mean, variance];
-        });
-      }
-      /**
-       * Broadcasting batch normalization for use in training (not inference).
-       *
-       * The input is normalized to zero mean and unit variance along the
-       * `reductionAxes`, followed by scaling with `gamma` and shifted by `beta`.
-       * The result of that is returned as the first element
-       * of the returned `Array`. The other two elements are the mean and variance,
-       * respectively.
-       *
-       * @param x Input tensor to be normalized.
-       * @param gamma Tensor by which to scale the input.
-       * @param beta Tensor by which to center the input.
-       * @param reductionAxes Axes over which to normalize.
-       * @param epsilon Fuzz factor.
-       * @returns An `Array` of three `Tensors`:
-       *   [normalized tensor, mean of input, variance of input].
-       */
-      function broadcastNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon = 1e-3) {
-        return Object(dist["tidy"])(() => {
-          const meanAndVariance = dist["moments"](x, reductionAxes);
-          const mean = meanAndVariance.mean;
-          const variance = meanAndVariance.variance;
-          const targetShape = [];
-          for (const axis of range(0, x.rank)) {
-            if (reductionAxes.indexOf(axis) !== -1) {
-              targetShape.push(1);
-            } else {
-              targetShape.push(x.shape[axis]);
-            }
-          }
-          const broadcastMean = mean.reshape(targetShape);
-          const broadcastVariance = variance.reshape(targetShape);
-          const broadcastGamma = gamma == null ? null : gamma.reshape(targetShape);
-          const broadcastBeta = beta == null ? null : beta.reshape(targetShape);
-          const normed = batchNormalization(
-            x,
-            broadcastMean,
-            broadcastVariance,
-            broadcastBeta,
-            broadcastGamma,
-            epsilon
-          );
-          return [normed, mean, variance];
-        });
-      }
-      /**
-       * Batch normalization for use in training (not inference).
-       *
-       * @param x Input tensor to be normalized.
-       * @param gamma Tensor by which to scale the input.
-       * @param beta Tensor by which to center the input.
-       * @param reductionAxes Axes over which to normalize.
-       * @param epsilon Fuzz factor.
-       * @returns An `Array` of three `Tensors`:
-       *   [normalized tensor, mean of input, variance of input].
-       */
-      function normalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon = 1e-3) {
-        if (dist["util"].arraysEqual(reductionAxes.slice().sort(), range(0, x.rank - 1))) {
-          return regularNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon);
-        } else {
-          return broadcastNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon);
-        }
-      }
-      class normalization_BatchNormalization extends topology_Layer {
-        constructor(args) {
-          if (args == null) {
-            args = {};
-          }
-          super(args);
-          this.supportsMasking = true;
-          this.axis = args.axis == null ? -1 : args.axis;
-          this.momentum = args.momentum == null ? 0.99 : args.momentum;
-          this.epsilon = args.epsilon == null ? 1e-3 : args.epsilon;
-          this.center = args.center == null ? true : args.center;
-          this.scale = args.scale == null ? true : args.scale;
-          this.betaInitializer = getInitializer(args.betaInitializer || "zeros");
-          this.gammaInitializer = getInitializer(args.gammaInitializer || "ones");
-          this.movingMeanInitializer = getInitializer(args.movingMeanInitializer || "zeros");
-          this.movingVarianceInitializer = getInitializer(args.movingVarianceInitializer || "ones");
-          this.betaConstraint = getConstraint(args.betaConstraint);
-          this.gammaConstraint = getConstraint(args.gammaConstraint);
-          this.betaRegularizer = getRegularizer(args.betaRegularizer);
-          this.gammaRegularizer = getRegularizer(args.gammaRegularizer);
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const axis = this.axis >= 0 ? this.axis : this.axis + inputShape.length;
-          const dim = inputShape[axis];
-          if (dim == null) {
-            throw new ValueError(
-              `Axis ${axis} of input tensor should have a defined dimension but ` +
-                `the layer received an input with shape ` +
-                `${JSON.stringify(inputShape)}.`
-            );
-          }
-          this.inputSpec = [new InputSpec({ ndim: inputShape.length, axes: { [axis]: dim } })];
-          const shape = [dim];
-          if (this.scale) {
-            this.gamma = this.addWeight(
-              "gamma",
-              shape,
-              null,
-              this.gammaInitializer,
-              this.gammaRegularizer,
-              true,
-              this.gammaConstraint
-            );
-          }
-          if (this.center) {
-            this.beta = this.addWeight(
-              "beta",
-              shape,
-              null,
-              this.betaInitializer,
-              this.betaRegularizer,
-              true,
-              this.betaConstraint
-            );
-          }
-          this.movingMean = this.addWeight(
-            "moving_mean",
-            shape,
-            null,
-            this.movingMeanInitializer,
-            null,
-            false
-          );
-          this.movingVariance = this.addWeight(
-            "moving_variance",
-            shape,
-            null,
-            this.movingVarianceInitializer,
-            null,
-            false
-          );
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            const training = kwargs["training"] == null ? false : kwargs["training"];
-            const input = getExactlyOneTensor(inputs);
-            const inputShape = input.shape;
-            const ndim = inputShape.length;
-            const reductionAxes = range(0, ndim);
-            const axis = this.axis >= 0 ? this.axis : this.axis + ndim;
-            reductionAxes.splice(axis, 1);
-            const broadcastShape = pyListRepeat(1, ndim);
-            broadcastShape[axis] = inputShape[axis];
-            const sortedReductionAxes = reductionAxes.slice();
-            sortedReductionAxes.sort();
-            const needsBroadcasting = !dist["util"].arraysEqual(
-              sortedReductionAxes,
-              range(0, ndim).slice(0, ndim - 1)
-            );
-            const normalizeInference = () => {
-              if (needsBroadcasting) {
-                const broadcastMovingMean = this.movingMean.read().reshape(broadcastShape);
-                const broadcastMovingVariance = this.movingVariance.read().reshape(broadcastShape);
-                const broadcastBeta = this.center ? this.beta.read().reshape(broadcastShape) : null;
-                const broadcastGamma = this.scale
-                  ? this.gamma.read().reshape(broadcastShape)
-                  : null;
-                return batchNormalization(
-                  input,
-                  broadcastMovingMean,
-                  broadcastMovingVariance,
-                  broadcastBeta,
-                  broadcastGamma,
-                  this.epsilon
-                );
-              } else {
-                return batchNormalization(
-                  input,
-                  this.movingMean.read(),
-                  this.movingVariance.read(),
-                  this.beta == null ? null : this.beta.read(),
-                  this.gamma == null ? null : this.gamma.read(),
-                  this.epsilon
-                );
-              }
-            };
-            if (!training) {
-              return normalizeInference();
-            }
-            const [normedTraining, mean, variance] = normalizeBatchInTraining(
-              input,
-              this.gamma.read(),
-              this.beta.read(),
-              reductionAxes,
-              this.epsilon
-            );
-            const doMovingAverage = (variable, value, momentum) => {
-              dist["tidy"](() => {
-                const decay = 1 - momentum;
-                const origValue = variable.read();
-                const updateDelta = origValue.sub(value).mul(decay);
-                variable.write(origValue.sub(updateDelta));
-              });
-            };
-            // Perform updates to moving mean and moving variance for training.
-            // Porting Note: In PyKeras, these updates to `movingMean` and
-            //   `movingAverage` are done as a deferred Graph, added to the `Layer`'s
-            //   `update`s using the `add_update()` method. Here we do it imperatively
-            //   and encapsulate the updates in a function that is invoked
-            //   immediately.
-            const updateMovingMeanAndVariance = () => {
-              doMovingAverage(this.movingMean, mean, this.momentum);
-              doMovingAverage(this.movingVariance, variance, this.momentum);
-            };
-            updateMovingMeanAndVariance();
-            return normedTraining;
-          });
-        }
-        getConfig() {
-          const config = {
-            axis: this.axis,
-            momentum: this.momentum,
-            epsilon: this.epsilon,
-            center: this.center,
-            scale: this.scale,
-            betaInitializer: serializeInitializer(this.betaInitializer),
-            gammaInitializer: serializeInitializer(this.gammaInitializer),
-            movingMeanInitializer: serializeInitializer(this.movingMeanInitializer),
-            movingVarianceInitializer: serializeInitializer(this.movingVarianceInitializer),
-            betaRegularizer: serializeRegularizer(this.betaRegularizer),
-            gammaRegularizer: serializeRegularizer(this.gammaRegularizer),
-            betaConstraint: serializeConstraint(this.betaConstraint),
-            gammaConstraint: serializeConstraint(this.gammaConstraint),
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      normalization_BatchNormalization.className = "BatchNormalization";
-      dist["serialization"].registerClass(normalization_BatchNormalization);
-      class normalization_LayerNormalization extends topology_Layer {
-        constructor(args) {
-          if (args == null) {
-            args = {};
-          }
-          super(args);
-          this.axis = args.axis == null ? -1 : args.axis;
-          if (typeof this.axis === "number") {
-            if (!Number.isInteger(this.axis)) {
-              throw new Error(`Expected axis to be an integer, but received ${this.axis}`);
-            }
-          } else if (Array.isArray(this.axis)) {
-            for (const axis of this.axis) {
-              if (!Number.isInteger(axis)) {
-                throw new Error(
-                  `Expected axis to be an array of integers, ` +
-                    `but received ${JSON.stringify(this.axis)}`
-                );
-              }
-            }
-          } else {
-            throw new Error(
-              `Expected axis to be an integer or an array of integers, ` +
-                `but received ${JSON.stringify(this.axis)}`
-            );
-          }
-          this.epsilon = args.epsilon == null ? 1e-3 : args.epsilon;
-          this.center = args.center == null ? true : args.center;
-          this.scale = args.scale == null ? true : args.scale;
-          this.betaInitializer = getInitializer(args.betaInitializer || "zeros");
-          this.gammaInitializer = getInitializer(args.gammaInitializer || "ones");
-          this.betaRegularizer = getRegularizer(args.betaRegularizer);
-          this.gammaRegularizer = getRegularizer(args.gammaRegularizer);
-          this.supportsMasking = true;
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const nDims = inputShape.length;
-          // Convert axis to array and resolve negatives.
-          if (typeof this.axis === "number") {
-            this.axis = [this.axis];
-          }
-          for (let i = 0; i < this.axis.length; ++i) {
-            if (this.axis[i] < 0) {
-              this.axis[i] += nDims;
-            }
-          }
-          // Further validate axes.
-          for (const axis of this.axis) {
-            if (axis < 0 || axis >= nDims) {
-              throw new Error(`Invalid axis: ${axis}`);
-            }
-          }
-          if (this.axis.length !== unique(this.axis).length) {
-            throw new Error(`Found duplicate axes in: ${this.axis}`);
-          }
-          const paramShape = this.axis.map((axis) => inputShape[axis]);
-          const trainable = true;
-          if (this.scale) {
-            this.gamma = this.addWeight(
-              "gamma",
-              paramShape,
-              "float32",
-              this.gammaInitializer,
-              this.gammaRegularizer,
-              trainable
-            );
-          } else {
-            this.gamma = null;
-          }
-          if (this.center) {
-            this.beta = this.addWeight(
-              "beta",
-              paramShape,
-              "float32",
-              this.betaInitializer,
-              this.betaRegularizer,
-              trainable
-            );
-          } else {
-            this.beta = null;
-          }
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          const input = getExactlyOneTensor(inputs);
-          const inputShape = input.shape;
-          const nDims = inputShape.length;
-          return Object(dist["tidy"])(() => {
-            const keepDims = true;
-            let { mean, variance } = Object(dist["moments"])(input, this.axis, keepDims);
-            const broadcastShape = pyListRepeat(1, nDims);
-            for (const dim of this.axis) {
-              broadcastShape[dim] = inputShape[dim];
-            }
-            const broadcast = (v) => {
-              if (v != null && v.shape.length !== nDims && this.axis !== [nDims - 1]) {
-                return v.reshape(broadcastShape);
-              } else {
-                return v;
-              }
-            };
-            let scale = broadcast(this.gamma.read());
-            let offset = broadcast(this.beta.read());
-            // TODO(https://github.com/tensorflow/tfjs/issues/2120): The tiling below
-            // is a workaround for the limitation of core's batchNormalization?d don't
-            // support broadcasting in their gradients. In addition, the tiling is
-            // necessary to ensure correctness on the browser CPU backend regardless
-            // of forward or backward computation. Remove this workaround once the
-            // limitation is addressed. See .
-            const momentsTiling = [];
-            const scaleOffsetTiling = [];
-            for (let i = 0; i < nDims; ++i) {
-              if (this.axis.indexOf(i) !== -1) {
-                momentsTiling.push(inputShape[i]);
-                scaleOffsetTiling.push(1);
-              } else {
-                momentsTiling.push(1);
-                scaleOffsetTiling.push(inputShape[i]);
-              }
-            }
-            mean = mean.tile(momentsTiling);
-            variance = variance.tile(momentsTiling);
-            scale = scale.tile(scaleOffsetTiling);
-            offset = offset.tile(scaleOffsetTiling);
-            return batchNormalization(input, mean, variance, offset, scale, this.epsilon);
-          });
-        }
-        getConfig() {
-          const config = {
-            axis: this.axis,
-            epsilon: this.epsilon,
-            center: this.center,
-            scale: this.scale,
-            betaInitializer: serializeInitializer(this.betaInitializer),
-            gammaInitializer: serializeInitializer(this.gammaInitializer),
-            betaRegularizer: serializeRegularizer(this.betaRegularizer),
-            gammaRegularizer: serializeRegularizer(this.gammaRegularizer),
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      normalization_LayerNormalization.className = "LayerNormalization";
-      dist["serialization"].registerClass(normalization_LayerNormalization);
-      //# sourceMappingURL=normalization.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/padding.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Padding Layers.
-       */
-      // Porting Note: In Python Keras, the padding layers are in convolutional.py,
-      //   but we decided to put them in a separate file (padding.ts) for clarity.
-
-      /**
-       * Pads the middle dimension of a 3D tensor.
-       *
-       * @param x Input `tf.Tensor` to be padded.
-       * @param padding `Array` of 2 integers, how many zeros to add at the start and
-       *   end of the middle dimension (i.e., dimension 1).
-       * @return A padded 3D `tf.Tensor`.
-       */
-      function temporalPadding(x, padding) {
-        return Object(dist["tidy"])(() => {
-          if (x.rank !== 3) {
-            throw new ValueError(
-              `temporalPadding expects input tensor to be 3-D, but received a ` +
-                `${x.rank}-D tensor.`
-            );
-          }
-          if (padding == null) {
-            padding = [1, 1];
-          }
-          if (padding.length !== 2) {
-            throw new ValueError(
-              `temporalPadding expects input padding pattern to be a length-2 ` +
-                `array, but received a length-${padding.length} array.`
-            );
-          }
-          const pattern = [[0, 0], padding, [0, 0]];
-          return dist["pad"](x, pattern);
-        });
-      }
-      /**
-       * Pads the 2nd and 3rd dimensions of a 4D tensor.
-       *
-       * @param x Input `tf.Tensor` to be padded.
-       * @param padding `Array` of two `Array`s, each of which is an `Array` of two
-       *   integers. The amount of padding at the beginning and end of the 2nd and 3rd
-       *   dimensions, respectively.
-       * @param dataFormat 'channelsLast' (default) or 'channelsFirst'.
-       * @return Padded 4D `tf.Tensor`.
-       */
-      function spatial2dPadding(x, padding, dataFormat) {
-        return Object(dist["tidy"])(() => {
-          if (x.rank !== 4) {
-            throw new ValueError(
-              `temporalPadding expects input tensor to be 4-D, but received a ` +
-                `${x.rank}-D tensor.`
-            );
-          }
-          if (padding == null) {
-            padding = [
-              [1, 1],
-              [1, 1],
-            ];
-          }
-          if (padding.length !== 2 || padding[0].length !== 2 || padding[1].length !== 2) {
-            throw new ValueError(
-              "spatial2dPadding expects `padding` to be an Array of two Arrays, " +
-                "each of which is an Array of two integers."
-            );
-          }
-          if (dataFormat == null) {
-            dataFormat = imageDataFormat();
-          }
-          if (dataFormat !== "channelsLast" && dataFormat !== "channelsFirst") {
-            throw new ValueError(
-              `Unknown data format: ${dataFormat}. ` +
-                `Supported data formats are 'channelsLast' and 'channelsFirst.`
-            );
-          }
-          let pattern;
-          if (dataFormat === "channelsFirst") {
-            pattern = [[0, 0], [0, 0], padding[0], padding[1]];
-          } else {
-            pattern = [[0, 0], padding[0], padding[1], [0, 0]];
-          }
-          return dist["pad"](x, pattern);
-        });
-      }
-      class padding_ZeroPadding2D extends topology_Layer {
-        constructor(args) {
-          if (args == null) {
-            args = {};
-          }
-          super(args);
-          this.dataFormat = args.dataFormat == null ? imageDataFormat() : args.dataFormat;
-          // TODO(cais): Maybe refactor the following logic surrounding `padding`
-          //   into a helper method.
-          if (args.padding == null) {
-            this.padding = [
-              [1, 1],
-              [1, 1],
-            ];
-          } else if (typeof args.padding === "number") {
-            this.padding = [
-              [args.padding, args.padding],
-              [args.padding, args.padding],
-            ];
-          } else {
-            args.padding = args.padding;
-            if (args.padding.length !== 2) {
-              throw new ValueError(
-                `ZeroPadding2D expects padding to be a length-2 array, but ` +
-                  `received a length-${args.padding.length} array.`
-              );
-            }
-            let heightPadding;
-            let widthPadding;
-            if (typeof args.padding[0] === "number") {
-              heightPadding = [args.padding[0], args.padding[0]];
-              widthPadding = [args.padding[1], args.padding[1]];
-            } else {
-              args.padding = args.padding;
-              if (args.padding[0].length !== 2) {
-                throw new ValueError(
-                  `ZeroPadding2D expects height padding to be a length-2 array, ` +
-                    `but received a length-${args.padding[0].length} array.`
-                );
-              }
-              heightPadding = args.padding[0];
-              if (args.padding[1].length !== 2) {
-                throw new ValueError(
-                  `ZeroPadding2D expects width padding to be a length-2 array, ` +
-                    `but received a length-${args.padding[1].length} array.`
-                );
-              }
-              widthPadding = args.padding[1];
-            }
-            this.padding = [heightPadding, widthPadding];
-          }
-          this.inputSpec = [new InputSpec({ ndim: 4 })];
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          let rows;
-          let cols;
-          if (this.dataFormat === "channelsFirst") {
-            if (inputShape[2] != null && inputShape[2] >= 0) {
-              rows = inputShape[2] + this.padding[0][0] + this.padding[0][1];
-            } else {
-              rows = null;
-            }
-            if (inputShape[3] != null && inputShape[3] >= 0) {
-              cols = inputShape[3] + this.padding[1][0] + this.padding[1][1];
-            } else {
-              cols = null;
-            }
-            return [inputShape[0], inputShape[1], rows, cols];
-          } else {
-            if (inputShape[1] != null && inputShape[1] >= 0) {
-              rows = inputShape[1] + this.padding[0][0] + this.padding[0][1];
-            } else {
-              rows = null;
-            }
-            if (inputShape[2] != null && inputShape[2] >= 0) {
-              cols = inputShape[2] + this.padding[1][0] + this.padding[1][1];
-            } else {
-              cols = null;
-            }
-            return [inputShape[0], rows, cols, inputShape[3]];
-          }
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() =>
-            spatial2dPadding(getExactlyOneTensor(inputs), this.padding, this.dataFormat)
-          );
-        }
-        getConfig() {
-          const config = {
-            padding: this.padding,
-            dataFormat: this.dataFormat,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      padding_ZeroPadding2D.className = "ZeroPadding2D";
-      dist["serialization"].registerClass(padding_ZeroPadding2D);
-      //# sourceMappingURL=padding.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/pooling.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * TensorFlow.js Layers: Pooling Layers.
-       */
-
-      /**
-       * 2D pooling.
-       * @param x
-       * @param poolSize
-       * @param stridesdes strides. Defaults to [1, 1].
-       * @param padding padding. Defaults to 'valid'.
-       * @param dataFormat data format. Defaults to 'channelsLast'.
-       * @param poolMode Mode of pooling. Defaults to 'max'.
-       * @returns Result of the 2D pooling.
-       */
-      function pool2d(x, poolSize, strides, padding, dataFormat, poolMode) {
-        return Object(dist["tidy"])(() => {
-          checkDataFormat(dataFormat);
-          checkPoolMode(poolMode);
-          checkPaddingMode(padding);
-          if (strides == null) {
-            strides = [1, 1];
-          }
-          if (padding == null) {
-            padding = "valid";
-          }
-          if (dataFormat == null) {
-            dataFormat = imageDataFormat();
-          }
-          if (poolMode == null) {
-            poolMode = "max";
-          }
-          // TODO(cais): Remove the preprocessing step once deeplearn.js supports
-          // dataFormat as an input argument.
-          x = preprocessConv2DInput(x, dataFormat); // x is NHWC after preprocessing.
-          let y;
-          const paddingString = padding === "same" ? "same" : "valid";
-          if (poolMode === "max") {
-            // TODO(cais): Rank check?
-            y = dist["maxPool"](x, poolSize, strides, paddingString);
-          } else {
-            // 'avg'
-            // TODO(cais): Check the dtype and rank of x and give clear error message
-            //   if those are incorrect.
-            y = dist["avgPool"](
-              // TODO(cais): Rank check?
-              x,
-              poolSize,
-              strides,
-              paddingString
-            );
-          }
-          if (dataFormat === "channelsFirst") {
-            y = dist["transpose"](y, [0, 3, 1, 2]); // NHWC -> NCHW.
-          }
-          return y;
-        });
-      }
-      /**
-       * 3D pooling.
-       * @param x
-       * @param poolSize. Default to [1, 1, 1].
-       * @param strides strides. Defaults to [1, 1, 1].
-       * @param padding padding. Defaults to 'valid'.
-       * @param dataFormat data format. Defaults to 'channelsLast'.
-       * @param poolMode Mode of pooling. Defaults to 'max'.
-       * @returns Result of the 3D pooling.
-       */
-      function pool3d(x, poolSize, strides, padding, dataFormat, poolMode) {
-        return Object(dist["tidy"])(() => {
-          checkDataFormat(dataFormat);
-          checkPoolMode(poolMode);
-          checkPaddingMode(padding);
-          if (strides == null) {
-            strides = [1, 1, 1];
-          }
-          if (padding == null) {
-            padding = "valid";
-          }
-          if (dataFormat == null) {
-            dataFormat = imageDataFormat();
-          }
-          if (poolMode == null) {
-            poolMode = "max";
-          }
-          // x is NDHWC after preprocessing.
-          x = preprocessConv3DInput(x, dataFormat);
-          let y;
-          const paddingString = padding === "same" ? "same" : "valid";
-          if (poolMode === "max") {
-            y = dist["maxPool3d"](x, poolSize, strides, paddingString);
-          } else {
-            // 'avg'
-            y = dist["avgPool3d"](x, poolSize, strides, paddingString);
-          }
-          if (dataFormat === "channelsFirst") {
-            y = dist["transpose"](y, [0, 4, 1, 2, 3]); // NDHWC -> NCDHW.
-          }
-          return y;
-        });
-      }
-      /**
-       * Abstract class for different pooling 1D layers.
-       */
-      class pooling_Pooling1D extends topology_Layer {
-        /**
-         *
-         * @param args Parameters for the Pooling layer.
-         *
-         * config.poolSize defaults to 2.
-         */
-        constructor(args) {
-          if (args.poolSize == null) {
-            args.poolSize = 2;
-          }
-          super(args);
-          if (typeof args.poolSize === "number") {
-            this.poolSize = [args.poolSize];
-          } else if (
-            Array.isArray(args.poolSize) &&
-            args.poolSize.length === 1 &&
-            typeof args.poolSize[0] === "number"
-          ) {
-            this.poolSize = args.poolSize;
-          } else {
-            throw new ValueError(
-              `poolSize for 1D convolutional layer must be a number or an ` +
-                `Array of a single number, but received ` +
-                `${JSON.stringify(args.poolSize)}`
-            );
-          }
-          assertPositiveInteger(this.poolSize, "poolSize");
-          if (args.strides == null) {
-            this.strides = this.poolSize;
-          } else {
-            if (typeof args.strides === "number") {
-              this.strides = [args.strides];
-            } else if (
-              Array.isArray(args.strides) &&
-              args.strides.length === 1 &&
-              typeof args.strides[0] === "number"
-            ) {
-              this.strides = args.strides;
-            } else {
-              throw new ValueError(
-                `strides for 1D convolutional layer must be a number or an ` +
-                  `Array of a single number, but received ` +
-                  `${JSON.stringify(args.strides)}`
-              );
-            }
-          }
-          assertPositiveInteger(this.strides, "strides");
-          this.padding = args.padding == null ? "valid" : args.padding;
-          checkPaddingMode(this.padding);
-          this.inputSpec = [new InputSpec({ ndim: 3 })];
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const length = convOutputLength(
-            inputShape[1],
-            this.poolSize[0],
-            this.padding,
-            this.strides[0]
-          );
-          return [inputShape[0], length, inputShape[2]];
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            // Add dummy last dimension.
-            inputs = expandDims(getExactlyOneTensor(inputs), 2);
-            const output = this.poolingFunction(
-              getExactlyOneTensor(inputs),
-              [this.poolSize[0], 1],
-              [this.strides[0], 1],
-              this.padding,
-              "channelsLast"
-            );
-            // Remove dummy last dimension.
-            return dist["squeeze"](output, [2]);
-          });
-        }
-        getConfig() {
-          const config = {
-            poolSize: this.poolSize,
-            padding: this.padding,
-            strides: this.strides,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      class pooling_MaxPooling1D extends pooling_Pooling1D {
-        constructor(args) {
-          super(args);
-        }
-        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
-          checkDataFormat(dataFormat);
-          checkPaddingMode(padding);
-          return pool2d(inputs, poolSize, strides, padding, dataFormat, "max");
-        }
-      }
-      /** @nocollapse */
-      pooling_MaxPooling1D.className = "MaxPooling1D";
-      dist["serialization"].registerClass(pooling_MaxPooling1D);
-      class pooling_AveragePooling1D extends pooling_Pooling1D {
-        constructor(args) {
-          super(args);
-        }
-        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
-          checkDataFormat(dataFormat);
-          checkPaddingMode(padding);
-          return pool2d(inputs, poolSize, strides, padding, dataFormat, "avg");
-        }
-      }
-      /** @nocollapse */
-      pooling_AveragePooling1D.className = "AveragePooling1D";
-      dist["serialization"].registerClass(pooling_AveragePooling1D);
-      /**
-       * Abstract class for different pooling 2D layers.
-       */
-      class pooling_Pooling2D extends topology_Layer {
-        constructor(args) {
-          if (args.poolSize == null) {
-            args.poolSize = [2, 2];
-          }
-          super(args);
-          this.poolSize = Array.isArray(args.poolSize)
-            ? args.poolSize
-            : [args.poolSize, args.poolSize];
-          if (args.strides == null) {
-            this.strides = this.poolSize;
-          } else if (Array.isArray(args.strides)) {
-            if (args.strides.length !== 2) {
-              throw new ValueError(
-                `If the strides property of a 2D pooling layer is an Array, ` +
-                  `it is expected to have a length of 2, but received length ` +
-                  `${args.strides.length}.`
-              );
-            }
-            this.strides = args.strides;
-          } else {
-            // `config.strides` is a number.
-            this.strides = [args.strides, args.strides];
-          }
-          assertPositiveInteger(this.poolSize, "poolSize");
-          assertPositiveInteger(this.strides, "strides");
-          this.padding = args.padding == null ? "valid" : args.padding;
-          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
-          checkDataFormat(this.dataFormat);
-          checkPaddingMode(this.padding);
-          this.inputSpec = [new InputSpec({ ndim: 4 })];
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          let rows = this.dataFormat === "channelsFirst" ? inputShape[2] : inputShape[1];
-          let cols = this.dataFormat === "channelsFirst" ? inputShape[3] : inputShape[2];
-          rows = convOutputLength(rows, this.poolSize[0], this.padding, this.strides[0]);
-          cols = convOutputLength(cols, this.poolSize[1], this.padding, this.strides[1]);
-          if (this.dataFormat === "channelsFirst") {
-            return [inputShape[0], inputShape[1], rows, cols];
-          } else {
-            return [inputShape[0], rows, cols, inputShape[3]];
-          }
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            return this.poolingFunction(
-              getExactlyOneTensor(inputs),
-              this.poolSize,
-              this.strides,
-              this.padding,
-              this.dataFormat
-            );
-          });
-        }
-        getConfig() {
-          const config = {
-            poolSize: this.poolSize,
-            padding: this.padding,
-            strides: this.strides,
-            dataFormat: this.dataFormat,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      class pooling_MaxPooling2D extends pooling_Pooling2D {
-        constructor(args) {
-          super(args);
-        }
-        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
-          checkDataFormat(dataFormat);
-          checkPaddingMode(padding);
-          return pool2d(inputs, poolSize, strides, padding, dataFormat, "max");
-        }
-      }
-      /** @nocollapse */
-      pooling_MaxPooling2D.className = "MaxPooling2D";
-      dist["serialization"].registerClass(pooling_MaxPooling2D);
-      class pooling_AveragePooling2D extends pooling_Pooling2D {
-        constructor(args) {
-          super(args);
-        }
-        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
-          checkDataFormat(dataFormat);
-          checkPaddingMode(padding);
-          return pool2d(inputs, poolSize, strides, padding, dataFormat, "avg");
-        }
-      }
-      /** @nocollapse */
-      pooling_AveragePooling2D.className = "AveragePooling2D";
-      dist["serialization"].registerClass(pooling_AveragePooling2D);
-      /**
-       * Abstract class for different pooling 3D layers.
-       */
-      class pooling_Pooling3D extends topology_Layer {
-        constructor(args) {
-          if (args.poolSize == null) {
-            args.poolSize = [2, 2, 2];
-          }
-          super(args);
-          this.poolSize = Array.isArray(args.poolSize)
-            ? args.poolSize
-            : [args.poolSize, args.poolSize, args.poolSize];
-          if (args.strides == null) {
-            this.strides = this.poolSize;
-          } else if (Array.isArray(args.strides)) {
-            if (args.strides.length !== 3) {
-              throw new ValueError(
-                `If the strides property of a 3D pooling layer is an Array, ` +
-                  `it is expected to have a length of 3, but received length ` +
-                  `${args.strides.length}.`
-              );
-            }
-            this.strides = args.strides;
-          } else {
-            // `config.strides` is a number.
-            this.strides = [args.strides, args.strides, args.strides];
-          }
-          assertPositiveInteger(this.poolSize, "poolSize");
-          assertPositiveInteger(this.strides, "strides");
-          this.padding = args.padding == null ? "valid" : args.padding;
-          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
-          checkDataFormat(this.dataFormat);
-          checkPaddingMode(this.padding);
-          this.inputSpec = [new InputSpec({ ndim: 5 })];
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          let depths = this.dataFormat === "channelsFirst" ? inputShape[2] : inputShape[1];
-          let rows = this.dataFormat === "channelsFirst" ? inputShape[3] : inputShape[2];
-          let cols = this.dataFormat === "channelsFirst" ? inputShape[4] : inputShape[3];
-          depths = convOutputLength(depths, this.poolSize[0], this.padding, this.strides[0]);
-          rows = convOutputLength(rows, this.poolSize[1], this.padding, this.strides[1]);
-          cols = convOutputLength(cols, this.poolSize[2], this.padding, this.strides[2]);
-          if (this.dataFormat === "channelsFirst") {
-            return [inputShape[0], inputShape[1], depths, rows, cols];
-          } else {
-            return [inputShape[0], depths, rows, cols, inputShape[4]];
-          }
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            this.invokeCallHook(inputs, kwargs);
-            return this.poolingFunction(
-              getExactlyOneTensor(inputs),
-              this.poolSize,
-              this.strides,
-              this.padding,
-              this.dataFormat
-            );
-          });
-        }
-        getConfig() {
-          const config = {
-            poolSize: this.poolSize,
-            padding: this.padding,
-            strides: this.strides,
-            dataFormat: this.dataFormat,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      class pooling_MaxPooling3D extends pooling_Pooling3D {
-        constructor(args) {
-          super(args);
-        }
-        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
-          checkDataFormat(dataFormat);
-          checkPaddingMode(padding);
-          return pool3d(inputs, poolSize, strides, padding, dataFormat, "max");
-        }
-      }
-      /** @nocollapse */
-      pooling_MaxPooling3D.className = "MaxPooling3D";
-      dist["serialization"].registerClass(pooling_MaxPooling3D);
-      class pooling_AveragePooling3D extends pooling_Pooling3D {
-        constructor(args) {
-          super(args);
-        }
-        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
-          checkDataFormat(dataFormat);
-          checkPaddingMode(padding);
-          return pool3d(inputs, poolSize, strides, padding, dataFormat, "avg");
-        }
-      }
-      /** @nocollapse */
-      pooling_AveragePooling3D.className = "AveragePooling3D";
-      dist["serialization"].registerClass(pooling_AveragePooling3D);
-      /**
-       * Abstract class for different global pooling 1D layers.
-       */
-      class pooling_GlobalPooling1D extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.inputSpec = [new InputSpec({ ndim: 3 })];
-        }
-        computeOutputShape(inputShape) {
-          return [inputShape[0], inputShape[2]];
-        }
-        call(inputs, kwargs) {
-          throw new NotImplementedError();
-        }
-      }
-      class pooling_GlobalAveragePooling1D extends pooling_GlobalPooling1D {
-        constructor(args) {
-          super(args || {});
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            const input = getExactlyOneTensor(inputs);
-            return dist["mean"](input, 1);
-          });
-        }
-      }
-      /** @nocollapse */
-      pooling_GlobalAveragePooling1D.className = "GlobalAveragePooling1D";
-      dist["serialization"].registerClass(pooling_GlobalAveragePooling1D);
-      class pooling_GlobalMaxPooling1D extends pooling_GlobalPooling1D {
-        constructor(args) {
-          super(args || {});
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            const input = getExactlyOneTensor(inputs);
-            return dist["max"](input, 1);
-          });
-        }
-      }
-      /** @nocollapse */
-      pooling_GlobalMaxPooling1D.className = "GlobalMaxPooling1D";
-      dist["serialization"].registerClass(pooling_GlobalMaxPooling1D);
-      /**
-       * Abstract class for different global pooling 2D layers.
-       */
-      class pooling_GlobalPooling2D extends topology_Layer {
-        constructor(args) {
-          super(args);
-          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
-          checkDataFormat(this.dataFormat);
-          this.inputSpec = [new InputSpec({ ndim: 4 })];
-        }
-        computeOutputShape(inputShape) {
-          inputShape = inputShape;
-          if (this.dataFormat === "channelsLast") {
-            return [inputShape[0], inputShape[3]];
-          } else {
-            return [inputShape[0], inputShape[1]];
-          }
-        }
-        call(inputs, kwargs) {
-          throw new NotImplementedError();
-        }
-        getConfig() {
-          const config = { dataFormat: this.dataFormat };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      class pooling_GlobalAveragePooling2D extends pooling_GlobalPooling2D {
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            const input = getExactlyOneTensor(inputs);
-            if (this.dataFormat === "channelsLast") {
-              return dist["mean"](input, [1, 2]);
-            } else {
-              return dist["mean"](input, [2, 3]);
-            }
-          });
-        }
-      }
-      /** @nocollapse */
-      pooling_GlobalAveragePooling2D.className = "GlobalAveragePooling2D";
-      dist["serialization"].registerClass(pooling_GlobalAveragePooling2D);
-      class pooling_GlobalMaxPooling2D extends pooling_GlobalPooling2D {
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            const input = getExactlyOneTensor(inputs);
-            if (this.dataFormat === "channelsLast") {
-              return dist["max"](input, [1, 2]);
-            } else {
-              return dist["max"](input, [2, 3]);
-            }
-          });
-        }
-      }
-      /** @nocollapse */
-      pooling_GlobalMaxPooling2D.className = "GlobalMaxPooling2D";
-      dist["serialization"].registerClass(pooling_GlobalMaxPooling2D);
-      //# sourceMappingURL=pooling.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/recurrent.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * TensorFlow.js Layers: Recurrent Neural Network Layers.
-       */
-
-      /**
-       * Standardize `apply()` args to a single list of tensor inputs.
-       *
-       * When running a model loaded from file, the input tensors `initialState` and
-       * `constants` are passed to `RNN.apply()` as part of `inputs` instead of the
-       * dedicated kwargs fields. `inputs` consists of
-       * `[inputs, initialState0, initialState1, ..., constant0, constant1]` in this
-       * case.
-       * This method makes sure that arguments are
-       * separated and that `initialState` and `constants` are `Array`s of tensors
-       * (or None).
-       *
-       * @param inputs Tensor or `Array` of  tensors.
-       * @param initialState Tensor or `Array` of tensors or `null`/`undefined`.
-       * @param constants Tensor or `Array` of tensors or `null`/`undefined`.
-       * @returns An object consisting of
-       *   inputs: A tensor.
-       *   initialState: `Array` of tensors or `null`.
-       *   constants: `Array` of tensors or `null`.
-       * @throws ValueError, if `inputs` is an `Array` but either `initialState` or
-       *   `constants` is provided.
-       */
-      function standardizeArgs(inputs, initialState, constants, numConstants) {
-        if (Array.isArray(inputs)) {
-          if (initialState != null || constants != null) {
-            throw new ValueError(
-              "When inputs is an array, neither initialState or constants " + "should be provided"
-            );
-          }
-          if (numConstants != null) {
-            constants = inputs.slice(inputs.length - numConstants, inputs.length);
-            inputs = inputs.slice(0, inputs.length - numConstants);
-          }
-          if (inputs.length > 1) {
-            initialState = inputs.slice(1, inputs.length);
-          }
-          inputs = inputs[0];
-        }
-        function toListOrNull(x) {
-          if (x == null || Array.isArray(x)) {
-            return x;
-          } else {
-            return [x];
-          }
-        }
-        initialState = toListOrNull(initialState);
-        constants = toListOrNull(constants);
-        return { inputs, initialState, constants };
-      }
-      /**
-       * Iterates over the time dimension of a tensor.
-       *
-       * @param stepFunction RNN step function.
-       *   Parameters:
-       *     inputs: tensor with shape `[samples, ...]` (no time dimension),
-       *       representing input for the batch of samples at a certain time step.
-       *     states: an Array of tensors.
-       *   Returns:
-       *     outputs: tensor with shape `[samples, outputDim]` (no time dimension).
-       *     newStates: list of tensors, same length and shapes as `states`. The first
-       *       state in the list must be the output tensor at the previous timestep.
-       * @param inputs Tensor of temporal data of shape `[samples, time, ...]` (at
-       *   least 3D).
-       * @param initialStates Tensor with shape `[samples, outputDim]` (no time
-       *   dimension), containing the initial values of the states used in the step
-       *   function.
-       * @param goBackwards If `true`, do the iteration over the time dimension in
-       *   reverse order and return the reversed sequence.
-       * @param mask Binary tensor with shape `[sample, time, 1]`, with a zero for
-       *   every element that is masked.
-       * @param constants An Array of constant values passed at each step.
-       * @param unroll Whether to unroll the RNN or to use a symbolic loop. *Not*
-       *   applicable to this imperative deeplearn.js backend. Its value is ignored.
-       * @param needPerStepOutputs Whether the per-step outputs are to be
-       *   concatenated into a single tensor and returned (as the second return
-       *   value). Default: `false`. This arg is included so that the relatively
-       *   expensive concatenation of the stepwise outputs can be omitted unless
-       *   the stepwise outputs need to be kept (e.g., for an LSTM layer of which
-       *   `returnSequence` is `true`.)
-       * @returns An Array: `[lastOutput, outputs, newStates]`.
-       *   lastOutput: the lastest output of the RNN, of shape `[samples, ...]`.
-       *   outputs: tensor with shape `[samples, time, ...]` where each entry
-       *     `output[s, t]` is the output of the step function at time `t` for sample
-       *     `s`. This return value is provided if and only if the
-       *     `needPerStepOutputs` is set as `true`. If it is set as `false`, this
-       *     return value will be `undefined`.
-       *   newStates: Array of tensors, latest states returned by the step function,
-       *      of shape `(samples, ...)`.
-       * @throws ValueError If input dimension is less than 3.
-       *
-       * TODO(nielsene): This needs to be tidy-ed.
-       */
-      function rnn(
-        stepFunction,
-        inputs,
-        initialStates,
-        goBackwards = false,
-        mask,
-        constants,
-        unroll = false,
-        needPerStepOutputs = false
-      ) {
-        return dist["tidy"](() => {
-          const ndim = inputs.shape.length;
-          if (ndim < 3) {
-            throw new ValueError(`Input should be at least 3D, but is ${ndim}D.`);
-          }
-          // Transpose to time-major, i.e., from [batch, time, ...] to [time, batch,
-          // ...].
-          const axes = [1, 0].concat(range(2, ndim));
-          inputs = dist["transpose"](inputs, axes);
-          if (constants != null) {
-            throw new NotImplementedError(
-              "The rnn() functoin of the deeplearn.js backend does not support " + "constants yet."
-            );
-          }
-          // Porting Note: the unroll option is ignored by the imperative backend.
-          if (unroll) {
-            console.warn(
-              "Backend rnn(): the unroll = true option is not applicable to the " +
-                "imperative deeplearn.js backend."
-            );
-          }
-          if (mask != null) {
-            mask = mask.asType("bool").asType("float32");
-            if (mask.rank === ndim - 1) {
-              mask = dist["expandDims"](mask, -1);
-            }
-            mask = dist["transpose"](mask, axes);
-          }
-          if (goBackwards) {
-            inputs = dist["reverse"](inputs, 0);
-            if (mask != null) {
-              mask = dist["reverse"](mask, 0);
-            }
-          }
-          // Porting Note: PyKeras with TensorFlow backend uses a symbolic loop
-          //   (tf.while_loop). But for the imperative deeplearn.js backend, we just
-          //   use the usual TypeScript control flow to iterate over the time steps in
-          //   the inputs.
-          // Porting Note: PyKeras patches a "_use_learning_phase" attribute to
-          // outputs.
-          //   This is not idiomatic in TypeScript. The info regarding whether we are
-          //   in a learning (i.e., training) phase for RNN is passed in a different
-          //   way.
-          const perStepOutputs = [];
-          let lastOutput;
-          let states = initialStates;
-          const timeSteps = inputs.shape[0];
-          const perStepInputs = dist["unstack"](inputs);
-          let perStepMasks;
-          if (mask != null) {
-            perStepMasks = dist["unstack"](mask);
-          }
-          for (let t = 0; t < timeSteps; ++t) {
-            const currentInput = perStepInputs[t];
-            const stepOutputs = dist["tidy"](() => stepFunction(currentInput, states));
-            if (mask == null) {
-              lastOutput = stepOutputs[0];
-              states = stepOutputs[1];
-            } else {
-              const maskedOutputs = dist["tidy"](() => {
-                const stepMask = perStepMasks[t];
-                const negStepMask = dist["onesLike"](stepMask).sub(stepMask);
-                // TODO(cais): Would tfc.where() be better for performance?
-                const output = stepOutputs[0].mul(stepMask).add(states[0].mul(negStepMask));
-                const newStates = states.map((state, i) => {
-                  return stepOutputs[1][i].mul(stepMask).add(state.mul(negStepMask));
-                });
-                return { output, newStates };
-              });
-              lastOutput = maskedOutputs.output;
-              states = maskedOutputs.newStates;
-            }
-            if (needPerStepOutputs) {
-              perStepOutputs.push(lastOutput);
-            }
-          }
-          let outputs;
-          if (needPerStepOutputs) {
-            const axis = 1;
-            outputs = dist["stack"](perStepOutputs, axis);
-          }
-          return [lastOutput, outputs, states];
-        });
-      }
-      class recurrent_RNN extends topology_Layer {
-        constructor(args) {
-          super(args);
-          let cell;
-          if (args.cell == null) {
-            throw new ValueError("cell property is missing for the constructor of RNN.");
-          } else if (Array.isArray(args.cell)) {
-            cell = new recurrent_StackedRNNCells({ cells: args.cell });
-          } else {
-            cell = args.cell;
-          }
-          if (cell.stateSize == null) {
-            throw new ValueError(
-              "The RNN cell should have an attribute `stateSize` (tuple of " +
-                "integers, one integer per RNN state)."
-            );
-          }
-          this.cell = cell;
-          this.returnSequences = args.returnSequences == null ? false : args.returnSequences;
-          this.returnState = args.returnState == null ? false : args.returnState;
-          this.goBackwards = args.goBackwards == null ? false : args.goBackwards;
-          this._stateful = args.stateful == null ? false : args.stateful;
-          this.unroll = args.unroll == null ? false : args.unroll;
-          this.supportsMasking = true;
-          this.inputSpec = [new InputSpec({ ndim: 3 })];
-          this.stateSpec = null;
-          this.states_ = null;
-          // TODO(cais): Add constantsSpec and numConstants.
-          this.numConstants = null;
-          // TODO(cais): Look into the use of initial_state in the kwargs of the
-          //   constructor.
-          this.keptStates = [];
-        }
-        // Porting Note: This is the equivalent of `RNN.states` property getter in
-        //   PyKeras.
-        getStates() {
-          if (this.states_ == null) {
-            const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;
-            return range(0, numStates).map((x) => null);
-          } else {
-            return this.states_;
-          }
-        }
-        // Porting Note: This is the equivalent of the `RNN.states` property setter in
-        //   PyKeras.
-        setStates(states) {
-          this.states_ = states;
-        }
-        computeOutputShape(inputShape) {
-          if (isArrayOfShapes(inputShape)) {
-            inputShape = inputShape[0];
-          }
-          inputShape = inputShape;
-          // TODO(cais): Remove the casting once stacked RNN cells become supported.
-          let stateSize = this.cell.stateSize;
-          if (!Array.isArray(stateSize)) {
-            stateSize = [stateSize];
-          }
-          const outputDim = stateSize[0];
-          let outputShape;
-          if (this.returnSequences) {
-            outputShape = [inputShape[0], inputShape[1], outputDim];
-          } else {
-            outputShape = [inputShape[0], outputDim];
-          }
-          if (this.returnState) {
-            const stateShape = [];
-            for (const dim of stateSize) {
-              stateShape.push([inputShape[0], dim]);
-            }
-            return [outputShape].concat(stateShape);
-          } else {
-            return outputShape;
-          }
-        }
-        computeMask(inputs, mask) {
-          return dist["tidy"](() => {
-            if (Array.isArray(mask)) {
-              mask = mask[0];
-            }
-            const outputMask = this.returnSequences ? mask : null;
-            if (this.returnState) {
-              const stateMask = this.states.map((s) => null);
-              return [outputMask].concat(stateMask);
-            } else {
-              return outputMask;
-            }
-          });
-        }
-        /**
-         * Get the current state tensors of the RNN.
-         *
-         * If the state hasn't been set, return an array of `null`s of the correct
-         * length.
-         */
-        get states() {
-          if (this.states_ == null) {
-            const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;
-            const output = [];
-            for (let i = 0; i < numStates; ++i) {
-              output.push(null);
-            }
-            return output;
-          } else {
-            return this.states_;
-          }
-        }
-        set states(s) {
-          this.states_ = s;
-        }
-        build(inputShape) {
-          // Note inputShape will be an Array of Shapes of initial states and
-          // constants if these are passed in apply().
-          const constantShape = null;
-          if (this.numConstants != null) {
-            throw new NotImplementedError("Constants support is not implemented in RNN yet.");
-          }
-          if (isArrayOfShapes(inputShape)) {
-            inputShape = inputShape[0];
-          }
-          inputShape = inputShape;
-          const batchSize = this.stateful ? inputShape[0] : null;
-          const inputDim = inputShape[inputShape.length - 1];
-          this.inputSpec[0] = new InputSpec({ shape: [batchSize, null, inputDim] });
-          // Allow cell (if RNNCell Layer) to build before we set or validate
-          // stateSpec.
-          const stepInputShape = [inputShape[0]].concat(inputShape.slice(2));
-          if (constantShape != null) {
-            throw new NotImplementedError("Constants support is not implemented in RNN yet.");
-          } else {
-            this.cell.build(stepInputShape);
-          }
-          // Set or validate stateSpec.
-          let stateSize;
-          if (Array.isArray(this.cell.stateSize)) {
-            stateSize = this.cell.stateSize;
-          } else {
-            stateSize = [this.cell.stateSize];
-          }
-          if (this.stateSpec != null) {
-            if (
-              !dist["util"].arraysEqual(
-                this.stateSpec.map((spec) => spec.shape[spec.shape.length - 1]),
-                stateSize
-              )
-            ) {
-              throw new ValueError(
-                `An initialState was passed that is not compatible with ` +
-                  `cell.stateSize. Received stateSpec=${this.stateSpec}; ` +
-                  `However cell.stateSize is ${this.cell.stateSize}`
-              );
-            }
-          } else {
-            this.stateSpec = stateSize.map((dim) => new InputSpec({ shape: [null, dim] }));
-          }
-          if (this.stateful) {
-            this.resetStates();
-          }
-        }
-        /**
-         * Reset the state tensors of the RNN.
-         *
-         * If the `states` argument is `undefined` or `null`, will set the
-         * state tensor(s) of the RNN to all-zero tensors of the appropriate
-         * shape(s).
-         *
-         * If `states` is provided, will set the state tensors of the RNN to its
-         * value.
-         *
-         * @param states Optional externally-provided initial states.
-         * @param training Whether this call is done during training. For stateful
-         *   RNNs, this affects whether the old states are kept or discarded. In
-         *   particular, if `training` is `true`, the old states will be kept so
-         *   that subsequent backpropgataion through time (BPTT) may work properly.
-         *   Else, the old states will be discarded.
-         */
-        resetStates(states, training = false) {
-          Object(dist["tidy"])(() => {
-            if (!this.stateful) {
-              throw new AttributeError(
-                "Cannot call resetStates() on an RNN Layer that is not stateful."
-              );
-            }
-            const batchSize = this.inputSpec[0].shape[0];
-            if (batchSize == null) {
-              throw new ValueError(
-                "If an RNN is stateful, it needs to know its batch size. Specify " +
-                  "the batch size of your input tensors: \n" +
-                  "- If using a Sequential model, specify the batch size by " +
-                  "passing a `batchInputShape` option to your first layer.\n" +
-                  "- If using the functional API, specify the batch size by " +
-                  "passing a `batchShape` option to your Input layer."
-              );
-            }
-            // Initialize state if null.
-            if (this.states_ == null) {
-              if (Array.isArray(this.cell.stateSize)) {
-                this.states_ = this.cell.stateSize.map((dim) => dist["zeros"]([batchSize, dim]));
-              } else {
-                this.states_ = [dist["zeros"]([batchSize, this.cell.stateSize])];
-              }
-            } else if (states == null) {
-              // Dispose old state tensors.
-              dist["dispose"](this.states_);
-              // For stateful RNNs, fully dispose kept old states.
-              if (this.keptStates != null) {
-                dist["dispose"](this.keptStates);
-                this.keptStates = [];
-              }
-              if (Array.isArray(this.cell.stateSize)) {
-                this.states_ = this.cell.stateSize.map((dim) => dist["zeros"]([batchSize, dim]));
-              } else {
-                this.states_[0] = dist["zeros"]([batchSize, this.cell.stateSize]);
-              }
-            } else {
-              if (!Array.isArray(states)) {
-                states = [states];
-              }
-              if (states.length !== this.states_.length) {
-                throw new ValueError(
-                  `Layer ${this.name} expects ${this.states_.length} state(s), ` +
-                    `but it received ${states.length} state value(s). Input ` +
-                    `received: ${states}`
-                );
-              }
-              if (training === true) {
-                // Store old state tensors for complete disposal later, i.e., during
-                // the next no-arg call to this method. We do not dispose the old
-                // states immediately because that BPTT (among other things) require
-                // them.
-                this.keptStates.push(this.states_.slice());
-              } else {
-                dist["dispose"](this.states_);
-              }
-              for (let index = 0; index < this.states_.length; ++index) {
-                const value = states[index];
-                const dim = Array.isArray(this.cell.stateSize)
-                  ? this.cell.stateSize[index]
-                  : this.cell.stateSize;
-                const expectedShape = [batchSize, dim];
-                if (!dist["util"].arraysEqual(value.shape, expectedShape)) {
-                  throw new ValueError(
-                    `State ${index} is incompatible with layer ${this.name}: ` +
-                      `expected shape=${expectedShape}, received shape=${value.shape}`
-                  );
-                }
-                this.states_[index] = value;
-              }
-            }
-            this.states_ = this.states_.map((state) => dist["keep"](state.clone()));
-          });
-        }
-        apply(inputs, kwargs) {
-          // TODO(cais): Figure out whether initialState is in kwargs or inputs.
-          let initialState = kwargs == null ? null : kwargs["initialState"];
-          let constants = kwargs == null ? null : kwargs["constants"];
-          if (kwargs == null) {
-            kwargs = {};
-          }
-          const standardized = standardizeArgs(inputs, initialState, constants, this.numConstants);
-          inputs = standardized.inputs;
-          initialState = standardized.initialState;
-          constants = standardized.constants;
-          // If any of `initial_state` or `constants` are specified and are
-          // `tf.SymbolicTensor`s, then add them to the inputs and temporarily modify
-          // the input_spec to include them.
-          let additionalInputs = [];
-          let additionalSpecs = [];
-          if (initialState != null) {
-            kwargs["initialState"] = initialState;
-            additionalInputs = additionalInputs.concat(initialState);
-            this.stateSpec = [];
-            for (const state of initialState) {
-              this.stateSpec.push(new InputSpec({ shape: state.shape }));
-            }
-            // TODO(cais): Use the following instead.
-            // this.stateSpec = initialState.map(state => new InputSpec({shape:
-            // state.shape}));
-            additionalSpecs = additionalSpecs.concat(this.stateSpec);
-          }
-          if (constants != null) {
-            kwargs["constants"] = constants;
-            additionalInputs = additionalInputs.concat(constants);
-            // TODO(cais): Add this.constantsSpec.
-            this.numConstants = constants.length;
-          }
-          const isTensor = additionalInputs[0] instanceof topology_SymbolicTensor;
-          if (isTensor) {
-            // Compute full input spec, including state and constants.
-            const fullInput = [inputs].concat(additionalInputs);
-            const fullInputSpec = this.inputSpec.concat(additionalSpecs);
-            // Perform the call with temporarily replaced inputSpec.
-            const originalInputSpec = this.inputSpec;
-            this.inputSpec = fullInputSpec;
-            const output = super.apply(fullInput, kwargs);
-            this.inputSpec = originalInputSpec;
-            return output;
-          } else {
-            return super.apply(inputs, kwargs);
-          }
-        }
-        // tslint:disable-next-line:no-any
-        call(inputs, kwargs) {
-          // Input shape: `[samples, time (padded with zeros), input_dim]`.
-          // Note that the .build() method of subclasses **must** define
-          // this.inputSpec and this.stateSpec owith complete input shapes.
-          return Object(dist["tidy"])(() => {
-            const mask = kwargs == null ? null : kwargs["mask"];
-            const training = kwargs == null ? null : kwargs["training"];
-            let initialState = kwargs == null ? null : kwargs["initialState"];
-            inputs = getExactlyOneTensor(inputs);
-            if (initialState == null) {
-              if (this.stateful) {
-                initialState = this.states_;
-              } else {
-                initialState = this.getInitialState(inputs);
-              }
-            }
-            const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;
-            if (initialState.length !== numStates) {
-              throw new ValueError(
-                `RNN Layer has ${numStates} state(s) but was passed ` +
-                  `${initialState.length} initial state(s).`
-              );
-            }
-            if (this.unroll) {
-              console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");
-            }
-            const cellCallKwargs = { training };
-            // TODO(cais): Add support for constants.
-            const step = (inputs, states) => {
-              // `inputs` and `states` are concatenated to form a single `Array` of
-              // `tf.Tensor`s as the input to `cell.call()`.
-              const outputs = this.cell.call([inputs].concat(states), cellCallKwargs);
-              // Marshall the return value into output and new states.
-              return [outputs[0], outputs.slice(1)];
-            };
-            // TODO(cais): Add support for constants.
-            const rnnOutputs = rnn(
-              step,
-              inputs,
-              initialState,
-              this.goBackwards,
-              mask,
-              null,
-              this.unroll,
-              this.returnSequences
-            );
-            const lastOutput = rnnOutputs[0];
-            const outputs = rnnOutputs[1];
-            const states = rnnOutputs[2];
-            if (this.stateful) {
-              this.resetStates(states, training);
-            }
-            const output = this.returnSequences ? outputs : lastOutput;
-            // TODO(cais): Porperty set learning phase flag.
-            if (this.returnState) {
-              return [output].concat(states);
-            } else {
-              return output;
-            }
-          });
-        }
-        getInitialState(inputs) {
-          return Object(dist["tidy"])(() => {
-            // Build an all-zero tensor of shape [samples, outputDim].
-            // [Samples, timeSteps, inputDim].
-            let initialState = dist["zeros"](inputs.shape);
-            // [Samples].
-            initialState = dist["sum"](initialState, [1, 2]);
-            initialState = expandDims(initialState); // [Samples, 1].
-            if (Array.isArray(this.cell.stateSize)) {
-              return this.cell.stateSize.map((dim) =>
-                dim > 1 ? tile(initialState, [1, dim]) : initialState
-              );
-            } else {
-              return this.cell.stateSize > 1
-                ? [tile(initialState, [1, this.cell.stateSize])]
-                : [initialState];
-            }
-          });
-        }
-        get trainableWeights() {
-          if (!this.trainable) {
-            return [];
-          }
-          // Porting Note: In TypeScript, `this` is always an instance of `Layer`.
-          return this.cell.trainableWeights;
-        }
-        get nonTrainableWeights() {
-          // Porting Note: In TypeScript, `this` is always an instance of `Layer`.
-          if (!this.trainable) {
-            return this.cell.weights;
-          }
-          return this.cell.nonTrainableWeights;
-        }
-        setFastWeightInitDuringBuild(value) {
-          super.setFastWeightInitDuringBuild(value);
-          if (this.cell != null) {
-            this.cell.setFastWeightInitDuringBuild(value);
-          }
-        }
-        getConfig() {
-          const config = {
-            returnSequences: this.returnSequences,
-            returnState: this.returnState,
-            goBackwards: this.goBackwards,
-            stateful: this.stateful,
-            unroll: this.unroll,
-          };
-          if (this.numConstants != null) {
-            config["numConstants"] = this.numConstants;
-          }
-          const cellConfig = this.cell.getConfig();
-          config["cell"] = {
-            className: this.cell.getClassName(),
-            config: cellConfig,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config, customObjects = {}) {
-          const cellConfig = config["cell"];
-          const cell = deserialize(cellConfig, customObjects);
-          return new cls(Object.assign(config, { cell }));
-        }
-      }
-      /** @nocollapse */
-      recurrent_RNN.className = "RNN";
-      dist["serialization"].registerClass(recurrent_RNN);
-      /**
-       * An RNNCell layer.
-       */
-      // Porting Note: This is a common parent class for RNN cells. There is no
-      // equivalent of this in PyKeras. Having a common parent class forgoes the
-      //  need for `has_attr(cell, ...)` checks or its TypeScript equivalent.
-      /** @doc {heading: 'Layers', subheading: 'Classes'} */
-      class recurrent_RNNCell extends topology_Layer {}
-      class recurrent_SimpleRNNCell extends recurrent_RNNCell {
-        constructor(args) {
-          super(args);
-          this.DEFAULT_ACTIVATION = "tanh";
-          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
-          this.DEFAULT_RECURRENT_INITIALIZER = "orthogonal";
-          this.DEFAULT_BIAS_INITIALIZER = "zeros";
-          this.units = args.units;
-          assertPositiveInteger(this.units, `units`);
-          this.activation = getActivation(
-            args.activation == null ? this.DEFAULT_ACTIVATION : args.activation
-          );
-          this.useBias = args.useBias == null ? true : args.useBias;
-          this.kernelInitializer = getInitializer(
-            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
-          );
-          this.recurrentInitializer = getInitializer(
-            args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER
-          );
-          this.biasInitializer = getInitializer(
-            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
-          );
-          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
-          this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);
-          this.biasRegularizer = getRegularizer(args.biasRegularizer);
-          this.kernelConstraint = getConstraint(args.kernelConstraint);
-          this.recurrentConstraint = getConstraint(args.recurrentConstraint);
-          this.biasConstraint = getConstraint(args.biasConstraint);
-          this.dropout = min([1, max([0, args.dropout == null ? 0 : args.dropout])]);
-          this.recurrentDropout = min([
-            1,
-            max([0, args.recurrentDropout == null ? 0 : args.recurrentDropout]),
-          ]);
-          this.stateSize = this.units;
-          this.dropoutMask = null;
-          this.recurrentDropoutMask = null;
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          // TODO(cais): Use regularizer.
-          this.kernel = this.addWeight(
-            "kernel",
-            [inputShape[inputShape.length - 1], this.units],
-            null,
-            this.kernelInitializer,
-            this.kernelRegularizer,
-            true,
-            this.kernelConstraint
-          );
-          this.recurrentKernel = this.addWeight(
-            "recurrent_kernel",
-            [this.units, this.units],
-            null,
-            this.recurrentInitializer,
-            this.recurrentRegularizer,
-            true,
-            this.recurrentConstraint
-          );
-          if (this.useBias) {
-            this.bias = this.addWeight(
-              "bias",
-              [this.units],
-              null,
-              this.biasInitializer,
-              this.biasRegularizer,
-              true,
-              this.biasConstraint
-            );
-          } else {
-            this.bias = null;
-          }
-          this.built = true;
-        }
-        // Porting Note: PyKeras' equivalent of this method takes two tensor inputs:
-        //   `inputs` and `states`. Here, the two tensors are combined into an
-        //   `Tensor[]` Array as the first input argument.
-        //   Similarly, PyKeras' equivalent of this method returns two values:
-        //    `output` and `[output]`. Here the two are combined into one length-2
-        //    `Tensor[]`, consisting of `output` repeated.
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = inputs;
-            if (inputs.length !== 2) {
-              throw new ValueError(`SimpleRNNCell expects 2 input Tensors, got ${inputs.length}.`);
-            }
-            let prevOutput = inputs[1];
-            inputs = inputs[0];
-            const training = kwargs["training"] == null ? false : kwargs["training"];
-            if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {
-              this.dropoutMask = generateDropoutMask(
-                () => dist["onesLike"](inputs),
-                this.dropout,
-                training
-              );
-            }
-            if (
-              0 < this.recurrentDropout &&
-              this.recurrentDropout < 1 &&
-              this.recurrentDropoutMask == null
-            ) {
-              this.recurrentDropoutMask = generateDropoutMask(
-                () => dist["onesLike"](prevOutput),
-                this.recurrentDropout,
-                training
-              );
-            }
-            let h;
-            const dpMask = this.dropoutMask;
-            const recDpMask = this.recurrentDropoutMask;
-            if (dpMask != null) {
-              h = dot(dist["mul"](inputs, dpMask), this.kernel.read());
-            } else {
-              h = dot(inputs, this.kernel.read());
-            }
-            if (this.bias != null) {
-              h = biasAdd(h, this.bias.read());
-            }
-            if (recDpMask != null) {
-              prevOutput = dist["mul"](prevOutput, recDpMask);
-            }
-            let output = dist["add"](h, dot(prevOutput, this.recurrentKernel.read()));
-            if (this.activation != null) {
-              output = this.activation.apply(output);
-            }
-            // TODO(cais): Properly set learning phase on output tensor?
-            return [output, output];
-          });
-        }
-        getConfig() {
-          const config = {
-            units: this.units,
-            activation: serializeActivation(this.activation),
-            useBias: this.useBias,
-            kernelInitializer: serializeInitializer(this.kernelInitializer),
-            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
-            biasInitializer: serializeInitializer(this.biasInitializer),
-            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
-            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
-            biasRegularizer: serializeRegularizer(this.biasRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            kernelConstraint: serializeConstraint(this.kernelConstraint),
-            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
-            biasConstraint: serializeConstraint(this.biasConstraint),
-            dropout: this.dropout,
-            recurrentDropout: this.recurrentDropout,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      recurrent_SimpleRNNCell.className = "SimpleRNNCell";
-      dist["serialization"].registerClass(recurrent_SimpleRNNCell);
-      class recurrent_SimpleRNN extends recurrent_RNN {
-        constructor(args) {
-          args.cell = new recurrent_SimpleRNNCell(args);
-          super(args);
-          // TODO(cais): Add activityRegularizer.
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            if (this.cell.dropoutMask != null) {
-              dist["dispose"](this.cell.dropoutMask);
-              this.cell.dropoutMask = null;
-            }
-            if (this.cell.recurrentDropoutMask != null) {
-              dist["dispose"](this.cell.recurrentDropoutMask);
-              this.cell.recurrentDropoutMask = null;
-            }
-            const mask = kwargs == null ? null : kwargs["mask"];
-            const training = kwargs == null ? null : kwargs["training"];
-            const initialState = kwargs == null ? null : kwargs["initialState"];
-            return super.call(inputs, { mask, training, initialState });
-          });
-        }
-        // TODO(cais): Research possibility of refactoring out the tedious all
-        //   the getters that delegate to `this.cell` below.
-        get units() {
-          return this.cell.units;
-        }
-        get activation() {
-          return this.cell.activation;
-        }
-        get useBias() {
-          return this.cell.useBias;
-        }
-        get kernelInitializer() {
-          return this.cell.kernelInitializer;
-        }
-        get recurrentInitializer() {
-          return this.cell.recurrentInitializer;
-        }
-        get biasInitializer() {
-          return this.cell.biasInitializer;
-        }
-        get kernelRegularizer() {
-          return this.cell.kernelRegularizer;
-        }
-        get recurrentRegularizer() {
-          return this.cell.recurrentRegularizer;
-        }
-        get biasRegularizer() {
-          return this.cell.biasRegularizer;
-        }
-        get kernelConstraint() {
-          return this.cell.kernelConstraint;
-        }
-        get recurrentConstraint() {
-          return this.cell.recurrentConstraint;
-        }
-        get biasConstraint() {
-          return this.cell.biasConstraint;
-        }
-        get dropout() {
-          return this.cell.dropout;
-        }
-        get recurrentDropout() {
-          return this.cell.recurrentDropout;
-        }
-        getConfig() {
-          const config = {
-            units: this.units,
-            activation: serializeActivation(this.activation),
-            useBias: this.useBias,
-            kernelInitializer: serializeInitializer(this.kernelInitializer),
-            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
-            biasInitializer: serializeInitializer(this.biasInitializer),
-            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
-            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
-            biasRegularizer: serializeRegularizer(this.biasRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            kernelConstraint: serializeConstraint(this.kernelConstraint),
-            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
-            biasConstraint: serializeConstraint(this.biasConstraint),
-            dropout: this.dropout,
-            recurrentDropout: this.recurrentDropout,
-          };
-          const baseConfig = super.getConfig();
-          delete baseConfig["cell"];
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          return new cls(config);
-        }
-      }
-      /** @nocollapse */
-      recurrent_SimpleRNN.className = "SimpleRNN";
-      dist["serialization"].registerClass(recurrent_SimpleRNN);
-      class recurrent_GRUCell extends recurrent_RNNCell {
-        constructor(args) {
-          super(args);
-          this.DEFAULT_ACTIVATION = "tanh";
-          this.DEFAULT_RECURRENT_ACTIVATION = "hardSigmoid";
-          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
-          this.DEFAULT_RECURRENT_INITIALIZER = "orthogonal";
-          this.DEFAULT_BIAS_INITIALIZER = "zeros";
-          if (args.resetAfter) {
-            throw new ValueError(`GRUCell does not support reset_after parameter set to true.`);
-          }
-          this.units = args.units;
-          assertPositiveInteger(this.units, "units");
-          this.activation = getActivation(
-            args.activation === undefined ? this.DEFAULT_ACTIVATION : args.activation
-          );
-          this.recurrentActivation = getActivation(
-            args.recurrentActivation === undefined
-              ? this.DEFAULT_RECURRENT_ACTIVATION
-              : args.recurrentActivation
-          );
-          this.useBias = args.useBias == null ? true : args.useBias;
-          this.kernelInitializer = getInitializer(
-            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
-          );
-          this.recurrentInitializer = getInitializer(
-            args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER
-          );
-          this.biasInitializer = getInitializer(
-            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
-          );
-          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
-          this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);
-          this.biasRegularizer = getRegularizer(args.biasRegularizer);
-          this.kernelConstraint = getConstraint(args.kernelConstraint);
-          this.recurrentConstraint = getConstraint(args.recurrentConstraint);
-          this.biasConstraint = getConstraint(args.biasConstraint);
-          this.dropout = min([1, max([0, args.dropout == null ? 0 : args.dropout])]);
-          this.recurrentDropout = min([
-            1,
-            max([0, args.recurrentDropout == null ? 0 : args.recurrentDropout]),
-          ]);
-          this.implementation = args.implementation;
-          this.stateSize = this.units;
-          this.dropoutMask = null;
-          this.recurrentDropoutMask = null;
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const inputDim = inputShape[inputShape.length - 1];
-          this.kernel = this.addWeight(
-            "kernel",
-            [inputDim, this.units * 3],
-            null,
-            this.kernelInitializer,
-            this.kernelRegularizer,
-            true,
-            this.kernelConstraint
-          );
-          this.recurrentKernel = this.addWeight(
-            "recurrent_kernel",
-            [this.units, this.units * 3],
-            null,
-            this.recurrentInitializer,
-            this.recurrentRegularizer,
-            true,
-            this.recurrentConstraint
-          );
-          if (this.useBias) {
-            this.bias = this.addWeight(
-              "bias",
-              [this.units * 3],
-              null,
-              this.biasInitializer,
-              this.biasRegularizer,
-              true,
-              this.biasConstraint
-            );
-          } else {
-            this.bias = null;
-          }
-          // Porting Notes: Unlike the PyKeras implementation, we perform slicing
-          //   of the weights and bias in the call() method, at execution time.
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = inputs;
-            if (inputs.length !== 2) {
-              throw new ValueError(
-                `GRUCell expects 2 input Tensors (inputs, h, c), got ` + `${inputs.length}.`
-              );
-            }
-            const training = kwargs["training"] == null ? false : kwargs["training"];
-            let hTMinus1 = inputs[1]; // Previous memory state.
-            inputs = inputs[0];
-            // Note: For superior performance, TensorFlow.js always uses
-            // implementation 2, regardless of the actual value of
-            // config.implementation.
-            if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {
-              this.dropoutMask = generateDropoutMask(
-                () => dist["onesLike"](inputs),
-                this.dropout,
-                training,
-                3
-              );
-            }
-            if (
-              0 < this.recurrentDropout &&
-              this.recurrentDropout < 1 &&
-              this.recurrentDropoutMask == null
-            ) {
-              this.recurrentDropoutMask = generateDropoutMask(
-                () => dist["onesLike"](hTMinus1),
-                this.recurrentDropout,
-                training,
-                3
-              );
-            }
-            const dpMask = this.dropoutMask;
-            const recDpMask = this.recurrentDropoutMask;
-            let z;
-            let r;
-            let hh;
-            if (0 < this.dropout && this.dropout < 1) {
-              inputs = dist["mul"](inputs, dpMask[0]);
-            }
-            let matrixX = dot(inputs, this.kernel.read());
-            if (this.useBias) {
-              matrixX = biasAdd(matrixX, this.bias.read());
-            }
-            if (0 < this.recurrentDropout && this.recurrentDropout < 1) {
-              hTMinus1 = dist["mul"](hTMinus1, recDpMask[0]);
-            }
-            const recurrentKernelValue = this.recurrentKernel.read();
-            const [rk1, rk2] = dist["split"](
-              recurrentKernelValue,
-              [2 * this.units, this.units],
-              recurrentKernelValue.rank - 1
-            );
-            const matrixInner = dot(hTMinus1, rk1);
-            const [xZ, xR, xH] = dist["split"](matrixX, 3, matrixX.rank - 1);
-            const [recurrentZ, recurrentR] = dist["split"](matrixInner, 2, matrixInner.rank - 1);
-            z = this.recurrentActivation.apply(dist["add"](xZ, recurrentZ));
-            r = this.recurrentActivation.apply(dist["add"](xR, recurrentR));
-            const recurrentH = dot(dist["mul"](r, hTMinus1), rk2);
-            hh = this.activation.apply(dist["add"](xH, recurrentH));
-            const h = dist["add"](
-              dist["mul"](z, hTMinus1),
-              dist["mul"](dist["add"](1, dist["neg"](z)), hh)
-            );
-            // TODO(cais): Add use_learning_phase flag properly.
-            return [h, h];
-          });
-        }
-        getConfig() {
-          const config = {
-            units: this.units,
-            activation: serializeActivation(this.activation),
-            recurrentActivation: serializeActivation(this.recurrentActivation),
-            useBias: this.useBias,
-            kernelInitializer: serializeInitializer(this.kernelInitializer),
-            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
-            biasInitializer: serializeInitializer(this.biasInitializer),
-            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
-            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
-            biasRegularizer: serializeRegularizer(this.biasRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            kernelConstraint: serializeConstraint(this.kernelConstraint),
-            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
-            biasConstraint: serializeConstraint(this.biasConstraint),
-            dropout: this.dropout,
-            recurrentDropout: this.recurrentDropout,
-            implementation: this.implementation,
-            resetAfter: false,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      recurrent_GRUCell.className = "GRUCell";
-      dist["serialization"].registerClass(recurrent_GRUCell);
-      class recurrent_GRU extends recurrent_RNN {
-        constructor(args) {
-          if (args.implementation === 0) {
-            console.warn(
-              "`implementation=0` has been deprecated, and now defaults to " +
-                "`implementation=1`. Please update your layer call."
-            );
-          }
-          args.cell = new recurrent_GRUCell(args);
-          super(args);
-          // TODO(cais): Add activityRegularizer.
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            if (this.cell.dropoutMask != null) {
-              dist["dispose"](this.cell.dropoutMask);
-              this.cell.dropoutMask = null;
-            }
-            if (this.cell.recurrentDropoutMask != null) {
-              dist["dispose"](this.cell.recurrentDropoutMask);
-              this.cell.recurrentDropoutMask = null;
-            }
-            const mask = kwargs == null ? null : kwargs["mask"];
-            const training = kwargs == null ? null : kwargs["training"];
-            const initialState = kwargs == null ? null : kwargs["initialState"];
-            return super.call(inputs, { mask, training, initialState });
-          });
-        }
-        get units() {
-          return this.cell.units;
-        }
-        get activation() {
-          return this.cell.activation;
-        }
-        get recurrentActivation() {
-          return this.cell.recurrentActivation;
-        }
-        get useBias() {
-          return this.cell.useBias;
-        }
-        get kernelInitializer() {
-          return this.cell.kernelInitializer;
-        }
-        get recurrentInitializer() {
-          return this.cell.recurrentInitializer;
-        }
-        get biasInitializer() {
-          return this.cell.biasInitializer;
-        }
-        get kernelRegularizer() {
-          return this.cell.kernelRegularizer;
-        }
-        get recurrentRegularizer() {
-          return this.cell.recurrentRegularizer;
-        }
-        get biasRegularizer() {
-          return this.cell.biasRegularizer;
-        }
-        get kernelConstraint() {
-          return this.cell.kernelConstraint;
-        }
-        get recurrentConstraint() {
-          return this.cell.recurrentConstraint;
-        }
-        get biasConstraint() {
-          return this.cell.biasConstraint;
-        }
-        get dropout() {
-          return this.cell.dropout;
-        }
-        get recurrentDropout() {
-          return this.cell.recurrentDropout;
-        }
-        get implementation() {
-          return this.cell.implementation;
-        }
-        getConfig() {
-          const config = {
-            units: this.units,
-            activation: serializeActivation(this.activation),
-            recurrentActivation: serializeActivation(this.recurrentActivation),
-            useBias: this.useBias,
-            kernelInitializer: serializeInitializer(this.kernelInitializer),
-            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
-            biasInitializer: serializeInitializer(this.biasInitializer),
-            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
-            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
-            biasRegularizer: serializeRegularizer(this.biasRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            kernelConstraint: serializeConstraint(this.kernelConstraint),
-            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
-            biasConstraint: serializeConstraint(this.biasConstraint),
-            dropout: this.dropout,
-            recurrentDropout: this.recurrentDropout,
-            implementation: this.implementation,
-            resetAfter: false,
-          };
-          const baseConfig = super.getConfig();
-          delete baseConfig["cell"];
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          if (config["implmentation"] === 0) {
-            config["implementation"] = 1;
-          }
-          return new cls(config);
-        }
-      }
-      /** @nocollapse */
-      recurrent_GRU.className = "GRU";
-      dist["serialization"].registerClass(recurrent_GRU);
-      class recurrent_LSTMCell extends recurrent_RNNCell {
-        constructor(args) {
-          super(args);
-          this.DEFAULT_ACTIVATION = "tanh";
-          this.DEFAULT_RECURRENT_ACTIVATION = "hardSigmoid";
-          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
-          this.DEFAULT_RECURRENT_INITIALIZER = "orthogonal";
-          this.DEFAULT_BIAS_INITIALIZER = "zeros";
-          this.units = args.units;
-          assertPositiveInteger(this.units, "units");
-          this.activation = getActivation(
-            args.activation === undefined ? this.DEFAULT_ACTIVATION : args.activation
-          );
-          this.recurrentActivation = getActivation(
-            args.recurrentActivation === undefined
-              ? this.DEFAULT_RECURRENT_ACTIVATION
-              : args.recurrentActivation
-          );
-          this.useBias = args.useBias == null ? true : args.useBias;
-          this.kernelInitializer = getInitializer(
-            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
-          );
-          this.recurrentInitializer = getInitializer(
-            args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER
-          );
-          this.biasInitializer = getInitializer(
-            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
-          );
-          this.unitForgetBias = args.unitForgetBias;
-          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
-          this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);
-          this.biasRegularizer = getRegularizer(args.biasRegularizer);
-          this.kernelConstraint = getConstraint(args.kernelConstraint);
-          this.recurrentConstraint = getConstraint(args.recurrentConstraint);
-          this.biasConstraint = getConstraint(args.biasConstraint);
-          this.dropout = min([1, max([0, args.dropout == null ? 0 : args.dropout])]);
-          this.recurrentDropout = min([
-            1,
-            max([0, args.recurrentDropout == null ? 0 : args.recurrentDropout]),
-          ]);
-          this.implementation = args.implementation;
-          this.stateSize = [this.units, this.units];
-          this.dropoutMask = null;
-          this.recurrentDropoutMask = null;
-        }
-        build(inputShape) {
-          var _a;
-          inputShape = getExactlyOneShape(inputShape);
-          const inputDim = inputShape[inputShape.length - 1];
-          this.kernel = this.addWeight(
-            "kernel",
-            [inputDim, this.units * 4],
-            null,
-            this.kernelInitializer,
-            this.kernelRegularizer,
-            true,
-            this.kernelConstraint
-          );
-          this.recurrentKernel = this.addWeight(
-            "recurrent_kernel",
-            [this.units, this.units * 4],
-            null,
-            this.recurrentInitializer,
-            this.recurrentRegularizer,
-            true,
-            this.recurrentConstraint
-          );
-          let biasInitializer;
-          if (this.useBias) {
-            if (this.unitForgetBias) {
-              const capturedBiasInit = this.biasInitializer;
-              const capturedUnits = this.units;
-              biasInitializer = new ((_a = class CustomInit extends initializers_Initializer {
-                apply(shape, dtype) {
-                  // TODO(cais): More informative variable names?
-                  const bI = capturedBiasInit.apply([capturedUnits]);
-                  const bF = new initializers_Ones().apply([capturedUnits]);
-                  const bCAndH = capturedBiasInit.apply([capturedUnits * 2]);
-                  return concatAlongFirstAxis(concatAlongFirstAxis(bI, bF), bCAndH);
-                }
-              }),
-              /** @nocollapse */
-              (_a.className = "CustomInit"),
-              _a)();
-            } else {
-              biasInitializer = this.biasInitializer;
-            }
-            this.bias = this.addWeight(
-              "bias",
-              [this.units * 4],
-              null,
-              biasInitializer,
-              this.biasRegularizer,
-              true,
-              this.biasConstraint
-            );
-          } else {
-            this.bias = null;
-          }
-          // Porting Notes: Unlike the PyKeras implementation, we perform slicing
-          //   of the weights and bias in the call() method, at execution time.
-          this.built = true;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            const training = kwargs["training"] == null ? false : kwargs["training"];
-            inputs = inputs;
-            if (inputs.length !== 3) {
-              throw new ValueError(
-                `LSTMCell expects 3 input Tensors (inputs, h, c), got ` + `${inputs.length}.`
-              );
-            }
-            let hTMinus1 = inputs[1]; // Previous memory state.
-            const cTMinus1 = inputs[2]; // Previous carry state.
-            inputs = inputs[0];
-            if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {
-              this.dropoutMask = generateDropoutMask(
-                () => dist["onesLike"](inputs),
-                this.dropout,
-                training,
-                4
-              );
-            }
-            if (
-              0 < this.recurrentDropout &&
-              this.recurrentDropout < 1 &&
-              this.recurrentDropoutMask == null
-            ) {
-              this.recurrentDropoutMask = generateDropoutMask(
-                () => dist["onesLike"](hTMinus1),
-                this.recurrentDropout,
-                training,
-                4
-              );
-            }
-            const dpMask = this.dropoutMask;
-            const recDpMask = this.recurrentDropoutMask;
-            // Note: For superior performance, TensorFlow.js always uses
-            // implementation 2 regardless of the actual value of
-            // config.implementation.
-            let i;
-            let f;
-            let c;
-            let o;
-            if (0 < this.dropout && this.dropout < 1) {
-              inputs = dist["mul"](inputs, dpMask[0]);
-            }
-            let z = dot(inputs, this.kernel.read());
-            if (0 < this.recurrentDropout && this.recurrentDropout < 1) {
-              hTMinus1 = dist["mul"](hTMinus1, recDpMask[0]);
-            }
-            z = dist["add"](z, dot(hTMinus1, this.recurrentKernel.read()));
-            if (this.useBias) {
-              z = biasAdd(z, this.bias.read());
-            }
-            const [z0, z1, z2, z3] = dist["split"](z, 4, z.rank - 1);
-            i = this.recurrentActivation.apply(z0);
-            f = this.recurrentActivation.apply(z1);
-            c = dist["add"](dist["mul"](f, cTMinus1), dist["mul"](i, this.activation.apply(z2)));
-            o = this.recurrentActivation.apply(z3);
-            const h = dist["mul"](o, this.activation.apply(c));
-            // TODO(cais): Add use_learning_phase flag properly.
-            return [h, h, c];
-          });
-        }
-        getConfig() {
-          const config = {
-            units: this.units,
-            activation: serializeActivation(this.activation),
-            recurrentActivation: serializeActivation(this.recurrentActivation),
-            useBias: this.useBias,
-            kernelInitializer: serializeInitializer(this.kernelInitializer),
-            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
-            biasInitializer: serializeInitializer(this.biasInitializer),
-            unitForgetBias: this.unitForgetBias,
-            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
-            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
-            biasRegularizer: serializeRegularizer(this.biasRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            kernelConstraint: serializeConstraint(this.kernelConstraint),
-            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
-            biasConstraint: serializeConstraint(this.biasConstraint),
-            dropout: this.dropout,
-            recurrentDropout: this.recurrentDropout,
-            implementation: this.implementation,
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-      }
-      /** @nocollapse */
-      recurrent_LSTMCell.className = "LSTMCell";
-      dist["serialization"].registerClass(recurrent_LSTMCell);
-      class recurrent_LSTM extends recurrent_RNN {
-        constructor(args) {
-          if (args.implementation === 0) {
-            console.warn(
-              "`implementation=0` has been deprecated, and now defaults to " +
-                "`implementation=1`. Please update your layer call."
-            );
-          }
-          args.cell = new recurrent_LSTMCell(args);
-          super(args);
-          // TODO(cais): Add activityRegularizer.
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            if (this.cell.dropoutMask != null) {
-              dist["dispose"](this.cell.dropoutMask);
-              this.cell.dropoutMask = null;
-            }
-            if (this.cell.recurrentDropoutMask != null) {
-              dist["dispose"](this.cell.recurrentDropoutMask);
-              this.cell.recurrentDropoutMask = null;
-            }
-            const mask = kwargs == null ? null : kwargs["mask"];
-            const training = kwargs == null ? null : kwargs["training"];
-            const initialState = kwargs == null ? null : kwargs["initialState"];
-            return super.call(inputs, { mask, training, initialState });
-          });
-        }
-        get units() {
-          return this.cell.units;
-        }
-        get activation() {
-          return this.cell.activation;
-        }
-        get recurrentActivation() {
-          return this.cell.recurrentActivation;
-        }
-        get useBias() {
-          return this.cell.useBias;
-        }
-        get kernelInitializer() {
-          return this.cell.kernelInitializer;
-        }
-        get recurrentInitializer() {
-          return this.cell.recurrentInitializer;
-        }
-        get biasInitializer() {
-          return this.cell.biasInitializer;
-        }
-        get unitForgetBias() {
-          return this.cell.unitForgetBias;
-        }
-        get kernelRegularizer() {
-          return this.cell.kernelRegularizer;
-        }
-        get recurrentRegularizer() {
-          return this.cell.recurrentRegularizer;
-        }
-        get biasRegularizer() {
-          return this.cell.biasRegularizer;
-        }
-        get kernelConstraint() {
-          return this.cell.kernelConstraint;
-        }
-        get recurrentConstraint() {
-          return this.cell.recurrentConstraint;
-        }
-        get biasConstraint() {
-          return this.cell.biasConstraint;
-        }
-        get dropout() {
-          return this.cell.dropout;
-        }
-        get recurrentDropout() {
-          return this.cell.recurrentDropout;
-        }
-        get implementation() {
-          return this.cell.implementation;
-        }
-        getConfig() {
-          const config = {
-            units: this.units,
-            activation: serializeActivation(this.activation),
-            recurrentActivation: serializeActivation(this.recurrentActivation),
-            useBias: this.useBias,
-            kernelInitializer: serializeInitializer(this.kernelInitializer),
-            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
-            biasInitializer: serializeInitializer(this.biasInitializer),
-            unitForgetBias: this.unitForgetBias,
-            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
-            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
-            biasRegularizer: serializeRegularizer(this.biasRegularizer),
-            activityRegularizer: serializeRegularizer(this.activityRegularizer),
-            kernelConstraint: serializeConstraint(this.kernelConstraint),
-            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
-            biasConstraint: serializeConstraint(this.biasConstraint),
-            dropout: this.dropout,
-            recurrentDropout: this.recurrentDropout,
-            implementation: this.implementation,
-          };
-          const baseConfig = super.getConfig();
-          delete baseConfig["cell"];
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          if (config["implmentation"] === 0) {
-            config["implementation"] = 1;
-          }
-          return new cls(config);
-        }
-      }
-      /** @nocollapse */
-      recurrent_LSTM.className = "LSTM";
-      dist["serialization"].registerClass(recurrent_LSTM);
-      class recurrent_StackedRNNCells extends recurrent_RNNCell {
-        constructor(args) {
-          super(args);
-          this.cells = args.cells;
-        }
-        get stateSize() {
-          // States are a flat list in reverse order of the cell stack.
-          // This allows perserving the requirement `stack.statesize[0] ===
-          // outputDim`. E.g., states of a 2-layer LSTM would be `[h2, c2, h1, c1]`,
-          // assuming one LSTM has states `[h, c]`.
-          const stateSize = [];
-          for (const cell of this.cells.slice().reverse()) {
-            if (Array.isArray(cell.stateSize)) {
-              stateSize.push(...cell.stateSize);
-            } else {
-              stateSize.push(cell.stateSize);
-            }
-          }
-          return stateSize;
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            inputs = inputs;
-            let states = inputs.slice(1);
-            // Recover per-cell states.
-            const nestedStates = [];
-            for (const cell of this.cells.slice().reverse()) {
-              if (Array.isArray(cell.stateSize)) {
-                nestedStates.push(states.splice(0, cell.stateSize.length));
-              } else {
-                nestedStates.push(states.splice(0, 1));
-              }
-            }
-            nestedStates.reverse();
-            // Call the cells in order and store the returned states.
-            const newNestedStates = [];
-            let callInputs;
-            for (let i = 0; i < this.cells.length; ++i) {
-              const cell = this.cells[i];
-              states = nestedStates[i];
-              // TODO(cais): Take care of constants.
-              if (i === 0) {
-                callInputs = [inputs[0]].concat(states);
-              } else {
-                callInputs = [callInputs[0]].concat(states);
-              }
-              callInputs = cell.call(callInputs, kwargs);
-              newNestedStates.push(callInputs.slice(1));
-            }
-            // Format the new states as a flat list in reverse cell order.
-            states = [];
-            for (const cellStates of newNestedStates.slice().reverse()) {
-              states.push(...cellStates);
-            }
-            return [callInputs[0]].concat(states);
-          });
-        }
-        build(inputShape) {
-          if (isArrayOfShapes(inputShape)) {
-            // TODO(cais): Take care of input constants.
-            // const constantShape = inputShape.slice(1);
-            inputShape = inputShape[0];
-          }
-          inputShape = inputShape;
-          let outputDim;
-          this.cells.forEach((cell, i) => {
-            nameScope(`RNNCell_${i}`, () => {
-              // TODO(cais): Take care of input constants.
-              cell.build(inputShape);
-              if (Array.isArray(cell.stateSize)) {
-                outputDim = cell.stateSize[0];
-              } else {
-                outputDim = cell.stateSize;
-              }
-              inputShape = [inputShape[0], outputDim];
-            });
-          });
-          this.built = true;
-        }
-        getConfig() {
-          const cellConfigs = [];
-          for (const cell of this.cells) {
-            cellConfigs.push({
-              className: cell.getClassName(),
-              config: cell.getConfig(),
-            });
-          }
-          const config = { cells: cellConfigs };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config, customObjects = {}) {
-          const cells = [];
-          for (const cellConfig of config["cells"]) {
-            cells.push(deserialize(cellConfig, customObjects));
-          }
-          return new cls({ cells });
-        }
-        get trainableWeights() {
-          if (!this.trainable) {
-            return [];
-          }
-          const weights = [];
-          for (const cell of this.cells) {
-            weights.push(...cell.trainableWeights);
-          }
-          return weights;
-        }
-        get nonTrainableWeights() {
-          const weights = [];
-          for (const cell of this.cells) {
-            weights.push(...cell.nonTrainableWeights);
-          }
-          if (!this.trainable) {
-            const trainableWeights = [];
-            for (const cell of this.cells) {
-              trainableWeights.push(...cell.trainableWeights);
-            }
-            return trainableWeights.concat(weights);
-          }
-          return weights;
-        }
-        /**
-         * Retrieve the weights of a the model.
-         *
-         * @returns A flat `Array` of `tf.Tensor`s.
-         */
-        getWeights() {
-          const weights = [];
-          for (const cell of this.cells) {
-            weights.push(...cell.weights);
-          }
-          return batchGetValue(weights);
-        }
-        /**
-         * Set the weights of the model.
-         *
-         * @param weights An `Array` of `tf.Tensor`s with shapes and types matching
-         *     the output of `getWeights()`.
-         */
-        setWeights(weights) {
-          const tuples = [];
-          for (const cell of this.cells) {
-            const numParams = cell.weights.length;
-            const inputWeights = weights.splice(numParams);
-            for (let i = 0; i < cell.weights.length; ++i) {
-              tuples.push([cell.weights[i], inputWeights[i]]);
-            }
-          }
-          batchSetValue(tuples);
-        }
-      }
-      /** @nocollapse */
-      recurrent_StackedRNNCells.className = "StackedRNNCells";
-      dist["serialization"].registerClass(recurrent_StackedRNNCells);
-      function generateDropoutMask(ones, rate, training = null, count = 1) {
-        function droppedInputs() {
-          return dropout(ones(), rate);
-        }
-        if (count > 1) {
-          const mask = [];
-          for (let i = 0; i < count; i++) {
-            mask.push(inTrainPhase(droppedInputs, ones, training));
-          }
-          return mask.map((m) => dist["keep"](m.clone()));
-        } else {
-          return dist["keep"](inTrainPhase(droppedInputs, ones, training).clone());
-        }
-      }
-      //# sourceMappingURL=recurrent.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/wrappers.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /**
-       * Layers that augment the functionality of a base layer.
-       */
-
-      /**
-       * Abstract wrapper base class.
-       *
-       * Wrappers take another layer and augment it in various ways.
-       * Do not use this class as a layer, it is only an abstract base class.
-       * Two usable wrappers are the `TimeDistributed` and `Bidirectional` wrappers.
-       */
-      class wrappers_Wrapper extends topology_Layer {
-        constructor(args) {
-          // Porting Note: In PyKeras, `self.layer` is set prior to the calling
-          //   `super()`. But we can't do that here due to TypeScript's restriction.
-          //   See: https://github.com/Microsoft/TypeScript/issues/8277
-          //   As a result, we have to add checks in `get trainable()` and
-          //   `set trainable()` below in order to prevent using `this.layer` when
-          //   its value is `undefined`. The super constructor does use the getter
-          //   and the setter of `this.layer`.
-          super(args);
-          this.layer = args.layer;
-        }
-        build(inputShape) {
-          this.built = true;
-        }
-        // TODO(cais): Implement activityRegularizer getter.
-        get trainable() {
-          // Porting Note: the check of `this.layer` here is necessary due to the
-          //   way the `constructor` of this class is written (see Porting Note
-          //   above).
-          if (this.layer != null) {
-            return this.layer.trainable;
-          } else {
-            return false;
-          }
-        }
-        set trainable(value) {
-          // Porting Note: the check of `this.layer` here is necessary due to the
-          //   way the `constructor` of this class is written (see Porting Note
-          //   above).
-          if (this.layer != null) {
-            this.layer.trainable = value;
-          }
-        }
-        get trainableWeights() {
-          return this.layer.trainableWeights;
-        }
-        // TODO(cais): Implement setter for trainableWeights.
-        get nonTrainableWeights() {
-          return this.layer.nonTrainableWeights;
-        }
-        // TODO(cais): Implement setter for nonTrainableWeights.
-        get updates() {
-          // tslint:disable-next-line:no-any
-          return this.layer._updates;
-        }
-        // TODO(cais): Implement getUpdatesFor().
-        get losses() {
-          return this.layer.losses;
-        }
-        // TODO(cais): Implement getLossesFor().
-        getWeights() {
-          return this.layer.getWeights();
-        }
-        setWeights(weights) {
-          this.layer.setWeights(weights);
-        }
-        getConfig() {
-          const config = {
-            layer: {
-              className: this.layer.getClassName(),
-              config: this.layer.getConfig(),
-            },
-          };
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        setFastWeightInitDuringBuild(value) {
-          super.setFastWeightInitDuringBuild(value);
-          if (this.layer != null) {
-            this.layer.setFastWeightInitDuringBuild(value);
-          }
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config, customObjects = {}) {
-          const layerConfig = config["layer"];
-          const layer = deserialize(layerConfig, customObjects);
-          delete config["layer"];
-          const newConfig = { layer };
-          Object.assign(newConfig, config);
-          return new cls(newConfig);
-        }
-      }
-      class wrappers_TimeDistributed extends wrappers_Wrapper {
-        constructor(args) {
-          super(args);
-          this.supportsMasking = true;
-        }
-        build(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          if (inputShape.length < 3) {
-            throw new ValueError(
-              `TimeDistributed layer expects an input shape >= 3D, but received ` +
-                `input shape ${JSON.stringify(inputShape)}`
-            );
-          }
-          this.inputSpec = [{ shape: inputShape }];
-          const childInputShape = [inputShape[0]].concat(inputShape.slice(2));
-          if (!this.layer.built) {
-            this.layer.build(childInputShape);
-            this.layer.built = true;
-          }
-          super.build(inputShape);
-        }
-        computeOutputShape(inputShape) {
-          inputShape = getExactlyOneShape(inputShape);
-          const childInputShape = [inputShape[0]].concat(inputShape.slice(2));
-          const childOutputShape = this.layer.computeOutputShape(childInputShape);
-          const timesteps = inputShape[1];
-          return [childOutputShape[0], timesteps].concat(childOutputShape.slice(1));
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            // TODO(cais): Add 'training' and 'useLearningPhase' to kwargs.
-            inputs = getExactlyOneTensor(inputs);
-            // Porting Note: In tfjs-layers, `inputs` are always concrete tensor
-            // values. Hence the inputs can't have an undetermined first (batch)
-            // dimension, which is why we always use the K.rnn approach here.
-            const step = (inputs, states) => {
-              // TODO(cais): Add useLearningPhase.
-              // NOTE(cais): `layer.call` may return a length-1 array of Tensor in
-              //   some cases (e.g., `layer` is a `Sequential` instance), which is
-              //   why `getExactlyOneTensor` is used below.
-              const output = getExactlyOneTensor(this.layer.call(inputs, kwargs));
-              return [output, []];
-            };
-            const rnnOutputs = rnn(
-              step,
-              inputs,
-              [],
-              false /* goBackwards */,
-              null /* mask */,
-              null /* constants */,
-              false /* unroll */,
-              true /* needPerStepOutputs */
-            );
-            const y = rnnOutputs[1];
-            // TODO(cais): Add activity regularization.
-            // TODO(cais): Add useLearningPhase.
-            return y;
-          });
-        }
-      }
-      /** @nocollapse */
-      wrappers_TimeDistributed.className = "TimeDistributed";
-      dist["serialization"].registerClass(wrappers_TimeDistributed);
-      function checkBidirectionalMergeMode(value) {
-        checkStringTypeUnionValue(VALID_BIDIRECTIONAL_MERGE_MODES, "BidirectionalMergeMode", value);
-      }
-      const DEFAULT_BIDIRECTIONAL_MERGE_MODE = "concat";
-      class wrappers_Bidirectional extends wrappers_Wrapper {
-        constructor(args) {
-          super(args);
-          // Note: When creating `this.forwardLayer`, the original Layer object
-          //   (`config.layer`) ought to be cloned. This is why we call
-          //   `getConfig()` followed by `deserialize()`. Without this cloning,
-          //   the layer names saved during serialization will incorrectly contain
-          //   the 'forward_' prefix. In Python Keras, this is done using
-          //   `copy.copy` (shallow copy), which does not have a simple equivalent
-          //   in JavaScript. JavaScript's `Object.assign()` does not copy
-          //   methods.
-          const layerConfig = args.layer.getConfig();
-          const forwDict = {};
-          forwDict["className"] = args.layer.getClassName();
-          forwDict["config"] = layerConfig;
-          this.forwardLayer = deserialize(forwDict);
-          layerConfig["goBackwards"] = layerConfig["goBackwards"] === true ? false : true;
-          const backDict = {};
-          backDict["className"] = args.layer.getClassName();
-          backDict["config"] = layerConfig;
-          this.backwardLayer = deserialize(backDict);
-          this.forwardLayer.name = "forward_" + this.forwardLayer.name;
-          this.backwardLayer.name = "backward_" + this.backwardLayer.name;
-          this.mergeMode =
-            args.mergeMode === undefined ? DEFAULT_BIDIRECTIONAL_MERGE_MODE : args.mergeMode;
-          checkBidirectionalMergeMode(this.mergeMode);
-          if (args.weights) {
-            throw new NotImplementedError(
-              "weights support is not implemented for Bidirectional layer yet."
-            );
-          }
-          this._stateful = args.layer.stateful;
-          this.returnSequences = args.layer.returnSequences;
-          this.returnState = args.layer.returnState;
-          this.supportsMasking = true;
-          this._trainable = true;
-          this.inputSpec = args.layer.inputSpec;
-          this.numConstants = null;
-        }
-        get trainable() {
-          return this._trainable;
-        }
-        set trainable(value) {
-          // Porting Note: the check of `this.layer` here is necessary due to the
-          //   way the `constructor` of this class is written (see Porting Note
-          //   above).
-          this._trainable = value;
-          if (this.forwardLayer != null) {
-            this.forwardLayer.trainable = value;
-          }
-          if (this.backwardLayer != null) {
-            this.backwardLayer.trainable = value;
-          }
-        }
-        getWeights() {
-          return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights());
-        }
-        setWeights(weights) {
-          const numWeights = weights.length;
-          const numeightsOver2 = Math.floor(numWeights / 2);
-          this.forwardLayer.setWeights(weights.slice(0, numeightsOver2));
-          this.backwardLayer.setWeights(weights.slice(numeightsOver2));
-        }
-        computeOutputShape(inputShape) {
-          let layerShapes = this.forwardLayer.computeOutputShape(inputShape);
-          if (!(Array.isArray(layerShapes) && Array.isArray(layerShapes[0]))) {
-            layerShapes = [layerShapes];
-          }
-          layerShapes = layerShapes;
-          let outputShape;
-          let outputShapes;
-          let stateShape;
-          if (this.returnState) {
-            stateShape = layerShapes.slice(1);
-            outputShape = layerShapes[0];
-          } else {
-            outputShape = layerShapes[0];
-          }
-          outputShape = outputShape;
-          if (this.mergeMode === "concat") {
-            outputShape[outputShape.length - 1] *= 2;
-            outputShapes = [outputShape];
-          } else if (this.mergeMode == null) {
-            outputShapes = [outputShape, outputShape.slice()];
-          } else {
-            outputShapes = [outputShape];
-          }
-          if (this.returnState) {
-            if (this.mergeMode == null) {
-              return outputShapes.concat(stateShape).concat(stateShape.slice());
-            }
-            return [outputShape].concat(stateShape).concat(stateShape.slice());
-          }
-          return singletonOrArray(outputShapes);
-        }
-        apply(inputs, kwargs) {
-          let initialState = kwargs == null ? null : kwargs["initialState"];
-          let constants = kwargs == null ? null : kwargs["constants"];
-          if (kwargs == null) {
-            kwargs = {};
-          }
-          const standardized = standardizeArgs(inputs, initialState, constants, this.numConstants);
-          inputs = standardized.inputs;
-          initialState = standardized.initialState;
-          constants = standardized.constants;
-          if (Array.isArray(inputs)) {
-            initialState = inputs.slice(1);
-            inputs = inputs[0];
-          }
-          if ((initialState == null || initialState.length === 0) && constants == null) {
-            return super.apply(inputs, kwargs);
-          }
-          const additionalInputs = [];
-          const additionalSpecs = [];
-          if (initialState != null) {
-            const numStates = initialState.length;
-            if (numStates % 2 > 0) {
-              throw new ValueError(
-                "When passing `initialState` to a Bidrectional RNN, " +
-                  "the state should be an Array containing the states of " +
-                  "the underlying RNNs."
-              );
-            }
-            kwargs["initialState"] = initialState;
-            additionalInputs.push(...initialState);
-            const stateSpecs = initialState.map((state) => new InputSpec({ shape: state.shape }));
-            this.forwardLayer.stateSpec = stateSpecs.slice(0, numStates / 2);
-            this.backwardLayer.stateSpec = stateSpecs.slice(numStates / 2);
-            additionalSpecs.push(...stateSpecs);
-          }
-          if (constants != null) {
-            throw new NotImplementedError(
-              "Support for constants in Bidirectional layers is not " + "implemented yet."
-            );
-          }
-          const isSymbolicTensor = additionalInputs[0] instanceof topology_SymbolicTensor;
-          for (const tensor of additionalInputs) {
-            if (tensor instanceof topology_SymbolicTensor !== isSymbolicTensor) {
-              throw new ValueError(
-                "The initial state of a Bidirectional layer cannot be " +
-                  "specified as a mix of symbolic and non-symbolic tensors"
-              );
-            }
-          }
-          if (isSymbolicTensor) {
-            // Compute the full input and specs, including the states.
-            const fullInput = [inputs].concat(additionalInputs);
-            const fullInputSpec = this.inputSpec.concat(additionalSpecs);
-            // Perform the call temporarily and replace inputSpec.
-            // Note: with initial states symbolic calls and non-symbolic calls to
-            // this method differ in how the initial states are passed. For
-            // symbolic calls, the initial states are passed in the first arg, as
-            // an Array of SymbolicTensors; for non-symbolic calls, they are
-            // passed in the second arg as a part of the kwargs. Hence the need to
-            // temporarily modify inputSpec here.
-            // TODO(cais): Make refactoring so that this hacky code below is no
-            // longer needed.
-            const originalInputSpec = this.inputSpec;
-            this.inputSpec = fullInputSpec;
-            const output = super.apply(fullInput, kwargs);
-            this.inputSpec = originalInputSpec;
-            return output;
-          } else {
-            return super.apply(inputs, kwargs);
-          }
-        }
-        call(inputs, kwargs) {
-          return Object(dist["tidy"])(() => {
-            const initialState = kwargs["initialState"];
-            let y;
-            let yRev;
-            if (initialState == null) {
-              y = this.forwardLayer.call(inputs, kwargs);
-              yRev = this.backwardLayer.call(inputs, kwargs);
-            } else {
-              const forwardState = initialState.slice(0, initialState.length / 2);
-              const backwardState = initialState.slice(initialState.length / 2);
-              y = this.forwardLayer.call(
-                inputs,
-                Object.assign(kwargs, { initialState: forwardState })
-              );
-              yRev = this.backwardLayer.call(
-                inputs,
-                Object.assign(kwargs, { initialState: backwardState })
-              );
-            }
-            let states;
-            if (this.returnState) {
-              if (Array.isArray(y)) {
-                states = y.slice(1).concat(yRev.slice(1));
-              } else {
-              }
-              y = y[0];
-              yRev = yRev[0];
-            }
-            if (this.returnSequences) {
-              yRev = dist["reverse"](yRev, 1);
-            }
-            let output;
-            if (this.mergeMode === "concat") {
-              output = concatenate([y, yRev]);
-            } else if (this.mergeMode === "sum") {
-              output = dist["add"](y, yRev);
-            } else if (this.mergeMode === "ave") {
-              output = dist["mul"](0.5, dist["add"](y, yRev));
-            } else if (this.mergeMode === "mul") {
-              output = dist["mul"](y, yRev);
-            } else if (this.mergeMode == null) {
-              output = [y, yRev];
-            }
-            // TODO(cais): Properly set learning phase.
-            if (this.returnState) {
-              if (this.mergeMode == null) {
-                return output.concat(states);
-              }
-              return [output].concat(states);
-            }
-            return output;
-          });
-        }
-        resetStates(states) {
-          this.forwardLayer.resetStates();
-          this.backwardLayer.resetStates();
-        }
-        build(inputShape) {
-          nameScope(this.forwardLayer.name, () => {
-            this.forwardLayer.build(inputShape);
-          });
-          nameScope(this.backwardLayer.name, () => {
-            this.backwardLayer.build(inputShape);
-          });
-          this.built = true;
-        }
-        computeMask(inputs, mask) {
-          if (Array.isArray(mask)) {
-            mask = mask[0];
-          }
-          let outputMask;
-          if (this.returnSequences) {
-            if (this.mergeMode == null) {
-              outputMask = [mask, mask];
-            } else {
-              outputMask = mask;
-            }
-          } else {
-            if (this.mergeMode == null) {
-              outputMask = [null, null];
-            } else {
-              outputMask = null;
-            }
-          }
-          if (this.returnState) {
-            const states = this.forwardLayer.states;
-            const stateMask = states.map((state) => null);
-            if (Array.isArray(outputMask)) {
-              return outputMask.concat(stateMask).concat(stateMask);
-            } else {
-              return [outputMask].concat(stateMask).concat(stateMask);
-            }
-          } else {
-            return outputMask;
-          }
-        }
-        get trainableWeights() {
-          return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights);
-        }
-        get nonTrainableWeights() {
-          return this.forwardLayer.nonTrainableWeights.concat(
-            this.backwardLayer.nonTrainableWeights
-          );
-        }
-        // TODO(cais): Implement constraints().
-        setFastWeightInitDuringBuild(value) {
-          super.setFastWeightInitDuringBuild(value);
-          if (this.forwardLayer != null) {
-            this.forwardLayer.setFastWeightInitDuringBuild(value);
-          }
-          if (this.backwardLayer != null) {
-            this.backwardLayer.setFastWeightInitDuringBuild(value);
-          }
-        }
-        getConfig() {
-          const config = {
-            mergeMode: this.mergeMode,
-          };
-          // TODO(cais): Add logic for `numConstants` once the property is added.
-          const baseConfig = super.getConfig();
-          Object.assign(config, baseConfig);
-          return config;
-        }
-        /** @nocollapse */
-        static fromConfig(cls, config) {
-          const rnnLayer = deserialize(config["layer"]);
-          delete config["layer"];
-          // TODO(cais): Add logic for `numConstants` once the property is added.
-          if (config["numConstants"] != null) {
-            throw new NotImplementedError(
-              `Deserialization of a Bidirectional layer with numConstants ` +
-                `present is not supported yet.`
-            );
-          }
-          // tslint:disable-next-line:no-any
-          const newConfig = config;
-          newConfig["layer"] = rnnLayer;
-          return new cls(newConfig);
-        }
-      }
-      /** @nocollapse */
-      wrappers_Bidirectional.className = "Bidirectional";
-      dist["serialization"].registerClass(wrappers_Bidirectional);
-      //# sourceMappingURL=wrappers.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_layers.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      // TODO(cais): Add doc string to all the public static functions in this
-      //   class; include exectuable JavaScript code snippets where applicable
-      //   (b/74074458).
-      // Input Layer.
-      /**
-       * An input layer is an entry point into a `tf.LayersModel`.
-       *
-       * `InputLayer` is generated automatically for `tf.Sequential`` models by
-       * specifying the `inputshape` or `batchInputShape` for the first layer.  It
-       * should not be specified explicitly. However, it can be useful sometimes,
-       * e.g., when constructing a sequential model from a subset of another
-       * sequential model's layers. Like the code snippet below shows.
-       *
-       * ```js
-       * // Define a model which simply adds two inputs.
-       * const model1 = tf.sequential();
-       * model1.add(tf.layers.dense({inputShape: [4], units: 3, activation: 'relu'}));
-       * model1.add(tf.layers.dense({units: 1, activation: 'sigmoid'}));
-       * model1.summary();
-       * model1.predict(tf.zeros([1, 4])).print();
-       *
-       * // Construct another model, reusing the second layer of `model1` while
-       * // not using the first layer of `model1`. Note that you cannot add the second
-       * // layer of `model` directly as the first layer of the new sequential model,
-       * // because doing so will lead to an error related to the fact that the layer
-       * // is not an input layer. Instead, you need to create an `inputLayer` and add
-       * // it to the new sequential model before adding the reused layer.
-       * const model2 = tf.sequential();
-       * // Use an inputShape that matches the input shape of `model1`'s second
-       * // layer.
-       * model2.add(tf.layers.inputLayer({inputShape: [3]}));
-       * model2.add(model1.layers[1]);
-       * model2.summary();
-       * model2.predict(tf.zeros([1, 3])).print();
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Inputs', namespace: 'layers'} */
-      function exports_layers_inputLayer(args) {
-        return new input_layer_InputLayer(args);
-      }
-      // Advanced Activation Layers.
-      /**
-       * Exponetial Linear Unit (ELU).
-       *
-       * It follows:
-       * `f(x) =  alpha * (exp(x) - 1.) for x < 0`,
-       * `f(x) = x for x >= 0`.
-       *
-       * Input shape:
-       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
-       *   first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as the input.
-       *
-       * References:
-       *   - [Fast and Accurate Deep Network Learning by Exponential Linear Units
-       * (ELUs)](https://arxiv.org/abs/1511.07289v1)
-       */
-      /**
-       * @doc {
-       *   heading: 'Layers',
-       *   subheading: 'Advanced Activation',
-       *   namespace: 'layers'
-       * }
-       */
-      function exports_layers_elu(args) {
-        return new advanced_activations_ELU(args);
-      }
-      /**
-       * Rectified Linear Unit activation function.
-       *
-       * Input shape:
-       *   Arbitrary. Use the config field `inputShape` (Array of integers, does
-       *   not include the sample axis) when using this layer as the first layer
-       *   in a model.
-       *
-       * Output shape:
-       *   Same shape as the input.
-       */
-      /**
-       * @doc {
-       *   heading: 'Layers',
-       *   subheading: 'Advanced Activation',
-       *   namespace: 'layers'
-       * }
-       */
-      function reLU(args) {
-        return new advanced_activations_ReLU(args);
-      }
-      /**
-       * Leaky version of a rectified linear unit.
-       *
-       * It allows a small gradient when the unit is not active:
-       * `f(x) = alpha * x for x < 0.`
-       * `f(x) = x for x >= 0.`
-       *
-       * Input shape:
-       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
-       *   first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as the input.
-       */
-      /**
-       * @doc {
-       *   heading: 'Layers',
-       *   subheading: 'Advanced Activation',
-       *   namespace: 'layers'
-       * }
-       */
-      function leakyReLU(args) {
-        return new advanced_activations_LeakyReLU(args);
-      }
-      /**
-       * Parameterized version of a leaky rectified linear unit.
-       *
-       * It follows
-       * `f(x) = alpha * x for x < 0.`
-       * `f(x) = x for x >= 0.`
-       * wherein `alpha` is a trainable weight.
-       *
-       * Input shape:
-       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
-       *   first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as the input.
-       */
-      /**
-       * @doc {
-       *   heading: 'Layers',
-       *   subheading: 'Advanced Activation',
-       *   namespace: 'layers'
-       * }
-       */
-      function prelu(args) {
-        return new advanced_activations_PReLU(args);
-      }
-      /**
-       * Softmax activation layer.
-       *
-       * Input shape:
-       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
-       *   first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as the input.
-       */
-      /**
-       * @doc {
-       *   heading: 'Layers',
-       *   subheading: 'Advanced Activation',
-       *   namespace: 'layers'
-       * }
-       */
-      function softmax(args) {
-        return new advanced_activations_Softmax(args);
-      }
-      /**
-       * Thresholded Rectified Linear Unit.
-       *
-       * It follows:
-       * `f(x) = x for x > theta`,
-       * `f(x) = 0 otherwise`.
-       *
-       * Input shape:
-       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
-       *   first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as the input.
-       *
-       * References:
-       *   - [Zero-Bias Autoencoders and the Benefits of Co-Adapting
-       * Features](http://arxiv.org/abs/1402.3337)
-       */
-      /**
-       * @doc {
-       *   heading: 'Layers',
-       *   subheading: 'Advanced Activation',
-       *   namespace: 'layers'
-       * }
-       */
-      function thresholdedReLU(args) {
-        return new advanced_activations_ThresholdedReLU(args);
-      }
-      // Convolutional Layers.
-      /**
-       * 1D convolution layer (e.g., temporal convolution).
-       *
-       * This layer creates a convolution kernel that is convolved
-       * with the layer input over a single spatial (or temporal) dimension
-       * to produce a tensor of outputs.
-       *
-       * If `use_bias` is True, a bias vector is created and added to the outputs.
-       *
-       * If `activation` is not `null`, it is applied to the outputs as well.
-       *
-       * When using this layer as the first layer in a model, provide an
-       * `inputShape` argument `Array` or `null`.
-       *
-       * For example, `inputShape` would be:
-       * - `[10, 128]` for sequences of 10 vectors of 128-dimensional vectors
-       * - `[null, 128]` for variable-length sequences of 128-dimensional vectors.
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Convolutional',  namespace: 'layers'}
-       */
-      function exports_layers_conv1d(args) {
-        return new convolutional_Conv1D(args);
-      }
-      /**
-       * 2D convolution layer (e.g. spatial convolution over images).
-       *
-       * This layer creates a convolution kernel that is convolved
-       * with the layer input to produce a tensor of outputs.
-       *
-       * If `useBias` is True, a bias vector is created and added to the outputs.
-       *
-       * If `activation` is not `null`, it is applied to the outputs as well.
-       *
-       * When using this layer as the first layer in a model,
-       * provide the keyword argument `inputShape`
-       * (Array of integers, does not include the sample axis),
-       * e.g. `inputShape=[128, 128, 3]` for 128x128 RGB pictures
-       * in `dataFormat='channelsLast'`.
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
-       */
-      function exports_layers_conv2d(args) {
-        return new convolutional_Conv2D(args);
-      }
-      /**
-       * Transposed convolutional layer (sometimes called Deconvolution).
-       *
-       * The need for transposed convolutions generally arises
-       * from the desire to use a transformation going in the opposite direction of
-       * a normal convolution, i.e., from something that has the shape of the output
-       * of some convolution to something that has the shape of its input while
-       * maintaining a connectivity pattern that is compatible with said
-       * convolution.
-       *
-       * When using this layer as the first layer in a model, provide the
-       * configuration `inputShape` (`Array` of integers, does not include the
-       * sample axis), e.g., `inputShape: [128, 128, 3]` for 128x128 RGB pictures in
-       * `dataFormat: 'channelsLast'`.
-       *
-       * Input shape:
-       *   4D tensor with shape:
-       *   `[batch, channels, rows, cols]` if `dataFormat` is `'channelsFirst'`.
-       *   or 4D tensor with shape
-       *   `[batch, rows, cols, channels]` if `dataFormat` is `'channelsLast`.
-       *
-       * Output shape:
-       *   4D tensor with shape:
-       *   `[batch, filters, newRows, newCols]` if `dataFormat` is
-       * `'channelsFirst'`. or 4D tensor with shape:
-       *   `[batch, newRows, newCols, filters]` if `dataFormat` is `'channelsLast'`.
-       *
-       * References:
-       *   - [A guide to convolution arithmetic for deep
-       * learning](https://arxiv.org/abs/1603.07285v1)
-       *   - [Deconvolutional
-       * Networks](http://www.matthewzeiler.com/pubs/cvpr2010/cvpr2010.pdf)
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
-       */
-      function conv2dTranspose(args) {
-        return new convolutional_Conv2DTranspose(args);
-      }
-      /**
-       * 3D convolution layer (e.g. spatial convolution over volumes).
-       *
-       * This layer creates a convolution kernel that is convolved
-       * with the layer input to produce a tensor of outputs.
-       *
-       * If `useBias` is True, a bias vector is created and added to the outputs.
-       *
-       * If `activation` is not `null`, it is applied to the outputs as well.
-       *
-       * When using this layer as the first layer in a model,
-       * provide the keyword argument `inputShape`
-       * (Array of integers, does not include the sample axis),
-       * e.g. `inputShape=[128, 128, 128, 1]` for 128x128x128 grayscale volumes
-       * in `dataFormat='channelsLast'`.
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
-       */
-      function exports_layers_conv3d(args) {
-        return new convolutional_Conv3D(args);
-      }
-      /**
-       * Depthwise separable 2D convolution.
-       *
-       * Separable convolution consists of first performing
-       * a depthwise spatial convolution
-       * (which acts on each input channel separately)
-       * followed by a pointwise convolution which mixes together the resulting
-       * output channels. The `depthMultiplier` argument controls how many
-       * output channels are generated per input channel in the depthwise step.
-       *
-       * Intuitively, separable convolutions can be understood as
-       * a way to factorize a convolution kernel into two smaller kernels,
-       * or as an extreme version of an Inception block.
-       *
-       * Input shape:
-       *   4D tensor with shape:
-       *     `[batch, channels, rows, cols]` if data_format='channelsFirst'
-       *   or 4D tensor with shape:
-       *     `[batch, rows, cols, channels]` if data_format='channelsLast'.
-       *
-       * Output shape:
-       *   4D tensor with shape:
-       *     `[batch, filters, newRows, newCols]` if data_format='channelsFirst'
-       *   or 4D tensor with shape:
-       *     `[batch, newRows, newCols, filters]` if data_format='channelsLast'.
-       *     `rows` and `cols` values might have changed due to padding.
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
-       */
-      function separableConv2d(args) {
-        return new SeparableConv2D(args);
-      }
-      /**
-       * Cropping layer for 2D input (e.g., image).
-       *
-       * This layer can crop an input
-       * at the top, bottom, left and right side of an image tensor.
-       *
-       * Input shape:
-       *   4D tensor with shape:
-       *   - If `dataFormat` is `"channelsLast"`:
-       *     `[batch, rows, cols, channels]`
-       *   - If `data_format` is `"channels_first"`:
-       *     `[batch, channels, rows, cols]`.
-       *
-       * Output shape:
-       *   4D with shape:
-       *   - If `dataFormat` is `"channelsLast"`:
-       *     `[batch, croppedRows, croppedCols, channels]`
-       *    - If `dataFormat` is `"channelsFirst"`:
-       *     `[batch, channels, croppedRows, croppedCols]`.
-       *
-       * Examples
-       * ```js
-       *
-       * const model = tf.sequential();
-       * model.add(tf.layers.cropping2D({cropping:[[2, 2], [2, 2]],
-       *                                inputShape: [128, 128, 3]}));
-       * //now output shape is [batch, 124, 124, 3]
-       * ```
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
-       */
-      function cropping2D(args) {
-        return new convolutional_Cropping2D(args);
-      }
-      /**
-       * Upsampling layer for 2D inputs.
-       *
-       * Repeats the rows and columns of the data
-       * by size[0] and size[1] respectively.
-       *
-       *
-       * Input shape:
-       *    4D tensor with shape:
-       *     - If `dataFormat` is `"channelsLast"`:
-       *         `[batch, rows, cols, channels]`
-       *     - If `dataFormat` is `"channelsFirst"`:
-       *        `[batch, channels, rows, cols]`
-       *
-       * Output shape:
-       *     4D tensor with shape:
-       *     - If `dataFormat` is `"channelsLast"`:
-       *        `[batch, upsampledRows, upsampledCols, channels]`
-       *     - If `dataFormat` is `"channelsFirst"`:
-       *         `[batch, channels, upsampledRows, upsampledCols]`
-       *
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
-       */
-      function upSampling2d(args) {
-        return new convolutional_UpSampling2D(args);
-      }
-      // Convolutional(depthwise) Layers.
-      /**
-       * Depthwise separable 2D convolution.
-       *
-       * Depthwise Separable convolutions consists in performing just the first step
-       * in a depthwise spatial convolution (which acts on each input channel
-       * separately). The `depthMultplier` argument controls how many output channels
-       * are generated per input channel in the depthwise step.
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
-       */
-      function exports_layers_depthwiseConv2d(args) {
-        return new convolutional_depthwise_DepthwiseConv2D(args);
-      }
-      // Basic Layers.
-      /**
-       * Applies an activation function to an output.
-       *
-       * This layer applies element-wise activation function.  Other layers, notably
-       * `dense` can also apply activation functions.  Use this isolated activation
-       * function to extract the values before and after the
-       * activation. For instance:
-       *
-       * ```js
-       * const input = tf.input({shape: [5]});
-       * const denseLayer = tf.layers.dense({units: 1});
-       * const activationLayer = tf.layers.activation({activation: 'relu6'});
-       *
-       * // Obtain the output symbolic tensors by applying the layers in order.
-       * const denseOutput = denseLayer.apply(input);
-       * const activationOutput = activationLayer.apply(denseOutput);
-       *
-       * // Create the model based on the inputs.
-       * const model = tf.model({
-       *     inputs: input,
-       *     outputs: [denseOutput, activationOutput]
-       * });
-       *
-       * // Collect both outputs and print separately.
-       * const [denseOut, activationOut] = model.predict(tf.randomNormal([6, 5]));
-       * denseOut.print();
-       * activationOut.print();
-       * ```
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'}
-       */
-      function exports_layers_activation(args) {
-        return new core_Activation(args);
-      }
-      /**
-       * Creates a dense (fully connected) layer.
-       *
-       * This layer implements the operation:
-       *   `output = activation(dot(input, kernel) + bias)`
-       *
-       * `activation` is the element-wise activation function
-       *   passed as the `activation` argument.
-       *
-       * `kernel` is a weights matrix created by the layer.
-       *
-       * `bias` is a bias vector created by the layer (only applicable if `useBias`
-       * is `true`).
-       *
-       * **Input shape:**
-       *
-       *   nD `tf.Tensor` with shape: `(batchSize, ..., inputDim)`.
-       *
-       *   The most common situation would be
-       *   a 2D input with shape `(batchSize, inputDim)`.
-       *
-       * **Output shape:**
-       *
-       *   nD tensor with shape: `(batchSize, ..., units)`.
-       *
-       *   For instance, for a 2D input with shape `(batchSize, inputDim)`,
-       *   the output would have shape `(batchSize, units)`.
-       *
-       * Note: if the input to the layer has a rank greater than 2, then it is
-       * flattened prior to the initial dot product with the kernel.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
-      function dense(args) {
-        return new core_Dense(args);
-      }
-      /**
-       * Applies
-       * [dropout](http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf) to
-       * the input.
-       *
-       * Dropout consists in randomly setting a fraction `rate` of input units to 0 at
-       * each update during training time, which helps prevent overfitting.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
-      function exports_layers_dropout(args) {
-        return new core_Dropout(args);
-      }
-      /**
-       * Spatial 1D version of Dropout.
-       *
-       * This Layer type performs the same function as the Dropout layer, but it drops
-       * entire 1D feature maps instead of individual elements. For example, if an
-       * input example consists of 3 timesteps and the feature map for each timestep
-       * has a size of 4, a `spatialDropout1d` layer may zero out the feature maps
-       * of the 1st timesteps and 2nd timesteps completely while sparing all feature
-       * elements of the 3rd timestep.
-       *
-       * If adjacent frames (timesteps) are strongly correlated (as is normally the
-       * case in early convolution layers), regular dropout will not regularize the
-       * activation and will otherwise just result in merely an effective learning
-       * rate decrease. In this case, `spatialDropout1d` will help promote
-       * independence among feature maps and should be used instead.
-       *
-       * **Arguments:**
-       *   rate: A floating-point number >=0 and <=1. Fraction of the input elements
-       *     to drop.
-       *
-       * **Input shape:**
-       *   3D tensor with shape `(samples, timesteps, channels)`.
-       *
-       * **Output shape:**
-       *   Same as the input shape.
-       *
-       * References:
-       *   - [Efficient Object Localization Using Convolutional
-       *      Networks](https://arxiv.org/abs/1411.4280)
-       */
-      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
-      function spatialDropout1d(args) {
-        return new SpatialDropout1D(args);
-      }
-      /**
-       * Flattens the input. Does not affect the batch size.
-       *
-       * A `Flatten` layer flattens each batch in its inputs to 1D (making the output
-       * 2D).
-       *
-       * For example:
-       *
-       * ```js
-       * const input = tf.input({shape: [4, 3]});
-       * const flattenLayer = tf.layers.flatten();
-       * // Inspect the inferred output shape of the flatten layer, which
-       * // equals `[null, 12]`. The 2nd dimension is 4 * 3, i.e., the result of the
-       * // flattening. (The 1st dimension is the undermined batch size.)
-       * console.log(JSON.stringify(flattenLayer.apply(input).shape));
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
-      function exports_layers_flatten(args) {
-        return new core_Flatten(args);
-      }
-      /**
-       * Repeats the input n times in a new dimension.
-       *
-       * ```js
-       *  const model = tf.sequential();
-       *  model.add(tf.layers.repeatVector({n: 4, inputShape: [2]}));
-       *  const x = tf.tensor2d([[10, 20]]);
-       *  // Use the model to do inference on a data point the model hasn't see
-       *  model.predict(x).print();
-       *  // output shape is now [batch, 2, 4]
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
-      function repeatVector(args) {
-        return new core_RepeatVector(args);
-      }
-      /**
-       * Reshapes an input to a certain shape.
-       *
-       * ```js
-       * const input = tf.input({shape: [4, 3]});
-       * const reshapeLayer = tf.layers.reshape({targetShape: [2, 6]});
-       * // Inspect the inferred output shape of the Reshape layer, which
-       * // equals `[null, 2, 6]`. (The 1st dimension is the undermined batch size.)
-       * console.log(JSON.stringify(reshapeLayer.apply(input).shape));
-       * ```
-       *
-       * Input shape:
-       *   Arbitrary, although all dimensions in the input shape must be fixed.
-       *   Use the configuration `inputShape` when using this layer as the
-       *   first layer in a model.
-       *
-       *
-       * Output shape:
-       *   [batchSize, targetShape[0], targetShape[1], ...,
-       *    targetShape[targetShape.length - 1]].
-       */
-      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
-      function reshape(args) {
-        return new core_Reshape(args);
-      }
-      /**
-       * Permutes the dimensions of the input according to a given pattern.
-       *
-       * Useful for, e.g., connecting RNNs and convnets together.
-       *
-       * Example:
-       *
-       * ```js
-       * const model = tf.sequential();
-       * model.add(tf.layers.permute({
-       *   dims: [2, 1],
-       *   inputShape: [10, 64]
-       * }));
-       * console.log(model.outputShape);
-       * // Now model's output shape is [null, 64, 10], where null is the
-       * // unpermuted sample (batch) dimension.
-       * ```
-       *
-       * Input shape:
-       *   Arbitrary. Use the configuration field `inputShape` when using this
-       *   layer as the first layer in a model.
-       *
-       * Output shape:
-       *   Same rank as the input shape, but with the dimensions re-ordered (i.e.,
-       *   permuted) according to the `dims` configuration of this layer.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
-      function permute(args) {
-        return new core_Permute(args);
-      }
-      /**
-       * Maps positive integers (indices) into dense vectors of fixed size.
-       * eg. [[4], [20]] -> [[0.25, 0.1], [0.6, -0.2]]
-       *
-       * **Input shape:** 2D tensor with shape: `[batchSize, sequenceLength]`.
-       *
-       * **Output shape:** 3D tensor with shape: `[batchSize, sequenceLength,
-       * outputDim]`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
-      function embedding(args) {
-        return new embeddings_Embedding(args);
-      }
-      // Merge Layers.
-      /**
-       * Layer that performs element-wise addition on an `Array` of inputs.
-       *
-       * It takes as input a list of tensors, all of the same shape, and returns a
-       * single tensor (also of the same shape). The inputs are specified as an
-       * `Array` when the `apply` method of the `Add` layer instance is called. For
-       * example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const addLayer = tf.layers.add();
-       * const sum = addLayer.apply([input1, input2]);
-       * console.log(JSON.stringify(sum.shape));
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
-      function exports_layers_add(args) {
-        return new merge_Add(args);
-      }
-      /**
-       * Layer that performs element-wise averaging on an `Array` of inputs.
-       *
-       * It takes as input a list of tensors, all of the same shape, and returns a
-       * single tensor (also of the same shape). For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const averageLayer = tf.layers.average();
-       * const average = averageLayer.apply([input1, input2]);
-       * console.log(JSON.stringify(average.shape));
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
-      function exports_layers_average(args) {
-        return new merge_Average(args);
-      }
-      /**
-       * Layer that concatenates an `Array` of inputs.
-       *
-       * It takes a list of tensors, all of the same shape except for the
-       * concatenation axis, and returns a single tensor, the concatenation
-       * of all inputs. For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 3]});
-       * const concatLayer = tf.layers.concatenate();
-       * const output = concatLayer.apply([input1, input2]);
-       * console.log(JSON.stringify(output.shape));
-       * // You get [null, 2, 5], with the first dimension as the undetermined batch
-       * // dimension. The last dimension (5) is the result of concatenating the
-       * // last dimensions of the inputs (2 and 3).
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
-      function exports_layers_concatenate(args) {
-        return new merge_Concatenate(args);
-      }
-      /**
-       * Layer that computes the element-wise maximum an `Array` of inputs.
-       *
-       * It takes as input a list of tensors, all of the same shape and returns a
-       * single tensor (also of the same shape). For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const maxLayer = tf.layers.maximum();
-       * const max = maxLayer.apply([input1, input2]);
-       * console.log(JSON.stringify(max.shape));
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
-      function exports_layers_maximum(args) {
-        return new merge_Maximum(args);
-      }
-      /**
-       * Layer that computes the element-wise minimum of an `Array` of inputs.
-       *
-       * It takes as input a list of tensors, all of the same shape and returns a
-       * single tensor (also of the same shape). For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const minLayer = tf.layers.minimum();
-       * const min = minLayer.apply([input1, input2]);
-       * console.log(JSON.stringify(min.shape));
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
-      function exports_layers_minimum(args) {
-        return new merge_Minimum(args);
-      }
-      /**
-       * Layer that multiplies (element-wise) an `Array` of inputs.
-       *
-       * It takes as input an Array of tensors, all of the same
-       * shape, and returns a single tensor (also of the same shape).
-       * For example:
-       *
-       * ```js
-       * const input1 = tf.input({shape: [2, 2]});
-       * const input2 = tf.input({shape: [2, 2]});
-       * const input3 = tf.input({shape: [2, 2]});
-       * const multiplyLayer = tf.layers.multiply();
-       * const product = multiplyLayer.apply([input1, input2, input3]);
-       * console.log(product.shape);
-       * // You get [null, 2, 2], with the first dimension as the undetermined batch
-       * // dimension.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
-      function exports_layers_multiply(args) {
-        return new merge_Multiply(args);
-      }
-      /**
-       * Layer that computes a dot product between samples in two tensors.
-       *
-       * E.g., if applied to a list of two tensors `a` and `b` both of shape
-       * `[batchSize, n]`, the output will be a tensor of shape `[batchSize, 1]`,
-       * where each entry at index `[i, 0]` will be the dot product between
-       * `a[i, :]` and `b[i, :]`.
-       *
-       * Example:
-       *
-       * ```js
-       * const dotLayer = tf.layers.dot({axes: -1});
-       * const x1 = tf.tensor2d([[10, 20], [30, 40]]);
-       * const x2 = tf.tensor2d([[-1, -2], [-3, -4]]);
-       *
-       * // Invoke the layer's apply() method in eager (imperative) mode.
-       * const y = dotLayer.apply([x1, x2]);
-       * y.print();
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
-      function exports_layers_dot(args) {
-        return new merge_Dot(args);
-      }
-      // Normalization Layers.
-      /**
-       * Batch normalization layer (Ioffe and Szegedy, 2014).
-       *
-       * Normalize the activations of the previous layer at each batch,
-       * i.e. applies a transformation that maintains the mean activation
-       * close to 0 and the activation standard deviation close to 1.
-       *
-       * Input shape:
-       *   Arbitrary. Use the keyword argument `inputShape` (Array of integers, does
-       *   not include the sample axis) when calling the constructor of this class,
-       *   if this layer is used as a first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as input.
-       *
-       * References:
-       *   - [Batch Normalization: Accelerating Deep Network Training by Reducing
-       * Internal Covariate Shift](https://arxiv.org/abs/1502.03167)
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Normalization', namespace: 'layers'}
-       */
-      function exports_layers_batchNormalization(args) {
-        return new normalization_BatchNormalization(args);
-      }
-      /**
-       * Layer-normalization layer (Ba et al., 2016).
-       *
-       * Normalizes the activations of the previous layer for each given example in a
-       * batch independently, instead of across a batch like in `batchNormalization`.
-       * In other words, this layer applies a transformation that maintanis the mean
-       * activation within each example close to0 and activation variance close to 1.
-       *
-       * Input shape:
-       *   Arbitrary. Use the argument `inputShape` when using this layer as the first
-       *   layer in a model.
-       *
-       * Output shape:
-       *   Same as input.
-       *
-       * References:
-       *   - [Layer Normalization](https://arxiv.org/abs/1607.06450)
-       */
-      /**
-       * @doc {heading: 'Layers', subheading: 'Normalization', namespace: 'layers'}
-       */
-      function layerNormalization(args) {
-        return new normalization_LayerNormalization(args);
-      }
-      // Padding Layers.
-      /**
-       * Zero-padding layer for 2D input (e.g., image).
-       *
-       * This layer can add rows and columns of zeros
-       * at the top, bottom, left and right side of an image tensor.
-       *
-       * Input shape:
-       *   4D tensor with shape:
-       *   - If `dataFormat` is `"channelsLast"`:
-       *     `[batch, rows, cols, channels]`
-       *   - If `data_format` is `"channels_first"`:
-       *     `[batch, channels, rows, cols]`.
-       *
-       * Output shape:
-       *   4D with shape:
-       *   - If `dataFormat` is `"channelsLast"`:
-       *     `[batch, paddedRows, paddedCols, channels]`
-       *    - If `dataFormat` is `"channelsFirst"`:
-       *     `[batch, channels, paddedRows, paddedCols]`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Padding', namespace: 'layers'} */
-      function zeroPadding2d(args) {
-        return new padding_ZeroPadding2D(args);
-      }
-      // Pooling Layers.
-      /**
-       * Average pooling operation for spatial data.
-       *
-       * Input shape: `[batchSize, inLength, channels]`
-       *
-       * Output shape: `[batchSize, pooledLength, channels]`
-       *
-       * `tf.avgPool1d` is an alias.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function averagePooling1d(args) {
-        return new pooling_AveragePooling1D(args);
-      }
-      function avgPool1d(args) {
-        return averagePooling1d(args);
-      }
-      // For backwards compatibility.
-      // See https://github.com/tensorflow/tfjs/issues/152
-      function avgPooling1d(args) {
-        return averagePooling1d(args);
-      }
-      /**
-       * Average pooling operation for spatial data.
-       *
-       * Input shape:
-       *  - If `dataFormat === CHANNEL_LAST`:
-       *      4D tensor with shape:
-       *      `[batchSize, rows, cols, channels]`
-       *  - If `dataFormat === CHANNEL_FIRST`:
-       *      4D tensor with shape:
-       *      `[batchSize, channels, rows, cols]`
-       *
-       * Output shape
-       *  - If `dataFormat === CHANNEL_LAST`:
-       *      4D tensor with shape:
-       *      `[batchSize, pooleRows, pooledCols, channels]`
-       *  - If `dataFormat === CHANNEL_FIRST`:
-       *      4D tensor with shape:
-       *      `[batchSize, channels, pooleRows, pooledCols]`
-       *
-       * `tf.avgPool2d` is an alias.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function averagePooling2d(args) {
-        return new pooling_AveragePooling2D(args);
-      }
-      function avgPool2d(args) {
-        return averagePooling2d(args);
-      }
-      // For backwards compatibility.
-      // See https://github.com/tensorflow/tfjs/issues/152
-      function avgPooling2d(args) {
-        return averagePooling2d(args);
-      }
-      /**
-       * Average pooling operation for 3D data.
-       *
-       * Input shape
-       *   - If `dataFormat === channelsLast`:
-       *       5D tensor with shape:
-       *       `[batchSize, depths, rows, cols, channels]`
-       *   - If `dataFormat === channelsFirst`:
-       *      4D tensor with shape:
-       *       `[batchSize, channels, depths, rows, cols]`
-       *
-       * Output shape
-       *   - If `dataFormat=channelsLast`:
-       *       5D tensor with shape:
-       *       `[batchSize, pooledDepths, pooledRows, pooledCols, channels]`
-       *   - If `dataFormat=channelsFirst`:
-       *       5D tensor with shape:
-       *       `[batchSize, channels, pooledDepths, pooledRows, pooledCols]`
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function averagePooling3d(args) {
-        return new pooling_AveragePooling3D(args);
-      }
-      function avgPool3d(args) {
-        return averagePooling3d(args);
-      }
-      // For backwards compatibility.
-      // See https://github.com/tensorflow/tfjs/issues/152
-      function avgPooling3d(args) {
-        return averagePooling3d(args);
-      }
-      /**
-       * Global average pooling operation for temporal data.
-       *
-       * Input Shape: 3D tensor with shape: `[batchSize, steps, features]`.
-       *
-       * Output Shape:2D tensor with shape: `[batchSize, features]`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function globalAveragePooling1d(args) {
-        return new pooling_GlobalAveragePooling1D(args);
-      }
-      /**
-       * Global average pooling operation for spatial data.
-       *
-       * Input shape:
-       *   - If `dataFormat` is `CHANNEL_LAST`:
-       *       4D tensor with shape: `[batchSize, rows, cols, channels]`.
-       *   - If `dataFormat` is `CHANNEL_FIRST`:
-       *       4D tensor with shape: `[batchSize, channels, rows, cols]`.
-       *
-       * Output shape:
-       *   2D tensor with shape: `[batchSize, channels]`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function globalAveragePooling2d(args) {
-        return new pooling_GlobalAveragePooling2D(args);
-      }
-      /**
-       * Global max pooling operation for temporal data.
-       *
-       * Input Shape: 3D tensor with shape: `[batchSize, steps, features]`.
-       *
-       * Output Shape:2D tensor with shape: `[batchSize, features]`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function globalMaxPooling1d(args) {
-        return new pooling_GlobalMaxPooling1D(args);
-      }
-      /**
-       * Global max pooling operation for spatial data.
-       *
-       * Input shape:
-       *   - If `dataFormat` is `CHANNEL_LAST`:
-       *       4D tensor with shape: `[batchSize, rows, cols, channels]`.
-       *   - If `dataFormat` is `CHANNEL_FIRST`:
-       *       4D tensor with shape: `[batchSize, channels, rows, cols]`.
-       *
-       * Output shape:
-       *   2D tensor with shape: `[batchSize, channels]`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function globalMaxPooling2d(args) {
-        return new pooling_GlobalMaxPooling2D(args);
-      }
-      /**
-       * Max pooling operation for temporal data.
-       *
-       * Input shape:  `[batchSize, inLength, channels]`
-       *
-       * Output shape: `[batchSize, pooledLength, channels]`
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function maxPooling1d(args) {
-        return new pooling_MaxPooling1D(args);
-      }
-      /**
-       * Max pooling operation for spatial data.
-       *
-       * Input shape
-       *   - If `dataFormat === CHANNEL_LAST`:
-       *       4D tensor with shape:
-       *       `[batchSize, rows, cols, channels]`
-       *   - If `dataFormat === CHANNEL_FIRST`:
-       *      4D tensor with shape:
-       *       `[batchSize, channels, rows, cols]`
-       *
-       * Output shape
-       *   - If `dataFormat=CHANNEL_LAST`:
-       *       4D tensor with shape:
-       *       `[batchSize, pooleRows, pooledCols, channels]`
-       *   - If `dataFormat=CHANNEL_FIRST`:
-       *       4D tensor with shape:
-       *       `[batchSize, channels, pooleRows, pooledCols]`
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function maxPooling2d(args) {
-        return new pooling_MaxPooling2D(args);
-      }
-      /**
-       * Max pooling operation for 3D data.
-       *
-       * Input shape
-       *   - If `dataFormat === channelsLast`:
-       *       5D tensor with shape:
-       *       `[batchSize, depths, rows, cols, channels]`
-       *   - If `dataFormat === channelsFirst`:
-       *      5D tensor with shape:
-       *       `[batchSize, channels, depths, rows, cols]`
-       *
-       * Output shape
-       *   - If `dataFormat=channelsLast`:
-       *       5D tensor with shape:
-       *       `[batchSize, pooledDepths, pooledRows, pooledCols, channels]`
-       *   - If `dataFormat=channelsFirst`:
-       *       5D tensor with shape:
-       *       `[batchSize, channels, pooledDepths, pooledRows, pooledCols]`
-       */
-      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
-      function maxPooling3d(args) {
-        return new pooling_MaxPooling3D(args);
-      }
-      // Recurrent Layers.
-      /**
-       * Gated Recurrent Unit - Cho et al. 2014.
-       *
-       * This is an `RNN` layer consisting of one `GRUCell`. However, unlike
-       * the underlying `GRUCell`, the `apply` method of `SimpleRNN` operates
-       * on a sequence of inputs. The shape of the input (not including the first,
-       * batch dimension) needs to be at least 2-D, with the first dimension being
-       * time steps. For example:
-       *
-       * ```js
-       * const rnn = tf.layers.gru({units: 8, returnSequences: true});
-       *
-       * // Create an input with 10 time steps.
-       * const input = tf.input({shape: [10, 20]});
-       * const output = rnn.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
-       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
-       * // 3rd dimension is the `GRUCell`'s number of units.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
-      function gru(args) {
-        return new recurrent_GRU(args);
-      }
-      /**
-       * Cell class for `GRU`.
-       *
-       * `GRUCell` is distinct from the `RNN` subclass `GRU` in that its
-       * `apply` method takes the input data of only a single time step and returns
-       * the cell's output at the time step, while `GRU` takes the input data
-       * over a number of time steps. For example:
-       *
-       * ```js
-       * const cell = tf.layers.gruCell({units: 2});
-       * const input = tf.input({shape: [10]});
-       * const output = cell.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10]: This is the cell's output at a single time step. The 1st
-       * // dimension is the unknown batch size.
-       * ```
-       *
-       * Instance(s) of `GRUCell` can be used to construct `RNN` layers. The
-       * most typical use of this workflow is to combine a number of cells into a
-       * stacked RNN cell (i.e., `StackedRNNCell` internally) and use it to create an
-       * RNN. For example:
-       *
-       * ```js
-       * const cells = [
-       *   tf.layers.gruCell({units: 4}),
-       *   tf.layers.gruCell({units: 8}),
-       * ];
-       * const rnn = tf.layers.rnn({cell: cells, returnSequences: true});
-       *
-       * // Create an input with 10 time steps and a length-20 vector at each step.
-       * const input = tf.input({shape: [10, 20]});
-       * const output = rnn.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
-       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
-       * // 3rd dimension is the last `gruCell`'s number of units.
-       * ```
-       *
-       * To create an `RNN` consisting of only *one* `GRUCell`, use the
-       * `tf.layers.gru`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
-      function gruCell(args) {
-        return new recurrent_GRUCell(args);
-      }
-      /**
-       * Long-Short Term Memory layer - Hochreiter 1997.
-       *
-       * This is an `RNN` layer consisting of one `LSTMCell`. However, unlike
-       * the underlying `LSTMCell`, the `apply` method of `LSTM` operates
-       * on a sequence of inputs. The shape of the input (not including the first,
-       * batch dimension) needs to be at least 2-D, with the first dimension being
-       * time steps. For example:
-       *
-       * ```js
-       * const lstm = tf.layers.lstm({units: 8, returnSequences: true});
-       *
-       * // Create an input with 10 time steps.
-       * const input = tf.input({shape: [10, 20]});
-       * const output = lstm.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
-       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
-       * // 3rd dimension is the `LSTMCell`'s number of units.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
-      function lstm(args) {
-        return new recurrent_LSTM(args);
-      }
-      /**
-       * Cell class for `LSTM`.
-       *
-       * `LSTMCell` is distinct from the `RNN` subclass `LSTM` in that its
-       * `apply` method takes the input data of only a single time step and returns
-       * the cell's output at the time step, while `LSTM` takes the input data
-       * over a number of time steps. For example:
-       *
-       * ```js
-       * const cell = tf.layers.lstmCell({units: 2});
-       * const input = tf.input({shape: [10]});
-       * const output = cell.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10]: This is the cell's output at a single time step. The 1st
-       * // dimension is the unknown batch size.
-       * ```
-       *
-       * Instance(s) of `LSTMCell` can be used to construct `RNN` layers. The
-       * most typical use of this workflow is to combine a number of cells into a
-       * stacked RNN cell (i.e., `StackedRNNCell` internally) and use it to create an
-       * RNN. For example:
-       *
-       * ```js
-       * const cells = [
-       *   tf.layers.lstmCell({units: 4}),
-       *   tf.layers.lstmCell({units: 8}),
-       * ];
-       * const rnn = tf.layers.rnn({cell: cells, returnSequences: true});
-       *
-       * // Create an input with 10 time steps and a length-20 vector at each step.
-       * const input = tf.input({shape: [10, 20]});
-       * const output = rnn.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
-       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
-       * // 3rd dimension is the last `lstmCell`'s number of units.
-       * ```
-       *
-       * To create an `RNN` consisting of only *one* `LSTMCell`, use the
-       * `tf.layers.lstm`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
-      function lstmCell(args) {
-        return new recurrent_LSTMCell(args);
-      }
-      /**
-       * Fully-connected RNN where the output is to be fed back to input.
-       *
-       * This is an `RNN` layer consisting of one `SimpleRNNCell`. However, unlike
-       * the underlying `SimpleRNNCell`, the `apply` method of `SimpleRNN` operates
-       * on a sequence of inputs. The shape of the input (not including the first,
-       * batch dimension) needs to be at least 2-D, with the first dimension being
-       * time steps. For example:
-       *
-       * ```js
-       * const rnn = tf.layers.simpleRNN({units: 8, returnSequences: true});
-       *
-       * // Create an input with 10 time steps.
-       * const input = tf.input({shape: [10, 20]});
-       * const output = rnn.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
-       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
-       * // 3rd dimension is the `SimpleRNNCell`'s number of units.
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
-      function simpleRNN(args) {
-        return new recurrent_SimpleRNN(args);
-      }
-      /**
-       * Cell class for `SimpleRNN`.
-       *
-       * `SimpleRNNCell` is distinct from the `RNN` subclass `SimpleRNN` in that its
-       * `apply` method takes the input data of only a single time step and returns
-       * the cell's output at the time step, while `SimpleRNN` takes the input data
-       * over a number of time steps. For example:
-       *
-       * ```js
-       * const cell = tf.layers.simpleRNNCell({units: 2});
-       * const input = tf.input({shape: [10]});
-       * const output = cell.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10]: This is the cell's output at a single time step. The 1st
-       * // dimension is the unknown batch size.
-       * ```
-       *
-       * Instance(s) of `SimpleRNNCell` can be used to construct `RNN` layers. The
-       * most typical use of this workflow is to combine a number of cells into a
-       * stacked RNN cell (i.e., `StackedRNNCell` internally) and use it to create an
-       * RNN. For example:
-       *
-       * ```js
-       * const cells = [
-       *   tf.layers.simpleRNNCell({units: 4}),
-       *   tf.layers.simpleRNNCell({units: 8}),
-       * ];
-       * const rnn = tf.layers.rnn({cell: cells, returnSequences: true});
-       *
-       * // Create an input with 10 time steps and a length-20 vector at each step.
-       * const input = tf.input({shape: [10, 20]});
-       * const output = rnn.apply(input);
-       *
-       * console.log(JSON.stringify(output.shape));
-       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
-       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
-       * // 3rd dimension is the last `SimpleRNNCell`'s number of units.
-       * ```
-       *
-       * To create an `RNN` consisting of only *one* `SimpleRNNCell`, use the
-       * `tf.layers.simpleRNN`.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
-      function simpleRNNCell(args) {
-        return new recurrent_SimpleRNNCell(args);
-      }
-      /**
-       * Base class for recurrent layers.
-       *
-       * Input shape:
-       *   3D tensor with shape `[batchSize, timeSteps, inputDim]`.
-       *
-       * Output shape:
-       *   - if `returnState`, an Array of tensors (i.e., `tf.Tensor`s). The first
-       *     tensor is the output. The remaining tensors are the states at the
-       *     last time step, each with shape `[batchSize, units]`.
-       *   - if `returnSequences`, the output will have shape
-       *     `[batchSize, timeSteps, units]`.
-       *   - else, the output will have shape `[batchSize, units]`.
-       *
-       * Masking:
-       *   This layer supports masking for input data with a variable number
-       *   of timesteps. To introduce masks to your data,
-       *   use an embedding layer with the `mask_zero` parameter
-       *   set to `True`.
-       *
-       * Notes on using statefulness in RNNs:
-       *   You can set RNN layers to be 'stateful', which means that the states
-       *   computed for the samples in one batch will be reused as initial states
-       *   for the samples in the next batch. This assumes a one-to-one mapping
-       *   between samples in different successive batches.
-       *
-       *   To enable statefulness:
-       *     - specify `stateful: true` in the layer constructor.
-       *     - specify a fixed batch size for your model, by passing
-       *       if sequential model:
-       *         `batchInputShape=[...]` to the first layer in your model.
-       *       else for functional model with 1 or more Input layers:
-       *         `batchShape=[...]` to all the first layers in your model.
-       *       This is the expected shape of your inputs *including the batch size*.
-       *       It should be a tuple of integers, e.g. `(32, 10, 100)`.
-       *     - specify `shuffle=False` when calling fit().
-       *
-       *   To reset the states of your model, call `.resetStates()` on either
-       *   a specific layer, or on your entire model.
-       *
-       * Note on specifying the initial state of RNNs
-       *   You can specify the initial state of RNN layers symbolically by
-       *   calling them with the option `initialState`. The value of
-       *   `initialState` should be a tensor or list of tensors representing
-       *   the initial state of the RNN layer.
-       *
-       *   You can specify the initial state of RNN layers numerically by
-       *   calling `resetStates` with the keyword argument `states`. The value of
-       *   `states` should be a numpy array or list of numpy arrays representing
-       *   the initial state of the RNN layer.
-       *
-       * Note on passing external constants to RNNs
-       *   You can pass "external" constants to the cell using the `constants`
-       *   keyword argument of `RNN.call` method. This requires that the `cell.call`
-       *   method accepts the same keyword argument `constants`. Such constants
-       *   can be used to conditon the cell transformation on additional static inputs
-       *   (not changing over time), a.k.a an attention mechanism.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
-      function exports_layers_rnn(args) {
-        return new recurrent_RNN(args);
-      }
-      /**
-       * Wrapper allowing a stack of RNN cells to behave as a single cell.
-       *
-       * Used to implement efficient stacked RNNs.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
-      function stackedRNNCells(args) {
-        return new recurrent_StackedRNNCells(args);
-      }
-      // Wrapper Layers.
-      /** @doc {heading: 'Layers', subheading: 'Wrapper', namespace: 'layers'} */
-      function bidirectional(args) {
-        return new wrappers_Bidirectional(args);
-      }
-      /**
-       * This wrapper applies a layer to every temporal slice of an input.
-       *
-       * The input should be at least 3D,  and the dimension of the index `1` will be
-       * considered to be the temporal dimension.
-       *
-       * Consider a batch of 32 samples, where each sample is a sequence of 10 vectors
-       * of 16 dimensions. The batch input shape of the layer is then `[32,  10,
-       * 16]`, and the `inputShape`, not including the sample dimension, is
-       * `[10, 16]`.
-       *
-       * You can then use `TimeDistributed` to apply a `Dense` layer to each of the 10
-       * timesteps, independently:
-       *
-       * ```js
-       * const model = tf.sequential();
-       * model.add(tf.layers.timeDistributed({
-       *   layer: tf.layers.dense({units: 8}),
-       *   inputShape: [10, 16],
-       * }));
-       *
-       * // Now model.outputShape = [null, 10, 8].
-       * // The output will then have shape `[32, 10, 8]`.
-       *
-       * // In subsequent layers, there is no need for `inputShape`:
-       * model.add(tf.layers.timeDistributed({layer: tf.layers.dense({units: 32})}));
-       * console.log(JSON.stringify(model.outputs[0].shape));
-       * // Now model.outputShape = [null, 10, 32].
-       * ```
-       *
-       * The output will then have shape `[32, 10, 32]`.
-       *
-       * `TimeDistributed` can be used with arbitrary layers, not just `Dense`, for
-       * instance a `Conv2D` layer.
-       *
-       * ```js
-       * const model = tf.sequential();
-       * model.add(tf.layers.timeDistributed({
-       *   layer: tf.layers.conv2d({filters: 64, kernelSize: [3, 3]}),
-       *   inputShape: [10, 299, 299, 3],
-       * }));
-       * console.log(JSON.stringify(model.outputs[0].shape));
-       * ```
-       */
-      /** @doc {heading: 'Layers', subheading: 'Wrapper', namespace: 'layers'} */
-      function timeDistributed(args) {
-        return new wrappers_TimeDistributed(args);
-      }
-      // Aliases for pooling.
-      const globalMaxPool1d = globalMaxPooling1d;
-      const globalMaxPool2d = globalMaxPooling2d;
-      const maxPool1d = maxPooling1d;
-      const maxPool2d = maxPooling2d;
-
-      /**
-       * Apply additive zero-centered Gaussian noise.
-       *
-       * As it is a regularization layer, it is only active at training time.
-       *
-       * This is useful to mitigate overfitting
-       * (you could see it as a form of random data augmentation).
-       * Gaussian Noise (GS) is a natural choice as corruption process
-       * for real valued inputs.
-       *
-       * # Arguments
-       *     stddev: float, standard deviation of the noise distribution.
-       *
-       * # Input shape
-       *         Arbitrary. Use the keyword argument `input_shape`
-       *         (tuple of integers, does not include the samples axis)
-       *         when using this layer as the first layer in a model.
-       *
-       * # Output shape
-       *         Same shape as input.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Noise', namespace: 'layers'} */
-      function gaussianNoise(args) {
-        return new noise_GaussianNoise(args);
-      }
-      /**
-       * Apply multiplicative 1-centered Gaussian noise.
-       *
-       * As it is a regularization layer, it is only active at training time.
-       *
-       * Arguments:
-       *   - `rate`: float, drop probability (as with `Dropout`).
-       *     The multiplicative noise will have
-       *     standard deviation `sqrt(rate / (1 - rate))`.
-       *
-       * Input shape:
-       *   Arbitrary. Use the keyword argument `inputShape`
-       *   (tuple of integers, does not include the samples axis)
-       *   when using this layer as the first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as input.
-       *
-       * References:
-       *   - [Dropout: A Simple Way to Prevent Neural Networks from Overfitting](
-       *      http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf)
-       *
-       */
-      /** @doc {heading: 'Layers', subheading: 'Noise', namespace: 'layers'} */
-      function gaussianDropout(args) {
-        return new noise_GaussianDropout(args);
-      }
-      /**
-       * Applies Alpha Dropout to the input.
-       *
-       * As it is a regularization layer, it is only active at training time.
-       *
-       * Alpha Dropout is a `Dropout` that keeps mean and variance of inputs
-       * to their original values, in order to ensure the self-normalizing property
-       * even after this dropout.
-       * Alpha Dropout fits well to Scaled Exponential Linear Units
-       * by randomly setting activations to the negative saturation value.
-       *
-       * Arguments:
-       *   - `rate`: float, drop probability (as with `Dropout`).
-       *     The multiplicative noise will have
-       *     standard deviation `sqrt(rate / (1 - rate))`.
-       *   - `noise_shape`: A 1-D `Tensor` of type `int32`, representing the
-       *     shape for randomly generated keep/drop flags.
-       *
-       * Input shape:
-       *   Arbitrary. Use the keyword argument `inputShape`
-       *   (tuple of integers, does not include the samples axis)
-       *   when using this layer as the first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as input.
-       *
-       * References:
-       *   - [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)
-       */
-      /** @doc {heading: 'Layers', subheading: 'Noise', namespace: 'layers'} */
-      function alphaDropout(args) {
-        return new noise_AlphaDropout(args);
-      }
-      /**
-       * Masks a sequence by using a mask value to skip timesteps.
-       *
-       * If all features for a given sample timestep are equal to `mask_value`,
-       * then the sample timestep will be masked (skipped) in all downstream layers
-       * (as long as they support masking).
-       *
-       * If any downstream layer does not support masking yet receives such
-       * an input mask, an exception will be raised.
-       *
-       * Arguments:
-       *   - `maskValue`: Either None or mask value to skip.
-       *
-       * Input shape:
-       *   Arbitrary. Use the keyword argument `inputShape`
-       *   (tuple of integers, does not include the samples axis)
-       *   when using this layer as the first layer in a model.
-       *
-       * Output shape:
-       *   Same shape as input.
-       */
-      /** @doc {heading: 'Layers', subheading: 'Mask', namespace: 'layers'} */
-      function masking(args) {
-        return new core_Masking(args);
-      }
-      //# sourceMappingURL=exports_layers.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_metrics.js
-
-      /**
-       * Binary accuracy metric function.
-       *
-       * `yTrue` and `yPred` can have 0-1 values. Example:
-       * ```js
-       * const x = tf.tensor2d([[1, 1, 1, 1], [0, 0, 0, 0]], [2, 4]);
-       * const y = tf.tensor2d([[1, 0, 1, 0], [0, 0, 0, 1]], [2, 4]);
-       * const accuracy = tf.metrics.binaryAccuracy(x, y);
-       * accuracy.print();
-       * ```
-       *
-       * `yTrue` and `yPred` can also have floating-number values between 0 and 1, in
-       * which case the values will be thresholded at 0.5 to yield 0-1 values (i.e.,
-       * a value >= 0.5 and <= 1.0 is interpreted as 1.
-       * )
-       * Example:
-       * ```js
-       * const x = tf.tensor1d([1, 1, 1, 1, 0, 0, 0, 0]);
-       * const y = tf.tensor1d([0.2, 0.4, 0.6, 0.8, 0.2, 0.3, 0.4, 0.7]);
-       * const accuracy = tf.metrics.binaryAccuracy(x, y);
-       * accuracy.print();
-       * ```
-       *
-       * @param yTrue Binary Tensor of truth.
-       * @param yPred Binary Tensor of prediction.
-       * @return Accuracy Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_binaryAccuracy(yTrue, yPred) {
-        return binaryAccuracy(yTrue, yPred);
-      }
-      /**
-       * Binary crossentropy metric function.
-       *
-       * Example:
-       * ```js
-       * const x = tf.tensor2d([[0], [1], [1], [1]]);
-       * const y = tf.tensor2d([[0], [0], [0.5], [1]]);
-       * const crossentropy = tf.metrics.binaryCrossentropy(x, y);
-       * crossentropy.print();
-       * ```
-       *
-       * @param yTrue Binary Tensor of truth.
-       * @param yPred Binary Tensor of prediction, probabilities for the `1` case.
-       * @return Accuracy Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_binaryCrossentropy(yTrue, yPred) {
-        return metrics_binaryCrossentropy(yTrue, yPred);
-      }
-      /**
-       * Sparse categorical accuracy metric function.
-       *
-       * Example:
-       * ```js
-       *
-       * const yTrue = tf.tensor1d([1, 1, 2, 2, 0]);
-       * const yPred = tf.tensor2d(
-       *      [[0, 1, 0], [1, 0, 0], [0, 0.4, 0.6], [0, 0.6, 0.4], [0.7, 0.3, 0]]);
-       * const crossentropy = tf.metrics.sparseCategoricalAccuracy(yTrue, yPred);
-       * crossentropy.print();
-       * ```
-       *
-       * @param yTrue True labels: indices.
-       * @param yPred Predicted probabilities or logits.
-       * @returns Accuracy tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_sparseCategoricalAccuracy(yTrue, yPred) {
-        return sparseCategoricalAccuracy(yTrue, yPred);
-      }
-      /**
-       * Categorical accuracy metric function.
-       *
-       * Example:
-       * ```js
-       * const x = tf.tensor2d([[0, 0, 0, 1], [0, 0, 0, 1]]);
-       * const y = tf.tensor2d([[0.1, 0.8, 0.05, 0.05], [0.1, 0.05, 0.05, 0.8]]);
-       * const accuracy = tf.metrics.categoricalAccuracy(x, y);
-       * accuracy.print();
-       * ```
-       *
-       * @param yTrue Binary Tensor of truth: one-hot encoding of categories.
-       * @param yPred Binary Tensor of prediction: probabilities or logits for the
-       *   same categories as in `yTrue`.
-       * @return Accuracy Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_categoricalAccuracy(yTrue, yPred) {
-        return categoricalAccuracy(yTrue, yPred);
-      }
-      /**
-       * Categorical crossentropy between an output tensor and a target tensor.
-       *
-       * @param target A tensor of the same shape as `output`.
-       * @param output A tensor resulting from a softmax (unless `fromLogits` is
-       *  `true`, in which case `output` is expected to be the logits).
-       * @param fromLogits Boolean, whether `output` is the result of a softmax, or is
-       *   a tensor of logits.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_categoricalCrossentropy(yTrue, yPred) {
-        return metrics_categoricalCrossentropy(yTrue, yPred);
-      }
-      /**
-       * Computes the precision of the predictions with respect to the labels.
-       *
-       * Example:
-       * ```js
-       * const x = tf.tensor2d(
-       *    [
-       *      [0, 0, 0, 1],
-       *      [0, 1, 0, 0],
-       *      [0, 0, 0, 1],
-       *      [1, 0, 0, 0],
-       *      [0, 0, 1, 0]
-       *    ]
-       * );
-       *
-       * const y = tf.tensor2d(
-       *    [
-       *      [0, 0, 1, 0],
-       *      [0, 1, 0, 0],
-       *      [0, 0, 0, 1],
-       *      [0, 1, 0, 0],
-       *      [0, 1, 0, 0]
-       *    ]
-       * );
-       *
-       * const precision = tf.metrics.precision(x, y);
-       * precision.print();
-       * ```
-       *
-       * @param yTrue The ground truth values. Expected to be contain only 0-1 values.
-       * @param yPred The predicted values. Expected to be contain only 0-1 values.
-       * @return Precision Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_precision(yTrue, yPred) {
-        return precision(yTrue, yPred);
-      }
-      /**
-       * Computes the recall of the predictions with respect to the labels.
-       *
-       * Example:
-       * ```js
-       * const x = tf.tensor2d(
-       *    [
-       *      [0, 0, 0, 1],
-       *      [0, 1, 0, 0],
-       *      [0, 0, 0, 1],
-       *      [1, 0, 0, 0],
-       *      [0, 0, 1, 0]
-       *    ]
-       * );
-       *
-       * const y = tf.tensor2d(
-       *    [
-       *      [0, 0, 1, 0],
-       *      [0, 1, 0, 0],
-       *      [0, 0, 0, 1],
-       *      [0, 1, 0, 0],
-       *      [0, 1, 0, 0]
-       *    ]
-       * );
-       *
-       * const recall = tf.metrics.recall(x, y);
-       * recall.print();
-       * ```
-       *
-       * @param yTrue The ground truth values. Expected to be contain only 0-1 values.
-       * @param yPred The predicted values. Expected to be contain only 0-1 values.
-       * @return Recall Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_recall(yTrue, yPred) {
-        return recall(yTrue, yPred);
-      }
-      /**
-       * Loss or metric function: Cosine proximity.
-       *
-       * Mathematically, cosine proximity is defined as:
-       *   `-sum(l2Normalize(yTrue) * l2Normalize(yPred))`,
-       * wherein `l2Normalize()` normalizes the L2 norm of the input to 1 and `*`
-       * represents element-wise multiplication.
-       *
-       * ```js
-       * const yTrue = tf.tensor2d([[1, 0], [1, 0]]);
-       * const yPred = tf.tensor2d([[1 / Math.sqrt(2), 1 / Math.sqrt(2)], [0, 1]]);
-       * const proximity = tf.metrics.cosineProximity(yTrue, yPred);
-       * proximity.print();
-       * ```
-       *
-       * @param yTrue Truth Tensor.
-       * @param yPred Prediction Tensor.
-       * @return Cosine proximity Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_cosineProximity(yTrue, yPred) {
-        return cosineProximity(yTrue, yPred);
-      }
-      /**
-       * Loss or metric function: Mean absolute error.
-       *
-       * Mathematically, mean absolute error is defined as:
-       *   `mean(abs(yPred - yTrue))`,
-       * wherein the `mean` is applied over feature dimensions.
-       *
-       * ```js
-       * const yTrue = tf.tensor2d([[0, 1], [0, 0], [2, 3]]);
-       * const yPred = tf.tensor2d([[0, 1], [0, 1], [-2, -3]]);
-       * const mse = tf.metrics.meanAbsoluteError(yTrue, yPred);
-       * mse.print();
-       * ```
-       *
-       * @param yTrue Truth Tensor.
-       * @param yPred Prediction Tensor.
-       * @return Mean absolute error Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_meanAbsoluteError(yTrue, yPred) {
-        return meanAbsoluteError(yTrue, yPred);
-      }
-      /**
-       * Loss or metric function: Mean absolute percentage error.
-       *
-       * ```js
-       * const yTrue = tf.tensor2d([[0, 1], [10, 20]]);
-       * const yPred = tf.tensor2d([[0, 1], [11, 24]]);
-       * const mse = tf.metrics.meanAbsolutePercentageError(yTrue, yPred);
-       * mse.print();
-       * ```
-       *
-       * Aliases: `tf.metrics.MAPE`, `tf.metrics.mape`.
-       *
-       * @param yTrue Truth Tensor.
-       * @param yPred Prediction Tensor.
-       * @return Mean absolute percentage error Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_meanAbsolutePercentageError(yTrue, yPred) {
-        return meanAbsolutePercentageError(yTrue, yPred);
-      }
-      function exports_metrics_MAPE(yTrue, yPred) {
-        return meanAbsolutePercentageError(yTrue, yPred);
-      }
-      function exports_metrics_mape(yTrue, yPred) {
-        return meanAbsolutePercentageError(yTrue, yPred);
-      }
-      /**
-       * Loss or metric function: Mean squared error.
-       *
-       * ```js
-       * const yTrue = tf.tensor2d([[0, 1], [3, 4]]);
-       * const yPred = tf.tensor2d([[0, 1], [-3, -4]]);
-       * const mse = tf.metrics.meanSquaredError(yTrue, yPred);
-       * mse.print();
-       * ```
-       *
-       * Aliases: `tf.metrics.MSE`, `tf.metrics.mse`.
-       *
-       * @param yTrue Truth Tensor.
-       * @param yPred Prediction Tensor.
-       * @return Mean squared error Tensor.
-       */
-      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
-      function exports_metrics_meanSquaredError(yTrue, yPred) {
-        return meanSquaredError(yTrue, yPred);
-      }
-      function exports_metrics_MSE(yTrue, yPred) {
-        return meanSquaredError(yTrue, yPred);
-      }
-      function exports_metrics_mse(yTrue, yPred) {
-        return meanSquaredError(yTrue, yPred);
-      }
-      //# sourceMappingURL=exports_metrics.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_models.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      //# sourceMappingURL=exports_models.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_regularizers.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-
-      // tslint:disable-next-line:max-line-length
-
-      /**
-       * Regularizer for L1 and L2 regularization.
-       *
-       * Adds a term to the loss to penalize large weights:
-       * loss += sum(l1 * abs(x)) + sum(l2 * x^2)
-       */
-      /** @doc {heading: 'Regularizers', namespace: 'regularizers'} */
-      function l1l2(config) {
-        return new regularizers_L1L2(config);
-      }
-      /**
-       * Regularizer for L1 regularization.
-       *
-       * Adds a term to the loss to penalize large weights:
-       * loss += sum(l1 * abs(x))
-       * @param args l1 config.
-       */
-      /** @doc {heading: 'Regularizers', namespace: 'regularizers'} */
-      function exports_regularizers_l1(config) {
-        return l1(config);
-      }
-      /**
-       * Regularizer for L2 regularization.
-       *
-       * Adds a term to the loss to penalize large weights:
-       * loss += sum(l2 * x^2)
-       * @param args l2 config.
-       */
-      /** @doc {heading: 'Regularizers', namespace: 'regularizers'} */
-      function exports_regularizers_l2(config) {
-        return l2(config);
-      }
-      //# sourceMappingURL=exports_regularizers.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/callbacks.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      /* Original source: keras/callbacks.py */
-
-      class callbacks_Callback extends BaseCallback {
-        constructor() {
-          super(...arguments);
-          /** Instance of `keras.models.Model`. Reference of the model being trained. */
-          this.model = null;
-        }
-        setModel(model) {
-          if (!(model instanceof training_LayersModel)) {
-            throw new Error("model must be a LayersModel, not some other Container");
-          }
-          this.model = model;
-        }
-      }
-      function less(currVal, prevVal) {
-        return currVal < prevVal;
-      }
-      function greater(currVal, prevVal) {
-        return currVal > prevVal;
-      }
-      /**
-       * A Callback that stops training when a monitored quantity has stopped
-       * improving.
-       */
-      class callbacks_EarlyStopping extends callbacks_Callback {
-        constructor(args) {
-          super();
-          if (args == null) {
-            args = {};
-          }
-          if (args.restoreBestWeights) {
-            throw new NotImplementedError(
-              "restoreBestWeights = True is not implemented in EarlyStopping yet."
-            );
-          }
-          this.monitor = args.monitor || "val_loss";
-          this.minDelta = Math.abs(args.minDelta || 0);
-          this.patience = args.patience || 0;
-          this.verbose = args.verbose || 0;
-          this.mode = args.mode || "auto";
-          this.baseline = args.baseline;
-          if (["auto", "min", "max"].indexOf(this.mode) === -1) {
-            console.warn(
-              `EarlyStopping mode '${this.mode}' is invalid. ` + `Falling back to mode 'auto'.`
-            );
-            this.mode = "auto";
-          }
-          if (this.mode === "min") {
-            this.monitorFunc = less;
-          } else if (this.mode === "max") {
-            this.monitorFunc = greater;
-          } else {
-            // For mode === 'auto'.
-            if (this.monitor.indexOf("acc") !== -1) {
-              this.monitorFunc = greater;
-            } else {
-              this.monitorFunc = less;
-            }
-          }
-          if (this.monitorFunc === less) {
-            this.minDelta *= -1;
-          }
-        }
-        async onTrainBegin(logs) {
-          this.wait = 0;
-          this.stoppedEpoch = 0;
-          if (this.baseline != null) {
-            this.best = this.baseline;
-          } else {
-            this.best = this.monitorFunc === less ? Infinity : -Infinity;
-          }
-        }
-        async onEpochEnd(epoch, logs) {
-          await resolveScalarsInLogs(logs);
-          const current = this.getMonitorValue(logs);
-          if (current == null) {
-            return;
-          }
-          if (this.monitorFunc(current - this.minDelta, this.best)) {
-            this.best = current;
-            this.wait = 0;
-            // TODO(cais): Logic for restoreBestWeights.
-          } else {
-            this.wait++;
-            if (this.wait >= this.patience) {
-              this.stoppedEpoch = epoch;
-              this.model.stopTraining = true;
-            }
-            // TODO(cais): Logic for restoreBestWeights.
-          }
-        }
-        async onTrainEnd(logs) {
-          if (this.stoppedEpoch > 0 && this.verbose) {
-            console.log(`Epoch ${this.stoppedEpoch}: early stopping.`);
-          }
-        }
-        getMonitorValue(logs) {
-          if (logs == null) {
-            logs = {};
-          }
-          const monitorValue = logs[this.monitor];
-          if (monitorValue == null) {
-            console.warn(
-              `Metric for EarlyStopping ${this.monitor} is not available. ` +
-                `Available metrics are: ${Object.keys(logs)}`
-            );
-          }
-          return monitorValue;
-        }
-      }
-      /**
-       * Factory function for a Callback that stops training when a monitored
-       * quantity has stopped improving.
-       *
-       * Early stopping is a type of regularization, and protects model against
-       * overfitting.
-       *
-       * The following example based on fake data illustrates how this callback
-       * can be used during `tf.LayersModel.fit()`:
-       *
-       * ```js
-       * const model = tf.sequential();
-       * model.add(tf.layers.dense({
-       *   units: 3,
-       *   activation: 'softmax',
-       *   kernelInitializer: 'ones',
-       *   inputShape: [2]
-       * }));
-       * const xs = tf.tensor2d([1, 2, 3, 4], [2, 2]);
-       * const ys = tf.tensor2d([[1, 0, 0], [0, 1, 0]], [2, 3]);
-       * const xsVal = tf.tensor2d([4, 3, 2, 1], [2, 2]);
-       * const ysVal = tf.tensor2d([[0, 0, 1], [0, 1, 0]], [2, 3]);
-       * model.compile(
-       *     {loss: 'categoricalCrossentropy', optimizer: 'sgd', metrics: ['acc']});
-       *
-       * // Without the EarlyStopping callback, the val_acc value would be:
-       * //   0.5, 0.5, 0.5, 0.5, ...
-       * // With val_acc being monitored, training should stop after the 2nd epoch.
-       * const history = await model.fit(xs, ys, {
-       *   epochs: 10,
-       *   validationData: [xsVal, ysVal],
-       *   callbacks: tf.callbacks.earlyStopping({monitor: 'val_acc'})
-       * });
-       *
-       * // Expect to see a length-2 array.
-       * console.log(history.history.val_acc);
-       * ```
-       */
-      /**
-       * @doc {
-       *   heading: 'Callbacks',
-       *   namespace: 'callbacks'
-       * }
-       */
-      function earlyStopping(args) {
-        return new callbacks_EarlyStopping(args);
-      }
-      const callbacks_callbacks = { earlyStopping };
-      //# sourceMappingURL=callbacks.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/index.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC
-       *
-       * Use of this source code is governed by an MIT-style
-       * license that can be found in the LICENSE file or at
-       * https://opensource.org/licenses/MIT.
-       * =============================================================================
-       */
-      // This file lists all exports of TensorFlow.js Layers
-
-      //# sourceMappingURL=index.js.map
-
-      /***/
-    },
-    /* 88 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      // ESM COMPAT FLAG
-      __webpack_require__.r(__webpack_exports__);
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "array", function () {
-        return /* reexport */ array;
-      });
-      __webpack_require__.d(__webpack_exports__, "Dataset", function () {
-        return /* reexport */ dataset_Dataset;
-      });
-      __webpack_require__.d(__webpack_exports__, "zip", function () {
-        return /* reexport */ zip;
-      });
-      __webpack_require__.d(__webpack_exports__, "CSVDataset", function () {
-        return /* reexport */ csv_dataset_CSVDataset;
-      });
-      __webpack_require__.d(__webpack_exports__, "TextLineDataset", function () {
-        return /* reexport */ text_line_dataset_TextLineDataset;
-      });
-      __webpack_require__.d(__webpack_exports__, "csv", function () {
-        return /* reexport */ csv;
-      });
-      __webpack_require__.d(__webpack_exports__, "func", function () {
-        return /* reexport */ func;
-      });
-      __webpack_require__.d(__webpack_exports__, "generator", function () {
-        return /* reexport */ readers_generator;
-      });
-      __webpack_require__.d(__webpack_exports__, "microphone", function () {
-        return /* reexport */ microphone;
-      });
-      __webpack_require__.d(__webpack_exports__, "webcam", function () {
-        return /* reexport */ webcam;
-      });
-      __webpack_require__.d(__webpack_exports__, "FileDataSource", function () {
-        return /* reexport */ file_data_source_FileDataSource;
-      });
-      __webpack_require__.d(__webpack_exports__, "URLDataSource", function () {
-        return /* reexport */ url_data_source_URLDataSource;
-      });
-      __webpack_require__.d(__webpack_exports__, "version_data", function () {
-        return /* reexport */ version;
-      });
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
-      var dist = __webpack_require__(0);
-
-      // EXTERNAL MODULE: ./node_modules/seedrandom/index.js
-      var seedrandom = __webpack_require__(20);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/lazy_iterator.js + 3 modules
-      var lazy_iterator = __webpack_require__(14);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/deep_map.js
-      var deep_map = __webpack_require__(19);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/dataset.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      // TODO(soergel): consider vectorized operations within the pipeline.
-      /**
-       * Represents a potentially large list of independent data elements (typically
-       * 'samples' or 'examples').
-       *
-       * A 'data example' may be a primitive, an array, a map from string keys to
-       * values, or any nested structure of these.
-       *
-       * A `Dataset` represents an ordered collection of elements, together with a
-       * chain of transformations to be performed on those elements. Each
-       * transformation is a method of `Dataset` that returns another `Dataset`, so
-       * these may be chained, e.g.
-       * `const processedDataset = rawDataset.filter(...).map(...).batch(...)`.
-       *
-       * Data loading and transformation is done in a lazy, streaming fashion.  The
-       * dataset may be iterated over multiple times; each iteration starts the data
-       * loading anew and recapitulates the transformations.
-       *
-       * A `Dataset` is typically processed as a stream of unbatched examples --i.e.,
-       * its transformations are applied one example at a time. Batching produces a
-       * new `Dataset` where each element is a batch. Batching should usually come
-       * last in a pipeline, because data transformations are easier to express on a
-       * per-example basis than on a per-batch basis.
-       *
-       * The following code examples are calling `await dataset.forEachAsync(...)` to
-       * iterate once over the entire dataset in order to print out the data.
-       */
-      /** @doc {heading: 'Data', subheading: 'Classes', namespace: 'data'} */
-      class dataset_Dataset {
-        constructor() {
-          this.size = null;
-        }
-        // TODO(soergel): Make Datasets report whether repeated iterator() calls
-        // produce the same result (e.g., reading from a file) or different results
-        // (e.g., from the webcam).  Currently we don't make this distinction but it
-        // could be important for the user to know.
-        // abstract isDeterministic(): boolean;
-        /**
-         * Groups elements into batches.
-         *
-         * It is assumed that each of the incoming dataset elements has the same
-         * structure-- i.e. the same set of keys at each location in an object
-         * hierarchy.  For each key, the resulting `Dataset` provides a batched
-         * element collecting all of the incoming values for that key.
-         *
-         *  * Incoming primitives are grouped into a 1-D Tensor.
-         *  * Incoming Tensors are grouped into a new Tensor where the 0'th axis is
-         *    the batch dimension.
-         *  * Incoming arrays are converted to Tensor and then batched.
-         *  * A nested array is interpreted as an n-D Tensor, so the batched result
-         *    has n+1 dimensions.
-         *  * An array that cannot be converted to Tensor produces an error.
-         *
-         * If an array should not be batched as a unit, it should first be converted
-         * to an object with integer keys.
-         *
-         * Here are a few examples:
-         *
-         * Batch a dataset of numbers:
-         * ```js
-         * const a = tf.data.array([1, 2, 3, 4, 5, 6, 7, 8]).batch(4);
-         * await a.forEachAsync(e => e.print());
-         * ```
-         *
-         * Batch a dataset of arrays:
-         * ```js
-         * const b = tf.data.array([[1], [2], [3], [4], [5], [6], [7], [8]]).batch(4);
-         * await b.forEachAsync(e => e.print());
-         * ```
-         *
-         * Batch a dataset of objects:
-         * ```js
-         * const c = tf.data.array([{a: 1, b: 11}, {a: 2, b: 12}, {a: 3, b: 13},
-         *   {a: 4, b: 14}, {a: 5, b: 15}, {a: 6, b: 16}, {a: 7, b: 17},
-         *   {a: 8, b: 18}]).batch(4);
-         * await c.forEachAsync(e => {
-         *   console.log('{');
-         *   for(var key in e) {
-         *     console.log(key+':');
-         *     e[key].print();
-         *   }
-         *   console.log('}');
-         * })
-         * ```
-         *
-         * @param batchSize The number of elements desired per batch.
-         * @param smallLastBatch Whether to emit the final batch when it has fewer
-         *   than batchSize elements. Default true.
-         * @returns A `Dataset`, from which a stream of batches can be obtained.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        batch(batchSize, smallLastBatch = true) {
-          const base = this;
-          dist["util"].assert(
-            batchSize > 0,
-            () => `batchSize needs to be positive, but it is
-      ${batchSize}`
-          );
-          let size;
-          if (this.size === Infinity || this.size == null) {
-            // If the size of this dataset is infinity or null, the new size keeps the
-            // same.
-            size = this.size;
-          } else if (smallLastBatch) {
-            // If the size of this dataset is known and include small last batch, the
-            // new size is full batch count plus last batch.
-            size = Math.ceil(this.size / batchSize);
-          } else {
-            // If the size of this dataset is known and not include small last batch,
-            // the new size is full batch count.
-            size = Math.floor(this.size / batchSize);
-          }
-          return datasetFromIteratorFn(async () => {
-            return (await base.iterator()).columnMajorBatch(
-              batchSize,
-              smallLastBatch,
-              deepBatchConcat
-            );
-          }, size);
-        }
-        /**
-         * Concatenates this `Dataset` with another.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3]);
-         * const b = tf.data.array([4, 5, 6]);
-         * const c = a.concatenate(b);
-         * await c.forEachAsync(e => console.log(e));
-         * ```
-         *
-         * @param dataset A `Dataset` to be concatenated onto this one.
-         * @returns A `Dataset`.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        concatenate(dataset) {
-          const base = this;
-          let size;
-          if (this.size === Infinity || dataset.size === Infinity) {
-            // If the size of any of these two dataset is infinity, new size is
-            // infinity.
-            size = Infinity;
-          } else if (this.size != null && dataset.size != null) {
-            // If the size of both datasets are known and not infinity, new size is
-            // sum the size of these two datasets.
-            size = this.size + dataset.size;
-          } else {
-            // If neither of these two datasets has infinite size and any of these two
-            // datasets' size is null, the new size is null.
-            size = null;
-          }
-          return datasetFromIteratorFn(
-            async () => (await base.iterator()).concatenate(await dataset.iterator()),
-            size
-          );
-        }
-        /**
-         * Filters this dataset according to `predicate`.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
-         *   .filter(x => x%2 === 0);
-         * await a.forEachAsync(e => console.log(e));
-         * ```
-         *
-         * @param predicate A function mapping a dataset element to a boolean or a
-         * `Promise` for one.
-         *
-         * @returns A `Dataset` of elements for which the predicate was true.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        filter(predicate) {
-          const base = this;
-          let size;
-          if (this.size === Infinity) {
-            // If the size of this dataset is infinity, new size is infinity
-            size = Infinity;
-          } else {
-            // If this dataset has limited elements, new size is null because it might
-            // exhausted randomly.
-            size = null;
-          }
-          return datasetFromIteratorFn(async () => {
-            return (await base.iterator()).filter((x) => dist["tidy"](() => predicate(x)));
-          }, size);
-        }
-        /**
-         * Apply a function to every element of the dataset.
-         *
-         * After the function is applied to a dataset element, any Tensors contained
-         * within that element are disposed.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3]);
-         * await a.forEachAsync(e => console.log(e));
-         * ```
-         *
-         * @param f A function to apply to each dataset element.
-         * @returns A `Promise` that resolves after all elements have been processed.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        async forEachAsync(f) {
-          return (await this.iterator()).forEachAsync(f);
-        }
-        /**
-         * Maps this dataset through a 1-to-1 transform.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3]).map(x => x*x);
-         * await a.forEachAsync(e => console.log(e));
-         * ```
-         *
-         * @param transform A function mapping a dataset element to a transformed
-         *   dataset element.
-         *
-         * @returns A `Dataset` of transformed elements.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        map(transform) {
-          const base = this;
-          return datasetFromIteratorFn(async () => {
-            return (await base.iterator()).map((x) => dist["tidy"](() => transform(x)));
-          }, this.size);
-        }
-        /**
-         * Maps this dataset through an async 1-to-1 transform.
-         *
-         * ```js
-         * const a =
-         *  tf.data.array([1, 2, 3]).mapAsync(x => new Promise(function(resolve){
-         *    setTimeout(() => {
-         *      resolve(x * x);
-         *    }, Math.random()*1000 + 500);
-         *  }));
-         * console.log(await a.toArray());
-         * ```
-         *
-         * @param transform A function mapping a dataset element to a `Promise` for a
-         *   transformed dataset element.  This transform is responsible for disposing
-         *   any intermediate `Tensor`s, i.e. by wrapping its computation in
-         *   `tf.tidy()`; that cannot be automated here (as it is in the synchronous
-         *   `map()` case).
-         *
-         * @returns A `Dataset` of transformed elements.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        mapAsync(transform) {
-          const base = this;
-          return datasetFromIteratorFn(async () => {
-            return (await base.iterator()).mapAsync(transform);
-          }, this.size);
-        }
-        /**
-         *  Creates a `Dataset` that prefetches elements from this dataset.
-         *
-         * @param bufferSize: An integer specifying the number of elements to be
-         *   prefetched.
-         * @returns A `Dataset`.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        prefetch(bufferSize) {
-          if (bufferSize == null) {
-            throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");
-          }
-          const base = this;
-          return datasetFromIteratorFn(
-            async () => (await base.iterator()).prefetch(bufferSize),
-            this.size
-          );
-        }
-        /**
-         * Repeats this dataset `count` times.
-         *
-         * NOTE: If this dataset is a function of global state (e.g. a random number
-         * generator), then different repetitions may produce different elements.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3]).repeat(3);
-         * await a.forEachAsync(e => console.log(e));
-         * ```
-         *
-         * @param count: (Optional) An integer, representing the number of times
-         *   the dataset should be repeated. The default behavior (if `count` is
-         *   `undefined` or negative) is for the dataset be repeated indefinitely.
-         * @returns A `Dataset`.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        repeat(count) {
-          const base = this;
-          let size;
-          if (this.size != null && count > 0) {
-            // If this dataset has size and count is positive, new size is current
-            // size multiply count. This also covers the case that current size is
-            // infinity.
-            size = this.size * count;
-          } else if (count === 0) {
-            // If count is 0, new size is 0.
-            size = 0;
-          } else if (this.size != null && (count === undefined || count < 0)) {
-            // If this dataset has size and count is undefined or negative, the
-            // dataset will be repeated indefinitely and new size is infinity.
-            size = Infinity;
-          } else {
-            // If the size of this dataset is null, the new dataset's size is null.
-            size = null;
-          }
-          return datasetFromIteratorFn(async () => {
-            const iteratorIterator = Object(lazy_iterator["e" /* iteratorFromFunction */])(
-              async () => ({ value: await base.iterator(), done: false })
-            );
-            return Object(lazy_iterator["d" /* iteratorFromConcatenated */])(
-              iteratorIterator.take(count)
-            );
-          }, size);
-        }
-        /**
-         * Creates a `Dataset` that skips `count` initial elements from this dataset.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3, 4, 5, 6]).skip(3);
-         * await a.forEachAsync(e => console.log(e));
-         * ```
-         *
-         * @param count: The number of elements of this dataset that should be skipped
-         *   to form the new dataset.  If `count` is greater than the size of this
-         *   dataset, the new dataset will contain no elements.  If `count`
-         *   is `undefined` or negative, skips the entire dataset.
-         *
-         * @returns A `Dataset`.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        skip(count) {
-          const base = this;
-          let size;
-          if (this.size != null && count >= 0 && this.size >= count) {
-            // If the size of this dataset is greater than count, the new dataset's
-            // size is current size minus skipped size.This also covers the case that
-            // current size is infinity.
-            size = this.size - count;
-          } else if (this.size != null && (this.size < count || count === undefined || count < 0)) {
-            // If the size of this dataset is smaller than count, or count is
-            // undefined or negative, skips the entire dataset and the new size is 0.
-            size = 0;
-          } else {
-            // If the size of this dataset is null, the new dataset's size is null.
-            size = null;
-          }
-          return datasetFromIteratorFn(async () => (await base.iterator()).skip(count), size);
-        }
-        /**
-         * Pseudorandomly shuffles the elements of this dataset. This is done in a
-         * streaming manner, by sampling from a given number of prefetched elements.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3, 4, 5, 6]).shuffle(3);
-         * await a.forEachAsync(e => console.log(e));
-         * ```
-         *
-         * @param bufferSize: An integer specifying the number of elements from this
-         *   dataset from which the new dataset will sample.
-         * @param seed: (Optional) An integer specifying the random seed that will
-         *   be used to create the distribution.
-         * @param reshuffleEachIteration: (Optional) A boolean, which if true
-         *   indicates that the dataset should be pseudorandomly reshuffled each time
-         *   it is iterated over. If false, elements will be returned in the same
-         *   shuffled order on each iteration. (Defaults to `true`.)
-         * @returns A `Dataset`.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        shuffle(bufferSize, seed, reshuffleEachIteration = true) {
-          if (bufferSize == null || bufferSize < 0) {
-            if (this.size == null) {
-              throw new RangeError("`Dataset.shuffle()` requires bufferSize to be specified.");
-            } else {
-              throw new RangeError(
-                "`Dataset.shuffle()` requires bufferSize to be specified.  " +
-                  "If your data fits in main memory (for regular JS objects), " +
-                  "and/or GPU memory (for `tf.Tensor`s), consider setting " +
-                  `bufferSize to the dataset size (${this.size} elements)`
-              );
-            }
-          }
-          const base = this;
-          const random = seedrandom["alea"](seed || dist["util"].now().toString());
-          return datasetFromIteratorFn(async () => {
-            let seed2 = random.int32();
-            if (reshuffleEachIteration) {
-              seed2 += random.int32();
-            }
-            return (await base.iterator()).shuffle(bufferSize, seed2.toString());
-          }, this.size);
-        }
-        /**
-         * Creates a `Dataset` with at most `count` initial elements from this
-         * dataset.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3, 4, 5, 6]).take(3);
-         * await a.forEachAsync(e => console.log(e));
-         * ```
-         *
-         * @param count: The number of elements of this dataset that should be taken
-         *   to form the new dataset.  If `count` is `undefined` or negative, or if
-         *   `count` is greater than the size of this dataset, the new dataset will
-         *   contain all elements of this dataset.
-         * @returns A `Dataset`.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        take(count) {
-          const base = this;
-          let size;
-          if (this.size != null && this.size > count) {
-            // If the size of this dataset is greater than count, the new dataset's
-            // size is count.
-            size = count;
-          } else if (this.size != null && this.size <= count) {
-            // If the size of this dataset is equal or smaller than count, the new
-            // dataset's size is the size of this dataset.
-            size = this.size;
-          } else {
-            // If the size of this dataset is null, the new dataset's size is null.
-            size = null;
-          }
-          return datasetFromIteratorFn(async () => (await base.iterator()).take(count), size);
-        }
-        /**
-         * Collect all elements of this dataset into an array.
-         *
-         * Obviously this will succeed only for small datasets that fit in memory.
-         * Useful for testing and generally should be avoided if possible.
-         *
-         * ```js
-         * const a = tf.data.array([1, 2, 3, 4, 5, 6]);
-         * console.log(await a.toArray());
-         * ```
-         *
-         * @returns A Promise for an array of elements, which will resolve
-         *   when a new stream has been obtained and fully consumed.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        async toArray() {
-          if (this.size === Infinity) {
-            throw new Error("Can not convert infinite data stream to array.");
-          }
-          return (await this.iterator()).toArray();
-        }
-        /**
-         * Collect all elements of this dataset into an array with prefetching 100
-         * elements. This is useful for testing, because the prefetch changes the
-         * order in which the Promises are resolved along the processing pipeline.
-         * This may help expose bugs where results are dependent on the order of
-         * Promise resolution rather than on the logical order of the stream (i.e.,
-         * due to hidden mutable state).
-         *
-         * @returns A Promise for an array of elements, which will resolve
-         *   when a new stream has been obtained and fully consumed.
-         */
-        async toArrayForTest() {
-          if (this.size === Infinity) {
-            throw new Error("Can not convert infinite data stream to array.");
-          }
-          return (await this.iterator()).toArrayForTest();
-        }
-      }
-      // TODO(soergel): deep sharded shuffle, where supported
-      dataset_Dataset.MAX_BUFFER_SIZE = 10000;
-      /**
-       * Create a `Dataset` defined by a provided iterator() function.
-       *
-       * ```js
-       * let i = -1;
-       * const func = () =>
-       *    ++i < 5 ? {value: i, done: false} : {value: null, done: true};
-       * const iter = tf.data.iteratorFromFunction(func);
-       * const ds = tf.data.datasetFromIteratorFn(iter);
-       * await ds.forEachAsync(e => console.log(e));
-       * ```
-       */
-      function datasetFromIteratorFn(iteratorFn, size = null) {
-        return new (class extends dataset_Dataset {
-          constructor() {
-            super(...arguments);
-            this.size = size;
-          }
-          /*
-           * Provide a new stream of elements.  Note this will also start new streams
-           * from any underlying `Dataset`s.
-           */
-          async iterator() {
-            return iteratorFn();
-          }
-        })();
-      }
-      /**
-       * Create a `Dataset` from an array of elements.
-       *
-       * Create a Dataset from an array of objects:
-       * ```js
-       * const a = tf.data.array([{'item': 1}, {'item': 2}, {'item': 3}]);
-       * await a.forEachAsync(e => console.log(e));
-       * ```
-       *
-       * Create a Dataset from an array of numbers:
-       * ```js
-       * const a = tf.data.array([4, 5, 6]);
-       * await a.forEachAsync(e => console.log(e));
-       * ```
-       * @param items An array of elements that will be parsed as items in a dataset.
-       */
-      /** @doc {heading: 'Data', subheading: 'Creation', namespace: 'data'} */
-      function array(items) {
-        return datasetFromIteratorFn(
-          async () => Object(lazy_iterator["f" /* iteratorFromItems */])(items),
-          items.length
-        );
-      }
-      /**
-       * Create a `Dataset` by zipping together an array, dict, or nested
-       * structure of `Dataset`s (and perhaps additional constants).
-       * The underlying datasets must provide elements in a consistent order such that
-       * they correspond.
-       *
-       * The number of elements in the resulting dataset is the same as the size of
-       * the smallest dataset in datasets.
-       *
-       * The nested structure of the `datasets` argument determines the
-       * structure of elements in the resulting iterator.
-       *
-       * Note this means that, given an array of two datasets that produce dict
-       * elements, the result is a dataset that produces elements that are arrays
-       * of two dicts:
-       *
-       * Zip an array of datasets:
-       * ```js
-       * console.log('Zip two datasets of objects:');
-       * const ds1 = tf.data.array([{a: 1}, {a: 2}, {a: 3}]);
-       * const ds2 = tf.data.array([{b: 4}, {b: 5}, {b: 6}]);
-       * const ds3 = tf.data.zip([ds1, ds2]);
-       * await ds3.forEachAsync(e => console.log(JSON.stringify(e)));
-       *
-       * // If the goal is to merge the dicts in order to produce elements like
-       * // {a: ..., b: ...}, this requires a second step such as:
-       * console.log('Merge the objects:');
-       * const ds4 = ds3.map(x => {return {a: x[0].a, b: x[1].b}});
-       * await ds4.forEachAsync(e => console.log(e));
-       * ```
-       *
-       * Zip a dict of datasets:
-       * ```js
-       * const a = tf.data.array([{a: 1}, {a: 2}, {a: 3}]);
-       * const b = tf.data.array([{b: 4}, {b: 5}, {b: 6}]);
-       * const c = tf.data.zip({c: a, d: b});
-       * await c.forEachAsync(e => console.log(JSON.stringify(e)));
-       * ```
-       */
-      /** @doc {heading: 'Data', subheading: 'Operations', namespace: 'data'} */
-      function zip(datasets) {
-        // manually type-check the argument for JS users
-        if (!Object(deep_map["e" /* isIterable */])(datasets)) {
-          throw new Error("The argument to zip() must be an object or array.");
-        }
-        let size;
-        if (Array.isArray(datasets)) {
-          for (let i = 0; i < datasets.length; i++) {
-            size = size == null ? datasets[i].size : Math.min(size, datasets[i].size);
-          }
-        } else if (datasets instanceof Object) {
-          for (const ds in datasets) {
-            size = size == null ? datasets[ds].size : Math.min(size, datasets[ds].size);
-          }
-        }
-        return datasetFromIteratorFn(async () => {
-          const streams = await Object(deep_map["c" /* deepMapAndAwaitAll */])(datasets, (d) => {
-            if (d instanceof dataset_Dataset) {
-              return { value: d.iterator(), recurse: false };
-            } else if (Object(deep_map["e" /* isIterable */])(d)) {
-              return { value: null, recurse: true };
-            } else {
-              throw new Error(
-                "Leaves of the structure passed to zip() must be Datasets, " + "not primitives."
-              );
-            }
-          });
-          return Object(lazy_iterator["g" /* iteratorFromZipped */])(
-            streams,
-            lazy_iterator["c" /* ZipMismatchMode */].SHORTEST
-          );
-        }, size);
-      }
-      /**
-       * A zip function for use with deepZip, passed via the columnMajorBatch call.
-       *
-       * Accepts an array of identically-structured nested elements and either batches
-       * them (if they are primitives, numeric arrays, or Tensors) or requests
-       * recursion (if not).
-       */
-      // tslint:disable-next-line:no-any
-      function deepBatchConcat(rows) {
-        if (rows === null) {
-          return null;
-        }
-        // use the first item to decide whether to recurse or batch here.
-        const exampleRow = rows[0];
-        if (Object(deep_map["a" /* canTensorify */])(exampleRow)) {
-          // rows is an array of primitives, Tensors, or arrays.  Batch them.
-          const value = batchConcat(rows);
-          return { value, recurse: false };
-        }
-        // the example row is an object, so recurse into it.
-        return { value: null, recurse: true };
-      }
-      /**
-       * Assembles a list of same-shaped numbers, number arrays, or Tensors
-       * into a single new Tensor where axis 0 is the batch dimension.
-       */
-      function batchConcat(arrays) {
-        if (arrays.length === 0) {
-          // We can't return an empty Tensor because we don't know the element shape.
-          throw new Error("Can't make a batch of zero elements.");
-        }
-        if (arrays[0] instanceof dist["Tensor"]) {
-          // Input is an array of Tensors
-          return dist["stack"](arrays);
-        } else {
-          // Input is a possibly-nested array of numbers.
-          return dist["tensor"](arrays);
-        }
-      }
-      //# sourceMappingURL=dataset.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/datasets/text_line_dataset.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      /**
-       * Represents a potentially large collection of text lines.
-       *
-       * The results are not batched.
-       */
-      class text_line_dataset_TextLineDataset extends dataset_Dataset {
-        /**
-         * Create a `TextLineDataset`.
-         *
-         * @param input A `DataSource` providing a chunked, UTF8-encoded byte stream.
-         */
-        constructor(input) {
-          super();
-          this.input = input;
-        }
-        async iterator() {
-          const inputIterator = await this.input.iterator();
-          const utf8Iterator = inputIterator.decodeUTF8();
-          const lineIterator = utf8Iterator.split("\n").map((line) => {
-            // Windows/DOS format text file has extra line breaker at the end of line.
-            if (line.endsWith("\r")) {
-              line = line.slice(0, -1);
-            }
-            return line;
-          });
-          return lineIterator;
-        }
-      }
-      //# sourceMappingURL=text_line_dataset.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/datasets/csv_dataset.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      const CODE_QUOTE = '"';
-      const STATE_OUT = Symbol("out");
-      const STATE_FIELD = Symbol("field");
-      const STATE_QUOTE = Symbol("quote");
-      const STATE_QUOTE_AFTER_QUOTE = Symbol("quoteafterquote");
-      const STATE_WITHIN_QUOTE_IN_QUOTE = Symbol("quoteinquote");
-      /**
-       * Represents a potentially large collection of delimited text records.
-       *
-       * The produced `TensorContainer`s each contain one key-value pair for
-       * every column of the table.  When a field is empty in the incoming data, the
-       * resulting value is `undefined`, or throw error if it is required.  Values
-       * that can be parsed as numbers are emitted as type `number`, other values
-       * are parsed as `string`.
-       *
-       * The results are not batched.
-       */
-      /** @doc {heading: 'Data', subheading: 'Classes', namespace: 'data'} */
-      class csv_dataset_CSVDataset extends dataset_Dataset {
-        /**
-         * Create a `CSVDataset`.
-         *
-         * @param input A `DataSource` providing a chunked, UTF8-encoded byte stream.
-         * @param csvConfig (Optional) A CSVConfig object that contains configurations
-         *     of reading and decoding from CSV file(s).
-         *
-         *     hasHeader: (Optional) A boolean value that indicates whether the first
-         *     row of provided CSV file is a header line with column names, and should
-         *     not be included in the data. Defaults to `true`.
-         *
-         *     columnNames: (Optional) A list of strings that corresponds to
-         *     the CSV column names, in order. If provided, it ignores the column
-         *     names inferred from the header row. If not provided, infers the column
-         *     names from the first row of the records. If hasHeader is false and
-         *     columnNames is not provided, this method throws an error.
-         *
-         *     columnConfigs: (Optional) A dictionary whose key is column names, value
-         *     is an object stating if this column is required, column's data type,
-         *     default value, and if this column is label. If provided, keys must
-         *     correspond to names provided in columnNames or inferred from the file
-         *     header lines. If isLabel is true any column, returns an array of two
-         *     items: the first item is a dict of features key/value pairs, the second
-         *     item is a dict of labels key/value pairs. If no feature is marked as
-         *     label, returns a dict of features only.
-         *
-         *     configuredColumnsOnly (Optional) If true, only columns provided in
-         *     columnConfigs will be parsed and provided during iteration.
-         *
-         *     delimiter (Optional) The string used to parse each line of the input
-         *     file. Defaults to `,`.
-         */
-        constructor(input, csvConfig) {
-          super();
-          this.input = input;
-          this.hasHeader = true;
-          this.fullColumnNames = null;
-          this.columnNamesValidated = false;
-          this.columnConfigs = null;
-          this.configuredColumnsOnly = false;
-          this.delimiter = ",";
-          this.delimWhitespace = false;
-          this.base = new text_line_dataset_TextLineDataset(input);
-          if (!csvConfig) {
-            csvConfig = {};
-          }
-          this.hasHeader = csvConfig.hasHeader === false ? false : true;
-          this.fullColumnNames = csvConfig.columnNames;
-          this.columnConfigs = csvConfig.columnConfigs;
-          this.configuredColumnsOnly = csvConfig.configuredColumnsOnly;
-          if (csvConfig.delimWhitespace) {
-            dist["util"].assert(
-              csvConfig.delimiter == null,
-              () => "Delimiter should not be provided when delimWhitespace is true."
-            );
-            this.delimWhitespace = true;
-            this.delimiter = " ";
-          } else {
-            this.delimiter = csvConfig.delimiter ? csvConfig.delimiter : ",";
-          }
-        }
-        /**
-         * Returns column names of the csv dataset. If `configuredColumnsOnly` is
-         * true, return column names in `columnConfigs`. If `configuredColumnsOnly` is
-         * false and `columnNames` is provided, `columnNames`. If
-         * `configuredColumnsOnly` is false and `columnNames` is not provided, return
-         * all column names parsed from the csv file. For example usage please go to
-         * `tf.data.csv`.
-         */
-        /** @doc {heading: 'Data', subheading: 'Classes'} */
-        async columnNames() {
-          if (!this.columnNamesValidated) {
-            await this.setColumnNames();
-          }
-          return this.configuredColumnsOnly
-            ? Object.keys(this.columnConfigs)
-            : this.fullColumnNames;
-        }
-        /* 1) If `columnNames` is provided as string[], use this string[] as output
-         * keys in corresponding order. The length must match the number of inferred
-         * columns if `hasHeader` is true .
-         * 2) If `columnNames` is not provided, parse header line as `columnNames` if
-         * hasHeader is true. If `hasHeader` is false, throw an error.
-         * 3) If `columnConfigs` is provided, all the keys in `columnConfigs` must
-         * exist in parsed `columnNames`.
-         */
-        async setColumnNames() {
-          const columnNamesFromFile = await this.maybeReadHeaderLine();
-          if (!this.fullColumnNames && !columnNamesFromFile) {
-            // Throw an error if columnNames is not provided and no header line.
-            throw new Error("Column names must be provided if there is no header line.");
-          } else if (this.fullColumnNames && columnNamesFromFile) {
-            // Check provided columnNames match header line.
-            dist["util"].assert(
-              columnNamesFromFile.length === this.fullColumnNames.length,
-              () =>
-                "The length of provided columnNames (" +
-                this.fullColumnNames.length.toString() +
-                ") does not match the length of the header line read from " +
-                "file (" +
-                columnNamesFromFile.length.toString() +
-                ")."
-            );
-          }
-          if (!this.fullColumnNames) {
-            this.fullColumnNames = columnNamesFromFile;
-          }
-          // Check if there are duplicate column names.
-          const counts = this.fullColumnNames.reduce((countAcc, name) => {
-            countAcc[name] = countAcc[name] + 1 || 1;
-            return countAcc;
-          }, {});
-          const duplicateNames = Object.keys(counts).filter((name) => counts[name] > 1);
-          dist["util"].assert(
-            duplicateNames.length === 0,
-            () => "Duplicate column names found: " + duplicateNames.toString()
-          );
-          // Check if keys in columnConfigs match columnNames.
-          if (this.columnConfigs) {
-            for (const key of Object.keys(this.columnConfigs)) {
-              const index = this.fullColumnNames.indexOf(key);
-              if (index === -1) {
-                throw new Error(
-                  'The key "' +
-                    key +
-                    '" provided in columnConfigs does not match any of the column ' +
-                    "names (" +
-                    this.fullColumnNames.toString() +
-                    ")."
-                );
-              }
-            }
-          }
-          this.columnNamesValidated = true;
-        }
-        async maybeReadHeaderLine() {
-          if (this.hasHeader) {
-            const iter = await this.base.iterator();
-            const firstElement = await iter.next();
-            if (firstElement.done) {
-              throw new Error("No data was found for CSV parsing.");
-            }
-            const firstLine = firstElement.value;
-            const headers = this.parseRow(firstLine, false);
-            return headers;
-          } else {
-            return null;
-          }
-        }
-        async iterator() {
-          if (!this.columnNamesValidated) {
-            await this.setColumnNames();
-          }
-          let lines = await this.base.iterator();
-          if (this.hasHeader) {
-            // We previously read the first line to get the columnNames.
-            // Now that we're providing data, skip it.
-            lines = lines.skip(1);
-          }
-          return lines.map((x) => this.makeDataElement(x));
-        }
-        makeDataElement(line) {
-          const values = this.parseRow(line);
-          const features = {};
-          const labels = {};
-          for (let i = 0; i < this.fullColumnNames.length; i++) {
-            const key = this.fullColumnNames[i];
-            const config = this.columnConfigs ? this.columnConfigs[key] : null;
-            if (this.configuredColumnsOnly && !config) {
-              // This column is not selected.
-              continue;
-            } else {
-              const value = values[i];
-              let parsedValue = null;
-              if (value === "") {
-                // If default value is provided, use it. If default value is not
-                // provided, set as undefined.
-                if (config && config.default !== undefined) {
-                  parsedValue = config.default;
-                } else if (config && (config.required || config.isLabel)) {
-                  throw new Error(`Required column ${key} is empty in this line: ${line}`);
-                } else {
-                  parsedValue = undefined;
-                }
-              } else {
-                // A value is present, so parse it based on type
-                const valueAsNum = Number(value);
-                if (isNaN(valueAsNum)) {
-                  // The value is a string and this column is declared as boolean
-                  // in config, parse it as boolean.
-                  if (config && config.dtype === "bool") {
-                    parsedValue = this.getBoolean(value);
-                  } else {
-                    // Set value as string
-                    parsedValue = value;
-                  }
-                } else if (!config || !config.dtype) {
-                  // If this value is a number and no type config is provided, return
-                  // it as number.
-                  parsedValue = valueAsNum;
-                } else {
-                  // If this value is a number and data type is provided, parse it
-                  // according to provided data type.
-                  switch (config.dtype) {
-                    case "float32":
-                      parsedValue = valueAsNum;
-                      break;
-                    case "int32":
-                      parsedValue = Math.floor(valueAsNum);
-                      break;
-                    case "bool":
-                      parsedValue = this.getBoolean(value);
-                      break;
-                    default:
-                      parsedValue = valueAsNum;
-                  }
-                }
-              }
-              // Check if this column is label.
-              config && config.isLabel
-                ? (labels[key] = parsedValue)
-                : (features[key] = parsedValue);
-            }
-          }
-          // If label exists, return an object of features and labels as {xs:features,
-          // ys:labels}, otherwise return features only.
-          if (Object.keys(labels).length === 0) {
-            return features;
-          } else {
-            return { xs: features, ys: labels };
-          }
-        }
-        getBoolean(value) {
-          if (value === "1" || value.toLowerCase() === "true") {
-            return 1;
-          } else {
-            return 0;
-          }
-        }
-        // adapted from https://beta.observablehq.com/@mbostock/streaming-csv
-        parseRow(line, validateElementCount = true) {
-          const result = [];
-          let readOffset = 0;
-          const readLength = line.length;
-          let currentState = STATE_OUT;
-          // Goes through the line to parse quote.
-          for (let i = 0; i < readLength; i++) {
-            switch (currentState) {
-              // Before enter a new field
-              case STATE_OUT:
-                switch (line.charAt(i)) {
-                  // Enter a quoted field
-                  case CODE_QUOTE:
-                    readOffset = i + 1;
-                    currentState = STATE_QUOTE;
-                    break;
-                  // Read an empty field
-                  case this.delimiter:
-                    readOffset = i + 1;
-                    // If delimiter is white space and configured to collapse
-                    // multiple white spaces, ignore this white space.
-                    if (this.delimiter === " " && this.delimWhitespace) {
-                      break;
-                    }
-                    result.push("");
-                    currentState = STATE_OUT;
-                    break;
-                  // Enter an unquoted field
-                  default:
-                    currentState = STATE_FIELD;
-                    readOffset = i;
-                    break;
-                }
-                break;
-              // In an unquoted field
-              case STATE_FIELD:
-                switch (line.charAt(i)) {
-                  // Exit an unquoted field, add it to result
-                  case this.delimiter:
-                    result.push(line.substring(readOffset, i));
-                    currentState = STATE_OUT;
-                    readOffset = i + 1;
-                    break;
-                  default:
-                }
-                break;
-              // In a quoted field
-              case STATE_QUOTE:
-                switch (line.charAt(i)) {
-                  // Read a quote after a quote
-                  case CODE_QUOTE:
-                    currentState = STATE_QUOTE_AFTER_QUOTE;
-                    break;
-                  default:
-                }
-                break;
-              // This state means it's right after a second quote in a field
-              case STATE_QUOTE_AFTER_QUOTE:
-                switch (line.charAt(i)) {
-                  // Finished a quoted field
-                  case this.delimiter:
-                    result.push(line.substring(readOffset, i - 1));
-                    currentState = STATE_OUT;
-                    readOffset = i + 1;
-                    break;
-                  // Finished a quoted part in a quoted field
-                  case CODE_QUOTE:
-                    currentState = STATE_QUOTE;
-                    break;
-                  // In a quoted part in a quoted field
-                  default:
-                    currentState = STATE_WITHIN_QUOTE_IN_QUOTE;
-                    break;
-                }
-                break;
-              case STATE_WITHIN_QUOTE_IN_QUOTE:
-                switch (line.charAt(i)) {
-                  // Exit a quoted part in a quoted field
-                  case CODE_QUOTE:
-                    currentState = STATE_QUOTE;
-                    break;
-                  default:
-                }
-                break;
-              default:
-            }
-          }
-          // Adds last item based on if it is quoted.
-          if (currentState === STATE_QUOTE_AFTER_QUOTE) {
-            result.push(line.substring(readOffset, readLength - 1));
-          } else {
-            result.push(line.substring(readOffset));
-          }
-          // Check if each row has the same number of elements as column names.
-          if (validateElementCount && result.length !== this.fullColumnNames.length) {
-            throw new Error(
-              `Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${result}`
-            );
-          }
-          return result;
-        }
-      }
-      // TODO(soergel): add more basic datasets for parity with tf.data
-      // tf.data.FixedLengthRecordDataset()
-      // tf.data.TFRecordDataset()
-      //# sourceMappingURL=csv_dataset.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/microphone_iterator.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      /**
-       * Provide a stream of tensors from microphone audio stream. The tensors are
-       * representing audio data as frequency-domain spectrogram generated with
-       * browser's native FFT. Tensors representing time-domain waveform is available
-       * based on configuration. Only works in browser environment.
-       */
-      class microphone_iterator_MicrophoneIterator extends lazy_iterator["a" /* LazyIterator */] {
-        constructor(microphoneConfig) {
-          super();
-          this.microphoneConfig = microphoneConfig;
-          this.isClosed = false;
-          this.fftSize = microphoneConfig.fftSize || 1024;
-          const fftSizeLog2 = Math.log2(this.fftSize);
-          if (
-            this.fftSize < 0 ||
-            fftSizeLog2 < 4 ||
-            fftSizeLog2 > 14 ||
-            !Number.isInteger(fftSizeLog2)
-          ) {
-            throw new Error(
-              `Invalid fftSize: it must be a power of 2 between ` +
-                `2 to 4 and 2 to 14, but got ${this.fftSize}`
-            );
-          }
-          this.numFrames = microphoneConfig.numFramesPerSpectrogram || 43;
-          this.sampleRateHz = microphoneConfig.sampleRateHz;
-          this.columnTruncateLength = microphoneConfig.columnTruncateLength || this.fftSize;
-          this.audioTrackConstraints = microphoneConfig.audioTrackConstraints;
-          this.smoothingTimeConstant = microphoneConfig.smoothingTimeConstant || 0;
-          this.includeSpectrogram = microphoneConfig.includeSpectrogram === false ? false : true;
-          this.includeWaveform = microphoneConfig.includeWaveform === true ? true : false;
-          if (!this.includeSpectrogram && !this.includeWaveform) {
-            throw new Error(
-              "Both includeSpectrogram and includeWaveform are false. " +
-                "At least one type of data should be returned."
-            );
-          }
-        }
-        summary() {
-          return `microphone`;
-        }
-        // Construct a MicrophoneIterator and start the audio stream.
-        static async create(microphoneConfig = {}) {
-          if (Object(dist["env"])().get("IS_NODE")) {
-            throw new Error("microphone API is only supported in browser environment.");
-          }
-          const microphoneIterator = new microphone_iterator_MicrophoneIterator(microphoneConfig);
-          // Call async function start() to initialize the audio stream.
-          await microphoneIterator.start();
-          return microphoneIterator;
-        }
-        // Start the audio stream and FFT.
-        async start() {
-          try {
-            this.stream = await navigator.mediaDevices.getUserMedia({
-              audio: this.audioTrackConstraints == null ? true : this.audioTrackConstraints,
-              video: false,
-            });
-          } catch (e) {
-            throw new Error(`Error thrown while initializing video stream: ${e.message}`);
-          }
-          if (!this.stream) {
-            throw new Error("Could not obtain audio from microphone.");
-          }
-          const ctxConstructor =
-            // tslint:disable-next-line:no-any
-            window.AudioContext || window.webkitAudioContext;
-          this.audioContext = new ctxConstructor();
-          if (!this.sampleRateHz) {
-            // If sample rate is not provided, use the available sample rate on
-            // device.
-            this.sampleRateHz = this.audioContext.sampleRate;
-          } else if (this.audioContext.sampleRate !== this.sampleRateHz) {
-            throw new Error(
-              `Mismatch in sampling rate: ` +
-                `Expected: ${this.sampleRateHz}; ` +
-                `Actual: ${this.audioContext.sampleRate}`
-            );
-          }
-          const streamSource = this.audioContext.createMediaStreamSource(this.stream);
-          this.analyser = this.audioContext.createAnalyser();
-          this.analyser.fftSize = this.fftSize * 2;
-          this.analyser.smoothingTimeConstant = this.smoothingTimeConstant;
-          streamSource.connect(this.analyser);
-          this.freqData = new Float32Array(this.fftSize);
-          this.timeData = new Float32Array(this.fftSize);
-          return;
-        }
-        async next() {
-          if (this.isClosed) {
-            return { value: null, done: true };
-          }
-          let spectrogramTensor;
-          let waveformTensor;
-          const audioDataQueue = await this.getAudioData();
-          if (this.includeSpectrogram) {
-            const freqData = this.flattenQueue(audioDataQueue.freqDataQueue);
-            spectrogramTensor = this.getTensorFromAudioDataArray(freqData, [
-              this.numFrames,
-              this.columnTruncateLength,
-              1,
-            ]);
-          }
-          if (this.includeWaveform) {
-            const timeData = this.flattenQueue(audioDataQueue.timeDataQueue);
-            waveformTensor = this.getTensorFromAudioDataArray(timeData, [
-              this.numFrames * this.fftSize,
-              1,
-            ]);
-          }
-          return {
-            value: { spectrogram: spectrogramTensor, waveform: waveformTensor },
-            done: false,
-          };
-        }
-        // Capture one result from the audio stream, and extract the value from
-        // iterator.next() result.
-        async capture() {
-          return (await this.next()).value;
-        }
-        async getAudioData() {
-          const freqDataQueue = [];
-          const timeDataQueue = [];
-          let currentFrames = 0;
-          return new Promise((resolve) => {
-            const intervalID = setInterval(() => {
-              if (this.includeSpectrogram) {
-                this.analyser.getFloatFrequencyData(this.freqData);
-                // If the audio stream is initializing, return empty queue.
-                if (this.freqData[0] === -Infinity) {
-                  resolve({ freqDataQueue, timeDataQueue });
-                }
-                freqDataQueue.push(this.freqData.slice(0, this.columnTruncateLength));
-              }
-              if (this.includeWaveform) {
-                this.analyser.getFloatTimeDomainData(this.timeData);
-                timeDataQueue.push(this.timeData.slice());
-              }
-              // Clean interval and return when all frames have been collected
-              if (++currentFrames === this.numFrames) {
-                clearInterval(intervalID);
-                resolve({ freqDataQueue, timeDataQueue });
-              }
-            }, (this.fftSize / this.sampleRateHz) * 1e3);
-          });
-        }
-        // Stop the audio stream and pause the iterator.
-        stop() {
-          if (!this.isClosed) {
-            this.isClosed = true;
-            this.analyser.disconnect();
-            this.audioContext.close();
-            if (this.stream != null && this.stream.getTracks().length > 0) {
-              this.stream.getTracks()[0].stop();
-            }
-          }
-        }
-        // Override toArray() function to prevent collecting.
-        toArray() {
-          throw new Error("Can not convert infinite audio stream to array.");
-        }
-        // Return audio sampling rate in Hz
-        getSampleRate() {
-          return this.sampleRateHz;
-        }
-        flattenQueue(queue) {
-          const frameSize = queue[0].length;
-          const freqData = new Float32Array(queue.length * frameSize);
-          queue.forEach((data, i) => freqData.set(data, i * frameSize));
-          return freqData;
-        }
-        getTensorFromAudioDataArray(freqData, shape) {
-          const vals = new Float32Array(dist["util"].sizeFromShape(shape));
-          // If the data is less than the output shape, the rest is padded with zeros.
-          vals.set(freqData, vals.length - freqData.length);
-          return Object(dist["tensor"])(vals, shape);
-        }
-      }
-      //# sourceMappingURL=microphone_iterator.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/webcam_iterator.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      /**
-       * Provide a stream of image tensors from webcam video stream. Only works in
-       * browser environment.
-       */
-      class webcam_iterator_WebcamIterator extends lazy_iterator["a" /* LazyIterator */] {
-        constructor(webcamVideoElement, webcamConfig) {
-          super();
-          this.webcamVideoElement = webcamVideoElement;
-          this.webcamConfig = webcamConfig;
-          this.isClosed = true;
-          this.resize = false;
-          if (this.needToResize()) {
-            this.resize = true;
-            this.cropSize = [this.webcamConfig.resizeHeight, this.webcamConfig.resizeWidth];
-            this.cropBoxInd = Object(dist["tensor1d"])([0], "int32");
-            if (this.webcamConfig.centerCrop) {
-              // Calculate the box based on resizing shape.
-              const widthCroppingRatio =
-                (this.webcamConfig.resizeWidth * 1.0) / this.webcamVideoElement.width;
-              const heightCroppingRatio =
-                (this.webcamConfig.resizeHeight * 1.0) / this.webcamVideoElement.height;
-              const widthCropStart = (1 - widthCroppingRatio) / 2;
-              const heightCropStart = (1 - heightCroppingRatio) / 2;
-              const widthCropEnd = widthCropStart + widthCroppingRatio;
-              const heightCropEnd = heightCroppingRatio + heightCropStart;
-              this.cropBox = Object(dist["tensor2d"])(
-                [heightCropStart, widthCropStart, heightCropEnd, widthCropEnd],
-                [1, 4]
-              );
-            } else {
-              this.cropBox = Object(dist["tensor2d"])([0, 0, 1, 1], [1, 4]);
-            }
-          }
-        }
-        summary() {
-          return `webcam`;
-        }
-        // Construct a WebcamIterator and start it's video stream.
-        static async create(webcamVideoElement, webcamConfig = {}) {
-          if (Object(dist["env"])().get("IS_NODE")) {
-            throw new Error("tf.data.webcam is only supported in browser environment.");
-          }
-          if (!webcamVideoElement) {
-            // If webcam video element is not provided, create a hidden video element
-            // with provided width and height.
-            webcamVideoElement = document.createElement("video");
-            if (!webcamConfig.resizeWidth || !webcamConfig.resizeHeight) {
-              throw new Error(
-                "Please provide webcam video element, or resizeWidth and " +
-                  "resizeHeight to create a hidden video element."
-              );
-            }
-            webcamVideoElement.width = webcamConfig.resizeWidth;
-            webcamVideoElement.height = webcamConfig.resizeHeight;
-          }
-          const webcamIterator = new webcam_iterator_WebcamIterator(
-            webcamVideoElement,
-            webcamConfig
-          );
-          // Call async function to initialize the video stream.
-          await webcamIterator.start();
-          return webcamIterator;
-        }
-        // Async function to start video stream.
-        async start() {
-          if (this.webcamConfig.facingMode) {
-            dist["util"].assert(
-              this.webcamConfig.facingMode === "user" ||
-                this.webcamConfig.facingMode === "environment",
-              () =>
-                `Invalid webcam facing mode: ${this.webcamConfig.facingMode}. ` +
-                `Please provide 'user' or 'environment'`
-            );
-          }
-          try {
-            this.stream = await navigator.mediaDevices.getUserMedia({
-              video: {
-                deviceId: this.webcamConfig.deviceId,
-                facingMode: this.webcamConfig.facingMode ? this.webcamConfig.facingMode : "user",
-                width: this.webcamVideoElement.width,
-                height: this.webcamVideoElement.height,
-              },
-            });
-          } catch (e) {
-            // Modify the error message but leave the stack trace intact
-            e.message = `Error thrown while initializing video stream: ${e.message}`;
-            throw e;
-          }
-          if (!this.stream) {
-            throw new Error("Could not obtain video from webcam.");
-          }
-          // Older browsers may not have srcObject
-          try {
-            this.webcamVideoElement.srcObject = this.stream;
-          } catch (error) {
-            console.log(error);
-            this.webcamVideoElement.src = window.URL.createObjectURL(this.stream);
-          }
-          // Start the webcam video stream
-          this.webcamVideoElement.play();
-          this.isClosed = false;
-          return new Promise((resolve) => {
-            // Add event listener to make sure the webcam has been fully initialized.
-            this.webcamVideoElement.onloadedmetadata = () => {
-              resolve();
-            };
-          });
-        }
-        async next() {
-          if (this.isClosed) {
-            return { value: null, done: true };
-          }
-          let img;
-          try {
-            img = dist["browser"].fromPixels(this.webcamVideoElement);
-          } catch (e) {
-            throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(e)}`);
-          }
-          if (this.resize) {
-            try {
-              return { value: this.cropAndResizeFrame(img), done: false };
-            } catch (e) {
-              throw new Error(`Error thrown cropping the video: ${e.message}`);
-            } finally {
-              img.dispose();
-            }
-          } else {
-            return { value: img, done: false };
-          }
-        }
-        needToResize() {
-          // If resizeWidth and resizeHeight are provided, and different from the
-          // width and height of original HTMLVideoElement, then resizing and cropping
-          // is required.
-          if (
-            this.webcamConfig.resizeWidth &&
-            this.webcamConfig.resizeHeight &&
-            (this.webcamVideoElement.width !== this.webcamConfig.resizeWidth ||
-              this.webcamVideoElement.height !== this.webcamConfig.resizeHeight)
-          ) {
-            return true;
-          }
-          return false;
-        }
-        // Cropping and resizing each frame based on config
-        cropAndResizeFrame(img) {
-          return Object(dist["tidy"])(() => {
-            const expandedImage = img.toFloat().expandDims(0);
-            let resizedImage;
-            resizedImage = dist["image"].cropAndResize(
-              expandedImage,
-              this.cropBox,
-              this.cropBoxInd,
-              this.cropSize,
-              "bilinear"
-            );
-            // Extract image from batch cropping.
-            const shape = resizedImage.shape;
-            return resizedImage.reshape(shape.slice(1));
-          });
-        }
-        // Capture one frame from the video stream, and extract the value from
-        // iterator.next() result.
-        async capture() {
-          return (await this.next()).value;
-        }
-        // Stop the video stream and pause webcam iterator.
-        stop() {
-          const tracks = this.stream.getTracks();
-          tracks.forEach((track) => track.stop());
-          try {
-            this.webcamVideoElement.srcObject = null;
-          } catch (error) {
-            console.log(error);
-            this.webcamVideoElement.src = null;
-          }
-          this.isClosed = true;
-        }
-        // Override toArray() function to prevent collecting.
-        toArray() {
-          throw new Error("Can not convert infinite video stream to array.");
-        }
-      }
-      //# sourceMappingURL=webcam_iterator.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/datasource.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-      /**
-       * Represents a data source readable as a stream of binary data chunks.
-       *
-       * Because `Dataset`s can be read repeatedly (via `Dataset.iterator()`), this
-       * provides a means to repeatedly create streams from the underlying data
-       * sources.
-       */
-      class DataSource {}
-      // TODO(soergel): consider convenience factory functions here
-      // in combination with chainable source->dataset above, e.g.:
-      // tf.data.url(...).asCsvDataset().shuffle().batch()
-      //# sourceMappingURL=datasource.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/byte_chunk_iterator.js
-      var byte_chunk_iterator = __webpack_require__(57);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/file_chunk_iterator.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-      // inspired by https://github.com/maxogden/filereader-stream
-
-      /**
-       * Provide a stream of chunks from a File, Blob, or Uint8Array.
-       * @param file The source File, Blob or Uint8Array.
-       * @param options Optional settings controlling file reading.
-       * @returns a lazy Iterator of Uint8Arrays containing sequential chunks of the
-       *   input File, Blob or Uint8Array.
-       */
-      class file_chunk_iterator_FileChunkIterator extends byte_chunk_iterator[
-        "a" /* ByteChunkIterator */
-      ] {
-        constructor(file, options = {}) {
-          super();
-          this.file = file;
-          this.options = options;
-          dist["util"].assert(
-            file instanceof Uint8Array ||
-              (Object(dist["env"])().get("IS_BROWSER")
-                ? file instanceof File || file instanceof Blob
-                : false),
-            () => "FileChunkIterator only supports File, Blob and Uint8Array " + "right now."
-          );
-          this.offset = options.offset || 0;
-          // default 1MB chunk has tolerable perf on large files
-          this.chunkSize = options.chunkSize || 1024 * 1024;
-        }
-        summary() {
-          return `FileChunks ${this.file}`;
-        }
-        async next() {
-          if (
-            this.offset >= (this.file instanceof Uint8Array ? this.file.byteLength : this.file.size)
-          ) {
-            return { value: null, done: true };
-          }
-          const chunk = new Promise((resolve, reject) => {
-            const end = this.offset + this.chunkSize;
-            if (this.file instanceof Uint8Array) {
-              // Note if end > this.uint8Array.byteLength, we just get a small last
-              // chunk.
-              resolve(new Uint8Array(this.file.slice(this.offset, end)));
-            } else {
-              // This branch assumes that this.file type is File or Blob, which
-              // means it is in the browser environment.
-              // TODO(soergel): is this a performance issue?
-              const fileReader = new FileReader();
-              fileReader.onload = (event) => {
-                let data = fileReader.result;
-                // Not sure we can trust the return type of
-                // FileReader.readAsArrayBuffer See e.g.
-                // https://github.com/node-file-api/FileReader/issues/2
-                if (data instanceof ArrayBuffer) {
-                  data = new Uint8Array(data);
-                }
-                if (!(data instanceof Uint8Array)) {
-                  return reject(new TypeError("FileReader returned unknown type."));
-                }
-                resolve(data);
-              };
-              fileReader.onabort = (event) => {
-                return reject(new Error("Aborted"));
-              };
-              fileReader.onerror = (event) => {
-                return reject(new Error(event.type));
-              };
-              // TODO(soergel): better handle onabort, onerror
-              // Note if end > this.file.size, we just get a small last chunk.
-              const slice = this.file.slice(this.offset, end);
-              // We can't use readAsText here (even if we know the file is text)
-              // because the slice boundary may fall within a multi-byte character.
-              fileReader.readAsArrayBuffer(slice);
-            }
-            this.offset = end;
-          });
-          return { value: await chunk, done: false };
-        }
-      }
-      //# sourceMappingURL=file_chunk_iterator.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/url_chunk_iterator.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      /**
-       * Provide a stream of chunks from a URL.
-       *
-       * Note this class first downloads the entire file into memory before providing
-       * the first element from the stream.  This is because the Fetch API does not
-       * yet reliably provide a reader stream for the response body.
-       */
-      async function urlChunkIterator(url, options = {}) {
-        let urlString;
-        let requestInit;
-        if (typeof url === "string") {
-          urlString = url;
-        } else {
-          urlString = url.url;
-          requestInit = getRequestInitFromRequest(url);
-        }
-        const response = await dist["util"].fetch(urlString, requestInit);
-        if (response.ok) {
-          const uint8Array = new Uint8Array(await response.arrayBuffer());
-          return new file_chunk_iterator_FileChunkIterator(uint8Array, options);
-        } else {
-          throw new Error(response.statusText);
-        }
-      }
-      // Generate RequestInit from Request to match tf.util.fetch signature.
-      const getRequestInitFromRequest = (request) => {
-        const init = {
-          method: request.method,
-          headers: request.headers,
-          body: request.body,
-          mode: request.mode,
-          credentials: request.credentials,
-          cache: request.cache,
-          redirect: request.redirect,
-          referrer: request.referrer,
-          integrity: request.integrity,
-        };
-        return init;
-      };
-      //# sourceMappingURL=url_chunk_iterator.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/source_util.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-      // Skip tslint any type check cause this method is aiming to check type of
-      // input.
-      // tslint:disable-next-line:no-any
-      function isLocalPath(source) {
-        return typeof source === "string" && source.substr(0, 7) === "file://";
-      }
-      //# sourceMappingURL=source_util.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/sources/file_data_source.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      /**
-       * Represents a file, blob, or Uint8Array readable as a stream of binary data
-       * chunks.
-       */
-      class file_data_source_FileDataSource extends DataSource {
-        /**
-         * Create a `FileDataSource`.
-         *
-         * @param input Local file path, or `File`/`Blob`/`Uint8Array` object to
-         *     read. Local file only works in node environment.
-         * @param options Options passed to the underlying `FileChunkIterator`s,
-         *   such as {chunksize: 1024}.
-         */
-        constructor(input, options = {}) {
-          super();
-          this.input = input;
-          this.options = options;
-        }
-        async iterator() {
-          if (isLocalPath(this.input) && Object(dist["env"])().get("IS_NODE")) {
-            // tslint:disable-next-line:no-require-imports
-            const fs = __webpack_require__(79);
-            this.input = fs.readFileSync(this.input.substr(7));
-          }
-          // TODO(kangyizhang): Add LocalFileChunkIterator to split local streaming
-          // with file in browser.
-          return new file_chunk_iterator_FileChunkIterator(this.input, this.options);
-        }
-      }
-      //# sourceMappingURL=file_data_source.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/sources/url_data_source.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      /*
-       * Represents a URL readable as a stream of binary data chunks.
-       */
-      class url_data_source_URLDataSource extends DataSource {
-        /**
-         * Create a `URLDataSource`.
-         *
-         * @param url A source URL string, or a `Request` object.
-         * @param options Options passed to the underlying `FileChunkIterator`s,
-         *   such as {chunksize: 1024}.
-         */
-        constructor(url, fileOptions = {}) {
-          super();
-          this.url = url;
-          this.fileOptions = fileOptions;
-        }
-        // TODO(soergel): provide appropriate caching options.  Currently this
-        // will download the URL anew for each call to iterator().  Since we have
-        // to treat the downloaded file as a blob/buffer anyway, we may as well retain
-        // it-- but that raises GC issues.  Also we may want a persistent disk cache.
-        async iterator() {
-          if (isLocalPath(this.url)) {
-            return new file_data_source_FileDataSource(this.url, this.fileOptions).iterator();
-          } else {
-            return urlChunkIterator(this.url, this.fileOptions);
-          }
-        }
-      }
-      //# sourceMappingURL=url_data_source.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/readers.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       *
-       * =============================================================================
-       */
-
-      /**
-       * Create a `CSVDataset` by reading and decoding CSV file(s) from provided URL
-       * or local path if it's in Node environment.
-       *
-       * Note: If isLabel in columnConfigs is `true` for at least one column, the
-       * element in returned `CSVDataset` will be an object of
-       * `{xs:features, ys:labels}`: xs is a dict of features key/value pairs, ys
-       * is a dict of labels key/value pairs. If no column is marked as label,
-       * returns a dict of features only.
-       *
-       * ```js
-       * const csvUrl =
-       * 'https://storage.googleapis.com/tfjs-examples/multivariate-linear-regression/data/boston-housing-train.csv';
-       *
-       * async function run() {
-       *   // We want to predict the column "medv", which represents a median value of
-       *   // a home (in $1000s), so we mark it as a label.
-       *   const csvDataset = tf.data.csv(
-       *     csvUrl, {
-       *       columnConfigs: {
-       *         medv: {
-       *           isLabel: true
-       *         }
-       *       }
-       *     });
-       *
-       *   // Number of features is the number of column names minus one for the label
-       *   // column.
-       *   const numOfFeatures = (await csvDataset.columnNames()).length - 1;
-       *
-       *   // Prepare the Dataset for training.
-       *   const flattenedDataset =
-       *     csvDataset
-       *     .map(({xs, ys}) =>
-       *       {
-       *         // Convert xs(features) and ys(labels) from object form (keyed by
-       *         // column name) to array form.
-       *         return {xs:Object.values(xs), ys:Object.values(ys)};
-       *       })
-       *     .batch(10);
-       *
-       *   // Define the model.
-       *   const model = tf.sequential();
-       *   model.add(tf.layers.dense({
-       *     inputShape: [numOfFeatures],
-       *     units: 1
-       *   }));
-       *   model.compile({
-       *     optimizer: tf.train.sgd(0.000001),
-       *     loss: 'meanSquaredError'
-       *   });
-       *
-       *   // Fit the model using the prepared Dataset
-       *   return model.fitDataset(flattenedDataset, {
-       *     epochs: 10,
-       *     callbacks: {
-       *       onEpochEnd: async (epoch, logs) => {
-       *         console.log(epoch + ':' + logs.loss);
-       *       }
-       *     }
-       *   });
-       * }
-       *
-       * await run();
-       * ```
-       *
-       * @param source URL or local path to get CSV file. If it's a local path, it
-       * must have prefix `file://` and it only works in node environment.
-       * @param csvConfig (Optional) A CSVConfig object that contains configurations
-       *     of reading and decoding from CSV file(s).
-       */
-      /**
-       * @doc {
-       *   heading: 'Data',
-       *   subheading: 'Creation',
-       *   namespace: 'data',
-       *   configParamIndices: [1]
-       *  }
-       */
-      function csv(source, csvConfig = {}) {
-        return new csv_dataset_CSVDataset(new url_data_source_URLDataSource(source), csvConfig);
-      }
-      /**
-       * Create a `Dataset` that produces each element by calling a provided function.
-       *
-       * Note that repeated iterations over this `Dataset` may produce different
-       * results, because the function will be called anew for each element of each
-       * iteration.
-       *
-       * Also, beware that the sequence of calls to this function may be out of order
-       * in time with respect to the logical order of the Dataset. This is due to the
-       * asynchronous lazy nature of stream processing, and depends on downstream
-       * transformations (e.g. .shuffle()). If the provided function is pure, this is
-       * no problem, but if it is a closure over a mutable state (e.g., a traversal
-       * pointer), then the order of the produced elements may be scrambled.
-       *
-       * ```js
-       * let i = -1;
-       * const func = () =>
-       *    ++i < 5 ? {value: i, done: false} : {value: null, done: true};
-       * const ds = tf.data.func(func);
-       * await ds.forEachAsync(e => console.log(e));
-       * ```
-       *
-       * @param f A function that produces one data element on each call.
-       */
-      function func(f) {
-        const iter = Object(lazy_iterator["e" /* iteratorFromFunction */])(f);
-        return datasetFromIteratorFn(async () => iter);
-      }
-      /**
-       * Create a `Dataset` that produces each element from provided JavaScript
-       * generator, which is a function*
-       * (https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Iterators_and_Generators#Generator_functions),
-       * or a function that returns an
-       * iterator
-       * (https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Iterators_and_Generators#Generator_functions).
-       *
-       * The returned iterator should have `.next()` function that returns element in
-       * format of `{value: TensorContainer, done:boolean}`.
-       *
-       * Example of creating a dataset from an iterator factory:
-       * ```js
-       * function makeIterator() {
-       *   const numElements = 10;
-       *   let index = 0;
-       *
-       *   const iterator = {
-       *     next: () => {
-       *       let result;
-       *       if (index < numElements) {
-       *         result = {value: index, done: false};
-       *         index++;
-       *         return result;
-       *       }
-       *       return {value: index, done: true};
-       *     }
-       *   };
-       *   return iterator;
-       * }
-       * const ds = tf.data.generator(makeIterator);
-       * await ds.forEachAsync(e => console.log(e));
-       * ```
-       *
-       * Example of creating a dataset from a generator:
-       * ```js
-       * function* dataGenerator() {
-       *   const numElements = 10;
-       *   let index = 0;
-       *   while (index < numElements) {
-       *     const x = index;
-       *     index++;
-       *     yield x;
-       *   }
-       * }
-       *
-       * const ds = tf.data.generator(dataGenerator);
-       * await ds.forEachAsync(e => console.log(e));
-       * ```
-       *
-       * @param generator A Javascript generator function that returns a JavaScript
-       *     iterator.
-       */
-      /**
-       * @doc {
-       *   heading: 'Data',
-       *   subheading: 'Creation',
-       *   namespace: 'data',
-       *   configParamIndices: [1]
-       *  }
-       */
-      function readers_generator(generator) {
-        return datasetFromIteratorFn(async () => {
-          const gen = await generator();
-          return Object(lazy_iterator["e" /* iteratorFromFunction */])(() => gen.next());
-        });
-      }
-      /**
-       * Create an iterator that generate `Tensor`s from webcam video stream. This API
-       * only works in Browser environment when the device has webcam.
-       *
-       * Note: this code snippet only works when the device has a webcam. It will
-       * request permission to open the webcam when running.
-       * ```js
-       * const videoElement = document.createElement('video');
-       * videoElement.width = 100;
-       * videoElement.height = 100;
-       * const cam = await tf.data.webcam(videoElement);
-       * const img = await cam.capture();
-       * img.print();
-       * cam.stop();
-       * ```
-       *
-       * @param webcamVideoElement A `HTMLVideoElement` used to play video from
-       *     webcam. If this element is not provided, a hidden `HTMLVideoElement` will
-       *     be created. In that case, `resizeWidth` and `resizeHeight` must be
-       *     provided to set the generated tensor shape.
-       * @param webcamConfig A `WebcamConfig` object that contains configurations of
-       *     reading and manipulating data from webcam video stream.
-       */
-      /**
-       * @doc {
-       *   heading: 'Data',
-       *   subheading: 'Creation',
-       *   namespace: 'data',
-       *   ignoreCI: true
-       *  }
-       */
-      async function webcam(webcamVideoElement, webcamConfig) {
-        return webcam_iterator_WebcamIterator.create(webcamVideoElement, webcamConfig);
-      }
-      /**
-       * Create an iterator that generate frequency-domain spectrogram `Tensor`s from
-       * microphone audio stream with browser's native FFT. This API only works in
-       * browser environment when the device has microphone.
-       *
-       * Note: this code snippet only works when the device has a microphone. It will
-       * request permission to open the microphone when running.
-       * ```js
-       * const mic = await tf.data.microphone({
-       *   fftSize: 1024,
-       *   columnTruncateLength: 232,
-       *   numFramesPerSpectrogram: 43,
-       *   sampleRateHz:44100,
-       *   includeSpectrogram: true,
-       *   includeWaveform: true
-       * });
-       * const audioData = await mic.capture();
-       * const spectrogramTensor = audioData.spectrogram;
-       * spectrogramTensor.print();
-       * const waveformTensor = audioData.waveform;
-       * waveformTensor.print();
-       * mic.stop();
-       * ```
-       *
-       * @param microphoneConfig A `MicrophoneConfig` object that contains
-       *     configurations of reading audio data from microphone.
-       */
-      /**
-       * @doc {
-       *   heading: 'Data',
-       *   subheading: 'Creation',
-       *   namespace: 'data',
-       *   ignoreCI: true
-       *  }
-       */
-      async function microphone(microphoneConfig) {
-        return microphone_iterator_MicrophoneIterator.create(microphoneConfig);
-      }
-      //# sourceMappingURL=readers.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/version.js
-      /** @license See the LICENSE file. */
-      // This code is auto-generated, do not modify this file!
-      const version = "2.0.1";
-
-      //# sourceMappingURL=version.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/index.js
-      /**
-       * @license
-       * Copyright 2018 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      //# sourceMappingURL=index.js.map
-
-      /***/
-    },
-    /* 89 */
-    /***/ function (module, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      // ESM COMPAT FLAG
-      __webpack_require__.r(__webpack_exports__);
-
-      // EXPORTS
-      __webpack_require__.d(__webpack_exports__, "MathBackendCPU", function () {
-        return /* reexport */ base["a" /* MathBackendCPU */];
-      });
-      __webpack_require__.d(__webpack_exports__, "version_cpu", function () {
-        return /* reexport */ base["c" /* version_cpu */];
-      });
-      __webpack_require__.d(__webpack_exports__, "shared", function () {
-        return /* reexport */ base["b" /* shared */];
-      });
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
-      var dist = __webpack_require__(0);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/base.js + 3 modules
-      var base = __webpack_require__(31);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/cpu_util.js
-      var cpu_util = __webpack_require__(9);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/kernel_utils.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function createBinaryKernelConfig(name, op) {
-        return {
-          kernelName: name,
-          backendName: "cpu",
-          kernelFunc: ({ inputs, backend }) => {
-            const { a, b } = inputs;
-            const cpuBackend = backend;
-            Object(cpu_util["a" /* assertNotComplex */])([a, b], name);
-            const aVals = cpuBackend.data.get(a.dataId).values;
-            const bVals = cpuBackend.data.get(b.dataId).values;
-            const [resultData, resultShape] = op(a.shape, b.shape, aVals, bVals, a.dtype);
-            const dataId = cpuBackend.write(resultData, resultShape, a.dtype);
-            return { dataId, shape: resultShape, dtype: a.dtype };
-          },
-        };
-      }
-      function createBinaryKernelImpl(op) {
-        return (aShape, bShape, aVals, bVals, dtype) => {
-          const newShape = dist["backend_util"].assertAndGetBroadcastShape(aShape, bShape);
-          const resultRank = newShape.length;
-          const resultStrides = dist["util"].computeStrides(newShape);
-          const resultSize = dist["util"].sizeFromShape(newShape);
-          const result = dist["util"].getTypedArrayFromDType(dtype, resultSize);
-          const aRank = aShape.length;
-          const bRank = bShape.length;
-          const aStrides = dist["util"].computeStrides(aShape);
-          const bStrides = dist["util"].computeStrides(bShape);
-          const aBroadcastDims = dist["backend_util"].getBroadcastDims(aShape, newShape);
-          const bBroadcastDims = dist["backend_util"].getBroadcastDims(bShape, newShape);
-          if (aBroadcastDims.length + bBroadcastDims.length === 0) {
-            for (let i = 0; i < result.length; ++i) {
-              result[i] = op(aVals[i % aVals.length], bVals[i % bVals.length]);
-            }
-          } else {
-            for (let i = 0; i < result.length; ++i) {
-              const loc = dist["util"].indexToLoc(i, resultRank, resultStrides);
-              const aLoc = loc.slice(-aRank);
-              aBroadcastDims.forEach((d) => (aLoc[d] = 0));
-              const aIndex = dist["util"].locToIndex(aLoc, aRank, aStrides);
-              const bLoc = loc.slice(-bRank);
-              bBroadcastDims.forEach((d) => (bLoc[d] = 0));
-              const bIndex = dist["util"].locToIndex(bLoc, bRank, bStrides);
-              result[i] = op(aVals[aIndex], bVals[bIndex]);
-            }
-          }
-          return [result, newShape];
-        };
-      }
-      //# sourceMappingURL=kernel_utils.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Div_impl.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const divImpl = createBinaryKernelImpl((a, b) => a / b);
-      //# sourceMappingURL=Div_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Div.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const divConfig = createBinaryKernelConfig(dist["Div"], divImpl);
-      //# sourceMappingURL=Div.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max_impl.js
-      var Max_impl = __webpack_require__(37);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose_impl.js
-      var Transpose_impl = __webpack_require__(30);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const maxConfig = {
-        kernelName: dist["Max"],
-        backendName: "cpu",
-        kernelFunc: ({ inputs, attrs, backend }) => {
-          const { x } = inputs;
-          const { reductionIndices } = attrs;
-          const cpuBackend = backend;
-          let xShape = x.shape;
-          const xRank = xShape.length;
-          const origAxes = dist["util"].parseAxisParam(reductionIndices, xShape);
-          let axes = origAxes;
-          const permutedAxes = dist["backend_util"].getAxesPermutation(axes, xRank);
-          let xVals = cpuBackend.data.get(x.dataId).values;
-          if (permutedAxes != null) {
-            const newShape = new Array(xRank);
-            for (let i = 0; i < newShape.length; i++) {
-              newShape[i] = xShape[permutedAxes[i]];
-            }
-            xVals = Object(Transpose_impl["a" /* transposeImpl */])(
-              xVals,
-              xShape,
-              x.dtype,
-              permutedAxes,
-              newShape
-            );
-            axes = dist["backend_util"].getInnerMostAxes(axes.length, xRank);
-            xShape = newShape;
-          }
-          Object(cpu_util["a" /* assertNotComplex */])(x, "max");
-          dist["backend_util"].assertAxesAreInnerMostDims("max", axes, xRank);
-          const [maxOutShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
-            xShape,
-            axes
-          );
-          const reduceSize = dist["util"].sizeFromShape(reduceShape);
-          const result = Object(Max_impl["a" /* maxImpl */])(
-            xVals,
-            reduceSize,
-            maxOutShape,
-            x.dtype
-          );
-          const dataId = cpuBackend.write(result, maxOutShape, x.dtype);
-          return { dataId, shape: maxOutShape, dtype: x.dtype };
-        },
-      };
-      //# sourceMappingURL=Max.js.map
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/pool_utils.js
-      var pool_utils = __webpack_require__(26);
-
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolWithArgmax_impl.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      function maxPoolWithArgmaxImpl(xValues, xShape, dtype, includeBatchInIndex, convInfo) {
-        const strides = dist["util"].computeStrides(xShape);
-        const maxPools = Object(pool_utils["b" /* pool */])(
-          xValues,
-          xShape,
-          dtype,
-          strides,
-          convInfo,
-          "max"
-        );
-        const maxPositions = Object(pool_utils["a" /* maxPoolPositions */])(
-          xValues,
-          xShape,
-          dtype,
-          convInfo,
-          true,
-          includeBatchInIndex
-        );
-        return [maxPools.values, maxPositions.values];
-      }
-      //# sourceMappingURL=MaxPoolWithArgmax_impl.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolWithArgmax.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const maxPoolWithArgmaxConfig = {
-        kernelName: dist["MaxPoolWithArgmax"],
-        backendName: "cpu",
-        kernelFunc: ({ inputs, attrs, backend }) => {
-          const { x } = inputs;
-          const { filterSize, strides, pad, includeBatchInIndex } = attrs;
-          const cpuBackend = backend;
-          Object(cpu_util["a" /* assertNotComplex */])(x, "MaxPoolWithArgmax");
-          const values = cpuBackend.data.get(x.dataId).values;
-          const convInfo = dist["backend_util"].computePool2DInfo(
-            x.shape,
-            filterSize,
-            strides,
-            [1, 1],
-            pad
-          );
-          const [pooled, indexes] = maxPoolWithArgmaxImpl(
-            values,
-            x.shape,
-            x.dtype,
-            includeBatchInIndex,
-            convInfo
-          );
-          const pooledDataId = cpuBackend.write(pooled, convInfo.outShape, x.dtype);
-          const indexesDataId = cpuBackend.write(indexes, convInfo.outShape, x.dtype);
-          return [
-            { dataId: pooledDataId, shape: convInfo.outShape, dtype: x.dtype },
-            { dataId: indexesDataId, shape: convInfo.outShape, dtype: "int32" },
-          ];
-        },
-      };
-      //# sourceMappingURL=MaxPoolWithArgmax.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NonMaxSuppressionV5.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const nonMaxSuppressionV5 = dist["kernel_impls"].nonMaxSuppressionV5;
-
-      const nonMaxSuppressionV5Config = {
-        kernelName: dist["NonMaxSuppressionV5"],
-        backendName: "cpu",
-        kernelFunc: ({ inputs, backend, attrs }) => {
-          const { boxes, scores } = inputs;
-          const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;
-          const cpuBackend = backend;
-          Object(cpu_util["a" /* assertNotComplex */])(boxes, "NonMaxSuppressionWithScore");
-          const boxesVals = cpuBackend.data.get(boxes.dataId).values;
-          const scoresVals = cpuBackend.data.get(scores.dataId).values;
-          const maxOutputSizeVal = maxOutputSize;
-          const iouThresholdVal = iouThreshold;
-          const scoreThresholdVal = scoreThreshold;
-          const softNmsSigmaVal = softNmsSigma;
-          const { selectedIndices, selectedScores } = nonMaxSuppressionV5(
-            boxesVals,
-            scoresVals,
-            maxOutputSizeVal,
-            iouThresholdVal,
-            scoreThresholdVal,
-            softNmsSigmaVal
-          );
-          return [selectedIndices, selectedScores];
-        },
-      };
-      //# sourceMappingURL=NonMaxSuppressionV5.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Square.js
-      /**
-       * @license
-       * Copyright 2019 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const squareConfig = {
-        kernelName: dist["Square"],
-        backendName: "cpu",
-        kernelFunc: ({ inputs, backend }) => {
-          const { x } = inputs;
-          const cpuBackend = backend;
-          Object(cpu_util["a" /* assertNotComplex */])(x, "square");
-          const values = cpuBackend.data.get(x.dataId).values;
-          const newValues = new Float32Array(values.length);
-          for (let i = 0; i < values.length; ++i) {
-            const value = values[i];
-            newValues[i] = value * value;
-          }
-          const dataId = cpuBackend.write(newValues, x.shape, x.dtype);
-          return { dataId, shape: x.shape, dtype: x.dtype };
-        },
-      };
-      //# sourceMappingURL=Square.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SquaredDifference.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const squaredDifferenceImpl = createBinaryKernelImpl((aVal, bVal) => {
-        const diff = aVal - bVal;
-        return diff * diff;
-      });
-      const squaredDifferenceConfig = createBinaryKernelConfig(
-        dist["SquaredDifference"],
-        squaredDifferenceImpl
-      );
-      //# sourceMappingURL=SquaredDifference.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      const transposeConfig = {
-        kernelName: dist["Transpose"],
-        backendName: "cpu",
-        kernelFunc: ({ inputs, attrs, backend }) => {
-          const { x } = inputs;
-          const { perm } = attrs;
-          const cpuBackend = backend;
-          Object(cpu_util["a" /* assertNotComplex */])(x, "transpose");
-          const xRank = x.shape.length;
-          const newShape = new Array(xRank);
-          for (let i = 0; i < newShape.length; i++) {
-            newShape[i] = x.shape[perm[i]];
-          }
-          const values = cpuBackend.data.get(x.dataId).values;
-          const result = Object(Transpose_impl["a" /* transposeImpl */])(
-            values,
-            x.shape,
-            x.dtype,
-            perm,
-            newShape
-          );
-          const dataId = cpuBackend.write(result, newShape, x.dtype);
-          return { dataId, shape: newShape, dtype: x.dtype };
-        },
-      };
-      //# sourceMappingURL=Transpose.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/register_all_kernels.js
-      /**
-       * @license
-       * Copyright 2020 Google Inc. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-      // We explicitly import the modular kernels so they get registered in the
-      // global registry when we compile the library. A modular build would replace
-      // the contents of this file and import only the kernels that are needed.
-
-      // List all kernel configs here
-      const kernelConfigs = [
-        nonMaxSuppressionV5Config,
-        squareConfig,
-        squaredDifferenceConfig,
-        divConfig,
-        transposeConfig,
-        maxPoolWithArgmaxConfig,
-        maxConfig,
-      ];
-      for (const kernelConfig of kernelConfigs) {
-        Object(dist["registerKernel"])(kernelConfig);
-      }
-      //# sourceMappingURL=register_all_kernels.js.map
-      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/index.js
-      /**
-       * @license
-       * Copyright 2020 Google LLC. All Rights Reserved.
-       * Licensed under the Apache License, Version 2.0 (the "License");
-       * you may not use this file except in compliance with the License.
-       * You may obtain a copy of the License at
-       *
-       * http://www.apache.org/licenses/LICENSE-2.0
-       *
-       * Unless required by applicable law or agreed to in writing, software
-       * distributed under the License is distributed on an "AS IS" BASIS,
-       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-       * See the License for the specific language governing permissions and
-       * limitations under the License.
-       * =============================================================================
-       */
-
-      // Side effects for default initialization of MathBackendCPU
-      Object(dist["registerBackend"])(
-        "cpu",
-        () => new base["a" /* MathBackendCPU */](),
-        1 /* priority */
-      );
-
-      // All exports from this package should be in base.
-
-      //# sourceMappingURL=index.js.map
-
-      /***/
-    },
-    /* 90 */
-    /***/ function (__webpack_module__, __webpack_exports__, __webpack_require__) {
-      "use strict";
-      // ESM COMPAT FLAG
-      __webpack_require__.r(__webpack_exports__);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs/dist/tf.node.js
-      var tf_node = __webpack_require__(60);
-
-      // EXTERNAL MODULE: ./node_modules/regression/dist/regression.js
-      var regression = __webpack_require__(80);
-
-      // CONCATENATED MODULE: ./src/params.mjs
-      const params = {
-        moveTickSize: 50,
-        videoContainerId: "webgazerVideoContainer",
-        videoElementId: "webgazerVideoFeed",
-        videoElementCanvasId: "webgazerVideoCanvas",
-        faceOverlayId: "webgazerFaceOverlay",
-        faceFeedbackBoxId: "webgazerFaceFeedbackBox",
-        gazeDotId: "webgazerGazeDot",
-        videoViewerWidth: 320,
-        videoViewerHeight: 240,
-        faceFeedbackBoxRatio: 0.66,
-        // View options
-        showVideo: true,
-        mirrorVideo: true,
-        showFaceOverlay: true,
-        showFaceFeedbackBox: true,
-        showGazeDot: true,
-        camConstraints: {
-          video: {
-            width: { min: 320, ideal: 640, max: 1920 },
-            height: { min: 240, ideal: 480, max: 1080 },
-            facingMode: "user",
-          },
-        },
-        dataTimestep: 50,
-        showVideoPreview: true,
-        applyKalmanFilter: true,
-        // Whether or not to store accuracy eigenValues, used by the calibration example file
-        storingPoints: false,
-      };
-
-      /* harmony default export */ var src_params = params;
-
-      // CONCATENATED MODULE: ./src/dom_util.mjs
-      // helper functions
-
-      /**
-       * Provides requestAnimationFrame in a cross browser way.
-       */
-      window.requestAnimFrame = (function () {
-        return (
-          window.requestAnimationFrame ||
-          window.webkitRequestAnimationFrame ||
-          window.mozRequestAnimationFrame ||
-          window.oRequestAnimationFrame ||
-          window.msRequestAnimationFrame ||
-          function (
-            /* function FrameRequestCallback */ callback,
-            /* DOMElement Element */ element
-          ) {
-            return window.setTimeout(callback, 1000 / 60);
-          }
-        );
-      })();
-
-      /**
-       * Provides cancelRequestAnimationFrame in a cross browser way.
-       */
-      window.cancelRequestAnimFrame = (function () {
-        return (
-          window.cancelCancelRequestAnimationFrame ||
-          window.webkitCancelRequestAnimationFrame ||
-          window.mozCancelRequestAnimationFrame ||
-          window.oCancelRequestAnimationFrame ||
-          window.msCancelRequestAnimationFrame ||
-          window.clearTimeout
-        );
-      })();
-
-      // EXTERNAL MODULE: ./node_modules/localforage/dist/localforage.js
-      var localforage = __webpack_require__(32);
-
-      // EXTERNAL MODULE: ./node_modules/@tensorflow-models/facemesh/dist/index.js
-      var dist = __webpack_require__(59);
-
-      // CONCATENATED MODULE: ./src/facemesh.mjs
-
-      /**
-       * Constructor of TFFaceMesh object
-       * @constructor
-       * */
-      const TFFaceMesh = function () {
-        //Backend options are webgl, wasm, and CPU.
-        //For recent laptops WASM is better than WebGL.
-        //TODO: This hack makes loading the model block the UI. We should fix that
-        // this.model = (async () => { return await facemesh.load({"maxFaces":1}) })();
-        this.model = dist.load({ maxFaces: 1 });
-        this.predictionReady = false;
-      };
-
-      // Global variable for face landmark positions array
-      TFFaceMesh.prototype.positionsArray = null;
-
-      /**
-       * Isolates the two patches that correspond to the user's eyes
-       * @param  {Canvas} imageCanvas - canvas corresponding to the webcam stream
-       * @param  {Number} width - of imageCanvas
-       * @param  {Number} height - of imageCanvas
-       * @return {Object} the two eye-patches, first left, then right eye
-       */
-      TFFaceMesh.prototype.getEyePatches = async function (imageCanvas, width, height) {
-        if (imageCanvas.width === 0) {
-          return null;
-        }
-
-        // Load the MediaPipe facemesh model.
-        const model = await this.model;
-
-        // Pass in a video stream (or an image, canvas, or 3D tensor) to obtain an
-        // array of detected faces from the MediaPipe graph.
-        const predictions = await model.estimateFaces(imageCanvas);
-
-        if (predictions.length == 0) {
-          return false;
-        }
-
-        // Save positions to global variable
-        this.positionsArray = predictions[0].scaledMesh;
-        const positions = this.positionsArray;
-
-        // Fit the detected eye in a rectangle. [20200626 xk] not clear which approach is better
-        // https://raw.githubusercontent.com/tensorflow/tfjs-models/master/facemesh/mesh_map.jpg
-
-        // // Maintains a relatively stable shape of the bounding box at the cost of cutting off parts of
-        // // the eye when the eye is tilted.
-        // var leftOriginX = Math.round(positions[130][0]);
-        // var leftOriginY = Math.round(positions[27][1]);
-        // var leftWidth = Math.round(positions[243][0] - leftOriginX);
-        // var leftHeight = Math.round(positions[23][1] - leftOriginY);
-        // var rightOriginX = Math.round(positions[463][0]);
-        // var rightOriginY = Math.round(positions[257][1]);
-        // var rightWidth = Math.round(positions[359][0] - rightOriginX);
-        // var rightHeight = Math.round(positions[253][1] - rightOriginY);
-
-        // Won't really cut off any parts of the eye, at the cost of warping the shape (i.e. height/
-        // width ratio) of the bounding box.
-        var leftOriginX = Math.round(
-          Math.min(positions[247][0], positions[130][0], positions[25][0])
-        );
-        var leftOriginY = Math.round(
-          Math.min(positions[247][1], positions[27][1], positions[190][1])
-        );
-        var leftWidth = Math.round(
-          Math.max(positions[190][0], positions[243][0], positions[233][0]) - leftOriginX
-        );
-        var leftHeight = Math.round(
-          Math.max(positions[25][1], positions[23][1], positions[112][1]) - leftOriginY
-        );
-        var rightOriginX = Math.round(
-          Math.min(positions[414][0], positions[463][0], positions[453][0])
-        );
-        var rightOriginY = Math.round(
-          Math.min(positions[414][1], positions[257][1], positions[467][1])
-        );
-        var rightWidth = Math.round(
-          Math.max(positions[467][0], positions[359][0], positions[255][0]) - rightOriginX
-        );
-        var rightHeight = Math.round(
-          Math.max(positions[341][1], positions[253][1], positions[255][1]) - rightOriginY
-        );
-
-        if (leftWidth === 0 || rightWidth === 0) {
-          console.log("an eye patch had zero width");
-          return null;
-        }
-
-        if (leftHeight === 0 || rightHeight === 0) {
-          console.log("an eye patch had zero height");
-          return null;
-        }
-
-        // Start building object to be returned
-        var eyeObjs = {};
-
-        var leftImageData = imageCanvas
-          .getContext("2d")
-          .getImageData(leftOriginX, leftOriginY, leftWidth, leftHeight);
-        eyeObjs.left = {
-          patch: leftImageData,
-          imagex: leftOriginX,
-          imagey: leftOriginY,
-          width: leftWidth,
-          height: leftHeight,
-        };
-
-        var rightImageData = imageCanvas
-          .getContext("2d")
-          .getImageData(rightOriginX, rightOriginY, rightWidth, rightHeight);
-        eyeObjs.right = {
-          patch: rightImageData,
-          imagex: rightOriginX,
-          imagey: rightOriginY,
-          width: rightWidth,
-          height: rightHeight,
-        };
-
-        this.predictionReady = true;
-
-        return eyeObjs;
-      };
-
-      /**
-       * Returns the positions array corresponding to the last call to getEyePatches.
-       * Requires that getEyePatches() was called previously, else returns null.
-       */
-      TFFaceMesh.prototype.getPositions = function () {
-        return this.positionsArray;
-      };
-
-      /**
-       * Reset the tracker to default values
-       */
-      TFFaceMesh.prototype.reset = function () {
-        console.log("Unimplemented; Tracking.js has no obvious reset function");
-      };
-
-      /**
-       * Draw TF_FaceMesh_Overlay
-       */
-      TFFaceMesh.prototype.drawFaceOverlay = function (ctx, keypoints) {
-        // If keypoints is falsy, don't do anything
-        if (keypoints) {
-          ctx.fillStyle = "#32EEDB";
-          ctx.strokeStyle = "#32EEDB";
-          ctx.lineWidth = 0.5;
-
-          for (let i = 0; i < keypoints.length; i++) {
-            const x = keypoints[i][0];
-            const y = keypoints[i][1];
-
-            ctx.beginPath();
-            ctx.arc(x, y, 1 /* radius */, 0, 2 * Math.PI);
-            ctx.closePath();
-            ctx.fill();
-          }
-        }
-      };
-
-      /**
-       * The TFFaceMesh object name
-       * @type {string}
-       */
-      TFFaceMesh.prototype.name = "TFFaceMesh";
-
-      /* harmony default export */ var facemesh = TFFaceMesh;
-
-      // EXTERNAL MODULE: ./node_modules/numeric/numeric-1.2.6.js
-      var numeric_1_2_6 = __webpack_require__(12);
-
-      // CONCATENATED MODULE: ./src/mat.mjs
-      const mat = {};
-      /**
-       * Transposes an mxn array
-       * @param {Array.<Array.<Number>>} matrix - of 'M x N' dimensionality
-       * @return {Array.<Array.<Number>>} transposed matrix
-       */
-      mat.transpose = function (matrix) {
-        var m = matrix.length;
-        var n = matrix[0].length;
-        var transposedMatrix = new Array(n);
-
-        for (var i = 0; i < m; i++) {
-          for (var j = 0; j < n; j++) {
-            if (i === 0) transposedMatrix[j] = new Array(m);
-            transposedMatrix[j][i] = matrix[i][j];
-          }
-        }
-
-        return transposedMatrix;
-      };
-
-      /**
-       * Get a sub-matrix of matrix
-       * @param {Array.<Array.<Number>>} matrix - original matrix
-       * @param {Array.<Number>} r - Array of row indices
-       * @param {Number} j0 - Initial column index
-       * @param {Number} j1 - Final column index
-       * @returns {Array} The sub-matrix matrix(r(:),j0:j1)
-       */
-      mat.getMatrix = function (matrix, r, j0, j1) {
-        var X = new Array(r.length),
-          m = j1 - j0 + 1;
-
-        for (var i = 0; i < r.length; i++) {
-          X[i] = new Array(m);
-          for (var j = j0; j <= j1; j++) {
-            X[i][j - j0] = matrix[r[i]][j];
-          }
-        }
-        return X;
-      };
-
-      /**
-       * Get a submatrix of matrix
-       * @param {Array.<Array.<Number>>} matrix - original matrix
-       * @param {Number} i0 - Initial row index
-       * @param {Number} i1 - Final row index
-       * @param {Number} j0 - Initial column index
-       * @param {Number} j1 - Final column index
-       * @return {Array} The sub-matrix matrix(i0:i1,j0:j1)
-       */
-      mat.getSubMatrix = function (matrix, i0, i1, j0, j1) {
-        var size = j1 - j0 + 1,
-          X = new Array(i1 - i0 + 1);
-
-        for (var i = i0; i <= i1; i++) {
-          var subI = i - i0;
-
-          X[subI] = new Array(size);
-
-          for (var j = j0; j <= j1; j++) {
-            X[subI][j - j0] = matrix[i][j];
-          }
-        }
-        return X;
-      };
-
-      /**
-       * Linear algebraic matrix multiplication, matrix1 * matrix2
-       * @param {Array.<Array.<Number>>} matrix1
-       * @param {Array.<Array.<Number>>} matrix2
-       * @return {Array.<Array.<Number>>} Matrix product, matrix1 * matrix2
-       */
-      mat.mult = function (matrix1, matrix2) {
-        if (matrix2.length != matrix1[0].length) {
-          console.log("Matrix inner dimensions must agree:");
-        }
-
-        var X = new Array(matrix1.length),
-          Bcolj = new Array(matrix1[0].length);
-
-        for (var j = 0; j < matrix2[0].length; j++) {
-          for (var k = 0; k < matrix1[0].length; k++) {
-            Bcolj[k] = matrix2[k][j];
-          }
-          for (var i = 0; i < matrix1.length; i++) {
-            if (j === 0) X[i] = new Array(matrix2[0].length);
-
-            var Arowi = matrix1[i];
-            var s = 0;
-            for (var k = 0; k < matrix1[0].length; k++) {
-              s += Arowi[k] * Bcolj[k];
-            }
-            X[i][j] = s;
-          }
-        }
-        return X;
-      };
-
-      /**
-       * LUDecomposition to solve A*X = B, based on WEKA code
-       * @param {Array.<Array.<Number>>} A - left matrix of equation to be solved
-       * @param {Array.<Array.<Number>>} B - right matrix of equation to be solved
-       * @return {Array.<Array.<Number>>} X so that L*U*X = B(piv,:)
-       */
-      mat.LUDecomposition = function (A, B) {
-        var LU = new Array(A.length);
-
-        for (var i = 0; i < A.length; i++) {
-          LU[i] = new Array(A[0].length);
-          for (var j = 0; j < A[0].length; j++) {
-            LU[i][j] = A[i][j];
-          }
-        }
-
-        var m = A.length;
-        var n = A[0].length;
-        var piv = new Array(m);
-        for (var i = 0; i < m; i++) {
-          piv[i] = i;
-        }
-        var pivsign = 1;
-        var LUrowi = new Array();
-        var LUcolj = new Array(m);
-        // Outer loop.
-        for (var j = 0; j < n; j++) {
-          // Make a copy of the j-th column to localize references.
-          for (var i = 0; i < m; i++) {
-            LUcolj[i] = LU[i][j];
-          }
-          // Apply previous transformations.
-          for (var i = 0; i < m; i++) {
-            LUrowi = LU[i];
-            // Most of the time is spent in the following dot product.
-            var kmax = Math.min(i, j);
-            var s = 0;
-            for (var k = 0; k < kmax; k++) {
-              s += LUrowi[k] * LUcolj[k];
-            }
-            LUrowi[j] = LUcolj[i] -= s;
-          }
-          // Find pivot and exchange if necessary.
-          var p = j;
-          for (var i = j + 1; i < m; i++) {
-            if (Math.abs(LUcolj[i]) > Math.abs(LUcolj[p])) {
-              p = i;
-            }
-          }
-          if (p != j) {
-            for (var k = 0; k < n; k++) {
-              var t = LU[p][k];
-              LU[p][k] = LU[j][k];
-              LU[j][k] = t;
-            }
-            var k = piv[p];
-            piv[p] = piv[j];
-            piv[j] = k;
-            pivsign = -pivsign;
-          }
-          // Compute multipliers.
-          if ((j < m) & (LU[j][j] != 0)) {
-            for (var i = j + 1; i < m; i++) {
-              LU[i][j] /= LU[j][j];
-            }
-          }
-        }
-        if (B.length != m) {
-          console.log("Matrix row dimensions must agree.");
-        }
-        for (var j = 0; j < n; j++) {
-          if (LU[j][j] === 0) {
-            console.log("Matrix is singular.");
-          }
-        }
-        var nx = B[0].length;
-        var X = self.webgazer.mat.getMatrix(B, piv, 0, nx - 1);
-        // Solve L*Y = B(piv,:)
-        for (var k = 0; k < n; k++) {
-          for (var i = k + 1; i < n; i++) {
-            for (var j = 0; j < nx; j++) {
-              X[i][j] -= X[k][j] * LU[i][k];
-            }
-          }
-        }
-        // Solve U*X = Y;
-        for (var k = n - 1; k >= 0; k--) {
-          for (var j = 0; j < nx; j++) {
-            X[k][j] /= LU[k][k];
-          }
-          for (var i = 0; i < k; i++) {
-            for (var j = 0; j < nx; j++) {
-              X[i][j] -= X[k][j] * LU[i][k];
-            }
-          }
-        }
-        return X;
-      };
-
-      /**
-       * Least squares solution of A*X = B, based on WEKA code
-       * @param {Array.<Array.<Number>>} A - left side matrix to be solved
-       * @param {Array.<Array.<Number>>} B - a matrix with as many rows as A and any number of columns.
-       * @return {Array.<Array.<Number>>} X - that minimizes the two norms of QR*X-B.
-       */
-      mat.QRDecomposition = function (A, B) {
-        // Initialize.
-        var QR = new Array(A.length);
-
-        for (var i = 0; i < A.length; i++) {
-          QR[i] = new Array(A[0].length);
-          for (var j = 0; j < A[0].length; j++) {
-            QR[i][j] = A[i][j];
-          }
-        }
-        var m = A.length;
-        var n = A[0].length;
-        var Rdiag = new Array(n);
-        var nrm;
-
-        // Main loop.
-        for (var k = 0; k < n; k++) {
-          // Compute 2-norm of k-th column without under/overflow.
-          nrm = 0;
-          for (var i = k; i < m; i++) {
-            nrm = Math.hypot(nrm, QR[i][k]);
-          }
-          if (nrm != 0) {
-            // Form k-th Householder vector.
-            if (QR[k][k] < 0) {
-              nrm = -nrm;
-            }
-            for (var i = k; i < m; i++) {
-              QR[i][k] /= nrm;
-            }
-            QR[k][k] += 1;
-
-            // Apply transformation to remaining columns.
-            for (var j = k + 1; j < n; j++) {
-              var s = 0;
-              for (var i = k; i < m; i++) {
-                s += QR[i][k] * QR[i][j];
-              }
-              s = -s / QR[k][k];
-              for (var i = k; i < m; i++) {
-                QR[i][j] += s * QR[i][k];
-              }
-            }
-          }
-          Rdiag[k] = -nrm;
-        }
-        if (B.length != m) {
-          console.log("Matrix row dimensions must agree.");
-        }
-        for (var j = 0; j < n; j++) {
-          if (Rdiag[j] === 0) console.log("Matrix is rank deficient");
-        }
-        // Copy right hand side
-        var nx = B[0].length;
-        var X = new Array(B.length);
-        for (var i = 0; i < B.length; i++) {
-          X[i] = new Array(B[0].length);
-        }
-        for (var i = 0; i < B.length; i++) {
-          for (var j = 0; j < B[0].length; j++) {
-            X[i][j] = B[i][j];
-          }
-        }
-        // Compute Y = transpose(Q)*B
-        for (var k = 0; k < n; k++) {
-          for (var j = 0; j < nx; j++) {
-            var s = 0.0;
-            for (var i = k; i < m; i++) {
-              s += QR[i][k] * X[i][j];
-            }
-            s = -s / QR[k][k];
-            for (var i = k; i < m; i++) {
-              X[i][j] += s * QR[i][k];
-            }
-          }
-        }
-        // Solve R*X = Y;
-        for (var k = n - 1; k >= 0; k--) {
-          for (var j = 0; j < nx; j++) {
-            X[k][j] /= Rdiag[k];
-          }
-          for (var i = 0; i < k; i++) {
-            for (var j = 0; j < nx; j++) {
-              X[i][j] -= X[k][j] * QR[i][k];
-            }
-          }
-        }
-        return mat.getSubMatrix(X, 0, n - 1, 0, nx - 1);
-      };
-
-      /* harmony default export */ var src_mat = mat;
-
-      // CONCATENATED MODULE: ./src/util.mjs
-
-      const util = {};
-
-      /**
-       * Eye class, represents an eye patch detected in the video stream
-       * @param {ImageData} patch - the image data corresponding to an eye
-       * @param {Number} imagex - x-axis offset from the top-left corner of the video canvas
-       * @param {Number} imagey - y-axis offset from the top-left corner of the video canvas
-       * @param {Number} width  - width of the eye patch
-       * @param {Number} height - height of the eye patch
-       */
-
-      var resizeWidth = 10;
-      var resizeHeight = 6;
-
-      util.Eye = function (patch, imagex, imagey, width, height) {
-        this.patch = patch;
-        this.imagex = imagex;
-        this.imagey = imagey;
-        this.width = width;
-        this.height = height;
-      };
-
-      util.getEyeFeats = function (eyes) {
-        var resizedLeft = this.resizeEye(eyes.left, resizeHeight, resizeHeight);
-        var resizedright = this.resizeEye(eyes.right, resizeHeight, resizeHeight);
-
-        var leftGray = this.grayscale(resizedLeft.data, resizedLeft.width, resizedLeft.height);
-        var rightGray = this.grayscale(resizedright.data, resizedright.width, resizedright.height);
-
-        var histLeft = [];
-        this.equalizeHistogram(leftGray, 5, histLeft);
-        var histRight = [];
-        this.equalizeHistogram(rightGray, 5, histRight);
-
-        var leftGrayArray = Array.prototype.slice.call(histLeft);
-        var rightGrayArray = Array.prototype.slice.call(histRight);
-
-        return leftGrayArray.concat(rightGrayArray);
-      };
-      //Data Window class
-      //operates like an array but 'wraps' data around to keep the array at a fixed windowSize
-      /**
-       * DataWindow class - Operates like an array, but 'wraps' data around to keep the array at a fixed windowSize
-       * @param {Number} windowSize - defines the maximum size of the window
-       * @param {Array} data - optional data to seed the DataWindow with
-       **/
-      util.DataWindow = function (windowSize, data) {
-        this.data = [];
-        this.windowSize = windowSize;
-        this.index = 0;
-        this.length = 0;
-        if (data) {
-          this.data = data.slice(data.length - windowSize, data.length);
-          this.length = this.data.length;
-        }
-      };
-
-      /**
-       * [push description]
-       * @param  {*} entry - item to be inserted. It either grows the DataWindow or replaces the oldest item
-       * @return {DataWindow} this
-       */
-      util.DataWindow.prototype.push = function (entry) {
-        if (this.data.length < this.windowSize) {
-          this.data.push(entry);
-          this.length = this.data.length;
-          return this;
-        }
-
-        //replace oldest entry by wrapping around the DataWindow
-        this.data[this.index] = entry;
-        this.index = (this.index + 1) % this.windowSize;
-        return this;
-      };
-
-      /**
-       * Get the element at the ind position by wrapping around the DataWindow
-       * @param  {Number} ind index of desired entry
-       * @return {*}
-       */
-      util.DataWindow.prototype.get = function (ind) {
-        return this.data[this.getTrueIndex(ind)];
-      };
-
-      /**
-       * Gets the true this.data array index given an index for a desired element
-       * @param {Number} ind - index of desired entry
-       * @return {Number} index of desired entry in this.data
-       */
-      util.DataWindow.prototype.getTrueIndex = function (ind) {
-        if (this.data.length < this.windowSize) {
-          return ind;
-        } else {
-          //wrap around ind so that we can traverse from oldest to newest
-          return (ind + this.index) % this.windowSize;
-        }
-      };
-
-      /**
-       * Append all the contents of data
-       * @param {Array} data - to be inserted
-       */
-      util.DataWindow.prototype.addAll = function (data) {
-        for (var i = 0; i < data.length; i++) {
-          this.push(data[i]);
-        }
-      };
-
-      //Helper functions
-      /**
-       * Grayscales an image patch. Can be used for the whole canvas, detected face, detected eye, etc.
-       *
-       * Code from tracking.js by Eduardo Lundgren, et al.
-       * https://github.com/eduardolundgren/tracking.js/blob/master/src/tracking.js
-       *
-       * Software License Agreement (BSD License) Copyright (c) 2014, Eduardo A. Lundgren Melo. All rights reserved.
-       * Redistribution and use of this software in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-       * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
-       * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
-       * The name of Eduardo A. Lundgren Melo may not be used to endorse or promote products derived from this software without specific prior written permission of Eduardo A. Lundgren Melo.
-       * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
-       * IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
-       * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
-       * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-       *
-       * @param  {Array} pixels - image data to be grayscaled
-       * @param  {Number} width  - width of image data to be grayscaled
-       * @param  {Number} height - height of image data to be grayscaled
-       * @return {Array} grayscaledImage
-       */
-      util.grayscale = function (pixels, width, height) {
-        var gray = new Uint8ClampedArray(pixels.length >> 2);
-        var p = 0;
-        var w = 0;
-        for (var i = 0; i < height; i++) {
-          for (var j = 0; j < width; j++) {
-            var value = pixels[w] * 0.299 + pixels[w + 1] * 0.587 + pixels[w + 2] * 0.114;
-            gray[p++] = value;
-
-            w += 4;
-          }
-        }
-        return gray;
-      };
-
-      /**
-       * Increase contrast of an image.
-       *
-       * Code from Martin Tschirsich, Copyright (c) 2012.
-       * https://github.com/mtschirs/js-objectdetect/blob/gh-pages/js/objectdetect.js
-       *
-       * @param {Array} src - grayscale integer array
-       * @param {Number} step - sampling rate, control performance
-       * @param {Array} dst - array to hold the resulting image
-       */
-      util.equalizeHistogram = function (src, step, dst) {
-        var srcLength = src.length;
-        if (!dst) dst = src;
-        if (!step) step = 5;
-
-        // Compute histogram and histogram sum:
-        var hist = [
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-        ];
-
-        for (var i = 0; i < srcLength; i += step) {
-          ++hist[src[i]];
-        }
-
-        // Compute integral histogram:
-        var norm = (255 * step) / srcLength,
-          prev = 0;
-        for (var i = 0; i < 256; ++i) {
-          var h = hist[i];
-          prev = h += prev;
-          hist[i] = h * norm; // For non-integer src: ~~(h * norm + 0.5);
-        }
-
-        // Equalize image:
-        for (var i = 0; i < srcLength; ++i) {
-          dst[i] = hist[src[i]];
-        }
-        return dst;
-      };
-
-      util.threshold = function (data, threshold) {
-        for (let i = 0; i < data.length; i++) {
-          data[i] = data[i] > threshold ? 255 : 0;
-        }
-        return data;
-      };
-
-      util.correlation = function (data1, data2) {
-        const length = Math.min(data1.length, data2.length);
-        let count = 0;
-        for (let i = 0; i < length; i++) {
-          if (data1[i] === data2[i]) {
-            count++;
-          }
-        }
-        return count / Math.max(data1.length, data2.length);
-      };
-
-      /**
-       * Gets an Eye object and resizes it to the desired resolution
-       * @param  {webgazer.util.Eye} eye - patch to be resized
-       * @param  {Number} resizeWidth - desired width
-       * @param  {Number} resizeHeight - desired height
-       * @return {webgazer.util.Eye} resized eye patch
-       */
-      util.resizeEye = function (eye, resizeWidth, resizeHeight) {
-        var canvas = document.createElement("canvas");
-        canvas.width = eye.width;
-        canvas.height = eye.height;
-
-        canvas.getContext("2d").putImageData(eye.patch, 0, 0);
-
-        var tempCanvas = document.createElement("canvas");
-
-        tempCanvas.width = resizeWidth;
-        tempCanvas.height = resizeHeight;
-
-        // save the canvas into temp canvas
-        tempCanvas
-          .getContext("2d")
-          .drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, resizeWidth, resizeHeight);
-
-        return tempCanvas.getContext("2d").getImageData(0, 0, resizeWidth, resizeHeight);
-      };
-
-      /**
-       * Checks if the prediction is within the boundaries of the viewport and constrains it
-       * @param  {Array} prediction [x,y] - predicted gaze coordinates
-       * @return {Array} constrained coordinates
-       */
-      util.bound = function (prediction) {
-        if (prediction.x < 0) prediction.x = 0;
-        if (prediction.y < 0) prediction.y = 0;
-        var w = Math.max(document.documentElement.clientWidth, window.innerWidth || 0);
-        var h = Math.max(document.documentElement.clientHeight, window.innerHeight || 0);
-        if (prediction.x > w) {
-          prediction.x = w;
-        }
-
-        if (prediction.y > h) {
-          prediction.y = h;
-        }
-        return prediction;
-      };
-
-      /**
-       * Write statistics in debug paragraph panel
-       * @param {HTMLElement} para - The <p> tag where write data
-       * @param {Object} stats - The stats data to output
-       */
-      function debugBoxWrite(para, stats) {
-        var str = "";
-        for (var key in stats) {
-          str += key + ": " + stats[key] + "\n";
-        }
-        para.innerText = str;
-      }
-
-      /**
-       * Constructor of DebugBox object,
-       * it insert an paragraph inside a div to the body, in view to display debug data
-       * @param {Number} interval - The log interval
-       * @constructor
-       */
-      util.DebugBox = function (interval) {
-        this.para = document.createElement("p");
-        this.div = document.createElement("div");
-        this.div.appendChild(this.para);
-        document.body.appendChild(this.div);
-
-        this.buttons = {};
-        this.canvas = {};
-        this.stats = {};
-        var updateInterval = interval || 300;
-        (function (localThis) {
-          setInterval(function () {
-            debugBoxWrite(localThis.para, localThis.stats);
-          }, updateInterval);
-        })(this);
-      };
-
-      /**
-       * Add stat data for log
-       * @param {String} key - The data key
-       * @param {*} value - The value
-       */
-      util.DebugBox.prototype.set = function (key, value) {
-        this.stats[key] = value;
-      };
-
-      /**
-       * Initialize stats in case where key does not exist, else
-       * increment value for key
-       * @param {String} key - The key to process
-       * @param {Number} incBy - Value to increment for given key (default: 1)
-       * @param {Number} init - Initial value in case where key does not exist (default: 0)
-       */
-      util.DebugBox.prototype.inc = function (key, incBy, init) {
-        if (!this.stats[key]) {
-          this.stats[key] = init || 0;
-        }
-        this.stats[key] += incBy || 1;
-      };
-
-      /**
-       * Create a button and register the given function to the button click event
-       * @param {String} name - The button name to link
-       * @param {Function} func - The onClick callback
-       */
-      util.DebugBox.prototype.addButton = function (name, func) {
-        if (!this.buttons[name]) {
-          this.buttons[name] = document.createElement("button");
-          this.div.appendChild(this.buttons[name]);
-        }
-        var button = this.buttons[name];
-        this.buttons[name] = button;
-        button.addEventListener("click", func);
-        button.innerText = name;
-      };
-
-      /**
-       * Search for a canvas elemenet with name, or create on if not exist.
-       * Then send the canvas element as callback parameter.
-       * @param {String} name - The canvas name to send/create
-       * @param {Function} func - The callback function where send canvas
-       */
-      util.DebugBox.prototype.show = function (name, func) {
-        if (!this.canvas[name]) {
-          this.canvas[name] = document.createElement("canvas");
-          this.div.appendChild(this.canvas[name]);
-        }
-        var canvas = this.canvas[name];
-        canvas.getContext("2d").clearRect(0, 0, canvas.width, canvas.height);
-        func(canvas);
-      };
-
-      /**
-       * Kalman Filter constructor
-       * Kalman filters work by reducing the amount of noise in a models.
-       * https://blog.cordiner.net/2011/05/03/object-tracking-using-a-kalman-filter-matlab/
-       *
-       * @param {Array.<Array.<Number>>} F - transition matrix
-       * @param {Array.<Array.<Number>>} Q - process noise matrix
-       * @param {Array.<Array.<Number>>} H - maps between measurement vector and noise matrix
-       * @param {Array.<Array.<Number>>} R - defines measurement error of the device
-       * @param {Array} P_initial - the initial state
-       * @param {Array} X_initial - the initial state of the device
-       */
-      util.KalmanFilter = function (F, H, Q, R, P_initial, X_initial) {
-        this.F = F; // State transition matrix
-        this.Q = Q; // Process noise matrix
-        this.H = H; // Transformation matrix
-        this.R = R; // Measurement Noise
-        this.P = P_initial; //Initial covariance matrix
-        this.X = X_initial; //Initial guess of measurement
-      };
-
-      /**
-       * Get Kalman next filtered value and update the internal state
-       * @param {Array} z - the new measurement
-       * @return {Array}
-       */
-      util.KalmanFilter.prototype.update = function (z) {
-        // Here, we define all the different matrix operations we will need
-        var add = numeric.add,
-          sub = numeric.sub,
-          inv = numeric.inv,
-          identity = numeric.identity;
-        var mult = src_mat.mult,
-          transpose = src_mat.transpose;
-        //TODO cache variables like the transpose of H
-
-        // prediction: X = F * X  |  P = F * P * F' + Q
-        var X_p = mult(this.F, this.X); //Update state vector
-        var P_p = add(mult(mult(this.F, this.P), transpose(this.F)), this.Q); //Predicted covaraince
-
-        //Calculate the update values
-        var y = sub(z, mult(this.H, X_p)); // This is the measurement error (between what we expect and the actual value)
-        var S = add(mult(mult(this.H, P_p), transpose(this.H)), this.R); //This is the residual covariance (the error in the covariance)
-
-        // kalman multiplier: K = P * H' * (H * P * H' + R)^-1
-        var K = mult(P_p, mult(transpose(this.H), inv(S))); //This is the Optimal Kalman Gain
-
-        //We need to change Y into it's column vector form
-        for (var i = 0; i < y.length; i++) {
-          y[i] = [y[i]];
-        }
-
-        //Now we correct the internal values of the model
-        // correction: X = X + K * (m - H * X)  |  P = (I - K * H) * P
-        this.X = add(X_p, mult(K, y));
-        this.P = mult(sub(identity(K.length), mult(K, this.H)), P_p);
-        return transpose(mult(this.H, this.X))[0]; //Transforms the predicted state back into it's measurement form
-      };
-
-      /* harmony default export */ var src_util = util;
-
-      // CONCATENATED MODULE: ./src/ridgeReg.mjs
-
-      const ridgeReg_reg = {};
-      var ridgeParameter = Math.pow(10, -5);
-      var dataWindow = 700;
-      var trailDataWindow = 10;
-
-      /**
-       * Performs ridge regression, according to the Weka code.
-       * @param {Array} y - corresponds to screen coordinates (either x or y) for each of n click events
-       * @param {Array.<Array.<Number>>} X - corresponds to gray pixel features (120 pixels for both eyes) for each of n clicks
-       * @param {Array} k - ridge parameter
-       * @return{Array} regression coefficients
-       */
-      function ridge(y, X, k) {
-        var nc = X[0].length;
-        var m_Coefficients = new Array(nc);
-        var xt = src_mat.transpose(X);
-        var solution = new Array();
-        var success = true;
-        do {
-          var ss = src_mat.mult(xt, X);
-          // Set ridge regression adjustment
-          for (var i = 0; i < nc; i++) {
-            ss[i][i] = ss[i][i] + k;
-          }
-
-          // Carry out the regression
-          var bb = src_mat.mult(xt, y);
-          for (var i = 0; i < nc; i++) {
-            m_Coefficients[i] = bb[i][0];
-          }
-          try {
-            var n = m_Coefficients.length !== 0 ? m_Coefficients.length / m_Coefficients.length : 0;
-            if (m_Coefficients.length * n !== m_Coefficients.length) {
-              console.log("Array length must be a multiple of m");
-            }
-            solution =
-              ss.length === ss[0].length
-                ? numeric_1_2_6.LUsolve(numeric_1_2_6.LU(ss, true), bb)
-                : src_mat.QRDecomposition(ss, bb);
-
-            for (var i = 0; i < nc; i++) {
-              m_Coefficients[i] = solution[i];
-            }
-            success = true;
-          } catch (ex) {
-            k *= 10;
-            console.log(ex);
-            success = false;
-          }
-        } while (!success);
-        return m_Coefficients;
-      }
-
-      //TODO: still usefull ???
-      /**
-       *
-       * @returns {Number}
-       */
-      function getCurrentFixationIndex() {
-        var index = 0;
-        var recentX = this.screenXTrailArray.get(0);
-        var recentY = this.screenYTrailArray.get(0);
-        for (var i = this.screenXTrailArray.length - 1; i >= 0; i--) {
-          var currX = this.screenXTrailArray.get(i);
-          var currY = this.screenYTrailArray.get(i);
-          var euclideanDistance = Math.sqrt(
-            Math.pow(currX - recentX, 2) + Math.pow(currY - recentY, 2)
-          );
-          if (euclideanDistance > 72) {
-            return i + 1;
-          }
-        }
-        return i;
-      }
-
-      /**
-       * Constructor of RidgeReg object,
-       * this object allow to perform ridge regression
-       * @constructor
-       */
-      ridgeReg_reg.RidgeReg = function () {
-        this.init();
-      };
-
-      /**
-       * Initialize new arrays and initialize Kalman filter.
-       */
-      ridgeReg_reg.RidgeReg.prototype.init = function () {
-        this.screenXClicksArray = new src_util.DataWindow(dataWindow);
-        this.screenYClicksArray = new src_util.DataWindow(dataWindow);
-        this.eyeFeaturesClicks = new src_util.DataWindow(dataWindow);
-
-        //sets to one second worth of cursor trail
-        this.trailTime = 1000;
-        this.trailDataWindow = this.trailTime / src_params.moveTickSize;
-        this.screenXTrailArray = new src_util.DataWindow(trailDataWindow);
-        this.screenYTrailArray = new src_util.DataWindow(trailDataWindow);
-        this.eyeFeaturesTrail = new src_util.DataWindow(trailDataWindow);
-        this.trailTimes = new src_util.DataWindow(trailDataWindow);
-
-        this.dataClicks = new src_util.DataWindow(dataWindow);
-        this.dataTrail = new src_util.DataWindow(trailDataWindow);
-
-        // Initialize Kalman filter [20200608 xk] what do we do about parameters?
-        // [20200611 xk] unsure what to do w.r.t. dimensionality of these matrices. So far at least
-        //               by my own anecdotal observation a 4x1 x vector seems to work alright
-        var F = [
-          [1, 0, 1, 0],
-          [0, 1, 0, 1],
-          [0, 0, 1, 0],
-          [0, 0, 0, 1],
-        ];
-
-        //Parameters Q and R may require some fine tuning
-        var Q = [
-          [1 / 4, 0, 1 / 2, 0],
-          [0, 1 / 4, 0, 1 / 2],
-          [1 / 2, 0, 1, 0],
-          [0, 1 / 2, 0, 1],
-        ]; // * delta_t
-        var delta_t = 1 / 10; // The amount of time between frames
-        Q = numeric_1_2_6.mul(Q, delta_t);
-
-        var H = [
-          [1, 0, 0, 0, 0, 0],
-          [0, 1, 0, 0, 0, 0],
-          [0, 0, 1, 0, 0, 0],
-          [0, 0, 0, 1, 0, 0],
-        ];
-        var H = [
-          [1, 0, 0, 0],
-          [0, 1, 0, 0],
-        ];
-        var pixel_error = 47; //We will need to fine tune this value [20200611 xk] I just put a random value here
-
-        //This matrix represents the expected measurement error
-        var R = numeric_1_2_6.mul(numeric_1_2_6.identity(2), pixel_error);
-
-        var P_initial = numeric_1_2_6.mul(numeric_1_2_6.identity(4), 0.0001); //Initial covariance matrix
-        var x_initial = [[500], [500], [0], [0]]; // Initial measurement matrix
-
-        this.kalman = new src_util.KalmanFilter(F, H, Q, R, P_initial, x_initial);
-      };
-
-      /**
-       * Add given data from eyes
-       * @param {Object} eyes - eyes where extract data to add
-       * @param {Object} screenPos - The current screen point
-       * @param {Object} type - The type of performed action
-       */
-      ridgeReg_reg.RidgeReg.prototype.addData = function (eyes, screenPos, type) {
-        if (!eyes) {
-          return;
-        }
-        //not doing anything with blink at present
-        // if (eyes.left.blink || eyes.right.blink) {
-        //   return;
-        // }
-        //why are we pushing these as arrays rather than single elements?
-        if (type === "click") {
-          this.screenXClicksArray.push([screenPos[0]]);
-          this.screenYClicksArray.push([screenPos[1]]);
-
-          this.eyeFeaturesClicks.push(src_util.getEyeFeats(eyes));
-          this.dataClicks.push({ eyes: eyes, screenPos: screenPos, type: type });
-        } else if (type === "move") {
-          this.screenXTrailArray.push([screenPos[0]]);
-          this.screenYTrailArray.push([screenPos[1]]);
-
-          this.eyeFeaturesTrail.push(src_util.getEyeFeats(eyes));
-          this.trailTimes.push(performance.now());
-          this.dataTrail.push({ eyes: eyes, screenPos: screenPos, type: type });
-        }
-
-        // [20180730 JT] Why do we do this? It doesn't return anything...
-        // But as JS is pass by reference, it still affects it.
-        //
-        // Causes problems for when we want to call 'addData' twice in a row on the same object, but perhaps with different screenPos or types (think multiple interactions within one video frame)
-        //eyes.left.patch = Array.from(eyes.left.patch.data);
-        //eyes.right.patch = Array.from(eyes.right.patch.data);
-      };
-
-      /**
-       * Try to predict coordinates from pupil data
-       * after apply linear regression on data set
-       * @param {Object} eyesObj - The current user eyes object
-       * @returns {Object}
-       */
-      ridgeReg_reg.RidgeReg.prototype.predict = function (eyesObj) {
-        if (!eyesObj || this.eyeFeaturesClicks.length === 0) {
-          return null;
-        }
-        var acceptTime = performance.now() - this.trailTime;
-        var trailX = [];
-        var trailY = [];
-        var trailFeat = [];
-        for (var i = 0; i < this.trailDataWindow; i++) {
-          if (this.trailTimes.get(i) > acceptTime) {
-            trailX.push(this.screenXTrailArray.get(i));
-            trailY.push(this.screenYTrailArray.get(i));
-            trailFeat.push(this.eyeFeaturesTrail.get(i));
-          }
-        }
-
-        var screenXArray = this.screenXClicksArray.data.concat(trailX);
-        var screenYArray = this.screenYClicksArray.data.concat(trailY);
-        var eyeFeatures = this.eyeFeaturesClicks.data.concat(trailFeat);
-
-        var coefficientsX = ridge(screenXArray, eyeFeatures, ridgeParameter);
-        var coefficientsY = ridge(screenYArray, eyeFeatures, ridgeParameter);
-
-        var eyeFeats = src_util.getEyeFeats(eyesObj);
-        var predictedX = 0;
-        for (var i = 0; i < eyeFeats.length; i++) {
-          predictedX += eyeFeats[i] * coefficientsX[i];
-        }
-        var predictedY = 0;
-        for (var i = 0; i < eyeFeats.length; i++) {
-          predictedY += eyeFeats[i] * coefficientsY[i];
-        }
-
-        predictedX = Math.floor(predictedX);
-        predictedY = Math.floor(predictedY);
-
-        if (src_params.applyKalmanFilter) {
-          // Update Kalman model, and get prediction
-          var newGaze = [predictedX, predictedY]; // [20200607 xk] Should we use a 1x4 vector?
-          newGaze = this.kalman.update(newGaze);
-
-          return {
-            x: newGaze[0],
-            y: newGaze[1],
-          };
-        } else {
-          return {
-            x: predictedX,
-            y: predictedY,
-          };
-        }
-      };
-
-      /**
-       * Add given data to current data set then,
-       * replace current data member with given data
-       * @param {Array.<Object>} data - The data to set
-       */
-      ridgeReg_reg.RidgeReg.prototype.setData = function (data) {
-        for (var i = 0; i < data.length; i++) {
-          // Clone data array
-          var leftData = new Uint8ClampedArray(data[i].eyes.left.patch.data);
-          var rightData = new Uint8ClampedArray(data[i].eyes.right.patch.data);
-          // Duplicate ImageData object
-          data[i].eyes.left.patch = new ImageData(
-            leftData,
-            data[i].eyes.left.width,
-            data[i].eyes.left.height
-          );
-          data[i].eyes.right.patch = new ImageData(
-            rightData,
-            data[i].eyes.right.width,
-            data[i].eyes.right.height
-          );
-
-          // Add those data objects to model
-          this.addData(data[i].eyes, data[i].screenPos, data[i].type);
-        }
-      };
-
-      /**
-       * Return the data
-       * @returns {Array.<Object>|*}
-       */
-      ridgeReg_reg.RidgeReg.prototype.getData = function () {
-        return this.dataClicks.data;
-      };
-
-      /**
-       * The RidgeReg object name
-       * @type {string}
-       */
-      ridgeReg_reg.RidgeReg.prototype.name = "ridge";
-
-      /* harmony default export */ var ridgeReg = ridgeReg_reg;
-
-      // CONCATENATED MODULE: ./src/ridgeWeightedReg.mjs
-
-      const ridgeWeightedReg_reg = {};
-
-      var ridgeWeightedReg_ridgeParameter = Math.pow(10, -5);
-      var ridgeWeightedReg_dataWindow = 700;
-      var ridgeWeightedReg_trailDataWindow = 10;
-
-      /**
-       * Performs ridge regression, according to the Weka code.
-       * @param {Array} y - corresponds to screen coordinates (either x or y) for each of n click events
-       * @param {Array.<Array.<Number>>} X - corresponds to gray pixel features (120 pixels for both eyes) for each of n clicks
-       * @param {Array} k - ridge parameter
-       * @return{Array} regression coefficients
-       */
-      function ridgeWeightedReg_ridge(y, X, k) {
-        var nc = X[0].length;
-        var m_Coefficients = new Array(nc);
-        var xt = src_mat.transpose(X);
-        var solution = new Array();
-        var success = true;
-        do {
-          var ss = src_mat.mult(xt, X);
-          // Set ridge regression adjustment
-          for (var i = 0; i < nc; i++) {
-            ss[i][i] = ss[i][i] + k;
-          }
-
-          // Carry out the regression
-          var bb = src_mat.mult(xt, y);
-          for (var i = 0; i < nc; i++) {
-            m_Coefficients[i] = bb[i][0];
-          }
-          try {
-            var n = m_Coefficients.length !== 0 ? m_Coefficients.length / m_Coefficients.length : 0;
-            if (m_Coefficients.length * n !== m_Coefficients.length) {
-              console.log("Array length must be a multiple of m");
-            }
-            solution =
-              ss.length === ss[0].length
-                ? numeric_1_2_6.LUsolve(numeric_1_2_6.LU(ss, true), bb)
-                : webgazer.mat.QRDecomposition(ss, bb);
-
-            for (var i = 0; i < nc; i++) {
-              m_Coefficients[i] = solution[i];
-            }
-            success = true;
-          } catch (ex) {
-            k *= 10;
-            console.log(ex);
-            success = false;
-          }
-        } while (!success);
-        return m_Coefficients;
-      }
-
-      /**
-       * Compute eyes size as gray histogram
-       * @param {Object} eyes - The eyes where looking for gray histogram
-       * @returns {Array.<T>} The eyes gray level histogram
-       */
-
-      //TODO: still usefull ???
-      /**
-       *
-       * @returns {Number}
-       */
-      function ridgeWeightedReg_getCurrentFixationIndex() {
-        var index = 0;
-        var recentX = this.screenXTrailArray.get(0);
-        var recentY = this.screenYTrailArray.get(0);
-        for (var i = this.screenXTrailArray.length - 1; i >= 0; i--) {
-          var currX = this.screenXTrailArray.get(i);
-          var currY = this.screenYTrailArray.get(i);
-          var euclideanDistance = Math.sqrt(
-            Math.pow(currX - recentX, 2) + Math.pow(currY - recentY, 2)
-          );
-          if (euclideanDistance > 72) {
-            return i + 1;
-          }
-        }
-        return i;
-      }
-
-      /**
-       * Constructor of RidgeWeightedReg object
-       * @constructor
-       */
-      ridgeWeightedReg_reg.RidgeWeightedReg = function () {
-        this.init();
-      };
-
-      /**
-       * Initialize new arrays and initialize Kalman filter.
-       */
-      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.init = function () {
-        this.screenXClicksArray = new src_util.DataWindow(ridgeWeightedReg_dataWindow);
-        this.screenYClicksArray = new src_util.DataWindow(ridgeWeightedReg_dataWindow);
-        this.eyeFeaturesClicks = new src_util.DataWindow(ridgeWeightedReg_dataWindow);
-
-        //sets to one second worth of cursor trail
-        this.trailTime = 1000;
-        this.trailDataWindow = this.trailTime / src_params.moveTickSize;
-        this.screenXTrailArray = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
-        this.screenYTrailArray = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
-        this.eyeFeaturesTrail = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
-        this.trailTimes = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
-
-        this.dataClicks = new src_util.DataWindow(ridgeWeightedReg_dataWindow);
-        this.dataTrail = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
-
-        // Initialize Kalman filter [20200608 xk] what do we do about parameters?
-        // [20200611 xk] unsure what to do w.r.t. dimensionality of these matrices. So far at least
-        //               by my own anecdotal observation a 4x1 x vector seems to work alright
-        var F = [
-          [1, 0, 1, 0],
-          [0, 1, 0, 1],
-          [0, 0, 1, 0],
-          [0, 0, 0, 1],
-        ];
-
-        //Parameters Q and R may require some fine tuning
-        var Q = [
-          [1 / 4, 0, 1 / 2, 0],
-          [0, 1 / 4, 0, 1 / 2],
-          [1 / 2, 0, 1, 0],
-          [0, 1 / 2, 0, 1],
-        ]; // * delta_t
-        var delta_t = 1 / 10; // The amount of time between frames
-        Q = numeric_1_2_6.mul(Q, delta_t);
-
-        var H = [
-          [1, 0, 0, 0, 0, 0],
-          [0, 1, 0, 0, 0, 0],
-          [0, 0, 1, 0, 0, 0],
-          [0, 0, 0, 1, 0, 0],
-        ];
-        var H = [
-          [1, 0, 0, 0],
-          [0, 1, 0, 0],
-        ];
-        var pixel_error = 47; //We will need to fine tune this value [20200611 xk] I just put a random value here
-
-        //This matrix represents the expected measurement error
-        var R = numeric_1_2_6.mul(numeric_1_2_6.identity(2), pixel_error);
-
-        var P_initial = numeric_1_2_6.mul(numeric_1_2_6.identity(4), 0.0001); //Initial covariance matrix
-        var x_initial = [[500], [500], [0], [0]]; // Initial measurement matrix
-
-        this.kalman = new src_util.KalmanFilter(F, H, Q, R, P_initial, x_initial);
-      };
-
-      /**
-       * Add given data from eyes
-       * @param {Object} eyes - eyes where extract data to add
-       * @param {Object} screenPos - The current screen point
-       * @param {Object} type - The type of performed action
-       */
-      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.addData = function (eyes, screenPos, type) {
-        if (!eyes) {
-          return;
-        }
-        //not doing anything with blink at present
-        // if (eyes.left.blink || eyes.right.blink) {
-        //     return;
-        // }
-        if (type === "click") {
-          this.screenXClicksArray.push([screenPos[0]]);
-          this.screenYClicksArray.push([screenPos[1]]);
-
-          this.eyeFeaturesClicks.push(src_util.getEyeFeats(eyes));
-          this.dataClicks.push({ eyes: eyes, screenPos: screenPos, type: type });
-        } else if (type === "move") {
-          this.screenXTrailArray.push([screenPos[0]]);
-          this.screenYTrailArray.push([screenPos[1]]);
-
-          this.eyeFeaturesTrail.push(src_util.getEyeFeats(eyes));
-          this.trailTimes.push(performance.now());
-          this.dataTrail.push({ eyes: eyes, screenPos: screenPos, type: type });
-        }
-
-        // [20180730 JT] Why do we do this? It doesn't return anything...
-        // But as JS is pass by reference, it still affects it.
-        //
-        // Causes problems for when we want to call 'addData' twice in a row on the same object, but perhaps with different screenPos or types (think multiple interactions within one video frame)
-        //eyes.left.patch = Array.from(eyes.left.patch.data);
-        //eyes.right.patch = Array.from(eyes.right.patch.data);
-      };
-
-      /**
-       * Try to predict coordinates from pupil data
-       * after apply linear regression on data set
-       * @param {Object} eyesObj - The current user eyes object
-       * @returns {Object}
-       */
-      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.predict = function (eyesObj) {
-        if (!eyesObj || this.eyeFeaturesClicks.length === 0) {
-          return null;
-        }
-        var acceptTime = performance.now() - this.trailTime;
-        var trailX = [];
-        var trailY = [];
-        var trailFeat = [];
-        for (var i = 0; i < this.trailDataWindow; i++) {
-          if (this.trailTimes.get(i) > acceptTime) {
-            trailX.push(this.screenXTrailArray.get(i));
-            trailY.push(this.screenYTrailArray.get(i));
-            trailFeat.push(this.eyeFeaturesTrail.get(i));
-          }
-        }
-
-        var len = this.eyeFeaturesClicks.data.length;
-        var weightedEyeFeats = Array(len);
-        var weightedXArray = Array(len);
-        var weightedYArray = Array(len);
-        for (var i = 0; i < len; i++) {
-          var weight = Math.sqrt(1 / (len - i)); // access from oldest to newest so should start with low weight and increase steadily
-          //abstraction is leaking...
-          var trueIndex = this.eyeFeaturesClicks.getTrueIndex(i);
-          for (var j = 0; j < this.eyeFeaturesClicks.data[trueIndex].length; j++) {
-            var val = this.eyeFeaturesClicks.data[trueIndex][j] * weight;
-            if (weightedEyeFeats[trueIndex] !== undefined) {
-              weightedEyeFeats[trueIndex].push(val);
-            } else {
-              weightedEyeFeats[trueIndex] = [val];
-            }
-          }
-          weightedXArray[trueIndex] = this.screenXClicksArray
-            .get(i)
-            .slice(0, this.screenXClicksArray.get(i).length);
-          weightedYArray[trueIndex] = this.screenYClicksArray
-            .get(i)
-            .slice(0, this.screenYClicksArray.get(i).length);
-          weightedXArray[i][0] = weightedXArray[i][0] * weight;
-          weightedYArray[i][0] = weightedYArray[i][0] * weight;
-        }
-
-        var screenXArray = weightedXArray.concat(trailX);
-        var screenYArray = weightedYArray.concat(trailY);
-        var eyeFeatures = weightedEyeFeats.concat(trailFeat);
-
-        var coefficientsX = ridgeWeightedReg_ridge(
-          screenXArray,
-          eyeFeatures,
-          ridgeWeightedReg_ridgeParameter
-        );
-        var coefficientsY = ridgeWeightedReg_ridge(
-          screenYArray,
-          eyeFeatures,
-          ridgeWeightedReg_ridgeParameter
-        );
-
-        var eyeFeats = src_util.getEyeFeats(eyesObj);
-        var predictedX = 0;
-        for (var i = 0; i < eyeFeats.length; i++) {
-          predictedX += eyeFeats[i] * coefficientsX[i];
-        }
-        var predictedY = 0;
-        for (var i = 0; i < eyeFeats.length; i++) {
-          predictedY += eyeFeats[i] * coefficientsY[i];
-        }
-
-        predictedX = Math.floor(predictedX);
-        predictedY = Math.floor(predictedY);
-
-        if (src_params.applyKalmanFilter) {
-          // Update Kalman model, and get prediction
-          var newGaze = [predictedX, predictedY]; // [20200607 xk] Should we use a 1x4 vector?
-          newGaze = this.kalman.update(newGaze);
-
-          return {
-            x: newGaze[0],
-            y: newGaze[1],
-          };
-        } else {
-          return {
-            x: predictedX,
-            y: predictedY,
-          };
-        }
-      };
-
-      /**
-       * Add given data to current data set then,
-       * replace current data member with given data
-       * @param {Array.<Object>} data - The data to set
-       */
-      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.setData = function (data) {
-        for (var i = 0; i < data.length; i++) {
-          // [20200611 xk] Previous comment said this was a kludge, but it seems like this is the best solution
-
-          // Clone data array
-          var leftData = new Uint8ClampedArray(data[i].eyes.left.patch.data);
-          var rightData = new Uint8ClampedArray(data[i].eyes.right.patch.data);
-          // Duplicate ImageData object
-          data[i].eyes.left.patch = new ImageData(
-            leftData,
-            data[i].eyes.left.width,
-            data[i].eyes.left.height
-          );
-          data[i].eyes.right.patch = new ImageData(
-            rightData,
-            data[i].eyes.right.width,
-            data[i].eyes.right.height
-          );
-
-          this.addData(data[i].eyes, data[i].screenPos, data[i].type);
-        }
-      };
-
-      /**
-       * Return the data
-       * @returns {Array.<Object>|*}
-       */
-      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.getData = function () {
-        return this.dataClicks.data;
-      };
-
-      /**
-       * The RidgeWeightedReg object name
-       * @type {string}
-       */
-      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.name = "ridge";
-
-      /* harmony default export */ var ridgeWeightedReg = ridgeWeightedReg_reg;
-
-      // CONCATENATED MODULE: ./src/ridgeRegThreaded.mjs
-
-      const ridgeRegThreaded_reg = {};
-
-      var ridgeRegThreaded_ridgeParameter = Math.pow(10, -5);
-      var ridgeRegThreaded_dataWindow = 700;
-      var weights = { X: [0], Y: [0] };
-      var ridgeRegThreaded_trailDataWindow = 10;
-
-      /**
-       * Constructor of RidgeRegThreaded object,
-       * it retrieve data window, and prepare a worker,
-       * this object allow to perform threaded ridge regression
-       * @constructor
-       */
-      ridgeRegThreaded_reg.RidgeRegThreaded = function (workerScriptURL) {
-        this.init(workerScriptURL);
-      };
-
-      /**
-       * Initialize new arrays and initialize Kalman filter.
-       */
-      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.init = function (workerScriptURL) {
-        this.screenXClicksArray = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
-        this.screenYClicksArray = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
-        this.eyeFeaturesClicks = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
-
-        this.screenXTrailArray = new src_util.DataWindow(ridgeRegThreaded_trailDataWindow);
-        this.screenYTrailArray = new src_util.DataWindow(ridgeRegThreaded_trailDataWindow);
-        this.eyeFeaturesTrail = new src_util.DataWindow(ridgeRegThreaded_trailDataWindow);
-
-        this.dataClicks = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
-        this.dataTrail = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
-
-        // Place the src/ridgeworker.js file into the same directory as your html file.
-        if (!this.worker) {
-          //this.worker = new Worker('ridgeWorker.mjs'); // [20200708] TODO: Figure out how to make this inline
-          this.worker = new Worker(workerScriptURL);
-          this.worker.onerror = function (err) {
-            console.log(err.message);
-          };
-          this.worker.onmessage = function (evt) {
-            weights.X = evt.data.X;
-            weights.Y = evt.data.Y;
-          };
-          console.log("initialized worker");
-        }
-
-        // Initialize Kalman filter [20200608 xk] what do we do about parameters?
-        // [20200611 xk] unsure what to do w.r.t. dimensionality of these matrices. So far at least
-        //               by my own anecdotal observation a 4x1 x vector seems to work alright
-        var F = [
-          [1, 0, 1, 0],
-          [0, 1, 0, 1],
-          [0, 0, 1, 0],
-          [0, 0, 0, 1],
-        ];
-
-        //Parameters Q and R may require some fine tuning
-        var Q = [
-          [1 / 4, 0, 1 / 2, 0],
-          [0, 1 / 4, 0, 1 / 2],
-          [1 / 2, 0, 1, 0],
-          [0, 1 / 2, 0, 1],
-        ]; // * delta_t
-        var delta_t = 1 / 10; // The amount of time between frames
-        Q = numeric_1_2_6.mul(Q, delta_t);
-
-        var H = [
-          [1, 0, 0, 0, 0, 0],
-          [0, 1, 0, 0, 0, 0],
-          [0, 0, 1, 0, 0, 0],
-          [0, 0, 0, 1, 0, 0],
-        ];
-        var H = [
-          [1, 0, 0, 0],
-          [0, 1, 0, 0],
-        ];
-        var pixel_error = 47; //We will need to fine tune this value [20200611 xk] I just put a random value here
-
-        //This matrix represents the expected measurement error
-        var R = numeric_1_2_6.mul(numeric_1_2_6.identity(2), pixel_error);
-
-        var P_initial = numeric_1_2_6.mul(numeric_1_2_6.identity(4), 0.0001); //Initial covariance matrix
-        var x_initial = [[500], [500], [0], [0]]; // Initial measurement matrix
-
-        this.kalman = new src_util.KalmanFilter(F, H, Q, R, P_initial, x_initial);
-      };
-
-      /**
-       * Add given data from eyes
-       * @param {Object} eyes - eyes where extract data to add
-       * @param {Object} screenPos - The current screen point
-       * @param {Object} type - The type of performed action
-       */
-      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.addData = function (eyes, screenPos, type) {
-        if (!eyes) {
-          return;
-        }
-        //not doing anything with blink at present
-        // if (eyes.left.blink || eyes.right.blink) {
-        //     return;
-        // }
-        this.worker.postMessage({
-          eyes: src_util.getEyeFeats(eyes),
-          screenPos: screenPos,
-          type: type,
-        });
-      };
-
-      /**
-       * Try to predict coordinates from pupil data
-       * after apply linear regression on data set
-       * @param {Object} eyesObj - The current user eyes object
-       * @returns {Object}
-       */
-      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.predict = function (eyesObj) {
-        // console.log('LOGGING..');
-        if (!eyesObj) {
-          return null;
-        }
-        var coefficientsX = weights.X;
-        var coefficientsY = weights.Y;
-
-        var eyeFeats = src_util.getEyeFeats(eyesObj);
-        var predictedX = 0,
-          predictedY = 0;
-        for (var i = 0; i < eyeFeats.length; i++) {
-          predictedX += eyeFeats[i] * coefficientsX[i];
-          predictedY += eyeFeats[i] * coefficientsY[i];
-        }
-
-        predictedX = Math.floor(predictedX);
-        predictedY = Math.floor(predictedY);
-
-        if (src_params.applyKalmanFilter) {
-          // Update Kalman model, and get prediction
-          var newGaze = [predictedX, predictedY]; // [20200607 xk] Should we use a 1x4 vector?
-          newGaze = this.kalman.update(newGaze);
-
-          return {
-            x: newGaze[0],
-            y: newGaze[1],
-          };
-        } else {
-          return {
-            x: predictedX,
-            y: predictedY,
-          };
-        }
-      };
-
-      /**
-       * Add given data to current data set then,
-       * replace current data member with given data
-       * @param {Array.<Object>} data - The data to set
-       */
-      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.setData = function (data) {
-        for (var i = 0; i < data.length; i++) {
-          // [20200611 xk] Previous comment said this was a kludge, but it seems like this is the best solution
-
-          // Clone data array
-          var leftData = new Uint8ClampedArray(data[i].eyes.left.patch.data);
-          var rightData = new Uint8ClampedArray(data[i].eyes.right.patch.data);
-          // Duplicate ImageData object
-          data[i].eyes.left.patch = new ImageData(
-            leftData,
-            data[i].eyes.left.width,
-            data[i].eyes.left.height
-          );
-          data[i].eyes.right.patch = new ImageData(
-            rightData,
-            data[i].eyes.right.width,
-            data[i].eyes.right.height
-          );
-
-          this.addData(data[i].eyes, data[i].screenPos, data[i].type);
-        }
-      };
-
-      /**
-       * Return the data
-       * @returns {Array.<Object>|*}
-       */
-      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.getData = function () {
-        return this.dataClicks.data;
-      };
-
-      /**
-       * The RidgeRegThreaded object name
-       * @type {string}
-       */
-      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.name = "ridge";
-
-      /* harmony default export */ var ridgeRegThreaded = ridgeRegThreaded_reg;
-
-      // CONCATENATED MODULE: ./src/index.mjs
-
-      const src_webgazer = {};
-      src_webgazer.tracker = {};
-      src_webgazer.tracker.TFFaceMesh = facemesh;
-      src_webgazer.reg = ridgeReg;
-      src_webgazer.reg.RidgeWeightedReg = ridgeWeightedReg.RidgeWeightedReg;
-      src_webgazer.reg.RidgeRegThreaded = ridgeRegThreaded.RidgeRegThreaded;
-      src_webgazer.util = src_util;
-      src_webgazer.params = src_params;
-      src_webgazer.workerScriptURL = "ridgeWorker.mjs";
-
-      //PRIVATE VARIABLES
-
-      //video elements
-      var videoStream = null;
-      var videoContainerElement = null;
-      var videoElement = null;
-      var videoElementCanvas = null;
-      var faceOverlay = null;
-      var faceFeedbackBox = null;
-      var gazeDot = null;
-      // Why is this not in webgazer.params ?
-      var debugVideoLoc = "";
-
-      /*
-       * Initialises variables used to store accuracy eigenValues
-       * This is used by the calibration example file
-       */
-      var xPast50 = new Array(50);
-      var yPast50 = new Array(50);
-
-      // loop parameters
-      var clockStart = performance.now();
-      var latestEyeFeatures = null;
-      var latestGazeData = null;
-      var paused = false;
-      //registered callback for loop
-      var nopCallback = function (data, time) {};
-      var callback = nopCallback;
-
-      //Types that regression systems should handle
-      //Describes the source of data so that regression systems may ignore or handle differently the various generating events
-      var eventTypes = ["click", "move"];
-
-      //movelistener timeout clock parameters
-      var moveClock = performance.now();
-      //currently used tracker and regression models, defaults to clmtrackr and linear regression
-      var curTracker = new src_webgazer.tracker.TFFaceMesh();
-      var regs = [new src_webgazer.reg.RidgeReg()];
-      // var blinkDetector = new webgazer.BlinkDetector();
-
-      //lookup tables
-      var curTrackerMap = {
-        TFFacemesh: function () {
-          return new src_webgazer.tracker.TFFaceMesh();
-        },
-      };
-      var regressionMap = {
-        ridge: function () {
-          return new src_webgazer.reg.RidgeReg();
-        },
-        weightedRidge: function () {
-          return new src_webgazer.reg.RidgeWeightedReg();
-        },
-        threadedRidge: function () {
-          return new src_webgazer.reg.RidgeRegThreaded(src_webgazer.workerScriptURL);
-        },
-      };
-
-      //localstorage name
-      var localstorageDataLabel = "webgazerGlobalData";
-      var localstorageSettingsLabel = "webgazerGlobalSettings";
-      //settings object for future storage of settings
-      var settings = {};
-      var data = [];
-      var defaults = {
-        data: [],
-        settings: {},
-      };
-
-      //PRIVATE FUNCTIONS
-
-      /**
-       * Computes the size of the face overlay validation box depending on the size of the video preview window.
-       * @returns {Object} The dimensions of the validation box as top, left, width, height.
-       */
-      src_webgazer.computeValidationBoxSize = function () {
-        var vw = videoElement.videoWidth;
-        var vh = videoElement.videoHeight;
-        var pw = parseInt(videoElement.style.width);
-        var ph = parseInt(videoElement.style.height);
-
-        // Find the size of the box.
-        // Pick the smaller of the two video preview sizes
-        var smaller = Math.min(vw, vh);
-        var larger = Math.max(vw, vh);
-
-        // Overall scalar
-        var scalar = vw == larger ? pw / vw : ph / vh;
-
-        // Multiply this by 2/3, then adjust it to the size of the preview
-        var boxSize = smaller * src_webgazer.params.faceFeedbackBoxRatio * scalar;
-
-        // Set the boundaries of the face overlay validation box based on the preview
-        var topVal = (ph - boxSize) / 2;
-        var leftVal = (pw - boxSize) / 2;
-
-        // top, left, width, height
-        return [topVal, leftVal, boxSize, boxSize];
-      };
-
-      /**
-       * Checks if the pupils are in the position box on the video
-       * // TODO These are all wrong. The latestEyeFeatures will be in 'video' space not 'preview' space, and so need to be converted.
-       */
-      function checkEyesInValidationBox() {
-        if (faceFeedbackBox != null && latestEyeFeatures) {
-          var w = videoElement.videoWidth;
-          var h = videoElement.videoHeight;
-
-          // Find the size of the box.
-          // Pick the smaller of the two video preview sizes
-          var smaller = Math.min(w, h);
-          var boxSize = smaller * src_webgazer.params.faceFeedbackBoxRatio;
-
-          // Set the boundaries of the face overlay validation box based on the preview
-          var topBound = (h - boxSize) / 2;
-          var leftBound = (w - boxSize) / 2;
-          var rightBound = leftBound + boxSize;
-          var bottomBound = topBound + boxSize;
-
-          //get the x and y positions of the left and right eyes
-          var eyeLX = latestEyeFeatures.left.imagex;
-          var eyeLY = latestEyeFeatures.left.imagey;
-          var eyeRX = latestEyeFeatures.right.imagex;
-          var eyeRY = latestEyeFeatures.right.imagey;
-
-          var xPositions = false;
-          var yPositions = false;
-
-          //check if the x values for the left and right eye are within the
-          //validation box
-          if (eyeLX > leftBound && eyeLX < rightBound) {
-            if (eyeRX > leftBound && eyeRX < rightBound) {
-              xPositions = true;
-            }
-          }
-
-          //check if the y values for the left and right eye are within the
-          //validation box
-          if (eyeLY > topBound && eyeLY < bottomBound) {
-            if (eyeRY > topBound && eyeRY < bottomBound) {
-              yPositions = true;
-            }
-          }
-
-          //if the x and y values for both the left and right eye are within
-          //the validation box then the box border turns green, otherwise if
-          //the eyes are outside of the box the colour is red
-          if (xPositions && yPositions) {
-            faceFeedbackBox.style.border = "solid green";
-          } else {
-            faceFeedbackBox.style.border = "solid red";
-          }
-        } else faceFeedbackBox.style.border = "solid black";
-      }
-
-      /**
-       * This draws the point (x,y) onto the canvas in the HTML
-       * @param {colour} colour - The colour of the circle to plot
-       * @param {x} x - The x co-ordinate of the desired point to plot
-       * @param {y} y - The y co-ordinate of the desired point to plot
-       */
-      function drawCoordinates(colour, x, y) {
-        var ctx = document.getElementById("plotting_canvas").getContext("2d");
-        ctx.fillStyle = colour; // Red color
-        ctx.beginPath();
-        ctx.arc(x, y, 5, 0, Math.PI * 2, true);
-        ctx.fill();
-      }
-
-      /**
-       * Gets the pupil features by following the pipeline which threads an eyes object through each call:
-       * curTracker gets eye patches -> blink detector -> pupil detection
-       * @param {Canvas} canvas - a canvas which will have the video drawn onto it
-       * @param {Number} width - the width of canvas
-       * @param {Number} height - the height of canvas
-       */
-      function getPupilFeatures(canvas, width, height) {
-        if (!canvas) {
-          return;
-        }
-        try {
-          return curTracker.getEyePatches(canvas, width, height);
-        } catch (err) {
-          console.log("can't get pupil features ", err);
-          return null;
-        }
-      }
-
-      /**
-       * Gets the most current frame of video and paints it to a resized version of the canvas with width and height
-       * @param {Canvas} canvas - the canvas to paint the video on to
-       * @param {Number} width - the new width of the canvas
-       * @param {Number} height - the new height of the canvas
-       */
-      function paintCurrentFrame(canvas, width, height) {
-        if (canvas.width != width) {
-          canvas.width = width;
-        }
-        if (canvas.height != height) {
-          canvas.height = height;
-        }
-
-        var ctx = canvas.getContext("2d");
-        ctx.drawImage(videoElement, 0, 0, canvas.width, canvas.height);
-      }
-
-      /**
-       * Paints the video to a canvas and runs the prediction pipeline to get a prediction
-       * @param {Number|undefined} regModelIndex - The prediction index we're looking for
-       * @returns {*}
-       */
-      async function getPrediction(regModelIndex) {
-        // this allows getPrediction to work even when webgazer is paused, since the only necessary
-        // component for getPrediction in loop() is paintCurrentFrame().
-        if (paused) {
-          paintCurrentFrame(
-            videoElementCanvas,
-            videoElementCanvas.width,
-            videoElementCanvas.height
-          );
-        }
-        var time = performance.now();
-
-        var predictions = [];
-        // [20200617 xk] TODO: this call should be made async somehow. will take some work.
-        latestEyeFeatures = await getPupilFeatures(
-          videoElementCanvas,
-          videoElementCanvas.width,
-          videoElementCanvas.height
-        );
-
-        if (regs.length === 0) {
-          console.log("regression not set, call setRegression()");
-          return null;
-        }
-        for (var reg in regs) {
-          predictions.push(regs[reg].predict(latestEyeFeatures));
-        }
-        if (regModelIndex !== undefined) {
-          return predictions[regModelIndex] === null
-            ? null
-            : {
-                x: predictions[regModelIndex].x,
-                y: predictions[regModelIndex].y,
-                eyeFeatures: latestEyeFeatures,
-                t: time,
-              };
-        } else {
-          return predictions.length === 0 || predictions[0] === null
-            ? null
-            : {
-                x: predictions[0].x,
-                y: predictions[0].y,
-                eyeFeatures: latestEyeFeatures,
-                all: predictions,
-                t: time,
-              };
-        }
-      }
-
-      /**
-       * Runs every available animation frame if webgazer is not paused
-       */
-      var smoothingVals = new src_webgazer.util.DataWindow(4);
-      var src_k = 0;
-
-      async function loop() {
-        if (!paused) {
-          // [20200617 XK] TODO: there is currently lag between the camera input and the face overlay. This behavior
-          // is not seen in the facemesh demo. probably need to optimize async implementation. I think the issue lies
-          // in the implementation of getPrediction().
-
-          // Paint the latest video frame into the canvas which will be analyzed by WebGazer
-          // [20180729 JT] Why do we need to do this? clmTracker does this itself _already_, which is just duplicating the work.
-          // Is it because other trackers need a canvas instead of an img/video element?
-          paintCurrentFrame(
-            videoElementCanvas,
-            videoElementCanvas.width,
-            videoElementCanvas.height
-          );
-
-          // Get gaze prediction (ask clm to track; pass the data to the regressor; get back a prediction)
-          latestGazeData = getPrediction();
-          // Count time
-          var elapsedTime = performance.now() - clockStart;
-
-          // Draw face overlay
-          if (src_webgazer.params.showFaceOverlay) {
-            // Get tracker object
-            var tracker = src_webgazer.getTracker();
-            faceOverlay
-              .getContext("2d")
-              .clearRect(0, 0, videoElement.videoWidth, videoElement.videoHeight);
-            tracker.drawFaceOverlay(faceOverlay.getContext("2d"), tracker.getPositions());
-          }
-
-          // Feedback box
-          // Check that the eyes are inside of the validation box
-          if (src_webgazer.params.showFaceFeedbackBox) checkEyesInValidationBox();
-
-          latestGazeData = await latestGazeData;
-
-          // [20200623 xk] callback to function passed into setGazeListener(fn)
-          callback(latestGazeData, elapsedTime);
-
-          if (latestGazeData) {
-            // [20200608 XK] Smoothing across the most recent 4 predictions, do we need this with Kalman filter?
-            smoothingVals.push(latestGazeData);
-            var x = 0;
-            var y = 0;
-            var len = smoothingVals.length;
-            for (var d in smoothingVals.data) {
-              x += smoothingVals.get(d).x;
-              y += smoothingVals.get(d).y;
-            }
-
-            var pred = src_webgazer.util.bound({ x: x / len, y: y / len });
-
-            if (src_webgazer.params.storingPoints) {
-              drawCoordinates("blue", pred.x, pred.y); //draws the previous predictions
-              //store the position of the past fifty occuring tracker preditions
-              src_webgazer.storePoints(pred.x, pred.y, src_k);
-              src_k++;
-              if (src_k == 50) {
-                src_k = 0;
-              }
-            }
-            // GazeDot
-            if (src_webgazer.params.showGazeDot) {
-              gazeDot.style.display = "block";
-            }
-            gazeDot.style.transform = "translate3d(" + pred.x + "px," + pred.y + "px,0)";
-          } else {
-            gazeDot.style.display = "none";
-          }
-
-          requestAnimationFrame(loop);
-        }
-      }
-
-      //is problematic to test
-      //because latestEyeFeatures is not set in many cases
-
-      /**
-       * Records screen position data based on current pupil feature and passes it
-       * to the regression model.
-       * @param {Number} x - The x screen position
-       * @param {Number} y - The y screen position
-       * @param {String} eventType - The event type to store
-       * @returns {null}
-       */
-      var recordScreenPosition = function (x, y, eventType) {
-        if (paused) {
-          return;
-        }
-        if (regs.length === 0) {
-          console.log("regression not set, call setRegression()");
-          return null;
-        }
-        for (var reg in regs) {
-          if (latestEyeFeatures) regs[reg].addData(latestEyeFeatures, [x, y], eventType);
-        }
-      };
-
-      /**
-       * Records click data and passes it to the regression model
-       * @param {Event} event - The listened event
-       */
-      var clickListener = async function (event) {
-        recordScreenPosition(event.clientX, event.clientY, eventTypes[0]); // eventType[0] === 'click'
-
-        if (window.saveDataAcrossSessions) {
-          // Each click stores the next data point into localforage.
-          await setGlobalData();
-
-          // // Debug line
-          // console.log('Model size: ' + JSON.stringify(await localforage.getItem(localstorageDataLabel)).length / 1000000 + 'MB');
-        }
-      };
-
-      /**
-       * Records mouse movement data and passes it to the regression model
-       * @param {Event} event - The listened event
-       */
-      var moveListener = function (event) {
-        if (paused) {
-          return;
-        }
-
-        var now = performance.now();
-        if (now < moveClock + src_webgazer.params.moveTickSize) {
-          return;
-        } else {
-          moveClock = now;
-        }
-        recordScreenPosition(event.clientX, event.clientY, eventTypes[1]); //eventType[1] === 'move'
-      };
-
-      /**
-       * Add event listeners for mouse click and move.
-       */
-      var addMouseEventListeners = function () {
-        //third argument set to true so that we get event on 'capture' instead of 'bubbling'
-        //this prevents a client using event.stopPropagation() preventing our access to the click
-        document.addEventListener("click", clickListener, true);
-        document.addEventListener("mousemove", moveListener, true);
-      };
-
-      /**
-       * Remove event listeners for mouse click and move.
-       */
-      var removeMouseEventListeners = function () {
-        // must set third argument to same value used in addMouseEventListeners
-        // for this to work.
-        document.removeEventListener("click", clickListener, true);
-        document.removeEventListener("mousemove", moveListener, true);
-      };
-
-      /**
-       * Loads the global data and passes it to the regression model
-       */
-      async function loadGlobalData() {
-        // Get settings object from localforage
-        // [20200611 xk] still unsure what this does, maybe would be good for Kalman filter settings etc?
-        settings = await localforage.getItem(localstorageSettingsLabel);
-        settings = settings || defaults;
-
-        // Get click data from localforage
-        var loadData = await localforage.getItem(localstorageDataLabel);
-        loadData = loadData || defaults;
-
-        // Set global var data to newly loaded data
-        data = loadData;
-
-        // Load data into regression model(s)
-        for (var reg in regs) {
-          regs[reg].setData(loadData);
-        }
-
-        console.log("loaded stored data into regression model");
-      }
-
-      /**
-       * Adds data to localforage
-       */
-      async function setGlobalData() {
-        // Grab data from regression model
-        var storeData = regs[0].getData() || data; // Array
-
-        // Store data into localforage
-        localforage.setItem(localstorageSettingsLabel, settings); // [20200605 XK] is 'settings' ever being used?
-        localforage.setItem(localstorageDataLabel, storeData);
-        //TODO data should probably be stored in webgazer object instead of each regression model
-        //     -> requires duplication of data, but is likely easier on regression model implementors
-      }
-
-      /**
-       * Clears data from model and global storage
-       */
-      function clearData() {
-        // Removes data from localforage
-        localforage.clear();
-
-        // Removes data from regression model
-        for (var reg in regs) {
-          regs[reg].init();
-        }
-      }
-
-      /**
-       * Initializes all needed dom elements and begins the loop
-       * @param {URL} stream - The video stream to use
-       */
-      async function init(stream) {
-        //////////////////////////
-        // Video and video preview
-        //////////////////////////
-        var topDist = "0px";
-        var leftDist = "0px";
-
-        // used for webgazer.stopVideo() and webgazer.setCameraConstraints()
-        videoStream = stream;
-
-        // create a video element container to enable customizable placement on the page
-        videoContainerElement = document.createElement("div");
-        videoContainerElement.id = src_webgazer.params.videoContainerId;
-        videoContainerElement.style.display = src_webgazer.params.showVideo ? "block" : "none";
-        videoContainerElement.style.position = "fixed";
-        videoContainerElement.style.top = topDist;
-        videoContainerElement.style.left = leftDist;
-        videoContainerElement.style.width = src_webgazer.params.videoViewerWidth + "px";
-        videoContainerElement.style.height = src_webgazer.params.videoViewerHeight + "px";
-
-        videoElement = document.createElement("video");
-        videoElement.setAttribute("playsinline", "");
-        videoElement.id = src_webgazer.params.videoElementId;
-        videoElement.srcObject = stream;
-        videoElement.autoplay = true;
-        videoElement.style.display = src_webgazer.params.showVideo ? "block" : "none";
-        videoElement.style.position = "absolute";
-        // We set these to stop the video appearing too large when it is added for the very first time
-        videoElement.style.width = src_webgazer.params.videoViewerWidth + "px";
-        videoElement.style.height = src_webgazer.params.videoViewerHeight + "px";
-        // videoElement.style.zIndex="-1";
-
-        // Canvas for drawing video to pass to clm tracker
-        videoElementCanvas = document.createElement("canvas");
-        videoElementCanvas.id = src_webgazer.params.videoElementCanvasId;
-        videoElementCanvas.style.display = "none";
-
-        // Face overlay
-        // Shows the CLM tracking result
-        faceOverlay = document.createElement("canvas");
-        faceOverlay.id = src_webgazer.params.faceOverlayId;
-        faceOverlay.style.display = src_webgazer.params.showFaceOverlay ? "block" : "none";
-        faceOverlay.style.position = "absolute";
-
-        // Mirror video feed
-        if (src_webgazer.params.mirrorVideo) {
-          videoElement.style.setProperty("-moz-transform", "scale(-1, 1)");
-          videoElement.style.setProperty("-webkit-transform", "scale(-1, 1)");
-          videoElement.style.setProperty("-o-transform", "scale(-1, 1)");
-          videoElement.style.setProperty("transform", "scale(-1, 1)");
-          videoElement.style.setProperty("filter", "FlipH");
-          faceOverlay.style.setProperty("-moz-transform", "scale(-1, 1)");
-          faceOverlay.style.setProperty("-webkit-transform", "scale(-1, 1)");
-          faceOverlay.style.setProperty("-o-transform", "scale(-1, 1)");
-          faceOverlay.style.setProperty("transform", "scale(-1, 1)");
-          faceOverlay.style.setProperty("filter", "FlipH");
-        }
-
-        // Feedback box
-        // Lets the user know when their face is in the middle
-        faceFeedbackBox = document.createElement("canvas");
-        faceFeedbackBox.id = src_webgazer.params.faceFeedbackBoxId;
-        faceFeedbackBox.style.display = src_webgazer.params.showFaceFeedbackBox ? "block" : "none";
-        faceFeedbackBox.style.border = "solid";
-        faceFeedbackBox.style.position = "absolute";
-
-        // Gaze dot
-        // Starts offscreen
-        gazeDot = document.createElement("div");
-        gazeDot.id = src_webgazer.params.gazeDotId;
-        gazeDot.style.display = src_webgazer.params.showGazeDot ? "block" : "none";
-        gazeDot.style.position = "fixed";
-        gazeDot.style.zIndex = 99999;
-        gazeDot.style.left = "-5px"; //'-999em';
-        gazeDot.style.top = "-5px";
-        gazeDot.style.background = "red";
-        gazeDot.style.borderRadius = "100%";
-        gazeDot.style.opacity = "0.7";
-        gazeDot.style.width = "10px";
-        gazeDot.style.height = "10px";
-
-        // Add other preview/feedback elements to the screen once the video has shown and its parameters are initialized
-        videoContainerElement.appendChild(videoElement);
-        document.body.appendChild(videoContainerElement);
-        function setupPreviewVideo(e) {
-          // All video preview parts have now been added, so set the size both internally and in the preview window.
-          setInternalVideoBufferSizes(videoElement.videoWidth, videoElement.videoHeight);
-          src_webgazer.setVideoViewerSize(
-            src_webgazer.params.videoViewerWidth,
-            src_webgazer.params.videoViewerHeight
-          );
-
-          videoContainerElement.appendChild(videoElementCanvas);
-          videoContainerElement.appendChild(faceOverlay);
-          videoContainerElement.appendChild(faceFeedbackBox);
-          document.body.appendChild(gazeDot);
-
-          // Run this only once, so remove the event listener
-          e.target.removeEventListener(e.type, setupPreviewVideo);
-        }
-        videoElement.addEventListener("timeupdate", setupPreviewVideo);
-
-        addMouseEventListeners();
-
-        //BEGIN CALLBACK LOOP
-        paused = false;
-        clockStart = performance.now();
-
-        await loop();
-      }
-
-      /**
-       * Initializes navigator.mediaDevices.getUserMedia
-       * depending on the browser capabilities
-       *
-       * @return Promise
-       */
-      function setUserMediaVariable() {
-        if (navigator.mediaDevices === undefined) {
-          navigator.mediaDevices = {};
-        }
-
-        if (navigator.mediaDevices.getUserMedia === undefined) {
-          navigator.mediaDevices.getUserMedia = function (constraints) {
-            // gets the alternative old getUserMedia is possible
-            var getUserMedia = navigator.webkitGetUserMedia || navigator.mozGetUserMedia;
-
-            // set an error message if browser doesn't support getUserMedia
-            if (!getUserMedia) {
-              return Promise.reject(
-                new Error(
-                  "Unfortunately, your browser does not support access to the webcam through the getUserMedia API. Try to use the latest version of Google Chrome, Mozilla Firefox, Opera, or Microsoft Edge instead."
-                )
-              );
-            }
-
-            // uses navigator.getUserMedia for older browsers
-            return new Promise(function (resolve, reject) {
-              getUserMedia.call(navigator, constraints, resolve, reject);
-            });
-          };
-        }
-      }
-
-      //PUBLIC FUNCTIONS - CONTROL
-
-      /**
-       * Starts all state related to webgazer -> dataLoop, video collection, click listener
-       * If starting fails, call `onFail` param function.
-       * @param {Function} onFail - Callback to call in case it is impossible to find user camera
-       * @returns {*}
-       */
-      src_webgazer.begin = function (onFail) {
-        if (
-          window.location.protocol !== "https:" &&
-          window.location.hostname !== "localhost" &&
-          window.chrome
-        ) {
-          alert(
-            "WebGazer works only over https. If you are doing local development, you need to run a local server."
-          );
-        }
-
-        // Load model data stored in localforage.
-        if (window.saveDataAcrossSessions) {
-          loadGlobalData();
-        }
-
-        onFail =
-          onFail ||
-          function () {
-            console.log("No stream");
-          };
-
-        if (debugVideoLoc) {
-          init(debugVideoLoc);
-          return src_webgazer;
-        }
-
-        ///////////////////////
-        // SETUP VIDEO ELEMENTS
-        // Sets .mediaDevices.getUserMedia depending on browser
-        setUserMediaVariable();
-
-        // Request webcam access under specific constraints
-        // WAIT for access
-        return new Promise(async (resolve, reject) => {
-          let stream;
-          try {
-            stream = await navigator.mediaDevices.getUserMedia(src_webgazer.params.camConstraints);
-            init(stream);
-            resolve(src_webgazer);
-          } catch (err) {
-            onFail();
-            videoElement = null;
-            stream = null;
-            reject(err);
-          }
-        });
-      };
-
-      /**
-       * Checks if webgazer has finished initializing after calling begin()
-       * [20180729 JT] This seems like a bad idea for how this function should be implemented.
-       * @returns {boolean} if webgazer is ready
-       */
-      src_webgazer.isReady = function () {
-        if (videoElementCanvas === null) {
-          return false;
-        }
-        return videoElementCanvas.width > 0;
-      };
-
-      /**
-       * Stops collection of data and predictions
-       * @returns {webgazer} this
-       */
-      src_webgazer.pause = function () {
-        paused = true;
-        return src_webgazer;
-      };
-
-      /**
-       * Resumes collection of data and predictions if paused
-       * @returns {webgazer} this
-       */
-      src_webgazer.resume = async function () {
-        if (!paused) {
-          return src_webgazer;
-        }
-        paused = false;
-        await loop();
-        return src_webgazer;
-      };
-
-      /**
-       * stops collection of data and removes dom modifications, must call begin() to reset up
-       * @return {webgazer} this
-       */
-      src_webgazer.end = function () {
-        //loop may run an extra time and fail due to removed elements
-        paused = true;
-
-        //webgazer.stopVideo(); // uncomment if you want to stop the video from streaming
-
-        //remove video element and canvas
-        document.body.removeChild(videoElement);
-        document.body.removeChild(videoElementCanvas);
-
-        return src_webgazer;
-      };
-
-      /**
-       * Stops the video camera from streaming and removes the video outlines
-       * @return {webgazer} this
-       */
-      src_webgazer.stopVideo = function () {
-        // Stops the video from streaming
-        videoStream.getTracks()[0].stop();
-
-        // Removes the outline of the face
-        document.body.removeChild(faceOverlay);
-
-        // Removes the box around the face
-        document.body.removeChild(faceFeedbackBox);
-
-        return src_webgazer;
-      };
-
-      //PUBLIC FUNCTIONS - DEBUG
-
-      /**
-       * Returns if the browser is compatible with webgazer
-       * @return {boolean} if browser is compatible
-       */
-      src_webgazer.detectCompatibility = function () {
-        var getUserMedia =
-          navigator.mediaDevices.getUserMedia ||
-          navigator.getUserMedia ||
-          navigator.webkitGetUserMedia ||
-          navigator.mozGetUserMedia;
-
-        return getUserMedia !== undefined;
-      };
-
-      /**
-       * Set whether to show any of the video previews (camera, face overlay, feedback box).
-       * If true: visibility depends on corresponding params (default all true).
-       * If false: camera, face overlay, feedback box are all hidden
-       * @param {bool} val
-       * @return {webgazer} this
-       */
-      src_webgazer.showVideoPreview = function (val) {
-        src_webgazer.params.showVideoPreview = val;
-        src_webgazer.showVideo(val && src_webgazer.params.showVideo);
-        src_webgazer.showFaceOverlay(val && src_webgazer.params.showFaceOverlay);
-        src_webgazer.showFaceFeedbackBox(val && src_webgazer.params.showFaceFeedbackBox);
-        return src_webgazer;
-      };
-
-      /**
-       * Set whether the camera video preview is visible or not (default true).
-       * @param {*} bool
-       * @return {webgazer} this
-       */
-      src_webgazer.showVideo = function (val) {
-        src_webgazer.params.showVideo = val;
-        if (videoElement) {
-          videoElement.style.display = val ? "block" : "none";
-        }
-        if (videoContainerElement) {
-          videoContainerElement.style.display = val ? "block" : "none";
-        }
-        return src_webgazer;
-      };
-
-      /**
-       * Set whether the face overlay is visible or not (default true).
-       * @param {*} bool
-       * @return {webgazer} this
-       */
-      src_webgazer.showFaceOverlay = function (val) {
-        src_webgazer.params.showFaceOverlay = val;
-        if (faceOverlay) {
-          faceOverlay.style.display = val ? "block" : "none";
-        }
-        return src_webgazer;
-      };
-
-      /**
-       * Set whether the face feedback box is visible or not (default true).
-       * @param {*} bool
-       * @return {webgazer} this
-       */
-      src_webgazer.showFaceFeedbackBox = function (val) {
-        src_webgazer.params.showFaceFeedbackBox = val;
-        if (faceFeedbackBox) {
-          faceFeedbackBox.style.display = val ? "block" : "none";
-        }
-        return src_webgazer;
-      };
-
-      /**
-       * Set whether the gaze prediction point(s) are visible or not.
-       * Multiple because of a trail of past dots. Default true
-       * @return {webgazer} this
-       */
-      src_webgazer.showPredictionPoints = function (val) {
-        src_webgazer.params.showGazeDot = val;
-        if (gazeDot) {
-          gazeDot.style.display = val ? "block" : "none";
-        }
-        return src_webgazer;
-      };
-
-      /**
-       * Set whether a Kalman filter will be applied to gaze predictions (default true);
-       * @return {webgazer} this
-       */
-      src_webgazer.applyKalmanFilter = function (val) {
-        src_webgazer.params.applyKalmanFilter = val;
-        return src_webgazer;
-      };
-
-      /**
-       * Define constraints on the video camera that is used. Useful for non-standard setups.
-       * This can be set before calling webgazer.begin(), but also mid stream.
-       *
-       * @param {Object} constraints Example constraints object:
-       * { width: { min: 320, ideal: 1280, max: 1920 }, height: { min: 240, ideal: 720, max: 1080 }, facingMode: "user" };
-       *
-       * Follows definition here:
-       * https://developer.mozilla.org/en-US/docs/Web/API/Media_Streams_API/Constraints
-       *
-       * Note: The constraints set here are applied to the video track only. They also _replace_ any constraints, so be sure to set everything you need.
-       * Warning: Setting a large video resolution will decrease performance, and may require
-       */
-      src_webgazer.setCameraConstraints = async function (constraints) {
-        var videoTrack, videoSettings;
-        src_webgazer.params.camConstraints = constraints;
-
-        // If the camera stream is already up...
-        if (videoStream) {
-          src_webgazer.pause();
-          videoTrack = videoStream.getVideoTracks()[0];
-          try {
-            await videoTrack.applyConstraints(src_webgazer.params.camConstraints);
-            videoSettings = videoTrack.getSettings();
-            setInternalVideoBufferSizes(videoSettings.width, videoSettings.height);
-          } catch (err) {
-            console.log(err);
-            return;
-          }
-          // Reset and recompute sizes of the video viewer.
-          // This is only to adjust the feedback box, say, if the aspect ratio of the video has changed.
-          src_webgazer.setVideoViewerSize(
-            src_webgazer.params.videoViewerWidth,
-            src_webgazer.params.videoViewerHeight
-          );
-          src_webgazer.getTracker().reset();
-          await src_webgazer.resume();
-        }
-      };
-
-      /**
-       * Does what it says on the tin.
-       * @param {*} width
-       * @param {*} height
-       */
-      function setInternalVideoBufferSizes(width, height) {
-        // Re-set the canvas size used by the internal processes
-        if (videoElementCanvas) {
-          videoElementCanvas.width = width;
-          videoElementCanvas.height = height;
-        }
-
-        // Re-set the face overlay canvas size
-        if (faceOverlay) {
-          faceOverlay.width = width;
-          faceOverlay.height = height;
-        }
-      }
-
-      /**
-       *  Set a static video file to be used instead of webcam video
-       *  @param {String} videoLoc - video file location
-       *  @return {webgazer} this
-       */
-      src_webgazer.setStaticVideo = function (videoLoc) {
-        debugVideoLoc = videoLoc;
-        return src_webgazer;
-      };
-
-      /**
-       * Set the size of the video viewer
-       */
-      src_webgazer.setVideoViewerSize = function (w, h) {
-        src_webgazer.params.videoViewerWidth = w;
-        src_webgazer.params.videoViewerHeight = h;
-
-        // Change the video viewer
-        videoElement.style.width = w + "px";
-        videoElement.style.height = h + "px";
-
-        // Change the face overlay
-        faceOverlay.style.width = w + "px";
-        faceOverlay.style.height = h + "px";
-
-        // Change the feedback box size
-        // Compute the boundaries of the face overlay validation box based on the video size
-        var tlwh = src_webgazer.computeValidationBoxSize();
-        // Assign them to the object
-        faceFeedbackBox.style.top = tlwh[0] + "px";
-        faceFeedbackBox.style.left = tlwh[1] + "px";
-        faceFeedbackBox.style.width = tlwh[2] + "px";
-        faceFeedbackBox.style.height = tlwh[3] + "px";
-      };
-
-      /**
-       *  Add the mouse click and move listeners that add training data.
-       *  @return {webgazer} this
-       */
-      src_webgazer.addMouseEventListeners = function () {
-        addMouseEventListeners();
-        return src_webgazer;
-      };
-
-      /**
-       *  Remove the mouse click and move listeners that add training data.
-       *  @return {webgazer} this
-       */
-      src_webgazer.removeMouseEventListeners = function () {
-        removeMouseEventListeners();
-        return src_webgazer;
-      };
-
-      /**
-       *  Records current screen position for current pupil features.
-       *  @param {String} x - position on screen in the x axis
-       *  @param {String} y - position on screen in the y axis
-       *  @return {webgazer} this
-       */
-      src_webgazer.recordScreenPosition = function (x, y) {
-        // give this the same weight that a click gets.
-        recordScreenPosition(x, y, eventTypes[0]);
-        return src_webgazer;
-      };
-
-      /**
-       *  Records current screen position for current pupil features.
-       *  @param {String} x - position on screen in the x axis
-       *  @param {String} y - position on screen in the y axis
-       *  @param {String} eventType - "click" or "move", as per eventTypes
-       *  @return {webgazer} this
-       */
-      src_webgazer.recordScreenPosition = function (x, y, eventType) {
-        // give this the same weight that a click gets.
-        recordScreenPosition(x, y, eventType);
-        return src_webgazer;
-      };
-
-      /*
-       * Stores the position of the fifty most recent tracker preditions
-       */
-      src_webgazer.storePoints = function (x, y, k) {
-        xPast50[k] = x;
-        yPast50[k] = y;
-      };
-
-      //SETTERS
-      /**
-       * Sets the tracking module
-       * @param {String} name - The name of the tracking module to use
-       * @return {webgazer} this
-       */
-      src_webgazer.setTracker = function (name) {
-        if (curTrackerMap[name] === undefined) {
-          console.log("Invalid tracker selection");
-          console.log("Options are: ");
-          for (var t in curTrackerMap) {
-            console.log(t);
-          }
-          return src_webgazer;
-        }
-        curTracker = curTrackerMap[name]();
-        return src_webgazer;
-      };
-
-      /**
-       * Sets the regression module and clears any other regression modules
-       * @param {String} name - The name of the regression module to use
-       * @return {webgazer} this
-       */
-      src_webgazer.setRegression = function (name) {
-        if (regressionMap[name] === undefined) {
-          console.log("Invalid regression selection");
-          console.log("Options are: ");
-          for (var reg in regressionMap) {
-            console.log(reg);
-          }
-          return src_webgazer;
-        }
-        data = regs[0].getData();
-        regs = [regressionMap[name]()];
-        regs[0].setData(data);
-        return src_webgazer;
-      };
-
-      /**
-       * Adds a new tracker module so that it can be used by setTracker()
-       * @param {String} name - the new name of the tracker
-       * @param {Function} constructor - the constructor of the curTracker object
-       * @return {webgazer} this
-       */
-      src_webgazer.addTrackerModule = function (name, constructor) {
-        curTrackerMap[name] = function () {
-          return new constructor();
-        };
-      };
-
-      /**
-       * Adds a new regression module so that it can be used by setRegression() and addRegression()
-       * @param {String} name - the new name of the regression
-       * @param {Function} constructor - the constructor of the regression object
-       */
-      src_webgazer.addRegressionModule = function (name, constructor) {
-        regressionMap[name] = function () {
-          return new constructor();
-        };
-      };
-
-      /**
-       * Adds a new regression module to the list of regression modules, seeding its data from the first regression module
-       * @param {String} name - the string name of the regression module to add
-       * @return {webgazer} this
-       */
-      src_webgazer.addRegression = function (name) {
-        var newReg = regressionMap[name]();
-        data = regs[0].getData();
-        newReg.setData(data);
-        regs.push(newReg);
-        return src_webgazer;
-      };
-
-      /**
-       * Sets a callback to be executed on every gaze event (currently all time steps)
-       * @param {function} listener - The callback function to call (it must be like function(data, elapsedTime))
-       * @return {webgazer} this
-       */
-      src_webgazer.setGazeListener = function (listener) {
-        callback = listener;
-        return src_webgazer;
-      };
-
-      /**
-       * Removes the callback set by setGazeListener
-       * @return {webgazer} this
-       */
-      src_webgazer.clearGazeListener = function () {
-        callback = nopCallback;
-        return src_webgazer;
-      };
-
-      /**
-       * Set the video element canvas; useful if you want to run WebGazer on your own canvas (e.g., on any random image).
-       * @return The current video element canvas
-       */
-      src_webgazer.setVideoElementCanvas = function (canvas) {
-        videoElementCanvas = canvas;
-      };
-
-      /**
-       * Clear data from localforage and from regs
-       */
-      src_webgazer.clearData = async function () {
-        clearData();
-      };
-
-      //GETTERS
-      /**
-       * Returns the tracker currently in use
-       * @return {tracker} an object following the tracker interface
-       */
-      src_webgazer.getTracker = function () {
-        return curTracker;
-      };
-
-      /**
-       * Returns the regression currently in use
-       * @return {Array.<Object>} an array of regression objects following the regression interface
-       */
-      src_webgazer.getRegression = function () {
-        return regs;
-      };
-
-      /**
-       * Requests an immediate prediction
-       * @return {object} prediction data object
-       */
-      src_webgazer.getCurrentPrediction = function () {
-        return getPrediction();
-      };
-
-      /**
-       * returns the different event types that may be passed to regressions when calling regression.addData()
-       * @return {Array} array of strings where each string is an event type
-       */
-      src_webgazer.params.getEventTypes = function () {
-        return eventTypes.slice();
-      };
-
-      /**
-       * Get the video element canvas that WebGazer uses internally on which to run its face tracker.
-       * @return The current video element canvas
-       */
-      src_webgazer.getVideoElementCanvas = function () {
-        return videoElementCanvas;
-      };
-
-      /**
-       * @return array [a,b] where a is width ratio and b is height ratio
-       */
-      src_webgazer.getVideoPreviewToCameraResolutionRatio = function () {
-        return [
-          src_webgazer.params.videoViewerWidth / videoElement.videoWidth,
-          src_webgazer.params.videoViewerHeight / videoElement.videoHeight,
-        ];
-      };
-
-      /*
-       * Gets the fifty most recent tracker preditions
-       */
-      src_webgazer.getStoredPoints = function () {
-        return [xPast50, yPast50];
-      };
-
-      /* harmony default export */ var src = (__webpack_exports__["default"] = src_webgazer);
-
-      /***/
-    },
-    /******/
-  ]
-)["default"];
-//# sourceMappingURL=webgazer.js.map
+/*!
+ *
+ *  WebGazer.js: Scalable Webcam EyeTracking Using User Interactions
+ *  Copyright (c) 2016-2020, Brown HCI Group
+ *  Licensed under GPLv3. Companies with a valuation of less than $1M can use WebGazer.js under LGPLv3.
+ *
+ */
+var webgazer = /******/ (function (modules) {
+  // webpackBootstrap
+  /******/ // The module cache
+  /******/ var installedModules = {};
+  /******/
+  /******/ // The require function
+  /******/ function __webpack_require__(moduleId) {
+    /******/
+    /******/ // Check if module is in cache
+    /******/ if (installedModules[moduleId]) {
+      /******/ return installedModules[moduleId].exports;
+      /******/
+    }
+    /******/ // Create a new module (and put it into the cache)
+    /******/ var module = (installedModules[moduleId] = {
+      /******/ i: moduleId,
+      /******/ l: false,
+      /******/ exports: {},
+      /******/
+    });
+    /******/
+    /******/ // Execute the module function
+    /******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__);
+    /******/
+    /******/ // Flag the module as loaded
+    /******/ module.l = true;
+    /******/
+    /******/ // Return the exports of the module
+    /******/ return module.exports;
+    /******/
+  }
+  /******/
+  /******/
+  /******/ // expose the modules object (__webpack_modules__)
+  /******/ __webpack_require__.m = modules;
+  /******/
+  /******/ // expose the module cache
+  /******/ __webpack_require__.c = installedModules;
+  /******/
+  /******/ // define getter function for harmony exports
+  /******/ __webpack_require__.d = function (exports, name, getter) {
+    /******/ if (!__webpack_require__.o(exports, name)) {
+      /******/ Object.defineProperty(exports, name, { enumerable: true, get: getter });
+      /******/
+    }
+    /******/
+  };
+  /******/
+  /******/ // define __esModule on exports
+  /******/ __webpack_require__.r = function (exports) {
+    /******/ if (typeof Symbol !== "undefined" && Symbol.toStringTag) {
+      /******/ Object.defineProperty(exports, Symbol.toStringTag, { value: "Module" });
+      /******/
+    }
+    /******/ Object.defineProperty(exports, "__esModule", { value: true });
+    /******/
+  };
+  /******/
+  /******/ // create a fake namespace object
+  /******/ // mode & 1: value is a module id, require it
+  /******/ // mode & 2: merge all properties of value into the ns
+  /******/ // mode & 4: return value when already ns object
+  /******/ // mode & 8|1: behave like require
+  /******/ __webpack_require__.t = function (value, mode) {
+    /******/ if (mode & 1) value = __webpack_require__(value);
+    /******/ if (mode & 8) return value;
+    /******/ if (mode & 4 && typeof value === "object" && value && value.__esModule) return value;
+    /******/ var ns = Object.create(null);
+    /******/ __webpack_require__.r(ns);
+    /******/ Object.defineProperty(ns, "default", { enumerable: true, value: value });
+    /******/ if (mode & 2 && typeof value != "string")
+      for (var key in value)
+        __webpack_require__.d(
+          ns,
+          key,
+          function (key) {
+            return value[key];
+          }.bind(null, key)
+        );
+    /******/ return ns;
+    /******/
+  };
+  /******/
+  /******/ // getDefaultExport function for compatibility with non-harmony modules
+  /******/ __webpack_require__.n = function (module) {
+    /******/ var getter =
+      module && module.__esModule
+        ? /******/ function getDefault() {
+            return module["default"];
+          }
+        : /******/ function getModuleExports() {
+            return module;
+          };
+    /******/ __webpack_require__.d(getter, "a", getter);
+    /******/ return getter;
+    /******/
+  };
+  /******/
+  /******/ // Object.prototype.hasOwnProperty.call
+  /******/ __webpack_require__.o = function (object, property) {
+    return Object.prototype.hasOwnProperty.call(object, property);
+  };
+  /******/
+  /******/ // __webpack_public_path__
+  /******/ __webpack_require__.p = "";
+  /******/
+  /******/
+  /******/ // Load entry module and return exports
+  /******/ return __webpack_require__((__webpack_require__.s = 90));
+  /******/
+})(
+  /************************************************************************/
+  /******/ [
+    /* 0 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      // ESM COMPAT FLAG
+      __webpack_require__.r(__webpack_exports__);
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "AdadeltaOptimizer", function () {
+        return /* reexport */ adadelta_optimizer_AdadeltaOptimizer;
+      });
+      __webpack_require__.d(__webpack_exports__, "AdagradOptimizer", function () {
+        return /* reexport */ adagrad_optimizer_AdagradOptimizer;
+      });
+      __webpack_require__.d(__webpack_exports__, "AdamOptimizer", function () {
+        return /* reexport */ adam_optimizer_AdamOptimizer;
+      });
+      __webpack_require__.d(__webpack_exports__, "AdamaxOptimizer", function () {
+        return /* reexport */ adamax_optimizer_AdamaxOptimizer;
+      });
+      __webpack_require__.d(__webpack_exports__, "MomentumOptimizer", function () {
+        return /* reexport */ momentum_optimizer_MomentumOptimizer;
+      });
+      __webpack_require__.d(__webpack_exports__, "Optimizer", function () {
+        return /* reexport */ optimizer_Optimizer;
+      });
+      __webpack_require__.d(__webpack_exports__, "RMSPropOptimizer", function () {
+        return /* reexport */ rmsprop_optimizer_RMSPropOptimizer;
+      });
+      __webpack_require__.d(__webpack_exports__, "SGDOptimizer", function () {
+        return /* reexport */ sgd_optimizer_SGDOptimizer;
+      });
+      __webpack_require__.d(__webpack_exports__, "Tensor", function () {
+        return /* reexport */ dist_tensor["a" /* Tensor */];
+      });
+      __webpack_require__.d(__webpack_exports__, "TensorBuffer", function () {
+        return /* reexport */ dist_tensor["b" /* TensorBuffer */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Variable", function () {
+        return /* reexport */ dist_tensor["c" /* Variable */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Rank", function () {
+        return /* reexport */ dist_types["a" /* Rank */];
+      });
+      __webpack_require__.d(__webpack_exports__, "sumOutType", function () {
+        return /* reexport */ dist_types["b" /* sumOutType */];
+      });
+      __webpack_require__.d(__webpack_exports__, "upcastType", function () {
+        return /* reexport */ dist_types["c" /* upcastType */];
+      });
+      __webpack_require__.d(__webpack_exports__, "add", function () {
+        return /* reexport */ add;
+      });
+      __webpack_require__.d(__webpack_exports__, "addN", function () {
+        return /* reexport */ addN;
+      });
+      __webpack_require__.d(__webpack_exports__, "atan2", function () {
+        return /* reexport */ atan2;
+      });
+      __webpack_require__.d(__webpack_exports__, "avgPool", function () {
+        return /* reexport */ avgPool;
+      });
+      __webpack_require__.d(__webpack_exports__, "avgPool3d", function () {
+        return /* reexport */ avgPool3d;
+      });
+      __webpack_require__.d(__webpack_exports__, "batchToSpaceND", function () {
+        return /* reexport */ batchToSpaceND;
+      });
+      __webpack_require__.d(__webpack_exports__, "batchNorm", function () {
+        return /* reexport */ batchNorm;
+      });
+      __webpack_require__.d(__webpack_exports__, "batchNorm2d", function () {
+        return /* reexport */ batchNorm2d;
+      });
+      __webpack_require__.d(__webpack_exports__, "batchNorm3d", function () {
+        return /* reexport */ batchNorm3d;
+      });
+      __webpack_require__.d(__webpack_exports__, "batchNorm4d", function () {
+        return /* reexport */ batchNorm4d;
+      });
+      __webpack_require__.d(__webpack_exports__, "broadcastTo", function () {
+        return /* reexport */ broadcastTo;
+      });
+      __webpack_require__.d(__webpack_exports__, "clone", function () {
+        return /* reexport */ clone;
+      });
+      __webpack_require__.d(__webpack_exports__, "complex", function () {
+        return /* reexport */ complex["a" /* complex */];
+      });
+      __webpack_require__.d(__webpack_exports__, "concat", function () {
+        return /* reexport */ concat;
+      });
+      __webpack_require__.d(__webpack_exports__, "concat1d", function () {
+        return /* reexport */ concat1d;
+      });
+      __webpack_require__.d(__webpack_exports__, "concat2d", function () {
+        return /* reexport */ concat2d;
+      });
+      __webpack_require__.d(__webpack_exports__, "concat3d", function () {
+        return /* reexport */ concat3d;
+      });
+      __webpack_require__.d(__webpack_exports__, "concat4d", function () {
+        return /* reexport */ concat4d;
+      });
+      __webpack_require__.d(__webpack_exports__, "conv1d", function () {
+        return /* reexport */ conv1d;
+      });
+      __webpack_require__.d(__webpack_exports__, "conv2d", function () {
+        return /* reexport */ conv2d;
+      });
+      __webpack_require__.d(__webpack_exports__, "conv2dTranspose", function () {
+        return /* reexport */ conv2dTranspose;
+      });
+      __webpack_require__.d(__webpack_exports__, "conv3d", function () {
+        return /* reexport */ conv3d;
+      });
+      __webpack_require__.d(__webpack_exports__, "conv3dTranspose", function () {
+        return /* reexport */ conv3dTranspose;
+      });
+      __webpack_require__.d(__webpack_exports__, "cumsum", function () {
+        return /* reexport */ cumsum;
+      });
+      __webpack_require__.d(__webpack_exports__, "depthToSpace", function () {
+        return /* reexport */ depthToSpace;
+      });
+      __webpack_require__.d(__webpack_exports__, "depthwiseConv2d", function () {
+        return /* reexport */ depthwiseConv2d;
+      });
+      __webpack_require__.d(__webpack_exports__, "diag", function () {
+        return /* reexport */ diag;
+      });
+      __webpack_require__.d(__webpack_exports__, "div", function () {
+        return /* reexport */ div;
+      });
+      __webpack_require__.d(__webpack_exports__, "divNoNan", function () {
+        return /* reexport */ divNoNan;
+      });
+      __webpack_require__.d(__webpack_exports__, "dot", function () {
+        return /* reexport */ dot;
+      });
+      __webpack_require__.d(__webpack_exports__, "elu", function () {
+        return /* reexport */ elu;
+      });
+      __webpack_require__.d(__webpack_exports__, "equal", function () {
+        return /* reexport */ equal;
+      });
+      __webpack_require__.d(__webpack_exports__, "eye", function () {
+        return /* reexport */ eye;
+      });
+      __webpack_require__.d(__webpack_exports__, "fill", function () {
+        return /* reexport */ fill;
+      });
+      __webpack_require__.d(__webpack_exports__, "floorDiv", function () {
+        return /* reexport */ floorDiv;
+      });
+      __webpack_require__.d(__webpack_exports__, "greater", function () {
+        return /* reexport */ greater;
+      });
+      __webpack_require__.d(__webpack_exports__, "greaterEqual", function () {
+        return /* reexport */ greaterEqual;
+      });
+      __webpack_require__.d(__webpack_exports__, "imag", function () {
+        return /* reexport */ imag["a" /* imag */];
+      });
+      __webpack_require__.d(__webpack_exports__, "leakyRelu", function () {
+        return /* reexport */ leakyRelu;
+      });
+      __webpack_require__.d(__webpack_exports__, "less", function () {
+        return /* reexport */ less;
+      });
+      __webpack_require__.d(__webpack_exports__, "lessEqual", function () {
+        return /* reexport */ lessEqual;
+      });
+      __webpack_require__.d(__webpack_exports__, "localResponseNormalization", function () {
+        return /* reexport */ localResponseNormalization;
+      });
+      __webpack_require__.d(__webpack_exports__, "matMul", function () {
+        return /* reexport */ matMul;
+      });
+      __webpack_require__.d(__webpack_exports__, "max", function () {
+        return /* reexport */ max_max;
+      });
+      __webpack_require__.d(__webpack_exports__, "maxPool", function () {
+        return /* reexport */ maxPool;
+      });
+      __webpack_require__.d(__webpack_exports__, "maxPool3d", function () {
+        return /* reexport */ maxPool3d;
+      });
+      __webpack_require__.d(__webpack_exports__, "maxPoolWithArgmax", function () {
+        return /* reexport */ maxPoolWithArgmax;
+      });
+      __webpack_require__.d(__webpack_exports__, "maximum", function () {
+        return /* reexport */ maximum;
+      });
+      __webpack_require__.d(__webpack_exports__, "minimum", function () {
+        return /* reexport */ minimum;
+      });
+      __webpack_require__.d(__webpack_exports__, "mod", function () {
+        return /* reexport */ mod;
+      });
+      __webpack_require__.d(__webpack_exports__, "mul", function () {
+        return /* reexport */ mul;
+      });
+      __webpack_require__.d(__webpack_exports__, "multinomial", function () {
+        return /* reexport */ multinomial;
+      });
+      __webpack_require__.d(__webpack_exports__, "notEqual", function () {
+        return /* reexport */ notEqual;
+      });
+      __webpack_require__.d(__webpack_exports__, "oneHot", function () {
+        return /* reexport */ oneHot;
+      });
+      __webpack_require__.d(__webpack_exports__, "outerProduct", function () {
+        return /* reexport */ outerProduct;
+      });
+      __webpack_require__.d(__webpack_exports__, "pad", function () {
+        return /* reexport */ pad_pad;
+      });
+      __webpack_require__.d(__webpack_exports__, "pad1d", function () {
+        return /* reexport */ pad1d;
+      });
+      __webpack_require__.d(__webpack_exports__, "pad2d", function () {
+        return /* reexport */ pad2d;
+      });
+      __webpack_require__.d(__webpack_exports__, "pad3d", function () {
+        return /* reexport */ pad3d;
+      });
+      __webpack_require__.d(__webpack_exports__, "pad4d", function () {
+        return /* reexport */ pad4d;
+      });
+      __webpack_require__.d(__webpack_exports__, "pool", function () {
+        return /* reexport */ pool;
+      });
+      __webpack_require__.d(__webpack_exports__, "pow", function () {
+        return /* reexport */ pow;
+      });
+      __webpack_require__.d(__webpack_exports__, "prelu", function () {
+        return /* reexport */ prelu;
+      });
+      __webpack_require__.d(__webpack_exports__, "rand", function () {
+        return /* reexport */ rand;
+      });
+      __webpack_require__.d(__webpack_exports__, "randomGamma", function () {
+        return /* reexport */ randomGamma;
+      });
+      __webpack_require__.d(__webpack_exports__, "randomNormal", function () {
+        return /* reexport */ randomNormal;
+      });
+      __webpack_require__.d(__webpack_exports__, "randomUniform", function () {
+        return /* reexport */ randomUniform;
+      });
+      __webpack_require__.d(__webpack_exports__, "real", function () {
+        return /* reexport */ real["a" /* real */];
+      });
+      __webpack_require__.d(__webpack_exports__, "relu", function () {
+        return /* reexport */ relu;
+      });
+      __webpack_require__.d(__webpack_exports__, "relu6", function () {
+        return /* reexport */ relu6;
+      });
+      __webpack_require__.d(__webpack_exports__, "selu", function () {
+        return /* reexport */ selu;
+      });
+      __webpack_require__.d(__webpack_exports__, "separableConv2d", function () {
+        return /* reexport */ separableConv2d;
+      });
+      __webpack_require__.d(__webpack_exports__, "spaceToBatchND", function () {
+        return /* reexport */ spaceToBatchND;
+      });
+      __webpack_require__.d(__webpack_exports__, "split", function () {
+        return /* reexport */ split;
+      });
+      __webpack_require__.d(__webpack_exports__, "square", function () {
+        return /* reexport */ square;
+      });
+      __webpack_require__.d(__webpack_exports__, "squaredDifference", function () {
+        return /* reexport */ squaredDifference;
+      });
+      __webpack_require__.d(__webpack_exports__, "sub", function () {
+        return /* reexport */ sub;
+      });
+      __webpack_require__.d(__webpack_exports__, "tile", function () {
+        return /* reexport */ tile;
+      });
+      __webpack_require__.d(__webpack_exports__, "truncatedNormal", function () {
+        return /* reexport */ truncatedNormal;
+      });
+      __webpack_require__.d(__webpack_exports__, "booleanMaskAsync", function () {
+        return /* reexport */ booleanMaskAsync;
+      });
+      __webpack_require__.d(__webpack_exports__, "reverse", function () {
+        return /* reexport */ reverse_reverse;
+      });
+      __webpack_require__.d(__webpack_exports__, "reverse1d", function () {
+        return /* reexport */ reverse1d;
+      });
+      __webpack_require__.d(__webpack_exports__, "reverse2d", function () {
+        return /* reexport */ reverse2d;
+      });
+      __webpack_require__.d(__webpack_exports__, "reverse3d", function () {
+        return /* reexport */ reverse3d;
+      });
+      __webpack_require__.d(__webpack_exports__, "reverse4d", function () {
+        return /* reexport */ reverse4d;
+      });
+      __webpack_require__.d(__webpack_exports__, "slice", function () {
+        return /* reexport */ slice;
+      });
+      __webpack_require__.d(__webpack_exports__, "slice1d", function () {
+        return /* reexport */ slice1d;
+      });
+      __webpack_require__.d(__webpack_exports__, "slice2d", function () {
+        return /* reexport */ slice2d;
+      });
+      __webpack_require__.d(__webpack_exports__, "slice3d", function () {
+        return /* reexport */ slice3d;
+      });
+      __webpack_require__.d(__webpack_exports__, "slice4d", function () {
+        return /* reexport */ slice4d;
+      });
+      __webpack_require__.d(__webpack_exports__, "abs", function () {
+        return /* reexport */ abs;
+      });
+      __webpack_require__.d(__webpack_exports__, "acos", function () {
+        return /* reexport */ acos;
+      });
+      __webpack_require__.d(__webpack_exports__, "acosh", function () {
+        return /* reexport */ acosh;
+      });
+      __webpack_require__.d(__webpack_exports__, "asin", function () {
+        return /* reexport */ asin;
+      });
+      __webpack_require__.d(__webpack_exports__, "asinh", function () {
+        return /* reexport */ asinh;
+      });
+      __webpack_require__.d(__webpack_exports__, "atan", function () {
+        return /* reexport */ atan;
+      });
+      __webpack_require__.d(__webpack_exports__, "atanh", function () {
+        return /* reexport */ atanh;
+      });
+      __webpack_require__.d(__webpack_exports__, "ceil", function () {
+        return /* reexport */ ceil;
+      });
+      __webpack_require__.d(__webpack_exports__, "clipByValue", function () {
+        return /* reexport */ clipByValue;
+      });
+      __webpack_require__.d(__webpack_exports__, "cos", function () {
+        return /* reexport */ cos;
+      });
+      __webpack_require__.d(__webpack_exports__, "cosh", function () {
+        return /* reexport */ cosh;
+      });
+      __webpack_require__.d(__webpack_exports__, "erf", function () {
+        return /* reexport */ erf;
+      });
+      __webpack_require__.d(__webpack_exports__, "exp", function () {
+        return /* reexport */ unary_ops_exp;
+      });
+      __webpack_require__.d(__webpack_exports__, "expm1", function () {
+        return /* reexport */ expm1;
+      });
+      __webpack_require__.d(__webpack_exports__, "floor", function () {
+        return /* reexport */ floor;
+      });
+      __webpack_require__.d(__webpack_exports__, "log", function () {
+        return /* reexport */ log;
+      });
+      __webpack_require__.d(__webpack_exports__, "log1p", function () {
+        return /* reexport */ log1p;
+      });
+      __webpack_require__.d(__webpack_exports__, "logSigmoid", function () {
+        return /* reexport */ logSigmoid;
+      });
+      __webpack_require__.d(__webpack_exports__, "neg", function () {
+        return /* reexport */ neg;
+      });
+      __webpack_require__.d(__webpack_exports__, "reciprocal", function () {
+        return /* reexport */ reciprocal;
+      });
+      __webpack_require__.d(__webpack_exports__, "round", function () {
+        return /* reexport */ round;
+      });
+      __webpack_require__.d(__webpack_exports__, "rsqrt", function () {
+        return /* reexport */ rsqrt;
+      });
+      __webpack_require__.d(__webpack_exports__, "sigmoid", function () {
+        return /* reexport */ sigmoid;
+      });
+      __webpack_require__.d(__webpack_exports__, "sign", function () {
+        return /* reexport */ sign;
+      });
+      __webpack_require__.d(__webpack_exports__, "isNaN", function () {
+        return /* reexport */ unary_ops_isNaN;
+      });
+      __webpack_require__.d(__webpack_exports__, "isInf", function () {
+        return /* reexport */ isInf;
+      });
+      __webpack_require__.d(__webpack_exports__, "isFinite", function () {
+        return /* reexport */ unary_ops_isFinite;
+      });
+      __webpack_require__.d(__webpack_exports__, "sin", function () {
+        return /* reexport */ sin;
+      });
+      __webpack_require__.d(__webpack_exports__, "sinh", function () {
+        return /* reexport */ sinh;
+      });
+      __webpack_require__.d(__webpack_exports__, "softplus", function () {
+        return /* reexport */ softplus;
+      });
+      __webpack_require__.d(__webpack_exports__, "sqrt", function () {
+        return /* reexport */ sqrt;
+      });
+      __webpack_require__.d(__webpack_exports__, "step", function () {
+        return /* reexport */ unary_ops_step;
+      });
+      __webpack_require__.d(__webpack_exports__, "tan", function () {
+        return /* reexport */ tan;
+      });
+      __webpack_require__.d(__webpack_exports__, "tanh", function () {
+        return /* reexport */ tanh;
+      });
+      __webpack_require__.d(__webpack_exports__, "all", function () {
+        return /* reexport */ reduction_ops_all;
+      });
+      __webpack_require__.d(__webpack_exports__, "any", function () {
+        return /* reexport */ any;
+      });
+      __webpack_require__.d(__webpack_exports__, "argMax", function () {
+        return /* reexport */ argMax;
+      });
+      __webpack_require__.d(__webpack_exports__, "argMin", function () {
+        return /* reexport */ argMin;
+      });
+      __webpack_require__.d(__webpack_exports__, "logSumExp", function () {
+        return /* reexport */ logSumExp;
+      });
+      __webpack_require__.d(__webpack_exports__, "mean", function () {
+        return /* reexport */ reduction_ops_mean;
+      });
+      __webpack_require__.d(__webpack_exports__, "min", function () {
+        return /* reexport */ reduction_ops_min;
+      });
+      __webpack_require__.d(__webpack_exports__, "moments", function () {
+        return /* reexport */ moments;
+      });
+      __webpack_require__.d(__webpack_exports__, "sum", function () {
+        return /* reexport */ sum;
+      });
+      __webpack_require__.d(__webpack_exports__, "prod", function () {
+        return /* reexport */ reduction_ops_prod;
+      });
+      __webpack_require__.d(__webpack_exports__, "equalStrict", function () {
+        return /* reexport */ equalStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "greaterEqualStrict", function () {
+        return /* reexport */ greaterEqualStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "greaterStrict", function () {
+        return /* reexport */ greaterStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "lessEqualStrict", function () {
+        return /* reexport */ lessEqualStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "lessStrict", function () {
+        return /* reexport */ lessStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "notEqualStrict", function () {
+        return /* reexport */ notEqualStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "addStrict", function () {
+        return /* reexport */ addStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "divStrict", function () {
+        return /* reexport */ divStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "maximumStrict", function () {
+        return /* reexport */ maximumStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "minimumStrict", function () {
+        return /* reexport */ minimumStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "modStrict", function () {
+        return /* reexport */ modStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "mulStrict", function () {
+        return /* reexport */ mulStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "powStrict", function () {
+        return /* reexport */ powStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "squaredDifferenceStrict", function () {
+        return /* reexport */ squaredDifferenceStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "subStrict", function () {
+        return /* reexport */ subStrict;
+      });
+      __webpack_require__.d(__webpack_exports__, "logicalAnd", function () {
+        return /* reexport */ logicalAnd;
+      });
+      __webpack_require__.d(__webpack_exports__, "logicalNot", function () {
+        return /* reexport */ logicalNot;
+      });
+      __webpack_require__.d(__webpack_exports__, "logicalOr", function () {
+        return /* reexport */ logicalOr;
+      });
+      __webpack_require__.d(__webpack_exports__, "logicalXor", function () {
+        return /* reexport */ logicalXor;
+      });
+      __webpack_require__.d(__webpack_exports__, "where", function () {
+        return /* reexport */ where;
+      });
+      __webpack_require__.d(__webpack_exports__, "whereAsync", function () {
+        return /* reexport */ whereAsync;
+      });
+      __webpack_require__.d(__webpack_exports__, "buffer", function () {
+        return /* reexport */ array_ops_buffer;
+      });
+      __webpack_require__.d(__webpack_exports__, "print", function () {
+        return /* reexport */ print;
+      });
+      __webpack_require__.d(__webpack_exports__, "cast", function () {
+        return /* reexport */ cast;
+      });
+      __webpack_require__.d(__webpack_exports__, "expandDims", function () {
+        return /* reexport */ expandDims;
+      });
+      __webpack_require__.d(__webpack_exports__, "reshape", function () {
+        return /* reexport */ reshape;
+      });
+      __webpack_require__.d(__webpack_exports__, "squeeze", function () {
+        return /* reexport */ squeeze;
+      });
+      __webpack_require__.d(__webpack_exports__, "stack", function () {
+        return /* reexport */ stack;
+      });
+      __webpack_require__.d(__webpack_exports__, "unstack", function () {
+        return /* reexport */ unstack;
+      });
+      __webpack_require__.d(__webpack_exports__, "setdiff1dAsync", function () {
+        return /* reexport */ setdiff1dAsync;
+      });
+      __webpack_require__.d(__webpack_exports__, "linspace", function () {
+        return /* reexport */ tensor_ops["a" /* linspace */];
+      });
+      __webpack_require__.d(__webpack_exports__, "ones", function () {
+        return /* reexport */ tensor_ops["b" /* ones */];
+      });
+      __webpack_require__.d(__webpack_exports__, "range", function () {
+        return /* reexport */ tensor_ops["d" /* range */];
+      });
+      __webpack_require__.d(__webpack_exports__, "scalar", function () {
+        return /* reexport */ tensor_ops["e" /* scalar */];
+      });
+      __webpack_require__.d(__webpack_exports__, "tensor", function () {
+        return /* reexport */ tensor_ops["f" /* tensor */];
+      });
+      __webpack_require__.d(__webpack_exports__, "tensor1d", function () {
+        return /* reexport */ tensor_ops["g" /* tensor1d */];
+      });
+      __webpack_require__.d(__webpack_exports__, "tensor2d", function () {
+        return /* reexport */ tensor_ops["h" /* tensor2d */];
+      });
+      __webpack_require__.d(__webpack_exports__, "tensor3d", function () {
+        return /* reexport */ tensor_ops["i" /* tensor3d */];
+      });
+      __webpack_require__.d(__webpack_exports__, "tensor4d", function () {
+        return /* reexport */ tensor_ops["j" /* tensor4d */];
+      });
+      __webpack_require__.d(__webpack_exports__, "tensor5d", function () {
+        return /* reexport */ tensor_ops["k" /* tensor5d */];
+      });
+      __webpack_require__.d(__webpack_exports__, "tensor6d", function () {
+        return /* reexport */ tensor_ops["l" /* tensor6d */];
+      });
+      __webpack_require__.d(__webpack_exports__, "variable", function () {
+        return /* reexport */ tensor_ops["m" /* variable */];
+      });
+      __webpack_require__.d(__webpack_exports__, "zeros", function () {
+        return /* reexport */ tensor_ops["n" /* zeros */];
+      });
+      __webpack_require__.d(__webpack_exports__, "onesLike", function () {
+        return /* reexport */ tensor_ops["c" /* onesLike */];
+      });
+      __webpack_require__.d(__webpack_exports__, "zerosLike", function () {
+        return /* reexport */ tensor_ops["o" /* zerosLike */];
+      });
+      __webpack_require__.d(__webpack_exports__, "transpose", function () {
+        return /* reexport */ transpose;
+      });
+      __webpack_require__.d(__webpack_exports__, "softmax", function () {
+        return /* reexport */ softmax;
+      });
+      __webpack_require__.d(__webpack_exports__, "logSoftmax", function () {
+        return /* reexport */ logSoftmax;
+      });
+      __webpack_require__.d(__webpack_exports__, "norm", function () {
+        return /* reexport */ norm_norm;
+      });
+      __webpack_require__.d(__webpack_exports__, "gather", function () {
+        return /* reexport */ gather;
+      });
+      __webpack_require__.d(__webpack_exports__, "unsortedSegmentSum", function () {
+        return /* reexport */ unsortedSegmentSum;
+      });
+      __webpack_require__.d(__webpack_exports__, "basicLSTMCell", function () {
+        return /* reexport */ basicLSTMCell;
+      });
+      __webpack_require__.d(__webpack_exports__, "multiRNNCell", function () {
+        return /* reexport */ multiRNNCell;
+      });
+      __webpack_require__.d(__webpack_exports__, "movingAverage", function () {
+        return /* reexport */ movingAverage;
+      });
+      __webpack_require__.d(__webpack_exports__, "stridedSlice", function () {
+        return /* reexport */ stridedSlice;
+      });
+      __webpack_require__.d(__webpack_exports__, "topk", function () {
+        return /* reexport */ topk;
+      });
+      __webpack_require__.d(__webpack_exports__, "scatterND", function () {
+        return /* reexport */ scatterND;
+      });
+      __webpack_require__.d(__webpack_exports__, "fft", function () {
+        return /* reexport */ fft;
+      });
+      __webpack_require__.d(__webpack_exports__, "ifft", function () {
+        return /* reexport */ ifft;
+      });
+      __webpack_require__.d(__webpack_exports__, "rfft", function () {
+        return /* reexport */ rfft;
+      });
+      __webpack_require__.d(__webpack_exports__, "irfft", function () {
+        return /* reexport */ irfft;
+      });
+      __webpack_require__.d(__webpack_exports__, "sparseToDense", function () {
+        return /* reexport */ sparseToDense;
+      });
+      __webpack_require__.d(__webpack_exports__, "gatherND", function () {
+        return /* reexport */ gatherND;
+      });
+      __webpack_require__.d(__webpack_exports__, "dropout", function () {
+        return /* reexport */ dropout;
+      });
+      __webpack_require__.d(__webpack_exports__, "hannWindow", function () {
+        return /* reexport */ hannWindow;
+      });
+      __webpack_require__.d(__webpack_exports__, "hammingWindow", function () {
+        return /* reexport */ hammingWindow;
+      });
+      __webpack_require__.d(__webpack_exports__, "frame", function () {
+        return /* reexport */ signal_ops_frame;
+      });
+      __webpack_require__.d(__webpack_exports__, "stft", function () {
+        return /* reexport */ stft;
+      });
+      __webpack_require__.d(__webpack_exports__, "inTopKAsync", function () {
+        return /* reexport */ inTopKAsync;
+      });
+      __webpack_require__.d(__webpack_exports__, "op", function () {
+        return /* reexport */ operation["a" /* op */];
+      });
+      __webpack_require__.d(__webpack_exports__, "image", function () {
+        return /* reexport */ image_ops_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "linalg", function () {
+        return /* reexport */ linalg_ops_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "losses", function () {
+        return /* reexport */ loss_ops_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "spectral", function () {
+        return /* reexport */ spectral_ops_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "fused", function () {
+        return /* reexport */ fused_ops_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "signal", function () {
+        return /* reexport */ signal_ops_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "Reduction", function () {
+        return /* reexport */ Reduction;
+      });
+      __webpack_require__.d(__webpack_exports__, "train", function () {
+        return /* reexport */ train;
+      });
+      __webpack_require__.d(__webpack_exports__, "enableProdMode", function () {
+        return /* reexport */ enableProdMode;
+      });
+      __webpack_require__.d(__webpack_exports__, "enableDebugMode", function () {
+        return /* reexport */ enableDebugMode;
+      });
+      __webpack_require__.d(__webpack_exports__, "disableDeprecationWarnings", function () {
+        return /* reexport */ disableDeprecationWarnings;
+      });
+      __webpack_require__.d(__webpack_exports__, "deprecationWarn", function () {
+        return /* reexport */ deprecationWarn;
+      });
+      __webpack_require__.d(__webpack_exports__, "disposeVariables", function () {
+        return /* reexport */ disposeVariables;
+      });
+      __webpack_require__.d(__webpack_exports__, "engine", function () {
+        return /* reexport */ globals_engine;
+      });
+      __webpack_require__.d(__webpack_exports__, "memory", function () {
+        return /* reexport */ memory;
+      });
+      __webpack_require__.d(__webpack_exports__, "profile", function () {
+        return /* reexport */ profile;
+      });
+      __webpack_require__.d(__webpack_exports__, "tidy", function () {
+        return /* reexport */ tidy;
+      });
+      __webpack_require__.d(__webpack_exports__, "dispose", function () {
+        return /* reexport */ dispose;
+      });
+      __webpack_require__.d(__webpack_exports__, "keep", function () {
+        return /* reexport */ keep;
+      });
+      __webpack_require__.d(__webpack_exports__, "time", function () {
+        return /* reexport */ time;
+      });
+      __webpack_require__.d(__webpack_exports__, "setBackend", function () {
+        return /* reexport */ setBackend;
+      });
+      __webpack_require__.d(__webpack_exports__, "ready", function () {
+        return /* reexport */ ready;
+      });
+      __webpack_require__.d(__webpack_exports__, "getBackend", function () {
+        return /* reexport */ getBackend;
+      });
+      __webpack_require__.d(__webpack_exports__, "removeBackend", function () {
+        return /* reexport */ removeBackend;
+      });
+      __webpack_require__.d(__webpack_exports__, "findBackend", function () {
+        return /* reexport */ findBackend;
+      });
+      __webpack_require__.d(__webpack_exports__, "findBackendFactory", function () {
+        return /* reexport */ findBackendFactory;
+      });
+      __webpack_require__.d(__webpack_exports__, "registerBackend", function () {
+        return /* reexport */ registerBackend;
+      });
+      __webpack_require__.d(__webpack_exports__, "backend", function () {
+        return /* reexport */ globals_backend;
+      });
+      __webpack_require__.d(__webpack_exports__, "setPlatform", function () {
+        return /* reexport */ setPlatform;
+      });
+      __webpack_require__.d(__webpack_exports__, "getKernel", function () {
+        return /* reexport */ kernel_registry["b" /* getKernel */];
+      });
+      __webpack_require__.d(__webpack_exports__, "getGradient", function () {
+        return /* reexport */ kernel_registry["a" /* getGradient */];
+      });
+      __webpack_require__.d(__webpack_exports__, "getKernelsForBackend", function () {
+        return /* reexport */ kernel_registry["c" /* getKernelsForBackend */];
+      });
+      __webpack_require__.d(__webpack_exports__, "registerKernel", function () {
+        return /* reexport */ kernel_registry["e" /* registerKernel */];
+      });
+      __webpack_require__.d(__webpack_exports__, "registerGradient", function () {
+        return /* reexport */ kernel_registry["d" /* registerGradient */];
+      });
+      __webpack_require__.d(__webpack_exports__, "unregisterKernel", function () {
+        return /* reexport */ kernel_registry["g" /* unregisterKernel */];
+      });
+      __webpack_require__.d(__webpack_exports__, "unregisterGradient", function () {
+        return /* reexport */ kernel_registry["f" /* unregisterGradient */];
+      });
+      __webpack_require__.d(__webpack_exports__, "customGrad", function () {
+        return /* reexport */ customGrad;
+      });
+      __webpack_require__.d(__webpack_exports__, "grad", function () {
+        return /* reexport */ gradients_grad;
+      });
+      __webpack_require__.d(__webpack_exports__, "grads", function () {
+        return /* reexport */ gradients_grads;
+      });
+      __webpack_require__.d(__webpack_exports__, "valueAndGrad", function () {
+        return /* reexport */ valueAndGrad;
+      });
+      __webpack_require__.d(__webpack_exports__, "valueAndGrads", function () {
+        return /* reexport */ valueAndGrads;
+      });
+      __webpack_require__.d(__webpack_exports__, "variableGrads", function () {
+        return /* reexport */ variableGrads;
+      });
+      __webpack_require__.d(__webpack_exports__, "Environment", function () {
+        return /* reexport */ environment["b" /* Environment */];
+      });
+      __webpack_require__.d(__webpack_exports__, "env", function () {
+        return /* reexport */ environment["c" /* env */];
+      });
+      __webpack_require__.d(__webpack_exports__, "ENV", function () {
+        return /* reexport */ environment["a" /* ENV */];
+      });
+      __webpack_require__.d(__webpack_exports__, "version_core", function () {
+        return /* reexport */ version;
+      });
+      __webpack_require__.d(__webpack_exports__, "nextFrame", function () {
+        return /* reexport */ browser_util["a" /* nextFrame */];
+      });
+      __webpack_require__.d(__webpack_exports__, "browser", function () {
+        return /* reexport */ browser_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "io", function () {
+        return /* reexport */ io_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "math", function () {
+        return /* reexport */ math_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "serialization", function () {
+        return /* reexport */ serialization_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "test_util", function () {
+        return /* reexport */ test_util_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "util", function () {
+        return /* reexport */ util;
+      });
+      __webpack_require__.d(__webpack_exports__, "backend_util", function () {
+        return /* reexport */ backend_util_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "tensor_util", function () {
+        return /* reexport */ tensor_util;
+      });
+      __webpack_require__.d(__webpack_exports__, "slice_util", function () {
+        return /* reexport */ slice_util_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "gather_util", function () {
+        return /* reexport */ gather_nd_util_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "scatter_util", function () {
+        return /* reexport */ scatter_nd_util_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "device_util", function () {
+        return /* reexport */ device_util;
+      });
+      __webpack_require__.d(__webpack_exports__, "kernel_impls", function () {
+        return /* reexport */ kernel_impls_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "KernelBackend", function () {
+        return /* reexport */ KernelBackend;
+      });
+      __webpack_require__.d(__webpack_exports__, "DataStorage", function () {
+        return /* reexport */ DataStorage;
+      });
+      __webpack_require__.d(__webpack_exports__, "Add", function () {
+        return /* reexport */ kernel_names["a" /* Add */];
+      });
+      __webpack_require__.d(__webpack_exports__, "AddN", function () {
+        return /* reexport */ kernel_names["b" /* AddN */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Atan2", function () {
+        return /* reexport */ kernel_names["c" /* Atan2 */];
+      });
+      __webpack_require__.d(__webpack_exports__, "AvgPool", function () {
+        return /* reexport */ kernel_names["d" /* AvgPool */];
+      });
+      __webpack_require__.d(__webpack_exports__, "AvgPoolBackprop", function () {
+        return /* reexport */ kernel_names["g" /* AvgPoolBackprop */];
+      });
+      __webpack_require__.d(__webpack_exports__, "AvgPool3D", function () {
+        return /* reexport */ kernel_names["e" /* AvgPool3D */];
+      });
+      __webpack_require__.d(__webpack_exports__, "AvgPool3DBackprop", function () {
+        return /* reexport */ kernel_names["f" /* AvgPool3DBackprop */];
+      });
+      __webpack_require__.d(__webpack_exports__, "BatchMatMul", function () {
+        return /* reexport */ kernel_names["h" /* BatchMatMul */];
+      });
+      __webpack_require__.d(__webpack_exports__, "BatchToSpaceND", function () {
+        return /* reexport */ kernel_names["i" /* BatchToSpaceND */];
+      });
+      __webpack_require__.d(__webpack_exports__, "BroadcastTo", function () {
+        return /* reexport */ kernel_names["j" /* BroadcastTo */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Complex", function () {
+        return /* reexport */ kernel_names["k" /* Complex */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Concat", function () {
+        return /* reexport */ kernel_names["l" /* Concat */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Conv2D", function () {
+        return /* reexport */ kernel_names["m" /* Conv2D */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Conv2DBackpropFilter", function () {
+        return /* reexport */ kernel_names["n" /* Conv2DBackpropFilter */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Conv2DBackpropInput", function () {
+        return /* reexport */ kernel_names["o" /* Conv2DBackpropInput */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Conv3D", function () {
+        return /* reexport */ kernel_names["p" /* Conv3D */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Conv3DBackpropFilterV2", function () {
+        return /* reexport */ kernel_names["q" /* Conv3DBackpropFilterV2 */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Conv3DBackpropInputV2", function () {
+        return /* reexport */ kernel_names["r" /* Conv3DBackpropInputV2 */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Cumsum", function () {
+        return /* reexport */ kernel_names["s" /* Cumsum */];
+      });
+      __webpack_require__.d(__webpack_exports__, "DepthToSpace", function () {
+        return /* reexport */ kernel_names["t" /* DepthToSpace */];
+      });
+      __webpack_require__.d(__webpack_exports__, "DepthwiseConv2dNative", function () {
+        return /* reexport */ kernel_names["u" /* DepthwiseConv2dNative */];
+      });
+      __webpack_require__.d(
+        __webpack_exports__,
+        "DepthwiseConv2dNativeBackpropFilter",
+        function () {
+          return /* reexport */ kernel_names["v" /* DepthwiseConv2dNativeBackpropFilter */];
+        }
+      );
+      __webpack_require__.d(__webpack_exports__, "DepthwiseConv2dNativeBackpropInput", function () {
+        return /* reexport */ kernel_names["w" /* DepthwiseConv2dNativeBackpropInput */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Diag", function () {
+        return /* reexport */ kernel_names["x" /* Diag */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Div", function () {
+        return /* reexport */ kernel_names["y" /* Div */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Elu", function () {
+        return /* reexport */ kernel_names["z" /* Elu */];
+      });
+      __webpack_require__.d(__webpack_exports__, "EluGrad", function () {
+        return /* reexport */ kernel_names["A" /* EluGrad */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Equal", function () {
+        return /* reexport */ kernel_names["B" /* Equal */];
+      });
+      __webpack_require__.d(__webpack_exports__, "FloorDiv", function () {
+        return /* reexport */ kernel_names["D" /* FloorDiv */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Fill", function () {
+        return /* reexport */ kernel_names["C" /* Fill */];
+      });
+      __webpack_require__.d(__webpack_exports__, "FusedBatchNorm", function () {
+        return /* reexport */ kernel_names["F" /* FusedBatchNorm */];
+      });
+      __webpack_require__.d(__webpack_exports__, "GatherNd", function () {
+        return /* reexport */ kernel_names["G" /* GatherNd */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Greater", function () {
+        return /* reexport */ kernel_names["H" /* Greater */];
+      });
+      __webpack_require__.d(__webpack_exports__, "GreaterEqual", function () {
+        return /* reexport */ kernel_names["I" /* GreaterEqual */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Identity", function () {
+        return /* reexport */ kernel_names["J" /* Identity */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Imag", function () {
+        return /* reexport */ kernel_names["K" /* Imag */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Less", function () {
+        return /* reexport */ kernel_names["N" /* Less */];
+      });
+      __webpack_require__.d(__webpack_exports__, "LessEqual", function () {
+        return /* reexport */ kernel_names["O" /* LessEqual */];
+      });
+      __webpack_require__.d(__webpack_exports__, "LRN", function () {
+        return /* reexport */ kernel_names["L" /* LRN */];
+      });
+      __webpack_require__.d(__webpack_exports__, "LRNBackprop", function () {
+        return /* reexport */ kernel_names["M" /* LRNBackprop */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Max", function () {
+        return /* reexport */ kernel_names["P" /* Max */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Maximum", function () {
+        return /* reexport */ kernel_names["V" /* Maximum */];
+      });
+      __webpack_require__.d(__webpack_exports__, "MaxPool", function () {
+        return /* reexport */ kernel_names["Q" /* MaxPool */];
+      });
+      __webpack_require__.d(__webpack_exports__, "MaxPoolBackprop", function () {
+        return /* reexport */ kernel_names["T" /* MaxPoolBackprop */];
+      });
+      __webpack_require__.d(__webpack_exports__, "MaxPool3D", function () {
+        return /* reexport */ kernel_names["R" /* MaxPool3D */];
+      });
+      __webpack_require__.d(__webpack_exports__, "MaxPool3DBackprop", function () {
+        return /* reexport */ kernel_names["S" /* MaxPool3DBackprop */];
+      });
+      __webpack_require__.d(__webpack_exports__, "MaxPoolWithArgmax", function () {
+        return /* reexport */ kernel_names["U" /* MaxPoolWithArgmax */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Minimum", function () {
+        return /* reexport */ kernel_names["W" /* Minimum */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Mod", function () {
+        return /* reexport */ kernel_names["X" /* Mod */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Multiply", function () {
+        return /* reexport */ kernel_names["Y" /* Multiply */];
+      });
+      __webpack_require__.d(__webpack_exports__, "NotEqual", function () {
+        return /* reexport */ kernel_names["bb" /* NotEqual */];
+      });
+      __webpack_require__.d(__webpack_exports__, "NonMaxSuppressionV3", function () {
+        return /* reexport */ kernel_names["Z" /* NonMaxSuppressionV3 */];
+      });
+      __webpack_require__.d(__webpack_exports__, "NonMaxSuppressionV5", function () {
+        return /* reexport */ kernel_names["ab" /* NonMaxSuppressionV5 */];
+      });
+      __webpack_require__.d(__webpack_exports__, "OneHot", function () {
+        return /* reexport */ kernel_names["cb" /* OneHot */];
+      });
+      __webpack_require__.d(__webpack_exports__, "PadV2", function () {
+        return /* reexport */ kernel_names["db" /* PadV2 */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Pool", function () {
+        return /* reexport */ kernel_names["eb" /* Pool */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Pow", function () {
+        return /* reexport */ kernel_names["fb" /* Pow */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Prelu", function () {
+        return /* reexport */ kernel_names["gb" /* Prelu */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Real", function () {
+        return /* reexport */ kernel_names["hb" /* Real */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Relu", function () {
+        return /* reexport */ kernel_names["ib" /* Relu */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Relu6", function () {
+        return /* reexport */ kernel_names["jb" /* Relu6 */];
+      });
+      __webpack_require__.d(__webpack_exports__, "SelectV2", function () {
+        return /* reexport */ kernel_names["kb" /* SelectV2 */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Selu", function () {
+        return /* reexport */ kernel_names["lb" /* Selu */];
+      });
+      __webpack_require__.d(__webpack_exports__, "SpaceToBatchND", function () {
+        return /* reexport */ kernel_names["mb" /* SpaceToBatchND */];
+      });
+      __webpack_require__.d(__webpack_exports__, "SplitV", function () {
+        return /* reexport */ kernel_names["nb" /* SplitV */];
+      });
+      __webpack_require__.d(__webpack_exports__, "SquaredDifference", function () {
+        return /* reexport */ kernel_names["pb" /* SquaredDifference */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Square", function () {
+        return /* reexport */ kernel_names["ob" /* Square */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Sub", function () {
+        return /* reexport */ kernel_names["qb" /* Sub */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Tile", function () {
+        return /* reexport */ kernel_names["rb" /* Tile */];
+      });
+      __webpack_require__.d(__webpack_exports__, "Transpose", function () {
+        return /* reexport */ kernel_names["sb" /* Transpose */];
+      });
+      __webpack_require__.d(__webpack_exports__, "FromPixels", function () {
+        return /* reexport */ kernel_names["E" /* FromPixels */];
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/slice_util.js
+      var slice_util_namespaceObject = {};
+      __webpack_require__.r(slice_util_namespaceObject);
+      __webpack_require__.d(slice_util_namespaceObject, "assertParamsValid", function () {
+        return assertParamsValid;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "maskToAxes", function () {
+        return maskToAxes;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "computeOutShape", function () {
+        return slice_util_computeOutShape;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "stridesWithElidedDims", function () {
+        return stridesWithElidedDims;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "startIndicesWithElidedDims", function () {
+        return startIndicesWithElidedDims;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "stopIndicesWithElidedDims", function () {
+        return stopIndicesWithElidedDims;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "stridesForAxis", function () {
+        return stridesForAxis;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "startForAxis", function () {
+        return startForAxis;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "stopForAxis", function () {
+        return stopForAxis;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "isSliceContinous", function () {
+        return isSliceContinous;
+      });
+      __webpack_require__.d(slice_util_namespaceObject, "computeFlatOffset", function () {
+        return computeFlatOffset;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/io/io.js
+      var io_namespaceObject = {};
+      __webpack_require__.r(io_namespaceObject);
+      __webpack_require__.d(io_namespaceObject, "copyModel", function () {
+        return copyModel;
+      });
+      __webpack_require__.d(io_namespaceObject, "listModels", function () {
+        return listModels;
+      });
+      __webpack_require__.d(io_namespaceObject, "moveModel", function () {
+        return moveModel;
+      });
+      __webpack_require__.d(io_namespaceObject, "removeModel", function () {
+        return removeModel;
+      });
+      __webpack_require__.d(io_namespaceObject, "browserFiles", function () {
+        return browserFiles;
+      });
+      __webpack_require__.d(io_namespaceObject, "browserHTTPRequest", function () {
+        return browserHTTPRequest;
+      });
+      __webpack_require__.d(io_namespaceObject, "concatenateArrayBuffers", function () {
+        return io_utils["d" /* concatenateArrayBuffers */];
+      });
+      __webpack_require__.d(io_namespaceObject, "decodeWeights", function () {
+        return io_utils["e" /* decodeWeights */];
+      });
+      __webpack_require__.d(io_namespaceObject, "encodeWeights", function () {
+        return io_utils["f" /* encodeWeights */];
+      });
+      __webpack_require__.d(io_namespaceObject, "fromMemory", function () {
+        return fromMemory;
+      });
+      __webpack_require__.d(io_namespaceObject, "getLoadHandlers", function () {
+        return getLoadHandlers;
+      });
+      __webpack_require__.d(io_namespaceObject, "getModelArtifactsInfoForJSON", function () {
+        return io_utils["g" /* getModelArtifactsInfoForJSON */];
+      });
+      __webpack_require__.d(io_namespaceObject, "getSaveHandlers", function () {
+        return getSaveHandlers;
+      });
+      __webpack_require__.d(io_namespaceObject, "http", function () {
+        return http;
+      });
+      __webpack_require__.d(io_namespaceObject, "isHTTPScheme", function () {
+        return isHTTPScheme;
+      });
+      __webpack_require__.d(io_namespaceObject, "loadWeights", function () {
+        return loadWeights;
+      });
+      __webpack_require__.d(io_namespaceObject, "registerLoadRouter", function () {
+        return registerLoadRouter;
+      });
+      __webpack_require__.d(io_namespaceObject, "registerSaveRouter", function () {
+        return registerSaveRouter;
+      });
+      __webpack_require__.d(io_namespaceObject, "weightsLoaderFactory", function () {
+        return weightsLoaderFactory;
+      });
+      __webpack_require__.d(io_namespaceObject, "withSaveHandler", function () {
+        return withSaveHandler;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/math.js
+      var math_namespaceObject = {};
+      __webpack_require__.r(math_namespaceObject);
+      __webpack_require__.d(math_namespaceObject, "confusionMatrix", function () {
+        return confusionMatrix;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/browser.js
+      var browser_namespaceObject = {};
+      __webpack_require__.r(browser_namespaceObject);
+      __webpack_require__.d(browser_namespaceObject, "toPixels", function () {
+        return toPixels;
+      });
+      __webpack_require__.d(browser_namespaceObject, "fromPixels", function () {
+        return fromPixels;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd_util.js
+      var gather_nd_util_namespaceObject = {};
+      __webpack_require__.r(gather_nd_util_namespaceObject);
+      __webpack_require__.d(gather_nd_util_namespaceObject, "prepareAndValidate", function () {
+        return prepareAndValidate;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd_util.js
+      var scatter_nd_util_namespaceObject = {};
+      __webpack_require__.r(scatter_nd_util_namespaceObject);
+      __webpack_require__.d(scatter_nd_util_namespaceObject, "validateUpdateShape", function () {
+        return validateUpdateShape;
+      });
+      __webpack_require__.d(scatter_nd_util_namespaceObject, "validateInput", function () {
+        return validateInput;
+      });
+      __webpack_require__.d(scatter_nd_util_namespaceObject, "calculateShapes", function () {
+        return calculateShapes;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/serialization.js
+      var serialization_namespaceObject = {};
+      __webpack_require__.r(serialization_namespaceObject);
+      __webpack_require__.d(serialization_namespaceObject, "Serializable", function () {
+        return Serializable;
+      });
+      __webpack_require__.d(serialization_namespaceObject, "SerializationMap", function () {
+        return SerializationMap;
+      });
+      __webpack_require__.d(serialization_namespaceObject, "registerClass", function () {
+        return registerClass;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/test_util.js
+      var test_util_namespaceObject = {};
+      __webpack_require__.r(test_util_namespaceObject);
+      __webpack_require__.d(test_util_namespaceObject, "TEST_EPSILON_FLOAT16", function () {
+        return TEST_EPSILON_FLOAT16;
+      });
+      __webpack_require__.d(test_util_namespaceObject, "expectArraysClose", function () {
+        return expectArraysClose;
+      });
+      __webpack_require__.d(test_util_namespaceObject, "testEpsilon", function () {
+        return testEpsilon;
+      });
+      __webpack_require__.d(test_util_namespaceObject, "expectPromiseToFail", function () {
+        return expectPromiseToFail;
+      });
+      __webpack_require__.d(test_util_namespaceObject, "expectArraysEqual", function () {
+        return expectArraysEqual;
+      });
+      __webpack_require__.d(test_util_namespaceObject, "expectNumbersClose", function () {
+        return expectNumbersClose;
+      });
+      __webpack_require__.d(test_util_namespaceObject, "expectValuesInRange", function () {
+        return expectValuesInRange;
+      });
+      __webpack_require__.d(test_util_namespaceObject, "expectArrayBuffersEqual", function () {
+        return expectArrayBuffersEqual;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/segment_util.js
+      var segment_util_namespaceObject = {};
+      __webpack_require__.r(segment_util_namespaceObject);
+      __webpack_require__.d(
+        segment_util_namespaceObject,
+        "segOpComputeOptimalWindowSize",
+        function () {
+          return segOpComputeOptimalWindowSize;
+        }
+      );
+      __webpack_require__.d(segment_util_namespaceObject, "computeOutShape", function () {
+        return segment_util_computeOutShape;
+      });
+      __webpack_require__.d(segment_util_namespaceObject, "collectGatherOpShapeInfo", function () {
+        return collectGatherOpShapeInfo;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/spectral_ops.js
+      var spectral_ops_namespaceObject = {};
+      __webpack_require__.r(spectral_ops_namespaceObject);
+      __webpack_require__.d(spectral_ops_namespaceObject, "fft", function () {
+        return fft;
+      });
+      __webpack_require__.d(spectral_ops_namespaceObject, "ifft", function () {
+        return ifft;
+      });
+      __webpack_require__.d(spectral_ops_namespaceObject, "rfft", function () {
+        return rfft;
+      });
+      __webpack_require__.d(spectral_ops_namespaceObject, "irfft", function () {
+        return irfft;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/signal_ops.js
+      var signal_ops_namespaceObject = {};
+      __webpack_require__.r(signal_ops_namespaceObject);
+      __webpack_require__.d(signal_ops_namespaceObject, "hannWindow", function () {
+        return hannWindow;
+      });
+      __webpack_require__.d(signal_ops_namespaceObject, "hammingWindow", function () {
+        return hammingWindow;
+      });
+      __webpack_require__.d(signal_ops_namespaceObject, "frame", function () {
+        return signal_ops_frame;
+      });
+      __webpack_require__.d(signal_ops_namespaceObject, "stft", function () {
+        return stft;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/loss_ops.js
+      var loss_ops_namespaceObject = {};
+      __webpack_require__.r(loss_ops_namespaceObject);
+      __webpack_require__.d(loss_ops_namespaceObject, "Reduction", function () {
+        return Reduction;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "absoluteDifference", function () {
+        return absoluteDifference;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "computeWeightedLoss", function () {
+        return computeWeightedLoss;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "cosineDistance", function () {
+        return cosineDistance;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "hingeLoss", function () {
+        return hingeLoss;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "huberLoss", function () {
+        return huberLoss;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "logLoss", function () {
+        return logLoss;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "meanSquaredError", function () {
+        return meanSquaredError;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "sigmoidCrossEntropy", function () {
+        return sigmoidCrossEntropy;
+      });
+      __webpack_require__.d(loss_ops_namespaceObject, "softmaxCrossEntropy", function () {
+        return softmaxCrossEntropy;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/linalg_ops.js
+      var linalg_ops_namespaceObject = {};
+      __webpack_require__.r(linalg_ops_namespaceObject);
+      __webpack_require__.d(linalg_ops_namespaceObject, "bandPart", function () {
+        return bandPart;
+      });
+      __webpack_require__.d(linalg_ops_namespaceObject, "gramSchmidt", function () {
+        return gramSchmidt;
+      });
+      __webpack_require__.d(linalg_ops_namespaceObject, "qr", function () {
+        return qr;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/image_ops.js
+      var image_ops_namespaceObject = {};
+      __webpack_require__.r(image_ops_namespaceObject);
+      __webpack_require__.d(image_ops_namespaceObject, "nonMaxSuppression", function () {
+        return nonMaxSuppression;
+      });
+      __webpack_require__.d(image_ops_namespaceObject, "resizeBilinear", function () {
+        return resizeBilinear;
+      });
+      __webpack_require__.d(image_ops_namespaceObject, "resizeNearestNeighbor", function () {
+        return resizeNearestNeighbor;
+      });
+      __webpack_require__.d(image_ops_namespaceObject, "nonMaxSuppressionAsync", function () {
+        return nonMaxSuppressionAsync;
+      });
+      __webpack_require__.d(image_ops_namespaceObject, "nonMaxSuppressionWithScore", function () {
+        return nonMaxSuppressionWithScore;
+      });
+      __webpack_require__.d(
+        image_ops_namespaceObject,
+        "nonMaxSuppressionWithScoreAsync",
+        function () {
+          return nonMaxSuppressionWithScoreAsync;
+        }
+      );
+      __webpack_require__.d(image_ops_namespaceObject, "cropAndResize", function () {
+        return cropAndResize;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/fused_ops.js
+      var fused_ops_namespaceObject = {};
+      __webpack_require__.r(fused_ops_namespaceObject);
+      __webpack_require__.d(fused_ops_namespaceObject, "matMul", function () {
+        return fused_ops_matMul;
+      });
+      __webpack_require__.d(fused_ops_namespaceObject, "conv2d", function () {
+        return fused_ops_conv2d;
+      });
+      __webpack_require__.d(fused_ops_namespaceObject, "depthwiseConv2d", function () {
+        return fused_ops_depthwiseConv2d;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/ops/ops.js
+      var ops_namespaceObject = {};
+      __webpack_require__.r(ops_namespaceObject);
+      __webpack_require__.d(ops_namespaceObject, "add", function () {
+        return add;
+      });
+      __webpack_require__.d(ops_namespaceObject, "addN", function () {
+        return addN;
+      });
+      __webpack_require__.d(ops_namespaceObject, "atan2", function () {
+        return atan2;
+      });
+      __webpack_require__.d(ops_namespaceObject, "avgPool", function () {
+        return avgPool;
+      });
+      __webpack_require__.d(ops_namespaceObject, "avgPool3d", function () {
+        return avgPool3d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "batchToSpaceND", function () {
+        return batchToSpaceND;
+      });
+      __webpack_require__.d(ops_namespaceObject, "batchNorm", function () {
+        return batchNorm;
+      });
+      __webpack_require__.d(ops_namespaceObject, "batchNorm2d", function () {
+        return batchNorm2d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "batchNorm3d", function () {
+        return batchNorm3d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "batchNorm4d", function () {
+        return batchNorm4d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "broadcastTo", function () {
+        return broadcastTo;
+      });
+      __webpack_require__.d(ops_namespaceObject, "clone", function () {
+        return clone;
+      });
+      __webpack_require__.d(ops_namespaceObject, "complex", function () {
+        return complex["a" /* complex */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "concat", function () {
+        return concat;
+      });
+      __webpack_require__.d(ops_namespaceObject, "concat1d", function () {
+        return concat1d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "concat2d", function () {
+        return concat2d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "concat3d", function () {
+        return concat3d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "concat4d", function () {
+        return concat4d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "conv1d", function () {
+        return conv1d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "conv2d", function () {
+        return conv2d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "conv2dTranspose", function () {
+        return conv2dTranspose;
+      });
+      __webpack_require__.d(ops_namespaceObject, "conv3d", function () {
+        return conv3d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "conv3dTranspose", function () {
+        return conv3dTranspose;
+      });
+      __webpack_require__.d(ops_namespaceObject, "cumsum", function () {
+        return cumsum;
+      });
+      __webpack_require__.d(ops_namespaceObject, "depthToSpace", function () {
+        return depthToSpace;
+      });
+      __webpack_require__.d(ops_namespaceObject, "depthwiseConv2d", function () {
+        return depthwiseConv2d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "diag", function () {
+        return diag;
+      });
+      __webpack_require__.d(ops_namespaceObject, "div", function () {
+        return div;
+      });
+      __webpack_require__.d(ops_namespaceObject, "divNoNan", function () {
+        return divNoNan;
+      });
+      __webpack_require__.d(ops_namespaceObject, "dot", function () {
+        return dot;
+      });
+      __webpack_require__.d(ops_namespaceObject, "elu", function () {
+        return elu;
+      });
+      __webpack_require__.d(ops_namespaceObject, "equal", function () {
+        return equal;
+      });
+      __webpack_require__.d(ops_namespaceObject, "eye", function () {
+        return eye;
+      });
+      __webpack_require__.d(ops_namespaceObject, "fill", function () {
+        return fill;
+      });
+      __webpack_require__.d(ops_namespaceObject, "floorDiv", function () {
+        return floorDiv;
+      });
+      __webpack_require__.d(ops_namespaceObject, "greater", function () {
+        return greater;
+      });
+      __webpack_require__.d(ops_namespaceObject, "greaterEqual", function () {
+        return greaterEqual;
+      });
+      __webpack_require__.d(ops_namespaceObject, "imag", function () {
+        return imag["a" /* imag */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "leakyRelu", function () {
+        return leakyRelu;
+      });
+      __webpack_require__.d(ops_namespaceObject, "less", function () {
+        return less;
+      });
+      __webpack_require__.d(ops_namespaceObject, "lessEqual", function () {
+        return lessEqual;
+      });
+      __webpack_require__.d(ops_namespaceObject, "localResponseNormalization", function () {
+        return localResponseNormalization;
+      });
+      __webpack_require__.d(ops_namespaceObject, "matMul", function () {
+        return matMul;
+      });
+      __webpack_require__.d(ops_namespaceObject, "max", function () {
+        return max_max;
+      });
+      __webpack_require__.d(ops_namespaceObject, "maxPool", function () {
+        return maxPool;
+      });
+      __webpack_require__.d(ops_namespaceObject, "maxPool3d", function () {
+        return maxPool3d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "maxPoolWithArgmax", function () {
+        return maxPoolWithArgmax;
+      });
+      __webpack_require__.d(ops_namespaceObject, "maximum", function () {
+        return maximum;
+      });
+      __webpack_require__.d(ops_namespaceObject, "minimum", function () {
+        return minimum;
+      });
+      __webpack_require__.d(ops_namespaceObject, "mod", function () {
+        return mod;
+      });
+      __webpack_require__.d(ops_namespaceObject, "mul", function () {
+        return mul;
+      });
+      __webpack_require__.d(ops_namespaceObject, "multinomial", function () {
+        return multinomial;
+      });
+      __webpack_require__.d(ops_namespaceObject, "notEqual", function () {
+        return notEqual;
+      });
+      __webpack_require__.d(ops_namespaceObject, "oneHot", function () {
+        return oneHot;
+      });
+      __webpack_require__.d(ops_namespaceObject, "outerProduct", function () {
+        return outerProduct;
+      });
+      __webpack_require__.d(ops_namespaceObject, "pad", function () {
+        return pad_pad;
+      });
+      __webpack_require__.d(ops_namespaceObject, "pad1d", function () {
+        return pad1d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "pad2d", function () {
+        return pad2d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "pad3d", function () {
+        return pad3d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "pad4d", function () {
+        return pad4d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "pool", function () {
+        return pool;
+      });
+      __webpack_require__.d(ops_namespaceObject, "pow", function () {
+        return pow;
+      });
+      __webpack_require__.d(ops_namespaceObject, "prelu", function () {
+        return prelu;
+      });
+      __webpack_require__.d(ops_namespaceObject, "rand", function () {
+        return rand;
+      });
+      __webpack_require__.d(ops_namespaceObject, "randomGamma", function () {
+        return randomGamma;
+      });
+      __webpack_require__.d(ops_namespaceObject, "randomNormal", function () {
+        return randomNormal;
+      });
+      __webpack_require__.d(ops_namespaceObject, "randomUniform", function () {
+        return randomUniform;
+      });
+      __webpack_require__.d(ops_namespaceObject, "real", function () {
+        return real["a" /* real */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "relu", function () {
+        return relu;
+      });
+      __webpack_require__.d(ops_namespaceObject, "relu6", function () {
+        return relu6;
+      });
+      __webpack_require__.d(ops_namespaceObject, "selu", function () {
+        return selu;
+      });
+      __webpack_require__.d(ops_namespaceObject, "separableConv2d", function () {
+        return separableConv2d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "spaceToBatchND", function () {
+        return spaceToBatchND;
+      });
+      __webpack_require__.d(ops_namespaceObject, "split", function () {
+        return split;
+      });
+      __webpack_require__.d(ops_namespaceObject, "square", function () {
+        return square;
+      });
+      __webpack_require__.d(ops_namespaceObject, "squaredDifference", function () {
+        return squaredDifference;
+      });
+      __webpack_require__.d(ops_namespaceObject, "sub", function () {
+        return sub;
+      });
+      __webpack_require__.d(ops_namespaceObject, "tile", function () {
+        return tile;
+      });
+      __webpack_require__.d(ops_namespaceObject, "truncatedNormal", function () {
+        return truncatedNormal;
+      });
+      __webpack_require__.d(ops_namespaceObject, "booleanMaskAsync", function () {
+        return booleanMaskAsync;
+      });
+      __webpack_require__.d(ops_namespaceObject, "reverse", function () {
+        return reverse_reverse;
+      });
+      __webpack_require__.d(ops_namespaceObject, "reverse1d", function () {
+        return reverse1d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "reverse2d", function () {
+        return reverse2d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "reverse3d", function () {
+        return reverse3d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "reverse4d", function () {
+        return reverse4d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "slice", function () {
+        return slice;
+      });
+      __webpack_require__.d(ops_namespaceObject, "slice1d", function () {
+        return slice1d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "slice2d", function () {
+        return slice2d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "slice3d", function () {
+        return slice3d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "slice4d", function () {
+        return slice4d;
+      });
+      __webpack_require__.d(ops_namespaceObject, "abs", function () {
+        return abs;
+      });
+      __webpack_require__.d(ops_namespaceObject, "acos", function () {
+        return acos;
+      });
+      __webpack_require__.d(ops_namespaceObject, "acosh", function () {
+        return acosh;
+      });
+      __webpack_require__.d(ops_namespaceObject, "asin", function () {
+        return asin;
+      });
+      __webpack_require__.d(ops_namespaceObject, "asinh", function () {
+        return asinh;
+      });
+      __webpack_require__.d(ops_namespaceObject, "atan", function () {
+        return atan;
+      });
+      __webpack_require__.d(ops_namespaceObject, "atanh", function () {
+        return atanh;
+      });
+      __webpack_require__.d(ops_namespaceObject, "ceil", function () {
+        return ceil;
+      });
+      __webpack_require__.d(ops_namespaceObject, "clipByValue", function () {
+        return clipByValue;
+      });
+      __webpack_require__.d(ops_namespaceObject, "cos", function () {
+        return cos;
+      });
+      __webpack_require__.d(ops_namespaceObject, "cosh", function () {
+        return cosh;
+      });
+      __webpack_require__.d(ops_namespaceObject, "erf", function () {
+        return erf;
+      });
+      __webpack_require__.d(ops_namespaceObject, "exp", function () {
+        return unary_ops_exp;
+      });
+      __webpack_require__.d(ops_namespaceObject, "expm1", function () {
+        return expm1;
+      });
+      __webpack_require__.d(ops_namespaceObject, "floor", function () {
+        return floor;
+      });
+      __webpack_require__.d(ops_namespaceObject, "log", function () {
+        return log;
+      });
+      __webpack_require__.d(ops_namespaceObject, "log1p", function () {
+        return log1p;
+      });
+      __webpack_require__.d(ops_namespaceObject, "logSigmoid", function () {
+        return logSigmoid;
+      });
+      __webpack_require__.d(ops_namespaceObject, "neg", function () {
+        return neg;
+      });
+      __webpack_require__.d(ops_namespaceObject, "reciprocal", function () {
+        return reciprocal;
+      });
+      __webpack_require__.d(ops_namespaceObject, "round", function () {
+        return round;
+      });
+      __webpack_require__.d(ops_namespaceObject, "rsqrt", function () {
+        return rsqrt;
+      });
+      __webpack_require__.d(ops_namespaceObject, "sigmoid", function () {
+        return sigmoid;
+      });
+      __webpack_require__.d(ops_namespaceObject, "sign", function () {
+        return sign;
+      });
+      __webpack_require__.d(ops_namespaceObject, "isNaN", function () {
+        return unary_ops_isNaN;
+      });
+      __webpack_require__.d(ops_namespaceObject, "isInf", function () {
+        return isInf;
+      });
+      __webpack_require__.d(ops_namespaceObject, "isFinite", function () {
+        return unary_ops_isFinite;
+      });
+      __webpack_require__.d(ops_namespaceObject, "sin", function () {
+        return sin;
+      });
+      __webpack_require__.d(ops_namespaceObject, "sinh", function () {
+        return sinh;
+      });
+      __webpack_require__.d(ops_namespaceObject, "softplus", function () {
+        return softplus;
+      });
+      __webpack_require__.d(ops_namespaceObject, "sqrt", function () {
+        return sqrt;
+      });
+      __webpack_require__.d(ops_namespaceObject, "step", function () {
+        return unary_ops_step;
+      });
+      __webpack_require__.d(ops_namespaceObject, "tan", function () {
+        return tan;
+      });
+      __webpack_require__.d(ops_namespaceObject, "tanh", function () {
+        return tanh;
+      });
+      __webpack_require__.d(ops_namespaceObject, "all", function () {
+        return reduction_ops_all;
+      });
+      __webpack_require__.d(ops_namespaceObject, "any", function () {
+        return any;
+      });
+      __webpack_require__.d(ops_namespaceObject, "argMax", function () {
+        return argMax;
+      });
+      __webpack_require__.d(ops_namespaceObject, "argMin", function () {
+        return argMin;
+      });
+      __webpack_require__.d(ops_namespaceObject, "logSumExp", function () {
+        return logSumExp;
+      });
+      __webpack_require__.d(ops_namespaceObject, "mean", function () {
+        return reduction_ops_mean;
+      });
+      __webpack_require__.d(ops_namespaceObject, "min", function () {
+        return reduction_ops_min;
+      });
+      __webpack_require__.d(ops_namespaceObject, "moments", function () {
+        return moments;
+      });
+      __webpack_require__.d(ops_namespaceObject, "sum", function () {
+        return sum;
+      });
+      __webpack_require__.d(ops_namespaceObject, "prod", function () {
+        return reduction_ops_prod;
+      });
+      __webpack_require__.d(ops_namespaceObject, "equalStrict", function () {
+        return equalStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "greaterEqualStrict", function () {
+        return greaterEqualStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "greaterStrict", function () {
+        return greaterStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "lessEqualStrict", function () {
+        return lessEqualStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "lessStrict", function () {
+        return lessStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "notEqualStrict", function () {
+        return notEqualStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "addStrict", function () {
+        return addStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "divStrict", function () {
+        return divStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "maximumStrict", function () {
+        return maximumStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "minimumStrict", function () {
+        return minimumStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "modStrict", function () {
+        return modStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "mulStrict", function () {
+        return mulStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "powStrict", function () {
+        return powStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "squaredDifferenceStrict", function () {
+        return squaredDifferenceStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "subStrict", function () {
+        return subStrict;
+      });
+      __webpack_require__.d(ops_namespaceObject, "logicalAnd", function () {
+        return logicalAnd;
+      });
+      __webpack_require__.d(ops_namespaceObject, "logicalNot", function () {
+        return logicalNot;
+      });
+      __webpack_require__.d(ops_namespaceObject, "logicalOr", function () {
+        return logicalOr;
+      });
+      __webpack_require__.d(ops_namespaceObject, "logicalXor", function () {
+        return logicalXor;
+      });
+      __webpack_require__.d(ops_namespaceObject, "where", function () {
+        return where;
+      });
+      __webpack_require__.d(ops_namespaceObject, "whereAsync", function () {
+        return whereAsync;
+      });
+      __webpack_require__.d(ops_namespaceObject, "buffer", function () {
+        return array_ops_buffer;
+      });
+      __webpack_require__.d(ops_namespaceObject, "print", function () {
+        return print;
+      });
+      __webpack_require__.d(ops_namespaceObject, "cast", function () {
+        return cast;
+      });
+      __webpack_require__.d(ops_namespaceObject, "expandDims", function () {
+        return expandDims;
+      });
+      __webpack_require__.d(ops_namespaceObject, "reshape", function () {
+        return reshape;
+      });
+      __webpack_require__.d(ops_namespaceObject, "squeeze", function () {
+        return squeeze;
+      });
+      __webpack_require__.d(ops_namespaceObject, "stack", function () {
+        return stack;
+      });
+      __webpack_require__.d(ops_namespaceObject, "unstack", function () {
+        return unstack;
+      });
+      __webpack_require__.d(ops_namespaceObject, "setdiff1dAsync", function () {
+        return setdiff1dAsync;
+      });
+      __webpack_require__.d(ops_namespaceObject, "linspace", function () {
+        return tensor_ops["a" /* linspace */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "ones", function () {
+        return tensor_ops["b" /* ones */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "range", function () {
+        return tensor_ops["d" /* range */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "scalar", function () {
+        return tensor_ops["e" /* scalar */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "tensor", function () {
+        return tensor_ops["f" /* tensor */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "tensor1d", function () {
+        return tensor_ops["g" /* tensor1d */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "tensor2d", function () {
+        return tensor_ops["h" /* tensor2d */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "tensor3d", function () {
+        return tensor_ops["i" /* tensor3d */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "tensor4d", function () {
+        return tensor_ops["j" /* tensor4d */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "tensor5d", function () {
+        return tensor_ops["k" /* tensor5d */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "tensor6d", function () {
+        return tensor_ops["l" /* tensor6d */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "variable", function () {
+        return tensor_ops["m" /* variable */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "zeros", function () {
+        return tensor_ops["n" /* zeros */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "onesLike", function () {
+        return tensor_ops["c" /* onesLike */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "zerosLike", function () {
+        return tensor_ops["o" /* zerosLike */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "transpose", function () {
+        return transpose;
+      });
+      __webpack_require__.d(ops_namespaceObject, "softmax", function () {
+        return softmax;
+      });
+      __webpack_require__.d(ops_namespaceObject, "logSoftmax", function () {
+        return logSoftmax;
+      });
+      __webpack_require__.d(ops_namespaceObject, "norm", function () {
+        return norm_norm;
+      });
+      __webpack_require__.d(ops_namespaceObject, "gather", function () {
+        return gather;
+      });
+      __webpack_require__.d(ops_namespaceObject, "unsortedSegmentSum", function () {
+        return unsortedSegmentSum;
+      });
+      __webpack_require__.d(ops_namespaceObject, "basicLSTMCell", function () {
+        return basicLSTMCell;
+      });
+      __webpack_require__.d(ops_namespaceObject, "multiRNNCell", function () {
+        return multiRNNCell;
+      });
+      __webpack_require__.d(ops_namespaceObject, "movingAverage", function () {
+        return movingAverage;
+      });
+      __webpack_require__.d(ops_namespaceObject, "stridedSlice", function () {
+        return stridedSlice;
+      });
+      __webpack_require__.d(ops_namespaceObject, "topk", function () {
+        return topk;
+      });
+      __webpack_require__.d(ops_namespaceObject, "scatterND", function () {
+        return scatterND;
+      });
+      __webpack_require__.d(ops_namespaceObject, "fft", function () {
+        return fft;
+      });
+      __webpack_require__.d(ops_namespaceObject, "ifft", function () {
+        return ifft;
+      });
+      __webpack_require__.d(ops_namespaceObject, "rfft", function () {
+        return rfft;
+      });
+      __webpack_require__.d(ops_namespaceObject, "irfft", function () {
+        return irfft;
+      });
+      __webpack_require__.d(ops_namespaceObject, "sparseToDense", function () {
+        return sparseToDense;
+      });
+      __webpack_require__.d(ops_namespaceObject, "gatherND", function () {
+        return gatherND;
+      });
+      __webpack_require__.d(ops_namespaceObject, "dropout", function () {
+        return dropout;
+      });
+      __webpack_require__.d(ops_namespaceObject, "hannWindow", function () {
+        return hannWindow;
+      });
+      __webpack_require__.d(ops_namespaceObject, "hammingWindow", function () {
+        return hammingWindow;
+      });
+      __webpack_require__.d(ops_namespaceObject, "frame", function () {
+        return signal_ops_frame;
+      });
+      __webpack_require__.d(ops_namespaceObject, "stft", function () {
+        return stft;
+      });
+      __webpack_require__.d(ops_namespaceObject, "inTopKAsync", function () {
+        return inTopKAsync;
+      });
+      __webpack_require__.d(ops_namespaceObject, "op", function () {
+        return operation["a" /* op */];
+      });
+      __webpack_require__.d(ops_namespaceObject, "image", function () {
+        return image_ops_namespaceObject;
+      });
+      __webpack_require__.d(ops_namespaceObject, "linalg", function () {
+        return linalg_ops_namespaceObject;
+      });
+      __webpack_require__.d(ops_namespaceObject, "losses", function () {
+        return loss_ops_namespaceObject;
+      });
+      __webpack_require__.d(ops_namespaceObject, "spectral", function () {
+        return spectral_ops_namespaceObject;
+      });
+      __webpack_require__.d(ops_namespaceObject, "fused", function () {
+        return fused_ops_namespaceObject;
+      });
+      __webpack_require__.d(ops_namespaceObject, "signal", function () {
+        return signal_ops_namespaceObject;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/backends/backend_util.js
+      var backend_util_namespaceObject = {};
+      __webpack_require__.r(backend_util_namespaceObject);
+      __webpack_require__.d(backend_util_namespaceObject, "axesAreInnerMostDims", function () {
+        return axesAreInnerMostDims;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "combineLocations", function () {
+        return combineLocations;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "computeOutAndReduceShapes", function () {
+        return computeOutAndReduceShapes;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "expandShapeToKeepDim", function () {
+        return expandShapeToKeepDim;
+      });
+      __webpack_require__.d(
+        backend_util_namespaceObject,
+        "assertAxesAreInnerMostDims",
+        function () {
+          return assertAxesAreInnerMostDims;
+        }
+      );
+      __webpack_require__.d(backend_util_namespaceObject, "getAxesPermutation", function () {
+        return getAxesPermutation;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getUndoAxesPermutation", function () {
+        return getUndoAxesPermutation;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getInnerMostAxes", function () {
+        return getInnerMostAxes;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getBroadcastDims", function () {
+        return getBroadcastDims;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getReductionAxes", function () {
+        return getReductionAxes;
+      });
+      __webpack_require__.d(
+        backend_util_namespaceObject,
+        "assertAndGetBroadcastShape",
+        function () {
+          return assertAndGetBroadcastShape;
+        }
+      );
+      __webpack_require__.d(backend_util_namespaceObject, "assertParamsConsistent", function () {
+        return assertParamsConsistent;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "computeOutShape", function () {
+        return computeOutShape;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "computePool2DInfo", function () {
+        return computePool2DInfo;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "computePool3DInfo", function () {
+        return computePool3DInfo;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "computeConv2DInfo", function () {
+        return computeConv2DInfo;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "computeConv3DInfo", function () {
+        return computeConv3DInfo;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "computeDefaultPad", function () {
+        return computeDefaultPad;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "tupleValuesAreOne", function () {
+        return tupleValuesAreOne;
+      });
+      __webpack_require__.d(
+        backend_util_namespaceObject,
+        "eitherStridesOrDilationsAreOne",
+        function () {
+          return eitherStridesOrDilationsAreOne;
+        }
+      );
+      __webpack_require__.d(backend_util_namespaceObject, "convertConv2DDataFormat", function () {
+        return convertConv2DDataFormat;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "PARALLELIZE_THRESHOLD", function () {
+        return PARALLELIZE_THRESHOLD;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "computeOptimalWindowSize", function () {
+        return computeOptimalWindowSize;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "nonMaxSuppressionV3", function () {
+        return nonMaxSuppressionV3;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "nonMaxSuppressionV5", function () {
+        return nonMaxSuppressionV5;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "upcastType", function () {
+        return dist_types["c" /* upcastType */];
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getReshaped", function () {
+        return getReshaped;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getPermuted", function () {
+        return getPermuted;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getReshapedPermuted", function () {
+        return getReshapedPermuted;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getSliceBeginCoords", function () {
+        return getSliceBeginCoords;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getSliceSize", function () {
+        return getSliceSize;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "prepareAndValidate", function () {
+        return prepareAndValidate;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "validateUpdateShape", function () {
+        return validateUpdateShape;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "validateInput", function () {
+        return validateInput;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "calculateShapes", function () {
+        return calculateShapes;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "SELU_SCALEALPHA", function () {
+        return SELU_SCALEALPHA;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "SELU_SCALE", function () {
+        return SELU_SCALE;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "shouldFuse", function () {
+        return shouldFuse;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "ERF_P", function () {
+        return ERF_P;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "ERF_A1", function () {
+        return ERF_A1;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "ERF_A2", function () {
+        return ERF_A2;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "ERF_A3", function () {
+        return ERF_A3;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "ERF_A4", function () {
+        return ERF_A4;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "ERF_A5", function () {
+        return ERF_A5;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "warn", function () {
+        return warn;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "log", function () {
+        return log_log;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "mergeRealAndImagArrays", function () {
+        return mergeRealAndImagArrays;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "splitRealAndImagArrays", function () {
+        return splitRealAndImagArrays;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "complexWithEvenIndex", function () {
+        return complexWithEvenIndex;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "complexWithOddIndex", function () {
+        return complexWithOddIndex;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "getComplexWithIndex", function () {
+        return getComplexWithIndex;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "assignToTypedArray", function () {
+        return assignToTypedArray;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "exponents", function () {
+        return exponents;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "exponent", function () {
+        return exponent;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "segment_util", function () {
+        return segment_util_namespaceObject;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "castTensor", function () {
+        return castTensor;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "reshapeTensor", function () {
+        return reshapeTensor;
+      });
+      __webpack_require__.d(backend_util_namespaceObject, "linspaceImpl", function () {
+        return linspaceImpl;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-core/dist/backends/kernel_impls.js
+      var kernel_impls_namespaceObject = {};
+      __webpack_require__.r(kernel_impls_namespaceObject);
+      __webpack_require__.d(kernel_impls_namespaceObject, "nonMaxSuppressionV3", function () {
+        return nonMaxSuppressionV3;
+      });
+      __webpack_require__.d(kernel_impls_namespaceObject, "nonMaxSuppressionV5", function () {
+        return nonMaxSuppressionV5;
+      });
+      __webpack_require__.d(kernel_impls_namespaceObject, "split", function () {
+        return split_shared_split;
+      });
+      __webpack_require__.d(kernel_impls_namespaceObject, "tile", function () {
+        return tile_impl_tile;
+      });
+      __webpack_require__.d(kernel_impls_namespaceObject, "topkImpl", function () {
+        return topkImpl;
+      });
+      __webpack_require__.d(kernel_impls_namespaceObject, "whereImpl", function () {
+        return whereImpl;
+      });
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/engine.js + 2 modules
+      var engine = __webpack_require__(5);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/flags.js
+      var flags = __webpack_require__(61);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/kernel_names.js
+      var kernel_names = __webpack_require__(6);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Returns the dimensions in the input shape that are broadcasted to
+       * produce the provided output shape.
+       *
+       * The returned dimensions are 0-indexed and sorted. An example:
+       * inShape = [4, 1, 3]
+       * outShape = [5, 4, 3, 3]
+       * result = [1]. Dimension 1 (2nd dimension of input) gets broadcasted 1 => 3.
+       */
+      function getBroadcastDims(inShape, outShape) {
+        const inRank = inShape.length;
+        const dims = [];
+        for (let i = 0; i < inRank; i++) {
+          const dim = inRank - 1 - i;
+          const a = inShape[dim] || 1;
+          const b = outShape[outShape.length - 1 - i] || 1;
+          if (b > 1 && a === 1) {
+            dims.unshift(dim);
+          }
+        }
+        return dims;
+      }
+      /**
+       * Returns the axes in the output space that should be reduced to produce
+       * the input space.
+       */
+      function getReductionAxes(inShape, outShape) {
+        const result = [];
+        for (let i = 0; i < outShape.length; i++) {
+          const inDim = inShape[inShape.length - i - 1];
+          const outAxis = outShape.length - i - 1;
+          const outDim = outShape[outAxis];
+          if (inDim == null || (inDim === 1 && outDim > 1)) {
+            result.unshift(outAxis);
+          }
+        }
+        return result;
+      }
+      function assertAndGetBroadcastShape(shapeA, shapeB) {
+        const result = [];
+        const l = Math.max(shapeA.length, shapeB.length);
+        for (let i = 0; i < l; i++) {
+          let a = shapeA[shapeA.length - i - 1];
+          if (a == null) {
+            a = 1;
+          }
+          let b = shapeB[shapeB.length - i - 1];
+          if (b == null) {
+            b = 1;
+          }
+          if (a === 1) {
+            result.unshift(b);
+          } else if (b === 1) {
+            result.unshift(a);
+          } else if (a !== b) {
+            const errMsg =
+              `Operands could not be broadcast together with shapes ` + `${shapeA} and ${shapeB}.`;
+            throw Error(errMsg);
+          } else {
+            result.unshift(a);
+          }
+        }
+        return result;
+      }
+      //# sourceMappingURL=broadcast_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Add_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const addGradConfig = {
+        kernelName: kernel_names["a" /* Add */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
+          const derA = () => {
+            let res = dy;
+            const reduceAxes = getReductionAxes(a.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = res.sum(reduceAxes);
+            }
+            return res.reshape(a.shape);
+          };
+          const derB = () => {
+            let res = dy;
+            const reduceAxes = getReductionAxes(b.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = res.sum(reduceAxes);
+            }
+            return res.reshape(b.shape);
+          };
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=Add_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/AddN_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const addNGradConfig = {
+        kernelName: kernel_names["b" /* AddN */],
+        saveAllInputs: true,
+        gradFunc: (dy, saved) => {
+          const ders = {};
+          saved.forEach((_, i) => {
+            ders[i] = () => dy.clone();
+          });
+          return ders;
+        },
+      };
+      //# sourceMappingURL=AddN_grad.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor_util.js
+      var tensor_util = __webpack_require__(11);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor_util_env.js
+      var tensor_util_env = __webpack_require__(3);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/operation.js
+      var operation = __webpack_require__(4);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/add.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Adds two `tf.Tensor`s element-wise, A + B. Supports broadcasting.
+       *
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3, 4]);
+       * const b = tf.tensor1d([10, 20, 30, 40]);
+       *
+       * a.add(b).print();  // or tf.add(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast add a with b.
+       * const a = tf.scalar(5);
+       * const b = tf.tensor1d([10, 20, 30, 40]);
+       *
+       * a.add(b).print();  // or tf.add(a, b)
+       * ```
+       * @param a The first `tf.Tensor` to add.
+       * @param b The second `tf.Tensor` to add. Must have the same type as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function add_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "add");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "add");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        const forward = (backend, save) => {
+          const res = backend.add($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["a" /* Add */]
+        );
+      }
+      const add = Object(operation["a" /* op */])({ add_ });
+      //# sourceMappingURL=add.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor.js + 1 modules
+      var dist_tensor = __webpack_require__(7);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/util.js
+      var util = __webpack_require__(1);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function assertParamsConsistent(shapes, axis) {
+        const rank = shapes[0].length;
+        shapes.forEach((shape, i) => {
+          util["assert"](
+            shape.length === rank,
+            () =>
+              `Error in concat${rank}D: rank of tensors[${i}] must be the same ` +
+              `as the rank of the rest (${rank})`
+          );
+        });
+        util["assert"](
+          axis >= 0 && axis < rank,
+          () => `Error in concat${rank}D: axis must be between 0 and ${rank - 1}.`
+        );
+        const firstShape = shapes[0];
+        shapes.forEach((shape, i) => {
+          for (let r = 0; r < rank; r++) {
+            util["assert"](
+              r === axis || shape[r] === firstShape[r],
+              () =>
+                `Error in concat${rank}D: Shape of tensors[${i}] (${shape}) ` +
+                `does not match the shape of the rest (${firstShape}) ` +
+                `along the non-concatenated axis ${i}.`
+            );
+          }
+        });
+      }
+      function computeOutShape(shapes, axis) {
+        const outputShape = shapes[0].slice();
+        for (let i = 1; i < shapes.length; i++) {
+          outputShape[axis] += shapes[i][axis];
+        }
+        return outputShape;
+      }
+      //# sourceMappingURL=concat_util.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/tensor_ops.js
+      var tensor_ops = __webpack_require__(8);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Concatenates a list of `tf.Tensor`s along a given axis.
+       *
+       * The tensors ranks and types must match, and their sizes must match in all
+       * dimensions except `axis`.
+       *
+       * Also available are stricter rank-specific methods that assert that
+       * `tensors` are of the given rank:
+       *   - `tf.concat1d`
+       *   - `tf.concat2d`
+       *   - `tf.concat3d`
+       *   - `tf.concat4d`
+       *
+       * Except `tf.concat1d` (which does not have axis param), all methods have
+       * same signature as this method.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2]);
+       * const b = tf.tensor1d([3, 4]);
+       * a.concat(b).print();  // or a.concat(b)
+       * ```
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2]);
+       * const b = tf.tensor1d([3, 4]);
+       * const c = tf.tensor1d([5, 6]);
+       * tf.concat([a, b, c]).print();
+       * ```
+       *
+       * ```js
+       * const a = tf.tensor2d([[1, 2], [10, 20]]);
+       * const b = tf.tensor2d([[3, 4], [30, 40]]);
+       * const axis = 1;
+       * tf.concat([a, b], axis).print();
+       * ```
+       * @param tensors A list of tensors to concatenate.
+       * @param axis The axis to concate along. Defaults to 0 (the first dim).
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      function concat_(tensors, axis = 0) {
+        Object(util["assert"])(tensors.length >= 1, () => "Pass at least one tensor to concat");
+        let $tensors = Object(tensor_util_env["b" /* convertToTensorArray */])(
+          tensors,
+          "tensors",
+          "concat"
+        );
+        if ($tensors[0].dtype === "complex64") {
+          $tensors.forEach((tensor) => {
+            if (tensor.dtype !== "complex64") {
+              throw new Error(`Cannot concatenate complex64 tensors with a tensor
+          with dtype ${tensor.dtype}. `);
+            }
+          });
+        }
+        const $axis = Object(util["parseAxisParam"])(axis, $tensors[0].shape)[0];
+        const outShape = computeOutShape(
+          $tensors.map((t) => t.shape),
+          $axis
+        );
+        if (Object(util["sizeFromShape"])(outShape) === 0) {
+          return Object(tensor_ops["f" /* tensor */])([], outShape);
+        }
+        // Keep only non-empty tensors (ignore tensors with 0 in their shape).
+        $tensors = $tensors.filter((t) => t.size > 0);
+        if ($tensors.length === 1) {
+          return $tensors[0];
+        }
+        const shapes = $tensors.map((t) => t.shape);
+        assertParamsConsistent(shapes, $axis);
+        const forward = (backend, save) => {
+          const res = backend.concat($tensors, $axis);
+          save($tensors);
+          return res;
+        };
+        const inputs = $tensors;
+        const attr = { axis };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["l" /* Concat */],
+          attr
+        );
+      }
+      const concat = Object(operation["a" /* op */])({ concat_ });
+      //# sourceMappingURL=concat.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/array_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Reshapes a `tf.Tensor` to a given shape.
+       *
+       * Given an input tensor, returns a new tensor with the same values as the
+       * input tensor with shape `shape`.
+       *
+       * If one component of shape is the special value -1, the size of that
+       * dimension is computed so that the total size remains constant. In
+       * particular, a shape of [-1] flattens into 1-D. At most one component of
+       * shape can be -1.
+       *
+       * If shape is 1-D or higher, then the operation returns a tensor with shape
+       * shape filled with the values of tensor. In this case, the number of
+       * elements implied by shape must be the same as the number of elements in
+       * tensor.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       * x.reshape([2, 2]).print();
+       * ```
+       *
+       * @param x The input tensor to be reshaped.
+       * @param shape An array of integers defining the output tensor shape.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function reshape_(x, shape) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reshape", null);
+        shape = util["inferFromImplicitShape"](shape, $x.size);
+        util["assert"](
+          $x.size === util["sizeFromShape"](shape),
+          () => "new shape and old shape must have the same number of elements."
+        );
+        const grad = (dy) => {
+          return { x: () => dy.reshape($x.shape) };
+        };
+        const attrs = { shape };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.reshape($x, shape),
+          { x: $x },
+          grad,
+          "Reshape",
+          attrs
+        );
+      }
+      /**
+       * Removes dimensions of size 1 from the shape of a `tf.Tensor`.
+       *
+       * ```js
+       * const x = tf.tensor([1, 2, 3, 4], [1, 1, 4]);
+       * x.squeeze().print();
+       * ```
+       *
+       * @param x The input tensor to be squeezed.
+       * @param axis An optional list of numbers. If specified, only
+       *     squeezes the dimensions listed. The dimension index starts at 0. It
+       * is an error to squeeze a dimension that is not 1.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function squeeze_(x, axis) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "squeeze");
+        return reshape($x, util["squeezeShape"]($x.shape, axis).newShape);
+      }
+      /**
+       * Casts a `tf.Tensor` to a new dtype.
+       *
+       * ```js
+       * const x = tf.tensor1d([1.5, 2.5, 3]);
+       * tf.cast(x, 'int32').print();
+       * ```
+       * @param x The input tensor to be casted.
+       * @param dtype The dtype to cast the input tensor to.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function cast_(x, dtype) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "cast");
+        // Sanity checks.
+        if (!util["isValidDtype"](dtype)) {
+          throw new Error(`Failed to cast to unknown dtype ${dtype}`);
+        }
+        if (
+          (dtype === "string" && $x.dtype !== "string") ||
+          (dtype !== "string" && $x.dtype === "string")
+        ) {
+          throw new Error("Only strings can be casted to strings");
+        }
+        const grad = (dy) => {
+          return { x: () => dy.clone() };
+        };
+        const attrs = { dtype };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.cast($x, dtype),
+          { x: $x },
+          grad,
+          "Cast",
+          attrs
+        );
+      }
+      /**
+       * Stacks a list of rank-`R` `tf.Tensor`s into one rank-`(R+1)` `tf.Tensor`.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2]);
+       * const b = tf.tensor1d([3, 4]);
+       * const c = tf.tensor1d([5, 6]);
+       * tf.stack([a, b, c]).print();
+       * ```
+       *
+       * @param tensors A list of tensor objects with the same shape and dtype.
+       * @param axis The axis to stack along. Defaults to 0 (the first dim).
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      function stack_(tensors, axis = 0) {
+        const $tensors = Object(tensor_util_env["b" /* convertToTensorArray */])(
+          tensors,
+          "tensors",
+          "stack"
+        );
+        util["assert"]($tensors.length >= 1, () => "Pass at least one tensor to tf.stack");
+        if ($tensors.length === 1) {
+          return $tensors[0].expandDims(axis);
+        }
+        const rank = $tensors[0].rank;
+        const shape = $tensors[0].shape;
+        const dtype = $tensors[0].dtype;
+        util["assert"](axis <= rank, () => "Axis must be <= rank of the tensor");
+        $tensors.forEach((t) => {
+          util["assertShapesMatch"](
+            shape,
+            t.shape,
+            "All tensors passed to stack must have matching shapes"
+          );
+        });
+        $tensors.forEach((t) => {
+          util["assert"](
+            dtype === t.dtype,
+            () => "All tensors passed to stack must have matching dtypes"
+          );
+        });
+        const expandedTensors = $tensors.map((t) => t.expandDims(axis));
+        return concat(expandedTensors, axis);
+      }
+      /**
+       * Unstacks a `tf.Tensor` of rank-`R` into a list of rank-`(R-1)` `tf.Tensor`s.
+       *
+       * ```js
+       * const a = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * tf.unstack(a).forEach(tensor => tensor.print());
+       * ```
+       *
+       * @param x A tensor object.
+       * @param axis The axis to unstack along. Defaults to 0 (the first dim).
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      function unstack_(x, axis = 0) {
+        axis = axis || 0;
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "unstack");
+        util["assert"](
+          axis >= -$x.shape.length && axis < $x.shape.length,
+          () => `Axis = ${axis} is not in [-${$x.shape.length}, ${$x.shape.length})`
+        );
+        if (axis < 0) {
+          axis += $x.shape.length;
+        }
+        const grad = (dy) => {
+          return { x: () => stack(dy, axis) };
+        };
+        const attrs = { axis };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.unstack($x, axis),
+          { x: $x },
+          grad,
+          "Unpack",
+          attrs
+        );
+      }
+      /**
+       * Returns a `tf.Tensor` that has expanded rank, by inserting a dimension
+       * into the tensor's shape.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       * const axis = 1;
+       * x.expandDims(axis).print();
+       * ```
+       *
+       * @param x The input tensor whose dimensions to be expanded.
+       * @param axis The dimension index at which to insert shape of `1`. Defaults
+       *     to 0 (the first dimension).
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function expandDims_(x, axis = 0) {
+        const parseAs = null;
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(
+          x,
+          "x",
+          "expandDims",
+          parseAs
+        );
+        util["assert"](axis <= $x.rank, () => "Axis must be <= rank of the tensor");
+        const newShape = $x.shape.slice();
+        if (axis < 0) {
+          // Negative value is counted from the tail of rank.
+          util["assert"](
+            -($x.rank + 1) <= axis,
+            () => `Axis must be in the interval [${-($x.rank + 1)}, ${$x.rank}]`
+          );
+          axis = $x.rank + axis + 1;
+        }
+        newShape.splice(axis, 0, 1);
+        return reshape($x, newShape);
+      }
+      /**
+       * Computes the difference between two lists of numbers.
+       *
+       * Given a Tensor `x` and a Tensor `y`, this operation returns a Tensor `out`
+       * that represents all values that are in `x` but not in `y`. The returned
+       * Tensor `out` is sorted in the same order that the numbers appear in `x`
+       * (duplicates are preserved). This operation also returns a Tensor indices that
+       * represents the position of each out element in `x`. In other words:
+       *
+       * `out[i] = x[idx[i]] for i in [0, 1, ..., out.length - 1]`
+       *
+       * ```js
+       * const x = [1, 2, 3, 4, 5, 6];
+       * const y = [1, 3, 5];
+       *
+       * const [out, indices] = await tf.setdiff1dAsync(x, y);
+       * out.print(); // [2, 4, 6]
+       * indices.print(); // [1, 3, 5]
+       * ```
+       *
+       * @param x 1-D Tensor. Values to keep.
+       * @param y 1-D Tensor. Must have the same type as x. Values to exclude in the
+       *     output.
+       * @returns Promise of Tensor tuple [out, indices].
+       *  out: Tensor with the same type as x.
+       *  indices: A Tensor of type int32.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      async function setdiff1dAsync_(x, y) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "setdiff1d");
+        const $y = Object(tensor_util_env["a" /* convertToTensor */])(y, "y", "setdiff1d");
+        util["assert"](
+          $x.dtype === $y.dtype,
+          () => `x and y should have the same dtype, but got x (${$x.dtype}) and y (${$y.dtype}).`
+        );
+        util["assert"]($x.rank === 1, () => `x should be 1D tensor, but got x (${$x.shape}).`);
+        util["assert"]($y.rank === 1, () => `y should be 1D tensor, but got y (${$y.shape}).`);
+        const xVals = await $x.data();
+        const yVals = await $y.data();
+        const ySet = new Set(yVals);
+        let outputSize = 0;
+        for (let i = 0; i < xVals.length; i++) {
+          if (!ySet.has(xVals[i])) {
+            outputSize++;
+          }
+        }
+        const buffer = new dist_tensor["b" /* TensorBuffer */]([outputSize], $x.dtype);
+        const indices = new dist_tensor["b" /* TensorBuffer */]([outputSize], "int32");
+        for (let i = 0, p = 0; i < xVals.length; i++) {
+          if (!ySet.has(xVals[i])) {
+            buffer.values[p] = xVals[i];
+            indices.values[p] = i;
+            p++;
+          }
+        }
+        return [buffer.toTensor(), indices.toTensor()];
+      }
+      /**
+       * Creates an empty `tf.TensorBuffer` with the specified `shape` and `dtype`.
+       *
+       * The values are stored in CPU as `TypedArray`. Fill the buffer using
+       * `buffer.set()`, or by modifying directly `buffer.values`.
+       *
+       * When done, call `buffer.toTensor()` to get an immutable `tf.Tensor` with
+       * those values.
+       *
+       * ```js
+       * // Create a buffer and set values at particular indices.
+       * const buffer = tf.buffer([2, 2]);
+       * buffer.set(3, 0, 0);
+       * buffer.set(5, 1, 0);
+       *
+       * // Convert the buffer back to a tensor.
+       * buffer.toTensor().print();
+       * ```
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param dtype The dtype of the buffer. Defaults to 'float32'.
+       * @param values The values of the buffer as `TypedArray`. Defaults to
+       * zeros.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function array_ops_buffer(shape, dtype = "float32", values) {
+        dtype = dtype || "float32";
+        util["assertNonNegativeIntegerDimensions"](shape);
+        return new dist_tensor["b" /* TensorBuffer */](shape, dtype, values);
+      }
+      /**
+       * Prints information about the `tf.Tensor` including its data.
+       *
+       * ```js
+       * const verbose = true;
+       * tf.tensor2d([1, 2, 3, 4], [2, 2]).print(verbose);
+       * ```
+       * @param x The tensor to be printed.
+       * @param verbose Whether to print verbose information about the ` Tensor`,
+       * including dtype and size.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function print(x, verbose = false) {
+        console.log(x.toString(verbose));
+      }
+
+      const cast = Object(operation["a" /* op */])({ cast_ });
+      const expandDims = Object(operation["a" /* op */])({ expandDims_ });
+      const reshape = Object(operation["a" /* op */])({ reshape_ });
+      const squeeze = Object(operation["a" /* op */])({ squeeze_ });
+      const stack = Object(operation["a" /* op */])({ stack_ });
+      const unstack = Object(operation["a" /* op */])({ unstack_ });
+      const setdiff1dAsync = setdiff1dAsync_;
+      //# sourceMappingURL=array_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/floorDiv.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Divides two `tf.Tensor`s element-wise, A / B. Supports broadcasting.
+       * The result is rounded with floor function.
+       *
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 4, 9, 16]);
+       * const b = tf.tensor1d([1, 2, 3, 4]);
+       *
+       * a.floorDiv(b).print();  // or tf.div(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast div a with b.
+       * const a = tf.tensor1d([2, 4, 6, 8]);
+       * const b = tf.scalar(2);
+       *
+       * a.floorDiv(b).print();  // or tf.floorDiv(a, b)
+       * ```
+       *
+       * @param a The first tensor as the numerator.
+       * @param b The second tensor as the denominator. Must have the same dtype as
+       * `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function floorDiv_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "floorDiv");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "floorDiv");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        const forward = (backend, save) => {
+          const res = backend.floorDiv($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["D" /* FloorDiv */]
+        );
+      }
+      const floorDiv = Object(operation["a" /* op */])({ floorDiv_ });
+      //# sourceMappingURL=floorDiv.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/div.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Divides two `tf.Tensor`s element-wise, A / B. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 4, 9, 16]);
+       * const b = tf.tensor1d([1, 2, 3, 4]);
+       *
+       * a.div(b).print();  // or tf.div(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast div a with b.
+       * const a = tf.tensor1d([2, 4, 6, 8]);
+       * const b = tf.scalar(2);
+       *
+       * a.div(b).print();  // or tf.div(a, b)
+       * ```
+       *
+       * @param a The first tensor as the numerator.
+       * @param b The second tensor as the denominator. Must have the same dtype as
+       * `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function div_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "div");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "div");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        if ($a.dtype === "int32" && $b.dtype === "int32") {
+          return floorDiv($a, $b);
+        }
+        const forward = (backend, save) => {
+          const res = backend.realDivide($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        const attrs = {};
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["y" /* Div */],
+          attrs
+        );
+      }
+      const div = Object(operation["a" /* op */])({ div_ });
+      //# sourceMappingURL=div.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/mul.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Multiplies two `tf.Tensor`s element-wise, A * B. Supports broadcasting.
+       *
+       * We also expose `tf.mulStrict` which has the same signature as this op and
+       * asserts that `a` and `b` are the same shape (does not broadcast).
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3, 4]);
+       * const b = tf.tensor1d([2, 3, 4, 5]);
+       *
+       * a.mul(b).print();  // or tf.mul(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast mul a with b.
+       * const a = tf.tensor1d([1, 2, 3, 4]);
+       * const b = tf.scalar(5);
+       *
+       * a.mul(b).print();  // or tf.mul(a, b)
+       * ```
+       * @param a The first tensor to multiply.
+       * @param b The second tensor to multiply. Must have the same dtype as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function mul_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "mul");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "mul");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        const forward = (backend, save) => {
+          const res = backend.multiply($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["Y" /* Multiply */]
+        );
+      }
+      const mul = Object(operation["a" /* op */])({ mul_ });
+      //# sourceMappingURL=mul.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Provided `f(x)`, returns another function `g(x, dy?)`, which gives the
+       * gradient of `f(x)` with respect to `x`.
+       *
+       * If `dy` is provided, the gradient of `f(x).mul(dy).sum()` with respect to
+       * `x` is computed instead. `f(x)` must take a single tensor `x` and return a
+       * single tensor `y`. If `f()` takes multiple inputs, use `tf.grads` instead.
+       *
+       * ```js
+       * // f(x) = x ^ 2
+       * const f = x => x.square();
+       * // f'(x) = 2x
+       * const g = tf.grad(f);
+       *
+       * const x = tf.tensor1d([2, 3]);
+       * g(x).print();
+       * ```
+       *
+       * ```js
+       * // f(x) = x ^ 3
+       * const f = x => x.pow(tf.scalar(3, 'int32'));
+       * // f'(x) = 3x ^ 2
+       * const g = tf.grad(f);
+       * // f''(x) = 6x
+       * const gg = tf.grad(g);
+       *
+       * const x = tf.tensor1d([2, 3]);
+       * gg(x).print();
+       * ```
+       *
+       * @param f The function f(x), to compute gradient for.
+       */
+      /** @doc {heading: 'Training', subheading: 'Gradients'} */
+      function gradients_grad(f) {
+        util["assert"](util["isFunction"](f), () => "The f passed in grad(f) must be a function");
+        return (x, dy) => {
+          // x can be of any dtype, thus null as the last argument.
+          const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "tf.grad", null);
+          const $dy =
+            dy != null
+              ? Object(tensor_util_env["a" /* convertToTensor */])(dy, "dy", "tf.grad")
+              : null;
+          return engine["a" /* ENGINE */].tidy(() => {
+            const { value, grads } = engine["a" /* ENGINE */].gradients(() => f($x), [$x], $dy);
+            if ($dy != null) {
+              util["assertShapesMatch"](
+                value.shape,
+                $dy.shape,
+                "The shape of dy passed in grad(f)(x, dy) must match the shape " +
+                  "returned by f(x)"
+              );
+            }
+            checkGrads(grads);
+            return grads[0];
+          });
+        };
+      }
+      /**
+       * Provided `f(x1, x2,...)`, returns another function `g([x1, x2,...], dy?)`,
+       * which gives an array of gradients of `f()` with respect to each input
+       * [`x1`,`x2`,...].
+       *
+       * If `dy` is passed when calling `g()`, the gradient of
+       * `f(x1,...).mul(dy).sum()` with respect to each input is computed instead.
+       * The provided `f` must take one or more tensors and return a single tensor
+       * `y`. If `f()` takes a single input, we recommend using `tf.grad` instead.
+       *
+       * ```js
+       * // f(a, b) = a * b
+       * const f = (a, b) => a.mul(b);
+       * // df / da = b, df / db = a
+       * const g = tf.grads(f);
+       *
+       * const a = tf.tensor1d([2, 3]);
+       * const b = tf.tensor1d([-2, -3]);
+       * const [da, db] = g([a, b]);
+       * console.log('da');
+       * da.print();
+       * console.log('db');
+       * db.print();
+       * ```
+       *
+       * @param f The function `f(x1, x2,...)` to compute gradients for.
+       */
+      /** @doc {heading: 'Training', subheading: 'Gradients'} */
+      function gradients_grads(f) {
+        util["assert"](util["isFunction"](f), () => "The f passed in grads(f) must be a function");
+        return (args, dy) => {
+          util["assert"](
+            Array.isArray(args),
+            () =>
+              "The args passed in grads(f)(args) must be an array " +
+              "of `Tensor`s or `TensorLike`s"
+          );
+          // args can be of any dtype, thus null as the last argument.
+          const $args = Object(tensor_util_env["b" /* convertToTensorArray */])(
+            args,
+            "args",
+            "tf.grads",
+            null
+          );
+          const $dy =
+            dy != null
+              ? Object(tensor_util_env["a" /* convertToTensor */])(dy, "dy", "tf.grads")
+              : null;
+          return engine["a" /* ENGINE */].tidy(() => {
+            const { value, grads } = engine["a" /* ENGINE */].gradients(
+              () => f(...$args),
+              $args,
+              $dy
+            );
+            if ($dy != null) {
+              util["assertShapesMatch"](
+                value.shape,
+                $dy.shape,
+                "The shape of dy passed in grads(f)([x1,...], dy) must " +
+                  "match the shape returned by f([x1,...])"
+              );
+            }
+            checkGrads(grads);
+            return grads;
+          });
+        };
+      }
+      /**
+       * Like `tf.grad`, but also returns the value of `f()`. Useful when `f()`
+       * returns a metric you want to show.
+       *
+       * The result is a rich object with the following properties:
+       * - grad: The gradient of `f(x)` w.r.t `x` (result of `tf.grad`).
+       * - value: The value returned by `f(x)`.
+       *
+       * ```js
+       * // f(x) = x ^ 2
+       * const f = x => x.square();
+       * // f'(x) = 2x
+       * const g = tf.valueAndGrad(f);
+       *
+       * const x = tf.tensor1d([2, 3]);
+       * const {value, grad} = g(x);
+       *
+       * console.log('value');
+       * value.print();
+       * console.log('grad');
+       * grad.print();
+       * ```
+       */
+      /** @doc {heading: 'Training', subheading: 'Gradients'} */
+      function valueAndGrad(f) {
+        util["assert"](
+          util["isFunction"](f),
+          () => "The f passed in valueAndGrad(f) must be a function"
+        );
+        return (x, dy) => {
+          util["assert"](
+            x instanceof dist_tensor["a" /* Tensor */],
+            () => "The x passed in valueAndGrad(f)(x) must be a tensor"
+          );
+          util["assert"](
+            dy == null || dy instanceof dist_tensor["a" /* Tensor */],
+            () => "The dy passed in valueAndGrad(f)(x, dy) must be a tensor"
+          );
+          const { grads, value } = engine["a" /* ENGINE */].gradients(() => f(x), [x], dy);
+          checkGrads(grads);
+          return { grad: grads[0], value };
+        };
+      }
+      /**
+       * Like `tf.grads`, but returns also the value of `f()`. Useful when `f()`
+       * returns a metric you want to show.
+       *
+       * The result is a rich object with the following properties:
+       * - grads: The gradients of `f()` w.r.t each input (result of `tf.grads`).
+       * - value: The value returned by `f(x)`.
+       *
+       * ```js
+       * // f(a, b) = a * b
+       * const f = (a, b) => a.mul(b);
+       * // df/da = b, df/db = a
+       * const g = tf.valueAndGrads(f);
+       *
+       * const a = tf.tensor1d([2, 3]);
+       * const b = tf.tensor1d([-2, -3]);
+       * const {value, grads} = g([a, b]);
+       *
+       * const [da, db] = grads;
+       *
+       * console.log('value');
+       * value.print();
+       *
+       * console.log('da');
+       * da.print();
+       * console.log('db');
+       * db.print();
+       * ```
+       */
+      /** @doc {heading: 'Training', subheading: 'Gradients'} */
+      function valueAndGrads(f) {
+        util["assert"](
+          util["isFunction"](f),
+          () => "The f passed in valueAndGrads(f) must be a function"
+        );
+        return (args, dy) => {
+          util["assert"](
+            Array.isArray(args) &&
+              args.every((arg) => arg instanceof dist_tensor["a" /* Tensor */]),
+            () => "The args passed in valueAndGrads(f)(args) must be array of " + "tensors"
+          );
+          util["assert"](
+            dy == null || dy instanceof dist_tensor["a" /* Tensor */],
+            () => "The dy passed in valueAndGrads(f)(args, dy) must be a tensor"
+          );
+          const res = engine["a" /* ENGINE */].gradients(() => f(...args), args, dy);
+          if (dy != null) {
+            util["assertShapesMatch"](
+              res.value.shape,
+              dy.shape,
+              "The shape of dy passed in valueAndGrads(f)([x1,...], dy) must " +
+                "match the shape returned by f([x1,...])"
+            );
+          }
+          checkGrads(res.grads);
+          return res;
+        };
+      }
+      /**
+       * Computes and returns the gradient of f(x) with respect to the list of
+       * trainable variables provided by `varList`. If no list is provided, it
+       * defaults to all trainable variables.
+       *
+       * ```js
+       * const a = tf.variable(tf.tensor1d([3, 4]));
+       * const b = tf.variable(tf.tensor1d([5, 6]));
+       * const x = tf.tensor1d([1, 2]);
+       *
+       * // f(a, b) = a * x ^ 2 + b * x
+       * const f = () => a.mul(x.square()).add(b.mul(x)).sum();
+       * // df/da = x ^ 2, df/db = x
+       * const {value, grads} = tf.variableGrads(f);
+       *
+       * Object.keys(grads).forEach(varName => grads[varName].print());
+       * ```
+       *
+       * @param f The function to execute. f() should return a scalar.
+       * @param varList The list of variables to compute the gradients with respect
+       *     to. Defaults to all trainable variables.
+       * @returns An object with the following keys and values:
+       *   - `value`: The value of the function `f`.
+       *   - `grads`: A map from the names of the variables to the gradients.
+       *     If the `varList` argument is provided explicitly and contains a subset of
+       *     non-trainable variables, this map in the return value will contain keys
+       *     that map the names of the non-trainable variables to `null`.
+       */
+      /** @doc {heading: 'Training', subheading: 'Gradients'} */
+      function variableGrads(f, varList) {
+        util["assert"](
+          util["isFunction"](f),
+          () => "The f passed in variableGrads(f) must be a function"
+        );
+        util["assert"](
+          varList == null ||
+            (Array.isArray(varList) &&
+              varList.every((v) => v instanceof dist_tensor["c" /* Variable */])),
+          () => "The varList passed in variableGrads(f, varList) must be an array " + "of variables"
+        );
+        const specifiedVarList = varList != null;
+        if (!specifiedVarList) {
+          // Get all of the trainable variables.
+          varList = [];
+          for (const varName in engine["a" /* ENGINE */].registeredVariables) {
+            varList.push(engine["a" /* ENGINE */].registeredVariables[varName]);
+          }
+        }
+        const specifiedNonTrainable = specifiedVarList
+          ? varList.filter((variable) => !variable.trainable)
+          : null;
+        // Prune non-trainable variables.
+        const originalVarCount = varList.length;
+        varList = varList.filter((variable) => variable.trainable);
+        util["assert"](
+          varList.length > 0,
+          () =>
+            `variableGrads() expects at least one of the input variables to ` +
+            `be trainable, but none of the ${originalVarCount} variables is ` +
+            `trainable.`
+        );
+        const allowNoGradients = true;
+        const { value, grads } = engine["a" /* ENGINE */].gradients(
+          f,
+          varList,
+          null,
+          allowNoGradients
+        );
+        util["assert"](
+          grads.some((g) => g != null),
+          () =>
+            "Cannot find a connection between any variable and the result of " +
+            "the loss function y=f(x). Please make sure the operations that " +
+            "use variables are inside the function f passed to minimize()."
+        );
+        util["assert"](
+          value.rank === 0,
+          () =>
+            `The f passed in variableGrads(f) must return a scalar, but it ` +
+            `returned a rank-${value.rank} tensor`
+        );
+        const namedGrads = {};
+        varList.forEach((v, i) => {
+          if (grads[i] != null) {
+            namedGrads[v.name] = grads[i];
+          }
+        });
+        if (specifiedNonTrainable != null) {
+          // If varList is explicitly provided and contains non-trainable values,
+          // add them to the returned gradients with `null` values.
+          specifiedNonTrainable.forEach((v) => (namedGrads[v.name] = null));
+        }
+        return { value, grads: namedGrads };
+      }
+      /**
+       * Overrides the gradient computation of a function `f`.
+       *
+       * Takes a function
+       * `f(...inputs, save) => {value: Tensor, gradFunc: (dy, saved) => Tensor[]}`
+       * and returns another function `g(...inputs)` which takes the same inputs as
+       * `f`. When called, `g` returns `f().value`. In backward mode, custom gradients
+       * with respect to each input of `f` are computed using `f().gradFunc`.
+       *
+       * The `save` function passsed to `f` should be used for saving tensors needed
+       * in the gradient. And the `saved` passed to the `gradFunc` is a
+       * `NamedTensorMap`, which contains those saved tensor.
+       *
+       * ```js
+       * const customOp = tf.customGrad((x, save) => {
+       *   // Save x to make sure it's available later for the gradient.
+       *   save([x]);
+       *   // Override gradient of our custom x ^ 2 op to be dy * abs(x);
+       *   return {
+       *     value: x.square(),
+       *     // Note `saved.x` which points to the `x` we saved earlier.
+       *     gradFunc: (dy, saved) => [dy.mul(saved[0].abs())]
+       *   };
+       * });
+       *
+       * const x = tf.tensor1d([-1, -2, 3]);
+       * const dx = tf.grad(x => customOp(x));
+       *
+       * console.log(`f(x):`);
+       * customOp(x).print();
+       * console.log(`f'(x):`);
+       * dx(x).print();
+       * ```
+       *
+       * @param f The function to evaluate in forward mode, which should return
+       *     `{value: Tensor, gradFunc: (dy, saved) => Tensor[]}`, where `gradFunc`
+       *     returns the custom gradients of `f` with respect to its inputs.
+       */
+      /** @doc {heading: 'Training', subheading: 'Gradients'} */
+      function customGrad(f) {
+        return engine["a" /* ENGINE */].customGrad(f);
+      }
+      function checkGrads(grads) {
+        const numNullGradients = grads.filter((g) => g == null).length;
+        if (numNullGradients > 0) {
+          throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that
+    the f you passed encloses all operations that lead from x to y.`);
+        }
+      }
+
+      //# sourceMappingURL=gradients.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/axis_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns true if the axis specifies the inner most dimensions of the
+       * array.
+       */
+      function axesAreInnerMostDims(axes, rank) {
+        for (let i = 0; i < axes.length; ++i) {
+          if (axes[axes.length - i - 1] !== rank - 1 - i) {
+            return false;
+          }
+        }
+        return true;
+      }
+      function combineLocations(outputLoc, reduceLoc, axes) {
+        const rank = outputLoc.length + reduceLoc.length;
+        const loc = [];
+        let outIdx = 0;
+        let reduceIdx = 0;
+        for (let dim = 0; dim < rank; dim++) {
+          if (axes.indexOf(dim) === -1) {
+            loc.push(outputLoc[outIdx++]);
+          } else {
+            loc.push(reduceLoc[reduceIdx++]);
+          }
+        }
+        return loc;
+      }
+      function computeOutAndReduceShapes(aShape, axes) {
+        const outShape = [];
+        const rank = aShape.length;
+        for (let dim = 0; dim < rank; dim++) {
+          if (axes.indexOf(dim) === -1) {
+            outShape.push(aShape[dim]);
+          }
+        }
+        const reduceShape = axes.map((dim) => aShape[dim]);
+        return [outShape, reduceShape];
+      }
+      function expandShapeToKeepDim(shape, axes) {
+        const reduceSubShape = axes.map((x) => 1);
+        return combineLocations(shape, reduceSubShape, axes);
+      }
+      function assertAxesAreInnerMostDims(msg, axes, rank) {
+        util["assert"](
+          axesAreInnerMostDims(axes, rank),
+          () =>
+            `${msg} supports only inner-most axes for now. ` +
+            `Got axes ${axes} and rank-${rank} input.`
+        );
+      }
+      /**
+       * Returns the axes permutation to be used with `tf.transpose`, if such
+       * permutation is necessary. Otherwise it returns null. This method is used by
+       * operations that operate only on inner-most axes.
+       */
+      function getAxesPermutation(axes, rank) {
+        if (axesAreInnerMostDims(axes, rank)) {
+          return null;
+        }
+        const result = [];
+        for (let i = 0; i < rank; ++i) {
+          if (axes.indexOf(i) === -1) {
+            result.push(i);
+          }
+        }
+        axes.forEach((axis) => result.push(axis));
+        return result;
+      }
+      /** Returns the axes permutation that undoes the original permutation. */
+      function getUndoAxesPermutation(axes) {
+        return axes
+          .map((axis, i) => [i, axis])
+          .sort((a, b) => a[1] - b[1])
+          .map((x) => x[0]);
+      }
+      function getInnerMostAxes(numAxes, rank) {
+        const res = [];
+        for (let i = rank - numAxes; i < rank; ++i) {
+          res.push(i);
+        }
+        return res;
+      }
+      //# sourceMappingURL=axis_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/reduction_ops_util.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Gradient helper function for the min and max operations.
+       */
+      function gradForMinAndMax(dy, y, xOrig, origAxes, permutedAxes) {
+        if (y.rank < xOrig.rank) {
+          y = y.reshape(expandShapeToKeepDim(y.shape, origAxes));
+        }
+        if (dy.rank < xOrig.rank) {
+          dy = dy.reshape(expandShapeToKeepDim(dy.shape, origAxes));
+        }
+        return {
+          x: () => {
+            const dx = dy.mul(xOrig.equal(y).cast(dy.dtype));
+            return permutedAxes == null ? dx : dx.transpose(permutedAxes);
+          },
+        };
+      }
+      //# sourceMappingURL=reduction_ops_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/reduction_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the log(sum(exp(elements across the reduction dimensions)).
+       *
+       * Reduces the input along the dimensions given in `axis`. Unless `keepDims`
+       * is true, the rank of the array is reduced by 1 for each entry in `axis`.
+       * If `keepDims` is true, the reduced dimensions are retained with length 1.
+       * If `axis` has no entries, all dimensions are reduced, and an array with a
+       * single element is returned.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3]);
+       *
+       * x.logSumExp().print();  // or tf.logSumExp(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * const axis = 1;
+       * x.logSumExp(axis).print();  // or tf.logSumExp(a, axis)
+       * ```
+       * @param x The input tensor.
+       * @param axis The dimension(s) to reduce. If null (the default),
+       *     reduces all dimensions.
+       * @param keepDims If true, retains reduced dimensions with length
+       *     of 1. Defaults to false.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function logSumExp_(x, axis = null, keepDims = false) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "logSumExp");
+        const axes = util["parseAxisParam"](axis, $x.shape);
+        const xMax = $x.max(axes, true /* keepDims */);
+        const a = $x.sub(xMax);
+        const b = a.exp();
+        const c = b.sum(axes);
+        const d = c.log();
+        const res = xMax.reshape(d.shape).add(d);
+        if (keepDims) {
+          const newShape = expandShapeToKeepDim(res.shape, axes);
+          return res.reshape(newShape);
+        }
+        return res;
+      }
+      /**
+       * Computes the sum of elements across dimensions of a `tf.Tensor`.
+       *
+       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
+       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
+       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
+       * length 1. If axes has no entries, all dimensions are reduced, and a
+       * `tf.Tensor` with a single element is returned.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3]);
+       *
+       * x.sum().print();  // or tf.sum(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * const axis = 1;
+       * x.sum(axis).print();  // or tf.sum(x, axis)
+       * ```
+       *
+       * @param x The input tensor to compute the sum over. If the dtype is `bool`
+       *   it will be converted to `int32` and the output dtype will be `int32`.
+       * @param axis The dimension(s) to reduce. By default it reduces
+       *     all dimensions.
+       * @param keepDims If true, retains reduced dimensions with size 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function sum_(x, axis = null, keepDims = false) {
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sum");
+        if ($x.dtype === "bool") {
+          $x = $x.toInt();
+        }
+        const axes = util["parseAxisParam"](axis, $x.shape);
+        // Use a custom gradient to bypass 2 gradient backprops since sum is used
+        // extremely often.
+        const customOp = customGrad((x) => {
+          const permutation = getAxesPermutation(axes, x.rank);
+          let reductionAxes = axes;
+          let permutedX = x;
+          if (permutation != null) {
+            permutedX = x.transpose(permutation);
+            reductionAxes = getInnerMostAxes(reductionAxes.length, x.rank);
+          }
+          const gradFunc = (dy) => {
+            const expandedDyShape = x.shape.slice();
+            axes.forEach((axis) => {
+              expandedDyShape[axis] = 1;
+            });
+            const expandedDy = dy.reshape(expandedDyShape);
+            const derX = expandedDy.mul(Object(tensor_ops["b" /* ones */])(x.shape, "float32"));
+            return derX;
+          };
+          const gradInputs = (dy) => {
+            return { x: () => gradFunc(dy) };
+          };
+          const attrs = { axes: reductionAxes };
+          let value = engine["a" /* ENGINE */].runKernelFunc(
+            (backend) => backend.sum(permutedX, reductionAxes),
+            { x: permutedX },
+            gradInputs,
+            "Sum",
+            attrs
+          );
+          if (keepDims) {
+            const newShape = expandShapeToKeepDim(value.shape, axes);
+            value = value.reshape(newShape);
+          }
+          return { value, gradFunc };
+        });
+        return customOp($x);
+      }
+      /**
+       * Computes the product of elements across dimensions of a `tf.Tensor`.
+       *
+       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
+       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
+       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
+       * length 1. If `axes` has no entries, all dimensions are reduced, and a
+       * `tf.Tensor` with a single element is returned.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3]);
+       *
+       * x.prod().print();  // or tf.prod(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * const axis = 1;
+       * x.prod(axis).print();  // or tf.prod(x, axis)
+       * ```
+       *
+       * @param x The input tensor to compute the product over. If the dtype is `bool`
+       *   it will be converted to `int32` and the output dtype will be `int32`.
+       * @param axis The dimension(s) to reduce. By default it reduces
+       *     all dimensions.
+       * @param keepDims If true, retains reduced dimensions with size 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function prod_(x, axis = null, keepDims = false) {
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "prod");
+        if ($x.dtype === "bool") {
+          $x = $x.toInt();
+        }
+        const axes = util["parseAxisParam"](axis, $x.shape);
+        const permutation = getAxesPermutation(axes, $x.rank);
+        let reductionAxes = axes;
+        let permutedX = $x;
+        if (permutation != null) {
+          permutedX = $x.transpose(permutation);
+          reductionAxes = getInnerMostAxes(reductionAxes.length, $x.rank);
+        }
+        let value = engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.prod(permutedX, reductionAxes),
+          { permutedX }
+        );
+        if (keepDims) {
+          const newShape = expandShapeToKeepDim(value.shape, axes);
+          value = value.reshape(newShape);
+        }
+        return value;
+      }
+      /**
+       * Computes the mean of elements across dimensions of a `tf.Tensor`.
+       *
+       * Reduces `x` along the dimensions given in `axis`. Unless `keepDims` is
+       * true, the rank of the `tf.Tensor` is reduced by 1 for each entry in `axis`.
+       * If `keepDims` is true, the reduced dimensions are retained with length 1.
+       * If `axis` has no entries, all dimensions are reduced, and a `tf.Tensor` with
+       * a single element is returned.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3]);
+       *
+       * x.mean().print();  // or tf.mean(a)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * const axis = 1;
+       * x.mean(axis).print();  // or tf.mean(x, axis)
+       * ```
+       *
+       * @param x The input tensor.
+       * @param axis The dimension(s) to reduce. By default it reduces
+       *     all dimensions.
+       * @param keepDims If true, retains reduced dimensions with size 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function mean_(x, axis = null, keepDims = false) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "mean");
+        const axes = util["parseAxisParam"](axis, $x.shape);
+        const shapes = computeOutAndReduceShapes($x.shape, axes);
+        const reduceShape = shapes[1];
+        const reduceSize = util["sizeFromShape"](reduceShape);
+        // Use a custom gradient to bypass 2 gradient backprops since mean is used
+        // extremely often.
+        const customOp = customGrad((x) => {
+          const reduceSizeScalar = Object(tensor_ops["e" /* scalar */])(reduceSize);
+          // Cast if needed.
+          const xReduce = reduceSizeScalar.dtype === x.dtype ? x : x.cast(reduceSizeScalar.dtype);
+          const res = xReduce.div(reduceSizeScalar);
+          const value = res.sum(axis, keepDims);
+          const gradFunc = (dy) => {
+            const expandedDyShape = x.shape.slice();
+            axes.forEach((axis) => {
+              expandedDyShape[axis] = 1;
+            });
+            const expandedDy = dy.reshape(expandedDyShape);
+            const derX = expandedDy
+              .mul(Object(tensor_ops["b" /* ones */])(x.shape, "float32"))
+              .div(reduceSize);
+            return derX;
+          };
+          return { value, gradFunc };
+        });
+        return customOp($x);
+      }
+      /**
+       * Computes the minimum value from the input.
+       *
+       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
+       * is true, the rank of the array is reduced by 1 for each entry in `axes`.
+       * If `keepDims` is true, the reduced dimensions are retained with length 1.
+       * If `axes` has no entries, all dimensions are reduced, and an array with a
+       * single element is returned.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3]);
+       *
+       * x.min().print();  // or tf.min(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * const axis = 1;
+       * x.min(axis).print();  // or tf.min(x, axis)
+       * ```
+       *
+       * @param x The input Tensor.
+       * @param axis The dimension(s) to reduce. By default it reduces
+       *     all dimensions.
+       * @param keepDims If true, retains reduced dimensions with size 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function min_(x, axis = null, keepDims = false) {
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "min");
+        const xOrig = $x;
+        const origAxes = util["parseAxisParam"](axis, $x.shape);
+        let axes = origAxes;
+        const permutedAxes = getAxesPermutation(axes, $x.rank);
+        if (permutedAxes != null) {
+          $x = $x.transpose(permutedAxes);
+          axes = getInnerMostAxes(axes.length, $x.rank);
+        }
+        const grad = (dy, saved) =>
+          gradForMinAndMax(dy, saved[1], saved[0], origAxes, permutedAxes);
+        const inputsToSave = [$x];
+        const outputsToSave = [true];
+        let res = engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const y = backend.min($x, axes);
+            save([xOrig, y]);
+            return y;
+          },
+          { x: $x },
+          grad,
+          "Min",
+          { axes },
+          inputsToSave,
+          outputsToSave
+        );
+        if (keepDims) {
+          const newShape = expandShapeToKeepDim(res.shape, origAxes);
+          res = res.reshape(newShape);
+        }
+        return res;
+      }
+      /**
+       * Returns the indices of the minimum values along an `axis`.
+       *
+       * The result has the same shape as `input` with the dimension along `axis`
+       * removed.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3]);
+       *
+       * x.argMin().print();  // or tf.argMin(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 4, 3], [2, 2]);
+       *
+       * const axis = 1;
+       * x.argMin(axis).print();  // or tf.argMin(x, axis)
+       * ```
+       *
+       * @param x The input tensor.
+       * @param axis The dimension to reduce. Defaults to 0 (outer-most dimension).
+       *
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function argMin_(x, axis = 0) {
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "argMin");
+        if (axis == null) {
+          axis = 0;
+        }
+        let axes = util["parseAxisParam"](axis, $x.shape);
+        const permutedAxes = getAxesPermutation(axes, $x.rank);
+        if (permutedAxes != null) {
+          $x = $x.transpose(permutedAxes);
+          axes = getInnerMostAxes(axes.length, $x.rank);
+        }
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])($x) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.argMin($x, axes[0]);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Returns the indices of the maximum values along an `axis`.
+       *
+       * The result has the same shape as `input` with the dimension along `axis`
+       * removed.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3]);
+       *
+       * x.argMax().print();  // or tf.argMax(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 4, 3], [2, 2]);
+       *
+       * const axis = 1;
+       * x.argMax(axis).print();  // or tf.argMax(x, axis)
+       * ```
+       *
+       * @param x The input tensor.
+       * @param axis The dimension to reduce. Defaults to 0 (outer-most dimension).
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function argMax_(x, axis = 0) {
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "argMax");
+        if (axis == null) {
+          axis = 0;
+        }
+        let axes = util["parseAxisParam"](axis, $x.shape);
+        const permutedAxes = getAxesPermutation(axes, $x.rank);
+        if (permutedAxes != null) {
+          $x = $x.transpose(permutedAxes);
+          axes = getInnerMostAxes(axes.length, $x.rank);
+        }
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { x: () => Object(tensor_ops["o" /* zerosLike */])($x) };
+        };
+        const attrs = { axis: axes[0] };
+        const inputsToSave = [$x];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.argMax($x, axes[0]);
+            save([$x]);
+            return res;
+          },
+          { x: $x },
+          grad,
+          "ArgMax",
+          attrs,
+          inputsToSave
+        );
+      }
+      /**
+       * Computes the logical and of elements across dimensions of a `tf.Tensor`.
+       *
+       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
+       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
+       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
+       * length 1. If `axes` has no entries, all dimensions are reduced, and an
+       * `tf.Tensor` with a single element is returned.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 1, 1], 'bool');
+       *
+       * x.all().print();  // or tf.all(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 1, 0, 0], [2, 2], 'bool');
+       *
+       * const axis = 1;
+       * x.all(axis).print();  // or tf.all(x, axis)
+       * ```
+       *
+       * @param x The input tensor. Must be of dtype bool.
+       * @param axis The dimension(s) to reduce. By default it reduces
+       *     all dimensions.
+       * @param keepDims If true, retains reduced dimensions with size 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function all_(x, axis = null, keepDims = false) {
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "all", "bool");
+        const origAxes = util["parseAxisParam"](axis, $x.shape);
+        let axes = origAxes;
+        const permutedAxes = getAxesPermutation(axes, $x.rank);
+        if (permutedAxes != null) {
+          $x = $x.transpose(permutedAxes);
+          axes = getInnerMostAxes(axes.length, $x.rank);
+        }
+        const res = engine["a" /* ENGINE */].runKernelFunc((backend) => backend.all($x, axes), {
+          $x,
+        });
+        if (keepDims) {
+          const newShape = expandShapeToKeepDim(res.shape, origAxes);
+          return res.reshape(newShape);
+        }
+        return res;
+      }
+      /**
+       * Computes the logical or of elements across dimensions of a `tf.Tensor`.
+       *
+       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
+       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
+       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
+       * length 1. If `axes` has no entries, all dimensions are reduced, and an
+       * `tf.Tensor` with a single element is returned.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 1, 1], 'bool');
+       *
+       * x.any().print();  // or tf.any(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 1, 0, 0], [2, 2], 'bool');
+       *
+       * const axis = 1;
+       * x.any(axis).print();  // or tf.any(x, axis)
+       * ```
+       *
+       * @param x The input tensor. Must be of dtype bool.
+       * @param axis The dimension(s) to reduce. By default it reduces
+       *     all dimensions.
+       * @param keepDims If true, retains reduced dimensions with size 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function any_(x, axis = null, keepDims = false) {
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "any", "bool");
+        const origAxes = util["parseAxisParam"](axis, $x.shape);
+        let axes = origAxes;
+        const permutedAxes = getAxesPermutation(axes, $x.rank);
+        if (permutedAxes != null) {
+          $x = $x.transpose(permutedAxes);
+          axes = getInnerMostAxes(axes.length, $x.rank);
+        }
+        const res = engine["a" /* ENGINE */].runKernelFunc((backend) => backend.any($x, axes), {
+          $x,
+        });
+        if (keepDims) {
+          const newShape = expandShapeToKeepDim(res.shape, origAxes);
+          return res.reshape(newShape);
+        }
+        return res;
+      }
+      /**
+       * Calculates the mean and variance of `x`. The mean and variance are
+       * calculated by aggregating the contents of `x` across `axes`. If `x` is
+       * 1-D and `axes = [0]` this is just the mean and variance of a vector.
+       *
+       * @param x The input tensor.
+       * @param axis The dimension(s) along with to compute mean and
+       *     variance. By default it reduces all dimensions.
+       * @param keepDims If true, the moments have the same dimensionality as the
+       *     input.
+       * @return An object with two keys: `mean` and `variance`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
+      function moments_(x, axis = null, keepDims = false) {
+        x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "moments");
+        const axes = util["parseAxisParam"](axis, x.shape);
+        const mean = x.mean(axes, keepDims);
+        let keepDimsShape = mean.shape;
+        if (!keepDims) {
+          keepDimsShape = expandShapeToKeepDim(mean.shape, axes);
+        }
+        const devSquared = x.toFloat().sub(mean.reshape(keepDimsShape)).square();
+        const variance = devSquared.mean(axes, keepDims);
+        return { mean, variance };
+      }
+      const reduction_ops_all = Object(operation["a" /* op */])({ all_ });
+      // tslint:disable-next-line:variable-name
+      const any = Object(operation["a" /* op */])({ any_ });
+      const argMax = Object(operation["a" /* op */])({ argMax_ });
+      const argMin = Object(operation["a" /* op */])({ argMin_ });
+      const logSumExp = Object(operation["a" /* op */])({ logSumExp_ });
+      const reduction_ops_mean = Object(operation["a" /* op */])({ mean_ });
+      const reduction_ops_min = Object(operation["a" /* op */])({ min_ });
+      const moments = Object(operation["a" /* op */])({ moments_ });
+      const sum = Object(operation["a" /* op */])({ sum_ });
+      const reduction_ops_prod = Object(operation["a" /* op */])({ prod_ });
+      //# sourceMappingURL=reduction_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/square.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes square of `x` element-wise: `x ^ 2`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, Math.sqrt(2), -1]);
+       *
+       * x.square().print();  // or tf.square(x)
+       * ```
+       * @param x The input Tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function square_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "square");
+        const attrs = {};
+        const inputsToSave = [$x];
+        const outputsToSave = [];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            save([$x]);
+            return backend.square($x);
+          },
+          { x: $x },
+          null /* grad */,
+          "Square",
+          attrs,
+          inputsToSave,
+          outputsToSave
+        );
+      }
+      const square = Object(operation["a" /* op */])({ square_ });
+      //# sourceMappingURL=square.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/unary_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes `-1 * x` element-wise.
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, -2, 0], [2, 2]);
+       *
+       * x.neg().print();  // or tf.neg(x)
+       * ```
+       *
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function neg_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "neg");
+        const grad = (dy) => {
+          return { x: () => dy.neg() };
+        };
+        const attrs = {};
+        const inputsToSave = [$x];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.neg($x),
+          { x: $x },
+          grad,
+          "Neg",
+          attrs,
+          inputsToSave
+        );
+      }
+      /**
+       * Computes ceiling of input `tf.Tensor` element-wise: `ceil(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([.6, 1.1, -3.3]);
+       *
+       * x.ceil().print();  // or tf.ceil(x)
+       * ```
+       * @param x The input Tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function ceil_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "ceil");
+        // TODO(manrajgrover): Return null for gradients when backprop supports it.
+        const grad = (dy) => {
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.ceil($x), { $x }, grad);
+      }
+      /**
+       * Computes floor of input `tf.Tensor` element-wise: `floor(x)`.
+       *
+       * ```js
+       * const x = tf.tensor1d([.6, 1.1, -3.3]);
+       *
+       * x.floor().print();  // or tf.floor(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function floor_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "floor");
+        // TODO(nsthorat): Let gradients be null for cases where we want to stop
+        // backpropgation.
+        const grad = (dy) => {
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.floor($x), { $x }, grad);
+      }
+      /**
+       * Returns an element-wise indication of the sign of a number.
+       *
+       * ```js
+       * const x = tf.tensor1d([.6, 1.1, -3.3, NaN, 0]);
+       *
+       * x.sign().print();  // or tf.sign(x)
+       * ```
+       * @param x The input Tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function sign_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sign");
+        const grad = (dy) => {
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.sign($x), { $x }, grad);
+      }
+      /**
+       * RReturns which elements of x are NaN.
+       *
+       * ```js
+       * const x = tf.tensor1d([NaN, Infinity, -Infinity, 0, 1]);
+       *
+       * x.isNaN().print();  // or tf.isNaN(x)
+       * ```
+       * @param x The input Tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function isNaN_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "isNaN");
+        // TODO(nsthorat): Let gradients be null for cases where we want to stop
+        // backpropgation.
+        const grad = (dy) => {
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.isNaN($x), { $x }, grad);
+      }
+      /**
+       * Returns which elements of x are Infinity or -Infinity.
+       *
+       * ```js
+       * const x = tf.tensor1d([NaN, Infinity, -Infinity, 0, 1]);
+       *
+       * x.isInf().print();  // or tf.isNaN(x)
+       * ```
+       * @param x The input Tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function isInf_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "isInf");
+        // TODO(nsthorat): Let gradients be null for cases where we want to stop
+        // backpropgation.
+        const grad = (dy) => {
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.isInf($x), { $x }, grad);
+      }
+      /**
+       * Returns which elements of x are finite.
+       *
+       * ```js
+       * const x = tf.tensor1d([NaN, Infinity, -Infinity, 0, 1]);
+       *
+       * x.isFinite().print();  // or tf.isNaN(x)
+       * ```
+       * @param x The input Tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function isFinite_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "isFinite");
+        // TODO(nsthorat): Let gradients be null for cases where we want to stop
+        // backpropgation.
+        const grad = (dy) => {
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.isFinite($x),
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes round of input `tf.Tensor` element-wise: `round(x)`.
+       * It implements banker's rounding.
+       *
+       * ```js
+       * const x = tf.tensor1d([.6, 1.1, -3.3]);
+       *
+       * x.round().print();  // or tf.round(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function round_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "round");
+        // TODO(nsthorat): Let gradients be null for cases where we want to stop
+        // backpropgation.
+        const grad = (dy) => {
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.round($x), { $x }, grad);
+      }
+      /**
+       * Computes exponential of the input `tf.Tensor` element-wise. `e ^ x`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, -3]);
+       *
+       * x.exp().print();  // or tf.exp(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function exp_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "exp");
+        const bck = (dy, saved) => {
+          // tslint:disable-next-line: no-unnecessary-type-assertion
+          return { x: () => dy.mul(saved[0]) };
+        };
+        const attrs = {};
+        const inputsToSave = [];
+        const outputsToSave = [true];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const y = backend.exp($x);
+            save([y]);
+            return y;
+          },
+          { x: $x },
+          bck,
+          "Exp",
+          attrs,
+          inputsToSave,
+          outputsToSave
+        );
+      }
+      /**
+       * Computes exponential of the input `tf.Tensor` minus one element-wise.
+       * `e ^ x - 1`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, -3]);
+       *
+       * x.expm1().print();  // or tf.expm1(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function expm1_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "expm1");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { $x: () => dy.mul($x.exp()) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.expm1($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes natural logarithm of the input `tf.Tensor` element-wise: `ln(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, Math.E]);
+       *
+       * x.log().print();  // or tf.log(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function log_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "log");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { x: () => dy.div($x.toFloat()) };
+        };
+        const attrs = {};
+        const inputsToSave = [$x];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.log($x);
+            save([$x]);
+            return res;
+          },
+          { x: $x },
+          grad,
+          "Log",
+          attrs,
+          inputsToSave
+        );
+      }
+      /**
+       * Computes natural logarithm of the input `tf.Tensor` plus one
+       * element-wise: `ln(1 + x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, Math.E - 1]);
+       *
+       * x.log1p().print();  // or tf.log1p(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function log1p_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "log1p");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { $x: () => dy.div($x.add(1)) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.log1p($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes square root of the input `tf.Tensor` element-wise: `y = sqrt(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 4, -1]);
+       *
+       * x.sqrt().print();  // or tf.sqrt(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function sqrt_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sqrt");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { x: () => dy.div($x.toFloat().sqrt().mul(2)) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.sqrt($x);
+            save([$x]);
+            return res;
+          },
+          { x: $x },
+          grad,
+          "Sqrt",
+          {}
+        );
+      }
+      /**
+       * Computes reciprocal of square root of the input `tf.Tensor` element-wise:
+       * `y = 1 / sqrt(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 4, -1]);
+       *
+       * x.rsqrt().print();  // or tf.rsqrt(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function rsqrt_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "rsqrt");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { x: () => dy.div($x.pow(1.5).mul(2)).neg() };
+        };
+        const inputsToSave = [$x];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.rsqrt($x);
+            save([$x]);
+            return res;
+          },
+          { x: $x },
+          grad,
+          "Rsqrt",
+          {} /* attrs */,
+          inputsToSave
+        );
+      }
+      /**
+       * Computes reciprocal of x element-wise: `1 / x`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, 2]);
+       *
+       * x.reciprocal().print();  // or tf.reciprocal(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function reciprocal_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reciprocal");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { $x: () => dy.div($x.square().neg()) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.reciprocal($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes absolute value element-wise: `abs(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([-1, 2, -3, 4]);
+       *
+       * x.abs().print();  // or tf.abs(x)
+       * ```
+       * @param x The input `tf.Tensor`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function abs_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "abs");
+        if ($x.dtype === "complex64") {
+          return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.complexAbs($x), {
+            $x,
+          });
+        }
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { x: () => dy.mul($x.toFloat().step(-1)) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.abs($x);
+            save([$x]);
+            return res;
+          },
+          { x: $x },
+          grad,
+          "Abs"
+        );
+      }
+      /**
+       * Clips values element-wise. `max(min(x, clipValueMax), clipValueMin)`
+       *
+       * ```js
+       * const x = tf.tensor1d([-1, 2, -3, 4]);
+       *
+       * x.clipByValue(-2, 3).print();  // or tf.clipByValue(x, -2, 3)
+       * ```
+       * @param x The input tensor.
+       * @param clipValueMin Lower-bound of range to be clipped to.
+       * @param clipValueMax Upper-bound of range to be clipped to.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function clipByValue_(x, clipValueMin, clipValueMax) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "clipByValue");
+        util["assert"](
+          clipValueMin <= clipValueMax,
+          () =>
+            `Error in clip: min (${clipValueMin}) must be ` +
+            `less than or equal to max (${clipValueMax}).`
+        );
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return {
+            x: () =>
+              dy.where(
+                $x.greaterEqual(clipValueMin).logicalAnd($x.lessEqual(clipValueMax)),
+                Object(tensor_ops["o" /* zerosLike */])(dy)
+              ),
+          };
+        };
+        const inputsToSave = [$x];
+        const attr = { min: clipValueMin, max: clipValueMax };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.clip($x, clipValueMin, clipValueMax);
+            save([$x]);
+            return res;
+          },
+          { x: $x },
+          grad,
+          "ClipByValue",
+          attr,
+          inputsToSave
+        );
+      }
+      /**
+       * Computes sigmoid element-wise, `1 / (1 + exp(-x))`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, -1, 2, -3]);
+       *
+       * x.sigmoid().print();  // or tf.sigmoid(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function sigmoid_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sigmoid");
+        const grad = (dy, saved) => {
+          const [y] = saved;
+          return { x: () => dy.mul(y.mul(Object(tensor_ops["e" /* scalar */])(1).sub(y))) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const y = backend.sigmoid($x);
+            save([y]);
+            return y;
+          },
+          { x: $x },
+          grad,
+          "Sigmoid"
+        );
+      }
+      /**
+       * Computes log sigmoid of the input `tf.Tensor` element-wise:
+       * `logSigmoid(x)`. For numerical stability, we use `-tf.softplus(-x)`.
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, .7]);
+       *
+       * x.logSigmoid().print();  // or tf.logSigmoid(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function logSigmoid_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "logSigmoid");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { $x: () => dy.mul($x.neg().sigmoid()) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.softplus($x.neg()).neg();
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes softplus of the input `tf.Tensor` element-wise: `log(exp(x) + 1)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, .7]);
+       *
+       * x.softplus().print();  // or tf.softplus(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function softplus_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "softplus");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { $x: () => dy.mul($x.sigmoid()) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.softplus($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes sin of the input Tensor element-wise: `sin(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, Math.PI / 2, Math.PI * 3 / 4]);
+       *
+       * x.sin().print();  // or tf.sin(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function sin_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sin");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { x: () => $x.toFloat().cos().mul(dy) };
+        };
+        const inputsToSave = [$x];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.sin($x);
+            save([$x]);
+            return res;
+          },
+          { x: $x },
+          grad,
+          "Sin",
+          {} /* attrs */,
+          inputsToSave
+        );
+      }
+      /**
+       * Computes cos of the input `tf.Tensor` element-wise: `cos(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, Math.PI / 2, Math.PI * 3 / 4]);
+       *
+       * x.cos().print();  // or tf.cos(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function cos_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "cos");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { x: () => $x.toFloat().sin().neg().mul(dy) };
+        };
+        const inputsToSave = [$x];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.cos($x);
+            save([$x]);
+            return res;
+          },
+          { x: $x },
+          grad,
+          "Cos",
+          {} /* attrs */,
+          inputsToSave
+        );
+      }
+      /**
+       * Computes tan of the input `tf.Tensor` element-wise, `tan(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, Math.PI / 2, Math.PI * 3 / 4]);
+       *
+       * x.tan().print();  // or tf.tan(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function tan_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "tan");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { $x: () => dy.div($x.cos().square()) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.tan($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes asin of the input `tf.Tensor` element-wise: `asin(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, .7]);
+       *
+       * x.asin().print();  // or tf.asin(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function asin_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "asin");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return {
+            // tslint:disable-next-line: no-unnecessary-type-assertion
+            $x: () =>
+              dy.div(Object(tensor_ops["e" /* scalar */])(1).sub($x.toFloat().square()).sqrt()),
+          };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.asin($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes acos of the input `tf.Tensor` element-wise: `acos(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, .7]);
+       *
+       * x.acos().print();  // or tf.acos(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function acos_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "acos");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return {
+            $x: () => {
+              const a = $x.toFloat().square();
+              const b = Object(tensor_ops["e" /* scalar */])(1).sub(a).sqrt();
+              // tslint:disable-next-line: no-unnecessary-type-assertion
+              return dy.div(b).neg();
+            },
+          };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.acos($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes atan of the input `tf.Tensor` element-wise: `atan(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, .7]);
+       *
+       * x.atan().print();  // or tf.atan(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function atan_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "atan");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return { $x: () => dy.div($x.toFloat().square().add(1)) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.atan($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes hyperbolic sin of the input `tf.Tensor` element-wise: `sinh(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, .7]);
+       *
+       * x.sinh().print();  // or tf.sinh(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function sinh_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "sinh");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          // tslint:disable-next-line: no-unnecessary-type-assertion
+          return { $x: () => $x.toFloat().cosh().mul(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.sinh($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes hyperbolic cos of the input `tf.Tensor` element-wise: `cosh(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, .7]);
+       *
+       * x.cosh().print();  // or tf.cosh(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function cosh_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "cosh");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          // tslint:disable-next-line: no-unnecessary-type-assertion
+          return { $x: () => $x.toFloat().sinh().mul(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.cosh($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes hyperbolic tangent of the input `tf.Tensor` element-wise: `tanh(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, 70]);
+       *
+       * x.tanh().print();  // or tf.tanh(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function tanh_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "tanh");
+        const grad = (dy, saved) => {
+          const [y] = saved;
+          // tslint:disable-next-line: no-unnecessary-type-assertion
+          return { x: () => Object(tensor_ops["e" /* scalar */])(1).sub(y.square()).mul(dy) };
+        };
+        const outputsToSave = [true];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const y = backend.tanh($x);
+            save([y]);
+            return y;
+          },
+          { x: $x },
+          grad,
+          "Tanh",
+          {} /* attrs */,
+          null /* inputsToSave */,
+          outputsToSave
+        );
+      }
+      /**
+       * Computes inverse hyperbolic sin of the input `tf.Tensor` element-wise:
+       * `asinh(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 1, -1, .7]);
+       *
+       * x.asinh().print();  // or tf.asinh(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function asinh_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "asinh");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return {
+            $x: () => {
+              const a = Object(tensor_ops["e" /* scalar */])(1).add($x.toFloat().square()).sqrt();
+              // tslint:disable-next-line: no-unnecessary-type-assertion
+              return dy.div(a);
+            },
+          };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.asinh($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes the inverse hyperbolic cos of the input `tf.Tensor` element-wise:
+       * `acosh(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([10, 1, 3, 5.7]);
+       *
+       * x.acosh().print();  // or tf.acosh(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function acosh_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "acosh");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return {
+            $x: () => {
+              const a = $x.toFloat().square().sub(1).sqrt();
+              // tslint:disable-next-line: no-unnecessary-type-assertion
+              return dy.div(a);
+            },
+          };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.acosh($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes inverse hyperbolic tan of the input `tf.Tensor` element-wise:
+       * `atanh(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, .1, -.1, .7]);
+       *
+       * x.atanh().print();  // or tf.atanh(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function atanh_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "atanh");
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return {
+            $x: () => dy.div(Object(tensor_ops["e" /* scalar */])(1).sub($x.toFloat().square())),
+          };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.atanh($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes gause error function of the input `tf.Tensor` element-wise:
+       * `erf(x)`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, .1, -.1, .7]);
+       *
+       * x.erf().print(); // or tf.erf(x);
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function erf_(x) {
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "erf");
+        util["assert"](
+          $x.dtype === "int32" || $x.dtype === "float32",
+          () => "Input dtype must be `int32` or `float32`."
+        );
+        if ($x.dtype === "int32") {
+          $x = $x.toFloat();
+        }
+        const grad = (dy, saved) => {
+          const [$x] = saved;
+          return {
+            $x: () =>
+              dy.mul(
+                $x
+                  .square()
+                  .neg()
+                  .exp()
+                  .mul(2 / Math.sqrt(Math.PI))
+              ),
+          };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.erf($x);
+            save([$x]);
+            return res;
+          },
+          { $x },
+          grad
+        );
+      }
+      /**
+       * Computes step of the input `tf.Tensor` element-wise: `x > 0 ? 1 : alpha * x`
+       *
+       * ```js
+       * const x = tf.tensor1d([0, 2, -1, -3]);
+       *
+       * x.step(.5).print();  // or tf.step(x, .5)
+       * ```
+       * @param x The input tensor.
+       * @param alpha The gradient when input is negative.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function step_(x, alpha = 0.0) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "step");
+        // TODO(manrajgrover): Return null for gradients when backprop supports
+        // it.
+        const grad = (dy) => {
+          return { $x: () => Object(tensor_ops["o" /* zerosLike */])(dy) };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.step($x, alpha),
+          { $x },
+          grad
+        );
+      }
+      const abs = Object(operation["a" /* op */])({ abs_ });
+      const acos = Object(operation["a" /* op */])({ acos_ });
+      const acosh = Object(operation["a" /* op */])({ acosh_ });
+      const asin = Object(operation["a" /* op */])({ asin_ });
+      const asinh = Object(operation["a" /* op */])({ asinh_ });
+      const atan = Object(operation["a" /* op */])({ atan_ });
+      const atanh = Object(operation["a" /* op */])({ atanh_ });
+      const ceil = Object(operation["a" /* op */])({ ceil_ });
+      const clipByValue = Object(operation["a" /* op */])({ clipByValue_ });
+      const cos = Object(operation["a" /* op */])({ cos_ });
+      const cosh = Object(operation["a" /* op */])({ cosh_ });
+      const erf = Object(operation["a" /* op */])({ erf_ });
+      const unary_ops_exp = Object(operation["a" /* op */])({ exp_ });
+      const expm1 = Object(operation["a" /* op */])({ expm1_ });
+      const floor = Object(operation["a" /* op */])({ floor_ });
+      const log = Object(operation["a" /* op */])({ log_ });
+      const log1p = Object(operation["a" /* op */])({ log1p_ });
+      const logSigmoid = Object(operation["a" /* op */])({ logSigmoid_ });
+      const neg = Object(operation["a" /* op */])({ neg_ });
+      const reciprocal = Object(operation["a" /* op */])({ reciprocal_ });
+      const round = Object(operation["a" /* op */])({ round_ });
+      const rsqrt = Object(operation["a" /* op */])({ rsqrt_ });
+      const sigmoid = Object(operation["a" /* op */])({ sigmoid_ });
+      const sign = Object(operation["a" /* op */])({ sign_ });
+      const unary_ops_isNaN = Object(operation["a" /* op */])({ isNaN_ });
+      const isInf = Object(operation["a" /* op */])({ isInf_ });
+      const unary_ops_isFinite = Object(operation["a" /* op */])({ isFinite_ });
+      const sin = Object(operation["a" /* op */])({ sin_ });
+      const sinh = Object(operation["a" /* op */])({ sinh_ });
+      const softplus = Object(operation["a" /* op */])({ softplus_ });
+      const sqrt = Object(operation["a" /* op */])({ sqrt_ });
+      const unary_ops_step = Object(operation["a" /* op */])({ step_ });
+      const tan = Object(operation["a" /* op */])({ tan_ });
+      const tanh = Object(operation["a" /* op */])({ tanh_ });
+      //# sourceMappingURL=unary_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Atan2_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const atan2GradConfig = {
+        kernelName: kernel_names["c" /* Atan2 */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
+          const derA = () => {
+            const d = add(square(a), square(b));
+            let res = mul(dy, div(b, d));
+            const reduceAxes = getReductionAxes(a.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = sum(res, reduceAxes);
+            }
+            return reshape(res, a.shape);
+          };
+          const derB = () => {
+            const d = add(square(a), square(b));
+            let res = neg(mul(dy, div(a, d)));
+            const reduceAxes = getReductionAxes(b.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = sum(res, reduceAxes);
+            }
+            return reshape(res, b.shape);
+          };
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=Atan2_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function computePool2DInfo(
+        inShape,
+        filterSize,
+        strides,
+        dilations,
+        pad,
+        roundingMode,
+        dataFormat = "channelsLast"
+      ) {
+        const [filterHeight, filterWidth] = parseTupleParam(filterSize);
+        let filterShape;
+        if (dataFormat === "channelsLast") {
+          filterShape = [filterHeight, filterWidth, inShape[3], inShape[3]];
+        } else if (dataFormat === "channelsFirst") {
+          filterShape = [filterHeight, filterWidth, inShape[1], inShape[1]];
+        } else {
+          throw new Error(`Unknown dataFormat ${dataFormat}`);
+        }
+        return computeConv2DInfo(
+          inShape,
+          filterShape,
+          strides,
+          dilations,
+          pad,
+          roundingMode,
+          false,
+          dataFormat
+        );
+      }
+      /**
+       * Computes the information for a forward pass of a pooling3D operation.
+       */
+      function computePool3DInfo(
+        inShape,
+        filterSize,
+        strides,
+        dilations,
+        pad,
+        roundingMode,
+        dataFormat = "NDHWC"
+      ) {
+        const [filterDepth, filterHeight, filterWidth] = parse3TupleParam(filterSize);
+        let filterShape;
+        let $dataFormat;
+        if (dataFormat === "NDHWC") {
+          $dataFormat = "channelsLast";
+          filterShape = [filterDepth, filterHeight, filterWidth, inShape[4], inShape[4]];
+        } else if (dataFormat === "NCDHW") {
+          $dataFormat = "channelsFirst";
+          filterShape = [filterDepth, filterHeight, filterWidth, inShape[1], inShape[1]];
+        } else {
+          throw new Error(`Unknown dataFormat ${dataFormat}`);
+        }
+        return computeConv3DInfo(
+          inShape,
+          filterShape,
+          strides,
+          dilations,
+          pad,
+          false,
+          $dataFormat,
+          roundingMode
+        );
+      }
+      /**
+       * Computes the information for a forward pass of a convolution/pooling
+       * operation.
+       */
+      function computeConv2DInfo(
+        inShape,
+        filterShape,
+        strides,
+        dilations,
+        pad,
+        roundingMode,
+        depthwise = false,
+        dataFormat = "channelsLast"
+      ) {
+        let [batchSize, inHeight, inWidth, inChannels] = [-1, -1, -1, -1];
+        if (dataFormat === "channelsLast") {
+          [batchSize, inHeight, inWidth, inChannels] = inShape;
+        } else if (dataFormat === "channelsFirst") {
+          [batchSize, inChannels, inHeight, inWidth] = inShape;
+        } else {
+          throw new Error(`Unknown dataFormat ${dataFormat}`);
+        }
+        const [filterHeight, filterWidth, , filterChannels] = filterShape;
+        const [strideHeight, strideWidth] = parseTupleParam(strides);
+        const [dilationHeight, dilationWidth] = parseTupleParam(dilations);
+        const effectiveFilterHeight = getEffectiveFilterSize(filterHeight, dilationHeight);
+        const effectiveFilterWidth = getEffectiveFilterSize(filterWidth, dilationWidth);
+        const { padInfo, outHeight, outWidth } = getPadAndOutInfo(
+          pad,
+          inHeight,
+          inWidth,
+          strideHeight,
+          strideWidth,
+          effectiveFilterHeight,
+          effectiveFilterWidth,
+          roundingMode,
+          dataFormat
+        );
+        const outChannels = depthwise ? filterChannels * inChannels : filterChannels;
+        let outShape;
+        if (dataFormat === "channelsFirst") {
+          outShape = [batchSize, outChannels, outHeight, outWidth];
+        } else if (dataFormat === "channelsLast") {
+          outShape = [batchSize, outHeight, outWidth, outChannels];
+        }
+        return {
+          batchSize,
+          dataFormat,
+          inHeight,
+          inWidth,
+          inChannels,
+          outHeight,
+          outWidth,
+          outChannels,
+          padInfo,
+          strideHeight,
+          strideWidth,
+          filterHeight,
+          filterWidth,
+          effectiveFilterHeight,
+          effectiveFilterWidth,
+          dilationHeight,
+          dilationWidth,
+          inShape,
+          outShape,
+          filterShape,
+        };
+      }
+      /**
+       * Computes the information for a forward pass of a 3D convolution/pooling
+       * operation.
+       */
+      function computeConv3DInfo(
+        inShape,
+        filterShape,
+        strides,
+        dilations,
+        pad,
+        depthwise = false,
+        dataFormat = "channelsLast",
+        roundingMode
+      ) {
+        let [batchSize, inDepth, inHeight, inWidth, inChannels] = [-1, -1, -1, -1, -1];
+        if (dataFormat === "channelsLast") {
+          [batchSize, inDepth, inHeight, inWidth, inChannels] = inShape;
+        } else if (dataFormat === "channelsFirst") {
+          [batchSize, inChannels, inDepth, inHeight, inWidth] = inShape;
+        } else {
+          throw new Error(`Unknown dataFormat ${dataFormat}`);
+        }
+        const [filterDepth, filterHeight, filterWidth, , filterChannels] = filterShape;
+        const [strideDepth, strideHeight, strideWidth] = parse3TupleParam(strides);
+        const [dilationDepth, dilationHeight, dilationWidth] = parse3TupleParam(dilations);
+        const effectiveFilterDepth = getEffectiveFilterSize(filterDepth, dilationDepth);
+        const effectiveFilterHeight = getEffectiveFilterSize(filterHeight, dilationHeight);
+        const effectiveFilterWidth = getEffectiveFilterSize(filterWidth, dilationWidth);
+        const { padInfo, outDepth, outHeight, outWidth } = get3DPadAndOutInfo(
+          pad,
+          inDepth,
+          inHeight,
+          inWidth,
+          strideDepth,
+          strideHeight,
+          strideWidth,
+          effectiveFilterDepth,
+          effectiveFilterHeight,
+          effectiveFilterWidth,
+          roundingMode
+        );
+        const outChannels = depthwise ? filterChannels * inChannels : filterChannels;
+        let outShape;
+        if (dataFormat === "channelsFirst") {
+          outShape = [batchSize, outChannels, outDepth, outHeight, outWidth];
+        } else if (dataFormat === "channelsLast") {
+          outShape = [batchSize, outDepth, outHeight, outWidth, outChannels];
+        }
+        return {
+          batchSize,
+          dataFormat,
+          inDepth,
+          inHeight,
+          inWidth,
+          inChannels,
+          outDepth,
+          outHeight,
+          outWidth,
+          outChannels,
+          padInfo,
+          strideDepth,
+          strideHeight,
+          strideWidth,
+          filterDepth,
+          filterHeight,
+          filterWidth,
+          effectiveFilterDepth,
+          effectiveFilterHeight,
+          effectiveFilterWidth,
+          dilationDepth,
+          dilationHeight,
+          dilationWidth,
+          inShape,
+          outShape,
+          filterShape,
+        };
+      }
+      function computeOutputShape2D(inShape, fieldSize, stride, zeroPad, roundingMode) {
+        if (zeroPad == null) {
+          zeroPad = computeDefaultPad(inShape, fieldSize, stride);
+        }
+        const inputRows = inShape[0];
+        const inputCols = inShape[1];
+        const outputRows = conditionalRound(
+          (inputRows - fieldSize + 2 * zeroPad) / stride + 1,
+          roundingMode
+        );
+        util["assert"](
+          util["isInt"](outputRows),
+          () =>
+            `The output # of rows (${outputRows}) must be an integer. ` +
+            `Change the stride and/or zero pad parameters`
+        );
+        const outputCols = conditionalRound(
+          (inputCols - fieldSize + 2 * zeroPad) / stride + 1,
+          roundingMode
+        );
+        util["assert"](
+          util["isInt"](outputCols),
+          () =>
+            `The output # of columns (${outputCols}) must be an integer. ` +
+            `Change the stride and/or zero pad parameters`
+        );
+        return [outputRows, outputCols];
+      }
+      function computeOutputShape4D(
+        inShape,
+        fieldSize,
+        outChannels,
+        stride,
+        zeroPad,
+        roundingMode
+      ) {
+        if (zeroPad == null) {
+          zeroPad = computeDefaultPad(inShape, fieldSize, stride);
+        }
+        const inputDepth = inShape[0];
+        const inputRows = inShape[1];
+        const inputCols = inShape[2];
+        const outputDepths = conditionalRound(
+          (inputDepth - fieldSize + 2 * zeroPad) / stride + 1,
+          roundingMode
+        );
+        util["assert"](
+          util["isInt"](outputDepths),
+          () =>
+            `The output # of depths (${outputDepths}) must be an integer. ` +
+            `Change the stride and/or zero pad parameters`
+        );
+        const outputRows = conditionalRound(
+          (inputRows - fieldSize + 2 * zeroPad) / stride + 1,
+          roundingMode
+        );
+        util["assert"](
+          util["isInt"](outputRows),
+          () =>
+            `The output # of rows (${outputRows}) must be an integer. ` +
+            `Change the stride and/or zero pad parameters`
+        );
+        const outputCols = conditionalRound(
+          (inputCols - fieldSize + 2 * zeroPad) / stride + 1,
+          roundingMode
+        );
+        util["assert"](
+          util["isInt"](outputCols),
+          () =>
+            `The output # of columns (${outputCols}) must be an integer. ` +
+            `Change the stride and/or zero pad parameters`
+        );
+        return [outputDepths, outputRows, outputCols, outChannels];
+      }
+      function computeDefaultPad(inputShape, fieldSize, stride, dilation = 1) {
+        const effectiveFieldSize = getEffectiveFilterSize(fieldSize, dilation);
+        return Math.floor((inputShape[0] * (stride - 1) - stride + effectiveFieldSize) / 2);
+      }
+      function parseTupleParam(param) {
+        if (typeof param === "number") {
+          return [param, param, param];
+        }
+        if (param.length === 2) {
+          return [param[0], param[1], 1];
+        }
+        return param;
+      }
+      function parse3TupleParam(param) {
+        return typeof param === "number" ? [param, param, param] : param;
+      }
+      /* See https://www.tensorflow.org/api_docs/python/tf/nn/atrous_conv2d
+       * Atrous convolution is equivalent to standard convolution with upsampled
+       * filters with effective_filter_height =
+       * filter_height + (filter_height - 1) * (dilation - 1)
+       * and effective_filter_width =
+       * filter_width + (filter_width - 1) * (dilation - 1),
+       * produced by inserting dilation - 1 zeros along consecutive elements across
+       * the filters' spatial dimensions.
+       * When there is a dilation, this converts a filter dimension to the
+       * effective filter dimension, so it can be used in a standard convolution.
+       */
+      function getEffectiveFilterSize(filterSize, dilation) {
+        if (dilation <= 1) {
+          return filterSize;
+        }
+        return filterSize + (filterSize - 1) * (dilation - 1);
+      }
+      function getPadAndOutInfo(
+        pad,
+        inHeight,
+        inWidth,
+        strideHeight,
+        strideWidth,
+        filterHeight,
+        filterWidth,
+        roundingMode,
+        dataFormat
+      ) {
+        let padInfo;
+        let outHeight;
+        let outWidth;
+        if (typeof pad === "number") {
+          const padType = pad === 0 ? "VALID" : "NUMBER";
+          padInfo = { top: pad, bottom: pad, left: pad, right: pad, type: padType };
+          const outShape = computeOutputShape2D(
+            [inHeight, inWidth],
+            filterHeight,
+            strideHeight,
+            pad,
+            roundingMode
+          );
+          outHeight = outShape[0];
+          outWidth = outShape[1];
+        } else if (pad === "same") {
+          outHeight = Math.ceil(inHeight / strideHeight);
+          outWidth = Math.ceil(inWidth / strideWidth);
+          const padAlongHeight = Math.max(
+            0,
+            (outHeight - 1) * strideHeight + filterHeight - inHeight
+          );
+          const padAlongWidth = Math.max(0, (outWidth - 1) * strideWidth + filterWidth - inWidth);
+          const top = Math.floor(padAlongHeight / 2);
+          const bottom = padAlongHeight - top;
+          const left = Math.floor(padAlongWidth / 2);
+          const right = padAlongWidth - left;
+          padInfo = { top, bottom, left, right, type: "SAME" };
+        } else if (pad === "valid") {
+          padInfo = { top: 0, bottom: 0, left: 0, right: 0, type: "VALID" };
+          outHeight = Math.ceil((inHeight - filterHeight + 1) / strideHeight);
+          outWidth = Math.ceil((inWidth - filterWidth + 1) / strideWidth);
+        } else if (typeof pad === "object") {
+          const top = dataFormat === "channelsLast" ? pad[1][0] : pad[2][0];
+          const bottom = dataFormat === "channelsLast" ? pad[1][1] : pad[2][1];
+          const left = dataFormat === "channelsLast" ? pad[2][0] : pad[3][0];
+          const right = dataFormat === "channelsLast" ? pad[2][1] : pad[3][1];
+          const padType =
+            top === 0 && bottom === 0 && left === 0 && right === 0 ? "VALID" : "EXPLICIT";
+          padInfo = { top, bottom, left, right, type: padType };
+          outHeight = conditionalRound(
+            (inHeight - filterHeight + top + bottom) / strideHeight + 1,
+            roundingMode
+          );
+          outWidth = conditionalRound(
+            (inWidth - filterWidth + left + right) / strideWidth + 1,
+            roundingMode
+          );
+        } else {
+          throw Error(`Unknown padding parameter: ${pad}`);
+        }
+        return { padInfo, outHeight, outWidth };
+      }
+      function get3DPadAndOutInfo(
+        pad,
+        inDepth,
+        inHeight,
+        inWidth,
+        strideDepth,
+        strideHeight,
+        strideWidth,
+        filterDepth,
+        filterHeight,
+        filterWidth,
+        roundingMode
+      ) {
+        let padInfo;
+        let outDepth;
+        let outHeight;
+        let outWidth;
+        if (typeof pad === "number") {
+          const padType = pad === 0 ? "VALID" : "NUMBER";
+          padInfo = {
+            top: pad,
+            bottom: pad,
+            left: pad,
+            right: pad,
+            front: pad,
+            back: pad,
+            type: padType,
+          };
+          const outShape = computeOutputShape4D(
+            [inDepth, inHeight, inWidth, 1],
+            filterDepth,
+            1,
+            strideDepth,
+            pad,
+            roundingMode
+          );
+          outDepth = outShape[0];
+          outHeight = outShape[1];
+          outWidth = outShape[2];
+        } else if (pad === "same") {
+          outDepth = Math.ceil(inDepth / strideDepth);
+          outHeight = Math.ceil(inHeight / strideHeight);
+          outWidth = Math.ceil(inWidth / strideWidth);
+          const padAlongDepth = (outDepth - 1) * strideDepth + filterDepth - inDepth;
+          const padAlongHeight = (outHeight - 1) * strideHeight + filterHeight - inHeight;
+          const padAlongWidth = (outWidth - 1) * strideWidth + filterWidth - inWidth;
+          const front = Math.floor(padAlongDepth / 2);
+          const back = padAlongDepth - front;
+          const top = Math.floor(padAlongHeight / 2);
+          const bottom = padAlongHeight - top;
+          const left = Math.floor(padAlongWidth / 2);
+          const right = padAlongWidth - left;
+          padInfo = { top, bottom, left, right, front, back, type: "SAME" };
+        } else if (pad === "valid") {
+          padInfo = {
+            top: 0,
+            bottom: 0,
+            left: 0,
+            right: 0,
+            front: 0,
+            back: 0,
+            type: "VALID",
+          };
+          outDepth = Math.ceil((inDepth - filterDepth + 1) / strideDepth);
+          outHeight = Math.ceil((inHeight - filterHeight + 1) / strideHeight);
+          outWidth = Math.ceil((inWidth - filterWidth + 1) / strideWidth);
+        } else {
+          throw Error(`Unknown padding parameter: ${pad}`);
+        }
+        return { padInfo, outDepth, outHeight, outWidth };
+      }
+      /**
+       * Rounds a value depending on the rounding mode
+       * @param value
+       * @param roundingMode
+       */
+      function conditionalRound(value, roundingMode) {
+        if (!roundingMode) {
+          return value;
+        }
+        switch (roundingMode) {
+          case "round":
+            // used for Caffe Conv
+            return Math.round(value);
+          case "ceil":
+            // used for Caffe Pool
+            return Math.ceil(value);
+          case "floor":
+            return Math.floor(value);
+          default:
+            throw new Error(`Unknown roundingMode ${roundingMode}`);
+        }
+      }
+      function tupleValuesAreOne(param) {
+        const [dimA, dimB, dimC] = parseTupleParam(param);
+        return dimA === 1 && dimB === 1 && dimC === 1;
+      }
+      function eitherStridesOrDilationsAreOne(strides, dilations) {
+        return tupleValuesAreOne(strides) || tupleValuesAreOne(dilations);
+      }
+      /**
+       * Convert Conv2D dataFormat from 'NHWC'|'NCHW' to
+       *    'channelsLast'|'channelsFirst'
+       * @param dataFormat in 'NHWC'|'NCHW' mode
+       * @return dataFormat in 'channelsLast'|'channelsFirst' mode
+       * @throws unknown dataFormat
+       */
+      function convertConv2DDataFormat(dataFormat) {
+        if (dataFormat === "NHWC") {
+          return "channelsLast";
+        } else if (dataFormat === "NCHW") {
+          return "channelsFirst";
+        } else {
+          throw new Error(`Unknown dataFormat ${dataFormat}`);
+        }
+      }
+      //# sourceMappingURL=conv_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_3d_backprop.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the backprop of a 3d avg pool.
+       *
+       * @param dy The dy error, of rank 5 of shape
+       *     [batchSize, depth, height, width, channels].
+       * assumed.
+       * @param input The original input image, of rank 5 or rank4 of shape
+       *     [batchSize, depth, height, width, channels].
+       * @param filterSize The filter size:
+       *     `[filterDepth, filterHeight, filterWidth]`.
+       *     `filterSize` is a single number,
+       *     then `filterDepth == filterHeight == filterWidth`.
+       * @param strides The strides of the pooling:
+       *     `[strideDepth, strideHeight, strideWidth]`. If
+       *     `strides` is a single number, then `strideHeight == strideWidth`.
+       * @param dilations Deprecated, this field will be gone in v3.0.0. The dilation
+       *     rates: `[dilationDepth, dilationHeight, dilationWidth]`
+       *     in which we sample input values across the depth, height and width
+       *     dimensions in dilated pooling.
+       *     Defaults to `[1, 1, 1]`. If `dilations` is a single number,
+       *     then `dilationDepth == dilationHeight == dilationWidth`.
+       *     If it is greater than 1, then all values of `strides` must be 1.
+       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
+       *     used in the forward prop of the op.
+       * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. The
+       *     rounding mode used when computing output dimensions if pad is a
+       *     number. If none is provided, it will not round and error if the output
+       *     is of fractional size.
+       */
+      function avgPool3dBackprop_(
+        dy,
+        input,
+        filterSize,
+        strides,
+        dilations = [1, 1, 1],
+        pad,
+        dimRoundingMode
+      ) {
+        const $dy = Object(tensor_util_env["a" /* convertToTensor */])(
+          dy,
+          "dy",
+          "avgPool3dBackprop"
+        );
+        const $input = Object(tensor_util_env["a" /* convertToTensor */])(
+          input,
+          "input",
+          "avgPool3dBackprop"
+        );
+        let dy5D = $dy;
+        let input5D = $input;
+        let reshapedTo5D = false;
+        if ($input.rank === 4) {
+          reshapedTo5D = true;
+          dy5D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]);
+          input5D = reshape($input, [
+            1,
+            $input.shape[0],
+            $input.shape[1],
+            $input.shape[2],
+            $input.shape[3],
+          ]);
+        }
+        util["assert"](
+          dy5D.rank === 5,
+          () => `Error in avgPool3dBackprop: dy must be rank 5 but got rank ` + `${dy5D.rank}.`
+        );
+        util["assert"](
+          input5D.rank === 5,
+          () =>
+            `Error in avgPool3dBackprop: input must be rank 5 but got rank ` + `${input5D.rank}.`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in avgPool3dBackprop: Either strides or dilations " +
+            `must be 1. Got strides ${strides} and dilations '${dilations}'`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in maxPool3dBackprop: pad must be an integer when ` +
+              `using, dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend) => {
+          const convInfo = computePool3DInfo(
+            input5D.shape,
+            filterSize,
+            strides,
+            dilations,
+            pad,
+            dimRoundingMode
+          );
+          return backend.avgPool3dBackprop(dy5D, input5D, convInfo);
+        };
+        const inputs = { dy: dy5D, input: input5D };
+        const attrs = { filterSize, strides, dilations, pad, dimRoundingMode };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["f" /* AvgPool3DBackprop */],
+          attrs
+        );
+        if (reshapedTo5D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);
+        }
+        return res;
+      }
+      const avgPool3dBackprop = Object(operation["a" /* op */])({ avgPool3dBackprop_ });
+      //# sourceMappingURL=avg_pool_3d_backprop.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/AvgPool3D_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const avgPool3DGradConfig = {
+        kernelName: kernel_names["e" /* AvgPool3D */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved, attrs) => {
+          const [x] = saved;
+          const { filterSize, strides, dilations, pad, dimRoundingMode } = attrs;
+          const $dilations = dilations == null ? [1, 1, 1] : dilations;
+          return {
+            x: () =>
+              avgPool3dBackprop(dy, x, filterSize, strides, $dilations, pad, dimRoundingMode),
+          };
+        },
+      };
+      //# sourceMappingURL=AvgPool3D_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_backprop.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the backprop of an 2D avg pool.
+       *
+       * @param dy The dy error, of rank 4 or rank 3 of shape
+       *     [batchSize, height, width, channels]. If rank 3, batch of 1 is
+       * assumed.
+       * @param input The input image, of rank 4 or rank 3 of shape
+       *     [batchSize, height, width, channels]. If rank 3, batch of 1 is
+       * assumed.
+       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
+       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
+       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
+       *     `strides` is a single number, then `strideHeight == strideWidth`.
+       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
+       *     used in the forward prop of the op.
+       */
+      function avgPoolBackprop_(dy, input, filterSize, strides, pad) {
+        const $dy = Object(tensor_util_env["a" /* convertToTensor */])(dy, "dy", "avgPoolBackprop");
+        const $input = Object(tensor_util_env["a" /* convertToTensor */])(
+          input,
+          "input",
+          "avgPoolBackprop"
+        );
+        util["assert"](
+          $input.rank === $dy.rank,
+          () => `Rank of input (${$input.rank}) does not match rank of dy (${$dy.rank})`
+        );
+        let input4D = $input;
+        let dy4D = $dy;
+        let reshapedTo4D = false;
+        if ($input.rank === 3) {
+          reshapedTo4D = true;
+          input4D = reshape($input, [1, $input.shape[0], $input.shape[1], $input.shape[2]]);
+          dy4D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2]]);
+        }
+        util["assert"](
+          dy4D.rank === 4,
+          () => `Error in avgPoolBackprop: dy must be rank 4 but got rank ` + `${dy4D.rank}.`
+        );
+        util["assert"](
+          input4D.rank === 4,
+          () => `Error in avgPoolBackprop: input must be rank 4 but got rank ` + `${input4D.rank}.`
+        );
+        const forward = (backend) => {
+          const convInfo = computePool2DInfo(
+            input4D.shape,
+            filterSize,
+            strides,
+            1 /* dilations */,
+            pad
+          );
+          return backend.avgPoolBackprop(dy4D, input4D, convInfo);
+        };
+        const inputs = { dy: dy4D, input: input4D };
+        const attrs = { filterSize, strides, pad };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null,
+          kernel_names["g" /* AvgPoolBackprop */],
+          attrs
+        );
+        if (reshapedTo4D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
+        }
+        return res;
+      }
+      const avgPoolBackprop = Object(operation["a" /* op */])({ avgPoolBackprop_ });
+      //# sourceMappingURL=avg_pool_backprop.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/AvgPool_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const avgPoolGradConfig = {
+        kernelName: kernel_names["d" /* AvgPool */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved, attrs) => {
+          const [x] = saved;
+          const { filterSize, strides, pad } = attrs;
+          return {
+            x: () => avgPoolBackprop(dy, x, filterSize, strides, pad),
+          };
+        },
+      };
+      //# sourceMappingURL=AvgPool_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/mat_mul.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the dot product of two matrices, A * B. These must be matrices.
+       *
+       * ```js
+       * const a = tf.tensor2d([1, 2], [1, 2]);
+       * const b = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * a.matMul(b).print();  // or tf.matMul(a, b)
+       * ```
+       * @param a First matrix in dot product operation.
+       * @param b Second matrix in dot product operation.
+       * @param transposeA If true, `a` is transposed before multiplication.
+       * @param transposeB If true, `b` is transposed before multiplication.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
+      function matMul_(a, b, transposeA = false, transposeB = false) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "matMul");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "matMul");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        util["assert"](
+          $a.rank >= 2 && $b.rank >= 2 && $a.rank === $b.rank,
+          () =>
+            `Error in matMul: inputs must have the same rank of at least 2, ` +
+            `got ranks ${$a.rank} and ${$b.rank}.`
+        );
+        const innerShapeA = transposeA ? $a.shape[$a.rank - 2] : $a.shape[$a.rank - 1];
+        const innerShapeB = transposeB ? $b.shape[$b.rank - 1] : $b.shape[$b.rank - 2];
+        const outerShapeA = transposeA ? $a.shape[$a.rank - 1] : $a.shape[$a.rank - 2];
+        const outerShapeB = transposeB ? $b.shape[$b.rank - 2] : $b.shape[$b.rank - 1];
+        const outerDimsA = $a.shape.slice(0, -2);
+        const outerDimsB = $b.shape.slice(0, -2);
+        const batchDimA = util["sizeFromShape"](outerDimsA);
+        const batchDimB = util["sizeFromShape"](outerDimsB);
+        util["assert"](
+          util["arraysEqual"](outerDimsA, outerDimsB),
+          () =>
+            `Error in matMul: outer dimensions (${outerDimsA}) and (` +
+            `${outerDimsB}) of Tensors with shapes ${$a.shape} and ` +
+            `${$b.shape} must match.`
+        );
+        util["assert"](
+          innerShapeA === innerShapeB,
+          () =>
+            `Error in matMul: inner shapes (${innerShapeA}) and (` +
+            `${innerShapeB}) of Tensors with shapes ${$a.shape} and ` +
+            `${$b.shape} and transposeA=${transposeA}` +
+            ` and transposeB=${transposeB} must match.`
+        );
+        const outShape = $a.shape.slice(0, -2).concat([outerShapeA, outerShapeB]);
+        const a3D = transposeA
+          ? reshape($a, [batchDimA, innerShapeA, outerShapeA])
+          : reshape($a, [batchDimA, outerShapeA, innerShapeA]);
+        const b3D = transposeB
+          ? reshape($b, [batchDimB, outerShapeB, innerShapeB])
+          : reshape($b, [batchDimB, innerShapeB, outerShapeB]);
+        const forward = (backend, save) => {
+          save([a3D, b3D]);
+          return backend.batchMatMul(a3D, b3D, transposeA, transposeB);
+        };
+        const inputs = { a: a3D, b: b3D };
+        const attrs = { transposeA, transposeB };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["h" /* BatchMatMul */],
+          attrs
+        );
+        return reshape(res, outShape);
+      }
+      const matMul = Object(operation["a" /* op */])({ matMul_ });
+      //# sourceMappingURL=mat_mul.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/BatchMatMul_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const batchMatMulGradConfig = {
+        kernelName: kernel_names["h" /* BatchMatMul */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved, attrs) => {
+          const [a, b] = saved;
+          const { transposeA, transposeB } = attrs;
+          if (!transposeA && !transposeB) {
+            return {
+              a: () => matMul(dy, b, false, true),
+              b: () => matMul(a, dy, true, false),
+            };
+          } else if (!transposeA && transposeB) {
+            return {
+              a: () => matMul(dy, b, false, false),
+              b: () => matMul(dy, a, true, false),
+            };
+          } else if (transposeA && !transposeB) {
+            return {
+              a: () => matMul(b, dy, false, true),
+              b: () => matMul(a, dy, false, false),
+            };
+          } else {
+            return {
+              a: () => matMul(b, dy, true, true),
+              b: () => matMul(dy, a, true, true),
+            };
+          }
+        },
+      };
+      //# sourceMappingURL=BatchMatMul_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/space_to_batch_nd.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * This operation divides "spatial" dimensions `[1, ..., M]` of the input into
+       * a grid of blocks of shape `blockShape`, and interleaves these blocks with
+       * the "batch" dimension (0) such that in the output, the spatial
+       * dimensions `[1, ..., M]` correspond to the position within the grid,
+       * and the batch dimension combines both the position within a spatial block
+       * and the original batch position. Prior to division into blocks,
+       * the spatial dimensions of the input are optionally zero padded
+       * according to `paddings`. See below for a precise description.
+       *
+       * ```js
+       * const x = tf.tensor4d([1, 2, 3, 4], [1, 2, 2, 1]);
+       * const blockShape = [2, 2];
+       * const paddings = [[0, 0], [0, 0]];
+       *
+       * x.spaceToBatchND(blockShape, paddings).print();
+       * ```
+       *
+       * @param x A `tf.Tensor`. N-D with `x.shape` = `[batch] + spatialShape +
+       * remainingShape`, where spatialShape has `M` dimensions.
+       * @param blockShape A 1-D array. Must have shape `[M]`, all values must
+       * be >= 1.
+       * @param paddings A 2-D array. Must have shape `[M, 2]`, all values must be >=
+       *     0. `paddings[i] = [padStart, padEnd]` specifies the amount to zero-pad
+       * from input dimension `i + 1`, which corresponds to spatial dimension `i`. It
+       * is required that
+       * `(inputShape[i + 1] + padStart + padEnd) % blockShape[i] === 0`
+       *
+       * This operation is equivalent to the following steps:
+       *
+       * 1. Zero-pad the start and end of dimensions `[1, ..., M]` of the input
+       * according to `paddings` to produce `padded` of shape paddedShape.
+       *
+       * 2. Reshape `padded` to `reshapedPadded` of shape:
+       * `[batch] + [paddedShape[1] / blockShape[0], blockShape[0], ...,
+       * paddedShape[M] / blockShape[M-1], blockShape[M-1]] + remainingShape`
+       *
+       * 3. Permute dimensions of `reshapedPadded` to produce `permutedReshapedPadded`
+       * of shape: `blockShape + [batch] + [paddedShape[1] / blockShape[0], ...,
+       * paddedShape[M] / blockShape[M-1]] + remainingShape`
+       *
+       * 4. Reshape `permutedReshapedPadded` to flatten `blockShape` into the
+       * batch dimension, producing an output tensor of shape:
+       * `[batch * prod(blockShape)] + [paddedShape[1] / blockShape[0], ...,
+       * paddedShape[M] / blockShape[M-1]] + remainingShape`
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function spaceToBatchND_(x, blockShape, paddings) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "spaceToBatchND");
+        util["assert"](
+          $x.rank >= 1 + blockShape.length,
+          () => `input rank ${$x.rank} should be > than [blockShape] ${blockShape.length}`
+        );
+        util["assert"](
+          paddings.length === blockShape.length,
+          () =>
+            `paddings.shape[0] ${paddings.length} must be equal to [blockShape] ${blockShape.length}`
+        );
+        util["assert"](
+          $x.shape.reduce((a, b, i) => {
+            if (i > 0 && i <= blockShape.length) {
+              return a && (b + paddings[i - 1][0] + paddings[i - 1][1]) % blockShape[i - 1] === 0;
+            }
+            return a;
+          }, true),
+          () =>
+            `input spatial dimensions ${$x.shape.slice(
+              1
+            )} with paddings ${paddings.toString()} must be divisible by blockShapes ${blockShape.toString()}`
+        );
+        const forward = (backend) => backend.spaceToBatchND($x, blockShape, paddings);
+        const inputs = { x: $x };
+        const attrs = { blockShape, paddings };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["mb" /* SpaceToBatchND */],
+          attrs
+        );
+      }
+      const spaceToBatchND = Object(operation["a" /* op */])({ spaceToBatchND_ });
+      //# sourceMappingURL=space_to_batch_nd.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/BatchToSpaceND_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const batchToSpaceNDGradConfig = {
+        kernelName: kernel_names["i" /* BatchToSpaceND */],
+        gradFunc: (dy, saved, attrs) => {
+          const { blockShape, crops } = attrs;
+          return { x: () => spaceToBatchND(dy, blockShape, crops) };
+        },
+      };
+      //# sourceMappingURL=BatchToSpaceND_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/BroadcastTo_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const broadcastToGradConfig = {
+        kernelName: kernel_names["j" /* BroadcastTo */],
+        gradFunc: (dy, saved, attrs) => {
+          const broadCastToAttrs = attrs;
+          const inputShape = broadCastToAttrs.inputShape;
+          const outputShape = broadCastToAttrs.shape;
+          const reps = Array.from(outputShape);
+          for (let i = inputShape.length - 1; i >= 0; i--) {
+            if (inputShape[i] === outputShape[i]) {
+              reps[i] = 1;
+            } else if (inputShape[i] !== 1) {
+              throw new Error(
+                `broadcastTo(): [${inputShape}] cannot be broadcast to [${outputShape}].`
+              );
+            }
+          }
+          const axes = [];
+          for (let i = 0; i < reps.length; i++) {
+            if (reps[i] > 1) {
+              axes.push(i);
+            }
+          }
+          return { x: () => sum(dy, axes, true /* keepDims */) };
+        },
+      };
+      //# sourceMappingURL=BroadcastTo_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/split.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Splits a `tf.Tensor` into sub tensors.
+       *
+       * If `numOrSizeSplits` is a number, splits `x` along dimension `axis`
+       * into `numOrSizeSplits` smaller tensors.
+       * Requires that `numOrSizeSplits` evenly divides `x.shape[axis]`.
+       *
+       * If `numOrSizeSplits` is a number array, splits `x` into
+       * `numOrSizeSplits.length` pieces. The shape of the `i`-th piece has the
+       * same size as `x` except along dimension `axis` where the size is
+       * `numOrSizeSplits[i]`.
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);
+       * const [a, b] = tf.split(x, 2, 1);
+       * a.print();
+       * b.print();
+       *
+       * const [c, d, e] = tf.split(x, [1, 2, 1], 1);
+       * c.print();
+       * d.print();
+       * e.print();
+       * ```
+       *
+       * @param x The input tensor to split.
+       * @param numOrSizeSplits Either an integer indicating the number of
+       * splits along the axis or an array of integers containing the sizes of
+       * each output tensor along the axis. If a number then it must evenly divide
+       * `x.shape[axis]`; otherwise the sum of sizes must match `x.shape[axis]`.
+       * @param axis The dimension along which to split. Defaults to 0 (the first
+       * dim).
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      function split_(x, numOrSizeSplits, axis = 0) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "split");
+        const $axis = Object(util["parseAxisParam"])(axis, $x.shape)[0];
+        let splitSizes;
+        if (typeof numOrSizeSplits === "number") {
+          Object(util["assert"])(
+            $x.shape[$axis] % numOrSizeSplits === 0,
+            () => "Number of splits must evenly divide the axis."
+          );
+          splitSizes = new Array(numOrSizeSplits).fill($x.shape[$axis] / numOrSizeSplits);
+        } else {
+          Object(util["assert"])(
+            $x.shape[$axis] === numOrSizeSplits.reduce((a, b) => a + b),
+            () => "The sum of sizes must match the size of the axis dimension."
+          );
+          splitSizes = numOrSizeSplits;
+        }
+        const forward = (backend, _) => {
+          return backend.split($x, splitSizes, $axis);
+        };
+        const inputs = { x: $x };
+        const attr = { numOrSizeSplits, axis };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["nb" /* SplitV */],
+          attr
+        );
+      }
+      const split = Object(operation["a" /* op */])({ split_ });
+      //# sourceMappingURL=split.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Concat_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const concatGradConfig = {
+        kernelName: kernel_names["l" /* Concat */],
+        saveAllInputs: true,
+        gradFunc: (dy, saved, attrs) => {
+          const shapes = saved.map((t) => t.shape);
+          const { axis } = attrs;
+          const $axis = Object(util["parseAxisParam"])(axis, saved[0].shape)[0];
+          const sizeSplits = shapes.map((s) => s[$axis]);
+          const derTensors = split(dy, sizeSplits, $axis);
+          return derTensors.map((t) => () => t);
+        },
+      };
+      //# sourceMappingURL=Concat_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_backprop_filter.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the derivative of the filter of a 2D convolution.
+       *
+       * @param x The input tensor, of rank 4 or rank 3 of shape
+       *     [batch, height, width, inChannels]. If rank 3, batch of 1 is assumed.
+       * @param dy The dy image, of rank 4 or rank 3, of shape
+       *     [batch, height, width, outDepth]. If rank 3, batch of 1 is assumed.
+       * @param filterShape The shape of the filter, length 4,
+       *     [filterHeight, filterWidth, inDepth, outDepth].
+       * @param strides The strides of the convolution: [strideHeight,
+       * strideWidth].
+       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
+       *     used in the forward prop of the op.
+       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
+       *     "NHWC". Specify the data format of the input and output data. With the
+       *     default format "NHWC", the data is stored in the order of: [batch,
+       *     height, width, channels].
+       * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. The
+       *     rounding mode used when computing output dimensions if pad is a
+       *     number. If none is provided, it will not round and error if the output
+       *     is of fractional size.
+       */
+      function conv2DBackpropFilter_(
+        x,
+        dy,
+        filterShape,
+        strides,
+        pad,
+        dataFormat = "NHWC",
+        dimRoundingMode
+      ) {
+        let x4D = x;
+        if (x.rank === 3) {
+          x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);
+        }
+        let dy4D = dy;
+        if (dy4D.rank === 3) {
+          dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
+        }
+        util["assert"](
+          x4D.rank === 4,
+          () => `Error in conv2dDerFilter: input must be rank 4, but got shape ` + `${x4D.shape}.`
+        );
+        util["assert"](
+          dy4D.rank === 4,
+          () => `Error in conv2dDerFilter: dy must be rank 4, but got shape ` + `${dy4D.shape}.`
+        );
+        util["assert"](
+          filterShape.length === 4,
+          () =>
+            `Error in conv2dDerFilter: filterShape must be length 4, but got ` + `${filterShape}.`
+        );
+        const inDepth = dataFormat === "NHWC" ? x4D.shape[3] : x4D.shape[1];
+        const outDepth = dataFormat === "NHWC" ? dy4D.shape[3] : dy4D.shape[1];
+        util["assert"](
+          inDepth === filterShape[2],
+          () =>
+            `Error in conv2dDerFilter: depth of input ${inDepth}) must ` +
+            `match input depth in filter (${filterShape[2]}.`
+        );
+        util["assert"](
+          outDepth === filterShape[3],
+          () =>
+            `Error in conv2dDerFilter: depth of dy (${outDepth}) must ` +
+            `match output depth for filter (${filterShape[3]}).`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in conv2dDerFilter: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend) => {
+          const dilations = 1;
+          const $dataFormat = convertConv2DDataFormat(dataFormat);
+          const convInfo = computeConv2DInfo(
+            x4D.shape,
+            filterShape,
+            strides,
+            dilations,
+            pad,
+            dimRoundingMode,
+            false,
+            $dataFormat
+          );
+          return backend.conv2dDerFilter(x4D, dy4D, convInfo);
+        };
+        const inputs = { x: x4D, dy: dy4D };
+        const attrs = { strides, pad, dataFormat, dimRoundingMode };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null,
+          kernel_names["n" /* Conv2DBackpropFilter */],
+          attrs
+        );
+      }
+      const conv2DBackpropFilter = Object(operation["a" /* op */])({ conv2DBackpropFilter_ });
+      //# sourceMappingURL=conv2d_backprop_filter.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_backprop_input.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the derivative of the input of a 2D convolution.
+       *
+       * @param xShape The shape of the input: [batch, height, width, inDepth].
+       * If length of 3, batch of 1 is assumed.
+       * @param dy The derivative of the output, of rank 4 or rank 3 of shape
+       *   `[batch, outHeight, outWidth, outDepth]`. If rank 3, batch of 1 is
+       * assumed.
+       * @param filter The filter, rank 4, of shape
+       *     `[filterHeight, filterWidth, inDepth, outDepth]`.
+       * @param strides The strides of the convolution: `[strideHeight,
+       * strideWidth]`.
+       * @param pad The type of padding algorithm used:
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
+       *     "NHWC". Specify the data format of the input and output data. With the
+       *     default format "NHWC", the data is stored in the order of: [batch,
+       *     height, width, channels].
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       */
+      function conv2DBackpropInput_(
+        xShape,
+        dy,
+        filter,
+        strides,
+        pad,
+        dataFormat = "NHWC",
+        dimRoundingMode
+      ) {
+        util["assert"](
+          xShape.length === dy.rank,
+          () => `Length of inShape ` + `(${xShape.length}) and rank of dy (${dy.rank}) must match`
+        );
+        let xShape4D = xShape;
+        let dy4D = dy;
+        let reshapedTo4D = false;
+        if (dy.rank === 3) {
+          reshapedTo4D = true;
+          dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
+          xShape4D = [1, xShape[0], xShape[1], xShape[2]];
+        }
+        util["assert"](
+          xShape4D.length === 4,
+          () =>
+            `Error in conv2dDerInput: inShape must be length 4, but got length ` +
+            `${xShape4D.length}.`
+        );
+        util["assert"](
+          dy4D.rank === 4,
+          () => `Error in conv2dDerInput: dy must be rank 4, but got ` + `rank ${dy4D.rank}`
+        );
+        util["assert"](
+          filter.rank === 4,
+          () => `Error in conv2dDerInput: filter must be rank 4, but got ` + `rank ${filter.rank}`
+        );
+        const inDepth = dataFormat === "NHWC" ? xShape4D[3] : xShape4D[1];
+        const outDepth = dataFormat === "NHWC" ? dy4D.shape[3] : dy4D.shape[1];
+        util["assert"](
+          inDepth === filter.shape[2],
+          () =>
+            `Error in conv2dDerInput: depth of input (${inDepth}) must ` +
+            `match input depth for filter ${filter.shape[2]}.`
+        );
+        util["assert"](
+          outDepth === filter.shape[3],
+          () =>
+            `Error in conv2dDerInput: depth of output (${outDepth}) must ` +
+            `match output depth for filter ${filter.shape[3]}.`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in conv2dDerInput: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend, save) => {
+          const dilations = 1;
+          const $dataFormat = convertConv2DDataFormat(dataFormat);
+          const convInfo = computeConv2DInfo(
+            xShape4D,
+            filter.shape,
+            strides,
+            dilations,
+            pad,
+            dimRoundingMode,
+            false,
+            $dataFormat
+          );
+          const res = backend.conv2dDerInput(dy4D, filter, convInfo);
+          save([dy4D, filter]);
+          return res;
+        };
+        const inputs = { dy: dy4D, filter };
+        const attrs = { strides, pad, dataFormat, dimRoundingMode };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["o" /* Conv2DBackpropInput */],
+          attrs
+        );
+        if (reshapedTo4D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
+        }
+        return res;
+      }
+      const conv2DBackpropInput = Object(operation["a" /* op */])({ conv2DBackpropInput_ });
+      //# sourceMappingURL=conv2d_backprop_input.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Conv2D_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const conv2DGradConfig = {
+        kernelName: kernel_names["m" /* Conv2D */],
+        inputsToSave: ["x", "filter"],
+        gradFunc: (dy, saved, attrs) => {
+          const [x4D, $filter] = saved;
+          const { dilations, strides, pad, dataFormat } = attrs;
+          util["assert"](
+            tupleValuesAreOne(dilations),
+            () =>
+              "Error in gradient of conv2D: dilation rates greater than 1 " +
+              `are not yet supported in gradients. Got dilations '${dilations}'`
+          );
+          return {
+            x: () => conv2DBackpropInput(x4D.shape, dy, $filter, strides, pad, dataFormat),
+            filter: () => conv2DBackpropFilter(x4D, dy, $filter.shape, strides, pad, dataFormat),
+          };
+        },
+      };
+      //# sourceMappingURL=Conv2D_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv2d.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes a 2D convolution over the input x.
+       *
+       * @param x The input tensor, of rank 4 or rank 3, of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
+       * assumed.
+       * @param filter The filter, rank 4, of shape
+       *     `[filterHeight, filterWidth, inDepth, outDepth]`.
+       * @param strides The strides of the convolution: `[strideHeight,
+       * strideWidth]`.
+       * @param pad The type of padding algorithm.
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *   - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
+       *     "NHWC". Specify the data format of the input and output data. With the
+       *     default format "NHWC", the data is stored in the order of: [batch,
+       *     height, width, channels].
+       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
+       *     in which we sample input values across the height and width dimensions
+       *     in atrous convolution. Defaults to `[1, 1]`. If `dilations` is a single
+       *     number, then `dilationHeight == dilationWidth`. If it is greater than
+       *     1, then all values of `strides` must be 1.
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function conv2d_(
+        x,
+        filter,
+        strides,
+        pad,
+        dataFormat = "NHWC",
+        dilations = [1, 1],
+        dimRoundingMode
+      ) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv2d");
+        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
+          filter,
+          "filter",
+          "conv2d"
+        );
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
+        }
+        util["assert"](
+          x4D.rank === 4,
+          () => `Error in conv2d: input must be rank 4, but got rank ${x4D.rank}.`
+        );
+        util["assert"](
+          $filter.rank === 4,
+          () => `Error in conv2d: filter must be rank 4, but got rank ` + `${$filter.rank}.`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in conv2d: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const inDepth = dataFormat === "NHWC" ? x4D.shape[3] : x4D.shape[1];
+        util["assert"](
+          inDepth === $filter.shape[2],
+          () =>
+            `Error in conv2d: depth of input (${inDepth}) must match ` +
+            `input depth for filter ${$filter.shape[2]}.`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in conv2D: Either strides or dilations must be 1. " +
+            `Got strides ${strides} and dilations '${dilations}'`
+        );
+        const forward = (backend, save) => {
+          const $dataFormat = convertConv2DDataFormat(dataFormat);
+          const convInfo = computeConv2DInfo(
+            x4D.shape,
+            $filter.shape,
+            strides,
+            dilations,
+            pad,
+            dimRoundingMode,
+            false,
+            $dataFormat
+          );
+          const res = backend.conv2d(x4D, $filter, convInfo);
+          save([x4D, $filter]);
+          return res;
+        };
+        const inputs = { x: x4D, filter: $filter };
+        const attrs = { strides, pad, dataFormat, dilations, dimRoundingMode };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["m" /* Conv2D */],
+          attrs
+        );
+        if (reshapedTo4D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
+        }
+        return res;
+      }
+      const conv2d = Object(operation["a" /* op */])({ conv2d_ });
+      //# sourceMappingURL=conv2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Conv2DBackpropInput_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const conv2DBackpropInputGradConfig = {
+        kernelName: kernel_names["o" /* Conv2DBackpropInput */],
+        inputsToSave: ["dy", "filter"],
+        gradFunc: (ddx, saved, attrs) => {
+          const [dy, filter] = saved;
+          const { strides, pad, dataFormat, dimRoundingMode } = attrs;
+          return {
+            dy: () =>
+              conv2d(ddx, filter, strides, pad, dataFormat, 1 /* dilations */, dimRoundingMode),
+            filter: () =>
+              conv2DBackpropFilter(
+                ddx,
+                dy,
+                filter.shape,
+                strides,
+                pad,
+                dataFormat,
+                dimRoundingMode
+              ),
+          };
+        },
+      };
+      //# sourceMappingURL=Conv2DBackpropInput_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_backprop_filter.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the derivative of the filter of a 3D convolution.
+       *
+       * @param x The input tensor, of rank 5 or rank 4 of shape
+       *     [batch, depth, height, width, inChannels]. If rank 4, batch of 1 is
+       *     assumed.
+       * @param dy The dy image, of rank 5 or rank 4, of shape
+       *     [batch, depth, height, width, outDepth]. If rank 4, batch of 1 is
+       *     assumed.
+       * @param filterShape The shape of the filter, length 5,
+       *     [filterDepth, filterHeight, filterWidth, inDepth, outDepth].
+       * @param strides The strides of the convolution: [strideDepth, strideHeight,
+       * strideWidth].
+       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
+       *     used in the forward prop of the op.
+       */
+      function conv3DBackpropFilter_(x, dy, filterShape, strides, pad) {
+        let x5D = x;
+        if (x.rank === 4) {
+          x5D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2], x.shape[3]]);
+        }
+        let dy5D = dy;
+        if (dy5D.rank === 4) {
+          dy5D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2], dy.shape[3]]);
+        }
+        util["assert"](
+          x5D.rank === 5,
+          () => `Error in conv3dDerFilter: input must be rank 5, but got shape ` + `${x5D.shape}.`
+        );
+        util["assert"](
+          dy5D.rank === 5,
+          () => `Error in conv3dDerFilter: dy must be rank 5, but got shape ` + `${dy5D.shape}.`
+        );
+        util["assert"](
+          filterShape.length === 5,
+          () =>
+            `Error in conv3dDerFilter: filterShape must be length 5, but got ` + `${filterShape}.`
+        );
+        util["assert"](
+          x5D.shape[4] === filterShape[3],
+          () =>
+            `Error in conv3dDerFilter: depth of input ${x5D.shape[4]}) must ` +
+            `match input depth in filter (${filterShape[3]}.`
+        );
+        util["assert"](
+          dy5D.shape[4] === filterShape[4],
+          () =>
+            `Error in conv3dDerFilter: depth of dy (${dy5D.shape[4]}) must ` +
+            `match output depth for filter (${filterShape[4]}).`
+        );
+        const forward = (backend) => {
+          const dilations = 1;
+          const convInfo = computeConv3DInfo(x5D.shape, filterShape, strides, dilations, pad);
+          return backend.conv3dDerFilter(x5D, dy5D, convInfo);
+        };
+        const inputs = { x: x5D, y: dy5D };
+        const attrs = { strides, pad };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null,
+          kernel_names["q" /* Conv3DBackpropFilterV2 */],
+          attrs
+        );
+      }
+      const conv3DBackpropFilter = Object(operation["a" /* op */])({ conv3DBackpropFilter_ });
+      //# sourceMappingURL=conv3d_backprop_filter.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_backprop_input.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the derivative of the input of a 3D convolution.
+       *
+       * @param xShape The shape of the input: [batch, depth, height, width,
+       * in_channels]. If length of 4, batch of 1 is assumed.
+       * @param dy The derivative of the output, of rank 5 or rank 4 of shape
+       *   `[batch, outDepth, outHeight, outWidth, in_channels]`.
+       * If rank 4, batch of 1 is assumed.
+       * @param filter The filter, rank 5, of shape
+       *     `[filterDepth, filterHeight, filterWidth, inDepth, outDepth]`.
+       * @param strides The strides of the convolution: `[strideDepth, strideHeight,
+       * strideWidth]`.
+       * @param pad The type of padding algorithm used:
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       */
+      function conv3DBackpropInput_(xShape, dy, filter, strides, pad) {
+        util["assert"](
+          xShape.length === dy.rank,
+          () => `Length of inShape ` + `(${xShape.length}) and rank of dy (${dy.rank}) must match`
+        );
+        let xShape5D = xShape;
+        let dy5D = dy;
+        let reshapedTo5D = false;
+        if (dy.rank === 4) {
+          reshapedTo5D = true;
+          dy5D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2], dy.shape[3]]);
+          xShape5D = [1, xShape[0], xShape[1], xShape[2], xShape[3]];
+        }
+        const inDepth = xShape5D[4];
+        const outDepth = dy5D.shape[4];
+        util["assert"](
+          xShape5D.length === 5,
+          () =>
+            `Error in conv3dDerInput: inShape must be length 5, but got length ` +
+            `${xShape5D.length}.`
+        );
+        util["assert"](
+          dy5D.rank === 5,
+          () => `Error in conv3dDerInput: dy must be rank 5, but got ` + `rank ${dy5D.rank}`
+        );
+        util["assert"](
+          filter.rank === 5,
+          () => `Error in conv3dDerInput: filter must be rank 5, but got ` + `rank ${filter.rank}`
+        );
+        util["assert"](
+          inDepth === filter.shape[3],
+          () =>
+            `Error in conv3dDerInput: depth of input (${inDepth}) must ` +
+            `match input depth for filter ${filter.shape[3]}.`
+        );
+        util["assert"](
+          outDepth === filter.shape[4],
+          () =>
+            `Error in conv3dDerInput: depth of output (${outDepth}) must ` +
+            `match output depth for filter ${filter.shape[4]}.`
+        );
+        const forward = (backend) => {
+          const dilations = 1;
+          const convInfo = computeConv3DInfo(xShape5D, filter.shape, strides, dilations, pad);
+          return backend.conv3dDerInput(dy5D, filter, convInfo);
+        };
+        const inputs = { dy: dy5D };
+        const attrs = { pad };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null,
+          kernel_names["r" /* Conv3DBackpropInputV2 */],
+          attrs
+        );
+        if (reshapedTo5D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);
+        }
+        return res;
+      }
+      const conv3DBackpropInput = Object(operation["a" /* op */])({ conv3DBackpropInput_ });
+      //# sourceMappingURL=conv3d_backprop_input.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Conv3D_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const conv3DGradConfig = {
+        kernelName: kernel_names["p" /* Conv3D */],
+        inputsToSave: ["x", "filter"],
+        gradFunc: (dy, saved, attrs) => {
+          const { dilations, strides, pad } = attrs;
+          util["assert"](
+            tupleValuesAreOne(dilations),
+            () =>
+              "Error in gradient of conv3D: dilation rates greater than 1 are " +
+              `not yet supported in gradients. Got dilations '${dilations}'`
+          );
+          const [x5D, $filter] = saved;
+          return {
+            x: () => conv3DBackpropInput(x5D.shape, dy, $filter, strides, pad),
+            filter: () => conv3DBackpropFilter(x5D, dy, $filter.shape, strides, pad),
+          };
+        },
+      };
+      //# sourceMappingURL=Conv3D_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/transpose.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Transposes the `tf.Tensor`. Permutes the dimensions according to `perm`.
+       *
+       * The returned `tf.Tensor`'s dimension `i` will correspond to the input
+       * dimension `perm[i]`. If `perm` is not given, it is set to `[n-1...0]`,
+       * where `n` is the rank of the input `tf.Tensor`. Hence by default, this
+       * operation performs a regular matrix transpose on 2-D input `tf.Tensor`s.
+       *
+       * ```js
+       * const a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
+       *
+       * a.transpose().print();  // or tf.transpose(a)
+       * ```
+       *
+       * @param x The tensor to transpose.
+       * @param perm The permutation of the dimensions of a.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
+      function transpose_(x, perm) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "transpose");
+        if (perm == null) {
+          perm = $x.shape.map((s, i) => i).reverse();
+        }
+        util["assert"](
+          $x.rank === perm.length,
+          () =>
+            `Error in transpose: rank of input ${$x.rank} ` + `must match length of perm ${perm}.`
+        );
+        perm.forEach((axis) => {
+          util["assert"](
+            axis >= 0 && axis < $x.rank,
+            () => `All entries in 'perm' must be between 0 and ${$x.rank - 1}` + ` but got ${perm}`
+          );
+        });
+        if ($x.rank <= 1) {
+          return $x.clone();
+        }
+        const attrs = { perm };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.transpose($x, perm),
+          { x: $x },
+          null /* gradient */,
+          "Transpose",
+          attrs
+        );
+      }
+      const transpose = Object(operation["a" /* op */])({ transpose_ });
+      //# sourceMappingURL=transpose.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/cumsum.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the cumulative sum of a `tf.Tensor` along `axis`.
+       *
+       * ```js
+       * const x = tf.tensor([1, 2, 3, 4]);
+       * x.cumsum().print();
+       * ```
+       * ```js
+       * const x = tf.tensor([[1, 2], [3, 4]]);
+       * x.cumsum().print();
+       * ```
+       *
+       * @param x The input tensor to be summed.
+       * @param axis The axis along which to sum. Optional. Defaults to 0.
+       * @param exclusive Whether to perform exclusive cumulative sum. Optional.
+       *     Defaults to false. If set to true then the sum of each tensor entry
+       *     does not include its own value, but only the values previous to it
+       *     along the specified axis.
+       * @param reverse Whether to sum in the opposite direction. Optional.
+       *     Defaults to false.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Scan'} */
+      function cumsum_(x, axis = 0, exclusive = false, reverse = false) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "cumsum");
+        const forward = (backend, save) => {
+          const permutation = getAxesPermutation([axis], $x.rank);
+          let permutedX = $x;
+          if (permutation != null) {
+            permutedX = transpose($x, permutation);
+          }
+          const permutedAxis = getInnerMostAxes(1, $x.rank)[0];
+          let value = backend.cumsum(permutedX, permutedAxis, exclusive, reverse);
+          save([$x]);
+          if (permutation != null) {
+            value = transpose(value, permutation);
+          }
+          return value;
+        };
+        const inputs = { x: $x };
+        const attrs = { axis, exclusive, reverse };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["s" /* Cumsum */],
+          attrs
+        );
+      }
+      const cumsum = Object(operation["a" /* op */])({ cumsum_ });
+      //# sourceMappingURL=cumsum.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Cumsum_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const cumsumGradConfig = {
+        kernelName: kernel_names["s" /* Cumsum */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved, attrs) => {
+          const [x] = saved;
+          const { axis, exclusive, reverse } = attrs;
+          return {
+            x: () => {
+              const permutation = getAxesPermutation([axis], x.rank);
+              let out = cumsum(dy, axis, exclusive, !reverse);
+              if (permutation != null) {
+                out = transpose(out, permutation);
+              }
+              return out;
+            },
+          };
+        },
+      };
+      //# sourceMappingURL=Cumsum_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d_native_backprop_filter.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function depthwiseConv2dNativeBackpropFilter_(x, dy, filterShape, convInfo) {
+        let x4D = x;
+        if (x.rank === 3) {
+          x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);
+        }
+        let dy4D = dy;
+        if (dy4D.rank === 3) {
+          dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
+        }
+        const forward = (backend) => backend.depthwiseConv2DDerFilter(x4D, dy4D, convInfo);
+        const inputs = { x: x4D, dy: dy4D };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null,
+          kernel_names["v" /* DepthwiseConv2dNativeBackpropFilter */]
+        );
+      }
+      const depthwiseConv2dNativeBackpropFilter = Object(operation["a" /* op */])({
+        depthwiseConv2dNativeBackpropFilter_,
+      });
+      //# sourceMappingURL=depthwise_conv2d_native_backprop_filter.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d_native_backprop_input.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function depthwiseConv2dNativeBackpropInput_(xShape, dy, filter, convInfo) {
+        let dy4D = dy;
+        let reshapedTo4D = false;
+        if (dy.rank === 3) {
+          reshapedTo4D = true;
+          dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
+        }
+        const forward = (backend) => backend.depthwiseConv2DDerInput(dy4D, filter, convInfo);
+        const inputs = { dy: dy4D };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null,
+          kernel_names["w" /* DepthwiseConv2dNativeBackpropInput */]
+        );
+        if (reshapedTo4D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
+        }
+        return res;
+      }
+      const depthwiseConv2dNativeBackpropInput = Object(operation["a" /* op */])({
+        depthwiseConv2dNativeBackpropInput_,
+      });
+      //# sourceMappingURL=depthwise_conv2d_native_backprop_input.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/DepthwiseConv2dNative_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const depthwiseConv2dNativeGradConfig = {
+        kernelName: kernel_names["u" /* DepthwiseConv2dNative */],
+        inputsToSave: ["x", "filter"],
+        gradFunc: (dy, saved, attrs) => {
+          const { dilations, strides, pad, dimRoundingMode } = attrs;
+          const $dilations = dilations == null ? [1, 1] : dilations;
+          util["assert"](
+            tupleValuesAreOne($dilations),
+            () =>
+              "Error in gradient of depthwiseConv2dNative: dilation rates " +
+              `greater than 1 are not yet supported. Got dilations ` +
+              `'${$dilations}'`
+          );
+          const [x, filter] = saved;
+          util["assert"](
+            x.rank === 4,
+            () =>
+              `Error in gradient of depthwiseConv2dNative: input must be ` +
+              `rank 4, but got rank ${x.rank}.`
+          );
+          util["assert"](
+            filter.rank === 4,
+            () =>
+              `Error in gradient of depthwiseConv2dNative: filter must be ` +
+              `rank 4, but got rank ${filter.rank}.`
+          );
+          util["assert"](
+            x.shape[3] === filter.shape[2],
+            () =>
+              `Error in gradient of depthwiseConv2d: number of input ` +
+              `channels (${x.shape[3]}) must match the inChannels dimension ` +
+              `in filter ${filter.shape[2]}.`
+          );
+          util["assert"](
+            eitherStridesOrDilationsAreOne(strides, $dilations),
+            () =>
+              "Error in gradient of depthwiseConv2d: Either strides or " +
+              `dilations must be  1. Got strides ${strides} and dilations ` +
+              `'${$dilations}'.`
+          );
+          if (dimRoundingMode != null) {
+            util["assert"](
+              util["isInt"](pad),
+              () =>
+                `Error in depthwiseConv2d: pad must be an integer when using, ` +
+                `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+            );
+          }
+          const convInfo = computeConv2DInfo(
+            x.shape,
+            filter.shape,
+            strides,
+            $dilations,
+            pad,
+            dimRoundingMode,
+            true /* depthwise */
+          );
+          return {
+            x: () => depthwiseConv2dNativeBackpropInput(x.shape, dy, filter, convInfo),
+            filter: () => depthwiseConv2dNativeBackpropFilter(x, dy, filter.shape, convInfo),
+          };
+        },
+      };
+      //# sourceMappingURL=DepthwiseConv2dNative_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Div_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const divGradConfig = {
+        kernelName: kernel_names["y" /* Div */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
+          const derA = () => {
+            const res = div(dy, b.toFloat());
+            const reduceAxes = getReductionAxes(a.shape, outShape);
+            if (reduceAxes.length > 0) {
+              return sum(res, reduceAxes).reshape(a.shape);
+            }
+            return res;
+          };
+          const derB = () => {
+            let res = mul(dy, a.toFloat());
+            const reduceAxes = getReductionAxes(b.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = reshape(sum(res, reduceAxes), b.shape);
+            }
+            const tmp = square(b);
+            return neg(div(res, tmp.toFloat()));
+          };
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=Div_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Elu_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const eluGradConfig = {
+        kernelName: kernel_names["z" /* Elu */],
+        outputsToSave: [true],
+        gradFunc: (dy, saved) => {
+          const [y] = saved;
+          const backPropKernelFunc = (backend) => {
+            return backend.eluDer(dy, y);
+          };
+          const inputs = { dy, y };
+          return {
+            x: () =>
+              engine["a" /* ENGINE */].runKernelFunc(
+                backPropKernelFunc,
+                inputs,
+                null /* grad */,
+                kernel_names["A" /* EluGrad */]
+              ),
+          };
+        },
+      };
+      //# sourceMappingURL=Elu_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/FloorDiv_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const floorDivGradConfig = {
+        kernelName: kernel_names["D" /* FloorDiv */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
+          const derA = () => {
+            const res = dy.div(b.toFloat());
+            const reduceAxes = getReductionAxes(a.shape, outShape);
+            if (reduceAxes.length > 0) {
+              return res.sum(reduceAxes).reshape(a.shape);
+            }
+            return res;
+          };
+          const derB = () => {
+            let res = dy.mul(a.toFloat());
+            const reduceAxes = getReductionAxes(b.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = res.sum(reduceAxes).reshape(b.shape);
+            }
+            const tmp = b.square();
+            return res.div(tmp.toFloat()).neg();
+          };
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=FloorDiv_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/sub.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Subtracts two `tf.Tensor`s element-wise, A - B. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([10, 20, 30, 40]);
+       * const b = tf.tensor1d([1, 2, 3, 4]);
+       *
+       * a.sub(b).print();  // or tf.sub(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast subtract a with b.
+       * const a = tf.tensor1d([10, 20, 30, 40]);
+       * const b = tf.scalar(5);
+       *
+       * a.sub(b).print();  // or tf.sub(a, b)
+       * ```
+       * @param a The first `tf.Tensor` to subtract from.
+       * @param b The second `tf.Tensor` to be subtracted. Must have the same dtype as
+       * `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function sub_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "sub");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "sub");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        const forward = (backend, save) => {
+          const res = backend.subtract($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["qb" /* Sub */]
+        );
+      }
+      const sub = Object(operation["a" /* op */])({ sub_ });
+      //# sourceMappingURL=sub.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/tile.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Construct a tensor by repeating it the number of times given by reps.
+       *
+       * This operation creates a new tensor by replicating `input` `reps`
+       * times. The output tensor's i'th dimension has `input.shape[i] *
+       * reps[i]` elements, and the values of `input` are replicated
+       * `reps[i]` times along the i'th dimension. For example, tiling
+       * `[a, b, c, d]` by `[2]` produces `[a, b, c, d, a, b, c, d]`.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2]);
+       *
+       * a.tile([2]).print();    // or a.tile([2])
+       * ```
+       *
+       * ```js
+       * const a = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * a.tile([1, 2]).print();  // or a.tile([1, 2])
+       * ```
+       * @param x The tensor to tile.
+       * @param reps Determines the number of replications per dimension.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      function tile_(x, reps) {
+        const parseAs = null;
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "tile", parseAs);
+        util["assert"](
+          $x.rank === reps.length,
+          () =>
+            `Error in transpose: rank of input ${$x.rank} ` + `must match length of reps ${reps}.`
+        );
+        const forward = (backend, save) => {
+          const res = backend.tile($x, reps);
+          save([$x]);
+          return res;
+        };
+        const inputsToSave = [$x];
+        const inputs = { x: $x };
+        const attrs = { reps };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["rb" /* Tile */],
+          attrs,
+          inputsToSave
+        );
+      }
+      const tile = Object(operation["a" /* op */])({ tile_ });
+      //# sourceMappingURL=tile.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/FusedBatchNorm_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const fusedBatchNormGradConfig = {
+        kernelName: kernel_names["F" /* FusedBatchNorm */],
+        inputsToSave: ["x", "mean", "variance", "scale"],
+        gradFunc: (dy, saved, attrs) => {
+          const { varianceEpsilon } = attrs;
+          const [x, mean, variance, scale] = saved;
+          const scaleValue = scale == null ? Object(tensor_ops["e" /* scalar */])(1) : scale;
+          const reductionAxes = getReductionAxes(mean.shape, x.shape);
+          const tileShape = [];
+          if (mean.rank === 1) {
+            for (let i = 0; i < x.shape.length - 1; ++i) {
+              tileShape.push(x.shape[i]);
+            }
+            tileShape.push(1);
+          }
+          const xMinusMean = sub(x, mean);
+          const dyTimesScaleValue = mul(dy, scaleValue);
+          const oneOverSqrtVariance = rsqrt(
+            add(variance, Object(tensor_ops["e" /* scalar */])(varianceEpsilon))
+          );
+          const minusHalfRCube = mul(
+            mul(mul(oneOverSqrtVariance, oneOverSqrtVariance), oneOverSqrtVariance),
+            Object(tensor_ops["e" /* scalar */])(-0.5)
+          );
+          const derX = () => {
+            if (mean.rank === 1) {
+              return reshape(
+                mul(
+                  mul(dy, tile(oneOverSqrtVariance.as4D(1, 1, 1, mean.shape[0]), tileShape)),
+                  scaleValue
+                ),
+                x.shape
+              );
+            } else {
+              return reshape(mul(mul(dy, oneOverSqrtVariance), scaleValue), x.shape);
+            }
+          };
+          const derMean = () => {
+            let meanDer = mul(
+              mul(oneOverSqrtVariance, Object(tensor_ops["e" /* scalar */])(-1)),
+              dyTimesScaleValue
+            );
+            if (mean.rank === 1) {
+              meanDer = sum(meanDer, reductionAxes);
+            }
+            return reshape(meanDer, mean.shape);
+          };
+          const derVariance = () => {
+            let varianceDer = mul(mul(minusHalfRCube, xMinusMean), dyTimesScaleValue);
+            if (mean.rank === 1) {
+              varianceDer = sum(varianceDer, reductionAxes);
+            }
+            return reshape(varianceDer, mean.shape);
+          };
+          const derScale = () => {
+            const xMinusMean2TimesRsqrt = mul(xMinusMean, oneOverSqrtVariance);
+            let scaleDer = mul(dy, xMinusMean2TimesRsqrt);
+            if (mean.rank === 1) {
+              scaleDer = sum(scaleDer, reductionAxes);
+            }
+            return reshape(scaleDer, mean.shape);
+          };
+          const derOffset = () => {
+            let offsetDer = dy;
+            if (mean.rank === 1) {
+              offsetDer = sum(offsetDer, reductionAxes);
+            }
+            return reshape(offsetDer, mean.shape);
+          };
+          return {
+            x: derX,
+            mean: derMean,
+            variance: derVariance,
+            scale: derScale,
+            offset: derOffset,
+          };
+        },
+      };
+      //# sourceMappingURL=FusedBatchNorm_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/GreaterEqual_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const greaterEqualGradConfig = {
+        kernelName: kernel_names["I" /* GreaterEqual */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          return {
+            a: () => Object(tensor_ops["o" /* zerosLike */])(a),
+            b: () => Object(tensor_ops["o" /* zerosLike */])(b),
+          };
+        },
+      };
+      //# sourceMappingURL=GreaterEqual_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Identity_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const identityGradConfig = {
+        kernelName: kernel_names["J" /* Identity */],
+        gradFunc: (dy) => {
+          return { x: () => dy.toFloat() };
+        },
+      };
+      //# sourceMappingURL=Identity_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/local_response_normalization_backprop.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function localResponseNormalizationBackprop_(
+        x,
+        y,
+        dy,
+        depthRadius = 5,
+        bias = 1,
+        alpha = 1,
+        beta = 0.5
+      ) {
+        const forward = (backend) => backend.LRNGrad(dy, x, y, depthRadius, bias, alpha, beta);
+        const inputs = { x, y, dy };
+        const attrs = { depthRadius, bias, alpha, beta };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["M" /* LRNBackprop */],
+          attrs
+        );
+      }
+      const localResponseNormalizationBackprop = Object(operation["a" /* op */])({
+        localResponseNormalizationBackprop_,
+      });
+      //# sourceMappingURL=local_response_normalization_backprop.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/LRN_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const lrnGradConfig = {
+        kernelName: kernel_names["L" /* LRN */],
+        inputsToSave: ["x"],
+        outputsToSave: [true],
+        gradFunc: (dy, saved, attrs) => {
+          const [x, y] = saved;
+          const { depthRadius, bias, alpha, beta } = attrs;
+          return {
+            x: () => localResponseNormalizationBackprop(x, y, dy, depthRadius, bias, alpha, beta),
+          };
+        },
+      };
+      //# sourceMappingURL=LRN_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Max_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const maxGradConfig = {
+        kernelName: kernel_names["P" /* Max */],
+        inputsToSave: ["x"],
+        outputsToSave: [true],
+        gradFunc: (dy, saved, attrs) => {
+          const maxAttrs = attrs;
+          const { reductionIndices } = maxAttrs;
+          const [x, y] = saved;
+          const origAxes = util["parseAxisParam"](reductionIndices, x.shape);
+          const permutedAxes = getAxesPermutation(origAxes, x.rank);
+          const maxGrad = gradForMinAndMax(dy, y, x, origAxes, permutedAxes);
+          return {
+            x: () => {
+              let out = maxGrad["x"]();
+              if (permutedAxes != null) {
+                out = transpose(out);
+              }
+              return out;
+            },
+          };
+        },
+      };
+      //# sourceMappingURL=Max_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/greater_equal.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the truth value of (a >= b) element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       * const b = tf.tensor1d([2, 2, 2]);
+       *
+       * a.greaterEqual(b).print();
+       * ```
+       *
+       * @param a The first input tensor.
+       * @param b The second input tensor. Must have the same dtype as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function greaterEqual_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "greaterEqual");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "greaterEqual");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend, save) => {
+          const res = backend.greaterEqual($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["I" /* GreaterEqual */]
+        );
+      }
+      const greaterEqual = Object(operation["a" /* op */])({ greaterEqual_ });
+      //# sourceMappingURL=greater_equal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/less.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the truth value of (a < b) element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       * const b = tf.tensor1d([2, 2, 2]);
+       *
+       * a.less(b).print();
+       * ```
+       * @param a The first input tensor.
+       * @param b The second input tensor. Must have the same dtype as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function less_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "less");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "less");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend) => backend.less($a, $b);
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["N" /* Less */]
+        );
+      }
+      const less = Object(operation["a" /* op */])({ less_ });
+      //# sourceMappingURL=less.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Maximum_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const maximumGradConfig = {
+        kernelName: kernel_names["V" /* Maximum */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const derA = () => mul(dy, cast(greaterEqual(a, b), "float32"));
+          const derB = () => mul(dy, cast(less(a, b), "float32"));
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=Maximum_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_3d_backprop.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the backprop of a 3d max pool.
+       *
+       * @param dy The dy error, of rank 5 of shape
+       *     [batchSize, depth, height, width, channels].
+       * assumed.
+       * @param input The original input image, of rank 5 or rank 4 of shape
+       *     [batchSize, depth, height, width, channels].
+       * @param output The original output image, of rank 5 of shape
+       *     [batchSize, outDepth, outHeight, outWidth, channels].
+       * @param filterSize The filter size:
+       *     `[filterDepth, filterHeight, filterWidth]`.
+       *     `filterSize` is a single number,
+       *     then `filterDepth == filterHeight == filterWidth`.
+       * @param strides The strides of the pooling:
+       *     `[strideDepth, strideHeight, strideWidth]`. If
+       *     `strides` is a single number, then `strideHeight == strideWidth`.
+       * @param dilations Deprecated, this field will be gone in v3.0.0.
+       *     The dilation rates: `[dilationDepth, dilationHeight, dilationWidth]`
+       *     in which we sample input values across the depth, height and width
+       *     dimensions in dilated pooling.
+       *     Defaults to `[1, 1, 1]`. If `dilations` is a single number,
+       *     then `dilationDepth == dilationHeight == dilationWidth`.
+       *     If it is greater than 1, then all values of `strides` must be 1.
+       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
+       *     used in the forward prop of the op.
+       * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. The
+       *     rounding mode used when computing output dimensions if pad is a
+       *     number. If none is provided, it will not round and error if the output
+       *     is of fractional size.
+       */
+      function maxPool3dBackprop_(
+        dy,
+        input,
+        output,
+        filterSize,
+        strides,
+        dilations = [1, 1, 1],
+        pad,
+        dimRoundingMode
+      ) {
+        const $dy = Object(tensor_util_env["a" /* convertToTensor */])(
+          dy,
+          "dy",
+          "maxPool3dBackprop"
+        );
+        const $input = Object(tensor_util_env["a" /* convertToTensor */])(
+          input,
+          "input",
+          "maxPool3dBackprop"
+        );
+        const $output = Object(tensor_util_env["a" /* convertToTensor */])(
+          output,
+          "output",
+          "maxPool3dBackprop"
+        );
+        let dy5D = $dy;
+        let input5D = $input;
+        let output5D = $output;
+        let reshapedTo5D = false;
+        if ($input.rank === 4) {
+          reshapedTo5D = true;
+          dy5D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]);
+          input5D = reshape($input, [
+            1,
+            $input.shape[0],
+            $input.shape[1],
+            $input.shape[2],
+            $input.shape[3],
+          ]);
+          output5D = reshape($output, [
+            1,
+            $output.shape[0],
+            $output.shape[1],
+            $output.shape[2],
+            $output.shape[3],
+          ]);
+        }
+        util["assert"](
+          dy5D.rank === 5,
+          () => `Error in maxPool3dBackprop: dy must be rank 5 but got rank ` + `${dy5D.rank}.`
+        );
+        util["assert"](
+          input5D.rank === 5,
+          () =>
+            `Error in maxPool3dBackprop: input must be rank 5 but got rank ` + `${input5D.rank}.`
+        );
+        util["assert"](
+          output5D.rank === 5,
+          () =>
+            `Error in maxPool3dBackprop: output must be rank 5 but got rank ` + `${output5D.rank}.`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in maxPool3dBackprop: Either strides or dilations " +
+            `must be 1. Got strides ${strides} and dilations '${dilations}'`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in maxPool3dBackprop: pad must be an integer when ` +
+              `using, dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend) => {
+          const convInfo = computePool3DInfo(
+            input5D.shape,
+            filterSize,
+            strides,
+            dilations,
+            pad,
+            dimRoundingMode
+          );
+          return backend.maxPool3dBackprop(dy5D, input5D, output5D, convInfo);
+        };
+        const inputs = { dy: dy5D, input: input5D, output: output5D };
+        const attrs = { filterSize, strides, dilations, pad, dimRoundingMode };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["S" /* MaxPool3DBackprop */],
+          attrs
+        );
+        if (reshapedTo5D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);
+        }
+        return res;
+      }
+      const maxPool3dBackprop = Object(operation["a" /* op */])({ maxPool3dBackprop_ });
+      //# sourceMappingURL=max_pool_3d_backprop.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/MaxPool3D_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const maxPool3DGradConfig = {
+        kernelName: kernel_names["R" /* MaxPool3D */],
+        inputsToSave: ["x"],
+        outputsToSave: [true],
+        gradFunc: (dy, saved, attrs) => {
+          const [x, y] = saved;
+          const { filterSize, strides, dilations, pad, dimRoundingMode } = attrs;
+          const $dilations = dilations == null ? [1, 1, 1] : dilations;
+          return {
+            x: () =>
+              maxPool3dBackprop(dy, x, y, filterSize, strides, $dilations, pad, dimRoundingMode),
+          };
+        },
+      };
+      //# sourceMappingURL=MaxPool3D_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_backprop.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the backprop of a 2D max pool.
+       *
+       * @param dy The dy error, of rank 4 or rank 3 of shape
+       *     [batchSize, height, width, channels]. If rank 3, batch of 1 is
+       * assumed.
+       * @param input The original input image, of rank 4, of shape
+       *     [batchSize, height, width, channels].
+       * @param output The original output image, of rank 4, of shape
+       *     [batchSize, outHeight, outWidth, channels].
+       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
+       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
+       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
+       *     `strides` is a single number, then `strideHeight == strideWidth`.
+       * @param pad A string from: 'same', 'valid'. The type of padding algorithm
+       *     used in the forward prop of the op.
+       * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. The
+       *     rounding mode used when computing output dimensions if pad is a
+       *     number. If none is provided, it will not round and error if the output
+       *     is of fractional size.
+       */
+      function maxPoolBackprop_(dy, input, output, filterSize, strides, pad, dimRoundingMode) {
+        const $dy = Object(tensor_util_env["a" /* convertToTensor */])(dy, "dy", "maxPoolBackprop");
+        const $input = Object(tensor_util_env["a" /* convertToTensor */])(
+          input,
+          "input",
+          "maxPoolBackprop"
+        );
+        const $output = Object(tensor_util_env["a" /* convertToTensor */])(
+          output,
+          "output",
+          "maxPoolBackprop"
+        );
+        util["assert"](
+          $input.rank === $dy.rank,
+          () => `Rank of input (${$input.rank}) does not match rank of dy ` + `(${$dy.rank})`
+        );
+        util["assert"](
+          $dy.rank === 4,
+          () => `Error in maxPoolBackprop: dy must be rank 4 but got rank ` + `${$dy.rank}.`
+        );
+        util["assert"](
+          $input.rank === 4,
+          () => `Error in maxPoolBackprop: input must be rank 4 but got rank ` + `${$input.rank}.`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in maxPoolBackprop: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend) => {
+          const convInfo = computePool2DInfo(
+            $input.shape,
+            filterSize,
+            strides,
+            1 /* dilations */,
+            pad,
+            dimRoundingMode
+          );
+          return backend.maxPoolBackprop($dy, $input, $output, convInfo);
+        };
+        const inputs = { dy: $dy, input: $input, output: $output };
+        const attrs = { filterSize, strides, pad, dimRoundingMode };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null,
+          kernel_names["T" /* MaxPoolBackprop */],
+          attrs
+        );
+      }
+      const maxPoolBackprop = Object(operation["a" /* op */])({ maxPoolBackprop_ });
+      //# sourceMappingURL=max_pool_backprop.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/MaxPool_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const maxPoolGradConfig = {
+        kernelName: kernel_names["Q" /* MaxPool */],
+        inputsToSave: ["x"],
+        outputsToSave: [true],
+        gradFunc: (dy, saved, attrs) => {
+          const [x, y] = saved;
+          const { filterSize, strides, pad } = attrs;
+          return {
+            x: () => maxPoolBackprop(dy, x, y, filterSize, strides, pad),
+          };
+        },
+      };
+      //# sourceMappingURL=MaxPool_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/greater.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the truth value of (a > b) element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       * const b = tf.tensor1d([2, 2, 2]);
+       *
+       * a.greater(b).print();
+       * ```
+       *
+       * @param a The first input tensor.
+       * @param b The second input tensor. Must have the same dtype as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function greater_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "greater");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "greater");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend) => backend.greater($a, $b);
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["H" /* Greater */]
+        );
+      }
+      const greater = Object(operation["a" /* op */])({ greater_ });
+      //# sourceMappingURL=greater.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/less_equal.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the truth value of (a <= b) element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       * const b = tf.tensor1d([2, 2, 2]);
+       *
+       * a.lessEqual(b).print();
+       * ```
+       *
+       * @param a The first input tensor.
+       * @param b The second input tensor. Must have the same dtype as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function lessEqual_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "lessEqual");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "lessEqual");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend, save) => {
+          const res = backend.lessEqual($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["O" /* LessEqual */]
+        );
+      }
+      const lessEqual = Object(operation["a" /* op */])({ lessEqual_ });
+      //# sourceMappingURL=less_equal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Minimum_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const minimumGradConfig = {
+        kernelName: kernel_names["W" /* Minimum */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const derA = () => mul(dy, cast(lessEqual(a, b), "float32"));
+          const derB = () => mul(dy, cast(greater(a, b), "float32"));
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=Minimum_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Mod_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const modGradConfig = {
+        kernelName: kernel_names["X" /* Mod */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
+          const derA = () => {
+            const reduceAxes = getReductionAxes(a.shape, outShape);
+            if (reduceAxes.length > 0) {
+              return reshape(sum(dy, reduceAxes), a.shape);
+            }
+            return dy;
+          };
+          const derB = () => {
+            const res = mul(dy, neg(floor(div(a, b))));
+            const reduceAxes = getReductionAxes(b.shape, outShape);
+            if (reduceAxes.length > 0) {
+              return reshape(sum(res, reduceAxes), b.shape);
+            }
+            return res;
+          };
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=Mod_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Multiply_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const multiplyGradConfig = {
+        kernelName: kernel_names["Y" /* Multiply */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
+          const derA = () => {
+            const res = mul(dy, cast(b, "float32"));
+            const reduceAxes = getReductionAxes(a.shape, outShape);
+            if (reduceAxes.length > 0) {
+              return reshape(sum(res, reduceAxes), a.shape);
+            }
+            return res;
+          };
+          const derB = () => {
+            const res = mul(dy, cast(a, "float32"));
+            const reduceAxes = getReductionAxes(b.shape, outShape);
+            if (reduceAxes.length > 0) {
+              return reshape(sum(res, reduceAxes), b.shape);
+            }
+            return res;
+          };
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=Multiply_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/OneHot_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const oneHotGradConfig = {
+        kernelName: kernel_names["cb" /* OneHot */],
+        inputsToSave: ["indices"],
+        gradFunc: (dy, saved) => {
+          const indices = saved[0];
+          return { indices: () => Object(tensor_ops["n" /* zeros */])(indices.shape, "float32") };
+        },
+      };
+      //# sourceMappingURL=OneHot_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/PadV2_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const padV2GradConfig = {
+        kernelName: kernel_names["db" /* PadV2 */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved, attrs) => {
+          // Pad introduces values around the original tensor, so the gradient
+          // slices the original shape out of the gradient.
+          const x = saved[0];
+          const { paddings } = attrs;
+          const begin = paddings.map((p) => p[0]);
+          return { x: () => dy.slice(begin, x.shape) };
+        },
+      };
+      //# sourceMappingURL=PadV2_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/where_impl.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /** An implementation of the Where kernel shared between cpu and webgl */
+
+      function whereImpl(condShape, condVals) {
+        const indices = [];
+        for (let i = 0; i < condVals.length; i++) {
+          if (condVals[i]) {
+            indices.push(i);
+          }
+        }
+        const inBuffer = array_ops_buffer(condShape, "int32");
+        const out = array_ops_buffer([indices.length, condShape.length], "int32");
+        for (let i = 0; i < indices.length; i++) {
+          const loc = inBuffer.indexToLoc(indices[i]);
+          const offset = i * condShape.length;
+          out.values.set(loc, offset);
+        }
+        return out.toTensor();
+      }
+      //# sourceMappingURL=where_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/logical_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the truth value of `NOT x` element-wise.
+       *
+       * ```js
+       * const a = tf.tensor1d([false, true], 'bool');
+       *
+       * a.logicalNot().print();
+       * ```
+       *
+       * @param x The input tensor. Must be of dtype 'bool'.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function logicalNot_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "logicalNot", "bool");
+        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.logicalNot($x), { $x });
+      }
+      /**
+       * Returns the truth value of `a AND b` element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([false, false, true, true], 'bool');
+       * const b = tf.tensor1d([false, true, false, true], 'bool');
+       *
+       * a.logicalAnd(b).print();
+       * ```
+       *
+       * @param a The first input tensor. Must be of dtype bool.
+       * @param b The second input tensor. Must be of dtype bool.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function logicalAnd_(a, b) {
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "logicalAnd", "bool");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "logicalAnd", "bool");
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.logicalAnd($a, $b),
+          { a: $a, b: $b },
+          null /* grad */,
+          "LogicalAnd"
+        );
+      }
+      /**
+       * Returns the truth value of `a OR b` element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([false, false, true, true], 'bool');
+       * const b = tf.tensor1d([false, true, false, true], 'bool');
+       *
+       * a.logicalOr(b).print();
+       * ```
+       * @param a The first input tensor. Must be of dtype bool.
+       * @param b The second input tensor. Must be of dtype bool.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function logicalOr_(a, b) {
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "logicalOr", "bool");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "logicalOr", "bool");
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        return engine["a" /* ENGINE */].runKernelFunc((backend) => backend.logicalOr($a, $b), {
+          $a,
+          $b,
+        });
+      }
+      /**
+       * Returns the truth value of `a XOR b` element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([false, false, true, true], 'bool');
+       * const b = tf.tensor1d([false, true, false, true], 'bool');
+       *
+       * a.logicalXor(b).print();
+       * ```
+       *
+       * @param a The first input tensor. Must be of dtype bool.
+       * @param b The second input tensor. Must be of dtype bool.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function logicalXor_(a, b) {
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "logicalXor", "bool");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "logicalXor", "bool");
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        // x ^ y = (x | y) & ~(x & y)
+        return logicalOr(a, b).logicalAnd(logicalAnd(a, b).logicalNot());
+      }
+      /**
+       * Returns the elements, either `a` or `b` depending on the `condition`.
+       *
+       * If the condition is true, select from `a`, otherwise select from `b`.
+       *
+       * ```js
+       * const cond = tf.tensor1d([false, false, true], 'bool');
+       * const a = tf.tensor1d([1 , 2, 3]);
+       * const b = tf.tensor1d([-1, -2, -3]);
+       *
+       * a.where(cond, b).print();
+       * ```
+       *
+       * @param condition The input condition. Must be of dtype bool.
+       * @param a If `condition` is rank 1, `a` may have a higher rank but
+       *     its first dimension must match the size of `condition`.
+       * @param b A tensor with the same shape and type as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function where_(condition, a, b) {
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "where");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "where");
+        const $condition = Object(tensor_util_env["a" /* convertToTensor */])(
+          condition,
+          "condition",
+          "where",
+          "bool"
+        );
+        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in where: ");
+        if ($condition.rank === 1) {
+          // If condition rank is 1, then the first dimension must match the size of
+          // condition.
+          Object(util["assert"])(
+            $condition.shape[0] === $a.shape[0],
+            () => "The first dimension of `a` must match the size of `condition`."
+          );
+        } else {
+          // A must have the same shape as condition.
+          Object(util["assertShapesMatch"])($condition.shape, $b.shape, "Error in where: ");
+        }
+        // TODO(julianoks): Return null for condition gradient
+        // when backprop supports it.
+        const grad = (dy, saved) => {
+          const [$condition] = saved;
+          return {
+            condition: () => Object(tensor_ops["o" /* zerosLike */])($condition).toFloat(),
+            t: () => dy.mul($condition.cast(dy.dtype)),
+            e: () => dy.mul($condition.logicalNot().cast(dy.dtype)),
+          };
+        };
+        const inputs = { condition: $condition, t: $a, e: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.select($condition, $a, $b);
+            save([$condition]);
+            return res;
+          },
+          inputs,
+          grad,
+          kernel_names["kb" /* SelectV2 */]
+        );
+      }
+      /**
+       * Returns the coordinates of true elements of condition.
+       *
+       * The coordinates are returned in a 2-D tensor where the first dimension (rows)
+       * represents the number of true elements, and the second dimension (columns)
+       * represents the coordinates of the true elements. Keep in mind, the shape of
+       * the output tensor can vary depending on how many true values there are in
+       * input. Indices are output in row-major order. The resulting tensor has the
+       * shape `[numTrueElems, condition.rank]`.
+       *
+       * This is analogous to calling the python `tf.where(cond)` without an x or y.
+       *
+       * ```js
+       * const cond = tf.tensor1d([false, false, true], 'bool');
+       * const result = await tf.whereAsync(cond);
+       * result.print();
+       * ```
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      async function whereAsync_(condition) {
+        const $condition = Object(tensor_util_env["a" /* convertToTensor */])(
+          condition,
+          "condition",
+          "whereAsync",
+          "bool"
+        );
+        const vals = await $condition.data();
+        const res = whereImpl($condition.shape, vals);
+        if (condition !== $condition) {
+          $condition.dispose();
+        }
+        return res;
+      }
+      const logicalAnd = Object(operation["a" /* op */])({ logicalAnd_ });
+      const logicalNot = Object(operation["a" /* op */])({ logicalNot_ });
+      const logicalOr = Object(operation["a" /* op */])({ logicalOr_ });
+      const logicalXor = Object(operation["a" /* op */])({ logicalXor_ });
+      const where = Object(operation["a" /* op */])({ where_ });
+      const whereAsync = whereAsync_;
+      //# sourceMappingURL=logical_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pow.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the power of one `tf.Tensor` to another. Supports broadcasting.
+       *
+       * Given a `tf.Tensor` x and a `tf.Tensor` y, this operation computes x^y for
+       * corresponding elements in x and y. The result's dtype will be the upcasted
+       * type of the `base` and `exp` dtypes.
+       *
+       * ```js
+       * const a = tf.tensor([[2, 3], [4, 5]])
+       * const b = tf.tensor([[1, 2], [3, 0]]).toInt();
+       *
+       * a.pow(b).print();  // or tf.pow(a, b)
+       * ```
+       *
+       * ```js
+       * const a = tf.tensor([[1, 2], [3, 4]])
+       * const b = tf.tensor(2).toInt();
+       *
+       * a.pow(b).print();  // or tf.pow(a, b)
+       * ```
+       * We also expose `powStrict` which has the same signature as this op and
+       * asserts that `base` and `exp` are the same shape (does not broadcast).
+       *
+       * @param base The base `tf.Tensor` to pow element-wise.
+       * @param exp The exponent `tf.Tensor` to pow element-wise.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function pow_(base, exp) {
+        let $base = Object(tensor_util_env["a" /* convertToTensor */])(base, "base", "pow");
+        let $exp = Object(tensor_util_env["a" /* convertToTensor */])(exp, "exp", "pow");
+        [$base, $exp] = Object(tensor_util["makeTypesMatch"])($base, $exp);
+        const inputs = { a: $base, b: $exp };
+        const forward = (backend, save) => {
+          const y = backend.pow($base, $exp);
+          save([$base, $exp, y]);
+          return y;
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["fb" /* Pow */]
+        );
+      }
+      const pow = Object(operation["a" /* op */])({ pow_ });
+      //# sourceMappingURL=pow.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Pow_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const powGradConfig = {
+        kernelName: kernel_names["fb" /* Pow */],
+        inputsToSave: ["a", "b"],
+        outputsToSave: [true],
+        gradFunc: (dy, saved) => {
+          const [a, b, y] = saved;
+          const base = a;
+          const exp = b;
+          const outShape = assertAndGetBroadcastShape(base.shape, exp.shape);
+          const derBase = () => {
+            const expFloat = cast(exp, "float32");
+            let res = mul(
+              dy,
+              mul(expFloat, pow(base, sub(expFloat, Object(tensor_ops["e" /* scalar */])(1))))
+            );
+            const reduceAxes = getReductionAxes(base.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = sum(res, reduceAxes);
+            }
+            return reshape(res, base.shape);
+          };
+          const derExp = () => {
+            const condition = greater(base, 0);
+            const logBase = where(
+              condition,
+              log(base),
+              Object(tensor_ops["o" /* zerosLike */])(base)
+            );
+            let res = mul(dy, mul(y, logBase));
+            const reduceAxes = getReductionAxes(exp.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = sum(res, reduceAxes);
+            }
+            return reshape(res, exp.shape);
+          };
+          return { a: derBase, b: derExp };
+        },
+      };
+      //# sourceMappingURL=Pow_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Prelu_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const preluGradConfig = {
+        kernelName: kernel_names["gb" /* Prelu */],
+        inputsToSave: ["x", "alpha"],
+        gradFunc: (dy, saved) => {
+          const [x, alpha] = saved;
+          const mask = greater(x, 0);
+          return {
+            x: () => where(mask, dy, mul(dy, alpha)),
+            alpha: () => {
+              let res = where(mask, Object(tensor_ops["o" /* zerosLike */])(dy), mul(dy, x));
+              const reduceAxes = getReductionAxes(alpha.shape, dy.shape);
+              if (reduceAxes.length > 0) {
+                res = sum(res, reduceAxes);
+              }
+              return reshape(res, alpha.shape);
+            },
+          };
+        },
+      };
+      //# sourceMappingURL=Prelu_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Relu6_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const relu6GradConfig = {
+        kernelName: kernel_names["jb" /* Relu6 */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved) => {
+          const [x] = saved;
+          const mask = mul(lessEqual(x, 6), unary_ops_step(x));
+          return { x: () => mul(dy, cast(mask, "float32")) };
+        },
+      };
+      //# sourceMappingURL=Relu6_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Relu_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const reluGradConfig = {
+        kernelName: kernel_names["ib" /* Relu */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved) => {
+          const [x] = saved;
+          return { x: () => mul(dy, cast(unary_ops_step(x), "float32")) };
+        },
+      };
+      //# sourceMappingURL=Relu_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/selu_util.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const SELU_SCALEALPHA = 1.7580993408473768599402175208123;
+      const SELU_SCALE = 1.0507009873554804934193349852946;
+      //# sourceMappingURL=selu_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Selu_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const seluGradConfig = {
+        kernelName: kernel_names["lb" /* Selu */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved) => {
+          const [x] = saved;
+          return {
+            x: () => {
+              const mask = greater(x, Object(tensor_ops["e" /* scalar */])(0));
+              const scaleAlpha = Object(tensor_ops["e" /* scalar */])(SELU_SCALEALPHA);
+              const scale = Object(tensor_ops["e" /* scalar */])(SELU_SCALE);
+              const greaterThanZeroDer = mul(dy, scale);
+              const lessEqualZeroDer = mul(mul(dy, scaleAlpha), unary_ops_exp(cast(x, "float32")));
+              return where(mask, greaterThanZeroDer, lessEqualZeroDer);
+            },
+          };
+        },
+      };
+      //# sourceMappingURL=Selu_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batch_to_space_nd.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * This operation reshapes the "batch" dimension 0 into `M + 1` dimensions of
+       * shape `blockShape + [batch]`, interleaves these blocks back into the grid
+       * defined by the spatial dimensions `[1, ..., M]`, to obtain a result with
+       * the same rank as the input. The spatial dimensions of this intermediate
+       * result are then optionally cropped according to `crops` to produce the
+       * output. This is the reverse of `tf.spaceToBatchND`. See below for a precise
+       * description.
+       *
+       * ```js
+       * const x = tf.tensor4d([1, 2, 3, 4], [4, 1, 1, 1]);
+       * const blockShape = [2, 2];
+       * const crops = [[0, 0], [0, 0]];
+       *
+       * x.batchToSpaceND(blockShape, crops).print();
+       * ```
+       *
+       * @param x A `tf.Tensor`. N-D with `x.shape` = `[batch] + spatialShape +
+       * remainingShape`, where spatialShape has `M` dimensions.
+       * @param blockShape A 1-D array. Must have shape `[M]`, all values must
+       * be >= 1.
+       * @param crops A 2-D array.  Must have shape `[M, 2]`, all values must be >= 0.
+       * `crops[i] = [cropStart, cropEnd]` specifies the amount to crop from input
+       * dimension `i + 1`, which corresponds to spatial dimension `i`. It is required
+       * that `cropStart[i] + cropEnd[i] <= blockShape[i] * inputShape[i + 1]`
+       *
+       * This operation is equivalent to the following steps:
+       *
+       * 1. Reshape `x` to `reshaped` of shape: `[blockShape[0], ...,
+       * blockShape[M-1], batch / prod(blockShape), x.shape[1], ...,
+       * x.shape[N-1]]`
+       *
+       * 2. Permute dimensions of `reshaped`to produce `permuted` of shape `[batch /
+       * prod(blockShape),x.shape[1], blockShape[0], ..., x.shape[M],
+       * blockShape[M-1],x.shape[M+1], ..., x.shape[N-1]]`
+       *
+       * 3. Reshape `permuted` to produce `reshapedPermuted` of shape `[batch /
+       * prod(blockShape),x.shape[1] * blockShape[0], ..., x.shape[M] *
+       * blockShape[M-1],x.shape[M+1], ..., x.shape[N-1]]`
+       *
+       * 4. Crop the start and end of dimensions `[1, ..., M]` of `reshapedPermuted`
+       * according to `crops` to produce the output of shape: `[batch /
+       * prod(blockShape),x.shape[1] * blockShape[0] - crops[0,0] - crops[0,1],
+       * ..., x.shape[M] * blockShape[M-1] - crops[M-1,0] -
+       * crops[M-1,1],x.shape[M+1], ..., x.shape[N-1]]`
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function batchToSpaceND_(x, blockShape, crops) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchToSpaceND");
+        const prod = blockShape.reduce((a, b) => a * b);
+        util["assert"](
+          $x.rank >= 1 + blockShape.length,
+          () =>
+            `input rank is ${$x.rank} but should be > than blockShape.length ${blockShape.length}`
+        );
+        util["assert"](
+          crops.length === blockShape.length,
+          () =>
+            `crops.length is ${crops.length} but should be equal to blockShape.length  ${blockShape.length}`
+        );
+        util["assert"](
+          $x.shape[0] % prod === 0,
+          () =>
+            `input tensor batch is ${$x.shape[0]} but is not divisible by the product of ` +
+            `the elements of blockShape ${blockShape.join(" * ")} === ${prod}`
+        );
+        const forward = (backend) => {
+          return backend.batchToSpaceND($x, blockShape, crops);
+        };
+        const inputs = { x: $x };
+        const attrs = { blockShape, crops };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["i" /* BatchToSpaceND */],
+          attrs
+        );
+      }
+      const batchToSpaceND = Object(operation["a" /* op */])({ batchToSpaceND_ });
+      //# sourceMappingURL=batch_to_space_nd.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/SpaceToBatchND_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const spaceToBatchNDGradConfig = {
+        kernelName: kernel_names["mb" /* SpaceToBatchND */],
+        gradFunc: (dy, saved, attrs) => {
+          const { blockShape, paddings } = attrs;
+          return { x: () => batchToSpaceND(dy, blockShape, paddings) };
+        },
+      };
+      //# sourceMappingURL=SpaceToBatchND_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/SplitV_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const splitVGradConfig = {
+        kernelName: kernel_names["nb" /* SplitV */],
+        gradFunc: (dy, saved, attrs) => {
+          const { axis } = attrs;
+          return { x: () => concat(dy, axis) };
+        },
+      };
+      //# sourceMappingURL=SplitV_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Square_grad.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const squareGradConfig = {
+        kernelName: kernel_names["ob" /* Square */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved) => {
+          const [x] = saved;
+          return { x: () => mul(dy, mul(x.toFloat(), 2)) };
+        },
+      };
+      //# sourceMappingURL=Square_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/SquaredDifference_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const squaredDifferenceGradConfig = {
+        kernelName: kernel_names["pb" /* SquaredDifference */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const two = Object(tensor_ops["e" /* scalar */])(2);
+          const derA = () => mul(dy, mul(two, sub(a, b)));
+          const derB = () => mul(dy, mul(two, sub(b, a)));
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=SquaredDifference_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Sub_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const subGradConfig = {
+        kernelName: kernel_names["qb" /* Sub */],
+        inputsToSave: ["a", "b"],
+        gradFunc: (dy, saved) => {
+          const [a, b] = saved;
+          const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
+          const derA = () => {
+            let res = dy;
+            const reduceAxes = getReductionAxes(a.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = sum(res, reduceAxes);
+            }
+            return reshape(res, a.shape);
+          };
+          const derB = () => {
+            let res = dy;
+            const reduceAxes = getReductionAxes(b.shape, outShape);
+            if (reduceAxes.length > 0) {
+              res = sum(res, reduceAxes);
+            }
+            return reshape(neg(res), b.shape);
+          };
+          return { a: derA, b: derB };
+        },
+      };
+      //# sourceMappingURL=Sub_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Pads a `tf.Tensor` with a given value and paddings.
+       *
+       * This operation currently only implements the `CONSTANT` mode.
+       *
+       * Also available are stricter rank-specific methods with the same signature
+       * as this method that assert that `paddings` is of given length.
+       *   - `tf.pad1d`
+       *   - `tf.pad2d`
+       *   - `tf.pad3d`
+       *   - `tf.pad4d`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       * x.pad([[1, 2]]).print();
+       * ```
+       * @param x The tensor to pad.
+       * @param paddings An array of length `R` (the rank of the tensor), where
+       * each element is a length-2 tuple of ints `[padBefore, padAfter]`,
+       * specifying how much to pad along each dimension of the tensor.
+       * @param constantValue The pad value to use. Defaults to 0.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function pad_(x, paddings, constantValue = 0) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "pad");
+        if ($x.rank === 0) {
+          throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");
+        }
+        const forward = (backend, save) => {
+          save([$x]);
+          return backend.pad($x, paddings, constantValue);
+        };
+        const attrs = { paddings, constantValue };
+        const inputs = { x: $x };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["db" /* PadV2 */],
+          attrs
+        );
+      }
+      const pad_pad = Object(operation["a" /* op */])({ pad_ });
+      //# sourceMappingURL=pad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/slice_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function assertParamsValid(input, begin, size) {
+        util["assert"](
+          input.rank === begin.length,
+          () =>
+            `Error in slice${input.rank}D: Length of begin ${begin} must ` +
+            `match the rank of the array (${input.rank}).`
+        );
+        util["assert"](
+          input.rank === size.length,
+          () =>
+            `Error in slice${input.rank}D: Length of size ${size} must ` +
+            `match the rank of the array (${input.rank}).`
+        );
+        for (let i = 0; i < input.rank; ++i) {
+          util["assert"](
+            begin[i] + size[i] <= input.shape[i],
+            () =>
+              `Error in slice${input.rank}D: begin[${i}] + size[${i}] ` +
+              `(${begin[i] + size[i]}) would overflow input.shape[${i}] (${input.shape[i]})`
+          );
+        }
+      }
+      /** Converts a binary mask to an array of axes. Used in stridedSlice(). */
+      function maskToAxes(mask) {
+        const axes = [];
+        let axis = 0;
+        while (mask > 0) {
+          if (mask & 1) {
+            axes.push(axis);
+          }
+          mask /= 2;
+          axis++;
+        }
+        return axes;
+      }
+      /** Computes the output shape given the strided slice params. */
+      function slice_util_computeOutShape(begin, end, strides) {
+        const size = [];
+        for (let axis = 0; axis < begin.length; axis++) {
+          size[axis] = Math.ceil((end[axis] - begin[axis]) / strides[axis]);
+        }
+        return size;
+      }
+      // Creates full selection at the elided dimensions. If the dimension matches
+      // the ellipsis mask, override the current stride value. Otherwise, insert.
+      function stridesWithElidedDims(strides, ellipsisInsertionIndex, numElidedAxes) {
+        const newStrides = [...strides];
+        for (let i = 0; i < numElidedAxes; i++) {
+          if (i === 0) {
+            newStrides[ellipsisInsertionIndex] = 1;
+          } else {
+            newStrides.splice(
+              ellipsisInsertionIndex,
+              0 /* num elements to delete */,
+              1 /* element to add */
+            );
+            newStrides.pop();
+          }
+        }
+        return newStrides;
+      }
+      // Creates full selection at the elided dimensions. If the dimension matches
+      // the ellipsis mask, override the current start value. Otherwise, insert.
+      function startIndicesWithElidedDims(startIndices, ellipsisInsertionIndex, numElidedAxes) {
+        const newIndices = [...startIndices];
+        for (let i = 0; i < numElidedAxes; i++) {
+          if (i === 0) {
+            newIndices[ellipsisInsertionIndex] = 0;
+          } else {
+            newIndices.splice(
+              ellipsisInsertionIndex,
+              0 /* num elements to delete */,
+              0 /* element to add */
+            );
+            newIndices.pop();
+          }
+        }
+        return newIndices;
+      }
+      // Creates full selection at the elided dimensions. If the dimension matches
+      // the ellipsis mask, override the current stop value. Otherwise, insert.
+      function stopIndicesWithElidedDims(
+        stopIndices,
+        ellipsisInsertionIndex,
+        numElidedAxes,
+        inputShape
+      ) {
+        const newIndices = [...stopIndices];
+        for (let i = 0; i < numElidedAxes; i++) {
+          if (i === 0) {
+            newIndices[ellipsisInsertionIndex] = Number.MAX_SAFE_INTEGER;
+          } else {
+            newIndices.splice(
+              ellipsisInsertionIndex,
+              0 /* num elements to delete */,
+              Number.MAX_SAFE_INTEGER /* element to add */
+            );
+            newIndices.pop();
+          }
+        }
+        for (let i = 0; i < newIndices.length; i++) {
+          newIndices[i] = util["clamp"](0, newIndices[i], inputShape[i]);
+        }
+        return newIndices;
+      }
+      function stridesForAxis(strides, axis, ellipsisMask) {
+        let stride = strides[axis];
+        if (ellipsisMask & (1 << axis) || stride == null) {
+          stride = 1;
+        }
+        return stride;
+      }
+      function startForAxis(beginMask, startIndices, strides, inputShape, axis, ellipsisMask) {
+        // Begin with the specified index
+        let start = startIndices[axis];
+        const stride = strides[axis] || 1;
+        // Check the axis bit from right of masked axes, or the begin index is not set
+        // for the axis.
+        if (beginMask & (1 << axis) || ellipsisMask & (1 << axis) || start == null) {
+          if (stride > 0) {
+            // Forward iteration - use the first element. These values will get
+            // clamped below (Note: We could have set them to 0 and axis_size-1, but
+            // use lowest() and max() to maintain symmetry with StopForAxis())
+            start = Number.MIN_SAFE_INTEGER;
+          } else {
+            // Backward iteration - use the last element.
+            start = Number.MAX_SAFE_INTEGER;
+          }
+        }
+        // Handle negative indices
+        const axisSize = inputShape[axis];
+        if (start < 0) {
+          start += axisSize;
+        }
+        // Clamping
+        start = util["clamp"](0, start, axisSize - 1);
+        return start;
+      }
+      function stopForAxis(endMask, stopIndices, strides, inputShape, axis, ellipsisMask) {
+        // Begin with the specified index
+        let stop = stopIndices[axis];
+        const stride = strides[axis] || 1;
+        // Check the axis bit from right of masked axes, or if the stop index is not
+        // set for this axis.
+        if (endMask & (1 << axis) || ellipsisMask & (1 << axis) || stop == null) {
+          if (stride > 0) {
+            // Forward iteration - use the last element. These values will get
+            // clamped below
+            stop = Number.MAX_SAFE_INTEGER;
+          } else {
+            // Backward iteration - use the first element.
+            stop = Number.MIN_SAFE_INTEGER;
+          }
+        }
+        // Handle negative indices
+        const axisSize = inputShape[axis];
+        if (stop < 0) {
+          stop += axisSize;
+        }
+        // Clamping
+        // Because the end index points one past the last element, we need slightly
+        // different clamping ranges depending on the direction.
+        if (stride > 0) {
+          // Forward iteration
+          stop = util["clamp"](0, stop, axisSize);
+        } else {
+          // Backward iteration
+          stop = util["clamp"](-1, stop, axisSize - 1);
+        }
+        return stop;
+      }
+      /**
+       * Returns true if the slice occupies a continous set of elements in the
+       * 'flat' space.
+       */
+      function isSliceContinous(shape, begin, size) {
+        // Index of the first axis that has size > 1.
+        let firstNonOneAxis = size.length;
+        for (let i = 0; i < size.length; i++) {
+          if (size[i] > 1) {
+            firstNonOneAxis = i;
+            break;
+          }
+        }
+        for (let i = firstNonOneAxis + 1; i < size.length; i++) {
+          if (begin[i] > 0 || size[i] !== shape[i]) {
+            return false;
+          }
+        }
+        return true;
+      }
+      function computeFlatOffset(begin, strides) {
+        let flatOffset = begin.length > 0 ? begin[begin.length - 1] : 1;
+        for (let i = 0; i < begin.length - 1; i++) {
+          flatOffset += begin[i] * strides[i];
+        }
+        return flatOffset;
+      }
+      //# sourceMappingURL=slice_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/slice.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Extracts a 1D slice from 1D array starting at coordinates `begin` and is
+       * of length `size`. See `slice` for details.
+       */
+      function slice1d_(x, begin, size) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice1d");
+        util["assert"](
+          $x.rank === 1,
+          () => `slice1d expects a rank-1 tensor, but got a rank-${$x.rank} tensor`
+        );
+        return slice($x, [begin], [size]);
+      }
+      /**
+       * Extracts a 2D slice from a 2D array starting at coordinates `begin` and
+       * is of size `size`. See `slice` for details.
+       */
+      function slice2d_(x, begin, size) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice2d");
+        util["assert"](
+          $x.rank === 2,
+          () => `slice2d expects a rank-2 tensor, but got a rank-${$x.rank} tensor`
+        );
+        return slice($x, begin, size);
+      }
+      /**
+       * Extracts a 3D slice from a 3D array starting at coordinates `begin` and
+       * is of size `size`. See `slice` for details.
+       */
+      function slice3d_(x, begin, size) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice3d");
+        util["assert"](
+          $x.rank === 3,
+          () => `slice3d expects a rank-3 tensor, but got a rank-${$x.rank} tensor`
+        );
+        return slice($x, begin, size);
+      }
+      /**
+       * Extracts a 4D slice from a 4D array starting at coordinates `begin` and
+       * is of size `size`. See `slice` for details.
+       */
+      function slice4d_(x, begin, size) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice4d");
+        util["assert"](
+          $x.rank === 4,
+          () => `slice4d expects a rank-4 tensor, but got a rank-${$x.rank} tensor`
+        );
+        return slice($x, begin, size);
+      }
+      /**
+       * Extracts a slice from a `tf.Tensor` starting at coordinates `begin`
+       * and is of size `size`.
+       *
+       * Also available are stricter rank-specific methods with the same signature
+       * as this method that assert that `x` is of the given rank:
+       *   - `tf.slice1d`
+       *   - `tf.slice2d`
+       *   - `tf.slice3d`
+       *   - `tf.slice4d`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       *
+       * x.slice([1], [2]).print();
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * x.slice([1, 0], [1, 2]).print();
+       * ```
+       * @param x The input `tf.Tensor` to slice from.
+       * @param begin The coordinates to start the slice from. The length can be
+       *     less than the rank of x - the rest of the axes will have implicit 0 as
+       *     start. Can also be a single number, in which case it specifies the
+       *     first axis.
+       * @param size The size of the slice. The length can be less than the rank of
+       *     x - the rest of the axes will have implicit -1. A value of -1 requests
+       *     the rest of the dimensions in the axis. Can also be a single number,
+       *     in which case it specifies the size of the first axis.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      function slice_(x, begin, size) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "slice");
+        if ($x.rank === 0) {
+          throw new Error("Slicing scalar is not possible");
+        }
+        // The following logic allows for more ergonomic calls.
+        let begin_;
+        if (typeof begin === "number") {
+          begin_ = [begin, ...new Array($x.rank - 1).fill(0)];
+        } else if (begin.length < $x.rank) {
+          begin_ = begin.concat(new Array($x.rank - begin.length).fill(0));
+        } else {
+          begin_ = begin.slice();
+        }
+        begin_.forEach((d) => {
+          util["assert"](d !== -1, () => "slice() does not support negative begin indexing.");
+        });
+        let size_;
+        if (size == null) {
+          size_ = new Array($x.rank).fill(-1);
+        } else if (typeof size === "number") {
+          size_ = [size, ...new Array($x.rank - 1).fill(-1)];
+        } else if (size.length < $x.rank) {
+          size_ = size.concat(new Array($x.rank - size.length).fill(-1));
+        } else {
+          size_ = size;
+        }
+        size_ = size_.map((d, i) => {
+          if (d >= 0) {
+            return d;
+          } else {
+            util["assert"](
+              d === -1,
+              () =>
+                `Negative size values should be exactly -1 but got ` +
+                `${d} for the slice() size at index ${i}.`
+            );
+            return $x.shape[i] - begin_[i];
+          }
+        });
+        assertParamsValid($x, begin_, size_);
+        const inputShape = $x.shape;
+        const grad = (dy) => {
+          // Create an Nx2 padding where the first column represents how many
+          // zeros are prepended (at start) for each dimension, and the second
+          // column indicates how many zeros are appended (at end).
+          // The number of zeros to append is the shape of the input
+          // elementwise-subtracted by both the begin vector and sizes vector.
+          const paddings = [];
+          for (let i = 0; i < dy.rank; i++) {
+            paddings.push([begin_[i], inputShape[i] - begin_[i] - size_[i]]);
+          }
+          return { x: () => pad_pad(dy, paddings) };
+        };
+        const attrs = { begin: begin_, size: size_ };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.slice($x, begin_, size_),
+          { x: $x },
+          grad,
+          "Slice",
+          attrs
+        );
+      }
+      const slice = Object(operation["a" /* op */])({ slice_ });
+      const slice1d = Object(operation["a" /* op */])({ slice1d_ });
+      const slice2d = Object(operation["a" /* op */])({ slice2d_ });
+      const slice3d = Object(operation["a" /* op */])({ slice3d_ });
+      const slice4d = Object(operation["a" /* op */])({ slice4d_ });
+      //# sourceMappingURL=slice.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Tile_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const tileGradConfig = {
+        kernelName: kernel_names["rb" /* Tile */],
+        inputsToSave: ["x"],
+        gradFunc: (dy, saved, attrs) => {
+          const [x] = saved;
+          const { reps } = attrs;
+          const derX = () => {
+            let xGrad = Object(tensor_ops["o" /* zerosLike */])(x);
+            // TODO(cais): Maybe reduce memory footprint by avoiding repeated
+            // slicing.
+            if (x.rank === 1) {
+              for (let i = 0; i < reps[0]; ++i) {
+                xGrad = add(xGrad, slice(dy, [i * x.shape[0]], [x.shape[0]]));
+              }
+            } else if (x.rank === 2) {
+              for (let i = 0; i < reps[0]; ++i) {
+                for (let j = 0; j < reps[1]; ++j) {
+                  xGrad = add(
+                    xGrad,
+                    slice(dy, [i * x.shape[0], j * x.shape[1]], [x.shape[0], x.shape[1]])
+                  );
+                }
+              }
+            } else if (x.rank === 3) {
+              for (let i = 0; i < reps[0]; ++i) {
+                for (let j = 0; j < reps[1]; ++j) {
+                  for (let k = 0; k < reps[2]; ++k) {
+                    xGrad = add(
+                      xGrad,
+                      slice(
+                        dy,
+                        [i * x.shape[0], j * x.shape[1], k * x.shape[2]],
+                        [x.shape[0], x.shape[1], x.shape[2]]
+                      )
+                    );
+                  }
+                }
+              }
+            } else if (x.rank === 4) {
+              for (let i = 0; i < reps[0]; ++i) {
+                for (let j = 0; j < reps[1]; ++j) {
+                  for (let k = 0; k < reps[2]; ++k) {
+                    for (let l = 0; l < reps[3]; ++l) {
+                      xGrad = add(
+                        xGrad,
+                        slice(
+                          dy,
+                          [i * x.shape[0], j * x.shape[1], k * x.shape[2], l * x.shape[3]],
+                          [x.shape[0], x.shape[1], x.shape[2], x.shape[3]]
+                        )
+                      );
+                    }
+                  }
+                }
+              }
+            } else {
+              throw new Error(
+                `Gradient for tile operation is not implemented for rank-` +
+                  `${x.rank} tensors yet.`
+              );
+            }
+            return xGrad;
+          };
+          return { x: derX };
+        },
+      };
+      //# sourceMappingURL=Tile_grad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/gradients/Transpose_grad.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const transposeGradConfig = {
+        kernelName: kernel_names["sb" /* Transpose */],
+        gradFunc: (dy, saved, attrs) => {
+          const transposeAttrs = attrs;
+          const { perm } = transposeAttrs;
+          const undoPerm = getUndoAxesPermutation(perm);
+          return { x: () => transpose(dy, undoPerm) };
+        },
+      };
+      //# sourceMappingURL=Transpose_grad.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/kernel_registry.js
+      var kernel_registry = __webpack_require__(17);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/register_all_gradients.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // Export all kernel configs here so that the package can auto register them
+      const gradConfigs = [
+        addGradConfig,
+        addNGradConfig,
+        atan2GradConfig,
+        avgPoolGradConfig,
+        avgPool3DGradConfig,
+        batchMatMulGradConfig,
+        batchToSpaceNDGradConfig,
+        broadcastToGradConfig,
+        concatGradConfig,
+        conv2DGradConfig,
+        conv2DBackpropInputGradConfig,
+        conv3DGradConfig,
+        cumsumGradConfig,
+        depthwiseConv2dNativeGradConfig,
+        divGradConfig,
+        eluGradConfig,
+        floorDivGradConfig,
+        fusedBatchNormGradConfig,
+        greaterEqualGradConfig,
+        identityGradConfig,
+        lrnGradConfig,
+        oneHotGradConfig,
+        padV2GradConfig,
+        splitVGradConfig,
+        maxGradConfig,
+        spaceToBatchNDGradConfig,
+        maxGradConfig,
+        maximumGradConfig,
+        maxPoolGradConfig,
+        maxPool3DGradConfig,
+        minimumGradConfig,
+        modGradConfig,
+        multiplyGradConfig,
+        oneHotGradConfig,
+        padV2GradConfig,
+        powGradConfig,
+        preluGradConfig,
+        reluGradConfig,
+        relu6GradConfig,
+        seluGradConfig,
+        spaceToBatchNDGradConfig,
+        splitVGradConfig,
+        squareGradConfig,
+        squaredDifferenceGradConfig,
+        tileGradConfig,
+        transposeGradConfig,
+        subGradConfig,
+      ];
+      for (const gradientConfig of gradConfigs) {
+        Object(kernel_registry["d" /* registerGradient */])(gradientConfig);
+      }
+      //# sourceMappingURL=register_all_gradients.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/environment.js
+      var environment = __webpack_require__(10);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/platforms/platform_browser.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class PlatformBrowser {
+        fetch(path, init) {
+          return fetch(path, init);
+        }
+        now() {
+          return performance.now();
+        }
+        encode(text, encoding) {
+          if (encoding !== "utf-8" && encoding !== "utf8") {
+            throw new Error(`Browser's encoder only supports utf-8, but got ${encoding}`);
+          }
+          if (this.textEncoder == null) {
+            this.textEncoder = new TextEncoder();
+          }
+          return this.textEncoder.encode(text);
+        }
+        decode(bytes, encoding) {
+          return new TextDecoder(encoding).decode(bytes);
+        }
+      }
+      if (Object(environment["c" /* env */])().get("IS_BROWSER")) {
+        Object(environment["c" /* env */])().setPlatform("browser", new PlatformBrowser());
+      }
+      //# sourceMappingURL=platform_browser.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/platforms/platform_node.js
+      var platform_node = __webpack_require__(62);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/io_utils.js
+      var io_utils = __webpack_require__(13);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/router_registry.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class IORouterRegistry {
+        constructor() {
+          this.saveRouters = [];
+          this.loadRouters = [];
+        }
+        static getInstance() {
+          if (IORouterRegistry.instance == null) {
+            IORouterRegistry.instance = new IORouterRegistry();
+          }
+          return IORouterRegistry.instance;
+        }
+        /**
+         * Register a save-handler router.
+         *
+         * @param saveRouter A function that maps a URL-like string onto an instance
+         * of `IOHandler` with the `save` method defined or `null`.
+         */
+        static registerSaveRouter(saveRouter) {
+          IORouterRegistry.getInstance().saveRouters.push(saveRouter);
+        }
+        /**
+         * Register a load-handler router.
+         *
+         * @param loadRouter A function that maps a URL-like string onto an instance
+         * of `IOHandler` with the `load` method defined or `null`.
+         */
+        static registerLoadRouter(loadRouter) {
+          IORouterRegistry.getInstance().loadRouters.push(loadRouter);
+        }
+        /**
+         * Look up IOHandler for saving, given a URL-like string.
+         *
+         * @param url
+         * @returns If only one match is found, an instance of IOHandler with the
+         * `save` method defined. If no match is found, `null`.
+         * @throws Error, if more than one match is found.
+         */
+        static getSaveHandlers(url) {
+          return IORouterRegistry.getHandlers(url, "save");
+        }
+        /**
+         * Look up IOHandler for loading, given a URL-like string.
+         *
+         * @param url
+         * @param loadOptions Optional, custom load options.
+         * @returns All valid handlers for `url`, given the currently registered
+         *   handler routers.
+         */
+        static getLoadHandlers(url, loadOptions) {
+          return IORouterRegistry.getHandlers(url, "load", loadOptions);
+        }
+        static getHandlers(url, handlerType, loadOptions) {
+          const validHandlers = [];
+          const routers =
+            handlerType === "load"
+              ? IORouterRegistry.getInstance().loadRouters
+              : IORouterRegistry.getInstance().saveRouters;
+          routers.forEach((router) => {
+            const handler = router(url, loadOptions);
+            if (handler !== null) {
+              validHandlers.push(handler);
+            }
+          });
+          return validHandlers;
+        }
+      }
+      const registerSaveRouter = (loudRouter) => IORouterRegistry.registerSaveRouter(loudRouter);
+      const registerLoadRouter = (loudRouter) => IORouterRegistry.registerLoadRouter(loudRouter);
+      const getSaveHandlers = (url) => IORouterRegistry.getSaveHandlers(url);
+      const getLoadHandlers = (url, loadOptions) =>
+        IORouterRegistry.getLoadHandlers(url, loadOptions);
+      //# sourceMappingURL=router_registry.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/model_management.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Classes and functions for model management across multiple storage mediums.
+       *
+       * Supported client actions:
+       * - Listing models on all registered storage mediums.
+       * - Remove model by URL from any registered storage mediums, by using URL
+       *   string.
+       * - Moving or copying model from one path to another in the same medium or from
+       *   one medium to another, by using URL strings.
+       */
+
+      const URL_SCHEME_SUFFIX = "://";
+      class model_management_ModelStoreManagerRegistry {
+        constructor() {
+          this.managers = {};
+        }
+        static getInstance() {
+          if (model_management_ModelStoreManagerRegistry.instance == null) {
+            model_management_ModelStoreManagerRegistry.instance =
+              new model_management_ModelStoreManagerRegistry();
+          }
+          return model_management_ModelStoreManagerRegistry.instance;
+        }
+        /**
+         * Register a save-handler router.
+         *
+         * @param saveRouter A function that maps a URL-like string onto an instance
+         * of `IOHandler` with the `save` method defined or `null`.
+         */
+        static registerManager(scheme, manager) {
+          Object(util["assert"])(scheme != null, () => "scheme must not be undefined or null.");
+          if (scheme.endsWith(URL_SCHEME_SUFFIX)) {
+            scheme = scheme.slice(0, scheme.indexOf(URL_SCHEME_SUFFIX));
+          }
+          Object(util["assert"])(scheme.length > 0, () => "scheme must not be an empty string.");
+          const registry = model_management_ModelStoreManagerRegistry.getInstance();
+          Object(util["assert"])(
+            registry.managers[scheme] == null,
+            () => `A model store manager is already registered for scheme '${scheme}'.`
+          );
+          registry.managers[scheme] = manager;
+        }
+        static getManager(scheme) {
+          const manager = this.getInstance().managers[scheme];
+          if (manager == null) {
+            throw new Error(`Cannot find model manager for scheme '${scheme}'`);
+          }
+          return manager;
+        }
+        static getSchemes() {
+          return Object.keys(this.getInstance().managers);
+        }
+      }
+      /**
+       * Helper method for parsing a URL string into a scheme and a path.
+       *
+       * @param url E.g., 'localstorage://my-model'
+       * @returns A dictionary with two fields: scheme and path.
+       *   Scheme: e.g., 'localstorage' in the example above.
+       *   Path: e.g., 'my-model' in the example above.
+       */
+      function parseURL(url) {
+        if (url.indexOf(URL_SCHEME_SUFFIX) === -1) {
+          throw new Error(
+            `The url string provided does not contain a scheme. ` +
+              `Supported schemes are: ` +
+              `${model_management_ModelStoreManagerRegistry.getSchemes().join(",")}`
+          );
+        }
+        return {
+          scheme: url.split(URL_SCHEME_SUFFIX)[0],
+          path: url.split(URL_SCHEME_SUFFIX)[1],
+        };
+      }
+      async function cloneModelInternal(sourceURL, destURL, deleteSource = false) {
+        Object(util["assert"])(
+          sourceURL !== destURL,
+          () => `Old path and new path are the same: '${sourceURL}'`
+        );
+        const loadHandlers = IORouterRegistry.getLoadHandlers(sourceURL);
+        Object(util["assert"])(
+          loadHandlers.length > 0,
+          () => `Copying failed because no load handler is found for source URL ${sourceURL}.`
+        );
+        Object(util["assert"])(
+          loadHandlers.length < 2,
+          () =>
+            `Copying failed because more than one (${loadHandlers.length}) ` +
+            `load handlers for source URL ${sourceURL}.`
+        );
+        const loadHandler = loadHandlers[0];
+        const saveHandlers = IORouterRegistry.getSaveHandlers(destURL);
+        Object(util["assert"])(
+          saveHandlers.length > 0,
+          () =>
+            `Copying failed because no save handler is found for destination ` + `URL ${destURL}.`
+        );
+        Object(util["assert"])(
+          saveHandlers.length < 2,
+          () =>
+            `Copying failed because more than one (${loadHandlers.length}) ` +
+            `save handlers for destination URL ${destURL}.`
+        );
+        const saveHandler = saveHandlers[0];
+        const sourceScheme = parseURL(sourceURL).scheme;
+        const sourcePath = parseURL(sourceURL).path;
+        const sameMedium = sourceScheme === parseURL(sourceURL).scheme;
+        const modelArtifacts = await loadHandler.load();
+        // If moving within the same storage medium, remove the old model as soon as
+        // the loading is done. Without doing this, it is possible that the combined
+        // size of the two models will cause the cloning to fail.
+        if (deleteSource && sameMedium) {
+          await model_management_ModelStoreManagerRegistry
+            .getManager(sourceScheme)
+            .removeModel(sourcePath);
+        }
+        const saveResult = await saveHandler.save(modelArtifacts);
+        // If moving between mediums, the deletion is done after the save succeeds.
+        // This guards against the case in which saving to the destination medium
+        // fails.
+        if (deleteSource && !sameMedium) {
+          await model_management_ModelStoreManagerRegistry
+            .getManager(sourceScheme)
+            .removeModel(sourcePath);
+        }
+        return saveResult.modelArtifactsInfo;
+      }
+      /**
+       * List all models stored in registered storage mediums.
+       *
+       * For a web browser environment, the registered mediums are Local Storage and
+       * IndexedDB.
+       *
+       * ```js
+       * // First create and save a model.
+       * const model = tf.sequential();
+       * model.add(tf.layers.dense(
+       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
+       * await model.save('localstorage://demo/management/model1');
+       *
+       * // Then list existing models.
+       * console.log(JSON.stringify(await tf.io.listModels()));
+       *
+       * // Delete the model.
+       * await tf.io.removeModel('localstorage://demo/management/model1');
+       *
+       * // List models again.
+       * console.log(JSON.stringify(await tf.io.listModels()));
+       * ```
+       *
+       * @returns A `Promise` of a dictionary mapping URLs of existing models to
+       * their model artifacts info. URLs include medium-specific schemes, e.g.,
+       *   'indexeddb://my/model/1'. Model artifacts info include type of the
+       * model's topology, byte sizes of the topology, weights, etc.
+       */
+      /**
+       * @doc {
+       *   heading: 'Models',
+       *   subheading: 'Management',
+       *   namespace: 'io',
+       *   ignoreCI: true
+       * }
+       */
+      async function listModels() {
+        const schemes = model_management_ModelStoreManagerRegistry.getSchemes();
+        const out = {};
+        for (const scheme of schemes) {
+          const schemeOut = await model_management_ModelStoreManagerRegistry
+            .getManager(scheme)
+            .listModels();
+          for (const path in schemeOut) {
+            const url = scheme + URL_SCHEME_SUFFIX + path;
+            out[url] = schemeOut[path];
+          }
+        }
+        return out;
+      }
+      /**
+       * Remove a model specified by URL from a reigstered storage medium.
+       *
+       * ```js
+       * // First create and save a model.
+       * const model = tf.sequential();
+       * model.add(tf.layers.dense(
+       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
+       * await model.save('localstorage://demo/management/model1');
+       *
+       * // Then list existing models.
+       * console.log(JSON.stringify(await tf.io.listModels()));
+       *
+       * // Delete the model.
+       * await tf.io.removeModel('localstorage://demo/management/model1');
+       *
+       * // List models again.
+       * console.log(JSON.stringify(await tf.io.listModels()));
+       * ```
+       *
+       * @param url A URL to a stored model, with a scheme prefix, e.g.,
+       *   'localstorage://my-model-1', 'indexeddb://my/model/2'.
+       * @returns ModelArtifactsInfo of the deleted model (if and only if deletion
+       *   is successful).
+       * @throws Error if deletion fails, e.g., if no model exists at `path`.
+       */
+      /**
+       * @doc {
+       *   heading: 'Models',
+       *   subheading: 'Management',
+       *   namespace: 'io',
+       *   ignoreCI: true
+       * }
+       */
+      async function removeModel(url) {
+        const schemeAndPath = parseURL(url);
+        const manager = model_management_ModelStoreManagerRegistry.getManager(schemeAndPath.scheme);
+        return manager.removeModel(schemeAndPath.path);
+      }
+      /**
+       * Copy a model from one URL to another.
+       *
+       * This function supports:
+       *
+       * 1. Copying within a storage medium, e.g.,
+       *    `tf.io.copyModel('localstorage://model-1', 'localstorage://model-2')`
+       * 2. Copying between two storage mediums, e.g.,
+       *    `tf.io.copyModel('localstorage://model-1', 'indexeddb://model-1')`
+       *
+       * ```js
+       * // First create and save a model.
+       * const model = tf.sequential();
+       * model.add(tf.layers.dense(
+       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
+       * await model.save('localstorage://demo/management/model1');
+       *
+       * // Then list existing models.
+       * console.log(JSON.stringify(await tf.io.listModels()));
+       *
+       * // Copy the model, from Local Storage to IndexedDB.
+       * await tf.io.copyModel(
+       *     'localstorage://demo/management/model1',
+       *     'indexeddb://demo/management/model1');
+       *
+       * // List models again.
+       * console.log(JSON.stringify(await tf.io.listModels()));
+       *
+       * // Remove both models.
+       * await tf.io.removeModel('localstorage://demo/management/model1');
+       * await tf.io.removeModel('indexeddb://demo/management/model1');
+       * ```
+       *
+       * @param sourceURL Source URL of copying.
+       * @param destURL Destination URL of copying.
+       * @returns ModelArtifactsInfo of the copied model (if and only if copying
+       *   is successful).
+       * @throws Error if copying fails, e.g., if no model exists at `sourceURL`, or
+       *   if `oldPath` and `newPath` are identical.
+       */
+      /**
+       * @doc {
+       *   heading: 'Models',
+       *   subheading: 'Management',
+       *   namespace: 'io',
+       *   ignoreCI: true
+       * }
+       */
+      async function copyModel(sourceURL, destURL) {
+        const deleteSource = false;
+        return cloneModelInternal(sourceURL, destURL, deleteSource);
+      }
+      /**
+       * Move a model from one URL to another.
+       *
+       * This function supports:
+       *
+       * 1. Moving within a storage medium, e.g.,
+       *    `tf.io.moveModel('localstorage://model-1', 'localstorage://model-2')`
+       * 2. Moving between two storage mediums, e.g.,
+       *    `tf.io.moveModel('localstorage://model-1', 'indexeddb://model-1')`
+       *
+       * ```js
+       * // First create and save a model.
+       * const model = tf.sequential();
+       * model.add(tf.layers.dense(
+       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
+       * await model.save('localstorage://demo/management/model1');
+       *
+       * // Then list existing models.
+       * console.log(JSON.stringify(await tf.io.listModels()));
+       *
+       * // Move the model, from Local Storage to IndexedDB.
+       * await tf.io.moveModel(
+       *     'localstorage://demo/management/model1',
+       *     'indexeddb://demo/management/model1');
+       *
+       * // List models again.
+       * console.log(JSON.stringify(await tf.io.listModels()));
+       *
+       * // Remove the moved model.
+       * await tf.io.removeModel('indexeddb://demo/management/model1');
+       * ```
+       *
+       * @param sourceURL Source URL of moving.
+       * @param destURL Destination URL of moving.
+       * @returns ModelArtifactsInfo of the copied model (if and only if copying
+       *   is successful).
+       * @throws Error if moving fails, e.g., if no model exists at `sourceURL`, or
+       *   if `oldPath` and `newPath` are identical.
+       */
+      /**
+       * @doc {
+       *   heading: 'Models',
+       *   subheading: 'Management',
+       *   namespace: 'io',
+       *   ignoreCI: true
+       * }
+       */
+      async function moveModel(sourceURL, destURL) {
+        const deleteSource = true;
+        return cloneModelInternal(sourceURL, destURL, deleteSource);
+      }
+
+      //# sourceMappingURL=model_management.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/indexed_db.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const DATABASE_NAME = "tensorflowjs";
+      const DATABASE_VERSION = 1;
+      // Model data and ModelArtifactsInfo (metadata) are stored in two separate
+      // stores for efficient access of the list of stored models and their metadata.
+      // 1. The object store for model data: topology, weights and weight manifests.
+      const MODEL_STORE_NAME = "models_store";
+      // 2. The object store for ModelArtifactsInfo, including meta-information such
+      //    as the type of topology (JSON vs binary), byte size of the topology, byte
+      //    size of the weights, etc.
+      const INFO_STORE_NAME = "model_info_store";
+      /**
+       * Delete the entire database for tensorflow.js, including the models store.
+       */
+      async function deleteDatabase() {
+        const idbFactory = getIndexedDBFactory();
+        return new Promise((resolve, reject) => {
+          const deleteRequest = idbFactory.deleteDatabase(DATABASE_NAME);
+          deleteRequest.onsuccess = () => resolve();
+          deleteRequest.onerror = (error) => reject(error);
+        });
+      }
+      function getIndexedDBFactory() {
+        if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
+          // TODO(cais): Add more info about what IOHandler subtypes are available.
+          //   Maybe point to a doc page on the web and/or automatically determine
+          //   the available IOHandlers and print them in the error message.
+          throw new Error(
+            "Failed to obtain IndexedDB factory because the current environment" +
+              "is not a web browser."
+          );
+        }
+        // tslint:disable-next-line:no-any
+        const theWindow = typeof window === "undefined" ? self : window;
+        const factory =
+          theWindow.indexedDB ||
+          theWindow.mozIndexedDB ||
+          theWindow.webkitIndexedDB ||
+          theWindow.msIndexedDB ||
+          theWindow.shimIndexedDB;
+        if (factory == null) {
+          throw new Error("The current browser does not appear to support IndexedDB.");
+        }
+        return factory;
+      }
+      function setUpDatabase(openRequest) {
+        const db = openRequest.result;
+        db.createObjectStore(MODEL_STORE_NAME, { keyPath: "modelPath" });
+        db.createObjectStore(INFO_STORE_NAME, { keyPath: "modelPath" });
+      }
+      /**
+       * IOHandler subclass: Browser IndexedDB.
+       *
+       * See the doc string of `browserIndexedDB` for more details.
+       */
+      class indexed_db_BrowserIndexedDB {
+        constructor(modelPath) {
+          this.indexedDB = getIndexedDBFactory();
+          if (modelPath == null || !modelPath) {
+            throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");
+          }
+          this.modelPath = modelPath;
+        }
+        async save(modelArtifacts) {
+          // TODO(cais): Support saving GraphDef models.
+          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
+            throw new Error(
+              "BrowserLocalStorage.save() does not support saving model topology " +
+                "in binary formats yet."
+            );
+          }
+          return this.databaseAction(this.modelPath, modelArtifacts);
+        }
+        async load() {
+          return this.databaseAction(this.modelPath);
+        }
+        /**
+         * Perform database action to put model artifacts into or read model artifacts
+         * from IndexedDB object store.
+         *
+         * Whether the action is put or get depends on whether `modelArtifacts` is
+         * specified. If it is specified, the action will be put; otherwise the action
+         * will be get.
+         *
+         * @param modelPath A unique string path for the model.
+         * @param modelArtifacts If specified, it will be the model artifacts to be
+         *   stored in IndexedDB.
+         * @returns A `Promise` of `SaveResult`, if the action is put, or a `Promise`
+         *   of `ModelArtifacts`, if the action is get.
+         */
+        databaseAction(modelPath, modelArtifacts) {
+          return new Promise((resolve, reject) => {
+            const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);
+            openRequest.onupgradeneeded = () => setUpDatabase(openRequest);
+            openRequest.onsuccess = () => {
+              const db = openRequest.result;
+              if (modelArtifacts == null) {
+                // Read model out from object store.
+                const modelTx = db.transaction(MODEL_STORE_NAME, "readonly");
+                const modelStore = modelTx.objectStore(MODEL_STORE_NAME);
+                const getRequest = modelStore.get(this.modelPath);
+                getRequest.onsuccess = () => {
+                  if (getRequest.result == null) {
+                    db.close();
+                    return reject(
+                      new Error(
+                        `Cannot find model with path '${this.modelPath}' ` + `in IndexedDB.`
+                      )
+                    );
+                  } else {
+                    resolve(getRequest.result.modelArtifacts);
+                  }
+                };
+                getRequest.onerror = (error) => {
+                  db.close();
+                  return reject(getRequest.error);
+                };
+                modelTx.oncomplete = () => db.close();
+              } else {
+                // Put model into object store.
+                const modelArtifactsInfo = Object(io_utils["g" /* getModelArtifactsInfoForJSON */])(
+                  modelArtifacts
+                );
+                // First, put ModelArtifactsInfo into info store.
+                const infoTx = db.transaction(INFO_STORE_NAME, "readwrite");
+                let infoStore = infoTx.objectStore(INFO_STORE_NAME);
+                const putInfoRequest = infoStore.put({
+                  modelPath: this.modelPath,
+                  modelArtifactsInfo,
+                });
+                let modelTx;
+                putInfoRequest.onsuccess = () => {
+                  // Second, put model data into model store.
+                  modelTx = db.transaction(MODEL_STORE_NAME, "readwrite");
+                  const modelStore = modelTx.objectStore(MODEL_STORE_NAME);
+                  const putModelRequest = modelStore.put({
+                    modelPath: this.modelPath,
+                    modelArtifacts,
+                    modelArtifactsInfo,
+                  });
+                  putModelRequest.onsuccess = () => resolve({ modelArtifactsInfo });
+                  putModelRequest.onerror = (error) => {
+                    // If the put-model request fails, roll back the info entry as
+                    // well.
+                    infoStore = infoTx.objectStore(INFO_STORE_NAME);
+                    const deleteInfoRequest = infoStore.delete(this.modelPath);
+                    deleteInfoRequest.onsuccess = () => {
+                      db.close();
+                      return reject(putModelRequest.error);
+                    };
+                    deleteInfoRequest.onerror = (error) => {
+                      db.close();
+                      return reject(putModelRequest.error);
+                    };
+                  };
+                };
+                putInfoRequest.onerror = (error) => {
+                  db.close();
+                  return reject(putInfoRequest.error);
+                };
+                infoTx.oncomplete = () => {
+                  if (modelTx == null) {
+                    db.close();
+                  } else {
+                    modelTx.oncomplete = () => db.close();
+                  }
+                };
+              }
+            };
+            openRequest.onerror = (error) => reject(openRequest.error);
+          });
+        }
+      }
+      indexed_db_BrowserIndexedDB.URL_SCHEME = "indexeddb://";
+      const indexedDBRouter = (url) => {
+        if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
+          return null;
+        } else {
+          if (!Array.isArray(url) && url.startsWith(indexed_db_BrowserIndexedDB.URL_SCHEME)) {
+            return browserIndexedDB(url.slice(indexed_db_BrowserIndexedDB.URL_SCHEME.length));
+          } else {
+            return null;
+          }
+        }
+      };
+      IORouterRegistry.registerSaveRouter(indexedDBRouter);
+      IORouterRegistry.registerLoadRouter(indexedDBRouter);
+      /**
+       * Creates a browser IndexedDB IOHandler for saving and loading models.
+       *
+       * ```js
+       * const model = tf.sequential();
+       * model.add(
+       *     tf.layers.dense({units: 1, inputShape: [100], activation: 'sigmoid'}));
+       *
+       * const saveResult = await model.save('indexeddb://MyModel'));
+       * console.log(saveResult);
+       * ```
+       *
+       * @param modelPath A unique identifier for the model to be saved. Must be a
+       *   non-empty string.
+       * @returns An instance of `BrowserIndexedDB` (sublcass of `IOHandler`),
+       *   which can be used with, e.g., `tf.Model.save`.
+       */
+      function browserIndexedDB(modelPath) {
+        return new indexed_db_BrowserIndexedDB(modelPath);
+      }
+      function maybeStripScheme(key) {
+        return key.startsWith(indexed_db_BrowserIndexedDB.URL_SCHEME)
+          ? key.slice(indexed_db_BrowserIndexedDB.URL_SCHEME.length)
+          : key;
+      }
+      class BrowserIndexedDBManager {
+        constructor() {
+          this.indexedDB = getIndexedDBFactory();
+        }
+        async listModels() {
+          return new Promise((resolve, reject) => {
+            const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);
+            openRequest.onupgradeneeded = () => setUpDatabase(openRequest);
+            openRequest.onsuccess = () => {
+              const db = openRequest.result;
+              const tx = db.transaction(INFO_STORE_NAME, "readonly");
+              const store = tx.objectStore(INFO_STORE_NAME);
+              // tslint:disable:max-line-length
+              // Need to cast `store` as `any` here because TypeScript's DOM
+              // library does not have the `getAll()` method even though the
+              // method is supported in the latest version of most mainstream
+              // browsers:
+              // https://developer.mozilla.org/en-US/docs/Web/API/IDBObjectStore/getAll
+              // tslint:enable:max-line-length
+              // tslint:disable-next-line:no-any
+              const getAllInfoRequest = store.getAll();
+              getAllInfoRequest.onsuccess = () => {
+                const out = {};
+                for (const item of getAllInfoRequest.result) {
+                  out[item.modelPath] = item.modelArtifactsInfo;
+                }
+                resolve(out);
+              };
+              getAllInfoRequest.onerror = (error) => {
+                db.close();
+                return reject(getAllInfoRequest.error);
+              };
+              tx.oncomplete = () => db.close();
+            };
+            openRequest.onerror = (error) => reject(openRequest.error);
+          });
+        }
+        async removeModel(path) {
+          path = maybeStripScheme(path);
+          return new Promise((resolve, reject) => {
+            const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);
+            openRequest.onupgradeneeded = () => setUpDatabase(openRequest);
+            openRequest.onsuccess = () => {
+              const db = openRequest.result;
+              const infoTx = db.transaction(INFO_STORE_NAME, "readwrite");
+              const infoStore = infoTx.objectStore(INFO_STORE_NAME);
+              const getInfoRequest = infoStore.get(path);
+              let modelTx;
+              getInfoRequest.onsuccess = () => {
+                if (getInfoRequest.result == null) {
+                  db.close();
+                  return reject(
+                    new Error(`Cannot find model with path '${path}' ` + `in IndexedDB.`)
+                  );
+                } else {
+                  // First, delete the entry in the info store.
+                  const deleteInfoRequest = infoStore.delete(path);
+                  const deleteModelData = () => {
+                    // Second, delete the entry in the model store.
+                    modelTx = db.transaction(MODEL_STORE_NAME, "readwrite");
+                    const modelStore = modelTx.objectStore(MODEL_STORE_NAME);
+                    const deleteModelRequest = modelStore.delete(path);
+                    deleteModelRequest.onsuccess = () =>
+                      resolve(getInfoRequest.result.modelArtifactsInfo);
+                    deleteModelRequest.onerror = (error) => reject(getInfoRequest.error);
+                  };
+                  // Proceed with deleting model data regardless of whether deletion
+                  // of info data succeeds or not.
+                  deleteInfoRequest.onsuccess = deleteModelData;
+                  deleteInfoRequest.onerror = (error) => {
+                    deleteModelData();
+                    db.close();
+                    return reject(getInfoRequest.error);
+                  };
+                }
+              };
+              getInfoRequest.onerror = (error) => {
+                db.close();
+                return reject(getInfoRequest.error);
+              };
+              infoTx.oncomplete = () => {
+                if (modelTx == null) {
+                  db.close();
+                } else {
+                  modelTx.oncomplete = () => db.close();
+                }
+              };
+            };
+            openRequest.onerror = (error) => reject(openRequest.error);
+          });
+        }
+      }
+      if (Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
+        // Wrap the construction and registration, to guard against browsers that
+        // don't support Local Storage.
+        try {
+          model_management_ModelStoreManagerRegistry.registerManager(
+            indexed_db_BrowserIndexedDB.URL_SCHEME,
+            new BrowserIndexedDBManager()
+          );
+        } catch (err) {}
+      }
+      //# sourceMappingURL=indexed_db.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/local_storage.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const PATH_SEPARATOR = "/";
+      const PATH_PREFIX = "tensorflowjs_models";
+      const INFO_SUFFIX = "info";
+      const MODEL_TOPOLOGY_SUFFIX = "model_topology";
+      const WEIGHT_SPECS_SUFFIX = "weight_specs";
+      const WEIGHT_DATA_SUFFIX = "weight_data";
+      const MODEL_METADATA_SUFFIX = "model_metadata";
+      /**
+       * Purge all tensorflow.js-saved model artifacts from local storage.
+       *
+       * @returns Paths of the models purged.
+       */
+      function purgeLocalStorageArtifacts() {
+        if (
+          !Object(environment["c" /* env */])().getBool("IS_BROWSER") ||
+          typeof window === "undefined" ||
+          typeof window.localStorage === "undefined"
+        ) {
+          throw new Error(
+            "purgeLocalStorageModels() cannot proceed because local storage is " +
+              "unavailable in the current environment."
+          );
+        }
+        const LS = window.localStorage;
+        const purgedModelPaths = [];
+        for (let i = 0; i < LS.length; ++i) {
+          const key = LS.key(i);
+          const prefix = PATH_PREFIX + PATH_SEPARATOR;
+          if (key.startsWith(prefix) && key.length > prefix.length) {
+            LS.removeItem(key);
+            const modelName = getModelPathFromKey(key);
+            if (purgedModelPaths.indexOf(modelName) === -1) {
+              purgedModelPaths.push(modelName);
+            }
+          }
+        }
+        return purgedModelPaths;
+      }
+      function getModelKeys(path) {
+        return {
+          info: [PATH_PREFIX, path, INFO_SUFFIX].join(PATH_SEPARATOR),
+          topology: [PATH_PREFIX, path, MODEL_TOPOLOGY_SUFFIX].join(PATH_SEPARATOR),
+          weightSpecs: [PATH_PREFIX, path, WEIGHT_SPECS_SUFFIX].join(PATH_SEPARATOR),
+          weightData: [PATH_PREFIX, path, WEIGHT_DATA_SUFFIX].join(PATH_SEPARATOR),
+          modelMetadata: [PATH_PREFIX, path, MODEL_METADATA_SUFFIX].join(PATH_SEPARATOR),
+        };
+      }
+      /**
+       * Get model path from a local-storage key.
+       *
+       * E.g., 'tensorflowjs_models/my/model/1/info' --> 'my/model/1'
+       *
+       * @param key
+       */
+      function getModelPathFromKey(key) {
+        const items = key.split(PATH_SEPARATOR);
+        if (items.length < 3) {
+          throw new Error(`Invalid key format: ${key}`);
+        }
+        return items.slice(1, items.length - 1).join(PATH_SEPARATOR);
+      }
+      function local_storage_maybeStripScheme(key) {
+        return key.startsWith(local_storage_BrowserLocalStorage.URL_SCHEME)
+          ? key.slice(local_storage_BrowserLocalStorage.URL_SCHEME.length)
+          : key;
+      }
+      /**
+       * IOHandler subclass: Browser Local Storage.
+       *
+       * See the doc string to `browserLocalStorage` for more details.
+       */
+      class local_storage_BrowserLocalStorage {
+        constructor(modelPath) {
+          if (
+            !Object(environment["c" /* env */])().getBool("IS_BROWSER") ||
+            typeof window === "undefined" ||
+            typeof window.localStorage === "undefined"
+          ) {
+            // TODO(cais): Add more info about what IOHandler subtypes are
+            // available.
+            //   Maybe point to a doc page on the web and/or automatically determine
+            //   the available IOHandlers and print them in the error message.
+            throw new Error("The current environment does not support local storage.");
+          }
+          this.LS = window.localStorage;
+          if (modelPath == null || !modelPath) {
+            throw new Error("For local storage, modelPath must not be null, undefined or empty.");
+          }
+          this.modelPath = modelPath;
+          this.keys = getModelKeys(this.modelPath);
+        }
+        /**
+         * Save model artifacts to browser local storage.
+         *
+         * See the documentation to `browserLocalStorage` for details on the saved
+         * artifacts.
+         *
+         * @param modelArtifacts The model artifacts to be stored.
+         * @returns An instance of SaveResult.
+         */
+        async save(modelArtifacts) {
+          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
+            throw new Error(
+              "BrowserLocalStorage.save() does not support saving model topology " +
+                "in binary formats yet."
+            );
+          } else {
+            const topology = JSON.stringify(modelArtifacts.modelTopology);
+            const weightSpecs = JSON.stringify(modelArtifacts.weightSpecs);
+            const modelArtifactsInfo = Object(io_utils["g" /* getModelArtifactsInfoForJSON */])(
+              modelArtifacts
+            );
+            try {
+              this.LS.setItem(this.keys.info, JSON.stringify(modelArtifactsInfo));
+              this.LS.setItem(this.keys.topology, topology);
+              this.LS.setItem(this.keys.weightSpecs, weightSpecs);
+              this.LS.setItem(
+                this.keys.weightData,
+                Object(io_utils["a" /* arrayBufferToBase64String */])(modelArtifacts.weightData)
+              );
+              this.LS.setItem(
+                this.keys.modelMetadata,
+                JSON.stringify({
+                  format: modelArtifacts.format,
+                  generatedBy: modelArtifacts.generatedBy,
+                  convertedBy: modelArtifacts.convertedBy,
+                  userDefinedMetadata: modelArtifacts.userDefinedMetadata,
+                })
+              );
+              return { modelArtifactsInfo };
+            } catch (err) {
+              // If saving failed, clean up all items saved so far.
+              this.LS.removeItem(this.keys.info);
+              this.LS.removeItem(this.keys.topology);
+              this.LS.removeItem(this.keys.weightSpecs);
+              this.LS.removeItem(this.keys.weightData);
+              this.LS.removeItem(this.keys.modelMetadata);
+              throw new Error(
+                `Failed to save model '${this.modelPath}' to local storage: ` +
+                  `size quota being exceeded is a possible cause of this failure: ` +
+                  `modelTopologyBytes=${modelArtifactsInfo.modelTopologyBytes}, ` +
+                  `weightSpecsBytes=${modelArtifactsInfo.weightSpecsBytes}, ` +
+                  `weightDataBytes=${modelArtifactsInfo.weightDataBytes}.`
+              );
+            }
+          }
+        }
+        /**
+         * Load a model from local storage.
+         *
+         * See the documentation to `browserLocalStorage` for details on the saved
+         * artifacts.
+         *
+         * @returns The loaded model (if loading succeeds).
+         */
+        async load() {
+          const info = JSON.parse(this.LS.getItem(this.keys.info));
+          if (info == null) {
+            throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);
+          }
+          if (info.modelTopologyType !== "JSON") {
+            throw new Error(
+              "BrowserLocalStorage does not support loading non-JSON model " + "topology yet."
+            );
+          }
+          const out = {};
+          // Load topology.
+          const topology = JSON.parse(this.LS.getItem(this.keys.topology));
+          if (topology == null) {
+            throw new Error(
+              `In local storage, the topology of model '${this.modelPath}' ` + `is missing.`
+            );
+          }
+          out.modelTopology = topology;
+          // Load weight specs.
+          const weightSpecs = JSON.parse(this.LS.getItem(this.keys.weightSpecs));
+          if (weightSpecs == null) {
+            throw new Error(
+              `In local storage, the weight specs of model '${this.modelPath}' ` + `are missing.`
+            );
+          }
+          out.weightSpecs = weightSpecs;
+          // Load meta-data fields.
+          const metadataString = this.LS.getItem(this.keys.modelMetadata);
+          if (metadataString != null) {
+            const metadata = JSON.parse(metadataString);
+            out.format = metadata["format"];
+            out.generatedBy = metadata["generatedBy"];
+            out.convertedBy = metadata["convertedBy"];
+            out.userDefinedMetadata = metadata["userDefinedMetadata"];
+          }
+          // Load weight data.
+          const weightDataBase64 = this.LS.getItem(this.keys.weightData);
+          if (weightDataBase64 == null) {
+            throw new Error(
+              `In local storage, the binary weight values of model ` +
+                `'${this.modelPath}' are missing.`
+            );
+          }
+          out.weightData = Object(io_utils["b" /* base64StringToArrayBuffer */])(weightDataBase64);
+          return out;
+        }
+      }
+      local_storage_BrowserLocalStorage.URL_SCHEME = "localstorage://";
+      const localStorageRouter = (url) => {
+        if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
+          return null;
+        } else {
+          if (!Array.isArray(url) && url.startsWith(local_storage_BrowserLocalStorage.URL_SCHEME)) {
+            return browserLocalStorage(
+              url.slice(local_storage_BrowserLocalStorage.URL_SCHEME.length)
+            );
+          } else {
+            return null;
+          }
+        }
+      };
+      IORouterRegistry.registerSaveRouter(localStorageRouter);
+      IORouterRegistry.registerLoadRouter(localStorageRouter);
+      /**
+       * Factory function for local storage IOHandler.
+       *
+       * This `IOHandler` supports both `save` and `load`.
+       *
+       * For each model's saved artifacts, four items are saved to local storage.
+       *   - `${PATH_SEPARATOR}/${modelPath}/info`: Contains meta-info about the
+       *     model, such as date saved, type of the topology, size in bytes, etc.
+       *   - `${PATH_SEPARATOR}/${modelPath}/topology`: Model topology. For Keras-
+       *     style models, this is a stringized JSON.
+       *   - `${PATH_SEPARATOR}/${modelPath}/weight_specs`: Weight specs of the
+       *     model, can be used to decode the saved binary weight values (see
+       *     item below).
+       *   - `${PATH_SEPARATOR}/${modelPath}/weight_data`: Concatenated binary
+       *     weight values, stored as a base64-encoded string.
+       *
+       * Saving may throw an `Error` if the total size of the artifacts exceed the
+       * browser-specific quota.
+       *
+       * @param modelPath A unique identifier for the model to be saved. Must be a
+       *   non-empty string.
+       * @returns An instance of `IOHandler`, which can be used with, e.g.,
+       *   `tf.Model.save`.
+       */
+      function browserLocalStorage(modelPath) {
+        return new local_storage_BrowserLocalStorage(modelPath);
+      }
+      class local_storage_BrowserLocalStorageManager {
+        constructor() {
+          Object(util["assert"])(
+            Object(environment["c" /* env */])().getBool("IS_BROWSER"),
+            () => "Current environment is not a web browser"
+          );
+          Object(util["assert"])(
+            typeof window === "undefined" || typeof window.localStorage !== "undefined",
+            () => "Current browser does not appear to support localStorage"
+          );
+          this.LS = window.localStorage;
+        }
+        async listModels() {
+          const out = {};
+          const prefix = PATH_PREFIX + PATH_SEPARATOR;
+          const suffix = PATH_SEPARATOR + INFO_SUFFIX;
+          for (let i = 0; i < this.LS.length; ++i) {
+            const key = this.LS.key(i);
+            if (key.startsWith(prefix) && key.endsWith(suffix)) {
+              const modelPath = getModelPathFromKey(key);
+              out[modelPath] = JSON.parse(this.LS.getItem(key));
+            }
+          }
+          return out;
+        }
+        async removeModel(path) {
+          path = local_storage_maybeStripScheme(path);
+          const keys = getModelKeys(path);
+          if (this.LS.getItem(keys.info) == null) {
+            throw new Error(`Cannot find model at path '${path}'`);
+          }
+          const info = JSON.parse(this.LS.getItem(keys.info));
+          this.LS.removeItem(keys.info);
+          this.LS.removeItem(keys.topology);
+          this.LS.removeItem(keys.weightSpecs);
+          this.LS.removeItem(keys.weightData);
+          return info;
+        }
+      }
+      if (Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
+        // Wrap the construction and registration, to guard against browsers that
+        // don't support Local Storage.
+        try {
+          model_management_ModelStoreManagerRegistry.registerManager(
+            local_storage_BrowserLocalStorage.URL_SCHEME,
+            new local_storage_BrowserLocalStorageManager()
+          );
+        } catch (err) {}
+      }
+      //# sourceMappingURL=local_storage.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/browser_files.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * IOHandlers related to files, such as browser-triggered file downloads,
+       * user-selected files in browser.
+       */
+
+      const DEFAULT_FILE_NAME_PREFIX = "model";
+      const DEFAULT_JSON_EXTENSION_NAME = ".json";
+      const DEFAULT_WEIGHT_DATA_EXTENSION_NAME = ".weights.bin";
+      function defer(f) {
+        return new Promise((resolve) => setTimeout(resolve)).then(f);
+      }
+      class browser_files_BrowserDownloads {
+        constructor(fileNamePrefix) {
+          if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
+            // TODO(cais): Provide info on what IOHandlers are available under the
+            //   current environment.
+            throw new Error(
+              "browserDownloads() cannot proceed because the current environment " +
+                "is not a browser."
+            );
+          }
+          if (fileNamePrefix.startsWith(browser_files_BrowserDownloads.URL_SCHEME)) {
+            fileNamePrefix = fileNamePrefix.slice(browser_files_BrowserDownloads.URL_SCHEME.length);
+          }
+          if (fileNamePrefix == null || fileNamePrefix.length === 0) {
+            fileNamePrefix = DEFAULT_FILE_NAME_PREFIX;
+          }
+          this.modelTopologyFileName = fileNamePrefix + DEFAULT_JSON_EXTENSION_NAME;
+          this.weightDataFileName = fileNamePrefix + DEFAULT_WEIGHT_DATA_EXTENSION_NAME;
+        }
+        async save(modelArtifacts) {
+          if (typeof document === "undefined") {
+            throw new Error(
+              "Browser downloads are not supported in " +
+                "this environment since `document` is not present"
+            );
+          }
+          const weightsURL = window.URL.createObjectURL(
+            new Blob([modelArtifacts.weightData], { type: "application/octet-stream" })
+          );
+          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
+            throw new Error(
+              "BrowserDownloads.save() does not support saving model topology " +
+                "in binary formats yet."
+            );
+          } else {
+            const weightsManifest = [
+              {
+                paths: ["./" + this.weightDataFileName],
+                weights: modelArtifacts.weightSpecs,
+              },
+            ];
+            const modelTopologyAndWeightManifest = {
+              modelTopology: modelArtifacts.modelTopology,
+              format: modelArtifacts.format,
+              generatedBy: modelArtifacts.generatedBy,
+              convertedBy: modelArtifacts.convertedBy,
+              weightsManifest,
+            };
+            const modelTopologyAndWeightManifestURL = window.URL.createObjectURL(
+              new Blob([JSON.stringify(modelTopologyAndWeightManifest)], {
+                type: "application/json",
+              })
+            );
+            // If anchor elements are not provided, create them without attaching them
+            // to parents, so that the downloaded file names can be controlled.
+            const jsonAnchor =
+              this.jsonAnchor == null ? document.createElement("a") : this.jsonAnchor;
+            jsonAnchor.download = this.modelTopologyFileName;
+            jsonAnchor.href = modelTopologyAndWeightManifestURL;
+            // Trigger downloads by evoking a click event on the download anchors.
+            // When multiple downloads are started synchronously, Firefox will only
+            // save the last one.
+            await defer(() => jsonAnchor.dispatchEvent(new MouseEvent("click")));
+            if (modelArtifacts.weightData != null) {
+              const weightDataAnchor =
+                this.weightDataAnchor == null ? document.createElement("a") : this.weightDataAnchor;
+              weightDataAnchor.download = this.weightDataFileName;
+              weightDataAnchor.href = weightsURL;
+              await defer(() => weightDataAnchor.dispatchEvent(new MouseEvent("click")));
+            }
+            return {
+              modelArtifactsInfo: Object(io_utils["g" /* getModelArtifactsInfoForJSON */])(
+                modelArtifacts
+              ),
+            };
+          }
+        }
+      }
+      browser_files_BrowserDownloads.URL_SCHEME = "downloads://";
+      class browser_files_BrowserFiles {
+        constructor(files) {
+          if (files == null || files.length < 1) {
+            throw new Error(
+              `When calling browserFiles, at least 1 file is required, ` + `but received ${files}`
+            );
+          }
+          this.files = files;
+        }
+        async load() {
+          const jsonFile = this.files[0];
+          const weightFiles = this.files.slice(1);
+          return new Promise((resolve, reject) => {
+            const jsonReader = new FileReader();
+            jsonReader.onload = (event) => {
+              // tslint:disable-next-line:no-any
+              const modelJSON = JSON.parse(event.target.result);
+              const modelTopology = modelJSON.modelTopology;
+              if (modelTopology == null) {
+                reject(new Error(`modelTopology field is missing from file ${jsonFile.name}`));
+                return;
+              }
+              if (weightFiles.length === 0) {
+                resolve({ modelTopology });
+              }
+              const weightsManifest = modelJSON.weightsManifest;
+              if (weightsManifest == null) {
+                reject(new Error(`weightManifest field is missing from file ${jsonFile.name}`));
+                return;
+              }
+              let pathToFile;
+              try {
+                pathToFile = this.checkManifestAndWeightFiles(weightsManifest, weightFiles);
+              } catch (err) {
+                reject(err);
+                return;
+              }
+              const weightSpecs = [];
+              const paths = [];
+              const perFileBuffers = [];
+              weightsManifest.forEach((weightsGroup) => {
+                weightsGroup.paths.forEach((path) => {
+                  paths.push(path);
+                  perFileBuffers.push(null);
+                });
+                weightSpecs.push(...weightsGroup.weights);
+              });
+              weightsManifest.forEach((weightsGroup) => {
+                weightsGroup.paths.forEach((path) => {
+                  const weightFileReader = new FileReader();
+                  weightFileReader.onload = (event) => {
+                    // tslint:disable-next-line:no-any
+                    const weightData = event.target.result;
+                    const index = paths.indexOf(path);
+                    perFileBuffers[index] = weightData;
+                    if (perFileBuffers.indexOf(null) === -1) {
+                      resolve({
+                        modelTopology,
+                        weightSpecs,
+                        weightData: Object(io_utils["d" /* concatenateArrayBuffers */])(
+                          perFileBuffers
+                        ),
+                        format: modelJSON.format,
+                        generatedBy: modelJSON.generatedBy,
+                        convertedBy: modelJSON.convertedBy,
+                        userDefinedMetadata: modelJSON.userDefinedMetadata,
+                      });
+                    }
+                  };
+                  weightFileReader.onerror = (error) =>
+                    reject(`Failed to weights data from file of path '${path}'.`);
+                  weightFileReader.readAsArrayBuffer(pathToFile[path]);
+                });
+              });
+            };
+            jsonReader.onerror = (error) =>
+              reject(
+                `Failed to read model topology and weights manifest JSON ` +
+                  `from file '${jsonFile.name}'. BrowserFiles supports loading ` +
+                  `Keras-style tf.Model artifacts only.`
+              );
+            jsonReader.readAsText(jsonFile);
+          });
+        }
+        /**
+         * Check the compatibility between weights manifest and weight files.
+         */
+        checkManifestAndWeightFiles(manifest, files) {
+          const basenames = [];
+          const fileNames = files.map((file) => Object(io_utils["c" /* basename */])(file.name));
+          const pathToFile = {};
+          for (const group of manifest) {
+            group.paths.forEach((path) => {
+              const pathBasename = Object(io_utils["c" /* basename */])(path);
+              if (basenames.indexOf(pathBasename) !== -1) {
+                throw new Error(
+                  `Duplicate file basename found in weights manifest: ` + `'${pathBasename}'`
+                );
+              }
+              basenames.push(pathBasename);
+              if (fileNames.indexOf(pathBasename) === -1) {
+                throw new Error(`Weight file with basename '${pathBasename}' is not provided.`);
+              } else {
+                pathToFile[path] = files[fileNames.indexOf(pathBasename)];
+              }
+            });
+          }
+          if (basenames.length !== files.length) {
+            throw new Error(
+              `Mismatch in the number of files in weights manifest ` +
+                `(${basenames.length}) and the number of weight files provided ` +
+                `(${files.length}).`
+            );
+          }
+          return pathToFile;
+        }
+      }
+      const browserDownloadsRouter = (url) => {
+        if (!Object(environment["c" /* env */])().getBool("IS_BROWSER")) {
+          return null;
+        } else {
+          if (!Array.isArray(url) && url.startsWith(browser_files_BrowserDownloads.URL_SCHEME)) {
+            return browserDownloads(url.slice(browser_files_BrowserDownloads.URL_SCHEME.length));
+          } else {
+            return null;
+          }
+        }
+      };
+      IORouterRegistry.registerSaveRouter(browserDownloadsRouter);
+      /**
+       * Creates an IOHandler that triggers file downloads from the browser.
+       *
+       * The returned `IOHandler` instance can be used as model exporting methods such
+       * as `tf.Model.save` and supports only saving.
+       *
+       * ```js
+       * const model = tf.sequential();
+       * model.add(tf.layers.dense(
+       *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
+       * const saveResult = await model.save('downloads://mymodel');
+       * // This will trigger downloading of two files:
+       * //   'mymodel.json' and 'mymodel.weights.bin'.
+       * console.log(saveResult);
+       * ```
+       *
+       * @param fileNamePrefix Prefix name of the files to be downloaded. For use with
+       *   `tf.Model`, `fileNamePrefix` should follow either of the following two
+       *   formats:
+       *   1. `null` or `undefined`, in which case the default file
+       *      names will be used:
+       *      - 'model.json' for the JSON file containing the model topology and
+       *        weights manifest.
+       *      - 'model.weights.bin' for the binary file containing the binary weight
+       *        values.
+       *   2. A single string or an Array of a single string, as the file name prefix.
+       *      For example, if `'foo'` is provided, the downloaded JSON
+       *      file and binary weights file will be named 'foo.json' and
+       *      'foo.weights.bin', respectively.
+       * @param config Additional configuration for triggering downloads.
+       * @returns An instance of `BrowserDownloads` `IOHandler`.
+       */
+      /**
+       * @doc {
+       *   heading: 'Models',
+       *   subheading: 'Loading',
+       *   namespace: 'io',
+       *   ignoreCI: true
+       * }
+       */
+      function browserDownloads(fileNamePrefix = "model") {
+        return new browser_files_BrowserDownloads(fileNamePrefix);
+      }
+      /**
+       * Creates an IOHandler that loads model artifacts from user-selected files.
+       *
+       * This method can be used for loading from files such as user-selected files
+       * in the browser.
+       * When used in conjunction with `tf.loadLayersModel`, an instance of
+       * `tf.LayersModel` (Keras-style) can be constructed from the loaded artifacts.
+       *
+       * ```js
+       * // Note: This code snippet won't run properly without the actual file input
+       * //   elements in the HTML DOM.
+       *
+       * // Suppose there are two HTML file input (`<input type="file" ...>`)
+       * // elements.
+       * const uploadJSONInput = document.getElementById('upload-json');
+       * const uploadWeightsInput = document.getElementById('upload-weights');
+       * const model = await tf.loadLayersModel(tf.io.browserFiles(
+       *     [uploadJSONInput.files[0], uploadWeightsInput.files[0]]));
+       * ```
+       *
+       * @param files `File`s to load from. Currently, this function supports only
+       *   loading from files that contain Keras-style models (i.e., `tf.Model`s), for
+       *   which an `Array` of `File`s is expected (in that order):
+       *   - A JSON file containing the model topology and weight manifest.
+       *   - Optionally, One or more binary files containing the binary weights.
+       *     These files must have names that match the paths in the `weightsManifest`
+       *     contained by the aforementioned JSON file, or errors will be thrown
+       *     during loading. These weights files have the same format as the ones
+       *     generated by `tensorflowjs_converter` that comes with the `tensorflowjs`
+       *     Python PIP package. If no weights files are provided, only the model
+       *     topology will be loaded from the JSON file above.
+       * @returns An instance of `Files` `IOHandler`.
+       */
+      /**
+       * @doc {
+       *   heading: 'Models',
+       *   subheading: 'Loading',
+       *   namespace: 'io',
+       *   ignoreCI: true
+       * }
+       */
+      function browserFiles(files) {
+        return new browser_files_BrowserFiles(files);
+      }
+      //# sourceMappingURL=browser_files.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/progress.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Monitor Promise.all progress, fire onProgress callback function.
+       *
+       * @param promises Promise list going to be monitored
+       * @param onProgress Callback function. Fired when a promise resolved.
+       * @param startFraction Optional fraction start. Default to 0.
+       * @param endFraction Optional fraction end. Default to 1.
+       */
+      function monitorPromisesProgress(promises, onProgress, startFraction, endFraction) {
+        checkPromises(promises);
+        startFraction = startFraction == null ? 0 : startFraction;
+        endFraction = endFraction == null ? 1 : endFraction;
+        checkFraction(startFraction, endFraction);
+        let resolvedPromise = 0;
+        const registerMonitor = (promise) => {
+          promise.then((value) => {
+            const fraction =
+              startFraction + (++resolvedPromise / promises.length) * (endFraction - startFraction);
+            // pass fraction as parameter to callback function.
+            onProgress(fraction);
+            return value;
+          });
+          return promise;
+        };
+        function checkPromises(promises) {
+          Object(util["assert"])(
+            promises != null && Array.isArray(promises) && promises.length > 0,
+            () => "promises must be a none empty array"
+          );
+        }
+        function checkFraction(startFraction, endFraction) {
+          Object(util["assert"])(
+            startFraction >= 0 && startFraction <= 1,
+            () =>
+              `Progress fraction must be in range [0, 1], but ` +
+              `got startFraction ${startFraction}`
+          );
+          Object(util["assert"])(
+            endFraction >= 0 && endFraction <= 1,
+            () =>
+              `Progress fraction must be in range [0, 1], but ` + `got endFraction ${endFraction}`
+          );
+          Object(util["assert"])(
+            endFraction >= startFraction,
+            () =>
+              `startFraction must be no more than endFraction, but ` +
+              `got startFraction ${startFraction} and endFraction ` +
+              `${endFraction}`
+          );
+        }
+        return Promise.all(promises.map(registerMonitor));
+      }
+      //# sourceMappingURL=progress.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/types.js
+      var types = __webpack_require__(34);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/weights_loader.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Reads binary weights data from a number of URLs.
+       *
+       * @param fetchURLs URLs to send the HTTP requests at, using `fetch` calls.
+       * @param requestOptions RequestInit (options) for the HTTP requests.
+       * @param fetchFunc Optional overriding value for the `window.fetch` function.
+       * @param onProgress Optional, progress callback function, fired periodically
+       *   before the load is completed.
+       * @returns A `Promise` of an Array of `ArrayBuffer`. The Array has the same
+       *   length as `fetchURLs`.
+       */
+      async function loadWeightsAsArrayBuffer(fetchURLs, loadOptions) {
+        if (loadOptions == null) {
+          loadOptions = {};
+        }
+        const fetchFunc =
+          loadOptions.fetchFunc == null
+            ? Object(environment["c" /* env */])().platform.fetch
+            : loadOptions.fetchFunc;
+        // Create the requests for all of the weights in parallel.
+        const requests = fetchURLs.map((fetchURL) =>
+          fetchFunc(fetchURL, loadOptions.requestInit, { isBinary: true })
+        );
+        const fetchStartFraction = 0;
+        const fetchEndFraction = 0.5;
+        const responses =
+          loadOptions.onProgress == null
+            ? await Promise.all(requests)
+            : await monitorPromisesProgress(
+                requests,
+                loadOptions.onProgress,
+                fetchStartFraction,
+                fetchEndFraction
+              );
+        const bufferPromises = responses.map((response) => response.arrayBuffer());
+        const bufferStartFraction = 0.5;
+        const bufferEndFraction = 1;
+        const buffers =
+          loadOptions.onProgress == null
+            ? await Promise.all(bufferPromises)
+            : await monitorPromisesProgress(
+                bufferPromises,
+                loadOptions.onProgress,
+                bufferStartFraction,
+                bufferEndFraction
+              );
+        return buffers;
+      }
+      /**
+       * Reads a weights manifest JSON configuration, fetches the weights and
+       * returns them as `Tensor`s.
+       *
+       * @param manifest The weights manifest JSON.
+       * @param filePathPrefix The path prefix for filenames given in the manifest.
+       *     Defaults to the empty string.
+       * @param weightNames The names of the weights to be fetched.
+       */
+      async function loadWeights(manifest, filePathPrefix = "", weightNames, requestInit) {
+        // TODO(nsthorat): Groups are currently fetched atomically. If you need a
+        // single weight from a group, the whole group will be fetched. At a future
+        // date, we should support fetching only the individual shards within a
+        // group that are needed to reconstruct the requested weight.
+        // TODO(cais): Use `decodeWeights` for implementation.
+        const fetchWeights = (fetchUrls) => loadWeightsAsArrayBuffer(fetchUrls, { requestInit });
+        const loadWeights = weightsLoaderFactory(fetchWeights);
+        return loadWeights(manifest, filePathPrefix, weightNames);
+      }
+      /**
+       * Creates a function, which reads a weights manifest JSON configuration,
+       * fetches the weight files using the specified function and returns them as
+       * `Tensor`s.
+       *
+       * ```js
+       * // example for creating a nodejs weight loader, which reads the weight files
+       * // from disk using fs.readFileSync
+       *
+       * import * as fs from 'fs'
+       *
+       * const fetchWeightsFromDisk = (filePaths: string[]) =>
+       *   filePaths.map(filePath => fs.readFileSync(filePath).buffer)
+       *
+       * const loadWeights = tf.io.weightsLoaderFactory(fetchWeightsFromDisk)
+       *
+       * const manifest = JSON.parse(
+       *   fs.readFileSync('./my_model-weights_manifest').toString()
+       * )
+       * const weightMap = await loadWeights(manifest, './')
+       * ```
+       * @param fetchWeightsFunction The function used for fetching the weight files.
+       * @returns Weight loading function.
+       */
+      function weightsLoaderFactory(fetchWeightsFunction) {
+        return async (manifest, filePathPrefix = "", weightNames) => {
+          // Collect all the groups, weights, and their relative offsets to be
+          // fetched.
+          const groupIndicesToFetchMap = manifest.map(() => false);
+          const groupWeightsToFetch = {};
+          const weightsFound = weightNames != null ? weightNames.map(() => false) : [];
+          const allManifestWeightNames = [];
+          manifest.forEach((manifestGroupConfig, groupIndex) => {
+            let groupOffset = 0;
+            manifestGroupConfig.weights.forEach((weightsEntry) => {
+              const rawDtype =
+                "quantization" in weightsEntry
+                  ? weightsEntry.quantization.dtype
+                  : weightsEntry.dtype;
+              const weightsBytes =
+                types["a" /* DTYPE_VALUE_SIZE_MAP */][rawDtype] *
+                util["sizeFromShape"](weightsEntry.shape);
+              const enqueueWeightsForFetchingFn = () => {
+                groupIndicesToFetchMap[groupIndex] = true;
+                if (groupWeightsToFetch[groupIndex] == null) {
+                  groupWeightsToFetch[groupIndex] = [];
+                }
+                groupWeightsToFetch[groupIndex].push({
+                  manifestEntry: weightsEntry,
+                  groupOffset,
+                  sizeBytes: weightsBytes,
+                });
+              };
+              if (weightNames != null) {
+                weightNames.forEach((weightName, weightIndex) => {
+                  if (weightName === weightsEntry.name) {
+                    enqueueWeightsForFetchingFn();
+                    weightsFound[weightIndex] = true;
+                  }
+                });
+              } else {
+                enqueueWeightsForFetchingFn();
+              }
+              allManifestWeightNames.push(weightsEntry.name);
+              groupOffset += weightsBytes;
+            });
+          });
+          if (!weightsFound.every((found) => found)) {
+            const weightsNotFound = weightNames.filter((_, i) => !weightsFound[i]);
+            throw new Error(
+              `Could not find weights in manifest with names: ` +
+                `${weightsNotFound.join(", ")}. \n` +
+                `Manifest JSON has weights with names: ` +
+                `${allManifestWeightNames.join(", ")}.`
+            );
+          }
+          // Convert the one-hot boolean groupId => shouldFetch map to a list of group
+          // IDs.
+          const groupIndicesToFetch = groupIndicesToFetchMap.reduce(
+            (accumulator, shouldFetch, i) => {
+              if (shouldFetch) {
+                accumulator.push(i);
+              }
+              return accumulator;
+            },
+            []
+          );
+          const fetchUrls = [];
+          groupIndicesToFetch.forEach((i) => {
+            manifest[i].paths.forEach((filepath) => {
+              const fetchUrl =
+                filePathPrefix + (!filePathPrefix.endsWith("/") ? "/" : "") + filepath;
+              fetchUrls.push(fetchUrl);
+            });
+          });
+          const buffers = await fetchWeightsFunction(fetchUrls);
+          const weightsTensorMap = {};
+          let bufferIndexOffset = 0;
+          groupIndicesToFetch.forEach((i) => {
+            const numBuffers = manifest[i].paths.length;
+            let groupBytes = 0;
+            for (let i = 0; i < numBuffers; i++) {
+              groupBytes += buffers[bufferIndexOffset + i].byteLength;
+            }
+            // Create a buffer for the whole group.
+            const groupBuffer = new ArrayBuffer(groupBytes);
+            const groupByteBuffer = new Uint8Array(groupBuffer);
+            let groupBufferOffset = 0;
+            for (let i = 0; i < numBuffers; i++) {
+              const buffer = new Uint8Array(buffers[bufferIndexOffset + i]);
+              groupByteBuffer.set(buffer, groupBufferOffset);
+              groupBufferOffset += buffer.byteLength;
+            }
+            const weightsEntries = groupWeightsToFetch[i];
+            weightsEntries.forEach((weightsEntry) => {
+              const byteBuffer = groupBuffer.slice(
+                weightsEntry.groupOffset,
+                weightsEntry.groupOffset + weightsEntry.sizeBytes
+              );
+              const nameToTensorMap = Object(io_utils["e" /* decodeWeights */])(byteBuffer, [
+                weightsEntry.manifestEntry,
+              ]);
+              for (const name in nameToTensorMap) {
+                weightsTensorMap[name] = nameToTensorMap[name];
+              }
+            });
+            bufferIndexOffset += numBuffers;
+          });
+          return weightsTensorMap;
+        };
+      }
+      //# sourceMappingURL=weights_loader.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/http.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * IOHandler implementations based on HTTP requests in the web browser.
+       *
+       * Uses [`fetch`](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API).
+       */
+
+      const OCTET_STREAM_MIME_TYPE = "application/octet-stream";
+      const JSON_TYPE = "application/json";
+      class http_HTTPRequest {
+        constructor(path, loadOptions) {
+          this.DEFAULT_METHOD = "POST";
+          if (loadOptions == null) {
+            loadOptions = {};
+          }
+          this.weightPathPrefix = loadOptions.weightPathPrefix;
+          this.onProgress = loadOptions.onProgress;
+          if (loadOptions.fetchFunc != null) {
+            Object(util["assert"])(
+              typeof loadOptions.fetchFunc === "function",
+              () =>
+                "Must pass a function that matches the signature of " +
+                "`fetch` (see " +
+                "https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"
+            );
+            this.fetch = loadOptions.fetchFunc;
+          } else {
+            this.fetch = Object(environment["c" /* env */])().platform.fetch;
+          }
+          Object(util["assert"])(
+            path != null && path.length > 0,
+            () => "URL path for http must not be null, undefined or " + "empty."
+          );
+          if (Array.isArray(path)) {
+            Object(util["assert"])(
+              path.length === 2,
+              () =>
+                "URL paths for http must have a length of 2, " +
+                `(actual length is ${path.length}).`
+            );
+          }
+          this.path = path;
+          if (loadOptions.requestInit != null && loadOptions.requestInit.body != null) {
+            throw new Error("requestInit is expected to have no pre-existing body, but has one.");
+          }
+          this.requestInit = loadOptions.requestInit || {};
+        }
+        async save(modelArtifacts) {
+          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
+            throw new Error(
+              "BrowserHTTPRequest.save() does not support saving model topology " +
+                "in binary formats yet."
+            );
+          }
+          const init = Object.assign({ method: this.DEFAULT_METHOD }, this.requestInit);
+          init.body = new FormData();
+          const weightsManifest = [
+            {
+              paths: ["./model.weights.bin"],
+              weights: modelArtifacts.weightSpecs,
+            },
+          ];
+          const modelTopologyAndWeightManifest = {
+            modelTopology: modelArtifacts.modelTopology,
+            format: modelArtifacts.format,
+            generatedBy: modelArtifacts.generatedBy,
+            convertedBy: modelArtifacts.convertedBy,
+            userDefinedMetadata: modelArtifacts.userDefinedMetadata,
+            weightsManifest,
+          };
+          init.body.append(
+            "model.json",
+            new Blob([JSON.stringify(modelTopologyAndWeightManifest)], { type: JSON_TYPE }),
+            "model.json"
+          );
+          if (modelArtifacts.weightData != null) {
+            init.body.append(
+              "model.weights.bin",
+              new Blob([modelArtifacts.weightData], { type: OCTET_STREAM_MIME_TYPE }),
+              "model.weights.bin"
+            );
+          }
+          const response = await this.fetch(this.path, init);
+          if (response.ok) {
+            return {
+              modelArtifactsInfo: Object(io_utils["g" /* getModelArtifactsInfoForJSON */])(
+                modelArtifacts
+              ),
+              responses: [response],
+            };
+          } else {
+            throw new Error(
+              `BrowserHTTPRequest.save() failed due to HTTP response status ` +
+                `${response.status}.`
+            );
+          }
+        }
+        /**
+         * Load model artifacts via HTTP request(s).
+         *
+         * See the documentation to `tf.io.http` for details on the saved
+         * artifacts.
+         *
+         * @returns The loaded model artifacts (if loading succeeds).
+         */
+        async load() {
+          const modelConfigRequest = await this.fetch(this.path, this.requestInit);
+          if (!modelConfigRequest.ok) {
+            throw new Error(
+              `Request to ${this.path} failed with status code ` +
+                `${modelConfigRequest.status}. Please verify this URL points to ` +
+                `the model JSON of the model to load.`
+            );
+          }
+          let modelConfig;
+          try {
+            modelConfig = await modelConfigRequest.json();
+          } catch (e) {
+            let message = `Failed to parse model JSON of response from ${this.path}.`;
+            // TODO(nsthorat): Remove this after some time when we're comfortable that
+            // .pb files are mostly gone.
+            if (this.path.endsWith(".pb")) {
+              message +=
+                " Your path contains a .pb file extension. " +
+                "Support for .pb models have been removed in TensorFlow.js 1.0 " +
+                "in favor of .json models. You can re-convert your Python " +
+                "TensorFlow model using the TensorFlow.js 1.0 conversion scripts " +
+                "or you can convert your.pb models with the 'pb2json'" +
+                "NPM script in the tensorflow/tfjs-converter repository.";
+            } else {
+              message +=
+                " Please make sure the server is serving valid " + "JSON for this request.";
+            }
+            throw new Error(message);
+          }
+          const modelTopology = modelConfig.modelTopology;
+          const weightsManifest = modelConfig.weightsManifest;
+          const generatedBy = modelConfig.generatedBy;
+          const convertedBy = modelConfig.convertedBy;
+          const format = modelConfig.format;
+          const userDefinedMetadata = modelConfig.userDefinedMetadata;
+          // We do not allow both modelTopology and weightsManifest to be missing.
+          if (modelTopology == null && weightsManifest == null) {
+            throw new Error(
+              `The JSON from HTTP path ${this.path} contains neither model ` +
+                `topology or manifest for weights.`
+            );
+          }
+          let weightSpecs;
+          let weightData;
+          if (weightsManifest != null) {
+            const results = await this.loadWeights(weightsManifest);
+            [weightSpecs, weightData] = results;
+          }
+          return {
+            modelTopology,
+            weightSpecs,
+            weightData,
+            userDefinedMetadata,
+            generatedBy,
+            convertedBy,
+            format,
+          };
+        }
+        async loadWeights(weightsManifest) {
+          const weightPath = Array.isArray(this.path) ? this.path[1] : this.path;
+          const [prefix, suffix] = parseUrl(weightPath);
+          const pathPrefix = this.weightPathPrefix || prefix;
+          const weightSpecs = [];
+          for (const entry of weightsManifest) {
+            weightSpecs.push(...entry.weights);
+          }
+          const fetchURLs = [];
+          weightsManifest.forEach((weightsGroup) => {
+            weightsGroup.paths.forEach((path) => {
+              fetchURLs.push(pathPrefix + path + suffix);
+            });
+          });
+          const buffers = await loadWeightsAsArrayBuffer(fetchURLs, {
+            requestInit: this.requestInit,
+            fetchFunc: this.fetch,
+            onProgress: this.onProgress,
+          });
+          return [weightSpecs, Object(io_utils["d" /* concatenateArrayBuffers */])(buffers)];
+        }
+      }
+      http_HTTPRequest.URL_SCHEME_REGEX = /^https?:\/\//;
+      /**
+       * Extract the prefix and suffix of the url, where the prefix is the path before
+       * the last file, and suffix is the search params after the last file.
+       * ```
+       * const url = 'http://tfhub.dev/model/1/tensorflowjs_model.pb?tfjs-format=file'
+       * [prefix, suffix] = parseUrl(url)
+       * // prefix = 'http://tfhub.dev/model/1/'
+       * // suffix = '?tfjs-format=file'
+       * ```
+       * @param url the model url to be parsed.
+       */
+      function parseUrl(url) {
+        const lastSlash = url.lastIndexOf("/");
+        const lastSearchParam = url.lastIndexOf("?");
+        const prefix = url.substring(0, lastSlash);
+        const suffix = lastSearchParam > lastSlash ? url.substring(lastSearchParam) : "";
+        return [prefix + "/", suffix];
+      }
+      function isHTTPScheme(url) {
+        return url.match(http_HTTPRequest.URL_SCHEME_REGEX) != null;
+      }
+      const httpRouter = (url, loadOptions) => {
+        if (
+          typeof fetch === "undefined" &&
+          (loadOptions == null || loadOptions.fetchFunc == null)
+        ) {
+          // `http` uses `fetch` or `node-fetch`, if one wants to use it in
+          // an environment that is not the browser or node they have to setup a
+          // global fetch polyfill.
+          return null;
+        } else {
+          let isHTTP = true;
+          if (Array.isArray(url)) {
+            isHTTP = url.every((urlItem) => isHTTPScheme(urlItem));
+          } else {
+            isHTTP = isHTTPScheme(url);
+          }
+          if (isHTTP) {
+            return http(url, loadOptions);
+          }
+        }
+        return null;
+      };
+      IORouterRegistry.registerSaveRouter(httpRouter);
+      IORouterRegistry.registerLoadRouter(httpRouter);
+      /**
+       * Creates an IOHandler subtype that sends model artifacts to HTTP server.
+       *
+       * An HTTP request of the `multipart/form-data` mime type will be sent to the
+       * `path` URL. The form data includes artifacts that represent the topology
+       * and/or weights of the model. In the case of Keras-style `tf.Model`, two
+       * blobs (files) exist in form-data:
+       *   - A JSON file consisting of `modelTopology` and `weightsManifest`.
+       *   - A binary weights file consisting of the concatenated weight values.
+       * These files are in the same format as the one generated by
+       * [tfjs_converter](https://js.tensorflow.org/tutorials/import-keras.html).
+       *
+       * The following code snippet exemplifies the client-side code that uses this
+       * function:
+       *
+       * ```js
+       * const model = tf.sequential();
+       * model.add(
+       *     tf.layers.dense({units: 1, inputShape: [100], activation: 'sigmoid'}));
+       *
+       * const saveResult = await model.save(tf.io.http(
+       *     'http://model-server:5000/upload', {requestInit: {method: 'PUT'}}));
+       * console.log(saveResult);
+       * ```
+       *
+       * If the default `POST` method is to be used, without any custom parameters
+       * such as headers, you can simply pass an HTTP or HTTPS URL to `model.save`:
+       *
+       * ```js
+       * const saveResult = await model.save('http://model-server:5000/upload');
+       * ```
+       *
+       * The following GitHub Gist
+       * https://gist.github.com/dsmilkov/1b6046fd6132d7408d5257b0976f7864
+       * implements a server based on [flask](https://github.com/pallets/flask) that
+       * can receive the request. Upon receiving the model artifacts via the requst,
+       * this particular server reconsistutes instances of [Keras
+       * Models](https://keras.io/models/model/) in memory.
+       *
+       *
+       * @param path A URL path to the model.
+       *   Can be an absolute HTTP path (e.g.,
+       *   'http://localhost:8000/model-upload)') or a relative path (e.g.,
+       *   './model-upload').
+       * @param requestInit Request configurations to be used when sending
+       *    HTTP request to server using `fetch`. It can contain fields such as
+       *    `method`, `credentials`, `headers`, `mode`, etc. See
+       *    https://developer.mozilla.org/en-US/docs/Web/API/Request/Request
+       *    for more information. `requestInit` must not have a body, because the
+       * body will be set by TensorFlow.js. File blobs representing the model
+       * topology (filename: 'model.json') and the weights of the model (filename:
+       * 'model.weights.bin') will be appended to the body. If `requestInit` has a
+       * `body`, an Error will be thrown.
+       * @param loadOptions Optional configuration for the loading. It includes the
+       *   following fields:
+       *   - weightPathPrefix Optional, this specifies the path prefix for weight
+       *     files, by default this is calculated from the path param.
+       *   - fetchFunc Optional, custom `fetch` function. E.g., in Node.js,
+       *     the `fetch` from node-fetch can be used here.
+       *   - onProgress Optional, progress callback function, fired periodically
+       *     before the load is completed.
+       * @returns An instance of `IOHandler`.
+       */
+      /**
+       * @doc {
+       *   heading: 'Models',
+       *   subheading: 'Loading',
+       *   namespace: 'io',
+       *   ignoreCI: true
+       * }
+       */
+      function http(path, loadOptions) {
+        return new http_HTTPRequest(path, loadOptions);
+      }
+      /**
+       * Deprecated. Use `tf.io.http`.
+       * @param path
+       * @param loadOptions
+       */
+      function browserHTTPRequest(path, loadOptions) {
+        return http(path, loadOptions);
+      }
+      //# sourceMappingURL=http.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/passthrough.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class PassthroughLoader {
+        constructor(modelArtifacts) {
+          this.modelArtifacts = modelArtifacts;
+        }
+        async load() {
+          return this.modelArtifacts;
+        }
+      }
+      class PassthroughSaver {
+        constructor(saveHandler) {
+          this.saveHandler = saveHandler;
+        }
+        async save(modelArtifacts) {
+          return this.saveHandler(modelArtifacts);
+        }
+      }
+      /**
+       * Creates an IOHandler that loads model artifacts from memory.
+       *
+       * When used in conjunction with `tf.loadLayersModel`, an instance of
+       * `tf.LayersModel` (Keras-style) can be constructed from the loaded artifacts.
+       *
+       * ```js
+       * const model = await tf.loadLayersModel(tf.io.fromMemory(
+       *     modelTopology, weightSpecs, weightData));
+       * ```
+       *
+       * @param modelArtifacts a object containing model topology (i.e., parsed from
+       *   the JSON format).
+       * @param weightSpecs An array of `WeightsManifestEntry` objects describing the
+       *   names, shapes, types, and quantization of the weight data.
+       * @param weightData A single `ArrayBuffer` containing the weight data,
+       *   concatenated in the order described by the weightSpecs.
+       * @param trainingConfig Model training configuration. Optional.
+       *
+       * @returns A passthrough `IOHandler` that simply loads the provided data.
+       */
+      function fromMemory(modelArtifacts, weightSpecs, weightData, trainingConfig) {
+        if (arguments.length === 1) {
+          const isModelArtifacts =
+            modelArtifacts.modelTopology != null || modelArtifacts.weightSpecs != null;
+          if (isModelArtifacts) {
+            return new PassthroughLoader(modelArtifacts);
+          } else {
+            // Legacy support: with only modelTopology.
+            // TODO(cais): Remove this deprecated API.
+            console.warn(
+              "Please call tf.io.fromMemory() with only one argument. " +
+                "The argument should be of type ModelArtifacts. " +
+                "The multi-argument signature of tf.io.fromMemory() has been " +
+                "deprecated and will be removed in a future release."
+            );
+            return new PassthroughLoader({ modelTopology: modelArtifacts });
+          }
+        } else {
+          // Legacy support.
+          // TODO(cais): Remove this deprecated API.
+          console.warn(
+            "Please call tf.io.fromMemory() with only one argument. " +
+              "The argument should be of type ModelArtifacts. " +
+              "The multi-argument signature of tf.io.fromMemory() has been " +
+              "deprecated and will be removed in a future release."
+          );
+          return new PassthroughLoader({
+            modelTopology: modelArtifacts,
+            weightSpecs,
+            weightData,
+            trainingConfig,
+          });
+        }
+      }
+      /**
+       * Creates an IOHandler that passes saved model artifacts to a callback.
+       *
+       * ```js
+       * function handleSave(artifacts) {
+       *   // ... do something with the artifacts ...
+       *   return {modelArtifactsInfo: {...}, ...};
+       * }
+       *
+       * const saveResult = model.save(tf.io.withSaveHandler(handleSave));
+       * ```
+       *
+       * @param saveHandler A function that accepts a `ModelArtifacts` and returns a
+       *     `SaveResult`.
+       */
+      function withSaveHandler(saveHandler) {
+        return new PassthroughSaver(saveHandler);
+      }
+      //# sourceMappingURL=passthrough.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/io/io.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // Importing local_storage and indexed_db is necessary for the routers to be
+      // registered.
+
+      //# sourceMappingURL=io.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/one_hot.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a one-hot `tf.Tensor`. The locations represented by `indices` take
+       * value `onValue` (defaults to 1), while all other locations take value
+       * `offValue` (defaults to 0). If `indices` is rank `R`, the output has rank
+       * `R+1` with the last axis of size `depth`.
+       *
+       * ```js
+       * tf.oneHot(tf.tensor1d([0, 1], 'int32'), 3).print();
+       * ```
+       *
+       * @param indices `tf.Tensor` of indices with dtype `int32`.
+       * @param depth The depth of the one hot dimension.
+       * @param onValue A number used to fill in the output when the index matches
+       * the location.
+       * @param offValue A number used to fill in the output when the index does
+       *     not match the location.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function oneHot_(indices, depth, onValue = 1, offValue = 0) {
+        if (depth < 2) {
+          throw new Error(`Error in oneHot: depth must be >=2, but it is ${depth}`);
+        }
+        let $indices = Object(tensor_util_env["a" /* convertToTensor */])(
+          indices,
+          "indices",
+          "oneHot",
+          "int32"
+        );
+        const outShape = [...$indices.shape, depth];
+        $indices = $indices.flatten();
+        const forward = (backend, save) => {
+          save([$indices]);
+          return reshape(backend.oneHot($indices, depth, onValue, offValue), outShape);
+        };
+        const inputs = { indices: $indices };
+        const attrs = { depth, onValue, offValue };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["cb" /* OneHot */],
+          attrs
+        );
+      }
+      const oneHot = Object(operation["a" /* op */])({ oneHot_ });
+      //# sourceMappingURL=one_hot.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/confusion_matrix.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the confusion matrix from true labels and predicted labels.
+       *
+       * ```js
+       * const labels = tf.tensor1d([0, 1, 2, 1, 0], 'int32');
+       * const predictions = tf.tensor1d([0, 2, 2, 1, 0], 'int32');
+       * const numClasses = 3;
+       * const out = tf.math.confusionMatrix(labels, predictions, numClasses);
+       * out.print();
+       * // Expected output matrix:
+       * // [[2, 0, 0],
+       * //  [0, 1, 1],
+       * //  [0, 0, 1]]
+       * ```
+       *
+       * @param labels The target labels, assumed to be 0-based integers
+       *   for the classes. The shape is `[numExamples]`, where
+       *   `numExamples` is the number of examples included.
+       * @param predictions The predicted classes, assumed to be
+       *   0-based integers for the classes. Must have the same shape as `labels`.
+       * @param numClasses Number of all classes, as an integer.
+       *   Its value must be larger than the largest element in `labels` and
+       *   `predictions`.
+       * @returns The confusion matrix as a int32-type 2D tensor. The value at
+       *   row `r` and column `c` is the number of times examples of actual class
+       *   `r` were predicted as class `c`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Evaluation'} */
+      function confusionMatrix_(labels, predictions, numClasses) {
+        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
+          labels,
+          "labels",
+          "confusionMatrix"
+        );
+        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
+          predictions,
+          "predictions",
+          "confusionMatrix"
+        );
+        util["assert"](
+          numClasses == null || (numClasses > 0 && Number.isInteger(numClasses)),
+          () => `If provided, numClasses must be a positive integer, ` + `but got ${numClasses}`
+        );
+        util["assert"](
+          $labels.rank === 1,
+          () => `Expected the rank of labels to be 1, but got ${$labels.rank}`
+        );
+        util["assert"](
+          $predictions.rank === 1,
+          () => `Expected the rank of predictions to be 1, ` + `but got ${$predictions.rank}`
+        );
+        util["assert"](
+          $labels.shape[0] === $predictions.shape[0],
+          () =>
+            `Mismatch in the number of examples: ` +
+            `${$labels.shape[0]} vs. ${$predictions.shape[0]}. ` +
+            `Labels and predictions should have the same number of elements.`
+        );
+        util["assert"](
+          numClasses > 0 && Number.isInteger(numClasses),
+          () => `numClasses is required to be a positive integer, but got ` + `${numClasses}`
+        );
+        // TODO(cais): In the future, if oneHot supports tensors inputs for
+        //   `numClasses`, `confusionMatrix` can make `numClasses` optional.
+        const oneHotLabels = oneHot($labels.asType("int32"), numClasses);
+        const oneHotPredictions = oneHot($predictions.asType("int32"), numClasses);
+        const oneHotLabelsT = oneHotLabels.transpose();
+        return oneHotLabelsT.matMul(oneHotPredictions).asType("int32");
+      }
+      const confusionMatrix = Object(operation["a" /* op */])({ confusionMatrix_ });
+      //# sourceMappingURL=confusion_matrix.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/math.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Exports under the tf.math.* namespace.
+       */
+
+      //# sourceMappingURL=math.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/browser.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      let fromPixels2DContext;
+      /**
+       * Creates a `tf.Tensor` from an image.
+       *
+       * ```js
+       * const image = new ImageData(1, 1);
+       * image.data[0] = 100;
+       * image.data[1] = 150;
+       * image.data[2] = 200;
+       * image.data[3] = 255;
+       *
+       * tf.browser.fromPixels(image).print();
+       * ```
+       *
+       * @param pixels The input image to construct the tensor from. The
+       * supported image types are all 4-channel. You can also pass in an image
+       * object with following attributes:
+       * `{data: Uint8Array; width: number; height: number}`
+       * @param numChannels The number of channels of the output tensor. A
+       * numChannels value less than 4 allows you to ignore channels. Defaults to
+       * 3 (ignores alpha channel of input image).
+       */
+      /** @doc {heading: 'Browser', namespace: 'browser', ignoreCI: true} */
+      function fromPixels_(pixels, numChannels = 3) {
+        // Sanity checks.
+        if (numChannels > 4) {
+          throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");
+        }
+        if (pixels == null) {
+          throw new Error("pixels passed to tf.browser.fromPixels() can not be null");
+        }
+        let isPixelData = false;
+        let isImageData = false;
+        let isVideo = false;
+        let isImage = false;
+        let isCanvasLike = false;
+        if (pixels.data instanceof Uint8Array) {
+          isPixelData = true;
+        } else if (typeof ImageData !== "undefined" && pixels instanceof ImageData) {
+          isImageData = true;
+        } else if (typeof HTMLVideoElement !== "undefined" && pixels instanceof HTMLVideoElement) {
+          isVideo = true;
+        } else if (typeof HTMLImageElement !== "undefined" && pixels instanceof HTMLImageElement) {
+          isImage = true;
+          // tslint:disable-next-line: no-any
+        } else if (pixels.getContext != null) {
+          isCanvasLike = true;
+        } else {
+          throw new Error(
+            "pixels passed to tf.browser.fromPixels() must be either an " +
+              `HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData ` +
+              `in browser, or OffscreenCanvas, ImageData in webworker` +
+              ` or {data: Uint32Array, width: number, height: number}, ` +
+              `but was ${pixels.constructor.name}`
+          );
+        }
+        if (isVideo) {
+          const HAVE_CURRENT_DATA_READY_STATE = 2;
+          if (isVideo && pixels.readyState < HAVE_CURRENT_DATA_READY_STATE) {
+            throw new Error(
+              "The video element has not loaded data yet. Please wait for " +
+                "`loadeddata` event on the <video> element."
+            );
+          }
+        }
+        // If the current backend has 'FromPixels' registered, it has a more
+        // efficient way of handling pixel uploads, so we call that.
+        const kernel = Object(kernel_registry["b" /* getKernel */])(
+          kernel_names["E" /* FromPixels */],
+          engine["a" /* ENGINE */].backendName
+        );
+        if (kernel != null) {
+          const inputs = { pixels };
+          const attrs = { numChannels };
+          return engine["a" /* ENGINE */].runKernel(
+            kernel_names["E" /* FromPixels */],
+            inputs,
+            attrs
+          );
+        }
+        const [width, height] = isVideo
+          ? [pixels.videoWidth, pixels.videoHeight]
+          : [pixels.width, pixels.height];
+        let vals;
+        if (isCanvasLike) {
+          vals =
+            // tslint:disable-next-line:no-any
+            pixels.getContext("2d").getImageData(0, 0, width, height).data;
+        } else if (isImageData || isPixelData) {
+          vals = pixels.data;
+        } else if (isImage || isVideo) {
+          if (fromPixels2DContext == null) {
+            fromPixels2DContext = document.createElement("canvas").getContext("2d");
+          }
+          fromPixels2DContext.canvas.width = width;
+          fromPixels2DContext.canvas.height = height;
+          fromPixels2DContext.drawImage(pixels, 0, 0, width, height);
+          vals = fromPixels2DContext.getImageData(0, 0, width, height).data;
+        }
+        let values;
+        if (numChannels === 4) {
+          values = new Int32Array(vals);
+        } else {
+          const numPixels = width * height;
+          values = new Int32Array(numPixels * numChannels);
+          for (let i = 0; i < numPixels; i++) {
+            for (let channel = 0; channel < numChannels; ++channel) {
+              values[i * numChannels + channel] = vals[i * 4 + channel];
+            }
+          }
+        }
+        const outShape = [height, width, numChannels];
+        return Object(tensor_ops["i" /* tensor3d */])(values, outShape, "int32");
+      }
+      /**
+       * Draws a `tf.Tensor` of pixel values to a byte array or optionally a
+       * canvas.
+       *
+       * When the dtype of the input is 'float32', we assume values in the range
+       * [0-1]. Otherwise, when input is 'int32', we assume values in the range
+       * [0-255].
+       *
+       * Returns a promise that resolves when the canvas has been drawn to.
+       *
+       * @param img A rank-2 or rank-3 tensor. If rank-2, draws grayscale. If
+       *     rank-3, must have depth of 1, 3 or 4. When depth of 1, draws
+       * grayscale. When depth of 3, we draw with the first three components of
+       * the depth dimension corresponding to r, g, b and alpha = 1. When depth of
+       * 4, all four components of the depth dimension correspond to r, g, b, a.
+       * @param canvas The canvas to draw to.
+       */
+      /** @doc {heading: 'Browser', namespace: 'browser'} */
+      async function toPixels(img, canvas) {
+        let $img = Object(tensor_util_env["a" /* convertToTensor */])(img, "img", "toPixels");
+        if (!(img instanceof dist_tensor["a" /* Tensor */])) {
+          // Assume int32 if user passed a native array.
+          const originalImgTensor = $img;
+          $img = originalImgTensor.toInt();
+          originalImgTensor.dispose();
+        }
+        if ($img.rank !== 2 && $img.rank !== 3) {
+          throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${$img.rank}.`);
+        }
+        const [height, width] = $img.shape.slice(0, 2);
+        const depth = $img.rank === 2 ? 1 : $img.shape[2];
+        if (depth > 4 || depth === 2) {
+          throw new Error(`toPixels only supports depth of size ` + `1, 3 or 4 but got ${depth}`);
+        }
+        const data = await $img.data();
+        const minTensor = $img.min();
+        const maxTensor = $img.max();
+        const vals = await Promise.all([minTensor.data(), maxTensor.data()]);
+        const minVals = vals[0];
+        const maxVals = vals[1];
+        const min = minVals[0];
+        const max = maxVals[0];
+        minTensor.dispose();
+        maxTensor.dispose();
+        if ($img.dtype === "float32") {
+          if (min < 0 || max > 1) {
+            throw new Error(
+              `Tensor values for a float32 Tensor must be in the ` +
+                `range [0 - 1] but got range [${min} - ${max}].`
+            );
+          }
+        } else if ($img.dtype === "int32") {
+          if (min < 0 || max > 255) {
+            throw new Error(
+              `Tensor values for a int32 Tensor must be in the ` +
+                `range [0 - 255] but got range [${min} - ${max}].`
+            );
+          }
+        } else {
+          throw new Error(
+            `Unsupported type for toPixels: ${$img.dtype}.` +
+              ` Please use float32 or int32 tensors.`
+          );
+        }
+        const multiplier = $img.dtype === "float32" ? 255 : 1;
+        const bytes = new Uint8ClampedArray(width * height * 4);
+        for (let i = 0; i < height * width; ++i) {
+          let r, g, b, a;
+          if (depth === 1) {
+            r = data[i] * multiplier;
+            g = data[i] * multiplier;
+            b = data[i] * multiplier;
+            a = 255;
+          } else if (depth === 3) {
+            r = data[i * 3] * multiplier;
+            g = data[i * 3 + 1] * multiplier;
+            b = data[i * 3 + 2] * multiplier;
+            a = 255;
+          } else if (depth === 4) {
+            r = data[i * 4] * multiplier;
+            g = data[i * 4 + 1] * multiplier;
+            b = data[i * 4 + 2] * multiplier;
+            a = data[i * 4 + 3] * multiplier;
+          }
+          const j = i * 4;
+          bytes[j + 0] = Math.round(r);
+          bytes[j + 1] = Math.round(g);
+          bytes[j + 2] = Math.round(b);
+          bytes[j + 3] = Math.round(a);
+        }
+        if (canvas != null) {
+          canvas.width = width;
+          canvas.height = height;
+          const ctx = canvas.getContext("2d");
+          const imageData = new ImageData(bytes, width, height);
+          ctx.putImageData(imageData, 0, 0);
+        }
+        if ($img !== img) {
+          $img.dispose();
+        }
+        return bytes;
+      }
+      const fromPixels = Object(operation["a" /* op */])({ fromPixels_ });
+      //# sourceMappingURL=browser.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd_util.js
+
+      /**
+       * Validate gather nd inputs.
+       *
+       * @param tensor The tensor contains the source values.
+       * @param indices The tensor contains the indices to slice the source.
+       *
+       * @returns [resultShape, numUpdates, sliceSize, strides]
+       */
+      function prepareAndValidate(tensor, indices) {
+        if (tensor.rank < 1) {
+          throw new Error(
+            "tf.gatherND() expects the input to be rank 1 or higher," +
+              ` but the rank was ${tensor.rank}.`
+          );
+        }
+        if (indices.rank < 1) {
+          throw new Error(
+            "tf.gatherND() expects the indices to be rank 1 or higher," +
+              ` but the rank was ${indices.rank}.`
+          );
+        }
+        if (indices.dtype !== "int32") {
+          throw new Error(
+            "tf.gatherND() expects the indices to be int32 type," +
+              ` but the dtype was ${indices.dtype}.`
+          );
+        }
+        if (indices.shape[indices.rank - 1] > tensor.rank) {
+          throw new Error(
+            "index innermost dimension length must be <= tensor rank; saw: " +
+              `${indices.shape[indices.rank - 1]} vs. ${tensor.rank}`
+          );
+        }
+        if (tensor.size === 0) {
+          throw new Error(
+            "Requested more than 0 entries, but input is empty." + ` Input shape: ${tensor.shape}.`
+          );
+        }
+        const indicesShape = indices.shape;
+        const sliceRank = indicesShape[indicesShape.length - 1];
+        // The result shape is
+        //   indices.shape[:-1] + params.shape[indices.shape[-1]:]
+        let nResult = 1;
+        for (let i = 0; i < indicesShape.length - 1; ++i) {
+          nResult *= indicesShape[i];
+        }
+        const inputShape = tensor.shape;
+        const resultShape = indicesShape.slice();
+        resultShape.pop();
+        let sliceSize = 1;
+        for (let i = sliceRank; i < tensor.rank; ++i) {
+          sliceSize *= inputShape[i];
+          resultShape.push(inputShape[i]);
+        }
+        const strides = [
+          ...Object(util["computeStrides"])(tensor.shape).map((stride) => stride / sliceSize),
+          1,
+        ].slice(0, sliceRank);
+        return [resultShape, nResult, sliceSize, strides];
+      }
+      //# sourceMappingURL=gather_nd_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd_util.js
+
+      /**
+       * Check whether updates.shape = indices.shape[:batchDim] +
+       * shape[sliceDim:]
+       *
+       * @param x The input tensor.
+       */
+      function validateUpdateShape(shape, indices, updates) {
+        const sliceDim = indices.rank > 1 ? indices.shape[indices.rank - 1] : 1;
+        const batchDim = indices.rank > 1 ? indices.rank - 1 : 1;
+        const shapeError =
+          "Must have updates.shape = indices.shape[:batchDim] + " +
+          `shape[sliceDim:], got updates.shape: ${updates.shape}` +
+          `, indices.shape: ${indices.shape}, shape: ${shape}` +
+          `, sliceDim: ${sliceDim}, and batchDim: ${batchDim}.`;
+        if (updates.rank < batchDim) {
+          throw new Error(shapeError + ` update.rank < ${batchDim}. `);
+        }
+        if (shape.length < sliceDim + (updates.rank - batchDim)) {
+          throw new Error(
+            shapeError + ` Output shape length < ${sliceDim + (updates.rank - batchDim)}`
+          );
+        }
+        if (updates.rank !== batchDim + shape.length - sliceDim) {
+          throw new Error(shapeError + ` update.rank != ${batchDim + shape.length - sliceDim}`);
+        }
+        for (let d = 0; d < batchDim; ++d) {
+          if (updates.shape[d] !== indices.shape[d]) {
+            throw new Error(
+              shapeError +
+                ` updates.shape[${d}] (${updates.shape[d]}) != indices.shape[${d}] (${indices.shape[d]}).`
+            );
+          }
+        }
+        for (let d = 0; d < updates.rank - batchDim; ++d) {
+          if (updates.shape[d + batchDim] !== shape[d + sliceDim]) {
+            throw new Error(
+              shapeError +
+                ` updates.shape[${d + batchDim}] (${updates.shape[d + batchDim]}) != shape[${
+                  d + batchDim
+                }] (${shape[d + batchDim]})`
+            );
+          }
+        }
+      }
+      /**
+       * Validate scatter nd inputs.
+       *
+       * @param update The tensor contains the update values.
+       * @param indices The tensor contains the indices for the update values.
+       * @param shape The shape of the output tensor.
+       */
+      function validateInput(updates, indices, shape) {
+        if (indices.rank < 1) {
+          throw new Error(
+            "tf.scatterND() expects the indices to be rank 1 or higher," +
+              ` but the rank was ${indices.rank}.`
+          );
+        }
+        if (updates.rank < 1) {
+          throw new Error(
+            "tf.scatterND() expects the updates to be rank 1 or higher," +
+              ` but the rank was ${updates.rank}.`
+          );
+        }
+        if (indices.dtype !== "int32") {
+          throw new Error(
+            `The dtype of 'indices' should be int32, but got dtype: ${indices.dtype}`
+          );
+        }
+        if (shape.length < 1) {
+          throw new Error(`Output rank must be greater or equal to 1, but got shape: ${shape}`);
+        }
+        if (shape.length === 0) {
+          if (indices.size === 0) {
+            throw new Error(`Indices specified for empty output. indices shape: ${indices.shape}`);
+          }
+          if (updates.size === 0) {
+            throw new Error(`Updates specified for empty output. updates shape: ${updates.shape}`);
+          }
+        }
+        validateUpdateShape(shape, indices, updates);
+      }
+      /**
+       * Calculate the shape information for the output.
+       *
+       * @param update The tensor contains the update values.
+       * @param indices The tensor contains the indices for the update values.
+       * @param shape The shape of the output tensor.
+       *
+       * @returns ScatterShapeInfo
+       */
+      function calculateShapes(updates, indices, shape) {
+        // Calculate the number of dimensions in indices
+        const indicesRank = indices.shape.length;
+        const sliceRank = indicesRank > 1 ? indices.shape[indicesRank - 1] : 1;
+        // Calculate the number of elements that make up each slice of our updated
+        // tensor. This allows us to work with flattened tensors and copy over whole
+        // slices at a time.
+        const totalNd = shape.length;
+        let sliceSize = 1;
+        for (let i = sliceRank; i < totalNd; ++i) {
+          sliceSize *= shape[i];
+        }
+        const safeSliceDim = sliceRank < 1 ? 1 : sliceRank;
+        const numUpdates = Object(util["sizeFromShape"])(indices.shape) / safeSliceDim;
+        const strides = [...Object(util["computeStrides"])(shape.slice(0, sliceRank)), 1];
+        const outputSize = Object(util["sizeFromShape"])(shape);
+        return { sliceRank, numUpdates, sliceSize, strides, outputSize };
+      }
+      //# sourceMappingURL=scatter_nd_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/serialization.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Serializable defines the serialization contract.
+       *
+       * TFJS requires serializable classes to return their className when asked
+       * to avoid issues with minification.
+       */
+      class Serializable {
+        /**
+         * Return the class name for this class to use in serialization contexts.
+         *
+         * Generally speaking this will be the same thing that constructor.name
+         * would have returned.  However, the class name needs to be robust
+         * against minification for serialization/deserialization to work properly.
+         *
+         * There's also places such as initializers.VarianceScaling, where
+         * implementation details between different languages led to different
+         * class hierarchies and a non-leaf node is used for serialization purposes.
+         */
+        getClassName() {
+          return this.constructor.className;
+        }
+        /**
+         * Creates an instance of T from a ConfigDict.
+         *
+         * This works for most descendants of serializable.  A few need to
+         * provide special handling.
+         * @param cls A Constructor for the class to instantiate.
+         * @param config The Configuration for the object.
+         */
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(config);
+        }
+      }
+      /**
+       * Maps string keys to class constructors.
+       *
+       * Used during (de)serialization from the cross-language JSON format, which
+       * requires the class name in the serialization format matches the class
+       * names as used in Python, should it exist.
+       */
+      class SerializationMap {
+        constructor() {
+          this.classNameMap = {};
+        }
+        /**
+         * Returns the singleton instance of the map.
+         */
+        static getMap() {
+          if (SerializationMap.instance == null) {
+            SerializationMap.instance = new SerializationMap();
+          }
+          return SerializationMap.instance;
+        }
+        /**
+         * Registers the class as serializable.
+         */
+        static register(cls) {
+          SerializationMap.getMap().classNameMap[cls.className] = [cls, cls.fromConfig];
+        }
+      }
+      /**
+       * Register a class with the serialization map of TensorFlow.js.
+       *
+       * This is often used for registering custom Layers, so they can be
+       * serialized and deserialized.
+       *
+       * Example:
+       *
+       * ```js
+       * class MyCustomLayer extends tf.layers.Layer {
+       *   static className = 'MyCustomLayer';
+       *
+       *   constructor(config) {
+       *     super(config);
+       *   }
+       * }
+       * tf.serialization.registerClass(MyCustomLayer);
+       * ```
+       *
+       * @param cls The class to be registered. It must have a public static member
+       *   called `className` defined and the value must be a non-empty string.
+       */
+      /** @doc {heading: 'Models', subheading: 'Serialization', ignoreCI: true} */
+      function registerClass(cls) {
+        Object(util["assert"])(
+          cls.className != null,
+          () => `Class being registered does not have the static className ` + `property defined.`
+        );
+        Object(util["assert"])(
+          typeof cls.className === "string",
+          () => `className is required to be a string, but got type ` + typeof cls.className
+        );
+        Object(util["assert"])(
+          cls.className.length > 0,
+          () =>
+            `Class being registered has an empty-string as its className, ` + `which is disallowed.`
+        );
+        SerializationMap.register(cls);
+      }
+      //# sourceMappingURL=serialization.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/test_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const TEST_EPSILON_FLOAT32 = 1e-3;
+      const TEST_EPSILON_FLOAT16 = 1e-1;
+      function expectArraysClose(actual, expected, epsilon) {
+        if (epsilon == null) {
+          epsilon = testEpsilon();
+        }
+        return expectArraysPredicate(actual, expected, (a, b) => areClose(a, b, epsilon));
+      }
+      function testEpsilon() {
+        return engine["a" /* ENGINE */].backend.floatPrecision() === 32
+          ? TEST_EPSILON_FLOAT32
+          : TEST_EPSILON_FLOAT16;
+      }
+      function expectArraysPredicate(actual, expected, predicate) {
+        let checkClassType = true;
+        if (Object(util["isTypedArray"])(actual) || Object(util["isTypedArray"])(expected)) {
+          checkClassType = false;
+        }
+        if (Object(util["isTypedArray"])(actual) && Object(util["isTypedArray"])(expected)) {
+          checkClassType = true;
+        }
+        if (checkClassType) {
+          const aType = actual.constructor.name;
+          const bType = expected.constructor.name;
+          if (aType !== bType) {
+            throw new Error(
+              `Arrays are of different type. Actual: ${aType}. ` + `Expected: ${bType}`
+            );
+          }
+        }
+        if (Array.isArray(actual) && Array.isArray(expected)) {
+          const actualShape = Object(tensor_util_env["c" /* inferShape */])(actual);
+          const expectedShape = Object(tensor_util_env["c" /* inferShape */])(expected);
+          if (!Object(util["arraysEqual"])(actualShape, expectedShape)) {
+            throw new Error(
+              `Arrays have different shapes. ` +
+                `Actual: [${actualShape}]. Expected: [${expectedShape}]`
+            );
+          }
+        }
+        const actualFlat = Object(util["isTypedArray"])(actual)
+          ? actual
+          : Object(util["flatten"])(actual);
+        const expectedFlat = Object(util["isTypedArray"])(expected)
+          ? expected
+          : Object(util["flatten"])(expected);
+        if (actualFlat.length !== expectedFlat.length) {
+          throw new Error(
+            `Arrays have different lengths actual: ${actualFlat.length} vs ` +
+              `expected: ${expectedFlat.length}.\n` +
+              `Actual:   ${actualFlat}.\n` +
+              `Expected: ${expectedFlat}.`
+          );
+        }
+        for (let i = 0; i < expectedFlat.length; ++i) {
+          const a = actualFlat[i];
+          const e = expectedFlat[i];
+          if (!predicate(a, e)) {
+            throw new Error(
+              `Arrays differ: actual[${i}] = ${a}, expected[${i}] = ${e}.\n` +
+                `Actual:   ${actualFlat}.\n` +
+                `Expected: ${expectedFlat}.`
+            );
+          }
+        }
+      }
+      function expectPromiseToFail(fn, done) {
+        fn().then(
+          () => done.fail(),
+          () => done()
+        );
+      }
+      function expectArraysEqual(actual, expected) {
+        const exp =
+          typeof expected === "string" ||
+          typeof expected === "number" ||
+          typeof expected === "boolean"
+            ? [expected]
+            : expected;
+        if (
+          Object(util["isString"])(actual) ||
+          Object(util["isString"])(actual[0]) ||
+          Object(util["isString"])(expected) ||
+          Object(util["isString"])(expected[0])
+        ) {
+          // tslint:disable-next-line: triple-equals
+          return expectArraysPredicate(actual, exp, (a, b) => a == b);
+        }
+        return expectArraysPredicate(actual, expected, (a, b) => areClose(a, b, 0));
+      }
+      function expectNumbersClose(a, e, epsilon) {
+        if (epsilon == null) {
+          epsilon = testEpsilon();
+        }
+        if (!areClose(a, e, epsilon)) {
+          throw new Error(`Numbers differ: actual === ${a}, expected === ${e}`);
+        }
+      }
+      function areClose(a, e, epsilon) {
+        if (!isFinite(a) && !isFinite(e)) {
+          return true;
+        }
+        if (isNaN(a) || isNaN(e) || Math.abs(a - e) > epsilon) {
+          return false;
+        }
+        return true;
+      }
+      function expectValuesInRange(actual, low, high) {
+        for (let i = 0; i < actual.length; i++) {
+          if (actual[i] < low || actual[i] > high) {
+            throw new Error(`Value out of range:${actual[i]} low: ${low}, high: ${high}`);
+          }
+        }
+      }
+      function expectArrayBuffersEqual(actual, expected) {
+        // Safari & Jasmine don't like comparing ArrayBuffers directly. Wrapping in
+        // a Float32Array solves this issue.
+        expect(new Float32Array(actual)).toEqual(new Float32Array(expected));
+      }
+      //# sourceMappingURL=test_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/version.js
+      /** @license See the LICENSE file. */
+      // This code is auto-generated, do not modify this file!
+      const version = "2.0.1";
+
+      //# sourceMappingURL=version.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/globals.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Enables production mode which disables correctness checks in favor of
+       * performance.
+       */
+      /** @doc {heading: 'Environment'} */
+      function enableProdMode() {
+        Object(environment["c" /* env */])().set("PROD", true);
+      }
+      /**
+       * Enables debug mode which will log information about all executed kernels:
+       * the elapsed time of the kernel execution, as well as the rank, shape, and
+       * size of the output tensor.
+       *
+       * Debug mode will significantly slow down your application as it will
+       * download the result of every operation to the CPU. This should not be used in
+       * production. Debug mode does not affect the timing information of the kernel
+       * execution as we do not measure download time in the kernel execution time.
+       *
+       * See also: `tf.profile`, `tf.memory`.
+       */
+      /** @doc {heading: 'Environment'} */
+      function enableDebugMode() {
+        Object(environment["c" /* env */])().set("DEBUG", true);
+      }
+      /** Globally disables deprecation warnings */
+      function disableDeprecationWarnings() {
+        Object(environment["c" /* env */])().set("DEPRECATION_WARNINGS_ENABLED", false);
+        console.warn(`TensorFlow.js deprecation warnings have been disabled.`);
+      }
+      /** Warn users about deprecated functionality. */
+      function deprecationWarn(msg) {
+        if (Object(environment["c" /* env */])().getBool("DEPRECATION_WARNINGS_ENABLED")) {
+          console.warn(
+            msg + " You can disable deprecation warnings with " + "tf.disableDeprecationWarnings()."
+          );
+        }
+      }
+      Object(dist_tensor["d" /* setDeprecationWarningFn */])(deprecationWarn);
+      /**
+       * Dispose all variables kept in backend engine.
+       */
+      /** @doc {heading: 'Environment'} */
+      function disposeVariables() {
+        engine["a" /* ENGINE */].disposeVariables();
+      }
+      /**
+       * It returns the global engine that keeps track of all tensors and backends.
+       */
+      /** @doc {heading: 'Environment'} */
+      function globals_engine() {
+        return engine["a" /* ENGINE */];
+      }
+      /**
+       * Returns memory info at the current time in the program. The result is an
+       * object with the following properties:
+       *
+       * - `numBytes`: Number of bytes allocated (undisposed) at this time.
+       * - `numTensors`: Number of unique tensors allocated.
+       * - `numDataBuffers`: Number of unique data buffers allocated
+       *   (undisposed) at this time, which is ≤ the number of tensors
+       *   (e.g. `a.reshape(newShape)` makes a new Tensor that shares the same
+       *   data buffer with `a`).
+       * - `unreliable`: True if the memory usage is unreliable. See `reasons` when
+       *    `unreliable` is true.
+       * - `reasons`: `string[]`, reasons why the memory is unreliable, present if
+       *    `unreliable` is true.
+       *
+       * WebGL Properties:
+       * - `numBytesInGPU`: Number of bytes allocated (undisposed) in the GPU only at
+       *     this time.
+       */
+      /** @doc {heading: 'Performance', subheading: 'Memory'} */
+      function memory() {
+        return engine["a" /* ENGINE */].memory();
+      }
+      /**
+       * Executes the provided function `f()` and returns a promise that resolves
+       * with information about the function's memory use:
+       * - `newBytes`: the number of new bytes allocated
+       * - `newTensors`: the number of new tensors created
+       * - `peakBytes`: the peak number of bytes allocated
+       * - `kernels`: an array of objects for each kernel involved that reports
+       * their input and output shapes, number of bytes used, and number of new
+       * tensors created.
+       *
+       * ```js
+       * const profile = await tf.profile(() => {
+       *   const x = tf.tensor1d([1, 2, 3]);
+       *   let x2 = x.square();
+       *   x2.dispose();
+       *   x2 = x.square();
+       *   x2.dispose();
+       *   return x;
+       * });
+       *
+       * console.log(`newBytes: ${profile.newBytes}`);
+       * console.log(`newTensors: ${profile.newTensors}`);
+       * console.log(`byte usage over all kernels: ${profile.kernels.map(k =>
+       * k.totalBytesSnapshot)}`);
+       * ```
+       *
+       */
+      /** @doc {heading: 'Performance', subheading: 'Profile'} */
+      function profile(f) {
+        return engine["a" /* ENGINE */].profile(f);
+      }
+      /**
+       * Executes the provided function `fn` and after it is executed, cleans up all
+       * intermediate tensors allocated by `fn` except those returned by `fn`.
+       * `fn` must not return a Promise (async functions not allowed). The returned
+       * result can be a complex object.
+       *
+       * Using this method helps avoid memory leaks. In general, wrap calls to
+       * operations in `tf.tidy` for automatic memory cleanup.
+       *
+       * NOTE: Variables do *not* get cleaned up when inside a tidy(). If you want to
+       * dispose variables, please use `tf.disposeVariables` or call dispose()
+       * directly on variables.
+       *
+       * ```js
+       * // y = 2 ^ 2 + 1
+       * const y = tf.tidy(() => {
+       *   // a, b, and one will be cleaned up when the tidy ends.
+       *   const one = tf.scalar(1);
+       *   const a = tf.scalar(2);
+       *   const b = a.square();
+       *
+       *   console.log('numTensors (in tidy): ' + tf.memory().numTensors);
+       *
+       *   // The value returned inside the tidy function will return
+       *   // through the tidy, in this case to the variable y.
+       *   return b.add(one);
+       * });
+       *
+       * console.log('numTensors (outside tidy): ' + tf.memory().numTensors);
+       * y.print();
+       * ```
+       *
+       * @param nameOrFn The name of the closure, or the function to execute.
+       *     If a name is provided, the 2nd argument should be the function.
+       *     If debug mode is on, the timing and the memory usage of the function
+       *     will be tracked and displayed on the console using the provided name.
+       * @param fn The function to execute.
+       */
+      /** @doc {heading: 'Performance', subheading: 'Memory'} */
+      function tidy(nameOrFn, fn) {
+        return engine["a" /* ENGINE */].tidy(nameOrFn, fn);
+      }
+      /**
+       * Disposes any `tf.Tensor`s found within the provided object.
+       *
+       * @param container an object that may be a `tf.Tensor` or may directly
+       *     contain `tf.Tensor`s, such as a `Tensor[]` or `{key: Tensor, ...}`. If
+       *     the object is not a `tf.Tensor` or does not contain `Tensors`, nothing
+       *     happens. In general it is safe to pass any object here, except that
+       *     `Promise`s are not supported.
+       */
+      /** @doc {heading: 'Performance', subheading: 'Memory'} */
+      function dispose(container) {
+        const tensors = Object(tensor_util["getTensorsInContainer"])(container);
+        tensors.forEach((tensor) => tensor.dispose());
+      }
+      /**
+       * Keeps a `tf.Tensor` generated inside a `tf.tidy` from being disposed
+       * automatically.
+       *
+       * ```js
+       * let b;
+       * const y = tf.tidy(() => {
+       *   const one = tf.scalar(1);
+       *   const a = tf.scalar(2);
+       *
+       *   // b will not be cleaned up by the tidy. a and one will be cleaned up
+       *   // when the tidy ends.
+       *   b = tf.keep(a.square());
+       *
+       *   console.log('numTensors (in tidy): ' + tf.memory().numTensors);
+       *
+       *   // The value returned inside the tidy function will return
+       *   // through the tidy, in this case to the variable y.
+       *   return b.add(one);
+       * });
+       *
+       * console.log('numTensors (outside tidy): ' + tf.memory().numTensors);
+       * console.log('y:');
+       * y.print();
+       * console.log('b:');
+       * b.print();
+       * ```
+       *
+       * @param result The tensor to keep from being disposed.
+       */
+      /** @doc {heading: 'Performance', subheading: 'Memory'} */
+      function keep(result) {
+        return engine["a" /* ENGINE */].keep(result);
+      }
+      /**
+       * Executes `f()` and returns a promise that resolves with timing
+       * information.
+       *
+       * The result is an object with the following properties:
+       *
+       * - `wallMs`: Wall execution time.
+       * - `kernelMs`: Kernel execution time, ignoring data transfer. If using the
+       * WebGL backend and the query timer extension is not available, this will
+       * return an error object.
+       * - On `WebGL` The following additional properties exist:
+       *   - `uploadWaitMs`: CPU blocking time on texture uploads.
+       *   - `downloadWaitMs`: CPU blocking time on texture downloads (readPixels).
+       *
+       * ```js
+       * const x = tf.randomNormal([20, 20]);
+       * const time = await tf.time(() => x.matMul(x));
+       *
+       * console.log(`kernelMs: ${time.kernelMs}, wallTimeMs: ${time.wallMs}`);
+       * ```
+       *
+       * @param f The function to execute and time.
+       */
+      /** @doc {heading: 'Performance', subheading: 'Timing'} */
+      function time(f) {
+        return engine["a" /* ENGINE */].time(f);
+      }
+      /**
+       * Sets the backend (cpu, webgl, wasm, etc) responsible for creating tensors and
+       * executing operations on those tensors. Returns a promise that resolves
+       * to a boolean if the backend initialization was successful.
+       *
+       * Note this disposes the current backend, if any, as well as any tensors
+       * associated with it. A new backend is initialized, even if it is of the
+       * same type as the previous one.
+       *
+       * @param backendName The name of the backend. Currently supports
+       *     `'webgl'|'cpu'` in the browser, `'tensorflow'` under node.js
+       *     (requires tfjs-node), and `'wasm'` (requires tfjs-backend-wasm).
+       */
+      /** @doc {heading: 'Backends'} */
+      function setBackend(backendName) {
+        return engine["a" /* ENGINE */].setBackend(backendName);
+      }
+      /**
+       * Returns a promise that resolves when the currently selected backend (or the
+       * highest priority one) has initialized. Await this promise when you are using
+       * a backend that has async initialization.
+       */
+      /** @doc {heading: 'Backends'} */
+      function ready() {
+        return engine["a" /* ENGINE */].ready();
+      }
+      /**
+       * Returns the current backend name (cpu, webgl, etc). The backend is
+       * responsible for creating tensors and executing operations on those tensors.
+       */
+      /** @doc {heading: 'Backends'} */
+      function getBackend() {
+        return engine["a" /* ENGINE */].backendName;
+      }
+      /**
+       * Removes a backend and the registered factory.
+       */
+      /** @doc {heading: 'Backends'} */
+      function removeBackend(name) {
+        engine["a" /* ENGINE */].removeBackend(name);
+      }
+      /**
+       * Finds the backend registered under the provided name. Returns null if the
+       * name is not in the registry, or the registration hasn't finished yet.
+       */
+      function findBackend(name) {
+        return engine["a" /* ENGINE */].findBackend(name);
+      }
+      /**
+       * Finds the backend factory registered under the provided name. Returns a
+       * function that produces a new backend when called. Returns null if the name
+       * is not in the registry.
+       */
+      function findBackendFactory(name) {
+        return engine["a" /* ENGINE */].findBackendFactory(name);
+      }
+      /**
+       * Registers a global backend. The registration should happen when importing
+       * a module file (e.g. when importing `backend_webgl.ts`), and is used for
+       * modular builds (e.g. custom tfjs bundle with only webgl support).
+       *
+       * @param factory The backend factory function. When called, it should
+       * return a backend instance, or a promise of an instance.
+       * @param priority The priority of the backend (higher = more important).
+       *     In case multiple backends are registered, the priority is used to find
+       *     the best backend. Defaults to 1.
+       * @return False if there is already a registered backend under this name, true
+       *     if not.
+       */
+      /** @doc {heading: 'Backends'} */
+      function registerBackend(name, factory, priority = 1) {
+        return engine["a" /* ENGINE */].registerBackend(name, factory, priority);
+      }
+      /**
+       * Gets the current backend. If no backends have been initialized, this will
+       * attempt to initialize the best backend. Will throw an error if the highest
+       * priority backend has async initialization, in which case, you should call
+       * 'await tf.ready()' before running other code.
+       */
+      /** @doc {heading: 'Backends'} */
+      function globals_backend() {
+        return engine["a" /* ENGINE */].backend;
+      }
+      /**
+       * Sets the global platform.
+       *
+       * @param platformName The name of this platform.
+       * @param platform A platform implementation.
+       */
+      function setPlatform(platformName, platform) {
+        Object(environment["c" /* env */])().setPlatform(platformName, platform);
+      }
+      //# sourceMappingURL=globals.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/add_n.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Adds a list of `tf.Tensor`s element-wise, each with the same shape and dtype.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2]);
+       * const b = tf.tensor1d([3, 4]);
+       * const c = tf.tensor1d([5, 6]);
+       *
+       * tf.addN([a, b, c]).print();
+       * ```
+       * @param tensors A list of tensors with the same shape and dtype.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function addN_(tensors) {
+        util["assert"](
+          Array.isArray(tensors),
+          () => "The argument passed to tf.addN() must be a list of tensors"
+        );
+        util["assert"](
+          tensors.length >= 1,
+          () => `Must pass at least one tensor to tf.addN(), but got ` + `${tensors.length}`
+        );
+        const $tensors = tensors.map((t, i) =>
+          Object(tensor_util_env["a" /* convertToTensor */])(t, `tensors${i}`, "addN")
+        );
+        const firstTensor = $tensors[0];
+        $tensors.forEach((t) => {
+          if (t.dtype !== firstTensor.dtype) {
+            throw new Error("All tensors passed to tf.addN() must have the same dtype");
+          }
+        });
+        $tensors.forEach((t) => {
+          if (!util["arraysEqual"](t.shape, firstTensor.shape)) {
+            throw new Error("All tensors passed to tf.addN() must have the same shape");
+          }
+        });
+        const forward = (backend, save) => {
+          const res = backend.addN($tensors);
+          save($tensors);
+          return res;
+        };
+        const inputs = $tensors;
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["b" /* AddN */]
+        );
+      }
+      const addN = Object(operation["a" /* op */])({ addN_ });
+      //# sourceMappingURL=add_n.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/atan2.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes arctangent of `tf.Tensor`s a / b element-wise: `atan2(a, b)`.
+       * Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1.0, 1.0, -1.0, .7]);
+       * const b = tf.tensor1d([2.0, 13.0, 3.5, .21]);
+       *
+       * tf.atan2(a, b).print()
+       * ```
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same dtype as `a`.
+       *
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function atan2_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "atan2");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "atan2");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        const forward = (backend, save) => {
+          const res = backend.atan2($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["c" /* Atan2 */]
+        );
+      }
+      const atan2 = Object(operation["a" /* op */])({ atan2_ });
+      //# sourceMappingURL=atan2.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the 2D average pooling of an image.
+       *
+       * @param x The input tensor, of rank 4 or rank 3 of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
+       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
+       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
+       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
+       *     `strides` is a single number, then `strideHeight == strideWidth`.
+       * @param pad The type of padding algorithm:
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *    - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *         https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       */
+      function avgPool_(x, filterSize, strides, pad, dimRoundingMode) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "avgPool", "float32");
+        const dilations = 1;
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in avgPool: Either strides or dilations must be 1. " +
+            `Got strides ${strides} and dilations '${dilations}'`
+        );
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
+        }
+        util["assert"](
+          x4D.rank === 4,
+          () => `Error in avgPool: x must be rank 4 but got rank ${x4D.rank}.`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in avgPool: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend, save) => {
+          const convInfo = computePool2DInfo(
+            x4D.shape,
+            filterSize,
+            strides,
+            1 /* dilations */,
+            pad,
+            dimRoundingMode
+          );
+          save([x4D]);
+          if (
+            convInfo.filterWidth === 1 &&
+            convInfo.filterHeight === 1 &&
+            util["arraysEqual"](convInfo.inShape, convInfo.outShape)
+          ) {
+            return x4D.clone();
+          }
+          return backend.avgPool(x4D, convInfo);
+        };
+        const inputs = { x: x4D };
+        const attrs = { filterSize, strides, pad, dimRoundingMode };
+        let res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["d" /* AvgPool */],
+          attrs
+        );
+        res = cast(res, $x.dtype);
+        if (reshapedTo4D) {
+          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
+        }
+        return res;
+      }
+      const avgPool = Object(operation["a" /* op */])({ avgPool_ });
+      //# sourceMappingURL=avg_pool.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_3d.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the 3D average pooling.
+       *
+       * ```js
+       * const x = tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]);
+       * const result = tf.avgPool3d(x, 2, 1, 'valid');
+       * result.print();
+       * ```
+       *
+       * @param x The input tensor, of rank 5 or rank 4 of shape
+       *     `[batch, depth, height, width, inChannels]`.
+       * @param filterSize The filter size:
+       *     `[filterDepth, filterHeight, filterWidth]`.
+       *     If `filterSize` is a single number,
+       *     then `filterDepth == filterHeight == filterWidth`.
+       * @param strides The strides of the pooling:
+       *     `[strideDepth, strideHeight, strideWidth]`.
+       *     If `strides` is a single number,
+       *     then `strideDepth == strideHeight == strideWidth`.
+       * @param pad The type of padding algorithm.
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1*1x1.
+       *    - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       * @param dataFormat An optional string from: "NDHWC", "NCDHW". Defaults to
+       *     "NDHWC". Specify the data format of the input and output data. With the
+       *     default format "NDHWC", the data is stored in the order of: [batch,
+       *     depth, height, width, channels]. Only "NDHWC" is currently supported.
+       * @param dilations Deprecated, this field will be gone in v3.0.0.
+       *     The dilation rates:
+       *     `[dilationDepth, dilationHeight, dilationWidth]`
+       *     in which we sample input values across the depth, height and width
+       *     dimensions in dilated pooling.
+       *     Defaults to `[1, 1, 1]`. If `dilations` is a single number,
+       *     then `dilationDepth == dilationHeight == dilationWidth`.
+       *     If it is greater than 1, then all values of `strides` must be 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function avgPool3d_(
+        x,
+        filterSize,
+        strides,
+        pad,
+        dimRoundingMode,
+        dataFormat = "NDHWC",
+        dilations
+      ) {
+        if (dilations == null) {
+          dilations = [1, 1, 1];
+        } else {
+          deprecationWarn("dilations is deprecated, this field will be gone in " + "v3.0.0.");
+        }
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(
+          x,
+          "x",
+          "avgPool3d",
+          "float32"
+        );
+        let x5D = $x;
+        let reshapedTo5D = false;
+        if ($x.rank === 4) {
+          reshapedTo5D = true;
+          x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);
+        }
+        util["assert"](
+          x5D.rank === 5,
+          () => `Error in avgPool3d: x must be rank 5 but got rank ${x5D.rank}.`
+        );
+        util["assert"](
+          dataFormat === "NDHWC",
+          () =>
+            `Error in avgPool3d: Only NDHWC is currently supported, ` +
+            `but got dataFormat of ${dataFormat}`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in avgPool3d: Either strides or dilations must be 1. " +
+            `Got strides ${strides} and dilations '${dilations}'`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in avgPool3d: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend, save) => {
+          if (dilations == null) {
+            dilations = [1, 1, 1];
+          }
+          const convInfo = computePool3DInfo(
+            x5D.shape,
+            filterSize,
+            strides,
+            dilations,
+            pad,
+            dimRoundingMode,
+            dataFormat
+          );
+          save([x5D]);
+          return backend.avgPool3d(x5D, convInfo);
+        };
+        const inputs = { x: x5D };
+        const attrs = { filterSize, strides, pad, dimRoundingMode, dataFormat, dilations };
+        let res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["e" /* AvgPool3D */],
+          attrs
+        );
+        res = cast(res, x5D.dtype);
+        if (reshapedTo5D) {
+          return res.as4D(res.shape[1], res.shape[2], res.shape[3], res.shape[4]);
+        }
+        return res;
+      }
+      const avgPool3d = Object(operation["a" /* op */])({ avgPool3d_ });
+      //# sourceMappingURL=avg_pool_3d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm_util.js
+      function xAs4D(x) {
+        let x4D;
+        if (x.rank === 0 || x.rank === 1) {
+          x4D = x.as4D(1, 1, 1, x.size);
+        } else if (x.rank === 2) {
+          x4D = x.as4D(1, 1, x.shape[0], x.shape[1]);
+        } else if (x.rank === 3) {
+          x4D = x.as4D(1, x.shape[0], x.shape[1], x.shape[2]);
+        } else {
+          x4D = x;
+        }
+        return x4D;
+      }
+      //# sourceMappingURL=batchnorm_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Batch normalization.
+       *
+       * As described in
+       * [http://arxiv.org/abs/1502.03167](http://arxiv.org/abs/1502.03167).
+       *
+       * Mean, variance, scale, and offset can be of two shapes:
+       *   - The same shape as the input.
+       *   - In the common case, the depth dimension is the last dimension of x, so
+       *     the values would be an `tf.Tensor1D` of shape [depth].
+       *
+       * Also available are stricter rank-specific methods with the same signature
+       * as this method that assert that parameters passed are of given rank
+       *   - `tf.batchNorm2d`
+       *   - `tf.batchNorm3d`
+       *   - `tf.batchNorm4d`
+       *
+       * @param x The input Tensor.
+       * @param mean A mean Tensor.
+       * @param variance A variance Tensor.
+       * @param offset An offset Tensor.
+       * @param scale A scale Tensor.
+       * @param varianceEpsilon A small float number to avoid dividing by 0.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
+      function batchNorm_(x, mean, variance, offset, scale, varianceEpsilon) {
+        if (varianceEpsilon == null) {
+          varianceEpsilon = 0.001;
+        }
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchNorm");
+        const $mean = Object(tensor_util_env["a" /* convertToTensor */])(mean, "mean", "batchNorm");
+        const $variance = Object(tensor_util_env["a" /* convertToTensor */])(
+          variance,
+          "variance",
+          "batchNorm"
+        );
+        let $scale;
+        if (scale != null) {
+          $scale = Object(tensor_util_env["a" /* convertToTensor */])(scale, "scale", "batchNorm");
+        }
+        let $offset;
+        if (offset != null) {
+          $offset = Object(tensor_util_env["a" /* convertToTensor */])(
+            offset,
+            "offset",
+            "batchNorm"
+          );
+        }
+        util["assert"](
+          $mean.rank === $variance.rank,
+          () => "Batch normalization gradient requires mean and variance to have " + "equal ranks."
+        );
+        util["assert"](
+          $offset == null || $mean.rank === $offset.rank,
+          () => "Batch normalization gradient requires mean and offset to have " + "equal ranks."
+        );
+        util["assert"](
+          $scale == null || $mean.rank === $scale.rank,
+          () => "Batch normalization gradient requires mean and scale to have " + "equal ranks."
+        );
+        const x4D = xAs4D($x);
+        const forward = (backend, save) => {
+          save([x4D, $mean, $variance, $scale]);
+          return backend.batchNorm(
+            x4D,
+            as1DOr4D($mean),
+            as1DOr4D($variance),
+            as1DOr4D($offset),
+            as1DOr4D($scale),
+            varianceEpsilon
+          );
+        };
+        const inputs = {
+          x: x4D,
+          scale: $scale,
+          offset: $offset,
+          mean: $mean,
+          variance: $variance,
+        };
+        const attrs = { varianceEpsilon };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["F" /* FusedBatchNorm */],
+          attrs
+        );
+        return reshape(res, $x.shape);
+      }
+      function as1DOr4D(x) {
+        if (x == null) {
+          return null;
+        }
+        if (x.rank === 0) {
+          return x.as1D();
+        } else if (x.rank === 1) {
+          return x;
+        } else if (x.rank === 2) {
+          return x.as4D(1, 1, x.shape[0], x.shape[1]);
+        } else if (x.rank === 3) {
+          return x.as4D(1, x.shape[0], x.shape[1], x.shape[2]);
+        }
+        return x;
+      }
+      const batchNorm = Object(operation["a" /* op */])({ batchNorm_ });
+      //# sourceMappingURL=batchnorm.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm2d.js
+
+      /**
+       * Batch normalization, strictly for 2D. For the more relaxed version, see
+       * `tf.batchNorm`.
+       *
+       * @param x The input Tensor.
+       * @param mean A mean Tensor.
+       * @param variance A variance Tensor.
+       * @param offset An offset Tensor.
+       * @param scale A scale Tensor.
+       * @param varianceEpsilon A small float number to avoid dividing by 0.
+       */
+      function batchNorm2d_(x, mean, variance, offset, scale, varianceEpsilon) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchNorm");
+        const $mean = Object(tensor_util_env["a" /* convertToTensor */])(mean, "mean", "batchNorm");
+        const $variance = Object(tensor_util_env["a" /* convertToTensor */])(
+          variance,
+          "variance",
+          "batchNorm"
+        );
+        let $scale;
+        if (scale != null) {
+          $scale = Object(tensor_util_env["a" /* convertToTensor */])(scale, "scale", "batchNorm");
+        }
+        let $offset;
+        if (offset != null) {
+          $offset = Object(tensor_util_env["a" /* convertToTensor */])(
+            offset,
+            "offset",
+            "batchNorm"
+          );
+        }
+        util["assert"](
+          $x.rank === 2,
+          () => `Error in batchNorm3D: x must be rank 3 but got rank ` + `${$x.rank}.`
+        );
+        util["assert"](
+          $mean.rank === 2 || $mean.rank === 1,
+          () =>
+            `Error in batchNorm2D: mean must be rank 2 or rank 1 but ` + `got rank ${$mean.rank}.`
+        );
+        util["assert"](
+          $variance.rank === 2 || $variance.rank === 1,
+          () =>
+            `Error in batchNorm2D: variance must be rank 2 or rank 1 ` +
+            `but got rank ${$variance.rank}.`
+        );
+        if ($scale != null) {
+          util["assert"](
+            $scale.rank === 2 || $scale.rank === 1,
+            () =>
+              `Error in batchNorm2D: scale must be rank 2 or rank 1 ` +
+              `but got rank ${$scale.rank}.`
+          );
+        }
+        if ($offset != null) {
+          util["assert"](
+            $offset.rank === 2 || $offset.rank === 1,
+            () =>
+              `Error in batchNorm2D: offset must be rank 2 or rank 1 ` +
+              `but got rank ${$offset.rank}.`
+          );
+        }
+        return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);
+      }
+      const batchNorm2d = Object(operation["a" /* op */])({ batchNorm2d_ });
+      //# sourceMappingURL=batchnorm2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm3d.js
+
+      /**
+       * Batch normalization, strictly for 3D. For the more relaxed version, see
+       * `tf.batchNorm`.
+       *
+       * @param x The input Tensor.
+       * @param mean A mean Tensor.
+       * @param variance A variance Tensor.
+       * @param offset An offset Tensor.
+       * @param scale A scale Tensor.
+       * @param varianceEpsilon A small float number to avoid dividing by 0.
+       */
+      function batchNorm3d_(x, mean, variance, offset, scale, varianceEpsilon) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchNorm");
+        const $mean = Object(tensor_util_env["a" /* convertToTensor */])(mean, "mean", "batchNorm");
+        const $variance = Object(tensor_util_env["a" /* convertToTensor */])(
+          variance,
+          "variance",
+          "batchNorm"
+        );
+        let $scale;
+        if (scale != null) {
+          $scale = Object(tensor_util_env["a" /* convertToTensor */])(scale, "scale", "batchNorm");
+        }
+        let $offset;
+        if (offset != null) {
+          $offset = Object(tensor_util_env["a" /* convertToTensor */])(
+            offset,
+            "offset",
+            "batchNorm"
+          );
+        }
+        util["assert"](
+          $x.rank === 3,
+          () => `Error in batchNorm3D: x must be rank 3 but got rank ` + `${$x.rank}.`
+        );
+        util["assert"](
+          $mean.rank === 3 || $mean.rank === 1,
+          () =>
+            `Error in batchNorm3D: mean must be rank 3 or rank 1 but ` + `got rank ${$mean.rank}.`
+        );
+        util["assert"](
+          $variance.rank === 3 || $variance.rank === 1,
+          () =>
+            `Error in batchNorm3D: variance must be rank 3 or rank 1 ` +
+            `but got rank ${$variance.rank}.`
+        );
+        if ($scale != null) {
+          util["assert"](
+            $scale.rank === 3 || $scale.rank === 1,
+            () =>
+              `Error in batchNorm3D: scale must be rank 3 or rank 1 ` +
+              `but got rank ${$scale.rank}.`
+          );
+        }
+        if ($offset != null) {
+          util["assert"](
+            $offset.rank === 3 || $offset.rank === 1,
+            () =>
+              `Error in batchNorm3D: offset must be rank 3 or rank 1 ` +
+              `but got rank ${$offset.rank}.`
+          );
+        }
+        return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);
+      }
+      const batchNorm3d = Object(operation["a" /* op */])({ batchNorm3d_ });
+      //# sourceMappingURL=batchnorm3d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm4d.js
+
+      /**
+       * Batch normalization, strictly for 4D. For the more relaxed version, see
+       * `tf.batchNorm`.
+       *
+       * @param x The input Tensor.
+       * @param mean A mean Tensor.
+       * @param variance A variance Tensor.
+       * @param offset An offset Tensor.
+       * @param scale A scale Tensor.
+       * @param varianceEpsilon A small float number to avoid dividing by 0.
+       */
+      function batchNorm4d_(x, mean, variance, offset, scale, varianceEpsilon) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "batchNorm");
+        const $mean = Object(tensor_util_env["a" /* convertToTensor */])(mean, "mean", "batchNorm");
+        const $variance = Object(tensor_util_env["a" /* convertToTensor */])(
+          variance,
+          "variance",
+          "batchNorm"
+        );
+        let $scale;
+        if (scale != null) {
+          $scale = Object(tensor_util_env["a" /* convertToTensor */])(scale, "scale", "batchNorm");
+        }
+        let $offset;
+        if (offset != null) {
+          $offset = Object(tensor_util_env["a" /* convertToTensor */])(
+            offset,
+            "offset",
+            "batchNorm"
+          );
+        }
+        util["assert"](
+          $x.rank === 4,
+          () => `Error in batchNorm4D: x must be rank 4 but got rank ` + `${$x.rank}.`
+        );
+        util["assert"](
+          $mean.rank === 4 || $mean.rank === 1,
+          () =>
+            `Error in batchNorm4D: mean must be rank 4 or rank 1 but ` + `got rank ${$mean.rank}.`
+        );
+        util["assert"](
+          $variance.rank === 4 || $variance.rank === 1,
+          () =>
+            `Error in batchNorm4D: variance must be rank 4 or rank 1 ` +
+            `but got rank ${$variance.rank}.`
+        );
+        if ($scale != null) {
+          util["assert"](
+            $scale.rank === 4 || $scale.rank === 1,
+            () =>
+              `Error in batchNorm4D: scale must be rank 4 or rank 1 ` +
+              `but got rank ${$scale.rank}.`
+          );
+        }
+        if ($offset != null) {
+          util["assert"](
+            $offset.rank === 4 || $offset.rank === 1,
+            () =>
+              `Error in batchNorm4D: offset must be rank 4 or rank 1 ` +
+              `but got rank ${$offset.rank}.`
+          );
+        }
+        return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);
+      }
+      const batchNorm4d = Object(operation["a" /* op */])({ batchNorm4d_ });
+      //# sourceMappingURL=batchnorm4d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/clone.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a new tensor with the same values and shape as the specified
+       * tensor.
+       *
+       * ```js
+       * const x = tf.tensor([1, 2]);
+       *
+       * x.clone().print();
+       * ```
+       *
+       * @param x The tensor to clone.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function clone_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "clone", null);
+        const forward = () =>
+          engine["a" /* ENGINE */].makeTensorFromDataId($x.dataId, $x.shape, $x.dtype);
+        // Note this op is called tf.identity in python. Hence the kernel name used
+        // here.
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          { x: $x },
+          null /* grad */,
+          kernel_names["J" /* Identity */]
+        );
+      }
+      const clone = Object(operation["a" /* op */])({ clone_ });
+      //# sourceMappingURL=clone.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_to.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Broadcast an array to a compatible shape NumPy-style.
+       *
+       * The tensor's shape is compared to the broadcast shape from end to beginning.
+       * Ones are prepended to the tensor's shape until is has the same length as
+       * the broadcast shape. If input.shape[i]==shape[i], the (i+1)-th axis is
+       * already broadcast-compatible. If input.shape[i]==1 and shape[i]==N, then
+       * the input tensor is tiled N times along that axis (using tf.tile).
+       *
+       * @param input The tensor that is to be broadcasted.
+       * @param shape The input is to be broadcast to this shape.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function broadcastTo_(x, shape) {
+        let input = Object(tensor_util_env["a" /* convertToTensor */])(x, "broadcastTo", "x");
+        const xShape = input.shape;
+        if (shape.some((d) => !(d > 0) || d % 1 !== 0)) {
+          throw new Error(`broadcastTo(): Invalid broadcast shape [${shape}].`);
+        }
+        if (shape.length < input.rank) {
+          throw new Error(
+            `broadcastTo(): shape.length=${shape.length} < input.rank=${input.rank}.`
+          );
+        }
+        if (shape.length > input.rank) {
+          const newShape = input.shape.slice();
+          while (newShape.length < shape.length) {
+            newShape.unshift(1);
+          }
+          input = reshape(input, newShape);
+        }
+        const inputShape = input.shape;
+        const reps = Array.from(shape);
+        for (let i = shape.length - 1; i >= 0; i--) {
+          if (inputShape[i] === shape[i]) {
+            reps[i] = 1;
+          } else if (input.shape[i] !== 1) {
+            throw new Error(`broadcastTo(): [${xShape}] cannot be broadcast to [${shape}].`);
+          }
+        }
+        const axes = reps.map((n, i) => (n > 1 ? i : -1)).filter((i) => i >= 0);
+        if (axes.length === 0) {
+          return clone(input);
+        }
+        const forward = (backend) => backend.tile(input, reps);
+        const inputs = { x: input };
+        const attrs = { shape, inputShape };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["j" /* BroadcastTo */],
+          attrs
+        );
+      }
+      const broadcastTo = Object(operation["a" /* op */])({ broadcastTo_ });
+      //# sourceMappingURL=broadcast_to.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/complex.js
+      var complex = __webpack_require__(18);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_1d.js
+
+      /**
+       * Concatenates a list of`tf.Tensor1D`s along an axis. See `concat` for details.
+       *
+       * For example, if:
+       * A: shape(3) = |r1, g1, b1|
+       * B: shape(2) = |r2, g2|
+       * C = tf.concat1d([A, B]) == |r1, g1, b1, r2, g2|
+       *
+       * @param tensors A list of`tf.Tensor`s to concatenate.
+       * @return The concatenated array.
+       */
+      function concat1d_(tensors) {
+        return concat(tensors, 0 /* axis */);
+      }
+      const concat1d = Object(operation["a" /* op */])({ concat1d_ });
+      //# sourceMappingURL=concat_1d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_2d.js
+
+      /**
+       * Concatenates a list of`tf.Tensor2D`s along an axis. See `concat` for details.
+       *
+       * For example, if:
+       * A: shape(2, 3) = | r1, g1, b1 |
+       *                  | r2, g2, b2 |
+       *
+       * B: shape(2, 3) = | r3, g3, b3 |
+       *                  | r4, g4, b4 |
+       *
+       * C = tf.concat2d([A, B], axis)
+       *
+       * if axis = 0:
+       * C: shape(4, 3) = | r1, g1, b1 |
+       *                  | r2, g2, b2 |
+       *                  | r3, g3, b3 |
+       *                  | r4, g4, b4 |
+       *
+       * if axis = 1:
+       * C = shape(2, 6) = | r1, g1, b1, r3, g3, b3 |
+       *                   | r2, g2, b2, r4, g4, b4 |
+       *
+       *
+       * @param tensors A list of `tf.Tensor`s to concatenate.
+       * @param axis The axis to concatenate along.
+       * @return The concatenated array.
+       */
+      function concat2d_(tensors, axis) {
+        return concat(tensors, axis);
+      }
+      const concat2d = Object(operation["a" /* op */])({ concat2d_ });
+      //# sourceMappingURL=concat_2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_3d.js
+
+      /**
+       * Concatenates a list of `tf.Tensor3D`s along an axis.
+       * See `concat` for details.
+       *
+       * For example, if:
+       * A: shape(2, 1, 3) = | r1, g1, b1 |
+       *                     | r2, g2, b2 |
+       *
+       * B: shape(2, 1, 3) = | r3, g3, b3 |
+       *                     | r4, g4, b4 |
+       *
+       * C = tf.concat3d([A, B], axis)
+       *
+       * if axis = 0:
+       * C: shape(4, 1, 3) = | r1, g1, b1 |
+       *                     | r2, g2, b2 |
+       *                     | r3, g3, b3 |
+       *                     | r4, g4, b4 |
+       *
+       * if axis = 1:
+       * C: shape(2, 2, 3) = | r1, g1, b1, r3, g3, b3 |
+       *                     | r2, g2, b2, r4, g4, b4 |
+       *
+       * if axis = 2:
+       * C = shape(2, 1, 6) = | r1, g1, b1, r3, g3, b3 |
+       *                      | r2, g2, b2, r4, g4, b4 |
+       *
+       * @param tensors A list of`tf.Tensor`s to concatenate.
+       * @param axis The axis to concate along.
+       * @return The concatenated array.
+       */
+      function concat3d_(tensors, axis) {
+        return concat(tensors, axis);
+      }
+      const concat3d = Object(operation["a" /* op */])({ concat3d_ });
+      //# sourceMappingURL=concat_3d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/concat_4d.js
+
+      /**
+       * Concatenates a list of `tf.Tensor4D`s along an axis.
+       * See `concat` for details.
+       *
+       * @param tensors A list of `tf.Tensor`s to concatenate.
+       * @param axis The axis to concate along.
+       * @return The concatenated array.
+       */
+      function concat4d_(tensors, axis) {
+        return concat(tensors, axis);
+      }
+      const concat4d = Object(operation["a" /* op */])({ concat4d_ });
+      //# sourceMappingURL=concat_4d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv1d.js
+
+      /**
+       * Computes a 1D convolution over the input x.
+       *
+       * @param x The input tensor, of rank 3 or rank 2, of shape
+       *     `[batch, width, inChannels]`. If rank 2, batch of 1 is assumed.
+       * @param filter The filter, rank 3, of shape
+       *     `[filterWidth, inDepth, outDepth]`.
+       * @param stride The number of entries by which the filter is moved right at
+       *     each step.
+       * @param pad The type of padding algorithm.
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *   - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dataFormat An optional string from "NWC", "NCW". Defaults to "NWC",
+       *     the data is stored in the order of [batch, in_width, in_channels]. Only
+       *     "NWC" is currently supported.
+       * @param dilation The dilation rate in which we sample input values in
+       *     atrous convolution. Defaults to `1`. If it is greater than 1, then
+       *     stride must be `1`.
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function conv1d_(x, filter, stride, pad, dataFormat = "NWC", dilation = 1, dimRoundingMode) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv1d");
+        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
+          filter,
+          "filter",
+          "conv1d"
+        );
+        let x3D = $x;
+        let reshapedTo3D = false;
+        if ($x.rank === 2) {
+          reshapedTo3D = true;
+          x3D = reshape($x, [1, $x.shape[0], $x.shape[1]]);
+        }
+        util["assert"](
+          x3D.rank === 3,
+          () => `Error in conv1d: input must be rank 3, but got rank ${x3D.rank}.`
+        );
+        util["assert"](
+          $filter.rank === 3,
+          () => `Error in conv1d: filter must be rank 3, but got rank ` + `${$filter.rank}.`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in conv1d: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        util["assert"](
+          x3D.shape[2] === $filter.shape[1],
+          () =>
+            `Error in conv1d: depth of input (${x3D.shape[2]}) must match ` +
+            `input depth for filter ${$filter.shape[1]}.`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(stride, dilation),
+          () =>
+            "Error in conv1D: Either stride or dilation must be 1. " +
+            `Got stride ${stride} and dilation '${dilation}'`
+        );
+        util["assert"](
+          dataFormat === "NWC",
+          () =>
+            `Error in conv1d: got dataFormat of ${dataFormat} but only NWC is currently supported.`
+        );
+        const filter4D = reshape($filter, [
+          1,
+          $filter.shape[0],
+          $filter.shape[1],
+          $filter.shape[2],
+        ]);
+        const input4D = reshape(x3D, [x3D.shape[0], 1, x3D.shape[1], x3D.shape[2]]);
+        const strides = [1, stride];
+        const dilations = [1, dilation];
+        const conv2dDataFormat = "NHWC";
+        const res = conv2d(
+          input4D,
+          filter4D,
+          strides,
+          pad,
+          conv2dDataFormat,
+          dilations,
+          dimRoundingMode
+        );
+        if (reshapedTo3D) {
+          return reshape(res, [res.shape[2], res.shape[3]]);
+        }
+        return reshape(res, [res.shape[0], res.shape[2], res.shape[3]]);
+      }
+      const conv1d = Object(operation["a" /* op */])({ conv1d_ });
+      //# sourceMappingURL=conv1d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_transpose.js
+
+      /**
+       * Computes the transposed 2D convolution of an image, also known as a
+       * deconvolution.
+       *
+       * @param x The input image, of rank 4 or rank 3, of shape
+       *   `[batch, height, width, inDepth]`. If rank 3, batch of 1 is assumed.
+       * @param filter The filter, rank 4, of shape
+       *     `[filterHeight, filterWidth, outDepth, inDepth]`.
+       *     `inDepth` must match `inDepth` in `x`.
+       * @param outputShape Output shape, of rank 4 or rank 3:
+       *     `[batch, height, width, outDepth]`. If rank 3, batch of 1 is assumed.
+       * @param strides The strides of the original convolution:
+       *     `[strideHeight, strideWidth]`.
+       * @param pad  The type of padding algorithm used in the non-transpose version
+       *    of the op.
+       * @param dimRoundingMode The rounding mode used when computing output
+       *    dimensions if pad is a number. If none is provided, it will not round
+       *    and error if the output is of fractional size.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function conv2dTranspose_(x, filter, outputShape, strides, pad, dimRoundingMode) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv2dTranspose");
+        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
+          filter,
+          "filter",
+          "conv2dTranspose"
+        );
+        return conv2DBackpropInput(outputShape, $x, $filter, strides, pad, "NHWC", dimRoundingMode);
+      }
+      const conv2dTranspose = Object(operation["a" /* op */])({ conv2dTranspose_ });
+      //# sourceMappingURL=conv2d_transpose.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv3d.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes a 3D convolution over the input x.
+       *
+       * @param x The input tensor, of rank 5 or rank 4, of shape
+       *     `[batch, depth, height, width, channels]`. If rank 4,
+       * batch of 1 is assumed.
+       * @param filter The filter, rank 5, of shape
+       *     `[filterDepth, filterHeight, filterWidth, inChannels, outChannels]`.
+       *      inChannels must match between input and filter.
+       * @param strides The strides of the convolution: `[strideDepth, strideHeight,
+       * strideWidth]`.
+       * @param pad The type of padding algorithm.
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *   - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dataFormat: An optional string from: "NDHWC", "NCDHW". Defaults to
+       *     "NDHWC". Specify the data format of the input and output data. With the
+       *     default format "NDHWC", the data is stored in the order of: [batch,
+       *     depth, height, width, channels]. Only "NDHWC" is currently supported.
+       * @param dilations The dilation rates: `[dilationDepth, dilationHeight,
+       *     dilationWidth]` in which we sample input values across the height
+       *     and width dimensions in atrous convolution. Defaults to `[1, 1, 1]`.
+       *     If `dilations` is a single number, then
+       *     `dilationDepth == dilationHeight == dilationWidth`. If it is greater
+       *     than 1, then all values of `strides` must be 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function conv3d_(x, filter, strides, pad, dataFormat = "NDHWC", dilations = [1, 1, 1]) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv3d");
+        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
+          filter,
+          "filter",
+          "conv3d"
+        );
+        let x5D = $x;
+        let reshapedTo5D = false;
+        if ($x.rank === 4) {
+          reshapedTo5D = true;
+          x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);
+        }
+        util["assert"](
+          x5D.rank === 5,
+          () => `Error in conv3d: input must be rank 5, but got rank ${x5D.rank}.`
+        );
+        util["assert"](
+          $filter.rank === 5,
+          () => `Error in conv3d: filter must be rank 5, but got rank ` + `${$filter.rank}.`
+        );
+        util["assert"](
+          x5D.shape[4] === $filter.shape[3],
+          () =>
+            `Error in conv3d: depth of input (${x5D.shape[4]}) must match ` +
+            `input depth for filter ${$filter.shape[3]}.`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in conv3D: Either strides or dilations must be 1. " +
+            `Got strides ${strides} and dilations '${dilations}'`
+        );
+        util["assert"](
+          dataFormat === "NDHWC",
+          () =>
+            `Error in conv3d: got dataFormat of ${dataFormat} but only NDHWC is currently supported.`
+        );
+        const forward = (backend, save) => {
+          const convInfo = computeConv3DInfo(x5D.shape, $filter.shape, strides, dilations, pad);
+          const res = backend.conv3d(x5D, $filter, convInfo);
+          save([x5D, $filter]);
+          return res;
+        };
+        const inputs = { x: x5D, filter: $filter };
+        const attrs = { strides, pad, dataFormat, dilations };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["p" /* Conv3D */],
+          attrs
+        );
+        if (reshapedTo5D) {
+          return res.as4D(res.shape[1], res.shape[2], res.shape[3], res.shape[4]);
+        }
+        return res;
+      }
+      const conv3d = Object(operation["a" /* op */])({ conv3d_ });
+      //# sourceMappingURL=conv3d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_transpose.js
+
+      /**
+       * Computes the transposed 3D convolution of a volume, also known as a
+       * deconvolution.
+       *
+       * @param x The input image, of rank 5 or rank 4, of shape
+       *   `[batch, depth, height, width, inDepth]`. If rank 4, batch of 1 is assumed.
+       * @param filter The filter, rank 4, of shape
+       *     `[depth, filterHeight, filterWidth, outDepth, inDepth]`.
+       *     `inDepth` must match `inDepth` in `x`.
+       * @param outputShape Output shape, of rank 5 or rank 4:
+       *     `[batch, depth, height, width, outDepth]`. If rank 3, batch of 1 is
+       *    assumed.
+       * @param strides The strides of the original convolution:
+       *     `[strideDepth, strideHeight, strideWidth]`.
+       * @param pad  The type of padding algorithm used in the non-transpose version
+       *    of the op.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function conv3dTranspose_(x, filter, outputShape, strides, pad) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv3dTranspose");
+        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
+          filter,
+          "filter",
+          "conv3dTranspose"
+        );
+        return conv3DBackpropInput(outputShape, $x, $filter, strides, pad);
+      }
+      const conv3dTranspose = Object(operation["a" /* op */])({ conv3dTranspose_ });
+      //# sourceMappingURL=conv3d_transpose.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/depth_to_space.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Rearranges data from depth into blocks of spatial data. More specifically,
+       * this op outputs a copy of the input tensor where values from the `depth`
+       * dimension are moved in spatial blocks to the `height` and `width` dimensions.
+       * The attr `blockSize` indicates the input block size and how the data is
+       * moved.
+       *
+       *  - Chunks of data of size `blockSize * blockSize` from depth are rearranged
+       * into non-overlapping blocks of size `blockSize x blockSize`
+       *
+       *  - The width the output tensor is `inputWidth * blockSize`, whereas the
+       * height is `inputHeight * blockSize`
+       *
+       *  - The Y, X coordinates within each block of the output image are determined
+       * by the high order component of the input channel index
+       *
+       *  - The depth of the input tensor must be divisible by `blockSize *
+       * blockSize`
+       *
+       * The `dataFormat` attr specifies the layout of the input and output tensors
+       * with the following options: "NHWC": [ `batch, height, width, channels` ]
+       * "NCHW": [ `batch, channels, height, width` ]
+       *
+       * ```js
+       * const x = tf.tensor4d([1, 2, 3, 4], [1, 1, 1, 4]);
+       * const blockSize = 2;
+       * const dataFormat = "NHWC";
+       *
+       * tf.depthToSpace(x, blockSize, dataFormat).print();
+       * ```
+       *
+       * @param x The input tensor of rank 4
+       * @param blockSIze  An `int` that is `>= 2`. The size of the spatial block
+       * @param dataFormat An optional string from: "NHWC", "NCHW". Defaults to "NHWC"
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
+      function depthToSpace_(x, blockSize, dataFormat = "NHWC") {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "depthToSpace");
+        const inputHeight = dataFormat === "NHWC" ? $x.shape[1] : $x.shape[2];
+        const inputWidth = dataFormat === "NHWC" ? $x.shape[2] : $x.shape[3];
+        const inputDepth = dataFormat === "NHWC" ? $x.shape[3] : $x.shape[1];
+        util["assert"](
+          inputHeight * blockSize >= 0,
+          () => `Negative dimension size caused by overflow when multiplying
+    ${inputHeight} and ${blockSize}  for depthToSpace with input shape
+    ${$x.shape}`
+        );
+        util["assert"](
+          inputWidth * blockSize >= 0,
+          () => `Negative dimension size caused by overflow when multiplying
+    ${inputWidth} and ${blockSize} for depthToSpace with input shape
+        ${$x.shape}`
+        );
+        util["assert"](
+          inputDepth % (blockSize * blockSize) === 0,
+          () =>
+            `Dimension size must be evenly divisible by ${
+              blockSize * blockSize
+            } but is ${inputDepth} for depthToSpace with input shape ${$x.shape}`
+        );
+        const forward = (backend) => backend.depthToSpace($x, blockSize, dataFormat);
+        const inputs = { x: $x };
+        const attrs = { blockSize, dataFormat };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["t" /* DepthToSpace */],
+          attrs
+        );
+      }
+      const depthToSpace = Object(operation["a" /* op */])({ depthToSpace_ });
+      //# sourceMappingURL=depth_to_space.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Depthwise 2D convolution.
+       *
+       * Given a 4D `input` array and a `filter` array of shape
+       * `[filterHeight, filterWidth, inChannels, channelMultiplier]` containing
+       * `inChannels` convolutional filters of depth 1, this op applies a
+       * different filter to each input channel (expanding from 1 channel to
+       * `channelMultiplier` channels for each), then concatenates the results
+       * together. The output has `inChannels * channelMultiplier` channels.
+       *
+       * See
+       * [https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d](
+       *     https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d)
+       * for more details.
+       *
+       * @param x The input tensor, of rank 4 or rank 3, of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
+       * assumed.
+       * @param filter The filter tensor, rank 4, of shape
+       *     `[filterHeight, filterWidth, inChannels, channelMultiplier]`.
+       * @param strides The strides of the convolution: `[strideHeight,
+       * strideWidth]`. If strides is a single number, then `strideHeight ==
+       * strideWidth`.
+       * @param pad The type of padding algorithm.
+       *   - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *   - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *   - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
+       *     in which we sample input values across the height and width dimensions
+       *     in atrous convolution. Defaults to `[1, 1]`. If `rate` is a single
+       *     number, then `dilationHeight == dilationWidth`. If it is greater than
+       *     1, then all values of `strides` must be 1.
+       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
+       *     "NHWC". Specify the data format of the input and output data. With the
+       *     default format "NHWC", the data is stored in the order of: [batch,
+       *     height, width, channels]. Only "NHWC" is currently supported.
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function depthwiseConv2d_(
+        x,
+        filter,
+        strides,
+        pad,
+        dataFormat = "NHWC",
+        dilations = [1, 1],
+        dimRoundingMode
+      ) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "depthwiseConv2d");
+        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
+          filter,
+          "filter",
+          "depthwiseConv2d"
+        );
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
+        }
+        util["assert"](
+          x4D.rank === 4,
+          () => `Error in depthwiseConv2d: input must be rank 4, but got ` + `rank ${x4D.rank}.`
+        );
+        util["assert"](
+          $filter.rank === 4,
+          () =>
+            `Error in depthwiseConv2d: filter must be rank 4, but got rank ` + `${$filter.rank}.`
+        );
+        util["assert"](
+          x4D.shape[3] === $filter.shape[2],
+          () =>
+            `Error in depthwiseConv2d: number of input channels ` +
+            `(${x4D.shape[3]}) must match the inChannels dimension in ` +
+            `filter ${$filter.shape[2]}.`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in depthwiseConv2d: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend, save) => {
+          if (dilations == null) {
+            dilations = [1, 1];
+          }
+          util["assert"](
+            eitherStridesOrDilationsAreOne(strides, dilations),
+            () =>
+              "Error in depthwiseConv2d: Either strides or dilations must be " +
+              `1. Got strides ${strides} and dilations '${dilations}'`
+          );
+          const convInfo = computeConv2DInfo(
+            x4D.shape,
+            $filter.shape,
+            strides,
+            dilations,
+            pad,
+            dimRoundingMode,
+            true /* depthwise */
+          );
+          const res = backend.depthwiseConv2D(x4D, $filter, convInfo);
+          save([x4D, $filter]);
+          return res;
+        };
+        const inputs = { x: x4D, filter: $filter };
+        const attrs = { strides, pad, dataFormat, dilations, dimRoundingMode };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["u" /* DepthwiseConv2dNative */],
+          attrs
+        );
+        if (reshapedTo4D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
+        }
+        return res;
+      }
+      const depthwiseConv2d = Object(operation["a" /* op */])({ depthwiseConv2d_ });
+      //# sourceMappingURL=depthwise_conv2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/diag.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns a diagonal tensor with a given diagonal values.
+       *
+       * Given a diagonal, this operation returns a tensor with the diagonal and
+       * everything else padded with zeros.
+       *
+       * Assume the input has dimensions `[D1,..., Dk]`, then the output is a tensor
+       * of rank 2k with dimensions `[D1,..., Dk, D1,..., Dk]`
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       *
+       * tf.diag(x).print()
+       * ```
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4, 5, 6, 6, 8], [4, 2])
+       *
+       * tf.diag(x).print()
+       * ```
+       * @param x The input tensor.
+       */
+      function diag_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "diag").flatten();
+        const forward = (backend) => {
+          const result = backend.diag($x);
+          const outShape = [...x.shape, ...x.shape];
+          return reshape(result, outShape);
+        };
+        const inputs = { x: $x };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["x" /* Diag */]
+        );
+      }
+      const diag = Object(operation["a" /* op */])({ diag_ });
+      //# sourceMappingURL=diag.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/div_no_nan.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Divides two `tf.Tensor`s element-wise, A / B. Supports broadcasting. Return 0
+       * if denominator is 0.
+       *
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 4, 9, 16]);
+       * const b = tf.tensor1d([1, 2, 3, 4]);
+       * const c = tf.tensor1d([0, 0, 0, 0]);
+       *
+       * a.divNoNan(b).print();  // or tf.divNoNan(a, b)
+       * a.divNoNan(c).print();  // or tf.divNoNan(a, c)
+       * ```
+       *
+       * ```js
+       * // Broadcast div a with b.
+       * const a = tf.tensor1d([2, 4, 6, 8]);
+       * const b = tf.scalar(2);
+       * const c = tf.scalar(0);
+       *
+       * a.divNoNan(b).print();  // or tf.divNoNan(a, b)
+       * a.divNoNan(c).print();  // or tf.divNoNan(a, c)
+       * ```
+       *
+       * @param a The first tensor as the numerator.
+       * @param b The second tensor as the denominator. Must have the same dtype as
+       * `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function divNoNan_(a, b) {
+        // TODO: Make this into its own kernel.
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "div");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "div");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        const divResult = div($a, $b);
+        const zeros = Object(tensor_ops["o" /* zerosLike */])(divResult);
+        const bEqualsZero = $b.equal(zeros);
+        return where(bEqualsZero, zeros, divResult);
+      }
+      const divNoNan = Object(operation["a" /* op */])({ divNoNan_ });
+      //# sourceMappingURL=div_no_nan.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/dot.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the dot product of two matrices and/or vectors, `t1` and `t2`.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2]);
+       * const b = tf.tensor2d([[1, 2], [3, 4]]);
+       * const c = tf.tensor2d([[1, 2, 3], [4, 5, 6]]);
+       *
+       * a.dot(b).print();  // or tf.dot(a, b)
+       * b.dot(a).print();
+       * b.dot(c).print();
+       * ```
+       * @param t1 The first tensor in the dot operation.
+       * @param t2 The second tensor in the dot operation.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
+      function dot_(t1, t2) {
+        const $t1 = Object(tensor_util_env["a" /* convertToTensor */])(t1, "t1", "dot");
+        const $t2 = Object(tensor_util_env["a" /* convertToTensor */])(t2, "t2", "dot");
+        util["assert"](
+          ($t1.rank === 1 || $t1.rank === 2) && ($t2.rank === 1 || $t2.rank === 2),
+          () =>
+            `Error in dot: inputs must all be rank 1 or 2, but got ranks ` +
+            `${$t1.rank} and ${$t2.rank}.`
+        );
+        const t1Inner = $t1.rank === 1 ? $t1.size : $t1.shape[1];
+        const t2Inner = $t2.rank === 1 ? $t2.size : $t2.shape[0];
+        util["assert"](
+          t1Inner === t2Inner,
+          () =>
+            `Error in dot: inner dimensions of inputs must match, but got ` +
+            `${t1Inner} and ${t2Inner}.`
+        );
+        if ($t1.rank === 1 && $t2.rank === 1) {
+          const t12D = reshape($t1, [1, -1]);
+          const t22D = reshape($t2, [-1, 1]);
+          const t1t2 = matMul(t12D, t22D);
+          return reshape(t1t2, []);
+        } else if ($t1.rank === 1 && $t2.rank === 2) {
+          const t12D = reshape($t1, [1, -1]);
+          const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);
+          const t1t2 = matMul(t12D, t22D);
+          return reshape(t1t2, [t1t2.size]);
+        } else if ($t1.rank === 2 && $t2.rank === 1) {
+          const t22D = reshape($t2, [-1, 1]);
+          const t1t2 = matMul($t1, t22D);
+          return reshape(t1t2, [t1t2.size]);
+        } else {
+          const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);
+          const t1t2 = matMul($t1, t22D);
+          return t1t2;
+        }
+      }
+      const dot = Object(operation["a" /* op */])({ dot_ });
+      //# sourceMappingURL=dot.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/elu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes exponential linear element-wise: `x > 0 ? e ^ x - 1 : 0`.
+       *
+       * ```js
+       * const x = tf.tensor1d([-1, 1, -3, 2]);
+       *
+       * x.elu().print();  // or tf.elu(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function elu_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "elu");
+        const forward = (backend, save) => {
+          const y = backend.elu($x);
+          save([y]);
+          return y;
+        };
+        const inputs = { x: $x };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["z" /* Elu */]
+        );
+      }
+      const elu = Object(operation["a" /* op */])({ elu_ });
+      //# sourceMappingURL=elu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/equal.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the truth value of (a == b) element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       * const b = tf.tensor1d([2, 2, 2]);
+       *
+       * a.equal(b).print();
+       * ```
+       *
+       * @param a The first input tensor.
+       * @param b The second input tensor. Must have the same dtype as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function equal_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "equal");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "equal");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend) => backend.equal($a, $b);
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null,
+          kernel_names["B" /* Equal */]
+        );
+      }
+      const equal = Object(operation["a" /* op */])({ equal_ });
+      //# sourceMappingURL=equal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/eye.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Create an identity matrix.
+       *
+       * @param numRows Number of rows.
+       * @param numColumns Number of columns. Defaults to `numRows`.
+       * @param batchShape If provided, will add the batch shape to the beginning
+       *   of the shape of the returned `tf.Tensor` by repeating the identity
+       *   matrix.
+       * @param dtype Data type.
+       * @returns Identity matrix of the specified size and data type, possibly
+       *   with batch repetition if `batchShape` is specified.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function eye_(numRows, numColumns, batchShape, dtype = "float32") {
+        if (numColumns == null) {
+          numColumns = numRows;
+        }
+        const buff = array_ops_buffer([numRows, numColumns], dtype);
+        const n = numRows <= numColumns ? numRows : numColumns;
+        for (let i = 0; i < n; ++i) {
+          buff.set(1, i, i);
+        }
+        const out = buff.toTensor().as2D(numRows, numColumns);
+        if (batchShape == null) {
+          return out;
+        } else {
+          if (batchShape.length === 1) {
+            return tile(expandDims(out, 0), [batchShape[0], 1, 1]);
+          } else if (batchShape.length === 2) {
+            return tile(expandDims(expandDims(out, 0), 0), [batchShape[0], batchShape[1], 1, 1]);
+          } else if (batchShape.length === 3) {
+            return tile(expandDims(expandDims(expandDims(out, 0), 0), 0), [
+              batchShape[0],
+              batchShape[1],
+              batchShape[2],
+              1,
+              1,
+            ]);
+          } else {
+            throw new Error(
+              `eye() currently supports only 1D and 2D ` +
+                // tslint:disable-next-line:no-any
+                `batchShapes, but received ${batchShape.length}D.`
+            );
+          }
+        }
+      }
+      const eye = Object(operation["a" /* op */])({ eye_ });
+      //# sourceMappingURL=eye.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/fill.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a `tf.Tensor` filled with a scalar value.
+       *
+       * ```js
+       * tf.fill([2, 2], 4).print();
+       * ```
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param value The scalar value to fill the tensor with.
+       * @param dtype The type of an element in the resulting tensor. Defaults to
+       * 'float'.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function fill(shape, value, dtype) {
+        const attrs = { shape, value, dtype };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.fill(shape, value, dtype),
+          {},
+          null,
+          kernel_names["C" /* Fill */],
+          attrs
+        );
+      }
+
+      //# sourceMappingURL=fill.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/imag.js
+      var imag = __webpack_require__(25);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/maximum.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the max of a and b (`a > b ? a : b`) element-wise.
+       * Supports broadcasting.
+       *
+       * We also expose `tf.maximumStrict` which has the same signature as this op and
+       * asserts that `a` and `b` are the same shape (does not broadcast).
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 4, 3, 16]);
+       * const b = tf.tensor1d([1, 2, 9, 4]);
+       *
+       * a.maximum(b).print();  // or tf.maximum(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast maximum a with b.
+       * const a = tf.tensor1d([2, 4, 6, 8]);
+       * const b = tf.scalar(5);
+       *
+       * a.maximum(b).print();  // or tf.maximum(a, b)
+       * ```
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same type as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function maximum_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "maximum");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "maximum");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        if ($a.dtype === "bool") {
+          $a = cast($a, "int32");
+          $b = cast($b, "int32");
+        }
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend, save) => {
+          const res = backend.maximum($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["V" /* Maximum */]
+        );
+      }
+      const maximum = Object(operation["a" /* op */])({ maximum_ });
+      //# sourceMappingURL=maximum.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/leaky_relu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes leaky rectified linear element-wise.
+       *
+       * See
+       * [http://web.stanford.edu/~awni/papers/relu_hybrid_icml2013_final.pdf](
+       *     http://web.stanford.edu/~awni/papers/relu_hybrid_icml2013_final.pdf)
+       *
+       * ```js
+       * const x = tf.tensor1d([-1, 2, -3, 4]);
+       *
+       * x.leakyRelu(0.1).print();  // or tf.leakyRelu(x, 0.1)
+       * ```
+       * @param x The input tensor.
+       * @param alpha The scaling factor for negative values, defaults to 0.2.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function leakyRelu_(x, alpha = 0.2) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "leakyRelu");
+        return maximum(mul(Object(tensor_ops["e" /* scalar */])(alpha), $x), $x);
+      }
+      const leakyRelu = Object(operation["a" /* op */])({ leakyRelu_ });
+      //# sourceMappingURL=leaky_relu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/local_response_normalization.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Normalizes the activation of a local neighborhood across or within
+       * channels.
+       *
+       * @param x The input tensor. The 4-D input tensor is treated as a 3-D array
+       *     of 1D vectors (along the last dimension), and each vector is
+       *     normalized independently.
+       * @param depthRadius The number of adjacent channels in the 1D normalization
+       *     window.
+       * @param bias A constant bias term for the basis.
+       * @param alpha A scale factor, usually positive.
+       * @param beta An exponent.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
+      function localResponseNormalization_(x, depthRadius = 5, bias = 1, alpha = 1, beta = 0.5) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(
+          x,
+          "x",
+          "localResponseNormalization"
+        );
+        util["assert"](
+          $x.rank === 4 || $x.rank === 3,
+          () => `Error in localResponseNormalization: x must be rank 3 or 4 but got
+               rank ${$x.rank}.`
+        );
+        util["assert"](
+          util["isInt"](depthRadius),
+          () =>
+            `Error in localResponseNormalization: depthRadius must be an ` +
+            `integer but got depthRadius ${depthRadius}.`
+        );
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
+        }
+        const forward = (backend, save) => {
+          const y = backend.localResponseNormalization4D(x4D, depthRadius, bias, alpha, beta);
+          save([x4D, y]);
+          return y;
+        };
+        const inputs = { x: x4D };
+        const attrs = { depthRadius, bias, alpha, beta };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["L" /* LRN */],
+          attrs
+        );
+        if (reshapedTo4D) {
+          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
+        } else {
+          return res;
+        }
+      }
+      const localResponseNormalization = Object(operation["a" /* op */])({
+        localResponseNormalization_,
+      });
+      //# sourceMappingURL=local_response_normalization.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the maximum of elements across dimensions of a `tf.Tensor`.
+       *
+       * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
+       * is true, the rank of the `tf.Tensor` is reduced by 1 for each entry in
+       * `axes`. If `keepDims` is true, the reduced dimensions are retained with
+       * length 1. If `axes` has no entries, all dimensions are reduced, and an
+       * `tf.Tensor` with a single element is returned.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3]);
+       *
+       * x.max().print();  // or tf.max(x)
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * const axis = 1;
+       * x.max(axis).print();  // or tf.max(x, axis)
+       * ```
+       *
+       * @param x The input tensor.
+       * @param axis The dimension(s) to reduce. By default it reduces
+       *     all dimensions.
+       * @param keepDims If true, retains reduced dimensions with size 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Reduction'} */
+      function max_(x, axis = null, keepDims = false) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "max");
+        const forward = (backend, save) => {
+          const origAxes = util["parseAxisParam"](axis, $x.shape);
+          let axes = origAxes;
+          const permutedAxes = getAxesPermutation(axes, $x.rank);
+          let maxInput = $x;
+          if (permutedAxes != null) {
+            maxInput = transpose($x, permutedAxes);
+            axes = getInnerMostAxes(axes.length, maxInput.rank);
+          }
+          const y = backend.max(maxInput, axes);
+          save([$x, y]);
+          if (permutedAxes != null) {
+            backend.disposeData(maxInput.dataId);
+          }
+          return y;
+        };
+        const inputs = { x: $x };
+        const attrs = { reductionIndices: axis, keepDims };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["P" /* Max */],
+          attrs
+        );
+        if (keepDims) {
+          return reshape(
+            res,
+            expandShapeToKeepDim(res.shape, util["parseAxisParam"](axis, $x.shape))
+          );
+        }
+        return res;
+      }
+      const max_max = Object(operation["a" /* op */])({ max_ });
+      //# sourceMappingURL=max.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the 2D max pooling of an image.
+       *
+       * @param x The input tensor, of rank 4 or rank 3 of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
+       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
+       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
+       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
+       *     `strides` is a single number, then `strideHeight == strideWidth`.
+       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
+       *     in which we sample input values across the height and width dimensions
+       *     in dilated pooling. Defaults to `[1, 1]`. If `dilations` is a single
+       *     number, then `dilationHeight == dilationWidth`. If it is greater than
+       *     1, then all values of `strides` must be 1.
+       * @param pad The type of padding algorithm.
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *    - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       */
+      function maxPool_(x, filterSize, strides, pad, dimRoundingMode) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "maxPool");
+        const dilations = 1;
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
+        }
+        util["assert"](
+          x4D.rank === 4,
+          () => `Error in maxPool: input must be rank 4 but got rank ${x4D.rank}.`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in maxPool: Either strides or dilations must be 1. " +
+            `Got strides ${strides} and dilations '${dilations}'`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in maxPool: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend, save) => {
+          const convInfo = computePool2DInfo(
+            x4D.shape,
+            filterSize,
+            strides,
+            1 /* dilations */,
+            pad,
+            dimRoundingMode
+          );
+          let y;
+          if (
+            convInfo.filterWidth === 1 &&
+            convInfo.filterHeight === 1 &&
+            util["arraysEqual"](convInfo.inShape, convInfo.outShape)
+          ) {
+            y = x4D.clone();
+          } else {
+            y = backend.maxPool(x4D, convInfo);
+          }
+          save([x4D, y]);
+          return y;
+        };
+        const inputs = { x: x4D };
+        const attrs = { filterSize, strides, pad, dimRoundingMode };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["Q" /* MaxPool */],
+          attrs
+        );
+        if (reshapedTo4D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
+        }
+        return res;
+      }
+      const maxPool = Object(operation["a" /* op */])({ maxPool_ });
+      //# sourceMappingURL=max_pool.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_3d.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the 3D max pooling.
+       *
+       * ```js
+       * const x = tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]);
+       * const result = tf.maxPool3d(x, 2, 1, 'valid');
+       * result.print();
+       * ```
+       *
+       * @param x The input tensor, of rank 5 or rank 4 of shape
+       *     `[batch, depth, height, width, inChannels]`.
+       * @param filterSize The filter size:
+       *     `[filterDepth, filterHeight, filterWidth]`.
+       *     If `filterSize` is a single number,
+       *     then `filterDepth == filterHeight == filterWidth`.
+       * @param strides The strides of the pooling:
+       *     `[strideDepth, strideHeight, strideWidth]`.
+       *     If `strides` is a single number,
+       *     then `strideDepth == strideHeight == strideWidth`.
+       * @param pad The type of padding algorithm.
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1*1x1.
+       *    - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       * @param dataFormat An optional string from: "NDHWC", "NCDHW". Defaults to
+       *     "NDHWC". Specify the data format of the input and output data. With the
+       *     default format "NDHWC", the data is stored in the order of: [batch,
+       *     depth, height, width, channels]. Only "NDHWC" is currently supported.
+       * @param dilations Deprecated, this field will be gone in v3.0.0.
+       *     The dilation rates: `[dilationDepth, dilationHeight, dilationWidth]`
+       *     in which we sample input values across the depth, height and width
+       *     dimensions in dilated pooling.
+       *     Defaults to `[1, 1, 1]`. If `dilations` is a single number,
+       *     then `dilationDepth == dilationHeight == dilationWidth`.
+       *     If it is greater than 1, then all values of `strides` must be 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function maxPool3d_(
+        x,
+        filterSize = [1, 1, 1],
+        strides,
+        pad,
+        dimRoundingMode,
+        dataFormat = "NDHWC",
+        dilations
+      ) {
+        if (dilations == null) {
+          dilations = [1, 1, 1];
+        } else {
+          deprecationWarn("dilations is deprecated, this field will be gone in " + "v3.0.0.");
+        }
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "maxPool3d");
+        let x5D = $x;
+        let reshapedTo5D = false;
+        if ($x.rank === 4) {
+          reshapedTo5D = true;
+          x5D = $x.as5D(1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]);
+        }
+        util["assert"](
+          x5D.rank === 5,
+          () => `Error in maxPool3d: x must be rank 5 but got rank ${x5D.rank}.`
+        );
+        util["assert"](
+          dataFormat === "NDHWC",
+          () =>
+            `Error in maxPool3d: Only NDHWC is currently supported, ` +
+            `but got dataFormat of ${dataFormat}`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in maxPool3d: Either strides or dilations must be 1. " +
+            `Got strides ${strides} and dilations '${dilations}'`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in maxPool3d: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const forward = (backend, save) => {
+          if (dilations == null) {
+            dilations = [1, 1, 1];
+          }
+          const convInfo = computePool3DInfo(
+            x5D.shape,
+            filterSize,
+            strides,
+            dilations,
+            pad,
+            dimRoundingMode,
+            dataFormat
+          );
+          const y = backend.maxPool3d(x5D, convInfo);
+          save([x5D, y]);
+          return y;
+        };
+        const inputs = { x: x5D };
+        const attrs = { filterSize, strides, pad, dimRoundingMode, dataFormat, dilations };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["R" /* MaxPool3D */],
+          attrs
+        );
+        if (reshapedTo5D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);
+        }
+        return res;
+      }
+      const maxPool3d = Object(operation["a" /* op */])({ maxPool3d_ });
+      //# sourceMappingURL=max_pool_3d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_with_argmax.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the 2D max pooling of an image with Argmax index.
+       * The indices in argmax are flattened, so that a maximum value at position `[b,
+       * y, x, c]` becomes flattened index: `(y * width + x) * channels + c` if
+       * include_batch_in_index is False; `((b * height + y) * width + x) * channels
+       * +c` if include_batch_in_index is True.
+       *
+       * The indices returned are always in `[0, height) x [0, width)` before
+       * flattening.
+       *
+       * @param x The input tensor, of rank 4 or rank 3 of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
+       * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
+       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
+       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
+       *     `strides` is a single number, then `strideHeight == strideWidth`.
+       * @param dataFormat An optional string from: "NDHWC", "NCDHW". Defaults to
+       *     "NDHWC". Specify the data format of the input and output data. With the
+       *     default format "NDHWC", the data is stored in the order of: [batch,
+       *     depth, height, width, channels]. Only "NDHWC" is currently supported.
+       * @param pad The type of padding algorithm.
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *    - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param includeBatchIndex Defaults to False. Whether to include batch
+       *    dimension in flattened index of argmax.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function maxPoolWithArgmax_(x, filterSize, strides, pad, includeBatchInIndex = false) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "maxPoolWithArgmax");
+        const inputs = { x: $x };
+        const attrs = { filterSize, strides, pad, includeBatchInIndex };
+        const result = engine["a" /* ENGINE */].runKernel(
+          kernel_names["U" /* MaxPoolWithArgmax */],
+          inputs,
+          attrs
+        );
+        return { result: result[0], indexes: result[1] };
+      }
+      const maxPoolWithArgmax = Object(operation["a" /* op */])({ maxPoolWithArgmax_ });
+      //# sourceMappingURL=max_pool_with_argmax.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/minimum.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the min of a and b (`a < b ? a : b`) element-wise.
+       * Supports broadcasting.
+       *
+       * We also expose `minimumStrict` which has the same signature as this op and
+       * asserts that `a` and `b` are the same shape (does not broadcast).
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 4, 3, 16]);
+       * const b = tf.tensor1d([1, 2, 9, 4]);
+       *
+       * a.minimum(b).print();  // or tf.minimum(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast minimum a with b.
+       * const a = tf.tensor1d([2, 4, 6, 8]);
+       * const b = tf.scalar(5);
+       *
+       * a.minimum(b).print();  // or tf.minimum(a, b)
+       * ```
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same type as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function minimum_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "minimum");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "minimum");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        if ($a.dtype === "bool") {
+          $a = cast($a, "int32");
+          $b = cast($b, "int32");
+        }
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend, save) => {
+          const res = backend.minimum($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["W" /* Minimum */]
+        );
+      }
+      const minimum = Object(operation["a" /* op */])({ minimum_ });
+      //# sourceMappingURL=minimum.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/mod.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the mod of a and b element-wise.
+       * `floor(x / y) * y + mod(x, y) = x`
+       * Supports broadcasting.
+       *
+       * We also expose `tf.modStrict` which has the same signature as this op and
+       * asserts that `a` and `b` are the same shape (does not broadcast).
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 4, 3, 16]);
+       * const b = tf.tensor1d([1, 2, 9, 4]);
+       *
+       * a.mod(b).print();  // or tf.mod(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast a mod b.
+       * const a = tf.tensor1d([2, 4, 6, 8]);
+       * const b = tf.scalar(5);
+       *
+       * a.mod(b).print();  // or tf.mod(a, b)
+       * ```
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same type as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function mod_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "mod");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "mod");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        const forward = (backend, save) => {
+          const res = backend.mod($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["X" /* Mod */]
+        );
+      }
+      const mod = Object(operation["a" /* op */])({ mod_ });
+      //# sourceMappingURL=mod.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/multinomial.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a `tf.Tensor` with values drawn from a multinomial distribution.
+       *
+       * ```js
+       * const probs = tf.tensor([.75, .25]);
+       * tf.multinomial(probs, 3).print();
+       * ```
+       *
+       * @param logits 1D array with unnormalized log-probabilities, or
+       *     2D array of shape `[batchSize, numOutcomes]`. See the `normalized`
+       *     parameter.
+       * @param numSamples Number of samples to draw for each row slice.
+       * @param seed The seed number.
+       * @param normalized Whether the provided `logits` are normalized true
+       *     probabilities (sum to 1). Defaults to false.
+       * @return 1D array of shape `[numSamples]`, or 2D array of shape
+       *     `[batchSize, numSamples]`, depending on the rank of the input.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Random'} */
+      function multinomial_(logits, numSamples, seed, normalized = false) {
+        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
+          logits,
+          "logits",
+          "multinomial"
+        );
+        const numOutcomes = $logits.size;
+        const origRank = $logits.rank;
+        if (numOutcomes < 2) {
+          throw new Error(
+            `Error in multinomial: you need at least 2 outcomes, but got ` + `${numOutcomes}.`
+          );
+        }
+        if (origRank > 2) {
+          throw new Error(`Rank of probabilities must be 1 or 2, but is ${origRank}`);
+        }
+        seed = seed || Math.random();
+        const logits2D = origRank === 1 ? $logits.as2D(1, -1) : $logits;
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.multinomial(logits2D, normalized, numSamples, seed),
+          { logits2D }
+        );
+        return origRank === 1 ? res.as1D() : res;
+      }
+      const multinomial = Object(operation["a" /* op */])({ multinomial_ });
+      //# sourceMappingURL=multinomial.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/not_equal.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the truth value of (a != b) element-wise. Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       * const b = tf.tensor1d([0, 2, 3]);
+       *
+       * a.notEqual(b).print();
+       * ```
+       * @param a The first input tensor.
+       * @param b The second input tensor. Must have the same dtype as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Logical'} */
+      function notEqual_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "notEqual");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "notEqual");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend) => backend.notEqual($a, $b);
+        const inputs = { a: $a, b: $b };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["bb" /* NotEqual */]
+        );
+      }
+      const notEqual = Object(operation["a" /* op */])({ notEqual_ });
+      //# sourceMappingURL=not_equal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/outer_product.js
+
+      /**
+       * Computes the outer product of two vectors, `v1` and `v2`.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       * const b = tf.tensor1d([3, 4, 5]);
+       *
+       * tf.outerProduct(a, b).print();
+       * ```
+       * @param v1 The first vector in the outer product operation.
+       * @param v2 The second vector in the outer product operation.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
+      function outerProduct_(v1, v2) {
+        const $v1 = Object(tensor_util_env["a" /* convertToTensor */])(v1, "v1", "outerProduct");
+        const $v2 = Object(tensor_util_env["a" /* convertToTensor */])(v2, "v2", "outerProduct");
+        util["assert"](
+          $v1.rank === 1 && $v2.rank === 1,
+          () =>
+            `Error in outerProduct: inputs must be rank 1, but got ranks ` +
+            `${$v1.rank} and ${$v2.rank}.`
+        );
+        const v12D = reshape($v1, [-1, 1]);
+        const v22D = reshape($v2, [1, -1]);
+        return matMul(v12D, v22D);
+      }
+      const outerProduct = Object(operation["a" /* op */])({ outerProduct_ });
+      //# sourceMappingURL=outer_product.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad1d.js
+
+      /**
+       * Pads a `tf.Tensor1D` with a given value and paddings. See `pad` for details.
+       */
+      function pad1d_(x, paddings, constantValue = 0) {
+        Object(util["assert"])(
+          paddings.length === 2,
+          () => "Invalid number of paddings. Must be length of 2."
+        );
+        return pad_pad(x, [paddings], constantValue);
+      }
+      const pad1d = Object(operation["a" /* op */])({ pad1d_ });
+      //# sourceMappingURL=pad1d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad2d.js
+
+      /**
+       * Pads a `tf.Tensor2D` with a given value and paddings. See `pad` for details.
+       */
+      function pad2d_(x, paddings, constantValue = 0) {
+        Object(util["assert"])(
+          paddings.length === 2 && paddings[0].length === 2 && paddings[1].length === 2,
+          () => "Invalid number of paddings. Must be length of 2 each."
+        );
+        return pad_pad(x, paddings, constantValue);
+      }
+      const pad2d = Object(operation["a" /* op */])({ pad2d_ });
+      //# sourceMappingURL=pad2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad3d.js
+
+      /**
+       * Pads a `tf.Tensor3D` with a given value and paddings. See `pad` for details.
+       */
+      function pad3d_(x, paddings, constantValue = 0) {
+        Object(util["assert"])(
+          paddings.length === 3 &&
+            paddings[0].length === 2 &&
+            paddings[1].length === 2 &&
+            paddings[2].length === 2,
+          () => "Invalid number of paddings. Must be length of 2 each."
+        );
+        return pad_pad(x, paddings, constantValue);
+      }
+      const pad3d = Object(operation["a" /* op */])({ pad3d_ });
+      //# sourceMappingURL=pad3d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pad4d.js
+
+      /**
+       * Pads a `tf.Tensor4D` with a given value and paddings. See `pad` for details.
+       */
+      function pad4d_(x, paddings, constantValue = 0) {
+        Object(util["assert"])(
+          paddings.length === 4 &&
+            paddings[0].length === 2 &&
+            paddings[1].length === 2 &&
+            paddings[2].length === 2 &&
+            paddings[3].length === 2,
+          () => "Invalid number of paddings. Must be length of 2 each."
+        );
+        return pad_pad(x, paddings, constantValue);
+      }
+      const pad4d = Object(operation["a" /* op */])({ pad4d_ });
+      //# sourceMappingURL=pad4d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/pool.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Performs an N-D pooling operation
+       *
+       * @param input The input tensor, of rank 4 or rank 3 of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
+       * @param windowShape The filter size: `[filterHeight, filterWidth]`. If
+       *     `filterSize` is a single number, then `filterHeight == filterWidth`.
+       * @param poolingType The type of pooling, either 'max' or 'avg'.
+       * @param pad The type of padding algorithm:
+       *    - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *    - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *    - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *         https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
+       *     in which we sample input values across the height and width dimensions
+       *     in dilated pooling. Defaults to `[1, 1]`. If `dilationRate` is a single
+       *     number, then `dilationHeight == dilationWidth`. If it is greater than
+       *     1, then all values of `strides` must be 1.
+       * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
+       *     `strides` is a single number, then `strideHeight == strideWidth`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function pool_(input, windowShape, poolingType, pad, dilations, strides) {
+        if (dilations == null) {
+          dilations = [1, 1];
+        }
+        if (strides == null) {
+          strides = 1;
+        }
+        if (pad === 0) {
+          pad = "valid";
+        }
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(input, "x", "maxPool");
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
+        }
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in pool: Either strides or dilations must be 1. " +
+            `Got strides ${strides} and dilations '${dilations}'`
+        );
+        const convInfo = computePool2DInfo(x4D.shape, windowShape, strides, dilations, pad);
+        const dilation = [convInfo.dilationHeight, convInfo.dilationWidth];
+        // The following implementation does batchToSpace(pool(spaceToBatch(x)))
+        // whenever dilation > 1 since the TF kernels do not support dilation > 1.
+        // tslint:disable-next-line:max-line-length
+        // https://github.com/tensorflow/tensorflow/blob/50f6bb67dc98c9b74630b6047aae7a4f8a40fd02/tensorflow/python/ops/nn_ops.py#L1037
+        let basePadding;
+        if (pad === "same") {
+          basePadding = withSpaceToBatchBasePaddings(
+            [convInfo.filterHeight, convInfo.filterWidth],
+            dilation
+          );
+        } else {
+          basePadding = [
+            [0, 0],
+            [0, 0],
+          ];
+        }
+        const isDilationOne = dilation[0] === 1 && dilation[1] === 1;
+        const [adjustedPadding, adjustedCrops] = requiredSpaceToBatchPaddings(
+          [convInfo.inHeight, convInfo.inWidth],
+          dilation,
+          basePadding
+        );
+        const convertedPad = isDilationOne ? pad : "valid";
+        const convertedX = isDilationOne ? x4D : spaceToBatchND(x4D, dilation, adjustedPadding);
+        const forwardOp =
+          poolingType === "avg"
+            ? () => avgPool(convertedX, windowShape, strides, convertedPad)
+            : () => maxPool(convertedX, windowShape, strides, convertedPad);
+        const y = forwardOp();
+        const res = isDilationOne ? y : batchToSpaceND(y, dilation, adjustedCrops);
+        if (reshapedTo4D) {
+          return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
+        }
+        return res;
+      }
+      // Helper function to compute crops and paddings for pool with dilation > 1.
+      // tslint:disable-next-line:max-line-length
+      // https://github.com/tensorflow/tensorflow/blob/50f6bb67dc98c9b74630b6047aae7a4f8a40fd02/tensorflow/python/ops/array_ops.py#L2184
+      function requiredSpaceToBatchPaddings(inputShape, blockShape, basePadding) {
+        const padStart = basePadding.map((b) => b[0]);
+        const origPadEnd = basePadding.map((b) => b[1]);
+        const fullInputShape = inputShape.concat(padStart, origPadEnd);
+        const padEndExtra = blockShape.map((b, i) => (b - (fullInputShape[i] % b)) % b);
+        const padEnd = origPadEnd.map((s, i) => s + padEndExtra[i]);
+        const paddings = blockShape.map((_, i) => [padStart[i], padEnd[i]]);
+        const crops = blockShape.map((_, i) => [0, padEndExtra[i]]);
+        return [paddings, crops];
+      }
+      // Helper function to compute base paddings for pool with dilation > 1.
+      // tslint:disable-next-line:max-line-length
+      // https://github.com/tensorflow/tensorflow/blob/50f6bb67dc98c9b74630b6047aae7a4f8a40fd02/tensorflow/python/ops/nn_ops.py#L524
+      function withSpaceToBatchBasePaddings(filterShape, dilation) {
+        // Spatial dimensions of the filters and the upsampled filters in which we
+        // introduce (rate - 1) zeros between consecutive filter values.
+        const dilatedFilterShape = filterShape.map((s, i) => {
+          return s + (s - 1) * (dilation[i] - 1);
+        });
+        const padExtraShape = dilatedFilterShape.map((s) => s - 1);
+        // When padding is odd, we pad more at end, following the same
+        // convention as conv2d.
+        const padExtraStart = padExtraShape.map((s) => Math.floor(s / 2));
+        const padExtraEnd = padExtraShape.map((s, i) => s - padExtraStart[i]);
+        return padExtraShape.map((_, i) => {
+          return [padExtraStart[i], padExtraEnd[i]];
+        });
+      }
+      const pool = Object(operation["a" /* op */])({ pool_ });
+      //# sourceMappingURL=pool.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/prelu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes leaky rectified linear element-wise with parametric alphas.
+       *
+       * `x < 0 ? alpha * x : f(x) = x`
+       *
+       * ```js
+       * const x = tf.tensor1d([-1, 2, -3, 4]);
+       * const alpha = tf.scalar(0.1);
+       *
+       * x.prelu(alpha).print();  // or tf.prelu(x, alpha)
+       * ```
+       * @param x The input tensor.
+       * @param alpha Scaling factor for negative values.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function prelu_(x, alpha) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "prelu");
+        const $alpha = Object(tensor_util_env["a" /* convertToTensor */])(alpha, "alpha", "prelu");
+        const forward = (backend, save) => {
+          const res = backend.prelu($x, $alpha);
+          save([$x, $alpha]);
+          return res;
+        };
+        const inputs = { x: $x, alpha: $alpha };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["gb" /* Prelu */]
+        );
+      }
+      const prelu = Object(operation["a" /* op */])({ prelu_ });
+      //# sourceMappingURL=prelu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/rand.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a `tf.Tensor` with values sampled from a random number generator
+       * function defined by the user.
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param randFunction A random number generator function which is called
+       * for each element in the output tensor.
+       * @param dtype The data type of the output tensor. Defaults to 'float32'.
+       */
+      function rand_(shape, randFunction, dtype) {
+        const size = Object(util["sizeFromShape"])(shape);
+        let values = null;
+        if (dtype == null || dtype === "float32") {
+          values = new Float32Array(size);
+        } else if (dtype === "int32") {
+          values = new Int32Array(size);
+        } else if (dtype === "bool") {
+          values = new Uint8Array(size);
+        } else {
+          throw new Error(`Unknown data type ${dtype}`);
+        }
+        for (let i = 0; i < size; i++) {
+          values[i] = randFunction();
+        }
+        return engine["a" /* ENGINE */].makeTensor(values, shape, dtype);
+      }
+      const rand = Object(operation["a" /* op */])({ rand_ });
+      //# sourceMappingURL=rand.js.map
+      // EXTERNAL MODULE: ./node_modules/seedrandom/index.js
+      var seedrandom = __webpack_require__(20);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/rand_util.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // https://en.wikipedia.org/wiki/Marsaglia_polar_method
+      class rand_util_MPRandGauss {
+        constructor(mean, stdDeviation, dtype, truncated, seed) {
+          this.mean = mean;
+          this.stdDev = stdDeviation;
+          this.dtype = dtype;
+          this.nextVal = NaN;
+          this.truncated = truncated;
+          if (this.truncated) {
+            this.upper = this.mean + this.stdDev * 2;
+            this.lower = this.mean - this.stdDev * 2;
+          }
+          const seedValue = seed ? seed : Math.random();
+          this.random = seedrandom["alea"](seedValue.toString());
+        }
+        /** Returns next sample from a Gaussian distribution. */
+        nextValue() {
+          if (!isNaN(this.nextVal)) {
+            const value = this.nextVal;
+            this.nextVal = NaN;
+            return value;
+          }
+          let resultX, resultY;
+          let isValid = false;
+          while (!isValid) {
+            let v1, v2, s;
+            do {
+              v1 = 2 * this.random() - 1;
+              v2 = 2 * this.random() - 1;
+              s = v1 * v1 + v2 * v2;
+            } while (s >= 1 || s === 0);
+            const mul = Math.sqrt((-2.0 * Math.log(s)) / s);
+            resultX = this.mean + this.stdDev * v1 * mul;
+            resultY = this.mean + this.stdDev * v2 * mul;
+            if (!this.truncated || this.isValidTruncated(resultX)) {
+              isValid = true;
+            }
+          }
+          if (!this.truncated || this.isValidTruncated(resultY)) {
+            this.nextVal = this.convertValue(resultY);
+          }
+          return this.convertValue(resultX);
+        }
+        /** Handles proper rounding for non-floating-point numbers. */
+        convertValue(value) {
+          if (this.dtype == null || this.dtype === "float32") {
+            return value;
+          }
+          return Math.round(value);
+        }
+        /** Returns true if less than 2-standard-deviations from the mean. */
+        isValidTruncated(value) {
+          return value <= this.upper && value >= this.lower;
+        }
+      }
+      // Marsaglia, George, and Wai Wan Tsang. 2000. "A Simple Method for Generating
+      // Gamma Variables."
+      class rand_util_RandGamma {
+        constructor(alpha, beta, dtype, seed) {
+          this.alpha = alpha;
+          this.beta = 1 / beta; // convert rate to scale parameter
+          this.dtype = dtype;
+          const seedValue = seed ? seed : Math.random();
+          this.randu = seedrandom["alea"](seedValue.toString());
+          this.randn = new rand_util_MPRandGauss(0, 1, dtype, false, this.randu());
+          if (alpha < 1) {
+            this.d = alpha + 2 / 3;
+          } else {
+            this.d = alpha - 1 / 3;
+          }
+          this.c = 1 / Math.sqrt(9 * this.d);
+        }
+        /** Returns next sample from a gamma distribution. */
+        nextValue() {
+          let x2, v0, v1, x, u, v;
+          while (true) {
+            do {
+              x = this.randn.nextValue();
+              v = 1 + this.c * x;
+            } while (v <= 0);
+            v *= v * v;
+            x2 = x * x;
+            v0 = 1 - 0.331 * x2 * x2;
+            v1 = 0.5 * x2 + this.d * (1 - v + Math.log(v));
+            u = this.randu();
+            if (u < v0 || Math.log(u) < v1) {
+              break;
+            }
+          }
+          v = (1 / this.beta) * this.d * v;
+          if (this.alpha < 1) {
+            v *= Math.pow(this.randu(), 1 / this.alpha);
+          }
+          return this.convertValue(v);
+        }
+        /** Handles proper rounding for non-floating-point numbers. */
+        convertValue(value) {
+          if (this.dtype === "float32") {
+            return value;
+          }
+          return Math.round(value);
+        }
+      }
+      class rand_util_UniformRandom {
+        constructor(min = 0, max = 1, dtype, seed) {
+          /** Handles proper rounding for non floating point numbers. */
+          this.canReturnFloat = () => this.dtype == null || this.dtype === "float32";
+          this.min = min;
+          this.range = max - min;
+          this.dtype = dtype;
+          if (seed == null) {
+            seed = Math.random();
+          }
+          if (typeof seed === "number") {
+            seed = seed.toString();
+          }
+          if (!this.canReturnFloat() && this.range <= 1) {
+            throw new Error(`The difference between ${min} - ${max} <= 1 and dtype is not float`);
+          }
+          this.random = seedrandom["alea"](seed);
+        }
+        convertValue(value) {
+          if (this.canReturnFloat()) {
+            return value;
+          }
+          return Math.round(value);
+        }
+        nextValue() {
+          return this.convertValue(this.min + this.range * this.random());
+        }
+      }
+      function jarqueBeraNormalityTest(values) {
+        // https://en.wikipedia.org/wiki/Jarque%E2%80%93Bera_test
+        const n = values.length;
+        const s = skewness(values);
+        const k = kurtosis(values);
+        const jb = (n / 6) * (Math.pow(s, 2) + 0.25 * Math.pow(k - 3, 2));
+        // JB test requires 2-degress of freedom from Chi-Square @ 0.95:
+        // http://www.itl.nist.gov/div898/handbook/eda/section3/eda3674.htm
+        const CHI_SQUARE_2DEG = 5.991;
+        if (jb > CHI_SQUARE_2DEG) {
+          throw new Error(`Invalid p-value for JB: ${jb}`);
+        }
+      }
+      function expectArrayInMeanStdRange(actual, expectedMean, expectedStdDev, epsilon) {
+        if (epsilon == null) {
+          epsilon = testEpsilon();
+        }
+        const actualMean = rand_util_mean(actual);
+        expectNumbersClose(actualMean, expectedMean, epsilon);
+        expectNumbersClose(standardDeviation(actual, actualMean), expectedStdDev, epsilon);
+      }
+      function rand_util_mean(values) {
+        let sum = 0;
+        for (let i = 0; i < values.length; i++) {
+          sum += values[i];
+        }
+        return sum / values.length;
+      }
+      function standardDeviation(values, mean) {
+        let squareDiffSum = 0;
+        for (let i = 0; i < values.length; i++) {
+          const diff = values[i] - mean;
+          squareDiffSum += diff * diff;
+        }
+        return Math.sqrt(squareDiffSum / values.length);
+      }
+      function kurtosis(values) {
+        // https://en.wikipedia.org/wiki/Kurtosis
+        const valuesMean = rand_util_mean(values);
+        const n = values.length;
+        let sum2 = 0;
+        let sum4 = 0;
+        for (let i = 0; i < n; i++) {
+          const v = values[i] - valuesMean;
+          sum2 += Math.pow(v, 2);
+          sum4 += Math.pow(v, 4);
+        }
+        return ((1 / n) * sum4) / Math.pow((1 / n) * sum2, 2);
+      }
+      function skewness(values) {
+        // https://en.wikipedia.org/wiki/Skewness
+        const valuesMean = rand_util_mean(values);
+        const n = values.length;
+        let sum2 = 0;
+        let sum3 = 0;
+        for (let i = 0; i < n; i++) {
+          const v = values[i] - valuesMean;
+          sum2 += Math.pow(v, 2);
+          sum3 += Math.pow(v, 3);
+        }
+        return ((1 / n) * sum3) / Math.pow((1 / (n - 1)) * sum2, 3 / 2);
+      }
+      //# sourceMappingURL=rand_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/random_gamma.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a `tf.Tensor` with values sampled from a gamma distribution.
+       *
+       * ```js
+       * tf.randomGamma([2, 2], 1).print();
+       * ```
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param alpha The shape parameter of the gamma distribution.
+       * @param beta The inverse scale parameter of the gamma distribution. Defaults
+       *     to 1.
+       * @param dtype The data type of the output. Defaults to float32.
+       * @param seed The seed for the random number generator.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Random'} */
+      function randomGamma_(shape, alpha, beta = 1, dtype = "float32", seed) {
+        if (beta == null) {
+          beta = 1;
+        }
+        if (dtype == null) {
+          dtype = "float32";
+        }
+        if (dtype !== "float32" && dtype !== "int32") {
+          throw new Error(`Unsupported data type ${dtype}`);
+        }
+        const rgamma = new rand_util_RandGamma(alpha, beta, dtype, seed);
+        const res = array_ops_buffer(shape, dtype);
+        for (let i = 0; i < res.values.length; i++) {
+          res.values[i] = rgamma.nextValue();
+        }
+        return res.toTensor();
+      }
+      const randomGamma = Object(operation["a" /* op */])({ randomGamma_ });
+      //# sourceMappingURL=random_gamma.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/random_normal.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a `tf.Tensor` with values sampled from a normal distribution.
+       *
+       * ```js
+       * tf.randomNormal([2, 2]).print();
+       * ```
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param mean The mean of the normal distribution.
+       * @param stdDev The standard deviation of the normal distribution.
+       * @param dtype The data type of the output.
+       * @param seed The seed for the random number generator.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Random'} */
+      function randomNormal_(shape, mean = 0, stdDev = 1, dtype, seed) {
+        if (dtype != null && dtype === "bool") {
+          throw new Error(`Unsupported data type ${dtype}`);
+        }
+        const randGauss = new rand_util_MPRandGauss(
+          mean,
+          stdDev,
+          dtype,
+          false /* truncated */,
+          seed
+        );
+        const res = array_ops_buffer(shape, dtype);
+        for (let i = 0; i < res.values.length; i++) {
+          res.values[i] = randGauss.nextValue();
+        }
+        return res.toTensor();
+      }
+      const randomNormal = Object(operation["a" /* op */])({ randomNormal_ });
+      //# sourceMappingURL=random_normal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/random_uniform.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a `tf.Tensor` with values sampled from a uniform distribution.
+       *
+       * The generated values follow a uniform distribution in the range [minval,
+       * maxval). The lower bound minval is included in the range, while the upper
+       * bound maxval is excluded.
+       *
+       * ```js
+       * tf.randomUniform([2, 2]).print();
+       * ```
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param minval The lower bound on the range of random values to generate.
+       *   Defaults to 0.
+       * @param maxval The upper bound on the range of random values to generate.
+       *   Defaults to 1.
+       * @param dtype The data type of the output tensor. Defaults to 'float32'.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Random'} */
+      function randomUniform_(shape, minval = 0, maxval = 1, dtype = "float32", seed) {
+        const res = array_ops_buffer(shape, dtype);
+        const random = new rand_util_UniformRandom(minval, maxval, null, seed);
+        for (let i = 0; i < res.values.length; i++) {
+          res.values[i] = random.nextValue();
+        }
+        return res.toTensor();
+      }
+      const randomUniform = Object(operation["a" /* op */])({ randomUniform_ });
+      //# sourceMappingURL=random_uniform.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/real.js
+      var real = __webpack_require__(22);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/relu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes rectified linear element-wise: `max(x, 0)`.
+       *
+       * ```js
+       * const x = tf.tensor1d([-1, 2, -3, 4]);
+       *
+       * x.relu().print();  // or tf.relu(x)
+       * ```
+       * @param x The input tensor. If the dtype is `bool`, the output dtype will be
+       *     `int32'.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function relu_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "relu");
+        const forward = (backend, save) => {
+          save([$x]);
+          if ($x.dtype === "bool") {
+            return $x.toInt();
+          }
+          return backend.relu($x);
+        };
+        const inputs = { x: $x };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["ib" /* Relu */]
+        );
+      }
+      const relu = Object(operation["a" /* op */])({ relu_ });
+      //# sourceMappingURL=relu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/relu6.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes rectified linear 6 element-wise: `min(max(x, 0), 6)`.
+       *
+       * ```js
+       * const x = tf.tensor1d([-1, 2, -3, 8]);
+       *
+       * x.relu6().print();  // or tf.relu6(x)
+       * ```
+       * @param x The input tensor. If the dtype is `bool`, the output dtype will be
+       *     `int32'.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function relu6_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "relu6");
+        const forward = (backend, save) => {
+          save([$x]);
+          if ($x.dtype === "bool") {
+            return cast($x, "int32");
+          }
+          return backend.relu6($x);
+        };
+        const inputs = { x: $x };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["jb" /* Relu6 */]
+        );
+      }
+      const relu6 = Object(operation["a" /* op */])({ relu6_ });
+      //# sourceMappingURL=relu6.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/selu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes scaled exponential linear element-wise.
+       *
+       * `x < 0 ? scale * alpha * (exp(x) - 1) : x`
+       *
+       * ```js
+       * const x = tf.tensor1d([-1, 2, -3, 4]);
+       *
+       * x.selu().print();  // or tf.selu(x)
+       * ```
+       * @param x The input tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Basic math'} */
+      function selu_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "selu");
+        const forward = (backend, save) => {
+          const res = backend.selu($x);
+          save([$x]);
+          return res;
+        };
+        const inputs = { x: $x };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["lb" /* Selu */]
+        );
+      }
+      const selu = Object(operation["a" /* op */])({ selu_ });
+      //# sourceMappingURL=selu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/separable_conv2d.js
+
+      /**
+       * 2-D convolution with separable filters.
+       *
+       * Performs a depthwise convolution that acts separately on channels followed
+       * by a pointwise convolution that mixes channels. Note that this is
+       * separability between dimensions [1, 2] and 3, not spatial separability
+       * between dimensions 1 and 2.
+       *
+       * See
+       * [https://www.tensorflow.org/api_docs/python/tf/nn/separable_conv2d](
+       *     https://www.tensorflow.org/api_docs/python/tf/nn/separable_conv2d)
+       * for more details.
+       *
+       * @param x The input tensor, of rank 4 or rank 3, of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
+       * assumed.
+       * @param depthwiseFilter The depthwise filter tensor, rank 4, of shape
+       *     `[filterHeight, filterWidth, inChannels, channelMultiplier]`. This is
+       *     the filter used in the first step.
+       * @param pointwiseFilter The pointwise filter tensor, rank 4, of shape
+       *     `[1, 1, inChannels * channelMultiplier, outChannels]`. This is
+       *     the filter used in the second step.
+       * @param strides The strides of the convolution: `[strideHeight,
+       * strideWidth]`. If strides is a single number, then `strideHeight ==
+       * strideWidth`.
+       * @param pad The type of padding algorithm.
+       *   - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *   - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *   - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
+       *     in which we sample input values across the height and width dimensions
+       *     in atrous convolution. Defaults to `[1, 1]`. If `rate` is a single
+       *     number, then `dilationHeight == dilationWidth`. If it is greater than
+       *     1, then all values of `strides` must be 1.
+       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
+       *     "NHWC". Specify the data format of the input and output data. With the
+       *     default format "NHWC", the data is stored in the order of: [batch,
+       *     height, width, channels]. Only "NHWC" is currently supported.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Convolution'} */
+      function separableConv2d_(
+        x,
+        depthwiseFilter,
+        pointwiseFilter,
+        strides,
+        pad,
+        dilation = [1, 1],
+        dataFormat = "NHWC"
+      ) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "separableConv2d");
+        const $depthwiseFilter = Object(tensor_util_env["a" /* convertToTensor */])(
+          depthwiseFilter,
+          "depthwiseFilter",
+          "separableConv2d"
+        );
+        const $pointwiseFilter = Object(tensor_util_env["a" /* convertToTensor */])(
+          pointwiseFilter,
+          "pointwiseFilter",
+          "separableConv2d"
+        );
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = $x.as4D(1, $x.shape[0], $x.shape[1], $x.shape[2]);
+        }
+        if (dataFormat === "NCHW") {
+          throw new Error(
+            "separableConv2d currently does not support dataFormat NCHW; only " +
+              "NHWC is supported"
+          );
+        }
+        util["assert"](
+          x4D.rank === 4,
+          () => `Error in separableConv2d: input must be rank 4, but got ` + `rank ${x4D.rank}.`
+        );
+        util["assert"](
+          $depthwiseFilter.rank === 4,
+          () =>
+            `Error in separableConv2d: depthwise filter must be rank 4, but ` +
+            `got rank ${$depthwiseFilter.rank}.`
+        );
+        util["assert"](
+          $pointwiseFilter.rank === 4,
+          () =>
+            `Error in separableConv2d: pointwise filter must be rank 4, but ` +
+            `got rank ${$depthwiseFilter.rank}.`
+        );
+        util["assert"](
+          $pointwiseFilter.shape[0] === 1,
+          () =>
+            `Error in separableConv2d: the first dimension of pointwise filter ` +
+            ` must be 1, but got ${$pointwiseFilter.shape[0]}.`
+        );
+        util["assert"](
+          $pointwiseFilter.shape[1] === 1,
+          () =>
+            `Error in separableConv2d: the second dimension of pointwise ` +
+            `filter must be 1, but got ${$pointwiseFilter.shape[1]}.`
+        );
+        const inChannels = $depthwiseFilter.shape[2];
+        const channelMultiplier = $depthwiseFilter.shape[3];
+        util["assert"](
+          $pointwiseFilter.shape[2] === inChannels * channelMultiplier,
+          () =>
+            `Error in separableConv2d: the third dimension of pointwise filter ` +
+            `must be ${inChannels * channelMultiplier}, ` +
+            `but got ${$pointwiseFilter.shape[2]}.`
+        );
+        const depthwise = depthwiseConv2d(
+          x4D,
+          $depthwiseFilter,
+          strides,
+          pad,
+          dataFormat,
+          dilation
+        );
+        const pointwiseStride = 1;
+        const res = conv2d(depthwise, $pointwiseFilter, pointwiseStride, "valid", dataFormat);
+        if (reshapedTo4D) {
+          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
+        }
+        return res;
+      }
+      const separableConv2d = Object(operation["a" /* op */])({ separableConv2d_ });
+      //# sourceMappingURL=separable_conv2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/squared_difference.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns (a - b) * (a - b) element-wise.
+       * Supports broadcasting.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 4, 3, 16]);
+       * const b = tf.tensor1d([1, 2, 9, 4]);
+       *
+       * a.squaredDifference(b).print();  // or tf.squaredDifference(a, b)
+       * ```
+       *
+       * ```js
+       * // Broadcast squared difference  a with b.
+       * const a = tf.tensor1d([2, 4, 6, 8]);
+       * const b = tf.scalar(5);
+       *
+       * a.squaredDifference(b).print();  // or tf.squaredDifference(a, b)
+       * ```
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same type as `a`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Arithmetic'} */
+      function squaredDifference_(a, b) {
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "squaredDifference");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "squaredDifference");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        assertAndGetBroadcastShape($a.shape, $b.shape);
+        const forward = (backend, save) => {
+          const res = backend.squaredDifference($a, $b);
+          save([$a, $b]);
+          return res;
+        };
+        const inputs = { a: $a, b: $b };
+        const attrs = {};
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* grad */,
+          kernel_names["pb" /* SquaredDifference */],
+          attrs
+        );
+      }
+      const squaredDifference = Object(operation["a" /* op */])({ squaredDifference_ });
+      //# sourceMappingURL=squared_difference.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/truncated_normal.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a `tf.Tensor` with values sampled from a truncated normal
+       * distribution.
+       *
+       * ```js
+       * tf.truncatedNormal([2, 2]).print();
+       * ```
+       *
+       * The generated values follow a normal distribution with specified mean and
+       * standard deviation, except that values whose magnitude is more than 2
+       * standard deviations from the mean are dropped and re-picked.
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param mean The mean of the normal distribution.
+       * @param stdDev The standard deviation of the normal distribution.
+       * @param dtype The data type of the output tensor.
+       * @param seed The seed for the random number generator.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function truncatedNormal_(shape, mean = 0, stdDev = 1, dtype, seed) {
+        if (dtype != null && dtype === "bool") {
+          throw new Error(`Unsupported data type $ { dtype }`);
+        }
+        const randGauss = new rand_util_MPRandGauss(
+          mean,
+          stdDev,
+          dtype,
+          true /* truncated */,
+          seed
+        );
+        const res = array_ops_buffer(shape, dtype);
+        for (let i = 0; i < res.values.length; i++) {
+          res.values[i] = randGauss.nextValue();
+        }
+        return res.toTensor();
+      }
+      const truncatedNormal = Object(operation["a" /* op */])({ truncatedNormal_ });
+      //# sourceMappingURL=truncated_normal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/reduce_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Inputs of size above this threshold will be parallelized by calling multiple
+       * shader programs.
+       */
+
+      const PARALLELIZE_THRESHOLD = 30;
+      function computeOptimalWindowSize(inSize) {
+        if (inSize <= PARALLELIZE_THRESHOLD) {
+          return inSize;
+        }
+        return Object(util["nearestDivisor"])(inSize, Math.floor(Math.sqrt(inSize)));
+      }
+      //# sourceMappingURL=reduce_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/segment_util.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function segOpComputeOptimalWindowSize(inSize, numSegments) {
+        let done = false;
+        let res;
+        if (inSize <= PARALLELIZE_THRESHOLD) {
+          res = inSize;
+          done = true;
+        } else {
+          res = Object(util["nearestDivisor"])(inSize, Math.floor(Math.sqrt(inSize)));
+        }
+        while (!done) {
+          if (res > numSegments || res === inSize) {
+            done = true;
+          } else {
+            res = Object(util["nearestDivisor"])(inSize, res + 1);
+          }
+        }
+        return res;
+      }
+      function segment_util_computeOutShape(aShape, axis, numSegments) {
+        const outShape = [];
+        const rank = aShape.length;
+        for (let dim = 0; dim < rank; dim++) {
+          if (dim !== axis) {
+            outShape.push(aShape[dim]);
+          } else {
+            outShape.push(numSegments);
+          }
+        }
+        return outShape;
+      }
+      function collectGatherOpShapeInfo(x, indices, axis) {
+        const dimSize = x.shape[axis];
+        const outputShape = [];
+        let batchSize = 1;
+        let sliceSize = 1;
+        for (let i = 0; i < axis; i++) {
+          outputShape.push(x.shape[i]);
+          batchSize *= x.shape[i];
+        }
+        for (let i = 0; i < indices.rank; i++) {
+          outputShape.push(indices.shape[i]);
+        }
+        for (let i = axis + 1; i < x.rank; i++) {
+          outputShape.push(x.shape[i]);
+          sliceSize *= x.shape[i];
+        }
+        return { batchSize, sliceSize, dimSize, outputShape };
+      }
+      //# sourceMappingURL=segment_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/segment_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the sum along segments of a `tf.Tensor`.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       * const segmentIds = tf.tensor1d([1, 2, 0, 1], 'int32');
+       * const numSegments = 3;
+       *
+       * x.unsortedSegmentSum(segmentIds, numSegments).print()
+       * //or tf.unsortedSegmentSum(x, segmentIds, numSegments)
+       * ```
+       * @param x The `tf.Tensor` that will be summed along its segments.
+       * @param segmentIds A `tf.Tensor1D` whose rank is equal to the rank of `x`'s
+       * dimension along the `axis`.  Maps each element of `x` to a segment.
+       * @param numSegments The number of distinct `segmentIds`.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Segment'} */
+      function unsortedSegmentSum_(x, segmentIds, numSegments) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "unsortedSegmentSum");
+        const $segmentIds = Object(tensor_util_env["a" /* convertToTensor */])(
+          segmentIds,
+          "segmentIds",
+          "unsortedSegmentSum",
+          "int32"
+        );
+        Object(util["assert"])(
+          Object(util["isInt"])(numSegments),
+          () => "numSegments must be of dtype int"
+        );
+        const gradFunc = (dy, saved) => {
+          const [$segmentIds] = saved;
+          const derX = () => {
+            return gatherDropNegatives(dy, $segmentIds);
+          };
+          return { $x: derX };
+        };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.unsortedSegmentSum($x, $segmentIds, numSegments);
+            save([$segmentIds]);
+            return res;
+          },
+          { $x },
+          gradFunc
+        );
+      }
+      /**
+       * Gather slices from tensor `x`'s axis `axis` according to `indices`.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       * const indices = tf.tensor1d([1, 3, 3], 'int32');
+       *
+       * x.gather(indices).print();
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       * const indices = tf.tensor1d([1, 1, 0], 'int32');
+       *
+       * x.gather(indices).print();
+       * ```
+       * @param x The input tensor whose slices to be gathered.
+       * @param indices The indices of the values to extract.
+       * @param axis The axis over which to select values. Defaults to 0.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      function gather_(x, indices, axis = 0) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "gather");
+        const $indices = Object(tensor_util_env["a" /* convertToTensor */])(
+          indices,
+          "indices",
+          "gather",
+          "int32"
+        );
+        axis = Object(util["parseAxisParam"])(axis, $x.shape)[0];
+        const shapeInfo = collectGatherOpShapeInfo($x, $indices, axis);
+        const grad = (dy, saved) => {
+          const [$indices] = saved;
+          const derX = () => {
+            const paramsShape = $x.shape;
+            const indicesSize = $indices.size;
+            const outerShape = paramsShape.slice(0, axis);
+            const outerDims = outerShape.length;
+            const innerShape = paramsShape.slice(axis, paramsShape.length).slice(1);
+            const innerDims = innerShape.length;
+            const outerAxesIndices = arrayRange(0, outerDims);
+            const innerAxesIndices = arrayRange(outerDims + 1, outerDims + 1 + innerDims);
+            const valuesShape = arrayConcat([outerShape, [indicesSize], innerShape]);
+            const values = dy.reshape(valuesShape);
+            const reshapedIndices = $indices.reshape([indicesSize]);
+            const transposeDims = arrayConcat([[outerDims], outerAxesIndices, innerAxesIndices]);
+            const valuesTranspose = values.transpose(transposeDims);
+            let paramsGrad = unsortedSegmentSum(valuesTranspose, reshapedIndices, $x.shape[axis]);
+            const invertTransposeDims = getUndoAxesPermutation(transposeDims);
+            paramsGrad = paramsGrad.transpose(invertTransposeDims);
+            return paramsGrad;
+          };
+          return { x: derX, indices: () => $indices };
+        };
+        return engine["a" /* ENGINE */]
+          .runKernelFunc(
+            (backend, save) => {
+              const res = backend.gather($x, $indices.flatten(), axis);
+              save([$indices]);
+              return res;
+            },
+            { x: $x, indices: $indices },
+            grad,
+            "Gather",
+            { axis }
+          )
+          .reshape(shapeInfo.outputShape);
+      }
+      function arrayRange(start, stop) {
+        const result = [];
+        for (let i = start; i < stop; ++i) {
+          result.push(i);
+        }
+        return result;
+      }
+      function arrayConcat(arrays) {
+        const result = [];
+        for (let i = 0; i < arrays.length; ++i) {
+          for (let j = 0; j < arrays[i].length; ++j) {
+            result.push(arrays[i][j]);
+          }
+        }
+        return result;
+      }
+      function gatherDropNegatives(x, indices) {
+        // Helper function for unsorted segment ops. Gathers params for
+        // positive segment ids and gathers 0 for inputs with negative segment id.
+        // Mirrors _GatherDropNegatives from tensorflow/python/ops/math_grad.py
+        const zeroClippedIndices = maximum(
+          indices,
+          Object(tensor_ops["o" /* zerosLike */])(indices)
+        );
+        const gathered = gather(x, zeroClippedIndices);
+        let isPositive = greaterEqual(indices, Object(tensor_ops["e" /* scalar */])(0, "int32"));
+        const numIters = gathered.rank - isPositive.rank;
+        for (let i = 0; i < numIters; ++i) {
+          isPositive = expandDims(isPositive, i + 1);
+        }
+        isPositive = logicalAnd(
+          isPositive,
+          Object(tensor_ops["b" /* ones */])(gathered.shape, "bool")
+        );
+        const zeroSlice = Object(tensor_ops["o" /* zerosLike */])(gathered);
+        return where(isPositive, gathered, zeroSlice);
+      }
+      const gather = Object(operation["a" /* op */])({ gather_ });
+      const unsortedSegmentSum = Object(operation["a" /* op */])({ unsortedSegmentSum_ });
+      //# sourceMappingURL=segment_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/boolean_mask.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Apply boolean mask to tensor.
+       *
+       * ```js
+       * const tensor = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
+       * const mask = tf.tensor1d([1, 0, 1], 'bool');
+       * const result = await tf.booleanMaskAsync(tensor, mask);
+       * result.print();
+       * ```
+       *
+       * @param tensor N-D tensor.
+       * @param mask K-D boolean tensor, K <= N and K must be known statically.
+       * @param axis A 0-D int Tensor representing the axis in tensor to mask from.
+       *     By default, axis is 0 which will mask from the first dimension.
+       *     Otherwise K + axis <= N.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      async function booleanMaskAsync_(tensor, mask, axis) {
+        const $tensor = Object(tensor_util_env["a" /* convertToTensor */])(
+          tensor,
+          "tensor",
+          "boolMask"
+        );
+        const $mask = Object(tensor_util_env["a" /* convertToTensor */])(
+          mask,
+          "mask",
+          "boolMask",
+          "bool"
+        );
+        const axisFrom = axis == null ? 0 : axis;
+        const maskDim = $mask.rank;
+        const tensorShape = $tensor.shape;
+        util["assert"](maskDim > 0, () => "mask cannot be scalar");
+        util["assertShapesMatch"](
+          tensorShape.slice(axisFrom, axisFrom + maskDim),
+          $mask.shape,
+          `mask's shape must match the first K dimensions of tensor's shape,`
+        );
+        let leadingSize = 1;
+        for (let i = axisFrom; i < axisFrom + maskDim; i++) {
+          leadingSize *= tensorShape[i];
+        }
+        const targetTensorShape = tensorShape
+          .slice(0, axisFrom)
+          .concat([leadingSize], tensorShape.slice(axisFrom + maskDim));
+        const reshapedTensor = $tensor.reshape(targetTensorShape);
+        const reshapedMask = $mask.reshape([-1]);
+        const positivePositions = await whereAsync(reshapedMask);
+        const indices = positivePositions.squeeze([1]);
+        const res = gather(reshapedTensor, indices, axisFrom);
+        // Ensure no memory leak.
+        if (tensor !== $tensor) {
+          $tensor.dispose();
+        }
+        if (mask !== $mask) {
+          $mask.dispose();
+        }
+        indices.dispose();
+        reshapedTensor.dispose();
+        reshapedMask.dispose();
+        positivePositions.dispose();
+        return res;
+      }
+      const booleanMaskAsync = booleanMaskAsync_;
+      //# sourceMappingURL=boolean_mask.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/reverse.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Reverses a `tf.Tensor1D`.
+       *
+       * @param x The input tensor.
+       */
+      function reverse1d_(x) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
+        util["assert"](
+          $x.rank === 1,
+          () => `Error in reverse1D: x must be rank 1 but got rank ${$x.rank}.`
+        );
+        return reverse_reverse($x, 0);
+      }
+      /**
+       * Reverses a `tf.Tensor2D` along a specified axis.
+       *
+       * @param x The input tensor.
+       * @param axis The set of dimensions to reverse. Must be in the
+       *     range [-rank(x), rank(x)). Defaults to all axes.
+       */
+      function reverse2d_(x, axis) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
+        util["assert"](
+          $x.rank === 2,
+          () => `Error in reverse2D: x must be rank 2 but got rank ${$x.rank}.`
+        );
+        return reverse_reverse($x, axis);
+      }
+      /**
+       * Reverses a `tf.Tensor3D` along a specified axis.
+       *
+       * @param x The input tensor.
+       * @param axis The set of dimensions to reverse. Must be in the
+       *     range [-rank(x), rank(x)). Defaults to all axes.
+       */
+      function reverse3d_(x, axis) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
+        util["assert"](
+          $x.rank === 3,
+          () => `Error in reverse3D: x must be rank 3 but got rank ${$x.rank}.`
+        );
+        return reverse_reverse($x, axis);
+      }
+      /**
+       * Reverses a `tf.Tensor4D` along a specified axis.
+       *
+       * @param x The input tensor.
+       * @param axis The set of dimensions to reverse. Must be in the
+       *     range [-rank(x), rank(x)). Defaults to all axes.
+       */
+      function reverse4d_(x, axis) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
+        util["assert"](
+          $x.rank === 4,
+          () => `Error in reverse4D: x must be rank 4 but got rank ${$x.rank}.`
+        );
+        return reverse_reverse($x, axis);
+      }
+      /**
+       * Reverses a `tf.Tensor` along a specified axis.
+       *
+       * Also available are stricter rank-specific methods that assert that `x` is
+       * of the given rank:
+       *   - `tf.reverse1d`
+       *   - `tf.reverse2d`
+       *   - `tf.reverse3d`
+       *   - `tf.reverse4d`
+       *
+       * Except `tf.reverse1d` (which does not have axis param), all methods have
+       * same signature as this method.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       *
+       * x.reverse().print();
+       * ```
+       *
+       * ```js
+       * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       *
+       * const axis = 1;
+       * x.reverse(axis).print();
+       * ```
+       * @param x The input tensor to be reversed.
+       * @param axis The set of dimensions to reverse. Must be in the
+       *     range [-rank(x), rank(x)). Defaults to all axes.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
+      function reverse_(x, axis) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "reverse");
+        if ($x.rank === 0) {
+          return $x.clone();
+        }
+        const axes = util["parseAxisParam"](axis, $x.shape);
+        const grad = (dy) => {
+          return { $x: () => dy.reverse(axes) };
+        };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.reverse($x, axes),
+          { $x },
+          grad
+        );
+        return res.reshapeAs($x);
+      }
+      const reverse_reverse = Object(operation["a" /* op */])({ reverse_ });
+      const reverse1d = Object(operation["a" /* op */])({ reverse1d_ });
+      const reverse2d = Object(operation["a" /* op */])({ reverse2d_ });
+      const reverse3d = Object(operation["a" /* op */])({ reverse3d_ });
+      const reverse4d = Object(operation["a" /* op */])({ reverse4d_ });
+      //# sourceMappingURL=reverse.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/compare.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * @deprecated
+       * Strict version of `tf.notEqual` that forces `a` and `b` to be of the same
+       * shape.
+       *
+       * @param a The first input tensor.
+       * @param b The second input tensor. Must have the same shape and dtype as
+       *     `a`.
+       */
+      function notEqualStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "notEqualStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "notEqualStrict");
+        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in notEqualStrict: ");
+        return $a.notEqual($b);
+      }
+      /**
+       * @deprecated
+       * Strict version of `tf.less` that forces `a` and `b` to be of the same
+       * shape.
+       *
+       * @param a The first input tensor.
+       * @param b The second input tensor. Must have the same shape and dtype as
+       *     `a`.
+       */
+      function lessStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "lessStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "lessStrict");
+        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in lessStrict: ");
+        return $a.less($b);
+      }
+      function equalStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "equalStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "equalStrict");
+        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in equalStrict: ");
+        return $a.equal($b);
+      }
+      function lessEqualStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "lessEqualStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "lessEqualStrict");
+        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in lessEqualStrict: ");
+        return $a.lessEqual($b);
+      }
+      function greaterStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "greaterStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "greaterStrict");
+        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in greaterStrict: ");
+        return $a.greater($b);
+      }
+      function greaterEqualStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "greaterEqualStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "greaterEqualStrict");
+        Object(util["assertShapesMatch"])($a.shape, $b.shape, "Error in greaterEqualStrict: ");
+        return $a.greaterEqual($b);
+      }
+      const equalStrict = Object(operation["a" /* op */])({ equalStrict_ });
+      const greaterEqualStrict = Object(operation["a" /* op */])({ greaterEqualStrict_ });
+      const greaterStrict = Object(operation["a" /* op */])({ greaterStrict_ });
+      const lessEqualStrict = Object(operation["a" /* op */])({ lessEqualStrict_ });
+      const lessStrict = Object(operation["a" /* op */])({ lessStrict_ });
+      const notEqualStrict = Object(operation["a" /* op */])({ notEqualStrict_ });
+      //# sourceMappingURL=compare.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/binary_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * @deprecated
+       * Adds two `tf.Tensor`s element-wise, A + B.
+       *
+       * Inputs must be the same shape. For broadcasting support, use add() instead.
+       *
+       * @param a The first Tensor to add element-wise.
+       * @param b The second Tensor to add element-wise.
+       */
+      function addStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "addStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "addStrict");
+        util["assertShapesMatch"]($a.shape, $b.shape, "Error in addStrict: ");
+        return $a.add($b);
+      }
+      /**
+       * @deprecated
+       * Subtracts two `tf.Tensor`s element-wise, A - B. Inputs must
+       * be the same shape.
+       *
+       * For broadcasting support, use `tf.sub` instead.
+       *
+       * @param a The first Tensor to subtract element-wise.
+       * @param b The second Tensor to subtract element-wise.
+       */
+      function subStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "subStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "subStrict");
+        util["assertShapesMatch"]($a.shape, $b.shape, "Error in subStrict: ");
+        return $a.sub($b);
+      }
+      /**
+       * @deprecated
+       * Computes the power of one `tf.Tensor` to another. Inputs must
+       * be the same shape.
+       *
+       * For broadcasting support, use `tf.pow` instead.
+       *
+       * @param base The base tensor to pow element-wise.
+       * @param exp The exponent tensor to pow element-wise.
+       */
+      function powStrict_(base, exp) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        util["assertShapesMatch"](base.shape, exp.shape, "Error in powStrict: ");
+        return base.pow(exp);
+      }
+      /**
+       * @deprecated
+       * Multiplies two `tf.Tensor`s element-wise, A * B.
+       *
+       * Inputs must be the same shape. For broadcasting support, use `tf.mul`.
+       *
+       * @param a The first tensor to multiply.
+       * @param b The first tensor to multiply. Must have the same
+       *    dtype as `a`.
+       */
+      function mulStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "mul");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "mul");
+        util["assertShapesMatch"]($a.shape, $b.shape, "Error in multiplyStrict: ");
+        return $a.mul($b);
+      }
+      /**
+       * @deprecated
+       * Divides two `tf.Tensor`s element-wise, A / B. Inputs must
+       * be the same shape.
+       *
+       * @param a The first tensor as the numerator for element-wise division.
+       * @param b The second tensor as the denominator for element-wise division.
+       */
+      function divStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "div");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "div");
+        util["assertShapesMatch"]($a.shape, $b.shape, "Error in divideStrict: ");
+        return $a.div($b);
+      }
+      /**
+       * @deprecated
+       * Returns the mod of a and b (`a < b ? a : b`) element-wise. Inputs must
+       * be the same shape. For broadcasting support, use mod().
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same dtype as `a`.
+       */
+      function modStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "modStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "modStrict");
+        util["assertShapesMatch"]($a.shape, $b.shape, "Error in modStrict: ");
+        return $a.mod($b);
+      }
+      /**
+       * @deprecated
+       * Returns the min of a and b (`a < b ? a : b`) element-wise. Inputs must
+       * be the same shape. For broadcasting support, use minimum().
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same dtype as `a`.
+       */
+      function minimumStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "minimumStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "minimumStrict");
+        util["assertShapesMatch"]($a.shape, $b.shape, "Error in minimumStrict: ");
+        return $a.minimum($b);
+      }
+      /**
+       * @deprecated
+       * Returns the max of a and b (`a > b ? a : b`) element-wise. Inputs must
+       * be the same shape. For broadcasting support, use maximum().
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same dtype as `a`.
+       */
+      function maximumStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "maximumStrict");
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "maximumStrict");
+        util["assertShapesMatch"]($a.shape, $b.shape, "Error in maximumStrict: ");
+        return $a.maximum($b);
+      }
+      /**
+       * @deprecated
+       * Returns (a - b) * (a - b) element-wise.
+       *
+       * Inputs must be the same shape. For broadcasting support, use
+       * `tf.squaredDifference` instead.
+       *
+       * @param a The first tensor.
+       * @param b The second tensor. Must have the same type as `a`.
+       */
+      function squaredDifferenceStrict_(a, b) {
+        deprecationWarn(
+          "strict variants of ops have been deprecated " + "and will be removed in future"
+        );
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(
+          a,
+          "a",
+          "squaredDifferenceStrict"
+        );
+        const $b = Object(tensor_util_env["a" /* convertToTensor */])(
+          b,
+          "b",
+          "squaredDifferenceStrict"
+        );
+        util["assertShapesMatch"]($a.shape, $b.shape, "Error in squaredDifferenceStrict: ");
+        return $a.squaredDifference($b);
+      }
+      const addStrict = Object(operation["a" /* op */])({ addStrict_ });
+      const divStrict = Object(operation["a" /* op */])({ divStrict_ });
+      const maximumStrict = Object(operation["a" /* op */])({ maximumStrict_ });
+      const minimumStrict = Object(operation["a" /* op */])({ minimumStrict_ });
+      const modStrict = Object(operation["a" /* op */])({ modStrict_ });
+      const mulStrict = Object(operation["a" /* op */])({ mulStrict_ });
+      const powStrict = Object(operation["a" /* op */])({ powStrict_ });
+      const squaredDifferenceStrict = Object(operation["a" /* op */])({ squaredDifferenceStrict_ });
+      const subStrict = Object(operation["a" /* op */])({ subStrict_ });
+      //# sourceMappingURL=binary_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/softmax.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the softmax normalized vector given the logits.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       *
+       * a.softmax().print();  // or tf.softmax(a)
+       * ```
+       *
+       * ```js
+       * const a = tf.tensor2d([2, 4, 6, 1, 2, 3], [2, 3]);
+       *
+       * a.softmax().print();  // or tf.softmax(a)
+       * ```
+       *
+       * @param logits The logits array.
+       * @param dim The dimension softmax would be performed on. Defaults to `-1`
+       *     which indicates the last dimension.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
+      function softmax_(logits, dim = -1) {
+        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
+          logits,
+          "logits",
+          "softmax",
+          "float32"
+        );
+        if (dim === -1) {
+          dim = $logits.rank - 1;
+        }
+        if (dim !== $logits.rank - 1) {
+          throw Error(
+            "Softmax along a non-last dimension is not yet supported. " +
+              `Logits was rank ${$logits.rank} and dim was ${dim}`
+          );
+        }
+        const inputsToSave = [];
+        const outputsToSave = [true];
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const y = backend.softmax($logits, dim);
+            save([y]);
+            return y;
+          },
+          { logits: $logits },
+          (dy, saved) => {
+            const [y] = saved;
+            const dyTimesY = dy.mul(y);
+            const keepDims = true;
+            return {
+              logits: () => dyTimesY.sub(dyTimesY.sum([dim], keepDims).mul(y)),
+            };
+          },
+          "Softmax",
+          { dim },
+          inputsToSave,
+          outputsToSave
+        );
+      }
+      /**
+       * Computes the log softmax.
+       *
+       * ```js
+       * const a = tf.tensor1d([1, 2, 3]);
+       *
+       * a.logSoftmax().print();  // or tf.logSoftmax(a)
+       * ```
+       *
+       * ```js
+       * const a = tf.tensor2d([2, 4, 6, 1, 2, 3], [2, 3]);
+       *
+       * a.logSoftmax().print();  // or tf.logSoftmax(a)
+       * ```
+       *
+       * @param logits The logits array.
+       * @param axis The dimension softmax would be performed on. Defaults to `-1`
+       *     which indicates the last dimension.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
+      function logSoftmax_(logits, axis = -1) {
+        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
+          logits,
+          "logits",
+          "logSoftmax"
+        );
+        if (axis === -1) {
+          axis = $logits.rank - 1;
+        }
+        if (axis !== $logits.rank - 1) {
+          throw Error(
+            "Log Softmax along a non-last dimension is not yet supported. " +
+              `Logits was rank ${$logits.rank} and axis was ${axis}`
+          );
+        }
+        const customOp = customGrad((logits, save) => {
+          const keepDims = true;
+          const xMax = logits.max(axis, true);
+          const shifted = logits.sub(xMax);
+          const value = shifted.toFloat().sub(shifted.exp().sum(axis, keepDims).log());
+          save([value]);
+          const gradFunc = (dy, saved) => {
+            const [value] = saved;
+            const softmax = value.exp();
+            return dy.sub(dy.sum(axis, keepDims).mul(softmax));
+          };
+          return { value, gradFunc };
+        });
+        return customOp($logits);
+      }
+      const softmax = Object(operation["a" /* op */])({ softmax_ });
+      const logSoftmax = Object(operation["a" /* op */])({ logSoftmax_ });
+      //# sourceMappingURL=softmax.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/norm.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the norm of scalar, vectors, and matrices.
+       * This function can compute several different vector norms (the 1-norm, the
+       * Euclidean or 2-norm, the inf-norm, and in general the p-norm for p > 0)
+       * and matrix norms (Frobenius, 1-norm, and inf-norm).
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 3, 4]);
+       *
+       * x.norm().print();  // or tf.norm(x)
+       * ```
+       *
+       * @param x The input array.
+       * @param ord Optional. Order of the norm. Supported norm types are
+       * following:
+       *
+       *  | ord        | norm for matrices         | norm for vectors
+       *  |------------|---------------------------|---------------------
+       *  |'euclidean' |Frobenius norm             |2-norm
+       *  |'fro'       |Frobenius norm	           |
+       *  |Infinity    |max(sum(abs(x), axis=1))   |max(abs(x))
+       *  |-Infinity   |min(sum(abs(x), axis=1))   |min(abs(x))
+       *  |1           |max(sum(abs(x), axis=0))   |sum(abs(x))
+       *  |2           |                           |sum(abs(x)^2)^1/2*
+       *
+       * @param axis Optional. If axis is null (the default), the input is
+       * considered a vector and a single vector norm is computed over the entire
+       * set of values in the Tensor, i.e. norm(x, ord) is equivalent
+       * to norm(x.reshape([-1]), ord). If axis is a integer, the input
+       * is considered a batch of vectors, and axis determines the axis in x
+       * over which to compute vector norms. If axis is a 2-tuple of integer it is
+       * considered a batch of matrices and axis determines the axes in NDArray
+       * over which to compute a matrix norm.
+       * @param keepDims Optional. If true, the norm have the same dimensionality
+       * as the input.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Matrices'} */
+      function norm_(x, ord = "euclidean", axis = null, keepDims = false) {
+        x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "norm");
+        const norm = normImpl(x, ord, axis);
+        let keepDimsShape = norm.shape;
+        if (keepDims) {
+          const axes = Object(util["parseAxisParam"])(axis, x.shape);
+          keepDimsShape = expandShapeToKeepDim(norm.shape, axes);
+        }
+        return norm.reshape(keepDimsShape);
+      }
+      function normImpl(x, p, axis = null) {
+        if (x.rank === 0) {
+          return x.abs();
+        }
+        // consider vector when no axis is specified
+        if (x.rank !== 1 && axis === null) {
+          return normImpl(x.reshape([-1]), p, axis);
+        }
+        // vector
+        if (
+          x.rank === 1 ||
+          typeof axis === "number" ||
+          (Array.isArray(axis) && axis.length === 1)
+        ) {
+          if (p === 1) {
+            return x.abs().sum(axis);
+          }
+          if (p === Infinity) {
+            return x.abs().max(axis);
+          }
+          if (p === -Infinity) {
+            return x.abs().min(axis);
+          }
+          if (p === "euclidean" || p === 2) {
+            // norm(x, 2) = sum(abs(xi) ^ 2) ^ 1/2
+            return x.abs().pow(Object(tensor_ops["e" /* scalar */])(2, "int32")).sum(axis).sqrt();
+          }
+          throw new Error(`Error in norm: invalid ord value: ${p}`);
+        }
+        // matrix (assumption axis[0] < axis[1])
+        if (Array.isArray(axis) && axis.length === 2) {
+          if (p === 1) {
+            return x
+              .abs()
+              .sum(axis[0])
+              .max(axis[1] - 1);
+          }
+          if (p === Infinity) {
+            return x.abs().sum(axis[1]).max(axis[0]);
+          }
+          if (p === -Infinity) {
+            return x.abs().sum(axis[1]).min(axis[0]);
+          }
+          if (p === "fro" || p === "euclidean") {
+            // norm(x) = sqrt(sum(pow(x, 2)))
+            return x.square().sum(axis).sqrt();
+          }
+          throw new Error(`Error in norm: invalid ord value: ${p}`);
+        }
+        throw new Error(`Error in norm: invalid axis: ${axis}`);
+      }
+      const norm_norm = Object(operation["a" /* op */])({ norm_ });
+      //# sourceMappingURL=norm.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/lstm.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes the next states and outputs of a stack of LSTMCells.
+       *
+       * Each cell output is used as input to the next cell.
+       *
+       * Returns `[cellState, cellOutput]`.
+       *
+       * Derived from tf.contrib.rn.MultiRNNCell.
+       *
+       * @param lstmCells Array of LSTMCell functions.
+       * @param data The input to the cell.
+       * @param c Array of previous cell states.
+       * @param h Array of previous cell outputs.
+       */
+      /** @doc {heading: 'Operations', subheading: 'RNN'} */
+      function multiRNNCell_(lstmCells, data, c, h) {
+        const $data = Object(tensor_util_env["a" /* convertToTensor */])(
+          data,
+          "data",
+          "multiRNNCell"
+        );
+        const $c = Object(tensor_util_env["b" /* convertToTensorArray */])(c, "c", "multiRNNCell");
+        const $h = Object(tensor_util_env["b" /* convertToTensorArray */])(h, "h", "multiRNNCell");
+        let input = $data;
+        const newStates = [];
+        for (let i = 0; i < lstmCells.length; i++) {
+          const output = lstmCells[i](input, $c[i], $h[i]);
+          newStates.push(output[0]);
+          newStates.push(output[1]);
+          input = output[1];
+        }
+        const newC = [];
+        const newH = [];
+        for (let i = 0; i < newStates.length; i += 2) {
+          newC.push(newStates[i]);
+          newH.push(newStates[i + 1]);
+        }
+        return [newC, newH];
+      }
+      /**
+       * Computes the next state and output of a BasicLSTMCell.
+       *
+       * Returns `[newC, newH]`.
+       *
+       * Derived from tf.contrib.rnn.BasicLSTMCell.
+       *
+       * @param forgetBias Forget bias for the cell.
+       * @param lstmKernel The weights for the cell.
+       * @param lstmBias The bias for the cell.
+       * @param data The input to the cell.
+       * @param c Previous cell state.
+       * @param h Previous cell output.
+       */
+      /** @doc {heading: 'Operations', subheading: 'RNN'} */
+      function basicLSTMCell_(forgetBias, lstmKernel, lstmBias, data, c, h) {
+        const $forgetBias = Object(tensor_util_env["a" /* convertToTensor */])(
+          forgetBias,
+          "forgetBias",
+          "basicLSTMCell"
+        );
+        const $lstmKernel = Object(tensor_util_env["a" /* convertToTensor */])(
+          lstmKernel,
+          "lstmKernel",
+          "basicLSTMCell"
+        );
+        const $lstmBias = Object(tensor_util_env["a" /* convertToTensor */])(
+          lstmBias,
+          "lstmBias",
+          "basicLSTMCell"
+        );
+        const $data = Object(tensor_util_env["a" /* convertToTensor */])(
+          data,
+          "data",
+          "basicLSTMCell"
+        );
+        const $c = Object(tensor_util_env["a" /* convertToTensor */])(c, "c", "basicLSTMCell");
+        const $h = Object(tensor_util_env["a" /* convertToTensor */])(h, "h", "basicLSTMCell");
+        const combined = $data.concat($h, 1);
+        const weighted = combined.matMul($lstmKernel);
+        const res = weighted.add($lstmBias);
+        // i = input_gate, j = new_input, f = forget_gate, o = output_gate
+        const batchSize = res.shape[0];
+        const sliceCols = res.shape[1] / 4;
+        const sliceSize = [batchSize, sliceCols];
+        const i = res.slice([0, 0], sliceSize);
+        const j = res.slice([0, sliceCols], sliceSize);
+        const f = res.slice([0, sliceCols * 2], sliceSize);
+        const o = res.slice([0, sliceCols * 3], sliceSize);
+        const newC = i
+          .sigmoid()
+          .mul(j.tanh())
+          .add($c.mul($forgetBias.add(f).sigmoid()));
+        const newH = newC.tanh().mul(o.sigmoid());
+        return [newC, newH];
+      }
+      const basicLSTMCell = Object(operation["a" /* op */])({ basicLSTMCell_ });
+      const multiRNNCell = Object(operation["a" /* op */])({ multiRNNCell_ });
+      //# sourceMappingURL=lstm.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/moving_average.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Compute the moving average of a variable.
+       *
+       * Without zeroDebias, the moving average operation is defined by:
+       *   `v += delta`
+       * where
+       *   `delta = (1 - decay) * (x - v)`
+       *
+       * With zeroDebias (default), the `delta` term is scaled to debias the
+       * effect of the (assumed) zero-initialization of `v`.
+       *   `delta /= (1 - decay ^ step)`
+       *
+       * For more details on the zero-debiasing algorithm, see:
+       *   https://arxiv.org/abs/1412.6980
+       *
+       * Note that this function is completely stateless and does not keep track of
+       * step count. The step count needs to be maintained by the caller and passed
+       * in as `step`.
+       *
+       * @param v The current moving average value.
+       * @param x New input value, must have the same shape and dtype as `v`.
+       * @param decay The decay factor. Typical values are 0.95 and 0.99.
+       * @param step Step count.
+       * @param zeroDebias: Whether zeroDebias is to be performed (default: `true`).
+       * @returns The new moving average value.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Moving Average'} */
+      function movingAverage_(v, x, decay, step, zeroDebias = true) {
+        const $v = Object(tensor_util_env["a" /* convertToTensor */])(v, "v", "movingAverage");
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "movingAverage");
+        const $decay = Object(tensor_util_env["a" /* convertToTensor */])(
+          decay,
+          "decay",
+          "movingAverage"
+        );
+        Object(tensor_util["assertTypesMatch"])($v, $x);
+        util["assert"](util["arraysEqual"]($v.shape, $x.shape), () => "Shape mismatch in v and x");
+        const one = Object(tensor_ops["e" /* scalar */])(1);
+        const oneMinusDecay = one.sub($decay);
+        let update = $x.sub($v).mul(oneMinusDecay);
+        if (zeroDebias) {
+          util["assert"](step != null, () => "When using zeroDebias: true, step is required.");
+          const $step = Object(tensor_util_env["a" /* convertToTensor */])(
+            step,
+            "step",
+            "movingAverage"
+          );
+          update = update.div(one.sub(pow($decay, $step)));
+        }
+        return $v.add(update);
+      }
+      const movingAverage = Object(operation["a" /* op */])({ movingAverage_ });
+      //# sourceMappingURL=moving_average.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/strided_slice.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Extracts a strided slice of a tensor.
+       *
+       * Roughly speaking, this op extracts a slice of size (end-begin)/stride from
+       * the given input tensor (x). Starting at the location specified by begin the
+       * slice continues by adding stride to the index until all dimensions are not
+       * less than end. Note that a stride can be negative, which causes a reverse
+       * slice.
+       *
+       * ```js
+       * const t = tf.tensor3d([1, 1, 1 ,2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6],
+       *    [3, 2, 3]);
+       * t.stridedSlice([1, 0, 0], [2, 1, 3], [1, 1, 1]).print()  // [[[3, 3, 3]]]
+       * t.stridedSlice([1, 0, 0], [2, 2, 3], [1, 1, 1]).print()  // [[[3, 3, 3],
+       *                                                     // [4, 4, 4]]]
+       * t.stridedSlice([1, -1, 0], [2, -3, 3], [1, -1, 1]).print() // [[[4, 4, 4],
+       *                                                     // [3, 3, 3]]]
+       * ```
+       *
+       * @param x The tensor to stride slice.
+       * @param begin The coordinates to start the slice from.
+       * @param end: The coordinates to end the slice at.
+       * @param strides: The size of the slice.
+       * @param beginMask: If the ith bit of beginMask is set, begin[i] is ignored
+       *      and the fullest possible range in that dimension is used instead.
+       * @param endMask: If the ith bit of endMask is set, end[i] is ignored
+       *      and the fullest possible range in that dimension is used instead.
+       * @param shrinkAxisMask: a bitmask where bit i implies that
+       * the ith specification should shrink the dimensionality. begin and end must
+       * imply a slice of size 1 in the dimension.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Slicing and Joining'} */
+      function stridedSlice_(
+        x,
+        begin,
+        end,
+        strides,
+        beginMask = 0,
+        endMask = 0,
+        ellipsisMask = 0,
+        newAxisMask = 0,
+        shrinkAxisMask = 0
+      ) {
+        if (strides == null) {
+          strides = new Array(begin.length);
+        }
+        const ellipsisAxes = maskToAxes(ellipsisMask);
+        if (ellipsisAxes.length > 1) {
+          throw new Error("Multiple ellipses in slice is not allowed.");
+        }
+        if (ellipsisMask !== 0 && newAxisMask !== 0) {
+          throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");
+        }
+        if (ellipsisMask !== 0 && shrinkAxisMask !== 0) {
+          throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");
+        }
+        let $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "stridedSlice");
+        const numInterpolatedAxes = $x.rank - begin.length;
+        // Expand the dims of x based on the newAxisMask.
+        const expandAxes = maskToAxes(newAxisMask);
+        const newShape = $x.shape.slice();
+        expandAxes.forEach((axis) => {
+          begin[axis] = 0;
+          end[axis] = 1;
+          newShape.splice(axis, 0, 1);
+        });
+        $x = $x.reshape(newShape);
+        // Normalize the start, end and strides.
+        for (let axis = 0; axis < $x.rank; axis++) {
+          begin[axis] = startForAxis(beginMask, begin, strides, $x.shape, axis, ellipsisMask);
+          end[axis] = stopForAxis(endMask, end, strides, $x.shape, axis, ellipsisMask);
+          strides[axis] = stridesForAxis(strides, axis, ellipsisMask);
+        }
+        if (ellipsisAxes.length && numInterpolatedAxes > 0) {
+          const fullIndex = ellipsisAxes[0];
+          // The ellipsis applies to the masked index as well as any dimensions that
+          // were interpolated as full selection.
+          const numElidedAxes = numInterpolatedAxes + 1;
+          begin = startIndicesWithElidedDims(begin, fullIndex, numElidedAxes);
+          end = stopIndicesWithElidedDims(end, fullIndex, numElidedAxes, $x.shape);
+          strides = stridesWithElidedDims(strides, fullIndex, numElidedAxes);
+        }
+        const shrinkAxes = maskToAxes(shrinkAxisMask);
+        // Adjust the ends based on the shrink mask.
+        shrinkAxes.forEach((axis) => {
+          end[axis] = begin[axis] + 1;
+          strides[axis] = 1;
+        });
+        // Figure out the output shape.
+        const size = slice_util_computeOutShape(begin, end, strides);
+        // Remove the axes based on shrinkMask.
+        const outShape = size.filter((_, axis) => shrinkAxes.indexOf(axis) === -1);
+        const nonStrided = strides.every((v) => v === 1);
+        if (nonStrided) {
+          return slice($x, begin, size).reshape(outShape);
+        }
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.stridedSlice($x, begin, end, strides),
+          { $x }
+        );
+        return res.reshape(outShape);
+      }
+      const stridedSlice = Object(operation["a" /* op */])({ stridedSlice_ });
+      //# sourceMappingURL=strided_slice.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/topk.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Finds the values and indices of the `k` largest entries along the last
+       * dimension.
+       *
+       * If the input is a vector (rank=1), finds the k largest entries in the vector
+       * and outputs their values and indices as vectors. Thus values[j] is the j-th
+       * largest entry in input, and its index is indices[j].
+       * For higher rank inputs, computes the top k entries along the last dimension.
+       *
+       * If two elements are equal, the lower-index element appears first.
+       *
+       * ```js
+       * const a = tf.tensor2d([[1, 5], [4, 3]]);
+       * const {values, indices} = tf.topk(a);
+       * values.print();
+       * indices.print();
+       * ```
+       * @param x 1-D or higher `tf.Tensor` with last dimension being at least `k`.
+       * @param k Number of top elements to look for along the last dimension.
+       * @param sorted If true, the resulting `k` elements will be sorted by the
+       *     values in descending order.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Evaluation'} */
+      function topk_(x, k = 1, sorted = true) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "topk");
+        if ($x.rank === 0) {
+          throw new Error("topk() expects the input to be of rank 1 or higher");
+        }
+        const lastDim = $x.shape[$x.shape.length - 1];
+        if (k > lastDim) {
+          throw new Error(
+            `'k' passed to topk() must be <= the last dimension (${lastDim}) ` + `but got ${k}`
+          );
+        }
+        const [values, indices] = engine["a" /* ENGINE */].runKernelFunc(
+          (b) => b.topk($x, k, sorted),
+          { $x }
+        );
+        return { values, indices };
+      }
+      const topk = Object(operation["a" /* op */])({ topk_ });
+      //# sourceMappingURL=topk.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a new tensor by applying sparse updates to individual
+       * values or slices within a zero tensor of the given shape tensor according to
+       * indices. This operator is the inverse of the `tf.gatherND` operator which
+       * extracts values or slices from a given tensor.
+       *
+       * ```js
+       * const indices = tf.tensor2d([4, 3, 1, 7], [4, 1], 'int32');
+       * const updates = tf.tensor1d([9, 10, 11, 12]);
+       * const shape = [8];
+       * tf.scatterND(indices, updates, shape).print() //[0, 11, 0, 10, 9, 0, 0, 12]
+       * ```
+       *
+       * @param indices The tensor contains the indices into the output tensor.
+       * @param updates The tensor contains the value for the indices.
+       * @param shape: The shape of the output tensor.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Slicing and Joining'} */
+      function scatterND_(indices, updates, shape) {
+        const $indices = Object(tensor_util_env["a" /* convertToTensor */])(
+          indices,
+          "indices",
+          "scatterND",
+          "int32"
+        );
+        const $updates = Object(tensor_util_env["a" /* convertToTensor */])(
+          updates,
+          "updates",
+          "scatterND"
+        );
+        validateInput($updates, $indices, shape);
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) => backend.scatterND($indices, $updates, shape),
+          { indices: $indices, updates: $updates },
+          null /* backward */,
+          "ScatterNd",
+          { shape }
+        );
+      }
+      const scatterND = Object(operation["a" /* op */])({ scatterND_ });
+      //# sourceMappingURL=scatter_nd.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/spectral_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Fast Fourier transform.
+       *
+       * Computes the 1-dimensional discrete Fourier transform over the inner-most
+       * dimension of input.
+       *
+       * ```js
+       * const real = tf.tensor1d([1, 2, 3]);
+       * const imag = tf.tensor1d([1, 2, 3]);
+       * const x = tf.complex(real, imag);
+       *
+       * x.fft().print();  // tf.spectral.fft(x).print();
+       * ```
+       * @param input The complex input to compute an fft over.
+       */
+      /**
+       * @doc {heading: 'Operations', subheading: 'Spectral', namespace: 'spectral'}
+       */
+      function fft_(input) {
+        Object(util["assert"])(
+          input.dtype === "complex64",
+          () => `The dtype for tf.spectral.fft() must be complex64 ` + `but got ${input.dtype}.`
+        );
+        // Collapse all outer dimensions to a single batch dimension.
+        const innerDimensionSize = input.shape[input.shape.length - 1];
+        const batch = input.size / innerDimensionSize;
+        const input2D = input.as2D(batch, innerDimensionSize);
+        const ret = engine["a" /* ENGINE */].runKernelFunc((backend) => backend.fft(input2D), {
+          input,
+        });
+        return ret.reshape(input.shape);
+      }
+      /**
+       * Inverse fast Fourier transform.
+       *
+       * Computes the inverse 1-dimensional discrete Fourier transform over the
+       * inner-most dimension of input.
+       *
+       * ```js
+       * const real = tf.tensor1d([1, 2, 3]);
+       * const imag = tf.tensor1d([1, 2, 3]);
+       * const x = tf.complex(real, imag);
+       *
+       * x.ifft().print();  // tf.spectral.ifft(x).print();
+       * ```
+       * @param input The complex input to compute an ifft over.
+       */
+      /**
+       * @doc {heading: 'Operations', subheading: 'Spectral', namespace: 'spectral'}
+       */
+      function ifft_(input) {
+        Object(util["assert"])(
+          input.dtype === "complex64",
+          () => `The dtype for tf.spectral.ifft() must be complex64 ` + `but got ${input.dtype}.`
+        );
+        // Collapse all outer dimensions to a single batch dimension.
+        const innerDimensionSize = input.shape[input.shape.length - 1];
+        const batch = input.size / innerDimensionSize;
+        const input2D = input.as2D(batch, innerDimensionSize);
+        const ret = engine["a" /* ENGINE */].runKernelFunc((backend) => backend.ifft(input2D), {
+          input,
+        });
+        return ret.reshape(input.shape);
+      }
+      /**
+       * Real value input fast Fourier transform.
+       *
+       * Computes the 1-dimensional discrete Fourier transform over the
+       * inner-most dimension of the real input.
+       *
+       * ```js
+       * const real = tf.tensor1d([1, 2, 3]);
+       *
+       * real.rfft().print();
+       * ```
+       * @param input The real value input to compute an rfft over.
+       */
+      /**
+       * @doc {heading: 'Operations', subheading: 'Spectral', namespace: 'spectral'}
+       */
+      function rfft_(input, fftLength) {
+        Object(util["assert"])(
+          input.dtype === "float32",
+          () => `The dtype for rfft() must be real value but got ${input.dtype}`
+        );
+        let innerDimensionSize = input.shape[input.shape.length - 1];
+        const batch = input.size / innerDimensionSize;
+        let adjustedInput;
+        if (fftLength != null && fftLength < innerDimensionSize) {
+          // Need to crop
+          const begin = input.shape.map((v) => 0);
+          const size = input.shape.map((v) => v);
+          size[input.shape.length - 1] = fftLength;
+          adjustedInput = input.slice(begin, size);
+          innerDimensionSize = fftLength;
+        } else if (fftLength != null && fftLength > innerDimensionSize) {
+          // Need to pad with zeros
+          const zerosShape = input.shape.map((v) => v);
+          zerosShape[input.shape.length - 1] = fftLength - innerDimensionSize;
+          adjustedInput = input.concat(
+            Object(tensor_ops["n" /* zeros */])(zerosShape),
+            input.shape.length - 1
+          );
+          innerDimensionSize = fftLength;
+        } else {
+          adjustedInput = input;
+        }
+        // Complement the input with zero imaginary numbers.
+        const zerosInput = adjustedInput.zerosLike();
+        const complexInput = Object(complex["a" /* complex */])(adjustedInput, zerosInput).as2D(
+          batch,
+          innerDimensionSize
+        );
+        const ret = fft(complexInput);
+        // Exclude complex conjugations. These conjugations are put symmetrically.
+        const half = Math.floor(innerDimensionSize / 2) + 1;
+        const realValues = Object(real["a" /* real */])(ret);
+        const imagValues = Object(imag["a" /* imag */])(ret);
+        const realComplexConjugate = realValues.split(
+          [half, innerDimensionSize - half],
+          realValues.shape.length - 1
+        );
+        const imagComplexConjugate = imagValues.split(
+          [half, innerDimensionSize - half],
+          imagValues.shape.length - 1
+        );
+        const outputShape = adjustedInput.shape.slice();
+        outputShape[adjustedInput.shape.length - 1] = half;
+        return Object(complex["a" /* complex */])(
+          realComplexConjugate[0],
+          imagComplexConjugate[0]
+        ).reshape(outputShape);
+      }
+      /**
+       * Inversed real value input fast Fourier transform.
+       *
+       * Computes the 1-dimensional inversed discrete Fourier transform over the
+       * inner-most dimension of the real input.
+       *
+       * ```js
+       * const real = tf.tensor1d([1, 2, 3]);
+       * const imag = tf.tensor1d([0, 0, 0]);
+       * const x = tf.complex(real, imag);
+       *
+       * x.irfft().print();
+       * ```
+       * @param input The real value input to compute an irfft over.
+       */
+      /**
+       * @doc {heading: 'Operations', subheading: 'Spectral', namespace: 'spectral'}
+       */
+      function irfft_(input) {
+        const innerDimensionSize = input.shape[input.shape.length - 1];
+        const batch = input.size / innerDimensionSize;
+        if (innerDimensionSize <= 2) {
+          const complexInput = input.as2D(batch, innerDimensionSize);
+          const ret = ifft(complexInput);
+          return Object(real["a" /* real */])(ret);
+        } else {
+          // The length of unique components of the DFT of a real-valued signal
+          // is 2 * (input_len - 1)
+          const outputShape = [batch, 2 * (innerDimensionSize - 1)];
+          const realInput = Object(real["a" /* real */])(input).as2D(batch, innerDimensionSize);
+          const imagInput = Object(imag["a" /* imag */])(input).as2D(batch, innerDimensionSize);
+          const realConjugate = realInput.slice([0, 1], [batch, innerDimensionSize - 2]).reverse(1);
+          const imagConjugate = imagInput
+            .slice([0, 1], [batch, innerDimensionSize - 2])
+            .reverse(1)
+            .mul(Object(tensor_ops["e" /* scalar */])(-1));
+          const r = realInput.concat(realConjugate, 1);
+          const i = imagInput.concat(imagConjugate, 1);
+          const complexInput = Object(complex["a" /* complex */])(r, i).as2D(
+            outputShape[0],
+            outputShape[1]
+          );
+          const ret = ifft(complexInput);
+          return Object(real["a" /* real */])(ret);
+        }
+      }
+      const fft = Object(operation["a" /* op */])({ fft_ });
+      const ifft = Object(operation["a" /* op */])({ ifft_ });
+      const rfft = Object(operation["a" /* op */])({ rfft_ });
+      const irfft = Object(operation["a" /* op */])({ irfft_ });
+      //# sourceMappingURL=spectral_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/sparse_to_dense_util.js
+      /**
+       * Validate sparseToDense inputs.
+       *
+       * @param sparseIndices A 0-D, 1-D, or 2-D Tensor of type int32.
+       * sparseIndices[i] contains the complete index where sparseValues[i] will be
+       * placed.
+       * @param sparseValues A 0-D or 1-D Tensor. Values
+       * corresponding to each row of sparseIndices, or a scalar value to be used for
+       * all sparse indices.
+       * @param outputShape number[]. Shape of the dense output tensor.
+       * @param validateIndices boolean. indice validation is not supported, error
+       * will be thrown if it is set.
+       */
+      function sparse_to_dense_util_validateInput(
+        sparseIndices,
+        sparseValues,
+        outputShape,
+        defaultValues
+      ) {
+        if (sparseIndices.dtype !== "int32") {
+          throw new Error(
+            "tf.sparseToDense() expects the indices to be int32 type," +
+              ` but the dtype was ${sparseIndices.dtype}.`
+          );
+        }
+        if (sparseIndices.rank > 2) {
+          throw new Error(
+            "sparseIndices should be a scalar, vector, or matrix," +
+              ` but got shape ${sparseIndices.shape}.`
+          );
+        }
+        const numElems = sparseIndices.rank > 0 ? sparseIndices.shape[0] : 1;
+        const numDims = sparseIndices.rank > 1 ? sparseIndices.shape[1] : 1;
+        if (outputShape.length !== numDims) {
+          throw new Error(
+            "outputShape has incorrect number of elements:," +
+              ` ${outputShape.length}, should be: ${numDims}.`
+          );
+        }
+        const numValues = sparseValues.size;
+        if (!(sparseValues.rank === 0 || (sparseValues.rank === 1 && numValues === numElems))) {
+          throw new Error(
+            "sparseValues has incorrect shape " +
+              `${sparseValues.shape}, should be [] or [${numElems}]`
+          );
+        }
+        if (sparseValues.dtype !== defaultValues.dtype) {
+          throw new Error("sparseValues.dtype must match defaultValues.dtype");
+        }
+      }
+      //# sourceMappingURL=sparse_to_dense_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/sparse_to_dense.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Converts a sparse representation into a dense tensor.
+       *
+       * Builds an array dense with shape outputShape such that:
+       *
+       * // If sparseIndices is scalar
+       * dense[i] = (i == sparseIndices ? sparseValues : defaultValue)
+       *
+       * // If sparseIndices is a vector, then for each i
+       * dense[sparseIndices[i]] = sparseValues[i]
+       *
+       * // If sparseIndices is an n by d matrix, then for each i in [0, n)
+       * dense[sparseIndices[i][0], ..., sparseIndices[i][d-1]] = sparseValues[i]
+       * All other values in dense are set to defaultValue. If sparseValues is a
+       * scalar, all sparse indices are set to this single value.
+       *
+       * If indices are repeated the final value is summed over all values for those
+       * indices.
+       *
+       * ```js
+       * const indices = tf.tensor1d([4, 5, 6, 1, 2, 3], 'int32');
+       * const values = tf.tensor1d([10, 11, 12, 13, 14, 15], 'float32');
+       * const shape = [8];
+       * tf.sparseToDense(indices, values, shape).print();
+       * ```
+       *
+       * @param sparseIndices A 0-D, 1-D, or 2-D Tensor of type int32.
+       * sparseIndices[i] contains the complete index where sparseValues[i] will be
+       * placed.
+       * @param sparseValues A 0-D or 1-D Tensor. Values
+       * corresponding to each row of sparseIndices, or a scalar value to be used for
+       * all sparse indices.
+       * @param outputShape Shape of the dense output tensor. the type is inferred.
+       * @param defaultValue Scalar. Value to set for indices not specified in
+       * sparseIndices. Defaults to zero.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Normalization'} */
+      function sparseToDense_(sparseIndices, sparseValues, outputShape, defaultValue = 0) {
+        const $sparseIndices = Object(tensor_util_env["a" /* convertToTensor */])(
+          sparseIndices,
+          "sparseIndices",
+          "sparseToDense",
+          "int32"
+        );
+        const $sparseValues = Object(tensor_util_env["a" /* convertToTensor */])(
+          sparseValues,
+          "sparseValues",
+          "sparseToDense"
+        );
+        const $defaultValue = Object(tensor_util_env["a" /* convertToTensor */])(
+          defaultValue,
+          "defaultValue",
+          "sparseToDense",
+          $sparseValues.dtype
+        );
+        sparse_to_dense_util_validateInput(
+          $sparseIndices,
+          $sparseValues,
+          outputShape,
+          $defaultValue
+        );
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (backend) =>
+            backend.sparseToDense($sparseIndices, $sparseValues, outputShape, $defaultValue),
+          { $sparseIndices, $sparseValues, $defaultValue }
+        );
+      }
+      const sparseToDense = Object(operation["a" /* op */])({ sparseToDense_ });
+      //# sourceMappingURL=sparse_to_dense.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Gather slices from input tensor into a Tensor with shape specified by
+       * `indices`.
+       *
+       * `indices` is an K-dimensional integer tensor, best thought of as a
+       * (K-1)-dimensional tensor of indices into input, where each element defines a
+       * slice of input:
+       * output[\\(i_0, ..., i_{K-2}\\)] = input[indices[\\(i_0, ..., i_{K-2}\\)]]
+       *
+       * Whereas in `tf.gather`, `indices` defines slices into the first dimension of
+       * input, in `tf.gatherND`, `indices` defines slices into the first N dimensions
+       * of input, where N = indices.shape[-1].
+       *
+       * The last dimension of indices can be at most the rank of input:
+       * indices.shape[-1] <= input.rank
+       *
+       * The last dimension of `indices` corresponds to elements
+       * (if indices.shape[-1] == input.rank) or slices
+       * (if indices.shape[-1] < input.rank) along dimension indices.shape[-1] of
+       * input.
+       * The output tensor has shape
+       * indices.shape[:-1] + input.shape[indices.shape[-1]:]
+       *
+       * Note that on CPU, if an out of bound index is found, an error is returned. On
+       * GPU, if an out of bound index is found, a 0 is stored in the corresponding
+       * output value.
+       *
+       * ```js
+       * const indices = tf.tensor2d([0, 1, 1, 0], [2,2], 'int32');
+       * const input = tf.tensor2d([9, 10, 11, 12], [2, 2]);
+       * tf.gatherND(input, indices).print() // [10, 11]
+       * ```
+       *
+       * @param x The tensor from which to gather values.
+       * @param indices Index tensor, must be of type int32.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Slicing and Joining'} */
+      function gatherND_(x, indices) {
+        const $indices = Object(tensor_util_env["a" /* convertToTensor */])(
+          indices,
+          "indices",
+          "gatherND",
+          "int32"
+        );
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "gatherND");
+        const forward = (backend) => {
+          return backend.gatherND($x, $indices);
+        };
+        const inputs = { params: $x, indices: $indices };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          kernel_names["G" /* GatherNd */]
+        );
+      }
+      const gatherND = Object(operation["a" /* op */])({ gatherND_ });
+      //# sourceMappingURL=gather_nd.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/dropout_util.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Normalize noise shape based on provided tensor and noise shape.
+       *
+       * @param x Tensor.
+       * @param noiseShape The shape for the randomly generated keep/drop flags, as
+       *   an array of numbers. Optional.
+       * @returns Normalized noise shape.
+       */
+      function getNoiseShape(x, noiseShape) {
+        if (noiseShape == null) {
+          return x.shape.slice();
+        }
+        if (util["arraysEqual"](x.shape, noiseShape)) {
+          return noiseShape;
+        }
+        if (x.shape.length === noiseShape.length) {
+          const newDimension = [];
+          for (let i = 0; i < x.shape.length; i++) {
+            if (noiseShape[i] == null && x.shape[i] != null) {
+              newDimension.push(x.shape[i]);
+            } else {
+              newDimension.push(noiseShape[i]);
+            }
+          }
+          return newDimension;
+        }
+        return noiseShape;
+      }
+      //# sourceMappingURL=dropout_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/dropout.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes dropout.
+       *
+       * ```js
+       * const x = tf.tensor1d([1, 2, 2, 1]);
+       * const rate = 0.75;
+       * const output = tf.dropout(x, rate);
+       * output.print();
+       * ```
+       *
+       * @param x A floating point Tensor or TensorLike.
+       * @param rate A float in the range [0, 1). The probability that each element
+       *   of x is discarded.
+       * @param noiseShape An array of numbers of type int32, representing the
+       * shape for randomly generated keep/drop flags. If the noiseShape has null
+       * value, it will be automatically replaced with the x's relative dimension
+       * size. Optional.
+       * @param seed Used to create random seeds. Optional.
+       * @returns A Tensor of the same shape of x.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Dropout'} */
+      function dropout_(x, rate, noiseShape, seed) {
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "dropout");
+        util["assert"](
+          $x.dtype === "float32",
+          () =>
+            `x has to be a floating point tensor since it's going to be ` +
+            `scaled, but got a ${$x.dtype} tensor instead.`
+        );
+        util["assert"](
+          rate >= 0 && rate < 1,
+          () => `rate must be a float in the range [0, 1), but got ${rate}.`
+        );
+        if (rate === 0) {
+          return x instanceof dist_tensor["a" /* Tensor */] ? $x.clone() : $x;
+        }
+        const $noiseShape = getNoiseShape($x, noiseShape);
+        const keepProb = 1 - rate;
+        const multiplier = randomUniform($noiseShape, 0, 1, "float32", seed)
+          .add(keepProb)
+          .floor()
+          .div(keepProb);
+        return $x.mul(multiplier);
+      }
+      const dropout = Object(operation["a" /* op */])({ dropout_ });
+      //# sourceMappingURL=dropout.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/signal_ops.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Generate a Hann window.
+       *
+       * See: https://en.wikipedia.org/wiki/Window_function#Hann_and_Hamming_windows
+       *
+       * ```js
+       * tf.signal.hannWindow(10).print();
+       * ```
+       * @param The length of window
+       */
+      /**
+       * @doc {heading: 'Operations', subheading: 'Signal', namespace: 'signal'}
+       */
+      function hannWindow_(windowLength) {
+        return cosineWindow(windowLength, 0.5, 0.5);
+      }
+      /**
+       * Generate a hamming window.
+       *
+       * See: https://en.wikipedia.org/wiki/Window_function#Hann_and_Hamming_windows
+       *
+       * ```js
+       * tf.signal.hammingWindow(10).print();
+       * ```
+       * @param The length of window
+       */
+      /**
+       * @doc {heading: 'Operations', subheading: 'Signal', namespace: 'signal'}
+       */
+      function hammingWindow_(windowLength) {
+        return cosineWindow(windowLength, 0.54, 0.46);
+      }
+      /**
+       * Expands input into frames of frameLength.
+       * Slides a window size with frameStep.
+       *
+       * ```js
+       * tf.signal.frame([1, 2, 3], 2, 1).print();
+       * ```
+       * @param signal The input tensor to be expanded
+       * @param frameLength Length of each frame
+       * @param frameStep The frame hop size in samples.
+       * @param padEnd Whether to pad the end of signal with padValue.
+       * @param padValue An number to use where the input signal does
+       *     not exist when padEnd is True.
+       */
+      /**
+       * @doc {heading: 'Operations', subheading: 'Signal', namespace: 'signal'}
+       */
+      function frame_(signal, frameLength, frameStep, padEnd = false, padValue = 0) {
+        let start = 0;
+        const output = [];
+        while (start + frameLength <= signal.size) {
+          output.push(slice(signal, start, frameLength));
+          start += frameStep;
+        }
+        if (padEnd) {
+          while (start < signal.size) {
+            const padLen = start + frameLength - signal.size;
+            const pad = concat([
+              slice(signal, start, frameLength - padLen),
+              fill([padLen], padValue),
+            ]);
+            output.push(pad);
+            start += frameStep;
+          }
+        }
+        if (output.length === 0) {
+          return Object(tensor_ops["h" /* tensor2d */])([], [0, frameLength]);
+        }
+        return concat(output).as2D(output.length, frameLength);
+      }
+      /**
+       * Computes the Short-time Fourier Transform of signals
+       * See: https://en.wikipedia.org/wiki/Short-time_Fourier_transform
+       *
+       * ```js
+       * const input = tf.tensor1d([1, 1, 1, 1, 1])
+       * tf.signal.stft(input, 3, 1).print();
+       * ```
+       * @param signal 1-dimensional real value tensor.
+       * @param frameLength The window length of samples.
+       * @param frameStep The number of samples to step.
+       * @param fftLength The size of the FFT to apply.
+       * @param windowFn A callable that takes a window length and returns 1-d tensor.
+       */
+      /**
+       * @doc {heading: 'Operations', subheading: 'Signal', namespace: 'signal'}
+       */
+      function stft_(signal, frameLength, frameStep, fftLength, windowFn = hannWindow) {
+        if (fftLength == null) {
+          fftLength = enclosingPowerOfTwo(frameLength);
+        }
+        const framedSignal = signal_ops_frame(signal, frameLength, frameStep);
+        const windowedSignal = mul(framedSignal, windowFn(frameLength));
+        const output = [];
+        for (let i = 0; i < framedSignal.shape[0]; i++) {
+          output.push(rfft(windowedSignal.slice([i, 0], [1, frameLength]), fftLength));
+        }
+        return concat(output);
+      }
+      function enclosingPowerOfTwo(value) {
+        // Return 2**N for integer N such that 2**N >= value.
+        return Math.floor(Math.pow(2, Math.ceil(Math.log(value) / Math.log(2.0))));
+      }
+      function cosineWindow(windowLength, a, b) {
+        const even = 1 - (windowLength % 2);
+        const newValues = new Float32Array(windowLength);
+        for (let i = 0; i < windowLength; ++i) {
+          const cosArg = (2.0 * Math.PI * i) / (windowLength + even - 1);
+          newValues[i] = a - b * Math.cos(cosArg);
+        }
+        return Object(tensor_ops["g" /* tensor1d */])(newValues, "float32");
+      }
+      const hannWindow = Object(operation["a" /* op */])({ hannWindow_ });
+      const hammingWindow = Object(operation["a" /* op */])({ hammingWindow_ });
+      const signal_ops_frame = Object(operation["a" /* op */])({ frame_ });
+      const stft = Object(operation["a" /* op */])({ stft_ });
+      //# sourceMappingURL=signal_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/in_top_k.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns whether the targets are in the top K predictions.
+       *
+       * ```js
+       * const predictions = tf.tensor2d([[20, 10, 40, 30], [30, 50, -20, 10]]);
+       * const targets = tf.tensor1d([2, 0]);
+       * const precision = await tf.inTopKAsync(predictions, targets);
+       * precision.print();
+       * ```
+       * @param predictions 2-D or higher `tf.Tensor` with last dimension being
+       *     at least `k`.
+       * @param targets 1-D or higher `tf.Tensor`.
+       * @param k Optional Number of top elements to look at for computing precision,
+       *     default to 1.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Evaluation'} */
+      async function inTopKAsync_(predictions, targets, k = 1) {
+        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
+          predictions,
+          "predictions",
+          "inTopK"
+        );
+        const $targets = Object(tensor_util_env["a" /* convertToTensor */])(
+          targets,
+          "targets",
+          "inTopK"
+        );
+        Object(util["assert"])(
+          $predictions.rank > 1,
+          () =>
+            "inTopK() expects the predictions to be of rank 2 or higher, " +
+            `but got ${$predictions.rank}`
+        );
+        Object(util["assert"])(
+          $predictions.rank - 1 === $targets.rank,
+          () =>
+            `predictions rank should be 1 larger than ` +
+            `targets rank, but got predictions rank ` +
+            `${$predictions.rank} and targets rank ${$targets.rank}`
+        );
+        Object(util["assertShapesMatch"])(
+          $predictions.shape.slice(0, $predictions.shape.length - 1),
+          $targets.shape,
+          `predictions's shape should be align with the targets' shape, ` +
+            "except the last dimension."
+        );
+        const lastDim = $predictions.shape[$predictions.shape.length - 1];
+        Object(util["assert"])(
+          k > 0 && k <= lastDim,
+          () =>
+            `'k' passed to inTopK() must be > 0 && <= the predictions last ` +
+            `dimension (${lastDim}), but got ${k}`
+        );
+        const predictionsVals = await $predictions.data();
+        const targetsVals = await $targets.data();
+        // Reshape predictionsVals into a 2d tensor [batch, lastDim]
+        // and look up topK along lastDim.
+        const [batch, size] = [predictionsVals.length / lastDim, lastDim];
+        const precision = Object(util["getTypedArrayFromDType"])("bool", batch);
+        for (let b = 0; b < batch; b++) {
+          const offset = b * size;
+          const vals = predictionsVals.subarray(offset, offset + size);
+          const valAndInd = [];
+          for (let i = 0; i < vals.length; i++) {
+            valAndInd.push({ value: vals[i], index: i });
+          }
+          valAndInd.sort((a, b) => b.value - a.value);
+          precision[b] = 0;
+          for (let i = 0; i < k; i++) {
+            if (valAndInd[i].index === targetsVals[b]) {
+              precision[b] = 1;
+              break;
+            }
+          }
+        }
+        if (predictions !== $predictions) {
+          $predictions.dispose();
+        }
+        if (targets !== $targets) {
+          $targets.dispose();
+        }
+        // Output precision has the same shape as targets.
+        return Object(tensor_ops["f" /* tensor */])(precision, $targets.shape, "bool");
+      }
+      const inTopKAsync = inTopKAsync_;
+      //# sourceMappingURL=in_top_k.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/loss_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      var Reduction;
+      (function (Reduction) {
+        Reduction[(Reduction["NONE"] = 0)] = "NONE";
+        Reduction[(Reduction["MEAN"] = 1)] = "MEAN";
+        Reduction[(Reduction["SUM"] = 2)] = "SUM";
+        Reduction[(Reduction["SUM_BY_NONZERO_WEIGHTS"] = 3)] = "SUM_BY_NONZERO_WEIGHTS";
+      })(Reduction || (Reduction = {}));
+      /**
+       * Computes the weighted loss between two tensors.
+       *
+       * @param losses Tensor of shape `[batch_size, d1, ... dN]`.
+       * @param weights Tensor whose rank is either 0, or the same rank as
+       *    `losses`, and must be broadcastable to `losses` (i.e., all
+       *    dimensions must be either `1`, or the same as the corresponding
+       *    `losses` dimension).
+       */
+      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
+      function computeWeightedLoss_(losses, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {
+        const $losses = Object(tensor_util_env["a" /* convertToTensor */])(
+          losses,
+          "losses",
+          "computeWeightedLoss"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "computeWeightedLoss"
+          );
+        }
+        const weightedLoss = $weights == null ? $losses : $losses.mul($weights);
+        if (reduction === Reduction.NONE) {
+          return weightedLoss;
+        }
+        if (reduction === Reduction.SUM) {
+          return weightedLoss.sum();
+        }
+        if (reduction === Reduction.MEAN) {
+          if ($weights == null) {
+            return weightedLoss.mean();
+          } else {
+            const broadcastFactor = $losses.size / $weights.size;
+            const result = weightedLoss.sum().div($weights.sum());
+            return broadcastFactor > 1
+              ? result.div(Object(tensor_ops["e" /* scalar */])(broadcastFactor))
+              : result;
+          }
+        }
+        if (reduction === Reduction.SUM_BY_NONZERO_WEIGHTS) {
+          if ($weights == null) {
+            return weightedLoss.sum().div(Object(tensor_ops["e" /* scalar */])($losses.size));
+          } else {
+            const broadcastedWeights = $weights.mul(
+              Object(tensor_ops["b" /* ones */])($losses.shape)
+            );
+            const numNonZeros = broadcastedWeights
+              .notEqual(Object(tensor_ops["e" /* scalar */])(0))
+              .sum()
+              .toFloat();
+            return weightedLoss.sum().div(numNonZeros);
+          }
+        }
+        throw Error(`Unknown reduction: ${reduction}`);
+      }
+      /**
+       * Computes the absolute difference loss between two tensors.
+       *
+       * @param labels The ground truth output tensor, same dimensions as
+       *    'predictions'.
+       * @param predictions The predicted outputs.
+       * @param weights Tensor whose rank is either 0, or the same rank as
+       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
+       *    must be either `1`, or the same as the corresponding `losses`
+       *    dimension).
+       * @param reduction Type of reduction to apply to loss. Should be of type
+       *    `Reduction`
+       */
+      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
+      function absoluteDifference_(
+        labels,
+        predictions,
+        weights,
+        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
+      ) {
+        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
+          labels,
+          "labels",
+          "absoluteDifference"
+        );
+        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
+          predictions,
+          "predictions",
+          "absoluteDifference"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "absoluteDifference"
+          );
+        }
+        Object(util["assertShapesMatch"])(
+          $labels.shape,
+          $predictions.shape,
+          "Error in absoluteDifference: "
+        );
+        const losses = $labels.sub($predictions).abs();
+        return computeWeightedLoss(losses, $weights, reduction);
+      }
+      /**
+       * Computes the mean squared error between two tensors.
+       *
+       * @param labels The ground truth output tensor, same dimensions as
+       *    'predictions'.
+       * @param predictions The predicted outputs.
+       * @param weights Tensor whose rank is either 0, or the same rank as
+       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
+       *    must be either `1`, or the same as the corresponding `losses`
+       *    dimension).
+       * @param reduction Type of reduction to apply to loss. Should be of type
+       *    `Reduction`
+       */
+      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
+      function meanSquaredError_(
+        labels,
+        predictions,
+        weights,
+        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
+      ) {
+        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
+          labels,
+          "labels",
+          "meanSquaredError"
+        );
+        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
+          predictions,
+          "predictions",
+          "meanSquaredError"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "meanSquaredError"
+          );
+        }
+        Object(util["assertShapesMatch"])(
+          $labels.shape,
+          $predictions.shape,
+          "Error in meanSquaredError: "
+        );
+        const losses = $labels.squaredDifference($predictions);
+        return computeWeightedLoss(losses, $weights, reduction);
+      }
+      /**
+       * Computes the cosine distance loss between two tensors.
+       *
+       * @param labels The ground truth output tensor, same dimensions as
+       *    'predictions'.
+       * @param predictions The predicted outputs.
+       * @param axis The dimension along which the cosine distance is computed.
+       * @param weights Tensor whose rank is either 0, or the same rank as
+       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
+       *    must be either `1`, or the same as the corresponding `losses`
+       *    dimension).
+       * @param reduction Type of reduction to apply to loss. Should be of type
+       *    `Reduction`
+       */
+      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
+      function cosineDistance_(
+        labels,
+        predictions,
+        axis,
+        weights,
+        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
+      ) {
+        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
+          labels,
+          "labels",
+          "cosineDistance"
+        );
+        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
+          predictions,
+          "predictions",
+          "cosineDistance"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "cosineDistance"
+          );
+        }
+        Object(util["assertShapesMatch"])(
+          $labels.shape,
+          $predictions.shape,
+          "Error in cosineDistance: "
+        );
+        const one = Object(tensor_ops["e" /* scalar */])(1);
+        const losses = one.sub($labels.mul($predictions).sum(axis, true));
+        return computeWeightedLoss(losses, $weights, reduction);
+      }
+      /**
+       * Computes the Hinge loss between two tensors.
+       *
+       * @param labels The ground truth output tensor, same dimensions as
+       *    'predictions'.
+       * @param predictions The predicted outputs.
+       * @param weights Tensor whose rank is either 0, or the same rank as
+       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
+       *    must be either `1`, or the same as the corresponding `losses`
+       *    dimension).
+       * @param reduction Type of reduction to apply to loss. Should be of type
+       *    `Reduction`
+       */
+      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
+      function hingeLoss_(
+        labels,
+        predictions,
+        weights,
+        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
+      ) {
+        let $labels = Object(tensor_util_env["a" /* convertToTensor */])(
+          labels,
+          "labels",
+          "hingeLoss"
+        );
+        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
+          predictions,
+          "predictions",
+          "hingeLoss"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "hingeLoss"
+          );
+        }
+        Object(util["assertShapesMatch"])(
+          $labels.shape,
+          $predictions.shape,
+          "Error in hingeLoss: "
+        );
+        const one = Object(tensor_ops["e" /* scalar */])(1);
+        // Convert binary labels to (-1, 1)
+        $labels = Object(tensor_ops["e" /* scalar */])(2).mul($labels).sub(one);
+        const losses = one.sub($labels.mul($predictions)).relu();
+        return computeWeightedLoss(losses, $weights, reduction);
+      }
+      /**
+       * Computes the log loss between two tensors.
+       *
+       * @param labels The ground truth output tensor, same dimensions as
+       *    'predictions'.
+       * @param predictions The predicted outputs.
+       * @param weights Tensor whose rank is either 0, or the same rank as
+       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
+       *    must be either `1`, or the same as the corresponding `losses`
+       *    dimension).
+       * @param epsilon A small increment to avoid taking log of zero
+       * @param reduction Type of reduction to apply to loss. Should be of type
+       *    `Reduction`
+       */
+      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
+      function logLoss_(
+        labels,
+        predictions,
+        weights,
+        epsilon = 1e-7,
+        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
+      ) {
+        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
+          labels,
+          "labels",
+          "logLoss"
+        );
+        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
+          predictions,
+          "predictions",
+          "logLoss"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "logLoss"
+          );
+        }
+        Object(util["assertShapesMatch"])($labels.shape, $predictions.shape, "Error in logLoss: ");
+        const one = Object(tensor_ops["e" /* scalar */])(1);
+        const epsilonScalar = Object(tensor_ops["e" /* scalar */])(epsilon);
+        const losses = $labels
+          .mul($predictions.add(epsilonScalar).log())
+          .neg()
+          .sub(one.sub($labels).mul(one.sub($predictions).add(epsilonScalar).log()));
+        return computeWeightedLoss(losses, $weights, reduction);
+      }
+      function sigmoidCrossEntropyWithLogits_(labels, logits) {
+        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
+          labels,
+          "labels",
+          "sigmoidCrossEntropyWithLogits"
+        );
+        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
+          logits,
+          "logits",
+          "sigmoidCrossEntropyWithLogits"
+        );
+        Object(util["assertShapesMatch"])(
+          $labels.shape,
+          $logits.shape,
+          "Error in sigmoidCrossEntropyWithLogits: "
+        );
+        /**
+         * Implementation Details:
+         *
+         * For brevity, let `x = logits`, `z = labels`.  The logistic loss is
+         *     z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
+         *   = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
+         *   = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
+         *   = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
+         *   = (1 - z) * x + log(1 + exp(-x))
+         *   = x - x * z + log(1 + exp(-x))
+         *
+         *   For x < 0, to avoid overflow in exp(-x), we reformulate the above
+         *     x - x * z + log(1 + exp(-x))
+         *   = log(exp(x)) - x * z + log(1 + exp(-x))
+         *   = - x * z + log(1 + exp(x))
+         *
+         * Hence, to ensure stability and avoid overflow, the implementation uses
+         * this equivalent formulation:
+         *     max(x, 0) - x * z + log(1 + exp(-abs(x)))
+         */
+        const maxOutput = $logits.relu();
+        const outputXTarget = $logits.mul($labels);
+        const sigmoidOutput = $logits.abs().neg().exp().log1p();
+        return maxOutput.sub(outputXTarget).add(sigmoidOutput);
+      }
+      /**
+       * Computes the sigmoid cross entropy loss between two tensors.
+       *
+       * If labelSmoothing is nonzero, smooth the labels towards 1/2:
+       *
+       *   newMulticlassLabels = multiclassLabels * (1 - labelSmoothing)
+       *                         + 0.5 * labelSmoothing
+       *
+       * @param multiClassLabels The ground truth output tensor of shape
+       * [batch_size, num_classes], same dimensions as 'predictions'.
+       * @param logits The predicted outputs.
+       * @param weights Tensor whose rank is either 0, or the same rank as
+       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
+       *    must be either `1`, or the same as the corresponding `losses`
+       *    dimension).
+       * @param labelSmoothing If greater than 0, then smooth the labels.
+       * @param reduction Type of reduction to apply to loss. Should be of type
+       *    `Reduction`
+       */
+      /** @doc { heading: 'Training', subheading: 'Losses', namespace: 'losses' } */
+      function sigmoidCrossEntropy_(
+        multiClassLabels,
+        logits,
+        weights,
+        labelSmoothing = 0,
+        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
+      ) {
+        let $multiClassLabels = Object(tensor_util_env["a" /* convertToTensor */])(
+          multiClassLabels,
+          "multiClassLabels",
+          "sigmoidCrossEntropy"
+        );
+        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
+          logits,
+          "logits",
+          "sigmoidCrossEntropy"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "sigmoidCrossEntropy"
+          );
+        }
+        Object(util["assertShapesMatch"])(
+          $multiClassLabels.shape,
+          $logits.shape,
+          "Error in sigmoidCrossEntropy: "
+        );
+        if (labelSmoothing > 0) {
+          const labelSmoothingScalar = Object(tensor_ops["e" /* scalar */])(labelSmoothing);
+          const one = Object(tensor_ops["e" /* scalar */])(1);
+          const half = Object(tensor_ops["e" /* scalar */])(0.5);
+          $multiClassLabels = $multiClassLabels
+            .mul(one.sub(labelSmoothingScalar))
+            .add(half.mul(labelSmoothingScalar));
+        }
+        const losses = sigmoidCrossEntropyWithLogits_($multiClassLabels, $logits);
+        return computeWeightedLoss(losses, $weights, reduction);
+      }
+      /**
+       * Computes the huber loss between two tensors.
+       *
+       * @param labels The ground truth output tensor, same dimensions as
+       *    'predictions'.
+       * @param predictions The predicted outputs.
+       * @param weights Tensor whose rank is either 0, or the same rank as
+       *    `labels`, and must be broadcastable to `labels` (i.e., all dimensions
+       *    must be either `1`, or the same as the corresponding `losses`
+       *    dimension).
+       * @param delta Point where huber loss changes from quadratic to linear.
+       * @param reduction Type of reduction to apply to loss. Should be of type
+       *    `Reduction`.
+       */
+      /** @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'} */
+      function huberLoss_(
+        labels,
+        predictions,
+        weights,
+        delta = 1.0,
+        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
+      ) {
+        const $labels = Object(tensor_util_env["a" /* convertToTensor */])(
+          labels,
+          "labels",
+          "huberLoss"
+        );
+        const $predictions = Object(tensor_util_env["a" /* convertToTensor */])(
+          predictions,
+          "predictions",
+          "huberLoss"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "huberLoss"
+          );
+        }
+        Object(util["assertShapesMatch"])(
+          $labels.shape,
+          $predictions.shape,
+          "Error in huberLoss: "
+        );
+        const deltaScalar = Object(tensor_ops["e" /* scalar */])(delta);
+        const error = $predictions.sub($labels).abs();
+        const quadratic = minimum(error, deltaScalar);
+        const linear = error.sub(quadratic);
+        const losses = Object(tensor_ops["e" /* scalar */])(0.5)
+          .mul(quadratic.square())
+          .add(deltaScalar.mul(linear));
+        return computeWeightedLoss(losses, $weights, reduction);
+      }
+      /**
+       * Computes softmax cross entropy between logits and labels.
+       *
+       * Measures the probability error in discrete classification tasks in which
+       * the classes are mutually exclusive (each entry is in exactly one class).
+       * For example, each CIFAR-10 image is labeled with one and only one label: an
+       * image can be a dog or a truck, but not both.
+       *
+       * `NOTE`: While the classes are mutually exclusive, their probabilities need
+       * not be. All that is required is that each row of labels is a valid
+       * probability distribution. If they are not, the computation of the gradient
+       * will be incorrect.
+       *
+       * `WARNING`: This op expects unscaled logits, since it performs a softmax on
+       * logits internally for efficiency. Do not call this op with the output of
+       * softmax, as it will produce incorrect results.
+       *
+       * logits and labels must have the same shape, e.g. [batch_size, num_classes]
+       * and the same dtype.
+       * @param labels The labels array.
+       * @param logits The logits array.
+       * @param dim The dimension softmax would be performed on. Defaults to `-1`
+       *     which indicates the last dimension.
+       */
+      function softmaxCrossEntropyWithLogits_(labels, logits, dim = -1) {
+        if (dim === -1) {
+          dim = logits.rank - 1;
+        }
+        if (dim !== logits.rank - 1) {
+          throw Error(
+            `Softmax cross entropy along a non-last dimension is not yet ` +
+              `supported. Labels / logits was rank ${logits.rank} ` +
+              `and dim was ${dim}`
+          );
+        }
+        // Use a custom gradient for numerical stability.
+        const customOp = customGrad((labels, logits, save) => {
+          // Reference:
+          //   1. http://cs231n.github.io/linear-classify/#softmax
+          //   2. https://blog.feedly.com/tricks-of-the-trade-logsumexp/
+          const keepDims = true;
+          const lse = logits.logSumExp([dim], keepDims);
+          const logResult = logits.toFloat().sub(lse);
+          save([labels, logResult]);
+          const costVector = logResult.mul(labels).neg();
+          const value = costVector.sum([dim]);
+          const gradFunc = (dy, saved) => {
+            const [labels, logResult] = saved;
+            const dyShape = expandShapeToKeepDim(dy.shape, [dim]);
+            return [
+              dy.reshape(dyShape).mul(labels.toFloat().sub(logResult.exp())),
+              dy.reshape(dyShape).mul(logResult.exp().sub(labels.toFloat())),
+            ];
+          };
+          return { value, gradFunc };
+        });
+        return customOp(labels, logits);
+      }
+      /**
+       * Computes the softmax cross entropy loss between two tensors.
+       *
+       * If labelSmoothing is nonzero, smooth the labels towards 1/2:
+       *
+       *   newOnehotLabels = onehotLabels * (1 - labelSmoothing)
+       *                         + labelSmoothing / numClasses
+       *
+       * @param onehotLabels One hot encoded labels
+       *    [batch_size, num_classes], same dimensions as 'predictions'.
+       * @param logits The predicted outputs.
+       * @param weights Tensor whose rank is either 0, or 1, and must be
+       *    broadcastable to `loss`  of shape [batch_size]
+       * @param labelSmoothing If greater than 0, then smooth the labels.
+       * @param reduction Type of reduction to apply to loss. Should be of type
+       *    `Reduction`
+       */
+      /** @doc { heading: 'Training', subheading: 'Losses', namespace: 'losses' } */
+      function softmaxCrossEntropy_(
+        onehotLabels,
+        logits,
+        weights,
+        labelSmoothing = 0,
+        reduction = Reduction.SUM_BY_NONZERO_WEIGHTS
+      ) {
+        let $onehotLabels = Object(tensor_util_env["a" /* convertToTensor */])(
+          onehotLabels,
+          "onehotLabels",
+          "softmaxCrossEntropy"
+        );
+        const $logits = Object(tensor_util_env["a" /* convertToTensor */])(
+          logits,
+          "logits",
+          "softmaxCrossEntropy"
+        );
+        let $weights = null;
+        if (weights != null) {
+          $weights = Object(tensor_util_env["a" /* convertToTensor */])(
+            weights,
+            "weights",
+            "softmaxCrossEntropy"
+          );
+        }
+        Object(util["assertShapesMatch"])(
+          $onehotLabels.shape,
+          $logits.shape,
+          "Error in softmaxCrossEntropy: "
+        );
+        if (labelSmoothing > 0) {
+          const labelSmoothingScalar = Object(tensor_ops["e" /* scalar */])(labelSmoothing);
+          const one = Object(tensor_ops["e" /* scalar */])(1);
+          const numClasses = Object(tensor_ops["e" /* scalar */])($onehotLabels.shape[1]);
+          $onehotLabels = $onehotLabels
+            .mul(one.sub(labelSmoothingScalar))
+            .add(labelSmoothingScalar.div(numClasses));
+        }
+        const losses = softmaxCrossEntropyWithLogits_($onehotLabels, $logits);
+        return computeWeightedLoss(losses, $weights, reduction);
+      }
+      const absoluteDifference = Object(operation["a" /* op */])({ absoluteDifference_ });
+      const computeWeightedLoss = Object(operation["a" /* op */])({ computeWeightedLoss_ });
+      const cosineDistance = Object(operation["a" /* op */])({ cosineDistance_ });
+      const hingeLoss = Object(operation["a" /* op */])({ hingeLoss_ });
+      const huberLoss = Object(operation["a" /* op */])({ huberLoss_ });
+      const logLoss = Object(operation["a" /* op */])({ logLoss_ });
+      const meanSquaredError = Object(operation["a" /* op */])({ meanSquaredError_ });
+      const sigmoidCrossEntropy = Object(operation["a" /* op */])({ sigmoidCrossEntropy_ });
+      const softmaxCrossEntropy = Object(operation["a" /* op */])({ softmaxCrossEntropy_ });
+      //# sourceMappingURL=loss_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/linalg_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Linear algebra ops.
+       */
+
+      /**
+       * Copy a tensor setting everything outside a central band in each innermost
+       * matrix to zero.
+       *
+       * The band part is computed as follows: Assume input has `k` dimensions
+       * `[I, J, K, ..., M, N]`, then the output is a tensor with the same shape where
+       * `band[i, j, k, ..., m, n] = in_band(m, n) * input[i, j, k, ..., m, n]`.
+       * The indicator function
+       * `in_band(m, n) = (num_lower < 0 || (m-n) <= num_lower))`
+       * `&& (num_upper < 0 || (n-m) <= num_upper)`
+       *
+       * ```js
+       * const x = tf.tensor2d([[ 0,  1,  2, 3],
+       *                        [-1,  0,  1, 2],
+       *                        [-2, -1,  0, 1],
+       *                        [-3, -2, -1, 0]]);
+       * let y = tf.linalg.bandPart(x, 1, -1);
+       * y.print(); // [[ 0,  1,  2, 3],
+       *            //  [-1,  0,  1, 2],
+       *            //  [ 0, -1,  0, 1],
+       *            //  [ 0, 0 , -1, 0]]
+       * let z = tf.linalg.bandPart(x, 2, 1);
+       * z.print(); // [[ 0,  1,  0, 0],
+       *            //  [-1,  0,  1, 0],
+       *            //  [-2, -1,  0, 1],
+       *            //  [ 0, -2, -1, 0]]
+       * ```
+       *
+       * @param x Rank `k` tensor
+       * @param numLower Number of subdiagonals to keep.
+       *   If negative, keep entire lower triangle.
+       * @param numUpper Number of subdiagonals to keep.
+       *   If negative, keep entire upper triangle.
+       * @returns Rank `k` tensor of the same shape as input.
+       *   The extracted banded tensor.
+       */
+      /**
+       * @doc {heading:'Operations',
+       *       subheading:'Linear Algebra',
+       *       namespace:'linalg'}
+       */
+      function bandPart_(a, numLower, numUpper) {
+        if (numLower % 1 !== 0) {
+          throw new Error(`bandPart(): numLower must be an integer, got ${numLower}.`);
+        }
+        if (numUpper % 1 !== 0) {
+          throw new Error(`bandPart(): numUpper must be an integer, got ${numUpper}.`);
+        }
+        const $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "bandPart");
+        if ($a.rank < 2) {
+          throw new Error(`bandPart(): Rank must be at least 2, got ${$a.rank}.`);
+        }
+        const shape = $a.shape,
+          [M, N] = $a.shape.slice(-2);
+        if (!(numLower <= M)) {
+          throw new Error(
+            `bandPart(): numLower (${numLower})` +
+              ` must not be greater than the number of rows (${M}).`
+          );
+        }
+        if (!(numUpper <= N)) {
+          throw new Error(
+            `bandPart(): numUpper (${numUpper})` +
+              ` must not be greater than the number of columns (${N}).`
+          );
+        }
+        if (numLower < 0) {
+          numLower = M;
+        }
+        if (numUpper < 0) {
+          numUpper = N;
+        }
+        const i = Object(tensor_ops["d" /* range */])(0, M, 1, "int32").reshape([-1, 1]),
+          j = Object(tensor_ops["d" /* range */])(0, N, 1, "int32"),
+          ij = sub(i, j);
+        const inBand = logicalAnd(
+          ij.lessEqual(Object(tensor_ops["e" /* scalar */])(+numLower, "int32")),
+          ij.greaterEqual(Object(tensor_ops["e" /* scalar */])(-numUpper, "int32"))
+        );
+        const zero = Object(tensor_ops["n" /* zeros */])([M, N], $a.dtype);
+        return stack(
+          unstack($a.reshape([-1, M, N])).map((mat) => where(inBand, mat, zero))
+        ).reshape(shape);
+      }
+      /**
+       * Gram-Schmidt orthogonalization.
+       *
+       * ```js
+       * const x = tf.tensor2d([[1, 2], [3, 4]]);
+       * let y = tf.linalg.gramSchmidt(x);
+       * y.print();
+       * console.log('Othogonalized:');
+       * y.dot(y.transpose()).print();  // should be nearly the identity matrix.
+       * console.log('First row direction maintained:');
+       * const data = await y.array();
+       * console.log(data[0][1] / data[0][0]);  // should be nearly 2.
+       * ```
+       *
+       * @param xs The vectors to be orthogonalized, in one of the two following
+       *   formats:
+       *   - An Array of `tf.Tensor1D`.
+       *   - A `tf.Tensor2D`, i.e., a matrix, in which case the vectors are the rows
+       *     of `xs`.
+       *   In each case, all the vectors must have the same length and the length
+       *   must be greater than or equal to the number of vectors.
+       * @returns The orthogonalized and normalized vectors or matrix.
+       *   Orthogonalization means that the vectors or the rows of the matrix
+       *   are orthogonal (zero inner products). Normalization means that each
+       *   vector or each row of the matrix has an L2 norm that equals `1`.
+       */
+      /**
+       * @doc {heading:'Operations',
+       *       subheading:'Linear Algebra',
+       *       namespace:'linalg'}
+       */
+      function gramSchmidt_(xs) {
+        let inputIsTensor2D;
+        if (Array.isArray(xs)) {
+          inputIsTensor2D = false;
+          Object(util["assert"])(
+            xs != null && xs.length > 0,
+            () => "Gram-Schmidt process: input must not be null, undefined, or " + "empty"
+          );
+          const dim = xs[0].shape[0];
+          for (let i = 1; i < xs.length; ++i) {
+            Object(util["assert"])(
+              xs[i].shape[0] === dim,
+              () =>
+                "Gram-Schmidt: Non-unique lengths found in the input vectors: " +
+                `(${xs[i].shape[0]} vs. ${dim})`
+            );
+          }
+        } else {
+          inputIsTensor2D = true;
+          xs = split(xs, xs.shape[0], 0).map((x) => squeeze(x, [0]));
+        }
+        Object(util["assert"])(
+          xs.length <= xs[0].shape[0],
+          () =>
+            `Gram-Schmidt: Number of vectors (${xs.length}) exceeds ` +
+            `number of dimensions (${xs[0].shape[0]}).`
+        );
+        const ys = [];
+        const xs1d = xs;
+        for (let i = 0; i < xs.length; ++i) {
+          ys.push(
+            engine["a" /* ENGINE */].tidy(() => {
+              let x = xs1d[i];
+              if (i > 0) {
+                for (let j = 0; j < i; ++j) {
+                  const proj = sum(ys[j].mul(x)).mul(ys[j]);
+                  x = x.sub(proj);
+                }
+              }
+              return x.div(norm_norm(x, "euclidean"));
+            })
+          );
+        }
+        if (inputIsTensor2D) {
+          return stack(ys, 0);
+        } else {
+          return ys;
+        }
+      }
+      /**
+       * Compute QR decomposition of m-by-n matrix using Householder transformation.
+       *
+       * Implementation based on
+       *   [http://www.cs.cornell.edu/~bindel/class/cs6210-f09/lec18.pdf]
+       * (http://www.cs.cornell.edu/~bindel/class/cs6210-f09/lec18.pdf)
+       *
+       * ```js
+       * const a = tf.tensor2d([[1, 2], [3, 4]]);
+       * let [q, r] = tf.linalg.qr(a);
+       * console.log('Q');
+       * q.print();
+       * console.log('R');
+       * r.print();
+       * console.log('Orthogonalized');
+       * q.dot(q.transpose()).print()  // should be nearly the identity matrix.
+       * console.log('Reconstructed');
+       * q.dot(r).print(); // should be nearly [[1, 2], [3, 4]];
+       * ```
+       *
+       * @param x The `tf.Tensor` to be QR-decomposed. Must have rank >= 2. Suppose
+       *   it has the shape `[..., M, N]`.
+       * @param fullMatrices An optional boolean parameter. Defaults to `false`.
+       *   If `true`, compute full-sized `Q`. If `false` (the default),
+       *   compute only the leading N columns of `Q` and `R`.
+       * @returns An `Array` of two `tf.Tensor`s: `[Q, R]`. `Q` is a unitary matrix,
+       *   i.e., its columns all have unit norm and are mutually orthogonal.
+       *   If `M >= N`,
+       *     If `fullMatrices` is `false` (default),
+       *       - `Q` has a shape of `[..., M, N]`,
+       *       - `R` has a shape of `[..., N, N]`.
+       *     If `fullMatrices` is `true` (default),
+       *       - `Q` has a shape of `[..., M, M]`,
+       *       - `R` has a shape of `[..., M, N]`.
+       *   If `M < N`,
+       *     - `Q` has a shape of `[..., M, M]`,
+       *     - `R` has a shape of `[..., M, N]`.
+       * @throws If the rank of `x` is less than 2.
+       */
+      /**
+       * @doc {heading:'Operations',
+       *       subheading:'Linear Algebra',
+       *       namespace:'linalg'}
+       */
+      function qr_(x, fullMatrices = false) {
+        if (x.rank < 2) {
+          throw new Error(`qr() requires input tensor to have a rank >= 2, but got rank ${x.rank}`);
+        } else if (x.rank === 2) {
+          return qr2d(x, fullMatrices);
+        } else {
+          // Rank > 2.
+          // TODO(cais): Below we split the input into individual 2D tensors,
+          //   perform QR decomposition on them and then stack the results back
+          //   together. We should explore whether this can be parallelized.
+          const outerDimsProd = x.shape
+            .slice(0, x.shape.length - 2)
+            .reduce((value, prev) => value * prev);
+          const x2ds = unstack(
+            x.reshape([outerDimsProd, x.shape[x.shape.length - 2], x.shape[x.shape.length - 1]]),
+            0
+          );
+          const q2ds = [];
+          const r2ds = [];
+          x2ds.forEach((x2d) => {
+            const [q2d, r2d] = qr2d(x2d, fullMatrices);
+            q2ds.push(q2d);
+            r2ds.push(r2d);
+          });
+          const q = stack(q2ds, 0).reshape(x.shape);
+          const r = stack(r2ds, 0).reshape(x.shape);
+          return [q, r];
+        }
+      }
+      function qr2d(x, fullMatrices = false) {
+        return engine["a" /* ENGINE */].tidy(() => {
+          if (x.shape.length !== 2) {
+            throw new Error(`qr2d() requires a 2D Tensor, but got a ${x.shape.length}D Tensor.`);
+          }
+          const m = x.shape[0];
+          const n = x.shape[1];
+          let q = eye(m); // Orthogonal transform so far.
+          let r = x.clone(); // Transformed matrix so far.
+          const one2D = Object(tensor_ops["h" /* tensor2d */])([[1]], [1, 1]);
+          let w = one2D.clone();
+          const iters = m >= n ? n : m;
+          for (let j = 0; j < iters; ++j) {
+            // This tidy within the for-loop ensures we clean up temporary
+            // tensors as soon as they are no longer needed.
+            const rTemp = r;
+            const wTemp = w;
+            const qTemp = q;
+            [w, r, q] = engine["a" /* ENGINE */].tidy(() => {
+              // Find H = I - tau * w * w', to put zeros below R(j, j).
+              const rjEnd1 = r.slice([j, j], [m - j, 1]);
+              const normX = rjEnd1.norm();
+              const rjj = r.slice([j, j], [1, 1]);
+              // The sign() function returns 0 on 0, which causes division by zero.
+              const s = Object(tensor_ops["h" /* tensor2d */])([[-1]]).where(
+                rjj.greater(0),
+                Object(tensor_ops["h" /* tensor2d */])([[1]])
+              );
+              const u1 = rjj.sub(s.mul(normX));
+              const wPre = rjEnd1.div(u1);
+              if (wPre.shape[0] === 1) {
+                w = one2D.clone();
+              } else {
+                w = one2D.concat(wPre.slice([1, 0], [wPre.shape[0] - 1, wPre.shape[1]]), 0);
+              }
+              const tau = s.matMul(u1).div(normX).neg();
+              // -- R := HR, Q := QH.
+              const rjEndAll = r.slice([j, 0], [m - j, n]);
+              const tauTimesW = tau.mul(w);
+              const wT = w.transpose();
+              if (j === 0) {
+                r = rjEndAll.sub(tauTimesW.matMul(wT.matMul(rjEndAll)));
+              } else {
+                const rTimesTau = rjEndAll.sub(tauTimesW.matMul(wT.matMul(rjEndAll)));
+                r = r.slice([0, 0], [j, n]).concat(rTimesTau, 0);
+              }
+              const tawTimesWT = tauTimesW.transpose();
+              const qAllJEnd = q.slice([0, j], [m, q.shape[1] - j]);
+              if (j === 0) {
+                q = qAllJEnd.sub(qAllJEnd.matMul(w).matMul(tawTimesWT));
+              } else {
+                const qTimesTau = qAllJEnd.sub(qAllJEnd.matMul(w).matMul(tawTimesWT));
+                q = q.slice([0, 0], [m, j]).concat(qTimesTau, 1);
+              }
+              return [w, r, q];
+            });
+            dispose([rTemp, wTemp, qTemp]);
+          }
+          if (!fullMatrices && m > n) {
+            q = q.slice([0, 0], [m, n]);
+            r = r.slice([0, 0], [n, n]);
+          }
+          return [q, r];
+        });
+      }
+      const bandPart = Object(operation["a" /* op */])({ bandPart_ });
+      const gramSchmidt = Object(operation["a" /* op */])({ gramSchmidt_ });
+      const qr = Object(operation["a" /* op */])({ qr_ });
+      //# sourceMappingURL=linalg_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/array_util.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Inserts a value into a sorted array. This method allows duplicate, meaning it
+       * allows inserting duplicate value, in which case, the element will be inserted
+       * at the lowest index of the value.
+       * @param arr The array to modify.
+       * @param element The element to insert.
+       * @param comparator Optional. If no comparator is specified, elements are
+       * compared using array_util.defaultComparator, which is suitable for Strings
+       * and Numbers in ascending arrays. If the array contains multiple instances of
+       * the target value, the left-most instance will be returned. To provide a
+       * comparator, it should take 2 arguments to compare and return a negative,
+       * zero, or a positive number.
+       */
+      function binaryInsert(arr, element, comparator) {
+        const index = binarySearch(arr, element, comparator);
+        const insertionPoint = index < 0 ? -(index + 1) : index;
+        arr.splice(insertionPoint, 0, element);
+      }
+      /**
+       * Searches the array for the target using binary search, returns the index
+       * of the found element, or position to insert if element not found. If no
+       * comparator is specified, elements are compared using array_
+       * util.defaultComparator, which is suitable for Strings and Numbers in
+       * ascending arrays. If the array contains multiple instances of the target
+       * value, the left-most instance will be returned.
+       * @param arr The array to be searched in.
+       * @param target The target to be searched for.
+       * @param comparator Should take 2 arguments to compare and return a negative,
+       *    zero, or a positive number.
+       * @return Lowest index of the target value if found, otherwise the insertion
+       *    point where the target should be inserted, in the form of
+       *    (-insertionPoint - 1).
+       */
+      function binarySearch(arr, target, comparator) {
+        return binarySearch_(arr, target, comparator || defaultComparator);
+      }
+      /**
+       * Compares its two arguments for order.
+       * @param a The first element to be compared.
+       * @param b The second element to be compared.
+       * @return A negative number, zero, or a positive number as the first
+       *     argument is less than, equal to, or greater than the second.
+       */
+      function defaultComparator(a, b) {
+        return a > b ? 1 : a < b ? -1 : 0;
+      }
+      function binarySearch_(arr, target, comparator) {
+        let left = 0;
+        let right = arr.length;
+        let middle = 0;
+        let found = false;
+        while (left < right) {
+          middle = left + ((right - left) >>> 1);
+          const compareResult = comparator(target, arr[middle]);
+          if (compareResult > 0) {
+            left = middle + 1;
+          } else {
+            right = middle;
+            // If compareResult is 0, the value is found. We record it is found,
+            // and then keep looking because there may be duplicate.
+            found = !compareResult;
+          }
+        }
+        return found ? left : -left - 1;
+      }
+      //# sourceMappingURL=array_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/non_max_suppression_impl.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Implementation of the NonMaxSuppression kernel shared between webgl and cpu.
+       */
+
+      function nonMaxSuppressionV3(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold) {
+        const dummySoftNmsSigma = 0.0;
+        const result = nonMaxSuppressionImpl_(
+          boxes,
+          scores,
+          maxOutputSize,
+          iouThreshold,
+          scoreThreshold,
+          dummySoftNmsSigma
+        );
+        result.selectedScores.dispose();
+        result.numValidOutputs.dispose();
+        return result.selectedIndices;
+      }
+      function nonMaxSuppressionV5(
+        boxes,
+        scores,
+        maxOutputSize,
+        iouThreshold,
+        scoreThreshold,
+        softNmsSigma
+      ) {
+        // For NonMaxSuppressionV5Op, we always return a second output holding
+        // corresponding scores.
+        const returnScoresTensor = true;
+        const result = nonMaxSuppressionImpl_(
+          boxes,
+          scores,
+          maxOutputSize,
+          iouThreshold,
+          scoreThreshold,
+          softNmsSigma,
+          returnScoresTensor
+        );
+        result.numValidOutputs.dispose();
+        return {
+          selectedIndices: result.selectedIndices,
+          selectedScores: result.selectedScores,
+        };
+      }
+      function nonMaxSuppressionImpl_(
+        boxes,
+        scores,
+        maxOutputSize,
+        iouThreshold,
+        scoreThreshold,
+        softNmsSigma,
+        returnScoresTensor = false,
+        padToMaxOutputSize = false
+      ) {
+        // The list is sorted in ascending order, so that we can always pop the
+        // candidate with the largest score in O(1) time.
+        const candidates = [];
+        for (let i = 0; i < scores.length; i++) {
+          if (scores[i] > scoreThreshold) {
+            candidates.push({ score: scores[i], boxIndex: i, suppressBeginIndex: 0 });
+          }
+        }
+        candidates.sort(ascendingComparator);
+        // If softNmsSigma is 0, the outcome of this algorithm is exactly same as
+        // before.
+        const scale = softNmsSigma > 0 ? -0.5 / softNmsSigma : 0.0;
+        const selectedIndices = [];
+        const selectedScores = [];
+        while (selectedIndices.length < maxOutputSize && candidates.length > 0) {
+          const candidate = candidates.pop();
+          const { score: originalScore, boxIndex, suppressBeginIndex } = candidate;
+          if (originalScore < scoreThreshold) {
+            break;
+          }
+          // Overlapping boxes are likely to have similar scores, therefore we
+          // iterate through the previously selected boxes backwards in order to
+          // see if candidate's score should be suppressed. We use
+          // suppressBeginIndex to track and ensure a candidate can be suppressed
+          // by a selected box no more than once. Also, if the overlap exceeds
+          // iouThreshold, we simply ignore the candidate.
+          let ignoreCandidate = false;
+          for (let j = selectedIndices.length - 1; j >= suppressBeginIndex; --j) {
+            const iou = intersectionOverUnion(boxes, boxIndex, selectedIndices[j]);
+            if (iou >= iouThreshold) {
+              ignoreCandidate = true;
+              break;
+            }
+            candidate.score = candidate.score * suppressWeight(iouThreshold, scale, iou);
+            if (candidate.score <= scoreThreshold) {
+              break;
+            }
+          }
+          // At this point, if `candidate.score` has not dropped below
+          // `scoreThreshold`, then we know that we went through all of the
+          // previous selections and can safely update `suppressBeginIndex` to the
+          // end of the selected array. Then we can re-insert the candidate with
+          // the updated score and suppressBeginIndex back in the candidate list.
+          // If on the other hand, `candidate.score` has dropped below the score
+          // threshold, we will not add it back to the candidates list.
+          candidate.suppressBeginIndex = selectedIndices.length;
+          if (!ignoreCandidate) {
+            // Candidate has passed all the tests, and is not suppressed, so
+            // select the candidate.
+            if (candidate.score === originalScore) {
+              selectedIndices.push(boxIndex);
+              selectedScores.push(candidate.score);
+            } else if (candidate.score > scoreThreshold) {
+              // Candidate's score is suppressed but is still high enough to be
+              // considered, so add back to the candidates list.
+              binaryInsert(candidates, candidate, ascendingComparator);
+            }
+          }
+        }
+        // NonMaxSuppressionV4 feature: padding output to maxOutputSize.
+        const numValidOutputs = selectedIndices.length;
+        if (padToMaxOutputSize) {
+          selectedIndices.fill(0, numValidOutputs);
+          selectedScores.fill(0.0, numValidOutputs);
+        }
+        return {
+          selectedIndices: Object(tensor_ops["g" /* tensor1d */])(selectedIndices, "int32"),
+          selectedScores: Object(tensor_ops["g" /* tensor1d */])(selectedScores, "float32"),
+          numValidOutputs: Object(tensor_ops["e" /* scalar */])(numValidOutputs, "int32"),
+        };
+      }
+      function intersectionOverUnion(boxes, i, j) {
+        const iCoord = boxes.subarray(i * 4, i * 4 + 4);
+        const jCoord = boxes.subarray(j * 4, j * 4 + 4);
+        const yminI = Math.min(iCoord[0], iCoord[2]);
+        const xminI = Math.min(iCoord[1], iCoord[3]);
+        const ymaxI = Math.max(iCoord[0], iCoord[2]);
+        const xmaxI = Math.max(iCoord[1], iCoord[3]);
+        const yminJ = Math.min(jCoord[0], jCoord[2]);
+        const xminJ = Math.min(jCoord[1], jCoord[3]);
+        const ymaxJ = Math.max(jCoord[0], jCoord[2]);
+        const xmaxJ = Math.max(jCoord[1], jCoord[3]);
+        const areaI = (ymaxI - yminI) * (xmaxI - xminI);
+        const areaJ = (ymaxJ - yminJ) * (xmaxJ - xminJ);
+        if (areaI <= 0 || areaJ <= 0) {
+          return 0.0;
+        }
+        const intersectionYmin = Math.max(yminI, yminJ);
+        const intersectionXmin = Math.max(xminI, xminJ);
+        const intersectionYmax = Math.min(ymaxI, ymaxJ);
+        const intersectionXmax = Math.min(xmaxI, xmaxJ);
+        const intersectionArea =
+          Math.max(intersectionYmax - intersectionYmin, 0.0) *
+          Math.max(intersectionXmax - intersectionXmin, 0.0);
+        return intersectionArea / (areaI + areaJ - intersectionArea);
+      }
+      // A Gaussian penalty function, this method always returns values in [0, 1].
+      // The weight is a function of similarity, the more overlap two boxes are, the
+      // smaller the weight is, meaning highly overlapping boxe will be significantly
+      // penalized. On the other hand, a non-overlapping box will not be penalized.
+      function suppressWeight(iouThreshold, scale, iou) {
+        const weight = Math.exp(scale * iou * iou);
+        return iou <= iouThreshold ? weight : 0.0;
+      }
+      function ascendingComparator(c1, c2) {
+        // For objects with same scores, we make the object with the larger index go
+        // first. In an array that pops from the end, this means that the object with
+        // the smaller index will be popped first. This ensures the same output as
+        // the TensorFlow python version.
+        return c1.score - c2.score || (c1.score === c2.score && c2.boxIndex - c1.boxIndex);
+      }
+      //# sourceMappingURL=non_max_suppression_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/nonmax_util.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function nonMaxSuppSanityCheck(
+        boxes,
+        scores,
+        maxOutputSize,
+        iouThreshold,
+        scoreThreshold,
+        softNmsSigma
+      ) {
+        if (iouThreshold == null) {
+          iouThreshold = 0.5;
+        }
+        if (scoreThreshold == null) {
+          scoreThreshold = Number.NEGATIVE_INFINITY;
+        }
+        if (softNmsSigma == null) {
+          softNmsSigma = 0.0;
+        }
+        const numBoxes = boxes.shape[0];
+        maxOutputSize = Math.min(maxOutputSize, numBoxes);
+        util["assert"](
+          0 <= iouThreshold && iouThreshold <= 1,
+          () => `iouThreshold must be in [0, 1], but was '${iouThreshold}'`
+        );
+        util["assert"](
+          boxes.rank === 2,
+          () => `boxes must be a 2D tensor, but was of rank '${boxes.rank}'`
+        );
+        util["assert"](
+          boxes.shape[1] === 4,
+          () => `boxes must have 4 columns, but 2nd dimension was ${boxes.shape[1]}`
+        );
+        util["assert"](scores.rank === 1, () => "scores must be a 1D tensor");
+        util["assert"](
+          scores.shape[0] === numBoxes,
+          () =>
+            `scores has incompatible shape with boxes. Expected ${numBoxes}, ` +
+            `but was ${scores.shape[0]}`
+        );
+        util["assert"](
+          0 <= softNmsSigma && softNmsSigma <= 1,
+          () => `softNmsSigma must be in [0, 1], but was '${softNmsSigma}'`
+        );
+        return { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };
+      }
+
+      //# sourceMappingURL=nonmax_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/non_max_suppression.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function nonMaxSuppression_(
+        boxes,
+        scores,
+        maxOutputSize,
+        iouThreshold = 0.5,
+        scoreThreshold = Number.NEGATIVE_INFINITY
+      ) {
+        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
+          boxes,
+          "boxes",
+          "nonMaxSuppression"
+        );
+        const $scores = Object(tensor_util_env["a" /* convertToTensor */])(
+          scores,
+          "scores",
+          "nonMaxSuppression"
+        );
+        const inputs = nonMaxSuppSanityCheck(
+          $boxes,
+          $scores,
+          maxOutputSize,
+          iouThreshold,
+          scoreThreshold
+        );
+        maxOutputSize = inputs.maxOutputSize;
+        iouThreshold = inputs.iouThreshold;
+        scoreThreshold = inputs.scoreThreshold;
+        const attrs = { maxOutputSize, iouThreshold, scoreThreshold };
+        return engine["a" /* ENGINE */].runKernelFunc(
+          (b) => b.nonMaxSuppression($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold),
+          { boxes: $boxes, scores: $scores },
+          null /* grad */,
+          kernel_names["Z" /* NonMaxSuppressionV3 */],
+          attrs
+        );
+      }
+      const nonMaxSuppression = Object(operation["a" /* op */])({ nonMaxSuppression_ });
+      //# sourceMappingURL=non_max_suppression.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/image_ops.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Bilinear resize a batch of 3D images to a new shape.
+       *
+       * @param images The images, of rank 4 or rank 3, of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
+       * @param size The new shape `[newHeight, newWidth]` to resize the
+       *     images to. Each channel is resized individually.
+       * @param alignCorners Defaults to False. If true, rescale
+       *     input by `(new_height - 1) / (height - 1)`, which exactly aligns the 4
+       *     corners of images and resized images. If false, rescale by
+       *     `new_height / height`. Treat similarly the width dimension.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
+      function resizeBilinear_(images, size, alignCorners = false) {
+        const $images = Object(tensor_util_env["a" /* convertToTensor */])(
+          images,
+          "images",
+          "resizeBilinear"
+        );
+        util["assert"](
+          $images.rank === 3 || $images.rank === 4,
+          () => `Error in resizeBilinear: x must be rank 3 or 4, but got ` + `rank ${$images.rank}.`
+        );
+        util["assert"](
+          size.length === 2,
+          () => `Error in resizeBilinear: new shape must 2D, but got shape ` + `${size}.`
+        );
+        let batchImages = $images;
+        let reshapedTo4D = false;
+        if ($images.rank === 3) {
+          reshapedTo4D = true;
+          batchImages = $images.as4D(1, $images.shape[0], $images.shape[1], $images.shape[2]);
+        }
+        const [newHeight, newWidth] = size;
+        const forward = (backend, save) => {
+          save([batchImages]);
+          return backend.resizeBilinear(batchImages, newHeight, newWidth, alignCorners);
+        };
+        const backward = (dy, saved) => {
+          return {
+            x: () =>
+              engine["a" /* ENGINE */].runKernelFunc(
+                (backend) => backend.resizeBilinearBackprop(dy, saved[0], alignCorners),
+                {}
+              ),
+          };
+        };
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          { x: batchImages },
+          backward,
+          "ResizeBilinear",
+          { alignCorners, newHeight, newWidth }
+        );
+        if (reshapedTo4D) {
+          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
+        }
+        return res;
+      }
+      /**
+       * NearestNeighbor resize a batch of 3D images to a new shape.
+       *
+       * @param images The images, of rank 4 or rank 3, of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
+       * @param size The new shape `[newHeight, newWidth]` to resize the
+       *     images to. Each channel is resized individually.
+       * @param alignCorners Defaults to False. If true, rescale
+       *     input by `(new_height - 1) / (height - 1)`, which exactly aligns the 4
+       *     corners of images and resized images. If false, rescale by
+       *     `new_height / height`. Treat similarly the width dimension.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
+      function resizeNearestNeighbor_(images, size, alignCorners = false) {
+        const $images = Object(tensor_util_env["a" /* convertToTensor */])(
+          images,
+          "images",
+          "resizeNearestNeighbor"
+        );
+        util["assert"](
+          $images.rank === 3 || $images.rank === 4,
+          () =>
+            `Error in resizeNearestNeighbor: x must be rank 3 or 4, but got ` +
+            `rank ${$images.rank}.`
+        );
+        util["assert"](
+          size.length === 2,
+          () => `Error in resizeNearestNeighbor: new shape must 2D, but got shape ` + `${size}.`
+        );
+        util["assert"](
+          $images.dtype === "float32" || $images.dtype === "int32",
+          () => "`images` must have `int32` or `float32` as dtype"
+        );
+        let batchImages = $images;
+        let reshapedTo4D = false;
+        if ($images.rank === 3) {
+          reshapedTo4D = true;
+          batchImages = $images.as4D(1, $images.shape[0], $images.shape[1], $images.shape[2]);
+        }
+        const [newHeight, newWidth] = size;
+        const forward = (backend, save) => {
+          save([batchImages]);
+          return backend.resizeNearestNeighbor(batchImages, newHeight, newWidth, alignCorners);
+        };
+        const backward = (dy, saved) => {
+          return {
+            batchImages: () =>
+              engine["a" /* ENGINE */].runKernelFunc(
+                (backend) => backend.resizeNearestNeighborBackprop(dy, saved[0], alignCorners),
+                {}
+              ),
+          };
+        };
+        const res = engine["a" /* ENGINE */].runKernelFunc(forward, { batchImages }, backward);
+        if (reshapedTo4D) {
+          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
+        }
+        return res;
+      }
+      /**
+       * Performs non maximum suppression of bounding boxes based on
+       * iou (intersection over union).
+       *
+       * @param boxes a 2d tensor of shape `[numBoxes, 4]`. Each entry is
+       *     `[y1, x1, y2, x2]`, where `(y1, x1)` and `(y2, x2)` are the corners of
+       *     the bounding box.
+       * @param scores a 1d tensor providing the box scores of shape `[numBoxes]`.
+       * @param maxOutputSize The maximum number of boxes to be selected.
+       * @param iouThreshold A float representing the threshold for deciding whether
+       *     boxes overlap too much with respect to IOU. Must be between [0, 1].
+       *     Defaults to 0.5 (50% box overlap).
+       * @param scoreThreshold A threshold for deciding when to remove boxes based
+       *     on score. Defaults to -inf, which means any score is accepted.
+       * @return A 1D tensor with the selected box indices.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
+      /** This is the async version of `nonMaxSuppression` */
+      async function nonMaxSuppressionAsync_(
+        boxes,
+        scores,
+        maxOutputSize,
+        iouThreshold = 0.5,
+        scoreThreshold = Number.NEGATIVE_INFINITY
+      ) {
+        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
+          boxes,
+          "boxes",
+          "nonMaxSuppressionAsync"
+        );
+        const $scores = Object(tensor_util_env["a" /* convertToTensor */])(
+          scores,
+          "scores",
+          "nonMaxSuppressionAsync"
+        );
+        const inputs = nonMaxSuppSanityCheck(
+          $boxes,
+          $scores,
+          maxOutputSize,
+          iouThreshold,
+          scoreThreshold
+        );
+        maxOutputSize = inputs.maxOutputSize;
+        iouThreshold = inputs.iouThreshold;
+        scoreThreshold = inputs.scoreThreshold;
+        const boxesAndScores = await Promise.all([$boxes.data(), $scores.data()]);
+        const boxesVals = boxesAndScores[0];
+        const scoresVals = boxesAndScores[1];
+        const res = nonMaxSuppressionV3(
+          boxesVals,
+          scoresVals,
+          maxOutputSize,
+          iouThreshold,
+          scoreThreshold
+        );
+        if ($boxes !== boxes) {
+          $boxes.dispose();
+        }
+        if ($scores !== scores) {
+          $scores.dispose();
+        }
+        return res;
+      }
+      /**
+       * Performs non maximum suppression of bounding boxes based on
+       * iou (intersection over union).
+       *
+       * This op also supports a Soft-NMS mode (c.f.
+       * Bodla et al, https://arxiv.org/abs/1704.04503) where boxes reduce the score
+       * of other overlapping boxes, therefore favoring different regions of the image
+       * with high scores. To enable this Soft-NMS mode, set the `softNmsSigma`
+       * parameter to be larger than 0.
+       *
+       * @param boxes a 2d tensor of shape `[numBoxes, 4]`. Each entry is
+       *     `[y1, x1, y2, x2]`, where `(y1, x1)` and `(y2, x2)` are the corners of
+       *     the bounding box.
+       * @param scores a 1d tensor providing the box scores of shape `[numBoxes]`.
+       * @param maxOutputSize The maximum number of boxes to be selected.
+       * @param iouThreshold A float representing the threshold for deciding whether
+       *     boxes overlap too much with respect to IOU. Must be between [0, 1].
+       *     Defaults to 0.5 (50% box overlap).
+       * @param scoreThreshold A threshold for deciding when to remove boxes based
+       *     on score. Defaults to -inf, which means any score is accepted.
+       * @param softNmsSigma A float representing the sigma parameter for Soft NMS.
+       *     When sigma is 0, it falls back to nonMaxSuppression.
+       * @return A map with the following properties:
+       *     - selectedIndices: A 1D tensor with the selected box indices.
+       *     - selectedScores: A 1D tensor with the corresponding scores for each
+       *       selected box.
+       */
+      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
+      function nonMaxSuppressionWithScore_(
+        boxes,
+        scores,
+        maxOutputSize,
+        iouThreshold = 0.5,
+        scoreThreshold = Number.NEGATIVE_INFINITY,
+        softNmsSigma = 0.0
+      ) {
+        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
+          boxes,
+          "boxes",
+          "nonMaxSuppression"
+        );
+        const $scores = Object(tensor_util_env["a" /* convertToTensor */])(
+          scores,
+          "scores",
+          "nonMaxSuppression"
+        );
+        const inputs = nonMaxSuppSanityCheck(
+          $boxes,
+          $scores,
+          maxOutputSize,
+          iouThreshold,
+          scoreThreshold,
+          softNmsSigma
+        );
+        maxOutputSize = inputs.maxOutputSize;
+        iouThreshold = inputs.iouThreshold;
+        scoreThreshold = inputs.scoreThreshold;
+        softNmsSigma = inputs.softNmsSigma;
+        const attrs = { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };
+        const result = engine["a" /* ENGINE */].runKernel(
+          "NonMaxSuppressionV5",
+          { boxes: $boxes, scores: $scores },
+          attrs
+        );
+        return { selectedIndices: result[0], selectedScores: result[1] };
+      }
+      /** This is the async version of `nonMaxSuppressionWithScore` */
+      async function nonMaxSuppressionWithScoreAsync_(
+        boxes,
+        scores,
+        maxOutputSize,
+        iouThreshold = 0.5,
+        scoreThreshold = Number.NEGATIVE_INFINITY,
+        softNmsSigma = 0.0
+      ) {
+        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
+          boxes,
+          "boxes",
+          "nonMaxSuppressionAsync"
+        );
+        const $scores = Object(tensor_util_env["a" /* convertToTensor */])(
+          scores,
+          "scores",
+          "nonMaxSuppressionAsync"
+        );
+        const inputs = nonMaxSuppSanityCheck(
+          $boxes,
+          $scores,
+          maxOutputSize,
+          iouThreshold,
+          scoreThreshold,
+          softNmsSigma
+        );
+        maxOutputSize = inputs.maxOutputSize;
+        iouThreshold = inputs.iouThreshold;
+        scoreThreshold = inputs.scoreThreshold;
+        softNmsSigma = inputs.softNmsSigma;
+        const boxesAndScores = await Promise.all([$boxes.data(), $scores.data()]);
+        const boxesVals = boxesAndScores[0];
+        const scoresVals = boxesAndScores[1];
+        const res = nonMaxSuppressionV5(
+          boxesVals,
+          scoresVals,
+          maxOutputSize,
+          iouThreshold,
+          scoreThreshold,
+          softNmsSigma
+        );
+        if ($boxes !== boxes) {
+          $boxes.dispose();
+        }
+        if ($scores !== scores) {
+          $scores.dispose();
+        }
+        return res;
+      }
+      /**
+       * Extracts crops from the input image tensor and resizes them using bilinear
+       * sampling or nearest neighbor sampling (possibly with aspect ratio change)
+       * to a common output size specified by crop_size.
+       *
+       * @param image 4d tensor of shape `[batch,imageHeight,imageWidth, depth]`,
+       *     where imageHeight and imageWidth must be positive, specifying the
+       *     batch of images from which to take crops
+       * @param boxes 2d float32 tensor of shape `[numBoxes, 4]`. Each entry is
+       *     `[y1, x1, y2, x2]`, where `(y1, x1)` and `(y2, x2)` are the normalized
+       *     coordinates of the box in the boxInd[i]'th image in the batch
+       * @param boxInd 1d int32 tensor of shape `[numBoxes]` with values in range
+       *     `[0, batch)` that specifies the image that the `i`-th box refers to.
+       * @param cropSize 1d int32 tensor of 2 elements `[cropHeigh, cropWidth]`
+       *     specifying the size to which all crops are resized to.
+       * @param method Optional string from `'bilinear' | 'nearest'`,
+       *     defaults to bilinear, which specifies the sampling method for resizing
+       * @param extrapolationValue A threshold for deciding when to remove boxes based
+       *     on score. Defaults to 0.
+       * @return A 4D tensor of the shape `[numBoxes,cropHeight,cropWidth,depth]`
+       */
+      /** @doc {heading: 'Operations', subheading: 'Images', namespace: 'image'} */
+      function cropAndResize_(image, boxes, boxInd, cropSize, method, extrapolationValue) {
+        const $image = Object(tensor_util_env["a" /* convertToTensor */])(
+          image,
+          "image",
+          "cropAndResize"
+        );
+        const $boxes = Object(tensor_util_env["a" /* convertToTensor */])(
+          boxes,
+          "boxes",
+          "cropAndResize",
+          "float32"
+        );
+        const $boxInd = Object(tensor_util_env["a" /* convertToTensor */])(
+          boxInd,
+          "boxInd",
+          "cropAndResize",
+          "int32"
+        );
+        method = method || "bilinear";
+        extrapolationValue = extrapolationValue || 0;
+        const numBoxes = $boxes.shape[0];
+        util["assert"](
+          $image.rank === 4,
+          () => "Error in cropAndResize: image must be rank 4," + `but got rank ${$image.rank}.`
+        );
+        util["assert"](
+          $boxes.rank === 2 && $boxes.shape[1] === 4,
+          () =>
+            `Error in cropAndResize: boxes must be have size [${numBoxes},4] ` +
+            `but had shape ${$boxes.shape}.`
+        );
+        util["assert"](
+          $boxInd.rank === 1 && $boxInd.shape[0] === numBoxes,
+          () =>
+            `Error in cropAndResize: boxInd must be have size [${numBoxes}] ` +
+            `but had shape ${$boxes.shape}.`
+        );
+        util["assert"](
+          cropSize.length === 2,
+          () =>
+            `Error in cropAndResize: cropSize must be of length 2, but got ` +
+            `length ${cropSize.length}.`
+        );
+        util["assert"](
+          cropSize[0] >= 1 && cropSize[1] >= 1,
+          () => `cropSize must be atleast [1,1], but was ${cropSize}`
+        );
+        util["assert"](
+          method === "bilinear" || method === "nearest",
+          () => `method must be bilinear or nearest, but was ${method}`
+        );
+        const forward = (backend, save) =>
+          backend.cropAndResize($image, $boxes, $boxInd, cropSize, method, extrapolationValue);
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          forward,
+          { images: $image, boxes: $boxes, boxInd: $boxInd },
+          null /* der */,
+          "CropAndResize",
+          { method, extrapolationValue, cropSize }
+        );
+        return res;
+      }
+      const resizeBilinear = Object(operation["a" /* op */])({ resizeBilinear_ });
+      const resizeNearestNeighbor = Object(operation["a" /* op */])({ resizeNearestNeighbor_ });
+      const nonMaxSuppressionAsync = nonMaxSuppressionAsync_;
+      const nonMaxSuppressionWithScore = Object(operation["a" /* op */])({
+        nonMaxSuppressionWithScore_,
+      });
+      const nonMaxSuppressionWithScoreAsync = nonMaxSuppressionWithScoreAsync_;
+      const cropAndResize = Object(operation["a" /* op */])({ cropAndResize_ });
+      //# sourceMappingURL=image_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/fused_util.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // Whether we should call fused ops.
+      const shouldFuse = (gradientDepth, activation) => {
+        const gradientMode = gradientDepth > 0;
+        return !gradientMode || activation === "linear";
+      };
+      //# sourceMappingURL=fused_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/fused_ops.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // Returns gradient for fused activation.
+      const getFusedDyActivation = (dy, y, activation) => {
+        if (activation == null || activation === "linear") {
+          return dy;
+        }
+        if (activation === "relu") {
+          return dy.mul(y.step());
+        }
+        throw new Error(`Gradient for activation ${activation} has not been ` + `implemented yet.`);
+      };
+      // Returns gradient for fused bias.
+      const getFusedBiasGradient = (bias, dyActivation) => {
+        let res = dyActivation;
+        const reduceAxes = getReductionAxes(bias.shape, dyActivation.shape);
+        if (reduceAxes.length > 0) {
+          res = res.sum(reduceAxes);
+        }
+        return res.reshape(bias.shape);
+      };
+      const applyActivation = (x, activation, preluActivationWeights) => {
+        if (activation === "linear") {
+          return x;
+        } else if (activation === "relu") {
+          return relu(x);
+        } else if (activation === "elu") {
+          return elu(x);
+        } else if (activation === "relu6") {
+          return relu6(x);
+        } else if (activation === "prelu") {
+          return prelu(x, preluActivationWeights);
+        }
+        throw new Error(`Unknown fused activation ${activation}.`);
+      };
+      /**
+       * Computes the dot product of two matrices with optional activation and bias.
+       *
+       * ```js
+       * const a = tf.tensor2d([-1, -2], [1, 2]);
+       * const b = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       * const bias = tf.tensor2d([1, 2], [1, 2]);
+       *
+       * tf.fused.matMul({a, b, bias, activation: 'relu'}).print();
+       * ```
+       *
+       * @param obj An object with the following properties:
+       * - `a` First matrix in dot product operation.
+       * - `b` Second matrix in dot product operation.
+       * - `transposeA` If true, `a` is transposed before multiplication.
+       * - `transposeB` If true, `b` is transposed before multiplication.
+       * - `bias` Matrix to be added to the result.
+       * - `activation` Name of activation kernel (defaults to `linear`).
+       * - `preluActivationWeights` Tensor of prelu weights.
+       */
+      function fusedMatMul_({
+        a,
+        b,
+        transposeA = false,
+        transposeB = false,
+        bias,
+        activation = "linear",
+        preluActivationWeights,
+      }) {
+        if (shouldFuse(engine["a" /* ENGINE */].state.gradientDepth, activation) === false) {
+          let result = matMul(a, b, transposeA, transposeB);
+          if (bias != null) {
+            result = add(result, bias);
+          }
+          return applyActivation(result, activation, preluActivationWeights);
+        }
+        let $a = Object(tensor_util_env["a" /* convertToTensor */])(a, "a", "fused matMul");
+        let $b = Object(tensor_util_env["a" /* convertToTensor */])(b, "b", "fused matMul");
+        [$a, $b] = Object(tensor_util["makeTypesMatch"])($a, $b);
+        const innerShapeA = transposeA ? $a.shape[$a.rank - 2] : $a.shape[$a.rank - 1];
+        const innerShapeB = transposeB ? $b.shape[$b.rank - 1] : $b.shape[$b.rank - 2];
+        const outerShapeA = transposeA ? $a.shape[$a.rank - 1] : $a.shape[$a.rank - 2];
+        const outerShapeB = transposeB ? $b.shape[$b.rank - 2] : $b.shape[$b.rank - 1];
+        const outerDimsA = $a.shape.slice(0, -2);
+        const outerDimsB = $b.shape.slice(0, -2);
+        const batchDimA = util["sizeFromShape"](outerDimsA);
+        const batchDimB = util["sizeFromShape"](outerDimsB);
+        util["assert"](
+          $a.rank >= 2 && $b.rank >= 2 && $a.rank === $b.rank,
+          () =>
+            `Error in fused matMul: inputs must have the same rank of at least ` +
+            `2, got ranks ${$a.rank} and ${$b.rank}.`
+        );
+        util["assert"](
+          util["arraysEqual"](outerDimsA, outerDimsB),
+          () =>
+            `Error in fused matMul: outer dimensions (${outerDimsA}) and (` +
+            `${outerDimsB}) of Tensors with shapes ${$a.shape} and ` +
+            `${$b.shape} must match.`
+        );
+        util["assert"](
+          innerShapeA === innerShapeB,
+          () =>
+            `Error in fused matMul: inner shapes (${innerShapeA}) and (` +
+            `${innerShapeB}) of Tensors with shapes ${$a.shape} and ` +
+            `${$b.shape} and transposeA=${transposeA}` +
+            ` and transposeB=${transposeB} must match.`
+        );
+        const outShape = $a.shape.slice(0, -2).concat([outerShapeA, outerShapeB]);
+        const a3D = transposeA
+          ? $a.as3D(batchDimA, innerShapeA, outerShapeA)
+          : $a.as3D(batchDimA, outerShapeA, innerShapeA);
+        const b3D = transposeB
+          ? $b.as3D(batchDimB, outerShapeB, innerShapeB)
+          : $b.as3D(batchDimB, innerShapeB, outerShapeB);
+        let $bias;
+        if (bias != null) {
+          $bias = Object(tensor_util_env["a" /* convertToTensor */])(bias, "bias", "fused matMul");
+          [$bias] = Object(tensor_util["makeTypesMatch"])($bias, $a);
+          assertAndGetBroadcastShape(outShape, $bias.shape);
+        }
+        let $preluActivationWeights;
+        if (preluActivationWeights != null) {
+          $preluActivationWeights = Object(tensor_util_env["a" /* convertToTensor */])(
+            preluActivationWeights,
+            "prelu weights",
+            "fused matMul"
+          );
+        }
+        const grad = (dy, saved) => {
+          const [a3D, b3D, y] = saved;
+          const dyActivation = getFusedDyActivation(dy, y, activation);
+          let biasGradient = {};
+          if (bias != null) {
+            biasGradient = { bias: () => getFusedBiasGradient($bias, dyActivation) };
+          }
+          if (!transposeA && !transposeB) {
+            return Object.assign(
+              {
+                a: () => dyActivation.matMul(b3D, false, true),
+                b: () => a3D.matMul(dyActivation, true, false),
+              },
+              biasGradient
+            );
+          } else if (!transposeA && transposeB) {
+            return Object.assign(
+              {
+                a: () => dyActivation.matMul(b3D, false, false),
+                b: () => dyActivation.matMul(a3D, true, false),
+              },
+              biasGradient
+            );
+          } else if (transposeA && !transposeB) {
+            return Object.assign(
+              {
+                a: () => b3D.matMul(dyActivation, false, true),
+                b: () => a3D.matMul(dyActivation, false, false),
+              },
+              biasGradient
+            );
+          } else {
+            return Object.assign(
+              {
+                a: () => b3D.matMul(dyActivation, true, true),
+                b: () => dyActivation.matMul(a3D, true, true),
+              },
+              biasGradient
+            );
+          }
+        };
+        const inputs = { a: a3D, b: b3D };
+        if (bias != null) {
+          inputs.bias = $bias;
+        }
+        if (preluActivationWeights != null) {
+          inputs.preluActivationWeights = $preluActivationWeights;
+        }
+        const inputsToSave = [a3D, b3D];
+        const outputsToSave = [true];
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const y = backend.fusedBatchMatMul({
+              a: a3D,
+              b: b3D,
+              transposeA,
+              transposeB,
+              bias: $bias,
+              activation,
+              preluActivationWeights: $preluActivationWeights,
+            });
+            save([a3D, b3D, y]);
+            return y;
+          },
+          inputs,
+          grad,
+          "_FusedMatMul",
+          { transposeA, transposeB, activation },
+          inputsToSave,
+          outputsToSave
+        );
+        return res.reshape(outShape);
+      }
+      /**
+       * Computes a 2D convolution over the input x, optionally fused with adding a
+       * bias and applying an activation.
+       *
+       * ```js
+       * const inputDepth = 2;
+       * const inShape = [2, 2, 2, inputDepth];
+       * const outputDepth = 2;
+       * const fSize = 1;
+       * const pad = 0;
+       * const strides = 1;
+       *
+       * const x = tf.tensor4d( [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
+       * 16], inShape);
+       * const w = tf.tensor4d([-1, 1, -2, 0.5], [fSize, fSize, inputDepth,
+       * outputDepth]);
+       *
+       * tf.fused.conv2d({ x, filter: w, strides, pad, dataFormat: 'NHWC',
+       * dilations: [1, 1], bias: tf.scalar(5), activation: 'relu' }).print();
+       * ```
+       *
+       * @param obj An object with the following properties:
+       * @param x The input tensor, of rank 4 or rank 3, of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
+       * assumed.
+       * @param filter The filter, rank 4, of shape
+       *     `[filterHeight, filterWidth, inDepth, outDepth]`.
+       * @param strides The strides of the convolution: `[strideHeight,
+       * strideWidth]`.
+       * @param pad The type of padding algorithm.
+       *   - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *   - `valid` output will be smaller than input if filter is larger
+       *       than 1x1.
+       *   - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dataFormat An optional string from: "NHWC", "NCHW". Defaults to
+       *     "NHWC". Specify the data format of the input and output data. With the
+       *     default format "NHWC", the data is stored in the order of: [batch,
+       *     height, width, channels]. Only "NHWC" is currently supported.
+       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
+       *     in which we sample input values across the height and width dimensions
+       *     in atrous convolution. Defaults to `[1, 1]`. If `dilations` is a single
+       *     number, then `dilationHeight == dilationWidth`. If it is greater than
+       *     1, then all values of `strides` must be 1.
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       * @param bias Tensor to be added to the result.
+       * @param activation Name of activation kernel (defaults to `linear`) to be
+       *     applied
+       *      after biasAdd.
+       * @param preluActivationWeights Tensor of prelu weights to be applied as part
+       *     of a `prelu` activation, typically the same shape as `x`.
+       */
+      function fusedConv2d_({
+        x,
+        filter,
+        strides,
+        pad,
+        dataFormat = "NHWC",
+        dilations = [1, 1],
+        dimRoundingMode,
+        bias,
+        activation = "linear",
+        preluActivationWeights,
+      }) {
+        activation = activation || "linear";
+        if (shouldFuse(engine["a" /* ENGINE */].state.gradientDepth, activation) === false) {
+          let result = conv2d(x, filter, strides, pad, dataFormat, dilations, dimRoundingMode);
+          if (bias != null) {
+            result = add(result, bias);
+          }
+          return applyActivation(result, activation, preluActivationWeights);
+        }
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "conv2d");
+        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
+          filter,
+          "filter",
+          "conv2d"
+        );
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = $x.as4D(1, $x.shape[0], $x.shape[1], $x.shape[2]);
+        }
+        util["assert"](
+          x4D.rank === 4,
+          () => `Error in fused conv2d: input must be rank 4, but got rank ` + `${x4D.rank}.`
+        );
+        util["assert"](
+          $filter.rank === 4,
+          () => `Error in fused conv2d: filter must be rank 4, but got rank ` + `${$filter.rank}.`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in fused conv2d: pad must be an integer when using, ` +
+              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        util["assert"](
+          x4D.shape[3] === $filter.shape[2],
+          () =>
+            `Error in conv2d: depth of input (${x4D.shape[3]}) must match ` +
+            `input depth for filter ${$filter.shape[2]}.`
+        );
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in conv2D: Either strides or dilations must be 1. " +
+            `Got strides ${strides} and dilations '${dilations}'`
+        );
+        util["assert"](
+          dataFormat === "NHWC",
+          () =>
+            `Error in conv2d: got dataFormat of ${dataFormat} but only NHWC is currently supported.`
+        );
+        const convInfo = computeConv2DInfo(
+          x4D.shape,
+          $filter.shape,
+          strides,
+          dilations,
+          pad,
+          dimRoundingMode
+        );
+        let $bias;
+        if (bias != null) {
+          $bias = Object(tensor_util_env["a" /* convertToTensor */])(bias, "bias", "fused conv2d");
+          [$bias] = Object(tensor_util["makeTypesMatch"])($bias, $x);
+          assertAndGetBroadcastShape(convInfo.outShape, $bias.shape);
+        }
+        let $preluActivationWeights;
+        if (preluActivationWeights != null) {
+          $preluActivationWeights = Object(tensor_util_env["a" /* convertToTensor */])(
+            preluActivationWeights,
+            "prelu weights",
+            "fused conv2d"
+          );
+        }
+        const grad = (dy, saved) => {
+          const [$filter, x4D, y] = saved;
+          const dyActivation = getFusedDyActivation(dy, y, activation);
+          util["assert"](
+            tupleValuesAreOne(dilations),
+            () =>
+              "Error in gradient of fused conv2D: " +
+              `dilation rates greater than 1 ` +
+              `are not yet supported in gradients. Got dilations '${dilations}'`
+          );
+          let biasGradient = {};
+          if (bias != null) {
+            biasGradient = { bias: () => getFusedBiasGradient($bias, dyActivation) };
+          }
+          return Object.assign(
+            {
+              x: () => conv2DBackpropInput(x4D.shape, dyActivation, $filter, strides, pad),
+              filter: () => conv2DBackpropFilter(x4D, dyActivation, $filter.shape, strides, pad),
+            },
+            biasGradient
+          );
+        };
+        const inputs = { x: x4D, filter: $filter };
+        if (bias != null) {
+          inputs.bias = $bias;
+        }
+        if (preluActivationWeights != null) {
+          inputs.preluActivationWeights = $preluActivationWeights;
+        }
+        const inputsToSave = [$filter, x4D];
+        const outputsToSave = [true]; // Save the only output.
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.fusedConv2d({
+              input: x4D,
+              filter: $filter,
+              convInfo,
+              bias: $bias,
+              activation,
+              preluActivationWeights: $preluActivationWeights,
+            });
+            save([$filter, x4D, res]);
+            return res;
+          },
+          inputs,
+          grad,
+          "FusedConv2D",
+          { convInfo, activation },
+          inputsToSave,
+          outputsToSave
+        );
+        if (reshapedTo4D) {
+          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
+        }
+        return res;
+      }
+      /**
+       * Computes depthwise 2D convolution, optionally fused with adding a
+       * bias and applying an activation.
+       *
+       * Given a 4D `input` array and a `filter` array of shape
+       * `[filterHeight, filterWidth, inChannels, channelMultiplier]` containing
+       * `inChannels` convolutional filters of depth 1, this op applies a
+       * different filter to each input channel (expanding from 1 channel to
+       * `channelMultiplier` channels for each), then concatenates the results
+       * together. The output has `inChannels * channelMultiplier` channels.
+       *
+       * See
+       * [https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d](
+       *     https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d)
+       * for more details.
+       *
+       * @param obj An object with the following properties:
+       * @param x The input tensor, of rank 4 or rank 3, of shape
+       *     `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
+       * assumed.
+       * @param filter The filter tensor, rank 4, of shape
+       *     `[filterHeight, filterWidth, inChannels, channelMultiplier]`.
+       * @param strides The strides of the convolution: `[strideHeight,
+       * strideWidth]`. If strides is a single number, then `strideHeight ==
+       * strideWidth`.
+       * @param pad The type of padding algorithm.
+       *   - `same` and stride 1: output will be of same size as input,
+       *       regardless of filter size.
+       *   - `valid`: output will be smaller than input if filter is larger
+       *       than 1x1.
+       *   - For more info, see this guide:
+       *     [https://www.tensorflow.org/api_guides/python/nn#Convolution](
+       *          https://www.tensorflow.org/api_guides/python/nn#Convolution)
+       * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
+       *     in which we sample input values across the height and width dimensions
+       *     in atrous convolution. Defaults to `[1, 1]`. If `rate` is a single
+       *     number, then `dilationHeight == dilationWidth`. If it is greater than
+       *     1, then all values of `strides` must be 1.
+       * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
+       *     "NHWC". Specify the data format of the input and output data. With the
+       *     default format "NHWC", the data is stored in the order of: [batch,
+       *     height, width, channels]. Only "NHWC" is currently supported.
+       * @param dimRoundingMode The rounding mode used when computing output
+       *     dimensions if pad is a number. If none is provided, it will not round
+       *     and error if the output is of fractional size.
+       * @param bias Tensor to be added to the result.
+       * @param activation Name of activation kernel (defaults to `linear`).
+       * @param preluActivationWeights Tensor of prelu weights to be applied as part
+       *     of a `prelu` activation, typically the same shape as `x`.
+       */
+      function fusedDepthwiseConv2d_({
+        x,
+        filter,
+        strides,
+        pad,
+        dataFormat = "NHWC",
+        dilations = [1, 1],
+        dimRoundingMode,
+        bias,
+        activation = "linear",
+        preluActivationWeights,
+      }) {
+        if (shouldFuse(engine["a" /* ENGINE */].state.gradientDepth, activation) === false) {
+          let result = depthwiseConv2d(
+            x,
+            filter,
+            strides,
+            pad,
+            dataFormat,
+            dilations,
+            dimRoundingMode
+          );
+          if (bias != null) {
+            result = add(result, bias);
+          }
+          return applyActivation(result, activation, preluActivationWeights);
+        }
+        const $x = Object(tensor_util_env["a" /* convertToTensor */])(x, "x", "depthwiseConv2d");
+        const $filter = Object(tensor_util_env["a" /* convertToTensor */])(
+          filter,
+          "filter",
+          "depthwiseConv2d"
+        );
+        let x4D = $x;
+        let reshapedTo4D = false;
+        if ($x.rank === 3) {
+          reshapedTo4D = true;
+          x4D = $x.as4D(1, $x.shape[0], $x.shape[1], $x.shape[2]);
+        }
+        util["assert"](
+          x4D.rank === 4,
+          () =>
+            `Error in fused depthwiseConv2d: input must be rank 4, but got ` + `rank ${x4D.rank}.`
+        );
+        util["assert"](
+          $filter.rank === 4,
+          () =>
+            `Error in fused depthwiseConv2d: filter must be rank 4, ` +
+            `but got rank ${$filter.rank}.`
+        );
+        util["assert"](
+          x4D.shape[3] === $filter.shape[2],
+          () =>
+            `Error in fused depthwiseConv2d: number of input channels ` +
+            `(${x4D.shape[3]}) must match the inChannels dimension in ` +
+            `filter ${$filter.shape[2]}.`
+        );
+        if (dilations == null) {
+          dilations = [1, 1];
+        }
+        util["assert"](
+          eitherStridesOrDilationsAreOne(strides, dilations),
+          () =>
+            "Error in fused depthwiseConv2d: Either strides or dilations must " +
+            `be 1. Got strides ${strides} and dilations '${dilations}'`
+        );
+        if (dimRoundingMode != null) {
+          util["assert"](
+            util["isInt"](pad),
+            () =>
+              `Error in fused depthwiseConv2d: pad must be an integer when ` +
+              `using dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`
+          );
+        }
+        const convInfo = computeConv2DInfo(
+          x4D.shape,
+          $filter.shape,
+          strides,
+          dilations,
+          pad,
+          dimRoundingMode,
+          true /* depthwise */
+        );
+        let $bias;
+        if (bias != null) {
+          $bias = Object(tensor_util_env["a" /* convertToTensor */])(bias, "bias", "fused conv2d");
+          [$bias] = Object(tensor_util["makeTypesMatch"])($bias, $x);
+          assertAndGetBroadcastShape(convInfo.outShape, $bias.shape);
+        }
+        let $preluActivationWeights;
+        if (preluActivationWeights != null) {
+          $preluActivationWeights = Object(tensor_util_env["a" /* convertToTensor */])(
+            preluActivationWeights,
+            "prelu weights",
+            "fused depthwiseConv2d"
+          );
+        }
+        const grad = (dy, saved) => {
+          util["assert"](
+            tupleValuesAreOne(dilations),
+            () =>
+              "Error in gradient of fused depthwiseConv2d: dilation rates " +
+              `greater than 1 are not yet supported. Got dilations ` +
+              `'${dilations}'`
+          );
+          const [$filter, x4D, y] = saved;
+          const dyActivation = getFusedDyActivation(dy, y, activation);
+          let biasGradient = {};
+          if (bias != null) {
+            biasGradient = { bias: () => getFusedBiasGradient($bias, dyActivation) };
+          }
+          return Object.assign(
+            {
+              x: () =>
+                depthwiseConv2dNativeBackpropInput(x4D.shape, dyActivation, $filter, convInfo),
+              filter: () =>
+                depthwiseConv2dNativeBackpropFilter(x4D, dyActivation, $filter.shape, convInfo),
+            },
+            biasGradient
+          );
+        };
+        const inputs = { x: x4D, filter: $filter };
+        if (bias != null) {
+          inputs.bias = $bias;
+        }
+        if (preluActivationWeights != null) {
+          inputs.preluActivationWeights = $preluActivationWeights;
+        }
+        const inputsToSave = [$filter, x4D];
+        const outputsToSave = [true];
+        const res = engine["a" /* ENGINE */].runKernelFunc(
+          (backend, save) => {
+            const res = backend.fusedDepthwiseConv2D({
+              input: x4D,
+              filter: $filter,
+              convInfo,
+              bias: $bias,
+              activation,
+              preluActivationWeights: $preluActivationWeights,
+            });
+            save([$filter, x4D, res]);
+            return res;
+          },
+          inputs,
+          grad,
+          "FusedDepthwiseConv2D",
+          { convInfo, activation },
+          inputsToSave,
+          outputsToSave
+        );
+        if (reshapedTo4D) {
+          return res.as3D(res.shape[1], res.shape[2], res.shape[3]);
+        }
+        return res;
+      }
+      const fused_ops_matMul = Object(operation["a" /* op */])({ fusedMatMul_ });
+      const fused_ops_conv2d = Object(operation["a" /* op */])({ fusedConv2d_ });
+      const fused_ops_depthwiseConv2d = Object(operation["a" /* op */])({ fusedDepthwiseConv2d_ });
+      //# sourceMappingURL=fused_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/ops.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // Modularized ops.
+
+      // Second level exports.
+
+      //# sourceMappingURL=ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/optimizer.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /** @doc {heading: 'Training', subheading: 'Classes', namespace: 'train'} */
+      class optimizer_Optimizer extends Serializable {
+        /**
+         * Executes `f()` and minimizes the scalar output of `f()` by computing
+         * gradients of y with respect to the list of trainable variables provided by
+         * `varList`. If no list is provided, it defaults to all trainable variables.
+         *
+         * @param f The function to execute and whose output to minimize.
+         * @param returnCost Whether to return the scalar cost value produced by
+         * executing `f()`.
+         * @param varList An optional list of variables to update. If specified, only
+         * the trainable variables in varList will be updated by minimize. Defaults to
+         * all trainable variables.
+         */
+        /** @doc {heading: 'Training', subheading: 'Optimizers'} */
+        minimize(f, returnCost = false, varList) {
+          const { value, grads } = this.computeGradients(f, varList);
+          if (varList != null) {
+            const gradArray = varList.map((v) => ({ name: v.name, tensor: grads[v.name] }));
+            this.applyGradients(gradArray);
+          } else {
+            this.applyGradients(grads);
+          }
+          // Dispose gradients.
+          dispose(grads);
+          if (returnCost) {
+            return value;
+          } else {
+            value.dispose();
+            return null;
+          }
+        }
+        /**
+         * The number of iterations that this optimizer instance has been invoked for.
+         */
+        get iterations() {
+          if (this.iterations_ == null) {
+            this.iterations_ = 0;
+          }
+          return this.iterations_;
+        }
+        incrementIterations() {
+          this.iterations_ = this.iterations + 1;
+        }
+        /**
+         * Executes f() and computes the gradient of the scalar output of f() with
+         * respect to the list of trainable variables provided by `varList`. If no
+         * list is provided, it defaults to all trainable variables.
+         *
+         * @param f The function to execute and whose output to use for computing
+         * gradients with respect to variables.
+         * @param varList An optional list of variables to compute gradients with
+         * respect to. If specified, only the trainable variables in varList will have
+         * gradients computed with respect to. Defaults to all trainable variables.
+         */
+        computeGradients(f, varList) {
+          return variableGrads(f, varList);
+        }
+        /**
+         * Dispose the variables (if any) owned by this optimizer instance.
+         */
+        dispose() {
+          if (this.iterations_ != null) {
+            dispose(this.iterations_);
+          }
+        }
+        async saveIterations() {
+          if (this.iterations_ == null) {
+            this.iterations_ = 0;
+          }
+          return {
+            name: "iter",
+            // TODO(cais): Use 'int64' type when available.
+            tensor: Object(tensor_ops["e" /* scalar */])(this.iterations_, "int32"),
+          };
+        }
+        async getWeights() {
+          throw new Error("getWeights() is not implemented for this optimizer yet.");
+        }
+        async setWeights(weightValues) {
+          throw new Error(
+            `setWeights() is not implemented for this optimizer class ` + `${this.getClassName()}`
+          );
+        }
+        /**
+         * Extract the first element of the weight values and set it
+         * as the iterations counter variable of this instance of optimizer.
+         *
+         * @param weightValues
+         * @returns Weight values with the first element consumed and excluded.
+         */
+        async extractIterations(weightValues) {
+          this.iterations_ = (await weightValues[0].tensor.data())[0];
+          return weightValues.slice(1);
+        }
+      }
+      Object.defineProperty(optimizer_Optimizer, Symbol.hasInstance, {
+        value: (instance) => {
+          return (
+            instance.minimize != null &&
+            instance.computeGradients != null &&
+            instance.applyGradients != null
+          );
+        },
+      });
+      //# sourceMappingURL=optimizer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/adadelta_optimizer.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /** @doclink Optimizer */
+      class adadelta_optimizer_AdadeltaOptimizer extends optimizer_Optimizer {
+        constructor(learningRate, rho, epsilon = null) {
+          super();
+          this.learningRate = learningRate;
+          this.rho = rho;
+          this.epsilon = epsilon;
+          this.accumulatedGrads = [];
+          this.accumulatedUpdates = [];
+          if (epsilon == null) {
+            this.epsilon = engine["a" /* ENGINE */].backend.epsilon();
+          }
+        }
+        applyGradients(variableGradients) {
+          const variableNames = Array.isArray(variableGradients)
+            ? variableGradients.map((item) => item.name)
+            : Object.keys(variableGradients);
+          variableNames.forEach((name, i) => {
+            const value = engine["a" /* ENGINE */].registeredVariables[name];
+            const trainable = false;
+            if (this.accumulatedGrads[i] == null) {
+              this.accumulatedGrads[i] = {
+                originalName: `${name}/accum_grad`,
+                variable: tidy(() =>
+                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
+                ),
+              };
+            }
+            if (this.accumulatedUpdates[i] == null) {
+              this.accumulatedUpdates[i] = {
+                originalName: `${name}/accum_var`,
+                variable: tidy(() =>
+                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
+                ),
+              };
+            }
+            const gradient = Array.isArray(variableGradients)
+              ? variableGradients[i].tensor
+              : variableGradients[name];
+            if (gradient == null) {
+              return;
+            }
+            const accumulatedGrad = this.accumulatedGrads[i].variable;
+            const accumulatedUpdate = this.accumulatedUpdates[i].variable;
+            tidy(() => {
+              const newAccumulatedGrad = accumulatedGrad
+                .mul(this.rho)
+                .add(gradient.square().mul(1 - this.rho));
+              const updates = accumulatedUpdate
+                .add(this.epsilon)
+                .sqrt()
+                .div(accumulatedGrad.add(this.epsilon).sqrt())
+                .mul(gradient);
+              const newAccumulatedUpdate = accumulatedUpdate
+                .mul(this.rho)
+                .add(updates.square().mul(1 - this.rho));
+              accumulatedGrad.assign(newAccumulatedGrad);
+              accumulatedUpdate.assign(newAccumulatedUpdate);
+              const newValue = updates.mul(-this.learningRate).add(value);
+              value.assign(newValue);
+            });
+          });
+          this.incrementIterations();
+        }
+        dispose() {
+          if (this.accumulatedUpdates != null) {
+            dispose(this.accumulatedGrads.map((v) => v.variable));
+            dispose(this.accumulatedUpdates.map((v) => v.variable));
+          }
+        }
+        async getWeights() {
+          // Order matters for Python compatibility.
+          const variables = [...this.accumulatedGrads, ...this.accumulatedUpdates];
+          return [await this.saveIterations()].concat(
+            variables.map((v) => ({ name: v.originalName, tensor: v.variable }))
+          );
+        }
+        async setWeights(weightValues) {
+          weightValues = await this.extractIterations(weightValues);
+          const variableCount = weightValues.length / 2;
+          const trainable = false;
+          this.accumulatedGrads = weightValues.slice(0, variableCount).map((v) => ({
+            originalName: v.name,
+            variable: v.tensor.variable(trainable),
+          }));
+          this.accumulatedUpdates = weightValues
+            .slice(variableCount, variableCount * 2)
+            .map((v) => ({
+              originalName: v.name,
+              variable: v.tensor.variable(trainable),
+            }));
+        }
+        getConfig() {
+          return {
+            learningRate: this.learningRate,
+            rho: this.rho,
+            epsilon: this.epsilon,
+          };
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(config["learningRate"], config["rho"], config["epsilon"]);
+        }
+      }
+      /** @nocollapse */
+      adadelta_optimizer_AdadeltaOptimizer.className = "Adadelta"; // Name matters for Python compatibility.
+      registerClass(adadelta_optimizer_AdadeltaOptimizer);
+      //# sourceMappingURL=adadelta_optimizer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/adagrad_optimizer.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /** @doclink Optimizer */
+      class adagrad_optimizer_AdagradOptimizer extends optimizer_Optimizer {
+        constructor(learningRate, initialAccumulatorValue = 0.1) {
+          super();
+          this.learningRate = learningRate;
+          this.initialAccumulatorValue = initialAccumulatorValue;
+          this.accumulatedGrads = [];
+        }
+        applyGradients(variableGradients) {
+          const variableNames = Array.isArray(variableGradients)
+            ? variableGradients.map((item) => item.name)
+            : Object.keys(variableGradients);
+          variableNames.forEach((name, i) => {
+            const value = engine["a" /* ENGINE */].registeredVariables[name];
+            if (this.accumulatedGrads[i] == null) {
+              const trainable = false;
+              this.accumulatedGrads[i] = {
+                originalName: `${name}/accumulator`,
+                variable: tidy(() =>
+                  fill(value.shape, this.initialAccumulatorValue).variable(trainable)
+                ),
+              };
+            }
+            const gradient = Array.isArray(variableGradients)
+              ? variableGradients[i].tensor
+              : variableGradients[name];
+            if (gradient == null) {
+              return;
+            }
+            const accumulatedGrad = this.accumulatedGrads[i].variable;
+            tidy(() => {
+              const newAccumulatedGrad = accumulatedGrad.add(gradient.square());
+              accumulatedGrad.assign(newAccumulatedGrad);
+              const newValue = gradient
+                .div(newAccumulatedGrad.add(engine["a" /* ENGINE */].backend.epsilon()).sqrt())
+                .mul(-this.learningRate)
+                .add(value);
+              value.assign(newValue);
+            });
+          });
+          this.incrementIterations();
+        }
+        dispose() {
+          if (this.accumulatedGrads != null) {
+            dispose(this.accumulatedGrads.map((v) => v.variable));
+          }
+        }
+        async getWeights() {
+          // Order matters for Python compatibility.
+          return [await this.saveIterations()].concat(
+            this.accumulatedGrads.map((v) => ({ name: v.originalName, tensor: v.variable }))
+          );
+        }
+        async setWeights(weightValues) {
+          weightValues = await this.extractIterations(weightValues);
+          const trainable = false;
+          this.accumulatedGrads = weightValues.map((v) => ({
+            originalName: v.name,
+            variable: v.tensor.variable(trainable),
+          }));
+        }
+        getConfig() {
+          return {
+            learningRate: this.learningRate,
+            initialAccumulatorValue: this.initialAccumulatorValue,
+          };
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(config["learningRate"], config["initialAccumulatorValue"]);
+        }
+      }
+      /** @nocollapse */
+      adagrad_optimizer_AdagradOptimizer.className = "Adagrad"; // Note: Name matters for Python compatibility.
+      registerClass(adagrad_optimizer_AdagradOptimizer);
+      //# sourceMappingURL=adagrad_optimizer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/adam_optimizer.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class adam_optimizer_AdamOptimizer extends optimizer_Optimizer {
+        constructor(learningRate, beta1, beta2, epsilon = null) {
+          super();
+          this.learningRate = learningRate;
+          this.beta1 = beta1;
+          this.beta2 = beta2;
+          this.epsilon = epsilon;
+          this.accumulatedFirstMoment = [];
+          this.accumulatedSecondMoment = [];
+          tidy(() => {
+            // accB* will be updated by batch.
+            this.accBeta1 = Object(tensor_ops["e" /* scalar */])(beta1).variable();
+            this.accBeta2 = Object(tensor_ops["e" /* scalar */])(beta2).variable();
+          });
+          if (epsilon == null) {
+            this.epsilon = engine["a" /* ENGINE */].backend.epsilon();
+          }
+        }
+        applyGradients(variableGradients) {
+          const varNames = Array.isArray(variableGradients)
+            ? variableGradients.map((v) => v.name)
+            : Object.keys(variableGradients);
+          tidy(() => {
+            const oneMinusAccBeta1 = sub(1, this.accBeta1);
+            const oneMinusAccBeta2 = sub(1, this.accBeta2);
+            varNames.forEach((name, i) => {
+              const value = engine["a" /* ENGINE */].registeredVariables[name];
+              const trainable = false;
+              if (this.accumulatedFirstMoment[i] == null) {
+                this.accumulatedFirstMoment[i] = {
+                  originalName: `${name}/m`,
+                  variable: tidy(() =>
+                    Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
+                  ),
+                };
+              }
+              if (this.accumulatedSecondMoment[i] == null) {
+                this.accumulatedSecondMoment[i] = {
+                  originalName: `${name}/v`,
+                  variable: tidy(() =>
+                    Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
+                  ),
+                };
+              }
+              const gradient = Array.isArray(variableGradients)
+                ? variableGradients[i].tensor
+                : variableGradients[name];
+              if (gradient == null) {
+                return;
+              }
+              const firstMoment = this.accumulatedFirstMoment[i].variable;
+              const secondMoment = this.accumulatedSecondMoment[i].variable;
+              const newFirstMoment = firstMoment.mul(this.beta1).add(gradient.mul(1 - this.beta1));
+              const newSecondMoment = secondMoment
+                .mul(this.beta2)
+                .add(gradient.square().mul(1 - this.beta2));
+              const biasCorrectedFirstMoment = newFirstMoment.div(oneMinusAccBeta1);
+              const biasCorrectedSecondMoment = newSecondMoment.div(oneMinusAccBeta2);
+              firstMoment.assign(newFirstMoment);
+              secondMoment.assign(newSecondMoment);
+              const newValue = biasCorrectedFirstMoment
+                .div(biasCorrectedSecondMoment.sqrt().add(this.epsilon))
+                .mul(-this.learningRate)
+                .add(value);
+              value.assign(newValue);
+            });
+            this.accBeta1.assign(this.accBeta1.mul(this.beta1));
+            this.accBeta2.assign(this.accBeta2.mul(this.beta2));
+          });
+          this.incrementIterations();
+        }
+        dispose() {
+          this.accBeta1.dispose();
+          this.accBeta2.dispose();
+          if (this.accumulatedFirstMoment != null) {
+            dispose(this.accumulatedFirstMoment.map((v) => v.variable));
+          }
+          if (this.accumulatedSecondMoment != null) {
+            dispose(this.accumulatedSecondMoment.map((v) => v.variable));
+          }
+        }
+        async getWeights() {
+          // Order matters for Python compatibility.
+          const variables = [...this.accumulatedFirstMoment, ...this.accumulatedSecondMoment];
+          return [await this.saveIterations()].concat(
+            variables.map((v) => ({ name: v.originalName, tensor: v.variable }))
+          );
+        }
+        async setWeights(weightValues) {
+          weightValues = await this.extractIterations(weightValues);
+          tidy(() => {
+            this.accBeta1.assign(pow(this.beta1, this.iterations_ + 1));
+            this.accBeta2.assign(pow(this.beta2, this.iterations_ + 1));
+          });
+          const variableCount = weightValues.length / 2;
+          const trainable = false;
+          this.accumulatedFirstMoment = weightValues.slice(0, variableCount).map((v) => ({
+            originalName: v.name,
+            variable: v.tensor.variable(trainable),
+          }));
+          this.accumulatedSecondMoment = weightValues
+            .slice(variableCount, variableCount * 2)
+            .map((v) => ({
+              originalName: v.name,
+              variable: v.tensor.variable(trainable),
+            }));
+        }
+        getConfig() {
+          return {
+            learningRate: this.learningRate,
+            beta1: this.beta1,
+            beta2: this.beta2,
+            epsilon: this.epsilon,
+          };
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(
+            config["learningRate"],
+            config["beta1"],
+            config["beta2"],
+            config["epsilon"]
+          );
+        }
+      }
+      /** @nocollapse */
+      adam_optimizer_AdamOptimizer.className = "Adam"; // Note: Name matters for Python compatibility.
+      registerClass(adam_optimizer_AdamOptimizer);
+      //# sourceMappingURL=adam_optimizer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/adamax_optimizer.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class adamax_optimizer_AdamaxOptimizer extends optimizer_Optimizer {
+        constructor(learningRate, beta1, beta2, epsilon = null, decay = 0.0) {
+          super();
+          this.learningRate = learningRate;
+          this.beta1 = beta1;
+          this.beta2 = beta2;
+          this.epsilon = epsilon;
+          this.decay = decay;
+          this.accumulatedFirstMoment = [];
+          this.accumulatedWeightedInfNorm = [];
+          tidy(() => {
+            this.iteration = Object(tensor_ops["e" /* scalar */])(0).variable();
+            this.accBeta1 = Object(tensor_ops["e" /* scalar */])(beta1).variable();
+          });
+          if (epsilon == null) {
+            this.epsilon = engine["a" /* ENGINE */].backend.epsilon();
+          }
+        }
+        applyGradients(variableGradients) {
+          const variableNames = Array.isArray(variableGradients)
+            ? variableGradients.map((item) => item.name)
+            : Object.keys(variableGradients);
+          tidy(() => {
+            const oneMinusAccBeta1 = sub(1, this.accBeta1);
+            const lr = div(-this.learningRate, this.iteration.mul(this.decay).add(1));
+            variableNames.forEach((name, i) => {
+              const value = engine["a" /* ENGINE */].registeredVariables[name];
+              const trainable = false;
+              if (this.accumulatedFirstMoment[i] == null) {
+                this.accumulatedFirstMoment[i] = {
+                  originalName: `${name}/m`,
+                  variable: Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable),
+                };
+              }
+              if (this.accumulatedWeightedInfNorm[i] == null) {
+                this.accumulatedWeightedInfNorm[i] = {
+                  originalName: `${name}/v`,
+                  variable: Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable),
+                };
+              }
+              const gradient = Array.isArray(variableGradients)
+                ? variableGradients[i].tensor
+                : variableGradients[name];
+              if (gradient == null) {
+                return;
+              }
+              const firstMoment = this.accumulatedFirstMoment[i].variable;
+              const weightedInfNorm = this.accumulatedWeightedInfNorm[i].variable;
+              const newFirstMoment = firstMoment.mul(this.beta1).add(gradient.mul(1 - this.beta1));
+              const ut0 = weightedInfNorm.mul(this.beta2);
+              const ut1 = gradient.abs();
+              const newWeightedInfNorm = ut0.maximum(ut1);
+              firstMoment.assign(newFirstMoment);
+              weightedInfNorm.assign(newWeightedInfNorm);
+              const newValue = lr
+                .div(oneMinusAccBeta1)
+                .mul(newFirstMoment.div(newWeightedInfNorm.add(this.epsilon)))
+                .add(value);
+              value.assign(newValue);
+            });
+            this.iteration.assign(this.iteration.add(1));
+            this.accBeta1.assign(this.accBeta1.mul(this.beta1));
+          });
+          this.incrementIterations();
+        }
+        dispose() {
+          this.accBeta1.dispose();
+          this.iteration.dispose();
+          if (this.accumulatedFirstMoment != null) {
+            dispose(this.accumulatedFirstMoment.map((v) => v.variable));
+          }
+          if (this.accumulatedWeightedInfNorm != null) {
+            dispose(this.accumulatedWeightedInfNorm.map((v) => v.variable));
+          }
+        }
+        async getWeights() {
+          throw new Error("getWeights() is not implemented for Adamax yet.");
+        }
+        async setWeights(weightValues) {
+          throw new Error("setWeights() is not implemented for Adamax yet.");
+        }
+        getConfig() {
+          return {
+            learningRate: this.learningRate,
+            beta1: this.beta1,
+            beta2: this.beta2,
+            epsilon: this.epsilon,
+            decay: this.decay,
+          };
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(
+            config["learningRate"],
+            config["beta1"],
+            config["beta2"],
+            config["epsilon"],
+            config["decay"]
+          );
+        }
+      }
+      /** @nocollapse */
+      adamax_optimizer_AdamaxOptimizer.className = "Adamax"; // Note: Name matters for Python compatbility.
+      registerClass(adamax_optimizer_AdamaxOptimizer);
+      //# sourceMappingURL=adamax_optimizer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/sgd_optimizer.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /** @doclink Optimizer */
+      class sgd_optimizer_SGDOptimizer extends optimizer_Optimizer {
+        constructor(learningRate) {
+          super();
+          this.learningRate = learningRate;
+          this.setLearningRate(learningRate);
+        }
+        applyGradients(variableGradients) {
+          const varNames = Array.isArray(variableGradients)
+            ? variableGradients.map((v) => v.name)
+            : Object.keys(variableGradients);
+          varNames.forEach((name, i) => {
+            const gradient = Array.isArray(variableGradients)
+              ? variableGradients[i].tensor
+              : variableGradients[name];
+            if (gradient == null) {
+              return;
+            }
+            const value = engine["a" /* ENGINE */].registeredVariables[name];
+            tidy(() => {
+              const newValue = this.c.mul(gradient).add(value);
+              value.assign(newValue);
+            });
+          });
+          this.incrementIterations();
+        }
+        /**
+         * Sets the learning rate of the optimizer.
+         */
+        setLearningRate(learningRate) {
+          this.learningRate = learningRate;
+          if (this.c != null) {
+            this.c.dispose();
+          }
+          this.c = keep(Object(tensor_ops["e" /* scalar */])(-learningRate));
+        }
+        dispose() {
+          this.c.dispose();
+        }
+        async getWeights() {
+          return [await this.saveIterations()];
+        }
+        async setWeights(weightValues) {
+          weightValues = await this.extractIterations(weightValues);
+          if (weightValues.length !== 0) {
+            throw new Error("SGD optimizer does not have settable weights.");
+          }
+        }
+        getConfig() {
+          return { learningRate: this.learningRate };
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(config["learningRate"]);
+        }
+      }
+      /** @nocollapse */
+      sgd_optimizer_SGDOptimizer.className = "SGD"; // Note: Name matters for Python compatibility.
+      registerClass(sgd_optimizer_SGDOptimizer);
+      //# sourceMappingURL=sgd_optimizer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/momentum_optimizer.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /** @doclink Optimizer */
+      class momentum_optimizer_MomentumOptimizer extends sgd_optimizer_SGDOptimizer {
+        constructor(learningRate, momentum, useNesterov = false) {
+          super(learningRate);
+          this.learningRate = learningRate;
+          this.momentum = momentum;
+          this.useNesterov = useNesterov;
+          this.accumulations = [];
+          this.m = Object(tensor_ops["e" /* scalar */])(this.momentum);
+        }
+        applyGradients(variableGradients) {
+          const variableNames = Array.isArray(variableGradients)
+            ? variableGradients.map((item) => item.name)
+            : Object.keys(variableGradients);
+          variableNames.forEach((name, i) => {
+            const value = engine["a" /* ENGINE */].registeredVariables[name];
+            if (this.accumulations[i] == null) {
+              const trainable = false;
+              this.accumulations[i] = {
+                originalName: `${name}/momentum`,
+                variable: tidy(() =>
+                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
+                ),
+              };
+            }
+            const accumulation = this.accumulations[i].variable;
+            const gradient = Array.isArray(variableGradients)
+              ? variableGradients[i].tensor
+              : variableGradients[name];
+            if (gradient == null) {
+              return;
+            }
+            tidy(() => {
+              let newValue;
+              const newAccumulation = this.m.mul(accumulation).add(gradient);
+              if (this.useNesterov) {
+                newValue = this.c.mul(gradient.add(newAccumulation.mul(this.m))).add(value);
+              } else {
+                newValue = this.c.mul(newAccumulation).add(value);
+              }
+              accumulation.assign(newAccumulation);
+              value.assign(newValue);
+            });
+          });
+          this.incrementIterations();
+        }
+        dispose() {
+          this.m.dispose();
+          if (this.accumulations != null) {
+            dispose(this.accumulations.map((v) => v.variable));
+          }
+        }
+        /**
+         * Sets the momentum of the optimizer.
+         *
+         * @param momentum
+         */
+        setMomentum(momentum) {
+          this.momentum = momentum;
+        }
+        async getWeights() {
+          // Order matters for Python compatibility.
+          return [await this.saveIterations()].concat(
+            this.accumulations.map((v) => ({ name: v.originalName, tensor: v.variable }))
+          );
+        }
+        async setWeights(weightValues) {
+          weightValues = await this.extractIterations(weightValues);
+          const trainable = false;
+          this.accumulations = weightValues.map((v) => ({
+            originalName: v.name,
+            variable: v.tensor.variable(trainable),
+          }));
+        }
+        getConfig() {
+          return {
+            learningRate: this.learningRate,
+            momentum: this.momentum,
+            useNesterov: this.useNesterov,
+          };
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(config["learningRate"], config["momentum"], config["useNesterov"]);
+        }
+      }
+      /** @nocollapse */
+      momentum_optimizer_MomentumOptimizer.className = "Momentum"; // Name matters for Python compatibility.
+      registerClass(momentum_optimizer_MomentumOptimizer);
+      //# sourceMappingURL=momentum_optimizer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/rmsprop_optimizer.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /** @doclink Optimizer */
+      class rmsprop_optimizer_RMSPropOptimizer extends optimizer_Optimizer {
+        constructor(learningRate, decay = 0.9, momentum = 0.0, epsilon = null, centered = false) {
+          super();
+          this.learningRate = learningRate;
+          this.decay = decay;
+          this.momentum = momentum;
+          this.epsilon = epsilon;
+          this.accumulatedMeanSquares = [];
+          this.accumulatedMoments = [];
+          this.accumulatedMeanGrads = [];
+          this.centered = centered;
+          if (epsilon == null) {
+            this.epsilon = engine["a" /* ENGINE */].backend.epsilon();
+          }
+          if (learningRate == null) {
+            throw new Error(`learningRate for RMSPropOptimizer must be defined.`);
+          }
+        }
+        applyGradients(variableGradients) {
+          const variableNames = Array.isArray(variableGradients)
+            ? variableGradients.map((item) => item.name)
+            : Object.keys(variableGradients);
+          variableNames.forEach((name, i) => {
+            const value = engine["a" /* ENGINE */].registeredVariables[name];
+            const trainable = false;
+            if (this.accumulatedMeanSquares[i] == null) {
+              this.accumulatedMeanSquares[i] = {
+                originalName: `${name}/rms`,
+                variable: tidy(() =>
+                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
+                ),
+              };
+            }
+            if (this.accumulatedMoments[i] == null) {
+              this.accumulatedMoments[i] = {
+                originalName: `${name}/momentum`,
+                variable: tidy(() =>
+                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
+                ),
+              };
+            }
+            if (this.accumulatedMeanGrads[i] == null && this.centered) {
+              this.accumulatedMeanGrads[i] = {
+                originalName: `${name}/mg`,
+                variable: tidy(() =>
+                  Object(tensor_ops["o" /* zerosLike */])(value).variable(trainable)
+                ),
+              };
+            }
+            const gradient = Array.isArray(variableGradients)
+              ? variableGradients[i].tensor
+              : variableGradients[name];
+            if (gradient == null) {
+              return;
+            }
+            const accumulatedMeanSquare = this.accumulatedMeanSquares[i].variable;
+            const accumulatedMoments = this.accumulatedMoments[i].variable;
+            tidy(() => {
+              const newAccumulatedMeanSquare = accumulatedMeanSquare
+                .mul(this.decay)
+                .add(gradient.square().mul(1 - this.decay));
+              if (this.centered) {
+                const accumulatedMeanGrad = this.accumulatedMeanGrads[i].variable;
+                // Centered gradient
+                const newAccumulatedMeanGrad = accumulatedMeanGrad
+                  .mul(this.decay)
+                  .add(gradient.mul(1 - this.decay));
+                const newAccumulatedMoments = accumulatedMoments
+                  .mul(this.momentum)
+                  .add(
+                    gradient
+                      .mul(this.learningRate)
+                      .div(
+                        newAccumulatedMeanSquare
+                          .sub(newAccumulatedMeanGrad.square().add(this.epsilon))
+                          .sqrt()
+                      )
+                  );
+                accumulatedMeanSquare.assign(newAccumulatedMeanSquare);
+                accumulatedMeanGrad.assign(newAccumulatedMeanGrad);
+                accumulatedMoments.assign(newAccumulatedMoments);
+                const newValue = value.sub(newAccumulatedMoments);
+                value.assign(newValue);
+              } else {
+                // Plain gradient
+                const newAccumulatedMeanSquare = accumulatedMeanSquare
+                  .mul(this.decay)
+                  .add(gradient.square().mul(1 - this.decay));
+                const newAccumulatedMoments = accumulatedMoments
+                  .mul(this.momentum)
+                  .add(
+                    gradient
+                      .mul(this.learningRate)
+                      .div(newAccumulatedMeanSquare.add(this.epsilon).sqrt())
+                  );
+                accumulatedMeanSquare.assign(newAccumulatedMeanSquare);
+                accumulatedMoments.assign(newAccumulatedMoments);
+                const newValue = value.sub(newAccumulatedMoments);
+                value.assign(newValue);
+              }
+            });
+          });
+          this.incrementIterations();
+        }
+        dispose() {
+          if (this.accumulatedMeanSquares != null) {
+            dispose(this.accumulatedMeanSquares.map((v) => v.variable));
+          }
+          if (this.accumulatedMeanGrads != null && this.centered) {
+            dispose(this.accumulatedMeanGrads.map((v) => v.variable));
+          }
+          if (this.accumulatedMoments != null) {
+            dispose(this.accumulatedMoments.map((v) => v.variable));
+          }
+        }
+        async getWeights() {
+          // Order matters for Python compatibility.
+          const variables = [...this.accumulatedMeanSquares, ...this.accumulatedMoments];
+          if (this.centered) {
+            variables.push(...this.accumulatedMeanGrads);
+          }
+          return [await this.saveIterations()].concat(
+            variables.map((v) => ({ name: v.originalName, tensor: v.variable }))
+          );
+        }
+        async setWeights(weightValues) {
+          weightValues = await this.extractIterations(weightValues);
+          const variableCount = this.centered ? weightValues.length / 3 : weightValues.length / 2;
+          const trainable = false;
+          this.accumulatedMeanSquares = weightValues.slice(0, variableCount).map((v) => ({
+            originalName: v.name,
+            variable: v.tensor.variable(trainable),
+          }));
+          this.accumulatedMoments = weightValues
+            .slice(variableCount, variableCount * 2)
+            .map((v) => ({
+              originalName: v.name,
+              variable: v.tensor.variable(trainable),
+            }));
+          if (this.centered) {
+            this.accumulatedMeanGrads = weightValues
+              .slice(variableCount * 2, variableCount * 3)
+              .map((v) => ({
+                originalName: v.name,
+                variable: v.tensor.variable(trainable),
+              }));
+          }
+        }
+        getConfig() {
+          return {
+            learningRate: this.learningRate,
+            decay: this.decay,
+            momentum: this.momentum,
+            epsilon: this.epsilon,
+            centered: this.centered,
+          };
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(
+            config["learningRate"],
+            config["decay"],
+            config["momentum"],
+            config["epsilon"],
+            config["centered"]
+          );
+        }
+      }
+      /** @nocollapse */
+      rmsprop_optimizer_RMSPropOptimizer.className = "RMSProp"; // Note: Name matters for Python compatibility.
+      registerClass(rmsprop_optimizer_RMSPropOptimizer);
+      //# sourceMappingURL=rmsprop_optimizer.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/types.js
+      var dist_types = __webpack_require__(23);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/optimizers/optimizer_constructors.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class optimizer_constructors_OptimizerConstructors {
+        /**
+         * Constructs a `tf.SGDOptimizer` that uses stochastic gradient descent.
+         *
+         * ```js
+         * // Fit a quadratic function by learning the coefficients a, b, c.
+         * const xs = tf.tensor1d([0, 1, 2, 3]);
+         * const ys = tf.tensor1d([1.1, 5.9, 16.8, 33.9]);
+         *
+         * const a = tf.scalar(Math.random()).variable();
+         * const b = tf.scalar(Math.random()).variable();
+         * const c = tf.scalar(Math.random()).variable();
+         *
+         * // y = a * x^2 + b * x + c.
+         * const f = x => a.mul(x.square()).add(b.mul(x)).add(c);
+         * const loss = (pred, label) => pred.sub(label).square().mean();
+         *
+         * const learningRate = 0.01;
+         * const optimizer = tf.train.sgd(learningRate);
+         *
+         * // Train the model.
+         * for (let i = 0; i < 10; i++) {
+         *   optimizer.minimize(() => loss(f(xs), ys));
+         * }
+         *
+         * // Make predictions.
+         * console.log(
+         *     `a: ${a.dataSync()}, b: ${b.dataSync()}, c: ${c.dataSync()}`);
+         * const preds = f(xs).dataSync();
+         * preds.forEach((pred, i) => {
+         *   console.log(`x: ${i}, pred: ${pred}`);
+         * });
+         * ```
+         *
+         * @param learningRate The learning rate to use for the SGD algorithm.
+         */
+        /**
+         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
+         */
+        static sgd(learningRate) {
+          return new sgd_optimizer_SGDOptimizer(learningRate);
+        }
+        /**
+         * Constructs a `tf.MomentumOptimizer` that uses momentum gradient
+         * descent.
+         *
+         * See
+         * [http://proceedings.mlr.press/v28/sutskever13.pdf](
+         * http://proceedings.mlr.press/v28/sutskever13.pdf)
+         *
+         * @param learningRate The learning rate to use for the Momentum gradient
+         * descent algorithm.
+         * @param momentum The momentum to use for the momentum gradient descent
+         * algorithm.
+         */
+        /**
+         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
+         */
+        static momentum(learningRate, momentum, useNesterov = false) {
+          return new momentum_optimizer_MomentumOptimizer(learningRate, momentum, useNesterov);
+        }
+        /**
+         * Constructs a `tf.RMSPropOptimizer` that uses RMSProp gradient
+         * descent. This implementation uses plain momentum and is not centered
+         * version of RMSProp.
+         *
+         * See
+         * [http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf](
+         * http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf)
+         *
+         * @param learningRate The learning rate to use for the RMSProp gradient
+         * descent algorithm.
+         * @param decay The discounting factor for the history/coming gradient.
+         * @param momentum The momentum to use for the RMSProp gradient descent
+         * algorithm.
+         * @param epsilon Small value to avoid zero denominator.
+         * @param centered If true, gradients are normalized by the estimated
+         * variance of the gradient.
+         */
+        /**
+         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
+         */
+        static rmsprop(
+          learningRate,
+          decay = 0.9,
+          momentum = 0.0,
+          epsilon = null,
+          centered = false
+        ) {
+          return new rmsprop_optimizer_RMSPropOptimizer(
+            learningRate,
+            decay,
+            momentum,
+            epsilon,
+            centered
+          );
+        }
+        /**
+         * Constructs a `tf.AdamOptimizer` that uses the Adam algorithm.
+         * See [https://arxiv.org/abs/1412.6980](https://arxiv.org/abs/1412.6980)
+         *
+         * @param learningRate The learning rate to use for the Adam gradient
+         * descent algorithm.
+         * @param beta1 The exponential decay rate for the 1st moment estimates.
+         * @param beta2 The exponential decay rate for the 2nd moment estimates.
+         * @param epsilon A small constant for numerical stability.
+         */
+        /**
+         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
+         */
+        static adam(learningRate = 0.001, beta1 = 0.9, beta2 = 0.999, epsilon = null) {
+          return new adam_optimizer_AdamOptimizer(learningRate, beta1, beta2, epsilon);
+        }
+        /**
+         * Constructs a `tf.AdadeltaOptimizer` that uses the Adadelta algorithm.
+         * See [https://arxiv.org/abs/1212.5701](https://arxiv.org/abs/1212.5701)
+         *
+         * @param learningRate The learning rate to use for the Adadelta gradient
+         * descent algorithm.
+         * @param rho The learning rate decay over each update.
+         * @param epsilon A constant epsilon used to better condition the grad
+         * update.
+         */
+        /**
+         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
+         */
+        static adadelta(learningRate = 0.001, rho = 0.95, epsilon = null) {
+          return new adadelta_optimizer_AdadeltaOptimizer(learningRate, rho, epsilon);
+        }
+        /**
+         * Constructs a `tf.AdamaxOptimizer` that uses the Adamax algorithm.
+         * See [https://arxiv.org/abs/1412.6980](https://arxiv.org/abs/1412.6980)
+         *
+         * @param learningRate The learning rate to use for the Adamax gradient
+         * descent algorithm.
+         * @param beta1 The exponential decay rate for the 1st moment estimates.
+         * @param beta2 The exponential decay rate for the 2nd moment estimates.
+         * @param epsilon A small constant for numerical stability.
+         * @param decay The learning rate decay over each update.
+         */
+        /**
+         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
+         */
+        static adamax(
+          learningRate = 0.002,
+          beta1 = 0.9,
+          beta2 = 0.999,
+          epsilon = null,
+          decay = 0.0
+        ) {
+          return new adamax_optimizer_AdamaxOptimizer(learningRate, beta1, beta2, epsilon, decay);
+        }
+        /**
+         * Constructs a `tf.AdagradOptimizer` that uses the Adagrad algorithm.
+         * See
+         * [http://www.jmlr.org/papers/volume12/duchi11a/duchi11a.pdf](
+         * http://www.jmlr.org/papers/volume12/duchi11a/duchi11a.pdf)
+         * or
+         * [http://ruder.io/optimizing-gradient-descent/index.html#adagrad](
+         * http://ruder.io/optimizing-gradient-descent/index.html#adagrad)
+         *
+         * @param learningRate The learning rate to use for the Adagrad gradient
+         * descent algorithm.
+         * @param initialAccumulatorValue Starting value for the accumulators, must be
+         * positive.
+         */
+        /**
+         * @doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}
+         */
+        static adagrad(learningRate, initialAccumulatorValue = 0.1) {
+          return new adagrad_optimizer_AdagradOptimizer(learningRate, initialAccumulatorValue);
+        }
+      }
+      //# sourceMappingURL=optimizer_constructors.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/train.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // So typings can propagate.
+
+      // tslint:disable-next-line:no-unused-expression
+      [
+        momentum_optimizer_MomentumOptimizer,
+        sgd_optimizer_SGDOptimizer,
+        adadelta_optimizer_AdadeltaOptimizer,
+        adagrad_optimizer_AdagradOptimizer,
+        rmsprop_optimizer_RMSPropOptimizer,
+        adamax_optimizer_AdamaxOptimizer,
+        adam_optimizer_AdamOptimizer,
+      ];
+      const train = {
+        sgd: optimizer_constructors_OptimizerConstructors.sgd,
+        momentum: optimizer_constructors_OptimizerConstructors.momentum,
+        adadelta: optimizer_constructors_OptimizerConstructors.adadelta,
+        adagrad: optimizer_constructors_OptimizerConstructors.adagrad,
+        rmsprop: optimizer_constructors_OptimizerConstructors.rmsprop,
+        adamax: optimizer_constructors_OptimizerConstructors.adamax,
+        adam: optimizer_constructors_OptimizerConstructors.adam,
+      };
+      //# sourceMappingURL=train.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/browser_util.js
+      var browser_util = __webpack_require__(40);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/array_ops_util.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Gets the new shape of the input Tensor after it's been reshaped
+       * to:
+       * [blockShape[0], ..., blockShape[M-1], batch / prod(blockShape),
+       * inputShape[1], ..., inputShape[N-1]]
+       *
+       * See step 1: https://www.tensorflow.org/api_docs/python/tf/batch_to_space_nd
+       */
+      function getReshaped(inputShape, blockShape, prod, batchToSpace = true) {
+        let reshaped = [];
+        if (batchToSpace) {
+          reshaped = reshaped.concat(blockShape.slice(0));
+          reshaped.push(inputShape[0] / prod);
+          reshaped = reshaped.concat(inputShape.slice(1));
+        } else {
+          reshaped = reshaped.concat(inputShape[0]);
+          const spatialLength = blockShape.length;
+          for (let i = 0; i < spatialLength; ++i) {
+            reshaped = reshaped.concat([inputShape[i + 1] / blockShape[i], blockShape[i]]);
+          }
+          reshaped = reshaped.concat(inputShape.slice(spatialLength + 1));
+        }
+        return reshaped;
+      }
+      /**
+       * Gets the permutation that will transpose the dimensions of the
+       * reshaped tensor to shape:
+       *
+       * [batch / prod(block_shape),inputShape[1], blockShape[0], ...,
+       * inputShape[M], blockShape[M-1],inputShape[M+1], ..., inputShape[N-1]]
+       *
+       * see step 2: https://www.tensorflow.org/api_docs/python/tf/batch_to_space_nd
+       */
+      function getPermuted(reshapedRank, blockShapeRank, batchToSpace = true) {
+        const permuted = [];
+        if (batchToSpace) {
+          permuted.push(blockShapeRank);
+          for (let i = blockShapeRank + 1; i < reshapedRank; ++i) {
+            if (i <= 2 * blockShapeRank) {
+              permuted.push(i);
+              permuted.push(i - (blockShapeRank + 1));
+            } else {
+              permuted.push(i);
+            }
+          }
+        } else {
+          const permutedBeforeBatch = [];
+          const permutedAfterBatch = [];
+          for (let i = 1; i < reshapedRank; ++i) {
+            if (i >= blockShapeRank * 2 + 1 || i % 2 === 1) {
+              permutedAfterBatch.push(i);
+            } else {
+              permutedBeforeBatch.push(i);
+            }
+          }
+          permuted.push(...permutedBeforeBatch);
+          permuted.push(0);
+          permuted.push(...permutedAfterBatch);
+        }
+        return permuted;
+      }
+      /**
+       * Gets the shape of the reshaped and permuted input Tensor before any cropping
+       * is applied.  The new shape will be:
+       *
+       * [batch / prod(blockShape),inputShape[1] * blockShape[0], ...,
+       * inputShape[M] * blockShape[M-1],inputShape[M+1], ..., inputShape[N-1]]
+       *
+       * See step 3: https://www.tensorflow.org/api_docs/python/tf/batch_to_space_nd
+       */
+      function getReshapedPermuted(inputShape, blockShape, prod, batchToSpace = true) {
+        const reshapedPermuted = [];
+        if (batchToSpace) {
+          reshapedPermuted.push(inputShape[0] / prod);
+        } else {
+          reshapedPermuted.push(inputShape[0] * prod);
+        }
+        for (let i = 1; i < inputShape.length; ++i) {
+          if (i <= blockShape.length) {
+            if (batchToSpace) {
+              reshapedPermuted.push(blockShape[i - 1] * inputShape[i]);
+            } else {
+              reshapedPermuted.push(inputShape[i] / blockShape[i - 1]);
+            }
+          } else {
+            reshapedPermuted.push(inputShape[i]);
+          }
+        }
+        return reshapedPermuted;
+      }
+      /**
+       * Converts the crops argument into the beginning coordinates of a slice
+       * operation.
+       */
+      function getSliceBeginCoords(crops, blockShape) {
+        const sliceBeginCoords = [0];
+        for (let i = 0; i < blockShape; ++i) {
+          sliceBeginCoords.push(crops[i][0]);
+        }
+        return sliceBeginCoords;
+      }
+      /**
+       * Converts the crops argument into the size of a slice operation.  When
+       * combined with getSliceBeginCoords this function allows the reshaped and
+       * permuted Tensor to be cropped to its final output shape of:
+       *
+       * inputShape[1] * blockShape[0] - crops[0,0] - crops[0,1], ...,
+       * inputShape[M] * blockShape[M-1] -crops[M-1,0] -
+       * crops[M-1,1],inputShape[M+1], ..., inputShape[N-1]]
+       *
+       * See step 4: https://www.tensorflow.org/api_docs/python/tf/batch_to_space_nd
+       */
+      function getSliceSize(uncroppedShape, crops, blockShape) {
+        const sliceSize = uncroppedShape.slice(0, 1);
+        for (let i = 0; i < blockShape; ++i) {
+          sliceSize.push(uncroppedShape[i + 1] - crops[i][0] - crops[i][1]);
+        }
+        return sliceSize;
+      }
+      //# sourceMappingURL=array_ops_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/ops/erf_util.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const ERF_P = 0.3275911;
+      const ERF_A1 = 0.254829592;
+      const ERF_A2 = -0.284496736;
+      const ERF_A3 = 1.421413741;
+      const ERF_A4 = -1.453152027;
+      const ERF_A5 = 1.061405429;
+      //# sourceMappingURL=erf_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/log.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function warn(...msg) {
+        if (!Object(environment["c" /* env */])().getBool("IS_TEST")) {
+          console.warn(...msg);
+        }
+      }
+      function log_log(...msg) {
+        if (!Object(environment["c" /* env */])().getBool("IS_TEST")) {
+          console.log(...msg);
+        }
+      }
+      //# sourceMappingURL=log.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/complex_util.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * Merges real and imaginary Float32Arrays into a single complex Float32Array.
+       *
+       * The memory layout is interleaved as follows:
+       * real: [r0, r1, r2]
+       * imag: [i0, i1, i2]
+       * complex: [r0, i0, r1, i1, r2, i2]
+       *
+       * This is the inverse of splitRealAndImagArrays.
+       *
+       * @param real The real values of the complex tensor values.
+       * @param imag The imag values of the complex tensor values.
+       * @returns A complex tensor as a Float32Array with merged values.
+       */
+      function mergeRealAndImagArrays(real, imag) {
+        if (real.length !== imag.length) {
+          throw new Error(
+            `Cannot merge real and imag arrays of different lengths. real:` +
+              `${real.length}, imag: ${imag.length}.`
+          );
+        }
+        const result = new Float32Array(real.length * 2);
+        for (let i = 0; i < result.length; i += 2) {
+          result[i] = real[i / 2];
+          result[i + 1] = imag[i / 2];
+        }
+        return result;
+      }
+      /**
+       * Splits a complex Float32Array into real and imag parts.
+       *
+       * The memory layout is interleaved as follows:
+       * complex: [r0, i0, r1, i1, r2, i2]
+       * real: [r0, r1, r2]
+       * imag: [i0, i1, i2]
+       *
+       * This is the inverse of mergeRealAndImagArrays.
+       *
+       * @param complex The complex tensor values.
+       * @returns An object with real and imag Float32Array components of the complex
+       *     tensor.
+       */
+      function splitRealAndImagArrays(complex) {
+        const real = new Float32Array(complex.length / 2);
+        const imag = new Float32Array(complex.length / 2);
+        for (let i = 0; i < complex.length; i += 2) {
+          real[i / 2] = complex[i];
+          imag[i / 2] = complex[i + 1];
+        }
+        return { real, imag };
+      }
+      /**
+       * Extracts even indexed complex values in the given array.
+       * @param complex The complex tensor values
+       */
+      function complexWithEvenIndex(complex) {
+        const len = Math.ceil(complex.length / 4);
+        const real = new Float32Array(len);
+        const imag = new Float32Array(len);
+        for (let i = 0; i < complex.length; i += 4) {
+          real[Math.floor(i / 4)] = complex[i];
+          imag[Math.floor(i / 4)] = complex[i + 1];
+        }
+        return { real, imag };
+      }
+      /**
+       * Extracts odd indexed comple values in the given array.
+       * @param complex The complex tensor values
+       */
+      function complexWithOddIndex(complex) {
+        const len = Math.floor(complex.length / 4);
+        const real = new Float32Array(len);
+        const imag = new Float32Array(len);
+        for (let i = 2; i < complex.length; i += 4) {
+          real[Math.floor(i / 4)] = complex[i];
+          imag[Math.floor(i / 4)] = complex[i + 1];
+        }
+        return { real, imag };
+      }
+      /**
+       * Get the map representing a complex value in the given array.
+       * @param complex The complex tensor values.
+       * @param index An index of the target complex value.
+       */
+      function getComplexWithIndex(complex, index) {
+        const real = complex[index * 2];
+        const imag = complex[index * 2 + 1];
+        return { real, imag };
+      }
+      /**
+       * Insert a given complex value into the TypedArray.
+       * @param data The array in which the complex value is inserted.
+       * @param c The complex value to be inserted.
+       * @param index An index of the target complex value.
+       */
+      function assignToTypedArray(data, real, imag, index) {
+        data[index * 2] = real;
+        data[index * 2 + 1] = imag;
+      }
+      /**
+       * Make the list of exponent terms used by FFT.
+       */
+      function exponents(n, inverse) {
+        const real = new Float32Array(n / 2);
+        const imag = new Float32Array(n / 2);
+        for (let i = 0; i < Math.ceil(n / 2); i++) {
+          const x = (inverse ? 2 : -2) * Math.PI * (i / n);
+          real[i] = Math.cos(x);
+          imag[i] = Math.sin(x);
+        }
+        return { real, imag };
+      }
+      /**
+       * Make the exponent term used by FFT.
+       */
+      function exponent(k, n, inverse) {
+        const x = (inverse ? 2 : -2) * Math.PI * (k / n);
+        const real = Math.cos(x);
+        const imag = Math.sin(x);
+        return { real, imag };
+      }
+      //# sourceMappingURL=complex_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/backend_util.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // Utilities needed by backend consumers of tf-core.
+
+      function castTensor(x, dtype, backend) {
+        if (dtype === "complex64") {
+          if (x.dtype === "complex64") {
+            return x.clone();
+          }
+          const zerosTensor = Object(tensor_ops["n" /* zeros */])(x.shape);
+          const floatX = x.toFloat();
+          const result = backend.complex(floatX, zerosTensor);
+          zerosTensor.dispose();
+          floatX.dispose();
+          return result;
+        }
+        if (!Object(util["hasEncodingLoss"])(x.dtype, dtype)) {
+          // We don't change the underlying data, since we cast to higher
+          // precision.
+          return engine["a" /* ENGINE */].makeTensorFromDataId(x.dataId, x.shape, dtype);
+        }
+        if (x.dtype === "complex64") {
+          const real = backend.real(x);
+          const result = real.cast(dtype);
+          real.dispose();
+          return result;
+        }
+        if (dtype === "int32") {
+          return backend.int(x);
+        } else if (dtype === "bool") {
+          const zero = Object(tensor_ops["e" /* scalar */])(0, x.dtype);
+          const result = backend.notEqual(x, zero);
+          zero.dispose();
+          return result;
+        } else {
+          throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`);
+        }
+      }
+      function reshapeTensor(x, shape) {
+        return engine["a" /* ENGINE */].makeTensorFromDataId(x.dataId, shape, x.dtype);
+      }
+      function linspaceImpl(start, stop, num) {
+        const step = (stop - start) / (num - 1);
+        const values = Object(util["makeZerosTypedArray"])(num, "float32");
+        values[0] = start;
+        for (let i = 1; i < values.length; i++) {
+          values[i] = values[i - 1] + step;
+        }
+        return Object(tensor_ops["g" /* tensor1d */])(values, "float32");
+      }
+      //# sourceMappingURL=backend_util.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/device_util.js
+      var device_util = __webpack_require__(36);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/split_shared.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // TODO(annxingyuan): Use this helper in WASM Split kernel once intermediate
+      // kernels have been modularized in WebGL and CPU
+      // https://github.com/tensorflow/tfjs/issues/2822.
+      /** Shared implementation of the split kernel across WebGL and CPU. */
+      function split_shared_split(x, sizeSplits, axis) {
+        const begin = new Array(x.rank).fill(0);
+        const size = x.shape.slice();
+        return sizeSplits.map((s) => {
+          const sliceSize = [...size];
+          sliceSize[axis] = s;
+          const slice = x.slice(begin, sliceSize);
+          begin[axis] += s;
+          return slice;
+        });
+      }
+      //# sourceMappingURL=split_shared.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/tile_impl.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * An implementation of the tile kernel shared between webgl and cpu for string
+       * tensors only.
+       */
+
+      function tile_impl_tile(xBuf, reps) {
+        const newShape = new Array(xBuf.rank);
+        for (let i = 0; i < newShape.length; i++) {
+          newShape[i] = xBuf.shape[i] * reps[i];
+        }
+        const result = array_ops_buffer(newShape, xBuf.dtype);
+        for (let i = 0; i < result.values.length; ++i) {
+          const newLoc = result.indexToLoc(i);
+          const originalLoc = new Array(xBuf.rank);
+          for (let j = 0; j < originalLoc.length; j++) {
+            originalLoc[j] = newLoc[j] % xBuf.shape[j];
+          }
+          const originalIndex = xBuf.locToIndex(originalLoc);
+          result.values[i] = xBuf.values[originalIndex];
+        }
+        return result.toTensor();
+      }
+      //# sourceMappingURL=tile_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/topk_impl.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /** An implementation of the TopK kernel shared between webgl and cpu. */
+
+      function topkImpl(x, xShape, xDtype, k, sorted) {
+        // Reshape into a 2d tensor [batch, lastDim] and compute topk along lastDim.
+        const lastDim = xShape[xShape.length - 1];
+        const [batch, size] = [x.length / lastDim, lastDim];
+        const allTopKVals = Object(util["getTypedArrayFromDType"])(xDtype, batch * k);
+        const allTopKIndices = Object(util["getTypedArrayFromDType"])("int32", batch * k);
+        for (let b = 0; b < batch; b++) {
+          const offset = b * size;
+          const vals = x.subarray(offset, offset + size);
+          const valAndInd = [];
+          for (let i = 0; i < vals.length; i++) {
+            valAndInd.push({ value: vals[i], index: i });
+          }
+          valAndInd.sort((a, b) => b.value - a.value);
+          const outOffset = b * k;
+          const topKVals = allTopKVals.subarray(outOffset, outOffset + k);
+          const topKIndices = allTopKIndices.subarray(outOffset, outOffset + k);
+          for (let i = 0; i < k; i++) {
+            topKVals[i] = valAndInd[i].value;
+            topKIndices[i] = valAndInd[i].index;
+          }
+        }
+        // Reshape back to the original input shape, except that the last
+        // dimension is k.
+        const outputShape = xShape.slice();
+        outputShape[outputShape.length - 1] = k;
+        return [
+          Object(tensor_ops["f" /* tensor */])(allTopKVals, outputShape, xDtype),
+          Object(tensor_ops["f" /* tensor */])(allTopKIndices, outputShape, "int32"),
+        ];
+      }
+      //# sourceMappingURL=topk_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/kernel_impls.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      //# sourceMappingURL=kernel_impls.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/backends/backend.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const EPSILON_FLOAT32 = 1e-7;
+      const EPSILON_FLOAT16 = 1e-4;
+      /** Convenient class for storing tensor-related data. */
+      class DataStorage {
+        constructor(backend, dataMover) {
+          this.backend = backend;
+          this.dataMover = dataMover;
+          this.data = new WeakMap();
+          this.dataIdsCount = 0;
+        }
+        get(dataId) {
+          if (!this.data.has(dataId)) {
+            this.dataMover.moveData(this.backend, dataId);
+          }
+          return this.data.get(dataId);
+        }
+        set(dataId, value) {
+          this.dataIdsCount++;
+          this.data.set(dataId, value);
+        }
+        has(dataId) {
+          return this.data.has(dataId);
+        }
+        delete(dataId) {
+          this.dataIdsCount--;
+          return this.data.delete(dataId);
+        }
+        numDataIds() {
+          return this.dataIdsCount;
+        }
+      }
+      /**
+       * The interface that defines the kernels that should be implemented when
+       * adding a new backend. New backends don't need to implement every one of the
+       * methods, this can be done gradually (throw an error for unimplemented
+       * methods).
+       */
+      class KernelBackend {
+        time(f) {
+          return notYetImplemented("time");
+        }
+        read(dataId) {
+          return notYetImplemented("read");
+        }
+        readSync(dataId) {
+          return notYetImplemented("readSync");
+        }
+        numDataIds() {
+          return notYetImplemented("numDataIds");
+        }
+        disposeData(dataId) {
+          return notYetImplemented("disposeData");
+        }
+        write(values, shape, dtype) {
+          return notYetImplemented("write");
+        }
+        move(dataId, values, shape, dtype) {
+          return notYetImplemented("move");
+        }
+        memory() {
+          return notYetImplemented("memory");
+        }
+        /** Returns the highest precision for floats in bits (e.g. 16 or 32) */
+        floatPrecision() {
+          return notYetImplemented("floatPrecision");
+        }
+        /** Returns the smallest representable number.  */
+        epsilon() {
+          return this.floatPrecision() === 32 ? EPSILON_FLOAT32 : EPSILON_FLOAT16;
+        }
+        batchMatMul(a, b, transposeA, transposeB) {
+          return notYetImplemented("batchMatMul");
+        }
+        fusedBatchMatMul({
+          a,
+          b,
+          transposeA,
+          transposeB,
+          bias,
+          activation,
+          preluActivationWeights,
+        }) {
+          return notYetImplemented("fusedBatchMatMul");
+        }
+        slice(x, begin, size) {
+          return notYetImplemented("slice");
+        }
+        stridedSlice(x, begin, end, strides) {
+          return notYetImplemented("stridedSlice");
+        }
+        unstack(x, axis) {
+          return notYetImplemented("unstack");
+        }
+        reverse(a, axis) {
+          return notYetImplemented("reverse");
+        }
+        concat(tensors, axis) {
+          return notYetImplemented("concat");
+        }
+        neg(a) {
+          return notYetImplemented("neg");
+        }
+        add(a, b) {
+          return notYetImplemented("add");
+        }
+        addN(tensors) {
+          return notYetImplemented("addN");
+        }
+        subtract(a, b) {
+          return notYetImplemented("subtract");
+        }
+        multiply(a, b) {
+          return notYetImplemented("multiply");
+        }
+        realDivide(a, b) {
+          return notYetImplemented("realDivide");
+        }
+        floorDiv(a, b) {
+          return notYetImplemented("floorDiv");
+        }
+        sum(x, axes) {
+          return notYetImplemented("sum");
+        }
+        prod(x, axes) {
+          return notYetImplemented("prod");
+        }
+        unsortedSegmentSum(x, segmentIds, numSegments) {
+          return notYetImplemented("unsortedSegmentSum");
+        }
+        argMin(x, axis) {
+          return notYetImplemented("argMin");
+        }
+        argMax(x, axis) {
+          return notYetImplemented("argMax");
+        }
+        equal(a, b) {
+          return notYetImplemented("equal");
+        }
+        notEqual(a, b) {
+          return notYetImplemented("notEqual");
+        }
+        less(a, b) {
+          return notYetImplemented("less");
+        }
+        lessEqual(a, b) {
+          return notYetImplemented("lessEqual");
+        }
+        greater(a, b) {
+          return notYetImplemented("greater");
+        }
+        greaterEqual(a, b) {
+          return notYetImplemented("greaterEqual");
+        }
+        logicalNot(a) {
+          return notYetImplemented("logicalNot");
+        }
+        logicalAnd(a, b) {
+          return notYetImplemented("logicalAnd");
+        }
+        logicalOr(a, b) {
+          return notYetImplemented("logicalOr");
+        }
+        where(condition) {
+          return notYetImplemented("where");
+        }
+        select(condition, a, b) {
+          return notYetImplemented("select");
+        }
+        topk(x, k, sorted) {
+          return notYetImplemented("topk");
+        }
+        min(x, axes) {
+          return notYetImplemented("min");
+        }
+        minimum(a, b) {
+          return notYetImplemented("minimum");
+        }
+        mod(a, b) {
+          return notYetImplemented("mod");
+        }
+        max(x, axes) {
+          return notYetImplemented("max");
+        }
+        maximum(a, b) {
+          return notYetImplemented("maximum");
+        }
+        all(x, axes) {
+          return notYetImplemented("all");
+        }
+        any(x, axes) {
+          return notYetImplemented("any");
+        }
+        squaredDifference(a, b) {
+          return notYetImplemented("squaredDifference");
+        }
+        ceil(x) {
+          return notYetImplemented("ceil");
+        }
+        floor(x) {
+          return notYetImplemented("floor");
+        }
+        round(x) {
+          return notYetImplemented("round");
+        }
+        sign(x) {
+          return notYetImplemented("sign");
+        }
+        isNaN(x) {
+          return notYetImplemented("isNaN");
+        }
+        isInf(x) {
+          return notYetImplemented("isInf");
+        }
+        isFinite(x) {
+          return notYetImplemented("isFinite");
+        }
+        pow(a, b) {
+          return notYetImplemented("pow");
+        }
+        exp(x) {
+          return notYetImplemented("exp");
+        }
+        expm1(x) {
+          return notYetImplemented("expm1");
+        }
+        softmax(x, dim) {
+          return notYetImplemented("softmax");
+        }
+        log(x) {
+          return notYetImplemented("log");
+        }
+        log1p(x) {
+          return notYetImplemented("log1p");
+        }
+        sqrt(x) {
+          return notYetImplemented("sqrt");
+        }
+        rsqrt(x) {
+          return notYetImplemented("rsqrt");
+        }
+        square(x) {
+          return notYetImplemented("square");
+        }
+        reciprocal(x) {
+          return notYetImplemented("reciprocal");
+        }
+        relu(x) {
+          return notYetImplemented("relu");
+        }
+        relu6(x) {
+          return notYetImplemented("relu6");
+        }
+        prelu(x, a) {
+          return notYetImplemented("prelu");
+        }
+        elu(x) {
+          return notYetImplemented("elu");
+        }
+        eluDer(dy, y) {
+          return notYetImplemented("eluDer");
+        }
+        selu(x) {
+          return notYetImplemented("selu");
+        }
+        int(x) {
+          return notYetImplemented("int");
+        }
+        clip(x, min, max) {
+          return notYetImplemented("clip");
+        }
+        abs(x) {
+          return notYetImplemented("abs");
+        }
+        complexAbs(x) {
+          return notYetImplemented("complexAbs");
+        }
+        sigmoid(x) {
+          return notYetImplemented("sigmoid");
+        }
+        softplus(x) {
+          return notYetImplemented("softplus");
+        }
+        sin(x) {
+          return notYetImplemented("sin");
+        }
+        cos(x) {
+          return notYetImplemented("cos");
+        }
+        tan(x) {
+          return notYetImplemented("tan");
+        }
+        asin(x) {
+          return notYetImplemented("asin");
+        }
+        acos(x) {
+          return notYetImplemented("acos");
+        }
+        atan(x) {
+          return notYetImplemented("atan");
+        }
+        atan2(a, b) {
+          return notYetImplemented("atan2");
+        }
+        sinh(x) {
+          return notYetImplemented("sinh");
+        }
+        cosh(x) {
+          return notYetImplemented("cosh");
+        }
+        tanh(x) {
+          return notYetImplemented("tanh");
+        }
+        asinh(x) {
+          return notYetImplemented("asinh");
+        }
+        acosh(x) {
+          return notYetImplemented("acosh");
+        }
+        atanh(x) {
+          return notYetImplemented("atanh");
+        }
+        erf(x) {
+          return notYetImplemented("erf");
+        }
+        step(x, alpha) {
+          return notYetImplemented("step");
+        }
+        fusedConv2d({ input, filter, convInfo, bias, activation, preluActivationWeights }) {
+          return notYetImplemented("fusedConv2d");
+        }
+        conv2d(x, filter, convInfo) {
+          return notYetImplemented("conv2d");
+        }
+        conv2dDerInput(dy, filter, convInfo) {
+          return notYetImplemented("conv2dDerInput");
+        }
+        conv2dDerFilter(x, dY, convInfo) {
+          return notYetImplemented("conv2dDerFilter");
+        }
+        fusedDepthwiseConv2D({
+          input,
+          filter,
+          convInfo,
+          bias,
+          activation,
+          preluActivationWeights,
+        }) {
+          return notYetImplemented("fusedDepthwiseConv2D");
+        }
+        depthwiseConv2D(input, filter, convInfo) {
+          return notYetImplemented("depthwiseConv2D");
+        }
+        depthwiseConv2DDerInput(dy, filter, convInfo) {
+          return notYetImplemented("depthwiseConv2DDerInput");
+        }
+        depthwiseConv2DDerFilter(x, dY, convInfo) {
+          return notYetImplemented("depthwiseConv2DDerFilter");
+        }
+        conv3d(x, filter, convInfo) {
+          return notYetImplemented("conv3d");
+        }
+        conv3dDerInput(dy, filter, convInfo) {
+          return notYetImplemented("conv3dDerInput");
+        }
+        conv3dDerFilter(x, dY, convInfo) {
+          return notYetImplemented("conv3dDerFilter");
+        }
+        maxPool(x, convInfo) {
+          return notYetImplemented("maxPool");
+        }
+        maxPoolBackprop(dy, x, y, convInfo) {
+          return notYetImplemented("maxPoolBackprop");
+        }
+        avgPool(x, convInfo) {
+          return notYetImplemented("avgPool");
+        }
+        avgPoolBackprop(dy, x, convInfo) {
+          return notYetImplemented("avgPoolBackprop");
+        }
+        avgPool3d(x, convInfo) {
+          return notYetImplemented("avgPool3d");
+        }
+        avgPool3dBackprop(dy, x, convInfo) {
+          return notYetImplemented("avgPool3dBackprop");
+        }
+        maxPool3d(x, convInfo) {
+          return notYetImplemented("maxPool3d");
+        }
+        maxPool3dBackprop(dy, x, y, convInfo) {
+          return notYetImplemented("maxPool3dBackprop");
+        }
+        reshape(x, shape) {
+          return notYetImplemented("reshape");
+        }
+        cast(x, dtype) {
+          return notYetImplemented("cast");
+        }
+        tile(x, reps) {
+          return notYetImplemented("tile");
+        }
+        pad(x, paddings, constantValue) {
+          return notYetImplemented("pad");
+        }
+        transpose(x, perm) {
+          return notYetImplemented("transpose");
+        }
+        gather(x, indices, axis) {
+          return notYetImplemented("gather");
+        }
+        gatherND(x, indices) {
+          return notYetImplemented("gatherND");
+        }
+        scatterND(indices, updates, shape) {
+          return notYetImplemented("scatterND");
+        }
+        batchToSpaceND(x, blockShape, crops) {
+          return notYetImplemented("batchToSpaceND");
+        }
+        spaceToBatchND(x, blockShape, paddings) {
+          return notYetImplemented("spaceToBatchND");
+        }
+        resizeBilinear(x, newHeight, newWidth, alignCorners) {
+          return notYetImplemented("resizeBilinear");
+        }
+        resizeBilinearBackprop(dy, x, alignCorners) {
+          return notYetImplemented("resizeBilinearBackprop");
+        }
+        resizeNearestNeighbor(x, newHEight, newWidth, alignCorners) {
+          return notYetImplemented("resizeNearestNeighbor");
+        }
+        resizeNearestNeighborBackprop(dy, x, alignCorners) {
+          return notYetImplemented("resizeNearestNeighborBackprop");
+        }
+        batchNorm(x, mean, variance, offset, scale, varianceEpsilon) {
+          return notYetImplemented("batchNorm");
+        }
+        localResponseNormalization4D(x, radius, bias, alpha, beta) {
+          return notYetImplemented("localResponseNormalization4D");
+        }
+        LRNGrad(dy, inputImage, outputImage, radius, bias, alpha, beta) {
+          return notYetImplemented("LRNGrad");
+        }
+        multinomial(logits, normalized, numSamples, seed) {
+          return notYetImplemented("multinomial");
+        }
+        oneHot(indices, depth, onValue, offValue) {
+          return notYetImplemented("oneHot");
+        }
+        cumsum(x, axis, exclusive, reverse) {
+          return notYetImplemented("cumsum");
+        }
+        nonMaxSuppression(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold) {
+          return notYetImplemented("nonMaxSuppression");
+        }
+        fft(x) {
+          return notYetImplemented("fft");
+        }
+        ifft(x) {
+          return notYetImplemented("ifft");
+        }
+        complex(real, imag) {
+          return notYetImplemented("complex");
+        }
+        real(input) {
+          return notYetImplemented("real");
+        }
+        imag(input) {
+          return notYetImplemented("imag");
+        }
+        cropAndResize(image, boxes, boxIndex, cropSize, method, extrapolationValue) {
+          return notYetImplemented("cropAndResize");
+        }
+        depthToSpace(x, blockSize, dataFormat) {
+          return notYetImplemented("depthToSpace");
+        }
+        // Aligns with the "SplitV" kernel in TensorFlow.
+        split(value, sizeSplits, axis) {
+          return notYetImplemented("split");
+        }
+        sparseToDense(sparseIndices, sparseValues, outputShape, defaultValue) {
+          return notYetImplemented("sparseToDense");
+        }
+        diag(x) {
+          return notYetImplemented("diag");
+        }
+        fill(shape, value, dtype) {
+          return notYetImplemented("fill");
+        }
+        onesLike(x) {
+          return notYetImplemented("onesLike");
+        }
+        zerosLike(x) {
+          return notYetImplemented("zerosLike");
+        }
+        linspace(start, stop, num) {
+          return notYetImplemented("linspace");
+        }
+        dispose() {
+          return notYetImplemented("dispose");
+        }
+      }
+      function notYetImplemented(kernelName) {
+        throw new Error(
+          `'${kernelName}' not yet implemented or not found in the registry. ` +
+            `Did you forget to import the kernel?`
+        );
+      }
+      //# sourceMappingURL=backend.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/add.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.add = function (b) {
+        this.throwIfDisposed();
+        return add(this, b);
+      };
+      //# sourceMappingURL=add.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/atan2.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.atan2 = function (b) {
+        this.throwIfDisposed();
+        return atan2(this, b);
+      };
+      //# sourceMappingURL=atan2.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/avg_pool.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.avgPool = function (
+        filterSize,
+        strides,
+        pad,
+        dimRoundingMode
+      ) {
+        this.throwIfDisposed();
+        return avgPool(this, filterSize, strides, pad, dimRoundingMode);
+      };
+      //# sourceMappingURL=avg_pool.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/batchnorm.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.batchNorm = function (
+        mean,
+        variance,
+        offset,
+        scale,
+        varianceEpsilon
+      ) {
+        this.throwIfDisposed();
+        return batchNorm(this, mean, variance, offset, scale, varianceEpsilon);
+      };
+      //# sourceMappingURL=batchnorm.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/broadcast_to.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.broadcastTo = function (shape) {
+        this.throwIfDisposed();
+        return broadcastTo(this, shape);
+      };
+      //# sourceMappingURL=broadcast_to.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/batch_to_space_nd.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.batchToSpaceND = function (blockShape, crops) {
+        this.throwIfDisposed();
+        return batchToSpaceND(this, blockShape, crops);
+      };
+      //# sourceMappingURL=batch_to_space_nd.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/concat.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.concat = function (x, axis) {
+        this.throwIfDisposed();
+        if (x instanceof dist_tensor["a" /* Tensor */]) {
+          x = [x];
+        }
+        return concat([this, ...x], axis);
+      };
+      //# sourceMappingURL=concat.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv1d.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.conv1d = function (
+        filter,
+        stride,
+        pad,
+        dataFormat,
+        dilation,
+        dimRoundingMode
+      ) {
+        this.throwIfDisposed();
+        return conv1d(this, filter, stride, pad, dataFormat, dilation, dimRoundingMode);
+      };
+      //# sourceMappingURL=conv1d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv2d.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.conv2d = function (
+        filter,
+        strides,
+        pad,
+        dataFormat,
+        dilations,
+        dimRoundingMode
+      ) {
+        this.throwIfDisposed();
+        return conv2d(this, filter, strides, pad, dataFormat, dilations, dimRoundingMode);
+      };
+      //# sourceMappingURL=conv2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv2d_transpose.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.conv2dTranspose = function (
+        filter,
+        outputShape,
+        strides,
+        pad,
+        dimRoundingMode
+      ) {
+        this.throwIfDisposed();
+        return conv2dTranspose(this, filter, outputShape, strides, pad, dimRoundingMode);
+      };
+      //# sourceMappingURL=conv2d_transpose.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cumsum.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.cumsum = function (axis, exclusive, reverse) {
+        this.throwIfDisposed();
+        return cumsum(this, axis, exclusive, reverse);
+      };
+      //# sourceMappingURL=cumsum.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depth_to_space.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.depthToSpace = function (blockSize, dataFormat) {
+        this.throwIfDisposed();
+        return depthToSpace(this, blockSize, dataFormat);
+      };
+      //# sourceMappingURL=depth_to_space.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depthwise_conv2d.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.depthwiseConv2d = function (
+        filter,
+        strides,
+        pad,
+        dataFormat,
+        dilations,
+        dimRoundingMode
+      ) {
+        this.throwIfDisposed();
+        return depthwiseConv2d(this, filter, strides, pad, dataFormat, dilations, dimRoundingMode);
+      };
+      //# sourceMappingURL=depthwise_conv2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depthwise_conv2D_deprecated.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * @deprecated Use `depthwiseConv2d` instead.
+       */
+      dist_tensor["a" /* Tensor */].prototype.depthwiseConv2D = function (
+        filter,
+        strides,
+        pad,
+        dataFormat,
+        dilations,
+        dimRoundingMode
+      ) {
+        deprecationWarn("depthwiseConv2D is deprecated, use depthwiseConv2d instead");
+        this.throwIfDisposed();
+        return depthwiseConv2d(this, filter, strides, pad, dataFormat, dilations, dimRoundingMode);
+      };
+      //# sourceMappingURL=depthwise_conv2D_deprecated.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/div.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.div = function (b) {
+        this.throwIfDisposed();
+        return div(this, b);
+      };
+      //# sourceMappingURL=div.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/div_no_nan.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.divNoNan = function (b) {
+        this.throwIfDisposed();
+        return divNoNan(this, b);
+      };
+      //# sourceMappingURL=div_no_nan.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/dot.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.dot = function (b) {
+        this.throwIfDisposed();
+        return dot(this, b);
+      };
+      //# sourceMappingURL=dot.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/elu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.elu = function () {
+        this.throwIfDisposed();
+        return elu(this);
+      };
+      //# sourceMappingURL=elu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/equal.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.equal = function (b) {
+        this.throwIfDisposed();
+        return equal(this, b);
+      };
+      //# sourceMappingURL=equal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/floorDiv.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.floorDiv = function (b) {
+        this.throwIfDisposed();
+        return floorDiv(this, b);
+      };
+      //# sourceMappingURL=floorDiv.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/greater.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.greater = function (b) {
+        this.throwIfDisposed();
+        return greater(this, b);
+      };
+      //# sourceMappingURL=greater.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/greater_equal.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.greaterEqual = function (b) {
+        this.throwIfDisposed();
+        return greaterEqual(this, b);
+      };
+      //# sourceMappingURL=greater_equal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/leaky_relu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.leakyRelu = function (alpha) {
+        this.throwIfDisposed();
+        return leakyRelu(this, alpha);
+      };
+      //# sourceMappingURL=leaky_relu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/less.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.less = function (b) {
+        this.throwIfDisposed();
+        return less(this, b);
+      };
+      //# sourceMappingURL=less.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/less_equal.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.lessEqual = function (b) {
+        this.throwIfDisposed();
+        return lessEqual(this, b);
+      };
+      //# sourceMappingURL=less_equal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/local_response_normalization.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.localResponseNormalization = function (
+        depthRadius,
+        bias,
+        alpha,
+        beta
+      ) {
+        this.throwIfDisposed();
+        return localResponseNormalization(this, depthRadius, bias, alpha, beta);
+      };
+      //# sourceMappingURL=local_response_normalization.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mat_mul.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.matMul = function (b, transposeA, transposeB) {
+        this.throwIfDisposed();
+        return matMul(this, b, transposeA, transposeB);
+      };
+      //# sourceMappingURL=mat_mul.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/max.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.max = function (axis, keepDims) {
+        this.throwIfDisposed();
+        return max_max(this, axis, keepDims);
+      };
+      //# sourceMappingURL=max.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/max_pool.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.maxPool = function (
+        filterSize,
+        strides,
+        pad,
+        dimRoundingMode
+      ) {
+        this.throwIfDisposed();
+        return maxPool(this, filterSize, strides, pad, dimRoundingMode);
+      };
+      //# sourceMappingURL=max_pool.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/maximum.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.maximum = function (b) {
+        this.throwIfDisposed();
+        return maximum(this, b);
+      };
+      //# sourceMappingURL=maximum.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/minimum.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.minimum = function (b) {
+        this.throwIfDisposed();
+        return minimum(this, b);
+      };
+      //# sourceMappingURL=minimum.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mod.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.mod = function (b) {
+        this.throwIfDisposed();
+        return mod(this, b);
+      };
+      //# sourceMappingURL=mod.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mul.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.mul = function (b) {
+        this.throwIfDisposed();
+        return mul(this, b);
+      };
+      //# sourceMappingURL=mul.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/not_equal.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.notEqual = function (b) {
+        this.throwIfDisposed();
+        return notEqual(this, b);
+      };
+      //# sourceMappingURL=not_equal.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/one_hot.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.oneHot = function (depth, onValue = 1, offValue = 0) {
+        this.throwIfDisposed();
+        return oneHot(this, depth, onValue, offValue);
+      };
+      //# sourceMappingURL=one_hot.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pad.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.pad = function (paddings, constantValue) {
+        this.throwIfDisposed();
+        return pad_pad(this, paddings, constantValue);
+      };
+      //# sourceMappingURL=pad.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pool.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.pool = function (
+        windowShape,
+        poolingType,
+        padding,
+        dilationRate,
+        strides
+      ) {
+        this.throwIfDisposed();
+        return pool(this, windowShape, poolingType, padding, dilationRate, strides);
+      };
+      //# sourceMappingURL=pool.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pow.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.pow = function (exp) {
+        this.throwIfDisposed();
+        return pow(this, exp);
+      };
+      //# sourceMappingURL=pow.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/prelu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.prelu = function (alpha) {
+        this.throwIfDisposed();
+        return prelu(this, alpha);
+      };
+      //# sourceMappingURL=prelu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/relu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.relu = function () {
+        this.throwIfDisposed();
+        return relu(this);
+      };
+      //# sourceMappingURL=relu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/relu6.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.relu6 = function () {
+        this.throwIfDisposed();
+        return relu6(this);
+      };
+      //# sourceMappingURL=relu6.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/selu.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.selu = function () {
+        this.throwIfDisposed();
+        return selu(this);
+      };
+      //# sourceMappingURL=selu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/separable_conv2d.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.separableConv2d = function (
+        depthwiseFilter,
+        pointwiseFilter,
+        strides,
+        pad,
+        dilation,
+        dataFormat
+      ) {
+        this.throwIfDisposed();
+        return separableConv2d(
+          this,
+          depthwiseFilter,
+          pointwiseFilter,
+          strides,
+          pad,
+          dilation,
+          dataFormat
+        );
+      };
+      //# sourceMappingURL=separable_conv2d.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/split.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.split = function (numOrSizeSplits, axis) {
+        this.throwIfDisposed();
+        return split(this, numOrSizeSplits, axis);
+      };
+      //# sourceMappingURL=split.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/squared_difference.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.squaredDifference = function (b) {
+        this.throwIfDisposed();
+        return squaredDifference(this, b);
+      };
+      //# sourceMappingURL=squared_difference.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/space_to_batch_nd.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.spaceToBatchND = function (blockShape, paddings) {
+        this.throwIfDisposed();
+        return spaceToBatchND(this, blockShape, paddings);
+      };
+      //# sourceMappingURL=space_to_batch_nd.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sub.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.sub = function (b) {
+        this.throwIfDisposed();
+        return sub(this, b);
+      };
+      //# sourceMappingURL=sub.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/tile.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.tile = function (reps) {
+        this.throwIfDisposed();
+        return tile(this, reps);
+      };
+      //# sourceMappingURL=tile.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/transpose.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      dist_tensor["a" /* Tensor */].prototype.transpose = function (perm) {
+        this.throwIfDisposed();
+        return transpose(this, perm);
+      };
+      //# sourceMappingURL=transpose.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/register_all_chained_ops.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      //# sourceMappingURL=register_all_chained_ops.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * @fileoverview
+       * @suppress {partialAlias} Optimization disabled due to passing the module
+       * object into a function below:
+       *
+       *   import * as ops from './ops/ops';
+       *   setOpHandler(ops);
+       */
+      // Engine is the global singleton that needs to be initialized before the rest
+      // of the app.
+
+      // Register backend-agnostic flags.
+
+      // Register all the gradients.
+
+      // Serialization.
+
+      // Optimizers.
+
+      // Top-level method exports.
+
+      // Second level exports.
+
+      // Backend specific.
+
+      Object(dist_tensor["e" /* setOpHandler */])(ops_namespaceObject);
+      // Export all kernel names / info.
+
+      // Import all op chainers and add type info to Tensor.
+
+      //# sourceMappingURL=index.js.map
+
+      /***/
+    },
+    /* 1 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "shuffle",
+        function () {
+          return shuffle;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "clamp",
+        function () {
+          return clamp;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "nearestLargerEven",
+        function () {
+          return nearestLargerEven;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "sum", function () {
+        return sum;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "randUniform",
+        function () {
+          return randUniform;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "distSquared",
+        function () {
+          return distSquared;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "assert",
+        function () {
+          return assert;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "assertShapesMatch",
+        function () {
+          return assertShapesMatch;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "assertNonNull",
+        function () {
+          return assertNonNull;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "flatten",
+        function () {
+          return flatten;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "sizeFromShape",
+        function () {
+          return sizeFromShape;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isScalarShape",
+        function () {
+          return isScalarShape;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "arraysEqual",
+        function () {
+          return arraysEqual;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isInt",
+        function () {
+          return isInt;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "tanh",
+        function () {
+          return tanh;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "sizeToSquarishShape",
+        function () {
+          return sizeToSquarishShape;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "createShuffledIndices",
+        function () {
+          return createShuffledIndices;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "rightPad",
+        function () {
+          return rightPad;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "repeatedTry",
+        function () {
+          return repeatedTry;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "inferFromImplicitShape",
+        function () {
+          return inferFromImplicitShape;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "parseAxisParam",
+        function () {
+          return parseAxisParam;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "squeezeShape",
+        function () {
+          return squeezeShape;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "getTypedArrayFromDType",
+        function () {
+          return getTypedArrayFromDType;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "getArrayFromDType",
+        function () {
+          return getArrayFromDType;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "checkConversionForErrors",
+        function () {
+          return checkConversionForErrors;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isValidDtype",
+        function () {
+          return isValidDtype;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "hasEncodingLoss",
+        function () {
+          return hasEncodingLoss;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isTypedArray",
+        function () {
+          return isTypedArray;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "bytesPerElement",
+        function () {
+          return bytesPerElement;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "bytesFromStringArray",
+        function () {
+          return bytesFromStringArray;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isString",
+        function () {
+          return isString;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isBoolean",
+        function () {
+          return isBoolean;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isNumber",
+        function () {
+          return isNumber;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "inferDtype",
+        function () {
+          return inferDtype;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isFunction",
+        function () {
+          return isFunction;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "nearestDivisor",
+        function () {
+          return nearestDivisor;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "computeStrides",
+        function () {
+          return computeStrides;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "toTypedArray",
+        function () {
+          return toTypedArray;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "toNestedArray",
+        function () {
+          return toNestedArray;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "makeOnesTypedArray",
+        function () {
+          return makeOnesTypedArray;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "makeZerosTypedArray",
+        function () {
+          return makeZerosTypedArray;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "now", function () {
+        return now;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "assertNonNegativeIntegerDimensions",
+        function () {
+          return assertNonNegativeIntegerDimensions;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "fetch",
+        function () {
+          return fetch;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "encodeString",
+        function () {
+          return encodeString;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "decodeString",
+        function () {
+          return decodeString;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "locToIndex",
+        function () {
+          return locToIndex;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "indexToLoc",
+        function () {
+          return indexToLoc;
+        }
+      );
+      /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(10);
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Shuffles the array in-place using Fisher-Yates algorithm.
+       *
+       * ```js
+       * const a = [1, 2, 3, 4, 5];
+       * tf.util.shuffle(a);
+       * console.log(a);
+       * ```
+       *
+       * @param array The array to shuffle in-place.
+       */
+      /** @doc {heading: 'Util', namespace: 'util'} */
+      // tslint:disable-next-line:no-any
+      function shuffle(array) {
+        let counter = array.length;
+        let temp = 0;
+        let index = 0;
+        // While there are elements in the array
+        while (counter > 0) {
+          // Pick a random index
+          index = (Math.random() * counter) | 0;
+          // Decrease counter by 1
+          counter--;
+          // And swap the last element with it
+          temp = array[counter];
+          array[counter] = array[index];
+          array[index] = temp;
+        }
+      }
+      /** Clamps a value to a specified range. */
+      function clamp(min, x, max) {
+        return Math.max(min, Math.min(x, max));
+      }
+      function nearestLargerEven(val) {
+        return val % 2 === 0 ? val : val + 1;
+      }
+      function sum(arr) {
+        let sum = 0;
+        for (let i = 0; i < arr.length; i++) {
+          sum += arr[i];
+        }
+        return sum;
+      }
+      /**
+       * Returns a sample from a uniform [a, b) distribution.
+       *
+       * @param a The minimum support (inclusive).
+       * @param b The maximum support (exclusive).
+       * @return A pseudorandom number on the half-open interval [a,b).
+       */
+      function randUniform(a, b) {
+        const r = Math.random();
+        return b * r + (1 - r) * a;
+      }
+      /** Returns the squared Euclidean distance between two vectors. */
+      function distSquared(a, b) {
+        let result = 0;
+        for (let i = 0; i < a.length; i++) {
+          const diff = Number(a[i]) - Number(b[i]);
+          result += diff * diff;
+        }
+        return result;
+      }
+      /**
+       * Asserts that the expression is true. Otherwise throws an error with the
+       * provided message.
+       *
+       * ```js
+       * const x = 2;
+       * tf.util.assert(x === 2, 'x is not 2');
+       * ```
+       *
+       * @param expr The expression to assert (as a boolean).
+       * @param msg A function that returns the message to report when throwing an
+       *     error. We use a function for performance reasons.
+       */
+      /** @doc {heading: 'Util', namespace: 'util'} */
+      function assert(expr, msg) {
+        if (!expr) {
+          throw new Error(typeof msg === "string" ? msg : msg());
+        }
+      }
+      function assertShapesMatch(shapeA, shapeB, errorMessagePrefix = "") {
+        assert(
+          arraysEqual(shapeA, shapeB),
+          () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`
+        );
+      }
+      function assertNonNull(a) {
+        assert(a != null, () => `The input to the tensor constructor must be a non-null value.`);
+      }
+      // NOTE: We explicitly type out what T extends instead of any so that
+      // util.flatten on a nested array of number doesn't try to infer T as a
+      // number[][], causing us to explicitly type util.flatten<number>().
+      /**
+       *  Flattens an arbitrarily nested array.
+       *
+       * ```js
+       * const a = [[1, 2], [3, 4], [5, [6, [7]]]];
+       * const flat = tf.util.flatten(a);
+       * console.log(flat);
+       * ```
+       *
+       *  @param arr The nested array to flatten.
+       *  @param result The destination array which holds the elements.
+       *  @param skipTypedArray If true, avoids flattening the typed arrays. Defaults
+       *      to false.
+       */
+      /** @doc {heading: 'Util', namespace: 'util'} */
+      function flatten(arr, result = [], skipTypedArray = false) {
+        if (result == null) {
+          result = [];
+        }
+        if (Array.isArray(arr) || (isTypedArray(arr) && !skipTypedArray)) {
+          for (let i = 0; i < arr.length; ++i) {
+            flatten(arr[i], result, skipTypedArray);
+          }
+        } else {
+          result.push(arr);
+        }
+        return result;
+      }
+      /**
+       * Returns the size (number of elements) of the tensor given its shape.
+       *
+       * ```js
+       * const shape = [3, 4, 2];
+       * const size = tf.util.sizeFromShape(shape);
+       * console.log(size);
+       * ```
+       */
+      /** @doc {heading: 'Util', namespace: 'util'} */
+      function sizeFromShape(shape) {
+        if (shape.length === 0) {
+          // Scalar.
+          return 1;
+        }
+        let size = shape[0];
+        for (let i = 1; i < shape.length; i++) {
+          size *= shape[i];
+        }
+        return size;
+      }
+      function isScalarShape(shape) {
+        return shape.length === 0;
+      }
+      function arraysEqual(n1, n2) {
+        if (n1 === n2) {
+          return true;
+        }
+        if (n1 == null || n2 == null) {
+          return false;
+        }
+        if (n1.length !== n2.length) {
+          return false;
+        }
+        for (let i = 0; i < n1.length; i++) {
+          if (n1[i] !== n2[i]) {
+            return false;
+          }
+        }
+        return true;
+      }
+      function isInt(a) {
+        return a % 1 === 0;
+      }
+      function tanh(x) {
+        // tslint:disable-next-line:no-any
+        if (Math.tanh != null) {
+          // tslint:disable-next-line:no-any
+          return Math.tanh(x);
+        }
+        if (x === Infinity) {
+          return 1;
+        } else if (x === -Infinity) {
+          return -1;
+        } else {
+          const e2x = Math.exp(2 * x);
+          return (e2x - 1) / (e2x + 1);
+        }
+      }
+      function sizeToSquarishShape(size) {
+        const width = Math.ceil(Math.sqrt(size));
+        return [width, Math.ceil(size / width)];
+      }
+      /**
+       * Creates a new array with randomized indicies to a given quantity.
+       *
+       * ```js
+       * const randomTen = tf.util.createShuffledIndices(10);
+       * console.log(randomTen);
+       * ```
+       *
+       * @param number Quantity of how many shuffled indicies to create.
+       */
+      /** @doc {heading: 'Util', namespace: 'util'} */
+      function createShuffledIndices(n) {
+        const shuffledIndices = new Uint32Array(n);
+        for (let i = 0; i < n; ++i) {
+          shuffledIndices[i] = i;
+        }
+        shuffle(shuffledIndices);
+        return shuffledIndices;
+      }
+      function rightPad(a, size) {
+        if (size <= a.length) {
+          return a;
+        }
+        return a + " ".repeat(size - a.length);
+      }
+      function repeatedTry(checkFn, delayFn = (counter) => 0, maxCounter) {
+        return new Promise((resolve, reject) => {
+          let tryCount = 0;
+          const tryFn = () => {
+            if (checkFn()) {
+              resolve();
+              return;
+            }
+            tryCount++;
+            const nextBackoff = delayFn(tryCount);
+            if (maxCounter != null && tryCount >= maxCounter) {
+              reject();
+              return;
+            }
+            setTimeout(tryFn, nextBackoff);
+          };
+          tryFn();
+        });
+      }
+      /**
+       * Given the full size of the array and a shape that may contain -1 as the
+       * implicit dimension, returns the inferred shape where -1 is replaced.
+       * E.g. For shape=[2, -1, 3] and size=24, it will return [2, 4, 3].
+       *
+       * @param shape The shape, which may contain -1 in some dimension.
+       * @param size The full size (number of elements) of the array.
+       * @return The inferred shape where -1 is replaced with the inferred size.
+       */
+      function inferFromImplicitShape(shape, size) {
+        let shapeProd = 1;
+        let implicitIdx = -1;
+        for (let i = 0; i < shape.length; ++i) {
+          if (shape[i] >= 0) {
+            shapeProd *= shape[i];
+          } else if (shape[i] === -1) {
+            if (implicitIdx !== -1) {
+              throw Error(
+                `Shapes can only have 1 implicit size. ` +
+                  `Found -1 at dim ${implicitIdx} and dim ${i}`
+              );
+            }
+            implicitIdx = i;
+          } else if (shape[i] < 0) {
+            throw Error(`Shapes can not be < 0. Found ${shape[i]} at dim ${i}`);
+          }
+        }
+        if (implicitIdx === -1) {
+          if (size > 0 && size !== shapeProd) {
+            throw Error(`Size(${size}) must match the product of shape ${shape}`);
+          }
+          return shape;
+        }
+        if (shapeProd === 0) {
+          throw Error(`Cannot infer the missing size in [${shape}] when ` + `there are 0 elements`);
+        }
+        if (size % shapeProd !== 0) {
+          throw Error(
+            `The implicit shape can't be a fractional number. ` + `Got ${size} / ${shapeProd}`
+          );
+        }
+        const newShape = shape.slice();
+        newShape[implicitIdx] = size / shapeProd;
+        return newShape;
+      }
+      function parseAxisParam(axis, shape) {
+        const rank = shape.length;
+        // Normalize input
+        axis = axis == null ? shape.map((s, i) => i) : [].concat(axis);
+        // Check for valid range
+        assert(
+          axis.every((ax) => ax >= -rank && ax < rank),
+          () =>
+            `All values in axis param must be in range [-${rank}, ${rank}) but ` +
+            `got axis ${axis}`
+        );
+        // Check for only integers
+        assert(
+          axis.every((ax) => isInt(ax)),
+          () => `All values in axis param must be integers but ` + `got axis ${axis}`
+        );
+        // Handle negative axis.
+        return axis.map((a) => (a < 0 ? rank + a : a));
+      }
+      /** Reduces the shape by removing all dimensions of shape 1. */
+      function squeezeShape(shape, axis) {
+        const newShape = [];
+        const keptDims = [];
+        const isEmptyArray = axis != null && Array.isArray(axis) && axis.length === 0;
+        const axes = axis == null || isEmptyArray ? null : parseAxisParam(axis, shape).sort();
+        let j = 0;
+        for (let i = 0; i < shape.length; ++i) {
+          if (axes != null) {
+            if (axes[j] === i && shape[i] !== 1) {
+              throw new Error(`Can't squeeze axis ${i} since its dim '${shape[i]}' is not 1`);
+            }
+            if ((axes[j] == null || axes[j] > i) && shape[i] === 1) {
+              newShape.push(shape[i]);
+              keptDims.push(i);
+            }
+            if (axes[j] <= i) {
+              j++;
+            }
+          }
+          if (shape[i] !== 1) {
+            newShape.push(shape[i]);
+            keptDims.push(i);
+          }
+        }
+        return { newShape, keptDims };
+      }
+      function getTypedArrayFromDType(dtype, size) {
+        let values = null;
+        if (dtype == null || dtype === "float32") {
+          values = new Float32Array(size);
+        } else if (dtype === "int32") {
+          values = new Int32Array(size);
+        } else if (dtype === "bool") {
+          values = new Uint8Array(size);
+        } else {
+          throw new Error(`Unknown data type ${dtype}`);
+        }
+        return values;
+      }
+      function getArrayFromDType(dtype, size) {
+        let values = null;
+        if (dtype == null || dtype === "float32") {
+          values = new Float32Array(size);
+        } else if (dtype === "int32") {
+          values = new Int32Array(size);
+        } else if (dtype === "bool") {
+          values = new Uint8Array(size);
+        } else if (dtype === "string") {
+          values = new Array(size);
+        } else {
+          throw new Error(`Unknown data type ${dtype}`);
+        }
+        return values;
+      }
+      function checkConversionForErrors(vals, dtype) {
+        for (let i = 0; i < vals.length; i++) {
+          const num = vals[i];
+          if (isNaN(num) || !isFinite(num)) {
+            throw Error(`A tensor of type ${dtype} being uploaded contains ${num}.`);
+          }
+        }
+      }
+      /** Returns true if the dtype is valid. */
+      function isValidDtype(dtype) {
+        return (
+          dtype === "bool" ||
+          dtype === "complex64" ||
+          dtype === "float32" ||
+          dtype === "int32" ||
+          dtype === "string"
+        );
+      }
+      /**
+       * Returns true if the new type can't encode the old type without loss of
+       * precision.
+       */
+      function hasEncodingLoss(oldType, newType) {
+        if (newType === "complex64") {
+          return false;
+        }
+        if (newType === "float32" && oldType !== "complex64") {
+          return false;
+        }
+        if (newType === "int32" && oldType !== "float32" && oldType !== "complex64") {
+          return false;
+        }
+        if (newType === "bool" && oldType === "bool") {
+          return false;
+        }
+        return true;
+      }
+      function isTypedArray(a) {
+        return a instanceof Float32Array || a instanceof Int32Array || a instanceof Uint8Array;
+      }
+      function bytesPerElement(dtype) {
+        if (dtype === "float32" || dtype === "int32") {
+          return 4;
+        } else if (dtype === "complex64") {
+          return 8;
+        } else if (dtype === "bool") {
+          return 1;
+        } else {
+          throw new Error(`Unknown dtype ${dtype}`);
+        }
+      }
+      /**
+       * Returns the approximate number of bytes allocated in the string array - 2
+       * bytes per character. Computing the exact bytes for a native string in JS is
+       * not possible since it depends on the encoding of the html page that serves
+       * the website.
+       */
+      function bytesFromStringArray(arr) {
+        if (arr == null) {
+          return 0;
+        }
+        let bytes = 0;
+        arr.forEach((x) => (bytes += x.length));
+        return bytes;
+      }
+      /** Returns true if the value is a string. */
+      function isString(value) {
+        return typeof value === "string" || value instanceof String;
+      }
+      function isBoolean(value) {
+        return typeof value === "boolean";
+      }
+      function isNumber(value) {
+        return typeof value === "number";
+      }
+      function inferDtype(values) {
+        if (Array.isArray(values)) {
+          return inferDtype(values[0]);
+        }
+        if (values instanceof Float32Array) {
+          return "float32";
+        } else if (values instanceof Int32Array || values instanceof Uint8Array) {
+          return "int32";
+        } else if (isNumber(values)) {
+          return "float32";
+        } else if (isString(values)) {
+          return "string";
+        } else if (isBoolean(values)) {
+          return "bool";
+        }
+        return "float32";
+      }
+      function isFunction(f) {
+        return !!(f && f.constructor && f.call && f.apply);
+      }
+      function nearestDivisor(size, start) {
+        for (let i = start; i < size; ++i) {
+          if (size % i === 0) {
+            return i;
+          }
+        }
+        return size;
+      }
+      function computeStrides(shape) {
+        const rank = shape.length;
+        if (rank < 2) {
+          return [];
+        }
+        // Last dimension has implicit stride of 1, thus having D-1 (instead of D)
+        // strides.
+        const strides = new Array(rank - 1);
+        strides[rank - 2] = shape[rank - 1];
+        for (let i = rank - 3; i >= 0; --i) {
+          strides[i] = strides[i + 1] * shape[i + 1];
+        }
+        return strides;
+      }
+      function toTypedArray(a, dtype, debugMode) {
+        if (dtype === "string") {
+          throw new Error("Cannot convert a string[] to a TypedArray");
+        }
+        if (Array.isArray(a)) {
+          a = flatten(a);
+        }
+        if (debugMode) {
+          checkConversionForErrors(a, dtype);
+        }
+        if (noConversionNeeded(a, dtype)) {
+          return a;
+        }
+        if (dtype == null || dtype === "float32" || dtype === "complex64") {
+          return new Float32Array(a);
+        } else if (dtype === "int32") {
+          return new Int32Array(a);
+        } else if (dtype === "bool") {
+          const bool = new Uint8Array(a.length);
+          for (let i = 0; i < bool.length; ++i) {
+            if (Math.round(a[i]) !== 0) {
+              bool[i] = 1;
+            }
+          }
+          return bool;
+        } else {
+          throw new Error(`Unknown data type ${dtype}`);
+        }
+      }
+      function createNestedArray(offset, shape, a) {
+        const ret = new Array();
+        if (shape.length === 1) {
+          const d = shape[0];
+          for (let i = 0; i < d; i++) {
+            ret[i] = a[offset + i];
+          }
+        } else {
+          const d = shape[0];
+          const rest = shape.slice(1);
+          const len = rest.reduce((acc, c) => acc * c);
+          for (let i = 0; i < d; i++) {
+            ret[i] = createNestedArray(offset + i * len, rest, a);
+          }
+        }
+        return ret;
+      }
+      // Provide a nested array of TypedArray in given shape.
+      function toNestedArray(shape, a) {
+        if (shape.length === 0) {
+          // Scalar type should return a single number.
+          return a[0];
+        }
+        const size = shape.reduce((acc, c) => acc * c);
+        if (size === 0) {
+          // A tensor with shape zero should be turned into empty list.
+          return [];
+        }
+        if (size !== a.length) {
+          throw new Error(`[${shape}] does not match the input size.`);
+        }
+        return createNestedArray(0, shape, a);
+      }
+      function noConversionNeeded(a, dtype) {
+        return (
+          (a instanceof Float32Array && dtype === "float32") ||
+          (a instanceof Int32Array && dtype === "int32") ||
+          (a instanceof Uint8Array && dtype === "bool")
+        );
+      }
+      function makeOnesTypedArray(size, dtype) {
+        const array = makeZerosTypedArray(size, dtype);
+        for (let i = 0; i < array.length; i++) {
+          array[i] = 1;
+        }
+        return array;
+      }
+      function makeZerosTypedArray(size, dtype) {
+        if (dtype == null || dtype === "float32" || dtype === "complex64") {
+          return new Float32Array(size);
+        } else if (dtype === "int32") {
+          return new Int32Array(size);
+        } else if (dtype === "bool") {
+          return new Uint8Array(size);
+        } else {
+          throw new Error(`Unknown data type ${dtype}`);
+        }
+      }
+      /**
+       * Returns the current high-resolution time in milliseconds relative to an
+       * arbitrary time in the past. It works across different platforms (node.js,
+       * browsers).
+       *
+       * ```js
+       * console.log(tf.util.now());
+       * ```
+       */
+      /** @doc {heading: 'Util', namespace: 'util'} */
+      function now() {
+        return Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().platform.now();
+      }
+      function assertNonNegativeIntegerDimensions(shape) {
+        shape.forEach((dimSize) => {
+          assert(
+            Number.isInteger(dimSize) && dimSize >= 0,
+            () =>
+              `Tensor must have a shape comprised of positive integers but got ` +
+              `shape [${shape}].`
+          );
+        });
+      }
+      /**
+       * Returns a platform-specific implementation of
+       * [`fetch`](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API).
+       *
+       * If `fetch` is defined on the global object (`window`, `process`, etc.),
+       * `tf.util.fetch` returns that function.
+       *
+       * If not, `tf.util.fetch` returns a platform-specific solution.
+       *
+       * ```js
+       * const resource = await tf.util.fetch('https://unpkg.com/@tensorflow/tfjs');
+       * // handle response
+       * ```
+       */
+      /** @doc {heading: 'Util'} */
+      function fetch(path, requestInits) {
+        return Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().platform.fetch(
+          path,
+          requestInits
+        );
+      }
+      /**
+       * Encodes the provided string into bytes using the provided encoding scheme.
+       *
+       * @param s The string to encode.
+       * @param encoding The encoding scheme. Defaults to utf-8.
+       *
+       */
+      /** @doc {heading: 'Util'} */
+      function encodeString(s, encoding = "utf-8") {
+        encoding = encoding || "utf-8";
+        return Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().platform.encode(
+          s,
+          encoding
+        );
+      }
+      /**
+       * Decodes the provided bytes into a string using the provided encoding scheme.
+       * @param bytes The bytes to decode.
+       *
+       * @param encoding The encoding scheme. Defaults to utf-8.
+       */
+      /** @doc {heading: 'Util'} */
+      function decodeString(bytes, encoding = "utf-8") {
+        encoding = encoding || "utf-8";
+        return Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().platform.decode(
+          bytes,
+          encoding
+        );
+      }
+      /**
+       * Computes flat index for a given location (multidimentionsal index) in a
+       * Tensor/multidimensional array.
+       *
+       * @param locs Location in the tensor.
+       * @param rank Rank of the tensor.
+       * @param strides Tensor strides.
+       */
+      function locToIndex(locs, rank, strides) {
+        if (rank === 0) {
+          return 0;
+        } else if (rank === 1) {
+          return locs[0];
+        }
+        let index = locs[locs.length - 1];
+        for (let i = 0; i < locs.length - 1; ++i) {
+          index += strides[i] * locs[i];
+        }
+        return index;
+      }
+      /**
+       * Computes the location (multidimensional index) in a tensor/multidimentional
+       * array for a given flat index.
+       *
+       * @param index Index in flat array.
+       * @param rank Rank of tensor.
+       * @param strides Strides of tensor.
+       */
+      function indexToLoc(index, rank, strides) {
+        if (rank === 0) {
+          return [];
+        } else if (rank === 1) {
+          return [index];
+        }
+        const locs = new Array(rank);
+        for (let i = 0; i < locs.length - 1; ++i) {
+          locs[i] = Math.floor(index / strides[i]);
+          index -= locs[i] * strides[i];
+        }
+        locs[locs.length - 1] = index;
+        return locs;
+      }
+      //# sourceMappingURL=util.js.map
+
+      /***/
+    },
+    /* 2 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return getParamValue;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return getTensor;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
+        return getTensorsForCurrentContenxt;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return getNodeNameAndIndex;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
+        return parseNodeName;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
+        return split;
+      });
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      function getParamValue(paramName, node, tensorMap, context) {
+        const inputParam = node.inputParams[paramName];
+        if (inputParam && inputParam.inputIndexStart !== undefined) {
+          const start = inputParam.inputIndexStart;
+          const end =
+            inputParam.inputIndexEnd === 0
+              ? undefined
+              : inputParam.inputIndexEnd === undefined
+              ? start + 1
+              : inputParam.inputIndexEnd;
+          if (inputParam.type === "tensor") {
+            return getTensor(node.inputNames[inputParam.inputIndexStart], tensorMap, context);
+          }
+          if (inputParam.type === "tensors") {
+            const inputs = node.inputNames.slice(start, end);
+            return inputs.map((name) => getTensor(name, tensorMap, context));
+          }
+          const data = Array.prototype.slice.call(
+            getTensor(node.inputNames.slice(start)[0], tensorMap, context).dataSync()
+          );
+          return inputParam.type === "number" ? data[0] : data;
+        }
+        const attrParam = node.attrParams[paramName];
+        return attrParam && attrParam.value;
+      }
+      /**
+       * Retrieve the tensor based on input name by extracting the node name and
+       * output index information.
+       * @param name Node input name
+       * @param tensorsMap Tensors map keyed by the node
+       */
+      function getTensor(name, tensorsMap, context) {
+        const [nodeName, index] = parseNodeName(name);
+        const contextId = context.currentContextIds.find((contextId) => {
+          return !!tensorsMap[getNodeNameWithContextId(nodeName, contextId)];
+        });
+        return contextId !== undefined
+          ? tensorsMap[getNodeNameWithContextId(nodeName, contextId)][index]
+          : undefined;
+      }
+      /**
+       * Retrieve the tensors based on input name for current context.
+       * @param name Node input name
+       * @param tensorsMap Tensors map keyed by the node
+       */
+      function getTensorsForCurrentContenxt(name, tensorsMap, context) {
+        return tensorsMap[getNodeNameWithContextId(name, context.currentContextId)];
+      }
+      /**
+       * Returns the node name and index from the Node input name.
+       * @param inputName The input name of the node, in format of
+       * node_name:output_index, i.e. MatMul:0, if the output_index is not set, it is
+       * default to 0.
+       */
+      function getNodeNameAndIndex(inputName, context) {
+        const [nodeName, index] = parseNodeName(inputName);
+        return [getNodeNameWithContextId(nodeName, context && context.currentContextId), index];
+      }
+      function getNodeNameWithContextId(name, contextId) {
+        return !!contextId ? `${name}-${contextId}` : name;
+      }
+      function parseNodeName(name) {
+        const parts = name.split(":");
+        if (parts.length === 1) {
+          return [name, 0];
+        }
+        const nodeName = parts[0];
+        return [nodeName, Number(parts[parts.length - 1])];
+      }
+      function split(arr, size) {
+        const res = [];
+        for (let i = 0; i < arr.length; i += size) {
+          res.push(arr.slice(i, i + size));
+        }
+        return res;
+      }
+      //# sourceMappingURL=utils.js.map
+
+      /***/
+    },
+    /* 3 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return inferShape;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return convertToTensor;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return convertToTensorArray;
+      });
+      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
+      /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(10);
+      /* harmony import */ var _tensor__WEBPACK_IMPORTED_MODULE_2__ = __webpack_require__(7);
+      /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(1);
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function inferShape(val, dtype) {
+        let firstElem = val;
+        if (Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(val)) {
+          return dtype === "string" ? [] : [val.length];
+        }
+        if (!Array.isArray(val)) {
+          return []; // Scalar.
+        }
+        const shape = [];
+        while (
+          Array.isArray(firstElem) ||
+          (Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(firstElem) &&
+            dtype !== "string")
+        ) {
+          shape.push(firstElem.length);
+          firstElem = firstElem[0];
+        }
+        if (
+          Array.isArray(val) &&
+          Object(_environment__WEBPACK_IMPORTED_MODULE_1__[/* env */ "c"])().getBool(
+            "TENSORLIKE_CHECK_SHAPE_CONSISTENCY"
+          )
+        ) {
+          deepAssertShapeConsistency(val, shape, []);
+        }
+        return shape;
+      }
+      function deepAssertShapeConsistency(val, shape, indices) {
+        indices = indices || [];
+        if (
+          !Array.isArray(val) &&
+          !Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(val)
+        ) {
+          Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
+            shape.length === 0,
+            () =>
+              `Element arr[${indices.join("][")}] is a primitive, ` +
+              `but should be an array/TypedArray of ${shape[0]} elements`
+          );
+          return;
+        }
+        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
+          shape.length > 0,
+          () =>
+            `Element arr[${indices.join("][")}] should be a primitive, ` +
+            `but is an array of ${val.length} elements`
+        );
+        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
+          val.length === shape[0],
+          () =>
+            `Element arr[${indices.join("][")}] should have ${shape[0]} ` +
+            `elements, but has ${val.length} elements`
+        );
+        const subShape = shape.slice(1);
+        for (let i = 0; i < val.length; ++i) {
+          deepAssertShapeConsistency(val[i], subShape, indices.concat(i));
+        }
+      }
+      function assertDtype(expectedDtype, actualDType, argName, functionName) {
+        if (expectedDtype == null) {
+          return;
+        }
+        if (
+          (expectedDtype !== "numeric" && expectedDtype !== actualDType) ||
+          (expectedDtype === "numeric" && actualDType === "string")
+        ) {
+          throw new Error(
+            `Argument '${argName}' passed to '${functionName}' must ` +
+              `be ${expectedDtype} tensor, but got ${actualDType} tensor`
+          );
+        }
+      }
+      function convertToTensor(x, argName, functionName, parseAsDtype = "numeric") {
+        if (x instanceof _tensor__WEBPACK_IMPORTED_MODULE_2__[/* Tensor */ "a"]) {
+          assertDtype(parseAsDtype, x.dtype, argName, functionName);
+          return x;
+        }
+        let inferredDtype = Object(_util__WEBPACK_IMPORTED_MODULE_3__["inferDtype"])(x);
+        // If the user expects a bool/int/float, use that info to update the
+        // inferredDtype when it is not a string.
+        if (inferredDtype !== "string" && ["bool", "int32", "float32"].indexOf(parseAsDtype) >= 0) {
+          inferredDtype = parseAsDtype;
+        }
+        assertDtype(parseAsDtype, inferredDtype, argName, functionName);
+        if (
+          x == null ||
+          (!Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(x) &&
+            !Array.isArray(x) &&
+            typeof x !== "number" &&
+            typeof x !== "boolean" &&
+            typeof x !== "string")
+        ) {
+          const type = x == null ? "null" : x.constructor.name;
+          throw new Error(
+            `Argument '${argName}' passed to '${functionName}' must be a ` +
+              `Tensor or TensorLike, but got '${type}'`
+          );
+        }
+        const inferredShape = inferShape(x, inferredDtype);
+        if (!Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(x) && !Array.isArray(x)) {
+          x = [x];
+        }
+        const skipTypedArray = true;
+        const values =
+          inferredDtype !== "string"
+            ? Object(_util__WEBPACK_IMPORTED_MODULE_3__["toTypedArray"])(
+                x,
+                inferredDtype,
+                Object(_environment__WEBPACK_IMPORTED_MODULE_1__[/* env */ "c"])().getBool("DEBUG")
+              )
+            : Object(_util__WEBPACK_IMPORTED_MODULE_3__["flatten"])(x, [], skipTypedArray);
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeTensor(
+          values,
+          inferredShape,
+          inferredDtype
+        );
+      }
+      function convertToTensorArray(arg, argName, functionName, parseAsDtype = "numeric") {
+        if (!Array.isArray(arg)) {
+          throw new Error(
+            `Argument ${argName} passed to ${functionName} must be a ` +
+              "`Tensor[]` or `TensorLike[]`"
+          );
+        }
+        const tensors = arg;
+        return tensors.map(
+          (t, i) => convertToTensor(t, `${argName}[${i}]`, functionName),
+          parseAsDtype
+        );
+      }
+      //# sourceMappingURL=tensor_util_env.js.map
+
+      /***/
+    },
+    /* 4 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return op;
+      });
+      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Used for wrapping functions that perform math operations on
+       * Tensors. The function will be wrapped in a named scope that cleans all
+       * memory usage after the function is done.
+       */
+      function op(f) {
+        const keys = Object.keys(f);
+        if (keys.length !== 1) {
+          throw new Error(
+            `Please provide an object with a single key ` +
+              `(operation name) mapping to a function. Got an object with ` +
+              `${keys.length} keys.`
+          );
+        }
+        let opName = keys[0];
+        const fn = f[opName];
+        // Strip the underscore from the end of the function name.
+        if (opName.endsWith("_")) {
+          opName = opName.substring(0, opName.length - 1);
+        }
+        // tslint:disable-next-line:no-any
+        const f2 = (...args) => {
+          _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].startScope(opName);
+          try {
+            const result = fn(...args);
+            if (result instanceof Promise) {
+              console.error("Cannot return a Promise inside of tidy.");
+            }
+            _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].endScope(result);
+            return result;
+          } catch (ex) {
+            _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].endScope(null);
+            throw ex;
+          }
+        };
+        Object.defineProperty(f2, "name", { value: opName, configurable: true });
+        // tslint:disable-next-line:no-any
+        return f2;
+      }
+      //# sourceMappingURL=operation.js.map
+
+      /***/
+    },
+    /* 5 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "a", function () {
+        return /* binding */ ENGINE;
+      });
+
+      // UNUSED EXPORTS: Engine
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/environment.js
+      var dist_environment = __webpack_require__(10);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/global_util.js
+      var global_util = __webpack_require__(33);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/kernel_registry.js
+      var kernel_registry = __webpack_require__(17);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/util.js
+      var util = __webpack_require__(1);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/profiler.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class Profiler {
+        constructor(backendTimer, logger) {
+          this.backendTimer = backendTimer;
+          this.logger = logger;
+          if (logger == null) {
+            this.logger = new profiler_Logger();
+          }
+        }
+        profileKernel(kernelName, inputs, f) {
+          let outputs;
+          const holdResultWrapperFn = () => {
+            outputs = f();
+          };
+          const timer = this.backendTimer.time(holdResultWrapperFn);
+          outputs.forEach((r) => {
+            // Dangling promise here because we don't want to propagate up
+            // asynchronicity.
+            r.data().then((vals) => {
+              checkComputationForErrors(vals, r.dtype, kernelName);
+              timer.then((timing) => {
+                let extraInfo = "";
+                if (timing.getExtraProfileInfo != null) {
+                  extraInfo = timing.getExtraProfileInfo();
+                }
+                this.logger.logKernelProfile(
+                  kernelName,
+                  r,
+                  vals,
+                  timing.kernelMs,
+                  inputs,
+                  extraInfo
+                );
+              });
+            });
+          });
+          return outputs;
+        }
+      }
+      function checkComputationForErrors(vals, dtype, kernelName) {
+        if (dtype !== "float32") {
+          // Only floating point computations will generate NaN values
+          return false;
+        }
+        for (let i = 0; i < vals.length; i++) {
+          const num = vals[i];
+          if (isNaN(num) || !isFinite(num)) {
+            // Throwing custom exception so behavior is testable.
+            console.warn(`Found ${num} in the result of '${kernelName}'`);
+            return true;
+          }
+        }
+        return false;
+      }
+      class profiler_Logger {
+        logKernelProfile(name, result, vals, timeMs, inputs, extraInfo) {
+          const time =
+            typeof timeMs === "number" ? util["rightPad"](`${timeMs}ms`, 9) : timeMs["error"];
+          const paddedName = util["rightPad"](name, 25);
+          const rank = result.rank;
+          const size = result.size;
+          const shape = util["rightPad"](result.shape.toString(), 14);
+          let inputShapesDescription = "";
+          for (const name in inputs) {
+            const input = inputs[name];
+            // The input might be a non-tensor (e.g HTMLImageElement), in which case
+            // we claim the output shape as input shape.
+            const inputShape = input.shape || result.shape;
+            const inputRank = inputShape.length;
+            inputShapesDescription += `${name}: ${inputRank}D ${inputRank > 0 ? inputShape : ""} `;
+          }
+          console.log(
+            `%c${paddedName}\t%c${time}\t%c${rank}D ${shape}\t%c${size}\t%c${inputShapesDescription}\t%c${extraInfo}`,
+            "font-weight:bold",
+            "color:red",
+            "color:blue",
+            "color: orange",
+            "color: green",
+            "color: steelblue"
+          );
+        }
+      }
+      //# sourceMappingURL=profiler.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tape.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Computes a list of TapeNodes that connect x to y, filtering everything else
+       * out and preserving the order of the original tape elements.
+       *
+       * @param tape The tape elements to filter.
+       * @param xs The input Tensors.
+       * @param y The output Tensor.
+       */
+      function getFilteredNodesXToY(tape, xs, y) {
+        // Forward pass to compute all the nodes and Tensors that are transitively a
+        // function of x.
+        const tensorsFromX = {};
+        const nodesFromX = {};
+        for (let i = 0; i < xs.length; i++) {
+          tensorsFromX[xs[i].id] = true;
+        }
+        for (let i = 0; i < tape.length; i++) {
+          const node = tape[i];
+          const nodeInputs = node.inputs;
+          for (const inputName in nodeInputs) {
+            const input = nodeInputs[inputName];
+            let anyInputFromX = false;
+            for (let j = 0; j < xs.length; j++) {
+              if (tensorsFromX[input.id]) {
+                node.outputs.forEach((output) => (tensorsFromX[output.id] = true));
+                anyInputFromX = true;
+                nodesFromX[node.id] = true;
+                break;
+              }
+            }
+            if (anyInputFromX) {
+              break;
+            }
+          }
+        }
+        // Backward pass to find all of the nodes and Tensors that lead to y.
+        const tensorsLeadToY = {};
+        tensorsLeadToY[y.id] = true;
+        const nodesToY = {};
+        for (let i = tape.length - 1; i >= 0; i--) {
+          const node = tape[i];
+          const nodeInputs = node.inputs;
+          // If any of the outputs lead to y, mark all of the inputs as leading to y.
+          for (let j = 0; j < node.outputs.length; j++) {
+            if (tensorsLeadToY[node.outputs[j].id]) {
+              for (const inputName in nodeInputs) {
+                tensorsLeadToY[nodeInputs[inputName].id] = true;
+                nodesToY[node.id] = true;
+              }
+              break;
+            }
+          }
+        }
+        // Return the paths that come from x and lead to y.
+        const filteredTape = [];
+        for (let i = 0; i < tape.length; i++) {
+          const node = tape[i];
+          if (nodesFromX[node.id] && nodesToY[node.id]) {
+            // Prune the inputs from the node that aren't a function of x.
+            const prunedInputs = {};
+            for (const inputName in node.inputs) {
+              const nodeInput = node.inputs[inputName];
+              if (tensorsFromX[nodeInput.id]) {
+                prunedInputs[inputName] = nodeInput;
+              }
+            }
+            // Copy the node and overwrite inputsAndArgs to the pruned version.
+            const prunedNode = Object.assign({}, node);
+            prunedNode.inputs = prunedInputs;
+            prunedNode.outputs = node.outputs;
+            filteredTape.push(prunedNode);
+          }
+        }
+        return filteredTape;
+      }
+      /**
+       * Backpropagate gradients through the filtered TapeNodes.
+       *
+       * @param tensorAccumulatedGradientMap A map of Tensor to its gradient. This map
+       * is mutated by this method.
+       * @param filteredTape The filtered TapeNodes to backprop through.
+       */
+      function backpropagateGradients(tensorAccumulatedGradientMap, filteredTape, tidy) {
+        // Walk the tape backward and keep a map of Tensor to its gradient.
+        for (let i = filteredTape.length - 1; i >= 0; i--) {
+          const node = filteredTape[i];
+          const dys = [];
+          node.outputs.forEach((o) => {
+            const gradTensor = tensorAccumulatedGradientMap[o.id];
+            if (gradTensor != null) {
+              dys.push(gradTensor);
+            } else {
+              // This particular output is not in the back-propagation subgraph, so it
+              // does not affect the final output, thus we put null for its dy.
+              dys.push(null);
+            }
+          });
+          if (node.gradient == null) {
+            throw new Error(
+              `Cannot compute gradient: gradient function not found ` + `for ${node.kernelName}.`
+            );
+          }
+          // Backprop dy through this node and accumulate gradients over the inputs.
+          const inputGradients = node.gradient(dys);
+          for (const inputName in node.inputs) {
+            if (!(inputName in inputGradients)) {
+              throw new Error(
+                `Cannot backprop through input ${inputName}. ` +
+                  `Available gradients found: ${Object.keys(inputGradients)}.`
+              );
+            }
+            // Call the gradient function.
+            const dx = tidy(() => inputGradients[inputName]());
+            if (dx.dtype !== "float32") {
+              throw new Error(
+                `Error in gradient for op ${node.kernelName}. The gradient of input ` +
+                  `${inputName} must have 'float32' dtype, but has '${dx.dtype}'`
+              );
+            }
+            const x = node.inputs[inputName];
+            if (!util["arraysEqual"](dx.shape, x.shape)) {
+              throw new Error(
+                `Error in gradient for op ${node.kernelName}. The gradient of input ` +
+                  `'${inputName}' has shape '${dx.shape}', which does not match ` +
+                  `the shape of the input '${x.shape}'`
+              );
+            }
+            if (tensorAccumulatedGradientMap[x.id] == null) {
+              tensorAccumulatedGradientMap[x.id] = dx;
+            } else {
+              const curGradient = tensorAccumulatedGradientMap[x.id];
+              tensorAccumulatedGradientMap[x.id] = curGradient.add(dx);
+              curGradient.dispose();
+            }
+          }
+        }
+      }
+      //# sourceMappingURL=tape.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor.js + 1 modules
+      var tensor = __webpack_require__(7);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor_util.js
+      var tensor_util = __webpack_require__(11);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/engine.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class EngineState {
+        constructor() {
+          // Public since optimizers will use it.
+          this.registeredVariables = {};
+          this.nextTapeNodeId = 0;
+          this.numBytes = 0;
+          this.numTensors = 0;
+          this.numStringTensors = 0;
+          this.numDataBuffers = 0;
+          // Number of nested tf.grad() statements when computing higher-order
+          // gradients. E.g. `1` for first-order gradients and `2` for second-order
+          // gradients. Used to track if the tape should be removed after a backprop.
+          this.gradientDepth = 0;
+          // Number of nested kernel calls. When kernel depth is greater than 1, we turn
+          // off the tape.
+          this.kernelDepth = 0;
+          this.scopeStack = [];
+          /**
+           * Keeps track of the number of data moves during a kernel execution. We
+           * maintain a stack since kernels can call other kernels, recursively.
+           */
+          this.numDataMovesStack = [];
+          this.nextScopeId = 0;
+          this.tensorInfo = new WeakMap();
+          this.profiling = false;
+          this.activeProfile = {
+            newBytes: 0,
+            newTensors: 0,
+            peakBytes: 0,
+            kernels: [],
+            result: null,
+          };
+        }
+        dispose() {
+          for (const variableName in this.registeredVariables) {
+            this.registeredVariables[variableName].dispose();
+          }
+        }
+      }
+      class engine_Engine {
+        constructor(ENV) {
+          this.ENV = ENV;
+          this.registry = {};
+          this.registryFactory = {};
+          this.pendingBackendInitId = 0;
+          this.state = new EngineState();
+        }
+        async ready() {
+          if (this.pendingBackendInit != null) {
+            return this.pendingBackendInit.then(() => {});
+          }
+          if (this.backendInstance != null) {
+            return;
+          }
+          const sortedBackends = this.getSortedBackends();
+          for (let i = 0; i < sortedBackends.length; i++) {
+            const backendName = sortedBackends[i];
+            const success = await this.initializeBackend(backendName).success;
+            if (success) {
+              await this.setBackend(backendName);
+              return;
+            }
+          }
+          throw new Error(
+            `Could not initialize any backends, all backend initializations ` + `failed.`
+          );
+        }
+        get backend() {
+          if (this.pendingBackendInit != null) {
+            throw new Error(
+              `Backend '${this.backendName}' has not yet been initialized. Make ` +
+                `sure to await tf.ready() or await tf.setBackend() before calling ` +
+                `other methods`
+            );
+          }
+          if (this.backendInstance == null) {
+            const { name, asyncInit } = this.initializeBackendsAndReturnBest();
+            if (asyncInit) {
+              throw new Error(
+                `The highest priority backend '${name}' has not yet been ` +
+                  `initialized. Make sure to await tf.ready() or ` +
+                  `await tf.setBackend() before calling other methods`
+              );
+            }
+            this.setBackend(name);
+          }
+          return this.backendInstance;
+        }
+        backendNames() {
+          return Object.keys(this.registryFactory);
+        }
+        findBackend(backendName) {
+          if (!(backendName in this.registry)) {
+            // If the backend hasn't been initialized but we have a registry entry for
+            // it, initialize it and return it.
+            if (backendName in this.registryFactory) {
+              const { asyncInit } = this.initializeBackend(backendName);
+              if (asyncInit) {
+                // Backend is not ready yet.
+                return null;
+              }
+            } else {
+              return null;
+            }
+          }
+          return this.registry[backendName];
+        }
+        findBackendFactory(backendName) {
+          if (!(backendName in this.registryFactory)) {
+            return null;
+          }
+          return this.registryFactory[backendName].factory;
+        }
+        registerBackend(backendName, factory, priority = 1) {
+          if (backendName in this.registryFactory) {
+            console.warn(
+              `${backendName} backend was already registered. ` +
+                `Reusing existing backend factory.`
+            );
+            return false;
+          }
+          this.registryFactory[backendName] = { factory, priority };
+          return true;
+        }
+        async setBackend(backendName) {
+          if (this.registryFactory[backendName] == null) {
+            throw new Error(`Backend name '${backendName}' not found in registry`);
+          }
+          this.backendName = backendName;
+          if (this.registry[backendName] == null) {
+            this.backendInstance = null;
+            const { success, asyncInit } = this.initializeBackend(backendName);
+            const result = asyncInit ? await success : success;
+            if (!result) {
+              return false;
+            }
+          }
+          this.backendInstance = this.registry[backendName];
+          this.setupRegisteredKernels();
+          // Reset the profiler.
+          this.profiler = new Profiler(this.backendInstance);
+          return true;
+        }
+        setupRegisteredKernels() {
+          const kernels = Object(kernel_registry["c" /* getKernelsForBackend */])(this.backendName);
+          kernels.forEach((kernel) => {
+            if (kernel.setupFunc != null) {
+              kernel.setupFunc(this.backendInstance);
+            }
+          });
+        }
+        disposeRegisteredKernels(backendName) {
+          const kernels = Object(kernel_registry["c" /* getKernelsForBackend */])(backendName);
+          kernels.forEach((kernel) => {
+            if (kernel.disposeFunc != null) {
+              kernel.disposeFunc(this.registry[backendName]);
+            }
+          });
+        }
+        /**
+         * Initializes a backend by looking up the backend name in the factory
+         * registry and calling the factory method. Returns a boolean representing
+         * whether the initialization of the backend suceeded. Throws an error if
+         * there is no backend in the factory registry.
+         */
+        initializeBackend(backendName) {
+          const registryFactoryEntry = this.registryFactory[backendName];
+          if (registryFactoryEntry == null) {
+            throw new Error(`Cannot initialize backend ${backendName}, no registration found.`);
+          }
+          try {
+            const backend = registryFactoryEntry.factory();
+            // Test if the factory returns a promise.
+            if (Promise.resolve(backend) === backend) {
+              const promiseId = ++this.pendingBackendInitId;
+              const success = backend
+                .then((backendInstance) => {
+                  // Outdated promise. Another backend was set in the meantime.
+                  if (promiseId < this.pendingBackendInitId) {
+                    return false;
+                  }
+                  this.registry[backendName] = backendInstance;
+                  this.pendingBackendInit = null;
+                  return true;
+                })
+                .catch((err) => {
+                  // Outdated promise. Another backend was set in the meantime.
+                  if (promiseId < this.pendingBackendInitId) {
+                    return false;
+                  }
+                  this.pendingBackendInit = null;
+                  console.warn(`Initialization of backend ${backendName} failed`);
+                  console.warn(err.stack || err.message);
+                  return false;
+                });
+              this.pendingBackendInit = success;
+              return { success, asyncInit: true };
+            } else {
+              this.registry[backendName] = backend;
+              return { success: true, asyncInit: false };
+            }
+          } catch (err) {
+            console.warn(`Initialization of backend ${backendName} failed`);
+            console.warn(err.stack || err.message);
+            return { success: false, asyncInit: false };
+          }
+        }
+        removeBackend(backendName) {
+          if (!(backendName in this.registryFactory)) {
+            throw new Error(`${backendName} backend not found in registry`);
+          }
+          if (this.backendName === backendName && this.pendingBackendInit != null) {
+            // There is a pending promise of the backend we want to remove. Make it
+            // obsolete.
+            this.pendingBackendInitId++;
+          }
+          if (backendName in this.registry) {
+            this.disposeRegisteredKernels(backendName);
+            this.registry[backendName].dispose();
+            delete this.registry[backendName];
+          }
+          delete this.registryFactory[backendName];
+          // Unset the backend if it is active.
+          if (this.backendName === backendName) {
+            this.pendingBackendInit = null;
+            this.backendName = null;
+            this.backendInstance = null;
+          }
+        }
+        getSortedBackends() {
+          if (Object.keys(this.registryFactory).length === 0) {
+            throw new Error("No backend found in registry.");
+          }
+          return Object.keys(this.registryFactory).sort((a, b) => {
+            // Highest priority comes first.
+            return this.registryFactory[b].priority - this.registryFactory[a].priority;
+          });
+        }
+        initializeBackendsAndReturnBest() {
+          const sortedBackends = this.getSortedBackends();
+          for (let i = 0; i < sortedBackends.length; i++) {
+            const backendName = sortedBackends[i];
+            const { success, asyncInit } = this.initializeBackend(backendName);
+            if (asyncInit || success) {
+              return { name: backendName, asyncInit };
+            }
+          }
+          throw new Error(
+            `Could not initialize any backends, all backend initializations ` + `failed.`
+          );
+        }
+        moveData(backend, dataId) {
+          const info = this.state.tensorInfo.get(dataId);
+          const srcBackend = info.backend;
+          const values = this.readSync(dataId);
+          // Delete the tensor from the old backend and move it to the new
+          // backend.
+          srcBackend.disposeData(dataId);
+          info.backend = backend;
+          backend.move(dataId, values, info.shape, info.dtype);
+          if (this.shouldCheckForMemLeaks()) {
+            // Track the number of moves during a kernel execution to correctly
+            // detect memory leaks.
+            this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1]++;
+          }
+        }
+        tidy(nameOrFn, fn) {
+          let name = null;
+          if (fn == null) {
+            // Called with only 1 argument.
+            if (typeof nameOrFn !== "function") {
+              throw new Error("Please provide a function to tidy()");
+            }
+            fn = nameOrFn;
+          } else {
+            // Called with 2 arguments.
+            if (typeof nameOrFn !== "string" && !(nameOrFn instanceof String)) {
+              throw new Error(
+                "When calling with two arguments, the first argument " +
+                  "to tidy() must be a string"
+              );
+            }
+            if (typeof fn !== "function") {
+              throw new Error(
+                "When calling with two arguments, the 2nd argument " +
+                  "to tidy() must be a function"
+              );
+            }
+            name = nameOrFn;
+            // TODO(nsthorat,smilkov): Do operation logging and performance
+            // profiling.
+          }
+          let result;
+          return this.scopedRun(
+            () => this.startScope(name),
+            () => this.endScope(result),
+            () => {
+              result = fn();
+              if (result instanceof Promise) {
+                console.error("Cannot return a Promise inside of tidy.");
+              }
+              return result;
+            }
+          );
+        }
+        scopedRun(start, end, f) {
+          start();
+          try {
+            const res = f();
+            end();
+            return res;
+          } catch (ex) {
+            end();
+            throw ex;
+          }
+        }
+        nextTensorId() {
+          return engine_Engine.nextTensorId++;
+        }
+        nextVariableId() {
+          return engine_Engine.nextVariableId++;
+        }
+        /**
+         * This method is called instead of the public-facing tensor.clone() when
+         * saving a tensor for backwards pass. It makes sure to add the clone
+         * operation to the tape regardless of being called inside a kernel
+         * execution.
+         *
+         * This method will go away once all kernels are modularized since we won't
+         * need to turn off the tape inside runKernel().
+         */
+        clone(x) {
+          const y = this.makeTensorFromDataId(x.dataId, x.shape, x.dtype);
+          const inputs = { x };
+          const grad = (dy) => ({ x: () => dy.toFloat() });
+          const saved = [];
+          this.addTapeNode(this.state.activeScope.name, inputs, [y], grad, saved, {});
+          return y;
+        }
+        /**
+         * Execute a kernel with the given name and return the output tensor.
+         *
+         * @param kernelName The name of the kernel to execute.
+         * @param inputs A map of input names to tensors.
+         * @param attrs A map of attribute names to their values. An attribute is a
+         *     primitive (non-tensor) input to the kernel.
+         * @param inputsToSave A list of tensors, inputs to save for the backprop
+         *     computation.
+         * @param outputsToSave A list of booleans, specifying which output to save
+         *     for the backprop computation. These are booleans since the output
+         * tensors are not visible to the user.
+         */
+        runKernel(kernelName, inputs, attrs, inputsToSave, outputsToSave) {
+          const forwardFunc = null;
+          const backwardsFunc = null;
+          // Call runKernel as a stop-gap until we modularize all kernels.
+          // Once we modularize all kernels, we will remove the existing
+          // `runKernelFunc`.
+          return this.runKernelFunc(
+            forwardFunc,
+            inputs,
+            backwardsFunc,
+            kernelName,
+            attrs,
+            inputsToSave,
+            outputsToSave
+          );
+        }
+        shouldCheckForMemLeaks() {
+          return this.ENV.getBool("IS_TEST");
+        }
+        checkKernelForMemLeak(kernelName, numDataIdsBefore, outInfos) {
+          const numDataIdsAfter = this.backend.numDataIds();
+          // Count the number of data ids associated with the result of the kernel.
+          let numOutputDataIds = 0;
+          outInfos.forEach((info) => {
+            // Complex numbers allocate 3 data ids, one for 'real', one for
+            // 'imaginary', and one for the container that holds the former two.
+            numOutputDataIds += info.dtype === "complex64" ? 3 : 1;
+          });
+          // Account for the number of moves during kernel execution. A "data move"
+          // can happen in the middle of a kernel execution, placing a new (key,value)
+          // pair in the data storage. Since data moves have net zero effect (we
+          // always remove the data from the old backend), we have to cancel them out
+          // when detecting memory leaks.
+          const numMoves = this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1];
+          const dataIdsLeaked = numDataIdsAfter - numDataIdsBefore - numOutputDataIds - numMoves;
+          if (dataIdsLeaked > 0) {
+            throw new Error(
+              `Backend '${this.backendName}' has an internal memory leak ` +
+                `(${dataIdsLeaked} data ids) after running '${kernelName}'`
+            );
+          }
+        }
+        /**
+         * @deprecated Use `runKernel` for newly added kernels. Keep using this method
+         *     only for kernels that are not yet fully modularized.
+         */
+        runKernelFunc(
+          forwardFunc,
+          inputs,
+          backwardsFunc,
+          kernelName,
+          attrs,
+          inputsToSave,
+          outputsToSave
+        ) {
+          let outputs;
+          let saved = [];
+          const isTapeOn = this.isTapeOn();
+          if (kernelName == null) {
+            kernelName = this.state.activeScope != null ? this.state.activeScope.name : "";
+          }
+          const startingBytecount = this.state.numBytes;
+          const startingNumTensors = this.state.numTensors;
+          if (this.shouldCheckForMemLeaks()) {
+            this.state.numDataMovesStack.push(0);
+          }
+          let kernelFunc;
+          const kernel = Object(kernel_registry["b" /* getKernel */])(kernelName, this.backendName);
+          let out;
+          if (kernel != null) {
+            kernelFunc = () => {
+              const numDataIdsBefore = this.backend.numDataIds();
+              out = kernel.kernelFunc({ inputs, attrs, backend: this.backend });
+              const outInfos = Array.isArray(out) ? out : [out];
+              if (this.shouldCheckForMemLeaks()) {
+                this.checkKernelForMemLeak(kernelName, numDataIdsBefore, outInfos);
+              }
+              const outTensors = outInfos.map(({ dataId, shape, dtype }) =>
+                this.makeTensorFromDataId(dataId, shape, dtype)
+              );
+              // Save the inputs and outputs.
+              // Do not save unless we are recording to the tape. Otherwise it would
+              // cause a mem leak since we would never run backprop, which disposes
+              // the kept tensors.
+              if (isTapeOn) {
+                let tensorsToSave = this.getTensorsForGradient(kernelName, inputs, outTensors);
+                if (tensorsToSave == null) {
+                  // Fallback for ops that call runKernelFunc and pass in
+                  // inputsToSave and outputsToSave. Currently this is the set of ops
+                  // with kernel support in the WASM backend. Once those ops and
+                  // respective gradients are modularised we can remove this path.
+                  if (outputsToSave == null) {
+                    outputsToSave = [];
+                  }
+                  const outsToSave = outTensors.filter((_, i) => outputsToSave[i]);
+                  tensorsToSave = (inputsToSave || []).slice().concat(outsToSave);
+                }
+                saved = this.saveTensorsForBackwardMode(tensorsToSave);
+              }
+              return outTensors;
+            };
+          } else {
+            const saveFunc = (tensors) => {
+              // Do not save unless we are recording to the tape. Otherwise it would
+              // cause a mem leak since we would never run backprop, which disposes
+              // the kept tensors.
+              if (!isTapeOn) {
+                return;
+              }
+              saved = tensors.map((tensor) => this.keep(this.clone(tensor)));
+            };
+            kernelFunc = () => {
+              const numDataIdsBefore = this.backend.numDataIds();
+              out = this.tidy(() => forwardFunc(this.backend, saveFunc));
+              const outs = Array.isArray(out) ? out : [out];
+              if (this.shouldCheckForMemLeaks()) {
+                this.checkKernelForMemLeak(kernelName, numDataIdsBefore, outs);
+              }
+              return outs;
+            };
+          }
+          // Stop recording to a tape when running a kernel.
+          this.scopedRun(
+            () => this.state.kernelDepth++,
+            () => this.state.kernelDepth--,
+            () => {
+              if (!this.ENV.getBool("DEBUG")) {
+                outputs = kernelFunc();
+              } else {
+                outputs = this.profiler.profileKernel(kernelName, inputs, () => kernelFunc());
+              }
+            }
+          );
+          if (isTapeOn) {
+            this.addTapeNode(kernelName, inputs, outputs, backwardsFunc, saved, attrs);
+          }
+          if (this.state.profiling) {
+            this.state.activeProfile.kernels.push({
+              name: kernelName,
+              bytesAdded: this.state.numBytes - startingBytecount,
+              totalBytesSnapshot: this.state.numBytes,
+              tensorsAdded: this.state.numTensors - startingNumTensors,
+              totalTensorsSnapshot: this.state.numTensors,
+              inputShapes: Object.keys(inputs).map((key) => inputs[key].shape),
+              outputShapes: outputs.map((item) => item.shape),
+            });
+          }
+          return Array.isArray(out) ? outputs : outputs[0];
+        }
+        /**
+         * Saves tensors used in forward mode for use in backward mode.
+         *
+         * @param tensors the list of tensors to save.
+         */
+        saveTensorsForBackwardMode(tensors) {
+          const saved = tensors.map((tensor) => this.keep(this.clone(tensor)));
+          return saved;
+        }
+        /**
+         * Returns a list of tensors to save for a given gradient calculation.
+         *
+         * Returns undefined if their is no registered gradient for this kernel in the
+         * gradient registry.
+         *
+         * @param kernelName name of kernel to look up gradient for.
+         * @param inputs a map of input tensors.
+         * @param outputs an array of output tensors from forward mode of kernel.
+         */
+        getTensorsForGradient(kernelName, inputs, outputs) {
+          const gradConfig = Object(kernel_registry["a" /* getGradient */])(kernelName);
+          if (gradConfig != null) {
+            const inputsToSave = gradConfig.inputsToSave || [];
+            const outputsToSave = gradConfig.outputsToSave || [];
+            // If saveAllInputs is true, all inputs will be saved. Otherwise, inputs
+            // specified in inputsToSave will be saved.
+            let inputTensorsToSave;
+            if (gradConfig.saveAllInputs) {
+              util["assert"](
+                Array.isArray(inputs),
+                () => "saveAllInputs is true, expected inputs to be an array."
+              );
+              inputTensorsToSave = Object.keys(inputs).map((key) => inputs[key]);
+            } else {
+              inputTensorsToSave = inputsToSave.map((inputName) => inputs[inputName]);
+            }
+            const outputTensorsToSave = outputs.filter((_, i) => outputsToSave[i]);
+            return inputTensorsToSave.concat(outputTensorsToSave);
+          }
+          // TODO(yassogba) throw exception here once all runkernelFunc calls with
+          // inputsToSave/outputsToSave are removed
+          return null;
+        }
+        /**
+         * Internal method used by public APIs for tensor creation. Makes a new
+         * tensor with the provided shape, dtype and values. It always
+         * creates a new data id and writes the values to the underlying backend.
+         */
+        makeTensor(values, shape, dtype, backend) {
+          if (values == null) {
+            throw new Error("Values passed to engine.makeTensor() are null");
+          }
+          dtype = dtype || "float32";
+          backend = backend || this.backend;
+          let backendVals = values;
+          if (dtype === "string" && util["isString"](values[0])) {
+            backendVals = values.map((d) => util["encodeString"](d));
+          }
+          const dataId = backend.write(backendVals, shape, dtype);
+          const t = new tensor["a" /* Tensor */](shape, dtype, dataId, this.nextTensorId());
+          this.incRef(t, backend);
+          // Count bytes for string tensors.
+          if (dtype === "string") {
+            const info = this.state.tensorInfo.get(dataId);
+            const newBytes = Object(util["bytesFromStringArray"])(backendVals);
+            this.state.numBytes += newBytes - info.bytes;
+            info.bytes = newBytes;
+          }
+          return t;
+        }
+        /**
+         * Internal method used by backends. Makes a new tensor
+         * that is a wrapper around an existing data id. It doesn't create
+         * a new data id, only increments the ref count used in memory tracking.
+         */
+        makeTensorFromDataId(dataId, shape, dtype, backend) {
+          dtype = dtype || "float32";
+          const t = new tensor["a" /* Tensor */](shape, dtype, dataId, this.nextTensorId());
+          this.incRef(t, backend);
+          return t;
+        }
+        makeVariable(initialValue, trainable = true, name, dtype) {
+          name = name || this.nextVariableId().toString();
+          if (dtype != null && dtype !== initialValue.dtype) {
+            initialValue = initialValue.asType(dtype);
+          }
+          const v = new tensor["c" /* Variable */](
+            initialValue,
+            trainable,
+            name,
+            this.nextTensorId()
+          );
+          if (this.state.registeredVariables[v.name] != null) {
+            throw new Error(`Variable with name ${v.name} was already registered`);
+          }
+          this.state.registeredVariables[v.name] = v;
+          this.incRef(v, this.backend);
+          return v;
+        }
+        incRef(a, backend) {
+          const refCount = this.state.tensorInfo.has(a.dataId)
+            ? this.state.tensorInfo.get(a.dataId).refCount
+            : 0;
+          this.state.numTensors++;
+          if (a.dtype === "string") {
+            this.state.numStringTensors++;
+          }
+          if (refCount === 0) {
+            this.state.numDataBuffers++;
+            // Bytes for complex numbers are counted by their components. Bytes for
+            // string tensors are counted when writing values.
+            let bytes = 0;
+            if (a.dtype !== "complex64" && a.dtype !== "string") {
+              bytes = a.size * util["bytesPerElement"](a.dtype);
+            }
+            this.state.tensorInfo.set(a.dataId, {
+              backend: backend || this.backend,
+              dtype: a.dtype,
+              shape: a.shape,
+              bytes,
+              refCount: 0,
+            });
+            this.state.numBytes += bytes;
+          }
+          this.state.tensorInfo.get(a.dataId).refCount++;
+          if (!(a instanceof tensor["c" /* Variable */])) {
+            this.track(a);
+          }
+        }
+        disposeTensor(a) {
+          if (!this.state.tensorInfo.has(a.dataId)) {
+            return;
+          }
+          this.state.numTensors--;
+          if (a.dtype === "string") {
+            this.state.numStringTensors--;
+          }
+          const info = this.state.tensorInfo.get(a.dataId);
+          const refCount = info.refCount;
+          if (refCount <= 1) {
+            // Don't count bytes for complex numbers as they are counted by their
+            // components.
+            if (a.dtype !== "complex64") {
+              this.state.numBytes -= info.bytes;
+            }
+            this.state.numDataBuffers--;
+            info.backend.disposeData(a.dataId);
+            this.state.tensorInfo.delete(a.dataId);
+          } else {
+            this.state.tensorInfo.get(a.dataId).refCount--;
+          }
+          // TODO(nsthorat): Construct an error and save the stack trace for
+          // debugging when in debug mode. Creating a stack trace is too expensive
+          // to do unconditionally.
+        }
+        disposeVariables() {
+          for (const varName in this.state.registeredVariables) {
+            const v = this.state.registeredVariables[varName];
+            this.disposeVariable(v);
+          }
+        }
+        disposeVariable(v) {
+          this.disposeTensor(v);
+          if (this.state.registeredVariables[v.name] != null) {
+            delete this.state.registeredVariables[v.name];
+          }
+        }
+        memory() {
+          const info = this.backend.memory();
+          info.numTensors = this.state.numTensors;
+          info.numDataBuffers = this.state.numDataBuffers;
+          info.numBytes = this.state.numBytes;
+          if (this.state.numStringTensors > 0) {
+            info.unreliable = true;
+            if (info.reasons == null) {
+              info.reasons = [];
+            }
+            info.reasons.push(
+              "Memory usage by string tensors is approximate " + "(2 bytes per character)"
+            );
+          }
+          return info;
+        }
+        async profile(query) {
+          this.state.profiling = true;
+          const startBytes = this.state.numBytes;
+          const startNumTensors = this.state.numTensors;
+          this.state.activeProfile.kernels = [];
+          this.state.activeProfile.result = query();
+          this.state.profiling = false;
+          this.state.activeProfile.peakBytes = Math.max(
+            ...this.state.activeProfile.kernels.map((d) => d.totalBytesSnapshot)
+          );
+          this.state.activeProfile.newBytes = this.state.numBytes - startBytes;
+          this.state.activeProfile.newTensors = this.state.numTensors - startNumTensors;
+          return this.state.activeProfile;
+        }
+        isTapeOn() {
+          return this.state.gradientDepth > 0 && this.state.kernelDepth === 0;
+        }
+        addTapeNode(kernelName, inputs, outputs, gradientsFunc, saved, attrs) {
+          const tapeNode = { id: this.state.nextTapeNodeId++, kernelName, inputs, outputs, saved };
+          const gradConfig = Object(kernel_registry["a" /* getGradient */])(kernelName);
+          if (gradConfig != null) {
+            gradientsFunc = gradConfig.gradFunc;
+          }
+          if (gradientsFunc != null) {
+            tapeNode.gradient = (dys) => {
+              // TODO(smilkov): To optimize back-prop, pass dys that are not used in
+              // the backprop graph to the user as null instead of zeros
+              dys = dys.map((dy, i) => {
+                if (dy == null) {
+                  const output = outputs[i];
+                  const vals = util["makeZerosTypedArray"](output.size, output.dtype);
+                  return this.makeTensor(vals, output.shape, output.dtype);
+                }
+                return dy;
+              });
+              // Grad functions of ops with single outputs expect a dy, while ops
+              // with multiple outputs expect dys (array of dy).
+              return gradientsFunc(dys.length > 1 ? dys : dys[0], saved, attrs);
+            };
+          }
+          this.state.activeTape.push(tapeNode);
+        }
+        keep(result) {
+          result.kept = true;
+          return result;
+        }
+        startTape() {
+          if (this.state.gradientDepth === 0) {
+            this.state.activeTape = [];
+          }
+          this.state.gradientDepth++;
+        }
+        endTape() {
+          this.state.gradientDepth--;
+        }
+        /**
+         * Start a scope. Use this with endScope() to achieve the same functionality
+         * as scope() without the need for a function closure.
+         */
+        startScope(name) {
+          const scopeInfo = {
+            track: [],
+            name: "unnamed scope",
+            id: this.state.nextScopeId++,
+          };
+          if (name) {
+            scopeInfo.name = name;
+          }
+          this.state.scopeStack.push(scopeInfo);
+          this.state.activeScope = scopeInfo;
+        }
+        /**
+         * End a scope. Use this with startScope() to achieve the same functionality
+         * as scope() without the need for a function closure.
+         */
+        endScope(result) {
+          const tensorsToTrackInParent = Object(tensor_util["getTensorsInContainer"])(result);
+          const tensorsToTrackInParentSet = new Set(tensorsToTrackInParent.map((t) => t.id));
+          // Dispose the arrays tracked in this scope.
+          for (let i = 0; i < this.state.activeScope.track.length; i++) {
+            const tensor = this.state.activeScope.track[i];
+            if (!tensor.kept && !tensorsToTrackInParentSet.has(tensor.id)) {
+              tensor.dispose();
+            }
+          }
+          const oldScope = this.state.scopeStack.pop();
+          this.state.activeScope =
+            this.state.scopeStack.length === 0
+              ? null
+              : this.state.scopeStack[this.state.scopeStack.length - 1];
+          // Track the current result in the parent scope.
+          tensorsToTrackInParent.forEach((tensor) => {
+            // Only track the tensor if was allocated in the inner scope and is not
+            // globally kept.
+            if (!tensor.kept && tensor.scopeId === oldScope.id) {
+              this.track(tensor);
+            }
+          });
+        }
+        /**
+         * Returns gradients of `f` with respect to each of the `xs`. The gradients
+         * returned are of the same length as `xs`, but some might be null if `f`
+         * was not a function of that `x`. It also takes optional dy to multiply the
+         * gradient, which defaults to `1`.
+         */
+        gradients(f, xs, dy, allowNoGradients = false) {
+          util["assert"](xs.length > 0, () => "gradients() received an empty list of xs.");
+          if (dy != null && dy.dtype !== "float32") {
+            throw new Error(`dy must have 'float32' dtype, but has '${dy.dtype}'`);
+          }
+          const y = this.scopedRun(
+            () => this.startTape(),
+            () => this.endTape(),
+            () => this.tidy("forward", f)
+          );
+          util["assert"](
+            y instanceof tensor["a" /* Tensor */],
+            () => "The result y returned by f() must be a tensor."
+          );
+          // Filter out the nodes that don't connect x => y.
+          const filteredTape = getFilteredNodesXToY(this.state.activeTape, xs, y);
+          if (!allowNoGradients && filteredTape.length === 0 && xs.length > 0) {
+            throw new Error(
+              "Cannot compute gradient of y=f(x) with respect to x. Make sure " +
+                "that the f you passed encloses all operations that lead from x " +
+                "to y."
+            );
+          }
+          return this.tidy("backward", () => {
+            const accumulatedGradientMap = {};
+            accumulatedGradientMap[y.id] = dy == null ? ones(y.shape) : dy;
+            // Backprop gradients through the filtered nodes.
+            backpropagateGradients(
+              accumulatedGradientMap,
+              filteredTape,
+              // Pass the tidy function to avoid circular dep with `tape.ts`.
+              (f) => this.tidy(f)
+            );
+            const grads = xs.map((x) => accumulatedGradientMap[x.id]);
+            if (this.state.gradientDepth === 0) {
+              // This means that we are not computing higher-order gradients
+              // and can clean up the tape.
+              this.state.activeTape.forEach((node) => {
+                for (const tensor of node.saved) {
+                  tensor.dispose();
+                }
+              });
+              this.state.activeTape = null;
+            }
+            return { value: y, grads };
+          });
+        }
+        customGrad(f) {
+          util["assert"](
+            util["isFunction"](f),
+            () => "The f passed in customGrad(f) must be a function."
+          );
+          return (...inputs) => {
+            util["assert"](
+              inputs.every((t) => t instanceof tensor["a" /* Tensor */]),
+              () => "The args passed in customGrad(f)(x1, x2,...) must all be " + "tensors"
+            );
+            let res;
+            const inputMap = {};
+            inputs.forEach((input, i) => {
+              inputMap[i] = input;
+            });
+            return this.runKernelFunc(
+              (_, save) => {
+                res = f(...[...inputs, save]);
+                util["assert"](
+                  res.value instanceof tensor["a" /* Tensor */],
+                  () =>
+                    "The function f passed in customGrad(f) must return an " +
+                    "object where `obj.value` is a tensor"
+                );
+                util["assert"](
+                  util["isFunction"](res.gradFunc),
+                  () =>
+                    "The function f passed in customGrad(f) must return an " +
+                    "object where `obj.gradFunc` is a function."
+                );
+                return res.value;
+              },
+              inputMap,
+              (dy, saved) => {
+                const gradRes = res.gradFunc(dy, saved);
+                const grads = Array.isArray(gradRes) ? gradRes : [gradRes];
+                util["assert"](
+                  grads.length === inputs.length,
+                  () =>
+                    "The function f passed in customGrad(f) must return an " +
+                    "object where `obj.gradFunc` is a function that returns " +
+                    "the same number of tensors as inputs passed to f(...)."
+                );
+                util["assert"](
+                  grads.every((t) => t instanceof tensor["a" /* Tensor */]),
+                  () =>
+                    "The function f passed in customGrad(f) must return an " +
+                    "object where `obj.gradFunc` is a function that returns " +
+                    "a list of only tensors."
+                );
+                const gradMap = {};
+                grads.forEach((grad, i) => {
+                  gradMap[i] = () => grad;
+                });
+                return gradMap;
+              }
+            );
+          };
+        }
+        readSync(dataId) {
+          // Route the read to the correct backend.
+          const info = this.state.tensorInfo.get(dataId);
+          return info.backend.readSync(dataId);
+        }
+        read(dataId) {
+          // Route the read to the correct backend.
+          const info = this.state.tensorInfo.get(dataId);
+          return info.backend.read(dataId);
+        }
+        async time(query) {
+          const start = Object(util["now"])();
+          const timingInfo = await this.backend.time(query);
+          timingInfo.wallMs = Object(util["now"])() - start;
+          return timingInfo;
+        }
+        /**
+         * Tracks a Tensor in the current scope to be automatically cleaned up
+         * when the current scope ends, and returns the value.
+         *
+         * @param result The Tensor to track in the current scope.
+         */
+        track(result) {
+          if (this.state.activeScope != null) {
+            result.scopeId = this.state.activeScope.id;
+            this.state.activeScope.track.push(result);
+          }
+          return result;
+        }
+        get registeredVariables() {
+          return this.state.registeredVariables;
+        }
+        /**
+         * Resets the engine state. Removes all backends but does not remove
+         * registered backend factories.
+         */
+        reset() {
+          // Make any pending promise obsolete.
+          this.pendingBackendInitId++;
+          this.state.dispose();
+          this.ENV.reset();
+          this.state = new EngineState();
+          for (const backendName in this.registry) {
+            this.disposeRegisteredKernels(backendName);
+            this.registry[backendName].dispose();
+            delete this.registry[backendName];
+          }
+          this.backendName = null;
+          this.backendInstance = null;
+          this.pendingBackendInit = null;
+        }
+      }
+      engine_Engine.nextTensorId = 0;
+      engine_Engine.nextVariableId = 0;
+      function ones(shape) {
+        const values = Object(util["makeOnesTypedArray"])(
+          Object(util["sizeFromShape"])(shape),
+          "float32"
+        );
+        return ENGINE.makeTensor(values, shape, "float32");
+      }
+      function getOrMakeEngine() {
+        const ns = Object(global_util["b" /* getGlobalNamespace */])();
+        if (ns._tfengine == null) {
+          const environment = new dist_environment["b" /* Environment */](ns);
+          ns._tfengine = new engine_Engine(environment);
+        }
+        Object(dist_environment["d" /* setEnvironmentGlobal */])(ns._tfengine.ENV);
+        // Tell the current tensor interface that the global engine is responsible
+        // for tracking.
+        Object(tensor["f" /* setTensorTracker */])(() => ns._tfengine);
+        return ns._tfengine;
+      }
+      const ENGINE = getOrMakeEngine();
+      //# sourceMappingURL=engine.js.map
+
+      /***/
+    },
+    /* 6 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return Add;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return AddN;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return Atan2;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
+        return AvgPool;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
+        return AvgPoolBackprop;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
+        return AvgPool3D;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
+        return AvgPool3DBackprop;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "h", function () {
+        return BatchMatMul;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "i", function () {
+        return BatchToSpaceND;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "j", function () {
+        return BroadcastTo;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "k", function () {
+        return Complex;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "l", function () {
+        return Concat;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "m", function () {
+        return Conv2D;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "n", function () {
+        return Conv2DBackpropFilter;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "o", function () {
+        return Conv2DBackpropInput;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "p", function () {
+        return Conv3D;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "q", function () {
+        return Conv3DBackpropFilterV2;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "r", function () {
+        return Conv3DBackpropInputV2;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "s", function () {
+        return Cumsum;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "t", function () {
+        return DepthToSpace;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "u", function () {
+        return DepthwiseConv2dNative;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "v", function () {
+        return DepthwiseConv2dNativeBackpropFilter;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "w", function () {
+        return DepthwiseConv2dNativeBackpropInput;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "x", function () {
+        return Diag;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "y", function () {
+        return Div;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "z", function () {
+        return Elu;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "A", function () {
+        return EluGrad;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "B", function () {
+        return Equal;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "D", function () {
+        return FloorDiv;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "C", function () {
+        return Fill;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "F", function () {
+        return FusedBatchNorm;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "G", function () {
+        return GatherNd;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "H", function () {
+        return Greater;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "I", function () {
+        return GreaterEqual;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "J", function () {
+        return Identity;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "K", function () {
+        return Imag;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "N", function () {
+        return Less;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "O", function () {
+        return LessEqual;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "L", function () {
+        return LRN;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "M", function () {
+        return LRNBackprop;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "P", function () {
+        return Max;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "V", function () {
+        return Maximum;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "Q", function () {
+        return MaxPool;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "T", function () {
+        return MaxPoolBackprop;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "R", function () {
+        return MaxPool3D;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "S", function () {
+        return MaxPool3DBackprop;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "U", function () {
+        return MaxPoolWithArgmax;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "W", function () {
+        return Minimum;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "X", function () {
+        return Mod;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "Y", function () {
+        return Multiply;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "bb", function () {
+        return NotEqual;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "Z", function () {
+        return NonMaxSuppressionV3;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "ab", function () {
+        return NonMaxSuppressionV5;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "cb", function () {
+        return OneHot;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "db", function () {
+        return PadV2;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "eb", function () {
+        return Pool;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "fb", function () {
+        return Pow;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "gb", function () {
+        return Prelu;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "hb", function () {
+        return Real;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "ib", function () {
+        return Relu;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "jb", function () {
+        return Relu6;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "kb", function () {
+        return SelectV2;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "lb", function () {
+        return Selu;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "mb", function () {
+        return SpaceToBatchND;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "nb", function () {
+        return SplitV;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "pb", function () {
+        return SquaredDifference;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "ob", function () {
+        return Square;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "qb", function () {
+        return Sub;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "rb", function () {
+        return Tile;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "sb", function () {
+        return Transpose;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "E", function () {
+        return FromPixels;
+      });
+      const Add = "Add";
+      const AddN = "AddN";
+      const Atan2 = "Atan2";
+      const AvgPool = "AvgPool";
+      const AvgPoolBackprop = "AvgPoolBackprop";
+      const AvgPool3D = "AvgPool3D";
+      const AvgPool3DBackprop = "AvgPool3DBackprop";
+      const BatchMatMul = "BatchMatMul";
+      const BatchToSpaceND = "BatchToSpaceND";
+      const BroadcastTo = "BroadcastTo";
+      const Complex = "Complex";
+      const Concat = "Concat";
+      const Conv2D = "Conv2D";
+      const Conv2DBackpropFilter = "Conv2DBackpropFilter";
+      const Conv2DBackpropInput = "Conv2DBackpropInput";
+      const Conv3D = "Conv3D";
+      const Conv3DBackpropFilterV2 = "Conv3DBackpropFilterV2";
+      const Conv3DBackpropInputV2 = "Conv3DBackpropInputV2";
+      const Cumsum = "Cumsum";
+      const DepthToSpace = "DepthToSpace";
+      const DepthwiseConv2dNative = "DepthwiseConv2dNative";
+      const DepthwiseConv2dNativeBackpropFilter = "DepthwiseConv2dNativeBackpropFilter";
+      const DepthwiseConv2dNativeBackpropInput = "DepthwiseConv2dNativeBackpropInput";
+      const Diag = "Diag";
+      const Div = "Div";
+      const Elu = "Elu";
+      const EluGrad = "EluGrad";
+      const Equal = "Equal";
+      const FloorDiv = "FloorDiv";
+      const Fill = "Fill";
+      const FusedBatchNorm = "FusedBatchNorm";
+      const GatherNd = "GatherNd";
+      const Greater = "Greater";
+      const GreaterEqual = "GreaterEqual";
+      const Identity = "Identity";
+      const Imag = "Imag";
+      const Less = "Less";
+      const LessEqual = "LessEqual";
+      const LRN = "LRN";
+      const LRNBackprop = "LRNBackprop";
+      const Max = "Max";
+      const Maximum = "Maximum";
+      const MaxPool = "MaxPool";
+      const MaxPoolBackprop = "MaxPoolBackprop";
+      const MaxPool3D = "MaxPool3D";
+      const MaxPool3DBackprop = "MaxPool3DBackprop";
+      const MaxPoolWithArgmax = "MaxPoolWithArgmax";
+      const Minimum = "Minimum";
+      const Mod = "Mod";
+      const Multiply = "Multiply";
+      const NotEqual = "NotEqual";
+      const NonMaxSuppressionV3 = "NonMaxSuppressionV3";
+      const NonMaxSuppressionV5 = "NonMaxSuppressionV5";
+      const OneHot = "OneHot";
+      const PadV2 = "PadV2";
+      const Pool = "Pool";
+      const Pow = "Pow";
+      const Prelu = "Prelu";
+      const Real = "Real";
+      const Relu = "Relu";
+      const Relu6 = "Relu6";
+      const SelectV2 = "SelectV2";
+      const Selu = "Selu";
+      const SpaceToBatchND = "SpaceToBatchND";
+      const SplitV = "SplitV";
+      const SquaredDifference = "SquaredDifference";
+      const Square = "Square";
+      const Sub = "Sub";
+      const Tile = "Tile";
+      const Transpose = "Transpose";
+      /**
+       * TensorFlow.js-only kernels
+       */
+      const FromPixels = "FromPixels";
+      //# sourceMappingURL=kernel_names.js.map
+
+      /***/
+    },
+    /* 7 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "b", function () {
+        return /* binding */ tensor_TensorBuffer;
+      });
+      __webpack_require__.d(__webpack_exports__, "f", function () {
+        return /* binding */ setTensorTracker;
+      });
+      __webpack_require__.d(__webpack_exports__, "e", function () {
+        return /* binding */ setOpHandler;
+      });
+      __webpack_require__.d(__webpack_exports__, "d", function () {
+        return /* binding */ setDeprecationWarningFn;
+      });
+      __webpack_require__.d(__webpack_exports__, "a", function () {
+        return /* binding */ tensor_Tensor;
+      });
+      __webpack_require__.d(__webpack_exports__, "c", function () {
+        return /* binding */ tensor_Variable;
+      });
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/util.js
+      var util = __webpack_require__(1);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor_format.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // Maximum number of values before we decide to show ellipsis.
+      const FORMAT_LIMIT_NUM_VALS = 20;
+      // Number of first and last values to show when displaying a, b,...,y, z.
+      const FORMAT_NUM_FIRST_LAST_VALS = 3;
+      // Number of significant digits to show.
+      const FORMAT_NUM_SIG_DIGITS = 7;
+      function tensorToString(vals, shape, dtype, verbose) {
+        const strides = Object(util["computeStrides"])(shape);
+        const padPerCol = computeMaxSizePerColumn(vals, shape, dtype, strides);
+        const rank = shape.length;
+        const valsLines = subTensorToString(vals, shape, dtype, strides, padPerCol);
+        const lines = ["Tensor"];
+        if (verbose) {
+          lines.push(`  dtype: ${dtype}`);
+          lines.push(`  rank: ${rank}`);
+          lines.push(`  shape: [${shape}]`);
+          lines.push(`  values:`);
+        }
+        lines.push(valsLines.map((l) => "    " + l).join("\n"));
+        return lines.join("\n");
+      }
+      function computeMaxSizePerColumn(vals, shape, dtype, strides) {
+        const n = Object(util["sizeFromShape"])(shape);
+        const numCols = strides[strides.length - 1];
+        const padPerCol = new Array(numCols).fill(0);
+        const rank = shape.length;
+        const valuesOrTuples = dtype === "complex64" ? createComplexTuples(vals) : vals;
+        if (rank > 1) {
+          for (let row = 0; row < n / numCols; row++) {
+            const offset = row * numCols;
+            for (let j = 0; j < numCols; j++) {
+              padPerCol[j] = Math.max(
+                padPerCol[j],
+                valToString(valuesOrTuples[offset + j], 0, dtype).length
+              );
+            }
+          }
+        }
+        return padPerCol;
+      }
+      function valToString(val, pad, dtype) {
+        let valStr;
+        if (Array.isArray(val)) {
+          valStr =
+            `${parseFloat(val[0].toFixed(FORMAT_NUM_SIG_DIGITS))} + ` +
+            `${parseFloat(val[1].toFixed(FORMAT_NUM_SIG_DIGITS))}j`;
+        } else if (Object(util["isString"])(val)) {
+          valStr = `'${val}'`;
+        } else if (dtype === "bool") {
+          valStr = boolNumToString(val);
+        } else {
+          valStr = parseFloat(val.toFixed(FORMAT_NUM_SIG_DIGITS)).toString();
+        }
+        return Object(util["rightPad"])(valStr, pad);
+      }
+      function boolNumToString(v) {
+        return v === 0 ? "false" : "true";
+      }
+      function subTensorToString(vals, shape, dtype, strides, padPerCol, isLast = true) {
+        const storagePerElement = dtype === "complex64" ? 2 : 1;
+        const size = shape[0];
+        const rank = shape.length;
+        if (rank === 0) {
+          if (dtype === "complex64") {
+            const complexTuple = createComplexTuples(vals);
+            return [valToString(complexTuple[0], 0, dtype)];
+          }
+          if (dtype === "bool") {
+            return [boolNumToString(vals[0])];
+          }
+          return [vals[0].toString()];
+        }
+        if (rank === 1) {
+          if (size > FORMAT_LIMIT_NUM_VALS) {
+            const firstValsSize = FORMAT_NUM_FIRST_LAST_VALS * storagePerElement;
+            let firstVals = Array.from(vals.slice(0, firstValsSize));
+            let lastVals = Array.from(
+              vals.slice(
+                (size - FORMAT_NUM_FIRST_LAST_VALS) * storagePerElement,
+                size * storagePerElement
+              )
+            );
+            if (dtype === "complex64") {
+              firstVals = createComplexTuples(firstVals);
+              lastVals = createComplexTuples(lastVals);
+            }
+            return [
+              "[" +
+                firstVals.map((x, i) => valToString(x, padPerCol[i], dtype)).join(", ") +
+                ", ..., " +
+                lastVals
+                  .map((x, i) =>
+                    valToString(x, padPerCol[size - FORMAT_NUM_FIRST_LAST_VALS + i], dtype)
+                  )
+                  .join(", ") +
+                "]",
+            ];
+          }
+          const displayVals = dtype === "complex64" ? createComplexTuples(vals) : Array.from(vals);
+          return [
+            "[" + displayVals.map((x, i) => valToString(x, padPerCol[i], dtype)).join(", ") + "]",
+          ];
+        }
+        // The array is rank 2 or more.
+        const subshape = shape.slice(1);
+        const substrides = strides.slice(1);
+        const stride = strides[0] * storagePerElement;
+        const lines = [];
+        if (size > FORMAT_LIMIT_NUM_VALS) {
+          for (let i = 0; i < FORMAT_NUM_FIRST_LAST_VALS; i++) {
+            const start = i * stride;
+            const end = start + stride;
+            lines.push(
+              ...subTensorToString(
+                vals.slice(start, end),
+                subshape,
+                dtype,
+                substrides,
+                padPerCol,
+                false /* isLast */
+              )
+            );
+          }
+          lines.push("...");
+          for (let i = size - FORMAT_NUM_FIRST_LAST_VALS; i < size; i++) {
+            const start = i * stride;
+            const end = start + stride;
+            lines.push(
+              ...subTensorToString(
+                vals.slice(start, end),
+                subshape,
+                dtype,
+                substrides,
+                padPerCol,
+                i === size - 1 /* isLast */
+              )
+            );
+          }
+        } else {
+          for (let i = 0; i < size; i++) {
+            const start = i * stride;
+            const end = start + stride;
+            lines.push(
+              ...subTensorToString(
+                vals.slice(start, end),
+                subshape,
+                dtype,
+                substrides,
+                padPerCol,
+                i === size - 1 /* isLast */
+              )
+            );
+          }
+        }
+        const sep = rank === 2 ? "," : "";
+        lines[0] = "[" + lines[0] + sep;
+        for (let i = 1; i < lines.length - 1; i++) {
+          lines[i] = " " + lines[i] + sep;
+        }
+        let newLineSep = ",\n";
+        for (let i = 2; i < rank; i++) {
+          newLineSep += "\n";
+        }
+        lines[lines.length - 1] = " " + lines[lines.length - 1] + "]" + (isLast ? "" : newLineSep);
+        return lines;
+      }
+      function createComplexTuples(vals) {
+        const complexTuples = [];
+        for (let i = 0; i < vals.length; i += 2) {
+          complexTuples.push([vals[i], vals[i + 1]]);
+        }
+        return complexTuples;
+      }
+      //# sourceMappingURL=tensor_format.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-core/dist/tensor.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * A mutable object, similar to `tf.Tensor`, that allows users to set values
+       * at locations before converting to an immutable `tf.Tensor`.
+       *
+       * See `tf.buffer` for creating a tensor buffer.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+      class tensor_TensorBuffer {
+        constructor(shape, dtype, values) {
+          this.dtype = dtype;
+          this.shape = shape.slice();
+          this.size = util["sizeFromShape"](shape);
+          if (values != null) {
+            const n = values.length;
+            util["assert"](
+              n === this.size,
+              () =>
+                `Length of values '${n}' does not match the size ` +
+                `inferred by the shape '${this.size}'.`
+            );
+          }
+          if (dtype === "complex64") {
+            throw new Error(
+              `complex64 dtype TensorBuffers are not supported. Please create ` +
+                `a TensorBuffer for the real and imaginary parts separately and ` +
+                `call tf.complex(real, imag).`
+            );
+          }
+          this.values = values || util["getArrayFromDType"](dtype, this.size);
+          this.strides = Object(util["computeStrides"])(shape);
+        }
+        /**
+         * Sets a value in the buffer at a given location.
+         *
+         * @param value The value to set.
+         * @param locs  The location indices.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+        set(value, ...locs) {
+          if (locs.length === 0) {
+            locs = [0];
+          }
+          util["assert"](
+            locs.length === this.rank,
+            () =>
+              `The number of provided coordinates (${locs.length}) must ` +
+              `match the rank (${this.rank})`
+          );
+          const index = this.locToIndex(locs);
+          this.values[index] = value;
+        }
+        /**
+         * Returns the value in the buffer at the provided location.
+         *
+         * @param locs The location indices.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+        get(...locs) {
+          if (locs.length === 0) {
+            locs = [0];
+          }
+          let i = 0;
+          for (const loc of locs) {
+            if (loc < 0 || loc >= this.shape[i]) {
+              const msg =
+                `Requested out of range element at ${locs}. ` + `  Buffer shape=${this.shape}`;
+              throw new Error(msg);
+            }
+            i++;
+          }
+          let index = locs[locs.length - 1];
+          for (let i = 0; i < locs.length - 1; ++i) {
+            index += this.strides[i] * locs[i];
+          }
+          return this.values[index];
+        }
+        locToIndex(locs) {
+          if (this.rank === 0) {
+            return 0;
+          } else if (this.rank === 1) {
+            return locs[0];
+          }
+          let index = locs[locs.length - 1];
+          for (let i = 0; i < locs.length - 1; ++i) {
+            index += this.strides[i] * locs[i];
+          }
+          return index;
+        }
+        indexToLoc(index) {
+          if (this.rank === 0) {
+            return [];
+          } else if (this.rank === 1) {
+            return [index];
+          }
+          const locs = new Array(this.shape.length);
+          for (let i = 0; i < locs.length - 1; ++i) {
+            locs[i] = Math.floor(index / this.strides[i]);
+            index -= locs[i] * this.strides[i];
+          }
+          locs[locs.length - 1] = index;
+          return locs;
+        }
+        get rank() {
+          return this.shape.length;
+        }
+        /**
+         * Creates an immutable `tf.Tensor` object from the buffer.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+        toTensor() {
+          return trackerFn().makeTensor(this.values, this.shape, this.dtype);
+        }
+      }
+      // For tracking tensor creation and disposal.
+      let trackerFn = null;
+      // Used by chaining methods to call into ops.
+      let opHandler = null;
+      // Used to warn about deprecated methods.
+      let deprecationWarningFn = null;
+      // This here so that we can use this method on dev branches and keep the
+      // functionality at master.
+      // tslint:disable-next-line:no-unused-expression
+      [deprecationWarningFn];
+      /**
+       * An external consumer can register itself as the tensor tracker. This way
+       * the Tensor class can notify the tracker for every tensor created and
+       * disposed.
+       */
+      function setTensorTracker(fn) {
+        trackerFn = fn;
+      }
+      /**
+       * An external consumer can register itself as the op handler. This way the
+       * Tensor class can have chaining methods that call into ops via the op
+       * handler.
+       */
+      function setOpHandler(handler) {
+        opHandler = handler;
+      }
+      /**
+       * Sets the deprecation warning function to be used by this file. This way the
+       * Tensor class can be a leaf but still use the environment.
+       */
+      function setDeprecationWarningFn(fn) {
+        deprecationWarningFn = fn;
+      }
+      /**
+       * A `tf.Tensor` object represents an immutable, multidimensional array of
+       * numbers that has a shape and a data type.
+       *
+       * See `tf.tensor` for details on how to create a `tf.Tensor`.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+      class tensor_Tensor {
+        constructor(shape, dtype, dataId, id) {
+          /** Whether this tensor has been globally kept. */
+          this.kept = false;
+          this.isDisposedInternal = false;
+          this.shape = shape.slice();
+          this.dtype = dtype || "float32";
+          this.size = util["sizeFromShape"](shape);
+          this.strides = Object(util["computeStrides"])(shape);
+          this.dataId = dataId;
+          this.id = id;
+          this.rankType = this.rank < 5 ? this.rank.toString() : "higher";
+        }
+        /** Flatten a Tensor to a 1D array. */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        flatten() {
+          this.throwIfDisposed();
+          return this.as1D();
+        }
+        /** Converts a size-1 `tf.Tensor` to a `tf.Scalar`. */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        asScalar() {
+          this.throwIfDisposed();
+          util["assert"](this.size === 1, () => "The array must have only 1 element.");
+          return this.reshape([]);
+        }
+        /** Converts a `tf.Tensor` to a `tf.Tensor1D`. */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        as1D() {
+          this.throwIfDisposed();
+          return this.reshape([this.size]);
+        }
+        /**
+         * Converts a `tf.Tensor` to a `tf.Tensor2D`.
+         *
+         * @param rows Number of rows in `tf.Tensor2D`.
+         * @param columns Number of columns in `tf.Tensor2D`.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        as2D(rows, columns) {
+          this.throwIfDisposed();
+          return this.reshape([rows, columns]);
+        }
+        /**
+         * Converts a `tf.Tensor` to a `tf.Tensor3D`.
+         *
+         * @param rows Number of rows in `tf.Tensor3D`.
+         * @param columns Number of columns in `tf.Tensor3D`.
+         * @param depth Depth of `tf.Tensor3D`.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        as3D(rows, columns, depth) {
+          this.throwIfDisposed();
+          return this.reshape([rows, columns, depth]);
+        }
+        /**
+         * Converts a `tf.Tensor` to a `tf.Tensor4D`.
+         *
+         * @param rows Number of rows in `tf.Tensor4D`.
+         * @param columns Number of columns in `tf.Tensor4D`.
+         * @param depth Depth of `tf.Tensor4D`.
+         * @param depth2 4th dimension of `tf.Tensor4D`.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        as4D(rows, columns, depth, depth2) {
+          this.throwIfDisposed();
+          return this.reshape([rows, columns, depth, depth2]);
+        }
+        /**
+         * Converts a `tf.Tensor` to a `tf.Tensor5D`.
+         *
+         * @param rows Number of rows in `tf.Tensor5D`.
+         * @param columns Number of columns in `tf.Tensor5D`.
+         * @param depth Depth of `tf.Tensor5D`.
+         * @param depth2 4th dimension of `tf.Tensor5D`.
+         * @param depth3 5th dimension of 'tf.Tensor5D'
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        as5D(rows, columns, depth, depth2, depth3) {
+          this.throwIfDisposed();
+          return this.reshape([rows, columns, depth, depth2, depth3]);
+        }
+        /**
+         * Casts a `tf.Tensor` to a specified dtype.
+         *
+         * @param dtype Data-type to cast the tensor to.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        asType(dtype) {
+          this.throwIfDisposed();
+          return opHandler.cast(this, dtype);
+        }
+        get rank() {
+          return this.shape.length;
+        }
+        /**
+         * Returns a promise of `tf.TensorBuffer` that holds the underlying data.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        async buffer() {
+          const vals = await this.data();
+          return opHandler.buffer(this.shape, this.dtype, vals);
+        }
+        /** Returns a `tf.TensorBuffer` that holds the underlying data. */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        bufferSync() {
+          return opHandler.buffer(this.shape, this.dtype, this.dataSync());
+        }
+        /**
+         * Returns the tensor data as a nested array. The transfer of data is done
+         * asynchronously.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        async array() {
+          const vals = await this.data();
+          return Object(util["toNestedArray"])(this.shape, vals);
+        }
+        /**
+         * Returns the tensor data as a nested array. The transfer of data is done
+         * synchronously.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        arraySync() {
+          return Object(util["toNestedArray"])(this.shape, this.dataSync());
+        }
+        /**
+         * Asynchronously downloads the values from the `tf.Tensor`. Returns a
+         * promise of `TypedArray` that resolves when the computation has finished.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        async data() {
+          this.throwIfDisposed();
+          const data = trackerFn().read(this.dataId);
+          if (this.dtype === "string") {
+            const bytes = await data;
+            try {
+              return bytes.map((b) => util["decodeString"](b));
+            } catch (_a) {
+              throw new Error(
+                "Failed to decode the string bytes into utf-8. " +
+                  "To get the original bytes, call tensor.bytes()."
+              );
+            }
+          }
+          return data;
+        }
+        /**
+         * Synchronously downloads the values from the `tf.Tensor`. This blocks the
+         * UI thread until the values are ready, which can cause performance issues.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        dataSync() {
+          this.throwIfDisposed();
+          const data = trackerFn().readSync(this.dataId);
+          if (this.dtype === "string") {
+            try {
+              return data.map((b) => util["decodeString"](b));
+            } catch (_a) {
+              throw new Error(
+                "Failed to decode the string bytes into utf-8. " +
+                  "To get the original bytes, call tensor.bytes()."
+              );
+            }
+          }
+          return data;
+        }
+        /** Returns the underlying bytes of the tensor's data. */
+        async bytes() {
+          this.throwIfDisposed();
+          const data = await trackerFn().read(this.dataId);
+          if (this.dtype === "string") {
+            return data;
+          } else {
+            return new Uint8Array(data.buffer);
+          }
+        }
+        /**
+         * Disposes `tf.Tensor` from memory.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        dispose() {
+          if (this.isDisposed) {
+            return;
+          }
+          trackerFn().disposeTensor(this);
+          this.isDisposedInternal = true;
+        }
+        get isDisposed() {
+          return this.isDisposedInternal;
+        }
+        throwIfDisposed() {
+          if (this.isDisposed) {
+            throw new Error(`Tensor is disposed.`);
+          }
+        }
+        /** Casts the array to type `float32` */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        toFloat() {
+          return this.asType("float32");
+        }
+        /** Casts the array to type `int32` */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        toInt() {
+          return this.asType("int32");
+        }
+        /** Casts the array to type `bool` */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        toBool() {
+          return this.asType("bool");
+        }
+        /**
+         * Prints the `tf.Tensor`. See `tf.print` for details.
+         *
+         * @param verbose Whether to print verbose information about the tensor,
+         *    including dtype and size.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        print(verbose = false) {
+          return opHandler.print(this, verbose);
+        }
+        /**
+         * Reshapes the tensor into the provided shape.
+         * See `tf.reshape` for more details.
+         *
+         * @param newShape An array of integers defining the output tensor shape.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        reshape(newShape) {
+          this.throwIfDisposed();
+          return opHandler.reshape(this, newShape);
+        }
+        /**
+         * Reshapes the tensor into the shape of the provided tensor.
+         *
+         * @param x The tensor of required shape.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        reshapeAs(x) {
+          this.throwIfDisposed();
+          return this.reshape(x.shape);
+        }
+        /**
+         * Returns a `tf.Tensor` that has expanded rank, by inserting a dimension
+         * into the tensor's shape. See `tf.expandDims` for details.
+         *
+         * @param axis The dimension index at which to insert shape of 1. Defaults to
+         *     0 (the first dimension).
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        expandDims(axis = 0) {
+          return opHandler.expandDims(this, axis);
+        }
+        /**
+         * Returns a `tf.Tensor` with dimensions of size 1 removed from the shape.
+         * See `tf.squeeze` for more details.
+         *
+         * @param axis A list of numbers. If specified, only squeezes the
+         *    dimensions listed. The dimension index starts at 0. It is an error to
+         *    squeeze a dimension that is not 1.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        squeeze(axis) {
+          this.throwIfDisposed();
+          return opHandler.squeeze(this, axis);
+        }
+        /** Returns a copy of the tensor. See `tf.clone` for details. */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        clone() {
+          this.throwIfDisposed();
+          return opHandler.clone(this);
+        }
+        /**
+         * Returns a human-readable description of the tensor. Useful for logging.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        toString(verbose = false) {
+          const vals = this.dataSync();
+          return tensorToString(vals, this.shape, this.dtype, verbose);
+        }
+        // Below is chain API that is not exposed to docs to avoid repetition. To
+        // expose a method, move it above this comment and add @doc and jsdoc.
+        gather(indices, axis = 0) {
+          this.throwIfDisposed();
+          return opHandler.gather(this, indices, axis);
+        }
+        norm(ord = "euclidean", axis = null, keepDims = false) {
+          this.throwIfDisposed();
+          return opHandler.norm(this, ord, axis, keepDims);
+        }
+        slice(begin, size) {
+          this.throwIfDisposed();
+          return opHandler.slice(this, begin, size);
+        }
+        reverse(axis) {
+          this.throwIfDisposed();
+          return opHandler.reverse(this, axis);
+        }
+        stack(x, axis = 0) {
+          return opHandler.stack([this, x], axis);
+        }
+        unstack(axis = 0) {
+          return opHandler.unstack(this, axis);
+        }
+        // Reduction ops.
+        all(axis = null, keepDims = false) {
+          this.throwIfDisposed();
+          return opHandler.all(this, axis, keepDims);
+        }
+        any(axis = null, keepDims = false) {
+          this.throwIfDisposed();
+          return opHandler.any(this, axis, keepDims);
+        }
+        logSumExp(axis = null, keepDims = false) {
+          this.throwIfDisposed();
+          return opHandler.logSumExp(this, axis, keepDims);
+        }
+        sum(axis = null, keepDims = false) {
+          this.throwIfDisposed();
+          return opHandler.sum(this, axis, keepDims);
+        }
+        prod(axis = null, keepDims = false) {
+          this.throwIfDisposed();
+          return opHandler.prod(this, axis, keepDims);
+        }
+        mean(axis = null, keepDims = false) {
+          this.throwIfDisposed();
+          return opHandler.mean(this, axis, keepDims);
+        }
+        min(axis = null, keepDims = false) {
+          this.throwIfDisposed();
+          return opHandler.min(this, axis, keepDims);
+        }
+        argMin(axis = null) {
+          this.throwIfDisposed();
+          return opHandler.argMin(this, axis);
+        }
+        argMax(axis = null) {
+          this.throwIfDisposed();
+          return opHandler.argMax(this, axis);
+        }
+        // Transformations
+        cast(dtype) {
+          this.throwIfDisposed();
+          return opHandler.cast(this, dtype);
+        }
+        // Binary ops.
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        addStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.addStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        subStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.subStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        powStrict(exp) {
+          this.throwIfDisposed();
+          return opHandler.powStrict(this, exp);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        mulStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.mulStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        divStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.divStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        minimumStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.minimumStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        maximumStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.maximumStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        modStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.modStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        squaredDifferenceStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.squaredDifferenceStrict(this, x);
+        }
+        // Compare ops.
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        notEqualStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.notEqualStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        lessStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.lessStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        equalStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.equalStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        lessEqualStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.lessEqualStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        greaterStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.greaterStrict(this, x);
+        }
+        /**
+         * @deprecated strict variants of ops have been deprecated
+         */
+        greaterEqualStrict(x) {
+          this.throwIfDisposed();
+          return opHandler.greaterEqualStrict(this, x);
+        }
+        // Compare ops.
+        logicalAnd(x) {
+          this.throwIfDisposed();
+          return opHandler.logicalAnd(this, x);
+        }
+        logicalOr(x) {
+          this.throwIfDisposed();
+          return opHandler.logicalOr(this, x);
+        }
+        logicalNot() {
+          this.throwIfDisposed();
+          return opHandler.logicalNot(this);
+        }
+        logicalXor(x) {
+          this.throwIfDisposed();
+          return opHandler.logicalXor(this, x);
+        }
+        where(condition, x) {
+          this.throwIfDisposed();
+          return opHandler.where(condition, this, x);
+        }
+        // Unary ops.
+        neg() {
+          this.throwIfDisposed();
+          return opHandler.neg(this);
+        }
+        ceil() {
+          this.throwIfDisposed();
+          return opHandler.ceil(this);
+        }
+        floor() {
+          this.throwIfDisposed();
+          return opHandler.floor(this);
+        }
+        sign() {
+          this.throwIfDisposed();
+          return opHandler.sign(this);
+        }
+        isNaN() {
+          this.throwIfDisposed();
+          return opHandler.isNaN(this);
+        }
+        isInf() {
+          this.throwIfDisposed();
+          return opHandler.isInf(this);
+        }
+        isFinite() {
+          this.throwIfDisposed();
+          return opHandler.isFinite(this);
+        }
+        exp() {
+          this.throwIfDisposed();
+          return opHandler.exp(this);
+        }
+        expm1() {
+          this.throwIfDisposed();
+          return opHandler.expm1(this);
+        }
+        log() {
+          this.throwIfDisposed();
+          return opHandler.log(this);
+        }
+        log1p() {
+          this.throwIfDisposed();
+          return opHandler.log1p(this);
+        }
+        sqrt() {
+          this.throwIfDisposed();
+          return opHandler.sqrt(this);
+        }
+        rsqrt() {
+          this.throwIfDisposed();
+          return opHandler.rsqrt(this);
+        }
+        square() {
+          this.throwIfDisposed();
+          return opHandler.square(this);
+        }
+        reciprocal() {
+          this.throwIfDisposed();
+          return opHandler.reciprocal(this);
+        }
+        abs() {
+          this.throwIfDisposed();
+          return opHandler.abs(this);
+        }
+        clipByValue(min, max) {
+          this.throwIfDisposed();
+          return opHandler.clipByValue(this, min, max);
+        }
+        sigmoid() {
+          this.throwIfDisposed();
+          return opHandler.sigmoid(this);
+        }
+        logSigmoid() {
+          this.throwIfDisposed();
+          return opHandler.logSigmoid(this);
+        }
+        softplus() {
+          this.throwIfDisposed();
+          return opHandler.softplus(this);
+        }
+        zerosLike() {
+          this.throwIfDisposed();
+          return opHandler.zerosLike(this);
+        }
+        onesLike() {
+          this.throwIfDisposed();
+          return opHandler.onesLike(this);
+        }
+        sin() {
+          this.throwIfDisposed();
+          return opHandler.sin(this);
+        }
+        cos() {
+          this.throwIfDisposed();
+          return opHandler.cos(this);
+        }
+        tan() {
+          this.throwIfDisposed();
+          return opHandler.tan(this);
+        }
+        asin() {
+          this.throwIfDisposed();
+          return opHandler.asin(this);
+        }
+        acos() {
+          this.throwIfDisposed();
+          return opHandler.acos(this);
+        }
+        atan() {
+          this.throwIfDisposed();
+          return opHandler.atan(this);
+        }
+        sinh() {
+          this.throwIfDisposed();
+          return opHandler.sinh(this);
+        }
+        cosh() {
+          this.throwIfDisposed();
+          return opHandler.cosh(this);
+        }
+        tanh() {
+          this.throwIfDisposed();
+          return opHandler.tanh(this);
+        }
+        asinh() {
+          this.throwIfDisposed();
+          return opHandler.asinh(this);
+        }
+        acosh() {
+          this.throwIfDisposed();
+          return opHandler.acosh(this);
+        }
+        atanh() {
+          this.throwIfDisposed();
+          return opHandler.atanh(this);
+        }
+        erf() {
+          this.throwIfDisposed();
+          return opHandler.erf(this);
+        }
+        round() {
+          this.throwIfDisposed();
+          return opHandler.round(this);
+        }
+        step(alpha = 0.0) {
+          this.throwIfDisposed();
+          return opHandler.step(this, alpha);
+        }
+        softmax(dim = -1) {
+          this.throwIfDisposed();
+          return opHandler.softmax(this, dim);
+        }
+        logSoftmax(axis = -1) {
+          this.throwIfDisposed();
+          return opHandler.logSoftmax(this, axis);
+        }
+        // Image ops.
+        resizeBilinear(newShape2D, alignCorners = false) {
+          this.throwIfDisposed();
+          return opHandler.image.resizeBilinear(this, newShape2D, alignCorners);
+        }
+        resizeNearestNeighbor(newShape2D, alignCorners = false) {
+          this.throwIfDisposed();
+          return opHandler.image.resizeNearestNeighbor(this, newShape2D, alignCorners);
+        }
+        // Pooling.
+        variable(trainable = true, name, dtype) {
+          this.throwIfDisposed();
+          return trackerFn().makeVariable(this, trainable, name, dtype);
+        }
+        unsortedSegmentSum(segmentIds, numSegments) {
+          this.throwIfDisposed();
+          return opHandler.unsortedSegmentSum(this, segmentIds, numSegments);
+        }
+        topk(k = 1, sorted = true) {
+          this.throwIfDisposed();
+          return opHandler.topk(this, k, sorted);
+        }
+        stridedSlice(
+          begin,
+          end,
+          strides,
+          beginMask = 0,
+          endMask = 0,
+          ellipsisMask = 0,
+          newAxisMask = 0,
+          shrinkAxisMask = 0
+        ) {
+          this.throwIfDisposed();
+          return opHandler.stridedSlice(
+            this,
+            begin,
+            end,
+            strides,
+            beginMask,
+            endMask,
+            ellipsisMask,
+            newAxisMask,
+            shrinkAxisMask
+          );
+        }
+        fft() {
+          this.throwIfDisposed();
+          return opHandler.spectral.fft(this);
+        }
+        ifft() {
+          this.throwIfDisposed();
+          return opHandler.spectral.ifft(this);
+        }
+        rfft() {
+          this.throwIfDisposed();
+          return opHandler.spectral.rfft(this);
+        }
+        irfft() {
+          this.throwIfDisposed();
+          return opHandler.spectral.irfft(this);
+        }
+      }
+      Object.defineProperty(tensor_Tensor, Symbol.hasInstance, {
+        value: (instance) => {
+          return (
+            !!instance &&
+            instance.dataId != null &&
+            instance.shape != null &&
+            instance.dtype != null
+          );
+        },
+      });
+      /**
+       * A mutable `tf.Tensor`, useful for persisting state, e.g. for training.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+      class tensor_Variable extends tensor_Tensor {
+        constructor(initialValue, trainable, name, tensorId) {
+          super(initialValue.shape, initialValue.dtype, initialValue.dataId, tensorId);
+          this.trainable = trainable;
+          this.name = name;
+        }
+        /**
+         * Assign a new `tf.Tensor` to this variable. The new `tf.Tensor` must have
+         * the same shape and dtype as the old `tf.Tensor`.
+         *
+         * @param newValue New tensor to be assigned to this variable.
+         */
+        /** @doc {heading: 'Tensors', subheading: 'Classes'} */
+        assign(newValue) {
+          if (newValue.dtype !== this.dtype) {
+            throw new Error(
+              `dtype of the new value (${newValue.dtype}) and ` +
+                `previous value (${this.dtype}) must match`
+            );
+          }
+          if (!util["arraysEqual"](newValue.shape, this.shape)) {
+            throw new Error(
+              `shape of the new value (${newValue.shape}) and ` +
+                `previous value (${this.shape}) must match`
+            );
+          }
+          trackerFn().disposeTensor(this);
+          this.dataId = newValue.dataId;
+          trackerFn().incRef(this, null /* backend */);
+        }
+        dispose() {
+          trackerFn().disposeVariable(this);
+          this.isDisposedInternal = true;
+        }
+      }
+      Object.defineProperty(tensor_Variable, Symbol.hasInstance, {
+        value: (instance) => {
+          return (
+            instance instanceof tensor_Tensor &&
+            instance.assign != null &&
+            instance.assign instanceof Function
+          );
+        },
+      });
+      //# sourceMappingURL=tensor.js.map
+
+      /***/
+    },
+    /* 8 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return linspace;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return ones;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
+        return range;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
+        return scalar;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
+        return tensor;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
+        return tensor1d;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "h", function () {
+        return tensor2d;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "i", function () {
+        return tensor3d;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "j", function () {
+        return tensor4d;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "k", function () {
+        return tensor5d;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "l", function () {
+        return tensor6d;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "m", function () {
+        return variable;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "n", function () {
+        return zeros;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return onesLike;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "o", function () {
+        return zerosLike;
+      });
+      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
+      /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(10);
+      /* harmony import */ var _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__ =
+        __webpack_require__(3);
+      /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(1);
+      /* harmony import */ var _complex__WEBPACK_IMPORTED_MODULE_4__ = __webpack_require__(18);
+      /* harmony import */ var _imag__WEBPACK_IMPORTED_MODULE_5__ = __webpack_require__(25);
+      /* harmony import */ var _operation__WEBPACK_IMPORTED_MODULE_6__ = __webpack_require__(4);
+      /* harmony import */ var _real__WEBPACK_IMPORTED_MODULE_7__ = __webpack_require__(22);
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Creates a `tf.Tensor` with the provided values, shape and dtype.
+       *
+       * ```js
+       * // Pass an array of values to create a vector.
+       * tf.tensor([1, 2, 3, 4]).print();
+       * ```
+       *
+       * ```js
+       * // Pass a nested array of values to make a matrix or a higher
+       * // dimensional tensor.
+       * tf.tensor([[1, 2], [3, 4]]).print();
+       * ```
+       *
+       * ```js
+       * // Pass a flat array and specify a shape yourself.
+       * tf.tensor([1, 2, 3, 4], [2, 2]).print();
+       * ```
+       *
+       * @param values The values of the tensor. Can be nested array of numbers,
+       *     or a flat array, or a `TypedArray`. If the values are strings,
+       *     they will be encoded as utf-8 and kept as `Uint8Array[]`.
+       * @param shape The shape of the tensor. Optional. If not provided,
+       *   it is inferred from `values`.
+       * @param dtype The data type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function tensor(values, shape, dtype) {
+        const inferredShape = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
+        )(values, dtype);
+        return makeTensor(values, shape, inferredShape, dtype);
+      }
+      /** This is shared code across all tensor creation methods. */
+      function makeTensor(values, shape, inferredShape, dtype) {
+        if (dtype == null) {
+          dtype = Object(_util__WEBPACK_IMPORTED_MODULE_3__["inferDtype"])(values);
+        }
+        if (dtype === "complex64") {
+          throw new Error(
+            `Cannot construct a complex64 tensor directly. ` + `Please use tf.complex(real, imag).`
+          );
+        }
+        if (
+          !Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(values) &&
+          !Array.isArray(values) &&
+          typeof values !== "number" &&
+          typeof values !== "boolean" &&
+          typeof values !== "string"
+        ) {
+          throw new Error(
+            "values passed to tensor(values) must be a number/boolean/string or " +
+              "an array of numbers/booleans/strings, or a TypedArray"
+          );
+        }
+        if (shape != null) {
+          Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNegativeIntegerDimensions"])(shape);
+          const providedSize = Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(shape);
+          const inferredSize = Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(
+            inferredShape
+          );
+          Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
+            providedSize === inferredSize,
+            () =>
+              `Based on the provided shape, [${shape}], the tensor should have ` +
+              `${providedSize} values but has ${inferredSize}`
+          );
+          for (let i = 0; i < inferredShape.length; ++i) {
+            const inferred = inferredShape[i];
+            const flatDimsDontMatch =
+              i === inferredShape.length - 1
+                ? inferred !==
+                  Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(shape.slice(i))
+                : true;
+            Object(_util__WEBPACK_IMPORTED_MODULE_3__["assert"])(
+              inferredShape[i] === shape[i] || !flatDimsDontMatch,
+              () =>
+                `Error creating a new Tensor. Inferred shape ` +
+                `(${inferredShape}) does not match the provided ` +
+                `shape (${shape}). `
+            );
+          }
+        }
+        if (
+          !Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(values) &&
+          !Array.isArray(values)
+        ) {
+          values = [values];
+        }
+        shape = shape || inferredShape;
+        values =
+          dtype !== "string"
+            ? Object(_util__WEBPACK_IMPORTED_MODULE_3__["toTypedArray"])(
+                values,
+                dtype,
+                Object(_environment__WEBPACK_IMPORTED_MODULE_1__[/* env */ "c"])().getBool("DEBUG")
+              )
+            : Object(_util__WEBPACK_IMPORTED_MODULE_3__["flatten"])(values, [], true);
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeTensor(
+          values,
+          shape,
+          dtype
+        );
+      }
+      /**
+       * Creates rank-0 `tf.Tensor` (scalar) with the provided value and dtype.
+       *
+       * The same functionality can be achieved with `tf.tensor`, but in general
+       * we recommend using `tf.scalar` as it makes the code more readable.
+       *
+       * ```js
+       * tf.scalar(3.14).print();
+       * ```
+       *
+       * @param value The value of the scalar.
+       * @param dtype The data type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function scalar(value, dtype) {
+        if (
+          ((Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(value) &&
+            dtype !== "string") ||
+            Array.isArray(value)) &&
+          dtype !== "complex64"
+        ) {
+          throw new Error(
+            "Error creating a new Scalar: value must be a primitive " + "(number|boolean|string)"
+          );
+        }
+        if (
+          dtype === "string" &&
+          Object(_util__WEBPACK_IMPORTED_MODULE_3__["isTypedArray"])(value) &&
+          !(value instanceof Uint8Array)
+        ) {
+          throw new Error(
+            "When making a scalar from encoded string, " + "the value must be `Uint8Array`."
+          );
+        }
+        const shape = [];
+        const inferredShape = [];
+        return makeTensor(value, shape, inferredShape, dtype);
+      }
+      /**
+       * Creates rank-1 `tf.Tensor` with the provided values, shape and dtype.
+       *
+       * The same functionality can be achieved with `tf.tensor`, but in general
+       * we recommend using `tf.tensor1d` as it makes the code more readable.
+       *
+       * ```js
+       * tf.tensor1d([1, 2, 3]).print();
+       * ```
+       *
+       * @param values The values of the tensor. Can be array of numbers,
+       *     or a `TypedArray`.
+       * @param dtype The data type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function tensor1d(values, dtype) {
+        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
+        const inferredShape = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
+        )(values, dtype);
+        if (inferredShape.length !== 1) {
+          throw new Error("tensor1d() requires values to be a flat/TypedArray");
+        }
+        const shape = null;
+        return makeTensor(values, shape, inferredShape, dtype);
+      }
+      /**
+       * Creates rank-2 `tf.Tensor` with the provided values, shape and dtype.
+       *
+       * The same functionality can be achieved with `tf.tensor`, but in general
+       * we recommend using `tf.tensor2d` as it makes the code more readable.
+       *
+       *  ```js
+       * // Pass a nested array.
+       * tf.tensor2d([[1, 2], [3, 4]]).print();
+       * ```
+       * ```js
+       * // Pass a flat array and specify a shape.
+       * tf.tensor2d([1, 2, 3, 4], [2, 2]).print();
+       * ```
+       *
+       * @param values The values of the tensor. Can be nested array of numbers,
+       *     or a flat array, or a `TypedArray`.
+       * @param shape The shape of the tensor. If not provided, it is inferred from
+       *     `values`.
+       * @param dtype The data type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function tensor2d(values, shape, dtype) {
+        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
+        if (shape != null && shape.length !== 2) {
+          throw new Error("tensor2d() requires shape to have two numbers");
+        }
+        const inferredShape = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
+        )(values, dtype);
+        if (inferredShape.length !== 2 && inferredShape.length !== 1) {
+          throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");
+        }
+        if (inferredShape.length === 1 && shape == null) {
+          throw new Error(
+            "tensor2d() requires shape to be provided when `values` " + "are a flat/TypedArray"
+          );
+        }
+        return makeTensor(values, shape, inferredShape, dtype);
+      }
+      /**
+       * Creates rank-3 `tf.Tensor` with the provided values, shape and dtype.
+       *
+       * The same functionality can be achieved with `tf.tensor`, but in general
+       * we recommend using `tf.tensor3d` as it makes the code more readable.
+       *
+       *  ```js
+       * // Pass a nested array.
+       * tf.tensor3d([[[1], [2]], [[3], [4]]]).print();
+       * ```
+       * ```js
+       * // Pass a flat array and specify a shape.
+       * tf.tensor3d([1, 2, 3, 4], [2, 2, 1]).print();
+       * ```
+       *
+       * @param values The values of the tensor. Can be nested array of numbers,
+       *     or a flat array, or a `TypedArray`.
+       * @param shape The shape of the tensor. If not provided,  it is inferred from
+       *     `values`.
+       * @param dtype The data type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function tensor3d(values, shape, dtype) {
+        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
+        if (shape != null && shape.length !== 3) {
+          throw new Error("tensor3d() requires shape to have three numbers");
+        }
+        const inferredShape = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
+        )(values, dtype);
+        if (inferredShape.length !== 3 && inferredShape.length !== 1) {
+          throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");
+        }
+        if (inferredShape.length === 1 && shape == null) {
+          throw new Error(
+            "tensor3d() requires shape to be provided when `values` " + "are a flat array"
+          );
+        }
+        return makeTensor(values, shape, inferredShape, dtype);
+      }
+      /**
+       * Creates rank-4 `tf.Tensor` with the provided values, shape and dtype.
+       *
+       * The same functionality can be achieved with `tf.tensor`, but in general
+       * we recommend using `tf.tensor4d` as it makes the code more readable.
+       *
+       *  ```js
+       * // Pass a nested array.
+       * tf.tensor4d([[[[1], [2]], [[3], [4]]]]).print();
+       * ```
+       * ```js
+       * // Pass a flat array and specify a shape.
+       * tf.tensor4d([1, 2, 3, 4], [1, 2, 2, 1]).print();
+       * ```
+       *
+       * @param values The values of the tensor. Can be nested array of numbers,
+       *     or a flat array, or a `TypedArray`.
+       * @param shape The shape of the tensor. Optional. If not provided,
+       *   it is inferred from `values`.
+       * @param dtype The data type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function tensor4d(values, shape, dtype) {
+        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
+        if (shape != null && shape.length !== 4) {
+          throw new Error("tensor4d() requires shape to have four numbers");
+        }
+        const inferredShape = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
+        )(values, dtype);
+        if (inferredShape.length !== 4 && inferredShape.length !== 1) {
+          throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");
+        }
+        if (inferredShape.length === 1 && shape == null) {
+          throw new Error(
+            "tensor4d() requires shape to be provided when `values` " + "are a flat array"
+          );
+        }
+        return makeTensor(values, shape, inferredShape, dtype);
+      }
+      /**
+       * Creates rank-5 `tf.Tensor` with the provided values, shape and dtype.
+       *
+       * The same functionality can be achieved with `tf.tensor`, but in general
+       * we recommend using `tf.tensor5d` as it makes the code more readable.
+       *
+       *  ```js
+       * // Pass a nested array.
+       * tf.tensor5d([[[[[1], [2]], [[3], [4]]]]]).print();
+       * ```
+       * ```js
+       * // Pass a flat array and specify a shape.
+       * tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]).print();
+       * ```
+       *
+       * @param values The values of the tensor. Can be nested array of numbers,
+       *     or a flat array, or a `TypedArray`.
+       * @param shape The shape of the tensor. Optional. If not provided,
+       *   it is inferred from `values`.
+       * @param dtype The data type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function tensor5d(values, shape, dtype) {
+        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
+        if (shape != null && shape.length !== 5) {
+          throw new Error("tensor5d() requires shape to have five numbers");
+        }
+        const inferredShape = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
+        )(values, dtype);
+        if (inferredShape.length !== 5 && inferredShape.length !== 1) {
+          throw new Error(
+            "tensor5d() requires values to be " + "number[][][][][] or flat/TypedArray"
+          );
+        }
+        if (inferredShape.length === 1 && shape == null) {
+          throw new Error(
+            "tensor5d() requires shape to be provided when `values` " + "are a flat array"
+          );
+        }
+        return makeTensor(values, shape, inferredShape, dtype);
+      }
+      /**
+       * Creates rank-6 `tf.Tensor` with the provided values, shape and dtype.
+       *
+       * The same functionality can be achieved with `tf.tensor`, but in general
+       * we recommend using `tf.tensor6d` as it makes the code more readable.
+       *
+       *  ```js
+       * // Pass a nested array.
+       * tf.tensor6d([[[[[[1],[2]],[[3],[4]]],[[[5],[6]],[[7],[8]]]]]]).print();
+       * ```
+       * ```js
+       * // Pass a flat array and specify a shape.
+       * tf.tensor6d([1, 2, 3, 4, 5, 6, 7, 8], [1, 1, 2, 2, 2, 1]).print();
+       * ```
+       *
+       * @param values The values of the tensor. Can be nested array of numbers,
+       *     or a flat array, or a `TypedArray`.
+       * @param shape The shape of the tensor. Optional. If not provided,
+       *   it is inferred from `values`.
+       * @param dtype The data type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function tensor6d(values, shape, dtype) {
+        Object(_util__WEBPACK_IMPORTED_MODULE_3__["assertNonNull"])(values);
+        if (shape != null && shape.length !== 6) {
+          throw new Error("tensor6d() requires shape to have six numbers");
+        }
+        const inferredShape = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* inferShape */ "c"]
+        )(values, dtype);
+        if (inferredShape.length !== 6 && inferredShape.length !== 1) {
+          throw new Error(
+            "tensor6d() requires values to be number[][][][][][] or " + "flat/TypedArray"
+          );
+        }
+        if (inferredShape.length === 1 && shape == null) {
+          throw new Error(
+            "tensor6d() requires shape to be provided when `values` " + "are a flat array"
+          );
+        }
+        shape = shape || inferredShape;
+        return makeTensor(values, shape, inferredShape, dtype);
+      }
+      /**
+       * Creates a new variable with the provided initial value.
+       * ```js
+       * const x = tf.variable(tf.tensor([1, 2, 3]));
+       * x.assign(tf.tensor([4, 5, 6]));
+       *
+       * x.print();
+       * ```
+       *
+       * @param initialValue Initial value for the tensor.
+       * @param trainable If true, optimizers are allowed to update it.
+       * @param name Name of the variable. Defaults to a unique id.
+       * @param dtype If set, initialValue will be converted to the given type.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function variable(initialValue, trainable = true, name, dtype) {
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeVariable(
+          initialValue,
+          trainable,
+          name,
+          dtype
+        );
+      }
+      /**
+       * Creates a `tf.Tensor` with all elements set to 1.
+       *
+       * ```js
+       * tf.ones([2, 2]).print();
+       * ```
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param dtype The type of an element in the resulting tensor. Defaults to
+       *     'float'.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function ones(shape, dtype = "float32") {
+        if (dtype === "complex64") {
+          const real = ones(shape, "float32");
+          const imag = zeros(shape, "float32");
+          return Object(_complex__WEBPACK_IMPORTED_MODULE_4__[/* complex */ "a"])(real, imag);
+        }
+        const values = Object(_util__WEBPACK_IMPORTED_MODULE_3__["makeOnesTypedArray"])(
+          Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(shape),
+          dtype
+        );
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeTensor(
+          values,
+          shape,
+          dtype
+        );
+      }
+      /**
+       * Creates a `tf.Tensor` with all elements set to 0.
+       *
+       * ```js
+       * tf.zeros([2, 2]).print();
+       * ```
+       *
+       * @param shape An array of integers defining the output tensor shape.
+       * @param dtype The type of an element in the resulting tensor. Can
+       *     be 'float32', 'int32' or 'bool'. Defaults to 'float'.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function zeros(shape, dtype = "float32") {
+        if (dtype === "complex64") {
+          const real = zeros(shape, "float32");
+          const imag = zeros(shape, "float32");
+          return Object(_complex__WEBPACK_IMPORTED_MODULE_4__[/* complex */ "a"])(real, imag);
+        }
+        const values = Object(_util__WEBPACK_IMPORTED_MODULE_3__["makeZerosTypedArray"])(
+          Object(_util__WEBPACK_IMPORTED_MODULE_3__["sizeFromShape"])(shape),
+          dtype
+        );
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].makeTensor(
+          values,
+          shape,
+          dtype
+        );
+      }
+      /**
+       * Creates a `tf.Tensor` with all elements set to 1 with the same shape as the
+       * given tensor.
+       *
+       * ```js
+       * const x = tf.tensor([1, 2]);
+       * tf.onesLike(x).print();
+       * ```
+       * @param x A tensor.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function onesLike_(x) {
+        const $x = Object(_tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"])(
+          x,
+          "x",
+          "onesLike"
+        );
+        if ($x.dtype === "complex64") {
+          const r = onesLike(Object(_real__WEBPACK_IMPORTED_MODULE_7__[/* real */ "a"])($x));
+          const i = zerosLike(Object(_imag__WEBPACK_IMPORTED_MODULE_5__[/* imag */ "a"])($x));
+          return Object(_complex__WEBPACK_IMPORTED_MODULE_4__[/* complex */ "a"])(r, i);
+        }
+        const der = (dy, saved) => ({ x: () => zerosLike(dy) });
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
+          (backend) => backend.onesLike($x),
+          { x: $x },
+          der,
+          "OnesLike"
+        );
+      }
+      /**
+       * Creates a `tf.Tensor` with all elements set to 0 with the same shape as the
+       * given tensor.
+       *
+       * ```js
+       * const x = tf.tensor([1, 2]);
+       * tf.zerosLike(x).print();
+       * ```
+       *
+       * @param x The tensor of required shape.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function zerosLike_(x) {
+        const $x = Object(_tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"])(
+          x,
+          "x",
+          "zerosLike"
+        );
+        const der = (dy, saved) => ({ x: () => zerosLike(dy) });
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
+          (backend) => backend.zerosLike($x),
+          { x: $x },
+          der,
+          "ZerosLike"
+        );
+      }
+      /**
+       * Return an evenly spaced sequence of numbers over the given interval.
+       *
+       * ```js
+       * tf.linspace(0, 9, 10).print();
+       * ```
+       * @param start The start value of the sequence.
+       * @param stop The end value of the sequence.
+       * @param num The number of values to generate.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function linspace(start, stop, num) {
+        if (num <= 0) {
+          throw new Error("The number of values should be positive.");
+        }
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
+          (backend) => backend.linspace(start, stop, num),
+          {}
+        );
+      }
+      /**
+       * Creates a new `tf.Tensor1D` filled with the numbers in the range provided.
+       *
+       * The tensor is a is half-open interval meaning it includes start, but
+       * excludes stop. Decrementing ranges and negative step values are also
+       * supported.
+       *
+       * ```js
+       * tf.range(0, 9, 2).print();
+       * ```
+       *
+       * @param start An integer start value
+       * @param stop An integer stop value
+       * @param step An integer increment (will default to 1 or -1)
+       * @param dtype The data type of the output tensor. Defaults to 'float32'.
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function range(start, stop, step = 1, dtype = "float32") {
+        if (step === 0) {
+          throw new Error("Cannot have a step of zero");
+        }
+        const sameStartStop = start === stop;
+        const increasingRangeNegativeStep = start < stop && step < 0;
+        const decreasingRangePositiveStep = stop < start && step > 1;
+        if (sameStartStop || increasingRangeNegativeStep || decreasingRangePositiveStep) {
+          return zeros([0], dtype);
+        }
+        const numElements = Math.abs(Math.ceil((stop - start) / step));
+        const values = Object(_util__WEBPACK_IMPORTED_MODULE_3__["makeZerosTypedArray"])(
+          numElements,
+          dtype
+        );
+        if (stop < start && step === 1) {
+          // Auto adjust the step's sign if it hasn't been set
+          // (or was set to 1)
+          step = -1;
+        }
+        values[0] = start;
+        for (let i = 1; i < values.length; i++) {
+          values[i] = values[i - 1] + step;
+        }
+        return tensor1d(values, dtype);
+      }
+
+      const onesLike = Object(_operation__WEBPACK_IMPORTED_MODULE_6__[/* op */ "a"])({ onesLike_ });
+      const zerosLike = Object(_operation__WEBPACK_IMPORTED_MODULE_6__[/* op */ "a"])({
+        zerosLike_,
+      });
+      //# sourceMappingURL=tensor_ops.js.map
+
+      /***/
+    },
+    /* 9 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return assertNotComplex;
+      });
+      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
+        __webpack_require__(0);
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function assertNotComplex(tensor, opName) {
+        if (!Array.isArray(tensor)) {
+          tensor = [tensor];
+        }
+        tensor.forEach((t) => {
+          if (t != null) {
+            _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].assert(
+              t.dtype !== "complex64",
+              () => `${opName} does not support complex64 tensors in the CPU backend.`
+            );
+          }
+        });
+      }
+      //# sourceMappingURL=cpu_util.js.map
+
+      /***/
+    },
+    /* 10 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return Environment;
+      });
+      /* unused harmony export getQueryParams */
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return env;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return ENV;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
+        return setEnvironmentGlobal;
+      });
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // Expects flags from URL in the format ?tfjsflags=FLAG1:1,FLAG2:true.
+      const TENSORFLOWJS_FLAGS_PREFIX = "tfjsflags";
+      /**
+       * The environment contains evaluated flags as well as the registered platform.
+       * This is always used as a global singleton and can be retrieved with
+       * `tf.env()`.
+       */
+      /** @doc {heading: 'Environment'} */
+      class Environment {
+        // tslint:disable-next-line: no-any
+        constructor(global) {
+          this.global = global;
+          this.flags = {};
+          this.flagRegistry = {};
+          this.urlFlags = {};
+          this.populateURLFlags();
+        }
+        setPlatform(platformName, platform) {
+          if (this.platform != null) {
+            console.warn(
+              `Platform ${this.platformName} has already been set. ` +
+                `Overwriting the platform with ${platform}.`
+            );
+          }
+          this.platformName = platformName;
+          this.platform = platform;
+        }
+        registerFlag(flagName, evaluationFn, setHook) {
+          this.flagRegistry[flagName] = { evaluationFn, setHook };
+          // Override the flag value from the URL. This has to happen here because the
+          // environment is initialized before flags get registered.
+          if (this.urlFlags[flagName] != null) {
+            const flagValue = this.urlFlags[flagName];
+            console.warn(`Setting feature override from URL ${flagName}: ${flagValue}.`);
+            this.set(flagName, flagValue);
+          }
+        }
+        async getAsync(flagName) {
+          if (flagName in this.flags) {
+            return this.flags[flagName];
+          }
+          this.flags[flagName] = await this.evaluateFlag(flagName);
+          return this.flags[flagName];
+        }
+        get(flagName) {
+          if (flagName in this.flags) {
+            return this.flags[flagName];
+          }
+          const flagValue = this.evaluateFlag(flagName);
+          if (flagValue instanceof Promise) {
+            throw new Error(
+              `Flag ${flagName} cannot be synchronously evaluated. ` +
+                `Please use getAsync() instead.`
+            );
+          }
+          this.flags[flagName] = flagValue;
+          return this.flags[flagName];
+        }
+        getNumber(flagName) {
+          return this.get(flagName);
+        }
+        getBool(flagName) {
+          return this.get(flagName);
+        }
+        getFlags() {
+          return this.flags;
+        }
+        // For backwards compatibility.
+        get features() {
+          return this.flags;
+        }
+        set(flagName, value) {
+          if (this.flagRegistry[flagName] == null) {
+            throw new Error(`Cannot set flag ${flagName} as it has not been registered.`);
+          }
+          this.flags[flagName] = value;
+          if (this.flagRegistry[flagName].setHook != null) {
+            this.flagRegistry[flagName].setHook(value);
+          }
+        }
+        evaluateFlag(flagName) {
+          if (this.flagRegistry[flagName] == null) {
+            throw new Error(`Cannot evaluate flag '${flagName}': no evaluation function found.`);
+          }
+          return this.flagRegistry[flagName].evaluationFn();
+        }
+        setFlags(flags) {
+          this.flags = Object.assign({}, flags);
+        }
+        reset() {
+          this.flags = {};
+          this.urlFlags = {};
+          this.populateURLFlags();
+        }
+        populateURLFlags() {
+          if (
+            typeof this.global === "undefined" ||
+            typeof this.global.location === "undefined" ||
+            typeof this.global.location.search === "undefined"
+          ) {
+            return;
+          }
+          const urlParams = getQueryParams(this.global.location.search);
+          if (TENSORFLOWJS_FLAGS_PREFIX in urlParams) {
+            const keyValues = urlParams[TENSORFLOWJS_FLAGS_PREFIX].split(",");
+            keyValues.forEach((keyValue) => {
+              const [key, value] = keyValue.split(":");
+              this.urlFlags[key] = parseValue(key, value);
+            });
+          }
+        }
+      }
+      function getQueryParams(queryString) {
+        const params = {};
+        queryString.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g, (s, ...t) => {
+          decodeParam(params, t[0], t[1]);
+          return t.join("=");
+        });
+        return params;
+      }
+      function decodeParam(params, name, value) {
+        params[decodeURIComponent(name)] = decodeURIComponent(value || "");
+      }
+      function parseValue(flagName, value) {
+        value = value.toLowerCase();
+        if (value === "true" || value === "false") {
+          return value === "true";
+        } else if (`${+value}` === value) {
+          return +value;
+        }
+        throw new Error(`Could not parse value flag value ${value} for flag ${flagName}.`);
+      }
+      /**
+       * Returns the current environment (a global singleton).
+       *
+       * The environment object contains the evaluated feature values as well as the
+       * active platform.
+       */
+      /** @doc {heading: 'Environment'} */
+      function env() {
+        return ENV;
+      }
+      let ENV = null;
+      function setEnvironmentGlobal(environment) {
+        ENV = environment;
+      }
+      //# sourceMappingURL=environment.js.map
+
+      /***/
+    },
+    /* 11 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "makeTypesMatch",
+        function () {
+          return makeTypesMatch;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "assertTypesMatch",
+        function () {
+          return assertTypesMatch;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isTensorInList",
+        function () {
+          return isTensorInList;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "getTensorsInContainer",
+        function () {
+          return getTensorsInContainer;
+        }
+      );
+      /* harmony import */ var _tensor__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(7);
+      /* harmony import */ var _types__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(23);
+      /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_2__ = __webpack_require__(1);
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function makeTypesMatch(a, b) {
+        if (a.dtype === b.dtype) {
+          return [a, b];
+        }
+        const dtype = Object(_types__WEBPACK_IMPORTED_MODULE_1__[/* upcastType */ "c"])(
+          a.dtype,
+          b.dtype
+        );
+        return [a.cast(dtype), b.cast(dtype)];
+      }
+      function assertTypesMatch(a, b) {
+        Object(_util__WEBPACK_IMPORTED_MODULE_2__["assert"])(
+          a.dtype === b.dtype,
+          () => `The dtypes of the first(${a.dtype}) and` + ` second(${b.dtype}) input must match`
+        );
+      }
+      function isTensorInList(tensor, tensorList) {
+        return tensorList.some((x) => x.id === tensor.id);
+      }
+      /**
+       * Extracts any `Tensor`s found within the provided object.
+       *
+       * @param container an object that may be a `Tensor` or may directly contain
+       *   `Tensor`s, such as a `Tensor[]` or `{key: Tensor, ...}`. In general it
+       *   is safe to pass any object here, except that `Promise`s are not
+       *   supported.
+       * @returns An array of `Tensors` found within the passed object. If the
+       *   argument is simply a `Tensor', a list containing that `Tensor` is
+       *   returned. If the object is not a `Tensor` or does not
+       *   contain `Tensors`, an empty list is returned.
+       */
+      function getTensorsInContainer(result) {
+        const list = [];
+        const seen = new Set();
+        walkTensorContainer(result, list, seen);
+        return list;
+      }
+      function walkTensorContainer(container, list, seen) {
+        if (container == null) {
+          return;
+        }
+        if (container instanceof _tensor__WEBPACK_IMPORTED_MODULE_0__[/* Tensor */ "a"]) {
+          list.push(container);
+          return;
+        }
+        if (!isIterable(container)) {
+          return;
+        }
+        // Iteration over keys works also for arrays.
+        const iterable = container;
+        for (const k in iterable) {
+          const val = iterable[k];
+          if (!seen.has(val)) {
+            seen.add(val);
+            walkTensorContainer(val, list, seen);
+          }
+        }
+      }
+      // tslint:disable-next-line:no-any
+      function isIterable(obj) {
+        return Array.isArray(obj) || typeof obj === "object";
+      }
+      //# sourceMappingURL=tensor_util.js.map
+
+      /***/
+    },
+    /* 12 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (global) {
+        var numeric = false ? undefined : exports;
+        if (typeof global !== "undefined") {
+          global.numeric = numeric;
+        }
+
+        numeric.version = "1.2.6";
+
+        // 1. Utility functions
+        numeric.bench = function bench(f, interval) {
+          var t1, t2, n, i;
+          if (typeof interval === "undefined") {
+            interval = 15;
+          }
+          n = 0.5;
+          t1 = new Date();
+          while (1) {
+            n *= 2;
+            for (i = n; i > 3; i -= 4) {
+              f();
+              f();
+              f();
+              f();
+            }
+            while (i > 0) {
+              f();
+              i--;
+            }
+            t2 = new Date();
+            if (t2 - t1 > interval) break;
+          }
+          for (i = n; i > 3; i -= 4) {
+            f();
+            f();
+            f();
+            f();
+          }
+          while (i > 0) {
+            f();
+            i--;
+          }
+          t2 = new Date();
+          return (1000 * (3 * n - 1)) / (t2 - t1);
+        };
+
+        numeric._myIndexOf = function _myIndexOf(w) {
+          var n = this.length,
+            k;
+          for (k = 0; k < n; ++k) if (this[k] === w) return k;
+          return -1;
+        };
+        numeric.myIndexOf = Array.prototype.indexOf ? Array.prototype.indexOf : numeric._myIndexOf;
+
+        numeric.Function = Function;
+        numeric.precision = 4;
+        numeric.largeArray = 50;
+
+        numeric.prettyPrint = function prettyPrint(x) {
+          function fmtnum(x) {
+            if (x === 0) {
+              return "0";
+            }
+            if (isNaN(x)) {
+              return "NaN";
+            }
+            if (x < 0) {
+              return "-" + fmtnum(-x);
+            }
+            if (isFinite(x)) {
+              var scale = Math.floor(Math.log(x) / Math.log(10));
+              var normalized = x / Math.pow(10, scale);
+              var basic = normalized.toPrecision(numeric.precision);
+              if (parseFloat(basic) === 10) {
+                scale++;
+                normalized = 1;
+                basic = normalized.toPrecision(numeric.precision);
+              }
+              return parseFloat(basic).toString() + "e" + scale.toString();
+            }
+            return "Infinity";
+          }
+          var ret = [];
+          function foo(x) {
+            var k;
+            if (typeof x === "undefined") {
+              ret.push(Array(numeric.precision + 8).join(" "));
+              return false;
+            }
+            if (typeof x === "string") {
+              ret.push('"' + x + '"');
+              return false;
+            }
+            if (typeof x === "boolean") {
+              ret.push(x.toString());
+              return false;
+            }
+            if (typeof x === "number") {
+              var a = fmtnum(x);
+              var b = x.toPrecision(numeric.precision);
+              var c = parseFloat(x.toString()).toString();
+              var d = [a, b, c, parseFloat(b).toString(), parseFloat(c).toString()];
+              for (k = 1; k < d.length; k++) {
+                if (d[k].length < a.length) a = d[k];
+              }
+              ret.push(Array(numeric.precision + 8 - a.length).join(" ") + a);
+              return false;
+            }
+            if (x === null) {
+              ret.push("null");
+              return false;
+            }
+            if (typeof x === "function") {
+              ret.push(x.toString());
+              var flag = false;
+              for (k in x) {
+                if (x.hasOwnProperty(k)) {
+                  if (flag) ret.push(",\n");
+                  else ret.push("\n{");
+                  flag = true;
+                  ret.push(k);
+                  ret.push(": \n");
+                  foo(x[k]);
+                }
+              }
+              if (flag) ret.push("}\n");
+              return true;
+            }
+            if (x instanceof Array) {
+              if (x.length > numeric.largeArray) {
+                ret.push("...Large Array...");
+                return true;
+              }
+              var flag = false;
+              ret.push("[");
+              for (k = 0; k < x.length; k++) {
+                if (k > 0) {
+                  ret.push(",");
+                  if (flag) ret.push("\n ");
+                }
+                flag = foo(x[k]);
+              }
+              ret.push("]");
+              return true;
+            }
+            ret.push("{");
+            var flag = false;
+            for (k in x) {
+              if (x.hasOwnProperty(k)) {
+                if (flag) ret.push(",\n");
+                flag = true;
+                ret.push(k);
+                ret.push(": \n");
+                foo(x[k]);
+              }
+            }
+            ret.push("}");
+            return true;
+          }
+          foo(x);
+          return ret.join("");
+        };
+
+        numeric.parseDate = function parseDate(d) {
+          function foo(d) {
+            if (typeof d === "string") {
+              return Date.parse(d.replace(/-/g, "/"));
+            }
+            if (!(d instanceof Array)) {
+              throw new Error("parseDate: parameter must be arrays of strings");
+            }
+            var ret = [],
+              k;
+            for (k = 0; k < d.length; k++) {
+              ret[k] = foo(d[k]);
+            }
+            return ret;
+          }
+          return foo(d);
+        };
+
+        numeric.parseFloat = function parseFloat_(d) {
+          function foo(d) {
+            if (typeof d === "string") {
+              return parseFloat(d);
+            }
+            if (!(d instanceof Array)) {
+              throw new Error("parseFloat: parameter must be arrays of strings");
+            }
+            var ret = [],
+              k;
+            for (k = 0; k < d.length; k++) {
+              ret[k] = foo(d[k]);
+            }
+            return ret;
+          }
+          return foo(d);
+        };
+
+        numeric.parseCSV = function parseCSV(t) {
+          var foo = t.split("\n");
+          var j, k;
+          var ret = [];
+          var pat = /(([^'",]*)|('[^']*')|("[^"]*")),/g;
+          var patnum =
+            /^\s*(([+-]?[0-9]+(\.[0-9]*)?(e[+-]?[0-9]+)?)|([+-]?[0-9]*(\.[0-9]+)?(e[+-]?[0-9]+)?))\s*$/;
+          var stripper = function (n) {
+            return n.substr(0, n.length - 1);
+          };
+          var count = 0;
+          for (k = 0; k < foo.length; k++) {
+            var bar = (foo[k] + ",").match(pat),
+              baz;
+            if (bar.length > 0) {
+              ret[count] = [];
+              for (j = 0; j < bar.length; j++) {
+                baz = stripper(bar[j]);
+                if (patnum.test(baz)) {
+                  ret[count][j] = parseFloat(baz);
+                } else ret[count][j] = baz;
+              }
+              count++;
+            }
+          }
+          return ret;
+        };
+
+        numeric.toCSV = function toCSV(A) {
+          var s = numeric.dim(A);
+          var i, j, m, n, row, ret;
+          m = s[0];
+          n = s[1];
+          ret = [];
+          for (i = 0; i < m; i++) {
+            row = [];
+            for (j = 0; j < m; j++) {
+              row[j] = A[i][j].toString();
+            }
+            ret[i] = row.join(", ");
+          }
+          return ret.join("\n") + "\n";
+        };
+
+        numeric.getURL = function getURL(url) {
+          var client = new XMLHttpRequest();
+          client.open("GET", url, false);
+          client.send();
+          return client;
+        };
+
+        numeric.imageURL = function imageURL(img) {
+          function base64(A) {
+            var n = A.length,
+              i,
+              x,
+              y,
+              z,
+              p,
+              q,
+              r,
+              s;
+            var key = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=";
+            var ret = "";
+            for (i = 0; i < n; i += 3) {
+              x = A[i];
+              y = A[i + 1];
+              z = A[i + 2];
+              p = x >> 2;
+              q = ((x & 3) << 4) + (y >> 4);
+              r = ((y & 15) << 2) + (z >> 6);
+              s = z & 63;
+              if (i + 1 >= n) {
+                r = s = 64;
+              } else if (i + 2 >= n) {
+                s = 64;
+              }
+              ret += key.charAt(p) + key.charAt(q) + key.charAt(r) + key.charAt(s);
+            }
+            return ret;
+          }
+          function crc32Array(a, from, to) {
+            if (typeof from === "undefined") {
+              from = 0;
+            }
+            if (typeof to === "undefined") {
+              to = a.length;
+            }
+            var table = [
+              0x00000000, 0x77073096, 0xee0e612c, 0x990951ba, 0x076dc419, 0x706af48f, 0xe963a535,
+              0x9e6495a3, 0x0edb8832, 0x79dcb8a4, 0xe0d5e91e, 0x97d2d988, 0x09b64c2b, 0x7eb17cbd,
+              0xe7b82d07, 0x90bf1d91, 0x1db71064, 0x6ab020f2, 0xf3b97148, 0x84be41de, 0x1adad47d,
+              0x6ddde4eb, 0xf4d4b551, 0x83d385c7, 0x136c9856, 0x646ba8c0, 0xfd62f97a, 0x8a65c9ec,
+              0x14015c4f, 0x63066cd9, 0xfa0f3d63, 0x8d080df5, 0x3b6e20c8, 0x4c69105e, 0xd56041e4,
+              0xa2677172, 0x3c03e4d1, 0x4b04d447, 0xd20d85fd, 0xa50ab56b, 0x35b5a8fa, 0x42b2986c,
+              0xdbbbc9d6, 0xacbcf940, 0x32d86ce3, 0x45df5c75, 0xdcd60dcf, 0xabd13d59, 0x26d930ac,
+              0x51de003a, 0xc8d75180, 0xbfd06116, 0x21b4f4b5, 0x56b3c423, 0xcfba9599, 0xb8bda50f,
+              0x2802b89e, 0x5f058808, 0xc60cd9b2, 0xb10be924, 0x2f6f7c87, 0x58684c11, 0xc1611dab,
+              0xb6662d3d, 0x76dc4190, 0x01db7106, 0x98d220bc, 0xefd5102a, 0x71b18589, 0x06b6b51f,
+              0x9fbfe4a5, 0xe8b8d433, 0x7807c9a2, 0x0f00f934, 0x9609a88e, 0xe10e9818, 0x7f6a0dbb,
+              0x086d3d2d, 0x91646c97, 0xe6635c01, 0x6b6b51f4, 0x1c6c6162, 0x856530d8, 0xf262004e,
+              0x6c0695ed, 0x1b01a57b, 0x8208f4c1, 0xf50fc457, 0x65b0d9c6, 0x12b7e950, 0x8bbeb8ea,
+              0xfcb9887c, 0x62dd1ddf, 0x15da2d49, 0x8cd37cf3, 0xfbd44c65, 0x4db26158, 0x3ab551ce,
+              0xa3bc0074, 0xd4bb30e2, 0x4adfa541, 0x3dd895d7, 0xa4d1c46d, 0xd3d6f4fb, 0x4369e96a,
+              0x346ed9fc, 0xad678846, 0xda60b8d0, 0x44042d73, 0x33031de5, 0xaa0a4c5f, 0xdd0d7cc9,
+              0x5005713c, 0x270241aa, 0xbe0b1010, 0xc90c2086, 0x5768b525, 0x206f85b3, 0xb966d409,
+              0xce61e49f, 0x5edef90e, 0x29d9c998, 0xb0d09822, 0xc7d7a8b4, 0x59b33d17, 0x2eb40d81,
+              0xb7bd5c3b, 0xc0ba6cad, 0xedb88320, 0x9abfb3b6, 0x03b6e20c, 0x74b1d29a, 0xead54739,
+              0x9dd277af, 0x04db2615, 0x73dc1683, 0xe3630b12, 0x94643b84, 0x0d6d6a3e, 0x7a6a5aa8,
+              0xe40ecf0b, 0x9309ff9d, 0x0a00ae27, 0x7d079eb1, 0xf00f9344, 0x8708a3d2, 0x1e01f268,
+              0x6906c2fe, 0xf762575d, 0x806567cb, 0x196c3671, 0x6e6b06e7, 0xfed41b76, 0x89d32be0,
+              0x10da7a5a, 0x67dd4acc, 0xf9b9df6f, 0x8ebeeff9, 0x17b7be43, 0x60b08ed5, 0xd6d6a3e8,
+              0xa1d1937e, 0x38d8c2c4, 0x4fdff252, 0xd1bb67f1, 0xa6bc5767, 0x3fb506dd, 0x48b2364b,
+              0xd80d2bda, 0xaf0a1b4c, 0x36034af6, 0x41047a60, 0xdf60efc3, 0xa867df55, 0x316e8eef,
+              0x4669be79, 0xcb61b38c, 0xbc66831a, 0x256fd2a0, 0x5268e236, 0xcc0c7795, 0xbb0b4703,
+              0x220216b9, 0x5505262f, 0xc5ba3bbe, 0xb2bd0b28, 0x2bb45a92, 0x5cb36a04, 0xc2d7ffa7,
+              0xb5d0cf31, 0x2cd99e8b, 0x5bdeae1d, 0x9b64c2b0, 0xec63f226, 0x756aa39c, 0x026d930a,
+              0x9c0906a9, 0xeb0e363f, 0x72076785, 0x05005713, 0x95bf4a82, 0xe2b87a14, 0x7bb12bae,
+              0x0cb61b38, 0x92d28e9b, 0xe5d5be0d, 0x7cdcefb7, 0x0bdbdf21, 0x86d3d2d4, 0xf1d4e242,
+              0x68ddb3f8, 0x1fda836e, 0x81be16cd, 0xf6b9265b, 0x6fb077e1, 0x18b74777, 0x88085ae6,
+              0xff0f6a70, 0x66063bca, 0x11010b5c, 0x8f659eff, 0xf862ae69, 0x616bffd3, 0x166ccf45,
+              0xa00ae278, 0xd70dd2ee, 0x4e048354, 0x3903b3c2, 0xa7672661, 0xd06016f7, 0x4969474d,
+              0x3e6e77db, 0xaed16a4a, 0xd9d65adc, 0x40df0b66, 0x37d83bf0, 0xa9bcae53, 0xdebb9ec5,
+              0x47b2cf7f, 0x30b5ffe9, 0xbdbdf21c, 0xcabac28a, 0x53b39330, 0x24b4a3a6, 0xbad03605,
+              0xcdd70693, 0x54de5729, 0x23d967bf, 0xb3667a2e, 0xc4614ab8, 0x5d681b02, 0x2a6f2b94,
+              0xb40bbe37, 0xc30c8ea1, 0x5a05df1b, 0x2d02ef8d,
+            ];
+
+            var crc = -1,
+              y = 0,
+              n = a.length,
+              i;
+
+            for (i = from; i < to; i++) {
+              y = (crc ^ a[i]) & 0xff;
+              crc = (crc >>> 8) ^ table[y];
+            }
+
+            return crc ^ -1;
+          }
+
+          var h = img[0].length,
+            w = img[0][0].length,
+            s1,
+            s2,
+            next,
+            k,
+            length,
+            a,
+            b,
+            i,
+            j,
+            adler32,
+            crc32;
+          var stream = [
+            137,
+            80,
+            78,
+            71,
+            13,
+            10,
+            26,
+            10, //  0: PNG signature
+            0,
+            0,
+            0,
+            13, //  8: IHDR Chunk length
+            73,
+            72,
+            68,
+            82, // 12: "IHDR"
+            (w >> 24) & 255,
+            (w >> 16) & 255,
+            (w >> 8) & 255,
+            w & 255, // 16: Width
+            (h >> 24) & 255,
+            (h >> 16) & 255,
+            (h >> 8) & 255,
+            h & 255, // 20: Height
+            8, // 24: bit depth
+            2, // 25: RGB
+            0, // 26: deflate
+            0, // 27: no filter
+            0, // 28: no interlace
+            -1,
+            -2,
+            -3,
+            -4, // 29: CRC
+            -5,
+            -6,
+            -7,
+            -8, // 33: IDAT Chunk length
+            73,
+            68,
+            65,
+            84, // 37: "IDAT"
+            // RFC 1950 header starts here
+            8, // 41: RFC1950 CMF
+            29, // 42: RFC1950 FLG
+          ];
+          crc32 = crc32Array(stream, 12, 29);
+          stream[29] = (crc32 >> 24) & 255;
+          stream[30] = (crc32 >> 16) & 255;
+          stream[31] = (crc32 >> 8) & 255;
+          stream[32] = crc32 & 255;
+          s1 = 1;
+          s2 = 0;
+          for (i = 0; i < h; i++) {
+            if (i < h - 1) {
+              stream.push(0);
+            } else {
+              stream.push(1);
+            }
+            a = (3 * w + 1 + (i === 0)) & 255;
+            b = ((3 * w + 1 + (i === 0)) >> 8) & 255;
+            stream.push(a);
+            stream.push(b);
+            stream.push(~a & 255);
+            stream.push(~b & 255);
+            if (i === 0) stream.push(0);
+            for (j = 0; j < w; j++) {
+              for (k = 0; k < 3; k++) {
+                a = img[k][i][j];
+                if (a > 255) a = 255;
+                else if (a < 0) a = 0;
+                else a = Math.round(a);
+                s1 = (s1 + a) % 65521;
+                s2 = (s2 + s1) % 65521;
+                stream.push(a);
+              }
+            }
+            stream.push(0);
+          }
+          adler32 = (s2 << 16) + s1;
+          stream.push((adler32 >> 24) & 255);
+          stream.push((adler32 >> 16) & 255);
+          stream.push((adler32 >> 8) & 255);
+          stream.push(adler32 & 255);
+          length = stream.length - 41;
+          stream[33] = (length >> 24) & 255;
+          stream[34] = (length >> 16) & 255;
+          stream[35] = (length >> 8) & 255;
+          stream[36] = length & 255;
+          crc32 = crc32Array(stream, 37);
+          stream.push((crc32 >> 24) & 255);
+          stream.push((crc32 >> 16) & 255);
+          stream.push((crc32 >> 8) & 255);
+          stream.push(crc32 & 255);
+          stream.push(0);
+          stream.push(0);
+          stream.push(0);
+          stream.push(0);
+          //    a = stream.length;
+          stream.push(73); // I
+          stream.push(69); // E
+          stream.push(78); // N
+          stream.push(68); // D
+          stream.push(174); // CRC1
+          stream.push(66); // CRC2
+          stream.push(96); // CRC3
+          stream.push(130); // CRC4
+          return "data:image/png;base64," + base64(stream);
+        };
+
+        // 2. Linear algebra with Arrays.
+        numeric._dim = function _dim(x) {
+          var ret = [];
+          while (typeof x === "object") {
+            ret.push(x.length);
+            x = x[0];
+          }
+          return ret;
+        };
+
+        numeric.dim = function dim(x) {
+          var y, z;
+          if (typeof x === "object") {
+            y = x[0];
+            if (typeof y === "object") {
+              z = y[0];
+              if (typeof z === "object") {
+                return numeric._dim(x);
+              }
+              return [x.length, y.length];
+            }
+            return [x.length];
+          }
+          return [];
+        };
+
+        numeric.mapreduce = function mapreduce(body, init) {
+          return Function(
+            "x",
+            "accum",
+            "_s",
+            "_k",
+            'if(typeof accum === "undefined") accum = ' +
+              init +
+              ";\n" +
+              'if(typeof x === "number") { var xi = x; ' +
+              body +
+              "; return accum; }\n" +
+              'if(typeof _s === "undefined") _s = numeric.dim(x);\n' +
+              'if(typeof _k === "undefined") _k = 0;\n' +
+              "var _n = _s[_k];\n" +
+              "var i,xi;\n" +
+              "if(_k < _s.length-1) {\n" +
+              "    for(i=_n-1;i>=0;i--) {\n" +
+              "        accum = arguments.callee(x[i],accum,_s,_k+1);\n" +
+              "    }" +
+              "    return accum;\n" +
+              "}\n" +
+              "for(i=_n-1;i>=1;i-=2) { \n" +
+              "    xi = x[i];\n" +
+              "    " +
+              body +
+              ";\n" +
+              "    xi = x[i-1];\n" +
+              "    " +
+              body +
+              ";\n" +
+              "}\n" +
+              "if(i === 0) {\n" +
+              "    xi = x[i];\n" +
+              "    " +
+              body +
+              "\n" +
+              "}\n" +
+              "return accum;"
+          );
+        };
+        numeric.mapreduce2 = function mapreduce2(body, setup) {
+          return Function(
+            "x",
+            "var n = x.length;\n" +
+              "var i,xi;\n" +
+              setup +
+              ";\n" +
+              "for(i=n-1;i!==-1;--i) { \n" +
+              "    xi = x[i];\n" +
+              "    " +
+              body +
+              ";\n" +
+              "}\n" +
+              "return accum;"
+          );
+        };
+
+        numeric.same = function same(x, y) {
+          var i, n;
+          if (!(x instanceof Array) || !(y instanceof Array)) {
+            return false;
+          }
+          n = x.length;
+          if (n !== y.length) {
+            return false;
+          }
+          for (i = 0; i < n; i++) {
+            if (x[i] === y[i]) {
+              continue;
+            }
+            if (typeof x[i] === "object") {
+              if (!same(x[i], y[i])) return false;
+            } else {
+              return false;
+            }
+          }
+          return true;
+        };
+
+        numeric.rep = function rep(s, v, k) {
+          if (typeof k === "undefined") {
+            k = 0;
+          }
+          var n = s[k],
+            ret = Array(n),
+            i;
+          if (k === s.length - 1) {
+            for (i = n - 2; i >= 0; i -= 2) {
+              ret[i + 1] = v;
+              ret[i] = v;
+            }
+            if (i === -1) {
+              ret[0] = v;
+            }
+            return ret;
+          }
+          for (i = n - 1; i >= 0; i--) {
+            ret[i] = numeric.rep(s, v, k + 1);
+          }
+          return ret;
+        };
+
+        numeric.dotMMsmall = function dotMMsmall(x, y) {
+          var i, j, k, p, q, r, ret, foo, bar, woo, i0, k0, p0, r0;
+          p = x.length;
+          q = y.length;
+          r = y[0].length;
+          ret = Array(p);
+          for (i = p - 1; i >= 0; i--) {
+            foo = Array(r);
+            bar = x[i];
+            for (k = r - 1; k >= 0; k--) {
+              woo = bar[q - 1] * y[q - 1][k];
+              for (j = q - 2; j >= 1; j -= 2) {
+                i0 = j - 1;
+                woo += bar[j] * y[j][k] + bar[i0] * y[i0][k];
+              }
+              if (j === 0) {
+                woo += bar[0] * y[0][k];
+              }
+              foo[k] = woo;
+            }
+            ret[i] = foo;
+          }
+          return ret;
+        };
+        numeric._getCol = function _getCol(A, j, x) {
+          var n = A.length,
+            i;
+          for (i = n - 1; i > 0; --i) {
+            x[i] = A[i][j];
+            --i;
+            x[i] = A[i][j];
+          }
+          if (i === 0) x[0] = A[0][j];
+        };
+        numeric.dotMMbig = function dotMMbig(x, y) {
+          var gc = numeric._getCol,
+            p = y.length,
+            v = Array(p);
+          var m = x.length,
+            n = y[0].length,
+            A = new Array(m),
+            xj;
+          var VV = numeric.dotVV;
+          var i, j, k, z;
+          --p;
+          --m;
+          for (i = m; i !== -1; --i) A[i] = Array(n);
+          --n;
+          for (i = n; i !== -1; --i) {
+            gc(y, i, v);
+            for (j = m; j !== -1; --j) {
+              z = 0;
+              xj = x[j];
+              A[j][i] = VV(xj, v);
+            }
+          }
+          return A;
+        };
+
+        numeric.dotMV = function dotMV(x, y) {
+          var p = x.length,
+            q = y.length,
+            i;
+          var ret = Array(p),
+            dotVV = numeric.dotVV;
+          for (i = p - 1; i >= 0; i--) {
+            ret[i] = dotVV(x[i], y);
+          }
+          return ret;
+        };
+
+        numeric.dotVM = function dotVM(x, y) {
+          var i, j, k, p, q, r, ret, foo, bar, woo, i0, k0, p0, r0, s1, s2, s3, baz, accum;
+          p = x.length;
+          q = y[0].length;
+          ret = Array(q);
+          for (k = q - 1; k >= 0; k--) {
+            woo = x[p - 1] * y[p - 1][k];
+            for (j = p - 2; j >= 1; j -= 2) {
+              i0 = j - 1;
+              woo += x[j] * y[j][k] + x[i0] * y[i0][k];
+            }
+            if (j === 0) {
+              woo += x[0] * y[0][k];
+            }
+            ret[k] = woo;
+          }
+          return ret;
+        };
+
+        numeric.dotVV = function dotVV(x, y) {
+          var i,
+            n = x.length,
+            i1,
+            ret = x[n - 1] * y[n - 1];
+          for (i = n - 2; i >= 1; i -= 2) {
+            i1 = i - 1;
+            ret += x[i] * y[i] + x[i1] * y[i1];
+          }
+          if (i === 0) {
+            ret += x[0] * y[0];
+          }
+          return ret;
+        };
+
+        numeric.dot = function dot(x, y) {
+          var d = numeric.dim;
+          switch (d(x).length * 1000 + d(y).length) {
+            case 2002:
+              if (y.length < 10) return numeric.dotMMsmall(x, y);
+              else return numeric.dotMMbig(x, y);
+            case 2001:
+              return numeric.dotMV(x, y);
+            case 1002:
+              return numeric.dotVM(x, y);
+            case 1001:
+              return numeric.dotVV(x, y);
+            case 1000:
+              return numeric.mulVS(x, y);
+            case 1:
+              return numeric.mulSV(x, y);
+            case 0:
+              return x * y;
+            default:
+              throw new Error("numeric.dot only works on vectors and matrices");
+          }
+        };
+
+        numeric.diag = function diag(d) {
+          var i,
+            i1,
+            j,
+            n = d.length,
+            A = Array(n),
+            Ai;
+          for (i = n - 1; i >= 0; i--) {
+            Ai = Array(n);
+            i1 = i + 2;
+            for (j = n - 1; j >= i1; j -= 2) {
+              Ai[j] = 0;
+              Ai[j - 1] = 0;
+            }
+            if (j > i) {
+              Ai[j] = 0;
+            }
+            Ai[i] = d[i];
+            for (j = i - 1; j >= 1; j -= 2) {
+              Ai[j] = 0;
+              Ai[j - 1] = 0;
+            }
+            if (j === 0) {
+              Ai[0] = 0;
+            }
+            A[i] = Ai;
+          }
+          return A;
+        };
+        numeric.getDiag = function (A) {
+          var n = Math.min(A.length, A[0].length),
+            i,
+            ret = Array(n);
+          for (i = n - 1; i >= 1; --i) {
+            ret[i] = A[i][i];
+            --i;
+            ret[i] = A[i][i];
+          }
+          if (i === 0) {
+            ret[0] = A[0][0];
+          }
+          return ret;
+        };
+
+        numeric.identity = function identity(n) {
+          return numeric.diag(numeric.rep([n], 1));
+        };
+        numeric.pointwise = function pointwise(params, body, setup) {
+          if (typeof setup === "undefined") {
+            setup = "";
+          }
+          var fun = [];
+          var k;
+          var avec = /\[i\]$/,
+            p,
+            thevec = "";
+          var haveret = false;
+          for (k = 0; k < params.length; k++) {
+            if (avec.test(params[k])) {
+              p = params[k].substring(0, params[k].length - 3);
+              thevec = p;
+            } else {
+              p = params[k];
+            }
+            if (p === "ret") haveret = true;
+            fun.push(p);
+          }
+          fun[params.length] = "_s";
+          fun[params.length + 1] = "_k";
+          fun[params.length + 2] =
+            'if(typeof _s === "undefined") _s = numeric.dim(' +
+            thevec +
+            ");\n" +
+            'if(typeof _k === "undefined") _k = 0;\n' +
+            "var _n = _s[_k];\n" +
+            "var i" +
+            (haveret ? "" : ", ret = Array(_n)") +
+            ";\n" +
+            "if(_k < _s.length-1) {\n" +
+            "    for(i=_n-1;i>=0;i--) ret[i] = arguments.callee(" +
+            params.join(",") +
+            ",_s,_k+1);\n" +
+            "    return ret;\n" +
+            "}\n" +
+            setup +
+            "\n" +
+            "for(i=_n-1;i!==-1;--i) {\n" +
+            "    " +
+            body +
+            "\n" +
+            "}\n" +
+            "return ret;";
+          return Function.apply(null, fun);
+        };
+        numeric.pointwise2 = function pointwise2(params, body, setup) {
+          if (typeof setup === "undefined") {
+            setup = "";
+          }
+          var fun = [];
+          var k;
+          var avec = /\[i\]$/,
+            p,
+            thevec = "";
+          var haveret = false;
+          for (k = 0; k < params.length; k++) {
+            if (avec.test(params[k])) {
+              p = params[k].substring(0, params[k].length - 3);
+              thevec = p;
+            } else {
+              p = params[k];
+            }
+            if (p === "ret") haveret = true;
+            fun.push(p);
+          }
+          fun[params.length] =
+            "var _n = " +
+            thevec +
+            ".length;\n" +
+            "var i" +
+            (haveret ? "" : ", ret = Array(_n)") +
+            ";\n" +
+            setup +
+            "\n" +
+            "for(i=_n-1;i!==-1;--i) {\n" +
+            body +
+            "\n" +
+            "}\n" +
+            "return ret;";
+          return Function.apply(null, fun);
+        };
+        numeric._biforeach = function _biforeach(x, y, s, k, f) {
+          if (k === s.length - 1) {
+            f(x, y);
+            return;
+          }
+          var i,
+            n = s[k];
+          for (i = n - 1; i >= 0; i--) {
+            _biforeach(
+              typeof x === "object" ? x[i] : x,
+              typeof y === "object" ? y[i] : y,
+              s,
+              k + 1,
+              f
+            );
+          }
+        };
+        numeric._biforeach2 = function _biforeach2(x, y, s, k, f) {
+          if (k === s.length - 1) {
+            return f(x, y);
+          }
+          var i,
+            n = s[k],
+            ret = Array(n);
+          for (i = n - 1; i >= 0; --i) {
+            ret[i] = _biforeach2(
+              typeof x === "object" ? x[i] : x,
+              typeof y === "object" ? y[i] : y,
+              s,
+              k + 1,
+              f
+            );
+          }
+          return ret;
+        };
+        numeric._foreach = function _foreach(x, s, k, f) {
+          if (k === s.length - 1) {
+            f(x);
+            return;
+          }
+          var i,
+            n = s[k];
+          for (i = n - 1; i >= 0; i--) {
+            _foreach(x[i], s, k + 1, f);
+          }
+        };
+        numeric._foreach2 = function _foreach2(x, s, k, f) {
+          if (k === s.length - 1) {
+            return f(x);
+          }
+          var i,
+            n = s[k],
+            ret = Array(n);
+          for (i = n - 1; i >= 0; i--) {
+            ret[i] = _foreach2(x[i], s, k + 1, f);
+          }
+          return ret;
+        };
+
+        /*numeric.anyV = numeric.mapreduce('if(xi) return true;','false');
+numeric.allV = numeric.mapreduce('if(!xi) return false;','true');
+numeric.any = function(x) { if(typeof x.length === "undefined") return x; return numeric.anyV(x); }
+numeric.all = function(x) { if(typeof x.length === "undefined") return x; return numeric.allV(x); }*/
+
+        numeric.ops2 = {
+          add: "+",
+          sub: "-",
+          mul: "*",
+          div: "/",
+          mod: "%",
+          and: "&&",
+          or: "||",
+          eq: "===",
+          neq: "!==",
+          lt: "<",
+          gt: ">",
+          leq: "<=",
+          geq: ">=",
+          band: "&",
+          bor: "|",
+          bxor: "^",
+          lshift: "<<",
+          rshift: ">>",
+          rrshift: ">>>",
+        };
+        numeric.opseq = {
+          addeq: "+=",
+          subeq: "-=",
+          muleq: "*=",
+          diveq: "/=",
+          modeq: "%=",
+          lshifteq: "<<=",
+          rshifteq: ">>=",
+          rrshifteq: ">>>=",
+          bandeq: "&=",
+          boreq: "|=",
+          bxoreq: "^=",
+        };
+        numeric.mathfuns = [
+          "abs",
+          "acos",
+          "asin",
+          "atan",
+          "ceil",
+          "cos",
+          "exp",
+          "floor",
+          "log",
+          "round",
+          "sin",
+          "sqrt",
+          "tan",
+          "isNaN",
+          "isFinite",
+        ];
+        numeric.mathfuns2 = ["atan2", "pow", "max", "min"];
+        numeric.ops1 = {
+          neg: "-",
+          not: "!",
+          bnot: "~",
+          clone: "",
+        };
+        numeric.mapreducers = {
+          any: ["if(xi) return true;", "var accum = false;"],
+          all: ["if(!xi) return false;", "var accum = true;"],
+          sum: ["accum += xi;", "var accum = 0;"],
+          prod: ["accum *= xi;", "var accum = 1;"],
+          norm2Squared: ["accum += xi*xi;", "var accum = 0;"],
+          norminf: [
+            "accum = max(accum,abs(xi));",
+            "var accum = 0, max = Math.max, abs = Math.abs;",
+          ],
+          norm1: ["accum += abs(xi)", "var accum = 0, abs = Math.abs;"],
+          sup: ["accum = max(accum,xi);", "var accum = -Infinity, max = Math.max;"],
+          inf: ["accum = min(accum,xi);", "var accum = Infinity, min = Math.min;"],
+        };
+
+        (function () {
+          var i, o;
+          for (i = 0; i < numeric.mathfuns2.length; ++i) {
+            o = numeric.mathfuns2[i];
+            numeric.ops2[o] = o;
+          }
+          for (i in numeric.ops2) {
+            if (numeric.ops2.hasOwnProperty(i)) {
+              o = numeric.ops2[i];
+              var code,
+                codeeq,
+                setup = "";
+              if (numeric.myIndexOf.call(numeric.mathfuns2, i) !== -1) {
+                setup = "var " + o + " = Math." + o + ";\n";
+                code = function (r, x, y) {
+                  return r + " = " + o + "(" + x + "," + y + ")";
+                };
+                codeeq = function (x, y) {
+                  return x + " = " + o + "(" + x + "," + y + ")";
+                };
+              } else {
+                code = function (r, x, y) {
+                  return r + " = " + x + " " + o + " " + y;
+                };
+                if (numeric.opseq.hasOwnProperty(i + "eq")) {
+                  codeeq = function (x, y) {
+                    return x + " " + o + "= " + y;
+                  };
+                } else {
+                  codeeq = function (x, y) {
+                    return x + " = " + x + " " + o + " " + y;
+                  };
+                }
+              }
+              numeric[i + "VV"] = numeric.pointwise2(
+                ["x[i]", "y[i]"],
+                code("ret[i]", "x[i]", "y[i]"),
+                setup
+              );
+              numeric[i + "SV"] = numeric.pointwise2(
+                ["x", "y[i]"],
+                code("ret[i]", "x", "y[i]"),
+                setup
+              );
+              numeric[i + "VS"] = numeric.pointwise2(
+                ["x[i]", "y"],
+                code("ret[i]", "x[i]", "y"),
+                setup
+              );
+              numeric[i] = Function(
+                "var n = arguments.length, i, x = arguments[0], y;\n" +
+                  "var VV = numeric." +
+                  i +
+                  "VV, VS = numeric." +
+                  i +
+                  "VS, SV = numeric." +
+                  i +
+                  "SV;\n" +
+                  "var dim = numeric.dim;\n" +
+                  "for(i=1;i!==n;++i) { \n" +
+                  "  y = arguments[i];\n" +
+                  '  if(typeof x === "object") {\n' +
+                  '      if(typeof y === "object") x = numeric._biforeach2(x,y,dim(x),0,VV);\n' +
+                  "      else x = numeric._biforeach2(x,y,dim(x),0,VS);\n" +
+                  '  } else if(typeof y === "object") x = numeric._biforeach2(x,y,dim(y),0,SV);\n' +
+                  "  else " +
+                  codeeq("x", "y") +
+                  "\n" +
+                  "}\nreturn x;\n"
+              );
+              numeric[o] = numeric[i];
+              numeric[i + "eqV"] = numeric.pointwise2(
+                ["ret[i]", "x[i]"],
+                codeeq("ret[i]", "x[i]"),
+                setup
+              );
+              numeric[i + "eqS"] = numeric.pointwise2(
+                ["ret[i]", "x"],
+                codeeq("ret[i]", "x"),
+                setup
+              );
+              numeric[i + "eq"] = Function(
+                "var n = arguments.length, i, x = arguments[0], y;\n" +
+                  "var V = numeric." +
+                  i +
+                  "eqV, S = numeric." +
+                  i +
+                  "eqS\n" +
+                  "var s = numeric.dim(x);\n" +
+                  "for(i=1;i!==n;++i) { \n" +
+                  "  y = arguments[i];\n" +
+                  '  if(typeof y === "object") numeric._biforeach(x,y,s,0,V);\n' +
+                  "  else numeric._biforeach(x,y,s,0,S);\n" +
+                  "}\nreturn x;\n"
+              );
+            }
+          }
+          for (i = 0; i < numeric.mathfuns2.length; ++i) {
+            o = numeric.mathfuns2[i];
+            delete numeric.ops2[o];
+          }
+          for (i = 0; i < numeric.mathfuns.length; ++i) {
+            o = numeric.mathfuns[i];
+            numeric.ops1[o] = o;
+          }
+          for (i in numeric.ops1) {
+            if (numeric.ops1.hasOwnProperty(i)) {
+              setup = "";
+              o = numeric.ops1[i];
+              if (numeric.myIndexOf.call(numeric.mathfuns, i) !== -1) {
+                if (Math.hasOwnProperty(o)) setup = "var " + o + " = Math." + o + ";\n";
+              }
+              numeric[i + "eqV"] = numeric.pointwise2(
+                ["ret[i]"],
+                "ret[i] = " + o + "(ret[i]);",
+                setup
+              );
+              numeric[i + "eq"] = Function(
+                "x",
+                'if(typeof x !== "object") return ' +
+                  o +
+                  "x\n" +
+                  "var i;\n" +
+                  "var V = numeric." +
+                  i +
+                  "eqV;\n" +
+                  "var s = numeric.dim(x);\n" +
+                  "numeric._foreach(x,s,0,V);\n" +
+                  "return x;\n"
+              );
+              numeric[i + "V"] = numeric.pointwise2(["x[i]"], "ret[i] = " + o + "(x[i]);", setup);
+              numeric[i] = Function(
+                "x",
+                'if(typeof x !== "object") return ' +
+                  o +
+                  "(x)\n" +
+                  "var i;\n" +
+                  "var V = numeric." +
+                  i +
+                  "V;\n" +
+                  "var s = numeric.dim(x);\n" +
+                  "return numeric._foreach2(x,s,0,V);\n"
+              );
+            }
+          }
+          for (i = 0; i < numeric.mathfuns.length; ++i) {
+            o = numeric.mathfuns[i];
+            delete numeric.ops1[o];
+          }
+          for (i in numeric.mapreducers) {
+            if (numeric.mapreducers.hasOwnProperty(i)) {
+              o = numeric.mapreducers[i];
+              numeric[i + "V"] = numeric.mapreduce2(o[0], o[1]);
+              numeric[i] = Function(
+                "x",
+                "s",
+                "k",
+                o[1] +
+                  'if(typeof x !== "object") {' +
+                  "    xi = x;\n" +
+                  o[0] +
+                  ";\n" +
+                  "    return accum;\n" +
+                  "}" +
+                  'if(typeof s === "undefined") s = numeric.dim(x);\n' +
+                  'if(typeof k === "undefined") k = 0;\n' +
+                  "if(k === s.length-1) return numeric." +
+                  i +
+                  "V(x);\n" +
+                  "var xi;\n" +
+                  "var n = x.length, i;\n" +
+                  "for(i=n-1;i!==-1;--i) {\n" +
+                  "   xi = arguments.callee(x[i]);\n" +
+                  o[0] +
+                  ";\n" +
+                  "}\n" +
+                  "return accum;\n"
+              );
+            }
+          }
+        })();
+
+        numeric.truncVV = numeric.pointwise(
+          ["x[i]", "y[i]"],
+          "ret[i] = round(x[i]/y[i])*y[i];",
+          "var round = Math.round;"
+        );
+        numeric.truncVS = numeric.pointwise(
+          ["x[i]", "y"],
+          "ret[i] = round(x[i]/y)*y;",
+          "var round = Math.round;"
+        );
+        numeric.truncSV = numeric.pointwise(
+          ["x", "y[i]"],
+          "ret[i] = round(x/y[i])*y[i];",
+          "var round = Math.round;"
+        );
+        numeric.trunc = function trunc(x, y) {
+          if (typeof x === "object") {
+            if (typeof y === "object") return numeric.truncVV(x, y);
+            return numeric.truncVS(x, y);
+          }
+          if (typeof y === "object") return numeric.truncSV(x, y);
+          return Math.round(x / y) * y;
+        };
+
+        numeric.inv = function inv(x) {
+          var s = numeric.dim(x),
+            abs = Math.abs,
+            m = s[0],
+            n = s[1];
+          var A = numeric.clone(x),
+            Ai,
+            Aj;
+          var I = numeric.identity(m),
+            Ii,
+            Ij;
+          var i, j, k, x;
+          for (j = 0; j < n; ++j) {
+            var i0 = -1;
+            var v0 = -1;
+            for (i = j; i !== m; ++i) {
+              k = abs(A[i][j]);
+              if (k > v0) {
+                i0 = i;
+                v0 = k;
+              }
+            }
+            Aj = A[i0];
+            A[i0] = A[j];
+            A[j] = Aj;
+            Ij = I[i0];
+            I[i0] = I[j];
+            I[j] = Ij;
+            x = Aj[j];
+            for (k = j; k !== n; ++k) Aj[k] /= x;
+            for (k = n - 1; k !== -1; --k) Ij[k] /= x;
+            for (i = m - 1; i !== -1; --i) {
+              if (i !== j) {
+                Ai = A[i];
+                Ii = I[i];
+                x = Ai[j];
+                for (k = j + 1; k !== n; ++k) Ai[k] -= Aj[k] * x;
+                for (k = n - 1; k > 0; --k) {
+                  Ii[k] -= Ij[k] * x;
+                  --k;
+                  Ii[k] -= Ij[k] * x;
+                }
+                if (k === 0) Ii[0] -= Ij[0] * x;
+              }
+            }
+          }
+          return I;
+        };
+
+        numeric.det = function det(x) {
+          var s = numeric.dim(x);
+          if (s.length !== 2 || s[0] !== s[1]) {
+            throw new Error("numeric: det() only works on square matrices");
+          }
+          var n = s[0],
+            ret = 1,
+            i,
+            j,
+            k,
+            A = numeric.clone(x),
+            Aj,
+            Ai,
+            alpha,
+            temp,
+            k1,
+            k2,
+            k3;
+          for (j = 0; j < n - 1; j++) {
+            k = j;
+            for (i = j + 1; i < n; i++) {
+              if (Math.abs(A[i][j]) > Math.abs(A[k][j])) {
+                k = i;
+              }
+            }
+            if (k !== j) {
+              temp = A[k];
+              A[k] = A[j];
+              A[j] = temp;
+              ret *= -1;
+            }
+            Aj = A[j];
+            for (i = j + 1; i < n; i++) {
+              Ai = A[i];
+              alpha = Ai[j] / Aj[j];
+              for (k = j + 1; k < n - 1; k += 2) {
+                k1 = k + 1;
+                Ai[k] -= Aj[k] * alpha;
+                Ai[k1] -= Aj[k1] * alpha;
+              }
+              if (k !== n) {
+                Ai[k] -= Aj[k] * alpha;
+              }
+            }
+            if (Aj[j] === 0) {
+              return 0;
+            }
+            ret *= Aj[j];
+          }
+          return ret * A[j][j];
+        };
+
+        numeric.transpose = function transpose(x) {
+          var i,
+            j,
+            m = x.length,
+            n = x[0].length,
+            ret = Array(n),
+            A0,
+            A1,
+            Bj;
+          for (j = 0; j < n; j++) ret[j] = Array(m);
+          for (i = m - 1; i >= 1; i -= 2) {
+            A1 = x[i];
+            A0 = x[i - 1];
+            for (j = n - 1; j >= 1; --j) {
+              Bj = ret[j];
+              Bj[i] = A1[j];
+              Bj[i - 1] = A0[j];
+              --j;
+              Bj = ret[j];
+              Bj[i] = A1[j];
+              Bj[i - 1] = A0[j];
+            }
+            if (j === 0) {
+              Bj = ret[0];
+              Bj[i] = A1[0];
+              Bj[i - 1] = A0[0];
+            }
+          }
+          if (i === 0) {
+            A0 = x[0];
+            for (j = n - 1; j >= 1; --j) {
+              ret[j][0] = A0[j];
+              --j;
+              ret[j][0] = A0[j];
+            }
+            if (j === 0) {
+              ret[0][0] = A0[0];
+            }
+          }
+          return ret;
+        };
+        numeric.negtranspose = function negtranspose(x) {
+          var i,
+            j,
+            m = x.length,
+            n = x[0].length,
+            ret = Array(n),
+            A0,
+            A1,
+            Bj;
+          for (j = 0; j < n; j++) ret[j] = Array(m);
+          for (i = m - 1; i >= 1; i -= 2) {
+            A1 = x[i];
+            A0 = x[i - 1];
+            for (j = n - 1; j >= 1; --j) {
+              Bj = ret[j];
+              Bj[i] = -A1[j];
+              Bj[i - 1] = -A0[j];
+              --j;
+              Bj = ret[j];
+              Bj[i] = -A1[j];
+              Bj[i - 1] = -A0[j];
+            }
+            if (j === 0) {
+              Bj = ret[0];
+              Bj[i] = -A1[0];
+              Bj[i - 1] = -A0[0];
+            }
+          }
+          if (i === 0) {
+            A0 = x[0];
+            for (j = n - 1; j >= 1; --j) {
+              ret[j][0] = -A0[j];
+              --j;
+              ret[j][0] = -A0[j];
+            }
+            if (j === 0) {
+              ret[0][0] = -A0[0];
+            }
+          }
+          return ret;
+        };
+
+        numeric._random = function _random(s, k) {
+          var i,
+            n = s[k],
+            ret = Array(n),
+            rnd;
+          if (k === s.length - 1) {
+            rnd = Math.random;
+            for (i = n - 1; i >= 1; i -= 2) {
+              ret[i] = rnd();
+              ret[i - 1] = rnd();
+            }
+            if (i === 0) {
+              ret[0] = rnd();
+            }
+            return ret;
+          }
+          for (i = n - 1; i >= 0; i--) ret[i] = _random(s, k + 1);
+          return ret;
+        };
+        numeric.random = function random(s) {
+          return numeric._random(s, 0);
+        };
+
+        numeric.norm2 = function norm2(x) {
+          return Math.sqrt(numeric.norm2Squared(x));
+        };
+
+        numeric.linspace = function linspace(a, b, n) {
+          if (typeof n === "undefined") n = Math.max(Math.round(b - a) + 1, 1);
+          if (n < 2) {
+            return n === 1 ? [a] : [];
+          }
+          var i,
+            ret = Array(n);
+          n--;
+          for (i = n; i >= 0; i--) {
+            ret[i] = (i * b + (n - i) * a) / n;
+          }
+          return ret;
+        };
+
+        numeric.getBlock = function getBlock(x, from, to) {
+          var s = numeric.dim(x);
+          function foo(x, k) {
+            var i,
+              a = from[k],
+              n = to[k] - a,
+              ret = Array(n);
+            if (k === s.length - 1) {
+              for (i = n; i >= 0; i--) {
+                ret[i] = x[i + a];
+              }
+              return ret;
+            }
+            for (i = n; i >= 0; i--) {
+              ret[i] = foo(x[i + a], k + 1);
+            }
+            return ret;
+          }
+          return foo(x, 0);
+        };
+
+        numeric.setBlock = function setBlock(x, from, to, B) {
+          var s = numeric.dim(x);
+          function foo(x, y, k) {
+            var i,
+              a = from[k],
+              n = to[k] - a;
+            if (k === s.length - 1) {
+              for (i = n; i >= 0; i--) {
+                x[i + a] = y[i];
+              }
+            }
+            for (i = n; i >= 0; i--) {
+              foo(x[i + a], y[i], k + 1);
+            }
+          }
+          foo(x, B, 0);
+          return x;
+        };
+
+        numeric.getRange = function getRange(A, I, J) {
+          var m = I.length,
+            n = J.length;
+          var i, j;
+          var B = Array(m),
+            Bi,
+            AI;
+          for (i = m - 1; i !== -1; --i) {
+            B[i] = Array(n);
+            Bi = B[i];
+            AI = A[I[i]];
+            for (j = n - 1; j !== -1; --j) Bi[j] = AI[J[j]];
+          }
+          return B;
+        };
+
+        numeric.blockMatrix = function blockMatrix(X) {
+          var s = numeric.dim(X);
+          if (s.length < 4) return numeric.blockMatrix([X]);
+          var m = s[0],
+            n = s[1],
+            M,
+            N,
+            i,
+            j,
+            Xij;
+          M = 0;
+          N = 0;
+          for (i = 0; i < m; ++i) M += X[i][0].length;
+          for (j = 0; j < n; ++j) N += X[0][j][0].length;
+          var Z = Array(M);
+          for (i = 0; i < M; ++i) Z[i] = Array(N);
+          var I = 0,
+            J,
+            ZI,
+            k,
+            l,
+            Xijk;
+          for (i = 0; i < m; ++i) {
+            J = N;
+            for (j = n - 1; j !== -1; --j) {
+              Xij = X[i][j];
+              J -= Xij[0].length;
+              for (k = Xij.length - 1; k !== -1; --k) {
+                Xijk = Xij[k];
+                ZI = Z[I + k];
+                for (l = Xijk.length - 1; l !== -1; --l) ZI[J + l] = Xijk[l];
+              }
+            }
+            I += X[i][0].length;
+          }
+          return Z;
+        };
+
+        numeric.tensor = function tensor(x, y) {
+          if (typeof x === "number" || typeof y === "number") return numeric.mul(x, y);
+          var s1 = numeric.dim(x),
+            s2 = numeric.dim(y);
+          if (s1.length !== 1 || s2.length !== 1) {
+            throw new Error("numeric: tensor product is only defined for vectors");
+          }
+          var m = s1[0],
+            n = s2[0],
+            A = Array(m),
+            Ai,
+            i,
+            j,
+            xi;
+          for (i = m - 1; i >= 0; i--) {
+            Ai = Array(n);
+            xi = x[i];
+            for (j = n - 1; j >= 3; --j) {
+              Ai[j] = xi * y[j];
+              --j;
+              Ai[j] = xi * y[j];
+              --j;
+              Ai[j] = xi * y[j];
+              --j;
+              Ai[j] = xi * y[j];
+            }
+            while (j >= 0) {
+              Ai[j] = xi * y[j];
+              --j;
+            }
+            A[i] = Ai;
+          }
+          return A;
+        };
+
+        // 3. The Tensor type T
+        numeric.T = function T(x, y) {
+          this.x = x;
+          this.y = y;
+        };
+        numeric.t = function t(x, y) {
+          return new numeric.T(x, y);
+        };
+
+        numeric.Tbinop = function Tbinop(rr, rc, cr, cc, setup) {
+          var io = numeric.indexOf;
+          if (typeof setup !== "string") {
+            var k;
+            setup = "";
+            for (k in numeric) {
+              if (
+                numeric.hasOwnProperty(k) &&
+                (rr.indexOf(k) >= 0 ||
+                  rc.indexOf(k) >= 0 ||
+                  cr.indexOf(k) >= 0 ||
+                  cc.indexOf(k) >= 0) &&
+                k.length > 1
+              ) {
+                setup += "var " + k + " = numeric." + k + ";\n";
+              }
+            }
+          }
+          return Function(
+            ["y"],
+            "var x = this;\n" +
+              "if(!(y instanceof numeric.T)) { y = new numeric.T(y); }\n" +
+              setup +
+              "\n" +
+              "if(x.y) {" +
+              "  if(y.y) {" +
+              "    return new numeric.T(" +
+              cc +
+              ");\n" +
+              "  }\n" +
+              "  return new numeric.T(" +
+              cr +
+              ");\n" +
+              "}\n" +
+              "if(y.y) {\n" +
+              "  return new numeric.T(" +
+              rc +
+              ");\n" +
+              "}\n" +
+              "return new numeric.T(" +
+              rr +
+              ");\n"
+          );
+        };
+
+        numeric.T.prototype.add = numeric.Tbinop(
+          "add(x.x,y.x)",
+          "add(x.x,y.x),y.y",
+          "add(x.x,y.x),x.y",
+          "add(x.x,y.x),add(x.y,y.y)"
+        );
+        numeric.T.prototype.sub = numeric.Tbinop(
+          "sub(x.x,y.x)",
+          "sub(x.x,y.x),neg(y.y)",
+          "sub(x.x,y.x),x.y",
+          "sub(x.x,y.x),sub(x.y,y.y)"
+        );
+        numeric.T.prototype.mul = numeric.Tbinop(
+          "mul(x.x,y.x)",
+          "mul(x.x,y.x),mul(x.x,y.y)",
+          "mul(x.x,y.x),mul(x.y,y.x)",
+          "sub(mul(x.x,y.x),mul(x.y,y.y)),add(mul(x.x,y.y),mul(x.y,y.x))"
+        );
+
+        numeric.T.prototype.reciprocal = function reciprocal() {
+          var mul = numeric.mul,
+            div = numeric.div;
+          if (this.y) {
+            var d = numeric.add(mul(this.x, this.x), mul(this.y, this.y));
+            return new numeric.T(div(this.x, d), div(numeric.neg(this.y), d));
+          }
+          return new T(div(1, this.x));
+        };
+        numeric.T.prototype.div = function div(y) {
+          if (!(y instanceof numeric.T)) y = new numeric.T(y);
+          if (y.y) {
+            return this.mul(y.reciprocal());
+          }
+          var div = numeric.div;
+          if (this.y) {
+            return new numeric.T(div(this.x, y.x), div(this.y, y.x));
+          }
+          return new numeric.T(div(this.x, y.x));
+        };
+        numeric.T.prototype.dot = numeric.Tbinop(
+          "dot(x.x,y.x)",
+          "dot(x.x,y.x),dot(x.x,y.y)",
+          "dot(x.x,y.x),dot(x.y,y.x)",
+          "sub(dot(x.x,y.x),dot(x.y,y.y)),add(dot(x.x,y.y),dot(x.y,y.x))"
+        );
+        numeric.T.prototype.transpose = function transpose() {
+          var t = numeric.transpose,
+            x = this.x,
+            y = this.y;
+          if (y) {
+            return new numeric.T(t(x), t(y));
+          }
+          return new numeric.T(t(x));
+        };
+        numeric.T.prototype.transjugate = function transjugate() {
+          var t = numeric.transpose,
+            x = this.x,
+            y = this.y;
+          if (y) {
+            return new numeric.T(t(x), numeric.negtranspose(y));
+          }
+          return new numeric.T(t(x));
+        };
+        numeric.Tunop = function Tunop(r, c, s) {
+          if (typeof s !== "string") {
+            s = "";
+          }
+          return Function(
+            "var x = this;\n" + s + "\n" + "if(x.y) {" + "  " + c + ";\n" + "}\n" + r + ";\n"
+          );
+        };
+
+        numeric.T.prototype.exp = numeric.Tunop(
+          "return new numeric.T(ex)",
+          "return new numeric.T(mul(cos(x.y),ex),mul(sin(x.y),ex))",
+          "var ex = numeric.exp(x.x), cos = numeric.cos, sin = numeric.sin, mul = numeric.mul;"
+        );
+        numeric.T.prototype.conj = numeric.Tunop(
+          "return new numeric.T(x.x);",
+          "return new numeric.T(x.x,numeric.neg(x.y));"
+        );
+        numeric.T.prototype.neg = numeric.Tunop(
+          "return new numeric.T(neg(x.x));",
+          "return new numeric.T(neg(x.x),neg(x.y));",
+          "var neg = numeric.neg;"
+        );
+        numeric.T.prototype.sin = numeric.Tunop(
+          "return new numeric.T(numeric.sin(x.x))",
+          "return x.exp().sub(x.neg().exp()).div(new numeric.T(0,2));"
+        );
+        numeric.T.prototype.cos = numeric.Tunop(
+          "return new numeric.T(numeric.cos(x.x))",
+          "return x.exp().add(x.neg().exp()).div(2);"
+        );
+        numeric.T.prototype.abs = numeric.Tunop(
+          "return new numeric.T(numeric.abs(x.x));",
+          "return new numeric.T(numeric.sqrt(numeric.add(mul(x.x,x.x),mul(x.y,x.y))));",
+          "var mul = numeric.mul;"
+        );
+        numeric.T.prototype.log = numeric.Tunop(
+          "return new numeric.T(numeric.log(x.x));",
+          "var theta = new numeric.T(numeric.atan2(x.y,x.x)), r = x.abs();\n" +
+            "return new numeric.T(numeric.log(r.x),theta.x);"
+        );
+        numeric.T.prototype.norm2 = numeric.Tunop(
+          "return numeric.norm2(x.x);",
+          "var f = numeric.norm2Squared;\n" + "return Math.sqrt(f(x.x)+f(x.y));"
+        );
+        numeric.T.prototype.inv = function inv() {
+          var A = this;
+          if (typeof A.y === "undefined") {
+            return new numeric.T(numeric.inv(A.x));
+          }
+          var n = A.x.length,
+            i,
+            j,
+            k;
+          var Rx = numeric.identity(n),
+            Ry = numeric.rep([n, n], 0);
+          var Ax = numeric.clone(A.x),
+            Ay = numeric.clone(A.y);
+          var Aix, Aiy, Ajx, Ajy, Rix, Riy, Rjx, Rjy;
+          var i, j, k, d, d1, ax, ay, bx, by, temp;
+          for (i = 0; i < n; i++) {
+            ax = Ax[i][i];
+            ay = Ay[i][i];
+            d = ax * ax + ay * ay;
+            k = i;
+            for (j = i + 1; j < n; j++) {
+              ax = Ax[j][i];
+              ay = Ay[j][i];
+              d1 = ax * ax + ay * ay;
+              if (d1 > d) {
+                k = j;
+                d = d1;
+              }
+            }
+            if (k !== i) {
+              temp = Ax[i];
+              Ax[i] = Ax[k];
+              Ax[k] = temp;
+              temp = Ay[i];
+              Ay[i] = Ay[k];
+              Ay[k] = temp;
+              temp = Rx[i];
+              Rx[i] = Rx[k];
+              Rx[k] = temp;
+              temp = Ry[i];
+              Ry[i] = Ry[k];
+              Ry[k] = temp;
+            }
+            Aix = Ax[i];
+            Aiy = Ay[i];
+            Rix = Rx[i];
+            Riy = Ry[i];
+            ax = Aix[i];
+            ay = Aiy[i];
+            for (j = i + 1; j < n; j++) {
+              bx = Aix[j];
+              by = Aiy[j];
+              Aix[j] = (bx * ax + by * ay) / d;
+              Aiy[j] = (by * ax - bx * ay) / d;
+            }
+            for (j = 0; j < n; j++) {
+              bx = Rix[j];
+              by = Riy[j];
+              Rix[j] = (bx * ax + by * ay) / d;
+              Riy[j] = (by * ax - bx * ay) / d;
+            }
+            for (j = i + 1; j < n; j++) {
+              Ajx = Ax[j];
+              Ajy = Ay[j];
+              Rjx = Rx[j];
+              Rjy = Ry[j];
+              ax = Ajx[i];
+              ay = Ajy[i];
+              for (k = i + 1; k < n; k++) {
+                bx = Aix[k];
+                by = Aiy[k];
+                Ajx[k] -= bx * ax - by * ay;
+                Ajy[k] -= by * ax + bx * ay;
+              }
+              for (k = 0; k < n; k++) {
+                bx = Rix[k];
+                by = Riy[k];
+                Rjx[k] -= bx * ax - by * ay;
+                Rjy[k] -= by * ax + bx * ay;
+              }
+            }
+          }
+          for (i = n - 1; i > 0; i--) {
+            Rix = Rx[i];
+            Riy = Ry[i];
+            for (j = i - 1; j >= 0; j--) {
+              Rjx = Rx[j];
+              Rjy = Ry[j];
+              ax = Ax[j][i];
+              ay = Ay[j][i];
+              for (k = n - 1; k >= 0; k--) {
+                bx = Rix[k];
+                by = Riy[k];
+                Rjx[k] -= ax * bx - ay * by;
+                Rjy[k] -= ax * by + ay * bx;
+              }
+            }
+          }
+          return new numeric.T(Rx, Ry);
+        };
+        numeric.T.prototype.get = function get(i) {
+          var x = this.x,
+            y = this.y,
+            k = 0,
+            ik,
+            n = i.length;
+          if (y) {
+            while (k < n) {
+              ik = i[k];
+              x = x[ik];
+              y = y[ik];
+              k++;
+            }
+            return new numeric.T(x, y);
+          }
+          while (k < n) {
+            ik = i[k];
+            x = x[ik];
+            k++;
+          }
+          return new numeric.T(x);
+        };
+        numeric.T.prototype.set = function set(i, v) {
+          var x = this.x,
+            y = this.y,
+            k = 0,
+            ik,
+            n = i.length,
+            vx = v.x,
+            vy = v.y;
+          if (n === 0) {
+            if (vy) {
+              this.y = vy;
+            } else if (y) {
+              this.y = undefined;
+            }
+            this.x = x;
+            return this;
+          }
+          if (vy) {
+            if (y) {
+              /* ok */
+            } else {
+              y = numeric.rep(numeric.dim(x), 0);
+              this.y = y;
+            }
+            while (k < n - 1) {
+              ik = i[k];
+              x = x[ik];
+              y = y[ik];
+              k++;
+            }
+            ik = i[k];
+            x[ik] = vx;
+            y[ik] = vy;
+            return this;
+          }
+          if (y) {
+            while (k < n - 1) {
+              ik = i[k];
+              x = x[ik];
+              y = y[ik];
+              k++;
+            }
+            ik = i[k];
+            x[ik] = vx;
+            if (vx instanceof Array) y[ik] = numeric.rep(numeric.dim(vx), 0);
+            else y[ik] = 0;
+            return this;
+          }
+          while (k < n - 1) {
+            ik = i[k];
+            x = x[ik];
+            k++;
+          }
+          ik = i[k];
+          x[ik] = vx;
+          return this;
+        };
+        numeric.T.prototype.getRows = function getRows(i0, i1) {
+          var n = i1 - i0 + 1,
+            j;
+          var rx = Array(n),
+            ry,
+            x = this.x,
+            y = this.y;
+          for (j = i0; j <= i1; j++) {
+            rx[j - i0] = x[j];
+          }
+          if (y) {
+            ry = Array(n);
+            for (j = i0; j <= i1; j++) {
+              ry[j - i0] = y[j];
+            }
+            return new numeric.T(rx, ry);
+          }
+          return new numeric.T(rx);
+        };
+        numeric.T.prototype.setRows = function setRows(i0, i1, A) {
+          var j;
+          var rx = this.x,
+            ry = this.y,
+            x = A.x,
+            y = A.y;
+          for (j = i0; j <= i1; j++) {
+            rx[j] = x[j - i0];
+          }
+          if (y) {
+            if (!ry) {
+              ry = numeric.rep(numeric.dim(rx), 0);
+              this.y = ry;
+            }
+            for (j = i0; j <= i1; j++) {
+              ry[j] = y[j - i0];
+            }
+          } else if (ry) {
+            for (j = i0; j <= i1; j++) {
+              ry[j] = numeric.rep([x[j - i0].length], 0);
+            }
+          }
+          return this;
+        };
+        numeric.T.prototype.getRow = function getRow(k) {
+          var x = this.x,
+            y = this.y;
+          if (y) {
+            return new numeric.T(x[k], y[k]);
+          }
+          return new numeric.T(x[k]);
+        };
+        numeric.T.prototype.setRow = function setRow(i, v) {
+          var rx = this.x,
+            ry = this.y,
+            x = v.x,
+            y = v.y;
+          rx[i] = x;
+          if (y) {
+            if (!ry) {
+              ry = numeric.rep(numeric.dim(rx), 0);
+              this.y = ry;
+            }
+            ry[i] = y;
+          } else if (ry) {
+            ry = numeric.rep([x.length], 0);
+          }
+          return this;
+        };
+
+        numeric.T.prototype.getBlock = function getBlock(from, to) {
+          var x = this.x,
+            y = this.y,
+            b = numeric.getBlock;
+          if (y) {
+            return new numeric.T(b(x, from, to), b(y, from, to));
+          }
+          return new numeric.T(b(x, from, to));
+        };
+        numeric.T.prototype.setBlock = function setBlock(from, to, A) {
+          if (!(A instanceof numeric.T)) A = new numeric.T(A);
+          var x = this.x,
+            y = this.y,
+            b = numeric.setBlock,
+            Ax = A.x,
+            Ay = A.y;
+          if (Ay) {
+            if (!y) {
+              this.y = numeric.rep(numeric.dim(this), 0);
+              y = this.y;
+            }
+            b(x, from, to, Ax);
+            b(y, from, to, Ay);
+            return this;
+          }
+          b(x, from, to, Ax);
+          if (y) b(y, from, to, numeric.rep(numeric.dim(Ax), 0));
+        };
+        numeric.T.rep = function rep(s, v) {
+          var T = numeric.T;
+          if (!(v instanceof T)) v = new T(v);
+          var x = v.x,
+            y = v.y,
+            r = numeric.rep;
+          if (y) return new T(r(s, x), r(s, y));
+          return new T(r(s, x));
+        };
+        numeric.T.diag = function diag(d) {
+          if (!(d instanceof numeric.T)) d = new numeric.T(d);
+          var x = d.x,
+            y = d.y,
+            diag = numeric.diag;
+          if (y) return new numeric.T(diag(x), diag(y));
+          return new numeric.T(diag(x));
+        };
+        numeric.T.eig = function eig() {
+          if (this.y) {
+            throw new Error("eig: not implemented for complex matrices.");
+          }
+          return numeric.eig(this.x);
+        };
+        numeric.T.identity = function identity(n) {
+          return new numeric.T(numeric.identity(n));
+        };
+        numeric.T.prototype.getDiag = function getDiag() {
+          var n = numeric;
+          var x = this.x,
+            y = this.y;
+          if (y) {
+            return new n.T(n.getDiag(x), n.getDiag(y));
+          }
+          return new n.T(n.getDiag(x));
+        };
+
+        // 4. Eigenvalues of real matrices
+
+        numeric.house = function house(x) {
+          var v = numeric.clone(x);
+          var s = x[0] >= 0 ? 1 : -1;
+          var alpha = s * numeric.norm2(x);
+          v[0] += alpha;
+          var foo = numeric.norm2(v);
+          if (foo === 0) {
+            /* this should not happen */ throw new Error("eig: internal error");
+          }
+          return numeric.div(v, foo);
+        };
+
+        numeric.toUpperHessenberg = function toUpperHessenberg(me) {
+          var s = numeric.dim(me);
+          if (s.length !== 2 || s[0] !== s[1]) {
+            throw new Error("numeric: toUpperHessenberg() only works on square matrices");
+          }
+          var m = s[0],
+            i,
+            j,
+            k,
+            x,
+            v,
+            A = numeric.clone(me),
+            B,
+            C,
+            Ai,
+            Ci,
+            Q = numeric.identity(m),
+            Qi;
+          for (j = 0; j < m - 2; j++) {
+            x = Array(m - j - 1);
+            for (i = j + 1; i < m; i++) {
+              x[i - j - 1] = A[i][j];
+            }
+            if (numeric.norm2(x) > 0) {
+              v = numeric.house(x);
+              B = numeric.getBlock(A, [j + 1, j], [m - 1, m - 1]);
+              C = numeric.tensor(v, numeric.dot(v, B));
+              for (i = j + 1; i < m; i++) {
+                Ai = A[i];
+                Ci = C[i - j - 1];
+                for (k = j; k < m; k++) Ai[k] -= 2 * Ci[k - j];
+              }
+              B = numeric.getBlock(A, [0, j + 1], [m - 1, m - 1]);
+              C = numeric.tensor(numeric.dot(B, v), v);
+              for (i = 0; i < m; i++) {
+                Ai = A[i];
+                Ci = C[i];
+                for (k = j + 1; k < m; k++) Ai[k] -= 2 * Ci[k - j - 1];
+              }
+              B = Array(m - j - 1);
+              for (i = j + 1; i < m; i++) B[i - j - 1] = Q[i];
+              C = numeric.tensor(v, numeric.dot(v, B));
+              for (i = j + 1; i < m; i++) {
+                Qi = Q[i];
+                Ci = C[i - j - 1];
+                for (k = 0; k < m; k++) Qi[k] -= 2 * Ci[k];
+              }
+            }
+          }
+          return { H: A, Q: Q };
+        };
+
+        numeric.epsilon = 2.220446049250313e-16;
+
+        numeric.QRFrancis = function (H, maxiter) {
+          if (typeof maxiter === "undefined") {
+            maxiter = 10000;
+          }
+          H = numeric.clone(H);
+          var H0 = numeric.clone(H);
+          var s = numeric.dim(H),
+            m = s[0],
+            x,
+            v,
+            a,
+            b,
+            c,
+            d,
+            det,
+            tr,
+            Hloc,
+            Q = numeric.identity(m),
+            Qi,
+            Hi,
+            B,
+            C,
+            Ci,
+            i,
+            j,
+            k,
+            iter;
+          if (m < 3) {
+            return { Q: Q, B: [[0, m - 1]] };
+          }
+          var epsilon = numeric.epsilon;
+          for (iter = 0; iter < maxiter; iter++) {
+            for (j = 0; j < m - 1; j++) {
+              if (
+                Math.abs(H[j + 1][j]) <
+                epsilon * (Math.abs(H[j][j]) + Math.abs(H[j + 1][j + 1]))
+              ) {
+                var QH1 = numeric.QRFrancis(numeric.getBlock(H, [0, 0], [j, j]), maxiter);
+                var QH2 = numeric.QRFrancis(
+                  numeric.getBlock(H, [j + 1, j + 1], [m - 1, m - 1]),
+                  maxiter
+                );
+                B = Array(j + 1);
+                for (i = 0; i <= j; i++) {
+                  B[i] = Q[i];
+                }
+                C = numeric.dot(QH1.Q, B);
+                for (i = 0; i <= j; i++) {
+                  Q[i] = C[i];
+                }
+                B = Array(m - j - 1);
+                for (i = j + 1; i < m; i++) {
+                  B[i - j - 1] = Q[i];
+                }
+                C = numeric.dot(QH2.Q, B);
+                for (i = j + 1; i < m; i++) {
+                  Q[i] = C[i - j - 1];
+                }
+                return { Q: Q, B: QH1.B.concat(numeric.add(QH2.B, j + 1)) };
+              }
+            }
+            a = H[m - 2][m - 2];
+            b = H[m - 2][m - 1];
+            c = H[m - 1][m - 2];
+            d = H[m - 1][m - 1];
+            tr = a + d;
+            det = a * d - b * c;
+            Hloc = numeric.getBlock(H, [0, 0], [2, 2]);
+            if (tr * tr >= 4 * det) {
+              var s1, s2;
+              s1 = 0.5 * (tr + Math.sqrt(tr * tr - 4 * det));
+              s2 = 0.5 * (tr - Math.sqrt(tr * tr - 4 * det));
+              Hloc = numeric.add(
+                numeric.sub(numeric.dot(Hloc, Hloc), numeric.mul(Hloc, s1 + s2)),
+                numeric.diag(numeric.rep([3], s1 * s2))
+              );
+            } else {
+              Hloc = numeric.add(
+                numeric.sub(numeric.dot(Hloc, Hloc), numeric.mul(Hloc, tr)),
+                numeric.diag(numeric.rep([3], det))
+              );
+            }
+            x = [Hloc[0][0], Hloc[1][0], Hloc[2][0]];
+            v = numeric.house(x);
+            B = [H[0], H[1], H[2]];
+            C = numeric.tensor(v, numeric.dot(v, B));
+            for (i = 0; i < 3; i++) {
+              Hi = H[i];
+              Ci = C[i];
+              for (k = 0; k < m; k++) Hi[k] -= 2 * Ci[k];
+            }
+            B = numeric.getBlock(H, [0, 0], [m - 1, 2]);
+            C = numeric.tensor(numeric.dot(B, v), v);
+            for (i = 0; i < m; i++) {
+              Hi = H[i];
+              Ci = C[i];
+              for (k = 0; k < 3; k++) Hi[k] -= 2 * Ci[k];
+            }
+            B = [Q[0], Q[1], Q[2]];
+            C = numeric.tensor(v, numeric.dot(v, B));
+            for (i = 0; i < 3; i++) {
+              Qi = Q[i];
+              Ci = C[i];
+              for (k = 0; k < m; k++) Qi[k] -= 2 * Ci[k];
+            }
+            var J;
+            for (j = 0; j < m - 2; j++) {
+              for (k = j; k <= j + 1; k++) {
+                if (
+                  Math.abs(H[k + 1][k]) <
+                  epsilon * (Math.abs(H[k][k]) + Math.abs(H[k + 1][k + 1]))
+                ) {
+                  var QH1 = numeric.QRFrancis(numeric.getBlock(H, [0, 0], [k, k]), maxiter);
+                  var QH2 = numeric.QRFrancis(
+                    numeric.getBlock(H, [k + 1, k + 1], [m - 1, m - 1]),
+                    maxiter
+                  );
+                  B = Array(k + 1);
+                  for (i = 0; i <= k; i++) {
+                    B[i] = Q[i];
+                  }
+                  C = numeric.dot(QH1.Q, B);
+                  for (i = 0; i <= k; i++) {
+                    Q[i] = C[i];
+                  }
+                  B = Array(m - k - 1);
+                  for (i = k + 1; i < m; i++) {
+                    B[i - k - 1] = Q[i];
+                  }
+                  C = numeric.dot(QH2.Q, B);
+                  for (i = k + 1; i < m; i++) {
+                    Q[i] = C[i - k - 1];
+                  }
+                  return { Q: Q, B: QH1.B.concat(numeric.add(QH2.B, k + 1)) };
+                }
+              }
+              J = Math.min(m - 1, j + 3);
+              x = Array(J - j);
+              for (i = j + 1; i <= J; i++) {
+                x[i - j - 1] = H[i][j];
+              }
+              v = numeric.house(x);
+              B = numeric.getBlock(H, [j + 1, j], [J, m - 1]);
+              C = numeric.tensor(v, numeric.dot(v, B));
+              for (i = j + 1; i <= J; i++) {
+                Hi = H[i];
+                Ci = C[i - j - 1];
+                for (k = j; k < m; k++) Hi[k] -= 2 * Ci[k - j];
+              }
+              B = numeric.getBlock(H, [0, j + 1], [m - 1, J]);
+              C = numeric.tensor(numeric.dot(B, v), v);
+              for (i = 0; i < m; i++) {
+                Hi = H[i];
+                Ci = C[i];
+                for (k = j + 1; k <= J; k++) Hi[k] -= 2 * Ci[k - j - 1];
+              }
+              B = Array(J - j);
+              for (i = j + 1; i <= J; i++) B[i - j - 1] = Q[i];
+              C = numeric.tensor(v, numeric.dot(v, B));
+              for (i = j + 1; i <= J; i++) {
+                Qi = Q[i];
+                Ci = C[i - j - 1];
+                for (k = 0; k < m; k++) Qi[k] -= 2 * Ci[k];
+              }
+            }
+          }
+          throw new Error("numeric: eigenvalue iteration does not converge -- increase maxiter?");
+        };
+
+        numeric.eig = function eig(A, maxiter) {
+          var QH = numeric.toUpperHessenberg(A);
+          var QB = numeric.QRFrancis(QH.H, maxiter);
+          var T = numeric.T;
+          var n = A.length,
+            i,
+            k,
+            flag = false,
+            B = QB.B,
+            H = numeric.dot(QB.Q, numeric.dot(QH.H, numeric.transpose(QB.Q)));
+          var Q = new T(numeric.dot(QB.Q, QH.Q)),
+            Q0;
+          var m = B.length,
+            j;
+          var a, b, c, d, p1, p2, disc, x, y, p, q, n1, n2;
+          var sqrt = Math.sqrt;
+          for (k = 0; k < m; k++) {
+            i = B[k][0];
+            if (i === B[k][1]) {
+              // nothing
+            } else {
+              j = i + 1;
+              a = H[i][i];
+              b = H[i][j];
+              c = H[j][i];
+              d = H[j][j];
+              if (b === 0 && c === 0) continue;
+              p1 = -a - d;
+              p2 = a * d - b * c;
+              disc = p1 * p1 - 4 * p2;
+              if (disc >= 0) {
+                if (p1 < 0) x = -0.5 * (p1 - sqrt(disc));
+                else x = -0.5 * (p1 + sqrt(disc));
+                n1 = (a - x) * (a - x) + b * b;
+                n2 = c * c + (d - x) * (d - x);
+                if (n1 > n2) {
+                  n1 = sqrt(n1);
+                  p = (a - x) / n1;
+                  q = b / n1;
+                } else {
+                  n2 = sqrt(n2);
+                  p = c / n2;
+                  q = (d - x) / n2;
+                }
+                Q0 = new T([
+                  [q, -p],
+                  [p, q],
+                ]);
+                Q.setRows(i, j, Q0.dot(Q.getRows(i, j)));
+              } else {
+                x = -0.5 * p1;
+                y = 0.5 * sqrt(-disc);
+                n1 = (a - x) * (a - x) + b * b;
+                n2 = c * c + (d - x) * (d - x);
+                if (n1 > n2) {
+                  n1 = sqrt(n1 + y * y);
+                  p = (a - x) / n1;
+                  q = b / n1;
+                  x = 0;
+                  y /= n1;
+                } else {
+                  n2 = sqrt(n2 + y * y);
+                  p = c / n2;
+                  q = (d - x) / n2;
+                  x = y / n2;
+                  y = 0;
+                }
+                Q0 = new T(
+                  [
+                    [q, -p],
+                    [p, q],
+                  ],
+                  [
+                    [x, y],
+                    [y, -x],
+                  ]
+                );
+                Q.setRows(i, j, Q0.dot(Q.getRows(i, j)));
+              }
+            }
+          }
+          var R = Q.dot(A).dot(Q.transjugate()),
+            n = A.length,
+            E = numeric.T.identity(n);
+          for (j = 0; j < n; j++) {
+            if (j > 0) {
+              for (k = j - 1; k >= 0; k--) {
+                var Rk = R.get([k, k]),
+                  Rj = R.get([j, j]);
+                if (numeric.neq(Rk.x, Rj.x) || numeric.neq(Rk.y, Rj.y)) {
+                  x = R.getRow(k).getBlock([k], [j - 1]);
+                  y = E.getRow(j).getBlock([k], [j - 1]);
+                  E.set([j, k], R.get([k, j]).neg().sub(x.dot(y)).div(Rk.sub(Rj)));
+                } else {
+                  E.setRow(j, E.getRow(k));
+                  continue;
+                }
+              }
+            }
+          }
+          for (j = 0; j < n; j++) {
+            x = E.getRow(j);
+            E.setRow(j, x.div(x.norm2()));
+          }
+          E = E.transpose();
+          E = Q.transjugate().dot(E);
+          return { lambda: R.getDiag(), E: E };
+        };
+
+        // 5. Compressed Column Storage matrices
+        numeric.ccsSparse = function ccsSparse(A) {
+          var m = A.length,
+            n,
+            foo,
+            i,
+            j,
+            counts = [];
+          for (i = m - 1; i !== -1; --i) {
+            foo = A[i];
+            for (j in foo) {
+              j = parseInt(j);
+              while (j >= counts.length) counts[counts.length] = 0;
+              if (foo[j] !== 0) counts[j]++;
+            }
+          }
+          var n = counts.length;
+          var Ai = Array(n + 1);
+          Ai[0] = 0;
+          for (i = 0; i < n; ++i) Ai[i + 1] = Ai[i] + counts[i];
+          var Aj = Array(Ai[n]),
+            Av = Array(Ai[n]);
+          for (i = m - 1; i !== -1; --i) {
+            foo = A[i];
+            for (j in foo) {
+              if (foo[j] !== 0) {
+                counts[j]--;
+                Aj[Ai[j] + counts[j]] = i;
+                Av[Ai[j] + counts[j]] = foo[j];
+              }
+            }
+          }
+          return [Ai, Aj, Av];
+        };
+        numeric.ccsFull = function ccsFull(A) {
+          var Ai = A[0],
+            Aj = A[1],
+            Av = A[2],
+            s = numeric.ccsDim(A),
+            m = s[0],
+            n = s[1],
+            i,
+            j,
+            j0,
+            j1,
+            k;
+          var B = numeric.rep([m, n], 0);
+          for (i = 0; i < n; i++) {
+            j0 = Ai[i];
+            j1 = Ai[i + 1];
+            for (j = j0; j < j1; ++j) {
+              B[Aj[j]][i] = Av[j];
+            }
+          }
+          return B;
+        };
+        numeric.ccsTSolve = function ccsTSolve(A, b, x, bj, xj) {
+          var Ai = A[0],
+            Aj = A[1],
+            Av = A[2],
+            m = Ai.length - 1,
+            max = Math.max,
+            n = 0;
+          if (typeof bj === "undefined") x = numeric.rep([m], 0);
+          if (typeof bj === "undefined") bj = numeric.linspace(0, x.length - 1);
+          if (typeof xj === "undefined") xj = [];
+          function dfs(j) {
+            var k;
+            if (x[j] !== 0) return;
+            x[j] = 1;
+            for (k = Ai[j]; k < Ai[j + 1]; ++k) dfs(Aj[k]);
+            xj[n] = j;
+            ++n;
+          }
+          var i, j, j0, j1, k, l, l0, l1, a;
+          for (i = bj.length - 1; i !== -1; --i) {
+            dfs(bj[i]);
+          }
+          xj.length = n;
+          for (i = xj.length - 1; i !== -1; --i) {
+            x[xj[i]] = 0;
+          }
+          for (i = bj.length - 1; i !== -1; --i) {
+            j = bj[i];
+            x[j] = b[j];
+          }
+          for (i = xj.length - 1; i !== -1; --i) {
+            j = xj[i];
+            j0 = Ai[j];
+            j1 = max(Ai[j + 1], j0);
+            for (k = j0; k !== j1; ++k) {
+              if (Aj[k] === j) {
+                x[j] /= Av[k];
+                break;
+              }
+            }
+            a = x[j];
+            for (k = j0; k !== j1; ++k) {
+              l = Aj[k];
+              if (l !== j) x[l] -= a * Av[k];
+            }
+          }
+          return x;
+        };
+        numeric.ccsDFS = function ccsDFS(n) {
+          this.k = Array(n);
+          this.k1 = Array(n);
+          this.j = Array(n);
+        };
+        numeric.ccsDFS.prototype.dfs = function dfs(J, Ai, Aj, x, xj, Pinv) {
+          var m = 0,
+            foo,
+            n = xj.length;
+          var k = this.k,
+            k1 = this.k1,
+            j = this.j,
+            km,
+            k11;
+          if (x[J] !== 0) return;
+          x[J] = 1;
+          j[0] = J;
+          k[0] = km = Ai[J];
+          k1[0] = k11 = Ai[J + 1];
+          while (1) {
+            if (km >= k11) {
+              xj[n] = j[m];
+              if (m === 0) return;
+              ++n;
+              --m;
+              km = k[m];
+              k11 = k1[m];
+            } else {
+              foo = Pinv[Aj[km]];
+              if (x[foo] === 0) {
+                x[foo] = 1;
+                k[m] = km;
+                ++m;
+                j[m] = foo;
+                km = Ai[foo];
+                k1[m] = k11 = Ai[foo + 1];
+              } else ++km;
+            }
+          }
+        };
+        numeric.ccsLPSolve = function ccsLPSolve(A, B, x, xj, I, Pinv, dfs) {
+          var Ai = A[0],
+            Aj = A[1],
+            Av = A[2],
+            m = Ai.length - 1,
+            n = 0;
+          var Bi = B[0],
+            Bj = B[1],
+            Bv = B[2];
+
+          var i, i0, i1, j, J, j0, j1, k, l, l0, l1, a;
+          i0 = Bi[I];
+          i1 = Bi[I + 1];
+          xj.length = 0;
+          for (i = i0; i < i1; ++i) {
+            dfs.dfs(Pinv[Bj[i]], Ai, Aj, x, xj, Pinv);
+          }
+          for (i = xj.length - 1; i !== -1; --i) {
+            x[xj[i]] = 0;
+          }
+          for (i = i0; i !== i1; ++i) {
+            j = Pinv[Bj[i]];
+            x[j] = Bv[i];
+          }
+          for (i = xj.length - 1; i !== -1; --i) {
+            j = xj[i];
+            j0 = Ai[j];
+            j1 = Ai[j + 1];
+            for (k = j0; k < j1; ++k) {
+              if (Pinv[Aj[k]] === j) {
+                x[j] /= Av[k];
+                break;
+              }
+            }
+            a = x[j];
+            for (k = j0; k < j1; ++k) {
+              l = Pinv[Aj[k]];
+              if (l !== j) x[l] -= a * Av[k];
+            }
+          }
+          return x;
+        };
+        numeric.ccsLUP1 = function ccsLUP1(A, threshold) {
+          var m = A[0].length - 1;
+          var L = [numeric.rep([m + 1], 0), [], []],
+            U = [numeric.rep([m + 1], 0), [], []];
+          var Li = L[0],
+            Lj = L[1],
+            Lv = L[2],
+            Ui = U[0],
+            Uj = U[1],
+            Uv = U[2];
+          var x = numeric.rep([m], 0),
+            xj = numeric.rep([m], 0);
+          var i, j, k, j0, j1, a, e, c, d, K;
+          var sol = numeric.ccsLPSolve,
+            max = Math.max,
+            abs = Math.abs;
+          var P = numeric.linspace(0, m - 1),
+            Pinv = numeric.linspace(0, m - 1);
+          var dfs = new numeric.ccsDFS(m);
+          if (typeof threshold === "undefined") {
+            threshold = 1;
+          }
+          for (i = 0; i < m; ++i) {
+            sol(L, A, x, xj, i, Pinv, dfs);
+            a = -1;
+            e = -1;
+            for (j = xj.length - 1; j !== -1; --j) {
+              k = xj[j];
+              if (k <= i) continue;
+              c = abs(x[k]);
+              if (c > a) {
+                e = k;
+                a = c;
+              }
+            }
+            if (abs(x[i]) < threshold * a) {
+              j = P[i];
+              a = P[e];
+              P[i] = a;
+              Pinv[a] = i;
+              P[e] = j;
+              Pinv[j] = e;
+              a = x[i];
+              x[i] = x[e];
+              x[e] = a;
+            }
+            a = Li[i];
+            e = Ui[i];
+            d = x[i];
+            Lj[a] = P[i];
+            Lv[a] = 1;
+            ++a;
+            for (j = xj.length - 1; j !== -1; --j) {
+              k = xj[j];
+              c = x[k];
+              xj[j] = 0;
+              x[k] = 0;
+              if (k <= i) {
+                Uj[e] = k;
+                Uv[e] = c;
+                ++e;
+              } else {
+                Lj[a] = P[k];
+                Lv[a] = c / d;
+                ++a;
+              }
+            }
+            Li[i + 1] = a;
+            Ui[i + 1] = e;
+          }
+          for (j = Lj.length - 1; j !== -1; --j) {
+            Lj[j] = Pinv[Lj[j]];
+          }
+          return { L: L, U: U, P: P, Pinv: Pinv };
+        };
+        numeric.ccsDFS0 = function ccsDFS0(n) {
+          this.k = Array(n);
+          this.k1 = Array(n);
+          this.j = Array(n);
+        };
+        numeric.ccsDFS0.prototype.dfs = function dfs(J, Ai, Aj, x, xj, Pinv, P) {
+          var m = 0,
+            foo,
+            n = xj.length;
+          var k = this.k,
+            k1 = this.k1,
+            j = this.j,
+            km,
+            k11;
+          if (x[J] !== 0) return;
+          x[J] = 1;
+          j[0] = J;
+          k[0] = km = Ai[Pinv[J]];
+          k1[0] = k11 = Ai[Pinv[J] + 1];
+          while (1) {
+            if (isNaN(km)) throw new Error("Ow!");
+            if (km >= k11) {
+              xj[n] = Pinv[j[m]];
+              if (m === 0) return;
+              ++n;
+              --m;
+              km = k[m];
+              k11 = k1[m];
+            } else {
+              foo = Aj[km];
+              if (x[foo] === 0) {
+                x[foo] = 1;
+                k[m] = km;
+                ++m;
+                j[m] = foo;
+                foo = Pinv[foo];
+                km = Ai[foo];
+                k1[m] = k11 = Ai[foo + 1];
+              } else ++km;
+            }
+          }
+        };
+        numeric.ccsLPSolve0 = function ccsLPSolve0(A, B, y, xj, I, Pinv, P, dfs) {
+          var Ai = A[0],
+            Aj = A[1],
+            Av = A[2],
+            m = Ai.length - 1,
+            n = 0;
+          var Bi = B[0],
+            Bj = B[1],
+            Bv = B[2];
+
+          var i, i0, i1, j, J, j0, j1, k, l, l0, l1, a;
+          i0 = Bi[I];
+          i1 = Bi[I + 1];
+          xj.length = 0;
+          for (i = i0; i < i1; ++i) {
+            dfs.dfs(Bj[i], Ai, Aj, y, xj, Pinv, P);
+          }
+          for (i = xj.length - 1; i !== -1; --i) {
+            j = xj[i];
+            y[P[j]] = 0;
+          }
+          for (i = i0; i !== i1; ++i) {
+            j = Bj[i];
+            y[j] = Bv[i];
+          }
+          for (i = xj.length - 1; i !== -1; --i) {
+            j = xj[i];
+            l = P[j];
+            j0 = Ai[j];
+            j1 = Ai[j + 1];
+            for (k = j0; k < j1; ++k) {
+              if (Aj[k] === l) {
+                y[l] /= Av[k];
+                break;
+              }
+            }
+            a = y[l];
+            for (k = j0; k < j1; ++k) y[Aj[k]] -= a * Av[k];
+            y[l] = a;
+          }
+        };
+        numeric.ccsLUP0 = function ccsLUP0(A, threshold) {
+          var m = A[0].length - 1;
+          var L = [numeric.rep([m + 1], 0), [], []],
+            U = [numeric.rep([m + 1], 0), [], []];
+          var Li = L[0],
+            Lj = L[1],
+            Lv = L[2],
+            Ui = U[0],
+            Uj = U[1],
+            Uv = U[2];
+          var y = numeric.rep([m], 0),
+            xj = numeric.rep([m], 0);
+          var i, j, k, j0, j1, a, e, c, d, K;
+          var sol = numeric.ccsLPSolve0,
+            max = Math.max,
+            abs = Math.abs;
+          var P = numeric.linspace(0, m - 1),
+            Pinv = numeric.linspace(0, m - 1);
+          var dfs = new numeric.ccsDFS0(m);
+          if (typeof threshold === "undefined") {
+            threshold = 1;
+          }
+          for (i = 0; i < m; ++i) {
+            sol(L, A, y, xj, i, Pinv, P, dfs);
+            a = -1;
+            e = -1;
+            for (j = xj.length - 1; j !== -1; --j) {
+              k = xj[j];
+              if (k <= i) continue;
+              c = abs(y[P[k]]);
+              if (c > a) {
+                e = k;
+                a = c;
+              }
+            }
+            if (abs(y[P[i]]) < threshold * a) {
+              j = P[i];
+              a = P[e];
+              P[i] = a;
+              Pinv[a] = i;
+              P[e] = j;
+              Pinv[j] = e;
+            }
+            a = Li[i];
+            e = Ui[i];
+            d = y[P[i]];
+            Lj[a] = P[i];
+            Lv[a] = 1;
+            ++a;
+            for (j = xj.length - 1; j !== -1; --j) {
+              k = xj[j];
+              c = y[P[k]];
+              xj[j] = 0;
+              y[P[k]] = 0;
+              if (k <= i) {
+                Uj[e] = k;
+                Uv[e] = c;
+                ++e;
+              } else {
+                Lj[a] = P[k];
+                Lv[a] = c / d;
+                ++a;
+              }
+            }
+            Li[i + 1] = a;
+            Ui[i + 1] = e;
+          }
+          for (j = Lj.length - 1; j !== -1; --j) {
+            Lj[j] = Pinv[Lj[j]];
+          }
+          return { L: L, U: U, P: P, Pinv: Pinv };
+        };
+        numeric.ccsLUP = numeric.ccsLUP0;
+
+        numeric.ccsDim = function ccsDim(A) {
+          return [numeric.sup(A[1]) + 1, A[0].length - 1];
+        };
+        numeric.ccsGetBlock = function ccsGetBlock(A, i, j) {
+          var s = numeric.ccsDim(A),
+            m = s[0],
+            n = s[1];
+          if (typeof i === "undefined") {
+            i = numeric.linspace(0, m - 1);
+          } else if (typeof i === "number") {
+            i = [i];
+          }
+          if (typeof j === "undefined") {
+            j = numeric.linspace(0, n - 1);
+          } else if (typeof j === "number") {
+            j = [j];
+          }
+          var p,
+            p0,
+            p1,
+            P = i.length,
+            q,
+            Q = j.length,
+            r,
+            jq,
+            ip;
+          var Bi = numeric.rep([n], 0),
+            Bj = [],
+            Bv = [],
+            B = [Bi, Bj, Bv];
+          var Ai = A[0],
+            Aj = A[1],
+            Av = A[2];
+          var x = numeric.rep([m], 0),
+            count = 0,
+            flags = numeric.rep([m], 0);
+          for (q = 0; q < Q; ++q) {
+            jq = j[q];
+            var q0 = Ai[jq];
+            var q1 = Ai[jq + 1];
+            for (p = q0; p < q1; ++p) {
+              r = Aj[p];
+              flags[r] = 1;
+              x[r] = Av[p];
+            }
+            for (p = 0; p < P; ++p) {
+              ip = i[p];
+              if (flags[ip]) {
+                Bj[count] = p;
+                Bv[count] = x[i[p]];
+                ++count;
+              }
+            }
+            for (p = q0; p < q1; ++p) {
+              r = Aj[p];
+              flags[r] = 0;
+            }
+            Bi[q + 1] = count;
+          }
+          return B;
+        };
+
+        numeric.ccsDot = function ccsDot(A, B) {
+          var Ai = A[0],
+            Aj = A[1],
+            Av = A[2];
+          var Bi = B[0],
+            Bj = B[1],
+            Bv = B[2];
+          var sA = numeric.ccsDim(A),
+            sB = numeric.ccsDim(B);
+          var m = sA[0],
+            n = sA[1],
+            o = sB[1];
+          var x = numeric.rep([m], 0),
+            flags = numeric.rep([m], 0),
+            xj = Array(m);
+          var Ci = numeric.rep([o], 0),
+            Cj = [],
+            Cv = [],
+            C = [Ci, Cj, Cv];
+          var i, j, k, j0, j1, i0, i1, l, p, a, b;
+          for (k = 0; k !== o; ++k) {
+            j0 = Bi[k];
+            j1 = Bi[k + 1];
+            p = 0;
+            for (j = j0; j < j1; ++j) {
+              a = Bj[j];
+              b = Bv[j];
+              i0 = Ai[a];
+              i1 = Ai[a + 1];
+              for (i = i0; i < i1; ++i) {
+                l = Aj[i];
+                if (flags[l] === 0) {
+                  xj[p] = l;
+                  flags[l] = 1;
+                  p = p + 1;
+                }
+                x[l] = x[l] + Av[i] * b;
+              }
+            }
+            j0 = Ci[k];
+            j1 = j0 + p;
+            Ci[k + 1] = j1;
+            for (j = p - 1; j !== -1; --j) {
+              b = j0 + j;
+              i = xj[j];
+              Cj[b] = i;
+              Cv[b] = x[i];
+              flags[i] = 0;
+              x[i] = 0;
+            }
+            Ci[k + 1] = Ci[k] + p;
+          }
+          return C;
+        };
+
+        numeric.ccsLUPSolve = function ccsLUPSolve(LUP, B) {
+          var L = LUP.L,
+            U = LUP.U,
+            P = LUP.P;
+          var Bi = B[0];
+          var flag = false;
+          if (typeof Bi !== "object") {
+            B = [[0, B.length], numeric.linspace(0, B.length - 1), B];
+            Bi = B[0];
+            flag = true;
+          }
+          var Bj = B[1],
+            Bv = B[2];
+          var n = L[0].length - 1,
+            m = Bi.length - 1;
+          var x = numeric.rep([n], 0),
+            xj = Array(n);
+          var b = numeric.rep([n], 0),
+            bj = Array(n);
+          var Xi = numeric.rep([m + 1], 0),
+            Xj = [],
+            Xv = [];
+          var sol = numeric.ccsTSolve;
+          var i,
+            j,
+            j0,
+            j1,
+            k,
+            J,
+            N = 0;
+          for (i = 0; i < m; ++i) {
+            k = 0;
+            j0 = Bi[i];
+            j1 = Bi[i + 1];
+            for (j = j0; j < j1; ++j) {
+              J = LUP.Pinv[Bj[j]];
+              bj[k] = J;
+              b[J] = Bv[j];
+              ++k;
+            }
+            bj.length = k;
+            sol(L, b, x, bj, xj);
+            for (j = bj.length - 1; j !== -1; --j) b[bj[j]] = 0;
+            sol(U, x, b, xj, bj);
+            if (flag) return b;
+            for (j = xj.length - 1; j !== -1; --j) x[xj[j]] = 0;
+            for (j = bj.length - 1; j !== -1; --j) {
+              J = bj[j];
+              Xj[N] = J;
+              Xv[N] = b[J];
+              b[J] = 0;
+              ++N;
+            }
+            Xi[i + 1] = N;
+          }
+          return [Xi, Xj, Xv];
+        };
+
+        numeric.ccsbinop = function ccsbinop(body, setup) {
+          if (typeof setup === "undefined") setup = "";
+          return Function(
+            "X",
+            "Y",
+            "var Xi = X[0], Xj = X[1], Xv = X[2];\n" +
+              "var Yi = Y[0], Yj = Y[1], Yv = Y[2];\n" +
+              "var n = Xi.length-1,m = Math.max(numeric.sup(Xj),numeric.sup(Yj))+1;\n" +
+              "var Zi = numeric.rep([n+1],0), Zj = [], Zv = [];\n" +
+              "var x = numeric.rep([m],0),y = numeric.rep([m],0);\n" +
+              "var xk,yk,zk;\n" +
+              "var i,j,j0,j1,k,p=0;\n" +
+              setup +
+              "for(i=0;i<n;++i) {\n" +
+              "  j0 = Xi[i]; j1 = Xi[i+1];\n" +
+              "  for(j=j0;j!==j1;++j) {\n" +
+              "    k = Xj[j];\n" +
+              "    x[k] = 1;\n" +
+              "    Zj[p] = k;\n" +
+              "    ++p;\n" +
+              "  }\n" +
+              "  j0 = Yi[i]; j1 = Yi[i+1];\n" +
+              "  for(j=j0;j!==j1;++j) {\n" +
+              "    k = Yj[j];\n" +
+              "    y[k] = Yv[j];\n" +
+              "    if(x[k] === 0) {\n" +
+              "      Zj[p] = k;\n" +
+              "      ++p;\n" +
+              "    }\n" +
+              "  }\n" +
+              "  Zi[i+1] = p;\n" +
+              "  j0 = Xi[i]; j1 = Xi[i+1];\n" +
+              "  for(j=j0;j!==j1;++j) x[Xj[j]] = Xv[j];\n" +
+              "  j0 = Zi[i]; j1 = Zi[i+1];\n" +
+              "  for(j=j0;j!==j1;++j) {\n" +
+              "    k = Zj[j];\n" +
+              "    xk = x[k];\n" +
+              "    yk = y[k];\n" +
+              body +
+              "\n" +
+              "    Zv[j] = zk;\n" +
+              "  }\n" +
+              "  j0 = Xi[i]; j1 = Xi[i+1];\n" +
+              "  for(j=j0;j!==j1;++j) x[Xj[j]] = 0;\n" +
+              "  j0 = Yi[i]; j1 = Yi[i+1];\n" +
+              "  for(j=j0;j!==j1;++j) y[Yj[j]] = 0;\n" +
+              "}\n" +
+              "return [Zi,Zj,Zv];"
+          );
+        };
+
+        (function () {
+          var k, A, B, C;
+          for (k in numeric.ops2) {
+            if (isFinite(eval("1" + numeric.ops2[k] + "0")))
+              A = "[Y[0],Y[1],numeric." + k + "(X,Y[2])]";
+            else A = "NaN";
+            if (isFinite(eval("0" + numeric.ops2[k] + "1")))
+              B = "[X[0],X[1],numeric." + k + "(X[2],Y)]";
+            else B = "NaN";
+            if (
+              isFinite(eval("1" + numeric.ops2[k] + "0")) &&
+              isFinite(eval("0" + numeric.ops2[k] + "1"))
+            )
+              C = "numeric.ccs" + k + "MM(X,Y)";
+            else C = "NaN";
+            numeric["ccs" + k + "MM"] = numeric.ccsbinop("zk = xk " + numeric.ops2[k] + "yk;");
+            numeric["ccs" + k] = Function(
+              "X",
+              "Y",
+              'if(typeof X === "number") return ' +
+                A +
+                ";\n" +
+                'if(typeof Y === "number") return ' +
+                B +
+                ";\n" +
+                "return " +
+                C +
+                ";\n"
+            );
+          }
+        })();
+
+        numeric.ccsScatter = function ccsScatter(A) {
+          var Ai = A[0],
+            Aj = A[1],
+            Av = A[2];
+          var n = numeric.sup(Aj) + 1,
+            m = Ai.length;
+          var Ri = numeric.rep([n], 0),
+            Rj = Array(m),
+            Rv = Array(m);
+          var counts = numeric.rep([n], 0),
+            i;
+          for (i = 0; i < m; ++i) counts[Aj[i]]++;
+          for (i = 0; i < n; ++i) Ri[i + 1] = Ri[i] + counts[i];
+          var ptr = Ri.slice(0),
+            k,
+            Aii;
+          for (i = 0; i < m; ++i) {
+            Aii = Aj[i];
+            k = ptr[Aii];
+            Rj[k] = Ai[i];
+            Rv[k] = Av[i];
+            ptr[Aii] = ptr[Aii] + 1;
+          }
+          return [Ri, Rj, Rv];
+        };
+
+        numeric.ccsGather = function ccsGather(A) {
+          var Ai = A[0],
+            Aj = A[1],
+            Av = A[2];
+          var n = Ai.length - 1,
+            m = Aj.length;
+          var Ri = Array(m),
+            Rj = Array(m),
+            Rv = Array(m);
+          var i, j, j0, j1, p;
+          p = 0;
+          for (i = 0; i < n; ++i) {
+            j0 = Ai[i];
+            j1 = Ai[i + 1];
+            for (j = j0; j !== j1; ++j) {
+              Rj[p] = i;
+              Ri[p] = Aj[j];
+              Rv[p] = Av[j];
+              ++p;
+            }
+          }
+          return [Ri, Rj, Rv];
+        };
+
+        // The following sparse linear algebra routines are deprecated.
+
+        numeric.sdim = function dim(A, ret, k) {
+          if (typeof ret === "undefined") {
+            ret = [];
+          }
+          if (typeof A !== "object") return ret;
+          if (typeof k === "undefined") {
+            k = 0;
+          }
+          if (!(k in ret)) {
+            ret[k] = 0;
+          }
+          if (A.length > ret[k]) ret[k] = A.length;
+          var i;
+          for (i in A) {
+            if (A.hasOwnProperty(i)) dim(A[i], ret, k + 1);
+          }
+          return ret;
+        };
+
+        numeric.sclone = function clone(A, k, n) {
+          if (typeof k === "undefined") {
+            k = 0;
+          }
+          if (typeof n === "undefined") {
+            n = numeric.sdim(A).length;
+          }
+          var i,
+            ret = Array(A.length);
+          if (k === n - 1) {
+            for (i in A) {
+              if (A.hasOwnProperty(i)) ret[i] = A[i];
+            }
+            return ret;
+          }
+          for (i in A) {
+            if (A.hasOwnProperty(i)) ret[i] = clone(A[i], k + 1, n);
+          }
+          return ret;
+        };
+
+        numeric.sdiag = function diag(d) {
+          var n = d.length,
+            i,
+            ret = Array(n),
+            i1,
+            i2,
+            i3;
+          for (i = n - 1; i >= 1; i -= 2) {
+            i1 = i - 1;
+            ret[i] = [];
+            ret[i][i] = d[i];
+            ret[i1] = [];
+            ret[i1][i1] = d[i1];
+          }
+          if (i === 0) {
+            ret[0] = [];
+            ret[0][0] = d[i];
+          }
+          return ret;
+        };
+
+        numeric.sidentity = function identity(n) {
+          return numeric.sdiag(numeric.rep([n], 1));
+        };
+
+        numeric.stranspose = function transpose(A) {
+          var ret = [],
+            n = A.length,
+            i,
+            j,
+            Ai;
+          for (i in A) {
+            if (!A.hasOwnProperty(i)) continue;
+            Ai = A[i];
+            for (j in Ai) {
+              if (!Ai.hasOwnProperty(j)) continue;
+              if (typeof ret[j] !== "object") {
+                ret[j] = [];
+              }
+              ret[j][i] = Ai[j];
+            }
+          }
+          return ret;
+        };
+
+        numeric.sLUP = function LUP(A, tol) {
+          throw new Error(
+            "The function numeric.sLUP had a bug in it and has been removed. Please use the new numeric.ccsLUP function instead."
+          );
+        };
+
+        numeric.sdotMM = function dotMM(A, B) {
+          var p = A.length,
+            q = B.length,
+            BT = numeric.stranspose(B),
+            r = BT.length,
+            Ai,
+            BTk;
+          var i, j, k, accum;
+          var ret = Array(p),
+            reti;
+          for (i = p - 1; i >= 0; i--) {
+            reti = [];
+            Ai = A[i];
+            for (k = r - 1; k >= 0; k--) {
+              accum = 0;
+              BTk = BT[k];
+              for (j in Ai) {
+                if (!Ai.hasOwnProperty(j)) continue;
+                if (j in BTk) {
+                  accum += Ai[j] * BTk[j];
+                }
+              }
+              if (accum) reti[k] = accum;
+            }
+            ret[i] = reti;
+          }
+          return ret;
+        };
+
+        numeric.sdotMV = function dotMV(A, x) {
+          var p = A.length,
+            Ai,
+            i,
+            j;
+          var ret = Array(p),
+            accum;
+          for (i = p - 1; i >= 0; i--) {
+            Ai = A[i];
+            accum = 0;
+            for (j in Ai) {
+              if (!Ai.hasOwnProperty(j)) continue;
+              if (x[j]) accum += Ai[j] * x[j];
+            }
+            if (accum) ret[i] = accum;
+          }
+          return ret;
+        };
+
+        numeric.sdotVM = function dotMV(x, A) {
+          var i, j, Ai, alpha;
+          var ret = [],
+            accum;
+          for (i in x) {
+            if (!x.hasOwnProperty(i)) continue;
+            Ai = A[i];
+            alpha = x[i];
+            for (j in Ai) {
+              if (!Ai.hasOwnProperty(j)) continue;
+              if (!ret[j]) {
+                ret[j] = 0;
+              }
+              ret[j] += alpha * Ai[j];
+            }
+          }
+          return ret;
+        };
+
+        numeric.sdotVV = function dotVV(x, y) {
+          var i,
+            ret = 0;
+          for (i in x) {
+            if (x[i] && y[i]) ret += x[i] * y[i];
+          }
+          return ret;
+        };
+
+        numeric.sdot = function dot(A, B) {
+          var m = numeric.sdim(A).length,
+            n = numeric.sdim(B).length;
+          var k = m * 1000 + n;
+          switch (k) {
+            case 0:
+              return A * B;
+            case 1001:
+              return numeric.sdotVV(A, B);
+            case 2001:
+              return numeric.sdotMV(A, B);
+            case 1002:
+              return numeric.sdotVM(A, B);
+            case 2002:
+              return numeric.sdotMM(A, B);
+            default:
+              throw new Error(
+                "numeric.sdot not implemented for tensors of order " + m + " and " + n
+              );
+          }
+        };
+
+        numeric.sscatter = function scatter(V) {
+          var n = V[0].length,
+            Vij,
+            i,
+            j,
+            m = V.length,
+            A = [],
+            Aj;
+          for (i = n - 1; i >= 0; --i) {
+            if (!V[m - 1][i]) continue;
+            Aj = A;
+            for (j = 0; j < m - 2; j++) {
+              Vij = V[j][i];
+              if (!Aj[Vij]) Aj[Vij] = [];
+              Aj = Aj[Vij];
+            }
+            Aj[V[j][i]] = V[j + 1][i];
+          }
+          return A;
+        };
+
+        numeric.sgather = function gather(A, ret, k) {
+          if (typeof ret === "undefined") ret = [];
+          if (typeof k === "undefined") k = [];
+          var n, i, Ai;
+          n = k.length;
+          for (i in A) {
+            if (A.hasOwnProperty(i)) {
+              k[n] = parseInt(i);
+              Ai = A[i];
+              if (typeof Ai === "number") {
+                if (Ai) {
+                  if (ret.length === 0) {
+                    for (i = n + 1; i >= 0; --i) ret[i] = [];
+                  }
+                  for (i = n; i >= 0; --i) ret[i].push(k[i]);
+                  ret[n + 1].push(Ai);
+                }
+              } else gather(Ai, ret, k);
+            }
+          }
+          if (k.length > n) k.pop();
+          return ret;
+        };
+
+        // 6. Coordinate matrices
+        numeric.cLU = function LU(A) {
+          var I = A[0],
+            J = A[1],
+            V = A[2];
+          var p = I.length,
+            m = 0,
+            i,
+            j,
+            k,
+            a,
+            b,
+            c;
+          for (i = 0; i < p; i++) if (I[i] > m) m = I[i];
+          m++;
+          var L = Array(m),
+            U = Array(m),
+            left = numeric.rep([m], Infinity),
+            right = numeric.rep([m], -Infinity);
+          var Ui, Uj, alpha;
+          for (k = 0; k < p; k++) {
+            i = I[k];
+            j = J[k];
+            if (j < left[i]) left[i] = j;
+            if (j > right[i]) right[i] = j;
+          }
+          for (i = 0; i < m - 1; i++) {
+            if (right[i] > right[i + 1]) right[i + 1] = right[i];
+          }
+          for (i = m - 1; i >= 1; i--) {
+            if (left[i] < left[i - 1]) left[i - 1] = left[i];
+          }
+          var countL = 0,
+            countU = 0;
+          for (i = 0; i < m; i++) {
+            U[i] = numeric.rep([right[i] - left[i] + 1], 0);
+            L[i] = numeric.rep([i - left[i]], 0);
+            countL += i - left[i] + 1;
+            countU += right[i] - i + 1;
+          }
+          for (k = 0; k < p; k++) {
+            i = I[k];
+            U[i][J[k] - left[i]] = V[k];
+          }
+          for (i = 0; i < m - 1; i++) {
+            a = i - left[i];
+            Ui = U[i];
+            for (j = i + 1; left[j] <= i && j < m; j++) {
+              b = i - left[j];
+              c = right[i] - i;
+              Uj = U[j];
+              alpha = Uj[b] / Ui[a];
+              if (alpha) {
+                for (k = 1; k <= c; k++) {
+                  Uj[k + b] -= alpha * Ui[k + a];
+                }
+                L[j][i - left[j]] = alpha;
+              }
+            }
+          }
+          var Ui = [],
+            Uj = [],
+            Uv = [],
+            Li = [],
+            Lj = [],
+            Lv = [];
+          var p, q, foo;
+          p = 0;
+          q = 0;
+          for (i = 0; i < m; i++) {
+            a = left[i];
+            b = right[i];
+            foo = U[i];
+            for (j = i; j <= b; j++) {
+              if (foo[j - a]) {
+                Ui[p] = i;
+                Uj[p] = j;
+                Uv[p] = foo[j - a];
+                p++;
+              }
+            }
+            foo = L[i];
+            for (j = a; j < i; j++) {
+              if (foo[j - a]) {
+                Li[q] = i;
+                Lj[q] = j;
+                Lv[q] = foo[j - a];
+                q++;
+              }
+            }
+            Li[q] = i;
+            Lj[q] = i;
+            Lv[q] = 1;
+            q++;
+          }
+          return { U: [Ui, Uj, Uv], L: [Li, Lj, Lv] };
+        };
+
+        numeric.cLUsolve = function LUsolve(lu, b) {
+          var L = lu.L,
+            U = lu.U,
+            ret = numeric.clone(b);
+          var Li = L[0],
+            Lj = L[1],
+            Lv = L[2];
+          var Ui = U[0],
+            Uj = U[1],
+            Uv = U[2];
+          var p = Ui.length,
+            q = Li.length;
+          var m = ret.length,
+            i,
+            j,
+            k;
+          k = 0;
+          for (i = 0; i < m; i++) {
+            while (Lj[k] < i) {
+              ret[i] -= Lv[k] * ret[Lj[k]];
+              k++;
+            }
+            k++;
+          }
+          k = p - 1;
+          for (i = m - 1; i >= 0; i--) {
+            while (Uj[k] > i) {
+              ret[i] -= Uv[k] * ret[Uj[k]];
+              k--;
+            }
+            ret[i] /= Uv[k];
+            k--;
+          }
+          return ret;
+        };
+
+        numeric.cgrid = function grid(n, shape) {
+          if (typeof n === "number") n = [n, n];
+          var ret = numeric.rep(n, -1);
+          var i, j, count;
+          if (typeof shape !== "function") {
+            switch (shape) {
+              case "L":
+                shape = function (i, j) {
+                  return i >= n[0] / 2 || j < n[1] / 2;
+                };
+                break;
+              default:
+                shape = function (i, j) {
+                  return true;
+                };
+                break;
+            }
+          }
+          count = 0;
+          for (i = 1; i < n[0] - 1; i++)
+            for (j = 1; j < n[1] - 1; j++)
+              if (shape(i, j)) {
+                ret[i][j] = count;
+                count++;
+              }
+          return ret;
+        };
+
+        numeric.cdelsq = function delsq(g) {
+          var dir = [
+            [-1, 0],
+            [0, -1],
+            [0, 1],
+            [1, 0],
+          ];
+          var s = numeric.dim(g),
+            m = s[0],
+            n = s[1],
+            i,
+            j,
+            k,
+            p,
+            q;
+          var Li = [],
+            Lj = [],
+            Lv = [];
+          for (i = 1; i < m - 1; i++)
+            for (j = 1; j < n - 1; j++) {
+              if (g[i][j] < 0) continue;
+              for (k = 0; k < 4; k++) {
+                p = i + dir[k][0];
+                q = j + dir[k][1];
+                if (g[p][q] < 0) continue;
+                Li.push(g[i][j]);
+                Lj.push(g[p][q]);
+                Lv.push(-1);
+              }
+              Li.push(g[i][j]);
+              Lj.push(g[i][j]);
+              Lv.push(4);
+            }
+          return [Li, Lj, Lv];
+        };
+
+        numeric.cdotMV = function dotMV(A, x) {
+          var ret,
+            Ai = A[0],
+            Aj = A[1],
+            Av = A[2],
+            k,
+            p = Ai.length,
+            N;
+          N = 0;
+          for (k = 0; k < p; k++) {
+            if (Ai[k] > N) N = Ai[k];
+          }
+          N++;
+          ret = numeric.rep([N], 0);
+          for (k = 0; k < p; k++) {
+            ret[Ai[k]] += Av[k] * x[Aj[k]];
+          }
+          return ret;
+        };
+
+        // 7. Splines
+
+        numeric.Spline = function Spline(x, yl, yr, kl, kr) {
+          this.x = x;
+          this.yl = yl;
+          this.yr = yr;
+          this.kl = kl;
+          this.kr = kr;
+        };
+        numeric.Spline.prototype._at = function _at(x1, p) {
+          var x = this.x;
+          var yl = this.yl;
+          var yr = this.yr;
+          var kl = this.kl;
+          var kr = this.kr;
+          var x1, a, b, t;
+          var add = numeric.add,
+            sub = numeric.sub,
+            mul = numeric.mul;
+          a = sub(mul(kl[p], x[p + 1] - x[p]), sub(yr[p + 1], yl[p]));
+          b = add(mul(kr[p + 1], x[p] - x[p + 1]), sub(yr[p + 1], yl[p]));
+          t = (x1 - x[p]) / (x[p + 1] - x[p]);
+          var s = t * (1 - t);
+          return add(
+            add(add(mul(1 - t, yl[p]), mul(t, yr[p + 1])), mul(a, s * (1 - t))),
+            mul(b, s * t)
+          );
+        };
+        numeric.Spline.prototype.at = function at(x0) {
+          if (typeof x0 === "number") {
+            var x = this.x;
+            var n = x.length;
+            var p,
+              q,
+              mid,
+              floor = Math.floor,
+              a,
+              b,
+              t;
+            p = 0;
+            q = n - 1;
+            while (q - p > 1) {
+              mid = floor((p + q) / 2);
+              if (x[mid] <= x0) p = mid;
+              else q = mid;
+            }
+            return this._at(x0, p);
+          }
+          var n = x0.length,
+            i,
+            ret = Array(n);
+          for (i = n - 1; i !== -1; --i) ret[i] = this.at(x0[i]);
+          return ret;
+        };
+        numeric.Spline.prototype.diff = function diff() {
+          var x = this.x;
+          var yl = this.yl;
+          var yr = this.yr;
+          var kl = this.kl;
+          var kr = this.kr;
+          var n = yl.length;
+          var i, dx, dy;
+          var zl = kl,
+            zr = kr,
+            pl = Array(n),
+            pr = Array(n);
+          var add = numeric.add,
+            mul = numeric.mul,
+            div = numeric.div,
+            sub = numeric.sub;
+          for (i = n - 1; i !== -1; --i) {
+            dx = x[i + 1] - x[i];
+            dy = sub(yr[i + 1], yl[i]);
+            pl[i] = div(add(mul(dy, 6), mul(kl[i], -4 * dx), mul(kr[i + 1], -2 * dx)), dx * dx);
+            pr[i + 1] = div(add(mul(dy, -6), mul(kl[i], 2 * dx), mul(kr[i + 1], 4 * dx)), dx * dx);
+          }
+          return new numeric.Spline(x, zl, zr, pl, pr);
+        };
+        numeric.Spline.prototype.roots = function roots() {
+          function sqr(x) {
+            return x * x;
+          }
+          function heval(y0, y1, k0, k1, x) {
+            var A = k0 * 2 - (y1 - y0);
+            var B = -k1 * 2 + (y1 - y0);
+            var t = (x + 1) * 0.5;
+            var s = t * (1 - t);
+            return (1 - t) * y0 + t * y1 + A * s * (1 - t) + B * s * t;
+          }
+          var ret = [];
+          var x = this.x,
+            yl = this.yl,
+            yr = this.yr,
+            kl = this.kl,
+            kr = this.kr;
+          if (typeof yl[0] === "number") {
+            yl = [yl];
+            yr = [yr];
+            kl = [kl];
+            kr = [kr];
+          }
+          var m = yl.length,
+            n = x.length - 1,
+            i,
+            j,
+            k,
+            y,
+            s,
+            t;
+          var ai,
+            bi,
+            ci,
+            di,
+            ret = Array(m),
+            ri,
+            k0,
+            k1,
+            y0,
+            y1,
+            A,
+            B,
+            D,
+            dx,
+            cx,
+            stops,
+            z0,
+            z1,
+            zm,
+            t0,
+            t1,
+            tm;
+          var sqrt = Math.sqrt;
+          for (i = 0; i !== m; ++i) {
+            ai = yl[i];
+            bi = yr[i];
+            ci = kl[i];
+            di = kr[i];
+            ri = [];
+            for (j = 0; j !== n; j++) {
+              if (j > 0 && bi[j] * ai[j] < 0) ri.push(x[j]);
+              dx = x[j + 1] - x[j];
+              cx = x[j];
+              y0 = ai[j];
+              y1 = bi[j + 1];
+              k0 = ci[j] / dx;
+              k1 = di[j + 1] / dx;
+              D = sqr(k0 - k1 + 3 * (y0 - y1)) + 12 * k1 * y0;
+              A = k1 + 3 * y0 + 2 * k0 - 3 * y1;
+              B = 3 * (k1 + k0 + 2 * (y0 - y1));
+              if (D <= 0) {
+                z0 = A / B;
+                if (z0 > x[j] && z0 < x[j + 1]) stops = [x[j], z0, x[j + 1]];
+                else stops = [x[j], x[j + 1]];
+              } else {
+                z0 = (A - sqrt(D)) / B;
+                z1 = (A + sqrt(D)) / B;
+                stops = [x[j]];
+                if (z0 > x[j] && z0 < x[j + 1]) stops.push(z0);
+                if (z1 > x[j] && z1 < x[j + 1]) stops.push(z1);
+                stops.push(x[j + 1]);
+              }
+              t0 = stops[0];
+              z0 = this._at(t0, j);
+              for (k = 0; k < stops.length - 1; k++) {
+                t1 = stops[k + 1];
+                z1 = this._at(t1, j);
+                if (z0 === 0) {
+                  ri.push(t0);
+                  t0 = t1;
+                  z0 = z1;
+                  continue;
+                }
+                if (z1 === 0 || z0 * z1 > 0) {
+                  t0 = t1;
+                  z0 = z1;
+                  continue;
+                }
+                var side = 0;
+                while (1) {
+                  tm = (z0 * t1 - z1 * t0) / (z0 - z1);
+                  if (tm <= t0 || tm >= t1) {
+                    break;
+                  }
+                  zm = this._at(tm, j);
+                  if (zm * z1 > 0) {
+                    t1 = tm;
+                    z1 = zm;
+                    if (side === -1) z0 *= 0.5;
+                    side = -1;
+                  } else if (zm * z0 > 0) {
+                    t0 = tm;
+                    z0 = zm;
+                    if (side === 1) z1 *= 0.5;
+                    side = 1;
+                  } else break;
+                }
+                ri.push(tm);
+                t0 = stops[k + 1];
+                z0 = this._at(t0, j);
+              }
+              if (z1 === 0) ri.push(t1);
+            }
+            ret[i] = ri;
+          }
+          if (typeof this.yl[0] === "number") return ret[0];
+          return ret;
+        };
+        numeric.spline = function spline(x, y, k1, kn) {
+          var n = x.length,
+            b = [],
+            dx = [],
+            dy = [];
+          var i;
+          var sub = numeric.sub,
+            mul = numeric.mul,
+            add = numeric.add;
+          for (i = n - 2; i >= 0; i--) {
+            dx[i] = x[i + 1] - x[i];
+            dy[i] = sub(y[i + 1], y[i]);
+          }
+          if (typeof k1 === "string" || typeof kn === "string") {
+            k1 = kn = "periodic";
+          }
+          // Build sparse tridiagonal system
+          var T = [[], [], []];
+          switch (typeof k1) {
+            case "undefined":
+              b[0] = mul(3 / (dx[0] * dx[0]), dy[0]);
+              T[0].push(0, 0);
+              T[1].push(0, 1);
+              T[2].push(2 / dx[0], 1 / dx[0]);
+              break;
+            case "string":
+              b[0] = add(
+                mul(3 / (dx[n - 2] * dx[n - 2]), dy[n - 2]),
+                mul(3 / (dx[0] * dx[0]), dy[0])
+              );
+              T[0].push(0, 0, 0);
+              T[1].push(n - 2, 0, 1);
+              T[2].push(1 / dx[n - 2], 2 / dx[n - 2] + 2 / dx[0], 1 / dx[0]);
+              break;
+            default:
+              b[0] = k1;
+              T[0].push(0);
+              T[1].push(0);
+              T[2].push(1);
+              break;
+          }
+          for (i = 1; i < n - 1; i++) {
+            b[i] = add(
+              mul(3 / (dx[i - 1] * dx[i - 1]), dy[i - 1]),
+              mul(3 / (dx[i] * dx[i]), dy[i])
+            );
+            T[0].push(i, i, i);
+            T[1].push(i - 1, i, i + 1);
+            T[2].push(1 / dx[i - 1], 2 / dx[i - 1] + 2 / dx[i], 1 / dx[i]);
+          }
+          switch (typeof kn) {
+            case "undefined":
+              b[n - 1] = mul(3 / (dx[n - 2] * dx[n - 2]), dy[n - 2]);
+              T[0].push(n - 1, n - 1);
+              T[1].push(n - 2, n - 1);
+              T[2].push(1 / dx[n - 2], 2 / dx[n - 2]);
+              break;
+            case "string":
+              T[1][T[1].length - 1] = 0;
+              break;
+            default:
+              b[n - 1] = kn;
+              T[0].push(n - 1);
+              T[1].push(n - 1);
+              T[2].push(1);
+              break;
+          }
+          if (typeof b[0] !== "number") b = numeric.transpose(b);
+          else b = [b];
+          var k = Array(b.length);
+          if (typeof k1 === "string") {
+            for (i = k.length - 1; i !== -1; --i) {
+              k[i] = numeric.ccsLUPSolve(numeric.ccsLUP(numeric.ccsScatter(T)), b[i]);
+              k[i][n - 1] = k[i][0];
+            }
+          } else {
+            for (i = k.length - 1; i !== -1; --i) {
+              k[i] = numeric.cLUsolve(numeric.cLU(T), b[i]);
+            }
+          }
+          if (typeof y[0] === "number") k = k[0];
+          else k = numeric.transpose(k);
+          return new numeric.Spline(x, y, y, k, k);
+        };
+
+        // 8. FFT
+        numeric.fftpow2 = function fftpow2(x, y) {
+          var n = x.length;
+          if (n === 1) return;
+          var cos = Math.cos,
+            sin = Math.sin,
+            i,
+            j;
+          var xe = Array(n / 2),
+            ye = Array(n / 2),
+            xo = Array(n / 2),
+            yo = Array(n / 2);
+          j = n / 2;
+          for (i = n - 1; i !== -1; --i) {
+            --j;
+            xo[j] = x[i];
+            yo[j] = y[i];
+            --i;
+            xe[j] = x[i];
+            ye[j] = y[i];
+          }
+          fftpow2(xe, ye);
+          fftpow2(xo, yo);
+          j = n / 2;
+          var t,
+            k = -6.2831853071795864769252867665590057683943387987502116419 / n,
+            ci,
+            si;
+          for (i = n - 1; i !== -1; --i) {
+            --j;
+            if (j === -1) j = n / 2 - 1;
+            t = k * i;
+            ci = cos(t);
+            si = sin(t);
+            x[i] = xe[j] + ci * xo[j] - si * yo[j];
+            y[i] = ye[j] + ci * yo[j] + si * xo[j];
+          }
+        };
+        numeric._ifftpow2 = function _ifftpow2(x, y) {
+          var n = x.length;
+          if (n === 1) return;
+          var cos = Math.cos,
+            sin = Math.sin,
+            i,
+            j;
+          var xe = Array(n / 2),
+            ye = Array(n / 2),
+            xo = Array(n / 2),
+            yo = Array(n / 2);
+          j = n / 2;
+          for (i = n - 1; i !== -1; --i) {
+            --j;
+            xo[j] = x[i];
+            yo[j] = y[i];
+            --i;
+            xe[j] = x[i];
+            ye[j] = y[i];
+          }
+          _ifftpow2(xe, ye);
+          _ifftpow2(xo, yo);
+          j = n / 2;
+          var t,
+            k = 6.2831853071795864769252867665590057683943387987502116419 / n,
+            ci,
+            si;
+          for (i = n - 1; i !== -1; --i) {
+            --j;
+            if (j === -1) j = n / 2 - 1;
+            t = k * i;
+            ci = cos(t);
+            si = sin(t);
+            x[i] = xe[j] + ci * xo[j] - si * yo[j];
+            y[i] = ye[j] + ci * yo[j] + si * xo[j];
+          }
+        };
+        numeric.ifftpow2 = function ifftpow2(x, y) {
+          numeric._ifftpow2(x, y);
+          numeric.diveq(x, x.length);
+          numeric.diveq(y, y.length);
+        };
+        numeric.convpow2 = function convpow2(ax, ay, bx, by) {
+          numeric.fftpow2(ax, ay);
+          numeric.fftpow2(bx, by);
+          var i,
+            n = ax.length,
+            axi,
+            bxi,
+            ayi,
+            byi;
+          for (i = n - 1; i !== -1; --i) {
+            axi = ax[i];
+            ayi = ay[i];
+            bxi = bx[i];
+            byi = by[i];
+            ax[i] = axi * bxi - ayi * byi;
+            ay[i] = axi * byi + ayi * bxi;
+          }
+          numeric.ifftpow2(ax, ay);
+        };
+        numeric.T.prototype.fft = function fft() {
+          var x = this.x,
+            y = this.y;
+          var n = x.length,
+            log = Math.log,
+            log2 = log(2),
+            p = Math.ceil(log(2 * n - 1) / log2),
+            m = Math.pow(2, p);
+          var cx = numeric.rep([m], 0),
+            cy = numeric.rep([m], 0),
+            cos = Math.cos,
+            sin = Math.sin;
+          var k,
+            c = -3.14159265358979323846264338327950288419716939937510582 / n,
+            t;
+          var a = numeric.rep([m], 0),
+            b = numeric.rep([m], 0),
+            nhalf = Math.floor(n / 2);
+          for (k = 0; k < n; k++) a[k] = x[k];
+          if (typeof y !== "undefined") for (k = 0; k < n; k++) b[k] = y[k];
+          cx[0] = 1;
+          for (k = 1; k <= m / 2; k++) {
+            t = c * k * k;
+            cx[k] = cos(t);
+            cy[k] = sin(t);
+            cx[m - k] = cos(t);
+            cy[m - k] = sin(t);
+          }
+          var X = new numeric.T(a, b),
+            Y = new numeric.T(cx, cy);
+          X = X.mul(Y);
+          numeric.convpow2(X.x, X.y, numeric.clone(Y.x), numeric.neg(Y.y));
+          X = X.mul(Y);
+          X.x.length = n;
+          X.y.length = n;
+          return X;
+        };
+        numeric.T.prototype.ifft = function ifft() {
+          var x = this.x,
+            y = this.y;
+          var n = x.length,
+            log = Math.log,
+            log2 = log(2),
+            p = Math.ceil(log(2 * n - 1) / log2),
+            m = Math.pow(2, p);
+          var cx = numeric.rep([m], 0),
+            cy = numeric.rep([m], 0),
+            cos = Math.cos,
+            sin = Math.sin;
+          var k,
+            c = 3.14159265358979323846264338327950288419716939937510582 / n,
+            t;
+          var a = numeric.rep([m], 0),
+            b = numeric.rep([m], 0),
+            nhalf = Math.floor(n / 2);
+          for (k = 0; k < n; k++) a[k] = x[k];
+          if (typeof y !== "undefined") for (k = 0; k < n; k++) b[k] = y[k];
+          cx[0] = 1;
+          for (k = 1; k <= m / 2; k++) {
+            t = c * k * k;
+            cx[k] = cos(t);
+            cy[k] = sin(t);
+            cx[m - k] = cos(t);
+            cy[m - k] = sin(t);
+          }
+          var X = new numeric.T(a, b),
+            Y = new numeric.T(cx, cy);
+          X = X.mul(Y);
+          numeric.convpow2(X.x, X.y, numeric.clone(Y.x), numeric.neg(Y.y));
+          X = X.mul(Y);
+          X.x.length = n;
+          X.y.length = n;
+          return X.div(n);
+        };
+
+        //9. Unconstrained optimization
+        numeric.gradient = function gradient(f, x) {
+          var n = x.length;
+          var f0 = f(x);
+          if (isNaN(f0)) throw new Error("gradient: f(x) is a NaN!");
+          var max = Math.max;
+          var i,
+            x0 = numeric.clone(x),
+            f1,
+            f2,
+            J = Array(n);
+          var div = numeric.div,
+            sub = numeric.sub,
+            errest,
+            roundoff,
+            max = Math.max,
+            eps = 1e-3,
+            abs = Math.abs,
+            min = Math.min;
+          var t0,
+            t1,
+            t2,
+            it = 0,
+            d1,
+            d2,
+            N;
+          for (i = 0; i < n; i++) {
+            var h = max(1e-6 * f0, 1e-8);
+            while (1) {
+              ++it;
+              if (it > 20) {
+                throw new Error("Numerical gradient fails");
+              }
+              x0[i] = x[i] + h;
+              f1 = f(x0);
+              x0[i] = x[i] - h;
+              f2 = f(x0);
+              x0[i] = x[i];
+              if (isNaN(f1) || isNaN(f2)) {
+                h /= 16;
+                continue;
+              }
+              J[i] = (f1 - f2) / (2 * h);
+              t0 = x[i] - h;
+              t1 = x[i];
+              t2 = x[i] + h;
+              d1 = (f1 - f0) / h;
+              d2 = (f0 - f2) / h;
+              N = max(abs(J[i]), abs(f0), abs(f1), abs(f2), abs(t0), abs(t1), abs(t2), 1e-8);
+              errest = min(max(abs(d1 - J[i]), abs(d2 - J[i]), abs(d1 - d2)) / N, h / N);
+              if (errest > eps) {
+                h /= 16;
+              } else break;
+            }
+          }
+          return J;
+        };
+
+        numeric.uncmin = function uncmin(f, x0, tol, gradient, maxit, callback, options) {
+          var grad = numeric.gradient;
+          if (typeof options === "undefined") {
+            options = {};
+          }
+          if (typeof tol === "undefined") {
+            tol = 1e-8;
+          }
+          if (typeof gradient === "undefined") {
+            gradient = function (x) {
+              return grad(f, x);
+            };
+          }
+          if (typeof maxit === "undefined") maxit = 1000;
+          x0 = numeric.clone(x0);
+          var n = x0.length;
+          var f0 = f(x0),
+            f1,
+            df0;
+          if (isNaN(f0)) throw new Error("uncmin: f(x0) is a NaN!");
+          var max = Math.max,
+            norm2 = numeric.norm2;
+          tol = max(tol, numeric.epsilon);
+          var step,
+            g0,
+            g1,
+            H1 = options.Hinv || numeric.identity(n);
+          var dot = numeric.dot,
+            inv = numeric.inv,
+            sub = numeric.sub,
+            add = numeric.add,
+            ten = numeric.tensor,
+            div = numeric.div,
+            mul = numeric.mul;
+          var all = numeric.all,
+            isfinite = numeric.isFinite,
+            neg = numeric.neg;
+          var it = 0,
+            i,
+            s,
+            x1,
+            y,
+            Hy,
+            Hs,
+            ys,
+            i0,
+            t,
+            nstep,
+            t1,
+            t2;
+          var msg = "";
+          g0 = gradient(x0);
+          while (it < maxit) {
+            if (typeof callback === "function") {
+              if (callback(it, x0, f0, g0, H1)) {
+                msg = "Callback returned true";
+                break;
+              }
+            }
+            if (!all(isfinite(g0))) {
+              msg = "Gradient has Infinity or NaN";
+              break;
+            }
+            step = neg(dot(H1, g0));
+            if (!all(isfinite(step))) {
+              msg = "Search direction has Infinity or NaN";
+              break;
+            }
+            nstep = norm2(step);
+            if (nstep < tol) {
+              msg = "Newton step smaller than tol";
+              break;
+            }
+            t = 1;
+            df0 = dot(g0, step);
+            // line search
+            x1 = x0;
+            while (it < maxit) {
+              if (t * nstep < tol) {
+                break;
+              }
+              s = mul(step, t);
+              x1 = add(x0, s);
+              f1 = f(x1);
+              if (f1 - f0 >= 0.1 * t * df0 || isNaN(f1)) {
+                t *= 0.5;
+                ++it;
+                continue;
+              }
+              break;
+            }
+            if (t * nstep < tol) {
+              msg = "Line search step size smaller than tol";
+              break;
+            }
+            if (it === maxit) {
+              msg = "maxit reached during line search";
+              break;
+            }
+            g1 = gradient(x1);
+            y = sub(g1, g0);
+            ys = dot(y, s);
+            Hy = dot(H1, y);
+            H1 = sub(
+              add(H1, mul((ys + dot(y, Hy)) / (ys * ys), ten(s, s))),
+              div(add(ten(Hy, s), ten(s, Hy)), ys)
+            );
+            x0 = x1;
+            f0 = f1;
+            g0 = g1;
+            ++it;
+          }
+          return {
+            solution: x0,
+            f: f0,
+            gradient: g0,
+            invHessian: H1,
+            iterations: it,
+            message: msg,
+          };
+        };
+
+        // 10. Ode solver (Dormand-Prince)
+        numeric.Dopri = function Dopri(x, y, f, ymid, iterations, msg, events) {
+          this.x = x;
+          this.y = y;
+          this.f = f;
+          this.ymid = ymid;
+          this.iterations = iterations;
+          this.events = events;
+          this.message = msg;
+        };
+        numeric.Dopri.prototype._at = function _at(xi, j) {
+          function sqr(x) {
+            return x * x;
+          }
+          var sol = this;
+          var xs = sol.x;
+          var ys = sol.y;
+          var k1 = sol.f;
+          var ymid = sol.ymid;
+          var n = xs.length;
+          var x0, x1, xh, y0, y1, yh, xi;
+          var floor = Math.floor,
+            h;
+          var c = 0.5;
+          var add = numeric.add,
+            mul = numeric.mul,
+            sub = numeric.sub,
+            p,
+            q,
+            w;
+          x0 = xs[j];
+          x1 = xs[j + 1];
+          y0 = ys[j];
+          y1 = ys[j + 1];
+          h = x1 - x0;
+          xh = x0 + c * h;
+          yh = ymid[j];
+          p = sub(k1[j], mul(y0, 1 / (x0 - xh) + 2 / (x0 - x1)));
+          q = sub(k1[j + 1], mul(y1, 1 / (x1 - xh) + 2 / (x1 - x0)));
+          w = [
+            (sqr(xi - x1) * (xi - xh)) / sqr(x0 - x1) / (x0 - xh),
+            (sqr(xi - x0) * sqr(xi - x1)) / sqr(x0 - xh) / sqr(x1 - xh),
+            (sqr(xi - x0) * (xi - xh)) / sqr(x1 - x0) / (x1 - xh),
+            ((xi - x0) * sqr(xi - x1) * (xi - xh)) / sqr(x0 - x1) / (x0 - xh),
+            ((xi - x1) * sqr(xi - x0) * (xi - xh)) / sqr(x0 - x1) / (x1 - xh),
+          ];
+          return add(
+            add(add(add(mul(y0, w[0]), mul(yh, w[1])), mul(y1, w[2])), mul(p, w[3])),
+            mul(q, w[4])
+          );
+        };
+        numeric.Dopri.prototype.at = function at(x) {
+          var i,
+            j,
+            k,
+            floor = Math.floor;
+          if (typeof x !== "number") {
+            var n = x.length,
+              ret = Array(n);
+            for (i = n - 1; i !== -1; --i) {
+              ret[i] = this.at(x[i]);
+            }
+            return ret;
+          }
+          var x0 = this.x;
+          i = 0;
+          j = x0.length - 1;
+          while (j - i > 1) {
+            k = floor(0.5 * (i + j));
+            if (x0[k] <= x) i = k;
+            else j = k;
+          }
+          return this._at(x, i);
+        };
+
+        numeric.dopri = function dopri(x0, x1, y0, f, tol, maxit, event) {
+          if (typeof tol === "undefined") {
+            tol = 1e-6;
+          }
+          if (typeof maxit === "undefined") {
+            maxit = 1000;
+          }
+          var xs = [x0],
+            ys = [y0],
+            k1 = [f(x0, y0)],
+            k2,
+            k3,
+            k4,
+            k5,
+            k6,
+            k7,
+            ymid = [];
+          var A2 = 1 / 5;
+          var A3 = [3 / 40, 9 / 40];
+          var A4 = [44 / 45, -56 / 15, 32 / 9];
+          var A5 = [19372 / 6561, -25360 / 2187, 64448 / 6561, -212 / 729];
+          var A6 = [9017 / 3168, -355 / 33, 46732 / 5247, 49 / 176, -5103 / 18656];
+          var b = [35 / 384, 0, 500 / 1113, 125 / 192, -2187 / 6784, 11 / 84];
+          var bm = [
+            (0.5 * 6025192743) / 30085553152,
+            0,
+            (0.5 * 51252292925) / 65400821598,
+            (0.5 * -2691868925) / 45128329728,
+            (0.5 * 187940372067) / 1594534317056,
+            (0.5 * -1776094331) / 19743644256,
+            (0.5 * 11237099) / 235043384,
+          ];
+          var c = [1 / 5, 3 / 10, 4 / 5, 8 / 9, 1, 1];
+          var e = [-71 / 57600, 0, 71 / 16695, -71 / 1920, 17253 / 339200, -22 / 525, 1 / 40];
+          var i = 0,
+            er,
+            j;
+          var h = (x1 - x0) / 10;
+          var it = 0;
+          var add = numeric.add,
+            mul = numeric.mul,
+            y1,
+            erinf;
+          var max = Math.max,
+            min = Math.min,
+            abs = Math.abs,
+            norminf = numeric.norminf,
+            pow = Math.pow;
+          var any = numeric.any,
+            lt = numeric.lt,
+            and = numeric.and,
+            sub = numeric.sub;
+          var e0, e1, ev;
+          var ret = new numeric.Dopri(xs, ys, k1, ymid, -1, "");
+          if (typeof event === "function") e0 = event(x0, y0);
+          while (x0 < x1 && it < maxit) {
+            ++it;
+            if (x0 + h > x1) h = x1 - x0;
+            k2 = f(x0 + c[0] * h, add(y0, mul(A2 * h, k1[i])));
+            k3 = f(x0 + c[1] * h, add(add(y0, mul(A3[0] * h, k1[i])), mul(A3[1] * h, k2)));
+            k4 = f(
+              x0 + c[2] * h,
+              add(add(add(y0, mul(A4[0] * h, k1[i])), mul(A4[1] * h, k2)), mul(A4[2] * h, k3))
+            );
+            k5 = f(
+              x0 + c[3] * h,
+              add(
+                add(add(add(y0, mul(A5[0] * h, k1[i])), mul(A5[1] * h, k2)), mul(A5[2] * h, k3)),
+                mul(A5[3] * h, k4)
+              )
+            );
+            k6 = f(
+              x0 + c[4] * h,
+              add(
+                add(
+                  add(add(add(y0, mul(A6[0] * h, k1[i])), mul(A6[1] * h, k2)), mul(A6[2] * h, k3)),
+                  mul(A6[3] * h, k4)
+                ),
+                mul(A6[4] * h, k5)
+              )
+            );
+            y1 = add(
+              add(
+                add(add(add(y0, mul(k1[i], h * b[0])), mul(k3, h * b[2])), mul(k4, h * b[3])),
+                mul(k5, h * b[4])
+              ),
+              mul(k6, h * b[5])
+            );
+            k7 = f(x0 + h, y1);
+            er = add(
+              add(
+                add(
+                  add(add(mul(k1[i], h * e[0]), mul(k3, h * e[2])), mul(k4, h * e[3])),
+                  mul(k5, h * e[4])
+                ),
+                mul(k6, h * e[5])
+              ),
+              mul(k7, h * e[6])
+            );
+            if (typeof er === "number") erinf = abs(er);
+            else erinf = norminf(er);
+            if (erinf > tol) {
+              // reject
+              h = 0.2 * h * pow(tol / erinf, 0.25);
+              if (x0 + h === x0) {
+                ret.msg = "Step size became too small";
+                break;
+              }
+              continue;
+            }
+            ymid[i] = add(
+              add(
+                add(
+                  add(add(add(y0, mul(k1[i], h * bm[0])), mul(k3, h * bm[2])), mul(k4, h * bm[3])),
+                  mul(k5, h * bm[4])
+                ),
+                mul(k6, h * bm[5])
+              ),
+              mul(k7, h * bm[6])
+            );
+            ++i;
+            xs[i] = x0 + h;
+            ys[i] = y1;
+            k1[i] = k7;
+            if (typeof event === "function") {
+              var yi,
+                xl = x0,
+                xr = x0 + 0.5 * h,
+                xi;
+              e1 = event(xr, ymid[i - 1]);
+              ev = and(lt(e0, 0), lt(0, e1));
+              if (!any(ev)) {
+                xl = xr;
+                xr = x0 + h;
+                e0 = e1;
+                e1 = event(xr, y1);
+                ev = and(lt(e0, 0), lt(0, e1));
+              }
+              if (any(ev)) {
+                var xc, yc, en, ei;
+                var side = 0,
+                  sl = 1.0,
+                  sr = 1.0;
+                while (1) {
+                  if (typeof e0 === "number")
+                    xi = (sr * e1 * xl - sl * e0 * xr) / (sr * e1 - sl * e0);
+                  else {
+                    xi = xr;
+                    for (j = e0.length - 1; j !== -1; --j) {
+                      if (e0[j] < 0 && e1[j] > 0)
+                        xi = min(
+                          xi,
+                          (sr * e1[j] * xl - sl * e0[j] * xr) / (sr * e1[j] - sl * e0[j])
+                        );
+                    }
+                  }
+                  if (xi <= xl || xi >= xr) break;
+                  yi = ret._at(xi, i - 1);
+                  ei = event(xi, yi);
+                  en = and(lt(e0, 0), lt(0, ei));
+                  if (any(en)) {
+                    xr = xi;
+                    e1 = ei;
+                    ev = en;
+                    sr = 1.0;
+                    if (side === -1) sl *= 0.5;
+                    else sl = 1.0;
+                    side = -1;
+                  } else {
+                    xl = xi;
+                    e0 = ei;
+                    sl = 1.0;
+                    if (side === 1) sr *= 0.5;
+                    else sr = 1.0;
+                    side = 1;
+                  }
+                }
+                y1 = ret._at(0.5 * (x0 + xi), i - 1);
+                ret.f[i] = f(xi, yi);
+                ret.x[i] = xi;
+                ret.y[i] = yi;
+                ret.ymid[i - 1] = y1;
+                ret.events = ev;
+                ret.iterations = it;
+                return ret;
+              }
+            }
+            x0 += h;
+            y0 = y1;
+            e0 = e1;
+            h = min(0.8 * h * pow(tol / erinf, 0.25), 4 * h);
+          }
+          ret.iterations = it;
+          return ret;
+        };
+
+        // 11. Ax = b
+        numeric.LU = function (A, fast) {
+          fast = fast || false;
+
+          var abs = Math.abs;
+          var i, j, k, absAjk, Akk, Ak, Pk, Ai;
+          var max;
+          var n = A.length,
+            n1 = n - 1;
+          var P = new Array(n);
+          if (!fast) A = numeric.clone(A);
+
+          for (k = 0; k < n; ++k) {
+            Pk = k;
+            Ak = A[k];
+            max = abs(Ak[k]);
+            for (j = k + 1; j < n; ++j) {
+              absAjk = abs(A[j][k]);
+              if (max < absAjk) {
+                max = absAjk;
+                Pk = j;
+              }
+            }
+            P[k] = Pk;
+
+            if (Pk != k) {
+              A[k] = A[Pk];
+              A[Pk] = Ak;
+              Ak = A[k];
+            }
+
+            Akk = Ak[k];
+
+            for (i = k + 1; i < n; ++i) {
+              A[i][k] /= Akk;
+            }
+
+            for (i = k + 1; i < n; ++i) {
+              Ai = A[i];
+              for (j = k + 1; j < n1; ++j) {
+                Ai[j] -= Ai[k] * Ak[j];
+                ++j;
+                Ai[j] -= Ai[k] * Ak[j];
+              }
+              if (j === n1) Ai[j] -= Ai[k] * Ak[j];
+            }
+          }
+
+          return {
+            LU: A,
+            P: P,
+          };
+        };
+
+        numeric.LUsolve = function LUsolve(LUP, b) {
+          var i, j;
+          var LU = LUP.LU;
+          var n = LU.length;
+          var x = numeric.clone(b);
+          var P = LUP.P;
+          var Pi, LUi, LUii, tmp;
+
+          for (i = n - 1; i !== -1; --i) x[i] = b[i];
+          for (i = 0; i < n; ++i) {
+            Pi = P[i];
+            if (P[i] !== i) {
+              tmp = x[i];
+              x[i] = x[Pi];
+              x[Pi] = tmp;
+            }
+
+            LUi = LU[i];
+            for (j = 0; j < i; ++j) {
+              x[i] -= x[j] * LUi[j];
+            }
+          }
+
+          for (i = n - 1; i >= 0; --i) {
+            LUi = LU[i];
+            for (j = i + 1; j < n; ++j) {
+              x[i] -= x[j] * LUi[j];
+            }
+
+            x[i] /= LUi[i];
+          }
+
+          return x;
+        };
+
+        numeric.solve = function solve(A, b, fast) {
+          return numeric.LUsolve(numeric.LU(A, fast), b);
+        };
+
+        // 12. Linear programming
+        numeric.echelonize = function echelonize(A) {
+          var s = numeric.dim(A),
+            m = s[0],
+            n = s[1];
+          var I = numeric.identity(m);
+          var P = Array(m);
+          var i, j, k, l, Ai, Ii, Z, a;
+          var abs = Math.abs;
+          var diveq = numeric.diveq;
+          A = numeric.clone(A);
+          for (i = 0; i < m; ++i) {
+            k = 0;
+            Ai = A[i];
+            Ii = I[i];
+            for (j = 1; j < n; ++j) if (abs(Ai[k]) < abs(Ai[j])) k = j;
+            P[i] = k;
+            diveq(Ii, Ai[k]);
+            diveq(Ai, Ai[k]);
+            for (j = 0; j < m; ++j)
+              if (j !== i) {
+                Z = A[j];
+                a = Z[k];
+                for (l = n - 1; l !== -1; --l) Z[l] -= Ai[l] * a;
+                Z = I[j];
+                for (l = m - 1; l !== -1; --l) Z[l] -= Ii[l] * a;
+              }
+          }
+          return { I: I, A: A, P: P };
+        };
+
+        numeric.__solveLP = function __solveLP(c, A, b, tol, maxit, x, flag) {
+          var sum = numeric.sum,
+            log = numeric.log,
+            mul = numeric.mul,
+            sub = numeric.sub,
+            dot = numeric.dot,
+            div = numeric.div,
+            add = numeric.add;
+          var m = c.length,
+            n = b.length,
+            y;
+          var unbounded = false,
+            cb,
+            i0 = 0;
+          var alpha = 1.0;
+          var f0,
+            df0,
+            AT = numeric.transpose(A),
+            svd = numeric.svd,
+            transpose = numeric.transpose,
+            leq = numeric.leq,
+            sqrt = Math.sqrt,
+            abs = Math.abs;
+          var muleq = numeric.muleq;
+          var norm = numeric.norminf,
+            any = numeric.any,
+            min = Math.min;
+          var all = numeric.all,
+            gt = numeric.gt;
+          var p = Array(m),
+            A0 = Array(n),
+            e = numeric.rep([n], 1),
+            H;
+          var solve = numeric.solve,
+            z = sub(b, dot(A, x)),
+            count;
+          var dotcc = dot(c, c);
+          var g;
+          for (count = i0; count < maxit; ++count) {
+            var i, j, d;
+            for (i = n - 1; i !== -1; --i) A0[i] = div(A[i], z[i]);
+            var A1 = transpose(A0);
+            for (i = m - 1; i !== -1; --i) p[i] = /*x[i]+*/ sum(A1[i]);
+            alpha = 0.25 * abs(dotcc / dot(c, p));
+            var a1 = 100 * sqrt(dotcc / dot(p, p));
+            if (!isFinite(alpha) || alpha > a1) alpha = a1;
+            g = add(c, mul(alpha, p));
+            H = dot(A1, A0);
+            for (i = m - 1; i !== -1; --i) H[i][i] += 1;
+            d = solve(H, div(g, alpha), true);
+            var t0 = div(z, dot(A, d));
+            var t = 1.0;
+            for (i = n - 1; i !== -1; --i) if (t0[i] < 0) t = min(t, -0.999 * t0[i]);
+            y = sub(x, mul(d, t));
+            z = sub(b, dot(A, y));
+            if (!all(gt(z, 0))) return { solution: x, message: "", iterations: count };
+            x = y;
+            if (alpha < tol) return { solution: y, message: "", iterations: count };
+            if (flag) {
+              var s = dot(c, g),
+                Ag = dot(A, g);
+              unbounded = true;
+              for (i = n - 1; i !== -1; --i)
+                if (s * Ag[i] < 0) {
+                  unbounded = false;
+                  break;
+                }
+            } else {
+              if (x[m - 1] >= 0) unbounded = false;
+              else unbounded = true;
+            }
+            if (unbounded) return { solution: y, message: "Unbounded", iterations: count };
+          }
+          return { solution: x, message: "maximum iteration count exceeded", iterations: count };
+        };
+
+        numeric._solveLP = function _solveLP(c, A, b, tol, maxit) {
+          var m = c.length,
+            n = b.length,
+            y;
+          var sum = numeric.sum,
+            log = numeric.log,
+            mul = numeric.mul,
+            sub = numeric.sub,
+            dot = numeric.dot,
+            div = numeric.div,
+            add = numeric.add;
+          var c0 = numeric.rep([m], 0).concat([1]);
+          var J = numeric.rep([n, 1], -1);
+          var A0 = numeric.blockMatrix([[A, J]]);
+          var b0 = b;
+          var y = numeric.rep([m], 0).concat(Math.max(0, numeric.sup(numeric.neg(b))) + 1);
+          var x0 = numeric.__solveLP(c0, A0, b0, tol, maxit, y, false);
+          var x = numeric.clone(x0.solution);
+          x.length = m;
+          var foo = numeric.inf(sub(b, dot(A, x)));
+          if (foo < 0) {
+            return { solution: NaN, message: "Infeasible", iterations: x0.iterations };
+          }
+          var ret = numeric.__solveLP(c, A, b, tol, maxit - x0.iterations, x, true);
+          ret.iterations += x0.iterations;
+          return ret;
+        };
+
+        numeric.solveLP = function solveLP(c, A, b, Aeq, beq, tol, maxit) {
+          if (typeof maxit === "undefined") maxit = 1000;
+          if (typeof tol === "undefined") tol = numeric.epsilon;
+          if (typeof Aeq === "undefined") return numeric._solveLP(c, A, b, tol, maxit);
+          var m = Aeq.length,
+            n = Aeq[0].length,
+            o = A.length;
+          var B = numeric.echelonize(Aeq);
+          var flags = numeric.rep([n], 0);
+          var P = B.P;
+          var Q = [];
+          var i;
+          for (i = P.length - 1; i !== -1; --i) flags[P[i]] = 1;
+          for (i = n - 1; i !== -1; --i) if (flags[i] === 0) Q.push(i);
+          var g = numeric.getRange;
+          var I = numeric.linspace(0, m - 1),
+            J = numeric.linspace(0, o - 1);
+          var Aeq2 = g(Aeq, I, Q),
+            A1 = g(A, J, P),
+            A2 = g(A, J, Q),
+            dot = numeric.dot,
+            sub = numeric.sub;
+          var A3 = dot(A1, B.I);
+          var A4 = sub(A2, dot(A3, Aeq2)),
+            b4 = sub(b, dot(A3, beq));
+          var c1 = Array(P.length),
+            c2 = Array(Q.length);
+          for (i = P.length - 1; i !== -1; --i) c1[i] = c[P[i]];
+          for (i = Q.length - 1; i !== -1; --i) c2[i] = c[Q[i]];
+          var c4 = sub(c2, dot(c1, dot(B.I, Aeq2)));
+          var S = numeric._solveLP(c4, A4, b4, tol, maxit);
+          var x2 = S.solution;
+          if (x2 !== x2) return S;
+          var x1 = dot(B.I, sub(beq, dot(Aeq2, x2)));
+          var x = Array(c.length);
+          for (i = P.length - 1; i !== -1; --i) x[P[i]] = x1[i];
+          for (i = Q.length - 1; i !== -1; --i) x[Q[i]] = x2[i];
+          return { solution: x, message: S.message, iterations: S.iterations };
+        };
+
+        numeric.MPStoLP = function MPStoLP(MPS) {
+          if (MPS instanceof String) {
+            MPS.split("\n");
+          }
+          var state = 0;
+          var states = ["Initial state", "NAME", "ROWS", "COLUMNS", "RHS", "BOUNDS", "ENDATA"];
+          var n = MPS.length;
+          var i,
+            j,
+            z,
+            N = 0,
+            rows = {},
+            sign = [],
+            rl = 0,
+            vars = {},
+            nv = 0;
+          var name;
+          var c = [],
+            A = [],
+            b = [];
+          function err(e) {
+            throw new Error(
+              "MPStoLP: " +
+                e +
+                "\nLine " +
+                i +
+                ": " +
+                MPS[i] +
+                "\nCurrent state: " +
+                states[state] +
+                "\n"
+            );
+          }
+          for (i = 0; i < n; ++i) {
+            z = MPS[i];
+            var w0 = z.match(/\S*/g);
+            var w = [];
+            for (j = 0; j < w0.length; ++j) if (w0[j] !== "") w.push(w0[j]);
+            if (w.length === 0) continue;
+            for (j = 0; j < states.length; ++j)
+              if (z.substr(0, states[j].length) === states[j]) break;
+            if (j < states.length) {
+              state = j;
+              if (j === 1) {
+                name = w[1];
+              }
+              if (j === 6)
+                return { name: name, c: c, A: numeric.transpose(A), b: b, rows: rows, vars: vars };
+              continue;
+            }
+            switch (state) {
+              case 0:
+              case 1:
+                err("Unexpected line");
+              case 2:
+                switch (w[0]) {
+                  case "N":
+                    if (N === 0) N = w[1];
+                    else err("Two or more N rows");
+                    break;
+                  case "L":
+                    rows[w[1]] = rl;
+                    sign[rl] = 1;
+                    b[rl] = 0;
+                    ++rl;
+                    break;
+                  case "G":
+                    rows[w[1]] = rl;
+                    sign[rl] = -1;
+                    b[rl] = 0;
+                    ++rl;
+                    break;
+                  case "E":
+                    rows[w[1]] = rl;
+                    sign[rl] = 0;
+                    b[rl] = 0;
+                    ++rl;
+                    break;
+                  default:
+                    err("Parse error " + numeric.prettyPrint(w));
+                }
+                break;
+              case 3:
+                if (!vars.hasOwnProperty(w[0])) {
+                  vars[w[0]] = nv;
+                  c[nv] = 0;
+                  A[nv] = numeric.rep([rl], 0);
+                  ++nv;
+                }
+                var p = vars[w[0]];
+                for (j = 1; j < w.length; j += 2) {
+                  if (w[j] === N) {
+                    c[p] = parseFloat(w[j + 1]);
+                    continue;
+                  }
+                  var q = rows[w[j]];
+                  A[p][q] = (sign[q] < 0 ? -1 : 1) * parseFloat(w[j + 1]);
+                }
+                break;
+              case 4:
+                for (j = 1; j < w.length; j += 2)
+                  b[rows[w[j]]] = (sign[rows[w[j]]] < 0 ? -1 : 1) * parseFloat(w[j + 1]);
+                break;
+              case 5:
+                /*FIXME*/ break;
+              case 6:
+                err("Internal error");
+            }
+          }
+          err("Reached end of file without ENDATA");
+        };
+        // seedrandom.js version 2.0.
+        // Author: David Bau 4/2/2011
+        //
+        // Defines a method Math.seedrandom() that, when called, substitutes
+        // an explicitly seeded RC4-based algorithm for Math.random().  Also
+        // supports automatic seeding from local or network sources of entropy.
+        //
+        // Usage:
+        //
+        //   <script src=http://davidbau.com/encode/seedrandom-min.js></script>
+        //
+        //   Math.seedrandom('yipee'); Sets Math.random to a function that is
+        //                             initialized using the given explicit seed.
+        //
+        //   Math.seedrandom();        Sets Math.random to a function that is
+        //                             seeded using the current time, dom state,
+        //                             and other accumulated local entropy.
+        //                             The generated seed string is returned.
+        //
+        //   Math.seedrandom('yowza', true);
+        //                             Seeds using the given explicit seed mixed
+        //                             together with accumulated entropy.
+        //
+        //   <script src="http://bit.ly/srandom-512"></script>
+        //                             Seeds using physical random bits downloaded
+        //                             from random.org.
+        //
+        //   <script src="https://jsonlib.appspot.com/urandom?callback=Math.seedrandom">
+        //   </script>                 Seeds using urandom bits from call.jsonlib.com,
+        //                             which is faster than random.org.
+        //
+        // Examples:
+        //
+        //   Math.seedrandom("hello");            // Use "hello" as the seed.
+        //   document.write(Math.random());       // Always 0.5463663768140734
+        //   document.write(Math.random());       // Always 0.43973793770592234
+        //   var rng1 = Math.random;              // Remember the current prng.
+        //
+        //   var autoseed = Math.seedrandom();    // New prng with an automatic seed.
+        //   document.write(Math.random());       // Pretty much unpredictable.
+        //
+        //   Math.random = rng1;                  // Continue "hello" prng sequence.
+        //   document.write(Math.random());       // Always 0.554769432473455
+        //
+        //   Math.seedrandom(autoseed);           // Restart at the previous seed.
+        //   document.write(Math.random());       // Repeat the 'unpredictable' value.
+        //
+        // Notes:
+        //
+        // Each time seedrandom('arg') is called, entropy from the passed seed
+        // is accumulated in a pool to help generate future seeds for the
+        // zero-argument form of Math.seedrandom, so entropy can be injected over
+        // time by calling seedrandom with explicit data repeatedly.
+        //
+        // On speed - This javascript implementation of Math.random() is about
+        // 3-10x slower than the built-in Math.random() because it is not native
+        // code, but this is typically fast enough anyway.  Seeding is more expensive,
+        // especially if you use auto-seeding.  Some details (timings on Chrome 4):
+        //
+        // Our Math.random()            - avg less than 0.002 milliseconds per call
+        // seedrandom('explicit')       - avg less than 0.5 milliseconds per call
+        // seedrandom('explicit', true) - avg less than 2 milliseconds per call
+        // seedrandom()                 - avg about 38 milliseconds per call
+        //
+        // LICENSE (BSD):
+        //
+        // Copyright 2010 David Bau, all rights reserved.
+        //
+        // Redistribution and use in source and binary forms, with or without
+        // modification, are permitted provided that the following conditions are met:
+        //
+        //   1. Redistributions of source code must retain the above copyright
+        //      notice, this list of conditions and the following disclaimer.
+        //
+        //   2. Redistributions in binary form must reproduce the above copyright
+        //      notice, this list of conditions and the following disclaimer in the
+        //      documentation and/or other materials provided with the distribution.
+        //
+        //   3. Neither the name of this module nor the names of its contributors may
+        //      be used to endorse or promote products derived from this software
+        //      without specific prior written permission.
+        //
+        // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+        // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+        // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+        // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+        // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+        // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+        // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+        // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+        // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+        // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+        // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+        //
+        /**
+         * All code is in an anonymous closure to keep the global namespace clean.
+         *
+         * @param {number=} overflow
+         * @param {number=} startdenom
+         */
+
+        // Patched by Seb so that seedrandom.js does not pollute the Math object.
+        // My tests suggest that doing Math.trouble = 1 makes Math lookups about 5%
+        // slower.
+        numeric.seedrandom = { pow: Math.pow, random: Math.random };
+
+        (function (pool, math, width, chunks, significance, overflow, startdenom) {
+          //
+          // seedrandom()
+          // This is the seedrandom function described above.
+          //
+          math["seedrandom"] = function seedrandom(seed, use_entropy) {
+            var key = [];
+            var arc4;
+
+            // Flatten the seed string or build one from local entropy if needed.
+            seed = mixkey(
+              flatten(
+                use_entropy
+                  ? [seed, pool]
+                  : arguments.length
+                  ? seed
+                  : [new Date().getTime(), pool, window],
+                3
+              ),
+              key
+            );
+
+            // Use the seed to initialize an ARC4 generator.
+            arc4 = new ARC4(key);
+
+            // Mix the randomness into accumulated entropy.
+            mixkey(arc4.S, pool);
+
+            // Override Math.random
+
+            // This function returns a random double in [0, 1) that contains
+            // randomness in every bit of the mantissa of the IEEE 754 value.
+
+            math["random"] = function random() {
+              // Closure to return a random double:
+              var n = arc4.g(chunks); // Start with a numerator n < 2 ^ 48
+              var d = startdenom; //   and denominator d = 2 ^ 48.
+              var x = 0; //   and no 'extra last byte'.
+              while (n < significance) {
+                // Fill up all significant digits by
+                n = (n + x) * width; //   shifting numerator and
+                d *= width; //   denominator and generating a
+                x = arc4.g(1); //   new least-significant-byte.
+              }
+              while (n >= overflow) {
+                // To avoid rounding up, before adding
+                n /= 2; //   last byte, shift everything
+                d /= 2; //   right using integer math until
+                x >>>= 1; //   we have exactly the desired bits.
+              }
+              return (n + x) / d; // Form the number within [0, 1).
+            };
+
+            // Return the seed that was used
+            return seed;
+          };
+
+          //
+          // ARC4
+          //
+          // An ARC4 implementation.  The constructor takes a key in the form of
+          // an array of at most (width) integers that should be 0 <= x < (width).
+          //
+          // The g(count) method returns a pseudorandom integer that concatenates
+          // the next (count) outputs from ARC4.  Its return value is a number x
+          // that is in the range 0 <= x < (width ^ count).
+          //
+          /** @constructor */
+          function ARC4(key) {
+            var t,
+              u,
+              me = this,
+              keylen = key.length;
+            var i = 0,
+              j = (me.i = me.j = me.m = 0);
+            me.S = [];
+            me.c = [];
+
+            // The empty key [] is treated as [0].
+            if (!keylen) {
+              key = [keylen++];
+            }
+
+            // Set up S using the standard key scheduling algorithm.
+            while (i < width) {
+              me.S[i] = i++;
+            }
+            for (i = 0; i < width; i++) {
+              t = me.S[i];
+              j = lowbits(j + t + key[i % keylen]);
+              u = me.S[j];
+              me.S[i] = u;
+              me.S[j] = t;
+            }
+
+            // The "g" method returns the next (count) outputs as one number.
+            me.g = function getnext(count) {
+              var s = me.S;
+              var i = lowbits(me.i + 1);
+              var t = s[i];
+              var j = lowbits(me.j + t);
+              var u = s[j];
+              s[i] = u;
+              s[j] = t;
+              var r = s[lowbits(t + u)];
+              while (--count) {
+                i = lowbits(i + 1);
+                t = s[i];
+                j = lowbits(j + t);
+                u = s[j];
+                s[i] = u;
+                s[j] = t;
+                r = r * width + s[lowbits(t + u)];
+              }
+              me.i = i;
+              me.j = j;
+              return r;
+            };
+            // For robust unpredictability discard an initial batch of values.
+            // See http://www.rsa.com/rsalabs/node.asp?id=2009
+            me.g(width);
+          }
+
+          //
+          // flatten()
+          // Converts an object tree to nested arrays of strings.
+          //
+          /** @param {Object=} result
+           * @param {string=} prop
+           * @param {string=} typ */
+          function flatten(obj, depth, result, prop, typ) {
+            result = [];
+            typ = typeof obj;
+            if (depth && typ == "object") {
+              for (prop in obj) {
+                if (prop.indexOf("S") < 5) {
+                  // Avoid FF3 bug (local/sessionStorage)
+                  try {
+                    result.push(flatten(obj[prop], depth - 1));
+                  } catch (e) {}
+                }
+              }
+            }
+            return result.length ? result : obj + (typ != "string" ? "\0" : "");
+          }
+
+          //
+          // mixkey()
+          // Mixes a string seed into a key that is an array of integers, and
+          // returns a shortened string seed that is equivalent to the result key.
+          //
+          /** @param {number=} smear
+           * @param {number=} j */
+          function mixkey(seed, key, smear, j) {
+            seed += ""; // Ensure the seed is a string
+            smear = 0;
+            for (j = 0; j < seed.length; j++) {
+              key[lowbits(j)] = lowbits((smear ^= key[lowbits(j)] * 19) + seed.charCodeAt(j));
+            }
+            seed = "";
+            for (j in key) {
+              seed += String.fromCharCode(key[j]);
+            }
+            return seed;
+          }
+
+          //
+          // lowbits()
+          // A quick "n mod width" for width a power of 2.
+          //
+          function lowbits(n) {
+            return n & (width - 1);
+          }
+
+          //
+          // The following constants are related to IEEE 754 limits.
+          //
+          startdenom = math.pow(width, chunks);
+          significance = math.pow(2, significance);
+          overflow = significance * 2;
+
+          //
+          // When seedrandom.js is loaded, we immediately mix a few bits
+          // from the built-in RNG into the entropy pool.  Because we do
+          // not want to intefere with determinstic PRNG state later,
+          // seedrandom will not call math.random on its own again after
+          // initialization.
+          //
+          mixkey(math.random(), pool);
+
+          // End anonymous scope, and pass initial values.
+        })(
+          [], // pool: entropy pool starts empty
+          numeric.seedrandom, // math: package containing random, pow, and seedrandom
+          256, // width: each RC4 output is 0 <= x < 256
+          6, // chunks: at least six RC4 outputs for each double
+          52 // significance: there are 52 significant digits in a double
+        );
+        /* This file is a slightly modified version of quadprog.js from Alberto Santini.
+         * It has been slightly modified by Sébastien Loisel to make sure that it handles
+         * 0-based Arrays instead of 1-based Arrays.
+         * License is in resources/LICENSE.quadprog */
+        (function (exports) {
+          function base0to1(A) {
+            if (typeof A !== "object") {
+              return A;
+            }
+            var ret = [],
+              i,
+              n = A.length;
+            for (i = 0; i < n; i++) ret[i + 1] = base0to1(A[i]);
+            return ret;
+          }
+          function base1to0(A) {
+            if (typeof A !== "object") {
+              return A;
+            }
+            var ret = [],
+              i,
+              n = A.length;
+            for (i = 1; i < n; i++) ret[i - 1] = base1to0(A[i]);
+            return ret;
+          }
+
+          function dpori(a, lda, n) {
+            var i, j, k, kp1, t;
+
+            for (k = 1; k <= n; k = k + 1) {
+              a[k][k] = 1 / a[k][k];
+              t = -a[k][k];
+              //~ dscal(k - 1, t, a[1][k], 1);
+              for (i = 1; i < k; i = i + 1) {
+                a[i][k] = t * a[i][k];
+              }
+
+              kp1 = k + 1;
+              if (n < kp1) {
+                break;
+              }
+              for (j = kp1; j <= n; j = j + 1) {
+                t = a[k][j];
+                a[k][j] = 0;
+                //~ daxpy(k, t, a[1][k], 1, a[1][j], 1);
+                for (i = 1; i <= k; i = i + 1) {
+                  a[i][j] = a[i][j] + t * a[i][k];
+                }
+              }
+            }
+          }
+
+          function dposl(a, lda, n, b) {
+            var i, k, kb, t;
+
+            for (k = 1; k <= n; k = k + 1) {
+              //~ t = ddot(k - 1, a[1][k], 1, b[1], 1);
+              t = 0;
+              for (i = 1; i < k; i = i + 1) {
+                t = t + a[i][k] * b[i];
+              }
+
+              b[k] = (b[k] - t) / a[k][k];
+            }
+
+            for (kb = 1; kb <= n; kb = kb + 1) {
+              k = n + 1 - kb;
+              b[k] = b[k] / a[k][k];
+              t = -b[k];
+              //~ daxpy(k - 1, t, a[1][k], 1, b[1], 1);
+              for (i = 1; i < k; i = i + 1) {
+                b[i] = b[i] + t * a[i][k];
+              }
+            }
+          }
+
+          function dpofa(a, lda, n, info) {
+            var i, j, jm1, k, t, s;
+
+            for (j = 1; j <= n; j = j + 1) {
+              info[1] = j;
+              s = 0;
+              jm1 = j - 1;
+              if (jm1 < 1) {
+                s = a[j][j] - s;
+                if (s <= 0) {
+                  break;
+                }
+                a[j][j] = Math.sqrt(s);
+              } else {
+                for (k = 1; k <= jm1; k = k + 1) {
+                  //~ t = a[k][j] - ddot(k - 1, a[1][k], 1, a[1][j], 1);
+                  t = a[k][j];
+                  for (i = 1; i < k; i = i + 1) {
+                    t = t - a[i][j] * a[i][k];
+                  }
+                  t = t / a[k][k];
+                  a[k][j] = t;
+                  s = s + t * t;
+                }
+                s = a[j][j] - s;
+                if (s <= 0) {
+                  break;
+                }
+                a[j][j] = Math.sqrt(s);
+              }
+              info[1] = 0;
+            }
+          }
+
+          function qpgen2(
+            dmat,
+            dvec,
+            fddmat,
+            n,
+            sol,
+            crval,
+            amat,
+            bvec,
+            fdamat,
+            q,
+            meq,
+            iact,
+            nact,
+            iter,
+            work,
+            ierr
+          ) {
+            var i,
+              j,
+              l,
+              l1,
+              info,
+              it1,
+              iwzv,
+              iwrv,
+              iwrm,
+              iwsv,
+              iwuv,
+              nvl,
+              r,
+              iwnbv,
+              temp,
+              sum,
+              t1,
+              tt,
+              gc,
+              gs,
+              nu,
+              t1inf,
+              t2min,
+              vsmall,
+              tmpa,
+              tmpb,
+              go;
+
+            r = Math.min(n, q);
+            l = 2 * n + (r * (r + 5)) / 2 + 2 * q + 1;
+
+            vsmall = 1.0e-60;
+            do {
+              vsmall = vsmall + vsmall;
+              tmpa = 1 + 0.1 * vsmall;
+              tmpb = 1 + 0.2 * vsmall;
+            } while (tmpa <= 1 || tmpb <= 1);
+
+            for (i = 1; i <= n; i = i + 1) {
+              work[i] = dvec[i];
+            }
+            for (i = n + 1; i <= l; i = i + 1) {
+              work[i] = 0;
+            }
+            for (i = 1; i <= q; i = i + 1) {
+              iact[i] = 0;
+            }
+
+            info = [];
+
+            if (ierr[1] === 0) {
+              dpofa(dmat, fddmat, n, info);
+              if (info[1] !== 0) {
+                ierr[1] = 2;
+                return;
+              }
+              dposl(dmat, fddmat, n, dvec);
+              dpori(dmat, fddmat, n);
+            } else {
+              for (j = 1; j <= n; j = j + 1) {
+                sol[j] = 0;
+                for (i = 1; i <= j; i = i + 1) {
+                  sol[j] = sol[j] + dmat[i][j] * dvec[i];
+                }
+              }
+              for (j = 1; j <= n; j = j + 1) {
+                dvec[j] = 0;
+                for (i = j; i <= n; i = i + 1) {
+                  dvec[j] = dvec[j] + dmat[j][i] * sol[i];
+                }
+              }
+            }
+
+            crval[1] = 0;
+            for (j = 1; j <= n; j = j + 1) {
+              sol[j] = dvec[j];
+              crval[1] = crval[1] + work[j] * sol[j];
+              work[j] = 0;
+              for (i = j + 1; i <= n; i = i + 1) {
+                dmat[i][j] = 0;
+              }
+            }
+            crval[1] = -crval[1] / 2;
+            ierr[1] = 0;
+
+            iwzv = n;
+            iwrv = iwzv + n;
+            iwuv = iwrv + r;
+            iwrm = iwuv + r + 1;
+            iwsv = iwrm + (r * (r + 1)) / 2;
+            iwnbv = iwsv + q;
+
+            for (i = 1; i <= q; i = i + 1) {
+              sum = 0;
+              for (j = 1; j <= n; j = j + 1) {
+                sum = sum + amat[j][i] * amat[j][i];
+              }
+              work[iwnbv + i] = Math.sqrt(sum);
+            }
+            nact = 0;
+            iter[1] = 0;
+            iter[2] = 0;
+
+            function fn_goto_50() {
+              iter[1] = iter[1] + 1;
+
+              l = iwsv;
+              for (i = 1; i <= q; i = i + 1) {
+                l = l + 1;
+                sum = -bvec[i];
+                for (j = 1; j <= n; j = j + 1) {
+                  sum = sum + amat[j][i] * sol[j];
+                }
+                if (Math.abs(sum) < vsmall) {
+                  sum = 0;
+                }
+                if (i > meq) {
+                  work[l] = sum;
+                } else {
+                  work[l] = -Math.abs(sum);
+                  if (sum > 0) {
+                    for (j = 1; j <= n; j = j + 1) {
+                      amat[j][i] = -amat[j][i];
+                    }
+                    bvec[i] = -bvec[i];
+                  }
+                }
+              }
+
+              for (i = 1; i <= nact; i = i + 1) {
+                work[iwsv + iact[i]] = 0;
+              }
+
+              nvl = 0;
+              temp = 0;
+              for (i = 1; i <= q; i = i + 1) {
+                if (work[iwsv + i] < temp * work[iwnbv + i]) {
+                  nvl = i;
+                  temp = work[iwsv + i] / work[iwnbv + i];
+                }
+              }
+              if (nvl === 0) {
+                return 999;
+              }
+
+              return 0;
+            }
+
+            function fn_goto_55() {
+              for (i = 1; i <= n; i = i + 1) {
+                sum = 0;
+                for (j = 1; j <= n; j = j + 1) {
+                  sum = sum + dmat[j][i] * amat[j][nvl];
+                }
+                work[i] = sum;
+              }
+
+              l1 = iwzv;
+              for (i = 1; i <= n; i = i + 1) {
+                work[l1 + i] = 0;
+              }
+              for (j = nact + 1; j <= n; j = j + 1) {
+                for (i = 1; i <= n; i = i + 1) {
+                  work[l1 + i] = work[l1 + i] + dmat[i][j] * work[j];
+                }
+              }
+
+              t1inf = true;
+              for (i = nact; i >= 1; i = i - 1) {
+                sum = work[i];
+                l = iwrm + (i * (i + 3)) / 2;
+                l1 = l - i;
+                for (j = i + 1; j <= nact; j = j + 1) {
+                  sum = sum - work[l] * work[iwrv + j];
+                  l = l + j;
+                }
+                sum = sum / work[l1];
+                work[iwrv + i] = sum;
+                if (iact[i] < meq) {
+                  // continue;
+                  break;
+                }
+                if (sum < 0) {
+                  // continue;
+                  break;
+                }
+                t1inf = false;
+                it1 = i;
+              }
+
+              if (!t1inf) {
+                t1 = work[iwuv + it1] / work[iwrv + it1];
+                for (i = 1; i <= nact; i = i + 1) {
+                  if (iact[i] < meq) {
+                    // continue;
+                    break;
+                  }
+                  if (work[iwrv + i] < 0) {
+                    // continue;
+                    break;
+                  }
+                  temp = work[iwuv + i] / work[iwrv + i];
+                  if (temp < t1) {
+                    t1 = temp;
+                    it1 = i;
+                  }
+                }
+              }
+
+              sum = 0;
+              for (i = iwzv + 1; i <= iwzv + n; i = i + 1) {
+                sum = sum + work[i] * work[i];
+              }
+              if (Math.abs(sum) <= vsmall) {
+                if (t1inf) {
+                  ierr[1] = 1;
+                  // GOTO 999
+                  return 999;
+                } else {
+                  for (i = 1; i <= nact; i = i + 1) {
+                    work[iwuv + i] = work[iwuv + i] - t1 * work[iwrv + i];
+                  }
+                  work[iwuv + nact + 1] = work[iwuv + nact + 1] + t1;
+                  // GOTO 700
+                  return 700;
+                }
+              } else {
+                sum = 0;
+                for (i = 1; i <= n; i = i + 1) {
+                  sum = sum + work[iwzv + i] * amat[i][nvl];
+                }
+                tt = -work[iwsv + nvl] / sum;
+                t2min = true;
+                if (!t1inf) {
+                  if (t1 < tt) {
+                    tt = t1;
+                    t2min = false;
+                  }
+                }
+
+                for (i = 1; i <= n; i = i + 1) {
+                  sol[i] = sol[i] + tt * work[iwzv + i];
+                  if (Math.abs(sol[i]) < vsmall) {
+                    sol[i] = 0;
+                  }
+                }
+
+                crval[1] = crval[1] + tt * sum * (tt / 2 + work[iwuv + nact + 1]);
+                for (i = 1; i <= nact; i = i + 1) {
+                  work[iwuv + i] = work[iwuv + i] - tt * work[iwrv + i];
+                }
+                work[iwuv + nact + 1] = work[iwuv + nact + 1] + tt;
+
+                if (t2min) {
+                  nact = nact + 1;
+                  iact[nact] = nvl;
+
+                  l = iwrm + ((nact - 1) * nact) / 2 + 1;
+                  for (i = 1; i <= nact - 1; i = i + 1) {
+                    work[l] = work[i];
+                    l = l + 1;
+                  }
+
+                  if (nact === n) {
+                    work[l] = work[n];
+                  } else {
+                    for (i = n; i >= nact + 1; i = i - 1) {
+                      if (work[i] === 0) {
+                        // continue;
+                        break;
+                      }
+                      gc = Math.max(Math.abs(work[i - 1]), Math.abs(work[i]));
+                      gs = Math.min(Math.abs(work[i - 1]), Math.abs(work[i]));
+                      if (work[i - 1] >= 0) {
+                        temp = Math.abs(gc * Math.sqrt(1 + (gs * gs) / (gc * gc)));
+                      } else {
+                        temp = -Math.abs(gc * Math.sqrt(1 + (gs * gs) / (gc * gc)));
+                      }
+                      gc = work[i - 1] / temp;
+                      gs = work[i] / temp;
+
+                      if (gc === 1) {
+                        // continue;
+                        break;
+                      }
+                      if (gc === 0) {
+                        work[i - 1] = gs * temp;
+                        for (j = 1; j <= n; j = j + 1) {
+                          temp = dmat[j][i - 1];
+                          dmat[j][i - 1] = dmat[j][i];
+                          dmat[j][i] = temp;
+                        }
+                      } else {
+                        work[i - 1] = temp;
+                        nu = gs / (1 + gc);
+                        for (j = 1; j <= n; j = j + 1) {
+                          temp = gc * dmat[j][i - 1] + gs * dmat[j][i];
+                          dmat[j][i] = nu * (dmat[j][i - 1] + temp) - dmat[j][i];
+                          dmat[j][i - 1] = temp;
+                        }
+                      }
+                    }
+                    work[l] = work[nact];
+                  }
+                } else {
+                  sum = -bvec[nvl];
+                  for (j = 1; j <= n; j = j + 1) {
+                    sum = sum + sol[j] * amat[j][nvl];
+                  }
+                  if (nvl > meq) {
+                    work[iwsv + nvl] = sum;
+                  } else {
+                    work[iwsv + nvl] = -Math.abs(sum);
+                    if (sum > 0) {
+                      for (j = 1; j <= n; j = j + 1) {
+                        amat[j][nvl] = -amat[j][nvl];
+                      }
+                      bvec[nvl] = -bvec[nvl];
+                    }
+                  }
+                  // GOTO 700
+                  return 700;
+                }
+              }
+
+              return 0;
+            }
+
+            function fn_goto_797() {
+              l = iwrm + (it1 * (it1 + 1)) / 2 + 1;
+              l1 = l + it1;
+              if (work[l1] === 0) {
+                // GOTO 798
+                return 798;
+              }
+              gc = Math.max(Math.abs(work[l1 - 1]), Math.abs(work[l1]));
+              gs = Math.min(Math.abs(work[l1 - 1]), Math.abs(work[l1]));
+              if (work[l1 - 1] >= 0) {
+                temp = Math.abs(gc * Math.sqrt(1 + (gs * gs) / (gc * gc)));
+              } else {
+                temp = -Math.abs(gc * Math.sqrt(1 + (gs * gs) / (gc * gc)));
+              }
+              gc = work[l1 - 1] / temp;
+              gs = work[l1] / temp;
+
+              if (gc === 1) {
+                // GOTO 798
+                return 798;
+              }
+              if (gc === 0) {
+                for (i = it1 + 1; i <= nact; i = i + 1) {
+                  temp = work[l1 - 1];
+                  work[l1 - 1] = work[l1];
+                  work[l1] = temp;
+                  l1 = l1 + i;
+                }
+                for (i = 1; i <= n; i = i + 1) {
+                  temp = dmat[i][it1];
+                  dmat[i][it1] = dmat[i][it1 + 1];
+                  dmat[i][it1 + 1] = temp;
+                }
+              } else {
+                nu = gs / (1 + gc);
+                for (i = it1 + 1; i <= nact; i = i + 1) {
+                  temp = gc * work[l1 - 1] + gs * work[l1];
+                  work[l1] = nu * (work[l1 - 1] + temp) - work[l1];
+                  work[l1 - 1] = temp;
+                  l1 = l1 + i;
+                }
+                for (i = 1; i <= n; i = i + 1) {
+                  temp = gc * dmat[i][it1] + gs * dmat[i][it1 + 1];
+                  dmat[i][it1 + 1] = nu * (dmat[i][it1] + temp) - dmat[i][it1 + 1];
+                  dmat[i][it1] = temp;
+                }
+              }
+
+              return 0;
+            }
+
+            function fn_goto_798() {
+              l1 = l - it1;
+              for (i = 1; i <= it1; i = i + 1) {
+                work[l1] = work[l];
+                l = l + 1;
+                l1 = l1 + 1;
+              }
+
+              work[iwuv + it1] = work[iwuv + it1 + 1];
+              iact[it1] = iact[it1 + 1];
+              it1 = it1 + 1;
+              if (it1 < nact) {
+                // GOTO 797
+                return 797;
+              }
+
+              return 0;
+            }
+
+            function fn_goto_799() {
+              work[iwuv + nact] = work[iwuv + nact + 1];
+              work[iwuv + nact + 1] = 0;
+              iact[nact] = 0;
+              nact = nact - 1;
+              iter[2] = iter[2] + 1;
+
+              return 0;
+            }
+
+            go = 0;
+            while (true) {
+              go = fn_goto_50();
+              if (go === 999) {
+                return;
+              }
+              while (true) {
+                go = fn_goto_55();
+                if (go === 0) {
+                  break;
+                }
+                if (go === 999) {
+                  return;
+                }
+                if (go === 700) {
+                  if (it1 === nact) {
+                    fn_goto_799();
+                  } else {
+                    while (true) {
+                      fn_goto_797();
+                      go = fn_goto_798();
+                      if (go !== 797) {
+                        break;
+                      }
+                    }
+                    fn_goto_799();
+                  }
+                }
+              }
+            }
+          }
+
+          function solveQP(Dmat, dvec, Amat, bvec, meq, factorized) {
+            Dmat = base0to1(Dmat);
+            dvec = base0to1(dvec);
+            Amat = base0to1(Amat);
+            var i,
+              n,
+              q,
+              nact,
+              r,
+              crval = [],
+              iact = [],
+              sol = [],
+              work = [],
+              iter = [],
+              message;
+
+            meq = meq || 0;
+            factorized = factorized ? base0to1(factorized) : [undefined, 0];
+            bvec = bvec ? base0to1(bvec) : [];
+
+            // In Fortran the array index starts from 1
+            n = Dmat.length - 1;
+            q = Amat[1].length - 1;
+
+            if (!bvec) {
+              for (i = 1; i <= q; i = i + 1) {
+                bvec[i] = 0;
+              }
+            }
+            for (i = 1; i <= q; i = i + 1) {
+              iact[i] = 0;
+            }
+            nact = 0;
+            r = Math.min(n, q);
+            for (i = 1; i <= n; i = i + 1) {
+              sol[i] = 0;
+            }
+            crval[1] = 0;
+            for (i = 1; i <= 2 * n + (r * (r + 5)) / 2 + 2 * q + 1; i = i + 1) {
+              work[i] = 0;
+            }
+            for (i = 1; i <= 2; i = i + 1) {
+              iter[i] = 0;
+            }
+
+            qpgen2(
+              Dmat,
+              dvec,
+              n,
+              n,
+              sol,
+              crval,
+              Amat,
+              bvec,
+              n,
+              q,
+              meq,
+              iact,
+              nact,
+              iter,
+              work,
+              factorized
+            );
+
+            message = "";
+            if (factorized[1] === 1) {
+              message = "constraints are inconsistent, no solution!";
+            }
+            if (factorized[1] === 2) {
+              message = "matrix D in quadratic function is not positive definite!";
+            }
+
+            return {
+              solution: base1to0(sol),
+              value: base1to0(crval),
+              unconstrained_solution: base1to0(dvec),
+              iterations: base1to0(iter),
+              iact: base1to0(iact),
+              message: message,
+            };
+          }
+          exports.solveQP = solveQP;
+        })(numeric);
+        /*
+Shanti Rao sent me this routine by private email. I had to modify it
+slightly to work on Arrays instead of using a Matrix object.
+It is apparently translated from http://stitchpanorama.sourceforge.net/Python/svd.py
+*/
+
+        numeric.svd = function svd(A) {
+          var temp;
+          //Compute the thin SVD from G. H. Golub and C. Reinsch, Numer. Math. 14, 403-420 (1970)
+          var prec = numeric.epsilon; //Math.pow(2,-52) // assumes double prec
+          var tolerance = 1e-64 / prec;
+          var itmax = 50;
+          var c = 0;
+          var i = 0;
+          var j = 0;
+          var k = 0;
+          var l = 0;
+
+          var u = numeric.clone(A);
+          var m = u.length;
+
+          var n = u[0].length;
+
+          if (m < n) throw "Need more rows than columns";
+
+          var e = new Array(n);
+          var q = new Array(n);
+          for (i = 0; i < n; i++) e[i] = q[i] = 0.0;
+          var v = numeric.rep([n, n], 0);
+          //	v.zero();
+
+          function pythag(a, b) {
+            a = Math.abs(a);
+            b = Math.abs(b);
+            if (a > b) return a * Math.sqrt(1.0 + (b * b) / a / a);
+            else if (b == 0.0) return a;
+            return b * Math.sqrt(1.0 + (a * a) / b / b);
+          }
+
+          //Householder's reduction to bidiagonal form
+
+          var f = 0.0;
+          var g = 0.0;
+          var h = 0.0;
+          var x = 0.0;
+          var y = 0.0;
+          var z = 0.0;
+          var s = 0.0;
+
+          for (i = 0; i < n; i++) {
+            e[i] = g;
+            s = 0.0;
+            l = i + 1;
+            for (j = i; j < m; j++) s += u[j][i] * u[j][i];
+            if (s <= tolerance) g = 0.0;
+            else {
+              f = u[i][i];
+              g = Math.sqrt(s);
+              if (f >= 0.0) g = -g;
+              h = f * g - s;
+              u[i][i] = f - g;
+              for (j = l; j < n; j++) {
+                s = 0.0;
+                for (k = i; k < m; k++) s += u[k][i] * u[k][j];
+                f = s / h;
+                for (k = i; k < m; k++) u[k][j] += f * u[k][i];
+              }
+            }
+            q[i] = g;
+            s = 0.0;
+            for (j = l; j < n; j++) s = s + u[i][j] * u[i][j];
+            if (s <= tolerance) g = 0.0;
+            else {
+              f = u[i][i + 1];
+              g = Math.sqrt(s);
+              if (f >= 0.0) g = -g;
+              h = f * g - s;
+              u[i][i + 1] = f - g;
+              for (j = l; j < n; j++) e[j] = u[i][j] / h;
+              for (j = l; j < m; j++) {
+                s = 0.0;
+                for (k = l; k < n; k++) s += u[j][k] * u[i][k];
+                for (k = l; k < n; k++) u[j][k] += s * e[k];
+              }
+            }
+            y = Math.abs(q[i]) + Math.abs(e[i]);
+            if (y > x) x = y;
+          }
+
+          // accumulation of right hand gtransformations
+          for (i = n - 1; i != -1; i += -1) {
+            if (g != 0.0) {
+              h = g * u[i][i + 1];
+              for (j = l; j < n; j++) v[j][i] = u[i][j] / h;
+              for (j = l; j < n; j++) {
+                s = 0.0;
+                for (k = l; k < n; k++) s += u[i][k] * v[k][j];
+                for (k = l; k < n; k++) v[k][j] += s * v[k][i];
+              }
+            }
+            for (j = l; j < n; j++) {
+              v[i][j] = 0;
+              v[j][i] = 0;
+            }
+            v[i][i] = 1;
+            g = e[i];
+            l = i;
+          }
+
+          // accumulation of left hand transformations
+          for (i = n - 1; i != -1; i += -1) {
+            l = i + 1;
+            g = q[i];
+            for (j = l; j < n; j++) u[i][j] = 0;
+            if (g != 0.0) {
+              h = u[i][i] * g;
+              for (j = l; j < n; j++) {
+                s = 0.0;
+                for (k = l; k < m; k++) s += u[k][i] * u[k][j];
+                f = s / h;
+                for (k = i; k < m; k++) u[k][j] += f * u[k][i];
+              }
+              for (j = i; j < m; j++) u[j][i] = u[j][i] / g;
+            } else for (j = i; j < m; j++) u[j][i] = 0;
+            u[i][i] += 1;
+          }
+
+          // diagonalization of the bidiagonal form
+          prec = prec * x;
+          for (k = n - 1; k != -1; k += -1) {
+            for (var iteration = 0; iteration < itmax; iteration++) {
+              // test f splitting
+              var test_convergence = false;
+              for (l = k; l != -1; l += -1) {
+                if (Math.abs(e[l]) <= prec) {
+                  test_convergence = true;
+                  break;
+                }
+                if (Math.abs(q[l - 1]) <= prec) break;
+              }
+              if (!test_convergence) {
+                // cancellation of e[l] if l>0
+                c = 0.0;
+                s = 1.0;
+                var l1 = l - 1;
+                for (i = l; i < k + 1; i++) {
+                  f = s * e[i];
+                  e[i] = c * e[i];
+                  if (Math.abs(f) <= prec) break;
+                  g = q[i];
+                  h = pythag(f, g);
+                  q[i] = h;
+                  c = g / h;
+                  s = -f / h;
+                  for (j = 0; j < m; j++) {
+                    y = u[j][l1];
+                    z = u[j][i];
+                    u[j][l1] = y * c + z * s;
+                    u[j][i] = -y * s + z * c;
+                  }
+                }
+              }
+              // test f convergence
+              z = q[k];
+              if (l == k) {
+                //convergence
+                if (z < 0.0) {
+                  //q[k] is made non-negative
+                  q[k] = -z;
+                  for (j = 0; j < n; j++) v[j][k] = -v[j][k];
+                }
+                break; //break out of iteration loop and move on to next k value
+              }
+              if (iteration >= itmax - 1) throw "Error: no convergence.";
+              // shift from bottom 2x2 minor
+              x = q[l];
+              y = q[k - 1];
+              g = e[k - 1];
+              h = e[k];
+              f = ((y - z) * (y + z) + (g - h) * (g + h)) / (2.0 * h * y);
+              g = pythag(f, 1.0);
+              if (f < 0.0) f = ((x - z) * (x + z) + h * (y / (f - g) - h)) / x;
+              else f = ((x - z) * (x + z) + h * (y / (f + g) - h)) / x;
+              // next QR transformation
+              c = 1.0;
+              s = 1.0;
+              for (i = l + 1; i < k + 1; i++) {
+                g = e[i];
+                y = q[i];
+                h = s * g;
+                g = c * g;
+                z = pythag(f, h);
+                e[i - 1] = z;
+                c = f / z;
+                s = h / z;
+                f = x * c + g * s;
+                g = -x * s + g * c;
+                h = y * s;
+                y = y * c;
+                for (j = 0; j < n; j++) {
+                  x = v[j][i - 1];
+                  z = v[j][i];
+                  v[j][i - 1] = x * c + z * s;
+                  v[j][i] = -x * s + z * c;
+                }
+                z = pythag(f, h);
+                q[i - 1] = z;
+                c = f / z;
+                s = h / z;
+                f = c * g + s * y;
+                x = -s * g + c * y;
+                for (j = 0; j < m; j++) {
+                  y = u[j][i - 1];
+                  z = u[j][i];
+                  u[j][i - 1] = y * c + z * s;
+                  u[j][i] = -y * s + z * c;
+                }
+              }
+              e[l] = 0.0;
+              e[k] = f;
+              q[k] = x;
+            }
+          }
+
+          //vt= transpose(v)
+          //return (u,q,vt)
+          for (i = 0; i < q.length; i++) if (q[i] < prec) q[i] = 0;
+
+          //sort eigenvalues
+          for (i = 0; i < n; i++) {
+            //writeln(q)
+            for (j = i - 1; j >= 0; j--) {
+              if (q[j] < q[i]) {
+                //  writeln(i,'-',j)
+                c = q[j];
+                q[j] = q[i];
+                q[i] = c;
+                for (k = 0; k < u.length; k++) {
+                  temp = u[k][i];
+                  u[k][i] = u[k][j];
+                  u[k][j] = temp;
+                }
+                for (k = 0; k < v.length; k++) {
+                  temp = v[k][i];
+                  v[k][i] = v[k][j];
+                  v[k][j] = temp;
+                }
+                //	   u.swapCols(i,j)
+                //	   v.swapCols(i,j)
+                i = j;
+              }
+            }
+          }
+
+          return { U: u, S: q, V: v };
+        };
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(27)));
+
+      /***/
+    },
+    /* 13 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (Buffer) {
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
+          return encodeWeights;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
+          return decodeWeights;
+        });
+        /* unused harmony export concatenateTypedArrays */
+        /* unused harmony export stringByteLength */
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+          return arrayBufferToBase64String;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+          return base64StringToArrayBuffer;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
+          return concatenateArrayBuffers;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+          return basename;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
+          return getModelArtifactsInfoForJSON;
+        });
+        /* unused harmony export getFloat16Decoder */
+        /* harmony import */ var _ops_complex__WEBPACK_IMPORTED_MODULE_0__ =
+          __webpack_require__(18);
+        /* harmony import */ var _ops_tensor_ops__WEBPACK_IMPORTED_MODULE_1__ =
+          __webpack_require__(8);
+        /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_2__ = __webpack_require__(1);
+        /* harmony import */ var _types__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(34);
+        /**
+         * @license
+         * Copyright 2018 Google LLC. All Rights Reserved.
+         * Licensed under the Apache License, Version 2.0 (the "License");
+         * you may not use this file except in compliance with the License.
+         * You may obtain a copy of the License at
+         *
+         * http://www.apache.org/licenses/LICENSE-2.0
+         *
+         * Unless required by applicable law or agreed to in writing, software
+         * distributed under the License is distributed on an "AS IS" BASIS,
+         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+         * See the License for the specific language governing permissions and
+         * limitations under the License.
+         * =============================================================================
+         */
+
+        /** Number of bytes reserved for the length of the string. (32bit integer). */
+        const NUM_BYTES_STRING_LENGTH = 4;
+        /**
+         * Encode a map from names to weight values as an ArrayBuffer, along with an
+         * `Array` of `WeightsManifestEntry` as specification of the encoded weights.
+         *
+         * This function does not perform sharding.
+         *
+         * This function is the reverse of `decodeWeights`.
+         *
+         * @param tensors A map ("dict") from names to tensors.
+         * @param group Group to which the weights belong (optional).
+         * @returns A `Promise` of
+         *   - A flat `ArrayBuffer` with all the binary values of the `Tensor`s
+         *     concatenated.
+         *   - An `Array` of `WeightManifestEntry`s, carrying information including
+         *     tensor names, `dtype`s and shapes.
+         * @throws Error: on unsupported tensor `dtype`.
+         */
+        async function encodeWeights(tensors, group) {
+          // TODO(adarob, cais): Support quantization.
+          const specs = [];
+          const dataPromises = [];
+          const names = Array.isArray(tensors)
+            ? tensors.map((tensor) => tensor.name)
+            : Object.keys(tensors);
+          for (let i = 0; i < names.length; ++i) {
+            const name = names[i];
+            const t = Array.isArray(tensors) ? tensors[i].tensor : tensors[name];
+            if (
+              t.dtype !== "float32" &&
+              t.dtype !== "int32" &&
+              t.dtype !== "bool" &&
+              t.dtype !== "string" &&
+              t.dtype !== "complex64"
+            ) {
+              throw new Error(`Unsupported dtype in weight '${name}': ${t.dtype}`);
+            }
+            const spec = { name, shape: t.shape, dtype: t.dtype };
+            if (t.dtype === "string") {
+              const utf8bytes = new Promise(async (resolve) => {
+                const vals = await t.bytes();
+                const totalNumBytes =
+                  vals.reduce((p, c) => p + c.length, 0) + NUM_BYTES_STRING_LENGTH * vals.length;
+                const bytes = new Uint8Array(totalNumBytes);
+                let offset = 0;
+                for (let i = 0; i < vals.length; i++) {
+                  const val = vals[i];
+                  const bytesOfLength = new Uint8Array(new Uint32Array([val.length]).buffer);
+                  bytes.set(bytesOfLength, offset);
+                  offset += NUM_BYTES_STRING_LENGTH;
+                  bytes.set(val, offset);
+                  offset += val.length;
+                }
+                resolve(bytes);
+              });
+              dataPromises.push(utf8bytes);
+            } else {
+              dataPromises.push(t.data());
+            }
+            if (group != null) {
+              spec.group = group;
+            }
+            specs.push(spec);
+          }
+          const tensorValues = await Promise.all(dataPromises);
+          return { data: concatenateTypedArrays(tensorValues), specs };
+        }
+        /**
+         * Decode flat ArrayBuffer as weights.
+         *
+         * This function does not handle sharding.
+         *
+         * This function is the reverse of `encodeWeights`.
+         *
+         * @param buffer A flat ArrayBuffer carrying the binary values of the tensors
+         *   concatenated in the order specified in `specs`.
+         * @param specs Specifications of the names, dtypes and shapes of the tensors
+         *   whose value are encoded by `buffer`.
+         * @return A map from tensor name to tensor value, with the names corresponding
+         *   to names in `specs`.
+         * @throws Error, if any of the tensors has unsupported dtype.
+         */
+        function decodeWeights(buffer, specs) {
+          // TODO(adarob, cais): Support quantization.
+          const out = {};
+          let float16Decode;
+          let offset = 0;
+          for (const spec of specs) {
+            const name = spec.name;
+            const dtype = spec.dtype;
+            const shape = spec.shape;
+            const size = Object(_util__WEBPACK_IMPORTED_MODULE_2__["sizeFromShape"])(shape);
+            let values;
+            if ("quantization" in spec) {
+              const quantization = spec.quantization;
+              if (quantization.dtype === "uint8" || quantization.dtype === "uint16") {
+                if (!("min" in quantization && "scale" in quantization)) {
+                  throw new Error(
+                    `Weight ${spec.name} with quantization ${quantization.dtype} ` +
+                      `doesn't have corresponding metadata min and scale.`
+                  );
+                }
+              } else if (quantization.dtype === "float16") {
+                if (dtype !== "float32") {
+                  throw new Error(
+                    `Weight ${spec.name} is quantized with ${quantization.dtype} ` +
+                      `which only supports weights of type float32 not ${dtype}.`
+                  );
+                }
+              } else {
+                throw new Error(
+                  `Weight ${spec.name} has unknown ` +
+                    `quantization dtype ${quantization.dtype}. ` +
+                    `Supported quantization dtypes are: ` +
+                    `'uint8', 'uint16', and 'float16'.`
+                );
+              }
+              const quantizationSizeFactor =
+                _types__WEBPACK_IMPORTED_MODULE_3__[/* DTYPE_VALUE_SIZE_MAP */ "a"][
+                  quantization.dtype
+                ];
+              const byteBuffer = buffer.slice(offset, offset + size * quantizationSizeFactor);
+              const quantizedArray =
+                quantization.dtype === "uint8"
+                  ? new Uint8Array(byteBuffer)
+                  : new Uint16Array(byteBuffer);
+              if (dtype === "float32") {
+                if (quantization.dtype === "uint8" || quantization.dtype === "uint16") {
+                  values = new Float32Array(quantizedArray.length);
+                  for (let i = 0; i < quantizedArray.length; i++) {
+                    const v = quantizedArray[i];
+                    values[i] = v * quantization.scale + quantization.min;
+                  }
+                } else if (quantization.dtype === "float16") {
+                  if (float16Decode === undefined) {
+                    float16Decode = getFloat16Decoder();
+                  }
+                  values = float16Decode(quantizedArray);
+                } else {
+                  throw new Error(
+                    `Unsupported quantization type ${quantization.dtype} ` +
+                      `for weight type float32.`
+                  );
+                }
+              } else if (dtype === "int32") {
+                if (quantization.dtype !== "uint8" && quantization.dtype !== "uint16") {
+                  throw new Error(
+                    `Unsupported quantization type ${quantization.dtype} ` +
+                      `for weight type int32.`
+                  );
+                }
+                values = new Int32Array(quantizedArray.length);
+                for (let i = 0; i < quantizedArray.length; i++) {
+                  const v = quantizedArray[i];
+                  values[i] = Math.round(v * quantization.scale + quantization.min);
+                }
+              } else {
+                throw new Error(`Unsupported dtype in weight '${name}': ${dtype}`);
+              }
+              offset += size * quantizationSizeFactor;
+            } else if (dtype === "string") {
+              const size = Object(_util__WEBPACK_IMPORTED_MODULE_2__["sizeFromShape"])(spec.shape);
+              values = [];
+              for (let i = 0; i < size; i++) {
+                const byteLength = new Uint32Array(
+                  buffer.slice(offset, offset + NUM_BYTES_STRING_LENGTH)
+                )[0];
+                offset += NUM_BYTES_STRING_LENGTH;
+                const bytes = new Uint8Array(buffer.slice(offset, offset + byteLength));
+                values.push(bytes);
+                offset += byteLength;
+              }
+            } else {
+              const dtypeFactor =
+                _types__WEBPACK_IMPORTED_MODULE_3__[/* DTYPE_VALUE_SIZE_MAP */ "a"][dtype];
+              const byteBuffer = buffer.slice(offset, offset + size * dtypeFactor);
+              if (dtype === "float32") {
+                values = new Float32Array(byteBuffer);
+              } else if (dtype === "int32") {
+                values = new Int32Array(byteBuffer);
+              } else if (dtype === "bool") {
+                values = new Uint8Array(byteBuffer);
+              } else if (dtype === "complex64") {
+                values = new Float32Array(byteBuffer);
+                const real = new Float32Array(values.length / 2);
+                const image = new Float32Array(values.length / 2);
+                for (let i = 0; i < real.length; i++) {
+                  real[i] = values[i * 2];
+                  image[i] = values[i * 2 + 1];
+                }
+                const realTensor = Object(
+                  _ops_tensor_ops__WEBPACK_IMPORTED_MODULE_1__[/* tensor */ "f"]
+                )(real, shape, "float32");
+                const imageTensor = Object(
+                  _ops_tensor_ops__WEBPACK_IMPORTED_MODULE_1__[/* tensor */ "f"]
+                )(image, shape, "float32");
+                out[name] = Object(_ops_complex__WEBPACK_IMPORTED_MODULE_0__[/* complex */ "a"])(
+                  realTensor,
+                  imageTensor
+                );
+              } else {
+                throw new Error(`Unsupported dtype in weight '${name}': ${dtype}`);
+              }
+              offset += size * dtypeFactor;
+            }
+            if (dtype !== "complex64") {
+              out[name] = Object(_ops_tensor_ops__WEBPACK_IMPORTED_MODULE_1__[/* tensor */ "f"])(
+                values,
+                shape,
+                dtype
+              );
+            }
+          }
+          return out;
+        }
+        /**
+         * Concatenate TypedArrays into an ArrayBuffer.
+         */
+        function concatenateTypedArrays(xs) {
+          // TODO(adarob, cais): Support quantization.
+          if (xs === null) {
+            throw new Error(`Invalid input value: ${JSON.stringify(xs)}`);
+          }
+          let totalByteLength = 0;
+          // `normalizedXs` is here for this reason: a `TypedArray`'s `buffer'
+          // can have a different byte length from that of the `TypedArray` itself,
+          // for example, when the `TypedArray` is created from an offset in an
+          // `ArrayBuffer`. `normliazedXs` holds `TypedArray`s whose `buffer`s match
+          // the `TypedArray` in byte length. If an element of `xs` does not show
+          // this property, a new `TypedArray` that satisfy this property will be
+          // constructed and pushed into `normalizedXs`.
+          const normalizedXs = [];
+          xs.forEach((x) => {
+            totalByteLength += x.byteLength;
+            // tslint:disable:no-any
+            normalizedXs.push(x.byteLength === x.buffer.byteLength ? x : new x.constructor(x));
+            if (
+              !(x instanceof Float32Array || x instanceof Int32Array || x instanceof Uint8Array)
+            ) {
+              throw new Error(`Unsupported TypedArray subtype: ${x.constructor.name}`);
+            }
+            // tslint:enable:no-any
+          });
+          const y = new Uint8Array(totalByteLength);
+          let offset = 0;
+          normalizedXs.forEach((x) => {
+            y.set(new Uint8Array(x.buffer), offset);
+            offset += x.byteLength;
+          });
+          return y.buffer;
+        }
+        // Use Buffer on Node.js instead of Blob/atob/btoa
+        const useNodeBuffer =
+          typeof Buffer !== "undefined" &&
+          (typeof Blob === "undefined" ||
+            typeof atob === "undefined" ||
+            typeof btoa === "undefined");
+        /**
+         * Calculate the byte length of a JavaScript string.
+         *
+         * Note that a JavaScript string can contain wide characters, therefore the
+         * length of the string is not necessarily equal to the byte length.
+         *
+         * @param str Input string.
+         * @returns Byte length.
+         */
+        function stringByteLength(str) {
+          if (useNodeBuffer) {
+            return Buffer.byteLength(str);
+          }
+          return new Blob([str]).size;
+        }
+        /**
+         * Encode an ArrayBuffer as a base64 encoded string.
+         *
+         * @param buffer `ArrayBuffer` to be converted.
+         * @returns A string that base64-encodes `buffer`.
+         */
+        function arrayBufferToBase64String(buffer) {
+          if (useNodeBuffer) {
+            return Buffer.from(buffer).toString("base64");
+          }
+          const buf = new Uint8Array(buffer);
+          let s = "";
+          for (let i = 0, l = buf.length; i < l; i++) {
+            s += String.fromCharCode(buf[i]);
+          }
+          return btoa(s);
+        }
+        /**
+         * Decode a base64 string as an ArrayBuffer.
+         *
+         * @param str Base64 string.
+         * @returns Decoded `ArrayBuffer`.
+         */
+        function base64StringToArrayBuffer(str) {
+          if (useNodeBuffer) {
+            const buf = Buffer.from(str, "base64");
+            return buf.buffer.slice(buf.byteOffset, buf.byteOffset + buf.byteLength);
+          }
+          const s = atob(str);
+          const buffer = new Uint8Array(s.length);
+          for (let i = 0; i < s.length; ++i) {
+            buffer.set([s.charCodeAt(i)], i);
+          }
+          return buffer.buffer;
+        }
+        /**
+         * Concatenate a number of ArrayBuffers into one.
+         *
+         * @param buffers A number of array buffers to concatenate.
+         * @returns Result of concatenating `buffers` in order.
+         */
+        function concatenateArrayBuffers(buffers) {
+          if (buffers.length === 1) {
+            return buffers[0];
+          }
+          let totalByteLength = 0;
+          buffers.forEach((buffer) => {
+            totalByteLength += buffer.byteLength;
+          });
+          const temp = new Uint8Array(totalByteLength);
+          let offset = 0;
+          buffers.forEach((buffer) => {
+            temp.set(new Uint8Array(buffer), offset);
+            offset += buffer.byteLength;
+          });
+          return temp.buffer;
+        }
+        /**
+         * Get the basename of a path.
+         *
+         * Behaves in a way analogous to Linux's basename command.
+         *
+         * @param path
+         */
+        function basename(path) {
+          const SEPARATOR = "/";
+          path = path.trim();
+          while (path.endsWith(SEPARATOR)) {
+            path = path.slice(0, path.length - 1);
+          }
+          const items = path.split(SEPARATOR);
+          return items[items.length - 1];
+        }
+        /**
+         * Populate ModelArtifactsInfo fields for a model with JSON topology.
+         * @param modelArtifacts
+         * @returns A ModelArtifactsInfo object.
+         */
+        function getModelArtifactsInfoForJSON(modelArtifacts) {
+          if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
+            throw new Error("Expected JSON model topology, received ArrayBuffer.");
+          }
+          return {
+            dateSaved: new Date(),
+            modelTopologyType: "JSON",
+            modelTopologyBytes:
+              modelArtifacts.modelTopology == null
+                ? 0
+                : stringByteLength(JSON.stringify(modelArtifacts.modelTopology)),
+            weightSpecsBytes:
+              modelArtifacts.weightSpecs == null
+                ? 0
+                : stringByteLength(JSON.stringify(modelArtifacts.weightSpecs)),
+            weightDataBytes:
+              modelArtifacts.weightData == null ? 0 : modelArtifacts.weightData.byteLength,
+          };
+        }
+        /**
+         * Computes mantisa table for casting Float16 to Float32
+         * See http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf
+         *
+         * @returns Uint32Array, 2048 mantissa lookup values.
+         */
+        function computeFloat16MantisaTable() {
+          const convertMantissa = (i) => {
+            let m = i << 13;
+            let e = 0;
+            while ((m & 0x00800000) === 0) {
+              e -= 0x00800000;
+              m <<= 1;
+            }
+            m &= ~0x00800000;
+            e += 0x38800000;
+            return m | e;
+          };
+          const mantisaTable = new Uint32Array(2048);
+          mantisaTable[0] = 0;
+          for (let i = 1; i < 1024; i++) {
+            mantisaTable[i] = convertMantissa(i);
+          }
+          for (let i = 1024; i < 2048; i++) {
+            mantisaTable[i] = 0x38000000 + ((i - 1024) << 13);
+          }
+          return mantisaTable;
+        }
+        /**
+         * Computes exponent table for casting Float16 to Float32
+         * See http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf
+         *
+         * @returns Uint32Array, 64 exponent lookup values.
+         */
+        function computeFloat16ExponentTable() {
+          const exponentTable = new Uint32Array(64);
+          exponentTable[0] = 0;
+          exponentTable[31] = 0x47800000;
+          exponentTable[32] = 0x80000000;
+          exponentTable[63] = 0xc7800000;
+          for (let i = 1; i < 31; i++) {
+            exponentTable[i] = i << 23;
+          }
+          for (let i = 33; i < 63; i++) {
+            exponentTable[i] = 0x80000000 + ((i - 32) << 23);
+          }
+          return exponentTable;
+        }
+        /**
+         * Computes offset table for casting Float16 to Float32
+         * See http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf
+         *
+         * @returns Uint32Array, 6d offset values.
+         */
+        function computeFloat16OffsetTable() {
+          const offsetTable = new Uint32Array(64);
+          for (let i = 0; i < 64; i++) {
+            offsetTable[i] = 1024;
+          }
+          offsetTable[0] = offsetTable[32] = 0;
+          return offsetTable;
+        }
+        /**
+         * Retrieve a Float16 decoder which will decode a ByteArray of Float16 values
+         * to a Float32Array.
+         *
+         * @returns Function (buffer: Uint16Array) => Float32Array which decodes
+         *          the Uint16Array of Float16 bytes to a Float32Array.
+         */
+        function getFloat16Decoder() {
+          // Algorithm is based off of http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf
+          // Cache lookup tables
+          const mantisaTable = computeFloat16MantisaTable();
+          const exponentTable = computeFloat16ExponentTable();
+          const offsetTable = computeFloat16OffsetTable();
+          return (quantizedArray) => {
+            const buffer = new ArrayBuffer(4 * quantizedArray.length);
+            const bufferUint32View = new Uint32Array(buffer);
+            for (let index = 0; index < quantizedArray.length; index++) {
+              const float16Bits = quantizedArray[index];
+              const float32Bits =
+                mantisaTable[offsetTable[float16Bits >> 10] + (float16Bits & 0x3ff)] +
+                exponentTable[float16Bits >> 10];
+              bufferUint32View[index] = float32Bits;
+            }
+            return new Float32Array(buffer);
+          };
+        }
+        //# sourceMappingURL=io_utils.js.map
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(39).Buffer));
+
+      /***/
+    },
+    /* 14 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "f", function () {
+        return /* binding */ iteratorFromItems;
+      });
+      __webpack_require__.d(__webpack_exports__, "e", function () {
+        return /* binding */ iteratorFromFunction;
+      });
+      __webpack_require__.d(__webpack_exports__, "d", function () {
+        return /* binding */ iteratorFromConcatenated;
+      });
+      __webpack_require__.d(__webpack_exports__, "g", function () {
+        return /* binding */ iteratorFromZipped;
+      });
+      __webpack_require__.d(__webpack_exports__, "a", function () {
+        return /* binding */ lazy_iterator_LazyIterator;
+      });
+      __webpack_require__.d(__webpack_exports__, "b", function () {
+        return /* binding */ lazy_iterator_OneToManyIterator;
+      });
+      __webpack_require__.d(__webpack_exports__, "c", function () {
+        return /* binding */ ZipMismatchMode;
+      });
+
+      // UNUSED EXPORTS: iteratorFromIncrementing, iteratorFromConcatenatedFunction, ChainedIterator, PrefetchIterator, ShuffleIterator
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
+      var dist = __webpack_require__(0);
+
+      // EXTERNAL MODULE: ./node_modules/seedrandom/index.js
+      var seedrandom = __webpack_require__(20);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/deep_map.js
+      var deep_map = __webpack_require__(19);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/deep_clone.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      function deepClone(container) {
+        return Object(deep_map["b" /* deepMap */])(container, cloneIfTensor);
+      }
+      // tslint:disable-next-line: no-any
+      function cloneIfTensor(item) {
+        if (item instanceof dist["Tensor"]) {
+          return { value: item.clone(), recurse: false };
+        } else if (Object(deep_map["e" /* isIterable */])(item)) {
+          return { value: null, recurse: true };
+        } else {
+          return { value: item, recurse: false };
+        }
+      }
+      //# sourceMappingURL=deep_clone.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/ring_buffer.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+      /**
+       * A ring buffer, providing O(1) FIFO, LIFO, and related operations.
+       */
+      class RingBuffer {
+        /**
+         * Constructs a `RingBuffer`.
+         * @param capacity The number of items that the buffer can accomodate.
+         */
+        constructor(capacity) {
+          this.capacity = capacity;
+          // Note we store the indices in the range 0 <= index < 2*capacity.
+          // This allows us to distinguish the full from the empty case.
+          // See https://www.snellman.net/blog/archive/2016-12-13-ring-buffers/
+          this.begin = 0; // inclusive
+          this.end = 0; // exclusive
+          if (capacity == null) {
+            throw new RangeError("Can't create a ring buffer of unknown capacity.");
+          }
+          if (capacity < 1) {
+            throw new RangeError("Can't create ring buffer of capacity < 1.");
+          }
+          this.data = new Array(capacity);
+          this.doubledCapacity = 2 * capacity;
+        }
+        /**
+         * Map any index into the range 0 <= index < 2*capacity.
+         */
+        wrap(index) {
+          // don't trust % on negative numbers
+          while (index < 0) {
+            index += this.doubledCapacity;
+          }
+          return index % this.doubledCapacity;
+        }
+        get(index) {
+          if (index < 0) {
+            throw new RangeError("Can't get item at a negative index.");
+          }
+          return this.data[index % this.capacity];
+        }
+        set(index, value) {
+          if (index < 0) {
+            throw new RangeError("Can't set item at a negative index.");
+          }
+          this.data[index % this.capacity] = value;
+        }
+        /**
+         * Returns the current number of items in the buffer.
+         */
+        length() {
+          let length = this.end - this.begin;
+          if (length < 0) {
+            length = this.doubledCapacity + length;
+          }
+          return length;
+        }
+        /**
+         * Reports whether the buffer is full.
+         * @returns true if the number of items in the buffer equals its capacity, and
+         *   false otherwise.
+         */
+        isFull() {
+          return this.length() === this.capacity;
+        }
+        /**
+         * Reports whether the buffer is empty.
+         * @returns true if the number of items in the buffer equals zero, and
+         *   false otherwise.
+         */
+        isEmpty() {
+          return this.length() === 0;
+        }
+        /**
+         * Adds an item to the end of the buffer.
+         */
+        push(value) {
+          if (this.isFull()) {
+            throw new RangeError("Ring buffer is full.");
+          }
+          this.set(this.end, value);
+          this.end = this.wrap(this.end + 1);
+        }
+        /**
+         * Adds many items to the end of the buffer, in order.
+         */
+        pushAll(values) {
+          for (const value of values) {
+            this.push(value);
+          }
+        }
+        /**
+         * Removes and returns the last item in the buffer.
+         */
+        pop() {
+          if (this.isEmpty()) {
+            throw new RangeError("Ring buffer is empty.");
+          }
+          this.end = this.wrap(this.end - 1);
+          const result = this.get(this.end);
+          this.set(this.end, undefined);
+          return result;
+        }
+        /**
+         * Adds an item to the beginning of the buffer.
+         */
+        unshift(value) {
+          if (this.isFull()) {
+            throw new RangeError("Ring buffer is full.");
+          }
+          this.begin = this.wrap(this.begin - 1);
+          this.set(this.begin, value);
+        }
+        /**
+         * Removes and returns the first item in the buffer.
+         */
+        shift() {
+          if (this.isEmpty()) {
+            throw new RangeError("Ring buffer is empty.");
+          }
+          const result = this.get(this.begin);
+          this.set(this.begin, undefined);
+          this.begin = this.wrap(this.begin + 1);
+          return result;
+        }
+        /**
+         * Removes and returns a specific item in the buffer, and moves the last item
+         * to the vacated slot.  This is useful for implementing a shuffling stream.
+         * Note that this operation necessarily scrambles the original order.
+         *
+         * @param relativeIndex: the index of the item to remove, relative to the
+         *   first item in the buffer (e.g., hiding the ring nature of the underlying
+         *   storage).
+         */
+        shuffleExcise(relativeIndex) {
+          if (this.isEmpty()) {
+            throw new RangeError("Ring buffer is empty.");
+          }
+          const index = this.wrap(this.begin + relativeIndex);
+          const result = this.get(index);
+          this.set(index, this.pop());
+          return result;
+        }
+      }
+      //# sourceMappingURL=ring_buffer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/growing_ring_buffer.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      class growing_ring_buffer_GrowingRingBuffer extends RingBuffer {
+        /**
+         * Constructs a `GrowingRingBuffer`.
+         */
+        constructor() {
+          super(growing_ring_buffer_GrowingRingBuffer.INITIAL_CAPACITY);
+        }
+        isFull() {
+          return false;
+        }
+        push(value) {
+          if (super.isFull()) {
+            this.expand();
+          }
+          super.push(value);
+        }
+        unshift(value) {
+          if (super.isFull()) {
+            this.expand();
+          }
+          super.unshift(value);
+        }
+        /**
+         * Doubles the capacity of the buffer.
+         */
+        expand() {
+          const newCapacity = this.capacity * 2;
+          const newData = new Array(newCapacity);
+          const len = this.length();
+          // Rotate the buffer to start at index 0 again, since we can't just
+          // allocate more space at the end.
+          for (let i = 0; i < len; i++) {
+            newData[i] = this.get(this.wrap(this.begin + i));
+          }
+          this.data = newData;
+          this.capacity = newCapacity;
+          this.doubledCapacity = 2 * this.capacity;
+          this.begin = 0;
+          this.end = len;
+        }
+      }
+      growing_ring_buffer_GrowingRingBuffer.INITIAL_CAPACITY = 32;
+      //# sourceMappingURL=growing_ring_buffer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/lazy_iterator.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      // Here we implement a simple asynchronous iterator.
+      // This lets us avoid using either third-party stream libraries or
+      // recent TypeScript language support requiring polyfills.
+      /**
+       * Create a `LazyIterator` from an array of items.
+       */
+      function iteratorFromItems(items) {
+        return new lazy_iterator_ArrayIterator(items);
+      }
+      /**
+       * Create a `LazyIterator` of incrementing integers.
+       */
+      function iteratorFromIncrementing(start) {
+        let i = start;
+        return iteratorFromFunction(() => ({ value: i++, done: false }));
+      }
+      /**
+       * Create a `LazyIterator` from a function.
+       *
+       * ```js
+       * let i = -1;
+       * const func = () =>
+       *    ++i < 5 ? {value: i, done: false} : {value: null, done: true};
+       * const iter = tf.data.iteratorFromFunction(func);
+       * await iter.forEachAsync(e => console.log(e));
+       * ```
+       *
+       * @param func A function that produces data on each call.
+       */
+      function iteratorFromFunction(func) {
+        return new FunctionCallIterator(func);
+      }
+      /**
+       * Create a `LazyIterator` by concatenating underlying streams, which are
+       * themselves provided as a stream.
+       *
+       * This can also be thought of as a "stream flatten" operation.
+       *
+       * @param baseIterators A stream of streams to be concatenated.
+       * @param baseErrorHandler An optional function that can intercept `Error`s
+       *   raised during a `next()` call on the base stream.  This function can decide
+       *   whether the error should be propagated, whether the error should be
+       *   ignored, or whether the base stream should be terminated.
+       */
+      function iteratorFromConcatenated(baseIterators, baseErrorHandler) {
+        return new ChainedIterator(baseIterators, baseErrorHandler);
+      }
+      /**
+       * Create a `LazyIterator` by concatenating streams produced by calling a
+       * stream-generating function a given number of times.
+       *
+       * Since a `LazyIterator` is read-once, it cannot be repeated, but this
+       * function can be used to achieve a similar effect:
+       *
+       *   LazyIterator.ofConcatenatedFunction(() => new MyIterator(), 6);
+       *
+       * @param iteratorFunc: A function that produces a new stream on each call.
+       * @param count: The number of times to call the function.
+       * @param baseErrorHandler An optional function that can intercept `Error`s
+       *   raised during a `next()` call on the base stream.  This function can decide
+       *   whether the error should be propagated, whether the error should be
+       *   ignored, or whether the base stream should be terminated.
+       */
+      function iteratorFromConcatenatedFunction(iteratorFunc, count, baseErrorHandler) {
+        return iteratorFromConcatenated(
+          iteratorFromFunction(iteratorFunc).take(count),
+          baseErrorHandler
+        );
+      }
+      /**
+       * Create a `LazyIterator` by zipping together an array, dict, or nested
+       * structure of `LazyIterator`s (and perhaps additional constants).
+       *
+       * The underlying streams must provide elements in a consistent order such
+       * that they correspond.
+       *
+       * Typically, the underlying streams should have the same number of
+       * elements. If they do not, the behavior is determined by the
+       * `mismatchMode` argument.
+       *
+       * The nested structure of the `iterators` argument determines the
+       * structure of elements in the resulting iterator.
+       *
+       * @param iterators: An array or object containing LazyIterators at the
+       * leaves.
+       * @param mismatchMode: Determines what to do when one underlying iterator
+       * is exhausted before the others.  `ZipMismatchMode.FAIL` (the default)
+       * causes an error to be thrown in this case.  `ZipMismatchMode.SHORTEST`
+       * causes the zipped iterator to terminate with the furst underlying
+       * streams, so elements remaining on the longer streams are ignored.
+       * `ZipMismatchMode.LONGEST` causes the zipped stream to continue, filling
+       * in nulls for the exhausted streams, until all streams are exhausted.
+       */
+      function iteratorFromZipped(iterators, mismatchMode = ZipMismatchMode.FAIL) {
+        return new lazy_iterator_ZipIterator(iterators, mismatchMode);
+      }
+      /**
+       * An asynchronous iterator, providing lazy access to a potentially
+       * unbounded stream of elements.
+       *
+       * Iterator can be obtained from a dataset:
+       * `const iter = await dataset.iterator();`
+       */
+      class lazy_iterator_LazyIterator {
+        /**
+         * Collect all remaining elements of a bounded stream into an array.
+         * Obviously this will succeed only for small streams that fit in memory.
+         * Useful for testing.
+         *
+         * @returns A Promise for an array of stream elements, which will resolve
+         *   when the stream is exhausted.
+         */
+        async toArray() {
+          const result = [];
+          let x = await this.next();
+          while (!x.done) {
+            result.push(x.value);
+            x = await this.next();
+          }
+          return result;
+        }
+        /**
+         * Collect all elements of this dataset into an array with prefetching 100
+         * elements. This is useful for testing, because the prefetch changes the
+         * order in which the Promises are resolved along the processing pipeline.
+         * This may help expose bugs where results are dependent on the order of
+         * Promise resolution rather than on the logical order of the stream (i.e.,
+         * due to hidden mutable state).
+         *
+         * @returns A Promise for an array of stream elements, which will resolve
+         *   when the stream is exhausted.
+         */
+        async toArrayForTest() {
+          const stream = this.prefetch(100);
+          const result = [];
+          let x = await stream.next();
+          while (!x.done) {
+            result.push(x.value);
+            x = await stream.next();
+          }
+          return result;
+        }
+        /**
+         * Draw items from the stream until it is exhausted.
+         *
+         * This can be useful when the stream has side effects but no output.  In
+         * that case, calling this function guarantees that the stream will be
+         * fully processed.
+         */
+        async resolveFully() {
+          let x = await this.next();
+          while (!x.done) {
+            x = await this.next();
+          }
+        }
+        /**
+         * Draw items from the stream until it is exhausted, or a predicate fails.
+         *
+         * This can be useful when the stream has side effects but no output.  In
+         * that case, calling this function guarantees that the stream will be
+         * fully processed.
+         */
+        async resolveWhile(predicate) {
+          let x = await this.next();
+          let shouldContinue = predicate(x.value);
+          while (!x.done && shouldContinue) {
+            x = await this.next();
+            shouldContinue = predicate(x.value);
+          }
+        }
+        /**
+         * Handles errors thrown on this stream using a provided handler function.
+         *
+         * @param handler A function that handles any `Error` thrown during a `next()`
+         *   call and returns true if the stream should continue (dropping the failed
+         *   call) or false if the stream should quietly terminate.  If the handler
+         *   itself throws (or rethrows) an `Error`, that will be propagated.
+         *
+         * @returns A `LazyIterator` of elements passed through from upstream,
+         *   possibly filtering or terminating on upstream `next()` calls that
+         *   throw an `Error`.
+         */
+        handleErrors(handler) {
+          return new ErrorHandlingLazyIterator(this, handler);
+        }
+        // TODO(soergel): Implement reduce() etc.
+        /**
+         * Filters this stream according to `predicate`.
+         *
+         * @param predicate A function mapping a stream element to a boolean or a
+         * `Promise` for one.
+         *
+         * @returns A `LazyIterator` of elements for which the predicate was true.
+         */
+        filter(predicate) {
+          return new lazy_iterator_FilterIterator(this, predicate);
+        }
+        /**
+         * Maps this stream through a 1-to-1 transform.
+         *
+         * @param transform A function mapping a stream element to a transformed
+         *   element.
+         *
+         * @returns A `LazyIterator` of transformed elements.
+         */
+        map(transform) {
+          return new lazy_iterator_MapIterator(this, transform);
+        }
+        /**
+         * Maps this stream through an async 1-to-1 transform.
+         *
+         * @param transform A function mapping a stream element to a `Promise` for a
+         *   transformed stream element.
+         *
+         * @returns A `LazyIterator` of transformed elements.
+         */
+        mapAsync(transform) {
+          return new lazy_iterator_AsyncMapIterator(this, transform);
+        }
+        /**
+         * Maps this stream through a 1-to-1 transform, forcing serial execution.
+         *
+         * @param transform A function mapping a stream element to a transformed
+         *   element.
+         *
+         * @returns A `LazyIterator` of transformed elements.
+         */
+        serialMapAsync(transform) {
+          return new lazy_iterator_AsyncMapIterator(this, transform).serial();
+        }
+        /**
+         * Maps this stream through a 1-to-many transform.
+         *
+         * @param transform A function mapping a stream element to an array of
+         *   transformed elements.
+         *
+         * @returns A `DataStream` of transformed elements.
+         */
+        flatmap(transform) {
+          return new lazy_iterator_FlatmapIterator(this, transform);
+        }
+        /**
+         * Apply a function to every element of the stream.
+         *
+         * @param f A function to apply to each stream element.
+         */
+        async forEachAsync(f) {
+          return this.map(f).resolveFully();
+        }
+        /**
+         * Apply a function to every element of the stream, forcing serial execution.
+         *
+         * @param f A function to apply to each stream element.  Should return 'true'
+         *   to indicate that the stream should continue, or 'false' to cause it to
+         *   terminate.
+         */
+        async serialForEach(f) {
+          return this.serialMapAsync(f).resolveWhile((x) => x === true);
+        }
+        /**
+         * Groups elements into batches, represented as arrays of elements.
+         *
+         * We can think of the elements of this iterator as 'rows' (even if they are
+         * nested structures).  By the same token, consecutive values for a given
+         * key within the elements form a 'column'.  This matches the usual sense of
+         * 'row' and 'column' when processing tabular data (e.g., parsing a CSV).
+         *
+         * Thus, "Row-major" means that the resulting batch is simply a collection of
+         * rows: `[row1, row2, row3, ...]`.  This is contrast to the column-major
+         * form, which is needed for vectorized computation.
+         *
+         * @param batchSize The number of elements desired per batch.
+         * @param smallLastBatch Whether to emit the final batch when it has fewer
+         *   than batchSize elements. Default true.
+         * @returns A `LazyIterator` of batches of elements, represented as arrays
+         *   of the original element type.
+         */
+        rowMajorBatch(batchSize, smallLastBatch = true) {
+          return new RowMajorBatchIterator(this, batchSize, smallLastBatch);
+        }
+        /**
+         * Groups elements into batches, represented in column-major form.
+         *
+         * We can think of the elements of this iterator as 'rows' (even if they are
+         * nested structures).  By the same token, consecutive values for a given
+         * key within the elements form a 'column'.  This matches the usual sense of
+         * 'row' and 'column' when processing tabular data (e.g., parsing a CSV).
+         *
+         * Thus, "column-major" means that the resulting batch is a (potentially
+         * nested) structure representing the columns.  Each column entry, then,
+         * contains a collection of the values found in that column for a range of
+         * input elements.  This representation allows for vectorized computation, in
+         * contrast to the row-major form.
+         *
+         * The inputs should all have the same nested structure (i.e., of arrays and
+         * dicts).  The result is a single object with the same nested structure,
+         * where the leaves are arrays collecting the values of the inputs at that
+         * location (or, optionally, the result of a custom function applied to those
+         * arrays).
+         *
+         * @param batchSize The number of elements desired per batch.
+         * @param smallLastBatch Whether to emit the final batch when it has fewer
+         *   than batchSize elements. Default true.
+         * @param zipFn: (optional) A function that expects an array of elements at a
+         *   single node of the object tree, and returns a `DeepMapResult`.  The
+         *   `DeepMapResult` either provides a result value for that node (i.e.,
+         *   representing the subtree), or indicates that the node should be processed
+         *   recursively.  The default zipFn recurses as far as possible and places
+         *   arrays at the leaves.
+         * @returns A `LazyIterator` of batches of elements, represented as an object
+         *   with collections at the leaves.
+         */
+        columnMajorBatch(
+          batchSize,
+          smallLastBatch = true,
+          // tslint:disable-next-line:no-any
+          zipFn = deep_map["f" /* zipToList */]
+        ) {
+          // First collect the desired number of input elements as a row-major batch.
+          const rowBatches = this.rowMajorBatch(batchSize, smallLastBatch);
+          // Now 'rotate' or 'pivot' the data, collecting all values from each column
+          // in the batch (i.e., for each key within the elements) into an array.
+          return rowBatches.map((x) => Object(deep_map["d" /* deepZip */])(x, zipFn));
+        }
+        /**
+         * Concatenate this `LazyIterator` with another.
+         *
+         * @param iterator A `LazyIterator` to be concatenated onto this one.
+         * @param baseErrorHandler An optional function that can intercept `Error`s
+         *   raised during a `next()` call on the base stream.  This function can
+         *   decide whether the error should be propagated, whether the error should
+         *   be ignored, or whether the base stream should be terminated.
+         * @returns A `LazyIterator`.
+         */
+        concatenate(iterator, baseErrorHandler) {
+          return new ChainedIterator(iteratorFromItems([this, iterator]), baseErrorHandler);
+        }
+        /**
+         * Limits this stream to return at most `count` items.
+         *
+         * @param count The maximum number of items to provide from the stream. If
+         * a negative or undefined value is given, the entire stream is returned
+         *   unaltered.
+         */
+        take(count) {
+          if (count < 0 || count == null) {
+            return this;
+          }
+          return new TakeIterator(this, count);
+        }
+        /**
+         * Skips the first `count` items in this stream.
+         *
+         * @param count The number of items to skip.  If a negative or undefined
+         * value is given, the entire stream is returned unaltered.
+         */
+        skip(count) {
+          if (count < 0 || count == null) {
+            return this;
+          }
+          return new lazy_iterator_SkipIterator(this, count);
+        }
+        /**
+         * Prefetch the first `bufferSize` items in this stream.
+         *
+         * Note this prefetches Promises, but makes no guarantees about when those
+         * Promises resolve.
+         *
+         * @param bufferSize: An integer specifying the number of elements to be
+         *   prefetched.
+         */
+        prefetch(bufferSize) {
+          return new lazy_iterator_PrefetchIterator(this, bufferSize);
+        }
+        // TODO(soergel): deep sharded shuffle, where supported
+        /**
+         * Randomly shuffles the elements of this stream.
+         *
+         * @param bufferSize: An integer specifying the number of elements from
+         * this stream from which the new stream will sample.
+         * @param seed: (Optional.) An integer specifying the random seed that
+         * will be used to create the distribution.
+         */
+        shuffle(windowSize, seed) {
+          return new lazy_iterator_ShuffleIterator(this, windowSize, seed);
+        }
+        /**
+         * Force an iterator to execute serially: each next() call will await the
+         * prior one, so that they cannot execute concurrently.
+         */
+        serial() {
+          return new SerialIterator(this);
+        }
+      }
+      // ============================================================================
+      // The following private classes serve to implement the chainable methods
+      // on LazyIterator.  Unfortunately they can't be placed in separate files,
+      // due to resulting trouble with circular imports.
+      // ============================================================================
+      // Iterators that just extend LazyIterator directly
+      // ============================================================================
+      class lazy_iterator_ArrayIterator extends lazy_iterator_LazyIterator {
+        constructor(items) {
+          super();
+          this.items = items;
+          this.trav = 0;
+        }
+        summary() {
+          return `Array of ${this.items.length} items`;
+        }
+        async next() {
+          if (this.trav >= this.items.length) {
+            return { value: null, done: true };
+          }
+          const item = this.items[this.trav];
+          this.trav++;
+          return { value: deepClone(item), done: false };
+        }
+      }
+      class FunctionCallIterator extends lazy_iterator_LazyIterator {
+        constructor(nextFn) {
+          super();
+          this.nextFn = nextFn;
+        }
+        summary() {
+          return `Function call`;
+        }
+        async next() {
+          try {
+            return this.nextFn();
+          } catch (e) {
+            // Modify the error message but leave the stack trace intact
+            e.message = `Error thrown while iterating through a dataset: ${e.message}`;
+            throw e;
+          }
+        }
+      }
+      class SerialIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream) {
+          super();
+          this.upstream = upstream;
+          this.lastRead = Promise.resolve({ value: null, done: false });
+        }
+        summary() {
+          return `${this.upstream.summary()} -> Serial`;
+        }
+        async next() {
+          // This sets this.lastRead to a new Promise right away, as opposed to
+          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
+          // would not work because this.nextRead would be updated only after the
+          // promise resolves.
+          this.lastRead = this.lastRead.then(() => this.serialNext());
+          return this.lastRead;
+        }
+        async serialNext() {
+          return this.upstream.next();
+        }
+      }
+      class lazy_iterator_SkipIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream, maxCount) {
+          super();
+          this.upstream = upstream;
+          this.maxCount = maxCount;
+          // Local state that should not be clobbered by out-of-order execution.
+          this.count = 0;
+          this.lastRead = Promise.resolve({ value: null, done: false });
+        }
+        summary() {
+          return `${this.upstream.summary()} -> Skip`;
+        }
+        async next() {
+          // This sets this.lastRead to a new Promise right away, as opposed to
+          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
+          // would not work because this.nextRead would be updated only after the
+          // promise resolves.
+          this.lastRead = this.lastRead.then(() => this.serialNext());
+          return this.lastRead;
+        }
+        async serialNext() {
+          // TODO(soergel): consider tradeoffs of reading in parallel, eg.
+          // collecting next() promises in an Array and then waiting for
+          // Promise.all() of those. Benefit: pseudo-parallel execution.  Drawback:
+          // maybe delayed GC.
+          while (this.count++ < this.maxCount) {
+            const skipped = await this.upstream.next();
+            // short-circuit if upstream is already empty
+            if (skipped.done) {
+              return skipped;
+            }
+            dist["dispose"](skipped.value);
+          }
+          return this.upstream.next();
+        }
+      }
+      class TakeIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream, maxCount) {
+          super();
+          this.upstream = upstream;
+          this.maxCount = maxCount;
+          this.count = 0;
+        }
+        summary() {
+          return `${this.upstream.summary()} -> Take`;
+        }
+        async next() {
+          if (this.count++ >= this.maxCount) {
+            return { value: null, done: true };
+          }
+          return this.upstream.next();
+        }
+      }
+      // Note this batch just groups items into row-wise element arrays.
+      // Rotating these to a column-wise representation happens only at the dataset
+      // level.
+      class RowMajorBatchIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream, batchSize, enableSmallLastBatch = true) {
+          super();
+          this.upstream = upstream;
+          this.batchSize = batchSize;
+          this.enableSmallLastBatch = enableSmallLastBatch;
+          this.lastRead = Promise.resolve({ value: null, done: false });
+        }
+        summary() {
+          return `${this.upstream.summary()} -> RowMajorBatch`;
+        }
+        async next() {
+          // This sets this.lastRead to a new Promise right away, as opposed to
+          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
+          // would not work because this.nextRead would be updated only after the
+          // promise resolves.
+          this.lastRead = this.lastRead.then(() => this.serialNext());
+          return this.lastRead;
+        }
+        async serialNext() {
+          const batch = [];
+          while (batch.length < this.batchSize) {
+            const item = await this.upstream.next();
+            if (item.done) {
+              if (this.enableSmallLastBatch && batch.length > 0) {
+                return { value: batch, done: false };
+              }
+              return { value: null, done: true };
+            }
+            batch.push(item.value);
+          }
+          return { value: batch, done: false };
+        }
+      }
+      class lazy_iterator_FilterIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream, predicate) {
+          super();
+          this.upstream = upstream;
+          this.predicate = predicate;
+          this.lastRead = Promise.resolve({ value: null, done: false });
+        }
+        summary() {
+          return `${this.upstream.summary()} -> Filter`;
+        }
+        async next() {
+          // This sets this.lastRead to a new Promise right away, as opposed to
+          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
+          // would not work because this.nextRead would be updated only after the
+          // promise resolves.
+          this.lastRead = this.lastRead.then(() => this.serialNext());
+          return this.lastRead;
+        }
+        async serialNext() {
+          while (true) {
+            const item = await this.upstream.next();
+            if (item.done || this.predicate(item.value)) {
+              return item;
+            }
+            dist["dispose"](item.value);
+          }
+        }
+      }
+      class lazy_iterator_MapIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream, transform) {
+          super();
+          this.upstream = upstream;
+          this.transform = transform;
+        }
+        summary() {
+          return `${this.upstream.summary()} -> Map`;
+        }
+        async next() {
+          const item = await this.upstream.next();
+          if (item.done) {
+            return { value: null, done: true };
+          }
+          const inputTensors = dist["tensor_util"].getTensorsInContainer(item.value);
+          // Careful: the transform may mutate the item in place.
+          // That's why we have to remember the input Tensors above, and then
+          // below dispose only those that were not passed through to the output.
+          // Note too that the transform function is responsible for tidying
+          // any intermediate Tensors.  Here we are concerned only about the
+          // inputs.
+          const mapped = this.transform(item.value);
+          const outputTensors = dist["tensor_util"].getTensorsInContainer(mapped);
+          // TODO(soergel) faster intersection
+          // TODO(soergel) move to tf.disposeExcept(in, out)?
+          for (const t of inputTensors) {
+            if (!dist["tensor_util"].isTensorInList(t, outputTensors)) {
+              t.dispose();
+            }
+          }
+          return { value: mapped, done: false };
+        }
+      }
+      class ErrorHandlingLazyIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream, handler) {
+          super();
+          this.upstream = upstream;
+          this.handler = handler;
+          this.count = 0;
+          this.lastRead = Promise.resolve({ value: null, done: false });
+        }
+        summary() {
+          return `${this.upstream.summary()} -> handleErrors`;
+        }
+        async next() {
+          // This sets this.lastRead to a new Promise right away, as opposed to
+          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
+          // would not work because this.nextRead would be updated only after the
+          // promise resolves.
+          this.lastRead = this.lastRead.then(() => this.serialNext());
+          return this.lastRead;
+        }
+        async serialNext() {
+          while (true) {
+            try {
+              return await this.upstream.next();
+            } catch (e) {
+              if (!this.handler(e)) {
+                return { value: null, done: true };
+              }
+              // If the handler returns true, loop and fetch the next upstream item.
+              // If the upstream iterator throws an endless stream of errors, and if
+              // the handler says to ignore them, then we loop forever here.  That is
+              // the correct behavior-- it's up to the handler to decide when to stop.
+            }
+          }
+        }
+      }
+      class lazy_iterator_AsyncMapIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream, transform) {
+          super();
+          this.upstream = upstream;
+          this.transform = transform;
+        }
+        summary() {
+          return `${this.upstream.summary()} -> AsyncMap`;
+        }
+        async next() {
+          const item = await this.upstream.next();
+          if (item.done) {
+            return { value: null, done: true };
+          }
+          const inputTensors = dist["tensor_util"].getTensorsInContainer(item.value);
+          // Careful: the transform may mutate the item in place.
+          // That's why we have to remember the input Tensors above, and then
+          // below dispose only those that were not passed through to the output.
+          // Note too that the transform function is responsible for tidying
+          // any intermediate Tensors.  Here we are concerned only about the
+          // inputs.
+          const mapped = await this.transform(item.value);
+          const outputTensors = dist["tensor_util"].getTensorsInContainer(mapped);
+          // TODO(soergel) faster intersection
+          // TODO(soergel) move to tf.disposeExcept(in, out)?
+          for (const t of inputTensors) {
+            if (!dist["tensor_util"].isTensorInList(t, outputTensors)) {
+              t.dispose();
+            }
+          }
+          return { value: mapped, done: false };
+        }
+      }
+      // Iterators that maintain a queue of pending items
+      // ============================================================================
+      /**
+       * A base class for transforming streams that operate by maintaining an
+       * output queue of elements that are ready to return via next().  This is
+       * commonly required when the transformation is 1-to-many:  A call to next()
+       * may trigger a call to the underlying stream, which will produce many
+       * mapped elements of this stream-- of which we need to return only one, so
+       * we have to queue the rest.
+       */
+      class lazy_iterator_OneToManyIterator extends lazy_iterator_LazyIterator {
+        constructor() {
+          super();
+          this.outputQueue = new growing_ring_buffer_GrowingRingBuffer();
+          this.lastRead = Promise.resolve({ value: null, done: false });
+        }
+        async next() {
+          // This sets this.lastRead to a new Promise right away, as opposed to
+          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
+          // would not work because this.nextRead would be updated only after the
+          // promise resolves.
+          this.lastRead = this.lastRead.then(() => this.serialNext());
+          return this.lastRead;
+        }
+        async serialNext() {
+          // Fetch so that the queue contains at least one item if possible.
+          // If the upstream source is exhausted, AND there are no items left in
+          // the output queue, then this stream is also exhausted.
+          while (this.outputQueue.length() === 0) {
+            // TODO(soergel): consider parallel reads.
+            if (!(await this.pump())) {
+              return { value: null, done: true };
+            }
+          }
+          return { value: this.outputQueue.shift(), done: false };
+        }
+      }
+      class lazy_iterator_FlatmapIterator extends lazy_iterator_OneToManyIterator {
+        constructor(upstream, transform) {
+          super();
+          this.upstream = upstream;
+          this.transform = transform;
+        }
+        summary() {
+          return `${this.upstream.summary()} -> Flatmap`;
+        }
+        async pump() {
+          const item = await this.upstream.next();
+          if (item.done) {
+            return false;
+          }
+          const inputTensors = dist["tensor_util"].getTensorsInContainer(item.value);
+          // Careful: the transform may mutate the item in place.
+          // that's why we have to remember the input Tensors above, and then
+          // below dispose only those that were not passed through to the output.
+          // Note too that the transform function is responsible for tidying any
+          // intermediate Tensors.  Here we are concerned only about the inputs.
+          const mappedArray = this.transform(item.value);
+          const outputTensors = dist["tensor_util"].getTensorsInContainer(mappedArray);
+          this.outputQueue.pushAll(mappedArray);
+          // TODO(soergel) faster intersection, and deduplicate outputTensors
+          // TODO(soergel) move to tf.disposeExcept(in, out)?
+          for (const t of inputTensors) {
+            if (!dist["tensor_util"].isTensorInList(t, outputTensors)) {
+              t.dispose();
+            }
+          }
+          return true;
+        }
+      }
+      /**
+       * Provides a `LazyIterator` that concatenates a stream of underlying
+       * streams.
+       *
+       * Doing this in a concurrency-safe way requires some trickery.  In
+       * particular, we want this stream to return the elements from the
+       * underlying streams in the correct order according to when next() was
+       * called, even if the resulting Promises resolve in a different order.
+       */
+      class ChainedIterator extends lazy_iterator_LazyIterator {
+        constructor(iterators, baseErrorHandler) {
+          super();
+          this.baseErrorHandler = baseErrorHandler;
+          // Strict Promise execution order:
+          // a next() call may not even begin until the previous one completes.
+          this.lastRead = null;
+          // Local state that should not be clobbered by out-of-order execution.
+          this.iterator = null;
+          this.moreIterators = iterators;
+        }
+        summary() {
+          const upstreamSummaries = "TODO: fill in upstream of chained summaries";
+          return `${upstreamSummaries} -> Chained`;
+        }
+        async next() {
+          this.lastRead = this.readFromChain(this.lastRead);
+          return this.lastRead;
+        }
+        async readFromChain(lastRead) {
+          // Must await on the previous read since the previous read may have advanced
+          // the stream of streams, from which we need to read.
+          // This is unfortunate since we can't parallelize reads. Which means
+          // prefetching of chained streams is a no-op.
+          // One solution is to prefetch immediately upstream of this.
+          await lastRead;
+          if (this.iterator == null) {
+            const iteratorResult = await this.moreIterators.next();
+            if (iteratorResult.done) {
+              // No more streams to stream from.
+              return { value: null, done: true };
+            }
+            this.iterator = iteratorResult.value;
+            if (this.baseErrorHandler != null) {
+              this.iterator = this.iterator.handleErrors(this.baseErrorHandler);
+            }
+          }
+          const itemResult = await this.iterator.next();
+          if (itemResult.done) {
+            this.iterator = null;
+            return this.readFromChain(lastRead);
+          }
+          return itemResult;
+        }
+      }
+      var ZipMismatchMode;
+      (function (ZipMismatchMode) {
+        ZipMismatchMode[(ZipMismatchMode["FAIL"] = 0)] = "FAIL";
+        ZipMismatchMode[(ZipMismatchMode["SHORTEST"] = 1)] = "SHORTEST";
+        ZipMismatchMode[(ZipMismatchMode["LONGEST"] = 2)] = "LONGEST"; // use nulls for exhausted streams; use up the longest stream.
+      })(ZipMismatchMode || (ZipMismatchMode = {}));
+      /**
+       * Provides a `LazyIterator` that zips together an array, dict, or nested
+       * structure of `LazyIterator`s (and perhaps additional constants).
+       *
+       * The underlying streams must provide elements in a consistent order such
+       * that they correspond.
+       *
+       * Typically, the underlying streams should have the same number of
+       * elements. If they do not, the behavior is determined by the
+       * `mismatchMode` argument.
+       *
+       * The nested structure of the `iterators` argument determines the
+       * structure of elements in the resulting iterator.
+       *
+       * Doing this in a concurrency-safe way requires some trickery.  In
+       * particular, we want this stream to return the elements from the
+       * underlying streams in the correct order according to when next() was
+       * called, even if the resulting Promises resolve in a different order.
+       *
+       * @param iterators: An array or object containing LazyIterators at the
+       * leaves.
+       * @param mismatchMode: Determines what to do when one underlying iterator
+       * is exhausted before the others.  `ZipMismatchMode.FAIL` (the default)
+       * causes an error to be thrown in this case.  `ZipMismatchMode.SHORTEST`
+       * causes the zipped iterator to terminate with the furst underlying
+       * streams, so elements remaining on the longer streams are ignored.
+       * `ZipMismatchMode.LONGEST` causes the zipped stream to continue, filling
+       * in nulls for the exhausted streams, until all streams are exhausted.
+       */
+      class lazy_iterator_ZipIterator extends lazy_iterator_LazyIterator {
+        constructor(iterators, mismatchMode = ZipMismatchMode.FAIL) {
+          super();
+          this.iterators = iterators;
+          this.mismatchMode = mismatchMode;
+          this.count = 0;
+          this.currentPromise = null;
+        }
+        summary() {
+          const upstreamSummaries = "TODO: fill in upstream of zip summaries";
+          return `{${upstreamSummaries}} -> Zip`;
+        }
+        async nextState(afterState) {
+          // This chaining ensures that the underlying next() are not even called
+          // before the previous ones have resolved.
+          await afterState;
+          // Collect underlying iterator "done" signals as a side effect in
+          // getNext()
+          let numIterators = 0;
+          let iteratorsDone = 0;
+          function getNext(container) {
+            if (container instanceof lazy_iterator_LazyIterator) {
+              const result = container.next();
+              return {
+                value: result.then((x) => {
+                  numIterators++;
+                  if (x.done) {
+                    iteratorsDone++;
+                  }
+                  return x.value;
+                }),
+                recurse: false,
+              };
+            } else {
+              return { value: null, recurse: true };
+            }
+          }
+          const mapped = await Object(deep_map["c" /* deepMapAndAwaitAll */])(
+            this.iterators,
+            getNext
+          );
+          if (numIterators === iteratorsDone) {
+            // The streams have all ended.
+            return { value: null, done: true };
+          }
+          if (iteratorsDone > 0) {
+            switch (this.mismatchMode) {
+              case ZipMismatchMode.FAIL:
+                throw new Error(
+                  "Zipped streams should have the same length. " +
+                    `Mismatched at element ${this.count}.`
+                );
+              case ZipMismatchMode.SHORTEST:
+                return { value: null, done: true };
+              case ZipMismatchMode.LONGEST:
+              default:
+              // Continue.  The exhausted streams already produced value: null.
+            }
+          }
+          this.count++;
+          return { value: mapped, done: false };
+        }
+        async next() {
+          this.currentPromise = this.nextState(this.currentPromise);
+          return this.currentPromise;
+        }
+      }
+      // Iterators that maintain a ring buffer of pending promises
+      // ============================================================================
+      /**
+       * A stream that prefetches a given number of items from an upstream source,
+       * returning them in FIFO order.
+       *
+       * Note this prefetches Promises, but makes no guarantees about when those
+       * Promises resolve.
+       */
+      class lazy_iterator_PrefetchIterator extends lazy_iterator_LazyIterator {
+        constructor(upstream, bufferSize) {
+          super();
+          this.upstream = upstream;
+          this.bufferSize = bufferSize;
+          this.buffer = new RingBuffer(bufferSize);
+        }
+        summary() {
+          return `${this.upstream.summary()} -> Prefetch`;
+        }
+        /**
+         * Refill the prefetch buffer.  Returns only after the buffer is full, or
+         * the upstream source is exhausted.
+         */
+        refill() {
+          while (!this.buffer.isFull()) {
+            const v = this.upstream.next();
+            this.buffer.push(v);
+          }
+        }
+        next() {
+          this.refill();
+          // This shift will never throw an error because the buffer is always
+          // full after a refill. If the stream is exhausted, the buffer will be
+          // full of Promises that will resolve to the end-of-stream signal.
+          return this.buffer.shift();
+        }
+      }
+      /**
+       * A stream that performs a sliding-window random shuffle on an upstream
+       * source. This is like a `PrefetchIterator` except that the items are
+       * returned in randomized order.  Mixing naturally improves as the buffer
+       * size increases.
+       */
+      class lazy_iterator_ShuffleIterator extends lazy_iterator_PrefetchIterator {
+        constructor(upstream, windowSize, seed) {
+          super(upstream, windowSize);
+          this.upstream = upstream;
+          this.windowSize = windowSize;
+          // Local state that should not be clobbered by out-of-order execution.
+          this.upstreamExhausted = false;
+          this.random = seedrandom["alea"](seed || dist["util"].now().toString());
+          this.lastRead = Promise.resolve({ value: null, done: false });
+        }
+        async next() {
+          // This sets this.lastRead to a new Promise right away, as opposed to
+          // saying `await this.lastRead; this.lastRead = this.serialNext();` which
+          // would not work because this.nextRead would be updated only after the
+          // promise resolves.
+          this.lastRead = this.lastRead.then(() => this.serialNext());
+          return this.lastRead;
+        }
+        randomInt(max) {
+          return Math.floor(this.random() * max);
+        }
+        chooseIndex() {
+          return this.randomInt(this.buffer.length());
+        }
+        async serialNext() {
+          // TODO(soergel): consider performance
+          if (!this.upstreamExhausted) {
+            this.refill();
+          }
+          while (!this.buffer.isEmpty()) {
+            const chosenIndex = this.chooseIndex();
+            const result = await this.buffer.shuffleExcise(chosenIndex);
+            if (result.done) {
+              this.upstreamExhausted = true;
+            } else {
+              this.refill();
+              return result;
+            }
+          }
+          return { value: null, done: true };
+        }
+      }
+      //# sourceMappingURL=lazy_iterator.js.map
+
+      /***/
+    },
+    /* 15 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (Buffer) {
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+          return OperationMapper;
+        });
+        /* unused harmony export decodeBase64 */
+        /* unused harmony export parseStringParam */
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "i", function () {
+          return getStringParam;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+          return getBoolParam;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
+          return getNumberParam;
+        });
+        /* unused harmony export parseDtypeParam */
+        /* unused harmony export getFuncParam */
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
+          return getDtypeParam;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
+          return getDtypeArrayParam;
+        });
+        /* unused harmony export parseTensorShapeParam */
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "k", function () {
+          return getTensorShapeParam;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
+          return getNumericArrayParam;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "h", function () {
+          return getStringArrayParam;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "j", function () {
+          return getTensorShapeArrayParam;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+          return getBoolArrayParam;
+        });
+        /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
+          __webpack_require__(0);
+        /* harmony import */ var _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__ =
+          __webpack_require__(21);
+        /* harmony import */ var _custom_op_register__WEBPACK_IMPORTED_MODULE_2__ =
+          __webpack_require__(24);
+        /* harmony import */ var _executors_utils__WEBPACK_IMPORTED_MODULE_3__ =
+          __webpack_require__(2);
+        /* harmony import */ var _op_list_arithmetic__WEBPACK_IMPORTED_MODULE_4__ =
+          __webpack_require__(41);
+        /* harmony import */ var _op_list_basic_math__WEBPACK_IMPORTED_MODULE_5__ =
+          __webpack_require__(42);
+        /* harmony import */ var _op_list_control__WEBPACK_IMPORTED_MODULE_6__ =
+          __webpack_require__(43);
+        /* harmony import */ var _op_list_convolution__WEBPACK_IMPORTED_MODULE_7__ =
+          __webpack_require__(44);
+        /* harmony import */ var _op_list_creation__WEBPACK_IMPORTED_MODULE_8__ =
+          __webpack_require__(45);
+        /* harmony import */ var _op_list_dynamic__WEBPACK_IMPORTED_MODULE_9__ =
+          __webpack_require__(46);
+        /* harmony import */ var _op_list_evaluation__WEBPACK_IMPORTED_MODULE_10__ =
+          __webpack_require__(47);
+        /* harmony import */ var _op_list_graph__WEBPACK_IMPORTED_MODULE_11__ =
+          __webpack_require__(48);
+        /* harmony import */ var _op_list_image__WEBPACK_IMPORTED_MODULE_12__ =
+          __webpack_require__(49);
+        /* harmony import */ var _op_list_logical__WEBPACK_IMPORTED_MODULE_13__ =
+          __webpack_require__(50);
+        /* harmony import */ var _op_list_matrices__WEBPACK_IMPORTED_MODULE_14__ =
+          __webpack_require__(51);
+        /* harmony import */ var _op_list_normalization__WEBPACK_IMPORTED_MODULE_15__ =
+          __webpack_require__(52);
+        /* harmony import */ var _op_list_reduction__WEBPACK_IMPORTED_MODULE_16__ =
+          __webpack_require__(53);
+        /* harmony import */ var _op_list_slice_join__WEBPACK_IMPORTED_MODULE_17__ =
+          __webpack_require__(54);
+        /* harmony import */ var _op_list_spectral__WEBPACK_IMPORTED_MODULE_18__ =
+          __webpack_require__(55);
+        /* harmony import */ var _op_list_transformation__WEBPACK_IMPORTED_MODULE_19__ =
+          __webpack_require__(56);
+        /**
+         * @license
+         * Copyright 2018 Google LLC. All Rights Reserved.
+         * Licensed under the Apache License, Version 2.0 (the "License");
+         * you may not use this file except in compliance with the License.
+         * You may obtain a copy of the License at
+         *
+         * http://www.apache.org/licenses/LICENSE-2.0
+         *
+         * Unless required by applicable law or agreed to in writing, software
+         * distributed under the License is distributed on an "AS IS" BASIS,
+         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+         * See the License for the specific language governing permissions and
+         * limitations under the License.
+         * =============================================================================
+         */
+
+        class OperationMapper {
+          // Singleton instance for the mapper
+          static get Instance() {
+            return this._instance || (this._instance = new this());
+          }
+          // Loads the op mapping from the JSON file.
+          constructor() {
+            const ops = [
+              _op_list_arithmetic__WEBPACK_IMPORTED_MODULE_4__,
+              _op_list_basic_math__WEBPACK_IMPORTED_MODULE_5__,
+              _op_list_control__WEBPACK_IMPORTED_MODULE_6__,
+              _op_list_convolution__WEBPACK_IMPORTED_MODULE_7__,
+              _op_list_creation__WEBPACK_IMPORTED_MODULE_8__,
+              _op_list_dynamic__WEBPACK_IMPORTED_MODULE_9__,
+              _op_list_evaluation__WEBPACK_IMPORTED_MODULE_10__,
+              _op_list_logical__WEBPACK_IMPORTED_MODULE_13__,
+              _op_list_image__WEBPACK_IMPORTED_MODULE_12__,
+              _op_list_graph__WEBPACK_IMPORTED_MODULE_11__,
+              _op_list_matrices__WEBPACK_IMPORTED_MODULE_14__,
+              _op_list_normalization__WEBPACK_IMPORTED_MODULE_15__,
+              _op_list_reduction__WEBPACK_IMPORTED_MODULE_16__,
+              _op_list_slice_join__WEBPACK_IMPORTED_MODULE_17__,
+              _op_list_spectral__WEBPACK_IMPORTED_MODULE_18__,
+              _op_list_transformation__WEBPACK_IMPORTED_MODULE_19__,
+            ];
+            const mappersJson = [].concat(...ops.map((op) => op.json));
+            this.opMappers = mappersJson.reduce((map, mapper) => {
+              map[mapper.tfOpName] = mapper;
+              return map;
+            }, {});
+          }
+          // Converts the model from Tensorflow GraphDef to local representation for
+          // TensorFlow.js API
+          transformGraph(graph, signature = {}) {
+            const tfNodes = graph.node;
+            const placeholders = [];
+            const weights = [];
+            const nodes = tfNodes.reduce((map, node) => {
+              map[node.name] = this.mapNode(node);
+              if (node.op.startsWith("Placeholder")) {
+                placeholders.push(map[node.name]);
+              }
+              if (node.op === "Const") {
+                weights.push(map[node.name]);
+              }
+              return map;
+            }, {});
+            let inputs = [];
+            const outputs = [];
+            let inputNodeNameToKey = {};
+            let outputNodeNameToKey = {};
+            if (signature != null) {
+              inputNodeNameToKey = this.mapSignatureEntries(signature.inputs);
+              outputNodeNameToKey = this.mapSignatureEntries(signature.outputs);
+            }
+            const allNodes = Object.keys(nodes);
+            allNodes.forEach((key) => {
+              const node = nodes[key];
+              node.inputNames.forEach((name) => {
+                const [nodeName] = Object(
+                  _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
+                )(name);
+                node.inputs.push(nodes[nodeName]);
+                nodes[nodeName].children.push(node);
+              });
+            });
+            // if signature has not outputs set, add any node that does not have
+            // outputs.
+            if (Object.keys(outputNodeNameToKey).length === 0) {
+              allNodes.forEach((key) => {
+                const node = nodes[key];
+                if (node.children.length === 0) {
+                  outputs.push(node);
+                }
+              });
+            } else {
+              Object.keys(outputNodeNameToKey).forEach((name) => {
+                const [nodeName] = Object(
+                  _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
+                )(name);
+                const node = nodes[nodeName];
+                if (node != null) {
+                  node.signatureKey = outputNodeNameToKey[name];
+                  outputs.push(node);
+                }
+              });
+            }
+            if (Object.keys(inputNodeNameToKey).length > 0) {
+              Object.keys(inputNodeNameToKey).forEach((name) => {
+                const [nodeName] = Object(
+                  _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
+                )(name);
+                const node = nodes[nodeName];
+                if (node) {
+                  node.signatureKey = inputNodeNameToKey[name];
+                  inputs.push(node);
+                }
+              });
+            } else {
+              inputs = placeholders;
+            }
+            let functions = {};
+            if (graph.library != null && graph.library.function != null) {
+              functions = graph.library.function.reduce((functions, func) => {
+                functions[func.signature.name] = this.mapFunction(func);
+                return functions;
+              }, {});
+            }
+            return {
+              nodes,
+              inputs,
+              outputs,
+              weights,
+              placeholders,
+              signature,
+              functions,
+            };
+          }
+          mapSignatureEntries(entries) {
+            return Object.keys(entries || {}).reduce((prev, curr) => {
+              prev[entries[curr].name] = curr;
+              return prev;
+            }, {});
+          }
+          mapNode(node) {
+            // Unsupported ops will cause an error at run-time (not parse time), since
+            // they may not be used by the actual execution subgraph.
+            const mapper =
+              Object(_custom_op_register__WEBPACK_IMPORTED_MODULE_2__[/* getRegisteredOp */ "b"])(
+                node.op
+              ) ||
+              this.opMappers[node.op] ||
+              {};
+            if (node.attr == null) {
+              node.attr = {};
+            }
+            const newNode = {
+              name: node.name,
+              op: node.op,
+              category: mapper.category,
+              inputNames: (node.input || []).map((input) =>
+                input.startsWith("^") ? input.substr(1) : input
+              ),
+              inputs: [],
+              children: [],
+              inputParams: {},
+              attrParams: {},
+              rawAttrs: node.attr,
+            };
+            if (mapper.inputs != null) {
+              newNode.inputParams = mapper.inputs.reduce((map, param) => {
+                map[param.name] = {
+                  type: param.type,
+                  inputIndexStart: param.start,
+                  inputIndexEnd: param.end,
+                };
+                return map;
+              }, {});
+            }
+            if (mapper.attrs != null) {
+              newNode.attrParams = mapper.attrs.reduce((map, param) => {
+                const type = param.type;
+                let value = undefined;
+                switch (param.type) {
+                  case "string":
+                    value = getStringParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getStringParam(node.attr, param.tfDeprecatedName, param.defaultValue);
+                    }
+                    break;
+                  case "string[]":
+                    value = getStringArrayParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getStringArrayParam(
+                        node.attr,
+                        param.tfDeprecatedName,
+                        param.defaultValue
+                      );
+                    }
+                    break;
+                  case "number":
+                    value = getNumberParam(node.attr, param.tfName, param.defaultValue || 0);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getNumberParam(node.attr, param.tfDeprecatedName, param.defaultValue);
+                    }
+                    break;
+                  case "number[]":
+                    value = getNumericArrayParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getNumericArrayParam(
+                        node.attr,
+                        param.tfDeprecatedName,
+                        param.defaultValue
+                      );
+                    }
+                    break;
+                  case "bool":
+                    value = getBoolParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getBoolParam(node.attr, param.tfDeprecatedName, param.defaultValue);
+                    }
+                    break;
+                  case "bool[]":
+                    value = getBoolArrayParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getBoolArrayParam(
+                        node.attr,
+                        param.tfDeprecatedName,
+                        param.defaultValue
+                      );
+                    }
+                    break;
+                  case "shape":
+                    value = getTensorShapeParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getTensorShapeParam(
+                        node.attr,
+                        param.tfDeprecatedName,
+                        param.defaultValue
+                      );
+                    }
+                    break;
+                  case "shape[]":
+                    value = getTensorShapeArrayParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getTensorShapeArrayParam(
+                        node.attr,
+                        param.tfDeprecatedName,
+                        param.defaultValue
+                      );
+                    }
+                    break;
+                  case "dtype":
+                    value = getDtypeParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getDtypeParam(node.attr, param.tfDeprecatedName, param.defaultValue);
+                    }
+                    break;
+                  case "dtype[]":
+                    value = getDtypeArrayParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getDtypeArrayParam(
+                        node.attr,
+                        param.tfDeprecatedName,
+                        param.defaultValue
+                      );
+                    }
+                    break;
+                  case "func":
+                    value = getFuncParam(node.attr, param.tfName, param.defaultValue);
+                    if (value === undefined && !!param.tfDeprecatedName) {
+                      value = getFuncParam(node.attr, param.tfDeprecatedName, param.defaultValue);
+                    }
+                    break;
+                  case "tensor":
+                  case "tensors":
+                    break;
+                  default:
+                    throw new Error(`Unsupported param type: ${param.type} for op: ${node.op}`);
+                }
+                map[param.name] = { value, type };
+                return map;
+              }, {});
+            }
+            return newNode;
+          }
+          // map the TFunctionDef to TFJS graph object
+          mapFunction(functionDef) {
+            const tfNodes = functionDef.nodeDef;
+            const placeholders = [];
+            const weights = [];
+            let nodes = {};
+            if (tfNodes != null) {
+              nodes = tfNodes.reduce((map, node) => {
+                map[node.name] = this.mapNode(node);
+                if (node.op === "Const") {
+                  weights.push(map[node.name]);
+                }
+                return map;
+              }, {});
+            }
+            const inputs = [];
+            const outputs = [];
+            functionDef.signature.inputArg.forEach((arg) => {
+              const [nodeName] = Object(
+                _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
+              )(arg.name);
+              const node = {
+                name: nodeName,
+                op: "Placeholder",
+                inputs: [],
+                inputNames: [],
+                category: "graph",
+                inputParams: {},
+                attrParams: { dtype: { value: parseDtypeParam(arg.type), type: "dtype" } },
+                children: [],
+              };
+              node.signatureKey = arg.name;
+              inputs.push(node);
+              nodes[nodeName] = node;
+            });
+            const allNodes = Object.keys(nodes);
+            allNodes.forEach((key) => {
+              const node = nodes[key];
+              node.inputNames.forEach((name) => {
+                const [nodeName] = Object(
+                  _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
+                )(name);
+                node.inputs.push(nodes[nodeName]);
+                nodes[nodeName].children.push(node);
+              });
+            });
+            const returnNodeMap = functionDef.ret;
+            functionDef.signature.outputArg.forEach((output) => {
+              const [nodeName, index] = Object(
+                _executors_utils__WEBPACK_IMPORTED_MODULE_3__[/* getNodeNameAndIndex */ "a"]
+              )(returnNodeMap[output.name]);
+              const node = nodes[nodeName];
+              if (node != null) {
+                node.defaultOutput = index;
+                outputs.push(node);
+              }
+            });
+            const signature = this.mapArgsToSignature(functionDef);
+            return { nodes, inputs, outputs, weights, placeholders, signature };
+          }
+          mapArgsToSignature(functionDef) {
+            return {
+              methodName: functionDef.signature.name,
+              inputs: functionDef.signature.inputArg.reduce((map, arg) => {
+                map[arg.name] = this.mapArgToTensorInfo(arg);
+                return map;
+              }, {}),
+              outputs: functionDef.signature.outputArg.reduce((map, arg) => {
+                map[arg.name] = this.mapArgToTensorInfo(arg, functionDef.ret);
+                return map;
+              }, {}),
+            };
+          }
+          mapArgToTensorInfo(arg, nameMap) {
+            let name = arg.name;
+            if (nameMap != null) {
+              name = nameMap[name];
+            }
+            return { name, dtype: arg.type };
+          }
+        }
+        function decodeBase64(text) {
+          const global = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["env"])().global;
+          if (typeof global.atob !== "undefined") {
+            return global.atob(text);
+          } else if (typeof Buffer !== "undefined") {
+            return new Buffer(text, "base64").toString();
+          } else {
+            throw new Error(
+              "Unable to decode base64 in this environment. " +
+                "Missing built-in atob() or Buffer()"
+            );
+          }
+        }
+        function parseStringParam(s, keepCase) {
+          const value = Array.isArray(s) ? String.fromCharCode.apply(null, s) : decodeBase64(s);
+          return keepCase ? value : value.toLowerCase();
+        }
+        function getStringParam(attrs, name, def, keepCase = false) {
+          const param = attrs[name];
+          if (param != null) {
+            return parseStringParam(param.s, keepCase);
+          }
+          return def;
+        }
+        function getBoolParam(attrs, name, def) {
+          const param = attrs[name];
+          return param ? param.b : def;
+        }
+        function getNumberParam(attrs, name, def) {
+          const param = attrs[name] || {};
+          const value = param["i"] != null ? param["i"] : param["f"] != null ? param["f"] : def;
+          return typeof value === "number" ? value : parseInt(value, 10);
+        }
+        function parseDtypeParam(value) {
+          if (typeof value === "string") {
+            // tslint:disable-next-line:no-any
+            value = _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"][value];
+          }
+          switch (value) {
+            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_FLOAT:
+              return "float32";
+            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_INT32:
+            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_INT64:
+            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_INT8:
+            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_UINT8:
+              return "int32";
+            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_BOOL:
+              return "bool";
+            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_DOUBLE:
+              return "float32";
+            case _data_compiled_api__WEBPACK_IMPORTED_MODULE_1__[/* DataType */ "a"].DT_STRING:
+              return "string";
+            default:
+              // Unknown dtype error will happen at runtime (instead of parse time),
+              // since these nodes might not be used by the actual subgraph execution.
+              return null;
+          }
+        }
+        function getFuncParam(attrs, name, def) {
+          const param = attrs[name];
+          if (param && param.func) {
+            return param.func.name;
+          }
+          return def;
+        }
+        function getDtypeParam(attrs, name, def) {
+          const param = attrs[name];
+          if (param && param.type) {
+            return parseDtypeParam(param.type);
+          }
+          return def;
+        }
+        function getDtypeArrayParam(attrs, name, def) {
+          const param = attrs[name];
+          if (param && param.list && param.list.type) {
+            return param.list.type.map((v) => parseDtypeParam(v));
+          }
+          return def;
+        }
+        function parseTensorShapeParam(shape) {
+          if (shape.unknownRank) {
+            return undefined;
+          }
+          if (shape.dim != null) {
+            return shape.dim.map((dim) =>
+              typeof dim.size === "number" ? dim.size : parseInt(dim.size, 10)
+            );
+          }
+          return [];
+        }
+        function getTensorShapeParam(attrs, name, def) {
+          const param = attrs[name];
+          if (param && param.shape) {
+            return parseTensorShapeParam(param.shape);
+          }
+          return def;
+        }
+        function getNumericArrayParam(attrs, name, def) {
+          const param = attrs[name];
+          if (param) {
+            return ((param.list.f && param.list.f.length ? param.list.f : param.list.i) || []).map(
+              (v) => (typeof v === "number" ? v : parseInt(v, 10))
+            );
+          }
+          return def;
+        }
+        function getStringArrayParam(attrs, name, def, keepCase = false) {
+          const param = attrs[name];
+          if (param && param.list && param.list.s) {
+            return param.list.s.map((v) => {
+              return parseStringParam(v, keepCase);
+            });
+          }
+          return def;
+        }
+        function getTensorShapeArrayParam(attrs, name, def) {
+          const param = attrs[name];
+          if (param && param.list && param.list.shape) {
+            return param.list.shape.map((v) => {
+              return parseTensorShapeParam(v);
+            });
+          }
+          return def;
+        }
+        function getBoolArrayParam(attrs, name, def) {
+          const param = attrs[name];
+          if (param && param.list && param.list.b) {
+            return param.list.b;
+          }
+          return def;
+        }
+        //# sourceMappingURL=operation_mapper.js.map
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(39).Buffer));
+
+      /***/
+    },
+    /* 16 */
+    /***/ function (module, exports) {
+      module.exports = function () {
+        throw new Error("define cannot be used indirect");
+      };
+
+      /***/
+    },
+    /* 17 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return getKernel;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return getGradient;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return getKernelsForBackend;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
+        return registerKernel;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
+        return registerGradient;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "g", function () {
+        return unregisterKernel;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
+        return unregisterGradient;
+      });
+      /* harmony import */ var _global_util__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(33);
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const kernelRegistry = Object(_global_util__WEBPACK_IMPORTED_MODULE_0__[/* getGlobal */ "a"])(
+        "kernelRegistry",
+        () => new Map()
+      );
+      const gradRegistry = Object(_global_util__WEBPACK_IMPORTED_MODULE_0__[/* getGlobal */ "a"])(
+        "gradRegistry",
+        () => new Map()
+      );
+      /**
+       * Returns the kernel function (code) associated with the provided names.
+       *
+       * @param kernelName The official name of the kernel.
+       * @param backendName The official name of the backend.
+       */
+      function getKernel(kernelName, backendName) {
+        const key = makeKey(kernelName, backendName);
+        return kernelRegistry.get(key);
+      }
+      /**
+       * Returns the registered gradient info associated with the provided kernel.
+       * @param kernelName The official TF kernel name.
+       */
+      function getGradient(kernelName) {
+        return gradRegistry.get(kernelName);
+      }
+      function getKernelsForBackend(backendName) {
+        const it = kernelRegistry.entries();
+        const result = [];
+        while (true) {
+          const { done, value } = it.next();
+          if (done) {
+            break;
+          }
+          const [key, config] = value;
+          const [backend] = key.split("_");
+          if (backend === backendName) {
+            result.push(config);
+          }
+        }
+        return result;
+      }
+      /**
+       * Registers the function (forward pass) for the kernel in a global registry.
+       *
+       * @param config A config object with the following properties:
+       * - `kernelName` The official name of the kernel.
+       * - `backendName` The official name of the backend.
+       * - `kernelFunc` The function to run during the forward pass of the kernel.
+       * - `setupFunc` Optional. Gets called once, after the backend initializes.
+       * - `disposeFunc` Optional. Gets called once, right before the backend is
+       * disposed.
+       */
+      function registerKernel(config) {
+        const { kernelName, backendName } = config;
+        const key = makeKey(kernelName, backendName);
+        if (kernelRegistry.has(key)) {
+          console.warn(
+            `The kernel '${kernelName}' for backend ` + `'${backendName}' is already registered`
+          );
+        }
+        kernelRegistry.set(key, config);
+      }
+      /**
+       * Registers a gradient function for a given kernel in the global registry,
+       * to be used during the back-propagation of that kernel.
+       *
+       * @param config An object with the following properties:
+       * - `kernelName` The name of the kernel that the gradient function is for.
+       * - `gradFunc` The function to run during back-propagation.
+       */
+      function registerGradient(config) {
+        const { kernelName } = config;
+        if (gradRegistry.has(kernelName)) {
+          console.warn(`Overriding the gradient for '${kernelName}'`);
+        }
+        gradRegistry.set(kernelName, config);
+      }
+      /**
+       * Removes the kernel function from the registry.
+       *
+       * @param kernelName The official name of the kernel.
+       * @param backendName The official name of the backend.
+       *
+       */
+      function unregisterKernel(kernelName, backendName) {
+        const key = makeKey(kernelName, backendName);
+        if (!kernelRegistry.has(key)) {
+          throw new Error(
+            `The kernel '${kernelName}' for backend ` + `'${backendName}' is not registered`
+          );
+        }
+        kernelRegistry.delete(key);
+      }
+      /** Removes the registered gradient from the global registry. */
+      function unregisterGradient(kernelName) {
+        if (!gradRegistry.has(kernelName)) {
+          throw new Error(`The gradient '${kernelName}' for backend is not registered`);
+        }
+        gradRegistry.delete(kernelName);
+      }
+      function makeKey(kernelName, backendName) {
+        return `${backendName}_${kernelName}`;
+      }
+      //# sourceMappingURL=kernel_registry.js.map
+
+      /***/
+    },
+    /* 18 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return complex;
+      });
+      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
+      /* harmony import */ var _kernel_names__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(6);
+      /* harmony import */ var _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__ =
+        __webpack_require__(3);
+      /* harmony import */ var _util__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(1);
+      /* harmony import */ var _operation__WEBPACK_IMPORTED_MODULE_4__ = __webpack_require__(4);
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Converts two real numbers to a complex number.
+       *
+       * Given a tensor `real` representing the real part of a complex number, and a
+       * tensor `imag` representing the imaginary part of a complex number, this
+       * operation returns complex numbers elementwise of the form [r0, i0, r1, i1],
+       * where r represents the real part and i represents the imag part.
+       *
+       * The input tensors real and imag must have the same shape.
+       *
+       * ```js
+       * const real = tf.tensor1d([2.25, 3.25]);
+       * const imag = tf.tensor1d([4.75, 5.75]);
+       * const complex = tf.complex(real, imag);
+       *
+       * complex.print();
+       * ```
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function complex_(real, imag) {
+        const $real = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"]
+        )(real, "real", "complex");
+        const $imag = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"]
+        )(imag, "imag", "complex");
+        _util__WEBPACK_IMPORTED_MODULE_3__["assertShapesMatch"](
+          $real.shape,
+          $imag.shape,
+          `real and imag shapes, ${$real.shape} and ${$imag.shape}, ` +
+            `must match in call to tf.complex().`
+        );
+        const forward = (backend) => {
+          return backend.complex($real, $imag);
+        };
+        const inputs = { real: $real, imag: $imag };
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          _kernel_names__WEBPACK_IMPORTED_MODULE_1__[/* Complex */ "k"]
+        );
+      }
+      const complex = Object(_operation__WEBPACK_IMPORTED_MODULE_4__[/* op */ "a"])({ complex_ });
+      //# sourceMappingURL=complex.js.map
+
+      /***/
+    },
+    /* 19 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return deepMap;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "d", function () {
+        return deepZip;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "f", function () {
+        return zipToList;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return deepMapAndAwaitAll;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "e", function () {
+        return isIterable;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return canTensorify;
+      });
+      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
+        __webpack_require__(0);
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      /**
+       * Apply a mapping function to a nested structure in a recursive manner.
+       *
+       * The result of the mapping is an object with the same nested structure (i.e.,
+       * of arrays and dicts) as the input, except that some subtrees are replaced,
+       * according to the results of the mapping function.
+       *
+       * Mappings are memoized.  Thus, if the nested structure contains the same
+       * object in multiple positions, the output will contain the same mapped object
+       * in those positions.  Cycles are not supported, however.
+       *
+       * @param input: The object to which to apply the mapping function.
+       * @param mapFn: A function that expects a single node of the object tree, and
+       *   returns a `DeepMapResult`.  The `DeepMapResult` either provides a
+       *   replacement value for that node (i.e., replacing the subtree), or indicates
+       *   that the node should be processed recursively.
+       */
+      function deepMap(input, mapFn) {
+        return deepMapInternal(input, mapFn);
+      }
+      /**
+       * @param seen: A Map of known object mappings (i.e., memoized results of
+       *   `mapFn()`)
+       * @param containedIn: An set containing objects on the reference path currently
+       *   being processed (used to detect cycles).
+       */
+      function deepMapInternal(input, mapFn, seen = new Map(), containedIn = new Set()) {
+        if (input == null) {
+          return null;
+        }
+        if (containedIn.has(input)) {
+          throw new Error("Circular references are not supported.");
+        }
+        if (seen.has(input)) {
+          return seen.get(input);
+        }
+        const result = mapFn(input);
+        if (result.recurse && result.value !== null) {
+          throw new Error("A deep map function may not return both a value and recurse=true.");
+        }
+        if (!result.recurse) {
+          seen.set(input, result.value);
+          return result.value;
+        } else if (isIterable(input)) {
+          // tslint:disable-next-line:no-any
+          const mappedIterable = Array.isArray(input) ? [] : {};
+          containedIn.add(input);
+          for (const k in input) {
+            const child = input[k];
+            const childResult = deepMapInternal(child, mapFn, seen, containedIn);
+            mappedIterable[k] = childResult;
+          }
+          containedIn.delete(input);
+          return mappedIterable;
+        } else {
+          throw new Error(`Can't recurse into non-iterable type: ${input}`);
+        }
+      }
+      // TODO(soergel, kangyizhang) Reconsider naming of deepZip() to avoid confusion
+      // with zip()
+      /**
+       * Zip nested structures together in a recursive manner.
+       *
+       * This has the effect of transposing or pivoting data, e.g. converting it from
+       * a row-major representation to a column-major representation.
+       *
+       * For example, `deepZip([{a: 1, b: 2}, {a: 3, b: 4}])` returns
+       * `{a: [1, 3], b: [2, 4]}`.
+       *
+       * The inputs should all have the same nested structure (i.e., of arrays and
+       * dicts).  The result is a single object with the same nested structure, where
+       * the leaves are arrays collecting the values of the inputs at that location
+       * (or, optionally, the result of a custom function applied to those arrays).
+       *
+       * @param inputs: An array of the objects to zip together.
+       * @param zipFn: (optional) A function that expects an array of elements at a
+       *   single node of the object tree, and returns a `DeepMapResult`.  The
+       *   `DeepMapResult` either provides a result value for that node (i.e.,
+       *   representing the subtree), or indicates that the node should be processed
+       *   recursively.  The default zipFn recurses as far as possible and places
+       *   arrays at the leaves.
+       */
+      function deepZip(inputs, zipFn = zipToList) {
+        return deepZipInternal(inputs, zipFn);
+      }
+      /**
+       * @param containedIn: An set containing objects on the reference path currently
+       *   being processed (used to detect cycles).
+       */
+      function deepZipInternal(inputs, zipFn, containedIn = new Set()) {
+        // The recursion follows the structure of input 0; it's assumed that all the
+        // other inputs have the same structure.
+        const input = inputs[0];
+        if (containedIn.has(input)) {
+          throw new Error("Circular references are not supported.");
+        }
+        const result = zipFn(inputs);
+        if (result.recurse && result.value !== null) {
+          throw new Error("A deep zip function may not return both a value and recurse=true.");
+        }
+        if (!result.recurse) {
+          return result.value;
+        } else if (isIterable(input)) {
+          // tslint:disable-next-line:no-any
+          const mappedIterable = Array.isArray(input) ? [] : {};
+          containedIn.add(input);
+          for (const k in input) {
+            const children = inputs.map((x) => x[k]);
+            const childResult = deepZipInternal(children, zipFn, containedIn);
+            mappedIterable[k] = childResult;
+          }
+          containedIn.delete(input);
+          return mappedIterable;
+        } else {
+          throw new Error(`Can't recurse into non-iterable type: ${input}`);
+        }
+      }
+      // tslint:disable-next-line:no-any
+      function zipToList(x) {
+        if (x === null) {
+          return null;
+        }
+        // TODO(soergel): validate array type?
+        if (isIterable(x[0])) {
+          return { value: null, recurse: true };
+        } else {
+          return { value: x, recurse: false };
+        }
+      }
+      /**
+       * Apply an async mapping function to a nested structure in a recursive manner.
+       *
+       * This first creates a nested structure of Promises, and then awaits all of
+       * those, resulting in a single Promise for a resolved nested structure.
+       *
+       * The result of the mapping is an object with the same nested structure (i.e.,
+       * of arrays and dicts) as the input, except that some subtrees are replaced,
+       * according to the results of the mapping function.
+       *
+       * Mappings are memoized.  Thus, if the nested structure contains the same
+       * object in multiple positions, the output will contain the same mapped object
+       * in those positions.  Cycles are not supported, however.
+       *
+       * @param input: The object to which to apply the mapping function.
+       * @param mapFn: A function that expects a single node of the object tree, and
+       *   returns a `DeepMapAsyncResult`.  The `DeepMapAsyncResult` either provides
+       *   a `Promise` for a replacement value for that node (i.e., replacing the
+       *   subtree), or indicates that the node should be processed recursively.  Note
+       *   that the decision whether or not to recurse must be made immediately; only
+       *   the mapped value may be promised.
+       */
+      async function deepMapAndAwaitAll(input, mapFn) {
+        const seen = new Map();
+        // First do a normal deepMap, collecting Promises in 'seen' as a side effect.
+        deepMapInternal(input, mapFn, seen);
+        // Replace the Promises in 'seen' in place.
+        // Note TypeScript provides no async map iteration, and regular map iteration
+        // is broken too, so sadly we have to do Array.from() to make it work.
+        // (There's no advantage to Promise.all(), and that would be tricky anyway.)
+        for (const key of Array.from(seen.keys())) {
+          const value = seen.get(key);
+          if (value instanceof Promise) {
+            const mappedValue = await value;
+            seen.set(key, mappedValue);
+          }
+        }
+        // Normal deepMap again, this time filling in the resolved values.
+        // It's unfortunate that we have to do two passes.
+        // TODO(soergel): test performance and think harder about a fast solution.
+        const result = deepMapInternal(input, mapFn, seen);
+        return result;
+      }
+      /**
+       * Determine whether the argument is iterable.
+       *
+       * @returns true if the argument is an array or any non-Tensor object.
+       */
+      // tslint:disable-next-line:no-any
+      function isIterable(obj) {
+        return (
+          obj != null &&
+          !ArrayBuffer.isView(obj) &&
+          (Array.isArray(obj) ||
+            (typeof obj === "object" &&
+              !(obj instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"])))
+        );
+      }
+      /**
+       * Determine whether the argument can be converted to Tensor.
+       *
+       * Tensors, primitives, arrays, and TypedArrays all qualify; anything else does
+       * not.
+       *
+       * @returns true if the argument can be converted to Tensor.
+       */
+      // tslint:disable-next-line:no-any
+      function canTensorify(obj) {
+        return (
+          obj == null ||
+          isPrimitive(obj) ||
+          Array.isArray(obj) ||
+          (typeof obj === "object" &&
+            obj instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]) ||
+          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].isTypedArray(obj)
+        );
+      }
+      /**
+       * Returns true if the given `value` is a primitive type. Otherwise returns
+       * false. This is equivalant to node util.isPrimitive
+       */
+      function isPrimitive(value) {
+        return value === null || (typeof value !== "object" && typeof value !== "function");
+      }
+      //# sourceMappingURL=deep_map.js.map
+
+      /***/
+    },
+    /* 20 */
+    /***/ function (module, exports, __webpack_require__) {
+      // A library of seedable RNGs implemented in Javascript.
+      //
+      // Usage:
+      //
+      // var seedrandom = require('seedrandom');
+      // var random = seedrandom(1); // or any seed.
+      // var x = random();       // 0 <= x < 1.  Every bit is random.
+      // var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.
+
+      // alea, a 53-bit multiply-with-carry generator by Johannes Baagøe.
+      // Period: ~2^116
+      // Reported to pass all BigCrush tests.
+      var alea = __webpack_require__(68);
+
+      // xor128, a pure xor-shift generator by George Marsaglia.
+      // Period: 2^128-1.
+      // Reported to fail: MatrixRank and LinearComp.
+      var xor128 = __webpack_require__(69);
+
+      // xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.
+      // Period: 2^192-2^32
+      // Reported to fail: CollisionOver, SimpPoker, and LinearComp.
+      var xorwow = __webpack_require__(70);
+
+      // xorshift7, by François Panneton and Pierre L'ecuyer, takes
+      // a different approach: it adds robustness by allowing more shifts
+      // than Marsaglia's original three.  It is a 7-shift generator
+      // with 256 bits, that passes BigCrush with no systmatic failures.
+      // Period 2^256-1.
+      // No systematic BigCrush failures reported.
+      var xorshift7 = __webpack_require__(71);
+
+      // xor4096, by Richard Brent, is a 4096-bit xor-shift with a
+      // very long period that also adds a Weyl generator. It also passes
+      // BigCrush with no systematic failures.  Its long period may
+      // be useful if you have many generators and need to avoid
+      // collisions.
+      // Period: 2^4128-2^32.
+      // No systematic BigCrush failures reported.
+      var xor4096 = __webpack_require__(72);
+
+      // Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random
+      // number generator derived from ChaCha, a modern stream cipher.
+      // https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf
+      // Period: ~2^127
+      // No systematic BigCrush failures reported.
+      var tychei = __webpack_require__(73);
+
+      // The original ARC4-based prng included in this library.
+      // Period: ~2^1600
+      var sr = __webpack_require__(74);
+
+      sr.alea = alea;
+      sr.xor128 = xor128;
+      sr.xorwow = xorwow;
+      sr.xorshift7 = xorshift7;
+      sr.xor4096 = xor4096;
+      sr.tychei = tychei;
+
+      module.exports = sr;
+
+      /***/
+    },
+    /* 21 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return DataType;
+      });
+      /* unused harmony export SaverDef */
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+      /** DataType enum. */
+      var DataType;
+      (function (DataType) {
+        DataType[(DataType["DT_INVALID"] = 0)] = "DT_INVALID";
+        DataType[(DataType["DT_FLOAT"] = 1)] = "DT_FLOAT";
+        DataType[(DataType["DT_DOUBLE"] = 2)] = "DT_DOUBLE";
+        DataType[(DataType["DT_INT32"] = 3)] = "DT_INT32";
+        DataType[(DataType["DT_UINT8"] = 4)] = "DT_UINT8";
+        DataType[(DataType["DT_INT16"] = 5)] = "DT_INT16";
+        DataType[(DataType["DT_INT8"] = 6)] = "DT_INT8";
+        DataType[(DataType["DT_STRING"] = 7)] = "DT_STRING";
+        DataType[(DataType["DT_COMPLEX64"] = 8)] = "DT_COMPLEX64";
+        DataType[(DataType["DT_INT64"] = 9)] = "DT_INT64";
+        DataType[(DataType["DT_BOOL"] = 10)] = "DT_BOOL";
+        DataType[(DataType["DT_QINT8"] = 11)] = "DT_QINT8";
+        DataType[(DataType["DT_QUINT8"] = 12)] = "DT_QUINT8";
+        DataType[(DataType["DT_QINT32"] = 13)] = "DT_QINT32";
+        DataType[(DataType["DT_BFLOAT16"] = 14)] = "DT_BFLOAT16";
+        DataType[(DataType["DT_FLOAT_REF"] = 101)] = "DT_FLOAT_REF";
+        DataType[(DataType["DT_DOUBLE_REF"] = 102)] = "DT_DOUBLE_REF";
+        DataType[(DataType["DT_INT32_REF"] = 103)] = "DT_INT32_REF";
+        DataType[(DataType["DT_UINT8_REF"] = 104)] = "DT_UINT8_REF";
+        DataType[(DataType["DT_INT16_REF"] = 105)] = "DT_INT16_REF";
+        DataType[(DataType["DT_INT8_REF"] = 106)] = "DT_INT8_REF";
+        DataType[(DataType["DT_STRING_REF"] = 107)] = "DT_STRING_REF";
+        DataType[(DataType["DT_COMPLEX64_REF"] = 108)] = "DT_COMPLEX64_REF";
+        DataType[(DataType["DT_INT64_REF"] = 109)] = "DT_INT64_REF";
+        DataType[(DataType["DT_BOOL_REF"] = 110)] = "DT_BOOL_REF";
+        DataType[(DataType["DT_QINT8_REF"] = 111)] = "DT_QINT8_REF";
+        DataType[(DataType["DT_QUINT8_REF"] = 112)] = "DT_QUINT8_REF";
+        DataType[(DataType["DT_QINT32_REF"] = 113)] = "DT_QINT32_REF";
+        DataType[(DataType["DT_BFLOAT16_REF"] = 114)] = "DT_BFLOAT16_REF";
+      })(DataType || (DataType = {}));
+      var SaverDef;
+      (function (SaverDef) {
+        /** CheckpointFormatVersion enum. */
+        let CheckpointFormatVersion;
+        (function (CheckpointFormatVersion) {
+          CheckpointFormatVersion[(CheckpointFormatVersion["LEGACY"] = 0)] = "LEGACY";
+          CheckpointFormatVersion[(CheckpointFormatVersion["V1"] = 1)] = "V1";
+          CheckpointFormatVersion[(CheckpointFormatVersion["V2"] = 2)] = "V2";
+        })(
+          (CheckpointFormatVersion =
+            SaverDef.CheckpointFormatVersion || (SaverDef.CheckpointFormatVersion = {}))
+        );
+      })(SaverDef || (SaverDef = {}));
+      //# sourceMappingURL=compiled_api.js.map
+
+      /***/
+    },
+    /* 22 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return real;
+      });
+      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
+      /* harmony import */ var _kernel_names__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(6);
+      /* harmony import */ var _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__ =
+        __webpack_require__(3);
+      /* harmony import */ var _operation__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(4);
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the real part of a complex (or real) tensor.
+       *
+       * Given a tensor input, this operation returns a tensor of type float that is
+       * the real part of each element in input considered as a complex number.
+       *
+       * If the input is real, it simply makes a clone.
+       *
+       * ```js
+       * const x = tf.complex([-2.25, 3.25], [4.75, 5.75]);
+       * tf.real(x).print();
+       * ```
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function real_(input) {
+        const $input = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"]
+        )(input, "input", "real");
+        const forward = (backend) => {
+          return backend.real($input);
+        };
+        const inputs = { input: $input };
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          _kernel_names__WEBPACK_IMPORTED_MODULE_1__[/* Real */ "hb"]
+        );
+      }
+      const real = Object(_operation__WEBPACK_IMPORTED_MODULE_3__[/* op */ "a"])({ real_ });
+      //# sourceMappingURL=real.js.map
+
+      /***/
+    },
+    /* 23 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return Rank;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return upcastType;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return sumOutType;
+      });
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      var Rank;
+      (function (Rank) {
+        Rank["R0"] = "R0";
+        Rank["R1"] = "R1";
+        Rank["R2"] = "R2";
+        Rank["R3"] = "R3";
+        Rank["R4"] = "R4";
+        Rank["R5"] = "R5";
+        Rank["R6"] = "R6";
+      })(Rank || (Rank = {}));
+      // Looks for upcasting types. Used, for example, in operations with mixed dtype
+      // inputs.
+      var UpcastInt32AndMap;
+      (function (UpcastInt32AndMap) {
+        UpcastInt32AndMap["float32"] = "float32";
+        UpcastInt32AndMap["int32"] = "int32";
+        UpcastInt32AndMap["bool"] = "int32";
+        UpcastInt32AndMap["complex64"] = "complex64";
+      })(UpcastInt32AndMap || (UpcastInt32AndMap = {}));
+      var UpcastBoolAndMap;
+      (function (UpcastBoolAndMap) {
+        UpcastBoolAndMap["float32"] = "float32";
+        UpcastBoolAndMap["int32"] = "int32";
+        UpcastBoolAndMap["bool"] = "bool";
+        UpcastBoolAndMap["complex64"] = "complex64";
+      })(UpcastBoolAndMap || (UpcastBoolAndMap = {}));
+      var UpcastFloat32AndMap;
+      (function (UpcastFloat32AndMap) {
+        UpcastFloat32AndMap["float32"] = "float32";
+        UpcastFloat32AndMap["int32"] = "float32";
+        UpcastFloat32AndMap["bool"] = "float32";
+        UpcastFloat32AndMap["complex64"] = "complex64";
+      })(UpcastFloat32AndMap || (UpcastFloat32AndMap = {}));
+      var UpcastComplex64AndMap;
+      (function (UpcastComplex64AndMap) {
+        UpcastComplex64AndMap["float32"] = "complex64";
+        UpcastComplex64AndMap["int32"] = "complex64";
+        UpcastComplex64AndMap["bool"] = "complex64";
+        UpcastComplex64AndMap["complex64"] = "complex64";
+      })(UpcastComplex64AndMap || (UpcastComplex64AndMap = {}));
+      const upcastTypeMap = {
+        float32: UpcastFloat32AndMap,
+        int32: UpcastInt32AndMap,
+        bool: UpcastBoolAndMap,
+        complex64: UpcastComplex64AndMap,
+      };
+      function upcastType(typeA, typeB) {
+        if (typeA === "string" || typeB === "string") {
+          if (typeA === "string" && typeB === "string") {
+            return "string";
+          }
+          throw new Error(`Can not upcast ${typeA} with ${typeB}`);
+        }
+        return upcastTypeMap[typeA][typeB];
+      }
+      /** Returns the output type after summation. */
+      function sumOutType(type) {
+        return upcastType(type, "int32");
+      }
+      //# sourceMappingURL=types.js.map
+
+      /***/
+    },
+    /* 24 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "c", function () {
+        return registerOp;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return getRegisteredOp;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return deregisterOp;
+      });
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const CUSTOM_OPS = {};
+      /**
+       * Register an Op for graph model executor. This allow you to register
+       * TensorFlow custom op or override existing op.
+       *
+       * Here is an example of registering a new MatMul Op.
+       * ```js
+       * const customMatmul = (node) =>
+       *    tf.matMul(
+       *        node.inputs[0], node.inputs[1],
+       *        node.attrs['transpose_a'], node.attrs['transpose_b']);
+       *
+       * tf.registerOp('MatMul', customMatmul);
+       * ```
+       * The inputs and attrs of the node object is based on the TensorFlow op
+       * registry.
+       *
+       * @param name The Tensorflow Op name.
+       * @param opFunc An op function which is called with the current graph node
+       * during execution and needs to return a tensor or a list of tensors. The node
+       * has the following attributes:
+       *    - attr: A map from attribute name to its value
+       *    - inputs: A list of input tensors
+       */
+      /** @doc {heading: 'Models', subheading: 'Op Registry'} */
+      function registerOp(name, opFunc) {
+        const opMapper = {
+          tfOpName: name,
+          category: "custom",
+          inputs: [],
+          attrs: [],
+          customExecutor: opFunc,
+        };
+        CUSTOM_OPS[name] = opMapper;
+      }
+      /**
+       * Retrieve the OpMapper object for the registered op.
+       *
+       * @param name The Tensorflow Op name.
+       */
+      /** @doc {heading: 'Models', subheading: 'Op Registry'} */
+      function getRegisteredOp(name) {
+        return CUSTOM_OPS[name];
+      }
+      /**
+       * Deregister the Op for graph model executor.
+       *
+       * @param name The Tensorflow Op name.
+       */
+      /** @doc {heading: 'Models', subheading: 'Op Registry'} */
+      function deregisterOp(name) {
+        delete CUSTOM_OPS[name];
+      }
+      //# sourceMappingURL=register.js.map
+
+      /***/
+    },
+    /* 25 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return imag;
+      });
+      /* harmony import */ var _engine__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(5);
+      /* harmony import */ var _kernel_names__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(6);
+      /* harmony import */ var _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__ =
+        __webpack_require__(3);
+      /* harmony import */ var _operation__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(4);
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Returns the imaginary part of a complex (or real) tensor.
+       *
+       * Given a tensor input, this operation returns a tensor of type float that is
+       * the imaginary part of each element in input considered as a complex number.
+       * If input is real, a tensor of all zeros is returned.
+       *
+       * ```js
+       * const x = tf.complex([-2.25, 3.25], [4.75, 5.75]);
+       * tf.imag(x).print();
+       * ```
+       */
+      /** @doc {heading: 'Tensors', subheading: 'Creation'} */
+      function imag_(input) {
+        const $input = Object(
+          _tensor_util_env__WEBPACK_IMPORTED_MODULE_2__[/* convertToTensor */ "a"]
+        )(input, "input", "imag");
+        const forward = (backend) => {
+          return backend.imag($input);
+        };
+        const inputs = { input: $input };
+        return _engine__WEBPACK_IMPORTED_MODULE_0__[/* ENGINE */ "a"].runKernelFunc(
+          forward,
+          inputs,
+          null /* gradient */,
+          _kernel_names__WEBPACK_IMPORTED_MODULE_1__[/* Imag */ "K"]
+        );
+      }
+      const imag = Object(_operation__WEBPACK_IMPORTED_MODULE_3__[/* op */ "a"])({ imag_ });
+      //# sourceMappingURL=imag.js.map
+
+      /***/
+    },
+    /* 26 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+        return pool;
+      });
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return maxPoolPositions;
+      });
+      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
+        __webpack_require__(0);
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function pool(xValues, xShape, dtype, strides, convInfo, poolType) {
+        const strideHeight = convInfo.strideHeight;
+        const strideWidth = convInfo.strideWidth;
+        const dilationHeight = convInfo.dilationHeight;
+        const dilationWidth = convInfo.dilationWidth;
+        const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+        const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+        const padTop = convInfo.padInfo.top;
+        const padLeft = convInfo.padInfo.left;
+        const initialValue =
+          poolType === "max" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY;
+        const output = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["buffer"])(
+          convInfo.outShape,
+          dtype
+        );
+        const outputVals = output.values;
+        const outputBatchStrides =
+          convInfo.outShape[1] * convInfo.outShape[2] * convInfo.outShape[3];
+        const outputRowStrides = convInfo.outShape[2] * convInfo.outShape[3];
+        const outputColStrides = convInfo.outShape[3];
+        for (let b = 0; b < convInfo.batchSize; ++b) {
+          const outputBatchOffset = b * outputBatchStrides;
+          const inputBatchOffset = b * strides[0];
+          for (let d = 0; d < convInfo.inChannels; ++d) {
+            for (let yR = 0; yR < convInfo.outHeight; ++yR) {
+              const xRCorner = yR * strideHeight - padTop;
+              const xRMin = Math.max(0, xRCorner);
+              const xRMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRCorner);
+              const outputRowOffset = outputBatchOffset + yR * outputRowStrides;
+              for (let yC = 0; yC < convInfo.outWidth; ++yC) {
+                const xCCorner = yC * strideWidth - padLeft;
+                const xCMin = Math.max(0, xCCorner);
+                const xCMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xCCorner);
+                let minMaxValue = initialValue;
+                let avgValue = 0;
+                let count = 0;
+                for (let xR = xRMin; xR < xRMax; xR += dilationHeight) {
+                  const xROffset = inputBatchOffset + xR * strides[1];
+                  for (let xC = xCMin; xC < xCMax; xC += dilationWidth) {
+                    const xCOffset = xROffset + xC * strides[2];
+                    const pixel = xValues[xCOffset + d];
+                    if (poolType === "max" && pixel > minMaxValue) {
+                      minMaxValue = pixel;
+                    } else if (poolType === "avg") {
+                      avgValue += pixel;
+                      count++;
+                    }
+                  }
+                  if (isNaN(minMaxValue)) {
+                    break;
+                  }
+                }
+                const outputOffset = outputRowOffset + yC * outputColStrides + d;
+                outputVals[outputOffset] = poolType === "avg" ? avgValue / count : minMaxValue;
+              }
+            }
+          }
+        }
+        return output;
+      }
+      function maxPoolPositions(
+        xValues,
+        xShape,
+        dtype,
+        convInfo,
+        flattenPositions = false,
+        includeBatchInIndex = false
+      ) {
+        const maxPositions = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["buffer"])(
+          convInfo.outShape,
+          "int32"
+        );
+        const strideHeight = convInfo.strideHeight;
+        const strideWidth = convInfo.strideWidth;
+        const dilationHeight = convInfo.dilationHeight;
+        const dilationWidth = convInfo.dilationWidth;
+        const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+        const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+        const padTop = convInfo.padInfo.top;
+        const padLeft = convInfo.padInfo.left;
+        const xBuf = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["buffer"])(
+          xShape,
+          dtype,
+          xValues
+        );
+        for (let b = 0; b < convInfo.batchSize; ++b) {
+          for (let d = 0; d < convInfo.inChannels; ++d) {
+            for (let yR = 0; yR < convInfo.outHeight; ++yR) {
+              const xRCorner = yR * strideHeight - padTop;
+              let xRMin = xRCorner;
+              while (xRMin < 0) {
+                xRMin += dilationHeight;
+              }
+              // const xRMin = Math.max(0, xRCorner);
+              const xRMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRCorner);
+              for (let yC = 0; yC < convInfo.outWidth; ++yC) {
+                const xCCorner = yC * strideWidth - padLeft;
+                let xCMin = xCCorner;
+                while (xCMin < 0) {
+                  xCMin += dilationWidth;
+                }
+                const xCMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xCCorner);
+                let maxValue = Number.NEGATIVE_INFINITY;
+                let maxPosition = -1;
+                for (let xR = xRMin; xR < xRMax; xR += dilationHeight) {
+                  const wR = xR - xRCorner;
+                  for (let xC = xCMin; xC < xCMax; xC += dilationWidth) {
+                    const wC = xC - xCCorner;
+                    const pixel = xBuf.get(b, xR, xC, d);
+                    if (pixel > maxValue) {
+                      maxValue = pixel;
+                      if (flattenPositions) {
+                        maxPosition = includeBatchInIndex
+                          ? ((b * convInfo.inHeight + xR) * convInfo.inWidth + xC) *
+                              convInfo.inChannels +
+                            d
+                          : (xR * convInfo.inWidth + xC) * convInfo.inChannels + d;
+                      } else {
+                        maxPosition = wR * effectiveFilterWidth + wC;
+                      }
+                    }
+                  }
+                }
+                maxPositions.set(maxPosition, b, yR, yC, d);
+              }
+            }
+          }
+        }
+        return maxPositions;
+      }
+      //# sourceMappingURL=pool_utils.js.map
+
+      /***/
+    },
+    /* 27 */
+    /***/ function (module, exports) {
+      var g;
+
+      // This works in non-strict mode
+      g = (function () {
+        return this;
+      })();
+
+      try {
+        // This works if eval is allowed (see CSP)
+        g = g || new Function("return this")();
+      } catch (e) {
+        // This works if the window reference is available
+        if (typeof window === "object") g = window;
+      }
+
+      // g can still be undefined, but nothing to do about it...
+      // We return undefined, instead of nothing here, so it's
+      // easier to handle this case. if(!global) { ...}
+
+      module.exports = g;
+
+      /***/
+    },
+    /* 28 */
+    /***/ function (module, exports) {
+      module.exports = function (module) {
+        if (!module.webpackPolyfill) {
+          module.deprecate = function () {};
+          module.paths = [];
+          // module.parent = undefined by default
+          if (!module.children) module.children = [];
+          Object.defineProperty(module, "loaded", {
+            enumerable: true,
+            get: function () {
+              return module.l;
+            },
+          });
+          Object.defineProperty(module, "id", {
+            enumerable: true,
+            get: function () {
+              return module.i;
+            },
+          });
+          module.webpackPolyfill = 1;
+        }
+        return module;
+      };
+
+      /***/
+    },
+    /* 29 */
+    /***/ function (module, exports) {
+      /* WEBPACK VAR INJECTION */ (function (__webpack_amd_options__) {
+        /* globals __webpack_amd_options__ */
+        module.exports = __webpack_amd_options__;
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, {}));
+
+      /***/
+    },
+    /* 30 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return transposeImpl;
+      });
+      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
+        __webpack_require__(0);
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function transposeImpl(xVals, xShape, dtype, perm, newShape) {
+        const xRank = xShape.length;
+        const xSize =
+          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].sizeFromShape(xShape);
+        const xStrides =
+          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].computeStrides(xShape);
+        const newStrides =
+          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].computeStrides(newShape);
+        const result = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__[
+          "util"
+        ].getTypedArrayFromDType(
+          dtype,
+          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].sizeFromShape(newShape)
+        );
+        for (let i = 0; i < xSize; ++i) {
+          const loc = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].indexToLoc(
+            i,
+            xRank,
+            xStrides
+          );
+          // Permute location.
+          const newLoc = new Array(loc.length);
+          for (let i = 0; i < newLoc.length; i++) {
+            newLoc[i] = loc[perm[i]];
+          }
+          const newIndex = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].locToIndex(
+            newLoc,
+            xRank,
+            newStrides
+          );
+          result[newIndex] = xVals[i];
+        }
+        return result;
+      }
+      //# sourceMappingURL=Transpose_impl.js.map
+
+      /***/
+    },
+    /* 31 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "a", function () {
+        return /* reexport */ backend_cpu_MathBackendCPU;
+      });
+      __webpack_require__.d(__webpack_exports__, "c", function () {
+        return /* reexport */ version;
+      });
+      __webpack_require__.d(__webpack_exports__, "b", function () {
+        return /* reexport */ shared_namespaceObject;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/shared.js
+      var shared_namespaceObject = {};
+      __webpack_require__.r(shared_namespaceObject);
+      __webpack_require__.d(shared_namespaceObject, "maxImpl", function () {
+        return Max_impl["a" /* maxImpl */];
+      });
+      __webpack_require__.d(shared_namespaceObject, "transposeImpl", function () {
+        return Transpose_impl["a" /* transposeImpl */];
+      });
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max_impl.js
+      var Max_impl = __webpack_require__(37);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose_impl.js
+      var Transpose_impl = __webpack_require__(30);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/shared.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // Shared kernel impls for use in other backends.
+
+      //# sourceMappingURL=shared.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
+      var dist = __webpack_require__(0);
+
+      // EXTERNAL MODULE: ./node_modules/seedrandom/index.js
+      var seedrandom = __webpack_require__(20);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/cpu_util.js
+      var cpu_util = __webpack_require__(9);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/pool_utils.js
+      var pool_utils = __webpack_require__(26);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/backend_cpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const nonMaxSuppressionV3 = dist["kernel_impls"].nonMaxSuppressionV3;
+      const split = dist["kernel_impls"].split;
+      const tile = dist["kernel_impls"].tile;
+      const topkImpl = dist["kernel_impls"].topkImpl;
+      const whereImpl = dist["kernel_impls"].whereImpl;
+
+      function mapActivation(backend, x, activation, preluActivationWeights) {
+        if (activation === "linear") {
+          return backend.linear(x);
+        } else if (activation === "relu") {
+          return backend.relu(x);
+        } else if (activation === "elu") {
+          return backend.elu(x);
+        } else if (activation === "relu6") {
+          return backend.relu6(x);
+        } else if (activation === "prelu") {
+          return backend.prelu(x, preluActivationWeights);
+        }
+        throw new Error(`Activation ${activation} has not been implemented for the CPU backend.`);
+      }
+      class backend_cpu_MathBackendCPU extends dist["KernelBackend"] {
+        constructor() {
+          super();
+          this.blockSize = 48;
+          this.firstUse = true;
+          this.data = new dist["DataStorage"](this, Object(dist["engine"])());
+        }
+        write(values, shape, dtype) {
+          if (this.firstUse) {
+            this.firstUse = false;
+            if (Object(dist["env"])().get("IS_NODE")) {
+              dist["backend_util"].warn(
+                "\n============================\n" +
+                  "Hi there 👋. Looks like you are running TensorFlow.js in " +
+                  "Node.js. To speed things up dramatically, install our node " +
+                  "backend, which binds to TensorFlow C++, by running " +
+                  "npm i @tensorflow/tfjs-node, " +
+                  "or npm i @tensorflow/tfjs-node-gpu if you have CUDA. " +
+                  "Then call require('@tensorflow/tfjs-node'); (-gpu " +
+                  "suffix for CUDA) at the start of your program. " +
+                  "Visit https://github.com/tensorflow/tfjs-node for more details." +
+                  "\n============================"
+              );
+            }
+          }
+          const dataId = {};
+          this.data.set(dataId, { values, dtype });
+          return dataId;
+        }
+        move(dataId, values, shape, dtype) {
+          this.data.set(dataId, { values, dtype });
+        }
+        numDataIds() {
+          return this.data.numDataIds();
+        }
+        async read(dataId) {
+          return this.readSync(dataId);
+        }
+        readSync(dataId) {
+          const { dtype, complexTensors } = this.data.get(dataId);
+          if (dtype === "complex64") {
+            const realValues = this.readSync(complexTensors.real.dataId);
+            const imagValues = this.readSync(complexTensors.imag.dataId);
+            return dist["backend_util"].mergeRealAndImagArrays(realValues, imagValues);
+          }
+          return this.data.get(dataId).values;
+        }
+        bufferSync(t) {
+          const data = this.readSync(t.dataId);
+          let decodedData = data;
+          if (t.dtype === "string") {
+            try {
+              // Decode the bytes into string.
+              decodedData = data.map((d) => dist["util"].decodeString(d));
+            } catch (_a) {
+              throw new Error("Failed to decode encoded string bytes into utf-8");
+            }
+          }
+          return dist["buffer"](t.shape, t.dtype, decodedData);
+        }
+        makeOutput(values, shape, dtype) {
+          const dataId = this.write(values, shape, dtype);
+          return Object(dist["engine"])().makeTensorFromDataId(dataId, shape, dtype, this);
+        }
+        disposeData(dataId) {
+          if (this.data.has(dataId)) {
+            const { complexTensors } = this.data.get(dataId);
+            if (complexTensors != null) {
+              complexTensors.real.dispose();
+              complexTensors.imag.dispose();
+            }
+            this.data.delete(dataId);
+          }
+        }
+        async time(f) {
+          const start = dist["util"].now();
+          f();
+          const kernelMs = dist["util"].now() - start;
+          return { kernelMs };
+        }
+        memory() {
+          return {
+            // Unreliable due to automatic gc. The numbers above are cumulative.
+            unreliable: true,
+            reasons: [
+              "The reported memory is an upper bound. Due to automatic garbage " +
+                "collection, the true allocated memory may be less.",
+            ],
+          };
+        }
+        complex(real, imag) {
+          const result = this.makeOutput(null, real.shape, "complex64");
+          const resultData = this.data.get(result.dataId);
+          // The backend owns the reference to the underlying real and imaginary
+          // clones. These will explicitly get disposed when the complex tensor is
+          // disposed.
+          resultData.complexTensors = {
+            real: Object(dist["engine"])().keep(real.clone()),
+            imag: Object(dist["engine"])().keep(imag.clone()),
+          };
+          return result;
+        }
+        real(input) {
+          const resultData = this.data.get(input.dataId);
+          return resultData.complexTensors.real.clone();
+        }
+        imag(input) {
+          const resultData = this.data.get(input.dataId);
+          return resultData.complexTensors.imag.clone();
+        }
+        slice(x, begin, size) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "slice");
+          const isContinous = dist["slice_util"].isSliceContinous(x.shape, begin, size);
+          if (isContinous) {
+            const flatOffset = dist["slice_util"].computeFlatOffset(begin, x.strides);
+            const length = dist["util"].sizeFromShape(size);
+            const vals = this.readSync(x.dataId);
+            return dist["tensor"](vals.subarray(flatOffset, flatOffset + length), size, x.dtype);
+          }
+          const buffer = dist["buffer"](size, x.dtype);
+          const xBuf = this.bufferSync(x);
+          for (let i = 0; i < buffer.size; ++i) {
+            const loc = buffer.indexToLoc(i);
+            const xLoc = loc.map((idx, j) => idx + begin[j]);
+            buffer.values[i] = xBuf.get(...xLoc);
+          }
+          return buffer.toTensor();
+        }
+        stridedSlice(x, begin, end, strides) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "stridedSlice");
+          const outShape = dist["slice_util"].computeOutShape(begin, end, strides);
+          if (outShape.some((axis) => axis === 0)) {
+            return dist["tensor"]([], outShape);
+          }
+          const buffer = dist["buffer"](outShape, x.dtype);
+          const xBuf = this.bufferSync(x);
+          for (let i = 0; i < buffer.size; i++) {
+            const loc = buffer.indexToLoc(i);
+            const newLoc = new Array(loc.length);
+            for (let j = 0; j < newLoc.length; j++) {
+              newLoc[j] = loc[j] * strides[j] + begin[j];
+            }
+            buffer.set(xBuf.get(...newLoc), ...loc);
+          }
+          return buffer.toTensor();
+        }
+        diag(x) {
+          const xVals = this.readSync(x.dataId);
+          const buffer = dist["buffer"]([x.size, x.size], x.dtype);
+          const vals = buffer.values;
+          for (let i = 0; i < xVals.length; i++) {
+            vals[i * x.size + i] = xVals[i];
+          }
+          return buffer.toTensor();
+        }
+        unstack(x, axis) {
+          const num = x.shape[axis];
+          const outShape = new Array(x.rank - 1);
+          let outIndex = 0;
+          for (let i = 0; i < x.rank; i++) {
+            if (i !== axis) {
+              outShape[outIndex++] = x.shape[i];
+            }
+          }
+          const begin = new Array(x.rank).fill(0);
+          const size = x.shape.slice();
+          size[axis] = 1;
+          const res = new Array(num);
+          for (let i = 0; i < res.length; i++) {
+            begin[axis] = i;
+            res[i] = this.slice(x, begin, size).reshape(outShape);
+          }
+          return res;
+        }
+        reverse(x, axis) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "reverse");
+          const buffer = dist["buffer"](x.shape, x.dtype);
+          const xBuf = this.bufferSync(x);
+          for (let i = 0; i < buffer.size; i++) {
+            const outLoc = buffer.indexToLoc(i);
+            const inLoc = outLoc.slice();
+            axis.forEach((ax) => (inLoc[ax] = x.shape[ax] - 1 - inLoc[ax]));
+            buffer.set(xBuf.get(...inLoc), ...outLoc);
+          }
+          return buffer.toTensor();
+        }
+        concat(tensors, axis) {
+          if (tensors[0].dtype === "complex64") {
+            const reals = tensors.map((t) => dist["real"](t));
+            const imags = tensors.map((t) => dist["imag"](t));
+            return dist["complex"](this.concat(reals, axis), this.concat(imags, axis));
+          }
+          const tensors2D = tensors.map((t) => {
+            const innerSize = dist["util"].sizeFromShape(t.shape.slice(axis));
+            return t.as2D(-1, innerSize);
+          });
+          const outShape = dist["backend_util"].computeOutShape(
+            tensors2D.map((t) => t.shape),
+            1
+            /* axis
+             */
+          );
+          const values = dist["buffer"](outShape, tensors[0].dtype).values;
+          if (tensors2D[0].shape[0] === 1) {
+            // Use built-in TypedArray.set() method for speed.
+            let offset = 0;
+            tensors2D.forEach((t) => {
+              values.set(this.readSync(t.dataId), offset);
+              offset += t.size;
+            });
+          } else {
+            let colOffset = 0;
+            tensors2D.forEach((t) => {
+              const tVals = this.readSync(t.dataId);
+              let tIdx = 0;
+              for (let row = 0; row < t.shape[0]; ++row) {
+                const resIdx = row * outShape[1] + colOffset;
+                for (let col = 0; col < t.shape[1]; ++col) {
+                  values[resIdx + col] = tVals[tIdx++];
+                }
+              }
+              colOffset += t.shape[1];
+            });
+          }
+          const finalOutShape = dist["backend_util"].computeOutShape(
+            tensors.map((t) => t.shape),
+            axis
+          );
+          return dist["tensor"](values, finalOutShape, tensors[0].dtype);
+        }
+        neg(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "neg");
+          return this.multiply(dist["scalar"](-1), x);
+        }
+        add(a, b) {
+          if (a.dtype === "complex64" || b.dtype === "complex64") {
+            return this.broadcastedBinaryComplexOp(
+              a.cast("complex64"),
+              b.cast("complex64"),
+              (aReal, aImag, bReal, bImag) => {
+                return { real: aReal + bReal, imag: aImag + bImag };
+              }
+            );
+          }
+          return this.broadcastedBinaryOp(
+            a,
+            b,
+            Object(dist["upcastType"])(a.dtype, b.dtype),
+            (aValue, bValue) => aValue + bValue
+          );
+        }
+        addN(tensors) {
+          Object(cpu_util["a" /* assertNotComplex */])(tensors, "addN");
+          const vals = tensors.map((t) => this.readSync(t.dataId));
+          const result = dist["buffer"](tensors[0].shape, tensors[0].dtype);
+          const resultVals = result.values;
+          for (let i = 0; i < tensors.length; i++) {
+            const currVals = vals[i];
+            for (let j = 0; j < resultVals.length; j++) {
+              resultVals[j] += currVals[j];
+            }
+          }
+          return result.toTensor();
+        }
+        softmax(logits, dim) {
+          const axes = dist["util"].parseAxisParam([dim], logits.shape);
+          // TODO(annxingyuan): Call maxImpl rather than op as part of softmax kernel
+          // modularization.
+          const maxLogit = Object(dist["max"])(logits, axes);
+          const expandedShape = dist["backend_util"].expandShapeToKeepDim(maxLogit.shape, axes);
+          const a = this.subtract(logits, maxLogit.reshape(expandedShape));
+          const b = this.exp(a);
+          const sumExp = this.sum(b, axes).reshape(expandedShape);
+          // TODO(annxingyuan): Call divImpl rather than op as part of softmax
+          // kernel modularization.
+          return dist["div"](b, sumExp);
+        }
+        subtract(a, b) {
+          if (a.dtype === "complex64" || b.dtype === "complex64") {
+            return this.broadcastedBinaryComplexOp(
+              a.cast("complex64"),
+              b.cast("complex64"),
+              (aReal, aImag, bReal, bImag) => {
+                return { real: aReal - bReal, imag: aImag - bImag };
+              }
+            );
+          }
+          return this.broadcastedBinaryOp(
+            a,
+            b,
+            Object(dist["upcastType"])(a.dtype, b.dtype),
+            (aValue, bValue) => aValue - bValue
+          );
+        }
+        pow(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "pow");
+          return this.broadcastedBinaryOp(a, b, a.dtype, (aValue, bValue) =>
+            Math.pow(aValue, bValue)
+          );
+        }
+        batchMatMul(a, b, transposeA, transposeB) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "matMul");
+          const sharedDim = transposeA ? a.shape[1] : a.shape[2];
+          const leftDim = transposeA ? a.shape[2] : a.shape[1];
+          const rightDim = transposeB ? b.shape[1] : b.shape[2];
+          const batchDim = a.shape[0];
+          const aValues = this.readSync(a.dataId);
+          const bValues = this.readSync(b.dataId);
+          const [aBatch, aOuterStep, aInnerStep] = transposeA
+            ? [a.strides[0], 1, a.strides[1]]
+            : [a.strides[0], a.strides[1], 1];
+          const [bInnerStep, bOuterStep, bBatch] = transposeB
+            ? [1, b.strides[1], b.strides[0]]
+            : [b.strides[1], 1, b.strides[0]];
+          const size = leftDim * rightDim;
+          const result = dist["buffer"]([batchDim, leftDim, rightDim], a.dtype);
+          const resVals = result.values;
+          const blockSize = this.blockSize;
+          for (let b = 0; b < batchDim; b++) {
+            for (let i0 = 0; i0 < leftDim; i0 += blockSize) {
+              for (let j0 = 0; j0 < rightDim; j0 += blockSize) {
+                for (let k0 = 0; k0 < sharedDim; k0 += blockSize) {
+                  // for when blockSize doesn't evenly divide the input
+                  const iBlock = Math.min(i0 + blockSize, leftDim);
+                  const jBlock = Math.min(j0 + blockSize, rightDim);
+                  const kBlock = Math.min(k0 + blockSize, sharedDim);
+                  for (let i = i0; i < iBlock; i++) {
+                    for (let j = j0; j < jBlock; j++) {
+                      let sum = 0.0;
+                      for (let k = k0; k < kBlock; k++) {
+                        sum +=
+                          aValues[b * aBatch + i * aOuterStep + k * aInnerStep] *
+                          bValues[k * bInnerStep + j * bOuterStep + b * bBatch];
+                      }
+                      resVals[b * size + (i * rightDim + j)] += sum;
+                    }
+                  }
+                }
+              }
+            }
+          }
+          return result.toTensor();
+        }
+        fusedBatchMatMul({
+          a,
+          b,
+          transposeA,
+          transposeB,
+          bias,
+          activation,
+          preluActivationWeights,
+        }) {
+          let result = this.batchMatMul(a, b, transposeA, transposeB);
+          if (bias) {
+            result = this.add(result, bias);
+          }
+          if (activation) {
+            result = mapActivation(this, result, activation, preluActivationWeights);
+          }
+          return result;
+        }
+        multiply(a, b) {
+          if (a.dtype === "complex64" || b.dtype === "complex64") {
+            return this.broadcastedBinaryComplexOp(
+              a.cast("complex64"),
+              b.cast("complex64"),
+              (aReal, aImag, bReal, bImag) => {
+                return {
+                  real: aReal * bReal - aImag * bImag,
+                  imag: aReal * bImag + aImag * bReal,
+                };
+              }
+            );
+          }
+          return this.broadcastedBinaryOp(
+            a,
+            b,
+            Object(dist["upcastType"])(a.dtype, b.dtype),
+            (aValue, bValue) => aValue * bValue
+          );
+        }
+        floorDiv(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "floorDiv");
+          const op = (a, b) => Math.floor(a / b);
+          const outputDtype = "int32";
+          return this.broadcastedBinaryOp(a, b, outputDtype, op);
+        }
+        sum(x, axes) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "sum");
+          dist["backend_util"].assertAxesAreInnerMostDims("sum", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const resultDtype = Object(dist["upcastType"])(x.dtype, "int32");
+          const result = dist["zeros"](outShape, resultDtype);
+          const reduceSize = dist["util"].sizeFromShape(reduceShape);
+          const vals = this.readSync(result.dataId);
+          const aVals = this.readSync(x.dataId);
+          for (let i = 0; i < vals.length; ++i) {
+            const offset = i * reduceSize;
+            let sum = 0;
+            for (let j = 0; j < reduceSize; ++j) {
+              sum += aVals[offset + j];
+            }
+            vals[i] = sum;
+          }
+          return result;
+        }
+        prod(x, axes) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "sum");
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const resultDtype = Object(dist["upcastType"])(x.dtype, "int32");
+          const result = dist["zeros"](outShape, resultDtype);
+          const reduceSize = dist["util"].sizeFromShape(reduceShape);
+          const vals = this.readSync(result.dataId);
+          const aVals = this.readSync(x.dataId);
+          for (let i = 0; i < vals.length; ++i) {
+            const offset = i * reduceSize;
+            let prod = 1;
+            for (let j = 0; j < reduceSize; ++j) {
+              prod *= aVals[offset + j];
+            }
+            vals[i] = prod;
+          }
+          return result;
+        }
+        unsortedSegmentSum(x, segmentIds, numSegments) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "unsortedSegmentSum");
+          const res = [];
+          // Reshape the segment id's so that they can be broadcast with
+          // x. The new shape should be [segmentIds.shape, 1, ..., 1]
+          const numIters = x.rank - segmentIds.rank;
+          for (let i = 0; i < numIters; ++i) {
+            segmentIds = segmentIds.expandDims(i + 1);
+          }
+          for (let i = 0; i < numSegments; ++i) {
+            const segmentId = dist["scalar"](i, "int32");
+            const mask = dist["equal"](segmentId, segmentIds).asType("float32");
+            const sum = mask.mul(x).sum(0);
+            res.push(sum);
+          }
+          return dist["stack"](res);
+        }
+        argMin(x, axis) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "argMin");
+          const axes = [axis];
+          dist["backend_util"].assertAxesAreInnerMostDims("argMin", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const result = dist["zeros"](outShape, "int32");
+          const reduceSize = dist["util"].sizeFromShape(reduceShape);
+          const vals = this.readSync(result.dataId);
+          const aVals = this.readSync(x.dataId);
+          for (let i = 0; i < vals.length; ++i) {
+            const offset = i * reduceSize;
+            let min = aVals[offset];
+            let minIndex = 0;
+            for (let j = 0; j < reduceSize; ++j) {
+              const value = aVals[offset + j];
+              if (value < min) {
+                min = value;
+                minIndex = j;
+              }
+            }
+            vals[i] = minIndex;
+          }
+          return result;
+        }
+        argMax(x, axis) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "argMax");
+          const axes = [axis];
+          dist["backend_util"].assertAxesAreInnerMostDims("argMax", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const result = dist["zeros"](outShape, "int32");
+          const reduceSize = dist["util"].sizeFromShape(reduceShape);
+          const vals = this.readSync(result.dataId);
+          const aVals = this.readSync(x.dataId);
+          for (let i = 0; i < vals.length; ++i) {
+            const offset = i * reduceSize;
+            let max = aVals[offset];
+            let maxIndex = 0;
+            for (let j = 0; j < reduceSize; ++j) {
+              const value = aVals[offset + j];
+              if (value > max) {
+                max = value;
+                maxIndex = j;
+              }
+            }
+            vals[i] = maxIndex;
+          }
+          return result;
+        }
+        cumsum(x, axis, exclusive, reverse) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "cumsum");
+          if (axis !== x.rank - 1) {
+            throw new Error(
+              `backend.cumsum in CPU expects an inner-most axis=${x.rank - 1} ` +
+                `but got axis=${axis}`
+            );
+          }
+          const resultDtype = Object(dist["upcastType"])(x.dtype, "int32");
+          const result = dist["zeros"](x.shape, resultDtype);
+          const vals = this.readSync(result.dataId);
+          const aVals = this.readSync(x.dataId);
+          const finalDim = x.shape[x.rank - 1];
+          const indexAdjuster = reverse ? (i, j) => i + finalDim - j - 1 : (i, j) => i + j;
+          for (let i = 0; i < aVals.length; i += finalDim) {
+            for (let j = 0; j < finalDim; j++) {
+              const idx = indexAdjuster(i, j);
+              if (j === 0) {
+                vals[idx] = exclusive ? 0 : aVals[idx];
+              } else {
+                const prevIdx = indexAdjuster(i, j - 1);
+                vals[idx] = exclusive ? aVals[prevIdx] + vals[prevIdx] : aVals[idx] + vals[prevIdx];
+              }
+            }
+          }
+          return result;
+        }
+        equal(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "equal");
+          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
+            return aVal === bVal ? 1 : 0;
+          });
+        }
+        notEqual(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "notEqual");
+          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
+            return aVal !== bVal ? 1 : 0;
+          });
+        }
+        less(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "less");
+          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
+            return aVal < bVal ? 1 : 0;
+          });
+        }
+        lessEqual(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "lessEqual");
+          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
+            return aVal <= bVal ? 1 : 0;
+          });
+        }
+        greater(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "greater");
+          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
+            return aVal > bVal ? 1 : 0;
+          });
+        }
+        greaterEqual(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "greaterEqual");
+          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
+            return aVal >= bVal ? 1 : 0;
+          });
+        }
+        logicalNot(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "logicalNot");
+          const values = this.readSync(x.dataId);
+          const newValues = new Uint8Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            newValues[i] = values[i] ? 0 : 1;
+          }
+          return this.makeOutput(newValues, x.shape, "bool");
+        }
+        logicalAnd(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "logicalAnd");
+          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
+            return aVal && bVal;
+          });
+        }
+        logicalOr(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "logicalOr");
+          return this.broadcastedBinaryOp(a, b, "bool", (aVal, bVal) => {
+            return aVal || bVal;
+          });
+        }
+        select(condition, a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([condition, a, b], "select");
+          const values = this.readSync(condition.dataId);
+          const aValues = this.readSync(a.dataId);
+          const bValues = this.readSync(b.dataId);
+          const result = dist["zeros"](a.shape, Object(dist["upcastType"])(a.dtype, b.dtype));
+          const newValues = this.readSync(result.dataId);
+          let index = 0;
+          const offset =
+            condition.rank === 0 || condition.rank > 1 || a.rank === 1
+              ? 1
+              : dist["util"].sizeFromShape(a.shape.slice(1));
+          for (let i = 0; i < values.length; i++) {
+            for (let j = 0; j < offset; j++) {
+              if (values[i] === 1) {
+                newValues[index++] = aValues[i];
+              } else {
+                newValues[index++] = bValues[i];
+              }
+            }
+          }
+          return result;
+        }
+        where(condition) {
+          Object(cpu_util["a" /* assertNotComplex */])([condition], "where");
+          const condVals = this.readSync(condition.dataId);
+          return whereImpl(condition.shape, condVals);
+        }
+        topk(x, k, sorted) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "topk");
+          const xVals = this.readSync(x.dataId);
+          return topkImpl(xVals, x.shape, x.dtype, k, sorted);
+        }
+        min(x, axes) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "min");
+          dist["backend_util"].assertAxesAreInnerMostDims("min", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const result = dist["zeros"](outShape, x.dtype);
+          const reduceSize = dist["util"].sizeFromShape(reduceShape);
+          const vals = this.readSync(result.dataId);
+          const aVals = this.readSync(x.dataId);
+          for (let i = 0; i < vals.length; ++i) {
+            const offset = i * reduceSize;
+            let min = aVals[offset];
+            for (let j = 0; j < reduceSize; ++j) {
+              const value = aVals[offset + j];
+              if (value < min) {
+                min = value;
+              }
+            }
+            vals[i] = min;
+          }
+          return result;
+        }
+        minimum(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "minimum");
+          return this.broadcastedBinaryOp(a, b, a.dtype, (aVal, bVal) => Math.min(aVal, bVal));
+        }
+        mod(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "mod");
+          return this.broadcastedBinaryOp(a, b, a.dtype, (aVal, bVal) => {
+            const rem = aVal % bVal;
+            if ((aVal < 0 && bVal < 0) || (aVal >= 0 && bVal >= 0)) {
+              return rem;
+            } else {
+              return (rem + bVal) % bVal;
+            }
+          });
+        }
+        maximum(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "maximum");
+          return this.broadcastedBinaryOp(a, b, a.dtype, (aVal, bVal) => Math.max(aVal, bVal));
+        }
+        all(x, axes) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "all");
+          dist["backend_util"].assertAxesAreInnerMostDims("all", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const result = dist["zeros"](outShape, x.dtype);
+          const reduceSize = dist["util"].sizeFromShape(reduceShape);
+          const vals = this.readSync(result.dataId);
+          const aVals = this.readSync(x.dataId);
+          for (let i = 0; i < vals.length; ++i) {
+            const offset = i * reduceSize;
+            let all = aVals[offset];
+            for (let j = 0; j < reduceSize; ++j) {
+              const value = aVals[offset + j];
+              all = all && value;
+            }
+            vals[i] = all;
+          }
+          return result;
+        }
+        any(x, axes) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "any");
+          dist["backend_util"].assertAxesAreInnerMostDims("any", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const result = dist["zeros"](outShape, x.dtype);
+          const reduceSize = dist["util"].sizeFromShape(reduceShape);
+          const vals = this.readSync(result.dataId);
+          const aVals = this.readSync(x.dataId);
+          for (let i = 0; i < vals.length; ++i) {
+            const offset = i * reduceSize;
+            let anyVal = aVals[offset];
+            for (let j = 0; j < reduceSize; ++j) {
+              const value = aVals[offset + j];
+              anyVal = anyVal || value;
+            }
+            vals[i] = anyVal;
+          }
+          return result;
+        }
+        squaredDifference(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "squaredDifference");
+          return this.broadcastedBinaryOp(a, b, a.dtype, (aVal, bVal) => {
+            const diff = aVal - bVal;
+            return diff * diff;
+          });
+        }
+        ceil(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "ceil");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            newValues[i] = Math.ceil(values[i]);
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        floor(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "floor");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            newValues[i] = Math.floor(values[i]);
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        sign(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "x");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            if (values[i] < 0) {
+              newValues[i] = -1;
+            } else if (values[i] > 0) {
+              newValues[i] = 1;
+            } else {
+              newValues[i] = 0;
+            }
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        isNaN(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "x");
+          const values = this.readSync(x.dataId);
+          const newValues = new Uint8Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            if (Number.isNaN(values[i])) {
+              newValues[i] = 1;
+            }
+          }
+          return this.makeOutput(newValues, x.shape, "bool");
+        }
+        isInf(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "x");
+          const values = this.readSync(x.dataId);
+          const newValues = new Uint8Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            if (Math.abs(values[i]) === Infinity) {
+              newValues[i] = 1;
+            }
+          }
+          return this.makeOutput(newValues, x.shape, "bool");
+        }
+        isFinite(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "x");
+          const values = this.readSync(x.dataId);
+          const newValues = new Uint8Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            if (Number.isFinite(values[i])) {
+              newValues[i] = 1;
+            }
+          }
+          return this.makeOutput(newValues, x.shape, "bool");
+        }
+        round(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "round");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            // The algorithm is based on banker's rounding.
+            const base = Math.floor(values[i]);
+            if (values[i] - base < 0.5) {
+              newValues[i] = Math.floor(values[i]);
+            } else if (values[i] - base > 0.5) {
+              newValues[i] = Math.ceil(values[i]);
+            } else {
+              if (base % 2.0 === 0.0) {
+                newValues[i] = base;
+              } else {
+                newValues[i] = base + 1.0;
+              }
+            }
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        exp(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "exp");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            newValues[i] = Math.exp(values[i]);
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        expm1(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "expm1");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            newValues[i] = Math.expm1(values[i]);
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        log(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "log");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            const value = values[i];
+            newValues[i] = Math.log(value);
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        log1p(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "log1p");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            const value = values[i];
+            newValues[i] = Math.log1p(value);
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        sqrt(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "sqrt");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            const value = values[i];
+            newValues[i] = Math.sqrt(value);
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        rsqrt(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "rsqrt");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            const value = values[i];
+            newValues[i] = 1 / Math.sqrt(value);
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        reciprocal(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "reciprocal");
+          const values = this.readSync(x.dataId);
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            newValues[i] = 1 / values[i];
+          }
+          return this.makeOutput(newValues, x.shape, "float32");
+        }
+        linear(x) {
+          return x;
+        }
+        relu(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "relu");
+          const res = dist["zeros"](x.shape, x.dtype);
+          const resVals = this.readSync(res.dataId);
+          const inVals = this.readSync(x.dataId);
+          for (let i = 0; i < inVals.length; ++i) {
+            resVals[i] = Math.max(0, inVals[i]);
+          }
+          return res;
+        }
+        relu6(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "relu");
+          const res = dist["zeros"](x.shape, x.dtype);
+          const resVals = this.readSync(res.dataId);
+          const inVals = this.readSync(x.dataId);
+          for (let i = 0; i < inVals.length; ++i) {
+            resVals[i] = Math.min(Math.max(0, inVals[i]), 6);
+          }
+          return res;
+        }
+        prelu(x, a) {
+          Object(cpu_util["a" /* assertNotComplex */])([x, a], "prelu");
+          return this.broadcastedBinaryOp(x, a, x.dtype, (xValue, aValue) =>
+            xValue < 0 ? aValue * xValue : xValue
+          );
+        }
+        elu(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "elu");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            const v = values[i];
+            if (v >= 0) {
+              resultValues[i] = v;
+            } else {
+              resultValues[i] = Math.exp(v) - 1;
+            }
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        eluDer(dy, y) {
+          Object(cpu_util["a" /* assertNotComplex */])([dy, y], "eluDer");
+          const resultValues = new Float32Array(y.size);
+          const values = this.readSync(y.dataId);
+          const dyValues = this.readSync(dy.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            const v = values[i];
+            if (v >= 1) {
+              resultValues[i] = dyValues[i];
+            } else {
+              resultValues[i] = dyValues[i] * (v + 1);
+            }
+          }
+          return this.makeOutput(resultValues, y.shape, "float32");
+        }
+        selu(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "selu");
+          // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
+          // see: https://arxiv.org/abs/1706.02515
+          const scaleAlpha = dist["backend_util"].SELU_SCALEALPHA;
+          const scale = dist["backend_util"].SELU_SCALE;
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            const v = values[i];
+            if (v >= 0) {
+              resultValues[i] = scale * v;
+            } else {
+              resultValues[i] = scaleAlpha * (Math.exp(v) - 1);
+            }
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        clip(x, min, max) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "clip");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            const v = values[i];
+            resultValues[i] = v > max ? max : v < min ? min : v;
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        abs(x) {
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.abs(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        complexAbs(x) {
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < x.size; ++i) {
+            const real = values[i * 2];
+            const imag = values[i * 2 + 1];
+            resultValues[i] = Math.hypot(real, imag);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        int(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "int");
+          const resultValues = new Int32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = values[i];
+          }
+          return this.makeOutput(resultValues, x.shape, "int32");
+        }
+        sigmoid(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "sigmoid");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = 1 / (1 + Math.exp(-values[i]));
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        softplus(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "softplus");
+          // mirrors the implementation of tf.nn.softplus: https://goo.gl/vkcvwX
+          // epsilon is the difference between 1.0 and the next representable float.
+          // For a single precision 32 bit float this should be 2^-23, see:
+          // https://math.byu.edu/~schow/work/IEEEFloatingPoint.htm
+          const epsilon = 1.1920928955078125e-7;
+          const threshold = Math.log(epsilon) + 2.0;
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            // Value above which exp(x) may overflow, but softplus(x) == x
+            // is within machine epsilon.
+            const tooLarge = values[i] > -threshold;
+            // Value below which exp(x) may underflow, but softplus(x) == exp(x)
+            // is within machine epsilon.
+            const tooSmall = values[i] < threshold;
+            const expX = Math.exp(values[i]);
+            let result;
+            if (tooSmall) {
+              result = expX;
+            } else if (tooLarge) {
+              result = values[i];
+            } else {
+              result = Math.log(1.0 + expX);
+            }
+            resultValues[i] = result;
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        sin(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "sin");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.sin(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        cos(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "cos");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.cos(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        tan(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "tan");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.tan(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        asin(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "asin");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.asin(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        acos(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "acos");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.acos(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        atan(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "atan");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.atan(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        atan2(a, b) {
+          Object(cpu_util["a" /* assertNotComplex */])([a, b], "atan2");
+          return this.broadcastedBinaryOp(a, b, a.dtype, (aValue, bValue) =>
+            Math.atan2(aValue, bValue)
+          );
+        }
+        sinh(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "sinh");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.sinh(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        cosh(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "cosh");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.cosh(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        tanh(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "tanh");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = dist["util"].tanh(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        asinh(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "asinh");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.asinh(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        acosh(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "acosh");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.acosh(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        atanh(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "atanh");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            resultValues[i] = Math.atanh(values[i]);
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        erf(x) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "erf");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          const p = dist["backend_util"].ERF_P;
+          const a1 = dist["backend_util"].ERF_A1;
+          const a2 = dist["backend_util"].ERF_A2;
+          const a3 = dist["backend_util"].ERF_A3;
+          const a4 = dist["backend_util"].ERF_A4;
+          const a5 = dist["backend_util"].ERF_A5;
+          for (let i = 0; i < values.length; ++i) {
+            const sign = Math.sign(values[i]);
+            const v = Math.abs(values[i]);
+            const t = 1.0 / (1.0 + p * v);
+            resultValues[i] =
+              sign * (1.0 - ((((a5 * t + a4) * t + a3) * t + a2) * t + a1) * t * Math.exp(-v * v));
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        step(x, alpha = 0) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "step");
+          const resultValues = new Float32Array(x.size);
+          const values = this.readSync(x.dataId);
+          for (let i = 0; i < values.length; ++i) {
+            const value = values[i];
+            if (isNaN(value)) {
+              resultValues[i] = NaN;
+            } else {
+              resultValues[i] = value > 0 ? 1 : alpha;
+            }
+          }
+          return this.makeOutput(resultValues, x.shape, "float32");
+        }
+        fusedConv2d({ input, filter, convInfo, bias, activation, preluActivationWeights }) {
+          let result = this.conv2d(input, filter, convInfo);
+          if (bias) {
+            result = this.add(result, bias);
+          }
+          if (activation) {
+            result = mapActivation(this, result, activation, preluActivationWeights);
+          }
+          return result;
+        }
+        conv2d(x, filter, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([x, filter], "conv2d");
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const padLeft = convInfo.padInfo.left;
+          const padTop = convInfo.padInfo.top;
+          const isChannelsLast = convInfo.dataFormat === "channelsLast";
+          const y = dist["buffer"](convInfo.outShape, x.dtype);
+          const xBatchStride = x.strides[0];
+          const xRowStride = isChannelsLast ? x.strides[1] : x.strides[2];
+          const xColStride = isChannelsLast ? x.strides[2] : 1;
+          const xChannelStride = isChannelsLast ? 1 : x.strides[1];
+          const yBatchStride = y.strides[0];
+          const yRowStride = isChannelsLast ? y.strides[1] : y.strides[2];
+          const yColStride = isChannelsLast ? y.strides[2] : 1;
+          const yChannelStride = isChannelsLast ? 1 : y.strides[1];
+          const xVals = this.readSync(x.dataId);
+          const wVals = this.readSync(filter.dataId);
+          const yVals = y.values;
+          for (let b = 0; b < convInfo.batchSize; ++b) {
+            const xOffset1 = b * xBatchStride;
+            const yOffset1 = b * yBatchStride;
+            for (let yR = 0; yR < convInfo.outHeight; ++yR) {
+              const yOffset2 = yOffset1 + yR * yRowStride;
+              const xRCorner = yR * convInfo.strideHeight - padTop;
+              for (let wR = 0; wR < filterHeight; wR++) {
+                const xR = xRCorner + wR * dilationHeight;
+                if (xR < 0 || xR >= convInfo.inHeight) {
+                  continue;
+                }
+                const wOffset1 = wR * filter.strides[0];
+                const xOffset2 = xOffset1 + xR * xRowStride;
+                for (let yC = 0; yC < convInfo.outWidth; ++yC) {
+                  const yOffset3 = yOffset2 + yC * yColStride;
+                  const xCCorner = yC * convInfo.strideWidth - padLeft;
+                  for (let wC = 0; wC < filterWidth; wC++) {
+                    const xC = xCCorner + wC * dilationWidth;
+                    if (xC < 0 || xC >= convInfo.inWidth) {
+                      continue;
+                    }
+                    const wOffset2 = wOffset1 + wC * filter.strides[1];
+                    const xOffset3 = xOffset2 + xC * xColStride;
+                    let wOffset3 = wOffset2;
+                    for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
+                      const xVal = xVals[xOffset3 + d1 * xChannelStride];
+                      for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
+                        yVals[yOffset3 + d2 * yChannelStride] += xVal * wVals[wOffset3 + d2];
+                      }
+                      wOffset3 += convInfo.outChannels;
+                    }
+                  }
+                }
+              }
+            }
+          }
+          return y.toTensor();
+        }
+        conv3d(x, filter, convInfo) {
+          const filterDepth = convInfo.filterDepth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const padFront = convInfo.padInfo.front;
+          const padLeft = convInfo.padInfo.left;
+          const padTop = convInfo.padInfo.top;
+          const y = dist["buffer"](convInfo.outShape, x.dtype);
+          const xVals = this.readSync(x.dataId);
+          const wVals = this.readSync(filter.dataId);
+          const yVals = y.values;
+          for (let b = 0; b < convInfo.batchSize; ++b) {
+            const xOffset1 = b * x.strides[0];
+            const yOffset1 = b * y.strides[0];
+            for (let yF = 0; yF < convInfo.outDepth; ++yF) {
+              const yOffset2 = yOffset1 + yF * y.strides[1];
+              const xFCorner = yF * convInfo.strideDepth - padFront;
+              for (let wF = 0; wF < filterDepth; wF++) {
+                const xF = xFCorner + wF * dilationDepth;
+                if (xF < 0 || xF >= convInfo.inDepth) {
+                  continue;
+                }
+                const wOffset1 = wF * filter.strides[0];
+                const xOffset2 = xOffset1 + xF * x.strides[1];
+                for (let yR = 0; yR < convInfo.outHeight; ++yR) {
+                  const yOffset3 = yOffset2 + yR * y.strides[2];
+                  const xRCorner = yR * convInfo.strideHeight - padTop;
+                  for (let wR = 0; wR < filterHeight; wR++) {
+                    const xR = xRCorner + wR * dilationHeight;
+                    if (xR < 0 || xR >= convInfo.inHeight) {
+                      continue;
+                    }
+                    const wOffset2 = wOffset1 + wR * filter.strides[1];
+                    const xOffset3 = xOffset2 + xR * x.strides[2];
+                    for (let yC = 0; yC < convInfo.outWidth; ++yC) {
+                      const yOffset4 = yOffset3 + yC * convInfo.outChannels;
+                      const xCCorner = yC * convInfo.strideWidth - padLeft;
+                      for (let wC = 0; wC < filterWidth; wC++) {
+                        const xC = xCCorner + wC * dilationWidth;
+                        if (xC < 0 || xC >= convInfo.inWidth) {
+                          continue;
+                        }
+                        const wOffset3 = wOffset2 + wC * filter.strides[2];
+                        const xOffset4 = xOffset3 + xC * convInfo.inChannels;
+                        let wOffset4 = wOffset3;
+                        for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
+                          const xVal = xVals[xOffset4 + d1];
+                          for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
+                            yVals[yOffset4 + d2] += xVal * wVals[wOffset4 + d2];
+                          }
+                          wOffset4 += convInfo.outChannels;
+                        }
+                      }
+                    }
+                  }
+                }
+              }
+            }
+          }
+          return y.toTensor();
+        }
+        conv2dDerInput(dy, filter, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([dy, filter], "conv2dDerInput");
+          const dx = dist["buffer"](convInfo.inShape, "float32");
+          const dxValues = dx.values;
+          const dyValues = this.readSync(dy.dataId);
+          const fltValues = this.readSync(filter.dataId);
+          const [fltS0, fltS1, fltS2] = filter.strides;
+          const {
+            batchSize,
+            filterHeight,
+            filterWidth,
+            inChannels,
+            inHeight,
+            inWidth,
+            outChannels,
+            outHeight,
+            outWidth,
+            strideHeight,
+            strideWidth,
+            dataFormat,
+          } = convInfo;
+          const topPad = filterHeight - 1 - convInfo.padInfo.top;
+          const leftPad = filterWidth - 1 - convInfo.padInfo.left;
+          const isChannelsLast = dataFormat === "channelsLast";
+          const xBatchStride = dx.strides[0];
+          const xRowStride = isChannelsLast ? dx.strides[1] : dx.strides[2];
+          const xColStride = isChannelsLast ? dx.strides[2] : 1;
+          const xChannelStride = isChannelsLast ? 1 : dx.strides[1];
+          const yBatchStride = dy.strides[0];
+          const yRowStride = isChannelsLast ? dy.strides[1] : dy.strides[2];
+          const yColStride = isChannelsLast ? dy.strides[2] : 1;
+          const yChannelStride = isChannelsLast ? 1 : dy.strides[1];
+          for (let b = 0; b < batchSize; ++b) {
+            for (let d1 = 0; d1 < inChannels; ++d1) {
+              for (let xR = 0; xR < inHeight; ++xR) {
+                const xRCorner = xR - topPad;
+                const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));
+                const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);
+                for (let xC = 0; xC < inWidth; ++xC) {
+                  const xCCorner = xC - leftPad;
+                  const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));
+                  const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);
+                  let dotProd = 0;
+                  for (let yR = xRMin; yR < yRMax; ++yR) {
+                    const wR = yR * strideHeight - xRCorner;
+                    for (let yC = xCMin; yC < yCMax; ++yC) {
+                      const wC = yC * strideWidth - xCCorner;
+                      const dyOffset = yBatchStride * b + yRowStride * yR + yColStride * yC;
+                      const fltOffset =
+                        fltS0 * (filterHeight - 1 - wR) +
+                        fltS1 * (filterWidth - 1 - wC) +
+                        fltS2 * d1;
+                      for (let d2 = 0; d2 < outChannels; ++d2) {
+                        const pixel = dyValues[dyOffset + yChannelStride * d2];
+                        const weight = fltValues[fltOffset + d2];
+                        dotProd += pixel * weight;
+                      }
+                    }
+                  }
+                  const dxOffset =
+                    xBatchStride * b + xRowStride * xR + xColStride * xC + xChannelStride * d1;
+                  dxValues[dxOffset] = dotProd;
+                }
+              }
+            }
+          }
+          return dx.toTensor();
+        }
+        conv3dDerInput(dy, filter, convInfo) {
+          const dx = dist["buffer"](convInfo.inShape, "float32");
+          const dxValues = dx.values;
+          const [dxS0, dxS1, dxS2, dxS3] = dx.strides;
+          const dyValues = this.readSync(dy.dataId);
+          const [dyS0, dyS1, dyS2, dyS3] = dy.strides;
+          const fltValues = this.readSync(filter.dataId);
+          const [fltS0, fltS1, fltS2, fltS3] = filter.strides;
+          const {
+            batchSize,
+            filterDepth,
+            filterHeight,
+            filterWidth,
+            inChannels,
+            inDepth,
+            inHeight,
+            inWidth,
+            outChannels,
+            outDepth,
+            outHeight,
+            outWidth,
+            strideDepth,
+            strideHeight,
+            strideWidth,
+          } = convInfo;
+          const frontPad = filterDepth - 1 - convInfo.padInfo.front;
+          const topPad = filterHeight - 1 - convInfo.padInfo.top;
+          const leftPad = filterWidth - 1 - convInfo.padInfo.left;
+          for (let b = 0; b < batchSize; ++b) {
+            for (let d1 = 0; d1 < inChannels; ++d1) {
+              // Frames of depth
+              for (let xF = 0; xF < inDepth; ++xF) {
+                const xFCorner = xF - frontPad;
+                const xFMin = Math.max(0, Math.ceil(xFCorner / strideDepth));
+                const yFMax = Math.min(outDepth, (filterDepth + xFCorner) / strideDepth);
+                // Rows as per standard 2d matrix notation
+                for (let xR = 0; xR < inHeight; ++xR) {
+                  const xRCorner = xR - topPad;
+                  const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));
+                  const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);
+                  // Columns as per standard 2d matrix notation
+                  for (let xC = 0; xC < inWidth; ++xC) {
+                    const xCCorner = xC - leftPad;
+                    const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));
+                    const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);
+                    let dotProd = 0;
+                    for (let yF = xFMin; yF < yFMax; ++yF) {
+                      const wF = yF * strideDepth - xFCorner;
+                      for (let yR = xRMin; yR < yRMax; ++yR) {
+                        const wR = yR * strideHeight - xRCorner;
+                        for (let yC = xCMin; yC < yCMax; ++yC) {
+                          const wC = yC * strideWidth - xCCorner;
+                          const dyOffset = dyS0 * b + dyS1 * yF + dyS2 * yR + dyS3 * yC;
+                          const fltOffset =
+                            fltS0 * (filterDepth - 1 - wF) +
+                            fltS1 * (filterHeight - 1 - wR) +
+                            fltS2 * (filterWidth - 1 - wC) +
+                            fltS3 * d1;
+                          for (let d2 = 0; d2 < outChannels; ++d2) {
+                            const pixel = dyValues[dyOffset + d2];
+                            const weight = fltValues[fltOffset + d2];
+                            dotProd += pixel * weight;
+                          }
+                        }
+                      }
+                    }
+                    dxValues[dxS0 * b + dxS1 * xF + dxS2 * xR + dxS3 * xC + d1] = dotProd;
+                  }
+                }
+              }
+            }
+          }
+          return dx.toTensor();
+        }
+        conv2dDerFilter(x, dy, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([x, dy], "conv2dDerFilter");
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const isChannelsLast = convInfo.dataFormat === "channelsLast";
+          const dW = dist["buffer"](convInfo.filterShape, "float32");
+          const leftPad = convInfo.padInfo.left;
+          const topPad = convInfo.padInfo.top;
+          const xBuf = this.bufferSync(x);
+          const dyBuf = this.bufferSync(dy);
+          for (let wR = 0; wR < filterHeight; ++wR) {
+            const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));
+            const yRMax = Math.min(
+              convInfo.outHeight,
+              (convInfo.inHeight + topPad - wR) / strideHeight
+            );
+            for (let wC = 0; wC < filterWidth; ++wC) {
+              const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));
+              const yCMax = Math.min(
+                convInfo.outWidth,
+                (convInfo.inWidth + leftPad - wC) / strideWidth
+              );
+              for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
+                for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
+                  // Need to convolve.
+                  let dotProd = 0;
+                  for (let b = 0; b < convInfo.batchSize; ++b) {
+                    for (let yR = yRMin; yR < yRMax; ++yR) {
+                      const xR = wR + yR * strideHeight - topPad;
+                      for (let yC = yCMin; yC < yCMax; ++yC) {
+                        const xC = wC + yC * strideWidth - leftPad;
+                        if (isChannelsLast) {
+                          dotProd += xBuf.get(b, xR, xC, d1) * dyBuf.get(b, yR, yC, d2);
+                        } else {
+                          dotProd += xBuf.get(b, d1, xR, xC) * dyBuf.get(b, d2, yR, yC);
+                        }
+                      }
+                    }
+                  }
+                  dW.set(dotProd, wR, wC, d1, d2);
+                }
+              }
+            }
+          }
+          return dW.toTensor();
+        }
+        conv3dDerFilter(x, dy, convInfo) {
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const filterDepth = convInfo.filterDepth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const dw = dist["buffer"](convInfo.filterShape, "float32");
+          const dwValues = dw.values;
+          const [dwS0, dwS1, dwS2, dwS3] = dw.strides;
+          const dyValues = this.readSync(dy.dataId);
+          const [dyS0, dyS1, dyS2, dyS3] = dy.strides;
+          const xValues = this.readSync(x.dataId);
+          const [xS0, xS1, xS2, xS3] = x.strides;
+          const frontPad = convInfo.padInfo.front;
+          const leftPad = convInfo.padInfo.left;
+          const topPad = convInfo.padInfo.top;
+          for (let wF = 0; wF < filterDepth; ++wF) {
+            const yFMin = Math.max(0, Math.ceil((frontPad - wF) / strideDepth));
+            const yFMax = Math.min(
+              convInfo.outDepth,
+              (convInfo.inDepth + frontPad - wF) / strideDepth
+            );
+            const wOffset1 = wF * dwS0;
+            for (let wR = 0; wR < filterHeight; ++wR) {
+              const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));
+              const yRMax = Math.min(
+                convInfo.outHeight,
+                (convInfo.inHeight + topPad - wR) / strideHeight
+              );
+              const wOffset2 = wR * dwS1 + wOffset1;
+              for (let wC = 0; wC < filterWidth; ++wC) {
+                const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));
+                const yCMax = Math.min(
+                  convInfo.outWidth,
+                  (convInfo.inWidth + leftPad - wC) / strideWidth
+                );
+                const wOffset3 = wC * dwS2 + wOffset2;
+                for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
+                  const wOffset4 = d1 * dwS3 + wOffset3;
+                  for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
+                    let dotProd = 0;
+                    for (let b = 0; b < convInfo.batchSize; ++b) {
+                      const xOffset1 = b * xS0;
+                      const yOffset1 = b * dyS0;
+                      for (let yF = yFMin; yF < yFMax; ++yF) {
+                        const xF = wF + yF * strideDepth - frontPad;
+                        const xOffset2 = xF * xS1 + xOffset1;
+                        const yOffset2 = yF * dyS1 + yOffset1;
+                        for (let yR = yRMin; yR < yRMax; ++yR) {
+                          const xR = wR + yR * strideHeight - topPad;
+                          const xOffset3 = xR * xS2 + xOffset2;
+                          const yOffset3 = yR * dyS2 + yOffset2;
+                          for (let yC = yCMin; yC < yCMax; ++yC) {
+                            const xC = wC + yC * strideWidth - leftPad;
+                            const xOffset4 = xC * xS3 + xOffset3;
+                            const yOffset4 = yC * dyS3 + yOffset3;
+                            dotProd += xValues[xOffset4 + d1] * dyValues[yOffset4 + d2];
+                          }
+                        }
+                      }
+                    }
+                    dwValues[wOffset4 + d2] = dotProd;
+                  }
+                }
+              }
+            }
+          }
+          return dw.toTensor();
+        }
+        fusedDepthwiseConv2D({
+          input,
+          filter,
+          convInfo,
+          bias,
+          activation,
+          preluActivationWeights,
+        }) {
+          let result = this.depthwiseConv2D(input, filter, convInfo);
+          if (bias) {
+            result = this.add(result, bias);
+          }
+          if (activation) {
+            result = mapActivation(this, result, activation, preluActivationWeights);
+          }
+          return result;
+        }
+        depthwiseConv2D(x, filter, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([x, filter], "depthwiseConv2D");
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const padLeft = convInfo.padInfo.left;
+          const padTop = convInfo.padInfo.top;
+          const chMul = convInfo.outChannels / convInfo.inChannels;
+          const y = dist["buffer"](convInfo.outShape, x.dtype);
+          const xVals = this.readSync(x.dataId);
+          const wVals = this.readSync(filter.dataId);
+          const yVals = y.values;
+          for (let b = 0; b < convInfo.batchSize; ++b) {
+            const xOffset1 = b * x.strides[0];
+            const yOffset1 = b * y.strides[0];
+            for (let yR = 0; yR < convInfo.outHeight; ++yR) {
+              const yOffset2 = yOffset1 + yR * y.strides[1];
+              const xRCorner = yR * convInfo.strideHeight - padLeft;
+              for (let wR = 0; wR < filterHeight; ++wR) {
+                const xR = xRCorner + wR * dilationHeight;
+                if (xR < 0 || xR >= convInfo.inHeight) {
+                  continue;
+                }
+                const wOffset1 = wR * filter.strides[0];
+                const xOffset2 = xOffset1 + xR * x.strides[1];
+                for (let yC = 0; yC < convInfo.outWidth; ++yC) {
+                  const yOffset3 = yOffset2 + yC * y.strides[2];
+                  const xCCorner = yC * convInfo.strideWidth - padTop;
+                  for (let wC = 0; wC < filterWidth; ++wC) {
+                    const xC = xCCorner + wC * dilationWidth;
+                    if (xC < 0 || xC >= convInfo.inWidth) {
+                      continue;
+                    }
+                    const wOffset2 = wOffset1 + wC * filter.strides[1];
+                    const xOffset3 = xOffset2 + xC * convInfo.inChannels;
+                    let yOffset4 = yOffset3;
+                    let wOffset3 = wOffset2;
+                    for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {
+                      const xVal = xVals[xOffset3 + d1];
+                      for (let q = 0; q < chMul; ++q) {
+                        yVals[yOffset4 + q] += xVal * wVals[wOffset3 + q];
+                      }
+                      yOffset4 += chMul;
+                      wOffset3 += chMul;
+                    }
+                  }
+                }
+              }
+            }
+          }
+          return y.toTensor();
+        }
+        depthwiseConv2DDerInput(dy, filter, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([dy, filter], "depthwiseConv2DDerInput");
+          const dx = dist["buffer"](convInfo.inShape, "float32");
+          const dxValues = dx.values;
+          const [dxS0, dxS1, dxS2] = dx.strides;
+          const dyValues = this.readSync(dy.dataId);
+          const [dyS0, dyS1, dyS2] = dy.strides;
+          const fltValues = this.readSync(filter.dataId);
+          const [fltS0, fltS1, fltS2] = filter.strides;
+          const {
+            batchSize,
+            filterHeight,
+            filterWidth,
+            inChannels,
+            inHeight,
+            inWidth,
+            outChannels,
+            outHeight,
+            outWidth,
+            strideHeight,
+            strideWidth,
+          } = convInfo;
+          const topPad = filterHeight - 1 - convInfo.padInfo.top;
+          const leftPad = filterWidth - 1 - convInfo.padInfo.left;
+          const chMul = outChannels / inChannels;
+          for (let b = 0; b < batchSize; ++b) {
+            for (let d1 = 0; d1 < inChannels; ++d1) {
+              for (let xR = 0; xR < inHeight; ++xR) {
+                const xRCorner = xR - topPad;
+                const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));
+                const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);
+                for (let xC = 0; xC < inWidth; ++xC) {
+                  const xCCorner = xC - leftPad;
+                  const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));
+                  const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);
+                  let dotProd = 0;
+                  for (let yR = xRMin; yR < yRMax; ++yR) {
+                    const wR = yR * strideHeight - xRCorner;
+                    for (let yC = xCMin; yC < yCMax; ++yC) {
+                      const wC = yC * strideWidth - xCCorner;
+                      const dyOffset = dyS0 * b + dyS1 * yR + dyS2 * yC;
+                      const fltOffset =
+                        fltS0 * (filterHeight - 1 - wR) +
+                        fltS1 * (filterWidth - 1 - wC) +
+                        fltS2 * d1;
+                      for (let dm = 0; dm < chMul; ++dm) {
+                        const d2 = d1 * chMul + dm;
+                        const pixel = dyValues[dyOffset + d2];
+                        const weight = fltValues[fltOffset + dm];
+                        dotProd += pixel * weight;
+                      }
+                    }
+                  }
+                  dxValues[dxS0 * b + dxS1 * xR + dxS2 * xC + d1] = dotProd;
+                }
+              }
+            }
+          }
+          return dx.toTensor();
+        }
+        depthwiseConv2DDerFilter(x, dy, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([x, dy], "depthwiseConv2DDerFilter");
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const dW = dist["buffer"](convInfo.filterShape, "float32");
+          const leftPad = convInfo.padInfo.left;
+          const topPad = convInfo.padInfo.top;
+          const chMul = convInfo.outChannels / convInfo.inChannels;
+          const xBuf = this.bufferSync(x);
+          const dyBuf = this.bufferSync(dy);
+          for (let wR = 0; wR < filterHeight; ++wR) {
+            const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));
+            const yRMax = Math.min(
+              convInfo.outHeight,
+              (convInfo.inHeight + topPad - wR) / strideHeight
+            );
+            for (let wC = 0; wC < filterWidth; ++wC) {
+              const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));
+              const yCMax = Math.min(
+                convInfo.outWidth,
+                (convInfo.inWidth + leftPad - wC) / strideWidth
+              );
+              for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {
+                const d1 = Math.trunc(d2 / chMul);
+                const dm = d2 % chMul;
+                let dotProd = 0;
+                for (let b = 0; b < convInfo.batchSize; ++b) {
+                  for (let yR = yRMin; yR < yRMax; ++yR) {
+                    const xR = wR + yR * strideHeight - topPad;
+                    for (let yC = yCMin; yC < yCMax; ++yC) {
+                      const xC = wC + yC * strideWidth - leftPad;
+                      dotProd += xBuf.get(b, xR, xC, d1) * dyBuf.get(b, yR, yC, d2);
+                    }
+                  }
+                }
+                dW.set(dotProd, wR, wC, d1, dm);
+              }
+            }
+          }
+          return dW.toTensor();
+        }
+        tile(x, reps) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "tile");
+          return tile(this.bufferSync(x), reps);
+        }
+        pad(x, paddings, constantValue) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "pad");
+          const outShape = paddings.map(
+            (p, i) => p[0] /* beforePad */ + x.shape[i] + p[1] /* afterPad */
+          );
+          const start = paddings.map((p) => p[0]);
+          const xBuffer = this.bufferSync(x);
+          const buffer = dist["buffer"](outShape, x.dtype);
+          if (constantValue !== 0) {
+            buffer.values.fill(constantValue);
+          }
+          for (let i = 0; i < x.size; i++) {
+            const coords = xBuffer.indexToLoc(i);
+            const outCoords = coords.map((c, i) => c + start[i]);
+            buffer.set(xBuffer.get(...coords), ...outCoords);
+          }
+          return buffer.toTensor();
+        }
+        gather(x, indices, axis) {
+          Object(cpu_util["a" /* assertNotComplex */])([x, indices], "gather");
+          const newShape = x.shape.slice();
+          const indicesValues = this.readSync(indices.dataId);
+          newShape[axis] = indicesValues.length;
+          const result = dist["buffer"](newShape, x.dtype);
+          const xBuf = this.bufferSync(x);
+          for (let i = 0; i < result.size; ++i) {
+            const newLoc = result.indexToLoc(i);
+            const originalLoc = newLoc.slice();
+            originalLoc[axis] = indicesValues[newLoc[axis]];
+            const originalIndex = xBuf.locToIndex(originalLoc);
+            result.values[i] = xBuf.values[originalIndex];
+          }
+          return result.toTensor();
+        }
+        batchToSpaceND(x, blockShape, crops) {
+          Object(cpu_util["a" /* assertNotComplex */])([x], "batchToSpaceND");
+          const prod = blockShape.reduce((a, b) => a * b);
+          const reshaped = dist["backend_util"].getReshaped(x.shape, blockShape, prod);
+          const permuted = dist["backend_util"].getPermuted(reshaped.length, blockShape.length);
+          const reshapedPermuted = dist["backend_util"].getReshapedPermuted(
+            x.shape,
+            blockShape,
+            prod
+          );
+          const sliceBeginCoords = dist["backend_util"].getSliceBeginCoords(
+            crops,
+            blockShape.length
+          );
+          const sliceSize = dist["backend_util"].getSliceSize(
+            reshapedPermuted,
+            crops,
+            blockShape.length
+          );
+          return dist["transpose"](x.reshape(reshaped), permuted)
+            .reshape(reshapedPermuted)
+            .slice(sliceBeginCoords, sliceSize);
+        }
+        spaceToBatchND(x, blockShape, paddings) {
+          Object(cpu_util["a" /* assertNotComplex */])([x], "spaceToBatchND");
+          const prod = blockShape.reduce((a, b) => a * b);
+          const completePaddings = [[0, 0]];
+          completePaddings.push(...paddings);
+          for (let i = 1 + blockShape.length; i < x.shape.length; ++i) {
+            completePaddings.push([0, 0]);
+          }
+          const paddedX = x.pad(completePaddings);
+          const reshapedPaddedShape = dist["backend_util"].getReshaped(
+            paddedX.shape,
+            blockShape,
+            prod,
+            false
+          );
+          const permutedReshapedPaddedPermutation = dist["backend_util"].getPermuted(
+            reshapedPaddedShape.length,
+            blockShape.length,
+            false
+          );
+          const flattenShape = dist["backend_util"].getReshapedPermuted(
+            paddedX.shape,
+            blockShape,
+            prod,
+            false
+          );
+          return dist["transpose"](
+            paddedX.reshape(reshapedPaddedShape),
+            permutedReshapedPaddedPermutation
+          ).reshape(flattenShape);
+        }
+        maxPool(x, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "maxPool");
+          const xValues = this.readSync(x.dataId);
+          return Object(pool_utils["b" /* pool */])(
+            xValues,
+            x.shape,
+            x.dtype,
+            x.strides,
+            convInfo,
+            "max"
+          ).toTensor();
+        }
+        maxPoolBackprop(dy, x, y, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([x, y], "maxPoolBackprop");
+          const xValues = this.readSync(x.dataId);
+          const maxPosBuf = Object(dist["buffer"])(
+            convInfo.outShape,
+            x.dtype,
+            Object(pool_utils["a" /* maxPoolPositions */])(xValues, x.shape, x.dtype, convInfo)
+              .values
+          );
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+          const dx = dist["buffer"](x.shape, "float32");
+          const dyBuf = this.bufferSync(dy);
+          for (let b = 0; b < convInfo.batchSize; ++b) {
+            for (let d = 0; d < convInfo.inChannels; ++d) {
+              for (let dxR = 0; dxR < convInfo.inHeight; ++dxR) {
+                for (let dxC = 0; dxC < convInfo.inWidth; ++dxC) {
+                  // Shader code begins.
+                  const dyRCorner = dxR - padTop;
+                  const dyCCorner = dxC - padLeft;
+                  let dotProd = 0;
+                  for (let wR = 0; wR < effectiveFilterHeight; wR += dilationHeight) {
+                    const dyR = (dyRCorner + wR) / strideHeight;
+                    if (dyR < 0 || dyR >= convInfo.outHeight || Math.floor(dyR) !== dyR) {
+                      continue;
+                    }
+                    for (let wC = 0; wC < effectiveFilterWidth; wC += dilationWidth) {
+                      const dyC = (dyCCorner + wC) / strideWidth;
+                      if (dyC < 0 || dyC >= convInfo.outWidth || Math.floor(dyC) !== dyC) {
+                        continue;
+                      }
+                      const maxPos =
+                        effectiveFilterHeight * effectiveFilterWidth -
+                        1 -
+                        maxPosBuf.get(b, dyR, dyC, d);
+                      const curPos = wR * effectiveFilterWidth + wC;
+                      const mask = maxPos === curPos ? 1 : 0;
+                      if (mask === 0) {
+                        continue;
+                      }
+                      const pixel = dyBuf.get(b, dyR, dyC, d);
+                      dotProd += pixel * mask;
+                    }
+                  }
+                  dx.set(dotProd, b, dxR, dxC, d);
+                }
+              }
+            }
+          }
+          return dx.toTensor();
+        }
+        avgPoolBackprop(dy, x, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([dy, x], "avgPoolBackprop");
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+          const dx = dist["buffer"](x.shape, "float32");
+          const avgMultiplier = 1 / (filterHeight * filterWidth);
+          const dyBuf = this.bufferSync(dy);
+          for (let b = 0; b < convInfo.batchSize; ++b) {
+            for (let d = 0; d < convInfo.inChannels; ++d) {
+              for (let dxR = 0; dxR < convInfo.inHeight; ++dxR) {
+                for (let dxC = 0; dxC < convInfo.inWidth; ++dxC) {
+                  // Shader code begins.
+                  const dyRCorner = dxR - padTop;
+                  const dyCCorner = dxC - padLeft;
+                  let dotProd = 0;
+                  for (let wR = 0; wR < effectiveFilterHeight; wR += dilationHeight) {
+                    const dyR = (dyRCorner + wR) / strideHeight;
+                    if (dyR < 0 || dyR >= convInfo.outHeight || Math.floor(dyR) !== dyR) {
+                      continue;
+                    }
+                    for (let wC = 0; wC < effectiveFilterWidth; wC += dilationWidth) {
+                      const dyC = (dyCCorner + wC) / strideWidth;
+                      if (dyC < 0 || dyC >= convInfo.outWidth || Math.floor(dyC) !== dyC) {
+                        continue;
+                      }
+                      const pixel = dyBuf.get(b, dyR, dyC, d);
+                      dotProd += pixel;
+                    }
+                  }
+                  dx.set(dotProd * avgMultiplier, b, dxR, dxC, d);
+                }
+              }
+            }
+          }
+          return dx.toTensor();
+        }
+        pool3d(x, convInfo, poolType) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "pool3d");
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padFront = convInfo.padInfo.front;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          const initialValue =
+            poolType === "max" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY;
+          const xValues = this.readSync(x.dataId);
+          const output = dist["buffer"](convInfo.outShape, x.dtype);
+          const outputVals = output.values;
+          const outputBatchStrides =
+            convInfo.outShape[1] *
+            convInfo.outShape[2] *
+            convInfo.outShape[3] *
+            convInfo.outShape[4];
+          const outputDepthStrides =
+            convInfo.outShape[2] * convInfo.outShape[3] * convInfo.outShape[4];
+          const outputRowStrides = convInfo.outShape[3] * convInfo.outShape[4];
+          const outputColStrides = convInfo.outShape[4];
+          for (let batch = 0; batch < convInfo.batchSize; ++batch) {
+            const outputBatchOffset = batch * outputBatchStrides;
+            const inputBatchOffset = batch * x.strides[0];
+            for (let channel = 0; channel < convInfo.inChannels; ++channel) {
+              for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {
+                const xDepthCorner = yDepth * strideDepth - padFront;
+                let xDepthMin = xDepthCorner;
+                while (xDepthMin < 0) {
+                  xDepthMin += dilationDepth;
+                }
+                const xDepthMax = Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);
+                const outputDepthOffset = outputBatchOffset + yDepth * outputDepthStrides;
+                for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {
+                  const xRowCorner = yRow * strideHeight - padTop;
+                  let xRowMin = xRowCorner;
+                  while (xRowMin < 0) {
+                    xRowMin += dilationHeight;
+                  }
+                  const xRowMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);
+                  const outputRowOffset = outputDepthOffset + yRow * outputRowStrides;
+                  for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {
+                    const xColCorner = yCol * strideWidth - padLeft;
+                    let xColMin = xColCorner;
+                    while (xColMin < 0) {
+                      xColMin += dilationWidth;
+                    }
+                    const xColMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);
+                    // Shader code begins
+                    const outputColOffset = outputRowOffset + yCol * outputColStrides;
+                    let minMaxValue = initialValue;
+                    let avgValue = 0;
+                    let count = 0;
+                    for (let xDepth = xDepthMin; xDepth < xDepthMax; xDepth += dilationDepth) {
+                      const xDepthOffset = inputBatchOffset + xDepth * x.strides[1];
+                      for (let xRow = xRowMin; xRow < xRowMax; xRow += dilationHeight) {
+                        const xRowOffset = xDepthOffset + xRow * x.strides[2];
+                        for (let xCol = xColMin; xCol < xColMax; xCol += dilationWidth) {
+                          const xColOffset = xRowOffset + xCol * x.strides[3];
+                          const pixel = xValues[xColOffset + channel];
+                          if (poolType === "max" && pixel > minMaxValue) {
+                            minMaxValue = pixel;
+                          } else if (poolType === "avg") {
+                            avgValue += pixel;
+                            count++;
+                          }
+                          if (isNaN(minMaxValue)) {
+                            break;
+                          }
+                        }
+                        if (isNaN(minMaxValue)) {
+                          break;
+                        }
+                      }
+                      if (isNaN(minMaxValue)) {
+                        break;
+                      }
+                    }
+                    const outputOffset = outputColOffset + channel;
+                    outputVals[outputOffset] = poolType === "avg" ? avgValue / count : minMaxValue;
+                  }
+                }
+              }
+            }
+          }
+          return output.toTensor();
+        }
+        avgPool3d(x, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "avgPool3d");
+          return this.pool3d(x, convInfo, "avg").toFloat();
+        }
+        avgPool3dBackprop(dy, x, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([dy, x], "avgPool3dBackprop");
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const filterDepth = convInfo.filterDepth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
+          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+          const dx = dist["buffer"](x.shape, "float32");
+          const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);
+          const dyBuf = this.bufferSync(dy);
+          for (let batch = 0; batch < convInfo.batchSize; ++batch) {
+            for (let channel = 0; channel < convInfo.inChannels; ++channel) {
+              for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {
+                for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {
+                  for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {
+                    // Shader code begins.
+                    const dyDepthCorner = dxDepth - padFront;
+                    const dyRowCorner = dxRow - padTop;
+                    const dyColCorner = dxCol - padLeft;
+                    let dotProd = 0;
+                    for (let wDepth = 0; wDepth < effectiveFilterDepth; wDepth += dilationDepth) {
+                      const dyDepth = (dyDepthCorner + wDepth) / strideDepth;
+                      if (
+                        dyDepth < 0 ||
+                        dyDepth >= convInfo.outDepth ||
+                        Math.floor(dyDepth) !== dyDepth
+                      ) {
+                        continue;
+                      }
+                      for (let wRow = 0; wRow < effectiveFilterHeight; wRow += dilationHeight) {
+                        const dyRow = (dyRowCorner + wRow) / strideHeight;
+                        if (
+                          dyRow < 0 ||
+                          dyRow >= convInfo.outHeight ||
+                          Math.floor(dyRow) !== dyRow
+                        ) {
+                          continue;
+                        }
+                        for (let wCol = 0; wCol < effectiveFilterWidth; wCol += dilationWidth) {
+                          const dyCol = (dyColCorner + wCol) / strideWidth;
+                          if (
+                            dyCol < 0 ||
+                            dyCol >= convInfo.outWidth ||
+                            Math.floor(dyCol) !== dyCol
+                          ) {
+                            continue;
+                          }
+                          const pixel = dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);
+                          dotProd += pixel;
+                        }
+                      }
+                    }
+                    dx.set(dotProd * avgMultiplier, batch, dxDepth, dxRow, dxCol, channel);
+                  }
+                }
+              }
+            }
+          }
+          return dx.toTensor();
+        }
+        maxPool3d(x, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "maxPool3d");
+          return this.pool3d(x, convInfo, "max").toFloat();
+        }
+        maxPool3dPositions(x, convInfo) {
+          const maxPositions = dist["buffer"](convInfo.outShape, "int32");
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padFront = convInfo.padInfo.front;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          const xBuf = this.bufferSync(x);
+          for (let batch = 0; batch < convInfo.batchSize; ++batch) {
+            for (let channel = 0; channel < convInfo.inChannels; ++channel) {
+              for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {
+                const xDepthCorner = yDepth * strideDepth - padFront;
+                let xDepthMin = xDepthCorner;
+                while (xDepthMin < 0) {
+                  xDepthMin += dilationDepth;
+                }
+                const xDepthMax = Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);
+                for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {
+                  const xRowCorner = yRow * strideHeight - padTop;
+                  let xRowMin = xRowCorner;
+                  while (xRowMin < 0) {
+                    xRowMin += dilationHeight;
+                  }
+                  const xRowMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);
+                  for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {
+                    const xColCorner = yCol * strideWidth - padLeft;
+                    let xColMin = xColCorner;
+                    while (xColMin < 0) {
+                      xColMin += dilationWidth;
+                    }
+                    const xColMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);
+                    // Shader code begins
+                    let maxValue = Number.NEGATIVE_INFINITY;
+                    let maxPosition = -1;
+                    for (let xDepth = xDepthMin; xDepth < xDepthMax; xDepth += dilationDepth) {
+                      const wDepth = xDepth - xDepthCorner;
+                      for (let xRow = xRowMin; xRow < xRowMax; xRow += dilationHeight) {
+                        const wRow = xRow - xRowCorner;
+                        for (let xCol = xColMin; xCol < xColMax; xCol += dilationWidth) {
+                          const wCol = xCol - xColCorner;
+                          const pixel = xBuf.get(batch, xDepth, xRow, xCol, channel);
+                          if (pixel >= maxValue) {
+                            maxValue = pixel;
+                            maxPosition =
+                              wDepth * effectiveFilterHeight * effectiveFilterWidth +
+                              wRow * effectiveFilterHeight +
+                              wCol;
+                          }
+                        }
+                      }
+                    }
+                    maxPositions.set(maxPosition, batch, yDepth, yRow, yCol, channel);
+                  }
+                }
+              }
+            }
+          }
+          return maxPositions.toTensor();
+        }
+        maxPool3dBackprop(dy, x, y, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])([x, y], "maxPool3dBackprop");
+          const maxPositions = this.maxPool3dPositions(x, convInfo);
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
+          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+          const dx = dist["buffer"](x.shape, "float32");
+          const maxPosBuf = this.bufferSync(maxPositions);
+          const dyBuf = this.bufferSync(dy);
+          for (let batch = 0; batch < convInfo.batchSize; ++batch) {
+            for (let channel = 0; channel < convInfo.inChannels; ++channel) {
+              for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {
+                for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {
+                  for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {
+                    // Shader code begins
+                    const dyDepthCorner = dxDepth - padFront;
+                    const dyRowCorner = dxRow - padTop;
+                    const dyColCorner = dxCol - padLeft;
+                    let dotProd = 0;
+                    for (let wDepth = 0; wDepth < effectiveFilterDepth; wDepth += dilationDepth) {
+                      const dyDepth = (dyDepthCorner + wDepth) / strideDepth;
+                      if (
+                        dyDepth < 0 ||
+                        dyDepth >= convInfo.outDepth ||
+                        Math.floor(dyDepth) !== dyDepth
+                      ) {
+                        continue;
+                      }
+                      for (let wRow = 0; wRow < effectiveFilterHeight; wRow += dilationHeight) {
+                        const dyRow = (dyRowCorner + wRow) / strideHeight;
+                        if (
+                          dyRow < 0 ||
+                          dyRow >= convInfo.outHeight ||
+                          Math.floor(dyRow) !== dyRow
+                        ) {
+                          continue;
+                        }
+                        for (let wCol = 0; wCol < effectiveFilterWidth; wCol += dilationWidth) {
+                          const dyCol = (dyColCorner + wCol) / strideWidth;
+                          if (
+                            dyCol < 0 ||
+                            dyCol >= convInfo.outWidth ||
+                            Math.floor(dyCol) !== dyCol
+                          ) {
+                            continue;
+                          }
+                          const maxPos =
+                            effectiveFilterDepth * effectiveFilterHeight * effectiveFilterWidth -
+                            1 -
+                            maxPosBuf.get(batch, dyDepth, dyRow, dyCol, channel);
+                          const curPos =
+                            wDepth * effectiveFilterHeight * effectiveFilterWidth +
+                            wRow * effectiveFilterWidth +
+                            wCol;
+                          const mask = maxPos === curPos ? 1 : 0;
+                          if (mask === 0) {
+                            continue;
+                          }
+                          const pixel = dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);
+                          dotProd += pixel * mask;
+                        }
+                      }
+                    }
+                    dx.set(dotProd, batch, dxDepth, dxRow, dxCol, channel);
+                  }
+                }
+              }
+            }
+          }
+          return dx.toTensor();
+        }
+        cast(x, dtype) {
+          return dist["backend_util"].castTensor(x, dtype, this);
+        }
+        reshape(x, shape) {
+          return dist["backend_util"].reshapeTensor(x, shape);
+        }
+        avgPool(x, convInfo) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "avgPool");
+          Object(cpu_util["a" /* assertNotComplex */])(x, "maxPool");
+          const xValues = this.readSync(x.dataId);
+          return Object(pool_utils["b" /* pool */])(
+            xValues,
+            x.shape,
+            x.dtype,
+            x.strides,
+            convInfo,
+            "avg"
+          )
+            .toTensor()
+            .toFloat();
+        }
+        resizeBilinear(x, newHeight, newWidth, alignCorners) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "resizeBilinear");
+          const [batch, oldHeight, oldWidth, numChannels] = x.shape;
+          const xValues = this.readSync(x.dataId);
+          const result = new Float32Array(
+            dist["util"].sizeFromShape([batch, newHeight, newWidth, numChannels])
+          );
+          const effectiveInputSize = [
+            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
+            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
+          ];
+          const effectiveOutputSize = [
+            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
+            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
+          ];
+          let outputIdx = 0;
+          const effectiveRowSizeRatio = effectiveInputSize[0] / effectiveOutputSize[0];
+          const effectiveColSizeRatio = effectiveInputSize[1] / effectiveOutputSize[1];
+          for (let b = 0; b < batch; b++) {
+            for (let r = 0; r < newHeight; r++) {
+              const sourceFracRow = effectiveRowSizeRatio * r;
+              const sourceRowFloor = Math.floor(sourceFracRow);
+              const rowFrac = sourceFracRow - sourceRowFloor;
+              const sourceRowCeil = Math.min(oldHeight - 1, Math.ceil(sourceFracRow));
+              const topRowOffset = b * x.strides[0] + sourceRowFloor * x.strides[1];
+              const botRowOffset = b * x.strides[0] + sourceRowCeil * x.strides[1];
+              for (let c = 0; c < newWidth; c++) {
+                const sourceFracCol = effectiveColSizeRatio * c;
+                const sourceColFloor = Math.floor(sourceFracCol);
+                const colFrac = sourceFracCol - sourceColFloor;
+                const sourceColCeil = Math.min(oldWidth - 1, Math.ceil(sourceFracCol));
+                const topLeftOffest = topRowOffset + sourceColFloor * x.strides[2];
+                const botLeftOffset = botRowOffset + sourceColFloor * x.strides[2];
+                const topRightOffset = topRowOffset + sourceColCeil * x.strides[2];
+                const botRightOffest = botRowOffset + sourceColCeil * x.strides[2];
+                for (let d = 0; d < numChannels; d++) {
+                  // Begin shader.
+                  // Compute the fractional index of the source.
+                  const topLeft = xValues[topLeftOffest + d];
+                  const bottomLeft = xValues[botLeftOffset + d];
+                  const topRight = xValues[topRightOffset + d];
+                  const bottomRight = xValues[botRightOffest + d];
+                  const top = topLeft + (topRight - topLeft) * colFrac;
+                  const bottom = bottomLeft + (bottomRight - bottomLeft) * colFrac;
+                  const newValue = top + (bottom - top) * rowFrac;
+                  result[outputIdx++] = newValue;
+                }
+              }
+            }
+          }
+          return dist["tensor"](result, [batch, newHeight, newWidth, numChannels]);
+        }
+        resizeBilinearBackprop(dy, x, alignCorners) {
+          Object(cpu_util["a" /* assertNotComplex */])([dy, x], "resizeBilinearBackprop");
+          const [batch, xHeight, xWidth, depth] = x.shape;
+          const [, yHeight, yWidth] = dy.shape;
+          const output = new Float32Array(batch * xHeight * xWidth * depth);
+          // In the backwards pass, we want to find the pixels that were generated
+          // for each pixel in the input image the forward pass and add the
+          // corresponding coefficient from dy to the gradient (with some
+          // interpolation).
+          const effectiveXSize = [
+            alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,
+            alignCorners && yWidth > 1 ? xWidth - 1 : xWidth,
+          ];
+          const effectiveYSize = [
+            alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,
+            alignCorners && yWidth > 1 ? yWidth - 1 : yWidth,
+          ];
+          const heightScale = effectiveXSize[0] / effectiveYSize[0];
+          const widthScale = effectiveXSize[1] / effectiveYSize[1];
+          // Reference implementation
+          // tslint:disable-next-line:max-line-length
+          // https://github.com/tensorflow/tensorflow/blob/3039375c86a5bbc9610c7725dcaa95d635f87ba2/tensorflow/core/kernels/resize_bilinear_op.cc#L275
+          const dyValues = this.readSync(dy.dataId);
+          let offset = 0;
+          for (let b = 0; b < batch; b++) {
+            const bOffset = b * x.strides[0];
+            for (let r = 0; r < yHeight; r++) {
+              const dxR = r * heightScale;
+              const topDxRIndex = Math.floor(dxR);
+              const bottomDxRIndex = Math.min(Math.ceil(dxR), xHeight - 1);
+              const topDxROffset = bOffset + topDxRIndex * x.strides[1];
+              const bottomDxROffset = bOffset + bottomDxRIndex * x.strides[1];
+              const dxRLerp = dxR - topDxRIndex;
+              const inverseDxRLerp = 1.0 - dxRLerp;
+              for (let c = 0; c < yWidth; c++) {
+                const dxC = c * widthScale;
+                const leftDxCIndex = Math.floor(dxC);
+                const rightDxCIndex = Math.min(Math.ceil(dxC), xWidth - 1);
+                const dxCLerp = dxC - leftDxCIndex;
+                const inverseDxCLerp = 1.0 - dxCLerp;
+                const topLeftRCOffset = topDxROffset + leftDxCIndex * x.strides[2];
+                const topRightRCOffset = topDxROffset + rightDxCIndex * x.strides[2];
+                const bottomLeftRCOffset = bottomDxROffset + leftDxCIndex * x.strides[2];
+                const bottomRightRCOffset = bottomDxROffset + rightDxCIndex * x.strides[2];
+                const inverseDxRLerpTimesInverseDxCLerp = inverseDxRLerp * inverseDxCLerp;
+                const inverseDxRLerpTimesDxCLerp = inverseDxRLerp * dxCLerp;
+                const dxRLerpTimesInverseDxCLerp = dxRLerp * inverseDxCLerp;
+                const dxRLerpTimesDxCLerp = dxRLerp * dxCLerp;
+                for (let d = 0; d < depth; d++) {
+                  const dyVal = dyValues[offset++];
+                  output[topLeftRCOffset + d] += dyVal * inverseDxRLerpTimesInverseDxCLerp;
+                  output[topRightRCOffset + d] += dyVal * inverseDxRLerpTimesDxCLerp;
+                  output[bottomLeftRCOffset + d] += dyVal * dxRLerpTimesInverseDxCLerp;
+                  output[bottomRightRCOffset + d] += dyVal * dxRLerpTimesDxCLerp;
+                }
+              }
+            }
+          }
+          return dist["tensor4d"](output, [batch, xWidth, xHeight, depth], x.dtype);
+        }
+        resizeNearestNeighbor(x, newHeight, newWidth, alignCorners) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "resizeNearestNeighbor");
+          const [batch, oldHeight, oldWidth, numChannels] = x.shape;
+          const xValues = this.readSync(x.dataId);
+          const output = new Float32Array(batch * newHeight * newWidth * numChannels);
+          const effectiveInputSize = [
+            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
+            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
+          ];
+          const effectiveOutputSize = [
+            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
+            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
+          ];
+          const effectiveRowSizeRatio = effectiveInputSize[0] / effectiveOutputSize[0];
+          const effectiveColSizeRatio = effectiveInputSize[1] / effectiveOutputSize[1];
+          let outputOffset = 0;
+          for (let b = 0; b < batch; b++) {
+            const batchOffset = b * x.strides[0];
+            for (let r = 0; r < newHeight; r++) {
+              const sourceFracRow = effectiveRowSizeRatio * r;
+              const sourceNearestRow = Math.min(
+                oldHeight - 1,
+                alignCorners ? Math.round(sourceFracRow) : Math.floor(sourceFracRow)
+              );
+              const rowOffset = batchOffset + sourceNearestRow * x.strides[1];
+              for (let c = 0; c < newWidth; c++) {
+                const sourceFracCol = effectiveColSizeRatio * c;
+                const sourceNearestCol = Math.min(
+                  oldWidth - 1,
+                  alignCorners ? Math.round(sourceFracCol) : Math.floor(sourceFracCol)
+                );
+                const colOffset = rowOffset + sourceNearestCol * x.strides[2];
+                for (let d = 0; d < numChannels; d++) {
+                  // Begin shader.
+                  // Compute the fractional index of the source.
+                  const newVal = xValues[colOffset + d];
+                  output[outputOffset++] = newVal;
+                }
+              }
+            }
+          }
+          return dist["tensor"](output, [batch, newHeight, newWidth, numChannels], x.dtype);
+        }
+        resizeNearestNeighborBackprop(dy, x, alignCorners) {
+          Object(cpu_util["a" /* assertNotComplex */])([dy, x], "resizeNearestNeighborBackprop");
+          const [batch, xHeight, xWidth, depth] = x.shape;
+          const [, yHeight, yWidth] = dy.shape;
+          const output = new Float32Array(batch * xHeight * xWidth * depth);
+          const dyValues = this.readSync(dy.dataId);
+          // In the backwards pass, we want to find the pixels that were generated
+          // for each pixel in the input image the forward pass
+          const effectiveXSize = [
+            alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,
+            alignCorners && yWidth > 1 ? xWidth - 1 : xWidth,
+          ];
+          const effectiveYSize = [
+            alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,
+            alignCorners && yWidth > 1 ? yWidth - 1 : yWidth,
+          ];
+          const heightScale = effectiveXSize[0] / effectiveYSize[0];
+          const widthScale = effectiveXSize[1] / effectiveYSize[1];
+          const invHeightScale = 1 / heightScale;
+          const invWidthScale = 1 / widthScale;
+          // This defines the size of the window of values around a particular
+          // index in dy that we want to search for contributions to dx.
+          const winHeight = Math.ceil(invHeightScale) * 2 + 2;
+          const winWidth = Math.ceil(invWidthScale) * 2 + 2;
+          // Loop over the output space.
+          for (let b = 0; b < batch; b++) {
+            const batchOffset = b * x.strides[0];
+            for (let r = 0; r < xHeight; r++) {
+              const rowOffset = batchOffset + r * x.strides[1];
+              // Compute bounds for where in dy we will look
+              const startRLerp = Math.floor(r * invHeightScale);
+              const startDyR = Math.floor(startRLerp - winHeight / 2);
+              for (let c = 0; c < xWidth; c++) {
+                const colOffset = rowOffset + c * x.strides[2];
+                // Compute bounds for where in dy we will look
+                const startCLerp = Math.floor(c * invWidthScale);
+                const startDyC = Math.floor(startCLerp - winWidth / 2);
+                for (let d = 0; d < depth; d++) {
+                  let accum = 0;
+                  // loop over dy
+                  for (let dyRIndex = 0; dyRIndex < winHeight; dyRIndex++) {
+                    const dyR = dyRIndex + startDyR;
+                    // Guard against the window exceeding the bounds of dy
+                    if (dyR < 0 || dyR >= yHeight) {
+                      continue;
+                    }
+                    const dyROffset = batchOffset + dyR * dy.strides[1];
+                    const sourceFracRow = dyR * heightScale;
+                    const sourceNearestRow = Math.min(
+                      xHeight - 1,
+                      alignCorners ? Math.round(sourceFracRow) : Math.floor(sourceFracRow)
+                    );
+                    if (r !== sourceNearestRow) {
+                      continue;
+                    }
+                    for (let dyCIndex = 0; dyCIndex < winWidth; dyCIndex++) {
+                      const dyC = dyCIndex + startDyC;
+                      // Guard against the window exceeding the bounds of dy
+                      if (dyC < 0 || dyC >= yWidth) {
+                        continue;
+                      }
+                      const dyCOffset = dyROffset + dyC * dy.strides[2];
+                      const sourceFracCol = dyC * widthScale;
+                      const sourceNearestCol = Math.min(
+                        xWidth - 1,
+                        alignCorners ? Math.round(sourceFracCol) : Math.floor(sourceFracCol)
+                      );
+                      if (c === sourceNearestCol) {
+                        accum += dyValues[dyCOffset + d];
+                      }
+                    }
+                  }
+                  output[colOffset + d] = accum;
+                }
+              }
+            }
+          }
+          return dist["tensor4d"](output, x.shape, x.dtype);
+        }
+        batchNorm(x, mean, variance, offset, scale, varianceEpsilon) {
+          Object(cpu_util["a" /* assertNotComplex */])(
+            [x, mean, variance, scale, offset],
+            "batchNorm"
+          );
+          const xVals = this.readSync(x.dataId);
+          const mVals = this.readSync(mean.dataId);
+          const varVals = this.readSync(variance.dataId);
+          const sVals = scale ? this.readSync(scale.dataId) : new Float32Array([1]);
+          const offVals = offset ? this.readSync(offset.dataId) : new Float32Array([0]);
+          const outVals = new Float32Array(xVals.length);
+          const offValsLength = offVals.length;
+          const sValsLength = sVals.length;
+          const varValsLength = varVals.length;
+          const mValsLength = mVals.length;
+          let offi = 0;
+          let mi = 0;
+          let si = 0;
+          let vi = 0;
+          for (let i = 0; i < xVals.length; ++i) {
+            outVals[i] =
+              offVals[offi++] +
+              ((xVals[i] - mVals[mi++]) * sVals[si++]) / Math.sqrt(varVals[vi++] + varianceEpsilon);
+            if (offi >= offValsLength) {
+              offi = 0;
+            }
+            if (mi >= mValsLength) {
+              mi = 0;
+            }
+            if (si >= sValsLength) {
+              si = 0;
+            }
+            if (vi >= varValsLength) {
+              vi = 0;
+            }
+          }
+          return dist["tensor4d"](outVals, x.shape);
+        }
+        localResponseNormalization4D(x, depthRadius, bias, alpha, beta) {
+          Object(cpu_util["a" /* assertNotComplex */])(x, "localResponseNormalization4D");
+          const channels = x.shape[3];
+          const maxD = channels - 1;
+          const xValues = this.readSync(x.dataId);
+          const size = x.size;
+          const result = new Float32Array(size);
+          function sumAcrossChannels(offset) {
+            const currentChannel = offset % channels;
+            let beginSumOffset =
+              offset - currentChannel + Math.max(0, currentChannel - depthRadius);
+            const endSumOffset =
+              offset - currentChannel + Math.min(currentChannel + depthRadius, maxD);
+            let sum = 0.0;
+            for (; beginSumOffset <= endSumOffset; beginSumOffset++) {
+              const z = xValues[beginSumOffset];
+              sum += z * z;
+            }
+            return sum;
+          }
+          for (let offset = 0; offset < size; offset++) {
+            const sum = sumAcrossChannels(offset);
+            const val = xValues[offset] * Math.pow(bias + alpha * sum, -beta);
+            result[offset] = val;
+          }
+          return dist["tensor4d"](result, x.shape);
+        }
+        LRNGrad(dy, inputImage, outputImage, depthRadius, bias, alpha, beta) {
+          Object(cpu_util["a" /* assertNotComplex */])(dy, "LRNGrad");
+          const channels = dy.shape[3];
+          const dyValues = this.readSync(dy.dataId);
+          const inputImageValues = this.readSync(inputImage.dataId);
+          const outputImageValues = this.readSync(outputImage.dataId);
+          const result = new Float32Array(dy.size);
+          const size = dy.size;
+          for (let offset = 0; offset < size; offset++) {
+            const currentChannel = offset % channels;
+            const depthBegin = offset - currentChannel + Math.max(0, currentChannel - depthRadius);
+            const depthEnd =
+              offset - currentChannel + Math.min(channels, currentChannel + depthRadius + 1);
+            let norm = 0;
+            for (let k = depthBegin; k < depthEnd; k++) {
+              norm += Math.pow(inputImageValues[k], 2);
+            }
+            norm = alpha * norm + bias;
+            for (let k = depthBegin; k < depthEnd; k++) {
+              let dyi =
+                (-2 * alpha * beta * inputImageValues[k] * outputImageValues[offset]) / norm;
+              if (offset === k) {
+                dyi += Math.pow(norm, -beta);
+              }
+              dyi *= dyValues[offset];
+              result[k] += dyi;
+            }
+          }
+          return dist["tensor4d"](result, dy.shape);
+        }
+        multinomial(logits, normalized, numSamples, seed) {
+          Object(cpu_util["a" /* assertNotComplex */])(logits, "multinomial");
+          const probabilities = normalized ? logits : dist["softmax"](logits);
+          const batchSize = probabilities.shape[0];
+          const numEvents = probabilities.shape[1];
+          const res = dist["zeros"]([batchSize, numSamples], "int32");
+          const resVals = this.readSync(res.dataId);
+          const probVals = this.readSync(probabilities.dataId);
+          for (let b = 0; b < batchSize; ++b) {
+            const offset = b * numEvents;
+            // The cdf won't include the last event. It will be implicit if no other
+            // event happened.
+            const cdf = new Float32Array(numEvents - 1);
+            cdf[0] = probVals[offset];
+            for (let event = 1; event < cdf.length; ++event) {
+              cdf[event] = cdf[event - 1] + probVals[offset + event];
+            }
+            const random = seedrandom["alea"](seed.toString());
+            const outOffset = b * numSamples;
+            for (let sampleId = 0; sampleId < numSamples; ++sampleId) {
+              const r = random();
+              // Assume last event happened by default.
+              resVals[outOffset + sampleId] = cdf.length;
+              for (let event = 0; event < cdf.length; event++) {
+                if (r < cdf[event]) {
+                  resVals[outOffset + sampleId] = event;
+                  break;
+                }
+              }
+            }
+          }
+          return res;
+        }
+        oneHot(indices, depth, onValue, offValue) {
+          Object(cpu_util["a" /* assertNotComplex */])(indices, "oneHot");
+          const res = new Float32Array(indices.size * depth);
+          res.fill(offValue);
+          const indicesVal = this.readSync(indices.dataId);
+          for (let event = 0; event < indices.size; ++event) {
+            if (indicesVal[event] >= 0 && indicesVal[event] < depth) {
+              res[event * depth + indicesVal[event]] = onValue;
+            }
+          }
+          return dist["tensor2d"](res, [indices.size, depth], "int32");
+        }
+        nonMaxSuppression(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold) {
+          Object(cpu_util["a" /* assertNotComplex */])(boxes, "nonMaxSuppression");
+          const boxesVals = this.readSync(boxes.dataId);
+          const scoresVals = this.readSync(scores.dataId);
+          return nonMaxSuppressionV3(
+            boxesVals,
+            scoresVals,
+            maxOutputSize,
+            iouThreshold,
+            scoreThreshold
+          );
+        }
+        fft(x) {
+          return this.fftBatch(x, false);
+        }
+        ifft(x) {
+          return this.fftBatch(x, true);
+        }
+        /**
+         * Calculate FFT of inner most elements of batch tensor.
+         */
+        fftBatch(x, inverse) {
+          const batch = x.shape[0];
+          const innerDim = x.shape[1];
+          // Collects real and imaginary values separately.
+          const realResult = dist["buffer"](x.shape, "float32");
+          const imagResult = dist["buffer"](x.shape, "float32");
+          const real = dist["real"](x).as2D(batch, innerDim);
+          const imag = dist["imag"](x).as2D(batch, innerDim);
+          for (let b = 0; b < batch; b++) {
+            // TODO: Support slice ops for complex type.
+            const r = real.slice([b, 0], [1, innerDim]);
+            const i = imag.slice([b, 0], [1, innerDim]);
+            const input = dist["complex"](r, i);
+            // Run FFT by batch element.
+            const res = this.readSync(this.fftImpl(input, inverse).dataId);
+            for (let d = 0; d < innerDim; d++) {
+              const c = dist["backend_util"].getComplexWithIndex(res, d);
+              realResult.values[b * innerDim + d] = c.real;
+              imagResult.values[b * innerDim + d] = c.imag;
+            }
+          }
+          const t = dist["complex"](realResult.toTensor(), imagResult.toTensor());
+          return t.as2D(batch, innerDim);
+        }
+        fftImpl(x, inverse) {
+          const x1D = x.as1D();
+          const n = x1D.size;
+          if (this.isExponentOf2(n)) {
+            let result = this.fftRadix2(x1D, n, inverse).as2D(x.shape[0], x.shape[1]);
+            if (inverse) {
+              result = dist["complex"](
+                dist["real"](result).div(dist["scalar"](n)),
+                dist["imag"](result).div(dist["scalar"](n))
+              );
+            }
+            return result;
+          } else {
+            const data = this.readSync(x.dataId);
+            const rawOutput = this.fourierTransformByMatmul(data, n, inverse);
+            const output = dist["backend_util"].splitRealAndImagArrays(rawOutput);
+            return dist["complex"](output.real, output.imag).as2D(x.shape[0], x.shape[1]);
+          }
+        }
+        isExponentOf2(size) {
+          return (size & (size - 1)) === 0;
+        }
+        // FFT using Cooley-Tukey algorithm on radix 2 dimensional input.
+        fftRadix2(input, size, inverse) {
+          if (size === 1) {
+            return input;
+          }
+          const data = this.readSync(input.dataId);
+          const half = size / 2;
+          const evenComplex = dist["backend_util"].complexWithEvenIndex(data);
+          let evenTensor = dist["complex"](evenComplex.real, evenComplex.imag).as1D();
+          const oddComplex = dist["backend_util"].complexWithOddIndex(data);
+          let oddTensor = dist["complex"](oddComplex.real, oddComplex.imag).as1D();
+          // Recursive call for half part of original input.
+          evenTensor = this.fftRadix2(evenTensor, half, inverse);
+          oddTensor = this.fftRadix2(oddTensor, half, inverse);
+          const e = dist["backend_util"].exponents(size, inverse);
+          const exponent = dist["complex"](e.real, e.imag).mul(oddTensor);
+          const addPart = evenTensor.add(exponent);
+          const subPart = evenTensor.sub(exponent);
+          const realTensor = dist["real"](addPart).concat(dist["real"](subPart));
+          const imagTensor = dist["imag"](addPart).concat(dist["imag"](subPart));
+          return dist["complex"](realTensor, imagTensor).as1D();
+        }
+        // Calculate fourier transform by multplying sinusoid matrix.
+        fourierTransformByMatmul(data, size, inverse) {
+          const ret = new Float32Array(size * 2);
+          // TODO: Use matmul instead once it supports complex64 type.
+          for (let r = 0; r < size; r++) {
+            let real = 0.0;
+            let imag = 0.0;
+            for (let c = 0; c < size; c++) {
+              const e = dist["backend_util"].exponent(r * c, size, inverse);
+              const term = dist["backend_util"].getComplexWithIndex(data, c);
+              real += term.real * e.real - term.imag * e.imag;
+              imag += term.real * e.imag + term.imag * e.real;
+            }
+            if (inverse) {
+              real /= size;
+              imag /= size;
+            }
+            dist["backend_util"].assignToTypedArray(ret, real, imag, r);
+          }
+          return ret;
+        }
+        depthToSpace(x, blockSize, dataFormat) {
+          dist["util"].assert(
+            dataFormat === "NHWC",
+            () => `Only NHWC dataFormat supported on CPU for depthToSpace. Got ${dataFormat}`
+          );
+          dist["util"].assert(
+            blockSize > 1,
+            () => `blockSize should be > 1 for depthToSpace, but was: ${blockSize}`
+          );
+          const batchSize = x.shape[0];
+          const inputHeight = x.shape[1];
+          const inputWidth = x.shape[2];
+          const inputDepth = x.shape[3];
+          const outputHeight = inputHeight * blockSize;
+          const outputWidth = inputWidth * blockSize;
+          const outputDepth = inputDepth / (blockSize * blockSize);
+          const xValues = this.readSync(x.dataId);
+          const result = new Float32Array(batchSize * outputHeight * outputWidth * outputDepth);
+          let outputIdx = 0;
+          for (let b = 0; b < batchSize; ++b) {
+            for (let h = 0; h < outputHeight; ++h) {
+              const inH = Math.floor(h / blockSize);
+              const offsetH = h % blockSize;
+              for (let w = 0; w < outputWidth; ++w) {
+                const inW = Math.floor(w / blockSize);
+                const offsetW = w % blockSize;
+                const offsetD = (offsetH * blockSize + offsetW) * outputDepth;
+                for (let d = 0; d < outputDepth; ++d) {
+                  const inD = d + offsetD;
+                  const inputIdx = inD + inputDepth * (inW + inputWidth * (inH + inputHeight * b));
+                  result[outputIdx++] = xValues[inputIdx];
+                }
+              }
+            }
+          }
+          return dist["tensor4d"](result, [batchSize, outputHeight, outputWidth, outputDepth]);
+        }
+        broadcastedBinaryOp(a, b, dtype, op) {
+          const newShape = dist["backend_util"].assertAndGetBroadcastShape(a.shape, b.shape);
+          const result = dist["buffer"](newShape, dtype);
+          const aVals = this.readSync(a.dataId);
+          const bVals = this.readSync(b.dataId);
+          const aBroadcastDims = dist["backend_util"].getBroadcastDims(a.shape, newShape);
+          const bBroadcastDims = dist["backend_util"].getBroadcastDims(b.shape, newShape);
+          const resVals = result.values;
+          if (aBroadcastDims.length + bBroadcastDims.length === 0) {
+            for (let i = 0; i < resVals.length; ++i) {
+              resVals[i] = op(aVals[i % aVals.length], bVals[i % bVals.length]);
+            }
+          } else {
+            const aBuf = this.bufferSync(a);
+            const bBuf = this.bufferSync(b);
+            for (let i = 0; i < resVals.length; ++i) {
+              const loc = result.indexToLoc(i);
+              const aLoc = loc.slice(-a.rank);
+              aBroadcastDims.forEach((d) => (aLoc[d] = 0));
+              const aIndex = aBuf.locToIndex(aLoc);
+              const bLoc = loc.slice(-b.rank);
+              bBroadcastDims.forEach((d) => (bLoc[d] = 0));
+              const bIndex = bBuf.locToIndex(bLoc);
+              resVals[i] = op(aVals[aIndex], bVals[bIndex]);
+            }
+          }
+          return result.toTensor();
+        }
+        broadcastedBinaryComplexOp(a, b, op) {
+          const newShape = dist["backend_util"].assertAndGetBroadcastShape(a.shape, b.shape);
+          const realResult = dist["buffer"](newShape, "float32");
+          const imagResult = dist["buffer"](newShape, "float32");
+          const aVals = this.readSync(a.dataId);
+          const bVals = this.readSync(b.dataId);
+          const aBroadcastDims = dist["backend_util"].getBroadcastDims(a.shape, newShape);
+          const bBroadcastDims = dist["backend_util"].getBroadcastDims(b.shape, newShape);
+          const realVals = realResult.values;
+          const imagVals = imagResult.values;
+          if (aBroadcastDims.length + bBroadcastDims.length === 0) {
+            for (let i = 0; i < realVals.length; i++) {
+              const aIdx = i % aVals.length;
+              const bIdx = i % bVals.length;
+              const result = op(
+                aVals[aIdx * 2],
+                aVals[aIdx * 2 + 1],
+                bVals[bIdx * 2],
+                bVals[bIdx * 2 + 1]
+              );
+              realVals[i] = result.real;
+              imagVals[i] = result.imag;
+            }
+          } else {
+            const aRealBuf = this.bufferSync(this.data.get(a.dataId).complexTensors.real);
+            const bRealBuf = this.bufferSync(this.data.get(b.dataId).complexTensors.real);
+            for (let i = 0; i < realVals.length; i++) {
+              const loc = realResult.indexToLoc(i);
+              const aLoc = loc.slice(-a.rank);
+              aBroadcastDims.forEach((d) => (aLoc[d] = 0));
+              const aIndex = aRealBuf.locToIndex(aLoc);
+              const bLoc = loc.slice(-b.rank);
+              bBroadcastDims.forEach((d) => (bLoc[d] = 0));
+              const bIndex = bRealBuf.locToIndex(bLoc);
+              const opResult = op(
+                aVals[aIndex * 2],
+                aVals[aIndex * 2 + 1],
+                bVals[bIndex * 2],
+                bVals[bIndex * 2 + 1]
+              );
+              realVals[i] = opResult.real;
+              imagVals[i] = opResult.imag;
+            }
+          }
+          return this.complex(realResult.toTensor(), imagResult.toTensor());
+        }
+        split(x, sizeSplits, axis) {
+          return split(x, sizeSplits, axis);
+        }
+        dispose() {}
+        floatPrecision() {
+          return 32;
+        }
+        /** Returns the smallest representable number.  */
+        epsilon() {
+          return super.epsilon();
+        }
+        cropAndResize(images, boxes, boxIndex, cropSize, method, extrapolationValue) {
+          const [batch, imageHeight, imageWidth, numChannels] = images.shape;
+          const numBoxes = boxes.shape[0];
+          const [cropHeight, cropWidth] = cropSize;
+          const output = dist["buffer"]([numBoxes, cropHeight, cropWidth, numChannels], "float32");
+          const boxVals = this.readSync(boxes.dataId);
+          const boxIndVals = this.readSync(boxIndex.dataId);
+          const imageVals = this.readSync(images.dataId);
+          const inStride = images.strides; // to calculate flat indexes into image
+          const outStride = output.strides; // to calculate flat indexes into output
+          // Reference implementation
+          // tslint:disable-next-line:max-line-length
+          // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/crop_and_resize_op.cc
+          for (let b = 0; b < numBoxes; b++) {
+            const startInd = b * 4;
+            const y1 = boxVals[startInd];
+            const x1 = boxVals[startInd + 1];
+            const y2 = boxVals[startInd + 2];
+            const x2 = boxVals[startInd + 3];
+            const bInd = boxIndVals[b];
+            if (bInd >= batch) {
+              continue;
+            }
+            const heightScale =
+              cropHeight > 1 ? ((y2 - y1) * (imageHeight - 1)) / (cropHeight - 1) : 0;
+            const widthScale = cropWidth > 1 ? ((x2 - x1) * (imageWidth - 1)) / (cropWidth - 1) : 0;
+            for (let y = 0; y < cropHeight; y++) {
+              const yInd =
+                cropHeight > 1
+                  ? y1 * (imageHeight - 1) + y * heightScale
+                  : 0.5 * (y1 + y2) * (imageHeight - 1);
+              if (yInd < 0 || yInd > imageHeight - 1) {
+                for (let x = 0; x < cropWidth; x++) {
+                  for (let c = 0; c < numChannels; c++) {
+                    const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
+                    output.values[ind] = extrapolationValue;
+                  }
+                }
+                continue;
+              }
+              if (method === "bilinear") {
+                const topInd = Math.floor(yInd);
+                const bottomInd = Math.ceil(yInd);
+                const yLerp = yInd - topInd;
+                for (let x = 0; x < cropWidth; x++) {
+                  const xInd =
+                    cropWidth > 1
+                      ? x1 * (imageWidth - 1) + x * widthScale
+                      : 0.5 * (x1 + x2) * (imageWidth - 1);
+                  if (xInd < 0 || xInd > imageWidth - 1) {
+                    for (let c = 0; c < numChannels; c++) {
+                      const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
+                      output.values[ind] = extrapolationValue;
+                    }
+                    continue;
+                  }
+                  const leftInd = Math.floor(xInd);
+                  const rightInd = Math.ceil(xInd);
+                  const xLerp = xInd - leftInd;
+                  for (let c = 0; c < numChannels; c++) {
+                    let ind = c + leftInd * inStride[2] + topInd * inStride[1] + bInd * inStride[0];
+                    const topLeft = imageVals[ind];
+                    ind = c + rightInd * inStride[2] + topInd * inStride[1] + bInd * inStride[0];
+                    const topRight = imageVals[ind];
+                    ind = c + leftInd * inStride[2] + bottomInd * inStride[1] + bInd * inStride[0];
+                    const bottomLeft = imageVals[ind];
+                    ind = c + rightInd * inStride[2] + bottomInd * inStride[1] + bInd * inStride[0];
+                    const bottomRight = imageVals[ind];
+                    const top = topLeft + (topRight - topLeft) * xLerp;
+                    const bottom = bottomLeft + (bottomRight - bottomLeft) * xLerp;
+                    ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
+                    output.values[ind] = top + (bottom - top) * yLerp;
+                  }
+                }
+              } else {
+                // method == "nearest"
+                for (let x = 0; x < cropWidth; ++x) {
+                  const xInd =
+                    cropWidth > 1
+                      ? x1 * (imageWidth - 1) + x * widthScale
+                      : 0.5 * (x1 + x2) * (imageWidth - 1);
+                  if (xInd < 0 || xInd > imageWidth - 1) {
+                    for (let c = 0; c < numChannels; c++) {
+                      const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
+                      output.values[ind] = extrapolationValue;
+                    }
+                    continue;
+                  }
+                  const closestX = Math.round(xInd);
+                  const closestY = Math.round(yInd);
+                  for (let c = 0; c < numChannels; c++) {
+                    const inInd =
+                      c + closestX * inStride[2] + closestY * inStride[1] + bInd * inStride[0];
+                    const outInd = c + x * outStride[2] + y * outStride[1] + b * outStride[0];
+                    output.values[outInd] = imageVals[inInd];
+                  }
+                }
+              }
+            }
+          }
+          return output.toTensor();
+        }
+        sparseToDense(sparseIndices, sparseValues, outputShape, defaultValue) {
+          const { sliceRank, numUpdates, sliceSize, strides, outputSize } = dist[
+            "backend_util"
+          ].calculateShapes(sparseValues, sparseIndices, outputShape);
+          const sumDupeIndices = false;
+          return this.scatter(
+            sparseIndices,
+            sparseValues,
+            outputShape,
+            outputSize,
+            sliceSize,
+            numUpdates,
+            sliceRank,
+            strides,
+            defaultValue,
+            sumDupeIndices
+          );
+        }
+        gatherND(x, indices) {
+          const indicesShape = indices.shape;
+          const sliceRank = indicesShape[indicesShape.length - 1];
+          const [resultShape, numSlices, sliceSize, strides] = dist[
+            "backend_util"
+          ].prepareAndValidate(x, indices);
+          if (numSlices === 0) {
+            return dist["tensor"]([], resultShape, x.dtype);
+          }
+          const buffer = new dist["TensorBuffer"]([numSlices, sliceSize], x.dtype);
+          const indicesData = this.readSync(indices.dataId);
+          const xData = this.readSync(x.dataId);
+          for (let i = 0; i < numSlices; i++) {
+            const index = [];
+            let flattenIndex = 0;
+            for (let j = 0; j < sliceRank; j++) {
+              const dim = indicesData[i * sliceRank + j];
+              flattenIndex += dim * strides[j];
+              index.push(dim);
+            }
+            if (flattenIndex < 0 || flattenIndex >= x.size / sliceSize) {
+              throw new Error(`Invalid indices: ${index} does not index into ${x.shape}`);
+            }
+            for (let k = 0; k < sliceSize; k++) {
+              buffer.values[i * sliceSize + k] = xData[flattenIndex * sliceSize + k];
+            }
+          }
+          return buffer.toTensor().reshape(resultShape);
+        }
+        scatterND(indices, updates, shape) {
+          const { sliceRank, numUpdates, sliceSize, strides, outputSize } = dist[
+            "backend_util"
+          ].calculateShapes(updates, indices, shape);
+          const defaultValue = dist["scalar"](0);
+          const sumDupeIndices = true;
+          return this.scatter(
+            indices,
+            updates,
+            shape,
+            outputSize,
+            sliceSize,
+            numUpdates,
+            sliceRank,
+            strides,
+            defaultValue,
+            sumDupeIndices
+          );
+        }
+        fill(shape, value, dtype) {
+          dtype = dtype || dist["util"].inferDtype(value);
+          const values = dist["util"].getArrayFromDType(dtype, dist["util"].sizeFromShape(shape));
+          values.fill(value);
+          return Object(dist["engine"])().makeTensor(values, shape, dtype, this);
+        }
+        onesLike(x) {
+          if (x.dtype === "string") {
+            throw new Error("onesLike is not supported for string tensors");
+          } else {
+            return this.fill(x.shape, 1, x.dtype);
+          }
+        }
+        zerosLike(x) {
+          const values = dist["util"].getArrayFromDType(
+            x.dtype,
+            dist["util"].sizeFromShape(x.shape)
+          );
+          return this.makeOutput(values, x.shape, x.dtype);
+        }
+        linspace(start, stop, num) {
+          return dist["backend_util"].linspaceImpl(start, stop, num);
+        }
+        scatter(
+          indices,
+          updates,
+          shape,
+          outputSize,
+          sliceSize,
+          numUpdates,
+          sliceRank,
+          strides,
+          defaultValue,
+          sumDupeIndices
+        ) {
+          const flattenShape = [outputSize / sliceSize, sliceSize];
+          const indicesData = this.readSync(indices.dataId);
+          const updatesData = this.readSync(updates.dataId);
+          if (outputSize === 0) {
+            return dist["tensor"]([], shape, updates.dtype);
+          }
+          const buffer = new dist["TensorBuffer"](flattenShape, updates.dtype);
+          buffer.values.fill(this.readSync(defaultValue.dataId)[0]);
+          for (let i = 0; i < numUpdates; i++) {
+            const index = [];
+            let flattenIndex = 0;
+            for (let j = 0; j < sliceRank; j++) {
+              const dim = indicesData[i * sliceRank + j];
+              index.push(dim);
+              flattenIndex += dim * strides[j];
+            }
+            if (flattenIndex < 0 || flattenIndex >= outputSize / sliceSize) {
+              throw new Error(`Invalid indices: ${index} does not index into ${shape}`);
+            }
+            for (let k = 0; k < sliceSize; k++) {
+              if (sumDupeIndices) {
+                buffer.values[flattenIndex * sliceSize + k] += updatesData[i * sliceSize + k];
+              } else {
+                buffer.values[flattenIndex * sliceSize + k] =
+                  updates.rank === 0 ? updatesData[0] : updatesData[i * sliceSize + k];
+              }
+            }
+          }
+          return buffer.toTensor().reshape(shape);
+        }
+      }
+      //# sourceMappingURL=backend_cpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/version.js
+      /** @license See the LICENSE file. */
+      // This code is auto-generated, do not modify this file!
+      const version = "2.0.1";
+
+      //# sourceMappingURL=version.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/base.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /*
+       * base.ts contains all the exports from tfjs-backend-cpu
+       * that do not trigger side effects.
+       */
+
+      //# sourceMappingURL=base.js.map
+
+      /***/
+    },
+    /* 32 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (global) {
+        var require;
+        var require; /*!
+    localForage -- Offline Storage, Improved
+    Version 1.7.3
+    https://localforage.github.io/localForage
+    (c) 2013-2017 Mozilla, Apache License 2.0
+*/
+        (function (f) {
+          if (true) {
+            module.exports = f();
+          } else {
+            var g;
+          }
+        })(function () {
+          var define, module, exports;
+          return (function e(t, n, r) {
+            function s(o, u) {
+              if (!n[o]) {
+                if (!t[o]) {
+                  var a = typeof require == "function" && require;
+                  if (!u && a) return require(o, !0);
+                  if (i) return i(o, !0);
+                  var f = new Error("Cannot find module '" + o + "'");
+                  throw ((f.code = "MODULE_NOT_FOUND"), f);
+                }
+                var l = (n[o] = { exports: {} });
+                t[o][0].call(
+                  l.exports,
+                  function (e) {
+                    var n = t[o][1][e];
+                    return s(n ? n : e);
+                  },
+                  l,
+                  l.exports,
+                  e,
+                  t,
+                  n,
+                  r
+                );
+              }
+              return n[o].exports;
+            }
+            var i = typeof require == "function" && require;
+            for (var o = 0; o < r.length; o++) s(r[o]);
+            return s;
+          })(
+            {
+              1: [
+                function (_dereq_, module, exports) {
+                  (function (global) {
+                    "use strict";
+                    var Mutation = global.MutationObserver || global.WebKitMutationObserver;
+
+                    var scheduleDrain;
+
+                    {
+                      if (Mutation) {
+                        var called = 0;
+                        var observer = new Mutation(nextTick);
+                        var element = global.document.createTextNode("");
+                        observer.observe(element, {
+                          characterData: true,
+                        });
+                        scheduleDrain = function () {
+                          element.data = called = ++called % 2;
+                        };
+                      } else if (
+                        !global.setImmediate &&
+                        typeof global.MessageChannel !== "undefined"
+                      ) {
+                        var channel = new global.MessageChannel();
+                        channel.port1.onmessage = nextTick;
+                        scheduleDrain = function () {
+                          channel.port2.postMessage(0);
+                        };
+                      } else if (
+                        "document" in global &&
+                        "onreadystatechange" in global.document.createElement("script")
+                      ) {
+                        scheduleDrain = function () {
+                          // Create a <script> element; its readystatechange event will be fired asynchronously once it is inserted
+                          // into the document. Do so, thus queuing up the task. Remember to clean up once it's been called.
+                          var scriptEl = global.document.createElement("script");
+                          scriptEl.onreadystatechange = function () {
+                            nextTick();
+
+                            scriptEl.onreadystatechange = null;
+                            scriptEl.parentNode.removeChild(scriptEl);
+                            scriptEl = null;
+                          };
+                          global.document.documentElement.appendChild(scriptEl);
+                        };
+                      } else {
+                        scheduleDrain = function () {
+                          setTimeout(nextTick, 0);
+                        };
+                      }
+                    }
+
+                    var draining;
+                    var queue = [];
+                    //named nextTick for less confusing stack traces
+                    function nextTick() {
+                      draining = true;
+                      var i, oldQueue;
+                      var len = queue.length;
+                      while (len) {
+                        oldQueue = queue;
+                        queue = [];
+                        i = -1;
+                        while (++i < len) {
+                          oldQueue[i]();
+                        }
+                        len = queue.length;
+                      }
+                      draining = false;
+                    }
+
+                    module.exports = immediate;
+                    function immediate(task) {
+                      if (queue.push(task) === 1 && !draining) {
+                        scheduleDrain();
+                      }
+                    }
+                  }.call(
+                    this,
+                    typeof global !== "undefined"
+                      ? global
+                      : typeof self !== "undefined"
+                      ? self
+                      : typeof window !== "undefined"
+                      ? window
+                      : {}
+                  ));
+                },
+                {},
+              ],
+              2: [
+                function (_dereq_, module, exports) {
+                  "use strict";
+                  var immediate = _dereq_(1);
+
+                  /* istanbul ignore next */
+                  function INTERNAL() {}
+
+                  var handlers = {};
+
+                  var REJECTED = ["REJECTED"];
+                  var FULFILLED = ["FULFILLED"];
+                  var PENDING = ["PENDING"];
+
+                  module.exports = Promise;
+
+                  function Promise(resolver) {
+                    if (typeof resolver !== "function") {
+                      throw new TypeError("resolver must be a function");
+                    }
+                    this.state = PENDING;
+                    this.queue = [];
+                    this.outcome = void 0;
+                    if (resolver !== INTERNAL) {
+                      safelyResolveThenable(this, resolver);
+                    }
+                  }
+
+                  Promise.prototype["catch"] = function (onRejected) {
+                    return this.then(null, onRejected);
+                  };
+                  Promise.prototype.then = function (onFulfilled, onRejected) {
+                    if (
+                      (typeof onFulfilled !== "function" && this.state === FULFILLED) ||
+                      (typeof onRejected !== "function" && this.state === REJECTED)
+                    ) {
+                      return this;
+                    }
+                    var promise = new this.constructor(INTERNAL);
+                    if (this.state !== PENDING) {
+                      var resolver = this.state === FULFILLED ? onFulfilled : onRejected;
+                      unwrap(promise, resolver, this.outcome);
+                    } else {
+                      this.queue.push(new QueueItem(promise, onFulfilled, onRejected));
+                    }
+
+                    return promise;
+                  };
+                  function QueueItem(promise, onFulfilled, onRejected) {
+                    this.promise = promise;
+                    if (typeof onFulfilled === "function") {
+                      this.onFulfilled = onFulfilled;
+                      this.callFulfilled = this.otherCallFulfilled;
+                    }
+                    if (typeof onRejected === "function") {
+                      this.onRejected = onRejected;
+                      this.callRejected = this.otherCallRejected;
+                    }
+                  }
+                  QueueItem.prototype.callFulfilled = function (value) {
+                    handlers.resolve(this.promise, value);
+                  };
+                  QueueItem.prototype.otherCallFulfilled = function (value) {
+                    unwrap(this.promise, this.onFulfilled, value);
+                  };
+                  QueueItem.prototype.callRejected = function (value) {
+                    handlers.reject(this.promise, value);
+                  };
+                  QueueItem.prototype.otherCallRejected = function (value) {
+                    unwrap(this.promise, this.onRejected, value);
+                  };
+
+                  function unwrap(promise, func, value) {
+                    immediate(function () {
+                      var returnValue;
+                      try {
+                        returnValue = func(value);
+                      } catch (e) {
+                        return handlers.reject(promise, e);
+                      }
+                      if (returnValue === promise) {
+                        handlers.reject(
+                          promise,
+                          new TypeError("Cannot resolve promise with itself")
+                        );
+                      } else {
+                        handlers.resolve(promise, returnValue);
+                      }
+                    });
+                  }
+
+                  handlers.resolve = function (self, value) {
+                    var result = tryCatch(getThen, value);
+                    if (result.status === "error") {
+                      return handlers.reject(self, result.value);
+                    }
+                    var thenable = result.value;
+
+                    if (thenable) {
+                      safelyResolveThenable(self, thenable);
+                    } else {
+                      self.state = FULFILLED;
+                      self.outcome = value;
+                      var i = -1;
+                      var len = self.queue.length;
+                      while (++i < len) {
+                        self.queue[i].callFulfilled(value);
+                      }
+                    }
+                    return self;
+                  };
+                  handlers.reject = function (self, error) {
+                    self.state = REJECTED;
+                    self.outcome = error;
+                    var i = -1;
+                    var len = self.queue.length;
+                    while (++i < len) {
+                      self.queue[i].callRejected(error);
+                    }
+                    return self;
+                  };
+
+                  function getThen(obj) {
+                    // Make sure we only access the accessor once as required by the spec
+                    var then = obj && obj.then;
+                    if (
+                      obj &&
+                      (typeof obj === "object" || typeof obj === "function") &&
+                      typeof then === "function"
+                    ) {
+                      return function appyThen() {
+                        then.apply(obj, arguments);
+                      };
+                    }
+                  }
+
+                  function safelyResolveThenable(self, thenable) {
+                    // Either fulfill, reject or reject with error
+                    var called = false;
+                    function onError(value) {
+                      if (called) {
+                        return;
+                      }
+                      called = true;
+                      handlers.reject(self, value);
+                    }
+
+                    function onSuccess(value) {
+                      if (called) {
+                        return;
+                      }
+                      called = true;
+                      handlers.resolve(self, value);
+                    }
+
+                    function tryToUnwrap() {
+                      thenable(onSuccess, onError);
+                    }
+
+                    var result = tryCatch(tryToUnwrap);
+                    if (result.status === "error") {
+                      onError(result.value);
+                    }
+                  }
+
+                  function tryCatch(func, value) {
+                    var out = {};
+                    try {
+                      out.value = func(value);
+                      out.status = "success";
+                    } catch (e) {
+                      out.status = "error";
+                      out.value = e;
+                    }
+                    return out;
+                  }
+
+                  Promise.resolve = resolve;
+                  function resolve(value) {
+                    if (value instanceof this) {
+                      return value;
+                    }
+                    return handlers.resolve(new this(INTERNAL), value);
+                  }
+
+                  Promise.reject = reject;
+                  function reject(reason) {
+                    var promise = new this(INTERNAL);
+                    return handlers.reject(promise, reason);
+                  }
+
+                  Promise.all = all;
+                  function all(iterable) {
+                    var self = this;
+                    if (Object.prototype.toString.call(iterable) !== "[object Array]") {
+                      return this.reject(new TypeError("must be an array"));
+                    }
+
+                    var len = iterable.length;
+                    var called = false;
+                    if (!len) {
+                      return this.resolve([]);
+                    }
+
+                    var values = new Array(len);
+                    var resolved = 0;
+                    var i = -1;
+                    var promise = new this(INTERNAL);
+
+                    while (++i < len) {
+                      allResolver(iterable[i], i);
+                    }
+                    return promise;
+                    function allResolver(value, i) {
+                      self.resolve(value).then(resolveFromAll, function (error) {
+                        if (!called) {
+                          called = true;
+                          handlers.reject(promise, error);
+                        }
+                      });
+                      function resolveFromAll(outValue) {
+                        values[i] = outValue;
+                        if (++resolved === len && !called) {
+                          called = true;
+                          handlers.resolve(promise, values);
+                        }
+                      }
+                    }
+                  }
+
+                  Promise.race = race;
+                  function race(iterable) {
+                    var self = this;
+                    if (Object.prototype.toString.call(iterable) !== "[object Array]") {
+                      return this.reject(new TypeError("must be an array"));
+                    }
+
+                    var len = iterable.length;
+                    var called = false;
+                    if (!len) {
+                      return this.resolve([]);
+                    }
+
+                    var i = -1;
+                    var promise = new this(INTERNAL);
+
+                    while (++i < len) {
+                      resolver(iterable[i]);
+                    }
+                    return promise;
+                    function resolver(value) {
+                      self.resolve(value).then(
+                        function (response) {
+                          if (!called) {
+                            called = true;
+                            handlers.resolve(promise, response);
+                          }
+                        },
+                        function (error) {
+                          if (!called) {
+                            called = true;
+                            handlers.reject(promise, error);
+                          }
+                        }
+                      );
+                    }
+                  }
+                },
+                { 1: 1 },
+              ],
+              3: [
+                function (_dereq_, module, exports) {
+                  (function (global) {
+                    "use strict";
+                    if (typeof global.Promise !== "function") {
+                      global.Promise = _dereq_(2);
+                    }
+                  }.call(
+                    this,
+                    typeof global !== "undefined"
+                      ? global
+                      : typeof self !== "undefined"
+                      ? self
+                      : typeof window !== "undefined"
+                      ? window
+                      : {}
+                  ));
+                },
+                { 2: 2 },
+              ],
+              4: [
+                function (_dereq_, module, exports) {
+                  "use strict";
+
+                  var _typeof =
+                    typeof Symbol === "function" && typeof Symbol.iterator === "symbol"
+                      ? function (obj) {
+                          return typeof obj;
+                        }
+                      : function (obj) {
+                          return obj &&
+                            typeof Symbol === "function" &&
+                            obj.constructor === Symbol &&
+                            obj !== Symbol.prototype
+                            ? "symbol"
+                            : typeof obj;
+                        };
+
+                  function _classCallCheck(instance, Constructor) {
+                    if (!(instance instanceof Constructor)) {
+                      throw new TypeError("Cannot call a class as a function");
+                    }
+                  }
+
+                  function getIDB() {
+                    /* global indexedDB,webkitIndexedDB,mozIndexedDB,OIndexedDB,msIndexedDB */
+                    try {
+                      if (typeof indexedDB !== "undefined") {
+                        return indexedDB;
+                      }
+                      if (typeof webkitIndexedDB !== "undefined") {
+                        return webkitIndexedDB;
+                      }
+                      if (typeof mozIndexedDB !== "undefined") {
+                        return mozIndexedDB;
+                      }
+                      if (typeof OIndexedDB !== "undefined") {
+                        return OIndexedDB;
+                      }
+                      if (typeof msIndexedDB !== "undefined") {
+                        return msIndexedDB;
+                      }
+                    } catch (e) {
+                      return;
+                    }
+                  }
+
+                  var idb = getIDB();
+
+                  function isIndexedDBValid() {
+                    try {
+                      // Initialize IndexedDB; fall back to vendor-prefixed versions
+                      // if needed.
+                      if (!idb) {
+                        return false;
+                      }
+                      // We mimic PouchDB here;
+                      //
+                      // We test for openDatabase because IE Mobile identifies itself
+                      // as Safari. Oh the lulz...
+                      var isSafari =
+                        typeof openDatabase !== "undefined" &&
+                        /(Safari|iPhone|iPad|iPod)/.test(navigator.userAgent) &&
+                        !/Chrome/.test(navigator.userAgent) &&
+                        !/BlackBerry/.test(navigator.platform);
+
+                      var hasFetch =
+                        typeof fetch === "function" &&
+                        fetch.toString().indexOf("[native code") !== -1;
+
+                      // Safari <10.1 does not meet our requirements for IDB support (#5572)
+                      // since Safari 10.1 shipped with fetch, we can use that to detect it
+                      return (
+                        (!isSafari || hasFetch) &&
+                        typeof indexedDB !== "undefined" &&
+                        // some outdated implementations of IDB that appear on Samsung
+                        // and HTC Android devices <4.4 are missing IDBKeyRange
+                        // See: https://github.com/mozilla/localForage/issues/128
+                        // See: https://github.com/mozilla/localForage/issues/272
+                        typeof IDBKeyRange !== "undefined"
+                      );
+                    } catch (e) {
+                      return false;
+                    }
+                  }
+
+                  // Abstracts constructing a Blob object, so it also works in older
+                  // browsers that don't support the native Blob constructor. (i.e.
+                  // old QtWebKit versions, at least).
+                  // Abstracts constructing a Blob object, so it also works in older
+                  // browsers that don't support the native Blob constructor. (i.e.
+                  // old QtWebKit versions, at least).
+                  function createBlob(parts, properties) {
+                    /* global BlobBuilder,MSBlobBuilder,MozBlobBuilder,WebKitBlobBuilder */
+                    parts = parts || [];
+                    properties = properties || {};
+                    try {
+                      return new Blob(parts, properties);
+                    } catch (e) {
+                      if (e.name !== "TypeError") {
+                        throw e;
+                      }
+                      var Builder =
+                        typeof BlobBuilder !== "undefined"
+                          ? BlobBuilder
+                          : typeof MSBlobBuilder !== "undefined"
+                          ? MSBlobBuilder
+                          : typeof MozBlobBuilder !== "undefined"
+                          ? MozBlobBuilder
+                          : WebKitBlobBuilder;
+                      var builder = new Builder();
+                      for (var i = 0; i < parts.length; i += 1) {
+                        builder.append(parts[i]);
+                      }
+                      return builder.getBlob(properties.type);
+                    }
+                  }
+
+                  // This is CommonJS because lie is an external dependency, so Rollup
+                  // can just ignore it.
+                  if (typeof Promise === "undefined") {
+                    // In the "nopromises" build this will just throw if you don't have
+                    // a global promise object, but it would throw anyway later.
+                    _dereq_(3);
+                  }
+                  var Promise$1 = Promise;
+
+                  function executeCallback(promise, callback) {
+                    if (callback) {
+                      promise.then(
+                        function (result) {
+                          callback(null, result);
+                        },
+                        function (error) {
+                          callback(error);
+                        }
+                      );
+                    }
+                  }
+
+                  function executeTwoCallbacks(promise, callback, errorCallback) {
+                    if (typeof callback === "function") {
+                      promise.then(callback);
+                    }
+
+                    if (typeof errorCallback === "function") {
+                      promise["catch"](errorCallback);
+                    }
+                  }
+
+                  function normalizeKey(key) {
+                    // Cast the key to a string, as that's all we can set as a key.
+                    if (typeof key !== "string") {
+                      console.warn(key + " used as a key, but it is not a string.");
+                      key = String(key);
+                    }
+
+                    return key;
+                  }
+
+                  function getCallback() {
+                    if (arguments.length && typeof arguments[arguments.length - 1] === "function") {
+                      return arguments[arguments.length - 1];
+                    }
+                  }
+
+                  // Some code originally from async_storage.js in
+                  // [Gaia](https://github.com/mozilla-b2g/gaia).
+
+                  var DETECT_BLOB_SUPPORT_STORE = "local-forage-detect-blob-support";
+                  var supportsBlobs = void 0;
+                  var dbContexts = {};
+                  var toString = Object.prototype.toString;
+
+                  // Transaction Modes
+                  var READ_ONLY = "readonly";
+                  var READ_WRITE = "readwrite";
+
+                  // Transform a binary string to an array buffer, because otherwise
+                  // weird stuff happens when you try to work with the binary string directly.
+                  // It is known.
+                  // From http://stackoverflow.com/questions/14967647/ (continues on next line)
+                  // encode-decode-image-with-base64-breaks-image (2013-04-21)
+                  function _binStringToArrayBuffer(bin) {
+                    var length = bin.length;
+                    var buf = new ArrayBuffer(length);
+                    var arr = new Uint8Array(buf);
+                    for (var i = 0; i < length; i++) {
+                      arr[i] = bin.charCodeAt(i);
+                    }
+                    return buf;
+                  }
+
+                  //
+                  // Blobs are not supported in all versions of IndexedDB, notably
+                  // Chrome <37 and Android <5. In those versions, storing a blob will throw.
+                  //
+                  // Various other blob bugs exist in Chrome v37-42 (inclusive).
+                  // Detecting them is expensive and confusing to users, and Chrome 37-42
+                  // is at very low usage worldwide, so we do a hacky userAgent check instead.
+                  //
+                  // content-type bug: https://code.google.com/p/chromium/issues/detail?id=408120
+                  // 404 bug: https://code.google.com/p/chromium/issues/detail?id=447916
+                  // FileReader bug: https://code.google.com/p/chromium/issues/detail?id=447836
+                  //
+                  // Code borrowed from PouchDB. See:
+                  // https://github.com/pouchdb/pouchdb/blob/master/packages/node_modules/pouchdb-adapter-idb/src/blobSupport.js
+                  //
+                  function _checkBlobSupportWithoutCaching(idb) {
+                    return new Promise$1(function (resolve) {
+                      var txn = idb.transaction(DETECT_BLOB_SUPPORT_STORE, READ_WRITE);
+                      var blob = createBlob([""]);
+                      txn.objectStore(DETECT_BLOB_SUPPORT_STORE).put(blob, "key");
+
+                      txn.onabort = function (e) {
+                        // If the transaction aborts now its due to not being able to
+                        // write to the database, likely due to the disk being full
+                        e.preventDefault();
+                        e.stopPropagation();
+                        resolve(false);
+                      };
+
+                      txn.oncomplete = function () {
+                        var matchedChrome = navigator.userAgent.match(/Chrome\/(\d+)/);
+                        var matchedEdge = navigator.userAgent.match(/Edge\//);
+                        // MS Edge pretends to be Chrome 42:
+                        // https://msdn.microsoft.com/en-us/library/hh869301%28v=vs.85%29.aspx
+                        resolve(
+                          matchedEdge || !matchedChrome || parseInt(matchedChrome[1], 10) >= 43
+                        );
+                      };
+                    })["catch"](function () {
+                      return false; // error, so assume unsupported
+                    });
+                  }
+
+                  function _checkBlobSupport(idb) {
+                    if (typeof supportsBlobs === "boolean") {
+                      return Promise$1.resolve(supportsBlobs);
+                    }
+                    return _checkBlobSupportWithoutCaching(idb).then(function (value) {
+                      supportsBlobs = value;
+                      return supportsBlobs;
+                    });
+                  }
+
+                  function _deferReadiness(dbInfo) {
+                    var dbContext = dbContexts[dbInfo.name];
+
+                    // Create a deferred object representing the current database operation.
+                    var deferredOperation = {};
+
+                    deferredOperation.promise = new Promise$1(function (resolve, reject) {
+                      deferredOperation.resolve = resolve;
+                      deferredOperation.reject = reject;
+                    });
+
+                    // Enqueue the deferred operation.
+                    dbContext.deferredOperations.push(deferredOperation);
+
+                    // Chain its promise to the database readiness.
+                    if (!dbContext.dbReady) {
+                      dbContext.dbReady = deferredOperation.promise;
+                    } else {
+                      dbContext.dbReady = dbContext.dbReady.then(function () {
+                        return deferredOperation.promise;
+                      });
+                    }
+                  }
+
+                  function _advanceReadiness(dbInfo) {
+                    var dbContext = dbContexts[dbInfo.name];
+
+                    // Dequeue a deferred operation.
+                    var deferredOperation = dbContext.deferredOperations.pop();
+
+                    // Resolve its promise (which is part of the database readiness
+                    // chain of promises).
+                    if (deferredOperation) {
+                      deferredOperation.resolve();
+                      return deferredOperation.promise;
+                    }
+                  }
+
+                  function _rejectReadiness(dbInfo, err) {
+                    var dbContext = dbContexts[dbInfo.name];
+
+                    // Dequeue a deferred operation.
+                    var deferredOperation = dbContext.deferredOperations.pop();
+
+                    // Reject its promise (which is part of the database readiness
+                    // chain of promises).
+                    if (deferredOperation) {
+                      deferredOperation.reject(err);
+                      return deferredOperation.promise;
+                    }
+                  }
+
+                  function _getConnection(dbInfo, upgradeNeeded) {
+                    return new Promise$1(function (resolve, reject) {
+                      dbContexts[dbInfo.name] = dbContexts[dbInfo.name] || createDbContext();
+
+                      if (dbInfo.db) {
+                        if (upgradeNeeded) {
+                          _deferReadiness(dbInfo);
+                          dbInfo.db.close();
+                        } else {
+                          return resolve(dbInfo.db);
+                        }
+                      }
+
+                      var dbArgs = [dbInfo.name];
+
+                      if (upgradeNeeded) {
+                        dbArgs.push(dbInfo.version);
+                      }
+
+                      var openreq = idb.open.apply(idb, dbArgs);
+
+                      if (upgradeNeeded) {
+                        openreq.onupgradeneeded = function (e) {
+                          var db = openreq.result;
+                          try {
+                            db.createObjectStore(dbInfo.storeName);
+                            if (e.oldVersion <= 1) {
+                              // Added when support for blob shims was added
+                              db.createObjectStore(DETECT_BLOB_SUPPORT_STORE);
+                            }
+                          } catch (ex) {
+                            if (ex.name === "ConstraintError") {
+                              console.warn(
+                                'The database "' +
+                                  dbInfo.name +
+                                  '"' +
+                                  " has been upgraded from version " +
+                                  e.oldVersion +
+                                  " to version " +
+                                  e.newVersion +
+                                  ', but the storage "' +
+                                  dbInfo.storeName +
+                                  '" already exists.'
+                              );
+                            } else {
+                              throw ex;
+                            }
+                          }
+                        };
+                      }
+
+                      openreq.onerror = function (e) {
+                        e.preventDefault();
+                        reject(openreq.error);
+                      };
+
+                      openreq.onsuccess = function () {
+                        resolve(openreq.result);
+                        _advanceReadiness(dbInfo);
+                      };
+                    });
+                  }
+
+                  function _getOriginalConnection(dbInfo) {
+                    return _getConnection(dbInfo, false);
+                  }
+
+                  function _getUpgradedConnection(dbInfo) {
+                    return _getConnection(dbInfo, true);
+                  }
+
+                  function _isUpgradeNeeded(dbInfo, defaultVersion) {
+                    if (!dbInfo.db) {
+                      return true;
+                    }
+
+                    var isNewStore = !dbInfo.db.objectStoreNames.contains(dbInfo.storeName);
+                    var isDowngrade = dbInfo.version < dbInfo.db.version;
+                    var isUpgrade = dbInfo.version > dbInfo.db.version;
+
+                    if (isDowngrade) {
+                      // If the version is not the default one
+                      // then warn for impossible downgrade.
+                      if (dbInfo.version !== defaultVersion) {
+                        console.warn(
+                          'The database "' +
+                            dbInfo.name +
+                            '"' +
+                            " can't be downgraded from version " +
+                            dbInfo.db.version +
+                            " to version " +
+                            dbInfo.version +
+                            "."
+                        );
+                      }
+                      // Align the versions to prevent errors.
+                      dbInfo.version = dbInfo.db.version;
+                    }
+
+                    if (isUpgrade || isNewStore) {
+                      // If the store is new then increment the version (if needed).
+                      // This will trigger an "upgradeneeded" event which is required
+                      // for creating a store.
+                      if (isNewStore) {
+                        var incVersion = dbInfo.db.version + 1;
+                        if (incVersion > dbInfo.version) {
+                          dbInfo.version = incVersion;
+                        }
+                      }
+
+                      return true;
+                    }
+
+                    return false;
+                  }
+
+                  // encode a blob for indexeddb engines that don't support blobs
+                  function _encodeBlob(blob) {
+                    return new Promise$1(function (resolve, reject) {
+                      var reader = new FileReader();
+                      reader.onerror = reject;
+                      reader.onloadend = function (e) {
+                        var base64 = btoa(e.target.result || "");
+                        resolve({
+                          __local_forage_encoded_blob: true,
+                          data: base64,
+                          type: blob.type,
+                        });
+                      };
+                      reader.readAsBinaryString(blob);
+                    });
+                  }
+
+                  // decode an encoded blob
+                  function _decodeBlob(encodedBlob) {
+                    var arrayBuff = _binStringToArrayBuffer(atob(encodedBlob.data));
+                    return createBlob([arrayBuff], { type: encodedBlob.type });
+                  }
+
+                  // is this one of our fancy encoded blobs?
+                  function _isEncodedBlob(value) {
+                    return value && value.__local_forage_encoded_blob;
+                  }
+
+                  // Specialize the default `ready()` function by making it dependent
+                  // on the current database operations. Thus, the driver will be actually
+                  // ready when it's been initialized (default) *and* there are no pending
+                  // operations on the database (initiated by some other instances).
+                  function _fullyReady(callback) {
+                    var self = this;
+
+                    var promise = self._initReady().then(function () {
+                      var dbContext = dbContexts[self._dbInfo.name];
+
+                      if (dbContext && dbContext.dbReady) {
+                        return dbContext.dbReady;
+                      }
+                    });
+
+                    executeTwoCallbacks(promise, callback, callback);
+                    return promise;
+                  }
+
+                  // Try to establish a new db connection to replace the
+                  // current one which is broken (i.e. experiencing
+                  // InvalidStateError while creating a transaction).
+                  function _tryReconnect(dbInfo) {
+                    _deferReadiness(dbInfo);
+
+                    var dbContext = dbContexts[dbInfo.name];
+                    var forages = dbContext.forages;
+
+                    for (var i = 0; i < forages.length; i++) {
+                      var forage = forages[i];
+                      if (forage._dbInfo.db) {
+                        forage._dbInfo.db.close();
+                        forage._dbInfo.db = null;
+                      }
+                    }
+                    dbInfo.db = null;
+
+                    return _getOriginalConnection(dbInfo)
+                      .then(function (db) {
+                        dbInfo.db = db;
+                        if (_isUpgradeNeeded(dbInfo)) {
+                          // Reopen the database for upgrading.
+                          return _getUpgradedConnection(dbInfo);
+                        }
+                        return db;
+                      })
+                      .then(function (db) {
+                        // store the latest db reference
+                        // in case the db was upgraded
+                        dbInfo.db = dbContext.db = db;
+                        for (var i = 0; i < forages.length; i++) {
+                          forages[i]._dbInfo.db = db;
+                        }
+                      })
+                      ["catch"](function (err) {
+                        _rejectReadiness(dbInfo, err);
+                        throw err;
+                      });
+                  }
+
+                  // FF doesn't like Promises (micro-tasks) and IDDB store operations,
+                  // so we have to do it with callbacks
+                  function createTransaction(dbInfo, mode, callback, retries) {
+                    if (retries === undefined) {
+                      retries = 1;
+                    }
+
+                    try {
+                      var tx = dbInfo.db.transaction(dbInfo.storeName, mode);
+                      callback(null, tx);
+                    } catch (err) {
+                      if (
+                        retries > 0 &&
+                        (!dbInfo.db ||
+                          err.name === "InvalidStateError" ||
+                          err.name === "NotFoundError")
+                      ) {
+                        return Promise$1.resolve()
+                          .then(function () {
+                            if (
+                              !dbInfo.db ||
+                              (err.name === "NotFoundError" &&
+                                !dbInfo.db.objectStoreNames.contains(dbInfo.storeName) &&
+                                dbInfo.version <= dbInfo.db.version)
+                            ) {
+                              // increase the db version, to create the new ObjectStore
+                              if (dbInfo.db) {
+                                dbInfo.version = dbInfo.db.version + 1;
+                              }
+                              // Reopen the database for upgrading.
+                              return _getUpgradedConnection(dbInfo);
+                            }
+                          })
+                          .then(function () {
+                            return _tryReconnect(dbInfo).then(function () {
+                              createTransaction(dbInfo, mode, callback, retries - 1);
+                            });
+                          })
+                          ["catch"](callback);
+                      }
+
+                      callback(err);
+                    }
+                  }
+
+                  function createDbContext() {
+                    return {
+                      // Running localForages sharing a database.
+                      forages: [],
+                      // Shared database.
+                      db: null,
+                      // Database readiness (promise).
+                      dbReady: null,
+                      // Deferred operations on the database.
+                      deferredOperations: [],
+                    };
+                  }
+
+                  // Open the IndexedDB database (automatically creates one if one didn't
+                  // previously exist), using any options set in the config.
+                  function _initStorage(options) {
+                    var self = this;
+                    var dbInfo = {
+                      db: null,
+                    };
+
+                    if (options) {
+                      for (var i in options) {
+                        dbInfo[i] = options[i];
+                      }
+                    }
+
+                    // Get the current context of the database;
+                    var dbContext = dbContexts[dbInfo.name];
+
+                    // ...or create a new context.
+                    if (!dbContext) {
+                      dbContext = createDbContext();
+                      // Register the new context in the global container.
+                      dbContexts[dbInfo.name] = dbContext;
+                    }
+
+                    // Register itself as a running localForage in the current context.
+                    dbContext.forages.push(self);
+
+                    // Replace the default `ready()` function with the specialized one.
+                    if (!self._initReady) {
+                      self._initReady = self.ready;
+                      self.ready = _fullyReady;
+                    }
+
+                    // Create an array of initialization states of the related localForages.
+                    var initPromises = [];
+
+                    function ignoreErrors() {
+                      // Don't handle errors here,
+                      // just makes sure related localForages aren't pending.
+                      return Promise$1.resolve();
+                    }
+
+                    for (var j = 0; j < dbContext.forages.length; j++) {
+                      var forage = dbContext.forages[j];
+                      if (forage !== self) {
+                        // Don't wait for itself...
+                        initPromises.push(forage._initReady()["catch"](ignoreErrors));
+                      }
+                    }
+
+                    // Take a snapshot of the related localForages.
+                    var forages = dbContext.forages.slice(0);
+
+                    // Initialize the connection process only when
+                    // all the related localForages aren't pending.
+                    return Promise$1.all(initPromises)
+                      .then(function () {
+                        dbInfo.db = dbContext.db;
+                        // Get the connection or open a new one without upgrade.
+                        return _getOriginalConnection(dbInfo);
+                      })
+                      .then(function (db) {
+                        dbInfo.db = db;
+                        if (_isUpgradeNeeded(dbInfo, self._defaultConfig.version)) {
+                          // Reopen the database for upgrading.
+                          return _getUpgradedConnection(dbInfo);
+                        }
+                        return db;
+                      })
+                      .then(function (db) {
+                        dbInfo.db = dbContext.db = db;
+                        self._dbInfo = dbInfo;
+                        // Share the final connection amongst related localForages.
+                        for (var k = 0; k < forages.length; k++) {
+                          var forage = forages[k];
+                          if (forage !== self) {
+                            // Self is already up-to-date.
+                            forage._dbInfo.db = dbInfo.db;
+                            forage._dbInfo.version = dbInfo.version;
+                          }
+                        }
+                      });
+                  }
+
+                  function getItem(key, callback) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
+                            if (err) {
+                              return reject(err);
+                            }
+
+                            try {
+                              var store = transaction.objectStore(self._dbInfo.storeName);
+                              var req = store.get(key);
+
+                              req.onsuccess = function () {
+                                var value = req.result;
+                                if (value === undefined) {
+                                  value = null;
+                                }
+                                if (_isEncodedBlob(value)) {
+                                  value = _decodeBlob(value);
+                                }
+                                resolve(value);
+                              };
+
+                              req.onerror = function () {
+                                reject(req.error);
+                              };
+                            } catch (e) {
+                              reject(e);
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Iterate over all items stored in database.
+                  function iterate(iterator, callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
+                            if (err) {
+                              return reject(err);
+                            }
+
+                            try {
+                              var store = transaction.objectStore(self._dbInfo.storeName);
+                              var req = store.openCursor();
+                              var iterationNumber = 1;
+
+                              req.onsuccess = function () {
+                                var cursor = req.result;
+
+                                if (cursor) {
+                                  var value = cursor.value;
+                                  if (_isEncodedBlob(value)) {
+                                    value = _decodeBlob(value);
+                                  }
+                                  var result = iterator(value, cursor.key, iterationNumber++);
+
+                                  // when the iterator callback retuns any
+                                  // (non-`undefined`) value, then we stop
+                                  // the iteration immediately
+                                  if (result !== void 0) {
+                                    resolve(result);
+                                  } else {
+                                    cursor["continue"]();
+                                  }
+                                } else {
+                                  resolve();
+                                }
+                              };
+
+                              req.onerror = function () {
+                                reject(req.error);
+                              };
+                            } catch (e) {
+                              reject(e);
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+
+                    return promise;
+                  }
+
+                  function setItem(key, value, callback) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      var dbInfo;
+                      self
+                        .ready()
+                        .then(function () {
+                          dbInfo = self._dbInfo;
+                          if (toString.call(value) === "[object Blob]") {
+                            return _checkBlobSupport(dbInfo.db).then(function (blobSupport) {
+                              if (blobSupport) {
+                                return value;
+                              }
+                              return _encodeBlob(value);
+                            });
+                          }
+                          return value;
+                        })
+                        .then(function (value) {
+                          createTransaction(self._dbInfo, READ_WRITE, function (err, transaction) {
+                            if (err) {
+                              return reject(err);
+                            }
+
+                            try {
+                              var store = transaction.objectStore(self._dbInfo.storeName);
+
+                              // The reason we don't _save_ null is because IE 10 does
+                              // not support saving the `null` type in IndexedDB. How
+                              // ironic, given the bug below!
+                              // See: https://github.com/mozilla/localForage/issues/161
+                              if (value === null) {
+                                value = undefined;
+                              }
+
+                              var req = store.put(value, key);
+
+                              transaction.oncomplete = function () {
+                                // Cast to undefined so the value passed to
+                                // callback/promise is the same as what one would get out
+                                // of `getItem()` later. This leads to some weirdness
+                                // (setItem('foo', undefined) will return `null`), but
+                                // it's not my fault localStorage is our baseline and that
+                                // it's weird.
+                                if (value === undefined) {
+                                  value = null;
+                                }
+
+                                resolve(value);
+                              };
+                              transaction.onabort = transaction.onerror = function () {
+                                var err = req.error ? req.error : req.transaction.error;
+                                reject(err);
+                              };
+                            } catch (e) {
+                              reject(e);
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function removeItem(key, callback) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          createTransaction(self._dbInfo, READ_WRITE, function (err, transaction) {
+                            if (err) {
+                              return reject(err);
+                            }
+
+                            try {
+                              var store = transaction.objectStore(self._dbInfo.storeName);
+                              // We use a Grunt task to make this safe for IE and some
+                              // versions of Android (including those used by Cordova).
+                              // Normally IE won't like `.delete()` and will insist on
+                              // using `['delete']()`, but we have a build step that
+                              // fixes this for us now.
+                              var req = store["delete"](key);
+                              transaction.oncomplete = function () {
+                                resolve();
+                              };
+
+                              transaction.onerror = function () {
+                                reject(req.error);
+                              };
+
+                              // The request will be also be aborted if we've exceeded our storage
+                              // space.
+                              transaction.onabort = function () {
+                                var err = req.error ? req.error : req.transaction.error;
+                                reject(err);
+                              };
+                            } catch (e) {
+                              reject(e);
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function clear(callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          createTransaction(self._dbInfo, READ_WRITE, function (err, transaction) {
+                            if (err) {
+                              return reject(err);
+                            }
+
+                            try {
+                              var store = transaction.objectStore(self._dbInfo.storeName);
+                              var req = store.clear();
+
+                              transaction.oncomplete = function () {
+                                resolve();
+                              };
+
+                              transaction.onabort = transaction.onerror = function () {
+                                var err = req.error ? req.error : req.transaction.error;
+                                reject(err);
+                              };
+                            } catch (e) {
+                              reject(e);
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function length(callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
+                            if (err) {
+                              return reject(err);
+                            }
+
+                            try {
+                              var store = transaction.objectStore(self._dbInfo.storeName);
+                              var req = store.count();
+
+                              req.onsuccess = function () {
+                                resolve(req.result);
+                              };
+
+                              req.onerror = function () {
+                                reject(req.error);
+                              };
+                            } catch (e) {
+                              reject(e);
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function key(n, callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      if (n < 0) {
+                        resolve(null);
+
+                        return;
+                      }
+
+                      self
+                        .ready()
+                        .then(function () {
+                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
+                            if (err) {
+                              return reject(err);
+                            }
+
+                            try {
+                              var store = transaction.objectStore(self._dbInfo.storeName);
+                              var advanced = false;
+                              var req = store.openCursor();
+
+                              req.onsuccess = function () {
+                                var cursor = req.result;
+                                if (!cursor) {
+                                  // this means there weren't enough keys
+                                  resolve(null);
+
+                                  return;
+                                }
+
+                                if (n === 0) {
+                                  // We have the first key, return it if that's what they
+                                  // wanted.
+                                  resolve(cursor.key);
+                                } else {
+                                  if (!advanced) {
+                                    // Otherwise, ask the cursor to skip ahead n
+                                    // records.
+                                    advanced = true;
+                                    cursor.advance(n);
+                                  } else {
+                                    // When we get here, we've got the nth key.
+                                    resolve(cursor.key);
+                                  }
+                                }
+                              };
+
+                              req.onerror = function () {
+                                reject(req.error);
+                              };
+                            } catch (e) {
+                              reject(e);
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function keys(callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          createTransaction(self._dbInfo, READ_ONLY, function (err, transaction) {
+                            if (err) {
+                              return reject(err);
+                            }
+
+                            try {
+                              var store = transaction.objectStore(self._dbInfo.storeName);
+                              var req = store.openCursor();
+                              var keys = [];
+
+                              req.onsuccess = function () {
+                                var cursor = req.result;
+
+                                if (!cursor) {
+                                  resolve(keys);
+                                  return;
+                                }
+
+                                keys.push(cursor.key);
+                                cursor["continue"]();
+                              };
+
+                              req.onerror = function () {
+                                reject(req.error);
+                              };
+                            } catch (e) {
+                              reject(e);
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function dropInstance(options, callback) {
+                    callback = getCallback.apply(this, arguments);
+
+                    var currentConfig = this.config();
+                    options = (typeof options !== "function" && options) || {};
+                    if (!options.name) {
+                      options.name = options.name || currentConfig.name;
+                      options.storeName = options.storeName || currentConfig.storeName;
+                    }
+
+                    var self = this;
+                    var promise;
+                    if (!options.name) {
+                      promise = Promise$1.reject("Invalid arguments");
+                    } else {
+                      var isCurrentDb = options.name === currentConfig.name && self._dbInfo.db;
+
+                      var dbPromise = isCurrentDb
+                        ? Promise$1.resolve(self._dbInfo.db)
+                        : _getOriginalConnection(options).then(function (db) {
+                            var dbContext = dbContexts[options.name];
+                            var forages = dbContext.forages;
+                            dbContext.db = db;
+                            for (var i = 0; i < forages.length; i++) {
+                              forages[i]._dbInfo.db = db;
+                            }
+                            return db;
+                          });
+
+                      if (!options.storeName) {
+                        promise = dbPromise.then(function (db) {
+                          _deferReadiness(options);
+
+                          var dbContext = dbContexts[options.name];
+                          var forages = dbContext.forages;
+
+                          db.close();
+                          for (var i = 0; i < forages.length; i++) {
+                            var forage = forages[i];
+                            forage._dbInfo.db = null;
+                          }
+
+                          var dropDBPromise = new Promise$1(function (resolve, reject) {
+                            var req = idb.deleteDatabase(options.name);
+
+                            req.onerror = req.onblocked = function (err) {
+                              var db = req.result;
+                              if (db) {
+                                db.close();
+                              }
+                              reject(err);
+                            };
+
+                            req.onsuccess = function () {
+                              var db = req.result;
+                              if (db) {
+                                db.close();
+                              }
+                              resolve(db);
+                            };
+                          });
+
+                          return dropDBPromise
+                            .then(function (db) {
+                              dbContext.db = db;
+                              for (var i = 0; i < forages.length; i++) {
+                                var _forage = forages[i];
+                                _advanceReadiness(_forage._dbInfo);
+                              }
+                            })
+                            ["catch"](function (err) {
+                              (_rejectReadiness(options, err) || Promise$1.resolve())["catch"](
+                                function () {}
+                              );
+                              throw err;
+                            });
+                        });
+                      } else {
+                        promise = dbPromise.then(function (db) {
+                          if (!db.objectStoreNames.contains(options.storeName)) {
+                            return;
+                          }
+
+                          var newVersion = db.version + 1;
+
+                          _deferReadiness(options);
+
+                          var dbContext = dbContexts[options.name];
+                          var forages = dbContext.forages;
+
+                          db.close();
+                          for (var i = 0; i < forages.length; i++) {
+                            var forage = forages[i];
+                            forage._dbInfo.db = null;
+                            forage._dbInfo.version = newVersion;
+                          }
+
+                          var dropObjectPromise = new Promise$1(function (resolve, reject) {
+                            var req = idb.open(options.name, newVersion);
+
+                            req.onerror = function (err) {
+                              var db = req.result;
+                              db.close();
+                              reject(err);
+                            };
+
+                            req.onupgradeneeded = function () {
+                              var db = req.result;
+                              db.deleteObjectStore(options.storeName);
+                            };
+
+                            req.onsuccess = function () {
+                              var db = req.result;
+                              db.close();
+                              resolve(db);
+                            };
+                          });
+
+                          return dropObjectPromise
+                            .then(function (db) {
+                              dbContext.db = db;
+                              for (var j = 0; j < forages.length; j++) {
+                                var _forage2 = forages[j];
+                                _forage2._dbInfo.db = db;
+                                _advanceReadiness(_forage2._dbInfo);
+                              }
+                            })
+                            ["catch"](function (err) {
+                              (_rejectReadiness(options, err) || Promise$1.resolve())["catch"](
+                                function () {}
+                              );
+                              throw err;
+                            });
+                        });
+                      }
+                    }
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  var asyncStorage = {
+                    _driver: "asyncStorage",
+                    _initStorage: _initStorage,
+                    _support: isIndexedDBValid(),
+                    iterate: iterate,
+                    getItem: getItem,
+                    setItem: setItem,
+                    removeItem: removeItem,
+                    clear: clear,
+                    length: length,
+                    key: key,
+                    keys: keys,
+                    dropInstance: dropInstance,
+                  };
+
+                  function isWebSQLValid() {
+                    return typeof openDatabase === "function";
+                  }
+
+                  // Sadly, the best way to save binary data in WebSQL/localStorage is serializing
+                  // it to Base64, so this is how we store it to prevent very strange errors with less
+                  // verbose ways of binary <-> string data storage.
+                  var BASE_CHARS =
+                    "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
+
+                  var BLOB_TYPE_PREFIX = "~~local_forage_type~";
+                  var BLOB_TYPE_PREFIX_REGEX = /^~~local_forage_type~([^~]+)~/;
+
+                  var SERIALIZED_MARKER = "__lfsc__:";
+                  var SERIALIZED_MARKER_LENGTH = SERIALIZED_MARKER.length;
+
+                  // OMG the serializations!
+                  var TYPE_ARRAYBUFFER = "arbf";
+                  var TYPE_BLOB = "blob";
+                  var TYPE_INT8ARRAY = "si08";
+                  var TYPE_UINT8ARRAY = "ui08";
+                  var TYPE_UINT8CLAMPEDARRAY = "uic8";
+                  var TYPE_INT16ARRAY = "si16";
+                  var TYPE_INT32ARRAY = "si32";
+                  var TYPE_UINT16ARRAY = "ur16";
+                  var TYPE_UINT32ARRAY = "ui32";
+                  var TYPE_FLOAT32ARRAY = "fl32";
+                  var TYPE_FLOAT64ARRAY = "fl64";
+                  var TYPE_SERIALIZED_MARKER_LENGTH =
+                    SERIALIZED_MARKER_LENGTH + TYPE_ARRAYBUFFER.length;
+
+                  var toString$1 = Object.prototype.toString;
+
+                  function stringToBuffer(serializedString) {
+                    // Fill the string into a ArrayBuffer.
+                    var bufferLength = serializedString.length * 0.75;
+                    var len = serializedString.length;
+                    var i;
+                    var p = 0;
+                    var encoded1, encoded2, encoded3, encoded4;
+
+                    if (serializedString[serializedString.length - 1] === "=") {
+                      bufferLength--;
+                      if (serializedString[serializedString.length - 2] === "=") {
+                        bufferLength--;
+                      }
+                    }
+
+                    var buffer = new ArrayBuffer(bufferLength);
+                    var bytes = new Uint8Array(buffer);
+
+                    for (i = 0; i < len; i += 4) {
+                      encoded1 = BASE_CHARS.indexOf(serializedString[i]);
+                      encoded2 = BASE_CHARS.indexOf(serializedString[i + 1]);
+                      encoded3 = BASE_CHARS.indexOf(serializedString[i + 2]);
+                      encoded4 = BASE_CHARS.indexOf(serializedString[i + 3]);
+
+                      /*jslint bitwise: true */
+                      bytes[p++] = (encoded1 << 2) | (encoded2 >> 4);
+                      bytes[p++] = ((encoded2 & 15) << 4) | (encoded3 >> 2);
+                      bytes[p++] = ((encoded3 & 3) << 6) | (encoded4 & 63);
+                    }
+                    return buffer;
+                  }
+
+                  // Converts a buffer to a string to store, serialized, in the backend
+                  // storage library.
+                  function bufferToString(buffer) {
+                    // base64-arraybuffer
+                    var bytes = new Uint8Array(buffer);
+                    var base64String = "";
+                    var i;
+
+                    for (i = 0; i < bytes.length; i += 3) {
+                      /*jslint bitwise: true */
+                      base64String += BASE_CHARS[bytes[i] >> 2];
+                      base64String += BASE_CHARS[((bytes[i] & 3) << 4) | (bytes[i + 1] >> 4)];
+                      base64String += BASE_CHARS[((bytes[i + 1] & 15) << 2) | (bytes[i + 2] >> 6)];
+                      base64String += BASE_CHARS[bytes[i + 2] & 63];
+                    }
+
+                    if (bytes.length % 3 === 2) {
+                      base64String = base64String.substring(0, base64String.length - 1) + "=";
+                    } else if (bytes.length % 3 === 1) {
+                      base64String = base64String.substring(0, base64String.length - 2) + "==";
+                    }
+
+                    return base64String;
+                  }
+
+                  // Serialize a value, afterwards executing a callback (which usually
+                  // instructs the `setItem()` callback/promise to be executed). This is how
+                  // we store binary data with localStorage.
+                  function serialize(value, callback) {
+                    var valueType = "";
+                    if (value) {
+                      valueType = toString$1.call(value);
+                    }
+
+                    // Cannot use `value instanceof ArrayBuffer` or such here, as these
+                    // checks fail when running the tests using casper.js...
+                    //
+                    // TODO: See why those tests fail and use a better solution.
+                    if (
+                      value &&
+                      (valueType === "[object ArrayBuffer]" ||
+                        (value.buffer && toString$1.call(value.buffer) === "[object ArrayBuffer]"))
+                    ) {
+                      // Convert binary arrays to a string and prefix the string with
+                      // a special marker.
+                      var buffer;
+                      var marker = SERIALIZED_MARKER;
+
+                      if (value instanceof ArrayBuffer) {
+                        buffer = value;
+                        marker += TYPE_ARRAYBUFFER;
+                      } else {
+                        buffer = value.buffer;
+
+                        if (valueType === "[object Int8Array]") {
+                          marker += TYPE_INT8ARRAY;
+                        } else if (valueType === "[object Uint8Array]") {
+                          marker += TYPE_UINT8ARRAY;
+                        } else if (valueType === "[object Uint8ClampedArray]") {
+                          marker += TYPE_UINT8CLAMPEDARRAY;
+                        } else if (valueType === "[object Int16Array]") {
+                          marker += TYPE_INT16ARRAY;
+                        } else if (valueType === "[object Uint16Array]") {
+                          marker += TYPE_UINT16ARRAY;
+                        } else if (valueType === "[object Int32Array]") {
+                          marker += TYPE_INT32ARRAY;
+                        } else if (valueType === "[object Uint32Array]") {
+                          marker += TYPE_UINT32ARRAY;
+                        } else if (valueType === "[object Float32Array]") {
+                          marker += TYPE_FLOAT32ARRAY;
+                        } else if (valueType === "[object Float64Array]") {
+                          marker += TYPE_FLOAT64ARRAY;
+                        } else {
+                          callback(new Error("Failed to get type for BinaryArray"));
+                        }
+                      }
+
+                      callback(marker + bufferToString(buffer));
+                    } else if (valueType === "[object Blob]") {
+                      // Conver the blob to a binaryArray and then to a string.
+                      var fileReader = new FileReader();
+
+                      fileReader.onload = function () {
+                        // Backwards-compatible prefix for the blob type.
+                        var str = BLOB_TYPE_PREFIX + value.type + "~" + bufferToString(this.result);
+
+                        callback(SERIALIZED_MARKER + TYPE_BLOB + str);
+                      };
+
+                      fileReader.readAsArrayBuffer(value);
+                    } else {
+                      try {
+                        callback(JSON.stringify(value));
+                      } catch (e) {
+                        console.error("Couldn't convert value into a JSON string: ", value);
+
+                        callback(null, e);
+                      }
+                    }
+                  }
+
+                  // Deserialize data we've inserted into a value column/field. We place
+                  // special markers into our strings to mark them as encoded; this isn't
+                  // as nice as a meta field, but it's the only sane thing we can do whilst
+                  // keeping localStorage support intact.
+                  //
+                  // Oftentimes this will just deserialize JSON content, but if we have a
+                  // special marker (SERIALIZED_MARKER, defined above), we will extract
+                  // some kind of arraybuffer/binary data/typed array out of the string.
+                  function deserialize(value) {
+                    // If we haven't marked this string as being specially serialized (i.e.
+                    // something other than serialized JSON), we can just return it and be
+                    // done with it.
+                    if (value.substring(0, SERIALIZED_MARKER_LENGTH) !== SERIALIZED_MARKER) {
+                      return JSON.parse(value);
+                    }
+
+                    // The following code deals with deserializing some kind of Blob or
+                    // TypedArray. First we separate out the type of data we're dealing
+                    // with from the data itself.
+                    var serializedString = value.substring(TYPE_SERIALIZED_MARKER_LENGTH);
+                    var type = value.substring(
+                      SERIALIZED_MARKER_LENGTH,
+                      TYPE_SERIALIZED_MARKER_LENGTH
+                    );
+
+                    var blobType;
+                    // Backwards-compatible blob type serialization strategy.
+                    // DBs created with older versions of localForage will simply not have the blob type.
+                    if (type === TYPE_BLOB && BLOB_TYPE_PREFIX_REGEX.test(serializedString)) {
+                      var matcher = serializedString.match(BLOB_TYPE_PREFIX_REGEX);
+                      blobType = matcher[1];
+                      serializedString = serializedString.substring(matcher[0].length);
+                    }
+                    var buffer = stringToBuffer(serializedString);
+
+                    // Return the right type based on the code/type set during
+                    // serialization.
+                    switch (type) {
+                      case TYPE_ARRAYBUFFER:
+                        return buffer;
+                      case TYPE_BLOB:
+                        return createBlob([buffer], { type: blobType });
+                      case TYPE_INT8ARRAY:
+                        return new Int8Array(buffer);
+                      case TYPE_UINT8ARRAY:
+                        return new Uint8Array(buffer);
+                      case TYPE_UINT8CLAMPEDARRAY:
+                        return new Uint8ClampedArray(buffer);
+                      case TYPE_INT16ARRAY:
+                        return new Int16Array(buffer);
+                      case TYPE_UINT16ARRAY:
+                        return new Uint16Array(buffer);
+                      case TYPE_INT32ARRAY:
+                        return new Int32Array(buffer);
+                      case TYPE_UINT32ARRAY:
+                        return new Uint32Array(buffer);
+                      case TYPE_FLOAT32ARRAY:
+                        return new Float32Array(buffer);
+                      case TYPE_FLOAT64ARRAY:
+                        return new Float64Array(buffer);
+                      default:
+                        throw new Error("Unkown type: " + type);
+                    }
+                  }
+
+                  var localforageSerializer = {
+                    serialize: serialize,
+                    deserialize: deserialize,
+                    stringToBuffer: stringToBuffer,
+                    bufferToString: bufferToString,
+                  };
+
+                  /*
+                   * Includes code from:
+                   *
+                   * base64-arraybuffer
+                   * https://github.com/niklasvh/base64-arraybuffer
+                   *
+                   * Copyright (c) 2012 Niklas von Hertzen
+                   * Licensed under the MIT license.
+                   */
+
+                  function createDbTable(t, dbInfo, callback, errorCallback) {
+                    t.executeSql(
+                      "CREATE TABLE IF NOT EXISTS " +
+                        dbInfo.storeName +
+                        " " +
+                        "(id INTEGER PRIMARY KEY, key unique, value)",
+                      [],
+                      callback,
+                      errorCallback
+                    );
+                  }
+
+                  // Open the WebSQL database (automatically creates one if one didn't
+                  // previously exist), using any options set in the config.
+                  function _initStorage$1(options) {
+                    var self = this;
+                    var dbInfo = {
+                      db: null,
+                    };
+
+                    if (options) {
+                      for (var i in options) {
+                        dbInfo[i] =
+                          typeof options[i] !== "string" ? options[i].toString() : options[i];
+                      }
+                    }
+
+                    var dbInfoPromise = new Promise$1(function (resolve, reject) {
+                      // Open the database; the openDatabase API will automatically
+                      // create it for us if it doesn't exist.
+                      try {
+                        dbInfo.db = openDatabase(
+                          dbInfo.name,
+                          String(dbInfo.version),
+                          dbInfo.description,
+                          dbInfo.size
+                        );
+                      } catch (e) {
+                        return reject(e);
+                      }
+
+                      // Create our key/value table if it doesn't exist.
+                      dbInfo.db.transaction(function (t) {
+                        createDbTable(
+                          t,
+                          dbInfo,
+                          function () {
+                            self._dbInfo = dbInfo;
+                            resolve();
+                          },
+                          function (t, error) {
+                            reject(error);
+                          }
+                        );
+                      }, reject);
+                    });
+
+                    dbInfo.serializer = localforageSerializer;
+                    return dbInfoPromise;
+                  }
+
+                  function tryExecuteSql(t, dbInfo, sqlStatement, args, callback, errorCallback) {
+                    t.executeSql(
+                      sqlStatement,
+                      args,
+                      callback,
+                      function (t, error) {
+                        if (error.code === error.SYNTAX_ERR) {
+                          t.executeSql(
+                            "SELECT name FROM sqlite_master " + "WHERE type='table' AND name = ?",
+                            [dbInfo.storeName],
+                            function (t, results) {
+                              if (!results.rows.length) {
+                                // if the table is missing (was deleted)
+                                // re-create it table and retry
+                                createDbTable(
+                                  t,
+                                  dbInfo,
+                                  function () {
+                                    t.executeSql(sqlStatement, args, callback, errorCallback);
+                                  },
+                                  errorCallback
+                                );
+                              } else {
+                                errorCallback(t, error);
+                              }
+                            },
+                            errorCallback
+                          );
+                        } else {
+                          errorCallback(t, error);
+                        }
+                      },
+                      errorCallback
+                    );
+                  }
+
+                  function getItem$1(key, callback) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          var dbInfo = self._dbInfo;
+                          dbInfo.db.transaction(function (t) {
+                            tryExecuteSql(
+                              t,
+                              dbInfo,
+                              "SELECT * FROM " + dbInfo.storeName + " WHERE key = ? LIMIT 1",
+                              [key],
+                              function (t, results) {
+                                var result = results.rows.length
+                                  ? results.rows.item(0).value
+                                  : null;
+
+                                // Check to see if this is serialized content we need to
+                                // unpack.
+                                if (result) {
+                                  result = dbInfo.serializer.deserialize(result);
+                                }
+
+                                resolve(result);
+                              },
+                              function (t, error) {
+                                reject(error);
+                              }
+                            );
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function iterate$1(iterator, callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          var dbInfo = self._dbInfo;
+
+                          dbInfo.db.transaction(function (t) {
+                            tryExecuteSql(
+                              t,
+                              dbInfo,
+                              "SELECT * FROM " + dbInfo.storeName,
+                              [],
+                              function (t, results) {
+                                var rows = results.rows;
+                                var length = rows.length;
+
+                                for (var i = 0; i < length; i++) {
+                                  var item = rows.item(i);
+                                  var result = item.value;
+
+                                  // Check to see if this is serialized content
+                                  // we need to unpack.
+                                  if (result) {
+                                    result = dbInfo.serializer.deserialize(result);
+                                  }
+
+                                  result = iterator(result, item.key, i + 1);
+
+                                  // void(0) prevents problems with redefinition
+                                  // of `undefined`.
+                                  if (result !== void 0) {
+                                    resolve(result);
+                                    return;
+                                  }
+                                }
+
+                                resolve();
+                              },
+                              function (t, error) {
+                                reject(error);
+                              }
+                            );
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function _setItem(key, value, callback, retriesLeft) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          // The localStorage API doesn't return undefined values in an
+                          // "expected" way, so undefined is always cast to null in all
+                          // drivers. See: https://github.com/mozilla/localForage/pull/42
+                          if (value === undefined) {
+                            value = null;
+                          }
+
+                          // Save the original value to pass to the callback.
+                          var originalValue = value;
+
+                          var dbInfo = self._dbInfo;
+                          dbInfo.serializer.serialize(value, function (value, error) {
+                            if (error) {
+                              reject(error);
+                            } else {
+                              dbInfo.db.transaction(
+                                function (t) {
+                                  tryExecuteSql(
+                                    t,
+                                    dbInfo,
+                                    "INSERT OR REPLACE INTO " +
+                                      dbInfo.storeName +
+                                      " " +
+                                      "(key, value) VALUES (?, ?)",
+                                    [key, value],
+                                    function () {
+                                      resolve(originalValue);
+                                    },
+                                    function (t, error) {
+                                      reject(error);
+                                    }
+                                  );
+                                },
+                                function (sqlError) {
+                                  // The transaction failed; check
+                                  // to see if it's a quota error.
+                                  if (sqlError.code === sqlError.QUOTA_ERR) {
+                                    // We reject the callback outright for now, but
+                                    // it's worth trying to re-run the transaction.
+                                    // Even if the user accepts the prompt to use
+                                    // more storage on Safari, this error will
+                                    // be called.
+                                    //
+                                    // Try to re-run the transaction.
+                                    if (retriesLeft > 0) {
+                                      resolve(
+                                        _setItem.apply(self, [
+                                          key,
+                                          originalValue,
+                                          callback,
+                                          retriesLeft - 1,
+                                        ])
+                                      );
+                                      return;
+                                    }
+                                    reject(sqlError);
+                                  }
+                                }
+                              );
+                            }
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function setItem$1(key, value, callback) {
+                    return _setItem.apply(this, [key, value, callback, 1]);
+                  }
+
+                  function removeItem$1(key, callback) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          var dbInfo = self._dbInfo;
+                          dbInfo.db.transaction(function (t) {
+                            tryExecuteSql(
+                              t,
+                              dbInfo,
+                              "DELETE FROM " + dbInfo.storeName + " WHERE key = ?",
+                              [key],
+                              function () {
+                                resolve();
+                              },
+                              function (t, error) {
+                                reject(error);
+                              }
+                            );
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Deletes every item in the table.
+                  // TODO: Find out if this resets the AUTO_INCREMENT number.
+                  function clear$1(callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          var dbInfo = self._dbInfo;
+                          dbInfo.db.transaction(function (t) {
+                            tryExecuteSql(
+                              t,
+                              dbInfo,
+                              "DELETE FROM " + dbInfo.storeName,
+                              [],
+                              function () {
+                                resolve();
+                              },
+                              function (t, error) {
+                                reject(error);
+                              }
+                            );
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Does a simple `COUNT(key)` to get the number of items stored in
+                  // localForage.
+                  function length$1(callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          var dbInfo = self._dbInfo;
+                          dbInfo.db.transaction(function (t) {
+                            // Ahhh, SQL makes this one soooooo easy.
+                            tryExecuteSql(
+                              t,
+                              dbInfo,
+                              "SELECT COUNT(key) as c FROM " + dbInfo.storeName,
+                              [],
+                              function (t, results) {
+                                var result = results.rows.item(0).c;
+                                resolve(result);
+                              },
+                              function (t, error) {
+                                reject(error);
+                              }
+                            );
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Return the key located at key index X; essentially gets the key from a
+                  // `WHERE id = ?`. This is the most efficient way I can think to implement
+                  // this rarely-used (in my experience) part of the API, but it can seem
+                  // inconsistent, because we do `INSERT OR REPLACE INTO` on `setItem()`, so
+                  // the ID of each key will change every time it's updated. Perhaps a stored
+                  // procedure for the `setItem()` SQL would solve this problem?
+                  // TODO: Don't change ID on `setItem()`.
+                  function key$1(n, callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          var dbInfo = self._dbInfo;
+                          dbInfo.db.transaction(function (t) {
+                            tryExecuteSql(
+                              t,
+                              dbInfo,
+                              "SELECT key FROM " + dbInfo.storeName + " WHERE id = ? LIMIT 1",
+                              [n + 1],
+                              function (t, results) {
+                                var result = results.rows.length ? results.rows.item(0).key : null;
+                                resolve(result);
+                              },
+                              function (t, error) {
+                                reject(error);
+                              }
+                            );
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function keys$1(callback) {
+                    var self = this;
+
+                    var promise = new Promise$1(function (resolve, reject) {
+                      self
+                        .ready()
+                        .then(function () {
+                          var dbInfo = self._dbInfo;
+                          dbInfo.db.transaction(function (t) {
+                            tryExecuteSql(
+                              t,
+                              dbInfo,
+                              "SELECT key FROM " + dbInfo.storeName,
+                              [],
+                              function (t, results) {
+                                var keys = [];
+
+                                for (var i = 0; i < results.rows.length; i++) {
+                                  keys.push(results.rows.item(i).key);
+                                }
+
+                                resolve(keys);
+                              },
+                              function (t, error) {
+                                reject(error);
+                              }
+                            );
+                          });
+                        })
+                        ["catch"](reject);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // https://www.w3.org/TR/webdatabase/#databases
+                  // > There is no way to enumerate or delete the databases available for an origin from this API.
+                  function getAllStoreNames(db) {
+                    return new Promise$1(function (resolve, reject) {
+                      db.transaction(
+                        function (t) {
+                          t.executeSql(
+                            "SELECT name FROM sqlite_master " +
+                              "WHERE type='table' AND name <> '__WebKitDatabaseInfoTable__'",
+                            [],
+                            function (t, results) {
+                              var storeNames = [];
+
+                              for (var i = 0; i < results.rows.length; i++) {
+                                storeNames.push(results.rows.item(i).name);
+                              }
+
+                              resolve({
+                                db: db,
+                                storeNames: storeNames,
+                              });
+                            },
+                            function (t, error) {
+                              reject(error);
+                            }
+                          );
+                        },
+                        function (sqlError) {
+                          reject(sqlError);
+                        }
+                      );
+                    });
+                  }
+
+                  function dropInstance$1(options, callback) {
+                    callback = getCallback.apply(this, arguments);
+
+                    var currentConfig = this.config();
+                    options = (typeof options !== "function" && options) || {};
+                    if (!options.name) {
+                      options.name = options.name || currentConfig.name;
+                      options.storeName = options.storeName || currentConfig.storeName;
+                    }
+
+                    var self = this;
+                    var promise;
+                    if (!options.name) {
+                      promise = Promise$1.reject("Invalid arguments");
+                    } else {
+                      promise = new Promise$1(function (resolve) {
+                        var db;
+                        if (options.name === currentConfig.name) {
+                          // use the db reference of the current instance
+                          db = self._dbInfo.db;
+                        } else {
+                          db = openDatabase(options.name, "", "", 0);
+                        }
+
+                        if (!options.storeName) {
+                          // drop all database tables
+                          resolve(getAllStoreNames(db));
+                        } else {
+                          resolve({
+                            db: db,
+                            storeNames: [options.storeName],
+                          });
+                        }
+                      }).then(function (operationInfo) {
+                        return new Promise$1(function (resolve, reject) {
+                          operationInfo.db.transaction(
+                            function (t) {
+                              function dropTable(storeName) {
+                                return new Promise$1(function (resolve, reject) {
+                                  t.executeSql(
+                                    "DROP TABLE IF EXISTS " + storeName,
+                                    [],
+                                    function () {
+                                      resolve();
+                                    },
+                                    function (t, error) {
+                                      reject(error);
+                                    }
+                                  );
+                                });
+                              }
+
+                              var operations = [];
+                              for (var i = 0, len = operationInfo.storeNames.length; i < len; i++) {
+                                operations.push(dropTable(operationInfo.storeNames[i]));
+                              }
+
+                              Promise$1.all(operations)
+                                .then(function () {
+                                  resolve();
+                                })
+                                ["catch"](function (e) {
+                                  reject(e);
+                                });
+                            },
+                            function (sqlError) {
+                              reject(sqlError);
+                            }
+                          );
+                        });
+                      });
+                    }
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  var webSQLStorage = {
+                    _driver: "webSQLStorage",
+                    _initStorage: _initStorage$1,
+                    _support: isWebSQLValid(),
+                    iterate: iterate$1,
+                    getItem: getItem$1,
+                    setItem: setItem$1,
+                    removeItem: removeItem$1,
+                    clear: clear$1,
+                    length: length$1,
+                    key: key$1,
+                    keys: keys$1,
+                    dropInstance: dropInstance$1,
+                  };
+
+                  function isLocalStorageValid() {
+                    try {
+                      return (
+                        typeof localStorage !== "undefined" &&
+                        "setItem" in localStorage &&
+                        // in IE8 typeof localStorage.setItem === 'object'
+                        !!localStorage.setItem
+                      );
+                    } catch (e) {
+                      return false;
+                    }
+                  }
+
+                  function _getKeyPrefix(options, defaultConfig) {
+                    var keyPrefix = options.name + "/";
+
+                    if (options.storeName !== defaultConfig.storeName) {
+                      keyPrefix += options.storeName + "/";
+                    }
+                    return keyPrefix;
+                  }
+
+                  // Check if localStorage throws when saving an item
+                  function checkIfLocalStorageThrows() {
+                    var localStorageTestKey = "_localforage_support_test";
+
+                    try {
+                      localStorage.setItem(localStorageTestKey, true);
+                      localStorage.removeItem(localStorageTestKey);
+
+                      return false;
+                    } catch (e) {
+                      return true;
+                    }
+                  }
+
+                  // Check if localStorage is usable and allows to save an item
+                  // This method checks if localStorage is usable in Safari Private Browsing
+                  // mode, or in any other case where the available quota for localStorage
+                  // is 0 and there wasn't any saved items yet.
+                  function _isLocalStorageUsable() {
+                    return !checkIfLocalStorageThrows() || localStorage.length > 0;
+                  }
+
+                  // Config the localStorage backend, using options set in the config.
+                  function _initStorage$2(options) {
+                    var self = this;
+                    var dbInfo = {};
+                    if (options) {
+                      for (var i in options) {
+                        dbInfo[i] = options[i];
+                      }
+                    }
+
+                    dbInfo.keyPrefix = _getKeyPrefix(options, self._defaultConfig);
+
+                    if (!_isLocalStorageUsable()) {
+                      return Promise$1.reject();
+                    }
+
+                    self._dbInfo = dbInfo;
+                    dbInfo.serializer = localforageSerializer;
+
+                    return Promise$1.resolve();
+                  }
+
+                  // Remove all keys from the datastore, effectively destroying all data in
+                  // the app's key/value store!
+                  function clear$2(callback) {
+                    var self = this;
+                    var promise = self.ready().then(function () {
+                      var keyPrefix = self._dbInfo.keyPrefix;
+
+                      for (var i = localStorage.length - 1; i >= 0; i--) {
+                        var key = localStorage.key(i);
+
+                        if (key.indexOf(keyPrefix) === 0) {
+                          localStorage.removeItem(key);
+                        }
+                      }
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Retrieve an item from the store. Unlike the original async_storage
+                  // library in Gaia, we don't modify return values at all. If a key's value
+                  // is `undefined`, we pass that value to the callback function.
+                  function getItem$2(key, callback) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = self.ready().then(function () {
+                      var dbInfo = self._dbInfo;
+                      var result = localStorage.getItem(dbInfo.keyPrefix + key);
+
+                      // If a result was found, parse it from the serialized
+                      // string into a JS object. If result isn't truthy, the key
+                      // is likely undefined and we'll pass it straight to the
+                      // callback.
+                      if (result) {
+                        result = dbInfo.serializer.deserialize(result);
+                      }
+
+                      return result;
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Iterate over all items in the store.
+                  function iterate$2(iterator, callback) {
+                    var self = this;
+
+                    var promise = self.ready().then(function () {
+                      var dbInfo = self._dbInfo;
+                      var keyPrefix = dbInfo.keyPrefix;
+                      var keyPrefixLength = keyPrefix.length;
+                      var length = localStorage.length;
+
+                      // We use a dedicated iterator instead of the `i` variable below
+                      // so other keys we fetch in localStorage aren't counted in
+                      // the `iterationNumber` argument passed to the `iterate()`
+                      // callback.
+                      //
+                      // See: github.com/mozilla/localForage/pull/435#discussion_r38061530
+                      var iterationNumber = 1;
+
+                      for (var i = 0; i < length; i++) {
+                        var key = localStorage.key(i);
+                        if (key.indexOf(keyPrefix) !== 0) {
+                          continue;
+                        }
+                        var value = localStorage.getItem(key);
+
+                        // If a result was found, parse it from the serialized
+                        // string into a JS object. If result isn't truthy, the
+                        // key is likely undefined and we'll pass it straight
+                        // to the iterator.
+                        if (value) {
+                          value = dbInfo.serializer.deserialize(value);
+                        }
+
+                        value = iterator(value, key.substring(keyPrefixLength), iterationNumber++);
+
+                        if (value !== void 0) {
+                          return value;
+                        }
+                      }
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Same as localStorage's key() method, except takes a callback.
+                  function key$2(n, callback) {
+                    var self = this;
+                    var promise = self.ready().then(function () {
+                      var dbInfo = self._dbInfo;
+                      var result;
+                      try {
+                        result = localStorage.key(n);
+                      } catch (error) {
+                        result = null;
+                      }
+
+                      // Remove the prefix from the key, if a key is found.
+                      if (result) {
+                        result = result.substring(dbInfo.keyPrefix.length);
+                      }
+
+                      return result;
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function keys$2(callback) {
+                    var self = this;
+                    var promise = self.ready().then(function () {
+                      var dbInfo = self._dbInfo;
+                      var length = localStorage.length;
+                      var keys = [];
+
+                      for (var i = 0; i < length; i++) {
+                        var itemKey = localStorage.key(i);
+                        if (itemKey.indexOf(dbInfo.keyPrefix) === 0) {
+                          keys.push(itemKey.substring(dbInfo.keyPrefix.length));
+                        }
+                      }
+
+                      return keys;
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Supply the number of keys in the datastore to the callback function.
+                  function length$2(callback) {
+                    var self = this;
+                    var promise = self.keys().then(function (keys) {
+                      return keys.length;
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Remove an item from the store, nice and simple.
+                  function removeItem$2(key, callback) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = self.ready().then(function () {
+                      var dbInfo = self._dbInfo;
+                      localStorage.removeItem(dbInfo.keyPrefix + key);
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  // Set a key's value and run an optional callback once the value is set.
+                  // Unlike Gaia's implementation, the callback function is passed the value,
+                  // in case you want to operate on that value only after you're sure it
+                  // saved, or something like that.
+                  function setItem$2(key, value, callback) {
+                    var self = this;
+
+                    key = normalizeKey(key);
+
+                    var promise = self.ready().then(function () {
+                      // Convert undefined values to null.
+                      // https://github.com/mozilla/localForage/pull/42
+                      if (value === undefined) {
+                        value = null;
+                      }
+
+                      // Save the original value to pass to the callback.
+                      var originalValue = value;
+
+                      return new Promise$1(function (resolve, reject) {
+                        var dbInfo = self._dbInfo;
+                        dbInfo.serializer.serialize(value, function (value, error) {
+                          if (error) {
+                            reject(error);
+                          } else {
+                            try {
+                              localStorage.setItem(dbInfo.keyPrefix + key, value);
+                              resolve(originalValue);
+                            } catch (e) {
+                              // localStorage capacity exceeded.
+                              // TODO: Make this a specific error/event.
+                              if (
+                                e.name === "QuotaExceededError" ||
+                                e.name === "NS_ERROR_DOM_QUOTA_REACHED"
+                              ) {
+                                reject(e);
+                              }
+                              reject(e);
+                            }
+                          }
+                        });
+                      });
+                    });
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  function dropInstance$2(options, callback) {
+                    callback = getCallback.apply(this, arguments);
+
+                    options = (typeof options !== "function" && options) || {};
+                    if (!options.name) {
+                      var currentConfig = this.config();
+                      options.name = options.name || currentConfig.name;
+                      options.storeName = options.storeName || currentConfig.storeName;
+                    }
+
+                    var self = this;
+                    var promise;
+                    if (!options.name) {
+                      promise = Promise$1.reject("Invalid arguments");
+                    } else {
+                      promise = new Promise$1(function (resolve) {
+                        if (!options.storeName) {
+                          resolve(options.name + "/");
+                        } else {
+                          resolve(_getKeyPrefix(options, self._defaultConfig));
+                        }
+                      }).then(function (keyPrefix) {
+                        for (var i = localStorage.length - 1; i >= 0; i--) {
+                          var key = localStorage.key(i);
+
+                          if (key.indexOf(keyPrefix) === 0) {
+                            localStorage.removeItem(key);
+                          }
+                        }
+                      });
+                    }
+
+                    executeCallback(promise, callback);
+                    return promise;
+                  }
+
+                  var localStorageWrapper = {
+                    _driver: "localStorageWrapper",
+                    _initStorage: _initStorage$2,
+                    _support: isLocalStorageValid(),
+                    iterate: iterate$2,
+                    getItem: getItem$2,
+                    setItem: setItem$2,
+                    removeItem: removeItem$2,
+                    clear: clear$2,
+                    length: length$2,
+                    key: key$2,
+                    keys: keys$2,
+                    dropInstance: dropInstance$2,
+                  };
+
+                  var sameValue = function sameValue(x, y) {
+                    return (
+                      x === y ||
+                      (typeof x === "number" && typeof y === "number" && isNaN(x) && isNaN(y))
+                    );
+                  };
+
+                  var includes = function includes(array, searchElement) {
+                    var len = array.length;
+                    var i = 0;
+                    while (i < len) {
+                      if (sameValue(array[i], searchElement)) {
+                        return true;
+                      }
+                      i++;
+                    }
+
+                    return false;
+                  };
+
+                  var isArray =
+                    Array.isArray ||
+                    function (arg) {
+                      return Object.prototype.toString.call(arg) === "[object Array]";
+                    };
+
+                  // Drivers are stored here when `defineDriver()` is called.
+                  // They are shared across all instances of localForage.
+                  var DefinedDrivers = {};
+
+                  var DriverSupport = {};
+
+                  var DefaultDrivers = {
+                    INDEXEDDB: asyncStorage,
+                    WEBSQL: webSQLStorage,
+                    LOCALSTORAGE: localStorageWrapper,
+                  };
+
+                  var DefaultDriverOrder = [
+                    DefaultDrivers.INDEXEDDB._driver,
+                    DefaultDrivers.WEBSQL._driver,
+                    DefaultDrivers.LOCALSTORAGE._driver,
+                  ];
+
+                  var OptionalDriverMethods = ["dropInstance"];
+
+                  var LibraryMethods = [
+                    "clear",
+                    "getItem",
+                    "iterate",
+                    "key",
+                    "keys",
+                    "length",
+                    "removeItem",
+                    "setItem",
+                  ].concat(OptionalDriverMethods);
+
+                  var DefaultConfig = {
+                    description: "",
+                    driver: DefaultDriverOrder.slice(),
+                    name: "localforage",
+                    // Default DB size is _JUST UNDER_ 5MB, as it's the highest size
+                    // we can use without a prompt.
+                    size: 4980736,
+                    storeName: "keyvaluepairs",
+                    version: 1.0,
+                  };
+
+                  function callWhenReady(localForageInstance, libraryMethod) {
+                    localForageInstance[libraryMethod] = function () {
+                      var _args = arguments;
+                      return localForageInstance.ready().then(function () {
+                        return localForageInstance[libraryMethod].apply(localForageInstance, _args);
+                      });
+                    };
+                  }
+
+                  function extend() {
+                    for (var i = 1; i < arguments.length; i++) {
+                      var arg = arguments[i];
+
+                      if (arg) {
+                        for (var _key in arg) {
+                          if (arg.hasOwnProperty(_key)) {
+                            if (isArray(arg[_key])) {
+                              arguments[0][_key] = arg[_key].slice();
+                            } else {
+                              arguments[0][_key] = arg[_key];
+                            }
+                          }
+                        }
+                      }
+                    }
+
+                    return arguments[0];
+                  }
+
+                  var LocalForage = (function () {
+                    function LocalForage(options) {
+                      _classCallCheck(this, LocalForage);
+
+                      for (var driverTypeKey in DefaultDrivers) {
+                        if (DefaultDrivers.hasOwnProperty(driverTypeKey)) {
+                          var driver = DefaultDrivers[driverTypeKey];
+                          var driverName = driver._driver;
+                          this[driverTypeKey] = driverName;
+
+                          if (!DefinedDrivers[driverName]) {
+                            // we don't need to wait for the promise,
+                            // since the default drivers can be defined
+                            // in a blocking manner
+                            this.defineDriver(driver);
+                          }
+                        }
+                      }
+
+                      this._defaultConfig = extend({}, DefaultConfig);
+                      this._config = extend({}, this._defaultConfig, options);
+                      this._driverSet = null;
+                      this._initDriver = null;
+                      this._ready = false;
+                      this._dbInfo = null;
+
+                      this._wrapLibraryMethodsWithReady();
+                      this.setDriver(this._config.driver)["catch"](function () {});
+                    }
+
+                    // Set any config values for localForage; can be called anytime before
+                    // the first API call (e.g. `getItem`, `setItem`).
+                    // We loop through options so we don't overwrite existing config
+                    // values.
+
+                    LocalForage.prototype.config = function config(options) {
+                      // If the options argument is an object, we use it to set values.
+                      // Otherwise, we return either a specified config value or all
+                      // config values.
+                      if (
+                        (typeof options === "undefined" ? "undefined" : _typeof(options)) ===
+                        "object"
+                      ) {
+                        // If localforage is ready and fully initialized, we can't set
+                        // any new configuration values. Instead, we return an error.
+                        if (this._ready) {
+                          return new Error(
+                            "Can't call config() after localforage " + "has been used."
+                          );
+                        }
+
+                        for (var i in options) {
+                          if (i === "storeName") {
+                            options[i] = options[i].replace(/\W/g, "_");
+                          }
+
+                          if (i === "version" && typeof options[i] !== "number") {
+                            return new Error("Database version must be a number.");
+                          }
+
+                          this._config[i] = options[i];
+                        }
+
+                        // after all config options are set and
+                        // the driver option is used, try setting it
+                        if ("driver" in options && options.driver) {
+                          return this.setDriver(this._config.driver);
+                        }
+
+                        return true;
+                      } else if (typeof options === "string") {
+                        return this._config[options];
+                      } else {
+                        return this._config;
+                      }
+                    };
+
+                    // Used to define a custom driver, shared across all instances of
+                    // localForage.
+
+                    LocalForage.prototype.defineDriver = function defineDriver(
+                      driverObject,
+                      callback,
+                      errorCallback
+                    ) {
+                      var promise = new Promise$1(function (resolve, reject) {
+                        try {
+                          var driverName = driverObject._driver;
+                          var complianceError = new Error(
+                            "Custom driver not compliant; see " +
+                              "https://mozilla.github.io/localForage/#definedriver"
+                          );
+
+                          // A driver name should be defined and not overlap with the
+                          // library-defined, default drivers.
+                          if (!driverObject._driver) {
+                            reject(complianceError);
+                            return;
+                          }
+
+                          var driverMethods = LibraryMethods.concat("_initStorage");
+                          for (var i = 0, len = driverMethods.length; i < len; i++) {
+                            var driverMethodName = driverMethods[i];
+
+                            // when the property is there,
+                            // it should be a method even when optional
+                            var isRequired = !includes(OptionalDriverMethods, driverMethodName);
+                            if (
+                              (isRequired || driverObject[driverMethodName]) &&
+                              typeof driverObject[driverMethodName] !== "function"
+                            ) {
+                              reject(complianceError);
+                              return;
+                            }
+                          }
+
+                          var configureMissingMethods = function configureMissingMethods() {
+                            var methodNotImplementedFactory = function methodNotImplementedFactory(
+                              methodName
+                            ) {
+                              return function () {
+                                var error = new Error(
+                                  "Method " +
+                                    methodName +
+                                    " is not implemented by the current driver"
+                                );
+                                var promise = Promise$1.reject(error);
+                                executeCallback(promise, arguments[arguments.length - 1]);
+                                return promise;
+                              };
+                            };
+
+                            for (var _i = 0, _len = OptionalDriverMethods.length; _i < _len; _i++) {
+                              var optionalDriverMethod = OptionalDriverMethods[_i];
+                              if (!driverObject[optionalDriverMethod]) {
+                                driverObject[optionalDriverMethod] =
+                                  methodNotImplementedFactory(optionalDriverMethod);
+                              }
+                            }
+                          };
+
+                          configureMissingMethods();
+
+                          var setDriverSupport = function setDriverSupport(support) {
+                            if (DefinedDrivers[driverName]) {
+                              console.info("Redefining LocalForage driver: " + driverName);
+                            }
+                            DefinedDrivers[driverName] = driverObject;
+                            DriverSupport[driverName] = support;
+                            // don't use a then, so that we can define
+                            // drivers that have simple _support methods
+                            // in a blocking manner
+                            resolve();
+                          };
+
+                          if ("_support" in driverObject) {
+                            if (
+                              driverObject._support &&
+                              typeof driverObject._support === "function"
+                            ) {
+                              driverObject._support().then(setDriverSupport, reject);
+                            } else {
+                              setDriverSupport(!!driverObject._support);
+                            }
+                          } else {
+                            setDriverSupport(true);
+                          }
+                        } catch (e) {
+                          reject(e);
+                        }
+                      });
+
+                      executeTwoCallbacks(promise, callback, errorCallback);
+                      return promise;
+                    };
+
+                    LocalForage.prototype.driver = function driver() {
+                      return this._driver || null;
+                    };
+
+                    LocalForage.prototype.getDriver = function getDriver(
+                      driverName,
+                      callback,
+                      errorCallback
+                    ) {
+                      var getDriverPromise = DefinedDrivers[driverName]
+                        ? Promise$1.resolve(DefinedDrivers[driverName])
+                        : Promise$1.reject(new Error("Driver not found."));
+
+                      executeTwoCallbacks(getDriverPromise, callback, errorCallback);
+                      return getDriverPromise;
+                    };
+
+                    LocalForage.prototype.getSerializer = function getSerializer(callback) {
+                      var serializerPromise = Promise$1.resolve(localforageSerializer);
+                      executeTwoCallbacks(serializerPromise, callback);
+                      return serializerPromise;
+                    };
+
+                    LocalForage.prototype.ready = function ready(callback) {
+                      var self = this;
+
+                      var promise = self._driverSet.then(function () {
+                        if (self._ready === null) {
+                          self._ready = self._initDriver();
+                        }
+
+                        return self._ready;
+                      });
+
+                      executeTwoCallbacks(promise, callback, callback);
+                      return promise;
+                    };
+
+                    LocalForage.prototype.setDriver = function setDriver(
+                      drivers,
+                      callback,
+                      errorCallback
+                    ) {
+                      var self = this;
+
+                      if (!isArray(drivers)) {
+                        drivers = [drivers];
+                      }
+
+                      var supportedDrivers = this._getSupportedDrivers(drivers);
+
+                      function setDriverToConfig() {
+                        self._config.driver = self.driver();
+                      }
+
+                      function extendSelfWithDriver(driver) {
+                        self._extend(driver);
+                        setDriverToConfig();
+
+                        self._ready = self._initStorage(self._config);
+                        return self._ready;
+                      }
+
+                      function initDriver(supportedDrivers) {
+                        return function () {
+                          var currentDriverIndex = 0;
+
+                          function driverPromiseLoop() {
+                            while (currentDriverIndex < supportedDrivers.length) {
+                              var driverName = supportedDrivers[currentDriverIndex];
+                              currentDriverIndex++;
+
+                              self._dbInfo = null;
+                              self._ready = null;
+
+                              return self
+                                .getDriver(driverName)
+                                .then(extendSelfWithDriver)
+                                ["catch"](driverPromiseLoop);
+                            }
+
+                            setDriverToConfig();
+                            var error = new Error("No available storage method found.");
+                            self._driverSet = Promise$1.reject(error);
+                            return self._driverSet;
+                          }
+
+                          return driverPromiseLoop();
+                        };
+                      }
+
+                      // There might be a driver initialization in progress
+                      // so wait for it to finish in order to avoid a possible
+                      // race condition to set _dbInfo
+                      var oldDriverSetDone =
+                        this._driverSet !== null
+                          ? this._driverSet["catch"](function () {
+                              return Promise$1.resolve();
+                            })
+                          : Promise$1.resolve();
+
+                      this._driverSet = oldDriverSetDone
+                        .then(function () {
+                          var driverName = supportedDrivers[0];
+                          self._dbInfo = null;
+                          self._ready = null;
+
+                          return self.getDriver(driverName).then(function (driver) {
+                            self._driver = driver._driver;
+                            setDriverToConfig();
+                            self._wrapLibraryMethodsWithReady();
+                            self._initDriver = initDriver(supportedDrivers);
+                          });
+                        })
+                        ["catch"](function () {
+                          setDriverToConfig();
+                          var error = new Error("No available storage method found.");
+                          self._driverSet = Promise$1.reject(error);
+                          return self._driverSet;
+                        });
+
+                      executeTwoCallbacks(this._driverSet, callback, errorCallback);
+                      return this._driverSet;
+                    };
+
+                    LocalForage.prototype.supports = function supports(driverName) {
+                      return !!DriverSupport[driverName];
+                    };
+
+                    LocalForage.prototype._extend = function _extend(libraryMethodsAndProperties) {
+                      extend(this, libraryMethodsAndProperties);
+                    };
+
+                    LocalForage.prototype._getSupportedDrivers = function _getSupportedDrivers(
+                      drivers
+                    ) {
+                      var supportedDrivers = [];
+                      for (var i = 0, len = drivers.length; i < len; i++) {
+                        var driverName = drivers[i];
+                        if (this.supports(driverName)) {
+                          supportedDrivers.push(driverName);
+                        }
+                      }
+                      return supportedDrivers;
+                    };
+
+                    LocalForage.prototype._wrapLibraryMethodsWithReady =
+                      function _wrapLibraryMethodsWithReady() {
+                        // Add a stub for each driver API method that delays the call to the
+                        // corresponding driver method until localForage is ready. These stubs
+                        // will be replaced by the driver methods as soon as the driver is
+                        // loaded, so there is no performance impact.
+                        for (var i = 0, len = LibraryMethods.length; i < len; i++) {
+                          callWhenReady(this, LibraryMethods[i]);
+                        }
+                      };
+
+                    LocalForage.prototype.createInstance = function createInstance(options) {
+                      return new LocalForage(options);
+                    };
+
+                    return LocalForage;
+                  })();
+
+                  // The actual localForage object that we expose as a module or via a
+                  // global. It's extended by pulling in one of our other libraries.
+
+                  var localforage_js = new LocalForage();
+
+                  module.exports = localforage_js;
+                },
+                { 3: 3 },
+              ],
+            },
+            {},
+            [4]
+          )(4);
+        });
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(27)));
+
+      /***/
+    },
+    /* 33 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (global, process) {
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "b", function () {
+          return getGlobalNamespace;
+        });
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+          return getGlobal;
+        });
+        /**
+         * @license
+         * Copyright 2020 Google Inc. All Rights Reserved.
+         * Licensed under the Apache License, Version 2.0 (the "License");
+         * you may not use this file except in compliance with the License.
+         * You may obtain a copy of the License at
+         *
+         * http://www.apache.org/licenses/LICENSE-2.0
+         *
+         * Unless required by applicable law or agreed to in writing, software
+         * distributed under the License is distributed on an "AS IS" BASIS,
+         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+         * See the License for the specific language governing permissions and
+         * limitations under the License.
+         * =============================================================================
+         */
+        // Note that the identifier globalNameSpace is scoped to this module, but will
+        // always resolve to the same global object regardless of how the module is
+        // resolved.
+        // tslint:disable-next-line:no-any
+        let globalNameSpace;
+        // tslint:disable-next-line:no-any
+        function getGlobalNamespace() {
+          if (globalNameSpace == null) {
+            // tslint:disable-next-line:no-any
+            let ns;
+            if (typeof window !== "undefined") {
+              ns = window;
+            } else if (typeof global !== "undefined") {
+              ns = global;
+            } else if (typeof process !== "undefined") {
+              ns = process;
+            } else if (typeof self !== "undefined") {
+              ns = self;
+            } else {
+              throw new Error("Could not find a global object");
+            }
+            globalNameSpace = ns;
+          }
+          return globalNameSpace;
+        }
+        // tslint:disable-next-line:no-any
+        function getGlobalMap() {
+          const ns = getGlobalNamespace();
+          if (ns._tfGlobals == null) {
+            ns._tfGlobals = new Map();
+          }
+          return ns._tfGlobals;
+        }
+        /**
+         * Returns a globally accessible 'singleton' object.
+         *
+         * @param key the name of the object
+         * @param init a function to initialize to initialize this object
+         *             the first time it is fetched.
+         */
+        function getGlobal(key, init) {
+          const globalMap = getGlobalMap();
+          if (globalMap.has(key)) {
+            return globalMap.get(key);
+          } else {
+            const singleton = init();
+            globalMap.set(key, singleton);
+            return globalMap.get(key);
+          }
+        }
+        //# sourceMappingURL=global_util.js.map
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(27), __webpack_require__(35)));
+
+      /***/
+    },
+    /* 34 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return DTYPE_VALUE_SIZE_MAP;
+      });
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /* Type definitions for exporting and importing of models. */
+      /**
+       * A map from Tensor dtype to number of bytes per element of the Tensor.
+       */
+      const DTYPE_VALUE_SIZE_MAP = {
+        float32: 4,
+        float16: 2,
+        int32: 4,
+        uint16: 2,
+        uint8: 1,
+        bool: 1,
+        complex64: 8,
+      };
+      //# sourceMappingURL=types.js.map
+
+      /***/
+    },
+    /* 35 */
+    /***/ function (module, exports) {
+      // shim for using process in browser
+      var process = (module.exports = {});
+
+      // cached from whatever global is present so that test runners that stub it
+      // don't break things.  But we need to wrap it in a try catch in case it is
+      // wrapped in strict mode code which doesn't define any globals.  It's inside a
+      // function because try/catches deoptimize in certain engines.
+
+      var cachedSetTimeout;
+      var cachedClearTimeout;
+
+      function defaultSetTimout() {
+        throw new Error("setTimeout has not been defined");
+      }
+      function defaultClearTimeout() {
+        throw new Error("clearTimeout has not been defined");
+      }
+      (function () {
+        try {
+          if (typeof setTimeout === "function") {
+            cachedSetTimeout = setTimeout;
+          } else {
+            cachedSetTimeout = defaultSetTimout;
+          }
+        } catch (e) {
+          cachedSetTimeout = defaultSetTimout;
+        }
+        try {
+          if (typeof clearTimeout === "function") {
+            cachedClearTimeout = clearTimeout;
+          } else {
+            cachedClearTimeout = defaultClearTimeout;
+          }
+        } catch (e) {
+          cachedClearTimeout = defaultClearTimeout;
+        }
+      })();
+      function runTimeout(fun) {
+        if (cachedSetTimeout === setTimeout) {
+          //normal enviroments in sane situations
+          return setTimeout(fun, 0);
+        }
+        // if setTimeout wasn't available but was latter defined
+        if ((cachedSetTimeout === defaultSetTimout || !cachedSetTimeout) && setTimeout) {
+          cachedSetTimeout = setTimeout;
+          return setTimeout(fun, 0);
+        }
+        try {
+          // when when somebody has screwed with setTimeout but no I.E. maddness
+          return cachedSetTimeout(fun, 0);
+        } catch (e) {
+          try {
+            // When we are in I.E. but the script has been evaled so I.E. doesn't trust the global object when called normally
+            return cachedSetTimeout.call(null, fun, 0);
+          } catch (e) {
+            // same as above but when it's a version of I.E. that must have the global object for 'this', hopfully our context correct otherwise it will throw a global error
+            return cachedSetTimeout.call(this, fun, 0);
+          }
+        }
+      }
+      function runClearTimeout(marker) {
+        if (cachedClearTimeout === clearTimeout) {
+          //normal enviroments in sane situations
+          return clearTimeout(marker);
+        }
+        // if clearTimeout wasn't available but was latter defined
+        if ((cachedClearTimeout === defaultClearTimeout || !cachedClearTimeout) && clearTimeout) {
+          cachedClearTimeout = clearTimeout;
+          return clearTimeout(marker);
+        }
+        try {
+          // when when somebody has screwed with setTimeout but no I.E. maddness
+          return cachedClearTimeout(marker);
+        } catch (e) {
+          try {
+            // When we are in I.E. but the script has been evaled so I.E. doesn't  trust the global object when called normally
+            return cachedClearTimeout.call(null, marker);
+          } catch (e) {
+            // same as above but when it's a version of I.E. that must have the global object for 'this', hopfully our context correct otherwise it will throw a global error.
+            // Some versions of I.E. have different rules for clearTimeout vs setTimeout
+            return cachedClearTimeout.call(this, marker);
+          }
+        }
+      }
+      var queue = [];
+      var draining = false;
+      var currentQueue;
+      var queueIndex = -1;
+
+      function cleanUpNextTick() {
+        if (!draining || !currentQueue) {
+          return;
+        }
+        draining = false;
+        if (currentQueue.length) {
+          queue = currentQueue.concat(queue);
+        } else {
+          queueIndex = -1;
+        }
+        if (queue.length) {
+          drainQueue();
+        }
+      }
+
+      function drainQueue() {
+        if (draining) {
+          return;
+        }
+        var timeout = runTimeout(cleanUpNextTick);
+        draining = true;
+
+        var len = queue.length;
+        while (len) {
+          currentQueue = queue;
+          queue = [];
+          while (++queueIndex < len) {
+            if (currentQueue) {
+              currentQueue[queueIndex].run();
+            }
+          }
+          queueIndex = -1;
+          len = queue.length;
+        }
+        currentQueue = null;
+        draining = false;
+        runClearTimeout(timeout);
+      }
+
+      process.nextTick = function (fun) {
+        var args = new Array(arguments.length - 1);
+        if (arguments.length > 1) {
+          for (var i = 1; i < arguments.length; i++) {
+            args[i - 1] = arguments[i];
+          }
+        }
+        queue.push(new Item(fun, args));
+        if (queue.length === 1 && !draining) {
+          runTimeout(drainQueue);
+        }
+      };
+
+      // v8 likes predictible objects
+      function Item(fun, array) {
+        this.fun = fun;
+        this.array = array;
+      }
+      Item.prototype.run = function () {
+        this.fun.apply(null, this.array);
+      };
+      process.title = "browser";
+      process.browser = true;
+      process.env = {};
+      process.argv = [];
+      process.version = ""; // empty string to avoid regexp issues
+      process.versions = {};
+
+      function noop() {}
+
+      process.on = noop;
+      process.addListener = noop;
+      process.once = noop;
+      process.off = noop;
+      process.removeListener = noop;
+      process.removeAllListeners = noop;
+      process.emit = noop;
+      process.prependListener = noop;
+      process.prependOnceListener = noop;
+
+      process.listeners = function (name) {
+        return [];
+      };
+
+      process.binding = function (name) {
+        throw new Error("process.binding is not supported");
+      };
+
+      process.cwd = function () {
+        return "/";
+      };
+      process.chdir = function (dir) {
+        throw new Error("process.chdir is not supported");
+      };
+      process.umask = function () {
+        return 0;
+      };
+
+      /***/
+    },
+    /* 36 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isMobile",
+        function () {
+          return isMobile;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "isBrowser",
+        function () {
+          return isBrowser;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // tslint:disable-next-line:no-any
+      function _isNavigatorDefined() {
+        return typeof navigator !== "undefined" && navigator != null;
+      }
+      function isMobile() {
+        if (_isNavigatorDefined()) {
+          // tslint:disable-next-line:no-any
+          const a = navigator.userAgent || navigator.vendor || window.opera;
+          // tslint:disable-next-line:max-line-length
+          return (
+            /(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(
+              a
+            ) ||
+            // tslint:disable-next-line:max-line-length
+            /1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(
+              a.substr(0, 4)
+            )
+          );
+        }
+        return false;
+      }
+      function isBrowser() {
+        return (
+          (typeof window !== "undefined" && window.document != null) ||
+          //@ts-ignore
+          typeof WorkerGlobalScope !== "undefined"
+        );
+      }
+      //# sourceMappingURL=device_util.js.map
+
+      /***/
+    },
+    /* 37 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return maxImpl;
+      });
+      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
+        __webpack_require__(0);
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function maxImpl(aVals, reduceSize, outShape, dtype) {
+        const vals = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__[
+          "util"
+        ].getTypedArrayFromDType(
+          dtype,
+          _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["util"].sizeFromShape(outShape)
+        );
+        for (let i = 0; i < vals.length; ++i) {
+          const offset = i * reduceSize;
+          let max = aVals[offset];
+          for (let j = 0; j < reduceSize; ++j) {
+            const value = aVals[offset + j];
+            if (value > max) {
+              max = value;
+            }
+          }
+          vals[i] = max;
+        }
+        return vals;
+      }
+      //# sourceMappingURL=Max_impl.js.map
+
+      /***/
+    },
+    /* 38 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      // ESM COMPAT FLAG
+      __webpack_require__.r(__webpack_exports__);
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "GraphModel", function () {
+        return /* reexport */ graph_model_GraphModel;
+      });
+      __webpack_require__.d(__webpack_exports__, "loadGraphModel", function () {
+        return /* reexport */ loadGraphModel;
+      });
+      __webpack_require__.d(__webpack_exports__, "deregisterOp", function () {
+        return /* reexport */ register["a" /* deregisterOp */];
+      });
+      __webpack_require__.d(__webpack_exports__, "registerOp", function () {
+        return /* reexport */ register["c" /* registerOp */];
+      });
+      __webpack_require__.d(__webpack_exports__, "version_converter", function () {
+        return /* reexport */ version;
+      });
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
+      var dist = __webpack_require__(0);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/operation_mapper.js
+      var operation_mapper = __webpack_require__(15);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/utils.js
+      var utils = __webpack_require__(2);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/custom_op/node_value_impl.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Helper class for lookup inputs and params for nodes in the model graph.
+       */
+      class node_value_impl_NodeValueImpl {
+        constructor(node, tensorMap, context) {
+          this.node = node;
+          this.tensorMap = tensorMap;
+          this.context = context;
+          this.inputs = [];
+          this.attrs = {};
+          this.inputs = node.inputNames.map((name) => this.getInput(name));
+          if (node.rawAttrs != null) {
+            this.attrs = Object.keys(node.rawAttrs).reduce((attrs, key) => {
+              attrs[key] = this.getAttr(key);
+              return attrs;
+            }, {});
+          }
+        }
+        /**
+         * Return the value of the attribute or input param.
+         * @param name String: name of attribute or input param.
+         */
+        getInput(name) {
+          return Object(utils["c" /* getTensor */])(name, this.tensorMap, this.context);
+        }
+        /**
+         * Return the value of the attribute or input param.
+         * @param name String: name of attribute or input param.
+         */
+        getAttr(name, defaultValue) {
+          const value = this.node.rawAttrs[name];
+          if (value.tensor != null) {
+            return Object(utils["c" /* getTensor */])(name, this.tensorMap, this.context);
+          }
+          if (value.i != null || value.f != null) {
+            return Object(operation_mapper["f" /* getNumberParam */])(
+              this.node.rawAttrs,
+              name,
+              defaultValue
+            );
+          }
+          if (value.s != null) {
+            return Object(operation_mapper["i" /* getStringParam */])(
+              this.node.rawAttrs,
+              name,
+              defaultValue
+            );
+          }
+          if (value.b != null) {
+            return Object(operation_mapper["c" /* getBoolParam */])(
+              this.node.rawAttrs,
+              name,
+              defaultValue
+            );
+          }
+          if (value.shape != null) {
+            return Object(operation_mapper["k" /* getTensorShapeParam */])(
+              this.node.rawAttrs,
+              name,
+              defaultValue
+            );
+          }
+          if (value.type != null) {
+            return Object(operation_mapper["e" /* getDtypeParam */])(
+              this.node.rawAttrs,
+              name,
+              defaultValue
+            );
+          }
+          if (value.list != null) {
+            if (value.list.i != null || value.list.f != null) {
+              return Object(operation_mapper["g" /* getNumericArrayParam */])(
+                this.node.rawAttrs,
+                name,
+                defaultValue
+              );
+            }
+            if (value.list.s != null) {
+              return Object(operation_mapper["h" /* getStringArrayParam */])(
+                this.node.rawAttrs,
+                name,
+                defaultValue
+              );
+            }
+            if (value.list.shape != null) {
+              return Object(operation_mapper["j" /* getTensorShapeArrayParam */])(
+                this.node.rawAttrs,
+                name,
+                defaultValue
+              );
+            }
+            if (value.list.b != null) {
+              return Object(operation_mapper["b" /* getBoolArrayParam */])(
+                this.node.rawAttrs,
+                name,
+                defaultValue
+              );
+            }
+            if (value.list.type != null) {
+              return Object(operation_mapper["d" /* getDtypeArrayParam */])(
+                this.node.rawAttrs,
+                name,
+                defaultValue
+              );
+            }
+          }
+          return defaultValue;
+        }
+      }
+      //# sourceMappingURL=node_value_impl.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/custom_op/register.js
+      var register = __webpack_require__(24);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/arithmetic_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "BiasAdd":
+          case "AddV2":
+          case "Add": {
+            return [
+              dist["add"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "AddN": {
+            return [
+              dist["addN"](
+                Object(utils["b" /* getParamValue */])("tensors", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "FloorMod":
+          case "Mod":
+            return [
+              dist["mod"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          case "Mul":
+            return [
+              dist["mul"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          case "RealDiv":
+          case "Div": {
+            return [
+              dist["div"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "DivNoNan": {
+            return [
+              dist["divNoNan"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "FloorDiv": {
+            return [
+              dist["floorDiv"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Sub": {
+            return [
+              dist["sub"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Minimum": {
+            return [
+              dist["minimum"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Maximum": {
+            return [
+              dist["maximum"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Pow": {
+            return [
+              dist["pow"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "SquaredDifference": {
+            return [
+              dist["squaredDifference"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const CATEGORY = "arithmetic";
+      //# sourceMappingURL=arithmetic_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/basic_math_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const basic_math_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "Abs":
+          case "ComplexAbs":
+            return [
+              dist["abs"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Acos":
+            return [
+              dist["acos"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Acosh":
+            return [
+              dist["acosh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Asin":
+            return [
+              dist["asin"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Asinh":
+            return [
+              dist["asinh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Atan":
+            return [
+              dist["atan"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Atan2":
+            return [
+              dist["atan2"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("y", node, tensorMap, context)
+              ),
+            ];
+          case "Atanh":
+            return [
+              dist["atanh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Ceil":
+            return [
+              dist["ceil"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Complex":
+            return [
+              dist["complex"](
+                Object(utils["b" /* getParamValue */])("real", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("imag", node, tensorMap, context)
+              ),
+            ];
+          case "Cos":
+            return [
+              dist["cos"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Cosh":
+            return [
+              dist["cosh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Elu":
+            return [
+              dist["elu"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Erf":
+            return [
+              dist["erf"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Exp":
+            return [
+              dist["exp"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Expm1": {
+            return [
+              dist["expm1"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "Floor":
+            return [
+              dist["floor"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Log":
+            return [
+              dist["log"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Log1p": {
+            return [
+              dist["log1p"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "Imag":
+            return [
+              dist["imag"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Neg":
+            return [
+              dist["neg"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Reciprocal": {
+            return [
+              dist["reciprocal"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Real":
+            return [
+              dist["real"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Relu":
+            return [
+              dist["relu"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Round": {
+            return [
+              dist["round"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "Selu":
+            return [
+              dist["selu"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Sigmoid":
+            return [
+              dist["sigmoid"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
+              ),
+            ];
+          case "Sin":
+            return [
+              dist["sin"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Sign": {
+            return [
+              dist["sign"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "Sinh": {
+            return [
+              dist["sinh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "Softplus": {
+            return [
+              dist["softplus"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Sqrt": {
+            return [
+              dist["sqrt"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "Square": {
+            return [
+              dist["square"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "Tanh": {
+            return [
+              dist["tanh"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "Tan":
+            return [
+              dist["tan"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          case "Relu6":
+          case "ClipByValue":
+            return [
+              dist["clipByValue"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("clipValueMin", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("clipValueMax", node, tensorMap, context)
+              ),
+            ];
+          case "Rsqrt":
+            return [
+              dist["rsqrt"](
+                Object(utils["c" /* getTensor */])(node.inputNames[0], tensorMap, context)
+              ),
+            ];
+          case "Prod":
+            return [
+              dist["prod"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("axes", node, tensorMap, context)
+              ),
+            ];
+          case "LeakyRelu":
+            return [
+              dist["leakyRelu"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("alpha", node, tensorMap, context)
+              ),
+            ];
+          case "Prelu":
+            return [
+              dist["prelu"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("alpha", node, tensorMap, context)
+              ),
+            ];
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const basic_math_executor_CATEGORY = "basic_math";
+      //# sourceMappingURL=basic_math_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_utils.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      /**
+       * This differs from util.assertShapesMatch in that it allows values of
+       * negative one, an undefined size of a dimensinon, in a shape to match
+       * anything.
+       */
+
+      function assertShapesMatchAllowUndefinedSize(shapeA, shapeB, errorMessagePrefix = "") {
+        dist["util"].assert(
+          shapesEqualAllowUndefinedSize(shapeA, shapeB),
+          () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`
+        );
+      }
+      function shapesEqualAllowUndefinedSize(n1, n2) {
+        if (n1.length !== n2.length) {
+          return false;
+        }
+        for (let i = 0; i < n1.length; i++) {
+          if (n1[i] !== -1 && n2[i] !== -1 && n1[i] !== n2[i]) {
+            return false;
+          }
+        }
+        return true;
+      }
+      //# sourceMappingURL=tensor_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_array.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * The TensorArray object keeps an array of Tensors.  It
+       * allows reading from the array and writing to the array.
+       */
+      class tensor_array_TensorArray {
+        constructor(
+          name,
+          dtype,
+          maxSize,
+          elementShape,
+          identicalElementShapes,
+          dynamicSize,
+          clearAfterRead
+        ) {
+          this.name = name;
+          this.dtype = dtype;
+          this.maxSize = maxSize;
+          this.elementShape = elementShape;
+          this.identicalElementShapes = identicalElementShapes;
+          this.dynamicSize = dynamicSize;
+          this.clearAfterRead = clearAfterRead;
+          this.tensors = [];
+          this.closed_ = false;
+          this.id = tensor_array_TensorArray.nextId++;
+        }
+        get closed() {
+          return this.closed_;
+        }
+        /**
+         * Close the current TensorArray.
+         */
+        clearAndClose() {
+          this.tensors.forEach((tensor) => tensor.tensor.dispose());
+          this.tensors = [];
+          this.closed_ = true;
+        }
+        size() {
+          return this.tensors.length;
+        }
+        /**
+         * Read the value at location index in the TensorArray.
+         * @param index Number the index to read from.
+         */
+        read(index) {
+          if (this.closed_) {
+            throw new Error(`TensorArray ${this.name} has already been closed.`);
+          }
+          if (index < 0 || index >= this.size()) {
+            throw new Error(`Tried to read from index ${index}, but array size is: ${this.size()}`);
+          }
+          const tensorWithState = this.tensors[index];
+          if (tensorWithState.cleared) {
+            throw new Error(
+              `TensorArray ${this.name}: Could not read index ${index} twice because it was cleared after a previous read ` +
+                `(perhaps try setting clear_after_read = false?).`
+            );
+          }
+          if (this.clearAfterRead) {
+            tensorWithState.cleared = true;
+          }
+          tensorWithState.read = true;
+          return tensorWithState.tensor;
+        }
+        /**
+         * Helper method to read multiple tensors from the specified indices.
+         */
+        readMany(indices) {
+          return indices.map((index) => this.read(index));
+        }
+        /**
+         * Write value into the index of the TensorArray.
+         * @param index number the index to write to.
+         * @param tensor
+         */
+        write(index, tensor) {
+          if (this.closed_) {
+            throw new Error(`TensorArray ${this.name} has already been closed.`);
+          }
+          if (index < 0 || (!this.dynamicSize && index >= this.maxSize)) {
+            throw new Error(
+              `Tried to write to index ${index}, but array is not resizeable and size is: ${this.maxSize}`
+            );
+          }
+          const t = this.tensors[index] || {};
+          if (tensor.dtype !== this.dtype) {
+            throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index},
+          because the value dtype is ${tensor.dtype}, but TensorArray dtype is ${this.dtype}.`);
+          }
+          // Set the shape for the first time write to unknow shape tensor array
+          if (this.size() === 0 && (this.elementShape == null || this.elementShape.length === 0)) {
+            this.elementShape = tensor.shape;
+          }
+          assertShapesMatchAllowUndefinedSize(
+            this.elementShape,
+            tensor.shape,
+            `TensorArray ${this.name}: Could not write to TensorArray index ${index}.`
+          );
+          if (t && t.read) {
+            throw new Error(
+              `TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been read.`
+            );
+          }
+          if (t && t.written) {
+            throw new Error(
+              `TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been written.`
+            );
+          }
+          t.tensor = tensor;
+          t.written = true;
+          this.tensors[index] = t;
+        }
+        /**
+         * Helper method to write multiple tensors to the specified indices.
+         */
+        writeMany(indices, tensors) {
+          if (indices.length !== tensors.length) {
+            throw new Error(
+              `TensorArray ${this.name}: could not write multiple tensors,` +
+                `because the index size: ${indices.length} is not the same as tensors size: ${tensors.length}.`
+            );
+          }
+          indices.forEach((i, index) => this.write(i, tensors[index]));
+        }
+        /**
+         * Return selected values in the TensorArray as a packed Tensor. All of
+         * selected values must have been written and their shapes must all match.
+         * @param [indices] number[] Optional. Taking values in [0, max_value). If the
+         *    TensorArray is not dynamic, max_value=size(). If not specified returns
+         *    all tensors in the original order.
+         * @param [dtype]
+         */
+        gather(indices, dtype) {
+          if (!!dtype && dtype !== this.dtype) {
+            throw new Error(
+              `TensorArray dtype is ${this.dtype} but gather requested dtype ${dtype}`
+            );
+          }
+          if (!indices) {
+            indices = [];
+            for (let i = 0; i < this.size(); i++) {
+              indices.push(i);
+            }
+          } else {
+            indices = indices.slice(0, this.size());
+          }
+          if (indices.length === 0) {
+            return Object(dist["tensor"])([], [0].concat(this.elementShape));
+          }
+          // Read all the PersistentTensors into a vector to keep track of
+          // their memory.
+          const tensors = this.readMany(indices);
+          assertShapesMatchAllowUndefinedSize(
+            this.elementShape,
+            tensors[0].shape,
+            "TensorArray shape mismatch: "
+          );
+          return Object(dist["stack"])(tensors, 0);
+        }
+        /**
+         * Return the values in the TensorArray as a concatenated Tensor.
+         */
+        concat(dtype) {
+          if (!!dtype && dtype !== this.dtype) {
+            throw new Error(
+              `TensorArray dtype is ${this.dtype} but concat requested dtype ${dtype}`
+            );
+          }
+          if (this.size() === 0) {
+            return Object(dist["tensor"])([], [0].concat(this.elementShape));
+          }
+          const indices = [];
+          for (let i = 0; i < this.size(); i++) {
+            indices.push(i);
+          }
+          // Collect all the tensors from the tensors array.
+          const tensors = this.readMany(indices);
+          assertShapesMatchAllowUndefinedSize(
+            this.elementShape,
+            tensors[0].shape,
+            `TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${tensors[0].shape})`
+          );
+          return Object(dist["concat"])(tensors, 0);
+        }
+        /**
+         * Scatter the values of a Tensor in specific indices of a TensorArray.
+         * @param indices nummber[] values in [0, max_value). If the
+         *    TensorArray is not dynamic, max_value=size().
+         * @param tensor Tensor input tensor.
+         */
+        scatter(indices, tensor) {
+          if (tensor.dtype !== this.dtype) {
+            throw new Error(
+              `TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor.dtype}`
+            );
+          }
+          if (indices.length !== tensor.shape[0]) {
+            throw new Error(
+              `Expected len(indices) == tensor.shape[0], but saw: ${indices.length} vs. ${tensor.shape[0]}`
+            );
+          }
+          const maxIndex = Math.max(...indices);
+          if (!this.dynamicSize && maxIndex >= this.maxSize) {
+            throw new Error(`Max index must be < array size (${maxIndex}  vs. ${this.maxSize})`);
+          }
+          this.writeMany(indices, Object(dist["unstack"])(tensor, 0));
+        }
+        /**
+         * Split the values of a Tensor into the TensorArray.
+         * @param length number[] with the lengths to use when splitting value along
+         *    its first dimension.
+         * @param tensor Tensor, the tensor to split.
+         */
+        split(length, tensor) {
+          if (tensor.dtype !== this.dtype) {
+            throw new Error(
+              `TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor.dtype}`
+            );
+          }
+          let totalLength = 0;
+          const cumulativeLengths = length.map((len) => {
+            totalLength += len;
+            return totalLength;
+          });
+          if (totalLength !== tensor.shape[0]) {
+            throw new Error(`Expected sum of lengths to be equal to
+          tensor.shape[0], but sum of lengths is
+        ${totalLength}, and tensor's shape is: ${tensor.shape}`);
+          }
+          if (!this.dynamicSize && length.length !== this.maxSize) {
+            throw new Error(
+              `TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${length.length}), ` +
+                "and the TensorArray is not marked as dynamically resizeable"
+            );
+          }
+          const elementPerRow = totalLength === 0 ? 0 : tensor.size / totalLength;
+          const tensors = [];
+          Object(dist["tidy"])(() => {
+            tensor = tensor.reshape([1, totalLength, elementPerRow]);
+            for (let i = 0; i < length.length; ++i) {
+              const previousLength = i === 0 ? 0 : cumulativeLengths[i - 1];
+              const indices = [0, previousLength, 0];
+              const sizes = [1, length[i], elementPerRow];
+              tensors[i] = Object(dist["slice"])(tensor, indices, sizes).reshape(this.elementShape);
+            }
+            return tensors;
+          });
+          const indices = [];
+          for (let i = 0; i < length.length; i++) {
+            indices[i] = i;
+          }
+          this.writeMany(indices, tensors);
+        }
+      }
+      tensor_array_TensorArray.nextId = 0;
+      //# sourceMappingURL=tensor_array.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/control_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const control_executor_executeOp = async (node, tensorMap, context) => {
+        switch (node.op) {
+          case "If":
+          case "StatelessIf": {
+            const thenFunc = Object(utils["b" /* getParamValue */])(
+              "thenBranch",
+              node,
+              tensorMap,
+              context
+            );
+            const elseFunc = Object(utils["b" /* getParamValue */])(
+              "elseBranch",
+              node,
+              tensorMap,
+              context
+            );
+            const cond = Object(utils["b" /* getParamValue */])("cond", node, tensorMap, context);
+            const args = Object(utils["b" /* getParamValue */])("args", node, tensorMap, context);
+            const condValue = await cond.data();
+            if (condValue[0]) {
+              return context.functionMap[thenFunc].executeFunctionAsync(args);
+            } else {
+              return context.functionMap[elseFunc].executeFunctionAsync(args);
+            }
+          }
+          case "While":
+          case "StatelessWhile": {
+            const bodyFunc = Object(utils["b" /* getParamValue */])(
+              "body",
+              node,
+              tensorMap,
+              context
+            );
+            const condFunc = Object(utils["b" /* getParamValue */])(
+              "cond",
+              node,
+              tensorMap,
+              context
+            );
+            const args = Object(utils["b" /* getParamValue */])("args", node, tensorMap, context);
+            const condTensor = (await context.functionMap[condFunc].executeFunctionAsync(args))[0];
+            let condValue = await condTensor.data();
+            let result = args;
+            while (condValue[0]) {
+              result = await context.functionMap[bodyFunc].executeFunctionAsync(result);
+              const condTensor = (
+                await context.functionMap[condFunc].executeFunctionAsync(result)
+              )[0];
+              condValue = await condTensor.data();
+            }
+            return result;
+          }
+          case "LoopCond":
+            return [
+              Object(utils["b" /* getParamValue */])("pred", node, tensorMap, context).clone(),
+            ];
+          case "Switch": {
+            const pred = Object(utils["b" /* getParamValue */])("pred", node, tensorMap, context);
+            const data = Object(utils["b" /* getParamValue */])("data", node, tensorMap, context);
+            // Outputs nodes :0 => false, :1 => true
+            return (await pred.data())[0] ? [undefined, data.clone()] : [data.clone(), undefined];
+          }
+          case "Merge":
+            const inputName = node.inputNames.find(
+              (name) => Object(utils["c" /* getTensor */])(name, tensorMap, context) !== undefined
+            );
+            return inputName
+              ? [Object(utils["c" /* getTensor */])(inputName, tensorMap, context).clone()]
+              : undefined;
+          case "Enter":
+            const frameId = Object(utils["b" /* getParamValue */])(
+              "frameName",
+              node,
+              tensorMap,
+              context
+            );
+            const data = Object(utils["b" /* getParamValue */])("tensor", node, tensorMap, context);
+            context.enterFrame(frameId);
+            return [data.clone()];
+          case "Exit":
+            const tensor = Object(utils["b" /* getParamValue */])(
+              "tensor",
+              node,
+              tensorMap,
+              context
+            );
+            context.exitFrame();
+            return [tensor.clone()];
+          case "NextIteration":
+            const input = Object(utils["b" /* getParamValue */])(
+              "tensor",
+              node,
+              tensorMap,
+              context
+            );
+            context.nextIteration();
+            return [input.clone()];
+          case "TensorArrayV3":
+            const size = Object(utils["b" /* getParamValue */])("size", node, tensorMap, context);
+            const dtype = Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context);
+            const elementShape = Object(utils["b" /* getParamValue */])(
+              "elementShape",
+              node,
+              tensorMap,
+              context
+            );
+            const dynamicSize = Object(utils["b" /* getParamValue */])(
+              "dynamicSize",
+              node,
+              tensorMap,
+              context
+            );
+            const clearAfterRead = Object(utils["b" /* getParamValue */])(
+              "clearAfterRead",
+              node,
+              tensorMap,
+              context
+            );
+            const identicalElementShapes = Object(utils["b" /* getParamValue */])(
+              "identicalElementShapes",
+              node,
+              tensorMap,
+              context
+            );
+            const name = Object(utils["b" /* getParamValue */])("name", node, tensorMap, context);
+            const tensorArray = new tensor_array_TensorArray(
+              name,
+              dtype,
+              size,
+              elementShape,
+              identicalElementShapes,
+              dynamicSize,
+              clearAfterRead
+            );
+            context.addTensorArray(tensorArray);
+            return [Object(dist["scalar"])(tensorArray.id), Object(dist["scalar"])(1.0)];
+          case "TensorArrayWriteV3":
+            const id = Object(utils["b" /* getParamValue */])(
+              "tensorArrayId",
+              node,
+              tensorMap,
+              context
+            );
+            const index = Object(utils["b" /* getParamValue */])("index", node, tensorMap, context);
+            const writeTensor = Object(utils["b" /* getParamValue */])(
+              "tensor",
+              node,
+              tensorMap,
+              context
+            );
+            const writeTensorArray = context.getTensorArray(id);
+            writeTensorArray.write(index, writeTensor);
+            return [Object(dist["scalar"])(1.0)];
+          case "TensorArrayReadV3":
+            const readId = Object(utils["b" /* getParamValue */])(
+              "tensorArrayId",
+              node,
+              tensorMap,
+              context
+            );
+            const readIndex = Object(utils["b" /* getParamValue */])(
+              "index",
+              node,
+              tensorMap,
+              context
+            );
+            const readTensorArray = context.getTensorArray(readId);
+            return [readTensorArray.read(readIndex)];
+          case "TensorArrayGatherV3":
+            const gatherId = Object(utils["b" /* getParamValue */])(
+              "tensorArrayId",
+              node,
+              tensorMap,
+              context
+            );
+            const gatherIndices = Object(utils["b" /* getParamValue */])(
+              "indices",
+              node,
+              tensorMap,
+              context
+            );
+            const gatherDtype = Object(utils["b" /* getParamValue */])(
+              "dtype",
+              node,
+              tensorMap,
+              context
+            );
+            const gatherTensorArray = context.getTensorArray(gatherId);
+            return [gatherTensorArray.gather(gatherIndices, gatherDtype)];
+          case "TensorArrayScatterV3":
+            const scatterId = Object(utils["b" /* getParamValue */])(
+              "tensorArrayId",
+              node,
+              tensorMap,
+              context
+            );
+            const scatterIndices = Object(utils["b" /* getParamValue */])(
+              "indices",
+              node,
+              tensorMap,
+              context
+            );
+            const scatterTensor = Object(utils["b" /* getParamValue */])(
+              "tensor",
+              node,
+              tensorMap,
+              context
+            );
+            const scatterTensorArray = context.getTensorArray(scatterId);
+            scatterTensorArray.scatter(scatterIndices, scatterTensor);
+            return [Object(dist["scalar"])(1.0)];
+          case "TensorArrayConcatV3":
+            const concatId = Object(utils["b" /* getParamValue */])(
+              "tensorArrayId",
+              node,
+              tensorMap,
+              context
+            );
+            const concatTensorArray = context.getTensorArray(concatId);
+            const concatDtype = Object(utils["b" /* getParamValue */])(
+              "dtype",
+              node,
+              tensorMap,
+              context
+            );
+            return [concatTensorArray.concat(concatDtype)];
+          case "TensorArraySplitV3":
+            const splitId = Object(utils["b" /* getParamValue */])(
+              "tensorArrayId",
+              node,
+              tensorMap,
+              context
+            );
+            const splitTensor = Object(utils["b" /* getParamValue */])(
+              "tensor",
+              node,
+              tensorMap,
+              context
+            );
+            const lengths = Object(utils["b" /* getParamValue */])(
+              "lengths",
+              node,
+              tensorMap,
+              context
+            );
+            const splitTensorArray = context.getTensorArray(splitId);
+            splitTensorArray.split(lengths, splitTensor);
+            return [Object(dist["scalar"])(1.0)];
+          case "TensorArraySizeV3":
+            const sizeId = Object(utils["b" /* getParamValue */])(
+              "tensorArrayId",
+              node,
+              tensorMap,
+              context
+            );
+            const sizeTensorArray = context.getTensorArray(sizeId);
+            return [Object(dist["scalar"])(sizeTensorArray.size(), "int32")];
+          case "TensorArrayCloseV3":
+            const closeId = Object(utils["b" /* getParamValue */])(
+              "tensorArrayId",
+              node,
+              tensorMap,
+              context
+            );
+            const closeTensorArray = context.getTensorArray(closeId);
+            closeTensorArray.clearAndClose();
+            return [Object(dist["scalar"])(0)];
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const control_executor_CATEGORY = "control";
+      //# sourceMappingURL=control_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/convolution_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const convolution_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "Conv1D": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "stride",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const dataFormat = Object(utils["b" /* getParamValue */])(
+              "dataFormat",
+              node,
+              tensorMap,
+              context
+            ).toUpperCase();
+            const dilation = Object(utils["b" /* getParamValue */])(
+              "dilation",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["conv1d"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
+                stride,
+                pad,
+                dataFormat,
+                dilation
+              ),
+            ];
+          }
+          case "Conv2D": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const dataFormat = Object(utils["b" /* getParamValue */])(
+              "dataFormat",
+              node,
+              tensorMap,
+              context
+            ).toUpperCase();
+            const dilations = Object(utils["b" /* getParamValue */])(
+              "dilations",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["conv2d"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
+                [stride[1], stride[2]],
+                pad,
+                dataFormat,
+                [dilations[1], dilations[2]]
+              ),
+            ];
+          }
+          case "_FusedConv2D":
+          case "FusedDepthwiseConv2dNative": {
+            const [extraOp, activationFunc] = Object(utils["b" /* getParamValue */])(
+              "fusedOps",
+              node,
+              tensorMap,
+              context
+            );
+            const isBiasAdd = extraOp === "biasadd";
+            const isPrelu = activationFunc === "prelu";
+            const isBatchNorm = extraOp === "fusedbatchnorm";
+            const numArgs = Object(utils["b" /* getParamValue */])(
+              "numArgs",
+              node,
+              tensorMap,
+              context
+            );
+            if (isBiasAdd) {
+              if (isPrelu && numArgs !== 2) {
+                throw new Error(
+                  "FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu " +
+                    "must have two extra arguments: bias and alpha."
+                );
+              }
+              if (!isPrelu && numArgs !== 1) {
+                throw new Error(
+                  "FusedConv2d and DepthwiseConv2d with BiasAdd must have " +
+                    "one extra argument: bias."
+                );
+              }
+            }
+            if (isBatchNorm) {
+              throw new Error(
+                "FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported."
+              );
+            }
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const dataFormat = Object(utils["b" /* getParamValue */])(
+              "dataFormat",
+              node,
+              tensorMap,
+              context
+            ).toUpperCase();
+            const dilations = Object(utils["b" /* getParamValue */])(
+              "dilations",
+              node,
+              tensorMap,
+              context
+            );
+            const [biasArg, preluArg] = Object(utils["b" /* getParamValue */])(
+              "args",
+              node,
+              tensorMap,
+              context
+            );
+            const kernelMethod =
+              node.op === "_FusedConv2D" ? dist["fused"].conv2d : dist["fused"].depthwiseConv2d;
+            return [
+              kernelMethod({
+                x: Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                filter: Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
+                strides: [stride[1], stride[2]],
+                pad: pad,
+                dataFormat: dataFormat,
+                dilations: [dilations[1], dilations[2]],
+                bias: biasArg,
+                activation: activationFunc,
+                preluActivationWeights: preluArg,
+              }),
+            ];
+          }
+          case "Conv2DBackpropInput":
+          case "Conv2dTranspose": {
+            const shape = Object(utils["b" /* getParamValue */])(
+              "outputShape",
+              node,
+              tensorMap,
+              context
+            );
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            return [
+              dist["conv2dTranspose"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
+                shape,
+                [stride[1], stride[2]],
+                pad
+              ),
+            ];
+          }
+          case "DepthwiseConv2dNative":
+          case "DepthwiseConv2d": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const dilations = Object(utils["b" /* getParamValue */])(
+              "dilations",
+              node,
+              tensorMap,
+              context
+            );
+            const dataFormat = Object(utils["b" /* getParamValue */])(
+              "dataFormat",
+              node,
+              tensorMap,
+              context
+            ).toUpperCase();
+            return [
+              dist["depthwiseConv2d"](
+                Object(utils["b" /* getParamValue */])("input", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
+                [stride[1], stride[2]],
+                pad,
+                dataFormat,
+                [dilations[1], dilations[2]]
+              ),
+            ];
+          }
+          case "Conv3D": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const dataFormat = Object(utils["b" /* getParamValue */])(
+              "dataFormat",
+              node,
+              tensorMap,
+              context
+            ).toUpperCase();
+            const dilations = Object(utils["b" /* getParamValue */])(
+              "dilations",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["conv3d"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("filter", node, tensorMap, context),
+                [stride[1], stride[2], stride[3]],
+                pad,
+                dataFormat,
+                [dilations[1], dilations[2], dilations[3]]
+              ),
+            ];
+          }
+          case "AvgPool": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const kernelSize = Object(utils["b" /* getParamValue */])(
+              "kernelSize",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["avgPool"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                [kernelSize[1], kernelSize[2]],
+                [stride[1], stride[2]],
+                pad
+              ),
+            ];
+          }
+          case "MaxPool": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const kernelSize = Object(utils["b" /* getParamValue */])(
+              "kernelSize",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["maxPool"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                [kernelSize[1], kernelSize[2]],
+                [stride[1], stride[2]],
+                pad
+              ),
+            ];
+          }
+          case "MaxPoolWithArgmax": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const kernelSize = Object(utils["b" /* getParamValue */])(
+              "kernelSize",
+              node,
+              tensorMap,
+              context
+            );
+            const includeBatchInIndex = Object(utils["b" /* getParamValue */])(
+              "includeBatchInIndex",
+              node,
+              tensorMap,
+              context
+            );
+            const { result, indexes } = dist["maxPoolWithArgmax"](
+              Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+              [kernelSize[1], kernelSize[2]],
+              [stride[1], stride[2]],
+              pad,
+              includeBatchInIndex
+            );
+            return [result, indexes];
+          }
+          case "AvgPool3D": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const kernelSize = Object(utils["b" /* getParamValue */])(
+              "kernelSize",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["avgPool3d"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                [kernelSize[1], kernelSize[2], kernelSize[3]],
+                [stride[1], stride[2], stride[3]],
+                pad
+              ),
+            ];
+          }
+          case "MaxPool3D": {
+            const stride = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const pad = Object(utils["b" /* getParamValue */])("pad", node, tensorMap, context);
+            const kernelSize = Object(utils["b" /* getParamValue */])(
+              "kernelSize",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["maxPool3d"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                [kernelSize[1], kernelSize[2], kernelSize[3]],
+                [stride[1], stride[2], stride[3]],
+                pad
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const convolution_executor_CATEGORY = "convolution";
+      //# sourceMappingURL=convolution_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/creation_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const creation_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "Fill": {
+            const shape = Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context);
+            const dtype = Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context);
+            const value = Object(utils["b" /* getParamValue */])("value", node, tensorMap, context);
+            return [dist["fill"](shape, value, dtype)];
+          }
+          case "LinSpace": {
+            const start = Object(utils["b" /* getParamValue */])("start", node, tensorMap, context);
+            const stop = Object(utils["b" /* getParamValue */])("stop", node, tensorMap, context);
+            const num = Object(utils["b" /* getParamValue */])("num", node, tensorMap, context);
+            return [dist["linspace"](start, stop, num)];
+          }
+          case "Multinomial": {
+            const logits = Object(utils["b" /* getParamValue */])(
+              "logits",
+              node,
+              tensorMap,
+              context
+            );
+            const numSamples = Object(utils["b" /* getParamValue */])(
+              "numSamples",
+              node,
+              tensorMap,
+              context
+            );
+            const seed = Object(utils["b" /* getParamValue */])("seed", node, tensorMap, context);
+            return [dist["multinomial"](logits, numSamples, seed)];
+          }
+          case "OneHot": {
+            const indices = Object(utils["b" /* getParamValue */])(
+              "indices",
+              node,
+              tensorMap,
+              context
+            );
+            const depth = Object(utils["b" /* getParamValue */])("depth", node, tensorMap, context);
+            const onValue = Object(utils["b" /* getParamValue */])(
+              "onValue",
+              node,
+              tensorMap,
+              context
+            );
+            const offValue = Object(utils["b" /* getParamValue */])(
+              "offValue",
+              node,
+              tensorMap,
+              context
+            );
+            return [dist["oneHot"](indices, depth, onValue, offValue)];
+          }
+          case "Ones": {
+            return [
+              dist["ones"](
+                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "OnesLike": {
+            return [
+              dist["onesLike"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "RandomUniform": {
+            return [
+              dist["randomUniform"](
+                // tslint:disable-next-line:no-any
+                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("minval", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("maxval", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Range": {
+            const start = Object(utils["b" /* getParamValue */])("start", node, tensorMap, context);
+            const stop = Object(utils["b" /* getParamValue */])("stop", node, tensorMap, context);
+            const step = Object(utils["b" /* getParamValue */])("step", node, tensorMap, context);
+            return [
+              dist["range"](
+                start,
+                stop,
+                step,
+                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "TruncatedNormal": {
+            const shape = Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context);
+            const mean = Object(utils["b" /* getParamValue */])("mean", node, tensorMap, context);
+            const stdDev = Object(utils["b" /* getParamValue */])(
+              "stdDev",
+              node,
+              tensorMap,
+              context
+            );
+            const seed = Object(utils["b" /* getParamValue */])("seed", node, tensorMap, context);
+            return [
+              dist["truncatedNormal"](
+                shape,
+                mean,
+                stdDev,
+                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context),
+                seed
+              ),
+            ];
+          }
+          case "Zeros": {
+            return [
+              dist["zeros"](
+                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "ZerosLike": {
+            return [
+              dist["zerosLike"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const creation_executor_CATEGORY = "creation";
+      //# sourceMappingURL=creation_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/dynamic_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const dynamic_executor_executeOp = async (node, tensorMap, context) => {
+        switch (node.op) {
+          case "NonMaxSuppressionV5":
+          case "NonMaxSuppressionV3":
+          case "NonMaxSuppressionV2": {
+            const boxes = Object(utils["b" /* getParamValue */])("boxes", node, tensorMap, context);
+            const scores = Object(utils["b" /* getParamValue */])(
+              "scores",
+              node,
+              tensorMap,
+              context
+            );
+            const maxOutputSize = Object(utils["b" /* getParamValue */])(
+              "maxOutputSize",
+              node,
+              tensorMap,
+              context
+            );
+            const iouThreshold = Object(utils["b" /* getParamValue */])(
+              "iouThreshold",
+              node,
+              tensorMap,
+              context
+            );
+            const scoreThreshold = Object(utils["b" /* getParamValue */])(
+              "scoreThreshold",
+              node,
+              tensorMap,
+              context
+            );
+            if (node.op === "NonMaxSuppressionV5") {
+              const softNmsSigma = Object(utils["b" /* getParamValue */])(
+                "softNmsSigma",
+                node,
+                tensorMap,
+                context
+              );
+              const result = await dist["image"].nonMaxSuppressionWithScoreAsync(
+                boxes,
+                scores,
+                maxOutputSize,
+                iouThreshold,
+                scoreThreshold,
+                softNmsSigma
+              );
+              return [result.selectedIndices, result.selectedScores];
+            }
+            return [
+              await dist["image"].nonMaxSuppressionAsync(
+                boxes,
+                scores,
+                maxOutputSize,
+                iouThreshold,
+                scoreThreshold
+              ),
+            ];
+          }
+          case "Where": {
+            const condition = Object(utils["b" /* getParamValue */])(
+              "condition",
+              node,
+              tensorMap,
+              context
+            ).asType("bool");
+            const result = [await dist["whereAsync"](condition)];
+            condition.dispose();
+            return result;
+          }
+          case "ListDiff": {
+            return dist["setdiff1dAsync"](
+              Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+              Object(utils["b" /* getParamValue */])("y", node, tensorMap, context)
+            );
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const dynamic_executor_CATEGORY = "dynamic";
+      //# sourceMappingURL=dynamic_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/evaluation_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const evaluation_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "TopKV2": {
+            const x = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
+            const k = Object(utils["b" /* getParamValue */])("k", node, tensorMap, context);
+            const sorted = Object(utils["b" /* getParamValue */])(
+              "sorted",
+              node,
+              tensorMap,
+              context
+            );
+            const result = dist["topk"](x, k, sorted);
+            return [result.values, result.indices];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const evaluation_executor_CATEGORY = "evaluation";
+      //# sourceMappingURL=evaluation_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/graph_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const graph_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "Const": {
+            return tensorMap[node.name];
+          }
+          case "PlaceholderWithDefault":
+            const def = Object(utils["b" /* getParamValue */])("default", node, tensorMap, context);
+            return [Object(utils["c" /* getTensor */])(node.name, tensorMap, context) || def];
+          case "Placeholder":
+            return [Object(utils["c" /* getTensor */])(node.name, tensorMap, context)];
+          case "Identity":
+          case "StopGradient":
+          case "FakeQuantWithMinMaxVars": // This op is currently ignored.
+            return [Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).clone()];
+          case "IdentityN":
+            return Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).map((t) =>
+              t.clone()
+            );
+          case "Snapshot":
+            const snapshot = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
+            return [snapshot.clone()];
+          case "Shape":
+            return [
+              dist["tensor1d"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).shape,
+                "int32"
+              ),
+            ];
+          case "ShapeN":
+            return Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).map((t) =>
+              dist["tensor1d"](t.shape)
+            );
+          case "Size":
+            return [
+              dist["scalar"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).size,
+                "int32"
+              ),
+            ];
+          case "Rank":
+            return [
+              dist["scalar"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context).rank,
+                "int32"
+              ),
+            ];
+          case "NoOp":
+            return [dist["scalar"](1)];
+          case "Print":
+            const input = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
+            const data = Object(utils["b" /* getParamValue */])("data", node, tensorMap, context);
+            const message = Object(utils["b" /* getParamValue */])(
+              "message",
+              node,
+              tensorMap,
+              context
+            );
+            const summarize = Object(utils["b" /* getParamValue */])(
+              "summarize",
+              node,
+              tensorMap,
+              context
+            );
+            console.warn(
+              "The graph has a tf.print() operation," +
+                "usually used for debugging, which slows down performance."
+            );
+            console.log(message);
+            for (let i = 0; i < data.length; i++) {
+              console.log(Array.prototype.slice.call(data[i].dataSync()).slice(0, summarize));
+            }
+            return [input];
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const graph_executor_CATEGORY = "graph";
+      //# sourceMappingURL=graph_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/image_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const image_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "ResizeBilinear": {
+            const images = Object(utils["b" /* getParamValue */])(
+              "images",
+              node,
+              tensorMap,
+              context
+            );
+            const size = Object(utils["b" /* getParamValue */])("size", node, tensorMap, context);
+            const alignCorners = Object(utils["b" /* getParamValue */])(
+              "alignCorners",
+              node,
+              tensorMap,
+              context
+            );
+            return [dist["image"].resizeBilinear(images, [size[0], size[1]], alignCorners)];
+          }
+          case "ResizeNearestNeighbor": {
+            const images = Object(utils["b" /* getParamValue */])(
+              "images",
+              node,
+              tensorMap,
+              context
+            );
+            const size = Object(utils["b" /* getParamValue */])("size", node, tensorMap, context);
+            const alignCorners = Object(utils["b" /* getParamValue */])(
+              "alignCorners",
+              node,
+              tensorMap,
+              context
+            );
+            return [dist["image"].resizeNearestNeighbor(images, [size[0], size[1]], alignCorners)];
+          }
+          case "CropAndResize": {
+            const image = Object(utils["b" /* getParamValue */])("image", node, tensorMap, context);
+            const boxes = Object(utils["b" /* getParamValue */])("boxes", node, tensorMap, context);
+            const boxInd = Object(utils["b" /* getParamValue */])(
+              "boxInd",
+              node,
+              tensorMap,
+              context
+            );
+            const cropSize = Object(utils["b" /* getParamValue */])(
+              "cropSize",
+              node,
+              tensorMap,
+              context
+            );
+            const method = Object(utils["b" /* getParamValue */])(
+              "method",
+              node,
+              tensorMap,
+              context
+            );
+            const extrapolationValue = Object(utils["b" /* getParamValue */])(
+              "extrapolationValue",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["image"].cropAndResize(
+                image,
+                boxes,
+                boxInd,
+                cropSize,
+                method,
+                extrapolationValue
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const image_executor_CATEGORY = "image";
+      //# sourceMappingURL=image_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/logical_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const logical_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "Equal": {
+            return [
+              dist["equal"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "NotEqual": {
+            return [
+              dist["notEqual"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Greater": {
+            return [
+              dist["greater"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "GreaterEqual": {
+            return [
+              dist["greaterEqual"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Less": {
+            return [
+              dist["less"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "LessEqual": {
+            return [
+              dist["lessEqual"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "LogicalAnd": {
+            return [
+              dist["logicalAnd"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "LogicalNot": {
+            return [
+              dist["logicalNot"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "LogicalOr": {
+            return [
+              dist["logicalOr"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Select":
+          case "SelectV2": {
+            return [
+              dist["where"](
+                Object(utils["b" /* getParamValue */])("condition", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context)
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const logical_executor_CATEGORY = "logical";
+      //# sourceMappingURL=logical_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/matrices_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const matrices_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "BatchMatMul":
+          case "BatchMatMulV2":
+          case "MatMul":
+            return [
+              dist["matMul"](
+                Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("b", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("transposeA", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("transposeB", node, tensorMap, context)
+              ),
+            ];
+          case "Transpose":
+            return [
+              dist["transpose"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("perm", node, tensorMap, context)
+              ),
+            ];
+          case "_FusedMatMul":
+            const [extraOp, activationFunc] = Object(utils["b" /* getParamValue */])(
+              "fusedOps",
+              node,
+              tensorMap,
+              context
+            );
+            const isBiasAdd = extraOp === "biasadd";
+            const isPrelu = activationFunc === "prelu";
+            const numArgs = Object(utils["b" /* getParamValue */])(
+              "numArgs",
+              node,
+              tensorMap,
+              context
+            );
+            if (isBiasAdd) {
+              if (isPrelu && numArgs !== 2) {
+                throw new Error(
+                  "Fused MatMul with BiasAdd and Prelu must have two " +
+                    "extra arguments: bias and alpha."
+                );
+              }
+              if (!isPrelu && numArgs !== 1) {
+                throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.");
+              }
+            }
+            const [biasArg, preluArg] = Object(utils["b" /* getParamValue */])(
+              "args",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["fused"].matMul({
+                a: Object(utils["b" /* getParamValue */])("a", node, tensorMap, context),
+                b: Object(utils["b" /* getParamValue */])("b", node, tensorMap, context),
+                transposeA: Object(utils["b" /* getParamValue */])(
+                  "transposeA",
+                  node,
+                  tensorMap,
+                  context
+                ),
+                transposeB: Object(utils["b" /* getParamValue */])(
+                  "transposeB",
+                  node,
+                  tensorMap,
+                  context
+                ),
+                bias: biasArg,
+                activation: activationFunc,
+                preluActivationWeights: preluArg,
+              }),
+            ];
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const matrices_executor_CATEGORY = "matrices";
+      //# sourceMappingURL=matrices_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/normalization_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const normalization_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "FusedBatchNorm":
+          case "FusedBatchNormV2": {
+            return [
+              dist["batchNorm"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("mean", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("variance", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("offset", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("scale", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("epsilon", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "FusedBatchNormV3": {
+            return [
+              dist["batchNorm"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("mean", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("variance", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("offset", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("scale", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("epsilon", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "LRN": {
+            return [
+              dist["localResponseNormalization"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("radius", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("bias", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("alpha", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("beta", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "Softmax": {
+            return [
+              dist["softmax"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "LogSoftmax": {
+            return [
+              dist["logSoftmax"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "SparseToDense": {
+            return [
+              dist["sparseToDense"](
+                Object(utils["b" /* getParamValue */])("sparseIndices", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("outputShape", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("sparseValues", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("defaultValue", node, tensorMap, context)
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const normalization_executor_CATEGORY = "normalization";
+      //# sourceMappingURL=normalization_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/reduction_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const reduction_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "Max": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const keepDims = Object(utils["b" /* getParamValue */])(
+              "keepDims",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["max"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis,
+                keepDims
+              ),
+            ];
+          }
+          case "Mean": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const keepDims = Object(utils["b" /* getParamValue */])(
+              "keepDims",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["mean"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis,
+                keepDims
+              ),
+            ];
+          }
+          case "Min": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const keepDims = Object(utils["b" /* getParamValue */])(
+              "keepDims",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["min"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis,
+                keepDims
+              ),
+            ];
+          }
+          case "Sum": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const keepDims = Object(utils["b" /* getParamValue */])(
+              "keepDims",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["sum"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis,
+                keepDims
+              ),
+            ];
+          }
+          case "All": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const keepDims = Object(utils["b" /* getParamValue */])(
+              "keepDims",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["all"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis,
+                keepDims
+              ),
+            ];
+          }
+          case "Any": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const keepDims = Object(utils["b" /* getParamValue */])(
+              "keepDims",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["any"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis,
+                keepDims
+              ),
+            ];
+          }
+          case "ArgMax": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            return [
+              dist["argMax"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis
+              ),
+            ];
+          }
+          case "ArgMin": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            return [
+              dist["argMin"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis
+              ),
+            ];
+          }
+          case "Prod": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const keepDims = Object(utils["b" /* getParamValue */])(
+              "keepDims",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["prod"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis,
+                keepDims
+              ),
+            ];
+          }
+          case "Cumsum": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const exclusive = Object(utils["b" /* getParamValue */])(
+              "exclusive",
+              node,
+              tensorMap,
+              context
+            );
+            const reverse = Object(utils["b" /* getParamValue */])(
+              "reverse",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["cumsum"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis,
+                exclusive,
+                reverse
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const reduction_executor_CATEGORY = "reduction";
+      //# sourceMappingURL=reduction_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/slice_join_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const slice_join_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "ConcatV2":
+          case "Concat": {
+            const n = Object(utils["b" /* getParamValue */])("n", node, tensorMap, context);
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            let inputs = Object(utils["b" /* getParamValue */])(
+              "tensors",
+              node,
+              tensorMap,
+              context
+            );
+            inputs = inputs.slice(0, n);
+            return [dist["concat"](inputs, axis)];
+          }
+          case "GatherV2":
+          case "Gather": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const input = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
+            const indices = Object(utils["b" /* getParamValue */])(
+              "indices",
+              node,
+              tensorMap,
+              context
+            );
+            return [dist["gather"](input, indices.asType("int32"), axis)];
+          }
+          case "ReverseV2":
+          case "Reverse": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const input = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
+            return [dist["reverse"](input, axis)];
+          }
+          case "Slice": {
+            // tslint:disable-next-line:no-any
+            const begin = Object(utils["b" /* getParamValue */])("begin", node, tensorMap, context);
+            // tslint:disable-next-line:no-any
+            const size = Object(utils["b" /* getParamValue */])("size", node, tensorMap, context);
+            return [
+              dist["slice"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                begin,
+                size
+              ),
+            ];
+          }
+          case "StridedSlice": {
+            const begin = Object(utils["b" /* getParamValue */])("begin", node, tensorMap, context);
+            const end = Object(utils["b" /* getParamValue */])("end", node, tensorMap, context);
+            const strides = Object(utils["b" /* getParamValue */])(
+              "strides",
+              node,
+              tensorMap,
+              context
+            );
+            const beginMask = Object(utils["b" /* getParamValue */])(
+              "beginMask",
+              node,
+              tensorMap,
+              context
+            );
+            const endMask = Object(utils["b" /* getParamValue */])(
+              "endMask",
+              node,
+              tensorMap,
+              context
+            );
+            const ellipsisMask = Object(utils["b" /* getParamValue */])(
+              "ellipsisMask",
+              node,
+              tensorMap,
+              context
+            );
+            const newAxisMask = Object(utils["b" /* getParamValue */])(
+              "newAxisMask",
+              node,
+              tensorMap,
+              context
+            );
+            const shrinkAxisMask = Object(utils["b" /* getParamValue */])(
+              "shrinkAxisMask",
+              node,
+              tensorMap,
+              context
+            );
+            const tensor = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
+            if (begin.length === 1 && tensor.shape.length > 1) {
+              for (let i = 1; i < tensor.shape.length; i++) {
+                begin.push(0);
+                end.push(tensor.shape[i]);
+                strides.push(strides[0]);
+              }
+            }
+            return [
+              dist["stridedSlice"](
+                tensor,
+                begin,
+                end,
+                strides,
+                beginMask,
+                endMask,
+                ellipsisMask,
+                newAxisMask,
+                shrinkAxisMask
+              ),
+            ];
+          }
+          case "Pack": {
+            return dist["tidy"](() => {
+              const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+              const tensors = Object(utils["b" /* getParamValue */])(
+                "tensors",
+                node,
+                tensorMap,
+                context
+              );
+              // Reshape the tensors to the first tensor's shape if they don't match.
+              const shape = tensors[0].shape;
+              const squeezedShape = tensors[0].squeeze().shape;
+              const mapped = tensors.map((tensor) => {
+                const sameShape = dist["util"].arraysEqual(tensor.shape, shape);
+                if (
+                  !sameShape &&
+                  !dist["util"].arraysEqual(tensor.squeeze().shape, squeezedShape)
+                ) {
+                  throw new Error("the input tensors shape does not match");
+                }
+                return sameShape ? tensor : tensor.reshape(shape);
+              });
+              return [dist["stack"](mapped, axis)];
+            });
+          }
+          case "Unpack": {
+            return dist["tidy"](() => {
+              const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+              const tensor = Object(utils["b" /* getParamValue */])(
+                "tensor",
+                node,
+                tensorMap,
+                context
+              );
+              return dist["unstack"](tensor, axis);
+            });
+          }
+          case "Tile": {
+            const reps = Object(utils["b" /* getParamValue */])("reps", node, tensorMap, context);
+            return [
+              dist["tile"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                reps
+              ),
+            ];
+          }
+          case "Split":
+          case "SplitV": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            const numOrSizeSplits = Object(utils["b" /* getParamValue */])(
+              "numOrSizeSplits",
+              node,
+              tensorMap,
+              context
+            );
+            return dist["split"](
+              Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+              numOrSizeSplits,
+              axis
+            );
+          }
+          case "ScatterNd": {
+            const indices = Object(utils["b" /* getParamValue */])(
+              "indices",
+              node,
+              tensorMap,
+              context
+            );
+            const values = Object(utils["b" /* getParamValue */])(
+              "values",
+              node,
+              tensorMap,
+              context
+            );
+            const shape = Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context);
+            return [dist["scatterND"](indices, values, shape)];
+          }
+          case "GatherNd": {
+            const x = Object(utils["b" /* getParamValue */])("x", node, tensorMap, context);
+            const indices = Object(utils["b" /* getParamValue */])(
+              "indices",
+              node,
+              tensorMap,
+              context
+            );
+            return [dist["gatherND"](x, indices)];
+          }
+          case "SparseToDense": {
+            const indices = Object(utils["b" /* getParamValue */])(
+              "sparseIndices",
+              node,
+              tensorMap,
+              context
+            );
+            const shape = Object(utils["b" /* getParamValue */])(
+              "outputShape",
+              node,
+              tensorMap,
+              context
+            );
+            const sparseValues = Object(utils["b" /* getParamValue */])(
+              "sparseValues",
+              node,
+              tensorMap,
+              context
+            );
+            const defaultValue = Object(utils["b" /* getParamValue */])(
+              "defaultValue",
+              node,
+              tensorMap,
+              context
+            );
+            return [
+              dist["sparseToDense"](
+                indices,
+                sparseValues,
+                shape,
+                sparseValues.dtype === defaultValue.dtype
+                  ? defaultValue
+                  : defaultValue.asType(sparseValues.dtype)
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const slice_join_executor_CATEGORY = "slice_join";
+      //# sourceMappingURL=slice_join_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/spectral_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const spectral_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "FFT": {
+            return [
+              dist["fft"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "IFFT": {
+            return [
+              dist["ifft"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "RFFT": {
+            return [
+              dist["rfft"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          case "IRFFT": {
+            return [
+              dist["irfft"](Object(utils["b" /* getParamValue */])("x", node, tensorMap, context)),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const spectral_executor_CATEGORY = "spectral";
+      //# sourceMappingURL=spectral_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/executors/transformation_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const transformation_executor_executeOp = (node, tensorMap, context) => {
+        switch (node.op) {
+          case "Cast": {
+            return [
+              dist["cast"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("dtype", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "ExpandDims": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            return [
+              dist["expandDims"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis
+              ),
+            ];
+          }
+          case "Squeeze": {
+            const axis = Object(utils["b" /* getParamValue */])("axis", node, tensorMap, context);
+            return [
+              dist["squeeze"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                axis
+              ),
+            ];
+          }
+          case "Reshape": {
+            return [
+              dist["reshape"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "PadV2":
+          case "Pad": {
+            return [
+              dist["pad"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["f" /* split */])(
+                  Object(utils["b" /* getParamValue */])("padding", node, tensorMap, context),
+                  2
+                ),
+                Object(utils["b" /* getParamValue */])("constantValue", node, tensorMap, context)
+              ),
+            ];
+          }
+          case "SpaceToBatchND": {
+            const blockShape = Object(utils["b" /* getParamValue */])(
+              "blockShape",
+              node,
+              tensorMap,
+              context
+            );
+            const paddings = Object(utils["f" /* split */])(
+              Object(utils["b" /* getParamValue */])("paddings", node, tensorMap, context),
+              2
+            );
+            return [
+              dist["spaceToBatchND"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                blockShape,
+                paddings
+              ),
+            ];
+          }
+          case "BatchToSpaceND": {
+            const blockShape = Object(utils["b" /* getParamValue */])(
+              "blockShape",
+              node,
+              tensorMap,
+              context
+            );
+            const crops = Object(utils["f" /* split */])(
+              Object(utils["b" /* getParamValue */])("crops", node, tensorMap, context),
+              2
+            );
+            return [
+              dist["batchToSpaceND"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                blockShape,
+                crops
+              ),
+            ];
+          }
+          case "DepthToSpace": {
+            const blockSize = Object(utils["b" /* getParamValue */])(
+              "blockSize",
+              node,
+              tensorMap,
+              context
+            );
+            const dataFormat = Object(utils["b" /* getParamValue */])(
+              "dataFormat",
+              node,
+              tensorMap,
+              context
+            ).toUpperCase();
+            return [
+              dist["depthToSpace"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                blockSize,
+                dataFormat
+              ),
+            ];
+          }
+          case "BroadcastTo": {
+            return [
+              dist["broadcastTo"](
+                Object(utils["b" /* getParamValue */])("x", node, tensorMap, context),
+                Object(utils["b" /* getParamValue */])("shape", node, tensorMap, context)
+              ),
+            ];
+          }
+          default:
+            throw TypeError(`Node type ${node.op} is not implemented`);
+        }
+      };
+      const transformation_executor_CATEGORY = "transformation";
+      //# sourceMappingURL=transformation_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/operations/operation_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Executes the op defined by the node object.
+       * @param node
+       * @param tensorMap contains tensors for executed nodes and weights
+       */
+      function operation_executor_executeOp(node, tensorMap, context) {
+        const value = ((node, tensorMap, context) => {
+          switch (node.category) {
+            case "arithmetic":
+              return dist["tidy"](() => executeOp(node, tensorMap, context));
+            case "basic_math":
+              return dist["tidy"](() => basic_math_executor_executeOp(node, tensorMap, context));
+            case "control":
+              return control_executor_executeOp(node, tensorMap, context);
+            case "convolution":
+              return dist["tidy"](() => convolution_executor_executeOp(node, tensorMap, context));
+            case "creation":
+              return dist["tidy"](() => creation_executor_executeOp(node, tensorMap, context));
+            case "dynamic":
+              return dynamic_executor_executeOp(node, tensorMap, context);
+            case "evaluation":
+              return dist["tidy"](() => evaluation_executor_executeOp(node, tensorMap, context));
+            case "image":
+              return dist["tidy"](() => image_executor_executeOp(node, tensorMap, context));
+            case "graph":
+              return dist["tidy"](() => graph_executor_executeOp(node, tensorMap, context));
+            case "logical":
+              return dist["tidy"](() => logical_executor_executeOp(node, tensorMap, context));
+            case "matrices":
+              return dist["tidy"](() => matrices_executor_executeOp(node, tensorMap, context));
+            case "normalization":
+              return dist["tidy"](() => normalization_executor_executeOp(node, tensorMap, context));
+            case "reduction":
+              return dist["tidy"](() => reduction_executor_executeOp(node, tensorMap, context));
+            case "slice_join":
+              return dist["tidy"](() => slice_join_executor_executeOp(node, tensorMap, context));
+            case "spectral":
+              return dist["tidy"](() => spectral_executor_executeOp(node, tensorMap, context));
+            case "transformation":
+              return dist["tidy"](() =>
+                transformation_executor_executeOp(node, tensorMap, context)
+              );
+            case "custom":
+              const opMapper = Object(register["b" /* getRegisteredOp */])(node.op);
+              if (opMapper && opMapper.customExecutor) {
+                return opMapper.customExecutor(
+                  new node_value_impl_NodeValueImpl(node, tensorMap, context)
+                );
+              } else {
+                throw TypeError(`Custom op ${node.op} is not registered.`);
+              }
+            default:
+              throw TypeError(
+                `Unknown op '${node.op}'. File an issue at ` +
+                  `https://github.com/tensorflow/tfjs/issues so we can add it` +
+                  `, or register a custom execution with tf.registerOp()`
+              );
+          }
+        })(node, tensorMap, context);
+        if (value instanceof Promise) {
+          return value.then((data) => [].concat(data));
+        }
+        return [].concat(value);
+      }
+      //# sourceMappingURL=operation_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/execution_context.js
+      /**
+       * ExecutionContext captures the runtime environment of the node. It keeps
+       * track of the current frame and iteration for the control flow ops.
+       *
+       * For example, typical Dynamic RNN model may contain loops, for which
+       * TensorFlow will generate graphs with Enter/Exit nodes to control the
+       * current execution frame, and NextIteration Nodes for iteration id increment.
+       * For model with branch logic, TensorFLow will generate Switch/Merge ops.
+       */
+      class ExecutionContext {
+        constructor(weightMap, tensorArrayMap, functionMap = {}) {
+          this.weightMap = weightMap;
+          this.tensorArrayMap = tensorArrayMap;
+          this.functionMap = functionMap;
+          this.rootContext = { id: 0, frameName: "", iterationId: 0 };
+          this.contexts = [this.rootContext];
+          this.lastId = 0;
+          this.generateCurrentContextIds();
+        }
+        newFrame(id, frameName) {
+          return { id, frameName, iterationId: 0 };
+        }
+        /**
+         * Set the current context
+         * @param contexts: ExecutionContextInfo[] the current path of execution
+         * frames
+         */
+        set currentContext(contexts) {
+          if (this.contexts !== contexts) {
+            this.contexts = contexts;
+            this.generateCurrentContextIds();
+          }
+        }
+        get currentContext() {
+          return this.contexts;
+        }
+        /**
+         * Returns the current context in string format.
+         */
+        get currentContextId() {
+          return this._currentContextIds[0];
+        }
+        /**
+         * Returns the current context and all parent contexts in string format.
+         * This allow access to the nodes in the current and parent frames.
+         */
+        get currentContextIds() {
+          return this._currentContextIds;
+        }
+        generateCurrentContextIds() {
+          const names = [];
+          for (let i = 0; i < this.contexts.length - 1; i++) {
+            const contexts = this.contexts.slice(0, this.contexts.length - i);
+            names.push(this.contextIdforContexts(contexts));
+          }
+          names.push("");
+          this._currentContextIds = names;
+        }
+        contextIdforContexts(contexts) {
+          return contexts
+            ? contexts
+                .map((context) =>
+                  context.id === 0 && context.iterationId === 0
+                    ? ""
+                    : `${context.frameName}-${context.iterationId}`
+                )
+                .join("/")
+            : "";
+        }
+        /**
+         * Enter a new frame, a new context is pushed on the current context list.
+         * @param frameId new frame id
+         */
+        enterFrame(frameId) {
+          if (this.contexts) {
+            this.lastId++;
+            this.contexts = this.contexts.slice();
+            this.contexts.push(this.newFrame(this.lastId, frameId));
+            this._currentContextIds.unshift(this.contextIdforContexts(this.contexts));
+          }
+        }
+        /**
+         * Exit the current frame, the last context is removed from the current
+         * context list.
+         */
+        exitFrame() {
+          if (this.contexts && this.contexts.length > 1) {
+            this.contexts = this.contexts.slice();
+            this.contexts.splice(-1);
+            this.currentContextIds.shift();
+          } else {
+            throw new Error("Cannot exit frame, the context is empty");
+          }
+        }
+        /**
+         * Enter the next iteration of a loop, the iteration id of last context is
+         * increased.
+         */
+        nextIteration() {
+          if (this.contexts && this.contexts.length > 0) {
+            this.contexts = this.contexts.slice();
+            this.lastId++;
+            const context = Object.assign({}, this.contexts[this.contexts.length - 1]);
+            context.iterationId += 1;
+            context.id = this.lastId;
+            this.contexts.splice(-1, 1, context);
+            this._currentContextIds.splice(0, 1, this.contextIdforContexts(this.contexts));
+          } else {
+            throw new Error("Cannot increase frame iteration, the context is empty");
+          }
+        }
+        getWeight(name) {
+          return this.weightMap[name];
+        }
+        addTensorArray(tensorArray) {
+          this.tensorArrayMap[tensorArray.id] = tensorArray;
+        }
+        getTensorArray(id) {
+          return this.tensorArrayMap[id];
+        }
+      }
+      //# sourceMappingURL=execution_context.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/model_analysis.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Given graph inputs and desired outputs, find the minimal set of nodes
+       * to execute in order to compute the outputs. In addition return other useful
+       * info such:
+       * - Missing inputs needed to compute the output.
+       * - Whether the subgraph contains dynamic ops (control flow, dynamic shape).
+       * - Alternative inputs in order to avoid async (dynamic op) execution.
+       */
+      function getExecutionSubgraph(inputs, outputs, weightMap) {
+        const usedNodes = new Set();
+        const missingInputs = [];
+        let dynamicNode = null;
+        let syncInputs = null;
+        // Start with the outputs, going backwards and find all the nodes that are
+        // needed to compute those outputs.
+        const seen = new Set();
+        const inputNodeNames = Object.keys(inputs).map(
+          (name) => Object(utils["e" /* parseNodeName */])(name)[0]
+        );
+        const frontier = [...outputs];
+        while (frontier.length > 0) {
+          const node = frontier.pop();
+          if (isControlFlow(node) || isDynamicShape(node)) {
+            if (dynamicNode == null) {
+              dynamicNode = node;
+              syncInputs = dynamicNode.children
+                .map((child) => child.name)
+                .filter((name) => usedNodes.has(name));
+            }
+          }
+          usedNodes.add(node.name);
+          // Weights are dead end since we already have their values.
+          if (weightMap[node.name] != null) {
+            continue;
+          }
+          // This node is a dead end since it's one of the user-provided inputs.
+          if (inputNodeNames.indexOf(node.name) !== -1) {
+            continue;
+          }
+          if (node.inputs.length === 0) {
+            missingInputs.push(node.name);
+            continue;
+          }
+          node.inputs.forEach((input) => {
+            // Don't add to the frontier if it is already there.
+            if (seen.has(input.name)) {
+              return;
+            }
+            seen.add(input.name);
+            frontier.push(input);
+          });
+        }
+        return { inputs, outputs, usedNodes, missingInputs, dynamicNode, syncInputs };
+      }
+      /**
+       * Given the execution info, return a list of nodes in topological order that
+       * need to be executed to compute the output.
+       */
+      function getNodesInTopologicalOrder(graph, weightMap, executionInfo) {
+        const { usedNodes, inputs } = executionInfo;
+        const frontier = [];
+        const inputNodes = Object.keys(inputs)
+          .map((name) => Object(utils["e" /* parseNodeName */])(name)[0])
+          .map((name) => graph.nodes[name]);
+        inputNodes.forEach((input) => {
+          if (usedNodes.has(input.name)) {
+            frontier.push(input);
+          }
+        });
+        graph.weights.forEach((weight) => {
+          if (usedNodes.has(weight.name)) {
+            frontier.push(weight);
+          }
+        });
+        const seen = new Set();
+        const orderedNodes = [];
+        while (frontier.length > 0) {
+          const node = frontier.pop();
+          seen.add(node.name);
+          if (!weightMap[node.name]) {
+            orderedNodes.push(node);
+          }
+          node.children.forEach((child) => {
+            if (
+              !seen.has(child.name) &&
+              usedNodes.has(child.name) &&
+              child.inputs.every((input) => seen.has(input.name))
+            ) {
+              frontier.push(child);
+            }
+          });
+        }
+        return orderedNodes;
+      }
+      const CONTROL_FLOW_OPS = [
+        "Switch",
+        "Merge",
+        "Enter",
+        "Exit",
+        "NextIteration",
+        "StatelessIf",
+        "StatelessWhile",
+      ];
+      const DYNAMIC_SHAPE_OPS = [
+        "NonMaxSuppressionV2",
+        "NonMaxSuppressionV3",
+        "NonMaxSuppressionV5",
+        "Where",
+      ];
+      function isControlFlow(node) {
+        return CONTROL_FLOW_OPS.indexOf(node.op) >= 0;
+      }
+      function isDynamicShape(node) {
+        return DYNAMIC_SHAPE_OPS.indexOf(node.op) >= 0;
+      }
+      //# sourceMappingURL=model_analysis.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/graph_executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class graph_executor_GraphExecutor {
+        /**
+         *
+         * @param graph Graph the model or function graph to be executed.
+         * @param parent When building function exector you need to set the parent
+         * executor. Since the weights and function executor maps are set at parant
+         * level, that function executor can access the function maps and weight maps
+         * through the parent.
+         */
+        constructor(graph, parent) {
+          this.graph = graph;
+          this.parent = parent;
+          this.compiledMap = new Map();
+          this._weightMap = {};
+          this.SEPERATOR = ",";
+          this._functions = {};
+          this._functionExecutorMap = {};
+          this._outputs = graph.outputs;
+          this._inputs = graph.inputs;
+          this._signature = graph.signature;
+          this._functions = graph.functions;
+          // create sub-graph executors
+          if (graph.functions != null) {
+            Object.keys(graph.functions).forEach((name) => {
+              this._functionExecutorMap[name] = new graph_executor_GraphExecutor(
+                graph.functions[name],
+                this
+              );
+            });
+          }
+        }
+        get weightIds() {
+          return this.parent ? this.parent.weightIds : this._weightIds;
+        }
+        get functionExecutorMap() {
+          return this.parent ? this.parent.functionExecutorMap : this._functionExecutorMap;
+        }
+        get weightMap() {
+          return this.parent ? this.parent.weightMap : this._weightMap;
+        }
+        set weightMap(weightMap) {
+          const weightIds = Object.keys(weightMap).map((key) =>
+            weightMap[key].map((tensor) => tensor.id)
+          );
+          this._weightIds = [].concat(...weightIds);
+          this._weightMap = weightMap;
+        }
+        get inputs() {
+          return this._inputs.map((node) => {
+            return {
+              name: node.name,
+              shape: node.attrParams["shape"] ? node.attrParams["shape"].value : undefined,
+              dtype: node.attrParams["dtype"] ? node.attrParams["dtype"].value : undefined,
+            };
+          });
+        }
+        get outputs() {
+          return this._outputs.map((node) => {
+            return {
+              name: node.name,
+              shape: node.attrParams["shape"] ? node.attrParams["shape"].value : undefined,
+              dtype: node.attrParams["dtype"] ? node.attrParams["dtype"].value : undefined,
+            };
+          });
+        }
+        get inputNodes() {
+          return this._inputs.map((node) => node.signatureKey || node.name);
+        }
+        get outputNodes() {
+          return this._outputs.map((node) => {
+            const name = node.signatureKey || node.name;
+            return node.defaultOutput ? `${name}:${node.defaultOutput}` : name;
+          });
+        }
+        get functions() {
+          return Object.keys(this._functions).reduce((map, key) => {
+            map[key] = this._functions[key].signature;
+            return map;
+          }, {});
+        }
+        getCompilationKey(inputs, outputs) {
+          const sortedInputs = inputs.map((node) => node.name).sort();
+          const sortedOutputs = outputs.map((node) => node.name).sort();
+          return sortedInputs.join(this.SEPERATOR) + "--" + sortedOutputs.join(this.SEPERATOR);
+        }
+        /**
+         * Compiles the inference graph and returns the minimal set of nodes that are
+         * required for execution, in the correct execution order.
+         */
+        compile(inputs, outputs) {
+          const executionInfo = getExecutionSubgraph(inputs, outputs, this.weightMap);
+          const { missingInputs, dynamicNode, syncInputs } = executionInfo;
+          if (dynamicNode != null) {
+            throw new Error(
+              `This execution contains the node '${dynamicNode.name}', which has ` +
+                `the dynamic op '${dynamicNode.op}'. Please use ` +
+                `model.executeAsync() instead. Alternatively, to avoid the ` +
+                `dynamic ops, specify the inputs [${syncInputs}]`
+            );
+          }
+          if (missingInputs.length > 0) {
+            const outNames = outputs.map((n) => n.name);
+            const inNames = Object.keys(inputs);
+            throw new Error(
+              `Cannot compute the outputs [${outNames}] from the provided inputs ` +
+                `[${inNames}]. Missing the following inputs: [${missingInputs}]`
+            );
+          }
+          return getNodesInTopologicalOrder(this.graph, this.weightMap, executionInfo);
+        }
+        /**
+         * Executes the inference for given input tensors.
+         * @param inputs Tensor map for the model inputs, keyed by the input node
+         * names.
+         * @param outputs output node name from the Tensorflow model, if no outputs
+         * are specified, the default outputs of the model would be used. You can
+         * inspect intermediate nodes of the model by adding them to the outputs
+         * array.
+         */
+        execute(inputs, outputs) {
+          inputs = this.mapInputs(inputs);
+          const names = Object.keys(inputs).sort();
+          this.checkInputs(inputs);
+          this.checkInputShapeAndType(inputs);
+          outputs = this.mapOutputs(outputs);
+          this.checkOutputs(outputs);
+          const inputNodes = names.map(
+            (name) => this.graph.nodes[Object(utils["e" /* parseNodeName */])(name)[0]]
+          );
+          const outputNodes = outputs.map(
+            (name) => this.graph.nodes[Object(utils["e" /* parseNodeName */])(name)[0]]
+          );
+          const compilationKey = this.getCompilationKey(inputNodes, outputNodes);
+          // Do nothing if the compiled graph cache contains the input.
+          let orderedNodes = this.compiledMap.get(compilationKey);
+          if (orderedNodes == null) {
+            orderedNodes = this.compile(inputs, outputNodes);
+            this.compiledMap.set(compilationKey, orderedNodes);
+          }
+          const tensorArrayMap = {};
+          return Object(dist["tidy"])(() => {
+            const context = new ExecutionContext(
+              this.weightMap,
+              tensorArrayMap,
+              this.functionExecutorMap
+            );
+            const tensorsMap = Object.assign({}, this.weightMap);
+            Object.keys(inputs).forEach((name) => {
+              const [nodeName, index] = Object(utils["e" /* parseNodeName */])(name);
+              const tensors = [];
+              tensors[index] = inputs[name];
+              tensorsMap[nodeName] = tensors;
+            });
+            const tensorsToKeep = this.getFrozenTensorIds(tensorsMap);
+            const intermediateTensorConsumerCount = {};
+            for (let i = 0; i < orderedNodes.length; i++) {
+              const node = orderedNodes[i];
+              if (!tensorsMap[node.name]) {
+                const tensors = operation_executor_executeOp(node, tensorsMap, context);
+                if (tensors instanceof Promise) {
+                  throw new Error(
+                    `The execution of the op '${node.op}' returned a promise. ` +
+                      `Please use model.executeAsync() instead.`
+                  );
+                }
+                tensorsMap[node.name] = tensors;
+                this.checkTensorForDisposal(
+                  node.name,
+                  node,
+                  tensorsMap,
+                  context,
+                  tensorsToKeep,
+                  outputs,
+                  intermediateTensorConsumerCount
+                );
+              }
+            }
+            return outputs.map((name) =>
+              Object(utils["c" /* getTensor */])(name, tensorsMap, context)
+            );
+          });
+        }
+        getFrozenTensorIds(tensorMap) {
+          const ids = [].concat.apply(
+            [],
+            Object.keys(tensorMap)
+              .map((key) => tensorMap[key])
+              .map((tensors) => tensors.map((tensor) => tensor.id))
+          );
+          return new Set(ids);
+        }
+        checkTensorForDisposal(
+          nodeName,
+          node,
+          tensorMap,
+          context,
+          tensorsToKeep,
+          outputNames,
+          intermediateTensorConsumerCount
+        ) {
+          // Skip output nodes and any control flow nodes, since its dependency is
+          // tricky to track correctly.
+          if (node.category === "control" || outputNames.indexOf(nodeName) !== -1) {
+            return;
+          }
+          tensorMap[nodeName].forEach((tensor) => {
+            if (tensor != null) {
+              intermediateTensorConsumerCount[tensor.id] =
+                (intermediateTensorConsumerCount[tensor.id] || 0) + node.children.length;
+            }
+          });
+          node.inputs.forEach((input) => {
+            // Skip any control flow nodes, since its dependency is tricky to track
+            // correctly.
+            if (input.category !== "control") {
+              const tensors = Object(utils["d" /* getTensorsForCurrentContenxt */])(
+                input.name,
+                tensorMap,
+                context
+              );
+              if (tensors != null) {
+                tensors.forEach((tensor) => {
+                  if (tensor && !tensorsToKeep.has(tensor.id)) {
+                    const count = intermediateTensorConsumerCount[tensor.id];
+                    if (count === 1) {
+                      tensor.dispose();
+                      delete intermediateTensorConsumerCount[tensor.id];
+                    } else if (count != null) {
+                      // only intermediate nodes has count set, inputs and weights are
+                      // not.
+                      intermediateTensorConsumerCount[tensor.id]--;
+                    }
+                  }
+                });
+              }
+            }
+          });
+        }
+        /**
+         * Executes the inference for given input tensors in Async fashion.
+         * @param inputs Tensor map for the model inputs, keyed by the input node
+         * names.
+         * @param outputs output node name from the Tensorflow model, if no outputs
+         * are specified, the default outputs of the model would be used. You can
+         * inspect intermediate nodes of the model by adding them to the outputs
+         * array.
+         * @param disableWarning disable the no dynamic ops warning message, default
+         * to false
+         */
+        async executeAsync(inputs, outputs, disableWarning = false) {
+          inputs = this.mapInputs(inputs);
+          this.checkInputs(inputs);
+          this.checkInputShapeAndType(inputs);
+          outputs = this.mapOutputs(outputs);
+          this.checkOutputs(outputs);
+          const tensorArrayMap = {};
+          const context = new ExecutionContext(
+            this.weightMap,
+            tensorArrayMap,
+            this.functionExecutorMap
+          );
+          // Graph with control flow op requires runtime evaluation of the execution
+          // order, while without control flow the execution order is pre-determined
+          // in the compile method.
+          const tensorMap = await this.executeWithControlFlow(
+            inputs,
+            context,
+            outputs,
+            disableWarning
+          );
+          const results = outputs.map((name) =>
+            Object(utils["c" /* getTensor */])(name, tensorMap, context)
+          );
+          // dispose all the intermediate tensors
+          const outputIds = new Set(results.map((t) => t.id));
+          const inputIds = new Set(Object.keys(inputs).map((name) => inputs[name].id));
+          Object.keys(tensorMap).forEach((key) => {
+            const tensorArray = tensorMap[key];
+            tensorArray.forEach((tensor) => {
+              if (
+                tensor &&
+                !tensor.isDisposed &&
+                !outputIds.has(tensor.id) &&
+                !inputIds.has(tensor.id) &&
+                this.weightIds.indexOf(tensor.id) === -1
+              ) {
+                tensor.dispose();
+              }
+            });
+          });
+          return results;
+        }
+        async executeFunctionAsync(inputs) {
+          const mappedInputs = inputs.reduce((map, tensor, index) => {
+            map[this.inputs[index].name] = tensor;
+            return map;
+          }, {});
+          return this.executeAsync(mappedInputs, this.outputNodes, true);
+        }
+        /**
+         * When there are control flow nodes in the graph, the graph execution use
+         * ExecutionContext to keep track of the frames and loop iterators.
+         * @param inputs placeholder tensors for the graph.
+         * @param context the execution context object for current execution.
+         * @param disableWarning disable no async op warning
+         */
+        async executeWithControlFlow(inputs, context, outputNames, disableWarning) {
+          const names = Object.keys(inputs);
+          const inputNodes = names.map(
+            (name) => this.graph.nodes[Object(utils["e" /* parseNodeName */])(name)[0]]
+          );
+          const outputNodes = outputNames.map(
+            (name) => this.graph.nodes[Object(utils["e" /* parseNodeName */])(name)[0]]
+          );
+          const { usedNodes, missingInputs, dynamicNode, syncInputs } = getExecutionSubgraph(
+            inputs,
+            outputNodes,
+            this.weightMap
+          );
+          const stack = [...inputNodes, ...this.graph.weights].map((node) => {
+            return { node, contexts: context.currentContext };
+          });
+          const tensorsMap = Object.assign({}, this.weightMap);
+          Object.keys(inputs).forEach((name) => {
+            const [nodeName, index] = Object(utils["e" /* parseNodeName */])(name);
+            const tensors = [];
+            tensors[index] = inputs[name];
+            tensorsMap[nodeName] = tensors;
+          });
+          const intermediateTensorConsumerCount = {};
+          const tensorsToKeep = this.getFrozenTensorIds(tensorsMap);
+          const added = {};
+          while (stack.length > 0) {
+            const promises = this.processStack(
+              inputNodes,
+              stack,
+              context,
+              tensorsMap,
+              added,
+              tensorsToKeep,
+              outputNames,
+              intermediateTensorConsumerCount,
+              usedNodes
+            );
+            await Promise.all(promises);
+          }
+          if (dynamicNode == null && !disableWarning) {
+            console.warn(
+              `This model execution did not contain any nodes with control flow ` +
+                `or dynamic output shapes. You can use model.execute() instead.`
+            );
+          }
+          const missingOutputs = outputNodes
+            .filter(
+              (node) =>
+                !isControlFlow(node) &&
+                !Object(utils["c" /* getTensor */])(node.name, tensorsMap, context)
+            )
+            .map((node) => node.name);
+          if (missingOutputs.length > 0) {
+            let alternativeMsg = "";
+            if (dynamicNode != null) {
+              alternativeMsg =
+                `Alternatively, to avoid the dynamic ops, use model.execute() ` +
+                `and specify the inputs [${syncInputs}]`;
+            }
+            throw new Error(
+              `Cannot compute the outputs [${missingOutputs}] from the provided ` +
+                `inputs [${names}]. Consider providing the following inputs: ` +
+                `[${missingInputs}]. ${alternativeMsg}`
+            );
+          }
+          return tensorsMap;
+        }
+        processStack(
+          inputNodes,
+          stack,
+          context,
+          tensorMap,
+          added,
+          tensorsToKeep,
+          outputNames,
+          intermediateTensorConsumerCount,
+          usedNodes
+        ) {
+          const promises = [];
+          while (stack.length > 0) {
+            const item = stack.pop();
+            context.currentContext = item.contexts;
+            let nodeName = "";
+            // The tensor of the Enter op with isConstant set should be set
+            // in the parent scope, so it will be available as constant for the
+            // whole loop.
+            if (
+              item.node.op === "Enter" &&
+              Object(utils["b" /* getParamValue */])("isConstant", item.node, tensorMap, context)
+            ) {
+              [nodeName] = Object(utils["a" /* getNodeNameAndIndex */])(item.node.name, context);
+            }
+            // only process nodes that are not provided as input nodes.
+            if (inputNodes.indexOf(item.node) === -1) {
+              const tensors = operation_executor_executeOp(item.node, tensorMap, context);
+              if (!nodeName) {
+                [nodeName] = Object(utils["a" /* getNodeNameAndIndex */])(item.node.name, context);
+              }
+              const currentContext = context.currentContext;
+              if (tensors instanceof Promise) {
+                promises.push(
+                  tensors.then((t) => {
+                    tensorMap[nodeName] = t;
+                    context.currentContext = currentContext;
+                    this.checkTensorForDisposal(
+                      nodeName,
+                      item.node,
+                      tensorMap,
+                      context,
+                      tensorsToKeep,
+                      outputNames,
+                      intermediateTensorConsumerCount
+                    );
+                    this.processChildNodes(item.node, stack, context, tensorMap, added, usedNodes);
+                    return t;
+                  })
+                );
+              } else {
+                tensorMap[nodeName] = tensors;
+                this.checkTensorForDisposal(
+                  nodeName,
+                  item.node,
+                  tensorMap,
+                  context,
+                  tensorsToKeep,
+                  outputNames,
+                  intermediateTensorConsumerCount
+                );
+                this.processChildNodes(item.node, stack, context, tensorMap, added, usedNodes);
+              }
+            } else {
+              this.processChildNodes(item.node, stack, context, tensorMap, added, usedNodes);
+            }
+          }
+          return promises;
+        }
+        processChildNodes(node, stack, context, tensorMap, added, usedNodes) {
+          node.children.forEach((childNode) => {
+            const [nodeName] = Object(utils["a" /* getNodeNameAndIndex */])(
+              childNode.name,
+              context
+            );
+            if (added[nodeName] || !usedNodes.has(childNode.name)) {
+              return;
+            }
+            // Merge op can be pushed if any of its inputs has value.
+            if (childNode.op === "Merge") {
+              if (
+                childNode.inputNames.some((name) => {
+                  return !!Object(utils["c" /* getTensor */])(name, tensorMap, context);
+                })
+              ) {
+                added[nodeName] = true;
+                stack.push({ contexts: context.currentContext, node: childNode });
+              }
+            } // Otherwise all inputs must to have value.
+            else if (
+              childNode.inputNames.every((name) => {
+                return !!Object(utils["c" /* getTensor */])(name, tensorMap, context);
+              })
+            ) {
+              added[nodeName] = true;
+              stack.push({ contexts: context.currentContext, node: childNode });
+            }
+          });
+        }
+        /**
+         * Releases the memory used by the weight tensors.
+         */
+        dispose() {
+          Object.keys(this.weightMap).forEach((key) =>
+            this.weightMap[key].forEach((tensor) => tensor.dispose())
+          );
+        }
+        checkInputShapeAndType(inputs) {
+          Object.keys(inputs).forEach((name) => {
+            const input = inputs[name];
+            const [nodeName] = Object(utils["e" /* parseNodeName */])(name);
+            const node = this.graph.nodes[nodeName];
+            if (node.attrParams["shape"] && node.attrParams["shape"].value) {
+              const shape = node.attrParams["shape"].value;
+              const match =
+                shape.length === input.shape.length &&
+                input.shape.every((dim, index) => shape[index] === -1 || shape[index] === dim);
+              dist["util"].assert(
+                match,
+                () =>
+                  `The shape of dict['${node.name}'] provided in ` +
+                  `model.execute(dict) must be [${shape}], but was ` +
+                  `[${input.shape}]`
+              );
+            }
+            if (node.attrParams["dtype"] && node.attrParams["dtype"].value) {
+              dist["util"].assert(
+                input.dtype === node.attrParams["dtype"].value,
+                () =>
+                  `The dtype of dict['${node.name}'] provided in ` +
+                  `model.execute(dict) must be ` +
+                  `${node.attrParams["dtype"].value}, but was ${input.dtype}`
+              );
+            }
+          });
+        }
+        mapInputs(inputs) {
+          const result = {};
+          for (const inputName in inputs) {
+            if (
+              this._signature != null &&
+              this._signature.inputs != null &&
+              this._signature.inputs[inputName] != null
+            ) {
+              const tensor = this._signature.inputs[inputName];
+              result[tensor.name] = inputs[inputName];
+            } else {
+              result[inputName] = inputs[inputName];
+            }
+          }
+          return result;
+        }
+        checkInputs(inputs) {
+          const notInGraph = Object.keys(inputs).filter((name) => {
+            const [nodeName] = Object(utils["e" /* parseNodeName */])(name);
+            return this.graph.nodes[nodeName] == null;
+          });
+          if (notInGraph.length > 0) {
+            throw new Error(
+              `The dict provided in model.execute(dict) has ` +
+                `keys: [${notInGraph}] that are not part of graph`
+            );
+          }
+        }
+        mapOutputs(outputs) {
+          return outputs.map((name) => {
+            if (
+              this._signature != null &&
+              this._signature.outputs != null &&
+              this._signature.outputs[name] != null
+            ) {
+              const tensor = this._signature.outputs[name];
+              return tensor.name;
+            }
+            return name;
+          }, {});
+        }
+        checkOutputs(outputs) {
+          outputs.forEach((name) => {
+            const [normalizedName] = Object(utils["e" /* parseNodeName */])(name);
+            if (!this.graph.nodes[normalizedName]) {
+              throw new Error(`The output '${name}' is not found in the graph`);
+            }
+          });
+        }
+      }
+      //# sourceMappingURL=graph_executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/executor/graph_model.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const TFHUB_SEARCH_PARAM = "?tfjs-format=file";
+      const DEFAULT_MODEL_NAME = "model.json";
+      /**
+       * A `tf.GraphModel` is a directed, acyclic graph built from a
+       * SavedModel GraphDef and allows inference execution.
+       *
+       * A `tf.GraphModel` can only be created by loading from a model converted from
+       * a [TensorFlow SavedModel](https://www.tensorflow.org/guide/saved_model) using
+       * the command line converter tool and loaded via `tf.loadGraphModel`.
+       */
+      /** @doc {heading: 'Models', subheading: 'Classes'} */
+      class graph_model_GraphModel {
+        /**
+         * @param modelUrl url for the model, or an `io.IOHandler`.
+         * @param weightManifestUrl url for the weight file generated by
+         * scripts/convert.py script.
+         * @param requestOption options for Request, which allows to send credentials
+         * and custom headers.
+         * @param onProgress Optional, progress callback function, fired periodically
+         * before the load is completed.
+         */
+        constructor(modelUrl, loadOptions = {}) {
+          this.modelUrl = modelUrl;
+          this.loadOptions = loadOptions;
+          this.version = "n/a";
+          if (loadOptions == null) {
+            this.loadOptions = {};
+          }
+        }
+        // Returns the version information for the tensorflow model GraphDef.
+        get modelVersion() {
+          return this.version;
+        }
+        get inputNodes() {
+          return this.executor.inputNodes;
+        }
+        get outputNodes() {
+          return this.executor.outputNodes;
+        }
+        get inputs() {
+          return this.executor.inputs;
+        }
+        get outputs() {
+          return this.executor.outputs;
+        }
+        get weights() {
+          return this.executor.weightMap;
+        }
+        findIOHandler() {
+          const path = this.modelUrl;
+          if (path.load != null) {
+            // Path is an IO Handler.
+            this.handler = path;
+          } else if (this.loadOptions.requestInit != null) {
+            this.handler = dist["io"].browserHTTPRequest(path, this.loadOptions);
+          } else {
+            const handlers = dist["io"].getLoadHandlers(path, this.loadOptions);
+            if (handlers.length === 0) {
+              // For backward compatibility: if no load handler can be found,
+              // assume it is a relative http path.
+              handlers.push(dist["io"].browserHTTPRequest(path, this.loadOptions));
+            } else if (handlers.length > 1) {
+              throw new Error(
+                `Found more than one (${handlers.length}) load handlers for ` + `URL '${[path]}'`
+              );
+            }
+            this.handler = handlers[0];
+          }
+        }
+        /**
+         * Loads the model and weight files, construct the in memory weight map and
+         * compile the inference graph.
+         */
+        async load() {
+          this.findIOHandler();
+          if (this.handler.load == null) {
+            throw new Error(
+              "Cannot proceed with model loading because the IOHandler provided " +
+                "does not have the `load` method implemented."
+            );
+          }
+          const artifacts = await this.handler.load();
+          return this.loadSync(artifacts);
+        }
+        /**
+         * Synchronously construct the in memory weight map and
+         * compile the inference graph.
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes', ignoreCI: true} */
+        loadSync(artifacts) {
+          this.artifacts = artifacts;
+          const graph = this.artifacts.modelTopology;
+          let signature = {};
+          if (this.artifacts.userDefinedMetadata != null) {
+            signature = this.artifacts.userDefinedMetadata.signature; // tslint:disable-next-line:no-any
+          }
+          this.version = `${graph.versions.producer}.${graph.versions.minConsumer}`;
+          const weightMap = dist["io"].decodeWeights(
+            this.artifacts.weightData,
+            this.artifacts.weightSpecs
+          );
+          this.executor = new graph_executor_GraphExecutor(
+            operation_mapper["a" /* OperationMapper */].Instance.transformGraph(graph, signature)
+          );
+          this.executor.weightMap = this.convertTensorMapToTensorsMap(weightMap);
+          return true;
+        }
+        /**
+         * Save the configuration and/or weights of the GraphModel.
+         *
+         * An `IOHandler` is an object that has a `save` method of the proper
+         * signature defined. The `save` method manages the storing or
+         * transmission of serialized data ("artifacts") that represent the
+         * model's topology and weights onto or via a specific medium, such as
+         * file downloads, local storage, IndexedDB in the web browser and HTTP
+         * requests to a server. TensorFlow.js provides `IOHandler`
+         * implementations for a number of frequently used saving mediums, such as
+         * `tf.io.browserDownloads` and `tf.io.browserLocalStorage`. See `tf.io`
+         * for more details.
+         *
+         * This method also allows you to refer to certain types of `IOHandler`s
+         * as URL-like string shortcuts, such as 'localstorage://' and
+         * 'indexeddb://'.
+         *
+         * Example 1: Save `model`'s topology and weights to browser [local
+         * storage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage);
+         * then load it back.
+         *
+         * ```js
+         * const modelUrl =
+         *    'https://storage.googleapis.com/tfjs-models/savedmodel/mobilenet_v2_1.0_224/model.json';
+         * const model = await tf.loadGraphModel(modelUrl);
+         * const zeros = tf.zeros([1, 224, 224, 3]);
+         * model.predict(zeros).print();
+         *
+         * const saveResults = await model.save('localstorage://my-model-1');
+         *
+         * const loadedModel = await tf.loadGraphModel('localstorage://my-model-1');
+         * console.log('Prediction from loaded model:');
+         * model.predict(zeros).print();
+         * ```
+         *
+         * @param handlerOrURL An instance of `IOHandler` or a URL-like,
+         * scheme-based string shortcut for `IOHandler`.
+         * @param config Options for saving the model.
+         * @returns A `Promise` of `SaveResult`, which summarizes the result of
+         * the saving, such as byte sizes of the saved artifacts for the model's
+         *   topology and weight values.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes', ignoreCI: true}
+         */
+        async save(handlerOrURL, config) {
+          if (typeof handlerOrURL === "string") {
+            const handlers = dist["io"].getSaveHandlers(handlerOrURL);
+            if (handlers.length === 0) {
+              throw new Error(`Cannot find any save handlers for URL '${handlerOrURL}'`);
+            } else if (handlers.length > 1) {
+              throw new Error(
+                `Found more than one (${handlers.length}) save handlers for ` +
+                  `URL '${handlerOrURL}'`
+              );
+            }
+            handlerOrURL = handlers[0];
+          }
+          if (handlerOrURL.save == null) {
+            throw new Error(
+              "GraphModel.save() cannot proceed because the IOHandler " +
+                "provided does not have the `save` attribute defined."
+            );
+          }
+          return handlerOrURL.save(this.artifacts);
+        }
+        /**
+         * Execute the inference for the input tensors.
+         *
+         * @param input The input tensors, when there is single input for the model,
+         * inputs param should be a `tf.Tensor`. For models with mutliple inputs,
+         * inputs params should be in either `tf.Tensor`[] if the input order is
+         * fixed, or otherwise NamedTensorMap format.
+         *
+         * For model with multiple inputs, we recommend you use NamedTensorMap as the
+         * input type, if you use `tf.Tensor`[], the order of the array needs to
+         * follow the
+         * order of inputNodes array. @see {@link GraphModel.inputNodes}
+         *
+         * You can also feed any intermediate nodes using the NamedTensorMap as the
+         * input type. For example, given the graph
+         *    InputNode => Intermediate => OutputNode,
+         * you can execute the subgraph Intermediate => OutputNode by calling
+         *    model.execute('IntermediateNode' : tf.tensor(...));
+         *
+         * This is useful for models that uses tf.dynamic_rnn, where the intermediate
+         * state needs to be fed manually.
+         *
+         * For batch inference execution, the tensors for each input need to be
+         * concatenated together. For example with mobilenet, the required input shape
+         * is [1, 244, 244, 3], which represents the [batch, height, width, channel].
+         * If we are provide a batched data of 100 images, the input tensor should be
+         * in the shape of [100, 244, 244, 3].
+         *
+         * @param config Prediction configuration for specifying the batch size and
+         * output node names. Currently the batch size option is ignored for graph
+         * model.
+         *
+         * @returns Inference result tensors. The output would be single `tf.Tensor`
+         * if model has single output node, otherwise Tensor[] or NamedTensorMap[]
+         * will be returned for model with multiple outputs.
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes'} */
+        predict(inputs, config) {
+          return this.execute(inputs, this.outputNodes);
+        }
+        normalizeInputs(inputs) {
+          if (!(inputs instanceof dist["Tensor"]) && !Array.isArray(inputs)) {
+            // The input is already a NamedTensorMap.
+            return inputs;
+          }
+          inputs = Array.isArray(inputs) ? inputs : [inputs];
+          if (inputs.length !== this.inputNodes.length) {
+            throw new Error(
+              "Input tensor count mismatch," +
+                `the graph model has ${this.inputNodes.length} placeholders, ` +
+                `while there are ${inputs.length} input tensors.`
+            );
+          }
+          return this.inputNodes.reduce((map, inputName, i) => {
+            map[inputName] = inputs[i];
+            return map;
+          }, {});
+        }
+        normalizeOutputs(outputs) {
+          outputs = outputs || this.outputNodes;
+          return !Array.isArray(outputs) ? [outputs] : outputs;
+        }
+        /**
+         * Executes inference for the model for given input tensors.
+         * @param inputs tensor, tensor array or tensor map of the inputs for the
+         * model, keyed by the input node names.
+         * @param outputs output node name from the Tensorflow model, if no
+         * outputs are specified, the default outputs of the model would be used.
+         * You can inspect intermediate nodes of the model by adding them to the
+         * outputs array.
+         *
+         * @returns A single tensor if provided with a single output or no outputs
+         * are provided and there is only one default output, otherwise return a
+         * tensor array. The order of the tensor array is the same as the outputs
+         * if provided, otherwise the order of outputNodes attribute of the model.
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes'} */
+        execute(inputs, outputs) {
+          inputs = this.normalizeInputs(inputs);
+          outputs = this.normalizeOutputs(outputs);
+          const result = this.executor.execute(inputs, outputs);
+          return result.length > 1 ? result : result[0];
+        }
+        /**
+         * Executes inference for the model for given input tensors in async
+         * fashion, use this method when your model contains control flow ops.
+         * @param inputs tensor, tensor array or tensor map of the inputs for the
+         * model, keyed by the input node names.
+         * @param outputs output node name from the Tensorflow model, if no outputs
+         * are specified, the default outputs of the model would be used. You can
+         * inspect intermediate nodes of the model by adding them to the outputs
+         * array.
+         *
+         * @returns A Promise of single tensor if provided with a single output or
+         * no outputs are provided and there is only one default output, otherwise
+         * return a tensor map.
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes'} */
+        async executeAsync(inputs, outputs) {
+          inputs = this.normalizeInputs(inputs);
+          outputs = this.normalizeOutputs(outputs);
+          const result = await this.executor.executeAsync(inputs, outputs);
+          return result.length > 1 ? result : result[0];
+        }
+        convertTensorMapToTensorsMap(map) {
+          return Object.keys(map).reduce((newMap, key) => {
+            newMap[key] = [map[key]];
+            return newMap;
+          }, {});
+        }
+        /**
+         * Releases the memory used by the weight tensors.
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes'} */
+        dispose() {
+          this.executor.dispose();
+        }
+      }
+      /**
+       * Load a graph model given a URL to the model definition.
+       *
+       * Example of loading MobileNetV2 from a URL and making a prediction with a
+       * zeros input:
+       *
+       * ```js
+       * const modelUrl =
+       *    'https://storage.googleapis.com/tfjs-models/savedmodel/mobilenet_v2_1.0_224/model.json';
+       * const model = await tf.loadGraphModel(modelUrl);
+       * const zeros = tf.zeros([1, 224, 224, 3]);
+       * model.predict(zeros).print();
+       * ```
+       *
+       * Example of loading MobileNetV2 from a TF Hub URL and making a prediction with
+       * a zeros input:
+       *
+       * ```js
+       * const modelUrl =
+       *    'https://tfhub.dev/google/imagenet/mobilenet_v2_140_224/classification/2';
+       * const model = await tf.loadGraphModel(modelUrl, {fromTFHub: true});
+       * const zeros = tf.zeros([1, 224, 224, 3]);
+       * model.predict(zeros).print();
+       * ```
+       * @param modelUrl The url or an `io.IOHandler` that loads the model.
+       * @param options Options for the HTTP request, which allows to send credentials
+       *    and custom headers.
+       */
+      /** @doc {heading: 'Models', subheading: 'Loading'} */
+      async function loadGraphModel(modelUrl, options = {}) {
+        if (modelUrl == null) {
+          throw new Error(
+            "modelUrl in loadGraphModel() cannot be null. Please provide a url " +
+              "or an IOHandler that loads the model"
+          );
+        }
+        if (options == null) {
+          options = {};
+        }
+        if (options.fromTFHub) {
+          if (modelUrl.load == null) {
+            if (!modelUrl.endsWith("/")) {
+              modelUrl = modelUrl + "/";
+            }
+            modelUrl = `${modelUrl}${DEFAULT_MODEL_NAME}${TFHUB_SEARCH_PARAM}`;
+          }
+        }
+        const model = new graph_model_GraphModel(modelUrl, options);
+        await model.load();
+        return model;
+      }
+      //# sourceMappingURL=graph_model.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/version.js
+      /** @license See the LICENSE file. */
+      // This code is auto-generated, do not modify this file!
+      const version = "2.0.1";
+
+      //# sourceMappingURL=version.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-converter/dist/index.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      //# sourceMappingURL=index.js.map
+
+      /***/
+    },
+    /* 39 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (global) {
+        /*!
+         * The buffer module from node.js, for the browser.
+         *
+         * @author   Feross Aboukhadijeh <http://feross.org>
+         * @license  MIT
+         */
+        /* eslint-disable no-proto */
+
+        var base64 = __webpack_require__(65);
+        var ieee754 = __webpack_require__(66);
+        var isArray = __webpack_require__(67);
+
+        exports.Buffer = Buffer;
+        exports.SlowBuffer = SlowBuffer;
+        exports.INSPECT_MAX_BYTES = 50;
+
+        /**
+ * If `Buffer.TYPED_ARRAY_SUPPORT`:
+ *   === true    Use Uint8Array implementation (fastest)
+ *   === false   Use Object implementation (most compatible, even IE6)
+ *
+ * Browsers that support typed arrays are IE 10+, Firefox 4+, Chrome 7+, Safari 5.1+,
+ * Opera 11.6+, iOS 4.2+.
+ *
+ * Due to various browser bugs, sometimes the Object implementation will be used even
+ * when the browser supports typed arrays.
+ *
+ * Note:
+ *
+ *   - Firefox 4-29 lacks support for adding new properties to `Uint8Array` instances,
+ *     See: https://bugzilla.mozilla.org/show_bug.cgi?id=695438.
+ *
+ *   - Chrome 9-10 is missing the `TypedArray.prototype.subarray` function.
+ *
+ *   - IE10 has a broken `TypedArray.prototype.subarray` function which returns arrays of
+ *     incorrect length in some situations.
+
+ * We detect these buggy browsers and set `Buffer.TYPED_ARRAY_SUPPORT` to `false` so they
+ * get the Object implementation, which is slower but behaves correctly.
+ */
+        Buffer.TYPED_ARRAY_SUPPORT =
+          global.TYPED_ARRAY_SUPPORT !== undefined
+            ? global.TYPED_ARRAY_SUPPORT
+            : typedArraySupport();
+
+        /*
+         * Export kMaxLength after typed array support is determined.
+         */
+        exports.kMaxLength = kMaxLength();
+
+        function typedArraySupport() {
+          try {
+            var arr = new Uint8Array(1);
+            arr.__proto__ = {
+              __proto__: Uint8Array.prototype,
+              foo: function () {
+                return 42;
+              },
+            };
+            return (
+              arr.foo() === 42 && // typed array instances can be augmented
+              typeof arr.subarray === "function" && // chrome 9-10 lack `subarray`
+              arr.subarray(1, 1).byteLength === 0
+            ); // ie10 has broken `subarray`
+          } catch (e) {
+            return false;
+          }
+        }
+
+        function kMaxLength() {
+          return Buffer.TYPED_ARRAY_SUPPORT ? 0x7fffffff : 0x3fffffff;
+        }
+
+        function createBuffer(that, length) {
+          if (kMaxLength() < length) {
+            throw new RangeError("Invalid typed array length");
+          }
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            // Return an augmented `Uint8Array` instance, for best performance
+            that = new Uint8Array(length);
+            that.__proto__ = Buffer.prototype;
+          } else {
+            // Fallback: Return an object instance of the Buffer class
+            if (that === null) {
+              that = new Buffer(length);
+            }
+            that.length = length;
+          }
+
+          return that;
+        }
+
+        /**
+         * The Buffer constructor returns instances of `Uint8Array` that have their
+         * prototype changed to `Buffer.prototype`. Furthermore, `Buffer` is a subclass of
+         * `Uint8Array`, so the returned instances will have all the node `Buffer` methods
+         * and the `Uint8Array` methods. Square bracket notation works as expected -- it
+         * returns a single octet.
+         *
+         * The `Uint8Array` prototype remains unmodified.
+         */
+
+        function Buffer(arg, encodingOrOffset, length) {
+          if (!Buffer.TYPED_ARRAY_SUPPORT && !(this instanceof Buffer)) {
+            return new Buffer(arg, encodingOrOffset, length);
+          }
+
+          // Common case.
+          if (typeof arg === "number") {
+            if (typeof encodingOrOffset === "string") {
+              throw new Error("If encoding is specified then the first argument must be a string");
+            }
+            return allocUnsafe(this, arg);
+          }
+          return from(this, arg, encodingOrOffset, length);
+        }
+
+        Buffer.poolSize = 8192; // not used by this implementation
+
+        // TODO: Legacy, not needed anymore. Remove in next major version.
+        Buffer._augment = function (arr) {
+          arr.__proto__ = Buffer.prototype;
+          return arr;
+        };
+
+        function from(that, value, encodingOrOffset, length) {
+          if (typeof value === "number") {
+            throw new TypeError('"value" argument must not be a number');
+          }
+
+          if (typeof ArrayBuffer !== "undefined" && value instanceof ArrayBuffer) {
+            return fromArrayBuffer(that, value, encodingOrOffset, length);
+          }
+
+          if (typeof value === "string") {
+            return fromString(that, value, encodingOrOffset);
+          }
+
+          return fromObject(that, value);
+        }
+
+        /**
+         * Functionally equivalent to Buffer(arg, encoding) but throws a TypeError
+         * if value is a number.
+         * Buffer.from(str[, encoding])
+         * Buffer.from(array)
+         * Buffer.from(buffer)
+         * Buffer.from(arrayBuffer[, byteOffset[, length]])
+         **/
+        Buffer.from = function (value, encodingOrOffset, length) {
+          return from(null, value, encodingOrOffset, length);
+        };
+
+        if (Buffer.TYPED_ARRAY_SUPPORT) {
+          Buffer.prototype.__proto__ = Uint8Array.prototype;
+          Buffer.__proto__ = Uint8Array;
+          if (
+            typeof Symbol !== "undefined" &&
+            Symbol.species &&
+            Buffer[Symbol.species] === Buffer
+          ) {
+            // Fix subarray() in ES2016. See: https://github.com/feross/buffer/pull/97
+            Object.defineProperty(Buffer, Symbol.species, {
+              value: null,
+              configurable: true,
+            });
+          }
+        }
+
+        function assertSize(size) {
+          if (typeof size !== "number") {
+            throw new TypeError('"size" argument must be a number');
+          } else if (size < 0) {
+            throw new RangeError('"size" argument must not be negative');
+          }
+        }
+
+        function alloc(that, size, fill, encoding) {
+          assertSize(size);
+          if (size <= 0) {
+            return createBuffer(that, size);
+          }
+          if (fill !== undefined) {
+            // Only pay attention to encoding if it's a string. This
+            // prevents accidentally sending in a number that would
+            // be interpretted as a start offset.
+            return typeof encoding === "string"
+              ? createBuffer(that, size).fill(fill, encoding)
+              : createBuffer(that, size).fill(fill);
+          }
+          return createBuffer(that, size);
+        }
+
+        /**
+         * Creates a new filled Buffer instance.
+         * alloc(size[, fill[, encoding]])
+         **/
+        Buffer.alloc = function (size, fill, encoding) {
+          return alloc(null, size, fill, encoding);
+        };
+
+        function allocUnsafe(that, size) {
+          assertSize(size);
+          that = createBuffer(that, size < 0 ? 0 : checked(size) | 0);
+          if (!Buffer.TYPED_ARRAY_SUPPORT) {
+            for (var i = 0; i < size; ++i) {
+              that[i] = 0;
+            }
+          }
+          return that;
+        }
+
+        /**
+         * Equivalent to Buffer(num), by default creates a non-zero-filled Buffer instance.
+         * */
+        Buffer.allocUnsafe = function (size) {
+          return allocUnsafe(null, size);
+        };
+        /**
+         * Equivalent to SlowBuffer(num), by default creates a non-zero-filled Buffer instance.
+         */
+        Buffer.allocUnsafeSlow = function (size) {
+          return allocUnsafe(null, size);
+        };
+
+        function fromString(that, string, encoding) {
+          if (typeof encoding !== "string" || encoding === "") {
+            encoding = "utf8";
+          }
+
+          if (!Buffer.isEncoding(encoding)) {
+            throw new TypeError('"encoding" must be a valid string encoding');
+          }
+
+          var length = byteLength(string, encoding) | 0;
+          that = createBuffer(that, length);
+
+          var actual = that.write(string, encoding);
+
+          if (actual !== length) {
+            // Writing a hex string, for example, that contains invalid characters will
+            // cause everything after the first invalid character to be ignored. (e.g.
+            // 'abxxcd' will be treated as 'ab')
+            that = that.slice(0, actual);
+          }
+
+          return that;
+        }
+
+        function fromArrayLike(that, array) {
+          var length = array.length < 0 ? 0 : checked(array.length) | 0;
+          that = createBuffer(that, length);
+          for (var i = 0; i < length; i += 1) {
+            that[i] = array[i] & 255;
+          }
+          return that;
+        }
+
+        function fromArrayBuffer(that, array, byteOffset, length) {
+          array.byteLength; // this throws if `array` is not a valid ArrayBuffer
+
+          if (byteOffset < 0 || array.byteLength < byteOffset) {
+            throw new RangeError("'offset' is out of bounds");
+          }
+
+          if (array.byteLength < byteOffset + (length || 0)) {
+            throw new RangeError("'length' is out of bounds");
+          }
+
+          if (byteOffset === undefined && length === undefined) {
+            array = new Uint8Array(array);
+          } else if (length === undefined) {
+            array = new Uint8Array(array, byteOffset);
+          } else {
+            array = new Uint8Array(array, byteOffset, length);
+          }
+
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            // Return an augmented `Uint8Array` instance, for best performance
+            that = array;
+            that.__proto__ = Buffer.prototype;
+          } else {
+            // Fallback: Return an object instance of the Buffer class
+            that = fromArrayLike(that, array);
+          }
+          return that;
+        }
+
+        function fromObject(that, obj) {
+          if (Buffer.isBuffer(obj)) {
+            var len = checked(obj.length) | 0;
+            that = createBuffer(that, len);
+
+            if (that.length === 0) {
+              return that;
+            }
+
+            obj.copy(that, 0, 0, len);
+            return that;
+          }
+
+          if (obj) {
+            if (
+              (typeof ArrayBuffer !== "undefined" && obj.buffer instanceof ArrayBuffer) ||
+              "length" in obj
+            ) {
+              if (typeof obj.length !== "number" || isnan(obj.length)) {
+                return createBuffer(that, 0);
+              }
+              return fromArrayLike(that, obj);
+            }
+
+            if (obj.type === "Buffer" && isArray(obj.data)) {
+              return fromArrayLike(that, obj.data);
+            }
+          }
+
+          throw new TypeError(
+            "First argument must be a string, Buffer, ArrayBuffer, Array, or array-like object."
+          );
+        }
+
+        function checked(length) {
+          // Note: cannot use `length < kMaxLength()` here because that fails when
+          // length is NaN (which is otherwise coerced to zero.)
+          if (length >= kMaxLength()) {
+            throw new RangeError(
+              "Attempt to allocate Buffer larger than maximum " +
+                "size: 0x" +
+                kMaxLength().toString(16) +
+                " bytes"
+            );
+          }
+          return length | 0;
+        }
+
+        function SlowBuffer(length) {
+          if (+length != length) {
+            // eslint-disable-line eqeqeq
+            length = 0;
+          }
+          return Buffer.alloc(+length);
+        }
+
+        Buffer.isBuffer = function isBuffer(b) {
+          return !!(b != null && b._isBuffer);
+        };
+
+        Buffer.compare = function compare(a, b) {
+          if (!Buffer.isBuffer(a) || !Buffer.isBuffer(b)) {
+            throw new TypeError("Arguments must be Buffers");
+          }
+
+          if (a === b) return 0;
+
+          var x = a.length;
+          var y = b.length;
+
+          for (var i = 0, len = Math.min(x, y); i < len; ++i) {
+            if (a[i] !== b[i]) {
+              x = a[i];
+              y = b[i];
+              break;
+            }
+          }
+
+          if (x < y) return -1;
+          if (y < x) return 1;
+          return 0;
+        };
+
+        Buffer.isEncoding = function isEncoding(encoding) {
+          switch (String(encoding).toLowerCase()) {
+            case "hex":
+            case "utf8":
+            case "utf-8":
+            case "ascii":
+            case "latin1":
+            case "binary":
+            case "base64":
+            case "ucs2":
+            case "ucs-2":
+            case "utf16le":
+            case "utf-16le":
+              return true;
+            default:
+              return false;
+          }
+        };
+
+        Buffer.concat = function concat(list, length) {
+          if (!isArray(list)) {
+            throw new TypeError('"list" argument must be an Array of Buffers');
+          }
+
+          if (list.length === 0) {
+            return Buffer.alloc(0);
+          }
+
+          var i;
+          if (length === undefined) {
+            length = 0;
+            for (i = 0; i < list.length; ++i) {
+              length += list[i].length;
+            }
+          }
+
+          var buffer = Buffer.allocUnsafe(length);
+          var pos = 0;
+          for (i = 0; i < list.length; ++i) {
+            var buf = list[i];
+            if (!Buffer.isBuffer(buf)) {
+              throw new TypeError('"list" argument must be an Array of Buffers');
+            }
+            buf.copy(buffer, pos);
+            pos += buf.length;
+          }
+          return buffer;
+        };
+
+        function byteLength(string, encoding) {
+          if (Buffer.isBuffer(string)) {
+            return string.length;
+          }
+          if (
+            typeof ArrayBuffer !== "undefined" &&
+            typeof ArrayBuffer.isView === "function" &&
+            (ArrayBuffer.isView(string) || string instanceof ArrayBuffer)
+          ) {
+            return string.byteLength;
+          }
+          if (typeof string !== "string") {
+            string = "" + string;
+          }
+
+          var len = string.length;
+          if (len === 0) return 0;
+
+          // Use a for loop to avoid recursion
+          var loweredCase = false;
+          for (;;) {
+            switch (encoding) {
+              case "ascii":
+              case "latin1":
+              case "binary":
+                return len;
+              case "utf8":
+              case "utf-8":
+              case undefined:
+                return utf8ToBytes(string).length;
+              case "ucs2":
+              case "ucs-2":
+              case "utf16le":
+              case "utf-16le":
+                return len * 2;
+              case "hex":
+                return len >>> 1;
+              case "base64":
+                return base64ToBytes(string).length;
+              default:
+                if (loweredCase) return utf8ToBytes(string).length; // assume utf8
+                encoding = ("" + encoding).toLowerCase();
+                loweredCase = true;
+            }
+          }
+        }
+        Buffer.byteLength = byteLength;
+
+        function slowToString(encoding, start, end) {
+          var loweredCase = false;
+
+          // No need to verify that "this.length <= MAX_UINT32" since it's a read-only
+          // property of a typed array.
+
+          // This behaves neither like String nor Uint8Array in that we set start/end
+          // to their upper/lower bounds if the value passed is out of range.
+          // undefined is handled specially as per ECMA-262 6th Edition,
+          // Section 13.3.3.7 Runtime Semantics: KeyedBindingInitialization.
+          if (start === undefined || start < 0) {
+            start = 0;
+          }
+          // Return early if start > this.length. Done here to prevent potential uint32
+          // coercion fail below.
+          if (start > this.length) {
+            return "";
+          }
+
+          if (end === undefined || end > this.length) {
+            end = this.length;
+          }
+
+          if (end <= 0) {
+            return "";
+          }
+
+          // Force coersion to uint32. This will also coerce falsey/NaN values to 0.
+          end >>>= 0;
+          start >>>= 0;
+
+          if (end <= start) {
+            return "";
+          }
+
+          if (!encoding) encoding = "utf8";
+
+          while (true) {
+            switch (encoding) {
+              case "hex":
+                return hexSlice(this, start, end);
+
+              case "utf8":
+              case "utf-8":
+                return utf8Slice(this, start, end);
+
+              case "ascii":
+                return asciiSlice(this, start, end);
+
+              case "latin1":
+              case "binary":
+                return latin1Slice(this, start, end);
+
+              case "base64":
+                return base64Slice(this, start, end);
+
+              case "ucs2":
+              case "ucs-2":
+              case "utf16le":
+              case "utf-16le":
+                return utf16leSlice(this, start, end);
+
+              default:
+                if (loweredCase) throw new TypeError("Unknown encoding: " + encoding);
+                encoding = (encoding + "").toLowerCase();
+                loweredCase = true;
+            }
+          }
+        }
+
+        // The property is used by `Buffer.isBuffer` and `is-buffer` (in Safari 5-7) to detect
+        // Buffer instances.
+        Buffer.prototype._isBuffer = true;
+
+        function swap(b, n, m) {
+          var i = b[n];
+          b[n] = b[m];
+          b[m] = i;
+        }
+
+        Buffer.prototype.swap16 = function swap16() {
+          var len = this.length;
+          if (len % 2 !== 0) {
+            throw new RangeError("Buffer size must be a multiple of 16-bits");
+          }
+          for (var i = 0; i < len; i += 2) {
+            swap(this, i, i + 1);
+          }
+          return this;
+        };
+
+        Buffer.prototype.swap32 = function swap32() {
+          var len = this.length;
+          if (len % 4 !== 0) {
+            throw new RangeError("Buffer size must be a multiple of 32-bits");
+          }
+          for (var i = 0; i < len; i += 4) {
+            swap(this, i, i + 3);
+            swap(this, i + 1, i + 2);
+          }
+          return this;
+        };
+
+        Buffer.prototype.swap64 = function swap64() {
+          var len = this.length;
+          if (len % 8 !== 0) {
+            throw new RangeError("Buffer size must be a multiple of 64-bits");
+          }
+          for (var i = 0; i < len; i += 8) {
+            swap(this, i, i + 7);
+            swap(this, i + 1, i + 6);
+            swap(this, i + 2, i + 5);
+            swap(this, i + 3, i + 4);
+          }
+          return this;
+        };
+
+        Buffer.prototype.toString = function toString() {
+          var length = this.length | 0;
+          if (length === 0) return "";
+          if (arguments.length === 0) return utf8Slice(this, 0, length);
+          return slowToString.apply(this, arguments);
+        };
+
+        Buffer.prototype.equals = function equals(b) {
+          if (!Buffer.isBuffer(b)) throw new TypeError("Argument must be a Buffer");
+          if (this === b) return true;
+          return Buffer.compare(this, b) === 0;
+        };
+
+        Buffer.prototype.inspect = function inspect() {
+          var str = "";
+          var max = exports.INSPECT_MAX_BYTES;
+          if (this.length > 0) {
+            str = this.toString("hex", 0, max).match(/.{2}/g).join(" ");
+            if (this.length > max) str += " ... ";
+          }
+          return "<Buffer " + str + ">";
+        };
+
+        Buffer.prototype.compare = function compare(target, start, end, thisStart, thisEnd) {
+          if (!Buffer.isBuffer(target)) {
+            throw new TypeError("Argument must be a Buffer");
+          }
+
+          if (start === undefined) {
+            start = 0;
+          }
+          if (end === undefined) {
+            end = target ? target.length : 0;
+          }
+          if (thisStart === undefined) {
+            thisStart = 0;
+          }
+          if (thisEnd === undefined) {
+            thisEnd = this.length;
+          }
+
+          if (start < 0 || end > target.length || thisStart < 0 || thisEnd > this.length) {
+            throw new RangeError("out of range index");
+          }
+
+          if (thisStart >= thisEnd && start >= end) {
+            return 0;
+          }
+          if (thisStart >= thisEnd) {
+            return -1;
+          }
+          if (start >= end) {
+            return 1;
+          }
+
+          start >>>= 0;
+          end >>>= 0;
+          thisStart >>>= 0;
+          thisEnd >>>= 0;
+
+          if (this === target) return 0;
+
+          var x = thisEnd - thisStart;
+          var y = end - start;
+          var len = Math.min(x, y);
+
+          var thisCopy = this.slice(thisStart, thisEnd);
+          var targetCopy = target.slice(start, end);
+
+          for (var i = 0; i < len; ++i) {
+            if (thisCopy[i] !== targetCopy[i]) {
+              x = thisCopy[i];
+              y = targetCopy[i];
+              break;
+            }
+          }
+
+          if (x < y) return -1;
+          if (y < x) return 1;
+          return 0;
+        };
+
+        // Finds either the first index of `val` in `buffer` at offset >= `byteOffset`,
+        // OR the last index of `val` in `buffer` at offset <= `byteOffset`.
+        //
+        // Arguments:
+        // - buffer - a Buffer to search
+        // - val - a string, Buffer, or number
+        // - byteOffset - an index into `buffer`; will be clamped to an int32
+        // - encoding - an optional encoding, relevant is val is a string
+        // - dir - true for indexOf, false for lastIndexOf
+        function bidirectionalIndexOf(buffer, val, byteOffset, encoding, dir) {
+          // Empty buffer means no match
+          if (buffer.length === 0) return -1;
+
+          // Normalize byteOffset
+          if (typeof byteOffset === "string") {
+            encoding = byteOffset;
+            byteOffset = 0;
+          } else if (byteOffset > 0x7fffffff) {
+            byteOffset = 0x7fffffff;
+          } else if (byteOffset < -0x80000000) {
+            byteOffset = -0x80000000;
+          }
+          byteOffset = +byteOffset; // Coerce to Number.
+          if (isNaN(byteOffset)) {
+            // byteOffset: it it's undefined, null, NaN, "foo", etc, search whole buffer
+            byteOffset = dir ? 0 : buffer.length - 1;
+          }
+
+          // Normalize byteOffset: negative offsets start from the end of the buffer
+          if (byteOffset < 0) byteOffset = buffer.length + byteOffset;
+          if (byteOffset >= buffer.length) {
+            if (dir) return -1;
+            else byteOffset = buffer.length - 1;
+          } else if (byteOffset < 0) {
+            if (dir) byteOffset = 0;
+            else return -1;
+          }
+
+          // Normalize val
+          if (typeof val === "string") {
+            val = Buffer.from(val, encoding);
+          }
+
+          // Finally, search either indexOf (if dir is true) or lastIndexOf
+          if (Buffer.isBuffer(val)) {
+            // Special case: looking for empty string/buffer always fails
+            if (val.length === 0) {
+              return -1;
+            }
+            return arrayIndexOf(buffer, val, byteOffset, encoding, dir);
+          } else if (typeof val === "number") {
+            val = val & 0xff; // Search for a byte value [0-255]
+            if (Buffer.TYPED_ARRAY_SUPPORT && typeof Uint8Array.prototype.indexOf === "function") {
+              if (dir) {
+                return Uint8Array.prototype.indexOf.call(buffer, val, byteOffset);
+              } else {
+                return Uint8Array.prototype.lastIndexOf.call(buffer, val, byteOffset);
+              }
+            }
+            return arrayIndexOf(buffer, [val], byteOffset, encoding, dir);
+          }
+
+          throw new TypeError("val must be string, number or Buffer");
+        }
+
+        function arrayIndexOf(arr, val, byteOffset, encoding, dir) {
+          var indexSize = 1;
+          var arrLength = arr.length;
+          var valLength = val.length;
+
+          if (encoding !== undefined) {
+            encoding = String(encoding).toLowerCase();
+            if (
+              encoding === "ucs2" ||
+              encoding === "ucs-2" ||
+              encoding === "utf16le" ||
+              encoding === "utf-16le"
+            ) {
+              if (arr.length < 2 || val.length < 2) {
+                return -1;
+              }
+              indexSize = 2;
+              arrLength /= 2;
+              valLength /= 2;
+              byteOffset /= 2;
+            }
+          }
+
+          function read(buf, i) {
+            if (indexSize === 1) {
+              return buf[i];
+            } else {
+              return buf.readUInt16BE(i * indexSize);
+            }
+          }
+
+          var i;
+          if (dir) {
+            var foundIndex = -1;
+            for (i = byteOffset; i < arrLength; i++) {
+              if (read(arr, i) === read(val, foundIndex === -1 ? 0 : i - foundIndex)) {
+                if (foundIndex === -1) foundIndex = i;
+                if (i - foundIndex + 1 === valLength) return foundIndex * indexSize;
+              } else {
+                if (foundIndex !== -1) i -= i - foundIndex;
+                foundIndex = -1;
+              }
+            }
+          } else {
+            if (byteOffset + valLength > arrLength) byteOffset = arrLength - valLength;
+            for (i = byteOffset; i >= 0; i--) {
+              var found = true;
+              for (var j = 0; j < valLength; j++) {
+                if (read(arr, i + j) !== read(val, j)) {
+                  found = false;
+                  break;
+                }
+              }
+              if (found) return i;
+            }
+          }
+
+          return -1;
+        }
+
+        Buffer.prototype.includes = function includes(val, byteOffset, encoding) {
+          return this.indexOf(val, byteOffset, encoding) !== -1;
+        };
+
+        Buffer.prototype.indexOf = function indexOf(val, byteOffset, encoding) {
+          return bidirectionalIndexOf(this, val, byteOffset, encoding, true);
+        };
+
+        Buffer.prototype.lastIndexOf = function lastIndexOf(val, byteOffset, encoding) {
+          return bidirectionalIndexOf(this, val, byteOffset, encoding, false);
+        };
+
+        function hexWrite(buf, string, offset, length) {
+          offset = Number(offset) || 0;
+          var remaining = buf.length - offset;
+          if (!length) {
+            length = remaining;
+          } else {
+            length = Number(length);
+            if (length > remaining) {
+              length = remaining;
+            }
+          }
+
+          // must be an even number of digits
+          var strLen = string.length;
+          if (strLen % 2 !== 0) throw new TypeError("Invalid hex string");
+
+          if (length > strLen / 2) {
+            length = strLen / 2;
+          }
+          for (var i = 0; i < length; ++i) {
+            var parsed = parseInt(string.substr(i * 2, 2), 16);
+            if (isNaN(parsed)) return i;
+            buf[offset + i] = parsed;
+          }
+          return i;
+        }
+
+        function utf8Write(buf, string, offset, length) {
+          return blitBuffer(utf8ToBytes(string, buf.length - offset), buf, offset, length);
+        }
+
+        function asciiWrite(buf, string, offset, length) {
+          return blitBuffer(asciiToBytes(string), buf, offset, length);
+        }
+
+        function latin1Write(buf, string, offset, length) {
+          return asciiWrite(buf, string, offset, length);
+        }
+
+        function base64Write(buf, string, offset, length) {
+          return blitBuffer(base64ToBytes(string), buf, offset, length);
+        }
+
+        function ucs2Write(buf, string, offset, length) {
+          return blitBuffer(utf16leToBytes(string, buf.length - offset), buf, offset, length);
+        }
+
+        Buffer.prototype.write = function write(string, offset, length, encoding) {
+          // Buffer#write(string)
+          if (offset === undefined) {
+            encoding = "utf8";
+            length = this.length;
+            offset = 0;
+            // Buffer#write(string, encoding)
+          } else if (length === undefined && typeof offset === "string") {
+            encoding = offset;
+            length = this.length;
+            offset = 0;
+            // Buffer#write(string, offset[, length][, encoding])
+          } else if (isFinite(offset)) {
+            offset = offset | 0;
+            if (isFinite(length)) {
+              length = length | 0;
+              if (encoding === undefined) encoding = "utf8";
+            } else {
+              encoding = length;
+              length = undefined;
+            }
+            // legacy write(string, encoding, offset, length) - remove in v0.13
+          } else {
+            throw new Error(
+              "Buffer.write(string, encoding, offset[, length]) is no longer supported"
+            );
+          }
+
+          var remaining = this.length - offset;
+          if (length === undefined || length > remaining) length = remaining;
+
+          if ((string.length > 0 && (length < 0 || offset < 0)) || offset > this.length) {
+            throw new RangeError("Attempt to write outside buffer bounds");
+          }
+
+          if (!encoding) encoding = "utf8";
+
+          var loweredCase = false;
+          for (;;) {
+            switch (encoding) {
+              case "hex":
+                return hexWrite(this, string, offset, length);
+
+              case "utf8":
+              case "utf-8":
+                return utf8Write(this, string, offset, length);
+
+              case "ascii":
+                return asciiWrite(this, string, offset, length);
+
+              case "latin1":
+              case "binary":
+                return latin1Write(this, string, offset, length);
+
+              case "base64":
+                // Warning: maxLength not taken into account in base64Write
+                return base64Write(this, string, offset, length);
+
+              case "ucs2":
+              case "ucs-2":
+              case "utf16le":
+              case "utf-16le":
+                return ucs2Write(this, string, offset, length);
+
+              default:
+                if (loweredCase) throw new TypeError("Unknown encoding: " + encoding);
+                encoding = ("" + encoding).toLowerCase();
+                loweredCase = true;
+            }
+          }
+        };
+
+        Buffer.prototype.toJSON = function toJSON() {
+          return {
+            type: "Buffer",
+            data: Array.prototype.slice.call(this._arr || this, 0),
+          };
+        };
+
+        function base64Slice(buf, start, end) {
+          if (start === 0 && end === buf.length) {
+            return base64.fromByteArray(buf);
+          } else {
+            return base64.fromByteArray(buf.slice(start, end));
+          }
+        }
+
+        function utf8Slice(buf, start, end) {
+          end = Math.min(buf.length, end);
+          var res = [];
+
+          var i = start;
+          while (i < end) {
+            var firstByte = buf[i];
+            var codePoint = null;
+            var bytesPerSequence =
+              firstByte > 0xef ? 4 : firstByte > 0xdf ? 3 : firstByte > 0xbf ? 2 : 1;
+
+            if (i + bytesPerSequence <= end) {
+              var secondByte, thirdByte, fourthByte, tempCodePoint;
+
+              switch (bytesPerSequence) {
+                case 1:
+                  if (firstByte < 0x80) {
+                    codePoint = firstByte;
+                  }
+                  break;
+                case 2:
+                  secondByte = buf[i + 1];
+                  if ((secondByte & 0xc0) === 0x80) {
+                    tempCodePoint = ((firstByte & 0x1f) << 0x6) | (secondByte & 0x3f);
+                    if (tempCodePoint > 0x7f) {
+                      codePoint = tempCodePoint;
+                    }
+                  }
+                  break;
+                case 3:
+                  secondByte = buf[i + 1];
+                  thirdByte = buf[i + 2];
+                  if ((secondByte & 0xc0) === 0x80 && (thirdByte & 0xc0) === 0x80) {
+                    tempCodePoint =
+                      ((firstByte & 0xf) << 0xc) |
+                      ((secondByte & 0x3f) << 0x6) |
+                      (thirdByte & 0x3f);
+                    if (
+                      tempCodePoint > 0x7ff &&
+                      (tempCodePoint < 0xd800 || tempCodePoint > 0xdfff)
+                    ) {
+                      codePoint = tempCodePoint;
+                    }
+                  }
+                  break;
+                case 4:
+                  secondByte = buf[i + 1];
+                  thirdByte = buf[i + 2];
+                  fourthByte = buf[i + 3];
+                  if (
+                    (secondByte & 0xc0) === 0x80 &&
+                    (thirdByte & 0xc0) === 0x80 &&
+                    (fourthByte & 0xc0) === 0x80
+                  ) {
+                    tempCodePoint =
+                      ((firstByte & 0xf) << 0x12) |
+                      ((secondByte & 0x3f) << 0xc) |
+                      ((thirdByte & 0x3f) << 0x6) |
+                      (fourthByte & 0x3f);
+                    if (tempCodePoint > 0xffff && tempCodePoint < 0x110000) {
+                      codePoint = tempCodePoint;
+                    }
+                  }
+              }
+            }
+
+            if (codePoint === null) {
+              // we did not generate a valid codePoint so insert a
+              // replacement char (U+FFFD) and advance only 1 byte
+              codePoint = 0xfffd;
+              bytesPerSequence = 1;
+            } else if (codePoint > 0xffff) {
+              // encode to utf16 (surrogate pair dance)
+              codePoint -= 0x10000;
+              res.push(((codePoint >>> 10) & 0x3ff) | 0xd800);
+              codePoint = 0xdc00 | (codePoint & 0x3ff);
+            }
+
+            res.push(codePoint);
+            i += bytesPerSequence;
+          }
+
+          return decodeCodePointsArray(res);
+        }
+
+        // Based on http://stackoverflow.com/a/22747272/680742, the browser with
+        // the lowest limit is Chrome, with 0x10000 args.
+        // We go 1 magnitude less, for safety
+        var MAX_ARGUMENTS_LENGTH = 0x1000;
+
+        function decodeCodePointsArray(codePoints) {
+          var len = codePoints.length;
+          if (len <= MAX_ARGUMENTS_LENGTH) {
+            return String.fromCharCode.apply(String, codePoints); // avoid extra slice()
+          }
+
+          // Decode in chunks to avoid "call stack size exceeded".
+          var res = "";
+          var i = 0;
+          while (i < len) {
+            res += String.fromCharCode.apply(
+              String,
+              codePoints.slice(i, (i += MAX_ARGUMENTS_LENGTH))
+            );
+          }
+          return res;
+        }
+
+        function asciiSlice(buf, start, end) {
+          var ret = "";
+          end = Math.min(buf.length, end);
+
+          for (var i = start; i < end; ++i) {
+            ret += String.fromCharCode(buf[i] & 0x7f);
+          }
+          return ret;
+        }
+
+        function latin1Slice(buf, start, end) {
+          var ret = "";
+          end = Math.min(buf.length, end);
+
+          for (var i = start; i < end; ++i) {
+            ret += String.fromCharCode(buf[i]);
+          }
+          return ret;
+        }
+
+        function hexSlice(buf, start, end) {
+          var len = buf.length;
+
+          if (!start || start < 0) start = 0;
+          if (!end || end < 0 || end > len) end = len;
+
+          var out = "";
+          for (var i = start; i < end; ++i) {
+            out += toHex(buf[i]);
+          }
+          return out;
+        }
+
+        function utf16leSlice(buf, start, end) {
+          var bytes = buf.slice(start, end);
+          var res = "";
+          for (var i = 0; i < bytes.length; i += 2) {
+            res += String.fromCharCode(bytes[i] + bytes[i + 1] * 256);
+          }
+          return res;
+        }
+
+        Buffer.prototype.slice = function slice(start, end) {
+          var len = this.length;
+          start = ~~start;
+          end = end === undefined ? len : ~~end;
+
+          if (start < 0) {
+            start += len;
+            if (start < 0) start = 0;
+          } else if (start > len) {
+            start = len;
+          }
+
+          if (end < 0) {
+            end += len;
+            if (end < 0) end = 0;
+          } else if (end > len) {
+            end = len;
+          }
+
+          if (end < start) end = start;
+
+          var newBuf;
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            newBuf = this.subarray(start, end);
+            newBuf.__proto__ = Buffer.prototype;
+          } else {
+            var sliceLen = end - start;
+            newBuf = new Buffer(sliceLen, undefined);
+            for (var i = 0; i < sliceLen; ++i) {
+              newBuf[i] = this[i + start];
+            }
+          }
+
+          return newBuf;
+        };
+
+        /*
+         * Need to make sure that buffer isn't trying to write out of bounds.
+         */
+        function checkOffset(offset, ext, length) {
+          if (offset % 1 !== 0 || offset < 0) throw new RangeError("offset is not uint");
+          if (offset + ext > length) throw new RangeError("Trying to access beyond buffer length");
+        }
+
+        Buffer.prototype.readUIntLE = function readUIntLE(offset, byteLength, noAssert) {
+          offset = offset | 0;
+          byteLength = byteLength | 0;
+          if (!noAssert) checkOffset(offset, byteLength, this.length);
+
+          var val = this[offset];
+          var mul = 1;
+          var i = 0;
+          while (++i < byteLength && (mul *= 0x100)) {
+            val += this[offset + i] * mul;
+          }
+
+          return val;
+        };
+
+        Buffer.prototype.readUIntBE = function readUIntBE(offset, byteLength, noAssert) {
+          offset = offset | 0;
+          byteLength = byteLength | 0;
+          if (!noAssert) {
+            checkOffset(offset, byteLength, this.length);
+          }
+
+          var val = this[offset + --byteLength];
+          var mul = 1;
+          while (byteLength > 0 && (mul *= 0x100)) {
+            val += this[offset + --byteLength] * mul;
+          }
+
+          return val;
+        };
+
+        Buffer.prototype.readUInt8 = function readUInt8(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 1, this.length);
+          return this[offset];
+        };
+
+        Buffer.prototype.readUInt16LE = function readUInt16LE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 2, this.length);
+          return this[offset] | (this[offset + 1] << 8);
+        };
+
+        Buffer.prototype.readUInt16BE = function readUInt16BE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 2, this.length);
+          return (this[offset] << 8) | this[offset + 1];
+        };
+
+        Buffer.prototype.readUInt32LE = function readUInt32LE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 4, this.length);
+
+          return (
+            (this[offset] | (this[offset + 1] << 8) | (this[offset + 2] << 16)) +
+            this[offset + 3] * 0x1000000
+          );
+        };
+
+        Buffer.prototype.readUInt32BE = function readUInt32BE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 4, this.length);
+
+          return (
+            this[offset] * 0x1000000 +
+            ((this[offset + 1] << 16) | (this[offset + 2] << 8) | this[offset + 3])
+          );
+        };
+
+        Buffer.prototype.readIntLE = function readIntLE(offset, byteLength, noAssert) {
+          offset = offset | 0;
+          byteLength = byteLength | 0;
+          if (!noAssert) checkOffset(offset, byteLength, this.length);
+
+          var val = this[offset];
+          var mul = 1;
+          var i = 0;
+          while (++i < byteLength && (mul *= 0x100)) {
+            val += this[offset + i] * mul;
+          }
+          mul *= 0x80;
+
+          if (val >= mul) val -= Math.pow(2, 8 * byteLength);
+
+          return val;
+        };
+
+        Buffer.prototype.readIntBE = function readIntBE(offset, byteLength, noAssert) {
+          offset = offset | 0;
+          byteLength = byteLength | 0;
+          if (!noAssert) checkOffset(offset, byteLength, this.length);
+
+          var i = byteLength;
+          var mul = 1;
+          var val = this[offset + --i];
+          while (i > 0 && (mul *= 0x100)) {
+            val += this[offset + --i] * mul;
+          }
+          mul *= 0x80;
+
+          if (val >= mul) val -= Math.pow(2, 8 * byteLength);
+
+          return val;
+        };
+
+        Buffer.prototype.readInt8 = function readInt8(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 1, this.length);
+          if (!(this[offset] & 0x80)) return this[offset];
+          return (0xff - this[offset] + 1) * -1;
+        };
+
+        Buffer.prototype.readInt16LE = function readInt16LE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 2, this.length);
+          var val = this[offset] | (this[offset + 1] << 8);
+          return val & 0x8000 ? val | 0xffff0000 : val;
+        };
+
+        Buffer.prototype.readInt16BE = function readInt16BE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 2, this.length);
+          var val = this[offset + 1] | (this[offset] << 8);
+          return val & 0x8000 ? val | 0xffff0000 : val;
+        };
+
+        Buffer.prototype.readInt32LE = function readInt32LE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 4, this.length);
+
+          return (
+            this[offset] |
+            (this[offset + 1] << 8) |
+            (this[offset + 2] << 16) |
+            (this[offset + 3] << 24)
+          );
+        };
+
+        Buffer.prototype.readInt32BE = function readInt32BE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 4, this.length);
+
+          return (
+            (this[offset] << 24) |
+            (this[offset + 1] << 16) |
+            (this[offset + 2] << 8) |
+            this[offset + 3]
+          );
+        };
+
+        Buffer.prototype.readFloatLE = function readFloatLE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 4, this.length);
+          return ieee754.read(this, offset, true, 23, 4);
+        };
+
+        Buffer.prototype.readFloatBE = function readFloatBE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 4, this.length);
+          return ieee754.read(this, offset, false, 23, 4);
+        };
+
+        Buffer.prototype.readDoubleLE = function readDoubleLE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 8, this.length);
+          return ieee754.read(this, offset, true, 52, 8);
+        };
+
+        Buffer.prototype.readDoubleBE = function readDoubleBE(offset, noAssert) {
+          if (!noAssert) checkOffset(offset, 8, this.length);
+          return ieee754.read(this, offset, false, 52, 8);
+        };
+
+        function checkInt(buf, value, offset, ext, max, min) {
+          if (!Buffer.isBuffer(buf))
+            throw new TypeError('"buffer" argument must be a Buffer instance');
+          if (value > max || value < min) throw new RangeError('"value" argument is out of bounds');
+          if (offset + ext > buf.length) throw new RangeError("Index out of range");
+        }
+
+        Buffer.prototype.writeUIntLE = function writeUIntLE(value, offset, byteLength, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          byteLength = byteLength | 0;
+          if (!noAssert) {
+            var maxBytes = Math.pow(2, 8 * byteLength) - 1;
+            checkInt(this, value, offset, byteLength, maxBytes, 0);
+          }
+
+          var mul = 1;
+          var i = 0;
+          this[offset] = value & 0xff;
+          while (++i < byteLength && (mul *= 0x100)) {
+            this[offset + i] = (value / mul) & 0xff;
+          }
+
+          return offset + byteLength;
+        };
+
+        Buffer.prototype.writeUIntBE = function writeUIntBE(value, offset, byteLength, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          byteLength = byteLength | 0;
+          if (!noAssert) {
+            var maxBytes = Math.pow(2, 8 * byteLength) - 1;
+            checkInt(this, value, offset, byteLength, maxBytes, 0);
+          }
+
+          var i = byteLength - 1;
+          var mul = 1;
+          this[offset + i] = value & 0xff;
+          while (--i >= 0 && (mul *= 0x100)) {
+            this[offset + i] = (value / mul) & 0xff;
+          }
+
+          return offset + byteLength;
+        };
+
+        Buffer.prototype.writeUInt8 = function writeUInt8(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 1, 0xff, 0);
+          if (!Buffer.TYPED_ARRAY_SUPPORT) value = Math.floor(value);
+          this[offset] = value & 0xff;
+          return offset + 1;
+        };
+
+        function objectWriteUInt16(buf, value, offset, littleEndian) {
+          if (value < 0) value = 0xffff + value + 1;
+          for (var i = 0, j = Math.min(buf.length - offset, 2); i < j; ++i) {
+            buf[offset + i] =
+              (value & (0xff << (8 * (littleEndian ? i : 1 - i)))) >>>
+              ((littleEndian ? i : 1 - i) * 8);
+          }
+        }
+
+        Buffer.prototype.writeUInt16LE = function writeUInt16LE(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 2, 0xffff, 0);
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            this[offset] = value & 0xff;
+            this[offset + 1] = value >>> 8;
+          } else {
+            objectWriteUInt16(this, value, offset, true);
+          }
+          return offset + 2;
+        };
+
+        Buffer.prototype.writeUInt16BE = function writeUInt16BE(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 2, 0xffff, 0);
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            this[offset] = value >>> 8;
+            this[offset + 1] = value & 0xff;
+          } else {
+            objectWriteUInt16(this, value, offset, false);
+          }
+          return offset + 2;
+        };
+
+        function objectWriteUInt32(buf, value, offset, littleEndian) {
+          if (value < 0) value = 0xffffffff + value + 1;
+          for (var i = 0, j = Math.min(buf.length - offset, 4); i < j; ++i) {
+            buf[offset + i] = (value >>> ((littleEndian ? i : 3 - i) * 8)) & 0xff;
+          }
+        }
+
+        Buffer.prototype.writeUInt32LE = function writeUInt32LE(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 4, 0xffffffff, 0);
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            this[offset + 3] = value >>> 24;
+            this[offset + 2] = value >>> 16;
+            this[offset + 1] = value >>> 8;
+            this[offset] = value & 0xff;
+          } else {
+            objectWriteUInt32(this, value, offset, true);
+          }
+          return offset + 4;
+        };
+
+        Buffer.prototype.writeUInt32BE = function writeUInt32BE(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 4, 0xffffffff, 0);
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            this[offset] = value >>> 24;
+            this[offset + 1] = value >>> 16;
+            this[offset + 2] = value >>> 8;
+            this[offset + 3] = value & 0xff;
+          } else {
+            objectWriteUInt32(this, value, offset, false);
+          }
+          return offset + 4;
+        };
+
+        Buffer.prototype.writeIntLE = function writeIntLE(value, offset, byteLength, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) {
+            var limit = Math.pow(2, 8 * byteLength - 1);
+
+            checkInt(this, value, offset, byteLength, limit - 1, -limit);
+          }
+
+          var i = 0;
+          var mul = 1;
+          var sub = 0;
+          this[offset] = value & 0xff;
+          while (++i < byteLength && (mul *= 0x100)) {
+            if (value < 0 && sub === 0 && this[offset + i - 1] !== 0) {
+              sub = 1;
+            }
+            this[offset + i] = (((value / mul) >> 0) - sub) & 0xff;
+          }
+
+          return offset + byteLength;
+        };
+
+        Buffer.prototype.writeIntBE = function writeIntBE(value, offset, byteLength, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) {
+            var limit = Math.pow(2, 8 * byteLength - 1);
+
+            checkInt(this, value, offset, byteLength, limit - 1, -limit);
+          }
+
+          var i = byteLength - 1;
+          var mul = 1;
+          var sub = 0;
+          this[offset + i] = value & 0xff;
+          while (--i >= 0 && (mul *= 0x100)) {
+            if (value < 0 && sub === 0 && this[offset + i + 1] !== 0) {
+              sub = 1;
+            }
+            this[offset + i] = (((value / mul) >> 0) - sub) & 0xff;
+          }
+
+          return offset + byteLength;
+        };
+
+        Buffer.prototype.writeInt8 = function writeInt8(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 1, 0x7f, -0x80);
+          if (!Buffer.TYPED_ARRAY_SUPPORT) value = Math.floor(value);
+          if (value < 0) value = 0xff + value + 1;
+          this[offset] = value & 0xff;
+          return offset + 1;
+        };
+
+        Buffer.prototype.writeInt16LE = function writeInt16LE(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 2, 0x7fff, -0x8000);
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            this[offset] = value & 0xff;
+            this[offset + 1] = value >>> 8;
+          } else {
+            objectWriteUInt16(this, value, offset, true);
+          }
+          return offset + 2;
+        };
+
+        Buffer.prototype.writeInt16BE = function writeInt16BE(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 2, 0x7fff, -0x8000);
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            this[offset] = value >>> 8;
+            this[offset + 1] = value & 0xff;
+          } else {
+            objectWriteUInt16(this, value, offset, false);
+          }
+          return offset + 2;
+        };
+
+        Buffer.prototype.writeInt32LE = function writeInt32LE(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 4, 0x7fffffff, -0x80000000);
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            this[offset] = value & 0xff;
+            this[offset + 1] = value >>> 8;
+            this[offset + 2] = value >>> 16;
+            this[offset + 3] = value >>> 24;
+          } else {
+            objectWriteUInt32(this, value, offset, true);
+          }
+          return offset + 4;
+        };
+
+        Buffer.prototype.writeInt32BE = function writeInt32BE(value, offset, noAssert) {
+          value = +value;
+          offset = offset | 0;
+          if (!noAssert) checkInt(this, value, offset, 4, 0x7fffffff, -0x80000000);
+          if (value < 0) value = 0xffffffff + value + 1;
+          if (Buffer.TYPED_ARRAY_SUPPORT) {
+            this[offset] = value >>> 24;
+            this[offset + 1] = value >>> 16;
+            this[offset + 2] = value >>> 8;
+            this[offset + 3] = value & 0xff;
+          } else {
+            objectWriteUInt32(this, value, offset, false);
+          }
+          return offset + 4;
+        };
+
+        function checkIEEE754(buf, value, offset, ext, max, min) {
+          if (offset + ext > buf.length) throw new RangeError("Index out of range");
+          if (offset < 0) throw new RangeError("Index out of range");
+        }
+
+        function writeFloat(buf, value, offset, littleEndian, noAssert) {
+          if (!noAssert) {
+            checkIEEE754(buf, value, offset, 4, 3.4028234663852886e38, -3.4028234663852886e38);
+          }
+          ieee754.write(buf, value, offset, littleEndian, 23, 4);
+          return offset + 4;
+        }
+
+        Buffer.prototype.writeFloatLE = function writeFloatLE(value, offset, noAssert) {
+          return writeFloat(this, value, offset, true, noAssert);
+        };
+
+        Buffer.prototype.writeFloatBE = function writeFloatBE(value, offset, noAssert) {
+          return writeFloat(this, value, offset, false, noAssert);
+        };
+
+        function writeDouble(buf, value, offset, littleEndian, noAssert) {
+          if (!noAssert) {
+            checkIEEE754(buf, value, offset, 8, 1.7976931348623157e308, -1.7976931348623157e308);
+          }
+          ieee754.write(buf, value, offset, littleEndian, 52, 8);
+          return offset + 8;
+        }
+
+        Buffer.prototype.writeDoubleLE = function writeDoubleLE(value, offset, noAssert) {
+          return writeDouble(this, value, offset, true, noAssert);
+        };
+
+        Buffer.prototype.writeDoubleBE = function writeDoubleBE(value, offset, noAssert) {
+          return writeDouble(this, value, offset, false, noAssert);
+        };
+
+        // copy(targetBuffer, targetStart=0, sourceStart=0, sourceEnd=buffer.length)
+        Buffer.prototype.copy = function copy(target, targetStart, start, end) {
+          if (!start) start = 0;
+          if (!end && end !== 0) end = this.length;
+          if (targetStart >= target.length) targetStart = target.length;
+          if (!targetStart) targetStart = 0;
+          if (end > 0 && end < start) end = start;
+
+          // Copy 0 bytes; we're done
+          if (end === start) return 0;
+          if (target.length === 0 || this.length === 0) return 0;
+
+          // Fatal error conditions
+          if (targetStart < 0) {
+            throw new RangeError("targetStart out of bounds");
+          }
+          if (start < 0 || start >= this.length) throw new RangeError("sourceStart out of bounds");
+          if (end < 0) throw new RangeError("sourceEnd out of bounds");
+
+          // Are we oob?
+          if (end > this.length) end = this.length;
+          if (target.length - targetStart < end - start) {
+            end = target.length - targetStart + start;
+          }
+
+          var len = end - start;
+          var i;
+
+          if (this === target && start < targetStart && targetStart < end) {
+            // descending copy from end
+            for (i = len - 1; i >= 0; --i) {
+              target[i + targetStart] = this[i + start];
+            }
+          } else if (len < 1000 || !Buffer.TYPED_ARRAY_SUPPORT) {
+            // ascending copy from start
+            for (i = 0; i < len; ++i) {
+              target[i + targetStart] = this[i + start];
+            }
+          } else {
+            Uint8Array.prototype.set.call(target, this.subarray(start, start + len), targetStart);
+          }
+
+          return len;
+        };
+
+        // Usage:
+        //    buffer.fill(number[, offset[, end]])
+        //    buffer.fill(buffer[, offset[, end]])
+        //    buffer.fill(string[, offset[, end]][, encoding])
+        Buffer.prototype.fill = function fill(val, start, end, encoding) {
+          // Handle string cases:
+          if (typeof val === "string") {
+            if (typeof start === "string") {
+              encoding = start;
+              start = 0;
+              end = this.length;
+            } else if (typeof end === "string") {
+              encoding = end;
+              end = this.length;
+            }
+            if (val.length === 1) {
+              var code = val.charCodeAt(0);
+              if (code < 256) {
+                val = code;
+              }
+            }
+            if (encoding !== undefined && typeof encoding !== "string") {
+              throw new TypeError("encoding must be a string");
+            }
+            if (typeof encoding === "string" && !Buffer.isEncoding(encoding)) {
+              throw new TypeError("Unknown encoding: " + encoding);
+            }
+          } else if (typeof val === "number") {
+            val = val & 255;
+          }
+
+          // Invalid ranges are not set to a default, so can range check early.
+          if (start < 0 || this.length < start || this.length < end) {
+            throw new RangeError("Out of range index");
+          }
+
+          if (end <= start) {
+            return this;
+          }
+
+          start = start >>> 0;
+          end = end === undefined ? this.length : end >>> 0;
+
+          if (!val) val = 0;
+
+          var i;
+          if (typeof val === "number") {
+            for (i = start; i < end; ++i) {
+              this[i] = val;
+            }
+          } else {
+            var bytes = Buffer.isBuffer(val)
+              ? val
+              : utf8ToBytes(new Buffer(val, encoding).toString());
+            var len = bytes.length;
+            for (i = 0; i < end - start; ++i) {
+              this[i + start] = bytes[i % len];
+            }
+          }
+
+          return this;
+        };
+
+        // HELPER FUNCTIONS
+        // ================
+
+        var INVALID_BASE64_RE = /[^+\/0-9A-Za-z-_]/g;
+
+        function base64clean(str) {
+          // Node strips out invalid characters like \n and \t from the string, base64-js does not
+          str = stringtrim(str).replace(INVALID_BASE64_RE, "");
+          // Node converts strings with length < 2 to ''
+          if (str.length < 2) return "";
+          // Node allows for non-padded base64 strings (missing trailing ===), base64-js does not
+          while (str.length % 4 !== 0) {
+            str = str + "=";
+          }
+          return str;
+        }
+
+        function stringtrim(str) {
+          if (str.trim) return str.trim();
+          return str.replace(/^\s+|\s+$/g, "");
+        }
+
+        function toHex(n) {
+          if (n < 16) return "0" + n.toString(16);
+          return n.toString(16);
+        }
+
+        function utf8ToBytes(string, units) {
+          units = units || Infinity;
+          var codePoint;
+          var length = string.length;
+          var leadSurrogate = null;
+          var bytes = [];
+
+          for (var i = 0; i < length; ++i) {
+            codePoint = string.charCodeAt(i);
+
+            // is surrogate component
+            if (codePoint > 0xd7ff && codePoint < 0xe000) {
+              // last char was a lead
+              if (!leadSurrogate) {
+                // no lead yet
+                if (codePoint > 0xdbff) {
+                  // unexpected trail
+                  if ((units -= 3) > -1) bytes.push(0xef, 0xbf, 0xbd);
+                  continue;
+                } else if (i + 1 === length) {
+                  // unpaired lead
+                  if ((units -= 3) > -1) bytes.push(0xef, 0xbf, 0xbd);
+                  continue;
+                }
+
+                // valid lead
+                leadSurrogate = codePoint;
+
+                continue;
+              }
+
+              // 2 leads in a row
+              if (codePoint < 0xdc00) {
+                if ((units -= 3) > -1) bytes.push(0xef, 0xbf, 0xbd);
+                leadSurrogate = codePoint;
+                continue;
+              }
+
+              // valid surrogate pair
+              codePoint = (((leadSurrogate - 0xd800) << 10) | (codePoint - 0xdc00)) + 0x10000;
+            } else if (leadSurrogate) {
+              // valid bmp char, but last char was a lead
+              if ((units -= 3) > -1) bytes.push(0xef, 0xbf, 0xbd);
+            }
+
+            leadSurrogate = null;
+
+            // encode utf8
+            if (codePoint < 0x80) {
+              if ((units -= 1) < 0) break;
+              bytes.push(codePoint);
+            } else if (codePoint < 0x800) {
+              if ((units -= 2) < 0) break;
+              bytes.push((codePoint >> 0x6) | 0xc0, (codePoint & 0x3f) | 0x80);
+            } else if (codePoint < 0x10000) {
+              if ((units -= 3) < 0) break;
+              bytes.push(
+                (codePoint >> 0xc) | 0xe0,
+                ((codePoint >> 0x6) & 0x3f) | 0x80,
+                (codePoint & 0x3f) | 0x80
+              );
+            } else if (codePoint < 0x110000) {
+              if ((units -= 4) < 0) break;
+              bytes.push(
+                (codePoint >> 0x12) | 0xf0,
+                ((codePoint >> 0xc) & 0x3f) | 0x80,
+                ((codePoint >> 0x6) & 0x3f) | 0x80,
+                (codePoint & 0x3f) | 0x80
+              );
+            } else {
+              throw new Error("Invalid code point");
+            }
+          }
+
+          return bytes;
+        }
+
+        function asciiToBytes(str) {
+          var byteArray = [];
+          for (var i = 0; i < str.length; ++i) {
+            // Node's code seems to be doing this and not & 0x7F..
+            byteArray.push(str.charCodeAt(i) & 0xff);
+          }
+          return byteArray;
+        }
+
+        function utf16leToBytes(str, units) {
+          var c, hi, lo;
+          var byteArray = [];
+          for (var i = 0; i < str.length; ++i) {
+            if ((units -= 2) < 0) break;
+
+            c = str.charCodeAt(i);
+            hi = c >> 8;
+            lo = c % 256;
+            byteArray.push(lo);
+            byteArray.push(hi);
+          }
+
+          return byteArray;
+        }
+
+        function base64ToBytes(str) {
+          return base64.toByteArray(base64clean(str));
+        }
+
+        function blitBuffer(src, dst, offset, length) {
+          for (var i = 0; i < length; ++i) {
+            if (i + offset >= dst.length || i >= src.length) break;
+            dst[i + offset] = src[i];
+          }
+          return i;
+        }
+
+        function isnan(val) {
+          return val !== val; // eslint-disable-line no-self-compare
+        }
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(27)));
+
+      /***/
+    },
+    /* 40 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (setImmediate) {
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+          return nextFrame;
+        });
+        /**
+         * @license
+         * Copyright 2017 Google Inc. All Rights Reserved.
+         * Licensed under the Apache License, Version 2.0 (the "License");
+         * you may not use this file except in compliance with the License.
+         * You may obtain a copy of the License at
+         *
+         * http://www.apache.org/licenses/LICENSE-2.0
+         *
+         * Unless required by applicable law or agreed to in writing, software
+         * distributed under the License is distributed on an "AS IS" BASIS,
+         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+         * See the License for the specific language governing permissions and
+         * limitations under the License.
+         * =============================================================================
+         */
+        const delayCallback = (() => {
+          if (typeof requestAnimationFrame !== "undefined") {
+            return requestAnimationFrame;
+          } else if (typeof setImmediate !== "undefined") {
+            return setImmediate;
+          }
+          return (f) => f(); // no delays
+        })();
+        /**
+         * Returns a promise that resolve when a requestAnimationFrame has completed.
+         *
+         * On Node.js this uses setImmediate instead of requestAnimationFrame.
+         *
+         * This is simply a sugar method so that users can do the following:
+         * `await tf.nextFrame();`
+         */
+        /** @doc {heading: 'Performance', subheading: 'Timing'} */
+        function nextFrame() {
+          return new Promise((resolve) => delayCallback(() => resolve()));
+        }
+
+        //# sourceMappingURL=browser_util.js.map
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(76).setImmediate));
+
+      /***/
+    },
+    /* 41 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "Add",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "AddV2",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "AddN",
+          category: "arithmetic",
+          inputs: [{ start: 0, end: 0, name: "tensors", type: "tensors" }],
+        },
+        {
+          tfOpName: "BiasAdd",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Sub",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "RealDiv",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Div",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "DivNoNan",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "FloorDiv",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Mul",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Maximum",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+        },
+        {
+          tfOpName: "Minimum",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+        },
+        {
+          tfOpName: "Pow",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "SquaredDifference",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Mod",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "FloorMod",
+          category: "arithmetic",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+      ];
+      //# sourceMappingURL=arithmetic.js.map
+
+      /***/
+    },
+    /* 42 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "Abs",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Acos",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Asin",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Atan",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Atan2",
+          category: "basic_math",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "y", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Ceil",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "ClipByValue",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "clip_value_min", name: "clipValueMin", type: "number" },
+            { tfName: "clip_value_max", name: "clipValueMax", type: "number" },
+          ],
+        },
+        {
+          tfOpName: "Complex",
+          category: "basic_math",
+          inputs: [
+            { start: 0, name: "real", type: "tensor" },
+            { start: 1, name: "imag", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "ComplexAbs",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Cos",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Cosh",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Elu",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Exp",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Floor",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Log",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Imag",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+            {
+              tfName: "Tout",
+              name: "outputType",
+              type: "dtype",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "Neg",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Real",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+            {
+              tfName: "Tout",
+              name: "outputType",
+              type: "dtype",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "Prelu",
+          category: "basic_math",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "alpha", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Relu",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Relu6",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+            {
+              tfName: "clipValueMin",
+              name: "clipValueMin",
+              type: "number",
+              defaultValue: 0,
+            },
+            {
+              tfName: "clipValueMax",
+              name: "clipValueMax",
+              type: "number",
+              defaultValue: 6,
+            },
+          ],
+        },
+        {
+          tfOpName: "Selu",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Sigmoid",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Sin",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Sinh",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Sqrt",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Rsqrt",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Square",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Tan",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Tanh",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Sign",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Round",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Expm1",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Log1p",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Reciprocal",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Softplus",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Asinh",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Acosh",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Atanh",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Erf",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Prod",
+          category: "basic_math",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axes", type: "number[]" },
+          ],
+          attrs: [
+            {
+              tfName: "keep_dims",
+              name: "keepDims",
+              type: "bool",
+              notSupported: true,
+            },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "LeakyRelu",
+          category: "basic_math",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            {
+              tfName: "alpha",
+              name: "alpha",
+              type: "number",
+              defaultValue: 0.2,
+            },
+            {
+              tfName: "T",
+              name: "dtype",
+              type: "dtype",
+              notSupported: true,
+            },
+          ],
+        },
+      ];
+      //# sourceMappingURL=basic_math.js.map
+
+      /***/
+    },
+    /* 43 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "LoopCond",
+          category: "control",
+          inputs: [{ start: 0, name: "pred", type: "tensor" }],
+        },
+        {
+          tfOpName: "Switch",
+          category: "control",
+          inputs: [
+            { start: 0, name: "data", type: "tensor" },
+            { start: 1, name: "pred", type: "tensor" },
+          ],
+        },
+        {
+          tfOpName: "Merge",
+          category: "control",
+          inputs: [{ start: 0, end: 0, name: "tensors", type: "tensors" }],
+        },
+        {
+          tfOpName: "Enter",
+          category: "control",
+          inputs: [{ start: 0, name: "tensor", type: "tensor" }],
+          attrs: [
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+            { tfName: "frame_name", name: "frameName", type: "string" },
+            { tfName: "is_constant", name: "isConstant", type: "bool" },
+          ],
+        },
+        {
+          tfOpName: "Exit",
+          category: "control",
+          inputs: [{ start: 0, name: "tensor", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "NextIteration",
+          category: "control",
+          inputs: [{ start: 0, name: "tensor", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "TensorArrayV3",
+          category: "control",
+          inputs: [{ start: 0, name: "size", type: "number" }],
+          attrs: [
+            { tfName: "dtype", name: "dtype", type: "dtype" },
+            { tfName: "element_shape", name: "elementShape", type: "shape" },
+            { tfName: "dynamic_size", name: "dynamicSize", type: "bool" },
+            { tfName: "clear_after_read", name: "clearAfterRead", type: "bool" },
+            {
+              tfName: "identical_element_shapes",
+              name: "identicalElementShapes",
+              type: "bool",
+            },
+            { tfName: "tensor_array_name", name: "name", type: "string" },
+          ],
+        },
+        {
+          tfOpName: "TensorArrayWriteV3",
+          category: "control",
+          inputs: [
+            { start: 0, name: "tensorArrayId", type: "number" },
+            { start: 1, name: "index", type: "number" },
+            { start: 2, name: "tensor", type: "tensor" },
+            { start: 3, name: "flowIn", type: "number" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "TensorArrayReadV3",
+          category: "control",
+          inputs: [
+            { start: 0, name: "tensorArrayId", type: "number" },
+            { start: 1, name: "index", type: "number" },
+            { start: 2, name: "flowIn", type: "number" },
+          ],
+          attrs: [
+            {
+              tfName: "dtype",
+              name: "dtype",
+              type: "dtype",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "TensorArrayGatherV3",
+          category: "control",
+          inputs: [
+            { start: 0, name: "tensorArrayId", type: "number" },
+            { start: 1, name: "indices", type: "number[]" },
+            { start: 2, name: "flowIn", type: "number" },
+          ],
+          attrs: [
+            { tfName: "dtype", name: "dtype", type: "dtype" },
+            { tfName: "element_shape", name: "elementShape", type: "shape" },
+          ],
+        },
+        {
+          tfOpName: "TensorArrayScatterV3",
+          category: "control",
+          inputs: [
+            { start: 0, name: "tensorArrayId", type: "number" },
+            { start: 1, name: "indices", type: "number[]" },
+            { start: 2, name: "tensor", type: "tensor" },
+            { start: 3, name: "flowIn", type: "number" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
+        },
+        {
+          tfOpName: "TensorArrayConcatV3",
+          category: "control",
+          inputs: [
+            { start: 0, name: "tensorArrayId", type: "number" },
+            { start: 1, name: "flowIn", type: "number" },
+          ],
+          attrs: [
+            { tfName: "dtype", name: "dtype", type: "dtype" },
+            {
+              tfName: "element_shape_except0",
+              name: "elementShapeExcept0",
+              type: "shape",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "TensorArraySplitV3",
+          category: "control",
+          inputs: [
+            { start: 0, name: "tensorArrayId", type: "number" },
+            { start: 1, name: "tensor", type: "tensor" },
+            { start: 2, name: "lengths", type: "number[]" },
+            { start: 3, name: "flowIn", type: "number" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
+        },
+        {
+          tfOpName: "TensorArraySizeV3",
+          category: "control",
+          inputs: [
+            { start: 0, name: "tensorArrayId", type: "number" },
+            { start: 1, name: "flowIn", type: "number" },
+          ],
+        },
+        {
+          tfOpName: "TensorArrayCloseV3",
+          category: "control",
+          inputs: [{ start: 0, name: "tensorArrayId", type: "number" }],
+        },
+        {
+          tfOpName: "StatelessIf",
+          category: "control",
+          inputs: [
+            { start: 0, name: "cond", type: "tensor" },
+            { start: 1, end: 0, name: "args", type: "tensors" },
+          ],
+          attrs: [
+            { tfName: "then_branch", name: "thenBranch", type: "func" },
+            { tfName: "else_branch", name: "elseBranch", type: "func" },
+          ],
+        },
+        {
+          tfOpName: "If",
+          category: "control",
+          inputs: [
+            { start: 0, name: "cond", type: "tensor" },
+            { start: 1, end: 0, name: "args", type: "tensors" },
+          ],
+          attrs: [
+            { tfName: "then_branch", name: "thenBranch", type: "func" },
+            { tfName: "else_branch", name: "elseBranch", type: "func" },
+          ],
+        },
+        {
+          tfOpName: "StatelessWhile",
+          category: "control",
+          inputs: [{ start: 0, end: 0, name: "args", type: "tensors" }],
+          attrs: [
+            { tfName: "cond", name: "cond", type: "func" },
+            { tfName: "body", name: "body", type: "func" },
+          ],
+        },
+        {
+          tfOpName: "While",
+          category: "control",
+          inputs: [{ start: 0, end: 0, name: "args", type: "tensors" }],
+          attrs: [
+            { tfName: "cond", name: "cond", type: "func" },
+            { tfName: "body", name: "body", type: "func" },
+          ],
+        },
+      ];
+      //# sourceMappingURL=control.js.map
+
+      /***/
+    },
+    /* 44 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "AvgPool",
+          category: "convolution",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              notSupported: true,
+            },
+            { tfName: "ksize", name: "kernelSize", type: "number[]" },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "MaxPool",
+          category: "convolution",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              notSupported: true,
+            },
+            { tfName: "ksize", name: "kernelSize", type: "number[]" },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "MaxPoolWithArgmax",
+          category: "convolution",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            { tfName: "ksize", name: "kernelSize", type: "number[]" },
+            {
+              tfName: "include_batch_in_index",
+              name: "includeBatchInIndex",
+              type: "bool",
+            },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "AvgPool3D",
+          category: "convolution",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              notSupported: true,
+            },
+            { tfName: "ksize", name: "kernelSize", type: "number[]" },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "MaxPool3D",
+          category: "convolution",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              notSupported: true,
+            },
+            { tfName: "ksize", name: "kernelSize", type: "number[]" },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "Conv1D",
+          category: "convolution",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "filter", type: "tensor" },
+          ],
+          attrs: [
+            { tfName: "stride", name: "stride", type: "number" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              defaultValue: "NWC",
+            },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+            {
+              tfName: "dilation",
+              name: "dilation",
+              type: "number",
+              defaultValue: 1,
+            },
+          ],
+        },
+        {
+          tfOpName: "Conv2D",
+          category: "convolution",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "filter", type: "tensor" },
+          ],
+          attrs: [
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            { tfName: "useCudnnOnGpu", name: "useCudnnOnGpu", type: "bool" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              defaultValue: "NHWC",
+            },
+            {
+              tfName: "explicit_paddings",
+              name: "explicitPaddings",
+              type: "number[]",
+              defaultValue: [],
+            },
+            { tfName: "dilations", name: "dilations", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "_FusedConv2D",
+          category: "convolution",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "filter", type: "tensor" },
+            { start: 2, end: 0, name: "args", type: "tensors" },
+          ],
+          attrs: [
+            { tfName: "num_args", name: "numArgs", type: "number" },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "explicit_paddings",
+              name: "explicitPaddings",
+              type: "number[]",
+              defaultValue: [],
+            },
+            {
+              tfName: "use_cudnn_on_gpu",
+              name: "useCudnnOnGpu",
+              type: "bool",
+              defaultValue: true,
+            },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              defaultValue: "NHWC",
+            },
+            {
+              tfName: "dilations",
+              name: "dilations",
+              type: "number[]",
+              defaultValue: [1, 1, 1, 1],
+            },
+            {
+              tfName: "fused_ops",
+              name: "fusedOps",
+              type: "string[]",
+              defaultValue: [],
+            },
+            {
+              tfName: "epsilon",
+              name: "epsilon",
+              type: "number",
+              defaultValue: 0.0001,
+            },
+          ],
+        },
+        {
+          tfOpName: "Conv2DBackpropInput",
+          category: "convolution",
+          inputs: [
+            { start: 2, name: "x", type: "tensor" },
+            { start: 1, name: "filter", type: "tensor" },
+            { start: 0, name: "outputShape", type: "number[]" },
+          ],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              notSupported: true,
+            },
+            {
+              tfName: "explicit_paddings",
+              name: "explicitPaddings",
+              type: "number[]",
+              defaultValue: [],
+            },
+          ],
+        },
+        {
+          tfOpName: "DepthwiseConv2d",
+          category: "convolution",
+          inputs: [
+            { start: 0, name: "input", type: "tensor" },
+            { start: 1, name: "filter", type: "tensor" },
+          ],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              defaultValue: "NHWC",
+            },
+            {
+              tfName: "explicit_paddings",
+              name: "explicitPaddings",
+              type: "number[]",
+              defaultValue: [],
+            },
+            { tfName: "dilations", name: "dilations", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "DepthwiseConv2dNative",
+          category: "convolution",
+          inputs: [
+            { start: 0, name: "input", type: "tensor" },
+            { start: 1, name: "filter", type: "tensor" },
+          ],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              defaultValue: "NHWC",
+            },
+            {
+              tfName: "explicit_paddings",
+              name: "explicitPaddings",
+              type: "number[]",
+              defaultValue: [],
+            },
+            { tfName: "dilations", name: "dilations", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "FusedDepthwiseConv2dNative",
+          category: "convolution",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "filter", type: "tensor" },
+            { start: 2, end: 0, name: "args", type: "tensors" },
+          ],
+          attrs: [
+            { tfName: "num_args", name: "numArgs", type: "number" },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              defaultValue: "NHWC",
+            },
+            {
+              tfName: "dilations",
+              name: "dilations",
+              type: "number[]",
+              defaultValue: [1, 1, 1, 1],
+            },
+            {
+              tfName: "fused_ops",
+              name: "fusedOps",
+              type: "string[]",
+              defaultValue: [],
+            },
+          ],
+        },
+        {
+          tfOpName: "Conv3D",
+          category: "convolution",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "filter", type: "tensor" },
+          ],
+          attrs: [
+            { tfName: "strides", name: "strides", type: "number[]" },
+            { tfName: "padding", name: "pad", type: "string" },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              defaultValue: "NHWC",
+            },
+            { tfName: "dilations", name: "dilations", type: "number[]" },
+          ],
+        },
+      ];
+      //# sourceMappingURL=convolution.js.map
+
+      /***/
+    },
+    /* 45 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "Fill",
+          category: "creation",
+          inputs: [
+            { start: 0, name: "shape", type: "number[]" },
+            { start: 1, name: "value", type: "number" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
+        },
+        {
+          tfOpName: "LinSpace",
+          category: "creation",
+          inputs: [
+            { start: 0, name: "start", type: "number" },
+            { start: 1, name: "stop", type: "number" },
+            { start: 2, name: "num", type: "number" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "OneHot",
+          category: "creation",
+          inputs: [
+            { start: 0, name: "indices", type: "tensor" },
+            { start: 1, name: "depth", type: "number" },
+            { start: 2, name: "onValue", type: "number", defaultValue: 1 },
+            { start: 3, name: "offValue", type: "number", defaultValue: 0 },
+          ],
+          attrs: [
+            {
+              tfName: "axis",
+              name: "axis",
+              type: "number",
+              notSupported: true,
+            },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "Ones",
+          category: "creation",
+          inputs: [{ start: 0, name: "shape", type: "number[]" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
+        },
+        {
+          tfOpName: "OnesLike",
+          category: "creation",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "dtype", name: "dtype", type: "dtype" }],
+        },
+        {
+          tfOpName: "RandomUniform",
+          category: "creation",
+          inputs: [{ start: 0, name: "shape", type: "number[]" }],
+          attrs: [
+            {
+              tfName: "minval",
+              name: "minval",
+              type: "number",
+              defaultValue: 0,
+            },
+            {
+              tfName: "maxval",
+              name: "maxval",
+              type: "number",
+              defaultValue: 1,
+            },
+            { tfName: "dtype", name: "dtype", type: "dtype" },
+            { tfName: "seed", name: "seed", type: "number", defaultValue: 0 },
+            {
+              tfName: "seed2",
+              name: "seed2",
+              type: "number",
+              defaultValue: 0,
+              notSupported: true,
+            },
+            { tfName: "T", name: "T", type: "number", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "Range",
+          category: "creation",
+          inputs: [
+            { start: 0, name: "start", type: "number" },
+            { start: 1, name: "stop", type: "number" },
+            { start: 2, name: "step", type: "number", defaultValue: 0 },
+          ],
+          attrs: [{ tfName: "Tidx", name: "dtype", type: "dtype" }],
+        },
+        {
+          tfOpName: "TruncatedNormal",
+          category: "creation",
+          inputs: [{ start: 0, name: "shape", type: "number[]" }],
+          attrs: [
+            {
+              tfName: "means",
+              name: "mean",
+              type: "number",
+              defaultValue: 0.0,
+            },
+            {
+              tfName: "stddev",
+              name: "stdDev",
+              type: "number",
+              defaultValue: 1.0,
+            },
+            { tfName: "seed", name: "seed", type: "number" },
+            {
+              tfName: "seed2",
+              name: "seed2",
+              type: "number",
+              defaultValue: 0,
+              notSupported: true,
+            },
+            { tfName: "dtype", name: "dtype", type: "dtype" },
+            { tfName: "T", name: "T", type: "number", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "Zeros",
+          category: "creation",
+          inputs: [{ start: 0, name: "shape", type: "number[]" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
+        },
+        {
+          tfOpName: "ZerosLike",
+          category: "creation",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype" }],
+        },
+        {
+          tfOpName: "Multinomial",
+          category: "creation",
+          inputs: [
+            { start: 0, name: "logits", type: "tensor" },
+            { start: 1, name: "numSamples", type: "number" },
+          ],
+          attrs: [
+            { tfName: "seed", name: "seed", type: "number" },
+            { tfName: "seed2", name: "seed2", type: "number" },
+            { tfName: "T", name: "dtype", type: "dtype" },
+            { tfName: "output_dtype", name: "output_dtype", type: "dtype" },
+          ],
+        },
+      ];
+      //# sourceMappingURL=creation.js.map
+
+      /***/
+    },
+    /* 46 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "NonMaxSuppressionV2",
+          category: "dynamic",
+          inputs: [
+            { start: 0, name: "boxes", type: "tensor" },
+            { start: 1, name: "scores", type: "tensor" },
+            { start: 2, name: "maxOutputSize", type: "number" },
+            { start: 3, name: "iouThreshold", type: "number" },
+          ],
+        },
+        {
+          tfOpName: "NonMaxSuppressionV3",
+          category: "dynamic",
+          inputs: [
+            { start: 0, name: "boxes", type: "tensor" },
+            { start: 1, name: "scores", type: "tensor" },
+            { start: 2, name: "maxOutputSize", type: "number" },
+            { start: 3, name: "iouThreshold", type: "number" },
+            { start: 4, name: "scoreThreshold", type: "number" },
+          ],
+        },
+        {
+          tfOpName: "NonMaxSuppressionV5",
+          category: "dynamic",
+          inputs: [
+            { start: 0, name: "boxes", type: "tensor" },
+            { start: 1, name: "scores", type: "tensor" },
+            { start: 2, name: "maxOutputSize", type: "number" },
+            { start: 3, name: "iouThreshold", type: "number" },
+            { start: 4, name: "scoreThreshold", type: "number" },
+            { start: 5, name: "softNmsSigma", type: "number" },
+          ],
+        },
+        {
+          tfOpName: "Where",
+          category: "dynamic",
+          inputs: [{ start: 0, name: "condition", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "ListDiff",
+          category: "dynamic",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "y", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "T",
+              name: "dtype",
+              type: "dtype",
+              notSupported: true,
+            },
+          ],
+        },
+      ];
+      //# sourceMappingURL=dynamic.js.map
+
+      /***/
+    },
+    /* 47 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "TopKV2",
+          category: "evaluation",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "k", type: "number" },
+          ],
+          attrs: [{ tfName: "sorted", name: "sorted", type: "bool" }],
+        },
+      ];
+      //# sourceMappingURL=evaluation.js.map
+
+      /***/
+    },
+    /* 48 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "PlaceholderWithDefault",
+          category: "graph",
+          inputs: [{ start: 0, name: "default", type: "tensor" }],
+          attrs: [
+            { tfName: "shape", name: "shape", type: "shape" },
+            { tfName: "dtype", name: "dtype", type: "dtype" },
+          ],
+        },
+        {
+          tfOpName: "Placeholder",
+          category: "graph",
+          attrs: [
+            { tfName: "shape", name: "shape", type: "shape" },
+            { tfName: "dtype", name: "dtype", type: "dtype" },
+          ],
+        },
+        { tfOpName: "Const", category: "graph" },
+        {
+          tfOpName: "Identity",
+          category: "graph",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "IdentityN",
+          category: "graph",
+          inputs: [{ start: 0, end: 0, name: "x", type: "tensors" }],
+        },
+        {
+          tfOpName: "Snapshot",
+          category: "graph",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "Rank",
+          category: "graph",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "Size",
+          category: "graph",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "Shape",
+          category: "graph",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "ShapeN",
+          category: "graph",
+          inputs: [{ start: 0, end: 0, name: "x", type: "tensors" }],
+        },
+        {
+          tfOpName: "Print",
+          category: "graph",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "data", type: "tensors" },
+          ],
+          attrs: [
+            { tfName: "message", name: "message", type: "string" },
+            {
+              tfName: "first_n",
+              name: "firstN",
+              type: "number",
+              notSupported: true,
+            },
+            {
+              tfName: "summarize",
+              name: "summarize",
+              type: "number",
+              defaultValue: 3,
+            },
+          ],
+        },
+        { tfOpName: "NoOp", category: "graph", inputs: [] },
+        {
+          tfOpName: "StopGradient",
+          category: "graph",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "FakeQuantWithMinMaxVars",
+          category: "graph",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "min", name: "min", type: "number" },
+            { tfName: "max", name: "max", type: "number" },
+          ],
+        },
+      ];
+      //# sourceMappingURL=graph.js.map
+
+      /***/
+    },
+    /* 49 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "ResizeBilinear",
+          category: "image",
+          inputs: [
+            { start: 0, name: "images", type: "tensor" },
+            { start: 1, name: "size", type: "number[]" },
+          ],
+          attrs: [
+            { tfName: "align_corners", name: "alignCorners", type: "bool" },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "ResizeNearestNeighbor",
+          category: "image",
+          inputs: [
+            { start: 0, name: "images", type: "tensor" },
+            { start: 1, name: "size", type: "number[]" },
+          ],
+          attrs: [
+            { tfName: "align_corners", name: "alignCorners", type: "bool" },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "CropAndResize",
+          category: "image",
+          inputs: [
+            { start: 0, name: "image", type: "tensor" },
+            { start: 1, name: "boxes", type: "tensor" },
+            { start: 2, name: "boxInd", type: "tensor" },
+            { start: 3, name: "cropSize", type: "number[]" },
+          ],
+          attrs: [
+            { tfName: "method", name: "method", type: "string" },
+            {
+              tfName: "extrapolation_value",
+              name: "extrapolationValue",
+              type: "number",
+            },
+          ],
+        },
+      ];
+      //# sourceMappingURL=image.js.map
+
+      /***/
+    },
+    /* 50 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "Equal",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "NotEqual",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Greater",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "GreaterEqual",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Less",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "LessEqual",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "LogicalAnd",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "LogicalNot",
+          category: "logical",
+          inputs: [{ start: 0, name: "a", type: "tensor" }],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "LogicalOr",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "Select",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "condition", type: "tensor" },
+            { start: 1, name: "a", type: "tensor" },
+            { start: 2, name: "b", type: "tensor" },
+          ],
+          attrs: [{ tfName: "T", name: "dtype", type: "dtype", notSupported: true }],
+        },
+        {
+          tfOpName: "SelectV2",
+          category: "logical",
+          inputs: [
+            { start: 0, name: "condition", type: "tensor" },
+            { start: 1, name: "a", type: "tensor" },
+            { start: 2, name: "b", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "T",
+              name: "dtype",
+              type: "dtype",
+              notSupported: true,
+            },
+          ],
+        },
+      ];
+      //# sourceMappingURL=logical.js.map
+
+      /***/
+    },
+    /* 51 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "_FusedMatMul",
+          category: "matrices",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+            { start: 2, end: 0, name: "args", type: "tensors" },
+          ],
+          attrs: [
+            { tfName: "num_args", name: "numArgs", type: "number" },
+            {
+              tfName: "fused_ops",
+              name: "fusedOps",
+              type: "string[]",
+              defaultValue: [],
+            },
+            {
+              tfName: "epsilon",
+              name: "epsilon",
+              type: "number",
+              defaultValue: 0.0001,
+            },
+            {
+              tfName: "transpose_a",
+              name: "transposeA",
+              type: "bool",
+              defaultValue: false,
+            },
+            {
+              tfName: "transpose_b",
+              name: "transposeB",
+              type: "bool",
+              defaultValue: false,
+            },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "MatMul",
+          category: "matrices",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "transpose_a",
+              name: "transposeA",
+              type: "bool",
+              defaultValue: false,
+            },
+            {
+              tfName: "transpose_b",
+              name: "transposeB",
+              type: "bool",
+              defaultValue: false,
+            },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "BatchMatMul",
+          category: "matrices",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "adj_x",
+              name: "transposeA",
+              type: "bool",
+              defaultValue: false,
+            },
+            {
+              tfName: "adj_y",
+              name: "transposeB",
+              type: "bool",
+              defaultValue: false,
+            },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "BatchMatMulV2",
+          category: "matrices",
+          inputs: [
+            { start: 0, name: "a", type: "tensor" },
+            { start: 1, name: "b", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "adj_x",
+              name: "transposeA",
+              type: "bool",
+              defaultValue: false,
+            },
+            {
+              tfName: "adj_y",
+              name: "transposeB",
+              type: "bool",
+              defaultValue: false,
+            },
+            { tfName: "T", name: "dtype", type: "dtype", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "Transpose",
+          category: "matrices",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "perm", type: "number[]" },
+          ],
+          attrs: [
+            {
+              tfName: "T",
+              name: "dtype",
+              type: "dtype",
+              notSupported: true,
+            },
+          ],
+        },
+      ];
+      //# sourceMappingURL=matrices.js.map
+
+      /***/
+    },
+    /* 52 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "FusedBatchNorm",
+          category: "normalization",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "scale", type: "tensor" },
+            { start: 2, name: "offset", type: "tensor" },
+            { start: 3, name: "mean", type: "tensor" },
+            { start: 4, name: "variance", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "epsilon",
+              name: "epsilon",
+              type: "number",
+              defaultValue: 0.001,
+            },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "FusedBatchNormV2",
+          category: "normalization",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "scale", type: "tensor" },
+            { start: 2, name: "offset", type: "tensor" },
+            { start: 3, name: "mean", type: "tensor" },
+            { start: 4, name: "variance", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "epsilon",
+              name: "epsilon",
+              type: "number",
+              defaultValue: 0.001,
+            },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "FusedBatchNormV3",
+          category: "normalization",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "scale", type: "tensor" },
+            { start: 2, name: "offset", type: "tensor" },
+            { start: 3, name: "mean", type: "tensor" },
+            { start: 4, name: "variance", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "epsilon",
+              name: "epsilon",
+              type: "number",
+              defaultValue: 0.001,
+            },
+            {
+              tfName: "data_format",
+              name: "dataFormat",
+              type: "string",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "LRN",
+          category: "normalization",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            {
+              tfName: "depth_radius",
+              name: "radius",
+              type: "number",
+              defaultValue: 5,
+            },
+            { tfName: "bias", name: "bias", type: "number", defaultValue: 1.0 },
+            {
+              tfName: "alpha",
+              name: "alpha",
+              type: "number",
+              defaultValue: 1.0,
+            },
+            {
+              tfName: "beta",
+              name: "beta",
+              type: "number",
+              defaultValue: 0.5,
+            },
+          ],
+        },
+        {
+          tfOpName: "Softmax",
+          category: "normalization",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "LogSoftmax",
+          category: "normalization",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "SparseToDense",
+          category: "normalization",
+          inputs: [
+            { start: 0, name: "sparseIndices", type: "tensor" },
+            { start: 1, name: "outputShape", type: "number[]" },
+            { start: 2, name: "sparseValues", type: "tensor" },
+            { start: 3, name: "defaultValue", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "validate_indices",
+              name: "validateIndices",
+              type: "bool",
+              defaultValue: true,
+              notSupported: true,
+            },
+          ],
+        },
+      ];
+      //# sourceMappingURL=normalization.js.map
+
+      /***/
+    },
+    /* 53 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "Max",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number[]" },
+          ],
+          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
+        },
+        {
+          tfOpName: "Mean",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number[]" },
+          ],
+          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
+        },
+        {
+          tfOpName: "Min",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number[]" },
+          ],
+          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
+        },
+        {
+          tfOpName: "Sum",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number[]" },
+          ],
+          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
+        },
+        {
+          tfOpName: "All",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number[]" },
+          ],
+          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
+        },
+        {
+          tfOpName: "Any",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number[]" },
+          ],
+          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
+        },
+        {
+          tfOpName: "ArgMax",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number" },
+          ],
+        },
+        {
+          tfOpName: "ArgMin",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number" },
+          ],
+        },
+        {
+          tfOpName: "Prod",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number[]" },
+          ],
+          attrs: [{ tfName: "keep_dims", name: "keepDims", type: "bool" }],
+        },
+        {
+          tfOpName: "Cumsum",
+          category: "reduction",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number" },
+          ],
+          attrs: [
+            { tfName: "exclusive", name: "exclusive", type: "bool" },
+            { tfName: "reverse", name: "reverse", type: "bool" },
+          ],
+        },
+      ];
+      //# sourceMappingURL=reduction.js.map
+
+      /***/
+    },
+    /* 54 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "ConcatV2",
+          category: "slice_join",
+          inputs: [
+            { start: 0, end: -1, name: "tensors", type: "tensors" },
+            { start: -1, name: "axis", type: "number" },
+          ],
+          attrs: [{ tfName: "N", name: "n", type: "number", defaultValue: 2 }],
+        },
+        {
+          tfOpName: "Concat",
+          category: "slice_join",
+          inputs: [
+            { start: 1, end: 0, name: "tensors", type: "tensors" },
+            { start: 0, name: "axis", type: "number" },
+          ],
+          attrs: [{ tfName: "N", name: "n", type: "number", defaultValue: 2 }],
+        },
+        {
+          tfOpName: "GatherV2",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "indices", type: "tensor" },
+            { start: 2, name: "axis", type: "number", defaultValue: 0 },
+          ],
+        },
+        {
+          tfOpName: "Gather",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "indices", type: "tensor" },
+          ],
+          attrs: [
+            { tfName: "axis", name: "axis", type: "number", defaultValue: 0 },
+            {
+              tfName: "validate_indices",
+              name: "validateIndices",
+              type: "bool",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "Reverse",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "dims", type: "bool", notSupported: true },
+          ],
+        },
+        {
+          tfOpName: "ReverseV2",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "Slice",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "begin", type: "number[]" },
+            { start: 2, name: "size", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "StridedSlice",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "begin", type: "number[]" },
+            { start: 2, name: "end", type: "number[]" },
+            { start: 3, name: "strides", type: "number[]" },
+          ],
+          attrs: [
+            {
+              tfName: "begin_mask",
+              name: "beginMask",
+              type: "number",
+              defaultValue: 0,
+            },
+            {
+              tfName: "end_mask",
+              name: "endMask",
+              type: "number",
+              defaultValue: 0,
+            },
+            {
+              tfName: "new_axis_mask",
+              name: "newAxisMask",
+              type: "number",
+              defaultValue: 0,
+            },
+            {
+              tfName: "ellipsis_mask",
+              name: "ellipsisMask",
+              type: "number",
+              defaultValue: 0,
+            },
+            {
+              tfName: "shrink_axis_mask",
+              name: "shrinkAxisMask",
+              type: "number",
+              defaultValue: 0,
+            },
+          ],
+        },
+        {
+          tfOpName: "Pack",
+          category: "slice_join",
+          inputs: [{ start: 0, end: 0, name: "tensors", type: "tensors" }],
+          attrs: [{ tfName: "axis", name: "axis", type: "number", defaultValue: 0 }],
+        },
+        {
+          tfOpName: "Unpack",
+          category: "slice_join",
+          inputs: [{ start: 0, name: "tensor", type: "tensor" }],
+          attrs: [
+            { tfName: "axis", name: "axis", type: "number", defaultValue: 0 },
+            {
+              tfName: "num",
+              name: "num",
+              type: "number",
+              defaultValue: 0,
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "Tile",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "reps", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "Split",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "axis", type: "number", defaultValue: 0 },
+            { start: 1, name: "x", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "num_split",
+              name: "numOrSizeSplits",
+              type: "number",
+              defaultValue: 1,
+            },
+          ],
+        },
+        {
+          tfOpName: "SplitV",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "numOrSizeSplits", type: "number[]" },
+            { start: 2, name: "axis", type: "number", defaultValue: 0 },
+          ],
+        },
+        {
+          tfOpName: "ScatterNd",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "indices", type: "tensor" },
+            { start: 1, name: "values", type: "tensor" },
+            { start: 2, name: "shape", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "GatherNd",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "indices", type: "tensor" },
+          ],
+        },
+        {
+          tfOpName: "SparseToDense",
+          category: "slice_join",
+          inputs: [
+            { start: 0, name: "sparseIndices", type: "tensor" },
+            { start: 1, name: "outputShape", type: "number[]" },
+            { start: 2, name: "sparseValues", type: "tensor" },
+            { start: 3, name: "defaultValue", type: "tensor" },
+          ],
+          attrs: [
+            {
+              tfName: "validate_indices",
+              name: "validateIndices",
+              type: "bool",
+              defaultValue: false,
+              notSupported: true,
+            },
+          ],
+        },
+      ];
+      //# sourceMappingURL=slice_join.js.map
+
+      /***/
+    },
+    /* 55 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "FFT",
+          category: "spectral",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "IFFT",
+          category: "spectral",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+        },
+        {
+          tfOpName: "RFFT",
+          category: "spectral",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            {
+              start: 1,
+              name: "fft_length",
+              type: "number",
+              notSupported: true,
+            },
+          ],
+        },
+        {
+          tfOpName: "IRFFT",
+          category: "spectral",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            {
+              start: 1,
+              name: "fft_length",
+              type: "number",
+              notSupported: true,
+            },
+          ],
+        },
+      ];
+      //# sourceMappingURL=spectral.js.map
+
+      /***/
+    },
+    /* 56 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "json",
+        function () {
+          return json;
+        }
+      );
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const json = [
+        {
+          tfOpName: "Cast",
+          category: "transformation",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            {
+              tfName: "SrcT",
+              name: "sdtype",
+              type: "dtype",
+              notSupported: true,
+            },
+            { tfName: "DstT", name: "dtype", type: "dtype" },
+          ],
+        },
+        {
+          tfOpName: "ExpandDims",
+          category: "transformation",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "axis", type: "number" },
+          ],
+        },
+        {
+          tfOpName: "Pad",
+          category: "transformation",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "padding", type: "number[]" },
+          ],
+          attrs: [
+            {
+              tfName: "constant_value",
+              name: "constantValue",
+              type: "number",
+              defaultValue: 0,
+            },
+          ],
+        },
+        {
+          tfOpName: "PadV2",
+          category: "transformation",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "padding", type: "number[]" },
+            {
+              start: 2,
+              name: "constantValue",
+              type: "number",
+              defaultValue: 0,
+            },
+          ],
+        },
+        {
+          tfOpName: "Reshape",
+          category: "transformation",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "shape", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "Squeeze",
+          category: "transformation",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            {
+              tfName: "axis",
+              tfDeprecatedName: "squeeze_dims",
+              name: "axis",
+              type: "number[]",
+            },
+          ],
+        },
+        {
+          tfOpName: "SpaceToBatchND",
+          category: "transformation",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "blockShape", type: "number[]" },
+            { start: 2, name: "paddings", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "BatchToSpaceND",
+          category: "transformation",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "blockShape", type: "number[]" },
+            { start: 2, name: "crops", type: "number[]" },
+          ],
+        },
+        {
+          tfOpName: "DepthToSpace",
+          category: "transformation",
+          inputs: [{ start: 0, name: "x", type: "tensor" }],
+          attrs: [
+            { tfName: "block_size", name: "blockSize", type: "number" },
+            { tfName: "data_format", name: "dataFormat", type: "string" },
+          ],
+        },
+        {
+          tfOpName: "BroadcastTo",
+          category: "transformation",
+          inputs: [
+            { start: 0, name: "x", type: "tensor" },
+            { start: 1, name: "shape", type: "number[]" },
+          ],
+          attrs: [],
+        },
+      ];
+      //# sourceMappingURL=transformation.js.map
+
+      /***/
+    },
+    /* 57 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (Buffer) {
+        /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+          return ByteChunkIterator;
+        });
+        /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
+          __webpack_require__(0);
+        /* harmony import */ var _lazy_iterator__WEBPACK_IMPORTED_MODULE_1__ =
+          __webpack_require__(14);
+        /* harmony import */ var _string_iterator__WEBPACK_IMPORTED_MODULE_2__ =
+          __webpack_require__(58);
+        /**
+         * @license
+         * Copyright 2018 Google LLC. All Rights Reserved.
+         * Licensed under the Apache License, Version 2.0 (the "License");
+         * you may not use this file except in compliance with the License.
+         * You may obtain a copy of the License at
+         *
+         * http://www.apache.org/licenses/LICENSE-2.0
+         *
+         * Unless required by applicable law or agreed to in writing, software
+         * distributed under the License is distributed on an "AS IS" BASIS,
+         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+         * See the License for the specific language governing permissions and
+         * limitations under the License.
+         *
+         * =============================================================================
+         */
+
+        class ByteChunkIterator extends _lazy_iterator__WEBPACK_IMPORTED_MODULE_1__[
+          /* LazyIterator */ "a"
+        ] {
+          /**
+           * Decode a stream of UTF8-encoded byte arrays to a stream of strings.
+           *
+           * The byte arrays producetd from the ByteChunkIterator on which this is
+           * called will be interpreted as concatenated.  No assumptions are made about
+           * the boundaries of the incoming chunks, so a multi-byte UTF8 encoding of a
+           * character may span the boundary between chunks.  This naturally happens,
+           * for instance, when reading fixed-size byte arrays from a file.
+           */
+          decodeUTF8() {
+            return new Utf8Iterator(this);
+          }
+        }
+        // ============================================================================
+        // The following private classes serve to implement the chainable methods
+        // on ByteChunkIterator.  Unfortunately they can't be placed in separate files,
+        // due to resulting trouble with circular imports.
+        // ============================================================================
+        // We wanted multiple inheritance, e.g.
+        //   class Utf8Iterator extends QueueIterator<string>, StringIterator
+        // but the TypeScript mixin approach is a bit hacky, so we take this adapter
+        // approach instead.
+        class Utf8Iterator extends _string_iterator__WEBPACK_IMPORTED_MODULE_2__[
+          /* StringIterator */ "a"
+        ] {
+          constructor(upstream) {
+            super();
+            this.upstream = upstream;
+            this.impl = new Utf8IteratorImpl(upstream);
+          }
+          summary() {
+            return this.impl.summary();
+          }
+          async next() {
+            return this.impl.next();
+          }
+        }
+        /**
+         * Decode a stream of UTF8-encoded byte arrays to a stream of strings.
+         *
+         * This is tricky because the incoming byte array boundaries may disrupt a
+         * multi-byte UTF8 character. Thus any incomplete character data at the end of
+         * a chunk must be carried over and prepended to the next chunk before
+         * decoding. Luckily with native decoder, TextDecoder in browser and
+         * string_decoder in node, byte array boundaries are handled automatically.
+         *
+         * In the context of an input pipeline for machine learning, UTF8 decoding is
+         * needed to parse text files containing training examples or prediction
+         * requests (e.g., formatted as CSV or JSON). We cannot use the built-in
+         * decoding provided by FileReader.readAsText() because here we are in a
+         * streaming context, which FileReader does not support.
+         *
+         * @param upstream A `LazyIterator` of `Uint8Arrays` containing UTF8-encoded
+         *   text, which should be interpreted as concatenated.  No assumptions are
+         *   made about the boundaries of the incoming chunks, so a multi-byte UTF8
+         *   encoding of a character may span the boundary between chunks.  This
+         *   naturally happens, for instance, when reading fixed-size byte arrays from a
+         *   file.
+         */
+        class Utf8IteratorImpl extends _lazy_iterator__WEBPACK_IMPORTED_MODULE_1__[
+          /* OneToManyIterator */ "b"
+        ] {
+          constructor(upstream) {
+            super();
+            this.upstream = upstream;
+            if (
+              Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["env"])().get("IS_BROWSER")
+            ) {
+              this.decoder = new TextDecoder("utf-8");
+            } else {
+              // tslint:disable-next-line:no-require-imports
+              const { StringDecoder } = __webpack_require__(78);
+              this.decoder = new StringDecoder("utf8");
+            }
+          }
+          summary() {
+            return `${this.upstream.summary()} -> Utf8`;
+          }
+          async pump() {
+            const chunkResult = await this.upstream.next();
+            let chunk;
+            if (chunkResult.done) {
+              return false;
+            } else {
+              chunk = chunkResult.value;
+            }
+            let text;
+            if (
+              Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["env"])().get("IS_BROWSER")
+            ) {
+              text = this.decoder.decode(chunk, { stream: true });
+            } else {
+              text = this.decoder.write(Buffer.from(chunk.buffer));
+            }
+            this.outputQueue.push(text);
+            return true;
+          }
+        }
+        //# sourceMappingURL=byte_chunk_iterator.js.map
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(39).Buffer));
+
+      /***/
+    },
+    /* 58 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* harmony export (binding) */ __webpack_require__.d(__webpack_exports__, "a", function () {
+        return StringIterator;
+      });
+      /* harmony import */ var _lazy_iterator__WEBPACK_IMPORTED_MODULE_0__ =
+        __webpack_require__(14);
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      class StringIterator extends _lazy_iterator__WEBPACK_IMPORTED_MODULE_0__[
+        /* LazyIterator */ "a"
+      ] {
+        /**
+         * Splits a string stream on a given separator.
+         *
+         * It is assumed that the incoming chunk boundaries have no semantic meaning,
+         * so conceptually the incoming stream is treated simply as the concatenation
+         * of its elements.
+         *
+         * The outgoing stream provides chunks corresponding to the results of the
+         * standard string split() operation (even if such a chunk spanned incoming
+         * chunks).  The separators are not included.
+         *
+         * A typical usage is to split a text file (represented as a stream with
+         * arbitrary chunk boundaries) into lines.
+         *
+         * @param upstream A readable stream of strings that can be treated as
+         *   concatenated.
+         * @param separator A character to split on.
+         */
+        split(separator) {
+          return new SplitIterator(this, separator);
+        }
+      }
+      // ============================================================================
+      // The following private classes serve to implement the chainable methods
+      // on StringIterator.  Unfortunately they can't be placed in separate files, due
+      // to resulting trouble with circular imports.
+      // ============================================================================
+      // We wanted multiple inheritance, e.g.
+      //   class SplitIterator extends QueueIterator<string>, StringIterator
+      // but the TypeScript mixin approach is a bit hacky, so we take this adapter
+      // approach instead.
+      class SplitIterator extends StringIterator {
+        constructor(upstream, separator) {
+          super();
+          this.upstream = upstream;
+          this.impl = new SplitIteratorImpl(upstream, separator);
+        }
+        summary() {
+          return this.impl.summary();
+        }
+        async next() {
+          return this.impl.next();
+        }
+      }
+      class SplitIteratorImpl extends _lazy_iterator__WEBPACK_IMPORTED_MODULE_0__[
+        /* OneToManyIterator */ "b"
+      ] {
+        constructor(upstream, separator) {
+          super();
+          this.upstream = upstream;
+          this.separator = separator;
+          // A partial string at the end of an upstream chunk
+          this.carryover = "";
+        }
+        summary() {
+          return `${this.upstream.summary()} -> Split('${this.separator}')`;
+        }
+        async pump() {
+          const chunkResult = await this.upstream.next();
+          if (chunkResult.done) {
+            if (this.carryover === "") {
+              return false;
+            }
+            // Pretend that the pump succeeded in order to emit the small last batch.
+            // The next pump() call will actually fail.
+            this.outputQueue.push(this.carryover);
+            this.carryover = "";
+            return true;
+          }
+          const lines = chunkResult.value.split(this.separator);
+          // Note the behavior: " ab ".split(' ') === ['', 'ab', '']
+          // Thus the carryover may be '' if the separator falls on a chunk
+          // boundary; this produces the correct result.
+          lines[0] = this.carryover + lines[0];
+          for (const line of lines.slice(0, -1)) {
+            this.outputQueue.push(line);
+          }
+          this.carryover = lines[lines.length - 1];
+          return true;
+        }
+      }
+      //# sourceMappingURL=string_iterator.js.map
+
+      /***/
+    },
+    /* 59 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+
+      Object.defineProperty(exports, "__esModule", { value: true });
+      const blazeface = __webpack_require__(81);
+      const tfconv = __webpack_require__(38);
+      const tf = __webpack_require__(0);
+      const keypoints_1 = __webpack_require__(82);
+      const pipeline_1 = __webpack_require__(83);
+      const uv_coords_1 = __webpack_require__(85);
+      const FACEMESH_GRAPHMODEL_PATH =
+        "https://tfhub.dev/mediapipe/tfjs-model/facemesh/1/default/1";
+      const MESH_MODEL_INPUT_WIDTH = 192;
+      const MESH_MODEL_INPUT_HEIGHT = 192;
+      async function load({
+        maxContinuousChecks = 5,
+        detectionConfidence = 0.9,
+        maxFaces = 10,
+        iouThreshold = 0.3,
+        scoreThreshold = 0.75,
+      } = {}) {
+        const [blazeFace, blazeMeshModel] = await Promise.all([
+          loadDetectorModel(maxFaces, iouThreshold, scoreThreshold),
+          loadMeshModel(),
+        ]);
+        const faceMesh = new FaceMesh(
+          blazeFace,
+          blazeMeshModel,
+          maxContinuousChecks,
+          detectionConfidence,
+          maxFaces
+        );
+        return faceMesh;
+      }
+      exports.load = load;
+      async function loadDetectorModel(maxFaces, iouThreshold, scoreThreshold) {
+        return blazeface.load({ maxFaces, iouThreshold, scoreThreshold });
+      }
+      async function loadMeshModel() {
+        return tfconv.loadGraphModel(FACEMESH_GRAPHMODEL_PATH, { fromTFHub: true });
+      }
+      function getInputTensorDimensions(input) {
+        return input instanceof tf.Tensor
+          ? [input.shape[0], input.shape[1]]
+          : [input.height, input.width];
+      }
+      function flipFaceHorizontal(face, imageWidth) {
+        if (face.mesh instanceof tf.Tensor) {
+          const [topLeft, bottomRight, mesh, scaledMesh] = tf.tidy(() => {
+            const subtractBasis = tf.tensor1d([imageWidth - 1, 0, 0]);
+            const multiplyBasis = tf.tensor1d([1, -1, 1]);
+            return tf.tidy(() => {
+              return [
+                tf.concat([
+                  tf.sub(imageWidth - 1, face.boundingBox.topLeft.slice(0, 1)),
+                  face.boundingBox.topLeft.slice(1, 1),
+                ]),
+                tf.concat([
+                  tf.sub(imageWidth - 1, face.boundingBox.bottomRight.slice(0, 1)),
+                  face.boundingBox.bottomRight.slice(1, 1),
+                ]),
+                tf.sub(subtractBasis, face.mesh).mul(multiplyBasis),
+                tf.sub(subtractBasis, face.scaledMesh).mul(multiplyBasis),
+              ];
+            });
+          });
+          return Object.assign({}, face, {
+            boundingBox: { topLeft, bottomRight },
+            mesh,
+            scaledMesh,
+          });
+        }
+        return Object.assign({}, face, {
+          boundingBox: {
+            topLeft: [imageWidth - 1 - face.boundingBox.topLeft[0], face.boundingBox.topLeft[1]],
+            bottomRight: [
+              imageWidth - 1 - face.boundingBox.bottomRight[0],
+              face.boundingBox.bottomRight[1],
+            ],
+          },
+          mesh: face.mesh.map((coord) => {
+            const flippedCoord = coord.slice(0);
+            flippedCoord[0] = imageWidth - 1 - coord[0];
+            return flippedCoord;
+          }),
+          scaledMesh: face.scaledMesh.map((coord) => {
+            const flippedCoord = coord.slice(0);
+            flippedCoord[0] = imageWidth - 1 - coord[0];
+            return flippedCoord;
+          }),
+        });
+      }
+      class FaceMesh {
+        constructor(blazeFace, blazeMeshModel, maxContinuousChecks, detectionConfidence, maxFaces) {
+          this.pipeline = new pipeline_1.Pipeline(
+            blazeFace,
+            blazeMeshModel,
+            MESH_MODEL_INPUT_WIDTH,
+            MESH_MODEL_INPUT_HEIGHT,
+            maxContinuousChecks,
+            maxFaces
+          );
+          this.detectionConfidence = detectionConfidence;
+        }
+        static getAnnotations() {
+          return keypoints_1.MESH_ANNOTATIONS;
+        }
+        static getUVCoords() {
+          return uv_coords_1.UV_COORDS;
+        }
+        async estimateFaces(input, returnTensors = false, flipHorizontal = false) {
+          const [, width] = getInputTensorDimensions(input);
+          const image = tf.tidy(() => {
+            if (!(input instanceof tf.Tensor)) {
+              input = tf.browser.fromPixels(input);
+            }
+            return input.toFloat().expandDims(0);
+          });
+          const savedWebglPackDepthwiseConvFlag = tf.env().get("WEBGL_PACK_DEPTHWISECONV");
+          tf.env().set("WEBGL_PACK_DEPTHWISECONV", true);
+          const predictions = await this.pipeline.predict(image);
+          tf.env().set("WEBGL_PACK_DEPTHWISECONV", savedWebglPackDepthwiseConvFlag);
+          image.dispose();
+          if (predictions != null && predictions.length > 0) {
+            return Promise.all(
+              predictions.map(async (prediction, i) => {
+                const { coords, scaledCoords, box, flag } = prediction;
+                let tensorsToRead = [flag];
+                if (!returnTensors) {
+                  tensorsToRead = tensorsToRead.concat([
+                    coords,
+                    scaledCoords,
+                    box.startPoint,
+                    box.endPoint,
+                  ]);
+                }
+                const tensorValues = await Promise.all(tensorsToRead.map(async (d) => d.array()));
+                const flagValue = tensorValues[0];
+                flag.dispose();
+                if (flagValue < this.detectionConfidence) {
+                  this.pipeline.clearRegionOfInterest(i);
+                }
+                if (returnTensors) {
+                  const annotatedPrediction = {
+                    faceInViewConfidence: flagValue,
+                    mesh: coords,
+                    scaledMesh: scaledCoords,
+                    boundingBox: {
+                      topLeft: box.startPoint.squeeze(),
+                      bottomRight: box.endPoint.squeeze(),
+                    },
+                  };
+                  if (flipHorizontal) {
+                    return flipFaceHorizontal(annotatedPrediction, width);
+                  }
+                  return annotatedPrediction;
+                }
+                const [coordsArr, coordsArrScaled, topLeft, bottomRight] = tensorValues.slice(1);
+                scaledCoords.dispose();
+                coords.dispose();
+                let annotatedPrediction = {
+                  faceInViewConfidence: flagValue,
+                  boundingBox: { topLeft, bottomRight },
+                  mesh: coordsArr,
+                  scaledMesh: coordsArrScaled,
+                };
+                if (flipHorizontal) {
+                  annotatedPrediction = flipFaceHorizontal(annotatedPrediction, width);
+                }
+                const annotations = {};
+                for (const key in keypoints_1.MESH_ANNOTATIONS) {
+                  annotations[key] = keypoints_1.MESH_ANNOTATIONS[key].map(
+                    (index) => annotatedPrediction.scaledMesh[index]
+                  );
+                }
+                annotatedPrediction["annotations"] = annotations;
+                return annotatedPrediction;
+              })
+            );
+          }
+          return [];
+        }
+      }
+      exports.FaceMesh = FaceMesh;
+      //# sourceMappingURL=index.js.map
+
+      /***/
+    },
+    /* 60 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      Object.defineProperty(exports, "__esModule", { value: true });
+
+      var tfjsCore = __webpack_require__(0);
+      var tfjsLayers = __webpack_require__(87);
+      var tfjsConverter = __webpack_require__(38);
+      var tfjsData = __webpack_require__(88);
+      var tfjsBackendCpu = __webpack_require__(89);
+      var tfjsBackendWebgl = __webpack_require__(86);
+
+      /** @license See the LICENSE file. */
+      // This code is auto-generated, do not modify this file!
+      var version = "2.0.1";
+
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      var version$1 = {
+        "tfjs-core": tfjsCore.version_core,
+        "tfjs-backend-cpu": tfjsBackendCpu.version_cpu,
+        "tfjs-backend-webgl": tfjsBackendWebgl.version_webgl,
+        "tfjs-data": tfjsData.version_data,
+        "tfjs-layers": tfjsLayers.version_layers,
+        "tfjs-converter": tfjsConverter.version_converter,
+        tfjs: version,
+      };
+
+      Object.keys(tfjsCore).forEach(function (k) {
+        if (k !== "default")
+          Object.defineProperty(exports, k, {
+            enumerable: true,
+            get: function () {
+              return tfjsCore[k];
+            },
+          });
+      });
+      Object.keys(tfjsLayers).forEach(function (k) {
+        if (k !== "default")
+          Object.defineProperty(exports, k, {
+            enumerable: true,
+            get: function () {
+              return tfjsLayers[k];
+            },
+          });
+      });
+      Object.keys(tfjsConverter).forEach(function (k) {
+        if (k !== "default")
+          Object.defineProperty(exports, k, {
+            enumerable: true,
+            get: function () {
+              return tfjsConverter[k];
+            },
+          });
+      });
+      exports.data = tfjsData;
+      exports.version = version$1;
+      //# sourceMappingURL=tf.node.js.map
+
+      /***/
+    },
+    /* 61 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (process) {
+        /* harmony import */ var _device_util__WEBPACK_IMPORTED_MODULE_0__ =
+          __webpack_require__(36);
+        /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_1__ =
+          __webpack_require__(10);
+        /**
+         * @license
+         * Copyright 2019 Google Inc. All Rights Reserved.
+         * Licensed under the Apache License, Version 2.0 (the "License");
+         * you may not use this file except in compliance with the License.
+         * You may obtain a copy of the License at
+         *
+         * http://www.apache.org/licenses/LICENSE-2.0
+         *
+         * Unless required by applicable law or agreed to in writing, software
+         * distributed under the License is distributed on an "AS IS" BASIS,
+         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+         * See the License for the specific language governing permissions and
+         * limitations under the License.
+         * =============================================================================
+         */
+
+        const ENV = Object(_environment__WEBPACK_IMPORTED_MODULE_1__[/* env */ "c"])();
+        /**
+         * This file contains environment-related flag registrations.
+         */
+        /** Whether to enable debug mode. */
+        ENV.registerFlag(
+          "DEBUG",
+          () => false,
+          (debugValue) => {
+            if (debugValue) {
+              console.warn(
+                "Debugging mode is ON. The output of every math call will " +
+                  "be downloaded to CPU and checked for NaNs. " +
+                  "This significantly impacts performance."
+              );
+            }
+          }
+        );
+        /** Whether we are in a browser (as versus, say, node.js) environment. */
+        ENV.registerFlag("IS_BROWSER", () =>
+          _device_util__WEBPACK_IMPORTED_MODULE_0__["isBrowser"]()
+        );
+        /** Whether we are in a browser (as versus, say, node.js) environment. */
+        ENV.registerFlag(
+          "IS_NODE",
+          () =>
+            typeof process !== "undefined" &&
+            typeof process.versions !== "undefined" &&
+            typeof process.versions.node !== "undefined"
+        );
+        /** Whether this browser is Chrome. */
+        ENV.registerFlag(
+          "IS_CHROME",
+          () =>
+            typeof navigator !== "undefined" &&
+            navigator != null &&
+            navigator.userAgent != null &&
+            /Chrome/.test(navigator.userAgent) &&
+            /Google Inc/.test(navigator.vendor)
+        );
+        /**
+         * True when the environment is "production" where we disable safety checks
+         * to gain performance.
+         */
+        ENV.registerFlag("PROD", () => false);
+        /**
+         * Whether to do sanity checks when inferring a shape from user-provided
+         * values, used when creating a new tensor.
+         */
+        ENV.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY", () => ENV.getBool("DEBUG"));
+        /** Whether deprecation warnings are enabled. */
+        ENV.registerFlag("DEPRECATION_WARNINGS_ENABLED", () => true);
+        /** True if running unit tests. */
+        ENV.registerFlag("IS_TEST", () => false);
+        //# sourceMappingURL=flags.js.map
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(35)));
+
+      /***/
+    },
+    /* 62 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      /* WEBPACK VAR INJECTION */ (function (process) {
+        /* unused harmony export getNodeFetch */
+        /* unused harmony export resetSystemFetch */
+        /* unused harmony export setSystemFetch */
+        /* unused harmony export getSystemFetch */
+        /* unused harmony export PlatformNode */
+        /* harmony import */ var _environment__WEBPACK_IMPORTED_MODULE_0__ =
+          __webpack_require__(10);
+        /**
+         * @license
+         * Copyright 2019 Google LLC. All Rights Reserved.
+         * Licensed under the Apache License, Version 2.0 (the "License");
+         * you may not use this file except in compliance with the License.
+         * You may obtain a copy of the License at
+         *
+         * http://www.apache.org/licenses/LICENSE-2.0
+         *
+         * Unless required by applicable law or agreed to in writing, software
+         * distributed under the License is distributed on an "AS IS" BASIS,
+         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+         * See the License for the specific language governing permissions and
+         * limitations under the License.
+         * =============================================================================
+         */
+
+        // We are wrapping this within an object so it can be stubbed by Jasmine.
+        const getNodeFetch = {
+          // tslint:disable-next-line:no-require-imports
+          importFetch: () => __webpack_require__(63),
+        };
+        let systemFetch;
+        // These getters and setters are for testing so we don't export a mutable
+        // variable.
+        function resetSystemFetch() {
+          systemFetch = null;
+        }
+        function setSystemFetch(fetchFn) {
+          systemFetch = fetchFn;
+        }
+        function getSystemFetch() {
+          return systemFetch;
+        }
+        class PlatformNode {
+          constructor() {
+            // tslint:disable-next-line:no-require-imports
+            this.util = __webpack_require__(64);
+            // According to the spec, the built-in encoder can do only UTF-8 encoding.
+            // https://developer.mozilla.org/en-US/docs/Web/API/TextEncoder/TextEncoder
+            this.textEncoder = new this.util.TextEncoder();
+          }
+          fetch(path, requestInits) {
+            if (
+              Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().global.fetch !=
+              null
+            ) {
+              return Object(
+                _environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"]
+              )().global.fetch(path, requestInits);
+            }
+            if (systemFetch == null) {
+              systemFetch = getNodeFetch.importFetch();
+            }
+            return systemFetch(path, requestInits);
+          }
+          now() {
+            const time = process.hrtime();
+            return time[0] * 1000 + time[1] / 1000000;
+          }
+          encode(text, encoding) {
+            if (encoding !== "utf-8" && encoding !== "utf8") {
+              throw new Error(`Node built-in encoder only supports utf-8, but got ${encoding}`);
+            }
+            return this.textEncoder.encode(text);
+          }
+          decode(bytes, encoding) {
+            if (bytes.length === 0) {
+              return "";
+            }
+            return new this.util.TextDecoder(encoding).decode(bytes);
+          }
+        }
+        if (Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().get("IS_NODE")) {
+          Object(_environment__WEBPACK_IMPORTED_MODULE_0__[/* env */ "c"])().setPlatform(
+            "node",
+            new PlatformNode()
+          );
+        }
+        //# sourceMappingURL=platform_node.js.map
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(35)));
+
+      /***/
+    },
+    /* 63 */
+    /***/ function (module, exports) {
+      /* (ignored) */
+      /***/
+    },
+    /* 64 */
+    /***/ function (module, exports) {
+      /* (ignored) */
+      /***/
+    },
+    /* 65 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+
+      exports.byteLength = byteLength;
+      exports.toByteArray = toByteArray;
+      exports.fromByteArray = fromByteArray;
+
+      var lookup = [];
+      var revLookup = [];
+      var Arr = typeof Uint8Array !== "undefined" ? Uint8Array : Array;
+
+      var code = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
+      for (var i = 0, len = code.length; i < len; ++i) {
+        lookup[i] = code[i];
+        revLookup[code.charCodeAt(i)] = i;
+      }
+
+      // Support decoding URL-safe base64 strings, as Node.js does.
+      // See: https://en.wikipedia.org/wiki/Base64#URL_applications
+      revLookup["-".charCodeAt(0)] = 62;
+      revLookup["_".charCodeAt(0)] = 63;
+
+      function getLens(b64) {
+        var len = b64.length;
+
+        if (len % 4 > 0) {
+          throw new Error("Invalid string. Length must be a multiple of 4");
+        }
+
+        // Trim off extra bytes after placeholder bytes are found
+        // See: https://github.com/beatgammit/base64-js/issues/42
+        var validLen = b64.indexOf("=");
+        if (validLen === -1) validLen = len;
+
+        var placeHoldersLen = validLen === len ? 0 : 4 - (validLen % 4);
+
+        return [validLen, placeHoldersLen];
+      }
+
+      // base64 is 4/3 + up to two characters of the original data
+      function byteLength(b64) {
+        var lens = getLens(b64);
+        var validLen = lens[0];
+        var placeHoldersLen = lens[1];
+        return ((validLen + placeHoldersLen) * 3) / 4 - placeHoldersLen;
+      }
+
+      function _byteLength(b64, validLen, placeHoldersLen) {
+        return ((validLen + placeHoldersLen) * 3) / 4 - placeHoldersLen;
+      }
+
+      function toByteArray(b64) {
+        var tmp;
+        var lens = getLens(b64);
+        var validLen = lens[0];
+        var placeHoldersLen = lens[1];
+
+        var arr = new Arr(_byteLength(b64, validLen, placeHoldersLen));
+
+        var curByte = 0;
+
+        // if there are placeholders, only get up to the last complete 4 chars
+        var len = placeHoldersLen > 0 ? validLen - 4 : validLen;
+
+        var i;
+        for (i = 0; i < len; i += 4) {
+          tmp =
+            (revLookup[b64.charCodeAt(i)] << 18) |
+            (revLookup[b64.charCodeAt(i + 1)] << 12) |
+            (revLookup[b64.charCodeAt(i + 2)] << 6) |
+            revLookup[b64.charCodeAt(i + 3)];
+          arr[curByte++] = (tmp >> 16) & 0xff;
+          arr[curByte++] = (tmp >> 8) & 0xff;
+          arr[curByte++] = tmp & 0xff;
+        }
+
+        if (placeHoldersLen === 2) {
+          tmp = (revLookup[b64.charCodeAt(i)] << 2) | (revLookup[b64.charCodeAt(i + 1)] >> 4);
+          arr[curByte++] = tmp & 0xff;
+        }
+
+        if (placeHoldersLen === 1) {
+          tmp =
+            (revLookup[b64.charCodeAt(i)] << 10) |
+            (revLookup[b64.charCodeAt(i + 1)] << 4) |
+            (revLookup[b64.charCodeAt(i + 2)] >> 2);
+          arr[curByte++] = (tmp >> 8) & 0xff;
+          arr[curByte++] = tmp & 0xff;
+        }
+
+        return arr;
+      }
+
+      function tripletToBase64(num) {
+        return (
+          lookup[(num >> 18) & 0x3f] +
+          lookup[(num >> 12) & 0x3f] +
+          lookup[(num >> 6) & 0x3f] +
+          lookup[num & 0x3f]
+        );
+      }
+
+      function encodeChunk(uint8, start, end) {
+        var tmp;
+        var output = [];
+        for (var i = start; i < end; i += 3) {
+          tmp =
+            ((uint8[i] << 16) & 0xff0000) + ((uint8[i + 1] << 8) & 0xff00) + (uint8[i + 2] & 0xff);
+          output.push(tripletToBase64(tmp));
+        }
+        return output.join("");
+      }
+
+      function fromByteArray(uint8) {
+        var tmp;
+        var len = uint8.length;
+        var extraBytes = len % 3; // if we have 1 byte left, pad 2 bytes
+        var parts = [];
+        var maxChunkLength = 16383; // must be multiple of 3
+
+        // go through the array every three bytes, we'll deal with trailing stuff later
+        for (var i = 0, len2 = len - extraBytes; i < len2; i += maxChunkLength) {
+          parts.push(encodeChunk(uint8, i, i + maxChunkLength > len2 ? len2 : i + maxChunkLength));
+        }
+
+        // pad the end with zeros, but make sure to not forget the extra bytes
+        if (extraBytes === 1) {
+          tmp = uint8[len - 1];
+          parts.push(lookup[tmp >> 2] + lookup[(tmp << 4) & 0x3f] + "==");
+        } else if (extraBytes === 2) {
+          tmp = (uint8[len - 2] << 8) + uint8[len - 1];
+          parts.push(
+            lookup[tmp >> 10] + lookup[(tmp >> 4) & 0x3f] + lookup[(tmp << 2) & 0x3f] + "="
+          );
+        }
+
+        return parts.join("");
+      }
+
+      /***/
+    },
+    /* 66 */
+    /***/ function (module, exports) {
+      exports.read = function (buffer, offset, isLE, mLen, nBytes) {
+        var e, m;
+        var eLen = nBytes * 8 - mLen - 1;
+        var eMax = (1 << eLen) - 1;
+        var eBias = eMax >> 1;
+        var nBits = -7;
+        var i = isLE ? nBytes - 1 : 0;
+        var d = isLE ? -1 : 1;
+        var s = buffer[offset + i];
+
+        i += d;
+
+        e = s & ((1 << -nBits) - 1);
+        s >>= -nBits;
+        nBits += eLen;
+        for (; nBits > 0; e = e * 256 + buffer[offset + i], i += d, nBits -= 8) {}
+
+        m = e & ((1 << -nBits) - 1);
+        e >>= -nBits;
+        nBits += mLen;
+        for (; nBits > 0; m = m * 256 + buffer[offset + i], i += d, nBits -= 8) {}
+
+        if (e === 0) {
+          e = 1 - eBias;
+        } else if (e === eMax) {
+          return m ? NaN : (s ? -1 : 1) * Infinity;
+        } else {
+          m = m + Math.pow(2, mLen);
+          e = e - eBias;
+        }
+        return (s ? -1 : 1) * m * Math.pow(2, e - mLen);
+      };
+
+      exports.write = function (buffer, value, offset, isLE, mLen, nBytes) {
+        var e, m, c;
+        var eLen = nBytes * 8 - mLen - 1;
+        var eMax = (1 << eLen) - 1;
+        var eBias = eMax >> 1;
+        var rt = mLen === 23 ? Math.pow(2, -24) - Math.pow(2, -77) : 0;
+        var i = isLE ? 0 : nBytes - 1;
+        var d = isLE ? 1 : -1;
+        var s = value < 0 || (value === 0 && 1 / value < 0) ? 1 : 0;
+
+        value = Math.abs(value);
+
+        if (isNaN(value) || value === Infinity) {
+          m = isNaN(value) ? 1 : 0;
+          e = eMax;
+        } else {
+          e = Math.floor(Math.log(value) / Math.LN2);
+          if (value * (c = Math.pow(2, -e)) < 1) {
+            e--;
+            c *= 2;
+          }
+          if (e + eBias >= 1) {
+            value += rt / c;
+          } else {
+            value += rt * Math.pow(2, 1 - eBias);
+          }
+          if (value * c >= 2) {
+            e++;
+            c /= 2;
+          }
+
+          if (e + eBias >= eMax) {
+            m = 0;
+            e = eMax;
+          } else if (e + eBias >= 1) {
+            m = (value * c - 1) * Math.pow(2, mLen);
+            e = e + eBias;
+          } else {
+            m = value * Math.pow(2, eBias - 1) * Math.pow(2, mLen);
+            e = 0;
+          }
+        }
+
+        for (; mLen >= 8; buffer[offset + i] = m & 0xff, i += d, m /= 256, mLen -= 8) {}
+
+        e = (e << mLen) | m;
+        eLen += mLen;
+        for (; eLen > 0; buffer[offset + i] = e & 0xff, i += d, e /= 256, eLen -= 8) {}
+
+        buffer[offset + i - d] |= s * 128;
+      };
+
+      /***/
+    },
+    /* 67 */
+    /***/ function (module, exports) {
+      var toString = {}.toString;
+
+      module.exports =
+        Array.isArray ||
+        function (arr) {
+          return toString.call(arr) == "[object Array]";
+        };
+
+      /***/
+    },
+    /* 68 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (module) {
+        var __WEBPACK_AMD_DEFINE_RESULT__; // A port of an algorithm by Johannes Baagøe <baagoe@baagoe.com>, 2010
+        // http://baagoe.com/en/RandomMusings/javascript/
+        // https://github.com/nquinlan/better-random-numbers-for-javascript-mirror
+        // Original work is under MIT license -
+
+        // Copyright (C) 2010 by Johannes Baagøe <baagoe@baagoe.org>
+        //
+        // Permission is hereby granted, free of charge, to any person obtaining a copy
+        // of this software and associated documentation files (the "Software"), to deal
+        // in the Software without restriction, including without limitation the rights
+        // to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+        // copies of the Software, and to permit persons to whom the Software is
+        // furnished to do so, subject to the following conditions:
+        //
+        // The above copyright notice and this permission notice shall be included in
+        // all copies or substantial portions of the Software.
+        //
+        // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+        // IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+        // FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+        // AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+        // LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+        // OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+        // THE SOFTWARE.
+
+        (function (global, module, define) {
+          function Alea(seed) {
+            var me = this,
+              mash = Mash();
+
+            me.next = function () {
+              var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32
+              me.s0 = me.s1;
+              me.s1 = me.s2;
+              return (me.s2 = t - (me.c = t | 0));
+            };
+
+            // Apply the seeding algorithm from Baagoe.
+            me.c = 1;
+            me.s0 = mash(" ");
+            me.s1 = mash(" ");
+            me.s2 = mash(" ");
+            me.s0 -= mash(seed);
+            if (me.s0 < 0) {
+              me.s0 += 1;
+            }
+            me.s1 -= mash(seed);
+            if (me.s1 < 0) {
+              me.s1 += 1;
+            }
+            me.s2 -= mash(seed);
+            if (me.s2 < 0) {
+              me.s2 += 1;
+            }
+            mash = null;
+          }
+
+          function copy(f, t) {
+            t.c = f.c;
+            t.s0 = f.s0;
+            t.s1 = f.s1;
+            t.s2 = f.s2;
+            return t;
+          }
+
+          function impl(seed, opts) {
+            var xg = new Alea(seed),
+              state = opts && opts.state,
+              prng = xg.next;
+            prng.int32 = function () {
+              return (xg.next() * 0x100000000) | 0;
+            };
+            prng.double = function () {
+              return prng() + ((prng() * 0x200000) | 0) * 1.1102230246251565e-16; // 2^-53
+            };
+            prng.quick = prng;
+            if (state) {
+              if (typeof state == "object") copy(state, xg);
+              prng.state = function () {
+                return copy(xg, {});
+              };
+            }
+            return prng;
+          }
+
+          function Mash() {
+            var n = 0xefc8249d;
+
+            var mash = function (data) {
+              data = data.toString();
+              for (var i = 0; i < data.length; i++) {
+                n += data.charCodeAt(i);
+                var h = 0.02519603282416938 * n;
+                n = h >>> 0;
+                h -= n;
+                h *= n;
+                n = h >>> 0;
+                h -= n;
+                n += h * 0x100000000; // 2^32
+              }
+              return (n >>> 0) * 2.3283064365386963e-10; // 2^-32
+            };
+
+            return mash;
+          }
+
+          if (module && module.exports) {
+            module.exports = impl;
+          } else if (__webpack_require__(16) && __webpack_require__(29)) {
+            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
+              return impl;
+            }.call(exports, __webpack_require__, exports, module)),
+            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
+              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
+          } else {
+            this.alea = impl;
+          }
+        })(
+          this,
+          true && module, // present in node.js
+          __webpack_require__(16) // present with an AMD loader
+        );
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(28)(module)));
+
+      /***/
+    },
+    /* 69 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (module) {
+        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of the "xor128" prng algorithm by
+        // George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper
+
+        (function (global, module, define) {
+          function XorGen(seed) {
+            var me = this,
+              strseed = "";
+
+            me.x = 0;
+            me.y = 0;
+            me.z = 0;
+            me.w = 0;
+
+            // Set up generator function.
+            me.next = function () {
+              var t = me.x ^ (me.x << 11);
+              me.x = me.y;
+              me.y = me.z;
+              me.z = me.w;
+              return (me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8));
+            };
+
+            if (seed === (seed | 0)) {
+              // Integer seed.
+              me.x = seed;
+            } else {
+              // String seed.
+              strseed += seed;
+            }
+
+            // Mix in string seed, then discard an initial batch of 64 values.
+            for (var k = 0; k < strseed.length + 64; k++) {
+              me.x ^= strseed.charCodeAt(k) | 0;
+              me.next();
+            }
+          }
+
+          function copy(f, t) {
+            t.x = f.x;
+            t.y = f.y;
+            t.z = f.z;
+            t.w = f.w;
+            return t;
+          }
+
+          function impl(seed, opts) {
+            var xg = new XorGen(seed),
+              state = opts && opts.state,
+              prng = function () {
+                return (xg.next() >>> 0) / 0x100000000;
+              };
+            prng.double = function () {
+              do {
+                var top = xg.next() >>> 11,
+                  bot = (xg.next() >>> 0) / 0x100000000,
+                  result = (top + bot) / (1 << 21);
+              } while (result === 0);
+              return result;
+            };
+            prng.int32 = xg.next;
+            prng.quick = prng;
+            if (state) {
+              if (typeof state == "object") copy(state, xg);
+              prng.state = function () {
+                return copy(xg, {});
+              };
+            }
+            return prng;
+          }
+
+          if (module && module.exports) {
+            module.exports = impl;
+          } else if (__webpack_require__(16) && __webpack_require__(29)) {
+            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
+              return impl;
+            }.call(exports, __webpack_require__, exports, module)),
+            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
+              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
+          } else {
+            this.xor128 = impl;
+          }
+        })(
+          this,
+          true && module, // present in node.js
+          __webpack_require__(16) // present with an AMD loader
+        );
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(28)(module)));
+
+      /***/
+    },
+    /* 70 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (module) {
+        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of the "xorwow" prng algorithm by
+        // George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper
+
+        (function (global, module, define) {
+          function XorGen(seed) {
+            var me = this,
+              strseed = "";
+
+            // Set up generator function.
+            me.next = function () {
+              var t = me.x ^ (me.x >>> 2);
+              me.x = me.y;
+              me.y = me.z;
+              me.z = me.w;
+              me.w = me.v;
+              return (
+                ((me.d = (me.d + 362437) | 0) + (me.v = me.v ^ (me.v << 4) ^ (t ^ (t << 1)))) | 0
+              );
+            };
+
+            me.x = 0;
+            me.y = 0;
+            me.z = 0;
+            me.w = 0;
+            me.v = 0;
+
+            if (seed === (seed | 0)) {
+              // Integer seed.
+              me.x = seed;
+            } else {
+              // String seed.
+              strseed += seed;
+            }
+
+            // Mix in string seed, then discard an initial batch of 64 values.
+            for (var k = 0; k < strseed.length + 64; k++) {
+              me.x ^= strseed.charCodeAt(k) | 0;
+              if (k == strseed.length) {
+                me.d = (me.x << 10) ^ (me.x >>> 4);
+              }
+              me.next();
+            }
+          }
+
+          function copy(f, t) {
+            t.x = f.x;
+            t.y = f.y;
+            t.z = f.z;
+            t.w = f.w;
+            t.v = f.v;
+            t.d = f.d;
+            return t;
+          }
+
+          function impl(seed, opts) {
+            var xg = new XorGen(seed),
+              state = opts && opts.state,
+              prng = function () {
+                return (xg.next() >>> 0) / 0x100000000;
+              };
+            prng.double = function () {
+              do {
+                var top = xg.next() >>> 11,
+                  bot = (xg.next() >>> 0) / 0x100000000,
+                  result = (top + bot) / (1 << 21);
+              } while (result === 0);
+              return result;
+            };
+            prng.int32 = xg.next;
+            prng.quick = prng;
+            if (state) {
+              if (typeof state == "object") copy(state, xg);
+              prng.state = function () {
+                return copy(xg, {});
+              };
+            }
+            return prng;
+          }
+
+          if (module && module.exports) {
+            module.exports = impl;
+          } else if (__webpack_require__(16) && __webpack_require__(29)) {
+            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
+              return impl;
+            }.call(exports, __webpack_require__, exports, module)),
+            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
+              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
+          } else {
+            this.xorwow = impl;
+          }
+        })(
+          this,
+          true && module, // present in node.js
+          __webpack_require__(16) // present with an AMD loader
+        );
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(28)(module)));
+
+      /***/
+    },
+    /* 71 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (module) {
+        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of the "xorshift7" algorithm by
+        // François Panneton and Pierre L'ecuyer:
+        // "On the Xorgshift Random Number Generators"
+        // http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf
+
+        (function (global, module, define) {
+          function XorGen(seed) {
+            var me = this;
+
+            // Set up generator function.
+            me.next = function () {
+              // Update xor generator.
+              var X = me.x,
+                i = me.i,
+                t,
+                v,
+                w;
+              t = X[i];
+              t ^= t >>> 7;
+              v = t ^ (t << 24);
+              t = X[(i + 1) & 7];
+              v ^= t ^ (t >>> 10);
+              t = X[(i + 3) & 7];
+              v ^= t ^ (t >>> 3);
+              t = X[(i + 4) & 7];
+              v ^= t ^ (t << 7);
+              t = X[(i + 7) & 7];
+              t = t ^ (t << 13);
+              v ^= t ^ (t << 9);
+              X[i] = v;
+              me.i = (i + 1) & 7;
+              return v;
+            };
+
+            function init(me, seed) {
+              var j,
+                w,
+                X = [];
+
+              if (seed === (seed | 0)) {
+                // Seed state array using a 32-bit integer.
+                w = X[0] = seed;
+              } else {
+                // Seed state using a string.
+                seed = "" + seed;
+                for (j = 0; j < seed.length; ++j) {
+                  X[j & 7] = (X[j & 7] << 15) ^ ((seed.charCodeAt(j) + X[(j + 1) & 7]) << 13);
+                }
+              }
+              // Enforce an array length of 8, not all zeroes.
+              while (X.length < 8) X.push(0);
+              for (j = 0; j < 8 && X[j] === 0; ++j);
+              if (j == 8) w = X[7] = -1;
+              else w = X[j];
+
+              me.x = X;
+              me.i = 0;
+
+              // Discard an initial 256 values.
+              for (j = 256; j > 0; --j) {
+                me.next();
+              }
+            }
+
+            init(me, seed);
+          }
+
+          function copy(f, t) {
+            t.x = f.x.slice();
+            t.i = f.i;
+            return t;
+          }
+
+          function impl(seed, opts) {
+            if (seed == null) seed = +new Date();
+            var xg = new XorGen(seed),
+              state = opts && opts.state,
+              prng = function () {
+                return (xg.next() >>> 0) / 0x100000000;
+              };
+            prng.double = function () {
+              do {
+                var top = xg.next() >>> 11,
+                  bot = (xg.next() >>> 0) / 0x100000000,
+                  result = (top + bot) / (1 << 21);
+              } while (result === 0);
+              return result;
+            };
+            prng.int32 = xg.next;
+            prng.quick = prng;
+            if (state) {
+              if (state.x) copy(state, xg);
+              prng.state = function () {
+                return copy(xg, {});
+              };
+            }
+            return prng;
+          }
+
+          if (module && module.exports) {
+            module.exports = impl;
+          } else if (__webpack_require__(16) && __webpack_require__(29)) {
+            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
+              return impl;
+            }.call(exports, __webpack_require__, exports, module)),
+            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
+              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
+          } else {
+            this.xorshift7 = impl;
+          }
+        })(
+          this,
+          true && module, // present in node.js
+          __webpack_require__(16) // present with an AMD loader
+        );
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(28)(module)));
+
+      /***/
+    },
+    /* 72 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (module) {
+        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.
+        //
+        // This fast non-cryptographic random number generator is designed for
+        // use in Monte-Carlo algorithms. It combines a long-period xorshift
+        // generator with a Weyl generator, and it passes all common batteries
+        // of stasticial tests for randomness while consuming only a few nanoseconds
+        // for each prng generated.  For background on the generator, see Brent's
+        // paper: "Some long-period random number generators using shifts and xors."
+        // http://arxiv.org/pdf/1004.3115v1.pdf
+        //
+        // Usage:
+        //
+        // var xor4096 = require('xor4096');
+        // random = xor4096(1);                        // Seed with int32 or string.
+        // assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.
+        // assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.
+        //
+        // For nonzero numeric keys, this impelementation provides a sequence
+        // identical to that by Brent's xorgens 3 implementaion in C.  This
+        // implementation also provides for initalizing the generator with
+        // string seeds, or for saving and restoring the state of the generator.
+        //
+        // On Chrome, this prng benchmarks about 2.1 times slower than
+        // Javascript's built-in Math.random().
+
+        (function (global, module, define) {
+          function XorGen(seed) {
+            var me = this;
+
+            // Set up generator function.
+            me.next = function () {
+              var w = me.w,
+                X = me.X,
+                i = me.i,
+                t,
+                v;
+              // Update Weyl generator.
+              me.w = w = (w + 0x61c88647) | 0;
+              // Update xor generator.
+              v = X[(i + 34) & 127];
+              t = X[(i = (i + 1) & 127)];
+              v ^= v << 13;
+              t ^= t << 17;
+              v ^= v >>> 15;
+              t ^= t >>> 12;
+              // Update Xor generator array state.
+              v = X[i] = v ^ t;
+              me.i = i;
+              // Result is the combination.
+              return (v + (w ^ (w >>> 16))) | 0;
+            };
+
+            function init(me, seed) {
+              var t,
+                v,
+                i,
+                j,
+                w,
+                X = [],
+                limit = 128;
+              if (seed === (seed | 0)) {
+                // Numeric seeds initialize v, which is used to generates X.
+                v = seed;
+                seed = null;
+              } else {
+                // String seeds are mixed into v and X one character at a time.
+                seed = seed + "\0";
+                v = 0;
+                limit = Math.max(limit, seed.length);
+              }
+              // Initialize circular array and weyl value.
+              for (i = 0, j = -32; j < limit; ++j) {
+                // Put the unicode characters into the array, and shuffle them.
+                if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);
+                // After 32 shuffles, take v as the starting w value.
+                if (j === 0) w = v;
+                v ^= v << 10;
+                v ^= v >>> 15;
+                v ^= v << 4;
+                v ^= v >>> 13;
+                if (j >= 0) {
+                  w = (w + 0x61c88647) | 0; // Weyl.
+                  t = X[j & 127] ^= v + w; // Combine xor and weyl to init array.
+                  i = 0 == t ? i + 1 : 0; // Count zeroes.
+                }
+              }
+              // We have detected all zeroes; make the key nonzero.
+              if (i >= 128) {
+                X[((seed && seed.length) || 0) & 127] = -1;
+              }
+              // Run the generator 512 times to further mix the state before using it.
+              // Factoring this as a function slows the main generator, so it is just
+              // unrolled here.  The weyl generator is not advanced while warming up.
+              i = 127;
+              for (j = 4 * 128; j > 0; --j) {
+                v = X[(i + 34) & 127];
+                t = X[(i = (i + 1) & 127)];
+                v ^= v << 13;
+                t ^= t << 17;
+                v ^= v >>> 15;
+                t ^= t >>> 12;
+                X[i] = v ^ t;
+              }
+              // Storing state as object members is faster than using closure variables.
+              me.w = w;
+              me.X = X;
+              me.i = i;
+            }
+
+            init(me, seed);
+          }
+
+          function copy(f, t) {
+            t.i = f.i;
+            t.w = f.w;
+            t.X = f.X.slice();
+            return t;
+          }
+
+          function impl(seed, opts) {
+            if (seed == null) seed = +new Date();
+            var xg = new XorGen(seed),
+              state = opts && opts.state,
+              prng = function () {
+                return (xg.next() >>> 0) / 0x100000000;
+              };
+            prng.double = function () {
+              do {
+                var top = xg.next() >>> 11,
+                  bot = (xg.next() >>> 0) / 0x100000000,
+                  result = (top + bot) / (1 << 21);
+              } while (result === 0);
+              return result;
+            };
+            prng.int32 = xg.next;
+            prng.quick = prng;
+            if (state) {
+              if (state.X) copy(state, xg);
+              prng.state = function () {
+                return copy(xg, {});
+              };
+            }
+            return prng;
+          }
+
+          if (module && module.exports) {
+            module.exports = impl;
+          } else if (__webpack_require__(16) && __webpack_require__(29)) {
+            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
+              return impl;
+            }.call(exports, __webpack_require__, exports, module)),
+            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
+              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
+          } else {
+            this.xor4096 = impl;
+          }
+        })(
+          this, // window object or global
+          true && module, // present in node.js
+          __webpack_require__(16) // present with an AMD loader
+        );
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(28)(module)));
+
+      /***/
+    },
+    /* 73 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (module) {
+        var __WEBPACK_AMD_DEFINE_RESULT__; // A Javascript implementaion of the "Tyche-i" prng algorithm by
+        // Samuel Neves and Filipe Araujo.
+        // See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf
+
+        (function (global, module, define) {
+          function XorGen(seed) {
+            var me = this,
+              strseed = "";
+
+            // Set up generator function.
+            me.next = function () {
+              var b = me.b,
+                c = me.c,
+                d = me.d,
+                a = me.a;
+              b = (b << 25) ^ (b >>> 7) ^ c;
+              c = (c - d) | 0;
+              d = (d << 24) ^ (d >>> 8) ^ a;
+              a = (a - b) | 0;
+              me.b = b = (b << 20) ^ (b >>> 12) ^ c;
+              me.c = c = (c - d) | 0;
+              me.d = (d << 16) ^ (c >>> 16) ^ a;
+              return (me.a = (a - b) | 0);
+            };
+
+            /* The following is non-inverted tyche, which has better internal
+   * bit diffusion, but which is about 25% slower than tyche-i in JS.
+  me.next = function() {
+    var a = me.a, b = me.b, c = me.c, d = me.d;
+    a = (me.a + me.b | 0) >>> 0;
+    d = me.d ^ a; d = d << 16 ^ d >>> 16;
+    c = me.c + d | 0;
+    b = me.b ^ c; b = b << 12 ^ d >>> 20;
+    me.a = a = a + b | 0;
+    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;
+    me.c = c = c + d | 0;
+    b = b ^ c;
+    return me.b = (b << 7 ^ b >>> 25);
+  }
+  */
+
+            me.a = 0;
+            me.b = 0;
+            me.c = 2654435769 | 0;
+            me.d = 1367130551;
+
+            if (seed === Math.floor(seed)) {
+              // Integer seed.
+              me.a = (seed / 0x100000000) | 0;
+              me.b = seed | 0;
+            } else {
+              // String seed.
+              strseed += seed;
+            }
+
+            // Mix in string seed, then discard an initial batch of 64 values.
+            for (var k = 0; k < strseed.length + 20; k++) {
+              me.b ^= strseed.charCodeAt(k) | 0;
+              me.next();
+            }
+          }
+
+          function copy(f, t) {
+            t.a = f.a;
+            t.b = f.b;
+            t.c = f.c;
+            t.d = f.d;
+            return t;
+          }
+
+          function impl(seed, opts) {
+            var xg = new XorGen(seed),
+              state = opts && opts.state,
+              prng = function () {
+                return (xg.next() >>> 0) / 0x100000000;
+              };
+            prng.double = function () {
+              do {
+                var top = xg.next() >>> 11,
+                  bot = (xg.next() >>> 0) / 0x100000000,
+                  result = (top + bot) / (1 << 21);
+              } while (result === 0);
+              return result;
+            };
+            prng.int32 = xg.next;
+            prng.quick = prng;
+            if (state) {
+              if (typeof state == "object") copy(state, xg);
+              prng.state = function () {
+                return copy(xg, {});
+              };
+            }
+            return prng;
+          }
+
+          if (module && module.exports) {
+            module.exports = impl;
+          } else if (__webpack_require__(16) && __webpack_require__(29)) {
+            !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
+              return impl;
+            }.call(exports, __webpack_require__, exports, module)),
+            __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
+              (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
+          } else {
+            this.tychei = impl;
+          }
+        })(
+          this,
+          true && module, // present in node.js
+          __webpack_require__(16) // present with an AMD loader
+        );
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(28)(module)));
+
+      /***/
+    },
+    /* 74 */
+    /***/ function (module, exports, __webpack_require__) {
+      var __WEBPACK_AMD_DEFINE_RESULT__; /*
+Copyright 2014 David Bau.
+
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be
+included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+*/
+
+      (function (pool, math) {
+        //
+        // The following constants are related to IEEE 754 limits.
+        //
+        var global = this,
+          width = 256, // each RC4 output is 0 <= x < 256
+          chunks = 6, // at least six RC4 outputs for each double
+          digits = 52, // there are 52 significant digits in a double
+          rngname = "random", // rngname: name for Math.random and Math.seedrandom
+          startdenom = math.pow(width, chunks),
+          significance = math.pow(2, digits),
+          overflow = significance * 2,
+          mask = width - 1,
+          nodecrypto; // node.js crypto module, initialized at the bottom.
+
+        //
+        // seedrandom()
+        // This is the seedrandom function described above.
+        //
+        function seedrandom(seed, options, callback) {
+          var key = [];
+          options = options == true ? { entropy: true } : options || {};
+
+          // Flatten the seed string or build one from local entropy if needed.
+          var shortseed = mixkey(
+            flatten(options.entropy ? [seed, tostring(pool)] : seed == null ? autoseed() : seed, 3),
+            key
+          );
+
+          // Use the seed to initialize an ARC4 generator.
+          var arc4 = new ARC4(key);
+
+          // This function returns a random double in [0, 1) that contains
+          // randomness in every bit of the mantissa of the IEEE 754 value.
+          var prng = function () {
+            var n = arc4.g(chunks), // Start with a numerator n < 2 ^ 48
+              d = startdenom, //   and denominator d = 2 ^ 48.
+              x = 0; //   and no 'extra last byte'.
+            while (n < significance) {
+              // Fill up all significant digits by
+              n = (n + x) * width; //   shifting numerator and
+              d *= width; //   denominator and generating a
+              x = arc4.g(1); //   new least-significant-byte.
+            }
+            while (n >= overflow) {
+              // To avoid rounding up, before adding
+              n /= 2; //   last byte, shift everything
+              d /= 2; //   right using integer math until
+              x >>>= 1; //   we have exactly the desired bits.
+            }
+            return (n + x) / d; // Form the number within [0, 1).
+          };
+
+          prng.int32 = function () {
+            return arc4.g(4) | 0;
+          };
+          prng.quick = function () {
+            return arc4.g(4) / 0x100000000;
+          };
+          prng.double = prng;
+
+          // Mix the randomness into accumulated entropy.
+          mixkey(tostring(arc4.S), pool);
+
+          // Calling convention: what to return as a function of prng, seed, is_math.
+          return (
+            options.pass ||
+            callback ||
+            function (prng, seed, is_math_call, state) {
+              if (state) {
+                // Load the arc4 state from the given state if it has an S array.
+                if (state.S) {
+                  copy(state, arc4);
+                }
+                // Only provide the .state method if requested via options.state.
+                prng.state = function () {
+                  return copy(arc4, {});
+                };
+              }
+
+              // If called as a method of Math (Math.seedrandom()), mutate
+              // Math.random because that is how seedrandom.js has worked since v1.0.
+              if (is_math_call) {
+                math[rngname] = prng;
+                return seed;
+              }
+
+              // Otherwise, it is a newer calling convention, so return the
+              // prng directly.
+              else return prng;
+            }
+          )(prng, shortseed, "global" in options ? options.global : this == math, options.state);
+        }
+        math["seed" + rngname] = seedrandom;
+
+        //
+        // ARC4
+        //
+        // An ARC4 implementation.  The constructor takes a key in the form of
+        // an array of at most (width) integers that should be 0 <= x < (width).
+        //
+        // The g(count) method returns a pseudorandom integer that concatenates
+        // the next (count) outputs from ARC4.  Its return value is a number x
+        // that is in the range 0 <= x < (width ^ count).
+        //
+        function ARC4(key) {
+          var t,
+            keylen = key.length,
+            me = this,
+            i = 0,
+            j = (me.i = me.j = 0),
+            s = (me.S = []);
+
+          // The empty key [] is treated as [0].
+          if (!keylen) {
+            key = [keylen++];
+          }
+
+          // Set up S using the standard key scheduling algorithm.
+          while (i < width) {
+            s[i] = i++;
+          }
+          for (i = 0; i < width; i++) {
+            s[i] = s[(j = mask & (j + key[i % keylen] + (t = s[i])))];
+            s[j] = t;
+          }
+
+          // The "g" method returns the next (count) outputs as one number.
+          (me.g = function (count) {
+            // Using instance members instead of closure state nearly doubles speed.
+            var t,
+              r = 0,
+              i = me.i,
+              j = me.j,
+              s = me.S;
+            while (count--) {
+              t = s[(i = mask & (i + 1))];
+              r = r * width + s[mask & ((s[i] = s[(j = mask & (j + t))]) + (s[j] = t))];
+            }
+            me.i = i;
+            me.j = j;
+            return r;
+            // For robust unpredictability, the function call below automatically
+            // discards an initial batch of values.  This is called RC4-drop[256].
+            // See http://google.com/search?q=rsa+fluhrer+response&btnI
+          })(width);
+        }
+
+        //
+        // copy()
+        // Copies internal state of ARC4 to or from a plain object.
+        //
+        function copy(f, t) {
+          t.i = f.i;
+          t.j = f.j;
+          t.S = f.S.slice();
+          return t;
+        }
+
+        //
+        // flatten()
+        // Converts an object tree to nested arrays of strings.
+        //
+        function flatten(obj, depth) {
+          var result = [],
+            typ = typeof obj,
+            prop;
+          if (depth && typ == "object") {
+            for (prop in obj) {
+              try {
+                result.push(flatten(obj[prop], depth - 1));
+              } catch (e) {}
+            }
+          }
+          return result.length ? result : typ == "string" ? obj : obj + "\0";
+        }
+
+        //
+        // mixkey()
+        // Mixes a string seed into a key that is an array of integers, and
+        // returns a shortened string seed that is equivalent to the result key.
+        //
+        function mixkey(seed, key) {
+          var stringseed = seed + "",
+            smear,
+            j = 0;
+          while (j < stringseed.length) {
+            key[mask & j] = mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));
+          }
+          return tostring(key);
+        }
+
+        //
+        // autoseed()
+        // Returns an object for autoseeding, using window.crypto and Node crypto
+        // module if available.
+        //
+        function autoseed() {
+          try {
+            var out;
+            if (nodecrypto && (out = nodecrypto.randomBytes)) {
+              // The use of 'out' to remember randomBytes makes tight minified code.
+              out = out(width);
+            } else {
+              out = new Uint8Array(width);
+              (global.crypto || global.msCrypto).getRandomValues(out);
+            }
+            return tostring(out);
+          } catch (e) {
+            var browser = global.navigator,
+              plugins = browser && browser.plugins;
+            return [+new Date(), global, plugins, global.screen, tostring(pool)];
+          }
+        }
+
+        //
+        // tostring()
+        // Converts an array of charcodes to a string
+        //
+        function tostring(a) {
+          return String.fromCharCode.apply(0, a);
+        }
+
+        //
+        // When seedrandom.js is loaded, we immediately mix a few bits
+        // from the built-in RNG into the entropy pool.  Because we do
+        // not want to interfere with deterministic PRNG state later,
+        // seedrandom will not call math.random on its own again after
+        // initialization.
+        //
+        mixkey(math.random(), pool);
+
+        //
+        // Nodejs and AMD support: export the implementation as a module using
+        // either convention.
+        //
+        if (true && module.exports) {
+          module.exports = seedrandom;
+          // When in node.js, try using crypto package for autoseeding.
+          try {
+            nodecrypto = __webpack_require__(75);
+          } catch (ex) {}
+        } else if (true) {
+          !((__WEBPACK_AMD_DEFINE_RESULT__ = function () {
+            return seedrandom;
+          }.call(exports, __webpack_require__, exports, module)),
+          __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
+            (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
+        }
+
+        // End anonymous scope, and pass initial values.
+      })(
+        [], // pool: entropy pool starts empty
+        Math // math: package containing random, pow, and seedrandom
+      );
+
+      /***/
+    },
+    /* 75 */
+    /***/ function (module, exports) {
+      /* (ignored) */
+      /***/
+    },
+    /* 76 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (global) {
+        var scope =
+          (typeof global !== "undefined" && global) ||
+          (typeof self !== "undefined" && self) ||
+          window;
+        var apply = Function.prototype.apply;
+
+        // DOM APIs, for completeness
+
+        exports.setTimeout = function () {
+          return new Timeout(apply.call(setTimeout, scope, arguments), clearTimeout);
+        };
+        exports.setInterval = function () {
+          return new Timeout(apply.call(setInterval, scope, arguments), clearInterval);
+        };
+        exports.clearTimeout = exports.clearInterval = function (timeout) {
+          if (timeout) {
+            timeout.close();
+          }
+        };
+
+        function Timeout(id, clearFn) {
+          this._id = id;
+          this._clearFn = clearFn;
+        }
+        Timeout.prototype.unref = Timeout.prototype.ref = function () {};
+        Timeout.prototype.close = function () {
+          this._clearFn.call(scope, this._id);
+        };
+
+        // Does not start the time, just sets up the members needed.
+        exports.enroll = function (item, msecs) {
+          clearTimeout(item._idleTimeoutId);
+          item._idleTimeout = msecs;
+        };
+
+        exports.unenroll = function (item) {
+          clearTimeout(item._idleTimeoutId);
+          item._idleTimeout = -1;
+        };
+
+        exports._unrefActive = exports.active = function (item) {
+          clearTimeout(item._idleTimeoutId);
+
+          var msecs = item._idleTimeout;
+          if (msecs >= 0) {
+            item._idleTimeoutId = setTimeout(function onTimeout() {
+              if (item._onTimeout) item._onTimeout();
+            }, msecs);
+          }
+        };
+
+        // setimmediate attaches itself to the global object
+        __webpack_require__(77);
+        // On some exotic environments, it's not clear which object `setimmediate` was
+        // able to install onto.  Search each possibility in the same order as the
+        // `setimmediate` library.
+        exports.setImmediate =
+          (typeof self !== "undefined" && self.setImmediate) ||
+          (typeof global !== "undefined" && global.setImmediate) ||
+          (this && this.setImmediate);
+        exports.clearImmediate =
+          (typeof self !== "undefined" && self.clearImmediate) ||
+          (typeof global !== "undefined" && global.clearImmediate) ||
+          (this && this.clearImmediate);
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(27)));
+
+      /***/
+    },
+    /* 77 */
+    /***/ function (module, exports, __webpack_require__) {
+      /* WEBPACK VAR INJECTION */ (function (global, process) {
+        (function (global, undefined) {
+          "use strict";
+
+          if (global.setImmediate) {
+            return;
+          }
+
+          var nextHandle = 1; // Spec says greater than zero
+          var tasksByHandle = {};
+          var currentlyRunningATask = false;
+          var doc = global.document;
+          var registerImmediate;
+
+          function setImmediate(callback) {
+            // Callback can either be a function or a string
+            if (typeof callback !== "function") {
+              callback = new Function("" + callback);
+            }
+            // Copy function arguments
+            var args = new Array(arguments.length - 1);
+            for (var i = 0; i < args.length; i++) {
+              args[i] = arguments[i + 1];
+            }
+            // Store and register the task
+            var task = { callback: callback, args: args };
+            tasksByHandle[nextHandle] = task;
+            registerImmediate(nextHandle);
+            return nextHandle++;
+          }
+
+          function clearImmediate(handle) {
+            delete tasksByHandle[handle];
+          }
+
+          function run(task) {
+            var callback = task.callback;
+            var args = task.args;
+            switch (args.length) {
+              case 0:
+                callback();
+                break;
+              case 1:
+                callback(args[0]);
+                break;
+              case 2:
+                callback(args[0], args[1]);
+                break;
+              case 3:
+                callback(args[0], args[1], args[2]);
+                break;
+              default:
+                callback.apply(undefined, args);
+                break;
+            }
+          }
+
+          function runIfPresent(handle) {
+            // From the spec: "Wait until any invocations of this algorithm started before this one have completed."
+            // So if we're currently running a task, we'll need to delay this invocation.
+            if (currentlyRunningATask) {
+              // Delay by doing a setTimeout. setImmediate was tried instead, but in Firefox 7 it generated a
+              // "too much recursion" error.
+              setTimeout(runIfPresent, 0, handle);
+            } else {
+              var task = tasksByHandle[handle];
+              if (task) {
+                currentlyRunningATask = true;
+                try {
+                  run(task);
+                } finally {
+                  clearImmediate(handle);
+                  currentlyRunningATask = false;
+                }
+              }
+            }
+          }
+
+          function installNextTickImplementation() {
+            registerImmediate = function (handle) {
+              process.nextTick(function () {
+                runIfPresent(handle);
+              });
+            };
+          }
+
+          function canUsePostMessage() {
+            // The test against `importScripts` prevents this implementation from being installed inside a web worker,
+            // where `global.postMessage` means something completely different and can't be used for this purpose.
+            if (global.postMessage && !global.importScripts) {
+              var postMessageIsAsynchronous = true;
+              var oldOnMessage = global.onmessage;
+              global.onmessage = function () {
+                postMessageIsAsynchronous = false;
+              };
+              global.postMessage("", "*");
+              global.onmessage = oldOnMessage;
+              return postMessageIsAsynchronous;
+            }
+          }
+
+          function installPostMessageImplementation() {
+            // Installs an event handler on `global` for the `message` event: see
+            // * https://developer.mozilla.org/en/DOM/window.postMessage
+            // * http://www.whatwg.org/specs/web-apps/current-work/multipage/comms.html#crossDocumentMessages
+
+            var messagePrefix = "setImmediate$" + Math.random() + "$";
+            var onGlobalMessage = function (event) {
+              if (
+                event.source === global &&
+                typeof event.data === "string" &&
+                event.data.indexOf(messagePrefix) === 0
+              ) {
+                runIfPresent(+event.data.slice(messagePrefix.length));
+              }
+            };
+
+            if (global.addEventListener) {
+              global.addEventListener("message", onGlobalMessage, false);
+            } else {
+              global.attachEvent("onmessage", onGlobalMessage);
+            }
+
+            registerImmediate = function (handle) {
+              global.postMessage(messagePrefix + handle, "*");
+            };
+          }
+
+          function installMessageChannelImplementation() {
+            var channel = new MessageChannel();
+            channel.port1.onmessage = function (event) {
+              var handle = event.data;
+              runIfPresent(handle);
+            };
+
+            registerImmediate = function (handle) {
+              channel.port2.postMessage(handle);
+            };
+          }
+
+          function installReadyStateChangeImplementation() {
+            var html = doc.documentElement;
+            registerImmediate = function (handle) {
+              // Create a <script> element; its readystatechange event will be fired asynchronously once it is inserted
+              // into the document. Do so, thus queuing up the task. Remember to clean up once it's been called.
+              var script = doc.createElement("script");
+              script.onreadystatechange = function () {
+                runIfPresent(handle);
+                script.onreadystatechange = null;
+                html.removeChild(script);
+                script = null;
+              };
+              html.appendChild(script);
+            };
+          }
+
+          function installSetTimeoutImplementation() {
+            registerImmediate = function (handle) {
+              setTimeout(runIfPresent, 0, handle);
+            };
+          }
+
+          // If supported, we should attach to the prototype of global, since that is where setTimeout et al. live.
+          var attachTo = Object.getPrototypeOf && Object.getPrototypeOf(global);
+          attachTo = attachTo && attachTo.setTimeout ? attachTo : global;
+
+          // Don't get fooled by e.g. browserify environments.
+          if ({}.toString.call(global.process) === "[object process]") {
+            // For Node.js before 0.9
+            installNextTickImplementation();
+          } else if (canUsePostMessage()) {
+            // For non-IE10 modern browsers
+            installPostMessageImplementation();
+          } else if (global.MessageChannel) {
+            // For web workers, where supported
+            installMessageChannelImplementation();
+          } else if (doc && "onreadystatechange" in doc.createElement("script")) {
+            // For IE 6–8
+            installReadyStateChangeImplementation();
+          } else {
+            // For older browsers
+            installSetTimeoutImplementation();
+          }
+
+          attachTo.setImmediate = setImmediate;
+          attachTo.clearImmediate = clearImmediate;
+        })(typeof self === "undefined" ? (typeof global === "undefined" ? this : global) : self);
+
+        /* WEBPACK VAR INJECTION */
+      }.call(this, __webpack_require__(27), __webpack_require__(35)));
+
+      /***/
+    },
+    /* 78 */
+    /***/ function (module, exports) {
+      /* (ignored) */
+      /***/
+    },
+    /* 79 */
+    /***/ function (module, exports) {
+      /* (ignored) */
+      /***/
+    },
+    /* 80 */
+    /***/ function (module, exports, __webpack_require__) {
+      var __WEBPACK_AMD_DEFINE_FACTORY__,
+        __WEBPACK_AMD_DEFINE_ARRAY__,
+        __WEBPACK_AMD_DEFINE_RESULT__;
+      (function (global, factory) {
+        if (true) {
+          !((__WEBPACK_AMD_DEFINE_ARRAY__ = [module]),
+          (__WEBPACK_AMD_DEFINE_FACTORY__ = factory),
+          (__WEBPACK_AMD_DEFINE_RESULT__ =
+            typeof __WEBPACK_AMD_DEFINE_FACTORY__ === "function"
+              ? __WEBPACK_AMD_DEFINE_FACTORY__.apply(exports, __WEBPACK_AMD_DEFINE_ARRAY__)
+              : __WEBPACK_AMD_DEFINE_FACTORY__),
+          __WEBPACK_AMD_DEFINE_RESULT__ !== undefined &&
+            (module.exports = __WEBPACK_AMD_DEFINE_RESULT__));
+        } else {
+          var mod;
+        }
+      })(this, function (module) {
+        "use strict";
+
+        function _defineProperty(obj, key, value) {
+          if (key in obj) {
+            Object.defineProperty(obj, key, {
+              value: value,
+              enumerable: true,
+              configurable: true,
+              writable: true,
+            });
+          } else {
+            obj[key] = value;
+          }
+
+          return obj;
+        }
+
+        var _extends =
+          Object.assign ||
+          function (target) {
+            for (var i = 1; i < arguments.length; i++) {
+              var source = arguments[i];
+
+              for (var key in source) {
+                if (Object.prototype.hasOwnProperty.call(source, key)) {
+                  target[key] = source[key];
+                }
+              }
+            }
+
+            return target;
+          };
+
+        function _toConsumableArray(arr) {
+          if (Array.isArray(arr)) {
+            for (var i = 0, arr2 = Array(arr.length); i < arr.length; i++) {
+              arr2[i] = arr[i];
+            }
+
+            return arr2;
+          } else {
+            return Array.from(arr);
+          }
+        }
+
+        var DEFAULT_OPTIONS = { order: 2, precision: 2, period: null };
+
+        /**
+         * Determine the coefficient of determination (r^2) of a fit from the observations
+         * and predictions.
+         *
+         * @param {Array<Array<number>>} data - Pairs of observed x-y values
+         * @param {Array<Array<number>>} results - Pairs of observed predicted x-y values
+         *
+         * @return {number} - The r^2 value, or NaN if one cannot be calculated.
+         */
+        function determinationCoefficient(data, results) {
+          var predictions = [];
+          var observations = [];
+
+          data.forEach(function (d, i) {
+            if (d[1] !== null) {
+              observations.push(d);
+              predictions.push(results[i]);
+            }
+          });
+
+          var sum = observations.reduce(function (a, observation) {
+            return a + observation[1];
+          }, 0);
+          var mean = sum / observations.length;
+
+          var ssyy = observations.reduce(function (a, observation) {
+            var difference = observation[1] - mean;
+            return a + difference * difference;
+          }, 0);
+
+          var sse = observations.reduce(function (accum, observation, index) {
+            var prediction = predictions[index];
+            var residual = observation[1] - prediction[1];
+            return accum + residual * residual;
+          }, 0);
+
+          return 1 - sse / ssyy;
+        }
+
+        /**
+         * Determine the solution of a system of linear equations A * x = b using
+         * Gaussian elimination.
+         *
+         * @param {Array<Array<number>>} input - A 2-d matrix of data in row-major form [ A | b ]
+         * @param {number} order - How many degrees to solve for
+         *
+         * @return {Array<number>} - Vector of normalized solution coefficients matrix (x)
+         */
+        function gaussianElimination(input, order) {
+          var matrix = input;
+          var n = input.length - 1;
+          var coefficients = [order];
+
+          for (var i = 0; i < n; i++) {
+            var maxrow = i;
+            for (var j = i + 1; j < n; j++) {
+              if (Math.abs(matrix[i][j]) > Math.abs(matrix[i][maxrow])) {
+                maxrow = j;
+              }
+            }
+
+            for (var k = i; k < n + 1; k++) {
+              var tmp = matrix[k][i];
+              matrix[k][i] = matrix[k][maxrow];
+              matrix[k][maxrow] = tmp;
+            }
+
+            for (var _j = i + 1; _j < n; _j++) {
+              for (var _k = n; _k >= i; _k--) {
+                matrix[_k][_j] -= (matrix[_k][i] * matrix[i][_j]) / matrix[i][i];
+              }
+            }
+          }
+
+          for (var _j2 = n - 1; _j2 >= 0; _j2--) {
+            var total = 0;
+            for (var _k2 = _j2 + 1; _k2 < n; _k2++) {
+              total += matrix[_k2][_j2] * coefficients[_k2];
+            }
+
+            coefficients[_j2] = (matrix[n][_j2] - total) / matrix[_j2][_j2];
+          }
+
+          return coefficients;
+        }
+
+        /**
+         * Round a number to a precision, specificed in number of decimal places
+         *
+         * @param {number} number - The number to round
+         * @param {number} precision - The number of decimal places to round to:
+         *                             > 0 means decimals, < 0 means powers of 10
+         *
+         *
+         * @return {numbr} - The number, rounded
+         */
+        function round(number, precision) {
+          var factor = Math.pow(10, precision);
+          return Math.round(number * factor) / factor;
+        }
+
+        /**
+         * The set of all fitting methods
+         *
+         * @namespace
+         */
+        var methods = {
+          linear: function linear(data, options) {
+            var sum = [0, 0, 0, 0, 0];
+            var len = 0;
+
+            for (var n = 0; n < data.length; n++) {
+              if (data[n][1] !== null) {
+                len++;
+                sum[0] += data[n][0];
+                sum[1] += data[n][1];
+                sum[2] += data[n][0] * data[n][0];
+                sum[3] += data[n][0] * data[n][1];
+                sum[4] += data[n][1] * data[n][1];
+              }
+            }
+
+            var run = len * sum[2] - sum[0] * sum[0];
+            var rise = len * sum[3] - sum[0] * sum[1];
+            var gradient = run === 0 ? 0 : round(rise / run, options.precision);
+            var intercept = round(sum[1] / len - (gradient * sum[0]) / len, options.precision);
+
+            var predict = function predict(x) {
+              return [
+                round(x, options.precision),
+                round(gradient * x + intercept, options.precision),
+              ];
+            };
+
+            var points = data.map(function (point) {
+              return predict(point[0]);
+            });
+
+            return {
+              points: points,
+              predict: predict,
+              equation: [gradient, intercept],
+              r2: round(determinationCoefficient(data, points), options.precision),
+              string:
+                intercept === 0 ? "y = " + gradient + "x" : "y = " + gradient + "x + " + intercept,
+            };
+          },
+          exponential: function exponential(data, options) {
+            var sum = [0, 0, 0, 0, 0, 0];
+
+            for (var n = 0; n < data.length; n++) {
+              if (data[n][1] !== null) {
+                sum[0] += data[n][0];
+                sum[1] += data[n][1];
+                sum[2] += data[n][0] * data[n][0] * data[n][1];
+                sum[3] += data[n][1] * Math.log(data[n][1]);
+                sum[4] += data[n][0] * data[n][1] * Math.log(data[n][1]);
+                sum[5] += data[n][0] * data[n][1];
+              }
+            }
+
+            var denominator = sum[1] * sum[2] - sum[5] * sum[5];
+            var a = Math.exp((sum[2] * sum[3] - sum[5] * sum[4]) / denominator);
+            var b = (sum[1] * sum[4] - sum[5] * sum[3]) / denominator;
+            var coeffA = round(a, options.precision);
+            var coeffB = round(b, options.precision);
+            var predict = function predict(x) {
+              return [
+                round(x, options.precision),
+                round(coeffA * Math.exp(coeffB * x), options.precision),
+              ];
+            };
+
+            var points = data.map(function (point) {
+              return predict(point[0]);
+            });
+
+            return {
+              points: points,
+              predict: predict,
+              equation: [coeffA, coeffB],
+              string: "y = " + coeffA + "e^(" + coeffB + "x)",
+              r2: round(determinationCoefficient(data, points), options.precision),
+            };
+          },
+          logarithmic: function logarithmic(data, options) {
+            var sum = [0, 0, 0, 0];
+            var len = data.length;
+
+            for (var n = 0; n < len; n++) {
+              if (data[n][1] !== null) {
+                sum[0] += Math.log(data[n][0]);
+                sum[1] += data[n][1] * Math.log(data[n][0]);
+                sum[2] += data[n][1];
+                sum[3] += Math.pow(Math.log(data[n][0]), 2);
+              }
+            }
+
+            var a = (len * sum[1] - sum[2] * sum[0]) / (len * sum[3] - sum[0] * sum[0]);
+            var coeffB = round(a, options.precision);
+            var coeffA = round((sum[2] - coeffB * sum[0]) / len, options.precision);
+
+            var predict = function predict(x) {
+              return [
+                round(x, options.precision),
+                round(round(coeffA + coeffB * Math.log(x), options.precision), options.precision),
+              ];
+            };
+
+            var points = data.map(function (point) {
+              return predict(point[0]);
+            });
+
+            return {
+              points: points,
+              predict: predict,
+              equation: [coeffA, coeffB],
+              string: "y = " + coeffA + " + " + coeffB + " ln(x)",
+              r2: round(determinationCoefficient(data, points), options.precision),
+            };
+          },
+          power: function power(data, options) {
+            var sum = [0, 0, 0, 0, 0];
+            var len = data.length;
+
+            for (var n = 0; n < len; n++) {
+              if (data[n][1] !== null) {
+                sum[0] += Math.log(data[n][0]);
+                sum[1] += Math.log(data[n][1]) * Math.log(data[n][0]);
+                sum[2] += Math.log(data[n][1]);
+                sum[3] += Math.pow(Math.log(data[n][0]), 2);
+              }
+            }
+
+            var b = (len * sum[1] - sum[0] * sum[2]) / (len * sum[3] - Math.pow(sum[0], 2));
+            var a = (sum[2] - b * sum[0]) / len;
+            var coeffA = round(Math.exp(a), options.precision);
+            var coeffB = round(b, options.precision);
+
+            var predict = function predict(x) {
+              return [
+                round(x, options.precision),
+                round(round(coeffA * Math.pow(x, coeffB), options.precision), options.precision),
+              ];
+            };
+
+            var points = data.map(function (point) {
+              return predict(point[0]);
+            });
+
+            return {
+              points: points,
+              predict: predict,
+              equation: [coeffA, coeffB],
+              string: "y = " + coeffA + "x^" + coeffB,
+              r2: round(determinationCoefficient(data, points), options.precision),
+            };
+          },
+          polynomial: function polynomial(data, options) {
+            var lhs = [];
+            var rhs = [];
+            var a = 0;
+            var b = 0;
+            var len = data.length;
+            var k = options.order + 1;
+
+            for (var i = 0; i < k; i++) {
+              for (var l = 0; l < len; l++) {
+                if (data[l][1] !== null) {
+                  a += Math.pow(data[l][0], i) * data[l][1];
+                }
+              }
+
+              lhs.push(a);
+              a = 0;
+
+              var c = [];
+              for (var j = 0; j < k; j++) {
+                for (var _l = 0; _l < len; _l++) {
+                  if (data[_l][1] !== null) {
+                    b += Math.pow(data[_l][0], i + j);
+                  }
+                }
+                c.push(b);
+                b = 0;
+              }
+              rhs.push(c);
+            }
+            rhs.push(lhs);
+
+            var coefficients = gaussianElimination(rhs, k).map(function (v) {
+              return round(v, options.precision);
+            });
+
+            var predict = function predict(x) {
+              return [
+                round(x, options.precision),
+                round(
+                  coefficients.reduce(function (sum, coeff, power) {
+                    return sum + coeff * Math.pow(x, power);
+                  }, 0),
+                  options.precision
+                ),
+              ];
+            };
+
+            var points = data.map(function (point) {
+              return predict(point[0]);
+            });
+
+            var string = "y = ";
+            for (var _i = coefficients.length - 1; _i >= 0; _i--) {
+              if (_i > 1) {
+                string += coefficients[_i] + "x^" + _i + " + ";
+              } else if (_i === 1) {
+                string += coefficients[_i] + "x + ";
+              } else {
+                string += coefficients[_i];
+              }
+            }
+
+            return {
+              string: string,
+              points: points,
+              predict: predict,
+              equation: [].concat(_toConsumableArray(coefficients)).reverse(),
+              r2: round(determinationCoefficient(data, points), options.precision),
+            };
+          },
+        };
+
+        function createWrapper() {
+          var reduce = function reduce(accumulator, name) {
+            return _extends(
+              {
+                _round: round,
+              },
+              accumulator,
+              _defineProperty({}, name, function (data, supplied) {
+                return methods[name](data, _extends({}, DEFAULT_OPTIONS, supplied));
+              })
+            );
+          };
+
+          return Object.keys(methods).reduce(reduce, {});
+        }
+
+        module.exports = createWrapper();
+      });
+
+      /***/
+    },
+    /* 81 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      __webpack_require__.r(__webpack_exports__);
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "load",
+        function () {
+          return load;
+        }
+      );
+      /* harmony export (binding) */ __webpack_require__.d(
+        __webpack_exports__,
+        "BlazeFaceModel",
+        function () {
+          return BlazeFaceModel;
+        }
+      );
+      /* harmony import */ var _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__ =
+        __webpack_require__(0);
+      /* harmony import */ var _tensorflow_tfjs_converter__WEBPACK_IMPORTED_MODULE_1__ =
+        __webpack_require__(38);
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const disposeBox = (t) => {
+          t.startEndTensor.dispose(), t.startPoint.dispose(), t.endPoint.dispose();
+        },
+        createBox = (t) => ({
+          startEndTensor: t,
+          startPoint: Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
+            t,
+            [0, 0],
+            [-1, 2]
+          ),
+          endPoint: Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
+            t,
+            [0, 2],
+            [-1, 2]
+          ),
+        }),
+        scaleBox = (t, o) => {
+          const s = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(
+              t.startPoint,
+              o
+            ),
+            e = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(t.endPoint, o),
+            i = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["concat2d"])([s, e], 1);
+          return createBox(i);
+        },
+        ANCHORS_CONFIG = { strides: [8, 16], anchors: [2, 6] },
+        NUM_LANDMARKS = 6;
+      function generateAnchors(t, o, s) {
+        const e = [];
+        for (let i = 0; i < s.strides.length; i++) {
+          const n = s.strides[i],
+            a = Math.floor((o + n - 1) / n),
+            r = Math.floor((t + n - 1) / n),
+            c = s.anchors[i];
+          for (let t = 0; t < a; t++) {
+            const o = n * (t + 0.5);
+            for (let t = 0; t < r; t++) {
+              const s = n * (t + 0.5);
+              for (let t = 0; t < c; t++) e.push([s, o]);
+            }
+          }
+        }
+        return e;
+      }
+      function decodeBounds(t, o, s) {
+        const e = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
+            t,
+            [0, 1],
+            [-1, 2]
+          ),
+          i = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["add"])(e, o),
+          n = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
+            t,
+            [0, 3],
+            [-1, 2]
+          ),
+          a = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["div"])(n, s),
+          r = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["div"])(i, s),
+          c = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["div"])(a, 2),
+          l = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(r, c),
+          d = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["add"])(r, c),
+          h = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(l, s),
+          p = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(d, s);
+        return Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["concat2d"])([h, p], 1);
+      }
+      function getInputTensorDimensions(t) {
+        return t instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]
+          ? [t.shape[0], t.shape[1]]
+          : [t.height, t.width];
+      }
+      function flipFaceHorizontal(t, o) {
+        let s, e, i;
+        if (
+          t.topLeft instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"] &&
+          t.bottomRight instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]
+        ) {
+          const [n, a] = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(() => [
+            Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["concat"])([
+              Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(
+                o - 1,
+                t.topLeft.slice(0, 1)
+              ),
+              t.topLeft.slice(1, 1),
+            ]),
+            Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["concat"])([
+              Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(
+                o - 1,
+                t.bottomRight.slice(0, 1)
+              ),
+              t.bottomRight.slice(1, 1),
+            ]),
+          ]);
+          (s = n),
+            (e = a),
+            null != t.landmarks &&
+              (i = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(() => {
+                const s = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(
+                    Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor1d"])([
+                      o - 1,
+                      0,
+                    ]),
+                    t.landmarks
+                  ),
+                  e = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor1d"])([
+                    1, -1,
+                  ]);
+                return Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(s, e);
+              }));
+        } else {
+          const [n, a] = t.topLeft,
+            [r, c] = t.bottomRight;
+          (s = [o - 1 - n, a]),
+            (e = [o - 1 - r, c]),
+            null != t.landmarks && (i = t.landmarks.map((t) => [o - 1 - t[0], t[1]]));
+        }
+        const n = { topLeft: s, bottomRight: e };
+        return (
+          null != i && (n.landmarks = i),
+          null != t.probability &&
+            (n.probability =
+              t.probability instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]
+                ? t.probability.clone()
+                : t.probability),
+          n
+        );
+      }
+      function scaleBoxFromPrediction(t, o) {
+        return Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(() => {
+          let s;
+          return (s = t.hasOwnProperty("box") ? t.box : t), scaleBox(s, o).startEndTensor.squeeze();
+        });
+      }
+      class BlazeFaceModel {
+        constructor(t, o, s, e, i, n) {
+          (this.blazeFaceModel = t),
+            (this.width = o),
+            (this.height = s),
+            (this.maxFaces = e),
+            (this.anchorsData = generateAnchors(o, s, ANCHORS_CONFIG)),
+            (this.anchors = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor2d"])(
+              this.anchorsData
+            )),
+            (this.inputSizeData = [o, s]),
+            (this.inputSize = Object(
+              _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor1d"]
+            )([o, s])),
+            (this.iouThreshold = i),
+            (this.scoreThreshold = n);
+        }
+        async getBoundingBoxes(t, o, s = !0) {
+          const [e, i, n] = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(
+              () => {
+                const o = t.resizeBilinear([this.width, this.height]),
+                  s = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["mul"])(
+                    Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sub"])(
+                      o.div(255),
+                      0.5
+                    ),
+                    2
+                  ),
+                  e = this.blazeFaceModel.predict(s).squeeze(),
+                  i = decodeBounds(e, this.anchors, this.inputSize),
+                  n = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
+                    e,
+                    [0, 0],
+                    [-1, 1]
+                  );
+                return [
+                  e,
+                  i,
+                  Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["sigmoid"])(
+                    n
+                  ).squeeze(),
+                ];
+              }
+            ),
+            a = console.warn;
+          console.warn = () => {};
+          const r = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["image"].nonMaxSuppression(
+            i,
+            n,
+            this.maxFaces,
+            this.iouThreshold,
+            this.scoreThreshold
+          );
+          console.warn = a;
+          const c = await r.array();
+          r.dispose();
+          let l = c.map((t) =>
+            Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(i, [t, 0], [1, -1])
+          );
+          o ||
+            (l = await Promise.all(
+              l.map(async (t) => {
+                const o = await t.array();
+                return t.dispose(), o;
+              })
+            ));
+          const d = t.shape[1],
+            h = t.shape[2];
+          let p;
+          p = o
+            ? Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["div"])(
+                [h, d],
+                this.inputSize
+              )
+            : [h / this.inputSizeData[0], d / this.inputSizeData[1]];
+          const u = [];
+          for (let t = 0; t < l.length; t++) {
+            const i = l[t],
+              a = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(() => {
+                const a = createBox(
+                  i instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"]
+                    ? i
+                    : Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tensor2d"])(i)
+                );
+                if (!s) return a;
+                const r = c[t];
+                let l;
+                return (
+                  (l = o ? this.anchors.slice([r, 0], [1, 2]) : this.anchorsData[r]),
+                  {
+                    box: a,
+                    landmarks: Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"])(
+                      e,
+                      [r, NUM_LANDMARKS - 1],
+                      [1, -1]
+                    )
+                      .squeeze()
+                      .reshape([NUM_LANDMARKS, -1]),
+                    probability: Object(
+                      _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["slice"]
+                    )(n, [r], [1]),
+                    anchor: l,
+                  }
+                );
+              });
+            u.push(a);
+          }
+          return i.dispose(), n.dispose(), e.dispose(), { boxes: u, scaleFactor: p };
+        }
+        async estimateFaces(t, o = !1, s = !1, e = !0) {
+          const [, i] = getInputTensorDimensions(t),
+            n = Object(_tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["tidy"])(
+              () => (
+                t instanceof _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["Tensor"] ||
+                  (t = _tensorflow_tfjs_core__WEBPACK_IMPORTED_MODULE_0__["browser"].fromPixels(t)),
+                t.toFloat().expandDims(0)
+              )
+            ),
+            { boxes: a, scaleFactor: r } = await this.getBoundingBoxes(n, o, e);
+          return (
+            n.dispose(),
+            o
+              ? a.map((t) => {
+                  const o = scaleBoxFromPrediction(t, r);
+                  let n = { topLeft: o.slice([0], [2]), bottomRight: o.slice([2], [2]) };
+                  if (e) {
+                    const { landmarks: o, probability: s, anchor: e } = t,
+                      i = o.add(e).mul(r);
+                    (n.landmarks = i), (n.probability = s);
+                  }
+                  return s && (n = flipFaceHorizontal(n, i)), n;
+                })
+              : Promise.all(
+                  a.map(async (t) => {
+                    const o = scaleBoxFromPrediction(t, r);
+                    let n;
+                    if (e) {
+                      const [s, e, i] = await Promise.all(
+                          [t.landmarks, o, t.probability].map(async (t) => t.array())
+                        ),
+                        a = t.anchor,
+                        [c, l] = r,
+                        d = s.map((t) => [(t[0] + a[0]) * c, (t[1] + a[1]) * l]);
+                      (n = {
+                        topLeft: e.slice(0, 2),
+                        bottomRight: e.slice(2),
+                        landmarks: d,
+                        probability: i,
+                      }),
+                        disposeBox(t.box),
+                        t.landmarks.dispose(),
+                        t.probability.dispose();
+                    } else {
+                      const t = await o.array();
+                      n = { topLeft: t.slice(0, 2), bottomRight: t.slice(2) };
+                    }
+                    return o.dispose(), s && (n = flipFaceHorizontal(n, i)), n;
+                  })
+                )
+          );
+        }
+      }
+      const BLAZEFACE_MODEL_URL = "https://tfhub.dev/tensorflow/tfjs-model/blazeface/1/default/1";
+      async function load({
+        maxFaces: t = 10,
+        inputWidth: o = 128,
+        inputHeight: s = 128,
+        iouThreshold: e = 0.3,
+        scoreThreshold: i = 0.75,
+      } = {}) {
+        const n = await Object(
+          _tensorflow_tfjs_converter__WEBPACK_IMPORTED_MODULE_1__["loadGraphModel"]
+        )(BLAZEFACE_MODEL_URL, { fromTFHub: !0 });
+        return new BlazeFaceModel(n, o, s, t, e, i);
+      }
+
+      /***/
+    },
+    /* 82 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+
+      Object.defineProperty(exports, "__esModule", { value: true });
+      exports.MESH_ANNOTATIONS = {
+        silhouette: [
+          10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288, 397, 365, 379, 378, 400, 377,
+          152, 148, 176, 149, 150, 136, 172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,
+        ],
+        lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],
+        lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],
+        lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],
+        lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],
+        rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],
+        rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],
+        rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],
+        rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],
+        rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],
+        rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],
+        rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],
+        rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],
+        rightEyebrowLower: [35, 124, 46, 53, 52, 65],
+        leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],
+        leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],
+        leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],
+        leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],
+        leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],
+        leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],
+        leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],
+        leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],
+        leftEyebrowLower: [265, 353, 276, 283, 282, 295],
+        midwayBetweenEyes: [168],
+        noseTip: [1],
+        noseBottom: [2],
+        noseRightCorner: [98],
+        noseLeftCorner: [327],
+        rightCheek: [205],
+        leftCheek: [425],
+      };
+      //# sourceMappingURL=keypoints.js.map
+
+      /***/
+    },
+    /* 83 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+
+      Object.defineProperty(exports, "__esModule", { value: true });
+      const tf = __webpack_require__(0);
+      const box_1 = __webpack_require__(84);
+      const LANDMARKS_COUNT = 468;
+      const UPDATE_REGION_OF_INTEREST_IOU_THRESHOLD = 0.25;
+      class Pipeline {
+        constructor(
+          boundingBoxDetector,
+          meshDetector,
+          meshWidth,
+          meshHeight,
+          maxContinuousChecks,
+          maxFaces
+        ) {
+          this.regionsOfInterest = [];
+          this.runsWithoutFaceDetector = 0;
+          this.boundingBoxDetector = boundingBoxDetector;
+          this.meshDetector = meshDetector;
+          this.meshWidth = meshWidth;
+          this.meshHeight = meshHeight;
+          this.maxContinuousChecks = maxContinuousChecks;
+          this.maxFaces = maxFaces;
+        }
+        async predict(input) {
+          if (this.shouldUpdateRegionsOfInterest()) {
+            const returnTensors = true;
+            const annotateFace = false;
+            const { boxes, scaleFactor } = await this.boundingBoxDetector.getBoundingBoxes(
+              input,
+              returnTensors,
+              annotateFace
+            );
+            if (boxes.length === 0) {
+              scaleFactor.dispose();
+              this.clearAllRegionsOfInterest();
+              return null;
+            }
+            const scaledBoxes = boxes.map((prediction) =>
+              box_1.enlargeBox(box_1.scaleBoxCoordinates(prediction, scaleFactor))
+            );
+            boxes.forEach(box_1.disposeBox);
+            this.updateRegionsOfInterest(scaledBoxes);
+            this.runsWithoutFaceDetector = 0;
+          } else {
+            this.runsWithoutFaceDetector++;
+          }
+          return tf.tidy(() => {
+            return this.regionsOfInterest.map((box, i) => {
+              const face = box_1
+                .cutBoxFromImageAndResize(box, input, [this.meshHeight, this.meshWidth])
+                .div(255);
+              const [, flag, coords] = this.meshDetector.predict(face);
+              const coordsReshaped = tf.reshape(coords, [-1, 3]);
+              const normalizedBox = tf.div(box_1.getBoxSize(box), [
+                this.meshWidth,
+                this.meshHeight,
+              ]);
+              const scaledCoords = tf
+                .mul(coordsReshaped, normalizedBox.concat(tf.tensor2d([1], [1, 1]), 1))
+                .add(box.startPoint.concat(tf.tensor2d([0], [1, 1]), 1));
+              const landmarksBox = this.calculateLandmarksBoundingBox(scaledCoords);
+              const previousBox = this.regionsOfInterest[i];
+              box_1.disposeBox(previousBox);
+              this.regionsOfInterest[i] = landmarksBox;
+              const prediction = {
+                coords: coordsReshaped,
+                scaledCoords,
+                box: landmarksBox,
+                flag: flag.squeeze(),
+              };
+              return prediction;
+            });
+          });
+        }
+        updateRegionsOfInterest(boxes) {
+          for (let i = 0; i < boxes.length; i++) {
+            const box = boxes[i];
+            const previousBox = this.regionsOfInterest[i];
+            let iou = 0;
+            if (previousBox && previousBox.startPoint) {
+              const [boxStartX, boxStartY, boxEndX, boxEndY] = box.startEndTensor.arraySync()[0];
+              const [previousBoxStartX, previousBoxStartY, previousBoxEndX, previousBoxEndY] =
+                previousBox.startEndTensor.arraySync()[0];
+              const xStartMax = Math.max(boxStartX, previousBoxStartX);
+              const yStartMax = Math.max(boxStartY, previousBoxStartY);
+              const xEndMin = Math.min(boxEndX, previousBoxEndX);
+              const yEndMin = Math.min(boxEndY, previousBoxEndY);
+              const intersection = (xEndMin - xStartMax) * (yEndMin - yStartMax);
+              const boxArea = (boxEndX - boxStartX) * (boxEndY - boxStartY);
+              const previousBoxArea =
+                (previousBoxEndX - previousBoxStartX) * (previousBoxEndY - boxStartY);
+              iou = intersection / (boxArea + previousBoxArea - intersection);
+            }
+            if (iou > UPDATE_REGION_OF_INTEREST_IOU_THRESHOLD) {
+              box_1.disposeBox(box);
+            } else {
+              this.regionsOfInterest[i] = box;
+              box_1.disposeBox(previousBox);
+            }
+          }
+          for (let i = boxes.length; i < this.regionsOfInterest.length; i++) {
+            box_1.disposeBox(this.regionsOfInterest[i]);
+          }
+          this.regionsOfInterest = this.regionsOfInterest.slice(0, boxes.length);
+        }
+        clearRegionOfInterest(index) {
+          if (this.regionsOfInterest[index] != null) {
+            box_1.disposeBox(this.regionsOfInterest[index]);
+            this.regionsOfInterest = [
+              ...this.regionsOfInterest.slice(0, index),
+              ...this.regionsOfInterest.slice(index + 1),
+            ];
+          }
+        }
+        clearAllRegionsOfInterest() {
+          for (let i = 0; i < this.regionsOfInterest.length; i++) {
+            box_1.disposeBox(this.regionsOfInterest[i]);
+          }
+          this.regionsOfInterest = [];
+        }
+        shouldUpdateRegionsOfInterest() {
+          const roisCount = this.regionsOfInterest.length;
+          const noROIs = roisCount === 0;
+          if (this.maxFaces === 1 || noROIs) {
+            return noROIs;
+          }
+          return (
+            roisCount !== this.maxFaces && this.runsWithoutFaceDetector >= this.maxContinuousChecks
+          );
+        }
+        calculateLandmarksBoundingBox(landmarks) {
+          const xs = landmarks.slice([0, 0], [LANDMARKS_COUNT, 1]);
+          const ys = landmarks.slice([0, 1], [LANDMARKS_COUNT, 1]);
+          const boxMinMax = tf.stack([xs.min(), ys.min(), xs.max(), ys.max()]);
+          const box = box_1.createBox(boxMinMax.expandDims(0));
+          return box_1.enlargeBox(box);
+        }
+      }
+      exports.Pipeline = Pipeline;
+      //# sourceMappingURL=pipeline.js.map
+
+      /***/
+    },
+    /* 84 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+
+      Object.defineProperty(exports, "__esModule", { value: true });
+      const tf = __webpack_require__(0);
+      function disposeBox(box) {
+        if (box != null && box.startPoint != null) {
+          box.startEndTensor.dispose();
+          box.startPoint.dispose();
+          box.endPoint.dispose();
+        }
+      }
+      exports.disposeBox = disposeBox;
+      function createBox(startEndTensor, startPoint, endPoint) {
+        return {
+          startEndTensor,
+          startPoint: startPoint != null ? startPoint : tf.slice(startEndTensor, [0, 0], [-1, 2]),
+          endPoint: endPoint != null ? endPoint : tf.slice(startEndTensor, [0, 2], [-1, 2]),
+        };
+      }
+      exports.createBox = createBox;
+      function scaleBoxCoordinates(box, factor) {
+        const newStart = tf.mul(box.startPoint, factor);
+        const newEnd = tf.mul(box.endPoint, factor);
+        return createBox(tf.concat2d([newStart, newEnd], 1));
+      }
+      exports.scaleBoxCoordinates = scaleBoxCoordinates;
+      function getBoxSize(box) {
+        return tf.tidy(() => {
+          const diff = tf.sub(box.endPoint, box.startPoint);
+          return tf.abs(diff);
+        });
+      }
+      exports.getBoxSize = getBoxSize;
+      function getBoxCenter(box) {
+        return tf.tidy(() => {
+          const halfSize = tf.div(tf.sub(box.endPoint, box.startPoint), 2);
+          return tf.add(box.startPoint, halfSize);
+        });
+      }
+      exports.getBoxCenter = getBoxCenter;
+      function cutBoxFromImageAndResize(box, image, cropSize) {
+        const height = image.shape[1];
+        const width = image.shape[2];
+        const xyxy = box.startEndTensor;
+        return tf.tidy(() => {
+          const yxyx = tf.concat2d(
+            [
+              xyxy.slice([0, 1], [-1, 1]),
+              xyxy.slice([0, 0], [-1, 1]),
+              xyxy.slice([0, 3], [-1, 1]),
+              xyxy.slice([0, 2], [-1, 1]),
+            ],
+            0
+          );
+          const roundedCoords = tf.div(yxyx.transpose(), [height, width, height, width]);
+          return tf.image.cropAndResize(image, roundedCoords, [0], cropSize);
+        });
+      }
+      exports.cutBoxFromImageAndResize = cutBoxFromImageAndResize;
+      function enlargeBox(box, factor = 1.5) {
+        return tf.tidy(() => {
+          const center = getBoxCenter(box);
+          const size = getBoxSize(box);
+          const newSize = tf.mul(tf.div(size, 2), factor);
+          const newStart = tf.sub(center, newSize);
+          const newEnd = tf.add(center, newSize);
+          return createBox(tf.concat2d([newStart, newEnd], 1), newStart, newEnd);
+        });
+      }
+      exports.enlargeBox = enlargeBox;
+      //# sourceMappingURL=box.js.map
+
+      /***/
+    },
+    /* 85 */
+    /***/ function (module, exports, __webpack_require__) {
+      "use strict";
+
+      Object.defineProperty(exports, "__esModule", { value: true });
+      exports.UV_COORDS = [
+        [0.499976992607117, 0.652534008026123],
+        [0.500025987625122, 0.547487020492554],
+        [0.499974012374878, 0.602371990680695],
+        [0.482113003730774, 0.471979022026062],
+        [0.500150978565216, 0.527155995368958],
+        [0.499909996986389, 0.498252987861633],
+        [0.499523013830185, 0.40106201171875],
+        [0.289712011814117, 0.380764007568359],
+        [0.499954998493195, 0.312398016452789],
+        [0.499987006187439, 0.269918978214264],
+        [0.500023007392883, 0.107050001621246],
+        [0.500023007392883, 0.666234016418457],
+        [0.5000159740448, 0.679224014282227],
+        [0.500023007392883, 0.692348003387451],
+        [0.499976992607117, 0.695277988910675],
+        [0.499976992607117, 0.70593398809433],
+        [0.499976992607117, 0.719385027885437],
+        [0.499976992607117, 0.737019002437592],
+        [0.499967992305756, 0.781370997428894],
+        [0.499816000461578, 0.562981009483337],
+        [0.473773002624512, 0.573909997940063],
+        [0.104906998574734, 0.254140973091125],
+        [0.365929991006851, 0.409575998783112],
+        [0.338757991790771, 0.41302502155304],
+        [0.311120003461838, 0.409460008144379],
+        [0.274657994508743, 0.389131009578705],
+        [0.393361985683441, 0.403706014156342],
+        [0.345234006643295, 0.344011008739471],
+        [0.370094001293182, 0.346076011657715],
+        [0.319321990013123, 0.347265005111694],
+        [0.297903001308441, 0.353591024875641],
+        [0.24779200553894, 0.410809993743896],
+        [0.396889001131058, 0.842755019664764],
+        [0.280097991228104, 0.375599980354309],
+        [0.106310002505779, 0.399955987930298],
+        [0.2099249958992, 0.391353011131287],
+        [0.355807989835739, 0.534406006336212],
+        [0.471751004457474, 0.65040397644043],
+        [0.474155008792877, 0.680191993713379],
+        [0.439785003662109, 0.657229006290436],
+        [0.414617002010345, 0.66654098033905],
+        [0.450374007225037, 0.680860996246338],
+        [0.428770989179611, 0.682690978050232],
+        [0.374971002340317, 0.727805018424988],
+        [0.486716985702515, 0.547628998756409],
+        [0.485300987958908, 0.527395009994507],
+        [0.257764995098114, 0.314490020275116],
+        [0.401223003864288, 0.455172002315521],
+        [0.429818987846375, 0.548614978790283],
+        [0.421351999044418, 0.533740997314453],
+        [0.276895999908447, 0.532056987285614],
+        [0.483370006084442, 0.499586999416351],
+        [0.33721199631691, 0.282882988452911],
+        [0.296391993761063, 0.293242990970612],
+        [0.169294998049736, 0.193813979625702],
+        [0.447580009698868, 0.302609980106354],
+        [0.392390012741089, 0.353887975215912],
+        [0.354490011930466, 0.696784019470215],
+        [0.067304998636246, 0.730105042457581],
+        [0.442739009857178, 0.572826027870178],
+        [0.457098007202148, 0.584792017936707],
+        [0.381974011659622, 0.694710969924927],
+        [0.392388999462128, 0.694203019142151],
+        [0.277076005935669, 0.271932005882263],
+        [0.422551989555359, 0.563233017921448],
+        [0.385919004678726, 0.281364023685455],
+        [0.383103013038635, 0.255840003490448],
+        [0.331431001424789, 0.119714021682739],
+        [0.229923993349075, 0.232002973556519],
+        [0.364500999450684, 0.189113974571228],
+        [0.229622006416321, 0.299540996551514],
+        [0.173287004232407, 0.278747975826263],
+        [0.472878992557526, 0.666198015213013],
+        [0.446828007698059, 0.668527007102966],
+        [0.422762006521225, 0.673889994621277],
+        [0.445307999849319, 0.580065965652466],
+        [0.388103008270264, 0.693961024284363],
+        [0.403039008378983, 0.706539988517761],
+        [0.403629004955292, 0.693953037261963],
+        [0.460041999816895, 0.557139039039612],
+        [0.431158006191254, 0.692366003990173],
+        [0.452181994915009, 0.692366003990173],
+        [0.475387006998062, 0.692366003990173],
+        [0.465828001499176, 0.779190003871918],
+        [0.472328990697861, 0.736225962638855],
+        [0.473087012767792, 0.717857003211975],
+        [0.473122000694275, 0.704625964164734],
+        [0.473033010959625, 0.695277988910675],
+        [0.427942007780075, 0.695277988910675],
+        [0.426479011774063, 0.703539967536926],
+        [0.423162013292313, 0.711845993995667],
+        [0.4183090031147, 0.720062971115112],
+        [0.390094995498657, 0.639572978019714],
+        [0.013953999616206, 0.560034036636353],
+        [0.499913990497589, 0.58014702796936],
+        [0.413199990987778, 0.69539999961853],
+        [0.409626007080078, 0.701822996139526],
+        [0.468080013990402, 0.601534962654114],
+        [0.422728985548019, 0.585985004901886],
+        [0.463079988956451, 0.593783974647522],
+        [0.37211999297142, 0.47341400384903],
+        [0.334562003612518, 0.496073007583618],
+        [0.411671012639999, 0.546965003013611],
+        [0.242175996303558, 0.14767599105835],
+        [0.290776997804642, 0.201445996761322],
+        [0.327338010072708, 0.256527006626129],
+        [0.399509996175766, 0.748921036720276],
+        [0.441727995872498, 0.261676013469696],
+        [0.429764986038208, 0.187834024429321],
+        [0.412198007106781, 0.108901023864746],
+        [0.288955003023148, 0.398952007293701],
+        [0.218936994671822, 0.435410976409912],
+        [0.41278201341629, 0.398970007896423],
+        [0.257135003805161, 0.355440020561218],
+        [0.427684992551804, 0.437960982322693],
+        [0.448339998722076, 0.536936044692993],
+        [0.178560003638268, 0.45755398273468],
+        [0.247308000922203, 0.457193970680237],
+        [0.286267012357712, 0.467674970626831],
+        [0.332827985286713, 0.460712015628815],
+        [0.368755996227264, 0.447206974029541],
+        [0.398963987827301, 0.432654976844788],
+        [0.476410001516342, 0.405806005001068],
+        [0.189241006970406, 0.523923993110657],
+        [0.228962004184723, 0.348950982093811],
+        [0.490725994110107, 0.562400996685028],
+        [0.404670000076294, 0.485132992267609],
+        [0.019469000399113, 0.401564002037048],
+        [0.426243007183075, 0.420431017875671],
+        [0.396993011236191, 0.548797011375427],
+        [0.266469985246658, 0.376977026462555],
+        [0.439121007919312, 0.51895797252655],
+        [0.032313998788595, 0.644356966018677],
+        [0.419054001569748, 0.387154996395111],
+        [0.462783008813858, 0.505746960639954],
+        [0.238978996872902, 0.779744982719421],
+        [0.198220998048782, 0.831938028335571],
+        [0.107550002634525, 0.540755033493042],
+        [0.183610007166862, 0.740257024765015],
+        [0.134409993886948, 0.333683013916016],
+        [0.385764002799988, 0.883153975009918],
+        [0.490967005491257, 0.579378008842468],
+        [0.382384985685349, 0.508572995662689],
+        [0.174399003386497, 0.397670984268188],
+        [0.318785011768341, 0.39623498916626],
+        [0.343364000320435, 0.400596976280212],
+        [0.396100014448166, 0.710216999053955],
+        [0.187885001301765, 0.588537991046906],
+        [0.430987000465393, 0.944064974784851],
+        [0.318993002176285, 0.898285031318665],
+        [0.266247987747192, 0.869701027870178],
+        [0.500023007392883, 0.190576016902924],
+        [0.499976992607117, 0.954452991485596],
+        [0.366169989109039, 0.398822009563446],
+        [0.393207013607025, 0.39553701877594],
+        [0.410373002290726, 0.391080021858215],
+        [0.194993004202843, 0.342101991176605],
+        [0.388664990663528, 0.362284004688263],
+        [0.365961998701096, 0.355970978736877],
+        [0.343364000320435, 0.355356991291046],
+        [0.318785011768341, 0.35834002494812],
+        [0.301414996385574, 0.363156020641327],
+        [0.058132998645306, 0.319076001644135],
+        [0.301414996385574, 0.387449026107788],
+        [0.499987989664078, 0.618434011936188],
+        [0.415838003158569, 0.624195992946625],
+        [0.445681989192963, 0.566076993942261],
+        [0.465844005346298, 0.620640993118286],
+        [0.49992299079895, 0.351523995399475],
+        [0.288718998432159, 0.819945991039276],
+        [0.335278987884521, 0.852819979190826],
+        [0.440512001514435, 0.902418971061707],
+        [0.128294005990028, 0.791940987110138],
+        [0.408771991729736, 0.373893976211548],
+        [0.455606997013092, 0.451801002025604],
+        [0.499877005815506, 0.908990025520325],
+        [0.375436991453171, 0.924192011356354],
+        [0.11421000212431, 0.615022003650665],
+        [0.448662012815475, 0.695277988910675],
+        [0.4480200111866, 0.704632043838501],
+        [0.447111994028091, 0.715808033943176],
+        [0.444831997156143, 0.730794012546539],
+        [0.430011987686157, 0.766808986663818],
+        [0.406787008047104, 0.685672998428345],
+        [0.400738000869751, 0.681069016456604],
+        [0.392399996519089, 0.677703022956848],
+        [0.367855995893478, 0.663918972015381],
+        [0.247923001646996, 0.601333022117615],
+        [0.452769994735718, 0.420849978923798],
+        [0.43639200925827, 0.359887003898621],
+        [0.416164010763168, 0.368713974952698],
+        [0.413385987281799, 0.692366003990173],
+        [0.228018000721931, 0.683571994304657],
+        [0.468268007040024, 0.352671027183533],
+        [0.411361992359161, 0.804327011108398],
+        [0.499989002943039, 0.469825029373169],
+        [0.479153990745544, 0.442654013633728],
+        [0.499974012374878, 0.439637005329132],
+        [0.432112008333206, 0.493588984012604],
+        [0.499886006116867, 0.866917014122009],
+        [0.49991300702095, 0.821729004383087],
+        [0.456548988819122, 0.819200992584229],
+        [0.344549000263214, 0.745438992977142],
+        [0.37890899181366, 0.574010014533997],
+        [0.374292999505997, 0.780184984207153],
+        [0.319687992334366, 0.570737957954407],
+        [0.357154995203018, 0.604269981384277],
+        [0.295284003019333, 0.621580958366394],
+        [0.447750002145767, 0.862477004528046],
+        [0.410986006259918, 0.508723020553589],
+        [0.31395098567009, 0.775308012962341],
+        [0.354128003120422, 0.812552988529205],
+        [0.324548006057739, 0.703992962837219],
+        [0.189096003770828, 0.646299958229065],
+        [0.279776990413666, 0.71465802192688],
+        [0.1338230073452, 0.682700991630554],
+        [0.336768001317978, 0.644733011722565],
+        [0.429883986711502, 0.466521978378296],
+        [0.455527991056442, 0.548622965812683],
+        [0.437114000320435, 0.558896005153656],
+        [0.467287987470627, 0.529924988746643],
+        [0.414712011814117, 0.335219979286194],
+        [0.37704598903656, 0.322777986526489],
+        [0.344107985496521, 0.320150971412659],
+        [0.312875986099243, 0.32233202457428],
+        [0.283526003360748, 0.333190023899078],
+        [0.241245999932289, 0.382785975933075],
+        [0.102986000478268, 0.468762993812561],
+        [0.267612010240555, 0.424560010433197],
+        [0.297879010438919, 0.433175981044769],
+        [0.333433985710144, 0.433878004550934],
+        [0.366427004337311, 0.426115989685059],
+        [0.396012008190155, 0.416696012020111],
+        [0.420121014118195, 0.41022801399231],
+        [0.007561000064015, 0.480777025222778],
+        [0.432949006557465, 0.569517970085144],
+        [0.458638995885849, 0.479089021682739],
+        [0.473466008901596, 0.545744001865387],
+        [0.476087987422943, 0.563830018043518],
+        [0.468472003936768, 0.555056989192963],
+        [0.433990985155106, 0.582361996173859],
+        [0.483518004417419, 0.562983989715576],
+        [0.482482999563217, 0.57784903049469],
+        [0.42645001411438, 0.389798998832703],
+        [0.438998997211456, 0.39649498462677],
+        [0.450067013502121, 0.400434017181396],
+        [0.289712011814117, 0.368252992630005],
+        [0.276670008897781, 0.363372981548309],
+        [0.517862021923065, 0.471948027610779],
+        [0.710287988185883, 0.380764007568359],
+        [0.526226997375488, 0.573909997940063],
+        [0.895093023777008, 0.254140973091125],
+        [0.634069979190826, 0.409575998783112],
+        [0.661242008209229, 0.41302502155304],
+        [0.688880026340485, 0.409460008144379],
+        [0.725341975688934, 0.389131009578705],
+        [0.606630027294159, 0.40370500087738],
+        [0.654766023159027, 0.344011008739471],
+        [0.629905998706818, 0.346076011657715],
+        [0.680678009986877, 0.347265005111694],
+        [0.702096998691559, 0.353591024875641],
+        [0.75221198797226, 0.410804986953735],
+        [0.602918028831482, 0.842862963676453],
+        [0.719901978969574, 0.375599980354309],
+        [0.893692970275879, 0.399959981441498],
+        [0.790081977844238, 0.391354024410248],
+        [0.643998026847839, 0.534487962722778],
+        [0.528249025344849, 0.65040397644043],
+        [0.525849997997284, 0.680191040039062],
+        [0.560214996337891, 0.657229006290436],
+        [0.585384011268616, 0.66654098033905],
+        [0.549625992774963, 0.680860996246338],
+        [0.57122802734375, 0.682691991329193],
+        [0.624852001667023, 0.72809898853302],
+        [0.513050019741058, 0.547281980514526],
+        [0.51509702205658, 0.527251958847046],
+        [0.742246985435486, 0.314507007598877],
+        [0.598631024360657, 0.454979002475739],
+        [0.570338010787964, 0.548575043678284],
+        [0.578631997108459, 0.533622980117798],
+        [0.723087012767792, 0.532054007053375],
+        [0.516445994377136, 0.499638974666595],
+        [0.662801027297974, 0.282917976379395],
+        [0.70362401008606, 0.293271005153656],
+        [0.830704987049103, 0.193813979625702],
+        [0.552385985851288, 0.302568018436432],
+        [0.607609987258911, 0.353887975215912],
+        [0.645429015159607, 0.696707010269165],
+        [0.932694971561432, 0.730105042457581],
+        [0.557260990142822, 0.572826027870178],
+        [0.542901992797852, 0.584792017936707],
+        [0.6180260181427, 0.694710969924927],
+        [0.607590973377228, 0.694203019142151],
+        [0.722943007946014, 0.271963000297546],
+        [0.577413976192474, 0.563166975975037],
+        [0.614082992076874, 0.281386971473694],
+        [0.616907000541687, 0.255886018276215],
+        [0.668509006500244, 0.119913995265961],
+        [0.770092010498047, 0.232020974159241],
+        [0.635536015033722, 0.189248979091644],
+        [0.77039098739624, 0.299556016921997],
+        [0.826722025871277, 0.278755009174347],
+        [0.527121007442474, 0.666198015213013],
+        [0.553171992301941, 0.668527007102966],
+        [0.577238023281097, 0.673889994621277],
+        [0.554691970348358, 0.580065965652466],
+        [0.611896991729736, 0.693961024284363],
+        [0.59696102142334, 0.706539988517761],
+        [0.596370995044708, 0.693953037261963],
+        [0.539958000183105, 0.557139039039612],
+        [0.568841993808746, 0.692366003990173],
+        [0.547818005084991, 0.692366003990173],
+        [0.52461302280426, 0.692366003990173],
+        [0.534089982509613, 0.779141008853912],
+        [0.527670979499817, 0.736225962638855],
+        [0.526912987232208, 0.717857003211975],
+        [0.526877999305725, 0.704625964164734],
+        [0.526966989040375, 0.695277988910675],
+        [0.572058022022247, 0.695277988910675],
+        [0.573521018028259, 0.703539967536926],
+        [0.57683801651001, 0.711845993995667],
+        [0.581691026687622, 0.720062971115112],
+        [0.609944999217987, 0.639909982681274],
+        [0.986046016216278, 0.560034036636353],
+        [0.5867999792099, 0.69539999961853],
+        [0.590372025966644, 0.701822996139526],
+        [0.531915009021759, 0.601536989212036],
+        [0.577268004417419, 0.585934996604919],
+        [0.536915004253387, 0.593786001205444],
+        [0.627542972564697, 0.473352015018463],
+        [0.665585994720459, 0.495950996875763],
+        [0.588353991508484, 0.546862006187439],
+        [0.757824003696442, 0.14767599105835],
+        [0.709249973297119, 0.201507985591888],
+        [0.672684013843536, 0.256581008434296],
+        [0.600408971309662, 0.74900496006012],
+        [0.55826598405838, 0.261672019958496],
+        [0.570303976535797, 0.187870979309082],
+        [0.588165998458862, 0.109044015407562],
+        [0.711045026779175, 0.398952007293701],
+        [0.781069993972778, 0.435405015945435],
+        [0.587247014045715, 0.398931980133057],
+        [0.742869973182678, 0.355445981025696],
+        [0.572156012058258, 0.437651991844177],
+        [0.55186802148819, 0.536570012569427],
+        [0.821442008018494, 0.457556009292603],
+        [0.752701997756958, 0.457181990146637],
+        [0.71375697851181, 0.467626988887787],
+        [0.66711300611496, 0.460672974586487],
+        [0.631101012229919, 0.447153985500336],
+        [0.6008620262146, 0.432473003864288],
+        [0.523481011390686, 0.405627012252808],
+        [0.810747981071472, 0.523926019668579],
+        [0.771045982837677, 0.348959028720856],
+        [0.509127020835876, 0.562718033790588],
+        [0.595292985439301, 0.485023975372314],
+        [0.980530977249146, 0.401564002037048],
+        [0.573499977588654, 0.420000016689301],
+        [0.602994978427887, 0.548687994480133],
+        [0.733529984951019, 0.376977026462555],
+        [0.560611009597778, 0.519016981124878],
+        [0.967685997486115, 0.644356966018677],
+        [0.580985009670258, 0.387160003185272],
+        [0.537728011608124, 0.505385041236877],
+        [0.760966002941132, 0.779752969741821],
+        [0.801778972148895, 0.831938028335571],
+        [0.892440974712372, 0.54076099395752],
+        [0.816350996494293, 0.740260004997253],
+        [0.865594983100891, 0.333687007427216],
+        [0.614073991775513, 0.883246004581451],
+        [0.508952975273132, 0.579437971115112],
+        [0.617941975593567, 0.508316040039062],
+        [0.825608015060425, 0.397674977779388],
+        [0.681214988231659, 0.39623498916626],
+        [0.656635999679565, 0.400596976280212],
+        [0.603900015354156, 0.710216999053955],
+        [0.81208598613739, 0.588539004325867],
+        [0.56801301240921, 0.944564998149872],
+        [0.681007981300354, 0.898285031318665],
+        [0.733752012252808, 0.869701027870178],
+        [0.633830010890961, 0.398822009563446],
+        [0.606792986392975, 0.39553701877594],
+        [0.589659988880157, 0.391062021255493],
+        [0.805015981197357, 0.342108011245728],
+        [0.611334979534149, 0.362284004688263],
+        [0.634037971496582, 0.355970978736877],
+        [0.656635999679565, 0.355356991291046],
+        [0.681214988231659, 0.35834002494812],
+        [0.698584973812103, 0.363156020641327],
+        [0.941866993904114, 0.319076001644135],
+        [0.698584973812103, 0.387449026107788],
+        [0.584177017211914, 0.624107003211975],
+        [0.554318010807037, 0.566076993942261],
+        [0.534153997898102, 0.62064003944397],
+        [0.711217999458313, 0.819975018501282],
+        [0.664629995822906, 0.852871000766754],
+        [0.559099972248077, 0.902631998062134],
+        [0.871706008911133, 0.791940987110138],
+        [0.591234028339386, 0.373893976211548],
+        [0.544341027736664, 0.451583981513977],
+        [0.624562978744507, 0.924192011356354],
+        [0.88577002286911, 0.615028977394104],
+        [0.551338016986847, 0.695277988910675],
+        [0.551980018615723, 0.704632043838501],
+        [0.552887976169586, 0.715808033943176],
+        [0.555167973041534, 0.730794012546539],
+        [0.569944024085999, 0.767035007476807],
+        [0.593203008174896, 0.685675978660583],
+        [0.599261999130249, 0.681069016456604],
+        [0.607599973678589, 0.677703022956848],
+        [0.631937980651855, 0.663500010967255],
+        [0.752032995223999, 0.601315021514893],
+        [0.547226011753082, 0.420395016670227],
+        [0.563543975353241, 0.359827995300293],
+        [0.583841025829315, 0.368713974952698],
+        [0.586614012718201, 0.692366003990173],
+        [0.771915018558502, 0.683578014373779],
+        [0.531597018241882, 0.352482974529266],
+        [0.588370978832245, 0.804440975189209],
+        [0.52079701423645, 0.442565023899078],
+        [0.567984998226166, 0.493479013442993],
+        [0.543282985687256, 0.819254994392395],
+        [0.655317008495331, 0.745514988899231],
+        [0.621008992195129, 0.574018001556396],
+        [0.625559985637665, 0.78031200170517],
+        [0.680198013782501, 0.570719003677368],
+        [0.64276397228241, 0.604337990283966],
+        [0.704662978649139, 0.621529996395111],
+        [0.552012026309967, 0.862591981887817],
+        [0.589071989059448, 0.508637011051178],
+        [0.685944974422455, 0.775357007980347],
+        [0.645735025405884, 0.812640011310577],
+        [0.675342977046967, 0.703978002071381],
+        [0.810858011245728, 0.646304965019226],
+        [0.72012197971344, 0.714666962623596],
+        [0.866151988506317, 0.682704985141754],
+        [0.663187026977539, 0.644596993923187],
+        [0.570082008838654, 0.466325998306274],
+        [0.544561982154846, 0.548375964164734],
+        [0.562758982181549, 0.558784961700439],
+        [0.531987011432648, 0.530140042304993],
+        [0.585271000862122, 0.335177004337311],
+        [0.622952997684479, 0.32277899980545],
+        [0.655896008014679, 0.320163011550903],
+        [0.687132000923157, 0.322345972061157],
+        [0.716481983661652, 0.333200991153717],
+        [0.758756995201111, 0.382786989212036],
+        [0.897013008594513, 0.468769013881683],
+        [0.732392013072968, 0.424547016620636],
+        [0.70211398601532, 0.433162987232208],
+        [0.66652500629425, 0.433866024017334],
+        [0.633504986763, 0.426087975502014],
+        [0.603875994682312, 0.416586995124817],
+        [0.579657971858978, 0.409945011138916],
+        [0.992439985275269, 0.480777025222778],
+        [0.567192018032074, 0.569419980049133],
+        [0.54136598110199, 0.478899002075195],
+        [0.526564002037048, 0.546118021011353],
+        [0.523913025856018, 0.563830018043518],
+        [0.531529009342194, 0.555056989192963],
+        [0.566035985946655, 0.582329034805298],
+        [0.51631098985672, 0.563053965568542],
+        [0.5174720287323, 0.577877044677734],
+        [0.573594987392426, 0.389806985855103],
+        [0.560697972774506, 0.395331978797913],
+        [0.549755990505219, 0.399751007556915],
+        [0.710287988185883, 0.368252992630005],
+        [0.723330020904541, 0.363372981548309],
+      ];
+      //# sourceMappingURL=uv_coords.js.map
+
+      /***/
+    },
+    /* 86 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      // ESM COMPAT FLAG
+      __webpack_require__.r(__webpack_exports__);
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "version_webgl", function () {
+        return /* reexport */ version_version;
+      });
+      __webpack_require__.d(__webpack_exports__, "MathBackendWebGL", function () {
+        return /* reexport */ backend_webgl_MathBackendWebGL;
+      });
+      __webpack_require__.d(__webpack_exports__, "setWebGLContext", function () {
+        return /* reexport */ setWebGLContext;
+      });
+      __webpack_require__.d(__webpack_exports__, "GPGPUContext", function () {
+        return /* reexport */ gpgpu_context_GPGPUContext;
+      });
+      __webpack_require__.d(__webpack_exports__, "gpgpu_util", function () {
+        return /* reexport */ gpgpu_util_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "webgl_util", function () {
+        return /* reexport */ webgl_util_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "forceHalfFloat", function () {
+        return /* reexport */ forceHalfFloat;
+      });
+      __webpack_require__.d(__webpack_exports__, "webgl", function () {
+        return /* binding */ webgl;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl_util.js
+      var webgl_util_namespaceObject = {};
+      __webpack_require__.r(webgl_util_namespaceObject);
+      __webpack_require__.d(webgl_util_namespaceObject, "callAndCheck", function () {
+        return callAndCheck;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "canBeRepresented", function () {
+        return canBeRepresented;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getWebGLErrorMessage", function () {
+        return getWebGLErrorMessage;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getExtensionOrThrow", function () {
+        return getExtensionOrThrow;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "createVertexShader", function () {
+        return createVertexShader;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "createFragmentShader", function () {
+        return createFragmentShader;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "createProgram", function () {
+        return createProgram;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "linkProgram", function () {
+        return linkProgram;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "validateProgram", function () {
+        return validateProgram;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "createStaticVertexBuffer", function () {
+        return createStaticVertexBuffer;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "createStaticIndexBuffer", function () {
+        return createStaticIndexBuffer;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getNumChannels", function () {
+        return getNumChannels;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "createTexture", function () {
+        return createTexture;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "validateTextureSize", function () {
+        return validateTextureSize;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "createFramebuffer", function () {
+        return createFramebuffer;
+      });
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "bindVertexBufferToProgramAttribute",
+        function () {
+          return bindVertexBufferToProgramAttribute;
+        }
+      );
+      __webpack_require__.d(webgl_util_namespaceObject, "bindTextureUnit", function () {
+        return bindTextureUnit;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "unbindTextureUnit", function () {
+        return unbindTextureUnit;
+      });
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "getProgramUniformLocationOrThrow",
+        function () {
+          return getProgramUniformLocationOrThrow;
+        }
+      );
+      __webpack_require__.d(webgl_util_namespaceObject, "getProgramUniformLocation", function () {
+        return getProgramUniformLocation;
+      });
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "bindTextureToProgramUniformSampler",
+        function () {
+          return bindTextureToProgramUniformSampler;
+        }
+      );
+      __webpack_require__.d(webgl_util_namespaceObject, "bindCanvasToFramebuffer", function () {
+        return bindCanvasToFramebuffer;
+      });
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "bindColorTextureToFramebuffer",
+        function () {
+          return bindColorTextureToFramebuffer;
+        }
+      );
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "unbindColorTextureFromFramebuffer",
+        function () {
+          return unbindColorTextureFromFramebuffer;
+        }
+      );
+      __webpack_require__.d(webgl_util_namespaceObject, "validateFramebuffer", function () {
+        return validateFramebuffer;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getFramebufferErrorMessage", function () {
+        return getFramebufferErrorMessage;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getBatchDim", function () {
+        return getBatchDim;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getRowsCols", function () {
+        return getRowsCols;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getShapeAs3D", function () {
+        return getShapeAs3D;
+      });
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "getTextureShapeFromLogicalShape",
+        function () {
+          return getTextureShapeFromLogicalShape;
+        }
+      );
+      __webpack_require__.d(webgl_util_namespaceObject, "isReshapeFree", function () {
+        return isReshapeFree;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getWebGLMaxTextureSize", function () {
+        return getWebGLMaxTextureSize;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "resetMaxTextureSize", function () {
+        return resetMaxTextureSize;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "resetMaxTexturesInShader", function () {
+        return resetMaxTexturesInShader;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "getMaxTexturesInShader", function () {
+        return getMaxTexturesInShader;
+      });
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "getWebGLDisjointQueryTimerVersion",
+        function () {
+          return getWebGLDisjointQueryTimerVersion;
+        }
+      );
+      __webpack_require__.d(webgl_util_namespaceObject, "hasExtension", function () {
+        return hasExtension;
+      });
+      __webpack_require__.d(webgl_util_namespaceObject, "isWebGLVersionEnabled", function () {
+        return isWebGLVersionEnabled;
+      });
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "isCapableOfRenderingToFloatTexture",
+        function () {
+          return isCapableOfRenderingToFloatTexture;
+        }
+      );
+      __webpack_require__.d(
+        webgl_util_namespaceObject,
+        "isDownloadFloatTextureEnabled",
+        function () {
+          return isDownloadFloatTextureEnabled;
+        }
+      );
+      __webpack_require__.d(webgl_util_namespaceObject, "isWebGLFenceEnabled", function () {
+        return isWebGLFenceEnabled;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_util.js
+      var gpgpu_util_namespaceObject = {};
+      __webpack_require__.r(gpgpu_util_namespaceObject);
+      __webpack_require__.d(gpgpu_util_namespaceObject, "createVertexShader", function () {
+        return gpgpu_util_createVertexShader;
+      });
+      __webpack_require__.d(gpgpu_util_namespaceObject, "createVertexBuffer", function () {
+        return createVertexBuffer;
+      });
+      __webpack_require__.d(gpgpu_util_namespaceObject, "createIndexBuffer", function () {
+        return createIndexBuffer;
+      });
+      __webpack_require__.d(gpgpu_util_namespaceObject, "createFloat32MatrixTexture", function () {
+        return createFloat32MatrixTexture;
+      });
+      __webpack_require__.d(gpgpu_util_namespaceObject, "createFloat16MatrixTexture", function () {
+        return createFloat16MatrixTexture;
+      });
+      __webpack_require__.d(
+        gpgpu_util_namespaceObject,
+        "createUnsignedBytesMatrixTexture",
+        function () {
+          return createUnsignedBytesMatrixTexture;
+        }
+      );
+      __webpack_require__.d(gpgpu_util_namespaceObject, "createPackedMatrixTexture", function () {
+        return createPackedMatrixTexture;
+      });
+      __webpack_require__.d(
+        gpgpu_util_namespaceObject,
+        "createFloat16PackedMatrixTexture",
+        function () {
+          return createFloat16PackedMatrixTexture;
+        }
+      );
+      __webpack_require__.d(
+        gpgpu_util_namespaceObject,
+        "bindVertexProgramAttributeStreams",
+        function () {
+          return bindVertexProgramAttributeStreams;
+        }
+      );
+      __webpack_require__.d(gpgpu_util_namespaceObject, "uploadDenseMatrixToTexture", function () {
+        return uploadDenseMatrixToTexture;
+      });
+      __webpack_require__.d(gpgpu_util_namespaceObject, "uploadPixelDataToTexture", function () {
+        return uploadPixelDataToTexture;
+      });
+      __webpack_require__.d(
+        gpgpu_util_namespaceObject,
+        "createBufferFromOutputTexture",
+        function () {
+          return createBufferFromOutputTexture;
+        }
+      );
+      __webpack_require__.d(
+        gpgpu_util_namespaceObject,
+        "downloadFloat32MatrixFromBuffer",
+        function () {
+          return downloadFloat32MatrixFromBuffer;
+        }
+      );
+      __webpack_require__.d(
+        gpgpu_util_namespaceObject,
+        "downloadByteEncodedFloatMatrixFromOutputTexture",
+        function () {
+          return downloadByteEncodedFloatMatrixFromOutputTexture;
+        }
+      );
+      __webpack_require__.d(
+        gpgpu_util_namespaceObject,
+        "downloadPackedMatrixFromBuffer",
+        function () {
+          return downloadPackedMatrixFromBuffer;
+        }
+      );
+      __webpack_require__.d(
+        gpgpu_util_namespaceObject,
+        "downloadMatrixFromPackedOutputTexture",
+        function () {
+          return downloadMatrixFromPackedOutputTexture;
+        }
+      );
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
+      var dist = __webpack_require__(0);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/canvas_util.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const contexts = {};
+      const WEBGL_ATTRIBUTES = {
+        alpha: false,
+        antialias: false,
+        premultipliedAlpha: false,
+        preserveDrawingBuffer: false,
+        depth: false,
+        stencil: false,
+        failIfMajorPerformanceCaveat: true,
+      };
+      function setWebGLContext(webGLVersion, gl) {
+        contexts[webGLVersion] = gl;
+      }
+      function getWebGLContext(webGLVersion) {
+        if (!(webGLVersion in contexts)) {
+          contexts[webGLVersion] = getWebGLRenderingContext(webGLVersion);
+        }
+        const gl = contexts[webGLVersion];
+        if (gl.isContextLost()) {
+          delete contexts[webGLVersion];
+          return getWebGLContext(webGLVersion);
+        }
+        gl.disable(gl.DEPTH_TEST);
+        gl.disable(gl.STENCIL_TEST);
+        gl.disable(gl.BLEND);
+        gl.disable(gl.DITHER);
+        gl.disable(gl.POLYGON_OFFSET_FILL);
+        gl.disable(gl.SAMPLE_COVERAGE);
+        gl.enable(gl.SCISSOR_TEST);
+        gl.enable(gl.CULL_FACE);
+        gl.cullFace(gl.BACK);
+        return contexts[webGLVersion];
+      }
+      function createCanvas(webGLVersion) {
+        if (typeof OffscreenCanvas !== "undefined" && webGLVersion === 2) {
+          return new OffscreenCanvas(300, 150);
+        } else if (typeof document !== "undefined") {
+          return document.createElement("canvas");
+        } else {
+          throw new Error("Cannot create a canvas in this context");
+        }
+      }
+      function getWebGLRenderingContext(webGLVersion) {
+        if (webGLVersion !== 1 && webGLVersion !== 2) {
+          throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");
+        }
+        const canvas = createCanvas(webGLVersion);
+        canvas.addEventListener(
+          "webglcontextlost",
+          (ev) => {
+            ev.preventDefault();
+            delete contexts[webGLVersion];
+          },
+          false
+        );
+        if (webGLVersion === 1) {
+          return (
+            canvas.getContext("webgl", WEBGL_ATTRIBUTES) ||
+            canvas.getContext("experimental-webgl", WEBGL_ATTRIBUTES)
+          );
+        }
+        return canvas.getContext("webgl2", WEBGL_ATTRIBUTES);
+      }
+      //# sourceMappingURL=canvas_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/tex_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      var PackingScheme;
+      (function (PackingScheme) {
+        /**
+         * All values in a single texel are densely packed without any constraints.
+         *
+         * This is how the shader encodes a tensor with shape = [2, 3, 4]
+         * (indices are [batch, row, col]).
+         *
+         * 000|001   010|011   020|021
+         * -------   -------   -------
+         * 002|003   012|013   022|023
+         *
+         * 100|101   110|111   120|121
+         * -------   -------   -------
+         * 102|103   112|113   122|123
+         *
+         */
+        PackingScheme[(PackingScheme["DENSE"] = 0)] = "DENSE";
+        /**
+         * Single texels contain only values from the same batch, and from adjacent
+         * rows and columns.
+         *
+         * This is how the shader encodes a tensor with shape = [2, 3, 5]
+         * (indices are [batch, row, col]).
+         *
+         * 000|001   002|003   004|xxx   020|021   022|023   024|xxx
+         * -------   -------   -------   -------   -------   -------
+         * 010|011   012|013   014|xxx   xxx|xxx   xxx|xxx   xxx|xxx
+         *
+         * 100|101   102|103   104|xxx   120|121   122|123   124|xxx
+         * -------   -------   -------   -------   -------   -------
+         * 110|111   112|113   114|xxx   xxx|xxx   xxx|xxx   xxx|xxx
+         *
+         */
+        PackingScheme[(PackingScheme["SHARED_BATCH"] = 1)] = "SHARED_BATCH";
+      })(PackingScheme || (PackingScheme = {}));
+      var TextureUsage;
+      (function (TextureUsage) {
+        TextureUsage[(TextureUsage["RENDER"] = 0)] = "RENDER";
+        TextureUsage[(TextureUsage["UPLOAD"] = 1)] = "UPLOAD";
+        TextureUsage[(TextureUsage["PIXELS"] = 2)] = "PIXELS";
+        TextureUsage[(TextureUsage["DOWNLOAD"] = 3)] = "DOWNLOAD";
+      })(TextureUsage || (TextureUsage = {}));
+      var PhysicalTextureType;
+      (function (PhysicalTextureType) {
+        PhysicalTextureType[(PhysicalTextureType["UNPACKED_FLOAT16"] = 0)] = "UNPACKED_FLOAT16";
+        PhysicalTextureType[(PhysicalTextureType["UNPACKED_FLOAT32"] = 1)] = "UNPACKED_FLOAT32";
+        PhysicalTextureType[(PhysicalTextureType["PACKED_4X1_UNSIGNED_BYTE"] = 2)] =
+          "PACKED_4X1_UNSIGNED_BYTE";
+        PhysicalTextureType[(PhysicalTextureType["PACKED_2X2_FLOAT32"] = 3)] = "PACKED_2X2_FLOAT32";
+        PhysicalTextureType[(PhysicalTextureType["PACKED_2X2_FLOAT16"] = 4)] = "PACKED_2X2_FLOAT16";
+      })(PhysicalTextureType || (PhysicalTextureType = {}));
+      function getUnpackedMatrixTextureShapeWidthHeight(rows, columns) {
+        return [columns, rows];
+      }
+      function getUnpackedArraySizeFromMatrixSize(matrixSize, channelsPerTexture) {
+        return matrixSize * channelsPerTexture;
+      }
+      function getColorMatrixTextureShapeWidthHeight(rows, columns) {
+        return [columns * 4, rows];
+      }
+      /**
+       * Get shape for densely packed RGBA texture.
+       */
+      function getDenseTexShape(shape) {
+        const size = dist["util"].sizeFromShape(shape);
+        const texelsNeeded = Math.ceil(size / 4);
+        return dist["util"].sizeToSquarishShape(texelsNeeded);
+      }
+      function getMatrixSizeFromUnpackedArraySize(unpackedSize, channelsPerTexture) {
+        if (unpackedSize % channelsPerTexture !== 0) {
+          throw new Error(
+            `unpackedSize (${unpackedSize}) must be a multiple of ` + `${channelsPerTexture}`
+          );
+        }
+        return unpackedSize / channelsPerTexture;
+      }
+      function decodeMatrixFromUnpackedColorRGBAArray(unpackedArray, matrix, channels) {
+        const requiredSize = (unpackedArray.length * channels) / 4;
+        if (matrix.length < requiredSize) {
+          throw new Error(`matrix length (${matrix.length}) must be >= ${requiredSize}`);
+        }
+        let dst = 0;
+        for (let src = 0; src < unpackedArray.length; src += 4) {
+          for (let c = 0; c < channels; c++) {
+            matrix[dst++] = unpackedArray[src + c];
+          }
+        }
+      }
+      function getPackedMatrixTextureShapeWidthHeight(rows, columns) {
+        return [Math.max(1, Math.ceil(columns / 2)), Math.max(1, Math.ceil(rows / 2))];
+      }
+      function getPackedRGBAArraySizeFromMatrixShape(rows, columns) {
+        const [w, h] = getPackedMatrixTextureShapeWidthHeight(rows, columns);
+        return w * h * 4;
+      }
+      function getTextureConfig(
+        // tslint:disable-next-line:no-any
+        gl,
+        textureHalfFloatExtension
+      ) {
+        // tslint:disable-next-line:no-any
+        const glany = gl;
+        let internalFormatFloat;
+        let internalFormatHalfFloat;
+        let internalFormatPackedHalfFloat;
+        let internalFormatPackedFloat;
+        let textureFormatFloat;
+        let downloadTextureFormat;
+        let downloadUnpackNumChannels;
+        let defaultNumChannels;
+        let textureTypeHalfFloat;
+        let textureTypeFloat;
+        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 2) {
+          internalFormatFloat = glany.R32F;
+          internalFormatHalfFloat = glany.R16F;
+          internalFormatPackedHalfFloat = glany.RGBA16F;
+          internalFormatPackedFloat = glany.RGBA32F;
+          textureFormatFloat = glany.RED;
+          downloadUnpackNumChannels = 4;
+          defaultNumChannels = 1;
+          textureTypeHalfFloat = glany.HALF_FLOAT;
+          textureTypeFloat = glany.FLOAT;
+        } else {
+          internalFormatFloat = gl.RGBA;
+          internalFormatHalfFloat = gl.RGBA;
+          internalFormatPackedHalfFloat = gl.RGBA;
+          internalFormatPackedFloat = glany.RGBA;
+          textureFormatFloat = gl.RGBA;
+          downloadUnpackNumChannels = 4;
+          defaultNumChannels = 4;
+          textureTypeHalfFloat =
+            textureHalfFloatExtension != null ? textureHalfFloatExtension.HALF_FLOAT_OES : null;
+          textureTypeFloat = gl.FLOAT;
+        }
+        downloadTextureFormat = gl.RGBA;
+        return {
+          internalFormatFloat,
+          internalFormatHalfFloat,
+          internalFormatPackedHalfFloat,
+          internalFormatPackedFloat,
+          textureFormatFloat,
+          downloadTextureFormat,
+          downloadUnpackNumChannels,
+          defaultNumChannels,
+          textureTypeHalfFloat,
+          textureTypeFloat,
+        };
+      }
+      //# sourceMappingURL=tex_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function callAndCheck(gl, debugMode, func) {
+        const returnValue = func();
+        if (debugMode) {
+          checkWebGLError(gl);
+        }
+        return returnValue;
+      }
+      function checkWebGLError(gl) {
+        const error = gl.getError();
+        if (error !== gl.NO_ERROR) {
+          throw new Error("WebGL Error: " + getWebGLErrorMessage(gl, error));
+        }
+      }
+      // https://en.wikipedia.org/wiki/Half-precision_floating-point_format
+      const MIN_FLOAT16 = 5.96e-8;
+      const MAX_FLOAT16 = 65504;
+      function canBeRepresented(num) {
+        if (
+          Object(dist["env"])().getBool("WEBGL_RENDER_FLOAT32_ENABLED") ||
+          num === 0 ||
+          (MIN_FLOAT16 < Math.abs(num) && Math.abs(num) < MAX_FLOAT16)
+        ) {
+          return true;
+        }
+        return false;
+      }
+      function getWebGLErrorMessage(gl, status) {
+        switch (status) {
+          case gl.NO_ERROR:
+            return "NO_ERROR";
+          case gl.INVALID_ENUM:
+            return "INVALID_ENUM";
+          case gl.INVALID_VALUE:
+            return "INVALID_VALUE";
+          case gl.INVALID_OPERATION:
+            return "INVALID_OPERATION";
+          case gl.INVALID_FRAMEBUFFER_OPERATION:
+            return "INVALID_FRAMEBUFFER_OPERATION";
+          case gl.OUT_OF_MEMORY:
+            return "OUT_OF_MEMORY";
+          case gl.CONTEXT_LOST_WEBGL:
+            return "CONTEXT_LOST_WEBGL";
+          default:
+            return `Unknown error code ${status}`;
+        }
+      }
+      function getExtensionOrThrow(gl, debug, extensionName) {
+        return throwIfNull(
+          gl,
+          debug,
+          () => gl.getExtension(extensionName),
+          'Extension "' + extensionName + '" not supported on this browser.'
+        );
+      }
+      function createVertexShader(gl, debug, vertexShaderSource) {
+        const vertexShader = throwIfNull(
+          gl,
+          debug,
+          () => gl.createShader(gl.VERTEX_SHADER),
+          "Unable to create vertex WebGLShader."
+        );
+        callAndCheck(gl, debug, () => gl.shaderSource(vertexShader, vertexShaderSource));
+        callAndCheck(gl, debug, () => gl.compileShader(vertexShader));
+        if (gl.getShaderParameter(vertexShader, gl.COMPILE_STATUS) === false) {
+          console.log(gl.getShaderInfoLog(vertexShader));
+          throw new Error("Failed to compile vertex shader.");
+        }
+        return vertexShader;
+      }
+      function createFragmentShader(gl, debug, fragmentShaderSource) {
+        const fragmentShader = throwIfNull(
+          gl,
+          debug,
+          () => gl.createShader(gl.FRAGMENT_SHADER),
+          "Unable to create fragment WebGLShader."
+        );
+        callAndCheck(gl, debug, () => gl.shaderSource(fragmentShader, fragmentShaderSource));
+        callAndCheck(gl, debug, () => gl.compileShader(fragmentShader));
+        if (gl.getShaderParameter(fragmentShader, gl.COMPILE_STATUS) === false) {
+          logShaderSourceAndInfoLog(fragmentShaderSource, gl.getShaderInfoLog(fragmentShader));
+          throw new Error("Failed to compile fragment shader.");
+        }
+        return fragmentShader;
+      }
+      const lineNumberRegex = /ERROR: [0-9]+:([0-9]+):/g;
+      function logShaderSourceAndInfoLog(shaderSource, shaderInfoLog) {
+        const lineNumberRegexResult = lineNumberRegex.exec(shaderInfoLog);
+        if (lineNumberRegexResult == null) {
+          console.log(`Couldn't parse line number in error: ${shaderInfoLog}`);
+          console.log(shaderSource);
+          return;
+        }
+        const lineNumber = +lineNumberRegexResult[1];
+        const shaderLines = shaderSource.split("\n");
+        const pad = shaderLines.length.toString().length + 2;
+        const linesWithLineNumbers = shaderLines.map(
+          (line, lineNumber) => dist["util"].rightPad((lineNumber + 1).toString(), pad) + line
+        );
+        let maxLineLength = 0;
+        for (let i = 0; i < linesWithLineNumbers.length; i++) {
+          maxLineLength = Math.max(linesWithLineNumbers[i].length, maxLineLength);
+        }
+        const beforeErrorLines = linesWithLineNumbers.slice(0, lineNumber - 1);
+        const errorLine = linesWithLineNumbers.slice(lineNumber - 1, lineNumber);
+        const afterErrorLines = linesWithLineNumbers.slice(lineNumber);
+        console.log(beforeErrorLines.join("\n"));
+        console.log(shaderInfoLog.split("\n")[0]);
+        console.log(
+          `%c ${dist["util"].rightPad(errorLine[0], maxLineLength)}`,
+          "border:1px solid red; background-color:#e3d2d2; color:#a61717"
+        );
+        console.log(afterErrorLines.join("\n"));
+      }
+      function createProgram(gl, debug) {
+        return throwIfNull(gl, debug, () => gl.createProgram(), "Unable to create WebGLProgram.");
+      }
+      function linkProgram(gl, debug, program) {
+        callAndCheck(gl, debug, () => gl.linkProgram(program));
+        if (gl.getProgramParameter(program, gl.LINK_STATUS) === false) {
+          console.log(gl.getProgramInfoLog(program));
+          throw new Error("Failed to link vertex and fragment shaders.");
+        }
+      }
+      function validateProgram(gl, debug, program) {
+        callAndCheck(gl, debug, () => gl.validateProgram(program));
+        if (gl.getProgramParameter(program, gl.VALIDATE_STATUS) === false) {
+          console.log(gl.getProgramInfoLog(program));
+          throw new Error("Shader program validation failed.");
+        }
+      }
+      function createStaticVertexBuffer(gl, debug, data) {
+        const buffer = throwIfNull(
+          gl,
+          debug,
+          () => gl.createBuffer(),
+          "Unable to create WebGLBuffer"
+        );
+        callAndCheck(gl, debug, () => gl.bindBuffer(gl.ARRAY_BUFFER, buffer));
+        callAndCheck(gl, debug, () => gl.bufferData(gl.ARRAY_BUFFER, data, gl.STATIC_DRAW));
+        return buffer;
+      }
+      function createStaticIndexBuffer(gl, debug, data) {
+        const buffer = throwIfNull(
+          gl,
+          debug,
+          () => gl.createBuffer(),
+          "Unable to create WebGLBuffer"
+        );
+        callAndCheck(gl, debug, () => gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, buffer));
+        callAndCheck(gl, debug, () => gl.bufferData(gl.ELEMENT_ARRAY_BUFFER, data, gl.STATIC_DRAW));
+        return buffer;
+      }
+      function getNumChannels() {
+        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 2) {
+          return 1;
+        }
+        return 4;
+      }
+      function createTexture(gl, debug) {
+        return throwIfNull(gl, debug, () => gl.createTexture(), "Unable to create WebGLTexture.");
+      }
+      function validateTextureSize(width, height) {
+        const maxTextureSize = Object(dist["env"])().getNumber("WEBGL_MAX_TEXTURE_SIZE");
+        if (width <= 0 || height <= 0) {
+          const requested = `[${width}x${height}]`;
+          throw new Error("Requested texture size " + requested + " is invalid.");
+        }
+        if (width > maxTextureSize || height > maxTextureSize) {
+          const requested = `[${width}x${height}]`;
+          const max = `[${maxTextureSize}x${maxTextureSize}]`;
+          throw new Error(
+            "Requested texture size " +
+              requested +
+              " greater than WebGL maximum on this browser / GPU " +
+              max +
+              "."
+          );
+        }
+      }
+      function createFramebuffer(gl, debug) {
+        return throwIfNull(
+          gl,
+          debug,
+          () => gl.createFramebuffer(),
+          "Unable to create WebGLFramebuffer."
+        );
+      }
+      function bindVertexBufferToProgramAttribute(
+        gl,
+        debug,
+        program,
+        attribute,
+        buffer,
+        arrayEntriesPerItem,
+        itemStrideInBytes,
+        itemOffsetInBytes
+      ) {
+        const loc = gl.getAttribLocation(program, attribute);
+        if (loc === -1) {
+          // The GPU compiler decided to strip out this attribute because it's unused,
+          // thus no need to bind.
+          return false;
+        }
+        callAndCheck(gl, debug, () => gl.bindBuffer(gl.ARRAY_BUFFER, buffer));
+        callAndCheck(gl, debug, () =>
+          gl.vertexAttribPointer(
+            loc,
+            arrayEntriesPerItem,
+            gl.FLOAT,
+            false,
+            itemStrideInBytes,
+            itemOffsetInBytes
+          )
+        );
+        callAndCheck(gl, debug, () => gl.enableVertexAttribArray(loc));
+        return true;
+      }
+      function bindTextureUnit(gl, debug, texture, textureUnit) {
+        validateTextureUnit(gl, textureUnit);
+        callAndCheck(gl, debug, () => gl.activeTexture(gl.TEXTURE0 + textureUnit));
+        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, texture));
+      }
+      function unbindTextureUnit(gl, debug, textureUnit) {
+        validateTextureUnit(gl, textureUnit);
+        callAndCheck(gl, debug, () => gl.activeTexture(gl.TEXTURE0 + textureUnit));
+        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, null));
+      }
+      function getProgramUniformLocationOrThrow(gl, debug, program, uniformName) {
+        return throwIfNull(
+          gl,
+          debug,
+          () => gl.getUniformLocation(program, uniformName),
+          'uniform "' + uniformName + '" not present in program.'
+        );
+      }
+      function getProgramUniformLocation(gl, program, uniformName) {
+        return gl.getUniformLocation(program, uniformName);
+      }
+      function bindTextureToProgramUniformSampler(
+        gl,
+        debug,
+        program,
+        texture,
+        uniformSamplerLocation,
+        textureUnit
+      ) {
+        callAndCheck(gl, debug, () => bindTextureUnit(gl, debug, texture, textureUnit));
+        callAndCheck(gl, debug, () => gl.uniform1i(uniformSamplerLocation, textureUnit));
+      }
+      function bindCanvasToFramebuffer(gl, debug) {
+        callAndCheck(gl, debug, () => gl.bindFramebuffer(gl.FRAMEBUFFER, null));
+        callAndCheck(gl, debug, () => gl.viewport(0, 0, gl.canvas.width, gl.canvas.height));
+        callAndCheck(gl, debug, () => gl.scissor(0, 0, gl.canvas.width, gl.canvas.height));
+      }
+      function bindColorTextureToFramebuffer(gl, debug, texture, framebuffer) {
+        callAndCheck(gl, debug, () => gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer));
+        callAndCheck(gl, debug, () =>
+          gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0)
+        );
+      }
+      function unbindColorTextureFromFramebuffer(gl, debug, framebuffer) {
+        callAndCheck(gl, debug, () => gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer));
+        callAndCheck(gl, debug, () =>
+          gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, null, 0)
+        );
+      }
+      function validateFramebuffer(gl) {
+        const status = gl.checkFramebufferStatus(gl.FRAMEBUFFER);
+        if (status !== gl.FRAMEBUFFER_COMPLETE) {
+          throw new Error("Error binding framebuffer: " + getFramebufferErrorMessage(gl, status));
+        }
+      }
+      function getFramebufferErrorMessage(gl, status) {
+        switch (status) {
+          case gl.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:
+            return "FRAMEBUFFER_INCOMPLETE_ATTACHMENT";
+          case gl.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:
+            return "FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";
+          case gl.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:
+            return "FRAMEBUFFER_INCOMPLETE_DIMENSIONS";
+          case gl.FRAMEBUFFER_UNSUPPORTED:
+            return "FRAMEBUFFER_UNSUPPORTED";
+          default:
+            return `unknown error ${status}`;
+        }
+      }
+      function throwIfNull(gl, debug, returnTOrNull, failureMessage) {
+        const tOrNull = callAndCheck(gl, debug, () => returnTOrNull());
+        if (tOrNull == null) {
+          throw new Error(failureMessage);
+        }
+        return tOrNull;
+      }
+      function validateTextureUnit(gl, textureUnit) {
+        const maxTextureUnit = gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS - 1;
+        const glTextureUnit = textureUnit + gl.TEXTURE0;
+        if (glTextureUnit < gl.TEXTURE0 || glTextureUnit > maxTextureUnit) {
+          const textureUnitRange = `[gl.TEXTURE0, gl.TEXTURE${maxTextureUnit}]`;
+          throw new Error(`textureUnit must be in ${textureUnitRange}.`);
+        }
+      }
+      function getBatchDim(shape, dimsToSkip = 2) {
+        return dist["util"].sizeFromShape(shape.slice(0, shape.length - dimsToSkip));
+      }
+      function getRowsCols(shape) {
+        if (shape.length === 0) {
+          throw Error("Cannot get rows and columns of an empty shape array.");
+        }
+        return [shape.length > 1 ? shape[shape.length - 2] : 1, shape[shape.length - 1]];
+      }
+      function getShapeAs3D(shape) {
+        let shapeAs3D = [1, 1, 1];
+        const isScalar = shape.length === 0 || (shape.length === 1 && shape[0] === 1);
+        if (!isScalar) {
+          shapeAs3D = [getBatchDim(shape), ...getRowsCols(shape)];
+        }
+        return shapeAs3D;
+      }
+      function getTextureShapeFromLogicalShape(logShape, isPacked = false) {
+        let maxTexSize = Object(dist["env"])().getNumber("WEBGL_MAX_TEXTURE_SIZE");
+        if (isPacked) {
+          maxTexSize = maxTexSize * 2;
+          // This logic ensures we accurately count the number of packed texels needed
+          // to accommodate the tensor. We can only pack values in the same texel if
+          // they are from adjacent pairs of rows/cols within the same batch. So if a
+          // tensor has 3 rows, we pretend it has 4 rows in order to account for the
+          // fact that the texels containing the third row are half empty.
+          logShape = logShape.map((d, i) =>
+            i >= logShape.length - 2 ? dist["util"].nearestLargerEven(logShape[i]) : logShape[i]
+          );
+          // Packed texture height is at least 2 (the channel height of a single
+          // texel).
+          if (logShape.length === 1) {
+            logShape = [2, logShape[0]];
+          }
+        }
+        // If logical shape is 2, we don't squeeze, since we want to match physical.
+        if (logShape.length !== 2) {
+          const squeezeResult = dist["util"].squeezeShape(logShape);
+          logShape = squeezeResult.newShape;
+        }
+        let size = dist["util"].sizeFromShape(logShape);
+        if (logShape.length <= 1 && size <= maxTexSize) {
+          return [1, size];
+        } else if (
+          logShape.length === 2 &&
+          logShape[0] <= maxTexSize &&
+          logShape[1] <= maxTexSize
+        ) {
+          return logShape;
+        } else if (
+          logShape.length === 3 &&
+          logShape[0] * logShape[1] <= maxTexSize &&
+          logShape[2] <= maxTexSize
+        ) {
+          return [logShape[0] * logShape[1], logShape[2]];
+        } else if (
+          logShape.length === 3 &&
+          logShape[0] <= maxTexSize &&
+          logShape[1] * logShape[2] <= maxTexSize
+        ) {
+          return [logShape[0], logShape[1] * logShape[2]];
+        } else if (
+          logShape.length === 4 &&
+          logShape[0] * logShape[1] * logShape[2] <= maxTexSize &&
+          logShape[3] <= maxTexSize
+        ) {
+          return [logShape[0] * logShape[1] * logShape[2], logShape[3]];
+        } else if (
+          logShape.length === 4 &&
+          logShape[0] <= maxTexSize &&
+          logShape[1] * logShape[2] * logShape[3] <= maxTexSize
+        ) {
+          return [logShape[0], logShape[1] * logShape[2] * logShape[3]];
+        } else {
+          if (isPacked) {
+            // For packed textures size equals the number of channels required to
+            // accommodate the texture data. However in order to squarify such that
+            // inner dimensions stay even, we rewrite size to equal the number of
+            // texels. Then in the return statement we rehydrate the squarified
+            // dimensions to channel units.
+            const batchDim = getBatchDim(logShape);
+            let rows = 2,
+              cols = 2;
+            if (logShape.length) {
+              [rows, cols] = getRowsCols(logShape);
+            }
+            size = batchDim * (rows / 2) * (cols / 2);
+            return dist["util"].sizeToSquarishShape(size).map((d) => d * 2);
+          }
+          return dist["util"].sizeToSquarishShape(size);
+        }
+      }
+      function isEven(n) {
+        return n % 2 === 0;
+      }
+      /**
+       * This determines whether reshaping a packed texture requires rearranging
+       * the data within the texture, assuming 2x2 packing.
+       */
+      function isReshapeFree(shape1, shape2) {
+        shape1 = shape1.slice(-2);
+        shape2 = shape2.slice(-2);
+        if (dist["util"].arraysEqual(shape1, shape2)) {
+          return true;
+        }
+        if (!shape1.length || !shape2.length) {
+          // One of the shapes is a scalar.
+          return true;
+        }
+        if (shape1[0] === 0 || shape1[1] === 0 || shape2[0] === 0 || shape2[1] === 0) {
+          return true;
+        }
+        if (shape1.length !== shape2.length) {
+          // One of the shapes is a vector.
+          const shape1Cols = shape1.slice(-1)[0];
+          const shape2Cols = shape2.slice(-1)[0];
+          if (shape1Cols === shape2Cols) {
+            return true;
+          }
+          if (isEven(shape1Cols) && isEven(shape2Cols) && (shape1[0] === 1 || shape2[0] === 1)) {
+            return true;
+          }
+        }
+        return shape1[1] === shape2[1] && isEven(shape1[0]) && isEven(shape2[0]);
+      }
+      // We cache webgl params because the environment gets reset between
+      // unit tests and we don't want to constantly query the WebGLContext for
+      // MAX_TEXTURE_SIZE.
+      let MAX_TEXTURE_SIZE;
+      let MAX_TEXTURES_IN_SHADER;
+      function getWebGLMaxTextureSize(webGLVersion) {
+        if (MAX_TEXTURE_SIZE == null) {
+          const gl = getWebGLContext(webGLVersion);
+          MAX_TEXTURE_SIZE = gl.getParameter(gl.MAX_TEXTURE_SIZE);
+        }
+        return MAX_TEXTURE_SIZE;
+      }
+      function resetMaxTextureSize() {
+        MAX_TEXTURE_SIZE = null;
+      }
+      function resetMaxTexturesInShader() {
+        MAX_TEXTURES_IN_SHADER = null;
+      }
+      function getMaxTexturesInShader(webGLVersion) {
+        if (MAX_TEXTURES_IN_SHADER == null) {
+          const gl = getWebGLContext(webGLVersion);
+          MAX_TEXTURES_IN_SHADER = gl.getParameter(gl.MAX_TEXTURE_IMAGE_UNITS);
+        }
+        // We cap at 16 to avoid spurious runtime "memory exhausted" error.
+        return Math.min(16, MAX_TEXTURES_IN_SHADER);
+      }
+      function getWebGLDisjointQueryTimerVersion(webGLVersion) {
+        if (webGLVersion === 0) {
+          return 0;
+        }
+        let queryTimerVersion;
+        const gl = getWebGLContext(webGLVersion);
+        if (hasExtension(gl, "EXT_disjoint_timer_query_webgl2") && webGLVersion === 2) {
+          queryTimerVersion = 2;
+        } else if (hasExtension(gl, "EXT_disjoint_timer_query")) {
+          queryTimerVersion = 1;
+        } else {
+          queryTimerVersion = 0;
+        }
+        return queryTimerVersion;
+      }
+      function hasExtension(gl, extensionName) {
+        const ext = gl.getExtension(extensionName);
+        return ext != null;
+      }
+      function isWebGLVersionEnabled(webGLVersion) {
+        try {
+          const gl = getWebGLContext(webGLVersion);
+          if (gl != null) {
+            return true;
+          }
+        } catch (e) {
+          return false;
+        }
+        return false;
+      }
+      function isCapableOfRenderingToFloatTexture(webGLVersion) {
+        if (webGLVersion === 0) {
+          return false;
+        }
+        const gl = getWebGLContext(webGLVersion);
+        if (webGLVersion === 1) {
+          if (!hasExtension(gl, "OES_texture_float")) {
+            return false;
+          }
+        } else {
+          if (!hasExtension(gl, "EXT_color_buffer_float")) {
+            return false;
+          }
+        }
+        const isFrameBufferComplete = createFloatTextureAndBindToFramebuffer(gl);
+        return isFrameBufferComplete;
+      }
+      /**
+       * Check if we can download values from a float/half-float texture.
+       *
+       * Note that for performance reasons we use binding a texture to a framebuffer
+       * as a proxy for ability to download float values later using readPixels. The
+       * texture params of this texture will not match those in readPixels exactly
+       * but if we are unable to bind some kind of float texture to the frameBuffer
+       * then we definitely will not be able to read float values from it.
+       */
+      function isDownloadFloatTextureEnabled(webGLVersion) {
+        if (webGLVersion === 0) {
+          return false;
+        }
+        const gl = getWebGLContext(webGLVersion);
+        if (webGLVersion === 1) {
+          if (!hasExtension(gl, "OES_texture_float")) {
+            return false;
+          }
+          if (!hasExtension(gl, "WEBGL_color_buffer_float")) {
+            return false;
+          }
+        } else {
+          if (hasExtension(gl, "EXT_color_buffer_float")) {
+            return createFloatTextureAndBindToFramebuffer(gl);
+          }
+          const COLOR_BUFFER_HALF_FLOAT = "EXT_color_buffer_half_float";
+          if (hasExtension(gl, COLOR_BUFFER_HALF_FLOAT)) {
+            const textureHalfFloatExtension = gl.getExtension(COLOR_BUFFER_HALF_FLOAT);
+            return createHalfFloatTextureAndBindToFramebuffer(gl, textureHalfFloatExtension);
+          }
+          return false;
+        }
+        const isFrameBufferComplete = createFloatTextureAndBindToFramebuffer(gl);
+        return isFrameBufferComplete;
+      }
+      function createFloatTextureAndBindToFramebuffer(gl) {
+        const texConfig = getTextureConfig(gl);
+        const texture = gl.createTexture();
+        gl.bindTexture(gl.TEXTURE_2D, texture);
+        const width = 1;
+        const height = 1;
+        gl.texImage2D(
+          gl.TEXTURE_2D,
+          0,
+          texConfig.internalFormatFloat,
+          width,
+          height,
+          0,
+          texConfig.textureFormatFloat,
+          texConfig.textureTypeFloat,
+          null
+        );
+        const frameBuffer = gl.createFramebuffer();
+        gl.bindFramebuffer(gl.FRAMEBUFFER, frameBuffer);
+        gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);
+        const isFrameBufferComplete =
+          gl.checkFramebufferStatus(gl.FRAMEBUFFER) === gl.FRAMEBUFFER_COMPLETE;
+        gl.bindTexture(gl.TEXTURE_2D, null);
+        gl.bindFramebuffer(gl.FRAMEBUFFER, null);
+        gl.deleteTexture(texture);
+        gl.deleteFramebuffer(frameBuffer);
+        return isFrameBufferComplete;
+      }
+      function createHalfFloatTextureAndBindToFramebuffer(
+        // tslint:disable-next-line:no-any
+        gl,
+        textureHalfFloatExtension
+      ) {
+        const texConfig = getTextureConfig(gl, textureHalfFloatExtension);
+        const texture = gl.createTexture();
+        gl.bindTexture(gl.TEXTURE_2D, texture);
+        const width = 1;
+        const height = 1;
+        gl.texImage2D(
+          gl.TEXTURE_2D,
+          0,
+          texConfig.internalFormatHalfFloat,
+          width,
+          height,
+          0,
+          texConfig.textureFormatFloat,
+          texConfig.textureTypeHalfFloat,
+          null
+        );
+        const frameBuffer = gl.createFramebuffer();
+        gl.bindFramebuffer(gl.FRAMEBUFFER, frameBuffer);
+        gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);
+        const isFrameBufferComplete =
+          gl.checkFramebufferStatus(gl.FRAMEBUFFER) === gl.FRAMEBUFFER_COMPLETE;
+        gl.bindTexture(gl.TEXTURE_2D, null);
+        gl.bindFramebuffer(gl.FRAMEBUFFER, null);
+        gl.deleteTexture(texture);
+        gl.deleteFramebuffer(frameBuffer);
+        return isFrameBufferComplete;
+      }
+      function isWebGLFenceEnabled(webGLVersion) {
+        if (webGLVersion !== 2) {
+          return false;
+        }
+        const gl = getWebGLContext(webGLVersion);
+        // tslint:disable-next-line:no-any
+        const isEnabled = gl.fenceSync != null;
+        return isEnabled;
+      }
+      //# sourceMappingURL=webgl_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/flags_webgl.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const ENV = Object(dist["env"])();
+      /**
+       * This file contains WebGL-specific flag registrations.
+       */
+      /**
+       * True if WebGL is supported.
+       */
+      ENV.registerFlag("HAS_WEBGL", () => ENV.getNumber("WEBGL_VERSION") > 0);
+      /** 0: No WebGL, 1: WebGL 1.0, 2: WebGL 2.0. */
+      ENV.registerFlag("WEBGL_VERSION", () => {
+        if (isWebGLVersionEnabled(2)) {
+          return 2;
+        } else if (isWebGLVersionEnabled(1)) {
+          return 1;
+        }
+        return 0;
+      });
+      ENV.registerFlag("WEBGL_BUFFER_SUPPORTED", () => ENV.get("WEBGL_VERSION") === 2);
+      /** Whether the WebGL backend will sometimes forward ops to the CPU. */
+      ENV.registerFlag("WEBGL_CPU_FORWARD", () => true);
+      /** Whether the WebGL backend will always use f16 textures for rendering. */
+      ENV.registerFlag("WEBGL_FORCE_F16_TEXTURES", () => false);
+      /** Whether to turn all packing related flags on. */
+      ENV.registerFlag("WEBGL_PACK", () => ENV.getBool("HAS_WEBGL"));
+      /** Whether we will pack the batchnormalization op. */
+      ENV.registerFlag("WEBGL_PACK_NORMALIZATION", () => ENV.getBool("WEBGL_PACK"));
+      /** Whether we will pack the clip op. */
+      ENV.registerFlag("WEBGL_PACK_CLIP", () => ENV.getBool("WEBGL_PACK"));
+      /** Whether we will pack the depthwise conv op. */
+      // TODO: https://github.com/tensorflow/tfjs/issues/1679
+      ENV.registerFlag("WEBGL_PACK_DEPTHWISECONV", () => false);
+      /** Whether we will pack binary ops. */
+      ENV.registerFlag("WEBGL_PACK_BINARY_OPERATIONS", () => ENV.getBool("WEBGL_PACK"));
+      /** Whether we will pack unary ops. */
+      ENV.registerFlag("WEBGL_PACK_UNARY_OPERATIONS", () => ENV.getBool("WEBGL_PACK"));
+      /** Whether we will pack array ops. */
+      ENV.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS", () => ENV.getBool("WEBGL_PACK"));
+      /** Whether we will pack image ops. */
+      ENV.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS", () => ENV.getBool("WEBGL_PACK"));
+      /** Whether we will pack reduce ops. */
+      ENV.registerFlag("WEBGL_PACK_REDUCE", () => ENV.getBool("WEBGL_PACK"));
+      /** Whether packed WebGL kernels lazily unpack their outputs. */
+      ENV.registerFlag("WEBGL_LAZILY_UNPACK", () => ENV.getBool("WEBGL_PACK"));
+      /** Whether we will use the im2col algorithm to speed up convolutions. */
+      ENV.registerFlag("WEBGL_CONV_IM2COL", () => ENV.getBool("WEBGL_PACK"));
+      /** The maximum texture dimension. */
+      ENV.registerFlag("WEBGL_MAX_TEXTURE_SIZE", () =>
+        getWebGLMaxTextureSize(ENV.getNumber("WEBGL_VERSION"))
+      );
+      /** The maximum texture dimension. */
+      ENV.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER", () =>
+        getMaxTexturesInShader(ENV.getNumber("WEBGL_VERSION"))
+      );
+      /**
+       * The disjoint_query_timer extension version.
+       * 0: disabled, 1: EXT_disjoint_timer_query, 2:
+       * EXT_disjoint_timer_query_webgl2.
+       * In Firefox with WebGL 2.0,
+       * EXT_disjoint_timer_query_webgl2 is not available, so we must use the
+       * WebGL 1.0 extension.
+       */
+      ENV.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION", () => {
+        const webGLVersion = ENV.getNumber("WEBGL_VERSION");
+        if (webGLVersion === 0) {
+          return 0;
+        }
+        return getWebGLDisjointQueryTimerVersion(webGLVersion);
+      });
+      /**
+       * Whether the timer object from the disjoint_query_timer extension gives
+       * timing information that is reliable.
+       */
+      ENV.registerFlag(
+        "WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",
+        () =>
+          ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") > 0 &&
+          !dist["device_util"].isMobile()
+      );
+      /**
+       * Whether the device is physically capable of rendering to float32 textures.
+       */
+      ENV.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE", () =>
+        isCapableOfRenderingToFloatTexture(ENV.getNumber("WEBGL_VERSION"))
+      );
+      /**
+       * Whether rendering to float32 textures is enabled. If disabled, renders to
+       * float16 textures.
+       */
+      ENV.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED", () => {
+        return ENV.getBool("WEBGL_FORCE_F16_TEXTURES")
+          ? false
+          : ENV.getBool("WEBGL_RENDER_FLOAT32_CAPABLE");
+      });
+      /**
+       * Whether downloading float textures is enabled (16 or 32 bit). If disabled,
+       * uses IEEE 754 encoding of the float32 values to 4 uint8 when downloading.
+       */
+      ENV.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED", () =>
+        isDownloadFloatTextureEnabled(ENV.getNumber("WEBGL_VERSION"))
+      );
+      /** Whether the fence API is available. */
+      ENV.registerFlag("WEBGL_FENCE_API_ENABLED", () =>
+        isWebGLFenceEnabled(ENV.getNumber("WEBGL_VERSION"))
+      );
+      /**
+       * Tensors with size <= than this will be uploaded as uniforms, not textures.
+       */
+      ENV.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM", () => {
+        // Use uniform uploads only when 32bit floats are supported. In
+        // 16bit
+        // environments there are problems with comparing a 16bit texture value
+        // with a 32bit uniform value.
+        const useUniforms = ENV.getBool("WEBGL_RENDER_FLOAT32_ENABLED");
+        return useUniforms ? 4 : 0;
+      });
+      //# sourceMappingURL=flags_webgl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/addn_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class AddNProgram {
+        constructor(outputShape, shapes) {
+          this.outputShape = [];
+          this.outputShape = outputShape;
+          this.variableNames = shapes.map((_, i) => `T${i}`);
+          const snippets = [];
+          // Get target elements from every input tensor.
+          this.variableNames.forEach((variable) => {
+            snippets.push(`float v${variable} = get${variable}AtOutCoords();`);
+          });
+          // Calculate the sum of all elements.
+          const operation = this.variableNames
+            .map((variable) => {
+              return `v${variable}`;
+            })
+            .join(" + ");
+          this.userCode = `
+      void main() {
+        ${snippets.join("\n        ")}
+
+        float result = ${operation};
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=addn_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/addn_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class AddNPackedProgram {
+        constructor(outputShape, shapes) {
+          this.outputShape = [];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = outputShape;
+          this.variableNames = shapes.map((_, i) => `T${i}`);
+          const snippets = [];
+          // Get target elements from every input tensor.
+          this.variableNames.forEach((variable) => {
+            snippets.push(`vec4 v${variable} = get${variable}AtOutCoords();`);
+          });
+          // Calculate the sum of all elements.
+          const operation = this.variableNames
+            .map((variable) => {
+              return `v${variable}`;
+            })
+            .join(" + ");
+          this.userCode = `
+      void main() {
+        ${snippets.join("\n        ")}
+
+        vec4 result = ${operation};
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=addn_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/argminmax_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ArgMinMaxProgram {
+        constructor(reduceInfo, op, firstPass) {
+          this.variableNames = ["A"];
+          const windowSize = reduceInfo.windowSize;
+          const batchSize = reduceInfo.batchSize;
+          const inSize = reduceInfo.inSize;
+          const outSize = Math.ceil(inSize / windowSize);
+          if (!firstPass) {
+            this.variableNames.push("bestIndicesA");
+          }
+          this.outputShape = [batchSize, outSize];
+          const compOp = op === "max" ? ">" : "<";
+          const indexSnippet = firstPass
+            ? "inOffset + i;"
+            : "round(getBestIndicesA(batch, inOffset + i));";
+          this.userCode = `
+      void main() {
+        ivec2 coords = getOutputCoords();
+        int batch = coords[0];
+        int outIdx = coords[1];
+        int inOffset = outIdx * ${windowSize};
+
+        int bestIndex = inOffset;
+        float bestValue = getA(batch, bestIndex);
+
+        for (int i = 0; i < ${windowSize}; i++) {
+          int inIdx = ${indexSnippet};
+          float candidate = getA(batch, inIdx);
+          if (candidate ${compOp} bestValue) {
+            bestValue = candidate;
+            bestIndex = inIdx;
+          }
+        }
+        setOutput(float(bestIndex));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=argminmax_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/packing_util.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      function getVecChannels(name, rank) {
+        return ["x", "y", "z", "w", "u", "v"].slice(0, rank).map((d) => `${name}.${d}`);
+      }
+      function getChannels(name, rank) {
+        if (rank === 1) {
+          return [name];
+        }
+        return getVecChannels(name, rank);
+      }
+      function getSourceCoords(rank, dims) {
+        if (rank === 1) {
+          return "rc";
+        }
+        let coords = "";
+        for (let i = 0; i < rank; i++) {
+          coords += dims[i];
+          if (i < rank - 1) {
+            coords += ",";
+          }
+        }
+        return coords;
+      }
+      //# sourceMappingURL=packing_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/glsl_version.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function getGlslDifferences() {
+        let version;
+        let attribute;
+        let varyingVs;
+        let varyingFs;
+        let texture2D;
+        let output;
+        let defineOutput;
+        let defineSpecialNaN;
+        let defineSpecialInf;
+        let defineRound;
+        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 2) {
+          version = "#version 300 es";
+          attribute = "in";
+          varyingVs = "out";
+          varyingFs = "in";
+          texture2D = "texture";
+          output = "outputColor";
+          defineOutput = "out vec4 outputColor;";
+          // Use custom isnan definition to work across differences between
+          // implementations on various platforms. While this should happen in ANGLE
+          // we still see differences between android and windows (on chrome) when
+          // using isnan directly.
+          defineSpecialNaN = `
+      bool isnan_custom(float val) {
+        return (val > 0.0 || val < 0.0) ? false : val != 0.0;
+      }
+
+      bvec4 isnan_custom(vec4 val) {
+        return bvec4(isnan_custom(val.x),
+          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
+      }
+
+      #define isnan(value) isnan_custom(value)
+    `;
+          // In webgl 2 we do not need to specify a custom isinf so there is no
+          // need for a special INFINITY constant.
+          defineSpecialInf = ``;
+          defineRound = `
+      #define round(value) newRound(value)
+      int newRound(float value) {
+        return int(floor(value + 0.5));
+      }
+
+      ivec4 newRound(vec4 value) {
+        return ivec4(floor(value + vec4(0.5)));
+      }
+    `;
+        } else {
+          version = "";
+          attribute = "attribute";
+          varyingVs = "varying";
+          varyingFs = "varying";
+          texture2D = "texture2D";
+          output = "gl_FragColor";
+          defineOutput = "";
+          // WebGL1 has no built in isnan so we define one here.
+          defineSpecialNaN = `
+      #define isnan(value) isnan_custom(value)
+      bool isnan_custom(float val) {
+        return (val > 0. || val < 1. || val == 0.) ? false : true;
+      }
+      bvec4 isnan_custom(vec4 val) {
+        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
+      }
+    `;
+          defineSpecialInf = `
+      uniform float INFINITY;
+
+      bool isinf(float val) {
+        return abs(val) == INFINITY;
+      }
+      bvec4 isinf(vec4 val) {
+        return equal(abs(val), vec4(INFINITY));
+      }
+    `;
+          defineRound = `
+      int round(float value) {
+        return int(floor(value + 0.5));
+      }
+
+      ivec4 round(vec4 value) {
+        return ivec4(floor(value + vec4(0.5)));
+      }
+    `;
+        }
+        return {
+          version,
+          attribute,
+          varyingVs,
+          varyingFs,
+          texture2D,
+          output,
+          defineOutput,
+          defineSpecialNaN,
+          defineSpecialInf,
+          defineRound,
+        };
+      }
+      //# sourceMappingURL=glsl_version.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/shader_compiler_util.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /**
+       * Produces GLSL code that derives logical coordinates from a flat
+       * index. The code performs integer division with each stride and decrements
+       * the index until the index equals the final dimension coordinate.
+       */
+      function getLogicalCoordinatesFromFlatIndex(coords, shape, index = "index") {
+        const strides = dist["util"].computeStrides(shape);
+        return strides
+          .map((stride, i) => {
+            const line1 = `int ${coords[i]} = ${index} / ${stride}`;
+            const line2 =
+              i === strides.length - 1
+                ? `int ${coords[i + 1]} = ${index} - ${coords[i]} * ${stride}`
+                : `index -= ${coords[i]} * ${stride}`;
+            return `${line1}; ${line2};`;
+          })
+          .join("");
+      }
+      function buildVec(x) {
+        if (x.length === 1) {
+          return `${x[0]}`;
+        }
+        return `vec${x.length}(${x.join(",")})`;
+      }
+      /**
+       * Produces GLSL code that computes the dot product of the input x and y
+       * vectors. Handles splitting inputs into increments of vec4s when necessary.
+       */
+      function dotify(x, y) {
+        if (x.length !== y.length) {
+          throw new Error(
+            `Vectors to be dotted must be of the same length -` + `got ${x.length} and ${y.length}`
+          );
+        }
+        const slices = [];
+        const nearestVec4 = Math.floor(x.length / 4);
+        const nearestVec4Remainder = x.length % 4;
+        for (let i = 0; i < nearestVec4; i++) {
+          const xSlice = x.slice(i * 4, i * 4 + 4);
+          const ySlice = y.slice(i * 4, i * 4 + 4);
+          slices.push(`${buildVec(xSlice)}, ${buildVec(ySlice)}`);
+        }
+        if (nearestVec4Remainder !== 0) {
+          let xSlice = x.slice(nearestVec4 * 4);
+          let ySlice = y.slice(nearestVec4 * 4);
+          if (xSlice.length === 1) {
+            xSlice = xSlice.map((d) => `float(${d})`);
+            ySlice = ySlice.map((d) => `float(${d})`);
+          }
+          slices.push(`${buildVec(xSlice)}, ${buildVec(ySlice)}`);
+        }
+        return slices.map((d, i) => `dot(${d})`).join("+");
+      }
+      /**
+       * Produces GLSL that computes the flat index from 3D coordinates.
+       */
+      function getFlatIndexFrom3D(shape) {
+        const strides = dist["util"].computeStrides(shape).map((d) => d.toString());
+        return `
+  int getFlatIndex(ivec3 coords) {
+    return coords.x * ${strides[0]} + coords.y * ${strides[1]} + coords.z;
+  }
+`;
+      }
+      const ENCODE_FLOAT_SNIPPET = `
+  const float FLOAT_MAX = 1.70141184e38;
+  const float FLOAT_MIN = 1.17549435e-38;
+
+  lowp vec4 encode_float(highp float v) {
+    if (isnan(v)) {
+      return vec4(255, 255, 255, 255);
+    }
+
+    highp float av = abs(v);
+
+    if(av < FLOAT_MIN) {
+      return vec4(0.0, 0.0, 0.0, 0.0);
+    } else if(v > FLOAT_MAX) {
+      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
+    } else if(v < -FLOAT_MAX) {
+      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
+    }
+
+    highp vec4 c = vec4(0,0,0,0);
+
+    highp float e = floor(log2(av));
+    highp float m = exp2(fract(log2(av))) - 1.0;
+
+    c[2] = floor(128.0 * m);
+    m -= c[2] / 128.0;
+    c[1] = floor(32768.0 * m);
+    m -= c[1] / 32768.0;
+    c[0] = floor(8388608.0 * m);
+
+    highp float ebias = e + 127.0;
+    c[3] = floor(ebias / 2.0);
+    ebias -= c[3] * 2.0;
+    c[2] += floor(ebias) * 128.0;
+
+    c[3] += 128.0 * step(0.0, -v);
+
+    return c / 255.0;
+  }
+`;
+      //# sourceMappingURL=shader_compiler_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/shader_compiler.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const { getBroadcastDims } = dist["backend_util"];
+
+      function makeShader(inputsInfo, outputShape, userCode, usesPackedTextures) {
+        const prefixSnippets = [];
+        inputsInfo.forEach((x) => {
+          const size = dist["util"].sizeFromShape(x.shapeInfo.logicalShape);
+          // Snippet when we decided to upload the values as uniform.
+          if (x.shapeInfo.isUniform) {
+            prefixSnippets.push(`uniform float ${x.name}${size > 1 ? `[${size}]` : ""};`);
+          } else {
+            prefixSnippets.push(`uniform sampler2D ${x.name};`);
+            prefixSnippets.push(`uniform int offset${x.name};`);
+          }
+        });
+        const inputPrefixSnippet = prefixSnippets.join("\n");
+        const inputSamplingSnippet = inputsInfo
+          .map((x) => getInputSamplingSnippet(x, outputShape, usesPackedTextures))
+          .join("\n");
+        const outTexShape = outputShape.texShape;
+        const glsl = getGlslDifferences();
+        const floatTextureSampleSnippet = getFloatTextureSampleSnippet(glsl);
+        let outputSamplingSnippet;
+        let floatTextureSetOutputSnippet;
+        let shaderPrefix = getShaderPrefix(glsl);
+        if (outputShape.isPacked) {
+          outputSamplingSnippet = getPackedOutputSamplingSnippet(
+            outputShape.logicalShape,
+            outTexShape
+          );
+          floatTextureSetOutputSnippet = getFloatTextureSetRGBASnippet(glsl);
+        } else {
+          outputSamplingSnippet = getOutputSamplingSnippet(outputShape.logicalShape, outTexShape);
+          floatTextureSetOutputSnippet = getFloatTextureSetRSnippet(glsl);
+        }
+        if (usesPackedTextures) {
+          shaderPrefix += SHADER_PACKED_PREFIX;
+        }
+        const source = [
+          shaderPrefix,
+          floatTextureSampleSnippet,
+          floatTextureSetOutputSnippet,
+          inputPrefixSnippet,
+          outputSamplingSnippet,
+          inputSamplingSnippet,
+          userCode,
+        ].join("\n");
+        return source;
+      }
+      function getSamplerFromInInfo(inInfo) {
+        const shape = inInfo.shapeInfo.logicalShape;
+        switch (shape.length) {
+          case 0:
+            return getSamplerScalar(inInfo);
+          case 1:
+            return getSampler1D(inInfo);
+          case 2:
+            return getSampler2D(inInfo);
+          case 3:
+            return getSampler3D(inInfo);
+          case 4:
+            return getSampler4D(inInfo);
+          case 5:
+            return getSampler5D(inInfo);
+          case 6:
+            return getSampler6D(inInfo);
+          default:
+            throw new Error(`${shape.length}-D input sampling` + ` is not yet supported`);
+        }
+      }
+      function getPackedSamplerFromInInfo(inInfo) {
+        const shape = inInfo.shapeInfo.logicalShape;
+        switch (shape.length) {
+          case 0:
+            return getPackedSamplerScalar(inInfo);
+          case 1:
+            return getPackedSampler1D(inInfo);
+          case 2:
+            return getPackedSampler2D(inInfo);
+          case 3:
+            return getPackedSampler3D(inInfo);
+          default:
+            return getPackedSamplerND(inInfo);
+        }
+      }
+      function getInputSamplingSnippet(inInfo, outShapeInfo, usesPackedTextures = false) {
+        let res = "";
+        if (usesPackedTextures) {
+          res += getPackedSamplerFromInInfo(inInfo);
+        } else {
+          res += getSamplerFromInInfo(inInfo);
+        }
+        const inShape = inInfo.shapeInfo.logicalShape;
+        const outShape = outShapeInfo.logicalShape;
+        if (inShape.length <= outShape.length) {
+          if (usesPackedTextures) {
+            res += getPackedSamplerAtOutputCoords(inInfo, outShapeInfo);
+          } else {
+            res += getSamplerAtOutputCoords(inInfo, outShapeInfo);
+          }
+        }
+        return res;
+      }
+      function getPackedOutputSamplingSnippet(outShape, outTexShape) {
+        switch (outShape.length) {
+          case 0:
+            return getOutputScalarCoords();
+          case 1:
+            return getOutputPacked1DCoords(outShape, outTexShape);
+          case 2:
+            return getOutputPacked2DCoords(outShape, outTexShape);
+          case 3:
+            return getOutputPacked3DCoords(outShape, outTexShape);
+          default:
+            return getOutputPackedNDCoords(outShape, outTexShape);
+        }
+      }
+      function getOutputSamplingSnippet(outShape, outTexShape) {
+        switch (outShape.length) {
+          case 0:
+            return getOutputScalarCoords();
+          case 1:
+            return getOutput1DCoords(outShape, outTexShape);
+          case 2:
+            return getOutput2DCoords(outShape, outTexShape);
+          case 3:
+            return getOutput3DCoords(outShape, outTexShape);
+          case 4:
+            return getOutput4DCoords(outShape, outTexShape);
+          case 5:
+            return getOutput5DCoords(outShape, outTexShape);
+          case 6:
+            return getOutput6DCoords(outShape, outTexShape);
+          default:
+            throw new Error(`${outShape.length}-D output sampling is not yet supported`);
+        }
+      }
+      function getFloatTextureSampleSnippet(glsl) {
+        return `
+    float sampleTexture(sampler2D textureSampler, vec2 uv) {
+      return ${glsl.texture2D}(textureSampler, uv).r;
+    }
+  `;
+      }
+      function getFloatTextureSetRSnippet(glsl) {
+        return `
+    void setOutput(float val) {
+      ${glsl.output} = vec4(val, 0, 0, 0);
+    }
+  `;
+      }
+      function getFloatTextureSetRGBASnippet(glsl) {
+        return `
+    void setOutput(vec4 val) {
+      ${glsl.output} = val;
+    }
+  `;
+      }
+      function getShaderPrefix(glsl) {
+        const SHADER_PREFIX = `${glsl.version}
+    precision highp float;
+    precision highp int;
+    precision highp sampler2D;
+    ${glsl.varyingFs} vec2 resultUV;
+    ${glsl.defineOutput}
+    const vec2 halfCR = vec2(0.5, 0.5);
+
+    struct ivec5
+    {
+      int x;
+      int y;
+      int z;
+      int w;
+      int u;
+    };
+
+    struct ivec6
+    {
+      int x;
+      int y;
+      int z;
+      int w;
+      int u;
+      int v;
+    };
+
+    uniform float NAN;
+    ${glsl.defineSpecialNaN}
+    ${glsl.defineSpecialInf}
+    ${glsl.defineRound}
+
+    int imod(int x, int y) {
+      return x - y * (x / y);
+    }
+
+    int idiv(int a, int b, float sign) {
+      int res = a / b;
+      int mod = imod(a, b);
+      if (sign < 0. && mod != 0) {
+        res -= 1;
+      }
+      return res;
+    }
+
+    //Based on the work of Dave Hoskins
+    //https://www.shadertoy.com/view/4djSRW
+    #define HASHSCALE1 443.8975
+    float random(float seed){
+      vec2 p = resultUV * seed;
+      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);
+      p3 += dot(p3, p3.yzx + 19.19);
+      return fract((p3.x + p3.y) * p3.z);
+    }
+
+    ${SAMPLE_1D_SNIPPET}
+    ${SAMPLE_2D_SNIPPET}
+    ${SAMPLE_3D_SNIPPET}
+  `;
+        return SHADER_PREFIX;
+      }
+      const SAMPLE_1D_SNIPPET = `
+vec2 uvFromFlat(int texNumR, int texNumC, int index) {
+  int texR = index / texNumC;
+  int texC = index - texR * texNumC;
+  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
+}
+vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
+  int texelIndex = index / 2;
+  int texR = texelIndex / texNumC;
+  int texC = texelIndex - texR * texNumC;
+  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
+}
+`;
+      const SAMPLE_2D_SNIPPET = `
+vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
+  int texNumC, int row, int col) {
+  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
+  int texR = texelIndex / texNumC;
+  int texC = texelIndex - texR * texNumC;
+  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
+}
+`;
+      const SAMPLE_3D_SNIPPET = `
+vec2 packedUVfrom3D(int texNumR, int texNumC,
+    int texelsInBatch, int texelsInLogicalRow, int b,
+    int row, int col) {
+  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
+  int texR = index / texNumC;
+  int texC = index - texR * texNumC;
+  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
+}
+`;
+      const SHADER_PACKED_PREFIX = `
+  float getChannel(vec4 frag, vec2 innerDims) {
+    vec2 modCoord = mod(innerDims, 2.);
+    return modCoord.x == 0. ?
+      (modCoord.y == 0. ? frag.r : frag.g) :
+      (modCoord.y == 0. ? frag.b : frag.a);
+  }
+  float getChannel(vec4 frag, int dim) {
+    float modCoord = mod(float(dim), 2.);
+    return modCoord == 0. ? frag.r : frag.g;
+  }
+`;
+      function getOutputScalarCoords() {
+        return `
+    int getOutputCoords() {
+      return 0;
+    }
+  `;
+      }
+      function getOutputPacked1DCoords(shape, texShape) {
+        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
+        if (packedTexShape[0] === 1) {
+          return `
+      int getOutputCoords() {
+        return 2 * int(resultUV.x * ${packedTexShape[1]}.0);
+      }
+    `;
+        }
+        if (packedTexShape[1] === 1) {
+          return `
+      int getOutputCoords() {
+        return 2 * int(resultUV.y * ${packedTexShape[0]}.0);
+      }
+    `;
+        }
+        return `
+    int getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
+      return 2 * (resTexRC.x * ${packedTexShape[1]} + resTexRC.y);
+    }
+  `;
+      }
+      function getOutput1DCoords(shape, texShape) {
+        if (texShape[0] === 1) {
+          return `
+      int getOutputCoords() {
+        return int(resultUV.x * ${texShape[1]}.0);
+      }
+    `;
+        }
+        if (texShape[1] === 1) {
+          return `
+      int getOutputCoords() {
+        return int(resultUV.y * ${texShape[0]}.0);
+      }
+    `;
+        }
+        return `
+    int getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+                             vec2(${texShape[0]}, ${texShape[1]}));
+      return resTexRC.x * ${texShape[1]} + resTexRC.y;
+    }
+  `;
+      }
+      function getOutputPacked3DCoords(shape, texShape) {
+        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
+        const texelsInLogicalRow = Math.ceil(shape[2] / 2);
+        const texelsInBatch = texelsInLogicalRow * Math.ceil(shape[1] / 2);
+        return `
+    ivec3 getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
+      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;
+
+      int b = index / ${texelsInBatch};
+      index -= b * ${texelsInBatch};
+
+      int r = 2 * (index / ${texelsInLogicalRow});
+      int c = imod(index, ${texelsInLogicalRow}) * 2;
+
+      return ivec3(b, r, c);
+    }
+  `;
+      }
+      function getOutput3DCoords(shape, texShape) {
+        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(["r", "c", "d"], shape);
+        return `
+    ivec3 getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+                             vec2(${texShape[0]}, ${texShape[1]}));
+      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
+      ${coordsFromIndexSnippet}
+      return ivec3(r, c, d);
+    }
+  `;
+      }
+      function getOutputPackedNDCoords(shape, texShape) {
+        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
+        const texelsInLogicalRow = Math.ceil(shape[shape.length - 1] / 2);
+        const texelsInBatch = texelsInLogicalRow * Math.ceil(shape[shape.length - 2] / 2);
+        let texelsInBatchN = texelsInBatch;
+        let batches = ``;
+        let coords = "b, r, c";
+        for (let b = 2; b < shape.length - 1; b++) {
+          texelsInBatchN *= shape[shape.length - b - 1];
+          batches =
+            `
+      int b${b} = index / ${texelsInBatchN};
+      index -= b${b} * ${texelsInBatchN};
+    ` + batches;
+          coords = `b${b}, ` + coords;
+        }
+        return `
+    ivec${shape.length} getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
+      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;
+
+      ${batches}
+
+      int b = index / ${texelsInBatch};
+      index -= b * ${texelsInBatch};
+
+      int r = 2 * (index / ${texelsInLogicalRow});
+      int c = imod(index, ${texelsInLogicalRow}) * 2;
+
+      return ivec${shape.length}(${coords});
+    }
+  `;
+      }
+      function getOutput4DCoords(shape, texShape) {
+        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(
+          ["r", "c", "d", "d2"],
+          shape
+        );
+        return `
+    ivec4 getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+        vec2(${texShape[0]}, ${texShape[1]}));
+      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
+      ${coordsFromIndexSnippet}
+      return ivec4(r, c, d, d2);
+    }
+  `;
+      }
+      function getOutput5DCoords(shape, texShape) {
+        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(
+          ["r", "c", "d", "d2", "d3"],
+          shape
+        );
+        return `
+    ivec5 getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${texShape[0]},
+                             ${texShape[1]}));
+
+      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
+
+      ${coordsFromIndexSnippet}
+
+      ivec5 outShape = ivec5(r, c, d, d2, d3);
+      return outShape;
+    }
+  `;
+      }
+      function getOutput6DCoords(shape, texShape) {
+        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(
+          ["r", "c", "d", "d2", "d3", "d4"],
+          shape
+        );
+        return `
+    ivec6 getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+        vec2(${texShape[0]}, ${texShape[1]}));
+      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
+
+      ${coordsFromIndexSnippet}
+
+      ivec6 result = ivec6(r, c, d, d2, d3, d4);
+      return result;
+    }
+  `;
+      }
+      function getOutputPacked2DCoords(shape, texShape) {
+        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
+        if (dist["util"].arraysEqual(shape, texShape)) {
+          return `
+      ivec2 getOutputCoords() {
+        return 2 * ivec2(resultUV.yx * vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
+      }
+    `;
+        }
+        // texels needed to accommodate a logical row
+        const texelsInLogicalRow = Math.ceil(shape[1] / 2);
+        /**
+         * getOutputCoords
+         *
+         * resTexRC: The rows and columns of the texels. If you move over one
+         * texel to the right in the packed texture, you are moving over one column
+         * (not two).
+         *
+         * index: The texel index
+         */
+        return `
+    ivec2 getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
+
+      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;
+      int r = 2 * (index / ${texelsInLogicalRow});
+      int c = imod(index, ${texelsInLogicalRow}) * 2;
+
+      return ivec2(r, c);
+    }
+  `;
+      }
+      function getOutput2DCoords(shape, texShape) {
+        if (dist["util"].arraysEqual(shape, texShape)) {
+          return `
+      ivec2 getOutputCoords() {
+        return ivec2(resultUV.yx * vec2(${texShape[0]}, ${texShape[1]}));
+      }
+    `;
+        }
+        if (shape[1] === 1) {
+          return `
+      ivec2 getOutputCoords() {
+        ivec2 resTexRC = ivec2(resultUV.yx *
+                               vec2(${texShape[0]}, ${texShape[1]}));
+        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
+        return ivec2(index, 0);
+      }
+    `;
+        }
+        if (shape[0] === 1) {
+          return `
+      ivec2 getOutputCoords() {
+        ivec2 resTexRC = ivec2(resultUV.yx *
+                               vec2(${texShape[0]}, ${texShape[1]}));
+        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
+        return ivec2(0, index);
+      }
+    `;
+        }
+        return `
+    ivec2 getOutputCoords() {
+      ivec2 resTexRC = ivec2(resultUV.yx *
+                             vec2(${texShape[0]}, ${texShape[1]}));
+      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
+      int r = index / ${shape[1]};
+      int c = index - r * ${shape[1]};
+      return ivec2(r, c);
+    }
+  `;
+      }
+      function getFlatOffsetUniformName(texName) {
+        return `offset${texName}`;
+      }
+      function getPackedSamplerScalar(inputInfo) {
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const glsl = getGlslDifferences();
+        return `
+    vec4 ${funcName}() {
+      return ${glsl.texture2D}(${texName}, halfCR);
+    }
+  `;
+      }
+      function getSamplerScalar(inputInfo) {
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        if (inputInfo.shapeInfo.isUniform) {
+          return `float ${funcName}() {return ${texName};}`;
+        }
+        const [texNumR, texNumC] = inputInfo.shapeInfo.texShape;
+        if (texNumR === 1 && texNumC === 1) {
+          return `
+      float ${funcName}() {
+        return sampleTexture(${texName}, halfCR);
+      }
+    `;
+        }
+        const [tNumR, tNumC] = inputInfo.shapeInfo.texShape;
+        const offset = getFlatOffsetUniformName(texName);
+        return `
+    float ${funcName}() {
+      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, ${offset});
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+      }
+      function getPackedSampler1D(inputInfo) {
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const texShape = inputInfo.shapeInfo.texShape;
+        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
+        const glsl = getGlslDifferences();
+        return `
+    vec4 ${funcName}(int index) {
+      vec2 uv = packedUVfrom1D(
+        ${packedTexShape[0]}, ${packedTexShape[1]}, index);
+      return ${glsl.texture2D}(${texName}, uv);
+    }
+  `;
+      }
+      function getSampler1D(inputInfo) {
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        if (inputInfo.shapeInfo.isUniform) {
+          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
+          return `
+      float ${funcName}(int index) {
+        ${getUniformSampler(inputInfo)}
+      }
+    `;
+        }
+        const texShape = inputInfo.shapeInfo.texShape;
+        const tNumR = texShape[0];
+        const tNumC = texShape[1];
+        if (tNumC === 1 && tNumR === 1) {
+          return `
+      float ${funcName}(int index) {
+        return sampleTexture(${texName}, halfCR);
+      }
+    `;
+        }
+        const offset = getFlatOffsetUniformName(texName);
+        if (tNumC === 1) {
+          return `
+      float ${funcName}(int index) {
+        vec2 uv = vec2(0.5, (float(index + ${offset}) + 0.5) / ${tNumR}.0);
+        return sampleTexture(${texName}, uv);
+      }
+    `;
+        }
+        if (tNumR === 1) {
+          return `
+      float ${funcName}(int index) {
+        vec2 uv = vec2((float(index + ${offset}) + 0.5) / ${tNumC}.0, 0.5);
+        return sampleTexture(${texName}, uv);
+      }
+    `;
+        }
+        return `
+    float ${funcName}(int index) {
+      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, index + ${offset});
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+      }
+      function getPackedSampler2D(inputInfo) {
+        const shape = inputInfo.shapeInfo.logicalShape;
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const texShape = inputInfo.shapeInfo.texShape;
+        const texNumR = texShape[0];
+        const texNumC = texShape[1];
+        const glsl = getGlslDifferences();
+        if (texShape != null && dist["util"].arraysEqual(shape, texShape)) {
+          return `
+      vec4 ${funcName}(int row, int col) {
+        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);
+
+        return ${glsl.texture2D}(${texName}, uv);
+      }
+    `;
+        }
+        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
+        const valuesPerRow = Math.ceil(shape[1] / 2);
+        return `
+    vec4 ${funcName}(int row, int col) {
+      vec2 uv = packedUVfrom2D(${valuesPerRow}, ${packedTexShape[0]}, ${packedTexShape[1]}, row, col);
+      return ${glsl.texture2D}(${texName}, uv);
+    }
+  `;
+      }
+      function getSampler2D(inputInfo) {
+        const shape = inputInfo.shapeInfo.logicalShape;
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const texShape = inputInfo.shapeInfo.texShape;
+        if (texShape != null && dist["util"].arraysEqual(shape, texShape)) {
+          const texNumR = texShape[0];
+          const texNumC = texShape[1];
+          return `
+    float ${funcName}(int row, int col) {
+      vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+        }
+        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
+        const squeezedShape = newShape;
+        if (squeezedShape.length < shape.length) {
+          const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);
+          const params = ["row", "col"];
+          return `
+      ${getSamplerFromInInfo(newInputInfo)}
+      float ${funcName}(int row, int col) {
+        return ${funcName}(${getSqueezedParams(params, keptDims)});
+      }
+    `;
+        }
+        if (inputInfo.shapeInfo.isUniform) {
+          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col) {
+        int index = round(dot(vec2(row, col), vec2(${shape[1]}, 1)));
+        ${getUniformSampler(inputInfo)}
+      }
+    `;
+        }
+        const texNumR = texShape[0];
+        const texNumC = texShape[1];
+        const offset = getFlatOffsetUniformName(texName);
+        if (texNumC === 1) {
+          // index is used directly as physical (no risk of float16 overflow).
+          return `
+    float ${funcName}(int row, int col) {
+      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));
+      vec2 uv = vec2(0.5, (index + 0.5) / ${texNumR}.0);
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+        }
+        if (texNumR === 1) {
+          // index is used directly as physical (no risk of float16 overflow).
+          return `
+    float ${funcName}(int row, int col) {
+      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));
+      vec2 uv = vec2((index + 0.5) / ${texNumC}.0, 0.5);
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+        }
+        return `
+  float ${funcName}(int row, int col) {
+    // Explicitly use integer operations as dot() only works on floats.
+    int index = row * ${shape[1]} + col + ${offset};
+    vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
+    return sampleTexture(${texName}, uv);
+  }
+`;
+      }
+      function getPackedSampler3D(inputInfo) {
+        const shape = inputInfo.shapeInfo.logicalShape;
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const texShape = inputInfo.shapeInfo.texShape;
+        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
+        if (shape[0] === 1) {
+          const squeezedShape = shape.slice(1);
+          const keptDims = [1, 2];
+          const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);
+          const params = ["b", "row", "col"];
+          return `
+        ${getPackedSamplerFromInInfo(newInputInfo)}
+        vec4 ${funcName}(int b, int row, int col) {
+          return ${funcName}(${getSqueezedParams(params, keptDims)});
+        }
+      `;
+        }
+        const texNumR = packedTexShape[0];
+        const texNumC = packedTexShape[1];
+        const valuesPerRow = Math.ceil(shape[2] / 2);
+        const texelsInBatch = valuesPerRow * Math.ceil(shape[1] / 2);
+        const glsl = getGlslDifferences();
+        return `
+    vec4 ${funcName}(int b, int row, int col) {
+      vec2 uv = packedUVfrom3D(
+        ${texNumR}, ${texNumC}, ${texelsInBatch}, ${valuesPerRow}, b, row, col);
+      return ${glsl.texture2D}(${texName}, uv);
+    }
+  `;
+      }
+      function getSampler3D(inputInfo) {
+        const shape = inputInfo.shapeInfo.logicalShape;
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const stride0 = shape[1] * shape[2];
+        const stride1 = shape[2];
+        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
+        const squeezedShape = newShape;
+        if (squeezedShape.length < shape.length) {
+          const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);
+          const params = ["row", "col", "depth"];
+          return `
+        ${getSamplerFromInInfo(newInputInfo)}
+        float ${funcName}(int row, int col, int depth) {
+          return ${funcName}(${getSqueezedParams(params, keptDims)});
+        }
+      `;
+        }
+        if (inputInfo.shapeInfo.isUniform) {
+          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth) {
+        int index = round(dot(vec3(row, col, depth),
+                          vec3(${stride0}, ${stride1}, 1)));
+        ${getUniformSampler(inputInfo)}
+      }
+    `;
+        }
+        const texShape = inputInfo.shapeInfo.texShape;
+        const texNumR = texShape[0];
+        const texNumC = texShape[1];
+        const flatOffset = inputInfo.shapeInfo.flatOffset;
+        if (texNumC === stride0 && flatOffset == null) {
+          // texC is used directly as physical (no risk of float16 overflow).
+          return `
+        float ${funcName}(int row, int col, int depth) {
+          float texR = float(row);
+          float texC = dot(vec2(col, depth), vec2(${stride1}, 1));
+          vec2 uv = (vec2(texC, texR) + halfCR) /
+                     vec2(${texNumC}.0, ${texNumR}.0);
+          return sampleTexture(${texName}, uv);
+        }
+      `;
+        }
+        if (texNumC === stride1 && flatOffset == null) {
+          // texR is used directly as physical (no risk of float16 overflow).
+          return `
+    float ${funcName}(int row, int col, int depth) {
+      float texR = dot(vec2(row, col), vec2(${shape[1]}, 1));
+      float texC = float(depth);
+      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+        }
+        const offset = getFlatOffsetUniformName(texName);
+        return `
+      float ${funcName}(int row, int col, int depth) {
+        // Explicitly use integer operations as dot() only works on floats.
+        int index = row * ${stride0} + col * ${stride1} + depth + ${offset};
+        vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
+        return sampleTexture(${texName}, uv);
+      }
+  `;
+      }
+      function getPackedSamplerND(inputInfo) {
+        const shape = inputInfo.shapeInfo.logicalShape;
+        const rank = shape.length;
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const texShape = inputInfo.shapeInfo.texShape;
+        const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];
+        const texNumR = packedTexShape[0];
+        const texNumC = packedTexShape[1];
+        const valuesPerRow = Math.ceil(shape[rank - 1] / 2);
+        let texelsInBatch = valuesPerRow * Math.ceil(shape[rank - 2] / 2);
+        let params = `int b, int row, int col`;
+        let index = `b * ${texelsInBatch} + (row / 2) * ${valuesPerRow} + (col / 2)`;
+        for (let b = 2; b < rank - 1; b++) {
+          params = `int b${b}, ` + params;
+          texelsInBatch *= shape[rank - b - 1];
+          index = `b${b} * ${texelsInBatch} + ` + index;
+        }
+        const glsl = getGlslDifferences();
+        return `
+    vec4 ${funcName}(${params}) {
+      int index = ${index};
+      int texR = index / ${texNumC};
+      int texC = index - texR * ${texNumC};
+      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}, ${texNumR});
+      return ${glsl.texture2D}(${texName}, uv);
+    }
+  `;
+      }
+      function getSampler4D(inputInfo) {
+        const shape = inputInfo.shapeInfo.logicalShape;
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const stride2 = shape[3];
+        const stride1 = shape[2] * stride2;
+        const stride0 = shape[1] * stride1;
+        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
+        if (newShape.length < shape.length) {
+          const newInputInfo = squeezeInputInfo(inputInfo, newShape);
+          const params = ["row", "col", "depth", "depth2"];
+          return `
+      ${getSamplerFromInInfo(newInputInfo)}
+      float ${funcName}(int row, int col, int depth, int depth2) {
+        return ${funcName}(${getSqueezedParams(params, keptDims)});
+      }
+    `;
+        }
+        if (inputInfo.shapeInfo.isUniform) {
+          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth, int depth2) {
+        int index = round(dot(vec4(row, col, depth, depth2),
+                          vec4(${stride0}, ${stride1}, ${stride2}, 1)));
+        ${getUniformSampler(inputInfo)}
+      }
+    `;
+        }
+        const flatOffset = inputInfo.shapeInfo.flatOffset;
+        const texShape = inputInfo.shapeInfo.texShape;
+        const texNumR = texShape[0];
+        const texNumC = texShape[1];
+        if (texNumC === stride0 && flatOffset == null) {
+          // texC is used directly as physical (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth, int depth2) {
+        float texR = float(row);
+        float texC =
+            dot(vec3(col, depth, depth2),
+                vec3(${stride1}, ${stride2}, 1));
+        vec2 uv = (vec2(texC, texR) + halfCR) /
+                   vec2(${texNumC}.0, ${texNumR}.0);
+        return sampleTexture(${texName}, uv);
+      }
+    `;
+        }
+        if (texNumC === stride2 && flatOffset == null) {
+          // texR is used directly as physical (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth, int depth2) {
+        float texR = dot(vec3(row, col, depth),
+                         vec3(${shape[1] * shape[2]}, ${shape[2]}, 1));
+        float texC = float(depth2);
+        vec2 uv = (vec2(texC, texR) + halfCR) /
+                  vec2(${texNumC}.0, ${texNumR}.0);
+        return sampleTexture(${texName}, uv);
+      }
+    `;
+        }
+        const offset = getFlatOffsetUniformName(texName);
+        return `
+    float ${funcName}(int row, int col, int depth, int depth2) {
+      // Explicitly use integer operations as dot() only works on floats.
+      int index = row * ${stride0} + col * ${stride1} +
+          depth * ${stride2} + depth2;
+      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index + ${offset});
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+      }
+      function getSampler5D(inputInfo) {
+        const shape = inputInfo.shapeInfo.logicalShape;
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const stride3 = shape[4];
+        const stride2 = shape[3] * stride3;
+        const stride1 = shape[2] * stride2;
+        const stride0 = shape[1] * stride1;
+        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
+        if (newShape.length < shape.length) {
+          const newInputInfo = squeezeInputInfo(inputInfo, newShape);
+          const params = ["row", "col", "depth", "depth2", "depth3"];
+          return `
+      ${getSamplerFromInInfo(newInputInfo)}
+      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
+        return ${funcName}(${getSqueezedParams(params, keptDims)});
+      }
+    `;
+        }
+        if (inputInfo.shapeInfo.isUniform) {
+          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
+        float index = dot(
+          vec4(row, col, depth, depth2),
+          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +
+          depth3;
+        ${getUniformSampler(inputInfo)}
+      }
+    `;
+        }
+        const flatOffset = inputInfo.shapeInfo.flatOffset;
+        const texShape = inputInfo.shapeInfo.texShape;
+        const texNumR = texShape[0];
+        const texNumC = texShape[1];
+        if (texNumC === stride0 && flatOffset == null) {
+          // texC is used directly as physical (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
+        int texR = row;
+        float texC = dot(vec4(col, depth, depth2, depth3),
+                         vec4(${stride1}, ${stride2}, ${stride3}, 1));
+        vec2 uv = (vec2(texC, texR) + halfCR) /
+                   vec2(${texNumC}.0, ${texNumR}.0);
+        return sampleTexture(${texName}, uv);
+      }
+    `;
+        }
+        if (texNumC === stride3 && flatOffset == null) {
+          // texR is used directly as physical (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
+        float texR = dot(
+          vec4(row, col, depth, depth2),
+          vec4(${shape[1] * shape[2] * shape[3]},
+               ${shape[2] * shape[3]}, ${shape[3]}, 1));
+        int texC = depth3;
+        vec2 uv = (vec2(texC, texR) + halfCR) /
+                  vec2(${texNumC}.0, ${texNumR}.0);
+        return sampleTexture(${texName}, uv);
+      }
+    `;
+        }
+        const offset = getFlatOffsetUniformName(texName);
+        return `
+    float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
+      // Explicitly use integer operations as dot() only works on floats.
+      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +
+          depth2 * ${stride3} + depth3 + ${offset};
+      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+      }
+      function getSampler6D(inputInfo) {
+        const shape = inputInfo.shapeInfo.logicalShape;
+        const texName = inputInfo.name;
+        const funcName = "get" + texName.charAt(0).toUpperCase() + texName.slice(1);
+        const { newShape, keptDims } = dist["util"].squeezeShape(shape);
+        if (newShape.length < shape.length) {
+          const newInputInfo = squeezeInputInfo(inputInfo, newShape);
+          const params = ["row", "col", "depth", "depth2", "depth3", "depth4"];
+          return `
+      ${getSamplerFromInInfo(newInputInfo)}
+      float ${funcName}(int row, int col, int depth,
+                    int depth2, int depth3, int depth4) {
+        return ${funcName}(${getSqueezedParams(params, keptDims)});
+      }
+    `;
+        }
+        const stride4 = shape[5];
+        const stride3 = shape[4] * stride4;
+        const stride2 = shape[3] * stride3;
+        const stride1 = shape[2] * stride2;
+        const stride0 = shape[1] * stride1;
+        if (inputInfo.shapeInfo.isUniform) {
+          // Uniform arrays will be less than 65505 (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth,
+                  int depth2, int depth3, int depth4) {
+        int index = round(dot(
+          vec4(row, col, depth, depth2),
+          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +
+          dot(
+            vec2(depth3, depth4),
+            vec2(${stride4}, 1)));
+        ${getUniformSampler(inputInfo)}
+      }
+    `;
+        }
+        const flatOffset = inputInfo.shapeInfo.flatOffset;
+        const texShape = inputInfo.shapeInfo.texShape;
+        const texNumR = texShape[0];
+        const texNumC = texShape[1];
+        if (texNumC === stride0 && flatOffset == null) {
+          // texC is used directly as physical (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth,
+                    int depth2, int depth3, int depth4) {
+        int texR = row;
+        float texC = dot(vec4(col, depth, depth2, depth3),
+          vec4(${stride1}, ${stride2}, ${stride3}, ${stride4})) +
+               float(depth4);
+        vec2 uv = (vec2(texC, texR) + halfCR) /
+                   vec2(${texNumC}.0, ${texNumR}.0);
+        return sampleTexture(${texName}, uv);
+      }
+    `;
+        }
+        if (texNumC === stride4 && flatOffset == null) {
+          // texR is used directly as physical (no risk of float16 overflow).
+          return `
+      float ${funcName}(int row, int col, int depth,
+                    int depth2, int depth3, int depth4) {
+        float texR = dot(vec4(row, col, depth, depth2),
+          vec4(${shape[1] * shape[2] * shape[3] * shape[4]},
+               ${shape[2] * shape[3] * shape[4]},
+               ${shape[3] * shape[4]},
+               ${shape[4]})) + float(depth3);
+        int texC = depth4;
+        vec2 uv = (vec2(texC, texR) + halfCR) /
+                  vec2(${texNumC}.0, ${texNumR}.0);
+        return sampleTexture(${texName}, uv);
+      }
+    `;
+        }
+        const offset = getFlatOffsetUniformName(texName);
+        return `
+    float ${funcName}(int row, int col, int depth,
+                  int depth2, int depth3, int depth4) {
+      // Explicitly use integer operations as dot() only works on floats.
+      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +
+          depth2 * ${stride3} + depth3 * ${stride4} + depth4 + ${offset};
+      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
+      return sampleTexture(${texName}, uv);
+    }
+  `;
+      }
+      function getUniformSampler(inputInfo) {
+        const texName = inputInfo.name;
+        const inSize = dist["util"].sizeFromShape(inputInfo.shapeInfo.logicalShape);
+        if (inSize < 2) {
+          return `return ${texName};`;
+        }
+        return `
+    for (int i = 0; i < ${inSize}; i++) {
+      if (i == index) {
+        return ${texName}[i];
+      }
+    }
+  `;
+      }
+      function getPackedSamplerAtOutputCoords(inputInfo, outShapeInfo) {
+        const texName = inputInfo.name;
+        const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);
+        const funcName = "get" + texFuncSnippet + "AtOutCoords";
+        const inRank = inputInfo.shapeInfo.logicalShape.length;
+        const outRank = outShapeInfo.logicalShape.length;
+        const broadcastDims = getBroadcastDims(
+          inputInfo.shapeInfo.logicalShape,
+          outShapeInfo.logicalShape
+        );
+        const type = getCoordsDataType(outRank);
+        const rankDiff = outRank - inRank;
+        let coordsSnippet;
+        const fields = ["x", "y", "z", "w", "u", "v"];
+        if (inRank === 0) {
+          coordsSnippet = "";
+        } else if (outRank < 2 && broadcastDims.length >= 1) {
+          coordsSnippet = "coords = 0;";
+        } else {
+          coordsSnippet = broadcastDims
+            .map((d) => `coords.${fields[d + rankDiff]} = 0;`)
+            .join("\n");
+        }
+        let unpackedCoordsSnippet = "";
+        if (outRank < 2 && inRank > 0) {
+          unpackedCoordsSnippet = "coords";
+        } else {
+          unpackedCoordsSnippet = inputInfo.shapeInfo.logicalShape
+            .map((s, i) => `coords.${fields[i + rankDiff]}`)
+            .join(", ");
+        }
+        let output = `return outputValue;`;
+        const inSize = dist["util"].sizeFromShape(inputInfo.shapeInfo.logicalShape);
+        const isInputScalar = inSize === 1;
+        const outSize = dist["util"].sizeFromShape(outShapeInfo.logicalShape);
+        const isOutputScalar = outSize === 1;
+        if (inRank === 1 && !isInputScalar && !isOutputScalar) {
+          output = `
+      return vec4(outputValue.xy, outputValue.xy);
+    `;
+        } else if (isInputScalar && !isOutputScalar) {
+          if (outRank === 1) {
+            output = `
+        return vec4(outputValue.x, outputValue.x, 0., 0.);
+      `;
+          } else {
+            output = `
+        return vec4(outputValue.x);
+      `;
+          }
+        } else if (broadcastDims.length) {
+          const rows = inRank - 2;
+          const cols = inRank - 1;
+          if (broadcastDims.indexOf(rows) > -1 && broadcastDims.indexOf(cols) > -1) {
+            output = `return vec4(outputValue.x);`;
+          } else if (broadcastDims.indexOf(rows) > -1) {
+            output =
+              `return vec4(outputValue.x, outputValue.y, ` + `outputValue.x, outputValue.y);`;
+          } else if (broadcastDims.indexOf(cols) > -1) {
+            output = `return vec4(outputValue.xx, outputValue.zz);`;
+          }
+        }
+        return `
+    vec4 ${funcName}() {
+      ${type} coords = getOutputCoords();
+      ${coordsSnippet}
+      vec4 outputValue = get${texFuncSnippet}(${unpackedCoordsSnippet});
+      ${output}
+    }
+  `;
+      }
+      function getSamplerAtOutputCoords(inputInfo, outShapeInfo) {
+        const texName = inputInfo.name;
+        const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);
+        const funcName = "get" + texFuncSnippet + "AtOutCoords";
+        const outTexShape = outShapeInfo.texShape;
+        const inTexShape = inputInfo.shapeInfo.texShape;
+        const inRank = inputInfo.shapeInfo.logicalShape.length;
+        const outRank = outShapeInfo.logicalShape.length;
+        if (
+          !inputInfo.shapeInfo.isUniform &&
+          inRank === outRank &&
+          inputInfo.shapeInfo.flatOffset == null &&
+          dist["util"].arraysEqual(inTexShape, outTexShape)
+        ) {
+          return `
+      float ${funcName}() {
+        return sampleTexture(${texName}, resultUV);
+      }
+    `;
+        }
+        const type = getCoordsDataType(outRank);
+        const broadcastDims = getBroadcastDims(
+          inputInfo.shapeInfo.logicalShape,
+          outShapeInfo.logicalShape
+        );
+        const rankDiff = outRank - inRank;
+        let coordsSnippet;
+        const fields = ["x", "y", "z", "w", "u", "v"];
+        if (inRank === 0) {
+          coordsSnippet = "";
+        } else if (outRank < 2 && broadcastDims.length >= 1) {
+          coordsSnippet = "coords = 0;";
+        } else {
+          coordsSnippet = broadcastDims
+            .map((d) => `coords.${fields[d + rankDiff]} = 0;`)
+            .join("\n");
+        }
+        let unpackedCoordsSnippet = "";
+        if (outRank < 2 && inRank > 0) {
+          unpackedCoordsSnippet = "coords";
+        } else {
+          unpackedCoordsSnippet = inputInfo.shapeInfo.logicalShape
+            .map((s, i) => `coords.${fields[i + rankDiff]}`)
+            .join(", ");
+        }
+        return `
+    float ${funcName}() {
+      ${type} coords = getOutputCoords();
+      ${coordsSnippet}
+      return get${texFuncSnippet}(${unpackedCoordsSnippet});
+    }
+  `;
+      }
+      function getCoordsDataType(rank) {
+        if (rank <= 1) {
+          return "int";
+        } else if (rank === 2) {
+          return "ivec2";
+        } else if (rank === 3) {
+          return "ivec3";
+        } else if (rank === 4) {
+          return "ivec4";
+        } else if (rank === 5) {
+          return "ivec5";
+        } else if (rank === 6) {
+          return "ivec6";
+        } else {
+          throw Error(`GPU for rank ${rank} is not yet supported`);
+        }
+      }
+      /** Returns a new input info (a copy) that has a squeezed logical shape. */
+      function squeezeInputInfo(inInfo, squeezedShape) {
+        // Deep copy.
+        const newInputInfo = JSON.parse(JSON.stringify(inInfo));
+        newInputInfo.shapeInfo.logicalShape = squeezedShape;
+        return newInputInfo;
+      }
+      function getSqueezedParams(params, keptDims) {
+        return keptDims.map((d) => params[d]).join(", ");
+      }
+      //# sourceMappingURL=shader_compiler.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/argminmax_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class argminmax_packed_gpu_ArgMinMaxPackedProgram {
+        constructor(shape, windowSize, op, firstPass) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          dist["util"].assert(
+            shape.length > 2,
+            () =>
+              `Packed arg${
+                op.charAt(0).toUpperCase() + op.slice(1)
+              } supports only inputs with rank above 2.`
+          );
+          const inSize = shape[shape.length - 1];
+          const outSize = Math.ceil(inSize / windowSize);
+          this.outputShape = shape.slice(0, -1);
+          if (outSize > 1) {
+            this.outputShape.push(outSize);
+          }
+          if (!firstPass) {
+            this.variableNames.push("bestIndicesA");
+          }
+          const outShape = this.outputShape;
+          const rank = outShape.length;
+          const dtype = getCoordsDataType(rank);
+          const coords = getChannels("coords", rank);
+          let sourceLocSetup;
+          let sourceRank;
+          if (outSize === 1) {
+            sourceRank = rank + 1;
+            const sourceLocDType = getCoordsDataType(sourceRank);
+            sourceLocSetup = `
+        ${sourceLocDType} sourceLocR = ${sourceLocDType}(${coords.join()}, 0);
+        ++${coords[rank - 1]};
+        ${sourceLocDType} sourceLocG = ${sourceLocDType}(${coords.join()}, 0);
+        ++${coords[rank - 2]};
+        ${sourceLocDType} sourceLocA = ${sourceLocDType}(${coords.join()}, 0);
+        --${coords[rank - 1]};
+        ${sourceLocDType} sourceLocB = ${sourceLocDType}(${coords.join()}, 0);
+        --${coords[rank - 2]};`;
+          } else {
+            sourceRank = rank;
+            sourceLocSetup = `
+        ${dtype} sourceLocR = coords;
+        ++${coords[rank - 1]};
+        ${dtype} sourceLocG = coords;
+        ++${coords[rank - 2]};
+        ${dtype} sourceLocA = coords;
+        --${coords[rank - 1]};
+        ${dtype} sourceLocB = coords;
+        --${coords[rank - 2]};`;
+          }
+          const channels = ["x", "y", "z", "w", "u", "v"].slice(0, sourceRank);
+          const inChannel = "." + channels[sourceRank - 1]; // e.g. ".b" for rank 3.
+          const intChannels = channels.map((x) => "int " + x);
+          const srcRCoords = getChannels("sourceLocR", sourceRank - 1).concat("inIdx.r");
+          const srcGCoords = getChannels("sourceLocG", sourceRank - 1).concat("inIdx.g");
+          const srcBCoords = getChannels("sourceLocB", sourceRank - 1).concat("inIdx.b");
+          const srcACoords = getChannels("sourceLocA", sourceRank - 1).concat("inIdx.a");
+          const compOp = op === "max" ? "greaterThan" : "lessThan";
+          const fetchCandidateIdx = firstPass
+            ? ""
+            : `
+          inIdx = round(vec4(getBestIndicesAChannel(${srcRCoords.join()}),
+                             getBestIndicesAChannel(${srcGCoords.join()}),
+                             getBestIndicesAChannel(${srcBCoords.join()}),
+                             getBestIndicesAChannel(${srcACoords.join()})));`;
+          const fetchValue = `vec4(
+            getAChannel(${srcRCoords.join()}),
+            hasNextCol ? getAChannel(${srcGCoords.join()}) : 0.,
+            hasNextRow ? getAChannel(${srcBCoords.join()}) : 0.,
+            hasNextRow && hasNextCol ? getAChannel(${srcACoords.join()}) : 0.)`;
+          const getBestIndicesAChannelSnippet = firstPass
+            ? ""
+            : `
+      float getBestIndicesAChannel(${intChannels.join()}) {
+        return getChannel(getBestIndicesA(${channels.join()}),
+                                          vec2(${channels.slice(-2).join()}));
+      }`;
+          this.userCode = `
+      float getAChannel(${intChannels.join()}) {
+        return getChannel(getA(${channels.join()}),
+                               vec2(${channels.slice(-2).join()}));
+      }
+      ${getBestIndicesAChannelSnippet}
+      void main() {
+        ${dtype} coords = getOutputCoords();
+        bool hasNextCol = ${coords[rank - 1]} < ${outShape[rank - 1] - 1};
+        bool hasNextRow = ${coords[rank - 2]} < ${outShape[rank - 2] - 1};
+        ${sourceLocSetup}
+        ivec4 srcIdx = ivec4(sourceLocR${inChannel}, sourceLocG${inChannel},
+          sourceLocB${inChannel}, sourceLocA${inChannel}) * ${windowSize};
+        ivec4 inIdx = srcIdx;
+        vec4 bestIndex = vec4(inIdx);
+        vec4 bestValue = ${fetchValue};
+
+        for (int i = 0; i < ${windowSize}; i++) {
+          inIdx = srcIdx;
+          ${fetchCandidateIdx}
+          vec4 candidate = ${fetchValue};
+          bvec4 nan = isnan(candidate);
+          bvec4 replace = bvec4(
+            vec4(${compOp}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
+
+          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
+                           replace.y  ? candidate.y : bestValue.y,
+                           replace.z  ? candidate.z : bestValue.z,
+                           replace.w  ? candidate.w : bestValue.w);
+          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
+          srcIdx++;
+        }
+        setOutput(bestIndex);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=argminmax_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/avg_pool_backprop_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class AvgPool2DBackpropProgram {
+        constructor(convInfo) {
+          this.variableNames = ["dy"];
+          this.outputShape = convInfo.inShape;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+          const avgMultiplier = 1 / (filterHeight * filterWidth);
+          this.userCode = `
+      const ivec2 pads = ivec2(${padTop}, ${padLeft});
+      const float avgMultiplier = float(${avgMultiplier});
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int d = coords[3];
+
+        ivec2 dyRCCorner = coords.yz - pads;
+        int dyRCorner = dyRCCorner.x;
+        int dyCCorner = dyRCCorner.y;
+
+        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
+        // ? = to be determined. : = across all values in that axis.
+        float dotProd = 0.0;
+        for (int wR = 0; wR < ${effectiveFilterHeight};
+            wR += ${dilationHeight}) {
+          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
+
+          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {
+            continue;
+          }
+          int idyR = int(dyR);
+
+          for (int wC = 0; wC < ${effectiveFilterWidth};
+            wC+= ${dilationWidth}) {
+            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
+
+            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
+                fract(dyC) > 0.0) {
+              continue;
+            }
+            int idyC = int(dyC);
+
+            float dyValue = getDy(b, idyR, idyC, d);
+
+            dotProd += dyValue * avgMultiplier;
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      class AvgPool3DBackpropProgram {
+        constructor(convInfo) {
+          this.variableNames = ["dy"];
+          this.outputShape = convInfo.inShape;
+          const filterDepth = convInfo.filterDepth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
+          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+          const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);
+          this.userCode = `
+      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
+      const float avgMultiplier = float(${avgMultiplier});
+
+      void main() {
+        ivec5 coords = getOutputCoords();
+        int batch = coords.x;
+        int ch = coords.u;
+
+        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
+        int dyDCorner = dyCorner.x;
+        int dyRCorner = dyCorner.y;
+        int dyCCorner = dyCorner.z;
+
+        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
+        // dx(xD, xR, xC, ch).
+        // ? = to be determined. : = across all values in that axis.
+        float dotProd = 0.0;
+
+        for (int wD = 0; wD < ${effectiveFilterDepth};
+            wD += ${dilationDepth}) {
+          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;
+
+          if (dyD < 0.0 || dyD >= ${convInfo.outDepth}.0 || fract(dyD) > 0.0) {
+            continue;
+          }
+          int idyD = int(dyD);
+
+          for (int wR = 0; wR < ${effectiveFilterHeight};
+              wR += ${dilationHeight}) {
+            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
+
+            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||
+                fract(dyR) > 0.0) {
+              continue;
+            }
+            int idyR = int(dyR);
+
+            for (int wC = 0; wC < ${effectiveFilterWidth};
+                wC += ${dilationWidth}) {
+              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
+
+              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
+                  fract(dyC) > 0.0) {
+                continue;
+              }
+              int idyC = int(dyC);
+
+              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
+
+              dotProd += dyValue * avgMultiplier;
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=avg_pool_backprop_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/batchnorm_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class batchnorm_gpu_BatchNormProgram {
+        constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {
+          this.outputShape = [];
+          this.variableNames = ["x", "mean", "variance"];
+          dist["backend_util"].assertAndGetBroadcastShape(xShape, meanShape);
+          dist["backend_util"].assertAndGetBroadcastShape(xShape, varianceShape);
+          let offsetSnippet = "0.0";
+          if (offsetShape != null) {
+            dist["backend_util"].assertAndGetBroadcastShape(xShape, offsetShape);
+            this.variableNames.push("offset");
+            offsetSnippet = "getOffsetAtOutCoords()";
+          }
+          let scaleSnippet = "1.0";
+          if (scaleShape != null) {
+            dist["backend_util"].assertAndGetBroadcastShape(xShape, scaleShape);
+            this.variableNames.push("scale");
+            scaleSnippet = "getScaleAtOutCoords()";
+          }
+          this.outputShape = xShape;
+          this.userCode = `
+      void main() {
+        float x = getXAtOutCoords();
+        float mean = getMeanAtOutCoords();
+        float variance = getVarianceAtOutCoords();
+        float offset = ${offsetSnippet};
+        float scale = ${scaleSnippet};
+        float inv = scale * inversesqrt(variance + float(${varianceEpsilon}));
+        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=batchnorm_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/batchnorm_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class batchnorm_packed_gpu_BatchNormPackedProgram {
+        constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.variableNames = ["x", "mean", "variance"];
+          dist["backend_util"].assertAndGetBroadcastShape(xShape, meanShape);
+          dist["backend_util"].assertAndGetBroadcastShape(xShape, varianceShape);
+          let offsetSnippet = "vec4(0.0)";
+          if (offsetShape != null) {
+            dist["backend_util"].assertAndGetBroadcastShape(xShape, offsetShape);
+            this.variableNames.push("offset");
+            offsetSnippet = "getOffsetAtOutCoords()";
+          }
+          let scaleSnippet = "vec4(1.0)";
+          if (scaleShape != null) {
+            dist["backend_util"].assertAndGetBroadcastShape(xShape, scaleShape);
+            this.variableNames.push("scale");
+            scaleSnippet = "getScaleAtOutCoords()";
+          }
+          this.outputShape = xShape;
+          this.userCode = `
+      void main() {
+        vec4 offset = ${offsetSnippet};
+        vec4 scale = ${scaleSnippet};
+
+        vec4 x = getXAtOutCoords();
+        vec4 mean = getMeanAtOutCoords();
+        vec4 variance = getVarianceAtOutCoords();
+
+        vec4 inv = scale * inversesqrt(variance + vec4(${varianceEpsilon}));
+
+        setOutput((x - mean) * inv + offset);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=batchnorm_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_complex_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // (Ar + Ai)(Br + Bi) =
+      // ArBr + ArBi + AiBr + AiBi = ArBr - AB + ArBi + AiBr
+      // Yr = ArBr - AB
+      // Yi = ArBi + AiBr
+      const COMPLEX_MULTIPLY = {
+        REAL: "return areal * breal - aimag * bimag;",
+        IMAG: "return areal * bimag + aimag * breal;",
+      };
+      class binaryop_complex_gpu_BinaryOpComplexProgram {
+        constructor(op, aShape, bShape) {
+          this.variableNames = ["AReal", "AImag", "BReal", "BImag"];
+          this.outputShape = dist["backend_util"].assertAndGetBroadcastShape(aShape, bShape);
+          this.userCode = `
+      float binaryOpComplex(
+          float areal, float aimag, float breal, float bimag) {
+        ${op}
+      }
+
+      void main() {
+        float areal = getARealAtOutCoords();
+        float aimag = getAImagAtOutCoords();
+        float breal = getBRealAtOutCoords();
+        float bimag = getBImagAtOutCoords();
+        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=binaryop_complex_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const CHECK_NAN_SNIPPET = `
+  if (isnan(a)) return a;
+  if (isnan(b)) return b;
+`;
+      const ADD = "return a + b;";
+      const SUB = "return a - b;";
+      const MUL = "return a * b;";
+      // Without the equality check div produces 0.9999 for a = b, which when
+      // floored can cause errors.
+      const DIV = `
+if (a == b) {
+  return 1.0;
+};
+return a / b;`;
+      // We use native integer division to deal with floating point imprecision. Since
+      // we implement floor division and glsl implements truncated division, we
+      // correct for this by subtracting 1 from result when the result is negative and
+      // there is a remainder.
+      const INT_DIV = `
+  float s = sign(a) * sign(b);
+  int ia = round(a);
+  int ib = round(b);
+  if (ib != 0) {
+    // Windows (D3D) wants guaranteed non-zero int division at compile-time.
+    return float(idiv(ia, ib, s));
+  } else {
+    return NAN;
+  }
+`;
+      const POW = `
+if(a < 0.0 && floor(b) < b){
+  return NAN;
+}
+if (b == 0.0) {
+  return 1.0;
+}
+return (round(mod(b, 2.0)) != 1) ?
+    pow(abs(a), b) : sign(a) * pow(abs(a), b);
+`;
+      const binaryop_gpu_SQUARED_DIFFERENCE = "return (a - b) * (a - b);";
+      const EQUAL = `return float(a == b);`;
+      const NOT_EQUAL = `return float(a != b);`;
+      const LESS = `return float(a < b);`;
+      const LESS_EQUAL = `return float(a <= b);`;
+      const GREATER = `return float(a > b);`;
+      const GREATER_EQUAL = `return float(a >= b);`;
+      const LOGICAL_AND = `return float(a >= 1.0 && b >= 1.0);`;
+      const LOGICAL_OR = `return float(a >= 1.0 || b >= 1.0);`;
+      const MAX =
+        CHECK_NAN_SNIPPET +
+        `
+  return max(a, b);
+`;
+      const MIN =
+        CHECK_NAN_SNIPPET +
+        `
+  return min(a, b);
+`;
+      const MOD = `if (b == 0.0) return NAN;
+  return mod(a, b);`;
+      const ATAN2 =
+        CHECK_NAN_SNIPPET +
+        `
+  return atan(a, b);
+`;
+      const ELU_DER = `return (b >= 1.0) ? a : a * (b + 1.0);`;
+      const PRELU = `return (a < 0.) ? b * a : a;`;
+      class binaryop_gpu_BinaryOpProgram {
+        constructor(op, aShape, bShape) {
+          this.variableNames = ["A", "B"];
+          this.outputShape = dist["backend_util"].assertAndGetBroadcastShape(aShape, bShape);
+          this.userCode = `
+      float binaryOperation(float a, float b) {
+        ${op}
+      }
+
+      void main() {
+        float a = getAAtOutCoords();
+        float b = getBAtOutCoords();
+        setOutput(binaryOperation(a, b));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=binaryop_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const binaryop_packed_gpu_CHECK_NAN_SNIPPET = `
+  result.r = isNaN.r > 0. ? NAN : result.r;
+  result.g = isNaN.g > 0. ? NAN : result.g;
+  result.b = isNaN.b > 0. ? NAN : result.b;
+  result.a = isNaN.a > 0. ? NAN : result.a;
+`;
+      // We do the same as in ./binaryop_gpu, with vec4 and ivec4.
+      // On Linux, the vectorized implementation produces NaNs when a and b are 0.
+      const binaryop_packed_gpu_DIV = `
+  // vec4 one = vec4(equal(a, b));
+  // return one + (vec4(1.0) - one) * a / b;
+  vec4 result = a / b;
+  if(a.x == b.x) {
+    result.x = 1.;
+  }
+  if(a.y == b.y) {
+    result.y = 1.;
+  }
+  if(a.z == b.z) {
+    result.z = 1.;
+  }
+  if(a.w == b.w) {
+    result.w = 1.;
+  }
+
+  return result;
+`;
+      const binaryop_packed_gpu_INT_DIV = `
+  ivec4 ia = round(a);
+  ivec4 ib = round(b);
+  bvec4 cond = notEqual(ib, ivec4(0));
+  ivec4 result = ivec4(0);
+  vec4 s = sign(a) * sign(b);
+
+  // Windows (D3D) wants guaranteed non-zero int division at compile-time.
+  if (cond[0]) {
+    result[0] = idiv(ia[0], ib[0], s[0]);
+  }
+  if (cond[1]) {
+    result[1] = idiv(ia[1], ib[1], s[1]);
+  }
+  if (cond[2]) {
+    result[2] = idiv(ia[2], ib[2], s[2]);
+  }
+  if (cond[3]) {
+    result[3] = idiv(ia[3], ib[3], s[3]);
+  }
+  return vec4(result);
+`;
+      const binaryop_packed_gpu_POW =
+        `
+  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
+  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
+  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
+  vec4 result = multiplier * pow(abs(a), b);
+
+  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
+  bvec4 isExpZero = equal(b, vec4(0.0));
+  result.r = isExpZero.r ? 1.0 : result.r;
+  result.g = isExpZero.g ? 1.0 : result.g;
+  result.b = isExpZero.b ? 1.0 : result.b;
+  result.a = isExpZero.a ? 1.0 : result.a;
+
+  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
+  ` +
+        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
+        `
+  return result;
+`;
+      const binaryop_packed_gpu_PRELU = `
+  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
+  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
+`;
+      const binaryop_packed_gpu_ELU_DER = `
+  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
+  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
+`;
+      const binaryop_packed_gpu_ATAN2 =
+        `
+  vec4 result = atan(a, b);
+  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
+  ` +
+        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
+        `
+  return result;
+`;
+      const binaryop_packed_gpu_EQUAL = `
+  return vec4(equal(a, b));
+`;
+      const binaryop_packed_gpu_NOT_EQUAL = `
+  return vec4(notEqual(a, b));
+`;
+      const binaryop_packed_gpu_LESS = `
+  return vec4(lessThan(a, b));
+`;
+      const binaryop_packed_gpu_LESS_EQUAL = `
+  return vec4(lessThanEqual(a, b));
+`;
+      const binaryop_packed_gpu_GREATER = `
+  return vec4(greaterThan(a, b));
+`;
+      const binaryop_packed_gpu_GREATER_EQUAL = `
+  return vec4(greaterThanEqual(a, b));
+`;
+      const binaryop_packed_gpu_LOGICAL_AND = `
+  return vec4(
+    vec4(greaterThanEqual(a, vec4(1.0))) *
+    vec4(greaterThanEqual(b, vec4(1.0))));
+`;
+      const binaryop_packed_gpu_LOGICAL_OR = `
+  return min(
+    vec4(greaterThanEqual(a, vec4(1.0))) +
+    vec4(greaterThanEqual(b, vec4(1.0))),
+    vec4(1.0));
+`;
+      const binaryop_packed_gpu_MAX =
+        `
+  vec4 result = vec4(max(a, b));
+  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
+  ` +
+        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
+        `
+  return result;
+`;
+      const binaryop_packed_gpu_MIN =
+        `
+  vec4 result = vec4(min(a, b));
+  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
+  ` +
+        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
+        `
+  return result;
+`;
+      const binaryop_packed_gpu_MOD =
+        `
+  vec4 result = mod(a, b);
+  vec4 isNaN = vec4(equal(b, vec4(0.0)));
+  ` +
+        binaryop_packed_gpu_CHECK_NAN_SNIPPET +
+        `
+  return result;
+`;
+      class binaryop_packed_gpu_BinaryOpPackedProgram {
+        constructor(op, aShape, bShape, checkOutOfBounds = false) {
+          this.variableNames = ["A", "B"];
+          this.supportsBroadcasting = true;
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = dist["backend_util"].assertAndGetBroadcastShape(aShape, bShape);
+          const rank = this.outputShape.length;
+          let checkOutOfBoundsString = "";
+          if (checkOutOfBounds) {
+            if (rank === 0 || dist["util"].sizeFromShape(this.outputShape) === 1) {
+              checkOutOfBoundsString = `
+          result.y = 0.;
+          result.z = 0.;
+          result.w = 0.;
+        `;
+            } else {
+              const dtype = getCoordsDataType(rank);
+              checkOutOfBoundsString = `
+          ${dtype} coords = getOutputCoords();
+        `;
+              if (rank === 1) {
+                checkOutOfBoundsString += `
+            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
+            result.z = 0.;
+            result.w = 0.;
+          `;
+              } else {
+                const channels = getChannels("coords", rank);
+                checkOutOfBoundsString += `
+            bool nextRowOutOfBounds =
+              (${channels[rank - 2]} + 1) >= ${this.outputShape[rank - 2]};
+            bool nextColOutOfBounds =
+              (${channels[rank - 1]} + 1) >= ${this.outputShape[rank - 1]};
+            result.y = nextColOutOfBounds ? 0. : result.y;
+            result.z = nextRowOutOfBounds ? 0. : result.z;
+            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
+          `;
+              }
+            }
+          }
+          this.userCode = `
+      vec4 binaryOperation(vec4 a, vec4 b) {
+        ${op}
+      }
+
+      void main() {
+        vec4 a = getAAtOutCoords();
+        vec4 b = getBAtOutCoords();
+
+        vec4 result = binaryOperation(a, b);
+        ${checkOutOfBoundsString}
+
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=binaryop_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/clip_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ClipProgram {
+        constructor(aShape) {
+          this.variableNames = ["A"];
+          this.outputShape = aShape;
+          this.userCode = `
+      uniform float minVal;
+      uniform float maxVal;
+
+      void main() {
+        float value = getAAtOutCoords();
+        if (isnan(value)) {
+          setOutput(value);
+          return;
+        }
+
+        setOutput(clamp(value, minVal, maxVal));
+      }
+    `;
+        }
+        getCustomSetupFunc(min, max) {
+          return (gpgpu, webGLProgram) => {
+            if (this.minLoc == null) {
+              this.minLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "minVal");
+              this.maxLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "maxVal");
+            }
+            gpgpu.gl.uniform1f(this.minLoc, min);
+            gpgpu.gl.uniform1f(this.maxLoc, max);
+          };
+        }
+      }
+      //# sourceMappingURL=clip_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/clip_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ClipPackedProgram {
+        constructor(aShape) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = aShape;
+          this.userCode = `
+      uniform float minVal;
+      uniform float maxVal;
+
+      void main() {
+        vec4 value = getAAtOutCoords();
+
+        if (any(isnan(value))) {
+          setOutput(value);
+          return;
+        }
+
+        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
+      }
+    `;
+        }
+        getCustomSetupFunc(min, max) {
+          return (gpgpu, webGLProgram) => {
+            if (this.minLoc == null) {
+              this.minLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "minVal");
+              this.maxLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "maxVal");
+            }
+            gpgpu.gl.uniform1f(this.minLoc, min);
+            gpgpu.gl.uniform1f(this.maxLoc, max);
+          };
+        }
+      }
+      //# sourceMappingURL=clip_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/complex_abs_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ComplexAbsProgram {
+        constructor(shape) {
+          this.variableNames = ["real", "imag"];
+          this.outputShape = shape;
+          this.userCode = `
+      void main() {
+        float re = abs(getRealAtOutCoords());
+        float im = abs(getImagAtOutCoords());
+        float mx = max(re, im);
+
+        // sadly the length function in glsl is not underflow-safe
+        // (at least not on Intel GPUs). So the safe solution is
+        // to ensure underflow-safety in all cases.
+        setOutput(
+          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
+        );
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=complex_abs_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/concat_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class concat_gpu_ConcatProgram {
+        // Concats 2d tensors along axis=1. See comments in MathBackendWebGL.concat().
+        constructor(shapes) {
+          this.outputShape = [];
+          this.outputShape = dist["backend_util"].computeOutShape(shapes, 1 /* axis */);
+          this.variableNames = shapes.map((_, i) => `T${i}`);
+          const offsets = new Array(shapes.length - 1);
+          offsets[0] = shapes[0][1];
+          for (let i = 1; i < offsets.length; i++) {
+            offsets[i] = offsets[i - 1] + shapes[i][1];
+          }
+          const snippets = [`if (yC < ${offsets[0]}) setOutput(getT0(yR, yC));`];
+          for (let i = 1; i < offsets.length; i++) {
+            const shift = offsets[i - 1];
+            snippets.push(
+              `else if (yC < ${offsets[i]}) ` + `setOutput(getT${i}(yR, yC-${shift}));`
+            );
+          }
+          const lastIndex = offsets.length;
+          const lastShift = offsets[offsets.length - 1];
+          snippets.push(`else setOutput(getT${lastIndex}(yR, yC-${lastShift}));`);
+          this.userCode = `
+      void main() {
+        ivec2 coords = getOutputCoords();
+        int yR = coords.x;
+        int yC = coords.y;
+
+        ${snippets.join("\n        ")}
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=concat_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/concat_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class concat_packed_gpu_ConcatPackedProgram {
+        constructor(shapes, axis) {
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = [];
+          this.outputShape = dist["backend_util"].computeOutShape(shapes, axis);
+          const shape = this.outputShape;
+          const rank = shape.length;
+          const dtype = getCoordsDataType(rank);
+          const coords = getChannels("coords", rank);
+          const channels = ["x", "y", "z", "w", "u", "v"].slice(0, rank);
+          this.variableNames = shapes.map((_, i) => `T${i}`);
+          const offsets = new Array(shapes.length - 1);
+          offsets[0] = shapes[0][axis];
+          for (let i = 1; i < offsets.length; i++) {
+            offsets[i] = offsets[i - 1] + shapes[i][axis];
+          }
+          const channel = channels[axis];
+          const lastChannels = channels.slice(-2);
+          const allChannels = channels.join();
+          let getValueSnippet = `if (${channel} < ${offsets[0]}) {
+        return getChannel(
+            getT0(${allChannels}), vec2(${lastChannels.join()}));
+        }`;
+          for (let i = 1; i < offsets.length; i++) {
+            const shift = offsets[i - 1];
+            // Note: the >= comparison below may seem unnecessary given the check
+            // above but is needed to workaround branch execution issues on some
+            // devices. It makes all the conditions exclusive without relying on
+            // execution order.
+            getValueSnippet += `
+        if (${channel} < ${offsets[i]}  && ${channel} >= ${offsets[i - 1]}) {
+          return getChannel(
+            getT${i}(${shiftedChannels(channels, channel, shift)}),
+            vec2(${shiftedChannels(lastChannels, channel, shift)}));
+        }`;
+          }
+          const lastIndex = offsets.length;
+          const shift = offsets[offsets.length - 1];
+          getValueSnippet += `
+        return getChannel(
+          getT${lastIndex}(${shiftedChannels(channels, channel, shift)}),
+          vec2(${shiftedChannels(lastChannels, channel, shift)}));`;
+          this.userCode = `
+      float getValue(${channels.map((x) => "int " + x)}) {
+        ${getValueSnippet}
+      }
+
+      void main() {
+        ${dtype} coords = getOutputCoords();
+        vec4 result = vec4(getValue(${coords}), 0., 0., 0.);
+
+        ${coords[rank - 1]} = ${coords[rank - 1]} + 1;
+        if (${coords[rank - 1]} < ${shape[rank - 1]}) {
+          result.g = getValue(${coords});
+        }
+
+        ${coords[rank - 2]} = ${coords[rank - 2]} + 1;
+        if (${coords[rank - 2]} < ${shape[rank - 2]}) {
+          result.a = getValue(${coords});
+        }
+
+        ${coords[rank - 1]} = ${coords[rank - 1]} - 1;
+        if (${coords[rank - 2]} < ${shape[rank - 2]} &&
+            ${coords[rank - 1]} < ${shape[rank - 1]}) {
+          result.b = getValue(${coords});
+        }
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      /**
+       * Return an expression for coordinates into a vector where a given channel
+       * will be offset by [shift].
+       *
+       * @param channels the channels to consider
+       * @param channel the channel we want shifted
+       * @param shift  the amount to subtract from the channel.
+       *
+       * @returns a string of the form 'x, y-[shift], z' where any one channel can
+       * have the shift applied.
+       */
+      function shiftedChannels(channels, channel, shift) {
+        const channelIdx = channels.indexOf(channel);
+        const res = channels.map((c, idx) => {
+          if (idx === channelIdx) {
+            return `${c} - ${shift}`;
+          } else {
+            return c;
+          }
+        });
+        return res.join();
+      }
+      //# sourceMappingURL=concat_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_backprop_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class Conv2DDerFilterProgram {
+        constructor(convInfo) {
+          this.variableNames = ["x", "dy"];
+          this.outputShape = convInfo.filterShape;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          const isChannelsLast = convInfo.dataFormat === "channelsLast";
+          this.userCode = `
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int wR = coords.x;
+        int wC = coords.y;
+        int d1 = coords.z;
+        int d2 = coords.w;
+
+        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
+        // ? = to be determined. : = across all values in that axis.
+        float dotProd = 0.0;
+
+        for (int b = 0; b < ${convInfo.batchSize}; b++) {
+          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {
+            int xR = wR + yR * ${strideHeight} - ${padTop};
+
+            if (xR < 0 || xR >= ${convInfo.inHeight}) {
+              continue;
+            }
+
+            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
+              int xC = wC + yC * ${strideWidth} - ${padLeft};
+
+              if (xC < 0 || xC >= ${convInfo.inWidth}) {
+                continue;
+              }
+
+              if (${isChannelsLast}) {
+                float dyValue = getDy(b, yR, yC, d2);
+                float xValue = getX(b, xR, xC, d1);
+                dotProd += (xValue * dyValue);
+              } else {
+                float dyValue = getDy(b, d2, yR, yC);
+                float xValue = getX(b, d1, xR, xC);
+                dotProd += (xValue * dyValue);
+              }
+
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      class Conv2DDerInputProgram {
+        constructor(convInfo) {
+          this.variableNames = ["dy", "W"];
+          this.outputShape = convInfo.inShape;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const isChannelsLast = convInfo.dataFormat === "channelsLast";
+          const padTop = filterHeight - 1 - convInfo.padInfo.top;
+          const padLeft = filterWidth - 1 - convInfo.padInfo.left;
+          const rowDim = isChannelsLast ? 1 : 2;
+          const colDim = isChannelsLast ? 2 : 3;
+          const channelDim = isChannelsLast ? 3 : 1;
+          this.userCode = `
+      const ivec2 pads = ivec2(${padTop}, ${padLeft});
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int batch = coords[0];
+        int d1 = coords[${channelDim}];
+
+        ivec2 dyCorner = ivec2(coords[${rowDim}], coords[${colDim}]) - pads;
+        int dyRCorner = dyCorner.x;
+        int dyCCorner = dyCorner.y;
+
+        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
+        // ? = to be determined. : = across all values in that axis.
+        float dotProd = 0.0;
+        for (int wR = 0; wR < ${filterHeight}; wR++) {
+          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
+
+          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {
+            continue;
+          }
+          int idyR = int(dyR);
+
+          int wRPerm = ${filterHeight} - 1 - wR;
+
+          for (int wC = 0; wC < ${filterWidth}; wC++) {
+            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
+
+            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
+                fract(dyC) > 0.0) {
+              continue;
+            }
+            int idyC = int(dyC);
+
+            int wCPerm = ${filterWidth} - 1 - wC;
+
+            for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {
+
+              if (${isChannelsLast}) {
+                float xValue = getDy(batch, idyR, idyC, d2);
+                float wValue = getW(wRPerm, wCPerm, d1, d2);
+                dotProd += xValue * wValue;
+              } else {
+                float xValue = getDy(batch, d2, idyR, idyC);
+                float wValue = getW(wRPerm, wCPerm, d1, d2);
+                dotProd += xValue * wValue;
+              }
+
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      class Conv3DDerFilterProgram {
+        constructor(convInfo) {
+          this.variableNames = ["x", "dy"];
+          this.outputShape = convInfo.filterShape;
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const padFront = convInfo.padInfo.front;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          this.userCode = `
+      void main() {
+        ivec5 coords = getOutputCoords();
+        int wF = coords.x;
+        int wR = coords.y;
+        int wC = coords.z;
+        int d1 = coords.w;
+        int d2 = coords.u;
+
+        float dotProd = 0.0;
+
+        for (int b = 0; b < ${convInfo.batchSize}; b++) {
+          for (int yF = 0; yF < ${convInfo.outDepth}; yF++) {
+            int xF = wF + yF * ${strideDepth} - ${padFront};
+
+            if (xF < 0 || xF >= ${convInfo.inDepth}) {
+              continue;
+            }
+
+            for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {
+              int xR = wR + yR * ${strideHeight} - ${padTop};
+
+              if (xR < 0 || xR >= ${convInfo.inHeight}) {
+                continue;
+              }
+
+              for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
+                int xC = wC + yC * ${strideWidth} - ${padLeft};
+
+                if (xC < 0 || xC >= ${convInfo.inWidth}) {
+                  continue;
+                }
+
+                float dyValue = getDy(b, yF, yR, yC, d2);
+                float xValue = getX(b, xF, xR, xC, d1);
+                dotProd += (xValue * dyValue);
+              }
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      class Conv3DDerInputProgram {
+        constructor(convInfo) {
+          this.variableNames = ["dy", "W"];
+          this.outputShape = convInfo.inShape;
+          const filterDepth = convInfo.filterDepth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const padFront = filterDepth - 1 - convInfo.padInfo.front;
+          const padTop = filterHeight - 1 - convInfo.padInfo.top;
+          const padLeft = filterWidth - 1 - convInfo.padInfo.left;
+          this.userCode = `
+      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
+
+      void main() {
+        ivec5 coords = getOutputCoords();
+        int batch = coords.x;
+        int d1 = coords.u;
+
+
+        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
+        int dyFCorner = dyCorner.x;
+        int dyRCorner = dyCorner.y;
+        int dyCCorner = dyCorner.z;
+
+        float dotProd = 0.0;
+        for (int wF = 0; wF < ${filterDepth}; wF++) {
+          float dyF = float(dyFCorner + wF) / ${strideDepth}.0;
+
+          if (dyF < 0.0 || dyF >= ${convInfo.outDepth}.0 || fract(dyF) > 0.0) {
+            continue;
+          }
+          int idyF = int(dyF);
+
+          int wFPerm = ${filterDepth} - 1 - wF;
+
+          for (int wR = 0; wR < ${filterHeight}; wR++) {
+            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
+
+            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||
+              fract(dyR) > 0.0) {
+              continue;
+            }
+            int idyR = int(dyR);
+
+            int wRPerm = ${filterHeight} - 1 - wR;
+
+            for (int wC = 0; wC < ${filterWidth}; wC++) {
+              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
+
+              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
+                  fract(dyC) > 0.0) {
+                continue;
+              }
+              int idyC = int(dyC);
+
+              int wCPerm = ${filterWidth} - 1 - wC;
+
+              for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {
+                float xValue = getDy(batch, idyF, idyR, idyC, d2);
+                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
+                dotProd += xValue * wValue;
+              }
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=conv_backprop_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_backprop_gpu_depthwise.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class DepthwiseConv2DDerFilterProgram {
+        constructor(convInfo) {
+          this.variableNames = ["x", "dy"];
+          this.outputShape = convInfo.filterShape;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          const channelMul = convInfo.outChannels / convInfo.inChannels;
+          this.userCode = `
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int wR = coords.x;
+        int wC = coords.y;
+        int d1 = coords.z;
+        int dm = coords.w;
+        int d2 = d1 * ${channelMul} + dm;
+
+        float dotProd = 0.0;
+
+        // TO DO: Vec4 over the batch size
+        for (int b = 0; b < ${convInfo.batchSize}; b++) {
+          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {
+            int xR = wR + yR * ${strideHeight} - ${padTop};
+
+            if (xR < 0 || xR >= ${convInfo.inHeight}) {
+              continue;
+            }
+
+            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
+              int xC = wC + yC * ${strideWidth} - ${padLeft};
+
+              if (xC < 0 || xC >= ${convInfo.inWidth}) {
+                continue;
+              }
+
+              float dyValue = getDy(b, yR, yC, d2);
+              float xValue = getX(b, xR, xC, d1);
+              dotProd += (xValue * dyValue);
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      class DepthwiseConv2DDerInputProgram {
+        constructor(convInfo) {
+          this.variableNames = ["dy", "W"];
+          this.outputShape = convInfo.inShape;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const padTop = filterHeight - 1 - convInfo.padInfo.top;
+          const padLeft = filterWidth - 1 - convInfo.padInfo.left;
+          const channelMul = convInfo.outChannels / convInfo.inChannels;
+          this.userCode = `
+      const ivec2 pads = ivec2(${padTop}, ${padLeft});
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int batch = coords[0];
+        int d1 = coords[3];
+        ivec2 dyCorner = coords.yz - pads;
+        int dyRCorner = dyCorner.x;
+        int dyCCorner = dyCorner.y;
+
+        float dotProd = 0.0;
+
+        for (int wR = 0; wR < ${filterHeight}; wR++) {
+          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
+
+          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {
+            continue;
+          }
+          int idyR = int(dyR);
+
+          int wRPerm = ${filterHeight} - 1 - wR;
+
+          for (int wC = 0; wC < ${filterWidth}; wC++) {
+            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
+
+            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
+                fract(dyC) > 0.0) {
+              continue;
+            }
+            int idyC = int(dyC);
+
+            int wCPerm = ${filterWidth} - 1 - wC;
+
+            // TO DO: Vec4 over the channelMul
+            for (int dm = 0; dm < ${channelMul}; dm++) {
+              int d2 = d1 * ${channelMul} + dm;
+              float xValue = getDy(batch, idyR, idyC, d2);
+              float wValue = getW(wRPerm, wCPerm, d1, dm);
+              dotProd += xValue * wValue;
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=conv_backprop_gpu_depthwise.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class Conv2DProgram {
+        constructor(
+          convInfo,
+          addBias = false,
+          activation = null,
+          hasPreluActivationWeights = false
+        ) {
+          this.variableNames = ["x", "W"];
+          this.outputShape = convInfo.outShape;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const inputDepthNearestVec4 = Math.floor(convInfo.inChannels / 4) * 4;
+          const inputDepthVec4Remainder = convInfo.inChannels % 4;
+          const isChannelsLast = convInfo.dataFormat === "channelsLast";
+          const rowDim = isChannelsLast ? 1 : 2;
+          const colDim = isChannelsLast ? 2 : 3;
+          const channelDim = isChannelsLast ? 3 : 1;
+          let activationSnippet = "",
+            applyActivationSnippet = "";
+          if (activation) {
+            if (hasPreluActivationWeights) {
+              activationSnippet = `float activation(float a) {
+          float b = getPreluActivationWeightsAtOutCoords();
+          ${activation}
+        }`;
+            } else {
+              activationSnippet = `
+          float activation(float x) {
+            ${activation}
+          }
+        `;
+            }
+            applyActivationSnippet = `result = activation(result);`;
+          }
+          const addBiasSnippet = addBias ? "result += getBiasAtOutCoords();" : "";
+          if (addBias) {
+            this.variableNames.push("bias");
+          }
+          if (hasPreluActivationWeights) {
+            this.variableNames.push("preluActivationWeights");
+          }
+          this.userCode = `
+      ${activationSnippet}
+
+      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
+      const ivec2 pads = ivec2(${padTop}, ${padLeft});
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int batch = coords[0];
+        int d2 = coords[${channelDim}];
+
+        ivec2 xRCCorner =
+            ivec2(coords[${rowDim}], coords[${colDim}]) * strides - pads;
+        int xRCorner = xRCCorner.x;
+        int xCCorner = xRCCorner.y;
+
+        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
+        // ? = to be determined. : = across all values in that axis.
+        float dotProd = 0.0;
+        for (int wR = 0; wR < ${filterHeight}; wR++) {
+          int xR = xRCorner + wR * ${dilationHeight};
+
+          if (xR < 0 || xR >= ${convInfo.inHeight}) {
+            continue;
+          }
+
+          for (int wC = 0; wC < ${filterWidth}; wC++) {
+            int xC = xCCorner + wC * ${dilationWidth};
+
+            if (xC < 0 || xC >= ${convInfo.inWidth}) {
+              continue;
+            }
+
+            for (int d1 = 0; d1 < ${inputDepthNearestVec4}; d1 += 4) {
+              vec4 wValues = vec4(
+                getW(wR, wC, d1, d2),
+                getW(wR, wC, d1 + 1, d2),
+                getW(wR, wC, d1 + 2, d2),
+                getW(wR, wC, d1 + 3, d2)
+              );
+
+              if (${isChannelsLast}) {
+                vec4 xValues = vec4(
+                  getX(batch, xR, xC, d1),
+                  getX(batch, xR, xC, d1 + 1),
+                  getX(batch, xR, xC, d1 + 2),
+                  getX(batch, xR, xC, d1 + 3)
+                );
+                dotProd += dot(xValues, wValues);
+              } else {
+                vec4 xValues = vec4(
+                  getX(batch, d1, xR, xC),
+                  getX(batch, d1 + 1, xR, xC),
+                  getX(batch, d1 + 2, xR, xC),
+                  getX(batch, d1 + 3, xR, xC)
+                );
+                dotProd += dot(xValues, wValues);
+              }
+            }
+
+            if (${inputDepthVec4Remainder === 1}) {
+
+              if (${isChannelsLast}) {
+                dotProd +=
+                    getX(batch, xR, xC, ${inputDepthNearestVec4}) *
+                    getW(wR, wC, ${inputDepthNearestVec4}, d2);
+              } else {
+                dotProd +=
+                    getX(batch, ${inputDepthNearestVec4}, xR, xC) *
+                    getW(wR, wC, ${inputDepthNearestVec4}, d2);
+              }
+
+            } else if (${inputDepthVec4Remainder === 2}) {
+              vec2 wValues = vec2(
+                getW(wR, wC, ${inputDepthNearestVec4}, d2),
+                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2)
+              );
+
+              if (${isChannelsLast}) {
+                vec2 xValues = vec2(
+                  getX(batch, xR, xC, ${inputDepthNearestVec4}),
+                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1)
+                );
+                dotProd += dot(xValues, wValues);
+              } else {
+                vec2 xValues = vec2(
+                  getX(batch, ${inputDepthNearestVec4}, xR, xC),
+                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC)
+                );
+                dotProd += dot(xValues, wValues);
+              }
+
+            } else if (${inputDepthVec4Remainder === 3}) {
+              vec3 wValues = vec3(
+                getW(wR, wC, ${inputDepthNearestVec4}, d2),
+                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2),
+                getW(wR, wC, ${inputDepthNearestVec4} + 2, d2)
+              );
+
+              if (${isChannelsLast}) {
+                vec3 xValues = vec3(
+                  getX(batch, xR, xC, ${inputDepthNearestVec4}),
+                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1),
+                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 2)
+                );
+                dotProd += dot(xValues, wValues);
+              } else {
+                vec3 xValues = vec3(
+                  getX(batch, ${inputDepthNearestVec4}, xR, xC),
+                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC),
+                  getX(batch, ${inputDepthNearestVec4} + 2, xR, xC)
+                );
+                dotProd += dot(xValues, wValues);
+              }
+
+            }
+          }
+        }
+
+        float result = dotProd;
+        ${addBiasSnippet}
+        ${applyActivationSnippet}
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      class Conv3DProgram {
+        constructor(convInfo) {
+          this.variableNames = ["x", "W"];
+          this.outputShape = convInfo.outShape;
+          const padFront = convInfo.padInfo.front;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const filterDepth = convInfo.filterDepth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const inputDepthNearestVec4 = Math.floor(convInfo.inChannels / 4) * 4;
+          const inputDepthVec4Remainder = convInfo.inChannels % 4;
+          this.userCode = `
+      const ivec3 strides = ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
+      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
+
+      void main() {
+        ivec5 coords = getOutputCoords();
+        int batch = coords.x;
+        int d2 = coords.u;
+
+        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
+        int xFCorner = xFRCCorner.x;
+        int xRCorner = xFRCCorner.y;
+        int xCCorner = xFRCCorner.z;
+
+        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
+        // y(yF, yR, yC, d2). ? = to be determined. : = across all
+        // values in that axis.
+        float dotProd = 0.0;
+        for (int wF = 0; wF < ${filterDepth}; wF++) {
+          int xF = xFCorner + wF * ${dilationDepth};
+
+          if (xF < 0 || xF >= ${convInfo.inDepth}) {
+            continue;
+          }
+
+          for (int wR = 0; wR < ${filterHeight}; wR++) {
+            int xR = xRCorner + wR * ${dilationHeight};
+
+            if (xR < 0 || xR >= ${convInfo.inHeight}) {
+              continue;
+            }
+
+            for (int wC = 0; wC < ${filterWidth}; wC++) {
+              int xC = xCCorner + wC * ${dilationWidth};
+
+              if (xC < 0 || xC >= ${convInfo.inWidth}) {
+                continue;
+              }
+
+              for (int d1 = 0; d1 < ${inputDepthNearestVec4}; d1 += 4) {
+                vec4 xValues = vec4(
+                  getX(batch, xF, xR, xC, d1),
+                  getX(batch, xF, xR, xC, d1 + 1),
+                  getX(batch, xF, xR, xC, d1 + 2),
+                  getX(batch, xF, xR, xC, d1 + 3)
+                );
+                vec4 wValues = vec4(
+                  getW(wF, wR, wC, d1, d2),
+                  getW(wF, wR, wC, d1 + 1, d2),
+                  getW(wF, wR, wC, d1 + 2, d2),
+                  getW(wF, wR, wC, d1 + 3, d2)
+                );
+
+                dotProd += dot(xValues, wValues);
+              }
+
+              if (${inputDepthVec4Remainder === 1}) {
+                dotProd +=
+                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}) *
+                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2);
+              } else if (${inputDepthVec4Remainder === 2}) {
+                vec2 xValues = vec2(
+                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),
+                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1)
+                );
+                vec2 wValues = vec2(
+                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),
+                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2)
+                );
+                dotProd += dot(xValues, wValues);
+              } else if (${inputDepthVec4Remainder === 3}) {
+                vec3 xValues = vec3(
+                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),
+                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1),
+                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 2)
+                );
+                vec3 wValues = vec3(
+                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),
+                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2),
+                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 2, d2)
+                );
+                dotProd += dot(xValues, wValues);
+              }
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=conv_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_gpu_depthwise.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class DepthwiseConv2DProgram {
+        constructor(convInfo, addBias = false, activation = null, hasPreluActivation = false) {
+          this.variableNames = ["x", "W"];
+          this.outputShape = convInfo.outShape;
+          const xNumRows = convInfo.inHeight;
+          const xNumCols = convInfo.inWidth;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const channelMul = convInfo.outChannels / convInfo.inChannels;
+          let activationSnippet = "",
+            applyActivationSnippet = "";
+          if (activation) {
+            if (hasPreluActivation) {
+              activationSnippet = `float activation(float a) {
+          float b = getPreluActivationWeightsAtOutCoords();
+          ${activation}
+        }`;
+            } else {
+              activationSnippet = `
+          float activation(float x) {
+            ${activation}
+          }
+        `;
+            }
+            applyActivationSnippet = `result = activation(result);`;
+          }
+          const addBiasSnippet = addBias ? "result += getBiasAtOutCoords();" : "";
+          if (addBias) {
+            this.variableNames.push("bias");
+          }
+          if (hasPreluActivation) {
+            this.variableNames.push("preluActivationWeights");
+          }
+          this.userCode = `
+      ${activationSnippet}
+
+      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
+      const ivec2 pads = ivec2(${padTop}, ${padLeft});
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int batch = coords.x;
+        ivec2 xRCCorner = coords.yz * strides - pads;
+        int d2 = coords.w;
+        int d1 = d2 / ${channelMul};
+        int q = d2 - d1 * ${channelMul};
+
+        int xRCorner = xRCCorner.x;
+        int xCCorner = xRCCorner.y;
+
+        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
+        // ? = to be determined. : = across all values in that axis.
+        float dotProd = 0.0;
+        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
+        for (int wR = 0; wR < ${filterHeight}; wR++) {
+          int xR = xRCorner + wR * ${dilationHeight};
+
+          if (xR < 0 || xR >= ${xNumRows}) {
+            continue;
+          }
+
+          for (int wC = 0; wC < ${filterWidth}; wC++) {
+            int xC = xCCorner + wC * ${dilationWidth};
+
+            if (xC < 0 || xC >= ${xNumCols}) {
+              continue;
+            }
+
+            float xVal = getX(batch, xR, xC, d1);
+            float wVal = getW(wR, wC, d1, q);
+            dotProd += xVal * wVal;
+          }
+        }
+
+        float result = dotProd;
+        ${addBiasSnippet}
+        ${applyActivationSnippet}
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=conv_gpu_depthwise.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_packed_gpu_depthwise.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class conv_packed_gpu_depthwise_DepthwiseConvPacked2DProgram {
+        constructor(convInfo, addBias = false, activation = null, hasPreluActivation = false) {
+          this.variableNames = ["x", "W"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = convInfo.outShape;
+          const xNumRows = convInfo.inHeight;
+          const xNumCols = convInfo.inWidth;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const filterHeight = convInfo.filterHeight;
+          const filterWidth = convInfo.filterWidth;
+          const texelsAcross = filterWidth;
+          let mainLoop = `int xR; int xC; int xCOffset;`;
+          for (let r = 0; r < filterHeight; r++) {
+            for (let c = 0; c < filterWidth; c++) {
+              mainLoop += `
+          vec4 xTexelR${r}C${c * 2} = vec4(0.);
+          vec4 wR${r}C${c} = vec4(0.);
+          vec4 xR${r}C${c} = vec4(0.);`;
+            }
+          }
+          /**
+           * This vectorized implementation works by gathering the values needed for
+           * each output channel's dot product into vec4's and then multiplying them
+           * all together (this happens in the final double for-loop below). Most of
+           * the main loop consists of constructing these vec4's with the minimum
+           * number of texture2D calls, which means making use of all four returned
+           * values from a texture2D call at once.
+           */
+          for (let r = 0; r < filterHeight; r++) {
+            for (let texelC = 0; texelC < texelsAcross; texelC++) {
+              const c = texelC * 2;
+              mainLoop += `
+          xR = xRCorner + ${r * dilationHeight};
+          xC = xCCorner + ${c * dilationWidth};
+        `;
+              if (strideWidth === 1) {
+                if (c < filterWidth) {
+                  // If padding is odd, the outer texels have to be composed.
+                  if (padLeft % 2 === 1) {
+                    // TODO: Ensure vec4 previous does not result in redundant sample,
+                    // and avoid setting xTexelRC's that exceed the boundary in the
+                    // first place rather than resetting them to vec4(0)).
+                    // To compute xCOffset:
+                    // - If padding is odd, we must add 1 to ensure we ask for an
+                    // even-numbered row.
+                    // - We subtract 2 to access the previous texel.
+                    mainLoop += `
+                xCOffset = xC + 1;
+                if(xR >= 0 && xR < ${xNumRows} && xCOffset >= 0 && xCOffset < ${xNumCols}) {
+                  xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);
+
+                  // Need to manually clear unused channels in case
+                  // we're reading from recycled texture.
+                  if(xCOffset + 1 >= ${xNumCols}) {
+                    xTexelR${r}C${c}.zw = vec2(0.);
+                  }
+                } else {
+                  xTexelR${r}C${c} = vec4(0.);
+                }
+
+                xCOffset = xC + 1 - 2;
+                if(xR >= 0 && xR < ${xNumRows} && xCOffset >= 0 && xCOffset < ${xNumCols}) {
+                  vec4 previous = getX(batch, xR, xCOffset, d1);
+
+                  // Need to manually clear unused channels in case
+                  // we're reading from recycled texture.
+                  if(xCOffset + 1 >= ${xNumCols}) {
+                    previous.zw = vec2(0.);
+                  }
+
+                  xR${r}C${c} = vec4(previous.zw, xTexelR${r}C${c}.xy);
+                } else {
+                  xR${r}C${c} = vec4(0, 0, xTexelR${r}C${c}.xy);
+                }
+              `;
+                  } else {
+                    // Padding is even, so xRC corresponds to a single texel.
+                    mainLoop += `
+                if(xR >= 0 && xR < ${xNumRows} && xC >= 0 && xC < ${xNumCols}) {
+                  xTexelR${r}C${c} = getX(batch, xR, xC, d1);
+                } else {
+                  xTexelR${r}C${c} = vec4(0.);
+                }
+
+                xR${r}C${c} = xTexelR${r}C${c};
+              `;
+                  }
+                  if (c + 1 < filterWidth) {
+                    // If dilation is even, the second entry should match the first
+                    // (either both are composed or both are single samples). But if
+                    // dilation is odd, then the second entry should be the opposite
+                    // of the first (if the first is composed, the second is a single
+                    // sample, and vice versa.)
+                    const nextTexelOffset =
+                      padLeft % 2 === 0
+                        ? dist["util"].nearestLargerEven(dilationWidth)
+                        : dilationWidth;
+                    if (
+                      (dilationWidth % 2 === 0 && padLeft % 2 === 1) ||
+                      (dilationWidth % 2 !== 0 && padLeft % 2 !== 1)
+                    ) {
+                      mainLoop += `
+                  xCOffset = xC + ${padLeft % 2} + ${nextTexelOffset};
+
+                  if(xR >= 0 && xR < ${xNumRows} &&
+                    xCOffset >= 0 && xCOffset < ${xNumCols}) {
+                    xTexelR${r}C${c + 2} = getX(batch, xR, xCOffset, d1);
+                  }
+                `;
+                      // If dilation > 1 then the xRC's will not be able to share any
+                      // values, so each xRC will require two unique calls to getX.
+                      if (dilationWidth > 1) {
+                        mainLoop += `
+                    xCOffset -= 2;
+                    if(xR >= 0 && xR < ${xNumRows} &&
+                      xCOffset >= 0 && xCOffset < ${xNumCols}) {
+                      xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);
+                    } else {
+                      xTexelR${r}C${c} = vec4(0.);
+                    }
+                  `;
+                      }
+                      mainLoop += `
+                  xR${r}C${c + 1} = vec4(
+                    xTexelR${r}C${c}.zw, xTexelR${r}C${c + 2}.xy);
+                `;
+                    } else {
+                      mainLoop += `
+                  xCOffset = xC + ${nextTexelOffset};
+
+                  if(xR >= 0 && xR < ${xNumRows} &&
+                    xCOffset >= 0 && xCOffset < ${xNumCols}) {
+                    xTexelR${r}C${c + 2} = getX(batch, xR, xCOffset, d1);
+                  }
+
+                  xR${r}C${c + 1} = xTexelR${r}C${c + 2};
+                `;
+                    }
+                  }
+                }
+              } else {
+                // stride > 1
+                if (c < filterWidth) {
+                  mainLoop += `
+              if(xR >= 0 && xR < ${xNumRows}) {
+            `;
+                  // Depending on whether padLeft is even or odd, we want either the
+                  // xy or zw channels from X texels for xR${r}C${c}. If padLeft is
+                  // even, xR${r}C${c + 1} is simply the zw channels of texels we've
+                  // already sampled. But if padLeft is odd, xR${r}C{$c + 1}.zw will
+                  // need to come from the xy channels of a new texel, hence the `vec4
+                  // final` initialized below.
+                  if (padLeft % 2 === 1) {
+                    mainLoop += `
+                xCOffset = xC + 1 - ${strideWidth};
+                if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
+                  xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);
+                } else {
+                  xTexelR${r}C${c} = vec4(0.);
+                }
+
+                if(xC + 1 >= 0 && xC + 1 < ${xNumCols}) {
+                  xTexelR${r}C${c + 2} = getX(batch, xR, xC + 1, d1);
+                } else {
+                  xTexelR${r}C${c + 2} = vec4(0.);
+                }
+
+                xR${r}C${c} = vec4(
+                  xTexelR${r}C${c}.zw, xTexelR${r}C${c + 2}.zw);
+              `;
+                    if (c + 1 < filterWidth) {
+                      mainLoop += `
+                  vec4 final = vec4(0.);
+                  xCOffset = xC + 1 + ${strideWidth};
+                  if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
+                    final = getX(batch, xR, xCOffset, d1);
+                  }
+                  xR${r}C${c + 1} = vec4(xTexelR${r}C${c + 2}.xy, final.xy);
+                `;
+                    }
+                  } else {
+                    mainLoop += `
+                if(xC >= 0 && xC < ${xNumCols}) {
+                  xTexelR${r}C${c} = getX(batch, xR, xC, d1);
+                } else {
+                  xTexelR${r}C${c} = vec4(0.);
+                }
+
+                xCOffset = xC + ${strideWidth};
+                if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
+                  xTexelR${r}C${c + 2} = getX(batch, xR, xCOffset, d1);
+                } else {
+                  xTexelR${r}C${c + 2} = vec4(0.);
+                }
+
+                xR${r}C${c} = vec4(
+                  xTexelR${r}C${c}.xy, xTexelR${r}C${c + 2}.xy);
+              `;
+                    if (c + 1 < filterWidth) {
+                      mainLoop += `
+                  xR${r}C${c + 1} = vec4(
+                    xTexelR${r}C${c}.zw, xTexelR${r}C${c + 2}.zw);
+                `;
+                    }
+                  }
+                  mainLoop += `}`;
+                }
+              }
+              if (c < filterWidth) {
+                mainLoop += `
+            vec4 wTexelR${r}C${c} = getW(${r}, ${c}, d1, q);
+            wR${r}C${c} = vec4(wTexelR${r}C${c}.xz, wTexelR${r}C${c}.xz);
+          `;
+                if (c + 1 < filterWidth) {
+                  mainLoop += `
+              vec4 wTexelR${r}C${c + 1} = getW(${r}, ${c + 1}, d1, q);
+              wR${r}C${c + 1} =
+                vec4(wTexelR${r}C${c + 1}.xz, wTexelR${r}C${c + 1}.xz);`;
+                }
+              }
+            }
+          }
+          for (let r = 0; r < filterHeight; r++) {
+            for (let c = 0; c < filterWidth; c++) {
+              mainLoop += `dotProd += xR${r}C${c} * wR${r}C${c};`;
+            }
+          }
+          let activationSnippet = "",
+            applyActivationSnippet = "";
+          if (activation) {
+            if (hasPreluActivation) {
+              activationSnippet = `vec4 activation(vec4 a) {
+          vec4 b = getPreluActivationWeightsAtOutCoords();
+          ${activation}
+        }`;
+            } else {
+              activationSnippet = `vec4 activation(vec4 x) {
+          ${activation}
+        }`;
+            }
+            applyActivationSnippet = `result = activation(result);`;
+          }
+          const addBiasSnippet = addBias ? "result += getBiasAtOutCoords();" : "";
+          if (addBias) {
+            this.variableNames.push("bias");
+          }
+          if (hasPreluActivation) {
+            this.variableNames.push("preluActivationWeights");
+          }
+          this.userCode = `
+      ${activationSnippet}
+
+      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
+      const ivec2 pads = ivec2(${padTop}, ${padLeft});
+
+      void main() {
+
+        ivec4 coords = getOutputCoords();
+        int batch = coords.x;
+        ivec2 xRCCorner = coords.yz * strides - pads;
+        int d2 = coords.w;
+        int d1 = d2;
+        int q = 0;
+        int xRCorner = xRCCorner.x;
+        int xCCorner = xRCCorner.y;
+
+        vec4 dotProd = vec4(0.);
+
+        ${mainLoop}
+
+        vec4 result = dotProd;
+        ${addBiasSnippet}
+        ${applyActivationSnippet}
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=conv_packed_gpu_depthwise.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/crop_and_resize_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class CropAndResizeProgram {
+        constructor(imageShape, boxShape, cropSize, method, extrapolationValue) {
+          this.variableNames = ["Image", "Boxes", "BoxInd"];
+          this.outputShape = [];
+          const [batch, imageHeight, imageWidth, depth] = imageShape;
+          const [numBoxes] = boxShape;
+          const [cropHeight, cropWidth] = cropSize;
+          this.outputShape = [numBoxes, cropHeight, cropWidth, depth];
+          const methodId = method === "bilinear" ? 1 : 0;
+          const [inputHeightFloat, inputWidthFloat] = [
+            `${imageHeight - 1}.0`,
+            `${imageWidth - 1}.0`,
+          ];
+          const [heightRatio, heightScale, inY] =
+            cropHeight > 1
+              ? [
+                  `${(imageHeight - 1) / (cropHeight - 1)}`,
+                  "(y2-y1) * height_ratio",
+                  `y1*${inputHeightFloat} + float(y)*(height_scale)`,
+                ]
+              : ["0.0", "0.0", `0.5 * (y1+y2) * ${inputHeightFloat}`];
+          const [widthRatio, widthScale, inX] =
+            cropWidth > 1
+              ? [
+                  `${(imageWidth - 1) / (cropWidth - 1)}`,
+                  "(x2-x1) * width_ratio",
+                  `x1*${inputWidthFloat} + float(x)*(width_scale)`,
+                ]
+              : ["0.0", "0.0", `0.5 * (x1+x2) * ${inputWidthFloat}`];
+          // Reference implementation
+          // tslint:disable-next-line:max-line-length
+          // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/crop_and_resize_op_gpu.cu.cc
+          this.userCode = `
+      const float height_ratio = float(${heightRatio});
+      const float width_ratio = float(${widthRatio});
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int y = coords[1];
+        int x = coords[2];
+        int d = coords[3];
+
+        // get box vals
+        float y1 = getBoxes(b,0);
+        float x1 = getBoxes(b,1);
+        float y2 = getBoxes(b,2);
+        float x2 = getBoxes(b,3);
+
+        // get image in batch index
+        int bInd = round(getBoxInd(b));
+        if(bInd < 0 || bInd >= ${batch}) {
+          return;
+        }
+
+        float height_scale = ${heightScale};
+        float width_scale = ${widthScale};
+
+        float in_y = ${inY};
+        if( in_y < 0.0 || in_y > ${inputHeightFloat} ) {
+          setOutput(float(${extrapolationValue}));
+          return;
+        }
+        float in_x = ${inX};
+        if( in_x < 0.0 || in_x > ${inputWidthFloat} ) {
+          setOutput(float(${extrapolationValue}));
+          return;
+        }
+
+        vec2 sourceFracIndexCR = vec2(in_x,in_y);
+        if(${methodId} == 1) {
+          // Compute the four integer indices.
+          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
+          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
+
+          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
+          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
+          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
+          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
+
+          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
+
+          float top = topLeft + (topRight - topLeft) * fracCR.x;
+          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
+          float newValue = top + (bottom - top) * fracCR.y;
+          setOutput(newValue);
+        } else {
+          // Compute the coordinators of nearest neighbor point.
+          ivec2 sourceNearestCR = ivec2(floor(
+            sourceFracIndexCR + vec2(0.5,0.5)));
+          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
+          setOutput(newValue);
+        }
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=crop_and_resize_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/cumsum_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class cumsum_gpu_CumSumProgram {
+        constructor(shape, exclusive, reverse) {
+          this.variableNames = ["x"];
+          this.outputShape = shape;
+          const rank = shape.length;
+          const finalDim = shape[shape.length - 1];
+          const comparator = reverse ? "<" : ">";
+          this.userCode = `
+      int getIndex(int i) {
+        ${reverse ? `return ${finalDim} -i - 1;` : "return i;"}
+      }
+
+      void main() {
+        ${getCoordsDataType(rank)} coords = getOutputCoords();
+        int end = ${getFinalCoord(rank, "coords")};
+        float val = 0.0;
+        for (int i = ${finalDim} - 1; i >= 0; i -= 1) {
+          int idx = getIndex(i);
+          if (idx ${comparator} end) {
+            continue;
+          }
+          if (idx == end && ${exclusive}) {
+            continue;
+          }
+          ${getFinalCoord(rank, "coords")} = idx;
+          val += getX(${getCoords(rank, "coords")});
+        }
+        setOutput(val);
+      }
+    `;
+        }
+      }
+      function getCoords(rank, name) {
+        if (rank === 1) {
+          return `${name}`;
+        } else if (rank === 2) {
+          return `${name}.x, ${name}.y`;
+        } else if (rank === 3) {
+          return `${name}.x, ${name}.y, ${name}.z`;
+        } else if (rank === 4) {
+          return `${name}.x, ${name}.y, ${name}.z, ${name}.w`;
+        } else {
+          throw Error(`Cumulative sum for rank ${rank} is not yet supported`);
+        }
+      }
+      function getFinalCoord(rank, name) {
+        if (rank === 1) {
+          return `${name}`;
+        } else if (rank === 2) {
+          return `${name}.y`;
+        } else if (rank === 3) {
+          return `${name}.z`;
+        } else if (rank === 4) {
+          return `${name}.w`;
+        } else {
+          throw Error(`Cumulative sum for rank ${rank} is not yet supported`);
+        }
+      }
+      //# sourceMappingURL=cumsum_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/decode_matrix_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class decode_matrix_gpu_DecodeMatrixProgram {
+        constructor(outputShape) {
+          this.variableNames = ["A"];
+          this.packedInputs = false;
+          this.packedOutput = true;
+          this.outPackingScheme = PackingScheme.DENSE;
+          const texShape = getDenseTexShape(outputShape);
+          const glsl = getGlslDifferences();
+          this.outputShape = outputShape;
+          this.userCode = `
+      ivec3 outCoordsFromFlatIndex(int index) {
+        ${getLogicalCoordinatesFromFlatIndex(["r", "c", "d"], outputShape)}
+        return ivec3(r, c, d);
+      }
+
+      void main() {
+        ivec2 resTexRC = ivec2(resultUV.yx *
+          vec2(${texShape[0]}, ${texShape[1]}));
+        int index = 4 * (resTexRC.x * ${texShape[1]} + resTexRC.y);
+
+        vec4 result = vec4(0.);
+
+        for (int i=0; i<4; i++) {
+          int flatIndex = index + i;
+          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
+          result[i] = getA(rc.x, rc.y, rc.z);
+        }
+
+        ${glsl.output} = result;
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=decode_matrix_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/decode_matrix_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class decode_matrix_packed_gpu_DecodeMatrixPackedProgram {
+        constructor(outputShape) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outPackingScheme = PackingScheme.DENSE;
+          const texShape = getDenseTexShape(outputShape);
+          const glsl = getGlslDifferences();
+          this.outputShape = outputShape;
+          this.userCode = `
+      ivec3 outCoordsFromFlatIndex(int index) {
+        ${getLogicalCoordinatesFromFlatIndex(["r", "c", "d"], outputShape)}
+        return ivec3(r, c, d);
+      }
+
+      void main() {
+        ivec2 resTexRC = ivec2(resultUV.yx *
+          vec2(${texShape[0]}, ${texShape[1]}));
+        int index = 4 * (resTexRC.x * ${texShape[1]} + resTexRC.y);
+
+        vec4 result = vec4(0.);
+
+        for (int i=0; i<4; i++) {
+          int flatIndex = index + i;
+          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
+          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
+        }
+
+        ${glsl.output} = result;
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=decode_matrix_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/depth_to_space_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class DepthToSpaceProgram {
+        constructor(outputShape, blockSize, dataFormat) {
+          this.variableNames = ["x"];
+          this.outputShape = [];
+          this.outputShape = outputShape;
+          this.blockSize = blockSize;
+          this.dataFormat = dataFormat;
+          this.userCode = `
+    void main() {
+      ivec4 coords = getOutputCoords();
+      int b = coords[0];
+      int h = ${this.getHeightCoordString()};
+      int w = ${this.getWidthCoordString()};
+      int d = ${this.getDepthCoordString()};
+
+      int in_h = h / ${blockSize};
+      int offset_h = imod(h, ${blockSize});
+      int in_w = w / ${blockSize};
+      int offset_w = imod(w, ${blockSize});
+      int offset_d = (offset_h * ${blockSize} + offset_w) *
+        ${this.getOutputDepthSize()};
+      int in_d = d + offset_d;
+
+      float result = ${this.getInputSamplingString()};
+      setOutput(result);
+    }
+  `;
+        }
+        getHeightCoordString() {
+          if (this.dataFormat === "NHWC") {
+            return `coords[1]`;
+          } else {
+            return `coords[2]`;
+          }
+        }
+        getWidthCoordString() {
+          if (this.dataFormat === "NHWC") {
+            return `coords[2]`;
+          } else {
+            return `coords[3]`;
+          }
+        }
+        getDepthCoordString() {
+          if (this.dataFormat === "NHWC") {
+            return `coords[3]`;
+          } else {
+            return `coords[1]`;
+          }
+        }
+        getOutputDepthSize() {
+          if (this.dataFormat === "NHWC") {
+            return this.outputShape[3];
+          } else {
+            return this.outputShape[1];
+          }
+        }
+        getInputSamplingString() {
+          if (this.dataFormat === "NHWC") {
+            return `getX(b, in_h, in_w, in_d)`;
+          } else {
+            return `getX(b, in_d, in_h, in_w)`;
+          }
+        }
+      }
+      //# sourceMappingURL=depth_to_space_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/diag_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class DiagProgram {
+        constructor(size) {
+          this.variableNames = ["X"];
+          this.outputShape = [size, size];
+          this.userCode = `
+      void main() {
+          ivec2 coords = getOutputCoords();
+          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
+          setOutput(val);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=diag_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_float_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class encode_float_gpu_EncodeFloatProgram {
+        constructor(outputShape) {
+          this.variableNames = ["A"];
+          this.outTexUsage = TextureUsage.DOWNLOAD;
+          const glsl = getGlslDifferences();
+          this.outputShape = outputShape;
+          this.userCode = `
+      ${ENCODE_FLOAT_SNIPPET}
+
+      void main() {
+        float x = getAAtOutCoords();
+        ${glsl.output} = encode_float(x);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=encode_float_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_float_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class encode_float_packed_gpu_EncodeFloatPackedProgram {
+        constructor(outputShape) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = false;
+          this.outTexUsage = TextureUsage.DOWNLOAD;
+          const glsl = getGlslDifferences();
+          this.outputShape = outputShape;
+          this.userCode = `
+      ${ENCODE_FLOAT_SNIPPET}
+
+      void main() {
+        ivec3 coords = getOutputCoords();
+        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
+        ${glsl.output} = encode_float(x);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=encode_float_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_matrix_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class encode_matrix_gpu_EncodeMatrixProgram {
+        constructor(outputShape, texShape, inputIsUnsignedByte = false) {
+          this.variableNames = ["A"];
+          const glsl = getGlslDifferences();
+          const [height, width] = texShape;
+          this.outputShape = outputShape;
+          let output = `result`;
+          if (inputIsUnsignedByte) {
+            output = `floor(result * 255. + 0.5)`;
+          }
+          this.userCode = `
+      ${getFlatIndexFrom3D(outputShape)}
+
+      void main() {
+        ivec3 coords = getOutputCoords();
+
+        int flatIndex = getFlatIndex(coords);
+        int offset = imod(flatIndex, 4);
+
+        flatIndex = idiv(flatIndex, 4, 1.);
+        
+        int r = flatIndex / ${width};
+        int c = imod(flatIndex, ${width});
+        vec2 uv = (vec2(c, r) + halfCR) / vec2(${width}.0, ${height}.0);
+        vec4 values = ${glsl.texture2D}(A, uv);
+
+        float result;
+
+        if(offset == 0) {
+          result = values[0];
+        } else if(offset == 1) {
+          result = values[1];
+        } else if(offset == 2) {
+          result = values[2];
+        } else {
+          result = values[3];
+        }
+
+        ${glsl.output} = vec4(${output}, 0., 0., 0.);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=encode_matrix_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_matrix_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      /*
+This is how the shader encodes a tensor with shape = [2, 3, 5]
+(indices are [batch, row, col]).
+
+000|001   002|003   004|xxx   020|021   022|023   024|xxx
+-------   -------   -------   -------   -------   -------
+010|011   012|013   014|xxx   xxx|xxx   xxx|xxx   xxx|xxx
+
+100|101   102|103   104|xxx   120|121   122|123   124|xxx
+-------   -------   -------   -------   -------   -------
+110|111   112|113   114|xxx   xxx|xxx   xxx|xxx   xxx|xxx
+
+Single texels contain only values from the same batch, and from adjacent rows
+and columns.
+ */
+      class encode_matrix_packed_gpu_EncodeMatrixPackedProgram {
+        constructor(outputShape, texShape, inputIsUnsignedByte = false) {
+          this.variableNames = ["A"];
+          this.packedInputs = false;
+          this.packedOutput = true;
+          const glsl = getGlslDifferences();
+          const [height, width] = texShape;
+          this.outputShape = outputShape;
+          let mainLoop = "";
+          let output = "result";
+          if (inputIsUnsignedByte) {
+            output = "floor(result * 255. + 0.5)";
+          }
+          for (let row = 0; row <= 1; row++) {
+            for (let col = 0; col <= 1; col++) {
+              const channel = row * 2 + col;
+              mainLoop += `
+          localCoords = coords;
+          if(localCoords[2] + ${col} < ${outputShape[2]}) {
+            localCoords[2] += ${col};
+            if(localCoords[1] + ${row} < ${outputShape[1]}) {
+              localCoords[1] += ${row};
+
+              flatIndex = getFlatIndex(localCoords);
+              offset = imod(flatIndex, 4);
+
+              flatIndex = idiv(flatIndex, 4, 1.);
+
+              r = flatIndex / ${width};
+              c = imod(flatIndex, ${width});
+              uv = (vec2(c, r) + halfCR) / vec2(${width}.0, ${height}.0);
+              values = ${glsl.texture2D}(A, uv);
+
+              if(offset == 0) {
+                result[${channel}] = values[0];
+              } else if(offset == 1) {
+                result[${channel}] = values[1];
+              } else if(offset == 2) {
+                result[${channel}] = values[2];
+              } else {
+                result[${channel}] = values[3];
+              }
+            }
+          }
+        `;
+            }
+          }
+          this.userCode = `
+      ${getFlatIndexFrom3D(outputShape)}
+
+      void main() {
+        ivec3 coords = getOutputCoords();
+
+        vec4 result = vec4(0.);
+        int flatIndex, r, c, offset;
+        ivec3 localCoords;
+        vec2 uv;
+        vec4 values;
+
+        ${mainLoop}
+
+        ${glsl.output} = ${output};
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=encode_matrix_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/fft_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const COMPLEX_FFT = {
+        REAL: "return real * expR - imag * expI;",
+        IMAG: "return real * expI + imag * expR;",
+      };
+      class FFTProgram {
+        constructor(op, inputShape, inverse) {
+          this.variableNames = ["real", "imag"];
+          const innerDim = inputShape[1];
+          this.outputShape = inputShape;
+          const exponentMultiplierSnippet = inverse ? `2.0 * ${Math.PI}` : `-2.0 * ${Math.PI}`;
+          const resultDenominator = inverse ? `${innerDim}.0` : "1.0";
+          this.userCode = `
+      const float exponentMultiplier = ${exponentMultiplierSnippet};
+
+      float unaryOpComplex(float real, float expR, float imag, float expI) {
+        ${op}
+      }
+
+      float mulMatDFT(int batch, int index) {
+        float indexRatio = float(index) / float(${innerDim});
+        float exponentMultiplierTimesIndexRatio =
+            exponentMultiplier * indexRatio;
+
+        float result = 0.0;
+
+        for (int i = 0; i < ${innerDim}; i++) {
+          // x = (-2|2 * PI / N) * index * i;
+          float x = exponentMultiplierTimesIndexRatio * float(i);
+          float expR = cos(x);
+          float expI = sin(x);
+          float real = getReal(batch, i);
+          float imag = getImag(batch, i);
+
+          result +=
+              unaryOpComplex(real, expR, imag, expI) / ${resultDenominator};
+        }
+
+        return result;
+      }
+
+      void main() {
+        ivec2 coords = getOutputCoords();
+        setOutput(mulMatDFT(coords[0], coords[1]));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=fft_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/fill_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class FillProgram {
+        constructor(shape, value) {
+          this.outputShape = [];
+          this.variableNames = ["x"];
+          this.outputShape = shape;
+          this.userCode = `
+      uniform float value;
+      void main() {
+        // Input can be obtained from uniform value.
+        setOutput(value);
+      }
+    `;
+        }
+        getCustomSetupFunc(value) {
+          return (gpgpu, webGLProgram) => {
+            if (this.valueLoc == null) {
+              this.valueLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "value");
+            }
+            gpgpu.gl.uniform1f(this.valueLoc, value);
+          };
+        }
+      }
+      //# sourceMappingURL=fill_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gather_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class gather_gpu_GatherProgram {
+        constructor(aShape, indicesLength, axis) {
+          this.variableNames = ["A", "indices"];
+          const outputShape = aShape.slice();
+          outputShape[axis] = indicesLength;
+          this.outputShape = outputShape;
+          this.rank = outputShape.length;
+          const dtype = getCoordsDataType(this.rank);
+          const sourceCoords = gather_gpu_getSourceCoords(aShape, axis);
+          this.userCode = `
+      void main() {
+        ${dtype} resRC = getOutputCoords();
+        setOutput(getA(${sourceCoords}));
+      }
+    `;
+        }
+      }
+      function gather_gpu_getSourceCoords(aShape, axis) {
+        const rank = aShape.length;
+        if (rank > 4) {
+          throw Error(`Gather for rank ${rank} is not yet supported`);
+        }
+        if (rank === 1) {
+          return `int(getIndices(resRC))`;
+        }
+        const currentCoords = ["resRC.x", "resRC.y", "resRC.z", "resRC.w"];
+        const sourceCoords = [];
+        for (let i = 0; i < aShape.length; i++) {
+          if (i === axis) {
+            sourceCoords.push(`int(getIndices(${currentCoords[i]}))`);
+          } else {
+            sourceCoords.push(`${currentCoords[i]}`);
+          }
+        }
+        return sourceCoords.join();
+      }
+      //# sourceMappingURL=gather_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gather_nd_gpu.js
+
+      class gather_nd_gpu_GatherNDProgram {
+        constructor(sliceDim, strides, shape) {
+          this.sliceDim = sliceDim;
+          this.strides = strides;
+          this.variableNames = ["x", "indices"];
+          this.outputShape = shape;
+          const stridesType = getCoordsDataType(strides.length);
+          const dtype = getCoordsDataType(shape.length);
+          const strideString = this.sliceDim > 1 ? "strides[j]" : "strides";
+          this.userCode = `
+        ${stridesType} strides = ${stridesType}(${this.strides});
+         void main() {
+          ${dtype} coords = getOutputCoords();
+          int flattenIndex = 0;
+          for (int j = 0; j < ${this.sliceDim}; j++) {
+            int index = round(getIndices(coords[0], j));
+            flattenIndex += index * ${strideString};
+          }
+          setOutput(getX(flattenIndex, coords[1]));
+        }
+      `;
+        }
+      }
+      //# sourceMappingURL=gather_nd_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_util.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function gpgpu_util_createVertexShader(gl, debug) {
+        const glsl = getGlslDifferences();
+        const vertexShaderSource = `${glsl.version}
+    precision highp float;
+    ${glsl.attribute} vec3 clipSpacePos;
+    ${glsl.attribute} vec2 uv;
+    ${glsl.varyingVs} vec2 resultUV;
+
+    void main() {
+      gl_Position = vec4(clipSpacePos, 1);
+      resultUV = uv;
+    }`;
+        return createVertexShader(gl, debug, vertexShaderSource);
+      }
+      function createVertexBuffer(gl, debug) {
+        // [x y z u v] * [upper-left, lower-left, upper-right, lower-right]
+        const vertexArray = new Float32Array([
+          -1, 1, 0, 0, 1, -1, -1, 0, 0, 0, 1, 1, 0, 1, 1, 1, -1, 0, 1, 0,
+        ]);
+        return createStaticVertexBuffer(gl, debug, vertexArray);
+      }
+      function createIndexBuffer(gl, debug) {
+        // OpenGL (and WebGL) have "CCW == front" winding
+        const triangleVertexIndices = new Uint16Array([0, 1, 2, 2, 1, 3]);
+        return createStaticIndexBuffer(gl, debug, triangleVertexIndices);
+      }
+      function createAndConfigureTexture(
+        gl,
+        debug,
+        width,
+        height,
+        internalFormat,
+        textureFormat,
+        textureType
+      ) {
+        validateTextureSize(width, height);
+        const texture = createTexture(gl, debug);
+        const tex2d = gl.TEXTURE_2D;
+        callAndCheck(gl, debug, () => gl.bindTexture(tex2d, texture));
+        callAndCheck(gl, debug, () => gl.texParameteri(tex2d, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE));
+        callAndCheck(gl, debug, () => gl.texParameteri(tex2d, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE));
+        callAndCheck(gl, debug, () => gl.texParameteri(tex2d, gl.TEXTURE_MIN_FILTER, gl.NEAREST));
+        callAndCheck(gl, debug, () => gl.texParameteri(tex2d, gl.TEXTURE_MAG_FILTER, gl.NEAREST));
+        callAndCheck(gl, debug, () =>
+          gl.texImage2D(
+            tex2d,
+            0,
+            internalFormat,
+            width,
+            height,
+            0,
+            textureFormat,
+            textureType,
+            null
+          )
+        );
+        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, null));
+        return texture;
+      }
+      function createFloat32MatrixTexture(gl, debug, rows, columns, textureConfig) {
+        const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);
+        return createAndConfigureTexture(
+          gl,
+          debug,
+          width,
+          height,
+          textureConfig.internalFormatFloat,
+          textureConfig.textureFormatFloat,
+          gl.FLOAT
+        );
+      }
+      function createFloat16MatrixTexture(gl, debug, rows, columns, textureConfig) {
+        const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);
+        return createAndConfigureTexture(
+          gl,
+          debug,
+          width,
+          height,
+          textureConfig.internalFormatHalfFloat,
+          textureConfig.textureFormatFloat,
+          textureConfig.textureTypeHalfFloat
+        );
+      }
+      function createUnsignedBytesMatrixTexture(gl, debug, rows, columns, textureConfig) {
+        const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);
+        return createAndConfigureTexture(
+          gl,
+          debug,
+          width,
+          height,
+          gl.RGBA,
+          gl.RGBA,
+          gl.UNSIGNED_BYTE
+        );
+      }
+      function createPackedMatrixTexture(gl, debug, rows, columns, textureConfig) {
+        const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);
+        return createAndConfigureTexture(
+          gl,
+          debug,
+          width,
+          height,
+          textureConfig.internalFormatPackedFloat,
+          gl.RGBA,
+          gl.FLOAT
+        );
+      }
+      function createFloat16PackedMatrixTexture(gl, debug, rows, columns, textureConfig) {
+        const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);
+        return createAndConfigureTexture(
+          gl,
+          debug,
+          width,
+          height,
+          textureConfig.internalFormatPackedHalfFloat,
+          gl.RGBA,
+          textureConfig.textureTypeHalfFloat
+        );
+      }
+      function bindVertexProgramAttributeStreams(gl, debug, program, vertexBuffer) {
+        const posOffset = 0; // x is the first buffer element
+        const uvOffset = 3 * 4; // uv comes after [x y z]
+        const stride = 3 * 4 + 2 * 4; // xyz + uv, each entry is 4-byte float.
+        callAndCheck(gl, debug, () => gl.bindBuffer(gl.ARRAY_BUFFER, vertexBuffer));
+        const success = bindVertexBufferToProgramAttribute(
+          gl,
+          debug,
+          program,
+          "clipSpacePos",
+          vertexBuffer,
+          3,
+          stride,
+          posOffset
+        );
+        return (
+          success &&
+          bindVertexBufferToProgramAttribute(
+            gl,
+            debug,
+            program,
+            "uv",
+            vertexBuffer,
+            2,
+            stride,
+            uvOffset
+          )
+        );
+      }
+      function uploadDenseMatrixToTexture(gl, debug, texture, width, height, data, textureConfig) {
+        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, texture));
+        let dataForUpload, texelDataType, internalFormat;
+        if (data instanceof Uint8Array) {
+          dataForUpload = new Uint8Array(width * height * 4);
+          texelDataType = gl.UNSIGNED_BYTE;
+          internalFormat = gl.RGBA;
+        } else {
+          dataForUpload = new Float32Array(width * height * 4);
+          texelDataType = gl.FLOAT;
+          internalFormat = textureConfig.internalFormatPackedFloat;
+        }
+        dataForUpload.set(data);
+        callAndCheck(gl, debug, () =>
+          gl.texImage2D(
+            gl.TEXTURE_2D,
+            0,
+            internalFormat,
+            width,
+            height,
+            0,
+            gl.RGBA,
+            texelDataType,
+            dataForUpload
+          )
+        );
+        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, null));
+      }
+      function uploadPixelDataToTexture(gl, debug, texture, pixels) {
+        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, texture));
+        if (pixels.data instanceof Uint8Array) {
+          callAndCheck(gl, debug, () =>
+            gl.texImage2D(
+              gl.TEXTURE_2D,
+              0,
+              gl.RGBA,
+              pixels.width,
+              pixels.height,
+              0,
+              gl.RGBA,
+              gl.UNSIGNED_BYTE,
+              pixels.data
+            )
+          );
+        } else {
+          callAndCheck(gl, debug, () =>
+            gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, pixels)
+          );
+        }
+        callAndCheck(gl, debug, () => gl.bindTexture(gl.TEXTURE_2D, null));
+      }
+      function createBufferFromOutputTexture(gl2, debug, rows, columns, textureConfig) {
+        // Create and bind the buffer.
+        const buffer = gl2.createBuffer();
+        callAndCheck(gl2, debug, () => gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer));
+        // Initialize the buffer to the size of the texture in bytes.
+        const bytesPerFloat = 4;
+        const valuesPerTexel = 4;
+        const bufferSizeBytes = bytesPerFloat * valuesPerTexel * rows * columns;
+        callAndCheck(gl2, debug, () =>
+          gl2.bufferData(gl2.PIXEL_PACK_BUFFER, bufferSizeBytes, gl2.STREAM_READ)
+        );
+        // Enqueue a command on the GPU command queue to copy of texture into the
+        // buffer.
+        callAndCheck(gl2, debug, () => gl2.readPixels(0, 0, columns, rows, gl2.RGBA, gl2.FLOAT, 0));
+        callAndCheck(gl2, debug, () => gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null));
+        return buffer;
+      }
+      function downloadFloat32MatrixFromBuffer(gl, buffer, size) {
+        const gl2 = gl;
+        const downloadTarget = new Float32Array(size);
+        gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer);
+        gl2.getBufferSubData(gl2.PIXEL_PACK_BUFFER, 0, downloadTarget);
+        gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null);
+        return downloadTarget;
+      }
+      function downloadByteEncodedFloatMatrixFromOutputTexture(
+        gl,
+        debug,
+        rows,
+        columns,
+        textureConfig
+      ) {
+        const [w, h] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);
+        const numChannels = 4;
+        const downloadTarget = new Uint8Array(
+          getUnpackedArraySizeFromMatrixSize(rows * columns, numChannels)
+        );
+        callAndCheck(gl, debug, () =>
+          gl.readPixels(
+            0,
+            0,
+            w,
+            h,
+            textureConfig.downloadTextureFormat,
+            gl.UNSIGNED_BYTE,
+            downloadTarget
+          )
+        );
+        // By wrapping the buffer in a Float32Array, we use native browser IEEE 754
+        // decoding of the 4 bytes that back each 32 bit float.
+        return new Float32Array(downloadTarget.buffer);
+      }
+      function downloadPackedMatrixFromBuffer(
+        gl,
+        buffer,
+        batch,
+        rows,
+        cols,
+        physicalRows,
+        physicalCols,
+        textureConfig
+      ) {
+        const gl2 = gl;
+        const downloadTarget = new Float32Array(
+          getPackedRGBAArraySizeFromMatrixShape(physicalRows, physicalCols)
+        );
+        gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer);
+        gl2.getBufferSubData(gl2.PIXEL_PACK_BUFFER, 0, downloadTarget);
+        gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null);
+        return downloadTarget;
+      }
+      function downloadMatrixFromPackedOutputTexture(gl, debug, physicalRows, physicalCols) {
+        const packedRGBA = new Float32Array(physicalRows * physicalCols * 4);
+        callAndCheck(gl, debug, () =>
+          gl.readPixels(0, 0, physicalCols, physicalRows, gl.RGBA, gl.FLOAT, packedRGBA)
+        );
+        return packedRGBA;
+      }
+      //# sourceMappingURL=gpgpu_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_context.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class gpgpu_context_GPGPUContext {
+        constructor(gl) {
+          this.outputTexture = null;
+          this.program = null;
+          this.disposed = false;
+          this.vertexAttrsAreBound = false;
+          this.itemsToPoll = [];
+          const glVersion = Object(dist["env"])().getNumber("WEBGL_VERSION");
+          if (gl != null) {
+            this.gl = gl;
+            setWebGLContext(glVersion, gl);
+          } else {
+            this.gl = getWebGLContext(glVersion);
+          }
+          // WebGL 2.0 enables texture floats without an extension.
+          let COLOR_BUFFER_FLOAT = "WEBGL_color_buffer_float";
+          const COLOR_BUFFER_HALF_FLOAT = "EXT_color_buffer_half_float";
+          if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 1) {
+            const TEXTURE_FLOAT = "OES_texture_float";
+            const TEXTURE_HALF_FLOAT = "OES_texture_half_float";
+            this.textureFloatExtension = getExtensionOrThrow(this.gl, this.debug, TEXTURE_FLOAT);
+            if (hasExtension(this.gl, TEXTURE_HALF_FLOAT)) {
+              this.textureHalfFloatExtension = getExtensionOrThrow(
+                this.gl,
+                this.debug,
+                TEXTURE_HALF_FLOAT
+              );
+            } else if (Object(dist["env"])().get("WEBGL_FORCE_F16_TEXTURES")) {
+              throw new Error(
+                "GL context does not support half float textures, yet the " +
+                  "environment flag WEBGL_FORCE_F16_TEXTURES is set to true."
+              );
+            }
+            this.colorBufferFloatExtension = this.gl.getExtension(COLOR_BUFFER_FLOAT);
+            if (hasExtension(this.gl, COLOR_BUFFER_HALF_FLOAT)) {
+              this.colorBufferHalfFloatExtension = getExtensionOrThrow(
+                this.gl,
+                this.debug,
+                COLOR_BUFFER_HALF_FLOAT
+              );
+            } else if (Object(dist["env"])().get("WEBGL_FORCE_F16_TEXTURES")) {
+              throw new Error(
+                "GL context does not support color renderable half floats, yet " +
+                  "the environment flag WEBGL_FORCE_F16_TEXTURES is set to true."
+              );
+            }
+          } else {
+            COLOR_BUFFER_FLOAT = "EXT_color_buffer_float";
+            if (hasExtension(this.gl, COLOR_BUFFER_FLOAT)) {
+              this.colorBufferFloatExtension = this.gl.getExtension(COLOR_BUFFER_FLOAT);
+            } else if (hasExtension(this.gl, COLOR_BUFFER_HALF_FLOAT)) {
+              this.colorBufferHalfFloatExtension = this.gl.getExtension(COLOR_BUFFER_HALF_FLOAT);
+            } else {
+              throw new Error("GL context does not support color renderable floats");
+            }
+          }
+          this.vertexBuffer = createVertexBuffer(this.gl, this.debug);
+          this.indexBuffer = createIndexBuffer(this.gl, this.debug);
+          this.framebuffer = createFramebuffer(this.gl, this.debug);
+          this.textureConfig = getTextureConfig(this.gl, this.textureHalfFloatExtension);
+        }
+        get debug() {
+          return Object(dist["env"])().getBool("DEBUG");
+        }
+        dispose() {
+          if (this.disposed) {
+            return;
+          }
+          if (this.program != null) {
+            console.warn(
+              "Disposing a GPGPUContext that still has a bound WebGLProgram." +
+                " This is probably a resource leak, delete the program with " +
+                "GPGPUContext.deleteProgram before disposing."
+            );
+          }
+          if (this.outputTexture != null) {
+            console.warn(
+              "Disposing a GPGPUContext that still has a bound output matrix " +
+                "texture.  This is probably a resource leak, delete the output " +
+                "matrix texture with GPGPUContext.deleteMatrixTexture before " +
+                "disposing."
+            );
+          }
+          const gl = this.gl;
+          callAndCheck(gl, this.debug, () => gl.finish());
+          callAndCheck(gl, this.debug, () => gl.bindFramebuffer(gl.FRAMEBUFFER, null));
+          callAndCheck(gl, this.debug, () => gl.deleteFramebuffer(this.framebuffer));
+          callAndCheck(gl, this.debug, () => gl.bindBuffer(gl.ARRAY_BUFFER, null));
+          callAndCheck(gl, this.debug, () => gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, null));
+          callAndCheck(gl, this.debug, () => gl.deleteBuffer(this.indexBuffer));
+          this.disposed = true;
+        }
+        createFloat32MatrixTexture(rows, columns) {
+          this.throwIfDisposed();
+          return createFloat32MatrixTexture(this.gl, this.debug, rows, columns, this.textureConfig);
+        }
+        createFloat16MatrixTexture(rows, columns) {
+          this.throwIfDisposed();
+          return createFloat16MatrixTexture(this.gl, this.debug, rows, columns, this.textureConfig);
+        }
+        createUnsignedBytesMatrixTexture(rows, columns) {
+          this.throwIfDisposed();
+          return createUnsignedBytesMatrixTexture(
+            this.gl,
+            this.debug,
+            rows,
+            columns,
+            this.textureConfig
+          );
+        }
+        uploadPixelDataToTexture(texture, pixels) {
+          this.throwIfDisposed();
+          uploadPixelDataToTexture(this.gl, this.debug, texture, pixels);
+        }
+        uploadDenseMatrixToTexture(texture, width, height, data) {
+          this.throwIfDisposed();
+          uploadDenseMatrixToTexture(
+            this.gl,
+            this.debug,
+            texture,
+            width,
+            height,
+            data,
+            this.textureConfig
+          );
+        }
+        createFloat16PackedMatrixTexture(rows, columns) {
+          this.throwIfDisposed();
+          return createFloat16PackedMatrixTexture(
+            this.gl,
+            this.debug,
+            rows,
+            columns,
+            this.textureConfig
+          );
+        }
+        createPackedMatrixTexture(rows, columns) {
+          this.throwIfDisposed();
+          return createPackedMatrixTexture(this.gl, this.debug, rows, columns, this.textureConfig);
+        }
+        deleteMatrixTexture(texture) {
+          this.throwIfDisposed();
+          if (this.outputTexture === texture) {
+            unbindColorTextureFromFramebuffer(this.gl, this.debug, this.framebuffer);
+            this.outputTexture = null;
+          }
+          callAndCheck(this.gl, this.debug, () => this.gl.deleteTexture(texture));
+        }
+        downloadByteEncodedFloatMatrixFromOutputTexture(texture, rows, columns) {
+          return this.downloadMatrixDriver(texture, () =>
+            downloadByteEncodedFloatMatrixFromOutputTexture(
+              this.gl,
+              this.debug,
+              rows,
+              columns,
+              this.textureConfig
+            )
+          );
+        }
+        downloadPackedMatrixFromBuffer(buffer, batch, rows, columns, physicalRows, physicalCols) {
+          return downloadPackedMatrixFromBuffer(
+            this.gl,
+            buffer,
+            batch,
+            rows,
+            columns,
+            physicalRows,
+            physicalCols,
+            this.textureConfig
+          );
+        }
+        downloadFloat32MatrixFromBuffer(buffer, size) {
+          return downloadFloat32MatrixFromBuffer(this.gl, buffer, size);
+        }
+        createBufferFromTexture(texture, rows, columns) {
+          this.bindTextureToFrameBuffer(texture);
+          const result = createBufferFromOutputTexture(
+            this.gl,
+            this.debug,
+            rows,
+            columns,
+            this.textureConfig
+          );
+          this.unbindTextureToFrameBuffer();
+          return result;
+        }
+        createAndWaitForFence() {
+          const fenceContext = this.createFence(this.gl);
+          return this.pollFence(fenceContext);
+        }
+        createFence(gl) {
+          let query;
+          let isFencePassed;
+          if (Object(dist["env"])().getBool("WEBGL_FENCE_API_ENABLED")) {
+            const gl2 = gl;
+            const sync = gl2.fenceSync(gl2.SYNC_GPU_COMMANDS_COMPLETE, 0);
+            gl.flush();
+            isFencePassed = () => {
+              const status = gl2.clientWaitSync(sync, 0, 0);
+              return status === gl2.ALREADY_SIGNALED || status === gl2.CONDITION_SATISFIED;
+            };
+            query = sync;
+          } else if (
+            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") > 0
+          ) {
+            query = this.beginQuery();
+            this.endQuery();
+            isFencePassed = () =>
+              this.isQueryAvailable(
+                query,
+                Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")
+              );
+          } else {
+            // If we have no way to fence, return true immediately. This will fire in
+            // WebGL 1.0 when there is no disjoint query timer. In this case, because
+            // the fence passes immediately, we'll immediately ask for a download of
+            // the texture, which will cause the UI thread to hang.
+            isFencePassed = () => true;
+          }
+          return { query, isFencePassed };
+        }
+        downloadMatrixFromPackedTexture(texture, physicalRows, physicalCols) {
+          return this.downloadMatrixDriver(texture, () =>
+            downloadMatrixFromPackedOutputTexture(this.gl, this.debug, physicalRows, physicalCols)
+          );
+        }
+        createProgram(fragmentShaderSource) {
+          this.throwIfDisposed();
+          const gl = this.gl;
+          const fragmentShader = createFragmentShader(gl, this.debug, fragmentShaderSource);
+          const vertexShader = gpgpu_util_createVertexShader(gl, this.debug);
+          const program = createProgram(gl, this.debug);
+          callAndCheck(gl, this.debug, () => gl.attachShader(program, vertexShader));
+          callAndCheck(gl, this.debug, () => gl.attachShader(program, fragmentShader));
+          linkProgram(gl, this.debug, program);
+          if (this.debug) {
+            validateProgram(gl, this.debug, program);
+          }
+          if (!this.vertexAttrsAreBound) {
+            this.setProgram(program);
+            this.vertexAttrsAreBound = bindVertexProgramAttributeStreams(
+              gl,
+              this.debug,
+              this.program,
+              this.vertexBuffer
+            );
+          }
+          return program;
+        }
+        deleteProgram(program) {
+          this.throwIfDisposed();
+          if (program === this.program) {
+            this.program = null;
+          }
+          if (program != null) {
+            callAndCheck(this.gl, this.debug, () => this.gl.deleteProgram(program));
+          }
+        }
+        setProgram(program) {
+          this.throwIfDisposed();
+          this.program = program;
+          if (this.program != null && this.debug) {
+            validateProgram(this.gl, this.debug, this.program);
+          }
+          callAndCheck(this.gl, this.debug, () => this.gl.useProgram(program));
+        }
+        getUniformLocation(program, uniformName, shouldThrow = true) {
+          this.throwIfDisposed();
+          if (shouldThrow) {
+            return getProgramUniformLocationOrThrow(this.gl, this.debug, program, uniformName);
+          } else {
+            return getProgramUniformLocation(this.gl, program, uniformName);
+          }
+        }
+        getAttributeLocation(program, attribute) {
+          this.throwIfDisposed();
+          return callAndCheck(this.gl, this.debug, () =>
+            this.gl.getAttribLocation(program, attribute)
+          );
+        }
+        getUniformLocationNoThrow(program, uniformName) {
+          this.throwIfDisposed();
+          return this.gl.getUniformLocation(program, uniformName);
+        }
+        setInputMatrixTexture(inputMatrixTexture, uniformLocation, textureUnit) {
+          this.throwIfDisposed();
+          this.throwIfNoProgram();
+          bindTextureToProgramUniformSampler(
+            this.gl,
+            this.debug,
+            this.program,
+            inputMatrixTexture,
+            uniformLocation,
+            textureUnit
+          );
+        }
+        setOutputMatrixTexture(outputMatrixTexture, rows, columns) {
+          this.setOutputMatrixTextureDriver(outputMatrixTexture, columns, rows);
+        }
+        setOutputPackedMatrixTexture(outputPackedMatrixTexture, rows, columns) {
+          this.throwIfDisposed();
+          const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);
+          this.setOutputMatrixTextureDriver(outputPackedMatrixTexture, width, height);
+        }
+        setOutputMatrixWriteRegion(startRow, numRows, startColumn, numColumns) {
+          this.setOutputMatrixWriteRegionDriver(startColumn, startRow, numColumns, numRows);
+        }
+        setOutputPackedMatrixWriteRegion(startRow, numRows, startColumn, numColumns) {
+          throw new Error("setOutputPackedMatrixWriteRegion not implemented.");
+        }
+        debugValidate() {
+          if (this.program != null) {
+            validateProgram(this.gl, this.debug, this.program);
+          }
+          validateFramebuffer(this.gl);
+        }
+        executeProgram() {
+          this.throwIfDisposed();
+          this.throwIfNoProgram();
+          const gl = this.gl;
+          if (this.debug) {
+            this.debugValidate();
+          }
+          callAndCheck(gl, this.debug, () =>
+            gl.drawElements(gl.TRIANGLES, 6, gl.UNSIGNED_SHORT, 0)
+          );
+        }
+        blockUntilAllProgramsCompleted() {
+          this.throwIfDisposed();
+          callAndCheck(this.gl, this.debug, () => this.gl.finish());
+        }
+        getQueryTimerExtension() {
+          if (this.disjointQueryTimerExtension == null) {
+            this.disjointQueryTimerExtension = getExtensionOrThrow(
+              this.gl,
+              this.debug,
+              Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2
+                ? "EXT_disjoint_timer_query_webgl2"
+                : "EXT_disjoint_timer_query"
+            );
+          }
+          return this.disjointQueryTimerExtension;
+        }
+        getQueryTimerExtensionWebGL2() {
+          return this.getQueryTimerExtension();
+        }
+        getQueryTimerExtensionWebGL1() {
+          return this.getQueryTimerExtension();
+        }
+        beginQuery() {
+          if (
+            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2
+          ) {
+            const gl2 = this.gl;
+            const ext = this.getQueryTimerExtensionWebGL2();
+            const query = gl2.createQuery();
+            gl2.beginQuery(ext.TIME_ELAPSED_EXT, query);
+            return query;
+          }
+          const ext = this.getQueryTimerExtensionWebGL1();
+          const query = ext.createQueryEXT();
+          ext.beginQueryEXT(ext.TIME_ELAPSED_EXT, query);
+          return query;
+        }
+        endQuery() {
+          if (
+            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2
+          ) {
+            const gl2 = this.gl;
+            const ext = this.getQueryTimerExtensionWebGL2();
+            gl2.endQuery(ext.TIME_ELAPSED_EXT);
+            return;
+          }
+          const ext = this.getQueryTimerExtensionWebGL1();
+          ext.endQueryEXT(ext.TIME_ELAPSED_EXT);
+        }
+        async waitForQueryAndGetTime(query) {
+          await dist["util"].repeatedTry(
+            () =>
+              this.disposed || // while testing contexts are created / disposed
+              // in rapid succession, so without this check we
+              // may poll for the query timer indefinitely
+              this.isQueryAvailable(
+                query,
+                Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")
+              )
+          );
+          return this.getQueryTime(
+            query,
+            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")
+          );
+        }
+        getQueryTime(query, queryTimerVersion) {
+          if (queryTimerVersion === 0) {
+            return null;
+          }
+          if (queryTimerVersion === 2) {
+            const gl2 = this.gl;
+            const timeElapsedNanos = gl2.getQueryParameter(query, gl2.QUERY_RESULT);
+            // Return milliseconds.
+            return timeElapsedNanos / 1000000;
+          } else {
+            const ext = this.getQueryTimerExtensionWebGL1();
+            const timeElapsedNanos = ext.getQueryObjectEXT(query, ext.QUERY_RESULT_EXT);
+            // Return milliseconds.
+            return timeElapsedNanos / 1000000;
+          }
+        }
+        isQueryAvailable(query, queryTimerVersion) {
+          if (queryTimerVersion === 0) {
+            return true;
+          }
+          if (queryTimerVersion === 2) {
+            const gl2 = this.gl;
+            const ext = this.getQueryTimerExtensionWebGL2();
+            const available = gl2.getQueryParameter(query, gl2.QUERY_RESULT_AVAILABLE);
+            if (this.disjoint == null) {
+              this.disjoint = this.gl.getParameter(ext.GPU_DISJOINT_EXT);
+            }
+            return available && !this.disjoint;
+          } else {
+            const ext = this.getQueryTimerExtensionWebGL1();
+            const available = ext.getQueryObjectEXT(query, ext.QUERY_RESULT_AVAILABLE_EXT);
+            if (this.disjoint == null) {
+              this.disjoint = this.gl.getParameter(ext.GPU_DISJOINT_EXT);
+            }
+            return available && !this.disjoint;
+          }
+        }
+        pollFence(fenceContext) {
+          return new Promise((resolve) => {
+            this.addItemToPoll(
+              () => fenceContext.isFencePassed(),
+              () => resolve()
+            );
+          });
+        }
+        pollItems() {
+          // Find the last query that has finished.
+          const index = linearSearchLastTrue(this.itemsToPoll.map((x) => x.isDoneFn));
+          for (let i = 0; i <= index; ++i) {
+            const { resolveFn } = this.itemsToPoll[i];
+            resolveFn();
+          }
+          this.itemsToPoll = this.itemsToPoll.slice(index + 1);
+        }
+        addItemToPoll(isDoneFn, resolveFn) {
+          this.itemsToPoll.push({ isDoneFn, resolveFn });
+          if (this.itemsToPoll.length > 1) {
+            // We already have a running loop that polls.
+            return;
+          }
+          // Start a new loop that polls.
+          dist["util"].repeatedTry(() => {
+            this.pollItems();
+            // End the loop if no more items to poll.
+            return this.itemsToPoll.length === 0;
+          });
+        }
+        bindTextureToFrameBuffer(texture) {
+          this.throwIfDisposed();
+          bindColorTextureToFramebuffer(this.gl, this.debug, texture, this.framebuffer);
+          if (this.debug) {
+            validateFramebuffer(this.gl);
+          }
+        }
+        unbindTextureToFrameBuffer() {
+          if (this.outputTexture != null) {
+            bindColorTextureToFramebuffer(
+              this.gl,
+              this.debug,
+              this.outputTexture,
+              this.framebuffer
+            );
+            if (this.debug) {
+              validateFramebuffer(this.gl);
+            }
+          } else {
+            unbindColorTextureFromFramebuffer(this.gl, this.debug, this.framebuffer);
+          }
+        }
+        downloadMatrixDriver(texture, downloadAndDecode) {
+          this.bindTextureToFrameBuffer(texture);
+          const result = downloadAndDecode();
+          this.unbindTextureToFrameBuffer();
+          return result;
+        }
+        setOutputMatrixTextureDriver(outputMatrixTextureMaybePacked, width, height) {
+          this.throwIfDisposed();
+          const gl = this.gl;
+          bindColorTextureToFramebuffer(
+            gl,
+            this.debug,
+            outputMatrixTextureMaybePacked,
+            this.framebuffer
+          );
+          if (this.debug) {
+            validateFramebuffer(gl);
+          }
+          this.outputTexture = outputMatrixTextureMaybePacked;
+          callAndCheck(gl, this.debug, () => gl.viewport(0, 0, width, height));
+          callAndCheck(gl, this.debug, () => gl.scissor(0, 0, width, height));
+        }
+        setOutputMatrixWriteRegionDriver(x, y, width, height) {
+          this.throwIfDisposed();
+          callAndCheck(this.gl, this.debug, () => this.gl.scissor(x, y, width, height));
+        }
+        throwIfDisposed() {
+          if (this.disposed) {
+            throw new Error("Attempted to use disposed GPGPUContext.");
+          }
+        }
+        throwIfNoProgram() {
+          if (this.program == null) {
+            throw new Error("No GPU program is currently set.");
+          }
+        }
+      }
+      /**
+       * Finds the index of the last true element using linear search.
+       * Note: We can't do binary search because Chrome expects us to explicitly
+       * test all fences before download:
+       * https://github.com/tensorflow/tfjs/issues/1145
+       */
+      function linearSearchLastTrue(arr) {
+        let i = 0;
+        for (; i < arr.length; ++i) {
+          const isDone = arr[i]();
+          if (!isDone) {
+            break;
+          }
+        }
+        return i - 1;
+      }
+      //# sourceMappingURL=gpgpu_context.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_math.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function compileProgram(gpgpu, program, inputs, output) {
+        const userCode = program.userCode;
+        const inputInfos = inputs.map((input, i) => {
+          const shapeInfo = {
+            logicalShape: input.shape,
+            texShape: input.isUniform ? null : input.texData.texShape,
+            isUniform: input.isUniform,
+            isPacked: input.isUniform ? false : input.texData.isPacked,
+            flatOffset: null,
+          };
+          if (
+            input.texData != null &&
+            input.texData.slice != null &&
+            input.texData.slice.flatOffset > 0
+          ) {
+            shapeInfo.flatOffset = input.texData.slice.flatOffset;
+          }
+          return { name: program.variableNames[i], shapeInfo };
+        });
+        const inShapeInfos = inputInfos.map((x) => x.shapeInfo);
+        const outShapeInfo = {
+          logicalShape: output.shape,
+          texShape: output.texData.texShape,
+          isUniform: false,
+          isPacked: output.texData.isPacked,
+          flatOffset: null,
+        };
+        const source = makeShader(inputInfos, outShapeInfo, userCode, program.packedInputs);
+        const webGLProgram = gpgpu.createProgram(source);
+        // Add special uniforms (NAN, INFINITY)
+        let infLoc = null;
+        const nanLoc = gpgpu.getUniformLocation(webGLProgram, "NAN", false);
+        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 1) {
+          infLoc = gpgpu.getUniformLocation(webGLProgram, "INFINITY", false);
+        }
+        // Add user-defined uniforms
+        const uniformLocations = {};
+        for (let i = 0; i < program.variableNames.length; i++) {
+          const varName = program.variableNames[i];
+          const shouldThrow = false;
+          uniformLocations[varName] = gpgpu.getUniformLocation(webGLProgram, varName, shouldThrow);
+          uniformLocations[`offset${varName}`] = gpgpu.getUniformLocation(
+            webGLProgram,
+            `offset${varName}`,
+            shouldThrow
+          );
+        }
+        return {
+          program,
+          source,
+          webGLProgram,
+          uniformLocations,
+          inShapeInfos,
+          outShapeInfo,
+          infLoc,
+          nanLoc,
+        };
+      }
+      function validateBinaryAndProgram(shapeInfos, inputs) {
+        if (shapeInfos.length !== inputs.length) {
+          throw Error(
+            `Binary was compiled with ${shapeInfos.length} inputs, but ` +
+              `was executed with ${inputs.length} inputs`
+          );
+        }
+        shapeInfos.forEach((s, i) => {
+          const shapeA = s.logicalShape;
+          const input = inputs[i];
+          const shapeB = input.shape;
+          if (!dist["util"].arraysEqual(shapeA, shapeB)) {
+            throw Error(
+              `Binary was compiled with different shapes than ` +
+                `the current args. Shapes ${shapeA} and ${shapeB} must match`
+            );
+          }
+          // The input is uploaded as uniform.
+          if (s.isUniform && input.isUniform) {
+            return;
+          }
+          const texShapeA = s.texShape;
+          const texShapeB = input.isUniform ? null : input.texData.texShape;
+          if (!dist["util"].arraysEqual(texShapeA, texShapeB)) {
+            throw Error(
+              `Binary was compiled with different texture shapes than the` +
+                ` current args. Shape ${texShapeA} and ${texShapeB} must match`
+            );
+          }
+        });
+      }
+      function runProgram(gpgpu, binary, inputs, output, customSetup) {
+        validateBinaryAndProgram(binary.inShapeInfos, inputs);
+        validateBinaryAndProgram([binary.outShapeInfo], [output]);
+        const outTex = output.texData.texture;
+        const outTexShape = output.texData.texShape;
+        if (output.texData.isPacked) {
+          gpgpu.setOutputPackedMatrixTexture(outTex, outTexShape[0], outTexShape[1]);
+        } else {
+          gpgpu.setOutputMatrixTexture(outTex, outTexShape[0], outTexShape[1]);
+        }
+        gpgpu.setProgram(binary.webGLProgram);
+        // Set special uniforms (NAN, INFINITY)
+        if (Object(dist["env"])().getNumber("WEBGL_VERSION") === 1) {
+          if (binary.infLoc !== null) {
+            gpgpu.gl.uniform1f(binary.infLoc, Infinity);
+          }
+        }
+        if (binary.nanLoc !== null) {
+          gpgpu.gl.uniform1f(binary.nanLoc, NaN);
+        }
+        // Set user-defined inputs
+        inputs.forEach((input, i) => {
+          const varName = binary.program.variableNames[i];
+          const varLoc = binary.uniformLocations[varName];
+          const varOffsetLoc = binary.uniformLocations[`offset${varName}`];
+          if (varLoc == null) {
+            // The compiler inferred that this variable is not used in this shader.
+            return;
+          }
+          if (input.isUniform) {
+            // Upload the values of the tensor as uniform.
+            if (dist["util"].sizeFromShape(input.shape) < 2) {
+              gpgpu.gl.uniform1f(varLoc, input.uniformValues[0]);
+            } else {
+              let vals = input.uniformValues;
+              if (!(vals instanceof Float32Array)) {
+                vals = new Float32Array(vals);
+              }
+              gpgpu.gl.uniform1fv(varLoc, vals);
+            }
+            return;
+          }
+          // If the input was sliced, upload the flat offset index.
+          if (input.texData.slice != null && varOffsetLoc != null) {
+            gpgpu.gl.uniform1i(varOffsetLoc, input.texData.slice.flatOffset);
+          }
+          gpgpu.setInputMatrixTexture(input.texData.texture, varLoc, i);
+        });
+        if (customSetup != null) {
+          customSetup(gpgpu, binary.webGLProgram);
+        }
+        gpgpu.executeProgram();
+      }
+      function makeShaderKey(program, inputs, output) {
+        let keyInputs = "";
+        inputs.concat(output).forEach((x) => {
+          const hasOffset =
+            x.texData != null && x.texData.slice != null && x.texData.slice.flatOffset > 0;
+          const texShape = x.isUniform ? "uniform" : x.texData.texShape;
+          keyInputs += `${x.shape}_${texShape}_${hasOffset}`;
+        });
+        const keyUserCode = program.userCode;
+        let key = program.constructor.name;
+        // Fast string concat. See https://jsperf.com/string-concatenation/14.
+        key += "_" + keyInputs + "_" + keyUserCode;
+        return key;
+      }
+      //# sourceMappingURL=gpgpu_math.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/im2col_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class im2col_packed_gpu_Im2ColPackedProgram {
+        constructor(outputShape, inputShape, convInfo) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = outputShape;
+          const {
+            filterWidth,
+            inChannels,
+            strideWidth,
+            strideHeight,
+            padInfo,
+            outWidth,
+            dilationWidth,
+            dilationHeight,
+            dataFormat,
+          } = convInfo;
+          const { left, top } = padInfo;
+          const itemsPerBlockRow = inChannels * filterWidth;
+          const glsl = getGlslDifferences();
+          const isChannelsLast = dataFormat === "channelsLast";
+          const rowDim = isChannelsLast ? 0 : 1;
+          const colDim = isChannelsLast ? 1 : 2;
+          let unrolled = ``;
+          for (let row = 0; row <= 1; row++) {
+            for (let col = 0; col <= 1; col++) {
+              unrolled += `
+          blockIndex = rc.y + ${col};
+          pos = rc.x + ${row};
+
+          if(blockIndex < ${outputShape[1]} && pos < ${outputShape[0]}) {
+            offsetY = int(blockIndex / (${outWidth})) * ${strideHeight} - ${top};
+            d0 = offsetY + ${dilationHeight} * (pos / ${itemsPerBlockRow});
+
+            if(d0 < ${inputShape[rowDim]} && d0 >= 0) {
+
+              offsetX = int(mod(float(blockIndex), ${outWidth}.) * ${strideWidth}. - ${left}.);
+              d1 = offsetX + ${dilationWidth} * (int(mod(float(pos), ${itemsPerBlockRow}.) / ${inChannels}.));
+
+              if(d1 < ${inputShape[colDim]} && d1 >= 0) {
+
+                ch = int(mod(float(pos), ${inChannels}.));
+
+                if (${isChannelsLast}) {
+                  innerDims = vec2(d1, ch);
+                  result[${row * 2 + col}] = getChannel(
+                    getA(d0, int(innerDims.x),
+                    int(innerDims.y)), innerDims);
+                } else {
+                  innerDims = vec2(d0, d1);
+                  result[${row * 2 + col}] = getChannel(
+                    getA(ch, int(innerDims.x),
+                    int(innerDims.y)), innerDims);
+                }
+              }
+            }
+          }
+        `;
+            }
+          }
+          this.userCode = `
+      void main() {
+        ivec2 rc = getOutputCoords();
+
+        vec4 result = vec4(0);
+
+        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
+        vec2 innerDims;
+
+        ${unrolled}
+
+        ${glsl.output} = result;
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=im2col_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class LRNProgram {
+        constructor(xShape, radius, bias, alpha, beta) {
+          this.variableNames = ["x"];
+          this.outputShape = [];
+          const rad = radius;
+          const maxD = xShape[3] - 1;
+          this.outputShape = xShape;
+          // optimize pow(bias + alpha * sum, -beta)
+          // src: https://github.com/tensorflow/tensorflow/..
+          // blob/26033a1644a9c4a5fbe3170ab2e864b6a4ccd4ca/..
+          // tensorflow/core/kernels/mkl_lrn_op.cc#L320
+          let powOperator;
+          const basis = `float(${bias}) + float(${alpha}) * sum`;
+          if (beta === 0.5) {
+            powOperator = `inversesqrt(${basis})`;
+          } else if (beta === 1.0) {
+            powOperator = `1.0/(${basis})`;
+          } else {
+            powOperator = `exp(log(${basis}) * float(-${beta}));`;
+          }
+          this.userCode = `
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int r = coords[1];
+        int c = coords[2];
+        int d = coords[3];
+        float x = getX(b, r, c, d);
+        float sum = 0.0;
+        for (int j = -${rad}; j <= ${rad}; j++) {
+          int idx = d + j;
+          if (idx >= 0 && idx <=  ${maxD}) {
+            float z = getX(b, r, c, idx);
+            sum += z * z;
+          }
+        }
+        float val = x * ${powOperator};
+        setOutput(val);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=lrn_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_grad_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class LRNGradProgram {
+        constructor(inputShape, depthRadius, bias, alpha, beta) {
+          this.variableNames = ["inputImage", "outputImage", "dy"];
+          this.outputShape = [];
+          this.outputShape = inputShape;
+          this.depth = inputShape[3];
+          this.depthRadius = depthRadius;
+          this.bias = bias;
+          this.alpha = alpha;
+          this.beta = beta;
+          this.userCode = `
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int r = coords[1];
+        int c = coords[2];
+
+        float result = 0.0;
+        for (int d = 0; d < ${this.depth}; ++d) {
+          int depthBegin = int(max(0.0, float(d - ${depthRadius})));
+          int depthEnd = int(min(float(${this.depth}),
+              float(d + ${depthRadius} + 1)));
+
+          const int MIN_DEPTH_BEGIN = 0;
+          const int MAX_DEPTH_END = ${this.depth};
+
+          float norm = 0.0;
+          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
+            if (k < depthBegin){
+              continue;
+            }
+            else if (k >= depthBegin && k < depthEnd) {
+              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
+            }
+            else {
+              break;
+            }
+          }
+
+          norm = float(${alpha}) * norm + float(${bias});
+
+          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
+            if (k < depthBegin){
+              continue;
+            }
+            else if (k >= depthBegin && k < depthEnd){
+              float dyi = -2.0 * float(${alpha})
+                * float(${beta})
+                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
+                / norm;
+              if (k == d) {
+                dyi += pow(norm, -1.0 * ${beta});
+              }
+              if (k == coords[3]) {
+                dyi *= getDy(b, r, c, d);
+                result += dyi;
+              }
+            }
+            else {
+              break;
+            }
+          }
+      }
+      setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=lrn_grad_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class LRNPackedProgram {
+        constructor(xShape, radius, bias, alpha, beta) {
+          this.variableNames = ["x"];
+          this.outputShape = [];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          const rad = radius;
+          const maxD = xShape[3] - 1;
+          this.outputShape = xShape;
+          // optimize pow(bias + alpha * sum, -beta)
+          // src: https://github.com/tensorflow/tensorflow/..
+          // blob/26033a1644a9c4a5fbe3170ab2e864b6a4ccd4ca/..
+          // tensorflow/core/kernels/mkl_lrn_op.cc#L320
+          let powOperator;
+          const basis = `float(${bias}) + float(${alpha}) * sum`;
+          if (beta === 0.5) {
+            powOperator = `inversesqrt(${basis})`;
+          } else if (beta === 1.0) {
+            powOperator = `1.0/(${basis})`;
+          } else {
+            powOperator = `exp(log(${basis}) * float(-${beta}));`;
+          }
+          this.userCode = `
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords.x;
+        int r = coords.y;
+        int c = coords.z;
+        int d = coords.w;
+
+        bool hasNextCol = d < ${this.outputShape[3]};
+        bool hasNextRow = c < ${this.outputShape[2]};
+
+        vec4 sum = vec4(0.);
+        vec4 xFragAtOutputCoords = getX(b, r, c, d);
+
+        vec4 xAtOutputCoords = vec4(
+          getChannel(xFragAtOutputCoords, vec2(c, d)),
+          hasNextCol ?
+            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
+          hasNextRow ?
+            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
+          (hasNextRow && hasNextCol) ?
+            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
+        );
+
+        int firstChannel = d - ${rad};
+        vec2 cache = vec2(0.);
+        if(firstChannel >= 0){
+          vec4 firstChannelFrag = getX(b, r, c, firstChannel);
+          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
+            if(hasNextRow){
+              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
+            }
+        }
+
+        ivec2 depth = ivec2(d, d + 1);
+        for (int j = - ${rad}; j <= ${rad}; j++) {
+          ivec2 idx = depth + j;
+          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
+          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${maxD}));
+
+          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
+          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;
+
+          if(depthInRange || depthPlusOneInRange){
+            vec4 z = vec4(0.);
+            vec4 xFragAtCurrentDepth;
+            z.xz = cache.xy;
+            if(depthPlusOneInRange && hasNextCol){
+              xFragAtCurrentDepth = idx.y != d ?
+                getX(b, r, c, idx.y) : xFragAtOutputCoords;
+              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
+              if(hasNextRow){
+                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
+              }
+            }
+            cache.xy = z.yw;
+            sum += z * z;
+          }
+        }
+        vec4 result = xAtOutputCoords * ${powOperator};
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=lrn_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/max_pool_backprop_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class MaxPool2DBackpropProgram {
+        constructor(convInfo) {
+          this.variableNames = ["dy", "maxPos"];
+          this.outputShape = convInfo.inShape;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+          const lastIndex = effectiveFilterHeight * effectiveFilterWidth - 1;
+          this.userCode = `
+      const ivec2 pads = ivec2(${padTop}, ${padLeft});
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int d = coords[3];
+
+        ivec2 dyRCCorner = coords.yz - pads;
+        int dyRCorner = dyRCCorner.x;
+        int dyCCorner = dyRCCorner.y;
+
+        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
+        // ? = to be determined. : = across all values in that axis.
+        float dotProd = 0.0;
+        for (int wR = 0; wR < ${effectiveFilterHeight};
+          wR += ${dilationHeight}) {
+          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
+
+          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {
+            continue;
+          }
+          int idyR = int(dyR);
+
+          for (int wC = 0; wC < ${effectiveFilterWidth}; wC++) {
+            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
+
+            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
+                fract(dyC) > 0.0) {
+              continue;
+            }
+            int idyC = int(dyC);
+
+            float dyValue = getDy(b, idyR, idyC, d);
+            int maxPosValue = ${lastIndex} - int(getMaxPos(b, idyR, idyC, d));
+
+            // Get the current value, check it against the value from the
+            // position matrix.
+            int curPosValue = wR * ${effectiveFilterWidth} + wC;
+            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
+
+            dotProd += dyValue * mask;
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      class MaxPool3DBackpropProgram {
+        constructor(convInfo) {
+          this.variableNames = ["dy", "maxPos"];
+          this.outputShape = convInfo.inShape;
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
+          const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+          const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+          const lastIndex = effectiveFilterDepth * effectiveFilterHeight * effectiveFilterWidth - 1;
+          this.userCode = `
+      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
+
+      void main() {
+        ivec5 coords = getOutputCoords();
+        int batch = coords.x;
+        int ch = coords.u;
+
+        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
+        int dyDCorner = dyCorner.x;
+        int dyRCorner = dyCorner.y;
+        int dyCCorner = dyCorner.z;
+
+        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
+        // dx(xD, xR, xC, ch).
+        // ? = to be determined. : = across all values in that axis.
+        float dotProd = 0.0;
+
+        for (int wD = 0; wD < ${effectiveFilterDepth};
+           wD += ${dilationDepth}) {
+          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;
+
+          if (dyD < 0.0 || dyD >= ${convInfo.outDepth}.0 || fract(dyD) > 0.0) {
+            continue;
+          }
+          int idyD = int(dyD);
+
+          for (int wR = 0; wR < ${effectiveFilterHeight};
+              wR += ${dilationHeight}) {
+            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;
+
+            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||
+                fract(dyR) > 0.0) {
+              continue;
+            }
+            int idyR = int(dyR);
+
+            for (int wC = 0; wC < ${effectiveFilterWidth};
+                wC += ${dilationWidth}) {
+              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;
+
+              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||
+                  fract(dyC) > 0.0) {
+                continue;
+              }
+              int idyC = int(dyC);
+
+              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
+              int maxPosValue = ${lastIndex} -
+                  int(getMaxPos(batch, idyD, idyR, idyC, ch));
+
+              // Get the current value, check it against the value from the
+              // position matrix.
+              int curPosValue =
+                  wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +
+                  wR * ${effectiveFilterWidth} + wC;
+              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
+
+              dotProd += dyValue * mask;
+            }
+          }
+        }
+        setOutput(dotProd);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=max_pool_backprop_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/mulmat_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class MatMulPackedProgram {
+        constructor(
+          aShape,
+          outputShape,
+          transposeA = false,
+          transposeB = false,
+          addBias = false,
+          activation = null,
+          hasPreluActivation = false
+        ) {
+          this.variableNames = ["matrixA", "matrixB"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = outputShape;
+          const sharedDim = transposeA ? aShape[1] : aShape[2];
+          const sharedDimensionPacked = Math.ceil(sharedDim / 2);
+          const aSample = transposeA ? "i * 2, rc.y" : "rc.y, i * 2";
+          const bSample = transposeB ? "rc.z, i * 2" : "i * 2, rc.z";
+          const aSwizzle = transposeA ? ["a.xxyy", "a.zzww"] : ["a.xxzz", "a.yyww"];
+          const bSwizzle = transposeB ? ["b.xzxz", "b.ywyw"] : ["b.xyxy", "b.zwzw"];
+          let activationSnippet = "",
+            applyActivationSnippet = "";
+          if (activation) {
+            if (hasPreluActivation) {
+              activationSnippet = `vec4 activation(vec4 a) {
+          vec4 b = getPreluActivationWeightsAtOutCoords();
+          ${activation}
+        }`;
+            } else {
+              activationSnippet = `vec4 activation(vec4 x) {
+          ${activation}
+        }`;
+            }
+            applyActivationSnippet = `result = activation(result);`;
+          }
+          const addBiasSnippet = addBias ? "result += getBiasAtOutCoords();" : "";
+          if (addBias) {
+            this.variableNames.push("bias");
+          }
+          if (hasPreluActivation) {
+            this.variableNames.push("preluActivationWeights");
+          }
+          this.userCode = `
+      ${activationSnippet}
+
+      const float sharedDimension = ${sharedDimensionPacked}.0;
+
+      vec4 dot2x2ARowBCol(ivec3 rc) {
+        vec4 result = vec4(0);
+        for (int i = 0; i < ${sharedDimensionPacked}; i++) {
+          vec4 a = getMatrixA(rc.x, ${aSample});
+          vec4 b = getMatrixB(rc.x, ${bSample});
+
+          // These swizzled products need to be separately added.
+          // See: https://github.com/tensorflow/tfjs/issues/1735
+          result += (${aSwizzle[0]} * ${bSwizzle[0]});
+          result += (${aSwizzle[1]} * ${bSwizzle[1]});
+        }
+        return result;
+      }
+
+      void main() {
+        ivec3 rc = getOutputCoords();
+        vec4 result = dot2x2ARowBCol(rc);
+
+        ${addBiasSnippet}
+
+        ${applyActivationSnippet}
+
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=mulmat_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/multinomial_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class MultinomialProgram {
+        constructor(batchSize, numOutcomes, numSamples) {
+          this.variableNames = ["probs"];
+          this.outputShape = [batchSize, numSamples];
+          this.userCode = `
+      uniform float seed;
+
+      void main() {
+        ivec2 coords = getOutputCoords();
+        int batch = coords[0];
+
+        float r = random(seed);
+        float cdf = 0.0;
+
+        for (int i = 0; i < ${numOutcomes - 1}; i++) {
+          cdf += getProbs(batch, i);
+
+          if (r < cdf) {
+            setOutput(float(i));
+            return;
+          }
+        }
+
+        // If no other event happened, last event happened.
+        setOutput(float(${numOutcomes - 1}));
+      }
+    `;
+        }
+        getCustomSetupFunc(seed) {
+          return (gpgpu, webGLProgram) => {
+            if (this.seedLoc == null) {
+              this.seedLoc = gpgpu.getUniformLocation(webGLProgram, "seed");
+            }
+            gpgpu.gl.uniform1f(this.seedLoc, seed);
+          };
+        }
+      }
+      //# sourceMappingURL=multinomial_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/onehot_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class OneHotProgram {
+        constructor(numIndices, depth, onValue, offValue) {
+          this.variableNames = ["indices"];
+          this.outputShape = [numIndices, depth];
+          this.userCode = `
+      void main() {
+        ivec2 coords = getOutputCoords();
+        int index = round(getIndices(coords.x));
+        setOutput(mix(float(${offValue}), float(${onValue}),
+                      float(index == coords.y)));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=onehot_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/pack_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class pack_gpu_PackProgram {
+        constructor(outputShape) {
+          this.variableNames = ["A"];
+          this.packedInputs = false;
+          this.packedOutput = true;
+          // Only input / output 3D tensors.
+          this.outputShape = outputShape;
+          const rank = outputShape.length;
+          if (rank === 0) {
+            this.userCode = `
+        void main() {
+          setOutput(vec4(getA(), 0., 0., 0.));
+        }
+      `;
+          } else {
+            const channels = getChannels("rc", rank);
+            const dtype = getCoordsDataType(rank);
+            const outOfBoundsCondition = getOutOfBoundsCondition(rank, outputShape, channels);
+            const setup = getSetup(
+              rank,
+              outputShape[outputShape.length - 1],
+              outputShape[outputShape.length - 2],
+              channels
+            );
+            const output = getOutput(outputShape, channels);
+            this.userCode = `
+        void main() {
+          ${dtype} rc = getOutputCoords();
+
+          if(${outOfBoundsCondition}) {
+            setOutput(vec4(0));
+          } else {
+            ${setup}
+
+            setOutput(vec4(${output}));
+          }
+        }
+      `;
+          }
+        }
+      }
+      function getSourceCoordsArr(rank, dims) {
+        const coords = [];
+        for (let row = 0; row <= 1; row++) {
+          for (let col = 0; col <= 1; col++) {
+            let coord = `${row === 0 ? "r" : "rp1"}, ${col === 0 ? "c" : "cp1"}`;
+            for (let d = 2; d < rank; d++) {
+              coord = `${dims[dims.length - 1 - d]},` + coord;
+            }
+            coords.push(coord);
+          }
+        }
+        return coords;
+      }
+      function getOutOfBoundsCondition(rank, shape, dims) {
+        if (rank === 1) {
+          return `rc > ${shape[0]}`;
+        }
+        let cond = "";
+        for (let i = rank - 2; i < rank; i++) {
+          cond += `${dims[i]} >= ${shape[i]}`;
+          if (i < rank - 1) {
+            cond += "||";
+          }
+        }
+        return cond;
+      }
+      function getSetup(rank, cols, rows, dims) {
+        if (rank === 1) {
+          return "";
+        }
+        const innerDims = dims.slice(-2);
+        return `
+    int r = ${innerDims[0]};
+    int c = ${innerDims[1]};
+    int rp1 = r + 1;
+    int cp1 = c + 1;
+
+    bool cEdge = cp1 >= ${cols};
+    bool rEdge = rp1 >= ${rows};
+  `;
+      }
+      function getOutput(shape, dims) {
+        const rank = shape.length;
+        const sourceCoords = getSourceCoordsArr(rank, dims);
+        if (rank === 1) {
+          return `getA(rc),
+            rc + 1 >= ${shape[0]} ? 0. : getA(rc + 1),
+            0, 0`;
+        }
+        return `getA(${sourceCoords[0]}),
+          cEdge ? 0. : getA(${sourceCoords[1]}),
+          rEdge ? 0. : getA(${sourceCoords[2]}),
+          rEdge || cEdge ? 0. : getA(${sourceCoords[3]})`;
+      }
+      //# sourceMappingURL=pack_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/pad_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class pad_gpu_PadProgram {
+        constructor(xShape, paddings, constantValue) {
+          this.variableNames = ["x"];
+          this.outputShape = paddings.map(
+            (p, i) => p[0] /* beforePad */ + xShape[i] + p[1] /* afterPad */
+          );
+          const rank = xShape.length;
+          const type = getCoordsDataType(rank);
+          const start = paddings.map((p) => p[0]).join(",");
+          const end = paddings.map((p, i) => p[0] + xShape[i]).join(",");
+          const unpackedCoords = ["coords[0]", "coords[1]", "coords[2]", "coords[3]"].slice(
+            0,
+            rank
+          );
+          if (rank === 1) {
+            this.userCode = `
+        int start = ${start};
+        int end = ${end};
+
+        void main() {
+          int outC = getOutputCoords();
+          if (outC < start || outC >= end) {
+            setOutput(float(${constantValue}));
+          } else {
+            setOutput(getX(outC - start));
+          }
+        }
+      `;
+            return;
+          }
+          this.userCode = `
+      ${type} start = ${type}(${start});
+      ${type} end = ${type}(${end});
+
+      void main() {
+        ${type} outC = getOutputCoords();
+        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
+          setOutput(float(${constantValue}));
+        } else {
+          ${type} coords = outC - start;
+          setOutput(getX(${unpackedCoords}));
+        }
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=pad_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/pad_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class pad_packed_gpu_PadPackedProgram {
+        constructor(xShape, paddings, constantValue) {
+          this.variableNames = ["x"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = paddings.map(
+            (p, i) => p[0] /* beforePad */ + xShape[i] + p[1] /* afterPad */
+          );
+          const rank = xShape.length;
+          const dtype = getCoordsDataType(rank);
+          const start = paddings.map((p) => p[0]).join(",");
+          const end = paddings.map((p, i) => p[0] + xShape[i]).join(",");
+          const coords = getChannels("rc", rank);
+          const source = getChannels("source", rank);
+          const cLimit = `${coords[rank - 1]} < ${this.outputShape[rank - 1]}`;
+          const innerDims = rank === 1 ? "source" : `vec2(${source.slice(-2).join()})`;
+          const componentSetup = [
+            `${dtype} rc = outputLoc;`,
+            `${coords[rank - 1]} += 1;
+       if(${cLimit}) {
+      `,
+            rank === 1
+              ? ""
+              : `}
+       rc = outputLoc;
+       ${coords[rank - 2]} += 1;
+       if(${coords[rank - 2]} < ${this.outputShape[rank - 2]}) {`,
+            rank === 1
+              ? ""
+              : `  ${coords[rank - 1]} += 1;
+         if(${cLimit}) {`,
+          ];
+          const paddingArea =
+            rank === 1
+              ? "rc < start || rc >= end"
+              : "any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))";
+          let mainLoop = "";
+          for (let i = 0, j = rank === 1 ? 2 : 4; i < j; i++) {
+            mainLoop += `
+        ${componentSetup[i]}
+        if (${paddingArea}) {
+          result[${i}] = float(${constantValue});
+        } else {
+          ${dtype} source = rc - start;
+          result[${i}] = getChannel(getX(${source.join()}), ${innerDims});
+        }
+      `;
+          }
+          mainLoop += rank === 1 ? `} ` : `}}`;
+          this.userCode = `
+      const ${dtype} start = ${dtype}(${start});
+      const ${dtype} end = ${dtype}(${end});
+
+      void main() {
+        ${dtype} outputLoc = getOutputCoords();
+        vec4 result = vec4(0.);
+        ${mainLoop}
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=pad_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/pool_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class Pool2DProgram {
+        constructor(
+          convInfo,
+          poolType,
+          computePositions,
+          flattenPositions = false,
+          includeBatchInIndex = false
+        ) {
+          this.variableNames = ["x"];
+          if (poolType === "avg" && computePositions) {
+            throw new Error("Cannot compute positions for average pool.");
+          }
+          const filterWidth = convInfo.filterWidth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          this.outputShape = convInfo.outShape;
+          const isAvgPool = poolType === "avg";
+          const batchFlattenPositionStr = `((batch  * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`;
+          const flattenPositionStr = `(xR * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`;
+          let initializationValue = "0.0";
+          if (!isAvgPool) {
+            // WebGL on Firefox Linux can't compile 1/0 so we do 1/eps.
+            initializationValue = "-1.0 / 1e-20";
+          }
+          if (computePositions) {
+            const compareOp = ">=";
+            this.userCode = `
+        const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
+        const ivec2 pads = ivec2(${padTop}, ${padLeft});
+
+        void main() {
+          ivec4 coords = getOutputCoords();
+          int batch = coords[0];
+          int d = coords[3];
+
+          ivec2 xRCCorner = coords.yz * strides - pads;
+          int xRCorner = xRCCorner.x;
+          int xCCorner = xRCCorner.y;
+
+          // max/min x(?, ?, d) to get y(yR, yC, d).
+          // ? = to be determined
+          float minMaxValue = 0.0;
+          float minMaxValueFound = 0.0;
+          int minMaxPosition = 0;
+          float avgValue = 0.0;
+
+          for (int wR = 0; wR < ${effectiveFilterHeight};
+              wR += ${dilationHeight}) {
+            int xR = xRCorner + wR;
+
+            if (xR < 0 || xR >= ${convInfo.inHeight}) {
+              continue;
+            }
+
+            for (int wC = 0; wC < ${effectiveFilterWidth};
+                wC += ${dilationWidth}) {
+              int xC = xCCorner + wC;
+
+              if (xC < 0 || xC >= ${convInfo.inWidth}) {
+                continue;
+              }
+
+              float value = getX(batch, xR, xC, d);
+
+              // If a min / max value has already been found, use it. If not,
+              // use the current value.
+              float currMinMaxValue = mix(
+                  value, minMaxValue, minMaxValueFound);
+              if (value ${compareOp} currMinMaxValue) {
+                minMaxValue = value;
+                minMaxValueFound = 1.0;
+                minMaxPosition = ${
+                  flattenPositions
+                    ? includeBatchInIndex
+                      ? batchFlattenPositionStr
+                      : flattenPositionStr
+                    : `wR * ${effectiveFilterWidth} + wC`
+                };
+              }
+            }
+          }
+          setOutput(float(minMaxPosition));
+        }
+      `;
+            return;
+          }
+          const compareOp = "max";
+          let returnValue =
+            `${poolType}(${poolType}(${poolType}(` +
+            "minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
+          if (poolType === "avg") {
+            returnValue = `avgValue / count`;
+          }
+          const filterWidthNearestVec4 = Math.floor(filterWidth / 4) * 4;
+          const filterWidthVec4Remainder = filterWidth % 4;
+          const updateSnippet = `
+      if (${isAvgPool}) {
+        avgValue += dot(values, ones);
+      } else {
+        minMaxValue = ${compareOp}(values, minMaxValue);
+      }
+    `;
+          this.userCode = `
+      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
+      const ivec2 pads = ivec2(${padTop}, ${padLeft});
+      const float initializationValue = ${initializationValue};
+      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
+
+      float count = 0.0;
+
+      float getValue(int batch, int xR, int xC, int d) {
+        if (xC < 0 || xC >= ${convInfo.inWidth}) {
+          return initializationValue;
+        }
+        count += 1.0;
+        return getX(batch, xR, xC, d);
+      }
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int batch = coords[0];
+        int d = coords[3];
+
+        ivec2 xRCCorner = coords.yz * strides - pads;
+        int xRCorner = xRCCorner.x;
+        int xCCorner = xRCCorner.y;
+
+        // max/min x(?, ?, d) to get y(yR, yC, d).
+        // ? = to be determined
+        vec4 minMaxValue = vec4(${initializationValue});
+        float avgValue = 0.0;
+        count = 0.0;
+
+        for (int wR = 0; wR < ${effectiveFilterHeight};
+            wR += ${dilationHeight}) {
+          int xR = xRCorner + wR;
+
+          if (xR < 0 || xR >= ${convInfo.inHeight}) {
+            continue;
+          }
+
+          for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {
+            int xC = xCCorner + wC * ${dilationWidth};
+
+            vec4 values = vec4(
+              getValue(batch, xR, xC, d),
+              getValue(batch, xR, xC + ${dilationWidth}, d),
+              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),
+              getValue(batch, xR, xC + 3 * ${dilationWidth}, d)
+            );
+
+            ${updateSnippet}
+          }
+
+          int xC = xCCorner + ${filterWidthNearestVec4};
+          if (${filterWidthVec4Remainder === 1}) {
+            vec4 values = vec4(
+              getValue(batch, xR, xC, d),
+              initializationValue,
+              initializationValue,
+              initializationValue
+            );
+
+            ${updateSnippet}
+          } else if (${filterWidthVec4Remainder === 2}) {
+            vec4 values = vec4(
+              getValue(batch, xR, xC, d),
+              getValue(batch, xR, xC + ${dilationWidth}, d),
+              initializationValue,
+              initializationValue
+            );
+
+            ${updateSnippet}
+          } else if (${filterWidthVec4Remainder === 3}) {
+            vec4 values = vec4(
+              getValue(batch, xR, xC, d),
+              getValue(batch, xR, xC + ${dilationWidth}, d),
+              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),
+              initializationValue
+            );
+
+            ${updateSnippet}
+          }
+        }
+        setOutput(${returnValue});
+      }
+    `;
+        }
+      }
+      class Pool3DProgram {
+        constructor(
+          convInfo,
+          poolType,
+          computePositions,
+          flattenPositions = false,
+          includeBatchInIndex = false
+        ) {
+          this.variableNames = ["x"];
+          if (poolType === "avg" && computePositions) {
+            throw new Error("Cannot compute positions for average pool.");
+          }
+          const filterWidth = convInfo.filterWidth;
+          const strideDepth = convInfo.strideDepth;
+          const strideHeight = convInfo.strideHeight;
+          const strideWidth = convInfo.strideWidth;
+          const dilationDepth = convInfo.dilationDepth;
+          const dilationHeight = convInfo.dilationHeight;
+          const dilationWidth = convInfo.dilationWidth;
+          const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+          const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+          const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+          const padFront = convInfo.padInfo.front;
+          const padTop = convInfo.padInfo.top;
+          const padLeft = convInfo.padInfo.left;
+          this.outputShape = convInfo.outShape;
+          const isAvgPool = poolType === "avg";
+          let initializationValue = "0.0";
+          if (!isAvgPool) {
+            // WebGL on Firefox Linux can't compile 1/0 so we do 1/eps.
+            initializationValue = "-1.0 / 1e-20";
+          }
+          if (computePositions) {
+            const compareOp = ">=";
+            this.userCode = `
+        const ivec3 strides =
+            ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
+        const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
+
+        void main() {
+          ivec5 coords = getOutputCoords();
+          int batch = coords.x;
+          int ch = coords.u;
+
+          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
+          int xDCorner = xCorner.x;
+          int xRCorner = xCorner.y;
+          int xCCorner = xCorner.z;
+
+          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
+          // ? = to be determined
+          float minMaxValue = 0.0;
+          float minMaxValueFound = 0.0;
+          int minMaxPosition = 0;
+
+          for (int wD = 0; wD < ${effectiveFilterDepth};
+              wD += ${dilationDepth}) {
+            int xD = xDCorner + wD;
+
+            if (xD < 0 || xD >= ${convInfo.inDepth}) {
+              continue;
+            }
+
+            for (int wR = 0; wR < ${effectiveFilterHeight};
+                wR += ${dilationHeight}) {
+              int xR = xRCorner + wR;
+
+              if (xR < 0 || xR >= ${convInfo.inHeight}) {
+                continue;
+              }
+
+              for (int wC = 0; wC < ${effectiveFilterWidth};
+                  wC += ${dilationWidth}) {
+                int xC = xCCorner + wC;
+
+                if (xC < 0 || xC >= ${convInfo.inWidth}) {
+                  continue;
+                }
+
+                float value = getX(batch, xD, xR, xC, ch);
+
+                // If a min / max value has already been found, use it. If not,
+                // use the current value.
+                float currMinMaxValue = mix(
+                    value, minMaxValue, minMaxValueFound);
+                if (value ${compareOp} currMinMaxValue) {
+                  minMaxValue = value;
+                  minMaxValueFound = 1.0;
+                  minMaxPosition = ${
+                    flattenPositions
+                      ? includeBatchInIndex
+                        ? `(((batch * ${convInfo.inDepth} + xD) * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch`
+                        : `((xD * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch`
+                      : `wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +
+                      wR * ${effectiveFilterWidth} + wC`
+                  };
+                }
+              }
+            }
+          }
+          setOutput(float(minMaxPosition));
+        }
+      `;
+            return;
+          }
+          const compareOp = "max";
+          let returnValue =
+            `${poolType}(${poolType}(${poolType}(` +
+            "minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
+          if (poolType === "avg") {
+            returnValue = `avgValue / count`;
+          }
+          const filterWidthNearestVec4 = Math.floor(filterWidth / 4) * 4;
+          const filterWidthVec4Remainder = filterWidth % 4;
+          const updateSnippet = `
+      if (${isAvgPool}) {
+        avgValue += dot(values, ones);
+      } else {
+        minMaxValue = ${compareOp}(values, minMaxValue);
+      }
+    `;
+          this.userCode = `
+      const ivec3 strides =
+        ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
+      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
+      const float initializationValue = ${initializationValue};
+      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
+
+      float count = 0.0;
+
+      float getValue(int batch, int xD, int xR, int xC, int ch) {
+        if (xC < 0 || xC >= ${convInfo.inWidth}) {
+          return initializationValue;
+        }
+        count += 1.0;
+        return getX(batch, xD, xR, xC, ch);
+      }
+
+      void main() {
+        ivec5 coords = getOutputCoords();
+        int batch = coords.x;
+        int ch = coords.u;
+
+        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
+        int xDCorner = xCorner.x;
+        int xRCorner = xCorner.y;
+        int xCCorner = xCorner.z;
+
+        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
+        // ? = to be determined
+        vec4 minMaxValue = vec4(${initializationValue});
+        float avgValue = 0.0;
+        count = 0.0;
+
+        for (int wD = 0; wD < ${effectiveFilterDepth};
+            wD += ${dilationDepth}) {
+          int xD = xDCorner + wD;
+
+          if (xD < 0 || xD >= ${convInfo.inDepth}) {
+            continue;
+          }
+
+          for (int wR = 0; wR < ${effectiveFilterHeight};
+            wR += ${dilationHeight}) {
+            int xR = xRCorner + wR;
+
+            if (xR < 0 || xR >= ${convInfo.inHeight}) {
+              continue;
+            }
+
+            for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {
+              int xC = xCCorner + wC * ${dilationWidth};
+
+              vec4 values = vec4(
+                getValue(batch, xD, xR, xC, ch),
+                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),
+                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),
+                getValue(batch, xD, xR, xC + 3 * ${dilationWidth}, ch)
+              );
+
+              ${updateSnippet}
+            }
+
+            int xC = xCCorner + ${filterWidthNearestVec4};
+            if (${filterWidthVec4Remainder === 1}) {
+              vec4 values = vec4(
+                getValue(batch, xD, xR, xC, ch),
+                initializationValue,
+                initializationValue,
+                initializationValue
+              );
+
+              ${updateSnippet}
+            } else if (${filterWidthVec4Remainder === 2}) {
+              vec4 values = vec4(
+                getValue(batch, xD, xR, xC, ch),
+                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),
+                initializationValue,
+                initializationValue
+              );
+
+              ${updateSnippet}
+            } else if (${filterWidthVec4Remainder === 3}) {
+              vec4 values = vec4(
+                getValue(batch, xD, xR, xC, ch),
+                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),
+                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),
+                initializationValue
+              );
+
+              ${updateSnippet}
+            }
+          }
+          setOutput(${returnValue});
+        }
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=pool_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/reduce_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ReduceProgram {
+        constructor(reduceInfo, reduceType) {
+          this.variableNames = ["x"];
+          const windowSize = reduceInfo.windowSize;
+          const batchSize = reduceInfo.batchSize;
+          const inSize = reduceInfo.inSize;
+          const outSize = Math.ceil(inSize / windowSize);
+          this.outputShape = [batchSize, outSize];
+          let initializationValue = "0.0";
+          let compareOp = ``;
+          if (reduceType === "prod") {
+            initializationValue = "1.0";
+          } else if (reduceType === "min") {
+            // WebGL on Firefox Linux can't compile 1/0 so we do 1/eps.
+            initializationValue = "1.0 / 1e-20";
+            compareOp = `min`;
+          } else if (reduceType === "max") {
+            // WebGL on Firefox Linux can't compile 1/0 so we do 1/eps.
+            initializationValue = "-1.0 / 1e-20";
+            compareOp = `max`;
+          }
+          let returnValue =
+            `${reduceType}(${reduceType}(${reduceType}(` +
+            "minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
+          if (reduceType === "sum") {
+            returnValue = `sumValue`;
+          } else if (reduceType === "prod") {
+            returnValue = `prodValue`;
+          } else if (reduceType === "all") {
+            returnValue = `allValue`;
+          } else if (reduceType === "any") {
+            returnValue = `anyValue`;
+          }
+          const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;
+          const windowSizeVec4Remainder = windowSize % 4;
+          let updateSnippet = `
+      if (${reduceType === "sum"}) {
+        sumValue += dot(values, ones);
+      } else if (${reduceType === "prod"}) {
+        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
+        prodValue *= tmp[0] * tmp[1];
+      } else {
+        minMaxValue = ${compareOp}(values, minMaxValue);
+      }
+    `;
+          let vecType = `vec4`;
+          if (reduceType === "all") {
+            initializationValue = "1.0";
+            updateSnippet = `
+        bool reducedAllValue = all(values);
+        float floatedReducedAllValue = float(reducedAllValue);
+        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
+      `;
+            vecType = `bvec4`;
+          } else if (reduceType === "any") {
+            initializationValue = "0.0";
+            updateSnippet = `
+        bool reducedAnyValue = any(values);
+        float floatedReducedAnyValue = float(reducedAnyValue);
+        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
+      `;
+            vecType = `bvec4`;
+          }
+          let checkOutOfBounds = "";
+          if (inSize % windowSize > 0) {
+            checkOutOfBounds = `
+        if (inIdx < 0 || inIdx >= ${inSize}) {
+          return initializationValue;
+        }
+      `;
+          }
+          this.userCode = `
+      const float initializationValue = ${initializationValue};
+      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
+
+      float getValue(int batch, int inIdx) {
+        ${checkOutOfBounds}
+        return getX(batch, inIdx);
+      }
+
+      void main() {
+        ivec2 coords = getOutputCoords();
+        int batch = coords[0];
+        int outIdx = coords[1];
+        int inOffset = outIdx * ${windowSize};
+
+        vec4 minMaxValue = vec4(${initializationValue});
+        float prodValue = 1.0;
+        float sumValue = 0.0;
+        float allValue = 1.0;
+        float anyValue = 0.0;
+
+        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {
+          int inIdx = inOffset + i;
+          ${vecType} values = ${vecType}(
+            getValue(batch, inIdx),
+            getValue(batch, inIdx + 1),
+            getValue(batch, inIdx + 2),
+            getValue(batch, inIdx + 3)
+          );
+
+          ${updateSnippet}
+        }
+
+        int inIdx = inOffset + ${windowSizeNearestVec4};
+        if (${windowSizeVec4Remainder === 1}) {
+          ${vecType} values = ${vecType}(
+            getValue(batch, inIdx),
+            initializationValue,
+            initializationValue,
+            initializationValue
+          );
+
+          ${updateSnippet}
+        } else if (${windowSizeVec4Remainder === 2}) {
+          ${vecType} values = ${vecType}(
+            getValue(batch, inIdx),
+            getValue(batch, inIdx + 1),
+            initializationValue,
+            initializationValue
+          );
+
+          ${updateSnippet}
+        } else if (${windowSizeVec4Remainder === 3}) {
+          ${vecType} values = ${vecType}(
+            getValue(batch, inIdx),
+            getValue(batch, inIdx + 1),
+            getValue(batch, inIdx + 2),
+            initializationValue
+          );
+
+          ${updateSnippet}
+        }
+        setOutput(${returnValue});
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=reduce_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/reshape_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class reshape_packed_gpu_ReshapePackedProgram {
+        constructor(outputShape, inputShape) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = outputShape;
+          let mainLoop = ``;
+          for (let i = 0; i < 4; i++) {
+            let thisRC = `thisRC = rc;`;
+            if (i % 2 === 1) {
+              thisRC += `thisRC.z += 1;`;
+            }
+            if (i > 1) {
+              thisRC += `thisRC.y += 1;`;
+            }
+            mainLoop += `
+        ${thisRC}
+        ${i > 0 ? `if(thisRC.y < rows && thisRC.z < cols){` : ""}
+          int flatIndex = getFlatIndex(thisRC);
+
+          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
+          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
+
+          result[${i}] =
+            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
+        ${i > 0 ? "}" : ""}
+      `;
+          }
+          this.userCode = `
+      ${getReshapedInputCoords(inputShape)}
+      ${getFlatIndexFrom3D(outputShape)}
+
+      void main() {
+        ivec3 rc = getOutputCoords();
+
+        vec4 result = vec4(0.);
+
+        ivec3 thisRC;
+        int rows = ${outputShape[1]};
+        int cols = ${outputShape[2]};
+
+        ${mainLoop}
+
+        setOutput(result);
+      }
+    `;
+        }
+      }
+      function getReshapedInputCoords(shape) {
+        const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex(["r", "c", "d"], shape);
+        return `
+    ivec3 inputCoordsFromReshapedOutCoords(int index) {
+      ${coordsFromIndexSnippet}
+      return ivec3(r, c, d);
+    }
+  `;
+      }
+      //# sourceMappingURL=reshape_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_backprop_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ResizeBilinearBackpropProgram {
+        constructor(dy, x, alignCorners) {
+          this.variableNames = ["dy"];
+          this.outputShape = [];
+          this.outputShape = x.shape;
+          const [, xHeight, xWidth] = x.shape;
+          const [, yHeight, yWidth] = dy.shape;
+          // In the backwards pass, we want to find the pixels that were generated for
+          // each pixel in the input image the forward pass and add the corresponding
+          // coefficient from dy to the gradient (with some interpolation).
+          const effectiveXSize = [
+            alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,
+            alignCorners && yWidth > 1 ? xWidth - 1 : xWidth,
+          ];
+          const effectiveYSize = [
+            alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,
+            alignCorners && yWidth > 1 ? yWidth - 1 : yWidth,
+          ];
+          const heightScale = effectiveXSize[0] / effectiveYSize[0];
+          const widthScale = effectiveXSize[1] / effectiveYSize[1];
+          const invHeightScale = 1 / heightScale;
+          const invWidthScale = 1 / widthScale;
+          // This defines the size of the window of values around a particular
+          // index in dy that we want to search for contributions to dx.
+          const winHeight = Math.ceil(invHeightScale) * 2 + 2;
+          const winWidth = Math.ceil(invWidthScale) * 2 + 2;
+          this.userCode = `
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int d = coords[3];
+        int r = coords[1];
+        int c = coords[2];
+
+        float accumulator = 0.0;
+
+        const float heightScale = float(${heightScale});
+        const float widthScale = float(${widthScale});
+
+        const float invHeightScale = float(${invHeightScale});
+        const float invWidthScale = float(${invWidthScale});
+
+        const int winHeight = int(${winHeight});
+        const int winWidth = int(${winWidth});
+
+        // Compute bounds for where in dy we will look
+        float startRLerp = floor(float(r) * invHeightScale);
+        int startDyR = int(startRLerp - float(winHeight / 2));
+
+        float startCLerp = floor(float(c) * invWidthScale);
+        int startDyC = int(startCLerp - float(winWidth / 2));
+
+        // Loop over dy
+        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
+          int dyR = dyROffset + startDyR;
+
+          // Guard against the window exceeding the bounds of dy
+          if (dyR < 0 || dyR >= ${yHeight}) {
+            continue;
+          }
+
+          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
+            int dyC = dyCOffset + startDyC;
+
+            // Guard against the window exceeding the bounds of dy
+            if (dyC < 0 || dyC >= ${yWidth}) {
+              continue;
+            }
+
+            float dxR = float(dyR) * heightScale;
+            int topDxRIndex = int(floor(dxR));
+            int bottomDxRIndex = int(min(ceil(dxR), ${xHeight - 1}.0));
+            float dxRLerp = dxR - float(topDxRIndex);
+            float inverseDxRLerp = 1.0 - dxRLerp;
+
+            float dxC = float(dyC) * widthScale;
+            int leftDxCIndex = int(floor(dxC));
+            int rightDxCIndex = int(min(ceil(dxC), ${xWidth - 1}.0));
+            float dxCLerp = dxC - float(leftDxCIndex);
+            float inverseDxCLerp = 1.0 - dxCLerp;
+
+            if (r == topDxRIndex && c == leftDxCIndex) {
+              // topLeft
+              accumulator +=
+                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
+            }
+
+            if (r == topDxRIndex && c == rightDxCIndex) {
+              // topRight
+              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
+            }
+
+            if (r == bottomDxRIndex && c == leftDxCIndex) {
+              // bottomLeft
+              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
+            }
+
+            if (r == bottomDxRIndex && c == rightDxCIndex) {
+              // bottomRight
+              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
+            }
+          }
+        }
+        // End loop over dy
+
+        setOutput(accumulator);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=resize_bilinear_backprop_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ResizeBilinearProgram {
+        constructor(inputShape, newHeight, newWidth, alignCorners) {
+          this.variableNames = ["A"];
+          this.outputShape = [];
+          const [batch, oldHeight, oldWidth, depth] = inputShape;
+          this.outputShape = [batch, newHeight, newWidth, depth];
+          const effectiveInSize = [
+            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
+            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
+          ];
+          const effectiveOutSize = [
+            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
+            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
+          ];
+          this.userCode = `
+      const vec2 effectiveInputOverOutputRatioRC = vec2(
+          ${effectiveInSize[0] / effectiveOutSize[0]},
+          ${effectiveInSize[1] / effectiveOutSize[1]});
+      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int d = coords[3];
+        ivec2 yRC = coords.yz;
+
+        // Fractional source index.
+        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;
+
+        // Compute the four integer indices.
+        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);
+        ivec2 sourceCeilRC = ivec2(
+          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
+
+        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);
+        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);
+        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);
+        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);
+
+        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);
+
+        float top = topLeft + (topRight - topLeft) * fracRC.y;
+        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
+        float newValue = top + (bottom - top) * fracRC.x;
+
+        setOutput(newValue);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=resize_bilinear_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ResizeBilinearPackedProgram {
+        constructor(inputShape, newHeight, newWidth, alignCorners) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = [];
+          const [batch, oldHeight, oldWidth, depth] = inputShape;
+          this.outputShape = [batch, newHeight, newWidth, depth];
+          const effectiveInSize = [
+            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
+            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
+          ];
+          const effectiveOutSize = [
+            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
+            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
+          ];
+          this.userCode = `
+      const vec3 effectiveInputOverOutputRatioRC = vec3(
+          ${effectiveInSize[0] / effectiveOutSize[0]},
+          ${effectiveInSize[1] / effectiveOutSize[1]},
+          ${effectiveInSize[1] / effectiveOutSize[1]});
+      const vec3 inputShapeRC = vec3(${oldHeight}.0, ${oldWidth}.0,
+                                     ${oldWidth}.0);
+
+      float getAValue(int b, int r, int c, int d) {
+        return getChannel(getA(b, r, c, d), vec2(c, d));
+      }
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int d = coords[3];
+        // Calculate values for next column in yRC.z.
+        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
+
+        // Fractional source index.
+        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;
+
+        // Compute the four integer indices.
+        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);
+        ivec3 sourceCeilRC = ivec3(
+          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
+
+        // Should we calculate next column and row elements in 2x2 packed cell.
+        bool hasNextCol = d < ${depth - 1};
+        bool hasNextRow = coords.z < ${newWidth - 1};
+
+        // In parallel, construct four corners for all four components in
+        // packed 2x2 cell.
+        vec4 topLeft = vec4(
+          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
+          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
+                     : 0.0,
+          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
+                     : 0.0,
+          (hasNextRow && hasNextCol) ?
+            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);
+
+        vec4 bottomLeft = vec4(
+          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
+          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
+                     : 0.0,
+          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
+                     : 0.0,
+          (hasNextRow && hasNextCol) ?
+            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);
+
+        vec4 topRight = vec4(
+          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
+          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
+                     : 0.0,
+          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
+                     : 0.0,
+          (hasNextRow && hasNextCol) ?
+            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);
+
+        vec4 bottomRight = vec4(
+          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
+          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
+                     : 0.0,
+          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
+                     : 0.0,
+          (hasNextRow && hasNextCol) ?
+            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);
+
+        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);
+
+        vec4 top = mix(topLeft, topRight, fracRC.yyzz);
+        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
+        vec4 newValue = mix(top, bottom, fracRC.x);
+
+        setOutput(newValue);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=resize_bilinear_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_backprop_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ResizeNearestNeigborBackpropProgram {
+        constructor(dy, x, alignCorners) {
+          this.variableNames = ["dy"];
+          this.outputShape = [];
+          this.outputShape = x.shape;
+          const [, xHeight, xWidth] = x.shape;
+          const [, yHeight, yWidth] = dy.shape;
+          // In the backwards pass, we want to find the pixels that were generated for
+          // each pixel in the input image the forward pass and add the corresponding
+          // coefficient from dy to the gradient (with some interpolation).
+          const effectiveXSize = [
+            alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,
+            alignCorners && yWidth > 1 ? xWidth - 1 : xWidth,
+          ];
+          const effectiveYSize = [
+            alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,
+            alignCorners && yWidth > 1 ? yWidth - 1 : yWidth,
+          ];
+          const heightScale = effectiveXSize[0] / effectiveYSize[0];
+          const widthScale = effectiveXSize[1] / effectiveYSize[1];
+          const invHeightScale = 1 / heightScale;
+          const invWidthScale = 1 / widthScale;
+          // This defines the size of the window of values around a particular
+          // index in dy that we want to search for contributions to dx.
+          const winHeight = Math.ceil(invHeightScale) * 2 + 2;
+          const winWidth = Math.ceil(invWidthScale) * 2 + 2;
+          this.userCode = `
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int d = coords[3];
+        int r = coords[1];
+        int c = coords[2];
+
+        float accumulator = 0.0;
+
+        const float heightScale = float(${heightScale});
+        const float widthScale = float(${widthScale});
+
+        const float invHeightScale = float(${invHeightScale});
+        const float invWidthScale = float(${invWidthScale});
+
+        const int winHeight = int(${winHeight});
+        const int winWidth = int(${winWidth});
+
+        // Compute bounds for where in dy we will look
+        float startRLerp = floor(float(r) * invHeightScale);
+        int startDyR = int(floor(startRLerp - float(winHeight / 2)));
+
+        float startCLerp = floor(float(c) * invWidthScale);
+        int startDyC = int(floor(startCLerp - float(winWidth / 2)));
+
+        // Loop over dy
+        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
+          int dyR = dyROffset + startDyR;
+
+          // Guard against the window exceeding the bounds of dy
+          if (dyR < 0 || dyR >= ${yHeight}) {
+            continue;
+          }
+
+          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
+            int dyC = dyCOffset + startDyC;
+
+            // Guard against the window exceeding the bounds of dy
+            if (dyC < 0 || dyC >= ${yWidth}) {
+              continue;
+            }
+
+            float sourceFracRow =
+              float(${effectiveXSize[0]}) *
+                (float(dyR) / float(${effectiveYSize[0]}));
+
+            float sourceFracCol =
+                float(${effectiveXSize[1]}) *
+                  (float(dyC) / float(${effectiveYSize[1]}));
+
+            int sourceNearestRow = int(min(
+                float(int(${xHeight}) - 1),
+                ${alignCorners} ? float(round(sourceFracRow)) :
+                                  float(floor(sourceFracRow))));
+
+            int sourceNearestCol = int(min(
+                float(int(${xWidth}) - 1),
+                ${alignCorners} ? float(round(sourceFracCol)) :
+                                  float(floor(sourceFracCol))));
+
+            if (r == sourceNearestRow && c == sourceNearestCol) {
+              accumulator += getDy(b, dyR, dyC, d);
+            }
+          }
+        }
+        // End loop over dy
+
+        setOutput(accumulator);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=resize_nearest_neighbor_backprop_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class ResizeNearestNeighborProgram {
+        constructor(inputShape, newHeight, newWidth, alignCorners) {
+          this.variableNames = ["A"];
+          this.outputShape = [];
+          const [batch, oldHeight, oldWidth, depth] = inputShape;
+          this.outputShape = [batch, newHeight, newWidth, depth];
+          const effectiveInSize = [
+            alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,
+            alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth,
+          ];
+          const effectiveOutSize = [
+            alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,
+            alignCorners && newWidth > 1 ? newWidth - 1 : newWidth,
+          ];
+          // When align corners is false, we rounds the value with floor.
+          const roundBase = alignCorners ? "0.5" : "0.0";
+          this.userCode = `
+      const vec2 effectiveInputOverOutputRatioRC = vec2(
+          ${effectiveInSize[0] / effectiveOutSize[0]},
+          ${effectiveInSize[1] / effectiveOutSize[1]});
+      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);
+
+      void main() {
+        ivec4 coords = getOutputCoords();
+        int b = coords[0];
+        int d = coords[3];
+        ivec2 yRC = coords.yz;
+
+        // Fractional source index.
+        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;
+
+        // Compute the coordinators of nearest neighbor point.
+        ivec2 sourceNearestRC = ivec2(
+          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${roundBase})));
+
+        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
+
+        setOutput(newValue);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=resize_nearest_neighbor_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/reverse_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class reverse_gpu_ReverseProgram {
+        constructor(xShape, axis) {
+          this.variableNames = ["x"];
+          const rank = xShape.length;
+          if (rank > 4) {
+            throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);
+          }
+          this.outputShape = xShape;
+          if (rank === 1) {
+            this.userCode = `
+        void main() {
+          int coord = getOutputCoords();
+          setOutput(getX(${xShape[0]} - coord - 1));
+        }
+      `;
+            return;
+          }
+          const getInCoord = (i) => {
+            if (axis.indexOf(i) !== -1 && xShape[i] !== 1) {
+              return `${xShape[i]} - coords[${i}] - 1`;
+            }
+            return `coords[${i}]`;
+          };
+          const inCoords = xShape.map((_, i) => getInCoord(i)).join(",");
+          const type = getCoordsDataType(rank);
+          this.userCode = `
+      void main() {
+        ${type} coords = getOutputCoords();
+        setOutput(getX(${inCoords}));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=reverse_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/reverse_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class reverse_packed_gpu_ReversePackedProgram {
+        constructor(xShape, axis) {
+          this.variableNames = ["x"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          const rank = xShape.length;
+          if (rank > 4) {
+            throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);
+          }
+          this.outputShape = xShape;
+          const channels = getChannels("rc", rank);
+          const nextColumn = `${channels[rank - 1]} + 1 < ${this.outputShape[rank - 1]}`;
+          const nextRow = `${channels[rank - 2]} + 1 < ${this.outputShape[rank - 2]}`;
+          const type = getCoordsDataType(rank);
+          if (rank === 1) {
+            this.userCode = `
+        void main(){
+          int rc = getOutputCoords();
+          vec4 result = vec4(0.);
+          result.r = getChannel(getX(${xShape[0]} - rc - 1),
+            ${xShape[0]} - rc - 1);
+          if(${nextColumn}){
+              result.g = getChannel(getX(${xShape[0]} - (rc  + 1) - 1),
+                ${xShape[0]} - (rc  + 1) - 1);
+          }
+          setOutput(result);
+        }
+      `;
+          } else {
+            this.userCode = `
+        void main() {
+          ${type} rc = getOutputCoords();
+          vec4 result = vec4(0.);
+          result.r = ${getR(channels.slice())};
+          if(${nextColumn}){
+            result.g = ${getG(channels.slice())};
+          }
+          if(${nextRow}) {
+            result.b = ${getB(channels.slice())};
+            if(${nextColumn}) {
+              result.a = ${getA(channels.slice())};
+            }
+          }
+          setOutput(result);
+        }
+    `;
+          }
+          function getR(channels) {
+            return getChannel(channels);
+          }
+          function getG(channels) {
+            channels[rank - 1] = "(" + channels[rank - 1] + ` + 1)`;
+            return getChannel(channels);
+          }
+          function getB(channels) {
+            channels[rank - 2] = "(" + channels[rank - 2] + ` + 1)`;
+            return getChannel(channels);
+          }
+          function getA(channels) {
+            channels[rank - 1] = "(" + channels[rank - 1] + ` + 1)`;
+            channels[rank - 2] = "(" + channels[rank - 2] + ` + 1)`;
+            return getChannel(channels);
+          }
+          function getChannel(channels) {
+            const inCoordsArray = xShape.map((_, i) => getInCoord(i, channels));
+            const inCoords = inCoordsArray.join(",");
+            const innerDims = inCoordsArray.slice(-2).join(",");
+            return `getChannel(getX(${inCoords}), vec2(${innerDims}))`;
+          }
+          function getInCoord(i, channels1) {
+            if (axis.indexOf(i) !== -1 && xShape[i] !== 1) {
+              return `${xShape[i]} - ${channels1[i]} - 1`;
+            } else {
+              return `${channels1[i]}`;
+            }
+          }
+        }
+      }
+      //# sourceMappingURL=reverse_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/scatter_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class scatter_gpu_ScatterProgram {
+        constructor(
+          updateSize,
+          sliceDim,
+          indicesRank,
+          updatesRank,
+          strides,
+          shape,
+          summingDupeIndex = true
+        ) {
+          this.variableNames = ["updates", "indices", "defaultValue"];
+          this.outputShape = shape;
+          const stridesType = getCoordsDataType(strides.length);
+          const dtype = getCoordsDataType(shape.length);
+          let indicesString = "";
+          if (indicesRank === 1) {
+            indicesString = "i";
+          } else if (indicesRank === 2) {
+            indicesString = "i, j";
+          }
+          const indicesSnippet = `getIndices(${indicesString})`;
+          let updatesString = "";
+          if (updatesRank === 1) {
+            updatesString = "i";
+          } else if (updatesRank === 2) {
+            updatesString = "i, coords[1]";
+          }
+          const updatesSnippet = `getUpdates(${updatesString})`;
+          const strideString = sliceDim > 1 ? "strides[j]" : "strides";
+          this.userCode = `
+        ${stridesType} strides = ${stridesType}(${strides});
+
+        void main() {
+          ${dtype} coords = getOutputCoords();
+          float sum = 0.0;
+          bool found = false;
+          for (int i = 0; i < ${updateSize}; i++) {
+            int flattenedIndex = 0;
+            for (int j = 0; j < ${sliceDim}; j++) {
+              int index = round(${indicesSnippet});
+              flattenedIndex += index * ${strideString};
+            }
+            if (flattenedIndex == coords[0]) {
+              sum += ${updatesSnippet};
+              found = true;
+            }
+          }
+          setOutput(mix(getDefaultValue(), sum, float(found)));
+        }
+      `;
+        }
+      }
+      //# sourceMappingURL=scatter_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/segment_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      class SegmentOpProgram {
+        constructor(segOpInfo, segOpType) {
+          this.variableNames = ["x", "segmentIds"];
+          const windowSize = segOpInfo.windowSize;
+          const batchSize = segOpInfo.batchSize;
+          const inSize = segOpInfo.inSize;
+          const numSegments = segOpInfo.numSegments;
+          const outSize = numSegments * Math.ceil(inSize / windowSize);
+          this.outputShape = [batchSize, outSize];
+          const initializationValue = "0.0";
+          const returnValue = `sumValue`;
+          const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;
+          const windowSizeVec4Remainder = windowSize % 4;
+          const updateSnippet = `
+        sumValue += dot(values, segFilter);
+    `;
+          let checkValueOutOfBounds = "";
+          if (inSize % windowSize > 0) {
+            checkValueOutOfBounds = `
+        if (inIdx < 0 || inIdx >= ${inSize}) {
+          return initializationValue;
+        }
+      `;
+          }
+          let checkSegmentIdOutOfBounds = "";
+          if (inSize % windowSize > 0) {
+            checkSegmentIdOutOfBounds = `
+        if (inIdx < 0 || inIdx >= ${inSize}) {
+          return -1.0;
+        }
+      `;
+          }
+          this.userCode = `
+      const float initializationValue = ${initializationValue};
+
+      float getValue(int batch, int inIdx) {
+        ${checkValueOutOfBounds}
+        return getX(batch, inIdx);
+      }
+
+      float getSegmentIdAtIndex(int inIdx) {
+        ${checkSegmentIdOutOfBounds}
+        return getSegmentIds(inIdx);
+      }
+
+      void main() {
+        ivec2 coords = getOutputCoords();
+        int batch = coords[0];
+        int outIdx = coords[1];
+        int inOffset = int(floor(float(outIdx) / float(
+          ${numSegments})) * float(${windowSize}));
+        int currentSeg = int(mod(float(outIdx), float(${numSegments})));
+
+        float sumValue = 0.0;
+
+        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {
+          int inIdx = inOffset + i;
+          vec4 values = vec4(
+            getValue(batch, inIdx),
+            getValue(batch, inIdx + 1),
+            getValue(batch, inIdx + 2),
+            getValue(batch, inIdx + 3)
+          );
+
+          vec4 segFilter = vec4(
+            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
+            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
+            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
+            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
+          );
+
+          ${updateSnippet}
+        }
+
+        int inIdx = inOffset + ${windowSizeNearestVec4};
+        if (${windowSizeVec4Remainder === 1}) {
+          vec4 values = vec4(
+            getValue(batch, inIdx),
+            initializationValue,
+            initializationValue,
+            initializationValue
+          );
+
+          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));
+
+          vec4 segFilter = vec4(
+            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
+            0,
+            0,
+            0
+          );
+
+          ${updateSnippet}
+        } else if (${windowSizeVec4Remainder === 2}) {
+          vec4 values = vec4(
+            getValue(batch, inIdx),
+            getValue(batch, inIdx + 1),
+            initializationValue,
+            initializationValue
+          );
+
+          vec4 segFilter = vec4(
+            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
+            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
+              0,
+              0
+          );
+
+          ${updateSnippet}
+        } else if (${windowSizeVec4Remainder === 3}) {
+          vec4 values = vec4(
+            getValue(batch, inIdx),
+            getValue(batch, inIdx + 1),
+            getValue(batch, inIdx + 2),
+            initializationValue
+          );
+
+          vec4 segFilter = vec4(
+            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
+            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
+            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
+            0
+          );
+
+          ${updateSnippet}
+        }
+        setOutput(${returnValue});
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=segment_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/select_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class select_gpu_SelectProgram {
+        constructor(cRank, shape, rank) {
+          this.variableNames = ["c", "a", "b"];
+          this.outputShape = shape;
+          let cCoords;
+          let abCoords;
+          if (rank > 4) {
+            throw Error(`Where for rank ${rank} is not yet supported`);
+          }
+          if (rank === 1) {
+            abCoords = `resRC`;
+            cCoords = `resRC`;
+          } else {
+            const currentCoords = ["resRC.x", "resRC.y", "resRC.z", "resRC.w"];
+            const cCoordVars = [];
+            const abCoordVars = [];
+            for (let i = 0; i < shape.length; i++) {
+              abCoordVars.push(`${currentCoords[i]}`);
+              if (i < cRank) {
+                cCoordVars.push(`${currentCoords[i]}`);
+              }
+            }
+            cCoords = cCoordVars.join();
+            abCoords = abCoordVars.join();
+          }
+          const dtype = getCoordsDataType(rank);
+          this.userCode = `
+      void main() {
+        ${dtype} resRC = getOutputCoords();
+        float cVal = getC(${cCoords});
+        if (cVal >= 1.0) {
+          setOutput(getA(${abCoords}));
+        } else {
+          setOutput(getB(${abCoords}));
+        }
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=select_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/slice_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class slice_gpu_SliceProgram {
+        constructor(destSize) {
+          this.variableNames = ["source"];
+          this.outputShape = destSize;
+          this.rank = destSize.length;
+          const dtype = getCoordsDataType(this.rank);
+          const uniformPart = `uniform int start[${this.rank}];`;
+          const sourceCoords = slice_gpu_getCoords(this.rank);
+          let body;
+          const coordSum = destSize.map((_, i) => {
+            return `sourceLoc.${slice_gpu_coords[i]} = start[${i}] + coords.${slice_gpu_coords[i]};`;
+          });
+          body = `
+        ${dtype} sourceLoc;
+        ${dtype} coords = getOutputCoords();
+        ${coordSum.join("\n")}
+      `;
+          this.userCode = `
+      ${uniformPart}
+      void main() {
+        ${body}
+        setOutput(getSource(${sourceCoords}));
+      }
+    `;
+        }
+        getCustomSetupFunc(start) {
+          if (start.length !== this.rank) {
+            throw Error(
+              `The rank (${this.rank}) of the program must match the ` +
+                `length of start (${start.length})`
+            );
+          }
+          return (gpgpu, webGLProgram) => {
+            if (this.startLoc == null) {
+              this.startLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "start");
+              if (this.startLoc == null) {
+                // This means the compiler has optimized and realized it doesn't need
+                // the uniform.
+                return;
+              }
+            }
+            gpgpu.gl.uniform1iv(this.startLoc, start);
+          };
+        }
+      }
+      const slice_gpu_coords = ["x", "y", "z", "w", "u", "v"];
+      function slice_gpu_getCoords(rank) {
+        if (rank === 1) {
+          return "sourceLoc";
+        } else if (rank <= 6) {
+          return slice_gpu_coords
+            .slice(0, rank)
+            .map((x) => "sourceLoc." + x)
+            .join(",");
+        } else {
+          throw Error(`Slicing for rank ${rank} is not yet supported`);
+        }
+      }
+      //# sourceMappingURL=slice_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/slice_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class slice_packed_gpu_SlicePackedProgram {
+        constructor(destSize) {
+          this.variableNames = ["source"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = destSize;
+          this.rank = destSize.length;
+          const dtype = getCoordsDataType(this.rank);
+          const coords = getChannels("coords", this.rank);
+          const sourceLoc = getChannels("sourceLoc", this.rank);
+          const innerDims = this.rank === 1 ? "sourceLoc" : `vec2(${sourceLoc.slice(-2).join()})`;
+          const getChannel = `getChannel(getSource(${sourceLoc.join()}), ${innerDims})`;
+          const upperRow = `
+      result.x = ${getChannel};
+      if (++${coords[this.rank - 1]} < ${destSize[this.rank - 1]}) {
+        ++${sourceLoc[this.rank - 1]};
+        result.y = ${getChannel};
+        --${sourceLoc[this.rank - 1]};
+      }
+    `;
+          const lowerRow =
+            this.rank === 1
+              ? ""
+              : `
+      --${coords[this.rank - 1]};
+      if (++${coords[this.rank - 2]} < ${destSize[this.rank - 2]}) {
+        ++${sourceLoc[this.rank - 2]};
+        result.z = ${getChannel};
+        if (++${coords[this.rank - 1]} < ${destSize[this.rank - 1]}) {
+          ++${sourceLoc[this.rank - 1]};
+          result.w = ${getChannel};
+        }
+      }
+    `;
+          const sourceLocSetup =
+            this.rank <= 4
+              ? `sourceLoc = coords +
+            ${dtype}(${destSize.map((_, i) => `start[${i}]`).join()});`
+              : destSize.map((_, i) => `${sourceLoc[i]} = ${coords[i]} + start[${i}];`).join("\n");
+          this.userCode = `
+      uniform int start[${this.rank}];
+      void main() {
+        ${dtype} coords = getOutputCoords();
+        ${dtype} sourceLoc;
+        ${sourceLocSetup}
+        vec4 result = vec4(0.);
+        ${upperRow}
+        ${lowerRow}
+        setOutput(result);
+      }
+    `;
+        }
+        getCustomSetupFunc(start) {
+          if (start.length !== this.rank) {
+            throw Error(
+              `The rank (${this.rank}) of the program must match the ` +
+                `length of start (${start.length})`
+            );
+          }
+          return (gpgpu, webGLProgram) => {
+            if (this.startLoc == null) {
+              this.startLoc = gpgpu.getUniformLocationNoThrow(webGLProgram, "start");
+              if (this.startLoc == null) {
+                // This means the compiler has optimized and realized it doesn't need
+                // the uniform.
+                return;
+              }
+            }
+            gpgpu.gl.uniform1iv(this.startLoc, start);
+          };
+        }
+      }
+      //# sourceMappingURL=slice_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/strided_slice_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class strided_slice_gpu_StridedSliceProgram {
+        constructor(begin, strides, size) {
+          this.variableNames = ["x"];
+          this.outputShape = size;
+          const rank = size.length;
+          const inputDtype = getCoordsDataType(size.length);
+          const dtype = getCoordsDataType(size.length);
+          let newCoords = "";
+          if (rank === 1) {
+            newCoords = "coords * strides + begin";
+          } else {
+            let outputAxis = 0;
+            newCoords = size
+              .map((_, i) => {
+                outputAxis++;
+                return size.length === 1
+                  ? `coords * strides[${i}] + begin[${i}]`
+                  : `coords[${outputAxis - 1}] * strides[${i}] + begin[${i}]`;
+              })
+              .join(",");
+          }
+          this.userCode = `
+      ${inputDtype} begin = ${inputDtype}(${begin});
+      ${inputDtype} strides = ${inputDtype}(${strides});
+
+      void main() {
+        ${dtype} coords = getOutputCoords();
+        setOutput(getX(${newCoords}));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=strided_slice_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/texture_manager.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class texture_manager_TextureManager {
+        constructor(gpgpu) {
+          this.gpgpu = gpgpu;
+          this.numUsedTextures = 0;
+          this.numFreeTextures = 0;
+          this.freeTextures = {};
+          this.logEnabled = false;
+          this.usedTextures = {};
+        }
+        acquireTexture(shapeRC, usage, isPacked) {
+          const physicalTexType = getPhysicalFromLogicalTextureType(usage, isPacked);
+          const shapeKey = getKeyFromTextureShape(shapeRC, physicalTexType, isPacked);
+          if (!(shapeKey in this.freeTextures)) {
+            this.freeTextures[shapeKey] = [];
+          }
+          if (!(shapeKey in this.usedTextures)) {
+            this.usedTextures[shapeKey] = [];
+          }
+          if (this.freeTextures[shapeKey].length > 0) {
+            this.numFreeTextures--;
+            this.numUsedTextures++;
+            this.log();
+            const newTexture = this.freeTextures[shapeKey].shift();
+            this.usedTextures[shapeKey].push(newTexture);
+            return newTexture;
+          }
+          this.numUsedTextures++;
+          this.log();
+          let newTexture;
+          if (physicalTexType === PhysicalTextureType.PACKED_2X2_FLOAT32) {
+            newTexture = this.gpgpu.createPackedMatrixTexture(shapeRC[0], shapeRC[1]);
+          } else if (physicalTexType === PhysicalTextureType.PACKED_2X2_FLOAT16) {
+            newTexture = this.gpgpu.createFloat16PackedMatrixTexture(shapeRC[0], shapeRC[1]);
+          } else if (physicalTexType === PhysicalTextureType.UNPACKED_FLOAT32) {
+            newTexture = this.gpgpu.createFloat32MatrixTexture(shapeRC[0], shapeRC[1]);
+          } else if (physicalTexType === PhysicalTextureType.UNPACKED_FLOAT16) {
+            newTexture = this.gpgpu.createFloat16MatrixTexture(shapeRC[0], shapeRC[1]);
+          } else if (physicalTexType === PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE) {
+            newTexture = this.gpgpu.createUnsignedBytesMatrixTexture(shapeRC[0], shapeRC[1]);
+          }
+          this.usedTextures[shapeKey].push(newTexture);
+          return newTexture;
+        }
+        releaseTexture(texture, shape, logicalTexType, isPacked) {
+          if (this.freeTextures == null) {
+            // Already disposed.
+            return;
+          }
+          const physicalTexType = getPhysicalFromLogicalTextureType(logicalTexType, isPacked);
+          const shapeKey = getKeyFromTextureShape(shape, physicalTexType, isPacked);
+          if (!(shapeKey in this.freeTextures)) {
+            this.freeTextures[shapeKey] = [];
+          }
+          this.freeTextures[shapeKey].push(texture);
+          this.numFreeTextures++;
+          this.numUsedTextures--;
+          const texList = this.usedTextures[shapeKey];
+          const texIndex = texList.indexOf(texture);
+          if (texIndex < 0) {
+            throw new Error(
+              "Cannot release a texture that was never provided by this " + "texture manager"
+            );
+          }
+          texList.splice(texIndex, 1);
+          this.log();
+        }
+        log() {
+          if (!this.logEnabled) {
+            return;
+          }
+          const total = this.numFreeTextures + this.numUsedTextures;
+          console.log(
+            "Free/Used",
+            `${this.numFreeTextures} / ${this.numUsedTextures}`,
+            `(${total})`
+          );
+        }
+        getNumUsedTextures() {
+          return this.numUsedTextures;
+        }
+        getNumFreeTextures() {
+          return this.numFreeTextures;
+        }
+        dispose() {
+          if (this.freeTextures == null) {
+            // Already disposed.
+            return;
+          }
+          for (const texShape in this.freeTextures) {
+            this.freeTextures[texShape].forEach((tex) => {
+              this.gpgpu.deleteMatrixTexture(tex);
+            });
+          }
+          for (const texShape in this.usedTextures) {
+            this.usedTextures[texShape].forEach((tex) => {
+              this.gpgpu.deleteMatrixTexture(tex);
+            });
+          }
+          this.freeTextures = null;
+          this.usedTextures = null;
+          this.numUsedTextures = 0;
+          this.numFreeTextures = 0;
+        }
+      }
+      function getPhysicalTextureForRendering(isPacked) {
+        if (Object(dist["env"])().getBool("WEBGL_RENDER_FLOAT32_ENABLED")) {
+          if (isPacked) {
+            return PhysicalTextureType.PACKED_2X2_FLOAT32;
+          }
+          return PhysicalTextureType.UNPACKED_FLOAT32;
+        }
+        if (isPacked) {
+          return PhysicalTextureType.PACKED_2X2_FLOAT16;
+        }
+        return PhysicalTextureType.UNPACKED_FLOAT16;
+      }
+      function getPhysicalFromLogicalTextureType(logicalTexType, isPacked) {
+        if (logicalTexType === TextureUsage.UPLOAD) {
+          return PhysicalTextureType.PACKED_2X2_FLOAT32;
+        } else if (logicalTexType === TextureUsage.RENDER || logicalTexType == null) {
+          return getPhysicalTextureForRendering(isPacked);
+        } else if (
+          logicalTexType === TextureUsage.DOWNLOAD ||
+          logicalTexType === TextureUsage.PIXELS
+        ) {
+          return PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE;
+        }
+        throw new Error(`Unknown logical texture type ${logicalTexType}`);
+      }
+      function getKeyFromTextureShape(shapeRowsCol, physicalTexType, isPacked) {
+        return `${shapeRowsCol[0]}_${shapeRowsCol[1]}_${physicalTexType}_${isPacked}`;
+      }
+      //# sourceMappingURL=texture_manager.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/tile_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class tile_gpu_TileProgram {
+        constructor(aShape, reps) {
+          this.variableNames = ["A"];
+          const outputShape = new Array(aShape.length);
+          for (let i = 0; i < outputShape.length; i++) {
+            outputShape[i] = aShape[i] * reps[i];
+          }
+          this.outputShape = outputShape;
+          this.rank = outputShape.length;
+          const dtype = getCoordsDataType(this.rank);
+          const sourceCoords = tile_gpu_getSourceCoords(aShape);
+          this.userCode = `
+      void main() {
+        ${dtype} resRC = getOutputCoords();
+        setOutput(getA(${sourceCoords}));
+      }
+    `;
+        }
+      }
+      function tile_gpu_getSourceCoords(aShape) {
+        const rank = aShape.length;
+        if (rank > 5) {
+          throw Error(`Tile for rank ${rank} is not yet supported`);
+        }
+        if (rank === 1) {
+          return `imod(resRC, ${aShape[0]})`;
+        }
+        const currentCoords = ["resRC.x", "resRC.y", "resRC.z", "resRC.w", "resRC.u"];
+        const sourceCoords = [];
+        for (let i = 0; i < aShape.length; i++) {
+          sourceCoords.push(`imod(${currentCoords[i]}, ${aShape[i]})`);
+        }
+        return sourceCoords.join();
+      }
+      //# sourceMappingURL=tile_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/unaryop_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class UnaryOpProgram {
+        constructor(aShape, opSnippet) {
+          this.variableNames = ["A"];
+          this.outputShape = aShape;
+          this.userCode = `
+      float unaryOperation(float x) {
+        ${opSnippet}
+      }
+
+      void main() {
+        float x = getAAtOutCoords();
+        float y = unaryOperation(x);
+
+        setOutput(y);
+      }
+    `;
+        }
+      }
+      const unaryop_gpu_CHECK_NAN_SNIPPET = `if (isnan(x)) return x;`;
+      const LINEAR = `return x;`;
+      const ABS = `return abs(x);`;
+      const RELU =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  return (x < 0.0) ? 0.0 : x;
+`;
+      const RELU6 =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  return (x < 0.0) ? 0.0 : min(6.0, x);
+`;
+      const ELU = `return (x >= 0.0) ? x : (exp(x) - 1.0);`;
+      const SELU = `
+  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
+  // see: https://arxiv.org/abs/1706.02515
+  float scaleAlpha = ${dist["backend_util"].SELU_SCALEALPHA};
+  float scale = ${dist["backend_util"].SELU_SCALE};
+  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
+`;
+      function STEP(alpha = 0.0) {
+        return (
+          unaryop_gpu_CHECK_NAN_SNIPPET +
+          `
+    return x > 0.0 ? 1.0 : float(${alpha});
+  `
+        );
+      }
+      const NEG = `return -x;`;
+      const CEIL = `return ceil(x);`;
+      const FLOOR = `return floor(x);`;
+      const SIGN = `
+  if (isnan(x)) { return 0.0; }
+  return sign(x);
+`;
+      const IS_NAN = `return float(isnan(x));`;
+      const IS_INF = `return float(isinf(x));`;
+      const IS_FINITE = `return float(!isnan(x) && !isinf(x));`;
+      const ROUND = `
+  // OpenGL ES does not support round function.
+  // The algorithm is based on banker's rounding.
+  float base = floor(x);
+  if ((x - base) < 0.5) {
+    return floor(x);
+  } else if ((x - base) > 0.5) {
+    return ceil(x);
+  } else {
+    if (mod(base, 2.0) == 0.0) {
+      return base;
+    } else {
+      return base + 1.0;
+    }
+  }
+`;
+      const EXP = `return exp(x);`;
+      const EXPM1 = `return exp(x) - 1.0;`;
+      const LOG = `if (x < 0.0) return NAN;
+  return log(x);`;
+      const LOG1P = `return log(1.0 + x);`;
+      const SQRT = `return sqrt(x);`;
+      const RSQRT = `return inversesqrt(x);`;
+      const SIGMOID = `return 1.0 / (1.0 + exp(-1.0 * x));`;
+      /**
+       * mirrors the implementation of tf.nn.softplus: https://goo.gl/vkcvwX
+       *
+       * epsilon is the difference between 1.0 and the next representable
+       * float. For a single precision 32 bit float this should be 2^-23, see:
+       * https://math.byu.edu/~schow/work/IEEEFloatingPoint.htm
+       *
+       * too_large = (x > -threshold) is value above which exp(x) may overflow
+       * but softplus(x) == x is within machine epsilon
+       *
+       * too_small = (x < threshold) is value below which exp(x) may underflow,
+       * but softplus(x) == exp(x) is within machine epsilon.
+       */
+      const SOFTPLUS = `
+  float epsilon = 1.1920928955078125e-7;
+  float threshold = log(epsilon) + 2.0;
+
+  bool too_large = x > -threshold;
+  bool too_small = x < threshold;
+
+  float result;
+  float exp_x = exp(x);
+
+  if (too_large){
+    result = x;
+  }
+  else if (too_small){
+    result = exp_x;
+  }
+  else{
+    result = log(exp_x + 1.0);
+  }
+  return result;
+`;
+      const SIN =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  return sin(x);
+`;
+      const COS =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  return cos(x);
+`;
+      const TAN = `return tan(x);`;
+      const ASIN =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  if (abs(x) > 1.) {
+    return NAN;
+  }
+  return asin(x);
+`;
+      const ACOS =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  if (abs(x) > 1.) {
+    return NAN;
+  }
+  return acos(x);
+`;
+      const ATAN =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  return atan(x);
+`;
+      const SINH = `
+  float e2x = exp(x);
+  return (e2x - 1.0 / e2x) / 2.0;
+`;
+      const COSH = `
+  float e2x = exp(-x);
+  return (e2x + 1.0 / e2x) / 2.0;
+`;
+      const TANH = `
+  float e2x = exp(-2.0 * abs(x));
+  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
+`;
+      const ASINH = unaryop_gpu_CHECK_NAN_SNIPPET + `return log(x + sqrt(x * x + 1.0));`;
+      const ACOSH =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  if (x < 1.0) return NAN;
+  return log(x + sqrt(x * x - 1.0));`;
+      const ATANH =
+        unaryop_gpu_CHECK_NAN_SNIPPET +
+        `
+  if ((x < -1.0) || (x > 1.0)) return NAN;
+  return (log(1.0 + x) - log(1.0 - x)) / 2.0;`;
+      const ERF = `
+  // Error function is calculated approximately with elementary function.
+  // See "Handbook of Mathematical Functions with Formulas,
+  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
+  float p = ${dist["backend_util"].ERF_P};
+  float a1 = ${dist["backend_util"].ERF_A1};
+  float a2 = ${dist["backend_util"].ERF_A2};
+  float a3 = ${dist["backend_util"].ERF_A3};
+  float a4 = ${dist["backend_util"].ERF_A4};
+  float a5 = ${dist["backend_util"].ERF_A5};
+
+  float sign = sign(x);
+  x = abs(x);
+  float t = 1.0 / (1.0 + p * x);
+  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
+`;
+      const SQUARE = `return x * x;`;
+      const RECIPROCAL = `return 1.0 / x;`;
+      const LOGICAL_NOT = `return float(!(x >= 1.0));`;
+      const TO_INT = `return float(int(x));`;
+      const CLONE = "return x;";
+      //# sourceMappingURL=unaryop_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/unaryop_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      const unaryop_packed_gpu_LINEAR = `return x;`;
+      const unaryop_packed_gpu_LOG = `
+  vec4 result = log(x);
+  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
+  result.r = isNaN.r == 1.0 ? NAN : result.r;
+  result.g = isNaN.g == 1.0 ? NAN : result.g;
+  result.b = isNaN.b == 1.0 ? NAN : result.b;
+  result.a = isNaN.a == 1.0 ? NAN : result.a;
+
+  return result;
+`;
+      const unaryop_packed_gpu_RELU = `
+  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
+  bvec4 isNaN = isnan(x);
+
+  result.r = isNaN.r ? x.r : result.r;
+  result.g = isNaN.g ? x.g : result.g;
+  result.b = isNaN.b ? x.b : result.b;
+  result.a = isNaN.a ? x.a : result.a;
+
+  return result;
+`;
+      const unaryop_packed_gpu_RELU6 = `
+  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
+  bvec4 isNaN = isnan(x);
+
+  result.r = isNaN.r ? x.r : result.r;
+  result.g = isNaN.g ? x.g : result.g;
+  result.b = isNaN.b ? x.b : result.b;
+  result.a = isNaN.a ? x.a : result.a;
+
+  return result;
+`;
+      const unaryop_packed_gpu_ELU = `
+  vec4 result;
+
+  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
+  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
+  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
+  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
+
+  return result;
+`;
+      class UnaryOpPackedProgram {
+        constructor(aShape, opSnippet) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          this.outputShape = aShape;
+          this.userCode = `
+      vec4 unaryOperation(vec4 x) {
+        ${opSnippet}
+      }
+
+      void main() {
+        vec4 x = getAAtOutCoords();
+        vec4 y = unaryOperation(x);
+
+        setOutput(y);
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=unaryop_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/unpack_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class unpack_gpu_UnpackProgram {
+        constructor(outputShape) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = false;
+          this.outputShape = outputShape;
+          const rank = outputShape.length;
+          const channels = getChannels("rc", rank);
+          const dtype = getCoordsDataType(rank);
+          const sourceCoords = getSourceCoords(rank, channels);
+          const innerDims = channels.slice(-2);
+          const coords = rank <= 1 ? "rc" : `vec2(${innerDims.join(",")})`;
+          this.userCode = `
+      void main() {
+        ${dtype} rc = getOutputCoords();
+        vec4 packedInput = getA(${sourceCoords});
+
+        setOutput(getChannel(packedInput, ${coords}));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=unpack_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/backend_webgl.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // Import webgl flags.
+
+      const { segment_util } = dist["backend_util"];
+      const split = dist["kernel_impls"].split;
+      const tile = dist["kernel_impls"].tile;
+      const topkImpl = dist["kernel_impls"].topkImpl;
+      const whereImpl = dist["kernel_impls"].whereImpl;
+
+      const EPSILON_FLOAT32 = 1e-7;
+      const EPSILON_FLOAT16 = 1e-4;
+      const binaryCaches = {};
+      function getBinaryCache(webGLVersion) {
+        if (webGLVersion in binaryCaches) {
+          return binaryCaches[webGLVersion];
+        }
+        binaryCaches[webGLVersion] = {};
+        return binaryCaches[webGLVersion];
+      }
+      function mapActivationToShaderProgram(activation, packed = false) {
+        if (activation === "linear") {
+          if (packed) {
+            return unaryop_packed_gpu_LINEAR;
+          }
+          return LINEAR;
+        } else if (activation === "relu") {
+          if (packed) {
+            return unaryop_packed_gpu_RELU;
+          }
+          return RELU;
+        } else if (activation === "elu") {
+          if (packed) {
+            return unaryop_packed_gpu_ELU;
+          }
+          return ELU;
+        } else if (activation === "relu6") {
+          if (packed) {
+            return unaryop_packed_gpu_RELU6;
+          }
+          return RELU6;
+        } else if (activation === "prelu") {
+          if (packed) {
+            return binaryop_packed_gpu_PRELU;
+          }
+          return PRELU;
+        }
+        throw new Error(`Activation ${activation} has not been implemented for the WebGL backend.`);
+      }
+      // Empirically determined constant used to determine size threshold for handing
+      // off execution to the CPU.
+      const CPU_HANDOFF_SIZE_THRESHOLD = 128;
+      // Empirically determined constant used to decide the number of MB on GPU
+      // before we warn about high memory use. The MB are this constant * screen area
+      // * dpi / 1024 / 1024.
+      const BEFORE_PAGING_CONSTANT = 600;
+      function numMBBeforeWarning() {
+        if (Object(dist["env"])().global.screen == null) {
+          return 1024; // 1 GB.
+        }
+        return (
+          (Object(dist["env"])().global.screen.height *
+            Object(dist["env"])().global.screen.width *
+            window.devicePixelRatio *
+            BEFORE_PAGING_CONSTANT) /
+          1024 /
+          1024
+        );
+      }
+      // Empirically determined minimal shared dimension in matmul before we forward
+      // to a.mul(b).sum() in order to take advantage of GPU parallelism. See
+      // https://github.com/tensorflow/tfjs-core/pull/1379 for benchmarks.
+      const MATMUL_SHARED_DIM_THRESHOLD = 1000;
+      class backend_webgl_MathBackendWebGL extends dist["KernelBackend"] {
+        constructor(gpgpu) {
+          super();
+          // Maps data ids that have a pending read operation, to list of subscribers.
+          this.pendingRead = new WeakMap();
+          // List of data ids that are scheduled for disposal, but are waiting on a
+          // pending read operation.
+          this.pendingDisposal = new WeakSet();
+          // Used to count the number of 'shallow' sliced tensors that point to the
+          // same data id.
+          this.dataRefCount = new WeakMap();
+          this.numBytesInGPU = 0;
+          // Accumulated time spent (including blocking) in uploading data to webgl.
+          this.uploadWaitMs = 0;
+          // Accumulated time spent (including blocking in downloading data from webgl.
+          this.downloadWaitMs = 0;
+          this.warnedAboutMemory = false;
+          this.pendingDeletes = 0;
+          this.disposed = false;
+          if (!Object(dist["env"])().getBool("HAS_WEBGL")) {
+            throw new Error("WebGL is not supported on this device");
+          }
+          if (gpgpu == null) {
+            const gl = getWebGLContext(Object(dist["env"])().getNumber("WEBGL_VERSION"));
+            this.binaryCache = getBinaryCache(Object(dist["env"])().getNumber("WEBGL_VERSION"));
+            this.gpgpu = new gpgpu_context_GPGPUContext(gl);
+            this.canvas = gl.canvas;
+            this.gpgpuCreatedLocally = true;
+          } else {
+            this.gpgpu = gpgpu;
+            this.binaryCache = {};
+            this.gpgpuCreatedLocally = false;
+            this.canvas = gpgpu.gl.canvas;
+          }
+          this.textureManager = new texture_manager_TextureManager(this.gpgpu);
+          this.numMBBeforeWarning = numMBBeforeWarning();
+          this.texData = new dist["DataStorage"](this, Object(dist["engine"])());
+        }
+        numDataIds() {
+          return (
+            this.texData.numDataIds() +
+            (this.cpuBackend ? this.cpuBackend.numDataIds() : 0) -
+            this.pendingDeletes
+          );
+        }
+        write(values, shape, dtype) {
+          if (Object(dist["env"])().getBool("DEBUG")) {
+            this.checkNumericalProblems(values);
+          }
+          if (dtype === "complex64" && values != null) {
+            throw new Error(
+              `Cannot write to a complex64 dtype. ` + `Please use tf.complex(real, imag).`
+            );
+          }
+          const dataId = {};
+          this.texData.set(dataId, { shape, dtype, values, usage: TextureUsage.UPLOAD });
+          return dataId;
+        }
+        move(dataId, values, shape, dtype) {
+          if (Object(dist["env"])().getBool("DEBUG")) {
+            this.checkNumericalProblems(values);
+          }
+          if (dtype === "complex64") {
+            throw new Error(
+              `Cannot write to a complex64 dtype. ` + `Please use tf.complex(real, imag).`
+            );
+          }
+          this.texData.set(dataId, { shape, dtype, values, usage: TextureUsage.UPLOAD });
+        }
+        readSync(dataId) {
+          const texData = this.texData.get(dataId);
+          const { values, dtype, complexTensors, slice, shape, isPacked } = texData;
+          if (slice != null) {
+            let program;
+            if (isPacked) {
+              program = new UnaryOpPackedProgram(shape, CLONE);
+            } else {
+              program = new UnaryOpProgram(shape, CLONE);
+            }
+            const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);
+            const data = this.readSync(res.dataId);
+            this.disposeData(res.dataId);
+            return data;
+          }
+          if (values != null) {
+            return this.convertAndCacheOnCPU(dataId);
+          }
+          if (dtype === "string") {
+            return values;
+          }
+          const shouldTimeProgram = this.activeTimers != null;
+          let start;
+          if (shouldTimeProgram) {
+            start = dist["util"].now();
+          }
+          let result;
+          if (dtype === "complex64") {
+            const realValues = complexTensors.real.dataSync();
+            const imagValues = complexTensors.imag.dataSync();
+            result = dist["backend_util"].mergeRealAndImagArrays(realValues, imagValues);
+          } else {
+            result = this.getValuesFromTexture(dataId);
+          }
+          if (shouldTimeProgram) {
+            this.downloadWaitMs += dist["util"].now() - start;
+          }
+          return this.convertAndCacheOnCPU(dataId, result);
+        }
+        async read(dataId) {
+          if (this.pendingRead.has(dataId)) {
+            const subscribers = this.pendingRead.get(dataId);
+            return new Promise((resolve) => subscribers.push(resolve));
+          }
+          const texData = this.texData.get(dataId);
+          const { values, shape, slice, dtype, complexTensors, isPacked } = texData;
+          if (slice != null) {
+            let program;
+            if (isPacked) {
+              program = new UnaryOpPackedProgram(shape, CLONE);
+            } else {
+              program = new UnaryOpProgram(shape, CLONE);
+            }
+            const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);
+            const data = this.read(res.dataId);
+            this.disposeData(res.dataId);
+            return data;
+          }
+          if (values != null) {
+            return this.convertAndCacheOnCPU(dataId);
+          }
+          if (
+            !Object(dist["env"])().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED") &&
+            Object(dist["env"])().getNumber("WEBGL_VERSION") === 2
+          ) {
+            throw new Error(
+              `tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and ` +
+                `WEBGL_VERSION=2 not yet supported.`
+            );
+          }
+          let buffer = null;
+          let tmpDownloadTarget;
+          if (dtype !== "complex64" && Object(dist["env"])().get("WEBGL_BUFFER_SUPPORTED")) {
+            // Possibly copy the texture into a buffer before inserting a fence.
+            tmpDownloadTarget = this.decode(dataId);
+            const tmpData = this.texData.get(tmpDownloadTarget.dataId);
+            buffer = this.gpgpu.createBufferFromTexture(
+              tmpData.texture,
+              ...getDenseTexShape(shape)
+            );
+          }
+          this.pendingRead.set(dataId, []);
+          if (dtype !== "complex64") {
+            // Create a fence and wait for it to resolve.
+            await this.gpgpu.createAndWaitForFence();
+          }
+          // Download the values from the GPU.
+          let vals;
+          if (dtype === "complex64") {
+            const ps = await Promise.all([complexTensors.real.data(), complexTensors.imag.data()]);
+            const realValues = ps[0];
+            const imagValues = ps[1];
+            vals = dist["backend_util"].mergeRealAndImagArrays(realValues, imagValues);
+          } else if (buffer == null) {
+            vals = this.getValuesFromTexture(dataId);
+          } else {
+            const size = dist["util"].sizeFromShape(shape);
+            vals = this.gpgpu.downloadFloat32MatrixFromBuffer(buffer, size);
+          }
+          if (tmpDownloadTarget != null) {
+            this.disposeData(tmpDownloadTarget.dataId);
+          }
+          const dTypeVals = this.convertAndCacheOnCPU(dataId, vals);
+          const subscribers = this.pendingRead.get(dataId);
+          this.pendingRead.delete(dataId);
+          // Notify all pending reads.
+          subscribers.forEach((resolve) => resolve(dTypeVals));
+          if (this.pendingDisposal.has(dataId)) {
+            this.pendingDisposal.delete(dataId);
+            this.disposeData(dataId);
+            this.pendingDeletes--;
+          }
+          return dTypeVals;
+        }
+        checkNumericalProblems(values) {
+          if (values == null) {
+            return;
+          }
+          for (let i = 0; i < values.length; i++) {
+            const num = values[i];
+            if (!canBeRepresented(num)) {
+              if (Object(dist["env"])().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")) {
+                throw Error(
+                  `The value ${num} cannot be represented with your ` +
+                    `current settings. Consider enabling float32 rendering: ` +
+                    `'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`
+                );
+              }
+              throw Error(`The value ${num} cannot be represented on this device.`);
+            }
+          }
+        }
+        getValuesFromTexture(dataId) {
+          const { shape, dtype, isPacked } = this.texData.get(dataId);
+          const size = dist["util"].sizeFromShape(shape);
+          if (Object(dist["env"])().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")) {
+            const tmpTarget = this.decode(dataId);
+            const tmpData = this.texData.get(tmpTarget.dataId);
+            const vals = this.gpgpu
+              .downloadMatrixFromPackedTexture(tmpData.texture, ...getDenseTexShape(shape))
+              .subarray(0, size);
+            this.disposeData(tmpTarget.dataId);
+            return vals;
+          }
+          const shouldUsePackedProgram =
+            Object(dist["env"])().getBool("WEBGL_PACK") && isPacked === true;
+          const outputShape = shouldUsePackedProgram ? getShapeAs3D(shape) : shape;
+          const program = shouldUsePackedProgram
+            ? new encode_float_packed_gpu_EncodeFloatPackedProgram(outputShape)
+            : new encode_float_gpu_EncodeFloatProgram(outputShape);
+          const output = this.runWebGLProgram(
+            program,
+            [{ shape: outputShape, dtype, dataId }],
+            "float32"
+          );
+          const tmpData = this.texData.get(output.dataId);
+          const vals = this.gpgpu
+            .downloadByteEncodedFloatMatrixFromOutputTexture(
+              tmpData.texture,
+              tmpData.texShape[0],
+              tmpData.texShape[1]
+            )
+            .subarray(0, size);
+          this.disposeData(output.dataId);
+          return vals;
+        }
+        async time(f) {
+          const oldActiveTimers = this.activeTimers;
+          const newActiveTimers = [];
+          let outerMostTime = false;
+          if (this.programTimersStack == null) {
+            this.programTimersStack = newActiveTimers;
+            outerMostTime = true;
+          } else {
+            this.activeTimers.push(newActiveTimers);
+          }
+          this.activeTimers = newActiveTimers;
+          f();
+          // needing to split these up because util.flatten only accepts certain types
+          const flattenedActiveTimerQueries = dist["util"]
+            .flatten(this.activeTimers.map((d) => d.query))
+            .filter((d) => d != null);
+          const flattenedActiveTimerNames = dist["util"]
+            .flatten(this.activeTimers.map((d) => d.name))
+            .filter((d) => d != null);
+          this.activeTimers = oldActiveTimers;
+          if (outerMostTime) {
+            this.programTimersStack = null;
+          }
+          const res = {
+            uploadWaitMs: this.uploadWaitMs,
+            downloadWaitMs: this.downloadWaitMs,
+            kernelMs: null,
+            wallMs: null, // will be filled by the engine
+          };
+          if (
+            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0
+          ) {
+            const kernelMs = await Promise.all(flattenedActiveTimerQueries);
+            res["kernelMs"] = dist["util"].sum(kernelMs);
+            res["getExtraProfileInfo"] = () =>
+              kernelMs
+                .map((d, i) => ({ name: flattenedActiveTimerNames[i], ms: d }))
+                .map((d) => `${d.name}: ${d.ms}`)
+                .join(", ");
+          } else {
+            res["kernelMs"] = {
+              error: "WebGL query timers are not supported in this environment.",
+            };
+          }
+          this.uploadWaitMs = 0;
+          this.downloadWaitMs = 0;
+          return res;
+        }
+        memory() {
+          return { unreliable: false, numBytesInGPU: this.numBytesInGPU };
+        }
+        startTimer() {
+          if (
+            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0
+          ) {
+            return this.gpgpu.beginQuery();
+          }
+          return { startMs: dist["util"].now(), endMs: null };
+        }
+        endTimer(query) {
+          if (
+            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0
+          ) {
+            this.gpgpu.endQuery();
+            return query;
+          }
+          query.endMs = dist["util"].now();
+          return query;
+        }
+        async getQueryTime(query) {
+          if (
+            Object(dist["env"])().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0
+          ) {
+            return this.gpgpu.waitForQueryAndGetTime(query);
+          }
+          const timerQuery = query;
+          return timerQuery.endMs - timerQuery.startMs;
+        }
+        disposeData(dataId) {
+          if (this.pendingDisposal.has(dataId)) {
+            return;
+          }
+          if (this.pendingRead.has(dataId)) {
+            this.pendingDisposal.add(dataId);
+            this.pendingDeletes++;
+            return;
+          }
+          // No-op if already disposed.
+          if (!this.texData.has(dataId)) {
+            return;
+          }
+          this.releaseGPUData(dataId);
+          const { complexTensors } = this.texData.get(dataId);
+          if (complexTensors != null) {
+            complexTensors.real.dispose();
+            complexTensors.imag.dispose();
+          }
+          this.texData.delete(dataId);
+        }
+        releaseGPUData(dataId) {
+          const { texture, dtype, texShape, usage, isPacked, slice } = this.texData.get(dataId);
+          const key = (slice && slice.origDataId) || dataId;
+          const refCount = this.dataRefCount.get(key);
+          if (refCount > 1) {
+            this.dataRefCount.set(key, refCount - 1);
+          } else {
+            this.dataRefCount.delete(key);
+            if (texture != null) {
+              this.numBytesInGPU -= this.computeBytes(texShape, dtype);
+              this.textureManager.releaseTexture(texture, texShape, usage, isPacked);
+            }
+          }
+          const texData = this.texData.get(dataId);
+          texData.texture = null;
+          texData.texShape = null;
+          texData.isPacked = false;
+          texData.slice = null;
+        }
+        getTexture(dataId) {
+          this.uploadToGPU(dataId);
+          return this.texData.get(dataId).texture;
+        }
+        /**
+         * Returns internal information for the specific data bucket. Used in unit
+         * tests.
+         */
+        getDataInfo(dataId) {
+          return this.texData.get(dataId);
+        }
+        getCPUBackend() {
+          if (!Object(dist["env"])().getBool("WEBGL_CPU_FORWARD")) {
+            return null;
+          }
+          if (this.cpuBackend == null) {
+            this.cpuBackend = Object(dist["engine"])().findBackend("cpu");
+          }
+          return this.cpuBackend;
+        }
+        /*
+    Tests whether all the inputs to an op are small and on the CPU. This heuristic
+    determines when it would be faster to execute a kernel on the CPU. WebGL
+    kernels opt into running this check and forwarding when appropriate.
+    TODO(https://github.com/tensorflow/tfjs/issues/872): Develop a more
+    sustainable strategy for optimizing backend execution of ops.
+     */
+        shouldExecuteOnCPU(inputs, sizeThreshold = CPU_HANDOFF_SIZE_THRESHOLD) {
+          return (
+            this.getCPUBackend() != null &&
+            inputs.every(
+              (input) =>
+                this.texData.get(input.dataId).texture == null &&
+                dist["util"].sizeFromShape(input.shape) < sizeThreshold
+            )
+          );
+        }
+        getGPGPUContext() {
+          return this.gpgpu;
+        }
+        complex(real, imag) {
+          const result = this.makeOutput(real.shape, "complex64");
+          const resultData = this.texData.get(result.dataId);
+          // The backend owns the reference to the underlying real and imaginary
+          // clones. These will explicitly get disposed when the complex tensor is
+          // disposed.
+          resultData.complexTensors = {
+            real: Object(dist["engine"])().keep(real.clone()),
+            imag: Object(dist["engine"])().keep(imag.clone()),
+          };
+          return result;
+        }
+        real(input) {
+          const resultData = this.texData.get(input.dataId);
+          return resultData.complexTensors.real.clone();
+        }
+        imag(input) {
+          const resultData = this.texData.get(input.dataId);
+          return resultData.complexTensors.imag.clone();
+        }
+        slice(x, begin, size) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.slice(x, begin, size);
+          }
+          // Short-circuit computation if the slice is zero-sized.
+          if (dist["util"].sizeFromShape(size) === 0) {
+            return Object(dist["tensor"])([], size, x.dtype);
+          }
+          const { isPacked } = this.texData.get(x.dataId);
+          const isContinous = dist["slice_util"].isSliceContinous(x.shape, begin, size);
+          if (isPacked || !isContinous) {
+            const program = Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS")
+              ? new slice_packed_gpu_SlicePackedProgram(size)
+              : new slice_gpu_SliceProgram(size);
+            const customSetup = program.getCustomSetupFunc(begin);
+            return this.compileAndRun(program, [x], null, customSetup);
+          }
+          this.uploadToGPU(x.dataId);
+          return this.shallowSlice(x, begin, size);
+        }
+        shallowSlice(x, begin, size) {
+          const xTexData = this.texData.get(x.dataId);
+          const t = this.makeOutput(size, x.dtype);
+          const newTexData = this.texData.get(t.dataId);
+          // Copy texture data from the original tensor.
+          Object.assign(newTexData, xTexData);
+          newTexData.shape = size;
+          newTexData.dtype = x.dtype;
+          let flatOffset = dist["slice_util"].computeFlatOffset(begin, x.strides);
+          if (xTexData.slice) {
+            // We are slicing an already sliced tensor, so we have to accumulate
+            // the offset.
+            flatOffset += xTexData.slice.flatOffset;
+          }
+          newTexData.slice = {
+            flatOffset,
+            // Point to the original dataId, which is used to do ref counting.
+            origDataId: (xTexData.slice && xTexData.slice.origDataId) || x.dataId,
+          };
+          // Increase the ref count for that data bucket.
+          const refCount = this.dataRefCount.get(newTexData.slice.origDataId) || 1;
+          this.dataRefCount.set(newTexData.slice.origDataId, refCount + 1);
+          return t;
+        }
+        stridedSlice(x, begin, end, strides) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.stridedSlice(x, begin, end, strides);
+          }
+          const outShape = dist["slice_util"].computeOutShape(begin, end, strides);
+          if (outShape.some((axis) => axis === 0)) {
+            return Object(dist["tensor"])([], outShape);
+          }
+          const program = new strided_slice_gpu_StridedSliceProgram(begin, strides, outShape);
+          return this.compileAndRun(program, [x]);
+        }
+        reverse(x, axis) {
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS")
+            ? new reverse_packed_gpu_ReversePackedProgram(x.shape, axis)
+            : new reverse_gpu_ReverseProgram(x.shape, axis);
+          return this.compileAndRun(program, [x]);
+        }
+        concat(tensors, axis) {
+          if (tensors[0].dtype === "complex64") {
+            const reals = tensors.map((t) => Object(dist["real"])(t));
+            const imags = tensors.map((t) => Object(dist["imag"])(t));
+            return Object(dist["complex"])(this.concat(reals, axis), this.concat(imags, axis));
+          }
+          if (this.shouldExecuteOnCPU(tensors)) {
+            return this.cpuBackend.concat(tensors, axis);
+          }
+          if (tensors.length === 1) {
+            return tensors[0];
+          }
+          if (tensors.length > Object(dist["env"])().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")) {
+            const midIndex = Math.floor(tensors.length / 2);
+            const leftSide = this.concat(tensors.slice(0, midIndex), axis);
+            const rightSide = this.concat(tensors.slice(midIndex), axis);
+            return this.concat([leftSide, rightSide], axis);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS") && tensors[0].rank > 1) {
+            const program = new concat_packed_gpu_ConcatPackedProgram(
+              tensors.map((t) => t.shape),
+              axis
+            );
+            return this.compileAndRun(program, tensors);
+          }
+          // Any concat of n-dimensional tensors across any axis can be reduced to
+          // a concatenation of two-dimensional tensors across the axis 1 by first
+          // partitioning the axes of the original tensors into those less than the
+          // axis to be concatenated and the rest. Then reshape the tensors
+          // into a two-dimensional tensor by collapsing these two sets of axes and
+          // concatenate the resulting matrices across the axis 1, finally reshaping
+          // the result to have the proper shape.
+          const outShape = dist["backend_util"].computeOutShape(
+            tensors.map((t) => t.shape),
+            axis
+          );
+          const tensors2D = tensors.map((t) =>
+            t.as2D(-1, dist["util"].sizeFromShape(t.shape.slice(axis)))
+          );
+          const program = new concat_gpu_ConcatProgram(tensors2D.map((t) => t.shape));
+          const res = this.compileAndRun(program, tensors2D);
+          return res.reshape(outShape);
+        }
+        neg(x) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.neg(x);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
+            return this.packedUnaryOp(x, NEG, x.dtype);
+          }
+          const program = new UnaryOpProgram(x.shape, NEG);
+          return this.compileAndRun(program, [x]);
+        }
+        batchMatMul(a, b, transposeA, transposeB) {
+          const outerShapeA = transposeA ? a.shape[2] : a.shape[1];
+          const outerShapeB = transposeB ? b.shape[1] : b.shape[2];
+          const sharedDim = transposeA ? a.shape[1] : a.shape[2];
+          const [batch, ,] = a.shape;
+          // Since the matrices are vectors, it is faster to call mul().sum()
+          // because sum() is O(sqrt(N)) due to divide-and-conquer.
+          if ((outerShapeA === 1 || outerShapeB === 1) && sharedDim > MATMUL_SHARED_DIM_THRESHOLD) {
+            if (transposeA) {
+              a = Object(dist["transpose"])(a, [0, 2, 1]);
+            }
+            if (transposeB) {
+              b = Object(dist["transpose"])(b, [0, 2, 1]);
+            }
+            const a3D = outerShapeB === 1 ? a : a.as3D(batch, sharedDim, 1);
+            const axis = outerShapeB === 1 ? 2 : 1;
+            const b3D = outerShapeB === 1 ? b.as3D(batch, 1, sharedDim) : b;
+            return this.multiply(a3D, b3D).sum(axis, true /* keepDims */);
+          }
+          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
+          const program = new MatMulPackedProgram(
+            a.shape,
+            [batch, outerShapeA, outerShapeB],
+            transposeA,
+            transposeB
+          );
+          return this.compileAndRun(program, [a, b], dtype);
+        }
+        fusedBatchMatMul({
+          a,
+          b,
+          transposeA,
+          transposeB,
+          bias,
+          activation,
+          preluActivationWeights,
+        }) {
+          const outerShapeA = transposeA ? a.shape[2] : a.shape[1];
+          const outerShapeB = transposeB ? b.shape[1] : b.shape[2];
+          const [batch, ,] = a.shape;
+          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
+          const hasBias = bias != null;
+          const hasPreluActivationWeights = preluActivationWeights != null;
+          const fusedActivation = activation
+            ? mapActivationToShaderProgram(activation, true)
+            : null;
+          const program = new MatMulPackedProgram(
+            a.shape,
+            [batch, outerShapeA, outerShapeB],
+            transposeA,
+            transposeB,
+            hasBias,
+            fusedActivation,
+            hasPreluActivationWeights
+          );
+          const inputs = [a, b];
+          if (bias) {
+            inputs.push(bias);
+          }
+          if (preluActivationWeights) {
+            inputs.push(preluActivationWeights);
+          }
+          return this.compileAndRun(program, inputs, dtype);
+        }
+        multiply(a, b) {
+          if (a.dtype === "complex64") {
+            const aData = this.texData.get(a.dataId);
+            const bData = this.texData.get(b.dataId);
+            const realProgram = new binaryop_complex_gpu_BinaryOpComplexProgram(
+              COMPLEX_MULTIPLY.REAL,
+              a.shape,
+              b.shape
+            );
+            const imagProgram = new binaryop_complex_gpu_BinaryOpComplexProgram(
+              COMPLEX_MULTIPLY.IMAG,
+              a.shape,
+              b.shape
+            );
+            const inputs = [
+              this.makeComplexComponentTensorInfo(a, aData.complexTensors.real),
+              this.makeComplexComponentTensorInfo(a, aData.complexTensors.imag),
+              this.makeComplexComponentTensorInfo(b, bData.complexTensors.real),
+              this.makeComplexComponentTensorInfo(b, bData.complexTensors.imag),
+            ];
+            const real = this.compileAndRun(realProgram, inputs);
+            const imag = this.compileAndRun(imagProgram, inputs);
+            const complex = this.complex(real, imag);
+            real.dispose();
+            imag.dispose();
+            return complex;
+          }
+          if (this.shouldExecuteOnCPU([a, b])) {
+            return this.cpuBackend.multiply(a, b);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, MUL, a.dtype);
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(MUL, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], a.dtype);
+        }
+        batchNorm(x, mean, variance, offset, scale, varianceEpsilon) {
+          const inputs = [x, mean, variance];
+          let offsetShape = null;
+          if (offset != null) {
+            offsetShape = offset.shape;
+            inputs.push(offset);
+          }
+          let scaleShape = null;
+          if (scale != null) {
+            scaleShape = scale.shape;
+            inputs.push(scale);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_NORMALIZATION")) {
+            const batchNormPackedProgram = new batchnorm_packed_gpu_BatchNormPackedProgram(
+              x.shape,
+              mean.shape,
+              variance.shape,
+              offsetShape,
+              scaleShape,
+              varianceEpsilon
+            );
+            return this.compileAndRun(batchNormPackedProgram, inputs);
+          }
+          const batchNormProgram = new batchnorm_gpu_BatchNormProgram(
+            x.shape,
+            mean.shape,
+            variance.shape,
+            offsetShape,
+            scaleShape,
+            varianceEpsilon
+          );
+          return this.compileAndRun(batchNormProgram, inputs);
+        }
+        localResponseNormalization4D(x, radius, bias, alpha, beta) {
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_NORMALIZATION")
+            ? new LRNPackedProgram(x.shape, radius, bias, alpha, beta)
+            : new LRNProgram(x.shape, radius, bias, alpha, beta);
+          return this.compileAndRun(program, [x]);
+        }
+        LRNGrad(dy, inputImage, outputImage, depthRadius, bias, alpha, beta) {
+          const program = new LRNGradProgram(inputImage.shape, depthRadius, bias, alpha, beta);
+          return this.compileAndRun(program, [inputImage, outputImage, dy]);
+        }
+        tile(x, reps) {
+          if (x.dtype === "string") {
+            const data = this.readSync(x.dataId);
+            const decodedData = data.map((d) => dist["util"].decodeString(d));
+            const buf = Object(dist["buffer"])(x.shape, x.dtype, decodedData);
+            return tile(buf, reps);
+          }
+          const program = new tile_gpu_TileProgram(x.shape, reps);
+          return this.compileAndRun(program, [x]);
+        }
+        pad(x, paddings, constantValue) {
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS")
+            ? new pad_packed_gpu_PadPackedProgram(x.shape, paddings, constantValue)
+            : new pad_gpu_PadProgram(x.shape, paddings, constantValue);
+          return this.compileAndRun(program, [x]);
+        }
+        gather(x, indices, axis) {
+          if (this.shouldExecuteOnCPU([x, indices])) {
+            return this.cpuBackend.gather(x, indices, axis);
+          }
+          const program = new gather_gpu_GatherProgram(x.shape, indices.size, axis);
+          return this.compileAndRun(program, [x, indices]);
+        }
+        batchToSpaceND(x, blockShape, crops) {
+          dist["util"].assert(
+            x.rank <= 4,
+            () => "batchToSpaceND for rank > 4 with a WebGL backend not " + "implemented yet"
+          );
+          const prod = blockShape.reduce((a, b) => a * b);
+          const reshaped = dist["backend_util"].getReshaped(x.shape, blockShape, prod);
+          const permuted = dist["backend_util"].getPermuted(reshaped.length, blockShape.length);
+          const reshapedPermuted = dist["backend_util"].getReshapedPermuted(
+            x.shape,
+            blockShape,
+            prod
+          );
+          const sliceBeginCoords = dist["backend_util"].getSliceBeginCoords(
+            crops,
+            blockShape.length
+          );
+          const sliceSize = dist["backend_util"].getSliceSize(
+            reshapedPermuted,
+            crops,
+            blockShape.length
+          );
+          return Object(dist["transpose"])(x.reshape(reshaped), permuted)
+            .reshape(reshapedPermuted)
+            .slice(sliceBeginCoords, sliceSize);
+        }
+        spaceToBatchND(x, blockShape, paddings) {
+          dist["util"].assert(
+            x.rank <= 4,
+            () => "spaceToBatchND for rank > 4 with a WebGL backend not " + "implemented yet"
+          );
+          const prod = blockShape.reduce((a, b) => a * b);
+          const completePaddings = [[0, 0]];
+          completePaddings.push(...paddings);
+          for (let i = 1 + blockShape.length; i < x.shape.length; ++i) {
+            completePaddings.push([0, 0]);
+          }
+          const paddedX = x.pad(completePaddings);
+          const reshapedPaddedShape = dist["backend_util"].getReshaped(
+            paddedX.shape,
+            blockShape,
+            prod,
+            false
+          );
+          const permutedReshapedPaddedPermutation = dist["backend_util"].getPermuted(
+            reshapedPaddedShape.length,
+            blockShape.length,
+            false
+          );
+          const flattenShape = dist["backend_util"].getReshapedPermuted(
+            paddedX.shape,
+            blockShape,
+            prod,
+            false
+          );
+          return Object(dist["transpose"])(
+            paddedX.reshape(reshapedPaddedShape),
+            permutedReshapedPaddedPermutation
+          ).reshape(flattenShape);
+        }
+        reduce(x, reduceType, dtype) {
+          const batchSize = x.shape[0];
+          const inSize = x.shape[1];
+          const windowSize = dist["backend_util"].computeOptimalWindowSize(inSize);
+          const reduceInfo = { windowSize, inSize, batchSize };
+          const program = new ReduceProgram(reduceInfo, reduceType);
+          const output = this.compileAndRun(program, [x], dtype);
+          // No need to run another GPGPU program.
+          if (output.shape[1] === 1) {
+            return output;
+          }
+          return this.reduce(output, reduceType, dtype);
+        }
+        argReduce(x, reduceType, bestIndicesA = null) {
+          let batchSize = x.shape[0];
+          let inSize = x.shape[1];
+          if (bestIndicesA != null) {
+            batchSize = bestIndicesA.shape[0];
+            inSize = bestIndicesA.shape[1];
+          }
+          const windowSize = dist["backend_util"].computeOptimalWindowSize(inSize);
+          const reduceInfo = { windowSize, inSize, batchSize };
+          const program = new ArgMinMaxProgram(reduceInfo, reduceType, bestIndicesA == null);
+          const inputs = [x];
+          if (bestIndicesA != null) {
+            inputs.push(bestIndicesA);
+          }
+          const output = this.compileAndRun(program, inputs, "int32");
+          // No need to run another GPGPU program.
+          if (output.shape[1] === 1) {
+            return output;
+          }
+          return this.argReduce(x, reduceType, output);
+        }
+        argReducePacked(x, reduceType, bestIndicesA = null) {
+          const inShape = bestIndicesA != null ? bestIndicesA.shape : x.shape;
+          const inSize = inShape[inShape.length - 1];
+          const windowSize = dist["backend_util"].computeOptimalWindowSize(inSize);
+          const program = new argminmax_packed_gpu_ArgMinMaxPackedProgram(
+            inShape,
+            windowSize,
+            reduceType,
+            bestIndicesA == null
+          );
+          const inputs = bestIndicesA == null ? [x] : [x, bestIndicesA];
+          const output = this.compileAndRun(program, inputs, "int32");
+          if (output.rank === x.rank) {
+            return this.argReducePacked(x, reduceType, output);
+          }
+          return output;
+        }
+        sum(x, axes) {
+          dist["backend_util"].assertAxesAreInnerMostDims("sum", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const inSize = dist["util"].sizeFromShape(reduceShape);
+          const a2D = x.as2D(-1, inSize);
+          const outputDType = dist["sumOutType"](x.dtype);
+          return this.reduce(a2D, "sum", outputDType).reshape(outShape);
+        }
+        prod(x, axes) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.prod(x, axes);
+          }
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const inSize = dist["util"].sizeFromShape(reduceShape);
+          const a2D = x.as2D(-1, inSize);
+          const outputDType = dist["sumOutType"](x.dtype);
+          return this.reduce(a2D, "prod", outputDType).reshape(outShape);
+        }
+        unsortedSegmentSum(x, segmentIds, numSegments) {
+          let axis = 0;
+          const permutation = dist["backend_util"].getAxesPermutation([axis], x.rank);
+          let permutedX = x;
+          if (permutation != null) {
+            permutedX = Object(dist["transpose"])(x, permutation);
+            axis = dist["backend_util"].getInnerMostAxes(1, x.rank)[0];
+          }
+          const outShape = segment_util.computeOutShape(permutedX.shape, axis, numSegments);
+          const inSize = dist["util"].sizeFromShape([permutedX.shape[axis]]);
+          const a2D = permutedX.as2D(-1, inSize);
+          const outputDType = dist["sumOutType"](x.dtype);
+          let result = this.segOpCompute(
+            a2D,
+            "unsortedSegmentSum",
+            segmentIds,
+            outputDType,
+            numSegments
+          ).reshape(outShape);
+          if (permutation != null) {
+            result = Object(dist["transpose"])(
+              result,
+              dist["backend_util"].getUndoAxesPermutation(permutation)
+            );
+          }
+          return result;
+        }
+        segOpCompute(x, segOpType, segmentIds, dtype, numSegments) {
+          const batchSize = x.shape[0];
+          const inSize = x.shape[1];
+          const windowSize = segment_util.segOpComputeOptimalWindowSize(inSize, numSegments);
+          const segOpInfo = { windowSize, inSize, batchSize, numSegments };
+          const program = new SegmentOpProgram(segOpInfo, segOpType);
+          const output = this.compileAndRun(program, [x, segmentIds], dtype);
+          // No need to run another GPGPU program.
+          if (output.shape[1] === numSegments) {
+            return output;
+          }
+          segmentIds = Object(dist["range"])(0, numSegments).tile([inSize / windowSize]);
+          return this.segOpCompute(output, segOpType, segmentIds, dtype, numSegments);
+        }
+        argMinMaxReduce(x, axis, reduceType) {
+          const axes = [axis];
+          dist["backend_util"].assertAxesAreInnerMostDims(
+            "arg" + reduceType.charAt(0).toUpperCase() + reduceType.slice(1),
+            axes,
+            x.rank
+          );
+          if (!Object(dist["env"])().getBool("WEBGL_PACK_REDUCE") || x.rank <= 2) {
+            const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+              x.shape,
+              axes
+            );
+            const inSize = dist["util"].sizeFromShape(reduceShape);
+            const a2D = x.as2D(-1, inSize);
+            return this.argReduce(a2D, reduceType).reshape(outShape);
+          }
+          return this.argReducePacked(x, reduceType);
+        }
+        argMin(x, axis) {
+          return this.argMinMaxReduce(x, axis, "min");
+        }
+        argMax(x, axis) {
+          return this.argMinMaxReduce(x, axis, "max");
+        }
+        cumsum(x, axis, exclusive, reverse) {
+          if (axis !== x.rank - 1) {
+            throw new Error(
+              `WebGL cumsum shader expects an inner-most axis=${x.rank - 1} ` +
+                `but got axis=${axis}`
+            );
+          }
+          const program = new cumsum_gpu_CumSumProgram(x.shape, exclusive, reverse);
+          return this.compileAndRun(program, [x]);
+        }
+        equal(a, b) {
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_EQUAL, "bool");
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(EQUAL, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], "bool");
+        }
+        notEqual(a, b) {
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_NOT_EQUAL, "bool");
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(NOT_EQUAL, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], "bool");
+        }
+        less(a, b) {
+          if (this.shouldExecuteOnCPU([a, b])) {
+            return this.cpuBackend.less(a, b);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_LESS, "bool");
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(LESS, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], "bool");
+        }
+        lessEqual(a, b) {
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_LESS_EQUAL, "bool");
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(LESS_EQUAL, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], "bool");
+        }
+        greater(a, b) {
+          if (this.shouldExecuteOnCPU([a, b])) {
+            return this.cpuBackend.greater(a, b);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_GREATER, "bool");
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(GREATER, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], "bool");
+        }
+        greaterEqual(a, b) {
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_GREATER_EQUAL, "bool");
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(GREATER_EQUAL, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], "bool");
+        }
+        logicalNot(x) {
+          const program = new UnaryOpProgram(x.shape, LOGICAL_NOT);
+          return this.compileAndRun(program, [x]);
+        }
+        logicalAnd(a, b) {
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_LOGICAL_AND, "bool");
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(LOGICAL_AND, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], "bool");
+        }
+        logicalOr(a, b) {
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_LOGICAL_OR, "bool");
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(LOGICAL_OR, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], "bool");
+        }
+        select(condition, a, b) {
+          const program = new select_gpu_SelectProgram(condition.rank, a.shape, a.rank);
+          return this.compileAndRun(
+            program,
+            [condition, a, b],
+            Object(dist["upcastType"])(a.dtype, b.dtype)
+          );
+        }
+        where(condition) {
+          dist["backend_util"].warn(
+            "tf.where() in webgl locks the UI thread. " + "Call tf.whereAsync() instead"
+          );
+          const condVals = condition.dataSync();
+          return whereImpl(condition.shape, condVals);
+        }
+        topk(x, k, sorted) {
+          const xVals = x.dataSync();
+          return topkImpl(xVals, x.shape, x.dtype, k, sorted);
+        }
+        min(x, axes) {
+          dist["backend_util"].assertAxesAreInnerMostDims("min", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const inSize = dist["util"].sizeFromShape(reduceShape);
+          const a2D = x.as2D(-1, inSize);
+          return this.reduce(a2D, "min", a2D.dtype).reshape(outShape);
+        }
+        minimum(a, b) {
+          if (this.shouldExecuteOnCPU([a, b])) {
+            return this.cpuBackend.minimum(a, b);
+          }
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
+            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
+                binaryop_packed_gpu_MIN,
+                a.shape,
+                b.shape
+              )
+            : new binaryop_gpu_BinaryOpProgram(MIN, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b]);
+        }
+        mod(a, b) {
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
+            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
+                binaryop_packed_gpu_MOD,
+                a.shape,
+                b.shape
+              )
+            : new binaryop_gpu_BinaryOpProgram(MOD, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b]);
+        }
+        maximum(a, b) {
+          if (this.shouldExecuteOnCPU([a, b])) {
+            return this.cpuBackend.maximum(a, b);
+          }
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
+            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
+                binaryop_packed_gpu_MAX,
+                a.shape,
+                b.shape
+              )
+            : new binaryop_gpu_BinaryOpProgram(MAX, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b]);
+        }
+        all(x, axes) {
+          dist["backend_util"].assertAxesAreInnerMostDims("all", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const inSize = dist["util"].sizeFromShape(reduceShape);
+          const a2D = x.as2D(-1, inSize);
+          return this.reduce(a2D, "all", a2D.dtype).reshape(outShape);
+        }
+        any(x, axes) {
+          dist["backend_util"].assertAxesAreInnerMostDims("any", axes, x.rank);
+          const [outShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            x.shape,
+            axes
+          );
+          const inSize = dist["util"].sizeFromShape(reduceShape);
+          const a2D = x.as2D(-1, inSize);
+          return this.reduce(a2D, "any", a2D.dtype).reshape(outShape);
+        }
+        floorDiv(a, b) {
+          const op = INT_DIV;
+          const outputDtype = "int32";
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, binaryop_packed_gpu_INT_DIV, outputDtype);
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(op, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], outputDtype);
+        }
+        add(a, b) {
+          if (a.dtype === "complex64" && b.dtype === "complex64") {
+            return this.complexSeparableBinaryOp(a, b, ADD);
+          }
+          if (this.shouldExecuteOnCPU([a, b])) {
+            return this.cpuBackend.add(a, b);
+          }
+          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, ADD, dtype);
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(ADD, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], dtype);
+        }
+        packedUnaryOp(x, op, dtype) {
+          const program = new UnaryOpPackedProgram(x.shape, op);
+          return this.compileAndRun(program, [x], dtype);
+        }
+        packedBinaryOp(a, b, op, dtype, checkOutOfBounds = false) {
+          const program = new binaryop_packed_gpu_BinaryOpPackedProgram(
+            op,
+            a.shape,
+            b.shape,
+            checkOutOfBounds
+          );
+          return this.compileAndRun(program, [a, b], dtype);
+        }
+        /**
+         * Computes a complex binary operation that can be decomposed into a simple
+         * binary operation on both the real and imagary parts.
+         */
+        complexSeparableBinaryOp(a, b, op) {
+          const aData = this.texData.get(a.dataId);
+          const bData = this.texData.get(b.dataId);
+          const [real, imag] = [
+            [aData.complexTensors.real, bData.complexTensors.real],
+            [aData.complexTensors.imag, bData.complexTensors.imag],
+          ].map((complexParts) => {
+            const [aPart, bPart] = complexParts;
+            const aHandle = this.makeComplexComponentTensorInfo(a, aPart);
+            const bHandle = this.makeComplexComponentTensorInfo(b, bPart);
+            const program = new binaryop_gpu_BinaryOpProgram(op, a.shape, b.shape);
+            return this.compileAndRun(
+              program,
+              [aHandle, bHandle],
+              Object(dist["upcastType"])(aPart.dtype, bPart.dtype)
+            );
+          });
+          const complex = this.complex(real, imag);
+          real.dispose();
+          imag.dispose();
+          return complex;
+        }
+        // Returns a TensorInfo with the complex shape and the dataId of the
+        // underlying part. We need to do this because a reshaped complex tensor is
+        // not reflected in its parts.
+        makeComplexComponentTensorInfo(complexTensor, complexPart) {
+          return {
+            dataId: complexPart.dataId,
+            dtype: complexPart.dtype,
+            shape: complexTensor.shape,
+          };
+        }
+        addN(tensors) {
+          if (tensors.length === 1) {
+            return tensors[0];
+          }
+          // Limit the number of uploaded textures for optimization.
+          if (tensors.length > Object(dist["env"])().get("WEBGL_MAX_TEXTURES_IN_SHADER")) {
+            const midIndex = Math.floor(tensors.length / 2);
+            const leftSide = this.addN(tensors.slice(0, midIndex));
+            const rightSide = this.addN(tensors.slice(midIndex));
+            return this.addN([leftSide, rightSide]);
+          }
+          const dtype = tensors
+            .map((t) => t.dtype)
+            .reduce((d1, d2) => Object(dist["upcastType"])(d1, d2));
+          const shapes = tensors.map((t) => t.shape);
+          // We can make sure shapes are identical in op level.
+          const usePackedOp = Object(dist["env"])().getBool("WEBGL_PACK");
+          const program = usePackedOp
+            ? new AddNPackedProgram(tensors[0].shape, shapes)
+            : new AddNProgram(tensors[0].shape, shapes);
+          return this.compileAndRun(program, tensors, dtype);
+        }
+        subtract(a, b) {
+          if (a.dtype === "complex64" && b.dtype === "complex64") {
+            return this.complexSeparableBinaryOp(a, b, SUB);
+          }
+          if (this.shouldExecuteOnCPU([a, b])) {
+            return this.cpuBackend.subtract(a, b);
+          }
+          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
+          if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+            return this.packedBinaryOp(a, b, SUB, a.dtype);
+          }
+          const program = new binaryop_gpu_BinaryOpProgram(SUB, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b], dtype);
+        }
+        pow(a, b) {
+          const usePackedOp = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS");
+          const program = usePackedOp
+            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
+                binaryop_packed_gpu_POW,
+                a.shape,
+                b.shape
+              )
+            : new binaryop_gpu_BinaryOpProgram(POW, a.shape, b.shape);
+          const dtype = Object(dist["upcastType"])(a.dtype, b.dtype);
+          return this.compileAndRun(program, [a, b], dtype);
+        }
+        ceil(x) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.ceil(x);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
+            return this.packedUnaryOp(x, CEIL, x.dtype);
+          }
+          const program = new UnaryOpProgram(x.shape, CEIL);
+          return this.compileAndRun(program, [x]);
+        }
+        floor(x) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.floor(x);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
+            return this.packedUnaryOp(x, FLOOR, x.dtype);
+          }
+          const program = new UnaryOpProgram(x.shape, FLOOR);
+          return this.compileAndRun(program, [x]);
+        }
+        sign(x) {
+          const program = new UnaryOpProgram(x.shape, SIGN);
+          return this.compileAndRun(program, [x]);
+        }
+        isNaN(x) {
+          const program = new UnaryOpProgram(x.shape, IS_NAN);
+          return this.compileAndRun(program, [x], "bool");
+        }
+        isInf(x) {
+          const program = new UnaryOpProgram(x.shape, IS_INF);
+          return this.compileAndRun(program, [x], "bool");
+        }
+        isFinite(x) {
+          const program = new UnaryOpProgram(x.shape, IS_FINITE);
+          return this.compileAndRun(program, [x], "bool");
+        }
+        round(x) {
+          const program = new UnaryOpProgram(x.shape, ROUND);
+          return this.compileAndRun(program, [x]);
+        }
+        exp(x) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.exp(x);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
+            return this.packedUnaryOp(x, EXP, x.dtype);
+          }
+          const program = new UnaryOpProgram(x.shape, EXP);
+          return this.compileAndRun(program, [x]);
+        }
+        expm1(x) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.expm1(x);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
+            return this.packedUnaryOp(x, EXPM1, x.dtype);
+          }
+          const program = new UnaryOpProgram(x.shape, EXPM1);
+          return this.compileAndRun(program, [x]);
+        }
+        softmax(logits, dim) {
+          const axes = dist["util"].parseAxisParam([dim], logits.shape);
+          // TODO(annxingyuan): Call maxImpl rather than op as part of softmax kernel
+          // modularization.
+          const maxLogit = Object(dist["max"])(logits, axes);
+          const expandedShape = dist["backend_util"].expandShapeToKeepDim(maxLogit.shape, axes);
+          const a = this.subtract(logits, maxLogit.reshape(expandedShape));
+          const b = this.exp(a);
+          const sumExp = this.sum(b, axes).reshape(expandedShape);
+          // TODO(annxingyuan): Call divImpl rather than op as part of softmax kernel
+          // modularization.
+          return Object(dist["div"])(b, sumExp);
+        }
+        log(x) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.log(x);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
+            return this.packedUnaryOp(x, unaryop_packed_gpu_LOG, x.dtype);
+          }
+          const program = new UnaryOpProgram(x.shape, LOG);
+          return this.compileAndRun(program, [x]);
+        }
+        log1p(x) {
+          const program = new UnaryOpProgram(x.shape, LOG1P);
+          return this.compileAndRun(program, [x]);
+        }
+        sqrt(x) {
+          const program = new UnaryOpProgram(x.shape, SQRT);
+          return this.compileAndRun(program, [x]);
+        }
+        rsqrt(x) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.rsqrt(x);
+          }
+          const program = new UnaryOpProgram(x.shape, RSQRT);
+          return this.compileAndRun(program, [x]);
+        }
+        reciprocal(x) {
+          const program = new UnaryOpProgram(x.shape, RECIPROCAL);
+          return this.compileAndRun(program, [x]);
+        }
+        relu(x) {
+          let program;
+          if (Object(dist["env"])().getBool("WEBGL_PACK")) {
+            program = new UnaryOpPackedProgram(x.shape, unaryop_packed_gpu_RELU);
+          } else {
+            program = new UnaryOpProgram(x.shape, RELU);
+          }
+          return this.compileAndRun(program, [x]);
+        }
+        relu6(x) {
+          let program;
+          if (Object(dist["env"])().getBool("WEBGL_PACK")) {
+            program = new UnaryOpPackedProgram(x.shape, unaryop_packed_gpu_RELU6);
+          } else {
+            program = new UnaryOpProgram(x.shape, RELU6);
+          }
+          return this.compileAndRun(program, [x]);
+        }
+        prelu(x, alpha) {
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
+            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
+                binaryop_packed_gpu_PRELU,
+                x.shape,
+                alpha.shape
+              )
+            : new binaryop_gpu_BinaryOpProgram(PRELU, x.shape, alpha.shape);
+          return this.compileAndRun(program, [x, alpha]);
+        }
+        elu(x) {
+          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
+            return this.packedUnaryOp(x, unaryop_packed_gpu_ELU, x.dtype);
+          }
+          const program = new UnaryOpProgram(x.shape, ELU);
+          return this.compileAndRun(program, [x]);
+        }
+        eluDer(dy, y) {
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
+            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
+                binaryop_packed_gpu_ELU_DER,
+                dy.shape,
+                y.shape
+              )
+            : new binaryop_gpu_BinaryOpProgram(ELU_DER, dy.shape, y.shape);
+          return this.compileAndRun(program, [dy, y]);
+        }
+        selu(x) {
+          const program = new UnaryOpProgram(x.shape, SELU);
+          return this.compileAndRun(program, [x]);
+        }
+        int(x) {
+          const program = new UnaryOpProgram(x.shape, TO_INT);
+          return this.compileAndRun(program, [x], "int32");
+        }
+        clip(x, min, max) {
+          let program;
+          if (Object(dist["env"])().getBool("WEBGL_PACK_CLIP")) {
+            program = new ClipPackedProgram(x.shape);
+          } else {
+            program = new ClipProgram(x.shape);
+          }
+          const customSetup = program.getCustomSetupFunc(min, max);
+          return this.compileAndRun(program, [x], null, customSetup);
+        }
+        abs(x) {
+          if (this.shouldExecuteOnCPU([x])) {
+            return this.cpuBackend.abs(x);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_PACK_UNARY_OPERATIONS")) {
+            return this.packedUnaryOp(x, ABS, x.dtype);
+          }
+          const program = new UnaryOpProgram(x.shape, ABS);
+          return this.compileAndRun(program, [x]);
+        }
+        complexAbs(x) {
+          const xData = this.texData.get(x.dataId);
+          const program = new ComplexAbsProgram(x.shape);
+          const inputs = [
+            this.makeComplexComponentTensorInfo(x, xData.complexTensors.real),
+            this.makeComplexComponentTensorInfo(x, xData.complexTensors.imag),
+          ];
+          return this.compileAndRun(program, inputs);
+        }
+        sigmoid(x) {
+          const program = new UnaryOpProgram(x.shape, SIGMOID);
+          return this.compileAndRun(program, [x]);
+        }
+        softplus(x) {
+          const program = new UnaryOpProgram(x.shape, SOFTPLUS);
+          return this.compileAndRun(program, [x]);
+        }
+        sin(x) {
+          const program = new UnaryOpProgram(x.shape, SIN);
+          return this.compileAndRun(program, [x]);
+        }
+        cos(x) {
+          const program = new UnaryOpProgram(x.shape, COS);
+          return this.compileAndRun(program, [x]);
+        }
+        tan(x) {
+          const program = new UnaryOpProgram(x.shape, TAN);
+          return this.compileAndRun(program, [x]);
+        }
+        asin(x) {
+          const program = new UnaryOpProgram(x.shape, ASIN);
+          return this.compileAndRun(program, [x]);
+        }
+        acos(x) {
+          const program = new UnaryOpProgram(x.shape, ACOS);
+          return this.compileAndRun(program, [x]);
+        }
+        atan(x) {
+          const program = new UnaryOpProgram(x.shape, ATAN);
+          return this.compileAndRun(program, [x]);
+        }
+        atan2(a, b) {
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
+            ? new binaryop_packed_gpu_BinaryOpPackedProgram(
+                binaryop_packed_gpu_ATAN2,
+                a.shape,
+                b.shape
+              )
+            : new binaryop_gpu_BinaryOpProgram(ATAN2, a.shape, b.shape);
+          return this.compileAndRun(program, [a, b]);
+        }
+        sinh(x) {
+          const program = new UnaryOpProgram(x.shape, SINH);
+          return this.compileAndRun(program, [x]);
+        }
+        cosh(x) {
+          const program = new UnaryOpProgram(x.shape, COSH);
+          return this.compileAndRun(program, [x]);
+        }
+        tanh(x) {
+          const program = new UnaryOpProgram(x.shape, TANH);
+          return this.compileAndRun(program, [x]);
+        }
+        asinh(x) {
+          const program = new UnaryOpProgram(x.shape, ASINH);
+          return this.compileAndRun(program, [x]);
+        }
+        acosh(x) {
+          const program = new UnaryOpProgram(x.shape, ACOSH);
+          return this.compileAndRun(program, [x]);
+        }
+        atanh(x) {
+          const program = new UnaryOpProgram(x.shape, ATANH);
+          return this.compileAndRun(program, [x]);
+        }
+        erf(x) {
+          const program = new UnaryOpProgram(x.shape, ERF);
+          return this.compileAndRun(program, [x]);
+        }
+        step(x, alpha) {
+          const program = new UnaryOpProgram(x.shape, STEP(alpha));
+          return this.compileAndRun(program, [x]);
+        }
+        conv2dByMatMul(x, filter, convInfo, bias, activation, preluActivationWeights) {
+          // Reshapes conv2D input to 2D tensors, uses matMul and then reshape the
+          // result from 2D to 4D.
+          const xShape = x.shape;
+          const xTexData = this.texData.get(x.dataId);
+          const sharedMatMulDim = convInfo.inChannels;
+          const outerShapeX = xShape[0] * xShape[1] * xShape[2];
+          const outerShapeFilter = convInfo.outChannels;
+          const isChannelsLast = convInfo.dataFormat === "channelsLast";
+          const transposeA = false;
+          const transposeB = false;
+          // TODO: Once reduction ops are packed, batchMatMul will always be packed
+          // and we can remove this condition.
+          const batchMatMulWillBeUnpacked =
+            (outerShapeX === 1 || outerShapeFilter === 1) &&
+            sharedMatMulDim > MATMUL_SHARED_DIM_THRESHOLD;
+          const reshapeWillBeExpensive = xShape[2] % 2 !== 0 && !!xTexData.isPacked;
+          if (
+            batchMatMulWillBeUnpacked ||
+            !Object(dist["env"])().getBool("WEBGL_LAZILY_UNPACK") ||
+            !Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS") ||
+            !reshapeWillBeExpensive
+          ) {
+            const targetShape = isChannelsLast
+              ? xShape[0] * xShape[1] * xShape[2]
+              : xShape[0] * xShape[2] * xShape[3];
+            const xReshaped = this.reshape(x, [1, targetShape, convInfo.inChannels]);
+            const filterReshaped = this.reshape(filter, [
+              1,
+              convInfo.inChannels,
+              convInfo.outChannels,
+            ]);
+            return this.reshape(
+              this.fusedBatchMatMul({
+                a: xReshaped,
+                b: filterReshaped,
+                transposeA,
+                transposeB,
+                bias,
+                activation,
+                preluActivationWeights,
+              }),
+              convInfo.outShape
+            );
+          }
+          // Following optimization is specific to packed |x| with odd row count
+          // (For example, in channelLast mode, 'row count' refers to x.shape[2]):
+          // we avoid expensive packed 2x2 reshape by padding row count to next,
+          // even number. When x.shape[2] is odd, the result of packed batchMatMul is
+          // the same (has the same texture layout and and values in the texture) as
+          // it is for even x.shape[2] + 1. We make the odd-rows tensor to look like
+          // even-rows tensor before the operation and, after the batchMatMul,
+          // fix the even-rows result to have odd number of rows.
+          const targetShape = isChannelsLast
+            ? xShape[0] * xShape[1] * (xShape[2] + 1)
+            : xShape[0] * xShape[2] * (xShape[3] + 1);
+          const xReshaped = {
+            dataId: x.dataId,
+            shape: [1, targetShape, convInfo.inChannels],
+            dtype: x.dtype,
+          };
+          // xTexData.shape gets referenced from GPGPUBinary.inShapeInfos.
+          // Decrementing row count, after batchMatMul->...->compileProgram leads to
+          // invalid row count within the reference in GPGPUBinary.inShapeInfos.
+          // Alternative fix would be to provide a copy to GPGPUBinary.inShapeInfos
+          // in compileProgram method, but that would affect compilation of all
+          // programs - instead, provide a copy here, with even row count, before
+          // calling batchMatMul->...->compileProgram and after that, the original
+          // xTexData.shape is restored.
+          const originalXTexDataShape = xTexData.shape;
+          xTexData.shape = xTexData.shape.slice();
+          xTexData.shape[xTexData.shape.length - 2]++;
+          dist["util"].assert(
+            isReshapeFree(xTexData.shape, xReshaped.shape),
+            () => `packed reshape ${xTexData.shape} to ${xReshaped.shape} isn't free`
+          );
+          const filterReshaped = this.reshape(filter, [
+            1,
+            convInfo.inChannels,
+            convInfo.outChannels,
+          ]);
+          const pointwiseConv = this.fusedBatchMatMul({
+            a: xReshaped,
+            b: filterReshaped,
+            transposeA,
+            transposeB,
+            bias,
+            activation,
+            preluActivationWeights,
+          });
+          const pointwiseConvTexData = this.texData.get(pointwiseConv.dataId);
+          dist["util"].assert(
+            pointwiseConvTexData.isPacked,
+            () => "batchMatMul result is expected to be packed"
+          );
+          // Restore the input shape to original.
+          xTexData.shape = originalXTexDataShape;
+          // Set the output shape - there is no need for expensive reshape as data
+          // layout is already correct.
+          pointwiseConvTexData.shape = convInfo.outShape;
+          return Object(dist["engine"])().makeTensorFromDataId(
+            pointwiseConv.dataId,
+            convInfo.outShape,
+            pointwiseConv.dtype
+          );
+        }
+        conv2dWithIm2Row(x, filter, convInfo, bias, activation, preluActivationWeights) {
+          // Rearranges conv2d input so each block to be convolved over forms the
+          // column of a new matrix with shape [filterWidth * filterHeight *
+          // inChannels, outHeight * outWidth]. The filter is also rearranged so each
+          // output channel forms a row of a new matrix with shape [outChannels,
+          // filterWidth * filterHeight * inChannels]. The convolution is then
+          // computed by multiplying these matrices and reshaping the result.
+          const { filterWidth, filterHeight, inChannels, outWidth, outHeight, dataFormat } =
+            convInfo;
+          const isChannelsLast = dataFormat === "channelsLast";
+          const sharedDim = filterWidth * filterHeight * inChannels;
+          const numCols = outHeight * outWidth;
+          const x2ColShape = [sharedDim, numCols];
+          const transposeA = true;
+          const transposeB = false;
+          const xSqueezed = x.squeeze([0]);
+          const w2Row = filter.reshape([1, sharedDim, -1]);
+          const im2ColProgram = new im2col_packed_gpu_Im2ColPackedProgram(
+            x2ColShape,
+            xSqueezed.shape,
+            convInfo
+          );
+          const im2Col = this.compileAndRun(im2ColProgram, [xSqueezed]).reshape([
+            1,
+            x2ColShape[0],
+            x2ColShape[1],
+          ]);
+          const hasBias = bias != null;
+          const hasPreluActivationWeights = preluActivationWeights != null;
+          const fusedActivation = activation
+            ? mapActivationToShaderProgram(activation, true)
+            : null;
+          const matmulProgram = new MatMulPackedProgram(
+            im2Col.shape,
+            [1, numCols, convInfo.outChannels],
+            transposeA,
+            transposeB,
+            hasBias,
+            fusedActivation,
+            hasPreluActivationWeights
+          );
+          const inputs = [im2Col, w2Row];
+          if (bias) {
+            inputs.push(bias);
+          }
+          if (hasPreluActivationWeights) {
+            inputs.push(preluActivationWeights);
+          }
+          const product = this.compileAndRun(matmulProgram, inputs);
+          if (isChannelsLast) {
+            return product.reshape([1, outHeight, outWidth, convInfo.outChannels]);
+          } else {
+            return product.reshape([1, convInfo.outChannels, outHeight, outWidth]);
+          }
+        }
+        fusedConv2d({ input, filter, convInfo, bias, activation, preluActivationWeights }) {
+          if (
+            convInfo.filterHeight === 1 &&
+            convInfo.filterWidth === 1 &&
+            convInfo.dilationHeight === 1 &&
+            convInfo.dilationWidth === 1 &&
+            convInfo.strideHeight === 1 &&
+            convInfo.strideWidth === 1 &&
+            (convInfo.padInfo.type === "SAME" || convInfo.padInfo.type === "VALID")
+          ) {
+            return this.conv2dByMatMul(
+              input,
+              filter,
+              convInfo,
+              bias,
+              activation,
+              preluActivationWeights
+            );
+          }
+          if (Object(dist["env"])().getBool("WEBGL_CONV_IM2COL") && input.shape[0] === 1) {
+            return this.conv2dWithIm2Row(
+              input,
+              filter,
+              convInfo,
+              bias,
+              activation,
+              preluActivationWeights
+            );
+          }
+          const hasBias = bias != null;
+          const hasPreluActivationWeights = preluActivationWeights != null;
+          const fusedActivation = activation
+            ? mapActivationToShaderProgram(activation, false)
+            : null;
+          const program = new Conv2DProgram(
+            convInfo,
+            hasBias,
+            fusedActivation,
+            hasPreluActivationWeights
+          );
+          const inputs = [input, filter];
+          if (bias) {
+            inputs.push(bias);
+          }
+          if (preluActivationWeights) {
+            inputs.push(preluActivationWeights);
+          }
+          return this.compileAndRun(program, inputs);
+        }
+        conv2d(x, filter, convInfo) {
+          if (
+            convInfo.filterHeight === 1 &&
+            convInfo.filterWidth === 1 &&
+            convInfo.dilationHeight === 1 &&
+            convInfo.dilationWidth === 1 &&
+            convInfo.strideHeight === 1 &&
+            convInfo.strideWidth === 1 &&
+            (convInfo.padInfo.type === "SAME" || convInfo.padInfo.type === "VALID")
+          ) {
+            return this.conv2dByMatMul(x, filter, convInfo);
+          }
+          if (Object(dist["env"])().getBool("WEBGL_CONV_IM2COL") && x.shape[0] === 1) {
+            return this.conv2dWithIm2Row(x, filter, convInfo);
+          }
+          const program = new Conv2DProgram(convInfo);
+          return this.compileAndRun(program, [x, filter]);
+        }
+        conv2dDerInput(dy, filter, convInfo) {
+          const program = new Conv2DDerInputProgram(convInfo);
+          return this.compileAndRun(program, [dy, filter]);
+        }
+        conv2dDerFilter(x, dy, convInfo) {
+          const program = new Conv2DDerFilterProgram(convInfo);
+          return this.compileAndRun(program, [x, dy]);
+        }
+        fusedDepthwiseConv2D({
+          input,
+          filter,
+          convInfo,
+          bias,
+          activation,
+          preluActivationWeights,
+        }) {
+          const shouldPackDepthwiseConv =
+            Object(dist["env"])().getBool("WEBGL_PACK_DEPTHWISECONV") &&
+            convInfo.strideWidth <= 2 &&
+            convInfo.outChannels / convInfo.inChannels === 1;
+          const fusedActivation = activation
+            ? mapActivationToShaderProgram(activation, shouldPackDepthwiseConv)
+            : null;
+          const inputs = [input, filter];
+          const hasBias = bias != null;
+          const hasPreluActivationWeights = preluActivationWeights != null;
+          if (hasBias) {
+            inputs.push(bias);
+          }
+          if (hasPreluActivationWeights) {
+            inputs.push(preluActivationWeights);
+          }
+          let program;
+          if (shouldPackDepthwiseConv) {
+            program = new conv_packed_gpu_depthwise_DepthwiseConvPacked2DProgram(
+              convInfo,
+              hasBias,
+              fusedActivation,
+              hasPreluActivationWeights
+            );
+            return this.compileAndRun(program, inputs);
+          }
+          program = new DepthwiseConv2DProgram(
+            convInfo,
+            hasBias,
+            fusedActivation,
+            hasPreluActivationWeights
+          );
+          return this.compileAndRun(program, inputs);
+        }
+        depthwiseConv2D(x, filter, convInfo) {
+          let program;
+          if (
+            Object(dist["env"])().getBool("WEBGL_PACK_DEPTHWISECONV") &&
+            convInfo.strideWidth <= 2 &&
+            convInfo.outChannels / convInfo.inChannels === 1
+          ) {
+            program = new conv_packed_gpu_depthwise_DepthwiseConvPacked2DProgram(convInfo);
+            return this.compileAndRun(program, [x, filter]);
+          }
+          program = new DepthwiseConv2DProgram(convInfo);
+          return this.compileAndRun(program, [x, filter]);
+        }
+        depthwiseConv2DDerInput(dy, filter, convInfo) {
+          const program = new DepthwiseConv2DDerInputProgram(convInfo);
+          return this.compileAndRun(program, [dy, filter]);
+        }
+        depthwiseConv2DDerFilter(x, dy, convInfo) {
+          const program = new DepthwiseConv2DDerFilterProgram(convInfo);
+          return this.compileAndRun(program, [x, dy]);
+        }
+        conv3d(x, filter, convInfo) {
+          const program = new Conv3DProgram(convInfo);
+          return this.compileAndRun(program, [x, filter]);
+        }
+        conv3dDerInput(dy, filter, convInfo) {
+          const program = new Conv3DDerInputProgram(convInfo);
+          return this.compileAndRun(program, [dy, filter]);
+        }
+        conv3dDerFilter(x, dy, convInfo) {
+          const program = new Conv3DDerFilterProgram(convInfo);
+          return this.compileAndRun(program, [x, dy]);
+        }
+        maxPool(x, convInfo) {
+          const program = new Pool2DProgram(convInfo, "max", false);
+          return this.compileAndRun(program, [x]);
+        }
+        avgPool(x, convInfo) {
+          const program = new Pool2DProgram(convInfo, "avg", false);
+          return this.compileAndRun(program, [x], "float32");
+        }
+        maxPoolBackprop(dy, x, y, convInfo) {
+          const getPositions = true;
+          const maxPoolPositionsProgram = new Pool2DProgram(convInfo, "max", getPositions);
+          const maxPoolPositions = this.compileAndRun(maxPoolPositionsProgram, [x]);
+          const maxPoolBackPropProgram = new MaxPool2DBackpropProgram(convInfo);
+          const result = this.compileAndRun(
+            maxPoolBackPropProgram,
+            [dy, maxPoolPositions],
+            x.dtype
+          );
+          maxPoolPositions.dispose();
+          return result;
+        }
+        avgPoolBackprop(dy, x, convInfo) {
+          const avgPoolBackpropProgram = new AvgPool2DBackpropProgram(convInfo);
+          return this.compileAndRun(avgPoolBackpropProgram, [dy], x.dtype);
+        }
+        cast(x, dtype) {
+          return dist["backend_util"].castTensor(x, dtype, this);
+        }
+        unstack(x, axis) {
+          const num = x.shape[axis];
+          const outShape = new Array(x.rank - 1);
+          let outIndex = 0;
+          for (let i = 0; i < x.rank; i++) {
+            if (i !== axis) {
+              outShape[outIndex++] = x.shape[i];
+            }
+          }
+          const begin = new Array(x.rank).fill(0);
+          const size = x.shape.slice();
+          size[axis] = 1;
+          const res = new Array(num);
+          for (let i = 0; i < res.length; i++) {
+            begin[axis] = i;
+            res[i] = this.slice(x, begin, size).reshape(outShape);
+          }
+          return res;
+        }
+        avgPool3d(x, convInfo) {
+          const program = new Pool3DProgram(convInfo, "avg", false);
+          return this.compileAndRun(program, [x], "float32");
+        }
+        avgPool3dBackprop(dy, x, convInfo) {
+          const avgPool3dBackpropProgram = new AvgPool3DBackpropProgram(convInfo);
+          return this.compileAndRun(avgPool3dBackpropProgram, [dy], x.dtype);
+        }
+        maxPool3d(x, convInfo) {
+          const program = new Pool3DProgram(convInfo, "max", false);
+          return this.compileAndRun(program, [x], "float32");
+        }
+        maxPool3dBackprop(dy, x, y, convInfo) {
+          const getPositions = true;
+          const maxPool3dPositionsProgram = new Pool3DProgram(convInfo, "max", getPositions);
+          const maxPool3dPositions = this.compileAndRun(maxPool3dPositionsProgram, [x]);
+          const maxPool3dBackPropProgram = new MaxPool3DBackpropProgram(convInfo);
+          const result = this.compileAndRun(
+            maxPool3dBackPropProgram,
+            [dy, maxPool3dPositions],
+            x.dtype
+          );
+          maxPool3dPositions.dispose();
+          return result;
+        }
+        reshape(x, shape) {
+          const texData = this.texData.get(x.dataId);
+          if (
+            texData.isPacked &&
+            !isReshapeFree(x.shape, shape) &&
+            !(texData.texture !== null && isReshapeFree(texData.shape, shape))
+          ) {
+            const info = this.packedReshape(x, shape);
+            return Object(dist["engine"])().makeTensorFromDataId(
+              info.dataId,
+              info.shape,
+              info.dtype
+            );
+          }
+          return dist["backend_util"].reshapeTensor(x, shape);
+        }
+        resizeBilinear(x, newHeight, newWidth, alignCorners) {
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_IMAGE_OPERATIONS")
+            ? new ResizeBilinearPackedProgram(x.shape, newHeight, newWidth, alignCorners)
+            : new ResizeBilinearProgram(x.shape, newHeight, newWidth, alignCorners);
+          return this.compileAndRun(program, [x], "float32");
+        }
+        resizeBilinearBackprop(dy, x, alignCorners) {
+          const program = new ResizeBilinearBackpropProgram(dy, x, alignCorners);
+          return this.compileAndRun(program, [dy]);
+        }
+        resizeNearestNeighbor(x, newHeight, newWidth, alignCorners) {
+          const program = new ResizeNearestNeighborProgram(
+            x.shape,
+            newHeight,
+            newWidth,
+            alignCorners
+          );
+          return this.compileAndRun(program, [x]);
+        }
+        resizeNearestNeighborBackprop(dy, x, alignCorners) {
+          const program = new ResizeNearestNeigborBackpropProgram(dy, x, alignCorners);
+          return this.compileAndRun(program, [dy]);
+        }
+        multinomial(logits, normalized, numSamples, seed) {
+          const probs = normalized ? logits : Object(dist["softmax"])(logits);
+          const batchSize = probs.shape[0];
+          const numOutcomes = probs.shape[1];
+          const program = new MultinomialProgram(batchSize, numOutcomes, numSamples);
+          const customSetup = program.getCustomSetupFunc(seed);
+          return this.compileAndRun(program, [probs], "int32", customSetup);
+        }
+        oneHot(indices, depth, onValue, offValue) {
+          const program = new OneHotProgram(indices.size, depth, onValue, offValue);
+          return this.compileAndRun(program, [indices]);
+        }
+        diag(x) {
+          const program = new DiagProgram(x.size);
+          return this.compileAndRun(program, [x]);
+        }
+        cropAndResize(image, boxes, boxIndex, cropSize, method, extrapolationValue) {
+          const program = new CropAndResizeProgram(
+            image.shape,
+            boxes.shape,
+            cropSize,
+            method,
+            extrapolationValue
+          );
+          return this.compileAndRun(program, [image, boxes, boxIndex], "float32");
+        }
+        depthToSpace(x, blockSize, dataFormat) {
+          dist["util"].assert(
+            blockSize > 1,
+            () => `blockSize should be > 1 for depthToSpace, but was: ${blockSize}`
+          );
+          const batchSize = x.shape[0];
+          const inputHeight = dataFormat === "NHWC" ? x.shape[1] : x.shape[2];
+          const inputWidth = dataFormat === "NHWC" ? x.shape[2] : x.shape[3];
+          const inputDepth = dataFormat === "NHWC" ? x.shape[3] : x.shape[1];
+          const outputHeight = inputHeight * blockSize;
+          const outputWidth = inputWidth * blockSize;
+          const outputDepth = inputDepth / (blockSize * blockSize);
+          const outputShape =
+            dataFormat === "NHWC"
+              ? [batchSize, outputHeight, outputWidth, outputDepth]
+              : [batchSize, outputDepth, outputHeight, outputWidth];
+          const program = new DepthToSpaceProgram(outputShape, blockSize, dataFormat);
+          return this.compileAndRun(program, [x]);
+        }
+        split(x, sizeSplits, axis) {
+          return split(x, sizeSplits, axis);
+        }
+        scatterND(indices, updates, shape) {
+          const { sliceRank, numUpdates, sliceSize, strides, outputSize } = dist[
+            "backend_util"
+          ].calculateShapes(updates, indices, shape);
+          const flattenShape = [outputSize / sliceSize, sliceSize];
+          const flattenIndices = indices.reshape([numUpdates, sliceRank]);
+          const flattenX = updates.reshape([numUpdates, sliceSize]);
+          if (outputSize === 0) {
+            return dist["backend_util"].reshapeTensor(Object(dist["tensor"])([]), shape);
+          }
+          const defaultValue = Object(dist["scalar"])(0);
+          const program = new scatter_gpu_ScatterProgram(
+            numUpdates,
+            sliceRank,
+            flattenIndices.rank,
+            flattenX.rank,
+            strides,
+            flattenShape
+          );
+          const res = this.compileAndRun(program, [flattenX, flattenIndices, defaultValue]);
+          return res.reshape(shape);
+        }
+        sparseToDense(sparseIndices, sparseValues, outputShape, defaultValue) {
+          const { sliceRank, numUpdates, strides, outputSize } = dist[
+            "backend_util"
+          ].calculateShapes(sparseValues, sparseIndices, outputShape);
+          const sumDupeIndices = false;
+          const program = new scatter_gpu_ScatterProgram(
+            numUpdates,
+            sliceRank,
+            sparseIndices.rank,
+            sparseValues.rank,
+            strides,
+            [outputSize, 1],
+            sumDupeIndices
+          );
+          const res = this.compileAndRun(program, [sparseValues, sparseIndices, defaultValue]);
+          return res.reshape(outputShape);
+        }
+        fft(x) {
+          const inverse = false;
+          return this.fftImpl(x, inverse);
+        }
+        ifft(x) {
+          const inverse = true;
+          return this.fftImpl(x, inverse);
+        }
+        fftImpl(x, inverse) {
+          const xData = this.texData.get(x.dataId);
+          const realProgram = new FFTProgram(COMPLEX_FFT.REAL, x.shape, inverse);
+          const imagProgram = new FFTProgram(COMPLEX_FFT.IMAG, x.shape, inverse);
+          const inputs = [
+            this.makeComplexComponentTensorInfo(x, xData.complexTensors.real),
+            this.makeComplexComponentTensorInfo(x, xData.complexTensors.imag),
+          ];
+          const real = this.compileAndRun(realProgram, inputs);
+          const imag = this.compileAndRun(imagProgram, inputs);
+          const complex = this.complex(real, imag).as2D(x.shape[0], x.shape[1]);
+          real.dispose();
+          imag.dispose();
+          return complex;
+        }
+        gatherND(x, indices) {
+          const indicesShape = indices.shape;
+          const sliceRank = indicesShape[indicesShape.length - 1];
+          const [resultShape, numSlices, sliceSize, strides] = dist[
+            "backend_util"
+          ].prepareAndValidate(x, indices);
+          const flattenIndices = indices.reshape([numSlices, sliceRank]);
+          const flattenX = x.reshape([x.size / sliceSize, sliceSize]);
+          const program = new gather_nd_gpu_GatherNDProgram(sliceRank, strides, [
+            numSlices,
+            sliceSize,
+          ]);
+          const res = this.compileAndRun(program, [flattenX, flattenIndices]);
+          return res.reshape(resultShape);
+        }
+        fill(shape, value, dtype) {
+          dtype = dtype || dist["util"].inferDtype(value);
+          if (dtype === "string") {
+            // String type should be handled in CPU memory.
+            const values = dist["util"].getArrayFromDType(dtype, dist["util"].sizeFromShape(shape));
+            values.fill(value);
+            return Object(dist["engine"])().makeTensor(values, shape, dtype, this);
+          } else {
+            const program = new FillProgram(shape, value);
+            const customSetup = program.getCustomSetupFunc(value);
+            return this.compileAndRun(program, [], dtype, customSetup);
+          }
+        }
+        onesLike(x) {
+          if (x.dtype === "string") {
+            throw new Error("onesLike is not supported under string dtype");
+          } else {
+            // TODO(cais, smilkov): Add WebGL shader for onesLike:
+            //   https://github.com/tensorflow/tfjs/issues/1293
+            return this.fill(x.shape, 1, x.dtype);
+          }
+        }
+        zerosLike(x) {
+          return this.fill(x.shape, x.dtype === "string" ? "" : 0, x.dtype);
+        }
+        linspace(start, stop, num) {
+          // TODO: Use CPU implementation due to the precision problem in Safari.
+          return dist["backend_util"].linspaceImpl(start, stop, num);
+        }
+        makeTensorInfo(shape, dtype) {
+          const dataId = this.write(null /* values */, shape, dtype);
+          this.texData.get(dataId).usage = null;
+          return { dataId, shape, dtype };
+        }
+        makeOutput(shape, dtype) {
+          const { dataId } = this.makeTensorInfo(shape, dtype);
+          return Object(dist["engine"])().makeTensorFromDataId(dataId, shape, dtype, this);
+        }
+        unpackTensor(input) {
+          const program = new unpack_gpu_UnpackProgram(input.shape);
+          return this.runWebGLProgram(program, [input], input.dtype);
+        }
+        packTensor(input) {
+          const program = new pack_gpu_PackProgram(input.shape);
+          const preventEagerUnpackingOutput = true;
+          return this.runWebGLProgram(
+            program,
+            [input],
+            input.dtype,
+            null /* customSetup */,
+            preventEagerUnpackingOutput
+          );
+        }
+        packedReshape(input, afterShape) {
+          const input3DShape = [getBatchDim(input.shape), ...getRowsCols(input.shape)];
+          const input3D = {
+            dtype: input.dtype,
+            shape: input3DShape,
+            dataId: input.dataId,
+          };
+          const afterShapeAs3D = [getBatchDim(afterShape), ...getRowsCols(afterShape)];
+          const program = new reshape_packed_gpu_ReshapePackedProgram(afterShapeAs3D, input3DShape);
+          const preventEagerUnpackingOfOutput = true;
+          const output = this.runWebGLProgram(
+            program,
+            [input3D],
+            input.dtype,
+            null /* customSetup */,
+            preventEagerUnpackingOfOutput
+          );
+          return { dataId: output.dataId, shape: afterShape, dtype: output.dtype };
+        }
+        decode(dataId) {
+          const texData = this.texData.get(dataId);
+          const { isPacked, shape, dtype } = texData;
+          const shapeAs3D = getShapeAs3D(shape);
+          let program;
+          if (isPacked) {
+            program = new decode_matrix_packed_gpu_DecodeMatrixPackedProgram(shapeAs3D);
+          } else {
+            program = new decode_matrix_gpu_DecodeMatrixProgram(shapeAs3D);
+          }
+          const preventEagerUnpackingOfOutput = true;
+          const out = this.runWebGLProgram(
+            program,
+            [{ shape: shapeAs3D, dtype, dataId }],
+            dtype,
+            null /* customSetup */,
+            preventEagerUnpackingOfOutput
+          );
+          return { dtype, shape, dataId: out.dataId };
+        }
+        runWebGLProgram(
+          program,
+          inputs,
+          outputDtype,
+          customSetup,
+          preventEagerUnpackingOfOutput = false
+        ) {
+          const output = this.makeTensorInfo(program.outputShape, outputDtype);
+          const outData = this.texData.get(output.dataId);
+          if (program.packedOutput) {
+            outData.isPacked = true;
+          }
+          if (program.outPackingScheme === PackingScheme.DENSE) {
+            const texelShape = getDenseTexShape(program.outputShape);
+            // For a densely packed output, we explicitly set texShape
+            // so it doesn't get assigned later according to our typical packing
+            // scheme wherein a single texel can only contain values from adjacent
+            // rows/cols.
+            outData.texShape = texelShape.map((d) => d * 2);
+          }
+          if (program.outTexUsage != null) {
+            outData.usage = program.outTexUsage;
+          }
+          if (dist["util"].sizeFromShape(output.shape) === 0) {
+            // Short-circuit the computation since the result is empty (has 0 in its
+            // shape).
+            outData.values = dist["util"].getTypedArrayFromDType(output.dtype, 0);
+            return output;
+          }
+          const dataToDispose = [];
+          const inputsData = inputs.map((input) => {
+            if (input.dtype === "complex64") {
+              throw new Error(
+                `GPGPUProgram does not support complex64 input. For complex64 ` +
+                  `dtypes, please separate the program into real and imaginary ` +
+                  `parts.`
+              );
+            }
+            let texData = this.texData.get(input.dataId);
+            if (texData.texture == null) {
+              if (
+                !program.packedInputs &&
+                dist["util"].sizeFromShape(input.shape) <=
+                  Object(dist["env"])().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM")
+              ) {
+                // Upload small tensors that live on the CPU as uniforms, not as
+                // textures. Do this only when the environment supports 32bit floats
+                // due to problems when comparing 16bit floats with 32bit floats.
+                // TODO(https://github.com/tensorflow/tfjs/issues/821): Make it
+                // possible for packed shaders to sample from uniforms.
+                return {
+                  shape: input.shape,
+                  texData: null,
+                  isUniform: true,
+                  uniformValues: texData.values,
+                };
+              }
+              // This ensures that if a packed program's inputs have not yet been
+              // uploaded to the GPU, they get uploaded as packed right off the bat.
+              if (program.packedInputs) {
+                texData.isPacked = true;
+                texData.shape = input.shape;
+              }
+            } else if (!!texData.isPacked !== !!program.packedInputs) {
+              input = texData.isPacked ? this.unpackTensor(input) : this.packTensor(input);
+              dataToDispose.push(input);
+              texData = this.texData.get(input.dataId);
+            } else if (texData.isPacked && !isReshapeFree(texData.shape, input.shape)) {
+              // This is a special case where a texture exists for a tensor
+              // but the shapes are incompatible (due to packing constraints) because
+              // the tensor did not have a chance to go through the packed reshape
+              // shader. This only happens when we reshape the *same* tensor to form
+              // *distinct* inputs to an op, e.g. dotting a vector with itself. This
+              // case will disappear once packed uploading is the default.
+              const savedInput = input;
+              const targetShape = input.shape;
+              input.shape = texData.shape;
+              input = this.packedReshape(input, targetShape);
+              dataToDispose.push(input);
+              texData = this.texData.get(input.dataId);
+              savedInput.shape = targetShape;
+            }
+            this.uploadToGPU(input.dataId);
+            return { shape: input.shape, texData, isUniform: false };
+          });
+          this.uploadToGPU(output.dataId);
+          const outputData = { shape: output.shape, texData: outData, isUniform: false };
+          const key = makeShaderKey(program, inputsData, outputData);
+          const binary = this.getAndSaveBinary(key, () => {
+            return compileProgram(this.gpgpu, program, inputsData, outputData);
+          });
+          const shouldTimeProgram = this.activeTimers != null;
+          let query;
+          if (shouldTimeProgram) {
+            query = this.startTimer();
+          }
+          runProgram(this.gpgpu, binary, inputsData, outputData, customSetup);
+          dataToDispose.forEach((info) => this.disposeData(info.dataId));
+          if (shouldTimeProgram) {
+            query = this.endTimer(query);
+            this.activeTimers.push({
+              name: program.constructor.name,
+              query: this.getQueryTime(query),
+            });
+          }
+          if (
+            !Object(dist["env"])().getBool("WEBGL_LAZILY_UNPACK") &&
+            outData.isPacked &&
+            preventEagerUnpackingOfOutput === false
+          ) {
+            const unpacked = this.unpackTensor(output);
+            this.disposeData(output.dataId);
+            return unpacked;
+          }
+          return output;
+        }
+        compileAndRun(
+          program,
+          inputs,
+          outputDtype,
+          customSetup,
+          preventEagerUnpackingOfOutput = false
+        ) {
+          outputDtype = outputDtype || inputs[0].dtype;
+          const outInfo = this.runWebGLProgram(
+            program,
+            inputs,
+            outputDtype,
+            customSetup,
+            preventEagerUnpackingOfOutput
+          );
+          return Object(dist["engine"])().makeTensorFromDataId(
+            outInfo.dataId,
+            outInfo.shape,
+            outInfo.dtype
+          );
+        }
+        getAndSaveBinary(key, getBinary) {
+          if (!(key in this.binaryCache)) {
+            this.binaryCache[key] = getBinary();
+          }
+          return this.binaryCache[key];
+        }
+        getTextureManager() {
+          return this.textureManager;
+        }
+        dispose() {
+          if (this.disposed) {
+            return;
+          }
+          // Avoid disposing the compiled webgl programs during unit testing because
+          // it slows down test execution.
+          if (!Object(dist["env"])().getBool("IS_TEST")) {
+            const allKeys = Object.keys(this.binaryCache);
+            allKeys.forEach((key) => {
+              this.gpgpu.deleteProgram(this.binaryCache[key].webGLProgram);
+              delete this.binaryCache[key];
+            });
+          }
+          this.textureManager.dispose();
+          if (
+            this.canvas != null &&
+            typeof HTMLCanvasElement !== "undefined" &&
+            this.canvas instanceof HTMLCanvasElement
+          ) {
+            this.canvas.remove();
+          } else {
+            this.canvas = null;
+          }
+          if (this.gpgpuCreatedLocally) {
+            this.gpgpu.program = null;
+            this.gpgpu.dispose();
+          }
+          this.disposed = true;
+        }
+        floatPrecision() {
+          if (this.floatPrecisionValue == null) {
+            this.floatPrecisionValue = Object(dist["tidy"])(() => {
+              if (!Object(dist["env"])().get("WEBGL_RENDER_FLOAT32_ENABLED")) {
+                // Momentarily switching DEBUG flag to false so we don't throw an
+                // error trying to upload a small value.
+                const debugFlag = Object(dist["env"])().getBool("DEBUG");
+                Object(dist["env"])().set("DEBUG", false);
+                const underflowCheckValue = this.abs(Object(dist["scalar"])(1e-8)).dataSync()[0];
+                Object(dist["env"])().set("DEBUG", debugFlag);
+                if (underflowCheckValue > 0) {
+                  return 32;
+                }
+              }
+              return 16;
+            });
+          }
+          return this.floatPrecisionValue;
+        }
+        /** Returns the smallest representable number.  */
+        epsilon() {
+          return this.floatPrecision() === 32 ? EPSILON_FLOAT32 : EPSILON_FLOAT16;
+        }
+        uploadToGPU(dataId) {
+          const texData = this.texData.get(dataId);
+          const { shape, dtype, values, texture, usage, isPacked } = texData;
+          if (texture != null) {
+            // Array is already on GPU. No-op.
+            return;
+          }
+          const shouldTimeProgram = this.activeTimers != null;
+          let start;
+          if (shouldTimeProgram) {
+            start = dist["util"].now();
+          }
+          let texShape = texData.texShape;
+          if (texShape == null) {
+            texShape = getTextureShapeFromLogicalShape(shape, isPacked);
+            texData.texShape = texShape;
+          }
+          if (values != null) {
+            const shapeAs3D = getShapeAs3D(shape);
+            let program;
+            let width = texShape[1],
+              height = texShape[0];
+            const isByteArray = values instanceof Uint8Array;
+            if (isPacked) {
+              [width, height] = getPackedMatrixTextureShapeWidthHeight(texShape[0], texShape[1]);
+              program = new encode_matrix_packed_gpu_EncodeMatrixPackedProgram(
+                shapeAs3D,
+                [height, width],
+                isByteArray
+              );
+            } else {
+              program = new encode_matrix_gpu_EncodeMatrixProgram(
+                shapeAs3D,
+                [height, width],
+                isByteArray
+              );
+            }
+            const tempDenseInputHandle = this.makeTensorInfo([height, width], dtype);
+            if (isByteArray) {
+              this.texData.get(tempDenseInputHandle.dataId).usage = TextureUsage.PIXELS;
+            } else {
+              this.texData.get(tempDenseInputHandle.dataId).usage = TextureUsage.UPLOAD;
+            }
+            this.gpgpu.uploadDenseMatrixToTexture(
+              this.getTexture(tempDenseInputHandle.dataId),
+              width,
+              height,
+              values
+            );
+            // We want the output to remain packed regardless of the value of
+            // WEBGL_PACK.
+            const preventEagerUnpacking = true;
+            const encodedOutputTarget = this.runWebGLProgram(
+              program,
+              [tempDenseInputHandle],
+              dtype,
+              null,
+              preventEagerUnpacking
+            );
+            // Have the original texture assume the identity of the encoded output.
+            const outputTexData = this.texData.get(encodedOutputTarget.dataId);
+            texData.texture = outputTexData.texture;
+            texData.texShape = outputTexData.texShape;
+            texData.isPacked = outputTexData.isPacked;
+            texData.usage = outputTexData.usage;
+            this.disposeData(tempDenseInputHandle.dataId);
+            this.texData.delete(encodedOutputTarget.dataId);
+            // Once uploaded, don't store the values on cpu.
+            texData.values = null;
+            if (shouldTimeProgram) {
+              this.uploadWaitMs += dist["util"].now() - start;
+            }
+          } else {
+            const newTexture = this.acquireTexture(texShape, usage, dtype, isPacked);
+            texData.texture = newTexture;
+          }
+        }
+        convertAndCacheOnCPU(dataId, float32Values) {
+          const texData = this.texData.get(dataId);
+          const { dtype } = texData;
+          this.releaseGPUData(dataId);
+          if (float32Values != null) {
+            texData.values = float32ToTypedArray(float32Values, dtype);
+          }
+          return texData.values;
+        }
+        acquireTexture(texShape, texType, dtype, isPacked) {
+          this.numBytesInGPU += this.computeBytes(texShape, dtype);
+          if (
+            !this.warnedAboutMemory &&
+            this.numBytesInGPU > this.numMBBeforeWarning * 1024 * 1024
+          ) {
+            const mb = (this.numBytesInGPU / 1024 / 1024).toFixed(2);
+            this.warnedAboutMemory = true;
+            console.warn(
+              `High memory usage in GPU: ${mb} MB, ` + `most likely due to a memory leak`
+            );
+          }
+          return this.textureManager.acquireTexture(texShape, texType, isPacked);
+        }
+        computeBytes(shape, dtype) {
+          return shape[0] * shape[1] * dist["util"].bytesPerElement(dtype);
+        }
+      }
+      function float32ToTypedArray(a, dtype) {
+        if (dtype === "float32" || dtype === "complex64") {
+          return a;
+        } else if (dtype === "int32" || dtype === "bool") {
+          const result = dtype === "int32" ? new Int32Array(a.length) : new Uint8Array(a.length);
+          for (let i = 0; i < result.length; ++i) {
+            result[i] = Math.round(a[i]);
+          }
+          return result;
+        } else {
+          throw new Error(`Unknown dtype ${dtype}`);
+        }
+      }
+      //# sourceMappingURL=backend_webgl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/version.js
+      /** @license See the LICENSE file. */
+      // This code is auto-generated, do not modify this file!
+      const version_version = "2.0.1";
+
+      //# sourceMappingURL=version.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Div_impl.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function divImpl(a, b, backend) {
+        let program = new binaryop_gpu_BinaryOpProgram(DIV, a.shape, b.shape);
+        if (Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")) {
+          program = new binaryop_packed_gpu_BinaryOpPackedProgram(
+            binaryop_packed_gpu_DIV,
+            a.shape,
+            b.shape,
+            true
+          );
+        }
+        const output = backend.runWebGLProgram(program, [a, b], "float32");
+        return output;
+      }
+      //# sourceMappingURL=Div_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Div.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const divConfig = {
+        kernelName: dist["Div"],
+        backendName: "webgl",
+        kernelFunc: ({ inputs, backend }) => {
+          const { a, b } = inputs;
+          const webglBackend = backend;
+          return divImpl(a, b, webglBackend);
+        },
+      };
+      //# sourceMappingURL=Div.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels_utils/from_pixels_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class from_pixels_gpu_FromPixelsProgram {
+        constructor(outputShape) {
+          this.variableNames = ["A"];
+          const glsl = getGlslDifferences();
+          const [height, width] = outputShape;
+          this.outputShape = outputShape;
+          this.userCode = `
+      void main() {
+        ivec3 coords = getOutputCoords();
+        int texR = coords[0];
+        int texC = coords[1];
+        int depth = coords[2];
+        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${width}.0, ${height}.0);
+
+        vec4 values = ${glsl.texture2D}(A, uv);
+        float value;
+        if (depth == 0) {
+          value = values.r;
+        } else if (depth == 1) {
+          value = values.g;
+        } else if (depth == 2) {
+          value = values.b;
+        } else if (depth == 3) {
+          value = values.a;
+        }
+
+        setOutput(floor(value * 255.0 + 0.5));
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=from_pixels_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels_utils/from_pixels_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2018 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class from_pixels_packed_gpu_FromPixelsPackedProgram {
+        constructor(outputShape) {
+          this.variableNames = ["A"];
+          this.packedInputs = false;
+          this.packedOutput = true;
+          const glsl = getGlslDifferences();
+          const [height, width] = outputShape;
+          this.outputShape = outputShape;
+          this.userCode = `
+      void main() {
+        ivec3 coords = getOutputCoords();
+        int texR = coords[0];
+        int texC = coords[1];
+        int depth = coords[2];
+
+        vec4 result = vec4(0.);
+
+        for(int row=0; row<=1; row++) {
+          for(int col=0; col<=1; col++) {
+            texC = coords[1] + row;
+            depth = coords[2] + col;
+
+            vec2 uv = (vec2(texC, texR) + halfCR) /
+                       vec2(${width}.0, ${height}.0);
+            vec4 values = ${glsl.texture2D}(A, uv);
+            float value;
+            if (depth == 0) {
+              value = values.r;
+            } else if (depth == 1) {
+              value = values.g;
+            } else if (depth == 2) {
+              value = values.b;
+            } else if (depth == 3) {
+              value = values.a;
+            }
+
+            result[row * 2 + col] = floor(value * 255.0 + 0.5);
+          }
+        }
+
+        ${glsl.output} = result;
+      }
+    `;
+        }
+      }
+      //# sourceMappingURL=from_pixels_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const fromPixelsConfig = {
+        kernelName: dist["FromPixels"],
+        backendName: "webgl",
+        kernelFunc: fromPixels,
+      };
+      let fromPixels2DContext;
+      function fromPixels(args) {
+        const { inputs, backend, attrs } = args;
+        let { pixels } = inputs;
+        const { numChannels } = attrs;
+        const isVideo =
+          typeof HTMLVideoElement !== "undefined" && pixels instanceof HTMLVideoElement;
+        const isImage =
+          typeof HTMLImageElement !== "undefined" && pixels instanceof HTMLImageElement;
+        const [width, height] = isVideo
+          ? [pixels.videoWidth, pixels.videoHeight]
+          : [pixels.width, pixels.height];
+        const texShape = [height, width];
+        const outShape = [height, width, numChannels];
+        if (isImage || isVideo) {
+          if (fromPixels2DContext == null) {
+            fromPixels2DContext = document.createElement("canvas").getContext("2d");
+          }
+          fromPixels2DContext.canvas.width = width;
+          fromPixels2DContext.canvas.height = height;
+          fromPixels2DContext.drawImage(pixels, 0, 0, width, height);
+          pixels = fromPixels2DContext.canvas;
+        }
+        const tempPixelHandle = backend.makeTensorInfo(texShape, "int32");
+        // This is a byte texture with pixels.
+        backend.texData.get(tempPixelHandle.dataId).usage = TextureUsage.PIXELS;
+        backend.gpgpu.uploadPixelDataToTexture(backend.getTexture(tempPixelHandle.dataId), pixels);
+        const program = Object(dist["env"])().getBool("WEBGL_PACK")
+          ? new from_pixels_packed_gpu_FromPixelsPackedProgram(outShape)
+          : new from_pixels_gpu_FromPixelsProgram(outShape);
+        const res = backend.runWebGLProgram(program, [tempPixelHandle], "int32");
+        backend.disposeData(tempPixelHandle.dataId);
+        return res;
+      }
+      //# sourceMappingURL=FromPixels.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/base.js + 3 modules
+      var base = __webpack_require__(31);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/shared.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // Import shared functionality from tfjs-backend-cpu without triggering
+      // side effects.
+      // tslint:disable-next-line: no-imports-from-dist
+
+      const { maxImpl: maxImplCPU, transposeImpl: transposeImplCPU } = base["b" /* shared */];
+
+      //# sourceMappingURL=shared.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/reduce.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function reduce(x, dtype, reductionType, backend) {
+        const [batchSize, inSize] = x.shape;
+        const windowSize = dist["backend_util"].computeOptimalWindowSize(inSize);
+        const reduceInfo = { windowSize, inSize, batchSize };
+        const program = new ReduceProgram(reduceInfo, reductionType);
+        const output = backend.runWebGLProgram(program, [x], dtype);
+        if (output.shape[1] === 1) {
+          return output;
+        }
+        return reduce(output, dtype, reductionType, backend);
+      }
+      //# sourceMappingURL=reduce.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/reshape.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function packedReshape(input, afterShape, backend) {
+        const input3DShape = [getBatchDim(input.shape), ...getRowsCols(input.shape)];
+        const input3D = {
+          dtype: input.dtype,
+          shape: input3DShape,
+          dataId: input.dataId,
+        };
+        const afterShapeAs3D = [getBatchDim(afterShape), ...getRowsCols(afterShape)];
+        const program = new reshape_packed_gpu_ReshapePackedProgram(afterShapeAs3D, input3DShape);
+        const preventEagerUnpackingOfOutput = true;
+        const output = backend.runWebGLProgram(
+          program,
+          [input3D],
+          input.dtype,
+          null /* customSetup */,
+          preventEagerUnpackingOfOutput
+        );
+        return { dataId: output.dataId, shape: afterShape, dtype: output.dtype };
+      }
+      function reshape(x, afterShape, backend) {
+        const xTexData = backend.texData.get(x.dataId);
+        if (
+          xTexData.isPacked &&
+          !isReshapeFree(x.shape, afterShape) &&
+          !(xTexData.texture !== null && isReshapeFree(xTexData.shape, afterShape))
+        ) {
+          return packedReshape(x, afterShape, backend);
+        }
+        return { dataId: x.dataId, shape: afterShape, dtype: x.dtype };
+      }
+      //# sourceMappingURL=reshape.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Max_impl.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function maxImpl(x, reduceShape, outShape, backend) {
+        const inSize = dist["util"].sizeFromShape(reduceShape);
+        const xSize = dist["util"].sizeFromShape(x.shape);
+        const batchSize = xSize / inSize;
+        const reshapedInput = reshape(x, [batchSize, inSize], backend);
+        const reduced = reduce(reshapedInput, x.dtype, "max", backend);
+        if (reshapedInput.dataId !== x.dataId) {
+          // dispose the output of the packed reshape.
+          backend.disposeData(reshapedInput.dataId);
+        }
+        return reshape(reduced, outShape, backend);
+      }
+      //# sourceMappingURL=Max_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/transpose_gpu.js
+      /**
+       * @license
+       * Copyright 2017 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class transpose_gpu_TransposeProgram {
+        constructor(aShape, newDim) {
+          this.variableNames = ["A"];
+          const outputShape = new Array(aShape.length);
+          for (let i = 0; i < outputShape.length; i++) {
+            outputShape[i] = aShape[newDim[i]];
+          }
+          this.outputShape = outputShape;
+          this.rank = outputShape.length;
+          const dtype = getCoordsDataType(this.rank);
+          const switched = getSwitchedCoords(newDim);
+          this.userCode = `
+    void main() {
+      ${dtype} resRC = getOutputCoords();
+      setOutput(getA(${switched}));
+    }
+    `;
+        }
+      }
+      function getSwitchedCoords(newDim) {
+        const rank = newDim.length;
+        if (rank > 6) {
+          throw Error(`Transpose for rank ${rank} is not yet supported`);
+        }
+        const originalOrder = ["resRC.x", "resRC.y", "resRC.z", "resRC.w", "resRC.u", "resRC.v"];
+        const switchedCoords = new Array(rank);
+        for (let i = 0; i < newDim.length; i++) {
+          switchedCoords[newDim[i]] = originalOrder[i];
+        }
+        return switchedCoords.join();
+      }
+      //# sourceMappingURL=transpose_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/transpose_packed_gpu.js
+      /**
+       * @license
+       * Copyright 2019 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      class transpose_packed_gpu_TransposePackedProgram {
+        constructor(aShape, newDim) {
+          this.variableNames = ["A"];
+          this.packedInputs = true;
+          this.packedOutput = true;
+          const outputShape = new Array(aShape.length);
+          for (let i = 0; i < outputShape.length; i++) {
+            outputShape[i] = aShape[newDim[i]];
+          }
+          this.outputShape = outputShape;
+          this.rank = outputShape.length;
+          if (this.rank > 6) {
+            throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);
+          }
+          const dtype = getCoordsDataType(this.rank);
+          const outputOrder = getVecChannels("rc", this.rank);
+          const switchedOrder = new Array(this.rank);
+          for (let i = 0; i < newDim.length; i++) {
+            switchedOrder[newDim[i]] = outputOrder[i];
+          }
+          const innerDims = `vec2(${switchedOrder.slice(-2).join()})`;
+          const nextColumn = `++${outputOrder[this.rank - 1]} < ${outputShape[this.rank - 1]}`;
+          const getc = `getChannel(getA(${switchedOrder.join()}), ${innerDims})`;
+          this.userCode = `
+    void main() {
+      ${dtype} rc = getOutputCoords();
+      vec4 result = vec4(0.);
+      result[0] = ${getc};
+      if(${nextColumn}) {
+        result[1] = ${getc};
+      }
+      --${outputOrder[this.rank - 1]};
+      if(++${outputOrder[this.rank - 2]} < ${outputShape[this.rank - 2]}) {
+        result[2] = ${getc};
+        if(${nextColumn}) {
+          result[3] = ${getc};
+        }
+      }
+      setOutput(result);
+    }
+    `;
+        }
+      }
+      //# sourceMappingURL=transpose_packed_gpu.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transpose_impl.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function transposeImpl(x, perm, backend) {
+        const program = Object(dist["env"])().getBool("WEBGL_PACK_ARRAY_OPERATIONS")
+          ? new transpose_packed_gpu_TransposePackedProgram(x.shape, perm)
+          : new transpose_gpu_TransposeProgram(x.shape, perm);
+        return backend.runWebGLProgram(program, [x], x.dtype);
+      }
+
+      //# sourceMappingURL=Transpose_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Max.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const maxConfig = {
+        kernelName: dist["Max"],
+        backendName: "webgl",
+        kernelFunc: ({ inputs, attrs, backend }) => {
+          const { x } = inputs;
+          const { reductionIndices } = attrs;
+          const webglBackend = backend;
+          const xRank = x.shape.length;
+          const origAxes = dist["util"].parseAxisParam(reductionIndices, x.shape);
+          let axes = origAxes;
+          const permutedAxes = dist["backend_util"].getAxesPermutation(axes, xRank);
+          const maxInputIsTransposed = permutedAxes != null;
+          const shouldExecuteOnCPU = webglBackend.shouldExecuteOnCPU([x]);
+          let maxInput = x;
+          if (maxInputIsTransposed) {
+            if (shouldExecuteOnCPU) {
+              const xTexData = webglBackend.texData.get(maxInput.dataId);
+              const values = xTexData.values;
+              const newShape = new Array(xRank);
+              for (let i = 0; i < newShape.length; i++) {
+                newShape[i] = x.shape[permutedAxes[i]];
+              }
+              const maxInputValues = transposeImplCPU(
+                values,
+                x.shape,
+                x.dtype,
+                permutedAxes,
+                newShape
+              );
+              maxInput = webglBackend.makeTensorInfo(newShape, x.dtype);
+              const maxInputData = webglBackend.texData.get(maxInput.dataId);
+              maxInputData.values = maxInputValues;
+            } else {
+              maxInput = transposeImpl(x, permutedAxes, webglBackend);
+            }
+            axes = dist["backend_util"].getInnerMostAxes(axes.length, xRank);
+          }
+          dist["backend_util"].assertAxesAreInnerMostDims("max", axes, xRank);
+          const [maxOutShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            maxInput.shape,
+            axes
+          );
+          let out;
+          if (shouldExecuteOnCPU) {
+            const xTexData = webglBackend.texData.get(maxInput.dataId);
+            const values = xTexData.values;
+            const outValues = maxImplCPU(
+              values,
+              dist["util"].sizeFromShape(reduceShape),
+              maxOutShape,
+              x.dtype
+            );
+            out = webglBackend.makeTensorInfo(maxOutShape, x.dtype);
+            const outData = webglBackend.texData.get(out.dataId);
+            outData.values = outValues;
+          } else {
+            out = maxImpl(maxInput, reduceShape, maxOutShape, webglBackend);
+          }
+          if (maxInputIsTransposed) {
+            webglBackend.disposeData(maxInput.dataId);
+          }
+          return out;
+        },
+      };
+      //# sourceMappingURL=Max.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolWithArgmax_impl.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function maxPoolWithArgmaxImpl(x, includeBatchInIndex, convInfo, backend) {
+        let program = new Pool2DProgram(convInfo, "max", false);
+        const poolOutput = backend.runWebGLProgram(program, [x], "float32");
+        program = new Pool2DProgram(convInfo, "max", true, true, includeBatchInIndex);
+        const indexOutput = backend.runWebGLProgram(program, [x], "float32");
+        return [poolOutput, indexOutput];
+      }
+      //# sourceMappingURL=MaxPoolWithArgmax_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolWithArgmax.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const maxPoolWithArgmaxConfig = {
+        kernelName: dist["MaxPoolWithArgmax"],
+        backendName: "webgl",
+        kernelFunc: ({ inputs, attrs, backend }) => {
+          const { x } = inputs;
+          const { filterSize, strides, pad, includeBatchInIndex } = attrs;
+          const webglBackend = backend;
+          dist["util"].assert(
+            x.shape.length === 4,
+            () => `Error in maxPool: input must be rank 4 but got rank ${x.shape.length}.`
+          );
+          const dilations = [1, 1];
+          dist["util"].assert(
+            dist["backend_util"].eitherStridesOrDilationsAreOne(strides, dilations),
+            () =>
+              "Error in maxPool: Either strides or dilations must be 1. " +
+              `Got strides ${strides} and dilations '${dilations}'`
+          );
+          const convInfo = dist["backend_util"].computePool2DInfo(
+            x.shape,
+            filterSize,
+            strides,
+            dilations,
+            pad
+          );
+          const [result, indexes] = maxPoolWithArgmaxImpl(
+            x,
+            includeBatchInIndex,
+            convInfo,
+            webglBackend
+          );
+          return [result, indexes];
+        },
+      };
+      //# sourceMappingURL=MaxPoolWithArgmax.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV3.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const nonMaxSuppressionV3Config = {
+        kernelName: dist["NonMaxSuppressionV3"],
+        backendName: "webgl",
+        kernelFunc: ({ inputs, backend, attrs }) => {
+          dist["backend_util"].warn(
+            "tf.nonMaxSuppression() in webgl locks the UI thread. " +
+              "Call tf.nonMaxSuppressionAsync() instead"
+          );
+          const { boxes, scores } = inputs;
+          const { maxOutputSize, iouThreshold, scoreThreshold } = attrs;
+          const gpuBackend = backend;
+          const boxesVals = gpuBackend.readSync(boxes.dataId);
+          const scoresVals = gpuBackend.readSync(scores.dataId);
+          const maxOutputSizeVal = maxOutputSize;
+          const iouThresholdVal = iouThreshold;
+          const scoreThresholdVal = scoreThreshold;
+          return dist["kernel_impls"].nonMaxSuppressionV3(
+            boxesVals,
+            scoresVals,
+            maxOutputSizeVal,
+            iouThresholdVal,
+            scoreThresholdVal
+          );
+        },
+      };
+      //# sourceMappingURL=NonMaxSuppressionV3.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV5.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const nonMaxSuppressionV5 = dist["kernel_impls"].nonMaxSuppressionV5;
+      const nonMaxSuppressionV5Config = {
+        kernelName: dist["NonMaxSuppressionV5"],
+        backendName: "webgl",
+        kernelFunc: ({ inputs, backend, attrs }) => {
+          dist["backend_util"].warn(
+            "tf.nonMaxSuppression() in webgl locks the UI thread. " +
+              "Call tf.nonMaxSuppressionAsync() instead"
+          );
+          const { boxes, scores } = inputs;
+          const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;
+          const gpuBackend = backend;
+          const boxesVals = gpuBackend.readSync(boxes.dataId);
+          const scoresVals = gpuBackend.readSync(scores.dataId);
+          const maxOutputSizeVal = maxOutputSize;
+          const iouThresholdVal = iouThreshold;
+          const scoreThresholdVal = scoreThreshold;
+          const softNmsSigmaVal = softNmsSigma;
+          const { selectedIndices, selectedScores } = nonMaxSuppressionV5(
+            boxesVals,
+            scoresVals,
+            maxOutputSizeVal,
+            iouThresholdVal,
+            scoreThresholdVal,
+            softNmsSigmaVal
+          );
+          return [selectedIndices, selectedScores];
+        },
+      };
+      //# sourceMappingURL=NonMaxSuppressionV5.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Square.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const squareConfig = {
+        kernelName: dist["Square"],
+        backendName: "webgl",
+        kernelFunc: ({ inputs, backend }) => {
+          const { x } = inputs;
+          const webglBackend = backend;
+          const program = new UnaryOpProgram(x.shape, SQUARE);
+          return webglBackend.runWebGLProgram(program, [x], x.dtype);
+        },
+      };
+      //# sourceMappingURL=Square.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SquaredDifference.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const squaredDifferenceConfig = {
+        kernelName: dist["SquaredDifference"],
+        backendName: "webgl",
+        kernelFunc: ({ inputs, backend }) => {
+          const { a, b } = inputs;
+          const SQUARED_DIFFERENCE = "return (a - b) * (a - b);";
+          const webGLBackend = backend;
+          const program = Object(dist["env"])().getBool("WEBGL_PACK_BINARY_OPERATIONS")
+            ? new binaryop_packed_gpu_BinaryOpPackedProgram(SQUARED_DIFFERENCE, a.shape, b.shape)
+            : new binaryop_gpu_BinaryOpProgram(SQUARED_DIFFERENCE, a.shape, b.shape);
+          return webGLBackend.compileAndRun(program, [a, b]);
+        },
+      };
+      //# sourceMappingURL=SquaredDifference.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transpose.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const transposeConfig = {
+        kernelName: dist["Transpose"],
+        backendName: "webgl",
+        kernelFunc: ({ inputs, attrs, backend }) => {
+          const { x } = inputs;
+          const { perm } = attrs;
+          const webglBackend = backend;
+          const xRank = x.shape.length;
+          const newShape = new Array(xRank);
+          for (let i = 0; i < newShape.length; i++) {
+            newShape[i] = x.shape[perm[i]];
+          }
+          let out;
+          if (webglBackend.shouldExecuteOnCPU([x])) {
+            const xTexData = webglBackend.texData.get(x.dataId);
+            const values = xTexData.values;
+            const outValues = transposeImplCPU(values, x.shape, x.dtype, perm, newShape);
+            out = webglBackend.makeTensorInfo(newShape, x.dtype);
+            const outData = webglBackend.texData.get(out.dataId);
+            outData.values = outValues;
+          } else {
+            out = transposeImpl(x, perm, webglBackend);
+          }
+          return out;
+        },
+      };
+      //# sourceMappingURL=Transpose.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/register_all_kernels.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // List all kernel configs here
+      const kernelConfigs = [
+        maxConfig,
+        fromPixelsConfig,
+        divConfig,
+        nonMaxSuppressionV3Config,
+        nonMaxSuppressionV5Config,
+        squareConfig,
+        squaredDifferenceConfig,
+        transposeConfig,
+        maxPoolWithArgmaxConfig,
+      ];
+      for (const kernelConfig of kernelConfigs) {
+        Object(dist["registerKernel"])(kernelConfig);
+      }
+      //# sourceMappingURL=register_all_kernels.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // WebGL specific utils.
+
+      /**
+       * Enforce use of half precision textures if available on the platform.
+       */
+      /** @doc {heading: 'Environment', namespace: 'webgl'} */
+      function forceHalfFloat() {
+        Object(dist["env"])().set("WEBGL_FORCE_F16_TEXTURES", true);
+      }
+      //# sourceMappingURL=webgl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-webgl/dist/index.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      if (dist["device_util"].isBrowser()) {
+        Object(dist["registerBackend"])(
+          "webgl",
+          () => new backend_webgl_MathBackendWebGL(),
+          2 /* priority */
+        );
+      }
+
+      // Export webgl utilities
+
+      // Export forceHalfFlost under webgl namespace for the union bundle.
+
+      const webgl = { forceHalfFloat: forceHalfFloat };
+      //# sourceMappingURL=index.js.map
+
+      /***/
+    },
+    /* 87 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      // ESM COMPAT FLAG
+      __webpack_require__.r(__webpack_exports__);
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "CallbackList", function () {
+        return /* reexport */ CallbackList;
+      });
+      __webpack_require__.d(__webpack_exports__, "CustomCallback", function () {
+        return /* reexport */ base_callbacks_CustomCallback;
+      });
+      __webpack_require__.d(__webpack_exports__, "History", function () {
+        return /* reexport */ History;
+      });
+      __webpack_require__.d(__webpack_exports__, "Callback", function () {
+        return /* reexport */ callbacks_Callback;
+      });
+      __webpack_require__.d(__webpack_exports__, "callbacks", function () {
+        return /* reexport */ callbacks_callbacks;
+      });
+      __webpack_require__.d(__webpack_exports__, "EarlyStopping", function () {
+        return /* reexport */ callbacks_EarlyStopping;
+      });
+      __webpack_require__.d(__webpack_exports__, "InputSpec", function () {
+        return /* reexport */ InputSpec;
+      });
+      __webpack_require__.d(__webpack_exports__, "SymbolicTensor", function () {
+        return /* reexport */ topology_SymbolicTensor;
+      });
+      __webpack_require__.d(__webpack_exports__, "LayersModel", function () {
+        return /* reexport */ training_LayersModel;
+      });
+      __webpack_require__.d(__webpack_exports__, "input", function () {
+        return /* reexport */ exports_input;
+      });
+      __webpack_require__.d(__webpack_exports__, "loadLayersModel", function () {
+        return /* reexport */ loadLayersModel;
+      });
+      __webpack_require__.d(__webpack_exports__, "model", function () {
+        return /* reexport */ exports_model;
+      });
+      __webpack_require__.d(__webpack_exports__, "registerCallbackConstructor", function () {
+        return /* reexport */ registerCallbackConstructor;
+      });
+      __webpack_require__.d(__webpack_exports__, "sequential", function () {
+        return /* reexport */ sequential;
+      });
+      __webpack_require__.d(__webpack_exports__, "RNN", function () {
+        return /* reexport */ recurrent_RNN;
+      });
+      __webpack_require__.d(__webpack_exports__, "Sequential", function () {
+        return /* reexport */ models_Sequential;
+      });
+      __webpack_require__.d(__webpack_exports__, "LayerVariable", function () {
+        return /* reexport */ variables_LayerVariable;
+      });
+      __webpack_require__.d(__webpack_exports__, "version_layers", function () {
+        return /* reexport */ version;
+      });
+      __webpack_require__.d(__webpack_exports__, "constraints", function () {
+        return /* reexport */ exports_constraints_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "initializers", function () {
+        return /* reexport */ exports_initializers_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "layers", function () {
+        return /* reexport */ exports_layers_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "metrics", function () {
+        return /* reexport */ exports_metrics_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "models", function () {
+        return /* reexport */ exports_models_namespaceObject;
+      });
+      __webpack_require__.d(__webpack_exports__, "regularizers", function () {
+        return /* reexport */ exports_regularizers_namespaceObject;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_constraints.js
+      var exports_constraints_namespaceObject = {};
+      __webpack_require__.r(exports_constraints_namespaceObject);
+      __webpack_require__.d(exports_constraints_namespaceObject, "maxNorm", function () {
+        return maxNorm;
+      });
+      __webpack_require__.d(exports_constraints_namespaceObject, "unitNorm", function () {
+        return unitNorm;
+      });
+      __webpack_require__.d(exports_constraints_namespaceObject, "nonNeg", function () {
+        return nonNeg;
+      });
+      __webpack_require__.d(exports_constraints_namespaceObject, "minMaxNorm", function () {
+        return minMaxNorm;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_initializers.js
+      var exports_initializers_namespaceObject = {};
+      __webpack_require__.r(exports_initializers_namespaceObject);
+      __webpack_require__.d(exports_initializers_namespaceObject, "zeros", function () {
+        return zeros;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "ones", function () {
+        return exports_initializers_ones;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "constant", function () {
+        return constant;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "randomUniform", function () {
+        return randomUniform;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "randomNormal", function () {
+        return exports_initializers_randomNormal;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "truncatedNormal", function () {
+        return truncatedNormal;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "identity", function () {
+        return identity;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "varianceScaling", function () {
+        return varianceScaling;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "glorotUniform", function () {
+        return glorotUniform;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "glorotNormal", function () {
+        return glorotNormal;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "heNormal", function () {
+        return heNormal;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "heUniform", function () {
+        return heUniform;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "leCunNormal", function () {
+        return leCunNormal;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "leCunUniform", function () {
+        return leCunUniform;
+      });
+      __webpack_require__.d(exports_initializers_namespaceObject, "orthogonal", function () {
+        return orthogonal;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_layers.js
+      var exports_layers_namespaceObject = {};
+      __webpack_require__.r(exports_layers_namespaceObject);
+      __webpack_require__.d(exports_layers_namespaceObject, "inputLayer", function () {
+        return exports_layers_inputLayer;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "elu", function () {
+        return exports_layers_elu;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "reLU", function () {
+        return reLU;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "leakyReLU", function () {
+        return leakyReLU;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "prelu", function () {
+        return prelu;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "softmax", function () {
+        return softmax;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "thresholdedReLU", function () {
+        return thresholdedReLU;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "conv1d", function () {
+        return exports_layers_conv1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "conv2d", function () {
+        return exports_layers_conv2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "conv2dTranspose", function () {
+        return conv2dTranspose;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "conv3d", function () {
+        return exports_layers_conv3d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "separableConv2d", function () {
+        return separableConv2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "cropping2D", function () {
+        return cropping2D;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "upSampling2d", function () {
+        return upSampling2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "depthwiseConv2d", function () {
+        return exports_layers_depthwiseConv2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "activation", function () {
+        return exports_layers_activation;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "dense", function () {
+        return dense;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "dropout", function () {
+        return exports_layers_dropout;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "spatialDropout1d", function () {
+        return spatialDropout1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "flatten", function () {
+        return exports_layers_flatten;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "repeatVector", function () {
+        return repeatVector;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "reshape", function () {
+        return reshape;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "permute", function () {
+        return permute;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "embedding", function () {
+        return embedding;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "add", function () {
+        return exports_layers_add;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "average", function () {
+        return exports_layers_average;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "concatenate", function () {
+        return exports_layers_concatenate;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "maximum", function () {
+        return exports_layers_maximum;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "minimum", function () {
+        return exports_layers_minimum;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "multiply", function () {
+        return exports_layers_multiply;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "dot", function () {
+        return exports_layers_dot;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "batchNormalization", function () {
+        return exports_layers_batchNormalization;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "layerNormalization", function () {
+        return layerNormalization;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "zeroPadding2d", function () {
+        return zeroPadding2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "averagePooling1d", function () {
+        return averagePooling1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "avgPool1d", function () {
+        return avgPool1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "avgPooling1d", function () {
+        return avgPooling1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "averagePooling2d", function () {
+        return averagePooling2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "avgPool2d", function () {
+        return avgPool2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "avgPooling2d", function () {
+        return avgPooling2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "averagePooling3d", function () {
+        return averagePooling3d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "avgPool3d", function () {
+        return avgPool3d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "avgPooling3d", function () {
+        return avgPooling3d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "globalAveragePooling1d", function () {
+        return globalAveragePooling1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "globalAveragePooling2d", function () {
+        return globalAveragePooling2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "globalMaxPooling1d", function () {
+        return globalMaxPooling1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "globalMaxPooling2d", function () {
+        return globalMaxPooling2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "maxPooling1d", function () {
+        return maxPooling1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "maxPooling2d", function () {
+        return maxPooling2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "maxPooling3d", function () {
+        return maxPooling3d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "gru", function () {
+        return gru;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "gruCell", function () {
+        return gruCell;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "lstm", function () {
+        return lstm;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "lstmCell", function () {
+        return lstmCell;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "simpleRNN", function () {
+        return simpleRNN;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "simpleRNNCell", function () {
+        return simpleRNNCell;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "rnn", function () {
+        return exports_layers_rnn;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "stackedRNNCells", function () {
+        return stackedRNNCells;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "bidirectional", function () {
+        return bidirectional;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "timeDistributed", function () {
+        return timeDistributed;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "globalMaxPool1d", function () {
+        return globalMaxPool1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "globalMaxPool2d", function () {
+        return globalMaxPool2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "maxPool1d", function () {
+        return maxPool1d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "maxPool2d", function () {
+        return maxPool2d;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "Layer", function () {
+        return topology_Layer;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "RNN", function () {
+        return recurrent_RNN;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "RNNCell", function () {
+        return recurrent_RNNCell;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "input", function () {
+        return exports_input;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "gaussianNoise", function () {
+        return gaussianNoise;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "gaussianDropout", function () {
+        return gaussianDropout;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "alphaDropout", function () {
+        return alphaDropout;
+      });
+      __webpack_require__.d(exports_layers_namespaceObject, "masking", function () {
+        return masking;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_metrics.js
+      var exports_metrics_namespaceObject = {};
+      __webpack_require__.r(exports_metrics_namespaceObject);
+      __webpack_require__.d(exports_metrics_namespaceObject, "binaryAccuracy", function () {
+        return exports_metrics_binaryAccuracy;
+      });
+      __webpack_require__.d(exports_metrics_namespaceObject, "binaryCrossentropy", function () {
+        return exports_metrics_binaryCrossentropy;
+      });
+      __webpack_require__.d(
+        exports_metrics_namespaceObject,
+        "sparseCategoricalAccuracy",
+        function () {
+          return exports_metrics_sparseCategoricalAccuracy;
+        }
+      );
+      __webpack_require__.d(exports_metrics_namespaceObject, "categoricalAccuracy", function () {
+        return exports_metrics_categoricalAccuracy;
+      });
+      __webpack_require__.d(
+        exports_metrics_namespaceObject,
+        "categoricalCrossentropy",
+        function () {
+          return exports_metrics_categoricalCrossentropy;
+        }
+      );
+      __webpack_require__.d(exports_metrics_namespaceObject, "precision", function () {
+        return exports_metrics_precision;
+      });
+      __webpack_require__.d(exports_metrics_namespaceObject, "recall", function () {
+        return exports_metrics_recall;
+      });
+      __webpack_require__.d(exports_metrics_namespaceObject, "cosineProximity", function () {
+        return exports_metrics_cosineProximity;
+      });
+      __webpack_require__.d(exports_metrics_namespaceObject, "meanAbsoluteError", function () {
+        return exports_metrics_meanAbsoluteError;
+      });
+      __webpack_require__.d(
+        exports_metrics_namespaceObject,
+        "meanAbsolutePercentageError",
+        function () {
+          return exports_metrics_meanAbsolutePercentageError;
+        }
+      );
+      __webpack_require__.d(exports_metrics_namespaceObject, "MAPE", function () {
+        return exports_metrics_MAPE;
+      });
+      __webpack_require__.d(exports_metrics_namespaceObject, "mape", function () {
+        return exports_metrics_mape;
+      });
+      __webpack_require__.d(exports_metrics_namespaceObject, "meanSquaredError", function () {
+        return exports_metrics_meanSquaredError;
+      });
+      __webpack_require__.d(exports_metrics_namespaceObject, "MSE", function () {
+        return exports_metrics_MSE;
+      });
+      __webpack_require__.d(exports_metrics_namespaceObject, "mse", function () {
+        return exports_metrics_mse;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_models.js
+      var exports_models_namespaceObject = {};
+      __webpack_require__.r(exports_models_namespaceObject);
+      __webpack_require__.d(exports_models_namespaceObject, "modelFromJSON", function () {
+        return modelFromJSON;
+      });
+
+      // NAMESPACE OBJECT: ./node_modules/@tensorflow/tfjs-layers/dist/exports_regularizers.js
+      var exports_regularizers_namespaceObject = {};
+      __webpack_require__.r(exports_regularizers_namespaceObject);
+      __webpack_require__.d(exports_regularizers_namespaceObject, "l1l2", function () {
+        return l1l2;
+      });
+      __webpack_require__.d(exports_regularizers_namespaceObject, "l1", function () {
+        return exports_regularizers_l1;
+      });
+      __webpack_require__.d(exports_regularizers_namespaceObject, "l2", function () {
+        return exports_regularizers_l2;
+      });
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
+      var dist = __webpack_require__(0);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/backend/common.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      let _epsilon;
+      /**
+       * Returns the value of the fuzz factor used in numeric expressions.
+       */
+      function common_epsilon() {
+        if (_epsilon == null) {
+          _epsilon = Object(dist["backend"])().epsilon();
+        }
+        return _epsilon;
+      }
+      /**
+       * Sets the value of the fuzz factor used in numeric expressions.
+       * @param e New value of epsilon.
+       */
+      function setEpsilon(e) {
+        _epsilon = e;
+      }
+      /**
+       * Returns the default image data format convention.
+       */
+      function imageDataFormat() {
+        return "channelsLast";
+      }
+      //# sourceMappingURL=common.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/errors.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Explicit error types.
+       *
+       * See the following link for more information about why the code includes
+       * calls to setPrototypeOf:
+       *
+       * https://github.com/Microsoft/TypeScript-wiki/blob/master/Breaking-Changes.md#extending-built-ins-like-error-array-and-map-may-no-longer-work
+       */
+      // tslint:enable
+      /**
+       * Equivalent of Python's AttributeError.
+       */
+      class AttributeError extends Error {
+        constructor(message) {
+          super(message);
+          // Set the prototype explicitly.
+          Object.setPrototypeOf(this, AttributeError.prototype);
+        }
+      }
+      /**
+       * Equivalent of Python's RuntimeError.
+       */
+      class RuntimeError extends Error {
+        constructor(message) {
+          super(message);
+          // Set the prototype explicitly.
+          Object.setPrototypeOf(this, RuntimeError.prototype);
+        }
+      }
+      /**
+       * Equivalent of Python's ValueError.
+       */
+      class ValueError extends Error {
+        constructor(message) {
+          super(message);
+          // Set the prototype explicitly.
+          Object.setPrototypeOf(this, ValueError.prototype);
+        }
+      }
+      /**
+       * Equivalent of Python's NotImplementedError.
+       */
+      class NotImplementedError extends Error {
+        constructor(message) {
+          super(message);
+          // Set the prototype explicitly.
+          Object.setPrototypeOf(this, NotImplementedError.prototype);
+        }
+      }
+      /**
+       * Equivalent of Python's AssertionError.
+       */
+      class AssertionError extends Error {
+        constructor(message) {
+          super(message);
+          // Set the prototype explicitly.
+          Object.setPrototypeOf(this, AssertionError.prototype);
+        }
+      }
+      /**
+       * Equivalent of Python's IndexError.
+       */
+      class IndexError extends Error {
+        constructor(message) {
+          super(message);
+          // Set the prototype explicitly.
+          Object.setPrototypeOf(this, IndexError.prototype);
+        }
+      }
+      //# sourceMappingURL=errors.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/generic_utils.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original source: utils/generic_utils.py */
+
+      // tslint:enable
+      /**
+       * If `value` is an Array, equivalent to Python's `value * numValues`.
+       * If `value` is not an Array, equivalent to Python's `[value] * numValues`
+       */
+      // tslint:disable-next-line:no-any
+      function pyListRepeat(value, numValues) {
+        if (Array.isArray(value)) {
+          // tslint:disable-next-line:no-any
+          let newArray = [];
+          for (let i = 0; i < numValues; i++) {
+            newArray = newArray.concat(value);
+          }
+          return newArray;
+        } else {
+          const newArray = new Array(numValues);
+          newArray.fill(value);
+          return newArray;
+        }
+      }
+      function assert(val, message) {
+        if (!val) {
+          throw new AssertionError(message);
+        }
+      }
+      /**
+       * Count the number of elements of the `array` that are equal to `reference`.
+       */
+      function generic_utils_count(array, refernce) {
+        let counter = 0;
+        for (const item of array) {
+          if (item === refernce) {
+            counter++;
+          }
+        }
+        return counter;
+      }
+      /**
+       * If an array is of length 1, just return the first element. Otherwise, return
+       * the full array.
+       * @param tensors
+       */
+      function singletonOrArray(xs) {
+        if (xs.length === 1) {
+          return xs[0];
+        }
+        return xs;
+      }
+      /**
+       * Normalizes a list/tensor into a list.
+       *
+       * If a tensor is passed, we return
+       * a list of size 1 containing the tensor.
+       *
+       * @param x target object to be normalized.
+       */
+      // tslint:disable-next-line:no-any
+      function toList(x) {
+        if (Array.isArray(x)) {
+          return x;
+        }
+        return [x];
+      }
+      /**
+       * Generate a UID for a list
+       */
+      // tslint:disable-next-line:no-any
+      function objectListUid(objs) {
+        const objectList = toList(objs);
+        let retVal = "";
+        for (const obj of objectList) {
+          if (obj.id == null) {
+            throw new ValueError(`Object ${obj} passed to objectListUid without an id`);
+          }
+          if (retVal !== "") {
+            retVal = retVal + ", ";
+          }
+          retVal = `${retVal}${Math.abs(obj.id)}`;
+        }
+        return retVal;
+      }
+      /**
+       * Converts string to snake-case.
+       * @param name
+       */
+      function toSnakeCase(name) {
+        const intermediate = name.replace(/(.)([A-Z][a-z0-9]+)/g, "$1_$2");
+        const insecure = intermediate.replace(/([a-z])([A-Z])/g, "$1_$2").toLowerCase();
+        /*
+     If the class is private the name starts with "_" which is not secure
+     for creating scopes. We prefix the name with "private" in this case.
+     */
+        if (insecure[0] !== "_") {
+          return insecure;
+        }
+        return "private" + insecure;
+      }
+      function toCamelCase(identifier) {
+        // quick return for empty string or single character strings
+        if (identifier.length <= 1) {
+          return identifier;
+        }
+        // Check for the underscore indicating snake_case
+        if (identifier.indexOf("_") === -1) {
+          return identifier;
+        }
+        return identifier.replace(/[_]+(\w|$)/g, (m, p1) => p1.toUpperCase());
+      }
+      // tslint:disable-next-line:no-any
+      let _GLOBAL_CUSTOM_OBJECTS = {};
+      function serializeKerasObject(instance) {
+        if (instance === null || instance === undefined) {
+          return null;
+        }
+        const dict = {};
+        dict["className"] = instance.getClassName();
+        dict["config"] = instance.getConfig();
+        return dict;
+      }
+      /**
+       * Replace ndarray-style scalar objects in serialization objects with numbers.
+       *
+       * Background: In some versions of tf.keras, certain scalar values in the HDF5
+       * model save file can be serialized as: `{'type': 'ndarray', 'value': num}`,
+       * where in `num` is a plain number. This method converts such serialization
+       * to a `number`.
+       *
+       * @param config The keras-format serialization object to be processed
+       *   (in place).
+       */
+      function convertNDArrayScalarsInConfig(config) {
+        if (config == null || typeof config !== "object") {
+          return;
+        } else if (Array.isArray(config)) {
+          config.forEach((configItem) => convertNDArrayScalarsInConfig(configItem));
+        } else {
+          const fields = Object.keys(config);
+          for (const field of fields) {
+            const value = config[field];
+            if (value != null && typeof value === "object") {
+              if (
+                !Array.isArray(value) &&
+                value["type"] === "ndarray" &&
+                typeof value["value"] === "number"
+              ) {
+                config[field] = value["value"];
+              } else {
+                convertNDArrayScalarsInConfig(value);
+              }
+            }
+          }
+        }
+      }
+      /**
+       * Deserialize a saved Keras Object
+       * @param identifier either a string ID or a saved Keras dictionary
+       * @param moduleObjects a list of Python class names to object constructors
+       * @param customObjects a list of Python class names to object constructors
+       * @param printableModuleName debug text for the object being reconstituted
+       * @param fastWeightInit Optional flag to use fast weight initialization
+       *   during deserialization. This is applicable to cases in which
+       *   the initialization will be immediately overwritten by loaded weight
+       *   values. Default: `false`.
+       * @returns a TensorFlow.js Layers object
+       */
+      // tslint:disable:no-any
+      function deserializeKerasObject(
+        identifier,
+        moduleObjects = {},
+        customObjects = {},
+        printableModuleName = "object",
+        fastWeightInit = false
+      ) {
+        // tslint:enable
+        if (typeof identifier === "string") {
+          const functionName = identifier;
+          let fn;
+          if (functionName in customObjects) {
+            fn = customObjects[functionName];
+          } else if (functionName in _GLOBAL_CUSTOM_OBJECTS) {
+            fn = _GLOBAL_CUSTOM_OBJECTS[functionName];
+          } else {
+            fn = moduleObjects[functionName];
+            if (fn == null) {
+              throw new ValueError(
+                `Unknown ${printableModuleName}: ${identifier}. ` +
+                  `This may be due to one of the following reasons:\n` +
+                  `1. The ${printableModuleName} is defined in Python, in which ` +
+                  `case it needs to be ported to TensorFlow.js or your JavaScript ` +
+                  `code.\n` +
+                  `2. The custom ${printableModuleName} is defined in JavaScript, ` +
+                  `but is not registered properly with ` +
+                  `tf.serialization.registerClass().`
+              );
+              // TODO(cais): Add link to tutorial page on custom layers.
+            }
+          }
+          return fn;
+        } else {
+          // In this case we are dealing with a Keras config dictionary.
+          const config = identifier;
+          if (config["className"] == null || config["config"] == null) {
+            throw new ValueError(
+              `${printableModuleName}: Improper config format: ` +
+                `${JSON.stringify(config)}.\n` +
+                `'className' and 'config' must set.`
+            );
+          }
+          const className = config["className"];
+          let cls, fromConfig;
+          if (className in customObjects) {
+            [cls, fromConfig] = customObjects[className];
+          } else if (className in _GLOBAL_CUSTOM_OBJECTS) {
+            [cls, fromConfig] = _GLOBAL_CUSTOM_OBJECTS["className"];
+          } else if (className in moduleObjects) {
+            [cls, fromConfig] = moduleObjects[className];
+          }
+          if (cls == null) {
+            throw new ValueError(
+              `Unknown ${printableModuleName}: ${className}. ` +
+                `This may be due to one of the following reasons:\n` +
+                `1. The ${printableModuleName} is defined in Python, in which ` +
+                `case it needs to be ported to TensorFlow.js or your JavaScript ` +
+                `code.\n` +
+                `2. The custom ${printableModuleName} is defined in JavaScript, ` +
+                `but is not registered properly with ` +
+                `tf.serialization.registerClass().`
+            );
+            // TODO(cais): Add link to tutorial page on custom layers.
+          }
+          if (fromConfig != null) {
+            // Porting notes: Instead of checking to see whether fromConfig accepts
+            // customObjects, we create a customObjects dictionary and tack it on to
+            // config['config'] as config['config'].customObjects. Objects can use it,
+            // if they want.
+            // tslint:disable-next-line:no-any
+            const customObjectsCombined = {};
+            for (const key of Object.keys(_GLOBAL_CUSTOM_OBJECTS)) {
+              customObjectsCombined[key] = _GLOBAL_CUSTOM_OBJECTS[key];
+            }
+            for (const key of Object.keys(customObjects)) {
+              customObjectsCombined[key] = customObjects[key];
+            }
+            // Add the customObjects to config
+            const nestedConfig = config["config"];
+            nestedConfig["customObjects"] = customObjectsCombined;
+            const backupCustomObjects = Object.assign({}, _GLOBAL_CUSTOM_OBJECTS);
+            for (const key of Object.keys(customObjects)) {
+              _GLOBAL_CUSTOM_OBJECTS[key] = customObjects[key];
+            }
+            convertNDArrayScalarsInConfig(config["config"]);
+            const returnObj = fromConfig(cls, config["config"], customObjects, fastWeightInit);
+            _GLOBAL_CUSTOM_OBJECTS = Object.assign({}, backupCustomObjects);
+            return returnObj;
+          } else {
+            // Then `cls` may be a function returning a class.
+            // In this case by convention `config` holds
+            // the kwargs of the function.
+            const backupCustomObjects = Object.assign({}, _GLOBAL_CUSTOM_OBJECTS);
+            for (const key of Object.keys(customObjects)) {
+              _GLOBAL_CUSTOM_OBJECTS[key] = customObjects[key];
+            }
+            // In python this is **config['config'], for tfjs-layers we require
+            // classes that use this fall-through construction method to take
+            // a config interface that mimics the expansion of named parameters.
+            const returnObj = new cls(config["config"]);
+            _GLOBAL_CUSTOM_OBJECTS = Object.assign({}, backupCustomObjects);
+            return returnObj;
+          }
+        }
+      }
+      /**
+       * Compares two numbers for sorting.
+       * @param a
+       * @param b
+       */
+      function numberCompare(a, b) {
+        return a < b ? -1 : a > b ? 1 : 0;
+      }
+      /**
+       * Comparison of two numbers for reverse sorting.
+       * @param a
+       * @param b
+       */
+      function reverseNumberCompare(a, b) {
+        return -1 * numberCompare(a, b);
+      }
+      /**
+       * Convert a string into the corresponding DType.
+       * @param dtype
+       * @returns An instance of DType.
+       */
+      function stringToDType(dtype) {
+        switch (dtype) {
+          case "float32":
+            return "float32";
+          default:
+            throw new ValueError(`Invalid dtype: ${dtype}`);
+        }
+      }
+      /**
+       * Test the element-by-element equality of two Arrays of strings.
+       * @param xs First array of strings.
+       * @param ys Second array of strings.
+       * @returns Wether the two arrays are all equal, element by element.
+       */
+      function stringsEqual(xs, ys) {
+        if (xs == null || ys == null) {
+          return xs === ys;
+        }
+        if (xs.length !== ys.length) {
+          return false;
+        }
+        for (let i = 0; i < xs.length; ++i) {
+          if (xs[i] !== ys[i]) {
+            return false;
+          }
+        }
+        return true;
+      }
+      /**
+       * Get the unique elements of an array.
+       * @param xs Array.
+       * @returns An Array consisting of the unique elements in `xs`.
+       */
+      function unique(xs) {
+        if (xs == null) {
+          return xs;
+        }
+        const out = [];
+        // TODO(cais): Maybe improve performance by sorting.
+        for (const x of xs) {
+          if (out.indexOf(x) === -1) {
+            out.push(x);
+          }
+        }
+        return out;
+      }
+      /**
+       * Determine if an Object is empty (i.e., does not have own properties).
+       * @param obj Object
+       * @returns Whether the Object is empty.
+       * @throws ValueError: If object is `null` or `undefined`.
+       */
+      function isObjectEmpty(obj) {
+        if (obj == null) {
+          throw new ValueError(`Invalid value in obj: ${JSON.stringify(obj)}`);
+        }
+        for (const key in obj) {
+          if (obj.hasOwnProperty(key)) {
+            return false;
+          }
+        }
+        return true;
+      }
+      /**
+       * Helper function used to build type union/enum run-time checkers.
+       * @param values The list of allowed values.
+       * @param label A string name for the type
+       * @param value The value to test.
+       * @throws ValueError: If the value is not in values nor `undefined`/`null`.
+       */
+      function checkStringTypeUnionValue(values, label, value) {
+        if (value == null) {
+          return;
+        }
+        if (values.indexOf(value) < 0) {
+          throw new ValueError(
+            `${value} is not a valid ${label}.  Valid values are ${values} or null/undefined.`
+          );
+        }
+      }
+      /**
+       * Helper function for verifying the types of inputs.
+       *
+       * Ensures that the elements of `x` are all of type `expectedType`.
+       * Also verifies that the length of `x` is within bounds.
+       *
+       * @param x Object to test.
+       * @param expectedType The string expected type of all of the elements in the
+       * Array.
+       * @param minLength Return false if x.length is less than this.
+       * @param maxLength Return false if x.length is greater than this.
+       * @returns true if and only if `x` is an `Array<expectedType>` with
+       * length >= `minLength` and <= `maxLength`.
+       */
+      // tslint:disable:no-any
+      function checkArrayTypeAndLength(x, expectedType, minLength = 0, maxLength = Infinity) {
+        assert(minLength >= 0);
+        assert(maxLength >= minLength);
+        return (
+          Array.isArray(x) &&
+          x.length >= minLength &&
+          x.length <= maxLength &&
+          x.every((e) => typeof e === expectedType)
+        );
+      }
+      // tslint:enable:no-any
+      /**
+       * Assert that a value or an array of value are positive integer.
+       *
+       * @param value The value being asserted on. May be a single number or an array
+       *   of numbers.
+       * @param name Name of the value, used to make the error message.
+       */
+      function assertPositiveInteger(value, name) {
+        if (Array.isArray(value)) {
+          dist["util"].assert(value.length > 0, () => `${name} is unexpectedly an empty array.`);
+          value.forEach((v, i) => assertPositiveInteger(v, `element ${i + 1} of ${name}`));
+        } else {
+          dist["util"].assert(
+            Number.isInteger(value) && value > 0,
+            () =>
+              `Expected ${name} to be a positive integer, but got ` +
+              `${formatAsFriendlyString(value)}.`
+          );
+        }
+      }
+      /**
+       * Format a value into a display-friendly, human-readable fashion.
+       *
+       * - `null` is formatted as `'null'`
+       * - Strings are formated with flanking pair of quotes.
+       * - Arrays are formatted with flanking pair of square brackets.
+       *
+       * @param value The value to display.
+       * @return Formatted string.
+       */
+      // tslint:disable-next-line:no-any
+      function formatAsFriendlyString(value) {
+        if (value === null) {
+          return "null";
+        } else if (Array.isArray(value)) {
+          return "[" + value.map((v) => formatAsFriendlyString(v)).join(",") + "]";
+        } else if (typeof value === "string") {
+          return `"${value}"`;
+        } else {
+          return `${value}`;
+        }
+      }
+      /**
+       * Returns a function `f2` (decorator) which wraps the original function
+       * `f`. `f2` guarantees that `f` can be called at most once
+       * every `waitMs` ms. If `f2` is called more often, it will return
+       * the last returned result of `f`.
+       *
+       * @param f The original function `f` to wrap.
+       * @param waitMs The time between two consecutive calls to `f` in ms.
+       */
+      function debounce(f, waitMs) {
+        let lastTime = dist["util"].now();
+        let lastResult;
+        const f2 = (...args) => {
+          const now = dist["util"].now();
+          if (now - lastTime < waitMs) {
+            return lastResult;
+          }
+          lastTime = now;
+          lastResult = f(...args);
+          return lastResult;
+        };
+        return f2;
+      }
+      /**
+       * Returns the fusable activation given a layers identifier.
+       *
+       * @param activationName The layers identifier string.
+       * @return The name of the fusable activation.
+       */
+      function mapActivationToFusedKernel(activationName) {
+        if (activationName === "relu") {
+          return "relu";
+        }
+        if (activationName === "linear") {
+          return "linear";
+        }
+        if (activationName === "elu") {
+          return "elu";
+        }
+        return null;
+      }
+      //# sourceMappingURL=generic_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/constraints.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original source: keras/contraints.py */
+
+      /**
+       * Helper function used by many of the Constraints to find the L2Norms.
+       */
+      function calcL2Norms(w, axis) {
+        return Object(dist["tidy"])(() => dist["sqrt"](dist["sum"](dist["mul"](w, w), axis, true)));
+      }
+      /**
+       * Base class for functions that impose constraints on weight values
+       */
+      /**
+       * @doc {
+       *   heading: 'Constraints',
+       *   subheading: 'Classes',
+       *   namespace: 'constraints'
+       * }
+       */
+      class constraints_Constraint extends dist["serialization"].Serializable {
+        getConfig() {
+          return {};
+        }
+      }
+      class constraints_MaxNorm extends constraints_Constraint {
+        constructor(args) {
+          super();
+          this.defaultMaxValue = 2;
+          this.defaultAxis = 0;
+          this.maxValue = args.maxValue != null ? args.maxValue : this.defaultMaxValue;
+          this.axis = args.axis != null ? args.axis : this.defaultAxis;
+        }
+        apply(w) {
+          return Object(dist["tidy"])(() => {
+            const norms = calcL2Norms(w, this.axis);
+            const desired = dist["clipByValue"](norms, 0, this.maxValue);
+            return dist["mul"](w, dist["div"](desired, dist["add"](common_epsilon(), norms)));
+          });
+        }
+        getConfig() {
+          return { maxValue: this.maxValue, axis: this.axis };
+        }
+      }
+      /** @nocollapse */
+      constraints_MaxNorm.className = "MaxNorm";
+      dist["serialization"].registerClass(constraints_MaxNorm);
+      class constraints_UnitNorm extends constraints_Constraint {
+        constructor(args) {
+          super();
+          this.defaultAxis = 0;
+          this.axis = args.axis != null ? args.axis : this.defaultAxis;
+        }
+        apply(w) {
+          return Object(dist["tidy"])(() =>
+            dist["div"](w, dist["add"](common_epsilon(), calcL2Norms(w, this.axis)))
+          );
+        }
+        getConfig() {
+          return { axis: this.axis };
+        }
+      }
+      /** @nocollapse */
+      constraints_UnitNorm.className = "UnitNorm";
+      dist["serialization"].registerClass(constraints_UnitNorm);
+      class constraints_NonNeg extends constraints_Constraint {
+        apply(w) {
+          return dist["relu"](w);
+        }
+      }
+      /** @nocollapse */
+      constraints_NonNeg.className = "NonNeg";
+      dist["serialization"].registerClass(constraints_NonNeg);
+      class constraints_MinMaxNorm extends constraints_Constraint {
+        constructor(args) {
+          super();
+          this.defaultMinValue = 0.0;
+          this.defaultMaxValue = 1.0;
+          this.defaultRate = 1.0;
+          this.defaultAxis = 0;
+          this.minValue = args.minValue != null ? args.minValue : this.defaultMinValue;
+          this.maxValue = args.maxValue != null ? args.maxValue : this.defaultMaxValue;
+          this.rate = args.rate != null ? args.rate : this.defaultRate;
+          this.axis = args.axis != null ? args.axis : this.defaultAxis;
+        }
+        apply(w) {
+          return Object(dist["tidy"])(() => {
+            const norms = calcL2Norms(w, this.axis);
+            const desired = dist["add"](
+              dist["mul"](this.rate, dist["clipByValue"](norms, this.minValue, this.maxValue)),
+              dist["mul"](1.0 - this.rate, norms)
+            );
+            return dist["mul"](w, dist["div"](desired, dist["add"](common_epsilon(), norms)));
+          });
+        }
+        getConfig() {
+          return {
+            minValue: this.minValue,
+            maxValue: this.maxValue,
+            rate: this.rate,
+            axis: this.axis,
+          };
+        }
+      }
+      /** @nocollapse */
+      constraints_MinMaxNorm.className = "MinMaxNorm";
+      dist["serialization"].registerClass(constraints_MinMaxNorm);
+      // Maps the JavaScript-like identifier keys to the corresponding registry
+      // symbols.
+      const CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP = {
+        maxNorm: "MaxNorm",
+        minMaxNorm: "MinMaxNorm",
+        nonNeg: "NonNeg",
+        unitNorm: "UnitNorm",
+      };
+      function serializeConstraint(constraint) {
+        return serializeKerasObject(constraint);
+      }
+      function deserializeConstraint(config, customObjects = {}) {
+        return deserializeKerasObject(
+          config,
+          dist["serialization"].SerializationMap.getMap().classNameMap,
+          customObjects,
+          "constraint"
+        );
+      }
+      function getConstraint(identifier) {
+        if (identifier == null) {
+          return null;
+        }
+        if (typeof identifier === "string") {
+          const className =
+            identifier in CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP
+              ? CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier]
+              : identifier;
+          const config = { className, config: {} };
+          return deserializeConstraint(config);
+        } else if (identifier instanceof constraints_Constraint) {
+          return identifier;
+        } else {
+          return deserializeConstraint(identifier);
+        }
+      }
+      //# sourceMappingURL=constraints.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_constraints.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      // tslint:disable-next-line:max-line-length
+
+      /**
+       * MaxNorm weight constraint.
+       *
+       * Constrains the weights incident to each hidden unit
+       * to have a norm less than or equal to a desired value.
+       *
+       * References
+       *       - [Dropout: A Simple Way to Prevent Neural Networks from Overfitting
+       * Srivastava, Hinton, et al.
+       * 2014](http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf)
+       */
+      /** @doc {heading: 'Constraints',namespace: 'constraints'} */
+      function maxNorm(args) {
+        return new constraints_MaxNorm(args);
+      }
+      /**
+       * Constrains the weights incident to each hidden unit to have unit norm.
+       */
+      /** @doc {heading: 'Constraints', namespace: 'constraints'} */
+      function unitNorm(args) {
+        return new constraints_UnitNorm(args);
+      }
+      /**
+       * Constains the weight to be non-negative.
+       */
+      /** @doc {heading: 'Constraints', namespace: 'constraints'} */
+      function nonNeg() {
+        return new constraints_NonNeg();
+      }
+      /** @doc {heading: 'Constraints', namespace: 'constraints'} */
+      function minMaxNorm(config) {
+        return new constraints_MinMaxNorm(config);
+      }
+      //# sourceMappingURL=exports_constraints.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/keras_format/common.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      const VALID_DATA_FORMAT_VALUES = ["channelsFirst", "channelsLast"];
+      const VALID_PADDING_MODE_VALUES = ["valid", "same", "causal"];
+      const VALID_POOL_MODE_VALUES = ["max", "avg"];
+      const VALID_BIDIRECTIONAL_MERGE_MODES = ["sum", "mul", "concat", "ave"];
+      const VALID_SAMPLE_WEIGHT_MODES = ["temporal"];
+      //# sourceMappingURL=common.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/common.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Common functions for TensorFlow.js Layers.
+       */
+
+      // A map from the requested scoped name of a Tensor to the number of Tensors
+      // wanting that name so far.  This allows enforcing name uniqueness by appending
+      // an incrementing index, e.g. scope/name, scope/name_1, scope/name_2, etc.
+      const nameMap = new Map();
+      function checkDataFormat(value) {
+        checkStringTypeUnionValue(VALID_DATA_FORMAT_VALUES, "DataFormat", value);
+      }
+      function checkPaddingMode(value) {
+        checkStringTypeUnionValue(VALID_PADDING_MODE_VALUES, "PaddingMode", value);
+      }
+      function checkPoolMode(value) {
+        checkStringTypeUnionValue(VALID_POOL_MODE_VALUES, "PoolMode", value);
+      }
+      const _nameScopeStack = [];
+      const _nameScopeDivider = "/";
+      /**
+       * Enter namescope, which can be nested.
+       */
+      function nameScope(name, fn) {
+        _nameScopeStack.push(name);
+        try {
+          const val = fn();
+          _nameScopeStack.pop();
+          return val;
+        } catch (e) {
+          _nameScopeStack.pop();
+          throw e;
+        }
+      }
+      /**
+       * Get the current namescope as a flat, concatenated string.
+       */
+      function currentNameScopePrefix() {
+        if (_nameScopeStack.length === 0) {
+          return "";
+        } else {
+          return _nameScopeStack.join(_nameScopeDivider) + _nameScopeDivider;
+        }
+      }
+      /**
+       * Get the name a Tensor (or Variable) would have if not uniqueified.
+       * @param tensorName
+       * @return Scoped name string.
+       */
+      function getScopedTensorName(tensorName) {
+        if (!isValidTensorName(tensorName)) {
+          throw new Error("Not a valid tensor name: '" + tensorName + "'");
+        }
+        return currentNameScopePrefix() + tensorName;
+      }
+      /**
+       * Get unique names for Tensors and Variables.
+       * @param scopedName The fully-qualified name of the Tensor, i.e. as produced by
+       *  `getScopedTensorName()`.
+       * @return A unique version of the given fully scoped name.
+       *   If this is the first time that the scoped name is seen in this session,
+       *   then the given `scopedName` is returned unaltered.  If the same name is
+       *   seen again (producing a collision), an incrementing suffix is added to the
+       *   end of the name, so it takes the form 'scope/name_1', 'scope/name_2', etc.
+       */
+      function getUniqueTensorName(scopedName) {
+        if (!isValidTensorName(scopedName)) {
+          throw new Error("Not a valid tensor name: '" + scopedName + "'");
+        }
+        if (!nameMap.has(scopedName)) {
+          nameMap.set(scopedName, 0);
+        }
+        const index = nameMap.get(scopedName);
+        nameMap.set(scopedName, nameMap.get(scopedName) + 1);
+        if (index > 0) {
+          const result = `${scopedName}_${index}`;
+          // Mark the composed name as used in case someone wants
+          // to call getUniqueTensorName("name_1").
+          nameMap.set(result, 1);
+          return result;
+        } else {
+          return scopedName;
+        }
+      }
+      const tensorNameRegex = new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);
+      /**
+       * Determine whether a string is a valid tensor name.
+       * @param name
+       * @returns A Boolean indicating whether `name` is a valid tensor name.
+       */
+      function isValidTensorName(name) {
+        return !!name.match(tensorNameRegex);
+      }
+      //# sourceMappingURL=common.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/math_utils.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Math utility functions.
+       *
+       * This file contains some frequently used math function that operates on
+       * number[] or Float32Array and return a number. Many of these functions are
+       * not-so-thick wrappers around TF.js Core functions. But they offer the
+       * convenience of
+       * 1) not having to convert the inputs into Tensors,
+       * 2) not having to convert the returned Tensors to numbers.
+       */
+
+      /**
+       * Determine if a number is an integer.
+       */
+      function isInteger(x) {
+        return x === parseInt(x.toString(), 10);
+      }
+      /**
+       * Calculate the product of an array of numbers.
+       * @param array The array to calculate the product over.
+       * @param begin Beginning index, inclusive.
+       * @param end Ending index, exclusive.
+       * @return The product.
+       */
+      function arrayProd(array, begin, end) {
+        if (begin == null) {
+          begin = 0;
+        }
+        if (end == null) {
+          end = array.length;
+        }
+        let prod = 1;
+        for (let i = begin; i < end; ++i) {
+          prod *= array[i];
+        }
+        return prod;
+      }
+      /**
+       * A helper function transforms the two input types to an instance of Tensor1D,
+       * so the return value can be fed directly into various TF.js Core functions.
+       * @param array
+       */
+      function toArray1D(array) {
+        array = Array.isArray(array) ? new Float32Array(array) : array;
+        return Object(dist["tensor1d"])(array);
+      }
+      /**
+       * Compute minimum value.
+       * @param array
+       * @return minimum value.
+       */
+      function min(array) {
+        return dist["min"](toArray1D(array)).dataSync()[0];
+      }
+      /**
+       * Compute maximum value.
+       * @param array
+       * @return maximum value
+       */
+      function max(array) {
+        return dist["max"](toArray1D(array)).dataSync()[0];
+      }
+      /**
+       * Compute sum of array.
+       * @param array
+       * @return The sum.
+       */
+      function sum(array) {
+        return dist["sum"](toArray1D(array)).dataSync()[0];
+      }
+      /**
+       * Compute mean of array.
+       * @param array
+       * @return The mean.
+       */
+      function math_utils_mean(array) {
+        return sum(array) / array.length;
+      }
+      /**
+       * Compute variance of array.
+       * @param array
+       * @return The variance.
+       */
+      function math_utils_variance(array) {
+        const demeaned = dist["sub"](
+          toArray1D(array),
+          Object(dist["scalar"])(math_utils_mean(array))
+        );
+        const sumSquare = dist["sum"](dist["mul"](demeaned, demeaned)).dataSync()[0];
+        return sumSquare / array.length;
+      }
+      /**
+       * Compute median of array.
+       * @param array
+       * @return The median value.
+       */
+      function median(array) {
+        const arraySorted = array.slice().sort((a, b) => a - b);
+        const lowIdx = Math.floor((arraySorted.length - 1) / 2);
+        const highIdx = Math.ceil((arraySorted.length - 1) / 2);
+        if (lowIdx === highIdx) {
+          return arraySorted[lowIdx];
+        }
+        return (arraySorted[lowIdx] + arraySorted[highIdx]) / 2;
+      }
+      /**
+       * Generate an array of integers in [begin, end).
+       * @param begin Beginning integer, inclusive.
+       * @param end Ending integer, exclusive.
+       * @returns Range array.
+       * @throws ValueError, iff `end` < `begin`.
+       */
+      function range(begin, end) {
+        if (end < begin) {
+          throw new ValueError(`end (${end}) < begin (${begin}) is forbidden.`);
+        }
+        const out = [];
+        for (let i = begin; i < end; ++i) {
+          out.push(i);
+        }
+        return out;
+      }
+      //# sourceMappingURL=math_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/backend/tfjs_backend.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * deeplearn.js backend.
+       */
+
+      // tslint:enable
+      /* Setting and getting backend from deeplearn.js. */
+      // Default deeplearn.js backend is WebGL (GPU).
+      let backend = "webgl";
+      function setBackend(requestedBackend) {
+        dist["setBackend"](requestedBackend);
+        backend = requestedBackend;
+      }
+      function getBackend() {
+        return backend;
+      }
+      /**
+       * Indicates whether the backend is operating symbolically.
+       *
+       * This function will be used to determine how to interpret user code. If
+       * it returns true, calls to the backend construct a symbolic graph; if
+       * it returns false, calls to the backend execute immediately.
+       */
+      function isBackendSymbolic() {
+        return false;
+      }
+      /**
+       * Get the number of elements in a Tensor.
+       * @param x The Tensor.
+       * @return Number of elements in `x`.
+       */
+      function countParams(x) {
+        const shape = x.shape;
+        if (shape.length > 0) {
+          return shape.reduce((a, b) => a * b);
+        } else {
+          // Scalar.
+          return 1;
+        }
+      }
+      /**
+       * Casts a tensor to a different dtype and returns it.
+       * @param x Input tensor.
+       * @param dtype String: 'float32'|'int32'|'bool'.
+       * @returns Tensor of the specified `dtype`.
+       */
+      function cast(x, dtype) {
+        return x.asType(dtype);
+      }
+      /**
+       * Adds a 1-sized dimension at index "axis".
+       * @param x Input tensor.
+       * @param axis Position where to add the new axis.
+       * @returns Result of the dimension expansion.
+       */
+      function expandDims(x, axis = -1) {
+        const outShape = x.shape.slice();
+        if (axis < 0) {
+          axis = outShape.length + axis + 1;
+        }
+        outShape.splice(axis, 0, 1);
+        return x.reshape(outShape);
+      }
+      /**
+       * Repeats a 2D tensor.
+       *
+       * If `x` has shape `[samples, dim]` and `n` is 2, for example, the output
+       * will have shape `[samples, 2, dim]`.
+       *
+       * @param x Input tensor.
+       * @param n Integer, number of times to repeat.
+       * @returns The result of the repeat operation.
+       * @throws ValueError: If input tensor is not 2D.
+       */
+      function repeat(x, n) {
+        return Object(dist["tidy"])(() => {
+          if (x.shape.length !== 2) {
+            throw new ValueError(
+              `repeat() expects a rank-2 tensor, but received a ` + `rank-${x.shape.length} tensor.`
+            );
+          }
+          const y = expandDims(x, 1);
+          return tile(y, [1, n, 1]);
+        });
+      }
+      /**
+       * Flatten a Tensor into 1D.
+       * @param x Input tensor.
+       * @return The result of the flattening `x`.
+       */
+      function flatten(x) {
+        const newShape = [arrayProd(x.shape)];
+        return x.reshape(newShape);
+      }
+      /**
+       * Turn a nD tensor into a 2D tensor with same 0th dimension.
+       * In other words, it flattens each data samples of a batch.
+       *
+       * @param x The tensor to flatten. The rank of this tensor is required to be 2
+       *   or higher.
+       * @return The result of the flattening.
+       */
+      function batchFlatten(x) {
+        if (x.rank <= 1) {
+          throw new ValueError(`batchFlatten requires a minimum rank of 2. Got rank: ${x.rank}.`);
+        }
+        const newShape = [x.shape[0], arrayProd(x.shape, 1)];
+        return x.reshape(newShape);
+      }
+      /**
+       * Do slicing along the first axis.
+       * @param array input `tf.Tensor`.
+       * @param start starting index, inclusive.
+       * @param size size of the slice along the first axis.
+       * @returns result of the slicing.
+       * @throws ValueError: If `array` is of an unsupported subtype of `tf.Tensor`.
+       */
+      function sliceAlongFirstAxis(array, start, size) {
+        return Object(dist["tidy"])(() => {
+          switch (array.rank) {
+            case 1:
+              return dist["slice1d"](array, start, size);
+            case 2:
+              return dist["slice2d"](array, [start, 0], [size, array.shape[1]]);
+            case 3:
+              return dist["slice3d"](array, [start, 0, 0], [size, array.shape[1], array.shape[2]]);
+            case 4:
+              return dist["slice4d"](
+                array,
+                [start, 0, 0, 0],
+                [size, array.shape[1], array.shape[2], array.shape[3]]
+              );
+            case 5:
+              return dist["slice"](
+                array,
+                [start, 0, 0, 0, 0],
+                [size, array.shape[1], array.shape[2], array.shape[3], array.shape[4]]
+              );
+            case 6:
+              return dist["slice"](
+                array,
+                [start, 0, 0, 0, 0, 0],
+                [
+                  size,
+                  array.shape[1],
+                  array.shape[2],
+                  array.shape[3],
+                  array.shape[4],
+                  array.shape[5],
+                ]
+              );
+            default:
+              throw new ValueError(
+                `sliceAlongFirstAxis() received an unsupported tensor rank: ` + `${array.rank}`
+              );
+          }
+        });
+      }
+      /**
+       * Do slicing along the last axis.
+       * @param array input `tf.Tensor`.
+       * @param start starting index, inclusive.
+       * @param size size of the slice along the last axis.
+       * @returns result of the slicing.
+       * @throws ValueError: If `array` is of an unsupported subtype of `tf.Tensor`.
+       */
+      function sliceAlongLastAxis(array, start, size) {
+        return Object(dist["tidy"])(() => {
+          switch (array.rank) {
+            case 1:
+              return dist["slice1d"](array, start, size);
+            case 2:
+              return dist["slice2d"](array, [0, start], [array.shape[0], size]);
+            case 3:
+              return dist["slice3d"](array, [0, 0, start], [array.shape[0], array.shape[1], size]);
+            case 4:
+              return dist["slice4d"](
+                array,
+                [0, 0, 0, start],
+                [array.shape[0], array.shape[1], array.shape[2], size]
+              );
+            default:
+              throw new ValueError(
+                `sliceAlongLastAxis() received an unsupported tensor rank: ` + `${array.rank}`
+              );
+          }
+        });
+      }
+      /**
+       * Do slicing along the sepcified axis.
+       * @param array input `tf.Tensor`.
+       * @param start starting index, inclusive.
+       * @param size of the slice along the chosen axis.
+       * @param choose an axis.
+       * @returns result of the slicing.
+       * @throws ValueError: If `array` is of an unsupported subtype of `tf.Tensor`.
+       */
+      function sliceAlongAxis(array, start, size, axis) {
+        return Object(dist["tidy"])(() => {
+          switch (array.rank) {
+            case 1:
+              return dist["slice1d"](array, start, size);
+            case 2:
+              switch (axis) {
+                case 1:
+                  return sliceAlongFirstAxis(array, start, size);
+                case 2:
+                  return sliceAlongLastAxis(array, start, size);
+                default:
+                  throw new ValueError(
+                    `The axis is not within the rank of the tensor ` + `${axis}`
+                  );
+              }
+            case 3:
+              switch (axis) {
+                case 1:
+                  return sliceAlongFirstAxis(array, start, size);
+                case 2:
+                  return dist["slice3d"](
+                    array,
+                    [0, start, 0],
+                    [array.shape[0], size, array.shape[2]]
+                  );
+                case 3:
+                  return sliceAlongLastAxis(array, start, size);
+                default:
+                  throw new ValueError(
+                    `The axis is not within the rank of the tensor ` + `${axis}`
+                  );
+              }
+            case 4:
+              switch (axis) {
+                case 1:
+                  return sliceAlongFirstAxis(array, start, size);
+                case 2:
+                  return dist["slice4d"](
+                    array,
+                    [0, start, 0, 0],
+                    [array.shape[0], size, array.shape[2], array.shape[3]]
+                  );
+                case 3:
+                  return dist["slice4d"](
+                    array,
+                    [0, 0, start, 0],
+                    [array.shape[0], array.shape[1], size, array.shape[3]]
+                  );
+                case 4:
+                  return sliceAlongLastAxis(array, start, size);
+                default:
+                  throw new ValueError(
+                    `The axis is not within the rank of the tensor ` + `${axis}`
+                  );
+              }
+            default:
+              throw new ValueError(
+                `sliceAlongLastAxis() received an unsupported tensor rank: ` + `${array.rank}`
+              );
+          }
+        });
+      }
+      /**
+       * Concatenates a list of tensors alongside the specified axis.
+       * @param tensors `Array` of tensors to concatenate.
+       * @param axis Concatenation axis.
+       * @returns The result of the concatenation.
+       */
+      function concatenate(tensors, axis = -1) {
+        let rank;
+        if (axis < 0) {
+          rank = tensors[0].rank;
+          if (rank !== 0) {
+            axis = rank;
+          } else {
+            axis = 0;
+          }
+        }
+        if (axis === tensors[0].rank) {
+          // Porting Note: This is necessary because tfc.concat() requires axis to be
+          //   in the interval [-rank, rank).
+          axis = -1;
+        }
+        // Porting Note: Sparse concat is not supported yet.
+        return dist["concat"](tensors, axis);
+      }
+      /**
+       * Concatenate two arrays along the first dimension.
+       * @param a The 1st `tf.Tensor` to concatenate.
+       * @param b The 2nd `tf.Tensor` to concatenate.
+       * @returns Result of the concatenation.
+       * @throws ValueError: If `a` is of an unsupported subtype of `tf.Tensor`.
+       */
+      function concatAlongFirstAxis(a, b) {
+        switch (a.rank) {
+          case 1:
+            return dist["concat1d"]([a, b]);
+          case 2:
+            return dist["concat2d"]([a, b], 0);
+          case 3:
+            return dist["concat3d"]([a, b], 0);
+          case 4:
+            return dist["concat4d"]([a, b], 0);
+          default:
+            throw new ValueError(
+              `concatAlongFirstAxis() received an unsupported ` + `tensor rank: ${a.rank}`
+            );
+        }
+      }
+      /**
+       * Creates a tensor by tiling `x` by `n`.
+       * @param x A tensor.
+       * @param n An Array of integers or a single integer. If an Array, the length
+       *   must be the same as the number of dimensions in `x`. If a single integer,
+       *   it will be treated as an Array of length 1.
+       */
+      function tile(x, n) {
+        if (!Array.isArray(n)) {
+          n = [n];
+        }
+        if (x.rank !== n.length) {
+          throw new ValueError(
+            `The length of input n (${n.length}) does not match ` +
+              `the number of dimensions in input x (${x.rank})`
+          );
+        }
+        return dist["tile"](x, n);
+      }
+      /* Creation of random tensors. */
+      /**
+       * Get a tensor with normal distribution of values.
+       *
+       * @param shape Shape of the tensor.
+       * @param mean mean value of the normal distribution.
+       * @param stddev standard deviation of the normal distribution.
+       * @param dtype
+       * @param seed
+       * @return The normal tensor.
+       */
+      function randomNormal(shape, mean = 0.0, stddev = 1.0, dtype, seed) {
+        return dist["randomNormal"](shape, mean, stddev, dtype, seed);
+      }
+      /* Linear Algebra */
+      /**
+       * Multiply two tensors and returns the result as a tensor.
+       *
+       * For 2D tensors, this is equivalent to matrix multiplication (matMul).
+       * For tensors of higher ranks, it follows the Theano behavior,
+       * (e.g. `(2, 3) * (4, 3, 5) -> (2, 4, 5)`).  From the Theano documentation:
+       *
+       * For N dimensions it is a sum product over the last axis of x and the
+       * second-to-last of y:
+       *
+       * @param a A tensor of at least rank 2.
+       * @param b A tensor of at least rank 2.
+       * @param activation (optional) A string identifying the activation
+       *   function.
+       * @return Result of the dot operation.
+       */
+      function dot(a, b, activation, bias) {
+        if (a.rank < 2 || b.rank < 2) {
+          throw new NotImplementedError(
+            `dot requires both inputs to be rank >= 2` +
+              ` but got x shape = ${a.shape} and y shape = ${b.shape}`
+          );
+        }
+        if (b.rank >= 3) {
+          const xLastDim = a.shape.slice(-1)[0];
+          const ySecondLastDim = b.shape.slice(-2)[0];
+          if (xLastDim !== ySecondLastDim) {
+            throw new NotImplementedError(
+              `If rank y >= 3, then the second last dim` +
+                ` of y must equal the last dim of x but got x shape = ${a.shape} and ` +
+                ` y shape = ${b.shape}`
+            );
+          }
+        }
+        // Handle basic 2D x 2D case.
+        if (a.rank === 2 && b.rank === 2) {
+          const transposeA = false;
+          const transposeB = false;
+          // tfc.fused.matMul only fuses certain activation functions. Unsupported
+          // activation functions are treated as 'linear' activations, which is
+          // equivalent to a no-op.
+          return dist["fused"].matMul({
+            a,
+            b: b,
+            transposeA,
+            transposeB,
+            bias: bias ? reshapeBias(a.rank, bias, imageDataFormat()) : null,
+            activation,
+          });
+        } else {
+          // Reshape x into the analogous 2D Tensor.
+          const aFirstDims = a.shape.slice(); // Holds all but the last dim of x.
+          const aLastDim = aFirstDims.pop();
+          a = a.reshape([-1, aLastDim]);
+          // Reshape y into the analogous 2D Tensor, and keep track of the
+          // required dimensions to reproduce the output shape.
+          const bShape = b.shape.slice();
+          const bLastDim = bShape.pop();
+          const ySecondLastDim = bShape.pop();
+          const yOtherDims = [...bShape, bLastDim];
+          // permutation should be like [r-2, 0, 1, 2, ... r-4, r-3, r-1]
+          // where r is the rank of y.
+          const perm = Array.from({ length: b.rank }, (_, i) => {
+            if (i === 0) {
+              return b.rank - 2;
+            } else if (i <= b.rank - 2) {
+              return i - 1;
+            }
+            return i;
+          });
+          b = b.transpose(perm).reshape([ySecondLastDim, -1]);
+          // Multiply x and y as 2D Tensors, and then reshape back to original.
+          const outputShape = [...aFirstDims, ...yOtherDims];
+          const transposeA = false;
+          const transposeB = false;
+          return dist["fused"]
+            .matMul({
+              a,
+              b,
+              transposeA,
+              transposeB,
+              bias: bias ? reshapeBias(a.rank, bias, imageDataFormat()) : null,
+              activation,
+            })
+            .reshape(outputShape);
+        }
+      }
+      /**
+       * Compute the sign Tensor of an input Tensor.
+       *
+       * Elements of the input `tf.Tensor` that are === 0 are mapped to 0.
+       * Elements of the input `tf.Tensor` that are > 0 are mapped to 1.
+       * Elements of the input `tf.Tensor` that are < 0 are mapped to -1.
+       *
+       * @param x Input `tf.Tensor`.
+       * @return The sign `tf.Tensor`.
+       */
+      function sign(x) {
+        // TODO(cais): Move to the core.
+        return Object(dist["tidy"])(() => {
+          const zerosLikeX = Object(dist["zerosLike"])(x);
+          const onesLikeX = Object(dist["onesLike"])(x);
+          return Object(dist["where"])(
+            dist["equal"](x, zerosLikeX),
+            zerosLikeX,
+            Object(dist["where"])(
+              dist["greater"](x, Object(dist["zerosLike"])(x)),
+              onesLikeX,
+              dist["mul"](-1, onesLikeX)
+            )
+          );
+        });
+      }
+      /**
+       * Computes the one-hot representation of an integer tensor.
+       * @param indices nD integer tensor of shape
+       *   `(batch_size, dim1, dim2, ... dim(n-1))`
+       * @param numClasses Integer, number of classes to consider.
+       * @returns (n + 1)D one hot representation of the input
+       *   with shape `(batch_size, dim1, dim2, ... dim(n-1), num_classes)`
+       */
+      function oneHot(indices, numClasses) {
+        return Object(dist["tidy"])(() => {
+          if (indices.rank !== 1) {
+            throw new Error(
+              "Only 1D one-hot tensors are supported in the " + "deeplearn backend, at present."
+            );
+          }
+          indices = indices.toInt();
+          return dist["oneHot"](indices, numClasses).toFloat();
+        });
+      }
+      /* Elementary math functions. */
+      /**
+       * Retrieves the elements of indices `indices` in the tensor `reference`.
+       * @param reference A tensor.
+       * @param indices An integer tensor of indices or an `Array` of integers.
+       * @param axis Axis along which to perform the gather operation.
+       * @returns The result of the gathering as a tensor.
+       */
+      function gather(reference, indices, axis) {
+        return Object(dist["tidy"])(() => {
+          if (Array.isArray(indices)) {
+            indices = Object(dist["tensor1d"])(indices, "int32");
+          } else {
+            indices = indices.toInt();
+          }
+          return dist["gather"](reference, indices, axis);
+        });
+      }
+      /**
+       * Element-wise square.
+       * @param x Input tensor.
+       * @return element-wise x^2
+       */
+      function square(x) {
+        return dist["mul"](x, x);
+      }
+      /**
+       * Element-wise exponentiation.
+       *
+       * Porting Note: In PyKeras, `a` (the exponent) is a Python integer, which
+       *   takes advatnage of the backend's (e.g., TensorFlow's) automatic
+       * conversion to tensor. Here we allow `a` to be either a number or a tensor.
+       *
+       * @param x The base tensor.
+       * @param a The exponent, tensor or number. If a number, it is rounded to the
+       *   nearest integer and converted to a tensor.
+       * @returns A tensor of the same shape as `x`.
+       */
+      function pow(x, a) {
+        return Object(dist["tidy"])(() => {
+          if (typeof a === "number") {
+            a = Object(dist["scalar"])(Math.round(a), "int32");
+          }
+          if (a.dtype !== "int32") {
+            throw new NotImplementedError(
+              `Non-int32 dtype (${a.dtype}) is not supported by pow() yet`
+            );
+          }
+          return dist["pow"](x, a);
+        });
+      }
+      /**
+       * Reshapes bias tensor according to rank of x.
+       */
+      function reshapeBias(xRank, bias, dataFormat) {
+        const biasShape = bias.shape;
+        if (bias.rank !== 1 && bias.rank !== xRank) {
+          throw new ValueError(
+            `Unexpected bias dimensions: ${bias.rank}` + `; expected it to be 1 or ${xRank}`
+          );
+        }
+        if (xRank === 5) {
+          if (dataFormat === "channelsFirst") {
+            if (biasShape.length === 1) {
+              return bias.reshape([1, biasShape[0], 1, 1, 1]);
+            } else {
+              return bias.reshape([1, biasShape[3], biasShape[0], biasShape[1], biasShape[2]]);
+            }
+          } else if (dataFormat === "channelsLast") {
+            if (biasShape.length === 1) {
+              return bias.reshape([1, 1, 1, 1, biasShape[0]]);
+            } else {
+              return bias.reshape([1].concat(biasShape));
+            }
+          }
+        } else if (xRank === 4) {
+          if (dataFormat === "channelsFirst") {
+            if (biasShape.length === 1) {
+              return bias.reshape([1, biasShape[0], 1, 1]);
+            } else {
+              return bias.reshape([1, biasShape[2], biasShape[0], biasShape[1]]);
+            }
+          } else if (dataFormat === "channelsLast") {
+            if (biasShape.length === 1) {
+              return bias.reshape([1, 1, 1, biasShape[0]]);
+            } else {
+              return bias.reshape([1].concat(biasShape));
+            }
+          }
+        } else if (xRank === 3) {
+          if (dataFormat === "channelsFirst") {
+            if (biasShape.length === 1) {
+              return bias.reshape([1, biasShape[0], 1]);
+            } else {
+              return bias.reshape([1, biasShape[1], biasShape[0]]);
+            }
+          } else if (dataFormat === "channelsLast") {
+            if (biasShape.length === 1) {
+              return bias.reshape([1, 1, biasShape[0]]);
+            } else {
+              return bias.reshape([1].concat(biasShape));
+            }
+          }
+        } else if (xRank < 3) {
+          return bias;
+        }
+        throw new ValueError(`Unsupported input rank by biasAdd: ${bias.rank}`);
+      }
+      /* Neural-network operations. */
+      /**
+       * Add a bias to a tensor.
+       *
+       * @param x The tensor to add the bias to.
+       * @param bias The bias to add to `x`. Must be 1D or the same rank as `x`.
+       * @return Result of the bias adding.
+       * @throws ValueError: If the rank of `bias` is incorrect.
+       */
+      function biasAdd(x, bias, dataFormat) {
+        return Object(dist["tidy"])(() => {
+          if (dataFormat == null) {
+            dataFormat = imageDataFormat();
+          }
+          checkDataFormat(dataFormat);
+          return x.add(reshapeBias(x.rank, bias, dataFormat));
+        });
+      }
+      /**
+       * Exponential linear unit (ELU).
+       * @param x A tensor or variable to compute the activation function for.
+       * @param alpha: A scalar, a scaling factor for the negative section.
+       * @return Output of the ELU operation.
+       */
+      function elu(x, alpha = 1) {
+        // TODO(cais): Add support for alpha values other than 1.
+        if (alpha !== 1) {
+          throw new NotImplementedError(
+            `Support for alpha values other than 1 (${alpha}) is not implemented ` + `yet.`
+          );
+        }
+        return dist["elu"](x);
+      }
+      /**
+       * Softsign of a tensor.
+       *
+       * Defined as x / (abs(x) + 1), element-wise.
+       *
+       * @param x: Input.
+       * @returns Output.
+       */
+      function softsign(x) {
+        return Object(dist["tidy"])(() => dist["div"](x, dist["abs"](x).add(1)));
+      }
+      /**
+       * Sets entries in `x` to zero at random, while scaling the entire tensor.
+       *
+       * @param x input tensor.
+       * @param level fraction of the entries in the tensor that will be set to 0.
+       * @param noiseShape shape of randomly generated keep/drop flags, must be
+       *   broadcastable to the shape of `x`. Optional.
+       * @param seed random seed to ensure determinism. Optional.
+       * @returns Result of the dropout operation.
+       */
+      function dropout(x, level, noiseShape, seed) {
+        return Object(dist["tidy"])(() => dist["dropout"](x, level, noiseShape, seed));
+      }
+      /**
+       * Element-wise, segment-wise linear approximation of sigmoid.
+       *
+       * Returns `0.` if `x < -2.5`, `1.` if `x > 2.5`.
+       * In `-2.5 <= x <= 2.5`, returns `0.2 * x + 0.5`.
+       *
+       * @param x Input tensor.
+       * @returns Output tensor.
+       */
+      function hardSigmoid(x) {
+        return Object(dist["tidy"])(() => {
+          const y = dist["add"](0.5, dist["mul"](0.2, x));
+          return dist["clipByValue"](y, 0, 1);
+        });
+      }
+      /**
+       * Invoke `x` in the training phase, and `alt` otherwise.
+       *
+       * Porting Note: We do not create placeholder tensors for the `training`
+       * boolean flag here, because there is no such thing in the TF.js imperative
+       * backend.
+       *
+       * @param x The function to invoke iff `training` is `true`.
+       * @param alt The function to invoke iff `training` is `false`.
+       * @param training Boolean flag for whether training phase is active.
+       * @returns The return value of `x()` if `training` is `true`, or the return
+       *   value of `alt()` if `training` is `false`.
+       */
+      function inTrainPhase(x, alt, training = false) {
+        return training ? x() : alt();
+      }
+      //# sourceMappingURL=tfjs_backend.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/keras_format/initializer_config.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      const VALID_FAN_MODE_VALUES = ["fanIn", "fanOut", "fanAvg"];
+      const VALID_DISTRIBUTION_VALUES = ["normal", "uniform", "truncatedNormal"];
+      // We can't easily extract a string[] from the string union type, but we can
+      // recapitulate the list, enforcing at compile time that the values are valid
+      // and that we have the right number of them.
+      /**
+       * A string array of valid Initializer class names.
+       *
+       * This is guaranteed to match the `InitializerClassName` union type.
+       */
+      const initializerClassNames = [
+        "Zeros",
+        "Ones",
+        "Constant",
+        "RandomNormal",
+        "RandomUniform",
+        "TruncatedNormal",
+        "VarianceScaling",
+        "Orthogonal",
+        "Identity",
+      ];
+      //# sourceMappingURL=initializer_config.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/initializers.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      function checkFanMode(value) {
+        checkStringTypeUnionValue(VALID_FAN_MODE_VALUES, "FanMode", value);
+      }
+      function checkDistribution(value) {
+        checkStringTypeUnionValue(VALID_DISTRIBUTION_VALUES, "Distribution", value);
+      }
+      /**
+       * Initializer base class.
+       *
+       * @doc {
+       *   heading: 'Initializers', subheading: 'Classes', namespace: 'initializers'}
+       */
+      class initializers_Initializer extends dist["serialization"].Serializable {
+        fromConfigUsesCustomObjects() {
+          return false;
+        }
+        getConfig() {
+          return {};
+        }
+      }
+      class initializers_Zeros extends initializers_Initializer {
+        apply(shape, dtype) {
+          return Object(dist["zeros"])(shape, dtype);
+        }
+      }
+      /** @nocollapse */
+      initializers_Zeros.className = "Zeros";
+      dist["serialization"].registerClass(initializers_Zeros);
+      class initializers_Ones extends initializers_Initializer {
+        apply(shape, dtype) {
+          return Object(dist["ones"])(shape, dtype);
+        }
+      }
+      /** @nocollapse */
+      initializers_Ones.className = "Ones";
+      dist["serialization"].registerClass(initializers_Ones);
+      class initializers_Constant extends initializers_Initializer {
+        constructor(args) {
+          super();
+          if (typeof args !== "object") {
+            throw new ValueError(`Expected argument of type ConstantConfig but got ${args}`);
+          }
+          if (args.value === undefined) {
+            throw new ValueError(`config must have value set but got ${args}`);
+          }
+          this.value = args.value;
+        }
+        apply(shape, dtype) {
+          return Object(dist["tidy"])(() =>
+            Object(dist["mul"])(
+              Object(dist["scalar"])(this.value),
+              Object(dist["ones"])(shape, dtype)
+            )
+          );
+        }
+        getConfig() {
+          return {
+            value: this.value,
+          };
+        }
+      }
+      /** @nocollapse */
+      initializers_Constant.className = "Constant";
+      dist["serialization"].registerClass(initializers_Constant);
+      class initializers_RandomUniform extends initializers_Initializer {
+        constructor(args) {
+          super();
+          this.DEFAULT_MINVAL = -0.05;
+          this.DEFAULT_MAXVAL = 0.05;
+          this.minval = args.minval || this.DEFAULT_MINVAL;
+          this.maxval = args.maxval || this.DEFAULT_MAXVAL;
+          this.seed = args.seed;
+        }
+        apply(shape, dtype) {
+          return Object(dist["randomUniform"])(shape, this.minval, this.maxval, dtype);
+        }
+        getConfig() {
+          return { minval: this.minval, maxval: this.maxval, seed: this.seed };
+        }
+      }
+      /** @nocollapse */
+      initializers_RandomUniform.className = "RandomUniform";
+      dist["serialization"].registerClass(initializers_RandomUniform);
+      class initializers_RandomNormal extends initializers_Initializer {
+        constructor(args) {
+          super();
+          this.DEFAULT_MEAN = 0;
+          this.DEFAULT_STDDEV = 0.05;
+          this.mean = args.mean || this.DEFAULT_MEAN;
+          this.stddev = args.stddev || this.DEFAULT_STDDEV;
+          this.seed = args.seed;
+        }
+        apply(shape, dtype) {
+          dtype = dtype || "float32";
+          if (dtype !== "float32" && dtype !== "int32") {
+            throw new NotImplementedError(`randomNormal does not support dType ${dtype}.`);
+          }
+          return randomNormal(shape, this.mean, this.stddev, dtype, this.seed);
+        }
+        getConfig() {
+          return { mean: this.mean, stddev: this.stddev, seed: this.seed };
+        }
+      }
+      /** @nocollapse */
+      initializers_RandomNormal.className = "RandomNormal";
+      dist["serialization"].registerClass(initializers_RandomNormal);
+      class initializers_TruncatedNormal extends initializers_Initializer {
+        constructor(args) {
+          super();
+          this.DEFAULT_MEAN = 0;
+          this.DEFAULT_STDDEV = 0.05;
+          this.mean = args.mean || this.DEFAULT_MEAN;
+          this.stddev = args.stddev || this.DEFAULT_STDDEV;
+          this.seed = args.seed;
+        }
+        apply(shape, dtype) {
+          dtype = dtype || "float32";
+          if (dtype !== "float32" && dtype !== "int32") {
+            throw new NotImplementedError(`truncatedNormal does not support dType ${dtype}.`);
+          }
+          return Object(dist["truncatedNormal"])(shape, this.mean, this.stddev, dtype, this.seed);
+        }
+        getConfig() {
+          return { mean: this.mean, stddev: this.stddev, seed: this.seed };
+        }
+      }
+      /** @nocollapse */
+      initializers_TruncatedNormal.className = "TruncatedNormal";
+      dist["serialization"].registerClass(initializers_TruncatedNormal);
+      class initializers_Identity extends initializers_Initializer {
+        constructor(args) {
+          super();
+          this.gain = args.gain != null ? args.gain : 1.0;
+        }
+        apply(shape, dtype) {
+          return Object(dist["tidy"])(() => {
+            if (shape.length !== 2 || shape[0] !== shape[1]) {
+              throw new ValueError(
+                "Identity matrix initializer can only be used for" + " 2D square matrices."
+              );
+            } else {
+              return Object(dist["mul"])(this.gain, Object(dist["eye"])(shape[0]));
+            }
+          });
+        }
+        getConfig() {
+          return { gain: this.gain };
+        }
+      }
+      /** @nocollapse */
+      initializers_Identity.className = "Identity";
+      dist["serialization"].registerClass(initializers_Identity);
+      /**
+       * Computes the number of input and output units for a weight shape.
+       * @param shape Shape of weight.
+       * @param dataFormat data format to use for convolution kernels.
+       *   Note that all kernels in Keras are standardized on the
+       *   CHANNEL_LAST ordering (even when inputs are set to CHANNEL_FIRST).
+       * @return An length-2 array: fanIn, fanOut.
+       */
+      function computeFans(shape, dataFormat = "channelsLast") {
+        let fanIn;
+        let fanOut;
+        checkDataFormat(dataFormat);
+        if (shape.length === 2) {
+          fanIn = shape[0];
+          fanOut = shape[1];
+        } else if ([3, 4, 5].indexOf(shape.length) !== -1) {
+          if (dataFormat === "channelsFirst") {
+            const receptiveFieldSize = arrayProd(shape, 2);
+            fanIn = shape[1] * receptiveFieldSize;
+            fanOut = shape[0] * receptiveFieldSize;
+          } else if (dataFormat === "channelsLast") {
+            const receptiveFieldSize = arrayProd(shape, 0, shape.length - 2);
+            fanIn = shape[shape.length - 2] * receptiveFieldSize;
+            fanOut = shape[shape.length - 1] * receptiveFieldSize;
+          }
+        } else {
+          const shapeProd = arrayProd(shape);
+          fanIn = Math.sqrt(shapeProd);
+          fanOut = Math.sqrt(shapeProd);
+        }
+        return [fanIn, fanOut];
+      }
+      class initializers_VarianceScaling extends initializers_Initializer {
+        /**
+         * Constructor of VarianceScaling.
+         * @throws ValueError for invalid value in scale.
+         */
+        constructor(args) {
+          super();
+          if (args.scale < 0.0) {
+            throw new ValueError(`scale must be a positive float. Got: ${args.scale}`);
+          }
+          this.scale = args.scale == null ? 1.0 : args.scale;
+          this.mode = args.mode == null ? "fanIn" : args.mode;
+          checkFanMode(this.mode);
+          this.distribution = args.distribution == null ? "normal" : args.distribution;
+          checkDistribution(this.distribution);
+          this.seed = args.seed;
+        }
+        apply(shape, dtype) {
+          const fans = computeFans(shape);
+          const fanIn = fans[0];
+          const fanOut = fans[1];
+          let scale = this.scale;
+          if (this.mode === "fanIn") {
+            scale /= Math.max(1, fanIn);
+          } else if (this.mode === "fanOut") {
+            scale /= Math.max(1, fanOut);
+          } else {
+            scale /= Math.max(1, (fanIn + fanOut) / 2);
+          }
+          if (this.distribution === "normal") {
+            const stddev = Math.sqrt(scale);
+            dtype = dtype || "float32";
+            if (dtype !== "float32" && dtype !== "int32") {
+              throw new NotImplementedError(
+                `${this.getClassName()} does not support dType ${dtype}.`
+              );
+            }
+            return Object(dist["truncatedNormal"])(shape, 0, stddev, dtype, this.seed);
+          } else {
+            const limit = Math.sqrt(3 * scale);
+            return Object(dist["randomUniform"])(shape, -limit, limit, dtype);
+          }
+        }
+        getConfig() {
+          return {
+            scale: this.scale,
+            mode: this.mode,
+            distribution: this.distribution,
+            seed: this.seed,
+          };
+        }
+      }
+      /** @nocollapse */
+      initializers_VarianceScaling.className = "VarianceScaling";
+      dist["serialization"].registerClass(initializers_VarianceScaling);
+      class GlorotUniform extends initializers_VarianceScaling {
+        /**
+         * Constructor of GlorotUniform
+         * @param scale
+         * @param mode
+         * @param distribution
+         * @param seed
+         */
+        constructor(args) {
+          super({
+            scale: 1.0,
+            mode: "fanAvg",
+            distribution: "uniform",
+            seed: args == null ? null : args.seed,
+          });
+        }
+        getClassName() {
+          // In Python Keras, GlorotUniform is not a class, but a helper method
+          // that creates a VarianceScaling object. Use 'VarianceScaling' as
+          // class name to be compatible with that.
+          return initializers_VarianceScaling.className;
+        }
+      }
+      /** @nocollapse */
+      GlorotUniform.className = "GlorotUniform";
+      dist["serialization"].registerClass(GlorotUniform);
+      class GlorotNormal extends initializers_VarianceScaling {
+        /**
+         * Constructor of GlorotNormal.
+         * @param scale
+         * @param mode
+         * @param distribution
+         * @param seed
+         */
+        constructor(args) {
+          super({
+            scale: 1.0,
+            mode: "fanAvg",
+            distribution: "normal",
+            seed: args == null ? null : args.seed,
+          });
+        }
+        getClassName() {
+          // In Python Keras, GlorotNormal is not a class, but a helper method
+          // that creates a VarianceScaling object. Use 'VarianceScaling' as
+          // class name to be compatible with that.
+          return initializers_VarianceScaling.className;
+        }
+      }
+      /** @nocollapse */
+      GlorotNormal.className = "GlorotNormal";
+      dist["serialization"].registerClass(GlorotNormal);
+      class HeNormal extends initializers_VarianceScaling {
+        constructor(args) {
+          super({
+            scale: 2.0,
+            mode: "fanIn",
+            distribution: "normal",
+            seed: args == null ? null : args.seed,
+          });
+        }
+        getClassName() {
+          // In Python Keras, HeNormal is not a class, but a helper method
+          // that creates a VarianceScaling object. Use 'VarianceScaling' as
+          // class name to be compatible with that.
+          return initializers_VarianceScaling.className;
+        }
+      }
+      /** @nocollapse */
+      HeNormal.className = "HeNormal";
+      dist["serialization"].registerClass(HeNormal);
+      class HeUniform extends initializers_VarianceScaling {
+        constructor(args) {
+          super({
+            scale: 2.0,
+            mode: "fanIn",
+            distribution: "uniform",
+            seed: args == null ? null : args.seed,
+          });
+        }
+        getClassName() {
+          // In Python Keras, HeUniform is not a class, but a helper method
+          // that creates a VarianceScaling object. Use 'VarianceScaling' as
+          // class name to be compatible with that.
+          return initializers_VarianceScaling.className;
+        }
+      }
+      /** @nocollapse */
+      HeUniform.className = "HeUniform";
+      dist["serialization"].registerClass(HeUniform);
+      class LeCunNormal extends initializers_VarianceScaling {
+        constructor(args) {
+          super({
+            scale: 1.0,
+            mode: "fanIn",
+            distribution: "normal",
+            seed: args == null ? null : args.seed,
+          });
+        }
+        getClassName() {
+          // In Python Keras, LeCunNormal is not a class, but a helper method
+          // that creates a VarianceScaling object. Use 'VarianceScaling' as
+          // class name to be compatible with that.
+          return initializers_VarianceScaling.className;
+        }
+      }
+      /** @nocollapse */
+      LeCunNormal.className = "LeCunNormal";
+      dist["serialization"].registerClass(LeCunNormal);
+      class LeCunUniform extends initializers_VarianceScaling {
+        constructor(args) {
+          super({
+            scale: 1.0,
+            mode: "fanIn",
+            distribution: "uniform",
+            seed: args == null ? null : args.seed,
+          });
+        }
+        getClassName() {
+          // In Python Keras, LeCunUniform is not a class, but a helper method
+          // that creates a VarianceScaling object. Use 'VarianceScaling' as
+          // class name to be compatible with that.
+          return initializers_VarianceScaling.className;
+        }
+      }
+      /** @nocollapse */
+      LeCunUniform.className = "LeCunNormal";
+      dist["serialization"].registerClass(LeCunUniform);
+      class initializers_Orthogonal extends initializers_Initializer {
+        constructor(args) {
+          super();
+          this.DEFAULT_GAIN = 1;
+          this.gain = args.gain == null ? this.DEFAULT_GAIN : args.gain;
+          this.seed = args.seed;
+          if (this.seed != null) {
+            throw new NotImplementedError(
+              "Random seed is not implemented for Orthogonal Initializer yet."
+            );
+          }
+        }
+        apply(shape, dtype) {
+          return Object(dist["tidy"])(() => {
+            if (shape.length !== 2) {
+              throw new NotImplementedError(
+                "The Orthogonal Initializer does not support non-2D shapes yet."
+              );
+            }
+            if (shape[0] * shape[1] > 2000) {
+              console.warn(
+                `Orthogonal initializer is being called on a matrix with more ` +
+                  `than 2000 (${shape[0] * shape[1]}) elements: ` +
+                  `Slowness may result.`
+              );
+            }
+            // TODO(cais): Add seed support.
+            const normalizedShape = shape[0] > shape[1] ? [shape[1], shape[0]] : shape;
+            const a = randomNormal(normalizedShape, 0, 1, "float32");
+            let q = dist["linalg"].gramSchmidt(a);
+            if (shape[0] > shape[1]) {
+              q = q.transpose();
+            }
+            return Object(dist["mul"])(this.gain, q);
+          });
+        }
+        getConfig() {
+          return {
+            gain: this.gain,
+            seed: this.seed,
+          };
+        }
+      }
+      /** @nocollapse */
+      initializers_Orthogonal.className = "Orthogonal";
+      dist["serialization"].registerClass(initializers_Orthogonal);
+      // Maps the JavaScript-like identifier keys to the corresponding registry
+      // symbols.
+      const INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP = {
+        constant: "Constant",
+        glorotNormal: "GlorotNormal",
+        glorotUniform: "GlorotUniform",
+        heNormal: "HeNormal",
+        heUniform: "HeUniform",
+        identity: "Identity",
+        leCunNormal: "LeCunNormal",
+        leCunUniform: "LeCunUniform",
+        ones: "Ones",
+        orthogonal: "Orthogonal",
+        randomNormal: "RandomNormal",
+        randomUniform: "RandomUniform",
+        truncatedNormal: "TruncatedNormal",
+        varianceScaling: "VarianceScaling",
+        zeros: "Zeros",
+      };
+      function deserializeInitializer(config, customObjects = {}) {
+        return deserializeKerasObject(
+          config,
+          dist["serialization"].SerializationMap.getMap().classNameMap,
+          customObjects,
+          "initializer"
+        );
+      }
+      function serializeInitializer(initializer) {
+        return serializeKerasObject(initializer);
+      }
+      function getInitializer(identifier) {
+        if (typeof identifier === "string") {
+          const className =
+            identifier in INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP
+              ? INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier]
+              : identifier;
+          /* We have four 'helper' classes for common initializers that
+        all get serialized as 'VarianceScaling' and shouldn't go through
+        the deserializeInitializer pathway. */
+          if (className === "GlorotNormal") {
+            return new GlorotNormal();
+          } else if (className === "GlorotUniform") {
+            return new GlorotUniform();
+          } else if (className === "HeNormal") {
+            return new HeNormal();
+          } else if (className === "HeUniform") {
+            return new HeUniform();
+          } else if (className === "LeCunNormal") {
+            return new LeCunNormal();
+          } else if (className === "LeCunUniform") {
+            return new LeCunUniform();
+          } else {
+            const config = {};
+            config["className"] = className;
+            config["config"] = {};
+            return deserializeInitializer(config);
+          }
+        } else if (identifier instanceof initializers_Initializer) {
+          return identifier;
+        } else {
+          return deserializeInitializer(identifier);
+        }
+      }
+      //# sourceMappingURL=initializers.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_initializers.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      // tslint:disable-next-line:max-line-length
+
+      /**
+       * Initializer that generates tensors initialized to 0.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function zeros() {
+        return new initializers_Zeros();
+      }
+      /**
+       * Initializer that generates tensors initialized to 1.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function exports_initializers_ones() {
+        return new initializers_Ones();
+      }
+      /**
+       * Initializer that generates values initialized to some constant.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function constant(args) {
+        return new initializers_Constant(args);
+      }
+      /**
+       * Initializer that generates random values initialized to a uniform
+       * distribution.
+       *
+       * Values will be distributed uniformly between the configured minval and
+       * maxval.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function randomUniform(args) {
+        return new initializers_RandomUniform(args);
+      }
+      /**
+       * Initializer that generates random values initialized to a normal
+       * distribution.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function exports_initializers_randomNormal(args) {
+        return new initializers_RandomNormal(args);
+      }
+      /**
+       * Initializer that generates random values initialized to a truncated normal.
+       * distribution.
+       *
+       * These values are similar to values from a `RandomNormal` except that values
+       * more than two standard deviations from the mean are discarded and re-drawn.
+       * This is the recommended initializer for neural network weights and filters.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function truncatedNormal(args) {
+        return new initializers_TruncatedNormal(args);
+      }
+      /**
+       * Initializer that generates the identity matrix.
+       * Only use for square 2D matrices.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function identity(args) {
+        return new initializers_Identity(args);
+      }
+      /**
+       * Initializer capable of adapting its scale to the shape of weights.
+       * With distribution=NORMAL, samples are drawn from a truncated normal
+       * distribution centered on zero, with `stddev = sqrt(scale / n)` where n is:
+       *   - number of input units in the weight tensor, if mode = FAN_IN.
+       *   - number of output units, if mode = FAN_OUT.
+       *   - average of the numbers of input and output units, if mode = FAN_AVG.
+       * With distribution=UNIFORM,
+       * samples are drawn from a uniform distribution
+       * within [-limit, limit], with `limit = sqrt(3 * scale / n)`.
+       */
+      /** @doc {heading: 'Initializers',namespace: 'initializers'} */
+      function varianceScaling(config) {
+        return new initializers_VarianceScaling(config);
+      }
+      /**
+       * Glorot uniform initializer, also called Xavier uniform initializer.
+       * It draws samples from a uniform distribution within [-limit, limit]
+       * where `limit` is `sqrt(6 / (fan_in + fan_out))`
+       * where `fan_in` is the number of input units in the weight tensor
+       * and `fan_out` is the number of output units in the weight tensor
+       *
+       * Reference:
+       *   Glorot & Bengio, AISTATS 2010
+       *       http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function glorotUniform(args) {
+        return new GlorotUniform(args);
+      }
+      /**
+       * Glorot normal initializer, also called Xavier normal initializer.
+       * It draws samples from a truncated normal distribution centered on 0
+       * with `stddev = sqrt(2 / (fan_in + fan_out))`
+       * where `fan_in` is the number of input units in the weight tensor
+       * and `fan_out` is the number of output units in the weight tensor.
+       *
+       * Reference:
+       *   Glorot & Bengio, AISTATS 2010
+       *       http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function glorotNormal(args) {
+        return new GlorotNormal(args);
+      }
+      /**
+       * He normal initializer.
+       *
+       * It draws samples from a truncated normal distribution centered on 0
+       * with `stddev = sqrt(2 / fanIn)`
+       * where `fanIn` is the number of input units in the weight tensor.
+       *
+       * Reference:
+       *     He et al., http://arxiv.org/abs/1502.01852
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function heNormal(args) {
+        return new HeNormal(args);
+      }
+      /**
+       * He uniform initializer.
+       *
+       * It draws samples from a uniform distribution within [-limit, limit]
+       * where `limit` is `sqrt(6 / fan_in)`
+       * where `fanIn` is the number of input units in the weight tensor.
+       *
+       * Reference:
+       *     He et al., http://arxiv.org/abs/1502.01852
+       */
+      /** @doc {heading: 'Initializers',namespace: 'initializers'} */
+      function heUniform(args) {
+        return new HeUniform(args);
+      }
+      /**
+       * LeCun normal initializer.
+       *
+       * It draws samples from a truncated normal distribution centered on 0
+       * with `stddev = sqrt(1 / fanIn)`
+       * where `fanIn` is the number of input units in the weight tensor.
+       *
+       * References:
+       *   [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)
+       *   [Efficient Backprop](http://yann.lecun.com/exdb/publis/pdf/lecun-98b.pdf)
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function leCunNormal(args) {
+        return new LeCunNormal(args);
+      }
+      /**
+       * LeCun uniform initializer.
+       *
+       * It draws samples from a uniform distribution in the interval
+       * `[-limit, limit]` with `limit = sqrt(3 / fanIn)`,
+       * where `fanIn` is the number of input units in the weight tensor.
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function leCunUniform(args) {
+        return new LeCunUniform(args);
+      }
+      /**
+       * Initializer that generates a random orthogonal matrix.
+       *
+       * Reference:
+       * [Saxe et al., http://arxiv.org/abs/1312.6120](http://arxiv.org/abs/1312.6120)
+       */
+      /** @doc {heading: 'Initializers', namespace: 'initializers'} */
+      function orthogonal(args) {
+        return new initializers_Orthogonal(args);
+      }
+      //# sourceMappingURL=exports_initializers.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/backend/state.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Utilities related to persistent state in the backend.
+       */
+      /**
+       * An ID to track `tf.SymbolicTensor`s and derived classes.
+       * Required in different places in engine/topology.ts to identify unique
+       * tensors.
+       */
+      let _nextUniqueTensorId = 0;
+      function getNextUniqueTensorId() {
+        return _nextUniqueTensorId++;
+      }
+      const _uidPrefixes = {};
+      /**
+       * Provides a unique UID given a string prefix.
+       *
+       * @param prefix
+       */
+      function getUid(prefix = "") {
+        if (!(prefix in _uidPrefixes)) {
+          _uidPrefixes[prefix] = 0;
+        }
+        _uidPrefixes[prefix] += 1;
+        return prefix + _uidPrefixes[prefix].toString();
+      }
+      //# sourceMappingURL=state.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/types_utils.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      // tslint:enable
+      /**
+       * Determine whether the input is an Array of Shapes.
+       */
+      function isArrayOfShapes(x) {
+        return Array.isArray(x) && Array.isArray(x[0]);
+      }
+      /**
+       * Special case of normalizing shapes to lists.
+       *
+       * @param x A shape or list of shapes to normalize into a list of Shapes.
+       * @return A list of Shapes.
+       */
+      function normalizeShapeList(x) {
+        if (x.length === 0) {
+          return [];
+        }
+        if (!Array.isArray(x[0])) {
+          return [x];
+        }
+        return x;
+      }
+      /**
+       * Helper function to obtain exactly one Tensor.
+       * @param xs: A single `tf.Tensor` or an `Array` of `tf.Tensor`s.
+       * @return A single `tf.Tensor`. If `xs` is an `Array`, return the first one.
+       * @throws ValueError: If `xs` is an `Array` and its length is not 1.
+       */
+      function getExactlyOneTensor(xs) {
+        let x;
+        if (Array.isArray(xs)) {
+          if (xs.length !== 1) {
+            throw new ValueError(`Expected Tensor length to be 1; got ${xs.length}`);
+          }
+          x = xs[0];
+        } else {
+          x = xs;
+        }
+        return x;
+      }
+      /**
+       * Helper function to obtain exactly on instance of Shape.
+       *
+       * @param shapes Input single `Shape` or Array of `Shape`s.
+       * @returns If input is a single `Shape`, return it unchanged. If the input is
+       *   an `Array` containing exactly one instance of `Shape`, return the instance.
+       *   Otherwise, throw a `ValueError`.
+       * @throws ValueError: If input is an `Array` of `Shape`s, and its length is not
+       *   1.
+       */
+      function getExactlyOneShape(shapes) {
+        if (Array.isArray(shapes) && Array.isArray(shapes[0])) {
+          if (shapes.length === 1) {
+            shapes = shapes;
+            return shapes[0];
+          } else {
+            throw new ValueError(`Expected exactly 1 Shape; got ${shapes.length}`);
+          }
+        } else {
+          return shapes;
+        }
+      }
+      //# sourceMappingURL=types_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/variable_utils.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Count the elements in an Array of LayerVariables.
+       *
+       * @param weights: The LayerVariables of which the constituent numbers are to
+       *   be counted.
+       * @returns A count of the elements in all the LayerVariables
+       */
+      function countParamsInWeights(weights) {
+        let count = 0;
+        for (const weight of weights) {
+          if (weight.shape.length === 0) {
+            count += 1;
+          } else {
+            count += weight.shape.reduce((a, b) => a * b);
+          }
+        }
+        return count;
+      }
+      //# sourceMappingURL=variable_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/variables.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      const DEFAULT_VARIABLE_NAME_PREFIX = "Variable";
+      /**
+       * A `tf.layers.LayerVariable` is similar to a `tf.Tensor` in that it has a
+       * dtype and shape, but its value is mutable.  The value is itself represented
+       * as a`tf.Tensor`, and can be read with the `read()` method and updated with
+       * the `write()` method.
+       */
+      class variables_LayerVariable {
+        /**
+         * Construct Variable from a `tf.Tensor`.
+         *
+         * If not explicitly named, the Variable will be given a name with the
+         * prefix 'Variable'. Variable names are unique. In the case of name
+         * collision, suffixies '_<num>' will be added to the name.
+         *
+         * @param val Initial value of the Variable.
+         * @param name Name of the variable. If `null` or `undefined` is provided, it
+         *   will default a name with the prefix 'Variable'.
+         * @param constraint Optional, projection function to be applied to the
+         * variable after optimize updates
+         * @throws ValueError if `name` is `null` or `undefined`.
+         */
+        constructor(
+          val,
+          dtype = "float32",
+          name = DEFAULT_VARIABLE_NAME_PREFIX,
+          trainable = true,
+          constraint = null
+        ) {
+          this.dtype = dtype == null ? "float32" : dtype;
+          this.shape = val.shape;
+          this.id = getNextUniqueTensorId();
+          name = name == null ? DEFAULT_VARIABLE_NAME_PREFIX : name;
+          this.originalName = getScopedTensorName(name);
+          this.name = getUniqueTensorName(this.originalName);
+          this.trainable_ = trainable;
+          this.constraint = constraint;
+          this.val = dist["variable"](val, this.trainable_, this.name, this.dtype);
+        }
+        /**
+         * Get a snapshot of the Variable's value.
+         *
+         * The returned value is a snapshot of the Variable's value at the time of
+         * the invocation. Future mutations in the value of the tensor will only
+         * be reflected by future calls to this method.
+         */
+        read() {
+          this.assertNotDisposed();
+          return this.val;
+        }
+        /**
+         * Update the value of the Variable.
+         *
+         * @param newVal: The new value to update to. Must be consistent with the
+         *   dtype and shape of the Variable.
+         * @return This Variable.
+         */
+        write(newVal) {
+          // TODO(cais): Once  TF.js Core supports Tensor.dtype, check dtype match.
+          this.assertNotDisposed();
+          checkShapesMatch(this.val, newVal);
+          // Skip updating if this is the exact same tensor.
+          if (this.val.id !== newVal.id) {
+            this.val.assign(newVal);
+            if (this.constraint != null) {
+              this.val.assign(this.constraint.apply(this.val));
+            }
+          }
+          return this;
+        }
+        /**
+         * Dispose this LayersVariable instance from memory.
+         */
+        dispose() {
+          this.assertNotDisposed();
+          this.val.dispose();
+        }
+        assertNotDisposed() {
+          if (this.val.isDisposed) {
+            throw new Error(`LayersVariable ${this.name} is already disposed.`);
+          }
+        }
+        get trainable() {
+          return this.trainable_;
+        }
+        set trainable(trainable) {
+          this.trainable_ = trainable;
+          this.val.trainable = trainable;
+        }
+      }
+      function checkShapesMatch(x, y) {
+        if (x.shape.toString() !== y.shape.toString()) {
+          throw new Error(
+            "Shape mismatch: " + JSON.stringify(x.shape) + " vs. " + JSON.stringify(y.shape)
+          );
+        }
+      }
+      /**
+       * Create a Variable.
+       * @param x The initial value of the `Variable`.
+       * @param dtype optional, the type of the variable.
+       * @param name optional, the name of the variable, default provided by
+       * Variable.
+       * @param constraint optional, a constraint to be applied after every update.
+       * @return The newly instantiated `Variable`.
+       */
+      function variables_variable(x, dtype, name, constraint) {
+        return new variables_LayerVariable(x, dtype, name, true, constraint);
+      }
+      /**
+       * Instantiates an all-zeros Variable and returns it.
+       *
+       * @param shape Shape of the tensor.
+       * @param dtype DType of the tensor.
+       * @param name Name of the tensor.
+       * @return An all-zero Variable.
+       */
+      function zerosVariable(shape, dtype, name) {
+        // TODO(cais): Implement logic for dtype.
+        return new variables_LayerVariable(dist["zeros"](shape), dtype, name);
+      }
+      /**
+       * Instantiates an all-zeros tensor of the same shape as another tensor.
+       *
+       * @param x The other tensor.
+       * @param dtype DType of the tensor.
+       * @param name Name of the tensor.
+       * @return A newly instantiated Variable.
+       */
+      function zerosLike(x, dtype, name) {
+        return new variables_LayerVariable(dist["zerosLike"](x), dtype, name);
+      }
+      /**
+       * Instantiates an all-ones tensor and returns it.
+       *
+       * @param shape Shape of the tensor.
+       * @param dtype DType of the tensor.
+       * @param name Name of the tensor.
+       * @return An all-ones Variable.
+       */
+      function onesVariable(shape, dtype, name) {
+        // TODO(cais): Implement logic for dtype.
+        const allocated = dist["ones"](shape);
+        return new variables_LayerVariable(allocated, dtype, name);
+      }
+      /**
+       * Instantiates an all-ones tensor of the same shape as another tensor.
+       *
+       * @param x The other tensor.
+       * @param dtype DType of the tensor.
+       * @param name Name of the tensor.
+       * @return A newly instantiated Variable.
+       */
+      function onesLike(x, dtype, name) {
+        const allocated = dist["onesLike"](x);
+        return new variables_LayerVariable(allocated, dtype, name);
+      }
+      /**
+       * Instantiate an identity matrix and returns it, as a Variable
+       *
+       * @param size Number of rows/columns.
+       * @param dtype Data type of returned Variable.
+       * @param name Name of returned Variable.
+       * @return A Variable, an identity matrix.
+       */
+      function eyeVariable(size, dtype, name) {
+        return new variables_LayerVariable(dist["eye"](size), dtype, name);
+      }
+      /**
+       * Get a Variable with uniform distribution of values.
+       * @param shape Shape of the tensor.
+       * @param minval Lower bound of the uniform distribution.
+       * @param maxval Upper bound of the uniform distribution.
+       * @param dtype
+       * @param seed
+       * @param name Optional name.
+       * @return The uniform-random Variable.
+       */
+      function randomUniformVariable(shape, minval, maxval, dtype, seed, name = "randomUniform") {
+        return new variables_LayerVariable(
+          dist["randomUniform"](shape, minval, maxval, dtype),
+          dtype,
+          name
+        );
+      }
+      /**
+       * Get a Variable with truncated-normal distribution of values.
+       * @param shape Shape of the tensor.
+       * @param mean mean value of the normal distribution.
+       * @param stddev standard deviation of the normal distribution.
+       * @param dtype
+       * @param seed
+       * @param name Optional name.
+       * @return The truncated-normal-random Variable.
+       */
+      function truncatedNormalVariable(
+        shape,
+        mean = 0.0,
+        stddev = 1.0,
+        dtype,
+        seed,
+        name = "truncatedNormal"
+      ) {
+        // TODO(cais): Implement logic for dtype and seed once they are supported
+        // by deeplearn.js.
+        dtype = dtype || "float32";
+        if (dtype !== "float32" && dtype !== "int32") {
+          throw new NotImplementedError(`randomNormal does not support dType ${dtype}.`);
+        }
+        return new variables_LayerVariable(
+          dist["truncatedNormal"](shape, mean, stddev, dtype, seed),
+          dtype,
+          name
+        );
+      }
+      /**
+       * Get a Variable with normal distribution of values.
+       * @param shape Shape of the tensor.
+       * @param mean mean value of the normal distribution.
+       * @param stddev standard deviation of the normal distribution.
+       * @param dtype
+       * @param seed
+       * @param name Optional name.
+       * @return The truncated-normal-random Variable.
+       */
+      function randomNormalVariable(
+        shape,
+        mean = 0.0,
+        stddev = 1.0,
+        dtype,
+        seed,
+        name = "randomNormal"
+      ) {
+        dtype = dtype || "float32";
+        if (dtype !== "float32" && dtype !== "int32") {
+          throw new NotImplementedError(`randomNormalVariable does not support dType ${dtype}.`);
+        }
+        return new variables_LayerVariable(
+          dist["randomNormal"](shape, mean, stddev, dtype, seed),
+          dtype,
+          name
+        );
+      }
+      /**
+       * Update the value of a Variable.
+       * @param x The Variable to be updated.
+       * @param xNew The new value to update to.
+       * @return The Variable updated.
+       */
+      function update(x, xNew) {
+        return x.write(xNew);
+      }
+      /**
+       * Update the value of a Variable by adding an increment.
+       * @param x The Variable to be updated.
+       * @param increment The incrment to add to `x`.
+       * @return The Variable updated.
+       */
+      function updateAdd(x, increment) {
+        return x.write(dist["add"](x.read(), increment));
+      }
+      /**
+       * Update the value of a Variable by subtracting a decrement.
+       * @param x The Variable to be updated.
+       * @param decrement The decrement to subtract from `x`.
+       * @return The Variable updated.
+       */
+      function updateSub(x, decrement) {
+        return x.write(dist["sub"](x.read(), decrement));
+      }
+      /**
+       * Get the values of an array of Variables.
+       *
+       * @param tensors An `Array` of `Variable`s to get the values of.
+       * @return The values of the inputs, as an `Array` of`tf.Tensor`s.
+       */
+      function batchGetValue(xs) {
+        return xs.map((x) => x.read());
+      }
+      /**
+       * Update the value of multiple Variables at once.
+       *
+       * @param variablesAndValues An `Array`, each element is of type
+       *   [Variable, Tensor]. The first item is the
+       *   `Variable` of which the value is to be updated. The second item
+       *   carries the new value.
+       */
+      function batchSetValue(variablesAndValues) {
+        variablesAndValues.forEach((variableAndValue) => {
+          const variable = variableAndValue[0];
+          variable.write(variableAndValue[1]);
+        });
+      }
+      /**
+       * Returns the gradients of `variables` w.r.t. the return value of `lossFn`.
+       * @param lossFn A function which returns a Scalar to be used as the function
+       *   value (i.e., numerator) for differentiation.
+       * @param variables List of variables to be used as the independent variables
+       *   (i.e., denominator) for differentiation.
+       * @returns An Array of gradients tensors.
+       */
+      function gradients(lossFn, variables) {
+        // TODO(cais): The return type signature can be simplified if deeplearn makes
+        //   the corresponding type public.
+        const variableList = variables.map((variable) => variable.read());
+        const valudAndGrads = Object(dist["variableGrads"])(lossFn, variableList);
+        return variables.map((variable) => valudAndGrads.grads[variable.name]);
+      }
+      //# sourceMappingURL=variables.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/topology.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original source: keras/engine/topology.py */
+
+      /**
+       * Specifies the ndim, dtype and shape of every input to a layer.
+       *
+       * Every layer should expose (if appropriate) an `inputSpec` attribute:
+       * a list of instances of InputSpec (one per input tensor).
+       *
+       * A null entry in a shape is compatible with any dimension,
+       * a null shape is compatible with any shape.
+       */
+      class InputSpec {
+        constructor(args) {
+          this.dtype = args.dtype;
+          this.shape = args.shape;
+          /*
+          TODO(michaelterry): Could throw error if ndim and shape are both defined
+            (then backport).
+        */
+          if (args.shape != null) {
+            this.ndim = args.shape.length;
+          } else {
+            this.ndim = args.ndim;
+          }
+          this.maxNDim = args.maxNDim;
+          this.minNDim = args.minNDim;
+          this.axes = args.axes || {};
+        }
+      }
+      /**
+       * `tf.SymbolicTensor` is a placeholder for a Tensor without any concrete value.
+       *
+       * They are most often encountered when building a graph of `Layer`s for a
+       * a `tf.LayersModel` and the input data's shape, but not values are known.
+       */
+      /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+      class topology_SymbolicTensor {
+        /**
+         *
+         * @param dtype
+         * @param shape
+         * @param sourceLayer The Layer that produced this symbolic tensor.
+         * @param inputs The inputs passed to sourceLayer's __call__() method.
+         * @param nodeIndex
+         * @param tensorIndex
+         * @param callArgs The keyword arguments passed to the __call__() method.
+         * @param name
+         * @param outputTensorIndex The index of this tensor in the list of outputs
+         *   returned by apply().
+         */
+        constructor(dtype, shape, sourceLayer, inputs, callArgs, name, outputTensorIndex) {
+          this.dtype = dtype;
+          this.shape = shape;
+          this.sourceLayer = sourceLayer;
+          this.inputs = inputs;
+          this.callArgs = callArgs;
+          this.outputTensorIndex = outputTensorIndex;
+          this.id = getNextUniqueTensorId();
+          if (name != null) {
+            this.originalName = getScopedTensorName(name);
+            this.name = getUniqueTensorName(this.originalName);
+          }
+          this.rank = shape.length;
+        }
+      }
+      let _nextNodeID = 0;
+      /**
+       * A `Node` describes the connectivity between two layers.
+       *
+       * Each time a layer is connected to some new input,
+       * a node is added to `layer.inboundNodes`.
+       *
+       * Each time the output of a layer is used by another layer,
+       * a node is added to `layer.outboundNodes`.
+       *
+       * `nodeIndices` and `tensorIndices` are basically fine-grained coordinates
+       * describing the origin of the `inputTensors`, verifying the following:
+       *
+       * `inputTensors[i] ==
+       * inboundLayers[i].inboundNodes[nodeIndices[i]].outputTensors[
+       *   tensorIndices[i]]`
+       *
+       * A node from layer A to layer B is added to:
+       *     A.outboundNodes
+       *     B.inboundNodes
+       */
+      class Node {
+        constructor(
+          args,
+          // TODO(michaelterry): Define actual type for this.
+          callArgs
+        ) {
+          this.callArgs = callArgs;
+          this.id = _nextNodeID++;
+          /*
+          Layer instance (NOT a list).
+          this is the layer that takes a list of input tensors
+          and turns them into a list of output tensors.
+          the current node will be added to
+          the inboundNodes of outboundLayer.
+        */
+          this.outboundLayer = args.outboundLayer;
+          /*
+            The following 3 properties describe where
+            the input tensors come from: which layers,
+            and for each layer, which node and which
+            tensor output of each node.
+        */
+          // List of layer instances.
+          this.inboundLayers = args.inboundLayers;
+          // List of integers, 1:1 mapping with inboundLayers.
+          this.nodeIndices = args.nodeIndices;
+          // List of integers, 1:1 mapping with inboundLayers.
+          this.tensorIndices = args.tensorIndices;
+          /*
+            Following 2 properties:
+            tensor inputs and outputs of outboundLayer.
+        */
+          // List of tensors. 1:1 mapping with inboundLayers.
+          this.inputTensors = args.inputTensors;
+          // List of tensors, created by outboundLayer.call().
+          this.outputTensors = args.outputTensors;
+          /*
+            Following 2 properties: input and output masks.
+            List of tensors, 1:1 mapping with inputTensor.
+        */
+          this.inputMasks = args.inputMasks;
+          // List of tensors, created by outboundLayer.computeMask().
+          this.outputMasks = args.outputMasks;
+          // Following 2 properties: input and output shapes.
+          // List of shape tuples, shapes of inputTensors.
+          this.inputShapes = args.inputShapes;
+          // List of shape tuples, shapes of outputTensors.
+          this.outputShapes = args.outputShapes;
+          // Add nodes to all layers involved.
+          for (const layer of args.inboundLayers) {
+            if (layer != null) {
+              layer.outboundNodes.push(this);
+            }
+          }
+          args.outboundLayer.inboundNodes.push(this);
+        }
+        getConfig() {
+          const inboundNames = [];
+          for (const layer of this.inboundLayers) {
+            if (layer != null) {
+              inboundNames.push(layer.name);
+            } else {
+              inboundNames.push(null);
+            }
+          }
+          return {
+            outboundLayer: this.outboundLayer ? this.outboundLayer.name : null,
+            inboundLayers: inboundNames,
+            nodeIndices: this.nodeIndices,
+            tensorIndices: this.tensorIndices,
+          };
+        }
+      }
+      let _nextLayerID = 0;
+      /**
+       * A layer is a grouping of operations and weights that can be composed to
+       * create a `tf.LayersModel`.
+       *
+       * Layers are constructed by using the functions under the
+       * [tf.layers](#Layers-Basic) namespace.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Classes', namespace: 'layers'} */
+      class topology_Layer extends dist["serialization"].Serializable {
+        constructor(args = {}) {
+          super();
+          this._callHook = null;
+          this._addedWeightNames = [];
+          // Porting Notes: PyKeras does not have this property in this base Layer
+          //   class. Instead lets Layer subclass set it dynamically and checks the
+          //   value with `hasattr`. In tfjs-layers, we let this be a member of this
+          //   base class.
+          this._stateful = false;
+          this.id = _nextLayerID++;
+          this.activityRegularizer = null;
+          this.inputSpec = null;
+          this.supportsMasking = false;
+          // These properties will be set upon call of this.build()
+          this._trainableWeights = [];
+          this._nonTrainableWeights = [];
+          this._losses = [];
+          this._updates = [];
+          this._built = false;
+          /*
+          These lists will be filled via successive calls
+          to this.addInboundNode().
+         */
+          this.inboundNodes = [];
+          this.outboundNodes = [];
+          let name = args.name;
+          if (!name) {
+            const prefix = this.getClassName();
+            name = toSnakeCase(prefix) + "_" + getUid(prefix);
+          }
+          this.name = name;
+          this.trainable_ = args.trainable == null ? true : args.trainable;
+          if (args.inputShape != null || args.batchInputShape != null) {
+            /*
+              In this case we will later create an input layer
+              to insert before the current layer
+             */
+            let batchInputShape;
+            if (args.batchInputShape != null) {
+              batchInputShape = args.batchInputShape;
+            } else if (args.inputShape != null) {
+              let batchSize = null;
+              if (args.batchSize != null) {
+                batchSize = args.batchSize;
+              }
+              batchInputShape = [batchSize].concat(args.inputShape);
+            }
+            this.batchInputShape = batchInputShape;
+            // Set dtype.
+            let dtype = args.dtype;
+            if (dtype == null) {
+              dtype = args.inputDType;
+            }
+            if (dtype == null) {
+              dtype = "float32";
+            }
+            this.dtype = dtype;
+          }
+          if (args.weights != null) {
+            this.initialWeights = args.weights;
+          } else {
+            this.initialWeights = null;
+          }
+          // The value of `_refCount` is initialized to null. When the layer is used
+          // in a symbolic way for the first time, it will be set to 1.
+          this._refCount = null;
+          this.fastWeightInitDuringBuild = false;
+        }
+        /**
+         * Converts a layer and its index to a unique (immutable type) name.
+         * This function is used internally with `this.containerNodes`.
+         * @param layer The layer.
+         * @param nodeIndex The layer's position (e.g. via enumerate) in a list of
+         *   nodes.
+         *
+         * @returns The unique name.
+         */
+        static nodeKey(layer, nodeIndex) {
+          return layer.name + "_ib-" + nodeIndex.toString();
+        }
+        /**
+         * Returns this.inboundNode at index nodeIndex.
+         *
+         * Porting note: This is a replacement for _get_node_attribute_at_index()
+         * @param nodeIndex
+         * @param attrName The name of the attribute related to request for this node.
+         */
+        getNodeAtIndex(nodeIndex, attrName) {
+          if (this.inboundNodes.length === 0) {
+            throw new RuntimeError(
+              "The layer has never been called " + `and thus has no defined ${attrName}.`
+            );
+          }
+          if (this.inboundNodes.length <= nodeIndex) {
+            throw new ValueError(
+              `Asked to get ${attrName} at node ${nodeIndex}, ` +
+                `but the layer has only ${this.inboundNodes.length} inbound nodes.`
+            );
+          }
+          return this.inboundNodes[nodeIndex];
+        }
+        /**
+         * Retrieves the input tensor(s) of a layer at a given node.
+         *
+         * @param nodeIndex Integer, index of the node from which to retrieve the
+         *   attribute. E.g. `nodeIndex=0` will correspond to the first time the layer
+         *   was called.
+         *
+         * @return A tensor (or list of tensors if the layer has multiple inputs).
+         */
+        getInputAt(nodeIndex) {
+          return singletonOrArray(this.getNodeAtIndex(nodeIndex, "input").inputTensors);
+        }
+        /**
+         * Retrieves the output tensor(s) of a layer at a given node.
+         *
+         * @param nodeIndex Integer, index of the node from which to retrieve the
+         *   attribute. E.g. `nodeIndex=0` will correspond to the first time the layer
+         *   was called.
+         *
+         * @return A tensor (or list of tensors if the layer has multiple outputs).
+         */
+        getOutputAt(nodeIndex) {
+          return singletonOrArray(this.getNodeAtIndex(nodeIndex, "output").outputTensors);
+        }
+        // Properties
+        /**
+         * Retrieves the input tensor(s) of a layer.
+         *
+         * Only applicable if the layer has exactly one inbound node,
+         * i.e. if it is connected to one incoming layer.
+         *
+         * @return Input tensor or list of input tensors.
+         *
+         * @exception AttributeError if the layer is connected to more than one
+         *   incoming layers.
+         */
+        get input() {
+          if (this.inboundNodes.length > 1) {
+            throw new AttributeError(
+              `Layer ${this.name}` +
+                " has multiple inbound nodes, " +
+                'hence the notion of "layer input" ' +
+                "is ill-defined. " +
+                "Use `getInputAt(nodeIndex)` instead."
+            );
+          } else if (this.inboundNodes.length === 0) {
+            throw new AttributeError(
+              `Layer ${this.name}` + " is not connected, no input to return."
+            );
+          }
+          return singletonOrArray(this.getNodeAtIndex(0, "input").inputTensors);
+        }
+        /**
+         * Retrieves the output tensor(s) of a layer.
+         *
+         * Only applicable if the layer has exactly one inbound node,
+         * i.e. if it is connected to one incoming layer.
+         *
+         * @return Output tensor or list of output tensors.
+         *
+         * @exception AttributeError if the layer is connected to more than one
+         *   incoming layers.
+         */
+        get output() {
+          if (this.inboundNodes.length === 0) {
+            throw new AttributeError(`Layer ${this.name}` + " has no inbound nodes.");
+          }
+          if (this.inboundNodes.length > 1) {
+            throw new AttributeError(
+              `Layer ${this.name}` +
+                " has multiple inbound nodes, " +
+                'hence the notion of "layer output" ' +
+                "is ill-defined. " +
+                "Use `getOutputAt(nodeIndex)` instead."
+            );
+          }
+          return singletonOrArray(this.getNodeAtIndex(0, "output").outputTensors);
+        }
+        get losses() {
+          return this._losses;
+        }
+        /**
+         * Retrieves the Layer's current loss values.
+         *
+         * Used for regularizers during training.
+         */
+        calculateLosses() {
+          // Porting Node: This is an augmentation to Layer.loss in PyKeras.
+          //   In PyKeras, Layer.loss returns symbolic tensors. Here a concrete
+          //   Tensor (specifically Scalar) values are returned. This is due to the
+          //   imperative backend.
+          return this.losses.map((lossFn) => lossFn());
+        }
+        get updates() {
+          return this._updates;
+        }
+        get built() {
+          return this._built;
+        }
+        set built(built) {
+          this._built = built;
+        }
+        get trainable() {
+          return this.trainable_;
+        }
+        set trainable(trainable) {
+          this._trainableWeights.forEach((w) => (w.trainable = trainable));
+          this.trainable_ = trainable;
+        }
+        get trainableWeights() {
+          if (this.trainable_) {
+            return this._trainableWeights.filter((w) => w.trainable);
+          } else {
+            return [];
+          }
+        }
+        set trainableWeights(weights) {
+          this._trainableWeights = weights;
+        }
+        get nonTrainableWeights() {
+          if (this.trainable) {
+            return this._trainableWeights
+              .filter((w) => !w.trainable)
+              .concat(this._nonTrainableWeights);
+          } else {
+            return this._trainableWeights.concat(this._nonTrainableWeights);
+          }
+        }
+        set nonTrainableWeights(weights) {
+          this._nonTrainableWeights = weights;
+        }
+        /**
+         * The concatenation of the lists trainableWeights and nonTrainableWeights
+         * (in this order).
+         */
+        get weights() {
+          return this.trainableWeights.concat(this.nonTrainableWeights);
+        }
+        get stateful() {
+          return this._stateful;
+        }
+        /**
+         * Reset the states of the layer.
+         *
+         * This method of the base Layer class is essentially a no-op.
+         * Subclasses that are stateful (e.g., stateful RNNs) should override this
+         * method.
+         */
+        resetStates() {
+          if (!this.stateful) {
+            throw new Error(
+              "Cannot call the resetStates() method of a non-stateful Layer " + "object."
+            );
+          }
+        }
+        /**
+         * Checks compatibility between the layer and provided inputs.
+         *
+         * This checks that the tensor(s) `input`
+         * verify the input assumptions of the layer
+         * (if any). If not, exceptions are raised.
+         *
+         * @param inputs Input tensor or list of input tensors.
+         *
+         * @exception ValueError in case of mismatch between
+         *   the provided inputs and the expectations of the layer.
+         */
+        assertInputCompatibility(inputs) {
+          inputs = toList(inputs);
+          if (this.inputSpec == null || this.inputSpec.length === 0) {
+            return;
+          }
+          const inputSpec = toList(this.inputSpec);
+          if (inputs.length !== inputSpec.length) {
+            throw new ValueError(
+              `Layer ${this.name} expects ${inputSpec.length} inputs, ` +
+                `but it received ${inputs.length} input tensors. ` +
+                `Input received: ${inputs}`
+            );
+          }
+          for (let inputIndex = 0; inputIndex < inputs.length; inputIndex++) {
+            const x = inputs[inputIndex];
+            const spec = inputSpec[inputIndex];
+            if (spec == null) {
+              continue;
+            }
+            // Check ndim.
+            const ndim = x.rank;
+            if (spec.ndim != null) {
+              if (ndim !== spec.ndim) {
+                throw new ValueError(
+                  `Input ${inputIndex} is incompatible with layer ${this.name}: ` +
+                    `expected ndim=${spec.ndim}, found ndim=${ndim}`
+                );
+              }
+            }
+            if (spec.maxNDim != null) {
+              if (ndim > spec.maxNDim) {
+                throw new ValueError(
+                  `Input ${inputIndex} is incompatible with layer ${this.name}` +
+                    `: expected max_ndim=${spec.maxNDim}, found ndim=${ndim}`
+                );
+              }
+            }
+            if (spec.minNDim != null) {
+              if (ndim < spec.minNDim) {
+                throw new ValueError(
+                  `Input ${inputIndex} is incompatible with layer ${this.name}` +
+                    `: expected min_ndim=${spec.minNDim}, found ndim=${ndim}.`
+                );
+              }
+            }
+            // Check dtype.
+            if (spec.dtype != null) {
+              if (x.dtype !== spec.dtype) {
+                throw new ValueError(
+                  `Input ${inputIndex} is incompatible with layer ${this.name} ` +
+                    `: expected dtype=${spec.dtype}, found dtype=${x.dtype}.`
+                );
+              }
+            }
+            // Check specific shape axes.
+            if (spec.axes) {
+              const xShape = x.shape;
+              for (const key in spec.axes) {
+                const axis = Number(key);
+                const value = spec.axes[key];
+                // Perform Python-style slicing in case axis < 0;
+                // TODO(cais): Use https://github.com/alvivi/typescript-underscore to
+                // ensure type safety through Underscore calls.
+                const xShapeAtAxis = axis >= 0 ? xShape[axis] : xShape[xShape.length + axis];
+                if (value != null && [value, null].indexOf(xShapeAtAxis) === -1) {
+                  throw new ValueError(
+                    `Input ${inputIndex} is incompatible with layer ` +
+                      `${this.name}: expected axis ${axis} of input shape to ` +
+                      `have value ${value} but got shape ${xShape}.`
+                  );
+                }
+              }
+            }
+            // Check shape.
+            if (spec.shape != null) {
+              for (let i = 0; i < spec.shape.length; ++i) {
+                const specDim = spec.shape[i];
+                const dim = x.shape[i];
+                if (specDim != null && dim != null) {
+                  if (specDim !== dim) {
+                    throw new ValueError(
+                      `Input ${inputIndex} is incompatible with layer ` +
+                        `${this.name}: expected shape=${spec.shape}, ` +
+                        `found shape=${x.shape}.`
+                    );
+                  }
+                }
+              }
+            }
+          }
+        }
+        /**
+         * This is where the layer's logic lives.
+         *
+         * @param inputs Input tensor, or list/tuple of input tensors.
+         * @param kwargs Additional keyword arguments.
+         *
+         * @return A tensor or list/tuple of tensors.
+         */
+        call(inputs, kwargs) {
+          return inputs;
+        }
+        invokeCallHook(inputs, kwargs) {
+          if (this._callHook != null) {
+            this._callHook(inputs, kwargs);
+          }
+        }
+        /**
+         * Set call hook.
+         * This is currently used for testing only.
+         * @param callHook
+         */
+        setCallHook(callHook) {
+          this._callHook = callHook;
+        }
+        /**
+         * Clear call hook.
+         * This is currently used for testing only.
+         */
+        clearCallHook() {
+          this._callHook = null;
+        }
+        /**
+         * Builds or executes a `Layer's logic.
+         *
+         * When called with `tf.Tensor`(s), execute the `Layer`s computation and
+         * return Tensor(s). For example:
+         *
+         * ```js
+         * const denseLayer = tf.layers.dense({
+         *   units: 1,
+         *   kernelInitializer: 'zeros',
+         *   useBias: false
+         * });
+         *
+         * // Invoke the layer's apply() method with a `tf.Tensor` (with concrete
+         * // numeric values).
+         * const input = tf.ones([2, 2]);
+         * const output = denseLayer.apply(input);
+         *
+         * // The output's value is expected to be [[0], [0]], due to the fact that
+         * // the dense layer has a kernel initialized to all-zeros and does not have
+         * // a bias.
+         * output.print();
+         * ```
+         *
+         * When called with `tf.SymbolicTensor`(s), this will prepare the layer for
+         * future execution.  This entails internal book-keeping on shapes of
+         * expected Tensors, wiring layers together, and initializing weights.
+         *
+         * Calling `apply` with `tf.SymbolicTensor`s are typically used during the
+         * building of non-`tf.Sequential` models. For example:
+         *
+         * ```js
+         * const flattenLayer = tf.layers.flatten();
+         * const denseLayer = tf.layers.dense({units: 1});
+         *
+         * // Use tf.layers.input() to obtain a SymbolicTensor as input to apply().
+         * const input = tf.input({shape: [2, 2]});
+         * const output1 = flattenLayer.apply(input);
+         *
+         * // output1.shape is [null, 4]. The first dimension is the undetermined
+         * // batch size. The second dimension comes from flattening the [2, 2]
+         * // shape.
+         * console.log(JSON.stringify(output1.shape));
+         *
+         * // The output SymbolicTensor of the flatten layer can be used to call
+         * // the apply() of the dense layer:
+         * const output2 = denseLayer.apply(output1);
+         *
+         * // output2.shape is [null, 1]. The first dimension is the undetermined
+         * // batch size. The second dimension matches the number of units of the
+         * // dense layer.
+         * console.log(JSON.stringify(output2.shape));
+         *
+         * // The input and output and be used to construct a model that consists
+         * // of the flatten and dense layers.
+         * const model = tf.model({inputs: input, outputs: output2});
+         * ```
+         *
+         * @param inputs a `tf.Tensor` or `tf.SymbolicTensor` or an Array of them.
+         * @param kwargs Additional keyword arguments to be passed to `call()`.
+         *
+         * @return Output of the layer's `call` method.
+         *
+         * @exception ValueError error in case the layer is missing shape information
+         *   for its `build` call.
+         */
+        // Porting Note: This is a replacement for __call__() in Python.
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        apply(inputs, kwargs) {
+          kwargs = kwargs || {};
+          this.assertNotDisposed();
+          // Ensure inputs are all the same type.
+          const inputsList = toList(inputs);
+          let allAreSymbolic = true;
+          for (const input of inputsList) {
+            if (!(input instanceof topology_SymbolicTensor)) {
+              allAreSymbolic = false;
+              break;
+            }
+          }
+          let noneAreSymbolic = true;
+          for (const input of inputsList) {
+            if (input instanceof topology_SymbolicTensor) {
+              noneAreSymbolic = false;
+              break;
+            }
+          }
+          if (allAreSymbolic === noneAreSymbolic) {
+            throw new ValueError(
+              "Arguments to apply() must be all " + "SymbolicTensors or all Tensors"
+            );
+          }
+          // TODO(michaelterry): nameScope() may not be necessary.
+          return nameScope(this.name, () => {
+            // Handle laying building (weight creating, input spec locking).
+            if (!this.built) {
+              /*
+                  Throw exceptions in case the input is not compatible
+                  with the inputSpec specified in the layer constructor.
+                 */
+              this.assertInputCompatibility(inputs);
+              // Collect input shapes to build layer.
+              const inputShapes = [];
+              for (const xElem of toList(inputs)) {
+                inputShapes.push(xElem.shape);
+              }
+              this.build(singletonOrArray(inputShapes));
+              this.built = true;
+              // Load weights that were specified at layer instantiation.
+              if (this.initialWeights) {
+                this.setWeights(this.initialWeights);
+              }
+              if (this._refCount === null && noneAreSymbolic) {
+                // The first use of this layer is a non-symbolic call, set ref count
+                // to 1 so the Layer can be properly disposed if its dispose() method
+                // is called.
+                this._refCount = 1;
+              }
+            }
+            /*
+              Throw exceptions in case the input is not compatible
+              with the inputSpec set at build time.
+            */
+            this.assertInputCompatibility(inputs);
+            // Handle mask propagation.
+            // TODO(michaelterry): Mask propagation not currently implemented.
+            // Actually call the layer, collecting output(s), mask(s), and shape(s).
+            if (noneAreSymbolic) {
+              let output = this.call(inputs, kwargs);
+              // TODO(michaelterry): Compute the outputMask
+              // If the layer returns tensors from its inputs, unmodified,
+              // we copy them to avoid loss of tensor metadata.
+              const outputList = toList(output);
+              const outputListCopy = [];
+              // TODO(michaelterry): This copying may not be necessary given our eager
+              // backend.
+              for (let x of outputList) {
+                if (inputsList.indexOf(x) !== -1) {
+                  x = x.clone();
+                }
+                outputListCopy.push(x);
+              }
+              output = singletonOrArray(outputListCopy);
+              if (this.activityRegularizer != null) {
+                throw new NotImplementedError(
+                  "Layer invocation in the presence of activity " +
+                    "regularizer(s) is not supported yet."
+                );
+              }
+              // TODO(michaelterry): Call addInboundNode()?
+              return output;
+            } else {
+              const inputShape = collectInputShape(inputs);
+              const outputShape = this.computeOutputShape(inputShape);
+              let output;
+              const outputDType = guessOutputDType(inputs);
+              this.warnOnIncompatibleInputShape(Array.isArray(inputs) ? inputShape[0] : inputShape);
+              if (outputShape != null && outputShape.length > 0 && Array.isArray(outputShape[0])) {
+                // We have multiple output shapes. Create multiple output tensors.
+                output = outputShape.map(
+                  (shape, index) =>
+                    new topology_SymbolicTensor(
+                      outputDType,
+                      shape,
+                      this,
+                      toList(inputs),
+                      kwargs,
+                      this.name,
+                      index
+                    )
+                );
+              } else {
+                output = new topology_SymbolicTensor(
+                  outputDType,
+                  outputShape,
+                  this,
+                  toList(inputs),
+                  kwargs,
+                  this.name
+                );
+              }
+              /*
+                  Add an inbound node to the layer, so that it keeps track
+                  of the call and of all new variables created during the call.
+                  This also updates the layer history of the output tensor(s).
+                  If the input tensor(s) had no previous history,
+                  this does nothing.
+                */
+              this.addInboundNode(inputs, output, null, null, inputShape, outputShape, kwargs);
+              this._refCount++;
+              if (this.activityRegularizer != null) {
+                throw new NotImplementedError(
+                  "Layer invocation in the presence of activity " +
+                    "regularizer(s) is not supported yet."
+                );
+              }
+              return output;
+            }
+          });
+        }
+        /**
+         * Check compatibility between input shape and this layer's batchInputShape.
+         *
+         * Print warning if any incompatibility is found.
+         *
+         * @param inputShape Input shape to be checked.
+         */
+        warnOnIncompatibleInputShape(inputShape) {
+          if (this.batchInputShape == null) {
+            return;
+          } else if (inputShape.length !== this.batchInputShape.length) {
+            console.warn(
+              `The rank of the input tensor provided (shape: ` +
+                `${JSON.stringify(inputShape)}) does not match that of the ` +
+                `batchInputShape (${JSON.stringify(this.batchInputShape)}) ` +
+                `of the layer ${this.name}`
+            );
+          } else {
+            let dimMismatch = false;
+            this.batchInputShape.forEach((dimension, i) => {
+              if (dimension != null && inputShape[i] != null && inputShape[i] !== dimension) {
+                dimMismatch = true;
+              }
+            });
+            if (dimMismatch) {
+              console.warn(
+                `The shape of the input tensor ` +
+                  `(${JSON.stringify(inputShape)}) does not ` +
+                  `match the expectation of layer ${this.name}: ` +
+                  `${JSON.stringify(this.batchInputShape)}`
+              );
+            }
+          }
+        }
+        /**
+         * Retrieves the output shape(s) of a layer.
+         *
+         * Only applicable if the layer has only one inbound node, or if all inbound
+         * nodes have the same output shape.
+         *
+         * @returns Output shape or shapes.
+         * @throws AttributeError: if the layer is connected to more than one incoming
+         *   nodes.
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        get outputShape() {
+          if (this.inboundNodes == null || this.inboundNodes.length === 0) {
+            throw new AttributeError(
+              `The layer ${this.name} has never been called and thus has no ` +
+                `defined output shape.`
+            );
+          }
+          const allOutputShapes = [];
+          for (const node of this.inboundNodes) {
+            const shapeString = JSON.stringify(node.outputShapes);
+            if (allOutputShapes.indexOf(shapeString) === -1) {
+              allOutputShapes.push(shapeString);
+            }
+          }
+          if (allOutputShapes.length === 1) {
+            const outputShapes = this.inboundNodes[0].outputShapes;
+            if (
+              Array.isArray(outputShapes) &&
+              Array.isArray(outputShapes[0]) &&
+              outputShapes.length === 1
+            ) {
+              return outputShapes[0];
+            } else {
+              return outputShapes;
+            }
+          } else {
+            throw new AttributeError(
+              `The layer ${this.name} has multiple inbound nodes with different ` +
+                `output shapes. Hence the notion of "outut shape" is ill-defined ` +
+                `for the layer.`
+            );
+            // TODO(cais): Implement getOutputShapeAt().
+          }
+        }
+        /**
+         * Counts the total number of numbers (e.g., float32, int32) in the
+         * weights.
+         *
+         * @returns An integer count.
+         * @throws RuntimeError: If the layer is not built yet (in which case its
+         *   weights are not defined yet.)
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        countParams() {
+          if (!this.built) {
+            throw new RuntimeError(
+              `You tried to call countParams() on ${this.name}, ` +
+                `but the layer is not built yet. Build it first by calling ` +
+                `build(batchInputShape).`
+            );
+          }
+          return countParamsInWeights(this.weights);
+        }
+        /**
+         * Creates the layer weights.
+         *
+         * Must be implemented on all layers that have weights.
+         *
+         * Called when apply() is called to construct the weights.
+         *
+         * @param inputShape A `Shape` or array of `Shape` (unused).
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        build(inputShape) {
+          this.built = true;
+        }
+        /**
+         * Returns the current values of the weights of the layer.
+         *
+         * @param trainableOnly Whether to get the values of only trainable weights.
+         * @returns Weight values as an `Array` of `tf.Tensor`s.
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        getWeights(trainableOnly = false) {
+          return batchGetValue(trainableOnly ? this.trainableWeights : this.weights);
+        }
+        /**
+         * Sets the weights of the layer, from Tensors.
+         *
+         * @param weights a list of Tensors. The number of arrays and their shape
+         *   must match number of the dimensions of the weights of the layer (i.e.
+         *   it should match the output of `getWeights`).
+         *
+         * @exception ValueError If the provided weights list does not match the
+         *   layer's specifications.
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        setWeights(weights) {
+          Object(dist["tidy"])(() => {
+            const params = this.weights;
+            if (params.length !== weights.length) {
+              // TODO(cais): Restore the following and use `providedWeights`, instead
+              // of `weights` in the error message, once the deeplearn.js bug is
+              // fixed: https://github.com/PAIR-code/deeplearnjs/issues/498 const
+              // providedWeights = JSON.stringify(weights).substr(0, 50);
+              throw new ValueError(
+                `You called setWeights(weights) on layer "${this.name}" ` +
+                  `with a weight list of length ${weights.length}, ` +
+                  `but the layer was expecting ${params.length} weights. ` +
+                  `Provided weights: ${weights}...`
+              );
+            }
+            if (params.length === 0) {
+              return;
+            }
+            const weightValueTuples = [];
+            const paramValues = batchGetValue(params);
+            for (let i = 0; i < paramValues.length; ++i) {
+              const pv = paramValues[i];
+              const p = params[i];
+              const w = weights[i];
+              if (!dist["util"].arraysEqual(pv.shape, w.shape)) {
+                throw new ValueError(
+                  `Layer weight shape ${pv.shape} ` +
+                    `not compatible with provided weight shape ${w.shape}`
+                );
+              }
+              weightValueTuples.push([p, w]);
+            }
+            batchSetValue(weightValueTuples);
+          });
+        }
+        /**
+         * Adds a weight variable to the layer.
+         *
+         * @param name Name of the new weight variable.
+         * @param shape The shape of the weight.
+         * @param dtype The dtype of the weight.
+         * @param initializer An initializer instance.
+         * @param regularizer A regularizer instance.
+         * @param trainable Whether the weight should be trained via backprop or not
+         *   (assuming that the layer itself is also trainable).
+         * @param constraint An optional trainable.
+         * @return The created weight variable.
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        addWeight(name, shape, dtype, initializer, regularizer, trainable, constraint) {
+          // Reject duplicate weight names.
+          if (this._addedWeightNames.indexOf(name) !== -1) {
+            throw new ValueError(`Duplicate weight name ${name} for layer ${this.name}`);
+          }
+          this._addedWeightNames.push(name);
+          if (dtype == null) {
+            dtype = "float32";
+          }
+          if (this.fastWeightInitDuringBuild) {
+            initializer = getInitializer("zeros");
+          }
+          const initValue = initializer.apply(shape, dtype);
+          const weight = new variables_LayerVariable(initValue, dtype, name, trainable, constraint);
+          initValue.dispose();
+          // Request backend not to dispose the weights of the model on scope() exit.
+          if (regularizer != null) {
+            this.addLoss(() => regularizer.apply(weight.read()));
+          }
+          if (trainable == null) {
+            trainable = true;
+          }
+          if (trainable) {
+            this._trainableWeights.push(weight);
+          } else {
+            this._nonTrainableWeights.push(weight);
+          }
+          return weight;
+        }
+        /**
+         * Set the fast-weight-initialization flag.
+         *
+         * In cases where the initialized weight values will be immediately
+         * overwritten by loaded weight values during model loading, setting
+         * the flag to `true` saves unnecessary calls to potentially expensive
+         * initializers and speeds up the loading process.
+         *
+         * @param value Target value of the flag.
+         */
+        setFastWeightInitDuringBuild(value) {
+          this.fastWeightInitDuringBuild = value;
+        }
+        /**
+         * Add losses to the layer.
+         *
+         * The loss may potentionally be conditional on some inputs tensors,
+         * for instance activity losses are conditional on the layer's inputs.
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        addLoss(losses) {
+          if (losses == null || (Array.isArray(losses) && losses.length === 0)) {
+            return;
+          }
+          // Update this.losses
+          losses = toList(losses);
+          if (this._losses !== undefined && this._losses !== null) {
+            this.losses.push(...losses);
+          }
+        }
+        /**
+         * Computes the output shape of the layer.
+         *
+         * Assumes that the layer will be built to match that input shape provided.
+         *
+         * @param inputShape A shape (tuple of integers) or a list of shape tuples
+         *   (one per output tensor of the layer). Shape tuples can include null for
+         *   free dimensions, instead of an integer.
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        /**
+         * Computes an output mask tensor.
+         *
+         * @param inputs Tensor or list of tensors.
+         * @param mask Tensor or list of tensors.
+         *
+         * @return null or a tensor (or list of tensors, one per output tensor of the
+         * layer).
+         */
+        computeMask(inputs, mask) {
+          if (!this.supportsMasking) {
+            if (mask != null) {
+              if (Array.isArray(mask)) {
+                mask.forEach((maskElement) => {
+                  if (maskElement != null) {
+                    throw new TypeError(
+                      `Layer ${this.name} does not support masking, ` +
+                        "but was passed an inputMask."
+                    );
+                  }
+                });
+              } else {
+                throw new TypeError(
+                  `Layer ${this.name} does not support masking, ` + "but was passed an inputMask."
+                );
+              }
+            }
+            // masking not explicitly supported: return null as mask
+            return null;
+          }
+          // if masking is explictly supported, by default
+          // carry over the input mask
+          return mask;
+        }
+        /**
+         * Internal method to create an inbound node for the layer.
+         *
+         * @param inputTensors List of input tensors.
+         * @param outputTensors List of output tensors.
+         * @param inputMasks List of input masks (a mask can be a tensor, or null).
+         * @param outputMasks List of output masks (a mask can be a tensor, or null).
+         * @param inputShapes List of input shape tuples.
+         * @param outputShapes List of output shape tuples.
+         * @param kwargs Dictionary of keyword arguments that were passed to the
+         *   `call` method of the layer at the call that created the node.
+         */
+        addInboundNode(
+          inputTensors,
+          outputTensors,
+          inputMasks,
+          outputMasks,
+          inputShapes,
+          outputShapes,
+          kwargs = null
+        ) {
+          const inputTensorList = toList(inputTensors);
+          outputTensors = toList(outputTensors);
+          inputMasks = toList(inputMasks);
+          outputMasks = toList(outputMasks);
+          inputShapes = normalizeShapeList(inputShapes);
+          outputShapes = normalizeShapeList(outputShapes);
+          // Collect input tensor(s) coordinates.
+          const inboundLayers = [];
+          const nodeIndices = [];
+          const tensorIndices = [];
+          for (const x of inputTensorList) {
+            /*
+             * TODO(michaelterry): Keras adds this value to tensors; it's not
+             * clear whether we'll use this or not.
+             */
+            inboundLayers.push(x.sourceLayer);
+            nodeIndices.push(x.nodeIndex);
+            tensorIndices.push(x.tensorIndex);
+          }
+          // Create node, add it to inbound nodes.
+          // (This call has side effects.)
+          // tslint:disable-next-line:no-unused-expression
+          new Node(
+            {
+              outboundLayer: this,
+              inboundLayers,
+              nodeIndices,
+              tensorIndices,
+              inputTensors: inputTensorList,
+              outputTensors,
+              inputMasks,
+              outputMasks,
+              inputShapes,
+              outputShapes,
+            },
+            kwargs
+          );
+          // Update tensor history
+          for (let i = 0; i < outputTensors.length; i++) {
+            // TODO(michaelterry: _uses_learning_phase not tracked.
+            outputTensors[i].sourceLayer = this;
+            outputTensors[i].nodeIndex = this.inboundNodes.length - 1;
+            outputTensors[i].tensorIndex = i;
+          }
+        }
+        /**
+         * Returns the config of the layer.
+         *
+         * A layer config is a TS dictionary (serializable)
+         * containing the configuration of a layer.
+         * The same layer can be reinstantiated later
+         * (without its trained weights) from this configuration.
+         *
+         * The config of a layer does not include connectivity
+         * information, nor the layer class name.  These are handled
+         * by 'Container' (one layer of abstraction above).
+         *
+         * Porting Note: The TS dictionary follows TS naming standrds for
+         * keys, and uses tfjs-layers type-safe Enums.  Serialization methods
+         * should use a helper function to convert to the pythonic storage
+         * standard. (see serialization_utils.convertTsToPythonic)
+         *
+         * @returns TS dictionary of configuration.
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        getConfig() {
+          const config = { name: this.name, trainable: this.trainable };
+          if (this.batchInputShape != null) {
+            config["batchInputShape"] = this.batchInputShape;
+          }
+          if (this.dtype != null) {
+            config["dtype"] = this.dtype;
+          }
+          return config;
+        }
+        /**
+         * Dispose the weight variables that this Layer instance holds.
+         *
+         * @returns {number} Number of disposed variables.
+         */
+        disposeWeights() {
+          this.weights.forEach((weight) => weight.dispose());
+          return this.weights.length;
+        }
+        assertNotDisposed() {
+          if (this._refCount === 0) {
+            throw new Error(`Layer '${this.name}' is already disposed.`);
+          }
+        }
+        /**
+         * Attempt to dispose layer's weights.
+         *
+         * This method decrease the reference count of the Layer object by 1.
+         *
+         * A Layer is reference-counted. Its reference count is incremented by 1
+         * the first item its `apply()` method is called and when it becomes a part
+         * of a new `Node` (through calling the `apply()`) method on a
+         * `tf.SymbolicTensor`).
+         *
+         * If the reference count of a Layer becomes 0, all the weights will be
+         * disposed and the underlying memory (e.g., the textures allocated in WebGL)
+         * will be freed.
+         *
+         * Note: If the reference count is greater than 0 after the decrement, the
+         * weights of the Layer will *not* be disposed.
+         *
+         * After a Layer is disposed, it cannot be used in calls such as `apply()`,
+         * `getWeights()` or `setWeights()` anymore.
+         *
+         * @returns A DisposeResult Object with the following fields:
+         *   - refCountAfterDispose: The reference count of the Container after this
+         *     `dispose()` call.
+         *   - numDisposedVariables: Number of `tf.Variable`s (i.e., weights) disposed
+         *     during this `dispose()` call.
+         * @throws {Error} If the layer is not built yet, or if the layer has already
+         *   been disposed.
+         */
+        /** @doc {heading: 'Models', 'subheading': 'Classes'} */
+        dispose() {
+          if (!this.built) {
+            throw new Error(
+              `Cannot dispose Layer ${this.name} because it has not been ` + `built yet.`
+            );
+          }
+          if (this._refCount === null) {
+            throw new Error(
+              `Cannot dispose Layer ${this.name} because it has not been used ` + `yet.`
+            );
+          }
+          this.assertNotDisposed();
+          let numDisposedVariables = 0;
+          if (--this._refCount === 0) {
+            numDisposedVariables = this.disposeWeights();
+          }
+          return { refCountAfterDispose: this._refCount, numDisposedVariables };
+        }
+      }
+      /**
+       * Collects the input shape(s) of a list of `tf.Tensor`s or
+       * `tf.SymbolicTensor`s.
+       *
+       * TODO(michaelterry): Update PyKeras docs (backport).
+       *
+       * @param inputTensors List of input tensors (or single input tensor).
+       *
+       * @return List of shape tuples (or single tuple), one tuple per input.
+       */
+      function collectInputShape(inputTensors) {
+        inputTensors = toList(inputTensors);
+        const shapes = [];
+        for (const x of inputTensors) {
+          shapes.push(x.shape);
+        }
+        return singletonOrArray(shapes);
+      }
+      /**
+       * Guesses output dtype based on inputs.
+       *
+       * At present, just returns 'float32' for any input.
+       *
+       * @param inputTensors List of input tensors (or single input tensor).
+       *
+       * @return The guessed DType. At present, always returns 'float32'.
+       */
+      function guessOutputDType(inputTensors) {
+        return "float32";
+      }
+      /**
+       * Returns the list of input tensors necessary to compute `tensor`.
+       *
+       * Output will always be a list of tensors (potentially with 1 element).
+       *
+       * @param tensor The tensor to start from.
+       * @param layer Origin layer of the tensor.
+       * @param nodeIndex Origin node index of the tensor.
+       *
+       * @return Array of input tensors.
+       */
+      function getSourceInputs(tensor, layer, nodeIndex) {
+        if (layer == null || (nodeIndex != null && nodeIndex > 0)) {
+          layer = tensor.sourceLayer;
+          nodeIndex = tensor.nodeIndex;
+        }
+        if (layer.inboundNodes.length === 0) {
+          return [tensor];
+        } else {
+          const node = layer.inboundNodes[nodeIndex];
+          if (node.inboundLayers.length === 0) {
+            return node.inputTensors;
+          } else {
+            const sourceTensors = [];
+            for (let i = 0; i < node.inboundLayers.length; i++) {
+              const x = node.inputTensors[i];
+              const layer = node.inboundLayers[i];
+              const nodeIndex = node.nodeIndices[i];
+              const previousSources = getSourceInputs(x, layer, nodeIndex);
+              // Avoid input redundancy.
+              for (const x of previousSources) {
+                if (sourceTensors.indexOf(x) === -1) {
+                  sourceTensors.push(x);
+                }
+              }
+            }
+            return sourceTensors;
+          }
+        }
+      }
+      //# sourceMappingURL=topology.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/input_layer.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      class input_layer_InputLayer extends topology_Layer {
+        constructor(args) {
+          super({
+            dtype: args.dtype,
+            name: args.name != null ? args.name : getUid("input").toString(),
+          });
+          // Normalize config.batchSize and config.sparse
+          if (args.batchSize == null) {
+            args.batchSize = null;
+          }
+          if (args.sparse == null) {
+            args.sparse = false;
+          }
+          this.trainable = false;
+          this.built = true;
+          this.sparse = args.sparse;
+          if (args.inputShape != null && args.batchInputShape != null) {
+            throw new ValueError(
+              "Only provide the inputShape OR " +
+                "batchInputShape argument to inputLayer, not both at the same time."
+            );
+          }
+          let batchInputShape = args.batchInputShape;
+          if (batchInputShape == null) {
+            if (args.inputShape == null) {
+              throw new ValueError(
+                "An InputLayer should be passed either a " + "`batchInputShape` or an `inputShape`."
+              );
+            } else {
+              batchInputShape = [args.batchSize].concat(args.inputShape);
+            }
+          } else {
+            // TODO(michaelterry): Backport to PyKeras
+            if (args.batchSize != null) {
+              throw new ValueError(
+                "Cannot specify batchSize if batchInputShape is " +
+                  "specified when creating an InputLayer."
+              );
+            }
+          }
+          const dtype = args.dtype || "float32";
+          this.batchInputShape = batchInputShape;
+          this.dtype = dtype;
+          // TODO(michaelterry): Backport this to PyKeras?
+          this.inputSpec = [{ shape: batchInputShape }];
+          const inputTensor = new topology_SymbolicTensor(
+            this.dtype,
+            this.batchInputShape,
+            this,
+            [],
+            {},
+            this.name
+          );
+          inputTensor.nodeIndex = 0;
+          inputTensor.tensorIndex = 0;
+          // Create an input node to add to this.outboundNode.
+          // (This call has side effects.)
+          // tslint:disable-next-line:no-unused-expression
+          new Node({
+            outboundLayer: this,
+            inboundLayers: [],
+            nodeIndices: [],
+            tensorIndices: [],
+            inputTensors: [inputTensor],
+            outputTensors: [inputTensor],
+            inputMasks: [null],
+            outputMasks: [null],
+            inputShapes: [batchInputShape],
+            outputShapes: [batchInputShape],
+          });
+        }
+        apply(inputs, kwargs) {
+          throw new ValueError(
+            "Cannot pass any input to an " +
+              `InputLayer's apply() method. InputLayer name: ${this.name}`
+          );
+        }
+        dispose() {
+          // dispose() for InputLayer is overridden as no-op.
+          return { refCountAfterDispose: this._refCount, numDisposedVariables: 0 };
+        }
+        getConfig() {
+          return {
+            batchInputShape: this.batchInputShape,
+            dtype: this.dtype,
+            sparse: this.sparse,
+            name: this.name,
+          };
+        }
+      }
+      /** @nocollapse */
+      input_layer_InputLayer.className = "InputLayer";
+      dist["serialization"].registerClass(input_layer_InputLayer);
+      function Input(config) {
+        if (config.batchShape == null && config.shape == null) {
+          throw new Error(
+            "Please provide to Input either a `shape`" +
+              " or a `batchShape` argument. Note that " +
+              "`shape` does not include the batch " +
+              "dimension."
+          );
+        }
+        if (config.batchShape != null && config.shape != null) {
+          // TODO(michaelterry): Backport to PyKeras.
+          throw new ValueError(
+            "Please provide either a `shape` or `batchShape` " + "argument to Input, but not both."
+          );
+        }
+        let batchShape = config.batchShape;
+        if (config.shape != null && batchShape == null) {
+          batchShape = [null].concat(config.shape);
+        }
+        let dtype = config.dtype;
+        if (dtype == null) {
+          dtype = "float32";
+        }
+        const inputLayer = new input_layer_InputLayer({
+          batchInputShape: batchShape,
+          name: config.name,
+          dtype,
+          sparse: config.sparse,
+        });
+        const outputs = inputLayer.inboundNodes[0].outputTensors;
+        return outputs[0];
+      }
+      //# sourceMappingURL=input_layer.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/logs.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      /**
+       * Turn any Scalar values in a Logs object into actual number values.
+       *
+       * @param logs The `Logs` object to be resolved in place.
+       */
+      async function resolveScalarsInLogs(logs) {
+        if (logs == null) {
+          return;
+        }
+        const promises = [];
+        const keys = [];
+        const scalarsToDispose = [];
+        for (const key in logs) {
+          const value = logs[key];
+          if (typeof value !== "number") {
+            const valueScalar = value;
+            promises.push(valueScalar.data());
+            keys.push(key);
+            scalarsToDispose.push(valueScalar);
+          }
+        }
+        if (promises.length > 0) {
+          const values = await Promise.all(promises);
+          for (let i = 0; i < values.length; ++i) {
+            logs[keys[i]] = values[i][0];
+          }
+          // Dispose the original scalar tensors.
+          Object(dist["dispose"])(scalarsToDispose);
+        }
+      }
+      /**
+       * Dispose all Tensors in an UnresolvedLogs object.
+       *
+       * @param logs An `UnresolvedLogs` object potentially containing `tf.Tensor`s in
+       *   places where the values can be `tf.Tensor` or `number`.
+       */
+      function disposeTensorsInLogs(logs) {
+        if (logs == null) {
+          return;
+        }
+        for (const key in logs) {
+          const value = logs[key];
+          if (typeof value !== "number") {
+            value.dispose();
+          }
+        }
+      }
+      //# sourceMappingURL=logs.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/base_callbacks.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original source: keras/callbacks.py */
+
+      /** Verbosity logging level when fitting a model. */
+      var ModelLoggingVerbosity;
+      (function (ModelLoggingVerbosity) {
+        ModelLoggingVerbosity[(ModelLoggingVerbosity["SILENT"] = 0)] = "SILENT";
+        ModelLoggingVerbosity[(ModelLoggingVerbosity["VERBOSE"] = 1)] = "VERBOSE";
+      })(ModelLoggingVerbosity || (ModelLoggingVerbosity = {}));
+      /** How often to yield to the main thread when training (in ms). */
+      const DEFAULT_YIELD_EVERY_MS = 125;
+      /**
+       * Abstract base class used to build new callbacks.
+       *
+       * The `logs` dictionary that callback methods take as argument will contain
+       * keys for quantities relevant to the current batch or epoch.
+       *
+       * Currently, the `.fit()` method of the `Sequential` model class
+       * will include the following quantities in the `logs` that
+       * it passes to its callbacks:
+       *
+       * onEpochEnd: Logs include `acc` and `loss`, and optionally include `valLoss`
+       *   (if validation is enabled in `fit`), and `valAcc` (if validation and
+       *   accuracy monitoring are enabled).
+       * onBatchBegin: Logs include `size`, the number of samples in the current
+       *   batch.
+       * onBatchEnd: Logs include `loss`, and optionally `acc` (if accuracy monitoring
+       *   is enabled).
+       */
+      class BaseCallback {
+        constructor() {
+          // TODO(michaelterry): This type is a best guess.
+          this.validationData = null;
+        }
+        setParams(params) {
+          this.params = params;
+        }
+        async onEpochBegin(epoch, logs) {}
+        async onEpochEnd(epoch, logs) {}
+        async onBatchBegin(batch, logs) {}
+        async onBatchEnd(batch, logs) {}
+        async onTrainBegin(logs) {}
+        async onTrainEnd(logs) {}
+        // LayersModel needs to call Callback.setModel(), but cannot actually depend
+        // on Callback because that creates a cyclic dependency.  Providing this no-op
+        // method on BaseCallback breaks the cycle: this way LayersModel can depend on
+        // BaseCallback but not on Callback.  The argument is typed as `Container`
+        // (the superclass of LayersModel) to avoid recapitulating the cycle. Callback
+        // overrides this method and enforces that the argument is really a
+        // LayersModel.
+        setModel(model) {
+          // Do nothing. Use Callback instead of BaseCallback to track the model.
+        }
+      }
+      /**
+       * Container abstracting a list of callbacks.
+       */
+      class CallbackList {
+        // TODO(cais): When the need arises, uncomment the following lines and
+        // implement the queue for time values.
+        // private deltaTBatch: number;
+        // private deltaTsBatchBegin: Array<number>;
+        // private deltaTsBatchEnd: Array<number>;
+        /**
+         * Constructor of CallbackList.
+         * @param callbacks Array of `Callback` instances.
+         * @param queueLength Queue length for keeping running statistics over
+         *   callback execution time.
+         */
+        constructor(callbacks, queueLength = 10) {
+          // TODO(cais): Make use of queueLength when implementing the queue for time
+          // values.
+          if (callbacks == null) {
+            callbacks = [];
+          }
+          this.callbacks = callbacks;
+          this.queueLength = queueLength;
+        }
+        append(callback) {
+          this.callbacks.push(callback);
+        }
+        setParams(params) {
+          for (const callback of this.callbacks) {
+            callback.setParams(params);
+          }
+        }
+        setModel(model) {
+          for (const callback of this.callbacks) {
+            callback.setModel(model);
+          }
+        }
+        /**
+         * Called at the start of an epoch.
+         * @param epoch Index of epoch.
+         * @param logs Dictionary of logs.
+         */
+        async onEpochBegin(epoch, logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          for (const callback of this.callbacks) {
+            await callback.onEpochBegin(epoch, logs);
+          }
+        }
+        /**
+         * Called at the end of an epoch.
+         * @param epoch Index of epoch.
+         * @param logs Dictionary of logs.
+         */
+        async onEpochEnd(epoch, logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          for (const callback of this.callbacks) {
+            await callback.onEpochEnd(epoch, logs);
+          }
+        }
+        /**
+         * Called  right before processing a batch.
+         * @param batch Index of batch within the current epoch.
+         * @param logs Dictionary of logs.
+         */
+        async onBatchBegin(batch, logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          for (const callback of this.callbacks) {
+            await callback.onBatchBegin(batch, logs);
+          }
+        }
+        /**
+         * Called at the end of a batch.
+         * @param batch Index of batch within the current epoch.
+         * @param logs Dictionary of logs.
+         */
+        async onBatchEnd(batch, logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          for (const callback of this.callbacks) {
+            await callback.onBatchEnd(batch, logs);
+          }
+        }
+        /**
+         * Called at the beginning of training.
+         * @param logs Dictionary of logs.
+         */
+        async onTrainBegin(logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          for (const callback of this.callbacks) {
+            await callback.onTrainBegin(logs);
+          }
+        }
+        /**
+         * Called at the end of training.
+         * @param logs Dictionary of logs.
+         */
+        async onTrainEnd(logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          for (const callback of this.callbacks) {
+            await callback.onTrainEnd(logs);
+          }
+        }
+      }
+      /**
+       * Callback that accumulates epoch averages of metrics.
+       *
+       * This callback is automatically applied to every LayersModel.
+       */
+      class base_callbacks_BaseLogger extends BaseCallback {
+        constructor() {
+          super();
+        }
+        async onEpochBegin(epoch) {
+          this.seen = 0;
+          this.totals = {};
+        }
+        async onBatchEnd(batch, logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          const batchSize = logs["size"] == null ? 0 : logs["size"];
+          this.seen += batchSize;
+          for (const key in logs) {
+            const value = logs[key];
+            if (typeof value === "number") {
+              if (!this.totals.hasOwnProperty(key)) {
+                this.totals[key] = 0;
+              }
+              this.totals[key] = this.totals[key] + value * batchSize;
+            } else {
+              let oldTotalsToDispose;
+              if (key in this.totals) {
+                oldTotalsToDispose = this.totals[key];
+              } else {
+                this.totals[key] = 0;
+              }
+              const total = Object(dist["tidy"])(() =>
+                Object(dist["add"])(this.totals[key], Object(dist["mul"])(value, batchSize))
+              );
+              this.totals[key] = total;
+              if (oldTotalsToDispose != null) {
+                oldTotalsToDispose.dispose();
+              }
+            }
+          }
+        }
+        async onEpochEnd(epoch, logs) {
+          if (logs != null) {
+            for (const key of this.params["metrics"]) {
+              if (this.totals[key] == null) {
+                continue;
+              }
+              if (typeof this.totals[key] === "number") {
+                logs[key] = this.totals[key] / this.seen;
+              } else {
+                Object(dist["tidy"])(() => {
+                  const log = Object(dist["mul"])(
+                    Object(dist["div"])(1, this.seen),
+                    this.totals[key]
+                  );
+                  logs[key] = log;
+                  this.totals[key].dispose();
+                  Object(dist["keep"])(logs[key]);
+                });
+              }
+            }
+          }
+        }
+      }
+      /**
+       * Callback that records events into a `History` object. This callback is
+       * automatically applied to every TF.js Layers model. The `History` object
+       * gets returned by the `fit` method of models.
+       */
+      class History extends BaseCallback {
+        async onTrainBegin(logs) {
+          this.epoch = [];
+          this.history = {};
+        }
+        async onEpochEnd(epoch, logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          this.epoch.push(epoch);
+          for (const key in logs) {
+            if (this.history[key] == null) {
+              this.history[key] = [];
+            }
+            this.history[key].push(logs[key]);
+          }
+        }
+        /**
+         * Await the values of all losses and metrics.
+         */
+        async syncData() {
+          const promises = [];
+          const keys = [];
+          const indices = [];
+          for (const key in this.history) {
+            const valueArray = this.history[key];
+            for (let i = 0; i < valueArray.length; ++i) {
+              if (typeof valueArray[i] !== "number") {
+                const valueScalar = valueArray[i];
+                promises.push(valueScalar.data());
+                keys.push(key);
+                indices.push(i);
+              }
+            }
+          }
+          const values = await Promise.all(promises);
+          for (let n = 0; n < values.length; ++n) {
+            const tensorToDispose = this.history[keys[n]][indices[n]];
+            tensorToDispose.dispose();
+            this.history[keys[n]][indices[n]] = values[n][0];
+          }
+        }
+      }
+      /**
+       * Custom callback for training.
+       */
+      class base_callbacks_CustomCallback extends BaseCallback {
+        constructor(args, yieldEvery) {
+          super();
+          this.currentEpoch = 0;
+          this.yieldEvery = yieldEvery || "auto";
+          if (this.yieldEvery === "auto") {
+            this.yieldEvery = DEFAULT_YIELD_EVERY_MS;
+          }
+          if (this.yieldEvery === "never" && args.onYield != null) {
+            throw new Error(
+              "yieldEvery is `never` but you provided an `onYield` callback. " +
+                "Either change `yieldEvery` or remove the callback"
+            );
+          }
+          if (dist["util"].isNumber(this.yieldEvery)) {
+            // Decorate `maybeWait` so it will be called at most once every
+            // `yieldEvery` ms.
+            this.maybeWait = debounce(this.maybeWait.bind(this), this.yieldEvery);
+          }
+          this.trainBegin = args.onTrainBegin;
+          this.trainEnd = args.onTrainEnd;
+          this.epochBegin = args.onEpochBegin;
+          this.epochEnd = args.onEpochEnd;
+          this.batchBegin = args.onBatchBegin;
+          this.batchEnd = args.onBatchEnd;
+          this.yield = args.onYield;
+        }
+        async maybeWait(epoch, batch, logs) {
+          const ps = [];
+          if (this.yield != null) {
+            await resolveScalarsInLogs(logs);
+            ps.push(this.yield(epoch, batch, logs));
+          }
+          ps.push(Object(dist["nextFrame"])());
+          await Promise.all(ps);
+        }
+        async onEpochBegin(epoch, logs) {
+          this.currentEpoch = epoch;
+          if (this.epochBegin != null) {
+            await resolveScalarsInLogs(logs);
+            await this.epochBegin(epoch, logs);
+          }
+        }
+        async onEpochEnd(epoch, logs) {
+          const ps = [];
+          if (this.epochEnd != null) {
+            await resolveScalarsInLogs(logs);
+            ps.push(this.epochEnd(epoch, logs));
+          }
+          if (this.yieldEvery === "epoch") {
+            ps.push(Object(dist["nextFrame"])());
+          }
+          await Promise.all(ps);
+        }
+        async onBatchBegin(batch, logs) {
+          if (this.batchBegin != null) {
+            await resolveScalarsInLogs(logs);
+            await this.batchBegin(batch, logs);
+          }
+        }
+        async onBatchEnd(batch, logs) {
+          const ps = [];
+          if (this.batchEnd != null) {
+            await resolveScalarsInLogs(logs);
+            ps.push(this.batchEnd(batch, logs));
+          }
+          if (this.yieldEvery === "batch") {
+            ps.push(Object(dist["nextFrame"])());
+          } else if (dist["util"].isNumber(this.yieldEvery)) {
+            ps.push(this.maybeWait(this.currentEpoch, batch, logs));
+          }
+          await Promise.all(ps);
+        }
+        async onTrainBegin(logs) {
+          if (this.trainBegin != null) {
+            await resolveScalarsInLogs(logs);
+            await this.trainBegin(logs);
+          }
+        }
+        async onTrainEnd(logs) {
+          if (this.trainEnd != null) {
+            await resolveScalarsInLogs(logs);
+            await this.trainEnd(logs);
+          }
+        }
+      }
+      /**
+       * Standardize callbacks or configurations of them to an Array of callbacks.
+       */
+      function standardizeCallbacks(callbacks, yieldEvery) {
+        if (callbacks == null) {
+          callbacks = {};
+        }
+        if (callbacks instanceof BaseCallback) {
+          return [callbacks];
+        }
+        if (Array.isArray(callbacks) && callbacks[0] instanceof BaseCallback) {
+          return callbacks;
+        }
+        // Convert custom callback configs to custom callback objects.
+        const callbackConfigs = toList(callbacks);
+        return callbackConfigs.map(
+          (callbackConfig) => new base_callbacks_CustomCallback(callbackConfig, yieldEvery)
+        );
+      }
+      /**
+       * A global registry for callback constructors to be used during
+       * LayersModel.fit().
+       */
+      class base_callbacks_CallbackConstructorRegistry {
+        /**
+         * Blocks public access to constructor.
+         */
+        constructor() {}
+        /**
+         * Register a tf.LayersModel.fit() callback constructor.
+         *
+         * The registered callback constructor will be used to instantiate
+         * callbacks for every tf.LayersModel.fit() call afterwards.
+         *
+         * @param verbosityLevel Level of verbosity at which the `callbackConstructor`
+         *   is to be reigstered.
+         * @param callbackConstructor A no-arg constructor for `tf.Callback`.
+         * @throws Error, if the same callbackConstructor has been registered before,
+         *   either at the same or a different `verbosityLevel`.
+         */
+        static registerCallbackConstructor(verbosityLevel, callbackConstructor) {
+          dist["util"].assert(
+            verbosityLevel >= 0 && Number.isInteger(verbosityLevel),
+            () =>
+              `Verbosity level is expected to be an integer >= 0, ` + `but got ${verbosityLevel}`
+          );
+          base_callbacks_CallbackConstructorRegistry.checkForDuplicate(callbackConstructor);
+          if (base_callbacks_CallbackConstructorRegistry.constructors[verbosityLevel] == null) {
+            base_callbacks_CallbackConstructorRegistry.constructors[verbosityLevel] = [];
+          }
+          base_callbacks_CallbackConstructorRegistry.constructors[verbosityLevel].push(
+            callbackConstructor
+          );
+        }
+        static checkForDuplicate(callbackConstructor) {
+          for (const levelName in base_callbacks_CallbackConstructorRegistry.constructors) {
+            const constructors =
+              base_callbacks_CallbackConstructorRegistry.constructors[+levelName];
+            constructors.forEach((ctor) => {
+              if (ctor === callbackConstructor) {
+                throw new ValueError("Duplicate callback constructor.");
+              }
+            });
+          }
+        }
+        /**
+         * Clear all registered callback constructors.
+         */
+        static clear() {
+          base_callbacks_CallbackConstructorRegistry.constructors = {};
+        }
+        /**
+         * Create callbacks using the registered callback constructors.
+         *
+         * Given `verbosityLevel`, all constructors registered at that level or above
+         * will be called and the instantiated callbacks will be used.
+         *
+         * @param verbosityLevel: Level of verbosity.
+         */
+        static createCallbacks(verbosityLevel) {
+          const constructors = [];
+          for (const levelName in base_callbacks_CallbackConstructorRegistry.constructors) {
+            const level = +levelName;
+            if (verbosityLevel >= level) {
+              constructors.push(...base_callbacks_CallbackConstructorRegistry.constructors[level]);
+            }
+          }
+          return constructors.map((ctor) => new ctor());
+        }
+      }
+      base_callbacks_CallbackConstructorRegistry.constructors = {};
+      function configureCallbacks(
+        callbacks,
+        verbose,
+        epochs,
+        initialEpoch,
+        numTrainSamples,
+        stepsPerEpoch,
+        batchSize,
+        doValidation,
+        callbackMetrics
+      ) {
+        const history = new History();
+        const actualCallbacks = [
+          new base_callbacks_BaseLogger(),
+          ...base_callbacks_CallbackConstructorRegistry.createCallbacks(verbose),
+        ];
+        if (callbacks != null) {
+          actualCallbacks.push(...callbacks);
+        }
+        actualCallbacks.push(history);
+        const callbackList = new CallbackList(actualCallbacks);
+        // TODO(cais): Figure out when this LayersModel instance can have a
+        // dynamically
+        //   set property called 'callback_model' as in PyKeras.
+        callbackList.setParams({
+          epochs,
+          initialEpoch,
+          samples: numTrainSamples,
+          steps: stepsPerEpoch,
+          batchSize,
+          verbose,
+          doValidation,
+          metrics: callbackMetrics,
+        });
+        return { callbackList, history };
+      }
+      //# sourceMappingURL=base_callbacks.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/serialization.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original Source layers/__init__.py */
+
+      /**
+       * Instantiate a layer from a config dictionary.
+       * @param config dict of the form {class_name: str, config: dict}
+       * @param customObjects dict mapping class names (or function names)
+       *   of custom (non-Keras) objects to class/functions
+       * @param fastWeightInit Optional flag to use fast weight initialization
+       *   during deserialization. This is applicable to cases in which
+       *   the initialization will be immediately overwritten by loaded weight
+       *   values. Default: `false`.
+       * @returns Layer instance (may be LayersModel, Sequential, Layer...)
+       */
+      function deserialize(config, customObjects = {}, fastWeightInit = false) {
+        return deserializeKerasObject(
+          config,
+          dist["serialization"].SerializationMap.getMap().classNameMap,
+          customObjects,
+          "layer",
+          fastWeightInit
+        );
+      }
+      //# sourceMappingURL=serialization.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/losses.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original Source: losses.py */
+
+      /**
+       * Normalizes a tensor wrt the L2 norm alongside the specified axis.
+       * @param x
+       * @param axis Axis along which to perform normalization.
+       */
+      function l2Normalize(x, axis) {
+        return Object(dist["tidy"])(() => {
+          if (x.dtype !== "float32") {
+            x = x.asType("float32");
+          }
+          const squareSum = dist["sum"](square(x), axis, true);
+          const epsilonTensor = dist["fill"](squareSum.shape, common_epsilon());
+          const norm = dist["sqrt"](dist["maximum"](squareSum, epsilonTensor));
+          return dist["div"](x, norm);
+        });
+      }
+      function meanSquaredError(yTrue, yPred) {
+        return Object(dist["tidy"])(() => dist["mean"](square(dist["sub"](yPred, yTrue)), -1));
+      }
+      function meanAbsoluteError(yTrue, yPred) {
+        return Object(dist["tidy"])(() => dist["mean"](dist["abs"](dist["sub"](yPred, yTrue)), -1));
+      }
+      function meanAbsolutePercentageError(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const diff = dist["sub"](yTrue, yPred);
+          const clippedTrue = dist["clipByValue"](
+            dist["abs"](yTrue),
+            common_epsilon(),
+            Number.MAX_VALUE
+          );
+          const absResult = dist["abs"](dist["div"](diff, clippedTrue));
+          return dist["mul"](100, dist["mean"](absResult, -1));
+        });
+      }
+      function meanSquaredLogarithmicError(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const clippedPred = dist["clipByValue"](yPred, common_epsilon(), Number.MAX_VALUE);
+          const firstLog = dist["log"](dist["add"](1, clippedPred));
+          const clippedTrue = dist["clipByValue"](yTrue, common_epsilon(), Number.MAX_VALUE);
+          const secondLog = dist["log"](dist["add"](1, clippedTrue));
+          return dist["mean"](square(dist["sub"](firstLog, secondLog)), -1);
+        });
+      }
+      function squaredHinge(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const maxResult = dist["maximum"](0, dist["sub"](1, dist["mul"](yTrue, yPred)));
+          return dist["mean"](square(maxResult), -1);
+        });
+      }
+      function hinge(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const maxResult = dist["maximum"](0, dist["sub"](1, dist["mul"](yTrue, yPred)));
+          return dist["mean"](maxResult, -1);
+        });
+      }
+      function categoricalHinge(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const pos = dist["sum"](dist["mul"](yTrue, yPred), -1);
+          const neg = dist["max"](dist["mul"](dist["sub"](1, yTrue), yPred), -1);
+          return dist["maximum"](0, dist["add"](1, dist["sub"](neg, pos)));
+        });
+      }
+      /**
+       * Logarithm of the hyperbolic cosine of the prediction error.
+       *
+       * `log(cosh(x))` is approximately equal to `(x ** 2) / 2` for small `x` and
+       * to `abs(x) - log(2)` for large `x`. This means that 'logcosh' works mostly
+       * like the mean squared error, but will not be so strongly affected by the
+       * occasional wildly incorrect prediction.
+       */
+      function logcosh(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const log2 = Math.log(2);
+          const predictionDiff = dist["sub"](yPred, yTrue);
+          const logcoshResult = dist["sub"](
+            dist["add"](predictionDiff, dist["softplus"](dist["mul"](-2, predictionDiff))),
+            log2
+          );
+          return dist["mean"](logcoshResult, -1);
+        });
+      }
+      function categoricalCrossentropy(target, output, fromLogits = false) {
+        return Object(dist["tidy"])(() => {
+          if (fromLogits) {
+            output = dist["softmax"](output);
+          } else {
+            // scale preds so that the class probabilities of each sample sum to 1.
+            const outputSum = dist["sum"](output, output.shape.length - 1, true);
+            output = dist["div"](output, outputSum);
+          }
+          output = dist["clipByValue"](output, common_epsilon(), 1 - common_epsilon());
+          return dist["neg"](
+            dist["sum"](dist["mul"](target.toFloat(), dist["log"](output)), output.shape.length - 1)
+          );
+        });
+      }
+      /**
+       * Categorical crossentropy with integer targets.
+       *
+       * @param target An integer tensor.
+       * @param output A tensor resulting from a softmax (unless `fromLogits` is
+       *  `true`, in which case `output` is expected to be the logits).
+       * @param fromLogits Boolean, whether `output` is the result of a softmax, or is
+       *   a tensor of logits.
+       */
+      function sparseCategoricalCrossentropy(target, output, fromLogits = false) {
+        return Object(dist["tidy"])(() => {
+          const flatTarget = dist["floor"](flatten(target)).toInt();
+          output = dist["clipByValue"](output, common_epsilon(), 1 - common_epsilon());
+          const outputShape = output.shape;
+          const oneHotTarget = dist["oneHot"](
+            flatTarget,
+            outputShape[outputShape.length - 1]
+          ).reshape(outputShape);
+          return categoricalCrossentropy(oneHotTarget, output, fromLogits);
+        });
+      }
+      /**
+       * From TensorFlow's implementation in nn_impl.py:
+       *
+       * For brevity, let `x = logits`, `z = labels`.  The logistic loss is
+       *      z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
+       *    = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
+       *    = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
+       *    = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
+       *    = (1 - z) * x + log(1 + exp(-x))
+       *    = x - x * z + log(1 + exp(-x))
+       * For x < 0, to avoid overflow in exp(-x), we reformulate the above
+       *      x - x * z + log(1 + exp(-x))
+       *    = log(exp(x)) - x * z + log(1 + exp(-x))
+       *    = - x * z + log(1 + exp(x))
+       * Hence, to ensure stability and avoid overflow, the implementation uses this
+       * equivalent formulation
+       *    max(x, 0) - x * z + log(1 + exp(-abs(x)))
+       *
+       * @param labels The labels.
+       * @param logits The logits.
+       */
+      function sigmoidCrossEntropyWithLogits(labels, logits) {
+        if (!dist["util"].arraysEqual(labels.shape, logits.shape)) {
+          throw new ValueError(
+            `logits and labels must have the same shape, but got shapes ` +
+              `${JSON.stringify(labels.shape)} and ${JSON.stringify(logits.shape)}`
+          );
+        }
+        return Object(dist["tidy"])(() => {
+          // The logistic loss formula from above is
+          //   x - x * z + log(1 + exp(-x))
+          // For x < 0, a more numerically stable formula is
+          //   -x * z + log(1 + exp(x))
+          // Note that these two expressions can be combined into the following:
+          //   max(x, 0) - x * z + log(1 + exp(-abs(x)))
+          const reluLogits = logits.relu();
+          const negAbsLogits = logits.abs().neg();
+          return reluLogits.sub(logits.mul(labels)).add(negAbsLogits.exp().log1p());
+        });
+      }
+      function binaryCrossentropy(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          let y;
+          y = dist["clipByValue"](yPred, common_epsilon(), 1 - common_epsilon());
+          y = dist["log"](dist["div"](y, dist["sub"](1, y)));
+          return dist["mean"](sigmoidCrossEntropyWithLogits(yTrue, y), -1);
+        });
+      }
+      function kullbackLeiblerDivergence(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const clippedTrue = dist["clipByValue"](yTrue, common_epsilon(), 1);
+          const clippedPred = dist["clipByValue"](yPred, common_epsilon(), 1);
+          return dist["sum"](
+            dist["mul"](yTrue, dist["log"](dist["div"](clippedTrue, clippedPred))),
+            -1
+          );
+        });
+      }
+      function poisson(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const logPred = dist["log"](dist["add"](common_epsilon(), yPred));
+          return dist["mean"](dist["sub"](yPred, dist["mul"](yTrue, logPred)), -1);
+        });
+      }
+      function cosineProximity(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const trueNormalized = l2Normalize(yTrue, -1);
+          const predNormalized = l2Normalize(yPred, -1);
+          const trueXPred = dist["mul"](trueNormalized, predNormalized);
+          return dist["neg"](dist["sum"](trueXPred, -1));
+        });
+      }
+      const mse = meanSquaredError;
+      const MSE = meanSquaredError;
+      const mae = meanAbsoluteError;
+      const MAE = meanAbsoluteError;
+      const mape = meanAbsolutePercentageError;
+      const MAPE = meanAbsolutePercentageError;
+      const msle = meanSquaredLogarithmicError;
+      const MSLE = meanSquaredLogarithmicError;
+      const kld = kullbackLeiblerDivergence;
+      const KLD = kullbackLeiblerDivergence;
+      const cosine = cosineProximity;
+      // TODO(michaelterry): Add deserialize() function.
+      const lossesMap = {
+        meanSquaredError,
+        meanAbsoluteError,
+        meanAbsolutePercentageError,
+        meanSquaredLogarithmicError,
+        squaredHinge,
+        hinge,
+        categoricalHinge,
+        logcosh,
+        categoricalCrossentropy,
+        sparseCategoricalCrossentropy,
+        binaryCrossentropy,
+        kullbackLeiblerDivergence,
+        poisson,
+        cosineProximity,
+      };
+      // Porting note: This diverges from the PyKeras implementation and may need to
+      // change based on (de)serialization requirements.
+      function get(identifierOrFn) {
+        if (typeof identifierOrFn === "string") {
+          if (identifierOrFn in lossesMap) {
+            return lossesMap[identifierOrFn];
+          }
+          let errMsg = `Unknown loss ${identifierOrFn}`;
+          if (identifierOrFn.toLowerCase().includes("softmaxcrossentropy")) {
+            errMsg =
+              `Unknown loss ${identifierOrFn}. ` +
+              'Use "categoricalCrossentropy" as the string name for ' +
+              "tf.losses.softmaxCrossEntropy";
+          }
+          throw new ValueError(errMsg);
+        } else {
+          return identifierOrFn;
+        }
+      }
+      //# sourceMappingURL=losses.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/metrics.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Built-in metrics.
+       */
+
+      function binaryAccuracy(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const threshold = dist["mul"](0.5, dist["onesLike"](yPred));
+          const yPredThresholded = cast(dist["greater"](yPred, threshold), yTrue.dtype);
+          return dist["mean"](dist["equal"](yTrue, yPredThresholded), -1);
+        });
+      }
+      function categoricalAccuracy(yTrue, yPred) {
+        return Object(dist["tidy"])(() =>
+          cast(dist["equal"](dist["argMax"](yTrue, -1), dist["argMax"](yPred, -1)), "float32")
+        );
+      }
+      function truePositives(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          return dist["logicalAnd"](yTrue.equal(1), yPred.equal(1)).sum().cast("float32");
+        });
+      }
+      function falseNegatives(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          return dist["logicalAnd"](yTrue.equal(1), yPred.equal(0)).sum().cast("float32");
+        });
+      }
+      function falsePositives(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          return dist["logicalAnd"](yTrue.equal(0), yPred.equal(1)).sum().cast("float32");
+        });
+      }
+      function precision(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const tp = truePositives(yTrue, yPred);
+          const fp = falsePositives(yTrue, yPred);
+          const denominator = tp.add(fp);
+          return dist["where"](dist["greater"](denominator, 0), tp.div(denominator), 0).cast(
+            "float32"
+          );
+        });
+      }
+      function recall(yTrue, yPred) {
+        return Object(dist["tidy"])(() => {
+          const tp = truePositives(yTrue, yPred);
+          const fn = falseNegatives(yTrue, yPred);
+          const denominator = tp.add(fn);
+          return dist["where"](dist["greater"](denominator, 0), tp.div(denominator), 0).cast(
+            "float32"
+          );
+        });
+      }
+      function metrics_binaryCrossentropy(yTrue, yPred) {
+        return binaryCrossentropy(yTrue, yPred);
+      }
+      function sparseCategoricalAccuracy(yTrue, yPred) {
+        if (yTrue.rank === yPred.rank) {
+          yTrue = yTrue.squeeze([yTrue.rank - 1]);
+        }
+        yPred = yPred.argMax(-1);
+        if (yPred.dtype !== yTrue.dtype) {
+          yPred = yPred.asType(yTrue.dtype);
+        }
+        return dist["equal"](yTrue, yPred).asType("float32");
+      }
+      function topKCategoricalAccuracy(yTrue, yPred) {
+        throw new NotImplementedError();
+      }
+      function sparseTopKCategoricalAccuracy(yTrue, yPred) {
+        throw new NotImplementedError();
+      }
+      // Aliases.
+      const metrics_mse = meanSquaredError;
+      const metrics_MSE = meanSquaredError;
+      const metrics_mae = meanAbsoluteError;
+      const metrics_MAE = meanAbsoluteError;
+      const metrics_mape = meanAbsolutePercentageError;
+      const metrics_MAPE = meanAbsolutePercentageError;
+      const metrics_categoricalCrossentropy = categoricalCrossentropy;
+      const metrics_cosine = cosineProximity;
+      const metrics_sparseCategoricalCrossentropy = sparseCategoricalCrossentropy;
+      // TODO(cais, nielsene): Add serialize().
+      const metricsMap = {
+        binaryAccuracy,
+        categoricalAccuracy,
+        precision,
+        categoricalCrossentropy: metrics_categoricalCrossentropy,
+        sparseCategoricalCrossentropy: metrics_sparseCategoricalCrossentropy,
+        mse: metrics_mse,
+        MSE: metrics_MSE,
+        mae: metrics_mae,
+        MAE: metrics_MAE,
+        mape: metrics_mape,
+        MAPE: metrics_MAPE,
+        cosine: metrics_cosine,
+      };
+      function metrics_get(identifier) {
+        if (typeof identifier === "string" && identifier in metricsMap) {
+          return metricsMap[identifier];
+        } else if (typeof identifier !== "string" && identifier != null) {
+          return identifier;
+        } else {
+          throw new ValueError(`Unknown metric ${identifier}`);
+        }
+      }
+      /**
+       * Get the shortcut function name.
+       *
+       * If the fn name is a string,
+       *   directly return the string name.
+       * If the function is included in metricsMap or lossesMap,
+       *   return key of the map.
+       *   - If the function relative to multiple keys,
+       *     return the first found key as the function name.
+       *   - If the function exists in both lossesMap and metricsMap,
+       *     search lossesMap first.
+       * If the function is not included in metricsMap or lossesMap,
+       *   return the function name.
+       *
+       * @param fn loss function, metric function, or short cut name.
+       * @returns Loss or Metric name in string.
+       */
+      function getLossOrMetricName(fn) {
+        assert(fn !== null, `Unknown LossOrMetricFn ${fn}`);
+        if (typeof fn === "string") {
+          return fn;
+        } else {
+          let fnName;
+          for (const key of Object.keys(lossesMap)) {
+            if (lossesMap[key] === fn) {
+              fnName = key;
+              break;
+            }
+          }
+          if (fnName !== undefined) {
+            return fnName;
+          }
+          for (const key of Object.keys(metricsMap)) {
+            if (metricsMap[key] === fn) {
+              fnName = key;
+              break;
+            }
+          }
+          if (fnName !== undefined) {
+            return fnName;
+          }
+          return fn.name;
+        }
+      }
+      //# sourceMappingURL=metrics.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/optimizers.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Optimizers.
+       */
+
+      // Add (de)serialize()
+      // Porting note: This diverges from the PyKeras implementation and may need to
+      // change based on (de)serialization requirements.
+      function getOptimizer(identifier) {
+        const optimizerMap = {
+          Adagrad: () => dist["train"].adagrad(0.01),
+          Adadelta: () => dist["train"].adadelta(1, 0.95, common_epsilon()),
+          Adam: () => dist["train"].adam(0.001, 0.9, 0.999, common_epsilon()),
+          Adamax: () => dist["train"].adamax(0.002, 0.9, 0.999, common_epsilon(), 0),
+          RMSProp: () => dist["train"].rmsprop(0.001, 0.9, 0, common_epsilon()),
+          SGD: () => dist["train"].sgd(0.01),
+        };
+        optimizerMap["adagrad"] = optimizerMap["Adagrad"];
+        optimizerMap["adadelta"] = optimizerMap["Adadelta"];
+        optimizerMap["adam"] = optimizerMap["Adam"];
+        optimizerMap["adamax"] = optimizerMap["Adamax"];
+        optimizerMap["rmsprop"] = optimizerMap["RMSProp"];
+        optimizerMap["sgd"] = optimizerMap["SGD"];
+        if (identifier in optimizerMap) {
+          return optimizerMap[identifier]();
+        }
+        throw new ValueError(`Unknown Optimizer ${identifier}`);
+      }
+      //# sourceMappingURL=optimizers.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/user_defined_metadata.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /** Utility functions related to user-defined metadata. */
+      // Maximum recommended serialized size for user-defined metadata.
+      // Beyond this limit, a warning message will be printed during model loading and
+      // saving.
+      const MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH = 1 * 1024 * 1024;
+      /**
+       * Check validity of user-defined metadata.
+       *
+       * @param userDefinedMetadata
+       * @param modelName Name of the model that the user-defined metadata belongs to.
+       *   Used during construction of error messages.
+       * @param checkSize Whether to check the size of the metadata is under
+       *   recommended limit. Default: `false`. If `true`, will try stringify the
+       *   JSON object and print a console warning if the serialzied size is above the
+       *   limit.
+       * @throws Error if `userDefinedMetadata` is not a plain JSON object.
+       */
+      function checkUserDefinedMetadata(userDefinedMetadata, modelName, checkSize = false) {
+        if (
+          userDefinedMetadata == null ||
+          typeof userDefinedMetadata !== "object" ||
+          Object.getPrototypeOf(userDefinedMetadata) !== Object.prototype ||
+          !plainObjectCheck(userDefinedMetadata)
+        ) {
+          throw new Error("User-defined metadata is expected to be a JSON object, but is not.");
+        }
+        if (checkSize) {
+          const out = JSON.stringify(userDefinedMetadata);
+          if (out.length > MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH) {
+            console.warn(
+              `User-defined metadata of model "${modelName}" is too large in ` +
+                `size (length=${out.length} when serialized). It is not ` +
+                `recommended to store such large objects in user-defined metadata. ` +
+                `Please make sure its serialized length is <= ` +
+                `${MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH}.`
+            );
+          }
+        }
+      }
+      /**
+       * Check if an input is plain JSON object or any valid subfield of it.
+       *
+       * @param x The input to be checked.
+       * @param assertObject Whether to assert `x` is a JSON object, i.e., reject
+       *   cases of arrays and primitives.
+       * @return Returns `true` if and only if `x` is a plain JSON object,
+       *   a JSON-valid primitive including string, number, boolean and null,
+       *   or an array of the said types.
+       */
+      // tslint:disable-next-line:no-any
+      function plainObjectCheck(x) {
+        if (x === null) {
+          // Note: typeof `null` is 'object', and `null` is valid in JSON.
+          return true;
+        } else if (typeof x === "object") {
+          if (Object.getPrototypeOf(x) === Object.prototype) {
+            // `x` is a JavaScript object and its prototype is Object.
+            const keys = Object.keys(x);
+            for (const key of keys) {
+              if (typeof key !== "string") {
+                // JSON keys must be strings.
+                return false;
+              }
+              if (!plainObjectCheck(x[key])) {
+                // Recursive call.
+                return false;
+              }
+            }
+            return true;
+          } else {
+            // `x` is a JavaScript object but its prototype is not Object.
+            if (Array.isArray(x)) {
+              // `x` is a JavaScript array.
+              for (const item of x) {
+                if (!plainObjectCheck(item)) {
+                  // Recursive call.
+                  return false;
+                }
+              }
+              return true;
+            } else {
+              // `x` is a JavaScript object and its prototype is not Object,
+              // and it's not an Array. I.e., it's a complex object such as
+              // `Error` and `Date`.
+              return false;
+            }
+          }
+        } else {
+          // `x` is not a JavaScript object or `null`.
+          const xType = typeof x;
+          return xType === "string" || xType === "number" || xType === "boolean";
+        }
+      }
+      //# sourceMappingURL=user_defined_metadata.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/layer_utils.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      /**
+       * Print the summary of a LayersModel object.
+       *
+       * @param model tf.LayersModel instance.
+       * @param lineLength Total length of printed lines. Set this to adapt to the
+       *   display to different terminal or console sizes.
+       * @param positions Relative or absolute positions of log elements in each
+       *   line. Each number corresponds to right-most (i.e., ending) position of a
+       *   column.
+       *   If not provided, defaults to `[0.45, 0.85, 1]` for sequential-like
+       *   models and `[0.33, 0.55, 0.67, 1]` for non-sequential like models.
+       * @param printFn Print function to use.
+       *   It will be called on each line of the summary. You can provide a custom
+       *   function in order to capture the string summary. Defaults to `console.log`.
+       */
+      function printSummary(
+        model,
+        lineLength,
+        positions,
+        // tslint:disable-next-line:no-any
+        printFn = console.log
+      ) {
+        const sequentialLike = isModelSequentialLike(model);
+        // Header names for different log elements.
+        const toDisplay = ["Layer (type)", "Output shape", "Param #"];
+        if (sequentialLike) {
+          lineLength = lineLength || 65;
+          positions = positions || [0.45, 0.85, 1];
+        } else {
+          lineLength = lineLength || 98;
+          positions = positions || [0.33, 0.55, 0.67, 1];
+          // Header names for different log elements.
+        }
+        if (positions[positions.length - 1] <= 1) {
+          // `positions` is relative. Convert it to absolute positioning.
+          positions = positions.map((p) => Math.floor(lineLength * p));
+        }
+        let relevantNodes;
+        if (!sequentialLike) {
+          toDisplay.push("Receives inputs");
+          relevantNodes = [];
+          for (const depth in model.nodesByDepth) {
+            relevantNodes.push(...model.nodesByDepth[depth]);
+          }
+        }
+        printFn("_".repeat(lineLength));
+        printRow(toDisplay, positions, printFn);
+        printFn("=".repeat(lineLength));
+        const layers = model.layers;
+        for (let i = 0; i < layers.length; ++i) {
+          if (sequentialLike) {
+            printLayerSummary(layers[i], positions, printFn);
+          } else {
+            printLayerSummaryWithConnections(layers[i], positions, relevantNodes, printFn);
+          }
+          printFn((i === layers.length - 1 ? "=" : "_").repeat(lineLength));
+        }
+        // tslint:disable-next-line:no-any
+        model.checkTrainableWeightsConsistency();
+        const trainableCount = countTrainableParams(model);
+        const nonTrainableCount = countParamsInWeights(model.nonTrainableWeights);
+        printFn(`Total params: ${trainableCount + nonTrainableCount}`);
+        printFn(`Trainable params: ${trainableCount}`);
+        printFn(`Non-trainable params: ${nonTrainableCount}`);
+        printFn("_".repeat(lineLength));
+      }
+      function countTrainableParams(model) {
+        let trainableCount;
+        // tslint:disable:no-any
+        if (model.collectedTrainableWeights != null) {
+          trainableCount = countParamsInWeights(model.collectedTrainableWeights);
+        } else {
+          trainableCount = countParamsInWeights(model.trainableWeights);
+        }
+        // tslint:enable:no-any
+        return trainableCount;
+      }
+      function isModelSequentialLike(model) {
+        let sequentialLike = true;
+        const nodesByDepth = [];
+        const nodes = [];
+        for (const depth in model.nodesByDepth) {
+          nodesByDepth.push(model.nodesByDepth[depth]);
+        }
+        for (const depthNodes of nodesByDepth) {
+          if (
+            depthNodes.length > 1 ||
+            (depthNodes.length === 1 && depthNodes[0].inboundLayers.length > 1)
+          ) {
+            sequentialLike = false;
+            break;
+          }
+          nodes.push(...depthNodes);
+        }
+        if (sequentialLike) {
+          // Search for shared layers.
+          for (const layer of model.layers) {
+            let flag = false;
+            for (const node of layer.inboundNodes) {
+              if (nodes.indexOf(node) !== -1) {
+                if (flag) {
+                  sequentialLike = false;
+                  break;
+                } else {
+                  flag = true;
+                }
+              }
+            }
+            if (!sequentialLike) {
+              break;
+            }
+          }
+        }
+        return sequentialLike;
+      }
+      function printRow(
+        fields,
+        positions,
+        // tslint:disable-next-line:no-any
+        printFn = console.log
+      ) {
+        let line = "";
+        for (let i = 0; i < fields.length; ++i) {
+          if (i > 0) {
+            line = line.slice(0, line.length - 1) + " ";
+          }
+          line += fields[i];
+          line = line.slice(0, positions[i]);
+          line += " ".repeat(positions[i] - line.length);
+        }
+        printFn(line);
+      }
+      /**
+       * Prints a summary for a single Layer, without connectivity information.
+       *
+       * @param layer: Layer instance to print.
+       */
+      function printLayerSummary(
+        layer,
+        positions,
+        // tslint:disable-next-line:no-any
+        printFn
+      ) {
+        let outputShape;
+        try {
+          outputShape = JSON.stringify(layer.outputShape);
+        } catch (err) {
+          outputShape = "multiple";
+        }
+        const name = layer.name;
+        const className = layer.getClassName();
+        const fields = [`${name} (${className})`, outputShape, layer.countParams().toString()];
+        printRow(fields, positions, printFn);
+      }
+      /**
+       * Prints a summary for a single Layer, with connectivity information.
+       */
+      function printLayerSummaryWithConnections(
+        layer,
+        positions,
+        relevantNodes,
+        // tslint:disable-next-line:no-any
+        printFn
+      ) {
+        let outputShape;
+        try {
+          outputShape = JSON.stringify(layer.outputShape);
+        } catch (err) {
+          outputShape = "multiple";
+        }
+        const connections = [];
+        for (const node of layer.inboundNodes) {
+          if (
+            relevantNodes != null &&
+            relevantNodes.length > 0 &&
+            relevantNodes.indexOf(node) === -1
+          ) {
+            continue;
+          }
+          for (let i = 0; i < node.inboundLayers.length; ++i) {
+            const inboundLayer = node.inboundLayers[i].name;
+            const inboundLayerIndex = node.nodeIndices[i];
+            const inboundTensorIndex = node.tensorIndices[i];
+            connections.push(`${inboundLayer}[${inboundLayerIndex}][${inboundTensorIndex}]`);
+          }
+        }
+        const name = layer.name;
+        const className = layer.getClassName();
+        const firstConnection = connections.length === 0 ? "" : connections[0];
+        const fields = [
+          `${name} (${className})`,
+          outputShape,
+          layer.countParams().toString(),
+          firstConnection,
+        ];
+        printRow(fields, positions, printFn);
+        for (let i = 1; i < connections.length; ++i) {
+          printRow(["", "", "", connections[i]], positions, printFn);
+        }
+      }
+      //# sourceMappingURL=layer_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/serialization_utils.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      // tslint:enable
+      /**
+       * Test whether a value in an array is the name of a LayersModel or Layer.
+       * @param key The key name that the value is found under. Note that the key
+       *   may not be at the level immediately above the value, if the value is in a
+       *   nested array.
+       * @param index Index of the value in the Array that it is found in.
+       * @param value The value object.
+       * @returns A boolean indicating whether value is a name.
+       */
+      function isArrayItemInputOrOutputName(key, index, value) {
+        return (
+          (key === "inboundNodes" || key === "outputLayers" || key === "inputLayers") &&
+          index === 0 &&
+          typeof value === "string"
+        );
+      }
+      /**
+       * Convert a Pythonic config object to TypeScript config object.
+       * @param pythonicConfig The config object to convert.
+       * @param key Optional key name of the object being converted.
+       * @returns Result of the conversion.
+       */
+      function convertPythonicToTs(pythonicConfig, key) {
+        if (pythonicConfig === null) {
+          return null;
+        } else if (typeof pythonicConfig === "string") {
+          return toCamelCase(pythonicConfig);
+        } else if (typeof pythonicConfig === "number" || typeof pythonicConfig === "boolean") {
+          return pythonicConfig;
+        } else if (pythonicConfig instanceof Array) {
+          const tsArray = [];
+          const arrayLength = pythonicConfig.length;
+          for (let i = 0; i < arrayLength; ++i) {
+            const item = pythonicConfig[i];
+            if (isArrayItemInputOrOutputName(key, i, item)) {
+              tsArray.push(item);
+            } else {
+              tsArray.push(convertPythonicToTs(item, key));
+            }
+          }
+          return tsArray;
+        } else {
+          const tsDict = {};
+          for (const pythonicKey of Object.keys(pythonicConfig)) {
+            const pythonicValue = pythonicConfig[pythonicKey];
+            if (pythonicKey === "name" && typeof pythonicValue === "string") {
+              // Special case the 'name' key with a string value. Name values, such as
+              // the names of LayersModel and Layer instances, should not undergo the
+              // camel-case conversion.
+              tsDict[pythonicKey] = pythonicValue;
+            } else {
+              const tsKey = toCamelCase(pythonicKey);
+              tsDict[tsKey] = convertPythonicToTs(pythonicValue, tsKey);
+            }
+          }
+          return tsDict;
+        }
+      }
+      /**
+       * Convert a TypeScript config object to Python config object.
+       * @param tsConfig The config object to convert.
+       * @param key Optional key name of the object being converted.
+       * @returns Result of the conversion.
+       */
+      function convertTsToPythonic(tsConfig, key) {
+        if (tsConfig === null || tsConfig === undefined) {
+          return null;
+        } else if (typeof tsConfig === "string") {
+          return toSnakeCase(tsConfig);
+        } else if (typeof tsConfig === "number" || typeof tsConfig === "boolean") {
+          return tsConfig;
+        } else if (tsConfig instanceof Array) {
+          const pyArray = [];
+          const arrayLength = tsConfig.length;
+          for (let i = 0; i < arrayLength; ++i) {
+            const item = tsConfig[i];
+            if (isArrayItemInputOrOutputName(key, i, item)) {
+              pyArray.push(item);
+            } else {
+              pyArray.push(convertTsToPythonic(item, key));
+            }
+          }
+          return pyArray;
+        } else {
+          const pyDict = {};
+          for (const tsKey of Object.keys(tsConfig)) {
+            const tsValue = tsConfig[tsKey];
+            const pyKey = toSnakeCase(tsKey);
+            if ((tsKey === "name" || tsKey === "className") && typeof tsValue === "string") {
+              // Special case the 'name' key with a string value. Name values, such as
+              // the names of LayersModel and Layer instances, should not undergo the
+              // snake-case conversion.
+              pyDict[pyKey] = tsValue;
+            } else {
+              pyDict[pyKey] = convertTsToPythonic(tsValue, tsKey);
+            }
+          }
+          return pyDict;
+        }
+      }
+      //# sourceMappingURL=serialization_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/version.js
+      /** @license See the LICENSE file. */
+      // This code is auto-generated, do not modify this file!
+      const version = "2.0.1";
+
+      //# sourceMappingURL=version.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/executor.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Executor: Evaluates SymbolicTensor based on feeds.
+       */
+
+      /**
+       * Helper function to check the dtype and shape compatibility of a feed value.
+       */
+      function assertFeedCompatibility(key, val) {
+        // Check dtype compatibility.
+        if (key.dtype == null || key.dtype === val.dtype) {
+          //  a.  If types match, return val tensor as is.
+          return val;
+        }
+        try {
+          //  b. Attempt to convert to expected type.
+          return Object(dist["cast"])(val, key.dtype);
+        } catch (err) {
+          //  c. If conversion fails, return helpful error.
+          throw new ValueError(
+            `The dtype of the feed (${val.dtype}) can not be cast to the dtype ` +
+              `of the key '${key.name}' (${key.dtype}).`
+          );
+        }
+      }
+      /**
+       * FeedDict: A mapping from unique SymbolicTensors to feed values for them.
+       * A feed value is a concrete value represented as an `Tensor`.
+       */
+      class executor_FeedDict {
+        /**
+         * Constructor, optionally does copy-construction.
+         * @param feeds An Array of `Feed`s, or another `FeedDict`, in which case
+         *   copy-construction will be performed.
+         */
+        constructor(feeds) {
+          this.id2Value = {};
+          this.id2Mask = {};
+          this.name2Id = {};
+          if (feeds instanceof executor_FeedDict) {
+            for (const id in feeds.id2Value) {
+              this.id2Value[id] = feeds.id2Value[id];
+              if (id in feeds.id2Mask) {
+                this.id2Mask[id] = feeds.id2Mask[id];
+              }
+            }
+          } else {
+            if (feeds == null) {
+              return;
+            }
+            for (const feed of feeds) {
+              this.add(feed.key, feed.value);
+            }
+          }
+        }
+        /**
+         * Add a key-value pair to the FeedDict.
+         *
+         * @param key The key of the feed.
+         * @param value The value of the tensor feed.
+         * @param mask The value of the mask feed (optional).
+         * @returns This `FeedDict`.
+         * @throws ValueError: If the key `SymbolicTensor` already exists in the
+         *   `FeedDict`.
+         */
+        add(key, value, mask) {
+          if (this.id2Value[key.id] == null) {
+            this.id2Value[key.id] = assertFeedCompatibility(key, value);
+            this.name2Id[key.name] = key.id;
+            if (mask != null) {
+              this.id2Mask[key.id] = mask;
+            }
+          } else {
+            throw new ValueError(`Duplicate key: name=${key.name}, id=${key.id}`);
+          }
+          return this;
+        }
+        /**
+         * Add a Feed to the FeedDict.
+         * @param feed The new `Feed` to add.
+         * @returns This `FeedDict`.
+         */
+        addFeed(feed) {
+          this.add(feed.key, feed.value);
+        }
+        /**
+         * Probe whether a key already exists in the FeedDict.
+         * @param key
+         */
+        hasKey(key) {
+          return this.id2Value[key.id] != null;
+        }
+        /**
+         * Get all the SymbolicTensor available in this FeedDict.
+         */
+        names() {
+          return Object.keys(this.name2Id);
+        }
+        /**
+         * Get the feed value for given key.
+         * @param key The SymbolicTensor, or its name (as a string), of which the
+         *     value is sought.
+         * @returns If `key` exists, the corresponding feed value.
+         * @throws ValueError: If `key` does not exist in this `FeedDict`.
+         */
+        getValue(key) {
+          if (key instanceof topology_SymbolicTensor) {
+            if (this.id2Value[key.id] == null) {
+              throw new ValueError(`Nonexistent key: ${key.name}`);
+            } else {
+              return this.id2Value[key.id];
+            }
+          } else {
+            const id = this.name2Id[key];
+            if (id == null) {
+              throw new ValueError(`Feed dict has no SymbolicTensor name: ${key}`);
+            }
+            return this.id2Value[id];
+          }
+        }
+        /**
+         * Get the feed mask for given key.
+         * @param key The SymbolicTensor, or its name (as a string), of which the
+         *     value is sought.
+         * @returns If `key` exists, the corresponding feed mask.
+         * @throws ValueError: If `key` does not exist in this `FeedDict`.
+         */
+        getMask(key) {
+          if (key instanceof topology_SymbolicTensor) {
+            if (this.id2Value[key.id] == null) {
+              throw new ValueError(`Nonexistent key: ${key.name}`);
+            } else {
+              return this.id2Mask[key.id];
+            }
+          } else {
+            const id = this.name2Id[key];
+            if (id == null) {
+              throw new ValueError(`Feed dict has no SymbolicTensor name: ${key}`);
+            }
+            return this.id2Mask[id];
+          }
+        }
+        /** Dispose all mask Tensors held by this object. */
+        disposeMasks() {
+          if (this.id2Mask != null) {
+            Object(dist["dispose"])(this.id2Mask);
+          }
+        }
+      }
+      // Cache for topologically sorted SymbolicTensors for given execution
+      // targets (i.e., fetches).
+      const cachedSorted = {};
+      // Cache for recipient count maps for given execution targets (i.e., fetches).
+      const cachedRecipientCounts = {};
+      /**
+       * Execute a SymbolicTensor by using concrete feed values.
+       *
+       * A `SymbolicTensor` object is a node in a computation graph of TF.js
+       * Layers. The object is backed by a source layer and input
+       * `SymbolicTensor`s to the source layer. This method evaluates
+       * the `call()` method of the source layer, using concrete values of the
+       * inputs obtained from either
+       * * `feedDict`, if the input key exists in `feedDict`, or else,
+       * * a recursive call to `execute()` itself.
+       *
+       * @param x: The `SymbolicTensor` to execute.
+       * @param feedDict: The feed values, as base condition of the recursion.
+       *   execution.
+       * @param kwargs: Optional keyword arguments.
+       * @param probe: A probe object (of interface `ExecutionProbe`) used for
+       *   testing memory footprint of `execute` calls.
+       * @returns Result of the execution.
+       * @throws ValueError: If any `SymbolicTensor`s from `InputLayer`s
+       *   encountered during the execution lacks a feed value in `feedDict`.
+       */
+      function execute(fetches, feedDict, kwargs, probe) {
+        const training = kwargs == null ? false : kwargs["training"];
+        const arrayFetches = Array.isArray(fetches);
+        const fetchArray = arrayFetches ? fetches : [fetches];
+        const outputNames = fetchArray.map((t) => t.name);
+        const finalOutputs = [];
+        const feedNames = feedDict.names();
+        for (const outputName of outputNames) {
+          if (feedNames.indexOf(outputName) !== -1) {
+            finalOutputs.push(feedDict.getValue(outputName));
+          } else {
+            finalOutputs.push(null);
+          }
+        }
+        if (probe != null) {
+          // For optional probing of memory footprint during execution.
+          probe.maxNumTensors = -Infinity;
+          probe.minNumTensors = Infinity;
+        }
+        // Check cache.
+        const fetchAndFeedKey = outputNames.join(",") + "|" + feedDict.names().join(",");
+        let sorted;
+        let recipientCounts;
+        if (cachedSorted[fetchAndFeedKey] == null) {
+          // Cache doesn't contain the desired combination of fetches. Compute
+          // topological sort for the combination for the first time.
+          const out = getTopologicalSortAndRecipientCounts(fetchArray, feedDict);
+          sorted = out.sorted;
+          recipientCounts = out.recipientCounts;
+          // Store results in cache for future use.
+          cachedSorted[fetchAndFeedKey] = sorted;
+          cachedRecipientCounts[fetchAndFeedKey] = recipientCounts;
+        }
+        sorted = cachedSorted[fetchAndFeedKey];
+        recipientCounts = {};
+        if (!training) {
+          Object.assign(recipientCounts, cachedRecipientCounts[fetchAndFeedKey]);
+        }
+        const internalFeedDict = new executor_FeedDict(feedDict);
+        // Start iterative execution on the topologically-sorted SymbolicTensors.
+        for (let i = 0; i < sorted.length; ++i) {
+          if (probe != null) {
+            // For optional probing of memory usage during execution.
+            const numTensors = Object(dist["memory"])().numTensors;
+            if (numTensors > probe.maxNumTensors) {
+              probe.maxNumTensors = numTensors;
+            }
+            if (numTensors < probe.minNumTensors) {
+              probe.minNumTensors = numTensors;
+            }
+          }
+          const symbolic = sorted[i];
+          const srcLayer = symbolic.sourceLayer;
+          if (srcLayer instanceof input_layer_InputLayer) {
+            continue;
+          }
+          const inputValues = [];
+          const inputMasks = [];
+          const tensorsToDispose = [];
+          let maskExists = false;
+          for (const input of symbolic.inputs) {
+            const value = internalFeedDict.getValue(input);
+            const mask = internalFeedDict.getMask(input);
+            inputValues.push(value);
+            inputMasks.push(mask);
+            if (mask != null) {
+              maskExists = true;
+            }
+            if (!training) {
+              recipientCounts[input.name]--;
+              if (
+                recipientCounts[input.name] === 0 &&
+                !feedDict.hasKey(input) &&
+                outputNames.indexOf(input.name) === -1 &&
+                !value.isDisposed &&
+                input.sourceLayer.stateful !== true
+              ) {
+                tensorsToDispose.push(value);
+              }
+            }
+          }
+          if (maskExists) {
+            kwargs = kwargs || {};
+            kwargs["mask"] = inputMasks[0];
+          }
+          const outputTensors = toList(srcLayer.apply(inputValues, kwargs));
+          let outputMask = null;
+          if (srcLayer.supportsMasking) {
+            outputMask = srcLayer.computeMask(inputValues, inputMasks);
+          }
+          const layerOutputs = getNodeOutputs(symbolic);
+          const outputSymbolicTensors = Array.isArray(layerOutputs) ? layerOutputs : [layerOutputs];
+          for (let i = 0; i < outputSymbolicTensors.length; ++i) {
+            if (!internalFeedDict.hasKey(outputSymbolicTensors[i])) {
+              internalFeedDict.add(
+                outputSymbolicTensors[i],
+                outputTensors[i],
+                Array.isArray(outputMask) ? outputMask[0] : outputMask
+              );
+            }
+            const index = outputNames.indexOf(outputSymbolicTensors[i].name);
+            if (index !== -1) {
+              finalOutputs[index] = outputTensors[i];
+            }
+          }
+          if (!training) {
+            // Clean up Tensors that are no longer needed.
+            Object(dist["dispose"])(tensorsToDispose);
+          }
+        }
+        // NOTE(cais): Unlike intermediate tensors, we don't discard mask
+        // tensors as we go, because these tensors are sometimes passed over a
+        // series of mutliple layers, i.e., not obeying the immediate input
+        // relations in the graph. If this becomes a memory-usage concern,
+        // we can improve this in the future.
+        internalFeedDict.disposeMasks();
+        return arrayFetches ? finalOutputs : finalOutputs[0];
+      }
+      /**
+       * Sort the `SymbolicTensor`s topologically, for an array of fetches.
+       *
+       * This function calls getTopologicalSortAndRecipientCountsForOneFetch and
+       * merges their results.
+       *
+       * @param fetch The array of fetches requested. Must be a non-empty array.
+       * @param feedDict The dictionary of fed values.
+       * @returns sorted: Topologically-sorted array of SymbolicTensors.
+       *   recipientCounts: Recipient counts for all SymbolicTensors in `sorted`.
+       */
+      function getTopologicalSortAndRecipientCounts(fetches, feedDict) {
+        dist["util"].assert(
+          fetches != null && fetches.length > 0,
+          () => `Expected at least one fetch, got none`
+        );
+        let finalSorted = [];
+        let finalRecipientMap = {};
+        if (fetches.length === 1) {
+          // Special-casing 1 fetch for efficiency.
+          const out = getTopologicalSortAndRecipientCountsForOneFetch(fetches[0], feedDict);
+          finalSorted = out.sorted;
+          finalRecipientMap = out.recipientMap;
+        } else {
+          const visited = new Set();
+          for (const fetch of fetches) {
+            const { sorted, recipientMap } = getTopologicalSortAndRecipientCountsForOneFetch(
+              fetch,
+              feedDict
+            );
+            // Merge sorted SymbolicTensor Arrays.
+            for (const symbolicTensor of sorted) {
+              if (!visited.has(symbolicTensor.name)) {
+                finalSorted.push(symbolicTensor);
+                visited.add(symbolicTensor.name);
+              }
+            }
+            // Merge recipient maps.
+            for (const name in recipientMap) {
+              if (finalRecipientMap[name] == null) {
+                finalRecipientMap[name] = new Set();
+              }
+              recipientMap[name].forEach((recipient) => finalRecipientMap[name].add(recipient));
+            }
+          }
+        }
+        return {
+          sorted: finalSorted,
+          recipientCounts: recipientMap2Counts(finalRecipientMap),
+        };
+      }
+      function recipientMap2Counts(recipientMap) {
+        const recipientCounts = {};
+        for (const name in recipientMap) {
+          recipientCounts[name] = recipientMap[name].size;
+        }
+        return recipientCounts;
+      }
+      /**
+       * Sort the `SymbolicTensor`s topologically, for a single fetch.
+       *
+       * This helper function processes the upstream SymbolicTensors of a single
+       * fetch.
+       *
+       * @param fetch The single fetch requested.
+       * @param feedDict The dictionary of fed values.
+       * @returns sorted: Topologically-sorted array of SymbolicTensors.
+       *   recipientMap: Recipient names for all SymbolicTensors in `sorted`.
+       */
+      function getTopologicalSortAndRecipientCountsForOneFetch(fetch, feedDict) {
+        const visited = new Set();
+        const sorted = [];
+        const recipientMap = {};
+        // Put keys of the feedDict into visited first, so they don't have to be
+        // walked. This is needed in case where there are feeds for intermediate
+        // SymbolicTensors of the graph.
+        for (const key of feedDict.names()) {
+          visited.add(key);
+        }
+        const stack = [];
+        const marks = [];
+        // Initial population of stack and marks.
+        stack.push(fetch);
+        while (stack.length > 0) {
+          const top = stack[stack.length - 1];
+          if (visited.has(top.name)) {
+            stack.pop();
+            continue;
+          }
+          const topIsMarked = marks[marks.length - 1] === stack.length - 1;
+          if (top.inputs.length === 0 || topIsMarked) {
+            // Input SymbolicTensor or all children have been visited.
+            stack.pop();
+            sorted.push(top);
+            visited.add(top.name);
+            if (topIsMarked) {
+              marks.pop();
+            }
+          } else {
+            // A non-input SymbolicTensor whose upstream SymbolicTensors haven't
+            // been visited yet. Push them onto the stack.
+            marks.push(stack.length - 1);
+            for (const input of top.inputs) {
+              // Increment the recipient count. Note that this needs to happen
+              // regardless of whether the SymbolicTensor has been visited before.
+              if (recipientMap[input.name] == null) {
+                recipientMap[input.name] = new Set();
+              }
+              recipientMap[input.name].add(top.name);
+              if (visited.has(input.name)) {
+                continue; // Avoid repeated visits to the same SymbolicTensor.
+              }
+              stack.push(input);
+            }
+          }
+        }
+        return { sorted, recipientMap };
+      }
+      /**
+       * Get the symbolic output tensors of the node to which a given fetch belongs.
+       * @param fetch The fetched symbolic tensor.
+       * @returns The Array of symbolic tensors output by the node to which `fetch`
+       *   belongs.
+       */
+      function getNodeOutputs(fetch) {
+        let layerOutputs;
+        if (fetch.sourceLayer.inboundNodes.length === 1) {
+          layerOutputs = fetch.sourceLayer.output;
+        } else {
+          let nodeIndex = null;
+          for (let i = 0; i < fetch.sourceLayer.inboundNodes.length; ++i) {
+            for (const outputTensor of fetch.sourceLayer.inboundNodes[i].outputTensors) {
+              if (outputTensor.id === fetch.id) {
+                nodeIndex = i;
+                break;
+              }
+            }
+          }
+          layerOutputs = fetch.sourceLayer.getOutputAt(nodeIndex);
+        }
+        return layerOutputs;
+      }
+      //# sourceMappingURL=executor.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/container.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original source: keras/engine/topology.py */
+
+      /**
+       * A Container is a directed acyclic graph of layers.
+       *
+       * It is the topological form of a "model". A LayersModel
+       * is simply a Container with added training routines.
+       *
+       */
+      class container_Container extends topology_Layer {
+        constructor(args) {
+          // No args passed to super's constructor.
+          super({});
+          this.containerNodes = new Set();
+          this.name = args.name;
+          if (this.name == null) {
+            const prefix = this.getClassName().toLowerCase();
+            this.name = getUid(prefix);
+          }
+          this.supportsMasking = false;
+          this.trainable_ = true;
+          // TODO(michaelterry): Initialize perInputLosses/Updates here.
+          // Container-specific properties.
+          if (Array.isArray(args.inputs)) {
+            this.inputs = args.inputs.slice();
+          } else {
+            this.inputs = [args.inputs];
+          }
+          if (Array.isArray(args.outputs)) {
+            this.outputs = args.outputs.slice();
+          } else {
+            this.outputs = [args.outputs];
+          }
+          // Check for redundancy in inputs.
+          if (unique(this.inputs).length !== this.inputs.length) {
+            throw new ValueError(
+              "The list of inputs passed to the model is " +
+                "redundant. All inputs should only appear once. Found: " +
+                `${this.inputs.map((x) => x.name)}`
+            );
+          }
+          // Check for redundancy in outputs.
+          if (unique(this.outputs).length !== this.outputs.length) {
+            console.warn(
+              "The list of outputs passed to the model is redundant. " +
+                "All outputs should only appear once. Found: " +
+                `${this.outputs.map((x) => x.name)}`
+            );
+          }
+          /*
+          List of initial layers (1 to 1 mapping with this.inputs, hence the same
+          layer might appear twice)
+        */
+          this.inputLayers = [];
+          this.inputLayersNodeIndices = [];
+          this.inputLayersTensorIndices = [];
+          /*
+          List of layers (1 to 1 mapping with this.outputs, hence the same layer
+          might appear twice)
+        */
+          this.outputLayers = [];
+          this.outputLayersNodeIndices = [];
+          this.outputLayersTensorIndices = [];
+          /*
+          All layers in order of horizontal graph traversal. Entries are unique.
+          Includes input and output layers.
+        */
+          this.layers = [];
+          /*
+          References to container layers that were constructed internally. We need
+          these to properly dispose of tensors from nested containers.
+        */
+          this.internalContainerRefs = [];
+          // TODO(michaelterry): Determine if caching still needed with eager
+          // backend.
+          /*
+          This is for performance optimization when calling the Container on new
+          inputs. Every time the Container is called on a set on input tensors,
+          we compute the output tensors, output masks and output shapes in one pass,
+          then cache them here. When one of these outputs is queried later,
+          we retrieve it from there instead of recomputing it.
+        */
+          // this.outputTensorCache = {};
+          // this.outputShapeCache = {};
+          // Build this.outputLayers:
+          for (const x of this.outputs) {
+            const layer = x.sourceLayer;
+            const nodeIndex = x.nodeIndex;
+            const tensorIndex = x.tensorIndex;
+            this.outputLayers.push(layer);
+            this.outputLayersNodeIndices.push(nodeIndex);
+            this.outputLayersTensorIndices.push(tensorIndex);
+          }
+          // TODO(michaelterry): Add output mask cache code.
+          // Build this.inputLayers:
+          for (const x of this.inputs) {
+            const layer = x.sourceLayer;
+            const nodeIndex = x.nodeIndex;
+            const tensorIndex = x.tensorIndex;
+            /*
+              It's supposed to be an input layer, so only one node
+              and one tensor output.
+            */
+            assert(nodeIndex === 0, "input layer has >1 nodes");
+            assert(tensorIndex === 0, "input layer has >1 tensors");
+            this.inputLayers.push(layer);
+            this.inputLayersNodeIndices.push(nodeIndex);
+            this.inputLayersTensorIndices.push(tensorIndex);
+          }
+          // Build this.inputNames and this.outputNames.
+          this.inputNames = [];
+          this.outputNames = [];
+          this.feedInputShapes = [];
+          this.feedInputNames = [];
+          this.feedOutputNames = [];
+          for (let i = 0; i < this.inputLayers.length; i++) {
+            const layer = this.inputLayers[i];
+            // Check that layer is an InputLayer.
+            if (!(layer instanceof input_layer_InputLayer)) {
+              throw new TypeError(
+                "Input layers to a LayersModel must be InputLayer objects. " +
+                  `Received inputs: ${args.inputs}. ` +
+                  `Input ${i} (0-based) originates ` +
+                  `from layer type ${layer.getClassName()}.`
+              );
+            }
+            this.inputNames.push(layer.name);
+            this.feedInputShapes.push(layer.batchInputShape);
+            this.feedInputNames.push(layer.name);
+          }
+          for (const layer of this.outputLayers) {
+            this.outputNames.push(layer.name);
+          }
+          this.internalInputShapes = this.inputs.map((x) => x.shape);
+          this.internalOutputShapes = this.outputs.map((x) => x.shape);
+          /*
+          Container_nodes: set of nodes included in the graph (not all nodes
+          included in the layers are relevant to the current graph).
+        */
+          // ids of all nodes relevant to the Container:
+          const nodesDepths = {};
+          // To recover nodes from their ID.
+          const nodeIDToNode = {};
+          const layersDepths = {};
+          // To layers from their ID.
+          const layerIDToLayer = {};
+          const layerIndices = {};
+          const nodesInDecreasingDepth = [];
+          /**
+           * Builds a map of the graph of layers.
+           *
+           * This recursively updates the map `layerIndices`,
+           * the list `nodesInDecreasingDepth` and the set `containerNodes`.
+           *
+           * @param tensor Some tensor in a graph.
+           * @param finishedNodes Set of nodes whose subgraphs have been traversed
+           *         completely. Useful to prevent duplicated work.
+           * @param nodesInProgress Set of nodes that are currently active on the
+           *         recursion stack. Useful to detect cycles.
+           * @param layer Layer from which `tensor` comes from. If not provided,
+           *   will be obtained from tensor.sourceLayer.
+           * @param nodeIndex Node index from which `tensor` comes from.
+           * @param tensorIndex TensorIndex from which `tensor` comes from.
+           *
+           * @exception RuntimeError if a cycle is detected.
+           */
+          const buildMapOfGraph = (
+            tensor,
+            finishedNodes,
+            nodesInProgress,
+            layer,
+            nodeIndex,
+            tensorIndex
+          ) => {
+            if (layer == null || nodeIndex == null || tensorIndex == null) {
+              layer = tensor.sourceLayer;
+              nodeIndex = tensor.nodeIndex;
+              tensorIndex = tensor.tensorIndex;
+            }
+            const node = layer.inboundNodes[nodeIndex];
+            // Prevent cycles.
+            if (nodesInProgress.indexOf(node) !== -1) {
+              throw new RuntimeError(
+                `The tensor ${tensor.name} at layer "${layer.name}" ` + "is part of a cycle."
+              );
+            }
+            // Don't repeat work for shared subgraphs
+            if (finishedNodes.indexOf(node) !== -1) {
+              return;
+            }
+            // Update containerNodes.
+            this.containerNodes.add(container_Container.nodeKey(layer, nodeIndex));
+            // Store the traversal order for layer sorting.
+            if (!(layer.id in layerIndices)) {
+              layerIndices[layer.id] = Object.keys(layerIndices).length;
+            }
+            if (nodesInProgress.indexOf(node) === -1) {
+              nodesInProgress.push(node);
+            }
+            // Propagate to all previous tensors connected to this node.
+            const numInboundLayers = node.inboundLayers.length;
+            for (let i = 0; i < numInboundLayers; i++) {
+              const x = node.inputTensors[i];
+              const layer = node.inboundLayers[i];
+              const nodeIndex = node.nodeIndices[i];
+              const tensorIndex = node.tensorIndices[i];
+              buildMapOfGraph(x, finishedNodes, nodesInProgress, layer, nodeIndex, tensorIndex);
+            }
+            finishedNodes.push(node);
+            while (nodesInProgress.indexOf(node) >= 0) {
+              nodesInProgress.splice(nodesInProgress.indexOf(node), 1);
+            }
+            nodesInDecreasingDepth.push(node);
+          };
+          const finishedNodes = [];
+          const nodesInProgress = [];
+          for (const x of this.outputs) {
+            buildMapOfGraph(x, finishedNodes, nodesInProgress);
+          }
+          const reversedNodesInDecreasingDepth = nodesInDecreasingDepth.slice().reverse();
+          for (const node of reversedNodesInDecreasingDepth) {
+            nodeIDToNode[node.id] = node;
+            // If the depth is not set, the node has no outbound nodes (depth 0).
+            if (!(node.id in nodesDepths)) {
+              nodesDepths[node.id] = 0;
+            }
+            let depth = nodesDepths[node.id];
+            // Update the depth of the corresponding layer
+            const previousDepth =
+              layersDepths[node.outboundLayer.id] == null ? 0 : layersDepths[node.outboundLayer.id];
+            /*
+              If we've seen this layer before at a higher depth, we should use that
+              depth instead of the node depth.  This is necessary for shared layers
+              that have inputs at different depth levels in the graph.
+            */
+            depth = Math.max(depth, previousDepth);
+            layersDepths[node.outboundLayer.id] = depth;
+            layerIDToLayer[node.outboundLayer.id] = node.outboundLayer;
+            nodesDepths[node.id] = depth;
+            // Update the depth of inbound nodes.
+            for (let i = 0; i < node.inboundLayers.length; i++) {
+              const inboundLayer = node.inboundLayers[i];
+              const nodeIndex = node.nodeIndices[i];
+              const inboundNode = inboundLayer.inboundNodes[nodeIndex];
+              const previousDepth =
+                nodesDepths[inboundNode.id] == null ? 0 : nodesDepths[inboundNode.id];
+              nodesDepths[inboundNode.id] = Math.max(depth + 1, previousDepth);
+              nodeIDToNode[inboundNode.id] = inboundNode;
+            }
+          }
+          // Build a dict {depth: list of nodes with this depth}
+          const nodesByDepth = {};
+          for (const nodeID in nodesDepths) {
+            const depth = nodesDepths[nodeID];
+            if (!(depth in nodesByDepth)) {
+              nodesByDepth[depth] = [];
+            }
+            nodesByDepth[depth].push(nodeIDToNode[nodeID]);
+          }
+          // Build a dict {depth: list of layers with this depth}
+          const layersByDepth = {};
+          for (const layerID in layersDepths) {
+            const depth = layersDepths[layerID];
+            if (!(depth in layersByDepth)) {
+              layersByDepth[depth] = [];
+            }
+            layersByDepth[depth].push(layerIDToLayer[layerID]);
+          }
+          // Get sorted list of layer depths.
+          let depthKeys = Object.keys(layersByDepth)
+            .map((x) => parseInt(x, 10))
+            .sort(reverseNumberCompare);
+          // Set this.layers and this.layersByDepth.
+          this.layers = [];
+          for (const depth of depthKeys) {
+            const layersForDepth = layersByDepth[depth];
+            // Container.layers needs to have a deterministic order:
+            // here we order them by traversal order.
+            layersForDepth.sort((a, b) => {
+              const aIndex = layerIndices[a.id];
+              const bIndex = layerIndices[b.id];
+              if (aIndex < bIndex) {
+                return -1;
+              }
+              if (aIndex > bIndex) {
+                return 1;
+              }
+              return 0;
+            });
+            for (const layer of layersForDepth) {
+              if (layer instanceof container_Container) {
+                this.internalContainerRefs.push(layer);
+              }
+              this.layers.push(layer);
+            }
+          }
+          this.layersByDepth = layersByDepth;
+          // Get sorted list of node depths;
+          depthKeys = Object.keys(nodesByDepth)
+            .map((x) => parseInt(x, 10))
+            .sort(reverseNumberCompare);
+          // Check that all tensors required are computable.
+          // computable_tensors: all tensors in the graph
+          // that can be computed from the inputs provided.
+          const computableTensors = this.inputs.slice();
+          // To provide a better error msg.
+          const layersWithCompleteInput = [];
+          for (const depth of depthKeys) {
+            for (const node of nodesByDepth[depth]) {
+              const layer = node.outboundLayer;
+              if (layer != null) {
+                for (const x of node.inputTensors) {
+                  if (computableTensors.indexOf(x) === -1) {
+                    throw new RuntimeError(
+                      `Graph disconnected: cannot obtain value for tensor ${x}` +
+                        ` at layer "${layer.name}". ` +
+                        "The following previous layers were accessed without " +
+                        `issue: ${layersWithCompleteInput}`
+                    );
+                  }
+                }
+                for (const x of node.outputTensors) {
+                  computableTensors.push(x);
+                }
+                layersWithCompleteInput.push(layer.name);
+              }
+            }
+          }
+          // Set this.containerNodes and this.nodesByDepth.
+          this.nodesByDepth = nodesByDepth;
+          // Ensure name unicity, which will be crucial for serialization
+          // (since serialized nodes refer to layers by their name).
+          const allNames = this.layers.map((x) => x.name);
+          for (const name of allNames) {
+            const numOccurrences = allNames.filter((x) => x === name).length;
+            if (numOccurrences !== 1) {
+              throw new RuntimeError(
+                `The name "${name}" is used ${numOccurrences} times ` +
+                  "in the model. All layer names should be unique. Layer names: " +
+                  JSON.stringify(allNames)
+              );
+            }
+          }
+          // Layer parameters.
+          // The new container starts with a single inbound node
+          // for its inputs, and no outbound nodes.
+          // Will be appended to by future calls to apply().
+          this.outboundNodes = [];
+          // Will be appended to below, and by future calls to apply().
+          this.inboundNodes = [];
+          // Create the node linking internal inputs to internal outputs.
+          // (This call has side effects.)
+          // tslint:disable-next-line:no-unused-expression
+          new Node({
+            outboundLayer: this,
+            inboundLayers: [],
+            nodeIndices: [],
+            tensorIndices: [],
+            inputTensors: this.inputs,
+            outputTensors: this.outputs,
+            inputMasks: this.inputs.map((x) => null),
+            outputMasks: this.outputs.map((x) => null),
+            inputShapes: this.inputs.map((x) => x.shape),
+            outputShapes: this.outputs.map((x) => x.shape),
+          });
+          this.built = true;
+          this._refCount = 1; // The ref count of a container always start at 1.
+        }
+        assertNotDisposed() {
+          if (this._refCount === 0) {
+            throw new Error(`Container '${this.name}' is already disposed.`);
+          }
+        }
+        /**
+         * Attempt to dispose a LayersModel's weights.
+         *
+         * This method decrease the reference count of the LayersModel object by 1.
+         *
+         * A LayersModel is reference-counted. Its reference count is incremented by 1
+         * when it is first constructed and when it is used as a Layer of another
+         * LayersModel.
+         *
+         * If the reference count of a LayersModel becomes 0, the `dispose` method of
+         * all its constituent `Layer`s will be called.
+         *
+         * Note: If the reference count is greater than 0 after the decrement, the
+         * `dispose` method of its constituent `Layer`s will *not* be called.
+         *
+         * After a LayersModel is disposed, it cannot be used in calls such as
+         * 'predict`, `evaluate` or `fit` anymore.
+         *
+         * @returns A DisposeResult Object with the following fields:
+         *   - refCountAfterDispose: The reference count of the LayersModel after this
+         *     `dispose()` call.
+         *   - numDisposedVariables: Number of `tf.Variable`s (i.e., weights) disposed
+         *     during this `dispose()` call.
+         * @throws {Error} If the layer is not built yet, or if the LayersModel has
+         *   already been disposed.
+         */
+        dispose() {
+          this.assertNotDisposed();
+          const result = { refCountAfterDispose: null, numDisposedVariables: 0 };
+          if (--this._refCount === 0) {
+            for (const layer of this.layers) {
+              result.numDisposedVariables += layer.dispose().numDisposedVariables;
+            }
+            // Call dispose on each internally created container layer again to ensure
+            // their refCounts hit zero and their tensors are subsequently deleted.
+            for (const container of this.internalContainerRefs) {
+              result.numDisposedVariables += container.dispose().numDisposedVariables;
+            }
+          }
+          result.refCountAfterDispose = this._refCount;
+          return result;
+        }
+        get trainable() {
+          return this.trainable_;
+        }
+        set trainable(trainable) {
+          this.layers.forEach((layer) => {
+            // tslint:disable-next-line:no-any
+            layer._trainableWeights.forEach((w) => (w.trainable = trainable));
+          });
+          this.trainable_ = trainable;
+        }
+        get trainableWeights() {
+          // Porting Note: This check below is to prevent errors where the
+          //   _trainableWeights inherited from the parent class (Layer) gets
+          //   inadvertently used.
+          if (this._trainableWeights.length > 0) {
+            throw new ValueError(
+              "Container instance unexpectedly contains _trainableWeights." +
+                "The trainable weights of a Container are a union of the " +
+                "trainable weights of its consituent Layers. Its own " +
+                "_trainableWeights must remain an empty Array."
+            );
+          }
+          if (!this.trainable) {
+            return [];
+          }
+          let weights = [];
+          for (const layer of this.layers) {
+            weights = weights.concat(layer.trainableWeights);
+          }
+          return weights;
+        }
+        get nonTrainableWeights() {
+          const weights = [];
+          for (const layer of this.layers) {
+            weights.push(...layer.nonTrainableWeights);
+          }
+          if (!this.trainable) {
+            const trainableWeights = [];
+            for (const layer of this.layers) {
+              trainableWeights.push(...layer.trainableWeights);
+            }
+            return trainableWeights.concat(weights);
+          }
+          return weights;
+        }
+        get weights() {
+          return this.trainableWeights.concat(this.nonTrainableWeights);
+        }
+        /**
+         * Loads all layer weights from a JSON object.
+         *
+         * Porting Note: HDF5 weight files cannot be directly loaded in JavaScript /
+         *   TypeScript. The utility script at `scripts/pykeras.py` offers means
+         *   to convert them into JSON strings compatible with this method.
+         * Porting Note: TensorFlow.js Layers supports only loading by name currently.
+         *
+         * @param weights A JSON mapping weight names to weight values as nested
+         *   arrays of numbers, or a `NamedTensorMap`, i.e., a JSON mapping weight
+         *   names to `tf.Tensor` objects.
+         * @param strict Require that the provided weights exactly match those
+         *   required by the container.  Default: `true`.  Passing `false` means that
+         *   extra weights and missing weights will be silently ignored.
+         */
+        loadWeights(weights, strict = true) {
+          const nameToWeight = {};
+          let totalWeightsCount = 0;
+          for (const layer of this.layers) {
+            for (const weight of layer.weights) {
+              if (nameToWeight[weight.originalName] != null) {
+                throw new ValueError(`Duplicate weight name: ${weight.originalName}`);
+              }
+              nameToWeight[weight.originalName] = weight;
+              totalWeightsCount++;
+            }
+          }
+          const weightValueTuples = [];
+          for (const name in weights) {
+            // TF 2.2.0 added cell name to the weight name in the format of
+            // layer_name/cell_name/weight_name, we need to remove
+            // the inner cell name.
+            let validatedName = name;
+            if (nameToWeight[name] == null) {
+              const tokens = name.split("/");
+              const shortenNameArray = tokens.slice(0, -2).concat([tokens[tokens.length - 1]]);
+              validatedName = shortenNameArray.join("/");
+            }
+            if (nameToWeight[validatedName] != null) {
+              weightValueTuples.push([nameToWeight[validatedName], weights[name]]);
+            } else if (strict) {
+              throw new ValueError(`Provided weight data has no target variable: ${name}`);
+            }
+            delete nameToWeight[validatedName];
+          }
+          if (strict) {
+            // Check that all weights are set.
+            const unsetNames = [];
+            for (const name in nameToWeight) {
+              unsetNames.push(name);
+            }
+            if (unsetNames.length > 0) {
+              throw new ValueError(
+                `${unsetNames.length} of ${totalWeightsCount} weights are not set: ` +
+                  `${unsetNames}`
+              );
+            }
+          }
+          batchSetValue(weightValueTuples);
+        }
+        /**
+         * Util shared between different serialization methods.
+         * @returns LayersModel config with Keras version information added.
+         */
+        updatedConfig() {
+          const theConfig = this.getConfig();
+          const modelConfig = {};
+          modelConfig["className"] = this.getClassName();
+          modelConfig["config"] = theConfig;
+          modelConfig["kerasVersion"] = `tfjs-layers ${version}`;
+          // TODO(nielsene): Replace something like K.backend() once
+          // possible.
+          modelConfig["backend"] = "TensorFlow.js";
+          return modelConfig;
+        }
+        /**
+         * Returns a JSON string containing the network configuration.
+         *
+         * To load a network from a JSON save file, use
+         * models.modelFromJSON(jsonString);
+         * @param extraJsonArgs Unused in tfjs-layers, maintained for PyKeras
+         * @param returnString Whether the return value should be stringified
+         *    (default: `true`).
+         * @returns a JSON string if `returnString` (default), or a JSON object if
+         *   `!returnString`.
+         */
+        // tslint:disable-next-line:no-any
+        toJSON(unused, returnString = true) {
+          const modelConfig = convertTsToPythonic(this.updatedConfig());
+          return returnString ? JSON.stringify(modelConfig) : modelConfig;
+        }
+        /**
+         * Call the model on new inputs.
+         *
+         * In this case `call` just reapplies all ops in the graph to the new inputs
+         * (e.g. build a new computational graph from the provided inputs).
+         *
+         * @param inputs A tensor or list of tensors.
+         * @param mask A mask or list of masks. A mask can be either a tensor or null
+         *   (no mask).
+         *
+         * @return A tensor if there is a single output, or a list of tensors if there
+         *   are more than one outputs.
+         */
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = toList(inputs);
+            const feedDict = new executor_FeedDict();
+            for (let i = 0; i < this.inputs.length; ++i) {
+              feedDict.add(this.inputs[i], inputs[i]);
+            }
+            return execute(this.outputs, feedDict, kwargs);
+          });
+        }
+        /**
+         * Computes an output mask tensor.
+         *
+         * @param inputs Tensor or list of tensors.
+         * @param mask Tensor or list of tensors.
+         *
+         * @return null or a tensor (or list of tensors, one per output tensor of the
+         * layer).
+         */
+        computeMask(inputs, mask) {
+          return Object(dist["tidy"])(() => {
+            inputs = toList(inputs);
+            let masks;
+            if (mask == null) {
+              masks = pyListRepeat(null, inputs.length);
+            } else {
+              masks = toList(mask);
+            }
+            // TODO(michaelterry): Add support for mask caching.
+            return this.runInternalGraph(inputs, masks)[1];
+          });
+        }
+        /**
+         * Computes the output shape of the layer.
+         *
+         * Assumes that the layer will be built to match that input shape provided.
+         *
+         * @param inputShape A shape (tuple of integers) or a list of shape tuples
+         *   (one per output tensor of the layer). Shape tuples can include null for
+         *   free dimensions, instead of an integer.
+         */
+        computeOutputShape(inputShape) {
+          const inputShapes = normalizeShapeList(inputShape);
+          if (inputShapes.length !== this.inputLayers.length) {
+            throw new ValueError(
+              `Invalid inputShape argument ${inputShape}: ` +
+                `model has ${this.inputLayers.length} tensor inputs.`
+            );
+          }
+          // TODO(michaelterry): Add caching
+          const layersToOutputShapes = {};
+          for (let i = 0; i < inputShapes.length; i++) {
+            const layer = this.inputLayers[i];
+            const inputShape = inputShapes[i];
+            // It's an input layer: computeOutputShape is identity,
+            // and there is only one node and one tensor output.
+            const shapeKey = layer.name + "_0_0";
+            layersToOutputShapes[shapeKey] = inputShape;
+          }
+          const depthKeys = Object.keys(this.nodesByDepth)
+            .map((x) => parseInt(x, 10))
+            .sort(reverseNumberCompare);
+          // Iterate over nodes, by depth level.
+          if (depthKeys.length > 1) {
+            for (const depth of depthKeys) {
+              const nodes = this.nodesByDepth[depth];
+              for (const node of nodes) {
+                // This is always a single layer, never a list.
+                const layer = node.outboundLayer;
+                if (this.inputLayers.map((x) => x.id).indexOf(layer.id) !== -1) {
+                  // We've already covered the input layers a few lines above.
+                  continue;
+                }
+                // Potentially redundant list, same size of node.inputTensors.
+                const inputShapes = [];
+                for (let j = 0; j < node.inboundLayers.length; j++) {
+                  const inboundLayer = node.inboundLayers[j];
+                  const nodeIndex = node.nodeIndices[j];
+                  const tensorIndex = node.tensorIndices[j];
+                  const shapeKey = `${inboundLayer.name}_${nodeIndex}_${tensorIndex}`;
+                  const inputShape = layersToOutputShapes[shapeKey];
+                  inputShapes.push(inputShape);
+                }
+                const outputShape = layer.computeOutputShape(singletonOrArray(inputShapes));
+                const outputShapes = normalizeShapeList(outputShape);
+                const nodeIndex = layer.inboundNodes.indexOf(node);
+                for (let j = 0; j < outputShapes.length; j++) {
+                  const shapeKey = `${layer.name}_${nodeIndex}_${j}`;
+                  layersToOutputShapes[shapeKey] = outputShapes[j];
+                }
+              }
+            }
+          }
+          // Read final output shapes from layersToOutputShapes.
+          const outputShapes = [];
+          const outputShapeKeys = [];
+          for (let i = 0; i < this.outputLayers.length; i++) {
+            const layer = this.outputLayers[i];
+            const nodeIndex = this.outputLayersNodeIndices[i];
+            const tensorIndex = this.outputLayersTensorIndices[i];
+            const shapeKey = `${layer.name}_${nodeIndex}_${tensorIndex}`;
+            outputShapeKeys.push(shapeKey);
+          }
+          for (let i = 0; i < outputShapeKeys.length; i++) {
+            const key = outputShapeKeys[i];
+            assert(key in layersToOutputShapes);
+            outputShapes.push(layersToOutputShapes[key]);
+          }
+          // TODO(michaelterry): Update cache
+          return singletonOrArray(outputShapes);
+        }
+        /**
+         * Computes output tensors for new inputs.
+         *
+         * Note:
+         *   - Expects `inputs` to be a list (potentially with 1 element).
+         *
+         * @param inputs List of tensors
+         * @param masks List of masks (tensors or null).
+         * @return Three lists: outputTensors, outputMasks, outputShapes
+         */
+        runInternalGraph(inputs, masks) {
+          if (masks == null) {
+            masks = pyListRepeat(null, inputs.length);
+          }
+          // Dictionary mapping reference tensors to tuples
+          // (computed tensor, compute mask)
+          // we assume a 1:1 mapping from tensor to mask
+          // TODO: raise exception when a `.computeMask()` call
+          // does not return a list the same size as `call`
+          const tensorMap = {};
+          for (let i = 0; i < this.inputs.length; ++i) {
+            const x = this.inputs[i];
+            const y = inputs[i];
+            const mask = masks[i];
+            tensorMap[x.id] = [y, mask];
+          }
+          const depthKeys = Object.keys(this.nodesByDepth)
+            .map((x) => parseInt(x, 10))
+            .sort(reverseNumberCompare);
+          for (const depth of depthKeys) {
+            const nodes = this.nodesByDepth[depth];
+            for (const node of nodes) {
+              // This is always a single layer, never a list.
+              const layer = node.outboundLayer;
+              const referenceInputTensors = node.inputTensors;
+              const referenceOutputTensors = node.outputTensors;
+              // If all previous input tensors are available in tensorMap,
+              // then call node.inboundLayer on them.
+              // List of tuples [input, mask]:
+              const computedData = new Array();
+              for (const x of referenceInputTensors) {
+                if (x.id in tensorMap) {
+                  computedData.push(tensorMap[x.id]);
+                }
+              }
+              if (computedData.length === referenceInputTensors.length) {
+                // TODO(michaelterry): Add K.name_scope here, if we need it.
+                let kwargs = {};
+                let computedTensors;
+                let computedMasks;
+                let outputTensors;
+                let outputMasks;
+                // call layer
+                if (node.callArgs != null) {
+                  kwargs = node.callArgs;
+                }
+                if (computedData.length === 1) {
+                  const [computedTensor, computedMask] = computedData[0];
+                  if (kwargs["mask"] == null) {
+                    kwargs["mask"] = computedMask;
+                  }
+                  outputTensors = toList(layer.call(computedTensor, kwargs));
+                  outputMasks = toList(layer.computeMask(computedTensor, computedMask));
+                  computedTensors = [computedTensor];
+                  computedMasks = [computedMask];
+                } else {
+                  computedTensors = computedData.map((x) => x[0]);
+                  computedMasks = computedData.map((x) => x[1]);
+                  if (kwargs["mask"] == null) {
+                    kwargs["mask"] = computedMasks;
+                  }
+                  outputTensors = toList(layer.call(computedTensors, kwargs));
+                  outputMasks = toList(layer.computeMask(computedTensors, computedMasks));
+                }
+                if (layer.activityRegularizer) {
+                  throw new NotImplementedError(
+                    "LayersModel invocation with concrete Tensor value(s) in the " +
+                      "presence of activity regularizer(s) is not supported yet."
+                  );
+                }
+                // TODO(michaelterry): Add model updates and losses
+                // Update tensor map.
+                for (let i = 0; i < referenceOutputTensors.length; ++i) {
+                  const x = referenceOutputTensors[i];
+                  const y = outputTensors[i];
+                  const mask = outputMasks[i];
+                  tensorMap[x.id] = [y, mask];
+                }
+              }
+            }
+          }
+          const outputTensors = [];
+          const outputMasks = [];
+          const outputShapes = [];
+          for (const x of this.outputs) {
+            assert(x.id in tensorMap, `Could not compute output ${x.name} : ${x.id}`);
+            const [tensor, mask] = tensorMap[x.id];
+            outputShapes.push(tensor.shape);
+            outputTensors.push(tensor);
+            outputMasks.push(mask);
+          }
+          // TODO(michaelterry): Add support for caches.
+          return [outputTensors, outputMasks, outputShapes];
+        }
+        /**
+         * Builds a map of internal node keys to node ordering.
+         * Used in serializaion a node orderings may change as unused nodes are
+         * dropped. Porting Note:  This helper method was pulled out of getConfig to
+         * improve readability.
+         * @param layers An array of Layers in the model.
+         * @returns Map of Node Keys to index order within the layer.
+         */
+        buildNodeConversionMap(layers) {
+          const nodeConversionMap = {};
+          let keptNodes;
+          for (const layer of this.layers) {
+            keptNodes = layer instanceof container_Container ? 1 : 0;
+            for (
+              let originalNodeIndex = 0;
+              originalNodeIndex < layer.inboundNodes.length;
+              originalNodeIndex++
+            ) {
+              const nodeKey = container_Container.nodeKey(layer, originalNodeIndex);
+              if (this.containerNodes.has(nodeKey)) {
+                // i.e. we mark it to be saved
+                nodeConversionMap[nodeKey] = keptNodes;
+                keptNodes += 1;
+              }
+            }
+          }
+          return nodeConversionMap;
+        }
+        /**
+         * Retrieves a layer based on either its name (unique) or index.
+         *
+         * Indices are based on order of horizontal graph traversal (bottom-up).
+         *
+         * If both `name` and `index` are specified, `index` takes precedence.
+         *
+         * @param name Name of layer.
+         * @param index Index of layer.
+         * @returns A Layer instance.
+         * @throws ValueError: In case of invalid layer name or index.
+         */
+        /**
+         * @doc {
+         *    heading: 'Layers',
+         *    subheading: 'Classes',
+         *    namespace: 'layers',
+         *    subclasses: ['LayersModel']
+         * }
+         */
+        getLayer(name, index) {
+          if (index != null) {
+            if (this.layers.length <= index) {
+              throw new ValueError(
+                `Was asked to retrieve layer at index ${index}, but model only ` +
+                  `has ${this.layers.length} layer(s).`
+              );
+            } else {
+              return this.layers[index];
+            }
+          } else {
+            if (name == null) {
+              throw new ValueError("Provide either a layer name or layer index");
+            }
+          }
+          for (const layer of this.layers) {
+            if (layer.name === name) {
+              return layer;
+            }
+          }
+          throw new ValueError(`No such layer: ${name}`);
+        }
+        /**
+         * Retrieves the Container's current loss values.
+         *
+         * Used for regularizers during training.
+         */
+        calculateLosses() {
+          // Porting Node: This is an augmentation to Container.loss in PyKeras.
+          //   In PyKeras, Container.loss returns symbolic tensors. Here a concrete
+          //   Tensor (specifically Scalar) values are returned. This is due to the
+          //   imperative backend.
+          return Object(dist["tidy"])(() => {
+            const losses = [];
+            for (const layer of this.layers) {
+              for (let nodeIndex = 0; nodeIndex < layer.inboundNodes.length; ++nodeIndex) {
+                const nodeKey = container_Container.nodeKey(layer, nodeIndex);
+                if (this.containerNodes.has(nodeKey)) {
+                  losses.push(...layer.calculateLosses());
+                }
+              }
+            }
+            // TODO(cais): Add any unconditional model-level losses?
+            return losses;
+          });
+        }
+        getConfig() {
+          const config = { name: this.name };
+          // Build a map from layer unique name (self._node_key)
+          // to the index of the nodes that are saved in the config.
+          // Only nodes in container_nodes are saved.
+          const nodeConversionMap = this.buildNodeConversionMap(this.layers);
+          // Serialize and save the layers in layerConfigs
+          const layerConfigs = [];
+          for (const layer of this.layers) {
+            const layerClassName = layer.getClassName();
+            const layerConfig = layer.getConfig();
+            const filteredInboundNodes = [];
+            for (
+              let originalNodeIndex = 0;
+              originalNodeIndex < layer.inboundNodes.length;
+              originalNodeIndex++
+            ) {
+              const node = layer.inboundNodes[originalNodeIndex];
+              const nodeKey = container_Container.nodeKey(layer, originalNodeIndex);
+              let kwargs = {};
+              if (this.containerNodes.has(nodeKey)) {
+                // The node is relevant to the model:
+                // add to filteredInboundNodes.
+                if (node.callArgs) {
+                  try {
+                    JSON.stringify(node.callArgs);
+                    kwargs = node.callArgs;
+                  } catch (err) {
+                    console.warn(
+                      `Layer ${layer.name} was passed ` +
+                        `non-serializable keyword arguments: ` +
+                        `${node.callArgs}. They will not be included ` +
+                        `in the serialized model (and thus will be ` +
+                        `missing at deserialization time).`
+                    );
+                    kwargs = {};
+                  }
+                }
+                if (node.inboundLayers.length > 0) {
+                  const nodeData = [];
+                  for (let i = 0; i < node.inboundLayers.length; i++) {
+                    const inboundLayer = node.inboundLayers[i];
+                    const nodeIndex = node.nodeIndices[i];
+                    const tensorIndex = node.tensorIndices[i];
+                    const nodeKey = container_Container.nodeKey(inboundLayer, nodeIndex);
+                    let newNodeIndex = nodeConversionMap[nodeKey];
+                    if (newNodeIndex == null) {
+                      newNodeIndex = 0;
+                    }
+                    nodeData.push([inboundLayer.name, newNodeIndex, tensorIndex, kwargs]);
+                  }
+                  filteredInboundNodes.push(nodeData);
+                }
+              }
+            }
+            const dict = {};
+            dict["name"] = layer.name;
+            dict["className"] = layerClassName;
+            dict["config"] = layerConfig;
+            dict["inboundNodes"] = filteredInboundNodes;
+            layerConfigs.push(dict);
+          }
+          config["layers"] = layerConfigs;
+          // Gather info about inputs and outputs
+          const modelInputs = [];
+          for (let i = 0; i < this.inputLayers.length; i++) {
+            const layer = this.inputLayers[i];
+            const nodeIndex = this.inputLayersNodeIndices[i];
+            const nodeKey = container_Container.nodeKey(layer, nodeIndex);
+            if (!this.containerNodes.has(nodeKey)) {
+              continue;
+            }
+            let newNodeIndex = nodeConversionMap[nodeKey];
+            if (newNodeIndex === null || newNodeIndex === undefined) {
+              newNodeIndex = 0;
+            }
+            const tensorIndex = this.inputLayersTensorIndices[i];
+            modelInputs.push([layer.name, newNodeIndex, tensorIndex]);
+          }
+          config["inputLayers"] = modelInputs;
+          const modelOutputs = [];
+          for (let i = 0; i < this.outputLayers.length; i++) {
+            const layer = this.outputLayers[i];
+            const nodeIndex = this.outputLayersNodeIndices[i];
+            const nodeKey = container_Container.nodeKey(layer, nodeIndex);
+            if (!this.containerNodes.has(nodeKey)) {
+              continue;
+            }
+            let newNodeIndex = nodeConversionMap[nodeKey];
+            if (newNodeIndex === null || newNodeIndex === undefined) {
+              newNodeIndex = 0;
+            }
+            const tensorIndex = this.outputLayersTensorIndices[i];
+            modelOutputs.push([layer.name, newNodeIndex, tensorIndex]);
+          }
+          config["outputLayers"] = modelOutputs;
+          return config;
+        }
+        /**
+         * Instantiates a LayersModel from its config (output of `get_config()`).
+         * @param cls the class to create
+         * @param config LayersModel config dictionary.
+         * @param customObjects An optional dictionary of custom objects.
+         * @param fastWeightInit Optional flag to use fast weight initialization
+         *   during deserialization. This is applicable to cases in which
+         *   the initialization will be immediately overwritten by loaded weight
+         *   values. Default: `false`.
+         * @returns A LayersModel instance.
+         * @throws ValueError: In case of improperly formatted config dict.
+         */
+        /** @nocollapse */
+        static fromConfig(cls, config, customObjects = {}, fastWeightInit = false) {
+          // Layer instances created during
+          // the graph reconstruction process
+          const createdLayers = {};
+          // Dictionary mapping layer instances to
+          // node data that specifies a layer call.
+          // It acts as a queue that maintains any unprocessed
+          // layer call until it becomes possible to process it
+          // (i.e. until the input tensors to the call all exist).
+          const unprocessedNodes = {};
+          function addUnprocessedNode(layer, nodeData) {
+            if (!(layer.name in unprocessedNodes)) {
+              unprocessedNodes[layer.name] = [nodeData];
+            } else {
+              unprocessedNodes[layer.name].push(nodeData);
+            }
+          }
+          function processNode(layer, nodeData) {
+            const inputTensors = [];
+            let kwargs;
+            for (const inputData of nodeData) {
+              const inboundLayerName = inputData[0];
+              const inboundNodeIndex = inputData[1];
+              const inboundTensorIndex = inputData[2];
+              kwargs = inputData[3] == null ? {} : inputData[3];
+              if (!(inboundLayerName in createdLayers)) {
+                addUnprocessedNode(layer, nodeData);
+                return;
+              }
+              const inboundLayer = createdLayers[inboundLayerName];
+              if (inboundLayer.inboundNodes.length <= inboundNodeIndex) {
+                addUnprocessedNode(layer, nodeData);
+                return;
+              }
+              const inboundNode = inboundLayer.inboundNodes[inboundNodeIndex];
+              inputTensors.push(inboundNode.outputTensors[inboundTensorIndex]);
+            }
+            // Call layer on its inputs, thus creating the node
+            // and building the layer if needed.
+            // Note: This has Eager vs Graph Implications.
+            if (inputTensors.length > 0) {
+              layer.apply(singletonOrArray(inputTensors), kwargs); // was ** kwargs
+            }
+          }
+          /**
+           * Deserialize a layer, then call it on appropriate inputs.
+           * @param layerData: layer config dict.
+           * @throws ValueError: In case of improperly formatted `layer_data`
+           * dict.
+           */
+          function processLayer(layerData) {
+            const layerName = layerData["name"];
+            // Instantiate layer.
+            const layer = deserialize(
+              layerData,
+              config["customObjects"] != null ? config["customObjects"] : {}
+            );
+            layer.setFastWeightInitDuringBuild(fastWeightInit);
+            createdLayers[layerName] = layer;
+            // Gather layer inputs.
+            const inboundNodesData = layerData["inboundNodes"];
+            inboundNodesData.forEach((nodeData) => {
+              if (!(nodeData instanceof Array)) {
+                throw new ValueError(
+                  `Corrupted configuration, expected array for nodeData: ${nodeData}`
+                );
+              }
+              // We don't process nodes (i.e. make layer calls)
+              // on the fly because the inbound node may not yet exist,
+              // in case of layer shared at different topological depths
+              // (e.g.a model such as A(B(A(B(x)))))
+              addUnprocessedNode(layer, nodeData);
+            });
+          }
+          // First, we create all layers and enqueue nodes to be processed.
+          const name = config["name"];
+          const layersFromConfig = config["layers"];
+          for (const layerData of layersFromConfig) {
+            processLayer(layerData);
+          }
+          // Then we process nodes in order of layer depth.
+          // Nodes that cannot yet be processed(if the inbound node
+          // does not yet exist) are re - enqueued, and the process
+          // is repeated until all nodes are processed.
+          while (!isObjectEmpty(unprocessedNodes)) {
+            for (const layerData of layersFromConfig) {
+              const layer = createdLayers[layerData["name"]];
+              if (layer.name in unprocessedNodes) {
+                const currentUnprocessedNodesForLayer = unprocessedNodes[layer.name];
+                delete unprocessedNodes[layer.name];
+                for (const nodeData of currentUnprocessedNodesForLayer) {
+                  processNode(layer, nodeData);
+                }
+              }
+            }
+          }
+          const inputTensors = [];
+          const outputTensors = [];
+          const inputLayersFromConfig = config["inputLayers"];
+          for (const layerData of inputLayersFromConfig) {
+            const layerName = layerData[0];
+            const nodeIndex = layerData[1];
+            const tensorIndex = layerData[2];
+            assert(layerName in createdLayers);
+            const layer = createdLayers[layerName];
+            const layerOutputTensors = layer.inboundNodes[nodeIndex].outputTensors;
+            inputTensors.push(layerOutputTensors[tensorIndex]);
+          }
+          const outputLayersFromConfig = config["outputLayers"];
+          for (const layerData of outputLayersFromConfig) {
+            const layerName = layerData[0];
+            const nodeIndex = layerData[1];
+            const tensorIndex = layerData[2];
+            assert(layerName in createdLayers);
+            const layer = createdLayers[layerName];
+            const layerOutputTensors = layer.inboundNodes[nodeIndex].outputTensors;
+            outputTensors.push(layerOutputTensors[tensorIndex]);
+          }
+          return new cls({ inputs: inputTensors, outputs: outputTensors, name });
+        }
+        /**
+         * Determine whether the container is stateful.
+         *
+         * Porting Note: this is the equivalent of the stateful @property of
+         *   the Container class in PyKeras.
+         */
+        get stateful() {
+          // Porting Note: This check is to prevent inadvertent setting of the
+          //   _stateful property of the Container instance.
+          if (this._stateful) {
+            throw new ValueError(
+              "Container instance unexpectedly has _stateful = true. The " +
+                "statefulness of a Container is determined by the Layers it " +
+                "contains. Its _stateful property must remain the default false."
+            );
+          }
+          for (const layer of this.layers) {
+            if (layer.stateful) {
+              return true;
+            }
+          }
+          return false;
+        }
+        /**
+         * Reset the state of all stateful constituent layers (if any).
+         *
+         * Examples of stateful layers include RNN layers whose `stateful` property
+         * is set as `true`.
+         */
+        resetStates() {
+          Object(dist["tidy"])(() => {
+            this.layers.forEach((layer) => {
+              // tslint:disable:no-any
+              if (layer.stateful) {
+                layer.resetStates();
+              }
+              // tslint:enable:no-any
+            });
+          });
+        }
+      }
+      //# sourceMappingURL=container.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/training_utils.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      function standardizeSampleOrClassWeights(xWeight, outputNames, weightType) {
+        const numOutputs = outputNames.length;
+        if (xWeight == null || (Array.isArray(xWeight) && xWeight.length === 0)) {
+          return outputNames.map((name) => null);
+        }
+        if (numOutputs === 1) {
+          if (Array.isArray(xWeight) && xWeight.length === 1) {
+            return xWeight;
+          } else if (typeof xWeight === "object" && outputNames[0] in xWeight) {
+            return [xWeight[outputNames[0]]];
+          } else {
+            return [xWeight];
+          }
+        }
+        if (Array.isArray(xWeight)) {
+          if (xWeight.length !== numOutputs) {
+            throw new Error(
+              `Provided ${weightType} is an array of ${xWeight.length} ` +
+                `element(s), but the model has ${numOutputs} outputs. ` +
+                `Make sure a set of weights is provided for each model output.`
+            );
+          }
+          return xWeight;
+        } else if (
+          typeof xWeight === "object" &&
+          Object.keys(xWeight).length > 0 &&
+          typeof xWeight[Object.keys(xWeight)[0]] === "object"
+        ) {
+          const output = [];
+          outputNames.forEach((outputName) => {
+            if (outputName in xWeight) {
+              output.push(xWeight[outputName]);
+            } else {
+              output.push(null);
+            }
+          });
+          return output;
+        } else {
+          throw new Error(
+            `The model has multiple (${numOutputs}) outputs, ` +
+              `so ${weightType} must be either an array with ` +
+              `${numOutputs} elements or an object with ${outputNames} keys. ` +
+              `Provided ${weightType} not understood: ${JSON.stringify(xWeight)}`
+          );
+        }
+      }
+      /**
+       * Standardize class weighting objects.
+       *
+       * This function takes a single class-weighting object, an array of them,
+       * or a map from output name to class-weighting object. It compares it to the
+       * output name(s) of the model, base on which it outputs an array of
+       * class-weighting objects of which the length matches the number of outputs.
+       *
+       * @param classWeight Input class-weighting object(s).
+       * @param outputNames All output name(s) of the model.
+       * @return An array of class-weighting objects. The length of the array matches
+       *   the model's number of outputs.
+       */
+      function standardizeClassWeights(classWeight, outputNames) {
+        return standardizeSampleOrClassWeights(classWeight, outputNames, "classWeight");
+      }
+      function standardizeSampleWeights(classWeight, outputNames) {
+        return standardizeSampleOrClassWeights(classWeight, outputNames, "sampleWeight");
+      }
+      /**
+       * Standardize by-sample and/or by-class weights for training.
+       *
+       * Note that this function operates on one model output at a time. For a model
+       * with multiple outputs, you must call this function multiple times.
+       *
+       * @param y The target tensor that the by-sample and/or by-class weight is for.
+       *     The values of y are assumed to encode the classes, either directly
+       *     as an integer index, or as one-hot encoding.
+       * @param sampleWeight By-sample weights.
+       * @param classWeight By-class weights: an object mapping class indices
+       *     (integers) to a weight (float) to apply to the model's loss for the
+       *     samples from this class during training. This can be useful to tell the
+       *     model to "pay more attention" to samples from an under-represented class.
+       * @param sampleWeightMode The mode for the sample weights.
+       * @return A Promise of weight tensor, of which the size of the first dimension
+       *     matches that of `y`.
+       */
+      async function standardizeWeights(y, sampleWeight, classWeight, sampleWeightMode) {
+        if (sampleWeight != null || sampleWeightMode != null) {
+          // TODO(cais): Once 'temporal' mode is implemented, document it in the doc
+          // string.
+          throw new Error("Support sampleWeight is not implemented yet");
+        }
+        if (classWeight != null) {
+          // Apply class weights per sample.
+          const yClasses = Object(dist["tidy"])(() => {
+            if (y.shape.length === 1) {
+              // Assume class indices.
+              return y.clone();
+            } else if (y.shape.length === 2) {
+              if (y.shape[1] > 1) {
+                // Assume one-hot encoding of classes.
+                const axis = 1;
+                return y.argMax(axis);
+              } else if (y.shape[1] === 1) {
+                // Class index.
+                return y.reshape([y.shape[0]]);
+              } else {
+                throw new Error(
+                  `Encountered unexpected last-dimension size (${y.shape[1]}) ` +
+                    `during handling of class weights. The size is expected to be ` +
+                    `>= 1.`
+                );
+              }
+            } else {
+              throw new Error(
+                `Unexpected rank of target (y) tensor (${y.rank}) during ` +
+                  `handling of class weights. The rank is expected to be 1 or 2.`
+              );
+            }
+          });
+          const yClassIndices = Array.from(await yClasses.data());
+          Object(dist["dispose"])(yClasses);
+          const classSampleWeight = [];
+          yClassIndices.forEach((classIndex) => {
+            if (classWeight[classIndex] == null) {
+              throw new Error(
+                `classWeight must contain all classes in the training data. ` +
+                  `The class ${classIndex} exists in the data but not in ` +
+                  `classWeight`
+              );
+            } else {
+              classSampleWeight.push(classWeight[classIndex]);
+            }
+          });
+          return Object(dist["tensor1d"])(classSampleWeight, "float32");
+        } else {
+          return null;
+        }
+      }
+      /**
+       * Apply per-sample weights on the loss values from a number of samples.
+       *
+       * @param losses Loss tensor of shape `[batchSize]`.
+       * @param sampleWeights Per-sample weight tensor of shape `[batchSize]`.
+       * @returns Tensor of the same shape as`losses`.
+       */
+      function computeWeightedLoss(losses, sampleWeights) {
+        return Object(dist["mul"])(losses, sampleWeights);
+      }
+      //# sourceMappingURL=training_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/training_dataset.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Interfaces and methods for training models using TensorFlow.js datasets.
+       */
+
+      // Default batch size used during tensor-based validation.
+      const DEFAULT_VALIDATION_BATCH_SIZE = 32;
+      /**
+       * Standardize the output of a dataset iterator for use by
+       * LayersModel.fitDataset().
+       *
+       * @param model: A `tf.LayersModel` object.
+       * @param iteratorOut The output of a dataset iterator. It is required to be
+       *   an object of the form `{xs: TensorOrArrayOrMap, ys:
+       * TensorOrArrayOrMap}`, where `TensorOrArrayOrMap` is a single `tf.Tensor`,
+       * a `tf.Tensor[]`, or a flat map from string names to `tf.Tensor`s.
+       * @returns A flat array of `tf.Tensor` objects: the input `tf.Tensor`s
+       *   followed by the target `tf.Tensor`s.  When `tf.Tensor`s are provided
+       *   as a map, the order in the resulting array is taken from the `inputNames`
+       *   and `outputNames` of the model.
+       */
+      function standardizeDataIteratorOutput(
+        // Type `model` as `any` here to avoid circular dependency w/
+        // training.ts.
+        // tslint:disable-next-line:no-any
+        model,
+        iteratorOut
+      ) {
+        let xs;
+        let ys;
+        const iteratorOutObj = iteratorOut;
+        xs = iteratorOutObj["xs"];
+        ys = iteratorOutObj["ys"];
+        dist["util"].assert(
+          xs != null && ys != null,
+          () =>
+            "A Dataset iterator for fitDataset() is expected to generate " +
+            "objects of the form `{xs: xVal, ys: yVal}`, where the two " +
+            "values may be `tf.Tensor`, an array of Tensors, or a map of " +
+            "string to Tensor.  The provided Dataset instead generates " +
+            `${iteratorOut}`
+        );
+        const flattenedXs = flattenTensorOrArrayOrMap("input", model.inputNames, xs);
+        const flattenedYs = flattenTensorOrArrayOrMap("output", model.outputNames, ys);
+        const batchSize = flattenedXs[0].shape[0];
+        dist["util"].assert(
+          flattenedXs.length === model.inputs.length,
+          () =>
+            `LayersModel has ${model.inputs.length} inputs, but the dataset ` +
+            `provides ${flattenedXs.length} inputs.  (Expected input keys: ` +
+            `${JSON.stringify(model.inputNames)})`
+        );
+        dist["util"].assert(
+          flattenedYs.length === model.outputs.length,
+          () =>
+            `LayersModel has ${model.outputs.length} outputs, but the dataset ` +
+            `provides ${flattenedYs.length} outputs.  (Expected output keys: ` +
+            `${JSON.stringify(model.outputNames)})`
+        );
+        for (let xIndex = 0; xIndex < flattenedXs.length; xIndex++) {
+          dist["util"].assert(
+            flattenedXs[xIndex].shape[0] === batchSize,
+            () =>
+              `Batch size mismatch: input ` +
+              `${model.inputNames[xIndex]} has ${flattenedXs[xIndex].shape[0]}; ` +
+              `expected  ${batchSize} based on input ${model.inputNames[0]}.`
+          );
+        }
+        for (let yIndex = 0; yIndex < flattenedYs.length; yIndex++) {
+          dist["util"].assert(
+            flattenedYs[yIndex].shape[0] === batchSize,
+            () =>
+              `Batch size mismatch: output ` +
+              `${model.outputNames[yIndex]} has ${flattenedYs[yIndex].shape[0]}; ` +
+              `expected  ${batchSize} based on input ${model.inputNames[0]}.`
+          );
+        }
+        return { xs: flattenedXs, ys: flattenedYs };
+      }
+      function flattenTensorOrArrayOrMap(inputOrOutput, names, values) {
+        if (values instanceof dist["Tensor"]) {
+          return [values];
+        } else if (Array.isArray(values)) {
+          dist["util"].assert(
+            values.length === names.length,
+            () =>
+              `Received an array of ${values.length} Tensors, but expected ${names.length} to match the ${inputOrOutput} keys ${names}.`
+          );
+          return values;
+        } else {
+          const result = [];
+          // Check that all the required keys are available.
+          for (const name of names) {
+            if (values[name] == null) {
+              throw new ValueError(
+                `The feature data generated by the dataset lacks the required ` +
+                  `${inputOrOutput} key '${name}'.`
+              );
+            }
+            result.push(values[name]);
+          }
+          return result;
+        }
+      }
+      function standardizeTensorValidationData(data) {
+        if (data.length === 3) {
+          throw new NotImplementedError("Validation with sample weights is not implemented yet.");
+        }
+        return { xs: data[0], ys: data[1] };
+      }
+      async function fitDataset(
+        // Type `model` as `any` here to avoid circular dependency w/
+        // training.ts.
+        // tslint:disable-next-line:no-any
+        model,
+        dataset,
+        args
+      ) {
+        const hasBatchesPerEpoch = args.batchesPerEpoch != null;
+        dist["util"].assert(
+          model.optimizer != null,
+          () =>
+            "You must compile a model before training/testing. Use " +
+            "LayersModel.compile(modelCompileConfig)."
+        );
+        dist["util"].assert(
+          args != null,
+          () =>
+            `For fitDataset(), the 2nd argument (config) is required, ` +
+            `but it is not provided in this call.`
+        );
+        dist["util"].assert(
+          args.epochs != null && args.epochs > 0 && Number.isInteger(args.epochs),
+          () =>
+            `For fitDataset(), config.epochs is expected to be a positive ` +
+            `integer, but got ${args.epochs}`
+        );
+        dist["util"].assert(
+          !hasBatchesPerEpoch ||
+            (args.batchesPerEpoch > 0 && Number.isInteger(args.batchesPerEpoch)),
+          () =>
+            `For fitDataset(), config.batchesPerEpoch is expected to be a ` +
+            `positive integer if specified, but got ${args.batchesPerEpoch}`
+        );
+        dist["util"].assert(
+          // tslint:disable-next-line:no-any
+          args["validationSplit"] == null,
+          () =>
+            "`validationSplit` is not supported by `fitDataset()`. " + "Use validationData instead."
+        );
+        if (model.isTraining) {
+          throw new Error("Cannot start training because another fit() call is ongoing.");
+        }
+        model.isTraining = true;
+        try {
+          const doValidation = args.validationData != null;
+          let valXs;
+          let valYs;
+          if (doValidation) {
+            if (isDatasetObject(args.validationData)) {
+              dist["util"].assert(
+                args.validationBatches == null ||
+                  (args.validationBatches > 0 && Number.isInteger(args.validationBatches)),
+                () =>
+                  `For fitDataset() with dataset-based validation, ` +
+                  `config.validationBatches is expected not to be provided, ` +
+                  `or to be a positive integer, ` +
+                  `but got ${args.validationBatches}`
+              );
+            } else {
+              const validationData = standardizeTensorValidationData(args.validationData);
+              valXs = validationData.xs;
+              valYs = validationData.ys;
+            }
+          }
+          const trainFunction = model.makeTrainFunction();
+          const outLabels = model.getDedupedMetricsNames();
+          let callbackMetrics;
+          if (doValidation) {
+            callbackMetrics = outLabels.slice().concat(outLabels.map((n) => "val_" + n));
+          } else {
+            callbackMetrics = outLabels.slice();
+          }
+          const callbacks = standardizeCallbacks(args.callbacks, args.yieldEvery);
+          const verbose = args.verbose == null ? 1 : args.verbose;
+          const { callbackList, history } = configureCallbacks(
+            callbacks,
+            verbose,
+            args.epochs,
+            null,
+            null,
+            getStepsPerEpoch(dataset, args),
+            null, // Batch size determined by the dataset itself.
+            doValidation,
+            callbackMetrics
+          );
+          callbackList.setModel(model);
+          model.history = history;
+          await callbackList.onTrainBegin();
+          model.stopTraining_ = false;
+          let epoch = args.initialEpoch == null ? 0 : args.initialEpoch;
+          let dataIterator = await dataset.iterator();
+          while (epoch < args.epochs) {
+            const epochLogs = {};
+            await callbackList.onEpochBegin(epoch);
+            let stepsDone = 0;
+            let batchIndex = 0;
+            if (!hasBatchesPerEpoch) {
+              dataIterator = await dataset.iterator();
+            }
+            while (hasBatchesPerEpoch ? stepsDone < args.batchesPerEpoch : true) {
+              const iteratorOut = await dataIterator.next();
+              // If `batchesPerEpoch` is specified, the dataset should not be
+              // exhausted until all epoches are done.
+              if (hasBatchesPerEpoch && iteratorOut.done) {
+                console.warn(
+                  "You provided `batchesPerEpoch` as " +
+                    `${args.batchesPerEpoch}, ` +
+                    "but your dataset iterator ran out of data after " +
+                    `${stepsDone} batches; ` +
+                    "interrupting training. Make sure that your " +
+                    "dataset can generate at least `batchesPerEpoch * epochs` " +
+                    "batches (in this case, " +
+                    `${args.batchesPerEpoch * args.epochs} batches). ` +
+                    "You may need to use the repeat() function when building " +
+                    "your dataset."
+                );
+                break;
+              }
+              if (iteratorOut.value != null) {
+                const { xs, ys } = standardizeDataIteratorOutput(model, iteratorOut.value);
+                const batchLogs = {};
+                batchLogs["batch"] = batchIndex;
+                batchLogs["size"] = xs[0].shape[0];
+                await callbackList.onBatchBegin(batchIndex, batchLogs);
+                const sampleWeights = [];
+                if (args.classWeight != null) {
+                  const standardClassWeights = standardizeClassWeights(
+                    args.classWeight,
+                    model.outputNames
+                  );
+                  for (let i = 0; i < standardClassWeights.length; ++i) {
+                    sampleWeights.push(
+                      await standardizeWeights(ys[i], null, standardClassWeights[i])
+                    );
+                  }
+                }
+                // Train on batch.
+                const ins = xs.concat(ys).concat(sampleWeights);
+                const outs = trainFunction(ins);
+                dist["dispose"](ins);
+                for (let i = 0; i < outLabels.length; ++i) {
+                  const label = outLabels[i];
+                  const out = outs[i];
+                  batchLogs[label] = out;
+                  dist["keep"](out);
+                }
+                await callbackList.onBatchEnd(batchIndex, batchLogs);
+                disposeTensorsInLogs(batchLogs);
+                batchIndex++;
+                stepsDone++;
+              }
+              if (hasBatchesPerEpoch ? stepsDone >= args.batchesPerEpoch : iteratorOut.done) {
+                // Epoch finished. Perform validation.
+                if (doValidation) {
+                  let valOuts;
+                  if (isDatasetObject(args.validationData)) {
+                    valOuts = toList(
+                      await model.evaluateDataset(args.validationData, {
+                        batches: args.validationBatches,
+                      })
+                    );
+                  } else {
+                    valOuts = toList(
+                      model.evaluate(valXs, valYs, {
+                        batchSize:
+                          args.validationBatchSize == null
+                            ? DEFAULT_VALIDATION_BATCH_SIZE
+                            : args.validationBatchSize,
+                        verbose: 0,
+                      })
+                    );
+                  }
+                  for (let i = 0; i < model.metricsNames.length; ++i) {
+                    epochLogs[`val_${model.metricsNames[i]}`] = valOuts[i];
+                  }
+                }
+                // Call `break` to exit one epoch lopp after validation is done. If
+                // config.batchesPerEpoch is specified, an epoch while loop will
+                // stop when `stepsDone >= config.batchesPerEpoch`. When
+                // config.batchesPerEpoch is not provided, the following `break` is
+                // required to exit the while lopp after dataset is exhausted.
+                break;
+              }
+              if (model.stopTraining_) {
+                break;
+              }
+            }
+            await callbackList.onEpochEnd(epoch, epochLogs);
+            epoch++;
+            if (model.stopTraining_) {
+              break;
+            }
+          }
+          await callbackList.onTrainEnd();
+          await model.history.syncData();
+          return model.history;
+        } finally {
+          model.isTraining = false;
+        }
+      }
+      /** Helper function that determines number of steps (batches) per epoch. */
+      function getStepsPerEpoch(dataset, args) {
+        // Attempt to determine # of batches in an epoch.
+        let stepsPerEpoch = null;
+        if (args.batchesPerEpoch != null) {
+          stepsPerEpoch = args.batchesPerEpoch;
+        } else if (Number.isFinite(dataset.size)) {
+          stepsPerEpoch = dataset.size;
+        }
+        return stepsPerEpoch;
+      }
+      // Check if provided object is a Dataset object by checking its .iterator
+      // element.
+      function isDatasetObject(dataset) {
+        return typeof dataset.iterator === "function";
+      }
+      // Check if provided object is a LazyIterator object by checking it's .next
+      // element.
+      function isLazyIteratorObject(iterator) {
+        return typeof iterator.next === "function";
+      }
+      async function evaluateDataset(
+        // Type `model` as `any` here to avoid circular dependency w/
+        // training.ts.
+        // tslint:disable-next-line:no-any
+        model,
+        dataset,
+        args
+      ) {
+        args = args || {};
+        const hasBatches = args.batches != null;
+        const f = model.testFunction;
+        let outs = [];
+        if (args.verbose > 0) {
+          throw new NotImplementedError("Verbose mode is not implemented yet.");
+        }
+        dist["util"].assert(
+          !hasBatches || (args.batches > 0 && Number.isInteger(args.batches)),
+          () =>
+            "Test loop expects `batches` to be a positive integer, but " +
+            `received ${JSON.stringify(args.batches)}`
+        );
+        const dataIterator = isLazyIteratorObject(dataset) ? dataset : await dataset.iterator();
+        // Keeps track of number of examples used in this evaluation.
+        let numExamples = 0;
+        let batch = 0;
+        while (hasBatches ? batch < args.batches : true) {
+          const iteratorOut = await dataIterator.next();
+          outs = dist["tidy"](() => {
+            if (iteratorOut.value) {
+              // TODO(cais): Once real dataset is available, use
+              //   `map(x => standardizeDataIteratorOutput(model, x).map(f)`.
+              const { xs, ys } = standardizeDataIteratorOutput(model, iteratorOut.value);
+              const xsAndYs = xs.concat(ys);
+              const batchOuts = dist["tidy"](() => f(xsAndYs));
+              dist["dispose"](xsAndYs);
+              if (batch === 0) {
+                for (let i = 0; i < batchOuts.length; ++i) {
+                  outs.push(Object(dist["scalar"])(0));
+                }
+              }
+              const batchSize = xsAndYs[0].shape[0];
+              for (let i = 0; i < batchOuts.length; ++i) {
+                const batchOut = batchOuts[i];
+                const oldScalar = outs[i];
+                outs[i] = dist["tidy"](() =>
+                  dist["add"](outs[i], dist["mul"](batchSize, batchOut))
+                );
+                if (batch > 0) {
+                  dist["dispose"](oldScalar);
+                }
+              }
+              dist["dispose"](batchOuts);
+              numExamples += batchSize;
+              ++batch;
+            }
+            return outs;
+          });
+          if (iteratorOut.done) {
+            if (hasBatches) {
+              console.warn(
+                "Your dataset iterator ran out of data during evaluateDataset(). " +
+                  "Interrupting evalution. Make sure that your " +
+                  "dataset can generate at least `batches` " +
+                  `batches (in this case, ${args.batches} batches). ` +
+                  "You may need to use the repeat() function when building " +
+                  "your dataset."
+              );
+            }
+            break;
+          }
+        }
+        for (let i = 0; i < outs.length; ++i) {
+          const oldScalar = outs[i];
+          outs[i] = dist["div"](outs[i], numExamples);
+          dist["dispose"](oldScalar);
+        }
+        return singletonOrArray(outs);
+      }
+      //# sourceMappingURL=training_dataset.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/training_tensors.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Interfaces and methods for training models using tf.Tensor objects.
+       */
+
+      function checkBatchSize(batchSize) {
+        dist["util"].assert(
+          batchSize > 0 && Number.isInteger(batchSize),
+          () => `batchSize is required to be a positive integer, but got ${batchSize}`
+        );
+      }
+      /**
+       * Slice a Tensor or an Array of Tensors, by start and stop indices.
+       *
+       * Porting Note: The `_slice_arrays` function in PyKeras is covered by this
+       *   function and `sliceArraysByIndices()` together.
+       *
+       * @param arrays: the input.
+       * @param start: the starting index (inclusive).
+       * @param stop: the stopping index (exclusive).
+       * @returns The result of the slicing. If `arrays` is an `Array` of
+       *   `tf.Tensor`s, the slicing will be applied to all elements of the `Array`
+       *   in the same way.
+       */
+      function sliceArrays(arrays, start, stop) {
+        if (arrays == null) {
+          return [null];
+        } else if (Array.isArray(arrays)) {
+          return arrays.map((array) => sliceAlongFirstAxis(array, start, stop - start));
+        } else {
+          // Tensor.
+          return sliceAlongFirstAxis(arrays, start, stop - start);
+        }
+      }
+      /**
+       * Slice a Tensor or an Array of Tensors, by random-order indices.
+       *
+       * Porting Note: The `_slice_arrays` function in PyKeras is covered by this
+       *   function and `sliceArrays()` together.
+       *
+       * @param arrays The input `tf.Tensor` or `Array` of `tf.Tensor`s to slice.
+       *   If an `Array` of `tf.Tensor`s, all `tf.Tensor`s will be sliced in the
+       *   same fashion.
+       * @param indices The indices to use for slicing along the first (batch)
+       *   dimension.
+       * @returns Result(s) of the slicing.
+       */
+      function sliceArraysByIndices(arrays, indices) {
+        return dist["tidy"](() => {
+          if (arrays == null) {
+            return null;
+          } else if (Array.isArray(arrays)) {
+            return arrays.map((array) => sliceArraysByIndices(array, indices));
+          } else {
+            // TODO(cais): indices should be a pre-constructed Tensor1D to avoid
+            //   tensor1d() calls.
+            return gather(arrays, indices.dtype === "int32" ? indices : indices.toInt());
+          }
+        });
+      }
+      /**
+       * Returns a list of batch indices (tuples of indices).
+       * @param size: Integer, total size of the data to slice into batches.
+       * @param batchSize: Integer, batch size.
+       * @returns An Array of [batchStart, batchEnd] tuples. batchStart is
+       *   inclusive; batchEnd is exclusive. I.e., each batch consists of indices x
+       *   that satisfy batchStart <= x < batchEnd.
+       */
+      function makeBatches(size, batchSize) {
+        const output = [];
+        let batchStart = 0;
+        let batchEnd = null;
+        while (batchStart < size) {
+          batchEnd = batchStart + batchSize;
+          if (batchEnd >= size) {
+            batchEnd = size;
+          }
+          output.push([batchStart, batchEnd]);
+          batchStart = batchEnd;
+        }
+        return output;
+      }
+      /**
+       * Abstract fit function for `f(ins)`.
+       * @param f A Function returning a list of tensors. For training, this
+       *   function is expected to perform the updates to the variables.
+       * @param ins List of tensors to be fed to `f`.
+       * @param outLabels List of strings, display names of the outputs of `f`.
+       * @param batchSize Integer batch size or `== null` if unknown. Default : 32.
+       * @param epochs Number of times to iterate over the data. Default : 1.
+       * @param verbose Verbosity mode: 0, 1, or 2. Default: 1.
+       * @param callbacks List of callbacks to be called during training.
+       * @param valF Function to call for validation.
+       * @param valIns List of tensors to be fed to `valF`.
+       * @param shuffle Whether to shuffle the data at the beginning of every
+       * epoch. Default : true.
+       * @param callbackMetrics List of strings, the display names of the metrics
+       *   passed to the callbacks. They should be the concatenation of the
+       *   display names of the outputs of `f` and the list of display names
+       *   of the outputs of `valF`.
+       * @param initialEpoch Epoch at which to start training (useful for
+       *   resuming a previous training run). Default : 0.
+       * @param stepsPerEpoch Total number of steps (batches on samples) before
+       *   declaring one epoch finished and starting the next epoch. Ignored with
+       *   the default value of `undefined` or `null`.
+       * @param validationSteps Number of steps to run validation for (only if
+       *   doing validation from data tensors). Not applicable for tfjs-layers.
+       * @returns A `History` object.
+       */
+      async function fitLoop(
+        // Type `model` as `any` here to avoid circular dependency w/ training.ts.
+        // tslint:disable-next-line:no-any
+        model,
+        f,
+        ins,
+        outLabels,
+        batchSize,
+        epochs,
+        verbose,
+        callbacks,
+        valF,
+        valIns,
+        shuffle,
+        callbackMetrics,
+        initialEpoch,
+        stepsPerEpoch,
+        validationSteps
+      ) {
+        if (batchSize == null) {
+          batchSize = 32;
+        }
+        if (epochs == null) {
+          epochs = 1;
+        }
+        if (shuffle == null) {
+          shuffle = true;
+        }
+        if (initialEpoch == null) {
+          initialEpoch = 0;
+        }
+        // TODO(cais): Change const to let below when implementing validation.
+        let doValidation = false;
+        if (valF != null && valIns != null) {
+          doValidation = true;
+          // TODO(cais): verbose message.
+        }
+        if (validationSteps != null) {
+          doValidation = true;
+          if (stepsPerEpoch == null) {
+            throw new ValueError(
+              "Can only use `validationSteps` when doing step-wise training, " +
+                "i.e., `stepsPerEpoch` must be set."
+            );
+          }
+        }
+        const numTrainSamples = model.checkNumSamples(
+          ins,
+          batchSize,
+          stepsPerEpoch,
+          "steps_per_epoch"
+        );
+        let indexArray;
+        if (numTrainSamples != null) {
+          indexArray = range(0, numTrainSamples);
+        }
+        if (verbose == null) {
+          verbose = 1;
+        }
+        const { callbackList, history } = configureCallbacks(
+          callbacks,
+          verbose,
+          epochs,
+          initialEpoch,
+          numTrainSamples,
+          stepsPerEpoch,
+          batchSize,
+          doValidation,
+          callbackMetrics
+        );
+        callbackList.setModel(model);
+        model.history = history;
+        await callbackList.onTrainBegin();
+        model.stopTraining_ = false;
+        // TODO(cais): Take care of callbacks.validation_data as in PyKeras.
+        // TODO(cais): Pre-convert feeds for performance as in PyKeras.
+        for (let epoch = initialEpoch; epoch < epochs; ++epoch) {
+          await callbackList.onEpochBegin(epoch);
+          const epochLogs = {};
+          if (stepsPerEpoch != null) {
+            throw new NotImplementedError("stepsPerEpoch mode is not implemented yet.");
+          } else {
+            if (shuffle === "batch") {
+              throw new NotImplementedError("batch shuffling is not implemneted yet");
+            } else if (shuffle) {
+              dist["util"].shuffle(indexArray);
+            }
+            // Convert the potentially shuffled indices to Tensor1D, to avoid the
+            // cost of repeated creation of Array1Ds later on.
+            const epochIndexArray1D = Object(dist["tensor1d"])(indexArray);
+            const batches = makeBatches(numTrainSamples, batchSize);
+            for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {
+              const batchLogs = {};
+              await callbackList.onBatchBegin(batchIndex, batchLogs);
+              dist["tidy"](() => {
+                const batchStart = batches[batchIndex][0];
+                const batchEnd = batches[batchIndex][1];
+                const batchIds = sliceAlongFirstAxis(
+                  epochIndexArray1D,
+                  batchStart,
+                  batchEnd - batchStart
+                );
+                batchLogs["batch"] = batchIndex;
+                batchLogs["size"] = batchEnd - batchStart;
+                // TODO(cais): In ins, train flag can be a number, instead of an
+                //   Tensor? Do we need to handle this in tfjs-layers?
+                const insBatch = sliceArraysByIndices(ins, batchIds);
+                const outs = f(insBatch);
+                for (let i = 0; i < outLabels.length; ++i) {
+                  const label = outLabels[i];
+                  const out = outs[i];
+                  batchLogs[label] = out;
+                  dist["keep"](out);
+                  // TODO(cais): Use scope() to avoid ownership.
+                }
+                if (batchIndex === batches.length - 1) {
+                  // Last batch.
+                  if (doValidation) {
+                    const valOuts = model.testLoop(valF, valIns, batchSize);
+                    // Porting Notes: In tfjs-layers, valOuts is always an Array.
+                    for (let i = 0; i < outLabels.length; ++i) {
+                      const label = outLabels[i];
+                      const out = valOuts[i];
+                      dist["keep"](out);
+                      // TODO(cais): Use scope() to avoid ownership.
+                      epochLogs["val_" + label] = out;
+                    }
+                  }
+                }
+              });
+              await callbackList.onBatchEnd(batchIndex, batchLogs);
+              disposeTensorsInLogs(batchLogs);
+              if (model.stopTraining_) {
+                break;
+              }
+              // TODO(cais): return outs as list of Tensor.
+            }
+            epochIndexArray1D.dispose();
+          }
+          // TODO(cais): Run validation at the end of the epoch.
+          await callbackList.onEpochEnd(epoch, epochLogs);
+          if (model.stopTraining_) {
+            break;
+          }
+        }
+        await callbackList.onTrainEnd();
+        await model.history.syncData();
+        return model.history;
+      }
+      async function fitTensors(
+        // Type `model` as `any` here to avoid circular dependency w/ training.ts.
+        // tslint:disable-next-line:no-any
+        model,
+        x,
+        y,
+        args = {}
+      ) {
+        if (model.isTraining) {
+          throw new Error("Cannot start training because another fit() call is ongoing.");
+        }
+        model.isTraining = true;
+        let inputs;
+        let targets;
+        let inputValX;
+        let inputValY;
+        let valX;
+        let valY;
+        let sampleWeights;
+        try {
+          const batchSize = args.batchSize == null ? 32 : args.batchSize;
+          checkBatchSize(batchSize);
+          // Validate user data.
+          // TODO(cais): Support sampleWeight.
+          const checkBatchAxis = false;
+          const standardizedOuts = await model.standardizeUserData(
+            x,
+            y,
+            args.sampleWeight,
+            args.classWeight,
+            checkBatchAxis,
+            batchSize
+          );
+          inputs = standardizedOuts[0];
+          targets = standardizedOuts[1];
+          sampleWeights = standardizedOuts[2];
+          // Prepare validation data.
+          let doValidation = false;
+          let valIns;
+          if (args.validationData != null && args.validationData.length > 0) {
+            doValidation = true;
+            if (args.validationData.length === 2) {
+              // config.validationData consists of valX and valY.
+              inputValX = args.validationData[0];
+              inputValY = args.validationData[1];
+            } else if (args.validationData.length === 3) {
+              throw new NotImplementedError(
+                "validationData including sample weights is not supported yet."
+              );
+            } else {
+              throw new ValueError(
+                `When passing validation data, it must contain 2 (valX, valY) ` +
+                  `or 3 (valX, valY, valSampleWeight) items; ` +
+                  `${args.validationData} is invalid.`
+              );
+            }
+            const checkBatchAxis = true;
+            const valStandardized = await model.standardizeUserData(
+              inputValX,
+              inputValY,
+              null,
+              /** Unused sample weights. */ null,
+              /** Unused class weights. */ checkBatchAxis,
+              batchSize
+            );
+            valX = valStandardized[0];
+            valY = valStandardized[1];
+            valIns = valX.concat(valY);
+            // TODO(cais): Add useLearningPhase data properly.
+          } else if (
+            args.validationSplit != null &&
+            args.validationSplit > 0 &&
+            args.validationSplit < 1
+          ) {
+            doValidation = true;
+            // Porting Note: In tfjs-layers, inputs[0] is always a Tensor.
+            const splitAt = Math.floor(inputs[0].shape[0] * (1 - args.validationSplit));
+            const originalBatchSize = inputs[0].shape[0];
+            valX = sliceArrays(inputs, splitAt, originalBatchSize);
+            inputs = sliceArrays(inputs, 0, splitAt);
+            valY = sliceArrays(targets, splitAt, originalBatchSize);
+            targets = sliceArrays(targets, 0, splitAt);
+            // TODO(cais): Once sampleWeights becomes available, slice it to get
+            //   valSampleWeights.
+            valIns = valX.concat(valY);
+            // TODO(cais): Add useLearningPhase data properly.
+          } else if (args.validationSteps != null) {
+            doValidation = true;
+            // TODO(cais): Add useLearningPhase.
+          }
+          const ins = inputs.concat(targets).concat(sampleWeights);
+          model.checkTrainableWeightsConsistency();
+          // TODO(cais): Handle use_learning_phase and learning_phase?
+          // Porting Note: Here we see a key deviation of tfjs-layers from
+          // Keras.
+          //  Due to the imperative nature of tfjs-layers' backend (tfjs-core),
+          //  we do not construct symbolic computation graphs to embody the
+          //  training process. Instead, we define a function that performs the
+          //  training action. In PyKeras, the data (inputs and targets) are fed
+          //  through graph placeholders. In tfjs-layers, the data are fed as
+          //  function arguments. Since the function are defined below in the
+          //  scope, we don't have equivalents of PyKeras's
+          //  `_make_train_funciton`.
+          const trainFunction = model.makeTrainFunction();
+          const outLabels = model.getDedupedMetricsNames();
+          let valFunction;
+          let callbackMetrics;
+          if (doValidation) {
+            model.makeTestFunction();
+            valFunction = model.testFunction;
+            callbackMetrics = outLabels.slice().concat(outLabels.map((n) => "val_" + n));
+          } else {
+            valFunction = null;
+            valIns = [];
+            callbackMetrics = outLabels.slice();
+          }
+          const callbacks = standardizeCallbacks(args.callbacks, args.yieldEvery);
+          const out = await fitLoop(
+            model,
+            trainFunction,
+            ins,
+            outLabels,
+            batchSize,
+            args.epochs,
+            args.verbose,
+            callbacks,
+            valFunction,
+            valIns,
+            args.shuffle,
+            callbackMetrics,
+            args.initialEpoch,
+            null,
+            null
+          );
+          return out;
+        } finally {
+          model.isTraining = false;
+          // Memory clean up.
+          disposeNewTensors(inputs, x);
+          disposeNewTensors(targets, y);
+          disposeNewTensors(valX, inputValX);
+          disposeNewTensors(valY, inputValY);
+          if (sampleWeights != null) {
+            dist["dispose"](sampleWeights);
+          }
+        }
+        // TODO(cais): Add value to outLabels.
+      }
+      /**
+       * Ensure tensors all have a rank of at least 2.
+       *
+       * If a tensor has a rank of 1, it is dimension-expanded to rank 2.
+       * If any tensor has a rank of 0 (i.e., is a scalar), an error will be thrown.
+       */
+      function ensureTensorsRank2OrHigher(tensors) {
+        const outs = [];
+        if (tensors instanceof dist["Tensor"]) {
+          tensors = [tensors];
+        }
+        // Make Tensors at least 2D.
+        for (let i = 0; i < tensors.length; ++i) {
+          const tensor = tensors[i];
+          if (tensor.rank === 1) {
+            outs.push(expandDims(tensor, 1));
+          } else if (tensor.rank === 0) {
+            throw new Error(
+              "Expected tensor to be at least 1D, but received a 0D tensor " + "(scalar)."
+            );
+          } else {
+            outs.push(tensor);
+          }
+        }
+        return outs;
+      }
+      /**
+       * Compare a set of tensors with a reference (old) set, discard the ones
+       * in the new set that are not present in the reference set.
+       *
+       * This method is used for memory clenaup during calls such as
+       * LayersModel.fit().
+       *
+       * @param tensors New set which may contain Tensors not present in
+       *   `refTensors`.
+       * @param refTensors Reference Tensor set.
+       */
+      // TODO(cais, kangyizhang): Deduplicate with tfjs-data.
+      function disposeNewTensors(tensors, refTensors) {
+        if (tensors == null) {
+          return;
+        }
+        const oldTensorIds = [];
+        if (refTensors instanceof dist["Tensor"]) {
+          oldTensorIds.push(refTensors.id);
+        } else if (Array.isArray(refTensors)) {
+          refTensors.forEach((t) => oldTensorIds.push(t.id));
+        } else if (refTensors != null) {
+          // `oldTensors` is a map from string name to Tensor.
+          for (const name in refTensors) {
+            const oldTensor = refTensors[name];
+            oldTensorIds.push(oldTensor.id);
+          }
+        }
+        const tensorsToDispose = [];
+        if (tensors instanceof dist["Tensor"]) {
+          if (oldTensorIds.indexOf(tensors.id) === -1) {
+            tensorsToDispose.push(tensors);
+          }
+        } else if (Array.isArray(tensors)) {
+          tensors.forEach((t) => {
+            if (oldTensorIds.indexOf(t.id) === -1) {
+              tensorsToDispose.push(t);
+            }
+          });
+        } else if (tensors != null) {
+          // `oldTensors` is a map from string name to Tensor.
+          for (const name in tensors) {
+            const tensor = tensors[name];
+            if (oldTensorIds.indexOf(tensor.id) === -1) {
+              tensorsToDispose.push(tensor);
+            }
+          }
+        }
+        tensorsToDispose.forEach((t) => {
+          if (!t.isDisposed) {
+            t.dispose();
+          }
+        });
+      }
+      //# sourceMappingURL=training_tensors.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/engine/training.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original Source: engine/training.py */
+
+      /**
+       * Helper function for polymorphic input data: 1. singleton Tensor.
+       */
+      function isDataTensor(x) {
+        return x instanceof dist["Tensor"];
+      }
+      /**
+       * Helper function for polymorphic input data: 2. Array of Tensor.
+       */
+      function isDataArray(x) {
+        return Array.isArray(x);
+      }
+      /**
+       * Helper function for polymorphic input data: 3. "dict" of Tensor.
+       */
+      function isDataDict(x) {
+        return !isDataTensor(x) && !isDataArray(x);
+      }
+      /**
+       * Normalizes inputs and targets provided by users.
+       * @param data User-provided input data (polymorphic).
+       * @param names An Array of expected Tensor names.
+       * @param shapes Optional Array of expected Tensor shapes.
+       * @param checkBatchAxis Whether to check that the batch axis of the arrays
+       *   match  the expected value found in `shapes`.
+       * @param exceptionPrefix String prefix used for exception formatting.
+       * @returns List of standardized input Tensors (one Tensor per model input).
+       * @throws ValueError: in case of improperly formatted user data.
+       */
+      function standardizeInputData(
+        data,
+        names,
+        shapes,
+        checkBatchAxis = true,
+        exceptionPrefix = ""
+      ) {
+        if (names == null || names.length === 0) {
+          // Check for the case where the model expected no data, but some data got
+          // sent.
+          if (data != null) {
+            let gotUnexpectedData = false;
+            if (isDataArray(data) && data.length > 0) {
+              gotUnexpectedData = true;
+            } else if (isDataDict(data)) {
+              for (const key in data) {
+                if (data.hasOwnProperty(key)) {
+                  gotUnexpectedData = true;
+                  break;
+                }
+              }
+            } else {
+              // `data` is a singleton Tensor in this case.
+              gotUnexpectedData = true;
+            }
+            if (gotUnexpectedData) {
+              throw new ValueError(
+                `Error when checking model ${exceptionPrefix} expected no data, ` +
+                  `but got ${data}`
+              );
+            }
+          }
+          return [];
+        }
+        if (data == null) {
+          return names.map((name) => null);
+        }
+        let arrays;
+        if (isDataDict(data)) {
+          data = data;
+          arrays = [];
+          for (const name of names) {
+            if (data[name] == null) {
+              throw new ValueError(
+                `No data provided for "${name}". Need data for each key in: ` + `${names}`
+              );
+            }
+            arrays.push(data[name]);
+          }
+        } else if (isDataArray(data)) {
+          data = data;
+          if (data.length !== names.length) {
+            throw new ValueError(
+              `Error when checking model ${exceptionPrefix}: the Array of ` +
+                `Tensors that you are passing to your model is not the size the ` +
+                `model expected. Expected to see ${names.length} Tensor(s), but ` +
+                `instead got the following list of Tensor(s): ${data}`
+            );
+          }
+          arrays = data;
+        } else {
+          data = data;
+          if (names.length > 1) {
+            throw new ValueError(
+              `The model ${exceptionPrefix} expects ${names.length} Tensor(s), ` +
+                `but only received one Tensor. Found: Tensor with shape ${data.shape}`
+            );
+          }
+          arrays = [data];
+        }
+        arrays = ensureTensorsRank2OrHigher(arrays);
+        // Check shape compatibility.
+        if (shapes != null) {
+          for (let i = 0; i < names.length; ++i) {
+            if (shapes[i] == null) {
+              continue;
+            }
+            const array = arrays[i];
+            if (array.shape.length !== shapes[i].length) {
+              throw new ValueError(
+                `Error when checking ${exceptionPrefix}: expected ${names[i]} ` +
+                  `to have ${shapes[i].length} dimension(s). but got array with ` +
+                  `shape ${array.shape}`
+              );
+            }
+            for (let j = 0; j < shapes[i].length; ++j) {
+              if (j === 0 && !checkBatchAxis) {
+                // Skip the first (batch) axis.
+                continue;
+              }
+              const dim = array.shape[j];
+              const refDim = shapes[i][j];
+              if (refDim != null && refDim >= 0 && dim !== refDim) {
+                throw new ValueError(
+                  `Error when checking ${exceptionPrefix}: expected ${names[i]} ` +
+                    `to have shape [${shapes[i]}], but got array with shape ` +
+                    `[${array.shape}].`
+                );
+              }
+            }
+          }
+        }
+        return arrays;
+      }
+      /**
+       * User input validation for Tensors.
+       * @param inputs `Array` of `tf.Tensor`s for inputs.
+       * @param targets `Array` of `tf.Tensor`s for targets.
+       * @param weights Optional `Array` of `tf.Tensor`s for sample weights.
+       * @throws ValueError: in case of incorrectly formatted data.
+       */
+      function checkArrayLengths(inputs, targets, weights) {
+        const setX = unique(inputs.map((input) => input.shape[0]));
+        setX.sort();
+        const setY = unique(targets.map((target) => target.shape[0]));
+        setY.sort();
+        // TODO(cais): Check `weights` as well.
+        if (setX.length > 1) {
+          throw new ValueError(
+            `All input Tensors (x) should have the same number of samples. ` +
+              `Got array shapes: ` +
+              `${JSON.stringify(inputs.map((input) => input.shape))}`
+          );
+        }
+        if (setY.length > 1) {
+          throw new ValueError(
+            `All target Tensors (y) should have the same number of samples. ` +
+              `Got array shapes: ` +
+              `${JSON.stringify(targets.map((target) => target.shape))}`
+          );
+        }
+        if (setX.length > 0 && setY.length > 0 && !dist["util"].arraysEqual(setX, setY)) {
+          throw new ValueError(
+            `Input Tensors should have the same number of samples as target ` +
+              `Tensors. Found ${setX[0]} input sample(s) and ${setY[0]} target ` +
+              `sample(s).`
+          );
+        }
+      }
+      /**
+       * Validation on the compatibility of targes and loss functions.
+       *
+       * This helps prevent users from using loss functions incorrectly.
+       *
+       * @param targets `Array` of `tf.Tensor`s of targets.
+       * @param lossFns `Array` of loss functions.
+       * @param outputShapes `Array` of shapes of model outputs.
+       */
+      function checkLossAndTargetCompatibility(targets, lossFns, outputShapes) {
+        // TODO(cais): Dedicated test coverage?
+        const keyLosses = [meanSquaredError, binaryCrossentropy, categoricalCrossentropy];
+        for (let i = 0; i < targets.length; ++i) {
+          const y = targets[i];
+          const loss = lossFns[i];
+          const shape = outputShapes[i];
+          if (loss == null) {
+            continue;
+          }
+          if (loss === categoricalCrossentropy) {
+            if (y.shape[y.shape.length - 1] === 1) {
+              throw new ValueError(
+                `You are passing a target array of shape ${y.shape} while using ` +
+                  `a loss 'categorical_crossentropy'. 'categorical_crossentropy'` +
+                  `expects targets to be binary matrices (1s and 0s) of shape ` +
+                  `[samples, classes].`
+              );
+              // TODO(cais): Example code in error message.
+            }
+          }
+          if (keyLosses.indexOf(loss) !== -1) {
+            const slicedYShape = y.shape.slice(1);
+            const slicedShape = shape.slice(1);
+            for (let j = 0; j < slicedYShape.length; ++j) {
+              const targetDim = slicedYShape[j];
+              const outDim = slicedShape[j];
+              if (outDim != null && targetDim !== outDim) {
+                throw new ValueError(
+                  `A target Tensor with shape ${y.shape} was passed for an ` +
+                    `output of shape ${shape}, while using a loss function that ` +
+                    `expects targets to have the same shape as the output.`
+                );
+              }
+            }
+          }
+        }
+      }
+      /**
+       * Check inputs provided by the user.
+       *
+       * Porting Note: This corresponds to _standardize_input_data() in Python
+       *   Keras. Because of the strong typing in TF.js, we do not need to convert
+       *   the data. Specifically:
+       *   1) in PyKeras, `data` can be `DataFrame` instances from pandas, for
+       *      example. We don't need to worry about that here because there is no
+       *      widely popular javascript/typesdcript equivalent of pandas (so far).
+       *      If one becomes available in the future, we can add support.
+       *   2) in PyKeras, inputs can be Python dict. But here we are stipulating
+       * that the data is either a single `tf.Tensor` or an Array of `tf.Tensor`s. We
+       * may add support for `Object` data inputs in the future when the need
+       * arises.
+       *
+       * Instead, we perform basic checks for number of parameters and shapes.
+       *
+       * @param data: The input data.
+       * @param names: Name for the inputs, from the model.
+       * @param shapes: Expected shapes for the input data, from the model.
+       * @param checkBatchAxis: Whether the size along the batch axis (i.e., the
+       *   first dimension) will be checked for matching.
+       * @param exceptionPrefix: Execption prefix message, used in generating error
+       *   messages.
+       * @throws ValueError: on incorrect number of inputs or mismatches in shapes.
+       */
+      function checkInputData(data, names, shapes, checkBatchAxis = true, exceptionPrefix = "") {
+        let arrays;
+        if (Array.isArray(data)) {
+          if (data.length !== names.length) {
+            throw new ValueError(
+              `Error when checking model ${exceptionPrefix}: the Array of ` +
+                `Tensors that you are passing to your model is not the size the ` +
+                `the model expected. Expected to see ${names.length} Tensor(s),` +
+                ` but instead got ${data.length} Tensors(s).`
+            );
+          }
+          arrays = data;
+        } else {
+          if (names.length > 1) {
+            throw new ValueError(
+              `The model expects ${names.length} ${exceptionPrefix} Tensors, ` +
+                `but only received one Tensor. Found: array with shape ` +
+                `${JSON.stringify(data.shape)}.`
+            );
+          }
+          arrays = [data];
+        }
+        if (shapes != null) {
+          for (let i = 0; i < names.length; ++i) {
+            if (shapes[i] == null) {
+              continue;
+            }
+            const array = arrays[i];
+            if (array.shape.length !== shapes[i].length) {
+              throw new ValueError(
+                `Error when checking ${exceptionPrefix}: expected ${names[i]} ` +
+                  `to have ${shapes[i].length} dimension(s), but got array with ` +
+                  `shape ${JSON.stringify(array.shape)}`
+              );
+            }
+            for (let j = 0; j < shapes[i].length; ++j) {
+              if (j === 0 && !checkBatchAxis) {
+                continue;
+              }
+              const dim = array.shape[j];
+              const refDim = shapes[i][j];
+              if (refDim != null) {
+                if (refDim !== dim) {
+                  throw new ValueError(
+                    `Error when checking ${exceptionPrefix}: expected ` +
+                      `${names[i]} to have shape ${JSON.stringify(shapes[i])} but ` +
+                      `got array with shape ${JSON.stringify(array.shape)}.`
+                  );
+                }
+              }
+            }
+          }
+        }
+      }
+      /**
+       * Maps metric functions to model outputs.
+       * @param metrics An shortcut strings name, metric function, `Array` or dict
+       *   (`Object`) of metric functions.
+       * @param outputNames An `Array` of the names of model outputs.
+       * @returns An `Array` (one entry per model output) of `Array` of metric
+       *   functions. For instance, if the model has 2 outputs, and for the first
+       *   output we want to compute `binaryAccuracy` and `binaryCrossentropy`,
+       *   and just `binaryAccuracy` for the second output, the `Array` would look
+       *   like:
+       *     `[[binaryAccuracy, binaryCrossentropy],  [binaryAccuracy]]`
+       * @throws TypeError: incompatible metrics format.
+       */
+      function collectMetrics(metrics, outputNames) {
+        if (metrics == null || (Array.isArray(metrics) && metrics.length === 0)) {
+          return outputNames.map((name) => []);
+        }
+        let wrappedMetrics;
+        if (typeof metrics === "string" || typeof metrics === "function") {
+          wrappedMetrics = [metrics];
+        } else if (Array.isArray(metrics) || typeof metrics === "object") {
+          wrappedMetrics = metrics;
+        } else {
+          throw new TypeError(
+            "Type of metrics argument not understood. Expected an string," +
+              `function, Array, or Object, found: ${metrics}`
+          );
+        }
+        if (Array.isArray(wrappedMetrics)) {
+          // We then apply all metrics to all outputs.
+          return outputNames.map((name) => wrappedMetrics);
+        } else {
+          // In this case, metrics is a dict.
+          const nestedMetrics = [];
+          for (const name of outputNames) {
+            let outputMetrics = wrappedMetrics.hasOwnProperty(name) ? wrappedMetrics[name] : [];
+            if (!Array.isArray(outputMetrics)) {
+              outputMetrics = [outputMetrics];
+            }
+            nestedMetrics.push(outputMetrics);
+          }
+          return nestedMetrics;
+        }
+      }
+      const LAYERS_MODEL_FORMAT_NAME = "layers-model";
+      /**
+       * A `tf.LayersModel` is a directed, acyclic graph of `tf.Layer`s plus methods
+       * for training, evaluation, prediction and saving.
+       *
+       * `tf.LayersModel` is the basic unit of training, inference and evaluation in
+       * TensorFlow.js. To create a `tf.LayersModel`, use `tf.LayersModel`.
+       *
+       * See also:
+       *   `tf.Sequential`, `tf.loadLayersModel`.
+       */
+      /** @doc {heading: 'Models', subheading: 'Classes'} */
+      class training_LayersModel extends container_Container {
+        constructor(args) {
+          super(args);
+          this.isTraining = false;
+        }
+        /**
+         * Print a text summary of the model's layers.
+         *
+         * The summary includes
+         * - Name and type of all layers that comprise the model.
+         * - Output shape(s) of the layers
+         * - Number of weight parameters of each layer
+         * - If the model has non-sequential-like topology, the inputs each layer
+         *   receives
+         * - The total number of trainable and non-trainable parameters of the model.
+         *
+         * ```js
+         * const input1 = tf.input({shape: [10]});
+         * const input2 = tf.input({shape: [20]});
+         * const dense1 = tf.layers.dense({units: 4}).apply(input1);
+         * const dense2 = tf.layers.dense({units: 8}).apply(input2);
+         * const concat = tf.layers.concatenate().apply([dense1, dense2]);
+         * const output =
+         *     tf.layers.dense({units: 3, activation: 'softmax'}).apply(concat);
+         *
+         * const model = tf.model({inputs: [input1, input2], outputs: output});
+         * model.summary();
+         * ```
+         *
+         * @param lineLength Custom line length, in number of characters.
+         * @param positions Custom widths of each of the columns, as either
+         *   fractions of `lineLength` (e.g., `[0.5, 0.75, 1]`) or absolute number
+         *   of characters (e.g., `[30, 50, 65]`). Each number corresponds to
+         *   right-most (i.e., ending) position of a column.
+         * @param printFn Custom print function. Can be used to replace the default
+         *   `console.log`. For example, you can use `x => {}` to mute the printed
+         *   messages in the console.
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes'} */
+        summary(lineLength, positions, printFn = console.log) {
+          if (!this.built) {
+            throw new ValueError(
+              `This model has never been called, thus its weights have not been ` +
+                `created yet. So no summary can be displayed. Build the model ` +
+                `first (e.g., by calling it on some test data).`
+            );
+          }
+          printSummary(this, lineLength, positions, printFn);
+        }
+        /**
+         * Configures and prepares the model for training and evaluation.  Compiling
+         * outfits the model with an optimizer, loss, and/or metrics.  Calling `fit`
+         * or `evaluate` on an un-compiled model will throw an error.
+         *
+         * @param args a `ModelCompileArgs` specifying the loss, optimizer, and
+         * metrics to be used for fitting and evaluating this model.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        compile(args) {
+          if (args.loss == null) {
+            args.loss = [];
+          }
+          this.loss = args.loss;
+          if (typeof args.optimizer === "string") {
+            this.optimizer_ = getOptimizer(args.optimizer);
+            this.isOptimizerOwned = true;
+          } else {
+            if (!(args.optimizer instanceof dist["Optimizer"])) {
+              throw new ValueError(`User-defined optimizer must be an instance of tf.Optimizer.`);
+            }
+            this.optimizer_ = args.optimizer;
+            this.isOptimizerOwned = false;
+          }
+          // TODO(cais): Add lossWeights.
+          // TODO(cais): Add sampleWeightMode.
+          // Prepare loss functions.
+          let lossFunctions = [];
+          if (
+            !Array.isArray(args.loss) &&
+            typeof args.loss !== "string" &&
+            typeof args.loss !== "function"
+          ) {
+            args.loss = args.loss;
+            for (const name in args.loss) {
+              if (this.outputNames.indexOf(name) === -1) {
+                throw new ValueError(
+                  `Unknown entry in loss dictionary: "${name}". ` +
+                    `Only expected the following keys: ${this.outputNames}`
+                );
+              }
+            }
+            for (const name of this.outputNames) {
+              if (args.loss[name] == null) {
+                console.warn(
+                  `Output "${name}" is missing from loss dictionary. We assume ` +
+                    `this was done on purpose, and we will not be expecting data ` +
+                    `to be passed to ${name} during training`
+                );
+              }
+              lossFunctions.push(get(args.loss[name]));
+            }
+          } else if (Array.isArray(args.loss)) {
+            if (args.loss.length !== this.outputs.length) {
+              throw new ValueError(
+                `When passing an Array as loss, it should have one entry per ` +
+                  `model output. The model has ${this.outputs.length} output(s), ` +
+                  `but you passed loss=${args.loss}.`
+              );
+            }
+            const theLosses = args.loss;
+            lossFunctions = theLosses.map((l) => get(l));
+          } else {
+            const lossFunction = get(args.loss);
+            this.outputs.forEach((_) => {
+              lossFunctions.push(lossFunction);
+            });
+          }
+          this.lossFunctions = lossFunctions;
+          this.feedOutputNames = [];
+          this.feedOutputShapes = [];
+          this.feedLossFns = [];
+          for (let i = 0; i < this.outputs.length; ++i) {
+            // TODO(cais): Logic for skipping target(s).
+            const shape = this.internalOutputShapes[i];
+            const name = this.outputNames[i];
+            this.feedOutputNames.push(name);
+            this.feedOutputShapes.push(shape);
+            this.feedLossFns.push(this.lossFunctions[i]);
+          }
+          // TODO(cais): Add logic for output masks.
+          // TODO(cais): Add logic for sample weights.
+          const skipTargetIndices = [];
+          // Prepare metrics.
+          this.metrics = args.metrics;
+          // TODO(cais): Add weightedMetrics.
+          this.metricsNames = ["loss"];
+          this.metricsTensors = [];
+          // Compute total loss.
+          // Porting Note: In PyKeras, metrics_tensors are symbolic tensor objects.
+          //   Here, metricsTensors are TypeScript functions. This difference is due
+          //   to the difference in symbolic/imperative property of the backends.
+          nameScope("loss", () => {
+            for (let i = 0; i < this.outputs.length; ++i) {
+              if (skipTargetIndices.indexOf(i) !== -1) {
+                continue;
+              }
+              // TODO(cais): Add weightedLoss, sampleWeight and mask.
+              //   The following line should be weightedLoss
+              const weightedLoss = this.lossFunctions[i];
+              if (this.outputs.length > 1) {
+                this.metricsTensors.push([weightedLoss, i]);
+                this.metricsNames.push(this.outputNames[i] + "_loss");
+              }
+            }
+            // Porting Note: Due to the imperative nature of the backend, we calculate
+            //   the regularizer penalties in the totalLossFunction, instead of here.
+          });
+          const nestedMetrics = collectMetrics(args.metrics, this.outputNames);
+          // TODO(cais): Add nestedWeightedMetrics.
+          /**
+           * Helper function used in loop below.
+           */
+          const appendMetric = (outputIndex, metricName, metricTensor) => {
+            if (this.outputNames.length > 1) {
+              metricName = this.outputNames[outputIndex] + "_" + metricName;
+            }
+            this.metricsNames.push(metricName);
+            this.metricsTensors.push([metricTensor, outputIndex]);
+          };
+          nameScope("metric", () => {
+            for (let i = 0; i < this.outputs.length; ++i) {
+              if (skipTargetIndices.indexOf(i) !== -1) {
+                continue;
+              }
+              const outputMetrics = nestedMetrics[i];
+              // TODO(cais): Add weights and outputWeightedMetrics.
+              // TODO(cais): Add optional arg `weights` to the following function.
+              const handleMetrics = (metrics) => {
+                const metricNamePrefix = "";
+                let metricName;
+                let accFn;
+                let weightedMetricFn;
+                //  TODO(cais): Use 'weights_' for weighted metrics.
+                for (const metric of metrics) {
+                  if (
+                    typeof metric === "string" &&
+                    ["accuracy", "acc", "crossentropy", "ce"].indexOf(metric) !== -1
+                  ) {
+                    const outputShape = this.internalOutputShapes[i];
+                    if (
+                      outputShape[outputShape.length - 1] === 1 ||
+                      this.lossFunctions[i] === binaryCrossentropy
+                    ) {
+                      // case: binary accuracy/crossentropy.
+                      if (["accuracy", "acc"].indexOf(metric) !== -1) {
+                        accFn = binaryAccuracy;
+                      } else if (["crossentropy", "ce"].indexOf(metric) !== -1) {
+                        accFn = metrics_binaryCrossentropy;
+                      }
+                    } else if (this.lossFunctions[i] === sparseCategoricalCrossentropy) {
+                      // case: categorical accuracy / crossentropy with sparse
+                      // targets.
+                      if (["accuracy", "acc"].indexOf(metric) !== -1) {
+                        accFn = sparseCategoricalAccuracy;
+                      } else if (["crossentropy", "ce"].indexOf(metric) !== -1) {
+                        accFn = metrics_sparseCategoricalCrossentropy;
+                      }
+                    } else {
+                      // case: categorical accuracy / crossentropy.
+                      if (["accuracy", "acc"].indexOf(metric) !== -1) {
+                        accFn = categoricalAccuracy;
+                      } else if (["crossentropy", "ce"].indexOf(metric) !== -1) {
+                        accFn = metrics_categoricalCrossentropy;
+                      }
+                    }
+                    let suffix;
+                    if (["accuracy", "acc"].indexOf(metric) !== -1) {
+                      suffix = "acc";
+                    } else if (["crossentropy", "ce"].indexOf(metric) !== -1) {
+                      suffix = "ce";
+                    }
+                    // TODO(cais): Add weighting actually.
+                    weightedMetricFn = accFn;
+                    metricName = metricNamePrefix + suffix;
+                  } else {
+                    const metricFn = metrics_get(metric);
+                    // TODO(cais): Add weighting actually.
+                    weightedMetricFn = metricFn;
+                    metricName = metricNamePrefix + getLossOrMetricName(metric);
+                  }
+                  // TODO(cais): Add weighting and masking to metricResult.
+                  let metricResult;
+                  nameScope(metricName, () => {
+                    metricResult = weightedMetricFn;
+                  });
+                  appendMetric(i, metricName, metricResult);
+                }
+              };
+              handleMetrics(outputMetrics);
+              // TODO(cais): Call handleMetrics with weights.
+            }
+          });
+          // Porting Notes: Given the imperative backend of tfjs-core,
+          //   there is no need for constructing the symbolic graph and placeholders.
+          this.collectedTrainableWeights = this.trainableWeights;
+        }
+        /**
+         * Check trainable weights count consistency.
+         *
+         * This will raise a warning if `this.trainableWeights` and
+         * `this.collectedTrainableWeights` are inconsistent (i.e., have different
+         * numbers of parameters).
+         * Inconsistency will typically arise when one modifies `model.trainable`
+         * without calling `model.compile()` again.
+         */
+        checkTrainableWeightsConsistency() {
+          if (this.collectedTrainableWeights == null) {
+            return;
+          }
+          if (this.trainableWeights.length !== this.collectedTrainableWeights.length) {
+            console.warn(
+              "Discrepancy between trainableweights and collected trainable " +
+                "weights. Did you set `model.trainable` without calling " +
+                "`model.compile()` afterwards?"
+            );
+          }
+        }
+        /**
+         * Returns the loss value & metrics values for the model in test mode.
+         *
+         * Loss and metrics are specified during `compile()`, which needs to happen
+         * before calls to `evaluate()`.
+         *
+         * Computation is done in batches.
+         *
+         * ```js
+         * const model = tf.sequential({
+         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
+         * });
+         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
+         * const result = model.evaluate(
+         *     tf.ones([8, 10]), tf.ones([8, 1]), {batchSize: 4});
+         * result.print();
+         * ```
+         *
+         * @param x `tf.Tensor` of test data, or an `Array` of `tf.Tensor`s if the
+         * model has multiple inputs.
+         * @param y `tf.Tensor` of target data, or an `Array` of `tf.Tensor`s if the
+         * model has multiple outputs.
+         * @param args A `ModelEvaluateArgs`, containing optional fields.
+         *
+         * @return `Scalar` test loss (if the model has a single output and no
+         *   metrics) or `Array` of `Scalar`s (if the model has multiple outputs
+         *   and/or metrics). The attribute `model.metricsNames`
+         *   will give you the display labels for the scalar outputs.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        evaluate(x, y, args = {}) {
+          const batchSize = args.batchSize == null ? 32 : args.batchSize;
+          checkBatchSize(batchSize);
+          // TODO(cais): Standardize `config.sampleWeights` as well.
+          // Validate user data.
+          const checkBatchAxis = true;
+          const standardizedOuts = this.standardizeUserDataXY(x, y, checkBatchAxis, batchSize);
+          try {
+            // TODO(cais): If uses `useLearningPhase`, set the corresponding element
+            // of the input to 0.
+            const ins = standardizedOuts[0].concat(standardizedOuts[1]);
+            this.makeTestFunction();
+            const f = this.testFunction;
+            const testOuts = this.testLoop(f, ins, batchSize, args.verbose, args.steps);
+            return singletonOrArray(testOuts);
+          } finally {
+            disposeNewTensors(standardizedOuts[0], x);
+            disposeNewTensors(standardizedOuts[1], y);
+          }
+        }
+        // TODO(cais): Add code snippet below once real dataset objects are
+        //   available.
+        /**
+         * Evaluate model using a dataset object.
+         *
+         * Note: Unlike `evaluate()`, this method is asynchronous (`async`);
+         *
+         * @param dataset A dataset object. Its `iterator()` method is expected
+         *   to generate a dataset iterator object, the `next()` method of which
+         *   is expected to produce data batches for evaluation. The return value
+         *   of the `next()` call ought to contain a boolean `done` field and a
+         *   `value` field. The `value` field is expected to be an array of two
+         *   `tf.Tensor`s or an array of two nested `tf.Tensor` structures. The former
+         *   case is for models with exactly one input and one output (e.g..
+         *   a sequential model). The latter case is for models with multiple
+         *   inputs and/or multiple outputs. Of the two items in the array, the
+         *   first is the input feature(s) and the second is the output target(s).
+         * @param args A configuration object for the dataset-based evaluation.
+         * @returns Loss and metric values as an Array of `Scalar` objects.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        async evaluateDataset(dataset, args) {
+          this.makeTestFunction();
+          return evaluateDataset(this, dataset, args);
+        }
+        /**
+         * Get number of samples provided for training, evaluation or prediction.
+         *
+         * @param ins Input `tf.Tensor`.
+         * @param batchSize Integer batch size, optional.
+         * @param steps Total number of steps (batches of samples) before
+         * declaring loop finished. Optional.
+         * @param stepsName The public API's parameter name for `steps`.
+         * @returns Number of samples provided.
+         */
+        checkNumSamples(ins, batchSize, steps, stepsName = "steps") {
+          let numSamples;
+          if (steps != null) {
+            numSamples = null;
+            if (batchSize != null) {
+              throw new ValueError(
+                `If ${stepsName} is set, batchSize must be null or undefined.` +
+                  `Got batchSize = ${batchSize}`
+              );
+            }
+          } else if (ins != null) {
+            if (Array.isArray(ins)) {
+              numSamples = ins[0].shape[0];
+            } else {
+              numSamples = ins.shape[0];
+            }
+          } else {
+            throw new ValueError(
+              `Either the input data should have a defined shape, or ` +
+                `${stepsName} shoud be specified.`
+            );
+          }
+          return numSamples;
+        }
+        /**
+         * Execute internal tensors of the model with input data feed.
+         * @param inputs Input data feed. Must match the inputs of the model.
+         * @param outputs Names of the output tensors to be fetched. Must match
+         *   names of the SymbolicTensors that belong to the graph.
+         * @returns Fetched values for `outputs`.
+         */
+        execute(inputs, outputs) {
+          if (Array.isArray(outputs) && outputs.length === 0) {
+            throw new ValueError("`outputs` is an empty Array, which is not allowed.");
+          }
+          const outputsIsArray = Array.isArray(outputs);
+          const outputNames = outputsIsArray ? outputs : [outputs];
+          const outputSymbolicTensors = this.retrieveSymbolicTensors(outputNames);
+          // Format the input into a FeedDict.
+          const feedDict = new executor_FeedDict();
+          if (inputs instanceof dist["Tensor"]) {
+            inputs = [inputs];
+          }
+          if (Array.isArray(inputs)) {
+            if (inputs.length !== this.inputs.length) {
+              throw new ValueError(
+                `The number of inputs provided (${inputs.length}) ` +
+                  `does not match the number of inputs of this model ` +
+                  `(${this.inputs.length}).`
+              );
+            }
+            for (let i = 0; i < this.inputs.length; ++i) {
+              feedDict.add(this.inputs[i], inputs[i]);
+            }
+          } else {
+            for (const input of this.inputs) {
+              const tensorValue = inputs[input.name];
+              if (tensorValue == null) {
+                throw new ValueError(`No value is provided for the model's input ${input.name}`);
+              }
+              feedDict.add(input, tensorValue);
+            }
+          }
+          // Run execution.
+          const executeOutputs = execute(outputSymbolicTensors, feedDict);
+          return outputsIsArray ? executeOutputs : executeOutputs[0];
+        }
+        /**
+         * Retrieve the model's internal symbolic tensors from symbolic-tensor names.
+         */
+        retrieveSymbolicTensors(symbolicTensorNames) {
+          const outputSymbolicTensors = pyListRepeat(null, symbolicTensorNames.length);
+          let outputsRemaining = symbolicTensorNames.length;
+          for (const layer of this.layers) {
+            const layerOutputs = Array.isArray(layer.output) ? layer.output : [layer.output];
+            const layerOutputNames = layerOutputs.map((output) => output.name);
+            for (let i = 0; i < symbolicTensorNames.length; ++i) {
+              const index = layerOutputNames.indexOf(symbolicTensorNames[i]);
+              if (index !== -1) {
+                outputSymbolicTensors[i] = layerOutputs[index];
+                outputsRemaining--;
+              }
+              if (outputsRemaining === 0) {
+                break;
+              }
+            }
+            if (outputsRemaining === 0) {
+              break;
+            }
+          }
+          if (outputsRemaining > 0) {
+            const remainingNames = [];
+            outputSymbolicTensors.forEach((tensor, i) => {
+              if (tensor == null) {
+                remainingNames.push(symbolicTensorNames[i]);
+              }
+            });
+            throw new ValueError(
+              `Cannot find SymbolicTensors for output name(s): ` +
+                `${JSON.stringify(remainingNames)}`
+            );
+          }
+          return outputSymbolicTensors;
+        }
+        /**
+         * Helper method to loop over some data in batches.
+         *
+         * Porting Note: Not using the functional approach in the Python equivalent
+         *   due to the imperative backend.
+         * Porting Note: Does not support step mode currently.
+         *
+         * @param ins: input data
+         * @param batchSize: integer batch size.
+         * @param verbose: verbosity model
+         * @returns: Predictions as `tf.Tensor` (if a single output) or an `Array` of
+         *   `tf.Tensor` (if multipe outputs).
+         */
+        predictLoop(ins, batchSize = 32, verbose = false) {
+          return dist["tidy"](() => {
+            const numSamples = this.checkNumSamples(ins);
+            if (verbose) {
+              throw new NotImplementedError("Verbose predictLoop() is not implemented yet.");
+            }
+            // Sample-based predictions.
+            // Porting Note: Tensor currently does not support sliced assignments as
+            //   in numpy, e.g., x[1:3] = y. Therefore we use concatenation while
+            //   iterating over the batches.
+            const batches = makeBatches(numSamples, batchSize);
+            const outsBatches = this.outputs.map((output) => []);
+            // TODO(cais): Can the scope() be pushed down inside the for loop?
+            for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {
+              const batchOuts = dist["tidy"](() => {
+                const batchStart = batches[batchIndex][0];
+                const batchEnd = batches[batchIndex][1];
+                // TODO(cais): Take care of the case of the last element is a flag for
+                //   training/test.
+                const insBatch = sliceArrays(ins, batchStart, batchEnd);
+                // Construct the feeds for execute();
+                const feeds = [];
+                if (Array.isArray(insBatch)) {
+                  for (let i = 0; i < insBatch.length; ++i) {
+                    feeds.push({ key: this.inputs[i], value: insBatch[i] });
+                  }
+                } else {
+                  feeds.push({ key: this.inputs[0], value: insBatch });
+                }
+                const feedDict = new executor_FeedDict(feeds);
+                return execute(this.outputs, feedDict);
+              });
+              batchOuts.forEach((batchOut, i) => outsBatches[i].push(batchOut));
+            }
+            return singletonOrArray(outsBatches.map((batches) => dist["concat"](batches, 0)));
+          });
+        }
+        /**
+         * Generates output predictions for the input samples.
+         *
+         * Computation is done in batches.
+         *
+         * Note: the "step" mode of predict() is currently not supported.
+         *   This is because the TensorFlow.js core backend is imperative only.
+         *
+         * ```js
+         * const model = tf.sequential({
+         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
+         * });
+         * model.predict(tf.ones([8, 10]), {batchSize: 4}).print();
+         * ```
+         *
+         * @param x The input data, as a Tensor, or an `Array` of `tf.Tensor`s if
+         *   the model has multiple inputs.
+         * @param args A `ModelPredictArgs` object containing optional fields.
+         *
+         * @return Prediction results as a `tf.Tensor`(s).
+         *
+         * @exception ValueError In case of mismatch between the provided input data
+         *   and the model's expectations, or in case a stateful model receives a
+         *   number of samples that is not a multiple of the batch size.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        predict(x, args = {}) {
+          const xsRank2OrHigher = ensureTensorsRank2OrHigher(x);
+          checkInputData(xsRank2OrHigher, this.inputNames, this.feedInputShapes, false);
+          try {
+            // TODO(cais): Take care of stateful models.
+            //   if (this.stateful) ...
+            // TODO(cais): Take care of the learning_phase boolean flag.
+            //   if (this.useLearningPhase) ...
+            const batchSize = args.batchSize == null ? 32 : args.batchSize;
+            checkBatchSize(batchSize);
+            return this.predictLoop(xsRank2OrHigher, batchSize);
+          } finally {
+            disposeNewTensors(xsRank2OrHigher, x);
+          }
+        }
+        /**
+         * Returns predictions for a single batch of samples.
+         *
+         * ```js
+         * const model = tf.sequential({
+         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
+         * });
+         * model.predictOnBatch(tf.ones([8, 10])).print();
+         * ```
+         * @param x: Input samples, as a Tensor (for models with exactly one
+         *   input) or an array of Tensors (for models with more than one input).
+         * @return Tensor(s) of predictions
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes'} */
+        predictOnBatch(x) {
+          checkInputData(x, this.inputNames, this.feedInputShapes, true);
+          // TODO(cais): Take care of the learning_phase boolean flag.
+          //   if (this.useLearningPhase) ...
+          const batchSize = (Array.isArray(x) ? x[0] : x).shape[0];
+          return this.predictLoop(x, batchSize);
+        }
+        standardizeUserDataXY(x, y, checkBatchAxis = true, batchSize) {
+          // TODO(cais): Add sampleWeight, classWeight
+          if (this.optimizer_ == null) {
+            throw new RuntimeError(
+              "You must compile a model before training/testing. Use " +
+                "LayersModel.compile(modelCompileArgs)."
+            );
+          }
+          const outputShapes = [];
+          for (let i = 0; i < this.feedOutputShapes.length; ++i) {
+            const outputShape = this.feedOutputShapes[i];
+            const lossFn = this.feedLossFns[i];
+            if (lossFn === sparseCategoricalCrossentropy) {
+              outputShapes.push(outputShape.slice(0, outputShape.length - 1).concat([1]));
+            } else {
+              // Porting Note: Because of strong typing `lossFn` must be a function.
+              outputShapes.push(outputShape);
+            }
+          }
+          x = standardizeInputData(x, this.feedInputNames, this.feedInputShapes, false, "input");
+          y = standardizeInputData(y, this.feedOutputNames, outputShapes, false, "target");
+          // TODO(cais): Standardize sampleWeights & classWeights.
+          checkArrayLengths(x, y, null);
+          // TODO(cais): Check sampleWeights as well.
+          checkLossAndTargetCompatibility(y, this.feedLossFns, this.feedOutputShapes);
+          if (this.stateful && batchSize != null && batchSize > 0) {
+            if (x[0].shape[0] % batchSize !== 0) {
+              throw new ValueError(
+                `In a stateful network, you should only pass inputs with a ` +
+                  `number of samples that is divisible by the batch size ` +
+                  `${batchSize}. Found: ${x[0].shape[0]} sample(s).`
+              );
+            }
+          }
+          return [x, y];
+        }
+        async standardizeUserData(
+          x,
+          y,
+          sampleWeight,
+          classWeight,
+          checkBatchAxis = true,
+          batchSize
+        ) {
+          const [standardXs, standardYs] = this.standardizeUserDataXY(
+            x,
+            y,
+            checkBatchAxis,
+            batchSize
+          );
+          // TODO(cais): Handle sampleWeights.
+          if (sampleWeight != null) {
+            throw new Error("sample weight is not supported yet.");
+          }
+          let standardSampleWeights = null;
+          if (classWeight != null) {
+            const classWeights = standardizeClassWeights(classWeight, this.outputNames);
+            standardSampleWeights = [];
+            for (let i = 0; i < classWeights.length; ++i) {
+              standardSampleWeights.push(
+                await standardizeWeights(standardYs[i], null, classWeights[i])
+              );
+            }
+          }
+          // TODO(cais): Deal with the case of model.stateful == true.
+          return [standardXs, standardYs, standardSampleWeights];
+        }
+        /**
+         * Loop over some test data in batches.
+         * @param f A Function returning a list of tensors.
+         * @param ins Array of tensors to be fed to `f`.
+         * @param batchSize Integer batch size or `null` / `undefined`.
+         * @param verbose verbosity mode.
+         * @param steps Total number of steps (batches of samples) before
+         * declaring test finished. Ignored with the default value of `null` /
+         * `undefined`.
+         * @returns Array of Scalars.
+         */
+        testLoop(f, ins, batchSize, verbose = 0, steps) {
+          return dist["tidy"](() => {
+            const numSamples = this.checkNumSamples(ins, batchSize, steps, "steps");
+            const outs = [];
+            if (verbose > 0) {
+              throw new NotImplementedError("Verbose mode is not implemented yet.");
+            }
+            // TODO(cais): Use `indicesForConversionToDense' to prevent slow down.
+            if (steps != null) {
+              throw new NotImplementedError("steps mode in testLoop() is not implemented yet");
+            } else {
+              const batches = makeBatches(numSamples, batchSize);
+              const indexArray = Object(dist["tensor1d"])(range(0, numSamples));
+              for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {
+                const batchStart = batches[batchIndex][0];
+                const batchEnd = batches[batchIndex][1];
+                const batchIds = sliceAlongFirstAxis(indexArray, batchStart, batchEnd - batchStart);
+                // TODO(cais): In ins, train flag can be a number, instead of an
+                //   Tensor? Do we need to handle this in tfjs-layers?
+                const insBatch = sliceArraysByIndices(ins, batchIds);
+                const batchOuts = f(insBatch);
+                if (batchIndex === 0) {
+                  for (let i = 0; i < batchOuts.length; ++i) {
+                    outs.push(Object(dist["scalar"])(0));
+                  }
+                }
+                for (let i = 0; i < batchOuts.length; ++i) {
+                  const batchOut = batchOuts[i];
+                  outs[i] = dist["add"](outs[i], dist["mul"](batchEnd - batchStart, batchOut));
+                }
+              }
+              for (let i = 0; i < outs.length; ++i) {
+                outs[i] = dist["div"](outs[i], numSamples);
+              }
+            }
+            return outs;
+          });
+        }
+        getDedupedMetricsNames() {
+          const outLabels = this.metricsNames;
+          // Rename duplicated metrics names (can happen with an output layer
+          // shared among multiple dataflows).
+          const dedupedOutLabels = [];
+          for (let i = 0; i < outLabels.length; ++i) {
+            const label = outLabels[i];
+            let newLabel = label;
+            if (generic_utils_count(outLabels, label) > 1) {
+              const dupIndex = generic_utils_count(outLabels.slice(0, i), label);
+              newLabel += `_${dupIndex}`;
+            }
+            dedupedOutLabels.push(newLabel);
+          }
+          return dedupedOutLabels;
+        }
+        /**
+         * Creates a function that performs the following actions:
+         *
+         * 1. computes the losses
+         * 2. sums them to get the total loss
+         * 3. call the optimizer computes the gradients of the LayersModel's
+         *    trainable weights w.r.t. the total loss and update the variables
+         * 4. calculates the metrics
+         * 5. returns the values of the losses and metrics.
+         */
+        makeTrainFunction() {
+          return (data) => {
+            const lossValues = [];
+            const inputs = data.slice(0, this.inputs.length);
+            const targets = data.slice(
+              this.inputs.length,
+              this.inputs.length + this.outputs.length
+            );
+            const sampleWeights = data.slice(
+              this.inputs.length + this.outputs.length,
+              this.inputs.length + this.outputs.length * 2
+            );
+            const metricsValues = [];
+            // Create a function that computes the total loss based on the
+            // inputs. This function is used for obtaining gradients through
+            // backprop.
+            const totalLossFunction = () => {
+              const feeds = [];
+              for (let i = 0; i < this.inputs.length; ++i) {
+                feeds.push({ key: this.inputs[i], value: inputs[i] });
+              }
+              const feedDict = new executor_FeedDict(feeds);
+              const outputs = execute(this.outputs, feedDict, { training: true });
+              // TODO(cais): Take care of the case of multiple outputs from a
+              //   single layer?
+              let totalLoss;
+              for (let i = 0; i < this.lossFunctions.length; ++i) {
+                const lossFunction = this.lossFunctions[i];
+                let loss = lossFunction(targets[i], outputs[i]);
+                if (sampleWeights[i] != null) {
+                  loss = computeWeightedLoss(loss, sampleWeights[i]);
+                }
+                // TODO(cais): push Scalar instead.
+                const meanLoss = dist["mean"](loss);
+                // TODO(cais): Use a scope() instead, to avoid ownership.
+                lossValues.push(meanLoss);
+                if (i === 0) {
+                  totalLoss = loss;
+                } else {
+                  totalLoss = dist["add"](totalLoss, loss);
+                }
+              }
+              // Compute the metrics.
+              // TODO(cais): These should probably be calculated outside
+              //   totalLossFunction to benefit speed?
+              for (let i = 0; i < this.metricsTensors.length; ++i) {
+                let weightedMetric;
+                if (this.outputs.length > 1 && i < this.outputs.length) {
+                  weightedMetric = lossValues[i];
+                } else {
+                  const metric = this.metricsTensors[i][0];
+                  const outputIndex = this.metricsTensors[i][1];
+                  weightedMetric = dist["mean"](metric(targets[outputIndex], outputs[outputIndex]));
+                }
+                dist["keep"](weightedMetric);
+                // TODO(cais): Use a scope() instead, to avoid ownership.
+                metricsValues.push(weightedMetric);
+              }
+              totalLoss = dist["mean"](totalLoss);
+              // Add regularizer penalties.
+              this.calculateLosses().forEach((regularizerLoss) => {
+                totalLoss = dist["add"](totalLoss, regularizerLoss);
+              });
+              return totalLoss;
+            };
+            const variables = this.collectedTrainableWeights.map((param) => param.read());
+            const returnCost = true;
+            const totalLossValue = this.optimizer_.minimize(
+              totalLossFunction,
+              returnCost,
+              variables
+            );
+            return [totalLossValue].concat(metricsValues);
+          };
+        }
+        /**
+         * Create a function which, when invoked with an array of `tf.Tensor`s as a
+         * batch of inputs, returns the prespecified loss and metrics of the model
+         * under the batch of input data.
+         */
+        makeTestFunction() {
+          this.testFunction = (data) => {
+            return dist["tidy"](() => {
+              const valOutputs = [];
+              let totalLoss;
+              const inputs = data.slice(0, this.inputs.length);
+              const targets = data.slice(
+                this.inputs.length,
+                this.inputs.length + this.outputs.length
+              );
+              const feeds = [];
+              for (let i = 0; i < this.inputs.length; ++i) {
+                feeds.push({ key: this.inputs[i], value: inputs[i] });
+              }
+              const feedDict = new executor_FeedDict(feeds);
+              const outputs = execute(this.outputs, feedDict);
+              // Compute total loss.
+              for (let i = 0; i < this.lossFunctions.length; ++i) {
+                const lossFunction = this.lossFunctions[i];
+                // TODO(cais): Add sample weighting and replace the simple
+                // averaging.
+                const loss = dist["mean"](lossFunction(targets[i], outputs[i]));
+                if (i === 0) {
+                  totalLoss = loss;
+                } else {
+                  totalLoss = dist["add"](totalLoss, loss);
+                }
+                valOutputs.push(totalLoss);
+              }
+              // Compute the metrics.
+              for (let i = 0; i < this.metricsTensors.length; ++i) {
+                const metric = this.metricsTensors[i][0];
+                const outputIndex = this.metricsTensors[i][1];
+                // TODO(cais): Replace K.mean() with a proper weighting function.
+                const meanMetric = dist["mean"](metric(targets[outputIndex], outputs[outputIndex]));
+                valOutputs.push(meanMetric);
+              }
+              return valOutputs;
+            });
+          };
+        }
+        /**
+         * Trains the model for a fixed number of epochs (iterations on a
+         * dataset).
+         *
+         * ```js
+         * const model = tf.sequential({
+         *     layers: [tf.layers.dense({units: 1, inputShape: [10]})]
+         * });
+         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
+         * for (let i = 1; i < 5 ; ++i) {
+         *   const h = await model.fit(tf.ones([8, 10]), tf.ones([8, 1]), {
+         *       batchSize: 4,
+         *       epochs: 3
+         *   });
+         *   console.log("Loss after Epoch " + i + " : " + h.history.loss[0]);
+         * }
+         * ```
+         *
+         * @param x `tf.Tensor` of training data, or an array of `tf.Tensor`s if the
+         * model has multiple inputs. If all inputs in the model are named, you
+         * can also pass a dictionary mapping input names to `tf.Tensor`s.
+         * @param y `tf.Tensor` of target (label) data, or an array of `tf.Tensor`s if
+         * the model has multiple outputs. If all outputs in the model are named,
+         * you can also pass a dictionary mapping output names to `tf.Tensor`s.
+         * @param args A `ModelFitArgs`, containing optional fields.
+         *
+         * @return A `History` instance. Its `history` attribute contains all
+         *   information collected during training.
+         *
+         * @exception ValueError In case of mismatch between the provided input
+         * data and what the model expects.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        async fit(x, y, args = {}) {
+          return fitTensors(this, x, y, args);
+        }
+        // TODO(cais): Add code snippet below when it's possible to instantiate
+        //   actual dataset objects.
+        /**
+         * Trains the model using a dataset object.
+         *
+         * @param dataset A dataset object. Its `iterator()` method is expected
+         *   to generate a dataset iterator object, the `next()` method of which
+         *   is expected to produce data batches for training. The return value
+         *   of the `next()` call ought to contain a boolean `done` field and a
+         *   `value` field. The `value` field is expected to be an array of two
+         *   `tf.Tensor`s or an array of two nested `tf.Tensor` structures. The former
+         *   case is for models with exactly one input and one output (e.g..
+         *   a sequential model). The latter case is for models with multiple
+         *   inputs and/or multiple outputs.
+         *   Of the two items in the array, the first is the input feature(s) and
+         *   the second is the output target(s).
+         * @param args A `ModelFitDatasetArgs`, containing optional fields.
+         *
+         * @return A `History` instance. Its `history` attribute contains all
+         *   information collected during training.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        async fitDataset(dataset, args) {
+          return fitDataset(this, dataset, args);
+        }
+        /**
+         * Runs a single gradient update on a single batch of data.
+         *
+         * This method differs from `fit()` and `fitDataset()` in the following
+         * regards:
+         *   - It operates on exactly one batch of data.
+         *   - It returns only the loss and matric values, instead of
+         *     returning the batch-by-batch loss and metric values.
+         *   - It doesn't support fine-grained options such as verbosity and
+         *     callbacks.
+         *
+         * @param x Input data. It could be one of the following:
+         *   - A `tf.Tensor`, or an Array of `tf.Tensor`s (in case the model has
+         *     multiple inputs).
+         *   - An Object mapping input names to corresponding `tf.Tensor` (if the
+         *     model has named inputs).
+         * @param y Target darta. It could be either a `tf.Tensor` a multiple
+         *   `tf.Tensor`s. It should be consistent with `x`.
+         * @returns Training loss or losses (in case the model has
+         *   multiple outputs), along with metrics (if any), as numbers.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        async trainOnBatch(x, y) {
+          // TODO(cais): Support sampleWeight and classWeight.
+          // TODO(cais): Support Dataset objects.
+          const standardizeOut = await this.standardizeUserData(x, y);
+          const inputs = standardizeOut[0];
+          const targets = standardizeOut[1];
+          const trainFunction = this.makeTrainFunction();
+          const losses = trainFunction(inputs.concat(targets));
+          const lossValues = [];
+          for (const loss of losses) {
+            const v = await loss.data();
+            lossValues.push(v[0]);
+          }
+          dist["dispose"](losses);
+          return singletonOrArray(lossValues);
+        }
+        /**
+         * Extract weight values of the model.
+         *
+         * @param config: An instance of `io.SaveConfig`, which specifies
+         * model-saving options such as whether only trainable weights are to be
+         * saved.
+         * @returns A `NamedTensorMap` mapping original weight names (i.e.,
+         *   non-uniqueified weight names) to their values.
+         */
+        getNamedWeights(config) {
+          const namedWeights = [];
+          const trainableOnly = config != null && config.trainableOnly;
+          const weights = trainableOnly ? this.trainableWeights : this.weights;
+          const weightValues = this.getWeights(trainableOnly);
+          for (let i = 0; i < weights.length; ++i) {
+            if (trainableOnly && !weights[i].trainable) {
+              // Optionally skip non-trainable weights.
+              continue;
+            }
+            namedWeights.push({ name: weights[i].originalName, tensor: weightValues[i] });
+          }
+          return namedWeights;
+        }
+        /**
+         * Setter used for force stopping of LayersModel.fit() (i.e., training).
+         *
+         * Example:
+         *
+         * ```js
+         * const input = tf.input({shape: [10]});
+         * const output = tf.layers.dense({units: 1}).apply(input);
+         * const model = tf.model({inputs: [input], outputs: [output]});
+         * model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
+         * const xs = tf.ones([8, 10]);
+         * const ys = tf.zeros([8, 1]);
+         *
+         * const history = await model.fit(xs, ys, {
+         *   epochs: 10,
+         *   callbacks: {
+         *     onEpochEnd: async (epoch, logs) => {
+         *       if (epoch === 2) {
+         *         model.stopTraining = true;
+         *       }
+         *     }
+         *   }
+         * });
+         *
+         * // There should be only 3 values in the loss array, instead of 10
+         * values,
+         * // due to the stopping after 3 epochs.
+         * console.log(history.history.loss);
+         * ```
+         */
+        set stopTraining(stop) {
+          this.stopTraining_ = stop;
+        }
+        get stopTraining() {
+          return this.stopTraining_;
+        }
+        get optimizer() {
+          return this.optimizer_;
+        }
+        set optimizer(optimizer) {
+          if (this.optimizer_ !== optimizer) {
+            this.optimizer_ = optimizer;
+            this.isOptimizerOwned = false;
+          }
+        }
+        dispose() {
+          const result = super.dispose();
+          if (
+            result.refCountAfterDispose === 0 &&
+            this.optimizer != null &&
+            this.isOptimizerOwned
+          ) {
+            const numTensorsBeforeOptmizerDisposal = dist["memory"]().numTensors;
+            this.optimizer_.dispose();
+            result.numDisposedVariables +=
+              numTensorsBeforeOptmizerDisposal - dist["memory"]().numTensors;
+          }
+          return result;
+        }
+        getLossIdentifiers() {
+          let lossNames;
+          if (typeof this.loss === "string") {
+            lossNames = toSnakeCase(this.loss);
+          } else if (Array.isArray(this.loss)) {
+            for (const loss of this.loss) {
+              if (typeof loss !== "string") {
+                throw new Error("Serialization of non-string loss is not supported.");
+              }
+            }
+            lossNames = this.loss.map((name) => toSnakeCase(name));
+          } else {
+            const outputNames = Object.keys(this.loss);
+            lossNames = {};
+            const losses = this.loss;
+            for (const outputName of outputNames) {
+              if (typeof losses[outputName] === "string") {
+                lossNames[outputName] = toSnakeCase(losses[outputName]);
+              } else {
+                throw new Error("Serialization of non-string loss is not supported.");
+              }
+            }
+          }
+          return lossNames;
+        }
+        getMetricIdentifiers() {
+          if (typeof this.metrics === "string" || typeof this.metrics === "function") {
+            return [toSnakeCase(getLossOrMetricName(this.metrics))];
+          } else if (Array.isArray(this.metrics)) {
+            return this.metrics.map((metric) => toSnakeCase(getLossOrMetricName(metric)));
+          } else {
+            const metricsIdentifiers = {};
+            for (const key in this.metrics) {
+              metricsIdentifiers[key] = toSnakeCase(getLossOrMetricName(this.metrics[key]));
+            }
+            return metricsIdentifiers;
+          }
+        }
+        getTrainingConfig() {
+          return {
+            loss: this.getLossIdentifiers(),
+            metrics: this.getMetricIdentifiers(),
+            optimizer_config: {
+              class_name: this.optimizer.getClassName(),
+              config: this.optimizer.getConfig(),
+            },
+          };
+          // TODO(cais): Add weight_metrics when they are supported.
+          // TODO(cais): Add sample_weight_mode when it's supported.
+          // TODO(cais): Add loss_weights when it's supported.
+        }
+        loadTrainingConfig(trainingConfig) {
+          if (trainingConfig.weighted_metrics != null) {
+            throw new Error("Loading weight_metrics is not supported yet.");
+          }
+          if (trainingConfig.loss_weights != null) {
+            throw new Error("Loading loss_weights is not supported yet.");
+          }
+          if (trainingConfig.sample_weight_mode != null) {
+            throw new Error("Loading sample_weight_mode is not supported yet.");
+          }
+          const tsConfig = convertPythonicToTs(trainingConfig.optimizer_config);
+          const optimizer = deserialize(tsConfig);
+          let loss;
+          if (typeof trainingConfig.loss === "string") {
+            loss = toCamelCase(trainingConfig.loss);
+          } else if (Array.isArray(trainingConfig.loss)) {
+            loss = trainingConfig.loss.map((lossEntry) => toCamelCase(lossEntry));
+          } else if (trainingConfig.loss != null) {
+            loss = {};
+            for (const key in trainingConfig.loss) {
+              loss[key] = toCamelCase(trainingConfig.loss[key]);
+            }
+          }
+          let metrics;
+          if (Array.isArray(trainingConfig.metrics)) {
+            metrics = trainingConfig.metrics.map((metric) => toCamelCase(metric));
+          } else if (trainingConfig.metrics != null) {
+            metrics = {};
+            for (const key in trainingConfig.metrics) {
+              metrics[key] = toCamelCase(trainingConfig.metrics[key]);
+            }
+          }
+          this.compile({ loss, metrics, optimizer });
+        }
+        /**
+         * Save the configuration and/or weights of the LayersModel.
+         *
+         * An `IOHandler` is an object that has a `save` method of the proper
+         * signature defined. The `save` method manages the storing or
+         * transmission of serialized data ("artifacts") that represent the
+         * model's topology and weights onto or via a specific medium, such as
+         * file downloads, local storage, IndexedDB in the web browser and HTTP
+         * requests to a server. TensorFlow.js provides `IOHandler`
+         * implementations for a number of frequently used saving mediums, such as
+         * `tf.io.browserDownloads` and `tf.io.browserLocalStorage`. See `tf.io`
+         * for more details.
+         *
+         * This method also allows you to refer to certain types of `IOHandler`s
+         * as URL-like string shortcuts, such as 'localstorage://' and
+         * 'indexeddb://'.
+         *
+         * Example 1: Save `model`'s topology and weights to browser [local
+         * storage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage);
+         * then load it back.
+         *
+         * ```js
+         * const model = tf.sequential(
+         *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
+         * console.log('Prediction from original model:');
+         * model.predict(tf.ones([1, 3])).print();
+         *
+         * const saveResults = await model.save('localstorage://my-model-1');
+         *
+         * const loadedModel = await tf.loadLayersModel('localstorage://my-model-1');
+         * console.log('Prediction from loaded model:');
+         * loadedModel.predict(tf.ones([1, 3])).print();
+         * ```
+         *
+         * Example 2. Saving `model`'s topology and weights to browser
+         * [IndexedDB](https://developer.mozilla.org/en-US/docs/Web/API/IndexedDB_API);
+         * then load it back.
+         *
+         * ```js
+         * const model = tf.sequential(
+         *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
+         * console.log('Prediction from original model:');
+         * model.predict(tf.ones([1, 3])).print();
+         *
+         * const saveResults = await model.save('indexeddb://my-model-1');
+         *
+         * const loadedModel = await tf.loadLayersModel('indexeddb://my-model-1');
+         * console.log('Prediction from loaded model:');
+         * loadedModel.predict(tf.ones([1, 3])).print();
+         * ```
+         *
+         * Example 3. Saving `model`'s topology and weights as two files
+         * (`my-model-1.json` and `my-model-1.weights.bin`) downloaded from
+         * browser.
+         *
+         * ```js
+         * const model = tf.sequential(
+         *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
+         * const saveResults = await model.save('downloads://my-model-1');
+         * ```
+         *
+         * Example 4. Send  `model`'s topology and weights to an HTTP server.
+         * See the documentation of `tf.io.http` for more details
+         * including specifying request parameters and implementation of the
+         * server.
+         *
+         * ```js
+         * const model = tf.sequential(
+         *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
+         * const saveResults = await model.save('http://my-server/model/upload');
+         * ```
+         *
+         * @param handlerOrURL An instance of `IOHandler` or a URL-like,
+         * scheme-based string shortcut for `IOHandler`.
+         * @param config Options for saving the model.
+         * @returns A `Promise` of `SaveResult`, which summarizes the result of
+         * the saving, such as byte sizes of the saved artifacts for the model's
+         *   topology and weight values.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes', ignoreCI: true}
+         */
+        async save(handlerOrURL, config) {
+          if (typeof handlerOrURL === "string") {
+            const handlers = dist["io"].getSaveHandlers(handlerOrURL);
+            if (handlers.length === 0) {
+              throw new ValueError(`Cannot find any save handlers for URL '${handlerOrURL}'`);
+            } else if (handlers.length > 1) {
+              throw new ValueError(
+                `Found more than one (${handlers.length}) save handlers for ` +
+                  `URL '${handlerOrURL}'`
+              );
+            }
+            handlerOrURL = handlers[0];
+          }
+          if (handlerOrURL.save == null) {
+            throw new ValueError(
+              "LayersModel.save() cannot proceed because the IOHandler " +
+                "provided does not have the `save` attribute defined."
+            );
+          }
+          const weightDataAndSpecs = await dist["io"].encodeWeights(this.getNamedWeights(config));
+          const returnString = false;
+          const unusedArg = null;
+          const modelConfig = this.toJSON(unusedArg, returnString);
+          const modelArtifacts = {
+            modelTopology: modelConfig,
+            format: LAYERS_MODEL_FORMAT_NAME,
+            generatedBy: `TensorFlow.js tfjs-layers v${version}`,
+            convertedBy: null,
+          };
+          const includeOptimizer = config == null ? false : config.includeOptimizer;
+          if (includeOptimizer && this.optimizer != null) {
+            modelArtifacts.trainingConfig = this.getTrainingConfig();
+            const weightType = "optimizer";
+            const { data: optimizerWeightData, specs: optimizerWeightSpecs } = await dist[
+              "io"
+            ].encodeWeights(await this.optimizer.getWeights(), weightType);
+            weightDataAndSpecs.specs.push(...optimizerWeightSpecs);
+            weightDataAndSpecs.data = dist["io"].concatenateArrayBuffers([
+              weightDataAndSpecs.data,
+              optimizerWeightData,
+            ]);
+          }
+          if (this.userDefinedMetadata != null) {
+            // Check serialized size of user-defined metadata.
+            const checkSize = true;
+            checkUserDefinedMetadata(this.userDefinedMetadata, this.name, checkSize);
+            modelArtifacts.userDefinedMetadata = this.userDefinedMetadata;
+          }
+          modelArtifacts.weightData = weightDataAndSpecs.data;
+          modelArtifacts.weightSpecs = weightDataAndSpecs.specs;
+          return handlerOrURL.save(modelArtifacts);
+        }
+        /**
+         * Set user-defined metadata.
+         *
+         * The set metadata will be serialized together with the topology
+         * and weights of the model during `save()` calls.
+         *
+         * @param setUserDefinedMetadata
+         */
+        setUserDefinedMetadata(userDefinedMetadata) {
+          checkUserDefinedMetadata(userDefinedMetadata, this.name);
+          this.userDefinedMetadata = userDefinedMetadata;
+        }
+        /**
+         * Get user-defined metadata.
+         *
+         * The metadata is supplied via one of the two routes:
+         *   1. By calling `setUserDefinedMetadata()`.
+         *   2. Loaded during model loading (if the model is constructed
+         *      via `tf.loadLayersModel()`.)
+         *
+         * If no user-defined metadata is available from either of the
+         * two routes, this function will return `undefined`.
+         */
+        getUserDefinedMetadata() {
+          return this.userDefinedMetadata;
+        }
+      }
+      // The class name is 'Model' rather than 'LayersModel' for backwards
+      // compatibility since this class name shows up in the serialization format.
+      /** @nocollapse */
+      training_LayersModel.className = "Model";
+      dist["serialization"].registerClass(training_LayersModel);
+      //# sourceMappingURL=training.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/models.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original source keras/models.py */
+
+      /**
+       * Parses a JSON model configuration file and returns a model instance.
+       *
+       * ```js
+       * // This example shows how to serialize a model using `toJSON()` and
+       * // deserialize it as another model using `tf.models.modelFromJSON()`.
+       * // Note: this example serializes and deserializes only the topology
+       * // of the model; the weights of the loaded model will be different
+       * // from those of the the original model, due to random weight
+       * // initialization.
+       * // To load the topology and weights of a model, use `tf.loadLayersModel()`.
+       * const model1 = tf.sequential();
+       * model1.add(tf.layers.repeatVector({inputShape: [2], n: 4}));
+       * // Serialize `model1` as a JSON object.
+       * const model1JSON = model1.toJSON(null, false);
+       * model1.summary();
+       *
+       * const model2 = await tf.models.modelFromJSON(model1JSON);
+       * model2.summary();
+       * ```
+       *
+       *  @param modelAndWeightsConfig JSON object or string encoding a model and
+       *       weights configuration. It can also be only the topology JSON of the
+       *       model, in which case the weights will not be loaded.
+       *  @param custom_objects Optional dictionary mapping names
+       *       (strings) to custom classes or functions to be
+       *       considered during deserialization.
+       * @returns A TensorFlow.js Layers `tf.LayersModel` instance (uncompiled).
+       */
+      async function modelFromJSON(modelAndWeightsConfig, customObjects) {
+        if (!("modelTopology" in modelAndWeightsConfig)) {
+          modelAndWeightsConfig = { modelTopology: modelAndWeightsConfig };
+        }
+        modelAndWeightsConfig = modelAndWeightsConfig;
+        let modelTopology = modelAndWeightsConfig.modelTopology;
+        if (modelTopology["model_config"] != null) {
+          // If the model-topology JSON contains a 'model_config' field, then it is
+          // a full model JSON (e.g., from `keras.Model.save()`), which contains
+          // not only the model's architecture in its 'model_config' field, but
+          // additional information such as the model's optimizer. We use only the
+          // 'model_config' field currently.
+          modelTopology = modelTopology["model_config"];
+        }
+        const tsConfig = convertPythonicToTs(modelTopology);
+        const model = deserialize(tsConfig, customObjects);
+        if (modelAndWeightsConfig.weightsManifest != null) {
+          // Load the weight values keyed by the original tensor names in the model
+          // file that was loaded.  These should match the keys of the weight
+          // manifest.
+          const weightValues = await dist["io"].loadWeights(
+            modelAndWeightsConfig.weightsManifest,
+            modelAndWeightsConfig.pathPrefix,
+            model.weights.map((weight) => weight.originalName)
+          );
+          // Map the weights to the unique tensor names generated during model loading
+          const uniqueWeightValues = {};
+          for (const weight of model.weights) {
+            uniqueWeightValues[weight.originalName] = weightValues[weight.originalName];
+          }
+          model.loadWeights(uniqueWeightValues);
+          // Dispose temporary weight values.
+          Object(dist["dispose"])(weightValues);
+        }
+        return model;
+      }
+      /**
+       * Load a model, including its topology and optionally weights.  See the
+       * Tutorial named "How to import a Keras Model" for usage examples.
+       *
+       * Example 1: Save `model`'s topology and weights to browser [local
+       * storage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage);
+       * then load it back.
+       *
+       * ```js
+       * const model = tf.sequential(
+       *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
+       * console.log('Prediction from original model:');
+       * model.predict(tf.ones([1, 3])).print();
+       *
+       * const saveResults = await model.save('localstorage://my-model-1');
+       *
+       * const loadedModel = await tf.loadLayersModel('localstorage://my-model-1');
+       * console.log('Prediction from loaded model:');
+       * loadedModel.predict(tf.ones([1, 3])).print();
+       * ```
+       *
+       * Example 2. Saving `model`'s topology and weights to browser
+       * [IndexedDB](https://developer.mozilla.org/en-US/docs/Web/API/IndexedDB_API);
+       * then load it back.
+       *
+       * ```js
+       * const model = tf.sequential(
+       *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
+       * console.log('Prediction from original model:');
+       * model.predict(tf.ones([1, 3])).print();
+       *
+       * const saveResults = await model.save('indexeddb://my-model-1');
+       *
+       * const loadedModel = await tf.loadLayersModel('indexeddb://my-model-1');
+       * console.log('Prediction from loaded model:');
+       * loadedModel.predict(tf.ones([1, 3])).print();
+       * ```
+       *
+       * Example 3. Load a model from user-selected files from HTML
+       * [file input
+       * elements](https://developer.mozilla.org/en-US/docs/Web/HTML/Element/input/file).
+       *
+       * ```js
+       * // Note: this code snippet will not work without the HTML elements in the
+       * //   page
+       * const jsonUpload = document.getElementById('json-upload');
+       * const weightsUpload = document.getElementById('weights-upload');
+       *
+       * const model = await tf.loadLayersModel(
+       *     tf.io.browserFiles([jsonUpload.files[0], weightsUpload.files[0]]));
+       * ```
+       *
+       * Example 4. Load a model from an HTTP server.
+       *
+       * ```js
+       * const model = await
+       *     tf.loadLayersModel('https://storage.googleapis.com/tfjs-models/tfjs/iris_v1/model.json');
+       * model.summary();
+       * ```
+       *
+       * @param pathOrIOHandler Can be either of the two formats
+       *   1. A string path to the `ModelAndWeightsConfig` JSON describing
+       *      the model in the canonical TensorFlow.js format. This path will be
+       *      interpreted as a relative HTTP path, to which `fetch` will be used to
+       *      request the model topology and weight manifest JSON.
+       *      The content of the JSON file is assumed to be a JSON object with the
+       *      following fields and values:
+       *      - 'modelTopology': A JSON object that can be either of:
+       *        1. a model architecture JSON consistent with the format of the return
+       *            value of `keras.Model.to_json()`
+       *        2. a full model JSON in the format of `keras.models.save_model()`.
+       *      - 'weightsManifest': A TensorFlow.js weights manifest.
+       *      See the Python converter function `save_model()` for more details.
+       *      It is also assumed that model weights can be accessed from relative
+       *      paths described by the `paths` fields in weights manifest.
+       *   2. An `tf.io.IOHandler` object that loads model artifacts with its `load`
+       *      method.
+       * @param options Optional configuration arguments for the model loading,
+       *   including:
+       *   - `strict`: Require that the provided weights exactly match those required
+       *     by the layers.  Default true.  Passing false means that both extra
+       *     weights and missing weights will be silently ignored.
+       *   - `onProgress`: A progress callback of the form:
+       *     `(fraction: number) => void`. This callback can be used to monitor the
+       *     model-loading process.
+       * @returns A `Promise` of `tf.LayersModel`, with the topology and weights
+       *     loaded.
+       */
+      async function loadLayersModelInternal(pathOrIOHandler, options) {
+        if (options == null) {
+          options = {};
+        }
+        if (typeof pathOrIOHandler === "string") {
+          const handlers = dist["io"].getLoadHandlers(pathOrIOHandler, options);
+          if (handlers.length === 0) {
+            // For backward compatibility: if no load handler can be found,
+            // assume it is a relative http path.
+            // TODO(cais): Reformat the args into a single `LoadOptions` once the core
+            // is refactored.
+            handlers.push(dist["io"].browserHTTPRequest(pathOrIOHandler, options));
+          } else if (handlers.length > 1) {
+            throw new ValueError(
+              `Found more than one (${handlers.length}) load handlers for ` +
+                `URL '${pathOrIOHandler}'`
+            );
+          }
+          pathOrIOHandler = handlers[0];
+        }
+        return loadLayersModelFromIOHandler(pathOrIOHandler, undefined, options);
+      }
+      /**
+       * Load a model and optionally its weights, using an IOHandler object.
+       *
+       * @param handler The instance of `IOHandler` to be used during the model
+       *   loading.
+       * @param customObjects Any optional custom objects to be used during model
+       *   loading.
+       * @param strict Whether the weight loading will be done in strict mode.
+       *   Default: `true`.
+       */
+      async function loadLayersModelFromIOHandler(handler, customObjects, options) {
+        if (options == null) {
+          options = {};
+        }
+        if (handler.load == null) {
+          throw new ValueError(
+            "Cannot proceed with model loading because the IOHandler provided " +
+              "does not have the `load` method implemented."
+          );
+        }
+        const artifacts = await handler.load();
+        let modelTopology = artifacts.modelTopology;
+        if (modelTopology["model_config"] != null) {
+          modelTopology = modelTopology["model_config"];
+        }
+        const strict = options.strict == null ? true : options.strict;
+        // If weights are provided and the weight-loading mode is strict, use
+        // fast weight initialization. This skips costly initializers such as
+        // 'orthogonal' and saves unnecessary computation in cases where
+        // the initialized weight values will immediately be overwritten by
+        // loaded weight values.
+        const fastWeightInit =
+          artifacts.weightData != null && artifacts.weightSpecs != null && strict;
+        const model = deserialize(
+          convertPythonicToTs(modelTopology),
+          customObjects,
+          fastWeightInit
+        );
+        const trainingConfig = artifacts.trainingConfig;
+        if (trainingConfig != null) {
+          model.loadTrainingConfig(trainingConfig);
+        }
+        if (artifacts.userDefinedMetadata != null) {
+          model.setUserDefinedMetadata(artifacts.userDefinedMetadata);
+        }
+        // If weightData is present, load the weights into the model.
+        if (artifacts.weightData != null) {
+          // Loading weights requires weightSpecs.
+          if (artifacts.weightSpecs == null) {
+            throw new ValueError(
+              "LayersModel artifacts contains weight data, but not weight specs. " +
+                "Therefore loading of weights cannot proceed."
+            );
+          }
+          const { modelWeights, optimizerWeights } = decodeModelAndOptimizerWeights(
+            artifacts.weightData,
+            artifacts.weightSpecs
+          );
+          model.loadWeights(modelWeights, strict);
+          if (model.optimizer != null && optimizerWeights.length > 0) {
+            await model.optimizer.setWeights(optimizerWeights);
+          }
+          // Dispose temporary weight values.
+          Object(dist["dispose"])(modelWeights);
+          Object(dist["dispose"])(optimizerWeights.map((w) => w.tensor));
+        }
+        return model;
+      }
+      function decodeModelAndOptimizerWeights(buffer, specs) {
+        const name2Tensor = dist["io"].decodeWeights(buffer, specs);
+        const modelWeights = {};
+        const optimizerWeights = [];
+        specs.forEach((spec) => {
+          if (spec.group === "optimizer") {
+            optimizerWeights.push({ name: spec.name, tensor: name2Tensor[spec.name] });
+          } else {
+            modelWeights[spec.name] = name2Tensor[spec.name];
+          }
+        });
+        return { modelWeights, optimizerWeights };
+      }
+      /**
+       * A model with a stack of layers, feeding linearly from one to the next.
+       *
+       * `tf.sequential` is a factory function that creates an instance of
+       * `tf.Sequential`.
+       *
+       * ```js
+       *  // Define a model for linear regression.
+       *  const model = tf.sequential();
+       *  model.add(tf.layers.dense({units: 1, inputShape: [1]}));
+       *
+       *  // Prepare the model for training: Specify the loss and the optimizer.
+       *  model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
+       *
+       *  // Generate some synthetic data for training.
+       *  const xs = tf.tensor2d([1, 2, 3, 4], [4, 1]);
+       *  const ys = tf.tensor2d([1, 3, 5, 7], [4, 1]);
+       *
+       *  // Train the model using the data then do inference on a data point the
+       *  // model hasn't seen:
+       *  await model.fit(xs, ys);
+       *  model.predict(tf.tensor2d([5], [1, 1])).print();
+       * ```
+       */
+      /** @doc {heading: 'Models', subheading: 'Classes'} */
+      class models_Sequential extends training_LayersModel {
+        constructor(args) {
+          super({ inputs: [], outputs: [] });
+          args = args || {};
+          this.trainable = true;
+          this.built = false;
+          // Set model name.
+          this.name = args.name != null ? args.name : getUid("sequential_");
+          // Add to the model any layers passed to the constructor.
+          if (args.layers != null) {
+            for (const layer of args.layers) {
+              this.add(layer);
+            }
+          }
+        }
+        // Helper function to Sequential.add  Throws if the new output shape will be
+        // invalid.
+        checkShape(layer) {
+          const shape = layer.inboundNodes[0].outputTensors[0].shape;
+          if (shape.some((x) => x < 0)) {
+            throw new ValueError(
+              "Negative dimension size caused by adding layer " +
+                `${layer.name} with input shape [` +
+                `${layer.inboundNodes[0].inputTensors[0].shape}]`
+            );
+          }
+        }
+        /**
+         * Adds a layer instance on top of the layer stack.
+         *
+         * ```js
+         *  const model = tf.sequential();
+         *  model.add(tf.layers.dense({units: 8, inputShape: [1]}));
+         *  model.add(tf.layers.dense({units: 4, activation: 'relu6'}));
+         *  model.add(tf.layers.dense({units: 1, activation: 'relu6'}));
+         *  // Note that the untrained model is random at this point.
+         *  model.predict(tf.randomNormal([10, 1])).print();
+         * ```
+         * @param layer Layer instance.
+         *
+         * @exception ValueError In case the `layer` argument does not know its
+         * input shape.
+         * @exception ValueError In case the `layer` argument has multiple output
+         *   tensors, or is already connected somewhere else (forbidden in
+         *   `Sequential` models).
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes'} */
+        add(layer) {
+          const isLayerModelInstance =
+            layer instanceof models_Sequential || layer instanceof training_LayersModel;
+          let modelLayer;
+          if (isLayerModelInstance) {
+            modelLayer = layer;
+            if (modelLayer.outputs.length !== 1) {
+              throw new ValueError(
+                "All layers in a Sequential model " +
+                  "should have a single output tensor. " +
+                  "For multi-output layers, " +
+                  "use the functional API."
+              );
+            }
+            if (modelLayer.inputs.length !== 1) {
+              throw new ValueError(
+                "All layers in a Sequential model " +
+                  "should have a single input tensor. " +
+                  "For multi-input layers, " +
+                  "use the functional API."
+              );
+            }
+          }
+          if (this.outputs.length === 0) {
+            // first layer in model: check that it is an input layer
+            if (layer.inboundNodes.length === 0) {
+              // create an input layer
+              if (layer.batchInputShape == null) {
+                throw new ValueError(
+                  "The first layer in a Sequential model must " +
+                    "get an `inputShape` or `batchInputShape` argument."
+                );
+              }
+              // Instantiate the input layer.
+              const x = Input({
+                batchShape: layer.batchInputShape,
+                dtype: layer.dtype,
+                name: layer.name + "_input",
+              });
+              // This will build the current layer and create the node connecting
+              // the current layer to the input layer we just created.
+              layer.apply(x);
+            }
+            if (isLayerModelInstance) {
+              this.outputs = modelLayer.outputs;
+              this.inputs = modelLayer.inputs;
+            } else {
+              if (layer.inboundNodes.length !== 1) {
+                throw new ValueError(
+                  "A layer added to a Sequential model must not already be " +
+                    `connected somewhere else. LayersModel received layer ${layer.name} ` +
+                    `which has ${layer.inboundNodes.length} pre-existing inbound ` +
+                    "connections."
+                );
+              }
+              if (layer.inboundNodes[0].outputTensors.length !== 1) {
+                throw new ValueError(
+                  "All layers in a Sequential model " +
+                    "should have a single output tensor. " +
+                    "For multi-output layers, " +
+                    "use the functional API."
+                );
+              }
+              this.checkShape(layer);
+              this.outputs = [layer.inboundNodes[0].outputTensors[0]];
+              this.inputs = getSourceInputs(this.outputs[0]);
+            }
+            this.inboundNodes = [];
+            // We create an input node, which we will keep updated
+            // as we add more layers.
+            // (This call has side effects.)
+            // tslint:disable-next-line:no-unused-expression
+            new Node({
+              outboundLayer: this,
+              inboundLayers: [],
+              nodeIndices: [],
+              tensorIndices: [],
+              inputTensors: this.inputs,
+              outputTensors: this.outputs,
+              // no model-level masking for now
+              inputMasks: pyListRepeat(null, this.inputs.length),
+              outputMasks: [null],
+              inputShapes: this.inputs.map((x) => x.shape),
+              outputShapes: this.outputs[0].shape,
+            });
+          } else {
+            const outputTensor = layer.apply(this.outputs[0]);
+            if (Array.isArray(outputTensor)) {
+              throw new TypeError(
+                "All layers in a Sequential model " +
+                  "should have a single output tensor. " +
+                  "For multi-output layers, " +
+                  "use the functional API."
+              );
+            }
+            this.checkShape(layer);
+            this.outputs = [outputTensor];
+            // update self.inbound_nodes
+            this.inboundNodes[0].outputTensors = this.outputs;
+            this.inboundNodes[0].outputShapes = [this.outputs[0].shape];
+          }
+          this.layers.push(layer);
+          this.built = false;
+        }
+        /**
+         * Removes the last layer in the model.
+         *
+         * @exception TypeError if there are no layers in the model.
+         */
+        pop() {
+          if (this.layers.length === 0) {
+            throw new TypeError("There are no layers in the model.");
+          }
+          this.layers.pop();
+          if (this.layers.length === 0) {
+            this.outputs = [];
+            this.inboundNodes = [];
+            this.outboundNodes = [];
+          } else {
+            const lastLayerIndex = this.layers.length - 1;
+            this.layers[lastLayerIndex].outboundNodes = [];
+            this.outputs = [this.layers[lastLayerIndex].output];
+            // update self.inbound_nodes
+            this.inboundNodes[0].outputTensors = this.outputs;
+            this.inboundNodes[0].outputShapes = [this.outputs[0].shape];
+          }
+        }
+        call(inputs, kwargs) {
+          if (this.model == null) {
+            this.build();
+          }
+          return this.model.call(inputs, kwargs);
+        }
+        build(inputShape) {
+          // Call `getExactlyOneShape` without using its return value,
+          // to verify that exactly one input shape is provided.
+          getExactlyOneShape(inputShape);
+          if (this.inputs.length === 0 || this.outputs.length === 0) {
+            throw new TypeError(
+              "Sequential model cannot be built: model is empty." + " Add some layers first."
+            );
+          }
+          // actually create the model
+          this.model = new training_LayersModel({
+            inputs: this.inputs,
+            outputs: this.outputs[0],
+            name: this.name + "_model",
+          });
+          this.model.trainable = this.trainable;
+          // mirror model attributes
+          this.supportsMasking = this.model.supportsMasking;
+          // TODO(michaelterry): Add caches
+          this.inputLayers = this.model.inputLayers;
+          this.inputLayersNodeIndices = this.model.inputLayersNodeIndices;
+          this.inputLayersTensorIndices = this.model.inputLayersTensorIndices;
+          this.outputLayers = this.model.outputLayers;
+          this.outputLayersNodeIndices = this.model.outputLayersNodeIndices;
+          this.outputLayersTensorIndices = this.model.outputLayersTensorIndices;
+          this.nodesByDepth = this.model.nodesByDepth;
+          this.containerNodes = this.model.containerNodes;
+          this.outputNames = this.model.outputNames;
+          this.inputNames = this.model.inputNames;
+          // TODO(michaelterry): Add feedInputNames, feedInputs, if needed.
+          // TODO(michaelterry): Add callbackModel if needed.
+          this.built = true;
+        }
+        countParams() {
+          if (!this.built) {
+            this.build();
+          }
+          return super.countParams();
+        }
+        /**
+         * Print a text summary of the Sequential model's layers.
+         *
+         * The summary includes
+         * - Name and type of all layers that comprise the model.
+         * - Output shape(s) of the layers
+         * - Number of weight parameters of each layer
+         * - The total number of trainable and non-trainable parameters of the
+         * model.
+         *
+         * ```js
+         * const model = tf.sequential();
+         * model.add(
+         *     tf.layers.dense({units: 100, inputShape: [10], activation: 'relu'}));
+         * model.add(tf.layers.dense({units: 1, activation: 'sigmoid'}));
+         *
+         * model.summary();
+         * ```
+         *
+         * @param lineLength Custom line length, in number of characters.
+         * @param positions Custom widths of each of the columns, as either
+         *   fractions of `lineLength` (e.g., `[0.5, 0.75, 1]`) or absolute number
+         *   of characters (e.g., `[30, 50, 65]`). Each number corresponds to
+         *   right-most (i.e., ending) position of a column.
+         * @param printFn Custom print function. Can be used to replace the default
+         *   `console.log`. For example, you can use `x => {}` to mute the printed
+         *   messages in the console.
+         */
+        /** @doc {heading: 'Models', subheading: 'Classes'} */
+        summary(lineLength, positions, printFn = console.log) {
+          if (!this.built) {
+            this.build();
+          }
+          super.summary(lineLength, positions, printFn);
+        }
+        /**
+         * Sets the weights of the model.
+         *
+         * @param weights Should be a list of Tensors with shapes and types matching
+         *   the output of `model.getWeights()`.
+         */
+        setWeights(weights) {
+          if (this.model == null) {
+            this.build();
+          }
+          this.model.setWeights(weights);
+        }
+        /**
+         * Returns the loss value & metrics values for the model in test mode.
+         *
+         * Loss and metrics are specified during `compile()`, which needs to happen
+         * before calls to `evaluate()`.
+         *
+         * Computation is done in batches.
+         *
+         * ```js
+         * const model = tf.sequential({
+         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
+         * });
+         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
+         * const result = model.evaluate(tf.ones([8, 10]), tf.ones([8, 1]), {
+         *   batchSize: 4,
+         * });
+         * result.print();
+         * ```
+         *
+         * @param x `tf.Tensor` of test data, or an `Array` of `tf.Tensor`s if the
+         * model has multiple inputs.
+         * @param y `tf.Tensor` of target data, or an `Array` of `tf.Tensor`s if the
+         * model has multiple outputs.
+         * @param args A `ModelEvaluateConfig`, containing optional fields.
+         *
+         * @return `Scalar` test loss (if the model has a single output and no
+         *   metrics) or `Array` of `Scalar`s (if the model has multiple outputs
+         *   and/or metrics). The attribute `model.metricsNames`
+         *   will give you the display labels for the scalar outputs.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        evaluate(x, y, args = {}) {
+          if (!this.built) {
+            throw new RuntimeError("The model needs to be compiled before being used.");
+          }
+          return this.model.evaluate(x, y, args);
+        }
+        // TODO(cais): Add code snippet below once real dataset objects are
+        //   available.
+        /**
+         * Evaluate model using a dataset object.
+         *
+         * Note: Unlike `evaluate()`, this method is asynchronous (`async`);
+         *
+         * @param dataset A dataset object. Its `iterator()` method is expected
+         *   to generate a dataset iterator object, the `next()` method of which
+         *   is expected to produce data batches for evaluation. The return value
+         *   of the `next()` call ought to contain a boolean `done` field and a
+         *   `value` field. The `value` field is expected to be an array of two
+         *   `tf.Tensor`s or an array of two nested `tf.Tensor` structures. The former
+         *   case is for models with exactly one input and one output (e.g..
+         *   a sequential model). The latter case is for models with multiple
+         *   inputs and/or multiple outputs. Of the two items in the array, the
+         *   first is the input feature(s) and the second is the output target(s).
+         * @param args A configuration object for the dataset-based evaluation.
+         * @returns Loss and metric values as an Array of `Scalar` objects.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        async evaluateDataset(dataset, args) {
+          if (!this.built) {
+            throw new RuntimeError("The model needs to be compiled before being used.");
+          }
+          return this.model.evaluateDataset(dataset, args);
+        }
+        /**
+         * Generates output predictions for the input samples.
+         *
+         * Computation is done in batches.
+         *
+         * Note: the "step" mode of predict() is currently not supported.
+         *   This is because the TensorFow.js core backend is imperative only.
+         *
+         * ```js
+         * const model = tf.sequential({
+         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
+         * });
+         * model.predict(tf.ones([2, 10])).print();
+         * ```
+         *
+         * @param x The input data, as a Tensor, or an `Array` of `tf.Tensor`s if
+         *   the model has multiple inputs.
+         * @param conifg A `ModelPredictConfig` object containing optional fields.
+         *
+         * @return `tf.Tensor`(s) of predictions.
+         *
+         * @exception ValueError In case of mismatch between the provided input data
+         *   and the model's expectations, or in case a stateful model receives a
+         *   number of samples that is not a multiple of the batch size.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        predict(x, args = {}) {
+          if (this.model == null) {
+            this.build();
+          }
+          return this.model.predict(x, args);
+        }
+        /**
+         * Returns predictions for a single batch of samples.
+         *
+         * @param x: Input samples, as a Tensor, or list of Tensors (if the model
+         *   has multiple inputs).
+         * @return Tensor(s) of predictions
+         */
+        predictOnBatch(x) {
+          if (this.model == null) {
+            this.build();
+          }
+          return this.model.predictOnBatch(x);
+        }
+        /**
+         * See `LayersModel.compile`.
+         *
+         * @param args
+         */
+        compile(args) {
+          this.build();
+          this.model.compile(args);
+          this.optimizer_ = this.model.optimizer;
+          // tslint:disable-next-line:no-any
+          this.isOptimizerOwned = this.model.isOptimizerOwned;
+          this.loss = this.model.loss;
+          this.metrics = this.model.metrics;
+          // TODO(cais): Add this.lossWeights, this.sampleWeightMode,
+          //   this.weightedMetrics, this.targets.
+          this.metricsTensors = this.model.metricsTensors;
+          this.metricsNames = this.model.metricsNames;
+          // TODO(cais): Add sampleWeights.
+        }
+        get optimizer() {
+          return this.model == null ? undefined : this.model.optimizer;
+        }
+        set optimizer(optimizer) {
+          this.model.optimizer = optimizer;
+        }
+        /**
+         * Trains the model for a fixed number of epochs (iterations on a dataset).
+         *
+         * ```js
+         * const model = tf.sequential({
+         *   layers: [tf.layers.dense({units: 1, inputShape: [10]})]
+         * });
+         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
+         * const history = await model.fit(tf.ones([8, 10]), tf.ones([8, 1]), {
+         *   batchSize: 4,
+         *   epochs: 3
+         * });
+         * console.log(history.history.loss[0]);
+         * ```
+         *
+         * @param x `tf.Tensor` of training data, or an array of `tf.Tensor`s if the
+         * model has multiple inputs. If all inputs in the model are named, you can
+         * also pass a dictionary mapping input names to `tf.Tensor`s.
+         * @param y `tf.Tensor` of target (label) data, or an array of `tf.Tensor`s if
+         * the model has multiple outputs. If all outputs in the model are named, you
+         *  can also pass a dictionary mapping output names to `tf.Tensor`s.
+         * @param args  A `ModelFitConfig`, containing optional fields.
+         *
+         * @return A `History` instance. Its `history` attribute contains all
+         *   information collected during training.
+         *
+         * @exception ValueError In case of mismatch between the provided input data
+         *   and what the model expects.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        async fit(x, y, args = {}) {
+          if (!this.built) {
+            throw new RuntimeError("The model needs to be compiled before " + "being used.");
+          }
+          return this.model.fit(x, y, args);
+        }
+        /**
+         * Trains the model using a dataset object.
+         *
+         * ```js
+         * const xArray = [
+         *   [1, 1, 1, 1, 1, 1, 1, 1, 1],
+         *   [1, 1, 1, 1, 1, 1, 1, 1, 1],
+         *   [1, 1, 1, 1, 1, 1, 1, 1, 1],
+         *   [1, 1, 1, 1, 1, 1, 1, 1, 1],
+         * ];
+         * const yArray = [1, 1, 1, 1];
+         * // Create a dataset from the JavaScript array.
+         * const xDataset = tf.data.array(xArray);
+         * const yDataset = tf.data.array(yArray);
+         * // Zip combines the `x` and `y` Datasets into a single Dataset, the
+         * // iterator of which will return an object containing of two tensors,
+         * // corresponding to `x` and `y`.  The call to `batch(4)` will bundle
+         * // four such samples into a single object, with the same keys now pointing
+         * // to tensors that hold 4 examples, organized along the batch dimension.
+         * // The call to `shuffle(4)` causes each iteration through the dataset to
+         * // happen in a different order.  The size of the shuffle window is 4.
+         * const xyDataset = tf.data.zip({xs: xDataset, ys: yDataset})
+         *     .batch(4)
+         *     .shuffle(4);
+         * const model = tf.sequential({
+         *   layers: [tf.layers.dense({units: 1, inputShape: [9]})]
+         * });
+         * model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});
+         * const history = await model.fitDataset(xyDataset, {
+         *   epochs: 4,
+         *   callbacks: {onEpochEnd: (epoch, logs) => console.log(logs.loss)}
+         * });
+         * ```
+         *
+         * @param dataset A dataset object. Its `iterator()` method is expected to
+         *   generate a dataset iterator object, the `next()` method of which is
+         *   expected to produce data batches for evaluation. The return value of the
+         *   `next()` call ought to contain a boolean `done` field and a `value`
+         *   field.
+         *
+         *   The `value` field is expected to be an object of with fields
+         *   `xs` and `ys`, which point to the feature tensor and the target tensor,
+         *   respectively. This case is for models with exactly one input and one
+         *   output (e.g.. a sequential model). For example:
+         *   ```js
+         *   {value: {xs: xsTensor, ys: ysTensor}, done: false}
+         *   ```
+         *
+         *   If the model has multiple inputs, the `xs` field of `value` should
+         *   be an object mapping input names to their respective feature tensors.
+         *   For example:
+         *   ```js
+         *   {
+         *     value: {
+         *       xs: {
+         *         input_1: xsTensor1,
+         *         input_2: xsTensor2
+         *       },
+         *       ys: ysTensor
+         *     },
+         *     done: false
+         *   }
+         *   ```
+         *   If the model has multiple outputs, the `ys` field of `value` should
+         *   be an object mapping output names to their respective target tensors.
+         *   For example:
+         *   ```js
+         *   {
+         *     value: {
+         *       xs: xsTensor,
+         *       ys: {
+         *         output_1: ysTensor1,
+         *         output_2: ysTensor2
+         *       },
+         *     },
+         *     done: false
+         *   }
+         *   ```
+         * @param args A `ModelFitDatasetArgs`, containing optional fields.
+         *
+         * @return A `History` instance. Its `history` attribute contains all
+         *   information collected during training.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes', ignoreCI: true}
+         */
+        async fitDataset(dataset, args) {
+          if (!this.built) {
+            throw new RuntimeError("The model needs to be compiled before " + "being used.");
+          }
+          return this.model.fitDataset(dataset, args);
+        }
+        /**
+         * Runs a single gradient update on a single batch of data.
+         *
+         * This method differs from `fit()` and `fitDataset()` in the following
+         * regards:
+         *   - It operates on exactly one batch of data.
+         *   - It returns only the loss and matric values, instead of
+         *     returning the batch-by-batch loss and metric values.
+         *   - It doesn't support fine-grained options such as verbosity and
+         *     callbacks.
+         *
+         * @param x Input data. It could be one of the following:
+         *   - A `tf.Tensor`, or an Array of `tf.Tensor`s (in case the model has
+         *     multiple inputs).
+         *   - An Object mapping input names to corresponding `tf.Tensor` (if the
+         *     model has named inputs).
+         * @param y Target darta. It could be either a `tf.Tensor` a multiple
+         *   `tf.Tensor`s. It should be consistent with `x`.
+         * @returns Training loss or losses (in case the model has
+         *   multiple outputs), along with metrics (if any), as numbers.
+         */
+        /**
+         * @doc {heading: 'Models', subheading: 'Classes'}
+         */
+        async trainOnBatch(x, y) {
+          return this.model.trainOnBatch(x, y);
+        }
+        /* See parent class for JsDoc */
+        /** @nocollapse */
+        static fromConfig(cls, config, customObjects = {}, fastWeightInit = false) {
+          let configArray;
+          let extraModelConfig = {};
+          if (config instanceof Array) {
+            if (!(config[0].className != null) || config[0]["className"] === "Merge") {
+              throw new ValueError("Legacy serialization format not supported yet.");
+            }
+            configArray = config;
+          } else {
+            dist["util"].assert(
+              config["layers"] != null,
+              () =>
+                `When the config data for a Sequential model is not an Array, ` +
+                `it must be an Object that contains the 'layers' field.`
+            );
+            configArray = config["layers"];
+            delete config["layers"];
+            extraModelConfig = config;
+          }
+          const model = new cls(extraModelConfig);
+          if (!(model instanceof models_Sequential)) {
+            throw new NotImplementedError(
+              `Sequential.fromConfig called on non-Sequential input: ${model}`
+            );
+          }
+          for (const conf of configArray) {
+            const customObjects = undefined;
+            const layer = deserialize(conf, customObjects, fastWeightInit);
+            if (fastWeightInit) {
+              layer.setFastWeightInitDuringBuild(true);
+            }
+            model.add(layer);
+          }
+          return model;
+        }
+        /**
+         * Setter used for force stopping of LayersModel.fit() (i.e., training).
+         *
+         * Example:
+         *
+         * ```js
+         * const model = tf.sequential();
+         * model.add(tf.layers.dense({units: 1, inputShape: [10]}));
+         * model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
+         * const xs = tf.ones([8, 10]);
+         * const ys = tf.zeros([8, 1]);
+         *
+         * const history = await model.fit(xs, ys, {
+         *   epochs: 10,
+         *   callbacks: {
+         *     onEpochEnd: async (epoch, logs) => {
+         *       if (epoch === 2) {
+         *         model.stopTraining = true;
+         *       }
+         *     }
+         *   }
+         * });
+         *
+         * // There should be only 3 values in the loss array, instead of 10 values,
+         * // due to the stopping after 3 epochs.
+         * console.log(history.history.loss);
+         * ```
+         */
+        set stopTraining(stop) {
+          // TODO(cais): When refactoring to remove the composition pattern happens,
+          // remove this method overriding.
+          if (this.model == null) {
+            throw new ValueError(
+              "Cannot set the stopTraining property of a sequential model before " +
+                "it is compiled."
+            );
+          }
+          this.model.stopTraining = stop;
+        }
+        get stopTraining() {
+          if (this.model == null) {
+            throw new ValueError(
+              "Cannot get the stopTraining property of a sequential model before " +
+                "it is compiled."
+            );
+          }
+          return this.model.stopTraining;
+        }
+        // TODO(cais): Override get trainableWeights() here
+        // tslint:disable-next-line:no-any
+        getConfig() {
+          // NOTE(cais): We override the return type of getConfig() to `any` here,
+          //   because the `Sequential` class is a special case among `Container`
+          //   subtypes in that its getConfig() method returns an Array (not a
+          //   dict).
+          const layers = [];
+          for (const layer of this.layers) {
+            const dict = {};
+            dict["className"] = layer.getClassName();
+            dict["config"] = layer.getConfig();
+            layers.push(dict);
+          }
+          return { name: this.name, layers };
+        }
+      }
+      /** @nocollapse */
+      models_Sequential.className = "Sequential";
+      dist["serialization"].registerClass(models_Sequential);
+      //# sourceMappingURL=models.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      // TODO(cais): Add doc string to all the public static functions in this
+      //   class; include exectuable JavaScript code snippets where applicable
+      //   (b/74074458).
+      // LayersModel and related factory methods.
+      /**
+       * A model is a data structure that consists of `Layers` and defines inputs
+       * and outputs.
+       *
+       * The key difference between `tf.model` and `tf.sequential` is that
+       * `tf.model` is more generic, supporting an arbitrary graph (without
+       * cycles) of layers. `tf.sequential` is less generic and supports only a linear
+       * stack of layers.
+       *
+       * When creating a `tf.LayersModel`, specify its input(s) and output(s). Layers
+       * are used to wire input(s) to output(s).
+       *
+       * For example, the following code snippet defines a model consisting of
+       * two `dense` layers, with 10 and 4 units, respectively.
+       *
+       * ```js
+       * // Define input, which has a size of 5 (not including batch dimension).
+       * const input = tf.input({shape: [5]});
+       *
+       * // First dense layer uses relu activation.
+       * const denseLayer1 = tf.layers.dense({units: 10, activation: 'relu'});
+       * // Second dense layer uses softmax activation.
+       * const denseLayer2 = tf.layers.dense({units: 4, activation: 'softmax'});
+       *
+       * // Obtain the output symbolic tensor by applying the layers on the input.
+       * const output = denseLayer2.apply(denseLayer1.apply(input));
+       *
+       * // Create the model based on the inputs.
+       * const model = tf.model({inputs: input, outputs: output});
+       *
+       * // The model can be used for training, evaluation and prediction.
+       * // For example, the following line runs prediction with the model on
+       * // some fake data.
+       * model.predict(tf.ones([2, 5])).print();
+       * ```
+       * See also:
+       *   `tf.sequential`, `tf.loadLayersModel`.
+       */
+      /**
+       * @doc {heading: 'Models', subheading: 'Creation'}
+       */
+      function exports_model(args) {
+        return new training_LayersModel(args);
+      }
+      /**
+       * Creates a `tf.Sequential` model.  A sequential model is any model where the
+       * outputs of one layer are the inputs to the next layer, i.e. the model
+       * topology is a simple 'stack' of layers, with no branching or skipping.
+       *
+       * This means that the first layer passed to a `tf.Sequential` model should have
+       * a defined input shape. What that means is that it should have received an
+       * `inputShape` or `batchInputShape` argument, or for some type of layers
+       * (recurrent, Dense...) an `inputDim` argument.
+       *
+       * The key difference between `tf.model` and `tf.sequential` is that
+       * `tf.sequential` is less generic, supporting only a linear stack of layers.
+       * `tf.model` is more generic and supports an arbitrary graph (without
+       * cycles) of layers.
+       *
+       * Examples:
+       *
+       * ```js
+       * const model = tf.sequential();
+       *
+       * // First layer must have an input shape defined.
+       * model.add(tf.layers.dense({units: 32, inputShape: [50]}));
+       * // Afterwards, TF.js does automatic shape inference.
+       * model.add(tf.layers.dense({units: 4}));
+       *
+       * // Inspect the inferred shape of the model's output, which equals
+       * // `[null, 4]`. The 1st dimension is the undetermined batch dimension; the
+       * // 2nd is the output size of the model's last layer.
+       * console.log(JSON.stringify(model.outputs[0].shape));
+       * ```
+       *
+       * It is also possible to specify a batch size (with potentially undetermined
+       * batch dimension, denoted by "null") for the first layer using the
+       * `batchInputShape` key. The following example is equivalent to the above:
+       *
+       * ```js
+       * const model = tf.sequential();
+       *
+       * // First layer must have a defined input shape
+       * model.add(tf.layers.dense({units: 32, batchInputShape: [null, 50]}));
+       * // Afterwards, TF.js does automatic shape inference.
+       * model.add(tf.layers.dense({units: 4}));
+       *
+       * // Inspect the inferred shape of the model's output.
+       * console.log(JSON.stringify(model.outputs[0].shape));
+       * ```
+       *
+       * You can also use an `Array` of already-constructed `Layer`s to create
+       * a `tf.Sequential` model:
+       *
+       * ```js
+       * const model = tf.sequential({
+       *   layers: [tf.layers.dense({units: 32, inputShape: [50]}),
+       *            tf.layers.dense({units: 4})]
+       * });
+       * console.log(JSON.stringify(model.outputs[0].shape));
+       * ```
+       */
+      /**
+       * @doc {heading: 'Models', subheading: 'Creation'}
+       */
+      function sequential(config) {
+        return new models_Sequential(config);
+      }
+      /**
+       * Load a model composed of Layer objects, including its topology and optionally
+       * weights. See the Tutorial named "How to import a Keras Model" for usage
+       * examples.
+       *
+       * This method is applicable to:
+       *
+       * 1. Models created with the `tf.layers.*`, `tf.sequential`, and
+       * `tf.model` APIs of TensorFlow.js and later saved with the
+       * `tf.LayersModel.save` method.
+       * 2. Models converted from Keras or TensorFlow tf.keras using the
+       * [tensorflowjs_converter](https://github.com/tensorflow/tfjs/tree/master/tfjs-converter).
+       *
+       * This mode is *not* applicable to TensorFlow `SavedModel`s or their converted
+       * forms. For those models, use `tf.loadGraphModel`.
+       *
+       * Example 1. Load a model from an HTTP server.
+       *
+       * ```js
+       * const model = await tf.loadLayersModel(
+       *     'https://storage.googleapis.com/tfjs-models/tfjs/iris_v1/model.json');
+       * model.summary();
+       * ```
+       *
+       * Example 2: Save `model`'s topology and weights to browser [local
+       * storage](https://developer.mozilla.org/en-US/docs/Web/API/Window/localStorage);
+       * then load it back.
+       *
+       * ```js
+       * const model = tf.sequential(
+       *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
+       * console.log('Prediction from original model:');
+       * model.predict(tf.ones([1, 3])).print();
+       *
+       * const saveResults = await model.save('localstorage://my-model-1');
+       *
+       * const loadedModel = await tf.loadLayersModel('localstorage://my-model-1');
+       * console.log('Prediction from loaded model:');
+       * loadedModel.predict(tf.ones([1, 3])).print();
+       * ```
+       *
+       * Example 3. Saving `model`'s topology and weights to browser
+       * [IndexedDB](https://developer.mozilla.org/en-US/docs/Web/API/IndexedDB_API);
+       * then load it back.
+       *
+       * ```js
+       * const model = tf.sequential(
+       *     {layers: [tf.layers.dense({units: 1, inputShape: [3]})]});
+       * console.log('Prediction from original model:');
+       * model.predict(tf.ones([1, 3])).print();
+       *
+       * const saveResults = await model.save('indexeddb://my-model-1');
+       *
+       * const loadedModel = await tf.loadLayersModel('indexeddb://my-model-1');
+       * console.log('Prediction from loaded model:');
+       * loadedModel.predict(tf.ones([1, 3])).print();
+       * ```
+       *
+       * Example 4. Load a model from user-selected files from HTML
+       * [file input
+       * elements](https://developer.mozilla.org/en-US/docs/Web/HTML/Element/input/file).
+       *
+       * ```js
+       * // Note: this code snippet will not work without the HTML elements in the
+       * //   page
+       * const jsonUpload = document.getElementById('json-upload');
+       * const weightsUpload = document.getElementById('weights-upload');
+       *
+       * const model = await tf.loadLayersModel(
+       *     tf.io.browserFiles([jsonUpload.files[0], weightsUpload.files[0]]));
+       * ```
+       *
+       * @param pathOrIOHandler Can be either of the two formats
+       *   1. A string path to the `ModelAndWeightsConfig` JSON describing
+       *      the model in the canonical TensorFlow.js format. For file://
+       *      (tfjs-node-only), http:// and https:// schemas, the path can be
+       *      either absolute or relative.
+       *   2. An `tf.io.IOHandler` object that loads model artifacts with its `load`
+       *      method.
+       * @param options Optional configuration arguments for the model loading,
+       *   including:
+       *   - `strict`: Require that the provided weights exactly match those required
+       *     by the layers.  Default true.  Passing false means that both extra
+       *     weights and missing weights will be silently ignored.
+       *   - `onProgress`: A function of the signature `(fraction: number) => void',
+       *     that can be used as the progress callback for the model loading.
+       * @returns A `Promise` of `tf.LayersModel`, with the topology and weights
+       *     loaded.
+       */
+      /** @doc {heading: 'Models', subheading: 'Loading'} */
+      function loadLayersModel(pathOrIOHandler, options) {
+        if (options == null) {
+          options = {};
+        }
+        return loadLayersModelInternal(pathOrIOHandler, options);
+      }
+      /**
+       * Used to instantiate an input to a model as a `tf.SymbolicTensor`.
+       *
+       * Users should call the `input` factory function for
+       * consistency with other generator functions.
+       *
+       * Example:
+       *
+       * ```js
+       * // Defines a simple logistic regression model with 32 dimensional input
+       * // and 3 dimensional output.
+       * const x = tf.input({shape: [32]});
+       * const y = tf.layers.dense({units: 3, activation: 'softmax'}).apply(x);
+       * const model = tf.model({inputs: x, outputs: y});
+       * model.predict(tf.ones([2, 32])).print();
+       * ```
+       *
+       * Note: `input` is only necessary when using `model`. When using
+       * `sequential`, specify `inputShape` for the first layer or use `inputLayer`
+       * as the first layer.
+       */
+      /** @doc {heading: 'Models', subheading: 'Inputs'} */
+      function exports_input(config) {
+        return Input(config);
+      }
+      function registerCallbackConstructor(verbosityLevel, callbackConstructor) {
+        base_callbacks_CallbackConstructorRegistry.registerCallbackConstructor(
+          verbosityLevel,
+          callbackConstructor
+        );
+      }
+      //# sourceMappingURL=exports.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/activations.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      // Layer activation functions
+
+      /**
+       * Base class for Activations.
+       *
+       * Special note: due to cross-language compatibility reasons, the
+       * static readonly className field in this family of classes must be set to
+       * the initialLowerCamelCase name of the activation.
+       */
+      class activations_Activation extends dist["serialization"].Serializable {
+        getConfig() {
+          return {};
+        }
+      }
+      /**
+       * Exponential linear unit (ELU).
+       * Reference: https://arxiv.org/abs/1511.07289
+       */
+      class activations_Elu extends activations_Activation {
+        /**
+         * Calculate the activation function.
+         *
+         * @param x: Input.
+         * @param alpha: Scaling factor the negative section.
+         * @return Output of the ELU activation.
+         */
+        apply(x, alpha = 1) {
+          return elu(x, alpha);
+        }
+      }
+      /** @nocollapse */
+      activations_Elu.className = "elu";
+      dist["serialization"].registerClass(activations_Elu);
+      /**
+       * Scaled Exponential Linear Unit. (Klambauer et al., 2017).
+       * Reference: Self-Normalizing Neural Networks, https://arxiv.org/abs/1706.02515
+       * Notes:
+       *   - To be used together with the initialization "lecunNormal".
+       *   - To be used together with the dropout variant "AlphaDropout".
+       */
+      class activations_Selu extends activations_Activation {
+        apply(x) {
+          return dist["selu"](x);
+        }
+      }
+      /** @nocollapse */
+      activations_Selu.className = "selu";
+      dist["serialization"].registerClass(activations_Selu);
+      /**
+       *  Rectified linear unit
+       */
+      class activations_Relu extends activations_Activation {
+        apply(x) {
+          return dist["relu"](x);
+        }
+      }
+      /** @nocollapse */
+      activations_Relu.className = "relu";
+      dist["serialization"].registerClass(activations_Relu);
+      /**
+       * Rectified linear unit activation maxing out at 6.0.
+       */
+      class activations_Relu6 extends activations_Activation {
+        apply(x) {
+          return Object(dist["tidy"])(() => dist["minimum"](6.0, dist["relu"](x)));
+        }
+      }
+      /** @nocollapse */
+      activations_Relu6.className = "relu6";
+      dist["serialization"].registerClass(activations_Relu6);
+      //* Linear activation (no-op) */
+      class Linear extends activations_Activation {
+        apply(x) {
+          return x;
+        }
+      }
+      /** @nocollapse */
+      Linear.className = "linear";
+      dist["serialization"].registerClass(Linear);
+      /**
+       * Sigmoid activation function.
+       */
+      class activations_Sigmoid extends activations_Activation {
+        apply(x) {
+          return dist["sigmoid"](x);
+        }
+      }
+      /** @nocollapse */
+      activations_Sigmoid.className = "sigmoid";
+      dist["serialization"].registerClass(activations_Sigmoid);
+      /**
+       * Segment-wise linear approximation of sigmoid.
+       */
+      class activations_HardSigmoid extends activations_Activation {
+        apply(x) {
+          return hardSigmoid(x);
+        }
+      }
+      /** @nocollapse */
+      activations_HardSigmoid.className = "hardSigmoid";
+      dist["serialization"].registerClass(activations_HardSigmoid);
+      /**
+       * Softplus activation function.
+       */
+      class activations_Softplus extends activations_Activation {
+        apply(x) {
+          return dist["softplus"](x);
+        }
+      }
+      /** @nocollapse */
+      activations_Softplus.className = "softplus";
+      dist["serialization"].registerClass(activations_Softplus);
+      /**
+       * Softsign activation function.
+       */
+      class activations_Softsign extends activations_Activation {
+        apply(x) {
+          return softsign(x);
+        }
+      }
+      /** @nocollapse */
+      activations_Softsign.className = "softsign";
+      dist["serialization"].registerClass(activations_Softsign);
+      /**
+       * Hyperbolic tangent function.
+       */
+      class activations_Tanh extends activations_Activation {
+        apply(x) {
+          return dist["tanh"](x);
+        }
+      }
+      /** @nocollapse */
+      activations_Tanh.className = "tanh";
+      dist["serialization"].registerClass(activations_Tanh);
+      /**
+       * Softmax activation function
+       */
+      class activations_Softmax extends activations_Activation {
+        /**
+         * Calculate the activation function.
+         *
+         * @param x Tensor.
+         * @param axis Integer, axis along which the softmax normalization is applied.
+         * Invalid if < 2, as softmax across 1 (the batch dimension) is assumed to be
+         * an error.
+         *
+         * @returns a Tensor of the same shape as x
+         *
+         * @throws ValueError: In case `dim(x) < 2`.
+         */
+        apply(x, axis = -1) {
+          return dist["softmax"](x, axis);
+        }
+      }
+      /** @nocollapse */
+      activations_Softmax.className = "softmax";
+      dist["serialization"].registerClass(activations_Softmax);
+      /**
+       * Log softmax activation function
+       */
+      class activations_LogSoftmax extends activations_Activation {
+        /**
+         * Calculate the activation function of log softmax:
+         * log( exp(x_i) / sum(exp(x)) )
+         *
+         * @param x Tensor.
+         * @param axis Integer, axis along which the softmax normalization is applied.
+         * Invalid if < 2, as softmax across 1 (the batch dimension) is assumed to be
+         * an error.
+         *
+         * @returns a Tensor of the same shape as x
+         *
+         * @throws ValueError: In case `dim(x) < 2`.
+         */
+        apply(x, axis = -1) {
+          return dist["logSoftmax"](x, axis);
+        }
+      }
+      /** @nocollapse */
+      activations_LogSoftmax.className = "logSoftmax";
+      dist["serialization"].registerClass(activations_LogSoftmax);
+      function serializeActivation(activation) {
+        return activation.getClassName();
+      }
+      function deserializeActivation(config, customObjects = {}) {
+        return deserializeKerasObject(
+          config,
+          dist["serialization"].SerializationMap.getMap().classNameMap,
+          customObjects,
+          "activation"
+        );
+      }
+      function getActivation(identifier) {
+        if (identifier == null) {
+          const config = {};
+          config["className"] = "linear";
+          config["config"] = {};
+          return deserializeActivation(config);
+        }
+        if (typeof identifier === "string") {
+          const config = {};
+          config["className"] = identifier;
+          config["config"] = {};
+          return deserializeActivation(config);
+        } else if (identifier instanceof activations_Activation) {
+          return identifier;
+        } else {
+          return deserializeActivation(identifier);
+        }
+      }
+      //# sourceMappingURL=activations.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/regularizers.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* original source: keras/regularizers.py */
+
+      function assertObjectArgs(args) {
+        if (args != null && typeof args !== "object") {
+          throw new Error(
+            `Argument to L1L2 regularizer's constructor is expected to be an ` +
+              `object, but received: ${args}`
+          );
+        }
+      }
+      /**
+       * Regularizer base class.
+       */
+      class regularizers_Regularizer extends dist["serialization"].Serializable {}
+      class regularizers_L1L2 extends regularizers_Regularizer {
+        constructor(args) {
+          super();
+          assertObjectArgs(args);
+          this.l1 = args == null || args.l1 == null ? 0.01 : args.l1;
+          this.l2 = args == null || args.l2 == null ? 0.01 : args.l2;
+          this.hasL1 = this.l1 !== 0;
+          this.hasL2 = this.l2 !== 0;
+        }
+        /**
+         * Porting note: Renamed from __call__.
+         * @param x Variable of which to calculate the regularization score.
+         */
+        apply(x) {
+          return Object(dist["tidy"])(() => {
+            let regularization = Object(dist["zeros"])([1]);
+            if (this.hasL1) {
+              regularization = Object(dist["add"])(
+                regularization,
+                Object(dist["sum"])(dist["mul"](this.l1, Object(dist["abs"])(x)))
+              );
+            }
+            if (this.hasL2) {
+              regularization = Object(dist["add"])(
+                regularization,
+                Object(dist["sum"])(dist["mul"](this.l2, square(x)))
+              );
+            }
+            return regularization.asScalar();
+          });
+        }
+        getConfig() {
+          return { l1: this.l1, l2: this.l2 };
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls({ l1: config["l1"], l2: config["l2"] });
+        }
+      }
+      /** @nocollapse */
+      regularizers_L1L2.className = "L1L2";
+      dist["serialization"].registerClass(regularizers_L1L2);
+      function l1(args) {
+        assertObjectArgs(args);
+        return new regularizers_L1L2({ l1: args != null ? args.l1 : null, l2: 0 });
+      }
+      function l2(args) {
+        assertObjectArgs(args);
+        return new regularizers_L1L2({ l2: args != null ? args.l2 : null, l1: 0 });
+      }
+      // Maps the JavaScript-like identifier keys to the corresponding keras symbols.
+      const REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP = {
+        l1l2: "L1L2",
+      };
+      function serializeRegularizer(constraint) {
+        return serializeKerasObject(constraint);
+      }
+      function deserializeRegularizer(config, customObjects = {}) {
+        return deserializeKerasObject(
+          config,
+          dist["serialization"].SerializationMap.getMap().classNameMap,
+          customObjects,
+          "regularizer"
+        );
+      }
+      function getRegularizer(identifier) {
+        if (identifier == null) {
+          return null;
+        }
+        if (typeof identifier === "string") {
+          const className =
+            identifier in REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP
+              ? REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier]
+              : identifier;
+          const config = { className, config: {} };
+          return deserializeRegularizer(config);
+        } else if (identifier instanceof regularizers_Regularizer) {
+          return identifier;
+        } else {
+          return deserializeRegularizer(identifier);
+        }
+      }
+      //# sourceMappingURL=regularizers.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/advanced_activations.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       *  Advanced activation layers.
+       */
+
+      class advanced_activations_ReLU extends topology_Layer {
+        constructor(args) {
+          super(args == null ? {} : args);
+          this.supportsMasking = true;
+          if (args != null) {
+            this.maxValue = args.maxValue;
+          }
+        }
+        call(inputs, kwargs) {
+          inputs = getExactlyOneTensor(inputs);
+          let output = Object(dist["relu"])(inputs);
+          if (this.maxValue != null) {
+            output = Object(dist["clipByValue"])(output, 0, this.maxValue);
+          }
+          return output;
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const config = { maxValue: this.maxValue };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      advanced_activations_ReLU.className = "ReLU";
+      dist["serialization"].registerClass(advanced_activations_ReLU);
+      class advanced_activations_LeakyReLU extends topology_Layer {
+        constructor(args) {
+          super(args == null ? {} : args);
+          this.DEFAULT_ALPHA = 0.3;
+          if (args == null) {
+            args = {};
+          }
+          this.alpha = args.alpha == null ? this.DEFAULT_ALPHA : args.alpha;
+        }
+        call(inputs, kwargs) {
+          const x = getExactlyOneTensor(inputs);
+          return Object(dist["leakyRelu"])(x, this.alpha);
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const config = { alpha: this.alpha };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      advanced_activations_LeakyReLU.className = "LeakyReLU";
+      dist["serialization"].registerClass(advanced_activations_LeakyReLU);
+      class advanced_activations_PReLU extends topology_Layer {
+        constructor(args) {
+          super(args == null ? {} : args);
+          this.DEFAULT_ALPHA_INITIALIZER = "zeros";
+          if (args == null) {
+            args = {};
+          }
+          this.supportsMasking = true;
+          this.alphaInitializer = getInitializer(
+            args.alphaInitializer || this.DEFAULT_ALPHA_INITIALIZER
+          );
+          this.alphaRegularizer = getRegularizer(args.alphaRegularizer);
+          this.alphaConstraint = getConstraint(args.alphaConstraint);
+          if (args.sharedAxes == null) {
+            this.sharedAxes = null;
+          } else if (Array.isArray(args.sharedAxes)) {
+            this.sharedAxes = args.sharedAxes;
+          } else if (typeof args.sharedAxes === "number") {
+            this.sharedAxes = [args.sharedAxes];
+          } else {
+            throw new ValueError(
+              `Expected sharedAxes to be a number or an array of numbers, ` +
+                `but got ${args.sharedAxes}`
+            );
+          }
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const paramShape = inputShape.slice(1);
+          if (this.sharedAxes != null) {
+            for (const i of this.sharedAxes) {
+              paramShape[i - 1] = 1;
+            }
+          }
+          this.alpha = this.addWeight(
+            "alpha",
+            paramShape,
+            "float32",
+            this.alphaInitializer,
+            this.alphaRegularizer,
+            true,
+            this.alphaConstraint
+          );
+          // Set input spec.
+          const axes = {};
+          if (this.sharedAxes != null) {
+            for (let i = 1; i < inputShape.length; ++i) {
+              axes[i] = inputShape[i];
+            }
+          }
+          this.inputSpec = [
+            new InputSpec({
+              ndim: inputShape.length,
+              axes,
+            }),
+          ];
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          inputs = getExactlyOneTensor(inputs);
+          return Object(dist["prelu"])(inputs, this.alpha.read());
+        }
+        getConfig() {
+          const config = {
+            alphaInitializer: serializeInitializer(this.alphaInitializer),
+            alphaRegularizer: serializeRegularizer(this.alphaRegularizer),
+            alphaConstraint: serializeConstraint(this.alphaConstraint),
+            sharedAxes: this.sharedAxes,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      advanced_activations_PReLU.className = "PReLU";
+      dist["serialization"].registerClass(advanced_activations_PReLU);
+      class advanced_activations_ELU extends topology_Layer {
+        constructor(args) {
+          super(args == null ? {} : args);
+          this.DEFAULT_ALPHA = 1.0;
+          if (args == null) {
+            args = {};
+          }
+          if (args.alpha != null && args.alpha !== this.DEFAULT_ALPHA) {
+            throw new NotImplementedError(
+              `Non-default alpha value (${args.alpha}) is not supported by the ` + `ELU layer yet.`
+            );
+          }
+          this.alpha = args.alpha == null ? this.DEFAULT_ALPHA : args.alpha;
+        }
+        call(inputs, kwargs) {
+          const x = getExactlyOneTensor(inputs);
+          return Object(dist["elu"])(x);
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const config = { alpha: this.alpha };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      advanced_activations_ELU.className = "ELU";
+      dist["serialization"].registerClass(advanced_activations_ELU);
+      class advanced_activations_ThresholdedReLU extends topology_Layer {
+        constructor(args) {
+          super(args == null ? {} : args);
+          this.DEFAULT_THETA = 1.0;
+          if (args == null) {
+            args = {};
+          }
+          this.theta = args.theta == null ? this.DEFAULT_THETA : args.theta;
+        }
+        call(inputs, kwargs) {
+          const x = getExactlyOneTensor(inputs);
+          return x.mul(cast(x.greater(this.theta), "float32"));
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const config = { theta: this.theta };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      advanced_activations_ThresholdedReLU.className = "ThresholdedReLU";
+      dist["serialization"].registerClass(advanced_activations_ThresholdedReLU);
+      class advanced_activations_Softmax extends topology_Layer {
+        constructor(args) {
+          super(args == null ? {} : args);
+          this.DEFAULT_AXIS = 1.0;
+          if (args == null) {
+            args = {};
+          }
+          this.softmax = new activations_Softmax().apply;
+          this.axis = args.axis == null ? this.DEFAULT_AXIS : args.axis;
+        }
+        call(inputs, kwargs) {
+          const x = getExactlyOneTensor(inputs);
+          return this.softmax(x, this.axis);
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const config = { axis: this.axis };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      advanced_activations_Softmax.className = "Softmax";
+      dist["serialization"].registerClass(advanced_activations_Softmax);
+      //# sourceMappingURL=advanced_activations.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/utils/conv_utils.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      /**
+       * Transforms a single number of array of numbers into an array of numbers.
+       * @param value
+       * @param n: The size of the tuple to be returned.
+       * @param name: Name of the parameter, used for generating error messages.
+       * @returns An array of numbers.
+       */
+      function normalizeArray(value, n, name) {
+        if (typeof value === "number") {
+          return pyListRepeat(value, n);
+        } else {
+          if (value.length !== n) {
+            throw new ValueError(
+              `The ${name} argument must be an integer or tuple of ${n} integers.` +
+                ` Received: ${value.length} elements.`
+            );
+          }
+          for (let i = 0; i < n; ++i) {
+            const singleValue = value[i];
+            if (!isInteger(singleValue)) {
+              throw new ValueError(
+                `The ${name} argument must be an integer or tuple of ${n}` +
+                  ` integers. Received: ${JSON.stringify(value)} including a` +
+                  ` non-integer number ${singleValue}`
+              );
+            }
+          }
+          return value;
+        }
+      }
+      /**
+       * Determines output length of a convolution given input length.
+       * @param inputLength
+       * @param filterSize
+       * @param padding
+       * @param stride
+       * @param dilation: dilation rate.
+       */
+      function convOutputLength(inputLength, filterSize, padding, stride, dilation = 1) {
+        if (inputLength == null) {
+          return inputLength;
+        }
+        const dilatedFilterSize = filterSize + (filterSize - 1) * (dilation - 1);
+        let outputLength;
+        if (padding === "same") {
+          outputLength = inputLength;
+        } else {
+          // VALID
+          outputLength = inputLength - dilatedFilterSize + 1;
+        }
+        return Math.floor((outputLength + stride - 1) / stride);
+      }
+      function deconvLength(dimSize, strideSize, kernelSize, padding) {
+        if (dimSize == null) {
+          return null;
+        }
+        if (padding === "valid") {
+          dimSize = dimSize * strideSize + max([kernelSize - strideSize, 0]);
+        } else if (padding === "same") {
+          dimSize = dimSize * strideSize;
+        } else {
+          throw new ValueError(`Unsupport padding mode: ${padding}.`);
+        }
+        return dimSize;
+      }
+      //# sourceMappingURL=conv_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * TensorFlow.js Layers: Convolutional Layers
+       */
+
+      /**
+       * Transpose and cast the input before the conv2d.
+       * @param x Input image tensor.
+       * @param dataFormat
+       */
+      function preprocessConv2DInput(x, dataFormat) {
+        // TODO(cais): Cast type to float32 if not.
+        return Object(dist["tidy"])(() => {
+          checkDataFormat(dataFormat);
+          if (dataFormat === "channelsFirst") {
+            return dist["transpose"](x, [0, 2, 3, 1]); // NCHW -> NHWC.
+          } else {
+            return x;
+          }
+        });
+      }
+      /**
+       * Transpose and cast the input before the conv3d.
+       * @param x Input image tensor.
+       * @param dataFormat
+       */
+      function preprocessConv3DInput(x, dataFormat) {
+        return Object(dist["tidy"])(() => {
+          checkDataFormat(dataFormat);
+          if (dataFormat === "channelsFirst") {
+            return dist["transpose"](x, [0, 2, 3, 4, 1]); // NCDHW -> NDHWC.
+          } else {
+            return x;
+          }
+        });
+      }
+      /**
+       * 1D-convolution with bias added.
+       *
+       * Porting Note: This function does not exist in the Python Keras backend.
+       *   It is exactly the same as `conv2d`, except the added `bias`.
+       *
+       * @param x Input tensor, rank-3, of shape `[batchSize, width, inChannels]`.
+       * @param kernel Kernel, rank-3, of shape `[filterWidth, inDepth, outDepth]`.
+       * @param bias Bias, rank-3, of shape `[outDepth]`.
+       * @param strides
+       * @param padding Padding mode.
+       * @param dataFormat Data format.
+       * @param dilationRate
+       * @returns The result of the 1D convolution.
+       * @throws ValueError, if `x`, `kernel` or `bias` is not of the correct rank.
+       */
+      function conv1dWithBias(
+        x,
+        kernel,
+        bias,
+        strides = 1,
+        padding = "valid",
+        dataFormat,
+        dilationRate = 1
+      ) {
+        return Object(dist["tidy"])(() => {
+          if (dataFormat == null) {
+            dataFormat = imageDataFormat();
+          }
+          checkDataFormat(dataFormat);
+          // Check the ranks of x, kernel and bias.
+          if (x.shape.length !== 3) {
+            throw new ValueError(
+              `The input of a conv1dWithBias operation should be 3, but is ` +
+                `${x.shape.length} instead.`
+            );
+          }
+          if (kernel.shape.length !== 3) {
+            throw new ValueError(
+              `The kernel for a conv1dWithBias operation should be 3, but is ` +
+                `${kernel.shape.length} instead`
+            );
+          }
+          if (bias != null && bias.shape.length !== 1) {
+            throw new ValueError(
+              `The bias for a conv1dWithBias operation should be 1, but is ` +
+                `${kernel.shape.length} instead`
+            );
+          }
+          // TODO(cais): Support CAUSAL padding mode.
+          if (dataFormat === "channelsFirst") {
+            x = dist["transpose"](x, [0, 2, 1]); // NCW -> NWC.
+          }
+          if (padding === "causal") {
+            throw new NotImplementedError(
+              "The support for CAUSAL padding mode in conv1dWithBias is not " + "implemented yet."
+            );
+          }
+          let y = dist["conv1d"](
+            x,
+            kernel,
+            strides,
+            padding === "same" ? "same" : "valid",
+            "NWC",
+            dilationRate
+          );
+          if (bias != null) {
+            y = biasAdd(y, bias);
+          }
+          return y;
+        });
+      }
+      /**
+       * 1D-convolution.
+       *
+       * @param x Input tensor, rank-3, of shape `[batchSize, width, inChannels]`.
+       * @param kernel Kernel, rank-3, of shape `[filterWidth, inDepth, outDepth]`.s
+       * @param strides
+       * @param padding Padding mode.
+       * @param dataFormat Data format.
+       * @param dilationRate
+       * @returns The result of the 1D convolution.
+       * @throws ValueError, if `x`, `kernel` or `bias` is not of the correct rank.
+       */
+      function conv1d(x, kernel, strides = 1, padding = "valid", dataFormat, dilationRate = 1) {
+        return Object(dist["tidy"])(() => {
+          checkDataFormat(dataFormat);
+          return conv1dWithBias(x, kernel, null, strides, padding, dataFormat, dilationRate);
+        });
+      }
+      /**
+       * 2D Convolution
+       * @param x
+       * @param kernel kernel of the convolution.
+       * @param strides strides array.
+       * @param padding padding mode. Default to 'valid'.
+       * @param dataFormat data format. Defaults to 'channelsLast'.
+       * @param dilationRate dilation rate array.
+       * @returns Result of the 2D pooling.
+       */
+      function conv2d(x, kernel, strides = [1, 1], padding = "valid", dataFormat, dilationRate) {
+        return Object(dist["tidy"])(() => {
+          checkDataFormat(dataFormat);
+          return conv2dWithBiasActivation(
+            x,
+            kernel,
+            null,
+            strides,
+            padding,
+            dataFormat,
+            dilationRate
+          );
+        });
+      }
+      /**
+       * 2D Convolution with an added bias and optional activation.
+       * Note: This function does not exist in the Python Keras Backend. This function
+       * is exactly the same as `conv2d`, except the added `bias`.
+       */
+      function conv2dWithBiasActivation(
+        x,
+        kernel,
+        bias,
+        strides = [1, 1],
+        padding = "valid",
+        dataFormat,
+        dilationRate,
+        activation = null
+      ) {
+        return Object(dist["tidy"])(() => {
+          if (dataFormat == null) {
+            dataFormat = imageDataFormat();
+          }
+          checkDataFormat(dataFormat);
+          if (x.rank !== 3 && x.rank !== 4) {
+            throw new ValueError(
+              `conv2dWithBiasActivation expects input to be of rank 3 or 4, ` +
+                `but received ${x.rank}.`
+            );
+          }
+          if (kernel.rank !== 3 && kernel.rank !== 4) {
+            throw new ValueError(
+              `conv2dWithBiasActivation expects kernel to be of rank 3 or 4, ` +
+                `but received ${x.rank}.`
+            );
+          }
+          let y = preprocessConv2DInput(x, dataFormat);
+          if (padding === "causal") {
+            throw new NotImplementedError(
+              "The support for CAUSAL padding mode in conv1dWithBias is not " + "implemented yet."
+            );
+          }
+          y = dist["fused"].conv2d({
+            x: y,
+            filter: kernel,
+            strides: strides,
+            pad: padding === "same" ? "same" : "valid",
+            dilations: dilationRate,
+            dataFormat: "NHWC",
+            bias,
+            activation,
+          });
+          if (dataFormat === "channelsFirst") {
+            y = dist["transpose"](y, [0, 3, 1, 2]);
+          }
+          return y;
+        });
+      }
+      /**
+       * 3D Convolution.
+       * @param x
+       * @param kernel kernel of the convolution.
+       * @param strides strides array.
+       * @param padding padding mode. Default to 'valid'.
+       * @param dataFormat data format. Defaults to 'channelsLast'.
+       * @param dilationRate dilation rate array.
+       * @returns Result of the 3D convolution.
+       */
+      function conv3d(x, kernel, strides = [1, 1, 1], padding = "valid", dataFormat, dilationRate) {
+        return Object(dist["tidy"])(() => {
+          checkDataFormat(dataFormat);
+          return conv3dWithBias(x, kernel, null, strides, padding, dataFormat, dilationRate);
+        });
+      }
+      /**
+       * 3D Convolution with an added bias.
+       * Note: This function does not exist in the Python Keras Backend. This function
+       * is exactly the same as `conv3d`, except the added `bias`.
+       */
+      function conv3dWithBias(
+        x,
+        kernel,
+        bias,
+        strides = [1, 1, 1],
+        padding = "valid",
+        dataFormat,
+        dilationRate
+      ) {
+        return Object(dist["tidy"])(() => {
+          if (dataFormat == null) {
+            dataFormat = imageDataFormat();
+          }
+          checkDataFormat(dataFormat);
+          if (x.rank !== 4 && x.rank !== 5) {
+            throw new ValueError(
+              `conv3dWithBias expects input to be of rank 4 or 5, but received ` + `${x.rank}.`
+            );
+          }
+          if (kernel.rank !== 4 && kernel.rank !== 5) {
+            throw new ValueError(
+              `conv3dWithBias expects kernel to be of rank 4 or 5, but received ` + `${x.rank}.`
+            );
+          }
+          let y = preprocessConv3DInput(x, dataFormat);
+          if (padding === "causal") {
+            throw new NotImplementedError(
+              "The support for CAUSAL padding mode in conv3dWithBias is not " + "implemented yet."
+            );
+          }
+          y = dist["conv3d"](
+            y,
+            kernel,
+            strides,
+            padding === "same" ? "same" : "valid",
+            "NDHWC",
+            dilationRate
+          );
+          if (bias != null) {
+            y = biasAdd(y, bias);
+          }
+          if (dataFormat === "channelsFirst") {
+            y = dist["transpose"](y, [0, 4, 1, 2, 3]);
+          }
+          return y;
+        });
+      }
+      /**
+       * Abstract convolution layer.
+       */
+      class convolutional_BaseConv extends topology_Layer {
+        constructor(rank, args) {
+          super(args);
+          this.bias = null;
+          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
+          this.DEFAULT_BIAS_INITIALIZER = "zeros";
+          convolutional_BaseConv.verifyArgs(args);
+          this.rank = rank;
+          assertPositiveInteger(this.rank, "rank");
+          if (this.rank !== 1 && this.rank !== 2 && this.rank !== 3) {
+            throw new NotImplementedError(
+              `Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is ` +
+                `not implemented yet.`
+            );
+          }
+          this.kernelSize = normalizeArray(args.kernelSize, rank, "kernelSize");
+          this.strides = normalizeArray(args.strides == null ? 1 : args.strides, rank, "strides");
+          this.padding = args.padding == null ? "valid" : args.padding;
+          checkPaddingMode(this.padding);
+          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
+          checkDataFormat(this.dataFormat);
+          this.activation = getActivation(args.activation);
+          this.useBias = args.useBias == null ? true : args.useBias;
+          this.biasInitializer = getInitializer(
+            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
+          );
+          this.biasConstraint = getConstraint(args.biasConstraint);
+          this.biasRegularizer = getRegularizer(args.biasRegularizer);
+          this.activityRegularizer = getRegularizer(args.activityRegularizer);
+          this.dilationRate = normalizeArray(
+            args.dilationRate == null ? 1 : args.dilationRate,
+            rank,
+            "dilationRate"
+          );
+          if (
+            this.rank === 1 &&
+            Array.isArray(this.dilationRate) &&
+            this.dilationRate.length !== 1
+          ) {
+            throw new ValueError(
+              `dilationRate must be a number or an array of a single number ` +
+                `for 1D convolution, but received ` +
+                `${JSON.stringify(this.dilationRate)}`
+            );
+          } else if (this.rank === 2) {
+            if (typeof this.dilationRate === "number") {
+              this.dilationRate = [this.dilationRate, this.dilationRate];
+            } else if (this.dilationRate.length !== 2) {
+              throw new ValueError(
+                `dilationRate must be a number or array of two numbers for 2D ` +
+                  `convolution, but received ${JSON.stringify(this.dilationRate)}`
+              );
+            }
+          } else if (this.rank === 3) {
+            if (typeof this.dilationRate === "number") {
+              this.dilationRate = [this.dilationRate, this.dilationRate, this.dilationRate];
+            } else if (this.dilationRate.length !== 3) {
+              throw new ValueError(
+                `dilationRate must be a number or array of three numbers for 3D ` +
+                  `convolution, but received ${JSON.stringify(this.dilationRate)}`
+              );
+            }
+          }
+        }
+        static verifyArgs(args) {
+          // Check config.kernelSize type and shape.
+          assert("kernelSize" in args, `required key 'kernelSize' not in config`);
+          if (
+            typeof args.kernelSize !== "number" &&
+            !checkArrayTypeAndLength(args.kernelSize, "number", 1, 3)
+          ) {
+            throw new ValueError(
+              `BaseConv expects config.kernelSize to be number or number[] with ` +
+                `length 1, 2, or 3, but received ${JSON.stringify(args.kernelSize)}.`
+            );
+          }
+        }
+        getConfig() {
+          const config = {
+            kernelSize: this.kernelSize,
+            strides: this.strides,
+            padding: this.padding,
+            dataFormat: this.dataFormat,
+            dilationRate: this.dilationRate,
+            activation: serializeActivation(this.activation),
+            useBias: this.useBias,
+            biasInitializer: serializeInitializer(this.biasInitializer),
+            biasRegularizer: serializeRegularizer(this.biasRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            biasConstraint: serializeConstraint(this.biasConstraint),
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /**
+       * Abstract nD convolution layer.  Ancestor of convolution layers which reduce
+       * across channels, i.e., Conv1D and Conv2D, but not DepthwiseConv2D.
+       */
+      class convolutional_Conv extends convolutional_BaseConv {
+        constructor(rank, args) {
+          super(rank, args);
+          this.kernel = null;
+          convolutional_Conv.verifyArgs(args);
+          this.filters = args.filters;
+          assertPositiveInteger(this.filters, "filters");
+          this.kernelInitializer = getInitializer(
+            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
+          );
+          this.kernelConstraint = getConstraint(args.kernelConstraint);
+          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const channelAxis = this.dataFormat === "channelsFirst" ? 1 : inputShape.length - 1;
+          if (inputShape[channelAxis] == null) {
+            throw new ValueError(
+              `The channel dimension of the input should be defined. ` +
+                `Found ${inputShape[channelAxis]}`
+            );
+          }
+          const inputDim = inputShape[channelAxis];
+          const kernelShape = this.kernelSize.concat([inputDim, this.filters]);
+          this.kernel = this.addWeight(
+            "kernel",
+            kernelShape,
+            null,
+            this.kernelInitializer,
+            this.kernelRegularizer,
+            true,
+            this.kernelConstraint
+          );
+          if (this.useBias) {
+            this.bias = this.addWeight(
+              "bias",
+              [this.filters],
+              null,
+              this.biasInitializer,
+              this.biasRegularizer,
+              true,
+              this.biasConstraint
+            );
+          }
+          this.inputSpec = [{ ndim: this.rank + 2, axes: { [channelAxis]: inputDim } }];
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = getExactlyOneTensor(inputs);
+            let outputs;
+            const biasValue = this.bias == null ? null : this.bias.read();
+            const fusedActivationName = mapActivationToFusedKernel(this.activation.getClassName());
+            if (fusedActivationName != null && this.rank === 2) {
+              outputs = conv2dWithBiasActivation(
+                inputs,
+                this.kernel.read(),
+                biasValue,
+                this.strides,
+                this.padding,
+                this.dataFormat,
+                this.dilationRate,
+                fusedActivationName
+              );
+            } else {
+              if (this.rank === 1) {
+                outputs = conv1dWithBias(
+                  inputs,
+                  this.kernel.read(),
+                  biasValue,
+                  this.strides[0],
+                  this.padding,
+                  this.dataFormat,
+                  this.dilationRate[0]
+                );
+              } else if (this.rank === 2) {
+                // TODO(cais): Move up to constructor.
+                outputs = conv2dWithBiasActivation(
+                  inputs,
+                  this.kernel.read(),
+                  biasValue,
+                  this.strides,
+                  this.padding,
+                  this.dataFormat,
+                  this.dilationRate
+                );
+              } else if (this.rank === 3) {
+                outputs = conv3dWithBias(
+                  inputs,
+                  this.kernel.read(),
+                  biasValue,
+                  this.strides,
+                  this.padding,
+                  this.dataFormat,
+                  this.dilationRate
+                );
+              } else {
+                throw new NotImplementedError(
+                  "convolutions greater than 3D are not implemented yet."
+                );
+              }
+              if (this.activation != null) {
+                outputs = this.activation.apply(outputs);
+              }
+            }
+            return outputs;
+          });
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const newSpace = [];
+          const space =
+            this.dataFormat === "channelsLast"
+              ? inputShape.slice(1, inputShape.length - 1)
+              : inputShape.slice(2);
+          for (let i = 0; i < space.length; ++i) {
+            const newDim = convOutputLength(
+              space[i],
+              this.kernelSize[i],
+              this.padding,
+              this.strides[i],
+              typeof this.dilationRate === "number" ? this.dilationRate : this.dilationRate[i]
+            );
+            newSpace.push(newDim);
+          }
+          let outputShape = [inputShape[0]];
+          if (this.dataFormat === "channelsLast") {
+            outputShape = outputShape.concat(newSpace);
+            outputShape.push(this.filters);
+          } else {
+            outputShape.push(this.filters);
+            outputShape = outputShape.concat(newSpace);
+          }
+          return outputShape;
+        }
+        getConfig() {
+          const config = {
+            filters: this.filters,
+            kernelInitializer: serializeInitializer(this.kernelInitializer),
+            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
+            kernelConstraint: serializeConstraint(this.kernelConstraint),
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        static verifyArgs(args) {
+          // Check config.filters type, shape, and value.
+          if (!("filters" in args) || typeof args.filters !== "number" || args.filters < 1) {
+            throw new ValueError(
+              `Convolution layer expected config.filters to be a 'number' > 0 ` +
+                `but got ${JSON.stringify(args.filters)}`
+            );
+          }
+        }
+      }
+      class convolutional_Conv2D extends convolutional_Conv {
+        constructor(args) {
+          super(2, args);
+          convolutional_Conv2D.verifyArgs(args);
+        }
+        getConfig() {
+          const config = super.getConfig();
+          delete config["rank"];
+          return config;
+        }
+        static verifyArgs(args) {
+          // config.kernelSize must be a number or array of numbers.
+          if (
+            typeof args.kernelSize !== "number" &&
+            !checkArrayTypeAndLength(args.kernelSize, "number", 1, 2)
+          ) {
+            throw new ValueError(
+              `Conv2D expects config.kernelSize to be number or number[] with ` +
+                `length 1 or 2, but received ${JSON.stringify(args.kernelSize)}.`
+            );
+          }
+        }
+      }
+      /** @nocollapse */
+      convolutional_Conv2D.className = "Conv2D";
+      dist["serialization"].registerClass(convolutional_Conv2D);
+      class convolutional_Conv3D extends convolutional_Conv {
+        constructor(args) {
+          super(3, args);
+          convolutional_Conv3D.verifyArgs(args);
+        }
+        getConfig() {
+          const config = super.getConfig();
+          delete config["rank"];
+          return config;
+        }
+        static verifyArgs(args) {
+          // config.kernelSize must be a number or array of numbers.
+          if (typeof args.kernelSize !== "number") {
+            if (
+              !(
+                Array.isArray(args.kernelSize) &&
+                (args.kernelSize.length === 1 || args.kernelSize.length === 3)
+              )
+            ) {
+              throw new ValueError(
+                `Conv3D expects config.kernelSize to be number or` +
+                  ` [number, number, number], but received ${JSON.stringify(args.kernelSize)}.`
+              );
+            }
+          }
+        }
+      }
+      /** @nocollapse */
+      convolutional_Conv3D.className = "Conv3D";
+      dist["serialization"].registerClass(convolutional_Conv3D);
+      class convolutional_Conv2DTranspose extends convolutional_Conv2D {
+        constructor(args) {
+          super(args);
+          this.inputSpec = [new InputSpec({ ndim: 4 })];
+          if (this.padding !== "same" && this.padding !== "valid") {
+            throw new ValueError(
+              `Conv2DTranspose currently supports only padding modes 'same' ` +
+                `and 'valid', but received padding mode ${this.padding}`
+            );
+          }
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          if (inputShape.length !== 4) {
+            throw new ValueError(
+              "Input should have rank 4; Received input shape: " + JSON.stringify(inputShape)
+            );
+          }
+          const channelAxis = this.dataFormat === "channelsFirst" ? 1 : inputShape.length - 1;
+          if (inputShape[channelAxis] == null) {
+            throw new ValueError(
+              "The channel dimension of the inputs should be defined. " + "Found `None`."
+            );
+          }
+          const inputDim = inputShape[channelAxis];
+          const kernelShape = this.kernelSize.concat([this.filters, inputDim]);
+          this.kernel = this.addWeight(
+            "kernel",
+            kernelShape,
+            "float32",
+            this.kernelInitializer,
+            this.kernelRegularizer,
+            true,
+            this.kernelConstraint
+          );
+          if (this.useBias) {
+            this.bias = this.addWeight(
+              "bias",
+              [this.filters],
+              "float32",
+              this.biasInitializer,
+              this.biasRegularizer,
+              true,
+              this.biasConstraint
+            );
+          }
+          // Set input spec.
+          this.inputSpec = [new InputSpec({ ndim: 4, axes: { [channelAxis]: inputDim } })];
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          return dist["tidy"](() => {
+            let input = getExactlyOneTensor(inputs);
+            if (input.shape.length !== 4) {
+              throw new ValueError(
+                `Conv2DTranspose.call() expects input tensor to be rank-4, but ` +
+                  `received a tensor of rank-${input.shape.length}`
+              );
+            }
+            const inputShape = input.shape;
+            const batchSize = inputShape[0];
+            let hAxis;
+            let wAxis;
+            if (this.dataFormat === "channelsFirst") {
+              hAxis = 2;
+              wAxis = 3;
+            } else {
+              hAxis = 1;
+              wAxis = 2;
+            }
+            const height = inputShape[hAxis];
+            const width = inputShape[wAxis];
+            const kernelH = this.kernelSize[0];
+            const kernelW = this.kernelSize[1];
+            const strideH = this.strides[0];
+            const strideW = this.strides[1];
+            // Infer the dynamic output shape.
+            const outHeight = deconvLength(height, strideH, kernelH, this.padding);
+            const outWidth = deconvLength(width, strideW, kernelW, this.padding);
+            // Porting Note: We don't branch based on `this.dataFormat` here,
+            // because
+            //   the tjfs-core function `conv2dTranspose` called below always
+            //   assumes channelsLast.
+            const outputShape = [batchSize, outHeight, outWidth, this.filters];
+            if (this.dataFormat !== "channelsLast") {
+              input = dist["transpose"](input, [0, 2, 3, 1]);
+            }
+            let outputs = dist["conv2dTranspose"](
+              input,
+              this.kernel.read(),
+              outputShape,
+              this.strides,
+              this.padding
+            );
+            if (this.dataFormat !== "channelsLast") {
+              outputs = dist["transpose"](outputs, [0, 3, 1, 2]);
+            }
+            if (this.bias != null) {
+              outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);
+            }
+            if (this.activation != null) {
+              outputs = this.activation.apply(outputs);
+            }
+            return outputs;
+          });
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const outputShape = inputShape.slice();
+          let channelAxis;
+          let heightAxis;
+          let widthAxis;
+          if (this.dataFormat === "channelsFirst") {
+            channelAxis = 1;
+            heightAxis = 2;
+            widthAxis = 3;
+          } else {
+            channelAxis = 3;
+            heightAxis = 1;
+            widthAxis = 2;
+          }
+          const kernelH = this.kernelSize[0];
+          const kernelW = this.kernelSize[1];
+          const strideH = this.strides[0];
+          const strideW = this.strides[1];
+          outputShape[channelAxis] = this.filters;
+          outputShape[heightAxis] = deconvLength(
+            outputShape[heightAxis],
+            strideH,
+            kernelH,
+            this.padding
+          );
+          outputShape[widthAxis] = deconvLength(
+            outputShape[widthAxis],
+            strideW,
+            kernelW,
+            this.padding
+          );
+          return outputShape;
+        }
+        getConfig() {
+          const config = super.getConfig();
+          delete config["dilationRate"];
+          return config;
+        }
+      }
+      /** @nocollapse */
+      convolutional_Conv2DTranspose.className = "Conv2DTranspose";
+      dist["serialization"].registerClass(convolutional_Conv2DTranspose);
+      class convolutional_SeparableConv extends convolutional_Conv {
+        constructor(rank, config) {
+          super(rank, config);
+          this.DEFAULT_DEPTHWISE_INITIALIZER = "glorotUniform";
+          this.DEFAULT_POINTWISE_INITIALIZER = "glorotUniform";
+          this.depthwiseKernel = null;
+          this.pointwiseKernel = null;
+          if (config.filters == null) {
+            throw new ValueError(
+              "The `filters` configuration field is required by SeparableConv, " +
+                "but is unspecified."
+            );
+          }
+          if (
+            config.kernelInitializer != null ||
+            config.kernelRegularizer != null ||
+            config.kernelConstraint != null
+          ) {
+            throw new ValueError(
+              "Fields kernelInitializer, kernelRegularizer and kernelConstraint " +
+                "are invalid for SeparableConv2D. Use depthwiseInitializer, " +
+                "depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, " +
+                "pointwiseRegularizer and pointwiseConstraint instead."
+            );
+          }
+          if (config.padding != null && config.padding !== "same" && config.padding !== "valid") {
+            throw new ValueError(
+              `SeparableConv${this.rank}D supports only padding modes: ` +
+                `'same' and 'valid', but received ${JSON.stringify(config.padding)}`
+            );
+          }
+          this.depthMultiplier = config.depthMultiplier == null ? 1 : config.depthMultiplier;
+          this.depthwiseInitializer = getInitializer(
+            config.depthwiseInitializer || this.DEFAULT_DEPTHWISE_INITIALIZER
+          );
+          this.depthwiseRegularizer = getRegularizer(config.depthwiseRegularizer);
+          this.depthwiseConstraint = getConstraint(config.depthwiseConstraint);
+          this.pointwiseInitializer = getInitializer(
+            config.depthwiseInitializer || this.DEFAULT_POINTWISE_INITIALIZER
+          );
+          this.pointwiseRegularizer = getRegularizer(config.pointwiseRegularizer);
+          this.pointwiseConstraint = getConstraint(config.pointwiseConstraint);
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          if (inputShape.length < this.rank + 2) {
+            throw new ValueError(
+              `Inputs to SeparableConv${this.rank}D should have rank ` +
+                `${this.rank + 2}, but received input shape: ` +
+                `${JSON.stringify(inputShape)}`
+            );
+          }
+          const channelAxis = this.dataFormat === "channelsFirst" ? 1 : inputShape.length - 1;
+          if (inputShape[channelAxis] == null || inputShape[channelAxis] < 0) {
+            throw new ValueError(
+              `The channel dimension of the inputs should be defined, ` +
+                `but found ${JSON.stringify(inputShape[channelAxis])}`
+            );
+          }
+          const inputDim = inputShape[channelAxis];
+          const depthwiseKernelShape = this.kernelSize.concat([inputDim, this.depthMultiplier]);
+          const pointwiseKernelShape = [];
+          for (let i = 0; i < this.rank; ++i) {
+            pointwiseKernelShape.push(1);
+          }
+          pointwiseKernelShape.push(inputDim * this.depthMultiplier, this.filters);
+          const trainable = true;
+          this.depthwiseKernel = this.addWeight(
+            "depthwise_kernel",
+            depthwiseKernelShape,
+            "float32",
+            this.depthwiseInitializer,
+            this.depthwiseRegularizer,
+            trainable,
+            this.depthwiseConstraint
+          );
+          this.pointwiseKernel = this.addWeight(
+            "pointwise_kernel",
+            pointwiseKernelShape,
+            "float32",
+            this.pointwiseInitializer,
+            this.pointwiseRegularizer,
+            trainable,
+            this.pointwiseConstraint
+          );
+          if (this.useBias) {
+            this.bias = this.addWeight(
+              "bias",
+              [this.filters],
+              "float32",
+              this.biasInitializer,
+              this.biasRegularizer,
+              trainable,
+              this.biasConstraint
+            );
+          } else {
+            this.bias = null;
+          }
+          this.inputSpec = [
+            new InputSpec({ ndim: this.rank + 2, axes: { [channelAxis]: inputDim } }),
+          ];
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = getExactlyOneTensor(inputs);
+            let output;
+            if (this.rank === 1) {
+              throw new NotImplementedError("1D separable convolution is not implemented yet.");
+            } else if (this.rank === 2) {
+              if (this.dataFormat === "channelsFirst") {
+                inputs = dist["transpose"](inputs, [0, 2, 3, 1]); // NCHW -> NHWC.
+              }
+              output = dist["separableConv2d"](
+                inputs,
+                this.depthwiseKernel.read(),
+                this.pointwiseKernel.read(),
+                this.strides,
+                this.padding,
+                this.dilationRate,
+                "NHWC"
+              );
+            }
+            if (this.useBias) {
+              output = biasAdd(output, this.bias.read(), this.dataFormat);
+            }
+            if (this.activation != null) {
+              output = this.activation.apply(output);
+            }
+            if (this.dataFormat === "channelsFirst") {
+              output = dist["transpose"](output, [0, 3, 1, 2]); // NHWC -> NCHW.
+            }
+            return output;
+          });
+        }
+        getConfig() {
+          const config = super.getConfig();
+          delete config["rank"];
+          delete config["kernelInitializer"];
+          delete config["kernelRegularizer"];
+          delete config["kernelConstraint"];
+          config["depthwiseInitializer"] = serializeInitializer(this.depthwiseInitializer);
+          config["pointwiseInitializer"] = serializeInitializer(this.pointwiseInitializer);
+          config["depthwiseRegularizer"] = serializeRegularizer(this.depthwiseRegularizer);
+          config["pointwiseRegularizer"] = serializeRegularizer(this.pointwiseRegularizer);
+          config["depthwiseConstraint"] = serializeConstraint(this.depthwiseConstraint);
+          config["pointwiseConstraint"] = serializeConstraint(this.pointwiseConstraint);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      convolutional_SeparableConv.className = "SeparableConv";
+      class SeparableConv2D extends convolutional_SeparableConv {
+        constructor(args) {
+          super(2, args);
+        }
+      }
+      /** @nocollapse */
+      SeparableConv2D.className = "SeparableConv2D";
+      dist["serialization"].registerClass(SeparableConv2D);
+      class convolutional_Conv1D extends convolutional_Conv {
+        constructor(args) {
+          super(1, args);
+          convolutional_Conv1D.verifyArgs(args);
+          this.inputSpec = [{ ndim: 3 }];
+        }
+        getConfig() {
+          const config = super.getConfig();
+          delete config["rank"];
+          delete config["dataFormat"];
+          return config;
+        }
+        static verifyArgs(args) {
+          // config.kernelSize must be a number or array of numbers.
+          if (
+            typeof args.kernelSize !== "number" &&
+            !checkArrayTypeAndLength(args.kernelSize, "number", 1, 1)
+          ) {
+            throw new ValueError(
+              `Conv1D expects config.kernelSize to be number or number[] with ` +
+                `length 1, but received ${JSON.stringify(args.kernelSize)}.`
+            );
+          }
+        }
+      }
+      /** @nocollapse */
+      convolutional_Conv1D.className = "Conv1D";
+      dist["serialization"].registerClass(convolutional_Conv1D);
+      class convolutional_Cropping2D extends topology_Layer {
+        constructor(args) {
+          super(args);
+          if (typeof args.cropping === "number") {
+            this.cropping = [
+              [args.cropping, args.cropping],
+              [args.cropping, args.cropping],
+            ];
+          } else if (typeof args.cropping[0] === "number") {
+            this.cropping = [
+              [args.cropping[0], args.cropping[0]],
+              [args.cropping[1], args.cropping[1]],
+            ];
+          } else {
+            this.cropping = args.cropping;
+          }
+          this.dataFormat = args.dataFormat === undefined ? "channelsLast" : args.dataFormat;
+          this.inputSpec = [{ ndim: 4 }];
+        }
+        computeOutputShape(inputShape) {
+          if (this.dataFormat === "channelsFirst") {
+            return [
+              inputShape[0],
+              inputShape[1],
+              inputShape[2] - this.cropping[0][0] - this.cropping[0][1],
+              inputShape[3] - this.cropping[1][0] - this.cropping[1][1],
+            ];
+          } else {
+            return [
+              inputShape[0],
+              inputShape[1] - this.cropping[0][0] - this.cropping[0][1],
+              inputShape[2] - this.cropping[1][0] - this.cropping[1][1],
+              inputShape[3],
+            ];
+          }
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = getExactlyOneTensor(inputs);
+            if (this.dataFormat === "channelsLast") {
+              const hSliced = sliceAlongAxis(
+                inputs,
+                this.cropping[0][0],
+                inputs.shape[1] - this.cropping[0][0] - this.cropping[0][1],
+                2
+              );
+              return sliceAlongAxis(
+                hSliced,
+                this.cropping[1][0],
+                inputs.shape[2] - this.cropping[1][1] - this.cropping[1][0],
+                3
+              );
+            } else {
+              const hSliced = sliceAlongAxis(
+                inputs,
+                this.cropping[0][0],
+                inputs.shape[2] - this.cropping[0][0] - this.cropping[0][1],
+                3
+              );
+              return sliceAlongAxis(
+                hSliced,
+                this.cropping[1][0],
+                inputs.shape[3] - this.cropping[1][1] - this.cropping[1][0],
+                4
+              );
+            }
+          });
+        }
+        getConfig() {
+          const config = { cropping: this.cropping, dataFormat: this.dataFormat };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      convolutional_Cropping2D.className = "Cropping2D";
+      dist["serialization"].registerClass(convolutional_Cropping2D);
+      class convolutional_UpSampling2D extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.DEFAULT_SIZE = [2, 2];
+          this.inputSpec = [{ ndim: 4 }];
+          this.size = args.size == null ? this.DEFAULT_SIZE : args.size;
+          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
+        }
+        computeOutputShape(inputShape) {
+          if (this.dataFormat === "channelsFirst") {
+            const height = inputShape[2] == null ? null : this.size[0] * inputShape[2];
+            const width = inputShape[3] == null ? null : this.size[1] * inputShape[3];
+            return [inputShape[0], inputShape[1], height, width];
+          } else {
+            const height = inputShape[1] == null ? null : this.size[0] * inputShape[1];
+            const width = inputShape[2] == null ? null : this.size[1] * inputShape[2];
+            return [inputShape[0], height, width, inputShape[3]];
+          }
+        }
+        call(inputs, kwargs) {
+          return dist["tidy"](() => {
+            let input = getExactlyOneTensor(inputs);
+            const inputShape = input.shape;
+            if (this.dataFormat === "channelsFirst") {
+              input = dist["transpose"](input, [0, 2, 3, 1]);
+              const height = this.size[0] * inputShape[2];
+              const width = this.size[1] * inputShape[3];
+              const resized = input.resizeNearestNeighbor([height, width]);
+              return dist["transpose"](resized, [0, 3, 1, 2]);
+            } else {
+              const height = this.size[0] * inputShape[1];
+              const width = this.size[1] * inputShape[2];
+              return input.resizeNearestNeighbor([height, width]);
+            }
+          });
+        }
+        getConfig() {
+          const config = { size: this.size, dataFormat: this.dataFormat };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      convolutional_UpSampling2D.className = "UpSampling2D";
+      dist["serialization"].registerClass(convolutional_UpSampling2D);
+      //# sourceMappingURL=convolutional.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional_depthwise.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * TensorFlow.js Layers: Depthwise Convolutional Layers
+       */
+
+      /**
+       * 2D convolution with separable filters.
+       * @param x Input tensor.
+       * @param depthwiseKernel Convolution kernel for depthwise convolution.
+       * @param strides Strides (Array of two integers).
+       * @param padding Padding model.
+       * @param dataFormat Data format.
+       * @param dilationRate Array of two integers, dilation rates for the separable
+       *   convolution.
+       * @returns Output tensor.
+       * @throws ValueError If depthwiseKernel is not a 4D array.
+       */
+      function depthwiseConv2d(
+        x,
+        depthwiseKernel,
+        strides = [1, 1],
+        padding = "valid",
+        dataFormat,
+        dilationRate
+      ) {
+        return Object(dist["tidy"])(() => {
+          if (dataFormat == null) {
+            dataFormat = imageDataFormat();
+          }
+          checkDataFormat(dataFormat);
+          let y = preprocessConv2DInput(x, dataFormat);
+          if (x.rank !== 4) {
+            throw new ValueError(
+              `Input for depthwiseConv2d is required to be 4-D, but is instead ` + `${x.rank}-D`
+            );
+          }
+          if (depthwiseKernel.rank !== 4) {
+            throw new ValueError(
+              `depthwiseKernel is required to be 4-D, but is instead ` + `${depthwiseKernel.rank}-D`
+            );
+          }
+          y = dist["depthwiseConv2d"](
+            y,
+            depthwiseKernel,
+            strides,
+            padding === "same" ? "same" : "valid",
+            "NHWC",
+            dilationRate
+          );
+          if (dataFormat === "channelsFirst") {
+            y = dist["transpose"](y, [0, 3, 1, 2]);
+          }
+          return y;
+        });
+      }
+      class convolutional_depthwise_DepthwiseConv2D extends convolutional_BaseConv {
+        constructor(args) {
+          super(2, args);
+          this.depthwiseKernel = null;
+          this.depthMultiplier = args.depthMultiplier == null ? 1 : args.depthMultiplier;
+          this.depthwiseInitializer = getInitializer(
+            args.depthwiseInitializer || this.DEFAULT_KERNEL_INITIALIZER
+          );
+          this.depthwiseConstraint = getConstraint(args.depthwiseConstraint);
+          this.depthwiseRegularizer = getRegularizer(args.depthwiseRegularizer);
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          if (inputShape.length < 4) {
+            throw new ValueError(
+              `Inputs to DepthwiseConv2D should have rank 4. ` +
+                `Received input shape: ${JSON.stringify(inputShape)}.`
+            );
+          }
+          const channelAxis = this.dataFormat === "channelsFirst" ? 1 : 3;
+          if (inputShape[channelAxis] == null || inputShape[channelAxis] < 0) {
+            throw new ValueError(
+              "The channel dimension of the inputs to DepthwiseConv2D should " +
+                `be defined, but is not (${inputShape[channelAxis]}).`
+            );
+          }
+          const inputDim = inputShape[channelAxis];
+          const depthwiseKernelShape = [
+            this.kernelSize[0],
+            this.kernelSize[1],
+            inputDim,
+            this.depthMultiplier,
+          ];
+          this.depthwiseKernel = this.addWeight(
+            "depthwise_kernel",
+            depthwiseKernelShape,
+            null,
+            this.depthwiseInitializer,
+            this.depthwiseRegularizer,
+            true,
+            this.depthwiseConstraint
+          );
+          if (this.useBias) {
+            this.bias = this.addWeight(
+              "bias",
+              [inputDim * this.depthMultiplier],
+              null,
+              this.biasInitializer,
+              this.biasRegularizer,
+              true,
+              this.biasConstraint
+            );
+          } else {
+            this.bias = null;
+          }
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = getExactlyOneTensor(inputs);
+            let outputs = depthwiseConv2d(
+              inputs,
+              this.depthwiseKernel.read(),
+              this.strides,
+              this.padding,
+              this.dataFormat,
+              null
+            );
+            // TODO(cais): Add support for dilation.
+            if (this.useBias) {
+              outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);
+            }
+            if (this.activation != null) {
+              outputs = this.activation.apply(outputs);
+            }
+            return outputs;
+          });
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const rows = this.dataFormat === "channelsFirst" ? inputShape[2] : inputShape[1];
+          const cols = this.dataFormat === "channelsFirst" ? inputShape[3] : inputShape[2];
+          const outFilters =
+            this.dataFormat === "channelsFirst"
+              ? inputShape[1] * this.depthMultiplier
+              : inputShape[3] * this.depthMultiplier;
+          const outRows = convOutputLength(rows, this.kernelSize[0], this.padding, this.strides[0]);
+          const outCols = convOutputLength(cols, this.kernelSize[1], this.padding, this.strides[1]);
+          if (this.dataFormat === "channelsFirst") {
+            return [inputShape[0], outFilters, outRows, outCols];
+          } else {
+            // In this case, assume 'channelsLast'.
+            return [inputShape[0], outRows, outCols, outFilters];
+          }
+        }
+        getConfig() {
+          const config = super.getConfig();
+          config["depthMultiplier"] = this.depthMultiplier;
+          config["depthwiseInitializer"] = serializeInitializer(this.depthwiseInitializer);
+          config["depthwiseRegularizer"] = serializeRegularizer(this.depthwiseRegularizer);
+          config["depthwiseConstraint"] = serializeConstraint(this.depthwiseRegularizer);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      convolutional_depthwise_DepthwiseConv2D.className = "DepthwiseConv2D";
+      dist["serialization"].registerClass(convolutional_depthwise_DepthwiseConv2D);
+      //# sourceMappingURL=convolutional_depthwise.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/core.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * TensorFlow.js Layers: Basic Layers.
+       */
+
+      class core_Dropout extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.rate = Math.max(Math.min(args.rate, 1), 0);
+          // So that the scalar doesn't get tidied up between executions.
+          this.noiseShape = args.noiseShape;
+          this.seed = args.seed;
+          this.supportsMasking = true;
+        }
+        getNoiseShape(input) {
+          if (this.noiseShape == null) {
+            return this.noiseShape;
+          }
+          const inputShape = input.shape;
+          const noiseShape = [];
+          for (let i = 0; i < this.noiseShape.length; ++i) {
+            noiseShape.push(this.noiseShape[i] == null ? inputShape[i] : this.noiseShape[i]);
+          }
+          return noiseShape;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            const input = getExactlyOneTensor(inputs);
+            if (0 < this.rate && this.rate < 1) {
+              const training = kwargs["training"] == null ? false : kwargs["training"];
+              const noiseShape = this.getNoiseShape(input);
+              const output = inTrainPhase(
+                () => dropout(input, this.rate, noiseShape, this.seed),
+                () => input,
+                training
+              );
+              return output;
+            }
+            return inputs;
+          });
+        }
+        getConfig() {
+          const config = {
+            rate: this.rate,
+            noiseShape: this.noiseShape,
+            seed: this.seed,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        dispose() {
+          return super.dispose();
+        }
+      }
+      /** @nocollapse */
+      core_Dropout.className = "Dropout";
+      dist["serialization"].registerClass(core_Dropout);
+      class SpatialDropout1D extends core_Dropout {
+        constructor(args) {
+          super(args);
+          this.inputSpec = [{ ndim: 3 }];
+        }
+        getNoiseShape(input) {
+          const inputShape = input.shape;
+          return [inputShape[0], 1, inputShape[2]];
+        }
+      }
+      /** @nocollapse */
+      SpatialDropout1D.className = "SpatialDropout1D";
+      dist["serialization"].registerClass(SpatialDropout1D);
+      class core_Dense extends topology_Layer {
+        constructor(args) {
+          super(args);
+          // Default activation: Linear (none).
+          this.activation = null;
+          this.useBias = true;
+          this.kernel = null;
+          this.bias = null;
+          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
+          this.DEFAULT_BIAS_INITIALIZER = "zeros";
+          if (args.batchInputShape == null && args.inputShape == null && args.inputDim != null) {
+            // This logic is copied from Layer's constructor, since we can't
+            // do exactly what the Python constructor does for Dense().
+            let batchSize = null;
+            if (args.batchSize != null) {
+              batchSize = args.batchSize;
+            }
+            this.batchInputShape = [batchSize, args.inputDim];
+          }
+          this.units = args.units;
+          assertPositiveInteger(this.units, "units");
+          this.activation = getActivation(args.activation);
+          if (args.useBias != null) {
+            this.useBias = args.useBias;
+          }
+          this.kernelInitializer = getInitializer(
+            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
+          );
+          this.biasInitializer = getInitializer(
+            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
+          );
+          this.kernelConstraint = getConstraint(args.kernelConstraint);
+          this.biasConstraint = getConstraint(args.biasConstraint);
+          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
+          this.biasRegularizer = getRegularizer(args.biasRegularizer);
+          this.activityRegularizer = getRegularizer(args.activityRegularizer);
+          this.supportsMasking = true;
+          this.inputSpec = [{ minNDim: 2 }];
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const inputLastDim = inputShape[inputShape.length - 1];
+          if (this.kernel == null) {
+            this.kernel = this.addWeight(
+              "kernel",
+              [inputLastDim, this.units],
+              null,
+              this.kernelInitializer,
+              this.kernelRegularizer,
+              true,
+              this.kernelConstraint
+            );
+            if (this.useBias) {
+              this.bias = this.addWeight(
+                "bias",
+                [this.units],
+                null,
+                this.biasInitializer,
+                this.biasRegularizer,
+                true,
+                this.biasConstraint
+              );
+            }
+          }
+          this.inputSpec = [{ minNDim: 2, axes: { [-1]: inputLastDim } }];
+          this.built = true;
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const outputShape = inputShape.slice();
+          outputShape[outputShape.length - 1] = this.units;
+          return outputShape;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            // Dense layer accepts only a single input.
+            const input = getExactlyOneTensor(inputs);
+            const fusedActivationName = mapActivationToFusedKernel(this.activation.getClassName());
+            let output;
+            if (fusedActivationName != null) {
+              output = dot(
+                input,
+                this.kernel.read(),
+                fusedActivationName,
+                this.bias ? this.bias.read() : null
+              );
+            } else {
+              output = dot(input, this.kernel.read());
+              if (this.bias != null) {
+                output = biasAdd(output, this.bias.read());
+              }
+              if (this.activation != null) {
+                output = this.activation.apply(output);
+              }
+            }
+            return output;
+          });
+        }
+        getConfig() {
+          const config = {
+            units: this.units,
+            activation: serializeActivation(this.activation),
+            useBias: this.useBias,
+            kernelInitializer: serializeInitializer(this.kernelInitializer),
+            biasInitializer: serializeInitializer(this.biasInitializer),
+            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
+            biasRegularizer: serializeRegularizer(this.biasRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            kernelConstraint: serializeConstraint(this.kernelConstraint),
+            biasConstraint: serializeConstraint(this.biasConstraint),
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      core_Dense.className = "Dense";
+      dist["serialization"].registerClass(core_Dense);
+      class core_Flatten extends topology_Layer {
+        constructor(args) {
+          args = args || {};
+          super(args);
+          this.inputSpec = [{ minNDim: 3 }];
+          this.dataFormat = args.dataFormat;
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          for (const dim of inputShape.slice(1)) {
+            if (dim == null) {
+              throw new ValueError(
+                `The shape of the input to "Flatten" is not fully defined ` +
+                  `(got ${inputShape.slice(1)}). Make sure to pass a complete ` +
+                  `"input_shape" or "batch_input_shape" argument to the first ` +
+                  `layer in your model.`
+              );
+            }
+          }
+          return [inputShape[0], arrayProd(inputShape, 1)];
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            let input = getExactlyOneTensor(inputs);
+            if (this.dataFormat === "channelsFirst" && input.rank > 1) {
+              const permutation = [0];
+              for (let i = 2; i < input.rank; ++i) {
+                permutation.push(i);
+              }
+              permutation.push(1);
+              input = input.transpose(permutation);
+            }
+            return batchFlatten(input);
+          });
+        }
+        getConfig() {
+          const config = {};
+          if (this.dataFormat != null) {
+            config["dataFormat"] = this.dataFormat;
+          }
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      core_Flatten.className = "Flatten";
+      dist["serialization"].registerClass(core_Flatten);
+      class core_Activation extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.supportsMasking = true;
+          this.activation = getActivation(args.activation);
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            const input = getExactlyOneTensor(inputs);
+            return this.activation.apply(input);
+          });
+        }
+        getConfig() {
+          const config = { activation: serializeActivation(this.activation) };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      core_Activation.className = "Activation";
+      dist["serialization"].registerClass(core_Activation);
+      class core_RepeatVector extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.n = args.n;
+          this.inputSpec = [{ ndim: 2 }];
+        }
+        computeOutputShape(inputShape) {
+          return [inputShape[0], this.n, inputShape[1]];
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = getExactlyOneTensor(inputs);
+            return repeat(inputs, this.n);
+          });
+        }
+        getConfig() {
+          const config = {
+            n: this.n,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      core_RepeatVector.className = "RepeatVector";
+      dist["serialization"].registerClass(core_RepeatVector);
+      class core_Reshape extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.targetShape = args.targetShape;
+          // Make sure that all unknown dimensions are represented as `null`.
+          for (let i = 0; i < this.targetShape.length; ++i) {
+            if (this.isUnknown(this.targetShape[i])) {
+              this.targetShape[i] = null;
+            }
+          }
+        }
+        isUnknown(dim) {
+          return dim < 0 || dim == null;
+        }
+        /**
+         * Finds and replaces a missing dimension in output shape.
+         *
+         * This is a near direct port of the internal Numpy function
+         * `_fix_unknown_dimension` in `numpy/core/src/multiarray/shape.c`.
+         *
+         * @param inputShape: Original shape of array begin reshape.
+         * @param outputShape: Target shape of the array, with at most a single
+         * `null` or negative number, which indicates an underdetermined dimension
+         * that should be derived from `inputShape` and the known dimensions of
+         *   `outputShape`.
+         * @returns: The output shape with `null` replaced with its computed value.
+         * @throws: ValueError: If `inputShape` and `outputShape` do not match.
+         */
+        fixUnknownDimension(inputShape, outputShape) {
+          const errorMsg = "Total size of new array must be unchanged.";
+          const finalShape = outputShape.slice();
+          let known = 1;
+          let unknown = null;
+          for (let i = 0; i < finalShape.length; ++i) {
+            const dim = finalShape[i];
+            if (this.isUnknown(dim)) {
+              if (unknown === null) {
+                unknown = i;
+              } else {
+                throw new ValueError("Can only specifiy one unknown dimension.");
+              }
+            } else {
+              known *= dim;
+            }
+          }
+          const originalSize = arrayProd(inputShape);
+          if (unknown !== null) {
+            if (known === 0 || originalSize % known !== 0) {
+              throw new ValueError(errorMsg);
+            }
+            finalShape[unknown] = originalSize / known;
+          } else if (originalSize !== known) {
+            throw new ValueError(errorMsg);
+          }
+          return finalShape;
+        }
+        computeOutputShape(inputShape) {
+          let anyUnknownDims = false;
+          for (let i = 0; i < inputShape.length; ++i) {
+            if (this.isUnknown(inputShape[i])) {
+              anyUnknownDims = true;
+              break;
+            }
+          }
+          if (anyUnknownDims) {
+            return inputShape.slice(0, 1).concat(this.targetShape);
+          } else {
+            return inputShape
+              .slice(0, 1)
+              .concat(this.fixUnknownDimension(inputShape.slice(1), this.targetShape));
+          }
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            const input = getExactlyOneTensor(inputs);
+            const inputShape = input.shape;
+            const outputShape = inputShape
+              .slice(0, 1)
+              .concat(this.fixUnknownDimension(inputShape.slice(1), this.targetShape));
+            return input.reshape(outputShape);
+          });
+        }
+        getConfig() {
+          const config = {
+            targetShape: this.targetShape,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      core_Reshape.className = "Reshape";
+      dist["serialization"].registerClass(core_Reshape);
+      class core_Permute extends topology_Layer {
+        constructor(args) {
+          super(args);
+          if (args.dims == null) {
+            throw new Error(
+              "Required configuration field `dims` is missing during Permute " + "constructor call."
+            );
+          }
+          if (!Array.isArray(args.dims)) {
+            throw new Error(
+              "Permute constructor requires `dims` to be an Array, but received " +
+                `${args.dims} instead.`
+            );
+          }
+          // Check the validity of the permutation indices.
+          const expectedSortedIndices = range(1, args.dims.length + 1);
+          if (!dist["util"].arraysEqual(args.dims.slice().sort(), expectedSortedIndices)) {
+            throw new Error(
+              "Invalid permutation `dims`: " +
+                JSON.stringify(args.dims) +
+                " `dims` must contain consecutive integers starting from 1."
+            );
+          }
+          this.dims = args.dims;
+          this.dimsIncludingBatch = [0].concat(this.dims);
+          this.inputSpec = [new InputSpec({ ndim: this.dims.length + 1 })];
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const outputShape = inputShape.slice();
+          this.dims.forEach((dim, i) => {
+            outputShape[i + 1] = inputShape[dim];
+          });
+          return outputShape;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["transpose"])(getExactlyOneTensor(inputs), this.dimsIncludingBatch);
+        }
+        getConfig() {
+          const config = {
+            dims: this.dims,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      core_Permute.className = "Permute";
+      dist["serialization"].registerClass(core_Permute);
+      class core_Masking extends topology_Layer {
+        constructor(args) {
+          super(args == null ? {} : args);
+          this.supportsMasking = true;
+          if (args != null) {
+            this.maskValue = args.maskValue == null ? 0 : args.maskValue;
+          } else {
+            this.maskValue = 0;
+          }
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const baseConfig = super.getConfig();
+          const config = { maskValue: this.maskValue };
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        computeMask(inputs, mask) {
+          const input = getExactlyOneTensor(inputs);
+          const axis = -1;
+          return Object(dist["any"])(Object(dist["notEqual"])(input, this.maskValue), axis);
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            const input = getExactlyOneTensor(inputs);
+            const axis = -1;
+            const keepDims = true;
+            const booleanMask = Object(dist["any"])(
+              Object(dist["notEqual"])(input, this.maskValue),
+              axis,
+              keepDims
+            );
+            const output = input.mul(booleanMask.asType(input.dtype));
+            return output;
+          });
+        }
+      }
+      /** @nocollapse */
+      core_Masking.className = "Masking";
+      dist["serialization"].registerClass(core_Masking);
+      //# sourceMappingURL=core.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/embeddings.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * TensorFlow.js Layers: Embedding Layer.
+       *
+       * Original source: keras/constraints.py
+       */
+
+      class embeddings_Embedding extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.embeddings = null;
+          this.DEFAULT_EMBEDDINGS_INITIALIZER = "randomUniform";
+          if (args.batchInputShape == null && args.inputShape == null) {
+            // Porting Note: This logic is copied from Layer's constructor, since we
+            // can't do exactly what the Python constructor does for Embedding().
+            // Specifically, the super constructor can not be called after the
+            // mutation of the `config` argument.
+            let batchSize = null;
+            if (args.batchSize != null) {
+              batchSize = args.batchSize;
+            }
+            if (args.inputLength == null) {
+              // Fix super-constructor to what it would have done if
+              // 'config.inputShape' were (None, )
+              this.batchInputShape = [batchSize, null];
+            } else {
+              // Fix super-constructor to what it would have done if
+              // 'config.inputShape' were (config.inputLength, )
+              this.batchInputShape = [batchSize].concat(toList(args.inputLength));
+            }
+          }
+          this.inputDim = args.inputDim;
+          assertPositiveInteger(this.inputDim, "inputDim");
+          this.outputDim = args.outputDim;
+          assertPositiveInteger(this.outputDim, "outputDim");
+          this.embeddingsInitializer = getInitializer(
+            args.embeddingsInitializer || this.DEFAULT_EMBEDDINGS_INITIALIZER
+          );
+          this.embeddingsRegularizer = getRegularizer(args.embeddingsRegularizer);
+          this.activityRegularizer = getRegularizer(args.activityRegularizer);
+          this.embeddingsConstraint = getConstraint(args.embeddingsConstraint);
+          this.maskZero = args.maskZero;
+          this.supportsMasking = args.maskZero;
+          this.inputLength = args.inputLength;
+        }
+        build(inputShape) {
+          this.embeddings = this.addWeight(
+            "embeddings",
+            [this.inputDim, this.outputDim],
+            this.dtype,
+            this.embeddingsInitializer,
+            this.embeddingsRegularizer,
+            true,
+            this.embeddingsConstraint
+          );
+          this.built = true;
+        }
+        // Override warnOnIncompatibleInputShape because an embedding layer allows
+        // the input to have varying ranks.
+        warnOnIncompatibleInputShape(inputShape) {}
+        computeMask(inputs, mask) {
+          return Object(dist["tidy"])(() => {
+            if (!this.maskZero) {
+              return null;
+            } else {
+              inputs = getExactlyOneTensor(inputs);
+              return Object(dist["notEqual"])(inputs, Object(dist["zerosLike"])(inputs));
+            }
+          });
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          if (this.inputLength == null) {
+            return [...inputShape, this.outputDim];
+          }
+          // inputLength can be an array if input is 3D or higher.
+          const inLens = toList(this.inputLength);
+          if (inLens.length !== inputShape.length - 1) {
+            throw new ValueError(
+              `"inputLength" is ${this.inputLength}, but received ` +
+                `input shape has shape ${inputShape}`
+            );
+          } else {
+            let i = 0;
+            for (let k = 0; k < inLens.length; ++k) {
+              const s1 = inLens[k];
+              const s2 = inputShape[k + 1];
+              if (s1 != null && s2 != null && s1 !== s2) {
+                throw new ValueError(
+                  `"inputLength" is ${this.inputLength}, but received ` +
+                    `input shape has shape ${inputShape}`
+                );
+              } else if (s1 == null) {
+                inLens[i] = s2;
+              }
+              i++;
+            }
+          }
+          return [inputShape[0], ...inLens, this.outputDim];
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            // Embedding layer accepts only a single input.
+            let input = getExactlyOneTensor(inputs);
+            if (input.dtype !== "int32") {
+              input = cast(input, "int32");
+            }
+            const output = gather(this.embeddings.read(), input.as1D());
+            return output.reshape(getExactlyOneShape(this.computeOutputShape(input.shape)));
+          });
+        }
+        getConfig() {
+          const config = {
+            inputDim: this.inputDim,
+            outputDim: this.outputDim,
+            embeddingsInitializer: serializeInitializer(this.embeddingsInitializer),
+            embeddingsRegularizer: serializeRegularizer(this.embeddingsRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            embeddingsConstraint: serializeConstraint(this.embeddingsConstraint),
+            maskZero: this.maskZero,
+            inputLength: this.inputLength,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      embeddings_Embedding.className = "Embedding";
+      dist["serialization"].registerClass(embeddings_Embedding);
+      //# sourceMappingURL=embeddings.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/merge.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * TensorFlow.js Layers: Merge Layers.
+       */
+
+      /**
+       * Generic Merge layer for element-wise merge functions.
+       *
+       * Used to implement `Sum`, `Average`, `Concatenate`, etc.
+       */
+      class merge_Merge extends topology_Layer {
+        constructor(args) {
+          super(args || {});
+          this.supportsMasking = true;
+        }
+        /**
+         * Logic for merging multiple tensors, to be overridden by subclasses.
+         * @param inputs
+         */
+        mergeFunction(inputs) {
+          throw new NotImplementedError();
+        }
+        /**
+         * Computes the shape of the result of an elementwise operation.
+         *
+         * @param shape1: Shape of the first tensor.
+         * @param shape2: Shape of the second tensor.
+         * @returns Expected output shape when an elementwise operation is carried
+         *   out on 2 tensors with shapes `shape1` and `shape2`.
+         * @throws ValueError: If `shape1` and `shape2` are not compatible for
+         *   element-wise operations.
+         */
+        computeElementwiseOpOutputShape(shape1, shape2) {
+          if (shape1 == null || shape2 == null) {
+            return null;
+          } else if (shape1.length < shape2.length) {
+            return this.computeElementwiseOpOutputShape(shape2, shape1);
+          } else if (shape2.length === 0) {
+            return shape1;
+          }
+          const outputShape = shape1.slice(0, shape1.length - shape2.length);
+          for (let k = 0; k < shape2.length; ++k) {
+            const i = shape1[shape1.length - shape2.length + k];
+            const j = shape2[k];
+            if (i == null || j == null || i < 0 || j < 0) {
+              outputShape.push(null);
+            } else if (i === 1) {
+              outputShape.push(j);
+            } else if (j === 1) {
+              outputShape.push(i);
+            } else {
+              if (i !== j) {
+                throw new ValueError(
+                  "Operands could not be broadcast together with shapes " +
+                    JSON.stringify(shape1) +
+                    " " +
+                    JSON.stringify(shape2)
+                );
+              }
+              outputShape.push(i);
+            }
+          }
+          return outputShape;
+        }
+        build(inputShape) {
+          // Used purely for shape validation.
+          if (Array.isArray(inputShape) && !Array.isArray(inputShape[0])) {
+            // Make sure that inputShape is an Array of shape.
+            inputShape = [getExactlyOneShape(inputShape)];
+          }
+          inputShape = inputShape;
+          if (inputShape.length < 2) {
+            throw new ValueError(
+              "A merge layer should be called on an Array of at least 2 inputs." +
+                ` Got ${inputShape.length} input(s).`
+            );
+          }
+          // Make sure that there is at most one unique batch size among the input
+          // shapes.
+          let batchSizes = [];
+          for (const shape of inputShape) {
+            if (shape != null && shape[0] !== null) {
+              batchSizes.push(shape[0]);
+            }
+          }
+          batchSizes = unique(batchSizes);
+          if (batchSizes.length > 1) {
+            throw new ValueError(
+              `Can not merge tensors with different batch sizes. ` +
+                `Got tensors with shapes: ${JSON.stringify(inputShape)}.`
+            );
+          }
+          let outputShape = inputShape[0] == null ? null : inputShape[0].slice(1);
+          for (let i = 1; i < inputShape.length; ++i) {
+            const shape = inputShape[i] == null ? null : inputShape[i].slice(1);
+            outputShape = this.computeElementwiseOpOutputShape(outputShape, shape);
+          }
+          // If the inputs have different ranks, we have to reshape them to make them
+          // broadcastable.
+          const allRanks = inputShape.map((shape) => shape.length);
+          if (inputShape.indexOf(null) === -1 && unique(allRanks).length === 1) {
+            this.reshapeRequired = false;
+          } else {
+            this.reshapeRequired = true;
+          }
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = inputs;
+            if (this.reshapeRequired) {
+              const reshapedInputs = [];
+              const inputDims = inputs.map((input) => input.rank);
+              if (inputDims.indexOf(null) === -1) {
+                // If ranks of all inputs are available, we simply expand each of them
+                // at axis=1 until all of them have the same rank.
+                const maxNDim = max(inputDims);
+                for (let x of inputs) {
+                  const xNDim = x.rank;
+                  for (let k = 0; k < maxNDim - xNDim; ++k) {
+                    x = expandDims(x, 1);
+                  }
+                  reshapedInputs.push(x);
+                }
+                return this.mergeFunction(reshapedInputs);
+              } else {
+                // Transpose all inputs so that batch size is the last dimension.
+                // [batchSize, dim1, dim2, ...] -> [dim1, dim2, ..., batchSize]
+                let transposed = false;
+                for (const x of inputs) {
+                  const xNDim = x.rank;
+                  if (xNDim == null) {
+                    const xShape = x.shape;
+                    const batchSize = xShape[0];
+                    const newShape = xShape.slice(1).concat([batchSize]);
+                    let xTransposed = x.reshape([batchSize].concat(arrayProd(xShape.slice(1))));
+                    xTransposed = dist["transpose"](xTransposed, [1, 0]);
+                    xTransposed = xTransposed.reshape(newShape);
+                    reshapedInputs.push(xTransposed);
+                    transposed = true;
+                  } else if (xNDim > 1) {
+                    const dims = range(1, xNDim).concat([0]);
+                    reshapedInputs.push(dist["transpose"](x, dims));
+                    transposed = true;
+                  } else {
+                    // We don't transpose inputs if they are 1D vectors or scalars.
+                    reshapedInputs.push(x);
+                  }
+                }
+                let y = this.mergeFunction(reshapedInputs);
+                const yNDim = y.rank;
+                if (transposed) {
+                  // If inputs have been transposed, we have to transpose the output
+                  // too.
+                  if (yNDim == null) {
+                    const yShape = y.shape;
+                    const yNDim = yShape.length;
+                    const batchSize = yShape[yNDim - 1];
+                    const newShape = [batchSize].concat(yShape.slice(0, yShape.length - 1));
+                    y = dist["transpose"](y.reshape([-1, batchSize]), [1, 0]).reshape(newShape);
+                  } else if (yNDim > 1) {
+                    const dims = [yNDim - 1].concat(range(0, yNDim - 1));
+                    y = dist["transpose"](y, dims);
+                  }
+                }
+                return y;
+              }
+            } else {
+              return this.mergeFunction(inputs);
+            }
+          });
+        }
+        computeOutputShape(inputShape) {
+          inputShape = inputShape;
+          let outputShape;
+          if (inputShape[0] == null) {
+            outputShape = null;
+          } else {
+            outputShape = inputShape[0].slice(1);
+          }
+          for (let i = 1; i < inputShape.length; ++i) {
+            const shape = inputShape[i] == null ? null : inputShape[i].slice(1);
+            outputShape = this.computeElementwiseOpOutputShape(outputShape, shape);
+          }
+          let batchSizes = [];
+          for (const shape of inputShape) {
+            if (shape != null && shape[0] !== null) {
+              batchSizes.push(shape[0]);
+            }
+          }
+          batchSizes = unique(batchSizes);
+          if (batchSizes.length === 1) {
+            outputShape = batchSizes.concat(outputShape);
+          } else {
+            outputShape = [null].concat(outputShape);
+          }
+          return outputShape;
+        }
+        computeMask(inputs, mask) {
+          return dist["tidy"](() => {
+            if (mask == null) {
+              return null;
+            }
+            if (!Array.isArray(mask)) {
+              throw new ValueError("`mask` should be an Array");
+            }
+            if (!Array.isArray(inputs)) {
+              throw new ValueError("`inputs` should be an Array");
+            }
+            if (mask.length !== inputs.length) {
+              throw new ValueError(
+                `The Array 'inputs' and 'mask' are expected to have the same ` +
+                  `length, but have different lengths ` +
+                  `(${inputs.length} vs ${mask.length})`
+              );
+            }
+            if (mask.every((m) => m == null)) {
+              return null;
+            }
+            mask = mask.map((m) => (m == null ? m : dist["expandDims"](m, 0)));
+            let output = mask[0];
+            for (let i = 1; i < mask.length - 1; ++i) {
+              output = dist["logicalAnd"](output, mask[i]);
+            }
+            return output;
+          });
+        }
+      }
+      class merge_Add extends merge_Merge {
+        constructor(args) {
+          super(args);
+        }
+        mergeFunction(inputs) {
+          return Object(dist["tidy"])(() => {
+            let output = inputs[0].clone();
+            for (let i = 1; i < inputs.length; ++i) {
+              output = dist["add"](output, inputs[i]);
+            }
+            return output;
+          });
+        }
+      }
+      /** @nocollapse */
+      merge_Add.className = "Add";
+      dist["serialization"].registerClass(merge_Add);
+      /**
+       * Calculate the element-wise sum of inputs, which all have the same shape.
+       *
+       * This function can be invoked in three ways.
+       *
+       * 1. Construct an instance of `Add` layer, by using no input argument
+       *    or a single configuration argument. The resultant `Add` layer can then
+       *    be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
+       *
+       * ```js
+       * const addLayer = tf.layers.add();
+       *
+       * // The layer can be applied to inputs.
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = addLayer.apply([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.SymbolicTensor`. For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = tf.layers.add([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.Tensor` as the result of the computation. For
+       * example:
+       *
+       * ```js
+       * const input1 = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       * const input2 = tf.tensor2d([10, 20, 30, 40], [2, 2]);
+       * tf.layers.add([input1, input2]).print();
+       * // Gives [[11, 22], [33, 44]].
+       *
+       */
+      function add(config) {
+        if (Array.isArray(config)) {
+          const layer = new merge_Add({});
+          return layer.apply(config);
+        } else {
+          return new merge_Add(config);
+        }
+      }
+      class merge_Multiply extends merge_Merge {
+        constructor(args) {
+          super(args);
+        }
+        mergeFunction(inputs) {
+          return Object(dist["tidy"])(() => {
+            let output = inputs[0].clone();
+            for (let i = 1; i < inputs.length; ++i) {
+              output = dist["mul"](output, inputs[i]);
+            }
+            return output;
+          });
+        }
+      }
+      /** @nocollapse */
+      merge_Multiply.className = "Multiply";
+      dist["serialization"].registerClass(merge_Multiply);
+      /**
+       * Calculate the element-wise product of inputs, which all have the same shape.
+       *
+       * This function can be invoked in three ways.
+       *
+       * 1. Construct an instance of `Multiply` layer, by using no input argument
+       *    or a single configuration argument. The resultant `Multiply` layer can
+       *    then be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
+       *
+       * ```js
+       * const multiplyLayer = tf.layers.multiply();
+       *
+       * // The layer can be applied to inputs.
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = multiplyLayer.apply([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.SymbolicTensor`. For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = tf.layers.multiply([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.Tensor` as the result of the computation. For
+       * example:
+       *
+       * ```js
+       * const input1 = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       * const input2 = tf.tensor2d([10, 20, 30, 40], [2, 2]);
+       * tf.layers.multiply([input1, input2]).print();
+       * // Gives [[10, 40], [90, 160]].
+       *
+       */
+      function multiply(config) {
+        if (Array.isArray(config)) {
+          const layer = new merge_Multiply({});
+          return layer.apply(config);
+        } else {
+          return new merge_Multiply(config);
+        }
+      }
+      class merge_Average extends merge_Merge {
+        constructor(args) {
+          super(args);
+        }
+        mergeFunction(inputs) {
+          return Object(dist["tidy"])(() => {
+            let output = inputs[0].clone();
+            for (let i = 1; i < inputs.length; ++i) {
+              output = dist["add"](output, inputs[i]);
+            }
+            return dist["mul"](1 / inputs.length, output);
+          });
+        }
+      }
+      /** @nocollapse */
+      merge_Average.className = "Average";
+      dist["serialization"].registerClass(merge_Average);
+      /**
+       * Calculate the element-wise arithmetic mean of inputs, which all have the same
+       * shape.
+       *
+       * This function can be invoked in three ways.
+       *
+       * 1. Construct an instance of `Average` layer, by using no input argument
+       *    or a single configuration argument. The resultant `Average` layer can then
+       *    be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
+       *
+       * ```js
+       * const averageLayer = tf.layers.average();
+       *
+       * // The layer can be applied to inputs.
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = averageLayer.apply([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.SymbolicTensor`. For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = tf.layers.average([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.Tensor` as the result of the computation. For
+       * example:
+       *
+       * ```js
+       * const input1 = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       * const input2 = tf.tensor2d([10, 20, 30, 40], [2, 2]);
+       * tf.layers.average([input1, input2]).print();
+       * // Gives [[5.5, 11], [16.5, 22]].
+       *
+       */
+      function average(config) {
+        if (Array.isArray(config)) {
+          const layer = new merge_Average({});
+          return layer.apply(config);
+        } else {
+          return new merge_Average(config);
+        }
+      }
+      class merge_Maximum extends merge_Merge {
+        constructor(args) {
+          super(args);
+        }
+        mergeFunction(inputs) {
+          return Object(dist["tidy"])(() => {
+            let output = inputs[0];
+            for (let i = 1; i < inputs.length; ++i) {
+              output = dist["maximum"](output, inputs[i]);
+            }
+            return output;
+          });
+        }
+      }
+      /** @nocollapse */
+      merge_Maximum.className = "Maximum";
+      dist["serialization"].registerClass(merge_Maximum);
+      /**
+       * Calculate the element-wise maximum of inputs, which all have the same shape.
+       *
+       * This function can be invoked in three ways.
+       *
+       * 1. Construct an instance of `Maximum` layer, by using no input argument
+       *    or a single configuration argument. The resultant `Maximum` layer can then
+       *    be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
+       *
+       * ```js
+       * const maximumLayer = tf.layers.maximum();
+       *
+       * // The layer can be applied to inputs.
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = maximumLayer.apply([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.SymbolicTensor`. For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = tf.layers.maximum([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.Tensor` as the result of the computation. For
+       * example:
+       *
+       * ```js
+       * const input1 = tf.tensor2d([1, 20, 3, 40], [2, 2]);
+       * const input2 = tf.tensor2d([10, 2, 30, 4], [2, 2]);
+       * tf.layers.maximum([input1, input2]).print();
+       * // Gives [[10, 20], [30, 40]].
+       *
+       */
+      function maximum(config) {
+        if (Array.isArray(config)) {
+          const layer = new merge_Maximum({});
+          return layer.apply(config);
+        } else {
+          return new merge_Maximum(config);
+        }
+      }
+      class merge_Minimum extends merge_Merge {
+        constructor(args) {
+          super(args);
+        }
+        mergeFunction(inputs) {
+          return Object(dist["tidy"])(() => {
+            let output = inputs[0];
+            for (let i = 1; i < inputs.length; ++i) {
+              output = dist["minimum"](output, inputs[i]);
+            }
+            return output;
+          });
+        }
+      }
+      /** @nocollapse */
+      merge_Minimum.className = "Minimum";
+      dist["serialization"].registerClass(merge_Minimum);
+      /**
+       * Calculate the element-wise minimum of inputs, which all have the same shape.
+       *
+       * This function can be invoked in three ways.
+       *
+       * 1. Construct an instance of `Minimum` layer, by using no input argument
+       *    or a single configuration argument. The resultant `Minimum` layer can then
+       *    be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
+       *
+       * ```js
+       * const minimumLayer = tf.layers.minimum();
+       *
+       * // The layer can be applied to inputs.
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = minimumLayer.apply([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.SymbolicTensor`. For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const output = tf.layers.minimum([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       *
+       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.Tensor` as the result of the computation. For
+       * example:
+       *
+       * ```js
+       * const input1 = tf.tensor2d([1, 20, 3, 40], [2, 2]);
+       * const input2 = tf.tensor2d([10, 2, 30, 4], [2, 2]);
+       * tf.layers.minimum([input1, input2]).print();
+       * // Gives [[1, 2], [3, 4]].
+       *
+       */
+      function minimum(config) {
+        if (Array.isArray(config)) {
+          const layer = new merge_Minimum({});
+          return layer.apply(config);
+        } else {
+          return new merge_Minimum(config);
+        }
+      }
+      class merge_Concatenate extends merge_Merge {
+        constructor(args) {
+          super(args);
+          this.DEFAULT_AXIS = -1;
+          if (args == null) {
+            args = {};
+          }
+          this.axis = args.axis == null ? this.DEFAULT_AXIS : args.axis;
+          this.supportsMasking = true;
+          this.reshapeRequired = false;
+        }
+        build(inputShape) {
+          // Used purely for shape validation.]
+          if (
+            !(Array.isArray(inputShape) && Array.isArray(inputShape[0])) ||
+            inputShape.length === 1
+          ) {
+            throw new ValueError(
+              "A `Concatenate` layer should be called on a list of at least 2 " + "inputs"
+            );
+          }
+          inputShape = inputShape;
+          let allNoneShape = true;
+          for (const shape of inputShape) {
+            if (shape != null) {
+              allNoneShape = false;
+              break;
+            }
+          }
+          if (allNoneShape) {
+            return;
+          }
+          const shapeSet = [];
+          for (let i = 0; i < inputShape.length; ++i) {
+            const shapeWithoutConcatAxis = inputShape[i].slice();
+            shapeWithoutConcatAxis.splice(this.axis, 1);
+            let exists = false;
+            for (const shape of shapeSet) {
+              if (dist["util"].arraysEqual(shape, shapeWithoutConcatAxis)) {
+                exists = true;
+                break;
+              }
+            }
+            if (!exists) {
+              shapeSet.push(shapeWithoutConcatAxis);
+            }
+          }
+          if (shapeSet.length > 1) {
+            throw new ValueError(
+              "A `Concatenate` layer requires inputs with matching shapes " +
+                "except for the concat axis. Got input shapes: " +
+                JSON.stringify(inputShape)
+            );
+          }
+        }
+        mergeFunction(inputs) {
+          return Object(dist["tidy"])(() => {
+            return concatenate(inputs, this.axis);
+          });
+        }
+        computeOutputShape(inputShape) {
+          if (!(Array.isArray(inputShape) && Array.isArray(inputShape[0]))) {
+            throw new ValueError("A `Concatenate` layer should be called on a list of inputs.");
+          }
+          const inputShapes = inputShape;
+          const outputShape = inputShapes[0].slice();
+          const axis = this.axis < 0 ? outputShape.length + this.axis : this.axis;
+          // Porting Note: the line above is because TypeScript doesn't support
+          //   negative indices.
+          for (const shape of inputShapes.slice(1)) {
+            if (outputShape[axis] == null || shape[axis] == null) {
+              outputShape[axis] = null;
+              break;
+            }
+            outputShape[axis] += shape[axis];
+          }
+          return outputShape;
+        }
+        computeMask(inputs, mask) {
+          if (mask == null) {
+            return null;
+          }
+          if (!Array.isArray(mask)) {
+            throw new ValueError("`mask` should be an array for Concatenate");
+          }
+          if (!Array.isArray(inputs)) {
+            throw new ValueError("`inputs` should be an array for Concatenate");
+          }
+          if (mask.length !== inputs.length) {
+            throw new ValueError(
+              `Mismatch in the length of mask (${mask.length}) ` +
+                `and the legnth of inputs (${inputs.length})`
+            );
+          }
+          return dist["tidy"](() => {
+            let allNullMasks = true;
+            mask.forEach((m) => {
+              if (m != null) {
+                allNullMasks = false;
+                return;
+              }
+            });
+            if (allNullMasks) {
+              return null;
+            }
+            const outputMasks = [];
+            for (let i = 0; i < inputs.length; ++i) {
+              if (mask[i] == null) {
+                // Input is unmasked. Append all 1's to masks.
+                outputMasks.push(dist["onesLike"](inputs[i]).asType("bool"));
+              } else if (mask[i].rank < inputs[i].rank) {
+                // Mask is smaller than the input, expand it.
+                outputMasks.push(dist["expandDims"](mask[i], -1));
+              } else {
+                outputMasks.push(mask[i]);
+              }
+            }
+            const concatenatedMasks = dist["concat"](outputMasks, this.axis);
+            return dist["all"](concatenatedMasks, -1, false);
+          });
+        }
+        getConfig() {
+          const config = {
+            axis: this.axis,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      merge_Concatenate.className = "Concatenate";
+      dist["serialization"].registerClass(merge_Concatenate);
+      /**
+       * Concatenate an `Array` of inputs.
+       *
+       * This function can be invoked in three ways.
+       *
+       * 1. Construct an instance of `Concatenate` layer, by using no input argument
+       *    or a single configuration argument. The resultant `Concatenate` layer can
+       *    then be used on `tf.SymbolicTensor`s or `tf.Tensor`s. For example:
+       *
+       * ```js
+       * const concatLayer = tf.layers.concatenate();
+       *
+       * // The layer can be applied to inputs.
+       * const input1 = tf.input({shape: [2, 3]});
+       * const input2 = tf.input({shape: [2, 4]});
+       * const output = concatLayer.apply([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 7], with the first dimension as the undetermined batch
+       * // dimension and the last dimension as the result of concatenating the
+       * // last dimensions of the two inputs.
+       * ```
+       *
+       * 2. Invoke directly on an `Array` of `tf.SymbolicTensor`s. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.SymbolicTensor`. For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 3]});
+       * const input2 = tf.input({shape: [2, 4]});
+       * const output = tf.layers.concatenate([input1, input2]);
+       * console.log(output.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension and the last dimension as the result of concatenating the
+       * // last dimensions of the two inputs.
+       * ```
+       *
+       * 3. Invoke directly on `tf.Tensor`s, i.e., concrete values. This constructs
+       *    an `Layer` object internally and calls its `apply` method on the inputs,
+       *    generating a new `tf.Tensor` as the result of the computation. For
+       * example:
+       *
+       * ```js
+       * const input1 = tf.tensor2d([[1, 2], [3, 4]], [2, 2]);
+       * const input2 = tf.tensor2d([[10, 20], [30, 40]], [2, 2]);
+       * tf.layers.concatenate([input1, input2]).print();
+       * // Gives [[1, 2, 10, 20], [3, 4, 30, 40]].
+       *
+       */
+      function merge_concatenate(config) {
+        if (Array.isArray(config)) {
+          const layer = new merge_Concatenate({});
+          return layer.apply(config);
+        } else {
+          return new merge_Concatenate(config);
+        }
+      }
+      /**
+       * Interpretable potentially negative axis index.
+       *
+       * For example, given axis = -1, and dim = 3, this function will return 2.
+       *
+       * @param axis The axis index, may be a positive, zero or negative integer.
+       * @param dim Total number of dimensions, a positive integer.
+       * @returns A non-negative axis index equivalent to the input `axis`.
+       */
+      function interpretAxis(axis, dim) {
+        while (axis < 0) {
+          axis += dim;
+        }
+        return axis;
+      }
+      function batchDot(x, y, axes) {
+        if (x.shape.length > 3 || y.shape.length > 3) {
+          throw new NotImplementedError(
+            "batchDot is not implemented for tensors of 4D or higher rank yet"
+          );
+        }
+        dist["util"].assert(
+          x.shape.length >= 2,
+          () => `batchDot requires the rank of x to be >= 2, ` + `but got ${x.shape.length}`
+        );
+        dist["util"].assert(
+          x.shape.length >= 2,
+          () => `batchDot requires the rank of y to be >= 2, ` + `but got ${y.shape.length}`
+        );
+        if (typeof axes === "number") {
+          axes = [axes, axes];
+        }
+        if (x.dtype === "complex64" || y.dtype === "complex64") {
+          throw new NotImplementedError(
+            "batchDot is not implemented for complex64-type Tensors yet."
+          );
+        }
+        const xNDim = x.shape.length;
+        const yNDim = y.shape.length;
+        if (axes == null) {
+          // Behave like batchMatmul by default.
+          axes = [xNDim - 1, yNDim - 2];
+        }
+        const axesArray = axes;
+        return dist["tidy"](() => {
+          let diff;
+          if (xNDim > yNDim) {
+            diff = xNDim - yNDim;
+            const diffShape = [];
+            for (let i = 0; i < diff; ++i) {
+              diffShape.push(1);
+            }
+            y = y.reshape(y.shape.concat(diffShape));
+          } else if (yNDim > xNDim) {
+            diff = yNDim - xNDim;
+            const diffShape = [];
+            for (let i = 0; i < diff; ++i) {
+              diffShape.push(1);
+            }
+            x = x.reshape(x.shape.concat(diffShape));
+          } else {
+            diff = 0;
+          }
+          let out;
+          if (x.shape.length === 2 && y.shape.length === 2) {
+            if (axesArray[0] === axesArray[1]) {
+              out = x.mul(y).sum(axesArray[0]);
+            } else {
+              out = x.transpose([1, 0]).mul(y).sum(axesArray[1]);
+            }
+          } else {
+            const adjX = axesArray[0] !== x.shape.length - 1;
+            const adjY = axesArray[1] === y.shape.length - 1;
+            out = x.matMul(y, adjX, adjY);
+          }
+          if (diff > 0) {
+            let idx;
+            if (xNDim > yNDim) {
+              idx = xNDim + yNDim - 3;
+            } else {
+              idx = xNDim - 1;
+            }
+            const squeezeAxes = [];
+            for (let i = idx; i < idx + diff; ++i) {
+              squeezeAxes.push(i);
+            }
+            out = out.squeeze(squeezeAxes);
+          }
+          if (out.shape.length === 1) {
+            out = out.expandDims(1);
+          }
+          return out;
+        });
+      }
+      class merge_Dot extends merge_Merge {
+        constructor(args) {
+          super(args);
+          this.axes = args.axes;
+          this.normalize = args.normalize == null ? false : args.normalize;
+          this.supportsMasking = true;
+          this.reshapeRequired = false;
+        }
+        build(inputShape) {
+          dist["util"].assert(
+            Array.isArray(inputShape) &&
+              inputShape.length === 2 &&
+              Array.isArray(inputShape[0]) &&
+              Array.isArray(inputShape[1]),
+            () => "A `Dot` layer should be called on a list of exactly 2 inputs."
+          );
+          const shape1 = inputShape[0];
+          const shape2 = inputShape[1];
+          if (shape1.length > 3 || shape2.length > 3) {
+            throw new NotImplementedError(
+              "Dot layer does not support tensors of 4D or higher rank yet."
+            );
+          }
+          const axes = this.interpretAxes(shape1, shape2);
+          if (shape1[axes[0]] !== shape2[axes[1]]) {
+            throw new ValueError(
+              `Dimension incompatibility: ` + `${shape1[axes[0]]} !== ${shape2[axes[1]]}`
+            );
+          }
+        }
+        mergeFunction(inputs) {
+          if (inputs.length !== 2) {
+            throw new ValueError(
+              "A `Dot` layer must be called on exactly 2 inputs, " +
+                `but received ${inputs.length} input(s).`
+            );
+          }
+          let x1 = inputs[0];
+          let x2 = inputs[1];
+          let axes;
+          if (!Array.isArray(this.axes)) {
+            axes = [
+              interpretAxis(this.axes, x1.shape.length),
+              interpretAxis(this.axes, x2.shape.length),
+            ];
+          } else {
+            axes = this.axes.map((axis, i) => interpretAxis(axis, inputs[i].shape.length));
+          }
+          if (this.normalize) {
+            x1 = l2Normalize(x1, axes[0]);
+            x2 = l2Normalize(x2, axes[1]);
+          }
+          return batchDot(x1, x2, axes);
+        }
+        interpretAxes(shape1, shape2) {
+          let axes;
+          if (!Array.isArray(this.axes)) {
+            // `this.axes` is a single integer.
+            axes = [
+              interpretAxis(this.axes, shape1.length),
+              interpretAxis(this.axes, shape2.length),
+            ];
+          } else {
+            // `this.axes` is an Array of integers.
+            axes = this.axes;
+          }
+          return axes;
+        }
+        computeOutputShape(inputShape) {
+          dist["util"].assert(
+            Array.isArray(inputShape) &&
+              inputShape.length === 2 &&
+              Array.isArray(inputShape[0]) &&
+              Array.isArray(inputShape[1]),
+            () => "A `Dot` layer should be called on a list of exactly 2 inputs."
+          );
+          const shape1 = inputShape[0].slice();
+          const shape2 = inputShape[1].slice();
+          if (shape1.length > 3 || shape2.length > 3) {
+            throw new NotImplementedError(
+              "Dot layer does not support tensors of 4D or higher rank yet."
+            );
+          }
+          const axes = this.interpretAxes(shape1, shape2);
+          shape1.splice(axes[0], 1);
+          shape2.splice(axes[1], 1);
+          shape2.splice(0, 1);
+          const outputShape = shape1.concat(shape2);
+          if (outputShape.length === 1) {
+            outputShape.push(1);
+          }
+          return outputShape;
+        }
+        computeMask(inputs, mask) {
+          return null;
+        }
+        getConfig() {
+          const config = {
+            axes: this.axes,
+            normalize: this.normalize,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      merge_Dot.className = "Dot";
+      dist["serialization"].registerClass(merge_Dot);
+      // TODO(cais): Add functional interfaces for the merge layers.
+      //# sourceMappingURL=merge.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/noise.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * TensorFlow.js Layers: Noise Layers.
+       */
+
+      class noise_GaussianNoise extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.supportsMasking = true;
+          this.stddev = args.stddev;
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const baseConfig = super.getConfig();
+          const config = { stddev: this.stddev };
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            const input = getExactlyOneTensor(inputs);
+            const noised = () => randomNormal(input.shape, 0, this.stddev).add(input);
+            const output = inTrainPhase(noised, () => input, kwargs["training"] || false);
+            return output;
+          });
+        }
+      }
+      /** @nocollapse */
+      noise_GaussianNoise.className = "GaussianNoise";
+      dist["serialization"].registerClass(noise_GaussianNoise);
+      class noise_GaussianDropout extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.supportsMasking = true;
+          this.rate = args.rate;
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const baseConfig = super.getConfig();
+          const config = { rate: this.rate };
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            const input = getExactlyOneTensor(inputs);
+            if (this.rate > 0 && this.rate < 1) {
+              const noised = () => {
+                const stddev = Math.sqrt(this.rate / (1 - this.rate));
+                return input.mul(randomNormal(input.shape, 1, stddev));
+              };
+              return inTrainPhase(noised, () => input, kwargs["training"] || false);
+            }
+            return input;
+          });
+        }
+      }
+      /** @nocollapse */
+      noise_GaussianDropout.className = "GaussianDropout";
+      dist["serialization"].registerClass(noise_GaussianDropout);
+      /**
+       * Applies Alpha Dropout to the input.
+       *
+       * As it is a regularization layer, it is only active at training time.
+       *
+       * Alpha Dropout is a `Dropout` that keeps mean and variance of inputs
+       * to their original values, in order to ensure the self-normalizing property
+       * even after this dropout.
+       * Alpha Dropout fits well to Scaled Exponential Linear Units
+       * by randomly setting activations to the negative saturation value.
+       *
+       * Arguments:
+       *   - `rate`: float, drop probability (as with `Dropout`).
+       *     The multiplicative noise will have
+       *     standard deviation `sqrt(rate / (1 - rate))`.
+       *   - `noise_shape`: A 1-D `Tensor` of type `int32`, representing the
+       *     shape for randomly generated keep/drop flags.
+       *
+       * Input shape:
+       *   Arbitrary. Use the keyword argument `inputShape`
+       *   (tuple of integers, does not include the samples axis)
+       *   when using this layer as the first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as input.
+       *
+       * References:
+       *   - [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)
+       */
+      class noise_AlphaDropout extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.supportsMasking = true;
+          this.rate = args.rate;
+          this.noiseShape = args.noiseShape;
+        }
+        _getNoiseShape(inputs) {
+          return this.noiseShape || getExactlyOneTensor(inputs).shape;
+        }
+        computeOutputShape(inputShape) {
+          return inputShape;
+        }
+        getConfig() {
+          const baseConfig = super.getConfig();
+          const config = { rate: this.rate };
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            if (this.rate < 1 && this.rate > 0) {
+              const noiseShape = this._getNoiseShape(inputs);
+              const droppedInputs = () => {
+                const input = getExactlyOneTensor(inputs);
+                const alpha = 1.6732632423543772848170429916717;
+                const scale = 1.0507009873554804934193349852946;
+                const alphaP = -alpha * scale;
+                let keptIdx = Object(dist["greaterEqual"])(
+                  Object(dist["randomUniform"])(noiseShape),
+                  this.rate
+                );
+                keptIdx = cast(keptIdx, "float32"); // get default dtype.
+                // Get affine transformation params.
+                const a = ((1 - this.rate) * (1 + this.rate * alphaP ** 2)) ** -0.5;
+                const b = -a * alphaP * this.rate;
+                // Apply mask.
+                const x = input.mul(keptIdx).add(keptIdx.add(-1).mul(alphaP));
+                return x.mul(a).add(b);
+              };
+              return inTrainPhase(
+                droppedInputs,
+                () => getExactlyOneTensor(inputs),
+                kwargs["training"] || false
+              );
+            }
+            return inputs;
+          });
+        }
+      }
+      /** @nocollapse */
+      noise_AlphaDropout.className = "AlphaDropout";
+      dist["serialization"].registerClass(noise_AlphaDropout);
+      //# sourceMappingURL=noise.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/normalization.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Normalization layers.
+       */
+
+      /**
+       * Applies batch normalization on x given mean, var, beta and gamma.
+       *
+       * I.e. returns:
+       *   `output = (x - mean) / (sqrt(var) + epsilon) * gamma + beta`
+       *
+       * @param x Input tensor.
+       * @param mean Mean of batch.
+       * @param variance Variance of batch.
+       * @param beta Tensor with which to center the input.
+       * @param gamma Tensor by which to scale the input.
+       * @param epsilon Fuzz factor.
+       * @returns The result of the batch normalization.
+       */
+      function batchNormalization(x, mean, variance, beta, gamma, epsilon = 1e-3) {
+        let out;
+        if (x.rank === 2) {
+          out = dist["batchNorm2d"](x, mean, variance, beta, gamma, epsilon);
+        } else if (x.rank === 3) {
+          // TODO(cais): Check rank; give proper error message.
+          out = dist["batchNorm3d"](x, mean, variance, beta, gamma, epsilon);
+        } else if (x.rank === 4) {
+          out = dist["batchNorm4d"](x, mean, variance, beta, gamma, epsilon);
+        } else {
+          throw new NotImplementedError(
+            `batchNormalization is not implemented for array of rank ${x.rank} ` + `yet`
+          );
+        }
+        return out;
+      }
+      /**
+       * Non-broadcasting batch normalization for use in training (not inference).
+       *
+       * The input is normalized to zero mean and unit variance along the
+       * `reductionAxes`, followed by scaling with `gamma` and shifted by `beta`.
+       * The result of that is returned as the first element
+       * of the returned `Array`. The other two elements are the mean and variance,
+       * respectively.
+       *
+       * @param x Input tensor to be normalized.
+       * @param gamma Tensor by which to scale the input.
+       * @param beta Tensor by which to center the input.
+       * @param reductionAxes Axes over which to normalize.
+       * @param epsilon Fuzz factor.
+       * @returns An `Array` of three `Tensors`:
+       *   [normalized tensor, mean of input, variance of input].
+       */
+      function regularNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon = 1e-3) {
+        return Object(dist["tidy"])(() => {
+          const meanAndVariance = dist["moments"](x, reductionAxes);
+          const mean = meanAndVariance.mean;
+          const variance = meanAndVariance.variance;
+          const normed = batchNormalization(x, mean, variance, beta, gamma, epsilon);
+          return [normed, mean, variance];
+        });
+      }
+      /**
+       * Broadcasting batch normalization for use in training (not inference).
+       *
+       * The input is normalized to zero mean and unit variance along the
+       * `reductionAxes`, followed by scaling with `gamma` and shifted by `beta`.
+       * The result of that is returned as the first element
+       * of the returned `Array`. The other two elements are the mean and variance,
+       * respectively.
+       *
+       * @param x Input tensor to be normalized.
+       * @param gamma Tensor by which to scale the input.
+       * @param beta Tensor by which to center the input.
+       * @param reductionAxes Axes over which to normalize.
+       * @param epsilon Fuzz factor.
+       * @returns An `Array` of three `Tensors`:
+       *   [normalized tensor, mean of input, variance of input].
+       */
+      function broadcastNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon = 1e-3) {
+        return Object(dist["tidy"])(() => {
+          const meanAndVariance = dist["moments"](x, reductionAxes);
+          const mean = meanAndVariance.mean;
+          const variance = meanAndVariance.variance;
+          const targetShape = [];
+          for (const axis of range(0, x.rank)) {
+            if (reductionAxes.indexOf(axis) !== -1) {
+              targetShape.push(1);
+            } else {
+              targetShape.push(x.shape[axis]);
+            }
+          }
+          const broadcastMean = mean.reshape(targetShape);
+          const broadcastVariance = variance.reshape(targetShape);
+          const broadcastGamma = gamma == null ? null : gamma.reshape(targetShape);
+          const broadcastBeta = beta == null ? null : beta.reshape(targetShape);
+          const normed = batchNormalization(
+            x,
+            broadcastMean,
+            broadcastVariance,
+            broadcastBeta,
+            broadcastGamma,
+            epsilon
+          );
+          return [normed, mean, variance];
+        });
+      }
+      /**
+       * Batch normalization for use in training (not inference).
+       *
+       * @param x Input tensor to be normalized.
+       * @param gamma Tensor by which to scale the input.
+       * @param beta Tensor by which to center the input.
+       * @param reductionAxes Axes over which to normalize.
+       * @param epsilon Fuzz factor.
+       * @returns An `Array` of three `Tensors`:
+       *   [normalized tensor, mean of input, variance of input].
+       */
+      function normalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon = 1e-3) {
+        if (dist["util"].arraysEqual(reductionAxes.slice().sort(), range(0, x.rank - 1))) {
+          return regularNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon);
+        } else {
+          return broadcastNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon);
+        }
+      }
+      class normalization_BatchNormalization extends topology_Layer {
+        constructor(args) {
+          if (args == null) {
+            args = {};
+          }
+          super(args);
+          this.supportsMasking = true;
+          this.axis = args.axis == null ? -1 : args.axis;
+          this.momentum = args.momentum == null ? 0.99 : args.momentum;
+          this.epsilon = args.epsilon == null ? 1e-3 : args.epsilon;
+          this.center = args.center == null ? true : args.center;
+          this.scale = args.scale == null ? true : args.scale;
+          this.betaInitializer = getInitializer(args.betaInitializer || "zeros");
+          this.gammaInitializer = getInitializer(args.gammaInitializer || "ones");
+          this.movingMeanInitializer = getInitializer(args.movingMeanInitializer || "zeros");
+          this.movingVarianceInitializer = getInitializer(args.movingVarianceInitializer || "ones");
+          this.betaConstraint = getConstraint(args.betaConstraint);
+          this.gammaConstraint = getConstraint(args.gammaConstraint);
+          this.betaRegularizer = getRegularizer(args.betaRegularizer);
+          this.gammaRegularizer = getRegularizer(args.gammaRegularizer);
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const axis = this.axis >= 0 ? this.axis : this.axis + inputShape.length;
+          const dim = inputShape[axis];
+          if (dim == null) {
+            throw new ValueError(
+              `Axis ${axis} of input tensor should have a defined dimension but ` +
+                `the layer received an input with shape ` +
+                `${JSON.stringify(inputShape)}.`
+            );
+          }
+          this.inputSpec = [new InputSpec({ ndim: inputShape.length, axes: { [axis]: dim } })];
+          const shape = [dim];
+          if (this.scale) {
+            this.gamma = this.addWeight(
+              "gamma",
+              shape,
+              null,
+              this.gammaInitializer,
+              this.gammaRegularizer,
+              true,
+              this.gammaConstraint
+            );
+          }
+          if (this.center) {
+            this.beta = this.addWeight(
+              "beta",
+              shape,
+              null,
+              this.betaInitializer,
+              this.betaRegularizer,
+              true,
+              this.betaConstraint
+            );
+          }
+          this.movingMean = this.addWeight(
+            "moving_mean",
+            shape,
+            null,
+            this.movingMeanInitializer,
+            null,
+            false
+          );
+          this.movingVariance = this.addWeight(
+            "moving_variance",
+            shape,
+            null,
+            this.movingVarianceInitializer,
+            null,
+            false
+          );
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            const training = kwargs["training"] == null ? false : kwargs["training"];
+            const input = getExactlyOneTensor(inputs);
+            const inputShape = input.shape;
+            const ndim = inputShape.length;
+            const reductionAxes = range(0, ndim);
+            const axis = this.axis >= 0 ? this.axis : this.axis + ndim;
+            reductionAxes.splice(axis, 1);
+            const broadcastShape = pyListRepeat(1, ndim);
+            broadcastShape[axis] = inputShape[axis];
+            const sortedReductionAxes = reductionAxes.slice();
+            sortedReductionAxes.sort();
+            const needsBroadcasting = !dist["util"].arraysEqual(
+              sortedReductionAxes,
+              range(0, ndim).slice(0, ndim - 1)
+            );
+            const normalizeInference = () => {
+              if (needsBroadcasting) {
+                const broadcastMovingMean = this.movingMean.read().reshape(broadcastShape);
+                const broadcastMovingVariance = this.movingVariance.read().reshape(broadcastShape);
+                const broadcastBeta = this.center ? this.beta.read().reshape(broadcastShape) : null;
+                const broadcastGamma = this.scale
+                  ? this.gamma.read().reshape(broadcastShape)
+                  : null;
+                return batchNormalization(
+                  input,
+                  broadcastMovingMean,
+                  broadcastMovingVariance,
+                  broadcastBeta,
+                  broadcastGamma,
+                  this.epsilon
+                );
+              } else {
+                return batchNormalization(
+                  input,
+                  this.movingMean.read(),
+                  this.movingVariance.read(),
+                  this.beta == null ? null : this.beta.read(),
+                  this.gamma == null ? null : this.gamma.read(),
+                  this.epsilon
+                );
+              }
+            };
+            if (!training) {
+              return normalizeInference();
+            }
+            const [normedTraining, mean, variance] = normalizeBatchInTraining(
+              input,
+              this.gamma.read(),
+              this.beta.read(),
+              reductionAxes,
+              this.epsilon
+            );
+            const doMovingAverage = (variable, value, momentum) => {
+              dist["tidy"](() => {
+                const decay = 1 - momentum;
+                const origValue = variable.read();
+                const updateDelta = origValue.sub(value).mul(decay);
+                variable.write(origValue.sub(updateDelta));
+              });
+            };
+            // Perform updates to moving mean and moving variance for training.
+            // Porting Note: In PyKeras, these updates to `movingMean` and
+            //   `movingAverage` are done as a deferred Graph, added to the `Layer`'s
+            //   `update`s using the `add_update()` method. Here we do it imperatively
+            //   and encapsulate the updates in a function that is invoked
+            //   immediately.
+            const updateMovingMeanAndVariance = () => {
+              doMovingAverage(this.movingMean, mean, this.momentum);
+              doMovingAverage(this.movingVariance, variance, this.momentum);
+            };
+            updateMovingMeanAndVariance();
+            return normedTraining;
+          });
+        }
+        getConfig() {
+          const config = {
+            axis: this.axis,
+            momentum: this.momentum,
+            epsilon: this.epsilon,
+            center: this.center,
+            scale: this.scale,
+            betaInitializer: serializeInitializer(this.betaInitializer),
+            gammaInitializer: serializeInitializer(this.gammaInitializer),
+            movingMeanInitializer: serializeInitializer(this.movingMeanInitializer),
+            movingVarianceInitializer: serializeInitializer(this.movingVarianceInitializer),
+            betaRegularizer: serializeRegularizer(this.betaRegularizer),
+            gammaRegularizer: serializeRegularizer(this.gammaRegularizer),
+            betaConstraint: serializeConstraint(this.betaConstraint),
+            gammaConstraint: serializeConstraint(this.gammaConstraint),
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      normalization_BatchNormalization.className = "BatchNormalization";
+      dist["serialization"].registerClass(normalization_BatchNormalization);
+      class normalization_LayerNormalization extends topology_Layer {
+        constructor(args) {
+          if (args == null) {
+            args = {};
+          }
+          super(args);
+          this.axis = args.axis == null ? -1 : args.axis;
+          if (typeof this.axis === "number") {
+            if (!Number.isInteger(this.axis)) {
+              throw new Error(`Expected axis to be an integer, but received ${this.axis}`);
+            }
+          } else if (Array.isArray(this.axis)) {
+            for (const axis of this.axis) {
+              if (!Number.isInteger(axis)) {
+                throw new Error(
+                  `Expected axis to be an array of integers, ` +
+                    `but received ${JSON.stringify(this.axis)}`
+                );
+              }
+            }
+          } else {
+            throw new Error(
+              `Expected axis to be an integer or an array of integers, ` +
+                `but received ${JSON.stringify(this.axis)}`
+            );
+          }
+          this.epsilon = args.epsilon == null ? 1e-3 : args.epsilon;
+          this.center = args.center == null ? true : args.center;
+          this.scale = args.scale == null ? true : args.scale;
+          this.betaInitializer = getInitializer(args.betaInitializer || "zeros");
+          this.gammaInitializer = getInitializer(args.gammaInitializer || "ones");
+          this.betaRegularizer = getRegularizer(args.betaRegularizer);
+          this.gammaRegularizer = getRegularizer(args.gammaRegularizer);
+          this.supportsMasking = true;
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const nDims = inputShape.length;
+          // Convert axis to array and resolve negatives.
+          if (typeof this.axis === "number") {
+            this.axis = [this.axis];
+          }
+          for (let i = 0; i < this.axis.length; ++i) {
+            if (this.axis[i] < 0) {
+              this.axis[i] += nDims;
+            }
+          }
+          // Further validate axes.
+          for (const axis of this.axis) {
+            if (axis < 0 || axis >= nDims) {
+              throw new Error(`Invalid axis: ${axis}`);
+            }
+          }
+          if (this.axis.length !== unique(this.axis).length) {
+            throw new Error(`Found duplicate axes in: ${this.axis}`);
+          }
+          const paramShape = this.axis.map((axis) => inputShape[axis]);
+          const trainable = true;
+          if (this.scale) {
+            this.gamma = this.addWeight(
+              "gamma",
+              paramShape,
+              "float32",
+              this.gammaInitializer,
+              this.gammaRegularizer,
+              trainable
+            );
+          } else {
+            this.gamma = null;
+          }
+          if (this.center) {
+            this.beta = this.addWeight(
+              "beta",
+              paramShape,
+              "float32",
+              this.betaInitializer,
+              this.betaRegularizer,
+              trainable
+            );
+          } else {
+            this.beta = null;
+          }
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          const input = getExactlyOneTensor(inputs);
+          const inputShape = input.shape;
+          const nDims = inputShape.length;
+          return Object(dist["tidy"])(() => {
+            const keepDims = true;
+            let { mean, variance } = Object(dist["moments"])(input, this.axis, keepDims);
+            const broadcastShape = pyListRepeat(1, nDims);
+            for (const dim of this.axis) {
+              broadcastShape[dim] = inputShape[dim];
+            }
+            const broadcast = (v) => {
+              if (v != null && v.shape.length !== nDims && this.axis !== [nDims - 1]) {
+                return v.reshape(broadcastShape);
+              } else {
+                return v;
+              }
+            };
+            let scale = broadcast(this.gamma.read());
+            let offset = broadcast(this.beta.read());
+            // TODO(https://github.com/tensorflow/tfjs/issues/2120): The tiling below
+            // is a workaround for the limitation of core's batchNormalization?d don't
+            // support broadcasting in their gradients. In addition, the tiling is
+            // necessary to ensure correctness on the browser CPU backend regardless
+            // of forward or backward computation. Remove this workaround once the
+            // limitation is addressed. See .
+            const momentsTiling = [];
+            const scaleOffsetTiling = [];
+            for (let i = 0; i < nDims; ++i) {
+              if (this.axis.indexOf(i) !== -1) {
+                momentsTiling.push(inputShape[i]);
+                scaleOffsetTiling.push(1);
+              } else {
+                momentsTiling.push(1);
+                scaleOffsetTiling.push(inputShape[i]);
+              }
+            }
+            mean = mean.tile(momentsTiling);
+            variance = variance.tile(momentsTiling);
+            scale = scale.tile(scaleOffsetTiling);
+            offset = offset.tile(scaleOffsetTiling);
+            return batchNormalization(input, mean, variance, offset, scale, this.epsilon);
+          });
+        }
+        getConfig() {
+          const config = {
+            axis: this.axis,
+            epsilon: this.epsilon,
+            center: this.center,
+            scale: this.scale,
+            betaInitializer: serializeInitializer(this.betaInitializer),
+            gammaInitializer: serializeInitializer(this.gammaInitializer),
+            betaRegularizer: serializeRegularizer(this.betaRegularizer),
+            gammaRegularizer: serializeRegularizer(this.gammaRegularizer),
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      normalization_LayerNormalization.className = "LayerNormalization";
+      dist["serialization"].registerClass(normalization_LayerNormalization);
+      //# sourceMappingURL=normalization.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/padding.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Padding Layers.
+       */
+      // Porting Note: In Python Keras, the padding layers are in convolutional.py,
+      //   but we decided to put them in a separate file (padding.ts) for clarity.
+
+      /**
+       * Pads the middle dimension of a 3D tensor.
+       *
+       * @param x Input `tf.Tensor` to be padded.
+       * @param padding `Array` of 2 integers, how many zeros to add at the start and
+       *   end of the middle dimension (i.e., dimension 1).
+       * @return A padded 3D `tf.Tensor`.
+       */
+      function temporalPadding(x, padding) {
+        return Object(dist["tidy"])(() => {
+          if (x.rank !== 3) {
+            throw new ValueError(
+              `temporalPadding expects input tensor to be 3-D, but received a ` +
+                `${x.rank}-D tensor.`
+            );
+          }
+          if (padding == null) {
+            padding = [1, 1];
+          }
+          if (padding.length !== 2) {
+            throw new ValueError(
+              `temporalPadding expects input padding pattern to be a length-2 ` +
+                `array, but received a length-${padding.length} array.`
+            );
+          }
+          const pattern = [[0, 0], padding, [0, 0]];
+          return dist["pad"](x, pattern);
+        });
+      }
+      /**
+       * Pads the 2nd and 3rd dimensions of a 4D tensor.
+       *
+       * @param x Input `tf.Tensor` to be padded.
+       * @param padding `Array` of two `Array`s, each of which is an `Array` of two
+       *   integers. The amount of padding at the beginning and end of the 2nd and 3rd
+       *   dimensions, respectively.
+       * @param dataFormat 'channelsLast' (default) or 'channelsFirst'.
+       * @return Padded 4D `tf.Tensor`.
+       */
+      function spatial2dPadding(x, padding, dataFormat) {
+        return Object(dist["tidy"])(() => {
+          if (x.rank !== 4) {
+            throw new ValueError(
+              `temporalPadding expects input tensor to be 4-D, but received a ` +
+                `${x.rank}-D tensor.`
+            );
+          }
+          if (padding == null) {
+            padding = [
+              [1, 1],
+              [1, 1],
+            ];
+          }
+          if (padding.length !== 2 || padding[0].length !== 2 || padding[1].length !== 2) {
+            throw new ValueError(
+              "spatial2dPadding expects `padding` to be an Array of two Arrays, " +
+                "each of which is an Array of two integers."
+            );
+          }
+          if (dataFormat == null) {
+            dataFormat = imageDataFormat();
+          }
+          if (dataFormat !== "channelsLast" && dataFormat !== "channelsFirst") {
+            throw new ValueError(
+              `Unknown data format: ${dataFormat}. ` +
+                `Supported data formats are 'channelsLast' and 'channelsFirst.`
+            );
+          }
+          let pattern;
+          if (dataFormat === "channelsFirst") {
+            pattern = [[0, 0], [0, 0], padding[0], padding[1]];
+          } else {
+            pattern = [[0, 0], padding[0], padding[1], [0, 0]];
+          }
+          return dist["pad"](x, pattern);
+        });
+      }
+      class padding_ZeroPadding2D extends topology_Layer {
+        constructor(args) {
+          if (args == null) {
+            args = {};
+          }
+          super(args);
+          this.dataFormat = args.dataFormat == null ? imageDataFormat() : args.dataFormat;
+          // TODO(cais): Maybe refactor the following logic surrounding `padding`
+          //   into a helper method.
+          if (args.padding == null) {
+            this.padding = [
+              [1, 1],
+              [1, 1],
+            ];
+          } else if (typeof args.padding === "number") {
+            this.padding = [
+              [args.padding, args.padding],
+              [args.padding, args.padding],
+            ];
+          } else {
+            args.padding = args.padding;
+            if (args.padding.length !== 2) {
+              throw new ValueError(
+                `ZeroPadding2D expects padding to be a length-2 array, but ` +
+                  `received a length-${args.padding.length} array.`
+              );
+            }
+            let heightPadding;
+            let widthPadding;
+            if (typeof args.padding[0] === "number") {
+              heightPadding = [args.padding[0], args.padding[0]];
+              widthPadding = [args.padding[1], args.padding[1]];
+            } else {
+              args.padding = args.padding;
+              if (args.padding[0].length !== 2) {
+                throw new ValueError(
+                  `ZeroPadding2D expects height padding to be a length-2 array, ` +
+                    `but received a length-${args.padding[0].length} array.`
+                );
+              }
+              heightPadding = args.padding[0];
+              if (args.padding[1].length !== 2) {
+                throw new ValueError(
+                  `ZeroPadding2D expects width padding to be a length-2 array, ` +
+                    `but received a length-${args.padding[1].length} array.`
+                );
+              }
+              widthPadding = args.padding[1];
+            }
+            this.padding = [heightPadding, widthPadding];
+          }
+          this.inputSpec = [new InputSpec({ ndim: 4 })];
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          let rows;
+          let cols;
+          if (this.dataFormat === "channelsFirst") {
+            if (inputShape[2] != null && inputShape[2] >= 0) {
+              rows = inputShape[2] + this.padding[0][0] + this.padding[0][1];
+            } else {
+              rows = null;
+            }
+            if (inputShape[3] != null && inputShape[3] >= 0) {
+              cols = inputShape[3] + this.padding[1][0] + this.padding[1][1];
+            } else {
+              cols = null;
+            }
+            return [inputShape[0], inputShape[1], rows, cols];
+          } else {
+            if (inputShape[1] != null && inputShape[1] >= 0) {
+              rows = inputShape[1] + this.padding[0][0] + this.padding[0][1];
+            } else {
+              rows = null;
+            }
+            if (inputShape[2] != null && inputShape[2] >= 0) {
+              cols = inputShape[2] + this.padding[1][0] + this.padding[1][1];
+            } else {
+              cols = null;
+            }
+            return [inputShape[0], rows, cols, inputShape[3]];
+          }
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() =>
+            spatial2dPadding(getExactlyOneTensor(inputs), this.padding, this.dataFormat)
+          );
+        }
+        getConfig() {
+          const config = {
+            padding: this.padding,
+            dataFormat: this.dataFormat,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      padding_ZeroPadding2D.className = "ZeroPadding2D";
+      dist["serialization"].registerClass(padding_ZeroPadding2D);
+      //# sourceMappingURL=padding.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/pooling.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * TensorFlow.js Layers: Pooling Layers.
+       */
+
+      /**
+       * 2D pooling.
+       * @param x
+       * @param poolSize
+       * @param stridesdes strides. Defaults to [1, 1].
+       * @param padding padding. Defaults to 'valid'.
+       * @param dataFormat data format. Defaults to 'channelsLast'.
+       * @param poolMode Mode of pooling. Defaults to 'max'.
+       * @returns Result of the 2D pooling.
+       */
+      function pool2d(x, poolSize, strides, padding, dataFormat, poolMode) {
+        return Object(dist["tidy"])(() => {
+          checkDataFormat(dataFormat);
+          checkPoolMode(poolMode);
+          checkPaddingMode(padding);
+          if (strides == null) {
+            strides = [1, 1];
+          }
+          if (padding == null) {
+            padding = "valid";
+          }
+          if (dataFormat == null) {
+            dataFormat = imageDataFormat();
+          }
+          if (poolMode == null) {
+            poolMode = "max";
+          }
+          // TODO(cais): Remove the preprocessing step once deeplearn.js supports
+          // dataFormat as an input argument.
+          x = preprocessConv2DInput(x, dataFormat); // x is NHWC after preprocessing.
+          let y;
+          const paddingString = padding === "same" ? "same" : "valid";
+          if (poolMode === "max") {
+            // TODO(cais): Rank check?
+            y = dist["maxPool"](x, poolSize, strides, paddingString);
+          } else {
+            // 'avg'
+            // TODO(cais): Check the dtype and rank of x and give clear error message
+            //   if those are incorrect.
+            y = dist["avgPool"](
+              // TODO(cais): Rank check?
+              x,
+              poolSize,
+              strides,
+              paddingString
+            );
+          }
+          if (dataFormat === "channelsFirst") {
+            y = dist["transpose"](y, [0, 3, 1, 2]); // NHWC -> NCHW.
+          }
+          return y;
+        });
+      }
+      /**
+       * 3D pooling.
+       * @param x
+       * @param poolSize. Default to [1, 1, 1].
+       * @param strides strides. Defaults to [1, 1, 1].
+       * @param padding padding. Defaults to 'valid'.
+       * @param dataFormat data format. Defaults to 'channelsLast'.
+       * @param poolMode Mode of pooling. Defaults to 'max'.
+       * @returns Result of the 3D pooling.
+       */
+      function pool3d(x, poolSize, strides, padding, dataFormat, poolMode) {
+        return Object(dist["tidy"])(() => {
+          checkDataFormat(dataFormat);
+          checkPoolMode(poolMode);
+          checkPaddingMode(padding);
+          if (strides == null) {
+            strides = [1, 1, 1];
+          }
+          if (padding == null) {
+            padding = "valid";
+          }
+          if (dataFormat == null) {
+            dataFormat = imageDataFormat();
+          }
+          if (poolMode == null) {
+            poolMode = "max";
+          }
+          // x is NDHWC after preprocessing.
+          x = preprocessConv3DInput(x, dataFormat);
+          let y;
+          const paddingString = padding === "same" ? "same" : "valid";
+          if (poolMode === "max") {
+            y = dist["maxPool3d"](x, poolSize, strides, paddingString);
+          } else {
+            // 'avg'
+            y = dist["avgPool3d"](x, poolSize, strides, paddingString);
+          }
+          if (dataFormat === "channelsFirst") {
+            y = dist["transpose"](y, [0, 4, 1, 2, 3]); // NDHWC -> NCDHW.
+          }
+          return y;
+        });
+      }
+      /**
+       * Abstract class for different pooling 1D layers.
+       */
+      class pooling_Pooling1D extends topology_Layer {
+        /**
+         *
+         * @param args Parameters for the Pooling layer.
+         *
+         * config.poolSize defaults to 2.
+         */
+        constructor(args) {
+          if (args.poolSize == null) {
+            args.poolSize = 2;
+          }
+          super(args);
+          if (typeof args.poolSize === "number") {
+            this.poolSize = [args.poolSize];
+          } else if (
+            Array.isArray(args.poolSize) &&
+            args.poolSize.length === 1 &&
+            typeof args.poolSize[0] === "number"
+          ) {
+            this.poolSize = args.poolSize;
+          } else {
+            throw new ValueError(
+              `poolSize for 1D convolutional layer must be a number or an ` +
+                `Array of a single number, but received ` +
+                `${JSON.stringify(args.poolSize)}`
+            );
+          }
+          assertPositiveInteger(this.poolSize, "poolSize");
+          if (args.strides == null) {
+            this.strides = this.poolSize;
+          } else {
+            if (typeof args.strides === "number") {
+              this.strides = [args.strides];
+            } else if (
+              Array.isArray(args.strides) &&
+              args.strides.length === 1 &&
+              typeof args.strides[0] === "number"
+            ) {
+              this.strides = args.strides;
+            } else {
+              throw new ValueError(
+                `strides for 1D convolutional layer must be a number or an ` +
+                  `Array of a single number, but received ` +
+                  `${JSON.stringify(args.strides)}`
+              );
+            }
+          }
+          assertPositiveInteger(this.strides, "strides");
+          this.padding = args.padding == null ? "valid" : args.padding;
+          checkPaddingMode(this.padding);
+          this.inputSpec = [new InputSpec({ ndim: 3 })];
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const length = convOutputLength(
+            inputShape[1],
+            this.poolSize[0],
+            this.padding,
+            this.strides[0]
+          );
+          return [inputShape[0], length, inputShape[2]];
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            // Add dummy last dimension.
+            inputs = expandDims(getExactlyOneTensor(inputs), 2);
+            const output = this.poolingFunction(
+              getExactlyOneTensor(inputs),
+              [this.poolSize[0], 1],
+              [this.strides[0], 1],
+              this.padding,
+              "channelsLast"
+            );
+            // Remove dummy last dimension.
+            return dist["squeeze"](output, [2]);
+          });
+        }
+        getConfig() {
+          const config = {
+            poolSize: this.poolSize,
+            padding: this.padding,
+            strides: this.strides,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      class pooling_MaxPooling1D extends pooling_Pooling1D {
+        constructor(args) {
+          super(args);
+        }
+        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
+          checkDataFormat(dataFormat);
+          checkPaddingMode(padding);
+          return pool2d(inputs, poolSize, strides, padding, dataFormat, "max");
+        }
+      }
+      /** @nocollapse */
+      pooling_MaxPooling1D.className = "MaxPooling1D";
+      dist["serialization"].registerClass(pooling_MaxPooling1D);
+      class pooling_AveragePooling1D extends pooling_Pooling1D {
+        constructor(args) {
+          super(args);
+        }
+        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
+          checkDataFormat(dataFormat);
+          checkPaddingMode(padding);
+          return pool2d(inputs, poolSize, strides, padding, dataFormat, "avg");
+        }
+      }
+      /** @nocollapse */
+      pooling_AveragePooling1D.className = "AveragePooling1D";
+      dist["serialization"].registerClass(pooling_AveragePooling1D);
+      /**
+       * Abstract class for different pooling 2D layers.
+       */
+      class pooling_Pooling2D extends topology_Layer {
+        constructor(args) {
+          if (args.poolSize == null) {
+            args.poolSize = [2, 2];
+          }
+          super(args);
+          this.poolSize = Array.isArray(args.poolSize)
+            ? args.poolSize
+            : [args.poolSize, args.poolSize];
+          if (args.strides == null) {
+            this.strides = this.poolSize;
+          } else if (Array.isArray(args.strides)) {
+            if (args.strides.length !== 2) {
+              throw new ValueError(
+                `If the strides property of a 2D pooling layer is an Array, ` +
+                  `it is expected to have a length of 2, but received length ` +
+                  `${args.strides.length}.`
+              );
+            }
+            this.strides = args.strides;
+          } else {
+            // `config.strides` is a number.
+            this.strides = [args.strides, args.strides];
+          }
+          assertPositiveInteger(this.poolSize, "poolSize");
+          assertPositiveInteger(this.strides, "strides");
+          this.padding = args.padding == null ? "valid" : args.padding;
+          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
+          checkDataFormat(this.dataFormat);
+          checkPaddingMode(this.padding);
+          this.inputSpec = [new InputSpec({ ndim: 4 })];
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          let rows = this.dataFormat === "channelsFirst" ? inputShape[2] : inputShape[1];
+          let cols = this.dataFormat === "channelsFirst" ? inputShape[3] : inputShape[2];
+          rows = convOutputLength(rows, this.poolSize[0], this.padding, this.strides[0]);
+          cols = convOutputLength(cols, this.poolSize[1], this.padding, this.strides[1]);
+          if (this.dataFormat === "channelsFirst") {
+            return [inputShape[0], inputShape[1], rows, cols];
+          } else {
+            return [inputShape[0], rows, cols, inputShape[3]];
+          }
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            return this.poolingFunction(
+              getExactlyOneTensor(inputs),
+              this.poolSize,
+              this.strides,
+              this.padding,
+              this.dataFormat
+            );
+          });
+        }
+        getConfig() {
+          const config = {
+            poolSize: this.poolSize,
+            padding: this.padding,
+            strides: this.strides,
+            dataFormat: this.dataFormat,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      class pooling_MaxPooling2D extends pooling_Pooling2D {
+        constructor(args) {
+          super(args);
+        }
+        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
+          checkDataFormat(dataFormat);
+          checkPaddingMode(padding);
+          return pool2d(inputs, poolSize, strides, padding, dataFormat, "max");
+        }
+      }
+      /** @nocollapse */
+      pooling_MaxPooling2D.className = "MaxPooling2D";
+      dist["serialization"].registerClass(pooling_MaxPooling2D);
+      class pooling_AveragePooling2D extends pooling_Pooling2D {
+        constructor(args) {
+          super(args);
+        }
+        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
+          checkDataFormat(dataFormat);
+          checkPaddingMode(padding);
+          return pool2d(inputs, poolSize, strides, padding, dataFormat, "avg");
+        }
+      }
+      /** @nocollapse */
+      pooling_AveragePooling2D.className = "AveragePooling2D";
+      dist["serialization"].registerClass(pooling_AveragePooling2D);
+      /**
+       * Abstract class for different pooling 3D layers.
+       */
+      class pooling_Pooling3D extends topology_Layer {
+        constructor(args) {
+          if (args.poolSize == null) {
+            args.poolSize = [2, 2, 2];
+          }
+          super(args);
+          this.poolSize = Array.isArray(args.poolSize)
+            ? args.poolSize
+            : [args.poolSize, args.poolSize, args.poolSize];
+          if (args.strides == null) {
+            this.strides = this.poolSize;
+          } else if (Array.isArray(args.strides)) {
+            if (args.strides.length !== 3) {
+              throw new ValueError(
+                `If the strides property of a 3D pooling layer is an Array, ` +
+                  `it is expected to have a length of 3, but received length ` +
+                  `${args.strides.length}.`
+              );
+            }
+            this.strides = args.strides;
+          } else {
+            // `config.strides` is a number.
+            this.strides = [args.strides, args.strides, args.strides];
+          }
+          assertPositiveInteger(this.poolSize, "poolSize");
+          assertPositiveInteger(this.strides, "strides");
+          this.padding = args.padding == null ? "valid" : args.padding;
+          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
+          checkDataFormat(this.dataFormat);
+          checkPaddingMode(this.padding);
+          this.inputSpec = [new InputSpec({ ndim: 5 })];
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          let depths = this.dataFormat === "channelsFirst" ? inputShape[2] : inputShape[1];
+          let rows = this.dataFormat === "channelsFirst" ? inputShape[3] : inputShape[2];
+          let cols = this.dataFormat === "channelsFirst" ? inputShape[4] : inputShape[3];
+          depths = convOutputLength(depths, this.poolSize[0], this.padding, this.strides[0]);
+          rows = convOutputLength(rows, this.poolSize[1], this.padding, this.strides[1]);
+          cols = convOutputLength(cols, this.poolSize[2], this.padding, this.strides[2]);
+          if (this.dataFormat === "channelsFirst") {
+            return [inputShape[0], inputShape[1], depths, rows, cols];
+          } else {
+            return [inputShape[0], depths, rows, cols, inputShape[4]];
+          }
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            this.invokeCallHook(inputs, kwargs);
+            return this.poolingFunction(
+              getExactlyOneTensor(inputs),
+              this.poolSize,
+              this.strides,
+              this.padding,
+              this.dataFormat
+            );
+          });
+        }
+        getConfig() {
+          const config = {
+            poolSize: this.poolSize,
+            padding: this.padding,
+            strides: this.strides,
+            dataFormat: this.dataFormat,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      class pooling_MaxPooling3D extends pooling_Pooling3D {
+        constructor(args) {
+          super(args);
+        }
+        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
+          checkDataFormat(dataFormat);
+          checkPaddingMode(padding);
+          return pool3d(inputs, poolSize, strides, padding, dataFormat, "max");
+        }
+      }
+      /** @nocollapse */
+      pooling_MaxPooling3D.className = "MaxPooling3D";
+      dist["serialization"].registerClass(pooling_MaxPooling3D);
+      class pooling_AveragePooling3D extends pooling_Pooling3D {
+        constructor(args) {
+          super(args);
+        }
+        poolingFunction(inputs, poolSize, strides, padding, dataFormat) {
+          checkDataFormat(dataFormat);
+          checkPaddingMode(padding);
+          return pool3d(inputs, poolSize, strides, padding, dataFormat, "avg");
+        }
+      }
+      /** @nocollapse */
+      pooling_AveragePooling3D.className = "AveragePooling3D";
+      dist["serialization"].registerClass(pooling_AveragePooling3D);
+      /**
+       * Abstract class for different global pooling 1D layers.
+       */
+      class pooling_GlobalPooling1D extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.inputSpec = [new InputSpec({ ndim: 3 })];
+        }
+        computeOutputShape(inputShape) {
+          return [inputShape[0], inputShape[2]];
+        }
+        call(inputs, kwargs) {
+          throw new NotImplementedError();
+        }
+      }
+      class pooling_GlobalAveragePooling1D extends pooling_GlobalPooling1D {
+        constructor(args) {
+          super(args || {});
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            const input = getExactlyOneTensor(inputs);
+            return dist["mean"](input, 1);
+          });
+        }
+      }
+      /** @nocollapse */
+      pooling_GlobalAveragePooling1D.className = "GlobalAveragePooling1D";
+      dist["serialization"].registerClass(pooling_GlobalAveragePooling1D);
+      class pooling_GlobalMaxPooling1D extends pooling_GlobalPooling1D {
+        constructor(args) {
+          super(args || {});
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            const input = getExactlyOneTensor(inputs);
+            return dist["max"](input, 1);
+          });
+        }
+      }
+      /** @nocollapse */
+      pooling_GlobalMaxPooling1D.className = "GlobalMaxPooling1D";
+      dist["serialization"].registerClass(pooling_GlobalMaxPooling1D);
+      /**
+       * Abstract class for different global pooling 2D layers.
+       */
+      class pooling_GlobalPooling2D extends topology_Layer {
+        constructor(args) {
+          super(args);
+          this.dataFormat = args.dataFormat == null ? "channelsLast" : args.dataFormat;
+          checkDataFormat(this.dataFormat);
+          this.inputSpec = [new InputSpec({ ndim: 4 })];
+        }
+        computeOutputShape(inputShape) {
+          inputShape = inputShape;
+          if (this.dataFormat === "channelsLast") {
+            return [inputShape[0], inputShape[3]];
+          } else {
+            return [inputShape[0], inputShape[1]];
+          }
+        }
+        call(inputs, kwargs) {
+          throw new NotImplementedError();
+        }
+        getConfig() {
+          const config = { dataFormat: this.dataFormat };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      class pooling_GlobalAveragePooling2D extends pooling_GlobalPooling2D {
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            const input = getExactlyOneTensor(inputs);
+            if (this.dataFormat === "channelsLast") {
+              return dist["mean"](input, [1, 2]);
+            } else {
+              return dist["mean"](input, [2, 3]);
+            }
+          });
+        }
+      }
+      /** @nocollapse */
+      pooling_GlobalAveragePooling2D.className = "GlobalAveragePooling2D";
+      dist["serialization"].registerClass(pooling_GlobalAveragePooling2D);
+      class pooling_GlobalMaxPooling2D extends pooling_GlobalPooling2D {
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            const input = getExactlyOneTensor(inputs);
+            if (this.dataFormat === "channelsLast") {
+              return dist["max"](input, [1, 2]);
+            } else {
+              return dist["max"](input, [2, 3]);
+            }
+          });
+        }
+      }
+      /** @nocollapse */
+      pooling_GlobalMaxPooling2D.className = "GlobalMaxPooling2D";
+      dist["serialization"].registerClass(pooling_GlobalMaxPooling2D);
+      //# sourceMappingURL=pooling.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/recurrent.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * TensorFlow.js Layers: Recurrent Neural Network Layers.
+       */
+
+      /**
+       * Standardize `apply()` args to a single list of tensor inputs.
+       *
+       * When running a model loaded from file, the input tensors `initialState` and
+       * `constants` are passed to `RNN.apply()` as part of `inputs` instead of the
+       * dedicated kwargs fields. `inputs` consists of
+       * `[inputs, initialState0, initialState1, ..., constant0, constant1]` in this
+       * case.
+       * This method makes sure that arguments are
+       * separated and that `initialState` and `constants` are `Array`s of tensors
+       * (or None).
+       *
+       * @param inputs Tensor or `Array` of  tensors.
+       * @param initialState Tensor or `Array` of tensors or `null`/`undefined`.
+       * @param constants Tensor or `Array` of tensors or `null`/`undefined`.
+       * @returns An object consisting of
+       *   inputs: A tensor.
+       *   initialState: `Array` of tensors or `null`.
+       *   constants: `Array` of tensors or `null`.
+       * @throws ValueError, if `inputs` is an `Array` but either `initialState` or
+       *   `constants` is provided.
+       */
+      function standardizeArgs(inputs, initialState, constants, numConstants) {
+        if (Array.isArray(inputs)) {
+          if (initialState != null || constants != null) {
+            throw new ValueError(
+              "When inputs is an array, neither initialState or constants " + "should be provided"
+            );
+          }
+          if (numConstants != null) {
+            constants = inputs.slice(inputs.length - numConstants, inputs.length);
+            inputs = inputs.slice(0, inputs.length - numConstants);
+          }
+          if (inputs.length > 1) {
+            initialState = inputs.slice(1, inputs.length);
+          }
+          inputs = inputs[0];
+        }
+        function toListOrNull(x) {
+          if (x == null || Array.isArray(x)) {
+            return x;
+          } else {
+            return [x];
+          }
+        }
+        initialState = toListOrNull(initialState);
+        constants = toListOrNull(constants);
+        return { inputs, initialState, constants };
+      }
+      /**
+       * Iterates over the time dimension of a tensor.
+       *
+       * @param stepFunction RNN step function.
+       *   Parameters:
+       *     inputs: tensor with shape `[samples, ...]` (no time dimension),
+       *       representing input for the batch of samples at a certain time step.
+       *     states: an Array of tensors.
+       *   Returns:
+       *     outputs: tensor with shape `[samples, outputDim]` (no time dimension).
+       *     newStates: list of tensors, same length and shapes as `states`. The first
+       *       state in the list must be the output tensor at the previous timestep.
+       * @param inputs Tensor of temporal data of shape `[samples, time, ...]` (at
+       *   least 3D).
+       * @param initialStates Tensor with shape `[samples, outputDim]` (no time
+       *   dimension), containing the initial values of the states used in the step
+       *   function.
+       * @param goBackwards If `true`, do the iteration over the time dimension in
+       *   reverse order and return the reversed sequence.
+       * @param mask Binary tensor with shape `[sample, time, 1]`, with a zero for
+       *   every element that is masked.
+       * @param constants An Array of constant values passed at each step.
+       * @param unroll Whether to unroll the RNN or to use a symbolic loop. *Not*
+       *   applicable to this imperative deeplearn.js backend. Its value is ignored.
+       * @param needPerStepOutputs Whether the per-step outputs are to be
+       *   concatenated into a single tensor and returned (as the second return
+       *   value). Default: `false`. This arg is included so that the relatively
+       *   expensive concatenation of the stepwise outputs can be omitted unless
+       *   the stepwise outputs need to be kept (e.g., for an LSTM layer of which
+       *   `returnSequence` is `true`.)
+       * @returns An Array: `[lastOutput, outputs, newStates]`.
+       *   lastOutput: the lastest output of the RNN, of shape `[samples, ...]`.
+       *   outputs: tensor with shape `[samples, time, ...]` where each entry
+       *     `output[s, t]` is the output of the step function at time `t` for sample
+       *     `s`. This return value is provided if and only if the
+       *     `needPerStepOutputs` is set as `true`. If it is set as `false`, this
+       *     return value will be `undefined`.
+       *   newStates: Array of tensors, latest states returned by the step function,
+       *      of shape `(samples, ...)`.
+       * @throws ValueError If input dimension is less than 3.
+       *
+       * TODO(nielsene): This needs to be tidy-ed.
+       */
+      function rnn(
+        stepFunction,
+        inputs,
+        initialStates,
+        goBackwards = false,
+        mask,
+        constants,
+        unroll = false,
+        needPerStepOutputs = false
+      ) {
+        return dist["tidy"](() => {
+          const ndim = inputs.shape.length;
+          if (ndim < 3) {
+            throw new ValueError(`Input should be at least 3D, but is ${ndim}D.`);
+          }
+          // Transpose to time-major, i.e., from [batch, time, ...] to [time, batch,
+          // ...].
+          const axes = [1, 0].concat(range(2, ndim));
+          inputs = dist["transpose"](inputs, axes);
+          if (constants != null) {
+            throw new NotImplementedError(
+              "The rnn() functoin of the deeplearn.js backend does not support " + "constants yet."
+            );
+          }
+          // Porting Note: the unroll option is ignored by the imperative backend.
+          if (unroll) {
+            console.warn(
+              "Backend rnn(): the unroll = true option is not applicable to the " +
+                "imperative deeplearn.js backend."
+            );
+          }
+          if (mask != null) {
+            mask = mask.asType("bool").asType("float32");
+            if (mask.rank === ndim - 1) {
+              mask = dist["expandDims"](mask, -1);
+            }
+            mask = dist["transpose"](mask, axes);
+          }
+          if (goBackwards) {
+            inputs = dist["reverse"](inputs, 0);
+            if (mask != null) {
+              mask = dist["reverse"](mask, 0);
+            }
+          }
+          // Porting Note: PyKeras with TensorFlow backend uses a symbolic loop
+          //   (tf.while_loop). But for the imperative deeplearn.js backend, we just
+          //   use the usual TypeScript control flow to iterate over the time steps in
+          //   the inputs.
+          // Porting Note: PyKeras patches a "_use_learning_phase" attribute to
+          // outputs.
+          //   This is not idiomatic in TypeScript. The info regarding whether we are
+          //   in a learning (i.e., training) phase for RNN is passed in a different
+          //   way.
+          const perStepOutputs = [];
+          let lastOutput;
+          let states = initialStates;
+          const timeSteps = inputs.shape[0];
+          const perStepInputs = dist["unstack"](inputs);
+          let perStepMasks;
+          if (mask != null) {
+            perStepMasks = dist["unstack"](mask);
+          }
+          for (let t = 0; t < timeSteps; ++t) {
+            const currentInput = perStepInputs[t];
+            const stepOutputs = dist["tidy"](() => stepFunction(currentInput, states));
+            if (mask == null) {
+              lastOutput = stepOutputs[0];
+              states = stepOutputs[1];
+            } else {
+              const maskedOutputs = dist["tidy"](() => {
+                const stepMask = perStepMasks[t];
+                const negStepMask = dist["onesLike"](stepMask).sub(stepMask);
+                // TODO(cais): Would tfc.where() be better for performance?
+                const output = stepOutputs[0].mul(stepMask).add(states[0].mul(negStepMask));
+                const newStates = states.map((state, i) => {
+                  return stepOutputs[1][i].mul(stepMask).add(state.mul(negStepMask));
+                });
+                return { output, newStates };
+              });
+              lastOutput = maskedOutputs.output;
+              states = maskedOutputs.newStates;
+            }
+            if (needPerStepOutputs) {
+              perStepOutputs.push(lastOutput);
+            }
+          }
+          let outputs;
+          if (needPerStepOutputs) {
+            const axis = 1;
+            outputs = dist["stack"](perStepOutputs, axis);
+          }
+          return [lastOutput, outputs, states];
+        });
+      }
+      class recurrent_RNN extends topology_Layer {
+        constructor(args) {
+          super(args);
+          let cell;
+          if (args.cell == null) {
+            throw new ValueError("cell property is missing for the constructor of RNN.");
+          } else if (Array.isArray(args.cell)) {
+            cell = new recurrent_StackedRNNCells({ cells: args.cell });
+          } else {
+            cell = args.cell;
+          }
+          if (cell.stateSize == null) {
+            throw new ValueError(
+              "The RNN cell should have an attribute `stateSize` (tuple of " +
+                "integers, one integer per RNN state)."
+            );
+          }
+          this.cell = cell;
+          this.returnSequences = args.returnSequences == null ? false : args.returnSequences;
+          this.returnState = args.returnState == null ? false : args.returnState;
+          this.goBackwards = args.goBackwards == null ? false : args.goBackwards;
+          this._stateful = args.stateful == null ? false : args.stateful;
+          this.unroll = args.unroll == null ? false : args.unroll;
+          this.supportsMasking = true;
+          this.inputSpec = [new InputSpec({ ndim: 3 })];
+          this.stateSpec = null;
+          this.states_ = null;
+          // TODO(cais): Add constantsSpec and numConstants.
+          this.numConstants = null;
+          // TODO(cais): Look into the use of initial_state in the kwargs of the
+          //   constructor.
+          this.keptStates = [];
+        }
+        // Porting Note: This is the equivalent of `RNN.states` property getter in
+        //   PyKeras.
+        getStates() {
+          if (this.states_ == null) {
+            const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;
+            return range(0, numStates).map((x) => null);
+          } else {
+            return this.states_;
+          }
+        }
+        // Porting Note: This is the equivalent of the `RNN.states` property setter in
+        //   PyKeras.
+        setStates(states) {
+          this.states_ = states;
+        }
+        computeOutputShape(inputShape) {
+          if (isArrayOfShapes(inputShape)) {
+            inputShape = inputShape[0];
+          }
+          inputShape = inputShape;
+          // TODO(cais): Remove the casting once stacked RNN cells become supported.
+          let stateSize = this.cell.stateSize;
+          if (!Array.isArray(stateSize)) {
+            stateSize = [stateSize];
+          }
+          const outputDim = stateSize[0];
+          let outputShape;
+          if (this.returnSequences) {
+            outputShape = [inputShape[0], inputShape[1], outputDim];
+          } else {
+            outputShape = [inputShape[0], outputDim];
+          }
+          if (this.returnState) {
+            const stateShape = [];
+            for (const dim of stateSize) {
+              stateShape.push([inputShape[0], dim]);
+            }
+            return [outputShape].concat(stateShape);
+          } else {
+            return outputShape;
+          }
+        }
+        computeMask(inputs, mask) {
+          return dist["tidy"](() => {
+            if (Array.isArray(mask)) {
+              mask = mask[0];
+            }
+            const outputMask = this.returnSequences ? mask : null;
+            if (this.returnState) {
+              const stateMask = this.states.map((s) => null);
+              return [outputMask].concat(stateMask);
+            } else {
+              return outputMask;
+            }
+          });
+        }
+        /**
+         * Get the current state tensors of the RNN.
+         *
+         * If the state hasn't been set, return an array of `null`s of the correct
+         * length.
+         */
+        get states() {
+          if (this.states_ == null) {
+            const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;
+            const output = [];
+            for (let i = 0; i < numStates; ++i) {
+              output.push(null);
+            }
+            return output;
+          } else {
+            return this.states_;
+          }
+        }
+        set states(s) {
+          this.states_ = s;
+        }
+        build(inputShape) {
+          // Note inputShape will be an Array of Shapes of initial states and
+          // constants if these are passed in apply().
+          const constantShape = null;
+          if (this.numConstants != null) {
+            throw new NotImplementedError("Constants support is not implemented in RNN yet.");
+          }
+          if (isArrayOfShapes(inputShape)) {
+            inputShape = inputShape[0];
+          }
+          inputShape = inputShape;
+          const batchSize = this.stateful ? inputShape[0] : null;
+          const inputDim = inputShape[inputShape.length - 1];
+          this.inputSpec[0] = new InputSpec({ shape: [batchSize, null, inputDim] });
+          // Allow cell (if RNNCell Layer) to build before we set or validate
+          // stateSpec.
+          const stepInputShape = [inputShape[0]].concat(inputShape.slice(2));
+          if (constantShape != null) {
+            throw new NotImplementedError("Constants support is not implemented in RNN yet.");
+          } else {
+            this.cell.build(stepInputShape);
+          }
+          // Set or validate stateSpec.
+          let stateSize;
+          if (Array.isArray(this.cell.stateSize)) {
+            stateSize = this.cell.stateSize;
+          } else {
+            stateSize = [this.cell.stateSize];
+          }
+          if (this.stateSpec != null) {
+            if (
+              !dist["util"].arraysEqual(
+                this.stateSpec.map((spec) => spec.shape[spec.shape.length - 1]),
+                stateSize
+              )
+            ) {
+              throw new ValueError(
+                `An initialState was passed that is not compatible with ` +
+                  `cell.stateSize. Received stateSpec=${this.stateSpec}; ` +
+                  `However cell.stateSize is ${this.cell.stateSize}`
+              );
+            }
+          } else {
+            this.stateSpec = stateSize.map((dim) => new InputSpec({ shape: [null, dim] }));
+          }
+          if (this.stateful) {
+            this.resetStates();
+          }
+        }
+        /**
+         * Reset the state tensors of the RNN.
+         *
+         * If the `states` argument is `undefined` or `null`, will set the
+         * state tensor(s) of the RNN to all-zero tensors of the appropriate
+         * shape(s).
+         *
+         * If `states` is provided, will set the state tensors of the RNN to its
+         * value.
+         *
+         * @param states Optional externally-provided initial states.
+         * @param training Whether this call is done during training. For stateful
+         *   RNNs, this affects whether the old states are kept or discarded. In
+         *   particular, if `training` is `true`, the old states will be kept so
+         *   that subsequent backpropgataion through time (BPTT) may work properly.
+         *   Else, the old states will be discarded.
+         */
+        resetStates(states, training = false) {
+          Object(dist["tidy"])(() => {
+            if (!this.stateful) {
+              throw new AttributeError(
+                "Cannot call resetStates() on an RNN Layer that is not stateful."
+              );
+            }
+            const batchSize = this.inputSpec[0].shape[0];
+            if (batchSize == null) {
+              throw new ValueError(
+                "If an RNN is stateful, it needs to know its batch size. Specify " +
+                  "the batch size of your input tensors: \n" +
+                  "- If using a Sequential model, specify the batch size by " +
+                  "passing a `batchInputShape` option to your first layer.\n" +
+                  "- If using the functional API, specify the batch size by " +
+                  "passing a `batchShape` option to your Input layer."
+              );
+            }
+            // Initialize state if null.
+            if (this.states_ == null) {
+              if (Array.isArray(this.cell.stateSize)) {
+                this.states_ = this.cell.stateSize.map((dim) => dist["zeros"]([batchSize, dim]));
+              } else {
+                this.states_ = [dist["zeros"]([batchSize, this.cell.stateSize])];
+              }
+            } else if (states == null) {
+              // Dispose old state tensors.
+              dist["dispose"](this.states_);
+              // For stateful RNNs, fully dispose kept old states.
+              if (this.keptStates != null) {
+                dist["dispose"](this.keptStates);
+                this.keptStates = [];
+              }
+              if (Array.isArray(this.cell.stateSize)) {
+                this.states_ = this.cell.stateSize.map((dim) => dist["zeros"]([batchSize, dim]));
+              } else {
+                this.states_[0] = dist["zeros"]([batchSize, this.cell.stateSize]);
+              }
+            } else {
+              if (!Array.isArray(states)) {
+                states = [states];
+              }
+              if (states.length !== this.states_.length) {
+                throw new ValueError(
+                  `Layer ${this.name} expects ${this.states_.length} state(s), ` +
+                    `but it received ${states.length} state value(s). Input ` +
+                    `received: ${states}`
+                );
+              }
+              if (training === true) {
+                // Store old state tensors for complete disposal later, i.e., during
+                // the next no-arg call to this method. We do not dispose the old
+                // states immediately because that BPTT (among other things) require
+                // them.
+                this.keptStates.push(this.states_.slice());
+              } else {
+                dist["dispose"](this.states_);
+              }
+              for (let index = 0; index < this.states_.length; ++index) {
+                const value = states[index];
+                const dim = Array.isArray(this.cell.stateSize)
+                  ? this.cell.stateSize[index]
+                  : this.cell.stateSize;
+                const expectedShape = [batchSize, dim];
+                if (!dist["util"].arraysEqual(value.shape, expectedShape)) {
+                  throw new ValueError(
+                    `State ${index} is incompatible with layer ${this.name}: ` +
+                      `expected shape=${expectedShape}, received shape=${value.shape}`
+                  );
+                }
+                this.states_[index] = value;
+              }
+            }
+            this.states_ = this.states_.map((state) => dist["keep"](state.clone()));
+          });
+        }
+        apply(inputs, kwargs) {
+          // TODO(cais): Figure out whether initialState is in kwargs or inputs.
+          let initialState = kwargs == null ? null : kwargs["initialState"];
+          let constants = kwargs == null ? null : kwargs["constants"];
+          if (kwargs == null) {
+            kwargs = {};
+          }
+          const standardized = standardizeArgs(inputs, initialState, constants, this.numConstants);
+          inputs = standardized.inputs;
+          initialState = standardized.initialState;
+          constants = standardized.constants;
+          // If any of `initial_state` or `constants` are specified and are
+          // `tf.SymbolicTensor`s, then add them to the inputs and temporarily modify
+          // the input_spec to include them.
+          let additionalInputs = [];
+          let additionalSpecs = [];
+          if (initialState != null) {
+            kwargs["initialState"] = initialState;
+            additionalInputs = additionalInputs.concat(initialState);
+            this.stateSpec = [];
+            for (const state of initialState) {
+              this.stateSpec.push(new InputSpec({ shape: state.shape }));
+            }
+            // TODO(cais): Use the following instead.
+            // this.stateSpec = initialState.map(state => new InputSpec({shape:
+            // state.shape}));
+            additionalSpecs = additionalSpecs.concat(this.stateSpec);
+          }
+          if (constants != null) {
+            kwargs["constants"] = constants;
+            additionalInputs = additionalInputs.concat(constants);
+            // TODO(cais): Add this.constantsSpec.
+            this.numConstants = constants.length;
+          }
+          const isTensor = additionalInputs[0] instanceof topology_SymbolicTensor;
+          if (isTensor) {
+            // Compute full input spec, including state and constants.
+            const fullInput = [inputs].concat(additionalInputs);
+            const fullInputSpec = this.inputSpec.concat(additionalSpecs);
+            // Perform the call with temporarily replaced inputSpec.
+            const originalInputSpec = this.inputSpec;
+            this.inputSpec = fullInputSpec;
+            const output = super.apply(fullInput, kwargs);
+            this.inputSpec = originalInputSpec;
+            return output;
+          } else {
+            return super.apply(inputs, kwargs);
+          }
+        }
+        // tslint:disable-next-line:no-any
+        call(inputs, kwargs) {
+          // Input shape: `[samples, time (padded with zeros), input_dim]`.
+          // Note that the .build() method of subclasses **must** define
+          // this.inputSpec and this.stateSpec owith complete input shapes.
+          return Object(dist["tidy"])(() => {
+            const mask = kwargs == null ? null : kwargs["mask"];
+            const training = kwargs == null ? null : kwargs["training"];
+            let initialState = kwargs == null ? null : kwargs["initialState"];
+            inputs = getExactlyOneTensor(inputs);
+            if (initialState == null) {
+              if (this.stateful) {
+                initialState = this.states_;
+              } else {
+                initialState = this.getInitialState(inputs);
+              }
+            }
+            const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;
+            if (initialState.length !== numStates) {
+              throw new ValueError(
+                `RNN Layer has ${numStates} state(s) but was passed ` +
+                  `${initialState.length} initial state(s).`
+              );
+            }
+            if (this.unroll) {
+              console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");
+            }
+            const cellCallKwargs = { training };
+            // TODO(cais): Add support for constants.
+            const step = (inputs, states) => {
+              // `inputs` and `states` are concatenated to form a single `Array` of
+              // `tf.Tensor`s as the input to `cell.call()`.
+              const outputs = this.cell.call([inputs].concat(states), cellCallKwargs);
+              // Marshall the return value into output and new states.
+              return [outputs[0], outputs.slice(1)];
+            };
+            // TODO(cais): Add support for constants.
+            const rnnOutputs = rnn(
+              step,
+              inputs,
+              initialState,
+              this.goBackwards,
+              mask,
+              null,
+              this.unroll,
+              this.returnSequences
+            );
+            const lastOutput = rnnOutputs[0];
+            const outputs = rnnOutputs[1];
+            const states = rnnOutputs[2];
+            if (this.stateful) {
+              this.resetStates(states, training);
+            }
+            const output = this.returnSequences ? outputs : lastOutput;
+            // TODO(cais): Porperty set learning phase flag.
+            if (this.returnState) {
+              return [output].concat(states);
+            } else {
+              return output;
+            }
+          });
+        }
+        getInitialState(inputs) {
+          return Object(dist["tidy"])(() => {
+            // Build an all-zero tensor of shape [samples, outputDim].
+            // [Samples, timeSteps, inputDim].
+            let initialState = dist["zeros"](inputs.shape);
+            // [Samples].
+            initialState = dist["sum"](initialState, [1, 2]);
+            initialState = expandDims(initialState); // [Samples, 1].
+            if (Array.isArray(this.cell.stateSize)) {
+              return this.cell.stateSize.map((dim) =>
+                dim > 1 ? tile(initialState, [1, dim]) : initialState
+              );
+            } else {
+              return this.cell.stateSize > 1
+                ? [tile(initialState, [1, this.cell.stateSize])]
+                : [initialState];
+            }
+          });
+        }
+        get trainableWeights() {
+          if (!this.trainable) {
+            return [];
+          }
+          // Porting Note: In TypeScript, `this` is always an instance of `Layer`.
+          return this.cell.trainableWeights;
+        }
+        get nonTrainableWeights() {
+          // Porting Note: In TypeScript, `this` is always an instance of `Layer`.
+          if (!this.trainable) {
+            return this.cell.weights;
+          }
+          return this.cell.nonTrainableWeights;
+        }
+        setFastWeightInitDuringBuild(value) {
+          super.setFastWeightInitDuringBuild(value);
+          if (this.cell != null) {
+            this.cell.setFastWeightInitDuringBuild(value);
+          }
+        }
+        getConfig() {
+          const config = {
+            returnSequences: this.returnSequences,
+            returnState: this.returnState,
+            goBackwards: this.goBackwards,
+            stateful: this.stateful,
+            unroll: this.unroll,
+          };
+          if (this.numConstants != null) {
+            config["numConstants"] = this.numConstants;
+          }
+          const cellConfig = this.cell.getConfig();
+          config["cell"] = {
+            className: this.cell.getClassName(),
+            config: cellConfig,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config, customObjects = {}) {
+          const cellConfig = config["cell"];
+          const cell = deserialize(cellConfig, customObjects);
+          return new cls(Object.assign(config, { cell }));
+        }
+      }
+      /** @nocollapse */
+      recurrent_RNN.className = "RNN";
+      dist["serialization"].registerClass(recurrent_RNN);
+      /**
+       * An RNNCell layer.
+       */
+      // Porting Note: This is a common parent class for RNN cells. There is no
+      // equivalent of this in PyKeras. Having a common parent class forgoes the
+      //  need for `has_attr(cell, ...)` checks or its TypeScript equivalent.
+      /** @doc {heading: 'Layers', subheading: 'Classes'} */
+      class recurrent_RNNCell extends topology_Layer {}
+      class recurrent_SimpleRNNCell extends recurrent_RNNCell {
+        constructor(args) {
+          super(args);
+          this.DEFAULT_ACTIVATION = "tanh";
+          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
+          this.DEFAULT_RECURRENT_INITIALIZER = "orthogonal";
+          this.DEFAULT_BIAS_INITIALIZER = "zeros";
+          this.units = args.units;
+          assertPositiveInteger(this.units, `units`);
+          this.activation = getActivation(
+            args.activation == null ? this.DEFAULT_ACTIVATION : args.activation
+          );
+          this.useBias = args.useBias == null ? true : args.useBias;
+          this.kernelInitializer = getInitializer(
+            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
+          );
+          this.recurrentInitializer = getInitializer(
+            args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER
+          );
+          this.biasInitializer = getInitializer(
+            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
+          );
+          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
+          this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);
+          this.biasRegularizer = getRegularizer(args.biasRegularizer);
+          this.kernelConstraint = getConstraint(args.kernelConstraint);
+          this.recurrentConstraint = getConstraint(args.recurrentConstraint);
+          this.biasConstraint = getConstraint(args.biasConstraint);
+          this.dropout = min([1, max([0, args.dropout == null ? 0 : args.dropout])]);
+          this.recurrentDropout = min([
+            1,
+            max([0, args.recurrentDropout == null ? 0 : args.recurrentDropout]),
+          ]);
+          this.stateSize = this.units;
+          this.dropoutMask = null;
+          this.recurrentDropoutMask = null;
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          // TODO(cais): Use regularizer.
+          this.kernel = this.addWeight(
+            "kernel",
+            [inputShape[inputShape.length - 1], this.units],
+            null,
+            this.kernelInitializer,
+            this.kernelRegularizer,
+            true,
+            this.kernelConstraint
+          );
+          this.recurrentKernel = this.addWeight(
+            "recurrent_kernel",
+            [this.units, this.units],
+            null,
+            this.recurrentInitializer,
+            this.recurrentRegularizer,
+            true,
+            this.recurrentConstraint
+          );
+          if (this.useBias) {
+            this.bias = this.addWeight(
+              "bias",
+              [this.units],
+              null,
+              this.biasInitializer,
+              this.biasRegularizer,
+              true,
+              this.biasConstraint
+            );
+          } else {
+            this.bias = null;
+          }
+          this.built = true;
+        }
+        // Porting Note: PyKeras' equivalent of this method takes two tensor inputs:
+        //   `inputs` and `states`. Here, the two tensors are combined into an
+        //   `Tensor[]` Array as the first input argument.
+        //   Similarly, PyKeras' equivalent of this method returns two values:
+        //    `output` and `[output]`. Here the two are combined into one length-2
+        //    `Tensor[]`, consisting of `output` repeated.
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = inputs;
+            if (inputs.length !== 2) {
+              throw new ValueError(`SimpleRNNCell expects 2 input Tensors, got ${inputs.length}.`);
+            }
+            let prevOutput = inputs[1];
+            inputs = inputs[0];
+            const training = kwargs["training"] == null ? false : kwargs["training"];
+            if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {
+              this.dropoutMask = generateDropoutMask(
+                () => dist["onesLike"](inputs),
+                this.dropout,
+                training
+              );
+            }
+            if (
+              0 < this.recurrentDropout &&
+              this.recurrentDropout < 1 &&
+              this.recurrentDropoutMask == null
+            ) {
+              this.recurrentDropoutMask = generateDropoutMask(
+                () => dist["onesLike"](prevOutput),
+                this.recurrentDropout,
+                training
+              );
+            }
+            let h;
+            const dpMask = this.dropoutMask;
+            const recDpMask = this.recurrentDropoutMask;
+            if (dpMask != null) {
+              h = dot(dist["mul"](inputs, dpMask), this.kernel.read());
+            } else {
+              h = dot(inputs, this.kernel.read());
+            }
+            if (this.bias != null) {
+              h = biasAdd(h, this.bias.read());
+            }
+            if (recDpMask != null) {
+              prevOutput = dist["mul"](prevOutput, recDpMask);
+            }
+            let output = dist["add"](h, dot(prevOutput, this.recurrentKernel.read()));
+            if (this.activation != null) {
+              output = this.activation.apply(output);
+            }
+            // TODO(cais): Properly set learning phase on output tensor?
+            return [output, output];
+          });
+        }
+        getConfig() {
+          const config = {
+            units: this.units,
+            activation: serializeActivation(this.activation),
+            useBias: this.useBias,
+            kernelInitializer: serializeInitializer(this.kernelInitializer),
+            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
+            biasInitializer: serializeInitializer(this.biasInitializer),
+            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
+            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
+            biasRegularizer: serializeRegularizer(this.biasRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            kernelConstraint: serializeConstraint(this.kernelConstraint),
+            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
+            biasConstraint: serializeConstraint(this.biasConstraint),
+            dropout: this.dropout,
+            recurrentDropout: this.recurrentDropout,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      recurrent_SimpleRNNCell.className = "SimpleRNNCell";
+      dist["serialization"].registerClass(recurrent_SimpleRNNCell);
+      class recurrent_SimpleRNN extends recurrent_RNN {
+        constructor(args) {
+          args.cell = new recurrent_SimpleRNNCell(args);
+          super(args);
+          // TODO(cais): Add activityRegularizer.
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            if (this.cell.dropoutMask != null) {
+              dist["dispose"](this.cell.dropoutMask);
+              this.cell.dropoutMask = null;
+            }
+            if (this.cell.recurrentDropoutMask != null) {
+              dist["dispose"](this.cell.recurrentDropoutMask);
+              this.cell.recurrentDropoutMask = null;
+            }
+            const mask = kwargs == null ? null : kwargs["mask"];
+            const training = kwargs == null ? null : kwargs["training"];
+            const initialState = kwargs == null ? null : kwargs["initialState"];
+            return super.call(inputs, { mask, training, initialState });
+          });
+        }
+        // TODO(cais): Research possibility of refactoring out the tedious all
+        //   the getters that delegate to `this.cell` below.
+        get units() {
+          return this.cell.units;
+        }
+        get activation() {
+          return this.cell.activation;
+        }
+        get useBias() {
+          return this.cell.useBias;
+        }
+        get kernelInitializer() {
+          return this.cell.kernelInitializer;
+        }
+        get recurrentInitializer() {
+          return this.cell.recurrentInitializer;
+        }
+        get biasInitializer() {
+          return this.cell.biasInitializer;
+        }
+        get kernelRegularizer() {
+          return this.cell.kernelRegularizer;
+        }
+        get recurrentRegularizer() {
+          return this.cell.recurrentRegularizer;
+        }
+        get biasRegularizer() {
+          return this.cell.biasRegularizer;
+        }
+        get kernelConstraint() {
+          return this.cell.kernelConstraint;
+        }
+        get recurrentConstraint() {
+          return this.cell.recurrentConstraint;
+        }
+        get biasConstraint() {
+          return this.cell.biasConstraint;
+        }
+        get dropout() {
+          return this.cell.dropout;
+        }
+        get recurrentDropout() {
+          return this.cell.recurrentDropout;
+        }
+        getConfig() {
+          const config = {
+            units: this.units,
+            activation: serializeActivation(this.activation),
+            useBias: this.useBias,
+            kernelInitializer: serializeInitializer(this.kernelInitializer),
+            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
+            biasInitializer: serializeInitializer(this.biasInitializer),
+            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
+            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
+            biasRegularizer: serializeRegularizer(this.biasRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            kernelConstraint: serializeConstraint(this.kernelConstraint),
+            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
+            biasConstraint: serializeConstraint(this.biasConstraint),
+            dropout: this.dropout,
+            recurrentDropout: this.recurrentDropout,
+          };
+          const baseConfig = super.getConfig();
+          delete baseConfig["cell"];
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          return new cls(config);
+        }
+      }
+      /** @nocollapse */
+      recurrent_SimpleRNN.className = "SimpleRNN";
+      dist["serialization"].registerClass(recurrent_SimpleRNN);
+      class recurrent_GRUCell extends recurrent_RNNCell {
+        constructor(args) {
+          super(args);
+          this.DEFAULT_ACTIVATION = "tanh";
+          this.DEFAULT_RECURRENT_ACTIVATION = "hardSigmoid";
+          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
+          this.DEFAULT_RECURRENT_INITIALIZER = "orthogonal";
+          this.DEFAULT_BIAS_INITIALIZER = "zeros";
+          if (args.resetAfter) {
+            throw new ValueError(`GRUCell does not support reset_after parameter set to true.`);
+          }
+          this.units = args.units;
+          assertPositiveInteger(this.units, "units");
+          this.activation = getActivation(
+            args.activation === undefined ? this.DEFAULT_ACTIVATION : args.activation
+          );
+          this.recurrentActivation = getActivation(
+            args.recurrentActivation === undefined
+              ? this.DEFAULT_RECURRENT_ACTIVATION
+              : args.recurrentActivation
+          );
+          this.useBias = args.useBias == null ? true : args.useBias;
+          this.kernelInitializer = getInitializer(
+            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
+          );
+          this.recurrentInitializer = getInitializer(
+            args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER
+          );
+          this.biasInitializer = getInitializer(
+            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
+          );
+          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
+          this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);
+          this.biasRegularizer = getRegularizer(args.biasRegularizer);
+          this.kernelConstraint = getConstraint(args.kernelConstraint);
+          this.recurrentConstraint = getConstraint(args.recurrentConstraint);
+          this.biasConstraint = getConstraint(args.biasConstraint);
+          this.dropout = min([1, max([0, args.dropout == null ? 0 : args.dropout])]);
+          this.recurrentDropout = min([
+            1,
+            max([0, args.recurrentDropout == null ? 0 : args.recurrentDropout]),
+          ]);
+          this.implementation = args.implementation;
+          this.stateSize = this.units;
+          this.dropoutMask = null;
+          this.recurrentDropoutMask = null;
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const inputDim = inputShape[inputShape.length - 1];
+          this.kernel = this.addWeight(
+            "kernel",
+            [inputDim, this.units * 3],
+            null,
+            this.kernelInitializer,
+            this.kernelRegularizer,
+            true,
+            this.kernelConstraint
+          );
+          this.recurrentKernel = this.addWeight(
+            "recurrent_kernel",
+            [this.units, this.units * 3],
+            null,
+            this.recurrentInitializer,
+            this.recurrentRegularizer,
+            true,
+            this.recurrentConstraint
+          );
+          if (this.useBias) {
+            this.bias = this.addWeight(
+              "bias",
+              [this.units * 3],
+              null,
+              this.biasInitializer,
+              this.biasRegularizer,
+              true,
+              this.biasConstraint
+            );
+          } else {
+            this.bias = null;
+          }
+          // Porting Notes: Unlike the PyKeras implementation, we perform slicing
+          //   of the weights and bias in the call() method, at execution time.
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = inputs;
+            if (inputs.length !== 2) {
+              throw new ValueError(
+                `GRUCell expects 2 input Tensors (inputs, h, c), got ` + `${inputs.length}.`
+              );
+            }
+            const training = kwargs["training"] == null ? false : kwargs["training"];
+            let hTMinus1 = inputs[1]; // Previous memory state.
+            inputs = inputs[0];
+            // Note: For superior performance, TensorFlow.js always uses
+            // implementation 2, regardless of the actual value of
+            // config.implementation.
+            if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {
+              this.dropoutMask = generateDropoutMask(
+                () => dist["onesLike"](inputs),
+                this.dropout,
+                training,
+                3
+              );
+            }
+            if (
+              0 < this.recurrentDropout &&
+              this.recurrentDropout < 1 &&
+              this.recurrentDropoutMask == null
+            ) {
+              this.recurrentDropoutMask = generateDropoutMask(
+                () => dist["onesLike"](hTMinus1),
+                this.recurrentDropout,
+                training,
+                3
+              );
+            }
+            const dpMask = this.dropoutMask;
+            const recDpMask = this.recurrentDropoutMask;
+            let z;
+            let r;
+            let hh;
+            if (0 < this.dropout && this.dropout < 1) {
+              inputs = dist["mul"](inputs, dpMask[0]);
+            }
+            let matrixX = dot(inputs, this.kernel.read());
+            if (this.useBias) {
+              matrixX = biasAdd(matrixX, this.bias.read());
+            }
+            if (0 < this.recurrentDropout && this.recurrentDropout < 1) {
+              hTMinus1 = dist["mul"](hTMinus1, recDpMask[0]);
+            }
+            const recurrentKernelValue = this.recurrentKernel.read();
+            const [rk1, rk2] = dist["split"](
+              recurrentKernelValue,
+              [2 * this.units, this.units],
+              recurrentKernelValue.rank - 1
+            );
+            const matrixInner = dot(hTMinus1, rk1);
+            const [xZ, xR, xH] = dist["split"](matrixX, 3, matrixX.rank - 1);
+            const [recurrentZ, recurrentR] = dist["split"](matrixInner, 2, matrixInner.rank - 1);
+            z = this.recurrentActivation.apply(dist["add"](xZ, recurrentZ));
+            r = this.recurrentActivation.apply(dist["add"](xR, recurrentR));
+            const recurrentH = dot(dist["mul"](r, hTMinus1), rk2);
+            hh = this.activation.apply(dist["add"](xH, recurrentH));
+            const h = dist["add"](
+              dist["mul"](z, hTMinus1),
+              dist["mul"](dist["add"](1, dist["neg"](z)), hh)
+            );
+            // TODO(cais): Add use_learning_phase flag properly.
+            return [h, h];
+          });
+        }
+        getConfig() {
+          const config = {
+            units: this.units,
+            activation: serializeActivation(this.activation),
+            recurrentActivation: serializeActivation(this.recurrentActivation),
+            useBias: this.useBias,
+            kernelInitializer: serializeInitializer(this.kernelInitializer),
+            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
+            biasInitializer: serializeInitializer(this.biasInitializer),
+            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
+            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
+            biasRegularizer: serializeRegularizer(this.biasRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            kernelConstraint: serializeConstraint(this.kernelConstraint),
+            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
+            biasConstraint: serializeConstraint(this.biasConstraint),
+            dropout: this.dropout,
+            recurrentDropout: this.recurrentDropout,
+            implementation: this.implementation,
+            resetAfter: false,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      recurrent_GRUCell.className = "GRUCell";
+      dist["serialization"].registerClass(recurrent_GRUCell);
+      class recurrent_GRU extends recurrent_RNN {
+        constructor(args) {
+          if (args.implementation === 0) {
+            console.warn(
+              "`implementation=0` has been deprecated, and now defaults to " +
+                "`implementation=1`. Please update your layer call."
+            );
+          }
+          args.cell = new recurrent_GRUCell(args);
+          super(args);
+          // TODO(cais): Add activityRegularizer.
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            if (this.cell.dropoutMask != null) {
+              dist["dispose"](this.cell.dropoutMask);
+              this.cell.dropoutMask = null;
+            }
+            if (this.cell.recurrentDropoutMask != null) {
+              dist["dispose"](this.cell.recurrentDropoutMask);
+              this.cell.recurrentDropoutMask = null;
+            }
+            const mask = kwargs == null ? null : kwargs["mask"];
+            const training = kwargs == null ? null : kwargs["training"];
+            const initialState = kwargs == null ? null : kwargs["initialState"];
+            return super.call(inputs, { mask, training, initialState });
+          });
+        }
+        get units() {
+          return this.cell.units;
+        }
+        get activation() {
+          return this.cell.activation;
+        }
+        get recurrentActivation() {
+          return this.cell.recurrentActivation;
+        }
+        get useBias() {
+          return this.cell.useBias;
+        }
+        get kernelInitializer() {
+          return this.cell.kernelInitializer;
+        }
+        get recurrentInitializer() {
+          return this.cell.recurrentInitializer;
+        }
+        get biasInitializer() {
+          return this.cell.biasInitializer;
+        }
+        get kernelRegularizer() {
+          return this.cell.kernelRegularizer;
+        }
+        get recurrentRegularizer() {
+          return this.cell.recurrentRegularizer;
+        }
+        get biasRegularizer() {
+          return this.cell.biasRegularizer;
+        }
+        get kernelConstraint() {
+          return this.cell.kernelConstraint;
+        }
+        get recurrentConstraint() {
+          return this.cell.recurrentConstraint;
+        }
+        get biasConstraint() {
+          return this.cell.biasConstraint;
+        }
+        get dropout() {
+          return this.cell.dropout;
+        }
+        get recurrentDropout() {
+          return this.cell.recurrentDropout;
+        }
+        get implementation() {
+          return this.cell.implementation;
+        }
+        getConfig() {
+          const config = {
+            units: this.units,
+            activation: serializeActivation(this.activation),
+            recurrentActivation: serializeActivation(this.recurrentActivation),
+            useBias: this.useBias,
+            kernelInitializer: serializeInitializer(this.kernelInitializer),
+            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
+            biasInitializer: serializeInitializer(this.biasInitializer),
+            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
+            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
+            biasRegularizer: serializeRegularizer(this.biasRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            kernelConstraint: serializeConstraint(this.kernelConstraint),
+            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
+            biasConstraint: serializeConstraint(this.biasConstraint),
+            dropout: this.dropout,
+            recurrentDropout: this.recurrentDropout,
+            implementation: this.implementation,
+            resetAfter: false,
+          };
+          const baseConfig = super.getConfig();
+          delete baseConfig["cell"];
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          if (config["implmentation"] === 0) {
+            config["implementation"] = 1;
+          }
+          return new cls(config);
+        }
+      }
+      /** @nocollapse */
+      recurrent_GRU.className = "GRU";
+      dist["serialization"].registerClass(recurrent_GRU);
+      class recurrent_LSTMCell extends recurrent_RNNCell {
+        constructor(args) {
+          super(args);
+          this.DEFAULT_ACTIVATION = "tanh";
+          this.DEFAULT_RECURRENT_ACTIVATION = "hardSigmoid";
+          this.DEFAULT_KERNEL_INITIALIZER = "glorotNormal";
+          this.DEFAULT_RECURRENT_INITIALIZER = "orthogonal";
+          this.DEFAULT_BIAS_INITIALIZER = "zeros";
+          this.units = args.units;
+          assertPositiveInteger(this.units, "units");
+          this.activation = getActivation(
+            args.activation === undefined ? this.DEFAULT_ACTIVATION : args.activation
+          );
+          this.recurrentActivation = getActivation(
+            args.recurrentActivation === undefined
+              ? this.DEFAULT_RECURRENT_ACTIVATION
+              : args.recurrentActivation
+          );
+          this.useBias = args.useBias == null ? true : args.useBias;
+          this.kernelInitializer = getInitializer(
+            args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER
+          );
+          this.recurrentInitializer = getInitializer(
+            args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER
+          );
+          this.biasInitializer = getInitializer(
+            args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER
+          );
+          this.unitForgetBias = args.unitForgetBias;
+          this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
+          this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);
+          this.biasRegularizer = getRegularizer(args.biasRegularizer);
+          this.kernelConstraint = getConstraint(args.kernelConstraint);
+          this.recurrentConstraint = getConstraint(args.recurrentConstraint);
+          this.biasConstraint = getConstraint(args.biasConstraint);
+          this.dropout = min([1, max([0, args.dropout == null ? 0 : args.dropout])]);
+          this.recurrentDropout = min([
+            1,
+            max([0, args.recurrentDropout == null ? 0 : args.recurrentDropout]),
+          ]);
+          this.implementation = args.implementation;
+          this.stateSize = [this.units, this.units];
+          this.dropoutMask = null;
+          this.recurrentDropoutMask = null;
+        }
+        build(inputShape) {
+          var _a;
+          inputShape = getExactlyOneShape(inputShape);
+          const inputDim = inputShape[inputShape.length - 1];
+          this.kernel = this.addWeight(
+            "kernel",
+            [inputDim, this.units * 4],
+            null,
+            this.kernelInitializer,
+            this.kernelRegularizer,
+            true,
+            this.kernelConstraint
+          );
+          this.recurrentKernel = this.addWeight(
+            "recurrent_kernel",
+            [this.units, this.units * 4],
+            null,
+            this.recurrentInitializer,
+            this.recurrentRegularizer,
+            true,
+            this.recurrentConstraint
+          );
+          let biasInitializer;
+          if (this.useBias) {
+            if (this.unitForgetBias) {
+              const capturedBiasInit = this.biasInitializer;
+              const capturedUnits = this.units;
+              biasInitializer = new ((_a = class CustomInit extends initializers_Initializer {
+                apply(shape, dtype) {
+                  // TODO(cais): More informative variable names?
+                  const bI = capturedBiasInit.apply([capturedUnits]);
+                  const bF = new initializers_Ones().apply([capturedUnits]);
+                  const bCAndH = capturedBiasInit.apply([capturedUnits * 2]);
+                  return concatAlongFirstAxis(concatAlongFirstAxis(bI, bF), bCAndH);
+                }
+              }),
+              /** @nocollapse */
+              (_a.className = "CustomInit"),
+              _a)();
+            } else {
+              biasInitializer = this.biasInitializer;
+            }
+            this.bias = this.addWeight(
+              "bias",
+              [this.units * 4],
+              null,
+              biasInitializer,
+              this.biasRegularizer,
+              true,
+              this.biasConstraint
+            );
+          } else {
+            this.bias = null;
+          }
+          // Porting Notes: Unlike the PyKeras implementation, we perform slicing
+          //   of the weights and bias in the call() method, at execution time.
+          this.built = true;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            const training = kwargs["training"] == null ? false : kwargs["training"];
+            inputs = inputs;
+            if (inputs.length !== 3) {
+              throw new ValueError(
+                `LSTMCell expects 3 input Tensors (inputs, h, c), got ` + `${inputs.length}.`
+              );
+            }
+            let hTMinus1 = inputs[1]; // Previous memory state.
+            const cTMinus1 = inputs[2]; // Previous carry state.
+            inputs = inputs[0];
+            if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {
+              this.dropoutMask = generateDropoutMask(
+                () => dist["onesLike"](inputs),
+                this.dropout,
+                training,
+                4
+              );
+            }
+            if (
+              0 < this.recurrentDropout &&
+              this.recurrentDropout < 1 &&
+              this.recurrentDropoutMask == null
+            ) {
+              this.recurrentDropoutMask = generateDropoutMask(
+                () => dist["onesLike"](hTMinus1),
+                this.recurrentDropout,
+                training,
+                4
+              );
+            }
+            const dpMask = this.dropoutMask;
+            const recDpMask = this.recurrentDropoutMask;
+            // Note: For superior performance, TensorFlow.js always uses
+            // implementation 2 regardless of the actual value of
+            // config.implementation.
+            let i;
+            let f;
+            let c;
+            let o;
+            if (0 < this.dropout && this.dropout < 1) {
+              inputs = dist["mul"](inputs, dpMask[0]);
+            }
+            let z = dot(inputs, this.kernel.read());
+            if (0 < this.recurrentDropout && this.recurrentDropout < 1) {
+              hTMinus1 = dist["mul"](hTMinus1, recDpMask[0]);
+            }
+            z = dist["add"](z, dot(hTMinus1, this.recurrentKernel.read()));
+            if (this.useBias) {
+              z = biasAdd(z, this.bias.read());
+            }
+            const [z0, z1, z2, z3] = dist["split"](z, 4, z.rank - 1);
+            i = this.recurrentActivation.apply(z0);
+            f = this.recurrentActivation.apply(z1);
+            c = dist["add"](dist["mul"](f, cTMinus1), dist["mul"](i, this.activation.apply(z2)));
+            o = this.recurrentActivation.apply(z3);
+            const h = dist["mul"](o, this.activation.apply(c));
+            // TODO(cais): Add use_learning_phase flag properly.
+            return [h, h, c];
+          });
+        }
+        getConfig() {
+          const config = {
+            units: this.units,
+            activation: serializeActivation(this.activation),
+            recurrentActivation: serializeActivation(this.recurrentActivation),
+            useBias: this.useBias,
+            kernelInitializer: serializeInitializer(this.kernelInitializer),
+            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
+            biasInitializer: serializeInitializer(this.biasInitializer),
+            unitForgetBias: this.unitForgetBias,
+            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
+            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
+            biasRegularizer: serializeRegularizer(this.biasRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            kernelConstraint: serializeConstraint(this.kernelConstraint),
+            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
+            biasConstraint: serializeConstraint(this.biasConstraint),
+            dropout: this.dropout,
+            recurrentDropout: this.recurrentDropout,
+            implementation: this.implementation,
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+      }
+      /** @nocollapse */
+      recurrent_LSTMCell.className = "LSTMCell";
+      dist["serialization"].registerClass(recurrent_LSTMCell);
+      class recurrent_LSTM extends recurrent_RNN {
+        constructor(args) {
+          if (args.implementation === 0) {
+            console.warn(
+              "`implementation=0` has been deprecated, and now defaults to " +
+                "`implementation=1`. Please update your layer call."
+            );
+          }
+          args.cell = new recurrent_LSTMCell(args);
+          super(args);
+          // TODO(cais): Add activityRegularizer.
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            if (this.cell.dropoutMask != null) {
+              dist["dispose"](this.cell.dropoutMask);
+              this.cell.dropoutMask = null;
+            }
+            if (this.cell.recurrentDropoutMask != null) {
+              dist["dispose"](this.cell.recurrentDropoutMask);
+              this.cell.recurrentDropoutMask = null;
+            }
+            const mask = kwargs == null ? null : kwargs["mask"];
+            const training = kwargs == null ? null : kwargs["training"];
+            const initialState = kwargs == null ? null : kwargs["initialState"];
+            return super.call(inputs, { mask, training, initialState });
+          });
+        }
+        get units() {
+          return this.cell.units;
+        }
+        get activation() {
+          return this.cell.activation;
+        }
+        get recurrentActivation() {
+          return this.cell.recurrentActivation;
+        }
+        get useBias() {
+          return this.cell.useBias;
+        }
+        get kernelInitializer() {
+          return this.cell.kernelInitializer;
+        }
+        get recurrentInitializer() {
+          return this.cell.recurrentInitializer;
+        }
+        get biasInitializer() {
+          return this.cell.biasInitializer;
+        }
+        get unitForgetBias() {
+          return this.cell.unitForgetBias;
+        }
+        get kernelRegularizer() {
+          return this.cell.kernelRegularizer;
+        }
+        get recurrentRegularizer() {
+          return this.cell.recurrentRegularizer;
+        }
+        get biasRegularizer() {
+          return this.cell.biasRegularizer;
+        }
+        get kernelConstraint() {
+          return this.cell.kernelConstraint;
+        }
+        get recurrentConstraint() {
+          return this.cell.recurrentConstraint;
+        }
+        get biasConstraint() {
+          return this.cell.biasConstraint;
+        }
+        get dropout() {
+          return this.cell.dropout;
+        }
+        get recurrentDropout() {
+          return this.cell.recurrentDropout;
+        }
+        get implementation() {
+          return this.cell.implementation;
+        }
+        getConfig() {
+          const config = {
+            units: this.units,
+            activation: serializeActivation(this.activation),
+            recurrentActivation: serializeActivation(this.recurrentActivation),
+            useBias: this.useBias,
+            kernelInitializer: serializeInitializer(this.kernelInitializer),
+            recurrentInitializer: serializeInitializer(this.recurrentInitializer),
+            biasInitializer: serializeInitializer(this.biasInitializer),
+            unitForgetBias: this.unitForgetBias,
+            kernelRegularizer: serializeRegularizer(this.kernelRegularizer),
+            recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),
+            biasRegularizer: serializeRegularizer(this.biasRegularizer),
+            activityRegularizer: serializeRegularizer(this.activityRegularizer),
+            kernelConstraint: serializeConstraint(this.kernelConstraint),
+            recurrentConstraint: serializeConstraint(this.recurrentConstraint),
+            biasConstraint: serializeConstraint(this.biasConstraint),
+            dropout: this.dropout,
+            recurrentDropout: this.recurrentDropout,
+            implementation: this.implementation,
+          };
+          const baseConfig = super.getConfig();
+          delete baseConfig["cell"];
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          if (config["implmentation"] === 0) {
+            config["implementation"] = 1;
+          }
+          return new cls(config);
+        }
+      }
+      /** @nocollapse */
+      recurrent_LSTM.className = "LSTM";
+      dist["serialization"].registerClass(recurrent_LSTM);
+      class recurrent_StackedRNNCells extends recurrent_RNNCell {
+        constructor(args) {
+          super(args);
+          this.cells = args.cells;
+        }
+        get stateSize() {
+          // States are a flat list in reverse order of the cell stack.
+          // This allows perserving the requirement `stack.statesize[0] ===
+          // outputDim`. E.g., states of a 2-layer LSTM would be `[h2, c2, h1, c1]`,
+          // assuming one LSTM has states `[h, c]`.
+          const stateSize = [];
+          for (const cell of this.cells.slice().reverse()) {
+            if (Array.isArray(cell.stateSize)) {
+              stateSize.push(...cell.stateSize);
+            } else {
+              stateSize.push(cell.stateSize);
+            }
+          }
+          return stateSize;
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            inputs = inputs;
+            let states = inputs.slice(1);
+            // Recover per-cell states.
+            const nestedStates = [];
+            for (const cell of this.cells.slice().reverse()) {
+              if (Array.isArray(cell.stateSize)) {
+                nestedStates.push(states.splice(0, cell.stateSize.length));
+              } else {
+                nestedStates.push(states.splice(0, 1));
+              }
+            }
+            nestedStates.reverse();
+            // Call the cells in order and store the returned states.
+            const newNestedStates = [];
+            let callInputs;
+            for (let i = 0; i < this.cells.length; ++i) {
+              const cell = this.cells[i];
+              states = nestedStates[i];
+              // TODO(cais): Take care of constants.
+              if (i === 0) {
+                callInputs = [inputs[0]].concat(states);
+              } else {
+                callInputs = [callInputs[0]].concat(states);
+              }
+              callInputs = cell.call(callInputs, kwargs);
+              newNestedStates.push(callInputs.slice(1));
+            }
+            // Format the new states as a flat list in reverse cell order.
+            states = [];
+            for (const cellStates of newNestedStates.slice().reverse()) {
+              states.push(...cellStates);
+            }
+            return [callInputs[0]].concat(states);
+          });
+        }
+        build(inputShape) {
+          if (isArrayOfShapes(inputShape)) {
+            // TODO(cais): Take care of input constants.
+            // const constantShape = inputShape.slice(1);
+            inputShape = inputShape[0];
+          }
+          inputShape = inputShape;
+          let outputDim;
+          this.cells.forEach((cell, i) => {
+            nameScope(`RNNCell_${i}`, () => {
+              // TODO(cais): Take care of input constants.
+              cell.build(inputShape);
+              if (Array.isArray(cell.stateSize)) {
+                outputDim = cell.stateSize[0];
+              } else {
+                outputDim = cell.stateSize;
+              }
+              inputShape = [inputShape[0], outputDim];
+            });
+          });
+          this.built = true;
+        }
+        getConfig() {
+          const cellConfigs = [];
+          for (const cell of this.cells) {
+            cellConfigs.push({
+              className: cell.getClassName(),
+              config: cell.getConfig(),
+            });
+          }
+          const config = { cells: cellConfigs };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config, customObjects = {}) {
+          const cells = [];
+          for (const cellConfig of config["cells"]) {
+            cells.push(deserialize(cellConfig, customObjects));
+          }
+          return new cls({ cells });
+        }
+        get trainableWeights() {
+          if (!this.trainable) {
+            return [];
+          }
+          const weights = [];
+          for (const cell of this.cells) {
+            weights.push(...cell.trainableWeights);
+          }
+          return weights;
+        }
+        get nonTrainableWeights() {
+          const weights = [];
+          for (const cell of this.cells) {
+            weights.push(...cell.nonTrainableWeights);
+          }
+          if (!this.trainable) {
+            const trainableWeights = [];
+            for (const cell of this.cells) {
+              trainableWeights.push(...cell.trainableWeights);
+            }
+            return trainableWeights.concat(weights);
+          }
+          return weights;
+        }
+        /**
+         * Retrieve the weights of a the model.
+         *
+         * @returns A flat `Array` of `tf.Tensor`s.
+         */
+        getWeights() {
+          const weights = [];
+          for (const cell of this.cells) {
+            weights.push(...cell.weights);
+          }
+          return batchGetValue(weights);
+        }
+        /**
+         * Set the weights of the model.
+         *
+         * @param weights An `Array` of `tf.Tensor`s with shapes and types matching
+         *     the output of `getWeights()`.
+         */
+        setWeights(weights) {
+          const tuples = [];
+          for (const cell of this.cells) {
+            const numParams = cell.weights.length;
+            const inputWeights = weights.splice(numParams);
+            for (let i = 0; i < cell.weights.length; ++i) {
+              tuples.push([cell.weights[i], inputWeights[i]]);
+            }
+          }
+          batchSetValue(tuples);
+        }
+      }
+      /** @nocollapse */
+      recurrent_StackedRNNCells.className = "StackedRNNCells";
+      dist["serialization"].registerClass(recurrent_StackedRNNCells);
+      function generateDropoutMask(ones, rate, training = null, count = 1) {
+        function droppedInputs() {
+          return dropout(ones(), rate);
+        }
+        if (count > 1) {
+          const mask = [];
+          for (let i = 0; i < count; i++) {
+            mask.push(inTrainPhase(droppedInputs, ones, training));
+          }
+          return mask.map((m) => dist["keep"](m.clone()));
+        } else {
+          return dist["keep"](inTrainPhase(droppedInputs, ones, training).clone());
+        }
+      }
+      //# sourceMappingURL=recurrent.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/layers/wrappers.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /**
+       * Layers that augment the functionality of a base layer.
+       */
+
+      /**
+       * Abstract wrapper base class.
+       *
+       * Wrappers take another layer and augment it in various ways.
+       * Do not use this class as a layer, it is only an abstract base class.
+       * Two usable wrappers are the `TimeDistributed` and `Bidirectional` wrappers.
+       */
+      class wrappers_Wrapper extends topology_Layer {
+        constructor(args) {
+          // Porting Note: In PyKeras, `self.layer` is set prior to the calling
+          //   `super()`. But we can't do that here due to TypeScript's restriction.
+          //   See: https://github.com/Microsoft/TypeScript/issues/8277
+          //   As a result, we have to add checks in `get trainable()` and
+          //   `set trainable()` below in order to prevent using `this.layer` when
+          //   its value is `undefined`. The super constructor does use the getter
+          //   and the setter of `this.layer`.
+          super(args);
+          this.layer = args.layer;
+        }
+        build(inputShape) {
+          this.built = true;
+        }
+        // TODO(cais): Implement activityRegularizer getter.
+        get trainable() {
+          // Porting Note: the check of `this.layer` here is necessary due to the
+          //   way the `constructor` of this class is written (see Porting Note
+          //   above).
+          if (this.layer != null) {
+            return this.layer.trainable;
+          } else {
+            return false;
+          }
+        }
+        set trainable(value) {
+          // Porting Note: the check of `this.layer` here is necessary due to the
+          //   way the `constructor` of this class is written (see Porting Note
+          //   above).
+          if (this.layer != null) {
+            this.layer.trainable = value;
+          }
+        }
+        get trainableWeights() {
+          return this.layer.trainableWeights;
+        }
+        // TODO(cais): Implement setter for trainableWeights.
+        get nonTrainableWeights() {
+          return this.layer.nonTrainableWeights;
+        }
+        // TODO(cais): Implement setter for nonTrainableWeights.
+        get updates() {
+          // tslint:disable-next-line:no-any
+          return this.layer._updates;
+        }
+        // TODO(cais): Implement getUpdatesFor().
+        get losses() {
+          return this.layer.losses;
+        }
+        // TODO(cais): Implement getLossesFor().
+        getWeights() {
+          return this.layer.getWeights();
+        }
+        setWeights(weights) {
+          this.layer.setWeights(weights);
+        }
+        getConfig() {
+          const config = {
+            layer: {
+              className: this.layer.getClassName(),
+              config: this.layer.getConfig(),
+            },
+          };
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        setFastWeightInitDuringBuild(value) {
+          super.setFastWeightInitDuringBuild(value);
+          if (this.layer != null) {
+            this.layer.setFastWeightInitDuringBuild(value);
+          }
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config, customObjects = {}) {
+          const layerConfig = config["layer"];
+          const layer = deserialize(layerConfig, customObjects);
+          delete config["layer"];
+          const newConfig = { layer };
+          Object.assign(newConfig, config);
+          return new cls(newConfig);
+        }
+      }
+      class wrappers_TimeDistributed extends wrappers_Wrapper {
+        constructor(args) {
+          super(args);
+          this.supportsMasking = true;
+        }
+        build(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          if (inputShape.length < 3) {
+            throw new ValueError(
+              `TimeDistributed layer expects an input shape >= 3D, but received ` +
+                `input shape ${JSON.stringify(inputShape)}`
+            );
+          }
+          this.inputSpec = [{ shape: inputShape }];
+          const childInputShape = [inputShape[0]].concat(inputShape.slice(2));
+          if (!this.layer.built) {
+            this.layer.build(childInputShape);
+            this.layer.built = true;
+          }
+          super.build(inputShape);
+        }
+        computeOutputShape(inputShape) {
+          inputShape = getExactlyOneShape(inputShape);
+          const childInputShape = [inputShape[0]].concat(inputShape.slice(2));
+          const childOutputShape = this.layer.computeOutputShape(childInputShape);
+          const timesteps = inputShape[1];
+          return [childOutputShape[0], timesteps].concat(childOutputShape.slice(1));
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            // TODO(cais): Add 'training' and 'useLearningPhase' to kwargs.
+            inputs = getExactlyOneTensor(inputs);
+            // Porting Note: In tfjs-layers, `inputs` are always concrete tensor
+            // values. Hence the inputs can't have an undetermined first (batch)
+            // dimension, which is why we always use the K.rnn approach here.
+            const step = (inputs, states) => {
+              // TODO(cais): Add useLearningPhase.
+              // NOTE(cais): `layer.call` may return a length-1 array of Tensor in
+              //   some cases (e.g., `layer` is a `Sequential` instance), which is
+              //   why `getExactlyOneTensor` is used below.
+              const output = getExactlyOneTensor(this.layer.call(inputs, kwargs));
+              return [output, []];
+            };
+            const rnnOutputs = rnn(
+              step,
+              inputs,
+              [],
+              false /* goBackwards */,
+              null /* mask */,
+              null /* constants */,
+              false /* unroll */,
+              true /* needPerStepOutputs */
+            );
+            const y = rnnOutputs[1];
+            // TODO(cais): Add activity regularization.
+            // TODO(cais): Add useLearningPhase.
+            return y;
+          });
+        }
+      }
+      /** @nocollapse */
+      wrappers_TimeDistributed.className = "TimeDistributed";
+      dist["serialization"].registerClass(wrappers_TimeDistributed);
+      function checkBidirectionalMergeMode(value) {
+        checkStringTypeUnionValue(VALID_BIDIRECTIONAL_MERGE_MODES, "BidirectionalMergeMode", value);
+      }
+      const DEFAULT_BIDIRECTIONAL_MERGE_MODE = "concat";
+      class wrappers_Bidirectional extends wrappers_Wrapper {
+        constructor(args) {
+          super(args);
+          // Note: When creating `this.forwardLayer`, the original Layer object
+          //   (`config.layer`) ought to be cloned. This is why we call
+          //   `getConfig()` followed by `deserialize()`. Without this cloning,
+          //   the layer names saved during serialization will incorrectly contain
+          //   the 'forward_' prefix. In Python Keras, this is done using
+          //   `copy.copy` (shallow copy), which does not have a simple equivalent
+          //   in JavaScript. JavaScript's `Object.assign()` does not copy
+          //   methods.
+          const layerConfig = args.layer.getConfig();
+          const forwDict = {};
+          forwDict["className"] = args.layer.getClassName();
+          forwDict["config"] = layerConfig;
+          this.forwardLayer = deserialize(forwDict);
+          layerConfig["goBackwards"] = layerConfig["goBackwards"] === true ? false : true;
+          const backDict = {};
+          backDict["className"] = args.layer.getClassName();
+          backDict["config"] = layerConfig;
+          this.backwardLayer = deserialize(backDict);
+          this.forwardLayer.name = "forward_" + this.forwardLayer.name;
+          this.backwardLayer.name = "backward_" + this.backwardLayer.name;
+          this.mergeMode =
+            args.mergeMode === undefined ? DEFAULT_BIDIRECTIONAL_MERGE_MODE : args.mergeMode;
+          checkBidirectionalMergeMode(this.mergeMode);
+          if (args.weights) {
+            throw new NotImplementedError(
+              "weights support is not implemented for Bidirectional layer yet."
+            );
+          }
+          this._stateful = args.layer.stateful;
+          this.returnSequences = args.layer.returnSequences;
+          this.returnState = args.layer.returnState;
+          this.supportsMasking = true;
+          this._trainable = true;
+          this.inputSpec = args.layer.inputSpec;
+          this.numConstants = null;
+        }
+        get trainable() {
+          return this._trainable;
+        }
+        set trainable(value) {
+          // Porting Note: the check of `this.layer` here is necessary due to the
+          //   way the `constructor` of this class is written (see Porting Note
+          //   above).
+          this._trainable = value;
+          if (this.forwardLayer != null) {
+            this.forwardLayer.trainable = value;
+          }
+          if (this.backwardLayer != null) {
+            this.backwardLayer.trainable = value;
+          }
+        }
+        getWeights() {
+          return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights());
+        }
+        setWeights(weights) {
+          const numWeights = weights.length;
+          const numeightsOver2 = Math.floor(numWeights / 2);
+          this.forwardLayer.setWeights(weights.slice(0, numeightsOver2));
+          this.backwardLayer.setWeights(weights.slice(numeightsOver2));
+        }
+        computeOutputShape(inputShape) {
+          let layerShapes = this.forwardLayer.computeOutputShape(inputShape);
+          if (!(Array.isArray(layerShapes) && Array.isArray(layerShapes[0]))) {
+            layerShapes = [layerShapes];
+          }
+          layerShapes = layerShapes;
+          let outputShape;
+          let outputShapes;
+          let stateShape;
+          if (this.returnState) {
+            stateShape = layerShapes.slice(1);
+            outputShape = layerShapes[0];
+          } else {
+            outputShape = layerShapes[0];
+          }
+          outputShape = outputShape;
+          if (this.mergeMode === "concat") {
+            outputShape[outputShape.length - 1] *= 2;
+            outputShapes = [outputShape];
+          } else if (this.mergeMode == null) {
+            outputShapes = [outputShape, outputShape.slice()];
+          } else {
+            outputShapes = [outputShape];
+          }
+          if (this.returnState) {
+            if (this.mergeMode == null) {
+              return outputShapes.concat(stateShape).concat(stateShape.slice());
+            }
+            return [outputShape].concat(stateShape).concat(stateShape.slice());
+          }
+          return singletonOrArray(outputShapes);
+        }
+        apply(inputs, kwargs) {
+          let initialState = kwargs == null ? null : kwargs["initialState"];
+          let constants = kwargs == null ? null : kwargs["constants"];
+          if (kwargs == null) {
+            kwargs = {};
+          }
+          const standardized = standardizeArgs(inputs, initialState, constants, this.numConstants);
+          inputs = standardized.inputs;
+          initialState = standardized.initialState;
+          constants = standardized.constants;
+          if (Array.isArray(inputs)) {
+            initialState = inputs.slice(1);
+            inputs = inputs[0];
+          }
+          if ((initialState == null || initialState.length === 0) && constants == null) {
+            return super.apply(inputs, kwargs);
+          }
+          const additionalInputs = [];
+          const additionalSpecs = [];
+          if (initialState != null) {
+            const numStates = initialState.length;
+            if (numStates % 2 > 0) {
+              throw new ValueError(
+                "When passing `initialState` to a Bidrectional RNN, " +
+                  "the state should be an Array containing the states of " +
+                  "the underlying RNNs."
+              );
+            }
+            kwargs["initialState"] = initialState;
+            additionalInputs.push(...initialState);
+            const stateSpecs = initialState.map((state) => new InputSpec({ shape: state.shape }));
+            this.forwardLayer.stateSpec = stateSpecs.slice(0, numStates / 2);
+            this.backwardLayer.stateSpec = stateSpecs.slice(numStates / 2);
+            additionalSpecs.push(...stateSpecs);
+          }
+          if (constants != null) {
+            throw new NotImplementedError(
+              "Support for constants in Bidirectional layers is not " + "implemented yet."
+            );
+          }
+          const isSymbolicTensor = additionalInputs[0] instanceof topology_SymbolicTensor;
+          for (const tensor of additionalInputs) {
+            if (tensor instanceof topology_SymbolicTensor !== isSymbolicTensor) {
+              throw new ValueError(
+                "The initial state of a Bidirectional layer cannot be " +
+                  "specified as a mix of symbolic and non-symbolic tensors"
+              );
+            }
+          }
+          if (isSymbolicTensor) {
+            // Compute the full input and specs, including the states.
+            const fullInput = [inputs].concat(additionalInputs);
+            const fullInputSpec = this.inputSpec.concat(additionalSpecs);
+            // Perform the call temporarily and replace inputSpec.
+            // Note: with initial states symbolic calls and non-symbolic calls to
+            // this method differ in how the initial states are passed. For
+            // symbolic calls, the initial states are passed in the first arg, as
+            // an Array of SymbolicTensors; for non-symbolic calls, they are
+            // passed in the second arg as a part of the kwargs. Hence the need to
+            // temporarily modify inputSpec here.
+            // TODO(cais): Make refactoring so that this hacky code below is no
+            // longer needed.
+            const originalInputSpec = this.inputSpec;
+            this.inputSpec = fullInputSpec;
+            const output = super.apply(fullInput, kwargs);
+            this.inputSpec = originalInputSpec;
+            return output;
+          } else {
+            return super.apply(inputs, kwargs);
+          }
+        }
+        call(inputs, kwargs) {
+          return Object(dist["tidy"])(() => {
+            const initialState = kwargs["initialState"];
+            let y;
+            let yRev;
+            if (initialState == null) {
+              y = this.forwardLayer.call(inputs, kwargs);
+              yRev = this.backwardLayer.call(inputs, kwargs);
+            } else {
+              const forwardState = initialState.slice(0, initialState.length / 2);
+              const backwardState = initialState.slice(initialState.length / 2);
+              y = this.forwardLayer.call(
+                inputs,
+                Object.assign(kwargs, { initialState: forwardState })
+              );
+              yRev = this.backwardLayer.call(
+                inputs,
+                Object.assign(kwargs, { initialState: backwardState })
+              );
+            }
+            let states;
+            if (this.returnState) {
+              if (Array.isArray(y)) {
+                states = y.slice(1).concat(yRev.slice(1));
+              } else {
+              }
+              y = y[0];
+              yRev = yRev[0];
+            }
+            if (this.returnSequences) {
+              yRev = dist["reverse"](yRev, 1);
+            }
+            let output;
+            if (this.mergeMode === "concat") {
+              output = concatenate([y, yRev]);
+            } else if (this.mergeMode === "sum") {
+              output = dist["add"](y, yRev);
+            } else if (this.mergeMode === "ave") {
+              output = dist["mul"](0.5, dist["add"](y, yRev));
+            } else if (this.mergeMode === "mul") {
+              output = dist["mul"](y, yRev);
+            } else if (this.mergeMode == null) {
+              output = [y, yRev];
+            }
+            // TODO(cais): Properly set learning phase.
+            if (this.returnState) {
+              if (this.mergeMode == null) {
+                return output.concat(states);
+              }
+              return [output].concat(states);
+            }
+            return output;
+          });
+        }
+        resetStates(states) {
+          this.forwardLayer.resetStates();
+          this.backwardLayer.resetStates();
+        }
+        build(inputShape) {
+          nameScope(this.forwardLayer.name, () => {
+            this.forwardLayer.build(inputShape);
+          });
+          nameScope(this.backwardLayer.name, () => {
+            this.backwardLayer.build(inputShape);
+          });
+          this.built = true;
+        }
+        computeMask(inputs, mask) {
+          if (Array.isArray(mask)) {
+            mask = mask[0];
+          }
+          let outputMask;
+          if (this.returnSequences) {
+            if (this.mergeMode == null) {
+              outputMask = [mask, mask];
+            } else {
+              outputMask = mask;
+            }
+          } else {
+            if (this.mergeMode == null) {
+              outputMask = [null, null];
+            } else {
+              outputMask = null;
+            }
+          }
+          if (this.returnState) {
+            const states = this.forwardLayer.states;
+            const stateMask = states.map((state) => null);
+            if (Array.isArray(outputMask)) {
+              return outputMask.concat(stateMask).concat(stateMask);
+            } else {
+              return [outputMask].concat(stateMask).concat(stateMask);
+            }
+          } else {
+            return outputMask;
+          }
+        }
+        get trainableWeights() {
+          return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights);
+        }
+        get nonTrainableWeights() {
+          return this.forwardLayer.nonTrainableWeights.concat(
+            this.backwardLayer.nonTrainableWeights
+          );
+        }
+        // TODO(cais): Implement constraints().
+        setFastWeightInitDuringBuild(value) {
+          super.setFastWeightInitDuringBuild(value);
+          if (this.forwardLayer != null) {
+            this.forwardLayer.setFastWeightInitDuringBuild(value);
+          }
+          if (this.backwardLayer != null) {
+            this.backwardLayer.setFastWeightInitDuringBuild(value);
+          }
+        }
+        getConfig() {
+          const config = {
+            mergeMode: this.mergeMode,
+          };
+          // TODO(cais): Add logic for `numConstants` once the property is added.
+          const baseConfig = super.getConfig();
+          Object.assign(config, baseConfig);
+          return config;
+        }
+        /** @nocollapse */
+        static fromConfig(cls, config) {
+          const rnnLayer = deserialize(config["layer"]);
+          delete config["layer"];
+          // TODO(cais): Add logic for `numConstants` once the property is added.
+          if (config["numConstants"] != null) {
+            throw new NotImplementedError(
+              `Deserialization of a Bidirectional layer with numConstants ` +
+                `present is not supported yet.`
+            );
+          }
+          // tslint:disable-next-line:no-any
+          const newConfig = config;
+          newConfig["layer"] = rnnLayer;
+          return new cls(newConfig);
+        }
+      }
+      /** @nocollapse */
+      wrappers_Bidirectional.className = "Bidirectional";
+      dist["serialization"].registerClass(wrappers_Bidirectional);
+      //# sourceMappingURL=wrappers.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_layers.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      // TODO(cais): Add doc string to all the public static functions in this
+      //   class; include exectuable JavaScript code snippets where applicable
+      //   (b/74074458).
+      // Input Layer.
+      /**
+       * An input layer is an entry point into a `tf.LayersModel`.
+       *
+       * `InputLayer` is generated automatically for `tf.Sequential`` models by
+       * specifying the `inputshape` or `batchInputShape` for the first layer.  It
+       * should not be specified explicitly. However, it can be useful sometimes,
+       * e.g., when constructing a sequential model from a subset of another
+       * sequential model's layers. Like the code snippet below shows.
+       *
+       * ```js
+       * // Define a model which simply adds two inputs.
+       * const model1 = tf.sequential();
+       * model1.add(tf.layers.dense({inputShape: [4], units: 3, activation: 'relu'}));
+       * model1.add(tf.layers.dense({units: 1, activation: 'sigmoid'}));
+       * model1.summary();
+       * model1.predict(tf.zeros([1, 4])).print();
+       *
+       * // Construct another model, reusing the second layer of `model1` while
+       * // not using the first layer of `model1`. Note that you cannot add the second
+       * // layer of `model` directly as the first layer of the new sequential model,
+       * // because doing so will lead to an error related to the fact that the layer
+       * // is not an input layer. Instead, you need to create an `inputLayer` and add
+       * // it to the new sequential model before adding the reused layer.
+       * const model2 = tf.sequential();
+       * // Use an inputShape that matches the input shape of `model1`'s second
+       * // layer.
+       * model2.add(tf.layers.inputLayer({inputShape: [3]}));
+       * model2.add(model1.layers[1]);
+       * model2.summary();
+       * model2.predict(tf.zeros([1, 3])).print();
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Inputs', namespace: 'layers'} */
+      function exports_layers_inputLayer(args) {
+        return new input_layer_InputLayer(args);
+      }
+      // Advanced Activation Layers.
+      /**
+       * Exponetial Linear Unit (ELU).
+       *
+       * It follows:
+       * `f(x) =  alpha * (exp(x) - 1.) for x < 0`,
+       * `f(x) = x for x >= 0`.
+       *
+       * Input shape:
+       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
+       *   first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as the input.
+       *
+       * References:
+       *   - [Fast and Accurate Deep Network Learning by Exponential Linear Units
+       * (ELUs)](https://arxiv.org/abs/1511.07289v1)
+       */
+      /**
+       * @doc {
+       *   heading: 'Layers',
+       *   subheading: 'Advanced Activation',
+       *   namespace: 'layers'
+       * }
+       */
+      function exports_layers_elu(args) {
+        return new advanced_activations_ELU(args);
+      }
+      /**
+       * Rectified Linear Unit activation function.
+       *
+       * Input shape:
+       *   Arbitrary. Use the config field `inputShape` (Array of integers, does
+       *   not include the sample axis) when using this layer as the first layer
+       *   in a model.
+       *
+       * Output shape:
+       *   Same shape as the input.
+       */
+      /**
+       * @doc {
+       *   heading: 'Layers',
+       *   subheading: 'Advanced Activation',
+       *   namespace: 'layers'
+       * }
+       */
+      function reLU(args) {
+        return new advanced_activations_ReLU(args);
+      }
+      /**
+       * Leaky version of a rectified linear unit.
+       *
+       * It allows a small gradient when the unit is not active:
+       * `f(x) = alpha * x for x < 0.`
+       * `f(x) = x for x >= 0.`
+       *
+       * Input shape:
+       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
+       *   first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as the input.
+       */
+      /**
+       * @doc {
+       *   heading: 'Layers',
+       *   subheading: 'Advanced Activation',
+       *   namespace: 'layers'
+       * }
+       */
+      function leakyReLU(args) {
+        return new advanced_activations_LeakyReLU(args);
+      }
+      /**
+       * Parameterized version of a leaky rectified linear unit.
+       *
+       * It follows
+       * `f(x) = alpha * x for x < 0.`
+       * `f(x) = x for x >= 0.`
+       * wherein `alpha` is a trainable weight.
+       *
+       * Input shape:
+       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
+       *   first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as the input.
+       */
+      /**
+       * @doc {
+       *   heading: 'Layers',
+       *   subheading: 'Advanced Activation',
+       *   namespace: 'layers'
+       * }
+       */
+      function prelu(args) {
+        return new advanced_activations_PReLU(args);
+      }
+      /**
+       * Softmax activation layer.
+       *
+       * Input shape:
+       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
+       *   first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as the input.
+       */
+      /**
+       * @doc {
+       *   heading: 'Layers',
+       *   subheading: 'Advanced Activation',
+       *   namespace: 'layers'
+       * }
+       */
+      function softmax(args) {
+        return new advanced_activations_Softmax(args);
+      }
+      /**
+       * Thresholded Rectified Linear Unit.
+       *
+       * It follows:
+       * `f(x) = x for x > theta`,
+       * `f(x) = 0 otherwise`.
+       *
+       * Input shape:
+       *   Arbitrary. Use the configuration `inputShape` when using this layer as the
+       *   first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as the input.
+       *
+       * References:
+       *   - [Zero-Bias Autoencoders and the Benefits of Co-Adapting
+       * Features](http://arxiv.org/abs/1402.3337)
+       */
+      /**
+       * @doc {
+       *   heading: 'Layers',
+       *   subheading: 'Advanced Activation',
+       *   namespace: 'layers'
+       * }
+       */
+      function thresholdedReLU(args) {
+        return new advanced_activations_ThresholdedReLU(args);
+      }
+      // Convolutional Layers.
+      /**
+       * 1D convolution layer (e.g., temporal convolution).
+       *
+       * This layer creates a convolution kernel that is convolved
+       * with the layer input over a single spatial (or temporal) dimension
+       * to produce a tensor of outputs.
+       *
+       * If `use_bias` is True, a bias vector is created and added to the outputs.
+       *
+       * If `activation` is not `null`, it is applied to the outputs as well.
+       *
+       * When using this layer as the first layer in a model, provide an
+       * `inputShape` argument `Array` or `null`.
+       *
+       * For example, `inputShape` would be:
+       * - `[10, 128]` for sequences of 10 vectors of 128-dimensional vectors
+       * - `[null, 128]` for variable-length sequences of 128-dimensional vectors.
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Convolutional',  namespace: 'layers'}
+       */
+      function exports_layers_conv1d(args) {
+        return new convolutional_Conv1D(args);
+      }
+      /**
+       * 2D convolution layer (e.g. spatial convolution over images).
+       *
+       * This layer creates a convolution kernel that is convolved
+       * with the layer input to produce a tensor of outputs.
+       *
+       * If `useBias` is True, a bias vector is created and added to the outputs.
+       *
+       * If `activation` is not `null`, it is applied to the outputs as well.
+       *
+       * When using this layer as the first layer in a model,
+       * provide the keyword argument `inputShape`
+       * (Array of integers, does not include the sample axis),
+       * e.g. `inputShape=[128, 128, 3]` for 128x128 RGB pictures
+       * in `dataFormat='channelsLast'`.
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
+       */
+      function exports_layers_conv2d(args) {
+        return new convolutional_Conv2D(args);
+      }
+      /**
+       * Transposed convolutional layer (sometimes called Deconvolution).
+       *
+       * The need for transposed convolutions generally arises
+       * from the desire to use a transformation going in the opposite direction of
+       * a normal convolution, i.e., from something that has the shape of the output
+       * of some convolution to something that has the shape of its input while
+       * maintaining a connectivity pattern that is compatible with said
+       * convolution.
+       *
+       * When using this layer as the first layer in a model, provide the
+       * configuration `inputShape` (`Array` of integers, does not include the
+       * sample axis), e.g., `inputShape: [128, 128, 3]` for 128x128 RGB pictures in
+       * `dataFormat: 'channelsLast'`.
+       *
+       * Input shape:
+       *   4D tensor with shape:
+       *   `[batch, channels, rows, cols]` if `dataFormat` is `'channelsFirst'`.
+       *   or 4D tensor with shape
+       *   `[batch, rows, cols, channels]` if `dataFormat` is `'channelsLast`.
+       *
+       * Output shape:
+       *   4D tensor with shape:
+       *   `[batch, filters, newRows, newCols]` if `dataFormat` is
+       * `'channelsFirst'`. or 4D tensor with shape:
+       *   `[batch, newRows, newCols, filters]` if `dataFormat` is `'channelsLast'`.
+       *
+       * References:
+       *   - [A guide to convolution arithmetic for deep
+       * learning](https://arxiv.org/abs/1603.07285v1)
+       *   - [Deconvolutional
+       * Networks](http://www.matthewzeiler.com/pubs/cvpr2010/cvpr2010.pdf)
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
+       */
+      function conv2dTranspose(args) {
+        return new convolutional_Conv2DTranspose(args);
+      }
+      /**
+       * 3D convolution layer (e.g. spatial convolution over volumes).
+       *
+       * This layer creates a convolution kernel that is convolved
+       * with the layer input to produce a tensor of outputs.
+       *
+       * If `useBias` is True, a bias vector is created and added to the outputs.
+       *
+       * If `activation` is not `null`, it is applied to the outputs as well.
+       *
+       * When using this layer as the first layer in a model,
+       * provide the keyword argument `inputShape`
+       * (Array of integers, does not include the sample axis),
+       * e.g. `inputShape=[128, 128, 128, 1]` for 128x128x128 grayscale volumes
+       * in `dataFormat='channelsLast'`.
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
+       */
+      function exports_layers_conv3d(args) {
+        return new convolutional_Conv3D(args);
+      }
+      /**
+       * Depthwise separable 2D convolution.
+       *
+       * Separable convolution consists of first performing
+       * a depthwise spatial convolution
+       * (which acts on each input channel separately)
+       * followed by a pointwise convolution which mixes together the resulting
+       * output channels. The `depthMultiplier` argument controls how many
+       * output channels are generated per input channel in the depthwise step.
+       *
+       * Intuitively, separable convolutions can be understood as
+       * a way to factorize a convolution kernel into two smaller kernels,
+       * or as an extreme version of an Inception block.
+       *
+       * Input shape:
+       *   4D tensor with shape:
+       *     `[batch, channels, rows, cols]` if data_format='channelsFirst'
+       *   or 4D tensor with shape:
+       *     `[batch, rows, cols, channels]` if data_format='channelsLast'.
+       *
+       * Output shape:
+       *   4D tensor with shape:
+       *     `[batch, filters, newRows, newCols]` if data_format='channelsFirst'
+       *   or 4D tensor with shape:
+       *     `[batch, newRows, newCols, filters]` if data_format='channelsLast'.
+       *     `rows` and `cols` values might have changed due to padding.
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
+       */
+      function separableConv2d(args) {
+        return new SeparableConv2D(args);
+      }
+      /**
+       * Cropping layer for 2D input (e.g., image).
+       *
+       * This layer can crop an input
+       * at the top, bottom, left and right side of an image tensor.
+       *
+       * Input shape:
+       *   4D tensor with shape:
+       *   - If `dataFormat` is `"channelsLast"`:
+       *     `[batch, rows, cols, channels]`
+       *   - If `data_format` is `"channels_first"`:
+       *     `[batch, channels, rows, cols]`.
+       *
+       * Output shape:
+       *   4D with shape:
+       *   - If `dataFormat` is `"channelsLast"`:
+       *     `[batch, croppedRows, croppedCols, channels]`
+       *    - If `dataFormat` is `"channelsFirst"`:
+       *     `[batch, channels, croppedRows, croppedCols]`.
+       *
+       * Examples
+       * ```js
+       *
+       * const model = tf.sequential();
+       * model.add(tf.layers.cropping2D({cropping:[[2, 2], [2, 2]],
+       *                                inputShape: [128, 128, 3]}));
+       * //now output shape is [batch, 124, 124, 3]
+       * ```
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
+       */
+      function cropping2D(args) {
+        return new convolutional_Cropping2D(args);
+      }
+      /**
+       * Upsampling layer for 2D inputs.
+       *
+       * Repeats the rows and columns of the data
+       * by size[0] and size[1] respectively.
+       *
+       *
+       * Input shape:
+       *    4D tensor with shape:
+       *     - If `dataFormat` is `"channelsLast"`:
+       *         `[batch, rows, cols, channels]`
+       *     - If `dataFormat` is `"channelsFirst"`:
+       *        `[batch, channels, rows, cols]`
+       *
+       * Output shape:
+       *     4D tensor with shape:
+       *     - If `dataFormat` is `"channelsLast"`:
+       *        `[batch, upsampledRows, upsampledCols, channels]`
+       *     - If `dataFormat` is `"channelsFirst"`:
+       *         `[batch, channels, upsampledRows, upsampledCols]`
+       *
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
+       */
+      function upSampling2d(args) {
+        return new convolutional_UpSampling2D(args);
+      }
+      // Convolutional(depthwise) Layers.
+      /**
+       * Depthwise separable 2D convolution.
+       *
+       * Depthwise Separable convolutions consists in performing just the first step
+       * in a depthwise spatial convolution (which acts on each input channel
+       * separately). The `depthMultplier` argument controls how many output channels
+       * are generated per input channel in the depthwise step.
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Convolutional', namespace: 'layers'}
+       */
+      function exports_layers_depthwiseConv2d(args) {
+        return new convolutional_depthwise_DepthwiseConv2D(args);
+      }
+      // Basic Layers.
+      /**
+       * Applies an activation function to an output.
+       *
+       * This layer applies element-wise activation function.  Other layers, notably
+       * `dense` can also apply activation functions.  Use this isolated activation
+       * function to extract the values before and after the
+       * activation. For instance:
+       *
+       * ```js
+       * const input = tf.input({shape: [5]});
+       * const denseLayer = tf.layers.dense({units: 1});
+       * const activationLayer = tf.layers.activation({activation: 'relu6'});
+       *
+       * // Obtain the output symbolic tensors by applying the layers in order.
+       * const denseOutput = denseLayer.apply(input);
+       * const activationOutput = activationLayer.apply(denseOutput);
+       *
+       * // Create the model based on the inputs.
+       * const model = tf.model({
+       *     inputs: input,
+       *     outputs: [denseOutput, activationOutput]
+       * });
+       *
+       * // Collect both outputs and print separately.
+       * const [denseOut, activationOut] = model.predict(tf.randomNormal([6, 5]));
+       * denseOut.print();
+       * activationOut.print();
+       * ```
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'}
+       */
+      function exports_layers_activation(args) {
+        return new core_Activation(args);
+      }
+      /**
+       * Creates a dense (fully connected) layer.
+       *
+       * This layer implements the operation:
+       *   `output = activation(dot(input, kernel) + bias)`
+       *
+       * `activation` is the element-wise activation function
+       *   passed as the `activation` argument.
+       *
+       * `kernel` is a weights matrix created by the layer.
+       *
+       * `bias` is a bias vector created by the layer (only applicable if `useBias`
+       * is `true`).
+       *
+       * **Input shape:**
+       *
+       *   nD `tf.Tensor` with shape: `(batchSize, ..., inputDim)`.
+       *
+       *   The most common situation would be
+       *   a 2D input with shape `(batchSize, inputDim)`.
+       *
+       * **Output shape:**
+       *
+       *   nD tensor with shape: `(batchSize, ..., units)`.
+       *
+       *   For instance, for a 2D input with shape `(batchSize, inputDim)`,
+       *   the output would have shape `(batchSize, units)`.
+       *
+       * Note: if the input to the layer has a rank greater than 2, then it is
+       * flattened prior to the initial dot product with the kernel.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
+      function dense(args) {
+        return new core_Dense(args);
+      }
+      /**
+       * Applies
+       * [dropout](http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf) to
+       * the input.
+       *
+       * Dropout consists in randomly setting a fraction `rate` of input units to 0 at
+       * each update during training time, which helps prevent overfitting.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
+      function exports_layers_dropout(args) {
+        return new core_Dropout(args);
+      }
+      /**
+       * Spatial 1D version of Dropout.
+       *
+       * This Layer type performs the same function as the Dropout layer, but it drops
+       * entire 1D feature maps instead of individual elements. For example, if an
+       * input example consists of 3 timesteps and the feature map for each timestep
+       * has a size of 4, a `spatialDropout1d` layer may zero out the feature maps
+       * of the 1st timesteps and 2nd timesteps completely while sparing all feature
+       * elements of the 3rd timestep.
+       *
+       * If adjacent frames (timesteps) are strongly correlated (as is normally the
+       * case in early convolution layers), regular dropout will not regularize the
+       * activation and will otherwise just result in merely an effective learning
+       * rate decrease. In this case, `spatialDropout1d` will help promote
+       * independence among feature maps and should be used instead.
+       *
+       * **Arguments:**
+       *   rate: A floating-point number >=0 and <=1. Fraction of the input elements
+       *     to drop.
+       *
+       * **Input shape:**
+       *   3D tensor with shape `(samples, timesteps, channels)`.
+       *
+       * **Output shape:**
+       *   Same as the input shape.
+       *
+       * References:
+       *   - [Efficient Object Localization Using Convolutional
+       *      Networks](https://arxiv.org/abs/1411.4280)
+       */
+      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
+      function spatialDropout1d(args) {
+        return new SpatialDropout1D(args);
+      }
+      /**
+       * Flattens the input. Does not affect the batch size.
+       *
+       * A `Flatten` layer flattens each batch in its inputs to 1D (making the output
+       * 2D).
+       *
+       * For example:
+       *
+       * ```js
+       * const input = tf.input({shape: [4, 3]});
+       * const flattenLayer = tf.layers.flatten();
+       * // Inspect the inferred output shape of the flatten layer, which
+       * // equals `[null, 12]`. The 2nd dimension is 4 * 3, i.e., the result of the
+       * // flattening. (The 1st dimension is the undermined batch size.)
+       * console.log(JSON.stringify(flattenLayer.apply(input).shape));
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
+      function exports_layers_flatten(args) {
+        return new core_Flatten(args);
+      }
+      /**
+       * Repeats the input n times in a new dimension.
+       *
+       * ```js
+       *  const model = tf.sequential();
+       *  model.add(tf.layers.repeatVector({n: 4, inputShape: [2]}));
+       *  const x = tf.tensor2d([[10, 20]]);
+       *  // Use the model to do inference on a data point the model hasn't see
+       *  model.predict(x).print();
+       *  // output shape is now [batch, 2, 4]
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
+      function repeatVector(args) {
+        return new core_RepeatVector(args);
+      }
+      /**
+       * Reshapes an input to a certain shape.
+       *
+       * ```js
+       * const input = tf.input({shape: [4, 3]});
+       * const reshapeLayer = tf.layers.reshape({targetShape: [2, 6]});
+       * // Inspect the inferred output shape of the Reshape layer, which
+       * // equals `[null, 2, 6]`. (The 1st dimension is the undermined batch size.)
+       * console.log(JSON.stringify(reshapeLayer.apply(input).shape));
+       * ```
+       *
+       * Input shape:
+       *   Arbitrary, although all dimensions in the input shape must be fixed.
+       *   Use the configuration `inputShape` when using this layer as the
+       *   first layer in a model.
+       *
+       *
+       * Output shape:
+       *   [batchSize, targetShape[0], targetShape[1], ...,
+       *    targetShape[targetShape.length - 1]].
+       */
+      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
+      function reshape(args) {
+        return new core_Reshape(args);
+      }
+      /**
+       * Permutes the dimensions of the input according to a given pattern.
+       *
+       * Useful for, e.g., connecting RNNs and convnets together.
+       *
+       * Example:
+       *
+       * ```js
+       * const model = tf.sequential();
+       * model.add(tf.layers.permute({
+       *   dims: [2, 1],
+       *   inputShape: [10, 64]
+       * }));
+       * console.log(model.outputShape);
+       * // Now model's output shape is [null, 64, 10], where null is the
+       * // unpermuted sample (batch) dimension.
+       * ```
+       *
+       * Input shape:
+       *   Arbitrary. Use the configuration field `inputShape` when using this
+       *   layer as the first layer in a model.
+       *
+       * Output shape:
+       *   Same rank as the input shape, but with the dimensions re-ordered (i.e.,
+       *   permuted) according to the `dims` configuration of this layer.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
+      function permute(args) {
+        return new core_Permute(args);
+      }
+      /**
+       * Maps positive integers (indices) into dense vectors of fixed size.
+       * eg. [[4], [20]] -> [[0.25, 0.1], [0.6, -0.2]]
+       *
+       * **Input shape:** 2D tensor with shape: `[batchSize, sequenceLength]`.
+       *
+       * **Output shape:** 3D tensor with shape: `[batchSize, sequenceLength,
+       * outputDim]`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'} */
+      function embedding(args) {
+        return new embeddings_Embedding(args);
+      }
+      // Merge Layers.
+      /**
+       * Layer that performs element-wise addition on an `Array` of inputs.
+       *
+       * It takes as input a list of tensors, all of the same shape, and returns a
+       * single tensor (also of the same shape). The inputs are specified as an
+       * `Array` when the `apply` method of the `Add` layer instance is called. For
+       * example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const addLayer = tf.layers.add();
+       * const sum = addLayer.apply([input1, input2]);
+       * console.log(JSON.stringify(sum.shape));
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
+      function exports_layers_add(args) {
+        return new merge_Add(args);
+      }
+      /**
+       * Layer that performs element-wise averaging on an `Array` of inputs.
+       *
+       * It takes as input a list of tensors, all of the same shape, and returns a
+       * single tensor (also of the same shape). For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const averageLayer = tf.layers.average();
+       * const average = averageLayer.apply([input1, input2]);
+       * console.log(JSON.stringify(average.shape));
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
+      function exports_layers_average(args) {
+        return new merge_Average(args);
+      }
+      /**
+       * Layer that concatenates an `Array` of inputs.
+       *
+       * It takes a list of tensors, all of the same shape except for the
+       * concatenation axis, and returns a single tensor, the concatenation
+       * of all inputs. For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 3]});
+       * const concatLayer = tf.layers.concatenate();
+       * const output = concatLayer.apply([input1, input2]);
+       * console.log(JSON.stringify(output.shape));
+       * // You get [null, 2, 5], with the first dimension as the undetermined batch
+       * // dimension. The last dimension (5) is the result of concatenating the
+       * // last dimensions of the inputs (2 and 3).
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
+      function exports_layers_concatenate(args) {
+        return new merge_Concatenate(args);
+      }
+      /**
+       * Layer that computes the element-wise maximum an `Array` of inputs.
+       *
+       * It takes as input a list of tensors, all of the same shape and returns a
+       * single tensor (also of the same shape). For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const maxLayer = tf.layers.maximum();
+       * const max = maxLayer.apply([input1, input2]);
+       * console.log(JSON.stringify(max.shape));
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
+      function exports_layers_maximum(args) {
+        return new merge_Maximum(args);
+      }
+      /**
+       * Layer that computes the element-wise minimum of an `Array` of inputs.
+       *
+       * It takes as input a list of tensors, all of the same shape and returns a
+       * single tensor (also of the same shape). For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const minLayer = tf.layers.minimum();
+       * const min = minLayer.apply([input1, input2]);
+       * console.log(JSON.stringify(min.shape));
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
+      function exports_layers_minimum(args) {
+        return new merge_Minimum(args);
+      }
+      /**
+       * Layer that multiplies (element-wise) an `Array` of inputs.
+       *
+       * It takes as input an Array of tensors, all of the same
+       * shape, and returns a single tensor (also of the same shape).
+       * For example:
+       *
+       * ```js
+       * const input1 = tf.input({shape: [2, 2]});
+       * const input2 = tf.input({shape: [2, 2]});
+       * const input3 = tf.input({shape: [2, 2]});
+       * const multiplyLayer = tf.layers.multiply();
+       * const product = multiplyLayer.apply([input1, input2, input3]);
+       * console.log(product.shape);
+       * // You get [null, 2, 2], with the first dimension as the undetermined batch
+       * // dimension.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
+      function exports_layers_multiply(args) {
+        return new merge_Multiply(args);
+      }
+      /**
+       * Layer that computes a dot product between samples in two tensors.
+       *
+       * E.g., if applied to a list of two tensors `a` and `b` both of shape
+       * `[batchSize, n]`, the output will be a tensor of shape `[batchSize, 1]`,
+       * where each entry at index `[i, 0]` will be the dot product between
+       * `a[i, :]` and `b[i, :]`.
+       *
+       * Example:
+       *
+       * ```js
+       * const dotLayer = tf.layers.dot({axes: -1});
+       * const x1 = tf.tensor2d([[10, 20], [30, 40]]);
+       * const x2 = tf.tensor2d([[-1, -2], [-3, -4]]);
+       *
+       * // Invoke the layer's apply() method in eager (imperative) mode.
+       * const y = dotLayer.apply([x1, x2]);
+       * y.print();
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Merge', namespace: 'layers'} */
+      function exports_layers_dot(args) {
+        return new merge_Dot(args);
+      }
+      // Normalization Layers.
+      /**
+       * Batch normalization layer (Ioffe and Szegedy, 2014).
+       *
+       * Normalize the activations of the previous layer at each batch,
+       * i.e. applies a transformation that maintains the mean activation
+       * close to 0 and the activation standard deviation close to 1.
+       *
+       * Input shape:
+       *   Arbitrary. Use the keyword argument `inputShape` (Array of integers, does
+       *   not include the sample axis) when calling the constructor of this class,
+       *   if this layer is used as a first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as input.
+       *
+       * References:
+       *   - [Batch Normalization: Accelerating Deep Network Training by Reducing
+       * Internal Covariate Shift](https://arxiv.org/abs/1502.03167)
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Normalization', namespace: 'layers'}
+       */
+      function exports_layers_batchNormalization(args) {
+        return new normalization_BatchNormalization(args);
+      }
+      /**
+       * Layer-normalization layer (Ba et al., 2016).
+       *
+       * Normalizes the activations of the previous layer for each given example in a
+       * batch independently, instead of across a batch like in `batchNormalization`.
+       * In other words, this layer applies a transformation that maintanis the mean
+       * activation within each example close to0 and activation variance close to 1.
+       *
+       * Input shape:
+       *   Arbitrary. Use the argument `inputShape` when using this layer as the first
+       *   layer in a model.
+       *
+       * Output shape:
+       *   Same as input.
+       *
+       * References:
+       *   - [Layer Normalization](https://arxiv.org/abs/1607.06450)
+       */
+      /**
+       * @doc {heading: 'Layers', subheading: 'Normalization', namespace: 'layers'}
+       */
+      function layerNormalization(args) {
+        return new normalization_LayerNormalization(args);
+      }
+      // Padding Layers.
+      /**
+       * Zero-padding layer for 2D input (e.g., image).
+       *
+       * This layer can add rows and columns of zeros
+       * at the top, bottom, left and right side of an image tensor.
+       *
+       * Input shape:
+       *   4D tensor with shape:
+       *   - If `dataFormat` is `"channelsLast"`:
+       *     `[batch, rows, cols, channels]`
+       *   - If `data_format` is `"channels_first"`:
+       *     `[batch, channels, rows, cols]`.
+       *
+       * Output shape:
+       *   4D with shape:
+       *   - If `dataFormat` is `"channelsLast"`:
+       *     `[batch, paddedRows, paddedCols, channels]`
+       *    - If `dataFormat` is `"channelsFirst"`:
+       *     `[batch, channels, paddedRows, paddedCols]`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Padding', namespace: 'layers'} */
+      function zeroPadding2d(args) {
+        return new padding_ZeroPadding2D(args);
+      }
+      // Pooling Layers.
+      /**
+       * Average pooling operation for spatial data.
+       *
+       * Input shape: `[batchSize, inLength, channels]`
+       *
+       * Output shape: `[batchSize, pooledLength, channels]`
+       *
+       * `tf.avgPool1d` is an alias.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function averagePooling1d(args) {
+        return new pooling_AveragePooling1D(args);
+      }
+      function avgPool1d(args) {
+        return averagePooling1d(args);
+      }
+      // For backwards compatibility.
+      // See https://github.com/tensorflow/tfjs/issues/152
+      function avgPooling1d(args) {
+        return averagePooling1d(args);
+      }
+      /**
+       * Average pooling operation for spatial data.
+       *
+       * Input shape:
+       *  - If `dataFormat === CHANNEL_LAST`:
+       *      4D tensor with shape:
+       *      `[batchSize, rows, cols, channels]`
+       *  - If `dataFormat === CHANNEL_FIRST`:
+       *      4D tensor with shape:
+       *      `[batchSize, channels, rows, cols]`
+       *
+       * Output shape
+       *  - If `dataFormat === CHANNEL_LAST`:
+       *      4D tensor with shape:
+       *      `[batchSize, pooleRows, pooledCols, channels]`
+       *  - If `dataFormat === CHANNEL_FIRST`:
+       *      4D tensor with shape:
+       *      `[batchSize, channels, pooleRows, pooledCols]`
+       *
+       * `tf.avgPool2d` is an alias.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function averagePooling2d(args) {
+        return new pooling_AveragePooling2D(args);
+      }
+      function avgPool2d(args) {
+        return averagePooling2d(args);
+      }
+      // For backwards compatibility.
+      // See https://github.com/tensorflow/tfjs/issues/152
+      function avgPooling2d(args) {
+        return averagePooling2d(args);
+      }
+      /**
+       * Average pooling operation for 3D data.
+       *
+       * Input shape
+       *   - If `dataFormat === channelsLast`:
+       *       5D tensor with shape:
+       *       `[batchSize, depths, rows, cols, channels]`
+       *   - If `dataFormat === channelsFirst`:
+       *      4D tensor with shape:
+       *       `[batchSize, channels, depths, rows, cols]`
+       *
+       * Output shape
+       *   - If `dataFormat=channelsLast`:
+       *       5D tensor with shape:
+       *       `[batchSize, pooledDepths, pooledRows, pooledCols, channels]`
+       *   - If `dataFormat=channelsFirst`:
+       *       5D tensor with shape:
+       *       `[batchSize, channels, pooledDepths, pooledRows, pooledCols]`
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function averagePooling3d(args) {
+        return new pooling_AveragePooling3D(args);
+      }
+      function avgPool3d(args) {
+        return averagePooling3d(args);
+      }
+      // For backwards compatibility.
+      // See https://github.com/tensorflow/tfjs/issues/152
+      function avgPooling3d(args) {
+        return averagePooling3d(args);
+      }
+      /**
+       * Global average pooling operation for temporal data.
+       *
+       * Input Shape: 3D tensor with shape: `[batchSize, steps, features]`.
+       *
+       * Output Shape:2D tensor with shape: `[batchSize, features]`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function globalAveragePooling1d(args) {
+        return new pooling_GlobalAveragePooling1D(args);
+      }
+      /**
+       * Global average pooling operation for spatial data.
+       *
+       * Input shape:
+       *   - If `dataFormat` is `CHANNEL_LAST`:
+       *       4D tensor with shape: `[batchSize, rows, cols, channels]`.
+       *   - If `dataFormat` is `CHANNEL_FIRST`:
+       *       4D tensor with shape: `[batchSize, channels, rows, cols]`.
+       *
+       * Output shape:
+       *   2D tensor with shape: `[batchSize, channels]`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function globalAveragePooling2d(args) {
+        return new pooling_GlobalAveragePooling2D(args);
+      }
+      /**
+       * Global max pooling operation for temporal data.
+       *
+       * Input Shape: 3D tensor with shape: `[batchSize, steps, features]`.
+       *
+       * Output Shape:2D tensor with shape: `[batchSize, features]`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function globalMaxPooling1d(args) {
+        return new pooling_GlobalMaxPooling1D(args);
+      }
+      /**
+       * Global max pooling operation for spatial data.
+       *
+       * Input shape:
+       *   - If `dataFormat` is `CHANNEL_LAST`:
+       *       4D tensor with shape: `[batchSize, rows, cols, channels]`.
+       *   - If `dataFormat` is `CHANNEL_FIRST`:
+       *       4D tensor with shape: `[batchSize, channels, rows, cols]`.
+       *
+       * Output shape:
+       *   2D tensor with shape: `[batchSize, channels]`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function globalMaxPooling2d(args) {
+        return new pooling_GlobalMaxPooling2D(args);
+      }
+      /**
+       * Max pooling operation for temporal data.
+       *
+       * Input shape:  `[batchSize, inLength, channels]`
+       *
+       * Output shape: `[batchSize, pooledLength, channels]`
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function maxPooling1d(args) {
+        return new pooling_MaxPooling1D(args);
+      }
+      /**
+       * Max pooling operation for spatial data.
+       *
+       * Input shape
+       *   - If `dataFormat === CHANNEL_LAST`:
+       *       4D tensor with shape:
+       *       `[batchSize, rows, cols, channels]`
+       *   - If `dataFormat === CHANNEL_FIRST`:
+       *      4D tensor with shape:
+       *       `[batchSize, channels, rows, cols]`
+       *
+       * Output shape
+       *   - If `dataFormat=CHANNEL_LAST`:
+       *       4D tensor with shape:
+       *       `[batchSize, pooleRows, pooledCols, channels]`
+       *   - If `dataFormat=CHANNEL_FIRST`:
+       *       4D tensor with shape:
+       *       `[batchSize, channels, pooleRows, pooledCols]`
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function maxPooling2d(args) {
+        return new pooling_MaxPooling2D(args);
+      }
+      /**
+       * Max pooling operation for 3D data.
+       *
+       * Input shape
+       *   - If `dataFormat === channelsLast`:
+       *       5D tensor with shape:
+       *       `[batchSize, depths, rows, cols, channels]`
+       *   - If `dataFormat === channelsFirst`:
+       *      5D tensor with shape:
+       *       `[batchSize, channels, depths, rows, cols]`
+       *
+       * Output shape
+       *   - If `dataFormat=channelsLast`:
+       *       5D tensor with shape:
+       *       `[batchSize, pooledDepths, pooledRows, pooledCols, channels]`
+       *   - If `dataFormat=channelsFirst`:
+       *       5D tensor with shape:
+       *       `[batchSize, channels, pooledDepths, pooledRows, pooledCols]`
+       */
+      /** @doc {heading: 'Layers', subheading: 'Pooling', namespace: 'layers'} */
+      function maxPooling3d(args) {
+        return new pooling_MaxPooling3D(args);
+      }
+      // Recurrent Layers.
+      /**
+       * Gated Recurrent Unit - Cho et al. 2014.
+       *
+       * This is an `RNN` layer consisting of one `GRUCell`. However, unlike
+       * the underlying `GRUCell`, the `apply` method of `SimpleRNN` operates
+       * on a sequence of inputs. The shape of the input (not including the first,
+       * batch dimension) needs to be at least 2-D, with the first dimension being
+       * time steps. For example:
+       *
+       * ```js
+       * const rnn = tf.layers.gru({units: 8, returnSequences: true});
+       *
+       * // Create an input with 10 time steps.
+       * const input = tf.input({shape: [10, 20]});
+       * const output = rnn.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
+       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
+       * // 3rd dimension is the `GRUCell`'s number of units.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
+      function gru(args) {
+        return new recurrent_GRU(args);
+      }
+      /**
+       * Cell class for `GRU`.
+       *
+       * `GRUCell` is distinct from the `RNN` subclass `GRU` in that its
+       * `apply` method takes the input data of only a single time step and returns
+       * the cell's output at the time step, while `GRU` takes the input data
+       * over a number of time steps. For example:
+       *
+       * ```js
+       * const cell = tf.layers.gruCell({units: 2});
+       * const input = tf.input({shape: [10]});
+       * const output = cell.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10]: This is the cell's output at a single time step. The 1st
+       * // dimension is the unknown batch size.
+       * ```
+       *
+       * Instance(s) of `GRUCell` can be used to construct `RNN` layers. The
+       * most typical use of this workflow is to combine a number of cells into a
+       * stacked RNN cell (i.e., `StackedRNNCell` internally) and use it to create an
+       * RNN. For example:
+       *
+       * ```js
+       * const cells = [
+       *   tf.layers.gruCell({units: 4}),
+       *   tf.layers.gruCell({units: 8}),
+       * ];
+       * const rnn = tf.layers.rnn({cell: cells, returnSequences: true});
+       *
+       * // Create an input with 10 time steps and a length-20 vector at each step.
+       * const input = tf.input({shape: [10, 20]});
+       * const output = rnn.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
+       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
+       * // 3rd dimension is the last `gruCell`'s number of units.
+       * ```
+       *
+       * To create an `RNN` consisting of only *one* `GRUCell`, use the
+       * `tf.layers.gru`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
+      function gruCell(args) {
+        return new recurrent_GRUCell(args);
+      }
+      /**
+       * Long-Short Term Memory layer - Hochreiter 1997.
+       *
+       * This is an `RNN` layer consisting of one `LSTMCell`. However, unlike
+       * the underlying `LSTMCell`, the `apply` method of `LSTM` operates
+       * on a sequence of inputs. The shape of the input (not including the first,
+       * batch dimension) needs to be at least 2-D, with the first dimension being
+       * time steps. For example:
+       *
+       * ```js
+       * const lstm = tf.layers.lstm({units: 8, returnSequences: true});
+       *
+       * // Create an input with 10 time steps.
+       * const input = tf.input({shape: [10, 20]});
+       * const output = lstm.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
+       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
+       * // 3rd dimension is the `LSTMCell`'s number of units.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
+      function lstm(args) {
+        return new recurrent_LSTM(args);
+      }
+      /**
+       * Cell class for `LSTM`.
+       *
+       * `LSTMCell` is distinct from the `RNN` subclass `LSTM` in that its
+       * `apply` method takes the input data of only a single time step and returns
+       * the cell's output at the time step, while `LSTM` takes the input data
+       * over a number of time steps. For example:
+       *
+       * ```js
+       * const cell = tf.layers.lstmCell({units: 2});
+       * const input = tf.input({shape: [10]});
+       * const output = cell.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10]: This is the cell's output at a single time step. The 1st
+       * // dimension is the unknown batch size.
+       * ```
+       *
+       * Instance(s) of `LSTMCell` can be used to construct `RNN` layers. The
+       * most typical use of this workflow is to combine a number of cells into a
+       * stacked RNN cell (i.e., `StackedRNNCell` internally) and use it to create an
+       * RNN. For example:
+       *
+       * ```js
+       * const cells = [
+       *   tf.layers.lstmCell({units: 4}),
+       *   tf.layers.lstmCell({units: 8}),
+       * ];
+       * const rnn = tf.layers.rnn({cell: cells, returnSequences: true});
+       *
+       * // Create an input with 10 time steps and a length-20 vector at each step.
+       * const input = tf.input({shape: [10, 20]});
+       * const output = rnn.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
+       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
+       * // 3rd dimension is the last `lstmCell`'s number of units.
+       * ```
+       *
+       * To create an `RNN` consisting of only *one* `LSTMCell`, use the
+       * `tf.layers.lstm`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
+      function lstmCell(args) {
+        return new recurrent_LSTMCell(args);
+      }
+      /**
+       * Fully-connected RNN where the output is to be fed back to input.
+       *
+       * This is an `RNN` layer consisting of one `SimpleRNNCell`. However, unlike
+       * the underlying `SimpleRNNCell`, the `apply` method of `SimpleRNN` operates
+       * on a sequence of inputs. The shape of the input (not including the first,
+       * batch dimension) needs to be at least 2-D, with the first dimension being
+       * time steps. For example:
+       *
+       * ```js
+       * const rnn = tf.layers.simpleRNN({units: 8, returnSequences: true});
+       *
+       * // Create an input with 10 time steps.
+       * const input = tf.input({shape: [10, 20]});
+       * const output = rnn.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
+       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
+       * // 3rd dimension is the `SimpleRNNCell`'s number of units.
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
+      function simpleRNN(args) {
+        return new recurrent_SimpleRNN(args);
+      }
+      /**
+       * Cell class for `SimpleRNN`.
+       *
+       * `SimpleRNNCell` is distinct from the `RNN` subclass `SimpleRNN` in that its
+       * `apply` method takes the input data of only a single time step and returns
+       * the cell's output at the time step, while `SimpleRNN` takes the input data
+       * over a number of time steps. For example:
+       *
+       * ```js
+       * const cell = tf.layers.simpleRNNCell({units: 2});
+       * const input = tf.input({shape: [10]});
+       * const output = cell.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10]: This is the cell's output at a single time step. The 1st
+       * // dimension is the unknown batch size.
+       * ```
+       *
+       * Instance(s) of `SimpleRNNCell` can be used to construct `RNN` layers. The
+       * most typical use of this workflow is to combine a number of cells into a
+       * stacked RNN cell (i.e., `StackedRNNCell` internally) and use it to create an
+       * RNN. For example:
+       *
+       * ```js
+       * const cells = [
+       *   tf.layers.simpleRNNCell({units: 4}),
+       *   tf.layers.simpleRNNCell({units: 8}),
+       * ];
+       * const rnn = tf.layers.rnn({cell: cells, returnSequences: true});
+       *
+       * // Create an input with 10 time steps and a length-20 vector at each step.
+       * const input = tf.input({shape: [10, 20]});
+       * const output = rnn.apply(input);
+       *
+       * console.log(JSON.stringify(output.shape));
+       * // [null, 10, 8]: 1st dimension is unknown batch size; 2nd dimension is the
+       * // same as the sequence length of `input`, due to `returnSequences`: `true`;
+       * // 3rd dimension is the last `SimpleRNNCell`'s number of units.
+       * ```
+       *
+       * To create an `RNN` consisting of only *one* `SimpleRNNCell`, use the
+       * `tf.layers.simpleRNN`.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
+      function simpleRNNCell(args) {
+        return new recurrent_SimpleRNNCell(args);
+      }
+      /**
+       * Base class for recurrent layers.
+       *
+       * Input shape:
+       *   3D tensor with shape `[batchSize, timeSteps, inputDim]`.
+       *
+       * Output shape:
+       *   - if `returnState`, an Array of tensors (i.e., `tf.Tensor`s). The first
+       *     tensor is the output. The remaining tensors are the states at the
+       *     last time step, each with shape `[batchSize, units]`.
+       *   - if `returnSequences`, the output will have shape
+       *     `[batchSize, timeSteps, units]`.
+       *   - else, the output will have shape `[batchSize, units]`.
+       *
+       * Masking:
+       *   This layer supports masking for input data with a variable number
+       *   of timesteps. To introduce masks to your data,
+       *   use an embedding layer with the `mask_zero` parameter
+       *   set to `True`.
+       *
+       * Notes on using statefulness in RNNs:
+       *   You can set RNN layers to be 'stateful', which means that the states
+       *   computed for the samples in one batch will be reused as initial states
+       *   for the samples in the next batch. This assumes a one-to-one mapping
+       *   between samples in different successive batches.
+       *
+       *   To enable statefulness:
+       *     - specify `stateful: true` in the layer constructor.
+       *     - specify a fixed batch size for your model, by passing
+       *       if sequential model:
+       *         `batchInputShape=[...]` to the first layer in your model.
+       *       else for functional model with 1 or more Input layers:
+       *         `batchShape=[...]` to all the first layers in your model.
+       *       This is the expected shape of your inputs *including the batch size*.
+       *       It should be a tuple of integers, e.g. `(32, 10, 100)`.
+       *     - specify `shuffle=False` when calling fit().
+       *
+       *   To reset the states of your model, call `.resetStates()` on either
+       *   a specific layer, or on your entire model.
+       *
+       * Note on specifying the initial state of RNNs
+       *   You can specify the initial state of RNN layers symbolically by
+       *   calling them with the option `initialState`. The value of
+       *   `initialState` should be a tensor or list of tensors representing
+       *   the initial state of the RNN layer.
+       *
+       *   You can specify the initial state of RNN layers numerically by
+       *   calling `resetStates` with the keyword argument `states`. The value of
+       *   `states` should be a numpy array or list of numpy arrays representing
+       *   the initial state of the RNN layer.
+       *
+       * Note on passing external constants to RNNs
+       *   You can pass "external" constants to the cell using the `constants`
+       *   keyword argument of `RNN.call` method. This requires that the `cell.call`
+       *   method accepts the same keyword argument `constants`. Such constants
+       *   can be used to conditon the cell transformation on additional static inputs
+       *   (not changing over time), a.k.a an attention mechanism.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
+      function exports_layers_rnn(args) {
+        return new recurrent_RNN(args);
+      }
+      /**
+       * Wrapper allowing a stack of RNN cells to behave as a single cell.
+       *
+       * Used to implement efficient stacked RNNs.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Recurrent', namespace: 'layers'} */
+      function stackedRNNCells(args) {
+        return new recurrent_StackedRNNCells(args);
+      }
+      // Wrapper Layers.
+      /** @doc {heading: 'Layers', subheading: 'Wrapper', namespace: 'layers'} */
+      function bidirectional(args) {
+        return new wrappers_Bidirectional(args);
+      }
+      /**
+       * This wrapper applies a layer to every temporal slice of an input.
+       *
+       * The input should be at least 3D,  and the dimension of the index `1` will be
+       * considered to be the temporal dimension.
+       *
+       * Consider a batch of 32 samples, where each sample is a sequence of 10 vectors
+       * of 16 dimensions. The batch input shape of the layer is then `[32,  10,
+       * 16]`, and the `inputShape`, not including the sample dimension, is
+       * `[10, 16]`.
+       *
+       * You can then use `TimeDistributed` to apply a `Dense` layer to each of the 10
+       * timesteps, independently:
+       *
+       * ```js
+       * const model = tf.sequential();
+       * model.add(tf.layers.timeDistributed({
+       *   layer: tf.layers.dense({units: 8}),
+       *   inputShape: [10, 16],
+       * }));
+       *
+       * // Now model.outputShape = [null, 10, 8].
+       * // The output will then have shape `[32, 10, 8]`.
+       *
+       * // In subsequent layers, there is no need for `inputShape`:
+       * model.add(tf.layers.timeDistributed({layer: tf.layers.dense({units: 32})}));
+       * console.log(JSON.stringify(model.outputs[0].shape));
+       * // Now model.outputShape = [null, 10, 32].
+       * ```
+       *
+       * The output will then have shape `[32, 10, 32]`.
+       *
+       * `TimeDistributed` can be used with arbitrary layers, not just `Dense`, for
+       * instance a `Conv2D` layer.
+       *
+       * ```js
+       * const model = tf.sequential();
+       * model.add(tf.layers.timeDistributed({
+       *   layer: tf.layers.conv2d({filters: 64, kernelSize: [3, 3]}),
+       *   inputShape: [10, 299, 299, 3],
+       * }));
+       * console.log(JSON.stringify(model.outputs[0].shape));
+       * ```
+       */
+      /** @doc {heading: 'Layers', subheading: 'Wrapper', namespace: 'layers'} */
+      function timeDistributed(args) {
+        return new wrappers_TimeDistributed(args);
+      }
+      // Aliases for pooling.
+      const globalMaxPool1d = globalMaxPooling1d;
+      const globalMaxPool2d = globalMaxPooling2d;
+      const maxPool1d = maxPooling1d;
+      const maxPool2d = maxPooling2d;
+
+      /**
+       * Apply additive zero-centered Gaussian noise.
+       *
+       * As it is a regularization layer, it is only active at training time.
+       *
+       * This is useful to mitigate overfitting
+       * (you could see it as a form of random data augmentation).
+       * Gaussian Noise (GS) is a natural choice as corruption process
+       * for real valued inputs.
+       *
+       * # Arguments
+       *     stddev: float, standard deviation of the noise distribution.
+       *
+       * # Input shape
+       *         Arbitrary. Use the keyword argument `input_shape`
+       *         (tuple of integers, does not include the samples axis)
+       *         when using this layer as the first layer in a model.
+       *
+       * # Output shape
+       *         Same shape as input.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Noise', namespace: 'layers'} */
+      function gaussianNoise(args) {
+        return new noise_GaussianNoise(args);
+      }
+      /**
+       * Apply multiplicative 1-centered Gaussian noise.
+       *
+       * As it is a regularization layer, it is only active at training time.
+       *
+       * Arguments:
+       *   - `rate`: float, drop probability (as with `Dropout`).
+       *     The multiplicative noise will have
+       *     standard deviation `sqrt(rate / (1 - rate))`.
+       *
+       * Input shape:
+       *   Arbitrary. Use the keyword argument `inputShape`
+       *   (tuple of integers, does not include the samples axis)
+       *   when using this layer as the first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as input.
+       *
+       * References:
+       *   - [Dropout: A Simple Way to Prevent Neural Networks from Overfitting](
+       *      http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf)
+       *
+       */
+      /** @doc {heading: 'Layers', subheading: 'Noise', namespace: 'layers'} */
+      function gaussianDropout(args) {
+        return new noise_GaussianDropout(args);
+      }
+      /**
+       * Applies Alpha Dropout to the input.
+       *
+       * As it is a regularization layer, it is only active at training time.
+       *
+       * Alpha Dropout is a `Dropout` that keeps mean and variance of inputs
+       * to their original values, in order to ensure the self-normalizing property
+       * even after this dropout.
+       * Alpha Dropout fits well to Scaled Exponential Linear Units
+       * by randomly setting activations to the negative saturation value.
+       *
+       * Arguments:
+       *   - `rate`: float, drop probability (as with `Dropout`).
+       *     The multiplicative noise will have
+       *     standard deviation `sqrt(rate / (1 - rate))`.
+       *   - `noise_shape`: A 1-D `Tensor` of type `int32`, representing the
+       *     shape for randomly generated keep/drop flags.
+       *
+       * Input shape:
+       *   Arbitrary. Use the keyword argument `inputShape`
+       *   (tuple of integers, does not include the samples axis)
+       *   when using this layer as the first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as input.
+       *
+       * References:
+       *   - [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)
+       */
+      /** @doc {heading: 'Layers', subheading: 'Noise', namespace: 'layers'} */
+      function alphaDropout(args) {
+        return new noise_AlphaDropout(args);
+      }
+      /**
+       * Masks a sequence by using a mask value to skip timesteps.
+       *
+       * If all features for a given sample timestep are equal to `mask_value`,
+       * then the sample timestep will be masked (skipped) in all downstream layers
+       * (as long as they support masking).
+       *
+       * If any downstream layer does not support masking yet receives such
+       * an input mask, an exception will be raised.
+       *
+       * Arguments:
+       *   - `maskValue`: Either None or mask value to skip.
+       *
+       * Input shape:
+       *   Arbitrary. Use the keyword argument `inputShape`
+       *   (tuple of integers, does not include the samples axis)
+       *   when using this layer as the first layer in a model.
+       *
+       * Output shape:
+       *   Same shape as input.
+       */
+      /** @doc {heading: 'Layers', subheading: 'Mask', namespace: 'layers'} */
+      function masking(args) {
+        return new core_Masking(args);
+      }
+      //# sourceMappingURL=exports_layers.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_metrics.js
+
+      /**
+       * Binary accuracy metric function.
+       *
+       * `yTrue` and `yPred` can have 0-1 values. Example:
+       * ```js
+       * const x = tf.tensor2d([[1, 1, 1, 1], [0, 0, 0, 0]], [2, 4]);
+       * const y = tf.tensor2d([[1, 0, 1, 0], [0, 0, 0, 1]], [2, 4]);
+       * const accuracy = tf.metrics.binaryAccuracy(x, y);
+       * accuracy.print();
+       * ```
+       *
+       * `yTrue` and `yPred` can also have floating-number values between 0 and 1, in
+       * which case the values will be thresholded at 0.5 to yield 0-1 values (i.e.,
+       * a value >= 0.5 and <= 1.0 is interpreted as 1.
+       * )
+       * Example:
+       * ```js
+       * const x = tf.tensor1d([1, 1, 1, 1, 0, 0, 0, 0]);
+       * const y = tf.tensor1d([0.2, 0.4, 0.6, 0.8, 0.2, 0.3, 0.4, 0.7]);
+       * const accuracy = tf.metrics.binaryAccuracy(x, y);
+       * accuracy.print();
+       * ```
+       *
+       * @param yTrue Binary Tensor of truth.
+       * @param yPred Binary Tensor of prediction.
+       * @return Accuracy Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_binaryAccuracy(yTrue, yPred) {
+        return binaryAccuracy(yTrue, yPred);
+      }
+      /**
+       * Binary crossentropy metric function.
+       *
+       * Example:
+       * ```js
+       * const x = tf.tensor2d([[0], [1], [1], [1]]);
+       * const y = tf.tensor2d([[0], [0], [0.5], [1]]);
+       * const crossentropy = tf.metrics.binaryCrossentropy(x, y);
+       * crossentropy.print();
+       * ```
+       *
+       * @param yTrue Binary Tensor of truth.
+       * @param yPred Binary Tensor of prediction, probabilities for the `1` case.
+       * @return Accuracy Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_binaryCrossentropy(yTrue, yPred) {
+        return metrics_binaryCrossentropy(yTrue, yPred);
+      }
+      /**
+       * Sparse categorical accuracy metric function.
+       *
+       * Example:
+       * ```js
+       *
+       * const yTrue = tf.tensor1d([1, 1, 2, 2, 0]);
+       * const yPred = tf.tensor2d(
+       *      [[0, 1, 0], [1, 0, 0], [0, 0.4, 0.6], [0, 0.6, 0.4], [0.7, 0.3, 0]]);
+       * const crossentropy = tf.metrics.sparseCategoricalAccuracy(yTrue, yPred);
+       * crossentropy.print();
+       * ```
+       *
+       * @param yTrue True labels: indices.
+       * @param yPred Predicted probabilities or logits.
+       * @returns Accuracy tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_sparseCategoricalAccuracy(yTrue, yPred) {
+        return sparseCategoricalAccuracy(yTrue, yPred);
+      }
+      /**
+       * Categorical accuracy metric function.
+       *
+       * Example:
+       * ```js
+       * const x = tf.tensor2d([[0, 0, 0, 1], [0, 0, 0, 1]]);
+       * const y = tf.tensor2d([[0.1, 0.8, 0.05, 0.05], [0.1, 0.05, 0.05, 0.8]]);
+       * const accuracy = tf.metrics.categoricalAccuracy(x, y);
+       * accuracy.print();
+       * ```
+       *
+       * @param yTrue Binary Tensor of truth: one-hot encoding of categories.
+       * @param yPred Binary Tensor of prediction: probabilities or logits for the
+       *   same categories as in `yTrue`.
+       * @return Accuracy Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_categoricalAccuracy(yTrue, yPred) {
+        return categoricalAccuracy(yTrue, yPred);
+      }
+      /**
+       * Categorical crossentropy between an output tensor and a target tensor.
+       *
+       * @param target A tensor of the same shape as `output`.
+       * @param output A tensor resulting from a softmax (unless `fromLogits` is
+       *  `true`, in which case `output` is expected to be the logits).
+       * @param fromLogits Boolean, whether `output` is the result of a softmax, or is
+       *   a tensor of logits.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_categoricalCrossentropy(yTrue, yPred) {
+        return metrics_categoricalCrossentropy(yTrue, yPred);
+      }
+      /**
+       * Computes the precision of the predictions with respect to the labels.
+       *
+       * Example:
+       * ```js
+       * const x = tf.tensor2d(
+       *    [
+       *      [0, 0, 0, 1],
+       *      [0, 1, 0, 0],
+       *      [0, 0, 0, 1],
+       *      [1, 0, 0, 0],
+       *      [0, 0, 1, 0]
+       *    ]
+       * );
+       *
+       * const y = tf.tensor2d(
+       *    [
+       *      [0, 0, 1, 0],
+       *      [0, 1, 0, 0],
+       *      [0, 0, 0, 1],
+       *      [0, 1, 0, 0],
+       *      [0, 1, 0, 0]
+       *    ]
+       * );
+       *
+       * const precision = tf.metrics.precision(x, y);
+       * precision.print();
+       * ```
+       *
+       * @param yTrue The ground truth values. Expected to be contain only 0-1 values.
+       * @param yPred The predicted values. Expected to be contain only 0-1 values.
+       * @return Precision Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_precision(yTrue, yPred) {
+        return precision(yTrue, yPred);
+      }
+      /**
+       * Computes the recall of the predictions with respect to the labels.
+       *
+       * Example:
+       * ```js
+       * const x = tf.tensor2d(
+       *    [
+       *      [0, 0, 0, 1],
+       *      [0, 1, 0, 0],
+       *      [0, 0, 0, 1],
+       *      [1, 0, 0, 0],
+       *      [0, 0, 1, 0]
+       *    ]
+       * );
+       *
+       * const y = tf.tensor2d(
+       *    [
+       *      [0, 0, 1, 0],
+       *      [0, 1, 0, 0],
+       *      [0, 0, 0, 1],
+       *      [0, 1, 0, 0],
+       *      [0, 1, 0, 0]
+       *    ]
+       * );
+       *
+       * const recall = tf.metrics.recall(x, y);
+       * recall.print();
+       * ```
+       *
+       * @param yTrue The ground truth values. Expected to be contain only 0-1 values.
+       * @param yPred The predicted values. Expected to be contain only 0-1 values.
+       * @return Recall Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_recall(yTrue, yPred) {
+        return recall(yTrue, yPred);
+      }
+      /**
+       * Loss or metric function: Cosine proximity.
+       *
+       * Mathematically, cosine proximity is defined as:
+       *   `-sum(l2Normalize(yTrue) * l2Normalize(yPred))`,
+       * wherein `l2Normalize()` normalizes the L2 norm of the input to 1 and `*`
+       * represents element-wise multiplication.
+       *
+       * ```js
+       * const yTrue = tf.tensor2d([[1, 0], [1, 0]]);
+       * const yPred = tf.tensor2d([[1 / Math.sqrt(2), 1 / Math.sqrt(2)], [0, 1]]);
+       * const proximity = tf.metrics.cosineProximity(yTrue, yPred);
+       * proximity.print();
+       * ```
+       *
+       * @param yTrue Truth Tensor.
+       * @param yPred Prediction Tensor.
+       * @return Cosine proximity Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_cosineProximity(yTrue, yPred) {
+        return cosineProximity(yTrue, yPred);
+      }
+      /**
+       * Loss or metric function: Mean absolute error.
+       *
+       * Mathematically, mean absolute error is defined as:
+       *   `mean(abs(yPred - yTrue))`,
+       * wherein the `mean` is applied over feature dimensions.
+       *
+       * ```js
+       * const yTrue = tf.tensor2d([[0, 1], [0, 0], [2, 3]]);
+       * const yPred = tf.tensor2d([[0, 1], [0, 1], [-2, -3]]);
+       * const mse = tf.metrics.meanAbsoluteError(yTrue, yPred);
+       * mse.print();
+       * ```
+       *
+       * @param yTrue Truth Tensor.
+       * @param yPred Prediction Tensor.
+       * @return Mean absolute error Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_meanAbsoluteError(yTrue, yPred) {
+        return meanAbsoluteError(yTrue, yPred);
+      }
+      /**
+       * Loss or metric function: Mean absolute percentage error.
+       *
+       * ```js
+       * const yTrue = tf.tensor2d([[0, 1], [10, 20]]);
+       * const yPred = tf.tensor2d([[0, 1], [11, 24]]);
+       * const mse = tf.metrics.meanAbsolutePercentageError(yTrue, yPred);
+       * mse.print();
+       * ```
+       *
+       * Aliases: `tf.metrics.MAPE`, `tf.metrics.mape`.
+       *
+       * @param yTrue Truth Tensor.
+       * @param yPred Prediction Tensor.
+       * @return Mean absolute percentage error Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_meanAbsolutePercentageError(yTrue, yPred) {
+        return meanAbsolutePercentageError(yTrue, yPred);
+      }
+      function exports_metrics_MAPE(yTrue, yPred) {
+        return meanAbsolutePercentageError(yTrue, yPred);
+      }
+      function exports_metrics_mape(yTrue, yPred) {
+        return meanAbsolutePercentageError(yTrue, yPred);
+      }
+      /**
+       * Loss or metric function: Mean squared error.
+       *
+       * ```js
+       * const yTrue = tf.tensor2d([[0, 1], [3, 4]]);
+       * const yPred = tf.tensor2d([[0, 1], [-3, -4]]);
+       * const mse = tf.metrics.meanSquaredError(yTrue, yPred);
+       * mse.print();
+       * ```
+       *
+       * Aliases: `tf.metrics.MSE`, `tf.metrics.mse`.
+       *
+       * @param yTrue Truth Tensor.
+       * @param yPred Prediction Tensor.
+       * @return Mean squared error Tensor.
+       */
+      /** @doc {heading: 'Metrics', namespace: 'metrics'} */
+      function exports_metrics_meanSquaredError(yTrue, yPred) {
+        return meanSquaredError(yTrue, yPred);
+      }
+      function exports_metrics_MSE(yTrue, yPred) {
+        return meanSquaredError(yTrue, yPred);
+      }
+      function exports_metrics_mse(yTrue, yPred) {
+        return meanSquaredError(yTrue, yPred);
+      }
+      //# sourceMappingURL=exports_metrics.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_models.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      //# sourceMappingURL=exports_models.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/exports_regularizers.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+
+      // tslint:disable-next-line:max-line-length
+
+      /**
+       * Regularizer for L1 and L2 regularization.
+       *
+       * Adds a term to the loss to penalize large weights:
+       * loss += sum(l1 * abs(x)) + sum(l2 * x^2)
+       */
+      /** @doc {heading: 'Regularizers', namespace: 'regularizers'} */
+      function l1l2(config) {
+        return new regularizers_L1L2(config);
+      }
+      /**
+       * Regularizer for L1 regularization.
+       *
+       * Adds a term to the loss to penalize large weights:
+       * loss += sum(l1 * abs(x))
+       * @param args l1 config.
+       */
+      /** @doc {heading: 'Regularizers', namespace: 'regularizers'} */
+      function exports_regularizers_l1(config) {
+        return l1(config);
+      }
+      /**
+       * Regularizer for L2 regularization.
+       *
+       * Adds a term to the loss to penalize large weights:
+       * loss += sum(l2 * x^2)
+       * @param args l2 config.
+       */
+      /** @doc {heading: 'Regularizers', namespace: 'regularizers'} */
+      function exports_regularizers_l2(config) {
+        return l2(config);
+      }
+      //# sourceMappingURL=exports_regularizers.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/callbacks.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      /* Original source: keras/callbacks.py */
+
+      class callbacks_Callback extends BaseCallback {
+        constructor() {
+          super(...arguments);
+          /** Instance of `keras.models.Model`. Reference of the model being trained. */
+          this.model = null;
+        }
+        setModel(model) {
+          if (!(model instanceof training_LayersModel)) {
+            throw new Error("model must be a LayersModel, not some other Container");
+          }
+          this.model = model;
+        }
+      }
+      function less(currVal, prevVal) {
+        return currVal < prevVal;
+      }
+      function greater(currVal, prevVal) {
+        return currVal > prevVal;
+      }
+      /**
+       * A Callback that stops training when a monitored quantity has stopped
+       * improving.
+       */
+      class callbacks_EarlyStopping extends callbacks_Callback {
+        constructor(args) {
+          super();
+          if (args == null) {
+            args = {};
+          }
+          if (args.restoreBestWeights) {
+            throw new NotImplementedError(
+              "restoreBestWeights = True is not implemented in EarlyStopping yet."
+            );
+          }
+          this.monitor = args.monitor || "val_loss";
+          this.minDelta = Math.abs(args.minDelta || 0);
+          this.patience = args.patience || 0;
+          this.verbose = args.verbose || 0;
+          this.mode = args.mode || "auto";
+          this.baseline = args.baseline;
+          if (["auto", "min", "max"].indexOf(this.mode) === -1) {
+            console.warn(
+              `EarlyStopping mode '${this.mode}' is invalid. ` + `Falling back to mode 'auto'.`
+            );
+            this.mode = "auto";
+          }
+          if (this.mode === "min") {
+            this.monitorFunc = less;
+          } else if (this.mode === "max") {
+            this.monitorFunc = greater;
+          } else {
+            // For mode === 'auto'.
+            if (this.monitor.indexOf("acc") !== -1) {
+              this.monitorFunc = greater;
+            } else {
+              this.monitorFunc = less;
+            }
+          }
+          if (this.monitorFunc === less) {
+            this.minDelta *= -1;
+          }
+        }
+        async onTrainBegin(logs) {
+          this.wait = 0;
+          this.stoppedEpoch = 0;
+          if (this.baseline != null) {
+            this.best = this.baseline;
+          } else {
+            this.best = this.monitorFunc === less ? Infinity : -Infinity;
+          }
+        }
+        async onEpochEnd(epoch, logs) {
+          await resolveScalarsInLogs(logs);
+          const current = this.getMonitorValue(logs);
+          if (current == null) {
+            return;
+          }
+          if (this.monitorFunc(current - this.minDelta, this.best)) {
+            this.best = current;
+            this.wait = 0;
+            // TODO(cais): Logic for restoreBestWeights.
+          } else {
+            this.wait++;
+            if (this.wait >= this.patience) {
+              this.stoppedEpoch = epoch;
+              this.model.stopTraining = true;
+            }
+            // TODO(cais): Logic for restoreBestWeights.
+          }
+        }
+        async onTrainEnd(logs) {
+          if (this.stoppedEpoch > 0 && this.verbose) {
+            console.log(`Epoch ${this.stoppedEpoch}: early stopping.`);
+          }
+        }
+        getMonitorValue(logs) {
+          if (logs == null) {
+            logs = {};
+          }
+          const monitorValue = logs[this.monitor];
+          if (monitorValue == null) {
+            console.warn(
+              `Metric for EarlyStopping ${this.monitor} is not available. ` +
+                `Available metrics are: ${Object.keys(logs)}`
+            );
+          }
+          return monitorValue;
+        }
+      }
+      /**
+       * Factory function for a Callback that stops training when a monitored
+       * quantity has stopped improving.
+       *
+       * Early stopping is a type of regularization, and protects model against
+       * overfitting.
+       *
+       * The following example based on fake data illustrates how this callback
+       * can be used during `tf.LayersModel.fit()`:
+       *
+       * ```js
+       * const model = tf.sequential();
+       * model.add(tf.layers.dense({
+       *   units: 3,
+       *   activation: 'softmax',
+       *   kernelInitializer: 'ones',
+       *   inputShape: [2]
+       * }));
+       * const xs = tf.tensor2d([1, 2, 3, 4], [2, 2]);
+       * const ys = tf.tensor2d([[1, 0, 0], [0, 1, 0]], [2, 3]);
+       * const xsVal = tf.tensor2d([4, 3, 2, 1], [2, 2]);
+       * const ysVal = tf.tensor2d([[0, 0, 1], [0, 1, 0]], [2, 3]);
+       * model.compile(
+       *     {loss: 'categoricalCrossentropy', optimizer: 'sgd', metrics: ['acc']});
+       *
+       * // Without the EarlyStopping callback, the val_acc value would be:
+       * //   0.5, 0.5, 0.5, 0.5, ...
+       * // With val_acc being monitored, training should stop after the 2nd epoch.
+       * const history = await model.fit(xs, ys, {
+       *   epochs: 10,
+       *   validationData: [xsVal, ysVal],
+       *   callbacks: tf.callbacks.earlyStopping({monitor: 'val_acc'})
+       * });
+       *
+       * // Expect to see a length-2 array.
+       * console.log(history.history.val_acc);
+       * ```
+       */
+      /**
+       * @doc {
+       *   heading: 'Callbacks',
+       *   namespace: 'callbacks'
+       * }
+       */
+      function earlyStopping(args) {
+        return new callbacks_EarlyStopping(args);
+      }
+      const callbacks_callbacks = { earlyStopping };
+      //# sourceMappingURL=callbacks.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-layers/dist/index.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC
+       *
+       * Use of this source code is governed by an MIT-style
+       * license that can be found in the LICENSE file or at
+       * https://opensource.org/licenses/MIT.
+       * =============================================================================
+       */
+      // This file lists all exports of TensorFlow.js Layers
+
+      //# sourceMappingURL=index.js.map
+
+      /***/
+    },
+    /* 88 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      // ESM COMPAT FLAG
+      __webpack_require__.r(__webpack_exports__);
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "array", function () {
+        return /* reexport */ array;
+      });
+      __webpack_require__.d(__webpack_exports__, "Dataset", function () {
+        return /* reexport */ dataset_Dataset;
+      });
+      __webpack_require__.d(__webpack_exports__, "zip", function () {
+        return /* reexport */ zip;
+      });
+      __webpack_require__.d(__webpack_exports__, "CSVDataset", function () {
+        return /* reexport */ csv_dataset_CSVDataset;
+      });
+      __webpack_require__.d(__webpack_exports__, "TextLineDataset", function () {
+        return /* reexport */ text_line_dataset_TextLineDataset;
+      });
+      __webpack_require__.d(__webpack_exports__, "csv", function () {
+        return /* reexport */ csv;
+      });
+      __webpack_require__.d(__webpack_exports__, "func", function () {
+        return /* reexport */ func;
+      });
+      __webpack_require__.d(__webpack_exports__, "generator", function () {
+        return /* reexport */ readers_generator;
+      });
+      __webpack_require__.d(__webpack_exports__, "microphone", function () {
+        return /* reexport */ microphone;
+      });
+      __webpack_require__.d(__webpack_exports__, "webcam", function () {
+        return /* reexport */ webcam;
+      });
+      __webpack_require__.d(__webpack_exports__, "FileDataSource", function () {
+        return /* reexport */ file_data_source_FileDataSource;
+      });
+      __webpack_require__.d(__webpack_exports__, "URLDataSource", function () {
+        return /* reexport */ url_data_source_URLDataSource;
+      });
+      __webpack_require__.d(__webpack_exports__, "version_data", function () {
+        return /* reexport */ version;
+      });
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
+      var dist = __webpack_require__(0);
+
+      // EXTERNAL MODULE: ./node_modules/seedrandom/index.js
+      var seedrandom = __webpack_require__(20);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/lazy_iterator.js + 3 modules
+      var lazy_iterator = __webpack_require__(14);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/deep_map.js
+      var deep_map = __webpack_require__(19);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/dataset.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      // TODO(soergel): consider vectorized operations within the pipeline.
+      /**
+       * Represents a potentially large list of independent data elements (typically
+       * 'samples' or 'examples').
+       *
+       * A 'data example' may be a primitive, an array, a map from string keys to
+       * values, or any nested structure of these.
+       *
+       * A `Dataset` represents an ordered collection of elements, together with a
+       * chain of transformations to be performed on those elements. Each
+       * transformation is a method of `Dataset` that returns another `Dataset`, so
+       * these may be chained, e.g.
+       * `const processedDataset = rawDataset.filter(...).map(...).batch(...)`.
+       *
+       * Data loading and transformation is done in a lazy, streaming fashion.  The
+       * dataset may be iterated over multiple times; each iteration starts the data
+       * loading anew and recapitulates the transformations.
+       *
+       * A `Dataset` is typically processed as a stream of unbatched examples --i.e.,
+       * its transformations are applied one example at a time. Batching produces a
+       * new `Dataset` where each element is a batch. Batching should usually come
+       * last in a pipeline, because data transformations are easier to express on a
+       * per-example basis than on a per-batch basis.
+       *
+       * The following code examples are calling `await dataset.forEachAsync(...)` to
+       * iterate once over the entire dataset in order to print out the data.
+       */
+      /** @doc {heading: 'Data', subheading: 'Classes', namespace: 'data'} */
+      class dataset_Dataset {
+        constructor() {
+          this.size = null;
+        }
+        // TODO(soergel): Make Datasets report whether repeated iterator() calls
+        // produce the same result (e.g., reading from a file) or different results
+        // (e.g., from the webcam).  Currently we don't make this distinction but it
+        // could be important for the user to know.
+        // abstract isDeterministic(): boolean;
+        /**
+         * Groups elements into batches.
+         *
+         * It is assumed that each of the incoming dataset elements has the same
+         * structure-- i.e. the same set of keys at each location in an object
+         * hierarchy.  For each key, the resulting `Dataset` provides a batched
+         * element collecting all of the incoming values for that key.
+         *
+         *  * Incoming primitives are grouped into a 1-D Tensor.
+         *  * Incoming Tensors are grouped into a new Tensor where the 0'th axis is
+         *    the batch dimension.
+         *  * Incoming arrays are converted to Tensor and then batched.
+         *  * A nested array is interpreted as an n-D Tensor, so the batched result
+         *    has n+1 dimensions.
+         *  * An array that cannot be converted to Tensor produces an error.
+         *
+         * If an array should not be batched as a unit, it should first be converted
+         * to an object with integer keys.
+         *
+         * Here are a few examples:
+         *
+         * Batch a dataset of numbers:
+         * ```js
+         * const a = tf.data.array([1, 2, 3, 4, 5, 6, 7, 8]).batch(4);
+         * await a.forEachAsync(e => e.print());
+         * ```
+         *
+         * Batch a dataset of arrays:
+         * ```js
+         * const b = tf.data.array([[1], [2], [3], [4], [5], [6], [7], [8]]).batch(4);
+         * await b.forEachAsync(e => e.print());
+         * ```
+         *
+         * Batch a dataset of objects:
+         * ```js
+         * const c = tf.data.array([{a: 1, b: 11}, {a: 2, b: 12}, {a: 3, b: 13},
+         *   {a: 4, b: 14}, {a: 5, b: 15}, {a: 6, b: 16}, {a: 7, b: 17},
+         *   {a: 8, b: 18}]).batch(4);
+         * await c.forEachAsync(e => {
+         *   console.log('{');
+         *   for(var key in e) {
+         *     console.log(key+':');
+         *     e[key].print();
+         *   }
+         *   console.log('}');
+         * })
+         * ```
+         *
+         * @param batchSize The number of elements desired per batch.
+         * @param smallLastBatch Whether to emit the final batch when it has fewer
+         *   than batchSize elements. Default true.
+         * @returns A `Dataset`, from which a stream of batches can be obtained.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        batch(batchSize, smallLastBatch = true) {
+          const base = this;
+          dist["util"].assert(
+            batchSize > 0,
+            () => `batchSize needs to be positive, but it is
+      ${batchSize}`
+          );
+          let size;
+          if (this.size === Infinity || this.size == null) {
+            // If the size of this dataset is infinity or null, the new size keeps the
+            // same.
+            size = this.size;
+          } else if (smallLastBatch) {
+            // If the size of this dataset is known and include small last batch, the
+            // new size is full batch count plus last batch.
+            size = Math.ceil(this.size / batchSize);
+          } else {
+            // If the size of this dataset is known and not include small last batch,
+            // the new size is full batch count.
+            size = Math.floor(this.size / batchSize);
+          }
+          return datasetFromIteratorFn(async () => {
+            return (await base.iterator()).columnMajorBatch(
+              batchSize,
+              smallLastBatch,
+              deepBatchConcat
+            );
+          }, size);
+        }
+        /**
+         * Concatenates this `Dataset` with another.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3]);
+         * const b = tf.data.array([4, 5, 6]);
+         * const c = a.concatenate(b);
+         * await c.forEachAsync(e => console.log(e));
+         * ```
+         *
+         * @param dataset A `Dataset` to be concatenated onto this one.
+         * @returns A `Dataset`.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        concatenate(dataset) {
+          const base = this;
+          let size;
+          if (this.size === Infinity || dataset.size === Infinity) {
+            // If the size of any of these two dataset is infinity, new size is
+            // infinity.
+            size = Infinity;
+          } else if (this.size != null && dataset.size != null) {
+            // If the size of both datasets are known and not infinity, new size is
+            // sum the size of these two datasets.
+            size = this.size + dataset.size;
+          } else {
+            // If neither of these two datasets has infinite size and any of these two
+            // datasets' size is null, the new size is null.
+            size = null;
+          }
+          return datasetFromIteratorFn(
+            async () => (await base.iterator()).concatenate(await dataset.iterator()),
+            size
+          );
+        }
+        /**
+         * Filters this dataset according to `predicate`.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
+         *   .filter(x => x%2 === 0);
+         * await a.forEachAsync(e => console.log(e));
+         * ```
+         *
+         * @param predicate A function mapping a dataset element to a boolean or a
+         * `Promise` for one.
+         *
+         * @returns A `Dataset` of elements for which the predicate was true.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        filter(predicate) {
+          const base = this;
+          let size;
+          if (this.size === Infinity) {
+            // If the size of this dataset is infinity, new size is infinity
+            size = Infinity;
+          } else {
+            // If this dataset has limited elements, new size is null because it might
+            // exhausted randomly.
+            size = null;
+          }
+          return datasetFromIteratorFn(async () => {
+            return (await base.iterator()).filter((x) => dist["tidy"](() => predicate(x)));
+          }, size);
+        }
+        /**
+         * Apply a function to every element of the dataset.
+         *
+         * After the function is applied to a dataset element, any Tensors contained
+         * within that element are disposed.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3]);
+         * await a.forEachAsync(e => console.log(e));
+         * ```
+         *
+         * @param f A function to apply to each dataset element.
+         * @returns A `Promise` that resolves after all elements have been processed.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        async forEachAsync(f) {
+          return (await this.iterator()).forEachAsync(f);
+        }
+        /**
+         * Maps this dataset through a 1-to-1 transform.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3]).map(x => x*x);
+         * await a.forEachAsync(e => console.log(e));
+         * ```
+         *
+         * @param transform A function mapping a dataset element to a transformed
+         *   dataset element.
+         *
+         * @returns A `Dataset` of transformed elements.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        map(transform) {
+          const base = this;
+          return datasetFromIteratorFn(async () => {
+            return (await base.iterator()).map((x) => dist["tidy"](() => transform(x)));
+          }, this.size);
+        }
+        /**
+         * Maps this dataset through an async 1-to-1 transform.
+         *
+         * ```js
+         * const a =
+         *  tf.data.array([1, 2, 3]).mapAsync(x => new Promise(function(resolve){
+         *    setTimeout(() => {
+         *      resolve(x * x);
+         *    }, Math.random()*1000 + 500);
+         *  }));
+         * console.log(await a.toArray());
+         * ```
+         *
+         * @param transform A function mapping a dataset element to a `Promise` for a
+         *   transformed dataset element.  This transform is responsible for disposing
+         *   any intermediate `Tensor`s, i.e. by wrapping its computation in
+         *   `tf.tidy()`; that cannot be automated here (as it is in the synchronous
+         *   `map()` case).
+         *
+         * @returns A `Dataset` of transformed elements.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        mapAsync(transform) {
+          const base = this;
+          return datasetFromIteratorFn(async () => {
+            return (await base.iterator()).mapAsync(transform);
+          }, this.size);
+        }
+        /**
+         *  Creates a `Dataset` that prefetches elements from this dataset.
+         *
+         * @param bufferSize: An integer specifying the number of elements to be
+         *   prefetched.
+         * @returns A `Dataset`.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        prefetch(bufferSize) {
+          if (bufferSize == null) {
+            throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");
+          }
+          const base = this;
+          return datasetFromIteratorFn(
+            async () => (await base.iterator()).prefetch(bufferSize),
+            this.size
+          );
+        }
+        /**
+         * Repeats this dataset `count` times.
+         *
+         * NOTE: If this dataset is a function of global state (e.g. a random number
+         * generator), then different repetitions may produce different elements.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3]).repeat(3);
+         * await a.forEachAsync(e => console.log(e));
+         * ```
+         *
+         * @param count: (Optional) An integer, representing the number of times
+         *   the dataset should be repeated. The default behavior (if `count` is
+         *   `undefined` or negative) is for the dataset be repeated indefinitely.
+         * @returns A `Dataset`.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        repeat(count) {
+          const base = this;
+          let size;
+          if (this.size != null && count > 0) {
+            // If this dataset has size and count is positive, new size is current
+            // size multiply count. This also covers the case that current size is
+            // infinity.
+            size = this.size * count;
+          } else if (count === 0) {
+            // If count is 0, new size is 0.
+            size = 0;
+          } else if (this.size != null && (count === undefined || count < 0)) {
+            // If this dataset has size and count is undefined or negative, the
+            // dataset will be repeated indefinitely and new size is infinity.
+            size = Infinity;
+          } else {
+            // If the size of this dataset is null, the new dataset's size is null.
+            size = null;
+          }
+          return datasetFromIteratorFn(async () => {
+            const iteratorIterator = Object(lazy_iterator["e" /* iteratorFromFunction */])(
+              async () => ({ value: await base.iterator(), done: false })
+            );
+            return Object(lazy_iterator["d" /* iteratorFromConcatenated */])(
+              iteratorIterator.take(count)
+            );
+          }, size);
+        }
+        /**
+         * Creates a `Dataset` that skips `count` initial elements from this dataset.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3, 4, 5, 6]).skip(3);
+         * await a.forEachAsync(e => console.log(e));
+         * ```
+         *
+         * @param count: The number of elements of this dataset that should be skipped
+         *   to form the new dataset.  If `count` is greater than the size of this
+         *   dataset, the new dataset will contain no elements.  If `count`
+         *   is `undefined` or negative, skips the entire dataset.
+         *
+         * @returns A `Dataset`.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        skip(count) {
+          const base = this;
+          let size;
+          if (this.size != null && count >= 0 && this.size >= count) {
+            // If the size of this dataset is greater than count, the new dataset's
+            // size is current size minus skipped size.This also covers the case that
+            // current size is infinity.
+            size = this.size - count;
+          } else if (this.size != null && (this.size < count || count === undefined || count < 0)) {
+            // If the size of this dataset is smaller than count, or count is
+            // undefined or negative, skips the entire dataset and the new size is 0.
+            size = 0;
+          } else {
+            // If the size of this dataset is null, the new dataset's size is null.
+            size = null;
+          }
+          return datasetFromIteratorFn(async () => (await base.iterator()).skip(count), size);
+        }
+        /**
+         * Pseudorandomly shuffles the elements of this dataset. This is done in a
+         * streaming manner, by sampling from a given number of prefetched elements.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3, 4, 5, 6]).shuffle(3);
+         * await a.forEachAsync(e => console.log(e));
+         * ```
+         *
+         * @param bufferSize: An integer specifying the number of elements from this
+         *   dataset from which the new dataset will sample.
+         * @param seed: (Optional) An integer specifying the random seed that will
+         *   be used to create the distribution.
+         * @param reshuffleEachIteration: (Optional) A boolean, which if true
+         *   indicates that the dataset should be pseudorandomly reshuffled each time
+         *   it is iterated over. If false, elements will be returned in the same
+         *   shuffled order on each iteration. (Defaults to `true`.)
+         * @returns A `Dataset`.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        shuffle(bufferSize, seed, reshuffleEachIteration = true) {
+          if (bufferSize == null || bufferSize < 0) {
+            if (this.size == null) {
+              throw new RangeError("`Dataset.shuffle()` requires bufferSize to be specified.");
+            } else {
+              throw new RangeError(
+                "`Dataset.shuffle()` requires bufferSize to be specified.  " +
+                  "If your data fits in main memory (for regular JS objects), " +
+                  "and/or GPU memory (for `tf.Tensor`s), consider setting " +
+                  `bufferSize to the dataset size (${this.size} elements)`
+              );
+            }
+          }
+          const base = this;
+          const random = seedrandom["alea"](seed || dist["util"].now().toString());
+          return datasetFromIteratorFn(async () => {
+            let seed2 = random.int32();
+            if (reshuffleEachIteration) {
+              seed2 += random.int32();
+            }
+            return (await base.iterator()).shuffle(bufferSize, seed2.toString());
+          }, this.size);
+        }
+        /**
+         * Creates a `Dataset` with at most `count` initial elements from this
+         * dataset.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3, 4, 5, 6]).take(3);
+         * await a.forEachAsync(e => console.log(e));
+         * ```
+         *
+         * @param count: The number of elements of this dataset that should be taken
+         *   to form the new dataset.  If `count` is `undefined` or negative, or if
+         *   `count` is greater than the size of this dataset, the new dataset will
+         *   contain all elements of this dataset.
+         * @returns A `Dataset`.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        take(count) {
+          const base = this;
+          let size;
+          if (this.size != null && this.size > count) {
+            // If the size of this dataset is greater than count, the new dataset's
+            // size is count.
+            size = count;
+          } else if (this.size != null && this.size <= count) {
+            // If the size of this dataset is equal or smaller than count, the new
+            // dataset's size is the size of this dataset.
+            size = this.size;
+          } else {
+            // If the size of this dataset is null, the new dataset's size is null.
+            size = null;
+          }
+          return datasetFromIteratorFn(async () => (await base.iterator()).take(count), size);
+        }
+        /**
+         * Collect all elements of this dataset into an array.
+         *
+         * Obviously this will succeed only for small datasets that fit in memory.
+         * Useful for testing and generally should be avoided if possible.
+         *
+         * ```js
+         * const a = tf.data.array([1, 2, 3, 4, 5, 6]);
+         * console.log(await a.toArray());
+         * ```
+         *
+         * @returns A Promise for an array of elements, which will resolve
+         *   when a new stream has been obtained and fully consumed.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        async toArray() {
+          if (this.size === Infinity) {
+            throw new Error("Can not convert infinite data stream to array.");
+          }
+          return (await this.iterator()).toArray();
+        }
+        /**
+         * Collect all elements of this dataset into an array with prefetching 100
+         * elements. This is useful for testing, because the prefetch changes the
+         * order in which the Promises are resolved along the processing pipeline.
+         * This may help expose bugs where results are dependent on the order of
+         * Promise resolution rather than on the logical order of the stream (i.e.,
+         * due to hidden mutable state).
+         *
+         * @returns A Promise for an array of elements, which will resolve
+         *   when a new stream has been obtained and fully consumed.
+         */
+        async toArrayForTest() {
+          if (this.size === Infinity) {
+            throw new Error("Can not convert infinite data stream to array.");
+          }
+          return (await this.iterator()).toArrayForTest();
+        }
+      }
+      // TODO(soergel): deep sharded shuffle, where supported
+      dataset_Dataset.MAX_BUFFER_SIZE = 10000;
+      /**
+       * Create a `Dataset` defined by a provided iterator() function.
+       *
+       * ```js
+       * let i = -1;
+       * const func = () =>
+       *    ++i < 5 ? {value: i, done: false} : {value: null, done: true};
+       * const iter = tf.data.iteratorFromFunction(func);
+       * const ds = tf.data.datasetFromIteratorFn(iter);
+       * await ds.forEachAsync(e => console.log(e));
+       * ```
+       */
+      function datasetFromIteratorFn(iteratorFn, size = null) {
+        return new (class extends dataset_Dataset {
+          constructor() {
+            super(...arguments);
+            this.size = size;
+          }
+          /*
+           * Provide a new stream of elements.  Note this will also start new streams
+           * from any underlying `Dataset`s.
+           */
+          async iterator() {
+            return iteratorFn();
+          }
+        })();
+      }
+      /**
+       * Create a `Dataset` from an array of elements.
+       *
+       * Create a Dataset from an array of objects:
+       * ```js
+       * const a = tf.data.array([{'item': 1}, {'item': 2}, {'item': 3}]);
+       * await a.forEachAsync(e => console.log(e));
+       * ```
+       *
+       * Create a Dataset from an array of numbers:
+       * ```js
+       * const a = tf.data.array([4, 5, 6]);
+       * await a.forEachAsync(e => console.log(e));
+       * ```
+       * @param items An array of elements that will be parsed as items in a dataset.
+       */
+      /** @doc {heading: 'Data', subheading: 'Creation', namespace: 'data'} */
+      function array(items) {
+        return datasetFromIteratorFn(
+          async () => Object(lazy_iterator["f" /* iteratorFromItems */])(items),
+          items.length
+        );
+      }
+      /**
+       * Create a `Dataset` by zipping together an array, dict, or nested
+       * structure of `Dataset`s (and perhaps additional constants).
+       * The underlying datasets must provide elements in a consistent order such that
+       * they correspond.
+       *
+       * The number of elements in the resulting dataset is the same as the size of
+       * the smallest dataset in datasets.
+       *
+       * The nested structure of the `datasets` argument determines the
+       * structure of elements in the resulting iterator.
+       *
+       * Note this means that, given an array of two datasets that produce dict
+       * elements, the result is a dataset that produces elements that are arrays
+       * of two dicts:
+       *
+       * Zip an array of datasets:
+       * ```js
+       * console.log('Zip two datasets of objects:');
+       * const ds1 = tf.data.array([{a: 1}, {a: 2}, {a: 3}]);
+       * const ds2 = tf.data.array([{b: 4}, {b: 5}, {b: 6}]);
+       * const ds3 = tf.data.zip([ds1, ds2]);
+       * await ds3.forEachAsync(e => console.log(JSON.stringify(e)));
+       *
+       * // If the goal is to merge the dicts in order to produce elements like
+       * // {a: ..., b: ...}, this requires a second step such as:
+       * console.log('Merge the objects:');
+       * const ds4 = ds3.map(x => {return {a: x[0].a, b: x[1].b}});
+       * await ds4.forEachAsync(e => console.log(e));
+       * ```
+       *
+       * Zip a dict of datasets:
+       * ```js
+       * const a = tf.data.array([{a: 1}, {a: 2}, {a: 3}]);
+       * const b = tf.data.array([{b: 4}, {b: 5}, {b: 6}]);
+       * const c = tf.data.zip({c: a, d: b});
+       * await c.forEachAsync(e => console.log(JSON.stringify(e)));
+       * ```
+       */
+      /** @doc {heading: 'Data', subheading: 'Operations', namespace: 'data'} */
+      function zip(datasets) {
+        // manually type-check the argument for JS users
+        if (!Object(deep_map["e" /* isIterable */])(datasets)) {
+          throw new Error("The argument to zip() must be an object or array.");
+        }
+        let size;
+        if (Array.isArray(datasets)) {
+          for (let i = 0; i < datasets.length; i++) {
+            size = size == null ? datasets[i].size : Math.min(size, datasets[i].size);
+          }
+        } else if (datasets instanceof Object) {
+          for (const ds in datasets) {
+            size = size == null ? datasets[ds].size : Math.min(size, datasets[ds].size);
+          }
+        }
+        return datasetFromIteratorFn(async () => {
+          const streams = await Object(deep_map["c" /* deepMapAndAwaitAll */])(datasets, (d) => {
+            if (d instanceof dataset_Dataset) {
+              return { value: d.iterator(), recurse: false };
+            } else if (Object(deep_map["e" /* isIterable */])(d)) {
+              return { value: null, recurse: true };
+            } else {
+              throw new Error(
+                "Leaves of the structure passed to zip() must be Datasets, " + "not primitives."
+              );
+            }
+          });
+          return Object(lazy_iterator["g" /* iteratorFromZipped */])(
+            streams,
+            lazy_iterator["c" /* ZipMismatchMode */].SHORTEST
+          );
+        }, size);
+      }
+      /**
+       * A zip function for use with deepZip, passed via the columnMajorBatch call.
+       *
+       * Accepts an array of identically-structured nested elements and either batches
+       * them (if they are primitives, numeric arrays, or Tensors) or requests
+       * recursion (if not).
+       */
+      // tslint:disable-next-line:no-any
+      function deepBatchConcat(rows) {
+        if (rows === null) {
+          return null;
+        }
+        // use the first item to decide whether to recurse or batch here.
+        const exampleRow = rows[0];
+        if (Object(deep_map["a" /* canTensorify */])(exampleRow)) {
+          // rows is an array of primitives, Tensors, or arrays.  Batch them.
+          const value = batchConcat(rows);
+          return { value, recurse: false };
+        }
+        // the example row is an object, so recurse into it.
+        return { value: null, recurse: true };
+      }
+      /**
+       * Assembles a list of same-shaped numbers, number arrays, or Tensors
+       * into a single new Tensor where axis 0 is the batch dimension.
+       */
+      function batchConcat(arrays) {
+        if (arrays.length === 0) {
+          // We can't return an empty Tensor because we don't know the element shape.
+          throw new Error("Can't make a batch of zero elements.");
+        }
+        if (arrays[0] instanceof dist["Tensor"]) {
+          // Input is an array of Tensors
+          return dist["stack"](arrays);
+        } else {
+          // Input is a possibly-nested array of numbers.
+          return dist["tensor"](arrays);
+        }
+      }
+      //# sourceMappingURL=dataset.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/datasets/text_line_dataset.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      /**
+       * Represents a potentially large collection of text lines.
+       *
+       * The results are not batched.
+       */
+      class text_line_dataset_TextLineDataset extends dataset_Dataset {
+        /**
+         * Create a `TextLineDataset`.
+         *
+         * @param input A `DataSource` providing a chunked, UTF8-encoded byte stream.
+         */
+        constructor(input) {
+          super();
+          this.input = input;
+        }
+        async iterator() {
+          const inputIterator = await this.input.iterator();
+          const utf8Iterator = inputIterator.decodeUTF8();
+          const lineIterator = utf8Iterator.split("\n").map((line) => {
+            // Windows/DOS format text file has extra line breaker at the end of line.
+            if (line.endsWith("\r")) {
+              line = line.slice(0, -1);
+            }
+            return line;
+          });
+          return lineIterator;
+        }
+      }
+      //# sourceMappingURL=text_line_dataset.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/datasets/csv_dataset.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      const CODE_QUOTE = '"';
+      const STATE_OUT = Symbol("out");
+      const STATE_FIELD = Symbol("field");
+      const STATE_QUOTE = Symbol("quote");
+      const STATE_QUOTE_AFTER_QUOTE = Symbol("quoteafterquote");
+      const STATE_WITHIN_QUOTE_IN_QUOTE = Symbol("quoteinquote");
+      /**
+       * Represents a potentially large collection of delimited text records.
+       *
+       * The produced `TensorContainer`s each contain one key-value pair for
+       * every column of the table.  When a field is empty in the incoming data, the
+       * resulting value is `undefined`, or throw error if it is required.  Values
+       * that can be parsed as numbers are emitted as type `number`, other values
+       * are parsed as `string`.
+       *
+       * The results are not batched.
+       */
+      /** @doc {heading: 'Data', subheading: 'Classes', namespace: 'data'} */
+      class csv_dataset_CSVDataset extends dataset_Dataset {
+        /**
+         * Create a `CSVDataset`.
+         *
+         * @param input A `DataSource` providing a chunked, UTF8-encoded byte stream.
+         * @param csvConfig (Optional) A CSVConfig object that contains configurations
+         *     of reading and decoding from CSV file(s).
+         *
+         *     hasHeader: (Optional) A boolean value that indicates whether the first
+         *     row of provided CSV file is a header line with column names, and should
+         *     not be included in the data. Defaults to `true`.
+         *
+         *     columnNames: (Optional) A list of strings that corresponds to
+         *     the CSV column names, in order. If provided, it ignores the column
+         *     names inferred from the header row. If not provided, infers the column
+         *     names from the first row of the records. If hasHeader is false and
+         *     columnNames is not provided, this method throws an error.
+         *
+         *     columnConfigs: (Optional) A dictionary whose key is column names, value
+         *     is an object stating if this column is required, column's data type,
+         *     default value, and if this column is label. If provided, keys must
+         *     correspond to names provided in columnNames or inferred from the file
+         *     header lines. If isLabel is true any column, returns an array of two
+         *     items: the first item is a dict of features key/value pairs, the second
+         *     item is a dict of labels key/value pairs. If no feature is marked as
+         *     label, returns a dict of features only.
+         *
+         *     configuredColumnsOnly (Optional) If true, only columns provided in
+         *     columnConfigs will be parsed and provided during iteration.
+         *
+         *     delimiter (Optional) The string used to parse each line of the input
+         *     file. Defaults to `,`.
+         */
+        constructor(input, csvConfig) {
+          super();
+          this.input = input;
+          this.hasHeader = true;
+          this.fullColumnNames = null;
+          this.columnNamesValidated = false;
+          this.columnConfigs = null;
+          this.configuredColumnsOnly = false;
+          this.delimiter = ",";
+          this.delimWhitespace = false;
+          this.base = new text_line_dataset_TextLineDataset(input);
+          if (!csvConfig) {
+            csvConfig = {};
+          }
+          this.hasHeader = csvConfig.hasHeader === false ? false : true;
+          this.fullColumnNames = csvConfig.columnNames;
+          this.columnConfigs = csvConfig.columnConfigs;
+          this.configuredColumnsOnly = csvConfig.configuredColumnsOnly;
+          if (csvConfig.delimWhitespace) {
+            dist["util"].assert(
+              csvConfig.delimiter == null,
+              () => "Delimiter should not be provided when delimWhitespace is true."
+            );
+            this.delimWhitespace = true;
+            this.delimiter = " ";
+          } else {
+            this.delimiter = csvConfig.delimiter ? csvConfig.delimiter : ",";
+          }
+        }
+        /**
+         * Returns column names of the csv dataset. If `configuredColumnsOnly` is
+         * true, return column names in `columnConfigs`. If `configuredColumnsOnly` is
+         * false and `columnNames` is provided, `columnNames`. If
+         * `configuredColumnsOnly` is false and `columnNames` is not provided, return
+         * all column names parsed from the csv file. For example usage please go to
+         * `tf.data.csv`.
+         */
+        /** @doc {heading: 'Data', subheading: 'Classes'} */
+        async columnNames() {
+          if (!this.columnNamesValidated) {
+            await this.setColumnNames();
+          }
+          return this.configuredColumnsOnly
+            ? Object.keys(this.columnConfigs)
+            : this.fullColumnNames;
+        }
+        /* 1) If `columnNames` is provided as string[], use this string[] as output
+         * keys in corresponding order. The length must match the number of inferred
+         * columns if `hasHeader` is true .
+         * 2) If `columnNames` is not provided, parse header line as `columnNames` if
+         * hasHeader is true. If `hasHeader` is false, throw an error.
+         * 3) If `columnConfigs` is provided, all the keys in `columnConfigs` must
+         * exist in parsed `columnNames`.
+         */
+        async setColumnNames() {
+          const columnNamesFromFile = await this.maybeReadHeaderLine();
+          if (!this.fullColumnNames && !columnNamesFromFile) {
+            // Throw an error if columnNames is not provided and no header line.
+            throw new Error("Column names must be provided if there is no header line.");
+          } else if (this.fullColumnNames && columnNamesFromFile) {
+            // Check provided columnNames match header line.
+            dist["util"].assert(
+              columnNamesFromFile.length === this.fullColumnNames.length,
+              () =>
+                "The length of provided columnNames (" +
+                this.fullColumnNames.length.toString() +
+                ") does not match the length of the header line read from " +
+                "file (" +
+                columnNamesFromFile.length.toString() +
+                ")."
+            );
+          }
+          if (!this.fullColumnNames) {
+            this.fullColumnNames = columnNamesFromFile;
+          }
+          // Check if there are duplicate column names.
+          const counts = this.fullColumnNames.reduce((countAcc, name) => {
+            countAcc[name] = countAcc[name] + 1 || 1;
+            return countAcc;
+          }, {});
+          const duplicateNames = Object.keys(counts).filter((name) => counts[name] > 1);
+          dist["util"].assert(
+            duplicateNames.length === 0,
+            () => "Duplicate column names found: " + duplicateNames.toString()
+          );
+          // Check if keys in columnConfigs match columnNames.
+          if (this.columnConfigs) {
+            for (const key of Object.keys(this.columnConfigs)) {
+              const index = this.fullColumnNames.indexOf(key);
+              if (index === -1) {
+                throw new Error(
+                  'The key "' +
+                    key +
+                    '" provided in columnConfigs does not match any of the column ' +
+                    "names (" +
+                    this.fullColumnNames.toString() +
+                    ")."
+                );
+              }
+            }
+          }
+          this.columnNamesValidated = true;
+        }
+        async maybeReadHeaderLine() {
+          if (this.hasHeader) {
+            const iter = await this.base.iterator();
+            const firstElement = await iter.next();
+            if (firstElement.done) {
+              throw new Error("No data was found for CSV parsing.");
+            }
+            const firstLine = firstElement.value;
+            const headers = this.parseRow(firstLine, false);
+            return headers;
+          } else {
+            return null;
+          }
+        }
+        async iterator() {
+          if (!this.columnNamesValidated) {
+            await this.setColumnNames();
+          }
+          let lines = await this.base.iterator();
+          if (this.hasHeader) {
+            // We previously read the first line to get the columnNames.
+            // Now that we're providing data, skip it.
+            lines = lines.skip(1);
+          }
+          return lines.map((x) => this.makeDataElement(x));
+        }
+        makeDataElement(line) {
+          const values = this.parseRow(line);
+          const features = {};
+          const labels = {};
+          for (let i = 0; i < this.fullColumnNames.length; i++) {
+            const key = this.fullColumnNames[i];
+            const config = this.columnConfigs ? this.columnConfigs[key] : null;
+            if (this.configuredColumnsOnly && !config) {
+              // This column is not selected.
+              continue;
+            } else {
+              const value = values[i];
+              let parsedValue = null;
+              if (value === "") {
+                // If default value is provided, use it. If default value is not
+                // provided, set as undefined.
+                if (config && config.default !== undefined) {
+                  parsedValue = config.default;
+                } else if (config && (config.required || config.isLabel)) {
+                  throw new Error(`Required column ${key} is empty in this line: ${line}`);
+                } else {
+                  parsedValue = undefined;
+                }
+              } else {
+                // A value is present, so parse it based on type
+                const valueAsNum = Number(value);
+                if (isNaN(valueAsNum)) {
+                  // The value is a string and this column is declared as boolean
+                  // in config, parse it as boolean.
+                  if (config && config.dtype === "bool") {
+                    parsedValue = this.getBoolean(value);
+                  } else {
+                    // Set value as string
+                    parsedValue = value;
+                  }
+                } else if (!config || !config.dtype) {
+                  // If this value is a number and no type config is provided, return
+                  // it as number.
+                  parsedValue = valueAsNum;
+                } else {
+                  // If this value is a number and data type is provided, parse it
+                  // according to provided data type.
+                  switch (config.dtype) {
+                    case "float32":
+                      parsedValue = valueAsNum;
+                      break;
+                    case "int32":
+                      parsedValue = Math.floor(valueAsNum);
+                      break;
+                    case "bool":
+                      parsedValue = this.getBoolean(value);
+                      break;
+                    default:
+                      parsedValue = valueAsNum;
+                  }
+                }
+              }
+              // Check if this column is label.
+              config && config.isLabel
+                ? (labels[key] = parsedValue)
+                : (features[key] = parsedValue);
+            }
+          }
+          // If label exists, return an object of features and labels as {xs:features,
+          // ys:labels}, otherwise return features only.
+          if (Object.keys(labels).length === 0) {
+            return features;
+          } else {
+            return { xs: features, ys: labels };
+          }
+        }
+        getBoolean(value) {
+          if (value === "1" || value.toLowerCase() === "true") {
+            return 1;
+          } else {
+            return 0;
+          }
+        }
+        // adapted from https://beta.observablehq.com/@mbostock/streaming-csv
+        parseRow(line, validateElementCount = true) {
+          const result = [];
+          let readOffset = 0;
+          const readLength = line.length;
+          let currentState = STATE_OUT;
+          // Goes through the line to parse quote.
+          for (let i = 0; i < readLength; i++) {
+            switch (currentState) {
+              // Before enter a new field
+              case STATE_OUT:
+                switch (line.charAt(i)) {
+                  // Enter a quoted field
+                  case CODE_QUOTE:
+                    readOffset = i + 1;
+                    currentState = STATE_QUOTE;
+                    break;
+                  // Read an empty field
+                  case this.delimiter:
+                    readOffset = i + 1;
+                    // If delimiter is white space and configured to collapse
+                    // multiple white spaces, ignore this white space.
+                    if (this.delimiter === " " && this.delimWhitespace) {
+                      break;
+                    }
+                    result.push("");
+                    currentState = STATE_OUT;
+                    break;
+                  // Enter an unquoted field
+                  default:
+                    currentState = STATE_FIELD;
+                    readOffset = i;
+                    break;
+                }
+                break;
+              // In an unquoted field
+              case STATE_FIELD:
+                switch (line.charAt(i)) {
+                  // Exit an unquoted field, add it to result
+                  case this.delimiter:
+                    result.push(line.substring(readOffset, i));
+                    currentState = STATE_OUT;
+                    readOffset = i + 1;
+                    break;
+                  default:
+                }
+                break;
+              // In a quoted field
+              case STATE_QUOTE:
+                switch (line.charAt(i)) {
+                  // Read a quote after a quote
+                  case CODE_QUOTE:
+                    currentState = STATE_QUOTE_AFTER_QUOTE;
+                    break;
+                  default:
+                }
+                break;
+              // This state means it's right after a second quote in a field
+              case STATE_QUOTE_AFTER_QUOTE:
+                switch (line.charAt(i)) {
+                  // Finished a quoted field
+                  case this.delimiter:
+                    result.push(line.substring(readOffset, i - 1));
+                    currentState = STATE_OUT;
+                    readOffset = i + 1;
+                    break;
+                  // Finished a quoted part in a quoted field
+                  case CODE_QUOTE:
+                    currentState = STATE_QUOTE;
+                    break;
+                  // In a quoted part in a quoted field
+                  default:
+                    currentState = STATE_WITHIN_QUOTE_IN_QUOTE;
+                    break;
+                }
+                break;
+              case STATE_WITHIN_QUOTE_IN_QUOTE:
+                switch (line.charAt(i)) {
+                  // Exit a quoted part in a quoted field
+                  case CODE_QUOTE:
+                    currentState = STATE_QUOTE;
+                    break;
+                  default:
+                }
+                break;
+              default:
+            }
+          }
+          // Adds last item based on if it is quoted.
+          if (currentState === STATE_QUOTE_AFTER_QUOTE) {
+            result.push(line.substring(readOffset, readLength - 1));
+          } else {
+            result.push(line.substring(readOffset));
+          }
+          // Check if each row has the same number of elements as column names.
+          if (validateElementCount && result.length !== this.fullColumnNames.length) {
+            throw new Error(
+              `Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${result}`
+            );
+          }
+          return result;
+        }
+      }
+      // TODO(soergel): add more basic datasets for parity with tf.data
+      // tf.data.FixedLengthRecordDataset()
+      // tf.data.TFRecordDataset()
+      //# sourceMappingURL=csv_dataset.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/microphone_iterator.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      /**
+       * Provide a stream of tensors from microphone audio stream. The tensors are
+       * representing audio data as frequency-domain spectrogram generated with
+       * browser's native FFT. Tensors representing time-domain waveform is available
+       * based on configuration. Only works in browser environment.
+       */
+      class microphone_iterator_MicrophoneIterator extends lazy_iterator["a" /* LazyIterator */] {
+        constructor(microphoneConfig) {
+          super();
+          this.microphoneConfig = microphoneConfig;
+          this.isClosed = false;
+          this.fftSize = microphoneConfig.fftSize || 1024;
+          const fftSizeLog2 = Math.log2(this.fftSize);
+          if (
+            this.fftSize < 0 ||
+            fftSizeLog2 < 4 ||
+            fftSizeLog2 > 14 ||
+            !Number.isInteger(fftSizeLog2)
+          ) {
+            throw new Error(
+              `Invalid fftSize: it must be a power of 2 between ` +
+                `2 to 4 and 2 to 14, but got ${this.fftSize}`
+            );
+          }
+          this.numFrames = microphoneConfig.numFramesPerSpectrogram || 43;
+          this.sampleRateHz = microphoneConfig.sampleRateHz;
+          this.columnTruncateLength = microphoneConfig.columnTruncateLength || this.fftSize;
+          this.audioTrackConstraints = microphoneConfig.audioTrackConstraints;
+          this.smoothingTimeConstant = microphoneConfig.smoothingTimeConstant || 0;
+          this.includeSpectrogram = microphoneConfig.includeSpectrogram === false ? false : true;
+          this.includeWaveform = microphoneConfig.includeWaveform === true ? true : false;
+          if (!this.includeSpectrogram && !this.includeWaveform) {
+            throw new Error(
+              "Both includeSpectrogram and includeWaveform are false. " +
+                "At least one type of data should be returned."
+            );
+          }
+        }
+        summary() {
+          return `microphone`;
+        }
+        // Construct a MicrophoneIterator and start the audio stream.
+        static async create(microphoneConfig = {}) {
+          if (Object(dist["env"])().get("IS_NODE")) {
+            throw new Error("microphone API is only supported in browser environment.");
+          }
+          const microphoneIterator = new microphone_iterator_MicrophoneIterator(microphoneConfig);
+          // Call async function start() to initialize the audio stream.
+          await microphoneIterator.start();
+          return microphoneIterator;
+        }
+        // Start the audio stream and FFT.
+        async start() {
+          try {
+            this.stream = await navigator.mediaDevices.getUserMedia({
+              audio: this.audioTrackConstraints == null ? true : this.audioTrackConstraints,
+              video: false,
+            });
+          } catch (e) {
+            throw new Error(`Error thrown while initializing video stream: ${e.message}`);
+          }
+          if (!this.stream) {
+            throw new Error("Could not obtain audio from microphone.");
+          }
+          const ctxConstructor =
+            // tslint:disable-next-line:no-any
+            window.AudioContext || window.webkitAudioContext;
+          this.audioContext = new ctxConstructor();
+          if (!this.sampleRateHz) {
+            // If sample rate is not provided, use the available sample rate on
+            // device.
+            this.sampleRateHz = this.audioContext.sampleRate;
+          } else if (this.audioContext.sampleRate !== this.sampleRateHz) {
+            throw new Error(
+              `Mismatch in sampling rate: ` +
+                `Expected: ${this.sampleRateHz}; ` +
+                `Actual: ${this.audioContext.sampleRate}`
+            );
+          }
+          const streamSource = this.audioContext.createMediaStreamSource(this.stream);
+          this.analyser = this.audioContext.createAnalyser();
+          this.analyser.fftSize = this.fftSize * 2;
+          this.analyser.smoothingTimeConstant = this.smoothingTimeConstant;
+          streamSource.connect(this.analyser);
+          this.freqData = new Float32Array(this.fftSize);
+          this.timeData = new Float32Array(this.fftSize);
+          return;
+        }
+        async next() {
+          if (this.isClosed) {
+            return { value: null, done: true };
+          }
+          let spectrogramTensor;
+          let waveformTensor;
+          const audioDataQueue = await this.getAudioData();
+          if (this.includeSpectrogram) {
+            const freqData = this.flattenQueue(audioDataQueue.freqDataQueue);
+            spectrogramTensor = this.getTensorFromAudioDataArray(freqData, [
+              this.numFrames,
+              this.columnTruncateLength,
+              1,
+            ]);
+          }
+          if (this.includeWaveform) {
+            const timeData = this.flattenQueue(audioDataQueue.timeDataQueue);
+            waveformTensor = this.getTensorFromAudioDataArray(timeData, [
+              this.numFrames * this.fftSize,
+              1,
+            ]);
+          }
+          return {
+            value: { spectrogram: spectrogramTensor, waveform: waveformTensor },
+            done: false,
+          };
+        }
+        // Capture one result from the audio stream, and extract the value from
+        // iterator.next() result.
+        async capture() {
+          return (await this.next()).value;
+        }
+        async getAudioData() {
+          const freqDataQueue = [];
+          const timeDataQueue = [];
+          let currentFrames = 0;
+          return new Promise((resolve) => {
+            const intervalID = setInterval(() => {
+              if (this.includeSpectrogram) {
+                this.analyser.getFloatFrequencyData(this.freqData);
+                // If the audio stream is initializing, return empty queue.
+                if (this.freqData[0] === -Infinity) {
+                  resolve({ freqDataQueue, timeDataQueue });
+                }
+                freqDataQueue.push(this.freqData.slice(0, this.columnTruncateLength));
+              }
+              if (this.includeWaveform) {
+                this.analyser.getFloatTimeDomainData(this.timeData);
+                timeDataQueue.push(this.timeData.slice());
+              }
+              // Clean interval and return when all frames have been collected
+              if (++currentFrames === this.numFrames) {
+                clearInterval(intervalID);
+                resolve({ freqDataQueue, timeDataQueue });
+              }
+            }, (this.fftSize / this.sampleRateHz) * 1e3);
+          });
+        }
+        // Stop the audio stream and pause the iterator.
+        stop() {
+          if (!this.isClosed) {
+            this.isClosed = true;
+            this.analyser.disconnect();
+            this.audioContext.close();
+            if (this.stream != null && this.stream.getTracks().length > 0) {
+              this.stream.getTracks()[0].stop();
+            }
+          }
+        }
+        // Override toArray() function to prevent collecting.
+        toArray() {
+          throw new Error("Can not convert infinite audio stream to array.");
+        }
+        // Return audio sampling rate in Hz
+        getSampleRate() {
+          return this.sampleRateHz;
+        }
+        flattenQueue(queue) {
+          const frameSize = queue[0].length;
+          const freqData = new Float32Array(queue.length * frameSize);
+          queue.forEach((data, i) => freqData.set(data, i * frameSize));
+          return freqData;
+        }
+        getTensorFromAudioDataArray(freqData, shape) {
+          const vals = new Float32Array(dist["util"].sizeFromShape(shape));
+          // If the data is less than the output shape, the rest is padded with zeros.
+          vals.set(freqData, vals.length - freqData.length);
+          return Object(dist["tensor"])(vals, shape);
+        }
+      }
+      //# sourceMappingURL=microphone_iterator.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/webcam_iterator.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      /**
+       * Provide a stream of image tensors from webcam video stream. Only works in
+       * browser environment.
+       */
+      class webcam_iterator_WebcamIterator extends lazy_iterator["a" /* LazyIterator */] {
+        constructor(webcamVideoElement, webcamConfig) {
+          super();
+          this.webcamVideoElement = webcamVideoElement;
+          this.webcamConfig = webcamConfig;
+          this.isClosed = true;
+          this.resize = false;
+          if (this.needToResize()) {
+            this.resize = true;
+            this.cropSize = [this.webcamConfig.resizeHeight, this.webcamConfig.resizeWidth];
+            this.cropBoxInd = Object(dist["tensor1d"])([0], "int32");
+            if (this.webcamConfig.centerCrop) {
+              // Calculate the box based on resizing shape.
+              const widthCroppingRatio =
+                (this.webcamConfig.resizeWidth * 1.0) / this.webcamVideoElement.width;
+              const heightCroppingRatio =
+                (this.webcamConfig.resizeHeight * 1.0) / this.webcamVideoElement.height;
+              const widthCropStart = (1 - widthCroppingRatio) / 2;
+              const heightCropStart = (1 - heightCroppingRatio) / 2;
+              const widthCropEnd = widthCropStart + widthCroppingRatio;
+              const heightCropEnd = heightCroppingRatio + heightCropStart;
+              this.cropBox = Object(dist["tensor2d"])(
+                [heightCropStart, widthCropStart, heightCropEnd, widthCropEnd],
+                [1, 4]
+              );
+            } else {
+              this.cropBox = Object(dist["tensor2d"])([0, 0, 1, 1], [1, 4]);
+            }
+          }
+        }
+        summary() {
+          return `webcam`;
+        }
+        // Construct a WebcamIterator and start it's video stream.
+        static async create(webcamVideoElement, webcamConfig = {}) {
+          if (Object(dist["env"])().get("IS_NODE")) {
+            throw new Error("tf.data.webcam is only supported in browser environment.");
+          }
+          if (!webcamVideoElement) {
+            // If webcam video element is not provided, create a hidden video element
+            // with provided width and height.
+            webcamVideoElement = document.createElement("video");
+            if (!webcamConfig.resizeWidth || !webcamConfig.resizeHeight) {
+              throw new Error(
+                "Please provide webcam video element, or resizeWidth and " +
+                  "resizeHeight to create a hidden video element."
+              );
+            }
+            webcamVideoElement.width = webcamConfig.resizeWidth;
+            webcamVideoElement.height = webcamConfig.resizeHeight;
+          }
+          const webcamIterator = new webcam_iterator_WebcamIterator(
+            webcamVideoElement,
+            webcamConfig
+          );
+          // Call async function to initialize the video stream.
+          await webcamIterator.start();
+          return webcamIterator;
+        }
+        // Async function to start video stream.
+        async start() {
+          if (this.webcamConfig.facingMode) {
+            dist["util"].assert(
+              this.webcamConfig.facingMode === "user" ||
+                this.webcamConfig.facingMode === "environment",
+              () =>
+                `Invalid webcam facing mode: ${this.webcamConfig.facingMode}. ` +
+                `Please provide 'user' or 'environment'`
+            );
+          }
+          try {
+            this.stream = await navigator.mediaDevices.getUserMedia({
+              video: {
+                deviceId: this.webcamConfig.deviceId,
+                facingMode: this.webcamConfig.facingMode ? this.webcamConfig.facingMode : "user",
+                width: this.webcamVideoElement.width,
+                height: this.webcamVideoElement.height,
+              },
+            });
+          } catch (e) {
+            // Modify the error message but leave the stack trace intact
+            e.message = `Error thrown while initializing video stream: ${e.message}`;
+            throw e;
+          }
+          if (!this.stream) {
+            throw new Error("Could not obtain video from webcam.");
+          }
+          // Older browsers may not have srcObject
+          try {
+            this.webcamVideoElement.srcObject = this.stream;
+          } catch (error) {
+            console.log(error);
+            this.webcamVideoElement.src = window.URL.createObjectURL(this.stream);
+          }
+          // Start the webcam video stream
+          this.webcamVideoElement.play();
+          this.isClosed = false;
+          return new Promise((resolve) => {
+            // Add event listener to make sure the webcam has been fully initialized.
+            this.webcamVideoElement.onloadedmetadata = () => {
+              resolve();
+            };
+          });
+        }
+        async next() {
+          if (this.isClosed) {
+            return { value: null, done: true };
+          }
+          let img;
+          try {
+            img = dist["browser"].fromPixels(this.webcamVideoElement);
+          } catch (e) {
+            throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(e)}`);
+          }
+          if (this.resize) {
+            try {
+              return { value: this.cropAndResizeFrame(img), done: false };
+            } catch (e) {
+              throw new Error(`Error thrown cropping the video: ${e.message}`);
+            } finally {
+              img.dispose();
+            }
+          } else {
+            return { value: img, done: false };
+          }
+        }
+        needToResize() {
+          // If resizeWidth and resizeHeight are provided, and different from the
+          // width and height of original HTMLVideoElement, then resizing and cropping
+          // is required.
+          if (
+            this.webcamConfig.resizeWidth &&
+            this.webcamConfig.resizeHeight &&
+            (this.webcamVideoElement.width !== this.webcamConfig.resizeWidth ||
+              this.webcamVideoElement.height !== this.webcamConfig.resizeHeight)
+          ) {
+            return true;
+          }
+          return false;
+        }
+        // Cropping and resizing each frame based on config
+        cropAndResizeFrame(img) {
+          return Object(dist["tidy"])(() => {
+            const expandedImage = img.toFloat().expandDims(0);
+            let resizedImage;
+            resizedImage = dist["image"].cropAndResize(
+              expandedImage,
+              this.cropBox,
+              this.cropBoxInd,
+              this.cropSize,
+              "bilinear"
+            );
+            // Extract image from batch cropping.
+            const shape = resizedImage.shape;
+            return resizedImage.reshape(shape.slice(1));
+          });
+        }
+        // Capture one frame from the video stream, and extract the value from
+        // iterator.next() result.
+        async capture() {
+          return (await this.next()).value;
+        }
+        // Stop the video stream and pause webcam iterator.
+        stop() {
+          const tracks = this.stream.getTracks();
+          tracks.forEach((track) => track.stop());
+          try {
+            this.webcamVideoElement.srcObject = null;
+          } catch (error) {
+            console.log(error);
+            this.webcamVideoElement.src = null;
+          }
+          this.isClosed = true;
+        }
+        // Override toArray() function to prevent collecting.
+        toArray() {
+          throw new Error("Can not convert infinite video stream to array.");
+        }
+      }
+      //# sourceMappingURL=webcam_iterator.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/datasource.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+      /**
+       * Represents a data source readable as a stream of binary data chunks.
+       *
+       * Because `Dataset`s can be read repeatedly (via `Dataset.iterator()`), this
+       * provides a means to repeatedly create streams from the underlying data
+       * sources.
+       */
+      class DataSource {}
+      // TODO(soergel): consider convenience factory functions here
+      // in combination with chainable source->dataset above, e.g.:
+      // tf.data.url(...).asCsvDataset().shuffle().batch()
+      //# sourceMappingURL=datasource.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/byte_chunk_iterator.js
+      var byte_chunk_iterator = __webpack_require__(57);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/file_chunk_iterator.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+      // inspired by https://github.com/maxogden/filereader-stream
+
+      /**
+       * Provide a stream of chunks from a File, Blob, or Uint8Array.
+       * @param file The source File, Blob or Uint8Array.
+       * @param options Optional settings controlling file reading.
+       * @returns a lazy Iterator of Uint8Arrays containing sequential chunks of the
+       *   input File, Blob or Uint8Array.
+       */
+      class file_chunk_iterator_FileChunkIterator extends byte_chunk_iterator[
+        "a" /* ByteChunkIterator */
+      ] {
+        constructor(file, options = {}) {
+          super();
+          this.file = file;
+          this.options = options;
+          dist["util"].assert(
+            file instanceof Uint8Array ||
+              (Object(dist["env"])().get("IS_BROWSER")
+                ? file instanceof File || file instanceof Blob
+                : false),
+            () => "FileChunkIterator only supports File, Blob and Uint8Array " + "right now."
+          );
+          this.offset = options.offset || 0;
+          // default 1MB chunk has tolerable perf on large files
+          this.chunkSize = options.chunkSize || 1024 * 1024;
+        }
+        summary() {
+          return `FileChunks ${this.file}`;
+        }
+        async next() {
+          if (
+            this.offset >= (this.file instanceof Uint8Array ? this.file.byteLength : this.file.size)
+          ) {
+            return { value: null, done: true };
+          }
+          const chunk = new Promise((resolve, reject) => {
+            const end = this.offset + this.chunkSize;
+            if (this.file instanceof Uint8Array) {
+              // Note if end > this.uint8Array.byteLength, we just get a small last
+              // chunk.
+              resolve(new Uint8Array(this.file.slice(this.offset, end)));
+            } else {
+              // This branch assumes that this.file type is File or Blob, which
+              // means it is in the browser environment.
+              // TODO(soergel): is this a performance issue?
+              const fileReader = new FileReader();
+              fileReader.onload = (event) => {
+                let data = fileReader.result;
+                // Not sure we can trust the return type of
+                // FileReader.readAsArrayBuffer See e.g.
+                // https://github.com/node-file-api/FileReader/issues/2
+                if (data instanceof ArrayBuffer) {
+                  data = new Uint8Array(data);
+                }
+                if (!(data instanceof Uint8Array)) {
+                  return reject(new TypeError("FileReader returned unknown type."));
+                }
+                resolve(data);
+              };
+              fileReader.onabort = (event) => {
+                return reject(new Error("Aborted"));
+              };
+              fileReader.onerror = (event) => {
+                return reject(new Error(event.type));
+              };
+              // TODO(soergel): better handle onabort, onerror
+              // Note if end > this.file.size, we just get a small last chunk.
+              const slice = this.file.slice(this.offset, end);
+              // We can't use readAsText here (even if we know the file is text)
+              // because the slice boundary may fall within a multi-byte character.
+              fileReader.readAsArrayBuffer(slice);
+            }
+            this.offset = end;
+          });
+          return { value: await chunk, done: false };
+        }
+      }
+      //# sourceMappingURL=file_chunk_iterator.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/iterators/url_chunk_iterator.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      /**
+       * Provide a stream of chunks from a URL.
+       *
+       * Note this class first downloads the entire file into memory before providing
+       * the first element from the stream.  This is because the Fetch API does not
+       * yet reliably provide a reader stream for the response body.
+       */
+      async function urlChunkIterator(url, options = {}) {
+        let urlString;
+        let requestInit;
+        if (typeof url === "string") {
+          urlString = url;
+        } else {
+          urlString = url.url;
+          requestInit = getRequestInitFromRequest(url);
+        }
+        const response = await dist["util"].fetch(urlString, requestInit);
+        if (response.ok) {
+          const uint8Array = new Uint8Array(await response.arrayBuffer());
+          return new file_chunk_iterator_FileChunkIterator(uint8Array, options);
+        } else {
+          throw new Error(response.statusText);
+        }
+      }
+      // Generate RequestInit from Request to match tf.util.fetch signature.
+      const getRequestInitFromRequest = (request) => {
+        const init = {
+          method: request.method,
+          headers: request.headers,
+          body: request.body,
+          mode: request.mode,
+          credentials: request.credentials,
+          cache: request.cache,
+          redirect: request.redirect,
+          referrer: request.referrer,
+          integrity: request.integrity,
+        };
+        return init;
+      };
+      //# sourceMappingURL=url_chunk_iterator.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/util/source_util.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+      // Skip tslint any type check cause this method is aiming to check type of
+      // input.
+      // tslint:disable-next-line:no-any
+      function isLocalPath(source) {
+        return typeof source === "string" && source.substr(0, 7) === "file://";
+      }
+      //# sourceMappingURL=source_util.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/sources/file_data_source.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      /**
+       * Represents a file, blob, or Uint8Array readable as a stream of binary data
+       * chunks.
+       */
+      class file_data_source_FileDataSource extends DataSource {
+        /**
+         * Create a `FileDataSource`.
+         *
+         * @param input Local file path, or `File`/`Blob`/`Uint8Array` object to
+         *     read. Local file only works in node environment.
+         * @param options Options passed to the underlying `FileChunkIterator`s,
+         *   such as {chunksize: 1024}.
+         */
+        constructor(input, options = {}) {
+          super();
+          this.input = input;
+          this.options = options;
+        }
+        async iterator() {
+          if (isLocalPath(this.input) && Object(dist["env"])().get("IS_NODE")) {
+            // tslint:disable-next-line:no-require-imports
+            const fs = __webpack_require__(79);
+            this.input = fs.readFileSync(this.input.substr(7));
+          }
+          // TODO(kangyizhang): Add LocalFileChunkIterator to split local streaming
+          // with file in browser.
+          return new file_chunk_iterator_FileChunkIterator(this.input, this.options);
+        }
+      }
+      //# sourceMappingURL=file_data_source.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/sources/url_data_source.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      /*
+       * Represents a URL readable as a stream of binary data chunks.
+       */
+      class url_data_source_URLDataSource extends DataSource {
+        /**
+         * Create a `URLDataSource`.
+         *
+         * @param url A source URL string, or a `Request` object.
+         * @param options Options passed to the underlying `FileChunkIterator`s,
+         *   such as {chunksize: 1024}.
+         */
+        constructor(url, fileOptions = {}) {
+          super();
+          this.url = url;
+          this.fileOptions = fileOptions;
+        }
+        // TODO(soergel): provide appropriate caching options.  Currently this
+        // will download the URL anew for each call to iterator().  Since we have
+        // to treat the downloaded file as a blob/buffer anyway, we may as well retain
+        // it-- but that raises GC issues.  Also we may want a persistent disk cache.
+        async iterator() {
+          if (isLocalPath(this.url)) {
+            return new file_data_source_FileDataSource(this.url, this.fileOptions).iterator();
+          } else {
+            return urlChunkIterator(this.url, this.fileOptions);
+          }
+        }
+      }
+      //# sourceMappingURL=url_data_source.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/readers.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       *
+       * =============================================================================
+       */
+
+      /**
+       * Create a `CSVDataset` by reading and decoding CSV file(s) from provided URL
+       * or local path if it's in Node environment.
+       *
+       * Note: If isLabel in columnConfigs is `true` for at least one column, the
+       * element in returned `CSVDataset` will be an object of
+       * `{xs:features, ys:labels}`: xs is a dict of features key/value pairs, ys
+       * is a dict of labels key/value pairs. If no column is marked as label,
+       * returns a dict of features only.
+       *
+       * ```js
+       * const csvUrl =
+       * 'https://storage.googleapis.com/tfjs-examples/multivariate-linear-regression/data/boston-housing-train.csv';
+       *
+       * async function run() {
+       *   // We want to predict the column "medv", which represents a median value of
+       *   // a home (in $1000s), so we mark it as a label.
+       *   const csvDataset = tf.data.csv(
+       *     csvUrl, {
+       *       columnConfigs: {
+       *         medv: {
+       *           isLabel: true
+       *         }
+       *       }
+       *     });
+       *
+       *   // Number of features is the number of column names minus one for the label
+       *   // column.
+       *   const numOfFeatures = (await csvDataset.columnNames()).length - 1;
+       *
+       *   // Prepare the Dataset for training.
+       *   const flattenedDataset =
+       *     csvDataset
+       *     .map(({xs, ys}) =>
+       *       {
+       *         // Convert xs(features) and ys(labels) from object form (keyed by
+       *         // column name) to array form.
+       *         return {xs:Object.values(xs), ys:Object.values(ys)};
+       *       })
+       *     .batch(10);
+       *
+       *   // Define the model.
+       *   const model = tf.sequential();
+       *   model.add(tf.layers.dense({
+       *     inputShape: [numOfFeatures],
+       *     units: 1
+       *   }));
+       *   model.compile({
+       *     optimizer: tf.train.sgd(0.000001),
+       *     loss: 'meanSquaredError'
+       *   });
+       *
+       *   // Fit the model using the prepared Dataset
+       *   return model.fitDataset(flattenedDataset, {
+       *     epochs: 10,
+       *     callbacks: {
+       *       onEpochEnd: async (epoch, logs) => {
+       *         console.log(epoch + ':' + logs.loss);
+       *       }
+       *     }
+       *   });
+       * }
+       *
+       * await run();
+       * ```
+       *
+       * @param source URL or local path to get CSV file. If it's a local path, it
+       * must have prefix `file://` and it only works in node environment.
+       * @param csvConfig (Optional) A CSVConfig object that contains configurations
+       *     of reading and decoding from CSV file(s).
+       */
+      /**
+       * @doc {
+       *   heading: 'Data',
+       *   subheading: 'Creation',
+       *   namespace: 'data',
+       *   configParamIndices: [1]
+       *  }
+       */
+      function csv(source, csvConfig = {}) {
+        return new csv_dataset_CSVDataset(new url_data_source_URLDataSource(source), csvConfig);
+      }
+      /**
+       * Create a `Dataset` that produces each element by calling a provided function.
+       *
+       * Note that repeated iterations over this `Dataset` may produce different
+       * results, because the function will be called anew for each element of each
+       * iteration.
+       *
+       * Also, beware that the sequence of calls to this function may be out of order
+       * in time with respect to the logical order of the Dataset. This is due to the
+       * asynchronous lazy nature of stream processing, and depends on downstream
+       * transformations (e.g. .shuffle()). If the provided function is pure, this is
+       * no problem, but if it is a closure over a mutable state (e.g., a traversal
+       * pointer), then the order of the produced elements may be scrambled.
+       *
+       * ```js
+       * let i = -1;
+       * const func = () =>
+       *    ++i < 5 ? {value: i, done: false} : {value: null, done: true};
+       * const ds = tf.data.func(func);
+       * await ds.forEachAsync(e => console.log(e));
+       * ```
+       *
+       * @param f A function that produces one data element on each call.
+       */
+      function func(f) {
+        const iter = Object(lazy_iterator["e" /* iteratorFromFunction */])(f);
+        return datasetFromIteratorFn(async () => iter);
+      }
+      /**
+       * Create a `Dataset` that produces each element from provided JavaScript
+       * generator, which is a function*
+       * (https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Iterators_and_Generators#Generator_functions),
+       * or a function that returns an
+       * iterator
+       * (https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Iterators_and_Generators#Generator_functions).
+       *
+       * The returned iterator should have `.next()` function that returns element in
+       * format of `{value: TensorContainer, done:boolean}`.
+       *
+       * Example of creating a dataset from an iterator factory:
+       * ```js
+       * function makeIterator() {
+       *   const numElements = 10;
+       *   let index = 0;
+       *
+       *   const iterator = {
+       *     next: () => {
+       *       let result;
+       *       if (index < numElements) {
+       *         result = {value: index, done: false};
+       *         index++;
+       *         return result;
+       *       }
+       *       return {value: index, done: true};
+       *     }
+       *   };
+       *   return iterator;
+       * }
+       * const ds = tf.data.generator(makeIterator);
+       * await ds.forEachAsync(e => console.log(e));
+       * ```
+       *
+       * Example of creating a dataset from a generator:
+       * ```js
+       * function* dataGenerator() {
+       *   const numElements = 10;
+       *   let index = 0;
+       *   while (index < numElements) {
+       *     const x = index;
+       *     index++;
+       *     yield x;
+       *   }
+       * }
+       *
+       * const ds = tf.data.generator(dataGenerator);
+       * await ds.forEachAsync(e => console.log(e));
+       * ```
+       *
+       * @param generator A Javascript generator function that returns a JavaScript
+       *     iterator.
+       */
+      /**
+       * @doc {
+       *   heading: 'Data',
+       *   subheading: 'Creation',
+       *   namespace: 'data',
+       *   configParamIndices: [1]
+       *  }
+       */
+      function readers_generator(generator) {
+        return datasetFromIteratorFn(async () => {
+          const gen = await generator();
+          return Object(lazy_iterator["e" /* iteratorFromFunction */])(() => gen.next());
+        });
+      }
+      /**
+       * Create an iterator that generate `Tensor`s from webcam video stream. This API
+       * only works in Browser environment when the device has webcam.
+       *
+       * Note: this code snippet only works when the device has a webcam. It will
+       * request permission to open the webcam when running.
+       * ```js
+       * const videoElement = document.createElement('video');
+       * videoElement.width = 100;
+       * videoElement.height = 100;
+       * const cam = await tf.data.webcam(videoElement);
+       * const img = await cam.capture();
+       * img.print();
+       * cam.stop();
+       * ```
+       *
+       * @param webcamVideoElement A `HTMLVideoElement` used to play video from
+       *     webcam. If this element is not provided, a hidden `HTMLVideoElement` will
+       *     be created. In that case, `resizeWidth` and `resizeHeight` must be
+       *     provided to set the generated tensor shape.
+       * @param webcamConfig A `WebcamConfig` object that contains configurations of
+       *     reading and manipulating data from webcam video stream.
+       */
+      /**
+       * @doc {
+       *   heading: 'Data',
+       *   subheading: 'Creation',
+       *   namespace: 'data',
+       *   ignoreCI: true
+       *  }
+       */
+      async function webcam(webcamVideoElement, webcamConfig) {
+        return webcam_iterator_WebcamIterator.create(webcamVideoElement, webcamConfig);
+      }
+      /**
+       * Create an iterator that generate frequency-domain spectrogram `Tensor`s from
+       * microphone audio stream with browser's native FFT. This API only works in
+       * browser environment when the device has microphone.
+       *
+       * Note: this code snippet only works when the device has a microphone. It will
+       * request permission to open the microphone when running.
+       * ```js
+       * const mic = await tf.data.microphone({
+       *   fftSize: 1024,
+       *   columnTruncateLength: 232,
+       *   numFramesPerSpectrogram: 43,
+       *   sampleRateHz:44100,
+       *   includeSpectrogram: true,
+       *   includeWaveform: true
+       * });
+       * const audioData = await mic.capture();
+       * const spectrogramTensor = audioData.spectrogram;
+       * spectrogramTensor.print();
+       * const waveformTensor = audioData.waveform;
+       * waveformTensor.print();
+       * mic.stop();
+       * ```
+       *
+       * @param microphoneConfig A `MicrophoneConfig` object that contains
+       *     configurations of reading audio data from microphone.
+       */
+      /**
+       * @doc {
+       *   heading: 'Data',
+       *   subheading: 'Creation',
+       *   namespace: 'data',
+       *   ignoreCI: true
+       *  }
+       */
+      async function microphone(microphoneConfig) {
+        return microphone_iterator_MicrophoneIterator.create(microphoneConfig);
+      }
+      //# sourceMappingURL=readers.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/version.js
+      /** @license See the LICENSE file. */
+      // This code is auto-generated, do not modify this file!
+      const version = "2.0.1";
+
+      //# sourceMappingURL=version.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-data/dist/index.js
+      /**
+       * @license
+       * Copyright 2018 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      //# sourceMappingURL=index.js.map
+
+      /***/
+    },
+    /* 89 */
+    /***/ function (module, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      // ESM COMPAT FLAG
+      __webpack_require__.r(__webpack_exports__);
+
+      // EXPORTS
+      __webpack_require__.d(__webpack_exports__, "MathBackendCPU", function () {
+        return /* reexport */ base["a" /* MathBackendCPU */];
+      });
+      __webpack_require__.d(__webpack_exports__, "version_cpu", function () {
+        return /* reexport */ base["c" /* version_cpu */];
+      });
+      __webpack_require__.d(__webpack_exports__, "shared", function () {
+        return /* reexport */ base["b" /* shared */];
+      });
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-core/dist/index.js + 269 modules
+      var dist = __webpack_require__(0);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/base.js + 3 modules
+      var base = __webpack_require__(31);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/cpu_util.js
+      var cpu_util = __webpack_require__(9);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/kernel_utils.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function createBinaryKernelConfig(name, op) {
+        return {
+          kernelName: name,
+          backendName: "cpu",
+          kernelFunc: ({ inputs, backend }) => {
+            const { a, b } = inputs;
+            const cpuBackend = backend;
+            Object(cpu_util["a" /* assertNotComplex */])([a, b], name);
+            const aVals = cpuBackend.data.get(a.dataId).values;
+            const bVals = cpuBackend.data.get(b.dataId).values;
+            const [resultData, resultShape] = op(a.shape, b.shape, aVals, bVals, a.dtype);
+            const dataId = cpuBackend.write(resultData, resultShape, a.dtype);
+            return { dataId, shape: resultShape, dtype: a.dtype };
+          },
+        };
+      }
+      function createBinaryKernelImpl(op) {
+        return (aShape, bShape, aVals, bVals, dtype) => {
+          const newShape = dist["backend_util"].assertAndGetBroadcastShape(aShape, bShape);
+          const resultRank = newShape.length;
+          const resultStrides = dist["util"].computeStrides(newShape);
+          const resultSize = dist["util"].sizeFromShape(newShape);
+          const result = dist["util"].getTypedArrayFromDType(dtype, resultSize);
+          const aRank = aShape.length;
+          const bRank = bShape.length;
+          const aStrides = dist["util"].computeStrides(aShape);
+          const bStrides = dist["util"].computeStrides(bShape);
+          const aBroadcastDims = dist["backend_util"].getBroadcastDims(aShape, newShape);
+          const bBroadcastDims = dist["backend_util"].getBroadcastDims(bShape, newShape);
+          if (aBroadcastDims.length + bBroadcastDims.length === 0) {
+            for (let i = 0; i < result.length; ++i) {
+              result[i] = op(aVals[i % aVals.length], bVals[i % bVals.length]);
+            }
+          } else {
+            for (let i = 0; i < result.length; ++i) {
+              const loc = dist["util"].indexToLoc(i, resultRank, resultStrides);
+              const aLoc = loc.slice(-aRank);
+              aBroadcastDims.forEach((d) => (aLoc[d] = 0));
+              const aIndex = dist["util"].locToIndex(aLoc, aRank, aStrides);
+              const bLoc = loc.slice(-bRank);
+              bBroadcastDims.forEach((d) => (bLoc[d] = 0));
+              const bIndex = dist["util"].locToIndex(bLoc, bRank, bStrides);
+              result[i] = op(aVals[aIndex], bVals[bIndex]);
+            }
+          }
+          return [result, newShape];
+        };
+      }
+      //# sourceMappingURL=kernel_utils.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Div_impl.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const divImpl = createBinaryKernelImpl((a, b) => a / b);
+      //# sourceMappingURL=Div_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Div.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const divConfig = createBinaryKernelConfig(dist["Div"], divImpl);
+      //# sourceMappingURL=Div.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max_impl.js
+      var Max_impl = __webpack_require__(37);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose_impl.js
+      var Transpose_impl = __webpack_require__(30);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const maxConfig = {
+        kernelName: dist["Max"],
+        backendName: "cpu",
+        kernelFunc: ({ inputs, attrs, backend }) => {
+          const { x } = inputs;
+          const { reductionIndices } = attrs;
+          const cpuBackend = backend;
+          let xShape = x.shape;
+          const xRank = xShape.length;
+          const origAxes = dist["util"].parseAxisParam(reductionIndices, xShape);
+          let axes = origAxes;
+          const permutedAxes = dist["backend_util"].getAxesPermutation(axes, xRank);
+          let xVals = cpuBackend.data.get(x.dataId).values;
+          if (permutedAxes != null) {
+            const newShape = new Array(xRank);
+            for (let i = 0; i < newShape.length; i++) {
+              newShape[i] = xShape[permutedAxes[i]];
+            }
+            xVals = Object(Transpose_impl["a" /* transposeImpl */])(
+              xVals,
+              xShape,
+              x.dtype,
+              permutedAxes,
+              newShape
+            );
+            axes = dist["backend_util"].getInnerMostAxes(axes.length, xRank);
+            xShape = newShape;
+          }
+          Object(cpu_util["a" /* assertNotComplex */])(x, "max");
+          dist["backend_util"].assertAxesAreInnerMostDims("max", axes, xRank);
+          const [maxOutShape, reduceShape] = dist["backend_util"].computeOutAndReduceShapes(
+            xShape,
+            axes
+          );
+          const reduceSize = dist["util"].sizeFromShape(reduceShape);
+          const result = Object(Max_impl["a" /* maxImpl */])(
+            xVals,
+            reduceSize,
+            maxOutShape,
+            x.dtype
+          );
+          const dataId = cpuBackend.write(result, maxOutShape, x.dtype);
+          return { dataId, shape: maxOutShape, dtype: x.dtype };
+        },
+      };
+      //# sourceMappingURL=Max.js.map
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/pool_utils.js
+      var pool_utils = __webpack_require__(26);
+
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolWithArgmax_impl.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      function maxPoolWithArgmaxImpl(xValues, xShape, dtype, includeBatchInIndex, convInfo) {
+        const strides = dist["util"].computeStrides(xShape);
+        const maxPools = Object(pool_utils["b" /* pool */])(
+          xValues,
+          xShape,
+          dtype,
+          strides,
+          convInfo,
+          "max"
+        );
+        const maxPositions = Object(pool_utils["a" /* maxPoolPositions */])(
+          xValues,
+          xShape,
+          dtype,
+          convInfo,
+          true,
+          includeBatchInIndex
+        );
+        return [maxPools.values, maxPositions.values];
+      }
+      //# sourceMappingURL=MaxPoolWithArgmax_impl.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolWithArgmax.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const maxPoolWithArgmaxConfig = {
+        kernelName: dist["MaxPoolWithArgmax"],
+        backendName: "cpu",
+        kernelFunc: ({ inputs, attrs, backend }) => {
+          const { x } = inputs;
+          const { filterSize, strides, pad, includeBatchInIndex } = attrs;
+          const cpuBackend = backend;
+          Object(cpu_util["a" /* assertNotComplex */])(x, "MaxPoolWithArgmax");
+          const values = cpuBackend.data.get(x.dataId).values;
+          const convInfo = dist["backend_util"].computePool2DInfo(
+            x.shape,
+            filterSize,
+            strides,
+            [1, 1],
+            pad
+          );
+          const [pooled, indexes] = maxPoolWithArgmaxImpl(
+            values,
+            x.shape,
+            x.dtype,
+            includeBatchInIndex,
+            convInfo
+          );
+          const pooledDataId = cpuBackend.write(pooled, convInfo.outShape, x.dtype);
+          const indexesDataId = cpuBackend.write(indexes, convInfo.outShape, x.dtype);
+          return [
+            { dataId: pooledDataId, shape: convInfo.outShape, dtype: x.dtype },
+            { dataId: indexesDataId, shape: convInfo.outShape, dtype: "int32" },
+          ];
+        },
+      };
+      //# sourceMappingURL=MaxPoolWithArgmax.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NonMaxSuppressionV5.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const nonMaxSuppressionV5 = dist["kernel_impls"].nonMaxSuppressionV5;
+
+      const nonMaxSuppressionV5Config = {
+        kernelName: dist["NonMaxSuppressionV5"],
+        backendName: "cpu",
+        kernelFunc: ({ inputs, backend, attrs }) => {
+          const { boxes, scores } = inputs;
+          const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;
+          const cpuBackend = backend;
+          Object(cpu_util["a" /* assertNotComplex */])(boxes, "NonMaxSuppressionWithScore");
+          const boxesVals = cpuBackend.data.get(boxes.dataId).values;
+          const scoresVals = cpuBackend.data.get(scores.dataId).values;
+          const maxOutputSizeVal = maxOutputSize;
+          const iouThresholdVal = iouThreshold;
+          const scoreThresholdVal = scoreThreshold;
+          const softNmsSigmaVal = softNmsSigma;
+          const { selectedIndices, selectedScores } = nonMaxSuppressionV5(
+            boxesVals,
+            scoresVals,
+            maxOutputSizeVal,
+            iouThresholdVal,
+            scoreThresholdVal,
+            softNmsSigmaVal
+          );
+          return [selectedIndices, selectedScores];
+        },
+      };
+      //# sourceMappingURL=NonMaxSuppressionV5.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Square.js
+      /**
+       * @license
+       * Copyright 2019 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const squareConfig = {
+        kernelName: dist["Square"],
+        backendName: "cpu",
+        kernelFunc: ({ inputs, backend }) => {
+          const { x } = inputs;
+          const cpuBackend = backend;
+          Object(cpu_util["a" /* assertNotComplex */])(x, "square");
+          const values = cpuBackend.data.get(x.dataId).values;
+          const newValues = new Float32Array(values.length);
+          for (let i = 0; i < values.length; ++i) {
+            const value = values[i];
+            newValues[i] = value * value;
+          }
+          const dataId = cpuBackend.write(newValues, x.shape, x.dtype);
+          return { dataId, shape: x.shape, dtype: x.dtype };
+        },
+      };
+      //# sourceMappingURL=Square.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SquaredDifference.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const squaredDifferenceImpl = createBinaryKernelImpl((aVal, bVal) => {
+        const diff = aVal - bVal;
+        return diff * diff;
+      });
+      const squaredDifferenceConfig = createBinaryKernelConfig(
+        dist["SquaredDifference"],
+        squaredDifferenceImpl
+      );
+      //# sourceMappingURL=SquaredDifference.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      const transposeConfig = {
+        kernelName: dist["Transpose"],
+        backendName: "cpu",
+        kernelFunc: ({ inputs, attrs, backend }) => {
+          const { x } = inputs;
+          const { perm } = attrs;
+          const cpuBackend = backend;
+          Object(cpu_util["a" /* assertNotComplex */])(x, "transpose");
+          const xRank = x.shape.length;
+          const newShape = new Array(xRank);
+          for (let i = 0; i < newShape.length; i++) {
+            newShape[i] = x.shape[perm[i]];
+          }
+          const values = cpuBackend.data.get(x.dataId).values;
+          const result = Object(Transpose_impl["a" /* transposeImpl */])(
+            values,
+            x.shape,
+            x.dtype,
+            perm,
+            newShape
+          );
+          const dataId = cpuBackend.write(result, newShape, x.dtype);
+          return { dataId, shape: newShape, dtype: x.dtype };
+        },
+      };
+      //# sourceMappingURL=Transpose.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/register_all_kernels.js
+      /**
+       * @license
+       * Copyright 2020 Google Inc. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+      // We explicitly import the modular kernels so they get registered in the
+      // global registry when we compile the library. A modular build would replace
+      // the contents of this file and import only the kernels that are needed.
+
+      // List all kernel configs here
+      const kernelConfigs = [
+        nonMaxSuppressionV5Config,
+        squareConfig,
+        squaredDifferenceConfig,
+        divConfig,
+        transposeConfig,
+        maxPoolWithArgmaxConfig,
+        maxConfig,
+      ];
+      for (const kernelConfig of kernelConfigs) {
+        Object(dist["registerKernel"])(kernelConfig);
+      }
+      //# sourceMappingURL=register_all_kernels.js.map
+      // CONCATENATED MODULE: ./node_modules/@tensorflow/tfjs-backend-cpu/dist/index.js
+      /**
+       * @license
+       * Copyright 2020 Google LLC. All Rights Reserved.
+       * Licensed under the Apache License, Version 2.0 (the "License");
+       * you may not use this file except in compliance with the License.
+       * You may obtain a copy of the License at
+       *
+       * http://www.apache.org/licenses/LICENSE-2.0
+       *
+       * Unless required by applicable law or agreed to in writing, software
+       * distributed under the License is distributed on an "AS IS" BASIS,
+       * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+       * See the License for the specific language governing permissions and
+       * limitations under the License.
+       * =============================================================================
+       */
+
+      // Side effects for default initialization of MathBackendCPU
+      Object(dist["registerBackend"])(
+        "cpu",
+        () => new base["a" /* MathBackendCPU */](),
+        1 /* priority */
+      );
+
+      // All exports from this package should be in base.
+
+      //# sourceMappingURL=index.js.map
+
+      /***/
+    },
+    /* 90 */
+    /***/ function (__webpack_module__, __webpack_exports__, __webpack_require__) {
+      "use strict";
+      // ESM COMPAT FLAG
+      __webpack_require__.r(__webpack_exports__);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow/tfjs/dist/tf.node.js
+      var tf_node = __webpack_require__(60);
+
+      // EXTERNAL MODULE: ./node_modules/regression/dist/regression.js
+      var regression = __webpack_require__(80);
+
+      // CONCATENATED MODULE: ./src/params.mjs
+      const params = {
+        moveTickSize: 50,
+        videoContainerId: "webgazerVideoContainer",
+        videoElementId: "webgazerVideoFeed",
+        videoElementCanvasId: "webgazerVideoCanvas",
+        faceOverlayId: "webgazerFaceOverlay",
+        faceFeedbackBoxId: "webgazerFaceFeedbackBox",
+        gazeDotId: "webgazerGazeDot",
+        videoViewerWidth: 320,
+        videoViewerHeight: 240,
+        faceFeedbackBoxRatio: 0.66,
+        // View options
+        showVideo: true,
+        mirrorVideo: true,
+        showFaceOverlay: true,
+        showFaceFeedbackBox: true,
+        showGazeDot: true,
+        camConstraints: {
+          video: {
+            width: { min: 320, ideal: 640, max: 1920 },
+            height: { min: 240, ideal: 480, max: 1080 },
+            facingMode: "user",
+          },
+        },
+        dataTimestep: 50,
+        showVideoPreview: true,
+        applyKalmanFilter: true,
+        // Whether or not to store accuracy eigenValues, used by the calibration example file
+        storingPoints: false,
+      };
+
+      /* harmony default export */ var src_params = params;
+
+      // CONCATENATED MODULE: ./src/dom_util.mjs
+      // helper functions
+
+      /**
+       * Provides requestAnimationFrame in a cross browser way.
+       */
+      window.requestAnimFrame = (function () {
+        return (
+          window.requestAnimationFrame ||
+          window.webkitRequestAnimationFrame ||
+          window.mozRequestAnimationFrame ||
+          window.oRequestAnimationFrame ||
+          window.msRequestAnimationFrame ||
+          function (
+            /* function FrameRequestCallback */ callback,
+            /* DOMElement Element */ element
+          ) {
+            return window.setTimeout(callback, 1000 / 60);
+          }
+        );
+      })();
+
+      /**
+       * Provides cancelRequestAnimationFrame in a cross browser way.
+       */
+      window.cancelRequestAnimFrame = (function () {
+        return (
+          window.cancelCancelRequestAnimationFrame ||
+          window.webkitCancelRequestAnimationFrame ||
+          window.mozCancelRequestAnimationFrame ||
+          window.oCancelRequestAnimationFrame ||
+          window.msCancelRequestAnimationFrame ||
+          window.clearTimeout
+        );
+      })();
+
+      // EXTERNAL MODULE: ./node_modules/localforage/dist/localforage.js
+      var localforage = __webpack_require__(32);
+
+      // EXTERNAL MODULE: ./node_modules/@tensorflow-models/facemesh/dist/index.js
+      var dist = __webpack_require__(59);
+
+      // CONCATENATED MODULE: ./src/facemesh.mjs
+
+      /**
+       * Constructor of TFFaceMesh object
+       * @constructor
+       * */
+      const TFFaceMesh = function () {
+        //Backend options are webgl, wasm, and CPU.
+        //For recent laptops WASM is better than WebGL.
+        //TODO: This hack makes loading the model block the UI. We should fix that
+        // this.model = (async () => { return await facemesh.load({"maxFaces":1}) })();
+        this.model = dist.load({ maxFaces: 1 });
+        this.predictionReady = false;
+      };
+
+      // Global variable for face landmark positions array
+      TFFaceMesh.prototype.positionsArray = null;
+
+      /**
+       * Isolates the two patches that correspond to the user's eyes
+       * @param  {Canvas} imageCanvas - canvas corresponding to the webcam stream
+       * @param  {Number} width - of imageCanvas
+       * @param  {Number} height - of imageCanvas
+       * @return {Object} the two eye-patches, first left, then right eye
+       */
+      TFFaceMesh.prototype.getEyePatches = async function (imageCanvas, width, height) {
+        if (imageCanvas.width === 0) {
+          return null;
+        }
+
+        // Load the MediaPipe facemesh model.
+        const model = await this.model;
+
+        // Pass in a video stream (or an image, canvas, or 3D tensor) to obtain an
+        // array of detected faces from the MediaPipe graph.
+        const predictions = await model.estimateFaces(imageCanvas);
+
+        if (predictions.length == 0) {
+          return false;
+        }
+
+        // Save positions to global variable
+        this.positionsArray = predictions[0].scaledMesh;
+        const positions = this.positionsArray;
+
+        // Fit the detected eye in a rectangle. [20200626 xk] not clear which approach is better
+        // https://raw.githubusercontent.com/tensorflow/tfjs-models/master/facemesh/mesh_map.jpg
+
+        // // Maintains a relatively stable shape of the bounding box at the cost of cutting off parts of
+        // // the eye when the eye is tilted.
+        // var leftOriginX = Math.round(positions[130][0]);
+        // var leftOriginY = Math.round(positions[27][1]);
+        // var leftWidth = Math.round(positions[243][0] - leftOriginX);
+        // var leftHeight = Math.round(positions[23][1] - leftOriginY);
+        // var rightOriginX = Math.round(positions[463][0]);
+        // var rightOriginY = Math.round(positions[257][1]);
+        // var rightWidth = Math.round(positions[359][0] - rightOriginX);
+        // var rightHeight = Math.round(positions[253][1] - rightOriginY);
+
+        // Won't really cut off any parts of the eye, at the cost of warping the shape (i.e. height/
+        // width ratio) of the bounding box.
+        var leftOriginX = Math.round(
+          Math.min(positions[247][0], positions[130][0], positions[25][0])
+        );
+        var leftOriginY = Math.round(
+          Math.min(positions[247][1], positions[27][1], positions[190][1])
+        );
+        var leftWidth = Math.round(
+          Math.max(positions[190][0], positions[243][0], positions[233][0]) - leftOriginX
+        );
+        var leftHeight = Math.round(
+          Math.max(positions[25][1], positions[23][1], positions[112][1]) - leftOriginY
+        );
+        var rightOriginX = Math.round(
+          Math.min(positions[414][0], positions[463][0], positions[453][0])
+        );
+        var rightOriginY = Math.round(
+          Math.min(positions[414][1], positions[257][1], positions[467][1])
+        );
+        var rightWidth = Math.round(
+          Math.max(positions[467][0], positions[359][0], positions[255][0]) - rightOriginX
+        );
+        var rightHeight = Math.round(
+          Math.max(positions[341][1], positions[253][1], positions[255][1]) - rightOriginY
+        );
+
+        if (leftWidth === 0 || rightWidth === 0) {
+          console.log("an eye patch had zero width");
+          return null;
+        }
+
+        if (leftHeight === 0 || rightHeight === 0) {
+          console.log("an eye patch had zero height");
+          return null;
+        }
+
+        // Start building object to be returned
+        var eyeObjs = {};
+
+        var leftImageData = imageCanvas
+          .getContext("2d")
+          .getImageData(leftOriginX, leftOriginY, leftWidth, leftHeight);
+        eyeObjs.left = {
+          patch: leftImageData,
+          imagex: leftOriginX,
+          imagey: leftOriginY,
+          width: leftWidth,
+          height: leftHeight,
+        };
+
+        var rightImageData = imageCanvas
+          .getContext("2d")
+          .getImageData(rightOriginX, rightOriginY, rightWidth, rightHeight);
+        eyeObjs.right = {
+          patch: rightImageData,
+          imagex: rightOriginX,
+          imagey: rightOriginY,
+          width: rightWidth,
+          height: rightHeight,
+        };
+
+        this.predictionReady = true;
+
+        return eyeObjs;
+      };
+
+      /**
+       * Returns the positions array corresponding to the last call to getEyePatches.
+       * Requires that getEyePatches() was called previously, else returns null.
+       */
+      TFFaceMesh.prototype.getPositions = function () {
+        return this.positionsArray;
+      };
+
+      /**
+       * Reset the tracker to default values
+       */
+      TFFaceMesh.prototype.reset = function () {
+        console.log("Unimplemented; Tracking.js has no obvious reset function");
+      };
+
+      /**
+       * Draw TF_FaceMesh_Overlay
+       */
+      TFFaceMesh.prototype.drawFaceOverlay = function (ctx, keypoints) {
+        // If keypoints is falsy, don't do anything
+        if (keypoints) {
+          ctx.fillStyle = "#32EEDB";
+          ctx.strokeStyle = "#32EEDB";
+          ctx.lineWidth = 0.5;
+
+          for (let i = 0; i < keypoints.length; i++) {
+            const x = keypoints[i][0];
+            const y = keypoints[i][1];
+
+            ctx.beginPath();
+            ctx.arc(x, y, 1 /* radius */, 0, 2 * Math.PI);
+            ctx.closePath();
+            ctx.fill();
+          }
+        }
+      };
+
+      /**
+       * The TFFaceMesh object name
+       * @type {string}
+       */
+      TFFaceMesh.prototype.name = "TFFaceMesh";
+
+      /* harmony default export */ var facemesh = TFFaceMesh;
+
+      // EXTERNAL MODULE: ./node_modules/numeric/numeric-1.2.6.js
+      var numeric_1_2_6 = __webpack_require__(12);
+
+      // CONCATENATED MODULE: ./src/mat.mjs
+      const mat = {};
+      /**
+       * Transposes an mxn array
+       * @param {Array.<Array.<Number>>} matrix - of 'M x N' dimensionality
+       * @return {Array.<Array.<Number>>} transposed matrix
+       */
+      mat.transpose = function (matrix) {
+        var m = matrix.length;
+        var n = matrix[0].length;
+        var transposedMatrix = new Array(n);
+
+        for (var i = 0; i < m; i++) {
+          for (var j = 0; j < n; j++) {
+            if (i === 0) transposedMatrix[j] = new Array(m);
+            transposedMatrix[j][i] = matrix[i][j];
+          }
+        }
+
+        return transposedMatrix;
+      };
+
+      /**
+       * Get a sub-matrix of matrix
+       * @param {Array.<Array.<Number>>} matrix - original matrix
+       * @param {Array.<Number>} r - Array of row indices
+       * @param {Number} j0 - Initial column index
+       * @param {Number} j1 - Final column index
+       * @returns {Array} The sub-matrix matrix(r(:),j0:j1)
+       */
+      mat.getMatrix = function (matrix, r, j0, j1) {
+        var X = new Array(r.length),
+          m = j1 - j0 + 1;
+
+        for (var i = 0; i < r.length; i++) {
+          X[i] = new Array(m);
+          for (var j = j0; j <= j1; j++) {
+            X[i][j - j0] = matrix[r[i]][j];
+          }
+        }
+        return X;
+      };
+
+      /**
+       * Get a submatrix of matrix
+       * @param {Array.<Array.<Number>>} matrix - original matrix
+       * @param {Number} i0 - Initial row index
+       * @param {Number} i1 - Final row index
+       * @param {Number} j0 - Initial column index
+       * @param {Number} j1 - Final column index
+       * @return {Array} The sub-matrix matrix(i0:i1,j0:j1)
+       */
+      mat.getSubMatrix = function (matrix, i0, i1, j0, j1) {
+        var size = j1 - j0 + 1,
+          X = new Array(i1 - i0 + 1);
+
+        for (var i = i0; i <= i1; i++) {
+          var subI = i - i0;
+
+          X[subI] = new Array(size);
+
+          for (var j = j0; j <= j1; j++) {
+            X[subI][j - j0] = matrix[i][j];
+          }
+        }
+        return X;
+      };
+
+      /**
+       * Linear algebraic matrix multiplication, matrix1 * matrix2
+       * @param {Array.<Array.<Number>>} matrix1
+       * @param {Array.<Array.<Number>>} matrix2
+       * @return {Array.<Array.<Number>>} Matrix product, matrix1 * matrix2
+       */
+      mat.mult = function (matrix1, matrix2) {
+        if (matrix2.length != matrix1[0].length) {
+          console.log("Matrix inner dimensions must agree:");
+        }
+
+        var X = new Array(matrix1.length),
+          Bcolj = new Array(matrix1[0].length);
+
+        for (var j = 0; j < matrix2[0].length; j++) {
+          for (var k = 0; k < matrix1[0].length; k++) {
+            Bcolj[k] = matrix2[k][j];
+          }
+          for (var i = 0; i < matrix1.length; i++) {
+            if (j === 0) X[i] = new Array(matrix2[0].length);
+
+            var Arowi = matrix1[i];
+            var s = 0;
+            for (var k = 0; k < matrix1[0].length; k++) {
+              s += Arowi[k] * Bcolj[k];
+            }
+            X[i][j] = s;
+          }
+        }
+        return X;
+      };
+
+      /**
+       * LUDecomposition to solve A*X = B, based on WEKA code
+       * @param {Array.<Array.<Number>>} A - left matrix of equation to be solved
+       * @param {Array.<Array.<Number>>} B - right matrix of equation to be solved
+       * @return {Array.<Array.<Number>>} X so that L*U*X = B(piv,:)
+       */
+      mat.LUDecomposition = function (A, B) {
+        var LU = new Array(A.length);
+
+        for (var i = 0; i < A.length; i++) {
+          LU[i] = new Array(A[0].length);
+          for (var j = 0; j < A[0].length; j++) {
+            LU[i][j] = A[i][j];
+          }
+        }
+
+        var m = A.length;
+        var n = A[0].length;
+        var piv = new Array(m);
+        for (var i = 0; i < m; i++) {
+          piv[i] = i;
+        }
+        var pivsign = 1;
+        var LUrowi = new Array();
+        var LUcolj = new Array(m);
+        // Outer loop.
+        for (var j = 0; j < n; j++) {
+          // Make a copy of the j-th column to localize references.
+          for (var i = 0; i < m; i++) {
+            LUcolj[i] = LU[i][j];
+          }
+          // Apply previous transformations.
+          for (var i = 0; i < m; i++) {
+            LUrowi = LU[i];
+            // Most of the time is spent in the following dot product.
+            var kmax = Math.min(i, j);
+            var s = 0;
+            for (var k = 0; k < kmax; k++) {
+              s += LUrowi[k] * LUcolj[k];
+            }
+            LUrowi[j] = LUcolj[i] -= s;
+          }
+          // Find pivot and exchange if necessary.
+          var p = j;
+          for (var i = j + 1; i < m; i++) {
+            if (Math.abs(LUcolj[i]) > Math.abs(LUcolj[p])) {
+              p = i;
+            }
+          }
+          if (p != j) {
+            for (var k = 0; k < n; k++) {
+              var t = LU[p][k];
+              LU[p][k] = LU[j][k];
+              LU[j][k] = t;
+            }
+            var k = piv[p];
+            piv[p] = piv[j];
+            piv[j] = k;
+            pivsign = -pivsign;
+          }
+          // Compute multipliers.
+          if ((j < m) & (LU[j][j] != 0)) {
+            for (var i = j + 1; i < m; i++) {
+              LU[i][j] /= LU[j][j];
+            }
+          }
+        }
+        if (B.length != m) {
+          console.log("Matrix row dimensions must agree.");
+        }
+        for (var j = 0; j < n; j++) {
+          if (LU[j][j] === 0) {
+            console.log("Matrix is singular.");
+          }
+        }
+        var nx = B[0].length;
+        var X = self.webgazer.mat.getMatrix(B, piv, 0, nx - 1);
+        // Solve L*Y = B(piv,:)
+        for (var k = 0; k < n; k++) {
+          for (var i = k + 1; i < n; i++) {
+            for (var j = 0; j < nx; j++) {
+              X[i][j] -= X[k][j] * LU[i][k];
+            }
+          }
+        }
+        // Solve U*X = Y;
+        for (var k = n - 1; k >= 0; k--) {
+          for (var j = 0; j < nx; j++) {
+            X[k][j] /= LU[k][k];
+          }
+          for (var i = 0; i < k; i++) {
+            for (var j = 0; j < nx; j++) {
+              X[i][j] -= X[k][j] * LU[i][k];
+            }
+          }
+        }
+        return X;
+      };
+
+      /**
+       * Least squares solution of A*X = B, based on WEKA code
+       * @param {Array.<Array.<Number>>} A - left side matrix to be solved
+       * @param {Array.<Array.<Number>>} B - a matrix with as many rows as A and any number of columns.
+       * @return {Array.<Array.<Number>>} X - that minimizes the two norms of QR*X-B.
+       */
+      mat.QRDecomposition = function (A, B) {
+        // Initialize.
+        var QR = new Array(A.length);
+
+        for (var i = 0; i < A.length; i++) {
+          QR[i] = new Array(A[0].length);
+          for (var j = 0; j < A[0].length; j++) {
+            QR[i][j] = A[i][j];
+          }
+        }
+        var m = A.length;
+        var n = A[0].length;
+        var Rdiag = new Array(n);
+        var nrm;
+
+        // Main loop.
+        for (var k = 0; k < n; k++) {
+          // Compute 2-norm of k-th column without under/overflow.
+          nrm = 0;
+          for (var i = k; i < m; i++) {
+            nrm = Math.hypot(nrm, QR[i][k]);
+          }
+          if (nrm != 0) {
+            // Form k-th Householder vector.
+            if (QR[k][k] < 0) {
+              nrm = -nrm;
+            }
+            for (var i = k; i < m; i++) {
+              QR[i][k] /= nrm;
+            }
+            QR[k][k] += 1;
+
+            // Apply transformation to remaining columns.
+            for (var j = k + 1; j < n; j++) {
+              var s = 0;
+              for (var i = k; i < m; i++) {
+                s += QR[i][k] * QR[i][j];
+              }
+              s = -s / QR[k][k];
+              for (var i = k; i < m; i++) {
+                QR[i][j] += s * QR[i][k];
+              }
+            }
+          }
+          Rdiag[k] = -nrm;
+        }
+        if (B.length != m) {
+          console.log("Matrix row dimensions must agree.");
+        }
+        for (var j = 0; j < n; j++) {
+          if (Rdiag[j] === 0) console.log("Matrix is rank deficient");
+        }
+        // Copy right hand side
+        var nx = B[0].length;
+        var X = new Array(B.length);
+        for (var i = 0; i < B.length; i++) {
+          X[i] = new Array(B[0].length);
+        }
+        for (var i = 0; i < B.length; i++) {
+          for (var j = 0; j < B[0].length; j++) {
+            X[i][j] = B[i][j];
+          }
+        }
+        // Compute Y = transpose(Q)*B
+        for (var k = 0; k < n; k++) {
+          for (var j = 0; j < nx; j++) {
+            var s = 0.0;
+            for (var i = k; i < m; i++) {
+              s += QR[i][k] * X[i][j];
+            }
+            s = -s / QR[k][k];
+            for (var i = k; i < m; i++) {
+              X[i][j] += s * QR[i][k];
+            }
+          }
+        }
+        // Solve R*X = Y;
+        for (var k = n - 1; k >= 0; k--) {
+          for (var j = 0; j < nx; j++) {
+            X[k][j] /= Rdiag[k];
+          }
+          for (var i = 0; i < k; i++) {
+            for (var j = 0; j < nx; j++) {
+              X[i][j] -= X[k][j] * QR[i][k];
+            }
+          }
+        }
+        return mat.getSubMatrix(X, 0, n - 1, 0, nx - 1);
+      };
+
+      /* harmony default export */ var src_mat = mat;
+
+      // CONCATENATED MODULE: ./src/util.mjs
+
+      const util = {};
+
+      /**
+       * Eye class, represents an eye patch detected in the video stream
+       * @param {ImageData} patch - the image data corresponding to an eye
+       * @param {Number} imagex - x-axis offset from the top-left corner of the video canvas
+       * @param {Number} imagey - y-axis offset from the top-left corner of the video canvas
+       * @param {Number} width  - width of the eye patch
+       * @param {Number} height - height of the eye patch
+       */
+
+      var resizeWidth = 10;
+      var resizeHeight = 6;
+
+      util.Eye = function (patch, imagex, imagey, width, height) {
+        this.patch = patch;
+        this.imagex = imagex;
+        this.imagey = imagey;
+        this.width = width;
+        this.height = height;
+      };
+
+      util.getEyeFeats = function (eyes) {
+        var resizedLeft = this.resizeEye(eyes.left, resizeHeight, resizeHeight);
+        var resizedright = this.resizeEye(eyes.right, resizeHeight, resizeHeight);
+
+        var leftGray = this.grayscale(resizedLeft.data, resizedLeft.width, resizedLeft.height);
+        var rightGray = this.grayscale(resizedright.data, resizedright.width, resizedright.height);
+
+        var histLeft = [];
+        this.equalizeHistogram(leftGray, 5, histLeft);
+        var histRight = [];
+        this.equalizeHistogram(rightGray, 5, histRight);
+
+        var leftGrayArray = Array.prototype.slice.call(histLeft);
+        var rightGrayArray = Array.prototype.slice.call(histRight);
+
+        return leftGrayArray.concat(rightGrayArray);
+      };
+      //Data Window class
+      //operates like an array but 'wraps' data around to keep the array at a fixed windowSize
+      /**
+       * DataWindow class - Operates like an array, but 'wraps' data around to keep the array at a fixed windowSize
+       * @param {Number} windowSize - defines the maximum size of the window
+       * @param {Array} data - optional data to seed the DataWindow with
+       **/
+      util.DataWindow = function (windowSize, data) {
+        this.data = [];
+        this.windowSize = windowSize;
+        this.index = 0;
+        this.length = 0;
+        if (data) {
+          this.data = data.slice(data.length - windowSize, data.length);
+          this.length = this.data.length;
+        }
+      };
+
+      /**
+       * [push description]
+       * @param  {*} entry - item to be inserted. It either grows the DataWindow or replaces the oldest item
+       * @return {DataWindow} this
+       */
+      util.DataWindow.prototype.push = function (entry) {
+        if (this.data.length < this.windowSize) {
+          this.data.push(entry);
+          this.length = this.data.length;
+          return this;
+        }
+
+        //replace oldest entry by wrapping around the DataWindow
+        this.data[this.index] = entry;
+        this.index = (this.index + 1) % this.windowSize;
+        return this;
+      };
+
+      /**
+       * Get the element at the ind position by wrapping around the DataWindow
+       * @param  {Number} ind index of desired entry
+       * @return {*}
+       */
+      util.DataWindow.prototype.get = function (ind) {
+        return this.data[this.getTrueIndex(ind)];
+      };
+
+      /**
+       * Gets the true this.data array index given an index for a desired element
+       * @param {Number} ind - index of desired entry
+       * @return {Number} index of desired entry in this.data
+       */
+      util.DataWindow.prototype.getTrueIndex = function (ind) {
+        if (this.data.length < this.windowSize) {
+          return ind;
+        } else {
+          //wrap around ind so that we can traverse from oldest to newest
+          return (ind + this.index) % this.windowSize;
+        }
+      };
+
+      /**
+       * Append all the contents of data
+       * @param {Array} data - to be inserted
+       */
+      util.DataWindow.prototype.addAll = function (data) {
+        for (var i = 0; i < data.length; i++) {
+          this.push(data[i]);
+        }
+      };
+
+      //Helper functions
+      /**
+       * Grayscales an image patch. Can be used for the whole canvas, detected face, detected eye, etc.
+       *
+       * Code from tracking.js by Eduardo Lundgren, et al.
+       * https://github.com/eduardolundgren/tracking.js/blob/master/src/tracking.js
+       *
+       * Software License Agreement (BSD License) Copyright (c) 2014, Eduardo A. Lundgren Melo. All rights reserved.
+       * Redistribution and use of this software in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
+       * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
+       * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
+       * The name of Eduardo A. Lundgren Melo may not be used to endorse or promote products derived from this software without specific prior written permission of Eduardo A. Lundgren Melo.
+       * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
+       * IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+       * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
+       * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+       *
+       * @param  {Array} pixels - image data to be grayscaled
+       * @param  {Number} width  - width of image data to be grayscaled
+       * @param  {Number} height - height of image data to be grayscaled
+       * @return {Array} grayscaledImage
+       */
+      util.grayscale = function (pixels, width, height) {
+        var gray = new Uint8ClampedArray(pixels.length >> 2);
+        var p = 0;
+        var w = 0;
+        for (var i = 0; i < height; i++) {
+          for (var j = 0; j < width; j++) {
+            var value = pixels[w] * 0.299 + pixels[w + 1] * 0.587 + pixels[w + 2] * 0.114;
+            gray[p++] = value;
+
+            w += 4;
+          }
+        }
+        return gray;
+      };
+
+      /**
+       * Increase contrast of an image.
+       *
+       * Code from Martin Tschirsich, Copyright (c) 2012.
+       * https://github.com/mtschirs/js-objectdetect/blob/gh-pages/js/objectdetect.js
+       *
+       * @param {Array} src - grayscale integer array
+       * @param {Number} step - sampling rate, control performance
+       * @param {Array} dst - array to hold the resulting image
+       */
+      util.equalizeHistogram = function (src, step, dst) {
+        var srcLength = src.length;
+        if (!dst) dst = src;
+        if (!step) step = 5;
+
+        // Compute histogram and histogram sum:
+        var hist = [
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+        ];
+
+        for (var i = 0; i < srcLength; i += step) {
+          ++hist[src[i]];
+        }
+
+        // Compute integral histogram:
+        var norm = (255 * step) / srcLength,
+          prev = 0;
+        for (var i = 0; i < 256; ++i) {
+          var h = hist[i];
+          prev = h += prev;
+          hist[i] = h * norm; // For non-integer src: ~~(h * norm + 0.5);
+        }
+
+        // Equalize image:
+        for (var i = 0; i < srcLength; ++i) {
+          dst[i] = hist[src[i]];
+        }
+        return dst;
+      };
+
+      util.threshold = function (data, threshold) {
+        for (let i = 0; i < data.length; i++) {
+          data[i] = data[i] > threshold ? 255 : 0;
+        }
+        return data;
+      };
+
+      util.correlation = function (data1, data2) {
+        const length = Math.min(data1.length, data2.length);
+        let count = 0;
+        for (let i = 0; i < length; i++) {
+          if (data1[i] === data2[i]) {
+            count++;
+          }
+        }
+        return count / Math.max(data1.length, data2.length);
+      };
+
+      /**
+       * Gets an Eye object and resizes it to the desired resolution
+       * @param  {webgazer.util.Eye} eye - patch to be resized
+       * @param  {Number} resizeWidth - desired width
+       * @param  {Number} resizeHeight - desired height
+       * @return {webgazer.util.Eye} resized eye patch
+       */
+      util.resizeEye = function (eye, resizeWidth, resizeHeight) {
+        var canvas = document.createElement("canvas");
+        canvas.width = eye.width;
+        canvas.height = eye.height;
+
+        canvas.getContext("2d").putImageData(eye.patch, 0, 0);
+
+        var tempCanvas = document.createElement("canvas");
+
+        tempCanvas.width = resizeWidth;
+        tempCanvas.height = resizeHeight;
+
+        // save the canvas into temp canvas
+        tempCanvas
+          .getContext("2d")
+          .drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, resizeWidth, resizeHeight);
+
+        return tempCanvas.getContext("2d").getImageData(0, 0, resizeWidth, resizeHeight);
+      };
+
+      /**
+       * Checks if the prediction is within the boundaries of the viewport and constrains it
+       * @param  {Array} prediction [x,y] - predicted gaze coordinates
+       * @return {Array} constrained coordinates
+       */
+      util.bound = function (prediction) {
+        if (prediction.x < 0) prediction.x = 0;
+        if (prediction.y < 0) prediction.y = 0;
+        var w = Math.max(document.documentElement.clientWidth, window.innerWidth || 0);
+        var h = Math.max(document.documentElement.clientHeight, window.innerHeight || 0);
+        if (prediction.x > w) {
+          prediction.x = w;
+        }
+
+        if (prediction.y > h) {
+          prediction.y = h;
+        }
+        return prediction;
+      };
+
+      /**
+       * Write statistics in debug paragraph panel
+       * @param {HTMLElement} para - The <p> tag where write data
+       * @param {Object} stats - The stats data to output
+       */
+      function debugBoxWrite(para, stats) {
+        var str = "";
+        for (var key in stats) {
+          str += key + ": " + stats[key] + "\n";
+        }
+        para.innerText = str;
+      }
+
+      /**
+       * Constructor of DebugBox object,
+       * it insert an paragraph inside a div to the body, in view to display debug data
+       * @param {Number} interval - The log interval
+       * @constructor
+       */
+      util.DebugBox = function (interval) {
+        this.para = document.createElement("p");
+        this.div = document.createElement("div");
+        this.div.appendChild(this.para);
+        document.body.appendChild(this.div);
+
+        this.buttons = {};
+        this.canvas = {};
+        this.stats = {};
+        var updateInterval = interval || 300;
+        (function (localThis) {
+          setInterval(function () {
+            debugBoxWrite(localThis.para, localThis.stats);
+          }, updateInterval);
+        })(this);
+      };
+
+      /**
+       * Add stat data for log
+       * @param {String} key - The data key
+       * @param {*} value - The value
+       */
+      util.DebugBox.prototype.set = function (key, value) {
+        this.stats[key] = value;
+      };
+
+      /**
+       * Initialize stats in case where key does not exist, else
+       * increment value for key
+       * @param {String} key - The key to process
+       * @param {Number} incBy - Value to increment for given key (default: 1)
+       * @param {Number} init - Initial value in case where key does not exist (default: 0)
+       */
+      util.DebugBox.prototype.inc = function (key, incBy, init) {
+        if (!this.stats[key]) {
+          this.stats[key] = init || 0;
+        }
+        this.stats[key] += incBy || 1;
+      };
+
+      /**
+       * Create a button and register the given function to the button click event
+       * @param {String} name - The button name to link
+       * @param {Function} func - The onClick callback
+       */
+      util.DebugBox.prototype.addButton = function (name, func) {
+        if (!this.buttons[name]) {
+          this.buttons[name] = document.createElement("button");
+          this.div.appendChild(this.buttons[name]);
+        }
+        var button = this.buttons[name];
+        this.buttons[name] = button;
+        button.addEventListener("click", func);
+        button.innerText = name;
+      };
+
+      /**
+       * Search for a canvas elemenet with name, or create on if not exist.
+       * Then send the canvas element as callback parameter.
+       * @param {String} name - The canvas name to send/create
+       * @param {Function} func - The callback function where send canvas
+       */
+      util.DebugBox.prototype.show = function (name, func) {
+        if (!this.canvas[name]) {
+          this.canvas[name] = document.createElement("canvas");
+          this.div.appendChild(this.canvas[name]);
+        }
+        var canvas = this.canvas[name];
+        canvas.getContext("2d").clearRect(0, 0, canvas.width, canvas.height);
+        func(canvas);
+      };
+
+      /**
+       * Kalman Filter constructor
+       * Kalman filters work by reducing the amount of noise in a models.
+       * https://blog.cordiner.net/2011/05/03/object-tracking-using-a-kalman-filter-matlab/
+       *
+       * @param {Array.<Array.<Number>>} F - transition matrix
+       * @param {Array.<Array.<Number>>} Q - process noise matrix
+       * @param {Array.<Array.<Number>>} H - maps between measurement vector and noise matrix
+       * @param {Array.<Array.<Number>>} R - defines measurement error of the device
+       * @param {Array} P_initial - the initial state
+       * @param {Array} X_initial - the initial state of the device
+       */
+      util.KalmanFilter = function (F, H, Q, R, P_initial, X_initial) {
+        this.F = F; // State transition matrix
+        this.Q = Q; // Process noise matrix
+        this.H = H; // Transformation matrix
+        this.R = R; // Measurement Noise
+        this.P = P_initial; //Initial covariance matrix
+        this.X = X_initial; //Initial guess of measurement
+      };
+
+      /**
+       * Get Kalman next filtered value and update the internal state
+       * @param {Array} z - the new measurement
+       * @return {Array}
+       */
+      util.KalmanFilter.prototype.update = function (z) {
+        // Here, we define all the different matrix operations we will need
+        var add = numeric.add,
+          sub = numeric.sub,
+          inv = numeric.inv,
+          identity = numeric.identity;
+        var mult = src_mat.mult,
+          transpose = src_mat.transpose;
+        //TODO cache variables like the transpose of H
+
+        // prediction: X = F * X  |  P = F * P * F' + Q
+        var X_p = mult(this.F, this.X); //Update state vector
+        var P_p = add(mult(mult(this.F, this.P), transpose(this.F)), this.Q); //Predicted covaraince
+
+        //Calculate the update values
+        var y = sub(z, mult(this.H, X_p)); // This is the measurement error (between what we expect and the actual value)
+        var S = add(mult(mult(this.H, P_p), transpose(this.H)), this.R); //This is the residual covariance (the error in the covariance)
+
+        // kalman multiplier: K = P * H' * (H * P * H' + R)^-1
+        var K = mult(P_p, mult(transpose(this.H), inv(S))); //This is the Optimal Kalman Gain
+
+        //We need to change Y into it's column vector form
+        for (var i = 0; i < y.length; i++) {
+          y[i] = [y[i]];
+        }
+
+        //Now we correct the internal values of the model
+        // correction: X = X + K * (m - H * X)  |  P = (I - K * H) * P
+        this.X = add(X_p, mult(K, y));
+        this.P = mult(sub(identity(K.length), mult(K, this.H)), P_p);
+        return transpose(mult(this.H, this.X))[0]; //Transforms the predicted state back into it's measurement form
+      };
+
+      /* harmony default export */ var src_util = util;
+
+      // CONCATENATED MODULE: ./src/ridgeReg.mjs
+
+      const ridgeReg_reg = {};
+      var ridgeParameter = Math.pow(10, -5);
+      var dataWindow = 700;
+      var trailDataWindow = 10;
+
+      /**
+       * Performs ridge regression, according to the Weka code.
+       * @param {Array} y - corresponds to screen coordinates (either x or y) for each of n click events
+       * @param {Array.<Array.<Number>>} X - corresponds to gray pixel features (120 pixels for both eyes) for each of n clicks
+       * @param {Array} k - ridge parameter
+       * @return{Array} regression coefficients
+       */
+      function ridge(y, X, k) {
+        var nc = X[0].length;
+        var m_Coefficients = new Array(nc);
+        var xt = src_mat.transpose(X);
+        var solution = new Array();
+        var success = true;
+        do {
+          var ss = src_mat.mult(xt, X);
+          // Set ridge regression adjustment
+          for (var i = 0; i < nc; i++) {
+            ss[i][i] = ss[i][i] + k;
+          }
+
+          // Carry out the regression
+          var bb = src_mat.mult(xt, y);
+          for (var i = 0; i < nc; i++) {
+            m_Coefficients[i] = bb[i][0];
+          }
+          try {
+            var n = m_Coefficients.length !== 0 ? m_Coefficients.length / m_Coefficients.length : 0;
+            if (m_Coefficients.length * n !== m_Coefficients.length) {
+              console.log("Array length must be a multiple of m");
+            }
+            solution =
+              ss.length === ss[0].length
+                ? numeric_1_2_6.LUsolve(numeric_1_2_6.LU(ss, true), bb)
+                : src_mat.QRDecomposition(ss, bb);
+
+            for (var i = 0; i < nc; i++) {
+              m_Coefficients[i] = solution[i];
+            }
+            success = true;
+          } catch (ex) {
+            k *= 10;
+            console.log(ex);
+            success = false;
+          }
+        } while (!success);
+        return m_Coefficients;
+      }
+
+      //TODO: still usefull ???
+      /**
+       *
+       * @returns {Number}
+       */
+      function getCurrentFixationIndex() {
+        var index = 0;
+        var recentX = this.screenXTrailArray.get(0);
+        var recentY = this.screenYTrailArray.get(0);
+        for (var i = this.screenXTrailArray.length - 1; i >= 0; i--) {
+          var currX = this.screenXTrailArray.get(i);
+          var currY = this.screenYTrailArray.get(i);
+          var euclideanDistance = Math.sqrt(
+            Math.pow(currX - recentX, 2) + Math.pow(currY - recentY, 2)
+          );
+          if (euclideanDistance > 72) {
+            return i + 1;
+          }
+        }
+        return i;
+      }
+
+      /**
+       * Constructor of RidgeReg object,
+       * this object allow to perform ridge regression
+       * @constructor
+       */
+      ridgeReg_reg.RidgeReg = function () {
+        this.init();
+      };
+
+      /**
+       * Initialize new arrays and initialize Kalman filter.
+       */
+      ridgeReg_reg.RidgeReg.prototype.init = function () {
+        this.screenXClicksArray = new src_util.DataWindow(dataWindow);
+        this.screenYClicksArray = new src_util.DataWindow(dataWindow);
+        this.eyeFeaturesClicks = new src_util.DataWindow(dataWindow);
+
+        //sets to one second worth of cursor trail
+        this.trailTime = 1000;
+        this.trailDataWindow = this.trailTime / src_params.moveTickSize;
+        this.screenXTrailArray = new src_util.DataWindow(trailDataWindow);
+        this.screenYTrailArray = new src_util.DataWindow(trailDataWindow);
+        this.eyeFeaturesTrail = new src_util.DataWindow(trailDataWindow);
+        this.trailTimes = new src_util.DataWindow(trailDataWindow);
+
+        this.dataClicks = new src_util.DataWindow(dataWindow);
+        this.dataTrail = new src_util.DataWindow(trailDataWindow);
+
+        // Initialize Kalman filter [20200608 xk] what do we do about parameters?
+        // [20200611 xk] unsure what to do w.r.t. dimensionality of these matrices. So far at least
+        //               by my own anecdotal observation a 4x1 x vector seems to work alright
+        var F = [
+          [1, 0, 1, 0],
+          [0, 1, 0, 1],
+          [0, 0, 1, 0],
+          [0, 0, 0, 1],
+        ];
+
+        //Parameters Q and R may require some fine tuning
+        var Q = [
+          [1 / 4, 0, 1 / 2, 0],
+          [0, 1 / 4, 0, 1 / 2],
+          [1 / 2, 0, 1, 0],
+          [0, 1 / 2, 0, 1],
+        ]; // * delta_t
+        var delta_t = 1 / 10; // The amount of time between frames
+        Q = numeric_1_2_6.mul(Q, delta_t);
+
+        var H = [
+          [1, 0, 0, 0, 0, 0],
+          [0, 1, 0, 0, 0, 0],
+          [0, 0, 1, 0, 0, 0],
+          [0, 0, 0, 1, 0, 0],
+        ];
+        var H = [
+          [1, 0, 0, 0],
+          [0, 1, 0, 0],
+        ];
+        var pixel_error = 47; //We will need to fine tune this value [20200611 xk] I just put a random value here
+
+        //This matrix represents the expected measurement error
+        var R = numeric_1_2_6.mul(numeric_1_2_6.identity(2), pixel_error);
+
+        var P_initial = numeric_1_2_6.mul(numeric_1_2_6.identity(4), 0.0001); //Initial covariance matrix
+        var x_initial = [[500], [500], [0], [0]]; // Initial measurement matrix
+
+        this.kalman = new src_util.KalmanFilter(F, H, Q, R, P_initial, x_initial);
+      };
+
+      /**
+       * Add given data from eyes
+       * @param {Object} eyes - eyes where extract data to add
+       * @param {Object} screenPos - The current screen point
+       * @param {Object} type - The type of performed action
+       */
+      ridgeReg_reg.RidgeReg.prototype.addData = function (eyes, screenPos, type) {
+        if (!eyes) {
+          return;
+        }
+        //not doing anything with blink at present
+        // if (eyes.left.blink || eyes.right.blink) {
+        //   return;
+        // }
+        //why are we pushing these as arrays rather than single elements?
+        if (type === "click") {
+          this.screenXClicksArray.push([screenPos[0]]);
+          this.screenYClicksArray.push([screenPos[1]]);
+
+          this.eyeFeaturesClicks.push(src_util.getEyeFeats(eyes));
+          this.dataClicks.push({ eyes: eyes, screenPos: screenPos, type: type });
+        } else if (type === "move") {
+          this.screenXTrailArray.push([screenPos[0]]);
+          this.screenYTrailArray.push([screenPos[1]]);
+
+          this.eyeFeaturesTrail.push(src_util.getEyeFeats(eyes));
+          this.trailTimes.push(performance.now());
+          this.dataTrail.push({ eyes: eyes, screenPos: screenPos, type: type });
+        }
+
+        // [20180730 JT] Why do we do this? It doesn't return anything...
+        // But as JS is pass by reference, it still affects it.
+        //
+        // Causes problems for when we want to call 'addData' twice in a row on the same object, but perhaps with different screenPos or types (think multiple interactions within one video frame)
+        //eyes.left.patch = Array.from(eyes.left.patch.data);
+        //eyes.right.patch = Array.from(eyes.right.patch.data);
+      };
+
+      /**
+       * Try to predict coordinates from pupil data
+       * after apply linear regression on data set
+       * @param {Object} eyesObj - The current user eyes object
+       * @returns {Object}
+       */
+      ridgeReg_reg.RidgeReg.prototype.predict = function (eyesObj) {
+        if (!eyesObj || this.eyeFeaturesClicks.length === 0) {
+          return null;
+        }
+        var acceptTime = performance.now() - this.trailTime;
+        var trailX = [];
+        var trailY = [];
+        var trailFeat = [];
+        for (var i = 0; i < this.trailDataWindow; i++) {
+          if (this.trailTimes.get(i) > acceptTime) {
+            trailX.push(this.screenXTrailArray.get(i));
+            trailY.push(this.screenYTrailArray.get(i));
+            trailFeat.push(this.eyeFeaturesTrail.get(i));
+          }
+        }
+
+        var screenXArray = this.screenXClicksArray.data.concat(trailX);
+        var screenYArray = this.screenYClicksArray.data.concat(trailY);
+        var eyeFeatures = this.eyeFeaturesClicks.data.concat(trailFeat);
+
+        var coefficientsX = ridge(screenXArray, eyeFeatures, ridgeParameter);
+        var coefficientsY = ridge(screenYArray, eyeFeatures, ridgeParameter);
+
+        var eyeFeats = src_util.getEyeFeats(eyesObj);
+        var predictedX = 0;
+        for (var i = 0; i < eyeFeats.length; i++) {
+          predictedX += eyeFeats[i] * coefficientsX[i];
+        }
+        var predictedY = 0;
+        for (var i = 0; i < eyeFeats.length; i++) {
+          predictedY += eyeFeats[i] * coefficientsY[i];
+        }
+
+        predictedX = Math.floor(predictedX);
+        predictedY = Math.floor(predictedY);
+
+        if (src_params.applyKalmanFilter) {
+          // Update Kalman model, and get prediction
+          var newGaze = [predictedX, predictedY]; // [20200607 xk] Should we use a 1x4 vector?
+          newGaze = this.kalman.update(newGaze);
+
+          return {
+            x: newGaze[0],
+            y: newGaze[1],
+          };
+        } else {
+          return {
+            x: predictedX,
+            y: predictedY,
+          };
+        }
+      };
+
+      /**
+       * Add given data to current data set then,
+       * replace current data member with given data
+       * @param {Array.<Object>} data - The data to set
+       */
+      ridgeReg_reg.RidgeReg.prototype.setData = function (data) {
+        for (var i = 0; i < data.length; i++) {
+          // Clone data array
+          var leftData = new Uint8ClampedArray(data[i].eyes.left.patch.data);
+          var rightData = new Uint8ClampedArray(data[i].eyes.right.patch.data);
+          // Duplicate ImageData object
+          data[i].eyes.left.patch = new ImageData(
+            leftData,
+            data[i].eyes.left.width,
+            data[i].eyes.left.height
+          );
+          data[i].eyes.right.patch = new ImageData(
+            rightData,
+            data[i].eyes.right.width,
+            data[i].eyes.right.height
+          );
+
+          // Add those data objects to model
+          this.addData(data[i].eyes, data[i].screenPos, data[i].type);
+        }
+      };
+
+      /**
+       * Return the data
+       * @returns {Array.<Object>|*}
+       */
+      ridgeReg_reg.RidgeReg.prototype.getData = function () {
+        return this.dataClicks.data;
+      };
+
+      /**
+       * The RidgeReg object name
+       * @type {string}
+       */
+      ridgeReg_reg.RidgeReg.prototype.name = "ridge";
+
+      /* harmony default export */ var ridgeReg = ridgeReg_reg;
+
+      // CONCATENATED MODULE: ./src/ridgeWeightedReg.mjs
+
+      const ridgeWeightedReg_reg = {};
+
+      var ridgeWeightedReg_ridgeParameter = Math.pow(10, -5);
+      var ridgeWeightedReg_dataWindow = 700;
+      var ridgeWeightedReg_trailDataWindow = 10;
+
+      /**
+       * Performs ridge regression, according to the Weka code.
+       * @param {Array} y - corresponds to screen coordinates (either x or y) for each of n click events
+       * @param {Array.<Array.<Number>>} X - corresponds to gray pixel features (120 pixels for both eyes) for each of n clicks
+       * @param {Array} k - ridge parameter
+       * @return{Array} regression coefficients
+       */
+      function ridgeWeightedReg_ridge(y, X, k) {
+        var nc = X[0].length;
+        var m_Coefficients = new Array(nc);
+        var xt = src_mat.transpose(X);
+        var solution = new Array();
+        var success = true;
+        do {
+          var ss = src_mat.mult(xt, X);
+          // Set ridge regression adjustment
+          for (var i = 0; i < nc; i++) {
+            ss[i][i] = ss[i][i] + k;
+          }
+
+          // Carry out the regression
+          var bb = src_mat.mult(xt, y);
+          for (var i = 0; i < nc; i++) {
+            m_Coefficients[i] = bb[i][0];
+          }
+          try {
+            var n = m_Coefficients.length !== 0 ? m_Coefficients.length / m_Coefficients.length : 0;
+            if (m_Coefficients.length * n !== m_Coefficients.length) {
+              console.log("Array length must be a multiple of m");
+            }
+            solution =
+              ss.length === ss[0].length
+                ? numeric_1_2_6.LUsolve(numeric_1_2_6.LU(ss, true), bb)
+                : webgazer.mat.QRDecomposition(ss, bb);
+
+            for (var i = 0; i < nc; i++) {
+              m_Coefficients[i] = solution[i];
+            }
+            success = true;
+          } catch (ex) {
+            k *= 10;
+            console.log(ex);
+            success = false;
+          }
+        } while (!success);
+        return m_Coefficients;
+      }
+
+      /**
+       * Compute eyes size as gray histogram
+       * @param {Object} eyes - The eyes where looking for gray histogram
+       * @returns {Array.<T>} The eyes gray level histogram
+       */
+
+      //TODO: still usefull ???
+      /**
+       *
+       * @returns {Number}
+       */
+      function ridgeWeightedReg_getCurrentFixationIndex() {
+        var index = 0;
+        var recentX = this.screenXTrailArray.get(0);
+        var recentY = this.screenYTrailArray.get(0);
+        for (var i = this.screenXTrailArray.length - 1; i >= 0; i--) {
+          var currX = this.screenXTrailArray.get(i);
+          var currY = this.screenYTrailArray.get(i);
+          var euclideanDistance = Math.sqrt(
+            Math.pow(currX - recentX, 2) + Math.pow(currY - recentY, 2)
+          );
+          if (euclideanDistance > 72) {
+            return i + 1;
+          }
+        }
+        return i;
+      }
+
+      /**
+       * Constructor of RidgeWeightedReg object
+       * @constructor
+       */
+      ridgeWeightedReg_reg.RidgeWeightedReg = function () {
+        this.init();
+      };
+
+      /**
+       * Initialize new arrays and initialize Kalman filter.
+       */
+      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.init = function () {
+        this.screenXClicksArray = new src_util.DataWindow(ridgeWeightedReg_dataWindow);
+        this.screenYClicksArray = new src_util.DataWindow(ridgeWeightedReg_dataWindow);
+        this.eyeFeaturesClicks = new src_util.DataWindow(ridgeWeightedReg_dataWindow);
+
+        //sets to one second worth of cursor trail
+        this.trailTime = 1000;
+        this.trailDataWindow = this.trailTime / src_params.moveTickSize;
+        this.screenXTrailArray = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
+        this.screenYTrailArray = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
+        this.eyeFeaturesTrail = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
+        this.trailTimes = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
+
+        this.dataClicks = new src_util.DataWindow(ridgeWeightedReg_dataWindow);
+        this.dataTrail = new src_util.DataWindow(ridgeWeightedReg_trailDataWindow);
+
+        // Initialize Kalman filter [20200608 xk] what do we do about parameters?
+        // [20200611 xk] unsure what to do w.r.t. dimensionality of these matrices. So far at least
+        //               by my own anecdotal observation a 4x1 x vector seems to work alright
+        var F = [
+          [1, 0, 1, 0],
+          [0, 1, 0, 1],
+          [0, 0, 1, 0],
+          [0, 0, 0, 1],
+        ];
+
+        //Parameters Q and R may require some fine tuning
+        var Q = [
+          [1 / 4, 0, 1 / 2, 0],
+          [0, 1 / 4, 0, 1 / 2],
+          [1 / 2, 0, 1, 0],
+          [0, 1 / 2, 0, 1],
+        ]; // * delta_t
+        var delta_t = 1 / 10; // The amount of time between frames
+        Q = numeric_1_2_6.mul(Q, delta_t);
+
+        var H = [
+          [1, 0, 0, 0, 0, 0],
+          [0, 1, 0, 0, 0, 0],
+          [0, 0, 1, 0, 0, 0],
+          [0, 0, 0, 1, 0, 0],
+        ];
+        var H = [
+          [1, 0, 0, 0],
+          [0, 1, 0, 0],
+        ];
+        var pixel_error = 47; //We will need to fine tune this value [20200611 xk] I just put a random value here
+
+        //This matrix represents the expected measurement error
+        var R = numeric_1_2_6.mul(numeric_1_2_6.identity(2), pixel_error);
+
+        var P_initial = numeric_1_2_6.mul(numeric_1_2_6.identity(4), 0.0001); //Initial covariance matrix
+        var x_initial = [[500], [500], [0], [0]]; // Initial measurement matrix
+
+        this.kalman = new src_util.KalmanFilter(F, H, Q, R, P_initial, x_initial);
+      };
+
+      /**
+       * Add given data from eyes
+       * @param {Object} eyes - eyes where extract data to add
+       * @param {Object} screenPos - The current screen point
+       * @param {Object} type - The type of performed action
+       */
+      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.addData = function (eyes, screenPos, type) {
+        if (!eyes) {
+          return;
+        }
+        //not doing anything with blink at present
+        // if (eyes.left.blink || eyes.right.blink) {
+        //     return;
+        // }
+        if (type === "click") {
+          this.screenXClicksArray.push([screenPos[0]]);
+          this.screenYClicksArray.push([screenPos[1]]);
+
+          this.eyeFeaturesClicks.push(src_util.getEyeFeats(eyes));
+          this.dataClicks.push({ eyes: eyes, screenPos: screenPos, type: type });
+        } else if (type === "move") {
+          this.screenXTrailArray.push([screenPos[0]]);
+          this.screenYTrailArray.push([screenPos[1]]);
+
+          this.eyeFeaturesTrail.push(src_util.getEyeFeats(eyes));
+          this.trailTimes.push(performance.now());
+          this.dataTrail.push({ eyes: eyes, screenPos: screenPos, type: type });
+        }
+
+        // [20180730 JT] Why do we do this? It doesn't return anything...
+        // But as JS is pass by reference, it still affects it.
+        //
+        // Causes problems for when we want to call 'addData' twice in a row on the same object, but perhaps with different screenPos or types (think multiple interactions within one video frame)
+        //eyes.left.patch = Array.from(eyes.left.patch.data);
+        //eyes.right.patch = Array.from(eyes.right.patch.data);
+      };
+
+      /**
+       * Try to predict coordinates from pupil data
+       * after apply linear regression on data set
+       * @param {Object} eyesObj - The current user eyes object
+       * @returns {Object}
+       */
+      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.predict = function (eyesObj) {
+        if (!eyesObj || this.eyeFeaturesClicks.length === 0) {
+          return null;
+        }
+        var acceptTime = performance.now() - this.trailTime;
+        var trailX = [];
+        var trailY = [];
+        var trailFeat = [];
+        for (var i = 0; i < this.trailDataWindow; i++) {
+          if (this.trailTimes.get(i) > acceptTime) {
+            trailX.push(this.screenXTrailArray.get(i));
+            trailY.push(this.screenYTrailArray.get(i));
+            trailFeat.push(this.eyeFeaturesTrail.get(i));
+          }
+        }
+
+        var len = this.eyeFeaturesClicks.data.length;
+        var weightedEyeFeats = Array(len);
+        var weightedXArray = Array(len);
+        var weightedYArray = Array(len);
+        for (var i = 0; i < len; i++) {
+          var weight = Math.sqrt(1 / (len - i)); // access from oldest to newest so should start with low weight and increase steadily
+          //abstraction is leaking...
+          var trueIndex = this.eyeFeaturesClicks.getTrueIndex(i);
+          for (var j = 0; j < this.eyeFeaturesClicks.data[trueIndex].length; j++) {
+            var val = this.eyeFeaturesClicks.data[trueIndex][j] * weight;
+            if (weightedEyeFeats[trueIndex] !== undefined) {
+              weightedEyeFeats[trueIndex].push(val);
+            } else {
+              weightedEyeFeats[trueIndex] = [val];
+            }
+          }
+          weightedXArray[trueIndex] = this.screenXClicksArray
+            .get(i)
+            .slice(0, this.screenXClicksArray.get(i).length);
+          weightedYArray[trueIndex] = this.screenYClicksArray
+            .get(i)
+            .slice(0, this.screenYClicksArray.get(i).length);
+          weightedXArray[i][0] = weightedXArray[i][0] * weight;
+          weightedYArray[i][0] = weightedYArray[i][0] * weight;
+        }
+
+        var screenXArray = weightedXArray.concat(trailX);
+        var screenYArray = weightedYArray.concat(trailY);
+        var eyeFeatures = weightedEyeFeats.concat(trailFeat);
+
+        var coefficientsX = ridgeWeightedReg_ridge(
+          screenXArray,
+          eyeFeatures,
+          ridgeWeightedReg_ridgeParameter
+        );
+        var coefficientsY = ridgeWeightedReg_ridge(
+          screenYArray,
+          eyeFeatures,
+          ridgeWeightedReg_ridgeParameter
+        );
+
+        var eyeFeats = src_util.getEyeFeats(eyesObj);
+        var predictedX = 0;
+        for (var i = 0; i < eyeFeats.length; i++) {
+          predictedX += eyeFeats[i] * coefficientsX[i];
+        }
+        var predictedY = 0;
+        for (var i = 0; i < eyeFeats.length; i++) {
+          predictedY += eyeFeats[i] * coefficientsY[i];
+        }
+
+        predictedX = Math.floor(predictedX);
+        predictedY = Math.floor(predictedY);
+
+        if (src_params.applyKalmanFilter) {
+          // Update Kalman model, and get prediction
+          var newGaze = [predictedX, predictedY]; // [20200607 xk] Should we use a 1x4 vector?
+          newGaze = this.kalman.update(newGaze);
+
+          return {
+            x: newGaze[0],
+            y: newGaze[1],
+          };
+        } else {
+          return {
+            x: predictedX,
+            y: predictedY,
+          };
+        }
+      };
+
+      /**
+       * Add given data to current data set then,
+       * replace current data member with given data
+       * @param {Array.<Object>} data - The data to set
+       */
+      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.setData = function (data) {
+        for (var i = 0; i < data.length; i++) {
+          // [20200611 xk] Previous comment said this was a kludge, but it seems like this is the best solution
+
+          // Clone data array
+          var leftData = new Uint8ClampedArray(data[i].eyes.left.patch.data);
+          var rightData = new Uint8ClampedArray(data[i].eyes.right.patch.data);
+          // Duplicate ImageData object
+          data[i].eyes.left.patch = new ImageData(
+            leftData,
+            data[i].eyes.left.width,
+            data[i].eyes.left.height
+          );
+          data[i].eyes.right.patch = new ImageData(
+            rightData,
+            data[i].eyes.right.width,
+            data[i].eyes.right.height
+          );
+
+          this.addData(data[i].eyes, data[i].screenPos, data[i].type);
+        }
+      };
+
+      /**
+       * Return the data
+       * @returns {Array.<Object>|*}
+       */
+      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.getData = function () {
+        return this.dataClicks.data;
+      };
+
+      /**
+       * The RidgeWeightedReg object name
+       * @type {string}
+       */
+      ridgeWeightedReg_reg.RidgeWeightedReg.prototype.name = "ridge";
+
+      /* harmony default export */ var ridgeWeightedReg = ridgeWeightedReg_reg;
+
+      // CONCATENATED MODULE: ./src/ridgeRegThreaded.mjs
+
+      const ridgeRegThreaded_reg = {};
+
+      var ridgeRegThreaded_ridgeParameter = Math.pow(10, -5);
+      var ridgeRegThreaded_dataWindow = 700;
+      var weights = { X: [0], Y: [0] };
+      var ridgeRegThreaded_trailDataWindow = 10;
+
+      /**
+       * Constructor of RidgeRegThreaded object,
+       * it retrieve data window, and prepare a worker,
+       * this object allow to perform threaded ridge regression
+       * @constructor
+       */
+      ridgeRegThreaded_reg.RidgeRegThreaded = function (workerScriptURL) {
+        this.init(workerScriptURL);
+      };
+
+      /**
+       * Initialize new arrays and initialize Kalman filter.
+       */
+      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.init = function (workerScriptURL) {
+        this.screenXClicksArray = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
+        this.screenYClicksArray = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
+        this.eyeFeaturesClicks = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
+
+        this.screenXTrailArray = new src_util.DataWindow(ridgeRegThreaded_trailDataWindow);
+        this.screenYTrailArray = new src_util.DataWindow(ridgeRegThreaded_trailDataWindow);
+        this.eyeFeaturesTrail = new src_util.DataWindow(ridgeRegThreaded_trailDataWindow);
+
+        this.dataClicks = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
+        this.dataTrail = new src_util.DataWindow(ridgeRegThreaded_dataWindow);
+
+        // Place the src/ridgeworker.js file into the same directory as your html file.
+        if (!this.worker) {
+          //this.worker = new Worker('ridgeWorker.mjs'); // [20200708] TODO: Figure out how to make this inline
+          this.worker = new Worker(workerScriptURL);
+          this.worker.onerror = function (err) {
+            console.log(err.message);
+          };
+          this.worker.onmessage = function (evt) {
+            weights.X = evt.data.X;
+            weights.Y = evt.data.Y;
+          };
+          console.log("initialized worker");
+        }
+
+        // Initialize Kalman filter [20200608 xk] what do we do about parameters?
+        // [20200611 xk] unsure what to do w.r.t. dimensionality of these matrices. So far at least
+        //               by my own anecdotal observation a 4x1 x vector seems to work alright
+        var F = [
+          [1, 0, 1, 0],
+          [0, 1, 0, 1],
+          [0, 0, 1, 0],
+          [0, 0, 0, 1],
+        ];
+
+        //Parameters Q and R may require some fine tuning
+        var Q = [
+          [1 / 4, 0, 1 / 2, 0],
+          [0, 1 / 4, 0, 1 / 2],
+          [1 / 2, 0, 1, 0],
+          [0, 1 / 2, 0, 1],
+        ]; // * delta_t
+        var delta_t = 1 / 10; // The amount of time between frames
+        Q = numeric_1_2_6.mul(Q, delta_t);
+
+        var H = [
+          [1, 0, 0, 0, 0, 0],
+          [0, 1, 0, 0, 0, 0],
+          [0, 0, 1, 0, 0, 0],
+          [0, 0, 0, 1, 0, 0],
+        ];
+        var H = [
+          [1, 0, 0, 0],
+          [0, 1, 0, 0],
+        ];
+        var pixel_error = 47; //We will need to fine tune this value [20200611 xk] I just put a random value here
+
+        //This matrix represents the expected measurement error
+        var R = numeric_1_2_6.mul(numeric_1_2_6.identity(2), pixel_error);
+
+        var P_initial = numeric_1_2_6.mul(numeric_1_2_6.identity(4), 0.0001); //Initial covariance matrix
+        var x_initial = [[500], [500], [0], [0]]; // Initial measurement matrix
+
+        this.kalman = new src_util.KalmanFilter(F, H, Q, R, P_initial, x_initial);
+      };
+
+      /**
+       * Add given data from eyes
+       * @param {Object} eyes - eyes where extract data to add
+       * @param {Object} screenPos - The current screen point
+       * @param {Object} type - The type of performed action
+       */
+      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.addData = function (eyes, screenPos, type) {
+        if (!eyes) {
+          return;
+        }
+        //not doing anything with blink at present
+        // if (eyes.left.blink || eyes.right.blink) {
+        //     return;
+        // }
+        this.worker.postMessage({
+          eyes: src_util.getEyeFeats(eyes),
+          screenPos: screenPos,
+          type: type,
+        });
+      };
+
+      /**
+       * Try to predict coordinates from pupil data
+       * after apply linear regression on data set
+       * @param {Object} eyesObj - The current user eyes object
+       * @returns {Object}
+       */
+      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.predict = function (eyesObj) {
+        // console.log('LOGGING..');
+        if (!eyesObj) {
+          return null;
+        }
+        var coefficientsX = weights.X;
+        var coefficientsY = weights.Y;
+
+        var eyeFeats = src_util.getEyeFeats(eyesObj);
+        var predictedX = 0,
+          predictedY = 0;
+        for (var i = 0; i < eyeFeats.length; i++) {
+          predictedX += eyeFeats[i] * coefficientsX[i];
+          predictedY += eyeFeats[i] * coefficientsY[i];
+        }
+
+        predictedX = Math.floor(predictedX);
+        predictedY = Math.floor(predictedY);
+
+        if (src_params.applyKalmanFilter) {
+          // Update Kalman model, and get prediction
+          var newGaze = [predictedX, predictedY]; // [20200607 xk] Should we use a 1x4 vector?
+          newGaze = this.kalman.update(newGaze);
+
+          return {
+            x: newGaze[0],
+            y: newGaze[1],
+          };
+        } else {
+          return {
+            x: predictedX,
+            y: predictedY,
+          };
+        }
+      };
+
+      /**
+       * Add given data to current data set then,
+       * replace current data member with given data
+       * @param {Array.<Object>} data - The data to set
+       */
+      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.setData = function (data) {
+        for (var i = 0; i < data.length; i++) {
+          // [20200611 xk] Previous comment said this was a kludge, but it seems like this is the best solution
+
+          // Clone data array
+          var leftData = new Uint8ClampedArray(data[i].eyes.left.patch.data);
+          var rightData = new Uint8ClampedArray(data[i].eyes.right.patch.data);
+          // Duplicate ImageData object
+          data[i].eyes.left.patch = new ImageData(
+            leftData,
+            data[i].eyes.left.width,
+            data[i].eyes.left.height
+          );
+          data[i].eyes.right.patch = new ImageData(
+            rightData,
+            data[i].eyes.right.width,
+            data[i].eyes.right.height
+          );
+
+          this.addData(data[i].eyes, data[i].screenPos, data[i].type);
+        }
+      };
+
+      /**
+       * Return the data
+       * @returns {Array.<Object>|*}
+       */
+      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.getData = function () {
+        return this.dataClicks.data;
+      };
+
+      /**
+       * The RidgeRegThreaded object name
+       * @type {string}
+       */
+      ridgeRegThreaded_reg.RidgeRegThreaded.prototype.name = "ridge";
+
+      /* harmony default export */ var ridgeRegThreaded = ridgeRegThreaded_reg;
+
+      // CONCATENATED MODULE: ./src/index.mjs
+
+      const src_webgazer = {};
+      src_webgazer.tracker = {};
+      src_webgazer.tracker.TFFaceMesh = facemesh;
+      src_webgazer.reg = ridgeReg;
+      src_webgazer.reg.RidgeWeightedReg = ridgeWeightedReg.RidgeWeightedReg;
+      src_webgazer.reg.RidgeRegThreaded = ridgeRegThreaded.RidgeRegThreaded;
+      src_webgazer.util = src_util;
+      src_webgazer.params = src_params;
+      src_webgazer.workerScriptURL = "ridgeWorker.mjs";
+
+      //PRIVATE VARIABLES
+
+      //video elements
+      var videoStream = null;
+      var videoContainerElement = null;
+      var videoElement = null;
+      var videoElementCanvas = null;
+      var faceOverlay = null;
+      var faceFeedbackBox = null;
+      var gazeDot = null;
+      // Why is this not in webgazer.params ?
+      var debugVideoLoc = "";
+
+      /*
+       * Initialises variables used to store accuracy eigenValues
+       * This is used by the calibration example file
+       */
+      var xPast50 = new Array(50);
+      var yPast50 = new Array(50);
+
+      // loop parameters
+      var clockStart = performance.now();
+      var latestEyeFeatures = null;
+      var latestGazeData = null;
+      var paused = false;
+      //registered callback for loop
+      var nopCallback = function (data, time) {};
+      var callback = nopCallback;
+
+      //Types that regression systems should handle
+      //Describes the source of data so that regression systems may ignore or handle differently the various generating events
+      var eventTypes = ["click", "move"];
+
+      //movelistener timeout clock parameters
+      var moveClock = performance.now();
+      //currently used tracker and regression models, defaults to clmtrackr and linear regression
+      var curTracker = new src_webgazer.tracker.TFFaceMesh();
+      var regs = [new src_webgazer.reg.RidgeReg()];
+      // var blinkDetector = new webgazer.BlinkDetector();
+
+      //lookup tables
+      var curTrackerMap = {
+        TFFacemesh: function () {
+          return new src_webgazer.tracker.TFFaceMesh();
+        },
+      };
+      var regressionMap = {
+        ridge: function () {
+          return new src_webgazer.reg.RidgeReg();
+        },
+        weightedRidge: function () {
+          return new src_webgazer.reg.RidgeWeightedReg();
+        },
+        threadedRidge: function () {
+          return new src_webgazer.reg.RidgeRegThreaded(src_webgazer.workerScriptURL);
+        },
+      };
+
+      //localstorage name
+      var localstorageDataLabel = "webgazerGlobalData";
+      var localstorageSettingsLabel = "webgazerGlobalSettings";
+      //settings object for future storage of settings
+      var settings = {};
+      var data = [];
+      var defaults = {
+        data: [],
+        settings: {},
+      };
+
+      //PRIVATE FUNCTIONS
+
+      /**
+       * Computes the size of the face overlay validation box depending on the size of the video preview window.
+       * @returns {Object} The dimensions of the validation box as top, left, width, height.
+       */
+      src_webgazer.computeValidationBoxSize = function () {
+        var vw = videoElement.videoWidth;
+        var vh = videoElement.videoHeight;
+        var pw = parseInt(videoElement.style.width);
+        var ph = parseInt(videoElement.style.height);
+
+        // Find the size of the box.
+        // Pick the smaller of the two video preview sizes
+        var smaller = Math.min(vw, vh);
+        var larger = Math.max(vw, vh);
+
+        // Overall scalar
+        var scalar = vw == larger ? pw / vw : ph / vh;
+
+        // Multiply this by 2/3, then adjust it to the size of the preview
+        var boxSize = smaller * src_webgazer.params.faceFeedbackBoxRatio * scalar;
+
+        // Set the boundaries of the face overlay validation box based on the preview
+        var topVal = (ph - boxSize) / 2;
+        var leftVal = (pw - boxSize) / 2;
+
+        // top, left, width, height
+        return [topVal, leftVal, boxSize, boxSize];
+      };
+
+      /**
+       * Checks if the pupils are in the position box on the video
+       * // TODO These are all wrong. The latestEyeFeatures will be in 'video' space not 'preview' space, and so need to be converted.
+       */
+      function checkEyesInValidationBox() {
+        if (faceFeedbackBox != null && latestEyeFeatures) {
+          var w = videoElement.videoWidth;
+          var h = videoElement.videoHeight;
+
+          // Find the size of the box.
+          // Pick the smaller of the two video preview sizes
+          var smaller = Math.min(w, h);
+          var boxSize = smaller * src_webgazer.params.faceFeedbackBoxRatio;
+
+          // Set the boundaries of the face overlay validation box based on the preview
+          var topBound = (h - boxSize) / 2;
+          var leftBound = (w - boxSize) / 2;
+          var rightBound = leftBound + boxSize;
+          var bottomBound = topBound + boxSize;
+
+          //get the x and y positions of the left and right eyes
+          var eyeLX = latestEyeFeatures.left.imagex;
+          var eyeLY = latestEyeFeatures.left.imagey;
+          var eyeRX = latestEyeFeatures.right.imagex;
+          var eyeRY = latestEyeFeatures.right.imagey;
+
+          var xPositions = false;
+          var yPositions = false;
+
+          //check if the x values for the left and right eye are within the
+          //validation box
+          if (eyeLX > leftBound && eyeLX < rightBound) {
+            if (eyeRX > leftBound && eyeRX < rightBound) {
+              xPositions = true;
+            }
+          }
+
+          //check if the y values for the left and right eye are within the
+          //validation box
+          if (eyeLY > topBound && eyeLY < bottomBound) {
+            if (eyeRY > topBound && eyeRY < bottomBound) {
+              yPositions = true;
+            }
+          }
+
+          //if the x and y values for both the left and right eye are within
+          //the validation box then the box border turns green, otherwise if
+          //the eyes are outside of the box the colour is red
+          if (xPositions && yPositions) {
+            faceFeedbackBox.style.border = "solid green";
+          } else {
+            faceFeedbackBox.style.border = "solid red";
+          }
+        } else faceFeedbackBox.style.border = "solid black";
+      }
+
+      /**
+       * This draws the point (x,y) onto the canvas in the HTML
+       * @param {colour} colour - The colour of the circle to plot
+       * @param {x} x - The x co-ordinate of the desired point to plot
+       * @param {y} y - The y co-ordinate of the desired point to plot
+       */
+      function drawCoordinates(colour, x, y) {
+        var ctx = document.getElementById("plotting_canvas").getContext("2d");
+        ctx.fillStyle = colour; // Red color
+        ctx.beginPath();
+        ctx.arc(x, y, 5, 0, Math.PI * 2, true);
+        ctx.fill();
+      }
+
+      /**
+       * Gets the pupil features by following the pipeline which threads an eyes object through each call:
+       * curTracker gets eye patches -> blink detector -> pupil detection
+       * @param {Canvas} canvas - a canvas which will have the video drawn onto it
+       * @param {Number} width - the width of canvas
+       * @param {Number} height - the height of canvas
+       */
+      function getPupilFeatures(canvas, width, height) {
+        if (!canvas) {
+          return;
+        }
+        try {
+          return curTracker.getEyePatches(canvas, width, height);
+        } catch (err) {
+          console.log("can't get pupil features ", err);
+          return null;
+        }
+      }
+
+      /**
+       * Gets the most current frame of video and paints it to a resized version of the canvas with width and height
+       * @param {Canvas} canvas - the canvas to paint the video on to
+       * @param {Number} width - the new width of the canvas
+       * @param {Number} height - the new height of the canvas
+       */
+      function paintCurrentFrame(canvas, width, height) {
+        if (canvas.width != width) {
+          canvas.width = width;
+        }
+        if (canvas.height != height) {
+          canvas.height = height;
+        }
+
+        var ctx = canvas.getContext("2d");
+        ctx.drawImage(videoElement, 0, 0, canvas.width, canvas.height);
+      }
+
+      /**
+       * Paints the video to a canvas and runs the prediction pipeline to get a prediction
+       * @param {Number|undefined} regModelIndex - The prediction index we're looking for
+       * @returns {*}
+       */
+      async function getPrediction(regModelIndex) {
+        // this allows getPrediction to work even when webgazer is paused, since the only necessary
+        // component for getPrediction in loop() is paintCurrentFrame().
+        if (paused) {
+          paintCurrentFrame(
+            videoElementCanvas,
+            videoElementCanvas.width,
+            videoElementCanvas.height
+          );
+        }
+        var time = performance.now();
+
+        var predictions = [];
+        // [20200617 xk] TODO: this call should be made async somehow. will take some work.
+        latestEyeFeatures = await getPupilFeatures(
+          videoElementCanvas,
+          videoElementCanvas.width,
+          videoElementCanvas.height
+        );
+
+        if (regs.length === 0) {
+          console.log("regression not set, call setRegression()");
+          return null;
+        }
+        for (var reg in regs) {
+          predictions.push(regs[reg].predict(latestEyeFeatures));
+        }
+        if (regModelIndex !== undefined) {
+          return predictions[regModelIndex] === null
+            ? null
+            : {
+                x: predictions[regModelIndex].x,
+                y: predictions[regModelIndex].y,
+                eyeFeatures: latestEyeFeatures,
+                t: time,
+              };
+        } else {
+          return predictions.length === 0 || predictions[0] === null
+            ? null
+            : {
+                x: predictions[0].x,
+                y: predictions[0].y,
+                eyeFeatures: latestEyeFeatures,
+                all: predictions,
+                t: time,
+              };
+        }
+      }
+
+      /**
+       * Runs every available animation frame if webgazer is not paused
+       */
+      var smoothingVals = new src_webgazer.util.DataWindow(4);
+      var src_k = 0;
+
+      async function loop() {
+        if (!paused) {
+          // [20200617 XK] TODO: there is currently lag between the camera input and the face overlay. This behavior
+          // is not seen in the facemesh demo. probably need to optimize async implementation. I think the issue lies
+          // in the implementation of getPrediction().
+
+          // Paint the latest video frame into the canvas which will be analyzed by WebGazer
+          // [20180729 JT] Why do we need to do this? clmTracker does this itself _already_, which is just duplicating the work.
+          // Is it because other trackers need a canvas instead of an img/video element?
+          paintCurrentFrame(
+            videoElementCanvas,
+            videoElementCanvas.width,
+            videoElementCanvas.height
+          );
+
+          // Get gaze prediction (ask clm to track; pass the data to the regressor; get back a prediction)
+          latestGazeData = getPrediction();
+          // Count time
+          var elapsedTime = performance.now() - clockStart;
+
+          // Draw face overlay
+          if (src_webgazer.params.showFaceOverlay) {
+            // Get tracker object
+            var tracker = src_webgazer.getTracker();
+            faceOverlay
+              .getContext("2d")
+              .clearRect(0, 0, videoElement.videoWidth, videoElement.videoHeight);
+            tracker.drawFaceOverlay(faceOverlay.getContext("2d"), tracker.getPositions());
+          }
+
+          // Feedback box
+          // Check that the eyes are inside of the validation box
+          if (src_webgazer.params.showFaceFeedbackBox) checkEyesInValidationBox();
+
+          latestGazeData = await latestGazeData;
+
+          // [20200623 xk] callback to function passed into setGazeListener(fn)
+          callback(latestGazeData, elapsedTime);
+
+          if (latestGazeData) {
+            // [20200608 XK] Smoothing across the most recent 4 predictions, do we need this with Kalman filter?
+            smoothingVals.push(latestGazeData);
+            var x = 0;
+            var y = 0;
+            var len = smoothingVals.length;
+            for (var d in smoothingVals.data) {
+              x += smoothingVals.get(d).x;
+              y += smoothingVals.get(d).y;
+            }
+
+            var pred = src_webgazer.util.bound({ x: x / len, y: y / len });
+
+            if (src_webgazer.params.storingPoints) {
+              drawCoordinates("blue", pred.x, pred.y); //draws the previous predictions
+              //store the position of the past fifty occuring tracker preditions
+              src_webgazer.storePoints(pred.x, pred.y, src_k);
+              src_k++;
+              if (src_k == 50) {
+                src_k = 0;
+              }
+            }
+            // GazeDot
+            if (src_webgazer.params.showGazeDot) {
+              gazeDot.style.display = "block";
+            }
+            gazeDot.style.transform = "translate3d(" + pred.x + "px," + pred.y + "px,0)";
+          } else {
+            gazeDot.style.display = "none";
+          }
+
+          requestAnimationFrame(loop);
+        }
+      }
+
+      //is problematic to test
+      //because latestEyeFeatures is not set in many cases
+
+      /**
+       * Records screen position data based on current pupil feature and passes it
+       * to the regression model.
+       * @param {Number} x - The x screen position
+       * @param {Number} y - The y screen position
+       * @param {String} eventType - The event type to store
+       * @returns {null}
+       */
+      var recordScreenPosition = function (x, y, eventType) {
+        if (paused) {
+          return;
+        }
+        if (regs.length === 0) {
+          console.log("regression not set, call setRegression()");
+          return null;
+        }
+        for (var reg in regs) {
+          if (latestEyeFeatures) regs[reg].addData(latestEyeFeatures, [x, y], eventType);
+        }
+      };
+
+      /**
+       * Records click data and passes it to the regression model
+       * @param {Event} event - The listened event
+       */
+      var clickListener = async function (event) {
+        recordScreenPosition(event.clientX, event.clientY, eventTypes[0]); // eventType[0] === 'click'
+
+        if (window.saveDataAcrossSessions) {
+          // Each click stores the next data point into localforage.
+          await setGlobalData();
+
+          // // Debug line
+          // console.log('Model size: ' + JSON.stringify(await localforage.getItem(localstorageDataLabel)).length / 1000000 + 'MB');
+        }
+      };
+
+      /**
+       * Records mouse movement data and passes it to the regression model
+       * @param {Event} event - The listened event
+       */
+      var moveListener = function (event) {
+        if (paused) {
+          return;
+        }
+
+        var now = performance.now();
+        if (now < moveClock + src_webgazer.params.moveTickSize) {
+          return;
+        } else {
+          moveClock = now;
+        }
+        recordScreenPosition(event.clientX, event.clientY, eventTypes[1]); //eventType[1] === 'move'
+      };
+
+      /**
+       * Add event listeners for mouse click and move.
+       */
+      var addMouseEventListeners = function () {
+        //third argument set to true so that we get event on 'capture' instead of 'bubbling'
+        //this prevents a client using event.stopPropagation() preventing our access to the click
+        document.addEventListener("click", clickListener, true);
+        document.addEventListener("mousemove", moveListener, true);
+      };
+
+      /**
+       * Remove event listeners for mouse click and move.
+       */
+      var removeMouseEventListeners = function () {
+        // must set third argument to same value used in addMouseEventListeners
+        // for this to work.
+        document.removeEventListener("click", clickListener, true);
+        document.removeEventListener("mousemove", moveListener, true);
+      };
+
+      /**
+       * Loads the global data and passes it to the regression model
+       */
+      async function loadGlobalData() {
+        // Get settings object from localforage
+        // [20200611 xk] still unsure what this does, maybe would be good for Kalman filter settings etc?
+        settings = await localforage.getItem(localstorageSettingsLabel);
+        settings = settings || defaults;
+
+        // Get click data from localforage
+        var loadData = await localforage.getItem(localstorageDataLabel);
+        loadData = loadData || defaults;
+
+        // Set global var data to newly loaded data
+        data = loadData;
+
+        // Load data into regression model(s)
+        for (var reg in regs) {
+          regs[reg].setData(loadData);
+        }
+
+        console.log("loaded stored data into regression model");
+      }
+
+      /**
+       * Adds data to localforage
+       */
+      async function setGlobalData() {
+        // Grab data from regression model
+        var storeData = regs[0].getData() || data; // Array
+
+        // Store data into localforage
+        localforage.setItem(localstorageSettingsLabel, settings); // [20200605 XK] is 'settings' ever being used?
+        localforage.setItem(localstorageDataLabel, storeData);
+        //TODO data should probably be stored in webgazer object instead of each regression model
+        //     -> requires duplication of data, but is likely easier on regression model implementors
+      }
+
+      /**
+       * Clears data from model and global storage
+       */
+      function clearData() {
+        // Removes data from localforage
+        localforage.clear();
+
+        // Removes data from regression model
+        for (var reg in regs) {
+          regs[reg].init();
+        }
+      }
+
+      /**
+       * Initializes all needed dom elements and begins the loop
+       * @param {URL} stream - The video stream to use
+       */
+      async function init(stream) {
+        //////////////////////////
+        // Video and video preview
+        //////////////////////////
+        var topDist = "0px";
+        var leftDist = "0px";
+
+        // used for webgazer.stopVideo() and webgazer.setCameraConstraints()
+        videoStream = stream;
+
+        // create a video element container to enable customizable placement on the page
+        videoContainerElement = document.createElement("div");
+        videoContainerElement.id = src_webgazer.params.videoContainerId;
+        videoContainerElement.style.display = src_webgazer.params.showVideo ? "block" : "none";
+        videoContainerElement.style.position = "fixed";
+        videoContainerElement.style.top = topDist;
+        videoContainerElement.style.left = leftDist;
+        videoContainerElement.style.width = src_webgazer.params.videoViewerWidth + "px";
+        videoContainerElement.style.height = src_webgazer.params.videoViewerHeight + "px";
+
+        videoElement = document.createElement("video");
+        videoElement.setAttribute("playsinline", "");
+        videoElement.id = src_webgazer.params.videoElementId;
+        videoElement.srcObject = stream;
+        videoElement.autoplay = true;
+        videoElement.style.display = src_webgazer.params.showVideo ? "block" : "none";
+        videoElement.style.position = "absolute";
+        // We set these to stop the video appearing too large when it is added for the very first time
+        videoElement.style.width = src_webgazer.params.videoViewerWidth + "px";
+        videoElement.style.height = src_webgazer.params.videoViewerHeight + "px";
+        // videoElement.style.zIndex="-1";
+
+        // Canvas for drawing video to pass to clm tracker
+        videoElementCanvas = document.createElement("canvas");
+        videoElementCanvas.id = src_webgazer.params.videoElementCanvasId;
+        videoElementCanvas.style.display = "none";
+
+        // Face overlay
+        // Shows the CLM tracking result
+        faceOverlay = document.createElement("canvas");
+        faceOverlay.id = src_webgazer.params.faceOverlayId;
+        faceOverlay.style.display = src_webgazer.params.showFaceOverlay ? "block" : "none";
+        faceOverlay.style.position = "absolute";
+
+        // Mirror video feed
+        if (src_webgazer.params.mirrorVideo) {
+          videoElement.style.setProperty("-moz-transform", "scale(-1, 1)");
+          videoElement.style.setProperty("-webkit-transform", "scale(-1, 1)");
+          videoElement.style.setProperty("-o-transform", "scale(-1, 1)");
+          videoElement.style.setProperty("transform", "scale(-1, 1)");
+          videoElement.style.setProperty("filter", "FlipH");
+          faceOverlay.style.setProperty("-moz-transform", "scale(-1, 1)");
+          faceOverlay.style.setProperty("-webkit-transform", "scale(-1, 1)");
+          faceOverlay.style.setProperty("-o-transform", "scale(-1, 1)");
+          faceOverlay.style.setProperty("transform", "scale(-1, 1)");
+          faceOverlay.style.setProperty("filter", "FlipH");
+        }
+
+        // Feedback box
+        // Lets the user know when their face is in the middle
+        faceFeedbackBox = document.createElement("canvas");
+        faceFeedbackBox.id = src_webgazer.params.faceFeedbackBoxId;
+        faceFeedbackBox.style.display = src_webgazer.params.showFaceFeedbackBox ? "block" : "none";
+        faceFeedbackBox.style.border = "solid";
+        faceFeedbackBox.style.position = "absolute";
+
+        // Gaze dot
+        // Starts offscreen
+        gazeDot = document.createElement("div");
+        gazeDot.id = src_webgazer.params.gazeDotId;
+        gazeDot.style.display = src_webgazer.params.showGazeDot ? "block" : "none";
+        gazeDot.style.position = "fixed";
+        gazeDot.style.zIndex = 99999;
+        gazeDot.style.left = "-5px"; //'-999em';
+        gazeDot.style.top = "-5px";
+        gazeDot.style.background = "red";
+        gazeDot.style.borderRadius = "100%";
+        gazeDot.style.opacity = "0.7";
+        gazeDot.style.width = "10px";
+        gazeDot.style.height = "10px";
+
+        // Add other preview/feedback elements to the screen once the video has shown and its parameters are initialized
+        videoContainerElement.appendChild(videoElement);
+        document.body.appendChild(videoContainerElement);
+        function setupPreviewVideo(e) {
+          // All video preview parts have now been added, so set the size both internally and in the preview window.
+          setInternalVideoBufferSizes(videoElement.videoWidth, videoElement.videoHeight);
+          src_webgazer.setVideoViewerSize(
+            src_webgazer.params.videoViewerWidth,
+            src_webgazer.params.videoViewerHeight
+          );
+
+          videoContainerElement.appendChild(videoElementCanvas);
+          videoContainerElement.appendChild(faceOverlay);
+          videoContainerElement.appendChild(faceFeedbackBox);
+          document.body.appendChild(gazeDot);
+
+          // Run this only once, so remove the event listener
+          e.target.removeEventListener(e.type, setupPreviewVideo);
+        }
+        videoElement.addEventListener("timeupdate", setupPreviewVideo);
+
+        addMouseEventListeners();
+
+        //BEGIN CALLBACK LOOP
+        paused = false;
+        clockStart = performance.now();
+
+        await loop();
+      }
+
+      /**
+       * Initializes navigator.mediaDevices.getUserMedia
+       * depending on the browser capabilities
+       *
+       * @return Promise
+       */
+      function setUserMediaVariable() {
+        if (navigator.mediaDevices === undefined) {
+          navigator.mediaDevices = {};
+        }
+
+        if (navigator.mediaDevices.getUserMedia === undefined) {
+          navigator.mediaDevices.getUserMedia = function (constraints) {
+            // gets the alternative old getUserMedia is possible
+            var getUserMedia = navigator.webkitGetUserMedia || navigator.mozGetUserMedia;
+
+            // set an error message if browser doesn't support getUserMedia
+            if (!getUserMedia) {
+              return Promise.reject(
+                new Error(
+                  "Unfortunately, your browser does not support access to the webcam through the getUserMedia API. Try to use the latest version of Google Chrome, Mozilla Firefox, Opera, or Microsoft Edge instead."
+                )
+              );
+            }
+
+            // uses navigator.getUserMedia for older browsers
+            return new Promise(function (resolve, reject) {
+              getUserMedia.call(navigator, constraints, resolve, reject);
+            });
+          };
+        }
+      }
+
+      //PUBLIC FUNCTIONS - CONTROL
+
+      /**
+       * Starts all state related to webgazer -> dataLoop, video collection, click listener
+       * If starting fails, call `onFail` param function.
+       * @param {Function} onFail - Callback to call in case it is impossible to find user camera
+       * @returns {*}
+       */
+      src_webgazer.begin = function (onFail) {
+        if (
+          window.location.protocol !== "https:" &&
+          window.location.hostname !== "localhost" &&
+          window.chrome
+        ) {
+          alert(
+            "WebGazer works only over https. If you are doing local development, you need to run a local server."
+          );
+        }
+
+        // Load model data stored in localforage.
+        if (window.saveDataAcrossSessions) {
+          loadGlobalData();
+        }
+
+        onFail =
+          onFail ||
+          function () {
+            console.log("No stream");
+          };
+
+        if (debugVideoLoc) {
+          init(debugVideoLoc);
+          return src_webgazer;
+        }
+
+        ///////////////////////
+        // SETUP VIDEO ELEMENTS
+        // Sets .mediaDevices.getUserMedia depending on browser
+        setUserMediaVariable();
+
+        // Request webcam access under specific constraints
+        // WAIT for access
+        return new Promise(async (resolve, reject) => {
+          let stream;
+          try {
+            stream = await navigator.mediaDevices.getUserMedia(src_webgazer.params.camConstraints);
+            init(stream);
+            resolve(src_webgazer);
+          } catch (err) {
+            onFail();
+            videoElement = null;
+            stream = null;
+            reject(err);
+          }
+        });
+      };
+
+      /**
+       * Checks if webgazer has finished initializing after calling begin()
+       * [20180729 JT] This seems like a bad idea for how this function should be implemented.
+       * @returns {boolean} if webgazer is ready
+       */
+      src_webgazer.isReady = function () {
+        if (videoElementCanvas === null) {
+          return false;
+        }
+        return videoElementCanvas.width > 0;
+      };
+
+      /**
+       * Stops collection of data and predictions
+       * @returns {webgazer} this
+       */
+      src_webgazer.pause = function () {
+        paused = true;
+        return src_webgazer;
+      };
+
+      /**
+       * Resumes collection of data and predictions if paused
+       * @returns {webgazer} this
+       */
+      src_webgazer.resume = async function () {
+        if (!paused) {
+          return src_webgazer;
+        }
+        paused = false;
+        await loop();
+        return src_webgazer;
+      };
+
+      /**
+       * stops collection of data and removes dom modifications, must call begin() to reset up
+       * @return {webgazer} this
+       */
+      src_webgazer.end = function () {
+        //loop may run an extra time and fail due to removed elements
+        paused = true;
+
+        //webgazer.stopVideo(); // uncomment if you want to stop the video from streaming
+
+        //remove video element and canvas
+        document.body.removeChild(videoElement);
+        document.body.removeChild(videoElementCanvas);
+
+        return src_webgazer;
+      };
+
+      /**
+       * Stops the video camera from streaming and removes the video outlines
+       * @return {webgazer} this
+       */
+      src_webgazer.stopVideo = function () {
+        // Stops the video from streaming
+        videoStream.getTracks()[0].stop();
+
+        // Removes the outline of the face
+        document.body.removeChild(faceOverlay);
+
+        // Removes the box around the face
+        document.body.removeChild(faceFeedbackBox);
+
+        return src_webgazer;
+      };
+
+      //PUBLIC FUNCTIONS - DEBUG
+
+      /**
+       * Returns if the browser is compatible with webgazer
+       * @return {boolean} if browser is compatible
+       */
+      src_webgazer.detectCompatibility = function () {
+        var getUserMedia =
+          navigator.mediaDevices.getUserMedia ||
+          navigator.getUserMedia ||
+          navigator.webkitGetUserMedia ||
+          navigator.mozGetUserMedia;
+
+        return getUserMedia !== undefined;
+      };
+
+      /**
+       * Set whether to show any of the video previews (camera, face overlay, feedback box).
+       * If true: visibility depends on corresponding params (default all true).
+       * If false: camera, face overlay, feedback box are all hidden
+       * @param {bool} val
+       * @return {webgazer} this
+       */
+      src_webgazer.showVideoPreview = function (val) {
+        src_webgazer.params.showVideoPreview = val;
+        src_webgazer.showVideo(val && src_webgazer.params.showVideo);
+        src_webgazer.showFaceOverlay(val && src_webgazer.params.showFaceOverlay);
+        src_webgazer.showFaceFeedbackBox(val && src_webgazer.params.showFaceFeedbackBox);
+        return src_webgazer;
+      };
+
+      /**
+       * Set whether the camera video preview is visible or not (default true).
+       * @param {*} bool
+       * @return {webgazer} this
+       */
+      src_webgazer.showVideo = function (val) {
+        src_webgazer.params.showVideo = val;
+        if (videoElement) {
+          videoElement.style.display = val ? "block" : "none";
+        }
+        if (videoContainerElement) {
+          videoContainerElement.style.display = val ? "block" : "none";
+        }
+        return src_webgazer;
+      };
+
+      /**
+       * Set whether the face overlay is visible or not (default true).
+       * @param {*} bool
+       * @return {webgazer} this
+       */
+      src_webgazer.showFaceOverlay = function (val) {
+        src_webgazer.params.showFaceOverlay = val;
+        if (faceOverlay) {
+          faceOverlay.style.display = val ? "block" : "none";
+        }
+        return src_webgazer;
+      };
+
+      /**
+       * Set whether the face feedback box is visible or not (default true).
+       * @param {*} bool
+       * @return {webgazer} this
+       */
+      src_webgazer.showFaceFeedbackBox = function (val) {
+        src_webgazer.params.showFaceFeedbackBox = val;
+        if (faceFeedbackBox) {
+          faceFeedbackBox.style.display = val ? "block" : "none";
+        }
+        return src_webgazer;
+      };
+
+      /**
+       * Set whether the gaze prediction point(s) are visible or not.
+       * Multiple because of a trail of past dots. Default true
+       * @return {webgazer} this
+       */
+      src_webgazer.showPredictionPoints = function (val) {
+        src_webgazer.params.showGazeDot = val;
+        if (gazeDot) {
+          gazeDot.style.display = val ? "block" : "none";
+        }
+        return src_webgazer;
+      };
+
+      /**
+       * Set whether a Kalman filter will be applied to gaze predictions (default true);
+       * @return {webgazer} this
+       */
+      src_webgazer.applyKalmanFilter = function (val) {
+        src_webgazer.params.applyKalmanFilter = val;
+        return src_webgazer;
+      };
+
+      /**
+       * Define constraints on the video camera that is used. Useful for non-standard setups.
+       * This can be set before calling webgazer.begin(), but also mid stream.
+       *
+       * @param {Object} constraints Example constraints object:
+       * { width: { min: 320, ideal: 1280, max: 1920 }, height: { min: 240, ideal: 720, max: 1080 }, facingMode: "user" };
+       *
+       * Follows definition here:
+       * https://developer.mozilla.org/en-US/docs/Web/API/Media_Streams_API/Constraints
+       *
+       * Note: The constraints set here are applied to the video track only. They also _replace_ any constraints, so be sure to set everything you need.
+       * Warning: Setting a large video resolution will decrease performance, and may require
+       */
+      src_webgazer.setCameraConstraints = async function (constraints) {
+        var videoTrack, videoSettings;
+        src_webgazer.params.camConstraints = constraints;
+
+        // If the camera stream is already up...
+        if (videoStream) {
+          src_webgazer.pause();
+          videoTrack = videoStream.getVideoTracks()[0];
+          try {
+            await videoTrack.applyConstraints(src_webgazer.params.camConstraints);
+            videoSettings = videoTrack.getSettings();
+            setInternalVideoBufferSizes(videoSettings.width, videoSettings.height);
+          } catch (err) {
+            console.log(err);
+            return;
+          }
+          // Reset and recompute sizes of the video viewer.
+          // This is only to adjust the feedback box, say, if the aspect ratio of the video has changed.
+          src_webgazer.setVideoViewerSize(
+            src_webgazer.params.videoViewerWidth,
+            src_webgazer.params.videoViewerHeight
+          );
+          src_webgazer.getTracker().reset();
+          await src_webgazer.resume();
+        }
+      };
+
+      /**
+       * Does what it says on the tin.
+       * @param {*} width
+       * @param {*} height
+       */
+      function setInternalVideoBufferSizes(width, height) {
+        // Re-set the canvas size used by the internal processes
+        if (videoElementCanvas) {
+          videoElementCanvas.width = width;
+          videoElementCanvas.height = height;
+        }
+
+        // Re-set the face overlay canvas size
+        if (faceOverlay) {
+          faceOverlay.width = width;
+          faceOverlay.height = height;
+        }
+      }
+
+      /**
+       *  Set a static video file to be used instead of webcam video
+       *  @param {String} videoLoc - video file location
+       *  @return {webgazer} this
+       */
+      src_webgazer.setStaticVideo = function (videoLoc) {
+        debugVideoLoc = videoLoc;
+        return src_webgazer;
+      };
+
+      /**
+       * Set the size of the video viewer
+       */
+      src_webgazer.setVideoViewerSize = function (w, h) {
+        src_webgazer.params.videoViewerWidth = w;
+        src_webgazer.params.videoViewerHeight = h;
+
+        // Change the video viewer
+        videoElement.style.width = w + "px";
+        videoElement.style.height = h + "px";
+
+        // Change the face overlay
+        faceOverlay.style.width = w + "px";
+        faceOverlay.style.height = h + "px";
+
+        // Change the feedback box size
+        // Compute the boundaries of the face overlay validation box based on the video size
+        var tlwh = src_webgazer.computeValidationBoxSize();
+        // Assign them to the object
+        faceFeedbackBox.style.top = tlwh[0] + "px";
+        faceFeedbackBox.style.left = tlwh[1] + "px";
+        faceFeedbackBox.style.width = tlwh[2] + "px";
+        faceFeedbackBox.style.height = tlwh[3] + "px";
+      };
+
+      /**
+       *  Add the mouse click and move listeners that add training data.
+       *  @return {webgazer} this
+       */
+      src_webgazer.addMouseEventListeners = function () {
+        addMouseEventListeners();
+        return src_webgazer;
+      };
+
+      /**
+       *  Remove the mouse click and move listeners that add training data.
+       *  @return {webgazer} this
+       */
+      src_webgazer.removeMouseEventListeners = function () {
+        removeMouseEventListeners();
+        return src_webgazer;
+      };
+
+      /**
+       *  Records current screen position for current pupil features.
+       *  @param {String} x - position on screen in the x axis
+       *  @param {String} y - position on screen in the y axis
+       *  @return {webgazer} this
+       */
+      src_webgazer.recordScreenPosition = function (x, y) {
+        // give this the same weight that a click gets.
+        recordScreenPosition(x, y, eventTypes[0]);
+        return src_webgazer;
+      };
+
+      /**
+       *  Records current screen position for current pupil features.
+       *  @param {String} x - position on screen in the x axis
+       *  @param {String} y - position on screen in the y axis
+       *  @param {String} eventType - "click" or "move", as per eventTypes
+       *  @return {webgazer} this
+       */
+      src_webgazer.recordScreenPosition = function (x, y, eventType) {
+        // give this the same weight that a click gets.
+        recordScreenPosition(x, y, eventType);
+        return src_webgazer;
+      };
+
+      /*
+       * Stores the position of the fifty most recent tracker preditions
+       */
+      src_webgazer.storePoints = function (x, y, k) {
+        xPast50[k] = x;
+        yPast50[k] = y;
+      };
+
+      //SETTERS
+      /**
+       * Sets the tracking module
+       * @param {String} name - The name of the tracking module to use
+       * @return {webgazer} this
+       */
+      src_webgazer.setTracker = function (name) {
+        if (curTrackerMap[name] === undefined) {
+          console.log("Invalid tracker selection");
+          console.log("Options are: ");
+          for (var t in curTrackerMap) {
+            console.log(t);
+          }
+          return src_webgazer;
+        }
+        curTracker = curTrackerMap[name]();
+        return src_webgazer;
+      };
+
+      /**
+       * Sets the regression module and clears any other regression modules
+       * @param {String} name - The name of the regression module to use
+       * @return {webgazer} this
+       */
+      src_webgazer.setRegression = function (name) {
+        if (regressionMap[name] === undefined) {
+          console.log("Invalid regression selection");
+          console.log("Options are: ");
+          for (var reg in regressionMap) {
+            console.log(reg);
+          }
+          return src_webgazer;
+        }
+        data = regs[0].getData();
+        regs = [regressionMap[name]()];
+        regs[0].setData(data);
+        return src_webgazer;
+      };
+
+      /**
+       * Adds a new tracker module so that it can be used by setTracker()
+       * @param {String} name - the new name of the tracker
+       * @param {Function} constructor - the constructor of the curTracker object
+       * @return {webgazer} this
+       */
+      src_webgazer.addTrackerModule = function (name, constructor) {
+        curTrackerMap[name] = function () {
+          return new constructor();
+        };
+      };
+
+      /**
+       * Adds a new regression module so that it can be used by setRegression() and addRegression()
+       * @param {String} name - the new name of the regression
+       * @param {Function} constructor - the constructor of the regression object
+       */
+      src_webgazer.addRegressionModule = function (name, constructor) {
+        regressionMap[name] = function () {
+          return new constructor();
+        };
+      };
+
+      /**
+       * Adds a new regression module to the list of regression modules, seeding its data from the first regression module
+       * @param {String} name - the string name of the regression module to add
+       * @return {webgazer} this
+       */
+      src_webgazer.addRegression = function (name) {
+        var newReg = regressionMap[name]();
+        data = regs[0].getData();
+        newReg.setData(data);
+        regs.push(newReg);
+        return src_webgazer;
+      };
+
+      /**
+       * Sets a callback to be executed on every gaze event (currently all time steps)
+       * @param {function} listener - The callback function to call (it must be like function(data, elapsedTime))
+       * @return {webgazer} this
+       */
+      src_webgazer.setGazeListener = function (listener) {
+        callback = listener;
+        return src_webgazer;
+      };
+
+      /**
+       * Removes the callback set by setGazeListener
+       * @return {webgazer} this
+       */
+      src_webgazer.clearGazeListener = function () {
+        callback = nopCallback;
+        return src_webgazer;
+      };
+
+      /**
+       * Set the video element canvas; useful if you want to run WebGazer on your own canvas (e.g., on any random image).
+       * @return The current video element canvas
+       */
+      src_webgazer.setVideoElementCanvas = function (canvas) {
+        videoElementCanvas = canvas;
+      };
+
+      /**
+       * Clear data from localforage and from regs
+       */
+      src_webgazer.clearData = async function () {
+        clearData();
+      };
+
+      //GETTERS
+      /**
+       * Returns the tracker currently in use
+       * @return {tracker} an object following the tracker interface
+       */
+      src_webgazer.getTracker = function () {
+        return curTracker;
+      };
+
+      /**
+       * Returns the regression currently in use
+       * @return {Array.<Object>} an array of regression objects following the regression interface
+       */
+      src_webgazer.getRegression = function () {
+        return regs;
+      };
+
+      /**
+       * Requests an immediate prediction
+       * @return {object} prediction data object
+       */
+      src_webgazer.getCurrentPrediction = function () {
+        return getPrediction();
+      };
+
+      /**
+       * returns the different event types that may be passed to regressions when calling regression.addData()
+       * @return {Array} array of strings where each string is an event type
+       */
+      src_webgazer.params.getEventTypes = function () {
+        return eventTypes.slice();
+      };
+
+      /**
+       * Get the video element canvas that WebGazer uses internally on which to run its face tracker.
+       * @return The current video element canvas
+       */
+      src_webgazer.getVideoElementCanvas = function () {
+        return videoElementCanvas;
+      };
+
+      /**
+       * @return array [a,b] where a is width ratio and b is height ratio
+       */
+      src_webgazer.getVideoPreviewToCameraResolutionRatio = function () {
+        return [
+          src_webgazer.params.videoViewerWidth / videoElement.videoWidth,
+          src_webgazer.params.videoViewerHeight / videoElement.videoHeight,
+        ];
+      };
+
+      /*
+       * Gets the fifty most recent tracker preditions
+       */
+      src_webgazer.getStoredPoints = function () {
+        return [xPast50, yPast50];
+      };
+
+      /* harmony default export */ var src = (__webpack_exports__["default"] = src_webgazer);
+
+      /***/
+    },
+    /******/
+  ]
+)["default"];
+//# sourceMappingURL=webgazer.js.map
diff --git a/7.3/demos/js/webgazer/worker_scripts/mat.js b/7.3/demos/js/webgazer/worker_scripts/mat.js
old mode 100755
new mode 100644
index 036445cb42..39fbe998fa
--- a/7.3/demos/js/webgazer/worker_scripts/mat.js
+++ b/7.3/demos/js/webgazer/worker_scripts/mat.js
@@ -1,299 +1,299 @@
-(function () {
-  "use strict";
-
-  self.webgazer = self.webgazer || {};
-  self.webgazer.mat = self.webgazer.mat || {};
-
-  /**
-   * Transposes an mxn array
-   * @param {Array.<Array.<Number>>} matrix - of 'M x N' dimensionality
-   * @return {Array.<Array.<Number>>} transposed matrix
-   */
-  self.webgazer.mat.transpose = function (matrix) {
-    var m = matrix.length;
-    var n = matrix[0].length;
-    var transposedMatrix = new Array(n);
-
-    for (var i = 0; i < m; i++) {
-      for (var j = 0; j < n; j++) {
-        if (i === 0) transposedMatrix[j] = new Array(m);
-        transposedMatrix[j][i] = matrix[i][j];
-      }
-    }
-
-    return transposedMatrix;
-  };
-
-  /**
-   * Get a sub-matrix of matrix
-   * @param {Array.<Array.<Number>>} matrix - original matrix
-   * @param {Array.<Number>} r - Array of row indices
-   * @param {Number} j0 - Initial column index
-   * @param {Number} j1 - Final column index
-   * @returns {Array} The sub-matrix matrix(r(:),j0:j1)
-   */
-  self.webgazer.mat.getMatrix = function (matrix, r, j0, j1) {
-    var X = new Array(r.length),
-      m = j1 - j0 + 1;
-
-    for (var i = 0; i < r.length; i++) {
-      X[i] = new Array(m);
-      for (var j = j0; j <= j1; j++) {
-        X[i][j - j0] = matrix[r[i]][j];
-      }
-    }
-    return X;
-  };
-
-  /**
-   * Get a submatrix of matrix
-   * @param {Array.<Array.<Number>>} matrix - original matrix
-   * @param {Number} i0 - Initial row index
-   * @param {Number} i1 - Final row index
-   * @param {Number} j0 - Initial column index
-   * @param {Number} j1 - Final column index
-   * @return {Array} The sub-matrix matrix(i0:i1,j0:j1)
-   */
-  self.webgazer.mat.getSubMatrix = function (matrix, i0, i1, j0, j1) {
-    var size = j1 - j0 + 1,
-      X = new Array(i1 - i0 + 1);
-
-    for (var i = i0; i <= i1; i++) {
-      var subI = i - i0;
-
-      X[subI] = new Array(size);
-
-      for (var j = j0; j <= j1; j++) {
-        X[subI][j - j0] = matrix[i][j];
-      }
-    }
-    return X;
-  };
-
-  /**
-   * Linear algebraic matrix multiplication, matrix1 * matrix2
-   * @param {Array.<Array.<Number>>} matrix1
-   * @param {Array.<Array.<Number>>} matrix2
-   * @return {Array.<Array.<Number>>} Matrix product, matrix1 * matrix2
-   */
-  self.webgazer.mat.mult = function (matrix1, matrix2) {
-    if (matrix2.length != matrix1[0].length) {
-      console.log("Matrix inner dimensions must agree:");
-    }
-
-    var X = new Array(matrix1.length),
-      Bcolj = new Array(matrix1[0].length);
-
-    for (var j = 0; j < matrix2[0].length; j++) {
-      for (var k = 0; k < matrix1[0].length; k++) {
-        Bcolj[k] = matrix2[k][j];
-      }
-      for (var i = 0; i < matrix1.length; i++) {
-        if (j === 0) X[i] = new Array(matrix2[0].length);
-
-        var Arowi = matrix1[i];
-        var s = 0;
-        for (var k = 0; k < matrix1[0].length; k++) {
-          s += Arowi[k] * Bcolj[k];
-        }
-        X[i][j] = s;
-      }
-    }
-    return X;
-  };
-
-  /**
-   * LUDecomposition to solve A*X = B, based on WEKA code
-   * @param {Array.<Array.<Number>>} A - left matrix of equation to be solved
-   * @param {Array.<Array.<Number>>} B - right matrix of equation to be solved
-   * @return {Array.<Array.<Number>>} X so that L*U*X = B(piv,:)
-   */
-  self.webgazer.mat.LUDecomposition = function (A, B) {
-    var LU = new Array(A.length);
-
-    for (var i = 0; i < A.length; i++) {
-      LU[i] = new Array(A[0].length);
-      for (var j = 0; j < A[0].length; j++) {
-        LU[i][j] = A[i][j];
-      }
-    }
-
-    var m = A.length;
-    var n = A[0].length;
-    var piv = new Array(m);
-    for (var i = 0; i < m; i++) {
-      piv[i] = i;
-    }
-    var pivsign = 1;
-    var LUrowi = new Array();
-    var LUcolj = new Array(m);
-    // Outer loop.
-    for (var j = 0; j < n; j++) {
-      // Make a copy of the j-th column to localize references.
-      for (var i = 0; i < m; i++) {
-        LUcolj[i] = LU[i][j];
-      }
-      // Apply previous transformations.
-      for (var i = 0; i < m; i++) {
-        LUrowi = LU[i];
-        // Most of the time is spent in the following dot product.
-        var kmax = Math.min(i, j);
-        var s = 0;
-        for (var k = 0; k < kmax; k++) {
-          s += LUrowi[k] * LUcolj[k];
-        }
-        LUrowi[j] = LUcolj[i] -= s;
-      }
-      // Find pivot and exchange if necessary.
-      var p = j;
-      for (var i = j + 1; i < m; i++) {
-        if (Math.abs(LUcolj[i]) > Math.abs(LUcolj[p])) {
-          p = i;
-        }
-      }
-      if (p != j) {
-        for (var k = 0; k < n; k++) {
-          var t = LU[p][k];
-          LU[p][k] = LU[j][k];
-          LU[j][k] = t;
-        }
-        var k = piv[p];
-        piv[p] = piv[j];
-        piv[j] = k;
-        pivsign = -pivsign;
-      }
-      // Compute multipliers.
-      if ((j < m) & (LU[j][j] != 0)) {
-        for (var i = j + 1; i < m; i++) {
-          LU[i][j] /= LU[j][j];
-        }
-      }
-    }
-    if (B.length != m) {
-      console.log("Matrix row dimensions must agree.");
-    }
-    for (var j = 0; j < n; j++) {
-      if (LU[j][j] === 0) {
-        console.log("Matrix is singular.");
-      }
-    }
-    var nx = B[0].length;
-    var X = self.webgazer.mat.getMatrix(B, piv, 0, nx - 1);
-    // Solve L*Y = B(piv,:)
-    for (var k = 0; k < n; k++) {
-      for (var i = k + 1; i < n; i++) {
-        for (var j = 0; j < nx; j++) {
-          X[i][j] -= X[k][j] * LU[i][k];
-        }
-      }
-    }
-    // Solve U*X = Y;
-    for (var k = n - 1; k >= 0; k--) {
-      for (var j = 0; j < nx; j++) {
-        X[k][j] /= LU[k][k];
-      }
-      for (var i = 0; i < k; i++) {
-        for (var j = 0; j < nx; j++) {
-          X[i][j] -= X[k][j] * LU[i][k];
-        }
-      }
-    }
-    return X;
-  };
-
-  /**
-   * Least squares solution of A*X = B, based on WEKA code
-   * @param {Array.<Array.<Number>>} A - left side matrix to be solved
-   * @param {Array.<Array.<Number>>} B - a matrix with as many rows as A and any number of columns.
-   * @return {Array.<Array.<Number>>} X - that minimizes the two norms of QR*X-B.
-   */
-  self.webgazer.mat.QRDecomposition = function (A, B) {
-    // Initialize.
-    var QR = new Array(A.length);
-
-    for (var i = 0; i < A.length; i++) {
-      QR[i] = new Array(A[0].length);
-      for (var j = 0; j < A[0].length; j++) {
-        QR[i][j] = A[i][j];
-      }
-    }
-    var m = A.length;
-    var n = A[0].length;
-    var Rdiag = new Array(n);
-    var nrm;
-
-    // Main loop.
-    for (var k = 0; k < n; k++) {
-      // Compute 2-norm of k-th column without under/overflow.
-      nrm = 0;
-      for (var i = k; i < m; i++) {
-        nrm = Math.hypot(nrm, QR[i][k]);
-      }
-      if (nrm != 0) {
-        // Form k-th Householder vector.
-        if (QR[k][k] < 0) {
-          nrm = -nrm;
-        }
-        for (var i = k; i < m; i++) {
-          QR[i][k] /= nrm;
-        }
-        QR[k][k] += 1;
-
-        // Apply transformation to remaining columns.
-        for (var j = k + 1; j < n; j++) {
-          var s = 0;
-          for (var i = k; i < m; i++) {
-            s += QR[i][k] * QR[i][j];
-          }
-          s = -s / QR[k][k];
-          for (var i = k; i < m; i++) {
-            QR[i][j] += s * QR[i][k];
-          }
-        }
-      }
-      Rdiag[k] = -nrm;
-    }
-    if (B.length != m) {
-      console.log("Matrix row dimensions must agree.");
-    }
-    for (var j = 0; j < n; j++) {
-      if (Rdiag[j] === 0) console.log("Matrix is rank deficient");
-    }
-    // Copy right hand side
-    var nx = B[0].length;
-    var X = new Array(B.length);
-    for (var i = 0; i < B.length; i++) {
-      X[i] = new Array(B[0].length);
-    }
-    for (var i = 0; i < B.length; i++) {
-      for (var j = 0; j < B[0].length; j++) {
-        X[i][j] = B[i][j];
-      }
-    }
-    // Compute Y = transpose(Q)*B
-    for (var k = 0; k < n; k++) {
-      for (var j = 0; j < nx; j++) {
-        var s = 0.0;
-        for (var i = k; i < m; i++) {
-          s += QR[i][k] * X[i][j];
-        }
-        s = -s / QR[k][k];
-        for (var i = k; i < m; i++) {
-          X[i][j] += s * QR[i][k];
-        }
-      }
-    }
-    // Solve R*X = Y;
-    for (var k = n - 1; k >= 0; k--) {
-      for (var j = 0; j < nx; j++) {
-        X[k][j] /= Rdiag[k];
-      }
-      for (var i = 0; i < k; i++) {
-        for (var j = 0; j < nx; j++) {
-          X[i][j] -= X[k][j] * QR[i][k];
-        }
-      }
-    }
-    return self.webgazer.mat.getSubMatrix(X, 0, n - 1, 0, nx - 1);
-  };
-})();
+(function () {
+  "use strict";
+
+  self.webgazer = self.webgazer || {};
+  self.webgazer.mat = self.webgazer.mat || {};
+
+  /**
+   * Transposes an mxn array
+   * @param {Array.<Array.<Number>>} matrix - of 'M x N' dimensionality
+   * @return {Array.<Array.<Number>>} transposed matrix
+   */
+  self.webgazer.mat.transpose = function (matrix) {
+    var m = matrix.length;
+    var n = matrix[0].length;
+    var transposedMatrix = new Array(n);
+
+    for (var i = 0; i < m; i++) {
+      for (var j = 0; j < n; j++) {
+        if (i === 0) transposedMatrix[j] = new Array(m);
+        transposedMatrix[j][i] = matrix[i][j];
+      }
+    }
+
+    return transposedMatrix;
+  };
+
+  /**
+   * Get a sub-matrix of matrix
+   * @param {Array.<Array.<Number>>} matrix - original matrix
+   * @param {Array.<Number>} r - Array of row indices
+   * @param {Number} j0 - Initial column index
+   * @param {Number} j1 - Final column index
+   * @returns {Array} The sub-matrix matrix(r(:),j0:j1)
+   */
+  self.webgazer.mat.getMatrix = function (matrix, r, j0, j1) {
+    var X = new Array(r.length),
+      m = j1 - j0 + 1;
+
+    for (var i = 0; i < r.length; i++) {
+      X[i] = new Array(m);
+      for (var j = j0; j <= j1; j++) {
+        X[i][j - j0] = matrix[r[i]][j];
+      }
+    }
+    return X;
+  };
+
+  /**
+   * Get a submatrix of matrix
+   * @param {Array.<Array.<Number>>} matrix - original matrix
+   * @param {Number} i0 - Initial row index
+   * @param {Number} i1 - Final row index
+   * @param {Number} j0 - Initial column index
+   * @param {Number} j1 - Final column index
+   * @return {Array} The sub-matrix matrix(i0:i1,j0:j1)
+   */
+  self.webgazer.mat.getSubMatrix = function (matrix, i0, i1, j0, j1) {
+    var size = j1 - j0 + 1,
+      X = new Array(i1 - i0 + 1);
+
+    for (var i = i0; i <= i1; i++) {
+      var subI = i - i0;
+
+      X[subI] = new Array(size);
+
+      for (var j = j0; j <= j1; j++) {
+        X[subI][j - j0] = matrix[i][j];
+      }
+    }
+    return X;
+  };
+
+  /**
+   * Linear algebraic matrix multiplication, matrix1 * matrix2
+   * @param {Array.<Array.<Number>>} matrix1
+   * @param {Array.<Array.<Number>>} matrix2
+   * @return {Array.<Array.<Number>>} Matrix product, matrix1 * matrix2
+   */
+  self.webgazer.mat.mult = function (matrix1, matrix2) {
+    if (matrix2.length != matrix1[0].length) {
+      console.log("Matrix inner dimensions must agree:");
+    }
+
+    var X = new Array(matrix1.length),
+      Bcolj = new Array(matrix1[0].length);
+
+    for (var j = 0; j < matrix2[0].length; j++) {
+      for (var k = 0; k < matrix1[0].length; k++) {
+        Bcolj[k] = matrix2[k][j];
+      }
+      for (var i = 0; i < matrix1.length; i++) {
+        if (j === 0) X[i] = new Array(matrix2[0].length);
+
+        var Arowi = matrix1[i];
+        var s = 0;
+        for (var k = 0; k < matrix1[0].length; k++) {
+          s += Arowi[k] * Bcolj[k];
+        }
+        X[i][j] = s;
+      }
+    }
+    return X;
+  };
+
+  /**
+   * LUDecomposition to solve A*X = B, based on WEKA code
+   * @param {Array.<Array.<Number>>} A - left matrix of equation to be solved
+   * @param {Array.<Array.<Number>>} B - right matrix of equation to be solved
+   * @return {Array.<Array.<Number>>} X so that L*U*X = B(piv,:)
+   */
+  self.webgazer.mat.LUDecomposition = function (A, B) {
+    var LU = new Array(A.length);
+
+    for (var i = 0; i < A.length; i++) {
+      LU[i] = new Array(A[0].length);
+      for (var j = 0; j < A[0].length; j++) {
+        LU[i][j] = A[i][j];
+      }
+    }
+
+    var m = A.length;
+    var n = A[0].length;
+    var piv = new Array(m);
+    for (var i = 0; i < m; i++) {
+      piv[i] = i;
+    }
+    var pivsign = 1;
+    var LUrowi = new Array();
+    var LUcolj = new Array(m);
+    // Outer loop.
+    for (var j = 0; j < n; j++) {
+      // Make a copy of the j-th column to localize references.
+      for (var i = 0; i < m; i++) {
+        LUcolj[i] = LU[i][j];
+      }
+      // Apply previous transformations.
+      for (var i = 0; i < m; i++) {
+        LUrowi = LU[i];
+        // Most of the time is spent in the following dot product.
+        var kmax = Math.min(i, j);
+        var s = 0;
+        for (var k = 0; k < kmax; k++) {
+          s += LUrowi[k] * LUcolj[k];
+        }
+        LUrowi[j] = LUcolj[i] -= s;
+      }
+      // Find pivot and exchange if necessary.
+      var p = j;
+      for (var i = j + 1; i < m; i++) {
+        if (Math.abs(LUcolj[i]) > Math.abs(LUcolj[p])) {
+          p = i;
+        }
+      }
+      if (p != j) {
+        for (var k = 0; k < n; k++) {
+          var t = LU[p][k];
+          LU[p][k] = LU[j][k];
+          LU[j][k] = t;
+        }
+        var k = piv[p];
+        piv[p] = piv[j];
+        piv[j] = k;
+        pivsign = -pivsign;
+      }
+      // Compute multipliers.
+      if ((j < m) & (LU[j][j] != 0)) {
+        for (var i = j + 1; i < m; i++) {
+          LU[i][j] /= LU[j][j];
+        }
+      }
+    }
+    if (B.length != m) {
+      console.log("Matrix row dimensions must agree.");
+    }
+    for (var j = 0; j < n; j++) {
+      if (LU[j][j] === 0) {
+        console.log("Matrix is singular.");
+      }
+    }
+    var nx = B[0].length;
+    var X = self.webgazer.mat.getMatrix(B, piv, 0, nx - 1);
+    // Solve L*Y = B(piv,:)
+    for (var k = 0; k < n; k++) {
+      for (var i = k + 1; i < n; i++) {
+        for (var j = 0; j < nx; j++) {
+          X[i][j] -= X[k][j] * LU[i][k];
+        }
+      }
+    }
+    // Solve U*X = Y;
+    for (var k = n - 1; k >= 0; k--) {
+      for (var j = 0; j < nx; j++) {
+        X[k][j] /= LU[k][k];
+      }
+      for (var i = 0; i < k; i++) {
+        for (var j = 0; j < nx; j++) {
+          X[i][j] -= X[k][j] * LU[i][k];
+        }
+      }
+    }
+    return X;
+  };
+
+  /**
+   * Least squares solution of A*X = B, based on WEKA code
+   * @param {Array.<Array.<Number>>} A - left side matrix to be solved
+   * @param {Array.<Array.<Number>>} B - a matrix with as many rows as A and any number of columns.
+   * @return {Array.<Array.<Number>>} X - that minimizes the two norms of QR*X-B.
+   */
+  self.webgazer.mat.QRDecomposition = function (A, B) {
+    // Initialize.
+    var QR = new Array(A.length);
+
+    for (var i = 0; i < A.length; i++) {
+      QR[i] = new Array(A[0].length);
+      for (var j = 0; j < A[0].length; j++) {
+        QR[i][j] = A[i][j];
+      }
+    }
+    var m = A.length;
+    var n = A[0].length;
+    var Rdiag = new Array(n);
+    var nrm;
+
+    // Main loop.
+    for (var k = 0; k < n; k++) {
+      // Compute 2-norm of k-th column without under/overflow.
+      nrm = 0;
+      for (var i = k; i < m; i++) {
+        nrm = Math.hypot(nrm, QR[i][k]);
+      }
+      if (nrm != 0) {
+        // Form k-th Householder vector.
+        if (QR[k][k] < 0) {
+          nrm = -nrm;
+        }
+        for (var i = k; i < m; i++) {
+          QR[i][k] /= nrm;
+        }
+        QR[k][k] += 1;
+
+        // Apply transformation to remaining columns.
+        for (var j = k + 1; j < n; j++) {
+          var s = 0;
+          for (var i = k; i < m; i++) {
+            s += QR[i][k] * QR[i][j];
+          }
+          s = -s / QR[k][k];
+          for (var i = k; i < m; i++) {
+            QR[i][j] += s * QR[i][k];
+          }
+        }
+      }
+      Rdiag[k] = -nrm;
+    }
+    if (B.length != m) {
+      console.log("Matrix row dimensions must agree.");
+    }
+    for (var j = 0; j < n; j++) {
+      if (Rdiag[j] === 0) console.log("Matrix is rank deficient");
+    }
+    // Copy right hand side
+    var nx = B[0].length;
+    var X = new Array(B.length);
+    for (var i = 0; i < B.length; i++) {
+      X[i] = new Array(B[0].length);
+    }
+    for (var i = 0; i < B.length; i++) {
+      for (var j = 0; j < B[0].length; j++) {
+        X[i][j] = B[i][j];
+      }
+    }
+    // Compute Y = transpose(Q)*B
+    for (var k = 0; k < n; k++) {
+      for (var j = 0; j < nx; j++) {
+        var s = 0.0;
+        for (var i = k; i < m; i++) {
+          s += QR[i][k] * X[i][j];
+        }
+        s = -s / QR[k][k];
+        for (var i = k; i < m; i++) {
+          X[i][j] += s * QR[i][k];
+        }
+      }
+    }
+    // Solve R*X = Y;
+    for (var k = n - 1; k >= 0; k--) {
+      for (var j = 0; j < nx; j++) {
+        X[k][j] /= Rdiag[k];
+      }
+      for (var i = 0; i < k; i++) {
+        for (var j = 0; j < nx; j++) {
+          X[i][j] -= X[k][j] * QR[i][k];
+        }
+      }
+    }
+    return self.webgazer.mat.getSubMatrix(X, 0, n - 1, 0, nx - 1);
+  };
+})();
diff --git a/7.3/demos/js/webgazer/worker_scripts/util.js b/7.3/demos/js/webgazer/worker_scripts/util.js
old mode 100755
new mode 100644
index 76eec585e2..a3cea6dd62
--- a/7.3/demos/js/webgazer/worker_scripts/util.js
+++ b/7.3/demos/js/webgazer/worker_scripts/util.js
@@ -1,391 +1,391 @@
-"use strict";
-(function () {
-  self.webgazer = self.webgazer || {};
-  self.webgazer.util = self.webgazer.util || {};
-  self.webgazer.mat = self.webgazer.mat || {};
-
-  /**
-   * Eye class, represents an eye patch detected in the video stream
-   * @param {ImageData} patch - the image data corresponding to an eye
-   * @param {Number} imagex - x-axis offset from the top-left corner of the video canvas
-   * @param {Number} imagey - y-axis offset from the top-left corner of the video canvas
-   * @param {Number} width  - width of the eye patch
-   * @param {Number} height - height of the eye patch
-   */
-  self.webgazer.util.Eye = function (patch, imagex, imagey, width, height) {
-    this.patch = patch;
-    this.imagex = imagex;
-    this.imagey = imagey;
-    this.width = width;
-    this.height = height;
-  };
-
-  //Data Window class
-  //operates like an array but 'wraps' data around to keep the array at a fixed windowSize
-  /**
-   * DataWindow class - Operates like an array, but 'wraps' data around to keep the array at a fixed windowSize
-   * @param {Number} windowSize - defines the maximum size of the window
-   * @param {Array} data - optional data to seed the DataWindow with
-   **/
-  self.webgazer.util.DataWindow = function (windowSize, data) {
-    this.data = [];
-    this.windowSize = windowSize;
-    this.index = 0;
-    this.length = 0;
-    if (data) {
-      this.data = data.slice(data.length - windowSize, data.length);
-      this.length = this.data.length;
-    }
-  };
-
-  /**
-   * [push description]
-   * @param  {*} entry - item to be inserted. It either grows the DataWindow or replaces the oldest item
-   * @return {DataWindow} this
-   */
-  self.webgazer.util.DataWindow.prototype.push = function (entry) {
-    if (this.data.length < this.windowSize) {
-      this.data.push(entry);
-      this.length = this.data.length;
-      return this;
-    }
-
-    //replace oldest entry by wrapping around the DataWindow
-    this.data[this.index] = entry;
-    this.index = (this.index + 1) % this.windowSize;
-    return this;
-  };
-
-  /**
-   * Get the element at the ind position by wrapping around the DataWindow
-   * @param  {Number} ind index of desired entry
-   * @return {*}
-   */
-  self.webgazer.util.DataWindow.prototype.get = function (ind) {
-    return this.data[this.getTrueIndex(ind)];
-  };
-
-  /**
-   * Gets the true this.data array index given an index for a desired element
-   * @param {Number} ind - index of desired entry
-   * @return {Number} index of desired entry in this.data
-   */
-  self.webgazer.util.DataWindow.prototype.getTrueIndex = function (ind) {
-    if (this.data.length < this.windowSize) {
-      return ind;
-    } else {
-      //wrap around ind so that we can traverse from oldest to newest
-      return (ind + this.index) % this.windowSize;
-    }
-  };
-
-  /**
-   * Append all the contents of data
-   * @param {Array} data - to be inserted
-   */
-  self.webgazer.util.DataWindow.prototype.addAll = function (data) {
-    for (var i = 0; i < data.length; i++) {
-      this.push(data[i]);
-    }
-  };
-
-  //Helper functions
-  /**
-   * Grayscales an image patch. Can be used for the whole canvas, detected face, detected eye, etc.
-   *
-   * Code from tracking.js by Eduardo Lundgren, et al.
-   * https://github.com/eduardolundgren/tracking.js/blob/master/src/tracking.js
-   *
-   * Software License Agreement (BSD License) Copyright (c) 2014, Eduardo A. Lundgren Melo. All rights reserved.
-   * Redistribution and use of this software in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-   * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
-   * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
-   * The name of Eduardo A. Lundgren Melo may not be used to endorse or promote products derived from this software without specific prior written permission of Eduardo A. Lundgren Melo.
-   * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
-   * IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
-   * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
-   * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-   *
-   * @param  {Array} pixels - image data to be grayscaled
-   * @param  {Number} width  - width of image data to be grayscaled
-   * @param  {Number} height - height of image data to be grayscaled
-   * @return {Array} grayscaledImage
-   */
-  self.webgazer.util.grayscale = function (pixels, width, height) {
-    var gray = new Uint8ClampedArray(pixels.length >> 2);
-    var p = 0;
-    var w = 0;
-    for (var i = 0; i < height; i++) {
-      for (var j = 0; j < width; j++) {
-        var value = pixels[w] * 0.299 + pixels[w + 1] * 0.587 + pixels[w + 2] * 0.114;
-        gray[p++] = value;
-
-        w += 4;
-      }
-    }
-    return gray;
-  };
-
-  /**
-   * Increase contrast of an image.
-   *
-   * Code from Martin Tschirsich, Copyright (c) 2012.
-   * https://github.com/mtschirs/js-objectdetect/blob/gh-pages/js/objectdetect.js
-   *
-   * @param {Array} src - grayscale integer array
-   * @param {Number} step - sampling rate, control performance
-   * @param {Array} dst - array to hold the resulting image
-   */
-  self.webgazer.util.equalizeHistogram = function (src, step, dst) {
-    var srcLength = src.length;
-    if (!dst) dst = src;
-    if (!step) step = 5;
-
-    // Compute histogram and histogram sum:
-    var hist = [
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0,
-    ];
-
-    for (var i = 0; i < srcLength; i += step) {
-      ++hist[src[i]];
-    }
-
-    // Compute integral histogram:
-    var norm = (255 * step) / srcLength,
-      prev = 0;
-    for (var i = 0; i < 256; ++i) {
-      var h = hist[i];
-      prev = h += prev;
-      hist[i] = h * norm; // For non-integer src: ~~(h * norm + 0.5);
-    }
-
-    // Equalize image:
-    for (var i = 0; i < srcLength; ++i) {
-      dst[i] = hist[src[i]];
-    }
-    return dst;
-  };
-
-  self.webgazer.util.threshold = function (data, threshold) {
-    for (let i = 0; i < data.length; i++) {
-      data[i] = data[i] > threshold ? 255 : 0;
-    }
-    return data;
-  };
-
-  self.webgazer.util.correlation = function (data1, data2) {
-    const length = Math.min(data1.length, data2.length);
-    let count = 0;
-    for (let i = 0; i < length; i++) {
-      if (data1[i] === data2[i]) {
-        count++;
-      }
-    }
-    return count / Math.max(data1.length, data2.length);
-  };
-
-  /**
-   * Gets an Eye object and resizes it to the desired resolution
-   * @param  {webgazer.util.Eye} eye - patch to be resized
-   * @param  {Number} resizeWidth - desired width
-   * @param  {Number} resizeHeight - desired height
-   * @return {webgazer.util.Eye} resized eye patch
-   */
-  self.webgazer.util.resizeEye = function (eye, resizeWidth, resizeHeight) {
-    var canvas = document.createElement("canvas");
-    canvas.width = eye.width;
-    canvas.height = eye.height;
-
-    canvas.getContext("2d").putImageData(eye.patch, 0, 0);
-
-    var tempCanvas = document.createElement("canvas");
-
-    tempCanvas.width = resizeWidth;
-    tempCanvas.height = resizeHeight;
-
-    // save the canvas into temp canvas
-    tempCanvas
-      .getContext("2d")
-      .drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, resizeWidth, resizeHeight);
-
-    return tempCanvas.getContext("2d").getImageData(0, 0, resizeWidth, resizeHeight);
-  };
-
-  /**
-   * Checks if the prediction is within the boundaries of the viewport and constrains it
-   * @param  {Array} prediction [x,y] - predicted gaze coordinates
-   * @return {Array} constrained coordinates
-   */
-  self.webgazer.util.bound = function (prediction) {
-    if (prediction.x < 0) prediction.x = 0;
-    if (prediction.y < 0) prediction.y = 0;
-    var w = Math.max(document.documentElement.clientWidth, window.innerWidth || 0);
-    var h = Math.max(document.documentElement.clientHeight, window.innerHeight || 0);
-    if (prediction.x > w) {
-      prediction.x = w;
-    }
-
-    if (prediction.y > h) {
-      prediction.y = h;
-    }
-    return prediction;
-  };
-
-  /**
-   * Write statistics in debug paragraph panel
-   * @param {HTMLElement} para - The <p> tag where write data
-   * @param {Object} stats - The stats data to output
-   */
-  function debugBoxWrite(para, stats) {
-    var str = "";
-    for (var key in stats) {
-      str += key + ": " + stats[key] + "\n";
-    }
-    para.innerText = str;
-  }
-
-  /**
-   * Constructor of DebugBox object,
-   * it insert an paragraph inside a div to the body, in view to display debug data
-   * @param {Number} interval - The log interval
-   * @constructor
-   */
-  self.webgazer.util.DebugBox = function (interval) {
-    this.para = document.createElement("p");
-    this.div = document.createElement("div");
-    this.div.appendChild(this.para);
-    document.body.appendChild(this.div);
-
-    this.buttons = {};
-    this.canvas = {};
-    this.stats = {};
-    var updateInterval = interval || 300;
-    (function (localThis) {
-      setInterval(function () {
-        debugBoxWrite(localThis.para, localThis.stats);
-      }, updateInterval);
-    })(this);
-  };
-
-  /**
-   * Add stat data for log
-   * @param {String} key - The data key
-   * @param {*} value - The value
-   */
-  self.webgazer.util.DebugBox.prototype.set = function (key, value) {
-    this.stats[key] = value;
-  };
-
-  /**
-   * Initialize stats in case where key does not exist, else
-   * increment value for key
-   * @param {String} key - The key to process
-   * @param {Number} incBy - Value to increment for given key (default: 1)
-   * @param {Number} init - Initial value in case where key does not exist (default: 0)
-   */
-  self.webgazer.util.DebugBox.prototype.inc = function (key, incBy, init) {
-    if (!this.stats[key]) {
-      this.stats[key] = init || 0;
-    }
-    this.stats[key] += incBy || 1;
-  };
-
-  /**
-   * Create a button and register the given function to the button click event
-   * @param {String} name - The button name to link
-   * @param {Function} func - The onClick callback
-   */
-  self.webgazer.util.DebugBox.prototype.addButton = function (name, func) {
-    if (!this.buttons[name]) {
-      this.buttons[name] = document.createElement("button");
-      this.div.appendChild(this.buttons[name]);
-    }
-    var button = this.buttons[name];
-    this.buttons[name] = button;
-    button.addEventListener("click", func);
-    button.innerText = name;
-  };
-
-  /**
-   * Search for a canvas elemenet with name, or create on if not exist.
-   * Then send the canvas element as callback parameter.
-   * @param {String} name - The canvas name to send/create
-   * @param {Function} func - The callback function where send canvas
-   */
-  self.webgazer.util.DebugBox.prototype.show = function (name, func) {
-    if (!this.canvas[name]) {
-      this.canvas[name] = document.createElement("canvas");
-      this.div.appendChild(this.canvas[name]);
-    }
-    var canvas = this.canvas[name];
-    canvas.getContext("2d").clearRect(0, 0, canvas.width, canvas.height);
-    func(canvas);
-  };
-
-  /**
-   * Kalman Filter constructor
-   * Kalman filters work by reducing the amount of noise in a models.
-   * https://blog.cordiner.net/2011/05/03/object-tracking-using-a-kalman-filter-matlab/
-   *
-   * @param {Array.<Array.<Number>>} F - transition matrix
-   * @param {Array.<Array.<Number>>} Q - process noise matrix
-   * @param {Array.<Array.<Number>>} H - maps between measurement vector and noise matrix
-   * @param {Array.<Array.<Number>>} R - defines measurement error of the device
-   * @param {Array} P_initial - the initial state
-   * @param {Array} X_initial - the initial state of the device
-   */
-  self.webgazer.util.KalmanFilter = function (F, H, Q, R, P_initial, X_initial) {
-    this.F = F; // State transition matrix
-    this.Q = Q; // Process noise matrix
-    this.H = H; // Transformation matrix
-    this.R = R; // Measurement Noise
-    this.P = P_initial; //Initial covariance matrix
-    this.X = X_initial; //Initial guess of measurement
-  };
-
-  /**
-   * Get Kalman next filtered value and update the internal state
-   * @param {Array} z - the new measurement
-   * @return {Array}
-   */
-  self.webgazer.util.KalmanFilter.prototype.update = function (z) {
-    // Here, we define all the different matrix operations we will need
-    var add = numeric.add,
-      sub = numeric.sub,
-      inv = numeric.inv,
-      identity = numeric.identity;
-    var mult = webgazer.mat.mult,
-      transpose = webgazer.mat.transpose;
-    //TODO cache variables like the transpose of H
-
-    // prediction: X = F * X  |  P = F * P * F' + Q
-    var X_p = mult(this.F, this.X); //Update state vector
-    var P_p = add(mult(mult(this.F, this.P), transpose(this.F)), this.Q); //Predicted covaraince
-
-    //Calculate the update values
-    var y = sub(z, mult(this.H, X_p)); // This is the measurement error (between what we expect and the actual value)
-    var S = add(mult(mult(this.H, P_p), transpose(this.H)), this.R); //This is the residual covariance (the error in the covariance)
-
-    // kalman multiplier: K = P * H' * (H * P * H' + R)^-1
-    var K = mult(P_p, mult(transpose(this.H), inv(S))); //This is the Optimal Kalman Gain
-
-    //We need to change Y into it's column vector form
-    for (var i = 0; i < y.length; i++) {
-      y[i] = [y[i]];
-    }
-
-    //Now we correct the internal values of the model
-    // correction: X = X + K * (m - H * X)  |  P = (I - K * H) * P
-    this.X = add(X_p, mult(K, y));
-    this.P = mult(sub(identity(K.length), mult(K, this.H)), P_p);
-    return transpose(mult(this.H, this.X))[0]; //Transforms the predicted state back into it's measurement form
-  };
-})();
+"use strict";
+(function () {
+  self.webgazer = self.webgazer || {};
+  self.webgazer.util = self.webgazer.util || {};
+  self.webgazer.mat = self.webgazer.mat || {};
+
+  /**
+   * Eye class, represents an eye patch detected in the video stream
+   * @param {ImageData} patch - the image data corresponding to an eye
+   * @param {Number} imagex - x-axis offset from the top-left corner of the video canvas
+   * @param {Number} imagey - y-axis offset from the top-left corner of the video canvas
+   * @param {Number} width  - width of the eye patch
+   * @param {Number} height - height of the eye patch
+   */
+  self.webgazer.util.Eye = function (patch, imagex, imagey, width, height) {
+    this.patch = patch;
+    this.imagex = imagex;
+    this.imagey = imagey;
+    this.width = width;
+    this.height = height;
+  };
+
+  //Data Window class
+  //operates like an array but 'wraps' data around to keep the array at a fixed windowSize
+  /**
+   * DataWindow class - Operates like an array, but 'wraps' data around to keep the array at a fixed windowSize
+   * @param {Number} windowSize - defines the maximum size of the window
+   * @param {Array} data - optional data to seed the DataWindow with
+   **/
+  self.webgazer.util.DataWindow = function (windowSize, data) {
+    this.data = [];
+    this.windowSize = windowSize;
+    this.index = 0;
+    this.length = 0;
+    if (data) {
+      this.data = data.slice(data.length - windowSize, data.length);
+      this.length = this.data.length;
+    }
+  };
+
+  /**
+   * [push description]
+   * @param  {*} entry - item to be inserted. It either grows the DataWindow or replaces the oldest item
+   * @return {DataWindow} this
+   */
+  self.webgazer.util.DataWindow.prototype.push = function (entry) {
+    if (this.data.length < this.windowSize) {
+      this.data.push(entry);
+      this.length = this.data.length;
+      return this;
+    }
+
+    //replace oldest entry by wrapping around the DataWindow
+    this.data[this.index] = entry;
+    this.index = (this.index + 1) % this.windowSize;
+    return this;
+  };
+
+  /**
+   * Get the element at the ind position by wrapping around the DataWindow
+   * @param  {Number} ind index of desired entry
+   * @return {*}
+   */
+  self.webgazer.util.DataWindow.prototype.get = function (ind) {
+    return this.data[this.getTrueIndex(ind)];
+  };
+
+  /**
+   * Gets the true this.data array index given an index for a desired element
+   * @param {Number} ind - index of desired entry
+   * @return {Number} index of desired entry in this.data
+   */
+  self.webgazer.util.DataWindow.prototype.getTrueIndex = function (ind) {
+    if (this.data.length < this.windowSize) {
+      return ind;
+    } else {
+      //wrap around ind so that we can traverse from oldest to newest
+      return (ind + this.index) % this.windowSize;
+    }
+  };
+
+  /**
+   * Append all the contents of data
+   * @param {Array} data - to be inserted
+   */
+  self.webgazer.util.DataWindow.prototype.addAll = function (data) {
+    for (var i = 0; i < data.length; i++) {
+      this.push(data[i]);
+    }
+  };
+
+  //Helper functions
+  /**
+   * Grayscales an image patch. Can be used for the whole canvas, detected face, detected eye, etc.
+   *
+   * Code from tracking.js by Eduardo Lundgren, et al.
+   * https://github.com/eduardolundgren/tracking.js/blob/master/src/tracking.js
+   *
+   * Software License Agreement (BSD License) Copyright (c) 2014, Eduardo A. Lundgren Melo. All rights reserved.
+   * Redistribution and use of this software in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
+   * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
+   * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
+   * The name of Eduardo A. Lundgren Melo may not be used to endorse or promote products derived from this software without specific prior written permission of Eduardo A. Lundgren Melo.
+   * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
+   * IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+   * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
+   * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+   *
+   * @param  {Array} pixels - image data to be grayscaled
+   * @param  {Number} width  - width of image data to be grayscaled
+   * @param  {Number} height - height of image data to be grayscaled
+   * @return {Array} grayscaledImage
+   */
+  self.webgazer.util.grayscale = function (pixels, width, height) {
+    var gray = new Uint8ClampedArray(pixels.length >> 2);
+    var p = 0;
+    var w = 0;
+    for (var i = 0; i < height; i++) {
+      for (var j = 0; j < width; j++) {
+        var value = pixels[w] * 0.299 + pixels[w + 1] * 0.587 + pixels[w + 2] * 0.114;
+        gray[p++] = value;
+
+        w += 4;
+      }
+    }
+    return gray;
+  };
+
+  /**
+   * Increase contrast of an image.
+   *
+   * Code from Martin Tschirsich, Copyright (c) 2012.
+   * https://github.com/mtschirs/js-objectdetect/blob/gh-pages/js/objectdetect.js
+   *
+   * @param {Array} src - grayscale integer array
+   * @param {Number} step - sampling rate, control performance
+   * @param {Array} dst - array to hold the resulting image
+   */
+  self.webgazer.util.equalizeHistogram = function (src, step, dst) {
+    var srcLength = src.length;
+    if (!dst) dst = src;
+    if (!step) step = 5;
+
+    // Compute histogram and histogram sum:
+    var hist = [
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0,
+    ];
+
+    for (var i = 0; i < srcLength; i += step) {
+      ++hist[src[i]];
+    }
+
+    // Compute integral histogram:
+    var norm = (255 * step) / srcLength,
+      prev = 0;
+    for (var i = 0; i < 256; ++i) {
+      var h = hist[i];
+      prev = h += prev;
+      hist[i] = h * norm; // For non-integer src: ~~(h * norm + 0.5);
+    }
+
+    // Equalize image:
+    for (var i = 0; i < srcLength; ++i) {
+      dst[i] = hist[src[i]];
+    }
+    return dst;
+  };
+
+  self.webgazer.util.threshold = function (data, threshold) {
+    for (let i = 0; i < data.length; i++) {
+      data[i] = data[i] > threshold ? 255 : 0;
+    }
+    return data;
+  };
+
+  self.webgazer.util.correlation = function (data1, data2) {
+    const length = Math.min(data1.length, data2.length);
+    let count = 0;
+    for (let i = 0; i < length; i++) {
+      if (data1[i] === data2[i]) {
+        count++;
+      }
+    }
+    return count / Math.max(data1.length, data2.length);
+  };
+
+  /**
+   * Gets an Eye object and resizes it to the desired resolution
+   * @param  {webgazer.util.Eye} eye - patch to be resized
+   * @param  {Number} resizeWidth - desired width
+   * @param  {Number} resizeHeight - desired height
+   * @return {webgazer.util.Eye} resized eye patch
+   */
+  self.webgazer.util.resizeEye = function (eye, resizeWidth, resizeHeight) {
+    var canvas = document.createElement("canvas");
+    canvas.width = eye.width;
+    canvas.height = eye.height;
+
+    canvas.getContext("2d").putImageData(eye.patch, 0, 0);
+
+    var tempCanvas = document.createElement("canvas");
+
+    tempCanvas.width = resizeWidth;
+    tempCanvas.height = resizeHeight;
+
+    // save the canvas into temp canvas
+    tempCanvas
+      .getContext("2d")
+      .drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, resizeWidth, resizeHeight);
+
+    return tempCanvas.getContext("2d").getImageData(0, 0, resizeWidth, resizeHeight);
+  };
+
+  /**
+   * Checks if the prediction is within the boundaries of the viewport and constrains it
+   * @param  {Array} prediction [x,y] - predicted gaze coordinates
+   * @return {Array} constrained coordinates
+   */
+  self.webgazer.util.bound = function (prediction) {
+    if (prediction.x < 0) prediction.x = 0;
+    if (prediction.y < 0) prediction.y = 0;
+    var w = Math.max(document.documentElement.clientWidth, window.innerWidth || 0);
+    var h = Math.max(document.documentElement.clientHeight, window.innerHeight || 0);
+    if (prediction.x > w) {
+      prediction.x = w;
+    }
+
+    if (prediction.y > h) {
+      prediction.y = h;
+    }
+    return prediction;
+  };
+
+  /**
+   * Write statistics in debug paragraph panel
+   * @param {HTMLElement} para - The <p> tag where write data
+   * @param {Object} stats - The stats data to output
+   */
+  function debugBoxWrite(para, stats) {
+    var str = "";
+    for (var key in stats) {
+      str += key + ": " + stats[key] + "\n";
+    }
+    para.innerText = str;
+  }
+
+  /**
+   * Constructor of DebugBox object,
+   * it insert an paragraph inside a div to the body, in view to display debug data
+   * @param {Number} interval - The log interval
+   * @constructor
+   */
+  self.webgazer.util.DebugBox = function (interval) {
+    this.para = document.createElement("p");
+    this.div = document.createElement("div");
+    this.div.appendChild(this.para);
+    document.body.appendChild(this.div);
+
+    this.buttons = {};
+    this.canvas = {};
+    this.stats = {};
+    var updateInterval = interval || 300;
+    (function (localThis) {
+      setInterval(function () {
+        debugBoxWrite(localThis.para, localThis.stats);
+      }, updateInterval);
+    })(this);
+  };
+
+  /**
+   * Add stat data for log
+   * @param {String} key - The data key
+   * @param {*} value - The value
+   */
+  self.webgazer.util.DebugBox.prototype.set = function (key, value) {
+    this.stats[key] = value;
+  };
+
+  /**
+   * Initialize stats in case where key does not exist, else
+   * increment value for key
+   * @param {String} key - The key to process
+   * @param {Number} incBy - Value to increment for given key (default: 1)
+   * @param {Number} init - Initial value in case where key does not exist (default: 0)
+   */
+  self.webgazer.util.DebugBox.prototype.inc = function (key, incBy, init) {
+    if (!this.stats[key]) {
+      this.stats[key] = init || 0;
+    }
+    this.stats[key] += incBy || 1;
+  };
+
+  /**
+   * Create a button and register the given function to the button click event
+   * @param {String} name - The button name to link
+   * @param {Function} func - The onClick callback
+   */
+  self.webgazer.util.DebugBox.prototype.addButton = function (name, func) {
+    if (!this.buttons[name]) {
+      this.buttons[name] = document.createElement("button");
+      this.div.appendChild(this.buttons[name]);
+    }
+    var button = this.buttons[name];
+    this.buttons[name] = button;
+    button.addEventListener("click", func);
+    button.innerText = name;
+  };
+
+  /**
+   * Search for a canvas elemenet with name, or create on if not exist.
+   * Then send the canvas element as callback parameter.
+   * @param {String} name - The canvas name to send/create
+   * @param {Function} func - The callback function where send canvas
+   */
+  self.webgazer.util.DebugBox.prototype.show = function (name, func) {
+    if (!this.canvas[name]) {
+      this.canvas[name] = document.createElement("canvas");
+      this.div.appendChild(this.canvas[name]);
+    }
+    var canvas = this.canvas[name];
+    canvas.getContext("2d").clearRect(0, 0, canvas.width, canvas.height);
+    func(canvas);
+  };
+
+  /**
+   * Kalman Filter constructor
+   * Kalman filters work by reducing the amount of noise in a models.
+   * https://blog.cordiner.net/2011/05/03/object-tracking-using-a-kalman-filter-matlab/
+   *
+   * @param {Array.<Array.<Number>>} F - transition matrix
+   * @param {Array.<Array.<Number>>} Q - process noise matrix
+   * @param {Array.<Array.<Number>>} H - maps between measurement vector and noise matrix
+   * @param {Array.<Array.<Number>>} R - defines measurement error of the device
+   * @param {Array} P_initial - the initial state
+   * @param {Array} X_initial - the initial state of the device
+   */
+  self.webgazer.util.KalmanFilter = function (F, H, Q, R, P_initial, X_initial) {
+    this.F = F; // State transition matrix
+    this.Q = Q; // Process noise matrix
+    this.H = H; // Transformation matrix
+    this.R = R; // Measurement Noise
+    this.P = P_initial; //Initial covariance matrix
+    this.X = X_initial; //Initial guess of measurement
+  };
+
+  /**
+   * Get Kalman next filtered value and update the internal state
+   * @param {Array} z - the new measurement
+   * @return {Array}
+   */
+  self.webgazer.util.KalmanFilter.prototype.update = function (z) {
+    // Here, we define all the different matrix operations we will need
+    var add = numeric.add,
+      sub = numeric.sub,
+      inv = numeric.inv,
+      identity = numeric.identity;
+    var mult = webgazer.mat.mult,
+      transpose = webgazer.mat.transpose;
+    //TODO cache variables like the transpose of H
+
+    // prediction: X = F * X  |  P = F * P * F' + Q
+    var X_p = mult(this.F, this.X); //Update state vector
+    var P_p = add(mult(mult(this.F, this.P), transpose(this.F)), this.Q); //Predicted covaraince
+
+    //Calculate the update values
+    var y = sub(z, mult(this.H, X_p)); // This is the measurement error (between what we expect and the actual value)
+    var S = add(mult(mult(this.H, P_p), transpose(this.H)), this.R); //This is the residual covariance (the error in the covariance)
+
+    // kalman multiplier: K = P * H' * (H * P * H' + R)^-1
+    var K = mult(P_p, mult(transpose(this.H), inv(S))); //This is the Optimal Kalman Gain
+
+    //We need to change Y into it's column vector form
+    for (var i = 0; i < y.length; i++) {
+      y[i] = [y[i]];
+    }
+
+    //Now we correct the internal values of the model
+    // correction: X = X + K * (m - H * X)  |  P = (I - K * H) * P
+    this.X = add(X_p, mult(K, y));
+    this.P = mult(sub(identity(K.length), mult(K, this.H)), P_p);
+    return transpose(mult(this.H, this.X))[0]; //Transforms the predicted state back into it's measurement form
+  };
+})();
diff --git a/7.3/demos/jspsych-animation-demo.html b/7.3/demos/jspsych-animation-demo.html
old mode 100755
new mode 100644
index f4e0789167..68abe34efc
--- a/7.3/demos/jspsych-animation-demo.html
+++ b/7.3/demos/jspsych-animation-demo.html
@@ -1,51 +1,51 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-animation@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <style>
-      #jspsych-animation-image {
-        height: 80% !important;
-        width: 80% !important;
-      }
-      .jspsych-btn {
-        margin-bottom: 10px;
-      }
-    </style>
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    var preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    var animation_trial = {
-      type: jsPsychAnimation,
-      stimuli: [
-        'img/happy_face_1.jpg',
-        'img/happy_face_2.jpg',
-        'img/happy_face_3.jpg',
-        'img/happy_face_4.jpg'
-      ],
-      sequence_reps: 3,
-      frame_time: 300,
-      prompt: '<p style="margin-top:0px;">Watch the faces.</p>'
-    };
-
-    const timeline = [animation_trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-animation@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <style>
+      #jspsych-animation-image {
+        height: 80% !important;
+        width: 80% !important;
+      }
+      .jspsych-btn {
+        margin-bottom: 10px;
+      }
+    </style>
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    var preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    var animation_trial = {
+      type: jsPsychAnimation,
+      stimuli: [
+        'img/happy_face_1.jpg',
+        'img/happy_face_2.jpg',
+        'img/happy_face_3.jpg',
+        'img/happy_face_4.jpg'
+      ],
+      sequence_reps: 3,
+      frame_time: 300,
+      prompt: '<p style="margin-top:0px;">Watch the faces.</p>'
+    };
+
+    const timeline = [animation_trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-audio-button-response-demo-1.html b/7.3/demos/jspsych-audio-button-response-demo-1.html
old mode 100755
new mode 100644
index 497c27fd9f..959aaa7ade
--- a/7.3/demos/jspsych-audio-button-response-demo-1.html
+++ b/7.3/demos/jspsych-audio-button-response-demo-1.html
@@ -1,38 +1,38 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const timeline = [];
-
-    const preload = {
-      type: jsPsychPreload,
-      auto_preload: true
-    };
-
-    const trial = {
-      type: jsPsychAudioButtonResponse,
-      stimulus: 'sound/tone.mp3',
-      choices: ['Low', 'High'],
-      prompt: "<p>Is the pitch high or low?</p>"
-    };
-
-    timeline.push(trial);
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const timeline = [];
+
+    const preload = {
+      type: jsPsychPreload,
+      auto_preload: true
+    };
+
+    const trial = {
+      type: jsPsychAudioButtonResponse,
+      stimulus: 'sound/tone.mp3',
+      choices: ['Low', 'High'],
+      prompt: "<p>Is the pitch high or low?</p>"
+    };
+
+    timeline.push(trial);
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-audio-button-response-demo-2.html b/7.3/demos/jspsych-audio-button-response-demo-2.html
old mode 100755
new mode 100644
index af25d1278c..28a0114fee
--- a/7.3/demos/jspsych-audio-button-response-demo-2.html
+++ b/7.3/demos/jspsych-audio-button-response-demo-2.html
@@ -1,44 +1,44 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const timeline = [];
-
-    // sound source: https://www.videvo.net/sound-effect/lion-growl-angry-gene-pe931902/249942/
-    // images source: http://clipart-library.com/cartoon-animal-clipart.html
-    const images = ['img/lion.png', 'img/elephant.png', 'img/monkey.png']
-
-    const preload = {
-      type: jsPsychPreload,
-      auto_preload: true,
-      images: images
-    }
-
-    const trial = {
-    	type: jsPsychAudioButtonResponse,
-    	stimulus: 'sound/roar.mp3',
-    	choices: images,
-    	prompt: "<p>Which animal made the sound?</p>",
-    	button_html: '<img src="%choice%" />'
-    };
-
-    timeline.push(trial);
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const timeline = [];
+
+    // sound source: https://www.videvo.net/sound-effect/lion-growl-angry-gene-pe931902/249942/
+    // images source: http://clipart-library.com/cartoon-animal-clipart.html
+    const images = ['img/lion.png', 'img/elephant.png', 'img/monkey.png']
+
+    const preload = {
+      type: jsPsychPreload,
+      auto_preload: true,
+      images: images
+    }
+
+    const trial = {
+    	type: jsPsychAudioButtonResponse,
+    	stimulus: 'sound/roar.mp3',
+    	choices: images,
+    	prompt: "<p>Which animal made the sound?</p>",
+    	button_html: '<img src="%choice%" />'
+    };
+
+    timeline.push(trial);
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-audio-keyboard-response-demo-1.html b/7.3/demos/jspsych-audio-keyboard-response-demo-1.html
old mode 100755
new mode 100644
index 7651ff545f..80fbb121b5
--- a/7.3/demos/jspsych-audio-keyboard-response-demo-1.html
+++ b/7.3/demos/jspsych-audio-keyboard-response-demo-1.html
@@ -1,37 +1,37 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial = {
-      type: jsPsychAudioKeyboardResponse,
-      stimulus: 'sound/tone.mp3',
-      choices: ['e', 'i'],
-      prompt: "<p>Is the pitch high or low? Press 'e' for low and 'i' for high.</p>",
-      response_ends_trial: true
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial = {
+      type: jsPsychAudioKeyboardResponse,
+      stimulus: 'sound/tone.mp3',
+      choices: ['e', 'i'],
+      prompt: "<p>Is the pitch high or low? Press 'e' for low and 'i' for high.</p>",
+      response_ends_trial: true
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-audio-keyboard-response-demo-2.html b/7.3/demos/jspsych-audio-keyboard-response-demo-2.html
old mode 100755
new mode 100644
index 8a1f926005..2a8fa4b167
--- a/7.3/demos/jspsych-audio-keyboard-response-demo-2.html
+++ b/7.3/demos/jspsych-audio-keyboard-response-demo-2.html
@@ -1,37 +1,37 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-
-    const trial = {
-      type: jsPsychAudioKeyboardResponse,
-      stimulus: 'sound/tone.mp3',
-      choices: "NO_KEYS",
-      trial_ends_after_audio: true
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+
+    const trial = {
+      type: jsPsychAudioKeyboardResponse,
+      stimulus: 'sound/tone.mp3',
+      choices: "NO_KEYS",
+      trial_ends_after_audio: true
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-audio-slider-response-demo-1.html b/7.3/demos/jspsych-audio-slider-response-demo-1.html
old mode 100755
new mode 100644
index 48ee1204dc..1fb02d32fd
--- a/7.3/demos/jspsych-audio-slider-response-demo-1.html
+++ b/7.3/demos/jspsych-audio-slider-response-demo-1.html
@@ -1,36 +1,36 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      auto_preload: true
-    };
-
-    const trial = {
-      type: jsPsychAudioSliderResponse,
-      stimulus: 'sound/speech_joke.mp3',
-      labels: ['Not Funny', 'Funny'],
-      prompt: '<p>How funny is the joke?</p>'
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      auto_preload: true
+    };
+
+    const trial = {
+      type: jsPsychAudioSliderResponse,
+      stimulus: 'sound/speech_joke.mp3',
+      labels: ['Not Funny', 'Funny'],
+      prompt: '<p>How funny is the joke?</p>'
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-audio-slider-response-demo-2.html b/7.3/demos/jspsych-audio-slider-response-demo-2.html
old mode 100755
new mode 100644
index 66976f8e7d..45ffe8ba77
--- a/7.3/demos/jspsych-audio-slider-response-demo-2.html
+++ b/7.3/demos/jspsych-audio-slider-response-demo-2.html
@@ -1,38 +1,38 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      auto_preload: true
-    };
-
-    const trial = {
-      type: jsPsychAudioSliderResponse,
-      stimulus: 'sound/speech_joke.mp3',
-      labels: ['Not Funny', 'Funny'],
-      prompt: '<p>How funny is the joke?</p>',
-      response_allowed_while_playing: false,
-      require_movement: true
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      auto_preload: true
+    };
+
+    const trial = {
+      type: jsPsychAudioSliderResponse,
+      stimulus: 'sound/speech_joke.mp3',
+      labels: ['Not Funny', 'Funny'],
+      prompt: '<p>How funny is the joke?</p>',
+      response_allowed_while_playing: false,
+      require_movement: true
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-browser-check-demo1.html b/7.3/demos/jspsych-browser-check-demo1.html
old mode 100755
new mode 100644
index 3f1d6ddcf5..a4bbb5145e
--- a/7.3/demos/jspsych-browser-check-demo1.html
+++ b/7.3/demos/jspsych-browser-check-demo1.html
@@ -1,27 +1,27 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-browser-check@1.0.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychBrowserCheck
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-browser-check@1.0.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychBrowserCheck
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-browser-check-demo2.html b/7.3/demos/jspsych-browser-check-demo2.html
old mode 100755
new mode 100644
index ecbe044ab2..84a337e33c
--- a/7.3/demos/jspsych-browser-check-demo2.html
+++ b/7.3/demos/jspsych-browser-check-demo2.html
@@ -1,33 +1,33 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-browser-check@1.0.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-    
-    const trial = {
-      type: jsPsychBrowserCheck,
-      inclusion_function: (data) => {
-        return ['chrome', 'firefox'].includes(data.browser);
-      },
-      exclusion_message: (data) => {
-            return `<p>You must use Chrome or Firefox to complete this experiment.</p>`
-      },
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-browser-check@1.0.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+    
+    const trial = {
+      type: jsPsychBrowserCheck,
+      inclusion_function: (data) => {
+        return ['chrome', 'firefox'].includes(data.browser);
+      },
+      exclusion_message: (data) => {
+            return `<p>You must use Chrome or Firefox to complete this experiment.</p>`
+      },
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-browser-check-demo3.html b/7.3/demos/jspsych-browser-check-demo3.html
old mode 100755
new mode 100644
index 407265d404..e95a31d018
--- a/7.3/demos/jspsych-browser-check-demo3.html
+++ b/7.3/demos/jspsych-browser-check-demo3.html
@@ -1,35 +1,35 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-browser-check@1.0.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const instructions = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: '<p>If you want to test the interactive resize, make your browser window small before continuing.</p>',
-      choices: ['OK']
-    };
-
-    const trial = {
-      type: jsPsychBrowserCheck,
-      minimum_width: 1000,
-      minimum_height: 600
-    };
-    
-    const timeline = [instructions, trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-browser-check@1.0.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const instructions = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: '<p>If you want to test the interactive resize, make your browser window small before continuing.</p>',
+      choices: ['OK']
+    };
+
+    const trial = {
+      type: jsPsychBrowserCheck,
+      minimum_width: 1000,
+      minimum_height: 600
+    };
+    
+    const timeline = [instructions, trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-browser-check-demo4.html b/7.3/demos/jspsych-browser-check-demo4.html
old mode 100755
new mode 100644
index 72e20dd8eb..027a3ba9a9
--- a/7.3/demos/jspsych-browser-check-demo4.html
+++ b/7.3/demos/jspsych-browser-check-demo4.html
@@ -1,37 +1,37 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-browser-check@1.0.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychBrowserCheck,
-      inclusion_function: (data) => {
-        return data.browser == 'chrome' && data.mobile === false
-      },
-      exclusion_message: (data) => {
-        if(data.mobile){
-          return '<p>You must use a desktop/laptop computer to participate in this experiment.</p>';
-        } else if(data.browser !== 'chrome'){
-          return '<p>You must use Chrome as your browser to complete this experiment.</p>'
-        }
-      }
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-browser-check@1.0.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychBrowserCheck,
+      inclusion_function: (data) => {
+        return data.browser == 'chrome' && data.mobile === false
+      },
+      exclusion_message: (data) => {
+        if(data.mobile){
+          return '<p>You must use a desktop/laptop computer to participate in this experiment.</p>';
+        } else if(data.browser !== 'chrome'){
+          return '<p>You must use Chrome as your browser to complete this experiment.</p>'
+        }
+      }
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-call-function-demo1.html b/7.3/demos/jspsych-call-function-demo1.html
old mode 100755
new mode 100644
index 081c668f8e..e621d86df1
--- a/7.3/demos/jspsych-call-function-demo1.html
+++ b/7.3/demos/jspsych-call-function-demo1.html
@@ -1,33 +1,33 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-call-function@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const myfunc = function() {
-      return 'you called?';
-    }
-
-    const trial = {
-      type: jsPsychCallFunction,
-      func: myfunc
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-call-function@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const myfunc = function() {
+      return 'you called?';
+    }
+
+    const trial = {
+      type: jsPsychCallFunction,
+      func: myfunc
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-call-function-demo2.html b/7.3/demos/jspsych-call-function-demo2.html
old mode 100755
new mode 100644
index 36351d623c..8c384cc472
--- a/7.3/demos/jspsych-call-function-demo2.html
+++ b/7.3/demos/jspsych-call-function-demo2.html
@@ -1,38 +1,38 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-call-function@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    //   Using an anonymous function to pass variables
-
-    const myfunc = function(data){
-      // data contains all the experiment data so far,
-      // so this function could implement code to write
-      // the data to a database.
-      console.log(data.values())
-    }
-
-    const trial = {
-      type: jsPsychCallFunction,
-      func: function(){ myfunc(jsPsych.data.get()) }
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-call-function@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    //   Using an anonymous function to pass variables
+
+    const myfunc = function(data){
+      // data contains all the experiment data so far,
+      // so this function could implement code to write
+      // the data to a database.
+      console.log(data.values())
+    }
+
+    const trial = {
+      type: jsPsychCallFunction,
+      func: function(){ myfunc(jsPsych.data.get()) }
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-call-function-demo3.html b/7.3/demos/jspsych-call-function-demo3.html
old mode 100755
new mode 100644
index c5a65cc891..21276d5f66
--- a/7.3/demos/jspsych-call-function-demo3.html
+++ b/7.3/demos/jspsych-call-function-demo3.html
@@ -1,39 +1,39 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-call-function@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychCallFunction,
-      async: true,
-      func: function(done){
-        // generate a delay between 1500 and 3000 milliseconds to simulate
-        // waiting for an event to finish after an unknown duration,
-        // then finish the trial
-        const rand_delay = (Math.floor(Math.random() * (3000 - 1500 + 1) + 1500));
-        jsPsych.pluginAPI.setTimeout(function() {
-          // end the trial and save the delay duration to the data
-          done(rand_delay.toString()+"ms");
-        }, rand_delay)
-      }
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-call-function@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychCallFunction,
+      async: true,
+      func: function(done){
+        // generate a delay between 1500 and 3000 milliseconds to simulate
+        // waiting for an event to finish after an unknown duration,
+        // then finish the trial
+        const rand_delay = (Math.floor(Math.random() * (3000 - 1500 + 1) + 1500));
+        jsPsych.pluginAPI.setTimeout(function() {
+          // end the trial and save the delay duration to the data
+          done(rand_delay.toString()+"ms");
+        }, rand_delay)
+      }
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-canvas-button-response-demo1.html b/7.3/demos/jspsych-canvas-button-response-demo1.html
old mode 100755
new mode 100644
index fd68096d2d..06500a9f96
--- a/7.3/demos/jspsych-canvas-button-response-demo1.html
+++ b/7.3/demos/jspsych-canvas-button-response-demo1.html
@@ -1,58 +1,58 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    // stimulus function that takes the canvas and additional parameters (radius, color)
-    // this can be called inside of an anonymous stimulus function, which takes the canvas (c) as its only argument
-    function filledCirc(canvas, radius, color) {
-      var ctx = canvas.getContext("2d");
-      ctx.beginPath();
-      ctx.arc(150, 150, radius, 0, 2 * Math.PI);
-      ctx.fillStyle = color;
-      ctx.fill();
-    }
-
-    const circle_1 = {
-      type: jsPsychCanvasButtonResponse,
-      stimulus: function(c) {
-        filledCirc(c, 100, 'blue');
-      },
-      canvas_size: [300, 300],
-      choices: ['Red', 'Green', 'Blue'],
-      prompt: '<p>What color is the circle?</p>',
-      data: {color: 'blue', radius: 100}
-    };
-
-    const circle_2 = {
-      type: jsPsychCanvasButtonResponse,
-      stimulus: function(c) {
-        filledCirc(c, 150, 'green');
-      },
-      canvas_size: [300, 300],
-      choices: ['Larger', 'Smaller'],
-      stimulus_duration: 1000,
-      prompt: '<p>Is this circle larger or smaller than the last one?</p>'+
-        '<p>Stimulus will be hidden after 1 second.</p>',
-      data: {color: 'green', radius: 150}
-    };
-
-    const timeline = [circle_1, circle_2];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    // stimulus function that takes the canvas and additional parameters (radius, color)
+    // this can be called inside of an anonymous stimulus function, which takes the canvas (c) as its only argument
+    function filledCirc(canvas, radius, color) {
+      var ctx = canvas.getContext("2d");
+      ctx.beginPath();
+      ctx.arc(150, 150, radius, 0, 2 * Math.PI);
+      ctx.fillStyle = color;
+      ctx.fill();
+    }
+
+    const circle_1 = {
+      type: jsPsychCanvasButtonResponse,
+      stimulus: function(c) {
+        filledCirc(c, 100, 'blue');
+      },
+      canvas_size: [300, 300],
+      choices: ['Red', 'Green', 'Blue'],
+      prompt: '<p>What color is the circle?</p>',
+      data: {color: 'blue', radius: 100}
+    };
+
+    const circle_2 = {
+      type: jsPsychCanvasButtonResponse,
+      stimulus: function(c) {
+        filledCirc(c, 150, 'green');
+      },
+      canvas_size: [300, 300],
+      choices: ['Larger', 'Smaller'],
+      stimulus_duration: 1000,
+      prompt: '<p>Is this circle larger or smaller than the last one?</p>'+
+        '<p>Stimulus will be hidden after 1 second.</p>',
+      data: {color: 'green', radius: 150}
+    };
+
+    const timeline = [circle_1, circle_2];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-canvas-button-response-demo2.html b/7.3/demos/jspsych-canvas-button-response-demo2.html
old mode 100755
new mode 100644
index e80e8bc861..fc9c58fffa
--- a/7.3/demos/jspsych-canvas-button-response-demo2.html
+++ b/7.3/demos/jspsych-canvas-button-response-demo2.html
@@ -1,51 +1,51 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    // write the canvas stimulus drawing function without using a named function
-    // the anonymous function must take the canvas as an argument
-    const lines = {
-      type: jsPsychCanvasButtonResponse,
-      stimulus: function(c) {
-        const ctx = c.getContext("2d");
-        // first line
-        ctx.beginPath();
-        ctx.moveTo(200, 10);
-        ctx.lineTo(200, 250);
-        ctx.lineWidth = 10;
-        ctx.strokeStyle = 'MediumBlue';
-        ctx.stroke();
-        // second line
-        ctx.beginPath();
-        ctx.moveTo(20, 100);
-        ctx.lineTo(100, 250);
-        ctx.lineWidth = 10;
-        ctx.strokeStyle = 'MediumPurple';
-        ctx.stroke();
-      },
-      canvas_size: [300, 300],
-      choices: ['Blue line', 'Purple line'],
-      prompt: '<p>Which line is longer?</p>',
-      data: {line1_color: 'blue', line1_length: 290, line2_color: "purple", line2_length: 170}
-    };
-
-    const timeline = [lines];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    // write the canvas stimulus drawing function without using a named function
+    // the anonymous function must take the canvas as an argument
+    const lines = {
+      type: jsPsychCanvasButtonResponse,
+      stimulus: function(c) {
+        const ctx = c.getContext("2d");
+        // first line
+        ctx.beginPath();
+        ctx.moveTo(200, 10);
+        ctx.lineTo(200, 250);
+        ctx.lineWidth = 10;
+        ctx.strokeStyle = 'MediumBlue';
+        ctx.stroke();
+        // second line
+        ctx.beginPath();
+        ctx.moveTo(20, 100);
+        ctx.lineTo(100, 250);
+        ctx.lineWidth = 10;
+        ctx.strokeStyle = 'MediumPurple';
+        ctx.stroke();
+      },
+      canvas_size: [300, 300],
+      choices: ['Blue line', 'Purple line'],
+      prompt: '<p>Which line is longer?</p>',
+      data: {line1_color: 'blue', line1_length: 290, line2_color: "purple", line2_length: 170}
+    };
+
+    const timeline = [lines];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-canvas-button-response-demo3.html b/7.3/demos/jspsych-canvas-button-response-demo3.html
old mode 100755
new mode 100644
index bd6c2176aa..631706d5a0
--- a/7.3/demos/jspsych-canvas-button-response-demo3.html
+++ b/7.3/demos/jspsych-canvas-button-response-demo3.html
@@ -1,61 +1,61 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    function filledCirc(canvas, radius, color) {
-      var ctx = canvas.getContext("2d");
-      ctx.beginPath();
-      ctx.arc(150, 150, radius, 0, 2 * Math.PI);
-      ctx.fillStyle = color;
-      ctx.fill();
-    }
-
-    // To use the canvas stimulus function with timeline variables,
-    // the jsPsych.timelineVariable() function can be used inside your stimulus function.
-    // In addition, this code demonstrates how to check whether participants' answers were correct or not.
-    const circle_procedure = {
-      timeline: [{
-        type: jsPsychCanvasButtonResponse,
-        stimulus: function(c) {
-            filledCirc(c, jsPsych.timelineVariable('radius'), jsPsych.timelineVariable('color'));
-        },
-        canvas_size: [300, 300],
-        choices: ['Red', 'Green', 'Blue'],
-        prompt: '<p>What color is the circle?</p>',
-        data: {
-          radius: jsPsych.timelineVariable('radius'),
-          color: jsPsych.timelineVariable('color'),
-          correct_response: jsPsych.timelineVariable('correct_response')
-        },
-        on_finish: function(data){
-          data.correct = (data.response == data.correct_response);
-        }
-      }],
-      timeline_variables: [
-        {radius: 80, color: 'red', correct_response: 0},
-        {radius: 100, color: 'green', correct_response: 1},
-        {radius: 50, color: 'blue', correct_response: 2}
-      ],
-      randomize_order: true
-    };
-
-    const timeline = [circle_procedure];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    function filledCirc(canvas, radius, color) {
+      var ctx = canvas.getContext("2d");
+      ctx.beginPath();
+      ctx.arc(150, 150, radius, 0, 2 * Math.PI);
+      ctx.fillStyle = color;
+      ctx.fill();
+    }
+
+    // To use the canvas stimulus function with timeline variables,
+    // the jsPsych.timelineVariable() function can be used inside your stimulus function.
+    // In addition, this code demonstrates how to check whether participants' answers were correct or not.
+    const circle_procedure = {
+      timeline: [{
+        type: jsPsychCanvasButtonResponse,
+        stimulus: function(c) {
+            filledCirc(c, jsPsych.timelineVariable('radius'), jsPsych.timelineVariable('color'));
+        },
+        canvas_size: [300, 300],
+        choices: ['Red', 'Green', 'Blue'],
+        prompt: '<p>What color is the circle?</p>',
+        data: {
+          radius: jsPsych.timelineVariable('radius'),
+          color: jsPsych.timelineVariable('color'),
+          correct_response: jsPsych.timelineVariable('correct_response')
+        },
+        on_finish: function(data){
+          data.correct = (data.response == data.correct_response);
+        }
+      }],
+      timeline_variables: [
+        {radius: 80, color: 'red', correct_response: 0},
+        {radius: 100, color: 'green', correct_response: 1},
+        {radius: 50, color: 'blue', correct_response: 2}
+      ],
+      randomize_order: true
+    };
+
+    const timeline = [circle_procedure];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-canvas-keyboard-response-demo1.html b/7.3/demos/jspsych-canvas-keyboard-response-demo1.html
old mode 100755
new mode 100644
index 3c1be6f1c4..a92ecdd29f
--- a/7.3/demos/jspsych-canvas-keyboard-response-demo1.html
+++ b/7.3/demos/jspsych-canvas-keyboard-response-demo1.html
@@ -1,40 +1,40 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    function drawRect(c){
-      const ctx = c.getContext('2d');
-      ctx.beginPath();
-      ctx.rect(30, 30, 200, 50);
-      ctx.stroke();
-    }
-
-    const trial = {
-      type: jsPsychCanvasKeyboardResponse,
-      canvas_size: [300, 300],
-      stimulus: drawRect,
-      choices: ['e','i'],
-      prompt: '<p>Is this a circle or a rectangle? Press "e" for circle and "i" for rectangle.</p>',
-      data: {shape: 'rectangle'}
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    function drawRect(c){
+      const ctx = c.getContext('2d');
+      ctx.beginPath();
+      ctx.rect(30, 30, 200, 50);
+      ctx.stroke();
+    }
+
+    const trial = {
+      type: jsPsychCanvasKeyboardResponse,
+      canvas_size: [300, 300],
+      stimulus: drawRect,
+      choices: ['e','i'],
+      prompt: '<p>Is this a circle or a rectangle? Press "e" for circle and "i" for rectangle.</p>',
+      data: {shape: 'rectangle'}
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-canvas-keyboard-response-demo2.html b/7.3/demos/jspsych-canvas-keyboard-response-demo2.html
old mode 100755
new mode 100644
index 1adb3182ae..5a6fa470dc
--- a/7.3/demos/jspsych-canvas-keyboard-response-demo2.html
+++ b/7.3/demos/jspsych-canvas-keyboard-response-demo2.html
@@ -1,41 +1,41 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    function drawCirc(c){
-      const ctx = c.getContext('2d');
-      ctx.beginPath();
-      ctx.arc(100, 75, 50, 0, 2 * Math.PI);
-      ctx.stroke();
-    }
-
-    const trial = {
-      type: jsPsychCanvasKeyboardResponse,
-      canvas_size: [300, 300],
-      stimulus: drawCirc,
-      prompt: '<p>No key response is allowed.</p><p>The stimulus disappears after 3 seconds.</p>',
-      choices: "NO_KEYS",
-      trial_duration: 3000,
-      data: {shape: 'circle', radius: 50}
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    function drawCirc(c){
+      const ctx = c.getContext('2d');
+      ctx.beginPath();
+      ctx.arc(100, 75, 50, 0, 2 * Math.PI);
+      ctx.stroke();
+    }
+
+    const trial = {
+      type: jsPsychCanvasKeyboardResponse,
+      canvas_size: [300, 300],
+      stimulus: drawCirc,
+      prompt: '<p>No key response is allowed.</p><p>The stimulus disappears after 3 seconds.</p>',
+      choices: "NO_KEYS",
+      trial_duration: 3000,
+      data: {shape: 'circle', radius: 50}
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-canvas-slider-response-demo1.html b/7.3/demos/jspsych-canvas-slider-response-demo1.html
old mode 100755
new mode 100644
index e8c306c819..073e52519d
--- a/7.3/demos/jspsych-canvas-slider-response-demo1.html
+++ b/7.3/demos/jspsych-canvas-slider-response-demo1.html
@@ -1,45 +1,45 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    // Draw two squares
-
-    const colors = ['#FF3333', '#FF6A33'];
-
-    function twoSquares(c) {
-      const ctx = c.getContext('2d');
-      ctx.fillStyle = colors[0];
-      ctx.fillRect(200, 70, 40, 40);
-      ctx.fillStyle = colors[1];
-      ctx.fillRect(260, 70, 40, 40);
-    }
-
-    const trial = {
-      type: jsPsychCanvasSliderResponse,
-      stimulus: twoSquares,
-      labels: ['0','10'],
-      canvas_size: [150, 500],
-      prompt: '<p>How different would you say the colors of these two squares are on a scale from 0 (the same) to 10 (completely different)</p>',
-      data: {color1: colors[0], color2: colors[1]}
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    // Draw two squares
+
+    const colors = ['#FF3333', '#FF6A33'];
+
+    function twoSquares(c) {
+      const ctx = c.getContext('2d');
+      ctx.fillStyle = colors[0];
+      ctx.fillRect(200, 70, 40, 40);
+      ctx.fillStyle = colors[1];
+      ctx.fillRect(260, 70, 40, 40);
+    }
+
+    const trial = {
+      type: jsPsychCanvasSliderResponse,
+      stimulus: twoSquares,
+      labels: ['0','10'],
+      canvas_size: [150, 500],
+      prompt: '<p>How different would you say the colors of these two squares are on a scale from 0 (the same) to 10 (completely different)</p>',
+      data: {color1: colors[0], color2: colors[1]}
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-canvas-slider-response-demo2.html b/7.3/demos/jspsych-canvas-slider-response-demo2.html
old mode 100755
new mode 100644
index ae538af2ae..438f02849f
--- a/7.3/demos/jspsych-canvas-slider-response-demo2.html
+++ b/7.3/demos/jspsych-canvas-slider-response-demo2.html
@@ -1,51 +1,51 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    // Draw two squares with additional parameters
-
-    let colors;
-
-    function twoSquares(c, colors) {
-      const ctx = c.getContext('2d');
-      ctx.fillStyle = colors[0];
-      ctx.fillRect(200, 70, 40, 40);
-      ctx.fillStyle = colors[1];
-      ctx.fillRect(260, 70, 40, 40);
-    }
-
-    const trial = {
-      type: jsPsychCanvasSliderResponse,
-      stimulus: function(c) {
-          colors = ['darkred', 'cyan'];
-          twoSquares(c, colors);
-      },
-      labels: ['Exactly<br>the same','Totally<br>different'],
-      canvas_size: [200, 500],
-      prompt: '<p>How different would you say the colors of these two squares are?</p>',
-      on_finish: function(data) {
-          data.color1 = colors[0];
-          data.color2 = colors[1];
-      }
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    // Draw two squares with additional parameters
+
+    let colors;
+
+    function twoSquares(c, colors) {
+      const ctx = c.getContext('2d');
+      ctx.fillStyle = colors[0];
+      ctx.fillRect(200, 70, 40, 40);
+      ctx.fillStyle = colors[1];
+      ctx.fillRect(260, 70, 40, 40);
+    }
+
+    const trial = {
+      type: jsPsychCanvasSliderResponse,
+      stimulus: function(c) {
+          colors = ['darkred', 'cyan'];
+          twoSquares(c, colors);
+      },
+      labels: ['Exactly<br>the same','Totally<br>different'],
+      canvas_size: [200, 500],
+      prompt: '<p>How different would you say the colors of these two squares are?</p>',
+      on_finish: function(data) {
+          data.color1 = colors[0];
+          data.color2 = colors[1];
+      }
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-categorize-animation-demo1.html b/7.3/demos/jspsych-categorize-animation-demo1.html
old mode 100755
new mode 100644
index 19beeb0748..297917f6c8
--- a/7.3/demos/jspsych-categorize-animation-demo1.html
+++ b/7.3/demos/jspsych-categorize-animation-demo1.html
@@ -1,51 +1,51 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <style>
-      #jspsych-categorize-animation-stimulus {
-        height: 80% !important;
-        width: 80% !important;
-      }
-      .jspsych-btn {
-        margin-bottom: 10px;
-      }
-    </style>
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial = {
-      type: jsPsychCategorizeAnimation,
-      stimuli: [
-        'img/happy_face_1.jpg',
-        'img/happy_face_2.jpg',
-        'img/happy_face_3.jpg',
-        'img/happy_face_4.jpg'
-      ],
-      prompt: `Press the P or Q key.`,
-      choices: ['p', 'q'],
-      key_answer: 'q',
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <style>
+      #jspsych-categorize-animation-stimulus {
+        height: 80% !important;
+        width: 80% !important;
+      }
+      .jspsych-btn {
+        margin-bottom: 10px;
+      }
+    </style>
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial = {
+      type: jsPsychCategorizeAnimation,
+      stimuli: [
+        'img/happy_face_1.jpg',
+        'img/happy_face_2.jpg',
+        'img/happy_face_3.jpg',
+        'img/happy_face_4.jpg'
+      ],
+      prompt: `Press the P or Q key.`,
+      choices: ['p', 'q'],
+      key_answer: 'q',
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-categorize-animation-demo2.html b/7.3/demos/jspsych-categorize-animation-demo2.html
old mode 100755
new mode 100644
index 0953b880bf..9f0499005f
--- a/7.3/demos/jspsych-categorize-animation-demo2.html
+++ b/7.3/demos/jspsych-categorize-animation-demo2.html
@@ -1,56 +1,56 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <style>
-      #jspsych-categorize-animation-stimulus {
-        height: 80% !important;
-        width: 80% !important;
-      }
-      .jspsych-btn {
-        margin-bottom: 10px;
-      }
-    </style>
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const images = [
-        'img/happy_face_1.jpg',
-        'img/happy_face_2.jpg',
-        'img/happy_face_3.jpg',
-        'img/happy_face_4.jpg'
-    ];
-
-    const trial = {
-      type: jsPsychCategorizeAnimation,
-      stimuli: images,
-      choices: ['p', 'q'],
-      prompt: `Press the P or Q key.`,
-      key_answer: 'q',
-      text_answer: 'Dax', // the label for the sequence is 'Dax'
-      correct_text: 'Correct! This was a %ANS%.',
-      incorrect_text: 'Incorrect. This was a %ANS%.'
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <style>
+      #jspsych-categorize-animation-stimulus {
+        height: 80% !important;
+        width: 80% !important;
+      }
+      .jspsych-btn {
+        margin-bottom: 10px;
+      }
+    </style>
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const images = [
+        'img/happy_face_1.jpg',
+        'img/happy_face_2.jpg',
+        'img/happy_face_3.jpg',
+        'img/happy_face_4.jpg'
+    ];
+
+    const trial = {
+      type: jsPsychCategorizeAnimation,
+      stimuli: images,
+      choices: ['p', 'q'],
+      prompt: `Press the P or Q key.`,
+      key_answer: 'q',
+      text_answer: 'Dax', // the label for the sequence is 'Dax'
+      correct_text: 'Correct! This was a %ANS%.',
+      incorrect_text: 'Incorrect. This was a %ANS%.'
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-categorize-html-demo1.html b/7.3/demos/jspsych-categorize-html-demo1.html
old mode 100755
new mode 100644
index fef775fa15..ffebfb0c09
--- a/7.3/demos/jspsych-categorize-html-demo1.html
+++ b/7.3/demos/jspsych-categorize-html-demo1.html
@@ -1,35 +1,35 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-categorize-html@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychCategorizeHtml,
-      stimulus: '<p>B</p>',
-      key_answer: 'p',
-      text_answer: 'letter',
-      choices: ['p', 'q'],
-      correct_text: "<p class='prompt'>Correct, this is a %ANS%.</p>",
-      incorrect_text: "<p class='prompt'>Incorrect, this is a %ANS%.</p>",
-      prompt: "<p>Press p for letter. Press q for number.</p>"
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-categorize-html@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychCategorizeHtml,
+      stimulus: '<p>B</p>',
+      key_answer: 'p',
+      text_answer: 'letter',
+      choices: ['p', 'q'],
+      correct_text: "<p class='prompt'>Correct, this is a %ANS%.</p>",
+      incorrect_text: "<p class='prompt'>Incorrect, this is a %ANS%.</p>",
+      prompt: "<p>Press p for letter. Press q for number.</p>"
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-categorize-image-demo1.html b/7.3/demos/jspsych-categorize-image-demo1.html
old mode 100755
new mode 100644
index 82cdad7c14..5476115555
--- a/7.3/demos/jspsych-categorize-image-demo1.html
+++ b/7.3/demos/jspsych-categorize-image-demo1.html
@@ -1,41 +1,41 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-categorize-image@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    var preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial = {
-      type: jsPsychCategorizeImage,
-      stimulus: 'img/blue.png',
-      key_answer: 'b',
-      text_answer: 'Blue',
-      choices: ['r', 'g', 'b'],
-      correct_text: "<p class='prompt'>Correct! The color is %ANS%.</p>",
-      incorrect_text: "<p class='prompt'>Incorrect. The color is %ANS%.</p>",
-      prompt: "<p>Is the color of this circle (R)ed, (G)reen, or (B)lue?</p>"
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-categorize-image@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    var preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial = {
+      type: jsPsychCategorizeImage,
+      stimulus: 'img/blue.png',
+      key_answer: 'b',
+      text_answer: 'Blue',
+      choices: ['r', 'g', 'b'],
+      correct_text: "<p class='prompt'>Correct! The color is %ANS%.</p>",
+      incorrect_text: "<p class='prompt'>Incorrect. The color is %ANS%.</p>",
+      prompt: "<p>Is the color of this circle (R)ed, (G)reen, or (B)lue?</p>"
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-cloze-demo1.html b/7.3/demos/jspsych-cloze-demo1.html
old mode 100755
new mode 100644
index 0247836656..50817d132d
--- a/7.3/demos/jspsych-cloze-demo1.html
+++ b/7.3/demos/jspsych-cloze-demo1.html
@@ -1,29 +1,29 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-cloze@1.2.0"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychCloze,
-      text: 'The %% is the largest terrestrial mammal. It lives in both %% and %%.'
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-cloze@1.2.1"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychCloze,
+      text: 'The %% is the largest terrestrial mammal. It lives in both %% and %%.'
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-cloze-demo2.html b/7.3/demos/jspsych-cloze-demo2.html
old mode 100755
new mode 100644
index dca20314a6..84817ed562
--- a/7.3/demos/jspsych-cloze-demo2.html
+++ b/7.3/demos/jspsych-cloze-demo2.html
@@ -1,32 +1,32 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-cloze@1.2.0"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-    
-    const trial = {
-      type: jsPsychCloze,
-      text: 'A rectangle has % 4 % corners and a triangle has % 3 %.',
-      check_answers: true,
-      button_text: 'Next',
-      mistake_fn: function(){alert("Wrong answer. Please check again.")}
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-cloze@1.2.1"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+    
+    const trial = {
+      type: jsPsychCloze,
+      text: 'A rectangle has % 4 % corners and a triangle has % 3 %.',
+      check_answers: true,
+      button_text: 'Next',
+      mistake_fn: function(){alert("Wrong answer. Please check again.")}
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-cloze-demo3.html b/7.3/demos/jspsych-cloze-demo3.html
old mode 100755
new mode 100644
index 15ccaf393f..584e26ea45
--- a/7.3/demos/jspsych-cloze-demo3.html
+++ b/7.3/demos/jspsych-cloze-demo3.html
@@ -1,31 +1,31 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-cloze@1.2.0"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-    
-    var trial = {
-        type: jsPsychCloze,
-        text: 'Science notebooks have a %%-colored front cover. Math notebooks have a %%-colored front cover.',
-        allow_blanks: false,
-        mistake_fn: function() { alert('Please fill in all blanks.'); }
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-cloze@1.2.1"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+    
+    var trial = {
+        type: jsPsychCloze,
+        text: 'Science notebooks have a %%-colored front cover. Math notebooks have a %%-colored front cover.',
+        allow_blanks: false,
+        mistake_fn: function() { alert('Please fill in all blanks.'); }
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-extension-mouse-tracking-demo1.html b/7.3/demos/jspsych-extension-mouse-tracking-demo1.html
old mode 100755
new mode 100644
index 7f657a1712..f5d72081f6
--- a/7.3/demos/jspsych-extension-mouse-tracking-demo1.html
+++ b/7.3/demos/jspsych-extension-mouse-tracking-demo1.html
@@ -1,74 +1,74 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <!--<script src="../../packages/extension-mouse-tracking/dist/index.browser.js"></script>-->
-    <script src="https://unpkg.com/@jspsych/extension-mouse-tracking@1.0.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych({
-      extensions: [
-        { type: jsPsychExtensionMouseTracking, params: {minimum_sample_time: 0} }
-      ]
-    });
-
-    const trial = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: '<div id="target" style="width:250px; height: 250px; background-color: #333; margin: auto;"></div>',
-      choices: ['Done'],
-      prompt: "<p>Move your mouse around inside the square.</p>",
-      extensions: [
-        {type: jsPsychExtensionMouseTracking, params: {targets: ['#target']}}
-      ],
-      data: {
-        task: 'draw'
-      }
-    };
-
-    const replay = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: '<div id="target" style="width:250px; height: 250px; background-color: #333; margin: auto; position: relative;"></div>',
-      choices: ['Done'],
-      prompt: "<p>Here's the recording of your mouse movements</p>",
-      on_load: function(){
-        const mouseMovements = jsPsych.data.get().last(1).values()[0].mouse_tracking_data;
-        const targetRect = jsPsych.data.get().last(1).values()[0].mouse_tracking_targets['#target'];
-
-        const startTime = performance.now();
-
-        function draw_frame() {
-          const timeElapsed = performance.now() - startTime;
-          const points = mouseMovements.filter((x) => x.t <= timeElapsed);
-          let html = ``;
-          for(const p of points){
-            html += `<div style="width: 3px; height: 3px; background-color: blue; position: absolute; top: ${p.y - 1 - targetRect.top}px; left: ${p.x - 1 - targetRect.left}px;"></div>`
-          }
-          document.querySelector('#target').innerHTML = html;
-          if(points.length < mouseMovements.length) {
-            requestAnimationFrame(draw_frame);
-          }
-        }
-
-        requestAnimationFrame(draw_frame);
-
-      },
-      data: {
-        task: 'replay'
-      }
-    }
-
-    const timeline = [trial, replay];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <!--<script src="../../packages/extension-mouse-tracking/dist/index.browser.js"></script>-->
+    <script src="https://unpkg.com/@jspsych/extension-mouse-tracking@1.0.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych({
+      extensions: [
+        { type: jsPsychExtensionMouseTracking, params: {minimum_sample_time: 0} }
+      ]
+    });
+
+    const trial = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: '<div id="target" style="width:250px; height: 250px; background-color: #333; margin: auto;"></div>',
+      choices: ['Done'],
+      prompt: "<p>Move your mouse around inside the square.</p>",
+      extensions: [
+        {type: jsPsychExtensionMouseTracking, params: {targets: ['#target']}}
+      ],
+      data: {
+        task: 'draw'
+      }
+    };
+
+    const replay = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: '<div id="target" style="width:250px; height: 250px; background-color: #333; margin: auto; position: relative;"></div>',
+      choices: ['Done'],
+      prompt: "<p>Here's the recording of your mouse movements</p>",
+      on_load: function(){
+        const mouseMovements = jsPsych.data.get().last(1).values()[0].mouse_tracking_data;
+        const targetRect = jsPsych.data.get().last(1).values()[0].mouse_tracking_targets['#target'];
+
+        const startTime = performance.now();
+
+        function draw_frame() {
+          const timeElapsed = performance.now() - startTime;
+          const points = mouseMovements.filter((x) => x.t <= timeElapsed);
+          let html = ``;
+          for(const p of points){
+            html += `<div style="width: 3px; height: 3px; background-color: blue; position: absolute; top: ${p.y - 1 - targetRect.top}px; left: ${p.x - 1 - targetRect.left}px;"></div>`
+          }
+          document.querySelector('#target').innerHTML = html;
+          if(points.length < mouseMovements.length) {
+            requestAnimationFrame(draw_frame);
+          }
+        }
+
+        requestAnimationFrame(draw_frame);
+
+      },
+      data: {
+        task: 'replay'
+      }
+    }
+
+    const timeline = [trial, replay];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-extension-record-video-demo1.html b/7.3/demos/jspsych-extension-record-video-demo1.html
old mode 100755
new mode 100644
index 3cc7538828..4ebc5b9dc8
--- a/7.3/demos/jspsych-extension-record-video-demo1.html
+++ b/7.3/demos/jspsych-extension-record-video-demo1.html
@@ -1,61 +1,61 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <!-- <script src="../../packages/extension-record-video/dist/index.browser.js"></script> -->
-    <script src="https://unpkg.com/@jspsych/extension-record-video@1.0.1"></script>
-    <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
-    <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych({
-      extensions: [
-        { type: jsPsychExtensionRecordVideo}
-      ]
-    });
-
-    const init_camera = {
-      type: jsPsychInitializeCamera
-    };
-
-    const trial = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: `<div id="target" style="width:250px; height: 250px; background-color: #333; position: relative; margin: 2em auto;">
-          <div class="orbit" style="width:25px; height:25px; border-radius:25px;background-color: #f00; position: absolute; top:calc(50% - 12px); left:calc(50% - 12px);"></div>
-        </div>
-        <style>
-          .orbit {
-            transform: translateX(100px);
-            animation: orbit 4s infinite;
-          }
-          @keyframes orbit {
-            0% {
-              transform: rotate(0deg) translateX(100px);
-            }
-            100% {
-              transform: rotate(360deg) translateX(100px);
-            }
-          }
-        </style>`,
-      choices: ['Done'],
-      prompt: "<p>Video is recording. Click done after a few seconds.</p>",
-      extensions: [
-        {type: jsPsychExtensionRecordVideo}
-      ]
-    };
-
-    const timeline = [init_camera, trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <!-- <script src="../../packages/extension-record-video/dist/index.browser.js"></script> -->
+    <script src="https://unpkg.com/@jspsych/extension-record-video@1.0.2"></script>
+    <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
+    <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych({
+      extensions: [
+        { type: jsPsychExtensionRecordVideo}
+      ]
+    });
+
+    const init_camera = {
+      type: jsPsychInitializeCamera
+    };
+
+    const trial = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: `<div id="target" style="width:250px; height: 250px; background-color: #333; position: relative; margin: 2em auto;">
+          <div class="orbit" style="width:25px; height:25px; border-radius:25px;background-color: #f00; position: absolute; top:calc(50% - 12px); left:calc(50% - 12px);"></div>
+        </div>
+        <style>
+          .orbit {
+            transform: translateX(100px);
+            animation: orbit 4s infinite;
+          }
+          @keyframes orbit {
+            0% {
+              transform: rotate(0deg) translateX(100px);
+            }
+            100% {
+              transform: rotate(360deg) translateX(100px);
+            }
+          }
+        </style>`,
+      choices: ['Done'],
+      prompt: "<p>Video is recording. Click done after a few seconds.</p>",
+      extensions: [
+        {type: jsPsychExtensionRecordVideo}
+      ]
+    };
+
+    const timeline = [init_camera, trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-external-html-demo1.html b/7.3/demos/jspsych-external-html-demo1.html
old mode 100755
new mode 100644
index fbc62ebdeb..579a3add3b
--- a/7.3/demos/jspsych-external-html-demo1.html
+++ b/7.3/demos/jspsych-external-html-demo1.html
@@ -1,45 +1,45 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-external-html@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    // sample function that might be used to check if a participant has given
-    // consent to participate.
-    const check_consent = function(elem) {
-      if (document.getElementById('consent_checkbox').checked) {
-        return true;
-      }
-      else {
-        alert("If you wish to participate, you must check the box next to the statement 'I agree to participate in this study.'");
-        return false;
-      }
-      return false;
-    };
-
-    // declare the block.
-    const trial = {
-      type: jsPsychExternalHtml,
-      url: "external_page.html",
-      cont_btn: "start",
-      check_fn: check_consent
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-external-html@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    // sample function that might be used to check if a participant has given
+    // consent to participate.
+    const check_consent = function(elem) {
+      if (document.getElementById('consent_checkbox').checked) {
+        return true;
+      }
+      else {
+        alert("If you wish to participate, you must check the box next to the statement 'I agree to participate in this study.'");
+        return false;
+      }
+      return false;
+    };
+
+    // declare the block.
+    const trial = {
+      type: jsPsychExternalHtml,
+      url: "external_page.html",
+      cont_btn: "start",
+      check_fn: check_consent
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-free-sort-demo1.html b/7.3/demos/jspsych-free-sort-demo1.html
old mode 100755
new mode 100644
index 9e66d3cd9a..e79e78215b
--- a/7.3/demos/jspsych-free-sort-demo1.html
+++ b/7.3/demos/jspsych-free-sort-demo1.html
@@ -1,49 +1,49 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-free-sort@1.0.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-
-    const sorting_stimuli = [
-      'img/happy_face_1.jpg',
-      'img/happy_face_2.jpg',
-      'img/happy_face_3.jpg',
-      'img/happy_face_4.jpg'
-    ]
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      images: sorting_stimuli
-    }
-
-    const trial = {
-      type: jsPsychFreeSort,
-      stimuli: sorting_stimuli,
-      stim_width: 80,
-      stim_height: 60,
-      sort_area_width: 500,
-      sort_area_height: 500,
-      stim_starts_inside: true,
-      prompt: "<p>Click and drag the images below to sort them so that similar items are close together.</p>"
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-free-sort@1.0.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+
+    const sorting_stimuli = [
+      'img/happy_face_1.jpg',
+      'img/happy_face_2.jpg',
+      'img/happy_face_3.jpg',
+      'img/happy_face_4.jpg'
+    ]
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      images: sorting_stimuli
+    }
+
+    const trial = {
+      type: jsPsychFreeSort,
+      stimuli: sorting_stimuli,
+      stim_width: 80,
+      stim_height: 60,
+      sort_area_width: 500,
+      sort_area_height: 500,
+      stim_starts_inside: true,
+      prompt: "<p>Click and drag the images below to sort them so that similar items are close together.</p>"
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-fullscreen-demo1.html b/7.3/demos/jspsych-fullscreen-demo1.html
old mode 100755
new mode 100644
index e797b6e92d..f22bdb7eb2
--- a/7.3/demos/jspsych-fullscreen-demo1.html
+++ b/7.3/demos/jspsych-fullscreen-demo1.html
@@ -1,55 +1,55 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-fullscreen@1.2.0"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <style>
-      html,
-      body {
-        background-color: white;
-      }
-      .jspsych-btn {
-        margin-bottom: 10px;
-      }
-    </style>
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const enter_fullscreen = {
-      type: jsPsychFullscreen,
-      fullscreen_mode: true
-    }
-
-    const trial_in_fullscreen = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: 'This trial will be in fullscreen mode.',
-      choices: ['Continue']
-    }
-
-    const exit_fullscreen = {
-      type: jsPsychFullscreen,
-      fullscreen_mode: false,
-      delay_after: 0
-    }
-
-    const trial_after_fullscreen = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: 'This trial will NOT be in fullscreen mode.',
-      choices: ['Continue']
-    }
-
-    const timeline = [enter_fullscreen, trial_in_fullscreen, exit_fullscreen, trial_after_fullscreen];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-fullscreen@1.2.1"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <style>
+      html,
+      body {
+        background-color: white;
+      }
+      .jspsych-btn {
+        margin-bottom: 10px;
+      }
+    </style>
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const enter_fullscreen = {
+      type: jsPsychFullscreen,
+      fullscreen_mode: true
+    }
+
+    const trial_in_fullscreen = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: 'This trial will be in fullscreen mode.',
+      choices: ['Continue']
+    }
+
+    const exit_fullscreen = {
+      type: jsPsychFullscreen,
+      fullscreen_mode: false,
+      delay_after: 0
+    }
+
+    const trial_after_fullscreen = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: 'This trial will NOT be in fullscreen mode.',
+      choices: ['Continue']
+    }
+
+    const timeline = [enter_fullscreen, trial_in_fullscreen, exit_fullscreen, trial_after_fullscreen];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-html-audio-response-demo1.html b/7.3/demos/jspsych-html-audio-response-demo1.html
old mode 100755
new mode 100644
index ad8aa20fa7..c621595e6d
--- a/7.3/demos/jspsych-html-audio-response-demo1.html
+++ b/7.3/demos/jspsych-html-audio-response-demo1.html
@@ -1,62 +1,62 @@
-<!DOCTYPE html>
-<html>
-<head>
-  <script src="https://unpkg.com/jspsych@7.3.3"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.2"></script>
-  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css">
-  <style>
-    .jspsych-btn {margin-bottom: 10px;}
-  </style>
-</head>
-<body></body>
-<script>
-
-  var jsPsych = initJsPsych();
-
-  var start = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: '',
-    choices: ['Run demo']
-  };
-
-  var show_data = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: function() {
-      var trial_data = jsPsych.data.getLastTrialData().values();
-      var trial_json = JSON.stringify(trial_data, null, 2);
-      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
-        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
-    },
-    choices: ['Repeat demo']
-  };
-
-  var init_mic = {
-    type: jsPsychInitializeMicrophone
-  }
-
-  var trial = {
-    type: jsPsychHtmlAudioResponse,
-    stimulus: `
-      <p style="font-size:48px; color:red;">GREEN</p>
-      <p>Speak the color of the ink.</p>`,
-    recording_duration: 3500
-  };
-
-  var trial_loop = {
-    timeline: [trial, show_data],
-    loop_function: function() {
-      return true;
-    }
-  };
-
-  if (typeof jsPsych !== "undefined") {
-    jsPsych.run([start, init_mic, trial_loop]);
-  } else {
-    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-  }
-
-</script>
-
-</html>
+<!DOCTYPE html>
+<html>
+<head>
+  <script src="https://unpkg.com/jspsych@7.3.4"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.3"></script>
+  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css">
+  <style>
+    .jspsych-btn {margin-bottom: 10px;}
+  </style>
+</head>
+<body></body>
+<script>
+
+  var jsPsych = initJsPsych();
+
+  var start = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: '',
+    choices: ['Run demo']
+  };
+
+  var show_data = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: function() {
+      var trial_data = jsPsych.data.getLastTrialData().values();
+      var trial_json = JSON.stringify(trial_data, null, 2);
+      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
+        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
+    },
+    choices: ['Repeat demo']
+  };
+
+  var init_mic = {
+    type: jsPsychInitializeMicrophone
+  }
+
+  var trial = {
+    type: jsPsychHtmlAudioResponse,
+    stimulus: `
+      <p style="font-size:48px; color:red;">GREEN</p>
+      <p>Speak the color of the ink.</p>`,
+    recording_duration: 3500
+  };
+
+  var trial_loop = {
+    timeline: [trial, show_data],
+    loop_function: function() {
+      return true;
+    }
+  };
+
+  if (typeof jsPsych !== "undefined") {
+    jsPsych.run([start, init_mic, trial_loop]);
+  } else {
+    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+  }
+
+</script>
+
+</html>
diff --git a/7.3/demos/jspsych-html-audio-response-demo2.html b/7.3/demos/jspsych-html-audio-response-demo2.html
old mode 100755
new mode 100644
index be1a935976..a7031c225f
--- a/7.3/demos/jspsych-html-audio-response-demo2.html
+++ b/7.3/demos/jspsych-html-audio-response-demo2.html
@@ -1,70 +1,70 @@
-<!DOCTYPE html>
-<html>
-<head>
-  <script src="https://unpkg.com/jspsych@7.3.3"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.2"></script>
-  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css">
-  <style>
-    .jspsych-btn {margin-bottom: 10px;}
-  </style>
-</head>
-<body></body>
-<script>
-
-  var jsPsych = initJsPsych();
-
-  var start = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: '',
-    choices: ['Run demo']
-  };
-
-  var show_data = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: function() {
-      var trial_data = jsPsych.data.getLastTrialData().values();
-      var trial_json = JSON.stringify(trial_data, null, 2);
-      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
-        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
-    },
-    choices: ['Repeat demo']
-  };
-
-  var init_mic = {
-    type: jsPsychInitializeMicrophone
-  }
-
-  var trial = {
-    type: jsPsychHtmlAudioResponse,
-    stimulus: `
-      <p>Please sing the first few seconds of a song and click the button when you are done.</p>`,
-    recording_duration: 15000,
-    allow_playback: true,
-    on_finish: function(data){
-      /*fetch('/save-my-data.php', { audio_base64: data.response })
-        .then((audio_id){
-          data.response = audio_id;
-        });*/
-      // need to fake the server part of this.
-      data.response = "584j29d01a";
-    }
-  };
-
-  var trial_loop = {
-    timeline: [trial, show_data],
-    loop_function: function() {
-      return true;
-    }
-  };
-
-  if (typeof jsPsych !== "undefined") {
-    jsPsych.run([start, init_mic, trial_loop]);
-  } else {
-    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-  }
-
-</script>
-
-</html>
+<!DOCTYPE html>
+<html>
+<head>
+  <script src="https://unpkg.com/jspsych@7.3.4"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.3"></script>
+  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css">
+  <style>
+    .jspsych-btn {margin-bottom: 10px;}
+  </style>
+</head>
+<body></body>
+<script>
+
+  var jsPsych = initJsPsych();
+
+  var start = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: '',
+    choices: ['Run demo']
+  };
+
+  var show_data = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: function() {
+      var trial_data = jsPsych.data.getLastTrialData().values();
+      var trial_json = JSON.stringify(trial_data, null, 2);
+      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
+        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
+    },
+    choices: ['Repeat demo']
+  };
+
+  var init_mic = {
+    type: jsPsychInitializeMicrophone
+  }
+
+  var trial = {
+    type: jsPsychHtmlAudioResponse,
+    stimulus: `
+      <p>Please sing the first few seconds of a song and click the button when you are done.</p>`,
+    recording_duration: 15000,
+    allow_playback: true,
+    on_finish: function(data){
+      /*fetch('/save-my-data.php', { audio_base64: data.response })
+        .then((audio_id){
+          data.response = audio_id;
+        });*/
+      // need to fake the server part of this.
+      data.response = "584j29d01a";
+    }
+  };
+
+  var trial_loop = {
+    timeline: [trial, show_data],
+    loop_function: function() {
+      return true;
+    }
+  };
+
+  if (typeof jsPsych !== "undefined") {
+    jsPsych.run([start, init_mic, trial_loop]);
+  } else {
+    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+  }
+
+</script>
+
+</html>
diff --git a/7.3/demos/jspsych-html-audio-response-demo3.html b/7.3/demos/jspsych-html-audio-response-demo3.html
old mode 100755
new mode 100644
index 0c77569208..41e6dbef58
--- a/7.3/demos/jspsych-html-audio-response-demo3.html
+++ b/7.3/demos/jspsych-html-audio-response-demo3.html
@@ -1,82 +1,82 @@
-<!DOCTYPE html>
-<html>
-<head>
-  <script src="https://unpkg.com/jspsych@7.3.3"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.2"></script>
-  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css">
-  <style>
-    .jspsych-btn {margin-bottom: 10px;}
-  </style>
-</head>
-<body></body>
-<script>
-
-  var jsPsych = initJsPsych();
-
-  var start = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: '',
-    choices: ['Run demo']
-  };
-
-  var show_data = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: function() {
-      var trial_data = jsPsych.data.get().last(2).values();
-      var trial_json = JSON.stringify(trial_data, null, 2);
-      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
-        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
-    },
-    choices: ['Repeat demo']
-  };
-
-  var init_mic = {
-    type: jsPsychInitializeMicrophone
-  }
-
-  var instruction = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: `
-      <img src='img/10.gif' style="width:100px; padding: 20px;"></img>
-      <p>Make up a name for this shape. When you have one in mind, click the button and then say the name aloud.</p>`,
-    choices: ['I am ready.']
-  }
-
-  var record = {
-    type: jsPsychHtmlAudioResponse,
-    stimulus: `
-      <img src='img/10.gif' style="width:100px; padding: 20px;"></img>
-      <p>Recording...</p>`,
-    recording_duration: 1500,
-    save_audio_url: true
-  };
-
-  var playback = {
-    type: jsPsychAudioButtonResponse,
-    stimulus: ()=>{
-      return jsPsych.data.get().last(1).values()[0].audio_url;
-    },
-    prompt: '<p>Click the object the matches the spoken name.</p>',
-    choices: ['img/9.gif','img/10.gif','img/11.gif','img/12.gif'],
-    button_html: '<img src="%choice%" style="width:100px; padding: 20px;"></img>'
-  }
-
-  var trial_loop = {
-    timeline: [instruction, record, playback, show_data],
-    loop_function: function() {
-      return true;
-    }
-  };
-
-  if (typeof jsPsych !== "undefined") {
-    jsPsych.run([start, init_mic, trial_loop]);
-  } else {
-    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-  }
-
-</script>
-
-</html>
+<!DOCTYPE html>
+<html>
+<head>
+  <script src="https://unpkg.com/jspsych@7.3.4"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.3"></script>
+  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css">
+  <style>
+    .jspsych-btn {margin-bottom: 10px;}
+  </style>
+</head>
+<body></body>
+<script>
+
+  var jsPsych = initJsPsych();
+
+  var start = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: '',
+    choices: ['Run demo']
+  };
+
+  var show_data = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: function() {
+      var trial_data = jsPsych.data.get().last(2).values();
+      var trial_json = JSON.stringify(trial_data, null, 2);
+      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
+        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
+    },
+    choices: ['Repeat demo']
+  };
+
+  var init_mic = {
+    type: jsPsychInitializeMicrophone
+  }
+
+  var instruction = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: `
+      <img src='img/10.gif' style="width:100px; padding: 20px;"></img>
+      <p>Make up a name for this shape. When you have one in mind, click the button and then say the name aloud.</p>`,
+    choices: ['I am ready.']
+  }
+
+  var record = {
+    type: jsPsychHtmlAudioResponse,
+    stimulus: `
+      <img src='img/10.gif' style="width:100px; padding: 20px;"></img>
+      <p>Recording...</p>`,
+    recording_duration: 1500,
+    save_audio_url: true
+  };
+
+  var playback = {
+    type: jsPsychAudioButtonResponse,
+    stimulus: ()=>{
+      return jsPsych.data.get().last(1).values()[0].audio_url;
+    },
+    prompt: '<p>Click the object the matches the spoken name.</p>',
+    choices: ['img/9.gif','img/10.gif','img/11.gif','img/12.gif'],
+    button_html: '<img src="%choice%" style="width:100px; padding: 20px;"></img>'
+  }
+
+  var trial_loop = {
+    timeline: [instruction, record, playback, show_data],
+    loop_function: function() {
+      return true;
+    }
+  };
+
+  if (typeof jsPsych !== "undefined") {
+    jsPsych.run([start, init_mic, trial_loop]);
+  } else {
+    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+  }
+
+</script>
+
+</html>
diff --git a/7.3/demos/jspsych-html-button-response-demo1.html b/7.3/demos/jspsych-html-button-response-demo1.html
old mode 100755
new mode 100644
index 7a031fc104..657ae2314b
--- a/7.3/demos/jspsych-html-button-response-demo1.html
+++ b/7.3/demos/jspsych-html-button-response-demo1.html
@@ -1,32 +1,32 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const timeline = [];
-
-    const trial = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: '<p style="font-size:48px; color:red;">GREEN</p>',
-      choices: ['Red', 'Green', 'Blue'],
-      prompt: "<p>What color is the ink?</p>"
-    };
-
-    timeline.push(trial);
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const timeline = [];
+
+    const trial = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: '<p style="font-size:48px; color:red;">GREEN</p>',
+      choices: ['Red', 'Green', 'Blue'],
+      prompt: "<p>What color is the ink?</p>"
+    };
+
+    timeline.push(trial);
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-html-keyboard-response-demo1.html b/7.3/demos/jspsych-html-keyboard-response-demo1.html
old mode 100755
new mode 100644
index e891e35eb5..aba01d24f4
--- a/7.3/demos/jspsych-html-keyboard-response-demo1.html
+++ b/7.3/demos/jspsych-html-keyboard-response-demo1.html
@@ -1,31 +1,31 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychHtmlKeyboardResponse,
-      stimulus: '<p style="font-size:48px; color:green;">BLUE</p>',
-      choices: ['r', 'g', 'b'],
-      prompt: "<p>Is the ink color (r)ed, (g)reen, or (b)lue?</p>"
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychHtmlKeyboardResponse,
+      stimulus: '<p style="font-size:48px; color:green;">BLUE</p>',
+      choices: ['r', 'g', 'b'],
+      prompt: "<p>Is the ink color (r)ed, (g)reen, or (b)lue?</p>"
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-html-keyboard-response-demo2.html b/7.3/demos/jspsych-html-keyboard-response-demo2.html
old mode 100755
new mode 100644
index b3baf714bf..874f5e6019
--- a/7.3/demos/jspsych-html-keyboard-response-demo2.html
+++ b/7.3/demos/jspsych-html-keyboard-response-demo2.html
@@ -1,31 +1,31 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychHtmlKeyboardResponse,
-      stimulus: '<p style="font-size: 48px;">+</p>',
-      choices: "NO_KEYS",
-      trial_duration: 1000,
-    };
-
-    const timeline = [trial];
-    
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychHtmlKeyboardResponse,
+      stimulus: '<p style="font-size: 48px;">+</p>',
+      choices: "NO_KEYS",
+      trial_duration: 1000,
+    };
+
+    const timeline = [trial];
+    
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-html-slider-response-demo1.html b/7.3/demos/jspsych-html-slider-response-demo1.html
old mode 100755
new mode 100644
index 66521d2208..5c66450fd8
--- a/7.3/demos/jspsych-html-slider-response-demo1.html
+++ b/7.3/demos/jspsych-html-slider-response-demo1.html
@@ -1,41 +1,41 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-slider-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychHtmlSliderResponse,
-      stimulus: `<div style="width:500px;">
-        <p>How likely is it that team A will win this match?</p>
-        <div style="width:240px; float: left;">
-          <p>TEAM A</p>
-          <p>10 wins, 5 losses, 6 draws</p>
-        </div>
-        <div style="width:240px; float: right;">
-          <p>TEAM B</p>
-          <p>6 wins, 4 losses, 11 draws</p>
-        </div>
-      </div>`,
-      require_movement: true,
-      labels: ['100% chance', '50% chance', '0% chance']
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-slider-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychHtmlSliderResponse,
+      stimulus: `<div style="width:500px;">
+        <p>How likely is it that team A will win this match?</p>
+        <div style="width:240px; float: left;">
+          <p>TEAM A</p>
+          <p>10 wins, 5 losses, 6 draws</p>
+        </div>
+        <div style="width:240px; float: right;">
+          <p>TEAM B</p>
+          <p>6 wins, 4 losses, 11 draws</p>
+        </div>
+      </div>`,
+      require_movement: true,
+      labels: ['100% chance', '50% chance', '0% chance']
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-html-video-response-demo1.html b/7.3/demos/jspsych-html-video-response-demo1.html
old mode 100755
new mode 100644
index 0b552f2606..f21203f626
--- a/7.3/demos/jspsych-html-video-response-demo1.html
+++ b/7.3/demos/jspsych-html-video-response-demo1.html
@@ -1,43 +1,43 @@
-<!DOCTYPE html>
-<html>
-<head>
-  <script src="docs-demo-timeline.js"></script>
-  <script src="https://unpkg.com/jspsych@7.3.3"></script>
-  <!-- <script src="../../packages/jspsych/dist/index.browser.js"></script> -->
-  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-video-response@1.0.1"></script>
-  <!-- <script src="../../packages/plugin-html-video-response/dist/index.browser.js"></script> -->
-  <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1"></script>
-  <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
-  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css">
-  <link rel="stylesheet" href="docs-demo.css" type="text/css">
-</head>
-<body></body>
-<script>
-
-  var jsPsych = initJsPsych();
-
-  var init_camera = {
-    type: jsPsychInitializeCamera
-  }
-
-  var trial = {
-    type: jsPsychHtmlVideoResponse,
-    stimulus: `
-      <p style="font-size:48px; color:red;"> <-- </p>
-      <p>Turn your head in the direction of the arrow</p>`,
-    recording_duration: 3500,
-    show_done_button: false,
-  };
-
-  const timeline = [init_camera, trial];
-
-  if (typeof jsPsych !== "undefined") {
-    jsPsych.run(generateDocsDemoTimeline(timeline));
-  } else {
-    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-  }
-
-</script>
-
-</html>
+<!DOCTYPE html>
+<html>
+<head>
+  <script src="docs-demo-timeline.js"></script>
+  <script src="https://unpkg.com/jspsych@7.3.4"></script>
+  <!-- <script src="../../packages/jspsych/dist/index.browser.js"></script> -->
+  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-video-response@1.0.2"></script>
+  <!-- <script src="../../packages/plugin-html-video-response/dist/index.browser.js"></script> -->
+  <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2"></script>
+  <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
+  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css">
+  <link rel="stylesheet" href="docs-demo.css" type="text/css">
+</head>
+<body></body>
+<script>
+
+  var jsPsych = initJsPsych();
+
+  var init_camera = {
+    type: jsPsychInitializeCamera
+  }
+
+  var trial = {
+    type: jsPsychHtmlVideoResponse,
+    stimulus: `
+      <p style="font-size:48px; color:red;"> <-- </p>
+      <p>Turn your head in the direction of the arrow</p>`,
+    recording_duration: 3500,
+    show_done_button: false,
+  };
+
+  const timeline = [init_camera, trial];
+
+  if (typeof jsPsych !== "undefined") {
+    jsPsych.run(generateDocsDemoTimeline(timeline));
+  } else {
+    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+  }
+
+</script>
+
+</html>
diff --git a/7.3/demos/jspsych-html-video-response-demo2.html b/7.3/demos/jspsych-html-video-response-demo2.html
old mode 100755
new mode 100644
index d63889dc0a..3d75ed35ff
--- a/7.3/demos/jspsych-html-video-response-demo2.html
+++ b/7.3/demos/jspsych-html-video-response-demo2.html
@@ -1,42 +1,42 @@
-<!DOCTYPE html>
-<html>
-<head>
-  <script src="docs-demo-timeline.js"></script>
-  <script src="https://unpkg.com/jspsych@7.3.3"></script>
-  <!-- <script src="../../packages/jspsych/dist/index.browser.js"></script> -->
-  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-video-response@1.0.1"></script>
-  <!-- <script src="../../packages/plugin-html-video-response/dist/index.browser.js"></script> -->
-  <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1"></script>
-  <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
-  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css">
-  <link rel="stylesheet" href="docs-demo.css" type="text/css">
-</head>
-<body></body>
-<script>
-
-  var jsPsych = initJsPsych();
-
-  var init_camera = {
-    type: jsPsychInitializeCamera
-  }
-
-  var trial = {
-    type: jsPsychHtmlVideoResponse,
-    stimulus: `<p>Make a sad face</p>`,
-    recording_duration: 3500,
-    show_done_button: false,
-    allow_playback: true
-  };
-
-  const timeline = [init_camera, trial];
-
-  if (typeof jsPsych !== "undefined") {
-    jsPsych.run(generateDocsDemoTimeline(timeline));
-  } else {
-    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-  }
-
-</script>
-
-</html>
+<!DOCTYPE html>
+<html>
+<head>
+  <script src="docs-demo-timeline.js"></script>
+  <script src="https://unpkg.com/jspsych@7.3.4"></script>
+  <!-- <script src="../../packages/jspsych/dist/index.browser.js"></script> -->
+  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-video-response@1.0.2"></script>
+  <!-- <script src="../../packages/plugin-html-video-response/dist/index.browser.js"></script> -->
+  <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2"></script>
+  <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
+  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css">
+  <link rel="stylesheet" href="docs-demo.css" type="text/css">
+</head>
+<body></body>
+<script>
+
+  var jsPsych = initJsPsych();
+
+  var init_camera = {
+    type: jsPsychInitializeCamera
+  }
+
+  var trial = {
+    type: jsPsychHtmlVideoResponse,
+    stimulus: `<p>Make a sad face</p>`,
+    recording_duration: 3500,
+    show_done_button: false,
+    allow_playback: true
+  };
+
+  const timeline = [init_camera, trial];
+
+  if (typeof jsPsych !== "undefined") {
+    jsPsych.run(generateDocsDemoTimeline(timeline));
+  } else {
+    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+  }
+
+</script>
+
+</html>
diff --git a/7.3/demos/jspsych-html-video-response-demo3.html b/7.3/demos/jspsych-html-video-response-demo3.html
old mode 100755
new mode 100644
index 27482175d0..6193b14896
--- a/7.3/demos/jspsych-html-video-response-demo3.html
+++ b/7.3/demos/jspsych-html-video-response-demo3.html
@@ -1,52 +1,52 @@
-<!DOCTYPE html>
-<html>
-<head>
-  <script src="docs-demo-timeline.js"></script>
-  <script src="https://unpkg.com/jspsych@7.3.3"></script>
-  <!-- <script src="../../packages/jspsych/dist/index.browser.js"></script> -->
-  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-video-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-video-response@1.0.1"></script>
-  <!-- <script src="../../packages/plugin-html-video-response/dist/index.browser.js"></script> -->
-  <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1"></script>
-  <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
-  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css">
-  <link rel="stylesheet" href="docs-demo.css" type="text/css">
-</head>
-<body></body>
-<script>
-
-  var jsPsych = initJsPsych();
-
-  var init_camera = {
-    type: jsPsychInitializeCamera
-  }
-
-  var record = {
-    type: jsPsychHtmlVideoResponse,
-    stimulus: `<p>Make a sad face.</p>`,
-    recording_duration: 1500,
-    show_done_button: false,
-    save_video_url: true
-  };
-
-  var classify = {
-    type: jsPsychVideoButtonResponse,
-    stimulus: () => {
-      return [jsPsych.data.get().last(1).values()[0].video_url];
-    },
-    choices: ["Happy", "Sad", "Angry", "Surprised"],
-    prompt: "<p>What emotion is this?</p>",
-  }
-
-  const timeline = [init_camera, record, classify];
-
-  if (typeof jsPsych !== "undefined") {
-    jsPsych.run(generateDocsDemoTimeline(timeline));
-  } else {
-    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-  }
-
-</script>
-
-</html>
+<!DOCTYPE html>
+<html>
+<head>
+  <script src="docs-demo-timeline.js"></script>
+  <script src="https://unpkg.com/jspsych@7.3.4"></script>
+  <!-- <script src="../../packages/jspsych/dist/index.browser.js"></script> -->
+  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-video-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-video-response@1.0.2"></script>
+  <!-- <script src="../../packages/plugin-html-video-response/dist/index.browser.js"></script> -->
+  <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2"></script>
+  <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
+  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css">
+  <link rel="stylesheet" href="docs-demo.css" type="text/css">
+</head>
+<body></body>
+<script>
+
+  var jsPsych = initJsPsych();
+
+  var init_camera = {
+    type: jsPsychInitializeCamera
+  }
+
+  var record = {
+    type: jsPsychHtmlVideoResponse,
+    stimulus: `<p>Make a sad face.</p>`,
+    recording_duration: 1500,
+    show_done_button: false,
+    save_video_url: true
+  };
+
+  var classify = {
+    type: jsPsychVideoButtonResponse,
+    stimulus: () => {
+      return [jsPsych.data.get().last(1).values()[0].video_url];
+    },
+    choices: ["Happy", "Sad", "Angry", "Surprised"],
+    prompt: "<p>What emotion is this?</p>",
+  }
+
+  const timeline = [init_camera, record, classify];
+
+  if (typeof jsPsych !== "undefined") {
+    jsPsych.run(generateDocsDemoTimeline(timeline));
+  } else {
+    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+  }
+
+</script>
+
+</html>
diff --git a/7.3/demos/jspsych-iat-html-demo1.html b/7.3/demos/jspsych-iat-html-demo1.html
old mode 100755
new mode 100644
index fb358c0baf..84a54238db
--- a/7.3/demos/jspsych-iat-html-demo1.html
+++ b/7.3/demos/jspsych-iat-html-demo1.html
@@ -1,40 +1,40 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-iat-html@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychIatHtml,
-      stimulus: 'Joyous',
-      stim_key_association: 'left',
-      html_when_wrong: '<span style="color: red; font-size: 80px">X</span>',
-      bottom_instructions: '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>',
-      force_correct_key_press: true,
-      display_feedback: true,
-      trial_duration: 3000, //Only if display_feedback is false
-      left_category_key: 'e',
-      right_category_key: 'i',
-      left_category_label: ['OLD', 'GOOD'],
-      right_category_label: ['YOUNG', 'BAD'],
-      response_ends_trial: true
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-iat-html@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychIatHtml,
+      stimulus: 'Joyous',
+      stim_key_association: 'left',
+      html_when_wrong: '<span style="color: red; font-size: 80px">X</span>',
+      bottom_instructions: '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>',
+      force_correct_key_press: true,
+      display_feedback: true,
+      trial_duration: 3000, //Only if display_feedback is false
+      left_category_key: 'e',
+      right_category_key: 'i',
+      left_category_label: ['OLD', 'GOOD'],
+      right_category_label: ['YOUNG', 'BAD'],
+      response_ends_trial: true
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-iat-image-demo1.html b/7.3/demos/jspsych-iat-image-demo1.html
old mode 100755
new mode 100644
index 4e4fa6e883..bdf31c508c
--- a/7.3/demos/jspsych-iat-image-demo1.html
+++ b/7.3/demos/jspsych-iat-image-demo1.html
@@ -1,46 +1,46 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-iat-image@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial = {
-      type: jsPsychIatImage,
-      stimulus: 'img/iat_old_face.jpg',
-      stim_key_association: 'left',
-      html_when_wrong: '<span style="color: red; font-size: 80px">X</span>',
-      bottom_instructions: '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>',
-      force_correct_key_press: true,
-      display_feedback: true,
-      trial_duration: 3000, //Only if display_feedback is false
-      left_category_key: 'e',
-      right_category_key: 'i',
-      left_category_label: ['OLD', 'GOOD'],
-      right_category_label: ['YOUNG', 'BAD'],
-      response_ends_trial: true
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-iat-image@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial = {
+      type: jsPsychIatImage,
+      stimulus: 'img/iat_old_face.jpg',
+      stim_key_association: 'left',
+      html_when_wrong: '<span style="color: red; font-size: 80px">X</span>',
+      bottom_instructions: '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>',
+      force_correct_key_press: true,
+      display_feedback: true,
+      trial_duration: 3000, //Only if display_feedback is false
+      left_category_key: 'e',
+      right_category_key: 'i',
+      left_category_label: ['OLD', 'GOOD'],
+      right_category_label: ['YOUNG', 'BAD'],
+      response_ends_trial: true
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-image-button-response-demo1.html b/7.3/demos/jspsych-image-button-response-demo1.html
old mode 100755
new mode 100644
index e6eb239988..d556088c20
--- a/7.3/demos/jspsych-image-button-response-demo1.html
+++ b/7.3/demos/jspsych-image-button-response-demo1.html
@@ -1,37 +1,37 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/happy_face_1.jpg',
-      choices: ['Happy', 'Sad'],
-      prompt: "<p>Is this person happy or sad?</p>"
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/happy_face_1.jpg',
+      choices: ['Happy', 'Sad'],
+      prompt: "<p>Is this person happy or sad?</p>"
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-image-keyboard-response-demo1.html b/7.3/demos/jspsych-image-keyboard-response-demo1.html
old mode 100755
new mode 100644
index 5d608122a2..77cdef4be1
--- a/7.3/demos/jspsych-image-keyboard-response-demo1.html
+++ b/7.3/demos/jspsych-image-keyboard-response-demo1.html
@@ -1,37 +1,37 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial = {
-      type: jsPsychImageKeyboardResponse,
-      stimulus: 'img/happy_face_1.jpg',
-      choices: ['e', 'i'],
-      prompt: "<p>Is this person happy or sad? Press 'e' for happy and 'i' for sad.</p>",
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial = {
+      type: jsPsychImageKeyboardResponse,
+      stimulus: 'img/happy_face_1.jpg',
+      choices: ['e', 'i'],
+      prompt: "<p>Is this person happy or sad? Press 'e' for happy and 'i' for sad.</p>",
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-image-keyboard-response-demo2.html b/7.3/demos/jspsych-image-keyboard-response-demo2.html
old mode 100755
new mode 100644
index 2fd7b5fc4a..1e9ca3e06e
--- a/7.3/demos/jspsych-image-keyboard-response-demo2.html
+++ b/7.3/demos/jspsych-image-keyboard-response-demo2.html
@@ -1,38 +1,38 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial = {
-      type: jsPsychImageKeyboardResponse,
-      stimulus: 'img/happy_face_1.jpg',
-      choices: "NO_KEYS",
-      prompt: "<p>Study this face for 5 seconds.</p>",
-      trial_duration: 5000
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial = {
+      type: jsPsychImageKeyboardResponse,
+      stimulus: 'img/happy_face_1.jpg',
+      choices: "NO_KEYS",
+      prompt: "<p>Study this face for 5 seconds.</p>",
+      trial_duration: 5000
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-image-slider-response-demo1.html b/7.3/demos/jspsych-image-slider-response-demo1.html
old mode 100755
new mode 100644
index a0022c4f94..d2437d89d2
--- a/7.3/demos/jspsych-image-slider-response-demo1.html
+++ b/7.3/demos/jspsych-image-slider-response-demo1.html
@@ -1,37 +1,37 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-slider-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial = {
-      type: jsPsychImageSliderResponse,
-      stimulus: 'img/happy_face_1.jpg',
-      labels: ['happy', 'sad'],
-      prompt: "<p>How happy/sad is this person?</p>",
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-slider-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial = {
+      type: jsPsychImageSliderResponse,
+      stimulus: 'img/happy_face_1.jpg',
+      labels: ['happy', 'sad'],
+      prompt: "<p>How happy/sad is this person?</p>",
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-initialize-camera-demo1.html b/7.3/demos/jspsych-initialize-camera-demo1.html
old mode 100755
new mode 100644
index 539744acc0..275fe537ec
--- a/7.3/demos/jspsych-initialize-camera-demo1.html
+++ b/7.3/demos/jspsych-initialize-camera-demo1.html
@@ -1,53 +1,53 @@
-<!DOCTYPE html>
-<html>
-<head>
-  <script src="https://unpkg.com/jspsych@7.3.3"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1"></script>
-  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css">
-  <style>
-    .jspsych-btn {margin-bottom: 10px;}
-  </style>
-</head>
-<body></body>
-<script>
-
-  var jsPsych = initJsPsych();
-
-  var start = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: '',
-    choices: ['Run demo']
-  };
-
-  var show_data = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: function() {
-      var trial_data = jsPsych.data.get().last(1).values();
-      var trial_json = JSON.stringify(trial_data, null, 2);
-      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
-        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
-    },
-    choices: ['Repeat demo']
-  };
-
-  var init_mic = {
-    type: jsPsychInitializeCamera
-  }
-
-  var trial_loop = {
-    timeline: [init_mic, show_data],
-    loop_function: function() {
-      return true;
-    }
-  };
-
-  if (typeof jsPsych !== "undefined") {
-    jsPsych.run([start,  trial_loop]);
-  } else {
-    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-  }
-
-</script>
-
-</html>
+<!DOCTYPE html>
+<html>
+<head>
+  <script src="https://unpkg.com/jspsych@7.3.4"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2"></script>
+  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css">
+  <style>
+    .jspsych-btn {margin-bottom: 10px;}
+  </style>
+</head>
+<body></body>
+<script>
+
+  var jsPsych = initJsPsych();
+
+  var start = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: '',
+    choices: ['Run demo']
+  };
+
+  var show_data = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: function() {
+      var trial_data = jsPsych.data.get().last(1).values();
+      var trial_json = JSON.stringify(trial_data, null, 2);
+      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
+        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
+    },
+    choices: ['Repeat demo']
+  };
+
+  var init_mic = {
+    type: jsPsychInitializeCamera
+  }
+
+  var trial_loop = {
+    timeline: [init_mic, show_data],
+    loop_function: function() {
+      return true;
+    }
+  };
+
+  if (typeof jsPsych !== "undefined") {
+    jsPsych.run([start,  trial_loop]);
+  } else {
+    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+  }
+
+</script>
+
+</html>
diff --git a/7.3/demos/jspsych-initialize-microphone-demo1.html b/7.3/demos/jspsych-initialize-microphone-demo1.html
old mode 100755
new mode 100644
index 0fea6832ae..9325278700
--- a/7.3/demos/jspsych-initialize-microphone-demo1.html
+++ b/7.3/demos/jspsych-initialize-microphone-demo1.html
@@ -1,53 +1,53 @@
-<!DOCTYPE html>
-<html>
-<head>
-  <script src="https://unpkg.com/jspsych@7.3.3"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-  <script src="https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.2"></script>
-  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css">
-  <style>
-    .jspsych-btn {margin-bottom: 10px;}
-  </style>
-</head>
-<body></body>
-<script>
-
-  var jsPsych = initJsPsych();
-
-  var start = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: '',
-    choices: ['Run demo']
-  };
-
-  var show_data = {
-    type: jsPsychHtmlButtonResponse,
-    stimulus: function() {
-      var trial_data = jsPsych.data.get().last(1).values();
-      var trial_json = JSON.stringify(trial_data, null, 2);
-      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
-        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
-    },
-    choices: ['Repeat demo']
-  };
-
-  var init_mic = {
-    type: jsPsychInitializeMicrophone
-  }
-
-  var trial_loop = {
-    timeline: [init_mic, show_data],
-    loop_function: function() {
-      return true;
-    }
-  };
-
-  if (typeof jsPsych !== "undefined") {
-    jsPsych.run([start,  trial_loop]);
-  } else {
-    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-  }
-
-</script>
-
-</html>
+<!DOCTYPE html>
+<html>
+<head>
+  <script src="https://unpkg.com/jspsych@7.3.4"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+  <script src="https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.3"></script>
+  <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css">
+  <style>
+    .jspsych-btn {margin-bottom: 10px;}
+  </style>
+</head>
+<body></body>
+<script>
+
+  var jsPsych = initJsPsych();
+
+  var start = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: '',
+    choices: ['Run demo']
+  };
+
+  var show_data = {
+    type: jsPsychHtmlButtonResponse,
+    stimulus: function() {
+      var trial_data = jsPsych.data.get().last(1).values();
+      var trial_json = JSON.stringify(trial_data, null, 2);
+      return `<p style="margin-bottom:0px;"><strong>Trial data:</strong></p>
+        <pre style="margin-top:0px;text-align:left;">${trial_json}</pre>`;
+    },
+    choices: ['Repeat demo']
+  };
+
+  var init_mic = {
+    type: jsPsychInitializeMicrophone
+  }
+
+  var trial_loop = {
+    timeline: [init_mic, show_data],
+    loop_function: function() {
+      return true;
+    }
+  };
+
+  if (typeof jsPsych !== "undefined") {
+    jsPsych.run([start,  trial_loop]);
+  } else {
+    document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+  }
+
+</script>
+
+</html>
diff --git a/7.3/demos/jspsych-instructions-demo-1.html b/7.3/demos/jspsych-instructions-demo-1.html
old mode 100755
new mode 100644
index 4507fcedde..bc4e668a0a
--- a/7.3/demos/jspsych-instructions-demo-1.html
+++ b/7.3/demos/jspsych-instructions-demo-1.html
@@ -1,35 +1,35 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-instructions@1.1.3"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychInstructions,
-      pages: [
-        'Welcome to the experiment. Click next to begin.',
-        'This is the second page of instructions.',
-        'This is the final page.'
-      ],
-      show_clickable_nav: true
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-instructions@1.1.4"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychInstructions,
+      pages: [
+        'Welcome to the experiment. Click next to begin.',
+        'This is the second page of instructions.',
+        'This is the final page.'
+      ],
+      show_clickable_nav: true
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-instructions-demo-2.html b/7.3/demos/jspsych-instructions-demo-2.html
old mode 100755
new mode 100644
index 4b18df263c..d1baba5014
--- a/7.3/demos/jspsych-instructions-demo-2.html
+++ b/7.3/demos/jspsych-instructions-demo-2.html
@@ -1,41 +1,41 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-instructions@1.1.3"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload_trial = {
-      type: jsPsychPreload,
-      images: ['img/con2.png']
-    }
-
-    const trial = {
-      type: jsPsychInstructions,
-      pages: [
-        'Welcome to the experiment. Click next to begin.',
-        'You will be looking at images of arrows: ' +
-        '<br>' +
-        '<img src="img/con2.png"></img>'
-      ],
-      show_clickable_nav: true
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-instructions@1.1.4"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload_trial = {
+      type: jsPsychPreload,
+      images: ['img/con2.png']
+    }
+
+    const trial = {
+      type: jsPsychInstructions,
+      pages: [
+        'Welcome to the experiment. Click next to begin.',
+        'You will be looking at images of arrows: ' +
+        '<br>' +
+        '<img src="img/con2.png"></img>'
+      ],
+      show_clickable_nav: true
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload_trial]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-instructions-demo-3.html b/7.3/demos/jspsych-instructions-demo-3.html
old mode 100755
new mode 100644
index b0d9675da5..035152ed9d
--- a/7.3/demos/jspsych-instructions-demo-3.html
+++ b/7.3/demos/jspsych-instructions-demo-3.html
@@ -1,37 +1,37 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-instructions@1.1.3"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychInstructions,
-      pages: [
-        'Welcome to the experiment. Click next to begin.',
-        'This is the second page of instructions.',
-        'This is the final page.'
-      ],
-      button_label_next: "Continue",
-      button_label_previous: "Return to the dark side",
-      show_clickable_nav: true
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-instructions@1.1.4"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychInstructions,
+      pages: [
+        'Welcome to the experiment. Click next to begin.',
+        'This is the second page of instructions.',
+        'This is the final page.'
+      ],
+      button_label_next: "Continue",
+      button_label_previous: "Return to the dark side",
+      show_clickable_nav: true
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-maxdiff-demo1.html b/7.3/demos/jspsych-maxdiff-demo1.html
old mode 100755
new mode 100644
index 64a478f01c..0f974e592b
--- a/7.3/demos/jspsych-maxdiff-demo1.html
+++ b/7.3/demos/jspsych-maxdiff-demo1.html
@@ -1,31 +1,31 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-maxdiff@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychMaxdiff,
-      alternatives: ['apple', 'orange', 'pear', 'banana'],
-      labels: ['Most Preferred', 'Least Preferred'],
-      preamble: '<p> Please select your <b>most preferred</b> and <b>least preferred</b> fruits. </p>'
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-maxdiff@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychMaxdiff,
+      alternatives: ['apple', 'orange', 'pear', 'banana'],
+      labels: ['Most Preferred', 'Least Preferred'],
+      preamble: '<p> Please select your <b>most preferred</b> and <b>least preferred</b> fruits. </p>'
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-mirror-camera-demo1.html b/7.3/demos/jspsych-mirror-camera-demo1.html
old mode 100755
new mode 100644
index 0b8b366b97..7873558e35
--- a/7.3/demos/jspsych-mirror-camera-demo1.html
+++ b/7.3/demos/jspsych-mirror-camera-demo1.html
@@ -1,36 +1,36 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <!-- <script src="../../packages/jspsych/dist/index.browser.js"></script> -->
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <!-- <script src="../../packages/plugin-mirror-camera/dist/index.browser.js"></script> -->
-    <script src="https://unpkg.com/@jspsych/plugin-mirror-camera@1.0.1"></script>
-    <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
-    <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const init_camera = {
-      type: jsPsychInitializeCamera,
-    }
-
-    const mirror_camera = {
-      type: jsPsychMirrorCamera,
-    }
-
-    const timeline = [init_camera, mirror_camera];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <!-- <script src="../../packages/jspsych/dist/index.browser.js"></script> -->
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <!-- <script src="../../packages/plugin-mirror-camera/dist/index.browser.js"></script> -->
+    <script src="https://unpkg.com/@jspsych/plugin-mirror-camera@1.0.2"></script>
+    <!-- <script src="../../packages/plugin-initialize-camera/dist/index.browser.js"></script> -->
+    <script src="https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const init_camera = {
+      type: jsPsychInitializeCamera,
+    }
+
+    const mirror_camera = {
+      type: jsPsychMirrorCamera,
+    }
+
+    const timeline = [init_camera, mirror_camera];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-preload-demo1.html b/7.3/demos/jspsych-preload-demo1.html
old mode 100755
new mode 100644
index deec214088..01f4dd68b6
--- a/7.3/demos/jspsych-preload-demo1.html
+++ b/7.3/demos/jspsych-preload-demo1.html
@@ -1,48 +1,48 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      auto_preload: true
-    }
-
-    const trial_1 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/happy_face_1.jpg',
-      choices: ['Next']
-    }
-
-    const trial_2 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/happy_face_2.jpg',
-      choices: ['Next']
-    }
-
-    const trial_3 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/happy_face_3.jpg',
-      choices: ['Next']
-    }
-
-    const timeline = [preload, trial_1, trial_2, trial_3];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      auto_preload: true
+    }
+
+    const trial_1 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/happy_face_1.jpg',
+      choices: ['Next']
+    }
+
+    const trial_2 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/happy_face_2.jpg',
+      choices: ['Next']
+    }
+
+    const trial_3 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/happy_face_3.jpg',
+      choices: ['Next']
+    }
+
+    const timeline = [preload, trial_1, trial_2, trial_3];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-preload-demo2.html b/7.3/demos/jspsych-preload-demo2.html
old mode 100755
new mode 100644
index 1f3d0b8cb6..c1d65260b4
--- a/7.3/demos/jspsych-preload-demo2.html
+++ b/7.3/demos/jspsych-preload-demo2.html
@@ -1,39 +1,39 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: ['img/sad_face_1.jpg']
-    }
-
-    const trial_1 = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: `
-        <p>Study this face</p>
-        <img src="img/sad_face_1.jpg"></img>
-      `,
-      choices: ['Next']
-    }
-
-    const timeline = [preload, trial_1];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: ['img/sad_face_1.jpg']
+    }
+
+    const trial_1 = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: `
+        <p>Study this face</p>
+        <img src="img/sad_face_1.jpg"></img>
+      `,
+      choices: ['Next']
+    }
+
+    const timeline = [preload, trial_1];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-preload-demo3.html b/7.3/demos/jspsych-preload-demo3.html
old mode 100755
new mode 100644
index 037a8f2f5b..cb5cacd3f6
--- a/7.3/demos/jspsych-preload-demo3.html
+++ b/7.3/demos/jspsych-preload-demo3.html
@@ -1,79 +1,79 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial_1 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/happy_face_1.jpg',
-      choices: ['Next']
-    }
-
-    const trial_2 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/happy_face_2.jpg',
-      choices: ['Next']
-    }
-
-    const trial_3 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/happy_face_3.jpg',
-      choices: ['Next']
-    }
-
-    const block_1 = {
-      timeline: [trial_1, trial_2, trial_3]
-    }
-
-    const trial_4 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/sad_face_1.jpg',
-      choices: ['Next']
-    }
-
-    const trial_5 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/sad_face_2.jpg',
-      choices: ['Next']
-    }
-
-    const trial_6 = {
-      type: jsPsychImageButtonResponse,
-      stimulus: 'img/sad_face_3.jpg',
-      choices: ['Next']
-    }
-
-    const block_2 = {
-      timeline: [trial_4, trial_5, trial_6]
-    }
-
-    const preload_block_1 = {
-      type: jsPsychPreload,
-      trials: [block_1]
-    }
-
-    const preload_block_2 = {
-      type: jsPsychPreload,
-      trials: [block_2]
-    }
-
-    const timeline = [preload_block_1, block_1, preload_block_2, block_2];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial_1 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/happy_face_1.jpg',
+      choices: ['Next']
+    }
+
+    const trial_2 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/happy_face_2.jpg',
+      choices: ['Next']
+    }
+
+    const trial_3 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/happy_face_3.jpg',
+      choices: ['Next']
+    }
+
+    const block_1 = {
+      timeline: [trial_1, trial_2, trial_3]
+    }
+
+    const trial_4 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/sad_face_1.jpg',
+      choices: ['Next']
+    }
+
+    const trial_5 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/sad_face_2.jpg',
+      choices: ['Next']
+    }
+
+    const trial_6 = {
+      type: jsPsychImageButtonResponse,
+      stimulus: 'img/sad_face_3.jpg',
+      choices: ['Next']
+    }
+
+    const block_2 = {
+      timeline: [trial_4, trial_5, trial_6]
+    }
+
+    const preload_block_1 = {
+      type: jsPsychPreload,
+      trials: [block_1]
+    }
+
+    const preload_block_2 = {
+      type: jsPsychPreload,
+      trials: [block_2]
+    }
+
+    const timeline = [preload_block_1, block_1, preload_block_2, block_2];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-preload-demo4.html b/7.3/demos/jspsych-preload-demo4.html
old mode 100755
new mode 100644
index 1d2c5e47d7..de40be750e
--- a/7.3/demos/jspsych-preload-demo4.html
+++ b/7.3/demos/jspsych-preload-demo4.html
@@ -1,31 +1,31 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: ['img/bad_file_path.png'],
-      show_detailed_errors: true
-    }
-
-    const timeline = [preload];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-image-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: ['img/bad_file_path.png'],
+      show_detailed_errors: true
+    }
+
+    const timeline = [preload];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-reconstruction-demo1.html b/7.3/demos/jspsych-reconstruction-demo1.html
old mode 100755
new mode 100644
index 0873fe8bb4..103adef809
--- a/7.3/demos/jspsych-reconstruction-demo1.html
+++ b/7.3/demos/jspsych-reconstruction-demo1.html
@@ -1,50 +1,50 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-reconstruction@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const sample_function = function(param){
-      const size = 50 + Math.floor(param*250);
-      const html = '<div style="display: block; margin: auto; height: 300px; width: 300px; position: relative;">'+
-        '<div style="display: block; position: absolute; top: '+(150 - size/2)+'px; left:'+(150 - size/2)+'px; background-color: #000000; '+
-        'width: '+size+'px; height: '+size+'px;"></div></div><p>Press "h" to make the square larger. Press "g" to make the square smaller.</p>'+
-        '<p>When the square is the same size as the previous one, click Continue.</p>';
-      return html;
-    }
-
-    const match_item = {
-      type: jsPsychHtmlKeyboardResponse,
-      stimulus: '<div style="display: block; margin: auto; height: 300px; width: 300px; position: relative;">'+
-        '<div style="display: block; position: absolute; top: '+(150 - 210/2)+'px; left:'+(150 - 210/2)+'px; background-color: #000000; '+
-        'width: 210px; height: 210px;"></div></div>',
-      choices: ['c'],
-      post_trial_gap: 1250,
-      prompt: '<p>Study the size of this square carefully. On the next screen you will have to recreate it. When you are ready, press "c".</p>'
-    }
-
-    const reconstruction = {
-      type: jsPsychReconstruction,
-      stim_function: sample_function,
-      starting_value: 0.5,
-    }
-
-    const timeline =  [match_item, reconstruction];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-reconstruction@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const sample_function = function(param){
+      const size = 50 + Math.floor(param*250);
+      const html = '<div style="display: block; margin: auto; height: 300px; width: 300px; position: relative;">'+
+        '<div style="display: block; position: absolute; top: '+(150 - size/2)+'px; left:'+(150 - size/2)+'px; background-color: #000000; '+
+        'width: '+size+'px; height: '+size+'px;"></div></div><p>Press "h" to make the square larger. Press "g" to make the square smaller.</p>'+
+        '<p>When the square is the same size as the previous one, click Continue.</p>';
+      return html;
+    }
+
+    const match_item = {
+      type: jsPsychHtmlKeyboardResponse,
+      stimulus: '<div style="display: block; margin: auto; height: 300px; width: 300px; position: relative;">'+
+        '<div style="display: block; position: absolute; top: '+(150 - 210/2)+'px; left:'+(150 - 210/2)+'px; background-color: #000000; '+
+        'width: 210px; height: 210px;"></div></div>',
+      choices: ['c'],
+      post_trial_gap: 1250,
+      prompt: '<p>Study the size of this square carefully. On the next screen you will have to recreate it. When you are ready, press "c".</p>'
+    }
+
+    const reconstruction = {
+      type: jsPsychReconstruction,
+      stim_function: sample_function,
+      starting_value: 0.5,
+    }
+
+    const timeline =  [match_item, reconstruction];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-resize-demo1.html b/7.3/demos/jspsych-resize-demo1.html
old mode 100755
new mode 100644
index 234b7eb167..51fccea7f5
--- a/7.3/demos/jspsych-resize-demo1.html
+++ b/7.3/demos/jspsych-resize-demo1.html
@@ -1,32 +1,32 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-resize@1.0.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychResize,
-      item_width: 3 + 3/8,
-      item_height: 2 + 1/8,
-      prompt: "<p>Click and drag the lower right corner of the box until the box is the same size as a credit card held up to the screen.</p>",
-      pixels_per_unit: 150
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-resize@1.0.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychResize,
+      item_width: 3 + 3/8,
+      item_height: 2 + 1/8,
+      prompt: "<p>Click and drag the lower right corner of the box until the box is the same size as a credit card held up to the screen.</p>",
+      pixels_per_unit: 150
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-same-different-html-demo1.html b/7.3/demos/jspsych-same-different-html-demo1.html
old mode 100755
new mode 100644
index 9f39a13252..08838729be
--- a/7.3/demos/jspsych-same-different-html-demo1.html
+++ b/7.3/demos/jspsych-same-different-html-demo1.html
@@ -1,38 +1,38 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-same-different-html@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSameDifferentHtml,
-      stimuli: [
-        '<p style="font-size:30px;">Climbing</p>',
-        '<p style="font-size:30px;">Walking</p>'
-      ],
-      prompt: `<p>Press 's' if the activities require the same amount of physical exertion.</p>
-        <p>Press 'd' if the activities require different amount of physical exertion.</p>`,
-      same_key: 's',
-      different_key: 'd',
-      first_stim_duration: 800,
-      answer: 'different'
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-same-different-html@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSameDifferentHtml,
+      stimuli: [
+        '<p style="font-size:30px;">Climbing</p>',
+        '<p style="font-size:30px;">Walking</p>'
+      ],
+      prompt: `<p>Press 's' if the activities require the same amount of physical exertion.</p>
+        <p>Press 'd' if the activities require different amount of physical exertion.</p>`,
+      same_key: 's',
+      different_key: 'd',
+      first_stim_duration: 800,
+      answer: 'different'
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-same-different-image-demo1.html b/7.3/demos/jspsych-same-different-image-demo1.html
old mode 100755
new mode 100644
index d48fc9244e..40af6c04c9
--- a/7.3/demos/jspsych-same-different-image-demo1.html
+++ b/7.3/demos/jspsych-same-different-image-demo1.html
@@ -1,48 +1,48 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-same-different-image@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: [
-        'img/happy_face_1.jpg',
-        'img/sad_face_3.jpg'
-      ]
-    }
-
-    const trial = {
-      type: jsPsychSameDifferentImage,
-      stimuli: [
-        'img/happy_face_1.jpg',
-        'img/sad_face_3.jpg'
-      ],
-      prompt: `<p>Press s if the faces had the same emotional expression.</p>
-        <p>Press d if the faces had different emotional expressions.</p>`,
-      same_key: 's',
-      different_key: 'd',
-      first_stim_duration: 800,
-      second_stim_duration: 800,
-      answer: 'different'
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-same-different-image@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: [
+        'img/happy_face_1.jpg',
+        'img/sad_face_3.jpg'
+      ]
+    }
+
+    const trial = {
+      type: jsPsychSameDifferentImage,
+      stimuli: [
+        'img/happy_face_1.jpg',
+        'img/sad_face_3.jpg'
+      ],
+      prompt: `<p>Press s if the faces had the same emotional expression.</p>
+        <p>Press d if the faces had different emotional expressions.</p>`,
+      same_key: 's',
+      different_key: 'd',
+      first_stim_duration: 800,
+      second_stim_duration: 800,
+      answer: 'different'
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-serial-reaction-time-demo1.html b/7.3/demos/jspsych-serial-reaction-time-demo1.html
old mode 100755
new mode 100644
index b9074cdc37..cc388ce0b0
--- a/7.3/demos/jspsych-serial-reaction-time-demo1.html
+++ b/7.3/demos/jspsych-serial-reaction-time-demo1.html
@@ -1,63 +1,63 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.3"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const instructions = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: '<p>Use the S, F, H, and K keys to respond.</p>',
-      choices: ['Continue']
-    }
-
-    const grid = [
-      [1,1,1,1]
-    ]
-
-    const response_map = [
-      ['s','f','h','k']
-    ]
-
-    const trial_1 = {
-      type: jsPsychSerialReactionTime,
-      grid: grid,
-      choices: response_map,
-      target: [0,0]
-    }
-    const trial_2 = {
-      type: jsPsychSerialReactionTime,
-      grid: grid,
-      choices: response_map,
-      target: [0,1]
-    }
-    const trial_3 = {
-      type: jsPsychSerialReactionTime,
-      grid: grid,
-      choices: response_map,
-      target: [0,2]
-    }
-    const trial_4 = {
-      type: jsPsychSerialReactionTime,
-      grid: grid,
-      choices: response_map,
-      target: [0,3]
-    }
-
-    const timeline = [instructions, trial_1, trial_2, trial_3, trial_4];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.4"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const instructions = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: '<p>Use the S, F, H, and K keys to respond.</p>',
+      choices: ['Continue']
+    }
+
+    const grid = [
+      [1,1,1,1]
+    ]
+
+    const response_map = [
+      ['s','f','h','k']
+    ]
+
+    const trial_1 = {
+      type: jsPsychSerialReactionTime,
+      grid: grid,
+      choices: response_map,
+      target: [0,0]
+    }
+    const trial_2 = {
+      type: jsPsychSerialReactionTime,
+      grid: grid,
+      choices: response_map,
+      target: [0,1]
+    }
+    const trial_3 = {
+      type: jsPsychSerialReactionTime,
+      grid: grid,
+      choices: response_map,
+      target: [0,2]
+    }
+    const trial_4 = {
+      type: jsPsychSerialReactionTime,
+      grid: grid,
+      choices: response_map,
+      target: [0,3]
+    }
+
+    const timeline = [instructions, trial_1, trial_2, trial_3, trial_4];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-serial-reaction-time-demo2.html b/7.3/demos/jspsych-serial-reaction-time-demo2.html
old mode 100755
new mode 100644
index 52d745e15b..5c77f5eca6
--- a/7.3/demos/jspsych-serial-reaction-time-demo2.html
+++ b/7.3/demos/jspsych-serial-reaction-time-demo2.html
@@ -1,73 +1,73 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.3"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const instructions = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: '<p>Use the R, I, V, and M keys to respond.</p>',
-      choices: ['Continue']
-    }
-
-    const grid = [
-      [1,1],
-      [1,1]
-    ]
-
-    const response_map = [
-      ['r','i'],
-      ['v','m']
-    ]
-
-    const trial_1 = {
-      type: jsPsychSerialReactionTime,
-      grid: grid,
-      choices: response_map,
-      target: [0,0],
-      show_response_feedback: true,
-      feedback_duration: 500
-    }
-    const trial_2 = {
-      type: jsPsychSerialReactionTime,
-      grid: grid,
-      choices: response_map,
-      target: [0,1],
-      show_response_feedback: true,
-      feedback_duration: 500
-    }
-    const trial_3 = {
-      type: jsPsychSerialReactionTime,
-      grid: grid,
-      choices: response_map,
-      target: [1,1],
-      show_response_feedback: true,
-      feedback_duration: 500
-    }
-    const trial_4 = {
-      type: jsPsychSerialReactionTime,
-      grid: grid,
-      choices: response_map,
-      target: [1,0],
-      show_response_feedback: true,
-      feedback_duration: 500
-    }
-
-    const timeline = [instructions, trial_1, trial_2, trial_3, trial_4];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.4"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const instructions = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: '<p>Use the R, I, V, and M keys to respond.</p>',
+      choices: ['Continue']
+    }
+
+    const grid = [
+      [1,1],
+      [1,1]
+    ]
+
+    const response_map = [
+      ['r','i'],
+      ['v','m']
+    ]
+
+    const trial_1 = {
+      type: jsPsychSerialReactionTime,
+      grid: grid,
+      choices: response_map,
+      target: [0,0],
+      show_response_feedback: true,
+      feedback_duration: 500
+    }
+    const trial_2 = {
+      type: jsPsychSerialReactionTime,
+      grid: grid,
+      choices: response_map,
+      target: [0,1],
+      show_response_feedback: true,
+      feedback_duration: 500
+    }
+    const trial_3 = {
+      type: jsPsychSerialReactionTime,
+      grid: grid,
+      choices: response_map,
+      target: [1,1],
+      show_response_feedback: true,
+      feedback_duration: 500
+    }
+    const trial_4 = {
+      type: jsPsychSerialReactionTime,
+      grid: grid,
+      choices: response_map,
+      target: [1,0],
+      show_response_feedback: true,
+      feedback_duration: 500
+    }
+
+    const timeline = [instructions, trial_1, trial_2, trial_3, trial_4];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-serial-reaction-time-mouse-demo1.html b/7.3/demos/jspsych-serial-reaction-time-mouse-demo1.html
old mode 100755
new mode 100644
index 532e2b72ce..9802a90f14
--- a/7.3/demos/jspsych-serial-reaction-time-mouse-demo1.html
+++ b/7.3/demos/jspsych-serial-reaction-time-mouse-demo1.html
@@ -1,49 +1,49 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const grid = [
-      [1,1,1,1]
-    ]
-
-    const trial_1 = {
-      type: jsPsychSerialReactionTimeMouse,
-      grid: grid,
-      target: [0,0]
-    }
-    const trial_2 = {
-      type: jsPsychSerialReactionTimeMouse,
-      grid: grid,
-      target: [0,1]
-    }
-    const trial_3 = {
-      type: jsPsychSerialReactionTimeMouse,
-      grid: grid,
-      target: [0,2]
-    }
-    const trial_4 = {
-      type: jsPsychSerialReactionTimeMouse,
-      grid: grid,
-      target: [0,3]
-    }
-
-    const timeline = [trial_1, trial_2, trial_3, trial_4]
-    
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const grid = [
+      [1,1,1,1]
+    ]
+
+    const trial_1 = {
+      type: jsPsychSerialReactionTimeMouse,
+      grid: grid,
+      target: [0,0]
+    }
+    const trial_2 = {
+      type: jsPsychSerialReactionTimeMouse,
+      grid: grid,
+      target: [0,1]
+    }
+    const trial_3 = {
+      type: jsPsychSerialReactionTimeMouse,
+      grid: grid,
+      target: [0,2]
+    }
+    const trial_4 = {
+      type: jsPsychSerialReactionTimeMouse,
+      grid: grid,
+      target: [0,3]
+    }
+
+    const timeline = [trial_1, trial_2, trial_3, trial_4]
+    
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-serial-reaction-time-mouse-demo2.html b/7.3/demos/jspsych-serial-reaction-time-mouse-demo2.html
old mode 100755
new mode 100644
index 5e2dfa4582..4f0e194038
--- a/7.3/demos/jspsych-serial-reaction-time-mouse-demo2.html
+++ b/7.3/demos/jspsych-serial-reaction-time-mouse-demo2.html
@@ -1,55 +1,55 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const grid = [
-      [1,0,1],
-      [0,0,0],
-      [1,0,1]
-    ]
-
-    const trial_1 = {
-      type: jsPsychSerialReactionTimeMouse,
-      grid: grid,
-      target: [0,0],
-      target_color: '#006738'
-    }
-    const trial_2 = {
-      type: jsPsychSerialReactionTimeMouse,
-      grid: grid,
-      target: [0,2],
-      target_color: '#F78F1E'
-    }
-    const trial_3 = {
-      type: jsPsychSerialReactionTimeMouse,
-      grid: grid,
-      target: [2,2],
-      target_color: '#13B24B'
-    }
-    const trial_4 = {
-      type: jsPsychSerialReactionTimeMouse,
-      grid: grid,
-      target: [2,0],
-      target_color: '#E74921'
-    }
-
-    const timeline = [trial_1, trial_2, trial_3, trial_4]
-      
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const grid = [
+      [1,0,1],
+      [0,0,0],
+      [1,0,1]
+    ]
+
+    const trial_1 = {
+      type: jsPsychSerialReactionTimeMouse,
+      grid: grid,
+      target: [0,0],
+      target_color: '#006738'
+    }
+    const trial_2 = {
+      type: jsPsychSerialReactionTimeMouse,
+      grid: grid,
+      target: [0,2],
+      target_color: '#F78F1E'
+    }
+    const trial_3 = {
+      type: jsPsychSerialReactionTimeMouse,
+      grid: grid,
+      target: [2,2],
+      target_color: '#13B24B'
+    }
+    const trial_4 = {
+      type: jsPsychSerialReactionTimeMouse,
+      grid: grid,
+      target: [2,0],
+      target_color: '#E74921'
+    }
+
+    const timeline = [trial_1, trial_2, trial_3, trial_4]
+      
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-sketchpad-demo1.html b/7.3/demos/jspsych-sketchpad-demo1.html
old mode 100755
new mode 100644
index 02c26cd679..e6c52e098f
--- a/7.3/demos/jspsych-sketchpad-demo1.html
+++ b/7.3/demos/jspsych-sketchpad-demo1.html
@@ -1,33 +1,33 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-sketchpad@1.0.3"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSketchpad,
-      prompt: '<p>Draw an apple!</p>',
-      prompt_location: 'abovecanvas',
-      canvas_width: 300,
-      canvas_height: 300,
-      canvas_border_width: 2
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-sketchpad@1.0.4"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSketchpad,
+      prompt: '<p>Draw an apple!</p>',
+      prompt_location: 'abovecanvas',
+      canvas_width: 300,
+      canvas_height: 300,
+      canvas_border_width: 2
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-sketchpad-demo2.html b/7.3/demos/jspsych-sketchpad-demo2.html
old mode 100755
new mode 100644
index 59e0986ff2..5d12cac2b3
--- a/7.3/demos/jspsych-sketchpad-demo2.html
+++ b/7.3/demos/jspsych-sketchpad-demo2.html
@@ -1,35 +1,35 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-sketchpad@1.0.3"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSketchpad,
-      prompt: '<p>Circle the mouth using red. Circle the eyes using blue.</p>',
-      prompt_location: 'abovecanvas',
-      stroke_color_palette: ['red', 'blue'],
-      stroke_color: 'red',
-      background_image: 'img/sad_face_4.jpg',
-      canvas_width: 380,
-      canvas_height: 252
-    }
-    
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-sketchpad@1.0.4"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSketchpad,
+      prompt: '<p>Circle the mouth using red. Circle the eyes using blue.</p>',
+      prompt_location: 'abovecanvas',
+      stroke_color_palette: ['red', 'blue'],
+      stroke_color: 'red',
+      background_image: 'img/sad_face_4.jpg',
+      canvas_width: 380,
+      canvas_height: 252
+    }
+    
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-sketchpad-demo3.html b/7.3/demos/jspsych-sketchpad-demo3.html
old mode 100755
new mode 100644
index 68d6089557..2ac701f157
--- a/7.3/demos/jspsych-sketchpad-demo3.html
+++ b/7.3/demos/jspsych-sketchpad-demo3.html
@@ -1,44 +1,44 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-sketchpad@1.0.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const draw = {
-      type: jsPsychSketchpad,
-      prompt: '<p>Draw the first animal that comes to mind. You have 30 seconds!</p>',
-      prompt_location: 'belowcanvas',
-      trial_duration: 30000,
-      show_countdown_trial_duration: true,
-    }
-
-    const label = {
-      type: jsPsychSurveyText,
-      preamble: () => {
-        const imageData = jsPsych.data.get().last(1).values()[0].png;
-        return `<img src="${imageData}"></img>`;
-      },
-      questions: [
-        {prompt: 'What animal did you draw?'}
-      ]
-    }
-
-    const timeline = [draw, label]
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-sketchpad@1.0.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const draw = {
+      type: jsPsychSketchpad,
+      prompt: '<p>Draw the first animal that comes to mind. You have 30 seconds!</p>',
+      prompt_location: 'belowcanvas',
+      trial_duration: 30000,
+      show_countdown_trial_duration: true,
+    }
+
+    const label = {
+      type: jsPsychSurveyText,
+      preamble: () => {
+        const imageData = jsPsych.data.get().last(1).values()[0].png;
+        return `<img src="${imageData}"></img>`;
+      },
+      questions: [
+        {prompt: 'What animal did you draw?'}
+      ]
+    }
+
+    const timeline = [draw, label]
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-demo1.html b/7.3/demos/jspsych-survey-demo1.html
old mode 100755
new mode 100644
index d8b2282caf..4f01f4f160
--- a/7.3/demos/jspsych-survey-demo1.html
+++ b/7.3/demos/jspsych-survey-demo1.html
@@ -1,51 +1,51 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.1"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.1/css/survey.css">
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurvey,
-      pages: [
-        [
-          {
-            type: 'html',
-            prompt: 'Please answer the following questions:',
-          },
-          {
-            type: 'multi-choice',
-            prompt: "Which of the following do you like the most?", 
-            name: 'VegetablesLike', 
-            options: ['Tomato', 'Cucumber', 'Eggplant', 'Corn', 'Peas'], 
-            required: true
-          }, 
-          {
-            type: 'multi-select',
-            prompt: "Which of the following do you like?", 
-            name: 'FruitLike', 
-            options: ['Apple', 'Banana', 'Orange', 'Grape', 'Strawberry'], 
-            required: false,
-          }
-        ]
-      ],
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.2"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.2/css/survey.css">
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurvey,
+      pages: [
+        [
+          {
+            type: 'html',
+            prompt: 'Please answer the following questions:',
+          },
+          {
+            type: 'multi-choice',
+            prompt: "Which of the following do you like the most?", 
+            name: 'VegetablesLike', 
+            options: ['Tomato', 'Cucumber', 'Eggplant', 'Corn', 'Peas'], 
+            required: true
+          }, 
+          {
+            type: 'multi-select',
+            prompt: "Which of the following do you like?", 
+            name: 'FruitLike', 
+            options: ['Apple', 'Banana', 'Orange', 'Grape', 'Strawberry'], 
+            required: false,
+          }
+        ]
+      ],
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-demo2.html b/7.3/demos/jspsych-survey-demo2.html
old mode 100755
new mode 100644
index 2bfde6d292..8104b15ccc
--- a/7.3/demos/jspsych-survey-demo2.html
+++ b/7.3/demos/jspsych-survey-demo2.html
@@ -1,69 +1,69 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <meta charset="utf-8">
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.1"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.1/css/survey.css">
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurvey,
-      pages: [
-        [
-          {
-            type: 'text',
-            prompt: "Where were you born?", 
-            placeholder: 'City, State, Country',
-            name: 'birthplace', 
-            required: true,
-          }, 
-          {
-            type: 'text',
-            prompt: "How old are you?", 
-            name: 'age', 
-            textbox_columns: 5,
-            required: false,
-          }
-        ],
-        [
-          {
-            type: 'multi-choice',
-            prompt: "What's your favorite color?", 
-            options: ['blue','yellow','pink','teal','orange','lime green','other','none of these'],
-            name: 'FavColor', 
-          }, 
-          {
-            type: 'multi-select',
-            prompt: "Which of these animals do you like? Select all that apply.", 
-            options: ['lion','squirrel','badger','whale'],
-            option_reorder: 'random',
-            columns: 0,
-            name: 'AnimalLike', 
-          }
-        ]
-      ],
-      title: 'My questionnaire',
-      button_label_next: 'Continue',
-      button_label_back: 'Previous',
-      button_label_finish: 'Submit',
-      show_question_numbers: 'onPage'
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <meta charset="utf-8">
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.2"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.2/css/survey.css">
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurvey,
+      pages: [
+        [
+          {
+            type: 'text',
+            prompt: "Where were you born?", 
+            placeholder: 'City, State, Country',
+            name: 'birthplace', 
+            required: true,
+          }, 
+          {
+            type: 'text',
+            prompt: "How old are you?", 
+            name: 'age', 
+            textbox_columns: 5,
+            required: false,
+          }
+        ],
+        [
+          {
+            type: 'multi-choice',
+            prompt: "What's your favorite color?", 
+            options: ['blue','yellow','pink','teal','orange','lime green','other','none of these'],
+            name: 'FavColor', 
+          }, 
+          {
+            type: 'multi-select',
+            prompt: "Which of these animals do you like? Select all that apply.", 
+            options: ['lion','squirrel','badger','whale'],
+            option_reorder: 'random',
+            columns: 0,
+            name: 'AnimalLike', 
+          }
+        ]
+      ],
+      title: 'My questionnaire',
+      button_label_next: 'Continue',
+      button_label_back: 'Previous',
+      button_label_finish: 'Submit',
+      show_question_numbers: 'onPage'
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-demo3.html b/7.3/demos/jspsych-survey-demo3.html
old mode 100755
new mode 100644
index 8577986ab8..d3940da9c3
--- a/7.3/demos/jspsych-survey-demo3.html
+++ b/7.3/demos/jspsych-survey-demo3.html
@@ -1,86 +1,86 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <meta charset="utf-8">
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.1"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.1/css/survey.css">
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurvey,
-      pages: [
-        [
-          {
-            type: 'likert',
-            prompt: 'I like to eat vegetables.',
-            likert_scale_min_label: 'Strongly Disagree',
-            likert_scale_max_label: 'Strongly Agree',
-            likert_scale_values: [
-              {value: 1},
-              {value: 2},
-              {value: 3},
-              {value: 4},
-              {value: 5}
-            ]
-          }, 
-          {
-            type: 'likert',
-            prompt: 'I like to eat fruit.',
-            likert_scale_min_label: 'Strongly Disagree',
-            likert_scale_max_label: 'Strongly Agree',
-            likert_scale_values: [
-              {value: 1},
-              {value: 2},
-              {value: 3},
-              {value: 4},
-              {value: 5}
-            ]
-          },
-          {
-            type: 'likert',
-            prompt: 'I like to eat meat.',
-            likert_scale_min_label: 'Strongly Disagree',
-            likert_scale_max_label: 'Strongly Agree',
-            likert_scale_values: [
-              {value: 1},
-              {value: 2},
-              {value: 3},
-              {value: 4},
-              {value: 5}
-            ]
-          },  
-          
-        ],
-        [
-          {
-            type: 'likert-table',
-            prompt: ' ',
-            statements: [
-              {prompt: 'I like to eat vegetables', name: 'VeggiesTable'},
-              {prompt: 'I like to eat fruit', name: 'FruitTable'},
-              {prompt: 'I like to eat meat', name: 'MeatTable'},
-            ],
-            options: ['Strongly Disagree', 'Disagree', 'Neutral', 'Agree', 'Strongly Agree'],
-          }
-        ]
-      ],
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <meta charset="utf-8">
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.2"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.2/css/survey.css">
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurvey,
+      pages: [
+        [
+          {
+            type: 'likert',
+            prompt: 'I like to eat vegetables.',
+            likert_scale_min_label: 'Strongly Disagree',
+            likert_scale_max_label: 'Strongly Agree',
+            likert_scale_values: [
+              {value: 1},
+              {value: 2},
+              {value: 3},
+              {value: 4},
+              {value: 5}
+            ]
+          }, 
+          {
+            type: 'likert',
+            prompt: 'I like to eat fruit.',
+            likert_scale_min_label: 'Strongly Disagree',
+            likert_scale_max_label: 'Strongly Agree',
+            likert_scale_values: [
+              {value: 1},
+              {value: 2},
+              {value: 3},
+              {value: 4},
+              {value: 5}
+            ]
+          },
+          {
+            type: 'likert',
+            prompt: 'I like to eat meat.',
+            likert_scale_min_label: 'Strongly Disagree',
+            likert_scale_max_label: 'Strongly Agree',
+            likert_scale_values: [
+              {value: 1},
+              {value: 2},
+              {value: 3},
+              {value: 4},
+              {value: 5}
+            ]
+          },  
+          
+        ],
+        [
+          {
+            type: 'likert-table',
+            prompt: ' ',
+            statements: [
+              {prompt: 'I like to eat vegetables', name: 'VeggiesTable'},
+              {prompt: 'I like to eat fruit', name: 'FruitTable'},
+              {prompt: 'I like to eat meat', name: 'MeatTable'},
+            ],
+            options: ['Strongly Disagree', 'Disagree', 'Neutral', 'Agree', 'Strongly Agree'],
+          }
+        ]
+      ],
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-demo4.html b/7.3/demos/jspsych-survey-demo4.html
old mode 100755
new mode 100644
index ee06f212ae..9a4e004d8f
--- a/7.3/demos/jspsych-survey-demo4.html
+++ b/7.3/demos/jspsych-survey-demo4.html
@@ -1,41 +1,41 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <meta charset="utf-8">
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.1"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.1/css/survey.css">
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurvey,
-      pages: [
-        [
-          {
-            type: 'multi-choice',
-            prompt: 'During the experiment, are allowed to write things down on paper to help you?',
-            options: ["Yes", "No"],
-            correct_response: "No",
-            required: true
-          }, 
-        ]
-      ],
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <meta charset="utf-8">
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.2"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.2/css/survey.css">
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurvey,
+      pages: [
+        [
+          {
+            type: 'multi-choice',
+            prompt: 'During the experiment, are allowed to write things down on paper to help you?',
+            options: ["Yes", "No"],
+            correct_response: "No",
+            required: true
+          }, 
+        ]
+      ],
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-demo5.html b/7.3/demos/jspsych-survey-demo5.html
old mode 100755
new mode 100644
index 9dd7fbaca4..31d883b0b0
--- a/7.3/demos/jspsych-survey-demo5.html
+++ b/7.3/demos/jspsych-survey-demo5.html
@@ -1,72 +1,72 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <meta charset="utf-8">
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.1"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.1/css/survey.css">
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const question_info = [
-      {
-        'fruit': 'apples',
-        'Q1_prompt': 'Do you like apples?', 
-        'Q1_type': 'regular'
-      },
-      {
-        'fruit': 'bananas',
-        'Q1_prompt': 'Do you NOT like bananas?', 
-        'Q1_type': 'reverse'
-      },
-    ];
-
-    const survey = {
-      type: jsPsychSurvey,
-      pages:[
-        [
-          {
-            type: 'multi-choice',
-            prompt: jsPsych.timelineVariable('Q1_prompt'),
-            options: ['Yes', 'No'],
-            name: 'Q1'
-          },
-          {
-            type: 'text',
-            prompt: function() {
-              return `What's your favorite thing about ${jsPsych.timelineVariable('fruit')}?`;
-            },
-            name: 'Q2'
-          }
-        ]
-      ],
-      data: {
-        'Q1_prompt': jsPsych.timelineVariable('Q1_prompt'),
-        'Q1_type': jsPsych.timelineVariable('Q1_type'),
-        'fruit': jsPsych.timelineVariable('fruit')                                                        
-      },
-      button_label_finish: 'Continue'                
-    };
-
-    const survey_procedure = {
-      timeline: [survey],
-      timeline_variables: question_info,
-      randomize_order: true
-    };
-
-    const timeline = [survey_procedure];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <meta charset="utf-8">
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey@0.2.2"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="https://unpkg.com/@jspsych/plugin-survey@0.2.2/css/survey.css">
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const question_info = [
+      {
+        'fruit': 'apples',
+        'Q1_prompt': 'Do you like apples?', 
+        'Q1_type': 'regular'
+      },
+      {
+        'fruit': 'bananas',
+        'Q1_prompt': 'Do you NOT like bananas?', 
+        'Q1_type': 'reverse'
+      },
+    ];
+
+    const survey = {
+      type: jsPsychSurvey,
+      pages:[
+        [
+          {
+            type: 'multi-choice',
+            prompt: jsPsych.timelineVariable('Q1_prompt'),
+            options: ['Yes', 'No'],
+            name: 'Q1'
+          },
+          {
+            type: 'text',
+            prompt: function() {
+              return `What's your favorite thing about ${jsPsych.timelineVariable('fruit')}?`;
+            },
+            name: 'Q2'
+          }
+        ]
+      ],
+      data: {
+        'Q1_prompt': jsPsych.timelineVariable('Q1_prompt'),
+        'Q1_type': jsPsych.timelineVariable('Q1_type'),
+        'fruit': jsPsych.timelineVariable('fruit')                                                        
+      },
+      button_label_finish: 'Continue'                
+    };
+
+    const survey_procedure = {
+      timeline: [survey],
+      timeline_variables: question_info,
+      randomize_order: true
+    };
+
+    const timeline = [survey_procedure];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-html-form-demo1.html b/7.3/demos/jspsych-survey-html-form-demo1.html
old mode 100755
new mode 100644
index 2a3b42e6d3..2a3d95e2bf
--- a/7.3/demos/jspsych-survey-html-form-demo1.html
+++ b/7.3/demos/jspsych-survey-html-form-demo1.html
@@ -1,30 +1,30 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyHtmlForm,
-      preamble: '<p>How are you feeling <b>right now?</b></p>',
-      html: '<p> I am feeling <input name="first" type="text" />, <input name="second" type="text" />, and <input name="third" type="text" />.</p>'
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyHtmlForm,
+      preamble: '<p>How are you feeling <b>right now?</b></p>',
+      html: '<p> I am feeling <input name="first" type="text" />, <input name="second" type="text" />, and <input name="third" type="text" />.</p>'
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-html-form-demo2.html b/7.3/demos/jspsych-survey-html-form-demo2.html
old mode 100755
new mode 100644
index 5f2b62c633..a52560e2c7
--- a/7.3/demos/jspsych-survey-html-form-demo2.html
+++ b/7.3/demos/jspsych-survey-html-form-demo2.html
@@ -1,31 +1,31 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyHtmlForm,
-      preamble: '<p>What is your favorite bird?</p>',
-      html: '<p>My favorite bird is <input type="text" id="test-resp-box" name="response" size="10" /></p>',
-      autofocus: 'test-resp-box'
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyHtmlForm,
+      preamble: '<p>What is your favorite bird?</p>',
+      html: '<p>My favorite bird is <input type="text" id="test-resp-box" name="response" size="10" /></p>',
+      autofocus: 'test-resp-box'
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-likert-demo1.html b/7.3/demos/jspsych-survey-likert-demo1.html
old mode 100755
new mode 100644
index 6ed3004160..27e08b5fad
--- a/7.3/demos/jspsych-survey-likert-demo1.html
+++ b/7.3/demos/jspsych-survey-likert-demo1.html
@@ -1,40 +1,40 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-likert@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyLikert,
-      questions: [
-        {
-          prompt: "I like vegetables.",
-          labels: [
-            "Strongly Disagree",
-            "Disagree",
-            "Neutral",
-            "Agree",
-            "Strongly Agree"
-          ]
-        }
-      ]
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-likert@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyLikert,
+      questions: [
+        {
+          prompt: "I like vegetables.",
+          labels: [
+            "Strongly Disagree",
+            "Disagree",
+            "Neutral",
+            "Agree",
+            "Strongly Agree"
+          ]
+        }
+      ]
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-likert-demo2.html b/7.3/demos/jspsych-survey-likert-demo2.html
old mode 100755
new mode 100644
index 82b73e6ad0..a46e6e7d12
--- a/7.3/demos/jspsych-survey-likert-demo2.html
+++ b/7.3/demos/jspsych-survey-likert-demo2.html
@@ -1,42 +1,42 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-likert@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const likert_scale = [
-      "Strongly Disagree",
-      "Disagree",
-      "Neutral",
-      "Agree",
-      "Strongly Agree"
-    ];
-
-    const trial = {
-      type: jsPsychSurveyLikert,
-      questions: [
-        {prompt: "I like vegetables.", name: 'Vegetables', labels: likert_scale},
-        {prompt: "I like fruit.", name: 'Fruit', labels: likert_scale},
-        {prompt: "I like meat.", name: 'Meat', labels: likert_scale},
-      ],
-      randomize_question_order: true
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-likert@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const likert_scale = [
+      "Strongly Disagree",
+      "Disagree",
+      "Neutral",
+      "Agree",
+      "Strongly Agree"
+    ];
+
+    const trial = {
+      type: jsPsychSurveyLikert,
+      questions: [
+        {prompt: "I like vegetables.", name: 'Vegetables', labels: likert_scale},
+        {prompt: "I like fruit.", name: 'Fruit', labels: likert_scale},
+        {prompt: "I like meat.", name: 'Meat', labels: likert_scale},
+      ],
+      randomize_question_order: true
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-multi-choice-demo1.html b/7.3/demos/jspsych-survey-multi-choice-demo1.html
old mode 100755
new mode 100644
index 515f6df325..3b0ed38b28
--- a/7.3/demos/jspsych-survey-multi-choice-demo1.html
+++ b/7.3/demos/jspsych-survey-multi-choice-demo1.html
@@ -1,42 +1,42 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyMultiChoice,
-      questions: [
-        {
-          prompt: "Which of the following do you like the most?",
-          name: 'VegetablesLike',
-          options: ['Tomato', 'Cucumber', 'Eggplant', 'Corn', 'Peas'],
-          required: true
-        },
-        {
-          prompt: "Which of the following do you like the least?",
-          name: 'FruitDislike',
-          options: ['Apple', 'Banana', 'Orange', 'Grape', 'Strawberry'],
-          required: false
-        }
-      ],
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyMultiChoice,
+      questions: [
+        {
+          prompt: "Which of the following do you like the most?",
+          name: 'VegetablesLike',
+          options: ['Tomato', 'Cucumber', 'Eggplant', 'Corn', 'Peas'],
+          required: true
+        },
+        {
+          prompt: "Which of the following do you like the least?",
+          name: 'FruitDislike',
+          options: ['Apple', 'Banana', 'Orange', 'Grape', 'Strawberry'],
+          required: false
+        }
+      ],
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-multi-choice-demo2.html b/7.3/demos/jspsych-survey-multi-choice-demo2.html
old mode 100755
new mode 100644
index e498191e5f..6b8dff0072
--- a/7.3/demos/jspsych-survey-multi-choice-demo2.html
+++ b/7.3/demos/jspsych-survey-multi-choice-demo2.html
@@ -1,44 +1,44 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyMultiChoice,
-      questions: [
-        {
-          prompt: "Which of the following do you like the most?",
-          name: 'VegetablesLike',
-          options: ['Tomato', 'Cucumber', 'Eggplant', 'Corn', 'Peas'],
-          required: true,
-          horizontal: true
-        },
-        {
-          prompt: "Which of the following do you like the least?",
-          name: 'FruitDislike',
-          options: ['Apple', 'Banana', 'Orange', 'Grape', 'Strawberry'],
-          required: false,
-          horizontal: true
-        }
-      ],
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyMultiChoice,
+      questions: [
+        {
+          prompt: "Which of the following do you like the most?",
+          name: 'VegetablesLike',
+          options: ['Tomato', 'Cucumber', 'Eggplant', 'Corn', 'Peas'],
+          required: true,
+          horizontal: true
+        },
+        {
+          prompt: "Which of the following do you like the least?",
+          name: 'FruitDislike',
+          options: ['Apple', 'Banana', 'Orange', 'Grape', 'Strawberry'],
+          required: false,
+          horizontal: true
+        }
+      ],
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-multi-select-demo1.html b/7.3/demos/jspsych-survey-multi-select-demo1.html
old mode 100755
new mode 100644
index cdb3275016..2cbafa68ad
--- a/7.3/demos/jspsych-survey-multi-select-demo1.html
+++ b/7.3/demos/jspsych-survey-multi-select-demo1.html
@@ -1,45 +1,45 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-multi-select@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyMultiSelect,
-      questions: [
-        {
-          prompt: "Which of these colors do you like?",
-          options: ["Red", "Yellow", "Green", "Blue", "Black"],
-          horizontal: true,
-          required: true,
-          name: 'Colors'
-        },
-        {
-          prompt: "Which of these foods do you like?",
-          options: ["Apples", "Bananas", "Carrots", "Donuts", "Eggplant"],
-          horizontal: true,
-          required: true,
-          name: 'Foods'
-        }
-      ],
-      randomize_question_order: true
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-multi-select@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css" />
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyMultiSelect,
+      questions: [
+        {
+          prompt: "Which of these colors do you like?",
+          options: ["Red", "Yellow", "Green", "Blue", "Black"],
+          horizontal: true,
+          required: true,
+          name: 'Colors'
+        },
+        {
+          prompt: "Which of these foods do you like?",
+          options: ["Apples", "Bananas", "Carrots", "Donuts", "Eggplant"],
+          horizontal: true,
+          required: true,
+          name: 'Foods'
+        }
+      ],
+      randomize_question_order: true
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-text-demo1.html b/7.3/demos/jspsych-survey-text-demo1.html
old mode 100755
new mode 100644
index d2a999eef0..261fcb9855
--- a/7.3/demos/jspsych-survey-text-demo1.html
+++ b/7.3/demos/jspsych-survey-text-demo1.html
@@ -1,31 +1,31 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyText,
-      questions: [
-        {prompt: 'How old are you?'}
-      ]
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyText,
+      questions: [
+        {prompt: 'How old are you?'}
+      ]
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-text-demo2.html b/7.3/demos/jspsych-survey-text-demo2.html
old mode 100755
new mode 100644
index 98e853fc61..4666dcfaba
--- a/7.3/demos/jspsych-survey-text-demo2.html
+++ b/7.3/demos/jspsych-survey-text-demo2.html
@@ -1,32 +1,32 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyText,
-      questions: [
-        {prompt: 'What is your date of birth?', placeholder: 'mm/dd/yyyy', required: true},
-        {prompt: 'What country do you currently live in?'}
-      ]
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyText,
+      questions: [
+        {prompt: 'What is your date of birth?', placeholder: 'mm/dd/yyyy', required: true},
+        {prompt: 'What country do you currently live in?'}
+      ]
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-text-demo3.html b/7.3/demos/jspsych-survey-text-demo3.html
old mode 100755
new mode 100644
index e9b170d220..b072bb9408
--- a/7.3/demos/jspsych-survey-text-demo3.html
+++ b/7.3/demos/jspsych-survey-text-demo3.html
@@ -1,32 +1,32 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const trial = {
-      type: jsPsychSurveyText,
-      questions: [
-        {prompt: 'What did you eat for breakfast?', name: 'Breakfast'},
-        {prompt: 'What did you eat for lunch?', name: 'Lunch'}
-      ]
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const trial = {
+      type: jsPsychSurveyText,
+      questions: [
+        {prompt: 'What did you eat for breakfast?', name: 'Breakfast'},
+        {prompt: 'What did you eat for lunch?', name: 'Lunch'}
+      ]
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-survey-text-demo4.html b/7.3/demos/jspsych-survey-text-demo4.html
old mode 100755
new mode 100644
index c0ec69d69b..c9a43c6cca
--- a/7.3/demos/jspsych-survey-text-demo4.html
+++ b/7.3/demos/jspsych-survey-text-demo4.html
@@ -1,38 +1,38 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: ['img/navarro_burst_03.jpg']
-    }
-
-    const trial = {
-      type: jsPsychSurveyText,
-      preamble: `<img src="img/navarro_burst_03.jpg" style="width:400px;"></img>`,
-      questions: [
-        {prompt: 'Describe your reaction to the image above', rows: 5}
-      ]
-    }
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-survey-text@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: ['img/navarro_burst_03.jpg']
+    }
+
+    const trial = {
+      type: jsPsychSurveyText,
+      preamble: `<img src="img/navarro_burst_03.jpg" style="width:400px;"></img>`,
+      questions: [
+        {prompt: 'Describe your reaction to the image above', rows: 5}
+      ]
+    }
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-video-button-response-demo1.html b/7.3/demos/jspsych-video-button-response-demo1.html
old mode 100755
new mode 100644
index 6b4e9e10d7..d3e1d3578d
--- a/7.3/demos/jspsych-video-button-response-demo1.html
+++ b/7.3/demos/jspsych-video-button-response-demo1.html
@@ -1,40 +1,40 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-video-button-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      video: 'video/fish.mp4'
-    }
-
-    const trial = {
-      type: jsPsychVideoButtonResponse,
-      stimulus: [
-        'video/fish.mp4'
-      ],
-      choices: ['0-5', '6-10','11-15','16-20','21-25','25+'],
-      prompt: "<p>How many different fish are shown in the video?</p>",
-      response_allowed_while_playing: false
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-video-button-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      video: 'video/fish.mp4'
+    }
+
+    const trial = {
+      type: jsPsychVideoButtonResponse,
+      stimulus: [
+        'video/fish.mp4'
+      ],
+      choices: ['0-5', '6-10','11-15','16-20','21-25','25+'],
+      prompt: "<p>How many different fish are shown in the video?</p>",
+      response_allowed_while_playing: false
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-video-keyboard-response-demo1.html b/7.3/demos/jspsych-video-keyboard-response-demo1.html
old mode 100755
new mode 100644
index f771a159b4..63b39379fb
--- a/7.3/demos/jspsych-video-keyboard-response-demo1.html
+++ b/7.3/demos/jspsych-video-keyboard-response-demo1.html
@@ -1,39 +1,39 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-video-keyboard-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      video: 'video/fish.mp4'
-    }
-
-    const trial = {
-      type: jsPsychVideoKeyboardResponse,
-      stimulus: [
-        'video/fish.mp4'
-      ],
-      choices: "NO_KEYS",
-      trial_ends_after_video: true
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-video-keyboard-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      video: 'video/fish.mp4'
+    }
+
+    const trial = {
+      type: jsPsychVideoKeyboardResponse,
+      stimulus: [
+        'video/fish.mp4'
+      ],
+      choices: "NO_KEYS",
+      trial_ends_after_video: true
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-video-slider-response-demo1.html b/7.3/demos/jspsych-video-slider-response-demo1.html
old mode 100755
new mode 100644
index 4982cbb68e..7e35e59920
--- a/7.3/demos/jspsych-video-slider-response-demo1.html
+++ b/7.3/demos/jspsych-video-slider-response-demo1.html
@@ -1,37 +1,37 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-video-slider-response@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      video: 'video/fish.mp4'
-    }
-
-    const trial = {
-      type: jsPsychVideoSliderResponse,
-      stimulus: [
-        'video/fish.mp4'
-      ],
-      labels: ["Hated it", "Loved it"],
-      prompt: '<p>Please rate your enjoyment of the video clip.</p>'
-    };
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-video-slider-response@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      video: 'video/fish.mp4'
+    }
+
+    const trial = {
+      type: jsPsychVideoSliderResponse,
+      stimulus: [
+        'video/fish.mp4'
+      ],
+      labels: ["Hated it", "Loved it"],
+      prompt: '<p>Please rate your enjoyment of the video clip.</p>'
+    };
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-virtual-chinrest-demo1.html b/7.3/demos/jspsych-virtual-chinrest-demo1.html
old mode 100755
new mode 100644
index 1129ed041f..47e8667bb6
--- a/7.3/demos/jspsych-virtual-chinrest-demo1.html
+++ b/7.3/demos/jspsych-virtual-chinrest-demo1.html
@@ -1,38 +1,38 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.2"></script>
-    <script src="https://cdnjs.cloudflare.com/ajax/libs/svg.js/2.6.3/svg.min"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: ['img/card.png']
-    };
-
-    const trial = {
-      type: jsPsychVirtualChinrest,
-      blindspot_reps: 3,
-      resize_units: "none",
-      item_path: "img/card.png"
-    };
-
-    const timeline = [trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.3"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/svg.js/2.6.3/svg.min"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: ['img/card.png']
+    };
+
+    const trial = {
+      type: jsPsychVirtualChinrest,
+      blindspot_reps: 3,
+      resize_units: "none",
+      item_path: "img/card.png"
+    };
+
+    const timeline = [trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-virtual-chinrest-demo2.html b/7.3/demos/jspsych-virtual-chinrest-demo2.html
old mode 100755
new mode 100644
index 60beab5f9c..a8095f5f8b
--- a/7.3/demos/jspsych-virtual-chinrest-demo2.html
+++ b/7.3/demos/jspsych-virtual-chinrest-demo2.html
@@ -1,48 +1,48 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.2"></script>
-    <script src="https://cdnjs.cloudflare.com/ajax/libs/svg.js/2.6.3/svg.min.js"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: ['img/card.png']
-    };
-
-    const trial = {
-      type: jsPsychVirtualChinrest,
-      blindspot_reps: 3,
-      resize_units: "cm",
-      pixels_per_unit: 50,
-      item_path: "img/card.png"
-    };
-
-    const resized_stimulus = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: `
-        <p>If the measurements were done correctly, the square below should be 10 cm x 10 cm.</p>
-        <div style="background-color: black; width: 500px; height: 500px; margin: 20px auto;"></div>
-      `,
-      choices: ['Continue']
-    }
-
-    const timeline = [trial, resized_stimulus];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.3"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/svg.js/2.6.3/svg.min.js"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: ['img/card.png']
+    };
+
+    const trial = {
+      type: jsPsychVirtualChinrest,
+      blindspot_reps: 3,
+      resize_units: "cm",
+      pixels_per_unit: 50,
+      item_path: "img/card.png"
+    };
+
+    const resized_stimulus = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: `
+        <p>If the measurements were done correctly, the square below should be 10 cm x 10 cm.</p>
+        <div style="background-color: black; width: 500px; height: 500px; margin: 20px auto;"></div>
+      `,
+      choices: ['Continue']
+    }
+
+    const timeline = [trial, resized_stimulus];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-virtual-chinrest-demo3.html b/7.3/demos/jspsych-virtual-chinrest-demo3.html
old mode 100755
new mode 100644
index 273f3d0aa5..15a1d85f55
--- a/7.3/demos/jspsych-virtual-chinrest-demo3.html
+++ b/7.3/demos/jspsych-virtual-chinrest-demo3.html
@@ -1,48 +1,48 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.2"></script>
-    <script src="https://cdnjs.cloudflare.com/ajax/libs/svg.js/2.6.3/svg.min.js"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: ['img/card.png']
-    }
-
-    const trial = {
-      type: jsPsychVirtualChinrest,
-      blindspot_reps: 3,
-      resize_units: "deg",
-      pixels_per_unit: 50,
-      item_path: "img/card.png"
-    };
-
-    const resized_stimulus = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: `
-        <p>If the measurements were done correctly, the square below should take up about 10 degrees of visual angle.</p>
-        <div style="background-color: black; width: 500px; height: 500px; margin: 20px auto;"></div>
-      `,
-      choices: ['Continue']
-    }
-
-    const timeline = [trial, resized_stimulus];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.3"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/svg.js/2.6.3/svg.min.js"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: ['img/card.png']
+    }
+
+    const trial = {
+      type: jsPsychVirtualChinrest,
+      blindspot_reps: 3,
+      resize_units: "deg",
+      pixels_per_unit: 50,
+      item_path: "img/card.png"
+    };
+
+    const resized_stimulus = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: `
+        <p>If the measurements were done correctly, the square below should take up about 10 degrees of visual angle.</p>
+        <div style="background-color: black; width: 500px; height: 500px; margin: 20px auto;"></div>
+      `,
+      choices: ['Continue']
+    }
+
+    const timeline = [trial, resized_stimulus];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-visual-search-circle-demo1.html b/7.3/demos/jspsych-visual-search-circle-demo1.html
old mode 100755
new mode 100644
index 977346e0c0..d4e2b1ccee
--- a/7.3/demos/jspsych-visual-search-circle-demo1.html
+++ b/7.3/demos/jspsych-visual-search-circle-demo1.html
@@ -1,46 +1,46 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: ['img/backwardN.gif', 'img/normalN.gif', 'img/fixation.gif']
-    }
-
-    const instructions = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: `<p>Press J if there is a backwards N.</p>
-        <p>Press F if all the Ns are in the normal orientation.</p>`,
-      choices: ['Continue']
-    }
-
-    const trial = {
-      type: jsPsychVisualSearchCircle,
-      target: 'img/backwardN.gif',
-      foil: 'img/normalN.gif',
-      fixation_image: 'img/fixation.gif',
-      target_present: true,
-      set_size: 4
-    }
-
-    const timeline = [instructions, trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: ['img/backwardN.gif', 'img/normalN.gif', 'img/fixation.gif']
+    }
+
+    const instructions = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: `<p>Press J if there is a backwards N.</p>
+        <p>Press F if all the Ns are in the normal orientation.</p>`,
+      choices: ['Continue']
+    }
+
+    const trial = {
+      type: jsPsychVisualSearchCircle,
+      target: 'img/backwardN.gif',
+      foil: 'img/normalN.gif',
+      fixation_image: 'img/fixation.gif',
+      target_present: true,
+      set_size: 4
+    }
+
+    const timeline = [instructions, trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/jspsych-visual-search-circle-demo2.html b/7.3/demos/jspsych-visual-search-circle-demo2.html
old mode 100755
new mode 100644
index 2ab29f775c..b566531a9b
--- a/7.3/demos/jspsych-visual-search-circle-demo2.html
+++ b/7.3/demos/jspsych-visual-search-circle-demo2.html
@@ -1,46 +1,46 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <script src="docs-demo-timeline.js"></script>
-    <script src="https://unpkg.com/jspsych@7.3.3"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2"></script>
-    <script src="https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.2"></script>
-    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.3/css/jspsych.css" />
-    <link rel="stylesheet" href="docs-demo.css" type="text/css">
-  </head>
-  <body></body>
-  <script>
-
-    const jsPsych = initJsPsych();
-
-    const preload = {
-      type: jsPsychPreload,
-      images: ['img/elephant.png', 'img/lion.png', 'img/monkey.png']
-    }
-
-    const instructions = {
-      type: jsPsychHtmlButtonResponse,
-      stimulus: `<p>Press E if there is an elephant in the group.</p>
-        <p>Press N if there is no elephant in the group.</p>`,
-      choices: ['Continue']
-    }
-
-    const trial = {
-      type: jsPsychVisualSearchCircle,
-      stimuli: ['img/elephant.png', 'img/lion.png', 'img/monkey.png'],
-      fixation_image: 'img/fixation.gif',
-      target_present_key: 'e',
-      target_absent_key: 'n',
-      target_present: true
-    }
-
-    const timeline = [instructions, trial];
-
-    if (typeof jsPsych !== "undefined") {
-      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
-    } else {
-      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
-    }
-  </script>
-</html>
+<!DOCTYPE html>
+<html>
+  <head>
+    <script src="docs-demo-timeline.js"></script>
+    <script src="https://unpkg.com/jspsych@7.3.4"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-preload@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3"></script>
+    <script src="https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.3"></script>
+    <link rel="stylesheet" href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" />
+    <link rel="stylesheet" href="docs-demo.css" type="text/css">
+  </head>
+  <body></body>
+  <script>
+
+    const jsPsych = initJsPsych();
+
+    const preload = {
+      type: jsPsychPreload,
+      images: ['img/elephant.png', 'img/lion.png', 'img/monkey.png']
+    }
+
+    const instructions = {
+      type: jsPsychHtmlButtonResponse,
+      stimulus: `<p>Press E if there is an elephant in the group.</p>
+        <p>Press N if there is no elephant in the group.</p>`,
+      choices: ['Continue']
+    }
+
+    const trial = {
+      type: jsPsychVisualSearchCircle,
+      stimuli: ['img/elephant.png', 'img/lion.png', 'img/monkey.png'],
+      fixation_image: 'img/fixation.gif',
+      target_present_key: 'e',
+      target_absent_key: 'n',
+      target_present: true
+    }
+
+    const timeline = [instructions, trial];
+
+    if (typeof jsPsych !== "undefined") {
+      jsPsych.run(generateDocsDemoTimeline(timeline, [preload]));
+    } else {
+      document.body.innerHTML = '<div style="text-align:center; margin-top:50%; transform:translate(0,-50%);">You must be online to view the plugin demo.</div>';
+    }
+  </script>
+</html>
diff --git a/7.3/demos/sound/hammer.mp3 b/7.3/demos/sound/hammer.mp3
old mode 100755
new mode 100644
diff --git a/7.3/demos/sound/roar.mp3 b/7.3/demos/sound/roar.mp3
old mode 100755
new mode 100644
diff --git a/7.3/demos/sound/sound.mp3 b/7.3/demos/sound/sound.mp3
old mode 100755
new mode 100644
diff --git a/7.3/demos/sound/speech_blue.mp3 b/7.3/demos/sound/speech_blue.mp3
old mode 100755
new mode 100644
diff --git a/7.3/demos/sound/speech_green.mp3 b/7.3/demos/sound/speech_green.mp3
old mode 100755
new mode 100644
diff --git a/7.3/demos/sound/speech_joke.mp3 b/7.3/demos/sound/speech_joke.mp3
old mode 100755
new mode 100644
diff --git a/7.3/demos/sound/speech_red.mp3 b/7.3/demos/sound/speech_red.mp3
old mode 100755
new mode 100644
diff --git a/7.3/demos/sound/tone.mp3 b/7.3/demos/sound/tone.mp3
old mode 100755
new mode 100644
diff --git a/7.3/demos/video/fish.mp4 b/7.3/demos/video/fish.mp4
old mode 100755
new mode 100644
diff --git a/7.3/developers/configuration/index.html b/7.3/developers/configuration/index.html
old mode 100755
new mode 100644
index a2d0a05625..7b139efd16
--- a/7.3/developers/configuration/index.html
+++ b/7.3/developers/configuration/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/developers/configuration/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1997,16 +2000,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/developers/configuration.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="configuring-the-jspsych-development-environment">Configuring the jsPsych development environment<a class="headerlink" href="#configuring-the-jspsych-development-environment" title="Permanent link">&para;</a></h1>
 <h2 id="setup">Setup<a class="headerlink" href="#setup" title="Permanent link">&para;</a></h2>
 <p>JsPsych is written using <a href="https://www.typescriptlang.org/">TypeScript</a>, a superset of JavaScript that adds static typing, but compiles to plain JavaScript.
@@ -2014,23 +2019,22 @@ <h2 id="setup">Setup<a class="headerlink" href="#setup" title="Permanent link">&
 Node.js comes with a package manager called NPM (Node Package Manager) that can install JavaScript libraries to run on your machine, such as TypeScript and other build tools for jsPsych.
 In order to work on code in the jsPsych or the jspsych-contrib repository, it is recommended that you follow the steps below to set up your development environment.</p>
 <h3 id="install-nodejs">Install Node.js<a class="headerlink" href="#install-nodejs" title="Permanent link">&para;</a></h3>
-<p>The jsPsych development setup requires Node.js &gt;= v14 to be installed on your machine.
-We recommend that you <a href="https://nodejs.org/en/">install version 16</a> since it includes version 7 of NPM (required for the workspaces feature that the jsPsych repositories use).
-If you are bound to Node.js v14, make sure to install NPM v7 manually (via <code>npm install -g npm@7</code>).</p>
+<p>The jsPsych development setup requires a <a href="https://nodejs.org/en/download/">Node.js LTS version</a> to be installed on your machine.</p>
 <h3 id="clone-the-repository-and-install-the-dependencies">Clone the repository and install the dependencies<a class="headerlink" href="#clone-the-repository-and-install-the-dependencies" title="Permanent link">&para;</a></h3>
 <p>Clone either the jsPsych repository or the jspsych-contrib repository by running</p>
-<div class="highlight"><pre><span></span><code>git clone https://github.com/jspsych/jsPsych.git <span class="o">&amp;&amp;</span> <span class="nb">cd</span> jsPsych
+<div class="highlight"><pre><span></span><code>git<span class="w"> </span>clone<span class="w"> </span>https://github.com/jspsych/jsPsych.git<span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="nb">cd</span><span class="w"> </span>jsPsych
 </code></pre></div>
 <p>or</p>
-<p><div class="highlight"><pre><span></span><code>git clone https://github.com/jspsych/jspsych-contrib.git <span class="o">&amp;&amp;</span> <span class="nb">cd</span> jspsych-contrib
+<p><div class="highlight"><pre><span></span><code>git<span class="w"> </span>clone<span class="w"> </span>https://github.com/jspsych/jspsych-contrib.git<span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="nb">cd</span><span class="w"> </span>jspsych-contrib
 </code></pre></div>
 in a terminal.</p>
 <p>Then run <code>npm install</code>.
 This will create a <code>node_modules</code> directory and install all the dependencies into it that are required to build and test jsPsych.</p>
-<div class="admonition attention">
-<p class="admonition-title">Attention</p>
-<p>It is important that <code>npm install</code> is only run in the root directory of the repository (due to the NPM workspaces feature).
-If you accidentally ran <code>npm install</code> anywhere else, remove the <code>node_modules</code> directory and the <code>package-lock.json</code> file that were created at that location and run <code>npm install</code> in the root directory again.</p>
+<div class="admonition info">
+<p class="admonition-title">Info</p>
+<p>The jsPsych (-contrib) repositories depend on the <code>canvas</code> package which comes with pre-built binaries.
+On systems for which no pre-built binaries are available, <code>npm install</code> will try to build the binaries from scratch, sometimes failing with an error message mentioning the <code>canvas</code> package.
+If you are facing such installation issues, please follow the <a href="https://github.com/Automattic/node-canvas/wiki#installation-guides">installation instructions</a> of the <code>canvas</code> package and run <code>npm install</code> again afterwards.</p>
 </div>
 <div class="admonition info">
 <p class="admonition-title">Info</p>
@@ -2093,16 +2097,25 @@ <h2 id="testing">Testing<a class="headerlink" href="#testing" title="Permanent l
 <p>Tests for plugins and extensions are located in the <code>/src</code> folder of the corresponding package. Test files for plugins and extensions are named <code>index.spec.ts</code>.</p>
 <p>There are helper functions for testing in <code>/packages/jspsych/tests/utils.ts</code>. We recommend looking at other test files to observe conventions for testing.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../../extensions/webgazer/" class="md-footer__link md-footer__link--prev" aria-label="Previous: webgazer" rel="prev">
@@ -2161,7 +2174,7 @@ <h2 id="testing">Testing<a class="headerlink" href="#testing" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2170,7 +2183,7 @@ <h2 id="testing">Testing<a class="headerlink" href="#testing" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2183,11 +2196,13 @@ <h2 id="testing">Testing<a class="headerlink" href="#testing" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/developers/contributing/index.html b/7.3/developers/contributing/index.html
old mode 100755
new mode 100644
index 9702c7a318..4480582ec1
--- a/7.3/developers/contributing/index.html
+++ b/7.3/developers/contributing/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/developers/contributing/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1969,16 +1972,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/developers/contributing.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="contributing-to-jspsych">Contributing to jsPsych<a class="headerlink" href="#contributing-to-jspsych" title="Permanent link">&para;</a></h1>
 <p>We welcome contributions of all kinds, including changes to the core codebase, the development of new plugins and extensions, and improvements to the documentation. </p>
 <p>The project is managed entirely through the <a href="https://github.com/jspsych/jsPsych">GitHub repository</a>. There you can:</p>
@@ -2015,16 +2020,25 @@ <h2 id="contributing-to-jspsych-vs-jspsych-contrib">Contributing to <code>jspsyc
 <p>The main <code>jspsych</code> repository is open to new plugins and extensions that are likely to be widely used. We require that contributions to main repository are well documented and tested before they are merged. Contributions to the main repository must use TypeScript. We limit contributions to this repository because once a plugin or extension is in the main codebase we are generally committed to providing updates as we develop new versions of jsPsych. Each new plugin and extension potentially increases the amount of development work that we will need to do in the future, so we are somewhat selective about what we will merge. If you have an idea that you'd like to discuss please <a href="https://github.com/jspsych/jsPsych/discussions/new">open a discussion thread</a> and we'd love to chat about it!</p>
 <p>The <code>jspsych-contrib</code> repository is open to any contributions that are complete and working code. There are some minimal guidelines in place about basic documentation that should be provided. Contributors can choose whether to develop their plugin or extension using our <a href="https://github.com/jspsych/jspsych-contrib/tree/main/packages/plugin-template-ts">TypeScript template</a> or using our <a href="https://github.com/jspsych/jspsych-contrib/tree/main/packages/plugin-template">JavaScript template</a>. Contributions to <code>jspsych-contrib</code> are not evaluated for general usefulness in the same way that contributions to the main repository are. We also periodically consider whether to move contributions into the main repository from <code>jspsych-contrib</code> based on their popularity and completeness (documentation and testing).</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../documentation/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Building the Documentation" rel="prev">
@@ -2083,7 +2097,7 @@ <h2 id="contributing-to-jspsych-vs-jspsych-contrib">Contributing to <code>jspsyc
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2092,7 +2106,7 @@ <h2 id="contributing-to-jspsych-vs-jspsych-contrib">Contributing to <code>jspsyc
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2105,11 +2119,13 @@ <h2 id="contributing-to-jspsych-vs-jspsych-contrib">Contributing to <code>jspsyc
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/developers/documentation/index.html b/7.3/developers/documentation/index.html
old mode 100755
new mode 100644
index 169fa3029c..0c2fb1393f
--- a/7.3/developers/documentation/index.html
+++ b/7.3/developers/documentation/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/developers/documentation/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,16 +1974,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/developers/documentation.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="building-the-jspsych-documentation">Building the jsPsych documentation<a class="headerlink" href="#building-the-jspsych-documentation" title="Permanent link">&para;</a></h1>
 <p>The documentation hosted at <a href="https://www.jspsych.org">https://www.jspsych.org</a> is generated using <a href="https://www.mkdocs.org/">mkdocs</a> and the <a href="https://squidfunk.github.io/mkdocs-material/">mkdocs-material theme</a>. The documentation files are located in the <a href="https://github.com/jspsych/jsPsych/tree/main/docs"><code>/docs</code> directory of the GitHub repository</a>. The documentation is written using markdown.</p>
 <p>To build a local copy of the docs, you will need to install <code>mkdocs</code>, <code>mkdocs-material</code>, and <code>mike</code> using <code>poetry</code>. </p>
@@ -2002,16 +2007,25 @@ <h2 id="updating-the-public-docs-site">Updating the public docs site<a class="he
 </div>
 <p>After the documentation has been built locally (and therefore committed to your local <code>gh-pages</code> branch), you can update the live documentation site by switching to your <code>gh-pages</code> branch and pushing to the remote <code>gh-pages</code> branch.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../configuration/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Configuration" rel="prev">
@@ -2070,7 +2084,7 @@ <h2 id="updating-the-public-docs-site">Updating the public docs site<a class="he
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2079,7 +2093,7 @@ <h2 id="updating-the-public-docs-site">Updating the public docs site<a class="he
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2092,11 +2106,13 @@ <h2 id="updating-the-public-docs-site">Updating the public docs site<a class="he
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/developers/extension-development/index.html b/7.3/developers/extension-development/index.html
old mode 100755
new mode 100644
index 00bd8794ce..b7b6ac5644
--- a/7.3/developers/extension-development/index.html
+++ b/7.3/developers/extension-development/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/developers/extension-development/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2079,16 +2082,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/developers/extension-development.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="extension-development">Extension development<a class="headerlink" href="#extension-development" title="Permanent link">&para;</a></h1>
 <h2 id="requirements-for-an-extension">Requirements for an extension<a class="headerlink" href="#requirements-for-an-extension" title="Permanent link">&para;</a></h2>
 <p>As of version 7.0, extensions are <a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Classes">JavaScript Classes</a>. An extension must implement:</p>
@@ -2105,117 +2110,117 @@ <h3 id="templates">Templates<a class="headerlink" href="#templates" title="Perma
 <h2 id="extension-components">Extension components<a class="headerlink" href="#extension-components" title="Permanent link">&para;</a></h2>
 <h3 id="constructor">constructor()<a class="headerlink" href="#constructor" title="Permanent link">&para;</a></h3>
 <p>The extension's <code>constructor()</code> will be passed a reference to the instance of the <code>JsPsych</code> class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="kr">constructor</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="kr">constructor</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">){</span>
+<span class="w">    </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="initialize">initialize()<a class="headerlink" href="#initialize" title="Permanent link">&para;</a></h3>
 <p>The <code>initialize()</code> function is called when an instance of jsPsych is first initialized, either through <code>initJsPsych()</code> or <code>new JsPsych()</code>. This is where setup code for the extension should be run. This event will happen once per experiment, unlike the other events which occur with each trial. The <code>params</code> object can include whatever parameters are necessary to configure the extension. The <code>params</code> object is passed from the call to <code>initJsPsych()</code> to <code>initialize()</code> method. <code>initialize()</code> must return a <code>Promise</code> that resolves when the extension is finished initializing. </p>
-<div class="highlight"><pre><span></span><code><span class="c1">//... experiment code ...//</span><span class="w"></span>
-<span class="kd">let</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">myAwesomeExtension</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">demo</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;value&#39;</span><span class="p">}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
-
-<span class="c1">//... extension code ...//</span><span class="w"></span>
-<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">initialize</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nb">Promise</span><span class="p">((</span><span class="nx">resolve</span><span class="p">,</span><span class="w"> </span><span class="nx">reject</span><span class="p">)=&gt;{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">params</span><span class="p">.</span><span class="nx">demo</span><span class="p">);</span><span class="w"> </span><span class="c1">// will output &#39;value&#39;</span><span class="w"></span>
-
-<span class="w">      </span><span class="nx">resolve</span><span class="p">();</span><span class="w"> </span><span class="c1">// finish initialzing</span><span class="w"></span>
-<span class="w">    </span><span class="p">})</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">//... experiment code ...//</span>
+<span class="kd">let</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">myAwesomeExtension</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">demo</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;value&#39;</span><span class="p">}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">});</span>
+
+<span class="c1">//... extension code ...//</span>
+<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span>
+
+<span class="w">  </span><span class="nx">initialize</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nb">Promise</span><span class="p">((</span><span class="nx">resolve</span><span class="p">,</span><span class="w"> </span><span class="nx">reject</span><span class="p">)=&gt;{</span>
+<span class="w">      </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">params</span><span class="p">.</span><span class="nx">demo</span><span class="p">);</span><span class="w"> </span><span class="c1">// will output &#39;value&#39;</span>
+
+<span class="w">      </span><span class="nx">resolve</span><span class="p">();</span><span class="w"> </span><span class="c1">// finish initialzing</span>
+<span class="w">    </span><span class="p">})</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="on_start">on_start()<a class="headerlink" href="#on_start" title="Permanent link">&para;</a></h3>
 <p><code>on_start()</code> is called at the start of the plugin execution, prior to calling <code>plugin.trial</code>. This is where trial-specific initialization can happen, such as creating empty containers to hold data or resetting internal state. The <code>params</code> object is passed from the declaration of the extension in the trial object. You can use <code>params</code> to customize the behavior of the extension for each trial.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">//... experiment code ...//</span><span class="w"></span>
-<span class="kd">let</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;You&#39;re awesome!&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">myAwesomeExtension</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">demo</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;value&#39;</span><span class="p">}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
-
-<span class="c1">//... extension code ...//</span><span class="w"></span>
-<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">initialize</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">on_start</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">params</span><span class="p">.</span><span class="nx">demo</span><span class="p">);</span><span class="w"> </span><span class="c1">// outputs &#39;value&#39; before the trial begins.</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">//... experiment code ...//</span>
+<span class="kd">let</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;You&#39;re awesome!&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">myAwesomeExtension</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">demo</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;value&#39;</span><span class="p">}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">});</span>
+
+<span class="c1">//... extension code ...//</span>
+<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span>
+
+<span class="w">  </span><span class="nx">initialize</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span>
+
+<span class="w">  </span><span class="nx">on_start</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">params</span><span class="p">.</span><span class="nx">demo</span><span class="p">);</span><span class="w"> </span><span class="c1">// outputs &#39;value&#39; before the trial begins.</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="on_load">on_load()<a class="headerlink" href="#on_load" title="Permanent link">&para;</a></h3>
 <p><code>on_load()</code> is called after the <code>on_load</code> event for the plugin has completed, which is typically when the plugin has finished executing initial DOM-modifying code and has set up various event listeners. This is where the extension can begin actively interacting with the DOM and recording data. The <code>params</code> object is passed from the declaration of the extension in the trial object. You can use <code>params</code> to customize the behavior of the extension for each trial.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">//... experiment code ...//</span><span class="w"></span>
-<span class="kd">let</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;You&#39;re awesome!&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">myAwesomeExtension</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">demo</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;value&#39;</span><span class="p">}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
-
-<span class="c1">//... extension code ...//</span><span class="w"></span>
-<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">initialize</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">on_start</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">on_load</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// replaces the contents of the display with &#39;value&#39;;</span><span class="w"></span>
-<span class="w">    </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getDisplayElement</span><span class="p">().</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">params</span><span class="p">.</span><span class="nx">demo</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">//... experiment code ...//</span>
+<span class="kd">let</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;You&#39;re awesome!&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">myAwesomeExtension</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">demo</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;value&#39;</span><span class="p">}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">});</span>
+
+<span class="c1">//... extension code ...//</span>
+<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span>
+
+<span class="w">  </span><span class="nx">initialize</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span>
+
+<span class="w">  </span><span class="nx">on_start</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span>
+
+<span class="w">  </span><span class="nx">on_load</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span>
+<span class="w">    </span><span class="c1">// replaces the contents of the display with &#39;value&#39;;</span>
+<span class="w">    </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getDisplayElement</span><span class="p">().</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">params</span><span class="p">.</span><span class="nx">demo</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="on_finish">on_finish()<a class="headerlink" href="#on_finish" title="Permanent link">&para;</a></h3>
 <p><code>on_finish()</code> is called after the plugin invokes <code>jsPsych.finishTrial()</code>. This can be used for any teardown at the end of the trial. This method should return an object of data to append to the plugin's data. Note that this event fires <em>before</em> the <code>on_finish</code> event for the plugin, so data added by the extension is accessible in any trial <code>on_finish</code> event handlers. The <code>params</code> object is passed from the declaration of the extension in the trial object. You can use <code>params</code> to customize the behavior of the extension for each trial.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">//... experiment code ...//</span><span class="w"></span>
-<span class="kd">let</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;You&#39;re awesome!&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">myAwesomeExtension</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">demo</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;value&#39;</span><span class="p">}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">awesome</span><span class="p">);</span><span class="w"> </span><span class="c1">// will output &#39;value&#39;.</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
-
-<span class="c1">//... extension code ...//</span><span class="w"></span>
-<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">initialize</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">on_start</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">on_load</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">on_finish</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">awesome</span><span class="o">:</span><span class="w"> </span><span class="nx">params</span><span class="p">.</span><span class="nx">value</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">//... experiment code ...//</span>
+<span class="kd">let</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;You&#39;re awesome!&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">myAwesomeExtension</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">demo</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;value&#39;</span><span class="p">}}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">awesome</span><span class="p">);</span><span class="w"> </span><span class="c1">// will output &#39;value&#39;.</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
+
+<span class="c1">//... extension code ...//</span>
+<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span>
+
+<span class="w">  </span><span class="nx">initialize</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span>
+
+<span class="w">  </span><span class="nx">on_start</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span>
+
+<span class="w">  </span><span class="nx">on_load</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">}</span>
+
+<span class="w">  </span><span class="nx">on_finish</span><span class="p">(</span><span class="nx">params</span><span class="p">){</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">awesome</span><span class="o">:</span><span class="w"> </span><span class="nx">params</span><span class="p">.</span><span class="nx">value</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="static-info">static .info<a class="headerlink" href="#static-info" title="Permanent link">&para;</a></h3>
 <p>The <code>info</code> property for the class must contain an object with a <code>name</code> property that has a unique name for the extension.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomeExtension</span><span class="w"> </span><span class="p">{</span>
 
-<span class="p">}</span><span class="w"></span>
+<span class="p">}</span>
 
-<span class="nx">MyAwesomeExtension</span><span class="p">.</span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;awesome&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="nx">MyAwesomeExtension</span><span class="p">.</span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;awesome&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="optional-methods">Optional methods<a class="headerlink" href="#optional-methods" title="Permanent link">&para;</a></h3>
 <p>The extension can also include any additional methods that are necessary for interacting with it. See the <a href="../../extensions/webgazer/">webgazer extension</a> for an example.</p>
@@ -2223,16 +2228,25 @@ <h2 id="advice-for-writing-extensions">Advice for writing extensions<a class="he
 <p>If you are developing an extension with the aim of including it in the main jsPsych repository we encourage you to follow the <a href="../contributing/#contributing-to-the-codebase">contribution guidelines</a>. </p>
 <p>In general, extensions should be able to work with any plugin. They should make very few assumptions about what the DOM will contain beyond the container elements generated by jsPsych. If you are making an extension targeted at one or a small number of specific plugins, consider modifying the plugin code instead.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../plugin-development/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Plugin Development" rel="prev">
@@ -2291,7 +2305,7 @@ <h2 id="advice-for-writing-extensions">Advice for writing extensions<a class="he
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2300,7 +2314,7 @@ <h2 id="advice-for-writing-extensions">Advice for writing extensions<a class="he
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2313,11 +2327,13 @@ <h2 id="advice-for-writing-extensions">Advice for writing extensions<a class="he
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/developers/plugin-development/index.html b/7.3/developers/plugin-development/index.html
old mode 100755
new mode 100644
index aaedc360be..7fd3dbea47
--- a/7.3/developers/plugin-development/index.html
+++ b/7.3/developers/plugin-development/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/developers/plugin-development/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2133,16 +2136,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/developers/plugin-development.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="plugin-development">Plugin development<a class="headerlink" href="#plugin-development" title="Permanent link">&para;</a></h1>
 <h2 id="requirements-for-a-plugin">Requirements for a plugin<a class="headerlink" href="#requirements-for-a-plugin" title="Permanent link">&para;</a></h2>
 <p>As of version 7.0, plugins are <a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Classes">JavaScript Classes</a>. A plugin must implement:</p>
@@ -2156,9 +2161,9 @@ <h3 id="templates">Templates<a class="headerlink" href="#templates" title="Perma
 <h2 id="plugin-components">Plugin components<a class="headerlink" href="#plugin-components" title="Permanent link">&para;</a></h2>
 <h3 id="constructor">constructor()<a class="headerlink" href="#constructor" title="Permanent link">&para;</a></h3>
 <p>The plugin's <code>constructor()</code> will be passed a reference to the instance of the <code>JsPsych</code> class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules.</p>
-<div class="highlight"><pre><span></span><code><span class="kr">constructor</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kr">constructor</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">){</span>
+<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">;</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="trial">trial()<a class="headerlink" href="#trial" title="Permanent link">&para;</a></h3>
 <p>The plugin's <code>trial()</code> method is responsible for running a single trial. When the jsPsych timeline reaches a trial using the plugin it will invoke the <code>trial()</code> method for the plugin.</p>
@@ -2171,140 +2176,140 @@ <h3 id="trial">trial()<a class="headerlink" href="#trial" title="Permanent link"
 <p>The only requirement for the <code>trial</code> method is that it calls <code>jsPsych.finishTrial()</code> when it is done. This is how jsPsych knows to advance to the next trial in the experiment (or end the experiment if it is the last trial). The plugin can do whatever it needs to do before that point.</p>
 <h3 id="static-info">static info<a class="headerlink" href="#static-info" title="Permanent link">&para;</a></h3>
 <p>The plugin's <code>info</code> property is an object with a <code>name</code> and <code>parameters</code> property. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;my-awesome-plugin&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">parameters</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;my-awesome-plugin&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">parameters</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>The <code>parameters</code> property is an object containing all of the parameters for the plugin. Each parameter has a <code>type</code> and <code>default</code> property.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;my-awesome-plugin&#39;</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;my-awesome-plugin&#39;</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">parameters</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span>
-<span class="w">    </span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jspsych</span><span class="p">.</span><span class="nx">ParameterType</span><span class="p">.</span><span class="nx">IMAGE</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="kc">undefined</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">image_duration</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jspsych</span><span class="p">.</span><span class="nx">ParameterType</span><span class="p">.</span><span class="nx">INT</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jspsych</span><span class="p">.</span><span class="nx">ParameterType</span><span class="p">.</span><span class="nx">IMAGE</span><span class="p">,</span>
+<span class="w">      </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="kc">undefined</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">image_duration</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jspsych</span><span class="p">.</span><span class="nx">ParameterType</span><span class="p">.</span><span class="nx">INT</span><span class="p">,</span>
+<span class="w">      </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>If the <code>default</code> value is <code>undefined</code> then a user must specify a value for this parameter when creating a trial using the plugin on the timeline. If they do not, then an error will be generated and shown in the console. If a <code>default</code> value is specified in <code>info</code> then that value will be used by the plugin unless the user overrides it by specifying that property.</p>
 <p>jsPsych allows most <a href="../../overview/dynamic-parameters/">plugin parameters to be dynamic</a>, which means that the parameter value can be a function that will be evaluated right before the trial starts. However, if you want your plugin to have a parameter that is a function that <em>shouldn't</em> be evaluated before the trial starts, then you should make sure that the parameter type is <code>'FUNCTION'</code>. This tells jsPsych not to evaluate the function as it normally does for dynamic parameters. See the <code>canvas-*</code> plugins for examples.</p>
 <p>The <code>info</code> object should be a <code>static</code> member of the class, as shown below.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;my-awesome-plugin&#39;</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;my-awesome-plugin&#39;</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">parameters</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span>
-<span class="w">    </span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jspsych</span><span class="p">.</span><span class="nx">ParameterType</span><span class="p">.</span><span class="nx">IMAGE</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="kc">undefined</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">image_duration</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jspsych</span><span class="p">.</span><span class="nx">ParameterType</span><span class="p">.</span><span class="nx">INT</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomePlugin</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="kr">constructor</span><span class="p">(...)</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">trial</span><span class="p">(...)</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">MyAwesomePlugin</span><span class="p">.</span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">info</span><span class="p">;</span><span class="w"></span>
+<span class="w">    </span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jspsych</span><span class="p">.</span><span class="nx">ParameterType</span><span class="p">.</span><span class="nx">IMAGE</span><span class="p">,</span>
+<span class="w">      </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="kc">undefined</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">image_duration</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jspsych</span><span class="p">.</span><span class="nx">ParameterType</span><span class="p">.</span><span class="nx">INT</span><span class="p">,</span>
+<span class="w">      </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="kd">class</span><span class="w"> </span><span class="nx">MyAwesomePlugin</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="kr">constructor</span><span class="p">(...)</span>
+
+<span class="w">  </span><span class="nx">trial</span><span class="p">(...)</span>
+<span class="p">}</span>
+
+<span class="nx">MyAwesomePlugin</span><span class="p">.</span><span class="nx">info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">info</span><span class="p">;</span>
 </code></pre></div>
 <h2 id="plugin-functionality">Plugin functionality<a class="headerlink" href="#plugin-functionality" title="Permanent link">&para;</a></h2>
 <p>Inside the <code>.trial()</code> method you can do pretty much anything that you want, including modifying the DOM, setting up event listeners, and making asynchronous requests. In this section we'll highlight a few common things that you might want to do as examples.</p>
 <h3 id="changing-the-content-of-the-display">Changing the content of the display<a class="headerlink" href="#changing-the-content-of-the-display" title="Permanent link">&para;</a></h3>
 <p>There are a few ways to change the content of the display. The <code>display_element</code> parameter of the trial method contains the <code>HTMLElement</code> for displaying jsPsych content, so you can use various JavaScript methods for interaction with the display element. A common one is to change the <code>innerHTML</code>. Here's an example of using <code>innerHTML</code> to display an image specified in the <code>trial</code> parameters.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="kd">let</span><span class="w"> </span><span class="nx">html_content</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;</span><span class="si">${</span><span class="nx">trial</span><span class="p">.</span><span class="nx">image</span><span class="si">}</span><span class="sb">&quot;&gt;&lt;/img&gt;`</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">){</span>
+<span class="w">  </span><span class="kd">let</span><span class="w"> </span><span class="nx">html_content</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;</span><span class="si">${</span><span class="nx">trial</span><span class="p">.</span><span class="nx">image</span><span class="si">}</span><span class="sb">&quot;&gt;&lt;/img&gt;`</span><span class="p">;</span>
 
-<span class="w">  </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">html_content</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">  </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">html_content</span><span class="p">;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>jsPsych doesn't clear the display before or after each trial, so it is usually appropriate to use <code>innerHTML</code> to clear the display at the end of a trial.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&#39;</span><span class="p">;</span>
 </code></pre></div>
 <h3 id="waiting-for-specified-durations">Waiting for specified durations<a class="headerlink" href="#waiting-for-specified-durations" title="Permanent link">&para;</a></h3>
 <p>If you need to delay code execution for a fixed amount of time, we recommend using jsPsych's wrapper of the <code>setTimeout()</code> function, <code>jsPsych.pluginAPI.setTimeout()</code>. In <code>7.0</code> the only advantage of using this method is that it registers the timeout handler so that it can be easily cleared at the end of the trial using <code>jsPsych.pluginAPI.clearAllTimeouts()</code>. In future versions we may replace the implementation of <code>jsPsych.pluginAPI.setTimeout()</code> with improved timing functionality based on <code>requestAnimationFrame</code>. </p>
-<div class="highlight"><pre><span></span><code><span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="c1">// show image</span><span class="w"></span>
-<span class="w">  </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;</span><span class="si">${</span><span class="nx">trial</span><span class="p">.</span><span class="nx">image</span><span class="si">}</span><span class="sb">&quot;&gt;&lt;/img&gt;`</span><span class="p">;</span><span class="w"></span>
-
-<span class="w">  </span><span class="c1">// hide image after trial.image_duration milliseconds</span><span class="w"></span>
-<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">setTimeout</span><span class="p">(()=&gt;{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"> </span><span class="nx">trial</span><span class="p">.</span><span class="nx">image_duration</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">){</span>
+<span class="w">  </span><span class="c1">// show image</span>
+<span class="w">  </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;</span><span class="si">${</span><span class="nx">trial</span><span class="p">.</span><span class="nx">image</span><span class="si">}</span><span class="sb">&quot;&gt;&lt;/img&gt;`</span><span class="p">;</span>
+
+<span class="w">  </span><span class="c1">// hide image after trial.image_duration milliseconds</span>
+<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">setTimeout</span><span class="p">(()=&gt;{</span>
+<span class="w">    </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&#39;</span><span class="p">;</span>
+<span class="w">  </span><span class="p">},</span><span class="w"> </span><span class="nx">trial</span><span class="p">.</span><span class="nx">image_duration</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="responding-to-keyboard-events">Responding to keyboard events<a class="headerlink" href="#responding-to-keyboard-events" title="Permanent link">&para;</a></h3>
 <p>While the plugin framework allows you to set up any events that you would like to, including normal handling of <code>keyup</code> or <code>keydown</code> events, the <code>jsPsych.pluginAPI</code> module contains the <a href="../../reference/jspsych-pluginAPI/#jspsychpluginapigetkeyboardresponse"><code>getKeyboardResponse</code> function</a>, which implements some additional helpful functionality for key responses in an experiment.</p>
 <p>Here's a basic example. See the <a href="../../reference/jspsych-pluginAPI/#jspsychpluginapigetkeyboardresponse"><code>getKeyboardResponse</code> docs</a> for additional examples.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="c1">// show image</span><span class="w"></span>
-<span class="w">  </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;</span><span class="si">${</span><span class="nx">trial</span><span class="p">.</span><span class="nx">image</span><span class="si">}</span><span class="sb">&quot;&gt;&lt;/img&gt;`</span><span class="p">;</span><span class="w"></span>
-
-<span class="w">  </span><span class="kd">const</span><span class="w"> </span><span class="nx">after_key_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="nx">info</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// hide the image</span><span class="w"></span>
-<span class="w">    </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&#39;</span><span class="p">;</span><span class="w"></span>
-
-<span class="w">    </span><span class="c1">// record the response time as data</span><span class="w"></span>
-<span class="w">    </span><span class="kd">let</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="nx">info</span><span class="p">.</span><span class="nx">rt</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">    </span><span class="c1">// end the trial</span><span class="w"></span>
-<span class="w">    </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="c1">// set up a keyboard event to respond only to the spacebar</span><span class="w"></span>
-<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">callback_function</span><span class="o">:</span><span class="w"> </span><span class="nx">after_key_response</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">valid_responses</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39; &#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">persist</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="w">  </span><span class="p">});</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">){</span>
+<span class="w">  </span><span class="c1">// show image</span>
+<span class="w">  </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;</span><span class="si">${</span><span class="nx">trial</span><span class="p">.</span><span class="nx">image</span><span class="si">}</span><span class="sb">&quot;&gt;&lt;/img&gt;`</span><span class="p">;</span>
+
+<span class="w">  </span><span class="kd">const</span><span class="w"> </span><span class="nx">after_key_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="nx">info</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="c1">// hide the image</span>
+<span class="w">    </span><span class="nx">display_element</span><span class="p">.</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&#39;</span><span class="p">;</span>
+
+<span class="w">    </span><span class="c1">// record the response time as data</span>
+<span class="w">    </span><span class="kd">let</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="nx">info</span><span class="p">.</span><span class="nx">rt</span>
+<span class="w">    </span><span class="p">}</span>
+
+<span class="w">    </span><span class="c1">// end the trial</span>
+<span class="w">    </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span>
+<span class="w">  </span><span class="p">}</span>
+
+<span class="w">  </span><span class="c1">// set up a keyboard event to respond only to the spacebar</span>
+<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">callback_function</span><span class="o">:</span><span class="w"> </span><span class="nx">after_key_response</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">valid_responses</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39; &#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">persist</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="w">  </span><span class="p">});</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="asynchronous-loading">Asynchronous loading<a class="headerlink" href="#asynchronous-loading" title="Permanent link">&para;</a></h3>
 <p>One of the <a href="../overview/events">trial events</a> is <code>on_load</code>, which is normally triggered automatically when the <code>.trial()</code> method returns. In most cases, this return happens after the plugin has done its initial setup of the DOM (e.g., rendering an image, setting up event listeners and timers, etc.). However, in some cases a plugin may implement an asynchronous operation that needs to complete before the initial loading of the plugin is considered done. An example of this is the <code>audio-keyboard-response</code> plugin, in which the check to see if the audio file is loaded is asynchronous and the <code>.trial()</code> method returns before the audio file has been initialized and the display updated. </p>
 <p>If you would like to manually trigger the <code>on_load</code> event for a plugin, the <code>.trial()</code> method accepts an optional third parameter that is a callback function to invoke when loading is complete. </p>
 <p>In order to tell jsPsych to <em>not</em> invoke the regular callback when the <code>.trial()</code> method returns, you need to explicitly return a <code>Promise</code>. As of version <code>7.0</code> this Promise only serves as a flag to tell jsPsych that the <code>on_load</code> event should not be triggered. In future versions we may make the <code>Promise</code> functional so that the <code>trial</code> operation can be an <code>async</code> function.</p>
 <p>Here's a sketch of how the <code>on_load</code> event can be utilized in a plugin. Note that this example is only a sketch and leaves out all the stuff that happens between loading and finishing the trial. See the source for the <code>audio-keyboard-response</code> plugin for a complete exampe.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span><span class="nx">on_load</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="kd">let</span><span class="w"> </span><span class="nx">trial_complete</span><span class="p">;</span><span class="w"></span>
-
-<span class="w">  </span><span class="nx">do_something_asynchronous</span><span class="p">().</span><span class="nx">then</span><span class="p">(()=&gt;{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_load</span><span class="p">();</span><span class="w"></span>
-<span class="w">  </span><span class="p">});</span><span class="w"></span>
-
-<span class="w">  </span><span class="kd">const</span><span class="w"> </span><span class="nx">end_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">({...})</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial_complete</span><span class="p">();</span><span class="w"> </span><span class="c1">// not strictly necessary, but doesn&#39;t hurt.</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="k">return</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nb">Promise</span><span class="p">((</span><span class="nx">resolve</span><span class="p">)=&gt;{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial_complete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">resolve</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">})</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span><span class="nx">on_load</span><span class="p">){</span>
+<span class="w">  </span><span class="kd">let</span><span class="w"> </span><span class="nx">trial_complete</span><span class="p">;</span>
+
+<span class="w">  </span><span class="nx">do_something_asynchronous</span><span class="p">().</span><span class="nx">then</span><span class="p">(()=&gt;{</span>
+<span class="w">    </span><span class="nx">on_load</span><span class="p">();</span>
+<span class="w">  </span><span class="p">});</span>
+
+<span class="w">  </span><span class="kd">const</span><span class="w"> </span><span class="nx">end_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">({...})</span>
+<span class="w">    </span><span class="nx">trial_complete</span><span class="p">();</span><span class="w"> </span><span class="c1">// not strictly necessary, but doesn&#39;t hurt.</span>
+<span class="w">  </span><span class="p">}</span>
+
+<span class="w">  </span><span class="k">return</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nb">Promise</span><span class="p">((</span><span class="nx">resolve</span><span class="p">)=&gt;{</span>
+<span class="w">    </span><span class="nx">trial_complete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">resolve</span><span class="p">;</span>
+<span class="w">  </span><span class="p">})</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="save-data">Save data<a class="headerlink" href="#save-data" title="Permanent link">&para;</a></h3>
 <p>To write data to <a href="../../reference/jspsych-data/#datacollection">jsPsych's data collection</a> pass an object of data as the parameter to <code>jsPsych.finishTrial()</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kr">constructor</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="kd">let</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">350</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kr">constructor</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">){</span>
+<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">;</span>
+<span class="p">}</span>
+
+<span class="nx">trial</span><span class="p">(</span><span class="nx">display_element</span><span class="p">,</span><span class="w"> </span><span class="nx">trial</span><span class="p">){</span>
+<span class="w">  </span><span class="kd">let</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">350</span>
+<span class="w">  </span><span class="p">}</span>
+
+<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>The data recorded will be that <code>correct</code> is <code>true</code> and that <code>rt</code> is <code>350</code>. <a href="../../overview/plugins/#data-collected-by-all-plugins">Additional data for the trial</a> will also be collected automatically.</p>
 <h2 id="simulation-mode">Simulation mode<a class="headerlink" href="#simulation-mode" title="Permanent link">&para;</a></h2>
@@ -2330,16 +2335,25 @@ <h2 id="advice-for-writing-plugins">Advice for writing plugins<a class="headerli
 <p>If you are developing a plugin with the aim of including it in the main jsPsych repository we encourage you to follow the <a href="../contributing/#contributing-to-the-codebase">contribution guidelines</a>. </p>
 <p>We also recommend that you make your plugin <em>as general as possible</em>. Consider using parameters to give the user of the plugin as many options for customization as possible. For example, if you have any text that displays in the plugin including things like button labels, implement the text as a parameter. This allows users running experiments in other languages to replace text values as needed.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../contributing/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Contributing to jsPsych" rel="prev">
@@ -2398,7 +2412,7 @@ <h2 id="advice-for-writing-plugins">Advice for writing plugins<a class="headerli
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2407,7 +2421,7 @@ <h2 id="advice-for-writing-plugins">Advice for writing plugins<a class="headerli
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2420,11 +2434,13 @@ <h2 id="advice-for-writing-plugins">Advice for writing plugins<a class="headerli
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/extensions/list-of-extensions/index.html b/7.3/extensions/list-of-extensions/index.html
old mode 100755
new mode 100644
index 3ae0cebe29..a87f6573b0
--- a/7.3/extensions/list-of-extensions/index.html
+++ b/7.3/extensions/list-of-extensions/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/extensions/list-of-extensions/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1869,16 +1872,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/extensions/list-of-extensions.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plugins" title="Permanent link">&para;</a></h1>
 <p>These are the extensions that are included in the jsPsych release. </p>
 <p>Additional extensions may be available in the <a href="https://github.com/jspsych/jspsych-contrib">community contributions repository</a>. </p>
@@ -1906,16 +1911,25 @@ <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plu
 </tbody>
 </table>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../../plugins/webgazer-validate/" class="md-footer__link md-footer__link--prev" aria-label="Previous: webgazer-validate" rel="prev">
@@ -1974,7 +1988,7 @@ <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plu
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -1983,7 +1997,7 @@ <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plu
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -1996,11 +2010,13 @@ <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plu
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/extensions/mouse-tracking/index.html b/7.3/extensions/mouse-tracking/index.html
old mode 100755
new mode 100644
index a7a333e582..33db4419c9
--- a/7.3/extensions/mouse-tracking/index.html
+++ b/7.3/extensions/mouse-tracking/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/extensions/mouse-tracking/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1983,16 +1986,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/extensions/mouse-tracking.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="mouse-tracking">mouse-tracking<a class="headerlink" href="#mouse-tracking" title="Permanent link">&para;</a></h1>
 <p>This extension supports mouse tracking. 
 Specifically, it can record the <code>x</code> and <code>y</code> coordinates, along with the time of <a href="https://developer.mozilla.org/en-US/docs/Web/API/Element/mousemove_event">mousemove events</a>, <a href="https://developer.mozilla.org/en-US/docs/Web/API/Element/mousedown_event">mousedown events</a>, and <a href="https://developer.mozilla.org/en-US/docs/Web/API/Element/mouseup_event">mouseup events</a>.
@@ -2000,11 +2005,11 @@ <h1 id="mouse-tracking">mouse-tracking<a class="headerlink" href="#mouse-trackin
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <h3 id="initialization-parameters">Initialization Parameters<a class="headerlink" href="#initialization-parameters" title="Permanent link">&para;</a></h3>
 <p>Initialization parameters can be set when calling <code>initJsPsych()</code></p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionMouseTracking</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionMouseTracking</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">})</span>
 </code></pre></div>
 <table>
 <thead>
@@ -2026,12 +2031,12 @@ <h3 id="initialization-parameters">Initialization Parameters<a class="headerlink
 </table>
 <h3 id="trial-parameters">Trial Parameters<a class="headerlink" href="#trial-parameters" title="Permanent link">&para;</a></h3>
 <p>Trial parameters can be set when adding the extension to a trial object.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">...,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionMouseTracking</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">...,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionMouseTracking</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <table>
 <thead>
@@ -2085,50 +2090,50 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div id=&quot;target&quot; style=&quot;width:250px; height: 250px; background-color: #333; margin: auto;&quot;&gt;&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Done&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Move your mouse around inside the square.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionMouseTracking</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">targets</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;#target&#39;</span><span class="p">]}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;draw&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">replay</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div id=&quot;target&quot; style=&quot;width:250px; height: 250px; background-color: #333; margin: auto; position: relative;&quot;&gt;&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Done&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Here&#39;s the recording of your mouse movements&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_load</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">mouseMovements</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">mouse_tracking_data</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">targetRect</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">mouse_tracking_targets</span><span class="p">[</span><span class="s1">&#39;#target&#39;</span><span class="p">];</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">startTime</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">performance</span><span class="p">.</span><span class="nx">now</span><span class="p">();</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">function</span><span class="w"> </span><span class="nx">draw_frame</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeElapsed</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">performance</span><span class="p">.</span><span class="nx">now</span><span class="p">()</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">startTime</span><span class="p">;</span><span class="w"></span>
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">points</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">mouseMovements</span><span class="p">.</span><span class="nx">filter</span><span class="p">((</span><span class="nx">x</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="nx">x</span><span class="p">.</span><span class="nx">t</span><span class="w"> </span><span class="o">&lt;=</span><span class="w"> </span><span class="nx">timeElapsed</span><span class="p">);</span><span class="w"></span>
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">html</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">``</span><span class="p">;</span><span class="w"></span>
-<span class="w">      </span><span class="k">for</span><span class="p">(</span><span class="kd">var</span><span class="w"> </span><span class="nx">p</span><span class="w"> </span><span class="k">of</span><span class="w"> </span><span class="nx">points</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="nx">html</span><span class="w"> </span><span class="o">+=</span><span class="w"> </span><span class="sb">`&lt;div style=&quot;width: 3px; height: 3px; background-color: blue; position: absolute; top: </span><span class="si">${</span><span class="nx">p</span><span class="p">.</span><span class="nx">y</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">1</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">targetRect</span><span class="p">.</span><span class="nx">top</span><span class="si">}</span><span class="sb">px; left: </span><span class="si">${</span><span class="nx">p</span><span class="p">.</span><span class="nx">x</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">1</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">targetRect</span><span class="p">.</span><span class="nx">left</span><span class="si">}</span><span class="sb">px;&quot;&gt;&lt;/div&gt;`</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">      </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;#target&#39;</span><span class="p">).</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">html</span><span class="p">;</span><span class="w"></span>
-<span class="w">      </span><span class="k">if</span><span class="p">(</span><span class="nx">points</span><span class="p">.</span><span class="nx">length</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="nx">mouseMovements</span><span class="p">.</span><span class="nx">length</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">requestAnimationFrame</span><span class="p">(</span><span class="nx">draw_frame</span><span class="p">);</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">    </span><span class="nx">requestAnimationFrame</span><span class="p">(</span><span class="nx">draw_frame</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;replay&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div id=&quot;target&quot; style=&quot;width:250px; height: 250px; background-color: #333; margin: auto;&quot;&gt;&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Done&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Move your mouse around inside the square.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionMouseTracking</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">targets</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;#target&#39;</span><span class="p">]}}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;draw&#39;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">replay</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div id=&quot;target&quot; style=&quot;width:250px; height: 250px; background-color: #333; margin: auto; position: relative;&quot;&gt;&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Done&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Here&#39;s the recording of your mouse movements&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_load</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">mouseMovements</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">mouse_tracking_data</span><span class="p">;</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">targetRect</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">mouse_tracking_targets</span><span class="p">[</span><span class="s1">&#39;#target&#39;</span><span class="p">];</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">startTime</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">performance</span><span class="p">.</span><span class="nx">now</span><span class="p">();</span>
+
+<span class="w">    </span><span class="kd">function</span><span class="w"> </span><span class="nx">draw_frame</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeElapsed</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">performance</span><span class="p">.</span><span class="nx">now</span><span class="p">()</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">startTime</span><span class="p">;</span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">points</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">mouseMovements</span><span class="p">.</span><span class="nx">filter</span><span class="p">((</span><span class="nx">x</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="nx">x</span><span class="p">.</span><span class="nx">t</span><span class="w"> </span><span class="o">&lt;=</span><span class="w"> </span><span class="nx">timeElapsed</span><span class="p">);</span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">html</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">``</span><span class="p">;</span>
+<span class="w">      </span><span class="k">for</span><span class="p">(</span><span class="kd">var</span><span class="w"> </span><span class="nx">p</span><span class="w"> </span><span class="k">of</span><span class="w"> </span><span class="nx">points</span><span class="p">){</span>
+<span class="w">        </span><span class="nx">html</span><span class="w"> </span><span class="o">+=</span><span class="w"> </span><span class="sb">`&lt;div style=&quot;width: 3px; height: 3px; background-color: blue; position: absolute; top: </span><span class="si">${</span><span class="nx">p</span><span class="p">.</span><span class="nx">y</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">1</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">targetRect</span><span class="p">.</span><span class="nx">top</span><span class="si">}</span><span class="sb">px; left: </span><span class="si">${</span><span class="nx">p</span><span class="p">.</span><span class="nx">x</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">1</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">targetRect</span><span class="p">.</span><span class="nx">left</span><span class="si">}</span><span class="sb">px;&quot;&gt;&lt;/div&gt;`</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">      </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;#target&#39;</span><span class="p">).</span><span class="nx">innerHTML</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">html</span><span class="p">;</span>
+<span class="w">      </span><span class="k">if</span><span class="p">(</span><span class="nx">points</span><span class="p">.</span><span class="nx">length</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="nx">mouseMovements</span><span class="p">.</span><span class="nx">length</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">requestAnimationFrame</span><span class="p">(</span><span class="nx">draw_frame</span><span class="p">);</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">}</span>
+
+<span class="w">    </span><span class="nx">requestAnimationFrame</span><span class="p">(</span><span class="nx">draw_frame</span><span class="p">);</span>
+
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;replay&#39;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2141,16 +2146,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-extension-mouse-tracking-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../list-of-extensions/" class="md-footer__link md-footer__link--prev" aria-label="Previous: List of Extensions" rel="prev">
@@ -2209,7 +2223,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2218,7 +2232,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2231,11 +2245,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/extensions/record-video/index.html b/7.3/extensions/record-video/index.html
old mode 100755
new mode 100644
index cbcc68ef29..4fe4a34c4b
--- a/7.3/extensions/record-video/index.html
+++ b/7.3/extensions/record-video/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/extensions/record-video/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1983,16 +1986,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/extensions/record-video.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="record-video">record-video<a class="headerlink" href="#record-video" title="Permanent link">&para;</a></h1>
 <p>This extension records video from the participant's webcam during a trial. </p>
 <p>This extension encodes the video data in <a href="https://developer.mozilla.org/en-US/docs/Glossary/Base64">base 64 format</a>. 
@@ -2000,11 +2005,11 @@ <h1 id="record-video">record-video<a class="headerlink" href="#record-video" tit
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <h3 id="initialization-parameters">Initialization Parameters<a class="headerlink" href="#initialization-parameters" title="Permanent link">&para;</a></h3>
 <p>Initialization parameters can be set when calling <code>initJsPsych()</code></p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionRecordVideo</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionRecordVideo</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">})</span>
 </code></pre></div>
 <table>
 <thead>
@@ -2026,12 +2031,12 @@ <h3 id="initialization-parameters">Initialization Parameters<a class="headerlink
 </table>
 <h3 id="trial-parameters">Trial Parameters<a class="headerlink" href="#trial-parameters" title="Permanent link">&para;</a></h3>
 <p>Trial parameters can be set when adding the extension to a trial object.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">...,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionRecordVideo</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">...,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionRecordVideo</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <table>
 <thead>
@@ -2074,12 +2079,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span>
+<span class="p">};</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;div id=&quot;target&quot; style=&quot;width:250px; height: 250px; background-color: #333; position: relative; margin: 2em auto;&quot;&gt;</span>
 <span class="sb">      &lt;div class=&quot;orbit&quot; style=&quot;width:25px; height:25px; border-radius:25px;background-color: #f00; position: absolute; top:calc(50% - 12px); left:calc(50% - 12px);&quot;&gt;&lt;/div&gt;</span>
 <span class="sb">    &lt;/div&gt;</span>
@@ -2096,13 +2101,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <span class="sb">          transform: rotate(360deg) translateX(100px);</span>
 <span class="sb">        }</span>
 <span class="sb">      }</span>
-<span class="sb">    &lt;/style&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Done&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Video is recording. Click done after a few seconds.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionRecordVideo</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="sb">    &lt;/style&gt;`</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Done&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Video is recording. Click done after a few seconds.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionRecordVideo</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2115,16 +2120,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-extension-record-video-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../mouse-tracking/" class="md-footer__link md-footer__link--prev" aria-label="Previous: mouse-tracking" rel="prev">
@@ -2183,7 +2197,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2192,7 +2206,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2205,11 +2219,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/extensions/webgazer/index.html b/7.3/extensions/webgazer/index.html
old mode 100755
new mode 100644
index 7412d2a9b9..5fdb71f815
--- a/7.3/extensions/webgazer/index.html
+++ b/7.3/extensions/webgazer/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/extensions/webgazer/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2247,26 +2250,28 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/extensions/webgazer.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="webgazer">webgazer<a class="headerlink" href="#webgazer" title="Permanent link">&para;</a></h1>
 <p>This extension supports eye tracking through the <a href="https://webgazer.cs.brown.edu/">WebGazer</a> library. For a narrative description of how to use this extension see the <a href="../../overview/eye-tracking/">eye tracking overview</a>.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <h3 id="initialization-parameters">Initialization Parameters<a class="headerlink" href="#initialization-parameters" title="Permanent link">&para;</a></h3>
 <p>Initialization parameters can be set when calling <code>initJsPsych()</code></p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">})</span>
 </code></pre></div>
 <table>
 <thead>
@@ -2306,12 +2311,12 @@ <h3 id="initialization-parameters">Initialization Parameters<a class="headerlink
 </table>
 <h3 id="trial-parameters">Trial Parameters<a class="headerlink" href="#trial-parameters" title="Permanent link">&para;</a></h3>
 <p>Trial parameters can be set when adding the extension to a trial object.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">...,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">...,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <table>
 <thead>
@@ -2393,24 +2398,33 @@ <h3 id="stopsampleinterval">stopSampleInterval()<a class="headerlink" href="#sto
 <h3 id="ongazeupdatecallback">onGazeUpdate(callback)<a class="headerlink" href="#ongazeupdatecallback" title="Permanent link">&para;</a></h3>
 <p>Subscribe to gaze updates. The <code>callback</code> will be invoked every time a new gaze prediction is generated. The first argument of the <code>callback</code> will be an object with <code>x</code>, <code>y</code>, and, if currently in a trial with the extension turned on, the time <code>t</code> in ms since the start of the trial. <code>t</code> will be the value of <code>performance.now()</code> at approximately the time that the video frame was recorded. If currently in an active trial then <code>t</code> will be relative to the start of the trial.</p>
 <p>This function returns a close handler. When you no longer need to subscribe to gaze updates, call the close handler. Example:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">cancelGazeUpdateHandler</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">extensions</span><span class="p">.</span><span class="nx">webgazer</span><span class="p">.</span><span class="nx">onGazeUpdate</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">prediction</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="sb">`Currently looking at </span><span class="si">${</span><span class="nx">prediction</span><span class="p">.</span><span class="nx">x</span><span class="si">}</span><span class="sb">, </span><span class="si">${</span><span class="nx">prediction</span><span class="p">.</span><span class="nx">y</span><span class="si">}</span><span class="sb">`</span><span class="p">);</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">cancelGazeUpdateHandler</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">extensions</span><span class="p">.</span><span class="nx">webgazer</span><span class="p">.</span><span class="nx">onGazeUpdate</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">prediction</span><span class="p">){</span>
+<span class="w">  </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="sb">`Currently looking at </span><span class="si">${</span><span class="nx">prediction</span><span class="p">.</span><span class="nx">x</span><span class="si">}</span><span class="sb">, </span><span class="si">${</span><span class="nx">prediction</span><span class="p">.</span><span class="nx">y</span><span class="si">}</span><span class="sb">`</span><span class="p">);</span>
+<span class="p">});</span>
 
-<span class="nx">cancelGazeUpdateHandler</span><span class="p">();</span><span class="w"></span>
+<span class="nx">cancelGazeUpdateHandler</span><span class="p">();</span>
 </code></pre></div>
 <p>You can add multiple handlers. Handlers are not closed automatically, so be sure to cancel them when no longer needed.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../record-video/" class="md-footer__link md-footer__link--prev" aria-label="Previous: record-video" rel="prev">
@@ -2469,7 +2483,7 @@ <h3 id="ongazeupdatecallback">onGazeUpdate(callback)<a class="headerlink" href="
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2478,7 +2492,7 @@ <h3 id="ongazeupdatecallback">onGazeUpdate(callback)<a class="headerlink" href="
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2491,11 +2505,13 @@ <h3 id="ongazeupdatecallback">onGazeUpdate(callback)<a class="headerlink" href="
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/img/blue.png b/7.3/img/blue.png
old mode 100755
new mode 100644
diff --git a/7.3/img/devtools-change-css.png b/7.3/img/devtools-change-css.png
old mode 100755
new mode 100644
diff --git a/7.3/img/devtools-css-errors.png b/7.3/img/devtools-css-errors.png
old mode 100755
new mode 100644
diff --git a/7.3/img/devtools-inspect-element.png b/7.3/img/devtools-inspect-element.png
old mode 100755
new mode 100644
diff --git a/7.3/img/folder-setup.png b/7.3/img/folder-setup.png
old mode 100755
new mode 100644
diff --git a/7.3/img/folder-with-html.png b/7.3/img/folder-with-html.png
old mode 100755
new mode 100644
diff --git a/7.3/img/githubreleases.jpg b/7.3/img/githubreleases.jpg
old mode 100755
new mode 100644
diff --git a/7.3/img/jspsych-favicon.png b/7.3/img/jspsych-favicon.png
old mode 100755
new mode 100644
diff --git a/7.3/img/jspsych-logo-no-text-mono.svg b/7.3/img/jspsych-logo-no-text-mono.svg
old mode 100755
new mode 100644
index af6ba1694a..a9308a90df
--- a/7.3/img/jspsych-logo-no-text-mono.svg
+++ b/7.3/img/jspsych-logo-no-text-mono.svg
@@ -1,493 +1,493 @@
-<?xml version="1.0" encoding="UTF-8" standalone="no"?>
-<!-- Created with Inkscape (http://www.inkscape.org/) -->
-
-<svg
-   xmlns:dc="http://purl.org/dc/elements/1.1/"
-   xmlns:cc="http://creativecommons.org/ns#"
-   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
-   xmlns:svg="http://www.w3.org/2000/svg"
-   xmlns="http://www.w3.org/2000/svg"
-   xmlns:sodipodi="http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd"
-   xmlns:inkscape="http://www.inkscape.org/namespaces/inkscape"
-   version="1.1"
-   id="svg3680"
-   xml:space="preserve"
-   width="340.36853"
-   height="226.6216"
-   viewBox="0 0 340.36853 226.6216"
-   sodipodi:docname="jspsych-logo-no-text-mono.svg"
-   inkscape:version="0.92.1 r15371"
-   inkscape:export-filename="C:\Users\Josh\Dropbox\jsPsych\jspsych-logo-no-text.png"
-   inkscape:export-xdpi="131.34"
-   inkscape:export-ydpi="131.34"><metadata
-     id="metadata3686"><rdf:RDF><cc:Work
-         rdf:about=""><dc:format>image/svg+xml</dc:format><dc:type
-           rdf:resource="http://purl.org/dc/dcmitype/StillImage" /><dc:title></dc:title></cc:Work></rdf:RDF></metadata><defs
-     id="defs3684"><clipPath
-       clipPathUnits="userSpaceOnUse"
-       id="clipPath3700"><path
-         d="M 0,271 H 474 V 0 H 0 Z"
-         id="path3698"
-         inkscape:connector-curvature="0" /></clipPath></defs><sodipodi:namedview
-     pagecolor="#ffffff"
-     bordercolor="#666666"
-     borderopacity="1"
-     objecttolerance="10"
-     gridtolerance="10"
-     guidetolerance="10"
-     inkscape:pageopacity="0"
-     inkscape:pageshadow="2"
-     inkscape:window-width="1920"
-     inkscape:window-height="1001"
-     id="namedview3682"
-     showgrid="false"
-     inkscape:zoom="2.2693726"
-     inkscape:cx="121.59559"
-     inkscape:cy="115.60594"
-     inkscape:window-x="2391"
-     inkscape:window-y="-9"
-     inkscape:window-maximized="1"
-     inkscape:current-layer="g3694"
-     fit-margin-top="24"
-     fit-margin-left="24"
-     fit-margin-right="24"
-     fit-margin-bottom="24" /><g
-     id="g3688"
-     inkscape:groupmode="layer"
-     inkscape:label="jspsych-logo"
-     transform="matrix(1.3333333,0,0,-1.3333333,-156.1236,344.56039)"><g
-       id="g3694"><g
-         transform="translate(270.4785,165.3169)"
-         id="g3702"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3704"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-7.729 -6.267,-13.997 -14,-13.997 -7.732,0 -14.001,6.268 -14.001,13.997 0,7.733 6.269,14.002 14.001,14.002 C -6.267,14.002 0,7.733 0,0" /></g><g
-         transform="translate(217.541,123.3291)"
-         id="g3706"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3708"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-7.729 -6.267,-13.994 -14,-13.994 -7.732,0 -14.001,6.265 -14.001,13.994 0,7.725 6.269,13.991 14.001,13.991 C -6.267,13.991 0,7.725 0,0" /></g><g
-         transform="translate(293.4795,138.3164)"
-         id="g3710"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3712"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-7.725 -6.267,-13.982 -14,-13.982 -7.732,0 -14.001,6.257 -14.001,13.982 0,7.734 6.269,14.003 14.001,14.003 C -6.267,14.003 0,7.734 0,0" /></g><g
-         transform="translate(262.4873,130.3223)"
-         id="g3714"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3716"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.85 -4.752,-10.603 -10.614,-10.603 -5.858,0 -10.609,4.753 -10.609,10.603 0,5.859 4.751,10.611 10.609,10.611 C -4.752,10.611 0,5.859 0,0" /></g><g
-         transform="translate(303.7871,162.2817)"
-         id="g3718"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3720"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.616 10.614,10.616 C -4.752,10.616 0,5.863 0,0" /></g><g
-         transform="translate(212.1562,147.3887)"
-         id="g3722"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3724"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(240.0127,132.0249)"
-         id="g3726"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3728"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.489 -2.834,-6.321 -6.332,-6.321 -3.498,0 -6.334,2.832 -6.334,6.321 0,3.497 2.836,6.333 6.334,6.333 C -2.834,6.333 0,3.497 0,0" /></g><g
-         transform="translate(306.4268,144.3188)"
-         id="g3730"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3732"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(228.6377,112.7861)"
-         id="g3734"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3736"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.836,-6.332 -6.334,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.498 2.835,6.334 6.333,6.334 C -2.836,6.334 0,3.498 0,0" /></g><g
-         transform="translate(228.2354,124.5215)"
-         id="g3738"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3740"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.101 -1.706,-3.806 -3.809,-3.806 -2.103,0 -3.808,1.705 -3.808,3.806 0,2.101 1.705,3.805 3.808,3.805 C -1.706,3.805 0,2.101 0,0" /></g><g
-         transform="translate(278.2354,156.7061)"
-         id="g3742"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3744"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.104 -1.706,-3.809 -3.809,-3.809 -2.103,0 -3.808,1.705 -3.808,3.809 0,2.103 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.103 0,0" /></g><g
-         transform="translate(239.9023,164.7754)"
-         id="g3746"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3748"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.104,0 -3.809,1.705 -3.809,3.808 0,2.104 1.705,3.809 3.809,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
-         transform="translate(238.5674,111.8584)"
-         id="g3750"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3752"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.104 -1.705,-3.809 -3.809,-3.809 -2.103,0 -3.807,1.705 -3.807,3.809 0,2.104 1.704,3.809 3.807,3.809 C -1.705,3.809 0,2.104 0,0" /></g><g
-         transform="translate(319.5498,159.0034)"
-         id="g3754"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3756"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.104 -1.706,-3.809 -3.809,-3.809 -2.103,0 -3.807,1.705 -3.807,3.809 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(265.0596,144.313)"
-         id="g3758"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3760"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
-         transform="translate(220.2705,138.8965)"
-         id="g3762"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3764"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
-         transform="translate(281.3672,167.6523)"
-         id="g3766"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3768"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(252.2354,146.7056)"
-         id="g3774"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3776"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(311.2354,153.7056)"
-         id="g3778"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3780"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(237.958,151.3179)"
-         id="g3782"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3784"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.858 -4.752,-10.612 -10.614,-10.612 -5.858,0 -10.609,4.754 -10.609,10.612 0,5.863 4.751,10.616 10.609,10.616 C -4.752,10.616 0,5.863 0,0" /></g><g
-         transform="translate(180.4268,145.812)"
-         id="g3786"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3788"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.497 -2.835,-6.333 -6.333,-6.333 -3.498,0 -6.333,2.836 -6.333,6.333 0,3.498 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.498 0,0" /></g><g
-         transform="translate(219.0283,174.7998)"
-         id="g3790"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3792"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-7.729 -6.268,-13.996 -14,-13.996 -7.732,0 -14.002,6.267 -14.002,13.996 0,7.734 6.27,14.003 14.002,14.003 C -6.268,14.003 0,7.734 0,0" /></g><g
-         transform="translate(163.0937,180.9414)"
-         id="g3794"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3796"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-7.729 -6.267,-13.996 -14,-13.996 -7.732,0 -14.001,6.267 -14.001,13.996 0,7.734 6.269,14.003 14.001,14.003 C -6.267,14.003 0,7.734 0,0" /></g><g
-         transform="translate(219.7939,213.999)"
-         id="g3798"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3800"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-7.729 -6.267,-13.996 -14,-13.996 -7.732,0 -14.001,6.267 -14.001,13.996 0,7.734 6.269,14.003 14.001,14.003 C -6.267,14.003 0,7.734 0,0" /></g><g
-         transform="translate(247.3955,222.7163)"
-         id="g3802"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3804"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.613,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
-         transform="translate(181.041,164.7744)"
-         id="g3806"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3808"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
-         transform="translate(176.708,207.5557)"
-         id="g3810"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3812"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.615,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
-         transform="translate(157.4795,150.1606)"
-         id="g3814"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3816"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.613,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
-         transform="translate(182.041,185.3882)"
-         id="g3818"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3820"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(194.584,157.9946)"
-         id="g3822"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3824"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(191.041,222.7173)"
-         id="g3826"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3828"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(204.1084,193.9229)"
-         id="g3830"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3832"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(223.834,235.9478)"
-         id="g3834"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3836"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(255.8447,236.6113)"
-         id="g3838"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3840"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(155.9014,131.3208)"
-         id="g3842"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3844"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.099 -1.705,-3.801 -3.809,-3.801 -2.103,0 -3.807,1.702 -3.807,3.801 0,2.102 1.704,3.807 3.807,3.807 C -1.705,3.807 0,2.102 0,0" /></g><g
-         transform="translate(186.377,128.5161)"
-         id="g3846"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3848"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.099 -1.706,-3.801 -3.809,-3.801 -2.103,0 -3.807,1.702 -3.807,3.801 0,2.101 1.704,3.805 3.807,3.805 C -1.706,3.805 0,2.101 0,0" /></g><g
-         transform="translate(233.0928,205.7705)"
-         id="g3850"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3852"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(196.6279,145.7632)"
-         id="g3854"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3856"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
-         transform="translate(192.041,203.7705)"
-         id="g3858"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3860"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(172.4272,131.3208)"
-         id="g3862"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3864"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.491 -2.835,-6.323 -6.333,-6.323 -3.498,0 -6.334,2.832 -6.334,6.323 0,3.496 2.836,6.332 6.334,6.332 C -2.835,6.332 0,3.496 0,0" /></g><g
-         transform="translate(327.8945,176.7759)"
-         id="g3866"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3868"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.836,-6.332 -6.334,-6.332 -3.497,0 -6.333,2.836 -6.333,6.332 0,3.499 2.836,6.334 6.333,6.334 C -2.836,6.334 0,3.499 0,0" /></g><g
-         transform="translate(328.3701,134.2197)"
-         id="g3870"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3872"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.101 -1.707,-3.804 -3.809,-3.804 -2.103,0 -3.808,1.703 -3.808,3.804 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
-         transform="translate(313.3701,134.3184)"
-         id="g3874"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3876"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.1 -1.706,-3.803 -3.809,-3.803 -2.103,0 -3.808,1.703 -3.808,3.803 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(354.3691,155.9951)"
-         id="g3878"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3880"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(341.9834,185.561)"
-         id="g3882"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3884"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
-         transform="translate(349.3154,141.6274)"
-         id="g3886"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3888"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.834,-6.332 -6.332,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.834,6.334 0,3.499 0,0" /></g><g
-         transform="translate(350.1221,169.8418)"
-         id="g3890"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3892"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
-         transform="translate(334.8945,148.9609)"
-         id="g3894"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3896"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(328.3691,162.8115)"
-         id="g3898"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3900"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(319.5498,144.3193)"
-         id="g3902"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3904"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(270.0937,203.9995)"
-         id="g3906"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3908"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-7.729 -6.267,-13.996 -14,-13.996 -7.732,0 -14.001,6.267 -14.001,13.996 0,7.734 6.269,14.003 14.001,14.003 C -6.267,14.003 0,7.734 0,0" /></g><g
-         transform="translate(306.5967,189)"
-         id="g3910"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3912"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-7.729 -6.268,-13.996 -14,-13.996 -7.732,0 -14.002,6.267 -14.002,13.996 0,7.734 6.27,14.003 14.002,14.003 C -6.268,14.003 0,7.734 0,0" /></g><g
-         transform="translate(246.707,184.3882)"
-         id="g3914"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3916"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
-         transform="translate(293.1729,226.0005)"
-         id="g3918"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3920"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
-         transform="translate(332.7881,195.3877)"
-         id="g3922"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3924"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
-         transform="translate(274.4238,183.7744)"
-         id="g3926"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3928"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(284.0801,207.1611)"
-         id="g3930"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3932"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(312.9336,207.5562)"
-         id="g3934"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3936"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
-         transform="translate(312.3691,172.9443)"
-         id="g3938"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3940"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(306.7861,223.8062)"
-         id="g3942"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3944"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(271.0937,234.9478)"
-         id="g3946"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3948"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
-           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
-         transform="translate(268.8672,222.7178)"
-         id="g3950"
-         style="fill:#ffffff;fill-opacity:1"><path
-           inkscape:connector-curvature="0"
-           id="path3952"
-           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<!-- Created with Inkscape (http://www.inkscape.org/) -->
+
+<svg
+   xmlns:dc="http://purl.org/dc/elements/1.1/"
+   xmlns:cc="http://creativecommons.org/ns#"
+   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
+   xmlns:svg="http://www.w3.org/2000/svg"
+   xmlns="http://www.w3.org/2000/svg"
+   xmlns:sodipodi="http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd"
+   xmlns:inkscape="http://www.inkscape.org/namespaces/inkscape"
+   version="1.1"
+   id="svg3680"
+   xml:space="preserve"
+   width="340.36853"
+   height="226.6216"
+   viewBox="0 0 340.36853 226.6216"
+   sodipodi:docname="jspsych-logo-no-text-mono.svg"
+   inkscape:version="0.92.1 r15371"
+   inkscape:export-filename="C:\Users\Josh\Dropbox\jsPsych\jspsych-logo-no-text.png"
+   inkscape:export-xdpi="131.34"
+   inkscape:export-ydpi="131.34"><metadata
+     id="metadata3686"><rdf:RDF><cc:Work
+         rdf:about=""><dc:format>image/svg+xml</dc:format><dc:type
+           rdf:resource="http://purl.org/dc/dcmitype/StillImage" /><dc:title></dc:title></cc:Work></rdf:RDF></metadata><defs
+     id="defs3684"><clipPath
+       clipPathUnits="userSpaceOnUse"
+       id="clipPath3700"><path
+         d="M 0,271 H 474 V 0 H 0 Z"
+         id="path3698"
+         inkscape:connector-curvature="0" /></clipPath></defs><sodipodi:namedview
+     pagecolor="#ffffff"
+     bordercolor="#666666"
+     borderopacity="1"
+     objecttolerance="10"
+     gridtolerance="10"
+     guidetolerance="10"
+     inkscape:pageopacity="0"
+     inkscape:pageshadow="2"
+     inkscape:window-width="1920"
+     inkscape:window-height="1001"
+     id="namedview3682"
+     showgrid="false"
+     inkscape:zoom="2.2693726"
+     inkscape:cx="121.59559"
+     inkscape:cy="115.60594"
+     inkscape:window-x="2391"
+     inkscape:window-y="-9"
+     inkscape:window-maximized="1"
+     inkscape:current-layer="g3694"
+     fit-margin-top="24"
+     fit-margin-left="24"
+     fit-margin-right="24"
+     fit-margin-bottom="24" /><g
+     id="g3688"
+     inkscape:groupmode="layer"
+     inkscape:label="jspsych-logo"
+     transform="matrix(1.3333333,0,0,-1.3333333,-156.1236,344.56039)"><g
+       id="g3694"><g
+         transform="translate(270.4785,165.3169)"
+         id="g3702"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3704"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-7.729 -6.267,-13.997 -14,-13.997 -7.732,0 -14.001,6.268 -14.001,13.997 0,7.733 6.269,14.002 14.001,14.002 C -6.267,14.002 0,7.733 0,0" /></g><g
+         transform="translate(217.541,123.3291)"
+         id="g3706"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3708"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-7.729 -6.267,-13.994 -14,-13.994 -7.732,0 -14.001,6.265 -14.001,13.994 0,7.725 6.269,13.991 14.001,13.991 C -6.267,13.991 0,7.725 0,0" /></g><g
+         transform="translate(293.4795,138.3164)"
+         id="g3710"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3712"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-7.725 -6.267,-13.982 -14,-13.982 -7.732,0 -14.001,6.257 -14.001,13.982 0,7.734 6.269,14.003 14.001,14.003 C -6.267,14.003 0,7.734 0,0" /></g><g
+         transform="translate(262.4873,130.3223)"
+         id="g3714"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3716"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.85 -4.752,-10.603 -10.614,-10.603 -5.858,0 -10.609,4.753 -10.609,10.603 0,5.859 4.751,10.611 10.609,10.611 C -4.752,10.611 0,5.859 0,0" /></g><g
+         transform="translate(303.7871,162.2817)"
+         id="g3718"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3720"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.616 10.614,10.616 C -4.752,10.616 0,5.863 0,0" /></g><g
+         transform="translate(212.1562,147.3887)"
+         id="g3722"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3724"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(240.0127,132.0249)"
+         id="g3726"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3728"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.489 -2.834,-6.321 -6.332,-6.321 -3.498,0 -6.334,2.832 -6.334,6.321 0,3.497 2.836,6.333 6.334,6.333 C -2.834,6.333 0,3.497 0,0" /></g><g
+         transform="translate(306.4268,144.3188)"
+         id="g3730"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3732"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(228.6377,112.7861)"
+         id="g3734"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3736"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.836,-6.332 -6.334,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.498 2.835,6.334 6.333,6.334 C -2.836,6.334 0,3.498 0,0" /></g><g
+         transform="translate(228.2354,124.5215)"
+         id="g3738"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3740"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.101 -1.706,-3.806 -3.809,-3.806 -2.103,0 -3.808,1.705 -3.808,3.806 0,2.101 1.705,3.805 3.808,3.805 C -1.706,3.805 0,2.101 0,0" /></g><g
+         transform="translate(278.2354,156.7061)"
+         id="g3742"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3744"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.104 -1.706,-3.809 -3.809,-3.809 -2.103,0 -3.808,1.705 -3.808,3.809 0,2.103 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.103 0,0" /></g><g
+         transform="translate(239.9023,164.7754)"
+         id="g3746"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3748"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.104,0 -3.809,1.705 -3.809,3.808 0,2.104 1.705,3.809 3.809,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
+         transform="translate(238.5674,111.8584)"
+         id="g3750"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3752"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.104 -1.705,-3.809 -3.809,-3.809 -2.103,0 -3.807,1.705 -3.807,3.809 0,2.104 1.704,3.809 3.807,3.809 C -1.705,3.809 0,2.104 0,0" /></g><g
+         transform="translate(319.5498,159.0034)"
+         id="g3754"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3756"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.104 -1.706,-3.809 -3.809,-3.809 -2.103,0 -3.807,1.705 -3.807,3.809 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(265.0596,144.313)"
+         id="g3758"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3760"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
+         transform="translate(220.2705,138.8965)"
+         id="g3762"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3764"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
+         transform="translate(281.3672,167.6523)"
+         id="g3766"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3768"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(252.2354,146.7056)"
+         id="g3774"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3776"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(311.2354,153.7056)"
+         id="g3778"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3780"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(237.958,151.3179)"
+         id="g3782"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3784"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.858 -4.752,-10.612 -10.614,-10.612 -5.858,0 -10.609,4.754 -10.609,10.612 0,5.863 4.751,10.616 10.609,10.616 C -4.752,10.616 0,5.863 0,0" /></g><g
+         transform="translate(180.4268,145.812)"
+         id="g3786"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3788"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.497 -2.835,-6.333 -6.333,-6.333 -3.498,0 -6.333,2.836 -6.333,6.333 0,3.498 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.498 0,0" /></g><g
+         transform="translate(219.0283,174.7998)"
+         id="g3790"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3792"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-7.729 -6.268,-13.996 -14,-13.996 -7.732,0 -14.002,6.267 -14.002,13.996 0,7.734 6.27,14.003 14.002,14.003 C -6.268,14.003 0,7.734 0,0" /></g><g
+         transform="translate(163.0937,180.9414)"
+         id="g3794"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3796"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-7.729 -6.267,-13.996 -14,-13.996 -7.732,0 -14.001,6.267 -14.001,13.996 0,7.734 6.269,14.003 14.001,14.003 C -6.267,14.003 0,7.734 0,0" /></g><g
+         transform="translate(219.7939,213.999)"
+         id="g3798"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3800"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-7.729 -6.267,-13.996 -14,-13.996 -7.732,0 -14.001,6.267 -14.001,13.996 0,7.734 6.269,14.003 14.001,14.003 C -6.267,14.003 0,7.734 0,0" /></g><g
+         transform="translate(247.3955,222.7163)"
+         id="g3802"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3804"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.613,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
+         transform="translate(181.041,164.7744)"
+         id="g3806"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3808"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
+         transform="translate(176.708,207.5557)"
+         id="g3810"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3812"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.615,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
+         transform="translate(157.4795,150.1606)"
+         id="g3814"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3816"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.613,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
+         transform="translate(182.041,185.3882)"
+         id="g3818"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3820"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(194.584,157.9946)"
+         id="g3822"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3824"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(191.041,222.7173)"
+         id="g3826"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3828"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(204.1084,193.9229)"
+         id="g3830"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3832"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(223.834,235.9478)"
+         id="g3834"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3836"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(255.8447,236.6113)"
+         id="g3838"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3840"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(155.9014,131.3208)"
+         id="g3842"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3844"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.099 -1.705,-3.801 -3.809,-3.801 -2.103,0 -3.807,1.702 -3.807,3.801 0,2.102 1.704,3.807 3.807,3.807 C -1.705,3.807 0,2.102 0,0" /></g><g
+         transform="translate(186.377,128.5161)"
+         id="g3846"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3848"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.099 -1.706,-3.801 -3.809,-3.801 -2.103,0 -3.807,1.702 -3.807,3.801 0,2.101 1.704,3.805 3.807,3.805 C -1.706,3.805 0,2.101 0,0" /></g><g
+         transform="translate(233.0928,205.7705)"
+         id="g3850"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3852"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(196.6279,145.7632)"
+         id="g3854"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3856"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
+         transform="translate(192.041,203.7705)"
+         id="g3858"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3860"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(172.4272,131.3208)"
+         id="g3862"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3864"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.491 -2.835,-6.323 -6.333,-6.323 -3.498,0 -6.334,2.832 -6.334,6.323 0,3.496 2.836,6.332 6.334,6.332 C -2.835,6.332 0,3.496 0,0" /></g><g
+         transform="translate(327.8945,176.7759)"
+         id="g3866"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3868"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.836,-6.332 -6.334,-6.332 -3.497,0 -6.333,2.836 -6.333,6.332 0,3.499 2.836,6.334 6.333,6.334 C -2.836,6.334 0,3.499 0,0" /></g><g
+         transform="translate(328.3701,134.2197)"
+         id="g3870"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3872"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.101 -1.707,-3.804 -3.809,-3.804 -2.103,0 -3.808,1.703 -3.808,3.804 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
+         transform="translate(313.3701,134.3184)"
+         id="g3874"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3876"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.1 -1.706,-3.803 -3.809,-3.803 -2.103,0 -3.808,1.703 -3.808,3.803 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(354.3691,155.9951)"
+         id="g3878"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3880"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(341.9834,185.561)"
+         id="g3882"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3884"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.707,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.707,3.809 0,2.104 0,0" /></g><g
+         transform="translate(349.3154,141.6274)"
+         id="g3886"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3888"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.834,-6.332 -6.332,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.834,6.334 0,3.499 0,0" /></g><g
+         transform="translate(350.1221,169.8418)"
+         id="g3890"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3892"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
+         transform="translate(334.8945,148.9609)"
+         id="g3894"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3896"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(328.3691,162.8115)"
+         id="g3898"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3900"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(319.5498,144.3193)"
+         id="g3902"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3904"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(270.0937,203.9995)"
+         id="g3906"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3908"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-7.729 -6.267,-13.996 -14,-13.996 -7.732,0 -14.001,6.267 -14.001,13.996 0,7.734 6.269,14.003 14.001,14.003 C -6.267,14.003 0,7.734 0,0" /></g><g
+         transform="translate(306.5967,189)"
+         id="g3910"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3912"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-7.729 -6.268,-13.996 -14,-13.996 -7.732,0 -14.002,6.267 -14.002,13.996 0,7.734 6.27,14.003 14.002,14.003 C -6.268,14.003 0,7.734 0,0" /></g><g
+         transform="translate(246.707,184.3882)"
+         id="g3914"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3916"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
+         transform="translate(293.1729,226.0005)"
+         id="g3918"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3920"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
+         transform="translate(332.7881,195.3877)"
+         id="g3922"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3924"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-5.859 -4.752,-10.611 -10.614,-10.611 -5.862,0 -10.614,4.752 -10.614,10.611 0,5.863 4.752,10.615 10.614,10.615 C -4.752,10.615 0,5.863 0,0" /></g><g
+         transform="translate(274.4238,183.7744)"
+         id="g3926"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3928"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(284.0801,207.1611)"
+         id="g3930"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3932"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.333,2.836 -6.333,6.332 0,3.499 2.835,6.334 6.333,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(312.9336,207.5562)"
+         id="g3934"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3936"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-3.496 -2.835,-6.332 -6.333,-6.332 -3.498,0 -6.334,2.836 -6.334,6.332 0,3.499 2.836,6.334 6.334,6.334 C -2.835,6.334 0,3.499 0,0" /></g><g
+         transform="translate(312.3691,172.9443)"
+         id="g3938"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3940"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(306.7861,223.8062)"
+         id="g3942"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3944"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.808,1.705 -3.808,3.808 0,2.104 1.705,3.809 3.808,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(271.0937,234.9478)"
+         id="g3946"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3948"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
+           d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g><g
+         transform="translate(268.8672,222.7178)"
+         id="g3950"
+         style="fill:#ffffff;fill-opacity:1"><path
+           inkscape:connector-curvature="0"
+           id="path3952"
+           style="fill:#ffffff;fill-opacity:1;fill-rule:nonzero;stroke:none"
            d="m 0,0 c 0,-2.103 -1.706,-3.808 -3.809,-3.808 -2.103,0 -3.807,1.705 -3.807,3.808 0,2.104 1.704,3.809 3.807,3.809 C -1.706,3.809 0,2.104 0,0" /></g></g></g></svg>
\ No newline at end of file
diff --git a/7.3/img/jspsych-logo.jpg b/7.3/img/jspsych-logo.jpg
old mode 100755
new mode 100644
diff --git a/7.3/img/orange.png b/7.3/img/orange.png
old mode 100755
new mode 100644
diff --git a/7.3/img/palmer_stim.png b/7.3/img/palmer_stim.png
old mode 100755
new mode 100644
diff --git a/7.3/img/progress_bar.png b/7.3/img/progress_bar.png
old mode 100755
new mode 100644
diff --git a/7.3/img/prolific-study-completion.png b/7.3/img/prolific-study-completion.png
old mode 100755
new mode 100644
diff --git a/7.3/img/prolific-study-link.png b/7.3/img/prolific-study-link.png
old mode 100755
new mode 100644
diff --git a/7.3/img/visual_search_example.jpg b/7.3/img/visual_search_example.jpg
old mode 100755
new mode 100644
diff --git a/7.3/index.html b/7.3/index.html
old mode 100755
new mode 100644
index 7e569b2e7a..a90e9292b2
--- a/7.3/index.html
+++ b/7.3/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/">
       
       <link rel="icon" href="img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL(".",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL(".",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1867,16 +1870,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/index.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="_1"><a class="headerlink" href="#_1" title="Permanent link">&para;</a></h1>
 <p><img alt="jsPsych" src="img/jspsych-logo.jpg" /></p>
 <p>jsPsych is a JavaScript framework for creating behavioral experiments that run in a web browser. </p>
@@ -1887,16 +1892,25 @@ <h1 id="_1"><a class="headerlink" href="#_1" title="Permanent link">&para;</a></
 <p><a href="overview/timeline/">The page on timelines</a> is a good place to start learning about jsPsych. 
 From there, you might want to complete the <a href="tutorials/hello-world/">hello world tutorial</a> to learn how to set up a jsPsych experiment and the <a href="tutorials/rt-task/">reaction time experiment tutorial</a> to learn the core features of the framework.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
       
         
@@ -1940,7 +1954,7 @@ <h1 id="_1"><a class="headerlink" href="#_1" title="Permanent link">&para;</a></
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -1949,7 +1963,7 @@ <h1 id="_1"><a class="headerlink" href="#_1" title="Permanent link">&para;</a></
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -1962,11 +1976,13 @@ <h1 id="_1"><a class="headerlink" href="#_1" title="Permanent link">&para;</a></
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": ".", "features": [], "search": "assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": ".", "features": [], "search": "assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/browser-device-support/index.html b/7.3/overview/browser-device-support/index.html
old mode 100755
new mode 100644
index 4736d7dc43..ff6a74a35e
--- a/7.3/overview/browser-device-support/index.html
+++ b/7.3/overview/browser-device-support/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/browser-device-support/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1943,16 +1946,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/browser-device-support.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="browser-and-device-support">Browser and Device Support<a class="headerlink" href="#browser-and-device-support" title="Permanent link">&para;</a></h1>
 <h2 id="desktop-and-laptop-browsers">Desktop and Laptop Browsers<a class="headerlink" href="#desktop-and-laptop-browsers" title="Permanent link">&para;</a></h2>
 <p><strong>Supported</strong></p>
@@ -1978,16 +1983,25 @@ <h2 id="mobile-devices">Mobile Devices<a class="headerlink" href="#mobile-device
 <h2 id="mobile-browsers">Mobile Browsers<a class="headerlink" href="#mobile-browsers" title="Permanent link">&para;</a></h2>
 <p>The browser options for mobile phones and tablets are slightly different than those for desktop and laptop computers. In addition to mobile versions of Chrome, Firefox, Safari, and Edge, other notable mobile browsers include Opera Mobile, Samsung Internet, UC Browser, and Dolphin. Because of the greater diversity of mobile browsers and volatility in their usage statistics, jsPsych does not officially support any particular set of mobile browsers. However, we do anticipate that most experiments should work in most mobile browsers, especially the mobile versions of browsers that we do support in Desktop mode. If you run into a problem using jsPsych in mobile browsers, please report it on the <a href="https://github.com/jspsych/jsPsych/issues">jsPsych GitHub Issues page</a>! We do our best to fix browser incompatibilities that are not specific to a single experiment.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../mturk/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Integrating with Mechanical Turk" rel="prev">
@@ -2046,7 +2060,7 @@ <h2 id="mobile-browsers">Mobile Browsers<a class="headerlink" href="#mobile-brow
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2055,7 +2069,7 @@ <h2 id="mobile-browsers">Mobile Browsers<a class="headerlink" href="#mobile-brow
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2068,11 +2082,13 @@ <h2 id="mobile-browsers">Mobile Browsers<a class="headerlink" href="#mobile-brow
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/data/index.html b/7.3/overview/data/index.html
old mode 100755
new mode 100644
index 0a20c76558..64aa4cf1df
--- a/7.3/overview/data/index.html
+++ b/7.3/overview/data/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/data/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2005,16 +2008,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/data.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
   <h1>Data Storage, Aggregation, and Manipulation</h1>
 
 <h2 id="data-in-jspsych-permanent-and-non-permanent-data">Data in jsPsych: permanent and non-permanent data.<a class="headerlink" href="#data-in-jspsych-permanent-and-non-permanent-data" title="Permanent link">&para;</a></h2>
@@ -2025,92 +2030,92 @@ <h2 id="storing-data-in-jspsychs-data-structure">Storing data in jsPsych's data
 <p>In most cases, data collection will be automatic and hidden. Plugins save data on their own so it is not uncommon to have the only interaction with the data be at the end of the experiment when it is time to save it in a permanent manner (see sections below about how to do this). However, there are some situations in which you may want to interact with the data; in particular, you may want to store additional data that the plugins are not recording, like a subject identifier or condition assignment. You may also want to add data on a trial by trial basis. For example, in a Stroop paradigm you would want to label which trials are congruent and which are incongruent. These scenarios are explored below.</p>
 <h3 id="adding-data-to-all-trials">Adding data to all trials<a class="headerlink" href="#adding-data-to-all-trials" title="Permanent link">&para;</a></h3>
 <p>Often it is useful to add a piece of data to <em>all</em> of the trials in the experiment. For example, appending the subject ID to each trial. This can be done  with the <code>jsPsych.data.addProperties()</code> function. Here is an example:</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// generate a random subject ID with 15 characters</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">subject_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomID</span><span class="p">(</span><span class="mf">15</span><span class="p">);</span><span class="w"></span>
-
-<span class="c1">// pick a random condition for the subject at the start of the experiment</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">condition_assignment</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="s1">&#39;conditionA&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;conditionB&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;conditionC&#39;</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-
-<span class="c1">// record the condition assignment in the jsPsych data</span><span class="w"></span>
-<span class="c1">// this adds a property called &#39;subject&#39; and a property called &#39;condition&#39; to every trial</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">subject</span><span class="o">:</span><span class="w"> </span><span class="nx">subject_id</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="nx">condition_assignment</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// generate a random subject ID with 15 characters</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">subject_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomID</span><span class="p">(</span><span class="mf">15</span><span class="p">);</span>
+
+<span class="c1">// pick a random condition for the subject at the start of the experiment</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">condition_assignment</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="s1">&#39;conditionA&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;conditionB&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;conditionC&#39;</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+
+<span class="c1">// record the condition assignment in the jsPsych data</span>
+<span class="c1">// this adds a property called &#39;subject&#39; and a property called &#39;condition&#39; to every trial</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">subject</span><span class="o">:</span><span class="w"> </span><span class="nx">subject_id</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="nx">condition_assignment</span>
+<span class="p">});</span>
 </code></pre></div>
 <h3 id="adding-data-to-a-particular-trial-or-set-of-trials">Adding data to a particular trial or set of trials<a class="headerlink" href="#adding-data-to-a-particular-trial-or-set-of-trials" title="Permanent link">&para;</a></h3>
 <p>Data can be added to a particular trial by setting the <code>data</code> parameter for the trial. The <code>data</code> parameter is an object of key-value pairs, and each pair is added to the data for that trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">image_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;A&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.jpg&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">image_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;A&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>Data declared in this way is also saved in the trials on any nested timelines:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">image_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;A&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA1.jpg&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA2.jpg&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">image_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;A&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA1.jpg&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA2.jpg&#39;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>The data object for a trial can also be updated in the <code>on_finish</code> event handler. You can override properties or add new ones. This is particularly useful for cases where the value depends on something that happened during the trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">)){</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.jpg&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">)){</span>
+<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="aggregating-and-manipulating-jspsych-data">Aggregating and manipulating jsPsych data<a class="headerlink" href="#aggregating-and-manipulating-jspsych-data" title="Permanent link">&para;</a></h2>
 <p>When accessing the data with <code>jsPsych.data.get()</code> the returned object is a special data collection object that exposes a number of methods for aggregating and manipulating the data. The full list of methods is detailed in the <a href="../../reference/jspsych-data/">data module documentation</a>.</p>
 <p>Here are some examples of data collection manipulation.</p>
 <p>All data generated by the image-keyboard-response plugin:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">trial_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image-keyboard-response&#39;</span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">trial_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image-keyboard-response&#39;</span><span class="p">});</span>
 </code></pre></div></p>
 <p>All data generated by the categorize-image plugin with a correct response:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">trial_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;categorize-image&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">trial_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;categorize-image&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span>
 </code></pre></div></p>
 <p>All data with a response time between 100 and 500ms:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filterCustom</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">){</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&gt;=</span><span class="w"> </span><span class="mf">100</span><span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="nx">x</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&lt;=</span><span class="mf">500</span><span class="w"> </span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filterCustom</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">){</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&gt;=</span><span class="w"> </span><span class="mf">100</span><span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="nx">x</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&lt;=</span><span class="mf">500</span><span class="w"> </span><span class="p">});</span>
 </code></pre></div></p>
 <p>Applying filters consecutively to get all trials from a particular plugin with a response time above 100ms:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">trial_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image-keyboard-response&#39;</span><span class="p">}).</span><span class="nx">filterCustom</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">){</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&gt;</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span><span class="w"> </span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">trial_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image-keyboard-response&#39;</span><span class="p">}).</span><span class="nx">filterCustom</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">){</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&gt;</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span><span class="w"> </span><span class="p">});</span>
 </code></pre></div></p>
 <p>Getting the data from the last n trials:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">n</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">3</span><span class="p">;</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="nx">n</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">n</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">3</span><span class="p">;</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="nx">n</span><span class="p">);</span>
 </code></pre></div></p>
 <p>Getting the data from the last n trials with a correct response:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">n</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">3</span><span class="p">;</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">}).</span><span class="nx">last</span><span class="p">(</span><span class="nx">n</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">n</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">3</span><span class="p">;</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">}).</span><span class="nx">last</span><span class="p">(</span><span class="nx">n</span><span class="p">);</span>
 </code></pre></div></p>
 <p>Getting the data from the first n trials:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">n</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">3</span><span class="p">;</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="nx">n</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">n</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">3</span><span class="p">;</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="nx">n</span><span class="p">);</span>
 </code></pre></div></p>
 <p>Counting the number of trials with a correct response in a data collection:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">count</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">}).</span><span class="nx">count</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">count</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">}).</span><span class="nx">count</span><span class="p">();</span>
 </code></pre></div></p>
 <p>Selecting all of the response times from a data collection:
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">response_times</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">response_times</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">);</span>
 </code></pre></div></p>
 <p>Calculating various descriptive statistics on the response times in a data collection:</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">mean</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">sum</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">min</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">max</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">variance</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">sd</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">median</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">count</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">mean</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">sum</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">min</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">max</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">variance</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">sd</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">median</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">count</span><span class="p">();</span>
 </code></pre></div>
 <h2 id="storing-data-permanently-as-a-file">Storing data permanently as a file<a class="headerlink" href="#storing-data-permanently-as-a-file" title="Permanent link">&para;</a></h2>
 <p>This is one of the simplest methods for saving jsPsych data on the server that is running the experiment. It involves a short PHP script and a few lines of JavaScript code. This method will save each participant's data as a CSV file on the server. <strong>This method will only work if you are running on a web server with PHP installed, or a local server with PHP (e.g., <a href="https://www.apachefriends.org/index.html">XAMPP</a>).</strong></p>
@@ -2125,21 +2130,21 @@ <h2 id="storing-data-permanently-as-a-file">Storing data permanently as a file<a
 <span class="nv">$name</span> <span class="o">=</span> <span class="s2">&quot;data/</span><span class="si">{</span><span class="nv">$file</span><span class="si">}</span><span class="s2">.csv&quot;</span><span class="p">;</span> 
 <span class="c1">// write the file to disk</span>
 <span class="nb">file_put_contents</span><span class="p">(</span><span class="nv">$name</span><span class="p">,</span> <span class="nv">$data</span><span class="p">);</span>
-<span class="cp">?&gt;</span><span class="x"></span>
+<span class="cp">?&gt;</span>
 </code></pre></div>
 <p>The <code>file_put_contents($name, $data)</code> method requires permission to write new files. An easy way to solve this is to create a directory on the server that will store the data and use the chmod command to give all users write permission to that directory. In the above example, the directory <code>data/</code> is used to store files.</p>
 <p>To use the PHP script, the JavaScript that runs jsPsych needs to send the <code>filedata</code> information. This is done through an <a href="http://www.w3schools.com/xml/ajax_intro.asp">AJAX</a> call.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">saveData</span><span class="p">(</span><span class="nx">name</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">xhr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nx">XMLHttpRequest</span><span class="p">();</span><span class="w"></span>
-<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">open</span><span class="p">(</span><span class="s1">&#39;POST&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;write_data.php&#39;</span><span class="p">);</span><span class="w"> </span><span class="c1">// &#39;write_data.php&#39; is the path to the php file described above.</span><span class="w"></span>
-<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">setRequestHeader</span><span class="p">(</span><span class="s1">&#39;Content-Type&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;application/json&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">send</span><span class="p">(</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">({</span><span class="nx">filedata</span><span class="o">:</span><span class="w"> </span><span class="nx">data</span><span class="p">}));</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// call the saveData function after the experiment is over</span><span class="w"></span>
-<span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">   </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">saveData</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">csv</span><span class="p">());</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">saveData</span><span class="p">(</span><span class="nx">name</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">){</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">xhr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nx">XMLHttpRequest</span><span class="p">();</span>
+<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">open</span><span class="p">(</span><span class="s1">&#39;POST&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;write_data.php&#39;</span><span class="p">);</span><span class="w"> </span><span class="c1">// &#39;write_data.php&#39; is the path to the php file described above.</span>
+<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">setRequestHeader</span><span class="p">(</span><span class="s1">&#39;Content-Type&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;application/json&#39;</span><span class="p">);</span>
+<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">send</span><span class="p">(</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">({</span><span class="nx">filedata</span><span class="o">:</span><span class="w"> </span><span class="nx">data</span><span class="p">}));</span>
+<span class="p">}</span>
+
+<span class="c1">// call the saveData function after the experiment is over</span>
+<span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">   </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">saveData</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">csv</span><span class="p">());</span><span class="w"> </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 <div class="admonition danger">
 <p class="admonition-title">Danger</p>
@@ -2159,7 +2164,7 @@ <h2 id="storing-data-permanently-in-a-mysql-database">Storing data permanently i
   <span class="nv">$password</span> <span class="o">=</span> <span class="s2">&quot;password&quot;</span><span class="p">;</span>
   <span class="nv">$dbname</span> <span class="o">=</span> <span class="s2">&quot;database&quot;</span><span class="p">;</span>
   <span class="nv">$table</span> <span class="o">=</span> <span class="s2">&quot;tablename&quot;</span><span class="p">;</span>
-<span class="cp">?&gt;</span><span class="x"></span>
+<span class="cp">?&gt;</span>
 </code></pre></div>
 <p>The second PHP file will write data to the database. This script reads the database to discover what columns are in the table, and then only allows data to be entered in that matches those columns. This is a security feature. Save this file as <code>write_data.php</code> on your server.</p>
 <div class="highlight"><pre><span></span><code><span class="cp">&lt;?php</span>
@@ -2209,52 +2214,61 @@ <h2 id="storing-data-permanently-in-a-mysql-database">Storing data permanently i
   <span class="k">echo</span> <span class="s1">&#39;{&quot;success&quot;: false, &quot;message&quot;: &#39;</span> <span class="o">.</span> <span class="nv">$e</span><span class="o">-&gt;</span><span class="na">getMessage</span><span class="p">();</span>
 <span class="p">}</span>
 <span class="nv">$conn</span> <span class="o">=</span> <span class="k">null</span><span class="p">;</span>
-<span class="cp">?&gt;</span><span class="x"></span>
+<span class="cp">?&gt;</span>
 </code></pre></div>
 <p>To send the data, we use an <code>XMLHttpRequest</code> request in JavaScript.
-<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">saveData</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">xhr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nx">XMLHttpRequest</span><span class="p">();</span><span class="w"></span>
-<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">open</span><span class="p">(</span><span class="s1">&#39;POST&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;write_data.php&#39;</span><span class="p">);</span><span class="w"> </span><span class="c1">// change &#39;write_data.php&#39; to point to php script.</span><span class="w"></span>
-<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">setRequestHeader</span><span class="p">(</span><span class="s1">&#39;Content-Type&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;application/json&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">onload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">xhr</span><span class="p">.</span><span class="nx">status</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">200</span><span class="p">){</span><span class="w"></span>
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">JSON</span><span class="p">.</span><span class="nx">parse</span><span class="p">(</span><span class="nx">xhr</span><span class="p">.</span><span class="nx">responseText</span><span class="p">);</span><span class="w"></span>
-<span class="w">      </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">response</span><span class="p">.</span><span class="nx">success</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">};</span><span class="w"></span>
-<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">send</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">());</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">saveData</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">xhr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nx">XMLHttpRequest</span><span class="p">();</span>
+<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">open</span><span class="p">(</span><span class="s1">&#39;POST&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;write_data.php&#39;</span><span class="p">);</span><span class="w"> </span><span class="c1">// change &#39;write_data.php&#39; to point to php script.</span>
+<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">setRequestHeader</span><span class="p">(</span><span class="s1">&#39;Content-Type&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;application/json&#39;</span><span class="p">);</span>
+<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">onload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">xhr</span><span class="p">.</span><span class="nx">status</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">200</span><span class="p">){</span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">JSON</span><span class="p">.</span><span class="nx">parse</span><span class="p">(</span><span class="nx">xhr</span><span class="p">.</span><span class="nx">responseText</span><span class="p">);</span>
+<span class="w">      </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">response</span><span class="p">.</span><span class="nx">success</span><span class="p">);</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">};</span>
+<span class="w">  </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">send</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">());</span>
+<span class="p">}</span>
 </code></pre></div></p>
 <p>It's important that the <code>XMLHttpRequest</code> is able to complete before the experiment is closed. If you invoke the <code>saveData()</code> function at the end of your experiment and the participant closes the window before all of the data has been transferred you will lose that data. To mitigate this risk, you can use the <code>call-function</code> plugin's <code>async</code> option to prevent the experiment from progressing until the request is complete.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="k">async</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">done</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">xhr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nx">XMLHttpRequest</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">open</span><span class="p">(</span><span class="s1">&#39;POST&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;write_data.php&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">setRequestHeader</span><span class="p">(</span><span class="s1">&#39;Content-Type&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;application/json&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">onload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="k">if</span><span class="p">(</span><span class="nx">xhr</span><span class="p">.</span><span class="nx">status</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">200</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">JSON</span><span class="p">.</span><span class="nx">parse</span><span class="p">(</span><span class="nx">xhr</span><span class="p">.</span><span class="nx">responseText</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">response</span><span class="p">.</span><span class="nx">success</span><span class="p">);</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">      </span><span class="nx">done</span><span class="p">();</span><span class="w"> </span><span class="c1">// invoking done() causes experiment to progress to next trial.</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">send</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">());</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span>
+<span class="w">  </span><span class="k">async</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">done</span><span class="p">){</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">xhr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nx">XMLHttpRequest</span><span class="p">();</span>
+<span class="w">    </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">open</span><span class="p">(</span><span class="s1">&#39;POST&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;write_data.php&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">setRequestHeader</span><span class="p">(</span><span class="s1">&#39;Content-Type&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;application/json&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">onload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="k">if</span><span class="p">(</span><span class="nx">xhr</span><span class="p">.</span><span class="nx">status</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">200</span><span class="p">){</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">JSON</span><span class="p">.</span><span class="nx">parse</span><span class="p">(</span><span class="nx">xhr</span><span class="p">.</span><span class="nx">responseText</span><span class="p">);</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">response</span><span class="p">.</span><span class="nx">success</span><span class="p">);</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">      </span><span class="nx">done</span><span class="p">();</span><span class="w"> </span><span class="c1">// invoking done() causes experiment to progress to next trial.</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">xhr</span><span class="p">.</span><span class="nx">send</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">());</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../style/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Controlling Visual Appearance" rel="prev">
@@ -2313,7 +2327,7 @@ <h2 id="storing-data-permanently-in-a-mysql-database">Storing data permanently i
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2322,7 +2336,7 @@ <h2 id="storing-data-permanently-in-a-mysql-database">Storing data permanently i
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2335,11 +2349,13 @@ <h2 id="storing-data-permanently-in-a-mysql-database">Storing data permanently i
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+    
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/dynamic-parameters/index.html b/7.3/overview/dynamic-parameters/index.html
old mode 100755
new mode 100644
index 10b83487ca..4595f11806
--- a/7.3/overview/dynamic-parameters/index.html
+++ b/7.3/overview/dynamic-parameters/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/dynamic-parameters/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1997,160 +2000,171 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/dynamic-parameters.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="dynamic-parameters">Dynamic parameters<a class="headerlink" href="#dynamic-parameters" title="Permanent link">&para;</a></h1>
 <p>Most trial parameters can also be specified as functions. In a typical declaration of a jsPsych trial, parameters are known at the start of the experiment. This makes it impossible to alter the content of the trial based on the outcome of previous trials. However, <strong>when functions are used as the parameter value, the function is evaluated right before the trial starts, and the return value of the function is used as the parameter value for that trial</strong>. This enables dynamic updating of the parameter based on data that a participant has generated or any other information that you do not know in advance.</p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <h3 id="providing-feedback">Providing Feedback<a class="headerlink" href="#providing-feedback" title="Permanent link">&para;</a></h3>
 <p>Here is a sketch of how this functionality could be used to display feedback to a participant in the Flanker Task.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;congruent&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">target_direction</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// Score the keyboard response as correct or incorrect.</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;f&quot;</span><span class="p">)){</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;congruent&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">target_direction</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">    </span><span class="c1">// Score the keyboard response as correct or incorrect.</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;f&quot;</span><span class="p">)){</span>
+<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"> </span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">feedback</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// The feedback stimulus is a dynamic parameter because we can&#39;t know in advance whether</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// the stimulus should be &#39;correct&#39; or &#39;incorrect&#39;.</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// Instead, this function will check the accuracy of the last response and use that information to set</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// the stimulus value on each trial.</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">last_trial_correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">correct</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">last_trial_correct</span><span class="p">){</span><span class="w"></span>
-<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Correct!&lt;/p&gt;&quot;</span><span class="p">;</span><span class="w"> </span><span class="c1">// the parameter value has to be returned from the function</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Wrong.&lt;/p&gt;&quot;</span><span class="p">;</span><span class="w"> </span><span class="c1">// the parameter value has to be returned from the function</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span><span class="nx">feedback</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">feedback</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="c1">// The feedback stimulus is a dynamic parameter because we can&#39;t know in advance whether</span>
+<span class="w">    </span><span class="c1">// the stimulus should be &#39;correct&#39; or &#39;incorrect&#39;.</span>
+<span class="w">    </span><span class="c1">// Instead, this function will check the accuracy of the last response and use that information to set</span>
+<span class="w">    </span><span class="c1">// the stimulus value on each trial.</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">last_trial_correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">correct</span><span class="p">;</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">last_trial_correct</span><span class="p">){</span>
+<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Correct!&lt;/p&gt;&quot;</span><span class="p">;</span><span class="w"> </span><span class="c1">// the parameter value has to be returned from the function</span>
+<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Wrong.&lt;/p&gt;&quot;</span><span class="p">;</span><span class="w"> </span><span class="c1">// the parameter value has to be returned from the function</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span><span class="nx">feedback</span><span class="p">);</span>
 </code></pre></div>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
 <p>When scoring a participant's response, the <code>jsPsych.pluginAPI.compareKeys</code> function is only needed to compare <em>keyboard</em> responses. For other kinds of response types, such as button presses, you can compare the participant's response and correct response values directly, e.g.
-<div class="highlight"><pre><span></span><code><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">0</span><span class="p">)){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">0</span><span class="p">)){</span>
+<span class="w">  </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
 <span class="w">  </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"> </span>
-<span class="p">}</span><span class="w"></span>
+<span class="p">}</span>
 </code></pre></div>
 Or:
-<div class="highlight"><pre><span></span><code><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">;</span>
 </code></pre></div></p>
 </div>
 <h3 id="randomizing-a-parameter-value">Randomizing a parameter value<a class="headerlink" href="#randomizing-a-parameter-value" title="Permanent link">&para;</a></h3>
 <p>Here's an example of using a dynamic parameter to randomize the inter-trial interval (ITI) duration. This time, the dynamic parameter is created using a named function instead of an anonymous function.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">random_duration</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">rand_dur</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">500</span><span class="p">,</span><span class="mf">600</span><span class="p">,</span><span class="mf">700</span><span class="p">,</span><span class="mf">800</span><span class="p">],</span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">rand_dur</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="nx">random_duration</span><span class="w">  </span><span class="c1">// if you use a named function for a dynamic parameter, then just use the function name (without parentheses after it)</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">random_duration</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">rand_dur</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">500</span><span class="p">,</span><span class="mf">600</span><span class="p">,</span><span class="mf">700</span><span class="p">,</span><span class="mf">800</span><span class="p">],</span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">rand_dur</span><span class="p">;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="nx">random_duration</span><span class="w">  </span><span class="c1">// if you use a named function for a dynamic parameter, then just use the function name (without parentheses after it)</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="storing-changing-variables-in-the-data">Storing changing variables in the data<a class="headerlink" href="#storing-changing-variables-in-the-data" title="Permanent link">&para;</a></h3>
 <p>The trial's <code>data</code> parameter can be also function, which is useful for when you want to save information to the data that can change during the experiment. For example, if you have a global variable called <code>current_difficulty</code> that tracks the difficulty level in an adaptive task, you can save the current value of this variable to the trial data like this:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">current_difficulty</span><span class="p">;</span><span class="w"> </span><span class="c1">// value changes during the experiment</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">current_difficulty</span><span class="p">;</span><span class="w"> </span><span class="c1">// value changes during the experiment</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Please enter your response.&quot;</span><span class="p">}]</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Please enter your response.&quot;</span><span class="p">}]</span>
 <span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"> </span>
 <span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="p">{</span><span class="nx">difficulty</span><span class="o">:</span><span class="w"> </span><span class="nx">current_difficulty</span><span class="p">};</span><span class="w"> </span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>It's also possible to use a function for any of the <em>individual properties</em> in the trial's <code>data</code> object, for instance if you want to combine static and dynamic information in the data:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Please enter your response.&quot;</span><span class="p">}]</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Please enter your response.&quot;</span><span class="p">}]</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
 <span class="w">    </span><span class="nx">difficulty</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"> </span>
-<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="nx">current_difficulty</span><span class="p">;</span><span class="w"> </span><span class="c1">// the difficulty value changes during the experiment</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">task_part</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;recall&#39;</span><span class="p">,</span><span class="w"> </span><span class="c1">// this part of the data is always the same</span><span class="w"></span>
-<span class="w">    </span><span class="nx">block_number</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="nx">current_difficulty</span><span class="p">;</span><span class="w"> </span><span class="c1">// the difficulty value changes during the experiment</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">task_part</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;recall&#39;</span><span class="p">,</span><span class="w"> </span><span class="c1">// this part of the data is always the same</span>
+<span class="w">    </span><span class="nx">block_number</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="nested-parameters">Nested Parameters<a class="headerlink" href="#nested-parameters" title="Permanent link">&para;</a></h3>
 <p>Dyanmic parameters work the same way with nested parameters, which are parameters that contain one or more sets of other parameters. For instance, many survey-* plugins have a <code>questions</code> parameter that is a nested parameter: it is an array that contains the parameters for one or more questions on the page. To make the <code>questions</code> parameter dynamic, you can use a function that returns the array with all of the parameters for each question:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">subject_id</span><span class="p">;</span><span class="w"> </span><span class="c1">// value is set during the experiment</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">subject_id</span><span class="p">;</span><span class="w"> </span><span class="c1">// value is set during the experiment</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
 <span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">questions_array</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"> </span>
-<span class="w">        </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Hi &quot;</span><span class="o">+</span><span class="nx">subject_id</span><span class="o">+</span><span class="s2">&quot;! What&#39;s your favorite city?&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fav_city&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;What is your favorite fruit?&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fav_fruit&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">];</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">questions_array</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">        </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Hi &quot;</span><span class="o">+</span><span class="nx">subject_id</span><span class="o">+</span><span class="s2">&quot;! What&#39;s your favorite city?&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fav_city&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;What is your favorite fruit?&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fav_fruit&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">];</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">questions_array</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>You can also use a function for any of the <em>individual parameters</em> inside of a nested parameter.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
 <span class="w">    </span><span class="p">{</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w">  </span>
-<span class="w">        </span><span class="c1">// this question prompt is dynamic - the text that is shown </span><span class="w"></span>
-<span class="w">        </span><span class="c1">// will change based on the participant&#39;s earlier response</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">favorite_city</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">().</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">response</span><span class="p">.</span><span class="nx">fav_city</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">text</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s2">&quot;Earlier you said your favorite city is &quot;</span><span class="o">+</span><span class="nx">favorite_city</span><span class="o">+</span><span class="s2">&quot;. What do you like most about &quot;</span><span class="o">+</span><span class="nx">favorite_city</span><span class="o">+</span><span class="s2">&quot;?&quot;</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">text</span><span class="p">;</span><span class="w"></span>
+<span class="w">        </span><span class="c1">// this question prompt is dynamic - the text that is shown </span>
+<span class="w">        </span><span class="c1">// will change based on the participant&#39;s earlier response</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">favorite_city</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">().</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">response</span><span class="p">.</span><span class="nx">fav_city</span><span class="p">;</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">text</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s2">&quot;Earlier you said your favorite city is &quot;</span><span class="o">+</span><span class="nx">favorite_city</span><span class="o">+</span><span class="s2">&quot;. What do you like most about &quot;</span><span class="o">+</span><span class="nx">favorite_city</span><span class="o">+</span><span class="s2">&quot;?&quot;</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">text</span><span class="p">;</span>
 <span class="w">      </span><span class="p">},</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">rows</span><span class="o">:</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">columns</span><span class="o">:</span><span class="w"> </span><span class="mf">10</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;What is your favorite fruit?&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fav_fruit&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">rows</span><span class="o">:</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">columns</span><span class="o">:</span><span class="w"> </span><span class="mf">10</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;What is your favorite fruit?&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fav_fruit&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="when-dynamic-parameters-cant-be-used">When dynamic parameters can't be used<a class="headerlink" href="#when-dynamic-parameters-cant-be-used" title="Permanent link">&para;</a></h2>
 <p>Note that if the plugin <em>expects</em> the value of a given parameter to be a function, then this function <em>will not</em> be evaluated at the start of the trial. This is because some plugins allow the researcher to specify functions that should be called at some point during the trial. Some examples of this include the <code>stimulus</code> parameter in the canvas-* plugins, the <code>mistake_fn</code> parameter in the cloze plugin, and the <code>stim_function</code> parameter in the reconstruction plugin. If you want to check whether this is the case for a particular plugin and parameter, then the parameter's <code>type</code> in the <code>plugin.info</code> section of the plugin file. If the parameter type is <code>ParameterType.FUNCTION</code>, then this parameter must be a function and it will not be executed before the trial starts. </p>
 <p>Even though function evaluation doesn't work the same way with these parameters, the fact that the parameters are functions means that you can get the same dynamic functionality. These functions are typically evaluated at some point during the trial, so you still get updates to values within the function during the trial.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../extensions/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Extensions" rel="prev">
@@ -2209,7 +2223,7 @@ <h2 id="when-dynamic-parameters-cant-be-used">When dynamic parameters can't be u
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2218,7 +2232,7 @@ <h2 id="when-dynamic-parameters-cant-be-used">When dynamic parameters can't be u
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2231,11 +2245,13 @@ <h2 id="when-dynamic-parameters-cant-be-used">When dynamic parameters can't be u
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/events/index.html b/7.3/overview/events/index.html
old mode 100755
new mode 100644
index ae5687404f..e83c526da6
--- a/7.3/overview/events/index.html
+++ b/7.3/overview/events/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/events/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2041,151 +2044,162 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/events.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="event-related-callback-functions">Event-related callback functions<a class="headerlink" href="#event-related-callback-functions" title="Permanent link">&para;</a></h1>
 <p>jsPsych offers the ability to call arbitrary functions in response to certain events occurring, like the end of a trial or when new data is saved. This page summarizes the different opportunities for callback functions and how to specify them.</p>
 <hr />
 <h2 id="on_close">on_close<a class="headerlink" href="#on_close" title="Permanent link">&para;</a></h2>
 <p>The <code>on_close</code> callback can be declared in the <code>initJsPsych</code> method. The callback triggers when the user leaves the page, but before any content on the page is removed from the browser's memory. This can be used, for example, to save data as the user is leaving the page.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_close</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="nx">save_data_to_server</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_close</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">();</span>
+<span class="w">    </span><span class="nx">save_data_to_server</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 <hr />
 <h2 id="on_data_update">on_data_update<a class="headerlink" href="#on_data_update" title="Permanent link">&para;</a></h2>
 <p>The <code>on_data_update</code> callback can be declared in the <code>initJsPsych</code> method. The callback triggers at the end of a data update cycle. This happens after every trial, after the on_finish (trial) and on_trial_finish events execute, allowing you to modify the data in those callbacks, and then use this callback to store the data. The function will be passed a single argument, which contains the data that was written.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_data_update</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Just added new data. The contents of the data are: &#39;</span><span class="o">+</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">data</span><span class="p">));</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_data_update</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Just added new data. The contents of the data are: &#39;</span><span class="o">+</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">data</span><span class="p">));</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 <hr />
 <h2 id="on_finish-trial">on_finish (trial)<a class="headerlink" href="#on_finish-trial" title="Permanent link">&para;</a></h2>
 <p>The <code>on_finish</code> callback can be added to any trial. The callback will trigger whenever the trial ends. The callback function will be passed a single argument, containing the data object from the trial. This data object is <em>editable</em>. Any changes made in the on_finish function will be stored in the internal data collection.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">)){</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.png&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">)){</span>
+<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <hr />
 <h2 id="on_finish-experiment">on_finish (experiment)<a class="headerlink" href="#on_finish-experiment" title="Permanent link">&para;</a></h2>
 <p>The <code>on_finish</code> callback can be declared in the <code>initJsPsych</code> method. The callback will trigger once all trials in the experiment have been run. The method will be passed a single argument, containing all of the data generated in the experiment.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The experiment is over! Here is all the data: &#39;</span><span class="o">+</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">data</span><span class="p">));</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The experiment is over! Here is all the data: &#39;</span><span class="o">+</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">data</span><span class="p">));</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 <hr />
 <h2 id="on_load">on_load<a class="headerlink" href="#on_load" title="Permanent link">&para;</a></h2>
 <p>The <code>on_load</code> callback can be added to any trial. The callback will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_load</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The trial just finished loading.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.png&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_load</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The trial just finished loading.&#39;</span><span class="p">);</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <hr />
 <h2 id="on_start-trial">on_start (trial)<a class="headerlink" href="#on_start-trial" title="Permanent link">&para;</a></h2>
 <p>The <code>on_start</code> callback can be added to any trial. The callback will trigger right before the trial begins. The callback function will be passed a single argument, containing the trial object. If any of the parameters of the trial are functions or timeline variables, these will be evaluated before <code>on_start</code> is called, and the trial object will contain the evaluated value. The trial object is modifiable, and any changes made will affect the trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The trial is about to start.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">stimulus</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;imgB.png&#39;</span><span class="p">;</span><span class="w"> </span><span class="c1">// this will change what stimulus is displayed in the trial</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.png&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The trial is about to start.&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">stimulus</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;imgB.png&#39;</span><span class="p">;</span><span class="w"> </span><span class="c1">// this will change what stimulus is displayed in the trial</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <hr />
 <h2 id="on_timeline_finish">on_timeline_finish<a class="headerlink" href="#on_timeline_finish" title="Permanent link">&para;</a></h2>
 <p>The <code>on_timeline_finish</code> callback can be declared in a timeline node. The callback will be triggered when the timeline ends during the experiment. If <code>timeline_variables</code>, <code>conditional_function</code>, <code>loop_function</code>, or <code>sample</code> options are used, this function will execute when all trials have finished. If a <code>loop_function</code> is used, then this <code>on_timeline_finish</code> function will be triggered before the loop function. If the <code>repetitions</code> option is used, this function will be triggered at the end of every repetition.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_timeline_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;This timeline has finished.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">loop_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;This loop function will execute after on_timeline_finish.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">  </span><span class="nx">on_timeline_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;This timeline has finished.&#39;</span><span class="p">);</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">loop_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;This loop function will execute after on_timeline_finish.&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="on_timeline_start">on_timeline_start<a class="headerlink" href="#on_timeline_start" title="Permanent link">&para;</a></h2>
 <p>The <code>on_timeline_start</code> callback can be declared in a timeline node. The callback will be triggered when the timeline starts during the experiment, including when <code>timeline_variables</code>, <code>loop_function</code>, or <code>sample</code> options are used. If a <code>conditional_function</code> is used, then the conditional function will execute first, and the <code>on_timeline_start</code> function will only execute if the conditional function returns <code>true</code>. If the <code>repetitions</code> option is used, this function will be triggered at the start of every repetition. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">conditional_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;This conditional function will execute first.&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_timeline_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;This timeline has started&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">conditional_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;This conditional function will execute first.&#39;</span><span class="p">)</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">on_timeline_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;This timeline has started&#39;</span><span class="p">);</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="on_trial_finish">on_trial_finish<a class="headerlink" href="#on_trial_finish" title="Permanent link">&para;</a></h2>
-<p>The <code>on_trial_finish</code> callback can be declared in the <code>initJsPsych</code> method. The callback will trigger at the end of every trial in the experiment. If you want a callback to trigger only for the end of certain trials, use the <a href="#onfinishtrial"><code>on_finish</code></a> callback on the trial object. The callback function will be passed a single argument, containing the data object from the trial.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_trial_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;A trial just ended.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">data</span><span class="p">));</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<p>The <code>on_trial_finish</code> callback can be declared in the <code>initJsPsych</code> method. The callback will trigger at the end of every trial in the experiment, after the trial object's <a href="#onfinishtrial"><code>on_finish</code></a> callback has been run. The callback function will be passed a single argument, containing the data object from the trial. If you want a callback to trigger only for the end of certain trials, use the <a href="#onfinishtrial"><code>on_finish</code></a> callback on the trial object instead.</p>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_trial_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;A trial just ended.&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">data</span><span class="p">));</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 <hr />
 <h2 id="on_trial_start">on_trial_start<a class="headerlink" href="#on_trial_start" title="Permanent link">&para;</a></h2>
-<p>The <code>on_trial_start</code> callback can be declared in the <code>initJsPsych</code> method. The callback will trigger at the start of every trial in the experiment. The function receives a single argument: a modifiable copy of the trial object that will be used to run the next trial. Changes can be made to this object to alter the parameters of the upcoming trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">current_score</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"> </span><span class="c1">// a variable that is updated throughout the experiment to keep track of the current score.</span><span class="w"></span>
-
-<span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_trial_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">score_at_start_of_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">current_score</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;A trial just started.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<p>The <code>on_trial_start</code> callback can be declared in the <code>initJsPsych</code> method. The callback will trigger at the start of every trial in the experiment, before the trial-specific <code>on_start</code> callback is executed. The function receives a single argument: a modifiable copy of the trial object that will be used to run the next trial. Changes can be made to this object to alter the parameters of the upcoming trial.</p>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">current_score</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"> </span><span class="c1">// a variable that is updated throughout the experiment to keep track of the current score.</span>
+
+<span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_trial_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">score_at_start_of_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">current_score</span><span class="p">;</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;A trial just started.&#39;</span><span class="p">);</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../experiment-options/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Experiment Settings" rel="prev">
@@ -2244,7 +2258,7 @@ <h2 id="on_trial_start">on_trial_start<a class="headerlink" href="#on_trial_star
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2253,7 +2267,7 @@ <h2 id="on_trial_start">on_trial_start<a class="headerlink" href="#on_trial_star
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2266,11 +2280,13 @@ <h2 id="on_trial_start">on_trial_start<a class="headerlink" href="#on_trial_star
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/exclude-browser/index.html b/7.3/overview/exclude-browser/index.html
old mode 100755
new mode 100644
index 2f937e58aa..e237ef3528
--- a/7.3/overview/exclude-browser/index.html
+++ b/7.3/overview/exclude-browser/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/exclude-browser/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1869,16 +1872,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/exclude-browser.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="exclude-participants-based-on-browser-features">Exclude Participants Based on Browser Features<a class="headerlink" href="#exclude-participants-based-on-browser-features" title="Permanent link">&para;</a></h1>
 <p><em>Changed in 7.1</em></p>
 <p>Online participants will use many different kinds of browsers. 
@@ -1889,16 +1894,25 @@ <h1 id="exclude-participants-based-on-browser-features">Exclude Participants Bas
 <p>The prior approach of using the <code>exclusions</code> parameter in <code>initJsPsych()</code> is deprecated and will be removed in <code>v8.0</code>. 
 You can find the documentation for it in the <a href="https://www.jspsych.org/7.0/overview/exclude-browser">7.0 docs</a>.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../eye-tracking/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Eye Tracking" rel="prev">
@@ -1957,7 +1971,7 @@ <h1 id="exclude-participants-based-on-browser-features">Exclude Participants Bas
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -1966,7 +1980,7 @@ <h1 id="exclude-participants-based-on-browser-features">Exclude Participants Bas
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -1979,11 +1993,13 @@ <h1 id="exclude-participants-based-on-browser-features">Exclude Participants Bas
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/experiment-options/index.html b/7.3/overview/experiment-options/index.html
old mode 100755
new mode 100644
index 72f1ea1fa2..d455a59237
--- a/7.3/overview/experiment-options/index.html
+++ b/7.3/overview/experiment-options/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/experiment-options/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2055,35 +2058,37 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/experiment-options.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="experiment-wide-settings">Experiment-wide settings<a class="headerlink" href="#experiment-wide-settings" title="Permanent link">&para;</a></h1>
 <p>There are several options that can be set when calling <code>initJsPsych()</code> to initialize the jsPsych experiment.</p>
 <p>Options are specified in the object passed to <code>initJsPsych</code>. For example, to specify a default inter-trial interval, a minimum valid response time duration, and a maximum width for all of the experiment's page content, the object would contain:</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
 <span class="w">    </span><span class="nx">default_iti</span><span class="o">:</span><span class="w"> </span><span class="mf">250</span><span class="p">,</span><span class="w"> </span>
 <span class="w">    </span><span class="nx">minimum_valid_rt</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span><span class="p">,</span><span class="w"> </span>
 <span class="w">    </span><span class="nx">experiment_width</span><span class="o">:</span><span class="w"> </span><span class="mf">800</span><span class="w"> </span>
-<span class="p">});</span><span class="w"></span>
+<span class="p">});</span>
 </code></pre></div>
 <h2 id="controlling-where-jspsych-renders-on-the-page">Controlling where jsPsych renders on the page<a class="headerlink" href="#controlling-where-jspsych-renders-on-the-page" title="Permanent link">&para;</a></h2>
 <p>By default, jsPsych will render the experiment in the <code>&lt;body&gt;</code> element of a page. It is possible to display the experiment in a different element (e.g., a <code>&lt;div&gt;</code>) by specifying the <code>display_element</code> parameter. </p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">div</span> <span class="na">id</span><span class="o">=</span><span class="s">&quot;jspsych-target&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">div</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
+<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
 
-<span class="w">    </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">        </span><span class="nx">display_element</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;jspsych-target&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">});</span><span class="w"></span>
+<span class="w">    </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">        </span><span class="nx">display_element</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;jspsych-target&#39;</span>
+<span class="w">    </span><span class="p">});</span>
 
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2105,68 +2110,77 @@ <h2 id="display-a-progress-bar">Display a progress bar<a class="headerlink" href
 <h2 id="choose-the-method-for-playing-audio-files">Choose the method for playing audio files<a class="headerlink" href="#choose-the-method-for-playing-audio-files" title="Permanent link">&para;</a></h2>
 <p>Specifying the <code>use_webaudio</code> parameter in <code>initJsPsych()</code> allows you to choose whether to use the WebAudio API or HTML5 audio for playing audio files during your experiment. By default, jsPsych uses the WebAudio API to play audio files. Among other features, the WebAudio API allows for more precise measurement of response times relative to the onset of the audio. </p>
 <p>However, loading files through the WebAudio API causes errors when running an experiment offline (i.e., by double-clicking on the HTML file, rather than hosting it on a web server). This is due to the <a href="https://security.stackexchange.com/a/190321">cross-origin security policy</a> implemented by web browsers. For this reason, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline, and automatically uses HTML5 audio to prevent errors, even when <code>use_webaudio</code> has been explicitly set to <code>true</code>. For more information, see the section <a href="../running-experiments/#cross-origin-requests-cors-and-safe-mode">Cross-origin requests (CORS) and safe mode</a> on the Running Experiments page.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">use_webaudio</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">use_webaudio</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="p">});</span>
 </code></pre></div>
 <h2 id="set-the-default-intertrial-interval">Set the default intertrial interval<a class="headerlink" href="#set-the-default-intertrial-interval" title="Permanent link">&para;</a></h2>
 <p>By default the next trial in a timeline will begin immediately after the conclusion of the previous trial. An experiment-wide delay can be specified using the <code>default_iti</code> parameter to <code>initJsPsych()</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">default_iti</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">default_iti</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="p">});</span>
 </code></pre></div>
 <p>This parameter is specified in milliseconds. A blank screen will display between each trial for the duration of the ITI.</p>
 <h2 id="specify-the-maximum-width-of-the-experiment">Specify the maximum width of the experiment<a class="headerlink" href="#specify-the-maximum-width-of-the-experiment" title="Permanent link">&para;</a></h2>
 <p>The experiment will, by default, take up 100% of the display element. Usually the display element is the <code>&lt;body&gt;</code>, and the experiment is the full width of the screen. (This can be overridden by specifying the <code>display_element</code> parameter described above).</p>
 <p>Specifying the <code>experiment_width</code> parameter will set a maximum width for the display. The parameter is specified in pixels.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">experiment_width</span><span class="o">:</span><span class="w"> </span><span class="mf">750</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">experiment_width</span><span class="o">:</span><span class="w"> </span><span class="mf">750</span>
+<span class="p">});</span>
 </code></pre></div>
 <h2 id="specify-a-minimum-valid-response-time">Specify a minimum valid response time<a class="headerlink" href="#specify-a-minimum-valid-response-time" title="Permanent link">&para;</a></h2>
 <p>By default, jsPsych will treat any keyboard response time as valid. However, it's possible to specify a minimum valid response time (in ms) for key presses. Any key press that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to <em>keyboard responses</em>, and not to other response types such as buttons and sliders. The default value is 0.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// ignore any keyboard responses that are less than 100 ms</span><span class="w"></span>
-<span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">minimum_valid_rt</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// ignore any keyboard responses that are less than 100 ms</span>
+<span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">minimum_valid_rt</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span>
+<span class="p">});</span>
 </code></pre></div>
 <h2 id="choose-whether-you-want-keyboard-choicesresponses-to-be-case-sensitive">Choose whether you want keyboard choices/responses to be case-sensitive<a class="headerlink" href="#choose-whether-you-want-keyboard-choicesresponses-to-be-case-sensitive" title="Permanent link">&para;</a></h2>
 <p>JavaScript keyboard events make a distinction between uppercase and lowercase key responses (e.g. 'a' and 'A'). Often the researcher just cares about which physical key was pressed, and not whether the key press would result in an uppercase letter (for instance, if CapsLock is on or if the Shift key is held down). For this reason, jsPsych converts all key choice parameters and key responses as lowercase by default. This makes it easier to specify key choices (e.g. <code>choices: ['a']</code>, instead of <code>choices: ['a','A']</code>), and it makes it easier to check and score a participant's response. </p>
 <p>There may be situations when you want key choices and responses to be case-sensitive. You can change this by setting the <code>case_sensitive_responses</code> parameter to <code>true</code> in <code>initJsPsych</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// use case-sensitive key choices and responses, </span><span class="w"></span>
-<span class="c1">// i.e. uppercase and lower case letters (&#39;a&#39; and &#39;A&#39;) will be treated as different key choices, </span><span class="w"></span>
-<span class="c1">// and will be recorded this way in the data</span><span class="w"></span>
-<span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">case_sensitive_responses</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// use case-sensitive key choices and responses, </span>
+<span class="c1">// i.e. uppercase and lower case letters (&#39;a&#39; and &#39;A&#39;) will be treated as different key choices, </span>
+<span class="c1">// and will be recorded this way in the data</span>
+<span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">case_sensitive_responses</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">});</span>
 </code></pre></div>
 <p>Note that this setting only applies to key choices and responses that use jsPsych's keyboard response listener, such as in the *<code>-keyboard-response</code> plugins. This does NOT apply to responses that are made by typing into a text box, such as in the <code>survey-text</code> and <code>cloze</code> plugins.</p>
 <h2 id="override-safe-mode-when-running-experiments-offline">Override 'safe mode' when running experiments offline<a class="headerlink" href="#override-safe-mode-when-running-experiments-offline" title="Permanent link">&para;</a></h2>
 <p>By default, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline (via the <code>file://</code> protocol) in order to prevent certain errors. Specifically, in safe mode, HTML5 audio is used to play audio files (even when <code>use_webaudio</code> has been explicitly set to <code>true</code>) and video preloading is disabled (both automatic and manual preloading). For more information, see the <a href="../running-experiments/#cross-origin-requests-cors-and-safe-mode">Cross-origin requests (CORS) and safe mode</a> section on the Running Experiments page.</p>
 <p>It's possible to override this safe mode feature by setting the <code>override_safe_mode</code> parameter to <code>true</code> in <code>initJsPsych</code>. This is something you might do if you've disabled certain security settings in your browser for testing purposes. This parameter has no effect when your experiment is running online (on a server), because it will be using the <code>http://</code> or <code>https://</code> protocol, which does not trigger safe mode. </p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">override_safe_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">override_safe_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">});</span>
 </code></pre></div>
 <h2 id="add-extensions">Add extensions<a class="headerlink" href="#add-extensions" title="Permanent link">&para;</a></h2>
 <p><a href="extensions/">Extensions</a> are jsPsych modules that can run throughout the experiment and interface with any plugin to extend the functionality of the plugin. One example of an extension is eye tracking, which allows you to gather gaze data during any trial and add it to that trial's data object. If you want to use extensions in your experiment, you must specify this when you initialize the experiment with <code>initJsPsych</code>. The <code>extensions</code> parameter in <code>initJsPsych</code> is an array of objects, where each object specifies the extension that you'd like to use in the experiment. Below is an example of adding the webgazer extension.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">});</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../running-experiments/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Running Experiments" rel="prev">
@@ -2225,7 +2239,7 @@ <h2 id="add-extensions">Add extensions<a class="headerlink" href="#add-extension
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2234,7 +2248,7 @@ <h2 id="add-extensions">Add extensions<a class="headerlink" href="#add-extension
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2247,11 +2261,13 @@ <h2 id="add-extensions">Add extensions<a class="headerlink" href="#add-extension
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/extensions/index.html b/7.3/overview/extensions/index.html
old mode 100755
new mode 100644
index 7ea078632d..f0e86413be
--- a/7.3/overview/extensions/index.html
+++ b/7.3/overview/extensions/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/extensions/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1943,37 +1946,39 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/extensions.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="extensions">Extensions<a class="headerlink" href="#extensions" title="Permanent link">&para;</a></h1>
 <p>Extensions are jsPsych modules that can interface with any plugin to extend the functionality of the plugin. A canonical example of an extension is eye tracking. An eye tracking extension allows a plugin to gather gaze data and add it to the plugin's data object.</p>
 <h2 id="using-an-extension">Using an Extension<a class="headerlink" href="#using-an-extension" title="Permanent link">&para;</a></h2>
 <p>To use an extension in an experiment, you'll load the extension file via a <code>&lt;script&gt;</code> tag (just like adding a plugin) and then initialize the extension in the parameters of <code>initJsPsych()</code>.</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/extension-example@1.0.0&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionExample</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionExample</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}</span><span class="w"> </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">})</span>
 </code></pre></div>
 <p>To enable an extension during a trial, add the extension to the <code>extensions</code> list for the trial. Some extensions may also support or require an object of parameters to configure the extension:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionExample</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionExample</span><span class="p">,</span><span class="w"> </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{...}</span><span class="w"> </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="list-of-extensions">List of Extensions<a class="headerlink" href="#list-of-extensions" title="Permanent link">&para;</a></h2>
 <table>
@@ -1993,16 +1998,25 @@ <h2 id="list-of-extensions">List of Extensions<a class="headerlink" href="#list-
 <h2 id="writing-an-extension">Writing an Extension<a class="headerlink" href="#writing-an-extension" title="Permanent link">&para;</a></h2>
 <p>See our <a href="../../developers/extension-development/">developer's guide for extensions</a> for information about how to create a new extension.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../plugins/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Plugins" rel="prev">
@@ -2061,7 +2075,7 @@ <h2 id="writing-an-extension">Writing an Extension<a class="headerlink" href="#w
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2070,7 +2084,7 @@ <h2 id="writing-an-extension">Writing an Extension<a class="headerlink" href="#w
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2083,11 +2097,13 @@ <h2 id="writing-an-extension">Writing an Extension<a class="headerlink" href="#w
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/eye-tracking/index.html b/7.3/overview/eye-tracking/index.html
old mode 100755
new mode 100644
index 1f980b1514..2daba14081
--- a/7.3/overview/eye-tracking/index.html
+++ b/7.3/overview/eye-tracking/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/eye-tracking/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2039,16 +2042,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/eye-tracking.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="eye-tracking">Eye Tracking<a class="headerlink" href="#eye-tracking" title="Permanent link">&para;</a></h1>
 <p>jsPsych supports eye tracking through the <a href="https://webgazer.cs.brown.edu/">WebGazer</a> library. WebGazer uses computer vision techniques to identify features of the participant's eyes via a webcam and predicts gaze location. The system is calibrated by having the participant click on or look at known locations on the screen. These locations are linked to eye features. Gaze location is predicted using regression.</p>
 <h2 id="getting-started">Getting Started<a class="headerlink" href="#getting-started" title="Permanent link">&para;</a></h2>
@@ -2058,7 +2063,7 @@ <h3 id="load-webgazerjs">Load webgazer.js<a class="headerlink" href="#load-webga
 However, the <code>webgazer.js</code> file is not part of any of the jsPsych NPM packages and is therefore not available via the unpkg.com CDN. 
 Instead, it can be found on the jsdelivr.net CDN at: "https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js".</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2073,80 +2078,80 @@ <h3 id="load-webgazerjs">Load webgazer.js<a class="headerlink" href="#load-webga
 <h3 id="load-the-jspsych-webgazer-extension">Load the jsPsych webgazer extension<a class="headerlink" href="#load-the-jspsych-webgazer-extension" title="Permanent link">&para;</a></h3>
 <p>The <a href="../../extensions/webgazer/">webgazer extension</a> adds functionality to jsPsych for interacting with webgazer. Load it like you would a plugin file.</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/extension-webgazer@1.0.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/extension-webgazer@1.0.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>To use the WebGazer extension in an experiment, include it in the list of extensions passed to <code>initJsPsych()</code></p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">})</span>
 </code></pre></div>
 <h3 id="initialize-the-camera">Initialize the camera<a class="headerlink" href="#initialize-the-camera" title="Permanent link">&para;</a></h3>
 <p>To help the participant position their face correctly for eye tracking you can use the <a href="../../plugins/webgazer-init-camera/">webgazer-init-camera plugin</a>. This will show the participant what the camera sees, including facial feature landmarks, and prevent the participant from continuing until their face is in good position for eye tracking. This plugin will also trigger the experiment to request permission to access the user's webcam if it hasn't already been granted.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerInitCamera</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerInitCamera</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="calibration">Calibration<a class="headerlink" href="#calibration" title="Permanent link">&para;</a></h3>
 <p>To calibrate WebGazer, you can use the <a href="../../plugins/webgazer-calibrate/">webgazer-calibrate plugin</a>. This plugin allows you to specify a set of points on the screen for calibration and to choose the method for calibrating -- either clicking on each point or simply fixating on each point. The location of calibration points is specified in percentages, e.g., <code>[25,50]</code> will result in a point that is 25% of the width of the screen from the left edge and 50% of the height of the screen from the top edge. Options for controlling other details of the calibration are explained in the <a href="../../plugins/webgazer-calibrate/">documentation for the plugin</a>.</p>
 <p>Note that instructions are not included in the calibration plugin, so you'll likely want to use a different plugin (e.g., <code>html-button-response</code>) to display instructions prior to running the calibration. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">calibration_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerCalibrate</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">calibration_points</span><span class="o">:</span><span class="w"> </span><span class="p">[[</span><span class="mf">25</span><span class="p">,</span><span class="mf">50</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">50</span><span class="p">,</span><span class="mf">50</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">75</span><span class="p">,</span><span class="mf">50</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">50</span><span class="p">,</span><span class="mf">25</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">50</span><span class="p">,</span><span class="mf">75</span><span class="p">]],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">calibration_mode</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;click&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">calibration_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerCalibrate</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">calibration_points</span><span class="o">:</span><span class="w"> </span><span class="p">[[</span><span class="mf">25</span><span class="p">,</span><span class="mf">50</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">50</span><span class="p">,</span><span class="mf">50</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">75</span><span class="p">,</span><span class="mf">50</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">50</span><span class="p">,</span><span class="mf">25</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">50</span><span class="p">,</span><span class="mf">75</span><span class="p">]],</span>
+<span class="w">  </span><span class="nx">calibration_mode</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;click&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="validation">Validation<a class="headerlink" href="#validation" title="Permanent link">&para;</a></h3>
 <p>To measure the accuracy and precision of the calibration, you can use the <a href="../../plugins/webgazer-validate/">webgazer-vaidate plugin</a>. Like the calibration plugin, you can specify a list of points to perform validation on. Here you can specify the points as either percentages or in terms of the distance from the center of the screen in pixels. Which mode you use will probably depend on how you are defining your stimuli throughout the experiment. You can also specify the radius of tolerance around each point, and the plugin will calculate the percentage of measured gaze samples within that radius. This is a potentially useful heuristic for deciding whether or not to calibrate again. Options for controlling other details of the validation are explained in the <a href="../../plugins/webgazer-validate/">documentation for the plugin</a>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">validation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerValidate</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">validation_points</span><span class="o">:</span><span class="w"> </span><span class="p">[[</span><span class="o">-</span><span class="mf">200</span><span class="p">,</span><span class="mf">200</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">200</span><span class="p">,</span><span class="mf">200</span><span class="p">],[</span><span class="o">-</span><span class="mf">200</span><span class="p">,</span><span class="o">-</span><span class="mf">200</span><span class="p">],[</span><span class="mf">200</span><span class="p">,</span><span class="o">-</span><span class="mf">200</span><span class="p">]],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">validation_point_coordinates</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;center-offset-pixels&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">roi_radius</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">validation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerValidate</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">validation_points</span><span class="o">:</span><span class="w"> </span><span class="p">[[</span><span class="o">-</span><span class="mf">200</span><span class="p">,</span><span class="mf">200</span><span class="p">],</span><span class="w"> </span><span class="p">[</span><span class="mf">200</span><span class="p">,</span><span class="mf">200</span><span class="p">],[</span><span class="o">-</span><span class="mf">200</span><span class="p">,</span><span class="o">-</span><span class="mf">200</span><span class="p">],[</span><span class="mf">200</span><span class="p">,</span><span class="o">-</span><span class="mf">200</span><span class="p">]],</span>
+<span class="w">  </span><span class="nx">validation_point_coordinates</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;center-offset-pixels&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">roi_radius</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>The validation procedure stores the raw gaze data for each validation point, the computed average offset from each validation point, the percentage of samples within the <code>roi_radius</code> for each validation point, and the number of samples collected per second.</p>
-<div class="highlight"><pre><span></span><code><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">raw_gaze</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">percent_in_roi</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">average_offset</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">samples_per_sec</span><span class="o">:</span><span class="w"> </span><span class="p">...</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nx">raw_gaze</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">  </span><span class="nx">percent_in_roi</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">  </span><span class="nx">average_offset</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">  </span><span class="nx">samples_per_sec</span><span class="o">:</span><span class="w"> </span><span class="p">...</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>We recommend performing calibration and validation periodically throughout your experiment.</p>
 <h3 id="adding-eye-tracking-to-a-trial">Adding eye tracking to a trial<a class="headerlink" href="#adding-eye-tracking-to-a-trial" title="Permanent link">&para;</a></h3>
 <p>To enable eye tracking for a trial in your experiment, you can simply add the WebGazer extension to the trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;img id=&quot;scene&quot; src=&quot;my-scene.png&quot;&gt;&lt;/img&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;img id=&quot;scene&quot; src=&quot;my-scene.png&quot;&gt;&lt;/img&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">targets</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;#scene&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">        </span><span class="nx">targets</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;#scene&#39;</span><span class="p">]</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>This will turn on WebGazer at the start of the trial. </p>
 <p>The <code>params</code> property in the <code>extensions</code> declaration allows you to pass in a list of <a href="https://www.w3schools.com/cssref/css_selectors.asp">CSS selector strings</a>. The <a href="https://developer.mozilla.org/en-US/docs/Web/API/Element/getBoundingClientRect">bounding rectangle</a> of the DOM element that matches each selector will be recorded in the data for that trial. This allows for easy alignment of the gaze data and objects on the screen.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">webgazer_targets</span><span class="w"> </span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="s1">&#39;selector&#39;</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">height</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">width</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">top</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">left</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">right</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">bottom</span><span class="o">:</span><span class="p">...}</span><span class="w"></span>
-<span class="w">  </span><span class="s1">&#39;selector&#39;</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">height</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">width</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">top</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">left</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">right</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">bottom</span><span class="o">:</span><span class="p">...}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">webgazer_targets</span><span class="w"> </span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="s1">&#39;selector&#39;</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">height</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">width</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">top</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">left</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">right</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">bottom</span><span class="o">:</span><span class="p">...}</span>
+<span class="w">  </span><span class="s1">&#39;selector&#39;</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">height</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">width</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">top</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">left</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">right</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">bottom</span><span class="o">:</span><span class="p">...}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>Gaze data will be added to the trial's data under the property <code>webgazer_data</code>. The gaze data is an array of objects. Each object has an <code>x</code>, a <code>y</code>, and a <code>t</code> property. The <code>x</code> and <code>y</code> properties specify the gaze location in pixels and <code>t</code> specifies the time in milliseconds since the start of the trial. Note that establishing the precision and accuracy of these measurements across the variety of web browsers and systems that your experiment participants might be using is quite difficult. For example, different browsers may cause small systematic shifts in the accuracy of <code>t</code> values. </p>
-<div class="highlight"><pre><span></span><code><span class="nx">webgazer_data</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">t</span><span class="o">:</span><span class="w"> </span><span class="p">...},</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">t</span><span class="o">:</span><span class="w"> </span><span class="p">...},</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">t</span><span class="o">:</span><span class="w"> </span><span class="p">...},</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">t</span><span class="o">:</span><span class="w"> </span><span class="p">...}</span><span class="w"></span>
-<span class="p">]</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">webgazer_data</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">t</span><span class="o">:</span><span class="w"> </span><span class="p">...},</span>
+<span class="w">  </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">t</span><span class="o">:</span><span class="w"> </span><span class="p">...},</span>
+<span class="w">  </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">t</span><span class="o">:</span><span class="w"> </span><span class="p">...},</span>
+<span class="w">  </span><span class="p">{</span><span class="nx">x</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">y</span><span class="o">:</span><span class="w"> </span><span class="p">...,</span><span class="w"> </span><span class="nx">t</span><span class="o">:</span><span class="w"> </span><span class="p">...}</span>
+<span class="p">]</span>
 </code></pre></div>
 <h2 id="tips-for-improving-data-quality">Tips for Improving Data Quality<a class="headerlink" href="#tips-for-improving-data-quality" title="Permanent link">&para;</a></h2>
 <p>These are some anecdotal observations about factors that improve data quality.</p>
@@ -2168,162 +2173,162 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <div class="highlight"><pre><span></span><code><span class="cp">&lt;!DOCTYPE html&gt;</span>
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/extension-webgazer@1.0.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/extension-webgazer@1.0.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">link</span>
       <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span>
-      <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span>
+      <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span>
     <span class="p">/&gt;</span>
-    <span class="p">&lt;</span><span class="nt">style</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">      </span><span class="p">.</span><span class="nc">jspsych-btn</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="k">margin-bottom</span><span class="p">:</span><span class="w"> </span><span class="mi">10</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
+    <span class="p">&lt;</span><span class="nt">style</span><span class="p">&gt;</span>
+<span class="w">      </span><span class="p">.</span><span class="nc">jspsych-btn</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="k">margin-bottom</span><span class="p">:</span><span class="w"> </span><span class="mi">10</span><span class="kt">px</span><span class="p">;</span>
+<span class="w">      </span><span class="p">}</span>
 <span class="w">    </span><span class="p">&lt;/</span><span class="nt">style</span><span class="p">&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
 
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">        </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span><span class="w"></span>
-<span class="w">        </span><span class="p">]</span><span class="w"></span>
-<span class="w">      </span><span class="p">});</span><span class="w"></span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">        </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span>
+<span class="w">        </span><span class="p">]</span>
+<span class="w">      </span><span class="p">});</span>
 
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">]</span>
+<span class="w">      </span><span class="p">}</span>
 
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">camera_instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">camera_instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">          &lt;p&gt;In order to participate you must allow the experiment to use your camera.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;You will be prompted to do this on the next screen.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;If you do not wish to allow use of your camera, you cannot participate in this experiment.&lt;p&gt;</span>
 <span class="sb">          &lt;p&gt;It may take up to 30 seconds for the camera to initialize after you give permission.&lt;/p&gt;</span>
-<span class="sb">        `</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Got it&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
+<span class="sb">        `</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Got it&#39;</span><span class="p">],</span>
+<span class="w">      </span><span class="p">}</span>
 
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerInitCamera</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerInitCamera</span>
+<span class="w">      </span><span class="p">}</span>
 
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">calibration_instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">calibration_instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">          &lt;p&gt;Now you&#39;ll calibrate the eye tracking, so that the software can use the image of your eyes to predict where you are looking.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;You&#39;ll see a series of dots appear on the screen. Look at each dot and click on it.&lt;/p&gt;</span>
-<span class="sb">        `</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Got it&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">calibration</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerCalibrate</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">calibration_points</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">          </span><span class="p">[</span><span class="mf">25</span><span class="p">,</span><span class="mf">25</span><span class="p">],[</span><span class="mf">75</span><span class="p">,</span><span class="mf">25</span><span class="p">],[</span><span class="mf">50</span><span class="p">,</span><span class="mf">50</span><span class="p">],[</span><span class="mf">25</span><span class="p">,</span><span class="mf">75</span><span class="p">],[</span><span class="mf">75</span><span class="p">,</span><span class="mf">75</span><span class="p">]</span><span class="w"></span>
-<span class="w">        </span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">repetitions_per_point</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">randomize_calibration_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">validation_instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<span class="sb">        `</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Got it&#39;</span><span class="p">],</span>
+<span class="w">      </span><span class="p">}</span>
+
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">calibration</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerCalibrate</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">calibration_points</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">          </span><span class="p">[</span><span class="mf">25</span><span class="p">,</span><span class="mf">25</span><span class="p">],[</span><span class="mf">75</span><span class="p">,</span><span class="mf">25</span><span class="p">],[</span><span class="mf">50</span><span class="p">,</span><span class="mf">50</span><span class="p">],[</span><span class="mf">25</span><span class="p">,</span><span class="mf">75</span><span class="p">],[</span><span class="mf">75</span><span class="p">,</span><span class="mf">75</span><span class="p">]</span>
+<span class="w">        </span><span class="p">],</span>
+<span class="w">        </span><span class="nx">repetitions_per_point</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">randomize_calibration_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">      </span><span class="p">}</span>
+
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">validation_instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">          &lt;p&gt;Now we&#39;ll measure the accuracy of the calibration.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;Look at each dot as it appears on the screen.&lt;/p&gt;</span>
 <span class="sb">          &lt;p style=&quot;font-weight: bold;&quot;&gt;You do not need to click on the dots this time.&lt;/p&gt;</span>
-<span class="sb">        `</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Got it&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">validation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerValidate</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">validation_points</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">          </span><span class="p">[</span><span class="mf">25</span><span class="p">,</span><span class="mf">25</span><span class="p">],[</span><span class="mf">75</span><span class="p">,</span><span class="mf">25</span><span class="p">],[</span><span class="mf">50</span><span class="p">,</span><span class="mf">50</span><span class="p">],[</span><span class="mf">25</span><span class="p">,</span><span class="mf">75</span><span class="p">],[</span><span class="mf">75</span><span class="p">,</span><span class="mf">75</span><span class="p">]</span><span class="w"></span>
-<span class="w">        </span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">roi_radius</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">time_to_saccade</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">validation_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">          </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;validate&#39;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">recalibrate_instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<span class="sb">        `</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Got it&#39;</span><span class="p">],</span>
+<span class="w">        </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span>
+<span class="w">      </span><span class="p">}</span>
+
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">validation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychWebgazerValidate</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">validation_points</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">          </span><span class="p">[</span><span class="mf">25</span><span class="p">,</span><span class="mf">25</span><span class="p">],[</span><span class="mf">75</span><span class="p">,</span><span class="mf">25</span><span class="p">],[</span><span class="mf">50</span><span class="p">,</span><span class="mf">50</span><span class="p">],[</span><span class="mf">25</span><span class="p">,</span><span class="mf">75</span><span class="p">],[</span><span class="mf">75</span><span class="p">,</span><span class="mf">75</span><span class="p">]</span>
+<span class="w">        </span><span class="p">],</span>
+<span class="w">        </span><span class="nx">roi_radius</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">time_to_saccade</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">validation_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">          </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;validate&#39;</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">      </span><span class="p">}</span>
+
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">recalibrate_instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">          &lt;p&gt;The accuracy of the calibration is a little lower than we&#39;d like.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;Let&#39;s try calibrating one more time.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;On the next screen, look at the dots and click on them.&lt;p&gt;</span>
-<span class="sb">        `</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;OK&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">recalibrate</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">recalibrate_instructions</span><span class="p">,</span><span class="w"> </span><span class="nx">calibration</span><span class="p">,</span><span class="w"> </span><span class="nx">validation_instructions</span><span class="p">,</span><span class="w"> </span><span class="nx">validation</span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">conditional_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">          </span><span class="kd">var</span><span class="w"> </span><span class="nx">validation_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;validate&#39;</span><span class="p">}).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">          </span><span class="k">return</span><span class="w"> </span><span class="nx">validation_data</span><span class="p">.</span><span class="nx">percent_in_roi</span><span class="p">.</span><span class="nx">some</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">){</span><span class="w"></span>
-<span class="w">            </span><span class="kd">var</span><span class="w"> </span><span class="nx">minimum_percent_acceptable</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">50</span><span class="p">;</span><span class="w"></span>
-<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="nx">minimum_percent_acceptable</span><span class="p">;</span><span class="w"></span>
-<span class="w">          </span><span class="p">});</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">          </span><span class="nx">phase</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;recalibration&#39;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">calibration_done</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<span class="sb">        `</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;OK&#39;</span><span class="p">],</span>
+<span class="w">      </span><span class="p">}</span>
+
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">recalibrate</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">recalibrate_instructions</span><span class="p">,</span><span class="w"> </span><span class="nx">calibration</span><span class="p">,</span><span class="w"> </span><span class="nx">validation_instructions</span><span class="p">,</span><span class="w"> </span><span class="nx">validation</span><span class="p">],</span>
+<span class="w">        </span><span class="nx">conditional_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">          </span><span class="kd">var</span><span class="w"> </span><span class="nx">validation_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;validate&#39;</span><span class="p">}).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">          </span><span class="k">return</span><span class="w"> </span><span class="nx">validation_data</span><span class="p">.</span><span class="nx">percent_in_roi</span><span class="p">.</span><span class="nx">some</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">){</span>
+<span class="w">            </span><span class="kd">var</span><span class="w"> </span><span class="nx">minimum_percent_acceptable</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">50</span><span class="p">;</span>
+<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="nx">minimum_percent_acceptable</span><span class="p">;</span>
+<span class="w">          </span><span class="p">});</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">          </span><span class="nx">phase</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;recalibration&#39;</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">      </span><span class="p">}</span>
+
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">calibration_done</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">          &lt;p&gt;Great, we&#39;re done with calibration!&lt;/p&gt;</span>
-<span class="sb">        `</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;OK&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
+<span class="sb">        `</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;OK&#39;</span><span class="p">]</span>
+<span class="w">      </span><span class="p">}</span>
 
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">begin</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">begin</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;The next screen will show an image to demonstrate adding the webgazer extension to a trial.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;Just look at the image while eye tracking data is collected. The trial will end automatically.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;Press any key to start.&lt;/p&gt;</span>
-<span class="sb">        `</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="w"></span>
+<span class="sb">        `</span>
+<span class="w">      </span><span class="p">}</span>
+
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">          </span><span class="p">{</span>
 <span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">,</span><span class="w"> </span>
-<span class="w">            </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">targets</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;#jspsych-image-keyboard-response-stimulus&#39;</span><span class="p">]}</span><span class="w"></span>
-<span class="w">          </span><span class="p">}</span><span class="w"></span>
-<span class="w">        </span><span class="p">]</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-
-<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">show_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">          </span><span class="kd">var</span><span class="w"> </span><span class="nx">trial_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">().</span><span class="nx">values</span><span class="p">();</span><span class="w"></span>
-<span class="w">          </span><span class="kd">var</span><span class="w"> </span><span class="nx">trial_json</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">trial_data</span><span class="p">,</span><span class="w"> </span><span class="kc">null</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span><span class="w"></span>
+<span class="w">            </span><span class="nx">params</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">targets</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;#jspsych-image-keyboard-response-stimulus&#39;</span><span class="p">]}</span>
+<span class="w">          </span><span class="p">}</span>
+<span class="w">        </span><span class="p">]</span>
+<span class="w">      </span><span class="p">}</span>
+
+<span class="w">      </span><span class="kd">var</span><span class="w"> </span><span class="nx">show_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">          </span><span class="kd">var</span><span class="w"> </span><span class="nx">trial_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">().</span><span class="nx">values</span><span class="p">();</span>
+<span class="w">          </span><span class="kd">var</span><span class="w"> </span><span class="nx">trial_json</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">trial_data</span><span class="p">,</span><span class="w"> </span><span class="kc">null</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span>
 <span class="w">          </span><span class="k">return</span><span class="w"> </span><span class="sb">`&lt;p style=&quot;margin-bottom:0px;&quot;&gt;&lt;strong&gt;Trial data:&lt;/strong&gt;&lt;/p&gt;</span>
-<span class="sb">            &lt;pre style=&quot;margin-top:0px;text-align:left;&quot;&gt;</span><span class="si">${</span><span class="nx">trial_json</span><span class="si">}</span><span class="sb">&lt;/pre&gt;`</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="w"></span>
-<span class="w">      </span><span class="p">};</span><span class="w"></span>
+<span class="sb">            &lt;pre style=&quot;margin-top:0px;text-align:left;&quot;&gt;</span><span class="si">${</span><span class="nx">trial_json</span><span class="si">}</span><span class="sb">&lt;/pre&gt;`</span><span class="p">;</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span>
+<span class="w">      </span><span class="p">};</span>
 
-<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="w"></span>
+<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span>
 <span class="w">        </span><span class="nx">preload</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">camera_instructions</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">init_camera</span><span class="p">,</span><span class="w"> </span>
@@ -2331,74 +2336,83 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <span class="w">        </span><span class="nx">calibration</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">validation_instructions</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">validation</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">recalibrate</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">calibration_done</span><span class="p">,</span><span class="w"></span>
+<span class="w">        </span><span class="nx">recalibrate</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">calibration_done</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">begin</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">show_data</span><span class="w"></span>
-<span class="w">      </span><span class="p">]);</span><span class="w"></span>
+<span class="w">        </span><span class="nx">show_data</span>
+<span class="w">      </span><span class="p">]);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>Below is example data from the image-keyboard-response trial taken from the experiment above. In addition to the standard data that is collected for this plugin, you can see the additional <code>webgazer_data</code> and <code>webgazer_targets</code> arrays. The <code>webgazer_data</code> shows 21 gaze location estimates during the 1-second image presentation. The <code>webgazer_targets</code> array shows that there was one target, the image-keyboard-response stimulus, and tells you the x- and y-coordinate boundaries for the target (image) rectangle. By comparing each of the x/y locations from the <code>webgazer_data</code> locations array with the target boundaries in <code>webgazer_targets</code>, you can determine if/when the estimated gaze location was inside the target area.</p>
-<div class="highlight"><pre><span></span><code><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;rt&quot;</span><span class="o">:</span><span class="w"> </span><span class="kc">null</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;stimulus&quot;</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;response&quot;</span><span class="o">:</span><span class="w"> </span><span class="kc">null</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;trial_type&quot;</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;image-keyboard-response&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;trial_index&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;time_elapsed&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">30701</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;internal_node_id&quot;</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;0.0-4.0&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;webgazer_data&quot;</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">1065</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">437</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">39</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">943</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">377</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">79</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">835</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">332</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">110</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">731</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">299</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">146</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">660</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">271</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">189</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">606</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">251</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">238</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">582</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">213</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">288</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">551</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">335</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">538</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">183</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">394</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">514</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">177</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">436</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">171</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">493</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">525</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">178</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">542</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">537</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">182</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">592</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">543</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">178</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">633</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">547</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">177</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">691</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">558</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">174</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">739</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">574</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">183</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">789</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">577</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">197</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">838</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">584</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">214</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">889</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">603</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">218</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">937</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">606</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">221</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">987</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;webgazer_targets&quot;</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="s2">&quot;#jspsych-image-keyboard-response-stimulus&quot;</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">490</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">135</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="s2">&quot;height&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="s2">&quot;width&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="s2">&quot;top&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">135</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="s2">&quot;bottom&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">435</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="s2">&quot;left&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">490</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="s2">&quot;right&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">790</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="s2">&quot;rt&quot;</span><span class="o">:</span><span class="w"> </span><span class="kc">null</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;stimulus&quot;</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;response&quot;</span><span class="o">:</span><span class="w"> </span><span class="kc">null</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;trial_type&quot;</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;image-keyboard-response&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;trial_index&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;time_elapsed&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">30701</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;internal_node_id&quot;</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;0.0-4.0&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;webgazer_data&quot;</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">1065</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">437</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">39</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">943</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">377</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">79</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">835</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">332</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">110</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">731</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">299</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">146</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">660</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">271</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">189</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">606</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">251</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">238</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">582</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">213</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">288</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">551</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">335</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">538</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">183</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">394</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">514</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">177</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">436</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">171</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">493</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">525</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">178</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">542</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">537</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">182</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">592</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">543</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">178</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">633</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">547</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">177</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">691</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">558</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">174</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">739</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">574</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">183</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">789</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">577</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">197</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">838</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">584</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">214</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">889</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">603</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">218</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">937</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="w"> </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">606</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">221</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;t&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">987</span><span class="p">}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="s2">&quot;webgazer_targets&quot;</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="s2">&quot;#jspsych-image-keyboard-response-stimulus&quot;</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="s2">&quot;x&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">490</span><span class="p">,</span>
+<span class="w">      </span><span class="s2">&quot;y&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">135</span><span class="p">,</span>
+<span class="w">      </span><span class="s2">&quot;height&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span>
+<span class="w">      </span><span class="s2">&quot;width&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span>
+<span class="w">      </span><span class="s2">&quot;top&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">135</span><span class="p">,</span>
+<span class="w">      </span><span class="s2">&quot;bottom&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">435</span><span class="p">,</span>
+<span class="w">      </span><span class="s2">&quot;left&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">490</span><span class="p">,</span>
+<span class="w">      </span><span class="s2">&quot;right&quot;</span><span class="o">:</span><span class="w"> </span><span class="mf">790</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../fullscreen/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Fullscreen Experiments" rel="prev">
@@ -2457,7 +2471,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2466,7 +2480,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2479,11 +2493,13 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/fullscreen/index.html b/7.3/overview/fullscreen/index.html
old mode 100755
new mode 100644
index 8813d37c27..5cf55c0ddf
--- a/7.3/overview/fullscreen/index.html
+++ b/7.3/overview/fullscreen/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/fullscreen/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1869,58 +1872,69 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/fullscreen.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="fullscreen-experiments">Fullscreen Experiments<a class="headerlink" href="#fullscreen-experiments" title="Permanent link">&para;</a></h1>
 <p>You can run your experiment in fullscreen mode by using the jspsych-fullscreen plugin.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
 
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFullscreen</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">fullscreen_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFullscreen</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">fullscreen_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">});</span>
 
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will be in fullscreen mode.&#39;</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will be in fullscreen mode.&#39;</span>
+<span class="p">});</span>
 
-<span class="c1">// exit fullscreen mode</span><span class="w"></span>
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFullscreen</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">fullscreen_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<span class="c1">// exit fullscreen mode</span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFullscreen</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">fullscreen_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="p">});</span>
 
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will NOT be in fullscreen mode.&#39;</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will NOT be in fullscreen mode.&#39;</span>
+<span class="p">});</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 </code></pre></div>
 <p>For security reasons, web browsers require that users initiate an action to launch fullscreen mode. The fullscreen plugin displays a button that the user must click to change the display to fullscreen.</p>
 <p>Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../media-preloading/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Media Preloading" rel="prev">
@@ -1979,7 +1993,7 @@ <h1 id="fullscreen-experiments">Fullscreen Experiments<a class="headerlink" href
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -1988,7 +2002,7 @@ <h1 id="fullscreen-experiments">Fullscreen Experiments<a class="headerlink" href
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2001,11 +2015,13 @@ <h1 id="fullscreen-experiments">Fullscreen Experiments<a class="headerlink" href
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/media-preloading/index.html b/7.3/overview/media-preloading/index.html
old mode 100755
new mode 100644
index 75d28e08af..f3774ed78d
--- a/7.3/overview/media-preloading/index.html
+++ b/7.3/overview/media-preloading/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/media-preloading/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2013,16 +2016,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/media-preloading.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="media-preloading">Media Preloading<a class="headerlink" href="#media-preloading" title="Permanent link">&para;</a></h1>
 <p>If an experiment uses image, audio, or video files as stimuli, it is a good idea to preload the files before running the experiment. You can preload files at any point in your experiment using the <a href="../../plugins/preload/">jsPsych <code>preload</code> plugin</a>. Preloading files means that the participant's browser will download the files and store them in local memory on the participant's computer. This is important because displaying or playing a media file is much faster if it is already in memory on the participant's computer. Without preloading, there will be noticeable delays in the display of media, which will affect any timing measurements (such as how long an image is displayed, or a participant's response time since first viewing an image). For particularly large files, like video, preloading content avoids lengthy pauses in the middle of the experiment that can be disruptive to the flow of the experiment.</p>
 <div class="admonition warning">
@@ -2031,319 +2036,328 @@ <h1 id="media-preloading">Media Preloading<a class="headerlink" href="#media-pre
 </div>
 <h2 id="automatic-preloading">Automatic Preloading<a class="headerlink" href="#automatic-preloading" title="Permanent link">&para;</a></h2>
 <p>jsPsych can automatically preload audio, video, and image files that are used as parameters for the standard set of plugins, based on the timeline that is passed to <code>jsPsych.run</code>. You must initiate this preloading using a <code>preload</code> trial. You should add this <code>preload</code> trial into your timeline when you want the preloading to occur, and set the <code>auto_preload</code> parameter to <code>true</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// the &quot;auto_preload: true&quot; setting tells the plugin to automatically find </span><span class="w"></span>
-<span class="c1">// stimuli to preload based the main experiment timeline (used in jsPsych.run)</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// the &quot;auto_preload: true&quot; setting tells the plugin to automatically find </span>
+<span class="c1">// stimuli to preload based the main experiment timeline (used in jsPsych.run)</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"> </span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// this image file can be automatically preloaded </span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file1.png&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// the sound file can be automatically preloaded </span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">sound_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;audio/hello.mp3&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// the video file can be automatically preloaded (as long as the experiment </span><span class="w"></span>
-<span class="c1">// is running on a server)</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">video_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/sample_video.mp4&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload</span><span class="p">,</span><span class="w"> </span><span class="nx">image_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">sound_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">video_trial</span><span class="p">]);</span><span class="w"></span>
+<span class="p">}</span>
+
+<span class="c1">// this image file can be automatically preloaded </span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file1.png&#39;</span>
+<span class="p">}</span>
+
+<span class="c1">// the sound file can be automatically preloaded </span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">sound_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;audio/hello.mp3&#39;</span>
+<span class="p">}</span>
+
+<span class="c1">// the video file can be automatically preloaded (as long as the experiment </span>
+<span class="c1">// is running on a server)</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">video_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/sample_video.mp4&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload</span><span class="p">,</span><span class="w"> </span><span class="nx">image_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">sound_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">video_trial</span><span class="p">]);</span>
 </code></pre></div>
 <h2 id="manual-preloading">Manual preloading<a class="headerlink" href="#manual-preloading" title="Permanent link">&para;</a></h2>
 <p>If you are using media files in your experiment but they are not being passed directly as parameters to the trials (e.g., because you are using functions as parameters that return the media files, you are using timeline variables, or you are embedding the media files in an HTML string), then these files will not be detected when you use the <code>auto_preload</code> option, so you must manually specify them. The <code>preload</code> plugin allows you to add these files using the <code>images</code>, <code>audio</code> and <code>video</code> parameters.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// this image file cannot be automatically preloaded because it is embedded in </span><span class="w"></span>
-<span class="c1">// an HTML string</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;img src=&quot;img/file1.png&quot;&gt;&lt;/img&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// this audio file cannot be automatically preloaded because it is returned </span><span class="w"></span>
-<span class="c1">// from a function</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">sound_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="s1">&#39;audio/sound1.mp3&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// these video files cannot be automatically preloaded because they are passed </span><span class="w"></span>
-<span class="c1">// into a trial using the jsPsych.timelineVariable function</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">video_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;video&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/1.mp4&#39;</span><span class="p">]},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/2.mp4&#39;</span><span class="p">]}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// to manually preload media files, create an array of file paths for each </span><span class="w"></span>
-<span class="c1">// media type</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/file1.png&#39;</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">audio</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;audio/sound1.mp3&#39;</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">video</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/1.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;video/2.mp4&#39;</span><span class="p">];</span><span class="w"></span>
-
-<span class="c1">// these array can be passed into the preload plugin using the images, audio </span><span class="w"></span>
-<span class="c1">// and video parameters</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="nx">images</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">audio</span><span class="o">:</span><span class="w"> </span><span class="nx">audio</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="nx">video</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload</span><span class="p">,</span><span class="w"> </span><span class="nx">image_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">sound_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">video_trials</span><span class="p">]);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// this image file cannot be automatically preloaded because it is embedded in </span>
+<span class="c1">// an HTML string</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;img src=&quot;img/file1.png&quot;&gt;&lt;/img&gt;&#39;</span><span class="p">,</span>
+<span class="p">}</span>
+
+<span class="c1">// this audio file cannot be automatically preloaded because it is returned </span>
+<span class="c1">// from a function</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">sound_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="s1">&#39;audio/sound1.mp3&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="c1">// these video files cannot be automatically preloaded because they are passed </span>
+<span class="c1">// into a trial using the jsPsych.timelineVariable function</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">video_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;video&#39;</span><span class="p">)</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/1.mp4&#39;</span><span class="p">]},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/2.mp4&#39;</span><span class="p">]}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="c1">// to manually preload media files, create an array of file paths for each </span>
+<span class="c1">// media type</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/file1.png&#39;</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">audio</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;audio/sound1.mp3&#39;</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">video</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/1.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;video/2.mp4&#39;</span><span class="p">];</span>
+
+<span class="c1">// these array can be passed into the preload plugin using the images, audio </span>
+<span class="c1">// and video parameters</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="nx">images</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">audio</span><span class="o">:</span><span class="w"> </span><span class="nx">audio</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="nx">video</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload</span><span class="p">,</span><span class="w"> </span><span class="nx">image_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">sound_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">video_trials</span><span class="p">]);</span>
 </code></pre></div>
 <h2 id="combining-automatic-and-manual-preloading">Combining automatic and manual preloading<a class="headerlink" href="#combining-automatic-and-manual-preloading" title="Permanent link">&para;</a></h2>
 <p>It's possible to combine automatic and manual preloading. For instance, you may want to automatically preload all of the media files based on your experiment timeline, while also manually preloading any files that can't be automatically preloaded. Any duplicate file names across all preloading methods will be removed before preloading starts, so including the same file names in multiple <code>preload</code> parameters will not affect the preloading duration. </p>
-<div class="highlight"><pre><span></span><code><span class="c1">// this file can be preloaded automatically</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file1.png&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// this file can be preloaded automatically</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">sound_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;audio/hello.mp3&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// these files must be preloaded manually</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">video_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;video&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/1.mp4&#39;</span><span class="p">]},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/2.mp4&#39;</span><span class="p">]}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">video</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/1.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;video/2.mp4&#39;</span><span class="p">];</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="c1">// automatically preload the image and audio files</span><span class="w"></span>
-<span class="w">    </span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="nx">video</span><span class="w"> </span><span class="c1">// manually preload the videos used with timeline variables</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload</span><span class="p">,</span><span class="w"> </span><span class="nx">image_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">sound_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">video_trials</span><span class="p">]);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// this file can be preloaded automatically</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file1.png&#39;</span>
+<span class="p">}</span>
+
+<span class="c1">// this file can be preloaded automatically</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">sound_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;audio/hello.mp3&#39;</span>
+<span class="p">}</span>
+
+<span class="c1">// these files must be preloaded manually</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">video_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;video&#39;</span><span class="p">)</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/1.mp4&#39;</span><span class="p">]},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/2.mp4&#39;</span><span class="p">]}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">video</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;video/1.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;video/2.mp4&#39;</span><span class="p">];</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="c1">// automatically preload the image and audio files</span>
+<span class="w">    </span><span class="nx">video</span><span class="o">:</span><span class="w"> </span><span class="nx">video</span><span class="w"> </span><span class="c1">// manually preload the videos used with timeline variables</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload</span><span class="p">,</span><span class="w"> </span><span class="nx">image_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">sound_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">video_trials</span><span class="p">]);</span>
 </code></pre></div>
 <h2 id="preloading-in-batches">Preloading in batches<a class="headerlink" href="#preloading-in-batches" title="Permanent link">&para;</a></h2>
 <p>Some experiments use many and/or large media files. This can cause problems when participants have slow and/or unreliable internet connections, because it increases the chances of loading errors during preloading. This can also cause problems with file caching, i.e. ensuring that the preloaded files remain in the browser's memory, because loading all stimuli at once may exceed the browser's cache limits. One option for mitigating these problems is to load the media files in smaller batches throughout the experiment. Files should be preloaded as close as possible to when they will be needed. For instance, if you have several blocks of trials, then right before each block, you can preload the stimuli that are needed for that block.</p>
 <p>Here is an example with trials where the stimuli files can be preloaded automatically. In this case, the <code>trials</code> parameter is used to tell the <code>preload</code> plugin to preload the stimuli from a specific part of the timeline. </p>
-<div class="highlight"><pre><span></span><code><span class="c1">// these image files in these trial blocks can be automatically preloaded</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file1.png&#39;</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file2.png&#39;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file3.png&#39;</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file4.png&#39;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trials</span><span class="o">:</span><span class="w"> </span><span class="nx">block_1</span><span class="w"> </span><span class="c1">// automatically preload just the images from block_1 trials</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trials</span><span class="o">:</span><span class="w"> </span><span class="nx">block_2</span><span class="w"> </span><span class="c1">// automatically preload just the images from block_2 trials</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// add each preload trial onto the timeline before the appropriate trial block</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="nx">preload_1</span><span class="p">,</span><span class="w"> </span><span class="nx">block_1</span><span class="p">,</span><span class="w"> </span><span class="nx">preload_2</span><span class="p">,</span><span class="w"> </span><span class="nx">block_2</span><span class="p">]</span><span class="w"></span>
-<span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// these image files in these trial blocks can be automatically preloaded</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file1.png&#39;</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file2.png&#39;</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file3.png&#39;</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/file4.png&#39;</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trials</span><span class="o">:</span><span class="w"> </span><span class="nx">block_1</span><span class="w"> </span><span class="c1">// automatically preload just the images from block_1 trials</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trials</span><span class="o">:</span><span class="w"> </span><span class="nx">block_2</span><span class="w"> </span><span class="c1">// automatically preload just the images from block_2 trials</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span>
+<span class="w">    </span><span class="c1">// add each preload trial onto the timeline before the appropriate trial block</span>
+<span class="w">    </span><span class="p">[</span><span class="nx">preload_1</span><span class="p">,</span><span class="w"> </span><span class="nx">block_1</span><span class="p">,</span><span class="w"> </span><span class="nx">preload_2</span><span class="p">,</span><span class="w"> </span><span class="nx">block_2</span><span class="p">]</span>
+<span class="p">);</span>
 </code></pre></div>
 <p>Below is an example with trials where the stimuli files cannot be preloaded automatically, because the stimuli files are passed to the trials via <code>jsPsych.timelineVariable</code>. In this case, we create separate arrays for each batch of files, and then pass those arrays to the each preload trial.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// these trial blocks cannot be automatically preloaded because </span><span class="w"></span>
-<span class="c1">// the media files are passed to the trial parameters with timeline variables</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stim</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file1.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stim</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file1.png&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stim</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file3.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stim</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file4.png&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">images_block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;file1.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file2.png&#39;</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">images_block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;file3.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file4.png&#39;</span><span class="p">];</span><span class="w"></span>
-
-<span class="c1">// preload trial for preloading the block 1 stimuli</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="nx">images_block_1</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// preload trial for preloading the block 2 stimuli</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="nx">images_block_2</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// add each preload trial to the timeline before the appropriate trial block</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="nx">preload_1</span><span class="p">,</span><span class="w"> </span><span class="nx">block_1</span><span class="p">,</span><span class="w"> </span><span class="nx">preload_2</span><span class="p">,</span><span class="w"> </span><span class="nx">block_2</span><span class="p">]</span><span class="w"></span>
-<span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// these trial blocks cannot be automatically preloaded because </span>
+<span class="c1">// the media files are passed to the trial parameters with timeline variables</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stim</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file1.png&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stim</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file1.png&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stim</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file3.png&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stim</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file4.png&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">images_block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;file1.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file2.png&#39;</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">images_block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;file3.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file4.png&#39;</span><span class="p">];</span>
+
+<span class="c1">// preload trial for preloading the block 1 stimuli</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="nx">images_block_1</span>
+<span class="p">}</span>
+
+<span class="c1">// preload trial for preloading the block 2 stimuli</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="nx">images_block_2</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span>
+<span class="w">    </span><span class="c1">// add each preload trial to the timeline before the appropriate trial block</span>
+<span class="w">    </span><span class="p">[</span><span class="nx">preload_1</span><span class="p">,</span><span class="w"> </span><span class="nx">block_1</span><span class="p">,</span><span class="w"> </span><span class="nx">preload_2</span><span class="p">,</span><span class="w"> </span><span class="nx">block_2</span><span class="p">]</span>
+<span class="p">);</span>
 </code></pre></div>
 <h2 id="preloading-progress-bar">Preloading progress bar<a class="headerlink" href="#preloading-progress-bar" title="Permanent link">&para;</a></h2>
 <p>By default, the <code>preload</code> plugin will display a progress bar while files are being preloaded. This progress bar represents all files that are being preloaded during the trial, regardless of whether the file is being preloaded automatically via the <code>auto_preload</code> or <code>trials</code> parameters, or manually via the <code>audio</code>, <code>images</code>, and <code>video</code> parameters. You may wish to turn the preload progress bar off if you are only loading a small number of files, as it will appear and disappear so quickly that the participant may be confused about what it was. You can control whether the preloading progress bar appears by setting the <code>show_progress_bar</code> parameter in the <code>preload</code> trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"> </span><span class="c1">// hide progress bar</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"> </span><span class="c1">// hide progress bar</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="loading-time-limits">Loading time limits<a class="headerlink" href="#loading-time-limits" title="Permanent link">&para;</a></h2>
 <p>It's usually a good idea to set a time limit for file loading, to ensure that participants aren't waiting for an unreasonable amount of time. Time limits can be specified in milliseconds using the <code>max_load_time</code> parameter. If you set a loading time limit and all files haven't finished loading before this time, then the <code>preload</code> trial will either stop an error (if <code>continue_after_error</code> is false, the default) or the trial will end and the experiment will continue (if <code>continue_after_error</code> is <code>true</code>). If <code>max_load_time</code> is <code>null</code> (the default), then there is no time limit. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="w">    </span><span class="nx">max_load_time</span><span class="o">:</span><span class="w"> </span><span class="mf">60000</span><span class="w"> </span><span class="c1">// 1 minute</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">    </span><span class="nx">max_load_time</span><span class="o">:</span><span class="w"> </span><span class="mf">60000</span><span class="w"> </span><span class="c1">// 1 minute</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="loading-and-error-messages">Loading and error messages<a class="headerlink" href="#loading-and-error-messages" title="Permanent link">&para;</a></h2>
 <p>It's possible to specify custom messages to be shown on the page while the media files are loading, and in case of one or more file loading errors. The <code>message</code> parameter allows you to customize the loading message using an HML-formatted string. If <code>show_progress_bar</code> is <code>true</code>, then this message will be shown above the progress bar. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="w">    </span><span class="nx">message</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Please wait while the experiment loads. This may take a few minutes.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">    </span><span class="nx">message</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Please wait while the experiment loads. This may take a few minutes.&#39;</span><span class="p">,</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>A preloading error will occur when either (a) one or more files produces a loading error, and/or (b) all files have not finished loading before the <code>max_load_time</code> duration. The <code>error_message</code> parameter allows you to customize the messsage that's shown on the page in these cases. This message will only be shown if <code>continue_after_error</code> is <code>false</code> (the default). </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">error_message</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;The experiment failed to load. Please contact the researcher.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">error_message</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;The experiment failed to load. Please contact the researcher.&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>In addition to the <code>error_message</code> parameter, it's also possible to show more detailed error messages on the page about any files that failed to load. You can control this with the <code>show_detailed_errors</code> parameter. Detailed error messages will appear below the general error message. This only applies if <code>continue_after_error</code> is <code>false</code> (the default). </p>
 <p>Detailed error messages can be useful when testing and debugging your experiment. If <code>show_detailed_errors</code> is <code>true</code>, then if one or more loading errors occurs before the <code>max_load_time</code> is reached, then the error page will also contian a list of the file(s) that produced an error, along with error information (if there is any). Note that this may not be a complete list, because it will only report any errors that occurred before the <code>max_load_time</code> was reached. If there are no file loading errors but preloading hasn't finished before the <code>max_load_time</code>, then detailed error message will just tell you that loading timed out. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// show details of any file loading errors and/or loading time out</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="c1">// show details of any file loading errors and/or loading time out</span>
 <span class="w">    </span><span class="nx">show_detailed_errors</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"> </span>
-<span class="p">}</span><span class="w"></span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="options-for-handling-errors">Options for handling errors<a class="headerlink" href="#options-for-handling-errors" title="Permanent link">&para;</a></h2>
 <p>If <code>continue_after_error</code> is <code>true</code>, then the experiment <em>will not stop</em> if one or more files fails to load. Instead, the trial will end and the experiment will continue. However, the preload trial data will contain a property called <code>success</code>, which is whether or not all files were loaded successfully, <code>timeout</code>, which is whether or not the files loaded successfully before the <code>max_load_time</code>. The preload trial data will also contain lists of any <code>image</code>, <code>audio</code>, and <code>video</code> files that failed to load. This gives you the option to continue the experiment after preloading fails and use the preload trial data decide what to do next. For instance, you may decide to skip the trials that use the stimuli files that failed to load, or try loading the failed files again. Another option is to simply end the experiment when preloading fails, but send the data back to your server so that you have more information about the loading failure.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">message</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Please wait while the experiment loads...&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// don&#39;t stop the experiment if there are file loading errors or if loading times out</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">message</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Please wait while the experiment loads...&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="c1">// don&#39;t stop the experiment if there are file loading errors or if loading times out</span>
 <span class="w">    </span><span class="nx">continue_after_error</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"> </span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">save_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="k">async</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">done</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">();</span><span class="w"></span>
-<span class="w">        </span><span class="nx">save_data</span><span class="p">(</span><span class="nx">data</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="nx">done</span><span class="p">()})</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// the experiment will stop here, since there are no valid key choices or trial duration </span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">fail_message</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;The experiment failed to load. Please contact the researcher.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">save_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span>
+<span class="w">    </span><span class="k">async</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">done</span><span class="p">){</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">();</span>
+<span class="w">        </span><span class="nx">save_data</span><span class="p">(</span><span class="nx">data</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="nx">done</span><span class="p">()})</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="c1">// the experiment will stop here, since there are no valid key choices or trial duration </span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">fail_message</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;The experiment failed to load. Please contact the researcher.&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kc">null</span><span class="w"> </span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">if_loading_fails</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">save_data</span><span class="p">,</span><span class="w"> </span><span class="nx">fail_message</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">conditional_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">values</span><span class="p">().</span><span class="nx">success</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="c1">// preloading was successful, so skip this conditional timeline</span><span class="w"></span>
-<span class="w">            </span><span class="c1">// and move on with the experiment</span><span class="w"></span>
-<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="c1">// preloading failed, so run this conditional timeline:</span><span class="w"></span>
-<span class="w">            </span><span class="c1">// save the data to the server and show the fail message</span><span class="w"></span>
-<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="c1">// ... rest of experiment</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">if_loading_fails</span><span class="p">,</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">])</span><span class="w"></span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">if_loading_fails</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">save_data</span><span class="p">,</span><span class="w"> </span><span class="nx">fail_message</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">conditional_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">values</span><span class="p">().</span><span class="nx">success</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">            </span><span class="c1">// preloading was successful, so skip this conditional timeline</span>
+<span class="w">            </span><span class="c1">// and move on with the experiment</span>
+<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="w">        </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">            </span><span class="c1">// preloading failed, so run this conditional timeline:</span>
+<span class="w">            </span><span class="c1">// save the data to the server and show the fail message</span>
+<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="c1">// ... rest of experiment</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">if_loading_fails</span><span class="p">,</span><span class="w"> </span><span class="p">...</span><span class="w"> </span><span class="p">])</span>
 </code></pre></div>
 <p>The <code>preload</code> plugin's <code>on_success</code> and <code>on_error</code> callback functions provide another way of tracking preloading progress and handling file loading errors. These functions are called after any file either loads successfully or produces an error, respectively. These functions receive a single argument, which is the path of the file (string) that loaded or produced an error.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">file_load_count</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">file_error_count</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_error</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">file_error_count</span><span class="o">++</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Error: &#39;</span><span class="p">,</span><span class="nx">file</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_success</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">file_load_count</span><span class="o">++</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Loaded: &#39;</span><span class="p">,</span><span class="nx">file</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">file_load_count</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">file_error_count</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">on_error</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">file_error_count</span><span class="o">++</span><span class="p">;</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Error: &#39;</span><span class="p">,</span><span class="nx">file</span><span class="p">);</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">on_success</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">file_load_count</span><span class="o">++</span><span class="p">;</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Loaded: &#39;</span><span class="p">,</span><span class="nx">file</span><span class="p">);</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>Note that there's no guarantee that any/all files will trigger one of these two callback functions, because they are cancelled after the <code>preload</code> trial ends. For instance, if a file takes longer to load then the <code>max_load_time</code>, then the <code>preload</code> trial will end due to timing out, and the <code>on_success</code> and <code>on_error</code> callbacks for any in-progress files will be cancelled.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../record-browser-interactions/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Record Browser Interactions" rel="prev">
@@ -2402,7 +2416,7 @@ <h2 id="options-for-handling-errors">Options for handling errors<a class="header
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2411,7 +2425,7 @@ <h2 id="options-for-handling-errors">Options for handling errors<a class="header
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2424,11 +2438,13 @@ <h2 id="options-for-handling-errors">Options for handling errors<a class="header
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/mturk/index.html b/7.3/overview/mturk/index.html
old mode 100755
new mode 100644
index cd7f22f431..0ae091e354
--- a/7.3/overview/mturk/index.html
+++ b/7.3/overview/mturk/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/mturk/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,16 +1974,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/mturk.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="integrating-with-mechanical-turk">Integrating with Mechanical Turk<a class="headerlink" href="#integrating-with-mechanical-turk" title="Permanent link">&para;</a></h1>
 <p>A common use of jsPsych is to build an online experiment and find participants using <a href="http://www.mturk.com/">Mechanical Turk</a>. Once an experiment is available through a web server and data is being <a href="../data/">saved on the server</a>, connecting the experiment with Mechanical Turk takes only a few additional steps. jsPsych has some built-in functionality to assist with this process. </p>
 <h2 id="the-jspsychturk-module">The jsPsych.turk module<a class="headerlink" href="#the-jspsychturk-module" title="Permanent link">&para;</a></h2>
@@ -1989,34 +1994,34 @@ <h2 id="creating-an-advertisement-page">Creating an advertisement page<a class="
 <p>When potential participants view your experiment on Mechanical Turk, they will be able to see a single webpage before deciding whether or not to accept the HIT (start the experiment). This first page is often used as an advertisement for the experiment, similar to posting a flier in a department hallway. The important thing to remember about this page is that potential participants will be able to interact with it even if they haven't accepted the HIT. Therefore, it can be useful to change the content of the page depending on whether the HIT has been accepted or not. This is relatively easy to do:</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">div</span> <span class="na">id</span><span class="o">=</span><span class="s">&quot;experiment_link&quot;</span><span class="p">&gt;</span>You must accept the HIT to begin the experiment<span class="p">&lt;/</span><span class="nt">div</span><span class="p">&gt;</span>.
 
-<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="c1">// jsPsych has a method turkInfo() which can determine whether or not the</span><span class="w"></span>
-<span class="c1">// HIT has been accepted.</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">turkInfo</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turkInfo</span><span class="p">();</span><span class="w"></span>
-
-<span class="c1">// turkInfo.previewMode is true in two cases: when the HIT has not been</span><span class="w"></span>
-<span class="c1">// accepted yet OR when the page is viewed outside of mechanical turk.</span><span class="w"></span>
-<span class="c1">// The second property, outsideTurk, is true when the page is viewed</span><span class="w"></span>
-<span class="c1">// outside of mechanical turk, so together, the statement will be true</span><span class="w"></span>
-<span class="c1">// only when in Turk and when the HIT is not accepted yet.</span><span class="w"></span>
-<span class="k">if</span><span class="p">(</span><span class="o">!</span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">previewMode</span><span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="o">!</span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">outsideTurk</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;#experiment_link&#39;</span><span class="p">).</span><span class="nx">innerHMTL</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&lt;a href=&quot;link_to_experiment.html&quot; target=&quot;_blank&quot;&gt;Click Here to Start Experiment&lt;/a&gt;&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="c1">// jsPsych has a method turkInfo() which can determine whether or not the</span>
+<span class="c1">// HIT has been accepted.</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">turkInfo</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turkInfo</span><span class="p">();</span>
+
+<span class="c1">// turkInfo.previewMode is true in two cases: when the HIT has not been</span>
+<span class="c1">// accepted yet OR when the page is viewed outside of mechanical turk.</span>
+<span class="c1">// The second property, outsideTurk, is true when the page is viewed</span>
+<span class="c1">// outside of mechanical turk, so together, the statement will be true</span>
+<span class="c1">// only when in Turk and when the HIT is not accepted yet.</span>
+<span class="k">if</span><span class="p">(</span><span class="o">!</span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">previewMode</span><span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="o">!</span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">outsideTurk</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;#experiment_link&#39;</span><span class="p">).</span><span class="nx">innerHMTL</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&lt;a href=&quot;link_to_experiment.html&quot; target=&quot;_blank&quot;&gt;Click Here to Start Experiment&lt;/a&gt;&#39;</span><span class="p">;</span>
+<span class="p">}</span>
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>One important issue with advertisement pages is that they must be served using the https protocol, which requires having an SSL certificate on the web server hosting the page. Instructions for how to do this vary depending on what kind of server you are using, so the best advice is to simply Google for instructions on how to acquire and install an SSL certificate on your particular server.</p>
 <h2 id="getting-the-worker-id">Getting the worker ID<a class="headerlink" href="#getting-the-worker-id" title="Permanent link">&para;</a></h2>
 <p>Every account on Mechanical Turk is given a unique identification string. Recording this ID is a useful way to keep track of who is doing your experiment. In particular, while Turk has built in tools for preventing the same person from doing a HIT more than once, there may be cases where you don't want participants to complete related experiments. If you store the worker ID of every person who starts an experiment in a database, then you can exclude people by running a query on the database to check for the ID. jsPsych can get the workerID, assignmentID, and hitID with the turkInfo method.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">turkInfo</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">turkInfo</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">turkInfo</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">turkInfo</span><span class="p">();</span>
 
-<span class="c1">// workerID</span><span class="w"></span>
-<span class="nx">turkInfo</span><span class="p">.</span><span class="nx">workerId</span><span class="w"></span>
+<span class="c1">// workerID</span>
+<span class="nx">turkInfo</span><span class="p">.</span><span class="nx">workerId</span>
 
-<span class="c1">// hitID</span><span class="w"></span>
-<span class="nx">turkInfo</span><span class="p">.</span><span class="nx">hitId</span><span class="w"></span>
+<span class="c1">// hitID</span>
+<span class="nx">turkInfo</span><span class="p">.</span><span class="nx">hitId</span>
 
-<span class="c1">// assignmentID</span><span class="w"></span>
-<span class="nx">turkInfo</span><span class="p">.</span><span class="nx">assignmentId</span><span class="w"></span>
+<span class="c1">// assignmentID</span>
+<span class="nx">turkInfo</span><span class="p">.</span><span class="nx">assignmentId</span>
 </code></pre></div>
 <p>Recording the workerId at the start of the experiment is also a good way to track dropouts.</p>
 <h2 id="submitting-results-to-mechanical-turk">Submitting results to Mechanical Turk<a class="headerlink" href="#submitting-results-to-mechanical-turk" title="Permanent link">&para;</a></h2>
@@ -2026,28 +2031,37 @@ <h2 id="submitting-results-to-mechanical-turk">Submitting results to Mechanical
 <span class="p">&lt;</span><span class="nt">input</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text&quot;</span> <span class="na">id</span><span class="o">=</span><span class="s">&quot;code&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">input</span><span class="p">&gt;</span>
 <span class="p">&lt;</span><span class="nt">button</span> <span class="na">onclick</span><span class="o">=</span><span class="s">&quot;sendData();&quot;</span><span class="p">&gt;</span>Submit HIT<span class="p">&lt;/</span><span class="nt">button</span><span class="p">&gt;</span>
 
-<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="kd">function</span><span class="w"> </span><span class="nx">sendData</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">submitToTurk</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">code</span><span class="o">:</span><span class="w"> </span><span class="nb">document</span><span class="p">.</span><span class="nx">getElementById</span><span class="p">(</span><span class="s1">&#39;code&#39;</span><span class="p">).</span><span class="nx">value</span><span class="w"></span>
-<span class="w">  </span><span class="p">});</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="kd">function</span><span class="w"> </span><span class="nx">sendData</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">submitToTurk</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">code</span><span class="o">:</span><span class="w"> </span><span class="nb">document</span><span class="p">.</span><span class="nx">getElementById</span><span class="p">(</span><span class="s1">&#39;code&#39;</span><span class="p">).</span><span class="nx">value</span>
+<span class="w">  </span><span class="p">});</span>
+<span class="p">}</span>
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>When workers click the button, the contents of the <code>code</code> text field will be sent to Mechanical Turk, and you'll be able to view the participants and the codes that they entered in the Mechanical Turk GUI. You can then approve or reject work using the Mechanical Turk website.</p>
 <h2 id="limitations">Limitations<a class="headerlink" href="#limitations" title="Permanent link">&para;</a></h2>
 <p>jsPsych is not designed to communicate with the Mechanical Turk API in a comprehensive manner. If you are looking for software to help you post and manage HITs, then you may want to look at <a href="http://www.psiturk.org">PsiTurk</a>. jsPsych and PsiTurk complement each other nicely, and there is <a href="https://psiturk.org/ee/W4v3TPAsiD6FUVY8PDyajH">an example of combining the two platforms</a> on PsiTurk's experiment exchange.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../prolific/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Integrating with Prolific" rel="prev">
@@ -2106,7 +2120,7 @@ <h2 id="limitations">Limitations<a class="headerlink" href="#limitations" title=
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2115,7 +2129,7 @@ <h2 id="limitations">Limitations<a class="headerlink" href="#limitations" title=
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2128,11 +2142,13 @@ <h2 id="limitations">Limitations<a class="headerlink" href="#limitations" title=
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/plugins/index.html b/7.3/overview/plugins/index.html
old mode 100755
new mode 100644
index 2ad3e5d4f6..7c6fd7ec76
--- a/7.3/overview/plugins/index.html
+++ b/7.3/overview/plugins/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/plugins/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2067,16 +2070,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/plugins.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="plugins">Plugins<a class="headerlink" href="#plugins" title="Permanent link">&para;</a></h1>
 <p>In jsPsych, plugins define the kinds of trials or events that should occur during the experiment. 
 Some plugins define very general events, like <a href="../plugins/instructions/">displaying a set of instructions pages</a>, <a href="../plugins/image-keyboard-response/">displaying an image and recording a keyboard response</a>, or <a href="../plugins/audio-button-response/">playing a sound file and recording a button response</a>. 
@@ -2086,8 +2091,8 @@ <h1 id="plugins">Plugins<a class="headerlink" href="#plugins" title="Permanent l
 <h2 id="using-a-plugin">Using a plugin<a class="headerlink" href="#using-a-plugin" title="Permanent link">&para;</a></h2>
 <p>To use a plugin, you'll need to load the plugin's JavaScript file in your experiment's HTML page. All jsPsych experiments also need to load the "jsPsych.js" file.</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/javascript&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/javascript&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/javascript&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/javascript&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>Once a plugin is loaded, you can use JavaScript to define a trial that uses that plugin. All jsPsych trials need a <code>type</code> parameter, which tells jsPsych what plugin to use to run the trial. The trial's <code>type</code> is similar to the plugin name, but it always starts with "jsPsych" and is written in <em>camel case</em> rather than with dashes between the words. The trial's <code>type</code> parameter should NOT be a string (i.e., no quotes around the <code>type</code> value). Here are some examples of plugin names and types:</p>
@@ -2114,18 +2119,18 @@ <h2 id="using-a-plugin">Using a plugin<a class="headerlink" href="#using-a-plugi
 </tbody>
 </table>
 <p>The following JavaScript code defines a trial using the <code>image-keyboard-response</code> plugin to display an image file. This trial uses the default values for valid keys, stimulus duration, trial duration, and other parameters. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
 <span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;images/happy_face.jpg&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;images/happy_face.jpg&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>You can override any default parameter values by adding them into your trial object. Here's an example of overriding the default values for <code>trial_duration</code> and <code>post_trial_gap</code>:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;images/happy_face.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3000</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;images/happy_face.jpg&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3000</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="parameters-available-in-all-plugins">Parameters available in all plugins<a class="headerlink" href="#parameters-available-in-all-plugins" title="Permanent link">&para;</a></h2>
 <p>Each plugin specifies its own set of parameters. Check the documentation for a plugin to see what parameters are available and what they do.</p>
@@ -2188,135 +2193,135 @@ <h3 id="the-data-parameter">The data parameter<a class="headerlink" href="#the-d
 <p>The <code>data</code> parameter allows you to add additional properties to the trial data. This can be useful for storing properties of the trial that are not directly apparent from the values that the plugin records. The <code>data</code> parameter value must be an object that contains key-value pairs.</p>
 <p>A simple example is the <a href="https://en.wikipedia.org/wiki/Eriksen_flanker_task">Flanker Task</a>. In this experiment, participants respond to the direction of a central arrow by pressing a key to the left for a left-pointing arrow (&lt;) and a key to the right for a right-pointing arrow (&gt;). The arrow appears in the center of <em>flankers</em>, or arrows that the participant should ignore. Those flankers can be congruent (&gt;&gt;&gt;&gt;&gt;) or incongruent (&lt;&lt;&gt;&lt;&lt;).</p>
 <p>A trial for the Flanker Task written with jsPsych might look like this:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;congruent&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">target_direction</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;congruent&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">target_direction</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>Note the use of the data parameter to add a property <code>stimulus_type</code> with the value <code>congruent</code> and a property <code>target_direction</code> with the value <code>left</code>. Having these properties recorded directly in the data simplifies data analysis, making it easy to aggregate data by <code>stimulus_type</code> and/or <code>target_direction</code>.</p>
 <h3 id="the-post_trial_gap-iti-parameter">The post_trial_gap (ITI) parameter<a class="headerlink" href="#the-post_trial_gap-iti-parameter" title="Permanent link">&para;</a></h3>
 <p>The default inter-trial interval (ITI) in jsPsych is 0 ms. This can be adjusted at the experiment-wide level by changing the <code>default_iti</code> parameter in <code>initJsPsych()</code>.</p>
 <p>The ITI can also be controlled at the trial level through the <code>post_trial_gap</code> parameter. Setting this parameter to a positive integer <em>x</em> will cause a blank screen to display after the trial for <em>x</em> milliseconds. Setting this parameter for a trial will override the <code>default_iti</code> value set in <code>initJsPsych</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;There will be a 1.5 second blank screen after this trial.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">1500</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;There will be a 1.5 second blank screen after this trial.&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">1500</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="the-on_start-parameter">The on_start parameter<a class="headerlink" href="#the-on_start-parameter" title="Permanent link">&para;</a></h3>
 <p>Immediately before a trial runs, there is an opportunity to run an arbitrary function through the <code>on_start</code> event handler. This event handler is passed a single argument containing an <em>editable</em> copy of the trial parameters. This function can therefore be used to alter the trial based on the state of the experiment, among other uses.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// when this trial runs, the on_start function will change the trial&#39;s stimulus and data parameters,</span><span class="w"></span>
-<span class="c1">// so the trial will display an incongruent Flanker stimulus with a right-facing central arrow</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;congruent&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">target_direction</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">stimulus</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&gt;&lt;&lt;&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">stimulus_type</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;incongruent&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">target_direction</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;right&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// when this trial runs, the on_start function will change the trial&#39;s stimulus and data parameters,</span>
+<span class="c1">// so the trial will display an incongruent Flanker stimulus with a right-facing central arrow</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;congruent&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">target_direction</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">on_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">stimulus</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&gt;&lt;&lt;&#39;</span><span class="p">;</span>
+<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">stimulus_type</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;incongruent&#39;</span><span class="p">;</span>
+<span class="w">    </span><span class="nx">trial</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">target_direction</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;right&#39;</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="the-on_finish-parameter">The on_finish parameter<a class="headerlink" href="#the-on_finish-parameter" title="Permanent link">&para;</a></h3>
 <p>After a trial is completed, there is an opportunity to run an arbitrary function through the <code>on_finish</code> event handler. This function is passed a single argument containing an <em>editable</em> copy of the data recorded for that trial. This function can therefore be used to update the state of the experiment based on the data collected, or modify the data collected.</p>
 <p>The <code>on_finish</code> function can be useful to calculate new data properties that were unknowable at the start of the trial. For example, with the Flanker Task example above, the <code>on_finish</code> function could check the response and use to this information to add a new property to the data called <code>correct</code>, which is either <code>true</code> or <code>false</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// in addition to all of the standard data collected for this trial, </span><span class="w"></span>
-<span class="c1">// this on_finish function adds a property called &#39;correct&#39; </span><span class="w"></span>
-<span class="c1">// which is either &#39;true&#39; or &#39;false&#39;</span><span class="w"></span>
-<span class="c1">// depending on the response that was made</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;congruent&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">target_direction</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">)){</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// in addition to all of the standard data collected for this trial, </span>
+<span class="c1">// this on_finish function adds a property called &#39;correct&#39; </span>
+<span class="c1">// which is either &#39;true&#39; or &#39;false&#39;</span>
+<span class="c1">// depending on the response that was made</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus_type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;congruent&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">target_direction</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">)){</span>
+<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="the-on_load-parameter">The on_load parameter<a class="headerlink" href="#the-on_load-parameter" title="Permanent link">&para;</a></h3>
 <p>The <code>on_load</code> callback function will trigger once the trial has completed loading. 
 For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. 
 This can be useful for changing various aspects of the page elements and their properties that would otherwise require modifying the plugin file.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_load</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// this will change the src attribute of the image after 500ms</span><span class="w"></span>
-<span class="w">    </span><span class="nx">setTimeout</span><span class="p">(</span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">      </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;img&#39;</span><span class="p">).</span><span class="nx">src</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;imgB.png&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"> </span><span class="mf">500</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;imgA.png&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_load</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="c1">// this will change the src attribute of the image after 500ms</span>
+<span class="w">    </span><span class="nx">setTimeout</span><span class="p">(</span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">      </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;img&#39;</span><span class="p">).</span><span class="nx">src</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;imgB.png&#39;</span>
+<span class="w">    </span><span class="p">},</span><span class="w"> </span><span class="mf">500</span><span class="p">);</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <h3 id="the-css_classes-parameter">The css_classes parameter<a class="headerlink" href="#the-css_classes-parameter" title="Permanent link">&para;</a></h3>
 <p>The <code>css_classes</code> parameter allows you to add an array of CSS class names to the jsPsych display element on that specific trial. 
 This allows you to create custom style and formatting rules that are only applied to specific trials. 
 If you want CSS rules that only apply to specific elements during a trial, you can use additional CSS selectors.</p>
-<div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">style</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">  </span><span class="p">.</span><span class="nc">flanker-stimulus</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">500</span><span class="kt">%</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">.</span><span class="nc">flanker-stimulus</span><span class="w"> </span><span class="p">#</span><span class="nn">prompt</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">18</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">.</span><span class="nc">fixation</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">80</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">style</span><span class="p">&gt;</span>
+<span class="w">  </span><span class="p">.</span><span class="nc">flanker-stimulus</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">500</span><span class="kt">%</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="w">  </span><span class="p">.</span><span class="nc">flanker-stimulus</span><span class="w"> </span><span class="p">#</span><span class="nn">prompt</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">18</span><span class="kt">px</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="w">  </span><span class="p">.</span><span class="nc">fixation</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">80</span><span class="kt">px</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
 <span class="p">&lt;/</span><span class="nt">style</span><span class="p">&gt;</span>
-<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;fixation&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="p">};</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">flanker_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;ArrowLeft&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;ArrowRight&quot;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&gt;&gt;&gt;&gt;&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;span id=&quot;prompt&quot;&gt;Press the left or right arrow key.&lt;/span&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;flanker-stimulus&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="p">};</span><span class="w"></span>
+<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;fixation&#39;</span><span class="p">]</span>
+<span class="w">  </span><span class="p">};</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">flanker_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;ArrowLeft&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;ArrowRight&quot;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&gt;&gt;&gt;&gt;&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;span id=&quot;prompt&quot;&gt;Press the left or right arrow key.&lt;/span&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;flanker-stimulus&#39;</span><span class="p">]</span>
+<span class="w">  </span><span class="p">};</span>
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
 <h3 id="the-save_trial_parameters-parameter">The save_trial_parameters parameter<a class="headerlink" href="#the-save_trial_parameters-parameter" title="Permanent link">&para;</a></h3>
 <p>The <code>save_trial_parameters</code> parameter allows you to tell jsPsych what parameters you want to be saved to the data. This can be used to override the parameter values that the plugin saves by default. You can add more parameter values to the data that are not normally saved, or remove parameter values that normally are saved. This can be especially useful when the parameter value is dynamic (i.e. a function) and you want to record the value that was used during the trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;color: orange; font-size: 48px; font-weight: bold;&quot;&gt;BLUE&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffle</span><span class="p">([</span><span class="s1">&#39;Yes&#39;</span><span class="p">,</span><span class="s1">&#39;No&#39;</span><span class="p">]);</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">200</span><span class="p">,</span><span class="mf">300</span><span class="p">,</span><span class="mf">400</span><span class="p">,</span><span class="mf">500</span><span class="p">],</span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">save_trial_parameters</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// save the randomly-selected button order and post trial gap duration to the trial data</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// don&#39;t save the stimulus</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;color: orange; font-size: 48px; font-weight: bold;&quot;&gt;BLUE&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffle</span><span class="p">([</span><span class="s1">&#39;Yes&#39;</span><span class="p">,</span><span class="s1">&#39;No&#39;</span><span class="p">]);</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">200</span><span class="p">,</span><span class="mf">300</span><span class="p">,</span><span class="mf">400</span><span class="p">,</span><span class="mf">500</span><span class="p">],</span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">save_trial_parameters</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="c1">// save the randomly-selected button order and post trial gap duration to the trial data</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="c1">// don&#39;t save the stimulus</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
@@ -2359,16 +2364,25 @@ <h2 id="data-collected-by-all-plugins">Data collected by all plugins<a class="he
 <h2 id="creating-a-new-plugin">Creating a new plugin<a class="headerlink" href="#creating-a-new-plugin" title="Permanent link">&para;</a></h2>
 <p>See our <a href="../../developers/plugin-development/">developer's guide for plugins</a> for information about how to create a new plugin.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../timeline/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Creating an Experiment: The Timeline" rel="prev">
@@ -2427,7 +2441,7 @@ <h2 id="creating-a-new-plugin">Creating a new plugin<a class="headerlink" href="
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2436,7 +2450,7 @@ <h2 id="creating-a-new-plugin">Creating a new plugin<a class="headerlink" href="
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2449,11 +2463,13 @@ <h2 id="creating-a-new-plugin">Creating a new plugin<a class="headerlink" href="
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/progress-bar/index.html b/7.3/overview/progress-bar/index.html
old mode 100755
new mode 100644
index 26633d006c..0af0b64127
--- a/7.3/overview/progress-bar/index.html
+++ b/7.3/overview/progress-bar/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/progress-bar/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1929,109 +1932,120 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/progress-bar.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="automatic-progress-bar">Automatic Progress Bar<a class="headerlink" href="#automatic-progress-bar" title="Permanent link">&para;</a></h1>
 <p>jsPsych can show a progress bar at the top of the experiment page indicating the participant's overall completion progress. The progress bar is rendered outside the jsPsych display element, and it requires the <code>jspsych.css</code> file to be loaded on the page. As of version 6.0, the progress bar looks like this:</p>
 <p><img alt="Progressbar Screenshot" src="../../img/progress_bar.png" /></p>
 <p>To show the progress bar, set the <code>show_progress_bar</code> option in <code>initJsPsych</code> to <code>true</code>:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">});</span>
 </code></pre></div>
 <p>The progress bar updates after every node on the top-level timeline updates. This avoids distracting updates in the middle of trials that are composed of multiple plugins, or confusing updates due to looping or conditional structures that may or may not execute depending on the actions of the participant. This also allows some flexibility for the programmer; by nesting timelines in a deliberate manner, the timing of progress bar updates can be controlled.</p>
 <h2 id="manual-control">Manual Control<a class="headerlink" href="#manual-control" title="Permanent link">&para;</a></h2>
 <p>The progress bar can also be manually controlled using the function <code>jsPsych.setProgressBar()</code>. This function takes a numeric value between 0 and 1, representing the proportion of the progress bar to fill.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Almost done...&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="mf">0.85</span><span class="p">);</span><span class="w"> </span><span class="c1">// set progress bar to 85% full.</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Almost done...&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="mf">0.85</span><span class="p">);</span><span class="w"> </span><span class="c1">// set progress bar to 85% full.</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>You can also get the current value of the progress bar with <code>jsPsych.getProgressBarCompleted()</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">proportion_complete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgressBarCompleted</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">proportion_complete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgressBarCompleted</span><span class="p">();</span>
 </code></pre></div>
 <p>If you are going to use manual progress bar control, you may want to disable the automatic progress bar updates by setting the <code>auto_update_progress_bar</code> property in <code>initJsPsych()</code> to <code>false</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_update_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_update_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="p">});</span>
 </code></pre></div>
 <p>Here's a complete example showing how to use these functions and <code>initJsPsych()</code> settings to manually update the progress bar:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_update_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">n_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">5</span><span class="p">;</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">start</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Press any key to start!&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// set progress bar to 0 at the start of experiment</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="mf">0</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is a trial!&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// at the end of each trial, update the progress bar</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// based on the current value and the proportion to update for each trial</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">curr_progress_bar_value</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgressBarCompleted</span><span class="p">();</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="nx">curr_progress_bar_value</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="p">(</span><span class="mf">1</span><span class="o">/</span><span class="nx">n_trials</span><span class="p">));</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="nx">n_trials</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">done</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Done!&#39;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">start</span><span class="p">,</span><span class="w"> </span><span class="nx">trials</span><span class="p">,</span><span class="w"> </span><span class="nx">done</span><span class="p">]);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_update_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="p">});</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">n_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">5</span><span class="p">;</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">start</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Press any key to start!&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">on_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="c1">// set progress bar to 0 at the start of experiment</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="mf">0</span><span class="p">);</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is a trial!&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="c1">// at the end of each trial, update the progress bar</span>
+<span class="w">        </span><span class="c1">// based on the current value and the proportion to update for each trial</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">curr_progress_bar_value</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgressBarCompleted</span><span class="p">();</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="nx">curr_progress_bar_value</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="p">(</span><span class="mf">1</span><span class="o">/</span><span class="nx">n_trials</span><span class="p">));</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="nx">n_trials</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">done</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Done!&#39;</span>
+<span class="p">};</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">start</span><span class="p">,</span><span class="w"> </span><span class="nx">trials</span><span class="p">,</span><span class="w"> </span><span class="nx">done</span><span class="p">]);</span>
 </code></pre></div>
 <h2 id="custom-text">Custom Text<a class="headerlink" href="#custom-text" title="Permanent link">&para;</a></h2>
 <p>By default, jsPsych adds the text "Completion Progress" to the left of the progress bar. You can specify custom text using the <code>message_progress_bar</code> parameter in <code>initJsPsych</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// support for different spoken languages</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">message_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Porcentaje completo&#39;</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// support for different spoken languages</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">message_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Porcentaje completo&#39;</span>
+<span class="p">});</span>
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="c1">// no message</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">message_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&#39;</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// no message</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">message_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&#39;</span>
+<span class="p">});</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../exclude-browser/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Exclude Participants Based on Browser Features" rel="prev">
@@ -2090,7 +2104,7 @@ <h2 id="custom-text">Custom Text<a class="headerlink" href="#custom-text" title=
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2099,7 +2113,7 @@ <h2 id="custom-text">Custom Text<a class="headerlink" href="#custom-text" title=
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2112,11 +2126,13 @@ <h2 id="custom-text">Custom Text<a class="headerlink" href="#custom-text" title=
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/prolific/index.html b/7.3/overview/prolific/index.html
old mode 100755
new mode 100644
index f5ee28b25c..13b79f6ab6
--- a/7.3/overview/prolific/index.html
+++ b/7.3/overview/prolific/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/prolific/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1969,16 +1972,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/prolific.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="integrating-with-prolific">Integrating with Prolific<a class="headerlink" href="#integrating-with-prolific" title="Permanent link">&para;</a></h1>
 <p><a href="https://www.prolific.co/?ref=5JCXZPVU">Prolific</a> is a participant recruitment service aimed at research. Integrating a jsPsych experiment with Prolific requires capturing the participant's ID and sending the participant to a completion URL at the end of the experiment.</p>
 <h2 id="capturing-the-participant-id-study-id-and-session-id">Capturing the Participant ID, Study ID, and Session ID<a class="headerlink" href="#capturing-the-participant-id-study-id-and-session-id" title="Permanent link">&para;</a></h2>
@@ -1986,24 +1991,24 @@ <h2 id="capturing-the-participant-id-study-id-and-session-id">Capturing the Part
 <p><img alt="Prolific screenshot" src="../../img/prolific-study-link.png" /></p>
 <p>This will append information about the participant's prolific ID (<code>PROLIFIC_PID</code>), the study's ID (<code>STUDY_ID</code>), and the session ID (<code>SESSION_ID</code>) to the URL that participants use to access your experiment. </p>
 <p>We can capture these variables with jsPsych, and add them to jsPsych's data. This can be done anywhere in your code. This code does not need to run as part of your experiment timeline.</p>
-<div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="w">  </span><span class="c1">// capture info from Prolific</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">subject_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;PROLIFIC_PID&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">study_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;STUDY_ID&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">session_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;SESSION_ID&#39;</span><span class="p">);</span><span class="w"></span>
+<span class="w">  </span><span class="c1">// capture info from Prolific</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">subject_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;PROLIFIC_PID&#39;</span><span class="p">);</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">study_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;STUDY_ID&#39;</span><span class="p">);</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">session_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;SESSION_ID&#39;</span><span class="p">);</span>
 
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">subject_id</span><span class="o">:</span><span class="w"> </span><span class="nx">subject_id</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">study_id</span><span class="o">:</span><span class="w"> </span><span class="nx">study_id</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">session_id</span><span class="o">:</span><span class="w"> </span><span class="nx">session_id</span><span class="w"></span>
-<span class="w">  </span><span class="p">});</span><span class="w"></span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">subject_id</span><span class="o">:</span><span class="w"> </span><span class="nx">subject_id</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">study_id</span><span class="o">:</span><span class="w"> </span><span class="nx">study_id</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">session_id</span><span class="o">:</span><span class="w"> </span><span class="nx">session_id</span>
+<span class="w">  </span><span class="p">});</span>
 
-<span class="w">  </span><span class="c1">// create the rest of the experiment</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[...]</span><span class="w"></span>
+<span class="w">  </span><span class="c1">// create the rest of the experiment</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[...]</span>
 
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">)</span><span class="w"></span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">)</span>
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
 <h2 id="completing-the-experiment">Completing the Experiment<a class="headerlink" href="#completing-the-experiment" title="Permanent link">&para;</a></h2>
@@ -2017,33 +2022,42 @@ <h2 id="completing-the-experiment">Completing the Experiment<a class="headerlink
 <h3 id="participant-clicks-a-link">Participant clicks a link<a class="headerlink" href="#participant-clicks-a-link" title="Permanent link">&para;</a></h3>
 <p>One option is to create a trial that contains a link that the participant clicks to end the experiment and return to Prolific. For example, the <code>html-keyboard-response</code> plugin can be used to display text that includes a link. This could go on a debriefing page.</p>
 <p>Here's an example trial that could be used. Note that <code>choices</code> is set to <code>"NO_KEYS"</code>, which will prevent the participant from continuing past this point in the experiment.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">final_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">final_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;You&#39;ve finished the last task. Thanks for participating!&lt;/p&gt;</span>
-<span class="sb">    &lt;p&gt;&lt;a href=&quot;https://app.prolific.co/submissions/complete?cc=XXXXXXX&quot;&gt;Click here to return to Prolific and complete the study&lt;/a&gt;.&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">    &lt;p&gt;&lt;a href=&quot;https://app.prolific.co/submissions/complete?cc=XXXXXXX&quot;&gt;Click here to return to Prolific and complete the study&lt;/a&gt;.&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="automatically-redirect">Automatically redirect<a class="headerlink" href="#automatically-redirect" title="Permanent link">&para;</a></h3>
 <p>A second option is to automatically redirect the participant to the completion URL when the experiment is finished. You could do this in a number of places in the jsPsych timeline.</p>
 <p>Here's an example using the <code>on_finish</code> event for the entire experiment.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="nb">window</span><span class="p">.</span><span class="nx">location</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s2">&quot;https://app.prolific.co/submissions/complete?cc=XXXXXXX&quot;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="nb">window</span><span class="p">.</span><span class="nx">location</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s2">&quot;https://app.prolific.co/submissions/complete?cc=XXXXXXX&quot;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../progress-bar/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Automatic Progress Bar" rel="prev">
@@ -2102,7 +2116,7 @@ <h3 id="automatically-redirect">Automatically redirect<a class="headerlink" href
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2111,7 +2125,7 @@ <h3 id="automatically-redirect">Automatically redirect<a class="headerlink" href
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2124,11 +2138,13 @@ <h3 id="automatically-redirect">Automatically redirect<a class="headerlink" href
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/record-browser-interactions/index.html b/7.3/overview/record-browser-interactions/index.html
old mode 100755
new mode 100644
index 0e85c7e291..5fba4ddf84
--- a/7.3/overview/record-browser-interactions/index.html
+++ b/7.3/overview/record-browser-interactions/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/record-browser-interactions/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1869,43 +1872,54 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/record-browser-interactions.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="record-browser-interactions">Record browser interactions<a class="headerlink" href="#record-browser-interactions" title="Permanent link">&para;</a></h1>
 <p>Participants in an online experiment have the freedom to multitask while performing an experiment. jsPsych automatically records information about when the user clicks on a window that is not the experiment, and about when the user exits full screen mode if the experiment is running in full screen mode. This data is stored separately from the main experiment data, and can be accessed with <a href="../../reference/jspsych-data/#jspsychdatagetinteractiondata">jsPsych.data.getInteractionData()</a>.</p>
 <p>Each time the user leaves the experiment window, returns to the experiment window, exits full screen mode, or enters full screen mode, the event is recorded in the interaction data. Each event has the following structure.</p>
-<div class="highlight"><pre><span></span><code><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">event</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;focus&#39;</span><span class="p">,</span><span class="w"> </span><span class="c1">// &#39;focus&#39; or &#39;blur&#39; or &#39;fullscreenenter&#39; or &#39;fullscreenexit&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial</span><span class="o">:</span><span class="w"> </span><span class="mf">12</span><span class="p">,</span><span class="w"> </span><span class="c1">// the index of the active trial when the event happened</span><span class="w"></span>
-<span class="w">  </span><span class="nx">time</span><span class="o">:</span><span class="w"> </span><span class="mf">1240543</span><span class="w"> </span><span class="c1">// time in ms since the start of the experiment</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="p">{</span>
+<span class="w">  </span><span class="nx">event</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;focus&#39;</span><span class="p">,</span><span class="w"> </span><span class="c1">// &#39;focus&#39; or &#39;blur&#39; or &#39;fullscreenenter&#39; or &#39;fullscreenexit&#39;</span>
+<span class="w">  </span><span class="nx">trial</span><span class="o">:</span><span class="w"> </span><span class="mf">12</span><span class="p">,</span><span class="w"> </span><span class="c1">// the index of the active trial when the event happened</span>
+<span class="w">  </span><span class="nx">time</span><span class="o">:</span><span class="w"> </span><span class="mf">1240543</span><span class="w"> </span><span class="c1">// time in ms since the start of the experiment</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>You can specify a custom function, in the initJsPsych() method, that is called whenever one of these events occurs</p>
-<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_interaction_data_update</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">data</span><span class="p">))</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_interaction_data_update</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">data</span><span class="p">))</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../events/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Events" rel="prev">
@@ -1964,7 +1978,7 @@ <h1 id="record-browser-interactions">Record browser interactions<a class="header
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -1973,7 +1987,7 @@ <h1 id="record-browser-interactions">Record browser interactions<a class="header
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -1986,11 +2000,13 @@ <h1 id="record-browser-interactions">Record browser interactions<a class="header
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/running-experiments/index.html b/7.3/overview/running-experiments/index.html
old mode 100755
new mode 100644
index 94a207229a..7233a4a1a1
--- a/7.3/overview/running-experiments/index.html
+++ b/7.3/overview/running-experiments/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/running-experiments/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2023,16 +2026,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/running-experiments.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="running-experiments">Running Experiments<a class="headerlink" href="#running-experiments" title="Permanent link">&para;</a></h1>
 <p>You can run your jsPsych experiment:</p>
 <p><strong>Offline</strong>, by opening the HTML file directly in the browser using the <code>file://</code> protocol.</p>
@@ -2065,15 +2070,15 @@ <h3 id="permanent-data-storage">Permanent data storage<a class="headerlink" href
 <p>As explained in the <a href="../data/#data-in-jspsych-permanent-and-non-permanent-data">Data Storage, Aggregation, and Manipulation</a> page, jsPsych stores information in the participant's browser. While running an experiment offline, you won't be able to send the data to a database. However you can still see the data that jsPsych collects by saving it as a local file (using <a href="../../reference/jspsych-data/#localsave"><code>jsPsych.data.get().localSave</code></a>), displaying it in the webpage at the end of the experiment (using <a href="../../reference/jspsych-data/#jspsychdatadisplaydata"><code>jsPsych.data.displayData</code></a>), or printing it to the browser's console (using <a href="https://www.w3schools.com/jsref/met_console_log.asp"><code>console.log</code></a>). </p>
 <p>Permanent data storage is also necessary when the code that runs the experiment depends on information that can't be known in advance, and that changes throughout data collection. Some common examples of this in cognitive behavioral research are <strong>version counterbalancing</strong>, where the experiment code needs to access and update the history of version assignment in order to determine which version should be assigned, and <strong>multi-session/training studies</strong>, where the experiment might need to access and update information about each participant like their current session number, task difficulty level, etc. </p>
 <p>Doing these things in an automated way requires the use of a server. While developing and testing your experiment offline, you might choose to simulate some of these things and then implement them properly once you move your experiment online. For instance, you could <a href="../../reference/jspsych-randomization/#jspsychrandomizationsamplewithoutreplacement">randomize</a> instead of counterbalancing version assignment:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">versions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">random_version</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">(</span><span class="nx">versions</span><span class="p">,</span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">versions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">random_version</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">(</span><span class="nx">versions</span><span class="p">,</span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
 </code></pre></div>
 <p>And use <a href="../../reference/jspsych-data/#jspsychdatageturlvariable">URL query parameters</a> to pass in variables like session number and difficulty level:</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// add the variables onto the end of the URL that appears in the browser when you open the file </span><span class="w"></span>
-<span class="c1">// e.g., file:///C:/my_experiment.html?id=1&amp;sess=2&amp;diff=3</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">participant_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;id&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">session</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;sess&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">difficulty</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;diff&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// add the variables onto the end of the URL that appears in the browser when you open the file </span>
+<span class="c1">// e.g., file:///C:/my_experiment.html?id=1&amp;sess=2&amp;diff=3</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">participant_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;id&#39;</span><span class="p">);</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">session</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;sess&#39;</span><span class="p">);</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">difficulty</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;diff&#39;</span><span class="p">);</span>
 </code></pre></div>
 <h2 id="online">Online<a class="headerlink" href="#online" title="Permanent link">&para;</a></h2>
 <h3 id="hosting-the-experiment-and-saving-the-data">Hosting the Experiment and Saving the Data<a class="headerlink" href="#hosting-the-experiment-and-saving-the-data" title="Permanent link">&para;</a></h3>
@@ -2097,16 +2102,25 @@ <h3 id="recruiting-participants">Recruiting Participants<a class="headerlink" hr
 </ul>
 <p>Like SONA, Prolific and MTurk use URL query parameters to get participant information, and redirection to specific URLs to mark participants as having finished the study. jsPsych includes <a href="../../reference/jspsych-turk/">convenience functions for interacting with MTurk participants</a>. Information about integrating with Prolific can be found in the researcher support section of their website.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../simulation/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Simulation Modes" rel="prev">
@@ -2165,7 +2179,7 @@ <h3 id="recruiting-participants">Recruiting Participants<a class="headerlink" hr
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2174,7 +2188,7 @@ <h3 id="recruiting-participants">Recruiting Participants<a class="headerlink" hr
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2187,11 +2201,13 @@ <h3 id="recruiting-participants">Recruiting Participants<a class="headerlink" hr
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/simulation/index.html b/7.3/overview/simulation/index.html
old mode 100755
new mode 100644
index 2599234434..1d339c9435
--- a/7.3/overview/simulation/index.html
+++ b/7.3/overview/simulation/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/simulation/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2105,16 +2108,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/simulation.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="simulation-modes">Simulation Modes<a class="headerlink" href="#simulation-modes" title="Permanent link">&para;</a></h1>
 <p><em>Added in 7.1</em></p>
 <p>Simulation mode allows you run your experiment automatically and generate artificial data. </p>
@@ -2125,12 +2130,12 @@ <h1 id="simulation-modes">Simulation Modes<a class="headerlink" href="#simulatio
 </div>
 <h2 id="getting-started">Getting Started<a class="headerlink" href="#getting-started" title="Permanent link">&para;</a></h2>
 <p>To use simulation mode, replace <code>jsPsych.run()</code> with <code>jsPsych.simulate()</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 </code></pre></div>
 <p>This will run jsPsych in the default <code>data-only</code> simulation mode. 
 To use the <code>visual</code> simulation mode you can specify the second parameter.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;data-only&quot;</span><span class="p">);</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;visual&quot;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;data-only&quot;</span><span class="p">);</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;visual&quot;</span><span class="p">);</span>
 </code></pre></div>
 <h2 id="what-happens-in-simulation-mode">What happens in simulation mode<a class="headerlink" href="#what-happens-in-simulation-mode" title="Permanent link">&para;</a></h2>
 <p>In simulation mode, plugins call their <code>simulate()</code> method instead of calling their <code>trial()</code> method.
@@ -2155,15 +2160,15 @@ <h2 id="controlling-simulation-mode-with-simulation_options">Controlling simulat
 <p>The parameters for simulation mode can be set using the <code>simulation_options</code> parameter in both <code>jsPsych.simulate()</code> and at the level of individual trials.</p>
 <h3 id="trial-level-options">Trial-level options<a class="headerlink" href="#trial-level-options" title="Permanent link">&para;</a></h3>
 <p>You can specify simulation options for an individual trial by setting the <code>simulation_options</code> parameter.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Hello!&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">simulation_options</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Hello!&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">simulation_options</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>Currently the three options that are available are <code>data</code>, <code>mode</code>, and <code>simulate</code>.</p>
 <h4 id="data"><code>data</code><a class="headerlink" href="#data" title="Permanent link">&para;</a></h4>
@@ -2183,56 +2188,56 @@ <h4 id="functions-and-timeline-variables">Functions and timeline variables<a cla
 <p>The <code>simulation_options</code> parameter is compatible with both <a href="../dynamic-parameters/">dynamic parameters</a> and <a href="../timeline/#timeline-variables">timeline variables</a>. 
 Dynamic parameters can be especially useful if you want to randomize the data for each run of the simulation. 
 For example, you can specify the <code>rt</code> as a sample from an ExGaussian distribution.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Hello!&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">simulation_options</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="p">()=&gt;{</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExGaussian</span><span class="p">(</span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">50</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="o">/</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">)</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Hello!&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">simulation_options</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="p">()=&gt;{</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExGaussian</span><span class="p">(</span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">50</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="o">/</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">)</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="experiment-level-options">Experiment-level options<a class="headerlink" href="#experiment-level-options" title="Permanent link">&para;</a></h3>
 <p>You can also control the parameters for simulation by passing in an object to the <code>simulation_options</code> argument of <code>jsPsych.simulate()</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">simulation_options</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;visual&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">simulation_options</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">simulation_options</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;visual&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">simulation_options</span><span class="p">)</span>
 </code></pre></div>
 <p>The above example will set the <code>rt</code> for any trial that doesn't have its own <code>simulation_options</code> specified to <code>200</code>. 
 This could be useful, for example, to create a very fast preview of the experiment to verify that everything is displaying correctly without having to wait through longer trials.</p>
 <p>You can also specify sets of parameters by name using the experiment-level simulation options.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">simulation_options</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">long_response</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExGaussian</span><span class="p">(</span><span class="mf">5000</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="o">/</span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">)</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;This is gonna take a bit.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">simulation_options</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;long_response&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial</span><span class="p">);</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;visual&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">simulation_options</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">simulation_options</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">default</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">long_response</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExGaussian</span><span class="p">(</span><span class="mf">5000</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="o">/</span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">)</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;This is gonna take a bit.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">simulation_options</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;long_response&#39;</span>
+<span class="p">}</span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial</span><span class="p">);</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">simulate</span><span class="p">(</span><span class="nx">timeline</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;visual&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">simulation_options</span><span class="p">)</span>
 </code></pre></div>
 <p>In the example above, we specified the <code>simulation_options</code> for <code>trial</code> using a string (<code>'long_response'</code>).
 This will look up the corresponding set of options in the experiment-level <code>simulation_options</code>.</p>
@@ -2250,16 +2255,25 @@ <h2 id="current-limitations">Current Limitations<a class="headerlink" href="#cur
 Some plugins are also not supported. 
 This will be noted on their documentation page. </p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../data/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Data Storage, Aggregation, and Manipulation" rel="prev">
@@ -2318,7 +2332,7 @@ <h2 id="current-limitations">Current Limitations<a class="headerlink" href="#cur
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2327,7 +2341,7 @@ <h2 id="current-limitations">Current Limitations<a class="headerlink" href="#cur
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2340,11 +2354,13 @@ <h2 id="current-limitations">Current Limitations<a class="headerlink" href="#cur
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/style/index.html b/7.3/overview/style/index.html
old mode 100755
new mode 100644
index ee98c248cf..81bd515c8d
--- a/7.3/overview/style/index.html
+++ b/7.3/overview/style/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/style/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1997,82 +2000,84 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/style.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="controlling-visual-appearance">Controlling Visual Appearance<a class="headerlink" href="#controlling-visual-appearance" title="Permanent link">&para;</a></h1>
 <p>Your experiment's style and formatting comes from the CSS (cascading style sheet) rules that are stored in the jspsych.css file, and the browser's defaults. There are a few ways to change the style and formatting in your experiment. The method that you choose is partly a matter of personal preference. It might also depend on whether you want the style/formatting change(s) to apply to <em>specific trials</em>, to <em>the whole experiment</em> (HTML page), or across <em>different experiments</em>. This section discusses the different ways of incorporating CSS into your jsPsych experiment. You can also see <a href="https://www.w3schools.com/html/html_css.asp">this page about adding CSS to web pages</a> to learn more.</p>
 <h2 id="inline-css">Inline CSS<a class="headerlink" href="#inline-css" title="Permanent link">&para;</a></h2>
 <p>Whenever you're using a parameter that accepts an HTML-formatted string, you have the option to include inline CSS. Inline CSS is a way of adding style and formatting directly into a specific HTML element using its <a href="https://www.w3schools.com/tags/att_style.asp">"style" attribute</a>. This is a good option for when you want to make few and/or simple style changes to an HTML trial parameter.</p>
 <p>To change an element's style using inline CSS, you can set the element's "style" attribute to a string that contains the CSS parameters that you want to change, along with the values that you want to use. The syntax is " &lt;parameter-name&gt; : &lt;parameter-value&gt; ;". </p>
 <p>In the example below, the stimulus font size is set to 30px and the text color is set to red. These changes will <em>only</em> be applied to this stimulus text in this specific trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size:30px;color:red;&quot;&gt;hello world!&lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size:30px;color:red;&quot;&gt;hello world!&lt;/p&gt;&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>You can also use a <a href="dynamic-parameters">dynamic parameter</a> to combine inline CSS and trial-specific variables. This allows you to easily apply the same inline CSS to multiple trials. Here's an example using a dynamic stimulus parameter and <a href="../timeline/#timeline-variables">timeline variables</a>:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">stim</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size:30px;font-weight:bold;&quot;&gt;&#39;</span><span class="o">+</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;text&#39;</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;&lt;/p&gt;&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">stim</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Welcome&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;to&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;the&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;experiment!&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">stim</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size:30px;font-weight:bold;&quot;&gt;&#39;</span><span class="o">+</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;text&#39;</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;&lt;/p&gt;&#39;</span><span class="p">;</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">stim</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Welcome&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;to&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;the&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;experiment!&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="adding-css-rules">Adding CSS rules<a class="headerlink" href="#adding-css-rules" title="Permanent link">&para;</a></h2>
 <p>You may want to add a lot of different CSS changes to your experiment, re-use the same change(s) across lots of different trials, and/or separate the style/formatting from the HTML string. In these cases, you might find it useful to create CSS rules rather than using inline CSS. </p>
 <p>Creating CSS rules is a lot like using inline CSS, except that you also need to use a <a href="https://www.w3schools.com/css/css_selectors.asp">CSS selector</a>. This is because your CSS rules aren't attached to any specific HTML element (unlike inline CSS), so you need to tell the browser which element(s) the style rules should apply to. The syntax is "css-selector { &lt;parameter-name&gt; : &lt;parameter-value&gt; ; }". </p>
 <p>In the example below, the CSS selector "p" tells the browser to apply the font size change to any text that is inside of a &lt;p&gt; element.</p>
-<div class="highlight"><pre><span></span><code><span class="nt">p</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">30</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nt">p</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">30</span><span class="kt">px</span><span class="p">;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>You can make more specific changes using CSS rules. The specificity will depend on the CSS selectors that are used. In addition to using the <a href="https://www.w3schools.com/cssref/sel_element.asp">tag name</a> (e.g. "p"), other common CSS selectors include the element's <a href="https://www.w3schools.com/html/html_id.asp">ID</a> or <a href="https://www.w3schools.com/html/html_classes.asp">class</a>. If you are selecting an element using it's ID, then the CSS selector needs to have a # in front of the ID, e.g. "#stimulus". If you are selecting elements based on their class, then you need to include a . in front of the class, e.g. ".large-text".</p>
 <p>In the example below, the "#stimulus" CSS selector means that the width change will only affect elements with the "stimulus" ID, and the ".large-text" CSS selector means that the font size change will only affect elements that have the "large-text" class.</p>
 <div class="highlight"><pre><span></span><code><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span>
-<span class="w">    </span><span class="nt">width</span><span class="o">:</span><span class="w"> </span><span class="nt">300px</span><span class="o">;</span><span class="w"></span>
-<span class="err">}</span><span class="w"></span>
-<span class="p">.</span><span class="nc">large-text</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">200</span><span class="kt">%</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="nt">width</span><span class="o">:</span><span class="w"> </span><span class="nt">300px</span><span class="o">;</span>
+<span class="err">}</span>
+<span class="p">.</span><span class="nc">large-text</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">200</span><span class="kt">%</span><span class="p">;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>It is possible to create even more specific CSS selectors, for instance by combining tags, IDs, and/or classes. For example, let's say that you are showing feedback text to participants, and that this text is inside of a &lt;p&gt; tag. You could add the ID "correct" to the &lt;p&gt; element for correct response feedback, and the ID "incorrect" to the &lt;p&gt; element for incorrect response feedback. Then you can define separate styles for correct and incorrect feedback text like this:</p>
-<div class="highlight"><pre><span></span><code><span class="nt">p</span><span class="p">#</span><span class="nn">incorrect</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">red</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="nt">p</span><span class="p">#</span><span class="nn">correct</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">green</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nt">p</span><span class="p">#</span><span class="nn">incorrect</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">red</span><span class="p">;</span>
+<span class="p">}</span>
+<span class="nt">p</span><span class="p">#</span><span class="nn">correct</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">green</span><span class="p">;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>See <a href="https://www.w3schools.com/cssref/css_selectors.asp">this page about CSS selectors</a> for a complete reference of CSS selector patterns and their meanings.</p>
 <h3 id="with-style-tags">With style tags<a class="headerlink" href="#with-style-tags" title="Permanent link">&para;</a></h3>
 <p>You can add CSS rules to your HTML page by putting them inside of &lt;style&gt; tags. These rules will be applied to your <em>whole experiment</em>. This method can be useful for making general changes to the way that your experiment looks. </p>
 <p>In the example below, the default font size is set to 25px throughout the experiment. This will overrule the default font size of 18px that is set in the jspsych.css file.</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">style</span><span class="p">&gt;</span><span class="w"> </span>
-<span class="w">    </span><span class="p">.</span><span class="nc">jspsych-display-element</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">25</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="p">.</span><span class="nc">jspsych-display-element</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">25</span><span class="kt">px</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span>
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">style</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2080,23 +2085,23 @@ <h3 id="with-a-stylesheet">With a stylesheet<a class="headerlink" href="#with-a-
 <p>CSS rules can also be applied to your experiment with a link to an external CSS file. This is the same method that is usually used to apply the style from jspsych.css to an experiment. These rules will be applied to your <em>whole experiment</em>. You may find it useful to use a custom stylesheet when you want to re-use the same CSS rules across <em>multiple experiments</em> (HTML files).</p>
 <p>This example shows how to add a custom CSS file in addition to the styles provided in jspsych.css. In this example, the custom CSS file is called "my_experiment_style.css" and it is located in the same directory as your HTML file.</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;my_experiment_style.css&quot;</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>Below are the some example contents of an external CSS file, like the "my_experiment_style.css" from the example above. This CSS will (1) change the page background color to black, (2) change the default font to 25px and white, and (3) limit the width of the page content so that it can only take up to 80% of its normal width. </p>
-<div class="highlight"><pre><span></span><code><span class="nt">body</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">background-color</span><span class="p">:</span><span class="w"> </span><span class="kc">black</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="p">.</span><span class="nc">jspsych-display-element</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">25</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">white</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="p">.</span><span class="nc">jspsych-content</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nt">body</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">background-color</span><span class="p">:</span><span class="w"> </span><span class="kc">black</span><span class="p">;</span>
+<span class="p">}</span>
+<span class="p">.</span><span class="nc">jspsych-display-element</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">25</span><span class="kt">px</span><span class="p">;</span>
+<span class="w">  </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">white</span><span class="p">;</span>
+<span class="p">}</span>
+<span class="p">.</span><span class="nc">jspsych-content</span><span class="w"> </span><span class="p">{</span>
 <span class="w">  </span><span class="k">max-width</span><span class="p">:</span><span class="w"> </span><span class="mi">80</span><span class="kt">%</span><span class="p">;</span><span class="w"> </span>
-<span class="p">}</span><span class="w"></span>
+<span class="p">}</span>
 </code></pre></div>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
@@ -2106,22 +2111,22 @@ <h3 id="using-the-css_classes-trial-parameter">Using the css_classes trial param
 <p>CSS rules can also be applied in a trial-specific way using the <code>css_classes</code> parameter. This parameter will apply one or more class to the &lt;div&gt; element that holds all of the jsPsych page content during that specific trial. This way you can treat CSS styles just like any other trial parameter. </p>
 <p>You can use a static <code>css_classes</code> parameter value if you always want to apply the same CSS rules to the trial. In the 'fixation' example below, separating the style rules from the <code>stimulus</code> string makes the code a little bit 'cleaner', and this makes it easier to re-use the same style rules in other parts of the experiment.</p>
 <div class="highlight"><pre><span></span><code> <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">style</span><span class="p">&gt;</span><span class="w"> </span>
-<span class="w">    </span><span class="p">.</span><span class="nc">fixation</span><span class="w"> </span><span class="p">{</span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">90</span><span class="kt">px</span><span class="p">;</span><span class="w"> </span><span class="k">font-weight</span><span class="p">:</span><span class="w"> </span><span class="kc">bold</span><span class="p">;</span><span class="w"> </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">gray</span><span class="p">;}</span><span class="w"></span>
+<span class="w">    </span><span class="p">.</span><span class="nc">fixation</span><span class="w"> </span><span class="p">{</span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">90</span><span class="kt">px</span><span class="p">;</span><span class="w"> </span><span class="k">font-weight</span><span class="p">:</span><span class="w"> </span><span class="kc">bold</span><span class="p">;</span><span class="w"> </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">gray</span><span class="p">;}</span>
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">style</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
-<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;fixation&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="c1">// ...</span><span class="w"></span>
+<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;fixation&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+<span class="c1">// ...</span>
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>You may want the  <code>css_classes</code> parameter to vary across trials. If so, you can turn it into a <a href="dynamic-parameters">dynamic parameter</a> or use <a href="../timeline/#timeline-variables">timeline variables</a> (see examples below). </p>
@@ -2142,61 +2147,61 @@ <h3 id="using-the-css_classes-trial-parameter">Using the css_classes trial param
 </div>
 <p>In the example below, the CSS selector <code>.left-align #stimulus</code> selects the element with the ID "stimulus" that is <em>inside</em> of an element with the class "left-align".</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">style</span><span class="p">&gt;</span><span class="w"> </span>
-<span class="w">    </span><span class="p">.</span><span class="nc">left-align</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">text-align</span><span class="p">:</span><span class="w"> </span><span class="kc">left</span><span class="p">;</span><span class="w"> </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">600</span><span class="kt">px</span><span class="p">;}</span><span class="w"></span>
-<span class="w">    </span><span class="p">.</span><span class="nc">right-align</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">text-align</span><span class="p">:</span><span class="w"> </span><span class="kc">right</span><span class="p">;</span><span class="w"> </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">600</span><span class="kt">px</span><span class="p">;}</span><span class="w"></span>
+<span class="w">    </span><span class="p">.</span><span class="nc">left-align</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">text-align</span><span class="p">:</span><span class="w"> </span><span class="kc">left</span><span class="p">;</span><span class="w"> </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">600</span><span class="kt">px</span><span class="p">;}</span>
+<span class="w">    </span><span class="p">.</span><span class="nc">right-align</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">text-align</span><span class="p">:</span><span class="w"> </span><span class="kc">right</span><span class="p">;</span><span class="w"> </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">600</span><span class="kt">px</span><span class="p">;}</span>
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">style</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
-<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p id=&quot;stimulus&quot;&gt;This is the stimulus.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;This text will not be affected by the CSS classes &#39;</span><span class="o">+</span><span class="w"></span>
-<span class="w">            </span><span class="s1">&#39;because it does not have the &quot;stimulus&quot; ID.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;css_classes&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">    </span><span class="p">}],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;left-align&#39;</span><span class="p">]},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;right-align&#39;</span><span class="p">]}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="c1">// ...</span><span class="w"></span>
+<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p id=&quot;stimulus&quot;&gt;This is the stimulus.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;This text will not be affected by the CSS classes &#39;</span><span class="o">+</span>
+<span class="w">            </span><span class="s1">&#39;because it does not have the &quot;stimulus&quot; ID.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;css_classes&#39;</span><span class="p">)</span>
+<span class="w">    </span><span class="p">}],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;left-align&#39;</span><span class="p">]},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;right-align&#39;</span><span class="p">]}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
+<span class="c1">// ...</span>
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>It's also possible to pass multiple class names to the <code>css_classes</code> parameter. This can be useful for creating conditions that involve crossing different style-related factors. This example shows you to combine two text alignment and two text color factors to produce four different stimulus conditions:</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">style</span><span class="p">&gt;</span><span class="w"> </span>
-<span class="w">    </span><span class="p">.</span><span class="nc">left-align</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">text-align</span><span class="p">:</span><span class="w"> </span><span class="kc">left</span><span class="p">;</span><span class="w"> </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">600</span><span class="kt">px</span><span class="p">;}</span><span class="w"></span>
-<span class="w">    </span><span class="p">.</span><span class="nc">right-align</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">text-align</span><span class="p">:</span><span class="w"> </span><span class="kc">right</span><span class="p">;</span><span class="w"> </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">600</span><span class="kt">px</span><span class="p">;}</span><span class="w"></span>
-<span class="w">    </span><span class="p">.</span><span class="nc">teal</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">teal</span><span class="p">;}</span><span class="w"></span>
-<span class="w">    </span><span class="p">.</span><span class="nc">purple</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">purple</span><span class="p">;}</span><span class="w"></span>
+<span class="w">    </span><span class="p">.</span><span class="nc">left-align</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">text-align</span><span class="p">:</span><span class="w"> </span><span class="kc">left</span><span class="p">;</span><span class="w"> </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">600</span><span class="kt">px</span><span class="p">;}</span>
+<span class="w">    </span><span class="p">.</span><span class="nc">right-align</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">text-align</span><span class="p">:</span><span class="w"> </span><span class="kc">right</span><span class="p">;</span><span class="w"> </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">600</span><span class="kt">px</span><span class="p">;}</span>
+<span class="w">    </span><span class="p">.</span><span class="nc">teal</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">teal</span><span class="p">;}</span>
+<span class="w">    </span><span class="p">.</span><span class="nc">purple</span><span class="w"> </span><span class="p">#</span><span class="nn">stimulus</span><span class="w"> </span><span class="p">{</span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">purple</span><span class="p">;}</span>
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">style</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
-<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p id=&quot;stimulus&quot;&gt;This is the stimulus.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;This text will not be affected by the CSS classes &#39;</span><span class="o">+</span><span class="w"></span>
-<span class="w">            </span><span class="s1">&#39;because it does not have the &quot;stimulus&quot; ID.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;css_classes&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">        </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;condition&#39;</span><span class="p">)}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;left-align&#39;</span><span class="p">,</span><span class="s1">&#39;teal&#39;</span><span class="p">],</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left-teal&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;right-align&#39;</span><span class="p">,</span><span class="s1">&#39;teal&#39;</span><span class="p">],</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;right-teal&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;left-align&#39;</span><span class="p">,</span><span class="s1">&#39;purple&#39;</span><span class="p">],</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left-purple&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;right-align&#39;</span><span class="p">,</span><span class="s1">&#39;purple&#39;</span><span class="p">],</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;right-purple&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="c1">// ...</span><span class="w"></span>
+<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p id=&quot;stimulus&quot;&gt;This is the stimulus.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;This text will not be affected by the CSS classes &#39;</span><span class="o">+</span>
+<span class="w">            </span><span class="s1">&#39;because it does not have the &quot;stimulus&quot; ID.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;css_classes&#39;</span><span class="p">),</span>
+<span class="w">        </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;condition&#39;</span><span class="p">)}</span>
+<span class="w">    </span><span class="p">}],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;left-align&#39;</span><span class="p">,</span><span class="s1">&#39;teal&#39;</span><span class="p">],</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left-teal&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;right-align&#39;</span><span class="p">,</span><span class="s1">&#39;teal&#39;</span><span class="p">],</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;right-teal&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;left-align&#39;</span><span class="p">,</span><span class="s1">&#39;purple&#39;</span><span class="p">],</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left-purple&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">css_classes</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;right-align&#39;</span><span class="p">,</span><span class="s1">&#39;purple&#39;</span><span class="p">],</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;right-purple&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
+<span class="c1">// ...</span>
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>See the "css-classes-parameter.html" file in jsPsych's examples subfolder for more explanation and examples.</p>
@@ -2210,19 +2215,19 @@ <h2 id="tips-for-working-with-css">Tips for working with CSS<a class="headerlink
 <p>You can then use this information to create a CSS selector to modify that element's style.</p>
 <p><img alt="devtools-element-inspector" src="../../img/devtools-inspect-element.png" /></p>
 <p>As you can see, jsPsych adds its own IDs and classes to many elements. You can use the developer tools to determine what IDs and classes already exist for the elements that you want to modify, as you may can often just use these instead of adding your own. For instance, in the "html-keyboard-response" plugin, the stimulus will always be shown in a &lt;div&gt; with the ID "jspsych-html-keyboard-response-stimulus". So you can create a CSS rule that is applied to all "html-keyboard-response" stimuli like this:</p>
-<div class="highlight"><pre><span></span><code><span class="p">#</span><span class="nn">jspsych-html-keyboard-response-stimulus</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">white</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="k">background-color</span><span class="p">:</span><span class="w"> </span><span class="kc">blue</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">100</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="k">border</span><span class="p">:</span><span class="w"> </span><span class="mi">4</span><span class="kt">px</span><span class="w"> </span><span class="kc">solid</span><span class="w"> </span><span class="kc">black</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="p">#</span><span class="nn">jspsych-html-keyboard-response-stimulus</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">color</span><span class="p">:</span><span class="w"> </span><span class="kc">white</span><span class="p">;</span>
+<span class="w">  </span><span class="k">background-color</span><span class="p">:</span><span class="w"> </span><span class="kc">blue</span><span class="p">;</span>
+<span class="w">  </span><span class="k">width</span><span class="p">:</span><span class="w"> </span><span class="mi">100</span><span class="kt">px</span><span class="p">;</span>
+<span class="w">  </span><span class="k">border</span><span class="p">:</span><span class="w"> </span><span class="mi">4</span><span class="kt">px</span><span class="w"> </span><span class="kc">solid</span><span class="w"> </span><span class="kc">black</span><span class="p">;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>As another example, most jsPsych buttons have the class "jspsych-btn", so you can use this class to change the default button styling:</p>
-<div class="highlight"><pre><span></span><code><span class="p">.</span><span class="nc">jspsych-btn</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="k">padding</span><span class="p">:</span><span class="w"> </span><span class="mi">20</span><span class="kt">px</span><span class="w"> </span><span class="mi">20</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">25</span><span class="kt">px</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="k">border-color</span><span class="p">:</span><span class="w"> </span><span class="kc">black</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="p">.</span><span class="nc">jspsych-btn</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="k">padding</span><span class="p">:</span><span class="w"> </span><span class="mi">20</span><span class="kt">px</span><span class="w"> </span><span class="mi">20</span><span class="kt">px</span><span class="p">;</span>
+<span class="w">  </span><span class="k">font-size</span><span class="p">:</span><span class="w"> </span><span class="mi">25</span><span class="kt">px</span><span class="p">;</span>
+<span class="w">  </span><span class="k">border-color</span><span class="p">:</span><span class="w"> </span><span class="kc">black</span><span class="p">;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>You can also use the developer tools to change an element's CSS and immediately see the effect that the changes will have on the page. These changes are just temporary, so you will still need to use one of methods described above to add the CSS changes to your experiment. However, making changes in the developer tools is very useful for figuring out which CSS properties to change and which values to use. This area of the developer tools also shows what styles are currently applied to the element and where those style rules are coming from. </p>
 <p><img alt="devtools-change-css" src="../../img/devtools-change-css.png" /></p>
@@ -2234,16 +2239,25 @@ <h2 id="tips-for-working-with-css">Tips for working with CSS<a class="headerlink
 <p>If one CSS style rule is overridden by another one, the rule that is overridden will appear in <s>strikethrough text</s> in the element's "Styles" section. Also, if you are using an incorrect CSS property name or an invalid value, then that will show up here as an error, indicated by both <s>strikethrough text</s> and a little yellow warning symbol.</p>
 <p><img alt="devtools-css-error" src="../../img/devtools-css-errors.png" /></p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../dynamic-parameters/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Dynamic Parameters" rel="prev">
@@ -2302,7 +2316,7 @@ <h2 id="tips-for-working-with-css">Tips for working with CSS<a class="headerlink
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2311,7 +2325,7 @@ <h2 id="tips-for-working-with-css">Tips for working with CSS<a class="headerlink
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2324,11 +2338,13 @@ <h2 id="tips-for-working-with-css">Tips for working with CSS<a class="headerlink
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/timeline/index.html b/7.3/overview/timeline/index.html
old mode 100755
new mode 100644
index 4cb7d007dd..34dc2a1ed8
--- a/7.3/overview/timeline/index.html
+++ b/7.3/overview/timeline/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/timeline/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2163,81 +2166,83 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/timeline.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="creating-an-experiment-the-timeline">Creating an Experiment: The Timeline<a class="headerlink" href="#creating-an-experiment-the-timeline" title="Permanent link">&para;</a></h1>
 <p>To create an experiment using jsPsych, you need to specify a timeline that describes the structure of the experiment. The timeline is an ordered set of trials. You must create the timeline before launching the experiment. Most of the code you will write for an experiment will be code to create the timeline. This page walks through the creation of timelines, including very basic examples and more advanced features.</p>
 <h2 id="a-single-trial">A single trial<a class="headerlink" href="#a-single-trial" title="Permanent link">&para;</a></h2>
 <p>To create a trial, you need to create an object that describes the trial. The most important feature of this object is the <code>type</code> parameter. This tells jsPsych which plugin to use to run the trial. For example, if you want to use the <a href="../plugins/html-keyboard-response">html-keyboard-response plugin</a> to display a short message, the trial object would look like this:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Welcome to the experiment.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Welcome to the experiment.&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>The parameters for this object (e.g., <code>stimulus</code>) will depend on the plugin that you choose. Each plugin defines the set of parameters that are needed to run a trial with that plugin. Visit the documentation for a plugin to learn about the parameters that you can use with that plugin.</p>
 <p>To create a timeline with the single trial and run the experiment, just embed the trial object in an array. A timeline can simply be an array of trials.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">];</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 </code></pre></div>
 <p>To create and run a simple experiment like this complete the <a href="../../tutorials/hello-world/">hello world tutorial</a>.</p>
 <h2 id="multiple-trials">Multiple trials<a class="headerlink" href="#multiple-trials" title="Permanent link">&para;</a></h2>
 <p>Scaling up to multiple trials is straightforward. Create an object for each trial, and add each object to the timeline array.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// with lots of trials, it might be easier to add the trials</span><span class="w"></span>
-<span class="c1">// to the timeline array as they are defined.</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is trial 1.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial_1</span><span class="p">);</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is trial 2.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial_2</span><span class="p">);</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is trial 3.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial_3</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// with lots of trials, it might be easier to add the trials</span>
+<span class="c1">// to the timeline array as they are defined.</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is trial 1.&#39;</span>
+<span class="p">}</span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial_1</span><span class="p">);</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is trial 2.&#39;</span>
+<span class="p">}</span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial_2</span><span class="p">);</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is trial 3.&#39;</span>
+<span class="p">}</span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">trial_3</span><span class="p">);</span>
 </code></pre></div>
 <h2 id="nested-timelines">Nested timelines<a class="headerlink" href="#nested-timelines" title="Permanent link">&para;</a></h2>
 <p>Each object on the timeline can also have it's own timeline. This is useful for many reasons. One is that it allows you to define common parameters across trials once and have them apply to all the trials on the nested timeline. The example below creates a series of trials using the <a href="../plugins/image-keyboard-response/">image-keyboard-response plugin</a>, where the only thing that changes from trial-to-trial is the image file being displayed on the screen.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">judgment_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press a number 1-7 to indicate how unusual the image is.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;1&#39;</span><span class="p">,</span><span class="s1">&#39;2&#39;</span><span class="p">,</span><span class="s1">&#39;3&#39;</span><span class="p">,</span><span class="s1">&#39;4&#39;</span><span class="p">,</span><span class="s1">&#39;5&#39;</span><span class="p">,</span><span class="s1">&#39;6&#39;</span><span class="p">,</span><span class="s1">&#39;7&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image1.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image2.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image3.png&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">judgment_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press a number 1-7 to indicate how unusual the image is.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;1&#39;</span><span class="p">,</span><span class="s1">&#39;2&#39;</span><span class="p">,</span><span class="s1">&#39;3&#39;</span><span class="p">,</span><span class="s1">&#39;4&#39;</span><span class="p">,</span><span class="s1">&#39;5&#39;</span><span class="p">,</span><span class="s1">&#39;6&#39;</span><span class="p">,</span><span class="s1">&#39;7&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image1.png&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image2.png&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image3.png&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>In the above code, the <code>type</code>, <code>prompt</code>, and <code>choices</code> parameters are automatically applied to all of the objects in the <code>timeline</code> array. This creates three trials with the same <code>type</code>, <code>prompt</code>, and <code>choices</code> parameters, but different values for the <code>stimulus</code> parameter.</p>
 <p>You can also override the values by declaring a new value in the <code>timeline</code> array. In the example below, the second trial will display a different prompt message.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">judgment_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press a number 1-7 to indicate how unusual the image is.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;1&#39;</span><span class="p">,</span><span class="s1">&#39;2&#39;</span><span class="p">,</span><span class="s1">&#39;3&#39;</span><span class="p">,</span><span class="s1">&#39;4&#39;</span><span class="p">,</span><span class="s1">&#39;5&#39;</span><span class="p">,</span><span class="s1">&#39;6&#39;</span><span class="p">,</span><span class="s1">&#39;7&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image1.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image2.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press 1 for this trial.&lt;/p&gt;&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image3.png&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">judgment_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press a number 1-7 to indicate how unusual the image is.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;1&#39;</span><span class="p">,</span><span class="s1">&#39;2&#39;</span><span class="p">,</span><span class="s1">&#39;3&#39;</span><span class="p">,</span><span class="s1">&#39;4&#39;</span><span class="p">,</span><span class="s1">&#39;5&#39;</span><span class="p">,</span><span class="s1">&#39;6&#39;</span><span class="p">,</span><span class="s1">&#39;7&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image1.png&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image2.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press 1 for this trial.&lt;/p&gt;&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image3.png&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>Timelines can be nested any number of times.</p>
 <h2 id="timeline-variables">Timeline variables<a class="headerlink" href="#timeline-variables" title="Permanent link">&para;</a></h2>
@@ -2246,110 +2251,110 @@ <h2 id="timeline-variables">Timeline variables<a class="headerlink" href="#timel
 <p>What follows is an example of how to use timeline variables. The <a href="../../tutorials/rt-task/">simple reaction time tutorial</a> also explains how to use timeline variables.</p>
 <p>Suppose we want to create an experiment where people see a set of faces. Perhaps this is a memory experiment and this is the phase of the experiment where the faces are being presented for the first time. In between each face, a fixation cross is displayed on the screen. Without timeline variables, we would need to add many trials to the timeline, alternating between trials showing the fixation cross and trials showing the face and name. This could be done efficiently using a loop or function to create the timeline, but timeline variables make it even easier - as well as adding extra features like sampling and randomization.</p>
 <p>Here's a basic version of the task with timeline variables.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;face&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">2500</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;face&#39;</span><span class="p">),</span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">2500</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>In the above version, there are four separate trials defined in the <code>timeline_variables</code> parameter. Each trial has a variable <code>face</code> and a variable <code>name</code>. The <code>timeline</code> defines a procedure of showing a fixation cross for 500ms followed by the face and name for 2500ms.  This procedure will repeat four times, with the first trial showing <code>'person-1.jpg'</code>, the second <code>'person-2.jpg'</code>, and so on. The variables are referenced within the procedure by calling the <code>jsPsych.timelineVariable()</code> method and passing in the name of the variable.</p>
 <p>What if we wanted to add an additional step to the task where the name is displayed prior to the face appearing? (Maybe this is one condition of an experiment investigating whether the order of name-face or face-name affects retention.) We can add another variable to our list that gives the name associated with each image. Then we can add another trial to our timeline to show the name.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">),</span>
+<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
 <span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;face&#39;</span><span class="p">),</span><span class="w">         </span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="using-in-a-function">Using in a function<a class="headerlink" href="#using-in-a-function" title="Permanent link">&para;</a></h3>
 <p>Continung the example from the previous section, what if we wanted to show the name with the face, combining the two variables together? 
 To do this, we can use a <a href="../dynamic-parameters/">dynamic parameter</a> (a function) to create an HTML-string that uses both variables in a single parameter.
 The value of the <code>stimulus</code> parameter will be a function that returns an HTML string that contains both the image and the name. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;+&#39;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">),</span>
+<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
 <span class="w">                </span><span class="kd">var</span><span class="w"> </span><span class="nx">html</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">                    &lt;img src=&quot;</span><span class="si">${</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;face&#39;</span><span class="p">)</span><span class="si">}</span><span class="sb">&quot;&gt;</span>
-<span class="sb">                    &lt;p&gt;</span><span class="si">${</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">)</span><span class="si">}</span><span class="sb">&lt;/p&gt;`</span><span class="p">;</span><span class="w"></span>
-<span class="w">                </span><span class="k">return</span><span class="w"> </span><span class="nx">html</span><span class="p">;</span><span class="w"></span>
+<span class="sb">                    &lt;p&gt;</span><span class="si">${</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">)</span><span class="si">}</span><span class="sb">&lt;/p&gt;`</span><span class="p">;</span>
+<span class="w">                </span><span class="k">return</span><span class="w"> </span><span class="nx">html</span><span class="p">;</span>
 <span class="w">            </span><span class="p">},</span><span class="w">          </span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">2500</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">2500</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="random-orders-of-trials">Random orders of trials<a class="headerlink" href="#random-orders-of-trials" title="Permanent link">&para;</a></h3>
 <p>If we want to randomize the order of the trials, we can set <code>randomize_order</code> to <code>true</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="sampling-methods">Sampling methods<a class="headerlink" href="#sampling-methods" title="Permanent link">&para;</a></h3>
 <p>There are also sampling methods that can be used to select a set of trials from the timeline_variables.
@@ -2366,250 +2371,259 @@ <h3 id="sampling-methods">Sampling methods<a class="headerlink" href="#sampling-
 </ul>
 <h4 id="sampling-with-replacement">Sampling with replacement<a class="headerlink" href="#sampling-with-replacement" title="Permanent link">&para;</a></h4>
 <p>This <code>sample</code> parameter will create 10 repetitions, sampling with replacement.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;with-replacement&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">size</span><span class="o">:</span><span class="w"> </span><span class="mf">10</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;with-replacement&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">size</span><span class="o">:</span><span class="w"> </span><span class="mf">10</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h4 id="sampling-with-replacement-unequal-probabilities">Sampling with replacement, unequal probabilities<a class="headerlink" href="#sampling-with-replacement-unequal-probabilities" title="Permanent link">&para;</a></h4>
 <p>This <code>sample</code> parameter will make the "Alex" trial three times as likely to be sampled as the others.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;with-replacement&#39;</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;with-replacement&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">size</span><span class="o">:</span><span class="w"> </span><span class="mf">10</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">weights</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">3</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">        </span><span class="nx">weights</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">3</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">]</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h4 id="sampling-without-replacement">Sampling without replacement<a class="headerlink" href="#sampling-without-replacement" title="Permanent link">&para;</a></h4>
 <p>This <code>sample</code> parameter will pick three of the four possible trials to run at random.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;without-replacement&#39;</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;without-replacement&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">size</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="w"> </span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h4 id="repeating-each-trial-a-fixed-number-of-times-in-a-random-order">Repeating each trial a fixed number of times in a random order<a class="headerlink" href="#repeating-each-trial-a-fixed-number-of-times-in-a-random-order" title="Permanent link">&para;</a></h4>
 <p>This <code>sample</code> parameter will create 3 repetitions of each trial, for a total of 12 trials, with a random order.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixed-repetitions&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">size</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixed-repetitions&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">size</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h4 id="alternating-groups">Alternating groups<a class="headerlink" href="#alternating-groups" title="Permanent link">&para;</a></h4>
 <p>This <code>sample</code> parameter puts the "Alex" and "Chad" trials in group 1 and the "Beth" and "Dave" trials in group 2. 
 The resulting sample of trials will follow the pattern <code>group 1</code> -&gt; <code>group 2</code> -&gt; <code>group 1</code> -&gt; <code>group 2</code>.
  Each trial will be selected only one time. 
 If you wanted <code>group 2</code> to sometimes be first, you could set <code>randomize_group_order: true</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;alternate-groups&#39;</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;alternate-groups&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">groups</span><span class="o">:</span><span class="w"> </span><span class="p">[[</span><span class="mf">0</span><span class="p">,</span><span class="mf">2</span><span class="p">],[</span><span class="mf">1</span><span class="p">,</span><span class="mf">3</span><span class="p">]],</span><span class="w">  </span>
-<span class="w">        </span><span class="nx">randomize_group_order</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">        </span><span class="nx">randomize_group_order</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h4 id="custom-sampling-function">Custom sampling function<a class="headerlink" href="#custom-sampling-function" title="Permanent link">&para;</a></h4>
 <p>Any sampling method can be implemented using the <code>custom</code> type sampler. 
 The order of trials will be determined by running the function supplied as <code>fn</code>. 
 The function has a single parameter, <code>t</code>, which is an array of integers from <code>0</code> to <code>n-1</code>, where <code>n</code> is the number of trials in the <code>timeline_variables</code> array. 
 The function must return an array that specifies the order of the trials, e.g., returning <code>[3,3,2,2,1,1,0,0]</code> would result in the order <code>Dave</code> -&gt; <code>Dave</code> -&gt; <code>Chad</code> -&gt; <code>Chad</code> -&gt; <code>Beth</code> -&gt; <code>Beth</code> -&gt; <code>Alex</code> -&gt; <code>Alex</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;custom&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">fn</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">t</span><span class="p">){</span><span class="w"></span>
-<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="nx">t</span><span class="p">.</span><span class="nx">reverse</span><span class="p">();</span><span class="w"> </span><span class="c1">// show the trials in the reverse order</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">sample</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;custom&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">fn</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">t</span><span class="p">){</span>
+<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="nx">t</span><span class="p">.</span><span class="nx">reverse</span><span class="p">();</span><span class="w"> </span><span class="c1">// show the trials in the reverse order</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="repeating-a-set-of-trials">Repeating a set of trials<a class="headerlink" href="#repeating-a-set-of-trials" title="Permanent link">&para;</a></h2>
 <p>To repeat a timeline multiple times, you can create an object (node) that contains a <code>timeline</code>, which is the timeline array to repeat, and <code>repetitions</code>, which is the number of times to repeat that timeline. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will be repeated twice.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">node</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will be repeated twice.&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">node</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>The <code>repetitions</code> parameter can be used alongside other node parameters, such as timeline variables, loop functions, and/or conditional functions. If you are using <code>timeline_variables</code> and <code>randomize_order</code> is <code>true</code>, then the order of the timeline variables will re-randomize before every repetition.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="w"> </span>
-<span class="p">}</span><span class="w"></span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="looping-timelines">Looping timelines<a class="headerlink" href="#looping-timelines" title="Permanent link">&para;</a></h2>
 <p>Any timeline can be looped using the <code>loop_function</code> option. 
 The loop function must be a function that evaluates to <code>true</code> if the timeline should repeat, and <code>false</code> if the timeline should end. It receives a single parameter, named <code>data</code> by convention. 
 This parameter will be the <a href="../../reference/jspsych-data/#datacollection">DataCollection object</a> with all of the data from the trials executed in the last iteration of the timeline. 
 The loop function will be evaluated after the timeline is completed.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial is in a loop. Press R to repeat this trial, or C to continue.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">loop_node</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">loop_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;r&#39;</span><span class="p">)){</span><span class="w"></span>
-<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial is in a loop. Press R to repeat this trial, or C to continue.&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">loop_node</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">loop_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">        </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;r&#39;</span><span class="p">)){</span>
+<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">        </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="conditional-timelines">Conditional timelines<a class="headerlink" href="#conditional-timelines" title="Permanent link">&para;</a></h2>
 <p>A timeline can be skipped or not based on the evaluation of the <code>conditional_function</code> option. 
 If the conditional function evaluates to <code>true</code>, the timeline will execute normally. 
 If the conditional function evaluates to <code>false</code> then the timeline will be skipped. 
 The conditional function is evaluated whenever jsPsych is about to run the first trial on the timeline.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">pre_if_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;The next trial is in a conditional statement. Press S to skip it, or V to view it.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">if_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;You chose to view the trial. Press any key to continue.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">if_node</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">if_trial</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">conditional_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// get the data from the previous trial,</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// and check which key was pressed</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">        </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;s&#39;</span><span class="p">)){</span><span class="w"></span>
-<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">after_if_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is the trial after the conditional.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">pre_if_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">if_node</span><span class="p">,</span><span class="w"> </span><span class="nx">after_if_trial</span><span class="p">]);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">pre_if_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;The next trial is in a conditional statement. Press S to skip it, or V to view it.&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">if_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;You chose to view the trial. Press any key to continue.&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">if_node</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">if_trial</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">conditional_function</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">        </span><span class="c1">// get the data from the previous trial,</span>
+<span class="w">        </span><span class="c1">// and check which key was pressed</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">        </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;s&#39;</span><span class="p">)){</span>
+<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="w">        </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">            </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">after_if_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is the trial after the conditional.&#39;</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">pre_if_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">if_node</span><span class="p">,</span><span class="w"> </span><span class="nx">after_if_trial</span><span class="p">]);</span>
 </code></pre></div>
 <h2 id="timeline-start-and-finish-functions">Timeline start and finish functions<a class="headerlink" href="#timeline-start-and-finish-functions" title="Permanent link">&para;</a></h2>
 <p>You can run a custom function at the start and end of a timeline node using the <code>on_timeline_start</code> and <code>on_timeline_finish</code> callback function parameters. These are functions that will run when the timeline starts and ends, respectively. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial_1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_2</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_timeline_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The trial procedure just started.&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_timeline_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The trial procedure just finished.&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial_1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_2</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">on_timeline_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The trial procedure just started.&#39;</span><span class="p">)</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">on_timeline_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The trial procedure just finished.&#39;</span><span class="p">)</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>This works the same way with timeline variables. The <code>on_timeline_start</code> and <code>on_timeline_finish</code> functions will run when timeline variables trials start and end, respectively.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_timeline_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;First trial is starting.&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_timeline_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Last trial just finished.&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">face_name_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[...],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-1.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Alex&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-2.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Beth&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-3.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Chad&#39;</span><span class="w"> </span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="w"> </span><span class="nx">face</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;person-4.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dave&#39;</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">on_timeline_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;First trial is starting.&#39;</span><span class="p">)</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">on_timeline_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Last trial just finished.&#39;</span><span class="p">)</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>When the <code>repetititons</code> option is used (and is greater than 1), these functions will run once per repetition of the timeline.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">repetition_count</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial_1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_2</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_timeline_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">repetition_count</span><span class="o">++</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Repetition number &#39;</span><span class="p">,</span><span class="nx">repetition_count</span><span class="p">,</span><span class="s1">&#39; has just started.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_timeline_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Repetition number &#39;</span><span class="p">,</span><span class="nx">repetition_count</span><span class="p">,</span><span class="s1">&#39; has just finished.&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">repetition_count</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial_1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_2</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">on_timeline_start</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">repetition_count</span><span class="o">++</span><span class="p">;</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Repetition number &#39;</span><span class="p">,</span><span class="nx">repetition_count</span><span class="p">,</span><span class="s1">&#39; has just started.&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">on_timeline_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Repetition number &#39;</span><span class="p">,</span><span class="nx">repetition_count</span><span class="p">,</span><span class="s1">&#39; has just finished.&#39;</span><span class="p">)</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../../tutorials/video-tutorials/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Video Tutorials" rel="prev">
@@ -2668,7 +2682,7 @@ <h2 id="timeline-start-and-finish-functions">Timeline start and finish functions
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2677,7 +2691,7 @@ <h2 id="timeline-start-and-finish-functions">Timeline start and finish functions
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2690,11 +2704,13 @@ <h2 id="timeline-start-and-finish-functions">Timeline start and finish functions
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/overview/timing-accuracy/index.html b/7.3/overview/timing-accuracy/index.html
old mode 100755
new mode 100644
index 7ea31951ed..d97a85a3f3
--- a/7.3/overview/timing-accuracy/index.html
+++ b/7.3/overview/timing-accuracy/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/overview/timing-accuracy/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1915,16 +1918,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/overview/timing-accuracy.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="timing-accuracy">Timing accuracy<a class="headerlink" href="#timing-accuracy" title="Permanent link">&para;</a></h1>
 <p>Wondering if jsPsych can be used for research that depends on accurate display times or response time measurement? For most purposes, the answer is yes. </p>
 <p><strong>Display timing</strong> is somewhat less accurate in JavaScript than in standard experimental software that runs on a desktop. Desktop software can have closer integration with the graphics devices of the machine than JavaScript currently permits. If a one or two frame (17-33ms) difference in display timing matters for your experiment, then you'll want to be careful with JavaScript-based experiments. It is possible to achieve this level of control in JavaScript, but it often requires code that is more tailored to your experiment and some restrictions about which browsers can be used to run the experiment.</p>
@@ -1948,16 +1953,25 @@ <h2 id="references">References<a class="headerlink" href="#references" title="Pe
 <li><a href="http://link.springer.com/article/10.3758%2Fs13428-014-0471-1">Reimers, S., &amp; Stewart, N. (2015). Presentation and response time accuracy in Adobe Flash and HTML5/JavaScript Web experiments. <em>Behavior Research Methods</em>, <em>47</em>(2), 309-327.</a></li>
 </ul>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../browser-device-support/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Browser and Device Support" rel="prev">
@@ -2016,7 +2030,7 @@ <h2 id="references">References<a class="headerlink" href="#references" title="Pe
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2025,7 +2039,7 @@ <h2 id="references">References<a class="headerlink" href="#references" title="Pe
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2038,11 +2052,13 @@ <h2 id="references">References<a class="headerlink" href="#references" title="Pe
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/animation/index.html b/7.3/plugins/animation/index.html
old mode 100755
new mode 100644
index d23a827192..188a2a46bc
--- a/7.3/plugins/animation/index.html
+++ b/7.3/plugins/animation/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/animation/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/animation.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="animation">animation<a class="headerlink" href="#animation" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-animation/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-animation/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays a sequence of images at a fixed frame rate. The sequence can be looped a specified number of times. The participant is free to respond at any point during the animation, and the time of the response is recorded.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2051,15 +2056,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-animation@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-animation@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-animation.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-animation.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-animation
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">animation</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-animation&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">animation</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-animation&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2067,15 +2072,15 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">animation_sequence</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;img/happy_face_1.jpg&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/happy_face_2.jpg&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/happy_face_3.jpg&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/happy_face_4.jpg&quot;</span><span class="p">];</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">animation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAnimation</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="nx">animation_sequence</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sequence_reps</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">frame_time</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Watch the faces.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">animation_sequence</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;img/happy_face_1.jpg&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/happy_face_2.jpg&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/happy_face_3.jpg&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/happy_face_4.jpg&quot;</span><span class="p">];</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">animation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAnimation</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="nx">animation_sequence</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">sequence_reps</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">frame_time</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Watch the faces.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2088,16 +2093,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-animation-demo.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../list-of-plugins/" class="md-footer__link md-footer__link--prev" aria-label="Previous: List of Plugins" rel="prev">
@@ -2156,7 +2170,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2165,7 +2179,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2178,11 +2192,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/audio-button-response/index.html b/7.3/plugins/audio-button-response/index.html
old mode 100755
new mode 100644
index 9c05119853..bb15ad41b1
--- a/7.3/plugins/audio-button-response/index.html
+++ b/7.3/plugins/audio-button-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/audio-button-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/audio-button-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="audio-button-response">audio-button-response<a class="headerlink" href="#audio-button-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-audio-button-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-audio-button-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin plays audio files and records responses generated with a button click.</p>
 <p>If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. </p>
 <p>Audio files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the audio stimulus, you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the audio.</p>
@@ -2090,15 +2095,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 This may change in a future version as we improve the simulation modes.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-audio-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-audio-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-audio-button-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">audioButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-audio-button-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">audioButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-audio-button-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2106,12 +2111,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/tone.mp3&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Low&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;High&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is the pitch high or low?&lt;/p&gt;&quot;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/tone.mp3&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Low&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;High&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is the pitch high or low?&lt;/p&gt;&quot;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2128,13 +2133,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/roar.mp3&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;lion.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;elephant.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;monkey.png&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Which animal made the sound?&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">button_html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;img src=&quot;%choice%&quot; /&gt;&#39;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/roar.mp3&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;lion.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;elephant.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;monkey.png&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Which animal made the sound?&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">button_html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;img src=&quot;%choice%&quot; /&gt;&#39;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2146,20 +2151,29 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 </div>
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-audio-button-response-demo-2.html">Open demo in new tab</a></p>
 <p><strong>Note</strong>: if you want the images to look more like jsPsych buttons, i.e. with borders and different styles for hover/active/disabled states, then you can also embed the image element inside the default <code>button_html</code> string:
-<div class="highlight"><pre><span></span><code><span class="nx">button_html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;button class=&quot;jspsych-btn&quot;&gt;&lt;img src=&quot;%choice%&quot; /&gt;&lt;/button&gt;&#39;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">button_html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;button class=&quot;jspsych-btn&quot;&gt;&lt;img src=&quot;%choice%&quot; /&gt;&lt;/button&gt;&#39;</span>
 </code></pre></div></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../animation/" class="md-footer__link md-footer__link--prev" aria-label="Previous: animation" rel="prev">
@@ -2218,7 +2232,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2227,7 +2241,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2240,11 +2254,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/audio-keyboard-response/index.html b/7.3/plugins/audio-keyboard-response/index.html
old mode 100755
new mode 100644
index 9ccb0b00bb..841290263f
--- a/7.3/plugins/audio-keyboard-response/index.html
+++ b/7.3/plugins/audio-keyboard-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/audio-keyboard-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/audio-keyboard-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="audio-keyboard-response">audio-keyboard-response<a class="headerlink" href="#audio-keyboard-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-audio-keyboard-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-audio-keyboard-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin plays audio files and records responses generated with the keyboard.</p>
 <p>If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. </p>
 <p>Audio files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the audio.</p>
@@ -2077,15 +2082,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 This may change in a future version as we improve the simulation modes.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-audio-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-audio-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-audio-keyboard-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">audioKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-audio-keyboard-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">audioKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-audio-keyboard-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2093,13 +2098,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/tone.mp3&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;i&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is the pitch high or low? Press &#39;e&#39; for low and &#39;i&#39; for high.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">response_ends_trial</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/tone.mp3&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;i&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is the pitch high or low? Press &#39;e&#39; for low and &#39;i&#39; for high.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">response_ends_trial</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2116,12 +2121,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/tone.mp3&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial_ends_after_audio</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/tone.mp3&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trial_ends_after_audio</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2134,16 +2139,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-audio-keyboard-response-demo-2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../audio-button-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: audio-button-response" rel="prev">
@@ -2202,7 +2216,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2211,7 +2225,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2224,11 +2238,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/audio-slider-response/index.html b/7.3/plugins/audio-slider-response/index.html
old mode 100755
new mode 100644
index 802b5a58f7..7557b7a16d
--- a/7.3/plugins/audio-slider-response/index.html
+++ b/7.3/plugins/audio-slider-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/audio-slider-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/audio-slider-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="audio-slider-response">audio-slider-response<a class="headerlink" href="#audio-slider-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-audio-slider-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-audio-slider-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin plays an audio file and allows the participant to respond by dragging a slider.</p>
 <p>If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. </p>
 <p>Audio files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the audio.</p>
@@ -2118,15 +2123,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 This may change in a future version as we improve the simulation modes.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-audio-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-audio-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-audio-slider-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">audioSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-audio-slider-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">audioSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-audio-slider-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2134,12 +2139,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioSliderResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/speech_joke.mp3&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Not Funny&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Funny&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How funny is the joke?&lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioSliderResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/speech_joke.mp3&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Not Funny&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Funny&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How funny is the joke?&lt;/p&gt;&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2156,14 +2161,14 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioSliderResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/speech_joke.mp3&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Not Funny&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Funny&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How funny is the joke?&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">response_allowed_while_playing</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">require_movement</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioSliderResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;sound/speech_joke.mp3&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Not Funny&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Funny&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How funny is the joke?&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">response_allowed_while_playing</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">require_movement</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2176,16 +2181,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-audio-slider-response-demo-2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../audio-keyboard-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: audio-keyboard-response" rel="prev">
@@ -2244,7 +2258,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2253,7 +2267,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2266,11 +2280,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/browser-check/index.html b/7.3/plugins/browser-check/index.html
old mode 100755
new mode 100644
index 2676cf6811..3afa4fcf7f
--- a/7.3/plugins/browser-check/index.html
+++ b/7.3/plugins/browser-check/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/browser-check/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/browser-check.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="browser-check">browser-check<a class="headerlink" href="#browser-check" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-browser-check/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-browser-check/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin measures and records various features of the participant's browser and can end the experiment if defined inclusion criteria are not met.</p>
 <p>The plugin currently can record the following features:</p>
 <ul>
@@ -2158,15 +2163,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>As with all simulated plugins, you can override the default (actual) data with fake data using <code>simulation_options</code>. This allows you to test your exclusion criteria by simulating other configurations.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-browser-check@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-browser-check@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-browser-check.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-browser-check.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-browser-check
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">browserCheck</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-browser-check&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">browserCheck</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-browser-check&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2174,9 +2179,9 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychBrowserCheck</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychBrowserCheck</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2193,15 +2198,15 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychBrowserCheck</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">inclusion_function</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;chrome&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;firefox&#39;</span><span class="p">].</span><span class="nx">includes</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">browser</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">exclusion_message</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="sb">`&lt;p&gt;You must use Chrome or Firefox to complete this experiment.&lt;/p&gt;`</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychBrowserCheck</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">inclusion_function</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;chrome&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;firefox&#39;</span><span class="p">].</span><span class="nx">includes</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">browser</span><span class="p">);</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">exclusion_message</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="sb">`&lt;p&gt;You must use Chrome or Firefox to complete this experiment.&lt;/p&gt;`</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2218,11 +2223,11 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychBrowserCheck</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">minimum_width</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">minimum_height</span><span class="o">:</span><span class="w"> </span><span class="mf">600</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychBrowserCheck</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">minimum_width</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">minimum_height</span><span class="o">:</span><span class="w"> </span><span class="mf">600</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2239,19 +2244,19 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="4:2"><input checked="checked" id="__tabbed_4_1" name="__tabbed_4" type="radio" /><input id="__tabbed_4_2" name="__tabbed_4" type="radio" /><div class="tabbed-labels"><label for="__tabbed_4_1">Code</label><label for="__tabbed_4_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychBrowserCheck</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">inclusion_function</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">browser</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="s1">&#39;chrome&#39;</span><span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">mobile</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">exclusion_message</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">mobile</span><span class="p">){</span><span class="w"></span>
-<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;You must use a desktop/laptop computer to participate in this experiment.&lt;/p&gt;&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="k">if</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">browser</span><span class="w"> </span><span class="o">!==</span><span class="w"> </span><span class="s1">&#39;chrome&#39;</span><span class="p">){</span><span class="w"></span>
-<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;You must use Chrome as your browser to complete this experiment.&lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychBrowserCheck</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">inclusion_function</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">browser</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="s1">&#39;chrome&#39;</span><span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">mobile</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="kc">false</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">exclusion_message</span><span class="o">:</span><span class="w"> </span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">mobile</span><span class="p">){</span>
+<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;You must use a desktop/laptop computer to participate in this experiment.&lt;/p&gt;&#39;</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="k">if</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">browser</span><span class="w"> </span><span class="o">!==</span><span class="w"> </span><span class="s1">&#39;chrome&#39;</span><span class="p">){</span>
+<span class="w">      </span><span class="k">return</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;You must use Chrome as your browser to complete this experiment.&lt;/p&gt;&#39;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2264,16 +2269,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-browser-check-demo4.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../audio-slider-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: audio-slider-response" rel="prev">
@@ -2332,7 +2346,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2341,7 +2355,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2354,11 +2368,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/call-function/index.html b/7.3/plugins/call-function/index.html
old mode 100755
new mode 100644
index 094f6d482a..10be69c110
--- a/7.3/plugins/call-function/index.html
+++ b/7.3/plugins/call-function/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/call-function/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/call-function.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="call-function">call-function<a class="headerlink" href="#call-function" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-call-function/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-call-function/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin executes a specified function. This allows the experimenter to run arbitrary code at any point during the experiment.</p>
 <p>The function cannot take any arguments. If arguments are needed, then an anonymous function should be used to wrap the function call (see examples below).</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2017,15 +2022,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-call-function@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-call-function@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-call-function.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-call-function.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-call-function
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">callFunction</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-call-function&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">callFunction</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-call-function&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2033,14 +2038,14 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myfunc</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="s1">&#39;you called?&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="nx">myfunc</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myfunc</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="s1">&#39;you called?&#39;</span><span class="p">;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="nx">myfunc</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2057,17 +2062,17 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myfunc</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// data contains all the experiment data so far,</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// so this function could implement code to write</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// the data to a database.</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">values</span><span class="p">())</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">myfunc</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">())</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myfunc</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">    </span><span class="c1">// data contains all the experiment data so far,</span>
+<span class="w">    </span><span class="c1">// so this function could implement code to write</span>
+<span class="w">    </span><span class="c1">// the data to a database.</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">values</span><span class="p">())</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">myfunc</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">())</span><span class="w"> </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2087,27 +2092,27 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 </div>
 </div>
 <p>There's no demo for this code, because it requires a server to communicate with.
-    <div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="k">async</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">done</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// can perform async operations here like</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// creating an XMLHttpRequest to communicate</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// with a server</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">xhttp</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nx">XMLHttpRequest</span><span class="p">();</span><span class="w"></span>
-<span class="w">        </span><span class="nx">xhttp</span><span class="p">.</span><span class="nx">onreadystatechange</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="k">this</span><span class="p">.</span><span class="nx">readyState</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">4</span><span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="k">this</span><span class="p">.</span><span class="nx">status</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">200</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">                </span><span class="kd">var</span><span class="w"> </span><span class="nx">response_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">xhttp</span><span class="p">.</span><span class="nx">responseText</span><span class="p">;</span><span class="w"></span>
-<span class="w">                </span><span class="c1">// line below is what causes jsPsych to </span><span class="w"></span>
-<span class="w">                </span><span class="c1">// continue to next trial. response_data</span><span class="w"></span>
-<span class="w">                </span><span class="c1">// will be stored in jsPsych data object.</span><span class="w"></span>
-<span class="w">                </span><span class="nx">done</span><span class="p">(</span><span class="nx">response_data</span><span class="p">);</span><span class="w"></span>
-<span class="w">            </span><span class="p">}</span><span class="w"></span>
-<span class="w">        </span><span class="p">};</span><span class="w"></span>
-<span class="w">        </span><span class="nx">xhttp</span><span class="p">.</span><span class="nx">open</span><span class="p">(</span><span class="s2">&quot;GET&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;path_to_server_script.php&quot;</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="nx">xhttp</span><span class="p">.</span><span class="nx">send</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+    <div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span>
+<span class="w">    </span><span class="k">async</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">done</span><span class="p">){</span>
+<span class="w">        </span><span class="c1">// can perform async operations here like</span>
+<span class="w">        </span><span class="c1">// creating an XMLHttpRequest to communicate</span>
+<span class="w">        </span><span class="c1">// with a server</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">xhttp</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="ow">new</span><span class="w"> </span><span class="nx">XMLHttpRequest</span><span class="p">();</span>
+<span class="w">        </span><span class="nx">xhttp</span><span class="p">.</span><span class="nx">onreadystatechange</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">            </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="k">this</span><span class="p">.</span><span class="nx">readyState</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">4</span><span class="w"> </span><span class="o">&amp;&amp;</span><span class="w"> </span><span class="k">this</span><span class="p">.</span><span class="nx">status</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mf">200</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">                </span><span class="kd">var</span><span class="w"> </span><span class="nx">response_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">xhttp</span><span class="p">.</span><span class="nx">responseText</span><span class="p">;</span>
+<span class="w">                </span><span class="c1">// line below is what causes jsPsych to </span>
+<span class="w">                </span><span class="c1">// continue to next trial. response_data</span>
+<span class="w">                </span><span class="c1">// will be stored in jsPsych data object.</span>
+<span class="w">                </span><span class="nx">done</span><span class="p">(</span><span class="nx">response_data</span><span class="p">);</span>
+<span class="w">            </span><span class="p">}</span>
+<span class="w">        </span><span class="p">};</span>
+<span class="w">        </span><span class="nx">xhttp</span><span class="p">.</span><span class="nx">open</span><span class="p">(</span><span class="s2">&quot;GET&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;path_to_server_script.php&quot;</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">);</span>
+<span class="w">        </span><span class="nx">xhttp</span><span class="p">.</span><span class="nx">send</span><span class="p">();</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div></p>
 </details>
 <details class="example" open="open">
@@ -2115,20 +2120,20 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="4:2"><input checked="checked" id="__tabbed_4_1" name="__tabbed_4" type="radio" /><input id="__tabbed_4_2" name="__tabbed_4" type="radio" /><div class="tabbed-labels"><label for="__tabbed_4_1">Code</label><label for="__tabbed_4_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="k">async</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">done</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// generate a delay between 1500 and 3000 milliseconds to simulate  </span><span class="w"></span>
-<span class="w">        </span><span class="c1">// waiting for an event to finish after an unknown duration,</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// then move on with the experiment</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">rand_delay</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="nb">Math</span><span class="p">.</span><span class="nx">floor</span><span class="p">(</span><span class="nb">Math</span><span class="p">.</span><span class="nx">random</span><span class="p">()</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="mf">3000</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">1500</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mf">1</span><span class="p">)</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mf">1500</span><span class="p">));</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">setTimeout</span><span class="p">(</span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="c1">// end the trial and save the delay duration to the data</span><span class="w"></span>
-<span class="w">            </span><span class="nx">done</span><span class="p">(</span><span class="nx">rand_delay</span><span class="p">.</span><span class="nx">toString</span><span class="p">()</span><span class="o">+</span><span class="s2">&quot;ms&quot;</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"> </span><span class="nx">rand_delay</span><span class="p">)</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCallFunction</span><span class="p">,</span>
+<span class="w">    </span><span class="k">async</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">func</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">done</span><span class="p">){</span>
+<span class="w">        </span><span class="c1">// generate a delay between 1500 and 3000 milliseconds to simulate  </span>
+<span class="w">        </span><span class="c1">// waiting for an event to finish after an unknown duration,</span>
+<span class="w">        </span><span class="c1">// then move on with the experiment</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">rand_delay</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="nb">Math</span><span class="p">.</span><span class="nx">floor</span><span class="p">(</span><span class="nb">Math</span><span class="p">.</span><span class="nx">random</span><span class="p">()</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="mf">3000</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">1500</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mf">1</span><span class="p">)</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mf">1500</span><span class="p">));</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">setTimeout</span><span class="p">(</span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">            </span><span class="c1">// end the trial and save the delay duration to the data</span>
+<span class="w">            </span><span class="nx">done</span><span class="p">(</span><span class="nx">rand_delay</span><span class="p">.</span><span class="nx">toString</span><span class="p">()</span><span class="o">+</span><span class="s2">&quot;ms&quot;</span><span class="p">);</span>
+<span class="w">        </span><span class="p">},</span><span class="w"> </span><span class="nx">rand_delay</span><span class="p">)</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2141,16 +2146,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-call-function-demo3.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../browser-check/" class="md-footer__link md-footer__link--prev" aria-label="Previous: browser-check" rel="prev">
@@ -2209,7 +2223,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2218,7 +2232,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2231,11 +2245,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/canvas-button-response/index.html b/7.3/plugins/canvas-button-response/index.html
old mode 100755
new mode 100644
index 936f5fb3cf..6bfc69a87b
--- a/7.3/plugins/canvas-button-response/index.html
+++ b/7.3/plugins/canvas-button-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/canvas-button-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/canvas-button-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="canvas-button-response">canvas-button-response<a class="headerlink" href="#canvas-button-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-canvas-button-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-canvas-button-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin can be used to draw a stimulus on a <a href="https://www.w3schools.com/html/html5_canvas.asp">HTML canvas element</a>, and record a button click response and response time. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. One or more button choices will be displayed under the canvas, and the button style can be customized using HTML formatting.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2070,15 +2075,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 <p>Note: the canvas stimulus is <em>not</em> included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the <code>data</code> parameter.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-canvas-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-canvas-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-canvas-button-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">canvasButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-canvas-button-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">canvasButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-canvas-button-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2086,37 +2091,37 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">canvas</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">canvas</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s2">&quot;2d&quot;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">arc</span><span class="p">(</span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="p">,</span><span class="w"> </span><span class="mf">0</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">PI</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">color</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fill</span><span class="p">();</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">circle_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Red&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Green&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Blue&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;What color is the circle?&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">circle_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;green&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Larger&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Smaller&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Is this circle larger or smaller than the last one?&lt;/p&gt;&#39;</span><span class="o">+</span><span class="w"></span>
-<span class="w">        </span><span class="s1">&#39;&lt;p&gt;Stimulus will be hidden after 1 second.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;green&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">150</span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">canvas</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">canvas</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s2">&quot;2d&quot;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">arc</span><span class="p">(</span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="p">,</span><span class="w"> </span><span class="mf">0</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">PI</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">color</span><span class="p">;</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fill</span><span class="p">();</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">circle_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Red&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Green&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Blue&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;What color is the circle?&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span><span class="p">}</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">circle_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;green&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Larger&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Smaller&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">stimulus_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Is this circle larger or smaller than the last one?&lt;/p&gt;&#39;</span><span class="o">+</span>
+<span class="w">        </span><span class="s1">&#39;&lt;p&gt;Stimulus will be hidden after 1 second.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;green&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">150</span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2133,30 +2138,30 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">lines</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s2">&quot;2d&quot;</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// first line</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">moveTo</span><span class="p">(</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">10</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">lineTo</span><span class="p">(</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">250</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">lineWidth</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">10</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">strokeStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;MediumBlue&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">stroke</span><span class="p">();</span><span class="w"></span>
-<span class="w">        </span><span class="c1">// second line</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">moveTo</span><span class="p">(</span><span class="mf">20</span><span class="p">,</span><span class="w"> </span><span class="mf">100</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">lineTo</span><span class="p">(</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">250</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">lineWidth</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">10</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">strokeStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;MediumPurple&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">stroke</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Blue line&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Purple line&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Which line is longer?&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">line1_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">line1_length</span><span class="o">:</span><span class="w"> </span><span class="mf">290</span><span class="p">,</span><span class="w"> </span><span class="nx">line2_color</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;purple&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">line2_length</span><span class="o">:</span><span class="w"> </span><span class="mf">170</span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">lines</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s2">&quot;2d&quot;</span><span class="p">);</span>
+<span class="w">        </span><span class="c1">// first line</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">moveTo</span><span class="p">(</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">10</span><span class="p">);</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">lineTo</span><span class="p">(</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">250</span><span class="p">);</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">lineWidth</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">10</span><span class="p">;</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">strokeStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;MediumBlue&#39;</span><span class="p">;</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">stroke</span><span class="p">();</span>
+<span class="w">        </span><span class="c1">// second line</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">moveTo</span><span class="p">(</span><span class="mf">20</span><span class="p">,</span><span class="w"> </span><span class="mf">100</span><span class="p">);</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">lineTo</span><span class="p">(</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">250</span><span class="p">);</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">lineWidth</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">10</span><span class="p">;</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">strokeStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;MediumPurple&#39;</span><span class="p">;</span>
+<span class="w">        </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">stroke</span><span class="p">();</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Blue line&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Purple line&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Which line is longer?&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">line1_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">line1_length</span><span class="o">:</span><span class="w"> </span><span class="mf">290</span><span class="p">,</span><span class="w"> </span><span class="nx">line2_color</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;purple&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">line2_length</span><span class="o">:</span><span class="w"> </span><span class="mf">170</span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2173,40 +2178,40 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">canvas</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">canvas</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s2">&quot;2d&quot;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">arc</span><span class="p">(</span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="p">,</span><span class="w"> </span><span class="mf">0</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">PI</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">color</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fill</span><span class="p">();</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">circle_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="w"></span>
-<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">                </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;radius&#39;</span><span class="p">),</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;color&#39;</span><span class="p">));</span><span class="w"></span>
-<span class="w">            </span><span class="p">},</span><span class="w"></span>
-<span class="w">            </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span><span class="w"></span>
-<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Red&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Green&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Blue&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">            </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;What color is the circle?&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">            </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">canvas</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">canvas</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s2">&quot;2d&quot;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">arc</span><span class="p">(</span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="p">,</span><span class="w"> </span><span class="mf">0</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">PI</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">color</span><span class="p">;</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fill</span><span class="p">();</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">circle_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span>
+<span class="w">            </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasButtonResponse</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">                </span><span class="nx">filledCirc</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;radius&#39;</span><span class="p">),</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;color&#39;</span><span class="p">));</span>
+<span class="w">            </span><span class="p">},</span>
+<span class="w">            </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span>
+<span class="w">            </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Red&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Green&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Blue&#39;</span><span class="p">],</span>
+<span class="w">            </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;What color is the circle?&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">            </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
 <span class="w">                </span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;radius&#39;</span><span class="p">),</span><span class="w"> </span>
-<span class="w">                </span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;color&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">                </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">            </span><span class="p">},</span><span class="w"></span>
-<span class="w">            </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">                </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">;</span><span class="w"></span>
-<span class="w">            </span><span class="p">}</span><span class="w"></span>
-<span class="w">        </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">80</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;red&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="mf">0</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;green&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">{</span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">50</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
+<span class="w">                </span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;color&#39;</span><span class="p">),</span>
+<span class="w">                </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span>
+<span class="w">            </span><span class="p">},</span>
+<span class="w">            </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">                </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">;</span>
+<span class="w">            </span><span class="p">}</span>
+<span class="w">        </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">80</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;red&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="mf">0</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;green&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span>
+<span class="w">        </span><span class="p">{</span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">50</span><span class="p">,</span><span class="w"> </span><span class="nx">color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
 <span class="p">};</span><span class="w">        </span>
 </code></pre></div>
 </div>
@@ -2220,16 +2225,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-canvas-button-response-demo3.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../call-function/" class="md-footer__link md-footer__link--prev" aria-label="Previous: call-function" rel="prev">
@@ -2288,7 +2302,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2297,7 +2311,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2310,11 +2324,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/canvas-keyboard-response/index.html b/7.3/plugins/canvas-keyboard-response/index.html
old mode 100755
new mode 100644
index 62896523c7..57433c11e5
--- a/7.3/plugins/canvas-keyboard-response/index.html
+++ b/7.3/plugins/canvas-keyboard-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/canvas-keyboard-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/canvas-keyboard-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="canvas-keyboard-response">canvas-keyboard-response<a class="headerlink" href="#canvas-keyboard-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-canvas-keyboard-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-canvas-keyboard-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin can be used to draw a stimulus on a <a href="https://www.w3schools.com/html/html5_canvas.asp">HTML canvas element</a> and record a keyboard response. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2052,15 +2057,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 <p>Note: the canvas stimulus is <em>not</em> included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the <code>data</code> parameter.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-canvas-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-canvas-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-canvas-keyboard-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">canvasKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-canvas-keyboard-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">canvasKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-canvas-keyboard-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2068,21 +2073,21 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">drawRect</span><span class="p">(</span><span class="nx">c</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s1">&#39;2d&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">rect</span><span class="p">(</span><span class="mf">30</span><span class="p">,</span><span class="w"> </span><span class="mf">30</span><span class="p">,</span><span class="w"> </span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">50</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">stroke</span><span class="p">();</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">drawRect</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="s1">&#39;i&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Is this a circle or a rectangle? Press &quot;e&quot; for circle and &quot;i&quot; for rectangle.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">shape</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;rectangle&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">drawRect</span><span class="p">(</span><span class="nx">c</span><span class="p">){</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s1">&#39;2d&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">rect</span><span class="p">(</span><span class="mf">30</span><span class="p">,</span><span class="w"> </span><span class="mf">30</span><span class="p">,</span><span class="w"> </span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">50</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">stroke</span><span class="p">();</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">drawRect</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="s1">&#39;i&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Is this a circle or a rectangle? Press &quot;e&quot; for circle and &quot;i&quot; for rectangle.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">shape</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;rectangle&#39;</span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2099,22 +2104,22 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">drawCirc</span><span class="p">(</span><span class="nx">c</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s1">&#39;2d&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">arc</span><span class="p">(</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">75</span><span class="p">,</span><span class="w"> </span><span class="mf">50</span><span class="p">,</span><span class="w"> </span><span class="mf">0</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">PI</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">stroke</span><span class="p">();</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">drawCirc</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;No key response is allowed.&lt;/p&gt;&lt;p&gt;The stimulus disappears after 3 seconds.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3000</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">shape</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;circle&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">50</span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">drawCirc</span><span class="p">(</span><span class="nx">c</span><span class="p">){</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s1">&#39;2d&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">beginPath</span><span class="p">();</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">arc</span><span class="p">(</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">75</span><span class="p">,</span><span class="w"> </span><span class="mf">50</span><span class="p">,</span><span class="w"> </span><span class="mf">0</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">PI</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">stroke</span><span class="p">();</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">300</span><span class="p">,</span><span class="w"> </span><span class="mf">300</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">drawCirc</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;No key response is allowed.&lt;/p&gt;&lt;p&gt;The stimulus disappears after 3 seconds.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3000</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">shape</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;circle&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">radius</span><span class="o">:</span><span class="w"> </span><span class="mf">50</span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2127,16 +2132,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-canvas-keyboard-response-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../canvas-button-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: canvas-button-response" rel="prev">
@@ -2195,7 +2209,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2204,7 +2218,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2217,11 +2231,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/canvas-slider-response/index.html b/7.3/plugins/canvas-slider-response/index.html
old mode 100755
new mode 100644
index 5c24ee9ee5..1510eee0de
--- a/7.3/plugins/canvas-slider-response/index.html
+++ b/7.3/plugins/canvas-slider-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/canvas-slider-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/canvas-slider-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="canvas-slider-response">canvas-slider-response<a class="headerlink" href="#canvas-slider-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-canvas-slider-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-canvas-slider-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin can be used to draw a stimulus on a <a href="https://www.w3schools.com/html/html5_canvas.asp">HTML canvas element</a> and collect a response within a range of values, which is made by dragging a slider. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2094,15 +2099,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 <p>Note: the canvas stimulus is <em>not</em> included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the <code>data</code> parameter.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-canvas-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-canvas-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-canvas-slider-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">canvasSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-canvas-slider-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">canvasSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-canvas-slider-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2110,24 +2115,24 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">colors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;#FF3333&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;#FF6A33&#39;</span><span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">colors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;#FF3333&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;#FF6A33&#39;</span><span class="p">];</span>
 
 <span class="kd">function</span><span class="w"> </span><span class="nx">twoSquares</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w">    </span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s1">&#39;2d&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillRect</span><span class="p">(</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">70</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">1</span><span class="p">];</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillRect</span><span class="p">(</span><span class="mf">260</span><span class="p">,</span><span class="w"> </span><span class="mf">70</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasSliderResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">twoSquares</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;0&#39;</span><span class="p">,</span><span class="s1">&#39;10&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How different would you say the colors of these two squares are on a scale from 0 (the same) to 10 (completely different)&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">color1</span><span class="o">:</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">0</span><span class="p">],</span><span class="w"> </span><span class="nx">color2</span><span class="o">:</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">1</span><span class="p">]}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s1">&#39;2d&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillRect</span><span class="p">(</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">70</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">1</span><span class="p">];</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillRect</span><span class="p">(</span><span class="mf">260</span><span class="p">,</span><span class="w"> </span><span class="mf">70</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">);</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasSliderResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">twoSquares</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;0&#39;</span><span class="p">,</span><span class="s1">&#39;10&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">150</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How different would you say the colors of these two squares are on a scale from 0 (the same) to 10 (completely different)&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="nx">color1</span><span class="o">:</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">0</span><span class="p">],</span><span class="w"> </span><span class="nx">color2</span><span class="o">:</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">1</span><span class="p">]}</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2144,30 +2149,30 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">colors</span><span class="p">;</span><span class="w"></span>
-
-<span class="kd">function</span><span class="w"> </span><span class="nx">twoSquares</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="nx">colors</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s1">&#39;2d&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillRect</span><span class="p">(</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">70</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">1</span><span class="p">];</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillRect</span><span class="p">(</span><span class="mf">260</span><span class="p">,</span><span class="w"> </span><span class="mf">70</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasSliderResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">colors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;darkred&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;cyan&#39;</span><span class="p">];</span><span class="w"></span>
-<span class="w">        </span><span class="nx">twoSquares</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="nx">colors</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Exactly&lt;br&gt;the same&#39;</span><span class="p">,</span><span class="s1">&#39;Totally&lt;br&gt;different&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How different would you say the colors of these two squares are?&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">data</span><span class="p">.</span><span class="nx">color1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">        </span><span class="nx">data</span><span class="p">.</span><span class="nx">color2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">1</span><span class="p">];</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">colors</span><span class="p">;</span>
+
+<span class="kd">function</span><span class="w"> </span><span class="nx">twoSquares</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="nx">colors</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">c</span><span class="p">.</span><span class="nx">getContext</span><span class="p">(</span><span class="s1">&#39;2d&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillRect</span><span class="p">(</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">70</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillStyle</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">1</span><span class="p">];</span>
+<span class="w">    </span><span class="nx">ctx</span><span class="p">.</span><span class="nx">fillRect</span><span class="p">(</span><span class="mf">260</span><span class="p">,</span><span class="w"> </span><span class="mf">70</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">,</span><span class="w"> </span><span class="mf">40</span><span class="p">);</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCanvasSliderResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">c</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">colors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;darkred&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;cyan&#39;</span><span class="p">];</span>
+<span class="w">        </span><span class="nx">twoSquares</span><span class="p">(</span><span class="nx">c</span><span class="p">,</span><span class="w"> </span><span class="nx">colors</span><span class="p">);</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Exactly&lt;br&gt;the same&#39;</span><span class="p">,</span><span class="s1">&#39;Totally&lt;br&gt;different&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">canvas_size</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">200</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How different would you say the colors of these two squares are?&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">data</span><span class="p">.</span><span class="nx">color1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">        </span><span class="nx">data</span><span class="p">.</span><span class="nx">color2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">colors</span><span class="p">[</span><span class="mf">1</span><span class="p">];</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2180,16 +2185,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-canvas-slider-response-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../canvas-keyboard-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: canvas-keyboard-response" rel="prev">
@@ -2248,7 +2262,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2257,7 +2271,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2270,11 +2284,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/categorize-animation/index.html b/7.3/plugins/categorize-animation/index.html
old mode 100755
new mode 100644
index b06a1a351c..68f91ad185
--- a/7.3/plugins/categorize-animation/index.html
+++ b/7.3/plugins/categorize-animation/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/categorize-animation/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/categorize-animation.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="categorize-animation">categorize-animation<a class="headerlink" href="#categorize-animation" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-categorize-animation/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-categorize-animation/CHANGELOG.md">See version history</a>.</p>
 <p>The categorize animation plugin shows a sequence of images at a specified frame rate. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2091,15 +2096,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-categorize-animation.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-categorize-animation.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-categorize-animation
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">categorizeAnimation</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-categorize-animation&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">categorizeAnimation</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-categorize-animation&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2107,18 +2112,18 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">animation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCategorizeAnimation</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">animation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCategorizeAnimation</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
 <span class="w">        </span><span class="s1">&#39;img/happy_face_1.jpg&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="s1">&#39;img/happy_face_2.jpg&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="s1">&#39;img/happy_face_3.jpg&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="s1">&#39;img/happy_face_4.jpg&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="sb">`Press the P or Q key.`</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">],</span><span class="w"></span>
+<span class="w">        </span><span class="s1">&#39;img/happy_face_4.jpg&#39;</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="sb">`Press the P or Q key.`</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">],</span>
 <span class="w">    </span><span class="nx">key_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="p">};</span><span class="w"></span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2135,23 +2140,23 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
 <span class="w">    </span><span class="s1">&#39;img/happy_face_1.jpg&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">    </span><span class="s1">&#39;img/happy_face_2.jpg&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">    </span><span class="s1">&#39;img/happy_face_3.jpg&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="s1">&#39;img/happy_face_4.jpg&#39;</span><span class="w"></span>
-<span class="p">];</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">animation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCategorizeAnimation</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="nx">images</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="sb">`Press the P or Q key.`</span><span class="p">,</span><span class="w"></span>
+<span class="w">    </span><span class="s1">&#39;img/happy_face_4.jpg&#39;</span>
+<span class="p">];</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">animation_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCategorizeAnimation</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="nx">images</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="sb">`Press the P or Q key.`</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">key_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="nx">text_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dax&#39;</span><span class="p">,</span><span class="w"> </span><span class="c1">// the label for the sequence is &#39;Dax&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Correct! This was a %ANS%.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">incorrect_text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Incorrect. This was a %ANS%.&#39;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">    </span><span class="nx">text_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Dax&#39;</span><span class="p">,</span><span class="w"> </span><span class="c1">// the label for the sequence is &#39;Dax&#39;</span>
+<span class="w">    </span><span class="nx">correct_text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Correct! This was a %ANS%.&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">incorrect_text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Incorrect. This was a %ANS%.&#39;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2164,16 +2169,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-categorize-animation-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../canvas-slider-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: canvas-slider-response" rel="prev">
@@ -2232,7 +2246,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2241,7 +2255,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2254,11 +2268,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/categorize-html/index.html b/7.3/plugins/categorize-html/index.html
old mode 100755
new mode 100644
index 028e505269..9fd888721f
--- a/7.3/plugins/categorize-html/index.html
+++ b/7.3/plugins/categorize-html/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/categorize-html/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/categorize-html.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="categorize-html">categorize-html<a class="headerlink" href="#categorize-html" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-categorize-html/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-categorize-html/CHANGELOG.md">See version history</a>.</p>
 <p>The categorize html plugin shows an HTML object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2103,15 +2108,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-categorize-html@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-categorize-html@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-categorize-html.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-categorize-html.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-categorize-html
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">categorizeHtml</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-categorize-html&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">categorizeHtml</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-categorize-html&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2119,16 +2124,16 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">categorization_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCategorizeHtml</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;B&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">key_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">text_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;letter&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">correct_text</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p class=&#39;prompt&#39;&gt;Correct, this is a %ANS%.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">incorrect_text</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p class=&#39;prompt&#39;&gt;Incorrect, this is a %ANS%.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Press p for letter. Press q for number.&lt;/p&gt;&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">categorization_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCategorizeHtml</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;B&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">key_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">text_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;letter&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">],</span>
+<span class="w">        </span><span class="nx">correct_text</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p class=&#39;prompt&#39;&gt;Correct, this is a %ANS%.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">incorrect_text</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p class=&#39;prompt&#39;&gt;Incorrect, this is a %ANS%.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Press p for letter. Press q for number.&lt;/p&gt;&quot;</span>
+<span class="w">    </span><span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2141,16 +2146,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-categorize-html-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../categorize-animation/" class="md-footer__link md-footer__link--prev" aria-label="Previous: categorize-animation" rel="prev">
@@ -2209,7 +2223,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2218,7 +2232,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2231,11 +2245,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/categorize-image/index.html b/7.3/plugins/categorize-image/index.html
old mode 100755
new mode 100644
index 021cc0a0b5..96f790a493
--- a/7.3/plugins/categorize-image/index.html
+++ b/7.3/plugins/categorize-image/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/categorize-image/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/categorize-image.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="categorize-image">categorize-image<a class="headerlink" href="#categorize-image" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-categorize-image/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-categorize-image/CHANGELOG.md">See version history</a>.</p>
 <p>The categorize image plugin shows an image object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2103,15 +2108,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-categorize-image@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-categorize-image@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-categorize-image.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-categorize-image.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-categorize-image
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">categorizeImage</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-categorize-image&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">categorizeImage</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-categorize-image&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2119,16 +2124,16 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">categorization_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCategorizeImage</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">key_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;b&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">text_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Blue&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;r&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;g&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_text</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p class=&#39;prompt&#39;&gt;Correct! The color is %ANS%.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">incorrect_text</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p class=&#39;prompt&#39;&gt;Incorrect. The color is %ANS%.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is the color of this circle (R)ed, (G)reen, or (B)lue?&lt;/p&gt;&quot;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">categorization_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCategorizeImage</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">key_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;b&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">text_answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Blue&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;r&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;g&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">correct_text</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p class=&#39;prompt&#39;&gt;Correct! The color is %ANS%.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">incorrect_text</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p class=&#39;prompt&#39;&gt;Incorrect. The color is %ANS%.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is the color of this circle (R)ed, (G)reen, or (B)lue?&lt;/p&gt;&quot;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2141,16 +2146,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-categorize-image-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../categorize-html/" class="md-footer__link md-footer__link--prev" aria-label="Previous: categorize-html" rel="prev">
@@ -2209,7 +2223,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2218,7 +2232,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2231,11 +2245,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/cloze/index.html b/7.3/plugins/cloze/index.html
old mode 100755
new mode 100644
index bd06f3eaec..7cec206bcc
--- a/7.3/plugins/cloze/index.html
+++ b/7.3/plugins/cloze/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/cloze/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/cloze.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="cloze">cloze<a class="headerlink" href="#cloze" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.2.0. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-cloze/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.2.1. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-cloze/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays a text with certain words omitted. Participants are asked to replace the missing items. Responses are recorded when clicking a button. Responses can be evaluated and a function is called in case of either differences or incomplete answers, making it possible to inform participants about mistakes before proceeding.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2034,15 +2039,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-cloze@1.2.0&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-cloze@1.2.1&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-cloze.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-cloze.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-cloze
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">cloze</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-cloze&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">cloze</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-cloze&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2050,10 +2055,10 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">cloze_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCloze</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;The %% is the largest terrestrial mammal. It lives in both %% and %%.&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">cloze_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCloze</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;The %% is the largest terrestrial mammal. It lives in both %% and %%.&#39;</span>
+<span class="w">    </span><span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2070,12 +2075,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">cloze_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCloze</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Science notebooks have a %%-colored front cover. Math notebooks have a %%-colored front cover.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">allow_blanks</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">mistake_fn</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Please fill in all blanks.&#39;</span><span class="p">);</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">cloze_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCloze</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Science notebooks have a %%-colored front cover. Math notebooks have a %%-colored front cover.&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">allow_blanks</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">mistake_fn</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Please fill in all blanks.&#39;</span><span class="p">);</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2092,13 +2097,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">cloze_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCloze</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;A rectangle has % 4 % corners and a triangle has % 3 %.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">check_answers</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">button_text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Next&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">mistake_fn</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="w"> </span><span class="p">(){</span><span class="w"> </span><span class="nx">alert</span><span class="p">(</span><span class="s2">&quot;Wrong answer. Please check again.&quot;</span><span class="p">)</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">cloze_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychCloze</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;A rectangle has % 4 % corners and a triangle has % 3 %.&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">check_answers</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">button_text</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Next&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">mistake_fn</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="w"> </span><span class="p">(){</span><span class="w"> </span><span class="nx">alert</span><span class="p">(</span><span class="s2">&quot;Wrong answer. Please check again.&quot;</span><span class="p">)</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2111,16 +2116,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-cloze-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../categorize-image/" class="md-footer__link md-footer__link--prev" aria-label="Previous: categorize-image" rel="prev">
@@ -2179,7 +2193,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2188,7 +2202,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2201,11 +2215,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/external-html/index.html b/7.3/plugins/external-html/index.html
old mode 100755
new mode 100644
index e0f85bb741..7c4575e0fc
--- a/7.3/plugins/external-html/index.html
+++ b/7.3/plugins/external-html/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/external-html/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2023,18 +2026,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/external-html.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="external-html">external-html<a class="headerlink" href="#external-html" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-external-html/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-external-html/CHANGELOG.md">See version history</a>.</p>
 <p>The HTML plugin displays an external HTML document (often a consent form). Either a keyboard response or a button press can be used to continue to the next trial. It allows the experimenter to check if conditions are met (such as indicating informed consent) before continuing.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2113,15 +2118,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>In <code>visual</code> simulation mode, the plugin cannot interact with any form elements on the screen other than the <code>cont_btn</code> specified in the trial parameters. If your <code>check_fn</code> requires other user interaction, for example, clicking a checkbox, then you'll need to disable simulation for the trial and complete the interaction manually.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-external-html@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-external-html@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-external-html.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-external-html.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-external-html
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">externalHtml</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-external-html&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">externalHtml</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-external-html&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <h3 id="loading-a-consent-form">Loading a consent form<a class="headerlink" href="#loading-a-consent-form" title="Permanent link">&para;</a></h3>
@@ -2144,26 +2149,26 @@ <h5 id="this-content-would-be-in-a-file-called-external_pagehtml">This content w
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="c1">// sample function that might be used to check if a participant has given</span><span class="w"></span>
-<span class="c1">// consent to participate.</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">check_consent</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">elem</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="nb">document</span><span class="p">.</span><span class="nx">getElementById</span><span class="p">(</span><span class="s1">&#39;consent_checkbox&#39;</span><span class="p">).</span><span class="nx">checked</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">alert</span><span class="p">(</span><span class="s2">&quot;If you wish to participate, you must check the box next to the statement &#39;I agree to participate in this study.&#39;&quot;</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="c1">// declare the block.</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExternalHtml</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">url</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;external_page.html&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">cont_btn</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;start&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">check_fn</span><span class="o">:</span><span class="w"> </span><span class="nx">check_consent</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// sample function that might be used to check if a participant has given</span>
+<span class="c1">// consent to participate.</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">check_consent</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">elem</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="nb">document</span><span class="p">.</span><span class="nx">getElementById</span><span class="p">(</span><span class="s1">&#39;consent_checkbox&#39;</span><span class="p">).</span><span class="nx">checked</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">    </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">alert</span><span class="p">(</span><span class="s2">&quot;If you wish to participate, you must check the box next to the statement &#39;I agree to participate in this study.&#39;&quot;</span><span class="p">);</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span>
+<span class="p">};</span>
+
+<span class="c1">// declare the block.</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExternalHtml</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">url</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;external_page.html&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">cont_btn</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;start&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">check_fn</span><span class="o">:</span><span class="w"> </span><span class="nx">check_consent</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2176,16 +2181,25 @@ <h5 id="this-content-would-be-in-a-file-called-external_pagehtml">This content w
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-external-html-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../cloze/" class="md-footer__link md-footer__link--prev" aria-label="Previous: cloze" rel="prev">
@@ -2244,7 +2258,7 @@ <h5 id="this-content-would-be-in-a-file-called-external_pagehtml">This content w
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2253,7 +2267,7 @@ <h5 id="this-content-would-be-in-a-file-called-external_pagehtml">This content w
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2266,11 +2280,13 @@ <h5 id="this-content-would-be-in-a-file-called-external_pagehtml">This content w
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/free-sort/index.html b/7.3/plugins/free-sort/index.html
old mode 100755
new mode 100644
index dc6e2c84ff..9d69250deb
--- a/7.3/plugins/free-sort/index.html
+++ b/7.3/plugins/free-sort/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/free-sort/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/free-sort.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="free-sort">free-sort<a class="headerlink" href="#free-sort" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-free-sort/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-free-sort/CHANGELOG.md">See version history</a>.</p>
 <p>The free-sort plugin displays one or more images on the screen that the participant can interact with by clicking and dragging with a mouse, or touching and dragging with a touchscreen device. When the trial starts, the images can be positioned outside or inside the sort area. All images must be moved into the sorting area before the participant can click a button to end the trial. All of the moves that the participant performs are recorded, as well as the final positions of all images. This plugin could be useful when asking participants to position images based on similarity to one another, or to recall image spatial locations.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2143,15 +2148,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-free-sort@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-free-sort@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-free-sort.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-free-sort.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-free-sort
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">freeSort</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-free-sort&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">freeSort</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-free-sort&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2159,15 +2164,15 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">sort_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFreeSort</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="nx">sorting_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stim_width</span><span class="o">:</span><span class="w"> </span><span class="mf">80</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stim_height</span><span class="o">:</span><span class="w"> </span><span class="mf">60</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sort_area_width</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">sort_area_height</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Click and drag the images below to sort them so that similar items are close together.&lt;/p&gt;&quot;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">sort_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFreeSort</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="nx">sorting_stimuli</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stim_width</span><span class="o">:</span><span class="w"> </span><span class="mf">80</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stim_height</span><span class="o">:</span><span class="w"> </span><span class="mf">60</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">sort_area_width</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">sort_area_height</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Click and drag the images below to sort them so that similar items are close together.&lt;/p&gt;&quot;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2180,16 +2185,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-free-sort-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../external-html/" class="md-footer__link md-footer__link--prev" aria-label="Previous: external-html" rel="prev">
@@ -2248,7 +2262,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2257,7 +2271,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2270,11 +2284,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/fullscreen/index.html b/7.3/plugins/fullscreen/index.html
old mode 100755
new mode 100644
index f7cc74c3da..d27545473b
--- a/7.3/plugins/fullscreen/index.html
+++ b/7.3/plugins/fullscreen/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/fullscreen/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/fullscreen.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="fullscreen">fullscreen<a class="headerlink" href="#fullscreen" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.2.0. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-fullscreen/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.2.1. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-fullscreen/CHANGELOG.md">See version history</a>.</p>
 <p>The fullscreen plugin allows the experiment to enter or exit fullscreen mode. For security reasons, all browsers require that entry into fullscreen mode is triggered by a user action. To enter fullscreen mode, this plugin has the user click a button. Exiting fullscreen mode can be done without user input.</p>
 <div class="admonition warning">
 <p class="admonition-title">Warning</p>
@@ -2055,15 +2060,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 If you want the display to actually enter fullscreen mode during the simulation, you should disable simulation for the fullscreen trial and manually click the button.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-fullscreen@1.2.0&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-fullscreen@1.2.1&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-fullscreen.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-fullscreen.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-fullscreen
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">fullscreen</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-fullscreen&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">fullscreen</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-fullscreen&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2071,28 +2076,28 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">enter_fullscreen</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFullscreen</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">fullscreen_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_in_fullscreen</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will be in fullscreen mode.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">exit_fullscreen</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFullscreen</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">fullscreen_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">delay_after</span><span class="o">:</span><span class="w"> </span><span class="mf">0</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_after_fullscreen</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will NOT be in fullscreen mode.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">enter_fullscreen</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFullscreen</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">fullscreen_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_in_fullscreen</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will be in fullscreen mode.&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">exit_fullscreen</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychFullscreen</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">fullscreen_mode</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">delay_after</span><span class="o">:</span><span class="w"> </span><span class="mf">0</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_after_fullscreen</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This trial will NOT be in fullscreen mode.&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2105,16 +2110,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-fullscreen-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../free-sort/" class="md-footer__link md-footer__link--prev" aria-label="Previous: free-sort" rel="prev">
@@ -2173,7 +2187,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2182,7 +2196,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2195,11 +2209,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/html-audio-response/index.html b/7.3/plugins/html-audio-response/index.html
old mode 100755
new mode 100644
index f1d31382a2..b44326dee8
--- a/7.3/plugins/html-audio-response/index.html
+++ b/7.3/plugins/html-audio-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/html-audio-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/html-audio-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="html-audio-response">html-audio-response<a class="headerlink" href="#html-audio-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-audio-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-audio-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays HTML content and records audio from the participant via a microphone. </p>
 <p>In order to get access to the microphone, you need to use the <a href="../initialize-microphone/">initialize-microphone plugin</a> on your timeline prior to using this plugin.
 Once access is granted for an experiment you do not need to get permission again.</p>
@@ -2112,15 +2117,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-audio-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-audio-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-html-audio-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlAudioResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-audio-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlAudioResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-audio-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2128,13 +2133,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlAudioResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlAudioResponse</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">    &lt;p style=&quot;font-size:48px; color:red;&quot;&gt;GREEN&lt;/p&gt;</span>
-<span class="sb">    &lt;p&gt;Speak the color of the ink.&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3500</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="sb">    &lt;p&gt;Speak the color of the ink.&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3500</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2151,20 +2156,20 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlAudioResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlAudioResponse</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;Please sing the first few seconds of a song and click the button when you are done.&lt;/p&gt;</span>
-<span class="sb">    `</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">15000</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">allow_playback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="nx">fetch</span><span class="p">(</span><span class="s1">&#39;/save-my-data.php&#39;</span><span class="p">,</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">audio_base64</span><span class="o">:</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="p">})</span><span class="w"></span>
-<span class="w">            </span><span class="p">.</span><span class="nx">then</span><span class="p">((</span><span class="nx">audio_id</span><span class="p">){</span><span class="w"></span>
-<span class="w">                </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">audio_id</span><span class="p">;</span><span class="w"></span>
-<span class="w">            </span><span class="p">});</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="sb">    `</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">15000</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">allow_playback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">        </span><span class="nx">fetch</span><span class="p">(</span><span class="s1">&#39;/save-my-data.php&#39;</span><span class="p">,</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">audio_base64</span><span class="o">:</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="p">})</span>
+<span class="w">            </span><span class="p">.</span><span class="nx">then</span><span class="p">((</span><span class="nx">audio_id</span><span class="p">){</span>
+<span class="w">                </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">audio_id</span><span class="p">;</span>
+<span class="w">            </span><span class="p">});</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>This example assumes that there is a script on your experiment server that accepts the data called <code>save-my-data.php</code>. It also assumes that the script will generate a response with an ID for the stored audio file (<code>audio_id</code>). In the example, we replace the very long base64 representation of the audio file with the generated ID, which could be just a handful of characters. This would let you link files to responses in data analysis, without having to store long audio files in memory during the experiment.</p>
 </div>
@@ -2182,34 +2187,34 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instruction</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instruction</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;img src=&#39;img/10.gif&#39; style=&quot;width:100px; padding: 20px;&quot;&gt;&lt;/img&gt;</span>
 <span class="sb">        &lt;p&gt;Make up a name for this shape. When you have one in mind, click the button and then say the name aloud.&lt;/p&gt;</span>
-<span class="sb">    `</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;I am ready.&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">    `</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;I am ready.&#39;</span><span class="p">]</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">record</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlAudioResponse</span><span class="p">,</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">record</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlAudioResponse</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;img src=&#39;img/10.gif&#39; style=&quot;width:100px; padding: 20px;&quot;&gt;&lt;/img&gt;</span>
 <span class="sb">        &lt;p&gt;Recording...&lt;/p&gt;</span>
-<span class="sb">    `</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">save_audio_url</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">playback</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">()=&gt;{</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">audio_url</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Click the object the matches the spoken name.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/9.gif&#39;</span><span class="p">,</span><span class="s1">&#39;img/10.gif&#39;</span><span class="p">,</span><span class="s1">&#39;img/11.gif&#39;</span><span class="p">,</span><span class="s1">&#39;img/12.gif&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">button_html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;img src=&quot;%choice%&quot; style=&quot;width:100px; padding: 20px;&quot;&gt;&lt;/img&gt;&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">    `</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">save_audio_url</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">playback</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">()=&gt;{</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">audio_url</span><span class="p">;</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Click the object the matches the spoken name.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/9.gif&#39;</span><span class="p">,</span><span class="s1">&#39;img/10.gif&#39;</span><span class="p">,</span><span class="s1">&#39;img/11.gif&#39;</span><span class="p">,</span><span class="s1">&#39;img/12.gif&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">button_html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;img src=&quot;%choice%&quot; style=&quot;width:100px; padding: 20px;&quot;&gt;&lt;/img&gt;&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2222,16 +2227,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-html-audio-response-demo3.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../fullscreen/" class="md-footer__link md-footer__link--prev" aria-label="Previous: fullscreen" rel="prev">
@@ -2290,7 +2304,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2299,7 +2313,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2312,11 +2326,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/html-button-response/index.html b/7.3/plugins/html-button-response/index.html
old mode 100755
new mode 100644
index 8eb9aa6437..70e594dc4c
--- a/7.3/plugins/html-button-response/index.html
+++ b/7.3/plugins/html-button-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/html-button-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/html-button-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="html-button-response">html-button-response<a class="headerlink" href="#html-button-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-button-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-button-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays HTML content and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2068,15 +2073,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-html-button-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-button-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-button-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2084,12 +2089,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size:48px; color:red;&quot;&gt;GREEN&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Red&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Green&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Blue&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;What color is the ink?&lt;/p&gt;&quot;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size:48px; color:red;&quot;&gt;GREEN&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Red&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Green&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Blue&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;What color is the ink?&lt;/p&gt;&quot;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2102,16 +2107,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-html-button-response-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../html-audio-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: html-audio-response" rel="prev">
@@ -2170,7 +2184,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2179,7 +2193,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2192,11 +2206,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/html-keyboard-response/index.html b/7.3/plugins/html-keyboard-response/index.html
old mode 100755
new mode 100644
index d784b2be05..9f199fabc8
--- a/7.3/plugins/html-keyboard-response/index.html
+++ b/7.3/plugins/html-keyboard-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/html-keyboard-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/html-keyboard-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="html-keyboard-response">html-keyboard-response<a class="headerlink" href="#html-keyboard-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-keyboard-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-keyboard-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays HTML content and records responses generated with the keyboard.The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2050,15 +2055,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-html-keyboard-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-keyboard-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-keyboard-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2066,12 +2071,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size:48px; color:green;&quot;&gt;BLUE&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;r&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;g&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is the ink color (r)ed, (g)reen, or (b)lue?&lt;/p&gt;&quot;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size:48px; color:green;&quot;&gt;BLUE&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;r&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;g&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is the ink color (r)ed, (g)reen, or (b)lue?&lt;/p&gt;&quot;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2088,11 +2093,11 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size: 48px;&quot;&gt;+&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;font-size: 48px;&quot;&gt;+&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
 <span class="p">};</span><span class="w">      </span>
 </code></pre></div>
 </div>
@@ -2106,16 +2111,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-html-keyboard-response-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../html-button-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: html-button-response" rel="prev">
@@ -2174,7 +2188,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2183,7 +2197,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2196,11 +2210,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/html-slider-response/index.html b/7.3/plugins/html-slider-response/index.html
old mode 100755
new mode 100644
index 9c9b29b6fc..6871be2314
--- a/7.3/plugins/html-slider-response/index.html
+++ b/7.3/plugins/html-slider-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/html-slider-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/html-slider-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="html-slider-response">html-slider-response<a class="headerlink" href="#html-slider-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-slider-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-slider-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays HTML content and allows the participant to respond by dragging a slider.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2097,15 +2102,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-slider-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-slider-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-html-slider-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-slider-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-slider-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2113,8 +2118,8 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlSliderResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlSliderResponse</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;div style=&quot;width:500px;&quot;&gt;</span>
 <span class="sb">        &lt;p&gt;How likely is it that team A will win this match?&lt;/p&gt;</span>
 <span class="sb">        &lt;div style=&quot;width:240px; float: left;&quot;&gt;</span>
@@ -2125,10 +2130,10 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <span class="sb">            &lt;p&gt;TEAM B&lt;/p&gt;</span>
 <span class="sb">            &lt;p&gt;6 wins, 4 losses, 11 draws&lt;/p&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
-<span class="sb">        &lt;/div&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">require_movement</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;100% chance&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;50% chance&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;0% chance&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="sb">        &lt;/div&gt;`</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">require_movement</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;100% chance&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;50% chance&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;0% chance&#39;</span><span class="p">]</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2141,16 +2146,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-html-slider-response-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../html-keyboard-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: html-keyboard-response" rel="prev">
@@ -2209,7 +2223,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2218,7 +2232,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2231,11 +2245,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/html-video-response/index.html b/7.3/plugins/html-video-response/index.html
old mode 100755
new mode 100644
index 1c711b0eb5..6366f65af8
--- a/7.3/plugins/html-video-response/index.html
+++ b/7.3/plugins/html-video-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/html-video-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/html-video-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="html-video-response">html-video-response<a class="headerlink" href="#html-video-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.1. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-video-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-html-video-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays HTML content and records video from the participant via a webcam. </p>
 <p>In order to get access to the camera, you need to use the <a href="../initialize-camera/">initialize-camera plugin</a> on your timeline prior to using this plugin.
 Once access is granted for an experiment you do not need to get permission again.</p>
@@ -2107,15 +2112,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-video-response@1.0.1&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-html-video-response@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-video-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-html-video-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-html-video-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlVideoResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-video-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">htmlVideoResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-video-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2123,18 +2128,18 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlVideoResponse</span><span class="p">,</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlVideoResponse</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">    &lt;p style=&quot;font-size:48px; color:red;&quot;&gt; &lt;-- &lt;/p&gt;</span>
-<span class="sb">    &lt;p&gt;Turn your head in the direction of the arrow&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3500</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_done_button</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="sb">    &lt;p&gt;Turn your head in the direction of the arrow&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3500</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">show_done_button</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2151,17 +2156,17 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlVideoResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;Make a sad face&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3500</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_done_button</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">allow_playback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlVideoResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;Make a sad face&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3500</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">show_done_button</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">allow_playback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2178,26 +2183,26 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">record</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlVideoResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;Make a sad face.&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_done_button</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">save_video_url</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">classify</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="p">[</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">video_url</span><span class="p">];</span><span class="w"></span>
-<span class="w">    </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Happy&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Sad&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Angry&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Surprised&quot;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;What emotion is this?&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">record</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlVideoResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;Make a sad face.&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">recording_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">show_done_button</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">save_video_url</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">classify</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="p">[</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">video_url</span><span class="p">];</span>
+<span class="w">    </span><span class="p">},</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Happy&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Sad&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Angry&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Surprised&quot;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;What emotion is this?&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2210,16 +2215,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-html-video-response-demo3.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../html-slider-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: html-slider-response" rel="prev">
@@ -2278,7 +2292,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2287,7 +2301,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2300,11 +2314,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/iat-html/index.html b/7.3/plugins/iat-html/index.html
old mode 100755
new mode 100644
index 3f68748a22..c09cfecfaa
--- a/7.3/plugins/iat-html/index.html
+++ b/7.3/plugins/iat-html/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/iat-html/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/iat-html.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="iat-html">iat-html<a class="headerlink" href="#iat-html" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-iat-html/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-iat-html/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin runs a single trial of the <a href="https://implicit.harvard.edu/implicit/iatdetails.html">implicit association test (IAT)</a>, using HTML content as the stimulus.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2097,15 +2102,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-iat-html@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-iat-html@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-iat-html.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-iat-html.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-iat-html
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">iatHtml</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-iat-html&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">iatHtml</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-iat-html&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2113,21 +2118,21 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychIatHtml</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Joyous&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stim_key_association</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">html_when_wrong</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;span style=&quot;color: red; font-size: 80px&quot;&gt;X&lt;/span&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">bottom_instructions</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;If you press the wrong key, a red X will appear. Press the other key to continue&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">force_correct_key_press</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">display_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3000</span><span class="p">,</span><span class="w"> </span><span class="c1">//Only if display_feedback is false</span><span class="w"></span>
-<span class="w">    </span><span class="nx">left_category_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">right_category_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;i&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">left_category_label</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;OLD&#39;</span><span class="p">,</span><span class="s1">&#39;GOOD&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">right_category_label</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;YOUNG&#39;</span><span class="p">,</span><span class="s1">&#39;BAD&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">response_ends_trial</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychIatHtml</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Joyous&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stim_key_association</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">html_when_wrong</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;span style=&quot;color: red; font-size: 80px&quot;&gt;X&lt;/span&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">bottom_instructions</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;If you press the wrong key, a red X will appear. Press the other key to continue&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">force_correct_key_press</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">display_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3000</span><span class="p">,</span><span class="w"> </span><span class="c1">//Only if display_feedback is false</span>
+<span class="w">    </span><span class="nx">left_category_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;e&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">right_category_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;i&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">left_category_label</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;OLD&#39;</span><span class="p">,</span><span class="s1">&#39;GOOD&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">right_category_label</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;YOUNG&#39;</span><span class="p">,</span><span class="s1">&#39;BAD&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">response_ends_trial</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2140,16 +2145,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-iat-html-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../html-video-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: html-video-response" rel="prev">
@@ -2208,7 +2222,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2217,7 +2231,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2230,11 +2244,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/iat-image/index.html b/7.3/plugins/iat-image/index.html
old mode 100755
new mode 100644
index 8d0350af4e..5f14dad954
--- a/7.3/plugins/iat-image/index.html
+++ b/7.3/plugins/iat-image/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/iat-image/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/iat-image.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="iat-image">iat-image<a class="headerlink" href="#iat-image" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-iat-image/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-iat-image/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin runs a single trial of the <a href="https://implicit.harvard.edu/implicit/iatdetails.html">implicit association test (IAT)</a>, using an image as the stimulus.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2097,15 +2102,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-iat-image@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-iat-image@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-iat-image.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-iat-image.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-iat-image
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">iatImage</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-iat-image&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">iatImage</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-iat-image&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2113,21 +2118,21 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial_block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychIatImage</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/iat_old_face.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stim_key_association</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">html_when_wrong</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;span style=&quot;color: red; font-size: 80px&quot;&gt;X&lt;/span&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">bottom_instructions</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;If you press the wrong key, a red X will appear. Press the other key to continue&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">force_correct_key_press</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">display_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3000</span><span class="p">,</span><span class="w"> </span><span class="c1">//Only if display_feedback is false</span><span class="w"></span>
-<span class="w">  </span><span class="nx">left_category_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">right_category_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;i&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">left_category_label</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;OLD&#39;</span><span class="p">,</span><span class="s1">&#39;GOOD&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">right_category_label</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;YOUNG&#39;</span><span class="p">,</span><span class="s1">&#39;BAD&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">response_ends_trial</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial_block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychIatImage</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/iat_old_face.jpg&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stim_key_association</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;left&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">html_when_wrong</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;span style=&quot;color: red; font-size: 80px&quot;&gt;X&lt;/span&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">bottom_instructions</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;If you press the wrong key, a red X will appear. Press the other key to continue&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">force_correct_key_press</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">display_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">3000</span><span class="p">,</span><span class="w"> </span><span class="c1">//Only if display_feedback is false</span>
+<span class="w">  </span><span class="nx">left_category_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;e&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">right_category_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;i&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">left_category_label</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;OLD&#39;</span><span class="p">,</span><span class="s1">&#39;GOOD&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">right_category_label</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;YOUNG&#39;</span><span class="p">,</span><span class="s1">&#39;BAD&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">response_ends_trial</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2140,16 +2145,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-iat-image-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../iat-html/" class="md-footer__link md-footer__link--prev" aria-label="Previous: iat-html" rel="prev">
@@ -2208,7 +2222,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2217,7 +2231,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2230,11 +2244,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/image-button-response/index.html b/7.3/plugins/image-button-response/index.html
old mode 100755
new mode 100644
index 1109071171..fb65778e5b
--- a/7.3/plugins/image-button-response/index.html
+++ b/7.3/plugins/image-button-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/image-button-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/image-button-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="image-button-response">image-button-response<a class="headerlink" href="#image-button-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-image-button-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-image-button-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays an image and records responses generated with a button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting.</p>
 <p>Image files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the images.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2093,15 +2098,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-image-button-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-image-button-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-image-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-image-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-image-button-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">imageButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-image-button-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">imageButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-image-button-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2109,12 +2114,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Happy&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Sad&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is this person happy or sad?&lt;/p&gt;&quot;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.png&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Happy&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Sad&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is this person happy or sad?&lt;/p&gt;&quot;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2127,16 +2132,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-image-button-response-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../iat-image/" class="md-footer__link md-footer__link--prev" aria-label="Previous: iat-image" rel="prev">
@@ -2195,7 +2209,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2204,7 +2218,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2217,11 +2231,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/image-keyboard-response/index.html b/7.3/plugins/image-keyboard-response/index.html
old mode 100755
new mode 100644
index 25440b8d5a..0a30137157
--- a/7.3/plugins/image-keyboard-response/index.html
+++ b/7.3/plugins/image-keyboard-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/image-keyboard-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/image-keyboard-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="image-keyboard-response">image-keyboard-response<a class="headerlink" href="#image-keyboard-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-image-keyboard-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-image-keyboard-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays an image and records responses generated with the keyboard. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.</p>
 <p>Image files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the images.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2075,15 +2080,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-image-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-image-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-image-keyboard-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">imageKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-image-keyboard-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">imageKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-image-keyboard-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2091,12 +2096,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;i&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is this person happy or sad? Press &#39;e&#39; for happy and &#39;i&#39; for sad.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.png&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;i&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Is this person happy or sad? Press &#39;e&#39; for happy and &#39;i&#39; for sad.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2113,13 +2118,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Study this face for 5 seconds.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">5000</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.png&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Study this face for 5 seconds.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">5000</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2132,16 +2137,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-image-keyboard-response-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../image-button-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: image-button-response" rel="prev">
@@ -2200,7 +2214,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2209,7 +2223,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2222,11 +2236,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/image-slider-response/index.html b/7.3/plugins/image-slider-response/index.html
old mode 100755
new mode 100644
index 6e6d70f95f..bbaab16de0
--- a/7.3/plugins/image-slider-response/index.html
+++ b/7.3/plugins/image-slider-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/image-slider-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/image-slider-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="image-slider-response">image-slider-response<a class="headerlink" href="#image-slider-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-image-slider-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-image-slider-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays and image and allows the participant to respond by dragging a slider.</p>
 <p>Image files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the images.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2122,15 +2127,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-image-slider-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-image-slider-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-image-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-image-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-image-slider-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">imageSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-image-slider-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">imageSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-image-slider-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2138,12 +2143,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageSliderResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;happy&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;sad&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;How happy/sad is this person?&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageSliderResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.png&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;happy&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;sad&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;How happy/sad is this person?&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2156,16 +2161,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-image-slider-response-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../image-keyboard-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: image-keyboard-response" rel="prev">
@@ -2224,7 +2238,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2233,7 +2247,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2246,11 +2260,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/initialize-camera/index.html b/7.3/plugins/initialize-camera/index.html
old mode 100755
new mode 100644
index 41d89918b4..e33243f138
--- a/7.3/plugins/initialize-camera/index.html
+++ b/7.3/plugins/initialize-camera/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/initialize-camera/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,16 +1974,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/initialize-camera.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="initialize-camera">initialize-camera<a class="headerlink" href="#initialize-camera" title="Permanent link">&para;</a></h1>
 <p>Current version: 1.0.0 <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-initialize-camera/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin asks the participant to grant permission to access a camera.
@@ -2063,15 +2068,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-initialize-camera.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-initialize-camera.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-initialize-camera
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">initializeCamera</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-initialize-camera&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">initializeCamera</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-initialize-camera&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2079,9 +2084,9 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2094,16 +2099,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-initialize-camera-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../image-slider-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: image-slider-response" rel="prev">
@@ -2162,7 +2176,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2171,7 +2185,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2184,11 +2198,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/initialize-microphone/index.html b/7.3/plugins/initialize-microphone/index.html
old mode 100755
new mode 100644
index dcccdc03d8..37c80bbef6
--- a/7.3/plugins/initialize-microphone/index.html
+++ b/7.3/plugins/initialize-microphone/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/initialize-microphone/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/initialize-microphone.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="initialize-microphone">initialize-microphone<a class="headerlink" href="#initialize-microphone" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-initialize-microphone/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-initialize-microphone/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin asks the participant to grant permission to access a microphone. 
 If multiple microphones are connected to the participant's device, then it allows the participant to pick which device to use. 
 Once access is granted for an experiment you do not need to get permission again.</p>
@@ -2039,15 +2044,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-initialize-microphone.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-initialize-microphone.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-initialize-microphone
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">initializeMicrophone</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-initialize-microphone&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">initializeMicrophone</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-initialize-microphone&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2055,9 +2060,9 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeMicrophone</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeMicrophone</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2070,16 +2075,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-initialize-microphone-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../initialize-camera/" class="md-footer__link md-footer__link--prev" aria-label="Previous: initialize-camera" rel="prev">
@@ -2138,7 +2152,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2147,7 +2161,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2160,11 +2174,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/instructions/index.html b/7.3/plugins/instructions/index.html
old mode 100755
new mode 100644
index 176dcb0867..457e70f8e9
--- a/7.3/plugins/instructions/index.html
+++ b/7.3/plugins/instructions/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/instructions/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2011,18 +2014,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/instructions.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="instructions">instructions<a class="headerlink" href="#instructions" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-instructions/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.4. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-instructions/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin is for showing instructions to the participant. It allows participants to navigate through multiple pages of instructions at their own pace, recording how long the participant spends on each page. Navigation can be done using the mouse or keyboard. participants can be allowed to navigate forwards and backwards through pages, if desired.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2123,15 +2128,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-instructions@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-instructions@1.1.4&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-instructions.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-instructions.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-instructions
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-instructions&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-instructions&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <h4 id="showing-simple-text-instructions">Showing simple text instructions<a class="headerlink" href="#showing-simple-text-instructions" title="Permanent link">&para;</a></h4>
@@ -2140,15 +2145,15 @@ <h4 id="showing-simple-text-instructions">Showing simple text instructions<a cla
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInstructions</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;Welcome to the experiment. Click next to begin.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;This is the second page of instructions.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;This is the final page.&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_clickable_nav</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInstructions</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="s1">&#39;Welcome to the experiment. Click next to begin.&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="s1">&#39;This is the second page of instructions.&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="s1">&#39;This is the final page.&#39;</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">show_clickable_nav</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2166,16 +2171,16 @@ <h4 id="including-images">Including images<a class="headerlink" href="#including
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInstructions</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;Welcome to the experiment. Click next to begin.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;You will be looking at images of arrows: &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInstructions</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="s1">&#39;Welcome to the experiment. Click next to begin.&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="s1">&#39;You will be looking at images of arrows: &#39;</span><span class="w"> </span><span class="o">+</span>
 <span class="w">    </span><span class="s1">&#39;&lt;br&gt;&#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span>
-<span class="w">    </span><span class="s1">&#39;&lt;img src=&quot;con2.png&quot;&gt;&lt;/img&gt;&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_clickable_nav</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="s1">&#39;&lt;img src=&quot;con2.png&quot;&gt;&lt;/img&gt;&#39;</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">show_clickable_nav</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2193,17 +2198,17 @@ <h4 id="changing-button-text">Changing Button Text<a class="headerlink" href="#c
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInstructions</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;Welcome to the experiment. Click next to begin.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;This is the second page of instructions.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;This is the final page.&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">button_label_next</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Continue&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">button_label_previous</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Return to the dark side&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_clickable_nav</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInstructions</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="s1">&#39;Welcome to the experiment. Click next to begin.&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="s1">&#39;This is the second page of instructions.&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="s1">&#39;This is the final page.&#39;</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="nx">button_label_next</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Continue&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">button_label_previous</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Return to the dark side&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">show_clickable_nav</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2216,16 +2221,25 @@ <h4 id="changing-button-text">Changing Button Text<a class="headerlink" href="#c
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-instructions-demo-3.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../initialize-microphone/" class="md-footer__link md-footer__link--prev" aria-label="Previous: initialize-microphone" rel="prev">
@@ -2284,7 +2298,7 @@ <h4 id="changing-button-text">Changing Button Text<a class="headerlink" href="#c
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2293,7 +2307,7 @@ <h4 id="changing-button-text">Changing Button Text<a class="headerlink" href="#c
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2306,11 +2320,13 @@ <h4 id="changing-button-text">Changing Button Text<a class="headerlink" href="#c
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/list-of-plugins/index.html b/7.3/plugins/list-of-plugins/index.html
old mode 100755
new mode 100644
index 5a1c6bfedd..e9edb868ca
--- a/7.3/plugins/list-of-plugins/index.html
+++ b/7.3/plugins/list-of-plugins/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/list-of-plugins/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1869,16 +1872,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/list-of-plugins.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plugins" title="Permanent link">&para;</a></h1>
 <p>These are the plugins that are included in the jsPsych release. </p>
 <p>Additional plugins may be available in the <a href="https://github.com/jspsych/jspsych-contrib">community contributions repository</a>. </p>
@@ -2102,16 +2107,25 @@ <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plu
 </tbody>
 </table>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../../reference/jspsych-pluginAPI/" class="md-footer__link md-footer__link--prev" aria-label="Previous: jsPsych.pluginAPI" rel="prev">
@@ -2170,7 +2184,7 @@ <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plu
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2179,7 +2193,7 @@ <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plu
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2192,11 +2206,13 @@ <h1 id="list-of-plugins">List of Plugins<a class="headerlink" href="#list-of-plu
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/maxdiff/index.html b/7.3/plugins/maxdiff/index.html
old mode 100755
new mode 100644
index 45e1d279ab..0da51fd57a
--- a/7.3/plugins/maxdiff/index.html
+++ b/7.3/plugins/maxdiff/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/maxdiff/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/maxdiff.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="maxdiff">maxdiff<a class="headerlink" href="#maxdiff" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-maxdiff/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-maxdiff/CHANGELOG.md">See version history</a>.</p>
 <p>The maxdiff plugin displays a table with rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. The same alternative cannot be endorsed on both the left and right response columns (e.g. 'most' and 'least') simultaneously.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2050,15 +2055,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-maxdiff@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-maxdiff@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-maxdiff.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-maxdiff.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-maxdiff
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">maxdiff</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-maxdiff&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">maxdiff</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-maxdiff&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2066,12 +2071,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">maxdiff_page</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychMaxdiff</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">alternatives</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;apple&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;orange&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;pear&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;banana&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Most Preferred&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Least Preferred&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt; Please select your &lt;b&gt;most preferred&lt;/b&gt; and &lt;b&gt;least preferred&lt;/b&gt; fruits. &lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">maxdiff_page</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychMaxdiff</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">alternatives</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;apple&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;orange&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;pear&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;banana&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Most Preferred&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Least Preferred&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt; Please select your &lt;b&gt;most preferred&lt;/b&gt; and &lt;b&gt;least preferred&lt;/b&gt; fruits. &lt;/p&gt;&#39;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2084,16 +2089,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-maxdiff-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../instructions/" class="md-footer__link md-footer__link--prev" aria-label="Previous: instructions" rel="prev">
@@ -2152,7 +2166,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2161,7 +2175,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2174,11 +2188,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/mirror-camera/index.html b/7.3/plugins/mirror-camera/index.html
old mode 100755
new mode 100644
index 5153858e94..61e75e7cdc
--- a/7.3/plugins/mirror-camera/index.html
+++ b/7.3/plugins/mirror-camera/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/mirror-camera/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,16 +1974,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/mirror-camera.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="mirror-camera">mirror-camera<a class="headerlink" href="#mirror-camera" title="Permanent link">&para;</a></h1>
 <p>Current version: 1.0.0 <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-mirror-camera/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin shows a live feed of the participant's camera. It can be useful in experiments that need to record video in order to give the participant a chance to see what is in the view of the camera.</p>
@@ -2055,15 +2060,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-mirror-camera@1.0.1&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-mirror-camera@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-mirror-camera.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-mirror-camera.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-mirror-camera
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">mirrorCamera</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-mirror-camera&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">mirrorCamera</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-mirror-camera&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2071,13 +2076,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">init_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychInitializeCamera</span><span class="p">,</span>
+<span class="p">}</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">mirror_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychMirrorCamera</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">mirror_camera</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychMirrorCamera</span><span class="p">,</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2090,16 +2095,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-mirror-camera-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../maxdiff/" class="md-footer__link md-footer__link--prev" aria-label="Previous: maxdiff" rel="prev">
@@ -2158,7 +2172,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2167,7 +2181,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2180,11 +2194,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/preload/index.html b/7.3/plugins/preload/index.html
old mode 100755
new mode 100644
index 49c229e846..106853126b
--- a/7.3/plugins/preload/index.html
+++ b/7.3/plugins/preload/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/preload/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/preload.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="preload">preload<a class="headerlink" href="#preload" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-preload/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-preload/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin loads images, audio, and video files. It is used for loading files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and avoid disruption to the experiment flow. We recommend using this plugin anytime you are loading media files, and especially when your experiment requires large and/or many media files. See the <a href="../overview/media-preloading/">Media Preloading page</a> for more information.</p>
 <p>The preload trial will end as soon as all files have loaded successfully. The trial will end or stop with an error message when one of these two scenarios occurs (whichever comes first): (a) all files have not finished loading when the <code>max_load_time</code> duration is reached, or (b) all file requests have responded with either a load or fail event, and one or more files has failed to load. The <code>continue_after_error</code> parameter determines whether the trial will stop with an error message or end (allowing the experiment to continue) when preloading is not successful.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2120,15 +2125,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>In <code>visual</code> simulation mode, the plugin will run the trial as if the experiment was running normally. Specifying <code>simulation_options.data</code> will not work in <code>visual</code> mode.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-preload.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-preload.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-preload
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-preload&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-preload&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2136,28 +2141,28 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<p><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_2.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_3.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<p><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">auto_preload</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_2.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_3.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 The <code>stimulus</code> parameter from the <code>image-button-response</code> trials will be automatically preloaded.</p>
 </div>
@@ -2175,19 +2180,19 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<p><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/sad_face_1.jpg&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<p><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/sad_face_1.jpg&#39;</span><span class="p">]</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;Study this face&lt;/p&gt;</span>
 <span class="sb">        &lt;img src=&quot;img/sad_face_1.jpg&quot;&gt;&lt;/img&gt;</span>
-<span class="sb">    `</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">    `</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 Because the image is embedded inside HTML from the <code>html-button-response</code> plugin, it will not be automatically preloaded. Instead we can preload manually.</p>
 </div>
@@ -2205,63 +2210,63 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<p><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_2.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_3.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial_1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_2</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_3</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/sad_face_1.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_5</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/sad_face_2.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_6</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/sad_face_3.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial_4</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_5</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_6</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload_block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trials</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">block_1</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">preload_block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trials</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">block_2</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload_block_1</span><span class="p">,</span><span class="w"> </span><span class="nx">block_1</span><span class="p">,</span><span class="w"> </span><span class="nx">preload_block_2</span><span class="p">,</span><span class="w"> </span><span class="nx">block_2</span><span class="p">])</span><span class="w"></span>
+<p><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_1.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_2.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/happy_face_3.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial_1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_2</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_3</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/sad_face_1.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_5</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/sad_face_2.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_6</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageButtonResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/sad_face_3.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Next&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial_4</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_5</span><span class="p">,</span><span class="w"> </span><span class="nx">trial_6</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload_block_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trials</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">block_1</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">preload_block_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trials</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">block_2</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">preload_block_1</span><span class="p">,</span><span class="w"> </span><span class="nx">block_1</span><span class="p">,</span><span class="w"> </span><span class="nx">preload_block_2</span><span class="p">,</span><span class="w"> </span><span class="nx">block_2</span><span class="p">])</span>
 </code></pre></div>
 You can put trials using the <code>preload</code> plugin throughout your experiment to distribute when files are loaded. In the example above, there are two blocks of trials and the images for each are preloaded just before the corresponding block.</p>
 </div>
@@ -2279,11 +2284,11 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="4:2"><input checked="checked" id="__tabbed_4_1" name="__tabbed_4" type="radio" /><input id="__tabbed_4_2" name="__tabbed_4" type="radio" /><div class="tabbed-labels"><label for="__tabbed_4_1">Code</label><label for="__tabbed_4_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/bad_file_path.png&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">show_detailed_errors</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/bad_file_path.png&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">show_detailed_errors</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2297,16 +2302,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 </details>
 <p>For more examples, see the <code>jspsych-preload.html</code> file in the <code>/examples</code> folder of the release and the <a href="../overview/media-preloading">Media Preloading</a> documentation page.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../mirror-camera/" class="md-footer__link md-footer__link--prev" aria-label="Previous: mirror-camera" rel="prev">
@@ -2365,7 +2379,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2374,7 +2388,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2387,11 +2401,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/reconstruction/index.html b/7.3/plugins/reconstruction/index.html
old mode 100755
new mode 100644
index 9e10bccd56..4605320301
--- a/7.3/plugins/reconstruction/index.html
+++ b/7.3/plugins/reconstruction/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/reconstruction/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/reconstruction.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="reconstruction">reconstruction<a class="headerlink" href="#reconstruction" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-reconstruction/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-reconstruction/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin allows a participant to interact with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time.</p>
 <p>The stimulus must be defined through a function that returns an HTML-formatted string. The function should take a single value, which is the parameter that can be modified by the participant. The value can only range from 0 to 1. See the example at the bottom of the page for a sample function.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2051,15 +2056,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-reconstruction@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-reconstruction@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-reconstruction.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-reconstruction.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-reconstruction
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">reconstruction</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-reconstruction&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">reconstruction</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-reconstruction&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2067,30 +2072,30 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">sample_function</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">param</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">50</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">floor</span><span class="p">(</span><span class="nx">param</span><span class="o">*</span><span class="mf">250</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">html</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;display: block; margin: auto; height: 300px; width: 300px; position: relative;&quot;&gt;&#39;</span><span class="o">+</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;&lt;div style=&quot;display: block; position: absolute; top: &#39;</span><span class="o">+</span><span class="p">(</span><span class="mf">150</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">size</span><span class="o">/</span><span class="mf">2</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;px; left:&#39;</span><span class="o">+</span><span class="p">(</span><span class="mf">150</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">size</span><span class="o">/</span><span class="mf">2</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;px; background-color: #000000; &#39;</span><span class="o">+</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;width: &#39;</span><span class="o">+</span><span class="nx">size</span><span class="o">+</span><span class="s1">&#39;px; height: &#39;</span><span class="o">+</span><span class="nx">size</span><span class="o">+</span><span class="s1">&#39;px;&quot;&gt;&lt;/div&gt;&lt;/div&gt;&lt;p&gt;Press &quot;h&quot; to make the square larger. Press &quot;g&quot; to make the square smaller.&lt;/p&gt;&#39;</span><span class="o">+</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;&lt;p&gt;When the square is the same size as the previous one, click Continue.&lt;/p&gt;&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">html</span><span class="p">;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">match_item</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;display: block; margin: auto; height: 300px; width: 300px; position: relative;&quot;&gt;&#39;</span><span class="o">+</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;&lt;div style=&quot;display: block; position: absolute; top: &#39;</span><span class="o">+</span><span class="p">(</span><span class="mf">150</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">210</span><span class="o">/</span><span class="mf">2</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;px; left:&#39;</span><span class="o">+</span><span class="p">(</span><span class="mf">150</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">210</span><span class="o">/</span><span class="mf">2</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;px; background-color: #000000; &#39;</span><span class="o">+</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;width: 210px; height: 210px;&quot;&gt;&lt;/div&gt;&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;c&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Study the size of this square carefully. On the next screen you will have to recreate it. When you are ready, press &quot;c&quot;.&lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">reconstruction</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychReconstruction</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stim_function</span><span class="o">:</span><span class="w"> </span><span class="nx">sample_function</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">starting_value</span><span class="o">:</span><span class="w"> </span><span class="mf">0.5</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">sample_function</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">param</span><span class="p">){</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">50</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">floor</span><span class="p">(</span><span class="nx">param</span><span class="o">*</span><span class="mf">250</span><span class="p">);</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">html</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;display: block; margin: auto; height: 300px; width: 300px; position: relative;&quot;&gt;&#39;</span><span class="o">+</span>
+<span class="w">    </span><span class="s1">&#39;&lt;div style=&quot;display: block; position: absolute; top: &#39;</span><span class="o">+</span><span class="p">(</span><span class="mf">150</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">size</span><span class="o">/</span><span class="mf">2</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;px; left:&#39;</span><span class="o">+</span><span class="p">(</span><span class="mf">150</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nx">size</span><span class="o">/</span><span class="mf">2</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;px; background-color: #000000; &#39;</span><span class="o">+</span>
+<span class="w">    </span><span class="s1">&#39;width: &#39;</span><span class="o">+</span><span class="nx">size</span><span class="o">+</span><span class="s1">&#39;px; height: &#39;</span><span class="o">+</span><span class="nx">size</span><span class="o">+</span><span class="s1">&#39;px;&quot;&gt;&lt;/div&gt;&lt;/div&gt;&lt;p&gt;Press &quot;h&quot; to make the square larger. Press &quot;g&quot; to make the square smaller.&lt;/p&gt;&#39;</span><span class="o">+</span>
+<span class="w">    </span><span class="s1">&#39;&lt;p&gt;When the square is the same size as the previous one, click Continue.&lt;/p&gt;&#39;</span><span class="p">;</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">html</span><span class="p">;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">match_item</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;display: block; margin: auto; height: 300px; width: 300px; position: relative;&quot;&gt;&#39;</span><span class="o">+</span>
+<span class="w">    </span><span class="s1">&#39;&lt;div style=&quot;display: block; position: absolute; top: &#39;</span><span class="o">+</span><span class="p">(</span><span class="mf">150</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">210</span><span class="o">/</span><span class="mf">2</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;px; left:&#39;</span><span class="o">+</span><span class="p">(</span><span class="mf">150</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mf">210</span><span class="o">/</span><span class="mf">2</span><span class="p">)</span><span class="o">+</span><span class="s1">&#39;px; background-color: #000000; &#39;</span><span class="o">+</span>
+<span class="w">    </span><span class="s1">&#39;width: 210px; height: 210px;&quot;&gt;&lt;/div&gt;&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;c&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Study the size of this square carefully. On the next screen you will have to recreate it. When you are ready, press &quot;c&quot;.&lt;/p&gt;&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">reconstruction</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychReconstruction</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">stim_function</span><span class="o">:</span><span class="w"> </span><span class="nx">sample_function</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">starting_value</span><span class="o">:</span><span class="w"> </span><span class="mf">0.5</span><span class="p">,</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2103,16 +2108,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-reconstruction-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../preload/" class="md-footer__link md-footer__link--prev" aria-label="Previous: preload" rel="prev">
@@ -2171,7 +2185,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2180,7 +2194,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2193,11 +2207,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/resize/index.html b/7.3/plugins/resize/index.html
old mode 100755
new mode 100644
index c0e1f5e183..63e9b46b67
--- a/7.3/plugins/resize/index.html
+++ b/7.3/plugins/resize/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/resize/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/resize.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="resize">resize<a class="headerlink" href="#resize" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-resize/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-resize/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin displays a resizable div container that allows the user to drag until the container is the same size as the item being measured. Once the user measures the item as close as possible, clicking the button sets a scaling factor for the div containing jsPsych content. This causes the stimuli that follow to have a known size, independent of monitor resolution.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2061,15 +2066,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-resize@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-resize@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-resize.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-resize.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-resize
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">resize</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-resize&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">resize</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-resize&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2077,13 +2082,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">inputs</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychResize</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">item_width</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mf">3</span><span class="o">/</span><span class="mf">8</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">item_height</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mf">1</span><span class="o">/</span><span class="mf">8</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Click and drag the lower right corner of the box until the box is the same size as a credit card held up to the screen.&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">pixels_per_unit</span><span class="o">:</span><span class="w"> </span><span class="mf">150</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">inputs</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychResize</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">item_width</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mf">3</span><span class="o">/</span><span class="mf">8</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">item_height</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mf">1</span><span class="o">/</span><span class="mf">8</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;Click and drag the lower right corner of the box until the box is the same size as a credit card held up to the screen.&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">pixels_per_unit</span><span class="o">:</span><span class="w"> </span><span class="mf">150</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2096,16 +2101,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-resize-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../reconstruction/" class="md-footer__link md-footer__link--prev" aria-label="Previous: reconstruction" rel="prev">
@@ -2164,7 +2178,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2173,7 +2187,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2186,11 +2200,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/same-different-html/index.html b/7.3/plugins/same-different-html/index.html
old mode 100755
new mode 100644
index 76cd9eec17..86c74441d7
--- a/7.3/plugins/same-different-html/index.html
+++ b/7.3/plugins/same-different-html/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/same-different-html/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/same-different-html.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="same-different-html">same-different-html<a class="headerlink" href="#same-different-html" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-same-different-html/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-same-different-html/CHANGELOG.md">See version history</a>.</p>
 <p>The same-different-html plugin displays two stimuli sequentially. Stimuli are HTML objects. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2094,15 +2099,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-same-different-html@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-same-different-html@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-same-different-html.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-same-different-html.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-same-different-html
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">sameDifferentHtml</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-same-different-html&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">sameDifferentHtml</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-same-different-html&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2110,19 +2115,19 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSameDifferentHtml</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSameDifferentHtml</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
 <span class="w">    </span><span class="s1">&#39;&lt;p style=&quot;font-size:30px;&quot;&gt;Climbing&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="s1">&#39;&lt;p style=&quot;font-size:30px;&quot;&gt;Walking&lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
+<span class="w">    </span><span class="s1">&#39;&lt;p style=&quot;font-size:30px;&quot;&gt;Walking&lt;/p&gt;&#39;</span>
+<span class="w">  </span><span class="p">],</span>
 <span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;Press &#39;s&#39; if the activities require the same amount of physical exertion.&lt;/p&gt;</span>
-<span class="sb">    &lt;p&gt;Press &#39;d&#39; if the activities require different amount of physical exertion.&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">same_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;s&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">different_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;d&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">first_stim_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">800</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;different&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">    &lt;p&gt;Press &#39;d&#39; if the activities require different amount of physical exertion.&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">same_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;s&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">different_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;d&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">first_stim_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">800</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;different&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2135,16 +2140,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-same-different-html-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../resize/" class="md-footer__link md-footer__link--prev" aria-label="Previous: resize" rel="prev">
@@ -2203,7 +2217,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2212,7 +2226,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2225,11 +2239,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/same-different-image/index.html b/7.3/plugins/same-different-image/index.html
old mode 100755
new mode 100644
index 46609c6d12..d1b3c8f019
--- a/7.3/plugins/same-different-image/index.html
+++ b/7.3/plugins/same-different-image/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/same-different-image/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/same-different-image.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="same-different-image">same-different-image<a class="headerlink" href="#same-different-image" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-same-different-image/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-same-different-image/CHANGELOG.md">See version history</a>.</p>
 <p>The same-different-image plugin displays two stimuli sequentially. Stimuli are images. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2094,15 +2099,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-same-different-image@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-same-different-image@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-same-different-image.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-same-different-image.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-same-different-image
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">sameDifferentImage</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-same-different-image&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">sameDifferentImage</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-same-different-image&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2110,19 +2115,19 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSameDifferentImage</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSameDifferentImage</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
 <span class="w">    </span><span class="s1">&#39;img/happy_face_1.jpg&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="s1">&#39;img/sad_face_3.jpg&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
+<span class="w">    </span><span class="s1">&#39;img/sad_face_3.jpg&#39;</span>
+<span class="w">  </span><span class="p">],</span>
 <span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;Press s if the faces had the same emotional expression.&lt;/p&gt;</span>
-<span class="sb">    &lt;p&gt;Press d if the faces had different emotional expressions.&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">same_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;s&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">different_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;d&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">first_stim_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">800</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;different&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">    &lt;p&gt;Press d if the faces had different emotional expressions.&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">same_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;s&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">different_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;d&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">first_stim_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">800</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">answer</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;different&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2135,16 +2140,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-same-different-image-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../same-different-html/" class="md-footer__link md-footer__link--prev" aria-label="Previous: same-different-html" rel="prev">
@@ -2203,7 +2217,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2212,7 +2226,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2225,11 +2239,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/serial-reaction-time-mouse/index.html b/7.3/plugins/serial-reaction-time-mouse/index.html
old mode 100755
new mode 100644
index 14ed579600..52e49a2491
--- a/7.3/plugins/serial-reaction-time-mouse/index.html
+++ b/7.3/plugins/serial-reaction-time-mouse/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/serial-reaction-time-mouse/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/serial-reaction-time-mouse.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="serial-reaction-time-mouse">serial-reaction-time-mouse<a class="headerlink" href="#serial-reaction-time-mouse" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-serial-reaction-time-mouse/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-serial-reaction-time-mouse/CHANGELOG.md">See version history</a>.</p>
 <p>The serial reaction time mouse plugin implements a generalized version of the SRT task <a href="https://doi.org/10.1016%2F0010-0285%2887%2990002-8">(Nissen &amp; Bullmer, 1987)</a>. Squares are displayed in a grid-based system on the screen, and one square changes color. The participant must click on the square that changes color.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2084,15 +2089,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-serial-reaction-time-mouse.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-serial-reaction-time-mouse.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-serial-reaction-time-mouse
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">serialReactionTimeMouse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-serial-reaction-time-mouse&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">serialReactionTimeMouse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-serial-reaction-time-mouse&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2100,30 +2105,30 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">grid</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span><span class="w"></span>
-<span class="p">]</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">2</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">3</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">grid</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span>
+<span class="p">]</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">]</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">2</span><span class="p">]</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">3</span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2140,36 +2145,36 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">grid</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span><span class="w"></span>
-<span class="p">]</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;#006738&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">2</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;#F78F1E&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">2</span><span class="p">,</span><span class="mf">2</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;#13B24B&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">2</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;#E74921&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">grid</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">],</span>
+<span class="w">  </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span>
+<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span>
+<span class="p">]</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">target_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;#006738&#39;</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">2</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">target_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;#F78F1E&#39;</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">2</span><span class="p">,</span><span class="mf">2</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">target_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;#13B24B&#39;</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTimeMouse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">2</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">target_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;#E74921&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2182,16 +2187,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-serial-reaction-time-mouse-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../serial-reaction-time/" class="md-footer__link md-footer__link--prev" aria-label="Previous: serial-reaction-time" rel="prev">
@@ -2250,7 +2264,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2259,7 +2273,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2272,11 +2286,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/serial-reaction-time/index.html b/7.3/plugins/serial-reaction-time/index.html
old mode 100755
new mode 100644
index 5f1ac911d8..7754dbdba4
--- a/7.3/plugins/serial-reaction-time/index.html
+++ b/7.3/plugins/serial-reaction-time/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/serial-reaction-time/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/serial-reaction-time.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="serial-reaction-time">serial-reaction-time<a class="headerlink" href="#serial-reaction-time" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-serial-reaction-time/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.4. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-serial-reaction-time/CHANGELOG.md">See version history</a>.</p>
 <p>The serial reaction time plugin implements a generalized version of the SRT task <a href="https://doi.org/10.1016%2F0010-0285%2887%2990002-8">(Nissen &amp; Bullemer, 1987)</a>. Squares are displayed in a grid-based system on the screen, and one square changes color. The participant presses a key that corresponds to the darkened key. Feedback is optionally displayed, showing the participant which square the key they pressed matches.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2096,15 +2101,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.4&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-serial-reaction-time.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-serial-reaction-time.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-serial-reaction-time
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">serialReactionTime</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-serial-reaction-time&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">serialReactionTime</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-serial-reaction-time&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2112,44 +2117,44 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Use the S, F, H, and K keys to respond.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">grid</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span><span class="w"></span>
-<span class="p">]</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">response_map</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="s1">&#39;s&#39;</span><span class="p">,</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;h&#39;</span><span class="p">,</span><span class="s1">&#39;k&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">]</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">2</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">3</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Use the S, F, H, and K keys to respond.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">grid</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span>
+<span class="p">]</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">response_map</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">[</span><span class="s1">&#39;s&#39;</span><span class="p">,</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;h&#39;</span><span class="p">,</span><span class="s1">&#39;k&#39;</span><span class="p">]</span>
+<span class="p">]</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">]</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">2</span><span class="p">]</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">3</span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2166,54 +2171,54 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Use the R, I, V, and M keys to respond.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">grid</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span><span class="w"></span>
-<span class="p">]</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">response_map</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="s1">&#39;r&#39;</span><span class="p">,</span><span class="s1">&#39;i&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="p">[</span><span class="s1">&#39;v&#39;</span><span class="p">,</span><span class="s1">&#39;m&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">]</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">show_response_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">feedback_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">show_response_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">feedback_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">show_response_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">feedback_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">show_response_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">feedback_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Use the R, I, V, and M keys to respond.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">grid</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">],</span>
+<span class="w">  </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">]</span>
+<span class="p">]</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">response_map</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">[</span><span class="s1">&#39;r&#39;</span><span class="p">,</span><span class="s1">&#39;i&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="p">[</span><span class="s1">&#39;v&#39;</span><span class="p">,</span><span class="s1">&#39;m&#39;</span><span class="p">]</span>
+<span class="p">]</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">show_response_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">feedback_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">0</span><span class="p">,</span><span class="mf">1</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">show_response_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">feedback_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">show_response_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">feedback_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="p">}</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_4</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSerialReactionTime</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">grid</span><span class="o">:</span><span class="w"> </span><span class="nx">grid</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="nx">response_map</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">0</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">show_response_feedback</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">feedback_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2226,16 +2231,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-serial-reaction-time-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../same-different-image/" class="md-footer__link md-footer__link--prev" aria-label="Previous: same-different-image" rel="prev">
@@ -2294,7 +2308,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2303,7 +2317,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2316,11 +2330,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/sketchpad/index.html b/7.3/plugins/sketchpad/index.html
old mode 100755
new mode 100644
index f13fd991db..e275efca87
--- a/7.3/plugins/sketchpad/index.html
+++ b/7.3/plugins/sketchpad/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/sketchpad/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/sketchpad.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="sketchpad">sketchpad<a class="headerlink" href="#sketchpad" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-sketchpad/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.4. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-sketchpad/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin creates an interactive canvas that the participant can draw on using their mouse or touchscreen.
 It can be used for sketching tasks, like asking the participant to draw a particular object.
 It can also be used for some image segmentation or annotation tasks by setting the <code>background_image</code> parameter to render an image on the canvas.</p>
@@ -2215,15 +2220,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-sketchpad@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-sketchpad@1.0.4&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-sketchpad.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-sketchpad.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-sketchpad
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">sketchpad</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-sketchpad&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">sketchpad</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-sketchpad&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2231,14 +2236,14 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSketchpad</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Draw an apple!&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt_location</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;abovecanvas&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">canvas_width</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">canvas_height</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">canvas_border_width</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSketchpad</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Draw an apple!&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">prompt_location</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;abovecanvas&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">canvas_width</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">canvas_height</span><span class="o">:</span><span class="w"> </span><span class="mf">300</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">canvas_border_width</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2255,16 +2260,16 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSketchpad</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;width:380px&quot;&gt;Circle the mouth using red. Circle the eyes using blue.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt_location</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;abovecanvas&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stroke_color_palette</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;red&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stroke_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;red&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">background_image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/sad_face_4.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">canvas_width</span><span class="o">:</span><span class="w"> </span><span class="mf">380</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">canvas_height</span><span class="o">:</span><span class="w"> </span><span class="mf">252</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSketchpad</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p style=&quot;width:380px&quot;&gt;Circle the mouth using red. Circle the eyes using blue.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">prompt_location</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;abovecanvas&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stroke_color_palette</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;red&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;blue&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">stroke_color</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;red&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">background_image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/sad_face_4.jpg&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">canvas_width</span><span class="o">:</span><span class="w"> </span><span class="mf">380</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">canvas_height</span><span class="o">:</span><span class="w"> </span><span class="mf">252</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2281,24 +2286,24 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">draw</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSketchpad</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Draw the first animal that comes to mind. You have 30 seconds!&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt_location</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;belowcanvas&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">30000</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">show_countdown_trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">label</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">imageData</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">png</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;</span><span class="si">${</span><span class="nx">imageData</span><span class="si">}</span><span class="sb">&quot;&gt;&lt;/img&gt;`</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What animal did you draw?&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">draw</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSketchpad</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Draw the first animal that comes to mind. You have 30 seconds!&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">prompt_location</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;belowcanvas&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">30000</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">show_countdown_trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">label</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">imageData</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">png</span><span class="p">;</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;</span><span class="si">${</span><span class="nx">imageData</span><span class="si">}</span><span class="sb">&quot;&gt;&lt;/img&gt;`</span><span class="p">;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What animal did you draw?&#39;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2311,16 +2316,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-sketchpad-demo3.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../serial-reaction-time-mouse/" class="md-footer__link md-footer__link--prev" aria-label="Previous: serial-reaction-time-mouse" rel="prev">
@@ -2379,7 +2393,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2388,7 +2402,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2401,11 +2415,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/survey-html-form/index.html b/7.3/plugins/survey-html-form/index.html
old mode 100755
new mode 100644
index 24b60fd4f9..0e5e745955
--- a/7.3/plugins/survey-html-form/index.html
+++ b/7.3/plugins/survey-html-form/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/survey-html-form/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/survey-html-form.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="survey-html-form">survey-html-form<a class="headerlink" href="#survey-html-form" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-html-form/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-html-form/CHANGELOG.md">See version history</a>.</p>
 <p>The survey-html-form plugin displays a set of <code>&lt;inputs&gt;</code> from a HTML string. The type of input can be freely chosen, for a list of possible input types see the <a href="https://developer.mozilla.org/en-US/docs/Web/HTML/Element/input">MDN page on inputs</a>. The participant provides answers to the input fields.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2061,15 +2066,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-html-form.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-html-form.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-survey-html-form
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyHtmlForm</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-html-form&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyHtmlForm</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-html-form&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2077,11 +2082,11 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyHtmlForm</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How are you feeling &lt;b&gt;right now?&lt;/b&gt;&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt; I am feeling &lt;input name=&quot;first&quot; type=&quot;text&quot; /&gt;, &lt;input name=&quot;second&quot; type=&quot;text&quot; /&gt;, and &lt;input name=&quot;third&quot; type=&quot;text&quot; /&gt;.&lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyHtmlForm</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;How are you feeling &lt;b&gt;right now?&lt;/b&gt;&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt; I am feeling &lt;input name=&quot;first&quot; type=&quot;text&quot; /&gt;, &lt;input name=&quot;second&quot; type=&quot;text&quot; /&gt;, and &lt;input name=&quot;third&quot; type=&quot;text&quot; /&gt;.&lt;/p&gt;&#39;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2098,12 +2103,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<p><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyHtmlForm</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;What is your favorite bird?&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;My favorite bird is &lt;input type=&quot;text&quot; id=&quot;test-resp-box&quot; name=&quot;response&quot; size=&quot;10&quot; /&gt;&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">autofocus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;test-resp-box&#39;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<p><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyHtmlForm</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;What is your favorite bird?&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">html</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;My favorite bird is &lt;input type=&quot;text&quot; id=&quot;test-resp-box&quot; name=&quot;response&quot; size=&quot;10&quot; /&gt;&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">autofocus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;test-resp-box&#39;</span>
+<span class="p">};</span>
 </code></pre></div>
 In this example, the browser will focus on the element with the ID <code>test-resp-box</code> when the trial loads. For <code>&lt;input type="text"&gt;</code> elements, this means that the cursor will appear inside the text box.</p>
 </div>
@@ -2117,16 +2122,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-survey-html-form-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../survey/" class="md-footer__link md-footer__link--prev" aria-label="Previous: survey" rel="prev">
@@ -2185,7 +2199,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2194,7 +2208,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2207,11 +2221,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/survey-likert/index.html b/7.3/plugins/survey-likert/index.html
old mode 100755
new mode 100644
index 9921ccbd52..1eec459aa4
--- a/7.3/plugins/survey-likert/index.html
+++ b/7.3/plugins/survey-likert/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/survey-likert/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/survey-likert.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="survey-likert">survey-likert<a class="headerlink" href="#survey-likert" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-likert/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-likert/CHANGELOG.md">See version history</a>.</p>
 <p>The survey-likert plugin displays a set of questions with Likert scale responses. The participant responds by selecting a radio button.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2050,15 +2055,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-likert@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-likert@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-likert.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-likert.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-survey-likert
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyLikert</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-likert&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyLikert</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-likert&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2066,21 +2071,21 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyLikert</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyLikert</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;I like vegetables.&quot;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
+<span class="w">      </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
 <span class="w">        </span><span class="s2">&quot;Strongly Disagree&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="s2">&quot;Disagree&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="s2">&quot;Neutral&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="s2">&quot;Agree&quot;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="s2">&quot;Strongly Agree&quot;</span><span class="w"></span>
-<span class="w">      </span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">        </span><span class="s2">&quot;Strongly Agree&quot;</span>
+<span class="w">      </span><span class="p">]</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2097,23 +2102,23 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">likert_scale</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">likert_scale</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
 <span class="w">  </span><span class="s2">&quot;Strongly Disagree&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">  </span><span class="s2">&quot;Disagree&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">  </span><span class="s2">&quot;Neutral&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">  </span><span class="s2">&quot;Agree&quot;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">  </span><span class="s2">&quot;Strongly Agree&quot;</span><span class="w"></span>
-<span class="p">];</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyLikert</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;I like vegetables.&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Vegetables&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="nx">likert_scale</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;I like fruit.&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Fruit&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="nx">likert_scale</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;I like meat.&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Meat&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="nx">likert_scale</span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">randomize_question_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">  </span><span class="s2">&quot;Strongly Agree&quot;</span>
+<span class="p">];</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyLikert</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;I like vegetables.&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Vegetables&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="nx">likert_scale</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;I like fruit.&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Fruit&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="nx">likert_scale</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;I like meat.&quot;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Meat&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="nx">likert_scale</span><span class="p">},</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nx">randomize_question_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2126,16 +2131,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-survey-likert-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../survey-html-form/" class="md-footer__link md-footer__link--prev" aria-label="Previous: survey-html-form" rel="prev">
@@ -2194,7 +2208,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2203,7 +2217,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2216,11 +2230,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/survey-multi-choice/index.html b/7.3/plugins/survey-multi-choice/index.html
old mode 100755
new mode 100644
index b46b28a5be..70f58bbf2c
--- a/7.3/plugins/survey-multi-choice/index.html
+++ b/7.3/plugins/survey-multi-choice/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/survey-multi-choice/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/survey-multi-choice.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="survey-multi-choice">survey-multi-choice<a class="headerlink" href="#survey-multi-choice" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-multi-choice/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-multi-choice/CHANGELOG.md">See version history</a>.</p>
 <p>The survey-multi-choice plugin displays a set of questions with multiple choice response fields. The participant selects a single answer.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2044,15 +2049,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-multi-choice.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-multi-choice.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-survey-multi-choice
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyMultiChoice</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-multi-choice&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyMultiChoice</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-multi-choice&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2060,23 +2065,23 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyMultiChoice</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyMultiChoice</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of the following do you like the most?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;VegetablesLike&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Tomato&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Cucumber&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Eggplant&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Corn&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Peas&#39;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
+<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
 <span class="w">    </span><span class="p">},</span><span class="w"> </span>
-<span class="w">    </span><span class="p">{</span><span class="w"></span>
+<span class="w">    </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of the following do you like the least?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;FruitDislike&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Apple&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Banana&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Orange&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Grape&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Strawberry&#39;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2093,25 +2098,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyMultiChoice</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyMultiChoice</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of the following do you like the most?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;VegetablesLike&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Tomato&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Cucumber&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Eggplant&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Corn&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Peas&#39;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">horizontal</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
+<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">horizontal</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
 <span class="w">    </span><span class="p">},</span><span class="w"> </span>
-<span class="w">    </span><span class="p">{</span><span class="w"></span>
+<span class="w">    </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of the following do you like the least?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;FruitDislike&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Apple&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Banana&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Orange&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Grape&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Strawberry&#39;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">horizontal</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">horizontal</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2124,16 +2129,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-survey-multi-choice-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../survey-likert/" class="md-footer__link md-footer__link--prev" aria-label="Previous: survey-likert" rel="prev">
@@ -2192,7 +2206,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2201,7 +2215,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2214,11 +2228,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/survey-multi-select/index.html b/7.3/plugins/survey-multi-select/index.html
old mode 100755
new mode 100644
index ea29d7ade3..7b28a85eb0
--- a/7.3/plugins/survey-multi-select/index.html
+++ b/7.3/plugins/survey-multi-select/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/survey-multi-select/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/survey-multi-select.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="survey-multi-select">survey-multi-select<a class="headerlink" href="#survey-multi-select" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-multi-select/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-multi-select/CHANGELOG.md">See version history</a>.</p>
 <p>The survey-multi-select plugin displays a set of questions with multiple select response fields. The participant can select multiple answers.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2050,15 +2055,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-multi-select@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-multi-select@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-multi-select.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-multi-select.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-survey-multi-select
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyMultiSelect</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-multi-select&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyMultiSelect</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-multi-select&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2066,26 +2071,26 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyMultiSelect</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyMultiSelect</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of these colors do you like?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Red&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Yellow&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Green&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Blue&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Black&quot;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">horizontal</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Colors&#39;</span><span class="w"></span>
+<span class="w">      </span><span class="nx">horizontal</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Colors&#39;</span>
 <span class="w">    </span><span class="p">},</span><span class="w"> </span>
-<span class="w">    </span><span class="p">{</span><span class="w"></span>
+<span class="w">    </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of these foods do you like?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Apples&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Bananas&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Carrots&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Donuts&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Eggplant&quot;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">horizontal</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Foods&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
+<span class="w">      </span><span class="nx">horizontal</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Foods&#39;</span>
+<span class="w">    </span><span class="p">}</span>
 <span class="w">  </span><span class="p">],</span><span class="w"> </span>
-<span class="w">  </span><span class="nx">randomize_question_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">  </span><span class="nx">randomize_question_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2098,16 +2103,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-survey-multi-select-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../survey-multi-choice/" class="md-footer__link md-footer__link--prev" aria-label="Previous: survey-multi-choice" rel="prev">
@@ -2166,7 +2180,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2175,7 +2189,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2188,11 +2202,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/survey-text/index.html b/7.3/plugins/survey-text/index.html
old mode 100755
new mode 100644
index 97db8c3a7e..5b190195d1
--- a/7.3/plugins/survey-text/index.html
+++ b/7.3/plugins/survey-text/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/survey-text/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/survey-text.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="survey-text">survey-text<a class="headerlink" href="#survey-text" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-text/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey-text/CHANGELOG.md">See version history</a>.</p>
 <p>The survey-text plugin displays a set of questions with free response text fields. The participant types in answers.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2044,15 +2049,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-text@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey-text@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-text.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey-text.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-survey-text
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyText</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-text&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">surveyText</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey-text&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2060,12 +2065,12 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;How old are you?&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;How old are you?&#39;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2082,13 +2087,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What is your date of birth?&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">placeholder</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;mm/dd/yyyy&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What country do you currently live in?&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What is your date of birth?&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">placeholder</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;mm/dd/yyyy&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What country do you currently live in?&#39;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2105,13 +2110,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What did you eat for breakfast?&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Breakfast&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What did you eat for lunch?&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Lunch&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What did you eat for breakfast?&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Breakfast&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;What did you eat for lunch?&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Lunch&#39;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2128,13 +2133,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="4:2"><input checked="checked" id="__tabbed_4_1" name="__tabbed_4" type="radio" /><input id="__tabbed_4_2" name="__tabbed_4" type="radio" /><div class="tabbed-labels"><label for="__tabbed_4_1">Code</label><label for="__tabbed_4_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;img/navarro_burst_03.jpg&quot; style=&quot;width:400px;&quot;&gt;&lt;/img&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Describe your reaction to the image above&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">rows</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurveyText</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">preamble</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;img src=&quot;img/navarro_burst_03.jpg&quot; style=&quot;width:400px;&quot;&gt;&lt;/img&gt;`</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">questions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Describe your reaction to the image above&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">rows</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <p><em>The artwork in this demo is by <a href="https://art.djnavarro.net/">Danielle Navarro</a></em></p>
 </div>
@@ -2148,16 +2153,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-survey-text-demo4.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../survey-multi-select/" class="md-footer__link md-footer__link--prev" aria-label="Previous: survey-multi-select" rel="prev">
@@ -2216,7 +2230,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2225,7 +2239,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2238,11 +2252,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/survey/index.html b/7.3/plugins/survey/index.html
old mode 100755
new mode 100644
index efd33ab13d..a58d0092cc
--- a/7.3/plugins/survey/index.html
+++ b/7.3/plugins/survey/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/survey/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2163,18 +2166,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/survey.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="survey">survey<a class="headerlink" href="#survey" title="Permanent link">&para;</a></h1>
-<p>Current version: 0.2.1. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 0.2.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-survey/CHANGELOG.md">See version history</a>.</p>
 <p>The survey plugin displays one or more questions of different types, on one or more pages that the participant can navigate. This plugin is built on top of the <a href="https://surveyjs.io/">SurveyJS</a> library.</p>
 <p>The supported question types are: </p>
 <ul>
@@ -2193,10 +2198,10 @@ <h1 id="survey">survey<a class="headerlink" href="#survey" title="Permanent link
 </div>
 <h2 id="css">CSS<a class="headerlink" href="#css" title="Permanent link">&para;</a></h2>
 <p>This plugin uses an additional stylesheet called <code>survey.css</code>. You can load it via: </p>
-<div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-survey@0.2.1/css/survey.css&quot;</span><span class="p">&gt;</span>
+<div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">link</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-survey@0.2.2/css/survey.css&quot;</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>If you are using a bundler such as <a href="https://webpack.js.org/">webpack</a>, you can also import it in JavaScript as follows, depending on your bundler configuration:
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey/css/survey.css&#39;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey/css/survey.css&#39;</span>
 </code></pre></div></p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. 
@@ -2629,15 +2634,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey@0.2.1&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-survey@0.2.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-survey.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-survey
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">survey</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">survey</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-survey&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2645,31 +2650,31 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;html&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Please answer the following questions:&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-choice&#39;</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;html&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Please answer the following questions:&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-choice&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of the following do you like the most?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;VegetablesLike&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Tomato&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Cucumber&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Eggplant&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Corn&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Peas&#39;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
+<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
 <span class="w">      </span><span class="p">},</span><span class="w"> </span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-select&#39;</span><span class="p">,</span><span class="w"></span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-select&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of the following do you like?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;FruitLike&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Apple&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Banana&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Orange&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Grape&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Strawberry&#39;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2686,48 +2691,48 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;text&#39;</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;text&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Where were you born?&quot;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">placeholder</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;City, State, Country&#39;</span><span class="p">,</span><span class="w"></span>
+<span class="w">        </span><span class="nx">placeholder</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;City, State, Country&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;birthplace&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
+<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
 <span class="w">      </span><span class="p">},</span><span class="w"> </span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;text&#39;</span><span class="p">,</span><span class="w"></span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;text&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;How old are you?&quot;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;age&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">textbox_columns</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-choice&#39;</span><span class="p">,</span><span class="w"></span>
+<span class="w">        </span><span class="nx">textbox_columns</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-choice&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;What&amp;#39;s your favorite color?&quot;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;blue&#39;</span><span class="p">,</span><span class="s1">&#39;yellow&#39;</span><span class="p">,</span><span class="s1">&#39;pink&#39;</span><span class="p">,</span><span class="s1">&#39;teal&#39;</span><span class="p">,</span><span class="s1">&#39;orange&#39;</span><span class="p">,</span><span class="s1">&#39;lime green&#39;</span><span class="p">,</span><span class="s1">&#39;other&#39;</span><span class="p">,</span><span class="s1">&#39;none of these&#39;</span><span class="p">],</span><span class="w"></span>
+<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;blue&#39;</span><span class="p">,</span><span class="s1">&#39;yellow&#39;</span><span class="p">,</span><span class="s1">&#39;pink&#39;</span><span class="p">,</span><span class="s1">&#39;teal&#39;</span><span class="p">,</span><span class="s1">&#39;orange&#39;</span><span class="p">,</span><span class="s1">&#39;lime green&#39;</span><span class="p">,</span><span class="s1">&#39;other&#39;</span><span class="p">,</span><span class="s1">&#39;none of these&#39;</span><span class="p">],</span>
 <span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;FavColor&#39;</span><span class="p">,</span><span class="w"> </span>
 <span class="w">      </span><span class="p">},</span><span class="w"> </span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-select&#39;</span><span class="p">,</span><span class="w"></span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-select&#39;</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Which of these animals do you like? Select all that apply.&quot;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;lion&#39;</span><span class="p">,</span><span class="s1">&#39;squirrel&#39;</span><span class="p">,</span><span class="s1">&#39;badger&#39;</span><span class="p">,</span><span class="s1">&#39;whale&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">option_reorder</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;random&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">columns</span><span class="o">:</span><span class="w"> </span><span class="mf">0</span><span class="p">,</span><span class="w"></span>
+<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;lion&#39;</span><span class="p">,</span><span class="s1">&#39;squirrel&#39;</span><span class="p">,</span><span class="s1">&#39;badger&#39;</span><span class="p">,</span><span class="s1">&#39;whale&#39;</span><span class="p">],</span>
+<span class="w">        </span><span class="nx">option_reorder</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;random&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">columns</span><span class="o">:</span><span class="w"> </span><span class="mf">0</span><span class="p">,</span>
 <span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;AnimalLike&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">title</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;My questionnaire&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">button_label_next</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Continue&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">button_label_back</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Previous&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">button_label_finish</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Submit&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">show_question_numbers</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;onPage&#39;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nx">title</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;My questionnaire&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">button_label_next</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Continue&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">button_label_back</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Previous&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">button_label_finish</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Submit&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">show_question_numbers</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;onPage&#39;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2744,65 +2749,65 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;likert&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat vegetables.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_min_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Disagree&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_max_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Agree&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_values</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">}</span><span class="w"></span>
-<span class="w">        </span><span class="p">]</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;likert&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat vegetables.&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_min_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Disagree&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_max_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Agree&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_values</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">}</span>
+<span class="w">        </span><span class="p">]</span>
 <span class="w">      </span><span class="p">},</span><span class="w"> </span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;likert&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat fruit.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_min_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Disagree&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_max_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Agree&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_values</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">}</span><span class="w"></span>
-<span class="w">        </span><span class="p">]</span><span class="w"></span>
-<span class="w">      </span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;likert&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat meat.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_min_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Disagree&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_max_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Agree&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">likert_scale_values</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">}</span><span class="w"></span>
-<span class="w">        </span><span class="p">]</span><span class="w"></span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;likert&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat fruit.&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_min_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Disagree&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_max_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Agree&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_values</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">}</span>
+<span class="w">        </span><span class="p">]</span>
+<span class="w">      </span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;likert&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat meat.&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_min_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Disagree&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_max_label</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Strongly Agree&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">likert_scale_values</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">2</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">value</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">}</span>
+<span class="w">        </span><span class="p">]</span>
 <span class="w">      </span><span class="p">},</span><span class="w">  </span>
 
-<span class="w">    </span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;likert-table&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39; &#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">statements</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat vegetables&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;VeggiesTable&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat fruit&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;FruitTable&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">          </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat meat&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;MeatTable&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Strongly Disagree&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Disagree&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Neutral&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Agree&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Strongly Agree&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">    </span><span class="p">],</span>
+<span class="w">    </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;likert-table&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39; &#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">statements</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat vegetables&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;VeggiesTable&#39;</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat fruit&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;FruitTable&#39;</span><span class="p">},</span>
+<span class="w">          </span><span class="p">{</span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;I like to eat meat&#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;MeatTable&#39;</span><span class="p">},</span>
+<span class="w">        </span><span class="p">],</span>
+<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Strongly Disagree&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Disagree&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Neutral&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Agree&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;Strongly Agree&#39;</span><span class="p">],</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2819,20 +2824,20 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="4:2"><input checked="checked" id="__tabbed_4_1" name="__tabbed_4" type="radio" /><input id="__tabbed_4_2" name="__tabbed_4" type="radio" /><div class="tabbed-labels"><label for="__tabbed_4_1">Code</label><label for="__tabbed_4_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-choice&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;During the experiment, are allowed to write things down on paper to help you?&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Yes&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;No&quot;</span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;No&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-choice&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;During the experiment, are allowed to write things down on paper to help you?&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Yes&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;No&quot;</span><span class="p">],</span>
+<span class="w">        </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;No&quot;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">required</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
 <span class="w">      </span><span class="p">},</span><span class="w"> </span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="w">    </span><span class="p">]</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2850,52 +2855,52 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="5:2"><input checked="checked" id="__tabbed_5_1" name="__tabbed_5" type="radio" /><input id="__tabbed_5_2" name="__tabbed_5" type="radio" /><div class="tabbed-labels"><label for="__tabbed_5_1">Code</label><label for="__tabbed_5_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">question_info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;fruit&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;apples&#39;</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">question_info</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">{</span>
+<span class="w">    </span><span class="s1">&#39;fruit&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;apples&#39;</span><span class="p">,</span>
 <span class="w">    </span><span class="s1">&#39;Q1_prompt&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Do you like apples?&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="s1">&#39;Q1_type&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;regular&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;fruit&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;bananas&#39;</span><span class="p">,</span><span class="w"></span>
+<span class="w">    </span><span class="s1">&#39;Q1_type&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;regular&#39;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="p">{</span>
+<span class="w">    </span><span class="s1">&#39;fruit&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;bananas&#39;</span><span class="p">,</span>
 <span class="w">    </span><span class="s1">&#39;Q1_prompt&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Do you NOT like bananas?&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="s1">&#39;Q1_type&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;reverse&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="p">];</span><span class="w"></span>
-
-<span class="kd">const</span><span class="w"> </span><span class="nx">survey</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-choice&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;Q1_prompt&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Yes&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;No&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Q1&#39;</span><span class="w"></span>
-<span class="w">      </span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;text&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">          </span><span class="k">return</span><span class="w"> </span><span class="sb">`What&#39;s your favorite thing about </span><span class="si">${</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;fruit&#39;</span><span class="p">)</span><span class="si">}</span><span class="sb">?`</span><span class="p">;</span><span class="w"></span>
-<span class="w">        </span><span class="p">},</span><span class="w"></span>
-<span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Q2&#39;</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="c1">// Add data at the whole-trial level here</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;Q1_prompt&#39;</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;Q1_prompt&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;Q1_type&#39;</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;Q1_type&#39;</span><span class="p">),</span><span class="w"></span>
+<span class="w">    </span><span class="s1">&#39;Q1_type&#39;</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;reverse&#39;</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="p">];</span>
+
+<span class="kd">const</span><span class="w"> </span><span class="nx">survey</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychSurvey</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">pages</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;multi-choice&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;Q1_prompt&#39;</span><span class="p">),</span>
+<span class="w">        </span><span class="nx">options</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Yes&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;No&#39;</span><span class="p">],</span>
+<span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Q1&#39;</span>
+<span class="w">      </span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;text&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">          </span><span class="k">return</span><span class="w"> </span><span class="sb">`What&#39;s your favorite thing about </span><span class="si">${</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;fruit&#39;</span><span class="p">)</span><span class="si">}</span><span class="sb">?`</span><span class="p">;</span>
+<span class="w">        </span><span class="p">},</span>
+<span class="w">        </span><span class="nx">name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Q2&#39;</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">]</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="c1">// Add data at the whole-trial level here</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="s1">&#39;Q1_prompt&#39;</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;Q1_prompt&#39;</span><span class="p">),</span>
+<span class="w">    </span><span class="s1">&#39;Q1_type&#39;</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;Q1_type&#39;</span><span class="p">),</span>
 <span class="w">    </span><span class="s1">&#39;fruit&#39;</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;fruit&#39;</span><span class="p">)</span><span class="w">                                                        </span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
+<span class="w">  </span><span class="p">},</span>
 <span class="w">  </span><span class="nx">button_label_finish</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Continue&#39;</span><span class="w">                </span>
-<span class="p">};</span><span class="w"></span>
+<span class="p">};</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">survey_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">survey</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">question_info</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">survey_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">survey</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">question_info</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2908,16 +2913,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-survey-demo5.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../sketchpad/" class="md-footer__link md-footer__link--prev" aria-label="Previous: sketchpad" rel="prev">
@@ -2976,7 +2990,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2985,7 +2999,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2998,11 +3012,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/video-button-response/index.html b/7.3/plugins/video-button-response/index.html
old mode 100755
new mode 100644
index fa27c155de..137fc5cbc1
--- a/7.3/plugins/video-button-response/index.html
+++ b/7.3/plugins/video-button-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/video-button-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/video-button-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="video-button-response">video-button-response<a class="headerlink" href="#video-button-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-video-button-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-video-button-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin plays a video and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the video has finished playing. The button itself can be customized using HTML formatting.</p>
 <p>Video files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on <a href="../../overview/running-experiments/">Running Experiments</a> for more information.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2135,15 +2140,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 This may change in a future version as we improve the simulation modes.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-video-button-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-video-button-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-video-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-video-button-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-video-button-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">videoButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-video-button-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">videoButtonResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-video-button-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2151,15 +2156,15 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoButtonResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;video/fish.mp4&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;0-5&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;6-10&#39;</span><span class="p">,</span><span class="s1">&#39;11-15&#39;</span><span class="p">,</span><span class="s1">&#39;16-20&#39;</span><span class="p">,</span><span class="s1">&#39;21-25&#39;</span><span class="p">,</span><span class="s1">&#39;25+&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;How many different fish are shown in the video?&lt;/p&gt;&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">response_allowed_while_playing</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoButtonResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="s1">&#39;video/fish.mp4&#39;</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;0-5&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;6-10&#39;</span><span class="p">,</span><span class="s1">&#39;11-15&#39;</span><span class="p">,</span><span class="s1">&#39;16-20&#39;</span><span class="p">,</span><span class="s1">&#39;21-25&#39;</span><span class="p">,</span><span class="s1">&#39;25+&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;&lt;p&gt;How many different fish are shown in the video?&lt;/p&gt;&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">response_allowed_while_playing</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="p">};</span>
 </code></pre></div>
 <p><em><a href="https://www.pond5.com/stock-footage/item/721819-school-yellowtail-snappers">Stock Footage</a> provided by rjt98, from <a href="https://www.pond5.com/">Pond5</a></em></p>
 </div>
@@ -2173,16 +2178,25 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-video-button-response-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../survey-text/" class="md-footer__link md-footer__link--prev" aria-label="Previous: survey-text" rel="prev">
@@ -2241,7 +2255,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2250,7 +2264,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2263,11 +2277,13 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/video-keyboard-response/index.html b/7.3/plugins/video-keyboard-response/index.html
old mode 100755
new mode 100644
index ee98019046..d0143280c3
--- a/7.3/plugins/video-keyboard-response/index.html
+++ b/7.3/plugins/video-keyboard-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/video-keyboard-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/video-keyboard-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="video-keyboard-response">video-keyboard-response<a class="headerlink" href="#video-keyboard-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-video-keyboard-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-video-keyboard-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin plays a video file and records a keyboard response. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the video has finished playing.</p>
 <p>Video files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on <a href="../../overview/running-experiments/">Running Experiments</a> for more information.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2117,15 +2122,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 This may change in a future version as we improve the simulation modes.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-video-keyboard-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-video-keyboard-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-video-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-video-keyboard-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-video-keyboard-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">videoKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-video-keyboard-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">videoKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-video-keyboard-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2133,14 +2138,14 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;video/fish.mp4&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_ends_after_video</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="s1">&#39;video/fish.mp4&#39;</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_ends_after_video</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
 </code></pre></div>
 <p><em><a href="https://www.pond5.com/stock-footage/item/721819-school-yellowtail-snappers">Stock Footage</a> provided by rjt98, from <a href="https://www.pond5.com/">Pond5</a></em></p>
 </div>
@@ -2154,16 +2159,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-video-keyboard-response-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../video-button-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: video-button-response" rel="prev">
@@ -2222,7 +2236,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2231,7 +2245,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2244,11 +2258,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/video-slider-response/index.html b/7.3/plugins/video-slider-response/index.html
old mode 100755
new mode 100644
index c0acc93e8e..e6002cb5b3
--- a/7.3/plugins/video-slider-response/index.html
+++ b/7.3/plugins/video-slider-response/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/video-slider-response/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/video-slider-response.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="video-slider-response">video-slider-response<a class="headerlink" href="#video-slider-response" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-video-slider-response/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-video-slider-response/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin plays a video and allows the participant to respond by dragging a slider. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the video has finished playing.</p>
 <p>Video files can be automatically preloaded by jsPsych using the <a href="../preload/"><code>preload</code> plugin</a>. However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to <a href="../../overview/media-preloading/#manual-preloading">manually preload</a> the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on <a href="../../overview/running-experiments/">Running Experiments</a> for more information.</p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2169,15 +2174,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 This may change in a future version as we improve the simulation modes.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-video-slider-response@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-video-slider-response@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-video-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-video-slider-response.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-video-slider-response
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">videoSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-video-slider-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">videoSliderResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-video-slider-response&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2185,14 +2190,14 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoSliderResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="s1">&#39;video/fish.mp4&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Hated it&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Loved it&quot;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Please rate your enjoyment of the video clip.&lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoSliderResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="s1">&#39;video/fish.mp4&#39;</span>
+<span class="w">  </span><span class="p">],</span>
+<span class="w">  </span><span class="nx">labels</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;Hated it&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;Loved it&quot;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Please rate your enjoyment of the video clip.&lt;/p&gt;&#39;</span>
+<span class="p">};</span>
 </code></pre></div>
 <p><em><a href="https://www.pond5.com/stock-footage/item/721819-school-yellowtail-snappers">Stock Footage</a> provided by rjt98, from <a href="https://www.pond5.com/">Pond5</a></em></p>
 </div>
@@ -2206,16 +2211,25 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-video-slider-response-demo1.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../video-keyboard-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: video-keyboard-response" rel="prev">
@@ -2274,7 +2288,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2283,7 +2297,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2296,11 +2310,13 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/virtual-chinrest/index.html b/7.3/plugins/virtual-chinrest/index.html
old mode 100755
new mode 100644
index 68784546c1..5e0393198e
--- a/7.3/plugins/virtual-chinrest/index.html
+++ b/7.3/plugins/virtual-chinrest/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/virtual-chinrest/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/virtual-chinrest.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="virtual-chinrest">virtual-chinrest<a class="headerlink" href="#virtual-chinrest" title="Permanent link">&para;</a></h1>
-<p>Current version: 2.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-virtual-chinrest/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 2.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-virtual-chinrest/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin provides a "virtual chinrest" that can measure the distance between the participant and the screen. It can also standardize the jsPsych page content to a known physical dimension (e.g., ensuring that a 200px wide stimulus is 2.2cm wide on the participant's monitor). This is based on the work of <a href="https://doi.org/10.1038/s41598-019-57204-1">Li, Joo, Yeatman, and Reinecke (2020)</a>, and the plugin code is a modified version of <a href="https://github.com/QishengLi/virtual_chinrest">their implementation</a>. We recommend citing their work in any paper that makes use of this plugin.</p>
 <div class="admonition note">
 <p class="admonition-title">Citation</p>
@@ -2167,15 +2172,15 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-virtual-chinrest.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-virtual-chinrest.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-virtual-chinrest
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">virtualChinrest</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-virtual-chinrest&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">virtualChinrest</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-virtual-chinrest&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2183,11 +2188,11 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVirtualChinrest</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">blindspot_reps</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">resize_units</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;none&quot;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVirtualChinrest</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">blindspot_reps</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">resize_units</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;none&quot;</span>
+<span class="p">};</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2202,21 +2207,21 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVirtualChinrest</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">blindspot_reps</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">resize_units</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;cm&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">pixels_per_unit</span><span class="o">:</span><span class="w"> </span><span class="mf">50</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">resized_stimulus</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVirtualChinrest</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">blindspot_reps</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">resize_units</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;cm&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">pixels_per_unit</span><span class="o">:</span><span class="w"> </span><span class="mf">50</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">resized_stimulus</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">    &lt;p&gt;If the measurements were done correctly, the square below should be 10 cm x 10 cm.&lt;/p&gt;</span>
 <span class="sb">    &lt;div style=&quot;background-color: black; width: 500px; height: 500px; margin: 20px auto;&quot;&gt;&lt;/div&gt;</span>
-<span class="sb">  `</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">  `</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2231,21 +2236,21 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <div class="tabbed-set tabbed-alternate" data-tabs="3:2"><input checked="checked" id="__tabbed_3_1" name="__tabbed_3" type="radio" /><input id="__tabbed_3_2" name="__tabbed_3" type="radio" /><div class="tabbed-labels"><label for="__tabbed_3_1">Code</label><label for="__tabbed_3_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVirtualChinrest</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">blindspot_reps</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">resize_units</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;deg&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">pixels_per_unit</span><span class="o">:</span><span class="w"> </span><span class="mf">50</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">resized_stimulus</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVirtualChinrest</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">blindspot_reps</span><span class="o">:</span><span class="w"> </span><span class="mf">3</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">resize_units</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;deg&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">pixels_per_unit</span><span class="o">:</span><span class="w"> </span><span class="mf">50</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">resized_stimulus</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">    &lt;p&gt;If the measurements were done correctly, the square below should take up about 10 degrees of visual angle.&lt;/p&gt;</span>
 <span class="sb">    &lt;div style=&quot;background-color: black; width: 500px; height: 500px; margin: 20px auto;&quot;&gt;&lt;/div&gt;</span>
-<span class="sb">  `</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">  `</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2256,16 +2261,25 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-virtual-chinrest-demo3.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../video-slider-response/" class="md-footer__link md-footer__link--prev" aria-label="Previous: video-slider-response" rel="prev">
@@ -2324,7 +2338,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2333,7 +2347,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2346,11 +2360,13 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/visual-search-circle/index.html b/7.3/plugins/visual-search-circle/index.html
old mode 100755
new mode 100644
index b11e55d629..127986ab7c
--- a/7.3/plugins/visual-search-circle/index.html
+++ b/7.3/plugins/visual-search-circle/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/visual-search-circle/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1957,18 +1960,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/visual-search-circle.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="visual-search-circle">visual-search-circle<a class="headerlink" href="#visual-search-circle" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.1.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-visual-search-circle/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.1.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-visual-search-circle/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin presents a customizable visual-search task modelled after <a href="http://dx.doi.org/10.3758/BF03206946">Wang, Cavanagh, &amp; Green (1994)</a>. The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. Here is an example using normal and backward Ns:</p>
 <p><img alt="Sample Visual Search Stimulus" src="../../img/visual_search_example.jpg" /></p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
@@ -2114,15 +2119,15 @@ <h2 id="data-generated">Data Generated<a class="headerlink" href="#data-generate
 </table>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-visual-search-circle.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-visual-search-circle.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-visual-search-circle
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">visualSearchCircle</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-visual-search-circle&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">visualSearchCircle</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-visual-search-circle&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h2>
 <details class="example" open="open">
@@ -2130,21 +2135,21 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="1:2"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Code</label><label for="__tabbed_1_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;Press J if there is a backwards N.&lt;/p&gt;</span>
-<span class="sb">    &lt;p&gt;Press F if all the Ns are in the normal orientation.&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVisualSearchCircle</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/backwardN.gif&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">foil</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/normalN.gif&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">fixation_image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/fixation.gif&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target_present</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">set_size</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">    &lt;p&gt;Press F if all the Ns are in the normal orientation.&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVisualSearchCircle</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/backwardN.gif&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">foil</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/normalN.gif&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">fixation_image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/fixation.gif&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target_present</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">set_size</span><span class="o">:</span><span class="w"> </span><span class="mf">4</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2161,21 +2166,21 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <div class="tabbed-set tabbed-alternate" data-tabs="2:2"><input checked="checked" id="__tabbed_2_1" name="__tabbed_2" type="radio" /><input id="__tabbed_2_2" name="__tabbed_2" type="radio" /><div class="tabbed-labels"><label for="__tabbed_2_1">Code</label><label for="__tabbed_2_2">Demo</label></div>
 <div class="tabbed-content">
 <div class="tabbed-block">
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlButtonResponse</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`&lt;p&gt;Press E if there is an elephant in the group.&lt;/p&gt;</span>
-<span class="sb">    &lt;p&gt;Press N if there is no elephant in the group.&lt;/p&gt;`</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVisualSearchCircle</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/elephant.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/lion.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/monkey.png&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">fixation_image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/fixation.gif&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target_present_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;e&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target_absent_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;n&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">target_present</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="sb">    &lt;p&gt;Press N if there is no elephant in the group.&lt;/p&gt;`</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;Continue&#39;</span><span class="p">]</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVisualSearchCircle</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimuli</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/elephant.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/lion.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/monkey.png&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">fixation_image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/fixation.gif&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target_present_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;e&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target_absent_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;n&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">target_present</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 </div>
 <div class="tabbed-block">
@@ -2188,16 +2193,25 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
 <p><a target="_blank" rel="noopener noreferrer" href="../../demos/jspsych-visual-search-circle-demo2.html">Open demo in new tab</a></p>
 </details>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../virtual-chinrest/" class="md-footer__link md-footer__link--prev" aria-label="Previous: virtual-chinrest" rel="prev">
@@ -2256,7 +2270,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2265,7 +2279,7 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2278,11 +2292,13 @@ <h2 id="examples">Examples<a class="headerlink" href="#examples" title="Permanen
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/webgazer-calibrate/index.html b/7.3/plugins/webgazer-calibrate/index.html
old mode 100755
new mode 100644
index 19c4669d0b..3f09abb995
--- a/7.3/plugins/webgazer-calibrate/index.html
+++ b/7.3/plugins/webgazer-calibrate/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/webgazer-calibrate/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/webgazer-calibrate.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="webgazer-calibrate">webgazer-calibrate<a class="headerlink" href="#webgazer-calibrate" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-webgazer-calibrate/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-webgazer-calibrate/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin can be used to calibrate the <a href="../../extensions/webgazer/">WebGazer extension</a>. For a narrative description of eye tracking with jsPsych, see the <a href="../../overview/eye-tracking/">eye tracking overview</a>. </p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2063,29 +2068,38 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-webgazer-calibrate.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-webgazer-calibrate.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-webgazer-calibrate
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">webgazerCalibrate</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-webgazer-calibrate&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">webgazerCalibrate</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-webgazer-calibrate&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h2>
 <p>Because the eye tracking plugins need to be used in conjunction with each other, please see the <a href="../../overview/eye-tracking/#example">example on the eye tracking overview page</a> for an integrated example. </p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../visual-search-circle/" class="md-footer__link md-footer__link--prev" aria-label="Previous: visual-search-circle" rel="prev">
@@ -2144,7 +2158,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2153,7 +2167,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2166,11 +2180,13 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/webgazer-init-camera/index.html b/7.3/plugins/webgazer-init-camera/index.html
old mode 100755
new mode 100644
index 6421b21668..d0fdc43ff1
--- a/7.3/plugins/webgazer-init-camera/index.html
+++ b/7.3/plugins/webgazer-init-camera/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/webgazer-init-camera/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/webgazer-init-camera.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="webgazer-init-camera">webgazer-init-camera<a class="headerlink" href="#webgazer-init-camera" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-webgazer-init-camera/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-webgazer-init-camera/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin initializes the camera and helps the participant center their face in the camera view for using the the <a href="../../extensions/webgazer/">WebGazer extension</a>. For a narrative description of eye tracking with jsPsych, see the <a href="../../overview/eye-tracking/">eye tracking overview</a>. </p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2032,29 +2037,38 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-webgazer-init-camera.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-webgazer-init-camera.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-webgazer-init-camera
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">webgazerInitCamera</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-webgazer-init-camera&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">webgazerInitCamera</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-webgazer-init-camera&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h2>
 <p>Because the eye tracking plugins need to be used in conjunction with each other, please see the <a href="../../overview/eye-tracking/#example">example on the eye tracking overview page</a> for an integrated example. </p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../webgazer-calibrate/" class="md-footer__link md-footer__link--prev" aria-label="Previous: webgazer-calibrate" rel="prev">
@@ -2113,7 +2127,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2122,7 +2136,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2135,11 +2149,13 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/plugins/webgazer-validate/index.html b/7.3/plugins/webgazer-validate/index.html
old mode 100755
new mode 100644
index 23973ab6ae..a8909242b6
--- a/7.3/plugins/webgazer-validate/index.html
+++ b/7.3/plugins/webgazer-validate/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/plugins/webgazer-validate/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1971,18 +1974,20 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/plugins/webgazer-validate.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="webgazer-validate">webgazer-validate<a class="headerlink" href="#webgazer-validate" title="Permanent link">&para;</a></h1>
-<p>Current version: 1.0.2. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-webgazer-validate/CHANGELOG.md">See version history</a>.</p>
+<p>Current version: 1.0.3. <a href="https://github.com/jspsych/jsPsych/blob/main/packages/plugin-webgazer-validate/CHANGELOG.md">See version history</a>.</p>
 <p>This plugin can be used to measure the accuracy and precision of gaze predictions made by the <a href="../../extensions/webgazer/">WebGazer extension</a>. For a narrative description of eye tracking with jsPsych, see the <a href="../../overview/eye-tracking/">eye tracking overview</a>. </p>
 <h2 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h2>
 <p>In addition to the <a href="../../overview/plugins/#parameters-available-in-all-plugins">parameters available in all plugins</a>, this plugin accepts the following parameters. Parameters with a default value of <em>undefined</em> must be specified. Other parameters can be left unspecified if the default value is acceptable.</p>
@@ -2088,29 +2093,38 @@ <h2 id="simulation-mode">Simulation Mode<a class="headerlink" href="#simulation-
 <p>This plugin does not yet support <a href="../../overview/simulation/">simulation mode</a>.</p>
 <h2 id="install">Install<a class="headerlink" href="#install" title="Permanent link">&para;</a></h2>
 <p>Using the CDN-hosted JavaScript file:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.2&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.3&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using the JavaScript file downloaded from a GitHub release dist archive:</p>
-<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-webgazer-validate.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="o">&lt;</span><span class="nx">script</span><span class="w"> </span><span class="nx">src</span><span class="o">=</span><span class="s2">&quot;jspsych/plugin-webgazer-validate.js&quot;</span><span class="o">&gt;&lt;</span><span class="err">/script&gt;</span>
 </code></pre></div>
 <p>Using NPM:</p>
 <p><div class="highlight"><pre><span></span><code>npm install @jspsych/plugin-webgazer-validate
 </code></pre></div>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">webgazerValidate</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-webgazer-validate&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="nx">webgazerValidate</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-webgazer-validate&#39;</span><span class="p">;</span>
 </code></pre></div></p>
 <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h2>
 <p>Because the eye tracking plugins need to be used in conjunction with each other, please see the <a href="../../overview/eye-tracking/#example">example on the eye tracking overview page</a> for an integrated example. </p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../webgazer-init-camera/" class="md-footer__link md-footer__link--prev" aria-label="Previous: webgazer-init-camera" rel="prev">
@@ -2169,7 +2183,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2178,7 +2192,7 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2191,11 +2205,13 @@ <h2 id="example">Example<a class="headerlink" href="#example" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/reference/jspsych-data/index.html b/7.3/reference/jspsych-data/index.html
old mode 100755
new mode 100644
index 51ac7e346b..45a49b42c6
--- a/7.3/reference/jspsych-data/index.html
+++ b/7.3/reference/jspsych-data/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/reference/jspsych-data/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -3175,21 +3178,23 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/reference/jspsych-data.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="jspsychdata">jsPsych.data<a class="headerlink" href="#jspsychdata" title="Permanent link">&para;</a></h1>
 <p>The jsPsych.data module contains functions for interacting with the data generated by jsPsych plugins.</p>
 <hr />
 <h2 id="jspsychdataaddproperties">jsPsych.data.addProperties<a class="headerlink" href="#jspsychdataaddproperties" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">(</span><span class="nx">properties</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">(</span><span class="nx">properties</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h3>
 <table>
@@ -3214,11 +3219,11 @@ <h3 id="description">Description<a class="headerlink" href="#description" title=
 <p>This method appends a set of properties to every trial in the data object, including trials that have already occurred and trials that have yet to occur. You can use this to record things like the subject ID or condition assignment.</p>
 <h3 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h3>
 <h4 id="assigning-a-subject-id-and-condition-code">Assigning a subject ID and condition code<a class="headerlink" href="#assigning-a-subject-id-and-condition-code" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">({</span><span class="nx">subject</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;control&#39;</span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">({</span><span class="nx">subject</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;control&#39;</span><span class="p">});</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdatadisplaydata">jsPsych.data.displayData<a class="headerlink" href="#jspsychdatadisplaydata" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">(</span><span class="nx">format</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">(</span><span class="nx">format</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_1">Parameters<a class="headerlink" href="#parameters_1" title="Permanent link">&para;</a></h3>
 <table>
@@ -3243,11 +3248,11 @@ <h3 id="description_1">Description<a class="headerlink" href="#description_1" ti
 <p>Outputs all of the data collected in the experiment to the screen in either JSON or CSV format. This is a useful method for quick debugging when developing an experiment.</p>
 <h3 id="examples_1">Examples<a class="headerlink" href="#examples_1" title="Permanent link">&para;</a></h3>
 <h4 id="using-the-on_finish-callback-function-to-show-data-at-the-end-of-the-experiment">Using the on_finish callback function to show data at the end of the experiment<a class="headerlink" href="#using-the-on_finish-callback-function-to-show-data-at-the-end-of-the-experiment" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">(</span><span class="s1">&#39;csv&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">(</span><span class="s1">&#39;csv&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">})</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdataget">jsPsych.data.get<a class="headerlink" href="#jspsychdataget" title="Permanent link">&para;</a></h2>
@@ -3262,15 +3267,15 @@ <h3 id="description_2">Description<a class="headerlink" href="#description_2" ti
 several methods that can be used to further filter, aggregate, and view the data. These methods are described under the DataCollection section
 on this page.</p>
 <h3 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="c1">// select all trials</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">all_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// select all trials</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">all_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">();</span>
 
-<span class="c1">// get csv representation of data and log to console</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">all_data</span><span class="p">.</span><span class="nx">csv</span><span class="p">());</span><span class="w"></span>
+<span class="c1">// get csv representation of data and log to console</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">all_data</span><span class="p">.</span><span class="nx">csv</span><span class="p">());</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdatagetdatabytimelinenode">jsPsych.data.getDataByTimelineNode<a class="headerlink" href="#jspsychdatagetdatabytimelinenode" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getDataByTimelineNode</span><span class="p">(</span><span class="nx">node_id</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getDataByTimelineNode</span><span class="p">(</span><span class="nx">node_id</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_3">Parameters<a class="headerlink" href="#parameters_3" title="Permanent link">&para;</a></h3>
 <table>
@@ -3294,12 +3299,12 @@ <h3 id="return-value_3">Return value<a class="headerlink" href="#return-value_3"
 <h3 id="description_3">Description<a class="headerlink" href="#description_3" title="Permanent link">&para;</a></h3>
 <p>Get all the data generated by a specified Timeline.</p>
 <h3 id="example_1">Example<a class="headerlink" href="#example_1" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">current_node_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTimelineNodeID</span><span class="p">();</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">data_from_current_node</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getDataByTimelineNode</span><span class="p">(</span><span class="nx">current_node_id</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">current_node_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTimelineNodeID</span><span class="p">();</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">data_from_current_node</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getDataByTimelineNode</span><span class="p">(</span><span class="nx">current_node_id</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdatagetinteractiondata">jsPsych.data.getInteractionData<a class="headerlink" href="#jspsychdatagetinteractiondata" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getInteractionData</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getInteractionData</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_4">Parameters<a class="headerlink" href="#parameters_4" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -3307,42 +3312,42 @@ <h3 id="return-value_4">Return value<a class="headerlink" href="#return-value_4"
 <p>Returns a DataCollection object with all of the interaction events.</p>
 <h3 id="description_4">Description<a class="headerlink" href="#description_4" title="Permanent link">&para;</a></h3>
 <p>jsPsych automatically records a few different kinds of user interaction events. <code>blur</code> events occur when the user clicks on another window or tab during the experiment, indicating that they are no longer interacting with the experiment. <code>focus</code> events occur when the user clicks on the experiment window after having clicked somewhere else first (i.e., generated a <code>blur</code> event). <code>fullscreenenter</code> and <code>fullscreenexit</code> events are triggered by the browser entering and exiting fullscreen mode. However, <code>fullscreenenter</code> events only occur when the script switches the browser to fullscreen mode, e.g., with the <a href="../../plugins/fullscreen/">fullscreen plugin</a>. Manually entering fullscreen mode does not trigger this event. <code>fullscreenexit</code> events occur whether the user manually exits fullscreen mode or the script exits fullscreen mode. This method returns the DataCollection containing all interaction events. This is useful for tracking whether the participant completed the task without diverting attention to other windows. Events are in the form:</p>
-<div class="highlight"><pre><span></span><code><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;focus&#39;</span><span class="w"> </span><span class="nx">or</span><span class="w"> </span><span class="s1">&#39;blur&#39;</span><span class="w"> </span><span class="nx">or</span><span class="w"> </span><span class="s1">&#39;fullscreenenter&#39;</span><span class="w"> </span><span class="nx">or</span><span class="w"> </span><span class="s1">&#39;fullscreenexit&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">trial</span><span class="o">:</span><span class="w"> </span><span class="mf">10</span><span class="p">,</span><span class="w"> </span><span class="c1">// the trial number when the event happened</span><span class="w"></span>
-<span class="w">    </span><span class="nx">time</span><span class="o">:</span><span class="w"> </span><span class="mf">13042</span><span class="w"> </span><span class="c1">// total time elapsed since the start of the experiment</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;focus&#39;</span><span class="w"> </span><span class="nx">or</span><span class="w"> </span><span class="s1">&#39;blur&#39;</span><span class="w"> </span><span class="nx">or</span><span class="w"> </span><span class="s1">&#39;fullscreenenter&#39;</span><span class="w"> </span><span class="nx">or</span><span class="w"> </span><span class="s1">&#39;fullscreenexit&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">trial</span><span class="o">:</span><span class="w"> </span><span class="mf">10</span><span class="p">,</span><span class="w"> </span><span class="c1">// the trial number when the event happened</span>
+<span class="w">    </span><span class="nx">time</span><span class="o">:</span><span class="w"> </span><span class="mf">13042</span><span class="w"> </span><span class="c1">// total time elapsed since the start of the experiment</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="example_2">Example<a class="headerlink" href="#example_2" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">interaction_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getInteractionData</span><span class="p">();</span><span class="w"></span>
-<span class="c1">// log data to console in json format</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">interaction_data</span><span class="p">.</span><span class="nx">json</span><span class="p">());</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">interaction_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getInteractionData</span><span class="p">();</span>
+<span class="c1">// log data to console in json format</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">interaction_data</span><span class="p">.</span><span class="nx">json</span><span class="p">());</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdatagetlasttimelinedata">jsPsych.data.getLastTimelineData<a class="headerlink" href="#jspsychdatagetlasttimelinedata" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTimelineData</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTimelineData</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="return-value_5">Return value<a class="headerlink" href="#return-value_5" title="Permanent link">&para;</a></h3>
 <p>Returns a DataCollection.</p>
 <h3 id="description_5">Description<a class="headerlink" href="#description_5" title="Permanent link">&para;</a></h3>
 <p>Gets all of the data generated in the same timeline as the last trial.</p>
 <h3 id="example_3">Example<a class="headerlink" href="#example_3" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">lasttimelinedata</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTimelineData</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">lasttimelinedata</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTimelineData</span><span class="p">();</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdatagetlasttrialdata">jsPsych.data.getLastTrialData<a class="headerlink" href="#jspsychdatagetlasttrialdata" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="return-value_6">Return value<a class="headerlink" href="#return-value_6" title="Permanent link">&para;</a></h3>
 <p>Returns a DataCollection.</p>
 <h3 id="description_6">Description<a class="headerlink" href="#description_6" title="Permanent link">&para;</a></h3>
 <p>Gets the data collection containing all data generated by the last trial.</p>
 <h3 id="example_4">Example<a class="headerlink" href="#example_4" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">lasttrialdata</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">lasttrialdata</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getLastTrialData</span><span class="p">();</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdatageturlvariable">jsPsych.data.getURLVariable<a class="headerlink" href="#jspsychdatageturlvariable" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="nx">var_name</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="nx">var_name</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_5">Parameters<a class="headerlink" href="#parameters_5" title="Permanent link">&para;</a></h3>
 <table>
@@ -3366,27 +3371,27 @@ <h3 id="return-value_7">Return value<a class="headerlink" href="#return-value_7"
 <h3 id="description_7">Description<a class="headerlink" href="#description_7" title="Permanent link">&para;</a></h3>
 <p>For extracting a particular variable passed in through a URL query string.</p>
 <h3 id="example_5">Example<a class="headerlink" href="#example_5" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="c1">// if the URL of the page is: experiment.html?subject=1234&amp;condition=test</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;subject&#39;</span><span class="p">))</span><span class="w"> </span><span class="c1">// logs &quot;1234&quot;</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;condition&#39;</span><span class="p">))</span><span class="w"> </span><span class="c1">// logs &quot;test&quot;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// if the URL of the page is: experiment.html?subject=1234&amp;condition=test</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;subject&#39;</span><span class="p">))</span><span class="w"> </span><span class="c1">// logs &quot;1234&quot;</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">getURLVariable</span><span class="p">(</span><span class="s1">&#39;condition&#39;</span><span class="p">))</span><span class="w"> </span><span class="c1">// logs &quot;test&quot;</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdataurlvariables">jsPsych.data.urlVariables<a class="headerlink" href="#jspsychdataurlvariables" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">urlVariables</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">urlVariables</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="return-value_8">Return value<a class="headerlink" href="#return-value_8" title="Permanent link">&para;</a></h3>
 <p>Returns an object (associative array) of the variables in the URL query string.</p>
 <h3 id="description_8">Description<a class="headerlink" href="#description_8" title="Permanent link">&para;</a></h3>
 <p>For extracting variables passed in through a URL query string.</p>
 <h3 id="example_6">Example<a class="headerlink" href="#example_6" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="c1">// if the URL of the page is: experiment.html?subject=1234&amp;condition=test</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">urlvar</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">urlVariables</span><span class="p">();</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">urlvar</span><span class="p">.</span><span class="nx">subject</span><span class="p">)</span><span class="w"> </span><span class="c1">// logs &quot;1234&quot;</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">urlvar</span><span class="p">.</span><span class="nx">condition</span><span class="p">)</span><span class="w"> </span><span class="c1">// logs &quot;test&quot;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// if the URL of the page is: experiment.html?subject=1234&amp;condition=test</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">urlvar</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">urlVariables</span><span class="p">();</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">urlvar</span><span class="p">.</span><span class="nx">subject</span><span class="p">)</span><span class="w"> </span><span class="c1">// logs &quot;1234&quot;</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">urlvar</span><span class="p">.</span><span class="nx">condition</span><span class="p">)</span><span class="w"> </span><span class="c1">// logs &quot;test&quot;</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychdatawrite">jsPsych.data.write<a class="headerlink" href="#jspsychdatawrite" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">write</span><span class="p">(</span><span class="nx">data_object</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">write</span><span class="p">(</span><span class="nx">data_object</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_6">Parameters<a class="headerlink" href="#parameters_6" title="Permanent link">&para;</a></h3>
 <table>
@@ -3410,195 +3415,204 @@ <h3 id="return-value_9">Return value<a class="headerlink" href="#return-value_9"
 <h3 id="description_9">Description<a class="headerlink" href="#description_9" title="Permanent link">&para;</a></h3>
 <p>This method is used by <code>jsPsych.finishTrial</code> for writing data. You should probably not use it to add data. Instead use <a href="#addProperties">jsPsych.data.addProperties</a>.</p>
 <h3 id="example_7">Example<a class="headerlink" href="#example_7" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="c1">// don&#39;t use this! data should only be written once per trial. use jsPsych.finishTrial to save data.</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// don&#39;t use this! data should only be written once per trial. use jsPsych.finishTrial to save data.</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">487</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">487</span>
+<span class="p">}</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">write</span><span class="p">(</span><span class="nx">trial_data</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">write</span><span class="p">(</span><span class="nx">trial_data</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="datacollection">DataCollection<a class="headerlink" href="#datacollection" title="Permanent link">&para;</a></h2>
 <p>All data is stored in the DataCollection object. Using methods like <code>jsPsych.data.get()</code> and <code>jsPsych.data.getLastTrialData()</code> return DataCollections containing the experiment data. This is a list of all of the methods that are available to call on a DataCollection object.</p>
 <h4 id="addtoall">.addToAll()<a class="headerlink" href="#addtoall" title="Permanent link">&para;</a></h4>
 <p>Adds a set of properties to all items in the DataCollection. Similar to <code>jsPsych.data.addProperties()</code>, except that it can be applied to a subset of the whole DataCollection by filtering down to a smaller DataCollection first.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">addToAll</span><span class="p">({</span><span class="nx">subject_id</span><span class="o">:</span><span class="w"> </span><span class="mf">123</span><span class="p">,</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;control&#39;</span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">addToAll</span><span class="p">({</span><span class="nx">subject_id</span><span class="o">:</span><span class="w"> </span><span class="mf">123</span><span class="p">,</span><span class="w"> </span><span class="nx">condition</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;control&#39;</span><span class="p">});</span>
 </code></pre></div>
 <h4 id="addtolast">.addToLast()<a class="headerlink" href="#addtolast" title="Permanent link">&para;</a></h4>
 <p>Adds a set of properties to the last trial in the DataCollection.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">addToLast</span><span class="p">({</span><span class="nx">success</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">addToLast</span><span class="p">({</span><span class="nx">success</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span>
 </code></pre></div>
 <h4 id="count">.count()<a class="headerlink" href="#count" title="Permanent link">&para;</a></h4>
 <p>Counts the number of trials in the DataCollection.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">count</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">count</span><span class="p">()</span>
 </code></pre></div>
 <h4 id="csv">.csv()<a class="headerlink" href="#csv" title="Permanent link">&para;</a></h4>
 <p>Generates a CSV string representing all of the data in the DataCollection.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">csv</span><span class="p">());</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">csv</span><span class="p">());</span>
 </code></pre></div>
 <h4 id="filter">.filter()<a class="headerlink" href="#filter" title="Permanent link">&para;</a></h4>
 <p>Returns a subset of the DataCollection based on the filter. The filter is an object, and trials are only kept in the returned DataCollection if they contain the key: value pair(s) in the filter object. For example, the code below selects all of the trials with a correct response.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">correct_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">correct_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span>
 </code></pre></div>
 <p>The object can have multiple key: value pairs, and the trials must match all of them in order to be included in the returned collection.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// keep only correct trials from the practice phase</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">correct_practice_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">phase</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;practice&#39;</span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// keep only correct trials from the practice phase</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">correct_practice_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">phase</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;practice&#39;</span><span class="p">});</span>
 </code></pre></div>
 <p>The filter can also be an array of objects. In this case each object in the array acts as an OR filter. As long as the trial has all the key: value pairs of one of the objects in the array, it will appear in the returned collection.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// select trials from block 1 and block 5.</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">([{</span><span class="nx">block</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span><span class="w"> </span><span class="p">{</span><span class="nx">block</span><span class="o">:</span><span class="mf">5</span><span class="p">}]);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// select trials from block 1 and block 5.</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">([{</span><span class="nx">block</span><span class="o">:</span><span class="w"> </span><span class="mf">1</span><span class="p">},</span><span class="w"> </span><span class="p">{</span><span class="nx">block</span><span class="o">:</span><span class="mf">5</span><span class="p">}]);</span>
 </code></pre></div>
 <p>The filter method returns a DataCollection object, so methods can be chained onto a single statement.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// count the number of correct trials in block 1</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">block_1_correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">block</span><span class="o">:</span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="nx">correct</span><span class="o">:</span><span class="kc">true</span><span class="p">}).</span><span class="nx">count</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// count the number of correct trials in block 1</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">block_1_correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">block</span><span class="o">:</span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="nx">correct</span><span class="o">:</span><span class="kc">true</span><span class="p">}).</span><span class="nx">count</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="filtercolumns">.filterColumns()<a class="headerlink" href="#filtercolumns" title="Permanent link">&para;</a></h4>
 <p>Selects the set of columns listed in the array. This is the opposite of the <code>.ignore()</code> method.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// Get only the subject, rt, and condition entries for each trial.</span><span class="w"></span>
-<span class="kd">const</span><span class="w"> </span><span class="nx">subset_of_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filterColumns</span><span class="p">([</span><span class="s1">&#39;subject&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;rt&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;condition&#39;</span><span class="p">])</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// Get only the subject, rt, and condition entries for each trial.</span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">subset_of_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filterColumns</span><span class="p">([</span><span class="s1">&#39;subject&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;rt&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;condition&#39;</span><span class="p">])</span>
 </code></pre></div>
 <h4 id="filtercustom">.filterCustom()<a class="headerlink" href="#filtercustom" title="Permanent link">&para;</a></h4>
 <p>This method is similar to the <code>.filter()</code> method, except that it accepts a function as the filter. The function is passed a single argument, containing the data for a trial. If the function returns <code>true</code> the trial is included in the returned DataCollection.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// count the number of trials with a response time greater than 2000ms.</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">too_long</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filterCustom</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">trial</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&gt;</span><span class="w"> </span><span class="mf">2000</span><span class="p">;</span><span class="w"></span>
-<span class="p">}).</span><span class="nx">count</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// count the number of trials with a response time greater than 2000ms.</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">too_long</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filterCustom</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">){</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">trial</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&gt;</span><span class="w"> </span><span class="mf">2000</span><span class="p">;</span>
+<span class="p">}).</span><span class="nx">count</span><span class="p">()</span>
 </code></pre></div>
 <h4 id="first-last">.first() / .last()<a class="headerlink" href="#first-last" title="Permanent link">&para;</a></h4>
 <p>Returns a DataCollection containing the first/last <em>n</em> trials. If <em>n</em> is greater than the number of trials in the DataCollection, then these functions will return an array of length equal to the number of trials. If there are no trials in the DataCollection, then these functions will return an empty array. If the <em>n</em> argument is omitted, then the functions will use the default value of 1. If <em>n</em> is zero or a negative number, then these functions will throw an error.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">first_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">);</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">last_trial_with_correct_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">}).</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">);</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">last_10_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">10</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">first_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">);</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">last_trial_with_correct_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">}).</span><span class="nx">last</span><span class="p">(</span><span class="mf">1</span><span class="p">);</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">last_10_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">last</span><span class="p">(</span><span class="mf">10</span><span class="p">);</span>
 </code></pre></div>
 <h4 id="ignore">.ignore()<a class="headerlink" href="#ignore" title="Permanent link">&para;</a></h4>
 <p>Returns a DataCollection with all instances of a particular key removed from the dataset.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// log a csv file that does not contain the internal_node_id values for each trial</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">ignore</span><span class="p">(</span><span class="s1">&#39;internal_node_id&#39;</span><span class="p">).</span><span class="nx">csv</span><span class="p">());</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// log a csv file that does not contain the internal_node_id values for each trial</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">ignore</span><span class="p">(</span><span class="s1">&#39;internal_node_id&#39;</span><span class="p">).</span><span class="nx">csv</span><span class="p">());</span>
 </code></pre></div>
 <h4 id="join">.join()<a class="headerlink" href="#join" title="Permanent link">&para;</a></h4>
 <p>Appends one DataCollection onto another and returns the combined collection.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// get a DataCollection with all trials that are either correct or</span><span class="w"></span>
-<span class="c1">// have a response time greater than 200ms.</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">dc1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">dc2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filterCustom</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">){</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">trial</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&gt;</span><span class="w"> </span><span class="mf">200</span><span class="p">});</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">dc1</span><span class="p">.</span><span class="nx">join</span><span class="p">(</span><span class="nx">dc2</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// get a DataCollection with all trials that are either correct or</span>
+<span class="c1">// have a response time greater than 200ms.</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">dc1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">dc2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filterCustom</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">trial</span><span class="p">){</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">trial</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">&gt;</span><span class="w"> </span><span class="mf">200</span><span class="p">});</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">dc1</span><span class="p">.</span><span class="nx">join</span><span class="p">(</span><span class="nx">dc2</span><span class="p">);</span>
 </code></pre></div>
 <h4 id="json">.json()<a class="headerlink" href="#json" title="Permanent link">&para;</a></h4>
 <p>Generates a JSON string representing all of the data in the DataCollection.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">());</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">json</span><span class="p">());</span>
 </code></pre></div>
 <h4 id="localsave">.localSave()<a class="headerlink" href="#localsave" title="Permanent link">&para;</a></h4>
 <p>Saves a CSV or JSON file on the computer running the experiment. If conducting an online experiment, this will download the file onto the subject's computer, and is therefore not a recommended data storage solution for online data collection.</p>
 <p><strong>Warning:</strong> This function may not behave correctly in older browsers. Upgrading to the latest version of any major web browser should solve the problem.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// first argument is the format, second is the filename.</span><span class="w"></span>
-<span class="c1">// the format can be either &#39;csv&#39; or &#39;json&#39;.</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">localSave</span><span class="p">(</span><span class="s1">&#39;csv&#39;</span><span class="p">,</span><span class="s1">&#39;mydata.csv&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// first argument is the format, second is the filename.</span>
+<span class="c1">// the format can be either &#39;csv&#39; or &#39;json&#39;.</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">localSave</span><span class="p">(</span><span class="s1">&#39;csv&#39;</span><span class="p">,</span><span class="s1">&#39;mydata.csv&#39;</span><span class="p">);</span>
 </code></pre></div>
 <h4 id="push">.push()<a class="headerlink" href="#push" title="Permanent link">&para;</a></h4>
 <p>Add a new entry to the DataCollection. This method is mostly used internally, and you shouldn't need to call it under normal circumstances.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">}</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">push</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"> </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">}</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">push</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span>
 </code></pre></div>
 <h4 id="readonly">.readOnly()<a class="headerlink" href="#readonly" title="Permanent link">&para;</a></h4>
 <p>Creates a copy of the DataCollection so that any modification of the values in the DataCollection will not affect the original.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// this line edits the rt property of the first trial</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">rt</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// this line edits the rt property of the first trial</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">rt</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span>
 
-<span class="c1">// readOnly creates a copy that can be modified without affecting the original</span><span class="w"></span>
+<span class="c1">// readOnly creates a copy that can be modified without affecting the original</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">rt</span><span class="w"></span>
-<span class="c1">// outputs 100</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">rt</span>
+<span class="c1">// outputs 100</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">readOnly</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">rt</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">200</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">rt</span><span class="w"></span>
-<span class="c1">// still outputs 100</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">readOnly</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">rt</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">200</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">first</span><span class="p">(</span><span class="mf">1</span><span class="p">).</span><span class="nx">values</span><span class="p">()[</span><span class="mf">0</span><span class="p">].</span><span class="nx">rt</span>
+<span class="c1">// still outputs 100</span>
 </code></pre></div>
 <h4 id="select">.select()<a class="headerlink" href="#select" title="Permanent link">&para;</a></h4>
 <p>Returns a DataColumn object (see documentation below) of a single property from a DataCollection object.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">rt_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="nx">rt_data</span><span class="p">.</span><span class="nx">mean</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">rt_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">);</span>
+<span class="nx">rt_data</span><span class="p">.</span><span class="nx">mean</span><span class="p">()</span>
 </code></pre></div>
 <h4 id="uniquenames">.uniqueNames()<a class="headerlink" href="#uniquenames" title="Permanent link">&para;</a></h4>
 <p>Generates an array of all the unique key names in the set of trials contained in the DataCollection. This is especially useful when setting up a relational database (e.g., MySQL) where the column names need to be specified in advance.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">uniqueNames</span><span class="p">());</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">uniqueNames</span><span class="p">());</span>
 </code></pre></div>
 <h4 id="values">.values()<a class="headerlink" href="#values" title="Permanent link">&para;</a></h4>
 <p>Returns the raw data array associated with the DataCollection. This array is modifiable, so changes to the array and values of objects in the array will change the DataCollection.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">raw_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">values</span><span class="p">();</span><span class="w"></span>
-
-<span class="c1">// was response in first trial correct?</span><span class="w"></span>
-<span class="k">if</span><span class="p">(</span><span class="nx">raw_data</span><span class="p">[</span><span class="mf">0</span><span class="p">].</span><span class="nx">correct</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;correct!&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;incorrect.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">raw_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">values</span><span class="p">();</span>
+
+<span class="c1">// was response in first trial correct?</span>
+<span class="k">if</span><span class="p">(</span><span class="nx">raw_data</span><span class="p">[</span><span class="mf">0</span><span class="p">].</span><span class="nx">correct</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;correct!&#39;</span><span class="p">);</span>
+<span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;incorrect.&#39;</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="datacolumn">DataColumn<a class="headerlink" href="#datacolumn" title="Permanent link">&para;</a></h2>
 <p>DataColumn objects represent all the values of a single property in a DataCollection. They are generated by using the <code>.select()</code> method on a DataCollection. Once a DataColumn is generated, the following methods can be used.</p>
 <h4 id="all">.all()<a class="headerlink" href="#all" title="Permanent link">&para;</a></h4>
 <p>Checks if all values in the DataColumn return <code>true</code> when passed to a function. The function takes a single argument, which represents one value from the DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// check if all the response times in the practice phase were under 1000ms</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">phase</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;practice&#39;</span><span class="p">}).</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;correct&#39;</span><span class="p">).</span><span class="nx">all</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="mf">1000</span><span class="p">;</span><span class="w"> </span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// check if all the response times in the practice phase were under 1000ms</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">phase</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;practice&#39;</span><span class="p">}).</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;correct&#39;</span><span class="p">).</span><span class="nx">all</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="mf">1000</span><span class="p">;</span><span class="w"> </span><span class="p">});</span>
 </code></pre></div>
 <h4 id="count_1">.count()<a class="headerlink" href="#count_1" title="Permanent link">&para;</a></h4>
 <p>Counts the number of values in the DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// count how many response times there are</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">count</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// count how many response times there are</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">count</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="frequencies">.frequencies()<a class="headerlink" href="#frequencies" title="Permanent link">&para;</a></h4>
 <p>Counts the number of occurrences of each unique value in the DataColumn. Returns this value as an object, where each key is a unique value and the value of each key is the number of occurrences of that key.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// get frequencies of correct and incorrect responses</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;correct&#39;</span><span class="p">).</span><span class="nx">frequencies</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// get frequencies of correct and incorrect responses</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;correct&#39;</span><span class="p">).</span><span class="nx">frequencies</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="max-min">.max() / .min()<a class="headerlink" href="#max-min" title="Permanent link">&para;</a></h4>
 <p>Returns the maximum or minimum value in a DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">max</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">min</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">max</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">min</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="mean">.mean()<a class="headerlink" href="#mean" title="Permanent link">&para;</a></h4>
 <p>Returns the average of all the values in a DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">mean</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">mean</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="median">.median()<a class="headerlink" href="#median" title="Permanent link">&para;</a></h4>
 <p>Returns the median of all the values in a DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">median</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">median</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="sd">.sd()<a class="headerlink" href="#sd" title="Permanent link">&para;</a></h4>
 <p>Returns the standard deviation of the values in a DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">sd</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">sd</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="subset">.subset()<a class="headerlink" href="#subset" title="Permanent link">&para;</a></h4>
 <p>Filters the DataColumn to include only values that return <code>true</code> when passed through the specified function.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// below results will be less than 200.</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">subset</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">){</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="mf">200</span><span class="p">;</span><span class="w"> </span><span class="p">}).</span><span class="nx">max</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// below results will be less than 200.</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">subset</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">x</span><span class="p">){</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">x</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="mf">200</span><span class="p">;</span><span class="w"> </span><span class="p">}).</span><span class="nx">max</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="sum">.sum()<a class="headerlink" href="#sum" title="Permanent link">&para;</a></h4>
 <p>Returns the sum of the values in a DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">sum</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">sum</span><span class="p">();</span>
 </code></pre></div>
 <h4 id="values_1">.values<a class="headerlink" href="#values_1" title="Permanent link">&para;</a></h4>
 <p>The raw array of values in the DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="c1">// note that this is not a function call.</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">values</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// note that this is not a function call.</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">values</span><span class="p">;</span>
 </code></pre></div>
 <h4 id="variance">.variance()<a class="headerlink" href="#variance" title="Permanent link">&para;</a></h4>
 <p>Returns the variance of the values in a DataColumn.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">variance</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">variance</span><span class="p">();</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../jspsych/" class="md-footer__link md-footer__link--prev" aria-label="Previous: jsPsych" rel="prev">
@@ -3657,7 +3671,7 @@ <h4 id="variance">.variance()<a class="headerlink" href="#variance" title="Perma
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -3666,7 +3680,7 @@ <h4 id="variance">.variance()<a class="headerlink" href="#variance" title="Perma
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -3679,11 +3693,13 @@ <h4 id="variance">.variance()<a class="headerlink" href="#variance" title="Perma
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/reference/jspsych-pluginAPI/index.html b/7.3/reference/jspsych-pluginAPI/index.html
old mode 100755
new mode 100644
index 13f8387b3d..88e6450266
--- a/7.3/reference/jspsych-pluginAPI/index.html
+++ b/7.3/reference/jspsych-pluginAPI/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/reference/jspsych-pluginAPI/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -3885,21 +3888,23 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/reference/jspsych-pluginAPI.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="jspsychpluginapi">jsPsych.pluginAPI<a class="headerlink" href="#jspsychpluginapi" title="Permanent link">&para;</a></h1>
 <p>The pluginAPI module contains functions that are useful when developing plugins. All of the functions are accessible through the <code>pluginAPI</code> object. In this documentation we've divided them up based on different kinds of functionality.</p>
 <h2 id="keyboard-input">Keyboard Input<a class="headerlink" href="#keyboard-input" title="Permanent link">&para;</a></h2>
 <h3 id="cancelallkeyboardresponses">cancelAllKeyboardResponses<a class="headerlink" href="#cancelallkeyboardresponses" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelAllKeyboardResponses</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelAllKeyboardResponses</span><span class="p">()</span>
 </code></pre></div>
 <h4 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h4>
 <p>None.</p>
@@ -3908,11 +3913,11 @@ <h4 id="return-value">Return value<a class="headerlink" href="#return-value" tit
 <h4 id="description">Description<a class="headerlink" href="#description" title="Permanent link">&para;</a></h4>
 <p>Cancels all currently active keyboard listeners created by <code>jsPsych.pluginAPI.getKeyboardResponse</code>.</p>
 <h4 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelAllKeyboardResponses</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelAllKeyboardResponses</span><span class="p">();</span>
 </code></pre></div>
 <hr />
 <h3 id="cancelkeyboardresponse">cancelKeyboardResponse<a class="headerlink" href="#cancelkeyboardresponse" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelKeyboardResponse</span><span class="p">(</span><span class="nx">listener_id</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelKeyboardResponse</span><span class="p">(</span><span class="nx">listener_id</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_1">Parameters<a class="headerlink" href="#parameters_1" title="Permanent link">&para;</a></h4>
 <table>
@@ -3936,21 +3941,21 @@ <h4 id="return-value_1">Return value<a class="headerlink" href="#return-value_1"
 <h4 id="description_1">Description<a class="headerlink" href="#description_1" title="Permanent link">&para;</a></h4>
 <p>Cancels a specific keyboard listener created by <code>jsPsych.pluginAPI.getKeyboardResponse</code>.</p>
 <h4 id="example_1">Example<a class="headerlink" href="#example_1" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="c1">// create a persistent keyboard listener</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">listener_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">({</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// create a persistent keyboard listener</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">listener_id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">({</span>
 <span class="w">    </span><span class="nx">callback_function</span><span class="o">:</span><span class="w"> </span><span class="nx">after_response</span><span class="p">,</span><span class="w"> </span>
 <span class="w">    </span><span class="nx">valid_responses</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="s1">&#39;q&#39;</span><span class="p">],</span><span class="w"> </span>
 <span class="w">    </span><span class="nx">rt_method</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;performance&#39;</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="nx">persist</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">allow_held_key</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<span class="w">    </span><span class="nx">persist</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">allow_held_key</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="p">});</span>
 
-<span class="c1">// cancel keyboard listener</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelKeyboardResponse</span><span class="p">(</span><span class="nx">listener_id</span><span class="p">);</span><span class="w"></span>
+<span class="c1">// cancel keyboard listener</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelKeyboardResponse</span><span class="p">(</span><span class="nx">listener_id</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="comparekeys">compareKeys<a class="headerlink" href="#comparekeys" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">key1</span><span class="p">,</span><span class="w"> </span><span class="nx">key2</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">key1</span><span class="p">,</span><span class="w"> </span><span class="nx">key2</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_2">Parameters<a class="headerlink" href="#parameters_2" title="Permanent link">&para;</a></h4>
 <table>
@@ -3982,47 +3987,47 @@ <h4 id="description_2">Description<a class="headerlink" href="#description_2" ti
 <p>We recommend using this function to compare keys in all plugin and experiment code, rather than using something like <code>if (response == 'j')...</code>. This is because the response key returned by the <code>jsPsych.pluginAPI.getKeyboardResponse</code> function will be converted to lowercase when <code>case_sensitive_responses</code> is <code>false</code>, and it will match the exact key press representation when <code>case_sensitive_responses</code> is <code>true</code>. Using this <code>compareKeys</code> function will ensure that your key comparisons work appropriately based on the experiment's <code>case_sensitive_responses</code> setting, and that you do not need to remember to check key responses against different case versions of the comparison key (e.g. <code>if (response == 'ArrowLeft' || response == 'arrowleft')...</code>). </p>
 <h4 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h4>
 <h5 id="basic-examples">Basic examples<a class="headerlink" href="#basic-examples" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;A&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// returns true when case_sensitive_responses is false in initJsPsych</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;A&#39;</span><span class="p">);</span>
+<span class="c1">// returns true when case_sensitive_responses is false in initJsPsych</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;A&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// returns false when case_sensitive_responses is true in initJsPsych</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;A&#39;</span><span class="p">);</span>
+<span class="c1">// returns false when case_sensitive_responses is true in initJsPsych</span>
 
-<span class="c1">// also works with numeric key codes (but note that numeric keyCode values are now deprecated)</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">,</span><span class="w"> </span><span class="mf">65</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// returns true</span><span class="w"></span>
+<span class="c1">// also works with numeric key codes (but note that numeric keyCode values are now deprecated)</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">,</span><span class="w"> </span><span class="mf">65</span><span class="p">);</span>
+<span class="c1">// returns true</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="s1">&#39;space&#39;</span><span class="p">,</span><span class="w"> </span><span class="mf">31</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// returns false</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="s1">&#39;space&#39;</span><span class="p">,</span><span class="w"> </span><span class="mf">31</span><span class="p">);</span>
+<span class="c1">// returns false</span>
 </code></pre></div>
 <h5 id="comparing-a-key-response-and-key-parameter-value-in-plugins">Comparing a key response and key parameter value in plugins<a class="headerlink" href="#comparing-a-key-response-and-key-parameter-value-in-plugins" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="c1">// this is the callback_function passed to jsPsych.pluginAPI.getKeyboardResponse</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">after_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">info</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="c1">// score the response by comparing the key that was pressed against the trial&#39;s key_answer parameter</span><span class="w"></span>
-<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">trial</span><span class="p">.</span><span class="nx">key_answer</span><span class="p">,</span><span class="w"> </span><span class="nx">info</span><span class="p">.</span><span class="nx">key</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="c1">//...</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// this is the callback_function passed to jsPsych.pluginAPI.getKeyboardResponse</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">after_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">info</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="c1">// score the response by comparing the key that was pressed against the trial&#39;s key_answer parameter</span>
+<span class="w">  </span><span class="kd">var</span><span class="w"> </span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">trial</span><span class="p">.</span><span class="nx">key_answer</span><span class="p">,</span><span class="w"> </span><span class="nx">info</span><span class="p">.</span><span class="nx">key</span><span class="p">);</span>
+<span class="w">  </span><span class="c1">//...</span>
+<span class="p">}</span>
 </code></pre></div>
 <h5 id="scoring-a-key-response-in-experiment-code">Scoring a key response in experiment code<a class="headerlink" href="#scoring-a-key-response-in-experiment-code" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Press f for left. Press j for right.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// score the response by comparing the key that was pressed (data.response) against the </span><span class="w"></span>
-<span class="w">    </span><span class="c1">// correct response for this trial (&#39;f&#39;), and store reponse accuracy in the trial data</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">)){</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;&lt;&lt;&lt;&lt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Press f for left. Press j for right.&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">    </span><span class="c1">// score the response by comparing the key that was pressed (data.response) against the </span>
+<span class="w">    </span><span class="c1">// correct response for this trial (&#39;f&#39;), and store reponse accuracy in the trial data</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">)){</span>
+<span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">true</span><span class="p">;</span>
+<span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
 <span class="w">      </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kc">false</span><span class="p">;</span><span class="w"> </span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h3 id="getkeyboardresponse">getKeyboardResponse<a class="headerlink" href="#getkeyboardresponse" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">(</span><span class="nx">parameters</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">(</span><span class="nx">parameters</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_3">Parameters<a class="headerlink" href="#parameters_3" title="Permanent link">&para;</a></h4>
 <p>The method accepts an object of parameter values (see example below). The valid keys for this object are listed in the table below.</p>
@@ -4081,36 +4086,36 @@ <h4 id="description_3">Description<a class="headerlink" href="#description_3" ti
 <p>This function uses the <code>.key</code> value of the keyboard event, which is <em>case sensitive</em>. When <code>case_sensitive_responses</code> is <code>false</code> in <code>initJsPsych</code> (the default), this function will convert both the <code>valid_responses</code> strings and the response key to lowercase before comparing them, and it will pass the lowercase version of the response key to the <code>callback_function</code>. For example, if <code>valid_responses</code> is <code>['a']</code>, then both 'A' and 'a' will be considered valid key presses, and 'a' will be returned as the response key. When <code>case_sensitive_responses</code> is <code>true</code> in <code>initJsPsych</code>, this function will not convert the case when comparing the <code>valid_responses</code> and response key, and it will not convert the case of the response key that is passed to the <code>callback_function</code>. For example, if <code>valid_responses</code> is <code>['a']</code>, then 'a' will be the only valid key press, and 'A' (i.e. 'a' with CapsLock on or Shift held down) will not be accepted. Also, if <code>valid_responses</code> includes multiple letter case options (e.g. <code>"ALL_KEYS"</code>), then you may need to check the response key against both letter cases when scoring etc., e.g. <code>if (response == 'ArrowLeft' || response =='arrowleft') ...</code>.</p>
 <h4 id="examples_1">Examples<a class="headerlink" href="#examples_1" title="Permanent link">&para;</a></h4>
 <h5 id="get-a-single-response-from-any-key">Get a single response from any key<a class="headerlink" href="#get-a-single-response-from-any-key" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">after_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">info</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;You pressed key &#39;</span><span class="o">+</span><span class="nx">info</span><span class="p">.</span><span class="nx">key</span><span class="o">+</span><span class="s1">&#39; after &#39;</span><span class="o">+</span><span class="nx">info</span><span class="p">.</span><span class="nx">rt</span><span class="o">+</span><span class="s1">&#39;ms&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">callback_function</span><span class="o">:</span><span class="nx">after_response</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">valid_responses</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;ALL_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">rt_method</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;performance&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">persist</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">after_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">info</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;You pressed key &#39;</span><span class="o">+</span><span class="nx">info</span><span class="p">.</span><span class="nx">key</span><span class="o">+</span><span class="s1">&#39; after &#39;</span><span class="o">+</span><span class="nx">info</span><span class="p">.</span><span class="nx">rt</span><span class="o">+</span><span class="s1">&#39;ms&#39;</span><span class="p">);</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">callback_function</span><span class="o">:</span><span class="nx">after_response</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">valid_responses</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;ALL_KEYS&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">rt_method</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;performance&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">persist</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span>
+<span class="p">});</span>
 </code></pre></div>
 <h5 id="get-a-responses-from-a-key-until-the-letter-q-is-pressed">Get a responses from a key until the letter q is pressed<a class="headerlink" href="#get-a-responses-from-a-key-until-the-letter-q-is-pressed" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">after_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">info</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;You pressed key &#39;</span><span class="o">+</span><span class="nx">info</span><span class="p">.</span><span class="nx">key</span><span class="o">+</span><span class="s1">&#39; after &#39;</span><span class="o">+</span><span class="nx">info</span><span class="p">.</span><span class="nx">rt</span><span class="o">+</span><span class="s1">&#39;ms&#39;</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">info</span><span class="p">.</span><span class="nx">key</span><span class="p">,</span><span class="s1">&#39;q&#39;</span><span class="p">)){</span><span class="w"> </span><span class="err">/</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelKeyboardResponse</span><span class="p">(</span><span class="nx">listener</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">listener</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">callback_function</span><span class="o">:</span><span class="nx">after_response</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">valid_responses</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;ALL_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">rt_method</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;performance&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">persist</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">after_response</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">info</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;You pressed key &#39;</span><span class="o">+</span><span class="nx">info</span><span class="p">.</span><span class="nx">key</span><span class="o">+</span><span class="s1">&#39; after &#39;</span><span class="o">+</span><span class="nx">info</span><span class="p">.</span><span class="nx">rt</span><span class="o">+</span><span class="s1">&#39;ms&#39;</span><span class="p">);</span>
+
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">info</span><span class="p">.</span><span class="nx">key</span><span class="p">,</span><span class="s1">&#39;q&#39;</span><span class="p">)){</span><span class="w"> </span><span class="err">/</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">cancelKeyboardResponse</span><span class="p">(</span><span class="nx">listener</span><span class="p">);</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">listener</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getKeyboardResponse</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">callback_function</span><span class="o">:</span><span class="nx">after_response</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">valid_responses</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;ALL_KEYS&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">rt_method</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;performance&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">persist</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">});</span>
 </code></pre></div>
 <h2 id="media">Media<a class="headerlink" href="#media" title="Permanent link">&para;</a></h2>
 <h3 id="getaudiobuffer">getAudioBuffer<a class="headerlink" href="#getaudiobuffer" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAudioBuffer</span><span class="p">(</span><span class="nx">filepath</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAudioBuffer</span><span class="p">(</span><span class="nx">filepath</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_4">Parameters<a class="headerlink" href="#parameters_4" title="Permanent link">&para;</a></h4>
 <table>
@@ -4136,32 +4141,32 @@ <h4 id="description_4">Description<a class="headerlink" href="#description_4" ti
 <p>It is strongly recommended that you preload audio files before calling this method. This method will load the files if they are not preloaded, but this may result in delays during the experiment as audio is downloaded.</p>
 <h4 id="examples_2">Examples<a class="headerlink" href="#examples_2" title="Permanent link">&para;</a></h4>
 <h5 id="html-5-audio">HTML 5 Audio<a class="headerlink" href="#html-5-audio" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAudioBuffer</span><span class="p">(</span><span class="s1">&#39;my-sound.mp3&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">  </span><span class="p">.</span><span class="nx">then</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">audio</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">audio</span><span class="p">.</span><span class="nx">play</span><span class="p">();</span><span class="w"></span>
-<span class="w">  </span><span class="p">})</span><span class="w"></span>
-<span class="w">  </span><span class="p">.</span><span class="k">catch</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">err</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">error</span><span class="p">(</span><span class="s1">&#39;Audio file failed to load&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">  </span><span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAudioBuffer</span><span class="p">(</span><span class="s1">&#39;my-sound.mp3&#39;</span><span class="p">)</span>
+<span class="w">  </span><span class="p">.</span><span class="nx">then</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">audio</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">audio</span><span class="p">.</span><span class="nx">play</span><span class="p">();</span>
+<span class="w">  </span><span class="p">})</span>
+<span class="w">  </span><span class="p">.</span><span class="k">catch</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">err</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">error</span><span class="p">(</span><span class="s1">&#39;Audio file failed to load&#39;</span><span class="p">)</span>
+<span class="w">  </span><span class="p">})</span>
 </code></pre></div>
 <h5 id="webaudio-api">WebAudio API<a class="headerlink" href="#webaudio-api" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">context</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">audioContext</span><span class="p">();</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAudioBuffer</span><span class="p">(</span><span class="s1">&#39;my-sound.mp3&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">  </span><span class="p">.</span><span class="nx">then</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">buffer</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">audio</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">context</span><span class="p">.</span><span class="nx">createBufferSource</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="nx">audio</span><span class="p">.</span><span class="nx">buffer</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">buffer</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="nx">audio</span><span class="p">.</span><span class="nx">connect</span><span class="p">(</span><span class="nx">context</span><span class="p">.</span><span class="nx">destination</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="nx">audio</span><span class="p">.</span><span class="nx">start</span><span class="p">(</span><span class="nx">context</span><span class="p">.</span><span class="nx">currentTime</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">})</span><span class="w"></span>
-<span class="w">  </span><span class="p">.</span><span class="k">catch</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">err</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">error</span><span class="p">(</span><span class="s1">&#39;Audio file failed to load&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">  </span><span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">context</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">audioContext</span><span class="p">();</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAudioBuffer</span><span class="p">(</span><span class="s1">&#39;my-sound.mp3&#39;</span><span class="p">)</span>
+<span class="w">  </span><span class="p">.</span><span class="nx">then</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">buffer</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">audio</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">context</span><span class="p">.</span><span class="nx">createBufferSource</span><span class="p">();</span>
+<span class="w">    </span><span class="nx">audio</span><span class="p">.</span><span class="nx">buffer</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">buffer</span><span class="p">;</span>
+<span class="w">    </span><span class="nx">audio</span><span class="p">.</span><span class="nx">connect</span><span class="p">(</span><span class="nx">context</span><span class="p">.</span><span class="nx">destination</span><span class="p">);</span>
+<span class="w">    </span><span class="nx">audio</span><span class="p">.</span><span class="nx">start</span><span class="p">(</span><span class="nx">context</span><span class="p">.</span><span class="nx">currentTime</span><span class="p">);</span>
+<span class="w">  </span><span class="p">})</span>
+<span class="w">  </span><span class="p">.</span><span class="k">catch</span><span class="p">(</span><span class="kd">function</span><span class="p">(</span><span class="nx">err</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">error</span><span class="p">(</span><span class="s1">&#39;Audio file failed to load&#39;</span><span class="p">)</span>
+<span class="w">  </span><span class="p">})</span>
 </code></pre></div>
 <p>See the <code>audio-keyboard-response</code> plugin for an example in a fuller context.</p>
 <hr />
 <h3 id="getautopreloadlist">getAutoPreloadList<a class="headerlink" href="#getautopreloadlist" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAutoPreloadList</span><span class="p">(</span><span class="nx">timeline</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAutoPreloadList</span><span class="p">(</span><span class="nx">timeline</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_5">Parameters<a class="headerlink" href="#parameters_5" title="Permanent link">&para;</a></h4>
 <table>
@@ -4189,28 +4194,28 @@ <h4 id="description_5">Description<a class="headerlink" href="#description_5" ti
 In these cases, the file should be preloaded manually.
 See <a href="../../overview/media-preloading/">Media Preloading</a> for more information.</p>
 <h4 id="example_2">Example<a class="headerlink" href="#example_2" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">audio_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file.mp3&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">audio_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file.mp3&#39;</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file.png&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">image_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file.png&#39;</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">video_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file.mp4&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">video_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychVideoKeyboardResponse</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;file.mp4&#39;</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="nx">audio_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">image_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">video_trial</span><span class="p">];</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="nx">audio_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">image_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">video_trial</span><span class="p">];</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAutoPreloadList</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getAutoPreloadList</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="getmicrophonerecorder">getMicrophoneRecorder<a class="headerlink" href="#getmicrophonerecorder" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getMicrophoneRecorder</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getMicrophoneRecorder</span><span class="p">()</span>
 </code></pre></div>
 <h4 id="parameters_6">Parameters<a class="headerlink" href="#parameters_6" title="Permanent link">&para;</a></h4>
 <p>None</p>
@@ -4220,11 +4225,11 @@ <h4 id="description_6">Description<a class="headerlink" href="#description_6" ti
 <p>Provides access to the <code>MediaRecorder</code> created by <a href="#initializemicrophonerecorder">initializeMicrophoneRecorder()</a>.
 If no microphone recorder exists, it returns <code>null</code>.</p>
 <h4 id="example_3">Example<a class="headerlink" href="#example_3" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">recorder</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getMicrophoneRecorder</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">recorder</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getMicrophoneRecorder</span><span class="p">();</span>
 </code></pre></div>
 <hr />
 <h3 id="initializemicrophonerecorder">initializeMicrophoneRecorder<a class="headerlink" href="#initializemicrophonerecorder" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">initializeMicrophoneRecorder</span><span class="p">(</span><span class="nx">stream</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">initializeMicrophoneRecorder</span><span class="p">(</span><span class="nx">stream</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_7">Parameters<a class="headerlink" href="#parameters_7" title="Permanent link">&para;</a></h4>
 <table>
@@ -4248,13 +4253,13 @@ <h4 id="return-value_7">Return value<a class="headerlink" href="#return-value_7"
 <h4 id="description_7">Description<a class="headerlink" href="#description_7" title="Permanent link">&para;</a></h4>
 <p>Generates a <code>MediaRecorder</code> object from provided <code>MediaStream</code> and stores this for access via <a href="#getmicrophonerecorder">getMicrophoneRecorder()</a>.</p>
 <h4 id="example_4">Example<a class="headerlink" href="#example_4" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">stream</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="k">await</span><span class="w"> </span><span class="nx">navigator</span><span class="p">.</span><span class="nx">mediaDevices</span><span class="p">.</span><span class="nx">getUserMedia</span><span class="p">({</span><span class="w"> </span><span class="nx">audio</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">deviceId</span><span class="o">:</span><span class="w"> </span><span class="nx">mic_id</span><span class="w"> </span><span class="p">}</span><span class="w"> </span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">stream</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="k">await</span><span class="w"> </span><span class="nx">navigator</span><span class="p">.</span><span class="nx">mediaDevices</span><span class="p">.</span><span class="nx">getUserMedia</span><span class="p">({</span><span class="w"> </span><span class="nx">audio</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">deviceId</span><span class="o">:</span><span class="w"> </span><span class="nx">mic_id</span><span class="w"> </span><span class="p">}</span><span class="w"> </span><span class="p">});</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">initializeMicrophoneRecorder</span><span class="p">(</span><span class="nx">stream</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">initializeMicrophoneRecorder</span><span class="p">(</span><span class="nx">stream</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="preloadaudio">preloadAudio<a class="headerlink" href="#preloadaudio" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadAudio</span><span class="p">(</span><span class="nx">files</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_complete</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_load</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_error</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadAudio</span><span class="p">(</span><span class="nx">files</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_complete</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_load</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_error</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_8">Parameters<a class="headerlink" href="#parameters_8" title="Permanent link">&para;</a></h4>
 <table>
@@ -4296,40 +4301,40 @@ <h4 id="description_8">Description<a class="headerlink" href="#description_8" ti
 <p>The <code>callback_load</code> and <code>callback_error</code> functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.</p>
 <h4 id="examples_3">Examples<a class="headerlink" href="#examples_3" title="Permanent link">&para;</a></h4>
 <h5 id="basic-use">Basic use<a class="headerlink" href="#basic-use" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">sounds</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;file1.mp3&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file2.mp3&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file3.mp3&#39;</span><span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">sounds</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;file1.mp3&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file2.mp3&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file3.mp3&#39;</span><span class="p">];</span>
 
 <span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadAudio</span><span class="p">(</span><span class="nx">sounds</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;file loaded: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;error loading file: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="p">);</span><span class="w"></span>
-
-<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;file loaded: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;error loading file: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span>
+<span class="p">);</span>
+
+<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <h5 id="show-progress-of-loading">Show progress of loading<a class="headerlink" href="#show-progress-of-loading" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">sounds</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;file1.mp3&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file2.mp3&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file3.mp3&#39;</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">sounds</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;file1.mp3&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file2.mp3&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;file3.mp3&#39;</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadAudio</span><span class="p">(</span><span class="nx">sounds</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">});</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadAudio</span><span class="p">(</span><span class="nx">sounds</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">});</span>
 
-<span class="kd">function</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">n_loaded</span><span class="o">++</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">percentcomplete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">sounds</span><span class="p">.</span><span class="nx">length</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span><span class="w"></span>
+<span class="kd">function</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span>
+<span class="w">  </span><span class="nx">n_loaded</span><span class="o">++</span><span class="p">;</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">percentcomplete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">sounds</span><span class="p">.</span><span class="nx">length</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span>
 
-<span class="w">    </span><span class="c1">// could put something fancier here, like a progress bar</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// or updating text in the DOM.</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Loaded &#39;</span><span class="o">+</span><span class="nx">percentcomplete</span><span class="o">+</span><span class="s1">&#39;% of audio files&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="c1">// could put something fancier here, like a progress bar</span>
+<span class="w">    </span><span class="c1">// or updating text in the DOM.</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Loaded &#39;</span><span class="o">+</span><span class="nx">percentcomplete</span><span class="o">+</span><span class="s1">&#39;% of audio files&#39;</span><span class="p">);</span>
+<span class="p">}</span>
 
-<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h3 id="preloadimages">preloadImages<a class="headerlink" href="#preloadimages" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadImages</span><span class="p">(</span><span class="nx">images</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_complete</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_load</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_error</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadImages</span><span class="p">(</span><span class="nx">images</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_complete</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_load</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_error</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_9">Parameters<a class="headerlink" href="#parameters_9" title="Permanent link">&para;</a></h4>
 <table>
@@ -4371,40 +4376,40 @@ <h4 id="description_9">Description<a class="headerlink" href="#description_9" ti
 <p>The <code>callback_load</code> and <code>callback_error</code> functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.</p>
 <h4 id="examples_4">Examples<a class="headerlink" href="#examples_4" title="Permanent link">&para;</a></h4>
 <h5 id="basic-use_1">Basic use<a class="headerlink" href="#basic-use_1" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/file1.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/file2.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/file3.png&#39;</span><span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/file1.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/file2.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/file3.png&#39;</span><span class="p">];</span>
 
 <span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadImages</span><span class="p">(</span><span class="nx">images</span><span class="p">,</span><span class="w"> </span>
-<span class="w">    </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;file loaded: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;error loading file: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="p">);</span><span class="w"></span>
-
-<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span>
+<span class="w">    </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;file loaded: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span>
+<span class="w">    </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;error loading file: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span>
+<span class="p">);</span>
+
+<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <h5 id="show-progress-of-loading_1">Show progress of loading<a class="headerlink" href="#show-progress-of-loading_1" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/file1.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/file2.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/file3.png&#39;</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/file1.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/file2.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/file3.png&#39;</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadImages</span><span class="p">(</span><span class="nx">images</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">});</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadImages</span><span class="p">(</span><span class="nx">images</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">});</span>
 
-<span class="kd">function</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">n_loaded</span><span class="o">++</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">percentcomplete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">images</span><span class="p">.</span><span class="nx">length</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span><span class="w"></span>
+<span class="kd">function</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span>
+<span class="w">  </span><span class="nx">n_loaded</span><span class="o">++</span><span class="p">;</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">percentcomplete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">images</span><span class="p">.</span><span class="nx">length</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span>
 
-<span class="w">    </span><span class="c1">// could put something fancier here, like a progress bar</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// or updating text in the DOM.</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Loaded &#39;</span><span class="o">+</span><span class="nx">percentcomplete</span><span class="o">+</span><span class="s1">&#39;% of images&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="c1">// could put something fancier here, like a progress bar</span>
+<span class="w">    </span><span class="c1">// or updating text in the DOM.</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Loaded &#39;</span><span class="o">+</span><span class="nx">percentcomplete</span><span class="o">+</span><span class="s1">&#39;% of images&#39;</span><span class="p">);</span>
+<span class="p">}</span>
 
-<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h3 id="preloadvideo">preloadVideo<a class="headerlink" href="#preloadvideo" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadVideo</span><span class="p">(</span><span class="nx">video</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_complete</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_load</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_error</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadVideo</span><span class="p">(</span><span class="nx">video</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_complete</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_load</span><span class="p">,</span><span class="w"> </span><span class="nx">callback_error</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_10">Parameters<a class="headerlink" href="#parameters_10" title="Permanent link">&para;</a></h4>
 <table>
@@ -4446,41 +4451,41 @@ <h4 id="description_10">Description<a class="headerlink" href="#description_10"
 <p>The <code>callback_load</code> and <code>callback_error</code> functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.</p>
 <h4 id="examples_5">Examples<a class="headerlink" href="#examples_5" title="Permanent link">&para;</a></h4>
 <h5 id="basic-use_2">Basic use<a class="headerlink" href="#basic-use_2" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">videos</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;vid/file1.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;vid/file2.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;vid/file3.mp4&#39;</span><span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">videos</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;vid/file1.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;vid/file2.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;vid/file3.mp4&#39;</span><span class="p">];</span>
 
 <span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadVideo</span><span class="p">(</span><span class="nx">videos</span><span class="p">,</span><span class="w"> </span>
-<span class="w">  </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;file loaded: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;error loading file: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
-<span class="p">);</span><span class="w"></span>
-
-<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">  </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span>
+<span class="w">  </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;file loaded: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span>
+<span class="w">  </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"> </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;error loading file: &#39;</span><span class="p">,</span><span class="w"> </span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">}</span>
+<span class="p">);</span>
+
+<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <h5 id="show-progress-of-loading_2">Show progress of loading<a class="headerlink" href="#show-progress-of-loading_2" title="Permanent link">&para;</a></h5>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">videos</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;vid/file1.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;vid/file2.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;vid/file3.mp4&#39;</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">videos</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;vid/file1.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;vid/file2.mp4&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;vid/file3.mp4&#39;</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadVideo</span><span class="p">(</span><span class="nx">videos</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">});</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">preloadVideo</span><span class="p">(</span><span class="nx">videos</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">();</span><span class="w"> </span><span class="p">},</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">file</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">);</span><span class="w"> </span><span class="p">});</span>
 
-<span class="kd">function</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">n_loaded</span><span class="o">++</span><span class="p">;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">percentcomplete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">videos</span><span class="p">.</span><span class="nx">length</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span><span class="w"></span>
+<span class="kd">function</span><span class="w"> </span><span class="nx">updateLoadedCount</span><span class="p">(</span><span class="nx">file</span><span class="p">){</span>
+<span class="w">  </span><span class="nx">n_loaded</span><span class="o">++</span><span class="p">;</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">percentcomplete</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">n_loaded</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">videos</span><span class="p">.</span><span class="nx">length</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">;</span>
 
-<span class="w">    </span><span class="c1">// could put something fancier here, like a progress bar</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// or updating text in the DOM.</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Loaded &#39;</span><span class="o">+</span><span class="nx">percentcomplete</span><span class="o">+</span><span class="s1">&#39;% of videos&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="c1">// could put something fancier here, like a progress bar</span>
+<span class="w">    </span><span class="c1">// or updating text in the DOM.</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;Loaded &#39;</span><span class="o">+</span><span class="nx">percentcomplete</span><span class="o">+</span><span class="s1">&#39;% of videos&#39;</span><span class="p">);</span>
+<span class="p">}</span>
 
-<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span><span class="w"></span>
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">function</span><span class="w"> </span><span class="nx">startExperiment</span><span class="p">(){</span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">exp</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="simulation">Simulation<a class="headerlink" href="#simulation" title="Permanent link">&para;</a></h2>
 <h3 id="clicktarget">clickTarget<a class="headerlink" href="#clicktarget" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">clickTarget</span><span class="p">(</span><span class="nx">target</span><span class="p">,</span><span class="w"> </span><span class="nx">delay</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">clickTarget</span><span class="p">(</span><span class="nx">target</span><span class="p">,</span><span class="w"> </span><span class="nx">delay</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_11">Parameters<a class="headerlink" href="#parameters_11" title="Permanent link">&para;</a></h4>
 <table>
@@ -4509,13 +4514,13 @@ <h4 id="return-value_11">Return value<a class="headerlink" href="#return-value_1
 <h4 id="description_11">Description<a class="headerlink" href="#description_11" title="Permanent link">&para;</a></h4>
 <p>Simulates clicking on a DOM element by dispatching three MouseEvents on the <code>target</code>: <code>'mousedown'</code>, then <code>'mouseup'</code>, then <code>'click'</code>. If <code>delay</code> is positive, then the events are scheduled to execute after the delay via <code>setTimeout</code>.</p>
 <h4 id="example_5">Example<a class="headerlink" href="#example_5" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">target</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;.jspsych-btn&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">target</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;.jspsych-btn&#39;</span><span class="p">);</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">clickTarget</span><span class="p">(</span><span class="nx">target</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">clickTarget</span><span class="p">(</span><span class="nx">target</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="ensuresimulationdataconsistency">ensureSimulationDataConsistency<a class="headerlink" href="#ensuresimulationdataconsistency" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">ensureSimulationDataConsistency</span><span class="p">(</span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">ensureSimulationDataConsistency</span><span class="p">(</span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_12">Parameters<a class="headerlink" href="#parameters_12" title="Permanent link">&para;</a></h4>
 <table>
@@ -4544,11 +4549,11 @@ <h4 id="return-value_12">Return value<a class="headerlink" href="#return-value_1
 <h4 id="description_12">Description<a class="headerlink" href="#description_12" title="Permanent link">&para;</a></h4>
 <p>Performs some basic consistency checks on the <code>data</code> based on the parameters specified in <code>trial</code>. For example, if <code>trial.choices</code> is <code>"NO_KEYS"</code> but <code>data.response</code> is a key string then <code>data.response</code> and <code>data.rt</code> are set to <code>null</code>.</p>
 <h4 id="example_6">Example<a class="headerlink" href="#example_6" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">ensureSimulationDataConsistency</span><span class="p">(</span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">ensureSimulationDataConsistency</span><span class="p">(</span><span class="nx">trial</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="filltextinput">fillTextInput<a class="headerlink" href="#filltextinput" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">fillTextInput</span><span class="p">(</span><span class="nx">target</span><span class="p">,</span><span class="w"> </span><span class="nx">text</span><span class="p">,</span><span class="w"> </span><span class="nx">delay</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">fillTextInput</span><span class="p">(</span><span class="nx">target</span><span class="p">,</span><span class="w"> </span><span class="nx">text</span><span class="p">,</span><span class="w"> </span><span class="nx">delay</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_13">Parameters<a class="headerlink" href="#parameters_13" title="Permanent link">&para;</a></h4>
 <table>
@@ -4582,13 +4587,13 @@ <h4 id="return-value_13">Return value<a class="headerlink" href="#return-value_1
 <h4 id="description_13">Description<a class="headerlink" href="#description_13" title="Permanent link">&para;</a></h4>
 <p>Sets the value of the <code>target</code> HTMLInputElement to equal <code>text</code>. </p>
 <h4 id="example_7">Example<a class="headerlink" href="#example_7" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">target</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;input[type=&quot;text&quot;]&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">target</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">document</span><span class="p">.</span><span class="nx">querySelector</span><span class="p">(</span><span class="s1">&#39;input[type=&quot;text&quot;]&#39;</span><span class="p">);</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">fillTextInput</span><span class="p">(</span><span class="nx">target</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;hello!&quot;</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">fillTextInput</span><span class="p">(</span><span class="nx">target</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;hello!&quot;</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="getvalidkey">getValidKey<a class="headerlink" href="#getvalidkey" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getValidKey</span><span class="p">(</span><span class="nx">choices</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getValidKey</span><span class="p">(</span><span class="nx">choices</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_14">Parameters<a class="headerlink" href="#parameters_14" title="Permanent link">&para;</a></h4>
 <table>
@@ -4612,11 +4617,11 @@ <h4 id="return-value_14">Return value<a class="headerlink" href="#return-value_1
 <h4 id="description_14">Description<a class="headerlink" href="#description_14" title="Permanent link">&para;</a></h4>
 <p>Picks a random key given a set of options. Currently it only picks letters and numbers when <code>choices</code> is <code>"ALL_KEYS"</code>.</p>
 <h4 id="example_8">Example<a class="headerlink" href="#example_8" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">random_key</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getValidKey</span><span class="p">(</span><span class="nx">trial</span><span class="p">.</span><span class="nx">choices</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">random_key</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">getValidKey</span><span class="p">(</span><span class="nx">trial</span><span class="p">.</span><span class="nx">choices</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="keydown">keyDown<a class="headerlink" href="#keydown" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">keyDown</span><span class="p">(</span><span class="nx">key</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">keyDown</span><span class="p">(</span><span class="nx">key</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_15">Parameters<a class="headerlink" href="#parameters_15" title="Permanent link">&para;</a></h4>
 <table>
@@ -4640,11 +4645,11 @@ <h4 id="return-value_15">Return value<a class="headerlink" href="#return-value_1
 <h4 id="description_15">Description<a class="headerlink" href="#description_15" title="Permanent link">&para;</a></h4>
 <p>Dispatches a <code>'keydown'</code> event for the specified <code>key</code>. </p>
 <h4 id="example_9">Example<a class="headerlink" href="#example_9" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">keyDown</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">keyDown</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="keyup">keyUp<a class="headerlink" href="#keyup" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">keyUp</span><span class="p">(</span><span class="nx">key</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">keyUp</span><span class="p">(</span><span class="nx">key</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_16">Parameters<a class="headerlink" href="#parameters_16" title="Permanent link">&para;</a></h4>
 <table>
@@ -4668,11 +4673,11 @@ <h4 id="return-value_16">Return value<a class="headerlink" href="#return-value_1
 <h4 id="description_16">Description<a class="headerlink" href="#description_16" title="Permanent link">&para;</a></h4>
 <p>Dispatches a <code>'keyup'</code> event for the specified <code>key</code>. </p>
 <h4 id="example_10">Example<a class="headerlink" href="#example_10" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">keyUp</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">keyUp</span><span class="p">(</span><span class="s1">&#39;a&#39;</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h3 id="mergesimulationdata">mergeSimulationData<a class="headerlink" href="#mergesimulationdata" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">mergeSimulationData</span><span class="p">(</span><span class="nx">default_data</span><span class="p">,</span><span class="w"> </span><span class="nx">simulation_options</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">mergeSimulationData</span><span class="p">(</span><span class="nx">default_data</span><span class="p">,</span><span class="w"> </span><span class="nx">simulation_options</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_17">Parameters<a class="headerlink" href="#parameters_17" title="Permanent link">&para;</a></h4>
 <table>
@@ -4701,25 +4706,25 @@ <h4 id="return-value_17">Return value<a class="headerlink" href="#return-value_1
 <h4 id="description_17">Description<a class="headerlink" href="#description_17" title="Permanent link">&para;</a></h4>
 <p>This method merges the <code>default_data</code> with any data specified in <code>simulation_options.data</code>, giving priority to values specified in <code>simulation_options.data</code>. It returns the merged data.</p>
 <h4 id="example_11">Example<a class="headerlink" href="#example_11" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">default_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;a&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">default_data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;a&#39;</span>
+<span class="p">}</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">simulation_options</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">simulation_options</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">rt</span><span class="o">:</span><span class="w"> </span><span class="mf">200</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">mergeSimulationData</span><span class="p">(</span><span class="nx">default_data</span><span class="p">,</span><span class="w"> </span><span class="nx">simulation_options</span><span class="p">);</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">mergeSimulationData</span><span class="p">(</span><span class="nx">default_data</span><span class="p">,</span><span class="w"> </span><span class="nx">simulation_options</span><span class="p">);</span>
 
-<span class="nx">data</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="mf">200</span><span class="p">;</span><span class="w"> </span><span class="c1">// true</span><span class="w"></span>
+<span class="nx">data</span><span class="p">.</span><span class="nx">rt</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="mf">200</span><span class="p">;</span><span class="w"> </span><span class="c1">// true</span>
 </code></pre></div>
 <hr />
 <h2 id="timeouts">Timeouts<a class="headerlink" href="#timeouts" title="Permanent link">&para;</a></h2>
 <h3 id="clearalltimeouts">clearAllTimeouts<a class="headerlink" href="#clearalltimeouts" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">clearAllTimeouts</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">clearAllTimeouts</span><span class="p">()</span>
 </code></pre></div>
 <h4 id="parameters_18">Parameters<a class="headerlink" href="#parameters_18" title="Permanent link">&para;</a></h4>
 <p>None.</p>
@@ -4729,7 +4734,7 @@ <h4 id="description_18">Description<a class="headerlink" href="#description_18"
 <p>Clears any pending timeouts that were set using jsPsych.pluginAPI.setTimeout().</p>
 <hr />
 <h3 id="settimeout">setTimeout<a class="headerlink" href="#settimeout" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">setTimeout</span><span class="p">(</span><span class="nx">callback</span><span class="p">,</span><span class="w"> </span><span class="nx">delay</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">setTimeout</span><span class="p">(</span><span class="nx">callback</span><span class="p">,</span><span class="w"> </span><span class="nx">delay</span><span class="p">)</span>
 </code></pre></div>
 <h4 id="parameters_19">Parameters<a class="headerlink" href="#parameters_19" title="Permanent link">&para;</a></h4>
 <table>
@@ -4758,25 +4763,34 @@ <h4 id="return-value_19">Return value<a class="headerlink" href="#return-value_1
 <h4 id="description_19">Description<a class="headerlink" href="#description_19" title="Permanent link">&para;</a></h4>
 <p>This is simply a call to the standard setTimeout function in JavaScript with the added benefit of registering the setTimeout call in a central list. This is useful for scenarios where some other event (the trial ending, aborting the experiment) should stop the execution of queued timeouts.</p>
 <h4 id="example_12">Example<a class="headerlink" href="#example_12" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="c1">// print the time</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">Date</span><span class="p">.</span><span class="nx">now</span><span class="p">())</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// print the time</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">Date</span><span class="p">.</span><span class="nx">now</span><span class="p">())</span>
 
-<span class="c1">// print the time 1s later</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">setTimeout</span><span class="p">(</span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">Date</span><span class="p">.</span><span class="nx">now</span><span class="p">())</span><span class="w"></span>
-<span class="p">},</span><span class="w"> </span><span class="mf">1000</span><span class="p">);</span><span class="w"></span>
+<span class="c1">// print the time 1s later</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">setTimeout</span><span class="p">(</span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">Date</span><span class="p">.</span><span class="nx">now</span><span class="p">())</span>
+<span class="p">},</span><span class="w"> </span><span class="mf">1000</span><span class="p">);</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../jspsych-turk/" class="md-footer__link md-footer__link--prev" aria-label="Previous: jsPsych.turk" rel="prev">
@@ -4835,7 +4849,7 @@ <h4 id="example_12">Example<a class="headerlink" href="#example_12" title="Perma
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -4844,7 +4858,7 @@ <h4 id="example_12">Example<a class="headerlink" href="#example_12" title="Perma
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -4857,11 +4871,13 @@ <h4 id="example_12">Example<a class="headerlink" href="#example_12" title="Perma
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/reference/jspsych-randomization/index.html b/7.3/reference/jspsych-randomization/index.html
old mode 100755
new mode 100644
index d98384cc3c..675688aad6
--- a/7.3/reference/jspsych-randomization/index.html
+++ b/7.3/reference/jspsych-randomization/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/reference/jspsych-randomization/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -3365,21 +3368,23 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/reference/jspsych-randomization.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="jspsychrandomization">jsPsych.randomization<a class="headerlink" href="#jspsychrandomization" title="Permanent link">&para;</a></h1>
 <p>The jsPsych.randomization module contains methods that are useful for generating random lists of trial variables.</p>
 <hr />
 <h2 id="jspsychrandomizationfactorial">jsPsych.randomization.factorial<a class="headerlink" href="#jspsychrandomizationfactorial" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">factorial</span><span class="p">(</span><span class="nx">factors</span><span class="p">,</span><span class="w"> </span><span class="nx">repetitions</span><span class="p">,</span><span class="w"> </span><span class="nx">unpack</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">factorial</span><span class="p">(</span><span class="nx">factors</span><span class="p">,</span><span class="w"> </span><span class="nx">repetitions</span><span class="p">,</span><span class="w"> </span><span class="nx">unpack</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h3>
 <table>
@@ -3414,12 +3419,12 @@ <h3 id="description">Description<a class="headerlink" href="#description" title=
 <p>This method takes a list of factors and their levels, and creates a full factorial design by creating each unique combination of the factors. The returned set of combinations is in a random order.</p>
 <h3 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h3>
 <h4 id="create-full-factorial-design">Create full factorial design<a class="headerlink" href="#create-full-factorial-design" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">factors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;a.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b.jpg&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ms_delay</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">200</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">factors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;a.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b.jpg&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">ms_delay</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">200</span><span class="p">]</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">full_design</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">factorial</span><span class="p">(</span><span class="nx">factors</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">);</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">full_design</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">factorial</span><span class="p">(</span><span class="nx">factors</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">);</span>
 
 <span class="cm">/*</span>
 <span class="cm">output:</span>
@@ -3429,15 +3434,15 @@ <h4 id="create-full-factorial-design">Create full factorial design<a class="head
 <span class="cm">    {stimulus: &#39;b.jpg&#39;, ms_delay: 100},</span>
 <span class="cm">    {stimulus: &#39;a.jpg&#39;, ms_delay: 100},</span>
 <span class="cm">]</span>
-<span class="cm">*/</span><span class="w"></span>
+<span class="cm">*/</span>
 </code></pre></div>
 <h4 id="create-full-factorial-design-with-repeats">Create full factorial design with repeats<a class="headerlink" href="#create-full-factorial-design-with-repeats" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">factors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;a.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b.jpg&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ms_delay</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">200</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">factors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;a.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b.jpg&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">ms_delay</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">200</span><span class="p">]</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">full_design</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">factorial</span><span class="p">(</span><span class="nx">factors</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">full_design</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">factorial</span><span class="p">(</span><span class="nx">factors</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span>
 
 <span class="cm">/*</span>
 <span class="cm">output:</span>
@@ -3451,15 +3456,15 @@ <h4 id="create-full-factorial-design-with-repeats">Create full factorial design
 <span class="cm">    {stimulus: &#39;a.jpg&#39;, ms_delay: 100},</span>
 <span class="cm">    {stimulus: &#39;a.jpg&#39;, ms_delay: 200},</span>
 <span class="cm">]</span>
-<span class="cm">*/</span><span class="w"></span>
+<span class="cm">*/</span>
 </code></pre></div>
 <h4 id="create-full-factorial-design-unpacked">Create full factorial design, unpacked<a class="headerlink" href="#create-full-factorial-design-unpacked" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">factors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;a.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b.jpg&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">    </span><span class="nx">ms_delay</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">200</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">factors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;a.jpg&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;b.jpg&#39;</span><span class="p">],</span>
+<span class="w">    </span><span class="nx">ms_delay</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">200</span><span class="p">]</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">full_design</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">factorial</span><span class="p">(</span><span class="nx">factors</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">);</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">full_design</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">factorial</span><span class="p">(</span><span class="nx">factors</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">);</span>
 
 <span class="cm">/*</span>
 <span class="cm">output:</span>
@@ -3467,11 +3472,11 @@ <h4 id="create-full-factorial-design-unpacked">Create full factorial design, unp
 <span class="cm">    stimulus: [&#39;a.jpg&#39;,&#39;b.jpg&#39;,&#39;b.jpg&#39;,&#39;a.jpg&#39;],</span>
 <span class="cm">    ms_delay: [200, 100, 200, 100]</span>
 <span class="cm">]</span>
-<span class="cm">*/</span><span class="w"></span>
+<span class="cm">*/</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationrandomid">jsPsych.randomization.randomID<a class="headerlink" href="#jspsychrandomizationrandomid" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomID</span><span class="p">(</span><span class="nx">length</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomID</span><span class="p">(</span><span class="nx">length</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_1">Parameters<a class="headerlink" href="#parameters_1" title="Permanent link">&para;</a></h3>
 <table>
@@ -3495,15 +3500,15 @@ <h3 id="return-value_1">Return value<a class="headerlink" href="#return-value_1"
 <h3 id="description_1">Description<a class="headerlink" href="#description_1" title="Permanent link">&para;</a></h3>
 <p>Generates a random string that is likely to be unique. If length is undefined, then the string length is 32.</p>
 <h3 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomID</span><span class="p">());</span><span class="w"></span>
-<span class="c1">// outputs: &quot;t7dwz0e713pc8juuaayyfvpkdd9un239&quot;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomID</span><span class="p">());</span>
+<span class="c1">// outputs: &quot;t7dwz0e713pc8juuaayyfvpkdd9un239&quot;</span>
 
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomID</span><span class="p">(</span><span class="mf">8</span><span class="p">));</span><span class="w"></span>
-<span class="c1">// outputs: &quot;3xtpcbck&quot;</span><span class="w"></span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomID</span><span class="p">(</span><span class="mf">8</span><span class="p">));</span>
+<span class="c1">// outputs: &quot;3xtpcbck&quot;</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationrandomint">jsPsych.randomization.randomInt<a class="headerlink" href="#jspsychrandomizationrandomint" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomInt</span><span class="p">(</span><span class="nx">lower</span><span class="p">,</span><span class="w"> </span><span class="nx">upper</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomInt</span><span class="p">(</span><span class="nx">lower</span><span class="p">,</span><span class="w"> </span><span class="nx">upper</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_2">Parameters<a class="headerlink" href="#parameters_2" title="Permanent link">&para;</a></h3>
 <table>
@@ -3532,12 +3537,12 @@ <h3 id="return-value_2">Return value<a class="headerlink" href="#return-value_2"
 <h3 id="description_2">Description<a class="headerlink" href="#description_2" title="Permanent link">&para;</a></h3>
 <p>Generates a random integer from <code>lower</code> to <code>upper</code></p>
 <h3 id="example_1">Example<a class="headerlink" href="#example_1" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomInt</span><span class="p">(</span><span class="mf">2</span><span class="p">,</span><span class="mf">4</span><span class="p">));</span><span class="w"></span>
-<span class="c1">// outputs: 2 or 3 or 4.</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">randomInt</span><span class="p">(</span><span class="mf">2</span><span class="p">,</span><span class="mf">4</span><span class="p">));</span>
+<span class="c1">// outputs: 2 or 3 or 4.</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationrepeat">jsPsych.randomization.repeat<a class="headerlink" href="#jspsychrandomizationrepeat" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">array</span><span class="p">,</span><span class="w"> </span><span class="nx">repetitions</span><span class="p">,</span><span class="w"> </span><span class="nx">unpack</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">array</span><span class="p">,</span><span class="w"> </span><span class="nx">repetitions</span><span class="p">,</span><span class="w"> </span><span class="nx">unpack</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_3">Parameters<a class="headerlink" href="#parameters_3" title="Permanent link">&para;</a></h3>
 <table>
@@ -3573,60 +3578,60 @@ <h3 id="description_3">Description<a class="headerlink" href="#description_3" ti
 <p>If the array elements are objects with the same set of properties, then this method can optionally return a single object where each property is a randomized order of the properties defined in the original set of objects. This is useful for randomizing sets of parameters that are used to define a jsPsych block.</p>
 <h3 id="examples_1">Examples<a class="headerlink" href="#examples_1" title="Permanent link">&para;</a></h3>
 <h4 id="shuffle-an-array-no-repeats">Shuffle an array, no repeats<a class="headerlink" href="#shuffle-an-array-no-repeats" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// output: shuffledArray = [3,2,4,1,5]</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">1</span><span class="p">);</span>
+<span class="c1">// output: shuffledArray = [3,2,4,1,5]</span>
 </code></pre></div>
 <h4 id="shuffle-an-array-with-repeats">Shuffle an array with repeats<a class="headerlink" href="#shuffle-an-array-with-repeats" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// output: shuffledArray = [1,3,4,2,2,4,5,1,5,3]</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span>
+<span class="c1">// output: shuffledArray = [1,3,4,2,2,4,5,1,5,3]</span>
 </code></pre></div>
 <h4 id="shuffle-an-array-of-objects">Shuffle an array of objects<a class="headerlink" href="#shuffle-an-array-of-objects" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceA.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Joe&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceB.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Fred&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceC.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Mary&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"> </span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">,</span><span class="w"> </span><span class="nx">trial3</span><span class="w"> </span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span><span class="w"></span>
-
-<span class="c1">// output: shuffledArray = [ trial1, trial3, trial3, trial2, trial1, trial2 ]</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceA.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Joe&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceB.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Fred&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceC.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Mary&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"> </span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">,</span><span class="w"> </span><span class="nx">trial3</span><span class="w"> </span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span>
+
+<span class="c1">// output: shuffledArray = [ trial1, trial3, trial3, trial2, trial1, trial2 ]</span>
 </code></pre></div>
 <h4 id="shuffle-an-array-of-objects-with-unpack">Shuffle an array of objects, with unpack<a class="headerlink" href="#shuffle-an-array-of-objects-with-unpack" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceA.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Joe&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceB.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Fred&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trial3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceC.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Mary&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"> </span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">,</span><span class="w"> </span><span class="nx">trial3</span><span class="w"> </span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceA.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Joe&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceB.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;p&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Fred&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trial3</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/faceC.jpg&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_key</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;q&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">person_name</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Mary&#39;</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"> </span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">,</span><span class="w"> </span><span class="nx">trial3</span><span class="w"> </span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">);</span>
 
 <span class="cm">/*</span>
 <span class="cm">output: shuffledArray = {</span>
@@ -3634,11 +3639,11 @@ <h4 id="shuffle-an-array-of-objects-with-unpack">Shuffle an array of objects, wi
 <span class="cm">    correct_key: [&#39;p&#39;, &#39;p&#39;, &#39;q&#39;, &#39;p&#39;, &#39;q&#39;, &#39;p&#39;],</span>
 <span class="cm">    person_name: [&#39;Fred&#39;, &#39;Joe&#39;, &#39;Mary&#39;, &#39;Joe&#39;, &#39;Mary&#39;, &#39;Fred&#39;]</span>
 <span class="cm">}</span>
-<span class="cm">*/</span><span class="w"></span>
+<span class="cm">*/</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationsamplebernoulli">jsPsych.randomization.sampleBernoulli<a class="headerlink" href="#jspsychrandomizationsamplebernoulli" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleBernoulli</span><span class="p">(</span><span class="nx">p</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleBernoulli</span><span class="p">(</span><span class="nx">p</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_4">Parameters<a class="headerlink" href="#parameters_4" title="Permanent link">&para;</a></h3>
 <table>
@@ -3663,15 +3668,15 @@ <h3 id="description_4">Description<a class="headerlink" href="#description_4" ti
 <p>Generates a random sample from a Bernoulli distribution.</p>
 <h3 id="examples_2">Examples<a class="headerlink" href="#examples_2" title="Permanent link">&para;</a></h3>
 <h4 id="sample-a-value">Sample a value<a class="headerlink" href="#sample-a-value" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleBernoulli</span><span class="p">(</span><span class="mf">0.8</span><span class="p">)){</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// this happens 80% of the time</span><span class="w"></span>
-<span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// this happens 20% of the time</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleBernoulli</span><span class="p">(</span><span class="mf">0.8</span><span class="p">)){</span>
+<span class="w">    </span><span class="c1">// this happens 80% of the time</span>
+<span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="c1">// this happens 20% of the time</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationsampleexgaussian">jsPsych.randomization.sampleExGaussian<a class="headerlink" href="#jspsychrandomizationsampleexgaussian" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExGaussian</span><span class="p">(</span><span class="nx">mean</span><span class="p">,</span><span class="w"> </span><span class="nx">standard_deviation</span><span class="p">,</span><span class="w"> </span><span class="nx">rate</span><span class="p">,</span><span class="w"> </span><span class="nx">positive</span><span class="o">=</span><span class="kc">false</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExGaussian</span><span class="p">(</span><span class="nx">mean</span><span class="p">,</span><span class="w"> </span><span class="nx">standard_deviation</span><span class="p">,</span><span class="w"> </span><span class="nx">rate</span><span class="p">,</span><span class="w"> </span><span class="nx">positive</span><span class="o">=</span><span class="kc">false</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_5">Parameters<a class="headerlink" href="#parameters_5" title="Permanent link">&para;</a></h3>
 <table>
@@ -3711,11 +3716,11 @@ <h3 id="description_5">Description<a class="headerlink" href="#description_5" ti
 <p>Generates a random sample from an exponentially modified Gaussian distribution.</p>
 <h3 id="examples_3">Examples<a class="headerlink" href="#examples_3" title="Permanent link">&para;</a></h3>
 <h4 id="sample-a-value_1">Sample a value<a class="headerlink" href="#sample-a-value_1" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">rand_sample_exg</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExGaussian</span><span class="p">(</span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">0.01</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">rand_sample_exg</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExGaussian</span><span class="p">(</span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">100</span><span class="p">,</span><span class="w"> </span><span class="mf">0.01</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationsampleexponential">jsPsych.randomization.sampleExponential<a class="headerlink" href="#jspsychrandomizationsampleexponential" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExponential</span><span class="p">(</span><span class="nx">rate</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExponential</span><span class="p">(</span><span class="nx">rate</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_6">Parameters<a class="headerlink" href="#parameters_6" title="Permanent link">&para;</a></h3>
 <table>
@@ -3740,11 +3745,11 @@ <h3 id="description_6">Description<a class="headerlink" href="#description_6" ti
 <p>Generates a random sample from an exponential distribution.</p>
 <h3 id="examples_4">Examples<a class="headerlink" href="#examples_4" title="Permanent link">&para;</a></h3>
 <h4 id="sample-a-value_2">Sample a value<a class="headerlink" href="#sample-a-value_2" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">rand_sample_exg</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExponential</span><span class="p">(</span><span class="mf">0.01</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">rand_sample_exg</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleExponential</span><span class="p">(</span><span class="mf">0.01</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationsamplenormal">jsPsych.randomization.sampleNormal<a class="headerlink" href="#jspsychrandomizationsamplenormal" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleNormal</span><span class="p">(</span><span class="nx">mean</span><span class="p">,</span><span class="w"> </span><span class="nx">standard_deviation</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleNormal</span><span class="p">(</span><span class="nx">mean</span><span class="p">,</span><span class="w"> </span><span class="nx">standard_deviation</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_7">Parameters<a class="headerlink" href="#parameters_7" title="Permanent link">&para;</a></h3>
 <table>
@@ -3774,11 +3779,11 @@ <h3 id="description_7">Description<a class="headerlink" href="#description_7" ti
 <p>Generates a random sample from a normal distribution.</p>
 <h3 id="examples_5">Examples<a class="headerlink" href="#examples_5" title="Permanent link">&para;</a></h3>
 <h4 id="sample-a-value_3">Sample a value<a class="headerlink" href="#sample-a-value_3" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">rand_sample_exg</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleNormal</span><span class="p">(</span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">250</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">rand_sample_exg</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleNormal</span><span class="p">(</span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">250</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationsamplewithreplacement">jsPsych.randomization.sampleWithReplacement<a class="headerlink" href="#jspsychrandomizationsamplewithreplacement" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithReplacement</span><span class="p">(</span><span class="nx">array</span><span class="p">,</span><span class="w"> </span><span class="nx">sampleSize</span><span class="p">,</span><span class="w"> </span><span class="nx">weights</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithReplacement</span><span class="p">(</span><span class="nx">array</span><span class="p">,</span><span class="w"> </span><span class="nx">sampleSize</span><span class="p">,</span><span class="w"> </span><span class="nx">weights</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_8">Parameters<a class="headerlink" href="#parameters_8" title="Permanent link">&para;</a></h3>
 <table>
@@ -3813,18 +3818,18 @@ <h3 id="description_8">Description<a class="headerlink" href="#description_8" ti
 <p>This method returns a sample drawn at random from a set of values with replacement. The relative probability of drawing each item can be controlled by specifying the <code>weights</code>.</p>
 <h3 id="examples_6">Examples<a class="headerlink" href="#examples_6" title="Permanent link">&para;</a></h3>
 <h4 id="sample-with-equal-probability">Sample with equal probability<a class="headerlink" href="#sample-with-equal-probability" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">sample</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithReplacement</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">10</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// output: sample = [3, 1, 2, 2, 5, 1, 4, 3, 1, 5];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">sample</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithReplacement</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">10</span><span class="p">);</span>
+<span class="c1">// output: sample = [3, 1, 2, 2, 5, 1, 4, 3, 1, 5];</span>
 </code></pre></div>
 <h4 id="sample-with-unequal-probability">Sample with unequal probability<a class="headerlink" href="#sample-with-unequal-probability" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">sample</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithReplacement</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">10</span><span class="p">,</span><span class="w"> </span><span class="p">[</span><span class="mf">6</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">]);</span><span class="w"></span>
-<span class="c1">// output: sample = [3, 4, 5, 1, 2, 1, 3, 1, 1, 1];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">sample</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithReplacement</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">10</span><span class="p">,</span><span class="w"> </span><span class="p">[</span><span class="mf">6</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">1</span><span class="p">]);</span>
+<span class="c1">// output: sample = [3, 4, 5, 1, 2, 1, 3, 1, 1, 1];</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationsamplewithoutreplacement">jsPsych.randomization.sampleWithoutReplacement<a class="headerlink" href="#jspsychrandomizationsamplewithoutreplacement" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">(</span><span class="nx">array</span><span class="p">,</span><span class="w"> </span><span class="nx">sampleSize</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">(</span><span class="nx">array</span><span class="p">,</span><span class="w"> </span><span class="nx">sampleSize</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_9">Parameters<a class="headerlink" href="#parameters_9" title="Permanent link">&para;</a></h3>
 <table>
@@ -3854,13 +3859,13 @@ <h3 id="description_9">Description<a class="headerlink" href="#description_9" ti
 <p>This method returns a sample drawn at random from a set of values without replacement. The sample size must be less than or equal to the length of the array.</p>
 <h3 id="examples_7">Examples<a class="headerlink" href="#examples_7" title="Permanent link">&para;</a></h3>
 <h4 id="sample-without-replacement">Sample without replacement<a class="headerlink" href="#sample-without-replacement" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">sample</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// output: sample = [3,2];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">sample</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">(</span><span class="nx">myArray</span><span class="p">,</span><span class="w"> </span><span class="mf">2</span><span class="p">);</span>
+<span class="c1">// output: sample = [3,2];</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationsetseed">jsPsych.randomization.setSeed<a class="headerlink" href="#jspsychrandomizationsetseed" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">setSeed</span><span class="p">(</span><span class="nx">seed</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">setSeed</span><span class="p">(</span><span class="nx">seed</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_10">Parameters<a class="headerlink" href="#parameters_10" title="Permanent link">&para;</a></h3>
 <table>
@@ -3890,17 +3895,17 @@ <h3 id="description_10">Description<a class="headerlink" href="#description_10"
 The seed value will be returned from the function call, allowing you to save it in the data for the experiment if needed.</p>
 <h3 id="examples_8">Examples<a class="headerlink" href="#examples_8" title="Permanent link">&para;</a></h3>
 <h4 id="use-a-random-32-bit-seed-and-save-to-data">Use a random 32-bit seed and save to data<a class="headerlink" href="#use-a-random-32-bit-seed-and-save-to-data" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">seed</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">setSeed</span><span class="p">();</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">rng_seed</span><span class="o">:</span><span class="w"> </span><span class="nx">seed</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">seed</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">setSeed</span><span class="p">();</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">addProperties</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">rng_seed</span><span class="o">:</span><span class="w"> </span><span class="nx">seed</span>
+<span class="p">});</span>
 </code></pre></div>
 <h4 id="use-your-own-seed">Use your own seed<a class="headerlink" href="#use-your-own-seed" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">setSeed</span><span class="p">(</span><span class="s2">&quot;jspsych&quot;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">setSeed</span><span class="p">(</span><span class="s2">&quot;jspsych&quot;</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationshuffle">jsPsych.randomization.shuffle<a class="headerlink" href="#jspsychrandomizationshuffle" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffle</span><span class="p">(</span><span class="nx">array</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffle</span><span class="p">(</span><span class="nx">array</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_11">Parameters<a class="headerlink" href="#parameters_11" title="Permanent link">&para;</a></h3>
 <table>
@@ -3925,13 +3930,13 @@ <h3 id="description_11">Description<a class="headerlink" href="#description_11"
 <p>A simple method for shuffling the order of an array.</p>
 <h3 id="examples_9">Examples<a class="headerlink" href="#examples_9" title="Permanent link">&para;</a></h3>
 <h4 id="shuffle-an-array">Shuffle an array<a class="headerlink" href="#shuffle-an-array" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffle</span><span class="p">(</span><span class="nx">myArray</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// output: shuffledArray = [3,2,4,1,5]</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffle</span><span class="p">(</span><span class="nx">myArray</span><span class="p">);</span>
+<span class="c1">// output: shuffledArray = [3,2,4,1,5]</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrandomizationshufflenorepeats">jsPsych.randomization.shuffleNoRepeats<a class="headerlink" href="#jspsychrandomizationshufflenorepeats" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffleNoRepeats</span><span class="p">(</span><span class="nx">array</span><span class="p">,</span><span class="w"> </span><span class="nx">equalityTest</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffleNoRepeats</span><span class="p">(</span><span class="nx">array</span><span class="p">,</span><span class="w"> </span><span class="nx">equalityTest</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_12">Parameters<a class="headerlink" href="#parameters_12" title="Permanent link">&para;</a></h3>
 <table>
@@ -3962,35 +3967,44 @@ <h3 id="description_12">Description<a class="headerlink" href="#description_12"
 <p><em>Warning: if you provide an array that has very few valid permutations with no neighboring elements, then this method will fail and cause the browser to hang.</em></p>
 <h3 id="examples_10">Examples<a class="headerlink" href="#examples_10" title="Permanent link">&para;</a></h3>
 <h4 id="basic-example">Basic example<a class="headerlink" href="#basic-example" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffleNoRepeats</span><span class="p">(</span><span class="nx">myArray</span><span class="p">);</span><span class="w"></span>
-<span class="c1">// output: shuffledArray = [2, 3, 5, 1, 2, 4, 1, 5, 4, 1, 3, 5, 4, 3, 2]</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">,</span><span class="mf">1</span><span class="p">,</span><span class="mf">2</span><span class="p">,</span><span class="mf">3</span><span class="p">,</span><span class="mf">4</span><span class="p">,</span><span class="mf">5</span><span class="p">];</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">shuffledArray</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffleNoRepeats</span><span class="p">(</span><span class="nx">myArray</span><span class="p">);</span>
+<span class="c1">// output: shuffledArray = [2, 3, 5, 1, 2, 4, 1, 5, 4, 1, 3, 5, 4, 3, 2]</span>
 </code></pre></div>
 <h4 id="custom-equalitytest">Custom equalityTest<a class="headerlink" href="#custom-equalitytest" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myObjects</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="s2">&quot;blue&quot;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="s2">&quot;red&quot;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="s2">&quot;yellow&quot;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="s2">&quot;orange&quot;</span><span class="p">}</span><span class="w"></span>
-<span class="p">];</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">repeatedSet</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myObjects</span><span class="p">,</span><span class="mf">3</span><span class="p">);</span><span class="w"></span>
-<span class="kd">var</span><span class="w"> </span><span class="nx">shuffled</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffleNoRepeats</span><span class="p">(</span><span class="nx">repeatedSet</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">a</span><span class="p">,</span><span class="nx">b</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">a</span><span class="p">.</span><span class="nx">color</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="nx">b</span><span class="p">.</span><span class="nx">color</span><span class="w"> </span><span class="p">});</span><span class="w"></span>
-
-<span class="c1">// console.log(JSON.stringify(shuffled))</span><span class="w"></span>
-<span class="c1">// &quot;[{&quot;color&quot;:&quot;red&quot;},{&quot;color&quot;:&quot;yellow&quot;},{&quot;color&quot;:&quot;blue&quot;},{&quot;color&quot;:&quot;yellow&quot;},{&quot;color&quot;:&quot;orange&quot;},{&quot;color&quot;:&quot;red&quot;},{&quot;color&quot;:&quot;yellow&quot;},{&quot;color&quot;:&quot;orange&quot;},{&quot;color&quot;:&quot;blue&quot;},{&quot;color&quot;:&quot;orange&quot;},{&quot;color&quot;:&quot;red&quot;},{&quot;color&quot;:&quot;blue&quot;}]&quot;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">myObjects</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="s2">&quot;blue&quot;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="s2">&quot;red&quot;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="s2">&quot;yellow&quot;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">color</span><span class="o">:</span><span class="s2">&quot;orange&quot;</span><span class="p">}</span>
+<span class="p">];</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">repeatedSet</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">repeat</span><span class="p">(</span><span class="nx">myObjects</span><span class="p">,</span><span class="mf">3</span><span class="p">);</span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">shuffled</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">shuffleNoRepeats</span><span class="p">(</span><span class="nx">repeatedSet</span><span class="p">,</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">a</span><span class="p">,</span><span class="nx">b</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nx">a</span><span class="p">.</span><span class="nx">color</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="nx">b</span><span class="p">.</span><span class="nx">color</span><span class="w"> </span><span class="p">});</span>
+
+<span class="c1">// console.log(JSON.stringify(shuffled))</span>
+<span class="c1">// &quot;[{&quot;color&quot;:&quot;red&quot;},{&quot;color&quot;:&quot;yellow&quot;},{&quot;color&quot;:&quot;blue&quot;},{&quot;color&quot;:&quot;yellow&quot;},{&quot;color&quot;:&quot;orange&quot;},{&quot;color&quot;:&quot;red&quot;},{&quot;color&quot;:&quot;yellow&quot;},{&quot;color&quot;:&quot;orange&quot;},{&quot;color&quot;:&quot;blue&quot;},{&quot;color&quot;:&quot;orange&quot;},{&quot;color&quot;:&quot;red&quot;},{&quot;color&quot;:&quot;blue&quot;}]&quot;</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../jspsych-data/" class="md-footer__link md-footer__link--prev" aria-label="Previous: jsPsych.data" rel="prev">
@@ -4049,7 +4063,7 @@ <h4 id="custom-equalitytest">Custom equalityTest<a class="headerlink" href="#cus
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -4058,7 +4072,7 @@ <h4 id="custom-equalitytest">Custom equalityTest<a class="headerlink" href="#cus
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -4071,11 +4085,13 @@ <h4 id="custom-equalitytest">Custom equalityTest<a class="headerlink" href="#cus
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/reference/jspsych-turk/index.html b/7.3/reference/jspsych-turk/index.html
old mode 100755
new mode 100644
index 994b03d316..e4049d4888
--- a/7.3/reference/jspsych-turk/index.html
+++ b/7.3/reference/jspsych-turk/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/reference/jspsych-turk/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2065,21 +2068,23 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/reference/jspsych-turk.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="jspsychturk">jsPsych.turk<a class="headerlink" href="#jspsychturk" title="Permanent link">&para;</a></h1>
 <p>The jsPsych.turk module contains functions for interacting with Mechanical Turk. </p>
 <hr />
 <h2 id="jspsychturksubmittoturk">jsPsych.turk.submitToTurk<a class="headerlink" href="#jspsychturksubmittoturk" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">submitToTurk</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">submitToTurk</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h3>
 <table>
@@ -2108,23 +2113,23 @@ <h3 id="example">Example<a class="headerlink" href="#example" title="Permanent l
 <span class="p">&lt;</span><span class="nt">input</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text&quot;</span> <span class="na">id</span><span class="o">=</span><span class="s">&quot;code&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">input</span><span class="p">&gt;</span>
 <span class="p">&lt;</span><span class="nt">button</span> <span class="na">onclick</span><span class="o">=</span><span class="s">&quot;sendData();&quot;</span><span class="p">&gt;</span>Submit HIT<span class="p">&lt;/</span><span class="nt">button</span><span class="p">&gt;</span>
 
-<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="c1">// this content must be loaded in the iframe on the mechanical turk website.</span><span class="w"></span>
-<span class="c1">// usually, this means that the content is part of your &#39;recruitment ad&#39;, the</span><span class="w"></span>
-<span class="c1">// page the workers can see when they are deciding whether or not to accept a HIT.</span><span class="w"></span>
-<span class="c1">// one option is to include a simple form on this page that workers submit, with a</span><span class="w"></span>
-<span class="c1">// special code that they get at the end of the experiment.</span><span class="w"></span>
-
-<span class="kd">function</span><span class="w"> </span><span class="nx">sendData</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">submitToTurk</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">code</span><span class="o">:</span><span class="w"> </span><span class="nb">document</span><span class="p">.</span><span class="nx">getElementById</span><span class="p">(</span><span class="s1">&#39;code&#39;</span><span class="p">).</span><span class="nx">value</span><span class="w"></span>
-<span class="w">  </span><span class="p">});</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="c1">// this content must be loaded in the iframe on the mechanical turk website.</span>
+<span class="c1">// usually, this means that the content is part of your &#39;recruitment ad&#39;, the</span>
+<span class="c1">// page the workers can see when they are deciding whether or not to accept a HIT.</span>
+<span class="c1">// one option is to include a simple form on this page that workers submit, with a</span>
+<span class="c1">// special code that they get at the end of the experiment.</span>
+
+<span class="kd">function</span><span class="w"> </span><span class="nx">sendData</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">submitToTurk</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">code</span><span class="o">:</span><span class="w"> </span><span class="nb">document</span><span class="p">.</span><span class="nx">getElementById</span><span class="p">(</span><span class="s1">&#39;code&#39;</span><span class="p">).</span><span class="nx">value</span>
+<span class="w">  </span><span class="p">});</span>
+<span class="p">}</span>
 <span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychturkturkinfo">jsPsych.turk.turkInfo<a class="headerlink" href="#jspsychturkturkinfo" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">turkInfo</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">turkInfo</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_1">Parameters<a class="headerlink" href="#parameters_1" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -2141,35 +2146,44 @@ <h3 id="return-value_1">Return value<a class="headerlink" href="#return-value_1"
 <h3 id="description_1">Description<a class="headerlink" href="#description_1" title="Permanent link">&para;</a></h3>
 <p>This method returns basic information about the current Mechanical Turk session, including the worker ID, assignment ID, and HIT ID.</p>
 <h3 id="example_1">Example<a class="headerlink" href="#example_1" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">turkInfo</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">turkInfo</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">turkInfo</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">turk</span><span class="p">.</span><span class="nx">turkInfo</span><span class="p">();</span>
 
-<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Worker ID is: &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">workerId</span><span class="p">);</span><span class="w"></span>
+<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Worker ID is: &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">workerId</span><span class="p">);</span>
 
-<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Assignment ID is: &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">assignmentId</span><span class="p">);</span><span class="w"></span>
+<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Assignment ID is: &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">assignmentId</span><span class="p">);</span>
 
-<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;HIT ID is: &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">hitId</span><span class="p">);</span><span class="w"></span>
+<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;HIT ID is: &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">hitId</span><span class="p">);</span>
 
-<span class="c1">// true if the page is viewed within Mechanical Turk, </span><span class="w"></span>
-<span class="c1">// but worker has not accepted the HIT yet.</span><span class="w"></span>
-<span class="c1">// false if the page is viewed outside Mechanical Turk,</span><span class="w"></span>
-<span class="c1">// OR the worker has accepted the HIT.</span><span class="w"></span>
+<span class="c1">// true if the page is viewed within Mechanical Turk, </span>
+<span class="c1">// but worker has not accepted the HIT yet.</span>
+<span class="c1">// false if the page is viewed outside Mechanical Turk,</span>
+<span class="c1">// OR the worker has accepted the HIT.</span>
 <span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Preview mode? &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">previewMode</span><span class="p">);</span><span class="w"> </span>
 
-<span class="c1">// true if the page is viewed outside mechanical turk,</span><span class="w"></span>
-<span class="c1">// false otherwise.</span><span class="w"></span>
-<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Outside turk? &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">outsideTurk</span><span class="p">);</span><span class="w"></span>
+<span class="c1">// true if the page is viewed outside mechanical turk,</span>
+<span class="c1">// false otherwise.</span>
+<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;Outside turk? &#39;</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="nx">turkInfo</span><span class="p">.</span><span class="nx">outsideTurk</span><span class="p">);</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../jspsych-randomization/" class="md-footer__link md-footer__link--prev" aria-label="Previous: jsPsych.randomization" rel="prev">
@@ -2228,7 +2242,7 @@ <h3 id="example_1">Example<a class="headerlink" href="#example_1" title="Permane
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2237,7 +2251,7 @@ <h3 id="example_1">Example<a class="headerlink" href="#example_1" title="Permane
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2250,11 +2264,13 @@ <h3 id="example_1">Example<a class="headerlink" href="#example_1" title="Permane
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/reference/jspsych/index.html b/7.3/reference/jspsych/index.html
old mode 100755
new mode 100644
index 687720ea0f..87d5aeda1d
--- a/7.3/reference/jspsych/index.html
+++ b/7.3/reference/jspsych/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/reference/jspsych/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -3655,20 +3658,22 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/reference/jspsych.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="jspsych">jsPsych<a class="headerlink" href="#jspsych" title="Permanent link">&para;</a></h1>
 <hr />
 <h2 id="initjspsych">initJsPsych<a class="headerlink" href="#initjspsych" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">(</span><span class="nx">settings</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">(</span><span class="nx">settings</span><span class="p">);</span>
 </code></pre></div>
 <h3 id="parameters">Parameters<a class="headerlink" href="#parameters" title="Permanent link">&para;</a></h3>
 <table>
@@ -3821,18 +3826,18 @@ <h3 id="return-value">Return value<a class="headerlink" href="#return-value" tit
 <h3 id="description">Description<a class="headerlink" href="#description" title="Permanent link">&para;</a></h3>
 <p>This function initializes jsPsych with the specified experiment settings.</p>
 <h3 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span>
 <span class="w">  </span><span class="p">},</span><span class="w"> </span>
-<span class="w">  </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">default_iti</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<span class="w">  </span><span class="nx">show_progress_bar</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">default_iti</span><span class="o">:</span><span class="w"> </span><span class="mf">500</span>
+<span class="p">});</span>
 </code></pre></div>
 <p>For more examples, see the HTML files in the <a href="https://github.com/jspsych/jsPsych/tree/main/examples">examples folder</a>.</p>
 <hr />
 <h2 id="jspsychaddnodetoendoftimeline">jsPsych.addNodeToEndOfTimeline<a class="headerlink" href="#jspsychaddnodetoendoftimeline" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">addNodeToEndOfTimeline</span><span class="p">(</span><span class="nx">node_parameters</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">addNodeToEndOfTimeline</span><span class="p">(</span><span class="nx">node_parameters</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_1">Parameters<a class="headerlink" href="#parameters_1" title="Permanent link">&para;</a></h3>
 <table>
@@ -3856,20 +3861,20 @@ <h3 id="return-value_1">Return value<a class="headerlink" href="#return-value_1"
 <h3 id="description_1">Description<a class="headerlink" href="#description_1" title="Permanent link">&para;</a></h3>
 <p>Adds the timeline to the end of the experiment.</p>
 <h3 id="example_1">Example<a class="headerlink" href="#example_1" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is a new trial.&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;This is a new trial.&#39;</span>
+<span class="p">}</span>
 
-<span class="kd">var</span><span class="w"> </span><span class="nx">new_timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">var</span><span class="w"> </span><span class="nx">new_timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">]</span>
+<span class="p">}</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">addNodeToEndOfTimeline</span><span class="p">(</span><span class="nx">new_timeline</span><span class="p">)</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">addNodeToEndOfTimeline</span><span class="p">(</span><span class="nx">new_timeline</span><span class="p">)</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychendcurrenttimeline">jsPsych.endCurrentTimeline<a class="headerlink" href="#jspsychendcurrenttimeline" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">endCurrentTimeline</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">endCurrentTimeline</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_2">Parameters<a class="headerlink" href="#parameters_2" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -3879,47 +3884,47 @@ <h3 id="description_2">Description<a class="headerlink" href="#description_2" ti
 <p>Ends the current timeline. If timelines are nested, then only the timeline that contains the current trial is ended.</p>
 <h3 id="example_2">Example<a class="headerlink" href="#example_2" title="Permanent link">&para;</a></h3>
 <h4 id="end-timeline-if-a-particular-key-is-pressed">End timeline if a particular key is pressed<a class="headerlink" href="#end-timeline-if-a-particular-key-is-pressed" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;img/1.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/2.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/3.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/4.gif&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;img/5.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/6.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/7.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/8.gif&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="s2">&quot;img/9.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/10.gif&quot;</span><span class="w"></span>
-<span class="p">];</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-<span class="k">for</span><span class="w"> </span><span class="p">(</span><span class="kd">var</span><span class="w"> </span><span class="nx">i</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"> </span><span class="nx">i</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="nx">images</span><span class="p">.</span><span class="nx">length</span><span class="p">;</span><span class="w"> </span><span class="nx">i</span><span class="o">++</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trials</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span><span class="w"></span>
-<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">images</span><span class="p">[</span><span class="nx">i</span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="p">});</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">images</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="s2">&quot;img/1.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/2.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/3.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/4.gif&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;img/5.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/6.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/7.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/8.gif&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="s2">&quot;img/9.gif&quot;</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;img/10.gif&quot;</span>
+<span class="p">];</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+<span class="k">for</span><span class="w"> </span><span class="p">(</span><span class="kd">var</span><span class="w"> </span><span class="nx">i</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">0</span><span class="p">;</span><span class="w"> </span><span class="nx">i</span><span class="w"> </span><span class="o">&lt;</span><span class="w"> </span><span class="nx">images</span><span class="p">.</span><span class="nx">length</span><span class="p">;</span><span class="w"> </span><span class="nx">i</span><span class="o">++</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">trials</span><span class="p">.</span><span class="nx">push</span><span class="p">({</span>
+<span class="w">    </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">images</span><span class="p">[</span><span class="nx">i</span><span class="p">]</span>
+<span class="w">  </span><span class="p">});</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;y&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;n&#39;</span><span class="p">],</span><span class="w"> </span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press &quot;y&quot; to Continue. Press &quot;n&quot; to end this node of the experiment.&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;n&#39;</span><span class="p">))</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">endCurrentTimeline</span><span class="p">();</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="nx">trials</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">after_block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;The next node&lt;/p&gt;&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">block</span><span class="p">,</span><span class="w"> </span><span class="nx">after_block</span><span class="p">]);</span><span class="w"></span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press &quot;y&quot; to Continue. Press &quot;n&quot; to end this node of the experiment.&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;n&#39;</span><span class="p">))</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">endCurrentTimeline</span><span class="p">();</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="nx">trials</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">after_block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;The next node&lt;/p&gt;&#39;</span>
+<span class="p">}</span>
+
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">block</span><span class="p">,</span><span class="w"> </span><span class="nx">after_block</span><span class="p">]);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychendexperiment">jsPsych.endExperiment<a class="headerlink" href="#jspsychendexperiment" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">endExperiment</span><span class="p">(</span><span class="nx">end_message</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">endExperiment</span><span class="p">(</span><span class="nx">end_message</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_3">Parameters<a class="headerlink" href="#parameters_3" title="Permanent link">&para;</a></h3>
 <table>
@@ -3949,21 +3954,21 @@ <h3 id="description_3">Description<a class="headerlink" href="#description_3" ti
 <p>Ends the experiment, skipping all remaining trials. If the <code>on_finish</code> event handler for <code>jsPsych</code> returns a <code>Promise</code> then the <code>end_message</code> will not be displayed until the promise is resolved.</p>
 <h3 id="example_3">Example<a class="headerlink" href="#example_3" title="Permanent link">&para;</a></h3>
 <h4 id="end-the-experiment-if-a-particular-response-is-given">End the experiment if a particular response is given<a class="headerlink" href="#end-the-experiment-if-a-particular-response-is-given" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image1.jpg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;y&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;n&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press &quot;y&quot; to Continue. Press &quot;n&quot; to end the experiment&lt;/p&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;n&quot;</span><span class="p">)){</span><span class="w"></span>
-<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">endExperiment</span><span class="p">(</span><span class="s1">&#39;The experiment was ended by pressing &quot;n&quot;.&#39;</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;image1.jpg&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;y&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;n&#39;</span><span class="p">]</span>
+<span class="w">  </span><span class="nx">prompt</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;p&gt;Press &quot;y&quot; to Continue. Press &quot;n&quot; to end the experiment&lt;/p&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;n&quot;</span><span class="p">)){</span>
+<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">endExperiment</span><span class="p">(</span><span class="s1">&#39;The experiment was ended by pressing &quot;n&quot;.&#39;</span><span class="p">);</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychfinishtrial">jsPsych.finishTrial<a class="headerlink" href="#jspsychfinishtrial" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_4">Parameters<a class="headerlink" href="#parameters_4" title="Permanent link">&para;</a></h3>
 <table>
@@ -3995,12 +4000,12 @@ <h3 id="description_4">Description<a class="headerlink" href="#description_4" ti
 <li>The next trial, if one exists, is started.</li>
 </ul>
 <h3 id="example_4">Example<a class="headerlink" href="#example_4" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="c1">// this code would be in a plugin</span><span class="w"></span>
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">({</span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="c1">// this code would be in a plugin</span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">({</span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychgetalltimelinevariables">jsPsych.getAllTimelineVariables<a class="headerlink" href="#jspsychgetalltimelinevariables" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getAllTimelineVariables</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getAllTimelineVariables</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_5">Parameters<a class="headerlink" href="#parameters_5" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4010,18 +4015,18 @@ <h3 id="description_5">Description<a class="headerlink" href="#description_5" ti
 <p>This function can be used to get all the timeline variables at a particular moment in the experiment. Can be useful for annotating
 data, such as in the example below.</p>
 <h3 id="example_5">Example<a class="headerlink" href="#example_5" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Just a demo&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="c1">// merge all timeline variables available at this trial into the data for this trial</span><span class="w"></span>
-<span class="w">    </span><span class="nb">Object</span><span class="p">.</span><span class="nx">assign</span><span class="p">(</span><span class="nx">data</span><span class="p">,</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getAllTimelineVariables</span><span class="p">())</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Just a demo&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">    </span><span class="c1">// merge all timeline variables available at this trial into the data for this trial</span>
+<span class="w">    </span><span class="nb">Object</span><span class="p">.</span><span class="nx">assign</span><span class="p">(</span><span class="nx">data</span><span class="p">,</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getAllTimelineVariables</span><span class="p">())</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychgetcurrenttimelinenodeid">jsPsych.getCurrentTimelineNodeID<a class="headerlink" href="#jspsychgetcurrenttimelinenodeid" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTimelineNodeID</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTimelineNodeID</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_6">Parameters<a class="headerlink" href="#parameters_6" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4050,12 +4055,12 @@ <h3 id="description_6">Description<a class="headerlink" href="#description_6" ti
 <li><code>"0.2-1.3"</code> is the ID of the second TimelineNode, executing for the fourth time, on the timeline of the first top-level TimelineNode, executing for the third time.</li>
 </ul>
 <h3 id="example_6">Example<a class="headerlink" href="#example_6" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTimelineNodeID</span><span class="p">();</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The current TimelineNode ID is &#39;</span><span class="o">+</span><span class="nx">id</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">id</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTimelineNodeID</span><span class="p">();</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The current TimelineNode ID is &#39;</span><span class="o">+</span><span class="nx">id</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychgetcurrenttrial">jsPsych.getCurrentTrial<a class="headerlink" href="#jspsychgetcurrenttrial" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTrial</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTrial</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_7">Parameters<a class="headerlink" href="#parameters_7" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4064,12 +4069,12 @@ <h3 id="return-value_7">Return value<a class="headerlink" href="#return-value_7"
 <h3 id="description_7">Description<a class="headerlink" href="#description_7" title="Permanent link">&para;</a></h3>
 <p>Get a description of the current trial</p>
 <h3 id="example_7">Example<a class="headerlink" href="#example_7" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTrial</span><span class="p">();</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The current trial is using the &#39;</span><span class="o">+</span><span class="nx">trial</span><span class="p">.</span><span class="nx">type</span><span class="o">+</span><span class="s1">&#39; plugin&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getCurrentTrial</span><span class="p">();</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="s1">&#39;The current trial is using the &#39;</span><span class="o">+</span><span class="nx">trial</span><span class="p">.</span><span class="nx">type</span><span class="o">+</span><span class="s1">&#39; plugin&#39;</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychgetdisplayelement">jsPsych.getDisplayElement<a class="headerlink" href="#jspsychgetdisplayelement" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getDisplayElement</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getDisplayElement</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_8">Parameters<a class="headerlink" href="#parameters_8" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4078,13 +4083,13 @@ <h3 id="return-value_8">Return value<a class="headerlink" href="#return-value_8"
 <h3 id="description_8">Description<a class="headerlink" href="#description_8" title="Permanent link">&para;</a></h3>
 <p>Get the DOM element that displays the experiment.</p>
 <h3 id="example_8">Example<a class="headerlink" href="#example_8" title="Permanent link">&para;</a></h3>
-<h2 id="var-el-jspsychgetdisplayelement-hide-the-jspsych-display-elstylevisibility-hidden"><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">el</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getDisplayElement</span><span class="p">();</span><span class="w"></span>
+<h2 id="var-el-jspsychgetdisplayelement-hide-the-jspsych-display-elstylevisibility-hidden"><div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">el</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getDisplayElement</span><span class="p">();</span>
 
-<span class="c1">// hide the jsPsych display</span><span class="w"></span>
-<span class="nx">el</span><span class="p">.</span><span class="nx">style</span><span class="p">.</span><span class="nx">visibility</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;hidden&#39;</span><span class="p">;</span><span class="w"></span>
+<span class="c1">// hide the jsPsych display</span>
+<span class="nx">el</span><span class="p">.</span><span class="nx">style</span><span class="p">.</span><span class="nx">visibility</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s1">&#39;hidden&#39;</span><span class="p">;</span>
 </code></pre></div><a class="headerlink" href="#var-el-jspsychgetdisplayelement-hide-the-jspsych-display-elstylevisibility-hidden" title="Permanent link">&para;</a></h2>
 <h2 id="jspsychgetinitsettings">jsPsych.getInitSettings<a class="headerlink" href="#jspsychgetinitsettings" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getInitSettings</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getInitSettings</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_9">Parameters<a class="headerlink" href="#parameters_9" title="Permanent link">&para;</a></h3>
 <p>None</p>
@@ -4093,14 +4098,14 @@ <h3 id="return-value_9">Return value<a class="headerlink" href="#return-value_9"
 <h3 id="description_9">Description<a class="headerlink" href="#description_9" title="Permanent link">&para;</a></h3>
 <p>Gets the object containing the settings for the current experiment.</p>
 <h3 id="example_9">Example<a class="headerlink" href="#example_9" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">settings</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getInitSettings</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">settings</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getInitSettings</span><span class="p">();</span>
 
-<span class="c1">// check the experiment structure</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">settings</span><span class="p">.</span><span class="nx">timeline</span><span class="p">));</span><span class="w"></span>
+<span class="c1">// check the experiment structure</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nb">JSON</span><span class="p">.</span><span class="nx">stringify</span><span class="p">(</span><span class="nx">settings</span><span class="p">.</span><span class="nx">timeline</span><span class="p">));</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychgetprogress">jsPsych.getProgress<a class="headerlink" href="#jspsychgetprogress" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgress</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgress</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_10">Parameters<a class="headerlink" href="#parameters_10" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4135,12 +4140,12 @@ <h3 id="return-value_10">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_10">Description<a class="headerlink" href="#description_10" title="Permanent link">&para;</a></h3>
 <p>This method returns information about the length of the experiment and the participant's current location in the experiment timeline.</p>
 <h3 id="example_10">Example<a class="headerlink" href="#example_10" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">progress</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgress</span><span class="p">();</span><span class="w"></span>
-<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;You have completed approximately &#39;</span><span class="o">+</span><span class="nx">progress</span><span class="p">.</span><span class="nx">percent_complete</span><span class="o">+</span><span class="s1">&#39;% of the experiment&#39;</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">progress</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgress</span><span class="p">();</span>
+<span class="nx">alert</span><span class="p">(</span><span class="s1">&#39;You have completed approximately &#39;</span><span class="o">+</span><span class="nx">progress</span><span class="p">.</span><span class="nx">percent_complete</span><span class="o">+</span><span class="s1">&#39;% of the experiment&#39;</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychgetprogressbarcompleted">jsPsych.getProgressBarCompleted<a class="headerlink" href="#jspsychgetprogressbarcompleted" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgressBarCompleted</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgressBarCompleted</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_11">Parameters<a class="headerlink" href="#parameters_11" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4149,11 +4154,11 @@ <h3 id="return-value_11">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_11">Description<a class="headerlink" href="#description_11" title="Permanent link">&para;</a></h3>
 <p>Used to get the current value of the progress bar. Works for automated and manual control.</p>
 <h3 id="example_11">Example<a class="headerlink" href="#example_11" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">progress_bar_amount</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgressBarCompleted</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">progress_bar_amount</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getProgressBarCompleted</span><span class="p">();</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychgetstarttime">jsPsych.getStartTime<a class="headerlink" href="#jspsychgetstarttime" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getStartTime</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getStartTime</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_12">Parameters<a class="headerlink" href="#parameters_12" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4162,11 +4167,11 @@ <h3 id="return-value_12">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_12">Description<a class="headerlink" href="#description_12" title="Permanent link">&para;</a></h3>
 <p>Get the time that the experiment began.</p>
 <h3 id="example_12">Example<a class="headerlink" href="#example_12" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">start_time</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getStartTime</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">start_time</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getStartTime</span><span class="p">();</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychgettotaltime">jsPsych.getTotalTime<a class="headerlink" href="#jspsychgettotaltime" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getTotalTime</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getTotalTime</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_13">Parameters<a class="headerlink" href="#parameters_13" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4175,12 +4180,12 @@ <h3 id="return-value_13">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_13">Description<a class="headerlink" href="#description_13" title="Permanent link">&para;</a></h3>
 <p>Gets the total time the participant has been in the experiment.</p>
 <h3 id="example_13">Example<a class="headerlink" href="#example_13" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">time</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getTotalTime</span><span class="p">();</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">time</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">time</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">getTotalTime</span><span class="p">();</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">time</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychpauseexperiment">jsPsych.pauseExperiment<a class="headerlink" href="#jspsychpauseexperiment" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pauseExperiment</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pauseExperiment</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_14">Parameters<a class="headerlink" href="#parameters_14" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4189,21 +4194,21 @@ <h3 id="return-value_14">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_14">Description<a class="headerlink" href="#description_14" title="Permanent link">&para;</a></h3>
 <p>Pauses the experiment. The experiment will finish the current trial, but will not execute any additional trials until <code>jsPsych.resumeExperiment()</code> is called.</p>
 <h3 id="example_14">Example<a class="headerlink" href="#example_14" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Press p to take a 30 second break. Otherwise, press c to continue immediately.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="s1">&#39;c&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Press p to take a 30 second break. Otherwise, press c to continue immediately.&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="s1">&#39;c&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
 <span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;p&quot;</span><span class="p">))</span><span class="w"> </span><span class="p">{</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pauseExperiment</span><span class="p">();</span><span class="w"></span>
-<span class="w">      </span><span class="nx">setTimeout</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">resumeExperiment</span><span class="p">,</span><span class="w"> </span><span class="mf">30000</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pauseExperiment</span><span class="p">();</span>
+<span class="w">      </span><span class="nx">setTimeout</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">resumeExperiment</span><span class="p">,</span><span class="w"> </span><span class="mf">30000</span><span class="p">);</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychresumeexperiment">jsPsych.resumeExperiment<a class="headerlink" href="#jspsychresumeexperiment" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">resumeExperiment</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">resumeExperiment</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_15">Parameters<a class="headerlink" href="#parameters_15" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4212,21 +4217,21 @@ <h3 id="return-value_15">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_15">Description<a class="headerlink" href="#description_15" title="Permanent link">&para;</a></h3>
 <p>Resumes the experiment after a call to <code>jsPsych.pauseExperiment()</code>. If the post trial delay (<code>post_trial_gap</code>) has not yet been reached, then the experiment will not continue until the delay is finished. For example, if <code>post_trial_gap</code> was 10,000ms and <code>jsPsych.resumeExperiment()</code> was called 6,000ms after the previous trial finished, then the experiment would not continue for another 4,000ms.</p>
 <h3 id="example_15">Example<a class="headerlink" href="#example_15" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Press p to take a 30 second break. Otherwise, press c to continue immediately.&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="s1">&#39;c&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Press p to take a 30 second break. Otherwise, press c to continue immediately.&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;p&#39;</span><span class="p">,</span><span class="s1">&#39;c&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
 <span class="w">    </span><span class="k">if</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="s2">&quot;p&quot;</span><span class="p">))</span><span class="w"> </span><span class="p">{</span><span class="w"> </span>
-<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pauseExperiment</span><span class="p">();</span><span class="w"></span>
-<span class="w">      </span><span class="nx">setTimeout</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">resumeExperiment</span><span class="p">,</span><span class="w"> </span><span class="mf">30000</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="w">      </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pauseExperiment</span><span class="p">();</span>
+<span class="w">      </span><span class="nx">setTimeout</span><span class="p">(</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">resumeExperiment</span><span class="p">,</span><span class="w"> </span><span class="mf">30000</span><span class="p">);</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychrun">jsPsych.run<a class="headerlink" href="#jspsychrun" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_16">Parameters<a class="headerlink" href="#parameters_16" title="Permanent link">&para;</a></h3>
 <table>
@@ -4250,13 +4255,13 @@ <h3 id="return-value_16">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_16">Description<a class="headerlink" href="#description_16" title="Permanent link">&para;</a></h3>
 <p>Start the jsPsych experiment with the specified timeline.</p>
 <h3 id="example_16">Example<a class="headerlink" href="#example_16" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">,</span><span class="w"> </span><span class="nx">trial3</span><span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="nx">trial1</span><span class="p">,</span><span class="w"> </span><span class="nx">trial2</span><span class="p">,</span><span class="w"> </span><span class="nx">trial3</span><span class="p">];</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychsetprogressbar">jsPsych.setProgressBar<a class="headerlink" href="#jspsychsetprogressbar" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="nx">value</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="nx">value</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_17">Parameters<a class="headerlink" href="#parameters_17" title="Permanent link">&para;</a></h3>
 <table>
@@ -4280,11 +4285,11 @@ <h3 id="return-value_17">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_17">Description<a class="headerlink" href="#description_17" title="Permanent link">&para;</a></h3>
 <p>Set the progress bar to a custom amount. Proportion must be between 0 and 1. Values larger than 1 are treated as 1.</p>
 <h3 id="example_17">Example<a class="headerlink" href="#example_17" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="mf">0.85</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">setProgressBar</span><span class="p">(</span><span class="mf">0.85</span><span class="p">);</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychtimelinevariable">jsPsych.timelineVariable<a class="headerlink" href="#jspsychtimelinevariable" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="nx">variable</span><span class="p">,</span><span class="w"> </span><span class="nx">call_immediate</span><span class="p">)</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="nx">variable</span><span class="p">,</span><span class="w"> </span><span class="nx">call_immediate</span><span class="p">)</span>
 </code></pre></div>
 <h3 id="parameters_18">Parameters<a class="headerlink" href="#parameters_18" title="Permanent link">&para;</a></h3>
 <table>
@@ -4314,60 +4319,60 @@ <h3 id="description_18">Description<a class="headerlink" href="#description_18"
 <p><a href="../../overview/timeline/#timeline-variables">Timeline variables</a> are a powerful technique for generating experiments with repetitive procedures but different parameter values. This function fetches the current value of a particular timeline variable. It must be used in conjunction with a timeline that has timeline variables. See the <a href="../../overview/timeline/#timeline-variables">timeline variable section</a> for details.</p>
 <h3 id="examples">Examples<a class="headerlink" href="#examples" title="Permanent link">&para;</a></h3>
 <h4 id="standard-use-as-a-parameter-for-a-trial">Standard use as a parameter for a trial<a class="headerlink" href="#standard-use-as-a-parameter-for-a-trial" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;image&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face1.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face2.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face3.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face4.png&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;image&#39;</span><span class="p">)</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face1.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face2.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face3.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face4.png&#39;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <h4 id="invoking-immediately-in-a-function">Invoking immediately in a function<a class="headerlink" href="#invoking-immediately-in-a-function" title="Permanent link">&para;</a></h4>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="s2">&quot;&lt;img style=&#39;width:100px; height:100px;&#39; src=&#39;&quot;</span><span class="o">+</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;image&#39;</span><span class="p">)</span><span class="o">+</span><span class="s2">&quot;&#39;&gt;&lt;/img&gt;&quot;</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face1.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face2.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face3.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face4.png&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="s2">&quot;&lt;img style=&#39;width:100px; height:100px;&#39; src=&#39;&quot;</span><span class="o">+</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;image&#39;</span><span class="p">)</span><span class="o">+</span><span class="s2">&quot;&#39;&gt;&lt;/img&gt;&quot;</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face1.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face2.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face3.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face4.png&#39;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>Prior to jsPsych v6.3.0, the <code>call_immediate</code> parameter must be set to <code>true</code> when <code>jsPsych.timelineVariable</code> is called from within a function, such as a <a href="../overview/dynamic-parameters">dynamic parameter</a>:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="s2">&quot;&lt;img style=&#39;width:100px; height:100px;&#39; src=&#39;&quot;</span><span class="o">+</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;image&#39;</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">)</span><span class="o">+</span><span class="s2">&quot;&#39;&gt;&lt;/img&gt;&quot;</span><span class="p">;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face1.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face2.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face3.png&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face4.png&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="s2">&quot;&lt;img style=&#39;width:100px; height:100px;&#39; src=&#39;&quot;</span><span class="o">+</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;image&#39;</span><span class="p">,</span><span class="w"> </span><span class="kc">true</span><span class="p">)</span><span class="o">+</span><span class="s2">&quot;&#39;&gt;&lt;/img&gt;&quot;</span><span class="p">;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">trial</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face1.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face2.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face3.png&#39;</span><span class="p">},</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">image</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;face4.png&#39;</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <hr />
 <h2 id="jspsychversion">jsPsych.version<a class="headerlink" href="#jspsychversion" title="Permanent link">&para;</a></h2>
-<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">version</span><span class="p">()</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">version</span><span class="p">()</span>
 </code></pre></div>
 <h3 id="parameters_19">Parameters<a class="headerlink" href="#parameters_19" title="Permanent link">&para;</a></h3>
 <p>None.</p>
@@ -4376,20 +4381,29 @@ <h3 id="return-value_19">Return value<a class="headerlink" href="#return-value_1
 <h3 id="description_19">Description<a class="headerlink" href="#description_19" title="Permanent link">&para;</a></h3>
 <p>Gets the version of jsPsych.</p>
 <h3 id="example_18">Example<a class="headerlink" href="#example_18" title="Permanent link">&para;</a></h3>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">version</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">version</span><span class="p">();</span><span class="w"></span>
-<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">version</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">version</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">version</span><span class="p">();</span>
+<span class="nx">console</span><span class="p">.</span><span class="nx">log</span><span class="p">(</span><span class="nx">version</span><span class="p">);</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../../overview/timing-accuracy/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Timing Accuracy" rel="prev">
@@ -4448,7 +4462,7 @@ <h3 id="example_18">Example<a class="headerlink" href="#example_18" title="Perma
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -4457,7 +4471,7 @@ <h3 id="example_18">Example<a class="headerlink" href="#example_18" title="Perma
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -4470,11 +4484,13 @@ <h3 id="example_18">Example<a class="headerlink" href="#example_18" title="Perma
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/search/search_index.json b/7.3/search/search_index.json
old mode 100755
new mode 100644
index 4f62f44882..69c735c3a5
--- a/7.3/search/search_index.json
+++ b/7.3/search/search_index.json
@@ -1 +1 @@
-{"config":{"indexing":"full","lang":["en"],"min_search_length":3,"prebuild_index":false,"separator":"[\\s\\-]+"},"docs":[{"location":"","text":"\u00b6 jsPsych is a JavaScript framework for creating behavioral experiments that run in a web browser. Experiments in jsPsych are created using plugins . Each plugin defines different kinds of events, like showing an image on the screen, and collects different kinds of data, like recording which key was pressed at which time. You can use the plugins that are included with jsPsych , use plugins that are developed by community members in the contrib repository , or create your own plugins . By assembling different plugins together into a timeline , it is possible to create a wide range of experiments. The page on timelines is a good place to start learning about jsPsych. From there, you might want to complete the hello world tutorial to learn how to set up a jsPsych experiment and the reaction time experiment tutorial to learn the core features of the framework.","title":"Introduction"},{"location":"#_1","text":"jsPsych is a JavaScript framework for creating behavioral experiments that run in a web browser. Experiments in jsPsych are created using plugins . Each plugin defines different kinds of events, like showing an image on the screen, and collects different kinds of data, like recording which key was pressed at which time. You can use the plugins that are included with jsPsych , use plugins that are developed by community members in the contrib repository , or create your own plugins . By assembling different plugins together into a timeline , it is possible to create a wide range of experiments. The page on timelines is a good place to start learning about jsPsych. From there, you might want to complete the hello world tutorial to learn how to set up a jsPsych experiment and the reaction time experiment tutorial to learn the core features of the framework.","title":""},{"location":"about/about/","text":"About jsPsych \u00b6 jsPsych is open source project with numerous contributors . The project is currently managed by the core team of Josh de Leeuw ( @jodeleeuw ), Becky Gilbert ( @becky-gilbert ), and Bj\u00f6rn Luchterhandt ( @bjoluc ). jsPsych was created by Josh de Leeuw . Citation \u00b6 If you use this library in academic work, the preferred citation is: de Leeuw, J.R., Gilbert, R.A., & Luchterhandt, B. (2023). jsPsych: Enabling an open-source collaborative ecosystem of behavioral experiments. Journal of Open Source Software , 8 (85), 5351, https://joss.theoj.org/papers/10.21105/joss.05351 . This paper is an updated description of jsPsych and includes all current core team members. It replaces the earlier paper that described jsPsych: de Leeuw, J.R. (2015). jsPsych: A JavaScript library for creating behavioral experiments in a Web browser. Behavior Research Methods , 47 (1), 1-12. doi: 10.3758/s13428-014-0458-y Citations help us demonstrate that this library is used and valued, which allows us to continue working on it.","title":"About jsPsych"},{"location":"about/about/#about-jspsych","text":"jsPsych is open source project with numerous contributors . The project is currently managed by the core team of Josh de Leeuw ( @jodeleeuw ), Becky Gilbert ( @becky-gilbert ), and Bj\u00f6rn Luchterhandt ( @bjoluc ). jsPsych was created by Josh de Leeuw .","title":"About jsPsych"},{"location":"about/about/#citation","text":"If you use this library in academic work, the preferred citation is: de Leeuw, J.R., Gilbert, R.A., & Luchterhandt, B. (2023). jsPsych: Enabling an open-source collaborative ecosystem of behavioral experiments. Journal of Open Source Software , 8 (85), 5351, https://joss.theoj.org/papers/10.21105/joss.05351 . This paper is an updated description of jsPsych and includes all current core team members. It replaces the earlier paper that described jsPsych: de Leeuw, J.R. (2015). jsPsych: A JavaScript library for creating behavioral experiments in a Web browser. Behavior Research Methods , 47 (1), 1-12. doi: 10.3758/s13428-014-0458-y Citations help us demonstrate that this library is used and valued, which allows us to continue working on it.","title":"Citation"},{"location":"about/license/","text":"License \u00b6 jsPsych is licensed under the MIT license. The MIT License (MIT) Copyright (c) 2014-2022 Joshua R. de Leeuw Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.","title":"License"},{"location":"about/license/#license","text":"jsPsych is licensed under the MIT license. The MIT License (MIT) Copyright (c) 2014-2022 Joshua R. de Leeuw Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.","title":"License"},{"location":"developers/configuration/","text":"Configuring the jsPsych development environment \u00b6 Setup \u00b6 JsPsych is written using TypeScript , a superset of JavaScript that adds static typing, but compiles to plain JavaScript. The TypeScript compiler itself is written in JavaScript and can be run by Node.js , a runtime to execute JavaScript code without a web browser. Node.js comes with a package manager called NPM (Node Package Manager) that can install JavaScript libraries to run on your machine, such as TypeScript and other build tools for jsPsych. In order to work on code in the jsPsych or the jspsych-contrib repository, it is recommended that you follow the steps below to set up your development environment. Install Node.js \u00b6 The jsPsych development setup requires Node.js >= v14 to be installed on your machine. We recommend that you install version 16 since it includes version 7 of NPM (required for the workspaces feature that the jsPsych repositories use). If you are bound to Node.js v14, make sure to install NPM v7 manually (via npm install -g npm@7 ). Clone the repository and install the dependencies \u00b6 Clone either the jsPsych repository or the jspsych-contrib repository by running git clone https://github.com/jspsych/jsPsych.git && cd jsPsych or git clone https://github.com/jspsych/jspsych-contrib.git && cd jspsych-contrib in a terminal. Then run npm install . This will create a node_modules directory and install all the dependencies into it that are required to build and test jsPsych. Attention It is important that npm install is only run in the root directory of the repository (due to the NPM workspaces feature). If you accidentally ran npm install anywhere else, remove the node_modules directory and the package-lock.json file that were created at that location and run npm install in the root directory again. Info If you are running npm install in the core jsPsych repository, this will also execute the build chain for all packages in the jsPsych repository. This step may take a few minutes. If you would like to use that time efficiently, consider reading the following two sections to know what's happening. Repository structure \u00b6 A Node.js package is a directory that contains a package.json file describing it. Most importantly, a package.json file lists other packages that the package depends on. The jsPsych and jspsych-contrib repositories use NPM workspaces . That means, running npm install in the repository root will install the dependencies for all packages in the packages directory. The core jsPsych library and every jsPsych plugin or extension is laid out as an individual package. These packages are published to the NPM registry where they can be downloaded by NPM or any CDN (such as unpkg ). Build chain and build artifacts \u00b6 JsPsych comes with a build chain (specified in the @jspsych/config package) that can be executed by running npm run build in a package's directory. The build chain will read the package (starting at its src/index.ts file) and create the following build artifacts in the package's dist directory: index.js This file contains everything from index.ts , but as plain JavaScript and bundled in a single file (i.e. without import ing files from the same package). It is used by bundlers like webpack . index.cjs Like index.js , but using the old CommonJS standard to support backwards-compatible tools like the Jest testing framework. index.browser.js This file, like index.js , contains the entire package as plain JavaScript, but this time wrapped in a function so that it can be included directly by browsers using the <script> tag. For plugins or extensions, the default export of a module (i.e. whatever statement comes after export default in the index.ts file) is assigned to a global variable. The name of this global variable is specified in the package's rollup.config.mjs file, as a parameter to the makeRollupConfig() function. Hence, for instance, including the index.browser.js file from the plugin-html-keyboard-response package would assign the HtmlKeyboardResponsePlugin class to the global jsPsychHtmlKeyboardResponse variable. Because the code in index.browser.js looks very similar to the index.ts code but is fully supported by modern web browsers, all examples in the examples directory reference the index.browser.js files so users can also modify the source code directly without running the build chain. index.browser.min.js There are different versions of the JavaScript language specification and not all web browsers and browser versions support all JavaScript features. That's why the jsPsych build chain uses Babel to translate the source files into code that a majority of web browsers can understand. The result of this operation is index.browser.min.js . It behaves just like index.browser.js , but adds support for older browsers by substituting new JavaScript features using older ones. Because this is the recommended build artifact for production usage (and is automatically served by unpkg), the code in index.browser.min.js is also processed by Terser to reduce its size and speed up experiment loading times. *.js.map When debugging code in a browser (especially index.browser.min.js , which is not easily readable due to Terser and Babel), it is important to be able to read the original source code in the debugger. For every build artifact, there is a .map file which contains a mapping of the generated code to the original source code. Browsers automatically read these .map files and display the original code in their debuggers instead of the generated one. *.d.ts The .d.ts files contain the TypeScript type definitions that would otherwise be lost during compilation to plain JavaScript. They are read by Typescript and editors when a package is imported into another TypeScript project. Testing \u00b6 Automated code testing for jsPsych is implemented with Jest . To run the tests, install Node and npm. Run npm install in the root jsPsych directory. Then run npm test . You can also run npm test in the directory of the package that you would like to test. For example, if you are developing tests for the html-keyboard-response plugin you can run npm test in /packages/plugin-html-keyboard-response . If you want to run one file from the root directory, using the aforementioned example, you can run npm test -- /packages/plugin-html-keyboard-response/src/index.spec.ts . Tests for the core jsPsych library are located in /packages/jspsych/tests . Tests for plugins and extensions are located in the /src folder of the corresponding package. Test files for plugins and extensions are named index.spec.ts . There are helper functions for testing in /packages/jspsych/tests/utils.ts . We recommend looking at other test files to observe conventions for testing.","title":"Configuration"},{"location":"developers/configuration/#configuring-the-jspsych-development-environment","text":"","title":"Configuring the jsPsych development environment"},{"location":"developers/configuration/#setup","text":"JsPsych is written using TypeScript , a superset of JavaScript that adds static typing, but compiles to plain JavaScript. The TypeScript compiler itself is written in JavaScript and can be run by Node.js , a runtime to execute JavaScript code without a web browser. Node.js comes with a package manager called NPM (Node Package Manager) that can install JavaScript libraries to run on your machine, such as TypeScript and other build tools for jsPsych. In order to work on code in the jsPsych or the jspsych-contrib repository, it is recommended that you follow the steps below to set up your development environment.","title":"Setup"},{"location":"developers/configuration/#install-nodejs","text":"The jsPsych development setup requires Node.js >= v14 to be installed on your machine. We recommend that you install version 16 since it includes version 7 of NPM (required for the workspaces feature that the jsPsych repositories use). If you are bound to Node.js v14, make sure to install NPM v7 manually (via npm install -g npm@7 ).","title":"Install Node.js"},{"location":"developers/configuration/#clone-the-repository-and-install-the-dependencies","text":"Clone either the jsPsych repository or the jspsych-contrib repository by running git clone https://github.com/jspsych/jsPsych.git && cd jsPsych or git clone https://github.com/jspsych/jspsych-contrib.git && cd jspsych-contrib in a terminal. Then run npm install . This will create a node_modules directory and install all the dependencies into it that are required to build and test jsPsych. Attention It is important that npm install is only run in the root directory of the repository (due to the NPM workspaces feature). If you accidentally ran npm install anywhere else, remove the node_modules directory and the package-lock.json file that were created at that location and run npm install in the root directory again. Info If you are running npm install in the core jsPsych repository, this will also execute the build chain for all packages in the jsPsych repository. This step may take a few minutes. If you would like to use that time efficiently, consider reading the following two sections to know what's happening.","title":"Clone the repository and install the dependencies"},{"location":"developers/configuration/#repository-structure","text":"A Node.js package is a directory that contains a package.json file describing it. Most importantly, a package.json file lists other packages that the package depends on. The jsPsych and jspsych-contrib repositories use NPM workspaces . That means, running npm install in the repository root will install the dependencies for all packages in the packages directory. The core jsPsych library and every jsPsych plugin or extension is laid out as an individual package. These packages are published to the NPM registry where they can be downloaded by NPM or any CDN (such as unpkg ).","title":"Repository structure"},{"location":"developers/configuration/#build-chain-and-build-artifacts","text":"JsPsych comes with a build chain (specified in the @jspsych/config package) that can be executed by running npm run build in a package's directory. The build chain will read the package (starting at its src/index.ts file) and create the following build artifacts in the package's dist directory: index.js This file contains everything from index.ts , but as plain JavaScript and bundled in a single file (i.e. without import ing files from the same package). It is used by bundlers like webpack . index.cjs Like index.js , but using the old CommonJS standard to support backwards-compatible tools like the Jest testing framework. index.browser.js This file, like index.js , contains the entire package as plain JavaScript, but this time wrapped in a function so that it can be included directly by browsers using the <script> tag. For plugins or extensions, the default export of a module (i.e. whatever statement comes after export default in the index.ts file) is assigned to a global variable. The name of this global variable is specified in the package's rollup.config.mjs file, as a parameter to the makeRollupConfig() function. Hence, for instance, including the index.browser.js file from the plugin-html-keyboard-response package would assign the HtmlKeyboardResponsePlugin class to the global jsPsychHtmlKeyboardResponse variable. Because the code in index.browser.js looks very similar to the index.ts code but is fully supported by modern web browsers, all examples in the examples directory reference the index.browser.js files so users can also modify the source code directly without running the build chain. index.browser.min.js There are different versions of the JavaScript language specification and not all web browsers and browser versions support all JavaScript features. That's why the jsPsych build chain uses Babel to translate the source files into code that a majority of web browsers can understand. The result of this operation is index.browser.min.js . It behaves just like index.browser.js , but adds support for older browsers by substituting new JavaScript features using older ones. Because this is the recommended build artifact for production usage (and is automatically served by unpkg), the code in index.browser.min.js is also processed by Terser to reduce its size and speed up experiment loading times. *.js.map When debugging code in a browser (especially index.browser.min.js , which is not easily readable due to Terser and Babel), it is important to be able to read the original source code in the debugger. For every build artifact, there is a .map file which contains a mapping of the generated code to the original source code. Browsers automatically read these .map files and display the original code in their debuggers instead of the generated one. *.d.ts The .d.ts files contain the TypeScript type definitions that would otherwise be lost during compilation to plain JavaScript. They are read by Typescript and editors when a package is imported into another TypeScript project.","title":"Build chain and build artifacts"},{"location":"developers/configuration/#testing","text":"Automated code testing for jsPsych is implemented with Jest . To run the tests, install Node and npm. Run npm install in the root jsPsych directory. Then run npm test . You can also run npm test in the directory of the package that you would like to test. For example, if you are developing tests for the html-keyboard-response plugin you can run npm test in /packages/plugin-html-keyboard-response . If you want to run one file from the root directory, using the aforementioned example, you can run npm test -- /packages/plugin-html-keyboard-response/src/index.spec.ts . Tests for the core jsPsych library are located in /packages/jspsych/tests . Tests for plugins and extensions are located in the /src folder of the corresponding package. Test files for plugins and extensions are named index.spec.ts . There are helper functions for testing in /packages/jspsych/tests/utils.ts . We recommend looking at other test files to observe conventions for testing.","title":"Testing"},{"location":"developers/contributing/","text":"Contributing to jsPsych \u00b6 We welcome contributions of all kinds, including changes to the core codebase, the development of new plugins and extensions, and improvements to the documentation. The project is managed entirely through the GitHub repository . There you can: Use discussions to propose ideas for development and seek feedback on contributions, such as a new plugin. Use issues to identify anything with an actionable next step. For example, a page in the documentation that needs to be fixed, a bug in the code, or a specific feature that has a clear scope. Submit a pull request with modifications to the codebase. Pull requests will be reviewed by one or more members of the core team. Guidelines for contibuting \u00b6 Contributing to the codebase \u00b6 We welcome contributions of any scope. Before we can merge changes into the main codebase, we generally require a few things. Note that you are welcome to contribute code without these things in place, but it will help us get to your contribution faster if you take care of whatever components you are comfortable doing. The code must be tested through our automated testing system. We use Jest as the testing framework. If you are fixing a bug, consider adding a test case that shows the bug has been resolved. If you are contributing new features, like a new plugin, a test suite for the plugin is very helpful. See testing jsPsych for more information about configuring the test tools and writing tests. Relevant documentation must be updated. Any pages in /docs that are affected by the contribution should be updated, and if new pages are needed they should be created. For example, if you are contributing a plugin then adding documentation for the plugin and updating the list of available plugins as well as the mkdocs configuration file is very helpful! An example file should be included if applicable. If you are contributing a new feature, new plugin, or new extension, or contributing a modification that changes the behavior of the library in some important way, consider adding an example file to the /examples folder in the repository. A changeset must be included in the pull request . We use changesets to generate new releases and their corresponding release notes. This is a good overview of changesets that explains how to add one to your pull request. Feel free to ask for help with this! Update the contributors.md file . If you are a first time contributor to jsPsych please add your name to our contributors file . And thanks! Contributing to the documentation \u00b6 We are very appreciative of both small and large contributions to the documentation, from fixing a typo to adding a whole new tutorial. All of the documentation that appears on this site is contained in the /docs folder of the repository. The documentation is built using MkDocs and themed using Material for MkDocs . You can edit any of the markdown files and submit a pull request to modify documentation. If you'd like to test your changes to the documentation locally you'll need to install MkDocs and Material for MkDocs . Then you can run the command mike serve in the root folder of the repository to launch a local webserver and view the documentation. Contributing to jspsych vs. jspsych-contrib \u00b6 If you are developing a new plugin or extension there are two different repositories that you can contribute to: jspsych or jspsych-contrib . The main jspsych repository is open to new plugins and extensions that are likely to be widely used. We require that contributions to main repository are well documented and tested before they are merged. Contributions to the main repository must use TypeScript. We limit contributions to this repository because once a plugin or extension is in the main codebase we are generally committed to providing updates as we develop new versions of jsPsych. Each new plugin and extension potentially increases the amount of development work that we will need to do in the future, so we are somewhat selective about what we will merge. If you have an idea that you'd like to discuss please open a discussion thread and we'd love to chat about it! The jspsych-contrib repository is open to any contributions that are complete and working code. There are some minimal guidelines in place about basic documentation that should be provided. Contributors can choose whether to develop their plugin or extension using our TypeScript template or using our JavaScript template . Contributions to jspsych-contrib are not evaluated for general usefulness in the same way that contributions to the main repository are. We also periodically consider whether to move contributions into the main repository from jspsych-contrib based on their popularity and completeness (documentation and testing).","title":"Contributing to jsPsych"},{"location":"developers/contributing/#contributing-to-jspsych","text":"We welcome contributions of all kinds, including changes to the core codebase, the development of new plugins and extensions, and improvements to the documentation. The project is managed entirely through the GitHub repository . There you can: Use discussions to propose ideas for development and seek feedback on contributions, such as a new plugin. Use issues to identify anything with an actionable next step. For example, a page in the documentation that needs to be fixed, a bug in the code, or a specific feature that has a clear scope. Submit a pull request with modifications to the codebase. Pull requests will be reviewed by one or more members of the core team.","title":"Contributing to jsPsych"},{"location":"developers/contributing/#guidelines-for-contibuting","text":"","title":"Guidelines for contibuting"},{"location":"developers/contributing/#contributing-to-the-codebase","text":"We welcome contributions of any scope. Before we can merge changes into the main codebase, we generally require a few things. Note that you are welcome to contribute code without these things in place, but it will help us get to your contribution faster if you take care of whatever components you are comfortable doing. The code must be tested through our automated testing system. We use Jest as the testing framework. If you are fixing a bug, consider adding a test case that shows the bug has been resolved. If you are contributing new features, like a new plugin, a test suite for the plugin is very helpful. See testing jsPsych for more information about configuring the test tools and writing tests. Relevant documentation must be updated. Any pages in /docs that are affected by the contribution should be updated, and if new pages are needed they should be created. For example, if you are contributing a plugin then adding documentation for the plugin and updating the list of available plugins as well as the mkdocs configuration file is very helpful! An example file should be included if applicable. If you are contributing a new feature, new plugin, or new extension, or contributing a modification that changes the behavior of the library in some important way, consider adding an example file to the /examples folder in the repository. A changeset must be included in the pull request . We use changesets to generate new releases and their corresponding release notes. This is a good overview of changesets that explains how to add one to your pull request. Feel free to ask for help with this! Update the contributors.md file . If you are a first time contributor to jsPsych please add your name to our contributors file . And thanks!","title":"Contributing to the codebase"},{"location":"developers/contributing/#contributing-to-the-documentation","text":"We are very appreciative of both small and large contributions to the documentation, from fixing a typo to adding a whole new tutorial. All of the documentation that appears on this site is contained in the /docs folder of the repository. The documentation is built using MkDocs and themed using Material for MkDocs . You can edit any of the markdown files and submit a pull request to modify documentation. If you'd like to test your changes to the documentation locally you'll need to install MkDocs and Material for MkDocs . Then you can run the command mike serve in the root folder of the repository to launch a local webserver and view the documentation.","title":"Contributing to the documentation"},{"location":"developers/contributing/#contributing-to-jspsych-vs-jspsych-contrib","text":"If you are developing a new plugin or extension there are two different repositories that you can contribute to: jspsych or jspsych-contrib . The main jspsych repository is open to new plugins and extensions that are likely to be widely used. We require that contributions to main repository are well documented and tested before they are merged. Contributions to the main repository must use TypeScript. We limit contributions to this repository because once a plugin or extension is in the main codebase we are generally committed to providing updates as we develop new versions of jsPsych. Each new plugin and extension potentially increases the amount of development work that we will need to do in the future, so we are somewhat selective about what we will merge. If you have an idea that you'd like to discuss please open a discussion thread and we'd love to chat about it! The jspsych-contrib repository is open to any contributions that are complete and working code. There are some minimal guidelines in place about basic documentation that should be provided. Contributors can choose whether to develop their plugin or extension using our TypeScript template or using our JavaScript template . Contributions to jspsych-contrib are not evaluated for general usefulness in the same way that contributions to the main repository are. We also periodically consider whether to move contributions into the main repository from jspsych-contrib based on their popularity and completeness (documentation and testing).","title":"Contributing to jspsych vs. jspsych-contrib"},{"location":"developers/documentation/","text":"Building the jsPsych documentation \u00b6 The documentation hosted at https://www.jspsych.org is generated using mkdocs and the mkdocs-material theme . The documentation files are located in the /docs directory of the GitHub repository . The documentation is written using markdown. To build a local copy of the docs, you will need to install mkdocs , mkdocs-material , and mike using poetry . Install poetry \u00b6 Poetry is a package manager for python. Follow the install instructions on the poetry website to get it running. Install dev dependencies \u00b6 Run the command poetry install in the root directory of jsPsych to install mkdocs , mkdocs-material , and their dependencies. Building a local copy of the docs \u00b6 Run poetry run mike deploy [version] -u to build a new version of the documentation or to override an existing version. For example, if you are testing an edit to version 7.2 of the documentation, run poetry run mike deploy 7.2 -u . You can also use jsPsych's custom npm command: npm run docs:deploy [version] , e.g. npm run docs:deploy 7.2 . This will build the documentation and commit it directly to the gh-pages branch. We use mike instead of mkdocs for the build step to support versioning of the documentation. mike runs the mkdocs command under the hood. Viewing the local docs \u00b6 To launch a local webserver, run poetry run mike serve , or use jsPsych's custom npm command: npm run docs:serve . The docs will be viewable at http://localhost:8000 . Updating the public docs site \u00b6 For core maintainers only After the documentation has been built locally (and therefore committed to your local gh-pages branch), you can update the live documentation site by switching to your gh-pages branch and pushing to the remote gh-pages branch.","title":"Building the Documentation"},{"location":"developers/documentation/#building-the-jspsych-documentation","text":"The documentation hosted at https://www.jspsych.org is generated using mkdocs and the mkdocs-material theme . The documentation files are located in the /docs directory of the GitHub repository . The documentation is written using markdown. To build a local copy of the docs, you will need to install mkdocs , mkdocs-material , and mike using poetry .","title":"Building the jsPsych documentation"},{"location":"developers/documentation/#install-poetry","text":"Poetry is a package manager for python. Follow the install instructions on the poetry website to get it running.","title":"Install poetry"},{"location":"developers/documentation/#install-dev-dependencies","text":"Run the command poetry install in the root directory of jsPsych to install mkdocs , mkdocs-material , and their dependencies.","title":"Install dev dependencies"},{"location":"developers/documentation/#building-a-local-copy-of-the-docs","text":"Run poetry run mike deploy [version] -u to build a new version of the documentation or to override an existing version. For example, if you are testing an edit to version 7.2 of the documentation, run poetry run mike deploy 7.2 -u . You can also use jsPsych's custom npm command: npm run docs:deploy [version] , e.g. npm run docs:deploy 7.2 . This will build the documentation and commit it directly to the gh-pages branch. We use mike instead of mkdocs for the build step to support versioning of the documentation. mike runs the mkdocs command under the hood.","title":"Building a local copy of the docs"},{"location":"developers/documentation/#viewing-the-local-docs","text":"To launch a local webserver, run poetry run mike serve , or use jsPsych's custom npm command: npm run docs:serve . The docs will be viewable at http://localhost:8000 .","title":"Viewing the local docs"},{"location":"developers/documentation/#updating-the-public-docs-site","text":"For core maintainers only After the documentation has been built locally (and therefore committed to your local gh-pages branch), you can update the live documentation site by switching to your gh-pages branch and pushing to the remote gh-pages branch.","title":"Updating the public docs site"},{"location":"developers/extension-development/","text":"Extension development \u00b6 Requirements for an extension \u00b6 As of version 7.0, extensions are JavaScript Classes . An extension must implement: A constructor() that accepts an instance of jsPsych. An initialize() function to handle the initialize event of the extension. An on_start() function to handle the on_start event of the extension. An on_load() function to handle the on_load event of the extension. An on_finish() function to handle the on_finish event of the extension and store data that the extension collects. A static info property containing a unique name for the extension. Templates \u00b6 Plugins can be written in either plain JavaScript or in TypeScript. Template files for both JavaScript and TypeScript are available in the jspsych-contrib repository . Extension components \u00b6 constructor() \u00b6 The extension's constructor() will be passed a reference to the instance of the JsPsych class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules. class MyAwesomeExtension { constructor ( jsPsych ){ this . jsPsych = jsPsych ; } } initialize() \u00b6 The initialize() function is called when an instance of jsPsych is first initialized, either through initJsPsych() or new JsPsych() . This is where setup code for the extension should be run. This event will happen once per experiment, unlike the other events which occur with each trial. The params object can include whatever parameters are necessary to configure the extension. The params object is passed from the call to initJsPsych() to initialize() method. initialize() must return a Promise that resolves when the extension is finished initializing. //... experiment code ...// let jsPsych = initJsPsych ({ extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ return new Promise (( resolve , reject )=>{ console . log ( params . demo ); // will output 'value' resolve (); // finish initialzing }) } } on_start() \u00b6 on_start() is called at the start of the plugin execution, prior to calling plugin.trial . This is where trial-specific initialization can happen, such as creating empty containers to hold data or resetting internal state. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ console . log ( params . demo ); // outputs 'value' before the trial begins. } } on_load() \u00b6 on_load() is called after the on_load event for the plugin has completed, which is typically when the plugin has finished executing initial DOM-modifying code and has set up various event listeners. This is where the extension can begin actively interacting with the DOM and recording data. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ ... } on_load ( params ){ // replaces the contents of the display with 'value'; this . jsPsych . getDisplayElement (). innerHTML = params . demo ; } } on_finish() \u00b6 on_finish() is called after the plugin invokes jsPsych.finishTrial() . This can be used for any teardown at the end of the trial. This method should return an object of data to append to the plugin's data. Note that this event fires before the on_finish event for the plugin, so data added by the extension is accessible in any trial on_finish event handlers. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ], on_finish : ( data ) => { console . log ( data . awesome ); // will output 'value'. } }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ ... } on_load ( params ){ ... } on_finish ( params ){ return { awesome : params . value } } } static .info \u00b6 The info property for the class must contain an object with a name property that has a unique name for the extension. class MyAwesomeExtension { } MyAwesomeExtension . info = { name : 'awesome' } Optional methods \u00b6 The extension can also include any additional methods that are necessary for interacting with it. See the webgazer extension for an example. Advice for writing extensions \u00b6 If you are developing an extension with the aim of including it in the main jsPsych repository we encourage you to follow the contribution guidelines . In general, extensions should be able to work with any plugin. They should make very few assumptions about what the DOM will contain beyond the container elements generated by jsPsych. If you are making an extension targeted at one or a small number of specific plugins, consider modifying the plugin code instead.","title":"Extension Development"},{"location":"developers/extension-development/#extension-development","text":"","title":"Extension development"},{"location":"developers/extension-development/#requirements-for-an-extension","text":"As of version 7.0, extensions are JavaScript Classes . An extension must implement: A constructor() that accepts an instance of jsPsych. An initialize() function to handle the initialize event of the extension. An on_start() function to handle the on_start event of the extension. An on_load() function to handle the on_load event of the extension. An on_finish() function to handle the on_finish event of the extension and store data that the extension collects. A static info property containing a unique name for the extension.","title":"Requirements for an extension"},{"location":"developers/extension-development/#templates","text":"Plugins can be written in either plain JavaScript or in TypeScript. Template files for both JavaScript and TypeScript are available in the jspsych-contrib repository .","title":"Templates"},{"location":"developers/extension-development/#extension-components","text":"","title":"Extension components"},{"location":"developers/extension-development/#constructor","text":"The extension's constructor() will be passed a reference to the instance of the JsPsych class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules. class MyAwesomeExtension { constructor ( jsPsych ){ this . jsPsych = jsPsych ; } }","title":"constructor()"},{"location":"developers/extension-development/#initialize","text":"The initialize() function is called when an instance of jsPsych is first initialized, either through initJsPsych() or new JsPsych() . This is where setup code for the extension should be run. This event will happen once per experiment, unlike the other events which occur with each trial. The params object can include whatever parameters are necessary to configure the extension. The params object is passed from the call to initJsPsych() to initialize() method. initialize() must return a Promise that resolves when the extension is finished initializing. //... experiment code ...// let jsPsych = initJsPsych ({ extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ return new Promise (( resolve , reject )=>{ console . log ( params . demo ); // will output 'value' resolve (); // finish initialzing }) } }","title":"initialize()"},{"location":"developers/extension-development/#on_start","text":"on_start() is called at the start of the plugin execution, prior to calling plugin.trial . This is where trial-specific initialization can happen, such as creating empty containers to hold data or resetting internal state. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ console . log ( params . demo ); // outputs 'value' before the trial begins. } }","title":"on_start()"},{"location":"developers/extension-development/#on_load","text":"on_load() is called after the on_load event for the plugin has completed, which is typically when the plugin has finished executing initial DOM-modifying code and has set up various event listeners. This is where the extension can begin actively interacting with the DOM and recording data. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ ... } on_load ( params ){ // replaces the contents of the display with 'value'; this . jsPsych . getDisplayElement (). innerHTML = params . demo ; } }","title":"on_load()"},{"location":"developers/extension-development/#on_finish","text":"on_finish() is called after the plugin invokes jsPsych.finishTrial() . This can be used for any teardown at the end of the trial. This method should return an object of data to append to the plugin's data. Note that this event fires before the on_finish event for the plugin, so data added by the extension is accessible in any trial on_finish event handlers. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ], on_finish : ( data ) => { console . log ( data . awesome ); // will output 'value'. } }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ ... } on_load ( params ){ ... } on_finish ( params ){ return { awesome : params . value } } }","title":"on_finish()"},{"location":"developers/extension-development/#static-info","text":"The info property for the class must contain an object with a name property that has a unique name for the extension. class MyAwesomeExtension { } MyAwesomeExtension . info = { name : 'awesome' }","title":"static .info"},{"location":"developers/extension-development/#optional-methods","text":"The extension can also include any additional methods that are necessary for interacting with it. See the webgazer extension for an example.","title":"Optional methods"},{"location":"developers/extension-development/#advice-for-writing-extensions","text":"If you are developing an extension with the aim of including it in the main jsPsych repository we encourage you to follow the contribution guidelines . In general, extensions should be able to work with any plugin. They should make very few assumptions about what the DOM will contain beyond the container elements generated by jsPsych. If you are making an extension targeted at one or a small number of specific plugins, consider modifying the plugin code instead.","title":"Advice for writing extensions"},{"location":"developers/plugin-development/","text":"Plugin development \u00b6 Requirements for a plugin \u00b6 As of version 7.0, plugins are JavaScript Classes . A plugin must implement: A constructor() that accepts an instance of jsPsych. A trial() method that accepts an HTMLElement as its first argument and an object of trial parameters as its second argument. There is an optional third argument to handle the on_load event in certain cirumstances. The trial() method should invoke jsPsych.finishTrial() to end the trial and save data at the appropriate moment. A static info property on the class that contains an object describing the plugin's parameters. Templates \u00b6 Plugins can be written in either plain JavaScript or in TypeScript. Template files for both JavaScript and TypeScript are available in the jspsych-contrib repository . Plugin components \u00b6 constructor() \u00b6 The plugin's constructor() will be passed a reference to the instance of the JsPsych class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules. constructor ( jsPsych ){ this . jsPsych = jsPsych ; } trial() \u00b6 The plugin's trial() method is responsible for running a single trial. When the jsPsych timeline reaches a trial using the plugin it will invoke the trial() method for the plugin. There are three parameters that are passed into the trial method. display_element is the DOM element where jsPsych content is being rendered. This parameter will be an HTMLElement , and you can use it to modify the portion of the document that jsPsych controls. trial is an object containing all of the parameters specified in the corresponding TimelineNode . on_load is an optional parameter that contains a callback function to invoke when trial() has completed its initial loading. See handling the on_load event . The only requirement for the trial method is that it calls jsPsych.finishTrial() when it is done. This is how jsPsych knows to advance to the next trial in the experiment (or end the experiment if it is the last trial). The plugin can do whatever it needs to do before that point. static info \u00b6 The plugin's info property is an object with a name and parameters property. const info = { name : 'my-awesome-plugin' , parameters : { } } The parameters property is an object containing all of the parameters for the plugin. Each parameter has a type and default property. const info = { name : 'my-awesome-plugin' , parameters : { image : { type : jspsych . ParameterType . IMAGE , default : undefined }, image_duration : { type : jspsych . ParameterType . INT , default : 500 } } } If the default value is undefined then a user must specify a value for this parameter when creating a trial using the plugin on the timeline. If they do not, then an error will be generated and shown in the console. If a default value is specified in info then that value will be used by the plugin unless the user overrides it by specifying that property. jsPsych allows most plugin parameters to be dynamic , which means that the parameter value can be a function that will be evaluated right before the trial starts. However, if you want your plugin to have a parameter that is a function that shouldn't be evaluated before the trial starts, then you should make sure that the parameter type is 'FUNCTION' . This tells jsPsych not to evaluate the function as it normally does for dynamic parameters. See the canvas-* plugins for examples. The info object should be a static member of the class, as shown below. const info = { name : 'my-awesome-plugin' , parameters : { image : { type : jspsych . ParameterType . IMAGE , default : undefined }, image_duration : { type : jspsych . ParameterType . INT , default : 500 } } } class MyAwesomePlugin { constructor (...) trial (...) } MyAwesomePlugin . info = info ; Plugin functionality \u00b6 Inside the .trial() method you can do pretty much anything that you want, including modifying the DOM, setting up event listeners, and making asynchronous requests. In this section we'll highlight a few common things that you might want to do as examples. Changing the content of the display \u00b6 There are a few ways to change the content of the display. The display_element parameter of the trial method contains the HTMLElement for displaying jsPsych content, so you can use various JavaScript methods for interaction with the display element. A common one is to change the innerHTML . Here's an example of using innerHTML to display an image specified in the trial parameters. trial ( display_element , trial ){ let html_content = `<img src=\" ${ trial . image } \"></img>` ; display_element . innerHTML = html_content ; } jsPsych doesn't clear the display before or after each trial, so it is usually appropriate to use innerHTML to clear the display at the end of a trial. display_element . innerHTML = '' ; Waiting for specified durations \u00b6 If you need to delay code execution for a fixed amount of time, we recommend using jsPsych's wrapper of the setTimeout() function, jsPsych.pluginAPI.setTimeout() . In 7.0 the only advantage of using this method is that it registers the timeout handler so that it can be easily cleared at the end of the trial using jsPsych.pluginAPI.clearAllTimeouts() . In future versions we may replace the implementation of jsPsych.pluginAPI.setTimeout() with improved timing functionality based on requestAnimationFrame . trial ( display_element , trial ){ // show image display_element . innerHTML = `<img src=\" ${ trial . image } \"></img>` ; // hide image after trial.image_duration milliseconds this . jsPsych . pluginAPI . setTimeout (()=>{ display_element . innerHTML = '' ; }, trial . image_duration ); } Responding to keyboard events \u00b6 While the plugin framework allows you to set up any events that you would like to, including normal handling of keyup or keydown events, the jsPsych.pluginAPI module contains the getKeyboardResponse function , which implements some additional helpful functionality for key responses in an experiment. Here's a basic example. See the getKeyboardResponse docs for additional examples. trial ( display_element , trial ){ // show image display_element . innerHTML = `<img src=\" ${ trial . image } \"></img>` ; const after_key_response = ( info ) => { // hide the image display_element . innerHTML = '' ; // record the response time as data let data = { rt : info . rt } // end the trial this . jsPsych . finishTrial ( data ); } // set up a keyboard event to respond only to the spacebar this . jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_key_response , valid_responses : [ ' ' ], persist : false }); } Asynchronous loading \u00b6 One of the trial events is on_load , which is normally triggered automatically when the .trial() method returns. In most cases, this return happens after the plugin has done its initial setup of the DOM (e.g., rendering an image, setting up event listeners and timers, etc.). However, in some cases a plugin may implement an asynchronous operation that needs to complete before the initial loading of the plugin is considered done. An example of this is the audio-keyboard-response plugin, in which the check to see if the audio file is loaded is asynchronous and the .trial() method returns before the audio file has been initialized and the display updated. If you would like to manually trigger the on_load event for a plugin, the .trial() method accepts an optional third parameter that is a callback function to invoke when loading is complete. In order to tell jsPsych to not invoke the regular callback when the .trial() method returns, you need to explicitly return a Promise . As of version 7.0 this Promise only serves as a flag to tell jsPsych that the on_load event should not be triggered. In future versions we may make the Promise functional so that the trial operation can be an async function. Here's a sketch of how the on_load event can be utilized in a plugin. Note that this example is only a sketch and leaves out all the stuff that happens between loading and finishing the trial. See the source for the audio-keyboard-response plugin for a complete exampe. trial ( display_element , trial , on_load ){ let trial_complete ; do_something_asynchronous (). then (()=>{ on_load (); }); const end_trial = () => { this . jsPsych . finishTrial ({...}) trial_complete (); // not strictly necessary, but doesn't hurt. } return new Promise (( resolve )=>{ trial_complete = resolve ; }) } Save data \u00b6 To write data to jsPsych's data collection pass an object of data as the parameter to jsPsych.finishTrial() . constructor ( jsPsych ){ this . jsPsych = jsPsych ; } trial ( display_element , trial ){ let data = { correct : true , rt : 350 } this . jsPsych . finishTrial ( data ); } The data recorded will be that correct is true and that rt is 350 . Additional data for the trial will also be collected automatically. Simulation mode \u00b6 Plugins can optionally support simulation modes . To add simulation support, a plugin needs a simulate() function that accepts four arguments simulate(trial, simulation_mode, simulation_options, load_callback) trial : This is the same as the trial parameter passed to the plugin's trial() method. It contains an object of the parameters for the trial. simulation_mode : A string, either \"data-only\" or \"visual\" . This specifies which simulation mode is being requested. Plugins can optionally support \"visual\" mode. If \"visual\" mode is not supported, the plugin should default to \"data-only\" mode when \"visual\" mode is requested. simulation_options : An object of simulation-specific options. load_callback : A function handle to invoke when the simulation is ready to trigger the on_load event for the trial. It is important to invoke this at the correct time during the simulation so that any on_load events in the experiment execute as expected. Typically the flow for supporting simulation mode involves: Generating artificial data that is consistent with the trial parameters. Merging that data with any data specified by the user in simulation_options . Verifying that the final data object is still consistent with the trial parameters. For example, checking that RTs are not longer than the duration of the trial. In data-only mode, call jsPsych.finishTrial() with the artificial data. In visual mode, invoke the trial() method of the plugin and then use the artificial data to trigger the appropriate events. There are a variety of methods in the Plugin API module to assist with things like simulating key presses and mouse clicks. We plan to add a longer guide about simulation development in the future. For now, we recommend browsing the source code of plugins that support simulation mode to see how the flow described above is implemented. Advice for writing plugins \u00b6 If you are developing a plugin with the aim of including it in the main jsPsych repository we encourage you to follow the contribution guidelines . We also recommend that you make your plugin as general as possible . Consider using parameters to give the user of the plugin as many options for customization as possible. For example, if you have any text that displays in the plugin including things like button labels, implement the text as a parameter. This allows users running experiments in other languages to replace text values as needed.","title":"Plugin Development"},{"location":"developers/plugin-development/#plugin-development","text":"","title":"Plugin development"},{"location":"developers/plugin-development/#requirements-for-a-plugin","text":"As of version 7.0, plugins are JavaScript Classes . A plugin must implement: A constructor() that accepts an instance of jsPsych. A trial() method that accepts an HTMLElement as its first argument and an object of trial parameters as its second argument. There is an optional third argument to handle the on_load event in certain cirumstances. The trial() method should invoke jsPsych.finishTrial() to end the trial and save data at the appropriate moment. A static info property on the class that contains an object describing the plugin's parameters.","title":"Requirements for a plugin"},{"location":"developers/plugin-development/#templates","text":"Plugins can be written in either plain JavaScript or in TypeScript. Template files for both JavaScript and TypeScript are available in the jspsych-contrib repository .","title":"Templates"},{"location":"developers/plugin-development/#plugin-components","text":"","title":"Plugin components"},{"location":"developers/plugin-development/#constructor","text":"The plugin's constructor() will be passed a reference to the instance of the JsPsych class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules. constructor ( jsPsych ){ this . jsPsych = jsPsych ; }","title":"constructor()"},{"location":"developers/plugin-development/#trial","text":"The plugin's trial() method is responsible for running a single trial. When the jsPsych timeline reaches a trial using the plugin it will invoke the trial() method for the plugin. There are three parameters that are passed into the trial method. display_element is the DOM element where jsPsych content is being rendered. This parameter will be an HTMLElement , and you can use it to modify the portion of the document that jsPsych controls. trial is an object containing all of the parameters specified in the corresponding TimelineNode . on_load is an optional parameter that contains a callback function to invoke when trial() has completed its initial loading. See handling the on_load event . The only requirement for the trial method is that it calls jsPsych.finishTrial() when it is done. This is how jsPsych knows to advance to the next trial in the experiment (or end the experiment if it is the last trial). The plugin can do whatever it needs to do before that point.","title":"trial()"},{"location":"developers/plugin-development/#static-info","text":"The plugin's info property is an object with a name and parameters property. const info = { name : 'my-awesome-plugin' , parameters : { } } The parameters property is an object containing all of the parameters for the plugin. Each parameter has a type and default property. const info = { name : 'my-awesome-plugin' , parameters : { image : { type : jspsych . ParameterType . IMAGE , default : undefined }, image_duration : { type : jspsych . ParameterType . INT , default : 500 } } } If the default value is undefined then a user must specify a value for this parameter when creating a trial using the plugin on the timeline. If they do not, then an error will be generated and shown in the console. If a default value is specified in info then that value will be used by the plugin unless the user overrides it by specifying that property. jsPsych allows most plugin parameters to be dynamic , which means that the parameter value can be a function that will be evaluated right before the trial starts. However, if you want your plugin to have a parameter that is a function that shouldn't be evaluated before the trial starts, then you should make sure that the parameter type is 'FUNCTION' . This tells jsPsych not to evaluate the function as it normally does for dynamic parameters. See the canvas-* plugins for examples. The info object should be a static member of the class, as shown below. const info = { name : 'my-awesome-plugin' , parameters : { image : { type : jspsych . ParameterType . IMAGE , default : undefined }, image_duration : { type : jspsych . ParameterType . INT , default : 500 } } } class MyAwesomePlugin { constructor (...) trial (...) } MyAwesomePlugin . info = info ;","title":"static info"},{"location":"developers/plugin-development/#plugin-functionality","text":"Inside the .trial() method you can do pretty much anything that you want, including modifying the DOM, setting up event listeners, and making asynchronous requests. In this section we'll highlight a few common things that you might want to do as examples.","title":"Plugin functionality"},{"location":"developers/plugin-development/#changing-the-content-of-the-display","text":"There are a few ways to change the content of the display. The display_element parameter of the trial method contains the HTMLElement for displaying jsPsych content, so you can use various JavaScript methods for interaction with the display element. A common one is to change the innerHTML . Here's an example of using innerHTML to display an image specified in the trial parameters. trial ( display_element , trial ){ let html_content = `<img src=\" ${ trial . image } \"></img>` ; display_element . innerHTML = html_content ; } jsPsych doesn't clear the display before or after each trial, so it is usually appropriate to use innerHTML to clear the display at the end of a trial. display_element . innerHTML = '' ;","title":"Changing the content of the display"},{"location":"developers/plugin-development/#waiting-for-specified-durations","text":"If you need to delay code execution for a fixed amount of time, we recommend using jsPsych's wrapper of the setTimeout() function, jsPsych.pluginAPI.setTimeout() . In 7.0 the only advantage of using this method is that it registers the timeout handler so that it can be easily cleared at the end of the trial using jsPsych.pluginAPI.clearAllTimeouts() . In future versions we may replace the implementation of jsPsych.pluginAPI.setTimeout() with improved timing functionality based on requestAnimationFrame . trial ( display_element , trial ){ // show image display_element . innerHTML = `<img src=\" ${ trial . image } \"></img>` ; // hide image after trial.image_duration milliseconds this . jsPsych . pluginAPI . setTimeout (()=>{ display_element . innerHTML = '' ; }, trial . image_duration ); }","title":"Waiting for specified durations"},{"location":"developers/plugin-development/#responding-to-keyboard-events","text":"While the plugin framework allows you to set up any events that you would like to, including normal handling of keyup or keydown events, the jsPsych.pluginAPI module contains the getKeyboardResponse function , which implements some additional helpful functionality for key responses in an experiment. Here's a basic example. See the getKeyboardResponse docs for additional examples. trial ( display_element , trial ){ // show image display_element . innerHTML = `<img src=\" ${ trial . image } \"></img>` ; const after_key_response = ( info ) => { // hide the image display_element . innerHTML = '' ; // record the response time as data let data = { rt : info . rt } // end the trial this . jsPsych . finishTrial ( data ); } // set up a keyboard event to respond only to the spacebar this . jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_key_response , valid_responses : [ ' ' ], persist : false }); }","title":"Responding to keyboard events"},{"location":"developers/plugin-development/#asynchronous-loading","text":"One of the trial events is on_load , which is normally triggered automatically when the .trial() method returns. In most cases, this return happens after the plugin has done its initial setup of the DOM (e.g., rendering an image, setting up event listeners and timers, etc.). However, in some cases a plugin may implement an asynchronous operation that needs to complete before the initial loading of the plugin is considered done. An example of this is the audio-keyboard-response plugin, in which the check to see if the audio file is loaded is asynchronous and the .trial() method returns before the audio file has been initialized and the display updated. If you would like to manually trigger the on_load event for a plugin, the .trial() method accepts an optional third parameter that is a callback function to invoke when loading is complete. In order to tell jsPsych to not invoke the regular callback when the .trial() method returns, you need to explicitly return a Promise . As of version 7.0 this Promise only serves as a flag to tell jsPsych that the on_load event should not be triggered. In future versions we may make the Promise functional so that the trial operation can be an async function. Here's a sketch of how the on_load event can be utilized in a plugin. Note that this example is only a sketch and leaves out all the stuff that happens between loading and finishing the trial. See the source for the audio-keyboard-response plugin for a complete exampe. trial ( display_element , trial , on_load ){ let trial_complete ; do_something_asynchronous (). then (()=>{ on_load (); }); const end_trial = () => { this . jsPsych . finishTrial ({...}) trial_complete (); // not strictly necessary, but doesn't hurt. } return new Promise (( resolve )=>{ trial_complete = resolve ; }) }","title":"Asynchronous loading"},{"location":"developers/plugin-development/#save-data","text":"To write data to jsPsych's data collection pass an object of data as the parameter to jsPsych.finishTrial() . constructor ( jsPsych ){ this . jsPsych = jsPsych ; } trial ( display_element , trial ){ let data = { correct : true , rt : 350 } this . jsPsych . finishTrial ( data ); } The data recorded will be that correct is true and that rt is 350 . Additional data for the trial will also be collected automatically.","title":"Save data"},{"location":"developers/plugin-development/#simulation-mode","text":"Plugins can optionally support simulation modes . To add simulation support, a plugin needs a simulate() function that accepts four arguments simulate(trial, simulation_mode, simulation_options, load_callback) trial : This is the same as the trial parameter passed to the plugin's trial() method. It contains an object of the parameters for the trial. simulation_mode : A string, either \"data-only\" or \"visual\" . This specifies which simulation mode is being requested. Plugins can optionally support \"visual\" mode. If \"visual\" mode is not supported, the plugin should default to \"data-only\" mode when \"visual\" mode is requested. simulation_options : An object of simulation-specific options. load_callback : A function handle to invoke when the simulation is ready to trigger the on_load event for the trial. It is important to invoke this at the correct time during the simulation so that any on_load events in the experiment execute as expected. Typically the flow for supporting simulation mode involves: Generating artificial data that is consistent with the trial parameters. Merging that data with any data specified by the user in simulation_options . Verifying that the final data object is still consistent with the trial parameters. For example, checking that RTs are not longer than the duration of the trial. In data-only mode, call jsPsych.finishTrial() with the artificial data. In visual mode, invoke the trial() method of the plugin and then use the artificial data to trigger the appropriate events. There are a variety of methods in the Plugin API module to assist with things like simulating key presses and mouse clicks. We plan to add a longer guide about simulation development in the future. For now, we recommend browsing the source code of plugins that support simulation mode to see how the flow described above is implemented.","title":"Simulation mode"},{"location":"developers/plugin-development/#advice-for-writing-plugins","text":"If you are developing a plugin with the aim of including it in the main jsPsych repository we encourage you to follow the contribution guidelines . We also recommend that you make your plugin as general as possible . Consider using parameters to give the user of the plugin as many options for customization as possible. For example, if you have any text that displays in the plugin including things like button labels, implement the text as a parameter. This allows users running experiments in other languages to replace text values as needed.","title":"Advice for writing plugins"},{"location":"extensions/list-of-extensions/","text":"List of Plugins \u00b6 These are the extensions that are included in the jsPsych release. Additional extensions may be available in the community contributions repository . For an overview of what extensions are and how they work, see our extensions overview . Extension Description mouse\u2011tracking Enables tracking of mouse events and recording location of objects on screen. record\u2011video Record video data from the participant's webcam during a trial. webgazer Enables eye tracking using the WebGazer library.","title":"List of Extensions"},{"location":"extensions/list-of-extensions/#list-of-plugins","text":"These are the extensions that are included in the jsPsych release. Additional extensions may be available in the community contributions repository . For an overview of what extensions are and how they work, see our extensions overview . Extension Description mouse\u2011tracking Enables tracking of mouse events and recording location of objects on screen. record\u2011video Record video data from the participant's webcam during a trial. webgazer Enables eye tracking using the WebGazer library.","title":"List of Plugins"},{"location":"extensions/mouse-tracking/","text":"mouse-tracking \u00b6 This extension supports mouse tracking. Specifically, it can record the x and y coordinates, along with the time of mousemove events , mousedown events , and mouseup events . It also allows recording of the bounding rectangle of elements on the screen to support the calculation of mouse events relative to different elements. Parameters \u00b6 Initialization Parameters \u00b6 Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionMouseTracking , params : {...}} ] }) Parameter Type Default Value Description minimum_sample_time number 0 The minimum time between samples for mousemove events in milliseconds. If mousemove events occur more rapidly than this limit, they will not be recorded. Use this if you want to keep the data files smaller and don't need high resolution tracking data. The default value of 0 means that all events will be recorded. Trial Parameters \u00b6 Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionMouseTracking , params : {...}} ] } Parameter Type Default Value Description targets array [] A list of elements on the page that you would like to record the coordinates of for comparison with the mouse tracking data. Each entry in the array should be a valid CSS selector string that identifies the element. The selector string should be valid for exactly one element on the page. If the selector is valid for more than one element then only the first matching element will be recorded. events array ['mousemove'] A list of events to track. Can include 'mousemove', 'mousedown', and 'mouseup'. Data Generated \u00b6 Name Type Value mouse_tracking_data array An array of objects containing mouse movement data for the trial. Each object has an x , a y , a t , and an event property. The x and y properties specify the mouse coordinates in pixels relative to the top left corner of the viewport and t specifies the time in milliseconds since the start of the trial. The event will be either 'mousemove', 'mousedown', or 'mouseup' depending on which event was generated. mouse_tracking_targets object An object contain the pixel coordinates of elements on the screen specified by the .targets parameter. Each key in this object will be a selector property, containing the CSS selector string used to find the element. The object corresponding to each key will contain x and y properties specifying the top-left corner of the object, width and height values, plus top , bottom , left , and right parameters which specify the bounding rectangle of the element. Examples \u00b6 Record mouse movement data and play it back Code Demo var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; margin: auto;\"></div>' , choices : [ 'Done' ], prompt : \"<p>Move your mouse around inside the square.</p>\" , extensions : [ { type : jsPsychExtensionMouseTracking , params : { targets : [ '#target' ]}} ], data : { task : 'draw' } }; var replay = { type : jsPsychHtmlButtonResponse , stimulus : '<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; margin: auto; position: relative;\"></div>' , choices : [ 'Done' ], prompt : \"<p>Here's the recording of your mouse movements</p>\" , on_load : function (){ var mouseMovements = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. mouse_tracking_data ; var targetRect = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. mouse_tracking_targets [ '#target' ]; var startTime = performance . now (); function draw_frame () { var timeElapsed = performance . now () - startTime ; var points = mouseMovements . filter (( x ) => x . t <= timeElapsed ); var html = `` ; for ( var p of points ){ html += `<div style=\"width: 3px; height: 3px; background-color: blue; position: absolute; top: ${ p . y - 1 - targetRect . top } px; left: ${ p . x - 1 - targetRect . left } px;\"></div>` } document . querySelector ( '#target' ). innerHTML = html ; if ( points . length < mouseMovements . length ) { requestAnimationFrame ( draw_frame ); } } requestAnimationFrame ( draw_frame ); }, data : { task : 'replay' } } Open demo in new tab","title":"mouse-tracking"},{"location":"extensions/mouse-tracking/#mouse-tracking","text":"This extension supports mouse tracking. Specifically, it can record the x and y coordinates, along with the time of mousemove events , mousedown events , and mouseup events . It also allows recording of the bounding rectangle of elements on the screen to support the calculation of mouse events relative to different elements.","title":"mouse-tracking"},{"location":"extensions/mouse-tracking/#parameters","text":"","title":"Parameters"},{"location":"extensions/mouse-tracking/#initialization-parameters","text":"Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionMouseTracking , params : {...}} ] }) Parameter Type Default Value Description minimum_sample_time number 0 The minimum time between samples for mousemove events in milliseconds. If mousemove events occur more rapidly than this limit, they will not be recorded. Use this if you want to keep the data files smaller and don't need high resolution tracking data. The default value of 0 means that all events will be recorded.","title":"Initialization Parameters"},{"location":"extensions/mouse-tracking/#trial-parameters","text":"Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionMouseTracking , params : {...}} ] } Parameter Type Default Value Description targets array [] A list of elements on the page that you would like to record the coordinates of for comparison with the mouse tracking data. Each entry in the array should be a valid CSS selector string that identifies the element. The selector string should be valid for exactly one element on the page. If the selector is valid for more than one element then only the first matching element will be recorded. events array ['mousemove'] A list of events to track. Can include 'mousemove', 'mousedown', and 'mouseup'.","title":"Trial Parameters"},{"location":"extensions/mouse-tracking/#data-generated","text":"Name Type Value mouse_tracking_data array An array of objects containing mouse movement data for the trial. Each object has an x , a y , a t , and an event property. The x and y properties specify the mouse coordinates in pixels relative to the top left corner of the viewport and t specifies the time in milliseconds since the start of the trial. The event will be either 'mousemove', 'mousedown', or 'mouseup' depending on which event was generated. mouse_tracking_targets object An object contain the pixel coordinates of elements on the screen specified by the .targets parameter. Each key in this object will be a selector property, containing the CSS selector string used to find the element. The object corresponding to each key will contain x and y properties specifying the top-left corner of the object, width and height values, plus top , bottom , left , and right parameters which specify the bounding rectangle of the element.","title":"Data Generated"},{"location":"extensions/mouse-tracking/#examples","text":"Record mouse movement data and play it back Code Demo var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; margin: auto;\"></div>' , choices : [ 'Done' ], prompt : \"<p>Move your mouse around inside the square.</p>\" , extensions : [ { type : jsPsychExtensionMouseTracking , params : { targets : [ '#target' ]}} ], data : { task : 'draw' } }; var replay = { type : jsPsychHtmlButtonResponse , stimulus : '<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; margin: auto; position: relative;\"></div>' , choices : [ 'Done' ], prompt : \"<p>Here's the recording of your mouse movements</p>\" , on_load : function (){ var mouseMovements = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. mouse_tracking_data ; var targetRect = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. mouse_tracking_targets [ '#target' ]; var startTime = performance . now (); function draw_frame () { var timeElapsed = performance . now () - startTime ; var points = mouseMovements . filter (( x ) => x . t <= timeElapsed ); var html = `` ; for ( var p of points ){ html += `<div style=\"width: 3px; height: 3px; background-color: blue; position: absolute; top: ${ p . y - 1 - targetRect . top } px; left: ${ p . x - 1 - targetRect . left } px;\"></div>` } document . querySelector ( '#target' ). innerHTML = html ; if ( points . length < mouseMovements . length ) { requestAnimationFrame ( draw_frame ); } } requestAnimationFrame ( draw_frame ); }, data : { task : 'replay' } } Open demo in new tab","title":"Examples"},{"location":"extensions/record-video/","text":"record-video \u00b6 This extension records video from the participant's webcam during a trial. This extension encodes the video data in base 64 format . This is a text-based representation of the video which can be coverted to various video formats using a variety of online tools as well as in languages like python and R. Parameters \u00b6 Initialization Parameters \u00b6 Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionRecordVideo , params : {...}} ] }) Parameter Type Default Value Description None Trial Parameters \u00b6 Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionRecordVideo , params : {...}} ] } Parameter Type Default Value Description None Data Generated \u00b6 Name Type Value record_video_data base64 string Base 64 encoded representation of the video data. Examples \u00b6 Record video data during a trial Code Demo const init_camera = { type : jsPsychInitializeCamera }; const trial = { type : jsPsychHtmlButtonResponse , stimulus : `<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; position: relative; margin: 2em auto;\"> <div class=\"orbit\" style=\"width:25px; height:25px; border-radius:25px;background-color: #f00; position: absolute; top:calc(50% - 12px); left:calc(50% - 12px);\"></div> </div> <style> .orbit { transform: translateX(100px); animation: orbit 4s infinite; } @keyframes orbit { 0% { transform: rotate(0deg) translateX(100px); } 100% { transform: rotate(360deg) translateX(100px); } } </style>` , choices : [ 'Done' ], prompt : \"<p>Video is recording. Click done after a few seconds.</p>\" , extensions : [ { type : jsPsychExtensionRecordVideo } ] }; Open demo in new tab","title":"record-video"},{"location":"extensions/record-video/#record-video","text":"This extension records video from the participant's webcam during a trial. This extension encodes the video data in base 64 format . This is a text-based representation of the video which can be coverted to various video formats using a variety of online tools as well as in languages like python and R.","title":"record-video"},{"location":"extensions/record-video/#parameters","text":"","title":"Parameters"},{"location":"extensions/record-video/#initialization-parameters","text":"Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionRecordVideo , params : {...}} ] }) Parameter Type Default Value Description None","title":"Initialization Parameters"},{"location":"extensions/record-video/#trial-parameters","text":"Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionRecordVideo , params : {...}} ] } Parameter Type Default Value Description None","title":"Trial Parameters"},{"location":"extensions/record-video/#data-generated","text":"Name Type Value record_video_data base64 string Base 64 encoded representation of the video data.","title":"Data Generated"},{"location":"extensions/record-video/#examples","text":"Record video data during a trial Code Demo const init_camera = { type : jsPsychInitializeCamera }; const trial = { type : jsPsychHtmlButtonResponse , stimulus : `<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; position: relative; margin: 2em auto;\"> <div class=\"orbit\" style=\"width:25px; height:25px; border-radius:25px;background-color: #f00; position: absolute; top:calc(50% - 12px); left:calc(50% - 12px);\"></div> </div> <style> .orbit { transform: translateX(100px); animation: orbit 4s infinite; } @keyframes orbit { 0% { transform: rotate(0deg) translateX(100px); } 100% { transform: rotate(360deg) translateX(100px); } } </style>` , choices : [ 'Done' ], prompt : \"<p>Video is recording. Click done after a few seconds.</p>\" , extensions : [ { type : jsPsychExtensionRecordVideo } ] }; Open demo in new tab","title":"Examples"},{"location":"extensions/webgazer/","text":"webgazer \u00b6 This extension supports eye tracking through the WebGazer library. For a narrative description of how to use this extension see the eye tracking overview . Parameters \u00b6 Initialization Parameters \u00b6 Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer , params : {...}} ] }) Parameter Type Default Value Description webgazer object undefined You can explicitly pass a reference to a loaded instance of the webgazer.js library. If no explicit reference is passed then the extension will look for a global webgazer object. If you are loading webgazer.js via a <script> tag you do not need to set this parameter in most circumstances. auto_initialize bool false Whether to automatically initialize webgazer when the experiment begins. If set to true then the experiment will attempt to access the user's webcam immediately upon page load. The default value is false because it is probably a good idea to explain to the user why camera permission will be needed before asking for it. The webgazer-init-camera plugin can be used to initialize the camera during the experiment. round_predictions bool true Whether to round the x , y coordinates predicted by WebGazer to the nearest whole number. This greatly reduces the size of the data, as WebGazer records data to 15 decimal places by default. Given the noise of the system, there's really no need to record data to this level of precision. sampling_interval numeric 34 Sets the interval between gaze predictions. Because the underlying code is partially asynchronous, this interval is only approximate. The sampling interval will not be faster than this, on average, but the time between samples may fluctuate. Setting the interval too fast will create performance problems and produce redundant data, as the video feed from most webcams only updates about 30 times per second. Trial Parameters \u00b6 Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionWebgazer , params : {...}} ] } Parameter Type Default Value Description targets array [] A list of elements on the page that you would like to record the coordinates of for comparison with the WebGazer data. Each entry in the array should be a valid CSS selector string that identifies the element. The selector string should be valid for exactly one element on the page. If the selector is valid for more than one element then only the first matching element will be recorded. Data Generated \u00b6 Name Type Value webgazer_data array An array of objects containing gaze data for the trial. Each object has an x , a y , and a t property. The x and y properties specify the gaze location in pixels and t specifies the time in milliseconds since the start of the trial. webgazer_targets object An object contain the pixel coordinates of elements on the screen specified by the .targets parameter. Each key in this object will be a selector property, containing the CSS selector string used to find the element. The object corresponding to each key will contain x and y properties specifying the top-left corner of the object, width and height values, plus top , bottom , left , and right parameters which specify the bounding rectangle of the element. Functions \u00b6 In addition to the jsPsych webgazer-* plugins, the jsPsych webgazer extension provides a set of functions that allow the researcher to interact more directly with WebGazer. These functions can be called at any point during an experiment, and are crucial for building trial plugins that interact with WebGazer. All of the functions below must be prefixed with jsPsych.extensions.webgazer (e.g. jsPsych.extensions.webgazer.faceDetected() ). start() \u00b6 Performs initialization of webgazer, including requesting permissions from the user to access the camera. Returns a Promise that resolves when the camera is initialized and fails if the camera cannot be accessed, e.g., because the user denies permission. This is handled automatically if using the webgazer-init-camera plugin or setting auto_initialize to true in the extension parameters. isInitialized() \u00b6 Returns true if start() has been successfully called at some point, and false otherwise. faceDetected() \u00b6 Returns true if WebGazer is ready to make predictions ( webgazer.getTracker().predictionReady is true ). showPredictions() \u00b6 Turns on WebGazer's real-time visualization of predicted gaze location. hidePredictions() \u00b6 Turns off WebGazer's real-time visualization of predicted gaze location. showVideo() \u00b6 Turns on a display of the webcam image, guiding box for positioning the face, and WebGazer's estimate of the location of facial landmarks. hideVideo() \u00b6 Turns off the camera display. resume() \u00b6 Turns on gaze prediction. The extension will automatically handle this for you in most cases. You probably only need to use this if you are writing your own plugin that interfaces directly with WebGazer. pause() \u00b6 Turns off gaze prediction. The extension will automatically handle this for you in most cases. You probably only need to use this if you are writing your own plugin that interfaces directly with WebGazer. resetCalibration() \u00b6 Clears all calibration data. startMouseCalibration() \u00b6 Turns on mouse movement and mouse clicks as calibration events. While the webgazer-calibration plugin can also be used to run a parmeterized calibration routine, this calibration function call allows you to continuously calibrate WebGazer to any mouse movements or clicks throughout the experiment. For example, any *-button-response trial would also function as a WebGazer calibration event. stopMouseCalibration() \u00b6 Stops WebGazer from using mouse movements and mouse clicks as calibration events. calibratePoint(x, y) \u00b6 Instructs WebGazer to register the location x , y (in screen pixel coordinates) as a calibration event. Can be used for passive viewing calibration, i.e., instructing participants to fixate at a particular location. setRegressionType(regression_type) \u00b6 Change the method that WebGazer is using to perform feature -> location regression. Valid options are ridge , weightedRidge , and threadedRidge . See the WebGazer docs for more information about these options. The extension uses the default mode specified by WebGazer (currently ridge ). getCurrentPrediction() \u00b6 Get the current predicted gaze location from WebGazer. This returns a Promise that resolves once WebGazer has finished computing the gaze prediction. The Promise has a single parameter with an object with x , y , and, t parameters. t will be the value of performance.now() at approximately the time that the video frame was recorded. startSampleInterval(interval) \u00b6 Starts sampling gaze predictions every interval milliseconds. If interval is left undefined then the default value at extension initialization is used. Every sample will trigger an onGazeUpdate callback, as well as side effects that result in data storage within the extension. stopSampleInterval() \u00b6 Stops the sampling started by startSampleInterval() . onGazeUpdate(callback) \u00b6 Subscribe to gaze updates. The callback will be invoked every time a new gaze prediction is generated. The first argument of the callback will be an object with x , y , and, if currently in a trial with the extension turned on, the time t in ms since the start of the trial. t will be the value of performance.now() at approximately the time that the video frame was recorded. If currently in an active trial then t will be relative to the start of the trial. This function returns a close handler. When you no longer need to subscribe to gaze updates, call the close handler. Example: var cancelGazeUpdateHandler = jsPsych . extensions . webgazer . onGazeUpdate ( function ( prediction ){ console . log ( `Currently looking at ${ prediction . x } , ${ prediction . y } ` ); }); cancelGazeUpdateHandler (); You can add multiple handlers. Handlers are not closed automatically, so be sure to cancel them when no longer needed.","title":"webgazer"},{"location":"extensions/webgazer/#webgazer","text":"This extension supports eye tracking through the WebGazer library. For a narrative description of how to use this extension see the eye tracking overview .","title":"webgazer"},{"location":"extensions/webgazer/#parameters","text":"","title":"Parameters"},{"location":"extensions/webgazer/#initialization-parameters","text":"Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer , params : {...}} ] }) Parameter Type Default Value Description webgazer object undefined You can explicitly pass a reference to a loaded instance of the webgazer.js library. If no explicit reference is passed then the extension will look for a global webgazer object. If you are loading webgazer.js via a <script> tag you do not need to set this parameter in most circumstances. auto_initialize bool false Whether to automatically initialize webgazer when the experiment begins. If set to true then the experiment will attempt to access the user's webcam immediately upon page load. The default value is false because it is probably a good idea to explain to the user why camera permission will be needed before asking for it. The webgazer-init-camera plugin can be used to initialize the camera during the experiment. round_predictions bool true Whether to round the x , y coordinates predicted by WebGazer to the nearest whole number. This greatly reduces the size of the data, as WebGazer records data to 15 decimal places by default. Given the noise of the system, there's really no need to record data to this level of precision. sampling_interval numeric 34 Sets the interval between gaze predictions. Because the underlying code is partially asynchronous, this interval is only approximate. The sampling interval will not be faster than this, on average, but the time between samples may fluctuate. Setting the interval too fast will create performance problems and produce redundant data, as the video feed from most webcams only updates about 30 times per second.","title":"Initialization Parameters"},{"location":"extensions/webgazer/#trial-parameters","text":"Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionWebgazer , params : {...}} ] } Parameter Type Default Value Description targets array [] A list of elements on the page that you would like to record the coordinates of for comparison with the WebGazer data. Each entry in the array should be a valid CSS selector string that identifies the element. The selector string should be valid for exactly one element on the page. If the selector is valid for more than one element then only the first matching element will be recorded.","title":"Trial Parameters"},{"location":"extensions/webgazer/#data-generated","text":"Name Type Value webgazer_data array An array of objects containing gaze data for the trial. Each object has an x , a y , and a t property. The x and y properties specify the gaze location in pixels and t specifies the time in milliseconds since the start of the trial. webgazer_targets object An object contain the pixel coordinates of elements on the screen specified by the .targets parameter. Each key in this object will be a selector property, containing the CSS selector string used to find the element. The object corresponding to each key will contain x and y properties specifying the top-left corner of the object, width and height values, plus top , bottom , left , and right parameters which specify the bounding rectangle of the element.","title":"Data Generated"},{"location":"extensions/webgazer/#functions","text":"In addition to the jsPsych webgazer-* plugins, the jsPsych webgazer extension provides a set of functions that allow the researcher to interact more directly with WebGazer. These functions can be called at any point during an experiment, and are crucial for building trial plugins that interact with WebGazer. All of the functions below must be prefixed with jsPsych.extensions.webgazer (e.g. jsPsych.extensions.webgazer.faceDetected() ).","title":"Functions"},{"location":"extensions/webgazer/#start","text":"Performs initialization of webgazer, including requesting permissions from the user to access the camera. Returns a Promise that resolves when the camera is initialized and fails if the camera cannot be accessed, e.g., because the user denies permission. This is handled automatically if using the webgazer-init-camera plugin or setting auto_initialize to true in the extension parameters.","title":"start()"},{"location":"extensions/webgazer/#isinitialized","text":"Returns true if start() has been successfully called at some point, and false otherwise.","title":"isInitialized()"},{"location":"extensions/webgazer/#facedetected","text":"Returns true if WebGazer is ready to make predictions ( webgazer.getTracker().predictionReady is true ).","title":"faceDetected()"},{"location":"extensions/webgazer/#showpredictions","text":"Turns on WebGazer's real-time visualization of predicted gaze location.","title":"showPredictions()"},{"location":"extensions/webgazer/#hidepredictions","text":"Turns off WebGazer's real-time visualization of predicted gaze location.","title":"hidePredictions()"},{"location":"extensions/webgazer/#showvideo","text":"Turns on a display of the webcam image, guiding box for positioning the face, and WebGazer's estimate of the location of facial landmarks.","title":"showVideo()"},{"location":"extensions/webgazer/#hidevideo","text":"Turns off the camera display.","title":"hideVideo()"},{"location":"extensions/webgazer/#resume","text":"Turns on gaze prediction. The extension will automatically handle this for you in most cases. You probably only need to use this if you are writing your own plugin that interfaces directly with WebGazer.","title":"resume()"},{"location":"extensions/webgazer/#pause","text":"Turns off gaze prediction. The extension will automatically handle this for you in most cases. You probably only need to use this if you are writing your own plugin that interfaces directly with WebGazer.","title":"pause()"},{"location":"extensions/webgazer/#resetcalibration","text":"Clears all calibration data.","title":"resetCalibration()"},{"location":"extensions/webgazer/#startmousecalibration","text":"Turns on mouse movement and mouse clicks as calibration events. While the webgazer-calibration plugin can also be used to run a parmeterized calibration routine, this calibration function call allows you to continuously calibrate WebGazer to any mouse movements or clicks throughout the experiment. For example, any *-button-response trial would also function as a WebGazer calibration event.","title":"startMouseCalibration()"},{"location":"extensions/webgazer/#stopmousecalibration","text":"Stops WebGazer from using mouse movements and mouse clicks as calibration events.","title":"stopMouseCalibration()"},{"location":"extensions/webgazer/#calibratepointx-y","text":"Instructs WebGazer to register the location x , y (in screen pixel coordinates) as a calibration event. Can be used for passive viewing calibration, i.e., instructing participants to fixate at a particular location.","title":"calibratePoint(x, y)"},{"location":"extensions/webgazer/#setregressiontyperegression_type","text":"Change the method that WebGazer is using to perform feature -> location regression. Valid options are ridge , weightedRidge , and threadedRidge . See the WebGazer docs for more information about these options. The extension uses the default mode specified by WebGazer (currently ridge ).","title":"setRegressionType(regression_type)"},{"location":"extensions/webgazer/#getcurrentprediction","text":"Get the current predicted gaze location from WebGazer. This returns a Promise that resolves once WebGazer has finished computing the gaze prediction. The Promise has a single parameter with an object with x , y , and, t parameters. t will be the value of performance.now() at approximately the time that the video frame was recorded.","title":"getCurrentPrediction()"},{"location":"extensions/webgazer/#startsampleintervalinterval","text":"Starts sampling gaze predictions every interval milliseconds. If interval is left undefined then the default value at extension initialization is used. Every sample will trigger an onGazeUpdate callback, as well as side effects that result in data storage within the extension.","title":"startSampleInterval(interval)"},{"location":"extensions/webgazer/#stopsampleinterval","text":"Stops the sampling started by startSampleInterval() .","title":"stopSampleInterval()"},{"location":"extensions/webgazer/#ongazeupdatecallback","text":"Subscribe to gaze updates. The callback will be invoked every time a new gaze prediction is generated. The first argument of the callback will be an object with x , y , and, if currently in a trial with the extension turned on, the time t in ms since the start of the trial. t will be the value of performance.now() at approximately the time that the video frame was recorded. If currently in an active trial then t will be relative to the start of the trial. This function returns a close handler. When you no longer need to subscribe to gaze updates, call the close handler. Example: var cancelGazeUpdateHandler = jsPsych . extensions . webgazer . onGazeUpdate ( function ( prediction ){ console . log ( `Currently looking at ${ prediction . x } , ${ prediction . y } ` ); }); cancelGazeUpdateHandler (); You can add multiple handlers. Handlers are not closed automatically, so be sure to cancel them when no longer needed.","title":"onGazeUpdate(callback)"},{"location":"overview/browser-device-support/","text":"Browser and Device Support \u00b6 Desktop and Laptop Browsers \u00b6 Supported jsPsych supports recent versions of the four most commonly-used web browsers: Chrome Firefox Safari Edge This means that jsPsych should work on these browsers. If something doesn't work as you expect on one of the browsers above, it might be a bug that should be fixed. You can search for and report bugs on the jsPsych GitHub Issues page . We're very grateful for anyone who takes the time to report bugs - it helps improve the library for everyone! Unsupported There are many other web browsers that are available, but that are not commonly used. The most well-known of these are Internet Explorer and Opera. jsPsych is not tested on these and other browsers not listed in the Supported section above. jsPsych experiments might work in these browsers, but they might not . If you want to give participants the option to use unsupported browsers, then we recommend carefully testing your experiment to make sure that everything works as expected. Otherwise, we suggest asking your participants to only use a supported browser, or incorporating browser, device, and/or feature checks at the start of your experiment. jsPsych offers built-in methods for exclusion based on minimum browser size and WebAudio API compatibility . You can incorporate other browser/device/feature checks into your experiment by adding custom JavaScript code. Mobile Devices \u00b6 In general, jsPsych experiments can be run on mobile devices (smartphones and tablets). However, certain plugins will not work on mobile. For instance, any plugin that requires a keyboard response without a text input box, such as the *-keyboard-response plugins, will not work. Even plugins that do work on mobile might work differently than they do on desktop and laptop computers. For instance, on mobile devices, a text input box will cause an on-screen keyboard to pop up, which affects the visible content on the screen. If you plan to run an experiment that allows people to use mobile devices, we recommend doing some extra testing to make sure that everything works as expected. In particular, you may want to check that: * Font sizes are readable on smaller screens * Stimuli sizes are large enough and appropriate for the task * Page is laid out as intended (e.g. elements are centered and do not overlap) * Response options are touchscreen-friendly (e.g. buttons rather than key presses) * Response options (e.g. buttons, text boxes, radio buttons) are large enough and far enough apart to be easily selected with a finger tap It's possible to use your browser's developer tools to emulate mobile devices ( this page shows how to do it in Chrome ), which is useful for getting a sense of how your experiment will look on mobile devices. Just be aware that there are limitations to emulator tools, and there are some aspects of mobile devices/browsers that a desktop browser will not be able to simulate. Mobile Browsers \u00b6 The browser options for mobile phones and tablets are slightly different than those for desktop and laptop computers. In addition to mobile versions of Chrome, Firefox, Safari, and Edge, other notable mobile browsers include Opera Mobile, Samsung Internet, UC Browser, and Dolphin. Because of the greater diversity of mobile browsers and volatility in their usage statistics, jsPsych does not officially support any particular set of mobile browsers. However, we do anticipate that most experiments should work in most mobile browsers, especially the mobile versions of browsers that we do support in Desktop mode. If you run into a problem using jsPsych in mobile browsers, please report it on the jsPsych GitHub Issues page ! We do our best to fix browser incompatibilities that are not specific to a single experiment.","title":"Browser and Device Support"},{"location":"overview/browser-device-support/#browser-and-device-support","text":"","title":"Browser and Device Support"},{"location":"overview/browser-device-support/#desktop-and-laptop-browsers","text":"Supported jsPsych supports recent versions of the four most commonly-used web browsers: Chrome Firefox Safari Edge This means that jsPsych should work on these browsers. If something doesn't work as you expect on one of the browsers above, it might be a bug that should be fixed. You can search for and report bugs on the jsPsych GitHub Issues page . We're very grateful for anyone who takes the time to report bugs - it helps improve the library for everyone! Unsupported There are many other web browsers that are available, but that are not commonly used. The most well-known of these are Internet Explorer and Opera. jsPsych is not tested on these and other browsers not listed in the Supported section above. jsPsych experiments might work in these browsers, but they might not . If you want to give participants the option to use unsupported browsers, then we recommend carefully testing your experiment to make sure that everything works as expected. Otherwise, we suggest asking your participants to only use a supported browser, or incorporating browser, device, and/or feature checks at the start of your experiment. jsPsych offers built-in methods for exclusion based on minimum browser size and WebAudio API compatibility . You can incorporate other browser/device/feature checks into your experiment by adding custom JavaScript code.","title":"Desktop and Laptop Browsers"},{"location":"overview/browser-device-support/#mobile-devices","text":"In general, jsPsych experiments can be run on mobile devices (smartphones and tablets). However, certain plugins will not work on mobile. For instance, any plugin that requires a keyboard response without a text input box, such as the *-keyboard-response plugins, will not work. Even plugins that do work on mobile might work differently than they do on desktop and laptop computers. For instance, on mobile devices, a text input box will cause an on-screen keyboard to pop up, which affects the visible content on the screen. If you plan to run an experiment that allows people to use mobile devices, we recommend doing some extra testing to make sure that everything works as expected. In particular, you may want to check that: * Font sizes are readable on smaller screens * Stimuli sizes are large enough and appropriate for the task * Page is laid out as intended (e.g. elements are centered and do not overlap) * Response options are touchscreen-friendly (e.g. buttons rather than key presses) * Response options (e.g. buttons, text boxes, radio buttons) are large enough and far enough apart to be easily selected with a finger tap It's possible to use your browser's developer tools to emulate mobile devices ( this page shows how to do it in Chrome ), which is useful for getting a sense of how your experiment will look on mobile devices. Just be aware that there are limitations to emulator tools, and there are some aspects of mobile devices/browsers that a desktop browser will not be able to simulate.","title":"Mobile Devices"},{"location":"overview/browser-device-support/#mobile-browsers","text":"The browser options for mobile phones and tablets are slightly different than those for desktop and laptop computers. In addition to mobile versions of Chrome, Firefox, Safari, and Edge, other notable mobile browsers include Opera Mobile, Samsung Internet, UC Browser, and Dolphin. Because of the greater diversity of mobile browsers and volatility in their usage statistics, jsPsych does not officially support any particular set of mobile browsers. However, we do anticipate that most experiments should work in most mobile browsers, especially the mobile versions of browsers that we do support in Desktop mode. If you run into a problem using jsPsych in mobile browsers, please report it on the jsPsych GitHub Issues page ! We do our best to fix browser incompatibilities that are not specific to a single experiment.","title":"Mobile Browsers"},{"location":"overview/data/","text":"Data in jsPsych: permanent and non-permanent data. \u00b6 There are two very different kinds of data storage: data stored in memory and data stored permanently . Data stored permanently exists even after the browser running jsPsych closes, typically in a database or in a file on a server. Data stored in memory exists only as long the browser window running jsPsych is open. jsPsych has many features for interacting with data stored in memory, but few for permanent data storage. This is a deliberate choice, as there are dozens of ways that data could be stored permanently. jsPsych does not lock you into one particular solution. However, saving data permanently is obviously a crucial component of any experiment, and the second half of this page contains a few suggestions on how to accomplish permanent data storage. Storing data in jsPsych's data structure \u00b6 jsPsych has a centralized collection of data that is built as the experiment runs. Each trial adds to the collection, and you can access the data with various functions, including jsPsych.data.get() , which returns the entire set of data. In most cases, data collection will be automatic and hidden. Plugins save data on their own so it is not uncommon to have the only interaction with the data be at the end of the experiment when it is time to save it in a permanent manner (see sections below about how to do this). However, there are some situations in which you may want to interact with the data; in particular, you may want to store additional data that the plugins are not recording, like a subject identifier or condition assignment. You may also want to add data on a trial by trial basis. For example, in a Stroop paradigm you would want to label which trials are congruent and which are incongruent. These scenarios are explored below. Adding data to all trials \u00b6 Often it is useful to add a piece of data to all of the trials in the experiment. For example, appending the subject ID to each trial. This can be done with the jsPsych.data.addProperties() function. Here is an example: // generate a random subject ID with 15 characters var subject_id = jsPsych . randomization . randomID ( 15 ); // pick a random condition for the subject at the start of the experiment var condition_assignment = jsPsych . randomization . sampleWithoutReplacement ([ 'conditionA' , 'conditionB' , 'conditionC' ], 1 )[ 0 ]; // record the condition assignment in the jsPsych data // this adds a property called 'subject' and a property called 'condition' to every trial jsPsych . data . addProperties ({ subject : subject_id , condition : condition_assignment }); Adding data to a particular trial or set of trials \u00b6 Data can be added to a particular trial by setting the data parameter for the trial. The data parameter is an object of key-value pairs, and each pair is added to the data for that trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.jpg' , data : { image_type : 'A' } } Data declared in this way is also saved in the trials on any nested timelines: var block = { type : jsPsychImageKeyboardResponse , data : { image_type : 'A' }, timeline : [ { stimulus : 'imgA1.jpg' }, { stimulus : 'imgA2.jpg' } ] } The data object for a trial can also be updated in the on_finish event handler. You can override properties or add new ones. This is particularly useful for cases where the value depends on something that happened during the trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.jpg' , on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , 'j' )){ data . correct = true ; } else { data . correct = false ; } } } Aggregating and manipulating jsPsych data \u00b6 When accessing the data with jsPsych.data.get() the returned object is a special data collection object that exposes a number of methods for aggregating and manipulating the data. The full list of methods is detailed in the data module documentation . Here are some examples of data collection manipulation. All data generated by the image-keyboard-response plugin: var data = jsPsych . data . get (). filter ({ trial_type : 'image-keyboard-response' }); All data generated by the categorize-image plugin with a correct response: var data = jsPsych . data . get (). filter ({ trial_type : 'categorize-image' , correct : true }); All data with a response time between 100 and 500ms: var data = jsPsych . data . get (). filterCustom ( function ( x ){ return x . rt >= 100 && x . rt <= 500 }); Applying filters consecutively to get all trials from a particular plugin with a response time above 100ms: var data = jsPsych . data . get (). filter ({ trial_type : 'image-keyboard-response' }). filterCustom ( function ( x ){ return x . rt > 100 ; }); Getting the data from the last n trials: var n = 3 ; var data = jsPsych . data . get (). last ( n ); Getting the data from the last n trials with a correct response: var n = 3 ; var data = jsPsych . data . get (). filter ({ correct : true }). last ( n ); Getting the data from the first n trials: var n = 3 ; var data = jsPsych . data . get (). first ( n ); Counting the number of trials with a correct response in a data collection: var count = jsPsych . data . get (). filter ({ correct : true }). count (); Selecting all of the response times from a data collection: var response_times = jsPsych . data . get (). select ( 'rt' ); Calculating various descriptive statistics on the response times in a data collection: jsPsych . data . get (). select ( 'rt' ). mean (); jsPsych . data . get (). select ( 'rt' ). sum (); jsPsych . data . get (). select ( 'rt' ). min (); jsPsych . data . get (). select ( 'rt' ). max (); jsPsych . data . get (). select ( 'rt' ). variance (); jsPsych . data . get (). select ( 'rt' ). sd (); jsPsych . data . get (). select ( 'rt' ). median (); jsPsych . data . get (). select ( 'rt' ). count (); Storing data permanently as a file \u00b6 This is one of the simplest methods for saving jsPsych data on the server that is running the experiment. It involves a short PHP script and a few lines of JavaScript code. This method will save each participant's data as a CSV file on the server. This method will only work if you are running on a web server with PHP installed, or a local server with PHP (e.g., XAMPP ). This method uses a short PHP script to write files to the server: <?php // get the data from the POST message $post_data = json_decode ( file_get_contents ( 'php://input' ), true ); $data = $post_data [ 'filedata' ]; // generate a unique ID for the file, e.g., session-6feu833950202 $file = uniqid ( \"session-\" ); // the directory \"data\" must be writable by the server $name = \"data/ { $file } .csv\" ; // write the file to disk file_put_contents ( $name , $data ); ?> The file_put_contents($name, $data) method requires permission to write new files. An easy way to solve this is to create a directory on the server that will store the data and use the chmod command to give all users write permission to that directory. In the above example, the directory data/ is used to store files. To use the PHP script, the JavaScript that runs jsPsych needs to send the filedata information. This is done through an AJAX call. function saveData ( name , data ){ var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); // 'write_data.php' is the path to the php file described above. xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . send ( JSON . stringify ({ filedata : data })); } // call the saveData function after the experiment is over initJsPsych ({ on_finish : function (){ saveData ( jsPsych . data . get (). csv ()); } }); Danger The example above has minimal security and should probably not be used without additional security measures put in place. The risk is that someone can write arbitrary data using the saveData() function and store it to a file on your webserver. If they can guess the file name generated by the PHP script, or access a directory listing containing all of the filenames, then they can potentially write executable code to your server and run it. One fix is to store the CSV files outside the web directory on the server. This requires changing the path in the PHP script above from /data to a folder that is not accessible on the web. You should only use this solution if you have access to more than just the web directory on your server. You can also configure your web server to block access to the folder you are storing data in . The MySQL option below is more secure. Storing data permanently in a MySQL database \u00b6 Another solution for storing data generated by jsPsych is to write it to a database. There are dozens of database options. MySQL is one of the most popular relational databases , is free to use, and relatively easy to install . This code will assume that you have a MySQL database installed on your server that is hosting the jsPsych experiment, and that your server is able to execute PHP code. If you are trying to run on a local machine, you'll need to install a local server environment like XAMPP . You'll need two PHP scripts. The first is a configuration file for your database. Save it as database_config.php on your server. Within this file are configuration options for the database. You'll need to change these according to how you have configured your MySQL installation. <?php $servername = \"localhost\" ; $port = 3306 ; $username = \"username\" ; $password = \"password\" ; $dbname = \"database\" ; $table = \"tablename\" ; ?> The second PHP file will write data to the database. This script reads the database to discover what columns are in the table, and then only allows data to be entered in that matches those columns. This is a security feature. Save this file as write_data.php on your server. <?php // this path should point to your configuration file. include ( 'database_config.php' ); $data_array = json_decode ( file_get_contents ( 'php://input' ), true ); try { $conn = new PDO ( \"mysql:host= $servername ;port= $port ;dbname= $dbname \" , $username , $password ); $conn -> setAttribute ( PDO :: ATTR_ERRMODE , PDO :: ERRMODE_EXCEPTION ); // First stage is to get all column names from the table and store // them in $col_names array. $stmt = $conn -> prepare ( \"SHOW COLUMNS FROM ` $table `\" ); $stmt -> execute (); $col_names = array (); while ( $row = $stmt -> fetchColumn ()) { $col_names [] = $row ; } // Second stage is to create prepared SQL statement using the column // names as a guide to what values might be in the JSON. // If a value is missing from a particular trial, then NULL is inserted $sql = \"INSERT INTO $table VALUES(\" ; for ( $i = 0 ; $i < count ( $col_names ); $i ++ ){ $name = $col_names [ $i ]; $sql .= \": $name \" ; if ( $i != count ( $col_names ) - 1 ){ $sql .= \", \" ; } } $sql .= \");\" ; $insertstmt = $conn -> prepare ( $sql ); for ( $i = 0 ; $i < count ( $data_array ); $i ++ ){ for ( $j = 0 ; $j < count ( $col_names ); $j ++ ){ $colname = $col_names [ $j ]; if ( ! isset ( $data_array [ $i ][ $colname ])){ $insertstmt -> bindValue ( \": $colname \" , null , PDO :: PARAM_NULL ); } else { $insertstmt -> bindValue ( \": $colname \" , $data_array [ $i ][ $colname ]); } } $insertstmt -> execute (); } echo '{\"success\": true}' ; } catch ( PDOException $e ) { echo '{\"success\": false, \"message\": ' . $e -> getMessage (); } $conn = null ; ?> To send the data, we use an XMLHttpRequest request in JavaScript. function saveData () { var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); // change 'write_data.php' to point to php script. xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . onload = function () { if ( xhr . status == 200 ){ var response = JSON . parse ( xhr . responseText ); console . log ( response . success ); } }; xhr . send ( jsPsych . data . get (). json ()); } It's important that the XMLHttpRequest is able to complete before the experiment is closed. If you invoke the saveData() function at the end of your experiment and the participant closes the window before all of the data has been transferred you will lose that data. To mitigate this risk, you can use the call-function plugin's async option to prevent the experiment from progressing until the request is complete. var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . onload = function () { if ( xhr . status == 200 ){ var response = JSON . parse ( xhr . responseText ); console . log ( response . success ); } done (); // invoking done() causes experiment to progress to next trial. }; xhr . send ( jsPsych . data . get (). json ()); } }","title":"Data Storage, Aggregation, and Manipulation"},{"location":"overview/data/#data-in-jspsych-permanent-and-non-permanent-data","text":"There are two very different kinds of data storage: data stored in memory and data stored permanently . Data stored permanently exists even after the browser running jsPsych closes, typically in a database or in a file on a server. Data stored in memory exists only as long the browser window running jsPsych is open. jsPsych has many features for interacting with data stored in memory, but few for permanent data storage. This is a deliberate choice, as there are dozens of ways that data could be stored permanently. jsPsych does not lock you into one particular solution. However, saving data permanently is obviously a crucial component of any experiment, and the second half of this page contains a few suggestions on how to accomplish permanent data storage.","title":"Data in jsPsych: permanent and non-permanent data."},{"location":"overview/data/#storing-data-in-jspsychs-data-structure","text":"jsPsych has a centralized collection of data that is built as the experiment runs. Each trial adds to the collection, and you can access the data with various functions, including jsPsych.data.get() , which returns the entire set of data. In most cases, data collection will be automatic and hidden. Plugins save data on their own so it is not uncommon to have the only interaction with the data be at the end of the experiment when it is time to save it in a permanent manner (see sections below about how to do this). However, there are some situations in which you may want to interact with the data; in particular, you may want to store additional data that the plugins are not recording, like a subject identifier or condition assignment. You may also want to add data on a trial by trial basis. For example, in a Stroop paradigm you would want to label which trials are congruent and which are incongruent. These scenarios are explored below.","title":"Storing data in jsPsych's data structure"},{"location":"overview/data/#adding-data-to-all-trials","text":"Often it is useful to add a piece of data to all of the trials in the experiment. For example, appending the subject ID to each trial. This can be done with the jsPsych.data.addProperties() function. Here is an example: // generate a random subject ID with 15 characters var subject_id = jsPsych . randomization . randomID ( 15 ); // pick a random condition for the subject at the start of the experiment var condition_assignment = jsPsych . randomization . sampleWithoutReplacement ([ 'conditionA' , 'conditionB' , 'conditionC' ], 1 )[ 0 ]; // record the condition assignment in the jsPsych data // this adds a property called 'subject' and a property called 'condition' to every trial jsPsych . data . addProperties ({ subject : subject_id , condition : condition_assignment });","title":"Adding data to all trials"},{"location":"overview/data/#adding-data-to-a-particular-trial-or-set-of-trials","text":"Data can be added to a particular trial by setting the data parameter for the trial. The data parameter is an object of key-value pairs, and each pair is added to the data for that trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.jpg' , data : { image_type : 'A' } } Data declared in this way is also saved in the trials on any nested timelines: var block = { type : jsPsychImageKeyboardResponse , data : { image_type : 'A' }, timeline : [ { stimulus : 'imgA1.jpg' }, { stimulus : 'imgA2.jpg' } ] } The data object for a trial can also be updated in the on_finish event handler. You can override properties or add new ones. This is particularly useful for cases where the value depends on something that happened during the trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.jpg' , on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , 'j' )){ data . correct = true ; } else { data . correct = false ; } } }","title":"Adding data to a particular trial or set of trials"},{"location":"overview/data/#aggregating-and-manipulating-jspsych-data","text":"When accessing the data with jsPsych.data.get() the returned object is a special data collection object that exposes a number of methods for aggregating and manipulating the data. The full list of methods is detailed in the data module documentation . Here are some examples of data collection manipulation. All data generated by the image-keyboard-response plugin: var data = jsPsych . data . get (). filter ({ trial_type : 'image-keyboard-response' }); All data generated by the categorize-image plugin with a correct response: var data = jsPsych . data . get (). filter ({ trial_type : 'categorize-image' , correct : true }); All data with a response time between 100 and 500ms: var data = jsPsych . data . get (). filterCustom ( function ( x ){ return x . rt >= 100 && x . rt <= 500 }); Applying filters consecutively to get all trials from a particular plugin with a response time above 100ms: var data = jsPsych . data . get (). filter ({ trial_type : 'image-keyboard-response' }). filterCustom ( function ( x ){ return x . rt > 100 ; }); Getting the data from the last n trials: var n = 3 ; var data = jsPsych . data . get (). last ( n ); Getting the data from the last n trials with a correct response: var n = 3 ; var data = jsPsych . data . get (). filter ({ correct : true }). last ( n ); Getting the data from the first n trials: var n = 3 ; var data = jsPsych . data . get (). first ( n ); Counting the number of trials with a correct response in a data collection: var count = jsPsych . data . get (). filter ({ correct : true }). count (); Selecting all of the response times from a data collection: var response_times = jsPsych . data . get (). select ( 'rt' ); Calculating various descriptive statistics on the response times in a data collection: jsPsych . data . get (). select ( 'rt' ). mean (); jsPsych . data . get (). select ( 'rt' ). sum (); jsPsych . data . get (). select ( 'rt' ). min (); jsPsych . data . get (). select ( 'rt' ). max (); jsPsych . data . get (). select ( 'rt' ). variance (); jsPsych . data . get (). select ( 'rt' ). sd (); jsPsych . data . get (). select ( 'rt' ). median (); jsPsych . data . get (). select ( 'rt' ). count ();","title":"Aggregating and manipulating jsPsych data"},{"location":"overview/data/#storing-data-permanently-as-a-file","text":"This is one of the simplest methods for saving jsPsych data on the server that is running the experiment. It involves a short PHP script and a few lines of JavaScript code. This method will save each participant's data as a CSV file on the server. This method will only work if you are running on a web server with PHP installed, or a local server with PHP (e.g., XAMPP ). This method uses a short PHP script to write files to the server: <?php // get the data from the POST message $post_data = json_decode ( file_get_contents ( 'php://input' ), true ); $data = $post_data [ 'filedata' ]; // generate a unique ID for the file, e.g., session-6feu833950202 $file = uniqid ( \"session-\" ); // the directory \"data\" must be writable by the server $name = \"data/ { $file } .csv\" ; // write the file to disk file_put_contents ( $name , $data ); ?> The file_put_contents($name, $data) method requires permission to write new files. An easy way to solve this is to create a directory on the server that will store the data and use the chmod command to give all users write permission to that directory. In the above example, the directory data/ is used to store files. To use the PHP script, the JavaScript that runs jsPsych needs to send the filedata information. This is done through an AJAX call. function saveData ( name , data ){ var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); // 'write_data.php' is the path to the php file described above. xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . send ( JSON . stringify ({ filedata : data })); } // call the saveData function after the experiment is over initJsPsych ({ on_finish : function (){ saveData ( jsPsych . data . get (). csv ()); } }); Danger The example above has minimal security and should probably not be used without additional security measures put in place. The risk is that someone can write arbitrary data using the saveData() function and store it to a file on your webserver. If they can guess the file name generated by the PHP script, or access a directory listing containing all of the filenames, then they can potentially write executable code to your server and run it. One fix is to store the CSV files outside the web directory on the server. This requires changing the path in the PHP script above from /data to a folder that is not accessible on the web. You should only use this solution if you have access to more than just the web directory on your server. You can also configure your web server to block access to the folder you are storing data in . The MySQL option below is more secure.","title":"Storing data permanently as a file"},{"location":"overview/data/#storing-data-permanently-in-a-mysql-database","text":"Another solution for storing data generated by jsPsych is to write it to a database. There are dozens of database options. MySQL is one of the most popular relational databases , is free to use, and relatively easy to install . This code will assume that you have a MySQL database installed on your server that is hosting the jsPsych experiment, and that your server is able to execute PHP code. If you are trying to run on a local machine, you'll need to install a local server environment like XAMPP . You'll need two PHP scripts. The first is a configuration file for your database. Save it as database_config.php on your server. Within this file are configuration options for the database. You'll need to change these according to how you have configured your MySQL installation. <?php $servername = \"localhost\" ; $port = 3306 ; $username = \"username\" ; $password = \"password\" ; $dbname = \"database\" ; $table = \"tablename\" ; ?> The second PHP file will write data to the database. This script reads the database to discover what columns are in the table, and then only allows data to be entered in that matches those columns. This is a security feature. Save this file as write_data.php on your server. <?php // this path should point to your configuration file. include ( 'database_config.php' ); $data_array = json_decode ( file_get_contents ( 'php://input' ), true ); try { $conn = new PDO ( \"mysql:host= $servername ;port= $port ;dbname= $dbname \" , $username , $password ); $conn -> setAttribute ( PDO :: ATTR_ERRMODE , PDO :: ERRMODE_EXCEPTION ); // First stage is to get all column names from the table and store // them in $col_names array. $stmt = $conn -> prepare ( \"SHOW COLUMNS FROM ` $table `\" ); $stmt -> execute (); $col_names = array (); while ( $row = $stmt -> fetchColumn ()) { $col_names [] = $row ; } // Second stage is to create prepared SQL statement using the column // names as a guide to what values might be in the JSON. // If a value is missing from a particular trial, then NULL is inserted $sql = \"INSERT INTO $table VALUES(\" ; for ( $i = 0 ; $i < count ( $col_names ); $i ++ ){ $name = $col_names [ $i ]; $sql .= \": $name \" ; if ( $i != count ( $col_names ) - 1 ){ $sql .= \", \" ; } } $sql .= \");\" ; $insertstmt = $conn -> prepare ( $sql ); for ( $i = 0 ; $i < count ( $data_array ); $i ++ ){ for ( $j = 0 ; $j < count ( $col_names ); $j ++ ){ $colname = $col_names [ $j ]; if ( ! isset ( $data_array [ $i ][ $colname ])){ $insertstmt -> bindValue ( \": $colname \" , null , PDO :: PARAM_NULL ); } else { $insertstmt -> bindValue ( \": $colname \" , $data_array [ $i ][ $colname ]); } } $insertstmt -> execute (); } echo '{\"success\": true}' ; } catch ( PDOException $e ) { echo '{\"success\": false, \"message\": ' . $e -> getMessage (); } $conn = null ; ?> To send the data, we use an XMLHttpRequest request in JavaScript. function saveData () { var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); // change 'write_data.php' to point to php script. xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . onload = function () { if ( xhr . status == 200 ){ var response = JSON . parse ( xhr . responseText ); console . log ( response . success ); } }; xhr . send ( jsPsych . data . get (). json ()); } It's important that the XMLHttpRequest is able to complete before the experiment is closed. If you invoke the saveData() function at the end of your experiment and the participant closes the window before all of the data has been transferred you will lose that data. To mitigate this risk, you can use the call-function plugin's async option to prevent the experiment from progressing until the request is complete. var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . onload = function () { if ( xhr . status == 200 ){ var response = JSON . parse ( xhr . responseText ); console . log ( response . success ); } done (); // invoking done() causes experiment to progress to next trial. }; xhr . send ( jsPsych . data . get (). json ()); } }","title":"Storing data permanently in a MySQL database"},{"location":"overview/dynamic-parameters/","text":"Dynamic parameters \u00b6 Most trial parameters can also be specified as functions. In a typical declaration of a jsPsych trial, parameters are known at the start of the experiment. This makes it impossible to alter the content of the trial based on the outcome of previous trials. However, when functions are used as the parameter value, the function is evaluated right before the trial starts, and the return value of the function is used as the parameter value for that trial . This enables dynamic updating of the parameter based on data that a participant has generated or any other information that you do not know in advance. Examples \u00b6 Providing Feedback \u00b6 Here is a sketch of how this functionality could be used to display feedback to a participant in the Flanker Task. var timeline = []; var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' }, on_finish : function ( data ){ // Score the keyboard response as correct or incorrect. if ( jsPsych . pluginAPI . compareKeys ( data . response , \"f\" )){ data . correct = true ; } else { data . correct = false ; } } } var feedback = { type : jsPsychHtmlKeyboardResponse , trial_duration : 1000 , stimulus : function (){ // The feedback stimulus is a dynamic parameter because we can't know in advance whether // the stimulus should be 'correct' or 'incorrect'. // Instead, this function will check the accuracy of the last response and use that information to set // the stimulus value on each trial. var last_trial_correct = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. correct ; if ( last_trial_correct ){ return \"<p>Correct!</p>\" ; // the parameter value has to be returned from the function } else { return \"<p>Wrong.</p>\" ; // the parameter value has to be returned from the function } } } timeline . push ( trial , feedback ); Note When scoring a participant's response, the jsPsych.pluginAPI.compareKeys function is only needed to compare keyboard responses. For other kinds of response types, such as button presses, you can compare the participant's response and correct response values directly, e.g. if ( data . response == 0 )){ data . correct = true ; } else { data . correct = false ; } Or: data . correct = data . response === data . correct_response ; Randomizing a parameter value \u00b6 Here's an example of using a dynamic parameter to randomize the inter-trial interval (ITI) duration. This time, the dynamic parameter is created using a named function instead of an anonymous function. var random_duration = function () { var rand_dur = jsPsych . randomization . sampleWithoutReplacement ([ 500 , 600 , 700 , 800 ], 1 )[ 0 ]; return rand_dur ; } var trial = { type : jsPsychHtmlKeyboardResponse stimulus : '+' , post_trial_gap : random_duration // if you use a named function for a dynamic parameter, then just use the function name (without parentheses after it) } Storing changing variables in the data \u00b6 The trial's data parameter can be also function, which is useful for when you want to save information to the data that can change during the experiment. For example, if you have a global variable called current_difficulty that tracks the difficulty level in an adaptive task, you can save the current value of this variable to the trial data like this: var current_difficulty ; // value changes during the experiment var trial = { type : jsPsychSurveyText , questions : [{ prompt : \"Please enter your response.\" }] data : function () { return { difficulty : current_difficulty }; } } It's also possible to use a function for any of the individual properties in the trial's data object, for instance if you want to combine static and dynamic information in the data: var trial = { type : jsPsychSurveyText , questions : [{ prompt : \"Please enter your response.\" }] data : { difficulty : function () { return current_difficulty ; // the difficulty value changes during the experiment }, task_part : 'recall' , // this part of the data is always the same block_number : 1 } } Nested Parameters \u00b6 Dyanmic parameters work the same way with nested parameters, which are parameters that contain one or more sets of other parameters. For instance, many survey-* plugins have a questions parameter that is a nested parameter: it is an array that contains the parameters for one or more questions on the page. To make the questions parameter dynamic, you can use a function that returns the array with all of the parameters for each question: var subject_id ; // value is set during the experiment var trial = { type : jsPsychSurveyText , questions : function (){ var questions_array = [ { prompt : \"Hi \" + subject_id + \"! What's your favorite city?\" , required : true , name : 'fav_city' }, { prompt : \"What is your favorite fruit?\" , required : true , name : 'fav_fruit' }, ]; return questions_array ; } } You can also use a function for any of the individual parameters inside of a nested parameter. var trial = { type : jsPsychSurveyText , questions : [ { prompt : function () { // this question prompt is dynamic - the text that is shown // will change based on the participant's earlier response var favorite_city = jsPsych . data . getLastTrialData (). values ()[ 0 ]. response . fav_city ; var text = \"Earlier you said your favorite city is \" + favorite_city + \". What do you like most about \" + favorite_city + \"?\" return text ; }, required : true , rows : 40 , columns : 10 }, { prompt : \"What is your favorite fruit?\" , required : true , name : 'fav_fruit' } ] } When dynamic parameters can't be used \u00b6 Note that if the plugin expects the value of a given parameter to be a function, then this function will not be evaluated at the start of the trial. This is because some plugins allow the researcher to specify functions that should be called at some point during the trial. Some examples of this include the stimulus parameter in the canvas-* plugins, the mistake_fn parameter in the cloze plugin, and the stim_function parameter in the reconstruction plugin. If you want to check whether this is the case for a particular plugin and parameter, then the parameter's type in the plugin.info section of the plugin file. If the parameter type is ParameterType.FUNCTION , then this parameter must be a function and it will not be executed before the trial starts. Even though function evaluation doesn't work the same way with these parameters, the fact that the parameters are functions means that you can get the same dynamic functionality. These functions are typically evaluated at some point during the trial, so you still get updates to values within the function during the trial.","title":"Dynamic Parameters"},{"location":"overview/dynamic-parameters/#dynamic-parameters","text":"Most trial parameters can also be specified as functions. In a typical declaration of a jsPsych trial, parameters are known at the start of the experiment. This makes it impossible to alter the content of the trial based on the outcome of previous trials. However, when functions are used as the parameter value, the function is evaluated right before the trial starts, and the return value of the function is used as the parameter value for that trial . This enables dynamic updating of the parameter based on data that a participant has generated or any other information that you do not know in advance.","title":"Dynamic parameters"},{"location":"overview/dynamic-parameters/#examples","text":"","title":"Examples"},{"location":"overview/dynamic-parameters/#providing-feedback","text":"Here is a sketch of how this functionality could be used to display feedback to a participant in the Flanker Task. var timeline = []; var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' }, on_finish : function ( data ){ // Score the keyboard response as correct or incorrect. if ( jsPsych . pluginAPI . compareKeys ( data . response , \"f\" )){ data . correct = true ; } else { data . correct = false ; } } } var feedback = { type : jsPsychHtmlKeyboardResponse , trial_duration : 1000 , stimulus : function (){ // The feedback stimulus is a dynamic parameter because we can't know in advance whether // the stimulus should be 'correct' or 'incorrect'. // Instead, this function will check the accuracy of the last response and use that information to set // the stimulus value on each trial. var last_trial_correct = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. correct ; if ( last_trial_correct ){ return \"<p>Correct!</p>\" ; // the parameter value has to be returned from the function } else { return \"<p>Wrong.</p>\" ; // the parameter value has to be returned from the function } } } timeline . push ( trial , feedback ); Note When scoring a participant's response, the jsPsych.pluginAPI.compareKeys function is only needed to compare keyboard responses. For other kinds of response types, such as button presses, you can compare the participant's response and correct response values directly, e.g. if ( data . response == 0 )){ data . correct = true ; } else { data . correct = false ; } Or: data . correct = data . response === data . correct_response ;","title":"Providing Feedback"},{"location":"overview/dynamic-parameters/#randomizing-a-parameter-value","text":"Here's an example of using a dynamic parameter to randomize the inter-trial interval (ITI) duration. This time, the dynamic parameter is created using a named function instead of an anonymous function. var random_duration = function () { var rand_dur = jsPsych . randomization . sampleWithoutReplacement ([ 500 , 600 , 700 , 800 ], 1 )[ 0 ]; return rand_dur ; } var trial = { type : jsPsychHtmlKeyboardResponse stimulus : '+' , post_trial_gap : random_duration // if you use a named function for a dynamic parameter, then just use the function name (without parentheses after it) }","title":"Randomizing a parameter value"},{"location":"overview/dynamic-parameters/#storing-changing-variables-in-the-data","text":"The trial's data parameter can be also function, which is useful for when you want to save information to the data that can change during the experiment. For example, if you have a global variable called current_difficulty that tracks the difficulty level in an adaptive task, you can save the current value of this variable to the trial data like this: var current_difficulty ; // value changes during the experiment var trial = { type : jsPsychSurveyText , questions : [{ prompt : \"Please enter your response.\" }] data : function () { return { difficulty : current_difficulty }; } } It's also possible to use a function for any of the individual properties in the trial's data object, for instance if you want to combine static and dynamic information in the data: var trial = { type : jsPsychSurveyText , questions : [{ prompt : \"Please enter your response.\" }] data : { difficulty : function () { return current_difficulty ; // the difficulty value changes during the experiment }, task_part : 'recall' , // this part of the data is always the same block_number : 1 } }","title":"Storing changing variables in the data"},{"location":"overview/dynamic-parameters/#nested-parameters","text":"Dyanmic parameters work the same way with nested parameters, which are parameters that contain one or more sets of other parameters. For instance, many survey-* plugins have a questions parameter that is a nested parameter: it is an array that contains the parameters for one or more questions on the page. To make the questions parameter dynamic, you can use a function that returns the array with all of the parameters for each question: var subject_id ; // value is set during the experiment var trial = { type : jsPsychSurveyText , questions : function (){ var questions_array = [ { prompt : \"Hi \" + subject_id + \"! What's your favorite city?\" , required : true , name : 'fav_city' }, { prompt : \"What is your favorite fruit?\" , required : true , name : 'fav_fruit' }, ]; return questions_array ; } } You can also use a function for any of the individual parameters inside of a nested parameter. var trial = { type : jsPsychSurveyText , questions : [ { prompt : function () { // this question prompt is dynamic - the text that is shown // will change based on the participant's earlier response var favorite_city = jsPsych . data . getLastTrialData (). values ()[ 0 ]. response . fav_city ; var text = \"Earlier you said your favorite city is \" + favorite_city + \". What do you like most about \" + favorite_city + \"?\" return text ; }, required : true , rows : 40 , columns : 10 }, { prompt : \"What is your favorite fruit?\" , required : true , name : 'fav_fruit' } ] }","title":"Nested Parameters"},{"location":"overview/dynamic-parameters/#when-dynamic-parameters-cant-be-used","text":"Note that if the plugin expects the value of a given parameter to be a function, then this function will not be evaluated at the start of the trial. This is because some plugins allow the researcher to specify functions that should be called at some point during the trial. Some examples of this include the stimulus parameter in the canvas-* plugins, the mistake_fn parameter in the cloze plugin, and the stim_function parameter in the reconstruction plugin. If you want to check whether this is the case for a particular plugin and parameter, then the parameter's type in the plugin.info section of the plugin file. If the parameter type is ParameterType.FUNCTION , then this parameter must be a function and it will not be executed before the trial starts. Even though function evaluation doesn't work the same way with these parameters, the fact that the parameters are functions means that you can get the same dynamic functionality. These functions are typically evaluated at some point during the trial, so you still get updates to values within the function during the trial.","title":"When dynamic parameters can't be used"},{"location":"overview/events/","text":"Event-related callback functions \u00b6 jsPsych offers the ability to call arbitrary functions in response to certain events occurring, like the end of a trial or when new data is saved. This page summarizes the different opportunities for callback functions and how to specify them. on_close \u00b6 The on_close callback can be declared in the initJsPsych method. The callback triggers when the user leaves the page, but before any content on the page is removed from the browser's memory. This can be used, for example, to save data as the user is leaving the page. initJsPsych ({ on_close : function (){ var data = jsPsych . data . get (). json (); save_data_to_server ( data ); } }); on_data_update \u00b6 The on_data_update callback can be declared in the initJsPsych method. The callback triggers at the end of a data update cycle. This happens after every trial, after the on_finish (trial) and on_trial_finish events execute, allowing you to modify the data in those callbacks, and then use this callback to store the data. The function will be passed a single argument, which contains the data that was written. initJsPsych ({ on_data_update : function ( data ) { console . log ( 'Just added new data. The contents of the data are: ' + JSON . stringify ( data )); } }); on_finish (trial) \u00b6 The on_finish callback can be added to any trial. The callback will trigger whenever the trial ends. The callback function will be passed a single argument, containing the data object from the trial. This data object is editable . Any changes made in the on_finish function will be stored in the internal data collection. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_finish : function ( data ) { if ( jsPsych . pluginAPI . compareKeys ( data . response , 'j' )){ data . correct = true ; } else { data . correct = false ; } } }; on_finish (experiment) \u00b6 The on_finish callback can be declared in the initJsPsych method. The callback will trigger once all trials in the experiment have been run. The method will be passed a single argument, containing all of the data generated in the experiment. initJsPsych ({ on_finish : function ( data ) { console . log ( 'The experiment is over! Here is all the data: ' + JSON . stringify ( data )); } }); on_load \u00b6 The on_load callback can be added to any trial. The callback will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_load : function () { console . log ( 'The trial just finished loading.' ); } }; on_start (trial) \u00b6 The on_start callback can be added to any trial. The callback will trigger right before the trial begins. The callback function will be passed a single argument, containing the trial object. If any of the parameters of the trial are functions or timeline variables, these will be evaluated before on_start is called, and the trial object will contain the evaluated value. The trial object is modifiable, and any changes made will affect the trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_start : function ( trial ) { console . log ( 'The trial is about to start.' ); trial . stimulus = 'imgB.png' ; // this will change what stimulus is displayed in the trial } }; on_timeline_finish \u00b6 The on_timeline_finish callback can be declared in a timeline node. The callback will be triggered when the timeline ends during the experiment. If timeline_variables , conditional_function , loop_function , or sample options are used, this function will execute when all trials have finished. If a loop_function is used, then this on_timeline_finish function will be triggered before the loop function. If the repetitions option is used, this function will be triggered at the end of every repetition. var procedure = { timeline : [ trial1 , trial2 ], timeline_variables : [ { stimulus : 'person-1.jpg' }, { stimulus : 'person-2.jpg' }, { stimulus : 'person-3.jpg' }, { stimulus : 'person-4.jpg' } ], on_timeline_finish : function () { console . log ( 'This timeline has finished.' ); }, loop_function : function () { console . log ( 'This loop function will execute after on_timeline_finish.' ); return false ; } } on_timeline_start \u00b6 The on_timeline_start callback can be declared in a timeline node. The callback will be triggered when the timeline starts during the experiment, including when timeline_variables , loop_function , or sample options are used. If a conditional_function is used, then the conditional function will execute first, and the on_timeline_start function will only execute if the conditional function returns true . If the repetitions option is used, this function will be triggered at the start of every repetition. var procedure = { timeline : [ trial1 , trial2 ], conditional_function : function () { console . log ( 'This conditional function will execute first.' ) return true ; }, on_timeline_start : function () { console . log ( 'This timeline has started' ); } } on_trial_finish \u00b6 The on_trial_finish callback can be declared in the initJsPsych method. The callback will trigger at the end of every trial in the experiment. If you want a callback to trigger only for the end of certain trials, use the on_finish callback on the trial object. The callback function will be passed a single argument, containing the data object from the trial. initJsPsych ({ on_trial_finish : function ( data ) { console . log ( 'A trial just ended.' ); console . log ( JSON . stringify ( data )); } }); on_trial_start \u00b6 The on_trial_start callback can be declared in the initJsPsych method. The callback will trigger at the start of every trial in the experiment. The function receives a single argument: a modifiable copy of the trial object that will be used to run the next trial. Changes can be made to this object to alter the parameters of the upcoming trial. var current_score = 0 ; // a variable that is updated throughout the experiment to keep track of the current score. initJsPsych ({ on_trial_start : function ( trial ) { trial . data . score_at_start_of_trial = current_score ; console . log ( 'A trial just started.' ); } });","title":"Events"},{"location":"overview/events/#event-related-callback-functions","text":"jsPsych offers the ability to call arbitrary functions in response to certain events occurring, like the end of a trial or when new data is saved. This page summarizes the different opportunities for callback functions and how to specify them.","title":"Event-related callback functions"},{"location":"overview/events/#on_close","text":"The on_close callback can be declared in the initJsPsych method. The callback triggers when the user leaves the page, but before any content on the page is removed from the browser's memory. This can be used, for example, to save data as the user is leaving the page. initJsPsych ({ on_close : function (){ var data = jsPsych . data . get (). json (); save_data_to_server ( data ); } });","title":"on_close"},{"location":"overview/events/#on_data_update","text":"The on_data_update callback can be declared in the initJsPsych method. The callback triggers at the end of a data update cycle. This happens after every trial, after the on_finish (trial) and on_trial_finish events execute, allowing you to modify the data in those callbacks, and then use this callback to store the data. The function will be passed a single argument, which contains the data that was written. initJsPsych ({ on_data_update : function ( data ) { console . log ( 'Just added new data. The contents of the data are: ' + JSON . stringify ( data )); } });","title":"on_data_update"},{"location":"overview/events/#on_finish-trial","text":"The on_finish callback can be added to any trial. The callback will trigger whenever the trial ends. The callback function will be passed a single argument, containing the data object from the trial. This data object is editable . Any changes made in the on_finish function will be stored in the internal data collection. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_finish : function ( data ) { if ( jsPsych . pluginAPI . compareKeys ( data . response , 'j' )){ data . correct = true ; } else { data . correct = false ; } } };","title":"on_finish (trial)"},{"location":"overview/events/#on_finish-experiment","text":"The on_finish callback can be declared in the initJsPsych method. The callback will trigger once all trials in the experiment have been run. The method will be passed a single argument, containing all of the data generated in the experiment. initJsPsych ({ on_finish : function ( data ) { console . log ( 'The experiment is over! Here is all the data: ' + JSON . stringify ( data )); } });","title":"on_finish (experiment)"},{"location":"overview/events/#on_load","text":"The on_load callback can be added to any trial. The callback will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_load : function () { console . log ( 'The trial just finished loading.' ); } };","title":"on_load"},{"location":"overview/events/#on_start-trial","text":"The on_start callback can be added to any trial. The callback will trigger right before the trial begins. The callback function will be passed a single argument, containing the trial object. If any of the parameters of the trial are functions or timeline variables, these will be evaluated before on_start is called, and the trial object will contain the evaluated value. The trial object is modifiable, and any changes made will affect the trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_start : function ( trial ) { console . log ( 'The trial is about to start.' ); trial . stimulus = 'imgB.png' ; // this will change what stimulus is displayed in the trial } };","title":"on_start (trial)"},{"location":"overview/events/#on_timeline_finish","text":"The on_timeline_finish callback can be declared in a timeline node. The callback will be triggered when the timeline ends during the experiment. If timeline_variables , conditional_function , loop_function , or sample options are used, this function will execute when all trials have finished. If a loop_function is used, then this on_timeline_finish function will be triggered before the loop function. If the repetitions option is used, this function will be triggered at the end of every repetition. var procedure = { timeline : [ trial1 , trial2 ], timeline_variables : [ { stimulus : 'person-1.jpg' }, { stimulus : 'person-2.jpg' }, { stimulus : 'person-3.jpg' }, { stimulus : 'person-4.jpg' } ], on_timeline_finish : function () { console . log ( 'This timeline has finished.' ); }, loop_function : function () { console . log ( 'This loop function will execute after on_timeline_finish.' ); return false ; } }","title":"on_timeline_finish"},{"location":"overview/events/#on_timeline_start","text":"The on_timeline_start callback can be declared in a timeline node. The callback will be triggered when the timeline starts during the experiment, including when timeline_variables , loop_function , or sample options are used. If a conditional_function is used, then the conditional function will execute first, and the on_timeline_start function will only execute if the conditional function returns true . If the repetitions option is used, this function will be triggered at the start of every repetition. var procedure = { timeline : [ trial1 , trial2 ], conditional_function : function () { console . log ( 'This conditional function will execute first.' ) return true ; }, on_timeline_start : function () { console . log ( 'This timeline has started' ); } }","title":"on_timeline_start"},{"location":"overview/events/#on_trial_finish","text":"The on_trial_finish callback can be declared in the initJsPsych method. The callback will trigger at the end of every trial in the experiment. If you want a callback to trigger only for the end of certain trials, use the on_finish callback on the trial object. The callback function will be passed a single argument, containing the data object from the trial. initJsPsych ({ on_trial_finish : function ( data ) { console . log ( 'A trial just ended.' ); console . log ( JSON . stringify ( data )); } });","title":"on_trial_finish"},{"location":"overview/events/#on_trial_start","text":"The on_trial_start callback can be declared in the initJsPsych method. The callback will trigger at the start of every trial in the experiment. The function receives a single argument: a modifiable copy of the trial object that will be used to run the next trial. Changes can be made to this object to alter the parameters of the upcoming trial. var current_score = 0 ; // a variable that is updated throughout the experiment to keep track of the current score. initJsPsych ({ on_trial_start : function ( trial ) { trial . data . score_at_start_of_trial = current_score ; console . log ( 'A trial just started.' ); } });","title":"on_trial_start"},{"location":"overview/exclude-browser/","text":"Exclude Participants Based on Browser Features \u00b6 Changed in 7.1 Online participants will use many different kinds of browsers. Depending on the experiment, it may be important to specify a minimum feature set of the browser. As of v7.1 of jsPsych, the recommended way to do this is using the browser-check plugin . This plugin can record many features of the participant's browser and exclude participants who do not meet a defined set of inclusion criteria. Please see the browser-check plugin documentation for more details. The prior approach of using the exclusions parameter in initJsPsych() is deprecated and will be removed in v8.0 . You can find the documentation for it in the 7.0 docs .","title":"Exclude Participants Based on Browser Features"},{"location":"overview/exclude-browser/#exclude-participants-based-on-browser-features","text":"Changed in 7.1 Online participants will use many different kinds of browsers. Depending on the experiment, it may be important to specify a minimum feature set of the browser. As of v7.1 of jsPsych, the recommended way to do this is using the browser-check plugin . This plugin can record many features of the participant's browser and exclude participants who do not meet a defined set of inclusion criteria. Please see the browser-check plugin documentation for more details. The prior approach of using the exclusions parameter in initJsPsych() is deprecated and will be removed in v8.0 . You can find the documentation for it in the 7.0 docs .","title":"Exclude Participants Based on Browser Features"},{"location":"overview/experiment-options/","text":"Experiment-wide settings \u00b6 There are several options that can be set when calling initJsPsych() to initialize the jsPsych experiment. Options are specified in the object passed to initJsPsych . For example, to specify a default inter-trial interval, a minimum valid response time duration, and a maximum width for all of the experiment's page content, the object would contain: initJsPsych ({ default_iti : 250 , minimum_valid_rt : 100 , experiment_width : 800 }); Controlling where jsPsych renders on the page \u00b6 By default, jsPsych will render the experiment in the <body> element of a page. It is possible to display the experiment in a different element (e.g., a <div> ) by specifying the display_element parameter. < body > < div id = \"jspsych-target\" ></ div > </ body > < script > initJsPsych ({ display_element : 'jspsych-target' }); </ script > This option is useful if the experiment needs to be rendered on a page with other content (e.g., a demo version of the experiment with annotation text), or if additional control over the display element is desired. Custom CSS rules can be applied to position, size, scale, etc. the display element. Experiment events \u00b6 Several experiment-wide events can trigger functions. This is documented in more detail on the event-related callback functions page . The events that trigger functions are: on_finish : Called at the end of the experiment. on_trial_start : Called at the beginning of every trial. on_trial_finish : Called at the end of every trial. on_data_update : Called whenever new data is added to the jsPsych data object. on_interaction_data_update : Called whenever new interaction data (e.g., the participant enters or exits fullscreen mode) is added. on_close : Called right before the page closes, such as when a participant closes the experiment early. Specify exclusion criteria \u00b6 Exclusion criteria can be specified based on features of the user's web browser, such as the display size and whether certain features are reported. See the page on excluding participants based on browser features . Display a progress bar \u00b6 An automatic or manually updated progress bar can be displayed at the top of the screen. By default, the text next to the progress bar is \"Completion Progress\", but this text can be changed with the message_progress_bar parameter in initJsPsych . See the progress bar page for more details. Choose the method for playing audio files \u00b6 Specifying the use_webaudio parameter in initJsPsych() allows you to choose whether to use the WebAudio API or HTML5 audio for playing audio files during your experiment. By default, jsPsych uses the WebAudio API to play audio files. Among other features, the WebAudio API allows for more precise measurement of response times relative to the onset of the audio. However, loading files through the WebAudio API causes errors when running an experiment offline (i.e., by double-clicking on the HTML file, rather than hosting it on a web server). This is due to the cross-origin security policy implemented by web browsers. For this reason, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline, and automatically uses HTML5 audio to prevent errors, even when use_webaudio has been explicitly set to true . For more information, see the section Cross-origin requests (CORS) and safe mode on the Running Experiments page. initJsPsych ({ use_webaudio : false }); Set the default intertrial interval \u00b6 By default the next trial in a timeline will begin immediately after the conclusion of the previous trial. An experiment-wide delay can be specified using the default_iti parameter to initJsPsych() . initJsPsych ({ default_iti : 500 }); This parameter is specified in milliseconds. A blank screen will display between each trial for the duration of the ITI. Specify the maximum width of the experiment \u00b6 The experiment will, by default, take up 100% of the display element. Usually the display element is the <body> , and the experiment is the full width of the screen. (This can be overridden by specifying the display_element parameter described above). Specifying the experiment_width parameter will set a maximum width for the display. The parameter is specified in pixels. initJsPsych ({ experiment_width : 750 }); Specify a minimum valid response time \u00b6 By default, jsPsych will treat any keyboard response time as valid. However, it's possible to specify a minimum valid response time (in ms) for key presses. Any key press that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to keyboard responses , and not to other response types such as buttons and sliders. The default value is 0. // ignore any keyboard responses that are less than 100 ms initJsPsych ({ minimum_valid_rt : 100 }); Choose whether you want keyboard choices/responses to be case-sensitive \u00b6 JavaScript keyboard events make a distinction between uppercase and lowercase key responses (e.g. 'a' and 'A'). Often the researcher just cares about which physical key was pressed, and not whether the key press would result in an uppercase letter (for instance, if CapsLock is on or if the Shift key is held down). For this reason, jsPsych converts all key choice parameters and key responses as lowercase by default. This makes it easier to specify key choices (e.g. choices: ['a'] , instead of choices: ['a','A'] ), and it makes it easier to check and score a participant's response. There may be situations when you want key choices and responses to be case-sensitive. You can change this by setting the case_sensitive_responses parameter to true in initJsPsych . // use case-sensitive key choices and responses, // i.e. uppercase and lower case letters ('a' and 'A') will be treated as different key choices, // and will be recorded this way in the data initJsPsych ({ case_sensitive_responses : true }); Note that this setting only applies to key choices and responses that use jsPsych's keyboard response listener, such as in the * -keyboard-response plugins. This does NOT apply to responses that are made by typing into a text box, such as in the survey-text and cloze plugins. Override 'safe mode' when running experiments offline \u00b6 By default, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline (via the file:// protocol) in order to prevent certain errors. Specifically, in safe mode, HTML5 audio is used to play audio files (even when use_webaudio has been explicitly set to true ) and video preloading is disabled (both automatic and manual preloading). For more information, see the Cross-origin requests (CORS) and safe mode section on the Running Experiments page. It's possible to override this safe mode feature by setting the override_safe_mode parameter to true in initJsPsych . This is something you might do if you've disabled certain security settings in your browser for testing purposes. This parameter has no effect when your experiment is running online (on a server), because it will be using the http:// or https:// protocol, which does not trigger safe mode. initJsPsych ({ override_safe_mode : true }); Add extensions \u00b6 Extensions are jsPsych modules that can run throughout the experiment and interface with any plugin to extend the functionality of the plugin. One example of an extension is eye tracking, which allows you to gather gaze data during any trial and add it to that trial's data object. If you want to use extensions in your experiment, you must specify this when you initialize the experiment with initJsPsych . The extensions parameter in initJsPsych is an array of objects, where each object specifies the extension that you'd like to use in the experiment. Below is an example of adding the webgazer extension. initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] });","title":"Experiment Settings"},{"location":"overview/experiment-options/#experiment-wide-settings","text":"There are several options that can be set when calling initJsPsych() to initialize the jsPsych experiment. Options are specified in the object passed to initJsPsych . For example, to specify a default inter-trial interval, a minimum valid response time duration, and a maximum width for all of the experiment's page content, the object would contain: initJsPsych ({ default_iti : 250 , minimum_valid_rt : 100 , experiment_width : 800 });","title":"Experiment-wide settings"},{"location":"overview/experiment-options/#controlling-where-jspsych-renders-on-the-page","text":"By default, jsPsych will render the experiment in the <body> element of a page. It is possible to display the experiment in a different element (e.g., a <div> ) by specifying the display_element parameter. < body > < div id = \"jspsych-target\" ></ div > </ body > < script > initJsPsych ({ display_element : 'jspsych-target' }); </ script > This option is useful if the experiment needs to be rendered on a page with other content (e.g., a demo version of the experiment with annotation text), or if additional control over the display element is desired. Custom CSS rules can be applied to position, size, scale, etc. the display element.","title":"Controlling where jsPsych renders on the page"},{"location":"overview/experiment-options/#experiment-events","text":"Several experiment-wide events can trigger functions. This is documented in more detail on the event-related callback functions page . The events that trigger functions are: on_finish : Called at the end of the experiment. on_trial_start : Called at the beginning of every trial. on_trial_finish : Called at the end of every trial. on_data_update : Called whenever new data is added to the jsPsych data object. on_interaction_data_update : Called whenever new interaction data (e.g., the participant enters or exits fullscreen mode) is added. on_close : Called right before the page closes, such as when a participant closes the experiment early.","title":"Experiment events"},{"location":"overview/experiment-options/#specify-exclusion-criteria","text":"Exclusion criteria can be specified based on features of the user's web browser, such as the display size and whether certain features are reported. See the page on excluding participants based on browser features .","title":"Specify exclusion criteria"},{"location":"overview/experiment-options/#display-a-progress-bar","text":"An automatic or manually updated progress bar can be displayed at the top of the screen. By default, the text next to the progress bar is \"Completion Progress\", but this text can be changed with the message_progress_bar parameter in initJsPsych . See the progress bar page for more details.","title":"Display a progress bar"},{"location":"overview/experiment-options/#choose-the-method-for-playing-audio-files","text":"Specifying the use_webaudio parameter in initJsPsych() allows you to choose whether to use the WebAudio API or HTML5 audio for playing audio files during your experiment. By default, jsPsych uses the WebAudio API to play audio files. Among other features, the WebAudio API allows for more precise measurement of response times relative to the onset of the audio. However, loading files through the WebAudio API causes errors when running an experiment offline (i.e., by double-clicking on the HTML file, rather than hosting it on a web server). This is due to the cross-origin security policy implemented by web browsers. For this reason, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline, and automatically uses HTML5 audio to prevent errors, even when use_webaudio has been explicitly set to true . For more information, see the section Cross-origin requests (CORS) and safe mode on the Running Experiments page. initJsPsych ({ use_webaudio : false });","title":"Choose the method for playing audio files"},{"location":"overview/experiment-options/#set-the-default-intertrial-interval","text":"By default the next trial in a timeline will begin immediately after the conclusion of the previous trial. An experiment-wide delay can be specified using the default_iti parameter to initJsPsych() . initJsPsych ({ default_iti : 500 }); This parameter is specified in milliseconds. A blank screen will display between each trial for the duration of the ITI.","title":"Set the default intertrial interval"},{"location":"overview/experiment-options/#specify-the-maximum-width-of-the-experiment","text":"The experiment will, by default, take up 100% of the display element. Usually the display element is the <body> , and the experiment is the full width of the screen. (This can be overridden by specifying the display_element parameter described above). Specifying the experiment_width parameter will set a maximum width for the display. The parameter is specified in pixels. initJsPsych ({ experiment_width : 750 });","title":"Specify the maximum width of the experiment"},{"location":"overview/experiment-options/#specify-a-minimum-valid-response-time","text":"By default, jsPsych will treat any keyboard response time as valid. However, it's possible to specify a minimum valid response time (in ms) for key presses. Any key press that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to keyboard responses , and not to other response types such as buttons and sliders. The default value is 0. // ignore any keyboard responses that are less than 100 ms initJsPsych ({ minimum_valid_rt : 100 });","title":"Specify a minimum valid response time"},{"location":"overview/experiment-options/#choose-whether-you-want-keyboard-choicesresponses-to-be-case-sensitive","text":"JavaScript keyboard events make a distinction between uppercase and lowercase key responses (e.g. 'a' and 'A'). Often the researcher just cares about which physical key was pressed, and not whether the key press would result in an uppercase letter (for instance, if CapsLock is on or if the Shift key is held down). For this reason, jsPsych converts all key choice parameters and key responses as lowercase by default. This makes it easier to specify key choices (e.g. choices: ['a'] , instead of choices: ['a','A'] ), and it makes it easier to check and score a participant's response. There may be situations when you want key choices and responses to be case-sensitive. You can change this by setting the case_sensitive_responses parameter to true in initJsPsych . // use case-sensitive key choices and responses, // i.e. uppercase and lower case letters ('a' and 'A') will be treated as different key choices, // and will be recorded this way in the data initJsPsych ({ case_sensitive_responses : true }); Note that this setting only applies to key choices and responses that use jsPsych's keyboard response listener, such as in the * -keyboard-response plugins. This does NOT apply to responses that are made by typing into a text box, such as in the survey-text and cloze plugins.","title":"Choose whether you want keyboard choices/responses to be case-sensitive"},{"location":"overview/experiment-options/#override-safe-mode-when-running-experiments-offline","text":"By default, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline (via the file:// protocol) in order to prevent certain errors. Specifically, in safe mode, HTML5 audio is used to play audio files (even when use_webaudio has been explicitly set to true ) and video preloading is disabled (both automatic and manual preloading). For more information, see the Cross-origin requests (CORS) and safe mode section on the Running Experiments page. It's possible to override this safe mode feature by setting the override_safe_mode parameter to true in initJsPsych . This is something you might do if you've disabled certain security settings in your browser for testing purposes. This parameter has no effect when your experiment is running online (on a server), because it will be using the http:// or https:// protocol, which does not trigger safe mode. initJsPsych ({ override_safe_mode : true });","title":"Override 'safe mode' when running experiments offline"},{"location":"overview/experiment-options/#add-extensions","text":"Extensions are jsPsych modules that can run throughout the experiment and interface with any plugin to extend the functionality of the plugin. One example of an extension is eye tracking, which allows you to gather gaze data during any trial and add it to that trial's data object. If you want to use extensions in your experiment, you must specify this when you initialize the experiment with initJsPsych . The extensions parameter in initJsPsych is an array of objects, where each object specifies the extension that you'd like to use in the experiment. Below is an example of adding the webgazer extension. initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] });","title":"Add extensions"},{"location":"overview/extensions/","text":"Extensions \u00b6 Extensions are jsPsych modules that can interface with any plugin to extend the functionality of the plugin. A canonical example of an extension is eye tracking. An eye tracking extension allows a plugin to gather gaze data and add it to the plugin's data object. Using an Extension \u00b6 To use an extension in an experiment, you'll load the extension file via a <script> tag (just like adding a plugin) and then initialize the extension in the parameters of initJsPsych() . < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-example@1.0.0\" ></ script > </ head > initJsPsych ({ extensions : [ { type : jsPsychExtensionExample , params : {...} } ] }) To enable an extension during a trial, add the extension to the extensions list for the trial. Some extensions may also support or require an object of parameters to configure the extension: var trial = { extensions : [ { type : jsPsychExtensionExample , params : {...} } ] } List of Extensions \u00b6 Extension Description jspsych\u2011ext\u2011webgazer.js Enables eye tracking using the WebGazer library. Writing an Extension \u00b6 See our developer's guide for extensions for information about how to create a new extension.","title":"Extensions"},{"location":"overview/extensions/#extensions","text":"Extensions are jsPsych modules that can interface with any plugin to extend the functionality of the plugin. A canonical example of an extension is eye tracking. An eye tracking extension allows a plugin to gather gaze data and add it to the plugin's data object.","title":"Extensions"},{"location":"overview/extensions/#using-an-extension","text":"To use an extension in an experiment, you'll load the extension file via a <script> tag (just like adding a plugin) and then initialize the extension in the parameters of initJsPsych() . < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-example@1.0.0\" ></ script > </ head > initJsPsych ({ extensions : [ { type : jsPsychExtensionExample , params : {...} } ] }) To enable an extension during a trial, add the extension to the extensions list for the trial. Some extensions may also support or require an object of parameters to configure the extension: var trial = { extensions : [ { type : jsPsychExtensionExample , params : {...} } ] }","title":"Using an Extension"},{"location":"overview/extensions/#list-of-extensions","text":"Extension Description jspsych\u2011ext\u2011webgazer.js Enables eye tracking using the WebGazer library.","title":"List of Extensions"},{"location":"overview/extensions/#writing-an-extension","text":"See our developer's guide for extensions for information about how to create a new extension.","title":"Writing an Extension"},{"location":"overview/eye-tracking/","text":"Eye Tracking \u00b6 jsPsych supports eye tracking through the WebGazer library. WebGazer uses computer vision techniques to identify features of the participant's eyes via a webcam and predicts gaze location. The system is calibrated by having the participant click on or look at known locations on the screen. These locations are linked to eye features. Gaze location is predicted using regression. Getting Started \u00b6 Load webgazer.js \u00b6 The official version of WebGazer is currently not supported by jsPsych. Our fork of the library contains some minor improvements aimed at the kind of experiments that jsPsych is typically used for, e.g., situations in which the timing of display screens needs to be accurate. You must include the webgazer.js file in your experiment via a <script> tag. However, the webgazer.js file is not part of any of the jsPsych NPM packages and is therefore not available via the unpkg.com CDN. Instead, it can be found on the jsdelivr.net CDN at: \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\". < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > </ head > Note A copy of our forked webgazer.js file is also included in the jsPsych release, in the /examples/js/webgazer folder. So if you prefer to download and host all of your jsPsych files (i.e. set-up option 2 in the Hello World tutorial), then another option is to load that file rather than using the jsdelivr link above. Assuming you downloaded the release and copied the webgazer.js file into a folder called js/webgazer in your root project directory, then you would load the file like this: < script src = \"js/webgazer/webgazer.js\" ></ script > Load the jsPsych webgazer extension \u00b6 The webgazer extension adds functionality to jsPsych for interacting with webgazer. Load it like you would a plugin file. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-webgazer@1.0.2\" ></ script > </ head > To use the WebGazer extension in an experiment, include it in the list of extensions passed to initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }) Initialize the camera \u00b6 To help the participant position their face correctly for eye tracking you can use the webgazer-init-camera plugin . This will show the participant what the camera sees, including facial feature landmarks, and prevent the participant from continuing until their face is in good position for eye tracking. This plugin will also trigger the experiment to request permission to access the user's webcam if it hasn't already been granted. var init_camera_trial = { type : jsPsychWebgazerInitCamera } Calibration \u00b6 To calibrate WebGazer, you can use the webgazer-calibrate plugin . This plugin allows you to specify a set of points on the screen for calibration and to choose the method for calibrating -- either clicking on each point or simply fixating on each point. The location of calibration points is specified in percentages, e.g., [25,50] will result in a point that is 25% of the width of the screen from the left edge and 50% of the height of the screen from the top edge. Options for controlling other details of the calibration are explained in the documentation for the plugin . Note that instructions are not included in the calibration plugin, so you'll likely want to use a different plugin (e.g., html-button-response ) to display instructions prior to running the calibration. var calibration_trial = { type : jsPsychWebgazerCalibrate , calibration_points : [[ 25 , 50 ], [ 50 , 50 ], [ 75 , 50 ], [ 50 , 25 ], [ 50 , 75 ]], calibration_mode : 'click' } Validation \u00b6 To measure the accuracy and precision of the calibration, you can use the webgazer-vaidate plugin . Like the calibration plugin, you can specify a list of points to perform validation on. Here you can specify the points as either percentages or in terms of the distance from the center of the screen in pixels. Which mode you use will probably depend on how you are defining your stimuli throughout the experiment. You can also specify the radius of tolerance around each point, and the plugin will calculate the percentage of measured gaze samples within that radius. This is a potentially useful heuristic for deciding whether or not to calibrate again. Options for controlling other details of the validation are explained in the documentation for the plugin . var validation_trial = { type : jsPsychWebgazerValidate , validation_points : [[ - 200 , 200 ], [ 200 , 200 ],[ - 200 , - 200 ],[ 200 , - 200 ]], validation_point_coordinates : 'center-offset-pixels' , roi_radius : 100 } The validation procedure stores the raw gaze data for each validation point, the computed average offset from each validation point, the percentage of samples within the roi_radius for each validation point, and the number of samples collected per second. { raw_gaze : [...], percent_in_roi : [...], average_offset : [...], samples_per_sec : ... } We recommend performing calibration and validation periodically throughout your experiment. Adding eye tracking to a trial \u00b6 To enable eye tracking for a trial in your experiment, you can simply add the WebGazer extension to the trial. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<img id=\"scene\" src=\"my-scene.png\"></img>' , extensions : [ { type : jsPsychExtensionWebgazer , params : { targets : [ '#scene' ] } } ] } This will turn on WebGazer at the start of the trial. The params property in the extensions declaration allows you to pass in a list of CSS selector strings . The bounding rectangle of the DOM element that matches each selector will be recorded in the data for that trial. This allows for easy alignment of the gaze data and objects on the screen. webgazer_targets : { 'selector' : { x : ..., y : ..., height : ..., width : ..., top : ..., left : ..., right : ..., bottom : ...} 'selector' : { x : ..., y : ..., height : ..., width : ..., top : ..., left : ..., right : ..., bottom : ...} } Gaze data will be added to the trial's data under the property webgazer_data . The gaze data is an array of objects. Each object has an x , a y , and a t property. The x and y properties specify the gaze location in pixels and t specifies the time in milliseconds since the start of the trial. Note that establishing the precision and accuracy of these measurements across the variety of web browsers and systems that your experiment participants might be using is quite difficult. For example, different browsers may cause small systematic shifts in the accuracy of t values. webgazer_data : [ { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...} ] Tips for Improving Data Quality \u00b6 These are some anecdotal observations about factors that improve data quality. The quality of the camera feed is essential. Good lighting makes a big difference. You may want to encourage participants to perform any eye tracking experiments in a well-lit room. Participants need to keep their head relatively still during and after calibration. The calibration is not robust to head movements. WebGazer's click-based calibration can be used throughout the experiment. You can turn this on by calling jsPsych.extensions.webgazer.startMouseCalibration() at any point in the experiment. If you use a continue button to advance through the experiment and move the location of the continue button around you can be making small adjustments to the calibration throughout. Computing the gaze predictions consumes more computational resources than most other things that jsPsych is typically used for. The sampling rate that WebGazer is able to achieve will depend on the computing power of the participant's device. You may want to ask the participant to close any non-essential software and browser windows prior to completing the experiment. You may also want to check that the sampling rate is sufficiently high as part of validation. If you have tips based on your own experience please consider sharing them on our discussion forum and we'll add to this list! Example \u00b6 Tip Additional example experiments using WebGazer are available in the /examples folder of the jsPsych release. See webgazer.html , webgazer_image.html , and webgazer_audio.html . Example Here's an example of putting all of the pieces above together. This example also shows how to use data from the validation to decide whether or not to recalibrate. You can try this experiment here (opens in new tab) . <!DOCTYPE html> < html > < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.2\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-webgazer@1.0.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" /> < style > . jspsych-btn { margin-bottom : 10 px ; } </ style > </ head > < body ></ body > < script > var jsPsych = initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }); var preload = { type : jsPsychPreload , images : [ 'img/blue.png' ] } var camera_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>In order to participate you must allow the experiment to use your camera.</p> <p>You will be prompted to do this on the next screen.</p> <p>If you do not wish to allow use of your camera, you cannot participate in this experiment.<p> <p>It may take up to 30 seconds for the camera to initialize after you give permission.</p> ` , choices : [ 'Got it' ], } var init_camera = { type : jsPsychWebgazerInitCamera } var calibration_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Now you'll calibrate the eye tracking, so that the software can use the image of your eyes to predict where you are looking.</p> <p>You'll see a series of dots appear on the screen. Look at each dot and click on it.</p> ` , choices : [ 'Got it' ], } var calibration = { type : jsPsychWebgazerCalibrate , calibration_points : [ [ 25 , 25 ],[ 75 , 25 ],[ 50 , 50 ],[ 25 , 75 ],[ 75 , 75 ] ], repetitions_per_point : 2 , randomize_calibration_order : true } var validation_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Now we'll measure the accuracy of the calibration.</p> <p>Look at each dot as it appears on the screen.</p> <p style=\"font-weight: bold;\">You do not need to click on the dots this time.</p> ` , choices : [ 'Got it' ], post_trial_gap : 1000 } var validation = { type : jsPsychWebgazerValidate , validation_points : [ [ 25 , 25 ],[ 75 , 25 ],[ 50 , 50 ],[ 25 , 75 ],[ 75 , 75 ] ], roi_radius : 200 , time_to_saccade : 1000 , validation_duration : 2000 , data : { task : 'validate' } } var recalibrate_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>The accuracy of the calibration is a little lower than we'd like.</p> <p>Let's try calibrating one more time.</p> <p>On the next screen, look at the dots and click on them.<p> ` , choices : [ 'OK' ], } var recalibrate = { timeline : [ recalibrate_instructions , calibration , validation_instructions , validation ], conditional_function : function (){ var validation_data = jsPsych . data . get (). filter ({ task : 'validate' }). values ()[ 0 ]; return validation_data . percent_in_roi . some ( function ( x ){ var minimum_percent_acceptable = 50 ; return x < minimum_percent_acceptable ; }); }, data : { phase : 'recalibration' } } var calibration_done = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Great, we're done with calibration!</p> ` , choices : [ 'OK' ] } var begin = { type : jsPsychHtmlKeyboardResponse , stimulus : `<p>The next screen will show an image to demonstrate adding the webgazer extension to a trial.</p> <p>Just look at the image while eye tracking data is collected. The trial will end automatically.</p> <p>Press any key to start.</p> ` } var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : \"NO_KEYS\" , trial_duration : 2000 , extensions : [ { type : jsPsychExtensionWebgazer , params : { targets : [ '#jspsych-image-keyboard-response-stimulus' ]} } ] } var show_data = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trial_data = jsPsych . data . getLastTrialData (). values (); var trial_json = JSON . stringify ( trial_data , null , 2 ); return `<p style=\"margin-bottom:0px;\"><strong>Trial data:</strong></p> <pre style=\"margin-top:0px;text-align:left;\"> ${ trial_json } </pre>` ; }, choices : \"NO_KEYS\" }; jsPsych . run ([ preload , camera_instructions , init_camera , calibration_instructions , calibration , validation_instructions , validation , recalibrate , calibration_done , begin , trial , show_data ]); </ script > </ html > Below is example data from the image-keyboard-response trial taken from the experiment above. In addition to the standard data that is collected for this plugin, you can see the additional webgazer_data and webgazer_targets arrays. The webgazer_data shows 21 gaze location estimates during the 1-second image presentation. The webgazer_targets array shows that there was one target, the image-keyboard-response stimulus, and tells you the x- and y-coordinate boundaries for the target (image) rectangle. By comparing each of the x/y locations from the webgazer_data locations array with the target boundaries in webgazer_targets , you can determine if/when the estimated gaze location was inside the target area. { \"rt\" : null , \"stimulus\" : \"img/blue.png\" , \"response\" : null , \"trial_type\" : \"image-keyboard-response\" , \"trial_index\" : 4 , \"time_elapsed\" : 30701 , \"internal_node_id\" : \"0.0-4.0\" , \"webgazer_data\" : [ { \"x\" : 1065 , \"y\" : 437 , \"t\" : 39 }, { \"x\" : 943 , \"y\" : 377 , \"t\" : 79 }, { \"x\" : 835 , \"y\" : 332 , \"t\" : 110 }, { \"x\" : 731 , \"y\" : 299 , \"t\" : 146 }, { \"x\" : 660 , \"y\" : 271 , \"t\" : 189 }, { \"x\" : 606 , \"y\" : 251 , \"t\" : 238 }, { \"x\" : 582 , \"y\" : 213 , \"t\" : 288 }, { \"x\" : 551 , \"y\" : 200 , \"t\" : 335 }, { \"x\" : 538 , \"y\" : 183 , \"t\" : 394 }, { \"x\" : 514 , \"y\" : 177 , \"t\" : 436 }, { \"x\" : 500 , \"y\" : 171 , \"t\" : 493 }, { \"x\" : 525 , \"y\" : 178 , \"t\" : 542 }, { \"x\" : 537 , \"y\" : 182 , \"t\" : 592 }, { \"x\" : 543 , \"y\" : 178 , \"t\" : 633 }, { \"x\" : 547 , \"y\" : 177 , \"t\" : 691 }, { \"x\" : 558 , \"y\" : 174 , \"t\" : 739 }, { \"x\" : 574 , \"y\" : 183 , \"t\" : 789 }, { \"x\" : 577 , \"y\" : 197 , \"t\" : 838 }, { \"x\" : 584 , \"y\" : 214 , \"t\" : 889 }, { \"x\" : 603 , \"y\" : 218 , \"t\" : 937 }, { \"x\" : 606 , \"y\" : 221 , \"t\" : 987 } ], \"webgazer_targets\" : [ \"#jspsych-image-keyboard-response-stimulus\" : { \"x\" : 490 , \"y\" : 135 , \"height\" : 300 , \"width\" : 300 , \"top\" : 135 , \"bottom\" : 435 , \"left\" : 490 , \"right\" : 790 } ] }","title":"Eye Tracking"},{"location":"overview/eye-tracking/#eye-tracking","text":"jsPsych supports eye tracking through the WebGazer library. WebGazer uses computer vision techniques to identify features of the participant's eyes via a webcam and predicts gaze location. The system is calibrated by having the participant click on or look at known locations on the screen. These locations are linked to eye features. Gaze location is predicted using regression.","title":"Eye Tracking"},{"location":"overview/eye-tracking/#getting-started","text":"","title":"Getting Started"},{"location":"overview/eye-tracking/#load-webgazerjs","text":"The official version of WebGazer is currently not supported by jsPsych. Our fork of the library contains some minor improvements aimed at the kind of experiments that jsPsych is typically used for, e.g., situations in which the timing of display screens needs to be accurate. You must include the webgazer.js file in your experiment via a <script> tag. However, the webgazer.js file is not part of any of the jsPsych NPM packages and is therefore not available via the unpkg.com CDN. Instead, it can be found on the jsdelivr.net CDN at: \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\". < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > </ head > Note A copy of our forked webgazer.js file is also included in the jsPsych release, in the /examples/js/webgazer folder. So if you prefer to download and host all of your jsPsych files (i.e. set-up option 2 in the Hello World tutorial), then another option is to load that file rather than using the jsdelivr link above. Assuming you downloaded the release and copied the webgazer.js file into a folder called js/webgazer in your root project directory, then you would load the file like this: < script src = \"js/webgazer/webgazer.js\" ></ script >","title":"Load webgazer.js"},{"location":"overview/eye-tracking/#load-the-jspsych-webgazer-extension","text":"The webgazer extension adds functionality to jsPsych for interacting with webgazer. Load it like you would a plugin file. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-webgazer@1.0.2\" ></ script > </ head > To use the WebGazer extension in an experiment, include it in the list of extensions passed to initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] })","title":"Load the jsPsych webgazer extension"},{"location":"overview/eye-tracking/#initialize-the-camera","text":"To help the participant position their face correctly for eye tracking you can use the webgazer-init-camera plugin . This will show the participant what the camera sees, including facial feature landmarks, and prevent the participant from continuing until their face is in good position for eye tracking. This plugin will also trigger the experiment to request permission to access the user's webcam if it hasn't already been granted. var init_camera_trial = { type : jsPsychWebgazerInitCamera }","title":"Initialize the camera"},{"location":"overview/eye-tracking/#calibration","text":"To calibrate WebGazer, you can use the webgazer-calibrate plugin . This plugin allows you to specify a set of points on the screen for calibration and to choose the method for calibrating -- either clicking on each point or simply fixating on each point. The location of calibration points is specified in percentages, e.g., [25,50] will result in a point that is 25% of the width of the screen from the left edge and 50% of the height of the screen from the top edge. Options for controlling other details of the calibration are explained in the documentation for the plugin . Note that instructions are not included in the calibration plugin, so you'll likely want to use a different plugin (e.g., html-button-response ) to display instructions prior to running the calibration. var calibration_trial = { type : jsPsychWebgazerCalibrate , calibration_points : [[ 25 , 50 ], [ 50 , 50 ], [ 75 , 50 ], [ 50 , 25 ], [ 50 , 75 ]], calibration_mode : 'click' }","title":"Calibration"},{"location":"overview/eye-tracking/#validation","text":"To measure the accuracy and precision of the calibration, you can use the webgazer-vaidate plugin . Like the calibration plugin, you can specify a list of points to perform validation on. Here you can specify the points as either percentages or in terms of the distance from the center of the screen in pixels. Which mode you use will probably depend on how you are defining your stimuli throughout the experiment. You can also specify the radius of tolerance around each point, and the plugin will calculate the percentage of measured gaze samples within that radius. This is a potentially useful heuristic for deciding whether or not to calibrate again. Options for controlling other details of the validation are explained in the documentation for the plugin . var validation_trial = { type : jsPsychWebgazerValidate , validation_points : [[ - 200 , 200 ], [ 200 , 200 ],[ - 200 , - 200 ],[ 200 , - 200 ]], validation_point_coordinates : 'center-offset-pixels' , roi_radius : 100 } The validation procedure stores the raw gaze data for each validation point, the computed average offset from each validation point, the percentage of samples within the roi_radius for each validation point, and the number of samples collected per second. { raw_gaze : [...], percent_in_roi : [...], average_offset : [...], samples_per_sec : ... } We recommend performing calibration and validation periodically throughout your experiment.","title":"Validation"},{"location":"overview/eye-tracking/#adding-eye-tracking-to-a-trial","text":"To enable eye tracking for a trial in your experiment, you can simply add the WebGazer extension to the trial. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<img id=\"scene\" src=\"my-scene.png\"></img>' , extensions : [ { type : jsPsychExtensionWebgazer , params : { targets : [ '#scene' ] } } ] } This will turn on WebGazer at the start of the trial. The params property in the extensions declaration allows you to pass in a list of CSS selector strings . The bounding rectangle of the DOM element that matches each selector will be recorded in the data for that trial. This allows for easy alignment of the gaze data and objects on the screen. webgazer_targets : { 'selector' : { x : ..., y : ..., height : ..., width : ..., top : ..., left : ..., right : ..., bottom : ...} 'selector' : { x : ..., y : ..., height : ..., width : ..., top : ..., left : ..., right : ..., bottom : ...} } Gaze data will be added to the trial's data under the property webgazer_data . The gaze data is an array of objects. Each object has an x , a y , and a t property. The x and y properties specify the gaze location in pixels and t specifies the time in milliseconds since the start of the trial. Note that establishing the precision and accuracy of these measurements across the variety of web browsers and systems that your experiment participants might be using is quite difficult. For example, different browsers may cause small systematic shifts in the accuracy of t values. webgazer_data : [ { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...} ]","title":"Adding eye tracking to a trial"},{"location":"overview/eye-tracking/#tips-for-improving-data-quality","text":"These are some anecdotal observations about factors that improve data quality. The quality of the camera feed is essential. Good lighting makes a big difference. You may want to encourage participants to perform any eye tracking experiments in a well-lit room. Participants need to keep their head relatively still during and after calibration. The calibration is not robust to head movements. WebGazer's click-based calibration can be used throughout the experiment. You can turn this on by calling jsPsych.extensions.webgazer.startMouseCalibration() at any point in the experiment. If you use a continue button to advance through the experiment and move the location of the continue button around you can be making small adjustments to the calibration throughout. Computing the gaze predictions consumes more computational resources than most other things that jsPsych is typically used for. The sampling rate that WebGazer is able to achieve will depend on the computing power of the participant's device. You may want to ask the participant to close any non-essential software and browser windows prior to completing the experiment. You may also want to check that the sampling rate is sufficiently high as part of validation. If you have tips based on your own experience please consider sharing them on our discussion forum and we'll add to this list!","title":"Tips for Improving Data Quality"},{"location":"overview/eye-tracking/#example","text":"Tip Additional example experiments using WebGazer are available in the /examples folder of the jsPsych release. See webgazer.html , webgazer_image.html , and webgazer_audio.html . Example Here's an example of putting all of the pieces above together. This example also shows how to use data from the validation to decide whether or not to recalibrate. You can try this experiment here (opens in new tab) . <!DOCTYPE html> < html > < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.2\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-webgazer@1.0.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" /> < style > . jspsych-btn { margin-bottom : 10 px ; } </ style > </ head > < body ></ body > < script > var jsPsych = initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }); var preload = { type : jsPsychPreload , images : [ 'img/blue.png' ] } var camera_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>In order to participate you must allow the experiment to use your camera.</p> <p>You will be prompted to do this on the next screen.</p> <p>If you do not wish to allow use of your camera, you cannot participate in this experiment.<p> <p>It may take up to 30 seconds for the camera to initialize after you give permission.</p> ` , choices : [ 'Got it' ], } var init_camera = { type : jsPsychWebgazerInitCamera } var calibration_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Now you'll calibrate the eye tracking, so that the software can use the image of your eyes to predict where you are looking.</p> <p>You'll see a series of dots appear on the screen. Look at each dot and click on it.</p> ` , choices : [ 'Got it' ], } var calibration = { type : jsPsychWebgazerCalibrate , calibration_points : [ [ 25 , 25 ],[ 75 , 25 ],[ 50 , 50 ],[ 25 , 75 ],[ 75 , 75 ] ], repetitions_per_point : 2 , randomize_calibration_order : true } var validation_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Now we'll measure the accuracy of the calibration.</p> <p>Look at each dot as it appears on the screen.</p> <p style=\"font-weight: bold;\">You do not need to click on the dots this time.</p> ` , choices : [ 'Got it' ], post_trial_gap : 1000 } var validation = { type : jsPsychWebgazerValidate , validation_points : [ [ 25 , 25 ],[ 75 , 25 ],[ 50 , 50 ],[ 25 , 75 ],[ 75 , 75 ] ], roi_radius : 200 , time_to_saccade : 1000 , validation_duration : 2000 , data : { task : 'validate' } } var recalibrate_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>The accuracy of the calibration is a little lower than we'd like.</p> <p>Let's try calibrating one more time.</p> <p>On the next screen, look at the dots and click on them.<p> ` , choices : [ 'OK' ], } var recalibrate = { timeline : [ recalibrate_instructions , calibration , validation_instructions , validation ], conditional_function : function (){ var validation_data = jsPsych . data . get (). filter ({ task : 'validate' }). values ()[ 0 ]; return validation_data . percent_in_roi . some ( function ( x ){ var minimum_percent_acceptable = 50 ; return x < minimum_percent_acceptable ; }); }, data : { phase : 'recalibration' } } var calibration_done = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Great, we're done with calibration!</p> ` , choices : [ 'OK' ] } var begin = { type : jsPsychHtmlKeyboardResponse , stimulus : `<p>The next screen will show an image to demonstrate adding the webgazer extension to a trial.</p> <p>Just look at the image while eye tracking data is collected. The trial will end automatically.</p> <p>Press any key to start.</p> ` } var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : \"NO_KEYS\" , trial_duration : 2000 , extensions : [ { type : jsPsychExtensionWebgazer , params : { targets : [ '#jspsych-image-keyboard-response-stimulus' ]} } ] } var show_data = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trial_data = jsPsych . data . getLastTrialData (). values (); var trial_json = JSON . stringify ( trial_data , null , 2 ); return `<p style=\"margin-bottom:0px;\"><strong>Trial data:</strong></p> <pre style=\"margin-top:0px;text-align:left;\"> ${ trial_json } </pre>` ; }, choices : \"NO_KEYS\" }; jsPsych . run ([ preload , camera_instructions , init_camera , calibration_instructions , calibration , validation_instructions , validation , recalibrate , calibration_done , begin , trial , show_data ]); </ script > </ html > Below is example data from the image-keyboard-response trial taken from the experiment above. In addition to the standard data that is collected for this plugin, you can see the additional webgazer_data and webgazer_targets arrays. The webgazer_data shows 21 gaze location estimates during the 1-second image presentation. The webgazer_targets array shows that there was one target, the image-keyboard-response stimulus, and tells you the x- and y-coordinate boundaries for the target (image) rectangle. By comparing each of the x/y locations from the webgazer_data locations array with the target boundaries in webgazer_targets , you can determine if/when the estimated gaze location was inside the target area. { \"rt\" : null , \"stimulus\" : \"img/blue.png\" , \"response\" : null , \"trial_type\" : \"image-keyboard-response\" , \"trial_index\" : 4 , \"time_elapsed\" : 30701 , \"internal_node_id\" : \"0.0-4.0\" , \"webgazer_data\" : [ { \"x\" : 1065 , \"y\" : 437 , \"t\" : 39 }, { \"x\" : 943 , \"y\" : 377 , \"t\" : 79 }, { \"x\" : 835 , \"y\" : 332 , \"t\" : 110 }, { \"x\" : 731 , \"y\" : 299 , \"t\" : 146 }, { \"x\" : 660 , \"y\" : 271 , \"t\" : 189 }, { \"x\" : 606 , \"y\" : 251 , \"t\" : 238 }, { \"x\" : 582 , \"y\" : 213 , \"t\" : 288 }, { \"x\" : 551 , \"y\" : 200 , \"t\" : 335 }, { \"x\" : 538 , \"y\" : 183 , \"t\" : 394 }, { \"x\" : 514 , \"y\" : 177 , \"t\" : 436 }, { \"x\" : 500 , \"y\" : 171 , \"t\" : 493 }, { \"x\" : 525 , \"y\" : 178 , \"t\" : 542 }, { \"x\" : 537 , \"y\" : 182 , \"t\" : 592 }, { \"x\" : 543 , \"y\" : 178 , \"t\" : 633 }, { \"x\" : 547 , \"y\" : 177 , \"t\" : 691 }, { \"x\" : 558 , \"y\" : 174 , \"t\" : 739 }, { \"x\" : 574 , \"y\" : 183 , \"t\" : 789 }, { \"x\" : 577 , \"y\" : 197 , \"t\" : 838 }, { \"x\" : 584 , \"y\" : 214 , \"t\" : 889 }, { \"x\" : 603 , \"y\" : 218 , \"t\" : 937 }, { \"x\" : 606 , \"y\" : 221 , \"t\" : 987 } ], \"webgazer_targets\" : [ \"#jspsych-image-keyboard-response-stimulus\" : { \"x\" : 490 , \"y\" : 135 , \"height\" : 300 , \"width\" : 300 , \"top\" : 135 , \"bottom\" : 435 , \"left\" : 490 , \"right\" : 790 } ] }","title":"Example"},{"location":"overview/fullscreen/","text":"Fullscreen Experiments \u00b6 You can run your experiment in fullscreen mode by using the jspsych-fullscreen plugin. var jsPsych = initJsPsych (); var timeline = []; timeline . push ({ type : jsPsychFullscreen , fullscreen_mode : true }); timeline . push ({ type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will be in fullscreen mode.' }); // exit fullscreen mode timeline . push ({ type : jsPsychFullscreen , fullscreen_mode : false }); timeline . push ({ type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will NOT be in fullscreen mode.' }); jsPsych . run ( timeline ); For security reasons, web browsers require that users initiate an action to launch fullscreen mode. The fullscreen plugin displays a button that the user must click to change the display to fullscreen. Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari.","title":"Fullscreen Experiments"},{"location":"overview/fullscreen/#fullscreen-experiments","text":"You can run your experiment in fullscreen mode by using the jspsych-fullscreen plugin. var jsPsych = initJsPsych (); var timeline = []; timeline . push ({ type : jsPsychFullscreen , fullscreen_mode : true }); timeline . push ({ type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will be in fullscreen mode.' }); // exit fullscreen mode timeline . push ({ type : jsPsychFullscreen , fullscreen_mode : false }); timeline . push ({ type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will NOT be in fullscreen mode.' }); jsPsych . run ( timeline ); For security reasons, web browsers require that users initiate an action to launch fullscreen mode. The fullscreen plugin displays a button that the user must click to change the display to fullscreen. Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari.","title":"Fullscreen Experiments"},{"location":"overview/media-preloading/","text":"Media Preloading \u00b6 If an experiment uses image, audio, or video files as stimuli, it is a good idea to preload the files before running the experiment. You can preload files at any point in your experiment using the jsPsych preload plugin . Preloading files means that the participant's browser will download the files and store them in local memory on the participant's computer. This is important because displaying or playing a media file is much faster if it is already in memory on the participant's computer. Without preloading, there will be noticeable delays in the display of media, which will affect any timing measurements (such as how long an image is displayed, or a participant's response time since first viewing an image). For particularly large files, like video, preloading content avoids lengthy pauses in the middle of the experiment that can be disruptive to the flow of the experiment. Warning Note that video preloading will not work when you run your experiment offline (e.g., by double-clicking on the HTML file), but it will work once your experiment is running online (hosted on a server). The Cross-origin requests (CORS) and safe mode section on the Running Experiments page contains more information about this. Automatic Preloading \u00b6 jsPsych can automatically preload audio, video, and image files that are used as parameters for the standard set of plugins, based on the timeline that is passed to jsPsych.run . You must initiate this preloading using a preload trial. You should add this preload trial into your timeline when you want the preloading to occur, and set the auto_preload parameter to true . // the \"auto_preload: true\" setting tells the plugin to automatically find // stimuli to preload based the main experiment timeline (used in jsPsych.run) var preload = { type : jsPsychPreload , auto_preload : true } // this image file can be automatically preloaded var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' } // the sound file can be automatically preloaded var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'audio/hello.mp3' } // the video file can be automatically preloaded (as long as the experiment // is running on a server) var video_trial = { type : jsPsychVideoKeyboardResponse , stimulus : [ 'video/sample_video.mp4' ] } jsPsych . run ([ preload , image_trial , sound_trial , video_trial ]); Manual preloading \u00b6 If you are using media files in your experiment but they are not being passed directly as parameters to the trials (e.g., because you are using functions as parameters that return the media files, you are using timeline variables, or you are embedding the media files in an HTML string), then these files will not be detected when you use the auto_preload option, so you must manually specify them. The preload plugin allows you to add these files using the images , audio and video parameters. // this image file cannot be automatically preloaded because it is embedded in // an HTML string var image_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<img src=\"img/file1.png\"></img>' , } // this audio file cannot be automatically preloaded because it is returned // from a function var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : function () { return 'audio/sound1.mp3' } } // these video files cannot be automatically preloaded because they are passed // into a trial using the jsPsych.timelineVariable function var video_trials = { timeline : [ { type : jsPsychVideoKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'video' ) } ], timeline_variables : [ { video : [ 'video/1.mp4' ]}, { video : [ 'video/2.mp4' ]} ] } // to manually preload media files, create an array of file paths for each // media type var images = [ 'img/file1.png' ]; var audio = [ 'audio/sound1.mp3' ]; var video = [ 'video/1.mp4' , 'video/2.mp4' ]; // these array can be passed into the preload plugin using the images, audio // and video parameters var preload = { type : jsPsychPreload , images : images , audio : audio , video : video } jsPsych . run ([ preload , image_trial , sound_trial , video_trials ]); Combining automatic and manual preloading \u00b6 It's possible to combine automatic and manual preloading. For instance, you may want to automatically preload all of the media files based on your experiment timeline, while also manually preloading any files that can't be automatically preloaded. Any duplicate file names across all preloading methods will be removed before preloading starts, so including the same file names in multiple preload parameters will not affect the preloading duration. // this file can be preloaded automatically var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' } // this file can be preloaded automatically var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'audio/hello.mp3' } // these files must be preloaded manually var video_trials = { timeline : [ { type : jsPsychVideoKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'video' ) } ], timeline_variables : [ { video : [ 'video/1.mp4' ]}, { video : [ 'video/2.mp4' ]} ] } var video = [ 'video/1.mp4' , 'video/2.mp4' ]; var preload = { type : jsPsychPreload , auto_preload : true , // automatically preload the image and audio files video : video // manually preload the videos used with timeline variables } jsPsych . run ([ preload , image_trial , sound_trial , video_trials ]); Preloading in batches \u00b6 Some experiments use many and/or large media files. This can cause problems when participants have slow and/or unreliable internet connections, because it increases the chances of loading errors during preloading. This can also cause problems with file caching, i.e. ensuring that the preloaded files remain in the browser's memory, because loading all stimuli at once may exceed the browser's cache limits. One option for mitigating these problems is to load the media files in smaller batches throughout the experiment. Files should be preloaded as close as possible to when they will be needed. For instance, if you have several blocks of trials, then right before each block, you can preload the stimuli that are needed for that block. Here is an example with trials where the stimuli files can be preloaded automatically. In this case, the trials parameter is used to tell the preload plugin to preload the stimuli from a specific part of the timeline. // these image files in these trial blocks can be automatically preloaded var block_1 = { timeline : [ { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' }, { type : jsPsychImageKeyboardResponse , stimulus : 'img/file2.png' } ] } var block_2 = { timeline : [ { type : jsPsychImageKeyboardResponse , stimulus : 'img/file3.png' }, { type : jsPsychImageKeyboardResponse , stimulus : 'img/file4.png' } ] } var preload_1 = { type : jsPsychPreload , trials : block_1 // automatically preload just the images from block_1 trials } var preload_2 = { type : jsPsychPreload , trials : block_2 // automatically preload just the images from block_2 trials } jsPsych . run ( // add each preload trial onto the timeline before the appropriate trial block [ preload_1 , block_1 , preload_2 , block_2 ] ); Below is an example with trials where the stimuli files cannot be preloaded automatically, because the stimuli files are passed to the trials via jsPsych.timelineVariable . In this case, we create separate arrays for each batch of files, and then pass those arrays to the each preload trial. // these trial blocks cannot be automatically preloaded because // the media files are passed to the trial parameters with timeline variables var block_1 = { timeline : [...], timeline_variables : [ { stim : 'file1.png' }, { stim : 'file1.png' } ] } var block_2 = { timeline : [...], timeline_variables : [ { stim : 'file3.png' }, { stim : 'file4.png' } ] } var images_block_1 = [ 'file1.png' , 'file2.png' ]; var images_block_2 = [ 'file3.png' , 'file4.png' ]; // preload trial for preloading the block 1 stimuli var preload_1 = { type : jsPsychPreload , images : images_block_1 } // preload trial for preloading the block 2 stimuli var preload_2 = { type : jsPsychPreload , images : images_block_2 } jsPsych . run ( // add each preload trial to the timeline before the appropriate trial block [ preload_1 , block_1 , preload_2 , block_2 ] ); Preloading progress bar \u00b6 By default, the preload plugin will display a progress bar while files are being preloaded. This progress bar represents all files that are being preloaded during the trial, regardless of whether the file is being preloaded automatically via the auto_preload or trials parameters, or manually via the audio , images , and video parameters. You may wish to turn the preload progress bar off if you are only loading a small number of files, as it will appear and disappear so quickly that the participant may be confused about what it was. You can control whether the preloading progress bar appears by setting the show_progress_bar parameter in the preload trial. var preload_trial = { type : jsPsychPreload , auto_preload : true show_progress_bar : false // hide progress bar } Loading time limits \u00b6 It's usually a good idea to set a time limit for file loading, to ensure that participants aren't waiting for an unreasonable amount of time. Time limits can be specified in milliseconds using the max_load_time parameter. If you set a loading time limit and all files haven't finished loading before this time, then the preload trial will either stop an error (if continue_after_error is false, the default) or the trial will end and the experiment will continue (if continue_after_error is true ). If max_load_time is null (the default), then there is no time limit. var preload_trial = { type : jsPsychPreload , auto_preload : true max_load_time : 60000 // 1 minute } Loading and error messages \u00b6 It's possible to specify custom messages to be shown on the page while the media files are loading, and in case of one or more file loading errors. The message parameter allows you to customize the loading message using an HML-formatted string. If show_progress_bar is true , then this message will be shown above the progress bar. var preload_trial = { type : jsPsychPreload , auto_preload : true message : 'Please wait while the experiment loads. This may take a few minutes.' , } A preloading error will occur when either (a) one or more files produces a loading error, and/or (b) all files have not finished loading before the max_load_time duration. The error_message parameter allows you to customize the messsage that's shown on the page in these cases. This message will only be shown if continue_after_error is false (the default). var preload_trial = { type : jsPsychPreload , auto_preload : true , error_message : 'The experiment failed to load. Please contact the researcher.' } In addition to the error_message parameter, it's also possible to show more detailed error messages on the page about any files that failed to load. You can control this with the show_detailed_errors parameter. Detailed error messages will appear below the general error message. This only applies if continue_after_error is false (the default). Detailed error messages can be useful when testing and debugging your experiment. If show_detailed_errors is true , then if one or more loading errors occurs before the max_load_time is reached, then the error page will also contian a list of the file(s) that produced an error, along with error information (if there is any). Note that this may not be a complete list, because it will only report any errors that occurred before the max_load_time was reached. If there are no file loading errors but preloading hasn't finished before the max_load_time , then detailed error message will just tell you that loading timed out. var preload_trial = { type : jsPsychPreload , auto_preload : true , // show details of any file loading errors and/or loading time out show_detailed_errors : true } Options for handling errors \u00b6 If continue_after_error is true , then the experiment will not stop if one or more files fails to load. Instead, the trial will end and the experiment will continue. However, the preload trial data will contain a property called success , which is whether or not all files were loaded successfully, timeout , which is whether or not the files loaded successfully before the max_load_time . The preload trial data will also contain lists of any image , audio , and video files that failed to load. This gives you the option to continue the experiment after preloading fails and use the preload trial data decide what to do next. For instance, you may decide to skip the trials that use the stimuli files that failed to load, or try loading the failed files again. Another option is to simply end the experiment when preloading fails, but send the data back to your server so that you have more information about the loading failure. var preload_trial = { type : jsPsychPreload , auto_preload : true , message : 'Please wait while the experiment loads...' , // don't stop the experiment if there are file loading errors or if loading times out continue_after_error : true } var save_data = { type : jsPsychCallFunction , async : true , func : function ( done ){ var data = jsPsych . data . get (). json (); save_data ( data , function () { done ()}) } } // the experiment will stop here, since there are no valid key choices or trial duration var fail_message = { type : jsPsychHtmlKeyboardResponse , stimulus : 'The experiment failed to load. Please contact the researcher.' , choices : \"NO_KEYS\" , trial_duration : null } var if_loading_fails = { timeline : [ save_data , fail_message ], conditional_function : function () { if ( jsPsych . data . getLastTrialData ()[ 0 ]. values (). success ) { // preloading was successful, so skip this conditional timeline // and move on with the experiment return false ; } else { // preloading failed, so run this conditional timeline: // save the data to the server and show the fail message return true ; } } } // ... rest of experiment jsPsych . run ([ preload_trial , if_loading_fails , ... ]) The preload plugin's on_success and on_error callback functions provide another way of tracking preloading progress and handling file loading errors. These functions are called after any file either loads successfully or produces an error, respectively. These functions receive a single argument, which is the path of the file (string) that loaded or produced an error. var file_load_count = 0 ; var file_error_count = 0 ; var preload_trial = { type : jsPsychPreload , auto_preload : true , on_error : function ( file ) { file_error_count ++ ; console . log ( 'Error: ' , file ); }, on_success : function ( file ) { file_load_count ++ ; console . log ( 'Loaded: ' , file ); } }; Note that there's no guarantee that any/all files will trigger one of these two callback functions, because they are cancelled after the preload trial ends. For instance, if a file takes longer to load then the max_load_time , then the preload trial will end due to timing out, and the on_success and on_error callbacks for any in-progress files will be cancelled.","title":"Media Preloading"},{"location":"overview/media-preloading/#media-preloading","text":"If an experiment uses image, audio, or video files as stimuli, it is a good idea to preload the files before running the experiment. You can preload files at any point in your experiment using the jsPsych preload plugin . Preloading files means that the participant's browser will download the files and store them in local memory on the participant's computer. This is important because displaying or playing a media file is much faster if it is already in memory on the participant's computer. Without preloading, there will be noticeable delays in the display of media, which will affect any timing measurements (such as how long an image is displayed, or a participant's response time since first viewing an image). For particularly large files, like video, preloading content avoids lengthy pauses in the middle of the experiment that can be disruptive to the flow of the experiment. Warning Note that video preloading will not work when you run your experiment offline (e.g., by double-clicking on the HTML file), but it will work once your experiment is running online (hosted on a server). The Cross-origin requests (CORS) and safe mode section on the Running Experiments page contains more information about this.","title":"Media Preloading"},{"location":"overview/media-preloading/#automatic-preloading","text":"jsPsych can automatically preload audio, video, and image files that are used as parameters for the standard set of plugins, based on the timeline that is passed to jsPsych.run . You must initiate this preloading using a preload trial. You should add this preload trial into your timeline when you want the preloading to occur, and set the auto_preload parameter to true . // the \"auto_preload: true\" setting tells the plugin to automatically find // stimuli to preload based the main experiment timeline (used in jsPsych.run) var preload = { type : jsPsychPreload , auto_preload : true } // this image file can be automatically preloaded var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' } // the sound file can be automatically preloaded var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'audio/hello.mp3' } // the video file can be automatically preloaded (as long as the experiment // is running on a server) var video_trial = { type : jsPsychVideoKeyboardResponse , stimulus : [ 'video/sample_video.mp4' ] } jsPsych . run ([ preload , image_trial , sound_trial , video_trial ]);","title":"Automatic Preloading"},{"location":"overview/media-preloading/#manual-preloading","text":"If you are using media files in your experiment but they are not being passed directly as parameters to the trials (e.g., because you are using functions as parameters that return the media files, you are using timeline variables, or you are embedding the media files in an HTML string), then these files will not be detected when you use the auto_preload option, so you must manually specify them. The preload plugin allows you to add these files using the images , audio and video parameters. // this image file cannot be automatically preloaded because it is embedded in // an HTML string var image_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<img src=\"img/file1.png\"></img>' , } // this audio file cannot be automatically preloaded because it is returned // from a function var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : function () { return 'audio/sound1.mp3' } } // these video files cannot be automatically preloaded because they are passed // into a trial using the jsPsych.timelineVariable function var video_trials = { timeline : [ { type : jsPsychVideoKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'video' ) } ], timeline_variables : [ { video : [ 'video/1.mp4' ]}, { video : [ 'video/2.mp4' ]} ] } // to manually preload media files, create an array of file paths for each // media type var images = [ 'img/file1.png' ]; var audio = [ 'audio/sound1.mp3' ]; var video = [ 'video/1.mp4' , 'video/2.mp4' ]; // these array can be passed into the preload plugin using the images, audio // and video parameters var preload = { type : jsPsychPreload , images : images , audio : audio , video : video } jsPsych . run ([ preload , image_trial , sound_trial , video_trials ]);","title":"Manual preloading"},{"location":"overview/media-preloading/#combining-automatic-and-manual-preloading","text":"It's possible to combine automatic and manual preloading. For instance, you may want to automatically preload all of the media files based on your experiment timeline, while also manually preloading any files that can't be automatically preloaded. Any duplicate file names across all preloading methods will be removed before preloading starts, so including the same file names in multiple preload parameters will not affect the preloading duration. // this file can be preloaded automatically var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' } // this file can be preloaded automatically var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'audio/hello.mp3' } // these files must be preloaded manually var video_trials = { timeline : [ { type : jsPsychVideoKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'video' ) } ], timeline_variables : [ { video : [ 'video/1.mp4' ]}, { video : [ 'video/2.mp4' ]} ] } var video = [ 'video/1.mp4' , 'video/2.mp4' ]; var preload = { type : jsPsychPreload , auto_preload : true , // automatically preload the image and audio files video : video // manually preload the videos used with timeline variables } jsPsych . run ([ preload , image_trial , sound_trial , video_trials ]);","title":"Combining automatic and manual preloading"},{"location":"overview/media-preloading/#preloading-in-batches","text":"Some experiments use many and/or large media files. This can cause problems when participants have slow and/or unreliable internet connections, because it increases the chances of loading errors during preloading. This can also cause problems with file caching, i.e. ensuring that the preloaded files remain in the browser's memory, because loading all stimuli at once may exceed the browser's cache limits. One option for mitigating these problems is to load the media files in smaller batches throughout the experiment. Files should be preloaded as close as possible to when they will be needed. For instance, if you have several blocks of trials, then right before each block, you can preload the stimuli that are needed for that block. Here is an example with trials where the stimuli files can be preloaded automatically. In this case, the trials parameter is used to tell the preload plugin to preload the stimuli from a specific part of the timeline. // these image files in these trial blocks can be automatically preloaded var block_1 = { timeline : [ { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' }, { type : jsPsychImageKeyboardResponse , stimulus : 'img/file2.png' } ] } var block_2 = { timeline : [ { type : jsPsychImageKeyboardResponse , stimulus : 'img/file3.png' }, { type : jsPsychImageKeyboardResponse , stimulus : 'img/file4.png' } ] } var preload_1 = { type : jsPsychPreload , trials : block_1 // automatically preload just the images from block_1 trials } var preload_2 = { type : jsPsychPreload , trials : block_2 // automatically preload just the images from block_2 trials } jsPsych . run ( // add each preload trial onto the timeline before the appropriate trial block [ preload_1 , block_1 , preload_2 , block_2 ] ); Below is an example with trials where the stimuli files cannot be preloaded automatically, because the stimuli files are passed to the trials via jsPsych.timelineVariable . In this case, we create separate arrays for each batch of files, and then pass those arrays to the each preload trial. // these trial blocks cannot be automatically preloaded because // the media files are passed to the trial parameters with timeline variables var block_1 = { timeline : [...], timeline_variables : [ { stim : 'file1.png' }, { stim : 'file1.png' } ] } var block_2 = { timeline : [...], timeline_variables : [ { stim : 'file3.png' }, { stim : 'file4.png' } ] } var images_block_1 = [ 'file1.png' , 'file2.png' ]; var images_block_2 = [ 'file3.png' , 'file4.png' ]; // preload trial for preloading the block 1 stimuli var preload_1 = { type : jsPsychPreload , images : images_block_1 } // preload trial for preloading the block 2 stimuli var preload_2 = { type : jsPsychPreload , images : images_block_2 } jsPsych . run ( // add each preload trial to the timeline before the appropriate trial block [ preload_1 , block_1 , preload_2 , block_2 ] );","title":"Preloading in batches"},{"location":"overview/media-preloading/#preloading-progress-bar","text":"By default, the preload plugin will display a progress bar while files are being preloaded. This progress bar represents all files that are being preloaded during the trial, regardless of whether the file is being preloaded automatically via the auto_preload or trials parameters, or manually via the audio , images , and video parameters. You may wish to turn the preload progress bar off if you are only loading a small number of files, as it will appear and disappear so quickly that the participant may be confused about what it was. You can control whether the preloading progress bar appears by setting the show_progress_bar parameter in the preload trial. var preload_trial = { type : jsPsychPreload , auto_preload : true show_progress_bar : false // hide progress bar }","title":"Preloading progress bar"},{"location":"overview/media-preloading/#loading-time-limits","text":"It's usually a good idea to set a time limit for file loading, to ensure that participants aren't waiting for an unreasonable amount of time. Time limits can be specified in milliseconds using the max_load_time parameter. If you set a loading time limit and all files haven't finished loading before this time, then the preload trial will either stop an error (if continue_after_error is false, the default) or the trial will end and the experiment will continue (if continue_after_error is true ). If max_load_time is null (the default), then there is no time limit. var preload_trial = { type : jsPsychPreload , auto_preload : true max_load_time : 60000 // 1 minute }","title":"Loading time limits"},{"location":"overview/media-preloading/#loading-and-error-messages","text":"It's possible to specify custom messages to be shown on the page while the media files are loading, and in case of one or more file loading errors. The message parameter allows you to customize the loading message using an HML-formatted string. If show_progress_bar is true , then this message will be shown above the progress bar. var preload_trial = { type : jsPsychPreload , auto_preload : true message : 'Please wait while the experiment loads. This may take a few minutes.' , } A preloading error will occur when either (a) one or more files produces a loading error, and/or (b) all files have not finished loading before the max_load_time duration. The error_message parameter allows you to customize the messsage that's shown on the page in these cases. This message will only be shown if continue_after_error is false (the default). var preload_trial = { type : jsPsychPreload , auto_preload : true , error_message : 'The experiment failed to load. Please contact the researcher.' } In addition to the error_message parameter, it's also possible to show more detailed error messages on the page about any files that failed to load. You can control this with the show_detailed_errors parameter. Detailed error messages will appear below the general error message. This only applies if continue_after_error is false (the default). Detailed error messages can be useful when testing and debugging your experiment. If show_detailed_errors is true , then if one or more loading errors occurs before the max_load_time is reached, then the error page will also contian a list of the file(s) that produced an error, along with error information (if there is any). Note that this may not be a complete list, because it will only report any errors that occurred before the max_load_time was reached. If there are no file loading errors but preloading hasn't finished before the max_load_time , then detailed error message will just tell you that loading timed out. var preload_trial = { type : jsPsychPreload , auto_preload : true , // show details of any file loading errors and/or loading time out show_detailed_errors : true }","title":"Loading and error messages"},{"location":"overview/media-preloading/#options-for-handling-errors","text":"If continue_after_error is true , then the experiment will not stop if one or more files fails to load. Instead, the trial will end and the experiment will continue. However, the preload trial data will contain a property called success , which is whether or not all files were loaded successfully, timeout , which is whether or not the files loaded successfully before the max_load_time . The preload trial data will also contain lists of any image , audio , and video files that failed to load. This gives you the option to continue the experiment after preloading fails and use the preload trial data decide what to do next. For instance, you may decide to skip the trials that use the stimuli files that failed to load, or try loading the failed files again. Another option is to simply end the experiment when preloading fails, but send the data back to your server so that you have more information about the loading failure. var preload_trial = { type : jsPsychPreload , auto_preload : true , message : 'Please wait while the experiment loads...' , // don't stop the experiment if there are file loading errors or if loading times out continue_after_error : true } var save_data = { type : jsPsychCallFunction , async : true , func : function ( done ){ var data = jsPsych . data . get (). json (); save_data ( data , function () { done ()}) } } // the experiment will stop here, since there are no valid key choices or trial duration var fail_message = { type : jsPsychHtmlKeyboardResponse , stimulus : 'The experiment failed to load. Please contact the researcher.' , choices : \"NO_KEYS\" , trial_duration : null } var if_loading_fails = { timeline : [ save_data , fail_message ], conditional_function : function () { if ( jsPsych . data . getLastTrialData ()[ 0 ]. values (). success ) { // preloading was successful, so skip this conditional timeline // and move on with the experiment return false ; } else { // preloading failed, so run this conditional timeline: // save the data to the server and show the fail message return true ; } } } // ... rest of experiment jsPsych . run ([ preload_trial , if_loading_fails , ... ]) The preload plugin's on_success and on_error callback functions provide another way of tracking preloading progress and handling file loading errors. These functions are called after any file either loads successfully or produces an error, respectively. These functions receive a single argument, which is the path of the file (string) that loaded or produced an error. var file_load_count = 0 ; var file_error_count = 0 ; var preload_trial = { type : jsPsychPreload , auto_preload : true , on_error : function ( file ) { file_error_count ++ ; console . log ( 'Error: ' , file ); }, on_success : function ( file ) { file_load_count ++ ; console . log ( 'Loaded: ' , file ); } }; Note that there's no guarantee that any/all files will trigger one of these two callback functions, because they are cancelled after the preload trial ends. For instance, if a file takes longer to load then the max_load_time , then the preload trial will end due to timing out, and the on_success and on_error callbacks for any in-progress files will be cancelled.","title":"Options for handling errors"},{"location":"overview/mturk/","text":"Integrating with Mechanical Turk \u00b6 A common use of jsPsych is to build an online experiment and find participants using Mechanical Turk . Once an experiment is available through a web server and data is being saved on the server , connecting the experiment with Mechanical Turk takes only a few additional steps. jsPsych has some built-in functionality to assist with this process. The jsPsych.turk module \u00b6 The jsPsych.turk module contains functions that are relevant for experiments running on Mechanical Turk. Creating an advertisement page \u00b6 When potential participants view your experiment on Mechanical Turk, they will be able to see a single webpage before deciding whether or not to accept the HIT (start the experiment). This first page is often used as an advertisement for the experiment, similar to posting a flier in a department hallway. The important thing to remember about this page is that potential participants will be able to interact with it even if they haven't accepted the HIT. Therefore, it can be useful to change the content of the page depending on whether the HIT has been accepted or not. This is relatively easy to do: < div id = \"experiment_link\" > You must accept the HIT to begin the experiment </ div > . < script > // jsPsych has a method turkInfo() which can determine whether or not the // HIT has been accepted. var turkInfo = jsPsych . turkInfo (); // turkInfo.previewMode is true in two cases: when the HIT has not been // accepted yet OR when the page is viewed outside of mechanical turk. // The second property, outsideTurk, is true when the page is viewed // outside of mechanical turk, so together, the statement will be true // only when in Turk and when the HIT is not accepted yet. if ( ! turkInfo . previewMode && ! turkInfo . outsideTurk ) { document . querySelector ( '#experiment_link' ). innerHMTL = '<a href=\"link_to_experiment.html\" target=\"_blank\">Click Here to Start Experiment</a>' ; } </ script > One important issue with advertisement pages is that they must be served using the https protocol, which requires having an SSL certificate on the web server hosting the page. Instructions for how to do this vary depending on what kind of server you are using, so the best advice is to simply Google for instructions on how to acquire and install an SSL certificate on your particular server. Getting the worker ID \u00b6 Every account on Mechanical Turk is given a unique identification string. Recording this ID is a useful way to keep track of who is doing your experiment. In particular, while Turk has built in tools for preventing the same person from doing a HIT more than once, there may be cases where you don't want participants to complete related experiments. If you store the worker ID of every person who starts an experiment in a database, then you can exclude people by running a query on the database to check for the ID. jsPsych can get the workerID, assignmentID, and hitID with the turkInfo method. var turkInfo = jsPsych . turk . turkInfo (); // workerID turkInfo . workerId // hitID turkInfo . hitId // assignmentID turkInfo . assignmentId Recording the workerId at the start of the experiment is also a good way to track dropouts. Submitting results to Mechanical Turk \u00b6 If you are running a HIT on Mechanical Turk using the ExternalQuestion template, then you'll need to provide a way for participants to indicate that they have completed the HIT. (If you are using another template, then the template will provide this code for you). jsPSych makes this a relatively easy task. A common strategy for external HITs is to display an HTML page on the Mechanical Turk website that links to your HIT. Participants click the link, which opens the actual experiment content in a new browser window or tab, allowing the experiment to take up the whole browser window instead of just the iframe that displays content on Mechanical Turk. On this page, you might include a submit button for workers to indicate that they have finished the experiment. The page would look something like this: < p > Enter the code you were given: </ p > < input type = \"text\" id = \"code\" ></ input > < button onclick = \"sendData();\" > Submit HIT </ button > < script > function sendData () { jsPsych . turk . submitToTurk ({ code : document . getElementById ( 'code' ). value }); } </ script > When workers click the button, the contents of the code text field will be sent to Mechanical Turk, and you'll be able to view the participants and the codes that they entered in the Mechanical Turk GUI. You can then approve or reject work using the Mechanical Turk website. Limitations \u00b6 jsPsych is not designed to communicate with the Mechanical Turk API in a comprehensive manner. If you are looking for software to help you post and manage HITs, then you may want to look at PsiTurk . jsPsych and PsiTurk complement each other nicely, and there is an example of combining the two platforms on PsiTurk's experiment exchange.","title":"Integrating with Mechanical Turk"},{"location":"overview/mturk/#integrating-with-mechanical-turk","text":"A common use of jsPsych is to build an online experiment and find participants using Mechanical Turk . Once an experiment is available through a web server and data is being saved on the server , connecting the experiment with Mechanical Turk takes only a few additional steps. jsPsych has some built-in functionality to assist with this process.","title":"Integrating with Mechanical Turk"},{"location":"overview/mturk/#the-jspsychturk-module","text":"The jsPsych.turk module contains functions that are relevant for experiments running on Mechanical Turk.","title":"The jsPsych.turk module"},{"location":"overview/mturk/#creating-an-advertisement-page","text":"When potential participants view your experiment on Mechanical Turk, they will be able to see a single webpage before deciding whether or not to accept the HIT (start the experiment). This first page is often used as an advertisement for the experiment, similar to posting a flier in a department hallway. The important thing to remember about this page is that potential participants will be able to interact with it even if they haven't accepted the HIT. Therefore, it can be useful to change the content of the page depending on whether the HIT has been accepted or not. This is relatively easy to do: < div id = \"experiment_link\" > You must accept the HIT to begin the experiment </ div > . < script > // jsPsych has a method turkInfo() which can determine whether or not the // HIT has been accepted. var turkInfo = jsPsych . turkInfo (); // turkInfo.previewMode is true in two cases: when the HIT has not been // accepted yet OR when the page is viewed outside of mechanical turk. // The second property, outsideTurk, is true when the page is viewed // outside of mechanical turk, so together, the statement will be true // only when in Turk and when the HIT is not accepted yet. if ( ! turkInfo . previewMode && ! turkInfo . outsideTurk ) { document . querySelector ( '#experiment_link' ). innerHMTL = '<a href=\"link_to_experiment.html\" target=\"_blank\">Click Here to Start Experiment</a>' ; } </ script > One important issue with advertisement pages is that they must be served using the https protocol, which requires having an SSL certificate on the web server hosting the page. Instructions for how to do this vary depending on what kind of server you are using, so the best advice is to simply Google for instructions on how to acquire and install an SSL certificate on your particular server.","title":"Creating an advertisement page"},{"location":"overview/mturk/#getting-the-worker-id","text":"Every account on Mechanical Turk is given a unique identification string. Recording this ID is a useful way to keep track of who is doing your experiment. In particular, while Turk has built in tools for preventing the same person from doing a HIT more than once, there may be cases where you don't want participants to complete related experiments. If you store the worker ID of every person who starts an experiment in a database, then you can exclude people by running a query on the database to check for the ID. jsPsych can get the workerID, assignmentID, and hitID with the turkInfo method. var turkInfo = jsPsych . turk . turkInfo (); // workerID turkInfo . workerId // hitID turkInfo . hitId // assignmentID turkInfo . assignmentId Recording the workerId at the start of the experiment is also a good way to track dropouts.","title":"Getting the worker ID"},{"location":"overview/mturk/#submitting-results-to-mechanical-turk","text":"If you are running a HIT on Mechanical Turk using the ExternalQuestion template, then you'll need to provide a way for participants to indicate that they have completed the HIT. (If you are using another template, then the template will provide this code for you). jsPSych makes this a relatively easy task. A common strategy for external HITs is to display an HTML page on the Mechanical Turk website that links to your HIT. Participants click the link, which opens the actual experiment content in a new browser window or tab, allowing the experiment to take up the whole browser window instead of just the iframe that displays content on Mechanical Turk. On this page, you might include a submit button for workers to indicate that they have finished the experiment. The page would look something like this: < p > Enter the code you were given: </ p > < input type = \"text\" id = \"code\" ></ input > < button onclick = \"sendData();\" > Submit HIT </ button > < script > function sendData () { jsPsych . turk . submitToTurk ({ code : document . getElementById ( 'code' ). value }); } </ script > When workers click the button, the contents of the code text field will be sent to Mechanical Turk, and you'll be able to view the participants and the codes that they entered in the Mechanical Turk GUI. You can then approve or reject work using the Mechanical Turk website.","title":"Submitting results to Mechanical Turk"},{"location":"overview/mturk/#limitations","text":"jsPsych is not designed to communicate with the Mechanical Turk API in a comprehensive manner. If you are looking for software to help you post and manage HITs, then you may want to look at PsiTurk . jsPsych and PsiTurk complement each other nicely, and there is an example of combining the two platforms on PsiTurk's experiment exchange.","title":"Limitations"},{"location":"overview/plugins/","text":"Plugins \u00b6 In jsPsych, plugins define the kinds of trials or events that should occur during the experiment. Some plugins define very general events, like displaying a set of instructions pages , displaying an image and recording a keyboard response , or playing a sound file and recording a button response . Other plugins are more specific, like those that display particular kinds of stimuli (e.g., a circular visual search array ), or run a specific version of particular kind of task (e.g., the Implicit Association Test ). Part of creating an experiment with jsPsych involves figuring out which plugins are needed to create the tasks you want your participants to perform. Plugins provide a structure for a particular trial or task, but often allow for significant customization and flexibility. For example, the image-keyboard-response plugin defines a simple structure for showing an image and collecting a keyboard response. You can specify the what the stimulus is, what keys the participant is allowed to press, how long the stimulus should be on the screen, how long the participant has to respond, and so on. Many of these options have reasonable default values; even though the image plugin has many different parameters, you only need to specify the image stimulus in order to use it. Each plugin has its own documentation page, which describes what the plugin does, what options are available, and what kind of data it collects. Using a plugin \u00b6 To use a plugin, you'll need to load the plugin's JavaScript file in your experiment's HTML page. All jsPsych experiments also need to load the \"jsPsych.js\" file. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" type = \"text/javascript\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" type = \"text/javascript\" ></ script > </ head > Once a plugin is loaded, you can use JavaScript to define a trial that uses that plugin. All jsPsych trials need a type parameter, which tells jsPsych what plugin to use to run the trial. The trial's type is similar to the plugin name, but it always starts with \"jsPsych\" and is written in camel case rather than with dashes between the words. The trial's type parameter should NOT be a string (i.e., no quotes around the type value). Here are some examples of plugin names and types: Plugin name Type image-keyboard-response jsPsychImageKeyboardResponse fullscreen jsPsychFullscreen webgazer-init-camera jsPsychWebgazerInitCamera The following JavaScript code defines a trial using the image-keyboard-response plugin to display an image file. This trial uses the default values for valid keys, stimulus duration, trial duration, and other parameters. var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'images/happy_face.jpg' } You can override any default parameter values by adding them into your trial object. Here's an example of overriding the default values for trial_duration and post_trial_gap : var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'images/happy_face.jpg' , trial_duration : 3000 , post_trial_gap : 2000 } Parameters available in all plugins \u00b6 Each plugin specifies its own set of parameters. Check the documentation for a plugin to see what parameters are available and what they do. There is also a set of parameters that can be specified for any plugin: Parameter Type Default Value Description data object undefined An object containing additional data to store for the trial. See the Data page for more details. post_trial_gap numeric null Sets the time, in milliseconds, between the current trial and the next trial. If null, there will be no gap. on_start function function(){ return; } A callback function to execute when the trial begins, before any loading has occurred. See the Event-Related Callbacks page for more details. on_finish function function(){ return; } A callback function to execute when the trial finishes, and before the next trial begins. See the Event-Related Callbacks page for more details. on_load function function(){ return; } A callback function to execute when the trial has loaded, which typically happens after the initial display of the plugin has loaded. See the Event-Related Callbacks page for more details. css_classes string null A list of CSS classes to add to the jsPsych display element for the duration of this trial. This allows you to create custom formatting rules (CSS classes) that are only applied to specific trials. For more information and examples, see the Controlling Visual Appearance page and the \"css-classes-parameter.html\" file in the jsPsych examples folder. save_trial_parameters object {} An object containing any trial parameters that should or should not be saved to the trial data. Each key is the name of a trial parameter, and its value should be true or false , depending on whether or not its value should be saved to the data. If the parameter is a function that returns the parameter value, then the value that is returned will be saved to the data. If the parameter is always expected to be a function (e.g., an event-related callback function), then the function itself will be saved as a string. For more examples, see the \"save-trial-parameters.html\" file in the jsPsych examples folder. The data parameter \u00b6 The data parameter allows you to add additional properties to the trial data. This can be useful for storing properties of the trial that are not directly apparent from the values that the plugin records. The data parameter value must be an object that contains key-value pairs. A simple example is the Flanker Task . In this experiment, participants respond to the direction of a central arrow by pressing a key to the left for a left-pointing arrow (<) and a key to the right for a right-pointing arrow (>). The arrow appears in the center of flankers , or arrows that the participant should ignore. Those flankers can be congruent (>>>>>) or incongruent (<<><<). A trial for the Flanker Task written with jsPsych might look like this: var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' } } Note the use of the data parameter to add a property stimulus_type with the value congruent and a property target_direction with the value left . Having these properties recorded directly in the data simplifies data analysis, making it easy to aggregate data by stimulus_type and/or target_direction . The post_trial_gap (ITI) parameter \u00b6 The default inter-trial interval (ITI) in jsPsych is 0 ms. This can be adjusted at the experiment-wide level by changing the default_iti parameter in initJsPsych() . The ITI can also be controlled at the trial level through the post_trial_gap parameter. Setting this parameter to a positive integer x will cause a blank screen to display after the trial for x milliseconds. Setting this parameter for a trial will override the default_iti value set in initJsPsych . var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'There will be a 1.5 second blank screen after this trial.' , post_trial_gap : 1500 } The on_start parameter \u00b6 Immediately before a trial runs, there is an opportunity to run an arbitrary function through the on_start event handler. This event handler is passed a single argument containing an editable copy of the trial parameters. This function can therefore be used to alter the trial based on the state of the experiment, among other uses. // when this trial runs, the on_start function will change the trial's stimulus and data parameters, // so the trial will display an incongruent Flanker stimulus with a right-facing central arrow var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' }, on_start : function ( trial ){ trial . stimulus = '<<><<' ; trial . data . stimulus_type = 'incongruent' ; trial . data . target_direction = 'right' ; } } The on_finish parameter \u00b6 After a trial is completed, there is an opportunity to run an arbitrary function through the on_finish event handler. This function is passed a single argument containing an editable copy of the data recorded for that trial. This function can therefore be used to update the state of the experiment based on the data collected, or modify the data collected. The on_finish function can be useful to calculate new data properties that were unknowable at the start of the trial. For example, with the Flanker Task example above, the on_finish function could check the response and use to this information to add a new property to the data called correct , which is either true or false . // in addition to all of the standard data collected for this trial, // this on_finish function adds a property called 'correct' // which is either 'true' or 'false' // depending on the response that was made var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' , correct_response : 'f' }, on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response )){ data . correct = true ; } else { data . correct = false ; } } } The on_load parameter \u00b6 The on_load callback function will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. This can be useful for changing various aspects of the page elements and their properties that would otherwise require modifying the plugin file. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_load : function () { // this will change the src attribute of the image after 500ms setTimeout ( function (){ document . querySelector ( 'img' ). src = 'imgB.png' }, 500 ); } }; The css_classes parameter \u00b6 The css_classes parameter allows you to add an array of CSS class names to the jsPsych display element on that specific trial. This allows you to create custom style and formatting rules that are only applied to specific trials. If you want CSS rules that only apply to specific elements during a trial, you can use additional CSS selectors. < style > . flanker-stimulus { font-size : 500 % ; } . flanker-stimulus # prompt { font-size : 18 px ; } . fixation { font-size : 80 px ; } </ style > < script > var fixation_trial = { type : jsPsychHtmlKeyboardResponse , choices : \"NO_KEYS\" , stimulus : '+' , css_classes : [ 'fixation' ] }; var flanker_trial = { type : jsPsychHtmlKeyboardResponse , choices : [ \"ArrowLeft\" , \"ArrowRight\" ], stimulus : '>>>>>' , prompt : '<span id=\"prompt\">Press the left or right arrow key.</span>' , css_classes : [ 'flanker-stimulus' ] }; </ script > The save_trial_parameters parameter \u00b6 The save_trial_parameters parameter allows you to tell jsPsych what parameters you want to be saved to the data. This can be used to override the parameter values that the plugin saves by default. You can add more parameter values to the data that are not normally saved, or remove parameter values that normally are saved. This can be especially useful when the parameter value is dynamic (i.e. a function) and you want to record the value that was used during the trial. var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<p style=\"color: orange; font-size: 48px; font-weight: bold;\">BLUE</p>' , choices : function () { return jsPsych . randomization . shuffle ([ 'Yes' , 'No' ]); }, post_trial_gap : function () { return jsPsych . randomization . sampleWithoutReplacement ([ 200 , 300 , 400 , 500 ], 1 )[ 0 ]; }, save_trial_parameters : { // save the randomly-selected button order and post trial gap duration to the trial data choices : true , post_trial_gap : true , // don't save the stimulus stimulus : false } } Note You cannot remove the internal_node_id and trial_index values from the trial data, because these are used internally by jsPsych. Data collected by all plugins \u00b6 Each plugin defines what data is collected on the trial. The documentation for each plugin specifies what information will be stored in the trial data. In addition to the data collected by a plugin, there is a default set of data that is collected on every trial. Name Type Value trial_type string The name of the plugin used to run the trial. trial_index numeric The index of the current trial across the whole experiment. time_elapsed numeric The number of milliseconds between the start of the experiment and when the trial ended. internal_node_id string A string identifier for the current TimelineNode. Creating a new plugin \u00b6 See our developer's guide for plugins for information about how to create a new plugin.","title":"Plugins"},{"location":"overview/plugins/#plugins","text":"In jsPsych, plugins define the kinds of trials or events that should occur during the experiment. Some plugins define very general events, like displaying a set of instructions pages , displaying an image and recording a keyboard response , or playing a sound file and recording a button response . Other plugins are more specific, like those that display particular kinds of stimuli (e.g., a circular visual search array ), or run a specific version of particular kind of task (e.g., the Implicit Association Test ). Part of creating an experiment with jsPsych involves figuring out which plugins are needed to create the tasks you want your participants to perform. Plugins provide a structure for a particular trial or task, but often allow for significant customization and flexibility. For example, the image-keyboard-response plugin defines a simple structure for showing an image and collecting a keyboard response. You can specify the what the stimulus is, what keys the participant is allowed to press, how long the stimulus should be on the screen, how long the participant has to respond, and so on. Many of these options have reasonable default values; even though the image plugin has many different parameters, you only need to specify the image stimulus in order to use it. Each plugin has its own documentation page, which describes what the plugin does, what options are available, and what kind of data it collects.","title":"Plugins"},{"location":"overview/plugins/#using-a-plugin","text":"To use a plugin, you'll need to load the plugin's JavaScript file in your experiment's HTML page. All jsPsych experiments also need to load the \"jsPsych.js\" file. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" type = \"text/javascript\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" type = \"text/javascript\" ></ script > </ head > Once a plugin is loaded, you can use JavaScript to define a trial that uses that plugin. All jsPsych trials need a type parameter, which tells jsPsych what plugin to use to run the trial. The trial's type is similar to the plugin name, but it always starts with \"jsPsych\" and is written in camel case rather than with dashes between the words. The trial's type parameter should NOT be a string (i.e., no quotes around the type value). Here are some examples of plugin names and types: Plugin name Type image-keyboard-response jsPsychImageKeyboardResponse fullscreen jsPsychFullscreen webgazer-init-camera jsPsychWebgazerInitCamera The following JavaScript code defines a trial using the image-keyboard-response plugin to display an image file. This trial uses the default values for valid keys, stimulus duration, trial duration, and other parameters. var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'images/happy_face.jpg' } You can override any default parameter values by adding them into your trial object. Here's an example of overriding the default values for trial_duration and post_trial_gap : var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'images/happy_face.jpg' , trial_duration : 3000 , post_trial_gap : 2000 }","title":"Using a plugin"},{"location":"overview/plugins/#parameters-available-in-all-plugins","text":"Each plugin specifies its own set of parameters. Check the documentation for a plugin to see what parameters are available and what they do. There is also a set of parameters that can be specified for any plugin: Parameter Type Default Value Description data object undefined An object containing additional data to store for the trial. See the Data page for more details. post_trial_gap numeric null Sets the time, in milliseconds, between the current trial and the next trial. If null, there will be no gap. on_start function function(){ return; } A callback function to execute when the trial begins, before any loading has occurred. See the Event-Related Callbacks page for more details. on_finish function function(){ return; } A callback function to execute when the trial finishes, and before the next trial begins. See the Event-Related Callbacks page for more details. on_load function function(){ return; } A callback function to execute when the trial has loaded, which typically happens after the initial display of the plugin has loaded. See the Event-Related Callbacks page for more details. css_classes string null A list of CSS classes to add to the jsPsych display element for the duration of this trial. This allows you to create custom formatting rules (CSS classes) that are only applied to specific trials. For more information and examples, see the Controlling Visual Appearance page and the \"css-classes-parameter.html\" file in the jsPsych examples folder. save_trial_parameters object {} An object containing any trial parameters that should or should not be saved to the trial data. Each key is the name of a trial parameter, and its value should be true or false , depending on whether or not its value should be saved to the data. If the parameter is a function that returns the parameter value, then the value that is returned will be saved to the data. If the parameter is always expected to be a function (e.g., an event-related callback function), then the function itself will be saved as a string. For more examples, see the \"save-trial-parameters.html\" file in the jsPsych examples folder.","title":"Parameters available in all plugins"},{"location":"overview/plugins/#the-data-parameter","text":"The data parameter allows you to add additional properties to the trial data. This can be useful for storing properties of the trial that are not directly apparent from the values that the plugin records. The data parameter value must be an object that contains key-value pairs. A simple example is the Flanker Task . In this experiment, participants respond to the direction of a central arrow by pressing a key to the left for a left-pointing arrow (<) and a key to the right for a right-pointing arrow (>). The arrow appears in the center of flankers , or arrows that the participant should ignore. Those flankers can be congruent (>>>>>) or incongruent (<<><<). A trial for the Flanker Task written with jsPsych might look like this: var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' } } Note the use of the data parameter to add a property stimulus_type with the value congruent and a property target_direction with the value left . Having these properties recorded directly in the data simplifies data analysis, making it easy to aggregate data by stimulus_type and/or target_direction .","title":"The data parameter"},{"location":"overview/plugins/#the-post_trial_gap-iti-parameter","text":"The default inter-trial interval (ITI) in jsPsych is 0 ms. This can be adjusted at the experiment-wide level by changing the default_iti parameter in initJsPsych() . The ITI can also be controlled at the trial level through the post_trial_gap parameter. Setting this parameter to a positive integer x will cause a blank screen to display after the trial for x milliseconds. Setting this parameter for a trial will override the default_iti value set in initJsPsych . var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'There will be a 1.5 second blank screen after this trial.' , post_trial_gap : 1500 }","title":"The post_trial_gap (ITI) parameter"},{"location":"overview/plugins/#the-on_start-parameter","text":"Immediately before a trial runs, there is an opportunity to run an arbitrary function through the on_start event handler. This event handler is passed a single argument containing an editable copy of the trial parameters. This function can therefore be used to alter the trial based on the state of the experiment, among other uses. // when this trial runs, the on_start function will change the trial's stimulus and data parameters, // so the trial will display an incongruent Flanker stimulus with a right-facing central arrow var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' }, on_start : function ( trial ){ trial . stimulus = '<<><<' ; trial . data . stimulus_type = 'incongruent' ; trial . data . target_direction = 'right' ; } }","title":"The on_start parameter"},{"location":"overview/plugins/#the-on_finish-parameter","text":"After a trial is completed, there is an opportunity to run an arbitrary function through the on_finish event handler. This function is passed a single argument containing an editable copy of the data recorded for that trial. This function can therefore be used to update the state of the experiment based on the data collected, or modify the data collected. The on_finish function can be useful to calculate new data properties that were unknowable at the start of the trial. For example, with the Flanker Task example above, the on_finish function could check the response and use to this information to add a new property to the data called correct , which is either true or false . // in addition to all of the standard data collected for this trial, // this on_finish function adds a property called 'correct' // which is either 'true' or 'false' // depending on the response that was made var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' , correct_response : 'f' }, on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response )){ data . correct = true ; } else { data . correct = false ; } } }","title":"The on_finish parameter"},{"location":"overview/plugins/#the-on_load-parameter","text":"The on_load callback function will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. This can be useful for changing various aspects of the page elements and their properties that would otherwise require modifying the plugin file. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_load : function () { // this will change the src attribute of the image after 500ms setTimeout ( function (){ document . querySelector ( 'img' ). src = 'imgB.png' }, 500 ); } };","title":"The on_load parameter"},{"location":"overview/plugins/#the-css_classes-parameter","text":"The css_classes parameter allows you to add an array of CSS class names to the jsPsych display element on that specific trial. This allows you to create custom style and formatting rules that are only applied to specific trials. If you want CSS rules that only apply to specific elements during a trial, you can use additional CSS selectors. < style > . flanker-stimulus { font-size : 500 % ; } . flanker-stimulus # prompt { font-size : 18 px ; } . fixation { font-size : 80 px ; } </ style > < script > var fixation_trial = { type : jsPsychHtmlKeyboardResponse , choices : \"NO_KEYS\" , stimulus : '+' , css_classes : [ 'fixation' ] }; var flanker_trial = { type : jsPsychHtmlKeyboardResponse , choices : [ \"ArrowLeft\" , \"ArrowRight\" ], stimulus : '>>>>>' , prompt : '<span id=\"prompt\">Press the left or right arrow key.</span>' , css_classes : [ 'flanker-stimulus' ] }; </ script >","title":"The css_classes parameter"},{"location":"overview/plugins/#the-save_trial_parameters-parameter","text":"The save_trial_parameters parameter allows you to tell jsPsych what parameters you want to be saved to the data. This can be used to override the parameter values that the plugin saves by default. You can add more parameter values to the data that are not normally saved, or remove parameter values that normally are saved. This can be especially useful when the parameter value is dynamic (i.e. a function) and you want to record the value that was used during the trial. var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<p style=\"color: orange; font-size: 48px; font-weight: bold;\">BLUE</p>' , choices : function () { return jsPsych . randomization . shuffle ([ 'Yes' , 'No' ]); }, post_trial_gap : function () { return jsPsych . randomization . sampleWithoutReplacement ([ 200 , 300 , 400 , 500 ], 1 )[ 0 ]; }, save_trial_parameters : { // save the randomly-selected button order and post trial gap duration to the trial data choices : true , post_trial_gap : true , // don't save the stimulus stimulus : false } } Note You cannot remove the internal_node_id and trial_index values from the trial data, because these are used internally by jsPsych.","title":"The save_trial_parameters parameter"},{"location":"overview/plugins/#data-collected-by-all-plugins","text":"Each plugin defines what data is collected on the trial. The documentation for each plugin specifies what information will be stored in the trial data. In addition to the data collected by a plugin, there is a default set of data that is collected on every trial. Name Type Value trial_type string The name of the plugin used to run the trial. trial_index numeric The index of the current trial across the whole experiment. time_elapsed numeric The number of milliseconds between the start of the experiment and when the trial ended. internal_node_id string A string identifier for the current TimelineNode.","title":"Data collected by all plugins"},{"location":"overview/plugins/#creating-a-new-plugin","text":"See our developer's guide for plugins for information about how to create a new plugin.","title":"Creating a new plugin"},{"location":"overview/progress-bar/","text":"Automatic Progress Bar \u00b6 jsPsych can show a progress bar at the top of the experiment page indicating the participant's overall completion progress. The progress bar is rendered outside the jsPsych display element, and it requires the jspsych.css file to be loaded on the page. As of version 6.0, the progress bar looks like this: To show the progress bar, set the show_progress_bar option in initJsPsych to true : var jsPsych = initJsPsych ({ show_progress_bar : true }); The progress bar updates after every node on the top-level timeline updates. This avoids distracting updates in the middle of trials that are composed of multiple plugins, or confusing updates due to looping or conditional structures that may or may not execute depending on the actions of the participant. This also allows some flexibility for the programmer; by nesting timelines in a deliberate manner, the timing of progress bar updates can be controlled. Manual Control \u00b6 The progress bar can also be manually controlled using the function jsPsych.setProgressBar() . This function takes a numeric value between 0 and 1, representing the proportion of the progress bar to fill. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Almost done...' , on_finish : function (){ jsPsych . setProgressBar ( 0.85 ); // set progress bar to 85% full. } } You can also get the current value of the progress bar with jsPsych.getProgressBarCompleted() . var proportion_complete = jsPsych . getProgressBarCompleted (); If you are going to use manual progress bar control, you may want to disable the automatic progress bar updates by setting the auto_update_progress_bar property in initJsPsych() to false . var jsPsych = initJsPsych ({ show_progress_bar : true , auto_update_progress_bar : false }); Here's a complete example showing how to use these functions and initJsPsych() settings to manually update the progress bar: var jsPsych = initJsPsych ({ show_progress_bar : true , auto_update_progress_bar : false }); var n_trials = 5 ; var start = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press any key to start!' , on_start : function () { // set progress bar to 0 at the start of experiment jsPsych . setProgressBar ( 0 ); } }; var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is a trial!' , on_finish : function () { // at the end of each trial, update the progress bar // based on the current value and the proportion to update for each trial var curr_progress_bar_value = jsPsych . getProgressBarCompleted (); jsPsych . setProgressBar ( curr_progress_bar_value + ( 1 / n_trials )); } }; var trials = { timeline : [ trial ], repetitions : n_trials }; var done = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Done!' }; jsPsych . run ([ start , trials , done ]); Custom Text \u00b6 By default, jsPsych adds the text \"Completion Progress\" to the left of the progress bar. You can specify custom text using the message_progress_bar parameter in initJsPsych . // support for different spoken languages var jsPsych = initJsPsych ({ show_progress_bar : true , message_progress_bar : 'Porcentaje completo' }); // no message var jsPsych = initJsPsych ({ show_progress_bar : true , message_progress_bar : '' });","title":"Automatic Progress Bar"},{"location":"overview/progress-bar/#automatic-progress-bar","text":"jsPsych can show a progress bar at the top of the experiment page indicating the participant's overall completion progress. The progress bar is rendered outside the jsPsych display element, and it requires the jspsych.css file to be loaded on the page. As of version 6.0, the progress bar looks like this: To show the progress bar, set the show_progress_bar option in initJsPsych to true : var jsPsych = initJsPsych ({ show_progress_bar : true }); The progress bar updates after every node on the top-level timeline updates. This avoids distracting updates in the middle of trials that are composed of multiple plugins, or confusing updates due to looping or conditional structures that may or may not execute depending on the actions of the participant. This also allows some flexibility for the programmer; by nesting timelines in a deliberate manner, the timing of progress bar updates can be controlled.","title":"Automatic Progress Bar"},{"location":"overview/progress-bar/#manual-control","text":"The progress bar can also be manually controlled using the function jsPsych.setProgressBar() . This function takes a numeric value between 0 and 1, representing the proportion of the progress bar to fill. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Almost done...' , on_finish : function (){ jsPsych . setProgressBar ( 0.85 ); // set progress bar to 85% full. } } You can also get the current value of the progress bar with jsPsych.getProgressBarCompleted() . var proportion_complete = jsPsych . getProgressBarCompleted (); If you are going to use manual progress bar control, you may want to disable the automatic progress bar updates by setting the auto_update_progress_bar property in initJsPsych() to false . var jsPsych = initJsPsych ({ show_progress_bar : true , auto_update_progress_bar : false }); Here's a complete example showing how to use these functions and initJsPsych() settings to manually update the progress bar: var jsPsych = initJsPsych ({ show_progress_bar : true , auto_update_progress_bar : false }); var n_trials = 5 ; var start = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press any key to start!' , on_start : function () { // set progress bar to 0 at the start of experiment jsPsych . setProgressBar ( 0 ); } }; var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is a trial!' , on_finish : function () { // at the end of each trial, update the progress bar // based on the current value and the proportion to update for each trial var curr_progress_bar_value = jsPsych . getProgressBarCompleted (); jsPsych . setProgressBar ( curr_progress_bar_value + ( 1 / n_trials )); } }; var trials = { timeline : [ trial ], repetitions : n_trials }; var done = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Done!' }; jsPsych . run ([ start , trials , done ]);","title":"Manual Control"},{"location":"overview/progress-bar/#custom-text","text":"By default, jsPsych adds the text \"Completion Progress\" to the left of the progress bar. You can specify custom text using the message_progress_bar parameter in initJsPsych . // support for different spoken languages var jsPsych = initJsPsych ({ show_progress_bar : true , message_progress_bar : 'Porcentaje completo' }); // no message var jsPsych = initJsPsych ({ show_progress_bar : true , message_progress_bar : '' });","title":"Custom Text"},{"location":"overview/prolific/","text":"Integrating with Prolific \u00b6 Prolific is a participant recruitment service aimed at research. Integrating a jsPsych experiment with Prolific requires capturing the participant's ID and sending the participant to a completion URL at the end of the experiment. Capturing the Participant ID, Study ID, and Session ID \u00b6 When creating a study on Prolific you must provide the URL to your study. You can host your jsPsych experiment however you'd like - some options are discussed in the Running Experiments documentation page. Once you've got a URL to your experiment, you can enter that in the study link section of Prolific. Then, click the option to record Prolific IDs via URL parameters. This will append information about the participant's prolific ID ( PROLIFIC_PID ), the study's ID ( STUDY_ID ), and the session ID ( SESSION_ID ) to the URL that participants use to access your experiment. We can capture these variables with jsPsych, and add them to jsPsych's data. This can be done anywhere in your code. This code does not need to run as part of your experiment timeline. < script > var jsPsych = initJsPsych (); // capture info from Prolific var subject_id = jsPsych . data . getURLVariable ( 'PROLIFIC_PID' ); var study_id = jsPsych . data . getURLVariable ( 'STUDY_ID' ); var session_id = jsPsych . data . getURLVariable ( 'SESSION_ID' ); jsPsych . data . addProperties ({ subject_id : subject_id , study_id : study_id , session_id : session_id }); // create the rest of the experiment var timeline = [...] jsPsych . run ( timeline ) </ script > Completing the Experiment \u00b6 When the experiment is complete, Prolific requires that you send the participant to a specific URL that marks the session as complete on Prolific's server. The link is provided to you by Prolific in the study completion section of the setup. You can accomplish this in a couple different ways. Warning It's important that you've saved all the data from your experiment before the participant returns to Prolific. Make sure that any server communication has completed prior to redirecting the participant. One way to do this is by using the async features of the call-function plugin ( example ). Participant clicks a link \u00b6 One option is to create a trial that contains a link that the participant clicks to end the experiment and return to Prolific. For example, the html-keyboard-response plugin can be used to display text that includes a link. This could go on a debriefing page. Here's an example trial that could be used. Note that choices is set to \"NO_KEYS\" , which will prevent the participant from continuing past this point in the experiment. var final_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : `<p>You've finished the last task. Thanks for participating!</p> <p><a href=\"https://app.prolific.co/submissions/complete?cc=XXXXXXX\">Click here to return to Prolific and complete the study</a>.</p>` , choices : \"NO_KEYS\" } Automatically redirect \u00b6 A second option is to automatically redirect the participant to the completion URL when the experiment is finished. You could do this in a number of places in the jsPsych timeline. Here's an example using the on_finish event for the entire experiment. var jsPsych = initJsPsych ({ on_finish : function (){ window . location = \"https://app.prolific.co/submissions/complete?cc=XXXXXXX\" } });","title":"Integrating with Prolific"},{"location":"overview/prolific/#integrating-with-prolific","text":"Prolific is a participant recruitment service aimed at research. Integrating a jsPsych experiment with Prolific requires capturing the participant's ID and sending the participant to a completion URL at the end of the experiment.","title":"Integrating with Prolific"},{"location":"overview/prolific/#capturing-the-participant-id-study-id-and-session-id","text":"When creating a study on Prolific you must provide the URL to your study. You can host your jsPsych experiment however you'd like - some options are discussed in the Running Experiments documentation page. Once you've got a URL to your experiment, you can enter that in the study link section of Prolific. Then, click the option to record Prolific IDs via URL parameters. This will append information about the participant's prolific ID ( PROLIFIC_PID ), the study's ID ( STUDY_ID ), and the session ID ( SESSION_ID ) to the URL that participants use to access your experiment. We can capture these variables with jsPsych, and add them to jsPsych's data. This can be done anywhere in your code. This code does not need to run as part of your experiment timeline. < script > var jsPsych = initJsPsych (); // capture info from Prolific var subject_id = jsPsych . data . getURLVariable ( 'PROLIFIC_PID' ); var study_id = jsPsych . data . getURLVariable ( 'STUDY_ID' ); var session_id = jsPsych . data . getURLVariable ( 'SESSION_ID' ); jsPsych . data . addProperties ({ subject_id : subject_id , study_id : study_id , session_id : session_id }); // create the rest of the experiment var timeline = [...] jsPsych . run ( timeline ) </ script >","title":"Capturing the Participant ID, Study ID, and Session ID"},{"location":"overview/prolific/#completing-the-experiment","text":"When the experiment is complete, Prolific requires that you send the participant to a specific URL that marks the session as complete on Prolific's server. The link is provided to you by Prolific in the study completion section of the setup. You can accomplish this in a couple different ways. Warning It's important that you've saved all the data from your experiment before the participant returns to Prolific. Make sure that any server communication has completed prior to redirecting the participant. One way to do this is by using the async features of the call-function plugin ( example ).","title":"Completing the Experiment"},{"location":"overview/prolific/#participant-clicks-a-link","text":"One option is to create a trial that contains a link that the participant clicks to end the experiment and return to Prolific. For example, the html-keyboard-response plugin can be used to display text that includes a link. This could go on a debriefing page. Here's an example trial that could be used. Note that choices is set to \"NO_KEYS\" , which will prevent the participant from continuing past this point in the experiment. var final_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : `<p>You've finished the last task. Thanks for participating!</p> <p><a href=\"https://app.prolific.co/submissions/complete?cc=XXXXXXX\">Click here to return to Prolific and complete the study</a>.</p>` , choices : \"NO_KEYS\" }","title":"Participant clicks a link"},{"location":"overview/prolific/#automatically-redirect","text":"A second option is to automatically redirect the participant to the completion URL when the experiment is finished. You could do this in a number of places in the jsPsych timeline. Here's an example using the on_finish event for the entire experiment. var jsPsych = initJsPsych ({ on_finish : function (){ window . location = \"https://app.prolific.co/submissions/complete?cc=XXXXXXX\" } });","title":"Automatically redirect"},{"location":"overview/record-browser-interactions/","text":"Record browser interactions \u00b6 Participants in an online experiment have the freedom to multitask while performing an experiment. jsPsych automatically records information about when the user clicks on a window that is not the experiment, and about when the user exits full screen mode if the experiment is running in full screen mode. This data is stored separately from the main experiment data, and can be accessed with jsPsych.data.getInteractionData() . Each time the user leaves the experiment window, returns to the experiment window, exits full screen mode, or enters full screen mode, the event is recorded in the interaction data. Each event has the following structure. { event : 'focus' , // 'focus' or 'blur' or 'fullscreenenter' or 'fullscreenexit' trial : 12 , // the index of the active trial when the event happened time : 1240543 // time in ms since the start of the experiment } You can specify a custom function, in the initJsPsych() method, that is called whenever one of these events occurs initJsPsych ({ on_interaction_data_update : function ( data ) { console . log ( JSON . stringify ( data )) } });","title":"Record Browser Interactions"},{"location":"overview/record-browser-interactions/#record-browser-interactions","text":"Participants in an online experiment have the freedom to multitask while performing an experiment. jsPsych automatically records information about when the user clicks on a window that is not the experiment, and about when the user exits full screen mode if the experiment is running in full screen mode. This data is stored separately from the main experiment data, and can be accessed with jsPsych.data.getInteractionData() . Each time the user leaves the experiment window, returns to the experiment window, exits full screen mode, or enters full screen mode, the event is recorded in the interaction data. Each event has the following structure. { event : 'focus' , // 'focus' or 'blur' or 'fullscreenenter' or 'fullscreenexit' trial : 12 , // the index of the active trial when the event happened time : 1240543 // time in ms since the start of the experiment } You can specify a custom function, in the initJsPsych() method, that is called whenever one of these events occurs initJsPsych ({ on_interaction_data_update : function ( data ) { console . log ( JSON . stringify ( data )) } });","title":"Record browser interactions"},{"location":"overview/running-experiments/","text":"Running Experiments \u00b6 You can run your jsPsych experiment: Offline , by opening the HTML file directly in the browser using the file:// protocol. Online , by hosting the files on a web server using the http:// or https:// protocol. The way that you run your experiment will have consequences for certain aspects about how the experiment works, and what your experiment will be able to do. This page explains what you need to know about both of these options. Info If you are looking for a tool to automate deployment-related tasks, check out the jsPsych Builder CLI utility. It automatically bundles scripts and style sheets, configures media preloading, and yields a zip file that contains all files for deployment (online or offline). jsPsych Builder can also directly build JATOS experiment files (.jzip) that you can upload to a JATOS server (see this section below for more info about JATOS and other server options). Offline \u00b6 You can run your jsPsych experiment offline by opening the HTML file directly in a web browser, for instance by double-clicking on it. This uses the file:// protocol. It's usually the fastest and easiest way to run through an experiment, and is very useful while writing and testing the code. At some point you will need to move your experiment files onto a server and send the data to a database, since this is how you will ultimately collect the data (unless you're planning to collect data on your local computer). There are some important differences between the way the experiment runs offline compared to online via a web server. Note that, unless noted, here we're using the word \"server\" to mean either a local server (which runs on your computer and only makes the experiment files available from within that computer, and is often used during development), or a remote server (which does not run on your computer and does share your experiment files over the internet). Cross-origin requests (CORS) and safe mode \u00b6 Web browsers have a security policy called cross-origin resource sharing (CORS) that determines whether the webpage can request files that come from a different origin (i.e. protocol, host/domain, and port). This isn't a problem when your study runs online , because in that case your experiment files all have the same origin. However, when you run your experiment offline , the CORS policy blocks some jsPsych features that require loading local files . If your experiment uses these features, then CORS errors will prevent the experiment from running. To prevent these errors, jsPsych uses a 'safe mode' when it detects that the HTML page is running via the file:// protocol, and if so, automatically disables the features that don't work in that context. Specifically, when a jsPsych experiment runs offline: Web Audio is disabled (even if use_webaudio is set to true in initJsPsych ). The WebAudio API option is used by default because it allows more precise measurement of response times relative to the onset of the audio. But because WebAudio doesn't work offline, audio will be played using HTML5 audio instead. This is equivalent to setting use_webaudio to false in initJsPsych . Video preloading is disabled (both automatic and manual preloading via the preload plugin). Videos will still play when you run your experiment offline, but they will load during the experiment, which might cause noticeable delays before video playback starts. This safe mode feature is controlled by the override_safe_mode parameter in initJsPsych , which defaults to false . If you leave this setting as the default, then you won't need to worry about CORS errors while running your experiment offline, or remembering to change your initJsPsych settings when you move the experiment online. It's possible to override jsPsych's safe mode by setting override_safe_mode to true in initJsPsych . One reason you might do this is if you've disabled web security features in your browser (see here and here for instructions in Chrome), which is safe to do if you know what you're doing. If your experiment does not use Web Audio or preloaded videos, then jsPsych's safe mode feature will not have any effect. The override_safe_mode parameter also has no effect when your experiment is running online a web server, because the page will be loaded via the http:// or https:// protocol. Media loading \u00b6 While running your experiment offline, any media files are likely to load very quickly because they are stored on your own computer's disk. Therefore you may not notice problems with file loading delays while running your experiment locally (either offline or on a local server) because the files will load fast enough that they never cause disruption. However, when your experiment is hosted on a remote server, the files will need to be transferred over the internet, which means they will take longer to load - in some cases much longer. Loading delays are most noticeable with media files: images, audio, and video. As explained on the Media Preloading page, loading delays during your experiment can cause problems for stimulus display and response times. It is important to test your experiment to ensure that any media files are preloading successfully and not being requested again during the experiment. You can use the Network tab in your browser's developer tools to see when files are loaded and to simulate a slow internet connection (see here for Chrome Network tab documentation). If you are preloading many and/or large files, such as videos, you may want to increase the max_load_time parameter in the preload plugin so that participants with slow/unreliable internet connections will be able to take part in your experiment. Permanent data storage \u00b6 As explained in the Data Storage, Aggregation, and Manipulation page, jsPsych stores information in the participant's browser. While running an experiment offline, you won't be able to send the data to a database. However you can still see the data that jsPsych collects by saving it as a local file (using jsPsych.data.get().localSave ), displaying it in the webpage at the end of the experiment (using jsPsych.data.displayData ), or printing it to the browser's console (using console.log ). Permanent data storage is also necessary when the code that runs the experiment depends on information that can't be known in advance, and that changes throughout data collection. Some common examples of this in cognitive behavioral research are version counterbalancing , where the experiment code needs to access and update the history of version assignment in order to determine which version should be assigned, and multi-session/training studies , where the experiment might need to access and update information about each participant like their current session number, task difficulty level, etc. Doing these things in an automated way requires the use of a server. While developing and testing your experiment offline, you might choose to simulate some of these things and then implement them properly once you move your experiment online. For instance, you could randomize instead of counterbalancing version assignment: var versions = [ 1 , 2 ]; var random_version = jsPsych . randomization . sampleWithoutReplacement ( versions , 1 )[ 0 ]; And use URL query parameters to pass in variables like session number and difficulty level: // add the variables onto the end of the URL that appears in the browser when you open the file // e.g., file:///C:/my_experiment.html?id=1&sess=2&diff=3 var participant_id = jsPsych . data . getURLVariable ( 'id' ); var session = jsPsych . data . getURLVariable ( 'sess' ); var difficulty = jsPsych . data . getURLVariable ( 'diff' ); Online \u00b6 Hosting the Experiment and Saving the Data \u00b6 jsPsych is a front-end JavaScript library that runs entirely on the participant's computer. To run a jsPsych experiment over the internet, the files need to be hosted on a public web server so that participants can access the experiment using a web browser. When the participant completes the experiment in the browser, all of the data that jsPsych collects is stored on the participant's computer in the browser's memory. To get access to this data, it needs to be sent from the participant's browser back to the web server and stored in a database or a file. To be maximally flexible, jsPsych doesn't provide a single built-in solution for the web server component of your experiment. This makes jsPsych compatible with a wide range of hosting services and tools, allowing researchers to choose the web server option that best suit their needs. Some options for running your jsPsych experiment online include: Cognition.run - A free service designed specifically for hosting jsPsych experiments, with an easy-to-use interface. JATOS - A free program that runs on your own server and provides a GUI for setting up experiments and accessing the data. Offers lots of features for creating more complex experiments and managing multiple researchers. Pavlovia - A paid hosting service for web-based experiments, run by the PsychoPy team. Experiment files are managed on a GitLab repository. Participants will access the experiment through a link to Pavlovia. PsiTurk - Python-based program to help you host your experiment on your own computer and collect data from MTurk (see Recruiting Participants below). Relatively easy for a DIY option. Pushkin - A set of tools to help you set up your own virtual laboratory for online experiments. This option differs from the others in that it helps you set up a complete website that may contain many different experiments, information about the laboratory, participant logins, and other features that are targeted at hosting large-scale data collection efforts. Full DIY - You can setup your own web server and database and handle the communication yourself. Traditional web server 'stacks' include LAMP / LEMP (Linux operating system, Apache or Nginx server application, MySQL database, and PHP programming language). Other common web server frameworks include Flask (Python) and Node.js (JavaScript). Recruiting Participants \u00b6 Once your experiment is running online, you could recruit participants in the same way that you would for lab-based studies. For instance, if your institution uses SONA, you can advertise your web-based study link on SONA. SONA allows you to automactically embed a unique ID in online study URLs, which you can then save in your data using jsPsych's URL query parameters function . SONA will also generate a completion URL that you can redirect participants to at the end of the study, and this will mark them as having completed the study in SONA. To take full advantage of hosting an experiment online, many researchers advertise their experiments more widely. Social media and other media outlets provide one option for reaching a large number of potential participants. There are also some commercial platforms that you can use to advertise your study and pay anonymous online participants. These recruitment platforms charge a fee for use. The advantages of these platforms are that they handle the participant payments and allow you to specify pre-screening criteria. The most commonly used recruitment platforms in online behavioral research are: Prolific : An online labor market designed specifically for web-based research. Amazon Mechanical Turk (MTurk) : An online labor market designed for advertising paid 'human intelligence tasks'. This service was designed for use by commercial businesses but has been used by behavioral researchers for many years. Like SONA, Prolific and MTurk use URL query parameters to get participant information, and redirection to specific URLs to mark participants as having finished the study. jsPsych includes convenience functions for interacting with MTurk participants . Information about integrating with Prolific can be found in the researcher support section of their website.","title":"Running Experiments"},{"location":"overview/running-experiments/#running-experiments","text":"You can run your jsPsych experiment: Offline , by opening the HTML file directly in the browser using the file:// protocol. Online , by hosting the files on a web server using the http:// or https:// protocol. The way that you run your experiment will have consequences for certain aspects about how the experiment works, and what your experiment will be able to do. This page explains what you need to know about both of these options. Info If you are looking for a tool to automate deployment-related tasks, check out the jsPsych Builder CLI utility. It automatically bundles scripts and style sheets, configures media preloading, and yields a zip file that contains all files for deployment (online or offline). jsPsych Builder can also directly build JATOS experiment files (.jzip) that you can upload to a JATOS server (see this section below for more info about JATOS and other server options).","title":"Running Experiments"},{"location":"overview/running-experiments/#offline","text":"You can run your jsPsych experiment offline by opening the HTML file directly in a web browser, for instance by double-clicking on it. This uses the file:// protocol. It's usually the fastest and easiest way to run through an experiment, and is very useful while writing and testing the code. At some point you will need to move your experiment files onto a server and send the data to a database, since this is how you will ultimately collect the data (unless you're planning to collect data on your local computer). There are some important differences between the way the experiment runs offline compared to online via a web server. Note that, unless noted, here we're using the word \"server\" to mean either a local server (which runs on your computer and only makes the experiment files available from within that computer, and is often used during development), or a remote server (which does not run on your computer and does share your experiment files over the internet).","title":"Offline"},{"location":"overview/running-experiments/#cross-origin-requests-cors-and-safe-mode","text":"Web browsers have a security policy called cross-origin resource sharing (CORS) that determines whether the webpage can request files that come from a different origin (i.e. protocol, host/domain, and port). This isn't a problem when your study runs online , because in that case your experiment files all have the same origin. However, when you run your experiment offline , the CORS policy blocks some jsPsych features that require loading local files . If your experiment uses these features, then CORS errors will prevent the experiment from running. To prevent these errors, jsPsych uses a 'safe mode' when it detects that the HTML page is running via the file:// protocol, and if so, automatically disables the features that don't work in that context. Specifically, when a jsPsych experiment runs offline: Web Audio is disabled (even if use_webaudio is set to true in initJsPsych ). The WebAudio API option is used by default because it allows more precise measurement of response times relative to the onset of the audio. But because WebAudio doesn't work offline, audio will be played using HTML5 audio instead. This is equivalent to setting use_webaudio to false in initJsPsych . Video preloading is disabled (both automatic and manual preloading via the preload plugin). Videos will still play when you run your experiment offline, but they will load during the experiment, which might cause noticeable delays before video playback starts. This safe mode feature is controlled by the override_safe_mode parameter in initJsPsych , which defaults to false . If you leave this setting as the default, then you won't need to worry about CORS errors while running your experiment offline, or remembering to change your initJsPsych settings when you move the experiment online. It's possible to override jsPsych's safe mode by setting override_safe_mode to true in initJsPsych . One reason you might do this is if you've disabled web security features in your browser (see here and here for instructions in Chrome), which is safe to do if you know what you're doing. If your experiment does not use Web Audio or preloaded videos, then jsPsych's safe mode feature will not have any effect. The override_safe_mode parameter also has no effect when your experiment is running online a web server, because the page will be loaded via the http:// or https:// protocol.","title":"Cross-origin requests (CORS) and safe mode"},{"location":"overview/running-experiments/#media-loading","text":"While running your experiment offline, any media files are likely to load very quickly because they are stored on your own computer's disk. Therefore you may not notice problems with file loading delays while running your experiment locally (either offline or on a local server) because the files will load fast enough that they never cause disruption. However, when your experiment is hosted on a remote server, the files will need to be transferred over the internet, which means they will take longer to load - in some cases much longer. Loading delays are most noticeable with media files: images, audio, and video. As explained on the Media Preloading page, loading delays during your experiment can cause problems for stimulus display and response times. It is important to test your experiment to ensure that any media files are preloading successfully and not being requested again during the experiment. You can use the Network tab in your browser's developer tools to see when files are loaded and to simulate a slow internet connection (see here for Chrome Network tab documentation). If you are preloading many and/or large files, such as videos, you may want to increase the max_load_time parameter in the preload plugin so that participants with slow/unreliable internet connections will be able to take part in your experiment.","title":"Media loading"},{"location":"overview/running-experiments/#permanent-data-storage","text":"As explained in the Data Storage, Aggregation, and Manipulation page, jsPsych stores information in the participant's browser. While running an experiment offline, you won't be able to send the data to a database. However you can still see the data that jsPsych collects by saving it as a local file (using jsPsych.data.get().localSave ), displaying it in the webpage at the end of the experiment (using jsPsych.data.displayData ), or printing it to the browser's console (using console.log ). Permanent data storage is also necessary when the code that runs the experiment depends on information that can't be known in advance, and that changes throughout data collection. Some common examples of this in cognitive behavioral research are version counterbalancing , where the experiment code needs to access and update the history of version assignment in order to determine which version should be assigned, and multi-session/training studies , where the experiment might need to access and update information about each participant like their current session number, task difficulty level, etc. Doing these things in an automated way requires the use of a server. While developing and testing your experiment offline, you might choose to simulate some of these things and then implement them properly once you move your experiment online. For instance, you could randomize instead of counterbalancing version assignment: var versions = [ 1 , 2 ]; var random_version = jsPsych . randomization . sampleWithoutReplacement ( versions , 1 )[ 0 ]; And use URL query parameters to pass in variables like session number and difficulty level: // add the variables onto the end of the URL that appears in the browser when you open the file // e.g., file:///C:/my_experiment.html?id=1&sess=2&diff=3 var participant_id = jsPsych . data . getURLVariable ( 'id' ); var session = jsPsych . data . getURLVariable ( 'sess' ); var difficulty = jsPsych . data . getURLVariable ( 'diff' );","title":"Permanent data storage"},{"location":"overview/running-experiments/#online","text":"","title":"Online"},{"location":"overview/running-experiments/#hosting-the-experiment-and-saving-the-data","text":"jsPsych is a front-end JavaScript library that runs entirely on the participant's computer. To run a jsPsych experiment over the internet, the files need to be hosted on a public web server so that participants can access the experiment using a web browser. When the participant completes the experiment in the browser, all of the data that jsPsych collects is stored on the participant's computer in the browser's memory. To get access to this data, it needs to be sent from the participant's browser back to the web server and stored in a database or a file. To be maximally flexible, jsPsych doesn't provide a single built-in solution for the web server component of your experiment. This makes jsPsych compatible with a wide range of hosting services and tools, allowing researchers to choose the web server option that best suit their needs. Some options for running your jsPsych experiment online include: Cognition.run - A free service designed specifically for hosting jsPsych experiments, with an easy-to-use interface. JATOS - A free program that runs on your own server and provides a GUI for setting up experiments and accessing the data. Offers lots of features for creating more complex experiments and managing multiple researchers. Pavlovia - A paid hosting service for web-based experiments, run by the PsychoPy team. Experiment files are managed on a GitLab repository. Participants will access the experiment through a link to Pavlovia. PsiTurk - Python-based program to help you host your experiment on your own computer and collect data from MTurk (see Recruiting Participants below). Relatively easy for a DIY option. Pushkin - A set of tools to help you set up your own virtual laboratory for online experiments. This option differs from the others in that it helps you set up a complete website that may contain many different experiments, information about the laboratory, participant logins, and other features that are targeted at hosting large-scale data collection efforts. Full DIY - You can setup your own web server and database and handle the communication yourself. Traditional web server 'stacks' include LAMP / LEMP (Linux operating system, Apache or Nginx server application, MySQL database, and PHP programming language). Other common web server frameworks include Flask (Python) and Node.js (JavaScript).","title":"Hosting the Experiment and Saving the Data"},{"location":"overview/running-experiments/#recruiting-participants","text":"Once your experiment is running online, you could recruit participants in the same way that you would for lab-based studies. For instance, if your institution uses SONA, you can advertise your web-based study link on SONA. SONA allows you to automactically embed a unique ID in online study URLs, which you can then save in your data using jsPsych's URL query parameters function . SONA will also generate a completion URL that you can redirect participants to at the end of the study, and this will mark them as having completed the study in SONA. To take full advantage of hosting an experiment online, many researchers advertise their experiments more widely. Social media and other media outlets provide one option for reaching a large number of potential participants. There are also some commercial platforms that you can use to advertise your study and pay anonymous online participants. These recruitment platforms charge a fee for use. The advantages of these platforms are that they handle the participant payments and allow you to specify pre-screening criteria. The most commonly used recruitment platforms in online behavioral research are: Prolific : An online labor market designed specifically for web-based research. Amazon Mechanical Turk (MTurk) : An online labor market designed for advertising paid 'human intelligence tasks'. This service was designed for use by commercial businesses but has been used by behavioral researchers for many years. Like SONA, Prolific and MTurk use URL query parameters to get participant information, and redirection to specific URLs to mark participants as having finished the study. jsPsych includes convenience functions for interacting with MTurk participants . Information about integrating with Prolific can be found in the researcher support section of their website.","title":"Recruiting Participants"},{"location":"overview/simulation/","text":"Simulation Modes \u00b6 Added in 7.1 Simulation mode allows you run your experiment automatically and generate artificial data. Info For a detailed description of the motivation behind simulation mode and a discussion of different use cases of simulation mode, see de Leeuw, J.R., Gilbert, R.A., Petrov, N.B., & Luchterhandt, B. (2022). Simulation behavior to help researchers build experiments. Behavior Research Methods , https://doi.org/10.3758/s13428-022-01899-0 . A pre-print version is available on PsyArXiv . Getting Started \u00b6 To use simulation mode, replace jsPsych.run() with jsPsych.simulate() . jsPsych . simulate ( timeline ); This will run jsPsych in the default data-only simulation mode. To use the visual simulation mode you can specify the second parameter. jsPsych . simulate ( timeline , \"data-only\" ); jsPsych . simulate ( timeline , \"visual\" ); What happens in simulation mode \u00b6 In simulation mode, plugins call their simulate() method instead of calling their trial() method. If a plugin doesn't implement a simulate() method, then the trial will run as usual (using the trial() method) and any interaction that is needed to advance to the next trial will be required. If a plugin doesn't support visual mode, then it will run in data-only mode. data-only mode \u00b6 In data-only mode plugins typically generate resonable artificial data given the parameters specified for the trial. For example, if the trial_duration parameter is set to 2,000 ms, then any response times generated will be capped at this value. Generally the default data generated by the plugin randomly selects any available options (e.g., buttons to click) with equal probability. Response times are usually generated by sampling from an exponentially-modified Gaussian distribution truncated to positive values using jsPsych.randomization.sampleExGaussian() . In data-only mode, the plugin's trial() method usually does not run. The data are simply calculated based on trial parameters and the finishTrial() method is called immediately with the simulated data. visual mode \u00b6 In visual mode a plugin will typically generate simulated data for the trial and then use that data to mimic the kinds of actions that a participant would do. The plugin's trial() method is called by the simulation, and you'll see the experiment progress in real time. Mouse, keyboard, and touch events are simulated to control the experiment. In visual mode each plugin will generate simulated data in the same manner as data-only mode, but this data will instead be used to generate actions in the experiment and the plugin's trial() method will ultimately be responsible for generating the data. This can create some subtle differences in data between the two modes. For example, if the simulated data generates a response time of 500 ms, the data.rt value will be exactly 500 in data-only mode, but may be 501 or another slightly larger value in visual mode. This is because the simulated response is triggered at 500 ms and small delays due to JavaScript's event loop might add a few ms to the measure. Controlling simulation mode with simulation_options \u00b6 The parameters for simulation mode can be set using the simulation_options parameter in both jsPsych.simulate() and at the level of individual trials. Trial-level options \u00b6 You can specify simulation options for an individual trial by setting the simulation_options parameter. const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>Hello!</p>' , simulation_options : { data : { rt : 500 } } } Currently the three options that are available are data , mode , and simulate . data \u00b6 Setting the data option will replace the default data generated by the plugin with whatever data you specify. You can specify some or all of the data parameters. Any parameters you do not specify will be generated by the plugin. In most cases plugins will try to ensure that the data generated is consistent with the trial parameters. For example, if a trial has a trial_duration parameter of 2000 but the simulation_options specify a rt of 2500 , this creates an impossible situation because the trial would have ended before the response at 2,500ms. In most cases, the plugin will act as if a response was attempted at 2500 , which will mean that no response is generated for the trial. As you might imagine, there are a lot of parameter combinations that can generate peculiar cases where data may be inconsistent with trial parameters. We recommend double checking the simulation output, and please alert us if you discover a situation where the simulation produces inconsistent data. mode \u00b6 You can override the simulation mode specified in jsPsych.simulate() for any trial. Setting mode: 'data-only' will run the trial in data-only mode and setting mode: 'visual' will run the trial in visual mode. simulate \u00b6 If you want to turn off simulation mode for a trial, set simulate: false . Functions and timeline variables \u00b6 The simulation_options parameter is compatible with both dynamic parameters and timeline variables . Dynamic parameters can be especially useful if you want to randomize the data for each run of the simulation. For example, you can specify the rt as a sample from an ExGaussian distribution. const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>Hello!</p>' , simulation_options : { data : { rt : ()=>{ return jsPsych . randomization . sampleExGaussian ( 500 , 50 , 1 / 100 , true ) } } } } Experiment-level options \u00b6 You can also control the parameters for simulation by passing in an object to the simulation_options argument of jsPsych.simulate() . const simulation_options = { default : { data : { rt : 200 } } } jsPsych . simulate ( timeline , \"visual\" , simulation_options ) The above example will set the rt for any trial that doesn't have its own simulation_options specified to 200 . This could be useful, for example, to create a very fast preview of the experiment to verify that everything is displaying correctly without having to wait through longer trials. You can also specify sets of parameters by name using the experiment-level simulation options. const simulation_options = { default : { data : { rt : 200 } }, long_response : { data : { rt : () => { return jsPsych . randomization . sampleExGaussian ( 5000 , 500 , 1 / 500 , true ) } } } } const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>This is gonna take a bit.</p>' , simulation_options : 'long_response' } timeline . push ( trial ); jsPsych . simulate ( timeline , \"visual\" , simulation_options ) In the example above, we specified the simulation_options for trial using a string ( 'long_response' ). This will look up the corresponding set of options in the experiment-level simulation_options . We had a few use cases in mind with this approach: You could group together trials with similar behavior without needing to specify unique options for each trial. You could easily swap out different simulation options to test different kinds of behavior. For example, if you want to test that a timeline with a conditional_function is working as expected, you could have one set of simulation options where the data will cause the conditional_function to evaluate to true and another to false . By using string-based identifiers, you don't need to change the timeline code at all. You can just change the object being passed to jsPsych.simulate() . In an extreme case of the previous example, every trial on the timeline could have its own unique identifier and you could have multiple sets of simulation options to have very precise control over the data output. Current Limitations \u00b6 Simulation mode is not yet as comprehensively tested as the rest of jsPsych. While we are confident that the simulation is accurate enough for many use cases, it's very likely that there are circumstances where the simulated behavior will be inconsistent with what is actually possible in the experiment. If you come across any such circumstances, please let us know ! Currently extensions are not supported in simulation mode. Some plugins are also not supported. This will be noted on their documentation page.","title":"Simulation Modes"},{"location":"overview/simulation/#simulation-modes","text":"Added in 7.1 Simulation mode allows you run your experiment automatically and generate artificial data. Info For a detailed description of the motivation behind simulation mode and a discussion of different use cases of simulation mode, see de Leeuw, J.R., Gilbert, R.A., Petrov, N.B., & Luchterhandt, B. (2022). Simulation behavior to help researchers build experiments. Behavior Research Methods , https://doi.org/10.3758/s13428-022-01899-0 . A pre-print version is available on PsyArXiv .","title":"Simulation Modes"},{"location":"overview/simulation/#getting-started","text":"To use simulation mode, replace jsPsych.run() with jsPsych.simulate() . jsPsych . simulate ( timeline ); This will run jsPsych in the default data-only simulation mode. To use the visual simulation mode you can specify the second parameter. jsPsych . simulate ( timeline , \"data-only\" ); jsPsych . simulate ( timeline , \"visual\" );","title":"Getting Started"},{"location":"overview/simulation/#what-happens-in-simulation-mode","text":"In simulation mode, plugins call their simulate() method instead of calling their trial() method. If a plugin doesn't implement a simulate() method, then the trial will run as usual (using the trial() method) and any interaction that is needed to advance to the next trial will be required. If a plugin doesn't support visual mode, then it will run in data-only mode.","title":"What happens in simulation mode"},{"location":"overview/simulation/#data-only-mode","text":"In data-only mode plugins typically generate resonable artificial data given the parameters specified for the trial. For example, if the trial_duration parameter is set to 2,000 ms, then any response times generated will be capped at this value. Generally the default data generated by the plugin randomly selects any available options (e.g., buttons to click) with equal probability. Response times are usually generated by sampling from an exponentially-modified Gaussian distribution truncated to positive values using jsPsych.randomization.sampleExGaussian() . In data-only mode, the plugin's trial() method usually does not run. The data are simply calculated based on trial parameters and the finishTrial() method is called immediately with the simulated data.","title":"data-only mode"},{"location":"overview/simulation/#visual-mode","text":"In visual mode a plugin will typically generate simulated data for the trial and then use that data to mimic the kinds of actions that a participant would do. The plugin's trial() method is called by the simulation, and you'll see the experiment progress in real time. Mouse, keyboard, and touch events are simulated to control the experiment. In visual mode each plugin will generate simulated data in the same manner as data-only mode, but this data will instead be used to generate actions in the experiment and the plugin's trial() method will ultimately be responsible for generating the data. This can create some subtle differences in data between the two modes. For example, if the simulated data generates a response time of 500 ms, the data.rt value will be exactly 500 in data-only mode, but may be 501 or another slightly larger value in visual mode. This is because the simulated response is triggered at 500 ms and small delays due to JavaScript's event loop might add a few ms to the measure.","title":"visual mode"},{"location":"overview/simulation/#controlling-simulation-mode-with-simulation_options","text":"The parameters for simulation mode can be set using the simulation_options parameter in both jsPsych.simulate() and at the level of individual trials.","title":"Controlling simulation mode with simulation_options"},{"location":"overview/simulation/#trial-level-options","text":"You can specify simulation options for an individual trial by setting the simulation_options parameter. const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>Hello!</p>' , simulation_options : { data : { rt : 500 } } } Currently the three options that are available are data , mode , and simulate .","title":"Trial-level options"},{"location":"overview/simulation/#data","text":"Setting the data option will replace the default data generated by the plugin with whatever data you specify. You can specify some or all of the data parameters. Any parameters you do not specify will be generated by the plugin. In most cases plugins will try to ensure that the data generated is consistent with the trial parameters. For example, if a trial has a trial_duration parameter of 2000 but the simulation_options specify a rt of 2500 , this creates an impossible situation because the trial would have ended before the response at 2,500ms. In most cases, the plugin will act as if a response was attempted at 2500 , which will mean that no response is generated for the trial. As you might imagine, there are a lot of parameter combinations that can generate peculiar cases where data may be inconsistent with trial parameters. We recommend double checking the simulation output, and please alert us if you discover a situation where the simulation produces inconsistent data.","title":"data"},{"location":"overview/simulation/#mode","text":"You can override the simulation mode specified in jsPsych.simulate() for any trial. Setting mode: 'data-only' will run the trial in data-only mode and setting mode: 'visual' will run the trial in visual mode.","title":"mode"},{"location":"overview/simulation/#simulate","text":"If you want to turn off simulation mode for a trial, set simulate: false .","title":"simulate"},{"location":"overview/simulation/#functions-and-timeline-variables","text":"The simulation_options parameter is compatible with both dynamic parameters and timeline variables . Dynamic parameters can be especially useful if you want to randomize the data for each run of the simulation. For example, you can specify the rt as a sample from an ExGaussian distribution. const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>Hello!</p>' , simulation_options : { data : { rt : ()=>{ return jsPsych . randomization . sampleExGaussian ( 500 , 50 , 1 / 100 , true ) } } } }","title":"Functions and timeline variables"},{"location":"overview/simulation/#experiment-level-options","text":"You can also control the parameters for simulation by passing in an object to the simulation_options argument of jsPsych.simulate() . const simulation_options = { default : { data : { rt : 200 } } } jsPsych . simulate ( timeline , \"visual\" , simulation_options ) The above example will set the rt for any trial that doesn't have its own simulation_options specified to 200 . This could be useful, for example, to create a very fast preview of the experiment to verify that everything is displaying correctly without having to wait through longer trials. You can also specify sets of parameters by name using the experiment-level simulation options. const simulation_options = { default : { data : { rt : 200 } }, long_response : { data : { rt : () => { return jsPsych . randomization . sampleExGaussian ( 5000 , 500 , 1 / 500 , true ) } } } } const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>This is gonna take a bit.</p>' , simulation_options : 'long_response' } timeline . push ( trial ); jsPsych . simulate ( timeline , \"visual\" , simulation_options ) In the example above, we specified the simulation_options for trial using a string ( 'long_response' ). This will look up the corresponding set of options in the experiment-level simulation_options . We had a few use cases in mind with this approach: You could group together trials with similar behavior without needing to specify unique options for each trial. You could easily swap out different simulation options to test different kinds of behavior. For example, if you want to test that a timeline with a conditional_function is working as expected, you could have one set of simulation options where the data will cause the conditional_function to evaluate to true and another to false . By using string-based identifiers, you don't need to change the timeline code at all. You can just change the object being passed to jsPsych.simulate() . In an extreme case of the previous example, every trial on the timeline could have its own unique identifier and you could have multiple sets of simulation options to have very precise control over the data output.","title":"Experiment-level options"},{"location":"overview/simulation/#current-limitations","text":"Simulation mode is not yet as comprehensively tested as the rest of jsPsych. While we are confident that the simulation is accurate enough for many use cases, it's very likely that there are circumstances where the simulated behavior will be inconsistent with what is actually possible in the experiment. If you come across any such circumstances, please let us know ! Currently extensions are not supported in simulation mode. Some plugins are also not supported. This will be noted on their documentation page.","title":"Current Limitations"},{"location":"overview/style/","text":"Controlling Visual Appearance \u00b6 Your experiment's style and formatting comes from the CSS (cascading style sheet) rules that are stored in the jspsych.css file, and the browser's defaults. There are a few ways to change the style and formatting in your experiment. The method that you choose is partly a matter of personal preference. It might also depend on whether you want the style/formatting change(s) to apply to specific trials , to the whole experiment (HTML page), or across different experiments . This section discusses the different ways of incorporating CSS into your jsPsych experiment. You can also see this page about adding CSS to web pages to learn more. Inline CSS \u00b6 Whenever you're using a parameter that accepts an HTML-formatted string, you have the option to include inline CSS. Inline CSS is a way of adding style and formatting directly into a specific HTML element using its \"style\" attribute . This is a good option for when you want to make few and/or simple style changes to an HTML trial parameter. To change an element's style using inline CSS, you can set the element's \"style\" attribute to a string that contains the CSS parameters that you want to change, along with the values that you want to use. The syntax is \" <parameter-name> : <parameter-value> ;\". In the example below, the stimulus font size is set to 30px and the text color is set to red. These changes will only be applied to this stimulus text in this specific trial. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size:30px;color:red;\">hello world!</p>' } You can also use a dynamic parameter to combine inline CSS and trial-specific variables. This allows you to easily apply the same inline CSS to multiple trials. Here's an example using a dynamic stimulus parameter and timeline variables : var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var stim = '<p style=\"font-size:30px;font-weight:bold;\">' + jsPsych . timelineVariable ( 'text' ) + '</p>' ; return stim ; } } var trial_procedure = { timeline : [ trial ], timeline_variables : [ { text : 'Welcome' }, { text : 'to' }, { text : 'the' }, { text : 'experiment!' } ] } Adding CSS rules \u00b6 You may want to add a lot of different CSS changes to your experiment, re-use the same change(s) across lots of different trials, and/or separate the style/formatting from the HTML string. In these cases, you might find it useful to create CSS rules rather than using inline CSS. Creating CSS rules is a lot like using inline CSS, except that you also need to use a CSS selector . This is because your CSS rules aren't attached to any specific HTML element (unlike inline CSS), so you need to tell the browser which element(s) the style rules should apply to. The syntax is \"css-selector { <parameter-name> : <parameter-value> ; }\". In the example below, the CSS selector \"p\" tells the browser to apply the font size change to any text that is inside of a <p> element. p { font-size : 30 px ; } You can make more specific changes using CSS rules. The specificity will depend on the CSS selectors that are used. In addition to using the tag name (e.g. \"p\"), other common CSS selectors include the element's ID or class . If you are selecting an element using it's ID, then the CSS selector needs to have a # in front of the ID, e.g. \"#stimulus\". If you are selecting elements based on their class, then you need to include a . in front of the class, e.g. \".large-text\". In the example below, the \"#stimulus\" CSS selector means that the width change will only affect elements with the \"stimulus\" ID, and the \".large-text\" CSS selector means that the font size change will only affect elements that have the \"large-text\" class. # stimulus width : 300px ; } . large-text { font-size : 200 % ; } It is possible to create even more specific CSS selectors, for instance by combining tags, IDs, and/or classes. For example, let's say that you are showing feedback text to participants, and that this text is inside of a <p> tag. You could add the ID \"correct\" to the <p> element for correct response feedback, and the ID \"incorrect\" to the <p> element for incorrect response feedback. Then you can define separate styles for correct and incorrect feedback text like this: p # incorrect { color : red ; } p # correct { color : green ; } See this page about CSS selectors for a complete reference of CSS selector patterns and their meanings. With style tags \u00b6 You can add CSS rules to your HTML page by putting them inside of <style> tags. These rules will be applied to your whole experiment . This method can be useful for making general changes to the way that your experiment looks. In the example below, the default font size is set to 25px throughout the experiment. This will overrule the default font size of 18px that is set in the jspsych.css file. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < style > . jspsych-display-element { font-size : 25 px ; } </ style > </ head > With a stylesheet \u00b6 CSS rules can also be applied to your experiment with a link to an external CSS file. This is the same method that is usually used to apply the style from jspsych.css to an experiment. These rules will be applied to your whole experiment . You may find it useful to use a custom stylesheet when you want to re-use the same CSS rules across multiple experiments (HTML files). This example shows how to add a custom CSS file in addition to the styles provided in jspsych.css. In this example, the custom CSS file is called \"my_experiment_style.css\" and it is located in the same directory as your HTML file. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < link rel = \"stylesheet\" href = \"my_experiment_style.css\" > </ head > Below are the some example contents of an external CSS file, like the \"my_experiment_style.css\" from the example above. This CSS will (1) change the page background color to black, (2) change the default font to 25px and white, and (3) limit the width of the page content so that it can only take up to 80% of its normal width. body { background-color : black ; } . jspsych-display-element { font-size : 25 px ; color : white ; } . jspsych-content { max-width : 80 % ; } Note <style> tags are not used inside of an external CSS file. Using the css_classes trial parameter \u00b6 CSS rules can also be applied in a trial-specific way using the css_classes parameter. This parameter will apply one or more class to the <div> element that holds all of the jsPsych page content during that specific trial. This way you can treat CSS styles just like any other trial parameter. You can use a static css_classes parameter value if you always want to apply the same CSS rules to the trial. In the 'fixation' example below, separating the style rules from the stimulus string makes the code a little bit 'cleaner', and this makes it easier to re-use the same style rules in other parts of the experiment. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < style > . fixation { font-size : 90 px ; font-weight : bold ; color : gray ;} </ style > </ head > < script > var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 , css_classes : [ 'fixation' ] } // ... </ script > You may want the css_classes parameter to vary across trials. If so, you can turn it into a dynamic parameter or use timeline variables (see examples below). One thing to note about the css_classes parameter is that it only adds the class(es) to the jspsych-content <div> element, which is the \"parent\" element that contains all of the experiment content. Often you'll want your CSS rules to be applied to other elements inside of this jspsych-content div. Sometimes your CSS rules will be \"inherited\" by all of the other jsPsych content inside of this parent <div>. For instance, in the fixation example above, the CSS rules that change the font size, weight and color are applied to the parent <div> and automatically passed on to the stimulus text through inheritance. There are two reasons why a CSS rule like the one above for fixation may not work the way you expect: Not all CSS properties are inherited from the parent element. When a CSS property is inherited from the parent element, it will affect all elements in a given trial. In these cases, you can change your CSS selector to make it more specific: add a space after class name, then add more CSS selectors to select the specific element(s) that you want to change. Tip To find out this more specific CSS selector, you can right-click on the element and select Inspect . In the inspector window, right-click on the property corresponding to the element and copy the selector. You might need to increase the trial's trial_duration to give yourself enough time to inspect the elements on the page. See more tips for working with CSS below. In the example below, the CSS selector .left-align #stimulus selects the element with the ID \"stimulus\" that is inside of an element with the class \"left-align\". < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < style > . left-align # stimulus { text-align : left ; width : 600 px ;} . right-align # stimulus { text-align : right ; width : 600 px ;} </ style > </ head > < script > var trial_procedure = { timeline : [{ type : jsPsychHtmlKeyboardResponse , stimulus : '<p id=\"stimulus\">This is the stimulus.</p>' , prompt : '<p>This text will not be affected by the CSS classes ' + 'because it does not have the \"stimulus\" ID.</p>' , css_classes : jsPsych . timelineVariable ( 'css_classes' ) }], timeline_variables : [ { css_classes : [ 'left-align' ]}, { css_classes : [ 'right-align' ]} ] } // ... </ script > It's also possible to pass multiple class names to the css_classes parameter. This can be useful for creating conditions that involve crossing different style-related factors. This example shows you to combine two text alignment and two text color factors to produce four different stimulus conditions: < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < style > . left-align # stimulus { text-align : left ; width : 600 px ;} . right-align # stimulus { text-align : right ; width : 600 px ;} . teal # stimulus { color : teal ;} . purple # stimulus { color : purple ;} </ style > </ head > < script > var trial_procedure = { timeline : [{ type : jsPsychHtmlKeyboardResponse , stimulus : '<p id=\"stimulus\">This is the stimulus.</p>' , prompt : '<p>This text will not be affected by the CSS classes ' + 'because it does not have the \"stimulus\" ID.</p>' , css_classes : jsPsych . timelineVariable ( 'css_classes' ), data : { condition : jsPsych . timelineVariable ( 'condition' )} }], timeline_variables : [ { css_classes : [ 'left-align' , 'teal' ], condition : 'left-teal' }, { css_classes : [ 'right-align' , 'teal' ], condition : 'right-teal' }, { css_classes : [ 'left-align' , 'purple' ], condition : 'left-purple' }, { css_classes : [ 'right-align' , 'purple' ], condition : 'right-purple' } ] } // ... </ script > See the \"css-classes-parameter.html\" file in jsPsych's examples subfolder for more explanation and examples. Tips for working with CSS \u00b6 Your browser's developer tools contain very useful features for exploring and debugging your experiment's style and formatting. Open your browser's developer tools and click on the Element Inspector button or go to the Elements tab. Once you have selected an element on the page, you can see all of the information that can be used to select it, including: tag name, e.g., \"div\", \"p\", \"img\", \"button\" ID, if it has one class(es), if it has any You can then use this information to create a CSS selector to modify that element's style. As you can see, jsPsych adds its own IDs and classes to many elements. You can use the developer tools to determine what IDs and classes already exist for the elements that you want to modify, as you may can often just use these instead of adding your own. For instance, in the \"html-keyboard-response\" plugin, the stimulus will always be shown in a <div> with the ID \"jspsych-html-keyboard-response-stimulus\". So you can create a CSS rule that is applied to all \"html-keyboard-response\" stimuli like this: # jspsych-html-keyboard-response-stimulus { color : white ; background-color : blue ; width : 100 px ; border : 4 px solid black ; } As another example, most jsPsych buttons have the class \"jspsych-btn\", so you can use this class to change the default button styling: . jspsych-btn { padding : 20 px 20 px ; font-size : 25 px ; border-color : black ; } You can also use the developer tools to change an element's CSS and immediately see the effect that the changes will have on the page. These changes are just temporary, so you will still need to use one of methods described above to add the CSS changes to your experiment. However, making changes in the developer tools is very useful for figuring out which CSS properties to change and which values to use. This area of the developer tools also shows what styles are currently applied to the element and where those style rules are coming from. There are a few things to be aware of while debugging problems with CSS. When there are conflicting CSS rules, some CSS rules will take precedence over others . For instance, inline CSS usually takes precedence over other CSS rules, and more specific CSS selectors usually take precedence over less specific ones. When there are conflicting CSS rules that have the same level of precedence, the last rule will override any earlier rules . For that reason it's important to add your own custom stylesheet after the default jspsych.css stylesheet. See this page about CSS precedence for more information. If one CSS style rule is overridden by another one, the rule that is overridden will appear in strikethrough text in the element's \"Styles\" section. Also, if you are using an incorrect CSS property name or an invalid value, then that will show up here as an error, indicated by both strikethrough text and a little yellow warning symbol.","title":"Controlling Visual Appearance"},{"location":"overview/style/#controlling-visual-appearance","text":"Your experiment's style and formatting comes from the CSS (cascading style sheet) rules that are stored in the jspsych.css file, and the browser's defaults. There are a few ways to change the style and formatting in your experiment. The method that you choose is partly a matter of personal preference. It might also depend on whether you want the style/formatting change(s) to apply to specific trials , to the whole experiment (HTML page), or across different experiments . This section discusses the different ways of incorporating CSS into your jsPsych experiment. You can also see this page about adding CSS to web pages to learn more.","title":"Controlling Visual Appearance"},{"location":"overview/style/#inline-css","text":"Whenever you're using a parameter that accepts an HTML-formatted string, you have the option to include inline CSS. Inline CSS is a way of adding style and formatting directly into a specific HTML element using its \"style\" attribute . This is a good option for when you want to make few and/or simple style changes to an HTML trial parameter. To change an element's style using inline CSS, you can set the element's \"style\" attribute to a string that contains the CSS parameters that you want to change, along with the values that you want to use. The syntax is \" <parameter-name> : <parameter-value> ;\". In the example below, the stimulus font size is set to 30px and the text color is set to red. These changes will only be applied to this stimulus text in this specific trial. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size:30px;color:red;\">hello world!</p>' } You can also use a dynamic parameter to combine inline CSS and trial-specific variables. This allows you to easily apply the same inline CSS to multiple trials. Here's an example using a dynamic stimulus parameter and timeline variables : var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var stim = '<p style=\"font-size:30px;font-weight:bold;\">' + jsPsych . timelineVariable ( 'text' ) + '</p>' ; return stim ; } } var trial_procedure = { timeline : [ trial ], timeline_variables : [ { text : 'Welcome' }, { text : 'to' }, { text : 'the' }, { text : 'experiment!' } ] }","title":"Inline CSS"},{"location":"overview/style/#adding-css-rules","text":"You may want to add a lot of different CSS changes to your experiment, re-use the same change(s) across lots of different trials, and/or separate the style/formatting from the HTML string. In these cases, you might find it useful to create CSS rules rather than using inline CSS. Creating CSS rules is a lot like using inline CSS, except that you also need to use a CSS selector . This is because your CSS rules aren't attached to any specific HTML element (unlike inline CSS), so you need to tell the browser which element(s) the style rules should apply to. The syntax is \"css-selector { <parameter-name> : <parameter-value> ; }\". In the example below, the CSS selector \"p\" tells the browser to apply the font size change to any text that is inside of a <p> element. p { font-size : 30 px ; } You can make more specific changes using CSS rules. The specificity will depend on the CSS selectors that are used. In addition to using the tag name (e.g. \"p\"), other common CSS selectors include the element's ID or class . If you are selecting an element using it's ID, then the CSS selector needs to have a # in front of the ID, e.g. \"#stimulus\". If you are selecting elements based on their class, then you need to include a . in front of the class, e.g. \".large-text\". In the example below, the \"#stimulus\" CSS selector means that the width change will only affect elements with the \"stimulus\" ID, and the \".large-text\" CSS selector means that the font size change will only affect elements that have the \"large-text\" class. # stimulus width : 300px ; } . large-text { font-size : 200 % ; } It is possible to create even more specific CSS selectors, for instance by combining tags, IDs, and/or classes. For example, let's say that you are showing feedback text to participants, and that this text is inside of a <p> tag. You could add the ID \"correct\" to the <p> element for correct response feedback, and the ID \"incorrect\" to the <p> element for incorrect response feedback. Then you can define separate styles for correct and incorrect feedback text like this: p # incorrect { color : red ; } p # correct { color : green ; } See this page about CSS selectors for a complete reference of CSS selector patterns and their meanings.","title":"Adding CSS rules"},{"location":"overview/style/#with-style-tags","text":"You can add CSS rules to your HTML page by putting them inside of <style> tags. These rules will be applied to your whole experiment . This method can be useful for making general changes to the way that your experiment looks. In the example below, the default font size is set to 25px throughout the experiment. This will overrule the default font size of 18px that is set in the jspsych.css file. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < style > . jspsych-display-element { font-size : 25 px ; } </ style > </ head >","title":"With style tags"},{"location":"overview/style/#with-a-stylesheet","text":"CSS rules can also be applied to your experiment with a link to an external CSS file. This is the same method that is usually used to apply the style from jspsych.css to an experiment. These rules will be applied to your whole experiment . You may find it useful to use a custom stylesheet when you want to re-use the same CSS rules across multiple experiments (HTML files). This example shows how to add a custom CSS file in addition to the styles provided in jspsych.css. In this example, the custom CSS file is called \"my_experiment_style.css\" and it is located in the same directory as your HTML file. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < link rel = \"stylesheet\" href = \"my_experiment_style.css\" > </ head > Below are the some example contents of an external CSS file, like the \"my_experiment_style.css\" from the example above. This CSS will (1) change the page background color to black, (2) change the default font to 25px and white, and (3) limit the width of the page content so that it can only take up to 80% of its normal width. body { background-color : black ; } . jspsych-display-element { font-size : 25 px ; color : white ; } . jspsych-content { max-width : 80 % ; } Note <style> tags are not used inside of an external CSS file.","title":"With a stylesheet"},{"location":"overview/style/#using-the-css_classes-trial-parameter","text":"CSS rules can also be applied in a trial-specific way using the css_classes parameter. This parameter will apply one or more class to the <div> element that holds all of the jsPsych page content during that specific trial. This way you can treat CSS styles just like any other trial parameter. You can use a static css_classes parameter value if you always want to apply the same CSS rules to the trial. In the 'fixation' example below, separating the style rules from the stimulus string makes the code a little bit 'cleaner', and this makes it easier to re-use the same style rules in other parts of the experiment. < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < style > . fixation { font-size : 90 px ; font-weight : bold ; color : gray ;} </ style > </ head > < script > var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 , css_classes : [ 'fixation' ] } // ... </ script > You may want the css_classes parameter to vary across trials. If so, you can turn it into a dynamic parameter or use timeline variables (see examples below). One thing to note about the css_classes parameter is that it only adds the class(es) to the jspsych-content <div> element, which is the \"parent\" element that contains all of the experiment content. Often you'll want your CSS rules to be applied to other elements inside of this jspsych-content div. Sometimes your CSS rules will be \"inherited\" by all of the other jsPsych content inside of this parent <div>. For instance, in the fixation example above, the CSS rules that change the font size, weight and color are applied to the parent <div> and automatically passed on to the stimulus text through inheritance. There are two reasons why a CSS rule like the one above for fixation may not work the way you expect: Not all CSS properties are inherited from the parent element. When a CSS property is inherited from the parent element, it will affect all elements in a given trial. In these cases, you can change your CSS selector to make it more specific: add a space after class name, then add more CSS selectors to select the specific element(s) that you want to change. Tip To find out this more specific CSS selector, you can right-click on the element and select Inspect . In the inspector window, right-click on the property corresponding to the element and copy the selector. You might need to increase the trial's trial_duration to give yourself enough time to inspect the elements on the page. See more tips for working with CSS below. In the example below, the CSS selector .left-align #stimulus selects the element with the ID \"stimulus\" that is inside of an element with the class \"left-align\". < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < style > . left-align # stimulus { text-align : left ; width : 600 px ;} . right-align # stimulus { text-align : right ; width : 600 px ;} </ style > </ head > < script > var trial_procedure = { timeline : [{ type : jsPsychHtmlKeyboardResponse , stimulus : '<p id=\"stimulus\">This is the stimulus.</p>' , prompt : '<p>This text will not be affected by the CSS classes ' + 'because it does not have the \"stimulus\" ID.</p>' , css_classes : jsPsych . timelineVariable ( 'css_classes' ) }], timeline_variables : [ { css_classes : [ 'left-align' ]}, { css_classes : [ 'right-align' ]} ] } // ... </ script > It's also possible to pass multiple class names to the css_classes parameter. This can be useful for creating conditions that involve crossing different style-related factors. This example shows you to combine two text alignment and two text color factors to produce four different stimulus conditions: < head > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" > < style > . left-align # stimulus { text-align : left ; width : 600 px ;} . right-align # stimulus { text-align : right ; width : 600 px ;} . teal # stimulus { color : teal ;} . purple # stimulus { color : purple ;} </ style > </ head > < script > var trial_procedure = { timeline : [{ type : jsPsychHtmlKeyboardResponse , stimulus : '<p id=\"stimulus\">This is the stimulus.</p>' , prompt : '<p>This text will not be affected by the CSS classes ' + 'because it does not have the \"stimulus\" ID.</p>' , css_classes : jsPsych . timelineVariable ( 'css_classes' ), data : { condition : jsPsych . timelineVariable ( 'condition' )} }], timeline_variables : [ { css_classes : [ 'left-align' , 'teal' ], condition : 'left-teal' }, { css_classes : [ 'right-align' , 'teal' ], condition : 'right-teal' }, { css_classes : [ 'left-align' , 'purple' ], condition : 'left-purple' }, { css_classes : [ 'right-align' , 'purple' ], condition : 'right-purple' } ] } // ... </ script > See the \"css-classes-parameter.html\" file in jsPsych's examples subfolder for more explanation and examples.","title":"Using the css_classes trial parameter"},{"location":"overview/style/#tips-for-working-with-css","text":"Your browser's developer tools contain very useful features for exploring and debugging your experiment's style and formatting. Open your browser's developer tools and click on the Element Inspector button or go to the Elements tab. Once you have selected an element on the page, you can see all of the information that can be used to select it, including: tag name, e.g., \"div\", \"p\", \"img\", \"button\" ID, if it has one class(es), if it has any You can then use this information to create a CSS selector to modify that element's style. As you can see, jsPsych adds its own IDs and classes to many elements. You can use the developer tools to determine what IDs and classes already exist for the elements that you want to modify, as you may can often just use these instead of adding your own. For instance, in the \"html-keyboard-response\" plugin, the stimulus will always be shown in a <div> with the ID \"jspsych-html-keyboard-response-stimulus\". So you can create a CSS rule that is applied to all \"html-keyboard-response\" stimuli like this: # jspsych-html-keyboard-response-stimulus { color : white ; background-color : blue ; width : 100 px ; border : 4 px solid black ; } As another example, most jsPsych buttons have the class \"jspsych-btn\", so you can use this class to change the default button styling: . jspsych-btn { padding : 20 px 20 px ; font-size : 25 px ; border-color : black ; } You can also use the developer tools to change an element's CSS and immediately see the effect that the changes will have on the page. These changes are just temporary, so you will still need to use one of methods described above to add the CSS changes to your experiment. However, making changes in the developer tools is very useful for figuring out which CSS properties to change and which values to use. This area of the developer tools also shows what styles are currently applied to the element and where those style rules are coming from. There are a few things to be aware of while debugging problems with CSS. When there are conflicting CSS rules, some CSS rules will take precedence over others . For instance, inline CSS usually takes precedence over other CSS rules, and more specific CSS selectors usually take precedence over less specific ones. When there are conflicting CSS rules that have the same level of precedence, the last rule will override any earlier rules . For that reason it's important to add your own custom stylesheet after the default jspsych.css stylesheet. See this page about CSS precedence for more information. If one CSS style rule is overridden by another one, the rule that is overridden will appear in strikethrough text in the element's \"Styles\" section. Also, if you are using an incorrect CSS property name or an invalid value, then that will show up here as an error, indicated by both strikethrough text and a little yellow warning symbol.","title":"Tips for working with CSS"},{"location":"overview/timeline/","text":"Creating an Experiment: The Timeline \u00b6 To create an experiment using jsPsych, you need to specify a timeline that describes the structure of the experiment. The timeline is an ordered set of trials. You must create the timeline before launching the experiment. Most of the code you will write for an experiment will be code to create the timeline. This page walks through the creation of timelines, including very basic examples and more advanced features. A single trial \u00b6 To create a trial, you need to create an object that describes the trial. The most important feature of this object is the type parameter. This tells jsPsych which plugin to use to run the trial. For example, if you want to use the html-keyboard-response plugin to display a short message, the trial object would look like this: var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Welcome to the experiment.' } The parameters for this object (e.g., stimulus ) will depend on the plugin that you choose. Each plugin defines the set of parameters that are needed to run a trial with that plugin. Visit the documentation for a plugin to learn about the parameters that you can use with that plugin. To create a timeline with the single trial and run the experiment, just embed the trial object in an array. A timeline can simply be an array of trials. var timeline = [ trial ]; jsPsych . run ( timeline ); To create and run a simple experiment like this complete the hello world tutorial . Multiple trials \u00b6 Scaling up to multiple trials is straightforward. Create an object for each trial, and add each object to the timeline array. // with lots of trials, it might be easier to add the trials // to the timeline array as they are defined. var timeline = []; var trial_1 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 1.' } timeline . push ( trial_1 ); var trial_2 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 2.' } timeline . push ( trial_2 ); var trial_3 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 3.' } timeline . push ( trial_3 ); Nested timelines \u00b6 Each object on the timeline can also have it's own timeline. This is useful for many reasons. One is that it allows you to define common parameters across trials once and have them apply to all the trials on the nested timeline. The example below creates a series of trials using the image-keyboard-response plugin , where the only thing that changes from trial-to-trial is the image file being displayed on the screen. var judgment_trials = { type : jsPsychImageKeyboardResponse , prompt : '<p>Press a number 1-7 to indicate how unusual the image is.</p>' , choices : [ '1' , '2' , '3' , '4' , '5' , '6' , '7' ], timeline : [ { stimulus : 'image1.png' }, { stimulus : 'image2.png' }, { stimulus : 'image3.png' } ] } In the above code, the type , prompt , and choices parameters are automatically applied to all of the objects in the timeline array. This creates three trials with the same type , prompt , and choices parameters, but different values for the stimulus parameter. You can also override the values by declaring a new value in the timeline array. In the example below, the second trial will display a different prompt message. var judgment_trials = { type : jsPsychImageKeyboardResponse , prompt : '<p>Press a number 1-7 to indicate how unusual the image is.</p>' , choices : [ '1' , '2' , '3' , '4' , '5' , '6' , '7' ], timeline : [ { stimulus : 'image1.png' }, { stimulus : 'image2.png' , prompt : '<p>Press 1 for this trial.</p>' }, { stimulus : 'image3.png' } ] } Timelines can be nested any number of times. Timeline variables \u00b6 A common pattern in behavioral experiments is to repeat the same procedure/task many times with slightly different parameters. A procedure might be a single trial, but it also might be a series of trials. For example, a task might involve a fixation cross appearing, followed by a blank screen, followed by an image for a short duration, followed by a prompt and a text box to report on some aspect of the image. One shortcut to implement this pattern is with the nested timeline approach described in the previous section, but this only works if all the trials use the same plugin type. Timeline variables are a more general solution. With timeline variables you define the procedure once (as a timeline) and specify a set of parameters and their values for each iteration through the timeline. What follows is an example of how to use timeline variables. The simple reaction time tutorial also explains how to use timeline variables. Suppose we want to create an experiment where people see a set of faces. Perhaps this is a memory experiment and this is the phase of the experiment where the faces are being presented for the first time. In between each face, a fixation cross is displayed on the screen. Without timeline variables, we would need to add many trials to the timeline, alternating between trials showing the fixation cross and trials showing the face and name. This could be done efficiently using a loop or function to create the timeline, but timeline variables make it even easier - as well as adding extra features like sampling and randomization. Here's a basic version of the task with timeline variables. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'face' ), choices : \"NO_KEYS\" , trial_duration : 2500 } ], timeline_variables : [ { face : 'person-1.jpg' }, { face : 'person-2.jpg' }, { face : 'person-3.jpg' }, { face : 'person-4.jpg' } ] } In the above version, there are four separate trials defined in the timeline_variables parameter. Each trial has a variable face and a variable name . The timeline defines a procedure of showing a fixation cross for 500ms followed by the face and name for 2500ms. This procedure will repeat four times, with the first trial showing 'person-1.jpg' , the second 'person-2.jpg' , and so on. The variables are referenced within the procedure by calling the jsPsych.timelineVariable() method and passing in the name of the variable. What if we wanted to add an additional step to the task where the name is displayed prior to the face appearing? (Maybe this is one condition of an experiment investigating whether the order of name-face or face-name affects retention.) We can add another variable to our list that gives the name associated with each image. Then we can add another trial to our timeline to show the name. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychHtmlKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'name' ), trial_duration : 1000 , choices : \"NO_KEYS\" }, { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'face' ), choices : \"NO_KEYS\" , trial_duration : 1000 } ], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ] } Using in a function \u00b6 Continung the example from the previous section, what if we wanted to show the name with the face, combining the two variables together? To do this, we can use a dynamic parameter (a function) to create an HTML-string that uses both variables in a single parameter. The value of the stimulus parameter will be a function that returns an HTML string that contains both the image and the name. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychHtmlKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'name' ), trial_duration : 1000 , choices : \"NO_KEYS\" }, { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ var html = ` <img src=\" ${ jsPsych . timelineVariable ( 'face' ) } \"> <p> ${ jsPsych . timelineVariable ( 'name' ) } </p>` ; return html ; }, choices : \"NO_KEYS\" , trial_duration : 2500 } ], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ] } Random orders of trials \u00b6 If we want to randomize the order of the trials, we can set randomize_order to true . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true } Sampling methods \u00b6 There are also sampling methods that can be used to select a set of trials from the timeline_variables. Sampling is declared by creating a sample parameter. The sample parameter is given an object of arguments. The type parameter in this object controls the type of sampling that is done. Valid values for type are \"with-replacement\" : Sample size items from the timeline variables with the possibility of choosing the same item multiple time. \"without-replacement\" : Sample size items from timeline variables, with each item being selected a maximum of 1 time. \"fixed-repetitons\" : Repeat each item in the timeline variables size times, in a random order. Unlike using the repetitons parameter, this method allows for consecutive trials to use the same timeline variable set. \"alternate-groups\" : Sample in an alternating order based on a declared group membership. Groups are defined by the groups parameter. This parameter takes an array of arrays, where each inner array is a group and the items in the inner array are the indices of the timeline variables in the timeline_variables array that belong to that group. \"custom\" : Write a function that returns a custom order of the timeline variables. Sampling with replacement \u00b6 This sample parameter will create 10 repetitions, sampling with replacement. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'with-replacement' , size : 10 } } Sampling with replacement, unequal probabilities \u00b6 This sample parameter will make the \"Alex\" trial three times as likely to be sampled as the others. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'with-replacement' , size : 10 , weights : [ 3 , 1 , 1 , 1 ] } } Sampling without replacement \u00b6 This sample parameter will pick three of the four possible trials to run at random. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'without-replacement' , size : 3 } } Repeating each trial a fixed number of times in a random order \u00b6 This sample parameter will create 3 repetitions of each trial, for a total of 12 trials, with a random order. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'fixed-repetitions' , size : 3 } } Alternating groups \u00b6 This sample parameter puts the \"Alex\" and \"Chad\" trials in group 1 and the \"Beth\" and \"Dave\" trials in group 2. The resulting sample of trials will follow the pattern group 1 -> group 2 -> group 1 -> group 2 . Each trial will be selected only one time. If you wanted group 2 to sometimes be first, you could set randomize_group_order: true . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'alternate-groups' , groups : [[ 0 , 2 ],[ 1 , 3 ]], randomize_group_order : false } } Custom sampling function \u00b6 Any sampling method can be implemented using the custom type sampler. The order of trials will be determined by running the function supplied as fn . The function has a single parameter, t , which is an array of integers from 0 to n-1 , where n is the number of trials in the timeline_variables array. The function must return an array that specifies the order of the trials, e.g., returning [3,3,2,2,1,1,0,0] would result in the order Dave -> Dave -> Chad -> Chad -> Beth -> Beth -> Alex -> Alex . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'custom' , fn : function ( t ){ return t . reverse (); // show the trials in the reverse order } } } Repeating a set of trials \u00b6 To repeat a timeline multiple times, you can create an object (node) that contains a timeline , which is the timeline array to repeat, and repetitions , which is the number of times to repeat that timeline. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will be repeated twice.' } var node = { timeline : [ trial ], repetitions : 2 } The repetitions parameter can be used alongside other node parameters, such as timeline variables, loop functions, and/or conditional functions. If you are using timeline_variables and randomize_order is true , then the order of the timeline variables will re-randomize before every repetition. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true , repetitions : 3 } Looping timelines \u00b6 Any timeline can be looped using the loop_function option. The loop function must be a function that evaluates to true if the timeline should repeat, and false if the timeline should end. It receives a single parameter, named data by convention. This parameter will be the DataCollection object with all of the data from the trials executed in the last iteration of the timeline. The loop function will be evaluated after the timeline is completed. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial is in a loop. Press R to repeat this trial, or C to continue.' } var loop_node = { timeline : [ trial ], loop_function : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . values ()[ 0 ]. response , 'r' )){ return true ; } else { return false ; } } } Conditional timelines \u00b6 A timeline can be skipped or not based on the evaluation of the conditional_function option. If the conditional function evaluates to true , the timeline will execute normally. If the conditional function evaluates to false then the timeline will be skipped. The conditional function is evaluated whenever jsPsych is about to run the first trial on the timeline. var jsPsych = initJsPsych (); var pre_if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'The next trial is in a conditional statement. Press S to skip it, or V to view it.' } var if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'You chose to view the trial. Press any key to continue.' } var if_node = { timeline : [ if_trial ], conditional_function : function (){ // get the data from the previous trial, // and check which key was pressed var data = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]; if ( jsPsych . pluginAPI . compareKeys ( data . response , 's' )){ return false ; } else { return true ; } } } var after_if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is the trial after the conditional.' } jsPsych . run ([ pre_if_trial , if_node , after_if_trial ]); Timeline start and finish functions \u00b6 You can run a custom function at the start and end of a timeline node using the on_timeline_start and on_timeline_finish callback function parameters. These are functions that will run when the timeline starts and ends, respectively. var procedure = { timeline : [ trial_1 , trial_2 ], on_timeline_start : function () { console . log ( 'The trial procedure just started.' ) }, on_timeline_finish : function () { console . log ( 'The trial procedure just finished.' ) } } This works the same way with timeline variables. The on_timeline_start and on_timeline_finish functions will run when timeline variables trials start and end, respectively. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true , on_timeline_start : function () { console . log ( 'First trial is starting.' ) }, on_timeline_finish : function () { console . log ( 'Last trial just finished.' ) } } When the repetititons option is used (and is greater than 1), these functions will run once per repetition of the timeline. var repetition_count = 0 ; var procedure = { timeline : [ trial_1 , trial_2 ], repetitions : 3 , on_timeline_start : function () { repetition_count ++ ; console . log ( 'Repetition number ' , repetition_count , ' has just started.' ); }, on_timeline_finish : function () { console . log ( 'Repetition number ' , repetition_count , ' has just finished.' ) } }","title":"Creating an Experiment: The Timeline"},{"location":"overview/timeline/#creating-an-experiment-the-timeline","text":"To create an experiment using jsPsych, you need to specify a timeline that describes the structure of the experiment. The timeline is an ordered set of trials. You must create the timeline before launching the experiment. Most of the code you will write for an experiment will be code to create the timeline. This page walks through the creation of timelines, including very basic examples and more advanced features.","title":"Creating an Experiment: The Timeline"},{"location":"overview/timeline/#a-single-trial","text":"To create a trial, you need to create an object that describes the trial. The most important feature of this object is the type parameter. This tells jsPsych which plugin to use to run the trial. For example, if you want to use the html-keyboard-response plugin to display a short message, the trial object would look like this: var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Welcome to the experiment.' } The parameters for this object (e.g., stimulus ) will depend on the plugin that you choose. Each plugin defines the set of parameters that are needed to run a trial with that plugin. Visit the documentation for a plugin to learn about the parameters that you can use with that plugin. To create a timeline with the single trial and run the experiment, just embed the trial object in an array. A timeline can simply be an array of trials. var timeline = [ trial ]; jsPsych . run ( timeline ); To create and run a simple experiment like this complete the hello world tutorial .","title":"A single trial"},{"location":"overview/timeline/#multiple-trials","text":"Scaling up to multiple trials is straightforward. Create an object for each trial, and add each object to the timeline array. // with lots of trials, it might be easier to add the trials // to the timeline array as they are defined. var timeline = []; var trial_1 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 1.' } timeline . push ( trial_1 ); var trial_2 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 2.' } timeline . push ( trial_2 ); var trial_3 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 3.' } timeline . push ( trial_3 );","title":"Multiple trials"},{"location":"overview/timeline/#nested-timelines","text":"Each object on the timeline can also have it's own timeline. This is useful for many reasons. One is that it allows you to define common parameters across trials once and have them apply to all the trials on the nested timeline. The example below creates a series of trials using the image-keyboard-response plugin , where the only thing that changes from trial-to-trial is the image file being displayed on the screen. var judgment_trials = { type : jsPsychImageKeyboardResponse , prompt : '<p>Press a number 1-7 to indicate how unusual the image is.</p>' , choices : [ '1' , '2' , '3' , '4' , '5' , '6' , '7' ], timeline : [ { stimulus : 'image1.png' }, { stimulus : 'image2.png' }, { stimulus : 'image3.png' } ] } In the above code, the type , prompt , and choices parameters are automatically applied to all of the objects in the timeline array. This creates three trials with the same type , prompt , and choices parameters, but different values for the stimulus parameter. You can also override the values by declaring a new value in the timeline array. In the example below, the second trial will display a different prompt message. var judgment_trials = { type : jsPsychImageKeyboardResponse , prompt : '<p>Press a number 1-7 to indicate how unusual the image is.</p>' , choices : [ '1' , '2' , '3' , '4' , '5' , '6' , '7' ], timeline : [ { stimulus : 'image1.png' }, { stimulus : 'image2.png' , prompt : '<p>Press 1 for this trial.</p>' }, { stimulus : 'image3.png' } ] } Timelines can be nested any number of times.","title":"Nested timelines"},{"location":"overview/timeline/#timeline-variables","text":"A common pattern in behavioral experiments is to repeat the same procedure/task many times with slightly different parameters. A procedure might be a single trial, but it also might be a series of trials. For example, a task might involve a fixation cross appearing, followed by a blank screen, followed by an image for a short duration, followed by a prompt and a text box to report on some aspect of the image. One shortcut to implement this pattern is with the nested timeline approach described in the previous section, but this only works if all the trials use the same plugin type. Timeline variables are a more general solution. With timeline variables you define the procedure once (as a timeline) and specify a set of parameters and their values for each iteration through the timeline. What follows is an example of how to use timeline variables. The simple reaction time tutorial also explains how to use timeline variables. Suppose we want to create an experiment where people see a set of faces. Perhaps this is a memory experiment and this is the phase of the experiment where the faces are being presented for the first time. In between each face, a fixation cross is displayed on the screen. Without timeline variables, we would need to add many trials to the timeline, alternating between trials showing the fixation cross and trials showing the face and name. This could be done efficiently using a loop or function to create the timeline, but timeline variables make it even easier - as well as adding extra features like sampling and randomization. Here's a basic version of the task with timeline variables. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'face' ), choices : \"NO_KEYS\" , trial_duration : 2500 } ], timeline_variables : [ { face : 'person-1.jpg' }, { face : 'person-2.jpg' }, { face : 'person-3.jpg' }, { face : 'person-4.jpg' } ] } In the above version, there are four separate trials defined in the timeline_variables parameter. Each trial has a variable face and a variable name . The timeline defines a procedure of showing a fixation cross for 500ms followed by the face and name for 2500ms. This procedure will repeat four times, with the first trial showing 'person-1.jpg' , the second 'person-2.jpg' , and so on. The variables are referenced within the procedure by calling the jsPsych.timelineVariable() method and passing in the name of the variable. What if we wanted to add an additional step to the task where the name is displayed prior to the face appearing? (Maybe this is one condition of an experiment investigating whether the order of name-face or face-name affects retention.) We can add another variable to our list that gives the name associated with each image. Then we can add another trial to our timeline to show the name. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychHtmlKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'name' ), trial_duration : 1000 , choices : \"NO_KEYS\" }, { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'face' ), choices : \"NO_KEYS\" , trial_duration : 1000 } ], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ] }","title":"Timeline variables"},{"location":"overview/timeline/#using-in-a-function","text":"Continung the example from the previous section, what if we wanted to show the name with the face, combining the two variables together? To do this, we can use a dynamic parameter (a function) to create an HTML-string that uses both variables in a single parameter. The value of the stimulus parameter will be a function that returns an HTML string that contains both the image and the name. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychHtmlKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'name' ), trial_duration : 1000 , choices : \"NO_KEYS\" }, { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ var html = ` <img src=\" ${ jsPsych . timelineVariable ( 'face' ) } \"> <p> ${ jsPsych . timelineVariable ( 'name' ) } </p>` ; return html ; }, choices : \"NO_KEYS\" , trial_duration : 2500 } ], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ] }","title":"Using in a function"},{"location":"overview/timeline/#random-orders-of-trials","text":"If we want to randomize the order of the trials, we can set randomize_order to true . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true }","title":"Random orders of trials"},{"location":"overview/timeline/#sampling-methods","text":"There are also sampling methods that can be used to select a set of trials from the timeline_variables. Sampling is declared by creating a sample parameter. The sample parameter is given an object of arguments. The type parameter in this object controls the type of sampling that is done. Valid values for type are \"with-replacement\" : Sample size items from the timeline variables with the possibility of choosing the same item multiple time. \"without-replacement\" : Sample size items from timeline variables, with each item being selected a maximum of 1 time. \"fixed-repetitons\" : Repeat each item in the timeline variables size times, in a random order. Unlike using the repetitons parameter, this method allows for consecutive trials to use the same timeline variable set. \"alternate-groups\" : Sample in an alternating order based on a declared group membership. Groups are defined by the groups parameter. This parameter takes an array of arrays, where each inner array is a group and the items in the inner array are the indices of the timeline variables in the timeline_variables array that belong to that group. \"custom\" : Write a function that returns a custom order of the timeline variables.","title":"Sampling methods"},{"location":"overview/timeline/#sampling-with-replacement","text":"This sample parameter will create 10 repetitions, sampling with replacement. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'with-replacement' , size : 10 } }","title":"Sampling with replacement"},{"location":"overview/timeline/#sampling-with-replacement-unequal-probabilities","text":"This sample parameter will make the \"Alex\" trial three times as likely to be sampled as the others. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'with-replacement' , size : 10 , weights : [ 3 , 1 , 1 , 1 ] } }","title":"Sampling with replacement, unequal probabilities"},{"location":"overview/timeline/#sampling-without-replacement","text":"This sample parameter will pick three of the four possible trials to run at random. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'without-replacement' , size : 3 } }","title":"Sampling without replacement"},{"location":"overview/timeline/#repeating-each-trial-a-fixed-number-of-times-in-a-random-order","text":"This sample parameter will create 3 repetitions of each trial, for a total of 12 trials, with a random order. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'fixed-repetitions' , size : 3 } }","title":"Repeating each trial a fixed number of times in a random order"},{"location":"overview/timeline/#alternating-groups","text":"This sample parameter puts the \"Alex\" and \"Chad\" trials in group 1 and the \"Beth\" and \"Dave\" trials in group 2. The resulting sample of trials will follow the pattern group 1 -> group 2 -> group 1 -> group 2 . Each trial will be selected only one time. If you wanted group 2 to sometimes be first, you could set randomize_group_order: true . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'alternate-groups' , groups : [[ 0 , 2 ],[ 1 , 3 ]], randomize_group_order : false } }","title":"Alternating groups"},{"location":"overview/timeline/#custom-sampling-function","text":"Any sampling method can be implemented using the custom type sampler. The order of trials will be determined by running the function supplied as fn . The function has a single parameter, t , which is an array of integers from 0 to n-1 , where n is the number of trials in the timeline_variables array. The function must return an array that specifies the order of the trials, e.g., returning [3,3,2,2,1,1,0,0] would result in the order Dave -> Dave -> Chad -> Chad -> Beth -> Beth -> Alex -> Alex . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'custom' , fn : function ( t ){ return t . reverse (); // show the trials in the reverse order } } }","title":"Custom sampling function"},{"location":"overview/timeline/#repeating-a-set-of-trials","text":"To repeat a timeline multiple times, you can create an object (node) that contains a timeline , which is the timeline array to repeat, and repetitions , which is the number of times to repeat that timeline. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will be repeated twice.' } var node = { timeline : [ trial ], repetitions : 2 } The repetitions parameter can be used alongside other node parameters, such as timeline variables, loop functions, and/or conditional functions. If you are using timeline_variables and randomize_order is true , then the order of the timeline variables will re-randomize before every repetition. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true , repetitions : 3 }","title":"Repeating a set of trials"},{"location":"overview/timeline/#looping-timelines","text":"Any timeline can be looped using the loop_function option. The loop function must be a function that evaluates to true if the timeline should repeat, and false if the timeline should end. It receives a single parameter, named data by convention. This parameter will be the DataCollection object with all of the data from the trials executed in the last iteration of the timeline. The loop function will be evaluated after the timeline is completed. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial is in a loop. Press R to repeat this trial, or C to continue.' } var loop_node = { timeline : [ trial ], loop_function : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . values ()[ 0 ]. response , 'r' )){ return true ; } else { return false ; } } }","title":"Looping timelines"},{"location":"overview/timeline/#conditional-timelines","text":"A timeline can be skipped or not based on the evaluation of the conditional_function option. If the conditional function evaluates to true , the timeline will execute normally. If the conditional function evaluates to false then the timeline will be skipped. The conditional function is evaluated whenever jsPsych is about to run the first trial on the timeline. var jsPsych = initJsPsych (); var pre_if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'The next trial is in a conditional statement. Press S to skip it, or V to view it.' } var if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'You chose to view the trial. Press any key to continue.' } var if_node = { timeline : [ if_trial ], conditional_function : function (){ // get the data from the previous trial, // and check which key was pressed var data = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]; if ( jsPsych . pluginAPI . compareKeys ( data . response , 's' )){ return false ; } else { return true ; } } } var after_if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is the trial after the conditional.' } jsPsych . run ([ pre_if_trial , if_node , after_if_trial ]);","title":"Conditional timelines"},{"location":"overview/timeline/#timeline-start-and-finish-functions","text":"You can run a custom function at the start and end of a timeline node using the on_timeline_start and on_timeline_finish callback function parameters. These are functions that will run when the timeline starts and ends, respectively. var procedure = { timeline : [ trial_1 , trial_2 ], on_timeline_start : function () { console . log ( 'The trial procedure just started.' ) }, on_timeline_finish : function () { console . log ( 'The trial procedure just finished.' ) } } This works the same way with timeline variables. The on_timeline_start and on_timeline_finish functions will run when timeline variables trials start and end, respectively. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true , on_timeline_start : function () { console . log ( 'First trial is starting.' ) }, on_timeline_finish : function () { console . log ( 'Last trial just finished.' ) } } When the repetititons option is used (and is greater than 1), these functions will run once per repetition of the timeline. var repetition_count = 0 ; var procedure = { timeline : [ trial_1 , trial_2 ], repetitions : 3 , on_timeline_start : function () { repetition_count ++ ; console . log ( 'Repetition number ' , repetition_count , ' has just started.' ); }, on_timeline_finish : function () { console . log ( 'Repetition number ' , repetition_count , ' has just finished.' ) } }","title":"Timeline start and finish functions"},{"location":"overview/timing-accuracy/","text":"Timing accuracy \u00b6 Wondering if jsPsych can be used for research that depends on accurate display times or response time measurement? For most purposes, the answer is yes. Display timing is somewhat less accurate in JavaScript than in standard experimental software that runs on a desktop. Desktop software can have closer integration with the graphics devices of the machine than JavaScript currently permits. If a one or two frame (17-33ms) difference in display timing matters for your experiment, then you'll want to be careful with JavaScript-based experiments. It is possible to achieve this level of control in JavaScript, but it often requires code that is more tailored to your experiment and some restrictions about which browsers can be used to run the experiment. Tip If you are hoping to run an experiment with the best timing that jsPsych can offer, we currently recommend using the jspsych-psychophysics plugin developed by Daiichiro Kuroki . Kuroki, D. (2021). A new jsPsych plugin for psychophysics, providing accurate display duration and stimulus onset asynchrony. Behavior Research Methods , 53 , 301\u2013310. https://doi.org/10.3758/s13428-020-01445-w Response time measurements in jsPsych (and JavaScript in general) are comparable to those taken in standard lab software like Psychophysics Toolbox and E-Prime. Response times measured in JavaScript tend to be a little bit longer (10-40ms), but have similar variance. References \u00b6 See the following papers for extensive work on display and response timing in browser-based experiments. Note that browsers are updating frequently and the JavaScript language specification is also changing. It's possible that the results from these papers do not apply to current versions of web browsers. Future updates to JavaScript APIs will likely improve the ability of online experiments to provide more accurate display timing and response time measurement. Bridges, D., Pitiot, A., MacAskill, M. R., & Peirce, J. W. (2020). The timing mega-study: Comparing a range of experiment generators, both lab-based and online. PeerJ, 8 , e9414. Anwyl-Irvine, A., Dalmaijer, E. S., Hodges, N., & Evershed, J. K. (2020). Realistic precision and accuracy of online experiment platforms, web browsers, and devices. Behavior Research Methods, 53, 1-19. Pronk, T., Wiers, R. W., Molenkamp, B., & Murre, J. (2020). Mental chronometry in the pocket? Timing accuracy of web applications on touchscreen and keyboard devices. Behavior Research Methods, 52 (3), 1371-1382. Pinet, S., Zielinski, C., Math\u00f4t, S. et al. (2017). Measuring sequences of keystrokes with jsPsych: Reliability of response times and interkeystroke intervals. Behavior Research Methods , 49 (3), 1177-1178. de Leeuw, J. R., & Motz, B. A. (2016). Psychophysics in a Web browser? Comparing response times collected with JavaScript and Psychophysics Toolbox in a visual search task. Behavior Research Methods , 48 (1), 1-12. Hilbig, B. E. (2016). Reaction time effects in lab- versus web-based research: Experimental evidence. Behavior Research Methods , 48 (4), 1718-1724. Reimers, S., & Stewart, N. (2015). Presentation and response time accuracy in Adobe Flash and HTML5/JavaScript Web experiments. Behavior Research Methods , 47 (2), 309-327.","title":"Timing Accuracy"},{"location":"overview/timing-accuracy/#timing-accuracy","text":"Wondering if jsPsych can be used for research that depends on accurate display times or response time measurement? For most purposes, the answer is yes. Display timing is somewhat less accurate in JavaScript than in standard experimental software that runs on a desktop. Desktop software can have closer integration with the graphics devices of the machine than JavaScript currently permits. If a one or two frame (17-33ms) difference in display timing matters for your experiment, then you'll want to be careful with JavaScript-based experiments. It is possible to achieve this level of control in JavaScript, but it often requires code that is more tailored to your experiment and some restrictions about which browsers can be used to run the experiment. Tip If you are hoping to run an experiment with the best timing that jsPsych can offer, we currently recommend using the jspsych-psychophysics plugin developed by Daiichiro Kuroki . Kuroki, D. (2021). A new jsPsych plugin for psychophysics, providing accurate display duration and stimulus onset asynchrony. Behavior Research Methods , 53 , 301\u2013310. https://doi.org/10.3758/s13428-020-01445-w Response time measurements in jsPsych (and JavaScript in general) are comparable to those taken in standard lab software like Psychophysics Toolbox and E-Prime. Response times measured in JavaScript tend to be a little bit longer (10-40ms), but have similar variance.","title":"Timing accuracy"},{"location":"overview/timing-accuracy/#references","text":"See the following papers for extensive work on display and response timing in browser-based experiments. Note that browsers are updating frequently and the JavaScript language specification is also changing. It's possible that the results from these papers do not apply to current versions of web browsers. Future updates to JavaScript APIs will likely improve the ability of online experiments to provide more accurate display timing and response time measurement. Bridges, D., Pitiot, A., MacAskill, M. R., & Peirce, J. W. (2020). The timing mega-study: Comparing a range of experiment generators, both lab-based and online. PeerJ, 8 , e9414. Anwyl-Irvine, A., Dalmaijer, E. S., Hodges, N., & Evershed, J. K. (2020). Realistic precision and accuracy of online experiment platforms, web browsers, and devices. Behavior Research Methods, 53, 1-19. Pronk, T., Wiers, R. W., Molenkamp, B., & Murre, J. (2020). Mental chronometry in the pocket? Timing accuracy of web applications on touchscreen and keyboard devices. Behavior Research Methods, 52 (3), 1371-1382. Pinet, S., Zielinski, C., Math\u00f4t, S. et al. (2017). Measuring sequences of keystrokes with jsPsych: Reliability of response times and interkeystroke intervals. Behavior Research Methods , 49 (3), 1177-1178. de Leeuw, J. R., & Motz, B. A. (2016). Psychophysics in a Web browser? Comparing response times collected with JavaScript and Psychophysics Toolbox in a visual search task. Behavior Research Methods , 48 (1), 1-12. Hilbig, B. E. (2016). Reaction time effects in lab- versus web-based research: Experimental evidence. Behavior Research Methods , 48 (4), 1718-1724. Reimers, S., & Stewart, N. (2015). Presentation and response time accuracy in Adobe Flash and HTML5/JavaScript Web experiments. Behavior Research Methods , 47 (2), 309-327.","title":"References"},{"location":"plugins/animation/","text":"animation \u00b6 Current version: 1.1.2. See version history . This plugin displays a sequence of images at a fixed frame rate. The sequence can be looped a specified number of times. The participant is free to respond at any point during the animation, and the time of the response is recorded. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of the array is a path to an image file. frame_time numeric 250 How long to display each image in milliseconds. frame_isi numeric 0 If greater than 0, then a gap will be shown between each image in the sequence. This parameter specifies the length of the gap in milliseconds. sequence_reps numeric 1 How many times to show the entire sequence. There will be no gap (other than the gap specified by frame_isi ) between repetitions. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key(s) to press). render_on_canvas boolean true If true, the images will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive images in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value animation_sequence array An array, where each element is an object that represents a stimulus in the animation sequence. Each object has a stimulus property, which is the image that was displayed, and a time property, which is the time in ms, measured from when the sequence began, that the stimulus was displayed. The array will be encoded in JSON format when data is saved using either the .json() or .csv() functions. response array An array, where each element is an object representing a response given by the participant. Each object has a stimulus property, indicating which image was displayed when the key was pressed, an rt property, indicating the time of the key press relative to the start of the animation, and a key_press property, indicating which key was pressed. The array will be encoded in JSON format when data is saved using either the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-animation@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-animation.js\" >< /script> Using NPM: npm install @jspsych/plugin-animation import animation from '@jspsych/plugin-animation' ; Examples \u00b6 Displaying a single sequence multiple times Code Demo var animation_sequence = [ \"img/happy_face_1.jpg\" , \"img/happy_face_2.jpg\" , \"img/happy_face_3.jpg\" , \"img/happy_face_4.jpg\" ]; var animation_trial = { type : jsPsychAnimation , stimuli : animation_sequence , sequence_reps : 3 , frame_time : 300 , prompt : '<p>Watch the faces.</p>' , }; Open demo in new tab","title":"animation"},{"location":"plugins/animation/#animation","text":"Current version: 1.1.2. See version history . This plugin displays a sequence of images at a fixed frame rate. The sequence can be looped a specified number of times. The participant is free to respond at any point during the animation, and the time of the response is recorded.","title":"animation"},{"location":"plugins/animation/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of the array is a path to an image file. frame_time numeric 250 How long to display each image in milliseconds. frame_isi numeric 0 If greater than 0, then a gap will be shown between each image in the sequence. This parameter specifies the length of the gap in milliseconds. sequence_reps numeric 1 How many times to show the entire sequence. There will be no gap (other than the gap specified by frame_isi ) between repetitions. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key(s) to press). render_on_canvas boolean true If true, the images will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive images in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych.","title":"Parameters"},{"location":"plugins/animation/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value animation_sequence array An array, where each element is an object that represents a stimulus in the animation sequence. Each object has a stimulus property, which is the image that was displayed, and a time property, which is the time in ms, measured from when the sequence began, that the stimulus was displayed. The array will be encoded in JSON format when data is saved using either the .json() or .csv() functions. response array An array, where each element is an object representing a response given by the participant. Each object has a stimulus property, indicating which image was displayed when the key was pressed, an rt property, indicating the time of the key press relative to the start of the animation, and a key_press property, indicating which key was pressed. The array will be encoded in JSON format when data is saved using either the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/animation/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-animation@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-animation.js\" >< /script> Using NPM: npm install @jspsych/plugin-animation import animation from '@jspsych/plugin-animation' ;","title":"Install"},{"location":"plugins/animation/#examples","text":"Displaying a single sequence multiple times Code Demo var animation_sequence = [ \"img/happy_face_1.jpg\" , \"img/happy_face_2.jpg\" , \"img/happy_face_3.jpg\" , \"img/happy_face_4.jpg\" ]; var animation_trial = { type : jsPsychAnimation , stimuli : animation_sequence , sequence_reps : 3 , frame_time : 300 , prompt : '<p>Watch the faces.</p>' , }; Open demo in new tab","title":"Examples"},{"location":"plugins/audio-button-response/","text":"audio-button-response \u00b6 Current version: 1.1.2. See version history . This plugin plays audio files and records responses generated with a button click. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, you will need to manually preload the audio. The trial can end when the participant responds, when the audio file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the audio has finished playing. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Path to audio file to be played. choices array of strings undefined Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. trial_ends_after_audio boolean false If true, then the trial will end as soon as the audio file finishes playing. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before the button choices are enabled and a response is accepted. Once the audio has played all the way through, the buttons are enabled and a response is allowed (including while the audio is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-button-response import audioButtonResponse from '@jspsych/plugin-audio-button-response' ; Examples \u00b6 Displaying question until participant gives a response Code Demo var trial = { type : jsPsychAudioButtonResponse , stimulus : 'sound/tone.mp3' , choices : [ 'Low' , 'High' ], prompt : \"<p>Is the pitch high or low?</p>\" }; Open demo in new tab Using custom button HTML to use images as buttons Code Demo var trial = { type : jsPsychAudioButtonResponse , stimulus : 'sound/roar.mp3' , choices : [ 'lion.png' , 'elephant.png' , 'monkey.png' ], prompt : \"<p>Which animal made the sound?</p>\" , button_html : '<img src=\"%choice%\" />' }; Open demo in new tab Note : if you want the images to look more like jsPsych buttons, i.e. with borders and different styles for hover/active/disabled states, then you can also embed the image element inside the default button_html string: button_html : '<button class=\"jspsych-btn\"><img src=\"%choice%\" /></button>'","title":"audio-button-response"},{"location":"plugins/audio-button-response/#audio-button-response","text":"Current version: 1.1.2. See version history . This plugin plays audio files and records responses generated with a button click. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, you will need to manually preload the audio. The trial can end when the participant responds, when the audio file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the audio has finished playing.","title":"audio-button-response"},{"location":"plugins/audio-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Path to audio file to be played. choices array of strings undefined Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. trial_ends_after_audio boolean false If true, then the trial will end as soon as the audio file finishes playing. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before the button choices are enabled and a response is accepted. Once the audio has played all the way through, the buttons are enabled and a response is allowed (including while the audio is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/audio-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on.","title":"Data Generated"},{"location":"plugins/audio-button-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/audio-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-button-response import audioButtonResponse from '@jspsych/plugin-audio-button-response' ;","title":"Install"},{"location":"plugins/audio-button-response/#examples","text":"Displaying question until participant gives a response Code Demo var trial = { type : jsPsychAudioButtonResponse , stimulus : 'sound/tone.mp3' , choices : [ 'Low' , 'High' ], prompt : \"<p>Is the pitch high or low?</p>\" }; Open demo in new tab Using custom button HTML to use images as buttons Code Demo var trial = { type : jsPsychAudioButtonResponse , stimulus : 'sound/roar.mp3' , choices : [ 'lion.png' , 'elephant.png' , 'monkey.png' ], prompt : \"<p>Which animal made the sound?</p>\" , button_html : '<img src=\"%choice%\" />' }; Open demo in new tab Note : if you want the images to look more like jsPsych buttons, i.e. with borders and different styles for hover/active/disabled states, then you can also embed the image element inside the default button_html string: button_html : '<button class=\"jspsych-btn\"><img src=\"%choice%\" /></button>'","title":"Examples"},{"location":"plugins/audio-keyboard-response/","text":"audio-keyboard-response \u00b6 Current version: 1.1.2. See version history . This plugin plays audio files and records responses generated with the keyboard. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to manually preload the audio. The trial can end when the participant responds, when the audio file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the audio has finished playing. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Path to audio file to be played. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. trial_ends_after_audio boolean false If true, then the trial will end as soon as the audio file finishes playing. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before a keyboard response is accepted. Once the audio has played all the way through, a valid keyboard response is allowed (including while the audio is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. If no key was pressed before the trial ended, then the value will be null . rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant made a key response. If no key was pressed before the trial ended, then the value will be null . stimulus string Path to the audio file that played during the trial. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-keyboard-response import audioKeyboardResponse from '@jspsych/plugin-audio-keyboard-response' ; Examples \u00b6 Trial continues until participant gives a response Code Demo var trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'sound/tone.mp3' , choices : [ 'e' , 'i' ], prompt : \"<p>Is the pitch high or low? Press 'e' for low and 'i' for high.</p>\" , response_ends_trial : true }; Open demo in new tab Play a sound with no user response; trial ends after sound plays Code Demo var trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'sound/tone.mp3' , choices : \"NO_KEYS\" , trial_ends_after_audio : true }; Open demo in new tab","title":"audio-keyboard-response"},{"location":"plugins/audio-keyboard-response/#audio-keyboard-response","text":"Current version: 1.1.2. See version history . This plugin plays audio files and records responses generated with the keyboard. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to manually preload the audio. The trial can end when the participant responds, when the audio file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the audio has finished playing.","title":"audio-keyboard-response"},{"location":"plugins/audio-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Path to audio file to be played. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. trial_ends_after_audio boolean false If true, then the trial will end as soon as the audio file finishes playing. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before a keyboard response is accepted. Once the audio has played all the way through, a valid keyboard response is allowed (including while the audio is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/audio-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. If no key was pressed before the trial ended, then the value will be null . rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant made a key response. If no key was pressed before the trial ended, then the value will be null . stimulus string Path to the audio file that played during the trial.","title":"Data Generated"},{"location":"plugins/audio-keyboard-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/audio-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-keyboard-response import audioKeyboardResponse from '@jspsych/plugin-audio-keyboard-response' ;","title":"Install"},{"location":"plugins/audio-keyboard-response/#examples","text":"Trial continues until participant gives a response Code Demo var trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'sound/tone.mp3' , choices : [ 'e' , 'i' ], prompt : \"<p>Is the pitch high or low? Press 'e' for low and 'i' for high.</p>\" , response_ends_trial : true }; Open demo in new tab Play a sound with no user response; trial ends after sound plays Code Demo var trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'sound/tone.mp3' , choices : \"NO_KEYS\" , trial_ends_after_audio : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/audio-slider-response/","text":"audio-slider-response \u00b6 Current version: 1.1.2. See version history . This plugin plays an audio file and allows the participant to respond by dragging a slider. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to manually preload the audio. The trial can end when the participant responds, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the audio has finished playing. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Audio file to be played labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider max integer 100 Sets the maximum value of the slider slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before the slider is enabled and the trial can end via the next button click. Once the audio has played all the way through, the slider is enabled and a response is allowed (including while the audio is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant's response. stimulus string The path of the audio file that was played. slider_start numeric The starting value of the slider. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-slider-response import audioSliderResponse from '@jspsych/plugin-audio-slider-response' ; Examples \u00b6 A simple rating scale Code Demo var trial = { type : jsPsychAudioSliderResponse , stimulus : 'sound/speech_joke.mp3' , labels : [ 'Not Funny' , 'Funny' ], prompt : '<p>How funny is the joke?</p>' } Open demo in new tab No response allowed until audio finishes; participant must interact with slider to continue Code Demo var trial = { type : jsPsychAudioSliderResponse , stimulus : 'sound/speech_joke.mp3' , labels : [ 'Not Funny' , 'Funny' ], prompt : '<p>How funny is the joke?</p>' , response_allowed_while_playing : false , require_movement : true } Open demo in new tab","title":"audio-slider-response"},{"location":"plugins/audio-slider-response/#audio-slider-response","text":"Current version: 1.1.2. See version history . This plugin plays an audio file and allows the participant to respond by dragging a slider. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to manually preload the audio. The trial can end when the participant responds, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the audio has finished playing.","title":"audio-slider-response"},{"location":"plugins/audio-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Audio file to be played labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider max integer 100 Sets the maximum value of the slider slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before the slider is enabled and the trial can end via the next button click. Once the audio has played all the way through, the slider is enabled and a response is allowed (including while the audio is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/audio-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant's response. stimulus string The path of the audio file that was played. slider_start numeric The starting value of the slider.","title":"Data Generated"},{"location":"plugins/audio-slider-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/audio-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-slider-response import audioSliderResponse from '@jspsych/plugin-audio-slider-response' ;","title":"Install"},{"location":"plugins/audio-slider-response/#examples","text":"A simple rating scale Code Demo var trial = { type : jsPsychAudioSliderResponse , stimulus : 'sound/speech_joke.mp3' , labels : [ 'Not Funny' , 'Funny' ], prompt : '<p>How funny is the joke?</p>' } Open demo in new tab No response allowed until audio finishes; participant must interact with slider to continue Code Demo var trial = { type : jsPsychAudioSliderResponse , stimulus : 'sound/speech_joke.mp3' , labels : [ 'Not Funny' , 'Funny' ], prompt : '<p>How funny is the joke?</p>' , response_allowed_while_playing : false , require_movement : true } Open demo in new tab","title":"Examples"},{"location":"plugins/browser-check/","text":"browser-check \u00b6 Current version: 1.0.2. See version history . This plugin measures and records various features of the participant's browser and can end the experiment if defined inclusion criteria are not met. The plugin currently can record the following features: The width and height of the browser window in pixels. The type of browser used (e.g., Chrome, Firefox, Edge, etc.) and the version number of the browser.* Whether the participant is using a mobile device.* The operating system.* Support for the WebAudio API. Support for the Fullscreen API, e.g., through the fullscreen plugin . The display refresh rate in frames per second. Whether the device has a webcam and microphone. Note that this only reveals whether a webcam/microphone exists. The participant still needs to grant permission in order for the experiment to use these devices. Warning Features with an * are recorded by parsing the user agent string . This method is accurate most of the time, but is not guaranteed to be correct. The plugin uses the detect-browser package to perform user agent parsing. You can find a list of supported browsers and OSes in the source file . The plugin begins by measuring the set of features requested. An inclusion function is evaluated to see if the paricipant passes the inclusion criteria. If they do, then the trial ends and the experiment continues. If they do not, then the experiment ends immediately. If a minimum width and/or minimum height is desired, the plugin will optionally display a message to participants whose browser windows are too small to give them an opportunity to make the window larger if possible. See the examples below for more guidance. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description features array of strings [\"width\", \"height\", \"webaudio\", \"browser\", \"browser_version\", \"mobile\", \"os\", \"fullscreen\", \"vsync_rate\", \"webcam\", \"microphone\"] The list of browser features to record. The default value includes all of the available options. skip_features array of strings [] Any features listed here will be skipped, even if they appear in features . Use this when you want to run most of the defaults. vsync_frame_count int 60 The number of frames to sample when measuring the display refresh rate ( \"vsync_rate\" ). Increasing the number will potenially improve the stability of the estimate at the cost of increasing the amount of time the plugin takes during this test. On most devices, 60 frames takes about 1 second to measure. allow_window_resize bool true Whether to allow the participant to resize the browser window if the window is smaller than minimum_width and/or minimum_height . If false , then the minimum_width and minimum_height parameters are ignored and you can validate the size in the inclusion_function . minimum_height int 0 If allow_window_resize is true , then this is the minimum height of the window (in pixels) that must be met before continuing. minimum_width int 0 If allow_window_resize is true , then this is the minimum width of the window (in pixels) that must be met before continuing. window_resize_message string see description The message that will be displayed during the interactive resize when allow_window_resize is true and the window is too small. If the message contains HTML elements with the special IDs browser-check-min-width , browser-check-min-height , browser-check-actual-height , and/or browser-check-actual-width , then the contents of those elements will be dynamically updated to reflect the minimum_width , minimum_height and measured width and height of the browser. The default message is: <p>Your browser window is too small to complete this experiment. Please maximize the size of your browser window. If your browser window is already maximized, you will not be able to complete this experiment.</p><p>The minimum window width is <span id=\"browser-check-min-width\"></span> px.</p><p>Your current window width is <span id=\"browser-check-actual-width\"></span> px.</p><p>The minimum window height is <span id=\"browser-check-min-height\"></span> px.</p><p>Your current window height is <span id=\"browser-check-actual-height\"></span> px.</p> . resize_fail_button_text string \"I cannot make the window any larger\" During the interactive resize, a button with this text will be displayed below the window_resize_message for the participant to click if the window cannot meet the minimum size needed. When the button is clicked, the experiment will end and exclusion_message will be displayed. inclusion_function function () => { return true; } A function that evaluates to true if the browser meets all of the inclusion criteria for the experiment, and false otherwise. The first argument to the function will be an object containing key value pairs with the measured features of the browser. The keys will be the same as those listed in features . See example below. exclusion_message function () => { return <p>Your browser does not meet the requirements to participate in this experiment.</p> } A function that returns the message to display if inclusion_function evaluates to false or if the participant clicks on the resize fail button during the interactive resize. In order to allow customization of the message, the first argument to the function will be an object containing key value pairs with the measured features of the browser. The keys will be the same as those listed in features . See example below. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value width int The width of the browser window in pixels. If interactive resizing happens, this is the width after resizing. height int The height of the browser window in pixels. If interactive resizing happens, this is the height after resizing. browser string The browser used. browser_version string The version number of the browser. os string The operating system used. mobile bool Whether the browser is a mobile device. webaudio bool Whether the browser supports the WebAudio API. fullscreen bool Whether the browser supports the Fullscreen API. vsync_rate number An estimate of the refresh rate of the screen, in frames per second. webcam bool Whether there is a webcam device available. Note that the participant still must grant permission to access the device before it can be used. microphone bool Whether there is an audio input device available. Note that the participant still must grant permission to access the device before it can be used. Note that all of these values are only recorded when the corresponding key is included in the features parameter for the trial. Simulation Mode \u00b6 In simulation mode the plugin will report the actual features of the browser, with the exception of vsync_rate , which is always 60. In data-only mode, if allow_window_resize is true and the browser's width and height are below the maximum value then the reported width and height will be equal to minimum_width and minimum_height , as if the participant resized the browser to meet the specifications. In visual mode, if allow_window_resize is true and the browser's width and height are below the maximum value then the experiment will wait for 3 seconds before clicking the resize fail button. During this time, you can adjust the window if you would like to. As with all simulated plugins, you can override the default (actual) data with fake data using simulation_options . This allows you to test your exclusion criteria by simulating other configurations. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-browser-check@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-browser-check.js\" >< /script> Using NPM: npm install @jspsych/plugin-browser-check import browserCheck from '@jspsych/plugin-browser-check' ; Examples \u00b6 Recording all of the available features, no exclusions Code Demo var trial = { type : jsPsychBrowserCheck }; Open demo in new tab Using the inclusion function to mandate the use of Chrome or Firefox as the browser Code Demo var trial = { type : jsPsychBrowserCheck , inclusion_function : ( data ) => { return [ 'chrome' , 'firefox' ]. includes ( data . browser ); }, exclusion_message : ( data ) => { return `<p>You must use Chrome or Firefox to complete this experiment.</p>` }, }; Open demo in new tab Setting a minimum window height & width, with the option to resize the window Code Demo var trial = { type : jsPsychBrowserCheck , minimum_width : 1000 , minimum_height : 600 }; This demo only works in a resizable window. Please open it in new tab Open demo in new tab Custom exclusion message based on measured features Code Demo var trial = { type : jsPsychBrowserCheck , inclusion_function : ( data ) => { return data . browser == 'chrome' && data . mobile === false }, exclusion_message : ( data ) => { if ( data . mobile ){ return '<p>You must use a desktop/laptop computer to participate in this experiment.</p>' ; } else if ( data . browser !== 'chrome' ){ return '<p>You must use Chrome as your browser to complete this experiment.</p>' } } }; Open demo in new tab","title":"browser-check"},{"location":"plugins/browser-check/#browser-check","text":"Current version: 1.0.2. See version history . This plugin measures and records various features of the participant's browser and can end the experiment if defined inclusion criteria are not met. The plugin currently can record the following features: The width and height of the browser window in pixels. The type of browser used (e.g., Chrome, Firefox, Edge, etc.) and the version number of the browser.* Whether the participant is using a mobile device.* The operating system.* Support for the WebAudio API. Support for the Fullscreen API, e.g., through the fullscreen plugin . The display refresh rate in frames per second. Whether the device has a webcam and microphone. Note that this only reveals whether a webcam/microphone exists. The participant still needs to grant permission in order for the experiment to use these devices. Warning Features with an * are recorded by parsing the user agent string . This method is accurate most of the time, but is not guaranteed to be correct. The plugin uses the detect-browser package to perform user agent parsing. You can find a list of supported browsers and OSes in the source file . The plugin begins by measuring the set of features requested. An inclusion function is evaluated to see if the paricipant passes the inclusion criteria. If they do, then the trial ends and the experiment continues. If they do not, then the experiment ends immediately. If a minimum width and/or minimum height is desired, the plugin will optionally display a message to participants whose browser windows are too small to give them an opportunity to make the window larger if possible. See the examples below for more guidance.","title":"browser-check"},{"location":"plugins/browser-check/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description features array of strings [\"width\", \"height\", \"webaudio\", \"browser\", \"browser_version\", \"mobile\", \"os\", \"fullscreen\", \"vsync_rate\", \"webcam\", \"microphone\"] The list of browser features to record. The default value includes all of the available options. skip_features array of strings [] Any features listed here will be skipped, even if they appear in features . Use this when you want to run most of the defaults. vsync_frame_count int 60 The number of frames to sample when measuring the display refresh rate ( \"vsync_rate\" ). Increasing the number will potenially improve the stability of the estimate at the cost of increasing the amount of time the plugin takes during this test. On most devices, 60 frames takes about 1 second to measure. allow_window_resize bool true Whether to allow the participant to resize the browser window if the window is smaller than minimum_width and/or minimum_height . If false , then the minimum_width and minimum_height parameters are ignored and you can validate the size in the inclusion_function . minimum_height int 0 If allow_window_resize is true , then this is the minimum height of the window (in pixels) that must be met before continuing. minimum_width int 0 If allow_window_resize is true , then this is the minimum width of the window (in pixels) that must be met before continuing. window_resize_message string see description The message that will be displayed during the interactive resize when allow_window_resize is true and the window is too small. If the message contains HTML elements with the special IDs browser-check-min-width , browser-check-min-height , browser-check-actual-height , and/or browser-check-actual-width , then the contents of those elements will be dynamically updated to reflect the minimum_width , minimum_height and measured width and height of the browser. The default message is: <p>Your browser window is too small to complete this experiment. Please maximize the size of your browser window. If your browser window is already maximized, you will not be able to complete this experiment.</p><p>The minimum window width is <span id=\"browser-check-min-width\"></span> px.</p><p>Your current window width is <span id=\"browser-check-actual-width\"></span> px.</p><p>The minimum window height is <span id=\"browser-check-min-height\"></span> px.</p><p>Your current window height is <span id=\"browser-check-actual-height\"></span> px.</p> . resize_fail_button_text string \"I cannot make the window any larger\" During the interactive resize, a button with this text will be displayed below the window_resize_message for the participant to click if the window cannot meet the minimum size needed. When the button is clicked, the experiment will end and exclusion_message will be displayed. inclusion_function function () => { return true; } A function that evaluates to true if the browser meets all of the inclusion criteria for the experiment, and false otherwise. The first argument to the function will be an object containing key value pairs with the measured features of the browser. The keys will be the same as those listed in features . See example below. exclusion_message function () => { return <p>Your browser does not meet the requirements to participate in this experiment.</p> } A function that returns the message to display if inclusion_function evaluates to false or if the participant clicks on the resize fail button during the interactive resize. In order to allow customization of the message, the first argument to the function will be an object containing key value pairs with the measured features of the browser. The keys will be the same as those listed in features . See example below.","title":"Parameters"},{"location":"plugins/browser-check/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value width int The width of the browser window in pixels. If interactive resizing happens, this is the width after resizing. height int The height of the browser window in pixels. If interactive resizing happens, this is the height after resizing. browser string The browser used. browser_version string The version number of the browser. os string The operating system used. mobile bool Whether the browser is a mobile device. webaudio bool Whether the browser supports the WebAudio API. fullscreen bool Whether the browser supports the Fullscreen API. vsync_rate number An estimate of the refresh rate of the screen, in frames per second. webcam bool Whether there is a webcam device available. Note that the participant still must grant permission to access the device before it can be used. microphone bool Whether there is an audio input device available. Note that the participant still must grant permission to access the device before it can be used. Note that all of these values are only recorded when the corresponding key is included in the features parameter for the trial.","title":"Data Generated"},{"location":"plugins/browser-check/#simulation-mode","text":"In simulation mode the plugin will report the actual features of the browser, with the exception of vsync_rate , which is always 60. In data-only mode, if allow_window_resize is true and the browser's width and height are below the maximum value then the reported width and height will be equal to minimum_width and minimum_height , as if the participant resized the browser to meet the specifications. In visual mode, if allow_window_resize is true and the browser's width and height are below the maximum value then the experiment will wait for 3 seconds before clicking the resize fail button. During this time, you can adjust the window if you would like to. As with all simulated plugins, you can override the default (actual) data with fake data using simulation_options . This allows you to test your exclusion criteria by simulating other configurations.","title":"Simulation Mode"},{"location":"plugins/browser-check/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-browser-check@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-browser-check.js\" >< /script> Using NPM: npm install @jspsych/plugin-browser-check import browserCheck from '@jspsych/plugin-browser-check' ;","title":"Install"},{"location":"plugins/browser-check/#examples","text":"Recording all of the available features, no exclusions Code Demo var trial = { type : jsPsychBrowserCheck }; Open demo in new tab Using the inclusion function to mandate the use of Chrome or Firefox as the browser Code Demo var trial = { type : jsPsychBrowserCheck , inclusion_function : ( data ) => { return [ 'chrome' , 'firefox' ]. includes ( data . browser ); }, exclusion_message : ( data ) => { return `<p>You must use Chrome or Firefox to complete this experiment.</p>` }, }; Open demo in new tab Setting a minimum window height & width, with the option to resize the window Code Demo var trial = { type : jsPsychBrowserCheck , minimum_width : 1000 , minimum_height : 600 }; This demo only works in a resizable window. Please open it in new tab Open demo in new tab Custom exclusion message based on measured features Code Demo var trial = { type : jsPsychBrowserCheck , inclusion_function : ( data ) => { return data . browser == 'chrome' && data . mobile === false }, exclusion_message : ( data ) => { if ( data . mobile ){ return '<p>You must use a desktop/laptop computer to participate in this experiment.</p>' ; } else if ( data . browser !== 'chrome' ){ return '<p>You must use Chrome as your browser to complete this experiment.</p>' } } }; Open demo in new tab","title":"Examples"},{"location":"plugins/call-function/","text":"call-function \u00b6 Current version: 1.1.2. See version history . This plugin executes a specified function. This allows the experimenter to run arbitrary code at any point during the experiment. The function cannot take any arguments. If arguments are needed, then an anonymous function should be used to wrap the function call (see examples below). Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description func function undefined The function to call. async boolean false Set to true if func is an asynchoronous function. If this is true, then the first argument passed to func will be a callback that you should call when the async operation is complete. You can pass data to the callback. See example below. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value value any The return value of the called function. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-call-function@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-call-function.js\" >< /script> Using NPM: npm install @jspsych/plugin-call-function import callFunction from '@jspsych/plugin-call-function' ; Examples \u00b6 Calling a simple function Code Demo var myfunc = function () { return 'you called?' ; } var trial = { type : jsPsychCallFunction , func : myfunc } Open demo in new tab Using an anonymous function to pass variables Code Demo var myfunc = function ( data ){ // data contains all the experiment data so far, // so this function could implement code to write // the data to a database. console . log ( data . values ()) } var trial = { type : jsPsychCallFunction , func : function (){ myfunc ( jsPsych . data . get ()) } } Open demo in new tab Async function call: wait for data to be saved to a server Code There's no demo for this code, because it requires a server to communicate with. var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ // can perform async operations here like // creating an XMLHttpRequest to communicate // with a server var xhttp = new XMLHttpRequest (); xhttp . onreadystatechange = function () { if ( this . readyState == 4 && this . status == 200 ) { var response_data = xhttp . responseText ; // line below is what causes jsPsych to // continue to next trial. response_data // will be stored in jsPsych data object. done ( response_data ); } }; xhttp . open ( \"GET\" , \"path_to_server_script.php\" , true ); xhttp . send (); } } Async function call: simulate waiting for an event to finish Code Demo var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ // generate a delay between 1500 and 3000 milliseconds to simulate // waiting for an event to finish after an unknown duration, // then move on with the experiment var rand_delay = ( Math . floor ( Math . random () * ( 3000 - 1500 + 1 ) + 1500 )); jsPsych . pluginAPI . setTimeout ( function () { // end the trial and save the delay duration to the data done ( rand_delay . toString () + \"ms\" ); }, rand_delay ) } }; Open demo in new tab","title":"call-function"},{"location":"plugins/call-function/#call-function","text":"Current version: 1.1.2. See version history . This plugin executes a specified function. This allows the experimenter to run arbitrary code at any point during the experiment. The function cannot take any arguments. If arguments are needed, then an anonymous function should be used to wrap the function call (see examples below).","title":"call-function"},{"location":"plugins/call-function/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description func function undefined The function to call. async boolean false Set to true if func is an asynchoronous function. If this is true, then the first argument passed to func will be a callback that you should call when the async operation is complete. You can pass data to the callback. See example below.","title":"Parameters"},{"location":"plugins/call-function/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value value any The return value of the called function.","title":"Data Generated"},{"location":"plugins/call-function/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-call-function@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-call-function.js\" >< /script> Using NPM: npm install @jspsych/plugin-call-function import callFunction from '@jspsych/plugin-call-function' ;","title":"Install"},{"location":"plugins/call-function/#examples","text":"Calling a simple function Code Demo var myfunc = function () { return 'you called?' ; } var trial = { type : jsPsychCallFunction , func : myfunc } Open demo in new tab Using an anonymous function to pass variables Code Demo var myfunc = function ( data ){ // data contains all the experiment data so far, // so this function could implement code to write // the data to a database. console . log ( data . values ()) } var trial = { type : jsPsychCallFunction , func : function (){ myfunc ( jsPsych . data . get ()) } } Open demo in new tab Async function call: wait for data to be saved to a server Code There's no demo for this code, because it requires a server to communicate with. var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ // can perform async operations here like // creating an XMLHttpRequest to communicate // with a server var xhttp = new XMLHttpRequest (); xhttp . onreadystatechange = function () { if ( this . readyState == 4 && this . status == 200 ) { var response_data = xhttp . responseText ; // line below is what causes jsPsych to // continue to next trial. response_data // will be stored in jsPsych data object. done ( response_data ); } }; xhttp . open ( \"GET\" , \"path_to_server_script.php\" , true ); xhttp . send (); } } Async function call: simulate waiting for an event to finish Code Demo var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ // generate a delay between 1500 and 3000 milliseconds to simulate // waiting for an event to finish after an unknown duration, // then move on with the experiment var rand_delay = ( Math . floor ( Math . random () * ( 3000 - 1500 + 1 ) + 1500 )); jsPsych . pluginAPI . setTimeout ( function () { // end the trial and save the delay duration to the data done ( rand_delay . toString () + \"ms\" ); }, rand_delay ) } }; Open demo in new tab","title":"Examples"},{"location":"plugins/canvas-button-response/","text":"canvas-button-response \u00b6 Current version: 1.1.2. See version history . This plugin can be used to draw a stimulus on a HTML canvas element , and record a button click response and response time. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. One or more button choices will be displayed under the canvas, and the button style can be customized using HTML formatting. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., what question to answer). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-button-response import canvasButtonResponse from '@jspsych/plugin-canvas-button-response' ; Examples \u00b6 Drawing circles based on parameters Code Demo function filledCirc ( canvas , radius , color ) { var ctx = canvas . getContext ( \"2d\" ); ctx . beginPath (); ctx . arc ( 150 , 150 , radius , 0 , 2 * Math . PI ); ctx . fillStyle = color ; ctx . fill (); } var circle_1 = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , 100 , 'blue' ); }, canvas_size : [ 300 , 300 ], choices : [ 'Red' , 'Green' , 'Blue' ], prompt : '<p>What color is the circle?</p>' , data : { color : 'blue' , radius : 100 } }; var circle_2 = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , 150 , 'green' ); }, canvas_size : [ 300 , 300 ], choices : [ 'Larger' , 'Smaller' ], stimulus_duration : 1000 , prompt : '<p>Is this circle larger or smaller than the last one?</p>' + '<p>Stimulus will be hidden after 1 second.</p>' , data : { color : 'green' , radius : 150 } }; Open demo in new tab Using an anonymous stimulus function Code Demo var lines = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { var ctx = c . getContext ( \"2d\" ); // first line ctx . beginPath (); ctx . moveTo ( 200 , 10 ); ctx . lineTo ( 200 , 250 ); ctx . lineWidth = 10 ; ctx . strokeStyle = 'MediumBlue' ; ctx . stroke (); // second line ctx . beginPath (); ctx . moveTo ( 20 , 100 ); ctx . lineTo ( 100 , 250 ); ctx . lineWidth = 10 ; ctx . strokeStyle = 'MediumPurple' ; ctx . stroke (); }, canvas_size : [ 300 , 300 ], choices : [ 'Blue line' , 'Purple line' ], prompt : '<p>Which line is longer?</p>' , data : { line1_color : 'blue' , line1_length : 290 , line2_color : \"purple\" , line2_length : 170 } }; Open demo in new tab Using the canvas stimulus function with timeline variables, and recording the correctness of responses Code Demo function filledCirc ( canvas , radius , color ) { var ctx = canvas . getContext ( \"2d\" ); ctx . beginPath (); ctx . arc ( 150 , 150 , radius , 0 , 2 * Math . PI ); ctx . fillStyle = color ; ctx . fill (); } var circle_procedure = { timeline : [ { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , jsPsych . timelineVariable ( 'radius' ), jsPsych . timelineVariable ( 'color' )); }, canvas_size : [ 300 , 300 ], choices : [ 'Red' , 'Green' , 'Blue' ], prompt : '<p>What color is the circle?</p>' , data : { radius : jsPsych . timelineVariable ( 'radius' ), color : jsPsych . timelineVariable ( 'color' ), correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = data . response == data . correct_response ; } } ], timeline_variables : [ { radius : 80 , color : 'red' , correct_response : 0 }, { radius : 100 , color : 'green' , correct_response : 1 }, { radius : 50 , color : 'blue' , correct_response : 2 } ], randomize_order : true }; Open demo in new tab","title":"canvas-button-response"},{"location":"plugins/canvas-button-response/#canvas-button-response","text":"Current version: 1.1.2. See version history . This plugin can be used to draw a stimulus on a HTML canvas element , and record a button click response and response time. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. One or more button choices will be displayed under the canvas, and the button style can be customized using HTML formatting.","title":"canvas-button-response"},{"location":"plugins/canvas-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., what question to answer). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/canvas-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter.","title":"Data Generated"},{"location":"plugins/canvas-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-button-response import canvasButtonResponse from '@jspsych/plugin-canvas-button-response' ;","title":"Install"},{"location":"plugins/canvas-button-response/#examples","text":"Drawing circles based on parameters Code Demo function filledCirc ( canvas , radius , color ) { var ctx = canvas . getContext ( \"2d\" ); ctx . beginPath (); ctx . arc ( 150 , 150 , radius , 0 , 2 * Math . PI ); ctx . fillStyle = color ; ctx . fill (); } var circle_1 = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , 100 , 'blue' ); }, canvas_size : [ 300 , 300 ], choices : [ 'Red' , 'Green' , 'Blue' ], prompt : '<p>What color is the circle?</p>' , data : { color : 'blue' , radius : 100 } }; var circle_2 = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , 150 , 'green' ); }, canvas_size : [ 300 , 300 ], choices : [ 'Larger' , 'Smaller' ], stimulus_duration : 1000 , prompt : '<p>Is this circle larger or smaller than the last one?</p>' + '<p>Stimulus will be hidden after 1 second.</p>' , data : { color : 'green' , radius : 150 } }; Open demo in new tab Using an anonymous stimulus function Code Demo var lines = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { var ctx = c . getContext ( \"2d\" ); // first line ctx . beginPath (); ctx . moveTo ( 200 , 10 ); ctx . lineTo ( 200 , 250 ); ctx . lineWidth = 10 ; ctx . strokeStyle = 'MediumBlue' ; ctx . stroke (); // second line ctx . beginPath (); ctx . moveTo ( 20 , 100 ); ctx . lineTo ( 100 , 250 ); ctx . lineWidth = 10 ; ctx . strokeStyle = 'MediumPurple' ; ctx . stroke (); }, canvas_size : [ 300 , 300 ], choices : [ 'Blue line' , 'Purple line' ], prompt : '<p>Which line is longer?</p>' , data : { line1_color : 'blue' , line1_length : 290 , line2_color : \"purple\" , line2_length : 170 } }; Open demo in new tab Using the canvas stimulus function with timeline variables, and recording the correctness of responses Code Demo function filledCirc ( canvas , radius , color ) { var ctx = canvas . getContext ( \"2d\" ); ctx . beginPath (); ctx . arc ( 150 , 150 , radius , 0 , 2 * Math . PI ); ctx . fillStyle = color ; ctx . fill (); } var circle_procedure = { timeline : [ { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , jsPsych . timelineVariable ( 'radius' ), jsPsych . timelineVariable ( 'color' )); }, canvas_size : [ 300 , 300 ], choices : [ 'Red' , 'Green' , 'Blue' ], prompt : '<p>What color is the circle?</p>' , data : { radius : jsPsych . timelineVariable ( 'radius' ), color : jsPsych . timelineVariable ( 'color' ), correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = data . response == data . correct_response ; } } ], timeline_variables : [ { radius : 80 , color : 'red' , correct_response : 0 }, { radius : 100 , color : 'green' , correct_response : 1 }, { radius : 50 , color : 'blue' , correct_response : 2 } ], randomize_order : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/canvas-keyboard-response/","text":"canvas-keyboard-response \u00b6 Current version: 1.1.2. See version history . This plugin can be used to draw a stimulus on a HTML canvas element and record a keyboard response. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-keyboard-response import canvasKeyboardResponse from '@jspsych/plugin-canvas-keyboard-response' ; Examples \u00b6 Draw rectangle and wait for response Code Demo function drawRect ( c ){ var ctx = c . getContext ( '2d' ); ctx . beginPath (); ctx . rect ( 30 , 30 , 200 , 50 ); ctx . stroke (); } var trial = { type : jsPsychCanvasKeyboardResponse , canvas_size : [ 300 , 300 ], stimulus : drawRect , choices : [ 'e' , 'i' ], prompt : '<p>Is this a circle or a rectangle? Press \"e\" for circle and \"i\" for rectangle.</p>' , data : { shape : 'rectangle' } } Open demo in new tab Draw circle, no response allowed Code Demo function drawCirc ( c ){ var ctx = c . getContext ( '2d' ); ctx . beginPath (); ctx . arc ( 100 , 75 , 50 , 0 , 2 * Math . PI ); ctx . stroke (); } var trial = { type : jsPsychCanvasKeyboardResponse , canvas_size : [ 300 , 300 ], stimulus : drawCirc , prompt : '<p>No key response is allowed.</p><p>The stimulus disappears after 3 seconds.</p>' , choices : \"NO_KEYS\" , trial_duration : 3000 , data : { shape : 'circle' , radius : 50 } } Open demo in new tab","title":"canvas-keyboard-response"},{"location":"plugins/canvas-keyboard-response/#canvas-keyboard-response","text":"Current version: 1.1.2. See version history . This plugin can be used to draw a stimulus on a HTML canvas element and record a keyboard response. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.","title":"canvas-keyboard-response"},{"location":"plugins/canvas-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/canvas-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter.","title":"Data Generated"},{"location":"plugins/canvas-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-keyboard-response import canvasKeyboardResponse from '@jspsych/plugin-canvas-keyboard-response' ;","title":"Install"},{"location":"plugins/canvas-keyboard-response/#examples","text":"Draw rectangle and wait for response Code Demo function drawRect ( c ){ var ctx = c . getContext ( '2d' ); ctx . beginPath (); ctx . rect ( 30 , 30 , 200 , 50 ); ctx . stroke (); } var trial = { type : jsPsychCanvasKeyboardResponse , canvas_size : [ 300 , 300 ], stimulus : drawRect , choices : [ 'e' , 'i' ], prompt : '<p>Is this a circle or a rectangle? Press \"e\" for circle and \"i\" for rectangle.</p>' , data : { shape : 'rectangle' } } Open demo in new tab Draw circle, no response allowed Code Demo function drawCirc ( c ){ var ctx = c . getContext ( '2d' ); ctx . beginPath (); ctx . arc ( 100 , 75 , 50 , 0 , 2 * Math . PI ); ctx . stroke (); } var trial = { type : jsPsychCanvasKeyboardResponse , canvas_size : [ 300 , 300 ], stimulus : drawCirc , prompt : '<p>No key response is allowed.</p><p>The stimulus disappears after 3 seconds.</p>' , choices : \"NO_KEYS\" , trial_duration : 3000 , data : { shape : 'circle' , radius : 50 } } Open demo in new tab","title":"Examples"},{"location":"plugins/canvas-slider-response/","text":"canvas-slider-response \u00b6 Current version: 1.1.2. See version history . This plugin can be used to draw a stimulus on a HTML canvas element and collect a response within a range of values, which is made by dragging a slider. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider. step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must click the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., what question to answer). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-slider-response import canvasSliderResponse from '@jspsych/plugin-canvas-slider-response' ; Examples \u00b6 Draw two squares Code Demo var colors = [ '#FF3333' , '#FF6A33' ]; function twoSquares ( c ) { var ctx = c . getContext ( '2d' ); ctx . fillStyle = colors [ 0 ]; ctx . fillRect ( 200 , 70 , 40 , 40 ); ctx . fillStyle = colors [ 1 ]; ctx . fillRect ( 260 , 70 , 40 , 40 ); } var trial = { type : jsPsychCanvasSliderResponse , stimulus : twoSquares , labels : [ '0' , '10' ], canvas_size : [ 150 , 500 ], prompt : '<p>How different would you say the colors of these two squares are on a scale from 0 (the same) to 10 (completely different)</p>' , data : { color1 : colors [ 0 ], color2 : colors [ 1 ]} } Open demo in new tab Draw two squares with additional parameters Code Demo var colors ; function twoSquares ( c , colors ) { var ctx = c . getContext ( '2d' ); ctx . fillStyle = colors [ 0 ]; ctx . fillRect ( 200 , 70 , 40 , 40 ); ctx . fillStyle = colors [ 1 ]; ctx . fillRect ( 260 , 70 , 40 , 40 ); } var trial = { type : jsPsychCanvasSliderResponse , stimulus : function ( c ) { colors = [ 'darkred' , 'cyan' ]; twoSquares ( c , colors ); }, labels : [ 'Exactly<br>the same' , 'Totally<br>different' ], canvas_size : [ 200 , 500 ], prompt : '<p>How different would you say the colors of these two squares are?</p>' , on_finish : function ( data ) { data . color1 = colors [ 0 ]; data . color2 = colors [ 1 ]; } }; Open demo in new tab","title":"canvas-slider-response"},{"location":"plugins/canvas-slider-response/#canvas-slider-response","text":"Current version: 1.1.2. See version history . This plugin can be used to draw a stimulus on a HTML canvas element and collect a response within a range of values, which is made by dragging a slider. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.","title":"canvas-slider-response"},{"location":"plugins/canvas-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider. step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must click the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., what question to answer). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/canvas-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter.","title":"Data Generated"},{"location":"plugins/canvas-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-slider-response import canvasSliderResponse from '@jspsych/plugin-canvas-slider-response' ;","title":"Install"},{"location":"plugins/canvas-slider-response/#examples","text":"Draw two squares Code Demo var colors = [ '#FF3333' , '#FF6A33' ]; function twoSquares ( c ) { var ctx = c . getContext ( '2d' ); ctx . fillStyle = colors [ 0 ]; ctx . fillRect ( 200 , 70 , 40 , 40 ); ctx . fillStyle = colors [ 1 ]; ctx . fillRect ( 260 , 70 , 40 , 40 ); } var trial = { type : jsPsychCanvasSliderResponse , stimulus : twoSquares , labels : [ '0' , '10' ], canvas_size : [ 150 , 500 ], prompt : '<p>How different would you say the colors of these two squares are on a scale from 0 (the same) to 10 (completely different)</p>' , data : { color1 : colors [ 0 ], color2 : colors [ 1 ]} } Open demo in new tab Draw two squares with additional parameters Code Demo var colors ; function twoSquares ( c , colors ) { var ctx = c . getContext ( '2d' ); ctx . fillStyle = colors [ 0 ]; ctx . fillRect ( 200 , 70 , 40 , 40 ); ctx . fillStyle = colors [ 1 ]; ctx . fillRect ( 260 , 70 , 40 , 40 ); } var trial = { type : jsPsychCanvasSliderResponse , stimulus : function ( c ) { colors = [ 'darkred' , 'cyan' ]; twoSquares ( c , colors ); }, labels : [ 'Exactly<br>the same' , 'Totally<br>different' ], canvas_size : [ 200 , 500 ], prompt : '<p>How different would you say the colors of these two squares are?</p>' , on_finish : function ( data ) { data . color1 = colors [ 0 ]; data . color2 = colors [ 1 ]; } }; Open demo in new tab","title":"Examples"},{"location":"plugins/categorize-animation/","text":"categorize-animation \u00b6 Current version: 1.1.2. See version history . The categorize animation plugin shows a sequence of images at a specified frame rate. The participant responds by pressing a key. Feedback indicating the correctness of the response is given. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of the array is a path to an image file. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. key_answer string undefined The key character indicating the correct response. text_answer string \"\" A text label that describes the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). frame_time numeric 500 How long to display each image (in milliseconds). sequence_reps numeric 1 How many times to show the entire sequence. allow_response_before_complete boolean false If true, the participant can respond before the animation sequence finishes. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus or the end of the animation depending on the allow_response_before_complete parameter. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). feedback_duration numeric 2000 How long to show the feedback (milliseconds). render_on_canvas boolean true If true, the images will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive images in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array Array of stimuli displayed in the trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-animation.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-animation import categorizeAnimation from '@jspsych/plugin-categorize-animation' ; Examples \u00b6 Basic example Code Demo var animation_trial = { type : jsPsychCategorizeAnimation , stimuli : [ 'img/happy_face_1.jpg' , 'img/happy_face_2.jpg' , 'img/happy_face_3.jpg' , 'img/happy_face_4.jpg' ], prompt : `Press the P or Q key.` , choices : [ 'p' , 'q' ], key_answer : 'q' , }; Open demo in new tab Giving feedback with %ANS% string Code Demo var images = [ 'img/happy_face_1.jpg' , 'img/happy_face_2.jpg' , 'img/happy_face_3.jpg' , 'img/happy_face_4.jpg' ]; var animation_trial = { type : jsPsychCategorizeAnimation , stimuli : images , choices : [ 'p' , 'q' ], prompt : `Press the P or Q key.` , key_answer : 'q' , text_answer : 'Dax' , // the label for the sequence is 'Dax' correct_text : 'Correct! This was a %ANS%.' , incorrect_text : 'Incorrect. This was a %ANS%.' }; Open demo in new tab","title":"categorize-animation"},{"location":"plugins/categorize-animation/#categorize-animation","text":"Current version: 1.1.2. See version history . The categorize animation plugin shows a sequence of images at a specified frame rate. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.","title":"categorize-animation"},{"location":"plugins/categorize-animation/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of the array is a path to an image file. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. key_answer string undefined The key character indicating the correct response. text_answer string \"\" A text label that describes the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). frame_time numeric 500 How long to display each image (in milliseconds). sequence_reps numeric 1 How many times to show the entire sequence. allow_response_before_complete boolean false If true, the participant can respond before the animation sequence finishes. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus or the end of the animation depending on the allow_response_before_complete parameter. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). feedback_duration numeric 2000 How long to show the feedback (milliseconds). render_on_canvas boolean true If true, the images will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive images in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych.","title":"Parameters"},{"location":"plugins/categorize-animation/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array Array of stimuli displayed in the trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise.","title":"Data Generated"},{"location":"plugins/categorize-animation/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-animation.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-animation import categorizeAnimation from '@jspsych/plugin-categorize-animation' ;","title":"Install"},{"location":"plugins/categorize-animation/#examples","text":"Basic example Code Demo var animation_trial = { type : jsPsychCategorizeAnimation , stimuli : [ 'img/happy_face_1.jpg' , 'img/happy_face_2.jpg' , 'img/happy_face_3.jpg' , 'img/happy_face_4.jpg' ], prompt : `Press the P or Q key.` , choices : [ 'p' , 'q' ], key_answer : 'q' , }; Open demo in new tab Giving feedback with %ANS% string Code Demo var images = [ 'img/happy_face_1.jpg' , 'img/happy_face_2.jpg' , 'img/happy_face_3.jpg' , 'img/happy_face_4.jpg' ]; var animation_trial = { type : jsPsychCategorizeAnimation , stimuli : images , choices : [ 'p' , 'q' ], prompt : `Press the P or Q key.` , key_answer : 'q' , text_answer : 'Dax' , // the label for the sequence is 'Dax' correct_text : 'Correct! This was a %ANS%.' , incorrect_text : 'Incorrect. This was a %ANS%.' }; Open demo in new tab","title":"Examples"},{"location":"plugins/categorize-html/","text":"categorize-html \u00b6 Current version: 1.1.2. See version history . The categorize html plugin shows an HTML object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus html string undefined The HTML stimulus to display. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. key_answer string undefined The key character indicating the correct response. text_answer string \"\" A label that is associated with the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). force_correct_button_press boolean false If set to true, then the participant must press the correct response key after feedback is given in order to advance to the next trial. show_stim_with_feedback boolean true If set to true, then the stimulus will be shown during feedback. If false, then only the text feedback will display during feedback. show_feedback_on_timeout boolean false If true, then category feedback will be displayed for an incorrect response after a timeout (trial_duration is exceeded). If false, then a timeout message will be shown. timeout_message string \"Please respond faster.\" The message to show on a timeout non-response. stimulus_duration numeric null How long to show the stimulus for (milliseconds). If null, then the stimulus is shown until a response is given. feedback_duration numeric 2000 How long to show the feedback for (milliseconds). trial_duration numeric null The maximum time allowed for a response. If null, then the experiment will wait indefinitely for a response. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-html@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-html import categorizeHtml from '@jspsych/plugin-categorize-html' ; Examples \u00b6 Categorizing HTML content Code Demo var categorization_trial = { type : jsPsychCategorizeHtml , stimulus : '<p>B</p>' , key_answer : 'p' , text_answer : 'letter' , choices : [ 'p' , 'q' ], correct_text : \"<p class='prompt'>Correct, this is a %ANS%.</p>\" , incorrect_text : \"<p class='prompt'>Incorrect, this is a %ANS%.</p>\" , prompt : \"<p>Press p for letter. Press q for number.</p>\" }; Open demo in new tab","title":"categorize-html"},{"location":"plugins/categorize-html/#categorize-html","text":"Current version: 1.1.2. See version history . The categorize html plugin shows an HTML object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.","title":"categorize-html"},{"location":"plugins/categorize-html/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus html string undefined The HTML stimulus to display. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. key_answer string undefined The key character indicating the correct response. text_answer string \"\" A label that is associated with the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). force_correct_button_press boolean false If set to true, then the participant must press the correct response key after feedback is given in order to advance to the next trial. show_stim_with_feedback boolean true If set to true, then the stimulus will be shown during feedback. If false, then only the text feedback will display during feedback. show_feedback_on_timeout boolean false If true, then category feedback will be displayed for an incorrect response after a timeout (trial_duration is exceeded). If false, then a timeout message will be shown. timeout_message string \"Please respond faster.\" The message to show on a timeout non-response. stimulus_duration numeric null How long to show the stimulus for (milliseconds). If null, then the stimulus is shown until a response is given. feedback_duration numeric 2000 How long to show the feedback for (milliseconds). trial_duration numeric null The maximum time allowed for a response. If null, then the experiment will wait indefinitely for a response.","title":"Parameters"},{"location":"plugins/categorize-html/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise.","title":"Data Generated"},{"location":"plugins/categorize-html/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-html@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-html import categorizeHtml from '@jspsych/plugin-categorize-html' ;","title":"Install"},{"location":"plugins/categorize-html/#examples","text":"Categorizing HTML content Code Demo var categorization_trial = { type : jsPsychCategorizeHtml , stimulus : '<p>B</p>' , key_answer : 'p' , text_answer : 'letter' , choices : [ 'p' , 'q' ], correct_text : \"<p class='prompt'>Correct, this is a %ANS%.</p>\" , incorrect_text : \"<p class='prompt'>Incorrect, this is a %ANS%.</p>\" , prompt : \"<p>Press p for letter. Press q for number.</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/categorize-image/","text":"categorize-image \u00b6 Current version: 1.1.2. See version history . The categorize image plugin shows an image object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path to the image file. key_answer string undefined The key character indicating the correct response. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. text_answer string \"\" A label that is associated with the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). force_correct_button_press boolean false If set to true, then the participant must press the correct response key after feedback is given in order to advance to the next trial. show_stim_with_feedback boolean true If set to true, then the stimulus will be shown during feedback. If false, then only the text feedback will display during feedback. show_feedback_on_timeout boolean false If true, then category feedback will be displayed for an incorrect response after a timeout (trial_duration is exceeded). If false, then a timeout message will be shown. timeout_message string \"Please respond faster.\" The message to show on a timeout non-response. stimulus_duration numeric null How long to show the stimulus for (milliseconds). If null, then the stimulus is shown until a response is given. feedback_duration numeric 2000 How long to show the feedback for (milliseconds). trial_duration numeric null The maximum time allowed for a response. If null, then the experiment will wait indefinitely for a response. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-image@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-image import categorizeImage from '@jspsych/plugin-categorize-image' ; Examples \u00b6 Categorizing an image Code Demo var categorization_trial = { type : jsPsychCategorizeImage , stimulus : 'img/blue.png' , key_answer : 'b' , text_answer : 'Blue' , choices : [ 'r' , 'g' , 'b' ], correct_text : \"<p class='prompt'>Correct! The color is %ANS%.</p>\" , incorrect_text : \"<p class='prompt'>Incorrect. The color is %ANS%.</p>\" , prompt : \"<p>Is the color of this circle (R)ed, (G)reen, or (B)lue?</p>\" }; Open demo in new tab","title":"categorize-image"},{"location":"plugins/categorize-image/#categorize-image","text":"Current version: 1.1.2. See version history . The categorize image plugin shows an image object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.","title":"categorize-image"},{"location":"plugins/categorize-image/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path to the image file. key_answer string undefined The key character indicating the correct response. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. text_answer string \"\" A label that is associated with the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). force_correct_button_press boolean false If set to true, then the participant must press the correct response key after feedback is given in order to advance to the next trial. show_stim_with_feedback boolean true If set to true, then the stimulus will be shown during feedback. If false, then only the text feedback will display during feedback. show_feedback_on_timeout boolean false If true, then category feedback will be displayed for an incorrect response after a timeout (trial_duration is exceeded). If false, then a timeout message will be shown. timeout_message string \"Please respond faster.\" The message to show on a timeout non-response. stimulus_duration numeric null How long to show the stimulus for (milliseconds). If null, then the stimulus is shown until a response is given. feedback_duration numeric 2000 How long to show the feedback for (milliseconds). trial_duration numeric null The maximum time allowed for a response. If null, then the experiment will wait indefinitely for a response.","title":"Parameters"},{"location":"plugins/categorize-image/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise.","title":"Data Generated"},{"location":"plugins/categorize-image/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-image@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-image import categorizeImage from '@jspsych/plugin-categorize-image' ;","title":"Install"},{"location":"plugins/categorize-image/#examples","text":"Categorizing an image Code Demo var categorization_trial = { type : jsPsychCategorizeImage , stimulus : 'img/blue.png' , key_answer : 'b' , text_answer : 'Blue' , choices : [ 'r' , 'g' , 'b' ], correct_text : \"<p class='prompt'>Correct! The color is %ANS%.</p>\" , incorrect_text : \"<p class='prompt'>Incorrect. The color is %ANS%.</p>\" , prompt : \"<p>Is the color of this circle (R)ed, (G)reen, or (B)lue?</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/cloze/","text":"cloze \u00b6 Current version: 1.2.0. See version history . This plugin displays a text with certain words omitted. Participants are asked to replace the missing items. Responses are recorded when clicking a button. Responses can be evaluated and a function is called in case of either differences or incomplete answers, making it possible to inform participants about mistakes before proceeding. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description text string undefined The cloze text to be displayed. Blanks are indicated by %% signs and automatically replaced by input fields. If there is a correct answer you want the system to check against, it must be typed between the two percentage signs (i.e. % correct solution %). button_text string OK Text of the button participants have to press for finishing the cloze test. check_answers boolean false Boolean value indicating if the answers given by participants should be compared against a correct solution given in the text (between % signs) after the button was clicked. If true , answers are checked and in case of differences, the mistake_fn is called. In this case, the trial does not automatically finish. If false , no checks are performed and the trial automatically ends when clicking the button. allow_blanks boolean true Boolean value indicating if the answers given by participants should be checked for completion after the button was clicked. If true , answers are not checked for completion and blank answers are allowed. The trial will then automatically finish upon the clicking the button. If false , answers are checked for completion, and in case there are some fields with missing answers, the mistake_fn is called. In this case, the trial does not automatically finish. mistake_fn function function(){} Function called if check_answers is set to true and there is a difference between the participant's answers and the correct solution provided in the text, or if allow_blanks is set to false and there is at least one field with a blank answer. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response array of strings Answers the partcipant gave Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-cloze@1.2.0\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-cloze.js\" >< /script> Using NPM: npm install @jspsych/plugin-cloze import cloze from '@jspsych/plugin-cloze' ; Examples \u00b6 Simple cloze using default settings (no check against correct solution, no custom button text) Code Demo var cloze_trial = { type : jsPsychCloze , text : 'The %% is the largest terrestrial mammal. It lives in both %% and %%.' }; Open demo in new tab Cloze example using default settings with completion checking and custom error handling Code Demo var cloze_trial = { type : jsPsychCloze , text : 'Science notebooks have a %%-colored front cover. Math notebooks have a %%-colored front cover.' , allow_blanks : false , mistake_fn : function () { alert ( 'Please fill in all blanks.' ); } }; Open demo in new tab More elaborate example (with check against correct solution, custom error handling and modified button text) Code Demo var cloze_trial = { type : jsPsychCloze , text : 'A rectangle has % 4 % corners and a triangle has % 3 %.' , check_answers : true , button_text : 'Next' , mistake_fn : function (){ alert ( \"Wrong answer. Please check again.\" ) } }; Open demo in new tab","title":"cloze"},{"location":"plugins/cloze/#cloze","text":"Current version: 1.2.0. See version history . This plugin displays a text with certain words omitted. Participants are asked to replace the missing items. Responses are recorded when clicking a button. Responses can be evaluated and a function is called in case of either differences or incomplete answers, making it possible to inform participants about mistakes before proceeding.","title":"cloze"},{"location":"plugins/cloze/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description text string undefined The cloze text to be displayed. Blanks are indicated by %% signs and automatically replaced by input fields. If there is a correct answer you want the system to check against, it must be typed between the two percentage signs (i.e. % correct solution %). button_text string OK Text of the button participants have to press for finishing the cloze test. check_answers boolean false Boolean value indicating if the answers given by participants should be compared against a correct solution given in the text (between % signs) after the button was clicked. If true , answers are checked and in case of differences, the mistake_fn is called. In this case, the trial does not automatically finish. If false , no checks are performed and the trial automatically ends when clicking the button. allow_blanks boolean true Boolean value indicating if the answers given by participants should be checked for completion after the button was clicked. If true , answers are not checked for completion and blank answers are allowed. The trial will then automatically finish upon the clicking the button. If false , answers are checked for completion, and in case there are some fields with missing answers, the mistake_fn is called. In this case, the trial does not automatically finish. mistake_fn function function(){} Function called if check_answers is set to true and there is a difference between the participant's answers and the correct solution provided in the text, or if allow_blanks is set to false and there is at least one field with a blank answer.","title":"Parameters"},{"location":"plugins/cloze/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response array of strings Answers the partcipant gave","title":"Data Generated"},{"location":"plugins/cloze/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-cloze@1.2.0\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-cloze.js\" >< /script> Using NPM: npm install @jspsych/plugin-cloze import cloze from '@jspsych/plugin-cloze' ;","title":"Install"},{"location":"plugins/cloze/#examples","text":"Simple cloze using default settings (no check against correct solution, no custom button text) Code Demo var cloze_trial = { type : jsPsychCloze , text : 'The %% is the largest terrestrial mammal. It lives in both %% and %%.' }; Open demo in new tab Cloze example using default settings with completion checking and custom error handling Code Demo var cloze_trial = { type : jsPsychCloze , text : 'Science notebooks have a %%-colored front cover. Math notebooks have a %%-colored front cover.' , allow_blanks : false , mistake_fn : function () { alert ( 'Please fill in all blanks.' ); } }; Open demo in new tab More elaborate example (with check against correct solution, custom error handling and modified button text) Code Demo var cloze_trial = { type : jsPsychCloze , text : 'A rectangle has % 4 % corners and a triangle has % 3 %.' , check_answers : true , button_text : 'Next' , mistake_fn : function (){ alert ( \"Wrong answer. Please check again.\" ) } }; Open demo in new tab","title":"Examples"},{"location":"plugins/external-html/","text":"external-html \u00b6 Current version: 1.1.2. See version history . The HTML plugin displays an external HTML document (often a consent form). Either a keyboard response or a button press can be used to continue to the next trial. It allows the experimenter to check if conditions are met (such as indicating informed consent) before continuing. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description url string undefined The URL of the page to display. cont_key string null The key character the participant can use to advance to the next trial. If left as null, then the participant will not be able to advance trials using the keyboard. cont_btn string null The ID of a clickable element on the page. When the element is clicked, the trial will advance. check_fn function function(){ return true; } This function is called with the jsPsych display_element as the only argument when the participant attempts to advance the trial. The trial will only advance if the function return true . This can be used to verify that the participant has correctly filled out a form before continuing, for example. force_refresh boolean false If true , then the plugin will avoid using the cached version of the HTML page to load if one exists. execute_script boolean false If true , then scripts on the remote page will be executed. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value url string The URL of the page. rt numeric The response time in milliseconds for the participant to finish the trial. Simulation Mode \u00b6 In visual simulation mode, the plugin cannot interact with any form elements on the screen other than the cont_btn specified in the trial parameters. If your check_fn requires other user interaction, for example, clicking a checkbox, then you'll need to disable simulation for the trial and complete the interaction manually. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-external-html@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-external-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-external-html import externalHtml from '@jspsych/plugin-external-html' ; Examples \u00b6 Loading a consent form \u00b6 This content would be in a file called 'external_page.html' \u00b6 < div id = \"consent\" > < p > This is a demo experiment, with this minimal consent form being loaded as an external html document. To continue, click the checkbox below and hit \"Start Experiment\". </ p > < p > < input type = \"checkbox\" id = \"consent_checkbox\" /> I agree to take part in this study. </ p > < button type = \"button\" id = \"start\" > Start Experiment </ button > </ div > jsPsych code to load above page. Code Demo // sample function that might be used to check if a participant has given // consent to participate. var check_consent = function ( elem ) { if ( document . getElementById ( 'consent_checkbox' ). checked ) { return true ; } else { alert ( \"If you wish to participate, you must check the box next to the statement 'I agree to participate in this study.'\" ); return false ; } return false ; }; // declare the block. var trial = { type : jsPsychExternalHtml , url : \"external_page.html\" , cont_btn : \"start\" , check_fn : check_consent }; Open demo in new tab","title":"external-html"},{"location":"plugins/external-html/#external-html","text":"Current version: 1.1.2. See version history . The HTML plugin displays an external HTML document (often a consent form). Either a keyboard response or a button press can be used to continue to the next trial. It allows the experimenter to check if conditions are met (such as indicating informed consent) before continuing.","title":"external-html"},{"location":"plugins/external-html/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description url string undefined The URL of the page to display. cont_key string null The key character the participant can use to advance to the next trial. If left as null, then the participant will not be able to advance trials using the keyboard. cont_btn string null The ID of a clickable element on the page. When the element is clicked, the trial will advance. check_fn function function(){ return true; } This function is called with the jsPsych display_element as the only argument when the participant attempts to advance the trial. The trial will only advance if the function return true . This can be used to verify that the participant has correctly filled out a form before continuing, for example. force_refresh boolean false If true , then the plugin will avoid using the cached version of the HTML page to load if one exists. execute_script boolean false If true , then scripts on the remote page will be executed.","title":"Parameters"},{"location":"plugins/external-html/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value url string The URL of the page. rt numeric The response time in milliseconds for the participant to finish the trial.","title":"Data Generated"},{"location":"plugins/external-html/#simulation-mode","text":"In visual simulation mode, the plugin cannot interact with any form elements on the screen other than the cont_btn specified in the trial parameters. If your check_fn requires other user interaction, for example, clicking a checkbox, then you'll need to disable simulation for the trial and complete the interaction manually.","title":"Simulation Mode"},{"location":"plugins/external-html/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-external-html@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-external-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-external-html import externalHtml from '@jspsych/plugin-external-html' ;","title":"Install"},{"location":"plugins/external-html/#examples","text":"","title":"Examples"},{"location":"plugins/external-html/#loading-a-consent-form","text":"","title":"Loading a consent form"},{"location":"plugins/external-html/#this-content-would-be-in-a-file-called-external_pagehtml","text":"< div id = \"consent\" > < p > This is a demo experiment, with this minimal consent form being loaded as an external html document. To continue, click the checkbox below and hit \"Start Experiment\". </ p > < p > < input type = \"checkbox\" id = \"consent_checkbox\" /> I agree to take part in this study. </ p > < button type = \"button\" id = \"start\" > Start Experiment </ button > </ div > jsPsych code to load above page. Code Demo // sample function that might be used to check if a participant has given // consent to participate. var check_consent = function ( elem ) { if ( document . getElementById ( 'consent_checkbox' ). checked ) { return true ; } else { alert ( \"If you wish to participate, you must check the box next to the statement 'I agree to participate in this study.'\" ); return false ; } return false ; }; // declare the block. var trial = { type : jsPsychExternalHtml , url : \"external_page.html\" , cont_btn : \"start\" , check_fn : check_consent }; Open demo in new tab","title":"This content would be in a file called 'external_page.html'"},{"location":"plugins/free-sort/","text":"free-sort \u00b6 Current version: 1.0.2. See version history . The free-sort plugin displays one or more images on the screen that the participant can interact with by clicking and dragging with a mouse, or touching and dragging with a touchscreen device. When the trial starts, the images can be positioned outside or inside the sort area. All images must be moved into the sorting area before the participant can click a button to end the trial. All of the moves that the participant performs are recorded, as well as the final positions of all images. This plugin could be useful when asking participants to position images based on similarity to one another, or to recall image spatial locations. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of this array is an image path. stim_height numeric 100 The height of the images in pixels. stim_width numeric 100 The width of the images in pixels. scale_factor numeric 1.5 How much larger to make the stimulus while moving (1 = no scaling). sort_area_height numeric 800 The height of the container that participants can move the stimuli in. Stimuli will be constrained to this area. sort_area_width numeric 800 The width of the container that participants can move the stimuli in. Stimuli will be constrained to this area. sort_area_shape string \"ellipse\" The shape of the sorting area, can be \"ellipse\" or \"square\". prompt string null This string can contain HTML markup. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). prompt_location string \"above\" Indicates whether to show the prompt \"above\" or \"below\" the sorting area. button_label string 'Continue' The text that appears on the button to continue to the next trial. change_border_background_color boolean true If true , the sort area border color will change while items are being moved in and out of the sort area, and the background color will change once all items have been moved into the sort area. If false , the border will remain black and the background will remain white throughout the trial. border_color_in string '#a1d99b' If change_border_background_color is true , the sort area border will change to this color when an item is being moved into the sort area, and the background will change to this color when all of the items have been moved into the sort area. border_color_out string '#fc9272' If change_border_background_color is true , this will be the color of the sort area border when there are one or more items that still need to be moved into the sort area. border_width numeric null The width in pixels of the border around the sort area. If null , the border width will be 3% of the sort_area_height . counter_text_unfinished string You still need to place %n% item%s% inside the sort area. Text to display when there are one or more items that still need to be placed in the sort area. If \"%n%\" is included in the string, it will be replaced with the number of items that still need to be moved inside. If \"%s%\" is included in the string, a \"s\" will be included when the number of items remaining is greater than one. counter_text_finished string All items placed. Feel free to reposition items if necessary. Text that will take the place of the counter_text_unfinished text when all items have been moved inside the sort area. stim_starts_inside boolean false If false , the images will be positioned to the left and right of the sort area when the trial loads. If true , the images will be positioned at random locations inside the sort area when the trial loads. column_spread_factor numeric 1 When the images appear outside the sort area, this determines the x-axis spread of the image columns. Default value is 1. Values less than 1 will compress the image columns along the x-axis, and values greater than 1 will spread them farther apart. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value init_locations array An array containing objects representing the initial locations of all the stimuli in the sorting area. Each element in the array represents a stimulus, and has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. moves array An array containing objects representing all of the moves the participant made when sorting. Each object represents a move. Each element in the array has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location after the move. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. final_locations array An array containing objects representing the final locations of all the stimuli in the sorting area. Each element in the array represents a stimulus, and has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to finish all sorting. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-free-sort@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-free-sort.js\" >< /script> Using NPM: npm install @jspsych/plugin-free-sort import freeSort from '@jspsych/plugin-free-sort' ; Examples \u00b6 Basic example Code Demo var sort_trial = { type : jsPsychFreeSort , stimuli : sorting_stimuli , stim_width : 80 , stim_height : 60 , sort_area_width : 500 , sort_area_height : 500 , prompt : \"<p>Click and drag the images below to sort them so that similar items are close together.</p>\" }; Open demo in new tab","title":"free-sort"},{"location":"plugins/free-sort/#free-sort","text":"Current version: 1.0.2. See version history . The free-sort plugin displays one or more images on the screen that the participant can interact with by clicking and dragging with a mouse, or touching and dragging with a touchscreen device. When the trial starts, the images can be positioned outside or inside the sort area. All images must be moved into the sorting area before the participant can click a button to end the trial. All of the moves that the participant performs are recorded, as well as the final positions of all images. This plugin could be useful when asking participants to position images based on similarity to one another, or to recall image spatial locations.","title":"free-sort"},{"location":"plugins/free-sort/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of this array is an image path. stim_height numeric 100 The height of the images in pixels. stim_width numeric 100 The width of the images in pixels. scale_factor numeric 1.5 How much larger to make the stimulus while moving (1 = no scaling). sort_area_height numeric 800 The height of the container that participants can move the stimuli in. Stimuli will be constrained to this area. sort_area_width numeric 800 The width of the container that participants can move the stimuli in. Stimuli will be constrained to this area. sort_area_shape string \"ellipse\" The shape of the sorting area, can be \"ellipse\" or \"square\". prompt string null This string can contain HTML markup. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). prompt_location string \"above\" Indicates whether to show the prompt \"above\" or \"below\" the sorting area. button_label string 'Continue' The text that appears on the button to continue to the next trial. change_border_background_color boolean true If true , the sort area border color will change while items are being moved in and out of the sort area, and the background color will change once all items have been moved into the sort area. If false , the border will remain black and the background will remain white throughout the trial. border_color_in string '#a1d99b' If change_border_background_color is true , the sort area border will change to this color when an item is being moved into the sort area, and the background will change to this color when all of the items have been moved into the sort area. border_color_out string '#fc9272' If change_border_background_color is true , this will be the color of the sort area border when there are one or more items that still need to be moved into the sort area. border_width numeric null The width in pixels of the border around the sort area. If null , the border width will be 3% of the sort_area_height . counter_text_unfinished string You still need to place %n% item%s% inside the sort area. Text to display when there are one or more items that still need to be placed in the sort area. If \"%n%\" is included in the string, it will be replaced with the number of items that still need to be moved inside. If \"%s%\" is included in the string, a \"s\" will be included when the number of items remaining is greater than one. counter_text_finished string All items placed. Feel free to reposition items if necessary. Text that will take the place of the counter_text_unfinished text when all items have been moved inside the sort area. stim_starts_inside boolean false If false , the images will be positioned to the left and right of the sort area when the trial loads. If true , the images will be positioned at random locations inside the sort area when the trial loads. column_spread_factor numeric 1 When the images appear outside the sort area, this determines the x-axis spread of the image columns. Default value is 1. Values less than 1 will compress the image columns along the x-axis, and values greater than 1 will spread them farther apart.","title":"Parameters"},{"location":"plugins/free-sort/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value init_locations array An array containing objects representing the initial locations of all the stimuli in the sorting area. Each element in the array represents a stimulus, and has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. moves array An array containing objects representing all of the moves the participant made when sorting. Each object represents a move. Each element in the array has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location after the move. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. final_locations array An array containing objects representing the final locations of all the stimuli in the sorting area. Each element in the array represents a stimulus, and has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to finish all sorting.","title":"Data Generated"},{"location":"plugins/free-sort/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/free-sort/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-free-sort@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-free-sort.js\" >< /script> Using NPM: npm install @jspsych/plugin-free-sort import freeSort from '@jspsych/plugin-free-sort' ;","title":"Install"},{"location":"plugins/free-sort/#examples","text":"Basic example Code Demo var sort_trial = { type : jsPsychFreeSort , stimuli : sorting_stimuli , stim_width : 80 , stim_height : 60 , sort_area_width : 500 , sort_area_height : 500 , prompt : \"<p>Click and drag the images below to sort them so that similar items are close together.</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/fullscreen/","text":"fullscreen \u00b6 Current version: 1.2.0. See version history . The fullscreen plugin allows the experiment to enter or exit fullscreen mode. For security reasons, all browsers require that entry into fullscreen mode is triggered by a user action. To enter fullscreen mode, this plugin has the user click a button. Exiting fullscreen mode can be done without user input. Warning Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description fullscreen_mode boolean true A value of true causes the experiment to enter fullscreen mode. A value of false causes the browser to exit fullscreen mode. message string <p>The experiment will switch to full screen mode when you press the button below</p> The HTML content to display above the button to enter fullscreen mode. button_label string 'Continue' The text that appears on the button to enter fullscreen mode. delay_after numeric 1000 The length of time to delay after entering fullscreen mode before ending the trial. This can be useful because entering fullscreen is jarring and most browsers display some kind of message that the browser has entered fullscreen mode. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value success boolean true if the browser supports fullscreen mode (i.e., is not Safari) rt number Response time to click the button that launches fullscreen mode Simulation Mode \u00b6 Web browsers do not allow fullscreen mode to be triggered by a script to avoid malicious usage of fullscreen behavior when the user is not wanting it. In visual simulation mode, the trial will run normally and the button will get a simulated click, but the display will not change. If you want the display to actually enter fullscreen mode during the simulation, you should disable simulation for the fullscreen trial and manually click the button. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-fullscreen@1.2.0\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-fullscreen.js\" >< /script> Using NPM: npm install @jspsych/plugin-fullscreen import fullscreen from '@jspsych/plugin-fullscreen' ; Examples \u00b6 Entering and exiting fullscreen Code Demo var enter_fullscreen = { type : jsPsychFullscreen , fullscreen_mode : true } var trial_in_fullscreen = { type : jsPsychHtmlButtonResponse , stimulus : 'This trial will be in fullscreen mode.' , choices : [ 'Continue' ] } var exit_fullscreen = { type : jsPsychFullscreen , fullscreen_mode : false , delay_after : 0 } var trial_after_fullscreen = { type : jsPsychHtmlButtonResponse , stimulus : 'This trial will NOT be in fullscreen mode.' , choices : [ 'Continue' ] } Open demo in new tab","title":"fullscreen"},{"location":"plugins/fullscreen/#fullscreen","text":"Current version: 1.2.0. See version history . The fullscreen plugin allows the experiment to enter or exit fullscreen mode. For security reasons, all browsers require that entry into fullscreen mode is triggered by a user action. To enter fullscreen mode, this plugin has the user click a button. Exiting fullscreen mode can be done without user input. Warning Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari.","title":"fullscreen"},{"location":"plugins/fullscreen/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description fullscreen_mode boolean true A value of true causes the experiment to enter fullscreen mode. A value of false causes the browser to exit fullscreen mode. message string <p>The experiment will switch to full screen mode when you press the button below</p> The HTML content to display above the button to enter fullscreen mode. button_label string 'Continue' The text that appears on the button to enter fullscreen mode. delay_after numeric 1000 The length of time to delay after entering fullscreen mode before ending the trial. This can be useful because entering fullscreen is jarring and most browsers display some kind of message that the browser has entered fullscreen mode.","title":"Parameters"},{"location":"plugins/fullscreen/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value success boolean true if the browser supports fullscreen mode (i.e., is not Safari) rt number Response time to click the button that launches fullscreen mode","title":"Data Generated"},{"location":"plugins/fullscreen/#simulation-mode","text":"Web browsers do not allow fullscreen mode to be triggered by a script to avoid malicious usage of fullscreen behavior when the user is not wanting it. In visual simulation mode, the trial will run normally and the button will get a simulated click, but the display will not change. If you want the display to actually enter fullscreen mode during the simulation, you should disable simulation for the fullscreen trial and manually click the button.","title":"Simulation Mode"},{"location":"plugins/fullscreen/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-fullscreen@1.2.0\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-fullscreen.js\" >< /script> Using NPM: npm install @jspsych/plugin-fullscreen import fullscreen from '@jspsych/plugin-fullscreen' ;","title":"Install"},{"location":"plugins/fullscreen/#examples","text":"Entering and exiting fullscreen Code Demo var enter_fullscreen = { type : jsPsychFullscreen , fullscreen_mode : true } var trial_in_fullscreen = { type : jsPsychHtmlButtonResponse , stimulus : 'This trial will be in fullscreen mode.' , choices : [ 'Continue' ] } var exit_fullscreen = { type : jsPsychFullscreen , fullscreen_mode : false , delay_after : 0 } var trial_after_fullscreen = { type : jsPsychHtmlButtonResponse , stimulus : 'This trial will NOT be in fullscreen mode.' , choices : [ 'Continue' ] } Open demo in new tab","title":"Examples"},{"location":"plugins/html-audio-response/","text":"html-audio-response \u00b6 Current version: 1.0.2. See version history . This plugin displays HTML content and records audio from the participant via a microphone. In order to get access to the microphone, you need to use the initialize-microphone plugin on your timeline prior to using this plugin. Once access is granted for an experiment you do not need to get permission again. This plugin records audio data in base 64 format . This is a text-based representation of the audio which can be coverted to various audio formats using a variety of online tools as well as in languages like python and R. This plugin will generate a large amount of data, and you will need to be careful about how you handle this data. Even a few seconds of audio recording will add 10s of kB to jsPsych's data. Multiply this by a handful (or more) of trials, and the data objects will quickly get large. If you need to record a lot of audio, either many trials worth or just a few trials with longer responses, we recommend that you save the data to your server immediately after the trial and delete the data in jsPsych's data object. See below for an example of how to do this. This plugin also provides the option to store the recorded audio files as Object URLs via save_audio_url: true . This will generate a URL that is storing a copy of the recorded audio, which can be used for subsequent playback. See below for an example where the recorded audio is used as the stimulus in a subsequent trial. This feature is turned off by default because it uses a relatively large amount of memory compared to most jsPsych features. If you are running an experiment where you need this feature and you are recording lots of audio snippets, you may want to manually revoke the URLs when you no longer need them using URL.revokeObjectURL(objectURL) . Warning When recording from a microphone your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. recording_duration numeric 2000 The maximum length of the recording, in milliseconds. The default value is intentionally set low because of the potential to accidentally record very large data files if left too high. You can set this to null to allow the participant to control the length of the recording via the done button, but be careful with this option as it can lead to crashing the browser if the participant waits too long to stop the recording. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. show_done_button bool true Whether to show a button on the screen that the participant can click to finish the recording. done_button_label string 'Continue' The label for the done button. allow_playback bool false Whether to allow the participant to listen to their recording and decide whether to rerecord or not. If true , then the participant will be shown an interface to play their recorded audio and click one of two buttons to either accept the recording or rerecord. If rerecord is selected, then stimulus will be shown again, as if the trial is starting again from the beginning. record_again_button_label string 'Record again' The label for the record again button enabled when allow_playback: true . accept_button_label string 'Continue' The label for the accept button enabled when allow_playback: true . save_audio_url bool false If true , then an Object URL will be generated and stored for the recorded audio. Only set this to true if you plan to reuse the recorded audio later in the experiment, as it is a potentially memory-intensive feature. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The time, since the onset of the stimulus, for the participant to click the done button. If the button is not clicked (or not enabled), then rt will be null . response base64 string The base64-encoded audio data. stimulus string The HTML content that was displayed on the screen. estimated_stimulus_onset number This is an estimate of when the stimulus appeared relative to the start of the audio recording. The plugin is configured so that the recording should start prior to the display of the stimulus. We have not yet been able to verify the accuracy of this estimate with external measurement devices. audio_url string A URL to a copy of the audio data. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-audio-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-audio-response import htmlAudioResponse from '@jspsych/plugin-html-audio-response' ; Examples \u00b6 Simple spoken response to a stimulus Code Demo var trial = { type : jsPsychHtmlAudioResponse , stimulus : ` <p style=\"font-size:48px; color:red;\">GREEN</p> <p>Speak the color of the ink.</p>` , recording_duration : 3500 }; Open demo in new tab Allow playback and rerecording; save data to server immediately Code Demo var trial = { type : jsPsychHtmlAudioResponse , stimulus : ` <p>Please sing the first few seconds of a song and click the button when you are done.</p> ` , recording_duration : 15000 , allow_playback : true , on_finish : function ( data ){ fetch ( '/save-my-data.php' , { audio_base64 : data . response }) . then (( audio_id ){ data . response = audio_id ; }); } }; This example assumes that there is a script on your experiment server that accepts the data called save-my-data.php . It also assumes that the script will generate a response with an ID for the stored audio file ( audio_id ). In the example, we replace the very long base64 representation of the audio file with the generated ID, which could be just a handful of characters. This would let you link files to responses in data analysis, without having to store long audio files in memory during the experiment. Open demo in new tab Use recorded audio as a subsequent stimulus Code Demo var instruction = { type : jsPsychHtmlButtonResponse , stimulus : ` <img src='img/10.gif' style=\"width:100px; padding: 20px;\"></img> <p>Make up a name for this shape. When you have one in mind, click the button and then say the name aloud.</p> ` , choices : [ 'I am ready.' ] } var record = { type : jsPsychHtmlAudioResponse , stimulus : ` <img src='img/10.gif' style=\"width:100px; padding: 20px;\"></img> <p>Recording...</p> ` , recording_duration : 1500 , save_audio_url : true }; var playback = { type : jsPsychAudioButtonResponse , stimulus : ()=>{ return jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. audio_url ; }, prompt : '<p>Click the object the matches the spoken name.</p>' , choices : [ 'img/9.gif' , 'img/10.gif' , 'img/11.gif' , 'img/12.gif' ], button_html : '<img src=\"%choice%\" style=\"width:100px; padding: 20px;\"></img>' } Open demo in new tab","title":"html-audio-response"},{"location":"plugins/html-audio-response/#html-audio-response","text":"Current version: 1.0.2. See version history . This plugin displays HTML content and records audio from the participant via a microphone. In order to get access to the microphone, you need to use the initialize-microphone plugin on your timeline prior to using this plugin. Once access is granted for an experiment you do not need to get permission again. This plugin records audio data in base 64 format . This is a text-based representation of the audio which can be coverted to various audio formats using a variety of online tools as well as in languages like python and R. This plugin will generate a large amount of data, and you will need to be careful about how you handle this data. Even a few seconds of audio recording will add 10s of kB to jsPsych's data. Multiply this by a handful (or more) of trials, and the data objects will quickly get large. If you need to record a lot of audio, either many trials worth or just a few trials with longer responses, we recommend that you save the data to your server immediately after the trial and delete the data in jsPsych's data object. See below for an example of how to do this. This plugin also provides the option to store the recorded audio files as Object URLs via save_audio_url: true . This will generate a URL that is storing a copy of the recorded audio, which can be used for subsequent playback. See below for an example where the recorded audio is used as the stimulus in a subsequent trial. This feature is turned off by default because it uses a relatively large amount of memory compared to most jsPsych features. If you are running an experiment where you need this feature and you are recording lots of audio snippets, you may want to manually revoke the URLs when you no longer need them using URL.revokeObjectURL(objectURL) . Warning When recording from a microphone your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems .","title":"html-audio-response"},{"location":"plugins/html-audio-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. recording_duration numeric 2000 The maximum length of the recording, in milliseconds. The default value is intentionally set low because of the potential to accidentally record very large data files if left too high. You can set this to null to allow the participant to control the length of the recording via the done button, but be careful with this option as it can lead to crashing the browser if the participant waits too long to stop the recording. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. show_done_button bool true Whether to show a button on the screen that the participant can click to finish the recording. done_button_label string 'Continue' The label for the done button. allow_playback bool false Whether to allow the participant to listen to their recording and decide whether to rerecord or not. If true , then the participant will be shown an interface to play their recorded audio and click one of two buttons to either accept the recording or rerecord. If rerecord is selected, then stimulus will be shown again, as if the trial is starting again from the beginning. record_again_button_label string 'Record again' The label for the record again button enabled when allow_playback: true . accept_button_label string 'Continue' The label for the accept button enabled when allow_playback: true . save_audio_url bool false If true , then an Object URL will be generated and stored for the recorded audio. Only set this to true if you plan to reuse the recorded audio later in the experiment, as it is a potentially memory-intensive feature.","title":"Parameters"},{"location":"plugins/html-audio-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The time, since the onset of the stimulus, for the participant to click the done button. If the button is not clicked (or not enabled), then rt will be null . response base64 string The base64-encoded audio data. stimulus string The HTML content that was displayed on the screen. estimated_stimulus_onset number This is an estimate of when the stimulus appeared relative to the start of the audio recording. The plugin is configured so that the recording should start prior to the display of the stimulus. We have not yet been able to verify the accuracy of this estimate with external measurement devices. audio_url string A URL to a copy of the audio data.","title":"Data Generated"},{"location":"plugins/html-audio-response/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/html-audio-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-audio-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-audio-response import htmlAudioResponse from '@jspsych/plugin-html-audio-response' ;","title":"Install"},{"location":"plugins/html-audio-response/#examples","text":"Simple spoken response to a stimulus Code Demo var trial = { type : jsPsychHtmlAudioResponse , stimulus : ` <p style=\"font-size:48px; color:red;\">GREEN</p> <p>Speak the color of the ink.</p>` , recording_duration : 3500 }; Open demo in new tab Allow playback and rerecording; save data to server immediately Code Demo var trial = { type : jsPsychHtmlAudioResponse , stimulus : ` <p>Please sing the first few seconds of a song and click the button when you are done.</p> ` , recording_duration : 15000 , allow_playback : true , on_finish : function ( data ){ fetch ( '/save-my-data.php' , { audio_base64 : data . response }) . then (( audio_id ){ data . response = audio_id ; }); } }; This example assumes that there is a script on your experiment server that accepts the data called save-my-data.php . It also assumes that the script will generate a response with an ID for the stored audio file ( audio_id ). In the example, we replace the very long base64 representation of the audio file with the generated ID, which could be just a handful of characters. This would let you link files to responses in data analysis, without having to store long audio files in memory during the experiment. Open demo in new tab Use recorded audio as a subsequent stimulus Code Demo var instruction = { type : jsPsychHtmlButtonResponse , stimulus : ` <img src='img/10.gif' style=\"width:100px; padding: 20px;\"></img> <p>Make up a name for this shape. When you have one in mind, click the button and then say the name aloud.</p> ` , choices : [ 'I am ready.' ] } var record = { type : jsPsychHtmlAudioResponse , stimulus : ` <img src='img/10.gif' style=\"width:100px; padding: 20px;\"></img> <p>Recording...</p> ` , recording_duration : 1500 , save_audio_url : true }; var playback = { type : jsPsychAudioButtonResponse , stimulus : ()=>{ return jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. audio_url ; }, prompt : '<p>Click the object the matches the spoken name.</p>' , choices : [ 'img/9.gif' , 'img/10.gif' , 'img/11.gif' , 'img/12.gif' ], button_html : '<img src=\"%choice%\" style=\"width:100px; padding: 20px;\"></img>' } Open demo in new tab","title":"Examples"},{"location":"plugins/html-button-response/","text":"html-button-response \u00b6 Current version: 1.1.2. See version history . This plugin displays HTML content and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. stimulus string The HTML content that was displayed on the screen. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-button-response import htmlButtonResponse from '@jspsych/plugin-html-button-response' ; Examples \u00b6 Displaying question until participant gives a response Code Demo var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<p style=\"font-size:48px; color:red;\">GREEN</p>' , choices : [ 'Red' , 'Green' , 'Blue' ], prompt : \"<p>What color is the ink?</p>\" }; Open demo in new tab","title":"html-button-response"},{"location":"plugins/html-button-response/#html-button-response","text":"Current version: 1.1.2. See version history . This plugin displays HTML content and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting.","title":"html-button-response"},{"location":"plugins/html-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/html-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. stimulus string The HTML content that was displayed on the screen.","title":"Data Generated"},{"location":"plugins/html-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-button-response import htmlButtonResponse from '@jspsych/plugin-html-button-response' ;","title":"Install"},{"location":"plugins/html-button-response/#examples","text":"Displaying question until participant gives a response Code Demo var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<p style=\"font-size:48px; color:red;\">GREEN</p>' , choices : [ 'Red' , 'Green' , 'Blue' ], prompt : \"<p>What color is the ink?</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/html-keyboard-response/","text":"html-keyboard-response \u00b6 Current version: 1.1.2. See version history . This plugin displays HTML content and records responses generated with the keyboard.The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The string to be displayed. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The HTML content that was displayed on the screen. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-keyboard-response import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; Examples \u00b6 Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size:48px; color:green;\">BLUE</p>' , choices : [ 'r' , 'g' , 'b' ], prompt : \"<p>Is the ink color (r)ed, (g)reen, or (b)lue?</p>\" }; Open demo in new tab Showing a 1 second fixation cross; no response allowed Code Demo var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size: 48px;\">+</p>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; Open demo in new tab","title":"html-keyboard-response"},{"location":"plugins/html-keyboard-response/#html-keyboard-response","text":"Current version: 1.1.2. See version history . This plugin displays HTML content and records responses generated with the keyboard.The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.","title":"html-keyboard-response"},{"location":"plugins/html-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The string to be displayed. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/html-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The HTML content that was displayed on the screen.","title":"Data Generated"},{"location":"plugins/html-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-keyboard-response import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ;","title":"Install"},{"location":"plugins/html-keyboard-response/#examples","text":"Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size:48px; color:green;\">BLUE</p>' , choices : [ 'r' , 'g' , 'b' ], prompt : \"<p>Is the ink color (r)ed, (g)reen, or (b)lue?</p>\" }; Open demo in new tab Showing a 1 second fixation cross; no response allowed Code Demo var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size: 48px;\">+</p>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; Open demo in new tab","title":"Examples"},{"location":"plugins/html-slider-response/","text":"html-slider-response \u00b6 Current version: 1.1.2. See version history . This plugin displays HTML content and allows the participant to respond by dragging a slider. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The string to be displayed labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The HTML content that was displayed on the screen. slider_start numeric The starting value of the slider. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-slider-response import htmlSliderResponse from '@jspsych/plugin-html-slider-response' ; Examples \u00b6 Displaying question until participant moves the slider Code Demo var trial = { type : jsPsychHtmlSliderResponse , stimulus : `<div style=\"width:500px;\"> <p>How likely is it that team A will win this match?</p> <div style=\"width:240px; float: left;\"> <p>TEAM A</p> <p>10 wins, 5 losses, 6 draws</p> </div> <div style=\"width:240px; float: right;\"> <p>TEAM B</p> <p>6 wins, 4 losses, 11 draws</p> </div> </div>` , require_movement : true , labels : [ '100% chance' , '50% chance' , '0% chance' ] }; Open demo in new tab","title":"html-slider-response"},{"location":"plugins/html-slider-response/#html-slider-response","text":"Current version: 1.1.2. See version history . This plugin displays HTML content and allows the participant to respond by dragging a slider.","title":"html-slider-response"},{"location":"plugins/html-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The string to be displayed labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/html-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The HTML content that was displayed on the screen. slider_start numeric The starting value of the slider.","title":"Data Generated"},{"location":"plugins/html-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-slider-response import htmlSliderResponse from '@jspsych/plugin-html-slider-response' ;","title":"Install"},{"location":"plugins/html-slider-response/#examples","text":"Displaying question until participant moves the slider Code Demo var trial = { type : jsPsychHtmlSliderResponse , stimulus : `<div style=\"width:500px;\"> <p>How likely is it that team A will win this match?</p> <div style=\"width:240px; float: left;\"> <p>TEAM A</p> <p>10 wins, 5 losses, 6 draws</p> </div> <div style=\"width:240px; float: right;\"> <p>TEAM B</p> <p>6 wins, 4 losses, 11 draws</p> </div> </div>` , require_movement : true , labels : [ '100% chance' , '50% chance' , '0% chance' ] }; Open demo in new tab","title":"Examples"},{"location":"plugins/html-video-response/","text":"html-video-response \u00b6 Current version: 1.0.1. See version history . This plugin displays HTML content and records video from the participant via a webcam. In order to get access to the camera, you need to use the initialize-camera plugin on your timeline prior to using this plugin. Once access is granted for an experiment you do not need to get permission again. This plugin records video data in base 64 format . This is a text-based representation of the video which can be coverted to various video formats using a variety of online tools as well as in languages like python and R. This plugin will generate a large amount of data, and you will need to be careful about how you handle this data. Even a few seconds of video recording will add 10s of kB to jsPsych's data. Multiply this by a handful (or more) of trials, and the data objects will quickly get large. If you need to record a lot of video, either many trials worth or just a few trials with longer responses, we recommend that you save the data to your server immediately after the trial and delete the data in jsPsych's data object. See below for an example of how to do this. This plugin also provides the option to store the recorded video files as Object URLs via save_video_url: true . This will generate a URL that stores a copy of the recorded video, which can be used for subsequent playback during the experiment. See below for an example where the recorded video is used as the stimulus in a subsequent trial. This feature is turned off by default because it uses a relatively large amount of memory compared to most jsPsych features. If you are running an experiment where you need this feature and you are recording lots of video clips, you may want to manually revoke the URLs when you no longer need them using URL.revokeObjectURL(objectURL) . Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the camera because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. recording_duration numeric 2000 The maximum length of the recording, in milliseconds. The default value is intentionally set low because of the potential to accidentally record very large data files if left too high. You can set this to null to allow the participant to control the length of the recording via the done button, but be careful with this option as it can lead to crashing the browser if the participant waits too long to stop the recording. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. show_done_button bool true Whether to show a button on the screen that the participant can click to finish the recording. done_button_label string 'Continue' The label for the done button. allow_playback bool false Whether to allow the participant to listen to their recording and decide whether to rerecord or not. If true , then the participant will be shown an interface to play their recorded video and click one of two buttons to either accept the recording or rerecord. If rerecord is selected, then stimulus will be shown again, as if the trial is starting again from the beginning. record_again_button_label string 'Record again' The label for the record again button enabled when allow_playback: true . accept_button_label string 'Continue' The label for the accept button enabled when allow_playback: true . save_video_url bool false If true , then an Object URL will be generated and stored for the recorded video. Only set this to true if you plan to reuse the recorded video later in the experiment, as it is a potentially memory-intensive feature. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The time, since the onset of the stimulus, for the participant to click the done button. If the button is not clicked (or not enabled), then rt will be null . response base64 string The base64-encoded video data. stimulus string The HTML content that was displayed on the screen. video_url string A URL to a copy of the video data. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-video-response@1.0.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-video-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-video-response import htmlVideoResponse from '@jspsych/plugin-html-video-response' ; Examples \u00b6 Simple recorded response to a stimulus Code Demo var init_camera = { type : jsPsychInitializeCamera } var trial = { type : jsPsychHtmlVideoResponse , stimulus : ` <p style=\"font-size:48px; color:red;\"> <-- </p> <p>Turn your head in the direction of the arrow</p>` , recording_duration : 3500 , show_done_button : false , }; Open demo in new tab Allow playback and rerecording Code Demo var init_camera = { type : jsPsychInitializeCamera } var trial = { type : jsPsychHtmlVideoResponse , stimulus : `<p>Make a sad face</p>` , recording_duration : 3500 , show_done_button : false , allow_playback : true }; Open demo in new tab Use recorded video as a subsequent stimulus Code Demo var init_camera = { type : jsPsychInitializeCamera } var record = { type : jsPsychHtmlVideoResponse , stimulus : `<p>Make a sad face.</p>` , recording_duration : 1500 , show_done_button : false , save_video_url : true }; var classify = { type : jsPsychVideoButtonResponse , stimulus : () => { return [ jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. video_url ]; }, choices : [ \"Happy\" , \"Sad\" , \"Angry\" , \"Surprised\" ], prompt : \"<p>What emotion is this?</p>\" , } Open demo in new tab","title":"html-video-response"},{"location":"plugins/html-video-response/#html-video-response","text":"Current version: 1.0.1. See version history . This plugin displays HTML content and records video from the participant via a webcam. In order to get access to the camera, you need to use the initialize-camera plugin on your timeline prior to using this plugin. Once access is granted for an experiment you do not need to get permission again. This plugin records video data in base 64 format . This is a text-based representation of the video which can be coverted to various video formats using a variety of online tools as well as in languages like python and R. This plugin will generate a large amount of data, and you will need to be careful about how you handle this data. Even a few seconds of video recording will add 10s of kB to jsPsych's data. Multiply this by a handful (or more) of trials, and the data objects will quickly get large. If you need to record a lot of video, either many trials worth or just a few trials with longer responses, we recommend that you save the data to your server immediately after the trial and delete the data in jsPsych's data object. See below for an example of how to do this. This plugin also provides the option to store the recorded video files as Object URLs via save_video_url: true . This will generate a URL that stores a copy of the recorded video, which can be used for subsequent playback during the experiment. See below for an example where the recorded video is used as the stimulus in a subsequent trial. This feature is turned off by default because it uses a relatively large amount of memory compared to most jsPsych features. If you are running an experiment where you need this feature and you are recording lots of video clips, you may want to manually revoke the URLs when you no longer need them using URL.revokeObjectURL(objectURL) . Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the camera because of potential security problems .","title":"html-video-response"},{"location":"plugins/html-video-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. recording_duration numeric 2000 The maximum length of the recording, in milliseconds. The default value is intentionally set low because of the potential to accidentally record very large data files if left too high. You can set this to null to allow the participant to control the length of the recording via the done button, but be careful with this option as it can lead to crashing the browser if the participant waits too long to stop the recording. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. show_done_button bool true Whether to show a button on the screen that the participant can click to finish the recording. done_button_label string 'Continue' The label for the done button. allow_playback bool false Whether to allow the participant to listen to their recording and decide whether to rerecord or not. If true , then the participant will be shown an interface to play their recorded video and click one of two buttons to either accept the recording or rerecord. If rerecord is selected, then stimulus will be shown again, as if the trial is starting again from the beginning. record_again_button_label string 'Record again' The label for the record again button enabled when allow_playback: true . accept_button_label string 'Continue' The label for the accept button enabled when allow_playback: true . save_video_url bool false If true , then an Object URL will be generated and stored for the recorded video. Only set this to true if you plan to reuse the recorded video later in the experiment, as it is a potentially memory-intensive feature.","title":"Parameters"},{"location":"plugins/html-video-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The time, since the onset of the stimulus, for the participant to click the done button. If the button is not clicked (or not enabled), then rt will be null . response base64 string The base64-encoded video data. stimulus string The HTML content that was displayed on the screen. video_url string A URL to a copy of the video data.","title":"Data Generated"},{"location":"plugins/html-video-response/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/html-video-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-video-response@1.0.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-video-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-video-response import htmlVideoResponse from '@jspsych/plugin-html-video-response' ;","title":"Install"},{"location":"plugins/html-video-response/#examples","text":"Simple recorded response to a stimulus Code Demo var init_camera = { type : jsPsychInitializeCamera } var trial = { type : jsPsychHtmlVideoResponse , stimulus : ` <p style=\"font-size:48px; color:red;\"> <-- </p> <p>Turn your head in the direction of the arrow</p>` , recording_duration : 3500 , show_done_button : false , }; Open demo in new tab Allow playback and rerecording Code Demo var init_camera = { type : jsPsychInitializeCamera } var trial = { type : jsPsychHtmlVideoResponse , stimulus : `<p>Make a sad face</p>` , recording_duration : 3500 , show_done_button : false , allow_playback : true }; Open demo in new tab Use recorded video as a subsequent stimulus Code Demo var init_camera = { type : jsPsychInitializeCamera } var record = { type : jsPsychHtmlVideoResponse , stimulus : `<p>Make a sad face.</p>` , recording_duration : 1500 , show_done_button : false , save_video_url : true }; var classify = { type : jsPsychVideoButtonResponse , stimulus : () => { return [ jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. video_url ]; }, choices : [ \"Happy\" , \"Sad\" , \"Angry\" , \"Surprised\" ], prompt : \"<p>What emotion is this?</p>\" , } Open demo in new tab","title":"Examples"},{"location":"plugins/iat-html/","text":"iat-html \u00b6 Current version: 1.1.2. See version history . This plugin runs a single trial of the implicit association test (IAT) , using HTML content as the stimulus. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The HTML-formatted stimulus to display. html_when_wrong string <span style=\"color: red; font-size: 80px\">X</span> The content to display when a user presses the wrong key. bottom_instructions string <p>If you press the wrong key, a red X will appear. Press any key to continue.</p> Instructions about making a wrong key press and whether another key press is needed to continue. force_correct_key_press boolean false If this is true and the user presses the wrong key then they have to press the other key to continue. An example would be two keys 'e' and 'i'. If the key associated with the stimulus is 'e' and key 'i' was pressed, then pressing 'e' is needed to continue the trial. When this is true , then parameter key_to_move_forward is not used. display_feedback boolean false If true , then html_when_wrong and wrong_image_name is required. If false , trial_duration is needed and trial will continue automatically. left_category_key string 'e' Key press that is associated with the left_category_label . right_category_key string 'i' Key press that is associated with the right_category_label . left_category_label string ['left'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the left side of the page. right_category_label string ['right'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the right side of the page. stim_key_association string undefined Either 'left' or 'right'. This indicates whether the stimulus is associated with the key press and category on the left or right side of the page ( left_category_key or right_category_key ). key_to_move_forward array of strings \"ALL_KEYS\" This array contains the characters the participant is allowed to press to move on to the next trial if their key press was incorrect and feedback was displayed. Can also have 'other key' as an option which will only allow the user to select the right key to move forward. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML-formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean Boolean indicating whether the user's key press was correct or incorrect for the given stimulus. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-iat-html@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-iat-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-iat-html import iatHtml from '@jspsych/plugin-iat-html' ; Examples \u00b6 Displaying IAT question using html Code Demo var trial = { type : jsPsychIatHtml , stimulus : 'Joyous' , stim_key_association : 'left' , html_when_wrong : '<span style=\"color: red; font-size: 80px\">X</span>' , bottom_instructions : '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>' , force_correct_key_press : true , display_feedback : true , trial_duration : 3000 , //Only if display_feedback is false left_category_key : 'e' , right_category_key : 'i' , left_category_label : [ 'OLD' , 'GOOD' ], right_category_label : [ 'YOUNG' , 'BAD' ], response_ends_trial : true } Open demo in new tab","title":"iat-html"},{"location":"plugins/iat-html/#iat-html","text":"Current version: 1.1.2. See version history . This plugin runs a single trial of the implicit association test (IAT) , using HTML content as the stimulus.","title":"iat-html"},{"location":"plugins/iat-html/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The HTML-formatted stimulus to display. html_when_wrong string <span style=\"color: red; font-size: 80px\">X</span> The content to display when a user presses the wrong key. bottom_instructions string <p>If you press the wrong key, a red X will appear. Press any key to continue.</p> Instructions about making a wrong key press and whether another key press is needed to continue. force_correct_key_press boolean false If this is true and the user presses the wrong key then they have to press the other key to continue. An example would be two keys 'e' and 'i'. If the key associated with the stimulus is 'e' and key 'i' was pressed, then pressing 'e' is needed to continue the trial. When this is true , then parameter key_to_move_forward is not used. display_feedback boolean false If true , then html_when_wrong and wrong_image_name is required. If false , trial_duration is needed and trial will continue automatically. left_category_key string 'e' Key press that is associated with the left_category_label . right_category_key string 'i' Key press that is associated with the right_category_label . left_category_label string ['left'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the left side of the page. right_category_label string ['right'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the right side of the page. stim_key_association string undefined Either 'left' or 'right'. This indicates whether the stimulus is associated with the key press and category on the left or right side of the page ( left_category_key or right_category_key ). key_to_move_forward array of strings \"ALL_KEYS\" This array contains the characters the participant is allowed to press to move on to the next trial if their key press was incorrect and feedback was displayed. Can also have 'other key' as an option which will only allow the user to select the right key to move forward. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/iat-html/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML-formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean Boolean indicating whether the user's key press was correct or incorrect for the given stimulus.","title":"Data Generated"},{"location":"plugins/iat-html/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-iat-html@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-iat-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-iat-html import iatHtml from '@jspsych/plugin-iat-html' ;","title":"Install"},{"location":"plugins/iat-html/#examples","text":"Displaying IAT question using html Code Demo var trial = { type : jsPsychIatHtml , stimulus : 'Joyous' , stim_key_association : 'left' , html_when_wrong : '<span style=\"color: red; font-size: 80px\">X</span>' , bottom_instructions : '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>' , force_correct_key_press : true , display_feedback : true , trial_duration : 3000 , //Only if display_feedback is false left_category_key : 'e' , right_category_key : 'i' , left_category_label : [ 'OLD' , 'GOOD' ], right_category_label : [ 'YOUNG' , 'BAD' ], response_ends_trial : true } Open demo in new tab","title":"Examples"},{"location":"plugins/iat-image/","text":"iat-image \u00b6 Current version: 1.1.2. See version history . This plugin runs a single trial of the implicit association test (IAT) , using an image as the stimulus. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The stimulus to display. The path to an image. html_when_wrong string <span style=\"color: red; font-size: 80px\">X</span> The HTML to display when a user presses the wrong key. bottom_instructions string <p>If you press the wrong key, a red X will appear. Press any key to continue.</p> Instructions about making a wrong key press and whether another key press is needed to continue. force_correct_key_press boolean false If this is true and the user presses the wrong key then they have to press the other key to continue. An example would be two keys 'e' and 'i'. If the key associated with the stimulus is 'e' and key 'i' was pressed, then pressing 'e' is needed to continue the trial. When this is true , then parameter key_to_move_forward is not used. display_feedback boolean false If true , then image_when_wrong and wrong_image_name are required. If false , trial_duration is needed and trial will continue automatically. left_category_key string 'e' Key press that is associated with the left_category_label . right_category_key string 'i' Key press that is associated with the right_category_label . left_category_label string ['left'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the left side of the page. right_category_label string ['right'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the right side of the page. stim_key_association string 'undefined' Either 'left' or 'right'. This indicates whether the stimulus is associated with the key press and category on the left or right side of the page ( left_category_key or right_category_key ). key_to_move_forward array of characters \"ALL_KEYS\" This array contains the characters the participant is allowed to press to move on to the next trial if their key press was incorrect and feedback was displayed. Can also have 'other key' as an option which will only allow the user to select the right key to move forward. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML-formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean Boolean indicating whether the user's key press was correct or incorrect for the given image. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-iat-image@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-iat-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-iat-image import iatImage from '@jspsych/plugin-iat-image' ; Examples \u00b6 Displaying IAT question using image files Code Demo var trial_block = { type : jsPsychIatImage , stimulus : 'img/iat_old_face.jpg' , stim_key_association : 'left' , html_when_wrong : '<span style=\"color: red; font-size: 80px\">X</span>' , bottom_instructions : '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>' , force_correct_key_press : true , display_feedback : true , trial_duration : 3000 , //Only if display_feedback is false left_category_key : 'e' , right_category_key : 'i' , left_category_label : [ 'OLD' , 'GOOD' ], right_category_label : [ 'YOUNG' , 'BAD' ], response_ends_trial : true } Open demo in new tab","title":"iat-image"},{"location":"plugins/iat-image/#iat-image","text":"Current version: 1.1.2. See version history . This plugin runs a single trial of the implicit association test (IAT) , using an image as the stimulus.","title":"iat-image"},{"location":"plugins/iat-image/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The stimulus to display. The path to an image. html_when_wrong string <span style=\"color: red; font-size: 80px\">X</span> The HTML to display when a user presses the wrong key. bottom_instructions string <p>If you press the wrong key, a red X will appear. Press any key to continue.</p> Instructions about making a wrong key press and whether another key press is needed to continue. force_correct_key_press boolean false If this is true and the user presses the wrong key then they have to press the other key to continue. An example would be two keys 'e' and 'i'. If the key associated with the stimulus is 'e' and key 'i' was pressed, then pressing 'e' is needed to continue the trial. When this is true , then parameter key_to_move_forward is not used. display_feedback boolean false If true , then image_when_wrong and wrong_image_name are required. If false , trial_duration is needed and trial will continue automatically. left_category_key string 'e' Key press that is associated with the left_category_label . right_category_key string 'i' Key press that is associated with the right_category_label . left_category_label string ['left'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the left side of the page. right_category_label string ['right'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the right side of the page. stim_key_association string 'undefined' Either 'left' or 'right'. This indicates whether the stimulus is associated with the key press and category on the left or right side of the page ( left_category_key or right_category_key ). key_to_move_forward array of characters \"ALL_KEYS\" This array contains the characters the participant is allowed to press to move on to the next trial if their key press was incorrect and feedback was displayed. Can also have 'other key' as an option which will only allow the user to select the right key to move forward. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/iat-image/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML-formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean Boolean indicating whether the user's key press was correct or incorrect for the given image.","title":"Data Generated"},{"location":"plugins/iat-image/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-iat-image@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-iat-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-iat-image import iatImage from '@jspsych/plugin-iat-image' ;","title":"Install"},{"location":"plugins/iat-image/#examples","text":"Displaying IAT question using image files Code Demo var trial_block = { type : jsPsychIatImage , stimulus : 'img/iat_old_face.jpg' , stim_key_association : 'left' , html_when_wrong : '<span style=\"color: red; font-size: 80px\">X</span>' , bottom_instructions : '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>' , force_correct_key_press : true , display_feedback : true , trial_duration : 3000 , //Only if display_feedback is false left_category_key : 'e' , right_category_key : 'i' , left_category_label : [ 'OLD' , 'GOOD' ], right_category_label : [ 'YOUNG' , 'BAD' ], response_ends_trial : true } Open demo in new tab","title":"Examples"},{"location":"plugins/image-button-response/","text":"image-button-response \u00b6 Current version: 1.1.2. See version history . This plugin displays an image and records responses generated with a button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path of the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ratio boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null, then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true, the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. stimulus string The path of the image that was displayed. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-button-response import imageButtonResponse from '@jspsych/plugin-image-button-response' ; Examples \u00b6 Displaying question until participant gives a response Code Demo var trial = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.png' , choices : [ 'Happy' , 'Sad' ], prompt : \"<p>Is this person happy or sad?</p>\" }; Open demo in new tab","title":"image-button-response"},{"location":"plugins/image-button-response/#image-button-response","text":"Current version: 1.1.2. See version history . This plugin displays an image and records responses generated with a button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images.","title":"image-button-response"},{"location":"plugins/image-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path of the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ratio boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null, then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true, the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images.","title":"Parameters"},{"location":"plugins/image-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. stimulus string The path of the image that was displayed.","title":"Data Generated"},{"location":"plugins/image-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-button-response import imageButtonResponse from '@jspsych/plugin-image-button-response' ;","title":"Install"},{"location":"plugins/image-button-response/#examples","text":"Displaying question until participant gives a response Code Demo var trial = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.png' , choices : [ 'Happy' , 'Sad' ], prompt : \"<p>Is this person happy or sad?</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/image-keyboard-response/","text":"image-keyboard-response \u00b6 Current version: 1.1.2. See version history . This plugin displays an image and records responses generated with the keyboard. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path of the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ratio boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null , then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true , the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false , the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The path of the image that was displayed. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-keyboard-response import imageKeyboardResponse from '@jspsych/plugin-image-keyboard-response' ; Examples \u00b6 Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/happy_face_1.png' , choices : [ 'e' , 'i' ], prompt : \"<p>Is this person happy or sad? Press 'e' for happy and 'i' for sad.</p>\" , }; Open demo in new tab Displaying image for a fixed duration; no response allowed Code Demo var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/happy_face_1.png' , choices : \"NO_KEYS\" , prompt : \"<p>Study this face for 5 seconds.</p>\" , trial_duration : 5000 }; Open demo in new tab","title":"image-keyboard-response"},{"location":"plugins/image-keyboard-response/#image-keyboard-response","text":"Current version: 1.1.2. See version history . This plugin displays an image and records responses generated with the keyboard. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images.","title":"image-keyboard-response"},{"location":"plugins/image-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path of the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ratio boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null , then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true , the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false , the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images.","title":"Parameters"},{"location":"plugins/image-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The path of the image that was displayed.","title":"Data Generated"},{"location":"plugins/image-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-keyboard-response import imageKeyboardResponse from '@jspsych/plugin-image-keyboard-response' ;","title":"Install"},{"location":"plugins/image-keyboard-response/#examples","text":"Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/happy_face_1.png' , choices : [ 'e' , 'i' ], prompt : \"<p>Is this person happy or sad? Press 'e' for happy and 'i' for sad.</p>\" , }; Open demo in new tab Displaying image for a fixed duration; no response allowed Code Demo var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/happy_face_1.png' , choices : \"NO_KEYS\" , prompt : \"<p>Study this face for 5 seconds.</p>\" , trial_duration : 5000 }; Open demo in new tab","title":"Examples"},{"location":"plugins/image-slider-response/","text":"image-slider-response \u00b6 Current version: 1.1.2. See version history . This plugin displays and image and allows the participant to respond by dragging a slider. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path to the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ration boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to advance/submit min integer 0 Sets the minimum value of the slider max integer 100 Sets the maximum value of the slider slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null, then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true, the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The path of the image that was displayed. slider_start numeric The starting value of the slider. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-slider-response import imageSliderResponse from '@jspsych/plugin-image-slider-response' ; Examples \u00b6 Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychImageSliderResponse , stimulus : 'img/happy_face_1.png' , labels : [ 'happy' , 'sad' ], prompt : \"<p>How happy/sad is this person?</p>\" , }; Open demo in new tab","title":"image-slider-response"},{"location":"plugins/image-slider-response/#image-slider-response","text":"Current version: 1.1.2. See version history . This plugin displays and image and allows the participant to respond by dragging a slider. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images.","title":"image-slider-response"},{"location":"plugins/image-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path to the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ration boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to advance/submit min integer 0 Sets the minimum value of the slider max integer 100 Sets the maximum value of the slider slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null, then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true, the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images.","title":"Parameters"},{"location":"plugins/image-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The path of the image that was displayed. slider_start numeric The starting value of the slider.","title":"Data Generated"},{"location":"plugins/image-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-slider-response import imageSliderResponse from '@jspsych/plugin-image-slider-response' ;","title":"Install"},{"location":"plugins/image-slider-response/#examples","text":"Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychImageSliderResponse , stimulus : 'img/happy_face_1.png' , labels : [ 'happy' , 'sad' ], prompt : \"<p>How happy/sad is this person?</p>\" , }; Open demo in new tab","title":"Examples"},{"location":"plugins/initialize-camera/","text":"initialize-camera \u00b6 Current version: 1.0.0 See version history . This plugin asks the participant to grant permission to access a camera. If multiple cameras are connected to the participant's device, then it allows the participant to pick which device to use. Once access is granted for an experiment you do not need to get permission again. Once the camera is selected with this plugin it can be accessed with jsPsych.pluginAPI.getCameraRecorder() . Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description device_select_message html string <p>Please select the camera you would like to use.</p> The message to display when the user is presented with a dropdown list of available devices. button_label sting 'Use this camera.' The label for the select button. include_audio bool false Set to true to include an audio track in the recordings. width int null Request a specific width for the recording. This is not a guarantee that this width will be used, as it depends on the capabilities of the participant's device. Learn more about MediaRecorder constraints here . height int null Request a specific height for the recording. This is not a guarantee that this height will be used, as it depends on the capabilities of the participant's device. Learn more about MediaRecorder constraints here . mime_type string null Set this to use a specific MIME type for the recording. Set the entire type, e.g., 'video/mp4; codecs=\"avc1.424028, mp4a.40.2\"' . Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value device_id string The device ID of the selected camera. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-initialize-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-initialize-camera import initializeCamera from '@jspsych/plugin-initialize-camera' ; Examples \u00b6 Ask for camera permission Code Demo var trial = { type : jsPsychInitializeCamera }; Open demo in new tab","title":"initialize-camera"},{"location":"plugins/initialize-camera/#initialize-camera","text":"Current version: 1.0.0 See version history . This plugin asks the participant to grant permission to access a camera. If multiple cameras are connected to the participant's device, then it allows the participant to pick which device to use. Once access is granted for an experiment you do not need to get permission again. Once the camera is selected with this plugin it can be accessed with jsPsych.pluginAPI.getCameraRecorder() . Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems .","title":"initialize-camera"},{"location":"plugins/initialize-camera/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description device_select_message html string <p>Please select the camera you would like to use.</p> The message to display when the user is presented with a dropdown list of available devices. button_label sting 'Use this camera.' The label for the select button. include_audio bool false Set to true to include an audio track in the recordings. width int null Request a specific width for the recording. This is not a guarantee that this width will be used, as it depends on the capabilities of the participant's device. Learn more about MediaRecorder constraints here . height int null Request a specific height for the recording. This is not a guarantee that this height will be used, as it depends on the capabilities of the participant's device. Learn more about MediaRecorder constraints here . mime_type string null Set this to use a specific MIME type for the recording. Set the entire type, e.g., 'video/mp4; codecs=\"avc1.424028, mp4a.40.2\"' .","title":"Parameters"},{"location":"plugins/initialize-camera/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value device_id string The device ID of the selected camera.","title":"Data Generated"},{"location":"plugins/initialize-camera/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/initialize-camera/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-initialize-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-initialize-camera import initializeCamera from '@jspsych/plugin-initialize-camera' ;","title":"Install"},{"location":"plugins/initialize-camera/#examples","text":"Ask for camera permission Code Demo var trial = { type : jsPsychInitializeCamera }; Open demo in new tab","title":"Examples"},{"location":"plugins/initialize-microphone/","text":"initialize-microphone \u00b6 Current version: 1.0.2. See version history . This plugin asks the participant to grant permission to access a microphone. If multiple microphones are connected to the participant's device, then it allows the participant to pick which device to use. Once access is granted for an experiment you do not need to get permission again. Once the microphone is selected with this plugin it can be accessed with jsPsych.pluginAPI.getMicrophoneRecorder() . Warning When recording from a microphone your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description device_select_message html string <p>Please select the microphone you would like to use.</p> The message to display when the user is presented with a dropdown list of available devices. button_label sting 'Use this microphone.' The label for the select button. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value device_id string The device ID of the selected microphone. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-initialize-microphone.js\" >< /script> Using NPM: npm install @jspsych/plugin-initialize-microphone import initializeMicrophone from '@jspsych/plugin-initialize-microphone' ; Examples \u00b6 Ask for microphone permission Code Demo var trial = { type : jsPsychInitializeMicrophone }; Open demo in new tab","title":"initialize-microphone"},{"location":"plugins/initialize-microphone/#initialize-microphone","text":"Current version: 1.0.2. See version history . This plugin asks the participant to grant permission to access a microphone. If multiple microphones are connected to the participant's device, then it allows the participant to pick which device to use. Once access is granted for an experiment you do not need to get permission again. Once the microphone is selected with this plugin it can be accessed with jsPsych.pluginAPI.getMicrophoneRecorder() . Warning When recording from a microphone your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems .","title":"initialize-microphone"},{"location":"plugins/initialize-microphone/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description device_select_message html string <p>Please select the microphone you would like to use.</p> The message to display when the user is presented with a dropdown list of available devices. button_label sting 'Use this microphone.' The label for the select button.","title":"Parameters"},{"location":"plugins/initialize-microphone/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value device_id string The device ID of the selected microphone.","title":"Data Generated"},{"location":"plugins/initialize-microphone/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/initialize-microphone/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-initialize-microphone.js\" >< /script> Using NPM: npm install @jspsych/plugin-initialize-microphone import initializeMicrophone from '@jspsych/plugin-initialize-microphone' ;","title":"Install"},{"location":"plugins/initialize-microphone/#examples","text":"Ask for microphone permission Code Demo var trial = { type : jsPsychInitializeMicrophone }; Open demo in new tab","title":"Examples"},{"location":"plugins/instructions/","text":"instructions \u00b6 Current version: 1.1.3. See version history . This plugin is for showing instructions to the participant. It allows participants to navigate through multiple pages of instructions at their own pace, recording how long the participant spends on each page. Navigation can be done using the mouse or keyboard. participants can be allowed to navigate forwards and backwards through pages, if desired. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description pages array undefined Each element of the array is the content for a single page. Each page should be an HTML-formatted string. key_forward string 'ArrowRight' This is the key that the participant can press in order to advance to the next page. This key should be specified as a string (e.g., 'a' , 'ArrowLeft' , ' ' , 'Enter' ). key_backward string 'ArrowLeft' This is the key that the participant can press to return to the previous page. This key should be specified as a string (e.g., 'a' , 'ArrowLeft' , ' ' , 'Enter' ). allow_backward boolean true If true, the participant can return to previous pages of the instructions. If false, they may only advace to the next page. allow_keys boolean true If true , the participant can use keyboard keys to navigate the pages. If false , they may not. show_clickable_nav boolean false If true, then a Previous and Next button will be displayed beneath the instructions. Participants can click the buttons to navigate. button_label_previous string 'Previous' The text that appears on the button to go backwards. button_label_next string 'Next' The text that appears on the button to go forwards. show_page_number boolean false If true, and clickable navigation is enabled, then Page x/y will be shown between the nav buttons. page_label string 'Page' The text that appears before x/y pages displayed when show_page_number is true. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value view_history array An array containing the order of pages the participant viewed (including when the participant returned to previous pages) and the time spent viewing each page. Each object in the array represents a single page view, and contains keys called page_index (the page number, starting with 0) and viewing_time (duration of the page view). This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to view all of the pages. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-instructions@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-instructions.js\" >< /script> Using NPM: npm install @jspsych/plugin-instructions import instructions from '@jspsych/plugin-instructions' ; Examples \u00b6 Showing simple text instructions \u00b6 Showing simple text instructions Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'This is the second page of instructions.' , 'This is the final page.' ], show_clickable_nav : true } Open demo in new tab Including images \u00b6 Including Images Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'You will be looking at images of arrows: ' + '<br>' + '<img src=\"con2.png\"></img>' ], show_clickable_nav : true } Open demo in new tab Changing Button Text \u00b6 Changing Button Text Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'This is the second page of instructions.' , 'This is the final page.' ], button_label_next : \"Continue\" , button_label_previous : \"Return to the dark side\" , show_clickable_nav : true } Open demo in new tab","title":"instructions"},{"location":"plugins/instructions/#instructions","text":"Current version: 1.1.3. See version history . This plugin is for showing instructions to the participant. It allows participants to navigate through multiple pages of instructions at their own pace, recording how long the participant spends on each page. Navigation can be done using the mouse or keyboard. participants can be allowed to navigate forwards and backwards through pages, if desired.","title":"instructions"},{"location":"plugins/instructions/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description pages array undefined Each element of the array is the content for a single page. Each page should be an HTML-formatted string. key_forward string 'ArrowRight' This is the key that the participant can press in order to advance to the next page. This key should be specified as a string (e.g., 'a' , 'ArrowLeft' , ' ' , 'Enter' ). key_backward string 'ArrowLeft' This is the key that the participant can press to return to the previous page. This key should be specified as a string (e.g., 'a' , 'ArrowLeft' , ' ' , 'Enter' ). allow_backward boolean true If true, the participant can return to previous pages of the instructions. If false, they may only advace to the next page. allow_keys boolean true If true , the participant can use keyboard keys to navigate the pages. If false , they may not. show_clickable_nav boolean false If true, then a Previous and Next button will be displayed beneath the instructions. Participants can click the buttons to navigate. button_label_previous string 'Previous' The text that appears on the button to go backwards. button_label_next string 'Next' The text that appears on the button to go forwards. show_page_number boolean false If true, and clickable navigation is enabled, then Page x/y will be shown between the nav buttons. page_label string 'Page' The text that appears before x/y pages displayed when show_page_number is true.","title":"Parameters"},{"location":"plugins/instructions/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value view_history array An array containing the order of pages the participant viewed (including when the participant returned to previous pages) and the time spent viewing each page. Each object in the array represents a single page view, and contains keys called page_index (the page number, starting with 0) and viewing_time (duration of the page view). This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to view all of the pages.","title":"Data Generated"},{"location":"plugins/instructions/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-instructions@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-instructions.js\" >< /script> Using NPM: npm install @jspsych/plugin-instructions import instructions from '@jspsych/plugin-instructions' ;","title":"Install"},{"location":"plugins/instructions/#examples","text":"","title":"Examples"},{"location":"plugins/instructions/#showing-simple-text-instructions","text":"Showing simple text instructions Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'This is the second page of instructions.' , 'This is the final page.' ], show_clickable_nav : true } Open demo in new tab","title":"Showing simple text instructions"},{"location":"plugins/instructions/#including-images","text":"Including Images Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'You will be looking at images of arrows: ' + '<br>' + '<img src=\"con2.png\"></img>' ], show_clickable_nav : true } Open demo in new tab","title":"Including images"},{"location":"plugins/instructions/#changing-button-text","text":"Changing Button Text Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'This is the second page of instructions.' , 'This is the final page.' ], button_label_next : \"Continue\" , button_label_previous : \"Return to the dark side\" , show_clickable_nav : true } Open demo in new tab","title":"Changing Button Text"},{"location":"plugins/list-of-plugins/","text":"List of Plugins \u00b6 These are the plugins that are included in the jsPsych release. Additional plugins may be available in the community contributions repository . For an overview of what plugins are and how they work, see our plugins overview . Plugin Description animation Shows a sequence of images at a specified frame rate. Records key presses (including timing information) made by the participant while they are viewing the animation. audio\u2011button\u2011response Play an audio file and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. audio\u2011keyboard\u2011response Play an audio file and allow the participant to respond by pressing a key. audio\u2011slider\u2011response Play an audio file and allow the participant to respond by moving a slider to indicate a value. browser\u2011check Measures various features of the participant's browser and runs an inclusion check to see if the browser meets a custom set of criteria for running the study. call\u2011function Executes an arbitrary function call. Doesn't display anything to the participant, and the participant is usually unaware that this plugin has even executed. It's useful for performing tasks at specified times in the experiment, such as saving data. canvas\u2011button\u2011response Draw a stimulus on a HTML canvas element , and record a button click response. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). canvas\u2011keyboard\u2011response Draw a stimulus on a HTML canvas element , and record a key press response. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). canvas\u2011slider\u2011response Draw a stimulus on a HTML canvas element , and ask the participant to respond by moving a slider to indicate a value. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). categorize\u2011animation The participant responds to an animation and can be given feedback about their response. categorize\u2011html The participant responds to an HTML-formatted stimulus using the keyboard and can be given feedback about the correctness of their response. categorize\u2011image The participant responds to an image using the keyboard and can be given feedback about the correctness of their response. cloze Plugin for displaying a cloze test and checking participants answers against a correct solution. external\u2011html Displays an external HTML page (such as a consent form) and lets the participant respond by clicking a button or pressing a key. Plugin can validate their response, which is useful for making sure that a participant has granted consent before starting the experiment. free\u2011sort Displays a set of images on the screen in random locations. Participants can click and drag the images to move them around the screen. Records all the moves made by the participant, so the sequence of moves can be recovered from the data. fullscreen Toggles the experiment in and out of fullscreen mode. html\u2011audio\u2011response Display an HTML-formatted stimulus and records an audio response via a microphone. html\u2011button\u2011response Display an HTML-formatted stimulus and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. html\u2011keyboard\u2011response Display an HTML-formatted stimulus and allow the participant to respond by pressing a key. html\u2011slider\u2011response Display an HTML-formatted stimulus and allow the participant to respond by moving a slider to indicate a value. html\u2011video\u2011response Display an HTML-formatted stimulus and records video data via a webcam. iat\u2011html The implicit association task, using HTML-formatted stimuli. iat\u2011image The implicit association task, using images as stimuli. image\u2011button\u2011response Display an image and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. image\u2011keyboard\u2011response Display an image and allow the participant to respond by pressing a key. image\u2011slider\u2011response Display an image and allow the participant to respond by moving a slider to indicate a value. initialize\u2011camera Request permission to use the participant's camera to record video and allows the participant to choose which camera to use if multiple devices are enabled. Also allows setting the mime type of the recorded video. initialize\u2011microphone Request permission to use the participant's microphone to record audio and allows the participant to choose which microphone to use if multiple devices are enabled. instructions For displaying instructions to the participant. Allows the participant to navigate between pages of instructions using keys or buttons. maxdiff Displays rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. mirror\u2011camera Shows a live feed of the participant's camera on the screen. preload This plugin loads images, audio, and video files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and to avoid disrupting the flow of the experiment. reconstruction The participant interacts with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time. resize Calibrate the display so that materials display with a known physical size. same\u2011different\u2011html A same-different judgment task. An HTML-formatted stimulus is shown, followed by a brief gap, and then another stimulus is shown. The participant indicates whether the stimuli are the same or different. same\u2011different\u2011image A same-different judgment task. An image is shown, followed by a brief gap, and then another stimulus is shown. The participant indicates whether the stimuli are the same or different. serial\u2011reaction\u2011time A set of boxes are displayed on the screen and one of them changes color. The participant presses a key that corresponds to the different color box as fast as possible. serial\u2011reaction\u2011time\u2011mouse A set of boxes are displayed on the screen and one of them changes color. The participants clicks the box that changed color as fast as possible. sketchpad Creates an interactive canvas that the participant can draw on using their mouse or touchscreen. survey\u2011html\u2011form Renders a custom HTML form. Allows for mixing multiple kinds of form input. survey\u2011likert Displays likert-style questions. survey\u2011multi\u2011choice Displays multiple choice questions with one answer allowed per question. survey\u2011multi\u2011select Displays multiple choice questions with multiple answes allowed per question. survey\u2011text Shows a prompt with a text box. The participant writes a response and then submits by clicking a button. video\u2011button\u2011response Displays a video file with many options for customizing playback. participant responds to the video by pressing a button. video\u2011keyboard\u2011response Displays a video file with many options for customizing playback. participant responds to the video by pressing a key. video\u2011slider\u2011response Displays a video file with many options for customizing playback. participant responds to the video by moving a slider. virtual\u2011chinrest An implementation of the \"virutal chinrest\" procedure developed by Li, Joo, Yeatman, and Reinecke (2020) . Calibrates the monitor to display items at a known physical size by having participants scale an image to be the same size as a physical credit card. Then uses a blind spot task to estimate the distance between the participant and the display. visual\u2011search\u2011circle A customizable visual-search task modelled after Wang, Cavanagh, & Green (1994) . The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. webgazer\u2011calibrate Calibrates the WebGazer extension for eye tracking. webgazer\u2011init\u2011camera Initializes the camera and helps the participant center their face for eye tracking. webgazer\u2011validate Performs validation to measure precision and accuracy of WebGazer eye tracking predictions.","title":"List of Plugins"},{"location":"plugins/list-of-plugins/#list-of-plugins","text":"These are the plugins that are included in the jsPsych release. Additional plugins may be available in the community contributions repository . For an overview of what plugins are and how they work, see our plugins overview . Plugin Description animation Shows a sequence of images at a specified frame rate. Records key presses (including timing information) made by the participant while they are viewing the animation. audio\u2011button\u2011response Play an audio file and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. audio\u2011keyboard\u2011response Play an audio file and allow the participant to respond by pressing a key. audio\u2011slider\u2011response Play an audio file and allow the participant to respond by moving a slider to indicate a value. browser\u2011check Measures various features of the participant's browser and runs an inclusion check to see if the browser meets a custom set of criteria for running the study. call\u2011function Executes an arbitrary function call. Doesn't display anything to the participant, and the participant is usually unaware that this plugin has even executed. It's useful for performing tasks at specified times in the experiment, such as saving data. canvas\u2011button\u2011response Draw a stimulus on a HTML canvas element , and record a button click response. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). canvas\u2011keyboard\u2011response Draw a stimulus on a HTML canvas element , and record a key press response. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). canvas\u2011slider\u2011response Draw a stimulus on a HTML canvas element , and ask the participant to respond by moving a slider to indicate a value. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). categorize\u2011animation The participant responds to an animation and can be given feedback about their response. categorize\u2011html The participant responds to an HTML-formatted stimulus using the keyboard and can be given feedback about the correctness of their response. categorize\u2011image The participant responds to an image using the keyboard and can be given feedback about the correctness of their response. cloze Plugin for displaying a cloze test and checking participants answers against a correct solution. external\u2011html Displays an external HTML page (such as a consent form) and lets the participant respond by clicking a button or pressing a key. Plugin can validate their response, which is useful for making sure that a participant has granted consent before starting the experiment. free\u2011sort Displays a set of images on the screen in random locations. Participants can click and drag the images to move them around the screen. Records all the moves made by the participant, so the sequence of moves can be recovered from the data. fullscreen Toggles the experiment in and out of fullscreen mode. html\u2011audio\u2011response Display an HTML-formatted stimulus and records an audio response via a microphone. html\u2011button\u2011response Display an HTML-formatted stimulus and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. html\u2011keyboard\u2011response Display an HTML-formatted stimulus and allow the participant to respond by pressing a key. html\u2011slider\u2011response Display an HTML-formatted stimulus and allow the participant to respond by moving a slider to indicate a value. html\u2011video\u2011response Display an HTML-formatted stimulus and records video data via a webcam. iat\u2011html The implicit association task, using HTML-formatted stimuli. iat\u2011image The implicit association task, using images as stimuli. image\u2011button\u2011response Display an image and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. image\u2011keyboard\u2011response Display an image and allow the participant to respond by pressing a key. image\u2011slider\u2011response Display an image and allow the participant to respond by moving a slider to indicate a value. initialize\u2011camera Request permission to use the participant's camera to record video and allows the participant to choose which camera to use if multiple devices are enabled. Also allows setting the mime type of the recorded video. initialize\u2011microphone Request permission to use the participant's microphone to record audio and allows the participant to choose which microphone to use if multiple devices are enabled. instructions For displaying instructions to the participant. Allows the participant to navigate between pages of instructions using keys or buttons. maxdiff Displays rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. mirror\u2011camera Shows a live feed of the participant's camera on the screen. preload This plugin loads images, audio, and video files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and to avoid disrupting the flow of the experiment. reconstruction The participant interacts with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time. resize Calibrate the display so that materials display with a known physical size. same\u2011different\u2011html A same-different judgment task. An HTML-formatted stimulus is shown, followed by a brief gap, and then another stimulus is shown. The participant indicates whether the stimuli are the same or different. same\u2011different\u2011image A same-different judgment task. An image is shown, followed by a brief gap, and then another stimulus is shown. The participant indicates whether the stimuli are the same or different. serial\u2011reaction\u2011time A set of boxes are displayed on the screen and one of them changes color. The participant presses a key that corresponds to the different color box as fast as possible. serial\u2011reaction\u2011time\u2011mouse A set of boxes are displayed on the screen and one of them changes color. The participants clicks the box that changed color as fast as possible. sketchpad Creates an interactive canvas that the participant can draw on using their mouse or touchscreen. survey\u2011html\u2011form Renders a custom HTML form. Allows for mixing multiple kinds of form input. survey\u2011likert Displays likert-style questions. survey\u2011multi\u2011choice Displays multiple choice questions with one answer allowed per question. survey\u2011multi\u2011select Displays multiple choice questions with multiple answes allowed per question. survey\u2011text Shows a prompt with a text box. The participant writes a response and then submits by clicking a button. video\u2011button\u2011response Displays a video file with many options for customizing playback. participant responds to the video by pressing a button. video\u2011keyboard\u2011response Displays a video file with many options for customizing playback. participant responds to the video by pressing a key. video\u2011slider\u2011response Displays a video file with many options for customizing playback. participant responds to the video by moving a slider. virtual\u2011chinrest An implementation of the \"virutal chinrest\" procedure developed by Li, Joo, Yeatman, and Reinecke (2020) . Calibrates the monitor to display items at a known physical size by having participants scale an image to be the same size as a physical credit card. Then uses a blind spot task to estimate the distance between the participant and the display. visual\u2011search\u2011circle A customizable visual-search task modelled after Wang, Cavanagh, & Green (1994) . The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. webgazer\u2011calibrate Calibrates the WebGazer extension for eye tracking. webgazer\u2011init\u2011camera Initializes the camera and helps the participant center their face for eye tracking. webgazer\u2011validate Performs validation to measure precision and accuracy of WebGazer eye tracking predictions.","title":"List of Plugins"},{"location":"plugins/maxdiff/","text":"maxdiff \u00b6 Current version: 1.1.2. See version history . The maxdiff plugin displays a table with rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. The same alternative cannot be endorsed on both the left and right response columns (e.g. 'most' and 'least') simultaneously. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description alternatives array undefined An array of one or more alternatives of string type to fill the rows of the maxdiff table. If required is true, then the array must contain two or more alternatives, so that at least one can be selected for both the left and right columns. labels array undefined An array with exactly two labels of string type to display as column headings (to the left and right of the alternatives) for responses on the criteria of interest. randomize_alternative_order boolean false If true, the display order of alternatives is randomly determined at the start of the trial. preamble string empty string HTML formatted string to display at the top of the page above the maxdiff table. required boolean false If true, prevents the user from submitting the response and proceeding until a radio button in both the left and right response columns has been selected. button_label string 'Continue' Label of the button. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the maxdiff table first appears on the screen until the participant's response. labels object An object with two keys, left and right , containing the labels (strings) corresponding to the left and right response columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response object An object with two keys, left and right , containing the alternatives selected on the left and right columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-maxdiff@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-maxdiff.js\" >< /script> Using NPM: npm install @jspsych/plugin-maxdiff import maxdiff from '@jspsych/plugin-maxdiff' ; Examples \u00b6 Basic example Code Demo var maxdiff_page = { type : jsPsychMaxdiff , alternatives : [ 'apple' , 'orange' , 'pear' , 'banana' ], labels : [ 'Most Preferred' , 'Least Preferred' ], preamble : '<p> Please select your <b>most preferred</b> and <b>least preferred</b> fruits. </p>' }; Open demo in new tab","title":"maxdiff"},{"location":"plugins/maxdiff/#maxdiff","text":"Current version: 1.1.2. See version history . The maxdiff plugin displays a table with rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. The same alternative cannot be endorsed on both the left and right response columns (e.g. 'most' and 'least') simultaneously.","title":"maxdiff"},{"location":"plugins/maxdiff/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description alternatives array undefined An array of one or more alternatives of string type to fill the rows of the maxdiff table. If required is true, then the array must contain two or more alternatives, so that at least one can be selected for both the left and right columns. labels array undefined An array with exactly two labels of string type to display as column headings (to the left and right of the alternatives) for responses on the criteria of interest. randomize_alternative_order boolean false If true, the display order of alternatives is randomly determined at the start of the trial. preamble string empty string HTML formatted string to display at the top of the page above the maxdiff table. required boolean false If true, prevents the user from submitting the response and proceeding until a radio button in both the left and right response columns has been selected. button_label string 'Continue' Label of the button.","title":"Parameters"},{"location":"plugins/maxdiff/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the maxdiff table first appears on the screen until the participant's response. labels object An object with two keys, left and right , containing the labels (strings) corresponding to the left and right response columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response object An object with two keys, left and right , containing the alternatives selected on the left and right columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/maxdiff/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-maxdiff@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-maxdiff.js\" >< /script> Using NPM: npm install @jspsych/plugin-maxdiff import maxdiff from '@jspsych/plugin-maxdiff' ;","title":"Install"},{"location":"plugins/maxdiff/#examples","text":"Basic example Code Demo var maxdiff_page = { type : jsPsychMaxdiff , alternatives : [ 'apple' , 'orange' , 'pear' , 'banana' ], labels : [ 'Most Preferred' , 'Least Preferred' ], preamble : '<p> Please select your <b>most preferred</b> and <b>least preferred</b> fruits. </p>' }; Open demo in new tab","title":"Examples"},{"location":"plugins/mirror-camera/","text":"mirror-camera \u00b6 Current version: 1.0.0 See version history . This plugin shows a live feed of the participant's camera. It can be useful in experiments that need to record video in order to give the participant a chance to see what is in the view of the camera. You must initialize the camera using the initialize-camera plugin prior to running this plugin. Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the camera because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description prompt html string null HTML-formatted content to display below the camera feed. width int null The width of the video playback element. If left null then it will match the size of the recording. height int null The height of the video playback element. If left null then it will match the size of the recording. button_label string \"Continue\" The label of the button to advance to the next trial. mirror_camera bool true Whether to mirror the video image. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt int The length of time the participant viewed the video playback. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-mirror-camera@1.0.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-mirror-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-mirror-camera import mirrorCamera from '@jspsych/plugin-mirror-camera' ; Examples \u00b6 Show the camera feed Code Demo const init_camera = { type : jsPsychInitializeCamera , } const mirror_camera = { type : jsPsychMirrorCamera , } Open demo in new tab","title":"mirror-camera"},{"location":"plugins/mirror-camera/#mirror-camera","text":"Current version: 1.0.0 See version history . This plugin shows a live feed of the participant's camera. It can be useful in experiments that need to record video in order to give the participant a chance to see what is in the view of the camera. You must initialize the camera using the initialize-camera plugin prior to running this plugin. Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the camera because of potential security problems .","title":"mirror-camera"},{"location":"plugins/mirror-camera/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description prompt html string null HTML-formatted content to display below the camera feed. width int null The width of the video playback element. If left null then it will match the size of the recording. height int null The height of the video playback element. If left null then it will match the size of the recording. button_label string \"Continue\" The label of the button to advance to the next trial. mirror_camera bool true Whether to mirror the video image.","title":"Parameters"},{"location":"plugins/mirror-camera/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt int The length of time the participant viewed the video playback.","title":"Data Generated"},{"location":"plugins/mirror-camera/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/mirror-camera/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-mirror-camera@1.0.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-mirror-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-mirror-camera import mirrorCamera from '@jspsych/plugin-mirror-camera' ;","title":"Install"},{"location":"plugins/mirror-camera/#examples","text":"Show the camera feed Code Demo const init_camera = { type : jsPsychInitializeCamera , } const mirror_camera = { type : jsPsychMirrorCamera , } Open demo in new tab","title":"Examples"},{"location":"plugins/preload/","text":"preload \u00b6 Current version: 1.1.2. See version history . This plugin loads images, audio, and video files. It is used for loading files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and avoid disruption to the experiment flow. We recommend using this plugin anytime you are loading media files, and especially when your experiment requires large and/or many media files. See the Media Preloading page for more information. The preload trial will end as soon as all files have loaded successfully. The trial will end or stop with an error message when one of these two scenarios occurs (whichever comes first): (a) all files have not finished loading when the max_load_time duration is reached, or (b) all file requests have responded with either a load or fail event, and one or more files has failed to load. The continue_after_error parameter determines whether the trial will stop with an error message or end (allowing the experiment to continue) when preloading is not successful. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. While there are no specific parameters that are required, the plugin expects to be given a set of files to load through one or more of the following parameters: auto_preload or trials (for automatic loading), and/or images , audio , video (for manual loading). To automatically load files based on a timeline of trials, either set the auto_preload parameter is true (to load files based on the main timeline passed to jsPsych.run ) or use the trials parameter to load files based on a specific subset of trials. To manually load a set of files, use the images , audio , and video parameters. You can combine automatic and manual loading methods in a single preload trial. All other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description auto_preload boolean false If true , the plugin will preload any files that can be automatically preloaded based on the main experiment timeline that is passed to jsPsych.run . If false , any file(s) to be preloaded should be specified by passing a timeline array to the trials parameter and/or an array of file paths to the images , audio , and/or video parameters. Setting this parameter to false is useful when you plan to preload your files in smaller batches throughout the experiment. trials timeline array [] An array containing one or more jsPsych trial or timeline objects. This parameter is useful when you want to automatically preload stimuli files from a specific subset of the experiment. See Creating an Experiment: The Timeline for information on constructing timelines. images array [] Array containing file paths for one or more image files to preload. This option is typically used for image files that can't be automatically preloaded from the timeline. audio array [] Array containing file paths for one or more audio files to preload. This option is typically used for audio files that can't be automatically preloaded from the timeline. video array [] Array containing file paths for one or more video files to preload. This option is typically used for video files that can't be automatically preloaded from the timeline. message HTML string null HTML-formatted message to show above the progress bar while the files are loading. If null , then no message is shown. show_progress_bar boolean true If true , a progress bar will be shown while the files are loading. If false , no progress bar is shown. continue_after_error boolean false If false , then the experiment will stop during this trial if either (a) one or more of the files fails to load, and/or (b) all files do not finish loading before the max_load_time duration is reached. The trial will display the error_message , as well as the detailed error messages if show_detailed_errors is true . If true , the experiment will continue even if loading fails or times out, and information about loading success/failure will be stored in the trial data (see \"Data Generated\" below). error_message HTML string 'The experiment failed to load.' HTML-formatted message to be shown on the page after loading fails or times out. Only applies when continue_after_error is false . show_detailed_errors boolean false If true , and if continue_after_error is false , then a list of detailed errors will be shown below the error_message . This list will contain the file paths for any files that produced a loading failure, as well as a message indicating that loading timed out, if that was the case. This setting is intended to help the researcher with testing/debugging. If false , and if continue_after_error is false , then only the error_message will be shown if loading fails or times out. max_load_time numeric null Duration to wait, in milliseconds, for all files to load before loading times out. If one or more files has not finished loading within this time limit, then the trial will stop with an error (if continue_after_error is false ), or the trial will end with information about the loading time-out in the trial data (see \"Data Generated\" below). If null , the trial will wait indefinitely for all files to either load or produce an error. on_error function null Function to be called immediately after a file loading request has returned an error. The function receives a single argument, which is the file path that produced the error. This callback is cancelled as soon as the trial ends. See example below. on_success function null Function to be called immediately after a file has successfully loaded. The function receives a single argument, which is the file path that finished loading. This callback is cancelled as soon as the trial ends. See example below. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value success boolean If true , then all files loaded successfully within the max_load_time . If false , then one or more file requests returned a failure and/or the file loading did not complete within the max_load_time duration. timeout boolean If true , then the files did not finish loading within the max_load_time duration. If false , then the file loading did not timeout. Note that when the preload trial does not timeout ( timeout: false ), it is still possible for loading to fail ( success: false ). This happens if one or more files fails to load and all file requests trigger either a success or failure event before the max_load_time duration. failed_images array One or more image file paths that produced a loading failure before the trial ended. failed_audio array One or more audio file paths that produced a loading failure before the trial ended. failed_video array One or more video file paths that produced a loading failure before the trial ended. Simulation Mode \u00b6 In visual simulation mode, the plugin will run the trial as if the experiment was running normally. Specifying simulation_options.data will not work in visual mode. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-preload.js\" >< /script> Using NPM: npm install @jspsych/plugin-preload import preload from '@jspsych/plugin-preload' ; Examples \u00b6 Automatically preloading based on other trials Code Demo var preload = { type : jsPsychPreload , auto_preload : true } var trial_1 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.jpg' , choices : [ 'Next' ] } var trial_2 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_2.jpg' , choices : [ 'Next' ] } var trial_3 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_3.jpg' , choices : [ 'Next' ] } The stimulus parameter from the image-button-response trials will be automatically preloaded. Open demo in new tab Manually preloading an image Code Demo var preload = { type : jsPsychPreload , images : [ 'img/sad_face_1.jpg' ] } var trial_1 = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Study this face</p> <img src=\"img/sad_face_1.jpg\"></img> ` , choices : [ 'Next' ] } Because the image is embedded inside HTML from the html-button-response plugin, it will not be automatically preloaded. Instead we can preload manually. Open demo in new tab Loading files in batches Code Demo var jsPsych = initJsPsych (); var trial_1 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.jpg' , choices : [ 'Next' ] } var trial_2 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_2.jpg' , choices : [ 'Next' ] } var trial_3 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_3.jpg' , choices : [ 'Next' ] } var block_1 = { timeline : [ trial_1 , trial_2 , trial_3 ] } var trial_4 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_1.jpg' , choices : [ 'Next' ] } var trial_5 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_2.jpg' , choices : [ 'Next' ] } var trial_6 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_3.jpg' , choices : [ 'Next' ] } var block_2 = { timeline : [ trial_4 , trial_5 , trial_6 ] } var preload_block_1 = { type : jsPsychPreload , trials : [ block_1 ] } var preload_block_2 = { type : jsPsychPreload , trials : [ block_2 ] } jsPsych . run ([ preload_block_1 , block_1 , preload_block_2 , block_2 ]) You can put trials using the preload plugin throughout your experiment to distribute when files are loaded. In the example above, there are two blocks of trials and the images for each are preloaded just before the corresponding block. Open demo in new tab Showing a detailed error message for debugging loading issues Code Demo var preload = { type : jsPsychPreload , images : [ 'img/bad_file_path.png' ], show_detailed_errors : true } Open demo in new tab For more examples, see the jspsych-preload.html file in the /examples folder of the release and the Media Preloading documentation page.","title":"preload"},{"location":"plugins/preload/#preload","text":"Current version: 1.1.2. See version history . This plugin loads images, audio, and video files. It is used for loading files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and avoid disruption to the experiment flow. We recommend using this plugin anytime you are loading media files, and especially when your experiment requires large and/or many media files. See the Media Preloading page for more information. The preload trial will end as soon as all files have loaded successfully. The trial will end or stop with an error message when one of these two scenarios occurs (whichever comes first): (a) all files have not finished loading when the max_load_time duration is reached, or (b) all file requests have responded with either a load or fail event, and one or more files has failed to load. The continue_after_error parameter determines whether the trial will stop with an error message or end (allowing the experiment to continue) when preloading is not successful.","title":"preload"},{"location":"plugins/preload/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. While there are no specific parameters that are required, the plugin expects to be given a set of files to load through one or more of the following parameters: auto_preload or trials (for automatic loading), and/or images , audio , video (for manual loading). To automatically load files based on a timeline of trials, either set the auto_preload parameter is true (to load files based on the main timeline passed to jsPsych.run ) or use the trials parameter to load files based on a specific subset of trials. To manually load a set of files, use the images , audio , and video parameters. You can combine automatic and manual loading methods in a single preload trial. All other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description auto_preload boolean false If true , the plugin will preload any files that can be automatically preloaded based on the main experiment timeline that is passed to jsPsych.run . If false , any file(s) to be preloaded should be specified by passing a timeline array to the trials parameter and/or an array of file paths to the images , audio , and/or video parameters. Setting this parameter to false is useful when you plan to preload your files in smaller batches throughout the experiment. trials timeline array [] An array containing one or more jsPsych trial or timeline objects. This parameter is useful when you want to automatically preload stimuli files from a specific subset of the experiment. See Creating an Experiment: The Timeline for information on constructing timelines. images array [] Array containing file paths for one or more image files to preload. This option is typically used for image files that can't be automatically preloaded from the timeline. audio array [] Array containing file paths for one or more audio files to preload. This option is typically used for audio files that can't be automatically preloaded from the timeline. video array [] Array containing file paths for one or more video files to preload. This option is typically used for video files that can't be automatically preloaded from the timeline. message HTML string null HTML-formatted message to show above the progress bar while the files are loading. If null , then no message is shown. show_progress_bar boolean true If true , a progress bar will be shown while the files are loading. If false , no progress bar is shown. continue_after_error boolean false If false , then the experiment will stop during this trial if either (a) one or more of the files fails to load, and/or (b) all files do not finish loading before the max_load_time duration is reached. The trial will display the error_message , as well as the detailed error messages if show_detailed_errors is true . If true , the experiment will continue even if loading fails or times out, and information about loading success/failure will be stored in the trial data (see \"Data Generated\" below). error_message HTML string 'The experiment failed to load.' HTML-formatted message to be shown on the page after loading fails or times out. Only applies when continue_after_error is false . show_detailed_errors boolean false If true , and if continue_after_error is false , then a list of detailed errors will be shown below the error_message . This list will contain the file paths for any files that produced a loading failure, as well as a message indicating that loading timed out, if that was the case. This setting is intended to help the researcher with testing/debugging. If false , and if continue_after_error is false , then only the error_message will be shown if loading fails or times out. max_load_time numeric null Duration to wait, in milliseconds, for all files to load before loading times out. If one or more files has not finished loading within this time limit, then the trial will stop with an error (if continue_after_error is false ), or the trial will end with information about the loading time-out in the trial data (see \"Data Generated\" below). If null , the trial will wait indefinitely for all files to either load or produce an error. on_error function null Function to be called immediately after a file loading request has returned an error. The function receives a single argument, which is the file path that produced the error. This callback is cancelled as soon as the trial ends. See example below. on_success function null Function to be called immediately after a file has successfully loaded. The function receives a single argument, which is the file path that finished loading. This callback is cancelled as soon as the trial ends. See example below.","title":"Parameters"},{"location":"plugins/preload/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value success boolean If true , then all files loaded successfully within the max_load_time . If false , then one or more file requests returned a failure and/or the file loading did not complete within the max_load_time duration. timeout boolean If true , then the files did not finish loading within the max_load_time duration. If false , then the file loading did not timeout. Note that when the preload trial does not timeout ( timeout: false ), it is still possible for loading to fail ( success: false ). This happens if one or more files fails to load and all file requests trigger either a success or failure event before the max_load_time duration. failed_images array One or more image file paths that produced a loading failure before the trial ended. failed_audio array One or more audio file paths that produced a loading failure before the trial ended. failed_video array One or more video file paths that produced a loading failure before the trial ended.","title":"Data Generated"},{"location":"plugins/preload/#simulation-mode","text":"In visual simulation mode, the plugin will run the trial as if the experiment was running normally. Specifying simulation_options.data will not work in visual mode.","title":"Simulation Mode"},{"location":"plugins/preload/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-preload.js\" >< /script> Using NPM: npm install @jspsych/plugin-preload import preload from '@jspsych/plugin-preload' ;","title":"Install"},{"location":"plugins/preload/#examples","text":"Automatically preloading based on other trials Code Demo var preload = { type : jsPsychPreload , auto_preload : true } var trial_1 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.jpg' , choices : [ 'Next' ] } var trial_2 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_2.jpg' , choices : [ 'Next' ] } var trial_3 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_3.jpg' , choices : [ 'Next' ] } The stimulus parameter from the image-button-response trials will be automatically preloaded. Open demo in new tab Manually preloading an image Code Demo var preload = { type : jsPsychPreload , images : [ 'img/sad_face_1.jpg' ] } var trial_1 = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Study this face</p> <img src=\"img/sad_face_1.jpg\"></img> ` , choices : [ 'Next' ] } Because the image is embedded inside HTML from the html-button-response plugin, it will not be automatically preloaded. Instead we can preload manually. Open demo in new tab Loading files in batches Code Demo var jsPsych = initJsPsych (); var trial_1 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.jpg' , choices : [ 'Next' ] } var trial_2 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_2.jpg' , choices : [ 'Next' ] } var trial_3 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_3.jpg' , choices : [ 'Next' ] } var block_1 = { timeline : [ trial_1 , trial_2 , trial_3 ] } var trial_4 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_1.jpg' , choices : [ 'Next' ] } var trial_5 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_2.jpg' , choices : [ 'Next' ] } var trial_6 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_3.jpg' , choices : [ 'Next' ] } var block_2 = { timeline : [ trial_4 , trial_5 , trial_6 ] } var preload_block_1 = { type : jsPsychPreload , trials : [ block_1 ] } var preload_block_2 = { type : jsPsychPreload , trials : [ block_2 ] } jsPsych . run ([ preload_block_1 , block_1 , preload_block_2 , block_2 ]) You can put trials using the preload plugin throughout your experiment to distribute when files are loaded. In the example above, there are two blocks of trials and the images for each are preloaded just before the corresponding block. Open demo in new tab Showing a detailed error message for debugging loading issues Code Demo var preload = { type : jsPsychPreload , images : [ 'img/bad_file_path.png' ], show_detailed_errors : true } Open demo in new tab For more examples, see the jspsych-preload.html file in the /examples folder of the release and the Media Preloading documentation page.","title":"Examples"},{"location":"plugins/reconstruction/","text":"reconstruction \u00b6 Current version: 1.1.2. See version history . This plugin allows a participant to interact with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time. The stimulus must be defined through a function that returns an HTML-formatted string. The function should take a single value, which is the parameter that can be modified by the participant. The value can only range from 0 to 1. See the example at the bottom of the page for a sample function. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stim_function function undefined A function with a single parameter that returns an HTML-formatted string representing the stimulus. starting_value numeric 0.5 The starting value of the stimulus parameter. step_size numeric 0.05 The change in the stimulus parameter caused by pressing one of the modification keys. key_increase string 'h' The key to press for increasing the parameter value. key_decrease string 'g' The key to press for decreasing the parameter value. button_label string 'Continue' The text that appears on the button to finish the trial. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value start_value numeric The starting value of the stimulus parameter. final_value numeric The final value of the stimulus parameter. rt numeric The length of time, in milliseconds, that the trial lasted. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-reconstruction@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-reconstruction.js\" >< /script> Using NPM: npm install @jspsych/plugin-reconstruction import reconstruction from '@jspsych/plugin-reconstruction' ; Examples \u00b6 Make a block larger and smaller Code Demo var sample_function = function ( param ){ var size = 50 + Math . floor ( param * 250 ); var html = '<div style=\"display: block; margin: auto; height: 300px; width: 300px; position: relative;\">' + '<div style=\"display: block; position: absolute; top: ' + ( 150 - size / 2 ) + 'px; left:' + ( 150 - size / 2 ) + 'px; background-color: #000000; ' + 'width: ' + size + 'px; height: ' + size + 'px;\"></div></div><p>Press \"h\" to make the square larger. Press \"g\" to make the square smaller.</p>' + '<p>When the square is the same size as the previous one, click Continue.</p>' ; return html ; } var match_item = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"display: block; margin: auto; height: 300px; width: 300px; position: relative;\">' + '<div style=\"display: block; position: absolute; top: ' + ( 150 - 210 / 2 ) + 'px; left:' + ( 150 - 210 / 2 ) + 'px; background-color: #000000; ' + 'width: 210px; height: 210px;\"></div></div>' , choices : [ 'c' ], post_trial_gap : 1250 , prompt : '<p>Study the size of this square carefully. On the next screen you will have to recreate it. When you are ready, press \"c\".</p>' } var reconstruction = { type : jsPsychReconstruction , stim_function : sample_function , starting_value : 0.5 , } Open demo in new tab","title":"reconstruction"},{"location":"plugins/reconstruction/#reconstruction","text":"Current version: 1.1.2. See version history . This plugin allows a participant to interact with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time. The stimulus must be defined through a function that returns an HTML-formatted string. The function should take a single value, which is the parameter that can be modified by the participant. The value can only range from 0 to 1. See the example at the bottom of the page for a sample function.","title":"reconstruction"},{"location":"plugins/reconstruction/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stim_function function undefined A function with a single parameter that returns an HTML-formatted string representing the stimulus. starting_value numeric 0.5 The starting value of the stimulus parameter. step_size numeric 0.05 The change in the stimulus parameter caused by pressing one of the modification keys. key_increase string 'h' The key to press for increasing the parameter value. key_decrease string 'g' The key to press for decreasing the parameter value. button_label string 'Continue' The text that appears on the button to finish the trial.","title":"Parameters"},{"location":"plugins/reconstruction/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value start_value numeric The starting value of the stimulus parameter. final_value numeric The final value of the stimulus parameter. rt numeric The length of time, in milliseconds, that the trial lasted.","title":"Data Generated"},{"location":"plugins/reconstruction/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-reconstruction@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-reconstruction.js\" >< /script> Using NPM: npm install @jspsych/plugin-reconstruction import reconstruction from '@jspsych/plugin-reconstruction' ;","title":"Install"},{"location":"plugins/reconstruction/#examples","text":"Make a block larger and smaller Code Demo var sample_function = function ( param ){ var size = 50 + Math . floor ( param * 250 ); var html = '<div style=\"display: block; margin: auto; height: 300px; width: 300px; position: relative;\">' + '<div style=\"display: block; position: absolute; top: ' + ( 150 - size / 2 ) + 'px; left:' + ( 150 - size / 2 ) + 'px; background-color: #000000; ' + 'width: ' + size + 'px; height: ' + size + 'px;\"></div></div><p>Press \"h\" to make the square larger. Press \"g\" to make the square smaller.</p>' + '<p>When the square is the same size as the previous one, click Continue.</p>' ; return html ; } var match_item = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"display: block; margin: auto; height: 300px; width: 300px; position: relative;\">' + '<div style=\"display: block; position: absolute; top: ' + ( 150 - 210 / 2 ) + 'px; left:' + ( 150 - 210 / 2 ) + 'px; background-color: #000000; ' + 'width: 210px; height: 210px;\"></div></div>' , choices : [ 'c' ], post_trial_gap : 1250 , prompt : '<p>Study the size of this square carefully. On the next screen you will have to recreate it. When you are ready, press \"c\".</p>' } var reconstruction = { type : jsPsychReconstruction , stim_function : sample_function , starting_value : 0.5 , } Open demo in new tab","title":"Examples"},{"location":"plugins/resize/","text":"resize \u00b6 Current version: 1.0.2. See version history . This plugin displays a resizable div container that allows the user to drag until the container is the same size as the item being measured. Once the user measures the item as close as possible, clicking the button sets a scaling factor for the div containing jsPsych content. This causes the stimuli that follow to have a known size, independent of monitor resolution. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description item_height numeric 1 The height of the item to be measured. Any units can be used as long as you are consistent with using the same units for all parameters. item_width numeric 1 The width of the item to be measured. pixels_per_unit numeric 100 After the scaling factor is applied, this many pixels will equal one unit of measurement. prompt string '' HTML content to display below the resizable box, and above the button. button_label string 'Continue' Label to display on the button to complete calibration. starting_size numeric 100 The initial size of the box, in pixels, along the largest dimension. The aspect ratio will be set automatically to match the item width and height. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value final_width_px numeric Final width of the resizable div container, in pixels. scale_factor numeric Scaling factor that will be applied to the div containing jsPsych content. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-resize@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-resize.js\" >< /script> Using NPM: npm install @jspsych/plugin-resize import resize from '@jspsych/plugin-resize' ; Examples \u00b6 Measuring a credit card and resizing the display to have 150 pixels equal an inch. Code Demo var inputs = { type : jsPsychResize , item_width : 3 + 3 / 8 , item_height : 2 + 1 / 8 , prompt : \"<p>Click and drag the lower right corner of the box until the box is the same size as a credit card held up to the screen.</p>\" , pixels_per_unit : 150 }; Open demo in new tab","title":"resize"},{"location":"plugins/resize/#resize","text":"Current version: 1.0.2. See version history . This plugin displays a resizable div container that allows the user to drag until the container is the same size as the item being measured. Once the user measures the item as close as possible, clicking the button sets a scaling factor for the div containing jsPsych content. This causes the stimuli that follow to have a known size, independent of monitor resolution.","title":"resize"},{"location":"plugins/resize/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description item_height numeric 1 The height of the item to be measured. Any units can be used as long as you are consistent with using the same units for all parameters. item_width numeric 1 The width of the item to be measured. pixels_per_unit numeric 100 After the scaling factor is applied, this many pixels will equal one unit of measurement. prompt string '' HTML content to display below the resizable box, and above the button. button_label string 'Continue' Label to display on the button to complete calibration. starting_size numeric 100 The initial size of the box, in pixels, along the largest dimension. The aspect ratio will be set automatically to match the item width and height.","title":"Parameters"},{"location":"plugins/resize/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value final_width_px numeric Final width of the resizable div container, in pixels. scale_factor numeric Scaling factor that will be applied to the div containing jsPsych content.","title":"Data Generated"},{"location":"plugins/resize/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/resize/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-resize@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-resize.js\" >< /script> Using NPM: npm install @jspsych/plugin-resize import resize from '@jspsych/plugin-resize' ;","title":"Install"},{"location":"plugins/resize/#examples","text":"Measuring a credit card and resizing the display to have 150 pixels equal an inch. Code Demo var inputs = { type : jsPsychResize , item_width : 3 + 3 / 8 , item_height : 2 + 1 / 8 , prompt : \"<p>Click and drag the lower right corner of the box until the box is the same size as a credit card held up to the screen.</p>\" , pixels_per_unit : 150 }; Open demo in new tab","title":"Examples"},{"location":"plugins/same-different-html/","text":"same-different-html \u00b6 Current version: 1.1.2. See version history . The same-different-html plugin displays two stimuli sequentially. Stimuli are HTML objects. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined A pair of stimuli, represented as an array with two entries, one for each stimulus. A stimulus is a string containing valid HTML markup. Stimuli will be shown in the order that they are defined in the array. answer string undefined Either 'same' or 'different' . same_key string 'q' The key that participants should press to indicate that the two stimuli are the same. different_key string 'p' The key that participants should press to indicate that the two stimuli are different. first_stim_duration numeric 1000 How long to show the first stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant presses any key. gap_duration numeric 500 How long to show a blank screen in between the two stimuli. second_stim_duration numeric 1000 How long to show the second stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant responds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array An array of length 2 containing the HTML-formatted content that the participant saw for each trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the answer for this trial. answer string The correct answer to the trial, either 'same' or 'different' . Additionally, if first_stim_duration is null, then the following data is also collected: Name Type Value rt_stim1 numeric The response time in milliseconds for the participant to continue after the first stimulus. The time is measured from when the first stimulus appears on the screen until the participant's response. response_stim1 string Indicates which key the participant pressed to continue. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-same-different-html@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-same-different-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-same-different-html import sameDifferentHtml from '@jspsych/plugin-same-different-html' ; Examples \u00b6 Two text choices Code Demo var trial = { type : jsPsychSameDifferentHtml , stimuli : [ '<p style=\"font-size:30px;\">Climbing</p>' , '<p style=\"font-size:30px;\">Walking</p>' ], prompt : `<p>Press 's' if the activities require the same amount of physical exertion.</p> <p>Press 'd' if the activities require different amount of physical exertion.</p>` , same_key : 's' , different_key : 'd' , first_stim_duration : 800 , answer : 'different' } Open demo in new tab","title":"same-different-html"},{"location":"plugins/same-different-html/#same-different-html","text":"Current version: 1.1.2. See version history . The same-different-html plugin displays two stimuli sequentially. Stimuli are HTML objects. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example.","title":"same-different-html"},{"location":"plugins/same-different-html/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined A pair of stimuli, represented as an array with two entries, one for each stimulus. A stimulus is a string containing valid HTML markup. Stimuli will be shown in the order that they are defined in the array. answer string undefined Either 'same' or 'different' . same_key string 'q' The key that participants should press to indicate that the two stimuli are the same. different_key string 'p' The key that participants should press to indicate that the two stimuli are different. first_stim_duration numeric 1000 How long to show the first stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant presses any key. gap_duration numeric 500 How long to show a blank screen in between the two stimuli. second_stim_duration numeric 1000 How long to show the second stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant responds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press).","title":"Parameters"},{"location":"plugins/same-different-html/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array An array of length 2 containing the HTML-formatted content that the participant saw for each trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the answer for this trial. answer string The correct answer to the trial, either 'same' or 'different' . Additionally, if first_stim_duration is null, then the following data is also collected: Name Type Value rt_stim1 numeric The response time in milliseconds for the participant to continue after the first stimulus. The time is measured from when the first stimulus appears on the screen until the participant's response. response_stim1 string Indicates which key the participant pressed to continue.","title":"Data Generated"},{"location":"plugins/same-different-html/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-same-different-html@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-same-different-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-same-different-html import sameDifferentHtml from '@jspsych/plugin-same-different-html' ;","title":"Install"},{"location":"plugins/same-different-html/#examples","text":"Two text choices Code Demo var trial = { type : jsPsychSameDifferentHtml , stimuli : [ '<p style=\"font-size:30px;\">Climbing</p>' , '<p style=\"font-size:30px;\">Walking</p>' ], prompt : `<p>Press 's' if the activities require the same amount of physical exertion.</p> <p>Press 'd' if the activities require different amount of physical exertion.</p>` , same_key : 's' , different_key : 'd' , first_stim_duration : 800 , answer : 'different' } Open demo in new tab","title":"Examples"},{"location":"plugins/same-different-image/","text":"same-different-image \u00b6 Current version: 1.1.2. See version history . The same-different-image plugin displays two stimuli sequentially. Stimuli are images. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined A pair of stimuli, represented as an array with two entries, one for each stimulus. The stimulus is a path to an image file. Stimuli will be shown in the order that they are defined in the array. answer string undefined Either 'same' or 'different' . same_key string 'q' The key that participants should press to indicate that the two stimuli are the same. different_key string 'p' The key that participants should press to indicate that the two stimuli are different. first_stim_duration numeric 1000 How long to show the first stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant presses any key. gap_duration numeric 500 How long to show a blank screen in between the two stimuli. second_stim_duration numeric 1000 How long to show the second stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant responds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array An array of length 2 containing the paths to the image files that the participant saw for each trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the answer for this trial. answer string The correct answer to the trial, either 'same' or 'different' . Additionally, if first_stim_duration is null, then the following data is also collected: Name Type Value rt_stim1 numeric The response time in milliseconds for the participant to continue after the first stimulus. The time is measured from when the first stimulus appears on the screen until the participant's response. response_stim1 string Indicates which key the participant pressed to continue. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-same-different-image@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-same-different-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-same-different-image import sameDifferentImage from '@jspsych/plugin-same-different-image' ; Examples \u00b6 Identifying emotional expressions Code Demo var trial = { type : jsPsychSameDifferentImage , stimuli : [ 'img/happy_face_1.jpg' , 'img/sad_face_3.jpg' ], prompt : `<p>Press s if the faces had the same emotional expression.</p> <p>Press d if the faces had different emotional expressions.</p>` , same_key : 's' , different_key : 'd' , first_stim_duration : 800 , answer : 'different' } Open demo in new tab","title":"same-different-image"},{"location":"plugins/same-different-image/#same-different-image","text":"Current version: 1.1.2. See version history . The same-different-image plugin displays two stimuli sequentially. Stimuli are images. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example.","title":"same-different-image"},{"location":"plugins/same-different-image/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined A pair of stimuli, represented as an array with two entries, one for each stimulus. The stimulus is a path to an image file. Stimuli will be shown in the order that they are defined in the array. answer string undefined Either 'same' or 'different' . same_key string 'q' The key that participants should press to indicate that the two stimuli are the same. different_key string 'p' The key that participants should press to indicate that the two stimuli are different. first_stim_duration numeric 1000 How long to show the first stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant presses any key. gap_duration numeric 500 How long to show a blank screen in between the two stimuli. second_stim_duration numeric 1000 How long to show the second stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant responds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press).","title":"Parameters"},{"location":"plugins/same-different-image/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array An array of length 2 containing the paths to the image files that the participant saw for each trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the answer for this trial. answer string The correct answer to the trial, either 'same' or 'different' . Additionally, if first_stim_duration is null, then the following data is also collected: Name Type Value rt_stim1 numeric The response time in milliseconds for the participant to continue after the first stimulus. The time is measured from when the first stimulus appears on the screen until the participant's response. response_stim1 string Indicates which key the participant pressed to continue.","title":"Data Generated"},{"location":"plugins/same-different-image/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-same-different-image@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-same-different-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-same-different-image import sameDifferentImage from '@jspsych/plugin-same-different-image' ;","title":"Install"},{"location":"plugins/same-different-image/#examples","text":"Identifying emotional expressions Code Demo var trial = { type : jsPsychSameDifferentImage , stimuli : [ 'img/happy_face_1.jpg' , 'img/sad_face_3.jpg' ], prompt : `<p>Press s if the faces had the same emotional expression.</p> <p>Press d if the faces had different emotional expressions.</p>` , same_key : 's' , different_key : 'd' , first_stim_duration : 800 , answer : 'different' } Open demo in new tab","title":"Examples"},{"location":"plugins/serial-reaction-time-mouse/","text":"serial-reaction-time-mouse \u00b6 Current version: 1.1.2. See version history . The serial reaction time mouse plugin implements a generalized version of the SRT task (Nissen & Bullmer, 1987) . Squares are displayed in a grid-based system on the screen, and one square changes color. The participant must click on the square that changes color. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target array undefined The location of the target. The array should be the [row, column] of the target. grid array [[1,1,1,1]] This array represents the grid of boxes shown on the screen. Each inner array represents a single row. The entries in the inner arrays represent the columns. If an entry is 1 then a square will be drawn at that location on the grid. If an entry is 0 then the corresponding location on the grid will be empty. Thus, by mixing 1 s and 0 s it is possible to create many different grid-based arrangements. grid_square_size numeric 100 The width and height in pixels of each square in the grid. target_color hex color code #999 The color of the target square. response_ends_trial boolean true If true, the trial ends after a mouse click. Feedback is displayed if show_response_feedback is true. pre_target_duration numeric 0 The number of milliseconds to display the grid before the target changes color. trial_duration numeric null The maximum length of time of the trial, not including feedback. fade_duration numeric null If a positive number, the target will progressively change color at the start of the trial, with the transition lasting this many milliseconds. allow_nontarget_responses boolean false If true, the user can make nontarget response. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which keys to press). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value grid array The grid representation. Each inner array represents a single row. The entries in the inner arrays represent the columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. target array The [row, column] target location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. response array The [row, column] response location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. correct boolean Whether the response location matches the target location ( true ) or not ( false ). Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-serial-reaction-time-mouse.js\" >< /script> Using NPM: npm install @jspsych/plugin-serial-reaction-time-mouse import serialReactionTimeMouse from '@jspsych/plugin-serial-reaction-time-mouse' ; Examples \u00b6 A classic version of the SRT Code Demo var grid = [ [ 1 , 1 , 1 , 1 ] ] var trial_1 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 0 ] } var trial_2 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 1 ] } var trial_3 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 2 ] } var trial_4 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 3 ] } Open demo in new tab A 2x2 grid with extra space and different colors Code Demo var grid = [ [ 1 , 0 , 1 ], [ 0 , 0 , 0 ], [ 1 , 0 , 1 ] ] var trial_1 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 0 ], target_color : '#006738' } var trial_2 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 2 ], target_color : '#F78F1E' } var trial_3 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 2 , 2 ], target_color : '#13B24B' } var trial_4 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 2 , 0 ], target_color : '#E74921' } Open demo in new tab","title":"serial-reaction-time-mouse"},{"location":"plugins/serial-reaction-time-mouse/#serial-reaction-time-mouse","text":"Current version: 1.1.2. See version history . The serial reaction time mouse plugin implements a generalized version of the SRT task (Nissen & Bullmer, 1987) . Squares are displayed in a grid-based system on the screen, and one square changes color. The participant must click on the square that changes color.","title":"serial-reaction-time-mouse"},{"location":"plugins/serial-reaction-time-mouse/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target array undefined The location of the target. The array should be the [row, column] of the target. grid array [[1,1,1,1]] This array represents the grid of boxes shown on the screen. Each inner array represents a single row. The entries in the inner arrays represent the columns. If an entry is 1 then a square will be drawn at that location on the grid. If an entry is 0 then the corresponding location on the grid will be empty. Thus, by mixing 1 s and 0 s it is possible to create many different grid-based arrangements. grid_square_size numeric 100 The width and height in pixels of each square in the grid. target_color hex color code #999 The color of the target square. response_ends_trial boolean true If true, the trial ends after a mouse click. Feedback is displayed if show_response_feedback is true. pre_target_duration numeric 0 The number of milliseconds to display the grid before the target changes color. trial_duration numeric null The maximum length of time of the trial, not including feedback. fade_duration numeric null If a positive number, the target will progressively change color at the start of the trial, with the transition lasting this many milliseconds. allow_nontarget_responses boolean false If true, the user can make nontarget response. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which keys to press).","title":"Parameters"},{"location":"plugins/serial-reaction-time-mouse/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value grid array The grid representation. Each inner array represents a single row. The entries in the inner arrays represent the columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. target array The [row, column] target location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. response array The [row, column] response location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. correct boolean Whether the response location matches the target location ( true ) or not ( false ).","title":"Data Generated"},{"location":"plugins/serial-reaction-time-mouse/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-serial-reaction-time-mouse.js\" >< /script> Using NPM: npm install @jspsych/plugin-serial-reaction-time-mouse import serialReactionTimeMouse from '@jspsych/plugin-serial-reaction-time-mouse' ;","title":"Install"},{"location":"plugins/serial-reaction-time-mouse/#examples","text":"A classic version of the SRT Code Demo var grid = [ [ 1 , 1 , 1 , 1 ] ] var trial_1 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 0 ] } var trial_2 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 1 ] } var trial_3 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 2 ] } var trial_4 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 3 ] } Open demo in new tab A 2x2 grid with extra space and different colors Code Demo var grid = [ [ 1 , 0 , 1 ], [ 0 , 0 , 0 ], [ 1 , 0 , 1 ] ] var trial_1 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 0 ], target_color : '#006738' } var trial_2 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 2 ], target_color : '#F78F1E' } var trial_3 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 2 , 2 ], target_color : '#13B24B' } var trial_4 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 2 , 0 ], target_color : '#E74921' } Open demo in new tab","title":"Examples"},{"location":"plugins/serial-reaction-time/","text":"serial-reaction-time \u00b6 Current version: 1.1.3. See version history . The serial reaction time plugin implements a generalized version of the SRT task (Nissen & Bullemer, 1987) . Squares are displayed in a grid-based system on the screen, and one square changes color. The participant presses a key that corresponds to the darkened key. Feedback is optionally displayed, showing the participant which square the key they pressed matches. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target array undefined The location of the target. The array should be the [row, column] of the target. grid array [[1,1,1,1]] This array represents the grid of boxes shown on the screen. Each inner array represents a single row. The entries in the inner arrays represent the columns. If an entry is 1 then a square will be drawn at that location on the grid. If an entry is 0 then the corresponding location on the grid will be empty. Thus, by mixing 1 s and 0 s it is possible to create many different grid-based arrangements. choices array of strings [['3','5','7','9']] The dimensions of this array must match the dimensions of grid . Each entry in this array is the key that should be pressed for that corresponding location in the grid. Entries can be left blank if there is no key associated with that location of the grid. grid_square_size numeric 100 The width and height in pixels of each square in the grid. target_color hex color code #999 The color of the target square. response_ends_trial boolean true If true, the trial ends after a key press. Feedback is displayed if show_response_feedback is true. pre_target_duration numeric 0 The number of milliseconds to display the grid before the target changes color. trial_duration numeric null The maximum length of time of the trial, not including feedback. show_response_feedback boolean false If true, show feedback indicating where the user responded and whether it was correct. feedback_duration numeric 200 The length of time in milliseconds to show the feedback. fade_duration numeric null If a positive number, the target will progressively change color at the start of the trial, with the transition lasting this many milliseconds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which keys to press). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value grid array The representation of the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. target array The representation of the target location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the target. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-serial-reaction-time.js\" >< /script> Using NPM: npm install @jspsych/plugin-serial-reaction-time import serialReactionTime from '@jspsych/plugin-serial-reaction-time' ; Examples \u00b6 A classic SRT Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : '<p>Use the S, F, H, and K keys to respond.</p>' , choices : [ 'Continue' ] } var grid = [ [ 1 , 1 , 1 , 1 ] ] var response_map = [ [ 's' , 'f' , 'h' , 'k' ] ] var trial_1 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 0 ] } var trial_2 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 1 ] } var trial_3 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 2 ] } var trial_4 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 3 ] } Open demo in new tab 2x2 grid with feedback Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : '<p>Use the R, I, V, and M keys to respond.</p>' , choices : [ 'Continue' ] } var grid = [ [ 1 , 1 ], [ 1 , 1 ] ] var response_map = [ [ 'r' , 'i' ], [ 'v' , 'm' ] ] var trial_1 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 0 ], show_response_feedback : true , feedback_duration : 500 } var trial_2 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 1 ], show_response_feedback : true , feedback_duration : 500 } var trial_3 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 1 , 1 ], show_response_feedback : true , feedback_duration : 500 } var trial_4 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 1 , 0 ], show_response_feedback : true , feedback_duration : 500 } Open demo in new tab","title":"serial-reaction-time"},{"location":"plugins/serial-reaction-time/#serial-reaction-time","text":"Current version: 1.1.3. See version history . The serial reaction time plugin implements a generalized version of the SRT task (Nissen & Bullemer, 1987) . Squares are displayed in a grid-based system on the screen, and one square changes color. The participant presses a key that corresponds to the darkened key. Feedback is optionally displayed, showing the participant which square the key they pressed matches.","title":"serial-reaction-time"},{"location":"plugins/serial-reaction-time/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target array undefined The location of the target. The array should be the [row, column] of the target. grid array [[1,1,1,1]] This array represents the grid of boxes shown on the screen. Each inner array represents a single row. The entries in the inner arrays represent the columns. If an entry is 1 then a square will be drawn at that location on the grid. If an entry is 0 then the corresponding location on the grid will be empty. Thus, by mixing 1 s and 0 s it is possible to create many different grid-based arrangements. choices array of strings [['3','5','7','9']] The dimensions of this array must match the dimensions of grid . Each entry in this array is the key that should be pressed for that corresponding location in the grid. Entries can be left blank if there is no key associated with that location of the grid. grid_square_size numeric 100 The width and height in pixels of each square in the grid. target_color hex color code #999 The color of the target square. response_ends_trial boolean true If true, the trial ends after a key press. Feedback is displayed if show_response_feedback is true. pre_target_duration numeric 0 The number of milliseconds to display the grid before the target changes color. trial_duration numeric null The maximum length of time of the trial, not including feedback. show_response_feedback boolean false If true, show feedback indicating where the user responded and whether it was correct. feedback_duration numeric 200 The length of time in milliseconds to show the feedback. fade_duration numeric null If a positive number, the target will progressively change color at the start of the trial, with the transition lasting this many milliseconds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which keys to press).","title":"Parameters"},{"location":"plugins/serial-reaction-time/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value grid array The representation of the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. target array The representation of the target location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the target.","title":"Data Generated"},{"location":"plugins/serial-reaction-time/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-serial-reaction-time.js\" >< /script> Using NPM: npm install @jspsych/plugin-serial-reaction-time import serialReactionTime from '@jspsych/plugin-serial-reaction-time' ;","title":"Install"},{"location":"plugins/serial-reaction-time/#examples","text":"A classic SRT Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : '<p>Use the S, F, H, and K keys to respond.</p>' , choices : [ 'Continue' ] } var grid = [ [ 1 , 1 , 1 , 1 ] ] var response_map = [ [ 's' , 'f' , 'h' , 'k' ] ] var trial_1 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 0 ] } var trial_2 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 1 ] } var trial_3 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 2 ] } var trial_4 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 3 ] } Open demo in new tab 2x2 grid with feedback Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : '<p>Use the R, I, V, and M keys to respond.</p>' , choices : [ 'Continue' ] } var grid = [ [ 1 , 1 ], [ 1 , 1 ] ] var response_map = [ [ 'r' , 'i' ], [ 'v' , 'm' ] ] var trial_1 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 0 ], show_response_feedback : true , feedback_duration : 500 } var trial_2 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 1 ], show_response_feedback : true , feedback_duration : 500 } var trial_3 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 1 , 1 ], show_response_feedback : true , feedback_duration : 500 } var trial_4 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 1 , 0 ], show_response_feedback : true , feedback_duration : 500 } Open demo in new tab","title":"Examples"},{"location":"plugins/sketchpad/","text":"sketchpad \u00b6 Current version: 1.0.3. See version history . This plugin creates an interactive canvas that the participant can draw on using their mouse or touchscreen. It can be used for sketching tasks, like asking the participant to draw a particular object. It can also be used for some image segmentation or annotation tasks by setting the background_image parameter to render an image on the canvas. The plugin stores a base 64 data URL representation of the final image. This can be converted to an image file using online tools or short programs in R , python , or another language of your choice. It also records all of the individual strokes that the participant made during the trial. Warning This plugin generates a lot of data. Each trial can easily add 500kb+ of data to a final JSON output. You can reduce the amount of data generated by turning off storage of the individual stroke data ( save_strokes: false ) or storage of the final image ( save_final_image: false ) if your use case doesn't require that information. If you are going to be collecting a lot of data with this plugin you may want to save your data to your server after each trial and not wait until the end of the experiment to perform a single bulk upload. You can do this by putting data saving code inside the on_data_update event handler . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameter Type Default Value Description canvas_shape \"rectangle\" or \"circle\" \"rectangle\" The shape of the canvas element. canvas_width int 500 Width of the canvas in pixels when canvas_shape is a \"rectangle\" . canvas_height int 500 Height of the canvas in pixels when canvas_shape is a \"rectangle\" . canvas_diameter int 500 Diameter of the canvas in pixels when canvas_shape is a \"circle\" . canvas_border_width int 0 Width of the canvas border. canvas_border_color string \"#000\" Color of the canvas border. background_image image path null Path to an image to render as the background of the canvas. background_color string \"#fff\" Color of the canvas background. Note that a background_image will render on top of the color. stroke_width int 2 Width of the stroke on the canvas. stroke_color string \"#000\" Color of the stroke on the canvas. stroke_color_palette array of strings [] Array of colors to render as a palette of choices for stroke color. Clicking on the corresponding color button will change the stroke color. prompt string null HTML content to render on the screen. prompt_location \"abovecanvas\" or \"belowcanvas\" or \"belowbutton\" \"abovecanvas\" The location to render the prompt content. save_final_image bool true Whether to save the final image in the data as a base64 encoded data URL. save_strokes bool true Whether to save the individual stroke data that generated the final image. key_to_draw key string null If this key is held down then it is like the mouse button being held down. The \"ink\" will flow when the button is held and stop when it is lifted. Pass in the string representation of the key, e.g., 'a' for the A key or ' ' for the spacebar. show_finished_button bool true Whether to show the button that ends the trial. finished_button_label string \"Finished\" The label for the button that ends the trial. show_clear_button bool true Whether to show the button that clears the entire drawing. clear_button_label string \"Clear\" The label for the button that clears the entire drawing. show_undo_button bool true Whether to show the button that enables an undo action. undo_button_label string \"Undo\" The label for the button that enables an undo action. show_redo_button bool true Whether to show the button that enables a redo action. Note that show_undo_button must be true for the redo button to show up. redo_button_label string \"Redo\" The label for the button that enables a redo action. choices array of keys \"NO_KEYS\" This array contains the key(s) that the participant is allowed to press in order to end the trial. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"NO_KEYS\" means that no keys will be accepted as valid responses. Specifying \"ALL_KEYS\" will mean that all responses are allowed. trial_duration int null Length of time before the trial ends. If null the trial will continue indefinitely (until another way of ending the trial occurs). show_countdown_trial_duration bool false Whether to show a timer that counts down until the end of the trial when trial_duration is not null . countdown_timer_html string '<span id=\"sketchpad-timer\"></span> remaining' The HTML to use for rendering the countdown timer. The element with id=\"sketchpad-timer\" will have its content replaced by a countdown timer in the format MM:SS . Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt int The length of time from the start of the trial to the end of the trial. response string If the trial was ended by clicking the finished button, then \"button\" . If the trial was ended by pressing a key, then the key that was pressed. If the trial timed out, then null . png base64 data URL string If save_final_image is true, then this will contain the base64 encoded data URL for the image, in png format. strokes array of stroke objects If save_strokes is true, then this will contain an array of stroke objects. Objects have an action property that is either \"start\" , \"move\" , or \"end\" . If action is \"start\" or \"move\" it will have an x and y property that report the coordinates of the action relative to the upper-left corner of the canvas. If action is \"start\" then the object will also have a t and color property, specifying the time of the action relative to the onset of the trial (ms) and the color of the stroke. If action is \"end\" then it will only have a t property. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-sketchpad@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-sketchpad.js\" >< /script> Using NPM: npm install @jspsych/plugin-sketchpad import sketchpad from '@jspsych/plugin-sketchpad' ; Examples \u00b6 Basic sketchpad with a prompt Code Demo var trial = { type : jsPsychSketchpad , prompt : '<p>Draw an apple!</p>' , prompt_location : 'abovecanvas' , canvas_width : 300 , canvas_height : 300 , canvas_border_width : 2 } Open demo in new tab Image segmentation with different colors Code Demo var trial = { type : jsPsychSketchpad , prompt : '<p style=\"width:380px\">Circle the mouth using red. Circle the eyes using blue.</p>' , prompt_location : 'abovecanvas' , stroke_color_palette : [ 'red' , 'blue' ], stroke_color : 'red' , background_image : 'img/sad_face_4.jpg' , canvas_width : 380 , canvas_height : 252 } Open demo in new tab Draw an image in a time limit, then display the image and ask for a label. Code Demo var draw = { type : jsPsychSketchpad , prompt : '<p>Draw the first animal that comes to mind. You have 30 seconds!</p>' , prompt_location : 'belowcanvas' , trial_duration : 30000 , show_countdown_trial_duration : true , } var label = { type : jsPsychSurveyText , preamble : () => { var imageData = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. png ; return `<img src=\" ${ imageData } \"></img>` ; }, questions : [ { prompt : 'What animal did you draw?' } ] } Open demo in new tab","title":"sketchpad"},{"location":"plugins/sketchpad/#sketchpad","text":"Current version: 1.0.3. See version history . This plugin creates an interactive canvas that the participant can draw on using their mouse or touchscreen. It can be used for sketching tasks, like asking the participant to draw a particular object. It can also be used for some image segmentation or annotation tasks by setting the background_image parameter to render an image on the canvas. The plugin stores a base 64 data URL representation of the final image. This can be converted to an image file using online tools or short programs in R , python , or another language of your choice. It also records all of the individual strokes that the participant made during the trial. Warning This plugin generates a lot of data. Each trial can easily add 500kb+ of data to a final JSON output. You can reduce the amount of data generated by turning off storage of the individual stroke data ( save_strokes: false ) or storage of the final image ( save_final_image: false ) if your use case doesn't require that information. If you are going to be collecting a lot of data with this plugin you may want to save your data to your server after each trial and not wait until the end of the experiment to perform a single bulk upload. You can do this by putting data saving code inside the on_data_update event handler .","title":"sketchpad"},{"location":"plugins/sketchpad/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameter Type Default Value Description canvas_shape \"rectangle\" or \"circle\" \"rectangle\" The shape of the canvas element. canvas_width int 500 Width of the canvas in pixels when canvas_shape is a \"rectangle\" . canvas_height int 500 Height of the canvas in pixels when canvas_shape is a \"rectangle\" . canvas_diameter int 500 Diameter of the canvas in pixels when canvas_shape is a \"circle\" . canvas_border_width int 0 Width of the canvas border. canvas_border_color string \"#000\" Color of the canvas border. background_image image path null Path to an image to render as the background of the canvas. background_color string \"#fff\" Color of the canvas background. Note that a background_image will render on top of the color. stroke_width int 2 Width of the stroke on the canvas. stroke_color string \"#000\" Color of the stroke on the canvas. stroke_color_palette array of strings [] Array of colors to render as a palette of choices for stroke color. Clicking on the corresponding color button will change the stroke color. prompt string null HTML content to render on the screen. prompt_location \"abovecanvas\" or \"belowcanvas\" or \"belowbutton\" \"abovecanvas\" The location to render the prompt content. save_final_image bool true Whether to save the final image in the data as a base64 encoded data URL. save_strokes bool true Whether to save the individual stroke data that generated the final image. key_to_draw key string null If this key is held down then it is like the mouse button being held down. The \"ink\" will flow when the button is held and stop when it is lifted. Pass in the string representation of the key, e.g., 'a' for the A key or ' ' for the spacebar. show_finished_button bool true Whether to show the button that ends the trial. finished_button_label string \"Finished\" The label for the button that ends the trial. show_clear_button bool true Whether to show the button that clears the entire drawing. clear_button_label string \"Clear\" The label for the button that clears the entire drawing. show_undo_button bool true Whether to show the button that enables an undo action. undo_button_label string \"Undo\" The label for the button that enables an undo action. show_redo_button bool true Whether to show the button that enables a redo action. Note that show_undo_button must be true for the redo button to show up. redo_button_label string \"Redo\" The label for the button that enables a redo action. choices array of keys \"NO_KEYS\" This array contains the key(s) that the participant is allowed to press in order to end the trial. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"NO_KEYS\" means that no keys will be accepted as valid responses. Specifying \"ALL_KEYS\" will mean that all responses are allowed. trial_duration int null Length of time before the trial ends. If null the trial will continue indefinitely (until another way of ending the trial occurs). show_countdown_trial_duration bool false Whether to show a timer that counts down until the end of the trial when trial_duration is not null . countdown_timer_html string '<span id=\"sketchpad-timer\"></span> remaining' The HTML to use for rendering the countdown timer. The element with id=\"sketchpad-timer\" will have its content replaced by a countdown timer in the format MM:SS .","title":"Parameters"},{"location":"plugins/sketchpad/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt int The length of time from the start of the trial to the end of the trial. response string If the trial was ended by clicking the finished button, then \"button\" . If the trial was ended by pressing a key, then the key that was pressed. If the trial timed out, then null . png base64 data URL string If save_final_image is true, then this will contain the base64 encoded data URL for the image, in png format. strokes array of stroke objects If save_strokes is true, then this will contain an array of stroke objects. Objects have an action property that is either \"start\" , \"move\" , or \"end\" . If action is \"start\" or \"move\" it will have an x and y property that report the coordinates of the action relative to the upper-left corner of the canvas. If action is \"start\" then the object will also have a t and color property, specifying the time of the action relative to the onset of the trial (ms) and the color of the stroke. If action is \"end\" then it will only have a t property.","title":"Data Generated"},{"location":"plugins/sketchpad/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/sketchpad/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-sketchpad@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-sketchpad.js\" >< /script> Using NPM: npm install @jspsych/plugin-sketchpad import sketchpad from '@jspsych/plugin-sketchpad' ;","title":"Install"},{"location":"plugins/sketchpad/#examples","text":"Basic sketchpad with a prompt Code Demo var trial = { type : jsPsychSketchpad , prompt : '<p>Draw an apple!</p>' , prompt_location : 'abovecanvas' , canvas_width : 300 , canvas_height : 300 , canvas_border_width : 2 } Open demo in new tab Image segmentation with different colors Code Demo var trial = { type : jsPsychSketchpad , prompt : '<p style=\"width:380px\">Circle the mouth using red. Circle the eyes using blue.</p>' , prompt_location : 'abovecanvas' , stroke_color_palette : [ 'red' , 'blue' ], stroke_color : 'red' , background_image : 'img/sad_face_4.jpg' , canvas_width : 380 , canvas_height : 252 } Open demo in new tab Draw an image in a time limit, then display the image and ask for a label. Code Demo var draw = { type : jsPsychSketchpad , prompt : '<p>Draw the first animal that comes to mind. You have 30 seconds!</p>' , prompt_location : 'belowcanvas' , trial_duration : 30000 , show_countdown_trial_duration : true , } var label = { type : jsPsychSurveyText , preamble : () => { var imageData = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. png ; return `<img src=\" ${ imageData } \"></img>` ; }, questions : [ { prompt : 'What animal did you draw?' } ] } Open demo in new tab","title":"Examples"},{"location":"plugins/survey-html-form/","text":"survey-html-form \u00b6 Current version: 1.0.2. See version history . The survey-html-form plugin displays a set of <inputs> from a HTML string. The type of input can be freely chosen, for a list of possible input types see the MDN page on inputs . The participant provides answers to the input fields. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description html string undefined HTML formatted string containing all the input elements to display. Every element has to have its own distinctive name attribute. The <form> tag must not be included and is generated by the plugin. This string can contain other HTML elements besides the input fields. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' The text that appears on the button to finish the trial. dataAsArray boolean false Retrieve the data as an array e.g. [{name: \"INPUT_NAME\", value: \"INPUT_VALUE\"}, ...] instead of an object e.g. {INPUT_NAME: INPUT_VALUE, ...}. This might be useful if you omit naming your inputs. autofocus string empty string The HTML element ID of a form field to autofocus on. The focused element is the element that will receive keyboard events. For elements like <input type=\"text\"> or <textbox> , autofocus means that the cursor will appear in the text input area when the trial loads. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each input. The object will have a separate key (variable) for the response to each input, with each variable being named after its corresponding input element. Each response is a string containing whatever the participant answered for this particular input. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-html-form.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-html-form import surveyHtmlForm from '@jspsych/plugin-survey-html-form' ; Examples \u00b6 Fill in the blanks Code Demo var trial = { type : jsPsychSurveyHtmlForm , preamble : '<p>How are you feeling <b>right now?</b></p>' , html : '<p> I am feeling <input name=\"first\" type=\"text\" />, <input name=\"second\" type=\"text\" />, and <input name=\"third\" type=\"text\" />.</p>' }; Open demo in new tab Using the autofocus parameter Code Demo var trial = { type : jsPsychSurveyHtmlForm , preamble : '<p>What is your favorite bird?</p>' , html : '<p>My favorite bird is <input type=\"text\" id=\"test-resp-box\" name=\"response\" size=\"10\" /></p>' , autofocus : 'test-resp-box' }; In this example, the browser will focus on the element with the ID test-resp-box when the trial loads. For <input type=\"text\"> elements, this means that the cursor will appear inside the text box. Open demo in new tab","title":"survey-html-form"},{"location":"plugins/survey-html-form/#survey-html-form","text":"Current version: 1.0.2. See version history . The survey-html-form plugin displays a set of <inputs> from a HTML string. The type of input can be freely chosen, for a list of possible input types see the MDN page on inputs . The participant provides answers to the input fields.","title":"survey-html-form"},{"location":"plugins/survey-html-form/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description html string undefined HTML formatted string containing all the input elements to display. Every element has to have its own distinctive name attribute. The <form> tag must not be included and is generated by the plugin. This string can contain other HTML elements besides the input fields. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' The text that appears on the button to finish the trial. dataAsArray boolean false Retrieve the data as an array e.g. [{name: \"INPUT_NAME\", value: \"INPUT_VALUE\"}, ...] instead of an object e.g. {INPUT_NAME: INPUT_VALUE, ...}. This might be useful if you omit naming your inputs. autofocus string empty string The HTML element ID of a form field to autofocus on. The focused element is the element that will receive keyboard events. For elements like <input type=\"text\"> or <textbox> , autofocus means that the cursor will appear in the text input area when the trial loads. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-html-form/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each input. The object will have a separate key (variable) for the response to each input, with each variable being named after its corresponding input element. Each response is a string containing whatever the participant answered for this particular input. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response.","title":"Data Generated"},{"location":"plugins/survey-html-form/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/survey-html-form/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-html-form.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-html-form import surveyHtmlForm from '@jspsych/plugin-survey-html-form' ;","title":"Install"},{"location":"plugins/survey-html-form/#examples","text":"Fill in the blanks Code Demo var trial = { type : jsPsychSurveyHtmlForm , preamble : '<p>How are you feeling <b>right now?</b></p>' , html : '<p> I am feeling <input name=\"first\" type=\"text\" />, <input name=\"second\" type=\"text\" />, and <input name=\"third\" type=\"text\" />.</p>' }; Open demo in new tab Using the autofocus parameter Code Demo var trial = { type : jsPsychSurveyHtmlForm , preamble : '<p>What is your favorite bird?</p>' , html : '<p>My favorite bird is <input type=\"text\" id=\"test-resp-box\" name=\"response\" size=\"10\" /></p>' , autofocus : 'test-resp-box' }; In this example, the browser will focus on the element with the ID test-resp-box when the trial loads. For <input type=\"text\"> elements, this means that the cursor will appear inside the text box. Open demo in new tab","title":"Examples"},{"location":"plugins/survey-likert/","text":"survey-likert \u00b6 Current version: 1.1.2. See version history . The survey-likert plugin displays a set of questions with Likert scale responses. The participant responds by selecting a radio button. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, labels and required parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value is undefined . The strings are the question that will be associated with a slider. labels : Type array, default value is undefined . Each array element is an array of strings. The innermost arrays contain a set of labels to display for an individual question. If you want to use blank responses and only label the end points or some subset of the options, just insert a blank string for the unlabeled responses. required : Type boolean, default value is false. Makes answering questions required. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. scale_width numeric null The width of the likert scale in pixels. If left null , then the width of the scale will be equal to the width of the widest content on the page. button_label string 'Continue' Label of the button. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. The responses are recorded as integers, representing the position selected on the likert scale for that question. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-likert@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-likert.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-likert import surveyLikert from '@jspsych/plugin-survey-likert' ; Examples \u00b6 Single Question Code Demo var trial = { type : jsPsychSurveyLikert , questions : [ { prompt : \"I like vegetables.\" , labels : [ \"Strongly Disagree\" , \"Disagree\" , \"Neutral\" , \"Agree\" , \"Strongly Agree\" ] } ] }; Open demo in new tab Multiple questions in a random order Code Demo var likert_scale = [ \"Strongly Disagree\" , \"Disagree\" , \"Neutral\" , \"Agree\" , \"Strongly Agree\" ]; var trial = { type : jsPsychSurveyLikert , questions : [ { prompt : \"I like vegetables.\" , name : 'Vegetables' , labels : likert_scale }, { prompt : \"I like fruit.\" , name : 'Fruit' , labels : likert_scale }, { prompt : \"I like meat.\" , name : 'Meat' , labels : likert_scale }, ], randomize_question_order : true }; Open demo in new tab","title":"survey-likert"},{"location":"plugins/survey-likert/#survey-likert","text":"Current version: 1.1.2. See version history . The survey-likert plugin displays a set of questions with Likert scale responses. The participant responds by selecting a radio button.","title":"survey-likert"},{"location":"plugins/survey-likert/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, labels and required parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value is undefined . The strings are the question that will be associated with a slider. labels : Type array, default value is undefined . Each array element is an array of strings. The innermost arrays contain a set of labels to display for an individual question. If you want to use blank responses and only label the end points or some subset of the options, just insert a blank string for the unlabeled responses. required : Type boolean, default value is false. Makes answering questions required. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. scale_width numeric null The width of the likert scale in pixels. If left null , then the width of the scale will be equal to the width of the widest content on the page. button_label string 'Continue' Label of the button. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-likert/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. The responses are recorded as integers, representing the position selected on the likert scale for that question. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/survey-likert/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-likert@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-likert.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-likert import surveyLikert from '@jspsych/plugin-survey-likert' ;","title":"Install"},{"location":"plugins/survey-likert/#examples","text":"Single Question Code Demo var trial = { type : jsPsychSurveyLikert , questions : [ { prompt : \"I like vegetables.\" , labels : [ \"Strongly Disagree\" , \"Disagree\" , \"Neutral\" , \"Agree\" , \"Strongly Agree\" ] } ] }; Open demo in new tab Multiple questions in a random order Code Demo var likert_scale = [ \"Strongly Disagree\" , \"Disagree\" , \"Neutral\" , \"Agree\" , \"Strongly Agree\" ]; var trial = { type : jsPsychSurveyLikert , questions : [ { prompt : \"I like vegetables.\" , name : 'Vegetables' , labels : likert_scale }, { prompt : \"I like fruit.\" , name : 'Fruit' , labels : likert_scale }, { prompt : \"I like meat.\" , name : 'Meat' , labels : likert_scale }, ], randomize_question_order : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/survey-multi-choice/","text":"survey-multi-choice \u00b6 Current version: 1.1.2. See version history . The survey-multi-choice plugin displays a set of questions with multiple choice response fields. The participant selects a single answer. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, options, required, and horizontal parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value is undefined . The string is prompt/question that will be associated with a group of options (radio buttons). All questions will get presented on the same page (trial). options : Type array, defualt value is undefined . An array of strings. The array contains a set of options to display for an individual question. required : Type boolean, default value is null. The boolean value indicates if a question is required('true') or not ('false'), using the HTML5 required attribute. If this parameter is undefined, the question will be optional. horizontal :Type boolean, default value is false. If true, then the question is centered and the options are displayed horizontally. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' Label of the button. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. The responses are recorded as the name of the option label selected (string). If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-multi-choice.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-multi-choice import surveyMultiChoice from '@jspsych/plugin-survey-multi-choice' ; Examples \u00b6 Vertical Question Alignment Code Demo var trial = { type : jsPsychSurveyMultiChoice , questions : [ { prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true }, { prompt : \"Which of the following do you like the least?\" , name : 'FruitDislike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false } ], }; Open demo in new tab Horizontal Question Alignment Code Demo var trial = { type : jsPsychSurveyMultiChoice , questions : [ { prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true , horizontal : true }, { prompt : \"Which of the following do you like the least?\" , name : 'FruitDislike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false , horizontal : true } ], }; Open demo in new tab","title":"survey-multi-choice"},{"location":"plugins/survey-multi-choice/#survey-multi-choice","text":"Current version: 1.1.2. See version history . The survey-multi-choice plugin displays a set of questions with multiple choice response fields. The participant selects a single answer.","title":"survey-multi-choice"},{"location":"plugins/survey-multi-choice/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, options, required, and horizontal parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value is undefined . The string is prompt/question that will be associated with a group of options (radio buttons). All questions will get presented on the same page (trial). options : Type array, defualt value is undefined . An array of strings. The array contains a set of options to display for an individual question. required : Type boolean, default value is null. The boolean value indicates if a question is required('true') or not ('false'), using the HTML5 required attribute. If this parameter is undefined, the question will be optional. horizontal :Type boolean, default value is false. If true, then the question is centered and the options are displayed horizontally. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' Label of the button. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-multi-choice/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. The responses are recorded as the name of the option label selected (string). If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/survey-multi-choice/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-multi-choice.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-multi-choice import surveyMultiChoice from '@jspsych/plugin-survey-multi-choice' ;","title":"Install"},{"location":"plugins/survey-multi-choice/#examples","text":"Vertical Question Alignment Code Demo var trial = { type : jsPsychSurveyMultiChoice , questions : [ { prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true }, { prompt : \"Which of the following do you like the least?\" , name : 'FruitDislike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false } ], }; Open demo in new tab Horizontal Question Alignment Code Demo var trial = { type : jsPsychSurveyMultiChoice , questions : [ { prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true , horizontal : true }, { prompt : \"Which of the following do you like the least?\" , name : 'FruitDislike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false , horizontal : true } ], }; Open demo in new tab","title":"Examples"},{"location":"plugins/survey-multi-select/","text":"survey-multi-select \u00b6 Current version: 1.1.2. See version history . The survey-multi-select plugin displays a set of questions with multiple select response fields. The participant can select multiple answers. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, options and horizontal parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value of undefined . The string is the prompt/question that will be associated with a group of options (check boxes). All questions will get presented on the same page (trial). options : Type array, default value of undefined . The array contains a set of options to display for an individual question. horizontal : Type boolean, default value of false. If true, the questions are centered and options are displayed horizontally. required : Type boolean, default value of true. If true, then at least one option must be selected. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' Label of the button. required_message string 'You must choose at least one response for this question' Message to display if required response is not given. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. For each question, the responses are recorded as arrays containing any response options that were selected (strings). If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) were submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-multi-select@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-multi-select.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-multi-select import surveyMultiSelect from '@jspsych/plugin-survey-multi-select' ; Examples \u00b6 Multiple Questions on a Page Code Demo var trial = { type : jsPsychSurveyMultiSelect , questions : [ { prompt : \"Which of these colors do you like?\" , options : [ \"Red\" , \"Yellow\" , \"Green\" , \"Blue\" , \"Black\" ], horizontal : true , required : true , name : 'Colors' }, { prompt : \"Which of these foods do you like?\" , options : [ \"Apples\" , \"Bananas\" , \"Carrots\" , \"Donuts\" , \"Eggplant\" ], horizontal : true , required : true , name : 'Foods' } ], randomize_question_order : true }; Open demo in new tab","title":"survey-multi-select"},{"location":"plugins/survey-multi-select/#survey-multi-select","text":"Current version: 1.1.2. See version history . The survey-multi-select plugin displays a set of questions with multiple select response fields. The participant can select multiple answers.","title":"survey-multi-select"},{"location":"plugins/survey-multi-select/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, options and horizontal parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value of undefined . The string is the prompt/question that will be associated with a group of options (check boxes). All questions will get presented on the same page (trial). options : Type array, default value of undefined . The array contains a set of options to display for an individual question. horizontal : Type boolean, default value of false. If true, the questions are centered and options are displayed horizontally. required : Type boolean, default value of true. If true, then at least one option must be selected. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' Label of the button. required_message string 'You must choose at least one response for this question' Message to display if required response is not given. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-multi-select/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. For each question, the responses are recorded as arrays containing any response options that were selected (strings). If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) were submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/survey-multi-select/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-multi-select@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-multi-select.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-multi-select import surveyMultiSelect from '@jspsych/plugin-survey-multi-select' ;","title":"Install"},{"location":"plugins/survey-multi-select/#examples","text":"Multiple Questions on a Page Code Demo var trial = { type : jsPsychSurveyMultiSelect , questions : [ { prompt : \"Which of these colors do you like?\" , options : [ \"Red\" , \"Yellow\" , \"Green\" , \"Blue\" , \"Black\" ], horizontal : true , required : true , name : 'Colors' }, { prompt : \"Which of these foods do you like?\" , options : [ \"Apples\" , \"Bananas\" , \"Carrots\" , \"Donuts\" , \"Eggplant\" ], horizontal : true , required : true , name : 'Foods' } ], randomize_question_order : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/survey-text/","text":"survey-text \u00b6 Current version: 1.1.2. See version history . The survey-text plugin displays a set of questions with free response text fields. The participant types in answers. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, placeholder, required, rows, and columns parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value of undefined . The string is the prompt for the participant to respond to. Each question gets its own response field. placeholder : Type string, default value of \"\" . The string will create placeholder text in the text field. required : Boolean; if true then the user must enter a response to submit. rows : Type integer, default value of 1. The number of rows for the response text box. columns : Type integer, default value of 40. The number of columns for the response text box. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' The text that appears on the button to finish the trial. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. For each question, the response is a string containing whatever text was in the response box when the responses were submitted. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) were submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-text@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-text.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-text import surveyText from '@jspsych/plugin-survey-text' ; Examples \u00b6 Single question and response Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'How old are you?' } ] } Open demo in new tab Multiple questions, with an optional placeholder and a required question Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'What is your date of birth?' , placeholder : 'mm/dd/yyyy' , required : true }, { prompt : 'What country do you currently live in?' } ] } Open demo in new tab Naming questions to improve readability of the stored data Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'What did you eat for breakfast?' , name : 'Breakfast' }, { prompt : 'What did you eat for lunch?' , name : 'Lunch' } ] } Open demo in new tab Using the preamble and a longer textbox response Code Demo var trial = { type : jsPsychSurveyText , preamble : `<img src=\"img/navarro_burst_03.jpg\" style=\"width:400px;\"></img>` , questions : [ { prompt : 'Describe your reaction to the image above' , rows : 5 } ] } The artwork in this demo is by Danielle Navarro Open demo in new tab","title":"survey-text"},{"location":"plugins/survey-text/#survey-text","text":"Current version: 1.1.2. See version history . The survey-text plugin displays a set of questions with free response text fields. The participant types in answers.","title":"survey-text"},{"location":"plugins/survey-text/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, placeholder, required, rows, and columns parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value of undefined . The string is the prompt for the participant to respond to. Each question gets its own response field. placeholder : Type string, default value of \"\" . The string will create placeholder text in the text field. required : Boolean; if true then the user must enter a response to submit. rows : Type integer, default value of 1. The number of rows for the response text box. columns : Type integer, default value of 40. The number of columns for the response text box. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' The text that appears on the button to finish the trial. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-text/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. For each question, the response is a string containing whatever text was in the response box when the responses were submitted. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) were submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/survey-text/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-text@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-text.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-text import surveyText from '@jspsych/plugin-survey-text' ;","title":"Install"},{"location":"plugins/survey-text/#examples","text":"Single question and response Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'How old are you?' } ] } Open demo in new tab Multiple questions, with an optional placeholder and a required question Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'What is your date of birth?' , placeholder : 'mm/dd/yyyy' , required : true }, { prompt : 'What country do you currently live in?' } ] } Open demo in new tab Naming questions to improve readability of the stored data Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'What did you eat for breakfast?' , name : 'Breakfast' }, { prompt : 'What did you eat for lunch?' , name : 'Lunch' } ] } Open demo in new tab Using the preamble and a longer textbox response Code Demo var trial = { type : jsPsychSurveyText , preamble : `<img src=\"img/navarro_burst_03.jpg\" style=\"width:400px;\"></img>` , questions : [ { prompt : 'Describe your reaction to the image above' , rows : 5 } ] } The artwork in this demo is by Danielle Navarro Open demo in new tab","title":"Examples"},{"location":"plugins/survey/","text":"survey \u00b6 Current version: 0.2.1. See version history . The survey plugin displays one or more questions of different types, on one or more pages that the participant can navigate. This plugin is built on top of the SurveyJS library. The supported question types are: \"drop-down\" for presenting a question with a limited set of options in a drop-down menu. The participant can only select one option. \"likert\" for presenting a prompt along with a discrete rating scale. \"likert-table\" for presenting a prompt along with a table of statements/questions (rows) and repeated response options for each statement/question (columns). \"multi-choice\" for presenting a question with a limited set of options. The participant can only select one option. \"multi-select\" for presenting a question with a limited set of options. The participant can select multiple options. \"ranking\" for presenting a question with a limited set of options, where participants respond by dragging and dropping (ordering/ranking) the options. \"text\" for presenting a question with a free response text field in which the participant can type in an answer. There is also an \"html\" type for adding arbitrary HTML-formatted content (without any associated response field) in the question set. Warning Development on this plugin is ongoing and we plan to incorporate more of the features that SurveyJS provides. Prior to release of version 1.0 of the plugin, we expect the parameters and implementation of this plugin to change. We recommend performing a little bit of extra testing with any experiments that utilize this plugin. CSS \u00b6 This plugin uses an additional stylesheet called survey.css . You can load it via: < link rel = \"stylesheet\" href = \"https://unpkg.com/@jspsych/plugin-survey@0.2.1/css/survey.css\" > If you are using a bundler such as webpack , you can also import it in JavaScript as follows, depending on your bundler configuration: import '@jspsych/plugin-survey/css/survey.css' Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Survey parameters \u00b6 Parameter Type Default Value Description pages array undefined An array of arrays. Each inner array contains the content for a single page, which is made up of one or more question objects. button_label_next string 'Continue' Label of the button to move forward to the next page, or finish the survey. button_label_back string 'Back' Label of the button to move to a previous page in the survey. button_label_finish string 'Finish' Label of the button to submit responses. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. show_question_numbers string \"off\" One of: \"on\", \"onPage\", \"off\". If \"on\", questions will be labelled starting with \"1.\" on the first page, and numbering will continue across pages. If \"onPage\", questions will be labelled starting with \"1.\", with separate numbering on each page. If \"off\", no numbers will be added before the question prompts. Note: HTML question types are ignored in automatic numbering. title string null If specified, this text will be shown at the top of the survey pages. required_error string \"Please answer the question.\" Text to display if a required question is not responeded to. required_question_label string \"*\" String to display at the end of required questions. Use an empty string (\"\") if you do not want to add a label to the end of required questions. Question types and parameters \u00b6 Parameters for all question types \u00b6 Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description type string undefined The question type. Options are: \"drop-down\", \"html\", \"likert\", \"likert-table\", \"multi-choice\", \"multi-select\", \"ranking\", \"rating\", \"text\". prompt string undefined The prompt/question that will be associated with the question's response field. If the question type is \"html\", then this string is the HTML-formatted string to be displayed. If the question type is \"likert-table\", the prompt is a general question or title presented above the table. required boolean false Whether a response to the question is required ( true ) or not ( false ), using the HTML5 required attribute. name string null Name of the question to be used for storing data. If this parameter is not provided, then default names will be used to identify the questions in the data: P0_Q0 , P0_Q1 , P1_Q0 etc. Question names must be unique across all pages within the trial. Drop-down \u00b6 Present a question with a limited set of options in a drop-down menu. The participant can only select one option. In addition to the parameters for all question types, the drop-down question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of multiple choice options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. correct_response string null String from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ). HTML \u00b6 Present arbitrary HTML-formatted content embedded in the list of questions, including text, images, and sounds. There are no response options. The only available parameters are those listed for all question types with a default value of undefined ( type and prompt ) and name . The name parameter is optional and used to identify the question in the data, with a response value of null . The required parameter will be ignored. Likert \u00b6 Present a prompt along with a discrete rating scale. The scale values are presented as buttons that can be selected and de-selected. The scale is specified by the likert_scale_values parameter, which is an array of text labels and associated values, or it is generated using the likert_rating_min / max / stepsize parameters (along with optional maximum/minimum descriptions). In addition to the parameters for all question types, the likert question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description likert_scale_values array of objects null Array of objects that defines the rating scale labels and associated values to be stored in the data. Each object defines a single rating option. The objects must have a value property, which is an integer or string value that will be stored as the response in the data. The objects can optionally have a text property, which is a string that will be displayed for that rating option (example: [{value: 1, text: \"A lot\"},{value: 2, text: \"Somewhat\"},{value: 3, text: \"Not much\"}] ). If no text property is specified then the value will be displayed (examples: [{value: 1},{value: 2},{value: 3}] , [{value: \"Yes\"},{value: \"Maybe\"},{value: \"No\"}] ). If provided, this parameter will override the likert_rating_min / max / stepsize parameters. likert_scale_min integer 1 If the likert_scale_values array is not specified, then this parameter will define the minimum scale value. likert_scale_max integer 5 If the likert_scale_values array is not specified, then this parameter will define the maximum scale value. likert_scale_stepsize integer 1 If the likert_scale_values array is not specified, then this parameter will define the step size that should be used for generating rating options between the minimum and maximum values. likert_scale_min_label string null Description for the minimum (first) rating option. If provided, this text will be shown inside the first rating button, before the rating text/value. This parameter is meant for defining the scale's minimum when integer values are used for the rating scale buttons. likert_scale_max_label string null Description for the maximum (last) rating option. If provided, this text will be shown inside the first rating button, after the rating text/value. This parameter is meant for defining the scale's maximum when integer values are used for the rating scale buttons. Likert-table \u00b6 Present a prompt along with a table of statements/questions (rows) and repeated response options for each statement/question (columns). In addition to the parameters for all question types, the likert-table question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description statements array of objects undefined This array contains one or more objects representing the statements/questions to be presented in the table rows. Each object must have a prompt , which is the statement/question text. The objects can optionally include a name , which is how the statement should be identified in the data. If no name is provided, then the default values of \"S0\", \"S1\" etc. will be used. options array of strings undefined This array contains the set of multiple choice options to be presented in the table columns. randomize_statement_order boolean false If true , the order of statements/questions in the statements array will be randomized. Multi-choice \u00b6 Present a question with a limited set of options. The participant can only select one option. In addition to the parameters for all question types, the multi-choice question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of multiple choice options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. columns integer 1 Number of columns to use for displaying the options. If 1 (default), the choices will be displayed in a single column (vertically). If 0, choices will be displayed in a single row (horizontally). Any value greater than 1 can be used to display options in multiple columns. correct_response string null String from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ). Multi-select \u00b6 Present a question with a limited set of options. The participant can select multiple options. In addition to the parameters for all question types, the multi-select question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. columns integer 1 Number of columns to use for displaying the options. If 1 (default), the choices will be displayed in a single column (vertically). If 0, choices will be displayed in a single row (horizontally). Any value greater than 1 can be used to display options in multiple columns. correct_response array of strings null Array of one or more strings from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ). Ranking \u00b6 Present a question with a limited set of options, where participants respond by dragging and dropping (ordering/ranking) the options. It is ideally used with a short list of options (up to about 7 items). It supports mouse responses, touch responses (mobile devices), and keyboard responses (Tab and Shift-Tab to select, and Up/Down arrow keys to re-order). In addition to the parameters for all question types, the ranking question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of to-be-ranked options for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. correct_response array of strings null The same array of strings used for the options array, but listed in the order that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ). Text \u00b6 Present a question with a free response text field in which the participant can type in an answer. In addition to the parameters for all question types, the text question also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description placeholder string \"\" Placeholder text in the text response field. textbox_rows integer 1 The number of rows (height) for the response text box. textbox_columns integer 40 The number of columns (width) for the response text box. validation string \"\" A regular expression used to validate the response. input_type string \"text\" Type for the HTML <input> element. The input_type parameter must be one of \"color\", \"date\", \"datetime-local\", \"email\", \"month\", \"number\", \"password\", \"range\", \"tel\", \"text\", \"time\", \"url\", \"week\". If the textbox_rows parameter is larger than 1, the input_type parameter will be ignored. The textbox_columns parameter only affects questions with input_type \"email\", \"password\", \"tel\", \"url\", or \"text\". Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response to each question. The object will have a separate key (variable) for each question, with the first question on the first page being recorded in P0_Q0 , the second question on the first page in P0_Q1 , and so on. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. The response type will depend on the question type. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Note that, if any questions use the other option ( add_other_option: true ), then the response value will be the other_option_text (e.g. \"Other\") and any text written in the textbox will be saved as \"(question name)-Comment\". rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey@0.2.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey import survey from '@jspsych/plugin-survey' ; Examples \u00b6 Basic single page Code Demo var trial = { type : jsPsychSurvey , pages : [ [ { type : 'html' , prompt : 'Please answer the following questions:' , }, { type : 'multi-choice' , prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true }, { type : 'multi-select' , prompt : \"Which of the following do you like?\" , name : 'FruitLike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false , } ] ], }; Open demo in new tab Multiple pages, more customization Code Demo var trial = { type : jsPsychSurvey , pages : [ [ { type : 'text' , prompt : \"Where were you born?\" , placeholder : 'City, State, Country' , name : 'birthplace' , required : true , }, { type : 'text' , prompt : \"How old are you?\" , name : 'age' , textbox_columns : 5 , required : false , } ], [ { type : 'multi-choice' , prompt : \"What&#39;s your favorite color?\" , options : [ 'blue' , 'yellow' , 'pink' , 'teal' , 'orange' , 'lime green' , 'other' , 'none of these' ], name : 'FavColor' , }, { type : 'multi-select' , prompt : \"Which of these animals do you like? Select all that apply.\" , options : [ 'lion' , 'squirrel' , 'badger' , 'whale' ], option_reorder : 'random' , columns : 0 , name : 'AnimalLike' , } ] ], title : 'My questionnaire' , button_label_next : 'Continue' , button_label_back : 'Previous' , button_label_finish : 'Submit' , show_question_numbers : 'onPage' }; Open demo in new tab Single and multiple item Likert-style scales Code Demo const trial = { type : jsPsychSurvey , pages : [ [ { type : 'likert' , prompt : 'I like to eat vegetables.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, { type : 'likert' , prompt : 'I like to eat fruit.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, { type : 'likert' , prompt : 'I like to eat meat.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, ], [ { type : 'likert-table' , prompt : ' ' , statements : [ { prompt : 'I like to eat vegetables' , name : 'VeggiesTable' }, { prompt : 'I like to eat fruit' , name : 'FruitTable' }, { prompt : 'I like to eat meat' , name : 'MeatTable' }, ], options : [ 'Strongly Disagree' , 'Disagree' , 'Neutral' , 'Agree' , 'Strongly Agree' ], } ] ], }; Open demo in new tab Response scoring Code Demo const trial = { type : jsPsychSurvey , pages : [ [ { type : 'multi-choice' , prompt : 'During the experiment, are allowed to write things down on paper to help you?' , options : [ \"Yes\" , \"No\" ], correct_response : \"No\" , required : true }, ] ], }; Open demo in new tab Adding data to trial When adding any data to a Survey trial, you should add it via the data parameter at the whole-trial level (not inside the question objects), even if it only relates to one question out of multiple questions/pages contained wihtin the trial. Code Demo const question_info = [ { 'fruit' : 'apples' , 'Q1_prompt' : 'Do you like apples?' , 'Q1_type' : 'regular' }, { 'fruit' : 'bananas' , 'Q1_prompt' : 'Do you NOT like bananas?' , 'Q1_type' : 'reverse' }, ]; const survey = { type : jsPsychSurvey , pages : [ [ { type : 'multi-choice' , prompt : jsPsych . timelineVariable ( 'Q1_prompt' ), options : [ 'Yes' , 'No' ], name : 'Q1' }, { type : 'text' , prompt : function () { return `What's your favorite thing about ${ jsPsych . timelineVariable ( 'fruit' ) } ?` ; }, name : 'Q2' } ] ], // Add data at the whole-trial level here data : { 'Q1_prompt' : jsPsych . timelineVariable ( 'Q1_prompt' ), 'Q1_type' : jsPsych . timelineVariable ( 'Q1_type' ), 'fruit' : jsPsych . timelineVariable ( 'fruit' ) }, button_label_finish : 'Continue' }; const survey_procedure = { timeline : [ survey ], timeline_variables : question_info , randomize_order : true }; Open demo in new tab","title":"survey"},{"location":"plugins/survey/#survey","text":"Current version: 0.2.1. See version history . The survey plugin displays one or more questions of different types, on one or more pages that the participant can navigate. This plugin is built on top of the SurveyJS library. The supported question types are: \"drop-down\" for presenting a question with a limited set of options in a drop-down menu. The participant can only select one option. \"likert\" for presenting a prompt along with a discrete rating scale. \"likert-table\" for presenting a prompt along with a table of statements/questions (rows) and repeated response options for each statement/question (columns). \"multi-choice\" for presenting a question with a limited set of options. The participant can only select one option. \"multi-select\" for presenting a question with a limited set of options. The participant can select multiple options. \"ranking\" for presenting a question with a limited set of options, where participants respond by dragging and dropping (ordering/ranking) the options. \"text\" for presenting a question with a free response text field in which the participant can type in an answer. There is also an \"html\" type for adding arbitrary HTML-formatted content (without any associated response field) in the question set. Warning Development on this plugin is ongoing and we plan to incorporate more of the features that SurveyJS provides. Prior to release of version 1.0 of the plugin, we expect the parameters and implementation of this plugin to change. We recommend performing a little bit of extra testing with any experiments that utilize this plugin.","title":"survey"},{"location":"plugins/survey/#css","text":"This plugin uses an additional stylesheet called survey.css . You can load it via: < link rel = \"stylesheet\" href = \"https://unpkg.com/@jspsych/plugin-survey@0.2.1/css/survey.css\" > If you are using a bundler such as webpack , you can also import it in JavaScript as follows, depending on your bundler configuration: import '@jspsych/plugin-survey/css/survey.css'","title":"CSS"},{"location":"plugins/survey/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable.","title":"Parameters"},{"location":"plugins/survey/#survey-parameters","text":"Parameter Type Default Value Description pages array undefined An array of arrays. Each inner array contains the content for a single page, which is made up of one or more question objects. button_label_next string 'Continue' Label of the button to move forward to the next page, or finish the survey. button_label_back string 'Back' Label of the button to move to a previous page in the survey. button_label_finish string 'Finish' Label of the button to submit responses. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. show_question_numbers string \"off\" One of: \"on\", \"onPage\", \"off\". If \"on\", questions will be labelled starting with \"1.\" on the first page, and numbering will continue across pages. If \"onPage\", questions will be labelled starting with \"1.\", with separate numbering on each page. If \"off\", no numbers will be added before the question prompts. Note: HTML question types are ignored in automatic numbering. title string null If specified, this text will be shown at the top of the survey pages. required_error string \"Please answer the question.\" Text to display if a required question is not responeded to. required_question_label string \"*\" String to display at the end of required questions. Use an empty string (\"\") if you do not want to add a label to the end of required questions.","title":"Survey parameters"},{"location":"plugins/survey/#question-types-and-parameters","text":"","title":"Question types and parameters"},{"location":"plugins/survey/#parameters-for-all-question-types","text":"Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description type string undefined The question type. Options are: \"drop-down\", \"html\", \"likert\", \"likert-table\", \"multi-choice\", \"multi-select\", \"ranking\", \"rating\", \"text\". prompt string undefined The prompt/question that will be associated with the question's response field. If the question type is \"html\", then this string is the HTML-formatted string to be displayed. If the question type is \"likert-table\", the prompt is a general question or title presented above the table. required boolean false Whether a response to the question is required ( true ) or not ( false ), using the HTML5 required attribute. name string null Name of the question to be used for storing data. If this parameter is not provided, then default names will be used to identify the questions in the data: P0_Q0 , P0_Q1 , P1_Q0 etc. Question names must be unique across all pages within the trial.","title":"Parameters for all question types"},{"location":"plugins/survey/#drop-down","text":"Present a question with a limited set of options in a drop-down menu. The participant can only select one option. In addition to the parameters for all question types, the drop-down question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of multiple choice options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. correct_response string null String from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ).","title":"Drop-down"},{"location":"plugins/survey/#html","text":"Present arbitrary HTML-formatted content embedded in the list of questions, including text, images, and sounds. There are no response options. The only available parameters are those listed for all question types with a default value of undefined ( type and prompt ) and name . The name parameter is optional and used to identify the question in the data, with a response value of null . The required parameter will be ignored.","title":"HTML"},{"location":"plugins/survey/#likert","text":"Present a prompt along with a discrete rating scale. The scale values are presented as buttons that can be selected and de-selected. The scale is specified by the likert_scale_values parameter, which is an array of text labels and associated values, or it is generated using the likert_rating_min / max / stepsize parameters (along with optional maximum/minimum descriptions). In addition to the parameters for all question types, the likert question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description likert_scale_values array of objects null Array of objects that defines the rating scale labels and associated values to be stored in the data. Each object defines a single rating option. The objects must have a value property, which is an integer or string value that will be stored as the response in the data. The objects can optionally have a text property, which is a string that will be displayed for that rating option (example: [{value: 1, text: \"A lot\"},{value: 2, text: \"Somewhat\"},{value: 3, text: \"Not much\"}] ). If no text property is specified then the value will be displayed (examples: [{value: 1},{value: 2},{value: 3}] , [{value: \"Yes\"},{value: \"Maybe\"},{value: \"No\"}] ). If provided, this parameter will override the likert_rating_min / max / stepsize parameters. likert_scale_min integer 1 If the likert_scale_values array is not specified, then this parameter will define the minimum scale value. likert_scale_max integer 5 If the likert_scale_values array is not specified, then this parameter will define the maximum scale value. likert_scale_stepsize integer 1 If the likert_scale_values array is not specified, then this parameter will define the step size that should be used for generating rating options between the minimum and maximum values. likert_scale_min_label string null Description for the minimum (first) rating option. If provided, this text will be shown inside the first rating button, before the rating text/value. This parameter is meant for defining the scale's minimum when integer values are used for the rating scale buttons. likert_scale_max_label string null Description for the maximum (last) rating option. If provided, this text will be shown inside the first rating button, after the rating text/value. This parameter is meant for defining the scale's maximum when integer values are used for the rating scale buttons.","title":"Likert"},{"location":"plugins/survey/#likert-table","text":"Present a prompt along with a table of statements/questions (rows) and repeated response options for each statement/question (columns). In addition to the parameters for all question types, the likert-table question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description statements array of objects undefined This array contains one or more objects representing the statements/questions to be presented in the table rows. Each object must have a prompt , which is the statement/question text. The objects can optionally include a name , which is how the statement should be identified in the data. If no name is provided, then the default values of \"S0\", \"S1\" etc. will be used. options array of strings undefined This array contains the set of multiple choice options to be presented in the table columns. randomize_statement_order boolean false If true , the order of statements/questions in the statements array will be randomized.","title":"Likert-table"},{"location":"plugins/survey/#multi-choice","text":"Present a question with a limited set of options. The participant can only select one option. In addition to the parameters for all question types, the multi-choice question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of multiple choice options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. columns integer 1 Number of columns to use for displaying the options. If 1 (default), the choices will be displayed in a single column (vertically). If 0, choices will be displayed in a single row (horizontally). Any value greater than 1 can be used to display options in multiple columns. correct_response string null String from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ).","title":"Multi-choice"},{"location":"plugins/survey/#multi-select","text":"Present a question with a limited set of options. The participant can select multiple options. In addition to the parameters for all question types, the multi-select question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. columns integer 1 Number of columns to use for displaying the options. If 1 (default), the choices will be displayed in a single column (vertically). If 0, choices will be displayed in a single row (horizontally). Any value greater than 1 can be used to display options in multiple columns. correct_response array of strings null Array of one or more strings from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ).","title":"Multi-select"},{"location":"plugins/survey/#ranking","text":"Present a question with a limited set of options, where participants respond by dragging and dropping (ordering/ranking) the options. It is ideally used with a short list of options (up to about 7 items). It supports mouse responses, touch responses (mobile devices), and keyboard responses (Tab and Shift-Tab to select, and Up/Down arrow keys to re-order). In addition to the parameters for all question types, the ranking question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of to-be-ranked options for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. correct_response array of strings null The same array of strings used for the options array, but listed in the order that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ).","title":"Ranking"},{"location":"plugins/survey/#text","text":"Present a question with a free response text field in which the participant can type in an answer. In addition to the parameters for all question types, the text question also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description placeholder string \"\" Placeholder text in the text response field. textbox_rows integer 1 The number of rows (height) for the response text box. textbox_columns integer 40 The number of columns (width) for the response text box. validation string \"\" A regular expression used to validate the response. input_type string \"text\" Type for the HTML <input> element. The input_type parameter must be one of \"color\", \"date\", \"datetime-local\", \"email\", \"month\", \"number\", \"password\", \"range\", \"tel\", \"text\", \"time\", \"url\", \"week\". If the textbox_rows parameter is larger than 1, the input_type parameter will be ignored. The textbox_columns parameter only affects questions with input_type \"email\", \"password\", \"tel\", \"url\", or \"text\".","title":"Text"},{"location":"plugins/survey/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response to each question. The object will have a separate key (variable) for each question, with the first question on the first page being recorded in P0_Q0 , the second question on the first page in P0_Q1 , and so on. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. The response type will depend on the question type. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Note that, if any questions use the other option ( add_other_option: true ), then the response value will be the other_option_text (e.g. \"Other\") and any text written in the textbox will be saved as \"(question name)-Comment\". rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted.","title":"Data Generated"},{"location":"plugins/survey/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/survey/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey@0.2.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey import survey from '@jspsych/plugin-survey' ;","title":"Install"},{"location":"plugins/survey/#examples","text":"Basic single page Code Demo var trial = { type : jsPsychSurvey , pages : [ [ { type : 'html' , prompt : 'Please answer the following questions:' , }, { type : 'multi-choice' , prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true }, { type : 'multi-select' , prompt : \"Which of the following do you like?\" , name : 'FruitLike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false , } ] ], }; Open demo in new tab Multiple pages, more customization Code Demo var trial = { type : jsPsychSurvey , pages : [ [ { type : 'text' , prompt : \"Where were you born?\" , placeholder : 'City, State, Country' , name : 'birthplace' , required : true , }, { type : 'text' , prompt : \"How old are you?\" , name : 'age' , textbox_columns : 5 , required : false , } ], [ { type : 'multi-choice' , prompt : \"What&#39;s your favorite color?\" , options : [ 'blue' , 'yellow' , 'pink' , 'teal' , 'orange' , 'lime green' , 'other' , 'none of these' ], name : 'FavColor' , }, { type : 'multi-select' , prompt : \"Which of these animals do you like? Select all that apply.\" , options : [ 'lion' , 'squirrel' , 'badger' , 'whale' ], option_reorder : 'random' , columns : 0 , name : 'AnimalLike' , } ] ], title : 'My questionnaire' , button_label_next : 'Continue' , button_label_back : 'Previous' , button_label_finish : 'Submit' , show_question_numbers : 'onPage' }; Open demo in new tab Single and multiple item Likert-style scales Code Demo const trial = { type : jsPsychSurvey , pages : [ [ { type : 'likert' , prompt : 'I like to eat vegetables.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, { type : 'likert' , prompt : 'I like to eat fruit.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, { type : 'likert' , prompt : 'I like to eat meat.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, ], [ { type : 'likert-table' , prompt : ' ' , statements : [ { prompt : 'I like to eat vegetables' , name : 'VeggiesTable' }, { prompt : 'I like to eat fruit' , name : 'FruitTable' }, { prompt : 'I like to eat meat' , name : 'MeatTable' }, ], options : [ 'Strongly Disagree' , 'Disagree' , 'Neutral' , 'Agree' , 'Strongly Agree' ], } ] ], }; Open demo in new tab Response scoring Code Demo const trial = { type : jsPsychSurvey , pages : [ [ { type : 'multi-choice' , prompt : 'During the experiment, are allowed to write things down on paper to help you?' , options : [ \"Yes\" , \"No\" ], correct_response : \"No\" , required : true }, ] ], }; Open demo in new tab Adding data to trial When adding any data to a Survey trial, you should add it via the data parameter at the whole-trial level (not inside the question objects), even if it only relates to one question out of multiple questions/pages contained wihtin the trial. Code Demo const question_info = [ { 'fruit' : 'apples' , 'Q1_prompt' : 'Do you like apples?' , 'Q1_type' : 'regular' }, { 'fruit' : 'bananas' , 'Q1_prompt' : 'Do you NOT like bananas?' , 'Q1_type' : 'reverse' }, ]; const survey = { type : jsPsychSurvey , pages : [ [ { type : 'multi-choice' , prompt : jsPsych . timelineVariable ( 'Q1_prompt' ), options : [ 'Yes' , 'No' ], name : 'Q1' }, { type : 'text' , prompt : function () { return `What's your favorite thing about ${ jsPsych . timelineVariable ( 'fruit' ) } ?` ; }, name : 'Q2' } ] ], // Add data at the whole-trial level here data : { 'Q1_prompt' : jsPsych . timelineVariable ( 'Q1_prompt' ), 'Q1_type' : jsPsych . timelineVariable ( 'Q1_type' ), 'fruit' : jsPsych . timelineVariable ( 'fruit' ) }, button_label_finish : 'Continue' }; const survey_procedure = { timeline : [ survey ], timeline_variables : question_info , randomize_order : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/video-button-response/","text":"video-button-response \u00b6 Current version: 1.1.2. See version history . This plugin plays a video and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the video has finished playing. The button itself can be customized using HTML formatting. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. choices array of strings undefined Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before the button choices are enabled and a response is accepted. Once the video has played all the way through, the buttons are enabled and a response is allowed (including while the video is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-button-response import videoButtonResponse from '@jspsych/plugin-video-button-response' ; Example \u00b6 Responses disabled until the video is complete Code Demo var trial = { type : jsPsychVideoButtonResponse , stimulus : [ 'video/fish.mp4' ], choices : [ '0-5' , '6-10' , '11-15' , '16-20' , '21-25' , '25+' ], prompt : \"<p>How many different fish are shown in the video?</p>\" , response_allowed_while_playing : false }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"video-button-response"},{"location":"plugins/video-button-response/#video-button-response","text":"Current version: 1.1.2. See version history . This plugin plays a video and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the video has finished playing. The button itself can be customized using HTML formatting. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information.","title":"video-button-response"},{"location":"plugins/video-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. choices array of strings undefined Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before the button choices are enabled and a response is accepted. Once the video has played all the way through, the buttons are enabled and a response is allowed (including while the video is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/video-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/video-button-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/video-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-button-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-button-response import videoButtonResponse from '@jspsych/plugin-video-button-response' ;","title":"Install"},{"location":"plugins/video-button-response/#example","text":"Responses disabled until the video is complete Code Demo var trial = { type : jsPsychVideoButtonResponse , stimulus : [ 'video/fish.mp4' ], choices : [ '0-5' , '6-10' , '11-15' , '16-20' , '21-25' , '25+' ], prompt : \"<p>How many different fish are shown in the video?</p>\" , response_allowed_while_playing : false }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"Example"},{"location":"plugins/video-keyboard-response/","text":"video-keyboard-response \u00b6 Current version: 1.1.2. See version history . This plugin plays a video file and records a keyboard response. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the video has finished playing. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before a keyboard response is accepted. Once the video has played all the way through, a valid keyboard response is allowed (including while the video is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-keyboard-response import videoKeyboardResponse from '@jspsych/plugin-video-keyboard-response' ; Examples \u00b6 Show a video and advance to next trial automatically Code Demo var trial = { type : jsPsychVideoKeyboardResponse , stimulus : [ 'video/fish.mp4' ], choices : \"NO_KEYS\" , trial_ends_after_video : true }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"video-keyboard-response"},{"location":"plugins/video-keyboard-response/#video-keyboard-response","text":"Current version: 1.1.2. See version history . This plugin plays a video file and records a keyboard response. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the video has finished playing. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information.","title":"video-keyboard-response"},{"location":"plugins/video-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before a keyboard response is accepted. Once the video has played all the way through, a valid keyboard response is allowed (including while the video is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/video-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/video-keyboard-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/video-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-keyboard-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-keyboard-response import videoKeyboardResponse from '@jspsych/plugin-video-keyboard-response' ;","title":"Install"},{"location":"plugins/video-keyboard-response/#examples","text":"Show a video and advance to next trial automatically Code Demo var trial = { type : jsPsychVideoKeyboardResponse , stimulus : [ 'video/fish.mp4' ], choices : \"NO_KEYS\" , trial_ends_after_video : true }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"Examples"},{"location":"plugins/video-slider-response/","text":"video-slider-response \u00b6 Current version: 1.1.2. See version history . This plugin plays a video and allows the participant to respond by dragging a slider. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the video has finished playing. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. button_label string 'Continue' Label of the button to end the trial. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before the slider is enabled and the trial can end via the next button click. Once the video has played all the way through, the slider is enabled and a response is allowed (including while the video is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. slider_start numeric The starting value of the slider. start numeric The start time of the video clip. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-slider-response import videoSliderResponse from '@jspsych/plugin-video-slider-response' ; Example \u00b6 Rate enjoyment of a video clip Code Demo var trial = { type : jsPsychVideoSliderResponse , stimulus : [ 'video/fish.mp4' ], labels : [ \"Hated it\" , \"Loved it\" ], prompt : '<p>Please rate your enjoyment of the video clip.</p>' }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"video-slider-response"},{"location":"plugins/video-slider-response/#video-slider-response","text":"Current version: 1.1.2. See version history . This plugin plays a video and allows the participant to respond by dragging a slider. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the video has finished playing. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information.","title":"video-slider-response"},{"location":"plugins/video-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. button_label string 'Continue' Label of the button to end the trial. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before the slider is enabled and the trial can end via the next button click. Once the video has played all the way through, the slider is enabled and a response is allowed (including while the video is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/video-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. slider_start numeric The starting value of the slider. start numeric The start time of the video clip.","title":"Data Generated"},{"location":"plugins/video-slider-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/video-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-slider-response@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-slider-response import videoSliderResponse from '@jspsych/plugin-video-slider-response' ;","title":"Install"},{"location":"plugins/video-slider-response/#example","text":"Rate enjoyment of a video clip Code Demo var trial = { type : jsPsychVideoSliderResponse , stimulus : [ 'video/fish.mp4' ], labels : [ \"Hated it\" , \"Loved it\" ], prompt : '<p>Please rate your enjoyment of the video clip.</p>' }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"Example"},{"location":"plugins/virtual-chinrest/","text":"virtual-chinrest \u00b6 Current version: 2.0.2. See version history . This plugin provides a \"virtual chinrest\" that can measure the distance between the participant and the screen. It can also standardize the jsPsych page content to a known physical dimension (e.g., ensuring that a 200px wide stimulus is 2.2cm wide on the participant's monitor). This is based on the work of Li, Joo, Yeatman, and Reinecke (2020) , and the plugin code is a modified version of their implementation . We recommend citing their work in any paper that makes use of this plugin. Citation Li, Q., Joo, S. J., Yeatman, J. D., & Reinecke, K. (2020). Controlling for Participants\u2019 Viewing Distance in Large-Scale, Psychophysical Online Experiments Using a Virtual Chinrest. Scientific Reports, 10 (1), 1-11. doi: 10.1038/s41598-019-57204-1 The plugin works in two phases. Phase 1 . To calculate the pixel-to-cm conversion rate for a participant\u2019s display, participants are asked to place a credit card or other item of the same size on the screen and resize an image until it is the same size as the credit card. Since we know the physical dimensions of the card, we can find the conversion rate for the participant's display. Phase 2 . To measure the participant's viewing distance from their screen we use a blind spot task. Participants are asked to focus on a black square on the screen with their right eye closed, while a red dot repeatedly sweeps from right to left. They press the spacebar on their keyboard whenever they perceive that the red dot has disappeared. This part allows the plugin to use the distance between the black square and the red dot when it disappears from eyesight to estimate how far the participant is from the monitor. This estimation assumes that the blind spot is located at 13.5\u00b0 temporally. Parameters \u00b6 Parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Descripton resize_units string \"none\" Units to resize the jsPsych content to after the trial is over: \"none\" \"cm\" \"inch\" or \"deg\" . If \"none\" , no resizing will be done to the jsPsych content after the virtual-chinrest trial ends. pixels_per_unit numeric 100 After the scaling factor is applied, this many pixels will equal one unit of measurement, where the units are indicated by resize_units . This is only used when resizing is done after the trial ends (i.e. the resize_units parameter is not \"none\"). adjustment_prompt HTML string \"Click and drag the lower right corner of the image until it is the same size as a credit card held up to the screen. You can use any card that is the same size as a credit card, like a membership card or driver's license. If you do not have access to a real card you can use a ruler to measure the image width to 3.37 inches or 85.6 mm.\" This string can contain HTML markup. Any content here will be displayed below the card stimulus during the resizing phase. adjustment_button_prompt HTML string \"Click here when the image is the correct size\" Content of the button displayed below the card stimulus during the resizing phase. item_path string null Path of the item to be presented in the card stimulus during the resizing phase. If null then no image is shown, and a solid color background is used instead. An example image is available in /examples/img/card.png item_height_mm numeric 53.98 The known height of the physical item (e.g. credit card) to be measured, in mm. item_width_mm numeric 85.6 The known width of the physical item (e.g. credit card) to be measured, in mm. item_init_size numeric 250 The initial size of the card stimulus, in pixels, along its largest dimension. blindspot_reps numeric 5 How many times to measure the blindspot location. If 0 , blindspot will not be detected, and viewing distance and degree data will not be computed. blindspot_prompt HTML string \"Now we will quickly measure how far away you are sitting. Put your left hand on the space bar. Cover your right eye with your right hand. Using your left eye, focus on the black square. Keep your focus on the black square. The red ball will disappear as it moves from right to left. Press the space bar as soon as the ball disappears. Press the space bar when you are ready to begin. This string can contain HTML markup. Any content here will be displayed above the blindspot task . redo_measurement_button_label HTML string 'No, that is not close. Try again' Text for the button on the viewing distance report page to re-do the viewing distance estimate. If the participant click this button, the blindspot task starts again. blindspot_done_prompt HTML string \"Yes\" Text for the button on the viewing distance report page that can be clicked to accept the viewing distance estimate. blindspot_measurements_prompt HTML string 'Remaining measurements: ' Text accompanying the remaining measurements counter that appears below the blindspot task. viewing_distance_report HTML string \"Based on your responses, you are sitting about <span id='distance-estimate' style='font-weight: bold;'></span> from the screen. Does that seem about right?\" Estimated viewing distance data displayed after blindspot task. If \"none\" is given, viewing distance will not be reported to the participant. The HTML span element with id = distance-estimate returns the distance. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Note: The deg data are only returned if viewing distance is estimated with the blindspot method (px2deg, win_height_deg, win_width_deg, item_width_deg). Name Type Value rt numeric The response time in milliseconds. item_height_mm numeric The height in millimeters of the item to be measured. item_width_mm numeric The width in millimeters of the item to be measured item_height_deg numeric Final height of the resizable div container, in degrees. item_width_deg numeric Final width of the resizable div container, in degrees. item_width_px numeric Final width of the resizable div container, in pixels. px2deg numeric Pixels to degrees conversion factor. px2mm numeric Pixels to millimeters conversion factor. scale_factor numeric Scaling factor that will be applied to the div containing jsPsych content. win_width_deg numeric The interior width of the window in degrees. win_height_deg numeric The interior height of the window in degrees. view_dist_mm numeric Estimated distance to the screen in millimeters. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-virtual-chinrest.js\" >< /script> Using NPM: npm install @jspsych/plugin-virtual-chinrest import virtualChinrest from '@jspsych/plugin-virtual-chinrest' ; Example \u00b6 Measure distance to screen and pixel ratio; no resizing Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"none\" }; This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab Resizing based on centimeters per pixel Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"cm\" , pixels_per_unit : 50 }; var resized_stimulus = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>If the measurements were done correctly, the square below should be 10 cm x 10 cm.</p> <div style=\"background-color: black; width: 500px; height: 500px; margin: 20px auto;\"></div> ` , choices : [ 'Continue' ] } This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab Resizing based on degrees of visual angle per pixel Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"deg\" , pixels_per_unit : 50 }; var resized_stimulus = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>If the measurements were done correctly, the square below should take up about 10 degrees of visual angle.</p> <div style=\"background-color: black; width: 500px; height: 500px; margin: 20px auto;\"></div> ` , choices : [ 'Continue' ] } This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab","title":"virtual-chinrest"},{"location":"plugins/virtual-chinrest/#virtual-chinrest","text":"Current version: 2.0.2. See version history . This plugin provides a \"virtual chinrest\" that can measure the distance between the participant and the screen. It can also standardize the jsPsych page content to a known physical dimension (e.g., ensuring that a 200px wide stimulus is 2.2cm wide on the participant's monitor). This is based on the work of Li, Joo, Yeatman, and Reinecke (2020) , and the plugin code is a modified version of their implementation . We recommend citing their work in any paper that makes use of this plugin. Citation Li, Q., Joo, S. J., Yeatman, J. D., & Reinecke, K. (2020). Controlling for Participants\u2019 Viewing Distance in Large-Scale, Psychophysical Online Experiments Using a Virtual Chinrest. Scientific Reports, 10 (1), 1-11. doi: 10.1038/s41598-019-57204-1 The plugin works in two phases. Phase 1 . To calculate the pixel-to-cm conversion rate for a participant\u2019s display, participants are asked to place a credit card or other item of the same size on the screen and resize an image until it is the same size as the credit card. Since we know the physical dimensions of the card, we can find the conversion rate for the participant's display. Phase 2 . To measure the participant's viewing distance from their screen we use a blind spot task. Participants are asked to focus on a black square on the screen with their right eye closed, while a red dot repeatedly sweeps from right to left. They press the spacebar on their keyboard whenever they perceive that the red dot has disappeared. This part allows the plugin to use the distance between the black square and the red dot when it disappears from eyesight to estimate how far the participant is from the monitor. This estimation assumes that the blind spot is located at 13.5\u00b0 temporally.","title":"virtual-chinrest"},{"location":"plugins/virtual-chinrest/#parameters","text":"Parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Descripton resize_units string \"none\" Units to resize the jsPsych content to after the trial is over: \"none\" \"cm\" \"inch\" or \"deg\" . If \"none\" , no resizing will be done to the jsPsych content after the virtual-chinrest trial ends. pixels_per_unit numeric 100 After the scaling factor is applied, this many pixels will equal one unit of measurement, where the units are indicated by resize_units . This is only used when resizing is done after the trial ends (i.e. the resize_units parameter is not \"none\"). adjustment_prompt HTML string \"Click and drag the lower right corner of the image until it is the same size as a credit card held up to the screen. You can use any card that is the same size as a credit card, like a membership card or driver's license. If you do not have access to a real card you can use a ruler to measure the image width to 3.37 inches or 85.6 mm.\" This string can contain HTML markup. Any content here will be displayed below the card stimulus during the resizing phase. adjustment_button_prompt HTML string \"Click here when the image is the correct size\" Content of the button displayed below the card stimulus during the resizing phase. item_path string null Path of the item to be presented in the card stimulus during the resizing phase. If null then no image is shown, and a solid color background is used instead. An example image is available in /examples/img/card.png item_height_mm numeric 53.98 The known height of the physical item (e.g. credit card) to be measured, in mm. item_width_mm numeric 85.6 The known width of the physical item (e.g. credit card) to be measured, in mm. item_init_size numeric 250 The initial size of the card stimulus, in pixels, along its largest dimension. blindspot_reps numeric 5 How many times to measure the blindspot location. If 0 , blindspot will not be detected, and viewing distance and degree data will not be computed. blindspot_prompt HTML string \"Now we will quickly measure how far away you are sitting. Put your left hand on the space bar. Cover your right eye with your right hand. Using your left eye, focus on the black square. Keep your focus on the black square. The red ball will disappear as it moves from right to left. Press the space bar as soon as the ball disappears. Press the space bar when you are ready to begin. This string can contain HTML markup. Any content here will be displayed above the blindspot task . redo_measurement_button_label HTML string 'No, that is not close. Try again' Text for the button on the viewing distance report page to re-do the viewing distance estimate. If the participant click this button, the blindspot task starts again. blindspot_done_prompt HTML string \"Yes\" Text for the button on the viewing distance report page that can be clicked to accept the viewing distance estimate. blindspot_measurements_prompt HTML string 'Remaining measurements: ' Text accompanying the remaining measurements counter that appears below the blindspot task. viewing_distance_report HTML string \"Based on your responses, you are sitting about <span id='distance-estimate' style='font-weight: bold;'></span> from the screen. Does that seem about right?\" Estimated viewing distance data displayed after blindspot task. If \"none\" is given, viewing distance will not be reported to the participant. The HTML span element with id = distance-estimate returns the distance.","title":"Parameters"},{"location":"plugins/virtual-chinrest/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Note: The deg data are only returned if viewing distance is estimated with the blindspot method (px2deg, win_height_deg, win_width_deg, item_width_deg). Name Type Value rt numeric The response time in milliseconds. item_height_mm numeric The height in millimeters of the item to be measured. item_width_mm numeric The width in millimeters of the item to be measured item_height_deg numeric Final height of the resizable div container, in degrees. item_width_deg numeric Final width of the resizable div container, in degrees. item_width_px numeric Final width of the resizable div container, in pixels. px2deg numeric Pixels to degrees conversion factor. px2mm numeric Pixels to millimeters conversion factor. scale_factor numeric Scaling factor that will be applied to the div containing jsPsych content. win_width_deg numeric The interior width of the window in degrees. win_height_deg numeric The interior height of the window in degrees. view_dist_mm numeric Estimated distance to the screen in millimeters.","title":"Data Generated"},{"location":"plugins/virtual-chinrest/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/virtual-chinrest/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-virtual-chinrest.js\" >< /script> Using NPM: npm install @jspsych/plugin-virtual-chinrest import virtualChinrest from '@jspsych/plugin-virtual-chinrest' ;","title":"Install"},{"location":"plugins/virtual-chinrest/#example","text":"Measure distance to screen and pixel ratio; no resizing Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"none\" }; This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab Resizing based on centimeters per pixel Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"cm\" , pixels_per_unit : 50 }; var resized_stimulus = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>If the measurements were done correctly, the square below should be 10 cm x 10 cm.</p> <div style=\"background-color: black; width: 500px; height: 500px; margin: 20px auto;\"></div> ` , choices : [ 'Continue' ] } This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab Resizing based on degrees of visual angle per pixel Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"deg\" , pixels_per_unit : 50 }; var resized_stimulus = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>If the measurements were done correctly, the square below should take up about 10 degrees of visual angle.</p> <div style=\"background-color: black; width: 500px; height: 500px; margin: 20px auto;\"></div> ` , choices : [ 'Continue' ] } This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab","title":"Example"},{"location":"plugins/visual-search-circle/","text":"visual-search-circle \u00b6 Current version: 1.1.2. See version history . This plugin presents a customizable visual-search task modelled after Wang, Cavanagh, & Green (1994) . The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. Here is an example using normal and backward Ns: Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. The set of images to display must be defined in one of two ways: The target , foil and set_size parameters: the combination of these parameters can be used to construct a 'classic' visual search task, where there is a single foil/distractor image that makes up all of the images in the set, with the exception of the target image if it is present. OR The stimuli parameter: this array that can be used to present any arbitrary set of image files, with or without the target image, with any number of different foils/distractors, and with any number of repeated images. The target_present and fixation_image parameters must always be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target string null Path to image file that is the search target. This parameter must specified when the stimuli set is defined using the target , foil and set_size parameters, but should NOT be specified when using the stimuli parameter. foil string null Path to image file that is the foil/distractor. This image will be repeated for all distractors up to the set_size value. This parameter must specified when the stimuli set is defined using the target , foil and set_size parameters, but should NOT be specified when using the stimuli parameter. set_size numeric null How many items should be displayed, including the target when target_present is true . The foil image will be repeated up to this value when target_present is false , or up to set_size - 1 when target_present is true . This parameter must specified when using the target , foil and set_size parameters to define the stimuli set, but should NOT be specified when using the stimuli parameter. stimuli array of images null Array containing all of the image files to be displayed. This parameter must be specified when NOT using the target , foil , and set_size parameters to define the stimuli set. target_present boolean undefined Is the target present? This parameter must always be specified. When using the target , foil and set_size parameters, false means that the foil image will be repeated up to the set_size, and true means that the target will be presented along with the foil image repeated up to set_size - 1. When using the stimuli parameter, this parameter is only used to determine the response accuracy. fixation_image string undefined Path to image file that is a fixation target. This parameter must always be specified. target_size array [50, 50] Two element array indicating the height and width of the search array element images. fixation_size array [16, 16] Two element array indicating the height and width of the fixation image. circle_diameter numeric 250 The diameter of the search array circle in pixels. target_present_key string 'j' The key to press if the target is present in the search array. target_absent_key string 'f' The key to press if the target is not present in the search array. trial_duration numeric null The maximum amount of time the participant is allowed to search before the trial will continue. A value of null will allow the participant to search indefinitely. fixation_duration numeric 1000 How long to show the fixation image for before the search array (in milliseconds). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value correct boolean True if the participant gave the correct response. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. set_size numeric The number of items in the search array target_present boolean True if the target is present in the search array locations array Array where each element is the pixel value of the center of an image in the search array. If the target is present, then the first element will represent the location of the target. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-visual-search-circle.js\" >< /script> Using NPM: npm install @jspsych/plugin-visual-search-circle import visualSearchCircle from '@jspsych/plugin-visual-search-circle' ; Examples \u00b6 Identical distractors Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : `<p>Press J if there is a backwards N.</p> <p>Press F if all the Ns are in the normal orientation.</p>` , choices : [ 'Continue' ] } var trial = { type : jsPsychVisualSearchCircle , target : 'img/backwardN.gif' , foil : 'img/normalN.gif' , fixation_image : 'img/fixation.gif' , target_present : true , set_size : 4 } Open demo in new tab Variety of different distractors Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : `<p>Press E if there is an elephant in the group.</p> <p>Press N if there is no elephant in the group.</p>` , choices : [ 'Continue' ] } var trial = { type : jsPsychVisualSearchCircle , stimuli : [ 'img/elephant.png' , 'img/lion.png' , 'img/monkey.png' ], fixation_image : 'img/fixation.gif' , target_present_key : 'e' , target_absent_key : 'n' , target_present : true } Open demo in new tab","title":"visual-search-circle"},{"location":"plugins/visual-search-circle/#visual-search-circle","text":"Current version: 1.1.2. See version history . This plugin presents a customizable visual-search task modelled after Wang, Cavanagh, & Green (1994) . The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. Here is an example using normal and backward Ns:","title":"visual-search-circle"},{"location":"plugins/visual-search-circle/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. The set of images to display must be defined in one of two ways: The target , foil and set_size parameters: the combination of these parameters can be used to construct a 'classic' visual search task, where there is a single foil/distractor image that makes up all of the images in the set, with the exception of the target image if it is present. OR The stimuli parameter: this array that can be used to present any arbitrary set of image files, with or without the target image, with any number of different foils/distractors, and with any number of repeated images. The target_present and fixation_image parameters must always be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target string null Path to image file that is the search target. This parameter must specified when the stimuli set is defined using the target , foil and set_size parameters, but should NOT be specified when using the stimuli parameter. foil string null Path to image file that is the foil/distractor. This image will be repeated for all distractors up to the set_size value. This parameter must specified when the stimuli set is defined using the target , foil and set_size parameters, but should NOT be specified when using the stimuli parameter. set_size numeric null How many items should be displayed, including the target when target_present is true . The foil image will be repeated up to this value when target_present is false , or up to set_size - 1 when target_present is true . This parameter must specified when using the target , foil and set_size parameters to define the stimuli set, but should NOT be specified when using the stimuli parameter. stimuli array of images null Array containing all of the image files to be displayed. This parameter must be specified when NOT using the target , foil , and set_size parameters to define the stimuli set. target_present boolean undefined Is the target present? This parameter must always be specified. When using the target , foil and set_size parameters, false means that the foil image will be repeated up to the set_size, and true means that the target will be presented along with the foil image repeated up to set_size - 1. When using the stimuli parameter, this parameter is only used to determine the response accuracy. fixation_image string undefined Path to image file that is a fixation target. This parameter must always be specified. target_size array [50, 50] Two element array indicating the height and width of the search array element images. fixation_size array [16, 16] Two element array indicating the height and width of the fixation image. circle_diameter numeric 250 The diameter of the search array circle in pixels. target_present_key string 'j' The key to press if the target is present in the search array. target_absent_key string 'f' The key to press if the target is not present in the search array. trial_duration numeric null The maximum amount of time the participant is allowed to search before the trial will continue. A value of null will allow the participant to search indefinitely. fixation_duration numeric 1000 How long to show the fixation image for before the search array (in milliseconds).","title":"Parameters"},{"location":"plugins/visual-search-circle/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value correct boolean True if the participant gave the correct response. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. set_size numeric The number of items in the search array target_present boolean True if the target is present in the search array locations array Array where each element is the pixel value of the center of an image in the search array. If the target is present, then the first element will represent the location of the target. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/visual-search-circle/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-visual-search-circle.js\" >< /script> Using NPM: npm install @jspsych/plugin-visual-search-circle import visualSearchCircle from '@jspsych/plugin-visual-search-circle' ;","title":"Install"},{"location":"plugins/visual-search-circle/#examples","text":"Identical distractors Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : `<p>Press J if there is a backwards N.</p> <p>Press F if all the Ns are in the normal orientation.</p>` , choices : [ 'Continue' ] } var trial = { type : jsPsychVisualSearchCircle , target : 'img/backwardN.gif' , foil : 'img/normalN.gif' , fixation_image : 'img/fixation.gif' , target_present : true , set_size : 4 } Open demo in new tab Variety of different distractors Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : `<p>Press E if there is an elephant in the group.</p> <p>Press N if there is no elephant in the group.</p>` , choices : [ 'Continue' ] } var trial = { type : jsPsychVisualSearchCircle , stimuli : [ 'img/elephant.png' , 'img/lion.png' , 'img/monkey.png' ], fixation_image : 'img/fixation.gif' , target_present_key : 'e' , target_absent_key : 'n' , target_present : true } Open demo in new tab","title":"Examples"},{"location":"plugins/webgazer-calibrate/","text":"webgazer-calibrate \u00b6 Current version: 1.0.2. See version history . This plugin can be used to calibrate the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description calibration_points array [[10,10], [10,50], [10,90], [50,10], [50,50], [50,90], [90,10], [90,50], [90,90]] Array of points in [x,y] coordinates. Specified as a percentage of the screen width and height, from the left and top edge. The default grid is 9 points. calibration_mode string 'click' Can specify click to have participants click on calibration points or view to have participants passively watch calibration points. repetitions_per_point numeric 1 The number of times to repeat the sequence of calibration points. point_size numeric 20 Diameter of the calibration points in pixels. randomize_calibration_order bool false Whether to randomize the order of the calibration points. time_to_saccade numeric 1000 If calibration_mode is set to view , then this is the delay before calibrating after showing a point. Gives the participant time to fixate on the new target before assuming that the participant is looking at the target. time_per_point numeric 1000 If calibration_mode is set to view , then this is the length of time to show a point while calibrating. Note that if click calibration is used then the point will remain on the screen until clicked. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value No data currently added by this plugin. Use the webgazer-validate plugin to measure the precision and accuracy of calibration. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-calibrate.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-calibrate import webgazerCalibrate from '@jspsych/plugin-webgazer-calibrate' ; Example \u00b6 Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"webgazer-calibrate"},{"location":"plugins/webgazer-calibrate/#webgazer-calibrate","text":"Current version: 1.0.2. See version history . This plugin can be used to calibrate the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview .","title":"webgazer-calibrate"},{"location":"plugins/webgazer-calibrate/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description calibration_points array [[10,10], [10,50], [10,90], [50,10], [50,50], [50,90], [90,10], [90,50], [90,90]] Array of points in [x,y] coordinates. Specified as a percentage of the screen width and height, from the left and top edge. The default grid is 9 points. calibration_mode string 'click' Can specify click to have participants click on calibration points or view to have participants passively watch calibration points. repetitions_per_point numeric 1 The number of times to repeat the sequence of calibration points. point_size numeric 20 Diameter of the calibration points in pixels. randomize_calibration_order bool false Whether to randomize the order of the calibration points. time_to_saccade numeric 1000 If calibration_mode is set to view , then this is the delay before calibrating after showing a point. Gives the participant time to fixate on the new target before assuming that the participant is looking at the target. time_per_point numeric 1000 If calibration_mode is set to view , then this is the length of time to show a point while calibrating. Note that if click calibration is used then the point will remain on the screen until clicked.","title":"Parameters"},{"location":"plugins/webgazer-calibrate/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value No data currently added by this plugin. Use the webgazer-validate plugin to measure the precision and accuracy of calibration.","title":"Data Generated"},{"location":"plugins/webgazer-calibrate/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/webgazer-calibrate/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-calibrate.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-calibrate import webgazerCalibrate from '@jspsych/plugin-webgazer-calibrate' ;","title":"Install"},{"location":"plugins/webgazer-calibrate/#example","text":"Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"Example"},{"location":"plugins/webgazer-init-camera/","text":"webgazer-init-camera \u00b6 Current version: 1.0.2. See version history . This plugin initializes the camera and helps the participant center their face in the camera view for using the the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description instructions string too long to put here Instructions for the participant to follow. button_text string Continue The text for the button that participants click to end the trial. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value load_time numeric The time it took for webgazer to initialize. This can be a long time in some situations, so this value is recorded for troubleshooting when participants are reporting difficulty. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-init-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-init-camera import webgazerInitCamera from '@jspsych/plugin-webgazer-init-camera' ; Example \u00b6 Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"webgazer-init-camera"},{"location":"plugins/webgazer-init-camera/#webgazer-init-camera","text":"Current version: 1.0.2. See version history . This plugin initializes the camera and helps the participant center their face in the camera view for using the the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview .","title":"webgazer-init-camera"},{"location":"plugins/webgazer-init-camera/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description instructions string too long to put here Instructions for the participant to follow. button_text string Continue The text for the button that participants click to end the trial.","title":"Parameters"},{"location":"plugins/webgazer-init-camera/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value load_time numeric The time it took for webgazer to initialize. This can be a long time in some situations, so this value is recorded for troubleshooting when participants are reporting difficulty.","title":"Data Generated"},{"location":"plugins/webgazer-init-camera/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/webgazer-init-camera/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-init-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-init-camera import webgazerInitCamera from '@jspsych/plugin-webgazer-init-camera' ;","title":"Install"},{"location":"plugins/webgazer-init-camera/#example","text":"Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"Example"},{"location":"plugins/webgazer-validate/","text":"webgazer-validate \u00b6 Current version: 1.0.2. See version history . This plugin can be used to measure the accuracy and precision of gaze predictions made by the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description validation_points array [[10,10], [10,50], [10,90], [50,10], [50,50], [50,90], [90,10], [90,50], [90,90]] Array of points in [x,y] coordinates. The default grid is 9 points. Meaning of coordinates controlled by validation_point_coordinates parameter. validation_point_coordinates string 'percent' Can specify percent to have validation point coordinates specified in percentage of screen width and height, or center-offset-pixels to specify each point as the distance in pixels from the center of the screen. roi_radius numeric 200 Tolerance around the validation point in pixels when calculating the percent of gaze measurements within the acceptable range. randomize_validation_order bool false Whether to randomize the order of the validation points. time_to_saccade numeric 1000 The delay before validating after showing a point. Gives the participant time to fixate on the new target before assuming that the participant is looking at the target. validation_duration numeric 2000 If calibration_mode is set to view , then this is the length of time to show a point while calibrating. Note that if click calibration is used then the point will remain on the screen until clicked. point_size numeric 20 Diameter of the validation points in pixels. show_validation_data bool false If true then a visualization of the validation data will be shown on the screen after the validation is complete. This will show each measured gaze location color coded by whether it is within the roi_radius of the target point. This is mainly intended for testing and debugging. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value raw_gaze array Raw gaze data for the trial. The array will contain a nested array for each validation point. Within each nested array will be a list of {x,y,dx,dy} values specifying the absolute x and y pixels, as well as the distance from the target for that gaze point. percent_in_roi array The percentage of samples within the roi_radius for each validation point. average_offset array The average x and y distance from each validation point, plus the median distance r of the points from this average offset. samples_per_sec numeric The average number of samples per second. Calculated by finding samples per second for each point and then averaging these estimates together. validation_points array The list of validation points, in the order that they appeared. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-validate.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-validate import webgazerValidate from '@jspsych/plugin-webgazer-validate' ; Example \u00b6 Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"webgazer-validate"},{"location":"plugins/webgazer-validate/#webgazer-validate","text":"Current version: 1.0.2. See version history . This plugin can be used to measure the accuracy and precision of gaze predictions made by the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview .","title":"webgazer-validate"},{"location":"plugins/webgazer-validate/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description validation_points array [[10,10], [10,50], [10,90], [50,10], [50,50], [50,90], [90,10], [90,50], [90,90]] Array of points in [x,y] coordinates. The default grid is 9 points. Meaning of coordinates controlled by validation_point_coordinates parameter. validation_point_coordinates string 'percent' Can specify percent to have validation point coordinates specified in percentage of screen width and height, or center-offset-pixels to specify each point as the distance in pixels from the center of the screen. roi_radius numeric 200 Tolerance around the validation point in pixels when calculating the percent of gaze measurements within the acceptable range. randomize_validation_order bool false Whether to randomize the order of the validation points. time_to_saccade numeric 1000 The delay before validating after showing a point. Gives the participant time to fixate on the new target before assuming that the participant is looking at the target. validation_duration numeric 2000 If calibration_mode is set to view , then this is the length of time to show a point while calibrating. Note that if click calibration is used then the point will remain on the screen until clicked. point_size numeric 20 Diameter of the validation points in pixels. show_validation_data bool false If true then a visualization of the validation data will be shown on the screen after the validation is complete. This will show each measured gaze location color coded by whether it is within the roi_radius of the target point. This is mainly intended for testing and debugging.","title":"Parameters"},{"location":"plugins/webgazer-validate/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value raw_gaze array Raw gaze data for the trial. The array will contain a nested array for each validation point. Within each nested array will be a list of {x,y,dx,dy} values specifying the absolute x and y pixels, as well as the distance from the target for that gaze point. percent_in_roi array The percentage of samples within the roi_radius for each validation point. average_offset array The average x and y distance from each validation point, plus the median distance r of the points from this average offset. samples_per_sec numeric The average number of samples per second. Calculated by finding samples per second for each point and then averaging these estimates together. validation_points array The list of validation points, in the order that they appeared.","title":"Data Generated"},{"location":"plugins/webgazer-validate/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/webgazer-validate/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-validate.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-validate import webgazerValidate from '@jspsych/plugin-webgazer-validate' ;","title":"Install"},{"location":"plugins/webgazer-validate/#example","text":"Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"Example"},{"location":"reference/jspsych-data/","text":"jsPsych.data \u00b6 The jsPsych.data module contains functions for interacting with the data generated by jsPsych plugins. jsPsych.data.addProperties \u00b6 jsPsych . data . addProperties ( properties ) Parameters \u00b6 Parameter Type Description properties object Object of key: value pairs to add to the data. Return value \u00b6 Returns nothing. Description \u00b6 This method appends a set of properties to every trial in the data object, including trials that have already occurred and trials that have yet to occur. You can use this to record things like the subject ID or condition assignment. Examples \u00b6 Assigning a subject ID and condition code \u00b6 jsPsych . data . addProperties ({ subject : 1 , condition : 'control' }); jsPsych.data.displayData \u00b6 jsPsych . data . displayData ( format ) Parameters \u00b6 Parameter Type Description format string Specifies whether to display the data in 'csv' or 'json' format. Return value \u00b6 Returns nothing. Description \u00b6 Outputs all of the data collected in the experiment to the screen in either JSON or CSV format. This is a useful method for quick debugging when developing an experiment. Examples \u00b6 Using the on_finish callback function to show data at the end of the experiment \u00b6 var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData ( 'csv' ); } }) jsPsych.data.get \u00b6 jsPsych.data.get() Parameters \u00b6 None. Return value \u00b6 Returns the data collection of all data generated by the experiment. Description \u00b6 This function is the standard starting point for accessing the data generated by the experiment. It returns a DataCollection object, which has several methods that can be used to further filter, aggregate, and view the data. These methods are described under the DataCollection section on this page. Example \u00b6 // select all trials var all_data = jsPsych . data . get (); // get csv representation of data and log to console console . log ( all_data . csv ()); jsPsych.data.getDataByTimelineNode \u00b6 jsPsych . data . getDataByTimelineNode ( node_id ) Parameters \u00b6 Parameter Type Description node_id string The id of the TimelineNodes to get data from. Return value \u00b6 Returns a DataCollection of all of the data generated in a specified TimelineNode. Description \u00b6 Get all the data generated by a specified Timeline. Example \u00b6 var current_node_id = jsPsych . getCurrentTimelineNodeID (); var data_from_current_node = jsPsych . data . getDataByTimelineNode ( current_node_id ); jsPsych.data.getInteractionData \u00b6 jsPsych . data . getInteractionData () Parameters \u00b6 None. Return value \u00b6 Returns a DataCollection object with all of the interaction events. Description \u00b6 jsPsych automatically records a few different kinds of user interaction events. blur events occur when the user clicks on another window or tab during the experiment, indicating that they are no longer interacting with the experiment. focus events occur when the user clicks on the experiment window after having clicked somewhere else first (i.e., generated a blur event). fullscreenenter and fullscreenexit events are triggered by the browser entering and exiting fullscreen mode. However, fullscreenenter events only occur when the script switches the browser to fullscreen mode, e.g., with the fullscreen plugin . Manually entering fullscreen mode does not trigger this event. fullscreenexit events occur whether the user manually exits fullscreen mode or the script exits fullscreen mode. This method returns the DataCollection containing all interaction events. This is useful for tracking whether the participant completed the task without diverting attention to other windows. Events are in the form: { type : 'focus' or 'blur' or 'fullscreenenter' or 'fullscreenexit' , trial : 10 , // the trial number when the event happened time : 13042 // total time elapsed since the start of the experiment } Example \u00b6 var interaction_data = jsPsych . data . getInteractionData (); // log data to console in json format console . log ( interaction_data . json ()); jsPsych.data.getLastTimelineData \u00b6 jsPsych . data . getLastTimelineData () Return value \u00b6 Returns a DataCollection. Description \u00b6 Gets all of the data generated in the same timeline as the last trial. Example \u00b6 var lasttimelinedata = jsPsych . data . getLastTimelineData (); jsPsych.data.getLastTrialData \u00b6 jsPsych . data . getLastTrialData () Return value \u00b6 Returns a DataCollection. Description \u00b6 Gets the data collection containing all data generated by the last trial. Example \u00b6 var lasttrialdata = jsPsych . data . getLastTrialData (); jsPsych.data.getURLVariable \u00b6 jsPsych . data . getURLVariable ( var_name ) Parameters \u00b6 Parameter Type Description var_name string Which variable to get the value of. Return value \u00b6 Returns the value of a variable passed in through the query string. Description \u00b6 For extracting a particular variable passed in through a URL query string. Example \u00b6 // if the URL of the page is: experiment.html?subject=1234&condition=test console . log ( jsPsych . data . getURLVariable ( 'subject' )) // logs \"1234\" console . log ( jsPsych . data . getURLVariable ( 'condition' )) // logs \"test\" jsPsych.data.urlVariables \u00b6 jsPsych . data . urlVariables () Return value \u00b6 Returns an object (associative array) of the variables in the URL query string. Description \u00b6 For extracting variables passed in through a URL query string. Example \u00b6 // if the URL of the page is: experiment.html?subject=1234&condition=test var urlvar = jsPsych . data . urlVariables (); console . log ( urlvar . subject ) // logs \"1234\" console . log ( urlvar . condition ) // logs \"test\" jsPsych.data.write \u00b6 jsPsych . data . write ( data_object ) Parameters \u00b6 Parameter Type Description data_object object Object of key: value pairs to store in jsPsych's data storage as a trial. Return value \u00b6 Returns nothing. Description \u00b6 This method is used by jsPsych.finishTrial for writing data. You should probably not use it to add data. Instead use jsPsych.data.addProperties . Example \u00b6 // don't use this! data should only be written once per trial. use jsPsych.finishTrial to save data. var trial_data = { correct : true , rt : 487 } jsPsych . data . write ( trial_data ); DataCollection \u00b6 All data is stored in the DataCollection object. Using methods like jsPsych.data.get() and jsPsych.data.getLastTrialData() return DataCollections containing the experiment data. This is a list of all of the methods that are available to call on a DataCollection object. .addToAll() \u00b6 Adds a set of properties to all items in the DataCollection. Similar to jsPsych.data.addProperties() , except that it can be applied to a subset of the whole DataCollection by filtering down to a smaller DataCollection first. jsPsych . data . get (). addToAll ({ subject_id : 123 , condition : 'control' }); .addToLast() \u00b6 Adds a set of properties to the last trial in the DataCollection. jsPsych . data . get (). addToLast ({ success : true }); .count() \u00b6 Counts the number of trials in the DataCollection. jsPsych . data . get (). count () .csv() \u00b6 Generates a CSV string representing all of the data in the DataCollection. console . log ( jsPsych . data . get (). csv ()); .filter() \u00b6 Returns a subset of the DataCollection based on the filter. The filter is an object, and trials are only kept in the returned DataCollection if they contain the key: value pair(s) in the filter object. For example, the code below selects all of the trials with a correct response. var correct_trials = jsPsych . data . get (). filter ({ correct : true }); The object can have multiple key: value pairs, and the trials must match all of them in order to be included in the returned collection. // keep only correct trials from the practice phase var correct_practice_trials = jsPsych . data . get (). filter ({ correct : true , phase : 'practice' }); The filter can also be an array of objects. In this case each object in the array acts as an OR filter. As long as the trial has all the key: value pairs of one of the objects in the array, it will appear in the returned collection. // select trials from block 1 and block 5. var trials = jsPsych . data . get (). filter ([{ block : 1 }, { block : 5 }]); The filter method returns a DataCollection object, so methods can be chained onto a single statement. // count the number of correct trials in block 1 var block_1_correct = jsPsych . data . get (). filter ({ block : 1 , correct : true }). count (); .filterColumns() \u00b6 Selects the set of columns listed in the array. This is the opposite of the .ignore() method. // Get only the subject, rt, and condition entries for each trial. const subset_of_data = jsPsych . data . get (). filterColumns ([ 'subject' , 'rt' , 'condition' ]) .filterCustom() \u00b6 This method is similar to the .filter() method, except that it accepts a function as the filter. The function is passed a single argument, containing the data for a trial. If the function returns true the trial is included in the returned DataCollection. // count the number of trials with a response time greater than 2000ms. var too_long = jsPsych . data . get (). filterCustom ( function ( trial ){ return trial . rt > 2000 ; }). count () .first() / .last() \u00b6 Returns a DataCollection containing the first/last n trials. If n is greater than the number of trials in the DataCollection, then these functions will return an array of length equal to the number of trials. If there are no trials in the DataCollection, then these functions will return an empty array. If the n argument is omitted, then the functions will use the default value of 1. If n is zero or a negative number, then these functions will throw an error. var first_trial = jsPsych . data . get (). first ( 1 ); var last_trial_with_correct_response = jsPsych . data . get (). filter ({ correct : true }). last ( 1 ); var last_10_trials = jsPsych . data . get (). last ( 10 ); .ignore() \u00b6 Returns a DataCollection with all instances of a particular key removed from the dataset. // log a csv file that does not contain the internal_node_id values for each trial console . log ( jsPsych . data . get (). ignore ( 'internal_node_id' ). csv ()); .join() \u00b6 Appends one DataCollection onto another and returns the combined collection. // get a DataCollection with all trials that are either correct or // have a response time greater than 200ms. var dc1 = jsPsych . data . get (). filter ({ correct : true }); var dc2 = jsPsych . data . get (). filterCustom ( function ( trial ){ return trial . rt > 200 }); var data = dc1 . join ( dc2 ); .json() \u00b6 Generates a JSON string representing all of the data in the DataCollection. console . log ( jsPsych . data . get (). json ()); .localSave() \u00b6 Saves a CSV or JSON file on the computer running the experiment. If conducting an online experiment, this will download the file onto the subject's computer, and is therefore not a recommended data storage solution for online data collection. Warning: This function may not behave correctly in older browsers. Upgrading to the latest version of any major web browser should solve the problem. // first argument is the format, second is the filename. // the format can be either 'csv' or 'json'. jsPsych . data . get (). localSave ( 'csv' , 'mydata.csv' ); .push() \u00b6 Add a new entry to the DataCollection. This method is mostly used internally, and you shouldn't need to call it under normal circumstances. var data = { correct : true , rt : 500 } jsPsych . data . get (). push ( data ); .readOnly() \u00b6 Creates a copy of the DataCollection so that any modification of the values in the DataCollection will not affect the original. // this line edits the rt property of the first trial jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt = 100 ; // readOnly creates a copy that can be modified without affecting the original jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt // outputs 100 jsPsych . data . get (). readOnly (). first ( 1 ). values ()[ 0 ]. rt = 200 jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt // still outputs 100 .select() \u00b6 Returns a DataColumn object (see documentation below) of a single property from a DataCollection object. var rt_data = jsPsych . data . get (). select ( 'rt' ); rt_data . mean () .uniqueNames() \u00b6 Generates an array of all the unique key names in the set of trials contained in the DataCollection. This is especially useful when setting up a relational database (e.g., MySQL) where the column names need to be specified in advance. console . log ( jsPsych . data . get (). uniqueNames ()); .values() \u00b6 Returns the raw data array associated with the DataCollection. This array is modifiable, so changes to the array and values of objects in the array will change the DataCollection. var raw_data = jsPsych . data . get (). values (); // was response in first trial correct? if ( raw_data [ 0 ]. correct ){ console . log ( 'correct!' ); } else { console . log ( 'incorrect.' ); } DataColumn \u00b6 DataColumn objects represent all the values of a single property in a DataCollection. They are generated by using the .select() method on a DataCollection. Once a DataColumn is generated, the following methods can be used. .all() \u00b6 Checks if all values in the DataColumn return true when passed to a function. The function takes a single argument, which represents one value from the DataColumn. // check if all the response times in the practice phase were under 1000ms jsPsych . data . get (). filter ({ phase : 'practice' }). select ( 'correct' ). all ( function ( x ) { return x < 1000 ; }); .count() \u00b6 Counts the number of values in the DataColumn. // count how many response times there are jsPsych . data . get (). select ( 'rt' ). count (); .frequencies() \u00b6 Counts the number of occurrences of each unique value in the DataColumn. Returns this value as an object, where each key is a unique value and the value of each key is the number of occurrences of that key. // get frequencies of correct and incorrect responses jsPsych . data . get (). select ( 'correct' ). frequencies (); .max() / .min() \u00b6 Returns the maximum or minimum value in a DataColumn. jsPsych . data . get (). select ( 'rt' ). max (); jsPsych . data . get (). select ( 'rt' ). min (); .mean() \u00b6 Returns the average of all the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). mean (); .median() \u00b6 Returns the median of all the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). median (); .sd() \u00b6 Returns the standard deviation of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). sd (); .subset() \u00b6 Filters the DataColumn to include only values that return true when passed through the specified function. // below results will be less than 200. jsPsych . data . get (). select ( 'rt' ). subset ( function ( x ){ return x < 200 ; }). max (); .sum() \u00b6 Returns the sum of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). sum (); .values \u00b6 The raw array of values in the DataColumn. // note that this is not a function call. jsPsych . data . get (). select ( 'rt' ). values ; .variance() \u00b6 Returns the variance of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). variance ();","title":"jsPsych.data"},{"location":"reference/jspsych-data/#jspsychdata","text":"The jsPsych.data module contains functions for interacting with the data generated by jsPsych plugins.","title":"jsPsych.data"},{"location":"reference/jspsych-data/#jspsychdataaddproperties","text":"jsPsych . data . addProperties ( properties )","title":"jsPsych.data.addProperties"},{"location":"reference/jspsych-data/#parameters","text":"Parameter Type Description properties object Object of key: value pairs to add to the data.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-data/#description","text":"This method appends a set of properties to every trial in the data object, including trials that have already occurred and trials that have yet to occur. You can use this to record things like the subject ID or condition assignment.","title":"Description"},{"location":"reference/jspsych-data/#examples","text":"","title":"Examples"},{"location":"reference/jspsych-data/#assigning-a-subject-id-and-condition-code","text":"jsPsych . data . addProperties ({ subject : 1 , condition : 'control' });","title":"Assigning a subject ID and condition code"},{"location":"reference/jspsych-data/#jspsychdatadisplaydata","text":"jsPsych . data . displayData ( format )","title":"jsPsych.data.displayData"},{"location":"reference/jspsych-data/#parameters_1","text":"Parameter Type Description format string Specifies whether to display the data in 'csv' or 'json' format.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_1","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-data/#description_1","text":"Outputs all of the data collected in the experiment to the screen in either JSON or CSV format. This is a useful method for quick debugging when developing an experiment.","title":"Description"},{"location":"reference/jspsych-data/#examples_1","text":"","title":"Examples"},{"location":"reference/jspsych-data/#using-the-on_finish-callback-function-to-show-data-at-the-end-of-the-experiment","text":"var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData ( 'csv' ); } })","title":"Using the on_finish callback function to show data at the end of the experiment"},{"location":"reference/jspsych-data/#jspsychdataget","text":"jsPsych.data.get()","title":"jsPsych.data.get"},{"location":"reference/jspsych-data/#parameters_2","text":"None.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_2","text":"Returns the data collection of all data generated by the experiment.","title":"Return value"},{"location":"reference/jspsych-data/#description_2","text":"This function is the standard starting point for accessing the data generated by the experiment. It returns a DataCollection object, which has several methods that can be used to further filter, aggregate, and view the data. These methods are described under the DataCollection section on this page.","title":"Description"},{"location":"reference/jspsych-data/#example","text":"// select all trials var all_data = jsPsych . data . get (); // get csv representation of data and log to console console . log ( all_data . csv ());","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatagetdatabytimelinenode","text":"jsPsych . data . getDataByTimelineNode ( node_id )","title":"jsPsych.data.getDataByTimelineNode"},{"location":"reference/jspsych-data/#parameters_3","text":"Parameter Type Description node_id string The id of the TimelineNodes to get data from.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_3","text":"Returns a DataCollection of all of the data generated in a specified TimelineNode.","title":"Return value"},{"location":"reference/jspsych-data/#description_3","text":"Get all the data generated by a specified Timeline.","title":"Description"},{"location":"reference/jspsych-data/#example_1","text":"var current_node_id = jsPsych . getCurrentTimelineNodeID (); var data_from_current_node = jsPsych . data . getDataByTimelineNode ( current_node_id );","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatagetinteractiondata","text":"jsPsych . data . getInteractionData ()","title":"jsPsych.data.getInteractionData"},{"location":"reference/jspsych-data/#parameters_4","text":"None.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_4","text":"Returns a DataCollection object with all of the interaction events.","title":"Return value"},{"location":"reference/jspsych-data/#description_4","text":"jsPsych automatically records a few different kinds of user interaction events. blur events occur when the user clicks on another window or tab during the experiment, indicating that they are no longer interacting with the experiment. focus events occur when the user clicks on the experiment window after having clicked somewhere else first (i.e., generated a blur event). fullscreenenter and fullscreenexit events are triggered by the browser entering and exiting fullscreen mode. However, fullscreenenter events only occur when the script switches the browser to fullscreen mode, e.g., with the fullscreen plugin . Manually entering fullscreen mode does not trigger this event. fullscreenexit events occur whether the user manually exits fullscreen mode or the script exits fullscreen mode. This method returns the DataCollection containing all interaction events. This is useful for tracking whether the participant completed the task without diverting attention to other windows. Events are in the form: { type : 'focus' or 'blur' or 'fullscreenenter' or 'fullscreenexit' , trial : 10 , // the trial number when the event happened time : 13042 // total time elapsed since the start of the experiment }","title":"Description"},{"location":"reference/jspsych-data/#example_2","text":"var interaction_data = jsPsych . data . getInteractionData (); // log data to console in json format console . log ( interaction_data . json ());","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatagetlasttimelinedata","text":"jsPsych . data . getLastTimelineData ()","title":"jsPsych.data.getLastTimelineData"},{"location":"reference/jspsych-data/#return-value_5","text":"Returns a DataCollection.","title":"Return value"},{"location":"reference/jspsych-data/#description_5","text":"Gets all of the data generated in the same timeline as the last trial.","title":"Description"},{"location":"reference/jspsych-data/#example_3","text":"var lasttimelinedata = jsPsych . data . getLastTimelineData ();","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatagetlasttrialdata","text":"jsPsych . data . getLastTrialData ()","title":"jsPsych.data.getLastTrialData"},{"location":"reference/jspsych-data/#return-value_6","text":"Returns a DataCollection.","title":"Return value"},{"location":"reference/jspsych-data/#description_6","text":"Gets the data collection containing all data generated by the last trial.","title":"Description"},{"location":"reference/jspsych-data/#example_4","text":"var lasttrialdata = jsPsych . data . getLastTrialData ();","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatageturlvariable","text":"jsPsych . data . getURLVariable ( var_name )","title":"jsPsych.data.getURLVariable"},{"location":"reference/jspsych-data/#parameters_5","text":"Parameter Type Description var_name string Which variable to get the value of.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_7","text":"Returns the value of a variable passed in through the query string.","title":"Return value"},{"location":"reference/jspsych-data/#description_7","text":"For extracting a particular variable passed in through a URL query string.","title":"Description"},{"location":"reference/jspsych-data/#example_5","text":"// if the URL of the page is: experiment.html?subject=1234&condition=test console . log ( jsPsych . data . getURLVariable ( 'subject' )) // logs \"1234\" console . log ( jsPsych . data . getURLVariable ( 'condition' )) // logs \"test\"","title":"Example"},{"location":"reference/jspsych-data/#jspsychdataurlvariables","text":"jsPsych . data . urlVariables ()","title":"jsPsych.data.urlVariables"},{"location":"reference/jspsych-data/#return-value_8","text":"Returns an object (associative array) of the variables in the URL query string.","title":"Return value"},{"location":"reference/jspsych-data/#description_8","text":"For extracting variables passed in through a URL query string.","title":"Description"},{"location":"reference/jspsych-data/#example_6","text":"// if the URL of the page is: experiment.html?subject=1234&condition=test var urlvar = jsPsych . data . urlVariables (); console . log ( urlvar . subject ) // logs \"1234\" console . log ( urlvar . condition ) // logs \"test\"","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatawrite","text":"jsPsych . data . write ( data_object )","title":"jsPsych.data.write"},{"location":"reference/jspsych-data/#parameters_6","text":"Parameter Type Description data_object object Object of key: value pairs to store in jsPsych's data storage as a trial.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_9","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-data/#description_9","text":"This method is used by jsPsych.finishTrial for writing data. You should probably not use it to add data. Instead use jsPsych.data.addProperties .","title":"Description"},{"location":"reference/jspsych-data/#example_7","text":"// don't use this! data should only be written once per trial. use jsPsych.finishTrial to save data. var trial_data = { correct : true , rt : 487 } jsPsych . data . write ( trial_data );","title":"Example"},{"location":"reference/jspsych-data/#datacollection","text":"All data is stored in the DataCollection object. Using methods like jsPsych.data.get() and jsPsych.data.getLastTrialData() return DataCollections containing the experiment data. This is a list of all of the methods that are available to call on a DataCollection object.","title":"DataCollection"},{"location":"reference/jspsych-data/#addtoall","text":"Adds a set of properties to all items in the DataCollection. Similar to jsPsych.data.addProperties() , except that it can be applied to a subset of the whole DataCollection by filtering down to a smaller DataCollection first. jsPsych . data . get (). addToAll ({ subject_id : 123 , condition : 'control' });","title":".addToAll()"},{"location":"reference/jspsych-data/#addtolast","text":"Adds a set of properties to the last trial in the DataCollection. jsPsych . data . get (). addToLast ({ success : true });","title":".addToLast()"},{"location":"reference/jspsych-data/#count","text":"Counts the number of trials in the DataCollection. jsPsych . data . get (). count ()","title":".count()"},{"location":"reference/jspsych-data/#csv","text":"Generates a CSV string representing all of the data in the DataCollection. console . log ( jsPsych . data . get (). csv ());","title":".csv()"},{"location":"reference/jspsych-data/#filter","text":"Returns a subset of the DataCollection based on the filter. The filter is an object, and trials are only kept in the returned DataCollection if they contain the key: value pair(s) in the filter object. For example, the code below selects all of the trials with a correct response. var correct_trials = jsPsych . data . get (). filter ({ correct : true }); The object can have multiple key: value pairs, and the trials must match all of them in order to be included in the returned collection. // keep only correct trials from the practice phase var correct_practice_trials = jsPsych . data . get (). filter ({ correct : true , phase : 'practice' }); The filter can also be an array of objects. In this case each object in the array acts as an OR filter. As long as the trial has all the key: value pairs of one of the objects in the array, it will appear in the returned collection. // select trials from block 1 and block 5. var trials = jsPsych . data . get (). filter ([{ block : 1 }, { block : 5 }]); The filter method returns a DataCollection object, so methods can be chained onto a single statement. // count the number of correct trials in block 1 var block_1_correct = jsPsych . data . get (). filter ({ block : 1 , correct : true }). count ();","title":".filter()"},{"location":"reference/jspsych-data/#filtercolumns","text":"Selects the set of columns listed in the array. This is the opposite of the .ignore() method. // Get only the subject, rt, and condition entries for each trial. const subset_of_data = jsPsych . data . get (). filterColumns ([ 'subject' , 'rt' , 'condition' ])","title":".filterColumns()"},{"location":"reference/jspsych-data/#filtercustom","text":"This method is similar to the .filter() method, except that it accepts a function as the filter. The function is passed a single argument, containing the data for a trial. If the function returns true the trial is included in the returned DataCollection. // count the number of trials with a response time greater than 2000ms. var too_long = jsPsych . data . get (). filterCustom ( function ( trial ){ return trial . rt > 2000 ; }). count ()","title":".filterCustom()"},{"location":"reference/jspsych-data/#first-last","text":"Returns a DataCollection containing the first/last n trials. If n is greater than the number of trials in the DataCollection, then these functions will return an array of length equal to the number of trials. If there are no trials in the DataCollection, then these functions will return an empty array. If the n argument is omitted, then the functions will use the default value of 1. If n is zero or a negative number, then these functions will throw an error. var first_trial = jsPsych . data . get (). first ( 1 ); var last_trial_with_correct_response = jsPsych . data . get (). filter ({ correct : true }). last ( 1 ); var last_10_trials = jsPsych . data . get (). last ( 10 );","title":".first() / .last()"},{"location":"reference/jspsych-data/#ignore","text":"Returns a DataCollection with all instances of a particular key removed from the dataset. // log a csv file that does not contain the internal_node_id values for each trial console . log ( jsPsych . data . get (). ignore ( 'internal_node_id' ). csv ());","title":".ignore()"},{"location":"reference/jspsych-data/#join","text":"Appends one DataCollection onto another and returns the combined collection. // get a DataCollection with all trials that are either correct or // have a response time greater than 200ms. var dc1 = jsPsych . data . get (). filter ({ correct : true }); var dc2 = jsPsych . data . get (). filterCustom ( function ( trial ){ return trial . rt > 200 }); var data = dc1 . join ( dc2 );","title":".join()"},{"location":"reference/jspsych-data/#json","text":"Generates a JSON string representing all of the data in the DataCollection. console . log ( jsPsych . data . get (). json ());","title":".json()"},{"location":"reference/jspsych-data/#localsave","text":"Saves a CSV or JSON file on the computer running the experiment. If conducting an online experiment, this will download the file onto the subject's computer, and is therefore not a recommended data storage solution for online data collection. Warning: This function may not behave correctly in older browsers. Upgrading to the latest version of any major web browser should solve the problem. // first argument is the format, second is the filename. // the format can be either 'csv' or 'json'. jsPsych . data . get (). localSave ( 'csv' , 'mydata.csv' );","title":".localSave()"},{"location":"reference/jspsych-data/#push","text":"Add a new entry to the DataCollection. This method is mostly used internally, and you shouldn't need to call it under normal circumstances. var data = { correct : true , rt : 500 } jsPsych . data . get (). push ( data );","title":".push()"},{"location":"reference/jspsych-data/#readonly","text":"Creates a copy of the DataCollection so that any modification of the values in the DataCollection will not affect the original. // this line edits the rt property of the first trial jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt = 100 ; // readOnly creates a copy that can be modified without affecting the original jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt // outputs 100 jsPsych . data . get (). readOnly (). first ( 1 ). values ()[ 0 ]. rt = 200 jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt // still outputs 100","title":".readOnly()"},{"location":"reference/jspsych-data/#select","text":"Returns a DataColumn object (see documentation below) of a single property from a DataCollection object. var rt_data = jsPsych . data . get (). select ( 'rt' ); rt_data . mean ()","title":".select()"},{"location":"reference/jspsych-data/#uniquenames","text":"Generates an array of all the unique key names in the set of trials contained in the DataCollection. This is especially useful when setting up a relational database (e.g., MySQL) where the column names need to be specified in advance. console . log ( jsPsych . data . get (). uniqueNames ());","title":".uniqueNames()"},{"location":"reference/jspsych-data/#values","text":"Returns the raw data array associated with the DataCollection. This array is modifiable, so changes to the array and values of objects in the array will change the DataCollection. var raw_data = jsPsych . data . get (). values (); // was response in first trial correct? if ( raw_data [ 0 ]. correct ){ console . log ( 'correct!' ); } else { console . log ( 'incorrect.' ); }","title":".values()"},{"location":"reference/jspsych-data/#datacolumn","text":"DataColumn objects represent all the values of a single property in a DataCollection. They are generated by using the .select() method on a DataCollection. Once a DataColumn is generated, the following methods can be used.","title":"DataColumn"},{"location":"reference/jspsych-data/#all","text":"Checks if all values in the DataColumn return true when passed to a function. The function takes a single argument, which represents one value from the DataColumn. // check if all the response times in the practice phase were under 1000ms jsPsych . data . get (). filter ({ phase : 'practice' }). select ( 'correct' ). all ( function ( x ) { return x < 1000 ; });","title":".all()"},{"location":"reference/jspsych-data/#count_1","text":"Counts the number of values in the DataColumn. // count how many response times there are jsPsych . data . get (). select ( 'rt' ). count ();","title":".count()"},{"location":"reference/jspsych-data/#frequencies","text":"Counts the number of occurrences of each unique value in the DataColumn. Returns this value as an object, where each key is a unique value and the value of each key is the number of occurrences of that key. // get frequencies of correct and incorrect responses jsPsych . data . get (). select ( 'correct' ). frequencies ();","title":".frequencies()"},{"location":"reference/jspsych-data/#max-min","text":"Returns the maximum or minimum value in a DataColumn. jsPsych . data . get (). select ( 'rt' ). max (); jsPsych . data . get (). select ( 'rt' ). min ();","title":".max() / .min()"},{"location":"reference/jspsych-data/#mean","text":"Returns the average of all the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). mean ();","title":".mean()"},{"location":"reference/jspsych-data/#median","text":"Returns the median of all the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). median ();","title":".median()"},{"location":"reference/jspsych-data/#sd","text":"Returns the standard deviation of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). sd ();","title":".sd()"},{"location":"reference/jspsych-data/#subset","text":"Filters the DataColumn to include only values that return true when passed through the specified function. // below results will be less than 200. jsPsych . data . get (). select ( 'rt' ). subset ( function ( x ){ return x < 200 ; }). max ();","title":".subset()"},{"location":"reference/jspsych-data/#sum","text":"Returns the sum of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). sum ();","title":".sum()"},{"location":"reference/jspsych-data/#values_1","text":"The raw array of values in the DataColumn. // note that this is not a function call. jsPsych . data . get (). select ( 'rt' ). values ;","title":".values"},{"location":"reference/jspsych-data/#variance","text":"Returns the variance of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). variance ();","title":".variance()"},{"location":"reference/jspsych-pluginAPI/","text":"jsPsych.pluginAPI \u00b6 The pluginAPI module contains functions that are useful when developing plugins. All of the functions are accessible through the pluginAPI object. In this documentation we've divided them up based on different kinds of functionality. Keyboard Input \u00b6 cancelAllKeyboardResponses \u00b6 jsPsych . pluginAPI . cancelAllKeyboardResponses () Parameters \u00b6 None. Return value \u00b6 Returns nothing. Description \u00b6 Cancels all currently active keyboard listeners created by jsPsych.pluginAPI.getKeyboardResponse . Example \u00b6 jsPsych . pluginAPI . cancelAllKeyboardResponses (); cancelKeyboardResponse \u00b6 jsPsych . pluginAPI . cancelKeyboardResponse ( listener_id ) Parameters \u00b6 Parameter Type Description listener_id object The listener_id object generated by the call to jsPsych.pluginAPI.getKeyboardResponse . Return value \u00b6 Returns nothing. Description \u00b6 Cancels a specific keyboard listener created by jsPsych.pluginAPI.getKeyboardResponse . Example \u00b6 // create a persistent keyboard listener var listener_id = jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : [ 'p' , 'q' ], rt_method : 'performance' , persist : true , allow_held_key : false }); // cancel keyboard listener jsPsych . pluginAPI . cancelKeyboardResponse ( listener_id ); compareKeys \u00b6 jsPsych . pluginAPI . compareKeys ( key1 , key2 ) Parameters \u00b6 Parameter Type Description key1 string or numeric The representation of a key, either string or keycode key2 string or numeric The representation of a key, either string or keycode Return value \u00b6 Returns true if keycodes or strings refer to the same key, regardless of type. Returns false if the keycodes or strings do not match. Description \u00b6 Compares two keys to see if they are the same, ignoring differences in representational type, and using the appropriate case sensitivity based on the experiment's settings. If case_sensitive_responses is set to false in initJsPsych (the default), then the string key comparison will not be case-sensitive, e.g., \"a\" and \"A\" will match, and this function will return true . If case_sensitive_responses is set to true in initJsPsych , then the string key comparison will not be case-sensitive, e.g., \"a\" and \"A\" will not match, and this function will return false . We recommend using this function to compare keys in all plugin and experiment code, rather than using something like if (response == 'j')... . This is because the response key returned by the jsPsych.pluginAPI.getKeyboardResponse function will be converted to lowercase when case_sensitive_responses is false , and it will match the exact key press representation when case_sensitive_responses is true . Using this compareKeys function will ensure that your key comparisons work appropriately based on the experiment's case_sensitive_responses setting, and that you do not need to remember to check key responses against different case versions of the comparison key (e.g. if (response == 'ArrowLeft' || response == 'arrowleft')... ). Examples \u00b6 Basic examples \u00b6 jsPsych . pluginAPI . compareKeys ( 'a' , 'A' ); // returns true when case_sensitive_responses is false in initJsPsych jsPsych . pluginAPI . compareKeys ( 'a' , 'A' ); // returns false when case_sensitive_responses is true in initJsPsych // also works with numeric key codes (but note that numeric keyCode values are now deprecated) jsPsych . pluginAPI . compareKeys ( 'a' , 65 ); // returns true jsPsych . pluginAPI . compareKeys ( 'space' , 31 ); // returns false Comparing a key response and key parameter value in plugins \u00b6 // this is the callback_function passed to jsPsych.pluginAPI.getKeyboardResponse var after_response = function ( info ) { // score the response by comparing the key that was pressed against the trial's key_answer parameter var correct = jsPsych . pluginAPI . compareKeys ( trial . key_answer , info . key ); //... } Scoring a key response in experiment code \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], prompt : 'Press f for left. Press j for right.' , on_finish : function ( data ){ // score the response by comparing the key that was pressed (data.response) against the // correct response for this trial ('f'), and store reponse accuracy in the trial data if ( jsPsych . pluginAPI . compareKeys ( data . response , 'f' )){ data . correct = true ; } else { data . correct = false ; } } } getKeyboardResponse \u00b6 jsPsych . pluginAPI . getKeyboardResponse ( parameters ) Parameters \u00b6 The method accepts an object of parameter values (see example below). The valid keys for this object are listed in the table below. Parameter Type Description callback_function function The function to execute whenever a valid keyboard response is generated. valid_responses array An array of key codes or character strings representing valid responses. Responses not on the list will be ignored. An empty array indicates that all responses are acceptable. rt_method string Indicates which method of recording time to use. The 'performance' method uses calls to performance.now() , which is the standard way of measuring timing in jsPsych. It is supported by up-to-date versions of all the major browsers . The audio method is used in conjuction with an audio_context (set as an additional parameter). This uses the clock time of the audio_context when audio stimuli are being played. audio_context AudioContext object The AudioContext of the audio file that is being played. audio_context_start_time numeric The scheduled time of the sound file in the AudioContext. This will be used as the start time. allow_held_key boolean If true , then responses will be registered from keys that are being held down. If false , then a held key can only register a response the first time that getKeyboardResponse is called for that key. For example, if a participant holds down the A key before the experiment starts, then the first time getKeyboardResponse is called, the A will register as a key press. However, any future calls to getKeyboardResponse will not register the A until the participant releases the key and presses it again. persist boolean If false, then the keyboard listener will only trigger the first time a valid key is pressed. If true, then it will trigger every time a valid key is pressed until it is explicitly cancelled by jsPsych.pluginAPI.cancelKeyboardResponse or jsPsych.pluginAPI.cancelAllKeyboardResponses . Return value \u00b6 Return an object that uniquely identifies the keyboard listener. This object can be passed to jsPsych.pluginAPI.cancelKeyboardResponse to cancel the keyboard listener. Description \u00b6 Gets a keyboard response from the participant, recording the response time from when the function is first called until a valid response is generated. The keyboard event listener will be bound to the display_element declared in initJsPsych() (or the <body> element if no display_element is specified). This allows jsPsych experiments to be embedded in websites with other content without disrupting the functionality of other UI elements. A valid response triggers the callback_function specified in the parameters. A single argument is passed to the callback function. The argument contains an object with the properties key and rt . key contains the string representation of the response key, and rt contains the response time. This function uses the .key value of the keyboard event, which is case sensitive . When case_sensitive_responses is false in initJsPsych (the default), this function will convert both the valid_responses strings and the response key to lowercase before comparing them, and it will pass the lowercase version of the response key to the callback_function . For example, if valid_responses is ['a'] , then both 'A' and 'a' will be considered valid key presses, and 'a' will be returned as the response key. When case_sensitive_responses is true in initJsPsych , this function will not convert the case when comparing the valid_responses and response key, and it will not convert the case of the response key that is passed to the callback_function . For example, if valid_responses is ['a'] , then 'a' will be the only valid key press, and 'A' (i.e. 'a' with CapsLock on or Shift held down) will not be accepted. Also, if valid_responses includes multiple letter case options (e.g. \"ALL_KEYS\" ), then you may need to check the response key against both letter cases when scoring etc., e.g. if (response == 'ArrowLeft' || response =='arrowleft') ... . Examples \u00b6 Get a single response from any key \u00b6 var after_response = function ( info ){ alert ( 'You pressed key ' + info . key + ' after ' + info . rt + 'ms' ); } jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : \"ALL_KEYS\" , rt_method : 'performance' , persist : false }); Get a responses from a key until the letter q is pressed \u00b6 var after_response = function ( info ){ alert ( 'You pressed key ' + info . key + ' after ' + info . rt + 'ms' ); if ( jsPsych . pluginAPI . compareKeys ( info . key , 'q' )){ / jsPsych . pluginAPI . cancelKeyboardResponse ( listener ); } } var listener = jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : \"ALL_KEYS\" , rt_method : 'performance' , persist : true }); Media \u00b6 getAudioBuffer \u00b6 jsPsych . pluginAPI . getAudioBuffer ( filepath ) Parameters \u00b6 Parameter Type Description filepath string The path to the audio file that was preloaded. Return value \u00b6 Returns a Promise that resolves when the audio file loads. Success handler's parameter will be the audio buffer. If the experiment is running using the WebAudio API it will be an AudioBuffer object. Otherwise, it will be an HTML5 Audio object. The failure handler's parameter is the error generated by preloadAudio . Description \u00b6 Gets an AudioBuffer that can be played with the WebAudio API or an Audio object that can be played with HTML5 Audio. It is strongly recommended that you preload audio files before calling this method. This method will load the files if they are not preloaded, but this may result in delays during the experiment as audio is downloaded. Examples \u00b6 HTML 5 Audio \u00b6 jsPsych . pluginAPI . getAudioBuffer ( 'my-sound.mp3' ) . then ( function ( audio ){ audio . play (); }) . catch ( function ( err ){ console . error ( 'Audio file failed to load' ) }) WebAudio API \u00b6 var context = jsPsych . pluginAPI . audioContext (); jsPsych . pluginAPI . getAudioBuffer ( 'my-sound.mp3' ) . then ( function ( buffer ){ audio = context . createBufferSource (); audio . buffer = buffer ; audio . connect ( context . destination ); audio . start ( context . currentTime ); }) . catch ( function ( err ){ console . error ( 'Audio file failed to load' ) }) See the audio-keyboard-response plugin for an example in a fuller context. getAutoPreloadList \u00b6 jsPsych . pluginAPI . getAutoPreloadList ( timeline ) Parameters \u00b6 Parameter Type Description timeline array An array containing the trial object(s) from which a list of media files should be automatically generated. This array can contain the entire experiment timeline, or any individual parts of a larger timeline, such as specific timeline nodes and trial objects. Return value \u00b6 An object with properties for each media type: images , audio , and video . Each property contains an array of the unique files of that media type that were automatically extracted from the timeline. If no files are found in the timeline for a particular media type, then the array will be empty for that type. Description \u00b6 This method is used to automatically generate lists of unique image, audio, and video files from a timeline. It is used by the preload plugin to generate a list of to-be-preloaded files based on the trials passed to the trials parameter and/or the experiment timeline passed to jsPsych.run (when auto_preload is true). It can be used in custom plugins and experiment code to generate a list of audio/image/video files, based on a timeline. This function will only return files from plugin parameters that are marked as parameter type AUDIO / IMAGE / VIDEO , and only when the preload flag of the corresponding parameter definition has not been set to false , and the trial's parameter value is not a function. When a file path is returned to the trial parameter from a function (including the jsPsych.timelineVariable function), or when the file path is embedded in an HTML string, that file will not be detected by the getAutoPreloadList method. In these cases, the file should be preloaded manually. See Media Preloading for more information. Example \u00b6 var audio_trial = { type : jsPsychAudioKeyboardResponse stimulus : 'file.mp3' } var image_trial = { type : jsPsychImageKeyboardResponse stimulus : 'file.png' } var video_trial = { type : jsPsychVideoKeyboardResponse stimulus : 'file.mp4' } var timeline = [ audio_trial , image_trial , video_trial ]; jsPsych . pluginAPI . getAutoPreloadList ( timeline ); getMicrophoneRecorder \u00b6 jsPsych . pluginAPI . getMicrophoneRecorder () Parameters \u00b6 None Return value \u00b6 A MediaRecorder object connected to the MediaStream for the active microphone. Description \u00b6 Provides access to the MediaRecorder created by initializeMicrophoneRecorder() . If no microphone recorder exists, it returns null . Example \u00b6 const recorder = jsPsych . pluginAPI . getMicrophoneRecorder (); initializeMicrophoneRecorder \u00b6 jsPsych . pluginAPI . initializeMicrophoneRecorder ( stream ) Parameters \u00b6 Parameter Type Description stream MediaStream The MediaStream object from an active microphone device. Return value \u00b6 None. Description \u00b6 Generates a MediaRecorder object from provided MediaStream and stores this for access via getMicrophoneRecorder() . Example \u00b6 const stream = await navigator . mediaDevices . getUserMedia ({ audio : { deviceId : mic_id } }); jsPsych . pluginAPI . initializeMicrophoneRecorder ( stream ); preloadAudio \u00b6 jsPsych . pluginAPI . preloadAudio ( files , callback_complete , callback_load , callback_error ) Parameters \u00b6 Parameter Type Description files array An array of audio file paths to load. The array can be nested (e.g., if images are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the files have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error. Return value \u00b6 Returns nothing. Description \u00b6 This function is used to preload audio files. It is used by the preload plugin, and could be called directly to preload audio files in custom plugins or experiment. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the files are loaded. Thus, it is possible that an audio file would be required for playing before it is done preloading. The callback_complete function will only execute after all the audio files are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below. Examples \u00b6 Basic use \u00b6 var sounds = [ 'file1.mp3' , 'file2.mp3' , 'file3.mp3' ]; jsPsych . pluginAPI . preloadAudio ( sounds , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); } Show progress of loading \u00b6 var sounds = [ 'file1.mp3' , 'file2.mp3' , 'file3.mp3' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadAudio ( sounds , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / sounds . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of audio files' ); } function startExperiment (){ jsPsych . run ( exp ); } preloadImages \u00b6 jsPsych . pluginAPI . preloadImages ( images , callback_complete , callback_load , callback_error ) Parameters \u00b6 Parameter Type Description images array An array of image paths to load. The array can be nested (e.g., if images are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the images have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error. Return value \u00b6 Returns nothing. Description \u00b6 This function is used to preload image files. It is used by the preload plugin, and could be called directly to preload image files in custom plugins or experiment code. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the images are loaded. Thus, it is possible that an image would be required for display before it is done preloading. The callback_complete function will only execute after all the images are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below. Examples \u00b6 Basic use \u00b6 var images = [ 'img/file1.png' , 'img/file2.png' , 'img/file3.png' ]; jsPsych . pluginAPI . preloadImages ( images , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); } Show progress of loading \u00b6 var images = [ 'img/file1.png' , 'img/file2.png' , 'img/file3.png' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadImages ( images , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / images . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of images' ); } function startExperiment (){ jsPsych . run ( exp ); } preloadVideo \u00b6 jsPsych . pluginAPI . preloadVideo ( video , callback_complete , callback_load , callback_error ) Parameters \u00b6 Parameter Type Description video array An array of video paths to load. The array can be nested (e.g., if videos are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the videos have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error. Return value \u00b6 Returns nothing. Description \u00b6 This function is used to preload video files. It is used by the preload plugin, and could be called directly to preload video files in custom plugins or experiment code. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the videos are loaded. Thus, it is possible that a video would be requested before it is done preloading. The callback_complete function will only execute after all the videos are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below. Examples \u00b6 Basic use \u00b6 var videos = [ 'vid/file1.mp4' , 'vid/file2.mp4' , 'vid/file3.mp4' ]; jsPsych . pluginAPI . preloadVideo ( videos , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); } Show progress of loading \u00b6 var videos = [ 'vid/file1.mp4' , 'vid/file2.mp4' , 'vid/file3.mp4' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadVideo ( videos , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / videos . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of videos' ); } function startExperiment (){ jsPsych . run ( exp ); } Simulation \u00b6 clickTarget \u00b6 jsPsych . pluginAPI . clickTarget ( target , delay ) Parameters \u00b6 Parameter Type Description target Element The DOM element to simulate clicking on. delay number Time to wait in milliseconds. The click will be executed after the delay. Return value \u00b6 None Description \u00b6 Simulates clicking on a DOM element by dispatching three MouseEvents on the target : 'mousedown' , then 'mouseup' , then 'click' . If delay is positive, then the events are scheduled to execute after the delay via setTimeout . Example \u00b6 const target = document . querySelector ( '.jspsych-btn' ); jsPsych . pluginAPI . clickTarget ( target , 500 ); ensureSimulationDataConsistency \u00b6 jsPsych . pluginAPI . ensureSimulationDataConsistency ( trial , data ) Parameters \u00b6 Parameter Type Description trial object Parameters for the trial, e.g., those passed to the plugin's trial() method. data object An object containing data for the trial. Return value \u00b6 None. The data object is modified in place by this method. Description \u00b6 Performs some basic consistency checks on the data based on the parameters specified in trial . For example, if trial.choices is \"NO_KEYS\" but data.response is a key string then data.response and data.rt are set to null . Example \u00b6 jsPsych . pluginAPI . ensureSimulationDataConsistency ( trial , data ); fillTextInput \u00b6 jsPsych . pluginAPI . fillTextInput ( target , text , delay ) Parameters \u00b6 Parameter Type Description target HTMLInputElement The input element to fill in with text. text string The text to input. delay number Time to wait in milliseconds. The text will be inserted after the delay. Return value \u00b6 None Description \u00b6 Sets the value of the target HTMLInputElement to equal text . Example \u00b6 const target = document . querySelector ( 'input[type=\"text\"]' ); jsPsych . pluginAPI . fillTextInput ( target , \"hello!\" , 500 ); getValidKey \u00b6 jsPsych . pluginAPI . getValidKey ( choices ) Parameters \u00b6 Parameter Type Description choices \"NO_KEYS\" or \"ALL_KEYS\" or array of strings Representation of the valid keys allowed for a keyboard response used by the getKeyboardResponse method. Return value \u00b6 A valid key given the choices parameter, chosen at random from the possible keys. Description \u00b6 Picks a random key given a set of options. Currently it only picks letters and numbers when choices is \"ALL_KEYS\" . Example \u00b6 const random_key = jsPsych . pluginAPI . getValidKey ( trial . choices ); keyDown \u00b6 jsPsych . pluginAPI . keyDown ( key ) Parameters \u00b6 Parameter Type Description key string The .key property of the corresponding key on the keyboard. Return value \u00b6 None. Description \u00b6 Dispatches a 'keydown' event for the specified key . Example \u00b6 jsPsych . pluginAPI . keyDown ( 'a' ); keyUp \u00b6 jsPsych . pluginAPI . keyUp ( key ) Parameters \u00b6 Parameter Type Description key string The .key property of the corresponding key on the keyboard. Return value \u00b6 None. Description \u00b6 Dispatches a 'keyup' event for the specified key . Example \u00b6 jsPsych . pluginAPI . keyUp ( 'a' ); mergeSimulationData \u00b6 jsPsych . pluginAPI . mergeSimulationData ( default_data , simulation_options ) Parameters \u00b6 Parameter Type Description default_data object An object containing data values for the simulated trial. simulation_options object The simulation_options specified for the trial. Return value \u00b6 An object of data. Description \u00b6 This method merges the default_data with any data specified in simulation_options.data , giving priority to values specified in simulation_options.data . It returns the merged data. Example \u00b6 const default_data = { rt : 500 , response : 'a' } const simulation_options = { data : { rt : 200 } } const data = jsPsych . pluginAPI . mergeSimulationData ( default_data , simulation_options ); data . rt === 200 ; // true Timeouts \u00b6 clearAllTimeouts \u00b6 jsPsych . pluginAPI . clearAllTimeouts () Parameters \u00b6 None. Return value \u00b6 Returns nothing. Description \u00b6 Clears any pending timeouts that were set using jsPsych.pluginAPI.setTimeout(). setTimeout \u00b6 jsPsych . pluginAPI . setTimeout ( callback , delay ) Parameters \u00b6 Parameter Type Description callback function A function to execute after waiting for delay. delay integer Time to wait in milliseconds. Return value \u00b6 Returns the ID of the setTimeout handle. Description \u00b6 This is simply a call to the standard setTimeout function in JavaScript with the added benefit of registering the setTimeout call in a central list. This is useful for scenarios where some other event (the trial ending, aborting the experiment) should stop the execution of queued timeouts. Example \u00b6 // print the time console . log ( Date . now ()) // print the time 1s later jsPsych . pluginAPI . setTimeout ( function (){ console . log ( Date . now ()) }, 1000 );","title":"jsPsych.pluginAPI"},{"location":"reference/jspsych-pluginAPI/#jspsychpluginapi","text":"The pluginAPI module contains functions that are useful when developing plugins. All of the functions are accessible through the pluginAPI object. In this documentation we've divided them up based on different kinds of functionality.","title":"jsPsych.pluginAPI"},{"location":"reference/jspsych-pluginAPI/#keyboard-input","text":"","title":"Keyboard Input"},{"location":"reference/jspsych-pluginAPI/#cancelallkeyboardresponses","text":"jsPsych . pluginAPI . cancelAllKeyboardResponses ()","title":"cancelAllKeyboardResponses"},{"location":"reference/jspsych-pluginAPI/#parameters","text":"None.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description","text":"Cancels all currently active keyboard listeners created by jsPsych.pluginAPI.getKeyboardResponse .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example","text":"jsPsych . pluginAPI . cancelAllKeyboardResponses ();","title":"Example"},{"location":"reference/jspsych-pluginAPI/#cancelkeyboardresponse","text":"jsPsych . pluginAPI . cancelKeyboardResponse ( listener_id )","title":"cancelKeyboardResponse"},{"location":"reference/jspsych-pluginAPI/#parameters_1","text":"Parameter Type Description listener_id object The listener_id object generated by the call to jsPsych.pluginAPI.getKeyboardResponse .","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_1","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_1","text":"Cancels a specific keyboard listener created by jsPsych.pluginAPI.getKeyboardResponse .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_1","text":"// create a persistent keyboard listener var listener_id = jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : [ 'p' , 'q' ], rt_method : 'performance' , persist : true , allow_held_key : false }); // cancel keyboard listener jsPsych . pluginAPI . cancelKeyboardResponse ( listener_id );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#comparekeys","text":"jsPsych . pluginAPI . compareKeys ( key1 , key2 )","title":"compareKeys"},{"location":"reference/jspsych-pluginAPI/#parameters_2","text":"Parameter Type Description key1 string or numeric The representation of a key, either string or keycode key2 string or numeric The representation of a key, either string or keycode","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_2","text":"Returns true if keycodes or strings refer to the same key, regardless of type. Returns false if the keycodes or strings do not match.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_2","text":"Compares two keys to see if they are the same, ignoring differences in representational type, and using the appropriate case sensitivity based on the experiment's settings. If case_sensitive_responses is set to false in initJsPsych (the default), then the string key comparison will not be case-sensitive, e.g., \"a\" and \"A\" will match, and this function will return true . If case_sensitive_responses is set to true in initJsPsych , then the string key comparison will not be case-sensitive, e.g., \"a\" and \"A\" will not match, and this function will return false . We recommend using this function to compare keys in all plugin and experiment code, rather than using something like if (response == 'j')... . This is because the response key returned by the jsPsych.pluginAPI.getKeyboardResponse function will be converted to lowercase when case_sensitive_responses is false , and it will match the exact key press representation when case_sensitive_responses is true . Using this compareKeys function will ensure that your key comparisons work appropriately based on the experiment's case_sensitive_responses setting, and that you do not need to remember to check key responses against different case versions of the comparison key (e.g. if (response == 'ArrowLeft' || response == 'arrowleft')... ).","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#basic-examples","text":"jsPsych . pluginAPI . compareKeys ( 'a' , 'A' ); // returns true when case_sensitive_responses is false in initJsPsych jsPsych . pluginAPI . compareKeys ( 'a' , 'A' ); // returns false when case_sensitive_responses is true in initJsPsych // also works with numeric key codes (but note that numeric keyCode values are now deprecated) jsPsych . pluginAPI . compareKeys ( 'a' , 65 ); // returns true jsPsych . pluginAPI . compareKeys ( 'space' , 31 ); // returns false","title":"Basic examples"},{"location":"reference/jspsych-pluginAPI/#comparing-a-key-response-and-key-parameter-value-in-plugins","text":"// this is the callback_function passed to jsPsych.pluginAPI.getKeyboardResponse var after_response = function ( info ) { // score the response by comparing the key that was pressed against the trial's key_answer parameter var correct = jsPsych . pluginAPI . compareKeys ( trial . key_answer , info . key ); //... }","title":"Comparing a key response and key parameter value in plugins"},{"location":"reference/jspsych-pluginAPI/#scoring-a-key-response-in-experiment-code","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], prompt : 'Press f for left. Press j for right.' , on_finish : function ( data ){ // score the response by comparing the key that was pressed (data.response) against the // correct response for this trial ('f'), and store reponse accuracy in the trial data if ( jsPsych . pluginAPI . compareKeys ( data . response , 'f' )){ data . correct = true ; } else { data . correct = false ; } } }","title":"Scoring a key response in experiment code"},{"location":"reference/jspsych-pluginAPI/#getkeyboardresponse","text":"jsPsych . pluginAPI . getKeyboardResponse ( parameters )","title":"getKeyboardResponse"},{"location":"reference/jspsych-pluginAPI/#parameters_3","text":"The method accepts an object of parameter values (see example below). The valid keys for this object are listed in the table below. Parameter Type Description callback_function function The function to execute whenever a valid keyboard response is generated. valid_responses array An array of key codes or character strings representing valid responses. Responses not on the list will be ignored. An empty array indicates that all responses are acceptable. rt_method string Indicates which method of recording time to use. The 'performance' method uses calls to performance.now() , which is the standard way of measuring timing in jsPsych. It is supported by up-to-date versions of all the major browsers . The audio method is used in conjuction with an audio_context (set as an additional parameter). This uses the clock time of the audio_context when audio stimuli are being played. audio_context AudioContext object The AudioContext of the audio file that is being played. audio_context_start_time numeric The scheduled time of the sound file in the AudioContext. This will be used as the start time. allow_held_key boolean If true , then responses will be registered from keys that are being held down. If false , then a held key can only register a response the first time that getKeyboardResponse is called for that key. For example, if a participant holds down the A key before the experiment starts, then the first time getKeyboardResponse is called, the A will register as a key press. However, any future calls to getKeyboardResponse will not register the A until the participant releases the key and presses it again. persist boolean If false, then the keyboard listener will only trigger the first time a valid key is pressed. If true, then it will trigger every time a valid key is pressed until it is explicitly cancelled by jsPsych.pluginAPI.cancelKeyboardResponse or jsPsych.pluginAPI.cancelAllKeyboardResponses .","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_3","text":"Return an object that uniquely identifies the keyboard listener. This object can be passed to jsPsych.pluginAPI.cancelKeyboardResponse to cancel the keyboard listener.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_3","text":"Gets a keyboard response from the participant, recording the response time from when the function is first called until a valid response is generated. The keyboard event listener will be bound to the display_element declared in initJsPsych() (or the <body> element if no display_element is specified). This allows jsPsych experiments to be embedded in websites with other content without disrupting the functionality of other UI elements. A valid response triggers the callback_function specified in the parameters. A single argument is passed to the callback function. The argument contains an object with the properties key and rt . key contains the string representation of the response key, and rt contains the response time. This function uses the .key value of the keyboard event, which is case sensitive . When case_sensitive_responses is false in initJsPsych (the default), this function will convert both the valid_responses strings and the response key to lowercase before comparing them, and it will pass the lowercase version of the response key to the callback_function . For example, if valid_responses is ['a'] , then both 'A' and 'a' will be considered valid key presses, and 'a' will be returned as the response key. When case_sensitive_responses is true in initJsPsych , this function will not convert the case when comparing the valid_responses and response key, and it will not convert the case of the response key that is passed to the callback_function . For example, if valid_responses is ['a'] , then 'a' will be the only valid key press, and 'A' (i.e. 'a' with CapsLock on or Shift held down) will not be accepted. Also, if valid_responses includes multiple letter case options (e.g. \"ALL_KEYS\" ), then you may need to check the response key against both letter cases when scoring etc., e.g. if (response == 'ArrowLeft' || response =='arrowleft') ... .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_1","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#get-a-single-response-from-any-key","text":"var after_response = function ( info ){ alert ( 'You pressed key ' + info . key + ' after ' + info . rt + 'ms' ); } jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : \"ALL_KEYS\" , rt_method : 'performance' , persist : false });","title":"Get a single response from any key"},{"location":"reference/jspsych-pluginAPI/#get-a-responses-from-a-key-until-the-letter-q-is-pressed","text":"var after_response = function ( info ){ alert ( 'You pressed key ' + info . key + ' after ' + info . rt + 'ms' ); if ( jsPsych . pluginAPI . compareKeys ( info . key , 'q' )){ / jsPsych . pluginAPI . cancelKeyboardResponse ( listener ); } } var listener = jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : \"ALL_KEYS\" , rt_method : 'performance' , persist : true });","title":"Get a responses from a key until the letter q is pressed"},{"location":"reference/jspsych-pluginAPI/#media","text":"","title":"Media"},{"location":"reference/jspsych-pluginAPI/#getaudiobuffer","text":"jsPsych . pluginAPI . getAudioBuffer ( filepath )","title":"getAudioBuffer"},{"location":"reference/jspsych-pluginAPI/#parameters_4","text":"Parameter Type Description filepath string The path to the audio file that was preloaded.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_4","text":"Returns a Promise that resolves when the audio file loads. Success handler's parameter will be the audio buffer. If the experiment is running using the WebAudio API it will be an AudioBuffer object. Otherwise, it will be an HTML5 Audio object. The failure handler's parameter is the error generated by preloadAudio .","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_4","text":"Gets an AudioBuffer that can be played with the WebAudio API or an Audio object that can be played with HTML5 Audio. It is strongly recommended that you preload audio files before calling this method. This method will load the files if they are not preloaded, but this may result in delays during the experiment as audio is downloaded.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_2","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#html-5-audio","text":"jsPsych . pluginAPI . getAudioBuffer ( 'my-sound.mp3' ) . then ( function ( audio ){ audio . play (); }) . catch ( function ( err ){ console . error ( 'Audio file failed to load' ) })","title":"HTML 5 Audio"},{"location":"reference/jspsych-pluginAPI/#webaudio-api","text":"var context = jsPsych . pluginAPI . audioContext (); jsPsych . pluginAPI . getAudioBuffer ( 'my-sound.mp3' ) . then ( function ( buffer ){ audio = context . createBufferSource (); audio . buffer = buffer ; audio . connect ( context . destination ); audio . start ( context . currentTime ); }) . catch ( function ( err ){ console . error ( 'Audio file failed to load' ) }) See the audio-keyboard-response plugin for an example in a fuller context.","title":"WebAudio API"},{"location":"reference/jspsych-pluginAPI/#getautopreloadlist","text":"jsPsych . pluginAPI . getAutoPreloadList ( timeline )","title":"getAutoPreloadList"},{"location":"reference/jspsych-pluginAPI/#parameters_5","text":"Parameter Type Description timeline array An array containing the trial object(s) from which a list of media files should be automatically generated. This array can contain the entire experiment timeline, or any individual parts of a larger timeline, such as specific timeline nodes and trial objects.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_5","text":"An object with properties for each media type: images , audio , and video . Each property contains an array of the unique files of that media type that were automatically extracted from the timeline. If no files are found in the timeline for a particular media type, then the array will be empty for that type.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_5","text":"This method is used to automatically generate lists of unique image, audio, and video files from a timeline. It is used by the preload plugin to generate a list of to-be-preloaded files based on the trials passed to the trials parameter and/or the experiment timeline passed to jsPsych.run (when auto_preload is true). It can be used in custom plugins and experiment code to generate a list of audio/image/video files, based on a timeline. This function will only return files from plugin parameters that are marked as parameter type AUDIO / IMAGE / VIDEO , and only when the preload flag of the corresponding parameter definition has not been set to false , and the trial's parameter value is not a function. When a file path is returned to the trial parameter from a function (including the jsPsych.timelineVariable function), or when the file path is embedded in an HTML string, that file will not be detected by the getAutoPreloadList method. In these cases, the file should be preloaded manually. See Media Preloading for more information.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_2","text":"var audio_trial = { type : jsPsychAudioKeyboardResponse stimulus : 'file.mp3' } var image_trial = { type : jsPsychImageKeyboardResponse stimulus : 'file.png' } var video_trial = { type : jsPsychVideoKeyboardResponse stimulus : 'file.mp4' } var timeline = [ audio_trial , image_trial , video_trial ]; jsPsych . pluginAPI . getAutoPreloadList ( timeline );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#getmicrophonerecorder","text":"jsPsych . pluginAPI . getMicrophoneRecorder ()","title":"getMicrophoneRecorder"},{"location":"reference/jspsych-pluginAPI/#parameters_6","text":"None","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_6","text":"A MediaRecorder object connected to the MediaStream for the active microphone.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_6","text":"Provides access to the MediaRecorder created by initializeMicrophoneRecorder() . If no microphone recorder exists, it returns null .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_3","text":"const recorder = jsPsych . pluginAPI . getMicrophoneRecorder ();","title":"Example"},{"location":"reference/jspsych-pluginAPI/#initializemicrophonerecorder","text":"jsPsych . pluginAPI . initializeMicrophoneRecorder ( stream )","title":"initializeMicrophoneRecorder"},{"location":"reference/jspsych-pluginAPI/#parameters_7","text":"Parameter Type Description stream MediaStream The MediaStream object from an active microphone device.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_7","text":"None.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_7","text":"Generates a MediaRecorder object from provided MediaStream and stores this for access via getMicrophoneRecorder() .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_4","text":"const stream = await navigator . mediaDevices . getUserMedia ({ audio : { deviceId : mic_id } }); jsPsych . pluginAPI . initializeMicrophoneRecorder ( stream );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#preloadaudio","text":"jsPsych . pluginAPI . preloadAudio ( files , callback_complete , callback_load , callback_error )","title":"preloadAudio"},{"location":"reference/jspsych-pluginAPI/#parameters_8","text":"Parameter Type Description files array An array of audio file paths to load. The array can be nested (e.g., if images are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the files have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_8","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_8","text":"This function is used to preload audio files. It is used by the preload plugin, and could be called directly to preload audio files in custom plugins or experiment. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the files are loaded. Thus, it is possible that an audio file would be required for playing before it is done preloading. The callback_complete function will only execute after all the audio files are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_3","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#basic-use","text":"var sounds = [ 'file1.mp3' , 'file2.mp3' , 'file3.mp3' ]; jsPsych . pluginAPI . preloadAudio ( sounds , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); }","title":"Basic use"},{"location":"reference/jspsych-pluginAPI/#show-progress-of-loading","text":"var sounds = [ 'file1.mp3' , 'file2.mp3' , 'file3.mp3' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadAudio ( sounds , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / sounds . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of audio files' ); } function startExperiment (){ jsPsych . run ( exp ); }","title":"Show progress of loading"},{"location":"reference/jspsych-pluginAPI/#preloadimages","text":"jsPsych . pluginAPI . preloadImages ( images , callback_complete , callback_load , callback_error )","title":"preloadImages"},{"location":"reference/jspsych-pluginAPI/#parameters_9","text":"Parameter Type Description images array An array of image paths to load. The array can be nested (e.g., if images are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the images have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_9","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_9","text":"This function is used to preload image files. It is used by the preload plugin, and could be called directly to preload image files in custom plugins or experiment code. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the images are loaded. Thus, it is possible that an image would be required for display before it is done preloading. The callback_complete function will only execute after all the images are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_4","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#basic-use_1","text":"var images = [ 'img/file1.png' , 'img/file2.png' , 'img/file3.png' ]; jsPsych . pluginAPI . preloadImages ( images , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); }","title":"Basic use"},{"location":"reference/jspsych-pluginAPI/#show-progress-of-loading_1","text":"var images = [ 'img/file1.png' , 'img/file2.png' , 'img/file3.png' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadImages ( images , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / images . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of images' ); } function startExperiment (){ jsPsych . run ( exp ); }","title":"Show progress of loading"},{"location":"reference/jspsych-pluginAPI/#preloadvideo","text":"jsPsych . pluginAPI . preloadVideo ( video , callback_complete , callback_load , callback_error )","title":"preloadVideo"},{"location":"reference/jspsych-pluginAPI/#parameters_10","text":"Parameter Type Description video array An array of video paths to load. The array can be nested (e.g., if videos are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the videos have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_10","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_10","text":"This function is used to preload video files. It is used by the preload plugin, and could be called directly to preload video files in custom plugins or experiment code. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the videos are loaded. Thus, it is possible that a video would be requested before it is done preloading. The callback_complete function will only execute after all the videos are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_5","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#basic-use_2","text":"var videos = [ 'vid/file1.mp4' , 'vid/file2.mp4' , 'vid/file3.mp4' ]; jsPsych . pluginAPI . preloadVideo ( videos , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); }","title":"Basic use"},{"location":"reference/jspsych-pluginAPI/#show-progress-of-loading_2","text":"var videos = [ 'vid/file1.mp4' , 'vid/file2.mp4' , 'vid/file3.mp4' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadVideo ( videos , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / videos . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of videos' ); } function startExperiment (){ jsPsych . run ( exp ); }","title":"Show progress of loading"},{"location":"reference/jspsych-pluginAPI/#simulation","text":"","title":"Simulation"},{"location":"reference/jspsych-pluginAPI/#clicktarget","text":"jsPsych . pluginAPI . clickTarget ( target , delay )","title":"clickTarget"},{"location":"reference/jspsych-pluginAPI/#parameters_11","text":"Parameter Type Description target Element The DOM element to simulate clicking on. delay number Time to wait in milliseconds. The click will be executed after the delay.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_11","text":"None","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_11","text":"Simulates clicking on a DOM element by dispatching three MouseEvents on the target : 'mousedown' , then 'mouseup' , then 'click' . If delay is positive, then the events are scheduled to execute after the delay via setTimeout .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_5","text":"const target = document . querySelector ( '.jspsych-btn' ); jsPsych . pluginAPI . clickTarget ( target , 500 );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#ensuresimulationdataconsistency","text":"jsPsych . pluginAPI . ensureSimulationDataConsistency ( trial , data )","title":"ensureSimulationDataConsistency"},{"location":"reference/jspsych-pluginAPI/#parameters_12","text":"Parameter Type Description trial object Parameters for the trial, e.g., those passed to the plugin's trial() method. data object An object containing data for the trial.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_12","text":"None. The data object is modified in place by this method.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_12","text":"Performs some basic consistency checks on the data based on the parameters specified in trial . For example, if trial.choices is \"NO_KEYS\" but data.response is a key string then data.response and data.rt are set to null .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_6","text":"jsPsych . pluginAPI . ensureSimulationDataConsistency ( trial , data );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#filltextinput","text":"jsPsych . pluginAPI . fillTextInput ( target , text , delay )","title":"fillTextInput"},{"location":"reference/jspsych-pluginAPI/#parameters_13","text":"Parameter Type Description target HTMLInputElement The input element to fill in with text. text string The text to input. delay number Time to wait in milliseconds. The text will be inserted after the delay.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_13","text":"None","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_13","text":"Sets the value of the target HTMLInputElement to equal text .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_7","text":"const target = document . querySelector ( 'input[type=\"text\"]' ); jsPsych . pluginAPI . fillTextInput ( target , \"hello!\" , 500 );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#getvalidkey","text":"jsPsych . pluginAPI . getValidKey ( choices )","title":"getValidKey"},{"location":"reference/jspsych-pluginAPI/#parameters_14","text":"Parameter Type Description choices \"NO_KEYS\" or \"ALL_KEYS\" or array of strings Representation of the valid keys allowed for a keyboard response used by the getKeyboardResponse method.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_14","text":"A valid key given the choices parameter, chosen at random from the possible keys.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_14","text":"Picks a random key given a set of options. Currently it only picks letters and numbers when choices is \"ALL_KEYS\" .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_8","text":"const random_key = jsPsych . pluginAPI . getValidKey ( trial . choices );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#keydown","text":"jsPsych . pluginAPI . keyDown ( key )","title":"keyDown"},{"location":"reference/jspsych-pluginAPI/#parameters_15","text":"Parameter Type Description key string The .key property of the corresponding key on the keyboard.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_15","text":"None.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_15","text":"Dispatches a 'keydown' event for the specified key .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_9","text":"jsPsych . pluginAPI . keyDown ( 'a' );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#keyup","text":"jsPsych . pluginAPI . keyUp ( key )","title":"keyUp"},{"location":"reference/jspsych-pluginAPI/#parameters_16","text":"Parameter Type Description key string The .key property of the corresponding key on the keyboard.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_16","text":"None.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_16","text":"Dispatches a 'keyup' event for the specified key .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_10","text":"jsPsych . pluginAPI . keyUp ( 'a' );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#mergesimulationdata","text":"jsPsych . pluginAPI . mergeSimulationData ( default_data , simulation_options )","title":"mergeSimulationData"},{"location":"reference/jspsych-pluginAPI/#parameters_17","text":"Parameter Type Description default_data object An object containing data values for the simulated trial. simulation_options object The simulation_options specified for the trial.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_17","text":"An object of data.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_17","text":"This method merges the default_data with any data specified in simulation_options.data , giving priority to values specified in simulation_options.data . It returns the merged data.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_11","text":"const default_data = { rt : 500 , response : 'a' } const simulation_options = { data : { rt : 200 } } const data = jsPsych . pluginAPI . mergeSimulationData ( default_data , simulation_options ); data . rt === 200 ; // true","title":"Example"},{"location":"reference/jspsych-pluginAPI/#timeouts","text":"","title":"Timeouts"},{"location":"reference/jspsych-pluginAPI/#clearalltimeouts","text":"jsPsych . pluginAPI . clearAllTimeouts ()","title":"clearAllTimeouts"},{"location":"reference/jspsych-pluginAPI/#parameters_18","text":"None.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_18","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_18","text":"Clears any pending timeouts that were set using jsPsych.pluginAPI.setTimeout().","title":"Description"},{"location":"reference/jspsych-pluginAPI/#settimeout","text":"jsPsych . pluginAPI . setTimeout ( callback , delay )","title":"setTimeout"},{"location":"reference/jspsych-pluginAPI/#parameters_19","text":"Parameter Type Description callback function A function to execute after waiting for delay. delay integer Time to wait in milliseconds.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_19","text":"Returns the ID of the setTimeout handle.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_19","text":"This is simply a call to the standard setTimeout function in JavaScript with the added benefit of registering the setTimeout call in a central list. This is useful for scenarios where some other event (the trial ending, aborting the experiment) should stop the execution of queued timeouts.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_12","text":"// print the time console . log ( Date . now ()) // print the time 1s later jsPsych . pluginAPI . setTimeout ( function (){ console . log ( Date . now ()) }, 1000 );","title":"Example"},{"location":"reference/jspsych-randomization/","text":"jsPsych.randomization \u00b6 The jsPsych.randomization module contains methods that are useful for generating random lists of trial variables. jsPsych.randomization.factorial \u00b6 jsPsych . randomization . factorial ( factors , repetitions , unpack ) Parameters \u00b6 Parameter Type Description factors object The factors object should contain a property for each different factor. Each property-factor should have a value of an array, with each element of the array corresponding to a level of the factor. repetitions integer The number of times to repeat each unique combination of the factors in the output sample. unpack boolean If true then the output will be an object with a property for each factor in the original factors object. The value of each property-factor will be an array containing the levels of the factor in a random order. The order will be consistent across each property-factor (e.g., the first element of each property-factor will specify one unique combination of the factors). If false , then the return value will be an array of objects where each property-factor contains only a single value. Return value \u00b6 The return value depends on the unpack parameter. See description of the parameter above, and examples below. Description \u00b6 This method takes a list of factors and their levels, and creates a full factorial design by creating each unique combination of the factors. The returned set of combinations is in a random order. Examples \u00b6 Create full factorial design \u00b6 var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 1 ); /* output: full_design = [ {stimulus: 'a.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 100}, ] */ Create full factorial design with repeats \u00b6 var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 2 ); /* output: full_design = [ {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'a.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 200}, ] */ Create full factorial design, unpacked \u00b6 var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 1 , true ); /* output: full_design = { stimulus: ['a.jpg','b.jpg','b.jpg','a.jpg'], ms_delay: [200, 100, 200, 100] ] */ jsPsych.randomization.randomID \u00b6 jsPsych . randomization . randomID ( length ) Parameters \u00b6 Parameter Type Description length integer The length of the randomly generated ID Return value \u00b6 Returns a string of length length where each character is randomly selected from the numbers 0-9 and all lowercase English letters a-z. Description \u00b6 Generates a random string that is likely to be unique. If length is undefined, then the string length is 32. Example \u00b6 console . log ( jsPsych . randomization . randomID ()); // outputs: \"t7dwz0e713pc8juuaayyfvpkdd9un239\" console . log ( jsPsych . randomization . randomID ( 8 )); // outputs: \"3xtpcbck\" jsPsych.randomization.randomInt \u00b6 jsPsych . randomization . randomInt ( lower , upper ) Parameters \u00b6 Parameter Type Description lower integer The smallest value it is possible to generate upper integer The largest value it is possible to generate Return value \u00b6 An integer Description \u00b6 Generates a random integer from lower to upper Example \u00b6 console . log ( jsPsych . randomization . randomInt ( 2 , 4 )); // outputs: 2 or 3 or 4. jsPsych.randomization.repeat \u00b6 jsPsych . randomization . repeat ( array , repetitions , unpack ) Parameters \u00b6 Parameter Type Description array array The array of values to randomize & repeat. repetitions integer or array The number of times to repeat each element of the array in the final sample. If this parameter is defined as an integer, then each element of array is repeated the same number of times. This parameter can also be an array of the same length as array , in which case each element of array will be repeated the number of times defined in the corresponding position of the repetitions array. unpack boolean If each element of array is an object with an equivalent set of properties, then setting unpack to true will make the return value an object with a property for each of the unique properties among the elements of the array . Each property in the output object will be an array containing the values for that property in the randomized order. The order will be consistent across properties. If this is false then the output is just an array containing a randomized order of the original array elements. Return value \u00b6 The return value depends on the unpack parameter. See description of the parameter above, and examples below. Description \u00b6 This method takes an array of values and generates a new random order of the array, with the option of repeating each element of the array a specified number of times. If the array elements are objects with the same set of properties, then this method can optionally return a single object where each property is a randomized order of the properties defined in the original set of objects. This is useful for randomizing sets of parameters that are used to define a jsPsych block. Examples \u00b6 Shuffle an array, no repeats \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 1 ); // output: shuffledArray = [3,2,4,1,5] Shuffle an array with repeats \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 ); // output: shuffledArray = [1,3,4,2,2,4,5,1,5,3] Shuffle an array of objects \u00b6 var trial1 = { stimulus : 'img/faceA.jpg' , correct_key : 'p' , person_name : 'Joe' } var trial2 = { stimulus : 'img/faceB.jpg' , correct_key : 'p' , person_name : 'Fred' } var trial3 = { stimulus : 'img/faceC.jpg' , correct_key : 'q' , person_name : 'Mary' } var myArray = [ trial1 , trial2 , trial3 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 ); // output: shuffledArray = [ trial1, trial3, trial3, trial2, trial1, trial2 ] Shuffle an array of objects, with unpack \u00b6 var trial1 = { stimulus : 'img/faceA.jpg' , correct_key : 'p' , person_name : 'Joe' } var trial2 = { stimulus : 'img/faceB.jpg' , correct_key : 'p' , person_name : 'Fred' } var trial3 = { stimulus : 'img/faceC.jpg' , correct_key : 'q' , person_name : 'Mary' } var myArray = [ trial1 , trial2 , trial3 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 , true ); /* output: shuffledArray = { stimulus: ['img/faceB.jpg','img/faceA.jpg','img/faceC.jpg','img/faceA.jpg','img/faceC.jpg','img/faceB.jpg'], correct_key: ['p', 'p', 'q', 'p', 'q', 'p'], person_name: ['Fred', 'Joe', 'Mary', 'Joe', 'Mary', 'Fred'] } */ jsPsych.randomization.sampleBernoulli \u00b6 jsPsych . randomization . sampleBernoulli ( p ) Parameters \u00b6 Parameter Type Description p number Probability of sampling 1 Return value \u00b6 Returns 0 with probability 1-p and 1 with probability p . Description \u00b6 Generates a random sample from a Bernoulli distribution. Examples \u00b6 Sample a value \u00b6 if ( jsPsych . randomization . sampleBernoulli ( 0.8 )){ // this happens 80% of the time } else { // this happens 20% of the time } jsPsych.randomization.sampleExGaussian \u00b6 jsPsych . randomization . sampleExGaussian ( mean , standard_deviation , rate , positive = false ) Parameters \u00b6 Parameter Type Description mean number Mean of the normal distribution component of the exGaussian standard_deviation number Standard deviation of the normal distribution component of the exGaussian rate number Rate of the exponential distribution component of the exGaussian positive bool If true sample will be constrained to > 0. Return value \u00b6 A random sample from the distribution Description \u00b6 Generates a random sample from an exponentially modified Gaussian distribution. Examples \u00b6 Sample a value \u00b6 var rand_sample_exg = jsPsych . randomization . sampleExGaussian ( 500 , 100 , 0.01 ); jsPsych.randomization.sampleExponential \u00b6 jsPsych . randomization . sampleExponential ( rate ) Parameters \u00b6 Parameter Type Description rate number Rate of the exponential distribution Return value \u00b6 A random sample from the distribution Description \u00b6 Generates a random sample from an exponential distribution. Examples \u00b6 Sample a value \u00b6 var rand_sample_exg = jsPsych . randomization . sampleExponential ( 0.01 ); jsPsych.randomization.sampleNormal \u00b6 jsPsych . randomization . sampleNormal ( mean , standard_deviation ) Parameters \u00b6 Parameter Type Description mean number Mean of the normal distribution standard_deviation number Standard deviation of the normal distribution Return value \u00b6 A random sample from the distribution Description \u00b6 Generates a random sample from a normal distribution. Examples \u00b6 Sample a value \u00b6 var rand_sample_exg = jsPsych . randomization . sampleNormal ( 500 , 250 ); jsPsych.randomization.sampleWithReplacement \u00b6 jsPsych . randomization . sampleWithReplacement ( array , sampleSize , weights ) Parameters \u00b6 Parameter Type Description array array The array of values to sample from sampleSize numeric The number of samples to draw weights array The relative weight of each element in array . This array is normalized, so the values do not need to sum to 1. The length must match the length of array . Return value \u00b6 An array containing the sample. Description \u00b6 This method returns a sample drawn at random from a set of values with replacement. The relative probability of drawing each item can be controlled by specifying the weights . Examples \u00b6 Sample with equal probability \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithReplacement ( myArray , 10 ); // output: sample = [3, 1, 2, 2, 5, 1, 4, 3, 1, 5]; Sample with unequal probability \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithReplacement ( myArray , 10 , [ 6 , 1 , 1 , 1 , 1 ]); // output: sample = [3, 4, 5, 1, 2, 1, 3, 1, 1, 1]; jsPsych.randomization.sampleWithoutReplacement \u00b6 jsPsych . randomization . sampleWithoutReplacement ( array , sampleSize ) Parameters \u00b6 Parameter Type Description array array The array of values to sample from sampleSize numeric The number of samples to draw Return value \u00b6 An array containing the sample. Description \u00b6 This method returns a sample drawn at random from a set of values without replacement. The sample size must be less than or equal to the length of the array. Examples \u00b6 Sample without replacement \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithoutReplacement ( myArray , 2 ); // output: sample = [3,2]; jsPsych.randomization.setSeed \u00b6 jsPsych . randomization . setSeed ( seed ) Parameters \u00b6 Parameter Type Description seed string A seed for the random number generator Return value \u00b6 Returns the seed value. Description \u00b6 This function will override the behavior of Math.random() to produce a seedable pseudo random number generator. It uses the seedrandom package . Note that calling setSeed() will change how Math.random() behaves for the entire document. If you have non-jsPsych components on the page that use Math.random() they will be affected. Using setSeed() without passing in a seed will generate a random 32-bit seed. The seed value will be returned from the function call, allowing you to save it in the data for the experiment if needed. Examples \u00b6 Use a random 32-bit seed and save to data \u00b6 const seed = jsPsych . randomization . setSeed (); jsPsych . data . addProperties ({ rng_seed : seed }); Use your own seed \u00b6 jsPsych . randomization . setSeed ( \"jspsych\" ); jsPsych.randomization.shuffle \u00b6 jsPsych . randomization . shuffle ( array ) Parameters \u00b6 Parameter Type Description array array The array of values to shuffle Return value \u00b6 Returns an array with the same elements as the input array in a random order. Description \u00b6 A simple method for shuffling the order of an array. Examples \u00b6 Shuffle an array \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . shuffle ( myArray ); // output: shuffledArray = [3,2,4,1,5] jsPsych.randomization.shuffleNoRepeats \u00b6 jsPsych . randomization . shuffleNoRepeats ( array , equalityTest ) Parameters \u00b6 Parameter Type Description array array The array of values to shuffle equalityTest function A function to use to evaluate the equality of neighbors in the array. The function should accept two parameters, which are the two elements to be tested. It should return true if they are equal and false if not. The default function, if none is specified, is to use the === operator. This will work for primitive values, but fail for Objects and Arrays. An example function is given below in the examples. Return value \u00b6 Returns an array with the same elements as the input array in a random order, with no repeating neighbors. Description \u00b6 Shuffle an array, ensuring that neighboring elements in the array are different. Warning: if you provide an array that has very few valid permutations with no neighboring elements, then this method will fail and cause the browser to hang. Examples \u00b6 Basic example \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . shuffleNoRepeats ( myArray ); // output: shuffledArray = [2, 3, 5, 1, 2, 4, 1, 5, 4, 1, 3, 5, 4, 3, 2] Custom equalityTest \u00b6 var myObjects = [ { color : \"blue\" }, { color : \"red\" }, { color : \"yellow\" }, { color : \"orange\" } ]; var repeatedSet = jsPsych . randomization . repeat ( myObjects , 3 ); var shuffled = jsPsych . randomization . shuffleNoRepeats ( repeatedSet , function ( a , b ) { return a . color === b . color }); // console.log(JSON.stringify(shuffled)) // \"[{\"color\":\"red\"},{\"color\":\"yellow\"},{\"color\":\"blue\"},{\"color\":\"yellow\"},{\"color\":\"orange\"},{\"color\":\"red\"},{\"color\":\"yellow\"},{\"color\":\"orange\"},{\"color\":\"blue\"},{\"color\":\"orange\"},{\"color\":\"red\"},{\"color\":\"blue\"}]\"","title":"jsPsych.randomization"},{"location":"reference/jspsych-randomization/#jspsychrandomization","text":"The jsPsych.randomization module contains methods that are useful for generating random lists of trial variables.","title":"jsPsych.randomization"},{"location":"reference/jspsych-randomization/#jspsychrandomizationfactorial","text":"jsPsych . randomization . factorial ( factors , repetitions , unpack )","title":"jsPsych.randomization.factorial"},{"location":"reference/jspsych-randomization/#parameters","text":"Parameter Type Description factors object The factors object should contain a property for each different factor. Each property-factor should have a value of an array, with each element of the array corresponding to a level of the factor. repetitions integer The number of times to repeat each unique combination of the factors in the output sample. unpack boolean If true then the output will be an object with a property for each factor in the original factors object. The value of each property-factor will be an array containing the levels of the factor in a random order. The order will be consistent across each property-factor (e.g., the first element of each property-factor will specify one unique combination of the factors). If false , then the return value will be an array of objects where each property-factor contains only a single value.","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value","text":"The return value depends on the unpack parameter. See description of the parameter above, and examples below.","title":"Return value"},{"location":"reference/jspsych-randomization/#description","text":"This method takes a list of factors and their levels, and creates a full factorial design by creating each unique combination of the factors. The returned set of combinations is in a random order.","title":"Description"},{"location":"reference/jspsych-randomization/#examples","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#create-full-factorial-design","text":"var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 1 ); /* output: full_design = [ {stimulus: 'a.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 100}, ] */","title":"Create full factorial design"},{"location":"reference/jspsych-randomization/#create-full-factorial-design-with-repeats","text":"var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 2 ); /* output: full_design = [ {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'a.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 200}, ] */","title":"Create full factorial design with repeats"},{"location":"reference/jspsych-randomization/#create-full-factorial-design-unpacked","text":"var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 1 , true ); /* output: full_design = { stimulus: ['a.jpg','b.jpg','b.jpg','a.jpg'], ms_delay: [200, 100, 200, 100] ] */","title":"Create full factorial design, unpacked"},{"location":"reference/jspsych-randomization/#jspsychrandomizationrandomid","text":"jsPsych . randomization . randomID ( length )","title":"jsPsych.randomization.randomID"},{"location":"reference/jspsych-randomization/#parameters_1","text":"Parameter Type Description length integer The length of the randomly generated ID","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_1","text":"Returns a string of length length where each character is randomly selected from the numbers 0-9 and all lowercase English letters a-z.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_1","text":"Generates a random string that is likely to be unique. If length is undefined, then the string length is 32.","title":"Description"},{"location":"reference/jspsych-randomization/#example","text":"console . log ( jsPsych . randomization . randomID ()); // outputs: \"t7dwz0e713pc8juuaayyfvpkdd9un239\" console . log ( jsPsych . randomization . randomID ( 8 )); // outputs: \"3xtpcbck\"","title":"Example"},{"location":"reference/jspsych-randomization/#jspsychrandomizationrandomint","text":"jsPsych . randomization . randomInt ( lower , upper )","title":"jsPsych.randomization.randomInt"},{"location":"reference/jspsych-randomization/#parameters_2","text":"Parameter Type Description lower integer The smallest value it is possible to generate upper integer The largest value it is possible to generate","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_2","text":"An integer","title":"Return value"},{"location":"reference/jspsych-randomization/#description_2","text":"Generates a random integer from lower to upper","title":"Description"},{"location":"reference/jspsych-randomization/#example_1","text":"console . log ( jsPsych . randomization . randomInt ( 2 , 4 )); // outputs: 2 or 3 or 4.","title":"Example"},{"location":"reference/jspsych-randomization/#jspsychrandomizationrepeat","text":"jsPsych . randomization . repeat ( array , repetitions , unpack )","title":"jsPsych.randomization.repeat"},{"location":"reference/jspsych-randomization/#parameters_3","text":"Parameter Type Description array array The array of values to randomize & repeat. repetitions integer or array The number of times to repeat each element of the array in the final sample. If this parameter is defined as an integer, then each element of array is repeated the same number of times. This parameter can also be an array of the same length as array , in which case each element of array will be repeated the number of times defined in the corresponding position of the repetitions array. unpack boolean If each element of array is an object with an equivalent set of properties, then setting unpack to true will make the return value an object with a property for each of the unique properties among the elements of the array . Each property in the output object will be an array containing the values for that property in the randomized order. The order will be consistent across properties. If this is false then the output is just an array containing a randomized order of the original array elements.","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_3","text":"The return value depends on the unpack parameter. See description of the parameter above, and examples below.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_3","text":"This method takes an array of values and generates a new random order of the array, with the option of repeating each element of the array a specified number of times. If the array elements are objects with the same set of properties, then this method can optionally return a single object where each property is a randomized order of the properties defined in the original set of objects. This is useful for randomizing sets of parameters that are used to define a jsPsych block.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_1","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#shuffle-an-array-no-repeats","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 1 ); // output: shuffledArray = [3,2,4,1,5]","title":"Shuffle an array, no repeats"},{"location":"reference/jspsych-randomization/#shuffle-an-array-with-repeats","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 ); // output: shuffledArray = [1,3,4,2,2,4,5,1,5,3]","title":"Shuffle an array with repeats"},{"location":"reference/jspsych-randomization/#shuffle-an-array-of-objects","text":"var trial1 = { stimulus : 'img/faceA.jpg' , correct_key : 'p' , person_name : 'Joe' } var trial2 = { stimulus : 'img/faceB.jpg' , correct_key : 'p' , person_name : 'Fred' } var trial3 = { stimulus : 'img/faceC.jpg' , correct_key : 'q' , person_name : 'Mary' } var myArray = [ trial1 , trial2 , trial3 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 ); // output: shuffledArray = [ trial1, trial3, trial3, trial2, trial1, trial2 ]","title":"Shuffle an array of objects"},{"location":"reference/jspsych-randomization/#shuffle-an-array-of-objects-with-unpack","text":"var trial1 = { stimulus : 'img/faceA.jpg' , correct_key : 'p' , person_name : 'Joe' } var trial2 = { stimulus : 'img/faceB.jpg' , correct_key : 'p' , person_name : 'Fred' } var trial3 = { stimulus : 'img/faceC.jpg' , correct_key : 'q' , person_name : 'Mary' } var myArray = [ trial1 , trial2 , trial3 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 , true ); /* output: shuffledArray = { stimulus: ['img/faceB.jpg','img/faceA.jpg','img/faceC.jpg','img/faceA.jpg','img/faceC.jpg','img/faceB.jpg'], correct_key: ['p', 'p', 'q', 'p', 'q', 'p'], person_name: ['Fred', 'Joe', 'Mary', 'Joe', 'Mary', 'Fred'] } */","title":"Shuffle an array of objects, with unpack"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsamplebernoulli","text":"jsPsych . randomization . sampleBernoulli ( p )","title":"jsPsych.randomization.sampleBernoulli"},{"location":"reference/jspsych-randomization/#parameters_4","text":"Parameter Type Description p number Probability of sampling 1","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_4","text":"Returns 0 with probability 1-p and 1 with probability p .","title":"Return value"},{"location":"reference/jspsych-randomization/#description_4","text":"Generates a random sample from a Bernoulli distribution.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_2","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-a-value","text":"if ( jsPsych . randomization . sampleBernoulli ( 0.8 )){ // this happens 80% of the time } else { // this happens 20% of the time }","title":"Sample a value"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsampleexgaussian","text":"jsPsych . randomization . sampleExGaussian ( mean , standard_deviation , rate , positive = false )","title":"jsPsych.randomization.sampleExGaussian"},{"location":"reference/jspsych-randomization/#parameters_5","text":"Parameter Type Description mean number Mean of the normal distribution component of the exGaussian standard_deviation number Standard deviation of the normal distribution component of the exGaussian rate number Rate of the exponential distribution component of the exGaussian positive bool If true sample will be constrained to > 0.","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_5","text":"A random sample from the distribution","title":"Return value"},{"location":"reference/jspsych-randomization/#description_5","text":"Generates a random sample from an exponentially modified Gaussian distribution.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_3","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-a-value_1","text":"var rand_sample_exg = jsPsych . randomization . sampleExGaussian ( 500 , 100 , 0.01 );","title":"Sample a value"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsampleexponential","text":"jsPsych . randomization . sampleExponential ( rate )","title":"jsPsych.randomization.sampleExponential"},{"location":"reference/jspsych-randomization/#parameters_6","text":"Parameter Type Description rate number Rate of the exponential distribution","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_6","text":"A random sample from the distribution","title":"Return value"},{"location":"reference/jspsych-randomization/#description_6","text":"Generates a random sample from an exponential distribution.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_4","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-a-value_2","text":"var rand_sample_exg = jsPsych . randomization . sampleExponential ( 0.01 );","title":"Sample a value"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsamplenormal","text":"jsPsych . randomization . sampleNormal ( mean , standard_deviation )","title":"jsPsych.randomization.sampleNormal"},{"location":"reference/jspsych-randomization/#parameters_7","text":"Parameter Type Description mean number Mean of the normal distribution standard_deviation number Standard deviation of the normal distribution","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_7","text":"A random sample from the distribution","title":"Return value"},{"location":"reference/jspsych-randomization/#description_7","text":"Generates a random sample from a normal distribution.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_5","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-a-value_3","text":"var rand_sample_exg = jsPsych . randomization . sampleNormal ( 500 , 250 );","title":"Sample a value"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsamplewithreplacement","text":"jsPsych . randomization . sampleWithReplacement ( array , sampleSize , weights )","title":"jsPsych.randomization.sampleWithReplacement"},{"location":"reference/jspsych-randomization/#parameters_8","text":"Parameter Type Description array array The array of values to sample from sampleSize numeric The number of samples to draw weights array The relative weight of each element in array . This array is normalized, so the values do not need to sum to 1. The length must match the length of array .","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_8","text":"An array containing the sample.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_8","text":"This method returns a sample drawn at random from a set of values with replacement. The relative probability of drawing each item can be controlled by specifying the weights .","title":"Description"},{"location":"reference/jspsych-randomization/#examples_6","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-with-equal-probability","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithReplacement ( myArray , 10 ); // output: sample = [3, 1, 2, 2, 5, 1, 4, 3, 1, 5];","title":"Sample with equal probability"},{"location":"reference/jspsych-randomization/#sample-with-unequal-probability","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithReplacement ( myArray , 10 , [ 6 , 1 , 1 , 1 , 1 ]); // output: sample = [3, 4, 5, 1, 2, 1, 3, 1, 1, 1];","title":"Sample with unequal probability"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsamplewithoutreplacement","text":"jsPsych . randomization . sampleWithoutReplacement ( array , sampleSize )","title":"jsPsych.randomization.sampleWithoutReplacement"},{"location":"reference/jspsych-randomization/#parameters_9","text":"Parameter Type Description array array The array of values to sample from sampleSize numeric The number of samples to draw","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_9","text":"An array containing the sample.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_9","text":"This method returns a sample drawn at random from a set of values without replacement. The sample size must be less than or equal to the length of the array.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_7","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-without-replacement","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithoutReplacement ( myArray , 2 ); // output: sample = [3,2];","title":"Sample without replacement"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsetseed","text":"jsPsych . randomization . setSeed ( seed )","title":"jsPsych.randomization.setSeed"},{"location":"reference/jspsych-randomization/#parameters_10","text":"Parameter Type Description seed string A seed for the random number generator","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_10","text":"Returns the seed value.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_10","text":"This function will override the behavior of Math.random() to produce a seedable pseudo random number generator. It uses the seedrandom package . Note that calling setSeed() will change how Math.random() behaves for the entire document. If you have non-jsPsych components on the page that use Math.random() they will be affected. Using setSeed() without passing in a seed will generate a random 32-bit seed. The seed value will be returned from the function call, allowing you to save it in the data for the experiment if needed.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_8","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#use-a-random-32-bit-seed-and-save-to-data","text":"const seed = jsPsych . randomization . setSeed (); jsPsych . data . addProperties ({ rng_seed : seed });","title":"Use a random 32-bit seed and save to data"},{"location":"reference/jspsych-randomization/#use-your-own-seed","text":"jsPsych . randomization . setSeed ( \"jspsych\" );","title":"Use your own seed"},{"location":"reference/jspsych-randomization/#jspsychrandomizationshuffle","text":"jsPsych . randomization . shuffle ( array )","title":"jsPsych.randomization.shuffle"},{"location":"reference/jspsych-randomization/#parameters_11","text":"Parameter Type Description array array The array of values to shuffle","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_11","text":"Returns an array with the same elements as the input array in a random order.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_11","text":"A simple method for shuffling the order of an array.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_9","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#shuffle-an-array","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . shuffle ( myArray ); // output: shuffledArray = [3,2,4,1,5]","title":"Shuffle an array"},{"location":"reference/jspsych-randomization/#jspsychrandomizationshufflenorepeats","text":"jsPsych . randomization . shuffleNoRepeats ( array , equalityTest )","title":"jsPsych.randomization.shuffleNoRepeats"},{"location":"reference/jspsych-randomization/#parameters_12","text":"Parameter Type Description array array The array of values to shuffle equalityTest function A function to use to evaluate the equality of neighbors in the array. The function should accept two parameters, which are the two elements to be tested. It should return true if they are equal and false if not. The default function, if none is specified, is to use the === operator. This will work for primitive values, but fail for Objects and Arrays. An example function is given below in the examples.","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_12","text":"Returns an array with the same elements as the input array in a random order, with no repeating neighbors.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_12","text":"Shuffle an array, ensuring that neighboring elements in the array are different. Warning: if you provide an array that has very few valid permutations with no neighboring elements, then this method will fail and cause the browser to hang.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_10","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#basic-example","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . shuffleNoRepeats ( myArray ); // output: shuffledArray = [2, 3, 5, 1, 2, 4, 1, 5, 4, 1, 3, 5, 4, 3, 2]","title":"Basic example"},{"location":"reference/jspsych-randomization/#custom-equalitytest","text":"var myObjects = [ { color : \"blue\" }, { color : \"red\" }, { color : \"yellow\" }, { color : \"orange\" } ]; var repeatedSet = jsPsych . randomization . repeat ( myObjects , 3 ); var shuffled = jsPsych . randomization . shuffleNoRepeats ( repeatedSet , function ( a , b ) { return a . color === b . color }); // console.log(JSON.stringify(shuffled)) // \"[{\"color\":\"red\"},{\"color\":\"yellow\"},{\"color\":\"blue\"},{\"color\":\"yellow\"},{\"color\":\"orange\"},{\"color\":\"red\"},{\"color\":\"yellow\"},{\"color\":\"orange\"},{\"color\":\"blue\"},{\"color\":\"orange\"},{\"color\":\"red\"},{\"color\":\"blue\"}]\"","title":"Custom equalityTest"},{"location":"reference/jspsych-turk/","text":"jsPsych.turk \u00b6 The jsPsych.turk module contains functions for interacting with Mechanical Turk. jsPsych.turk.submitToTurk \u00b6 jsPsych . turk . submitToTurk ( data ) Parameters \u00b6 Parameter Type Description data object The data parameter is an object of key: value pairs. Any pairs in the data parameter will be saved by Mechanical Turk, and can be downloaded in a CSV file through the Mechanical Turk interface. Important : the data parameter must contain at least one key: value pair, even just a dummy value, or the HIT will not be submitted correctly. Return value \u00b6 Returns nothing. Description \u00b6 This method will submit a HIT to Mechanical Turk, causing the HIT to finish. This method will only work when called from within the mechanical turk website. If you are using an external HIT to send workers to your own server, this method will not work on an externally hosted page. It will work if your external content is loaded in the iframe on the Mechanical Turk website. Example \u00b6 < p > Enter the code you were given: </ p > < input type = \"text\" id = \"code\" ></ input > < button onclick = \"sendData();\" > Submit HIT </ button > < script > // this content must be loaded in the iframe on the mechanical turk website. // usually, this means that the content is part of your 'recruitment ad', the // page the workers can see when they are deciding whether or not to accept a HIT. // one option is to include a simple form on this page that workers submit, with a // special code that they get at the end of the experiment. function sendData () { jsPsych . turk . submitToTurk ({ code : document . getElementById ( 'code' ). value }); } </ script > jsPsych.turk.turkInfo \u00b6 jsPsych . turk . turkInfo () Parameters \u00b6 None. Return value \u00b6 Returns an object with six properties: .assignmentId contains the assignment ID string of the HIT. .hitId contains the HIT ID. .workerId contains the worker ID of the worker completing the HIT. .turkSubmitTo contains the URL for submitting the HIT. This parameter is used in the jsPsych.turk.submitToTurk method, and is probably not useful outside of that context. .previewMode is a boolean value indicating whether or not the worker has accepted the HIT yet. If the page is viewed inside Mechancial Turk and the worker has not clicked 'Accept HIT' then this will be true. If the page is viewed outside Mechanical Turk or the worker has acccepted the HIT, then it will be false. .outsideTurk is a boolean value indicating if the page is being viewed within Mechanical Turk, or if it is being viewed from another source (e.g., someone directly going to the page URL instead of going through mturk). Description \u00b6 This method returns basic information about the current Mechanical Turk session, including the worker ID, assignment ID, and HIT ID. Example \u00b6 var turkInfo = jsPsych . turk . turkInfo (); alert ( 'Worker ID is: ' + turkInfo . workerId ); alert ( 'Assignment ID is: ' + turkInfo . assignmentId ); alert ( 'HIT ID is: ' + turkInfo . hitId ); // true if the page is viewed within Mechanical Turk, // but worker has not accepted the HIT yet. // false if the page is viewed outside Mechanical Turk, // OR the worker has accepted the HIT. alert ( 'Preview mode? ' + turkInfo . previewMode ); // true if the page is viewed outside mechanical turk, // false otherwise. alert ( 'Outside turk? ' + turkInfo . outsideTurk );","title":"jsPsych.turk"},{"location":"reference/jspsych-turk/#jspsychturk","text":"The jsPsych.turk module contains functions for interacting with Mechanical Turk.","title":"jsPsych.turk"},{"location":"reference/jspsych-turk/#jspsychturksubmittoturk","text":"jsPsych . turk . submitToTurk ( data )","title":"jsPsych.turk.submitToTurk"},{"location":"reference/jspsych-turk/#parameters","text":"Parameter Type Description data object The data parameter is an object of key: value pairs. Any pairs in the data parameter will be saved by Mechanical Turk, and can be downloaded in a CSV file through the Mechanical Turk interface. Important : the data parameter must contain at least one key: value pair, even just a dummy value, or the HIT will not be submitted correctly.","title":"Parameters"},{"location":"reference/jspsych-turk/#return-value","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-turk/#description","text":"This method will submit a HIT to Mechanical Turk, causing the HIT to finish. This method will only work when called from within the mechanical turk website. If you are using an external HIT to send workers to your own server, this method will not work on an externally hosted page. It will work if your external content is loaded in the iframe on the Mechanical Turk website.","title":"Description"},{"location":"reference/jspsych-turk/#example","text":"< p > Enter the code you were given: </ p > < input type = \"text\" id = \"code\" ></ input > < button onclick = \"sendData();\" > Submit HIT </ button > < script > // this content must be loaded in the iframe on the mechanical turk website. // usually, this means that the content is part of your 'recruitment ad', the // page the workers can see when they are deciding whether or not to accept a HIT. // one option is to include a simple form on this page that workers submit, with a // special code that they get at the end of the experiment. function sendData () { jsPsych . turk . submitToTurk ({ code : document . getElementById ( 'code' ). value }); } </ script >","title":"Example"},{"location":"reference/jspsych-turk/#jspsychturkturkinfo","text":"jsPsych . turk . turkInfo ()","title":"jsPsych.turk.turkInfo"},{"location":"reference/jspsych-turk/#parameters_1","text":"None.","title":"Parameters"},{"location":"reference/jspsych-turk/#return-value_1","text":"Returns an object with six properties: .assignmentId contains the assignment ID string of the HIT. .hitId contains the HIT ID. .workerId contains the worker ID of the worker completing the HIT. .turkSubmitTo contains the URL for submitting the HIT. This parameter is used in the jsPsych.turk.submitToTurk method, and is probably not useful outside of that context. .previewMode is a boolean value indicating whether or not the worker has accepted the HIT yet. If the page is viewed inside Mechancial Turk and the worker has not clicked 'Accept HIT' then this will be true. If the page is viewed outside Mechanical Turk or the worker has acccepted the HIT, then it will be false. .outsideTurk is a boolean value indicating if the page is being viewed within Mechanical Turk, or if it is being viewed from another source (e.g., someone directly going to the page URL instead of going through mturk).","title":"Return value"},{"location":"reference/jspsych-turk/#description_1","text":"This method returns basic information about the current Mechanical Turk session, including the worker ID, assignment ID, and HIT ID.","title":"Description"},{"location":"reference/jspsych-turk/#example_1","text":"var turkInfo = jsPsych . turk . turkInfo (); alert ( 'Worker ID is: ' + turkInfo . workerId ); alert ( 'Assignment ID is: ' + turkInfo . assignmentId ); alert ( 'HIT ID is: ' + turkInfo . hitId ); // true if the page is viewed within Mechanical Turk, // but worker has not accepted the HIT yet. // false if the page is viewed outside Mechanical Turk, // OR the worker has accepted the HIT. alert ( 'Preview mode? ' + turkInfo . previewMode ); // true if the page is viewed outside mechanical turk, // false otherwise. alert ( 'Outside turk? ' + turkInfo . outsideTurk );","title":"Example"},{"location":"reference/jspsych/","text":"jsPsych \u00b6 initJsPsych \u00b6 var jsPsych = initJsPsych ( settings ); Parameters \u00b6 Parameter Type Description settings object The settings object for initializing jsPsych. See table below. The settings object can contain several parameters. None of the parameters are required. Parameter Type Description display_element string The ID of an HTML element to display the experiment in. If left blank, jsPsych will use the <body> element to display content. All keyboard event listeners are bound to this element. In order for a keyboard event to be detected, this element must have focus (be the last thing that the participant clicked on). on_finish function Function to execute when the experiment ends. on_trial_start function Function to execute when a new trial begins. on_trial_finish function Function to execute when a trial ends. on_data_update function Function to execute every time data is stored using the jsPsych.data.write method. All plugins use this method to save data (via a call to jsPsych.finishTrial , so this function runs every time a plugin stores new data. on_interaction_data_update function Function to execute every time a new interaction event occurs. Interaction events include clicking on a different window (blur), returning to the experiment window (focus), entering full screen mode (fullscreenenter), and exiting full screen mode (fullscreenexit). on_close function Function to execute when the user leaves the page. Can be used, for example, to save data before the page is closed. exclusions object Specifies restrictions on the browser the participant can use to complete the experiment. See list of options below. This feature is deprecated as of v7.1 and will be removed in v8.0. The browser-check plugin is an improved way to handle exclusions. show_progress_bar boolean If true , then a progress bar is shown at the top of the page. Default is false . message_progress_bar string Message to display next to the progress bar. The default is 'Completion Progress'. auto_update_progress_bar boolean If true, then the progress bar at the top of the page will automatically update as every top-level timeline or trial is completed. use_webaudio boolean If false, then jsPsych will not attempt to use the WebAudio API for audio playback. Instead, HTML5 Audio objects will be used. The WebAudio API offers more precise control over the timing of audio events, and should be used when possible. The default value is true . default_iti numeric The default inter-trial interval in ms. The default value if none is specified is 0ms. experiment_width numeric The desired width of the jsPsych container in pixels. If left undefined, the width will be 100% of the display element. Usually this is the <body> element, and the width will be 100% of the screen size. minimum_valid_rt numeric The minimum valid response time for key presses during the experiment. Any key press response time that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to keyboard responses , and not to other response types such as buttons and sliders. The default value is 0. override_safe_mode boolean Running a jsPsych experiment directly in a web browser (e.g., by double clicking on a local HTML file) will load the page using the file:// protocol. Some features of jsPsych don't work with this protocol. By default, when jsPsych detects that it's running on a page loaded via the file:// protocol, it runs in safe mode , which automatically disables features that don't work in this context. Specifically, the use of Web Audio is disabled (audio will be played using HTML5 audio instead, even if use_webaudio is true ) and video preloading is disabled. The override_safe_mode parameter defaults to false , but you can set it to true to force these features to operate under the file:// protocol. In order for this to work, you will need to disable web security (CORS) features in your browser - this is safe to do if you know what you are doing. Note that this parameter has no effect when you are running the experiment on a web server, because the page will be loaded via the http:// or https:// protocol. case_sensitive_responses boolean If true , then jsPsych will make a distinction between uppercase and lowercase keys when evaluating keyboard responses, e.g. \"A\" (uppercase) will not be recognized as a valid response if the trial only accepts \"a\" (lowercase). If false, then jsPsych will not make a distinction between uppercase and lowercase keyboard responses, e.g. both \"a\" and \"A\" responses will be valid when the trial's key choice parameter is \"a\". Setting this parameter to false is useful if you want key responses to be treated the same way when CapsLock is turned on or the Shift key is held down. The default value is false . extensions array Array containing information about one or more jsPsych extensions that are used during the experiment. Each extension should be specified as an object with type (required), which is the name of the extension, and params (optional), which is an object containing any parameter-value pairs to be passed to the extension's initialize function. Default value is an empty array. Possible values for the exclusions parameter above. Parameter Type Description min_width numeric The minimum width of the browser window. If the width is below this value, a message will be displayed to the participant asking them to maximize their browser window. The experiment will sit on this page until the browser window is large enough. min_height numeric Same as above, but with height. audio boolean Set to true to require support for the WebAudio API (used by plugins that play audio files). Return value \u00b6 Returns a jsPsych instance, which all jsPsych methods on this page are called on. Therefore it is not possible to call any of the jsPsych methods listed on this page until this initJsPsych function is called and a jsPsych instance is created. Description \u00b6 This function initializes jsPsych with the specified experiment settings. Example \u00b6 var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); }, show_progress_bar : true , default_iti : 500 }); For more examples, see the HTML files in the examples folder . jsPsych.addNodeToEndOfTimeline \u00b6 jsPsych . addNodeToEndOfTimeline ( node_parameters ) Parameters \u00b6 Parameter Type Description node_parameters object An object defining a timeline. It must have, at a minimum, a timeline parameter with a valid timeline array as the value for that parameter. Return value \u00b6 None. Description \u00b6 Adds the timeline to the end of the experiment. Example \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is a new trial.' } var new_timeline = { timeline : [ trial ] } jsPsych . addNodeToEndOfTimeline ( new_timeline ) jsPsych.endCurrentTimeline \u00b6 jsPsych . endCurrentTimeline () Parameters \u00b6 None. Return value \u00b6 None. Description \u00b6 Ends the current timeline. If timelines are nested, then only the timeline that contains the current trial is ended. Example \u00b6 End timeline if a particular key is pressed \u00b6 var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); var images = [ \"img/1.gif\" , \"img/2.gif\" , \"img/3.gif\" , \"img/4.gif\" , \"img/5.gif\" , \"img/6.gif\" , \"img/7.gif\" , \"img/8.gif\" , \"img/9.gif\" , \"img/10.gif\" ]; var trials = []; for ( var i = 0 ; i < images . length ; i ++ ) { trials . push ({ stimulus : images [ i ] }); } var block = { type : jsPsychImageKeyboardResponse , choices : [ 'y' , 'n' ], prompt : '<p>Press \"y\" to Continue. Press \"n\" to end this node of the experiment.</p>' , on_finish : function ( data ) { if ( jsPsych . pluginAPI . compareKeys ( data . response , 'n' )) { jsPsych . endCurrentTimeline (); } }, timeline : trials } var after_block = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>The next node</p>' } jsPsych . run ([ block , after_block ]); jsPsych.endExperiment \u00b6 jsPsych . endExperiment ( end_message , data ) Parameters \u00b6 Parameter Type Description end_message string A message to display on the screen after the experiment is over. Can include HTML formatting. data object An optional object of key-value pairs to store as data in the final trial of the experiment. Return value \u00b6 None. Description \u00b6 Ends the experiment, skipping all remaining trials. If the on_finish event handler for jsPsych returns a Promise then the end_message will not be displayed until the promise is resolved. Example \u00b6 End the experiment if a particular response is given \u00b6 var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'image1.jpg' , choices : [ 'y' , 'n' ] prompt : '<p>Press \"y\" to Continue. Press \"n\" to end the experiment</p>' , on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"n\" )){ jsPsych . endExperiment ( 'The experiment was ended by pressing \"n\".' ); } } } jsPsych.finishTrial \u00b6 jsPsych . finishTrial ( data ) Parameters \u00b6 Parameter Type Description data object The data to store for the trial. Return value \u00b6 Returns nothing. Description \u00b6 This method tells jsPsych that the current trial is over. It is used in all of the plugins to end the current trial. When the trial ends a few things happen: The data is stored using jsPsych.data.write() The on_finish callback function is executed for the trial The on_trial_finish callback function is executed The progress bar is updated if it is being displayed The experiment ends if the trial is the last one (and the on_finish callback function is executed). The next trial, if one exists, is started. Example \u00b6 // this code would be in a plugin jsPsych . finishTrial ({ correct_response : true }); jsPsych.getAllTimelineVariables \u00b6 jsPsych . getAllTimelineVariables () Parameters \u00b6 None. Return value \u00b6 Returns an object with all available timeline variables at this moment in the experiment, represented as key: value pairs. Description \u00b6 This function can be used to get all the timeline variables at a particular moment in the experiment. Can be useful for annotating data, such as in the example below. Example \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Just a demo' , on_finish : function ( data ){ // merge all timeline variables available at this trial into the data for this trial Object . assign ( data , jsPsych . getAllTimelineVariables ()) } } jsPsych.getCurrentTimelineNodeID \u00b6 jsPsych . getCurrentTimelineNodeID () Parameters \u00b6 None. Return value \u00b6 Returns the ID of the TimelineNode that is currently active. Description \u00b6 Gets the ID of the active TimelineNode. The ID is a string that follows a specific format: \"0.0\" is the ID of the first top-level TimelineNode \"1.0\" is the ID of the second top-level TimelineNode \"2.0\" is the ID of the third top-level TimelineNode, and so on... If a TimelineNode iterates multiple times (using the loop function, for example), then the iterations are indicated in the second number: \"0.0\" is the ID of the first top-level TimelineNode during the first iteration \"0.1\" is the ID of the first top-level TimelineNode during the second iteration \"0.2\" is the ID of the first top-level TimelineNode during the third iteration, and so on... If TimelineNodes are nested in other TimelineNodes, then the hierarchical structure is shown with \"-\" : \"0.0-1.0\" is the ID of the second TimelineNode on the timeline of the first top-level TimelineNode. \"0.0-2.0\" is the ID of the third TimelineNode on the timeline of the first top-level TimelineNode, and so on... The rules about iterations apply throughout the hierarchical ID: \"0.2-1.3\" is the ID of the second TimelineNode, executing for the fourth time, on the timeline of the first top-level TimelineNode, executing for the third time. Example \u00b6 var id = jsPsych . getCurrentTimelineNodeID (); console . log ( 'The current TimelineNode ID is ' + id ); jsPsych.getCurrentTrial \u00b6 jsPsych . getCurrentTrial () Parameters \u00b6 None. Return value \u00b6 Returns the object describing the current trial. The object will contain all of the parameters associated with the current trial. Description \u00b6 Get a description of the current trial Example \u00b6 var trial = jsPsych . getCurrentTrial (); console . log ( 'The current trial is using the ' + trial . type + ' plugin' ); jsPsych.getDisplayElement \u00b6 jsPsych . getDisplayElement () Parameters \u00b6 None. Return value \u00b6 Returns the HTML DOM element used for displaying the experiment. Description \u00b6 Get the DOM element that displays the experiment. Example \u00b6 var el = jsPsych . getDisplayElement (); // hide the jsPsych display el . style . visibility = 'hidden' ; \u00b6 jsPsych.getInitSettings \u00b6 jsPsych . getInitSettings () Parameters \u00b6 None Return value \u00b6 Returns the settings object used to initialize the experiment. Description \u00b6 Gets the object containing the settings for the current experiment. Example \u00b6 var settings = jsPsych . getInitSettings (); // check the experiment structure console . log ( JSON . stringify ( settings . timeline )); jsPsych.getProgress \u00b6 jsPsych . getProgress () Parameters \u00b6 None. Return value \u00b6 Returns an object with the following properties: Property Type Description total_trials numeric Indicates the number of trials in the experiment. Note that this does not count possible loops or skipped trials due to conditional statements. current_trial_global numeric Returns the trial index of the current trial in a global scope. Every trial will increase this count by 1. percent_complete numeric Estimates the percent of the experiment that is complete. Works as expected for experiments without conditional or looping timelines. For complex timelines, the percent is an approximation. Description \u00b6 This method returns information about the length of the experiment and the participant's current location in the experiment timeline. Example \u00b6 var progress = jsPsych . getProgress (); alert ( 'You have completed approximately ' + progress . percent_complete + '% of the experiment' ); jsPsych.getProgressBarCompleted \u00b6 jsPsych . getProgressBarCompleted () Parameters \u00b6 None. Return value \u00b6 Returns a value between 0 and 1 representing how full the progress bar currently is. Description \u00b6 Used to get the current value of the progress bar. Works for automated and manual control. Example \u00b6 var progress_bar_amount = jsPsych . getProgressBarCompleted (); jsPsych.getStartTime \u00b6 jsPsych . getStartTime () Parameters \u00b6 None. Return value \u00b6 Returns a Date object indicating when the experiment began. Description \u00b6 Get the time that the experiment began. Example \u00b6 var start_time = jsPsych . getStartTime (); jsPsych.getTotalTime \u00b6 jsPsych . getTotalTime () Parameters \u00b6 None. Return value \u00b6 Returns a numeric value indicating the number of milliseconds since jsPsych.run was called. Description \u00b6 Gets the total time the participant has been in the experiment. Example \u00b6 var time = jsPsych . getTotalTime (); console . log ( time ); jsPsych.pauseExperiment \u00b6 jsPsych . pauseExperiment () Parameters \u00b6 None. Return value \u00b6 None. Description \u00b6 Pauses the experiment. The experiment will finish the current trial, but will not execute any additional trials until jsPsych.resumeExperiment() is called. Example \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press p to take a 30 second break. Otherwise, press c to continue immediately.' , choices : [ 'p' , 'c' ], on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"p\" )) { jsPsych . pauseExperiment (); setTimeout ( jsPsych . resumeExperiment , 30000 ); } } } jsPsych.resumeExperiment \u00b6 jsPsych . resumeExperiment () Parameters \u00b6 None. Return value \u00b6 None. Description \u00b6 Resumes the experiment after a call to jsPsych.pauseExperiment() . If the post trial delay ( post_trial_gap ) has not yet been reached, then the experiment will not continue until the delay is finished. For example, if post_trial_gap was 10,000ms and jsPsych.resumeExperiment() was called 6,000ms after the previous trial finished, then the experiment would not continue for another 4,000ms. Example \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press p to take a 30 second break. Otherwise, press c to continue immediately.' , choices : [ 'p' , 'c' ], on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"p\" )) { jsPsych . pauseExperiment (); setTimeout ( jsPsych . resumeExperiment , 30000 ); } } } jsPsych.run \u00b6 jsPsych . run ( timeline ) Parameters \u00b6 Parameter Type Description timeline array An array containing the objects that describe the experiment timeline. See Creating an Experiment: The Timeline . Return value \u00b6 None. Description \u00b6 Start the jsPsych experiment with the specified timeline. Example \u00b6 var timeline = [ trial1 , trial2 , trial3 ]; jsPsych . run ( timeline ); jsPsych.setProgressBar \u00b6 jsPsych . setProgressBar ( value ) Parameters \u00b6 Parameter Type Description value numeric Proprotion (between 0 and 1) to fill the progress bar. Return value \u00b6 None. Description \u00b6 Set the progress bar to a custom amount. Proportion must be between 0 and 1. Values larger than 1 are treated as 1. Example \u00b6 jsPsych . setProgressBar ( 0.85 ); jsPsych.timelineVariable \u00b6 jsPsych . timelineVariable ( variable , call_immediate ) Parameters \u00b6 Parameter Type Description variable string Name of the timeline variable call_immediate bool This parameter is optional and can usually be omitted. It determines the return value of jsPsych.timelineVariable . If true , the function returns the value of the current timeline variable. If false , the function returns a function that returns the value of the current timeline variable. When call_immediate is omitted, the appropriate option is determined automatically based on the context in which this function is called. When jsPsych.timelineVariable is used as a parameter value, call_immediate will be false . This allows it to be used as a dynamic trial parameter . When jsPsych.timelineVariable is used inside of a function, call_immediate will be true . It is possible to explicitly set this option to true to force the function to immediately return the current value of the timeline variable. Return value \u00b6 Either a function that returns the value of the timeline variable, or the value of the timeline variable, depending on the context in which it is used. See call_immediate description above. Description \u00b6 Timeline variables are a powerful technique for generating experiments with repetitive procedures but different parameter values. This function fetches the current value of a particular timeline variable. It must be used in conjunction with a timeline that has timeline variables. See the timeline variable section for details. Examples \u00b6 Standard use as a parameter for a trial \u00b6 var trial = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'image' ) } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] } Invoking immediately in a function \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ return \"<img style='width:100px; height:100px;' src='\" + jsPsych . timelineVariable ( 'image' ) + \"'></img>\" ; } } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] } Prior to jsPsych v6.3.0, the call_immediate parameter must be set to true when jsPsych.timelineVariable is called from within a function, such as a dynamic parameter : var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ return \"<img style='width:100px; height:100px;' src='\" + jsPsych . timelineVariable ( 'image' , true ) + \"'></img>\" ; } } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] } jsPsych.version \u00b6 jsPsych . version () Parameters \u00b6 None. Return value \u00b6 Returns the version number as a string. Description \u00b6 Gets the version of jsPsych. Example \u00b6 var version = jsPsych . version (); console . log ( version );","title":"jsPsych"},{"location":"reference/jspsych/#jspsych","text":"","title":"jsPsych"},{"location":"reference/jspsych/#initjspsych","text":"var jsPsych = initJsPsych ( settings );","title":"initJsPsych"},{"location":"reference/jspsych/#parameters","text":"Parameter Type Description settings object The settings object for initializing jsPsych. See table below. The settings object can contain several parameters. None of the parameters are required. Parameter Type Description display_element string The ID of an HTML element to display the experiment in. If left blank, jsPsych will use the <body> element to display content. All keyboard event listeners are bound to this element. In order for a keyboard event to be detected, this element must have focus (be the last thing that the participant clicked on). on_finish function Function to execute when the experiment ends. on_trial_start function Function to execute when a new trial begins. on_trial_finish function Function to execute when a trial ends. on_data_update function Function to execute every time data is stored using the jsPsych.data.write method. All plugins use this method to save data (via a call to jsPsych.finishTrial , so this function runs every time a plugin stores new data. on_interaction_data_update function Function to execute every time a new interaction event occurs. Interaction events include clicking on a different window (blur), returning to the experiment window (focus), entering full screen mode (fullscreenenter), and exiting full screen mode (fullscreenexit). on_close function Function to execute when the user leaves the page. Can be used, for example, to save data before the page is closed. exclusions object Specifies restrictions on the browser the participant can use to complete the experiment. See list of options below. This feature is deprecated as of v7.1 and will be removed in v8.0. The browser-check plugin is an improved way to handle exclusions. show_progress_bar boolean If true , then a progress bar is shown at the top of the page. Default is false . message_progress_bar string Message to display next to the progress bar. The default is 'Completion Progress'. auto_update_progress_bar boolean If true, then the progress bar at the top of the page will automatically update as every top-level timeline or trial is completed. use_webaudio boolean If false, then jsPsych will not attempt to use the WebAudio API for audio playback. Instead, HTML5 Audio objects will be used. The WebAudio API offers more precise control over the timing of audio events, and should be used when possible. The default value is true . default_iti numeric The default inter-trial interval in ms. The default value if none is specified is 0ms. experiment_width numeric The desired width of the jsPsych container in pixels. If left undefined, the width will be 100% of the display element. Usually this is the <body> element, and the width will be 100% of the screen size. minimum_valid_rt numeric The minimum valid response time for key presses during the experiment. Any key press response time that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to keyboard responses , and not to other response types such as buttons and sliders. The default value is 0. override_safe_mode boolean Running a jsPsych experiment directly in a web browser (e.g., by double clicking on a local HTML file) will load the page using the file:// protocol. Some features of jsPsych don't work with this protocol. By default, when jsPsych detects that it's running on a page loaded via the file:// protocol, it runs in safe mode , which automatically disables features that don't work in this context. Specifically, the use of Web Audio is disabled (audio will be played using HTML5 audio instead, even if use_webaudio is true ) and video preloading is disabled. The override_safe_mode parameter defaults to false , but you can set it to true to force these features to operate under the file:// protocol. In order for this to work, you will need to disable web security (CORS) features in your browser - this is safe to do if you know what you are doing. Note that this parameter has no effect when you are running the experiment on a web server, because the page will be loaded via the http:// or https:// protocol. case_sensitive_responses boolean If true , then jsPsych will make a distinction between uppercase and lowercase keys when evaluating keyboard responses, e.g. \"A\" (uppercase) will not be recognized as a valid response if the trial only accepts \"a\" (lowercase). If false, then jsPsych will not make a distinction between uppercase and lowercase keyboard responses, e.g. both \"a\" and \"A\" responses will be valid when the trial's key choice parameter is \"a\". Setting this parameter to false is useful if you want key responses to be treated the same way when CapsLock is turned on or the Shift key is held down. The default value is false . extensions array Array containing information about one or more jsPsych extensions that are used during the experiment. Each extension should be specified as an object with type (required), which is the name of the extension, and params (optional), which is an object containing any parameter-value pairs to be passed to the extension's initialize function. Default value is an empty array. Possible values for the exclusions parameter above. Parameter Type Description min_width numeric The minimum width of the browser window. If the width is below this value, a message will be displayed to the participant asking them to maximize their browser window. The experiment will sit on this page until the browser window is large enough. min_height numeric Same as above, but with height. audio boolean Set to true to require support for the WebAudio API (used by plugins that play audio files).","title":"Parameters"},{"location":"reference/jspsych/#return-value","text":"Returns a jsPsych instance, which all jsPsych methods on this page are called on. Therefore it is not possible to call any of the jsPsych methods listed on this page until this initJsPsych function is called and a jsPsych instance is created.","title":"Return value"},{"location":"reference/jspsych/#description","text":"This function initializes jsPsych with the specified experiment settings.","title":"Description"},{"location":"reference/jspsych/#example","text":"var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); }, show_progress_bar : true , default_iti : 500 }); For more examples, see the HTML files in the examples folder .","title":"Example"},{"location":"reference/jspsych/#jspsychaddnodetoendoftimeline","text":"jsPsych . addNodeToEndOfTimeline ( node_parameters )","title":"jsPsych.addNodeToEndOfTimeline"},{"location":"reference/jspsych/#parameters_1","text":"Parameter Type Description node_parameters object An object defining a timeline. It must have, at a minimum, a timeline parameter with a valid timeline array as the value for that parameter.","title":"Parameters"},{"location":"reference/jspsych/#return-value_1","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_1","text":"Adds the timeline to the end of the experiment.","title":"Description"},{"location":"reference/jspsych/#example_1","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is a new trial.' } var new_timeline = { timeline : [ trial ] } jsPsych . addNodeToEndOfTimeline ( new_timeline )","title":"Example"},{"location":"reference/jspsych/#jspsychendcurrenttimeline","text":"jsPsych . endCurrentTimeline ()","title":"jsPsych.endCurrentTimeline"},{"location":"reference/jspsych/#parameters_2","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_2","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_2","text":"Ends the current timeline. If timelines are nested, then only the timeline that contains the current trial is ended.","title":"Description"},{"location":"reference/jspsych/#example_2","text":"","title":"Example"},{"location":"reference/jspsych/#end-timeline-if-a-particular-key-is-pressed","text":"var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); var images = [ \"img/1.gif\" , \"img/2.gif\" , \"img/3.gif\" , \"img/4.gif\" , \"img/5.gif\" , \"img/6.gif\" , \"img/7.gif\" , \"img/8.gif\" , \"img/9.gif\" , \"img/10.gif\" ]; var trials = []; for ( var i = 0 ; i < images . length ; i ++ ) { trials . push ({ stimulus : images [ i ] }); } var block = { type : jsPsychImageKeyboardResponse , choices : [ 'y' , 'n' ], prompt : '<p>Press \"y\" to Continue. Press \"n\" to end this node of the experiment.</p>' , on_finish : function ( data ) { if ( jsPsych . pluginAPI . compareKeys ( data . response , 'n' )) { jsPsych . endCurrentTimeline (); } }, timeline : trials } var after_block = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>The next node</p>' } jsPsych . run ([ block , after_block ]);","title":"End timeline if a particular key is pressed"},{"location":"reference/jspsych/#jspsychendexperiment","text":"jsPsych . endExperiment ( end_message , data )","title":"jsPsych.endExperiment"},{"location":"reference/jspsych/#parameters_3","text":"Parameter Type Description end_message string A message to display on the screen after the experiment is over. Can include HTML formatting. data object An optional object of key-value pairs to store as data in the final trial of the experiment.","title":"Parameters"},{"location":"reference/jspsych/#return-value_3","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_3","text":"Ends the experiment, skipping all remaining trials. If the on_finish event handler for jsPsych returns a Promise then the end_message will not be displayed until the promise is resolved.","title":"Description"},{"location":"reference/jspsych/#example_3","text":"","title":"Example"},{"location":"reference/jspsych/#end-the-experiment-if-a-particular-response-is-given","text":"var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'image1.jpg' , choices : [ 'y' , 'n' ] prompt : '<p>Press \"y\" to Continue. Press \"n\" to end the experiment</p>' , on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"n\" )){ jsPsych . endExperiment ( 'The experiment was ended by pressing \"n\".' ); } } }","title":"End the experiment if a particular response is given"},{"location":"reference/jspsych/#jspsychfinishtrial","text":"jsPsych . finishTrial ( data )","title":"jsPsych.finishTrial"},{"location":"reference/jspsych/#parameters_4","text":"Parameter Type Description data object The data to store for the trial.","title":"Parameters"},{"location":"reference/jspsych/#return-value_4","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych/#description_4","text":"This method tells jsPsych that the current trial is over. It is used in all of the plugins to end the current trial. When the trial ends a few things happen: The data is stored using jsPsych.data.write() The on_finish callback function is executed for the trial The on_trial_finish callback function is executed The progress bar is updated if it is being displayed The experiment ends if the trial is the last one (and the on_finish callback function is executed). The next trial, if one exists, is started.","title":"Description"},{"location":"reference/jspsych/#example_4","text":"// this code would be in a plugin jsPsych . finishTrial ({ correct_response : true });","title":"Example"},{"location":"reference/jspsych/#jspsychgetalltimelinevariables","text":"jsPsych . getAllTimelineVariables ()","title":"jsPsych.getAllTimelineVariables"},{"location":"reference/jspsych/#parameters_5","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_5","text":"Returns an object with all available timeline variables at this moment in the experiment, represented as key: value pairs.","title":"Return value"},{"location":"reference/jspsych/#description_5","text":"This function can be used to get all the timeline variables at a particular moment in the experiment. Can be useful for annotating data, such as in the example below.","title":"Description"},{"location":"reference/jspsych/#example_5","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Just a demo' , on_finish : function ( data ){ // merge all timeline variables available at this trial into the data for this trial Object . assign ( data , jsPsych . getAllTimelineVariables ()) } }","title":"Example"},{"location":"reference/jspsych/#jspsychgetcurrenttimelinenodeid","text":"jsPsych . getCurrentTimelineNodeID ()","title":"jsPsych.getCurrentTimelineNodeID"},{"location":"reference/jspsych/#parameters_6","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_6","text":"Returns the ID of the TimelineNode that is currently active.","title":"Return value"},{"location":"reference/jspsych/#description_6","text":"Gets the ID of the active TimelineNode. The ID is a string that follows a specific format: \"0.0\" is the ID of the first top-level TimelineNode \"1.0\" is the ID of the second top-level TimelineNode \"2.0\" is the ID of the third top-level TimelineNode, and so on... If a TimelineNode iterates multiple times (using the loop function, for example), then the iterations are indicated in the second number: \"0.0\" is the ID of the first top-level TimelineNode during the first iteration \"0.1\" is the ID of the first top-level TimelineNode during the second iteration \"0.2\" is the ID of the first top-level TimelineNode during the third iteration, and so on... If TimelineNodes are nested in other TimelineNodes, then the hierarchical structure is shown with \"-\" : \"0.0-1.0\" is the ID of the second TimelineNode on the timeline of the first top-level TimelineNode. \"0.0-2.0\" is the ID of the third TimelineNode on the timeline of the first top-level TimelineNode, and so on... The rules about iterations apply throughout the hierarchical ID: \"0.2-1.3\" is the ID of the second TimelineNode, executing for the fourth time, on the timeline of the first top-level TimelineNode, executing for the third time.","title":"Description"},{"location":"reference/jspsych/#example_6","text":"var id = jsPsych . getCurrentTimelineNodeID (); console . log ( 'The current TimelineNode ID is ' + id );","title":"Example"},{"location":"reference/jspsych/#jspsychgetcurrenttrial","text":"jsPsych . getCurrentTrial ()","title":"jsPsych.getCurrentTrial"},{"location":"reference/jspsych/#parameters_7","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_7","text":"Returns the object describing the current trial. The object will contain all of the parameters associated with the current trial.","title":"Return value"},{"location":"reference/jspsych/#description_7","text":"Get a description of the current trial","title":"Description"},{"location":"reference/jspsych/#example_7","text":"var trial = jsPsych . getCurrentTrial (); console . log ( 'The current trial is using the ' + trial . type + ' plugin' );","title":"Example"},{"location":"reference/jspsych/#jspsychgetdisplayelement","text":"jsPsych . getDisplayElement ()","title":"jsPsych.getDisplayElement"},{"location":"reference/jspsych/#parameters_8","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_8","text":"Returns the HTML DOM element used for displaying the experiment.","title":"Return value"},{"location":"reference/jspsych/#description_8","text":"Get the DOM element that displays the experiment.","title":"Description"},{"location":"reference/jspsych/#example_8","text":"","title":"Example"},{"location":"reference/jspsych/#var-el-jspsychgetdisplayelement-hide-the-jspsych-display-elstylevisibility-hidden","text":"","title":"var el = jsPsych.getDisplayElement();\n\n// hide the jsPsych display\nel.style.visibility = &#39;hidden&#39;;\n"},{"location":"reference/jspsych/#jspsychgetinitsettings","text":"jsPsych . getInitSettings ()","title":"jsPsych.getInitSettings"},{"location":"reference/jspsych/#parameters_9","text":"None","title":"Parameters"},{"location":"reference/jspsych/#return-value_9","text":"Returns the settings object used to initialize the experiment.","title":"Return value"},{"location":"reference/jspsych/#description_9","text":"Gets the object containing the settings for the current experiment.","title":"Description"},{"location":"reference/jspsych/#example_9","text":"var settings = jsPsych . getInitSettings (); // check the experiment structure console . log ( JSON . stringify ( settings . timeline ));","title":"Example"},{"location":"reference/jspsych/#jspsychgetprogress","text":"jsPsych . getProgress ()","title":"jsPsych.getProgress"},{"location":"reference/jspsych/#parameters_10","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_10","text":"Returns an object with the following properties: Property Type Description total_trials numeric Indicates the number of trials in the experiment. Note that this does not count possible loops or skipped trials due to conditional statements. current_trial_global numeric Returns the trial index of the current trial in a global scope. Every trial will increase this count by 1. percent_complete numeric Estimates the percent of the experiment that is complete. Works as expected for experiments without conditional or looping timelines. For complex timelines, the percent is an approximation.","title":"Return value"},{"location":"reference/jspsych/#description_10","text":"This method returns information about the length of the experiment and the participant's current location in the experiment timeline.","title":"Description"},{"location":"reference/jspsych/#example_10","text":"var progress = jsPsych . getProgress (); alert ( 'You have completed approximately ' + progress . percent_complete + '% of the experiment' );","title":"Example"},{"location":"reference/jspsych/#jspsychgetprogressbarcompleted","text":"jsPsych . getProgressBarCompleted ()","title":"jsPsych.getProgressBarCompleted"},{"location":"reference/jspsych/#parameters_11","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_11","text":"Returns a value between 0 and 1 representing how full the progress bar currently is.","title":"Return value"},{"location":"reference/jspsych/#description_11","text":"Used to get the current value of the progress bar. Works for automated and manual control.","title":"Description"},{"location":"reference/jspsych/#example_11","text":"var progress_bar_amount = jsPsych . getProgressBarCompleted ();","title":"Example"},{"location":"reference/jspsych/#jspsychgetstarttime","text":"jsPsych . getStartTime ()","title":"jsPsych.getStartTime"},{"location":"reference/jspsych/#parameters_12","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_12","text":"Returns a Date object indicating when the experiment began.","title":"Return value"},{"location":"reference/jspsych/#description_12","text":"Get the time that the experiment began.","title":"Description"},{"location":"reference/jspsych/#example_12","text":"var start_time = jsPsych . getStartTime ();","title":"Example"},{"location":"reference/jspsych/#jspsychgettotaltime","text":"jsPsych . getTotalTime ()","title":"jsPsych.getTotalTime"},{"location":"reference/jspsych/#parameters_13","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_13","text":"Returns a numeric value indicating the number of milliseconds since jsPsych.run was called.","title":"Return value"},{"location":"reference/jspsych/#description_13","text":"Gets the total time the participant has been in the experiment.","title":"Description"},{"location":"reference/jspsych/#example_13","text":"var time = jsPsych . getTotalTime (); console . log ( time );","title":"Example"},{"location":"reference/jspsych/#jspsychpauseexperiment","text":"jsPsych . pauseExperiment ()","title":"jsPsych.pauseExperiment"},{"location":"reference/jspsych/#parameters_14","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_14","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_14","text":"Pauses the experiment. The experiment will finish the current trial, but will not execute any additional trials until jsPsych.resumeExperiment() is called.","title":"Description"},{"location":"reference/jspsych/#example_14","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press p to take a 30 second break. Otherwise, press c to continue immediately.' , choices : [ 'p' , 'c' ], on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"p\" )) { jsPsych . pauseExperiment (); setTimeout ( jsPsych . resumeExperiment , 30000 ); } } }","title":"Example"},{"location":"reference/jspsych/#jspsychresumeexperiment","text":"jsPsych . resumeExperiment ()","title":"jsPsych.resumeExperiment"},{"location":"reference/jspsych/#parameters_15","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_15","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_15","text":"Resumes the experiment after a call to jsPsych.pauseExperiment() . If the post trial delay ( post_trial_gap ) has not yet been reached, then the experiment will not continue until the delay is finished. For example, if post_trial_gap was 10,000ms and jsPsych.resumeExperiment() was called 6,000ms after the previous trial finished, then the experiment would not continue for another 4,000ms.","title":"Description"},{"location":"reference/jspsych/#example_15","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press p to take a 30 second break. Otherwise, press c to continue immediately.' , choices : [ 'p' , 'c' ], on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"p\" )) { jsPsych . pauseExperiment (); setTimeout ( jsPsych . resumeExperiment , 30000 ); } } }","title":"Example"},{"location":"reference/jspsych/#jspsychrun","text":"jsPsych . run ( timeline )","title":"jsPsych.run"},{"location":"reference/jspsych/#parameters_16","text":"Parameter Type Description timeline array An array containing the objects that describe the experiment timeline. See Creating an Experiment: The Timeline .","title":"Parameters"},{"location":"reference/jspsych/#return-value_16","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_16","text":"Start the jsPsych experiment with the specified timeline.","title":"Description"},{"location":"reference/jspsych/#example_16","text":"var timeline = [ trial1 , trial2 , trial3 ]; jsPsych . run ( timeline );","title":"Example"},{"location":"reference/jspsych/#jspsychsetprogressbar","text":"jsPsych . setProgressBar ( value )","title":"jsPsych.setProgressBar"},{"location":"reference/jspsych/#parameters_17","text":"Parameter Type Description value numeric Proprotion (between 0 and 1) to fill the progress bar.","title":"Parameters"},{"location":"reference/jspsych/#return-value_17","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_17","text":"Set the progress bar to a custom amount. Proportion must be between 0 and 1. Values larger than 1 are treated as 1.","title":"Description"},{"location":"reference/jspsych/#example_17","text":"jsPsych . setProgressBar ( 0.85 );","title":"Example"},{"location":"reference/jspsych/#jspsychtimelinevariable","text":"jsPsych . timelineVariable ( variable , call_immediate )","title":"jsPsych.timelineVariable"},{"location":"reference/jspsych/#parameters_18","text":"Parameter Type Description variable string Name of the timeline variable call_immediate bool This parameter is optional and can usually be omitted. It determines the return value of jsPsych.timelineVariable . If true , the function returns the value of the current timeline variable. If false , the function returns a function that returns the value of the current timeline variable. When call_immediate is omitted, the appropriate option is determined automatically based on the context in which this function is called. When jsPsych.timelineVariable is used as a parameter value, call_immediate will be false . This allows it to be used as a dynamic trial parameter . When jsPsych.timelineVariable is used inside of a function, call_immediate will be true . It is possible to explicitly set this option to true to force the function to immediately return the current value of the timeline variable.","title":"Parameters"},{"location":"reference/jspsych/#return-value_18","text":"Either a function that returns the value of the timeline variable, or the value of the timeline variable, depending on the context in which it is used. See call_immediate description above.","title":"Return value"},{"location":"reference/jspsych/#description_18","text":"Timeline variables are a powerful technique for generating experiments with repetitive procedures but different parameter values. This function fetches the current value of a particular timeline variable. It must be used in conjunction with a timeline that has timeline variables. See the timeline variable section for details.","title":"Description"},{"location":"reference/jspsych/#examples","text":"","title":"Examples"},{"location":"reference/jspsych/#standard-use-as-a-parameter-for-a-trial","text":"var trial = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'image' ) } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] }","title":"Standard use as a parameter for a trial"},{"location":"reference/jspsych/#invoking-immediately-in-a-function","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ return \"<img style='width:100px; height:100px;' src='\" + jsPsych . timelineVariable ( 'image' ) + \"'></img>\" ; } } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] } Prior to jsPsych v6.3.0, the call_immediate parameter must be set to true when jsPsych.timelineVariable is called from within a function, such as a dynamic parameter : var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ return \"<img style='width:100px; height:100px;' src='\" + jsPsych . timelineVariable ( 'image' , true ) + \"'></img>\" ; } } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] }","title":"Invoking immediately in a function"},{"location":"reference/jspsych/#jspsychversion","text":"jsPsych . version ()","title":"jsPsych.version"},{"location":"reference/jspsych/#parameters_19","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_19","text":"Returns the version number as a string.","title":"Return value"},{"location":"reference/jspsych/#description_19","text":"Gets the version of jsPsych.","title":"Description"},{"location":"reference/jspsych/#example_18","text":"var version = jsPsych . version (); console . log ( version );","title":"Example"},{"location":"support/migration-v7/","text":"Migrating an experiment to v7.x \u00b6 The release of version 7.0 changes a number of core components of jsPsych. We made these changes to improve jsPsych's compatibility with modern JavaScript tools like package managers and bundlers and to improve the developer experience for people contributing to jsPsych's codebase. We hope these changes will improve the long-term viability of the project and encourage more developers to contribute to jsPsych. Our aim was to accomplish these goals with minimal changes to the user experience of jsPsych. However, we did have to change a few critical things. This guide is aimed at users who are familiar with v6.x of jsPsych and would like to understand what's changed in v7.x. Loading jsPsych \u00b6 There are now three different ways you can load jsPsych into your HTML file. We've updated the hello world tutorial to walk through each of the three options. If you are looking for the option that is most similar to the version 6.x experience, check out option 2 . The biggest difference from what you are used to is that the directory structure of the downloaded library is slightly different and plugin files are named a little bit differently. Initializing and running jsPsych \u00b6 We've removed jsPsych.init() and split the features into two different functions. At the start of your experiment script, you'll now call initJsPsych() to get a new instance of jsPsych and store it in a variable called jsPsych . This is where you will pass in the variety of parameters that used to go into jsPsych.init() , with the exception of the timeline parameter. var jsPsych = initJsPsych ({ use_webaudio : false , on_finish : function (){ jsPsych . data . displayData (); } }); Once you've created your timeline, then you'll launch the experiment by calling jsPsych.run() , passing in the timeline as the only argument. This is the point in your script where you've used the jsPsych.init function in jsPsych v6.x. Because the jsPsych.run function only needs the experiment timeline, this argument should be an array (rather than an object like {timeline: timeline} in jsPsych v6.x). var timeline = [...] jsPsych . run ( timeline ); The type parameter for trials \u00b6 The type parameter now expects the value to be a plugin class rather than a string. For example, if you load the html-keyboard-response plugin from the CDN... < script src = \"http://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.0\" ></ script > ... or from the plugin-html-keyboard-response.js file in the release archive... < script src = \"plugin-html-keyboard-response.js\" ></ script > ... then a global variable defining the plugin's class called jsPsychHtmlKeyboardResponse is available. To create a trial using the plugin, pass this class as the type parameter. The plugin classes are named starting with jsPsych , followed by the plugin name written in camel case (rather than with dashes between words). See the \"Using a plugin\" section of the Plugins overview page for more examples. Note that the value is not a string . var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello, version 7.0!' } The choices parameter for keyboard response trials \u00b6 The choices parameter for keyboard response trials no longer supports jsPsych.NO_KEYS and jsPsych.ALL_KEYS , and they have been replaced by the strings \"NO_KEYS\" and \"ALL_KEYS\" respectively. For example, if you load the audio-keyboard-response plugin, you can prevent any user input like... var trial = { type : jsPsychAudioKeyboardResponse , choices : \"NO_KEYS\" , stimulus : 'example.ogg' , trial_ends_after_audio : true } Using extensions \u00b6 Like plugins, extensions are now also referenced by their class. Extensions are initiliazed in initJsPsych() instead of jsPsych.init() . Extension classes are named similarly to plugins, except that they start with jsPsychExtension . var jsPsych = initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }) The class is also used in trials that use the extension. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello, version 7.0!' , extensions : [ { type : jsPsychExtensionWebgazer } ] } Custom plugins \u00b6 If you have custom plugins that you would like to upgrade to be compatible with v7.x we recommend using our plugin template . The new template implements plugins as a class, but the core components are essentially unchanged. Anything in plugin.info from a v6.x plugin should be moved into the info object. Note that the type argument for the parameters follows a slightly different syntax in the v7.x plugins. This object is then assigned as a static property of the class . Anything in plugin.trial from a v6.x plugin should be moved into the trial method inside the class. The new template has a constructor() function that accepts an instance of jsPsych. You do not need to adjust this portion of the plugin. There are a few changes to be aware of that may affect your plugin code. We removed the registerPreload function and we now auto-detect media to preload via the type argument specified in the info object. If a parameter is listed as IMAGE , AUDIO , or VIDEO , it will be automatically preloaded. If you wish to disable preloading you can set the preload flag to false for the parameter. If you invoke any functions from jsPsych, like jsPsych.finishTrial() , note that jsPsych is no longer a global variable and you must use the reference to jsPsych that is passed to the constructor. To do this, simply prefix all jsPsych references with this. , e.g., jsPsych.finishTrial() becomes this.jsPsych.finishTrial() . If your reference to a jsPsych function is inside of another function, then in order for the this keyword to appropriately reference the jsPsych instance, you must also use a JavaScript arrow function expression for the outer function. For example, this: function end_trial () { // ... jsPsych . finishTrial ( data ); } Would be re-written as: const end_trial = () => { // ... this . jsPsych . finishTrial ( data ); } Need help? \u00b6 If you encounter issues migrating code to v7.x, feel free to post in our support thread for migration .","title":"Migrating from 6.x to 7.x"},{"location":"support/migration-v7/#migrating-an-experiment-to-v7x","text":"The release of version 7.0 changes a number of core components of jsPsych. We made these changes to improve jsPsych's compatibility with modern JavaScript tools like package managers and bundlers and to improve the developer experience for people contributing to jsPsych's codebase. We hope these changes will improve the long-term viability of the project and encourage more developers to contribute to jsPsych. Our aim was to accomplish these goals with minimal changes to the user experience of jsPsych. However, we did have to change a few critical things. This guide is aimed at users who are familiar with v6.x of jsPsych and would like to understand what's changed in v7.x.","title":"Migrating an experiment to v7.x"},{"location":"support/migration-v7/#loading-jspsych","text":"There are now three different ways you can load jsPsych into your HTML file. We've updated the hello world tutorial to walk through each of the three options. If you are looking for the option that is most similar to the version 6.x experience, check out option 2 . The biggest difference from what you are used to is that the directory structure of the downloaded library is slightly different and plugin files are named a little bit differently.","title":"Loading jsPsych"},{"location":"support/migration-v7/#initializing-and-running-jspsych","text":"We've removed jsPsych.init() and split the features into two different functions. At the start of your experiment script, you'll now call initJsPsych() to get a new instance of jsPsych and store it in a variable called jsPsych . This is where you will pass in the variety of parameters that used to go into jsPsych.init() , with the exception of the timeline parameter. var jsPsych = initJsPsych ({ use_webaudio : false , on_finish : function (){ jsPsych . data . displayData (); } }); Once you've created your timeline, then you'll launch the experiment by calling jsPsych.run() , passing in the timeline as the only argument. This is the point in your script where you've used the jsPsych.init function in jsPsych v6.x. Because the jsPsych.run function only needs the experiment timeline, this argument should be an array (rather than an object like {timeline: timeline} in jsPsych v6.x). var timeline = [...] jsPsych . run ( timeline );","title":"Initializing and running jsPsych"},{"location":"support/migration-v7/#the-type-parameter-for-trials","text":"The type parameter now expects the value to be a plugin class rather than a string. For example, if you load the html-keyboard-response plugin from the CDN... < script src = \"http://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.0\" ></ script > ... or from the plugin-html-keyboard-response.js file in the release archive... < script src = \"plugin-html-keyboard-response.js\" ></ script > ... then a global variable defining the plugin's class called jsPsychHtmlKeyboardResponse is available. To create a trial using the plugin, pass this class as the type parameter. The plugin classes are named starting with jsPsych , followed by the plugin name written in camel case (rather than with dashes between words). See the \"Using a plugin\" section of the Plugins overview page for more examples. Note that the value is not a string . var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello, version 7.0!' }","title":"The type parameter for trials"},{"location":"support/migration-v7/#the-choices-parameter-for-keyboard-response-trials","text":"The choices parameter for keyboard response trials no longer supports jsPsych.NO_KEYS and jsPsych.ALL_KEYS , and they have been replaced by the strings \"NO_KEYS\" and \"ALL_KEYS\" respectively. For example, if you load the audio-keyboard-response plugin, you can prevent any user input like... var trial = { type : jsPsychAudioKeyboardResponse , choices : \"NO_KEYS\" , stimulus : 'example.ogg' , trial_ends_after_audio : true }","title":"The choices parameter for keyboard response trials"},{"location":"support/migration-v7/#using-extensions","text":"Like plugins, extensions are now also referenced by their class. Extensions are initiliazed in initJsPsych() instead of jsPsych.init() . Extension classes are named similarly to plugins, except that they start with jsPsychExtension . var jsPsych = initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }) The class is also used in trials that use the extension. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello, version 7.0!' , extensions : [ { type : jsPsychExtensionWebgazer } ] }","title":"Using extensions"},{"location":"support/migration-v7/#custom-plugins","text":"If you have custom plugins that you would like to upgrade to be compatible with v7.x we recommend using our plugin template . The new template implements plugins as a class, but the core components are essentially unchanged. Anything in plugin.info from a v6.x plugin should be moved into the info object. Note that the type argument for the parameters follows a slightly different syntax in the v7.x plugins. This object is then assigned as a static property of the class . Anything in plugin.trial from a v6.x plugin should be moved into the trial method inside the class. The new template has a constructor() function that accepts an instance of jsPsych. You do not need to adjust this portion of the plugin. There are a few changes to be aware of that may affect your plugin code. We removed the registerPreload function and we now auto-detect media to preload via the type argument specified in the info object. If a parameter is listed as IMAGE , AUDIO , or VIDEO , it will be automatically preloaded. If you wish to disable preloading you can set the preload flag to false for the parameter. If you invoke any functions from jsPsych, like jsPsych.finishTrial() , note that jsPsych is no longer a global variable and you must use the reference to jsPsych that is passed to the constructor. To do this, simply prefix all jsPsych references with this. , e.g., jsPsych.finishTrial() becomes this.jsPsych.finishTrial() . If your reference to a jsPsych function is inside of another function, then in order for the this keyword to appropriately reference the jsPsych instance, you must also use a JavaScript arrow function expression for the outer function. For example, this: function end_trial () { // ... jsPsych . finishTrial ( data ); } Would be re-written as: const end_trial = () => { // ... this . jsPsych . finishTrial ( data ); }","title":"Custom plugins"},{"location":"support/migration-v7/#need-help","text":"If you encounter issues migrating code to v7.x, feel free to post in our support thread for migration .","title":"Need help?"},{"location":"support/support/","text":"Support \u00b6 For questions about jsPsych, the preferred method of support is GitHub Discussions . Questions are most likely to be answered when they include a reproducible example of the problem. If you can make your code available online and link to the experiment, that will make the question easier to answer. Please consider searching through the archive of Q&As before posting a new question. If you have identified a problem with jsPsych, such as a bug in the code or an error in the documentation, please open a new issue on GitHub. If you have a suggestion for fixing the problem, feel free to contribute to the project ! Inquiries for paid consultation to develop experiments using jsPsych or to create new custom jsPsych features can be sent to josh.deleeuw@gmail.com .","title":"Getting Help"},{"location":"support/support/#support","text":"For questions about jsPsych, the preferred method of support is GitHub Discussions . Questions are most likely to be answered when they include a reproducible example of the problem. If you can make your code available online and link to the experiment, that will make the question easier to answer. Please consider searching through the archive of Q&As before posting a new question. If you have identified a problem with jsPsych, such as a bug in the code or an error in the documentation, please open a new issue on GitHub. If you have a suggestion for fixing the problem, feel free to contribute to the project ! Inquiries for paid consultation to develop experiments using jsPsych or to create new custom jsPsych features can be sent to josh.deleeuw@gmail.com .","title":"Support"},{"location":"tutorials/hello-world/","text":"jsPsych \"Hello world\" experiment \u00b6 In the long tradition of \"Hello world!\" examples, this tutorial creates an experiment that outputs the phrase \"Hello world!\" to the browser. Though useless as an actual experiment, the process is helpful for learning the basics of using the jsPsych library. Choose your own (setup) adventure \u00b6 Starting with the release of version 7.0 of jsPsych there are three different ways that you can add jsPsych to your project. Which approach you choose will depend on what your goals are. I want the simplest possible setup . This approach involves using scripts that are hosted on a CDN. You do not need to download or install anything to start using jsPsych. The limitation is that you cannot customize the library. For most experiments, this approach will be sufficient. I want to be able to do some customization, but have a simple setup. . This approach involves downloading a bundle of scripts that make up jsPsych. If you used jsPsych prior to version 7.0, this will feel like the most familiar approach . Having your own copy of the scripts means that you can make modifications to the library such as tweaking plugin behavior. I want to use modern JavaScript tooling, like npm and import statements. You can install jsPsych, plugins for jsPsych, and extensions for jsPsych from NPM. This approach allows you to integrate jsPsych into your favorite JavaScript frameworks and get the benefits of TypeScript, bundlers, and more. Option 1: Using CDN-hosted scripts \u00b6 Step 1: Create an HTML file \u00b6 Tip To edit jsPsych code you'll need a programming-friendly text editor. A great free option is Visual Studio Code (Windows, OSX, Linux). Create a new file called experiment.html . There's some basic code that (nearly) all HTML documents have in common. Here's a typical bare-bones HTML document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > </ head > < body ></ body > </ html > Add the above code to the experiment.html file and save it. If you open the file in a web browser, you should see a blank page and the title of the page will be 'My experiment'. Step 2: Load the jsPsych library \u00b6 To use jsPsych, add a <script> tag to load the library. We'll load the library from a CDN , which means that the library is hosted on another server and can be loaded without having your own copy. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > </ head > < body ></ body > </ html > Note that the URL for the jsPsych library includes the version number, which ensures that the behavior of your experiment won't change with any future updates to jsPsych. You may also want to import the jsPsych stylesheet, which applies a basic set of visual styles to the experiment. This requires adding a <link> tag to the <head> section of the document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > </ html > Step 3: Create a script element and initialize jsPsych \u00b6 To add JavaScript code directly to the webpage we need to add a pair of <script> tags after the <body> tags. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > To initialize jsPsych we use the initJsPsych() function and assign the output to a new variable. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Step 4: Use a plugin to print a message \u00b6 For this demo we want to show some text on the screen. This is exactly what the html-keyboard-response plugin is designed to do. To use the plugin, we need to load it with a <script> tag. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Once the plugin is loaded we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to jsPsychHtmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } </ script > </ html > Step 5: Run the experiment \u00b6 Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } jsPsych . run ([ hello_trial ]); </ script > </ html > Once you've saved the file, open it in a browser. You should see \"Hello world!\" printed on the screen, and if you press a key on the keyboard, the text should disappear (ending the trial). Option 2: Download and host jsPsych \u00b6 Step 1: Download jsPsych \u00b6 Start by downloading the latest release of jsPsych. Here's a direct link (jspsych.zip) . The most recent version can always be found at the top of the GitHub releases page . Note that even the releases that are for a particular plugin or extension will contain the full set of files needed to run jsPsych locally in the dist archive (zip) release asset. You should download the zip file for whatever the most recently released package is. This will ensure that you have the most recent version of all the packages associated with jsPsych. Step 2: Create a folder to store your experiment files \u00b6 Create a folder on your computer to put the experiment files in. We'll call this \"MyExperiment\" for the tutorial. Add a subfolder called jspsych . Once you've created the folder, open the downloaded archive from step 1 and copy the contents of the dist folder into the jspsych folder. It should look like this: \ud83d\udcc2 MyExperiment -- \ud83d\udcc2 jspsych ---- \ud83d\udcc4 jspsych.js ---- \ud83d\udcc4 plugin-animation.js ---- \ud83d\udcc4 plugin-audio-keyboard-response.js ---- ... Step 3: Create an HTML file \u00b6 Tip To edit jsPsych code you'll need a programming-friendly text editor. A great free option is Visual Studio Code (Windows, OSX, Linux). Create a new file called experiment.html in the MyExperiment folder. The directory structure should look like this: \ud83d\udcc2 MyExperiment -- \ud83d\udcc4 experiment.html -- \ud83d\udcc2 jspsych There's some basic code that (nearly) all HTML documents have in common. Here's a typical bare-bones HTML document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > </ head > < body ></ body > </ html > Add the above code to the experiment.html file and save it. If you open the file in a web browser, you should see a blank page and the title of the page will be 'My experiment'. Step 4: Load the jsPsych library \u00b6 To use jsPsych, add a <script> tag to load the library. Set the src attribute to the path to the jspsych.js file. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > </ head > < body ></ body > </ html > You may also want to import the jsPsych stylesheet, which applies a basic set of visual styles to the experiment. This requires adding a <link> tag to the <head> section of the document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > </ html > Step 5: Create a script element and initialize jsPsych \u00b6 To add JavaScript code directly to the webpage we need to add a pair of <script> tags after the <body> tags. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > To initialize jsPsych we use the initJsPsych() function and assign the output to a new variable. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Step 6: Use a plugin to print a message \u00b6 For this demo we want to show some text on the screen. This is exactly what the html-keyboard-response plugin is designed to do. To use the plugin, we need to load it with a <script> tag. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Once the plugin is loaded we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to jsPsychHtmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } </ script > </ html > Step 7: Run the experiment \u00b6 Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } jsPsych . run ([ hello_trial ]); </ script > </ html > Once you've saved the file, open it in a browser. You should see \"Hello world!\" printed on the screen, and if you press a key on the keyboard, the text should disappear (ending the trial). Option 3: Using NPM \u00b6 If you are electing to use npm to install jsPsych we will assume that you already are familiar with Node.js and generally know what you are doing with web development. We will also assume that you are using a webpack or a similar bundler. Info You may want to check out the jsPsych Builder CLI utility. jsPsych Builder allows you to automate the experiment setup, spin up a development server, and transpile and bundle scripts and styles using webpack. Using jsPsych Builder will automate some of the steps in this tutorial, so if you prefer that option, you may want to switch to the getting started instructions on the jsPsych Builder GitHub page. Step 1: Install jspsych \u00b6 Run npm install jspsych . This installs the core jsPsych package. Plugins and extensions are installed separately. Step 2: Import the initJsPsych function and create a new JsPsych instance \u00b6 We create a new instance of the JsPsych class by calling initJsPsych . The instance can optionally be configured via a variety of options , passed as an object to initJsPsych . import { initJsPsych } from 'jspsych' ; const jsPsych = initJsPsych (); Step 3: Static markup and CSS \u00b6 jsPsych requires nothing but a body element in your HTML document. For the jsPsych stylesheet, depending on your bundler setup, you can either directly import 'jspsych/css/jspsych.css' into your JavaScript file or add a link tag (like <link href=\"path/to/jspsych.css\" rel=\"stylesheet\" type=\"text/css\" /> ) to your HTML document's head. Step 4: Install and import a plugin \u00b6 Install the html-keyboard-response plugin with: npm install @jspsych/plugin-html-keyboard-response Then import the htmlKeyboardResponse plugin class. import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); Step 5: Create a trial \u00b6 Once the plugin is imported we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to htmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); const trial = { type : htmlKeyboardResponse , stimulus : 'Hello world!' , } Step 6: Run \u00b6 Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); const trial = { type : htmlKeyboardResponse , stimulus : 'Hello world!' , } jsPsych . run ([ trial ]);","title":"The Basics: Hello World"},{"location":"tutorials/hello-world/#jspsych-hello-world-experiment","text":"In the long tradition of \"Hello world!\" examples, this tutorial creates an experiment that outputs the phrase \"Hello world!\" to the browser. Though useless as an actual experiment, the process is helpful for learning the basics of using the jsPsych library.","title":"jsPsych \"Hello world\" experiment"},{"location":"tutorials/hello-world/#choose-your-own-setup-adventure","text":"Starting with the release of version 7.0 of jsPsych there are three different ways that you can add jsPsych to your project. Which approach you choose will depend on what your goals are. I want the simplest possible setup . This approach involves using scripts that are hosted on a CDN. You do not need to download or install anything to start using jsPsych. The limitation is that you cannot customize the library. For most experiments, this approach will be sufficient. I want to be able to do some customization, but have a simple setup. . This approach involves downloading a bundle of scripts that make up jsPsych. If you used jsPsych prior to version 7.0, this will feel like the most familiar approach . Having your own copy of the scripts means that you can make modifications to the library such as tweaking plugin behavior. I want to use modern JavaScript tooling, like npm and import statements. You can install jsPsych, plugins for jsPsych, and extensions for jsPsych from NPM. This approach allows you to integrate jsPsych into your favorite JavaScript frameworks and get the benefits of TypeScript, bundlers, and more.","title":"Choose your own (setup) adventure"},{"location":"tutorials/hello-world/#option-1-using-cdn-hosted-scripts","text":"","title":"Option 1: Using CDN-hosted scripts"},{"location":"tutorials/hello-world/#step-1-create-an-html-file","text":"Tip To edit jsPsych code you'll need a programming-friendly text editor. A great free option is Visual Studio Code (Windows, OSX, Linux). Create a new file called experiment.html . There's some basic code that (nearly) all HTML documents have in common. Here's a typical bare-bones HTML document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > </ head > < body ></ body > </ html > Add the above code to the experiment.html file and save it. If you open the file in a web browser, you should see a blank page and the title of the page will be 'My experiment'.","title":"Step 1: Create an HTML file"},{"location":"tutorials/hello-world/#step-2-load-the-jspsych-library","text":"To use jsPsych, add a <script> tag to load the library. We'll load the library from a CDN , which means that the library is hosted on another server and can be loaded without having your own copy. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > </ head > < body ></ body > </ html > Note that the URL for the jsPsych library includes the version number, which ensures that the behavior of your experiment won't change with any future updates to jsPsych. You may also want to import the jsPsych stylesheet, which applies a basic set of visual styles to the experiment. This requires adding a <link> tag to the <head> section of the document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > </ html >","title":"Step 2: Load the jsPsych library"},{"location":"tutorials/hello-world/#step-3-create-a-script-element-and-initialize-jspsych","text":"To add JavaScript code directly to the webpage we need to add a pair of <script> tags after the <body> tags. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > To initialize jsPsych we use the initJsPsych() function and assign the output to a new variable. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html >","title":"Step 3: Create a script element and initialize jsPsych"},{"location":"tutorials/hello-world/#step-4-use-a-plugin-to-print-a-message","text":"For this demo we want to show some text on the screen. This is exactly what the html-keyboard-response plugin is designed to do. To use the plugin, we need to load it with a <script> tag. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Once the plugin is loaded we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to jsPsychHtmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } </ script > </ html >","title":"Step 4: Use a plugin to print a message"},{"location":"tutorials/hello-world/#step-5-run-the-experiment","text":"Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } jsPsych . run ([ hello_trial ]); </ script > </ html > Once you've saved the file, open it in a browser. You should see \"Hello world!\" printed on the screen, and if you press a key on the keyboard, the text should disappear (ending the trial).","title":"Step 5: Run the experiment"},{"location":"tutorials/hello-world/#option-2-download-and-host-jspsych","text":"","title":"Option 2: Download and host jsPsych"},{"location":"tutorials/hello-world/#step-1-download-jspsych","text":"Start by downloading the latest release of jsPsych. Here's a direct link (jspsych.zip) . The most recent version can always be found at the top of the GitHub releases page . Note that even the releases that are for a particular plugin or extension will contain the full set of files needed to run jsPsych locally in the dist archive (zip) release asset. You should download the zip file for whatever the most recently released package is. This will ensure that you have the most recent version of all the packages associated with jsPsych.","title":"Step 1: Download jsPsych"},{"location":"tutorials/hello-world/#step-2-create-a-folder-to-store-your-experiment-files","text":"Create a folder on your computer to put the experiment files in. We'll call this \"MyExperiment\" for the tutorial. Add a subfolder called jspsych . Once you've created the folder, open the downloaded archive from step 1 and copy the contents of the dist folder into the jspsych folder. It should look like this: \ud83d\udcc2 MyExperiment -- \ud83d\udcc2 jspsych ---- \ud83d\udcc4 jspsych.js ---- \ud83d\udcc4 plugin-animation.js ---- \ud83d\udcc4 plugin-audio-keyboard-response.js ---- ...","title":"Step 2: Create a folder to store your experiment files"},{"location":"tutorials/hello-world/#step-3-create-an-html-file","text":"Tip To edit jsPsych code you'll need a programming-friendly text editor. A great free option is Visual Studio Code (Windows, OSX, Linux). Create a new file called experiment.html in the MyExperiment folder. The directory structure should look like this: \ud83d\udcc2 MyExperiment -- \ud83d\udcc4 experiment.html -- \ud83d\udcc2 jspsych There's some basic code that (nearly) all HTML documents have in common. Here's a typical bare-bones HTML document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > </ head > < body ></ body > </ html > Add the above code to the experiment.html file and save it. If you open the file in a web browser, you should see a blank page and the title of the page will be 'My experiment'.","title":"Step 3: Create an HTML file"},{"location":"tutorials/hello-world/#step-4-load-the-jspsych-library","text":"To use jsPsych, add a <script> tag to load the library. Set the src attribute to the path to the jspsych.js file. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > </ head > < body ></ body > </ html > You may also want to import the jsPsych stylesheet, which applies a basic set of visual styles to the experiment. This requires adding a <link> tag to the <head> section of the document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > </ html >","title":"Step 4: Load the jsPsych library"},{"location":"tutorials/hello-world/#step-5-create-a-script-element-and-initialize-jspsych","text":"To add JavaScript code directly to the webpage we need to add a pair of <script> tags after the <body> tags. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > To initialize jsPsych we use the initJsPsych() function and assign the output to a new variable. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html >","title":"Step 5: Create a script element and initialize jsPsych"},{"location":"tutorials/hello-world/#step-6-use-a-plugin-to-print-a-message","text":"For this demo we want to show some text on the screen. This is exactly what the html-keyboard-response plugin is designed to do. To use the plugin, we need to load it with a <script> tag. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Once the plugin is loaded we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to jsPsychHtmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } </ script > </ html >","title":"Step 6: Use a plugin to print a message"},{"location":"tutorials/hello-world/#step-7-run-the-experiment","text":"Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } jsPsych . run ([ hello_trial ]); </ script > </ html > Once you've saved the file, open it in a browser. You should see \"Hello world!\" printed on the screen, and if you press a key on the keyboard, the text should disappear (ending the trial).","title":"Step 7: Run the experiment"},{"location":"tutorials/hello-world/#option-3-using-npm","text":"If you are electing to use npm to install jsPsych we will assume that you already are familiar with Node.js and generally know what you are doing with web development. We will also assume that you are using a webpack or a similar bundler. Info You may want to check out the jsPsych Builder CLI utility. jsPsych Builder allows you to automate the experiment setup, spin up a development server, and transpile and bundle scripts and styles using webpack. Using jsPsych Builder will automate some of the steps in this tutorial, so if you prefer that option, you may want to switch to the getting started instructions on the jsPsych Builder GitHub page.","title":"Option 3: Using NPM"},{"location":"tutorials/hello-world/#step-1-install-jspsych","text":"Run npm install jspsych . This installs the core jsPsych package. Plugins and extensions are installed separately.","title":"Step 1: Install jspsych"},{"location":"tutorials/hello-world/#step-2-import-the-initjspsych-function-and-create-a-new-jspsych-instance","text":"We create a new instance of the JsPsych class by calling initJsPsych . The instance can optionally be configured via a variety of options , passed as an object to initJsPsych . import { initJsPsych } from 'jspsych' ; const jsPsych = initJsPsych ();","title":"Step 2: Import the initJsPsych function and create a new JsPsych instance"},{"location":"tutorials/hello-world/#step-3-static-markup-and-css","text":"jsPsych requires nothing but a body element in your HTML document. For the jsPsych stylesheet, depending on your bundler setup, you can either directly import 'jspsych/css/jspsych.css' into your JavaScript file or add a link tag (like <link href=\"path/to/jspsych.css\" rel=\"stylesheet\" type=\"text/css\" /> ) to your HTML document's head.","title":"Step 3: Static markup and CSS"},{"location":"tutorials/hello-world/#step-4-install-and-import-a-plugin","text":"Install the html-keyboard-response plugin with: npm install @jspsych/plugin-html-keyboard-response Then import the htmlKeyboardResponse plugin class. import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych ();","title":"Step 4: Install and import a plugin"},{"location":"tutorials/hello-world/#step-5-create-a-trial","text":"Once the plugin is imported we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to htmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); const trial = { type : htmlKeyboardResponse , stimulus : 'Hello world!' , }","title":"Step 5: Create a trial"},{"location":"tutorials/hello-world/#step-6-run","text":"Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); const trial = { type : htmlKeyboardResponse , stimulus : 'Hello world!' , } jsPsych . run ([ trial ]);","title":"Step 6: Run"},{"location":"tutorials/rt-task/","text":"Summary of Tutorial Content \u00b6 This tutorial will work through the creation of a simple response time task. The task is to press one key for a blue colored circle and another key for an orange colored circle. Despite this simple task, the tutorial covers many of the key features of jsPsych, including: Using a plugin to create a standard trial. Combining plugins together to create new kinds of trials. Using timeline variables to maximize code reuse. Preloading media. Randomizing presentation order. Manipulating, filtering, and aggregating data. Using dynamic content to change the experiment parameters based on the participant's responses. Part 1: Creating a blank experiment \u00b6 Start by setting up a new HTML file with jsPsych, the html-keyboard-response plugin, and the jspsych.css file loaded. If you are unsure how to do this, follow the Hello World tutorial . You should have an HTML document that looks like this: Info: Loading jsPsych This tutorial assumes that you are using the CDN-based method of loading jsPsych . If you are using another method then everything is the same except for how jsPsych is loaded. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > This will be our starting point for building the rest of the experiment. Part 2: Display welcome message \u00b6 First we have to initialize jsPsych. We can do this using the initJsPsych() function , and saving the result to a variable called jsPsych . var jsPsych = initJsPsych (); All jsPsych experiments are defined by a timeline. The timeline is an array that contains the set of trials we want to run in the experiment. We can start by defining an empty timeline array. We'll add trials to this array as we create them. var timeline = []; Let's greet the participant with a simple welcome message using the html-keyboard-response plugin. First, we create a trial that uses the html-keyboard-response plugin and contains a simple string to show the participant. As explained on the plugins documentation page , the trial object must have a type parameter that tells jsPsych which plugin to use. The value of type is similar to the plugin name, but starts with jsPsych and is written in camel case rather than with dashes. So to use the html-keyboard-response plugin, we need to write jsPsychHtmlKeyboardResponse as the trial type. var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; Next, we push the welcome trial to the timeline, which adds it to the end of the array. timeline . push ( welcome ); Finally, we tell jsPsych to run the experiment by calling the jsPsych.run() function and passing in the array that defines the experiment timeline. jsPsych . run ( timeline ); After each step in the tutorial you can view the complete code up to that point by clicking on the expandable box below. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 3: Show instructions \u00b6 We can use the same basic structure from part 2 to create a new html-keyboard-response trial that shows instructions to the participant. The only difference in this trial is that we will use HTML formatting to control how the instructions display and we will add a two second gap after the trial using the post_trial_gap parameter. The trial definition looks like this: var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; Tip In JavaScript there are three different ways to define a string . You can use single quotes ' , double quotes \" , or backticks ` . Using backticks has two advantages over the other approaches, especially when you are creating long strings with HTML. You can extend the string across multiple lines and you can use template strings to easily incorporate variables. Notice that the HTML includes <img> tags to display the images that the participant will be responding to. You'll need to download these image files. Right-click on each image below and select Save image as... . Put the images in a folder called img in the experiment folder you created in part 1. Don't forget to add the trial to the timeline: timeline . push ( instructions ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 4: Displaying stimuli and getting responses \u00b6 Creating trials to show the stimuli is conceptually the same as creating a trial to show instructions, except that now we are displaying an image instead of text or html. This means we need to use a different plugin: image-keyboard-response . We need to start by loading this plugin by adding a <script> tag to the document. < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > For now, we will just show each image once. The path to the image file should be set as the stimulus parameter. We will also set the option for which keys the participant is allowed to use to respond ( choices ) so that only the 'f' and 'j' keys are valid responses. var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; As usual, we need to add the trials to the timeline. timeline . push ( blue_trial , orange_trial ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define test trials */ var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; timeline . push ( blue_trial , orange_trial ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 5: Preloading media \u00b6 Whenever we use media elements (images, audio, or video) in an experiment it is a good idea to preload them prior to needing them for a trial. By preloading media we ask the participant's browser to download the media ahead of needing it, so that when we do need to display or play it there is no lag from needing to download it. We are going to use the preload plugin to preload the two images. The media preloading section goes into a lot of detail about various options for preloading and different ways that you can use this plugin. Here we are simply going to give the plugin a list of the files that we want to be preloaded. First we need to add the preload plugin to our <head> section. < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > We'll put this trial at the very start of the experiment, so add this code before the welcome trial. var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; As always, add the trial to the timeline. timeline . push ( preload ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define test trials */ var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; timeline . push ( blue_trial , orange_trial ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 6: Timeline variables \u00b6 In the full experiment, we will want more than two trials. One way we could do this is to create many more objects that define trials and push them all onto the timeline, but there is a more efficient way: using timeline variables. The parameters for showing the blue and orange circle are very similar. The only difference is which image is displayed. Timeline variables allow us to define the procedure for showing the stimulus once, and then repeatedly use it with different variables. We'll see how, even in this relatively simple case, this can save us a lot of lines of code. To start, let's make an array that contains all the different trials we want to run in the test phase. There are only two for the experiment: blue trials and orange trials. var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; Instead of just showing the blue and orange circles, let's also set up the experiment to show a fixation cross (+) in between trials. We can define a trial to show the fixation cross for a fixed amount of time by using the trial_duration parameter of the html-keyboard-response plugin and setting the choices parameter to the special value \"NO_KEYS\" , which means that no responses will be accepted as a valid response and the trial will last however long the trial_duration parameter specifies. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; To show the circles, we'll set up another trial with the image-keyboard-response plugin, but we'll use the function jsPsych.timelineVariable() to indicate that we want jsPsych to substitute the value of the parameter in from the timeline variables. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] } To link the variables that we declared in the test_stimuli array with the call to jsPsych.timelineVariable() we need to create a new timeline and set the timeline_variables property: var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli } We have to add the test_procedure to the main timeline array, but the fixation and test trial do not need to be added to timeline because they already exist on the test_procedure timeline. timeline . push ( test_procedure ); What happens when the experiment reaches the test procedure? jsPsych will run the test_procedure timeline one time for each entry in the test_stimuli array (two times total, in this case). The first time through, jsPsych will substitute the timeline variables from the first array entry (blue image), and the second time through the second array entry will be used (orange image). Notice that the fixation trial occurs before both the orange and the blue circles, because the entire timeline of the test_procedure is repeated for each entry in the timeline_variables array. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] } timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 7: Parameters for timelines with timeline variables \u00b6 Right now our experiment is a measly two trials long. Even worse is that the order of the stimuli is the same every time! When we use timeline variables, we get access to some methods to randomize the order and repeat the trials. To randomize the order, simply set randomize_order: true on the object with the timeline_variables : var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true }; We can also easily make the test phase longer by setting the repetitions parameter. This parameter controls how many times the experiment will loop through all of the entries in the timeline_variables array. For example, if we set repetitions: 5 , then the experiment will loop through the two entries in the timeline_variables 5 times, for a total of 10 test trials. var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; Info: Randomizing timeline variables In a timeline variables procedure, when randomize_order is true and repetitions is greater than 1, the trial order will be re-randomized on each repetition through the timeline_variables array. This means that there will be some constraints on the randomization of all trials in the procedure. For example, if a timeline_variables array contains one trial per stimulus, then the same stimulus could occur twice in a row (since it could be at the end of one repetition and the start of the next one), but it could not be repeated more than twice in a row, regardless of the number of repetitions . If you want to repeat your timeline_variables array but randomize across all trials, you could use the sample parameter with the fixed-repetitions option: this will combine all the repeitions of your timeline_variables array into one larger array, and then randomize the whole thing. You can read more about the randomization, repetition, and sampling options for timeline variables in the Timeline Variables documentation . The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 8: Using functions to generate parameters \u00b6 One aspect of the experiment that could be improved is the duration of the fixation cross. As the experiment stands right now, the timing of the circles appearing is very predictable. We can change that by using a different value for the trial_duration parameter in the fixation trial for each trial. But how can we do that and keep the simple code structure we have now where we only have to define the fixation trial once? One option would be to add another timeline variable, like \"fixation_duration\" and use that to control the timing. But another option is to specify the trial_duration parameter as a function. If a parameter is a function, jsPsych will execute the function every time the trial runs. That means that if the function returns different results probabilistically, we can get a different parameter value every time the trial runs. To do that here, we'll use one of the built-in randomization methods in jsPsych's randomization module . jsPsych.randomization.sampleWithoutReplacement() takes an array of items to sample from and generates a new array of length N by sampling without replacement. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } } In the code above, we replaced the trial_duration: 1000 parameter in fixation with a function. Inside the function, we take a sample from the array [250, 500, 750, 1000, 1250, 1500, 1750, 2000] of size 1 (second parameter to jsPsych.randomization.sampleWithoutReplacement ). The return value from calling jsPsych.randomization.sampleWithoutReplacement is an array of length 1, so we add the [0] selection at the end to get the value out of the array. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] } timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 10: Displaying the data \u00b6 We have created a complete, if simple, experiment at this point, so let's take a look at the data being generated. jsPsych has a built-in function called jsPsych.data.displayData() that is useful for debugging your experiment. It will remove all of the information on the screen and replace it with the raw data collected so far. This isn't terribly useful when you are actually running an experiment, but it's nice for checking the data during development. We need the displayData function to execute when the experiment ends. One way to do this is to use the on_finish callback function . This function will automatically execute once all the trials in the experiment are finished. We can specify this function in the experiment settings when we initialize jsPsych with the initJsPsych method. var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 11: Tagging trials with additional data \u00b6 All trials in jsPsych can be tagged with additional arbitrary data. This data will get stored alongside the data that the plugin normally generates, which allows experimenters to record properties of a trial along with the data from the trial. When might you use this feature? In this experiment, it would be nice to tag each trial with a circle as a response trial, so that the resulting data can be easily filtered to look at only the critical trials. We can do that like this. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' } }; We also could tag the test trials with a property that indicates what the correct response should be (F for the blue circles, J for the orange). In our current code, we are using the timeline variables feature of jsPsych to choose which circle gets presented on a trial. Since we want to tag the trials differently based on which circle is presented, we need to add the tagging data to the test_stimuli array, and then use the jsPsych.timelineVariable() function to get the value and assign it to a property in the data of the trial. We start by adding a \"correct_response\" property and value to each object in the test_stimuli : var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; Now we can use timelineVariable() in the data parameter of the test trial to get the appropriate \"correct_response\" value for each trial. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) } }; Another kind of tagging that would be useful is to mark each fixation trial as such, to make removing the data from fixation trials easier. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 12: Manipulating data during the experiment \u00b6 Now that the data from the test trials has a tag that describes the correct response, it would be easy to analyze the data after the fact and calculate whether the participant responded correctly. But, we can also do this in jsPsych as the experiment runs to save time later and enable a limited set of data analysis directly in the experiment code. To do this, we'll use the on_finish event of the test trial. We can assign a function to on_finish , and that function will receive an object containing the data generated by the trial. This object can be manipulated inside the function, and any changes made to the object will be stored in jsPsych's internal representation of the data. For this example, we'll determine whether the participant responded correctly, and add a new correct property to the data object. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; The data.response value is a string representation of the key the participant pressed. We can compare this with the data.correct_response value, and assign this computed value to a new property data.correct . Info: The compareKeys function Here we are comparing the values of data.response and data.correct_response using a jsPsych function called jsPsych.pluginAPI.compareKeys . We're using this function because it allows us to compare keys in either a case sensitive or case insensitive way, depending on the case_sensitive_responses parameter in the experiment settings . The participant's key response will be recorded in a case-sensitive way in the data (e.g. 'f' or 'F'), but in most cases, we don't care if their response corresponds to an upper or lower case letter (which is why the case_sensitive_responses experiment setting is false by default). Using the jsPsych.pluginAPI.commpareKeys function here means that the response will be scored correctly, even if the participant holds down Shift or has Caps Lock on. This function is only relevant for keyboard responses; for other kinds of responses, such as button presses, you can simply compare the response and correct response values directly, e.g. data . correct = data . response === data . correct_response ; The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 13: Data aggregation \u00b6 jsPsych provides a limited set of analysis functions to allow you to calculate things like mean response times for a selected set of trials. In this part, we'll use these functions to add a final trial to the experiment that tells the participant their accuracy and their mean response time for correct responses. We'll use the html-keyboard-response plugin. Because the text that we want to display changes based on the participant's performance in the experiment, we need to use a function for the stimulus parameter and return the desired text. Info: Dynamic parameters Using a function as the value of a 'normal' parameter (i.e. a parameter that isn't usually a function) provides lots of flexibility in jsPsych experiments, because it allows you to dynamically change the parameter's value based on the participant's earlier responses, and any other information that you don't know before the experiment has started. For more information and examples, see the dynamic parameter documentation page . Here's what the code looks like, and a description follows below. var debrief_block = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trials = jsPsych . data . get (). filter ({ task : 'response' }); var correct_trials = trials . filter ({ correct : true }); var accuracy = Math . round ( correct_trials . count () / trials . count () * 100 ); var rt = Math . round ( correct_trials . select ( 'rt' ). mean ()); return `<p>You responded correctly on ${ accuracy } % of the trials.</p> <p>Your average response time was ${ rt } ms.</p> <p>Press any key to complete the experiment. Thank you!</p>` ; } }; timeline . push ( debrief_block ); To create the variable trials , we use jsPsych.data.get() which returns a jsPsych data collection containing all of the data from the experiment. We can then use .filter to select only the trials where task is 'response' (a benefit of tagging the trials in part 11). trials contains all of the data from the trials where a circle was shown. To get only the correct trials, we can use .filter() again to select only the trials from the trials data collection where the property correct is true . To calculate accuracy, we can use the .count() method to determine how many trials were correct and how many trials there were total. We also use Math.round() to avoid extra digits after the decimal. Finally, to calculate the mean response time on correct trials, we use the .select method on the correct_trials data collection to select only the 'rt' property of those trials. We can then use the .mean() method to find the mean of all the RT values. The final code \u00b6 This code is available in the /examples folder in the jsPsych release download. It is called demo-simple-rt-task.html . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , repetitions : 5 , randomize_order : true }; timeline . push ( test_procedure ); /* define debrief */ var debrief_block = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trials = jsPsych . data . get (). filter ({ task : 'response' }); var correct_trials = trials . filter ({ correct : true }); var accuracy = Math . round ( correct_trials . count () / trials . count () * 100 ); var rt = Math . round ( correct_trials . select ( 'rt' ). mean ()); return `<p>You responded correctly on ${ accuracy } % of the trials.</p> <p>Your average response time was ${ rt } ms.</p> <p>Press any key to complete the experiment. Thank you!</p>` ; } }; timeline . push ( debrief_block ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Demo Experiment: Simple Reaction Time Task"},{"location":"tutorials/rt-task/#summary-of-tutorial-content","text":"This tutorial will work through the creation of a simple response time task. The task is to press one key for a blue colored circle and another key for an orange colored circle. Despite this simple task, the tutorial covers many of the key features of jsPsych, including: Using a plugin to create a standard trial. Combining plugins together to create new kinds of trials. Using timeline variables to maximize code reuse. Preloading media. Randomizing presentation order. Manipulating, filtering, and aggregating data. Using dynamic content to change the experiment parameters based on the participant's responses.","title":"Summary of Tutorial Content"},{"location":"tutorials/rt-task/#part-1-creating-a-blank-experiment","text":"Start by setting up a new HTML file with jsPsych, the html-keyboard-response plugin, and the jspsych.css file loaded. If you are unsure how to do this, follow the Hello World tutorial . You should have an HTML document that looks like this: Info: Loading jsPsych This tutorial assumes that you are using the CDN-based method of loading jsPsych . If you are using another method then everything is the same except for how jsPsych is loaded. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > This will be our starting point for building the rest of the experiment.","title":"Part 1: Creating a blank experiment"},{"location":"tutorials/rt-task/#part-2-display-welcome-message","text":"First we have to initialize jsPsych. We can do this using the initJsPsych() function , and saving the result to a variable called jsPsych . var jsPsych = initJsPsych (); All jsPsych experiments are defined by a timeline. The timeline is an array that contains the set of trials we want to run in the experiment. We can start by defining an empty timeline array. We'll add trials to this array as we create them. var timeline = []; Let's greet the participant with a simple welcome message using the html-keyboard-response plugin. First, we create a trial that uses the html-keyboard-response plugin and contains a simple string to show the participant. As explained on the plugins documentation page , the trial object must have a type parameter that tells jsPsych which plugin to use. The value of type is similar to the plugin name, but starts with jsPsych and is written in camel case rather than with dashes. So to use the html-keyboard-response plugin, we need to write jsPsychHtmlKeyboardResponse as the trial type. var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; Next, we push the welcome trial to the timeline, which adds it to the end of the array. timeline . push ( welcome ); Finally, we tell jsPsych to run the experiment by calling the jsPsych.run() function and passing in the array that defines the experiment timeline. jsPsych . run ( timeline ); After each step in the tutorial you can view the complete code up to that point by clicking on the expandable box below. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 2: Display welcome message"},{"location":"tutorials/rt-task/#part-3-show-instructions","text":"We can use the same basic structure from part 2 to create a new html-keyboard-response trial that shows instructions to the participant. The only difference in this trial is that we will use HTML formatting to control how the instructions display and we will add a two second gap after the trial using the post_trial_gap parameter. The trial definition looks like this: var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; Tip In JavaScript there are three different ways to define a string . You can use single quotes ' , double quotes \" , or backticks ` . Using backticks has two advantages over the other approaches, especially when you are creating long strings with HTML. You can extend the string across multiple lines and you can use template strings to easily incorporate variables. Notice that the HTML includes <img> tags to display the images that the participant will be responding to. You'll need to download these image files. Right-click on each image below and select Save image as... . Put the images in a folder called img in the experiment folder you created in part 1. Don't forget to add the trial to the timeline: timeline . push ( instructions ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 3: Show instructions"},{"location":"tutorials/rt-task/#part-4-displaying-stimuli-and-getting-responses","text":"Creating trials to show the stimuli is conceptually the same as creating a trial to show instructions, except that now we are displaying an image instead of text or html. This means we need to use a different plugin: image-keyboard-response . We need to start by loading this plugin by adding a <script> tag to the document. < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > For now, we will just show each image once. The path to the image file should be set as the stimulus parameter. We will also set the option for which keys the participant is allowed to use to respond ( choices ) so that only the 'f' and 'j' keys are valid responses. var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; As usual, we need to add the trials to the timeline. timeline . push ( blue_trial , orange_trial ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define test trials */ var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; timeline . push ( blue_trial , orange_trial ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 4: Displaying stimuli and getting responses"},{"location":"tutorials/rt-task/#part-5-preloading-media","text":"Whenever we use media elements (images, audio, or video) in an experiment it is a good idea to preload them prior to needing them for a trial. By preloading media we ask the participant's browser to download the media ahead of needing it, so that when we do need to display or play it there is no lag from needing to download it. We are going to use the preload plugin to preload the two images. The media preloading section goes into a lot of detail about various options for preloading and different ways that you can use this plugin. Here we are simply going to give the plugin a list of the files that we want to be preloaded. First we need to add the preload plugin to our <head> section. < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > We'll put this trial at the very start of the experiment, so add this code before the welcome trial. var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; As always, add the trial to the timeline. timeline . push ( preload ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define test trials */ var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; timeline . push ( blue_trial , orange_trial ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 5: Preloading media"},{"location":"tutorials/rt-task/#part-6-timeline-variables","text":"In the full experiment, we will want more than two trials. One way we could do this is to create many more objects that define trials and push them all onto the timeline, but there is a more efficient way: using timeline variables. The parameters for showing the blue and orange circle are very similar. The only difference is which image is displayed. Timeline variables allow us to define the procedure for showing the stimulus once, and then repeatedly use it with different variables. We'll see how, even in this relatively simple case, this can save us a lot of lines of code. To start, let's make an array that contains all the different trials we want to run in the test phase. There are only two for the experiment: blue trials and orange trials. var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; Instead of just showing the blue and orange circles, let's also set up the experiment to show a fixation cross (+) in between trials. We can define a trial to show the fixation cross for a fixed amount of time by using the trial_duration parameter of the html-keyboard-response plugin and setting the choices parameter to the special value \"NO_KEYS\" , which means that no responses will be accepted as a valid response and the trial will last however long the trial_duration parameter specifies. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; To show the circles, we'll set up another trial with the image-keyboard-response plugin, but we'll use the function jsPsych.timelineVariable() to indicate that we want jsPsych to substitute the value of the parameter in from the timeline variables. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] } To link the variables that we declared in the test_stimuli array with the call to jsPsych.timelineVariable() we need to create a new timeline and set the timeline_variables property: var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli } We have to add the test_procedure to the main timeline array, but the fixation and test trial do not need to be added to timeline because they already exist on the test_procedure timeline. timeline . push ( test_procedure ); What happens when the experiment reaches the test procedure? jsPsych will run the test_procedure timeline one time for each entry in the test_stimuli array (two times total, in this case). The first time through, jsPsych will substitute the timeline variables from the first array entry (blue image), and the second time through the second array entry will be used (orange image). Notice that the fixation trial occurs before both the orange and the blue circles, because the entire timeline of the test_procedure is repeated for each entry in the timeline_variables array. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] } timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 6: Timeline variables"},{"location":"tutorials/rt-task/#part-7-parameters-for-timelines-with-timeline-variables","text":"Right now our experiment is a measly two trials long. Even worse is that the order of the stimuli is the same every time! When we use timeline variables, we get access to some methods to randomize the order and repeat the trials. To randomize the order, simply set randomize_order: true on the object with the timeline_variables : var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true }; We can also easily make the test phase longer by setting the repetitions parameter. This parameter controls how many times the experiment will loop through all of the entries in the timeline_variables array. For example, if we set repetitions: 5 , then the experiment will loop through the two entries in the timeline_variables 5 times, for a total of 10 test trials. var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; Info: Randomizing timeline variables In a timeline variables procedure, when randomize_order is true and repetitions is greater than 1, the trial order will be re-randomized on each repetition through the timeline_variables array. This means that there will be some constraints on the randomization of all trials in the procedure. For example, if a timeline_variables array contains one trial per stimulus, then the same stimulus could occur twice in a row (since it could be at the end of one repetition and the start of the next one), but it could not be repeated more than twice in a row, regardless of the number of repetitions . If you want to repeat your timeline_variables array but randomize across all trials, you could use the sample parameter with the fixed-repetitions option: this will combine all the repeitions of your timeline_variables array into one larger array, and then randomize the whole thing. You can read more about the randomization, repetition, and sampling options for timeline variables in the Timeline Variables documentation . The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 7: Parameters for timelines with timeline variables"},{"location":"tutorials/rt-task/#part-8-using-functions-to-generate-parameters","text":"One aspect of the experiment that could be improved is the duration of the fixation cross. As the experiment stands right now, the timing of the circles appearing is very predictable. We can change that by using a different value for the trial_duration parameter in the fixation trial for each trial. But how can we do that and keep the simple code structure we have now where we only have to define the fixation trial once? One option would be to add another timeline variable, like \"fixation_duration\" and use that to control the timing. But another option is to specify the trial_duration parameter as a function. If a parameter is a function, jsPsych will execute the function every time the trial runs. That means that if the function returns different results probabilistically, we can get a different parameter value every time the trial runs. To do that here, we'll use one of the built-in randomization methods in jsPsych's randomization module . jsPsych.randomization.sampleWithoutReplacement() takes an array of items to sample from and generates a new array of length N by sampling without replacement. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } } In the code above, we replaced the trial_duration: 1000 parameter in fixation with a function. Inside the function, we take a sample from the array [250, 500, 750, 1000, 1250, 1500, 1750, 2000] of size 1 (second parameter to jsPsych.randomization.sampleWithoutReplacement ). The return value from calling jsPsych.randomization.sampleWithoutReplacement is an array of length 1, so we add the [0] selection at the end to get the value out of the array. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] } timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 8: Using functions to generate parameters"},{"location":"tutorials/rt-task/#part-10-displaying-the-data","text":"We have created a complete, if simple, experiment at this point, so let's take a look at the data being generated. jsPsych has a built-in function called jsPsych.data.displayData() that is useful for debugging your experiment. It will remove all of the information on the screen and replace it with the raw data collected so far. This isn't terribly useful when you are actually running an experiment, but it's nice for checking the data during development. We need the displayData function to execute when the experiment ends. One way to do this is to use the on_finish callback function . This function will automatically execute once all the trials in the experiment are finished. We can specify this function in the experiment settings when we initialize jsPsych with the initJsPsych method. var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 10: Displaying the data"},{"location":"tutorials/rt-task/#part-11-tagging-trials-with-additional-data","text":"All trials in jsPsych can be tagged with additional arbitrary data. This data will get stored alongside the data that the plugin normally generates, which allows experimenters to record properties of a trial along with the data from the trial. When might you use this feature? In this experiment, it would be nice to tag each trial with a circle as a response trial, so that the resulting data can be easily filtered to look at only the critical trials. We can do that like this. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' } }; We also could tag the test trials with a property that indicates what the correct response should be (F for the blue circles, J for the orange). In our current code, we are using the timeline variables feature of jsPsych to choose which circle gets presented on a trial. Since we want to tag the trials differently based on which circle is presented, we need to add the tagging data to the test_stimuli array, and then use the jsPsych.timelineVariable() function to get the value and assign it to a property in the data of the trial. We start by adding a \"correct_response\" property and value to each object in the test_stimuli : var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; Now we can use timelineVariable() in the data parameter of the test trial to get the appropriate \"correct_response\" value for each trial. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) } }; Another kind of tagging that would be useful is to mark each fixation trial as such, to make removing the data from fixation trials easier. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 11: Tagging trials with additional data"},{"location":"tutorials/rt-task/#part-12-manipulating-data-during-the-experiment","text":"Now that the data from the test trials has a tag that describes the correct response, it would be easy to analyze the data after the fact and calculate whether the participant responded correctly. But, we can also do this in jsPsych as the experiment runs to save time later and enable a limited set of data analysis directly in the experiment code. To do this, we'll use the on_finish event of the test trial. We can assign a function to on_finish , and that function will receive an object containing the data generated by the trial. This object can be manipulated inside the function, and any changes made to the object will be stored in jsPsych's internal representation of the data. For this example, we'll determine whether the participant responded correctly, and add a new correct property to the data object. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; The data.response value is a string representation of the key the participant pressed. We can compare this with the data.correct_response value, and assign this computed value to a new property data.correct . Info: The compareKeys function Here we are comparing the values of data.response and data.correct_response using a jsPsych function called jsPsych.pluginAPI.compareKeys . We're using this function because it allows us to compare keys in either a case sensitive or case insensitive way, depending on the case_sensitive_responses parameter in the experiment settings . The participant's key response will be recorded in a case-sensitive way in the data (e.g. 'f' or 'F'), but in most cases, we don't care if their response corresponds to an upper or lower case letter (which is why the case_sensitive_responses experiment setting is false by default). Using the jsPsych.pluginAPI.commpareKeys function here means that the response will be scored correctly, even if the participant holds down Shift or has Caps Lock on. This function is only relevant for keyboard responses; for other kinds of responses, such as button presses, you can simply compare the response and correct response values directly, e.g. data . correct = data . response === data . correct_response ; The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 12: Manipulating data during the experiment"},{"location":"tutorials/rt-task/#part-13-data-aggregation","text":"jsPsych provides a limited set of analysis functions to allow you to calculate things like mean response times for a selected set of trials. In this part, we'll use these functions to add a final trial to the experiment that tells the participant their accuracy and their mean response time for correct responses. We'll use the html-keyboard-response plugin. Because the text that we want to display changes based on the participant's performance in the experiment, we need to use a function for the stimulus parameter and return the desired text. Info: Dynamic parameters Using a function as the value of a 'normal' parameter (i.e. a parameter that isn't usually a function) provides lots of flexibility in jsPsych experiments, because it allows you to dynamically change the parameter's value based on the participant's earlier responses, and any other information that you don't know before the experiment has started. For more information and examples, see the dynamic parameter documentation page . Here's what the code looks like, and a description follows below. var debrief_block = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trials = jsPsych . data . get (). filter ({ task : 'response' }); var correct_trials = trials . filter ({ correct : true }); var accuracy = Math . round ( correct_trials . count () / trials . count () * 100 ); var rt = Math . round ( correct_trials . select ( 'rt' ). mean ()); return `<p>You responded correctly on ${ accuracy } % of the trials.</p> <p>Your average response time was ${ rt } ms.</p> <p>Press any key to complete the experiment. Thank you!</p>` ; } }; timeline . push ( debrief_block ); To create the variable trials , we use jsPsych.data.get() which returns a jsPsych data collection containing all of the data from the experiment. We can then use .filter to select only the trials where task is 'response' (a benefit of tagging the trials in part 11). trials contains all of the data from the trials where a circle was shown. To get only the correct trials, we can use .filter() again to select only the trials from the trials data collection where the property correct is true . To calculate accuracy, we can use the .count() method to determine how many trials were correct and how many trials there were total. We also use Math.round() to avoid extra digits after the decimal. Finally, to calculate the mean response time on correct trials, we use the .select method on the correct_trials data collection to select only the 'rt' property of those trials. We can then use the .mean() method to find the mean of all the RT values.","title":"Part 13: Data aggregation"},{"location":"tutorials/rt-task/#the-final-code","text":"This code is available in the /examples folder in the jsPsych release download. It is called demo-simple-rt-task.html . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.2\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.3/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , repetitions : 5 , randomize_order : true }; timeline . push ( test_procedure ); /* define debrief */ var debrief_block = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trials = jsPsych . data . get (). filter ({ task : 'response' }); var correct_trials = trials . filter ({ correct : true }); var accuracy = Math . round ( correct_trials . count () / trials . count () * 100 ); var rt = Math . round ( correct_trials . select ( 'rt' ). mean ()); return `<p>You responded correctly on ${ accuracy } % of the trials.</p> <p>Your average response time was ${ rt } ms.</p> <p>Press any key to complete the experiment. Thank you!</p>` ; } }; timeline . push ( debrief_block ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"The final code"},{"location":"tutorials/video-tutorials/","text":"Video tutorials \u00b6 Warning Most of these videos are using version 6.x of jsPsych. Using version 7.x requires a few changes that are not covered in these videos. We recommend starting with the tutorials on this website to understand how to work with 7.x and then watching these videos for additional information. Much of the content covered in the videos still applies to 7.x , but you'll need a solid understanding of how to use 7.x in order to make use of the examples in the videos. YouTube Channel \u00b6 A variety of video tutorials are available on Josh de Leeuw's YouTube channel . Some tutorials walk through creating a basic version of an entire experiment, like the tutorial on creating a dichotic listening experiment aimed at new users. Others focus on specific features of jsPsych, like how to use functions as parameters to create experiments that change in response to participant input or how to create a new plugin . Workshops \u00b6 Moving Research Online (2020) . Recordings from a Summer 2020 workshop on conducting online research are available on the workshop's YouTube channel . Session 1 provides an overview of jsPsych suitable for brand new users. Session 3 covers some more advanced features of jsPsych. This workshop was funded by the National Science Foundation. babySTEP (2021) . The Centre for Comparative Psycholinguistics (CCP, University of Alberta Department of Linguistics) hosted a two-part jsPsych workshop in 2021 as part of their annual STEP program . Day 1 covered the basics of creating a jsPsych experiment, with an emphasis on audio stimuli. Day 2 was organized around pre-submitted questions. The video demonstrates how to create a more complex experiment involving reading a sentence and hearing different audio options for completing the sentences, and answers several questions about timing accuracy, recording participant generated audio, embedding jsPsych into course (or other) websites, and some (non-empirical) advice about attention checks.","title":"Video Tutorials"},{"location":"tutorials/video-tutorials/#video-tutorials","text":"Warning Most of these videos are using version 6.x of jsPsych. Using version 7.x requires a few changes that are not covered in these videos. We recommend starting with the tutorials on this website to understand how to work with 7.x and then watching these videos for additional information. Much of the content covered in the videos still applies to 7.x , but you'll need a solid understanding of how to use 7.x in order to make use of the examples in the videos.","title":"Video tutorials"},{"location":"tutorials/video-tutorials/#youtube-channel","text":"A variety of video tutorials are available on Josh de Leeuw's YouTube channel . Some tutorials walk through creating a basic version of an entire experiment, like the tutorial on creating a dichotic listening experiment aimed at new users. Others focus on specific features of jsPsych, like how to use functions as parameters to create experiments that change in response to participant input or how to create a new plugin .","title":"YouTube Channel"},{"location":"tutorials/video-tutorials/#workshops","text":"Moving Research Online (2020) . Recordings from a Summer 2020 workshop on conducting online research are available on the workshop's YouTube channel . Session 1 provides an overview of jsPsych suitable for brand new users. Session 3 covers some more advanced features of jsPsych. This workshop was funded by the National Science Foundation. babySTEP (2021) . The Centre for Comparative Psycholinguistics (CCP, University of Alberta Department of Linguistics) hosted a two-part jsPsych workshop in 2021 as part of their annual STEP program . Day 1 covered the basics of creating a jsPsych experiment, with an emphasis on audio stimuli. Day 2 was organized around pre-submitted questions. The video demonstrates how to create a more complex experiment involving reading a sentence and hearing different audio options for completing the sentences, and answers several questions about timing accuracy, recording participant generated audio, embedding jsPsych into course (or other) websites, and some (non-empirical) advice about attention checks.","title":"Workshops"}]}
\ No newline at end of file
+{"config":{"indexing":"full","lang":["en"],"min_search_length":3,"prebuild_index":false,"separator":"[\\s\\-]+"},"docs":[{"location":"","text":"\u00b6 jsPsych is a JavaScript framework for creating behavioral experiments that run in a web browser. Experiments in jsPsych are created using plugins . Each plugin defines different kinds of events, like showing an image on the screen, and collects different kinds of data, like recording which key was pressed at which time. You can use the plugins that are included with jsPsych , use plugins that are developed by community members in the contrib repository , or create your own plugins . By assembling different plugins together into a timeline , it is possible to create a wide range of experiments. The page on timelines is a good place to start learning about jsPsych. From there, you might want to complete the hello world tutorial to learn how to set up a jsPsych experiment and the reaction time experiment tutorial to learn the core features of the framework.","title":"Introduction"},{"location":"#_1","text":"jsPsych is a JavaScript framework for creating behavioral experiments that run in a web browser. Experiments in jsPsych are created using plugins . Each plugin defines different kinds of events, like showing an image on the screen, and collects different kinds of data, like recording which key was pressed at which time. You can use the plugins that are included with jsPsych , use plugins that are developed by community members in the contrib repository , or create your own plugins . By assembling different plugins together into a timeline , it is possible to create a wide range of experiments. The page on timelines is a good place to start learning about jsPsych. From there, you might want to complete the hello world tutorial to learn how to set up a jsPsych experiment and the reaction time experiment tutorial to learn the core features of the framework.","title":""},{"location":"about/about/","text":"About jsPsych \u00b6 jsPsych is open source project with numerous contributors . The project is currently managed by the core team of Josh de Leeuw ( @jodeleeuw ), Becky Gilbert ( @becky-gilbert ), and Bj\u00f6rn Luchterhandt ( @bjoluc ). jsPsych was created by Josh de Leeuw . Citation \u00b6 If you use this library in academic work, the preferred citation is: de Leeuw, J.R., Gilbert, R.A., & Luchterhandt, B. (2023). jsPsych: Enabling an open-source collaborative ecosystem of behavioral experiments. Journal of Open Source Software , 8 (85), 5351, https://joss.theoj.org/papers/10.21105/joss.05351 . This paper is an updated description of jsPsych and includes all current core team members. It replaces the earlier paper that described jsPsych: de Leeuw, J.R. (2015). jsPsych: A JavaScript library for creating behavioral experiments in a Web browser. Behavior Research Methods , 47 (1), 1-12. doi: 10.3758/s13428-014-0458-y Citations help us demonstrate that this library is used and valued, which allows us to continue working on it.","title":"About jsPsych"},{"location":"about/about/#about-jspsych","text":"jsPsych is open source project with numerous contributors . The project is currently managed by the core team of Josh de Leeuw ( @jodeleeuw ), Becky Gilbert ( @becky-gilbert ), and Bj\u00f6rn Luchterhandt ( @bjoluc ). jsPsych was created by Josh de Leeuw .","title":"About jsPsych"},{"location":"about/about/#citation","text":"If you use this library in academic work, the preferred citation is: de Leeuw, J.R., Gilbert, R.A., & Luchterhandt, B. (2023). jsPsych: Enabling an open-source collaborative ecosystem of behavioral experiments. Journal of Open Source Software , 8 (85), 5351, https://joss.theoj.org/papers/10.21105/joss.05351 . This paper is an updated description of jsPsych and includes all current core team members. It replaces the earlier paper that described jsPsych: de Leeuw, J.R. (2015). jsPsych: A JavaScript library for creating behavioral experiments in a Web browser. Behavior Research Methods , 47 (1), 1-12. doi: 10.3758/s13428-014-0458-y Citations help us demonstrate that this library is used and valued, which allows us to continue working on it.","title":"Citation"},{"location":"about/license/","text":"License \u00b6 jsPsych is licensed under the MIT license. The MIT License (MIT) Copyright (c) 2014-2022 Joshua R. de Leeuw Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.","title":"License"},{"location":"about/license/#license","text":"jsPsych is licensed under the MIT license. The MIT License (MIT) Copyright (c) 2014-2022 Joshua R. de Leeuw Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.","title":"License"},{"location":"developers/configuration/","text":"Configuring the jsPsych development environment \u00b6 Setup \u00b6 JsPsych is written using TypeScript , a superset of JavaScript that adds static typing, but compiles to plain JavaScript. The TypeScript compiler itself is written in JavaScript and can be run by Node.js , a runtime to execute JavaScript code without a web browser. Node.js comes with a package manager called NPM (Node Package Manager) that can install JavaScript libraries to run on your machine, such as TypeScript and other build tools for jsPsych. In order to work on code in the jsPsych or the jspsych-contrib repository, it is recommended that you follow the steps below to set up your development environment. Install Node.js \u00b6 The jsPsych development setup requires a Node.js LTS version to be installed on your machine. Clone the repository and install the dependencies \u00b6 Clone either the jsPsych repository or the jspsych-contrib repository by running git clone https://github.com/jspsych/jsPsych.git && cd jsPsych or git clone https://github.com/jspsych/jspsych-contrib.git && cd jspsych-contrib in a terminal. Then run npm install . This will create a node_modules directory and install all the dependencies into it that are required to build and test jsPsych. Info The jsPsych (-contrib) repositories depend on the canvas package which comes with pre-built binaries. On systems for which no pre-built binaries are available, npm install will try to build the binaries from scratch, sometimes failing with an error message mentioning the canvas package. If you are facing such installation issues, please follow the installation instructions of the canvas package and run npm install again afterwards. Info If you are running npm install in the core jsPsych repository, this will also execute the build chain for all packages in the jsPsych repository. This step may take a few minutes. If you would like to use that time efficiently, consider reading the following two sections to know what's happening. Repository structure \u00b6 A Node.js package is a directory that contains a package.json file describing it. Most importantly, a package.json file lists other packages that the package depends on. The jsPsych and jspsych-contrib repositories use NPM workspaces . That means, running npm install in the repository root will install the dependencies for all packages in the packages directory. The core jsPsych library and every jsPsych plugin or extension is laid out as an individual package. These packages are published to the NPM registry where they can be downloaded by NPM or any CDN (such as unpkg ). Build chain and build artifacts \u00b6 JsPsych comes with a build chain (specified in the @jspsych/config package) that can be executed by running npm run build in a package's directory. The build chain will read the package (starting at its src/index.ts file) and create the following build artifacts in the package's dist directory: index.js This file contains everything from index.ts , but as plain JavaScript and bundled in a single file (i.e. without import ing files from the same package). It is used by bundlers like webpack . index.cjs Like index.js , but using the old CommonJS standard to support backwards-compatible tools like the Jest testing framework. index.browser.js This file, like index.js , contains the entire package as plain JavaScript, but this time wrapped in a function so that it can be included directly by browsers using the <script> tag. For plugins or extensions, the default export of a module (i.e. whatever statement comes after export default in the index.ts file) is assigned to a global variable. The name of this global variable is specified in the package's rollup.config.mjs file, as a parameter to the makeRollupConfig() function. Hence, for instance, including the index.browser.js file from the plugin-html-keyboard-response package would assign the HtmlKeyboardResponsePlugin class to the global jsPsychHtmlKeyboardResponse variable. Because the code in index.browser.js looks very similar to the index.ts code but is fully supported by modern web browsers, all examples in the examples directory reference the index.browser.js files so users can also modify the source code directly without running the build chain. index.browser.min.js There are different versions of the JavaScript language specification and not all web browsers and browser versions support all JavaScript features. That's why the jsPsych build chain uses Babel to translate the source files into code that a majority of web browsers can understand. The result of this operation is index.browser.min.js . It behaves just like index.browser.js , but adds support for older browsers by substituting new JavaScript features using older ones. Because this is the recommended build artifact for production usage (and is automatically served by unpkg), the code in index.browser.min.js is also processed by Terser to reduce its size and speed up experiment loading times. *.js.map When debugging code in a browser (especially index.browser.min.js , which is not easily readable due to Terser and Babel), it is important to be able to read the original source code in the debugger. For every build artifact, there is a .map file which contains a mapping of the generated code to the original source code. Browsers automatically read these .map files and display the original code in their debuggers instead of the generated one. *.d.ts The .d.ts files contain the TypeScript type definitions that would otherwise be lost during compilation to plain JavaScript. They are read by Typescript and editors when a package is imported into another TypeScript project. Testing \u00b6 Automated code testing for jsPsych is implemented with Jest . To run the tests, install Node and npm. Run npm install in the root jsPsych directory. Then run npm test . You can also run npm test in the directory of the package that you would like to test. For example, if you are developing tests for the html-keyboard-response plugin you can run npm test in /packages/plugin-html-keyboard-response . If you want to run one file from the root directory, using the aforementioned example, you can run npm test -- /packages/plugin-html-keyboard-response/src/index.spec.ts . Tests for the core jsPsych library are located in /packages/jspsych/tests . Tests for plugins and extensions are located in the /src folder of the corresponding package. Test files for plugins and extensions are named index.spec.ts . There are helper functions for testing in /packages/jspsych/tests/utils.ts . We recommend looking at other test files to observe conventions for testing.","title":"Configuration"},{"location":"developers/configuration/#configuring-the-jspsych-development-environment","text":"","title":"Configuring the jsPsych development environment"},{"location":"developers/configuration/#setup","text":"JsPsych is written using TypeScript , a superset of JavaScript that adds static typing, but compiles to plain JavaScript. The TypeScript compiler itself is written in JavaScript and can be run by Node.js , a runtime to execute JavaScript code without a web browser. Node.js comes with a package manager called NPM (Node Package Manager) that can install JavaScript libraries to run on your machine, such as TypeScript and other build tools for jsPsych. In order to work on code in the jsPsych or the jspsych-contrib repository, it is recommended that you follow the steps below to set up your development environment.","title":"Setup"},{"location":"developers/configuration/#install-nodejs","text":"The jsPsych development setup requires a Node.js LTS version to be installed on your machine.","title":"Install Node.js"},{"location":"developers/configuration/#clone-the-repository-and-install-the-dependencies","text":"Clone either the jsPsych repository or the jspsych-contrib repository by running git clone https://github.com/jspsych/jsPsych.git && cd jsPsych or git clone https://github.com/jspsych/jspsych-contrib.git && cd jspsych-contrib in a terminal. Then run npm install . This will create a node_modules directory and install all the dependencies into it that are required to build and test jsPsych. Info The jsPsych (-contrib) repositories depend on the canvas package which comes with pre-built binaries. On systems for which no pre-built binaries are available, npm install will try to build the binaries from scratch, sometimes failing with an error message mentioning the canvas package. If you are facing such installation issues, please follow the installation instructions of the canvas package and run npm install again afterwards. Info If you are running npm install in the core jsPsych repository, this will also execute the build chain for all packages in the jsPsych repository. This step may take a few minutes. If you would like to use that time efficiently, consider reading the following two sections to know what's happening.","title":"Clone the repository and install the dependencies"},{"location":"developers/configuration/#repository-structure","text":"A Node.js package is a directory that contains a package.json file describing it. Most importantly, a package.json file lists other packages that the package depends on. The jsPsych and jspsych-contrib repositories use NPM workspaces . That means, running npm install in the repository root will install the dependencies for all packages in the packages directory. The core jsPsych library and every jsPsych plugin or extension is laid out as an individual package. These packages are published to the NPM registry where they can be downloaded by NPM or any CDN (such as unpkg ).","title":"Repository structure"},{"location":"developers/configuration/#build-chain-and-build-artifacts","text":"JsPsych comes with a build chain (specified in the @jspsych/config package) that can be executed by running npm run build in a package's directory. The build chain will read the package (starting at its src/index.ts file) and create the following build artifacts in the package's dist directory: index.js This file contains everything from index.ts , but as plain JavaScript and bundled in a single file (i.e. without import ing files from the same package). It is used by bundlers like webpack . index.cjs Like index.js , but using the old CommonJS standard to support backwards-compatible tools like the Jest testing framework. index.browser.js This file, like index.js , contains the entire package as plain JavaScript, but this time wrapped in a function so that it can be included directly by browsers using the <script> tag. For plugins or extensions, the default export of a module (i.e. whatever statement comes after export default in the index.ts file) is assigned to a global variable. The name of this global variable is specified in the package's rollup.config.mjs file, as a parameter to the makeRollupConfig() function. Hence, for instance, including the index.browser.js file from the plugin-html-keyboard-response package would assign the HtmlKeyboardResponsePlugin class to the global jsPsychHtmlKeyboardResponse variable. Because the code in index.browser.js looks very similar to the index.ts code but is fully supported by modern web browsers, all examples in the examples directory reference the index.browser.js files so users can also modify the source code directly without running the build chain. index.browser.min.js There are different versions of the JavaScript language specification and not all web browsers and browser versions support all JavaScript features. That's why the jsPsych build chain uses Babel to translate the source files into code that a majority of web browsers can understand. The result of this operation is index.browser.min.js . It behaves just like index.browser.js , but adds support for older browsers by substituting new JavaScript features using older ones. Because this is the recommended build artifact for production usage (and is automatically served by unpkg), the code in index.browser.min.js is also processed by Terser to reduce its size and speed up experiment loading times. *.js.map When debugging code in a browser (especially index.browser.min.js , which is not easily readable due to Terser and Babel), it is important to be able to read the original source code in the debugger. For every build artifact, there is a .map file which contains a mapping of the generated code to the original source code. Browsers automatically read these .map files and display the original code in their debuggers instead of the generated one. *.d.ts The .d.ts files contain the TypeScript type definitions that would otherwise be lost during compilation to plain JavaScript. They are read by Typescript and editors when a package is imported into another TypeScript project.","title":"Build chain and build artifacts"},{"location":"developers/configuration/#testing","text":"Automated code testing for jsPsych is implemented with Jest . To run the tests, install Node and npm. Run npm install in the root jsPsych directory. Then run npm test . You can also run npm test in the directory of the package that you would like to test. For example, if you are developing tests for the html-keyboard-response plugin you can run npm test in /packages/plugin-html-keyboard-response . If you want to run one file from the root directory, using the aforementioned example, you can run npm test -- /packages/plugin-html-keyboard-response/src/index.spec.ts . Tests for the core jsPsych library are located in /packages/jspsych/tests . Tests for plugins and extensions are located in the /src folder of the corresponding package. Test files for plugins and extensions are named index.spec.ts . There are helper functions for testing in /packages/jspsych/tests/utils.ts . We recommend looking at other test files to observe conventions for testing.","title":"Testing"},{"location":"developers/contributing/","text":"Contributing to jsPsych \u00b6 We welcome contributions of all kinds, including changes to the core codebase, the development of new plugins and extensions, and improvements to the documentation. The project is managed entirely through the GitHub repository . There you can: Use discussions to propose ideas for development and seek feedback on contributions, such as a new plugin. Use issues to identify anything with an actionable next step. For example, a page in the documentation that needs to be fixed, a bug in the code, or a specific feature that has a clear scope. Submit a pull request with modifications to the codebase. Pull requests will be reviewed by one or more members of the core team. Guidelines for contibuting \u00b6 Contributing to the codebase \u00b6 We welcome contributions of any scope. Before we can merge changes into the main codebase, we generally require a few things. Note that you are welcome to contribute code without these things in place, but it will help us get to your contribution faster if you take care of whatever components you are comfortable doing. The code must be tested through our automated testing system. We use Jest as the testing framework. If you are fixing a bug, consider adding a test case that shows the bug has been resolved. If you are contributing new features, like a new plugin, a test suite for the plugin is very helpful. See testing jsPsych for more information about configuring the test tools and writing tests. Relevant documentation must be updated. Any pages in /docs that are affected by the contribution should be updated, and if new pages are needed they should be created. For example, if you are contributing a plugin then adding documentation for the plugin and updating the list of available plugins as well as the mkdocs configuration file is very helpful! An example file should be included if applicable. If you are contributing a new feature, new plugin, or new extension, or contributing a modification that changes the behavior of the library in some important way, consider adding an example file to the /examples folder in the repository. A changeset must be included in the pull request . We use changesets to generate new releases and their corresponding release notes. This is a good overview of changesets that explains how to add one to your pull request. Feel free to ask for help with this! Update the contributors.md file . If you are a first time contributor to jsPsych please add your name to our contributors file . And thanks! Contributing to the documentation \u00b6 We are very appreciative of both small and large contributions to the documentation, from fixing a typo to adding a whole new tutorial. All of the documentation that appears on this site is contained in the /docs folder of the repository. The documentation is built using MkDocs and themed using Material for MkDocs . You can edit any of the markdown files and submit a pull request to modify documentation. If you'd like to test your changes to the documentation locally you'll need to install MkDocs and Material for MkDocs . Then you can run the command mike serve in the root folder of the repository to launch a local webserver and view the documentation. Contributing to jspsych vs. jspsych-contrib \u00b6 If you are developing a new plugin or extension there are two different repositories that you can contribute to: jspsych or jspsych-contrib . The main jspsych repository is open to new plugins and extensions that are likely to be widely used. We require that contributions to main repository are well documented and tested before they are merged. Contributions to the main repository must use TypeScript. We limit contributions to this repository because once a plugin or extension is in the main codebase we are generally committed to providing updates as we develop new versions of jsPsych. Each new plugin and extension potentially increases the amount of development work that we will need to do in the future, so we are somewhat selective about what we will merge. If you have an idea that you'd like to discuss please open a discussion thread and we'd love to chat about it! The jspsych-contrib repository is open to any contributions that are complete and working code. There are some minimal guidelines in place about basic documentation that should be provided. Contributors can choose whether to develop their plugin or extension using our TypeScript template or using our JavaScript template . Contributions to jspsych-contrib are not evaluated for general usefulness in the same way that contributions to the main repository are. We also periodically consider whether to move contributions into the main repository from jspsych-contrib based on their popularity and completeness (documentation and testing).","title":"Contributing to jsPsych"},{"location":"developers/contributing/#contributing-to-jspsych","text":"We welcome contributions of all kinds, including changes to the core codebase, the development of new plugins and extensions, and improvements to the documentation. The project is managed entirely through the GitHub repository . There you can: Use discussions to propose ideas for development and seek feedback on contributions, such as a new plugin. Use issues to identify anything with an actionable next step. For example, a page in the documentation that needs to be fixed, a bug in the code, or a specific feature that has a clear scope. Submit a pull request with modifications to the codebase. Pull requests will be reviewed by one or more members of the core team.","title":"Contributing to jsPsych"},{"location":"developers/contributing/#guidelines-for-contibuting","text":"","title":"Guidelines for contibuting"},{"location":"developers/contributing/#contributing-to-the-codebase","text":"We welcome contributions of any scope. Before we can merge changes into the main codebase, we generally require a few things. Note that you are welcome to contribute code without these things in place, but it will help us get to your contribution faster if you take care of whatever components you are comfortable doing. The code must be tested through our automated testing system. We use Jest as the testing framework. If you are fixing a bug, consider adding a test case that shows the bug has been resolved. If you are contributing new features, like a new plugin, a test suite for the plugin is very helpful. See testing jsPsych for more information about configuring the test tools and writing tests. Relevant documentation must be updated. Any pages in /docs that are affected by the contribution should be updated, and if new pages are needed they should be created. For example, if you are contributing a plugin then adding documentation for the plugin and updating the list of available plugins as well as the mkdocs configuration file is very helpful! An example file should be included if applicable. If you are contributing a new feature, new plugin, or new extension, or contributing a modification that changes the behavior of the library in some important way, consider adding an example file to the /examples folder in the repository. A changeset must be included in the pull request . We use changesets to generate new releases and their corresponding release notes. This is a good overview of changesets that explains how to add one to your pull request. Feel free to ask for help with this! Update the contributors.md file . If you are a first time contributor to jsPsych please add your name to our contributors file . And thanks!","title":"Contributing to the codebase"},{"location":"developers/contributing/#contributing-to-the-documentation","text":"We are very appreciative of both small and large contributions to the documentation, from fixing a typo to adding a whole new tutorial. All of the documentation that appears on this site is contained in the /docs folder of the repository. The documentation is built using MkDocs and themed using Material for MkDocs . You can edit any of the markdown files and submit a pull request to modify documentation. If you'd like to test your changes to the documentation locally you'll need to install MkDocs and Material for MkDocs . Then you can run the command mike serve in the root folder of the repository to launch a local webserver and view the documentation.","title":"Contributing to the documentation"},{"location":"developers/contributing/#contributing-to-jspsych-vs-jspsych-contrib","text":"If you are developing a new plugin or extension there are two different repositories that you can contribute to: jspsych or jspsych-contrib . The main jspsych repository is open to new plugins and extensions that are likely to be widely used. We require that contributions to main repository are well documented and tested before they are merged. Contributions to the main repository must use TypeScript. We limit contributions to this repository because once a plugin or extension is in the main codebase we are generally committed to providing updates as we develop new versions of jsPsych. Each new plugin and extension potentially increases the amount of development work that we will need to do in the future, so we are somewhat selective about what we will merge. If you have an idea that you'd like to discuss please open a discussion thread and we'd love to chat about it! The jspsych-contrib repository is open to any contributions that are complete and working code. There are some minimal guidelines in place about basic documentation that should be provided. Contributors can choose whether to develop their plugin or extension using our TypeScript template or using our JavaScript template . Contributions to jspsych-contrib are not evaluated for general usefulness in the same way that contributions to the main repository are. We also periodically consider whether to move contributions into the main repository from jspsych-contrib based on their popularity and completeness (documentation and testing).","title":"Contributing to jspsych vs. jspsych-contrib"},{"location":"developers/documentation/","text":"Building the jsPsych documentation \u00b6 The documentation hosted at https://www.jspsych.org is generated using mkdocs and the mkdocs-material theme . The documentation files are located in the /docs directory of the GitHub repository . The documentation is written using markdown. To build a local copy of the docs, you will need to install mkdocs , mkdocs-material , and mike using poetry . Install poetry \u00b6 Poetry is a package manager for python. Follow the install instructions on the poetry website to get it running. Install dev dependencies \u00b6 Run the command poetry install in the root directory of jsPsych to install mkdocs , mkdocs-material , and their dependencies. Building a local copy of the docs \u00b6 Run poetry run mike deploy [version] -u to build a new version of the documentation or to override an existing version. For example, if you are testing an edit to version 7.2 of the documentation, run poetry run mike deploy 7.2 -u . You can also use jsPsych's custom npm command: npm run docs:deploy [version] , e.g. npm run docs:deploy 7.2 . This will build the documentation and commit it directly to the gh-pages branch. We use mike instead of mkdocs for the build step to support versioning of the documentation. mike runs the mkdocs command under the hood. Viewing the local docs \u00b6 To launch a local webserver, run poetry run mike serve , or use jsPsych's custom npm command: npm run docs:serve . The docs will be viewable at http://localhost:8000 . Updating the public docs site \u00b6 For core maintainers only After the documentation has been built locally (and therefore committed to your local gh-pages branch), you can update the live documentation site by switching to your gh-pages branch and pushing to the remote gh-pages branch.","title":"Building the Documentation"},{"location":"developers/documentation/#building-the-jspsych-documentation","text":"The documentation hosted at https://www.jspsych.org is generated using mkdocs and the mkdocs-material theme . The documentation files are located in the /docs directory of the GitHub repository . The documentation is written using markdown. To build a local copy of the docs, you will need to install mkdocs , mkdocs-material , and mike using poetry .","title":"Building the jsPsych documentation"},{"location":"developers/documentation/#install-poetry","text":"Poetry is a package manager for python. Follow the install instructions on the poetry website to get it running.","title":"Install poetry"},{"location":"developers/documentation/#install-dev-dependencies","text":"Run the command poetry install in the root directory of jsPsych to install mkdocs , mkdocs-material , and their dependencies.","title":"Install dev dependencies"},{"location":"developers/documentation/#building-a-local-copy-of-the-docs","text":"Run poetry run mike deploy [version] -u to build a new version of the documentation or to override an existing version. For example, if you are testing an edit to version 7.2 of the documentation, run poetry run mike deploy 7.2 -u . You can also use jsPsych's custom npm command: npm run docs:deploy [version] , e.g. npm run docs:deploy 7.2 . This will build the documentation and commit it directly to the gh-pages branch. We use mike instead of mkdocs for the build step to support versioning of the documentation. mike runs the mkdocs command under the hood.","title":"Building a local copy of the docs"},{"location":"developers/documentation/#viewing-the-local-docs","text":"To launch a local webserver, run poetry run mike serve , or use jsPsych's custom npm command: npm run docs:serve . The docs will be viewable at http://localhost:8000 .","title":"Viewing the local docs"},{"location":"developers/documentation/#updating-the-public-docs-site","text":"For core maintainers only After the documentation has been built locally (and therefore committed to your local gh-pages branch), you can update the live documentation site by switching to your gh-pages branch and pushing to the remote gh-pages branch.","title":"Updating the public docs site"},{"location":"developers/extension-development/","text":"Extension development \u00b6 Requirements for an extension \u00b6 As of version 7.0, extensions are JavaScript Classes . An extension must implement: A constructor() that accepts an instance of jsPsych. An initialize() function to handle the initialize event of the extension. An on_start() function to handle the on_start event of the extension. An on_load() function to handle the on_load event of the extension. An on_finish() function to handle the on_finish event of the extension and store data that the extension collects. A static info property containing a unique name for the extension. Templates \u00b6 Plugins can be written in either plain JavaScript or in TypeScript. Template files for both JavaScript and TypeScript are available in the jspsych-contrib repository . Extension components \u00b6 constructor() \u00b6 The extension's constructor() will be passed a reference to the instance of the JsPsych class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules. class MyAwesomeExtension { constructor ( jsPsych ){ this . jsPsych = jsPsych ; } } initialize() \u00b6 The initialize() function is called when an instance of jsPsych is first initialized, either through initJsPsych() or new JsPsych() . This is where setup code for the extension should be run. This event will happen once per experiment, unlike the other events which occur with each trial. The params object can include whatever parameters are necessary to configure the extension. The params object is passed from the call to initJsPsych() to initialize() method. initialize() must return a Promise that resolves when the extension is finished initializing. //... experiment code ...// let jsPsych = initJsPsych ({ extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ return new Promise (( resolve , reject )=>{ console . log ( params . demo ); // will output 'value' resolve (); // finish initialzing }) } } on_start() \u00b6 on_start() is called at the start of the plugin execution, prior to calling plugin.trial . This is where trial-specific initialization can happen, such as creating empty containers to hold data or resetting internal state. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ console . log ( params . demo ); // outputs 'value' before the trial begins. } } on_load() \u00b6 on_load() is called after the on_load event for the plugin has completed, which is typically when the plugin has finished executing initial DOM-modifying code and has set up various event listeners. This is where the extension can begin actively interacting with the DOM and recording data. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ ... } on_load ( params ){ // replaces the contents of the display with 'value'; this . jsPsych . getDisplayElement (). innerHTML = params . demo ; } } on_finish() \u00b6 on_finish() is called after the plugin invokes jsPsych.finishTrial() . This can be used for any teardown at the end of the trial. This method should return an object of data to append to the plugin's data. Note that this event fires before the on_finish event for the plugin, so data added by the extension is accessible in any trial on_finish event handlers. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ], on_finish : ( data ) => { console . log ( data . awesome ); // will output 'value'. } }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ ... } on_load ( params ){ ... } on_finish ( params ){ return { awesome : params . value } } } static .info \u00b6 The info property for the class must contain an object with a name property that has a unique name for the extension. class MyAwesomeExtension { } MyAwesomeExtension . info = { name : 'awesome' } Optional methods \u00b6 The extension can also include any additional methods that are necessary for interacting with it. See the webgazer extension for an example. Advice for writing extensions \u00b6 If you are developing an extension with the aim of including it in the main jsPsych repository we encourage you to follow the contribution guidelines . In general, extensions should be able to work with any plugin. They should make very few assumptions about what the DOM will contain beyond the container elements generated by jsPsych. If you are making an extension targeted at one or a small number of specific plugins, consider modifying the plugin code instead.","title":"Extension Development"},{"location":"developers/extension-development/#extension-development","text":"","title":"Extension development"},{"location":"developers/extension-development/#requirements-for-an-extension","text":"As of version 7.0, extensions are JavaScript Classes . An extension must implement: A constructor() that accepts an instance of jsPsych. An initialize() function to handle the initialize event of the extension. An on_start() function to handle the on_start event of the extension. An on_load() function to handle the on_load event of the extension. An on_finish() function to handle the on_finish event of the extension and store data that the extension collects. A static info property containing a unique name for the extension.","title":"Requirements for an extension"},{"location":"developers/extension-development/#templates","text":"Plugins can be written in either plain JavaScript or in TypeScript. Template files for both JavaScript and TypeScript are available in the jspsych-contrib repository .","title":"Templates"},{"location":"developers/extension-development/#extension-components","text":"","title":"Extension components"},{"location":"developers/extension-development/#constructor","text":"The extension's constructor() will be passed a reference to the instance of the JsPsych class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules. class MyAwesomeExtension { constructor ( jsPsych ){ this . jsPsych = jsPsych ; } }","title":"constructor()"},{"location":"developers/extension-development/#initialize","text":"The initialize() function is called when an instance of jsPsych is first initialized, either through initJsPsych() or new JsPsych() . This is where setup code for the extension should be run. This event will happen once per experiment, unlike the other events which occur with each trial. The params object can include whatever parameters are necessary to configure the extension. The params object is passed from the call to initJsPsych() to initialize() method. initialize() must return a Promise that resolves when the extension is finished initializing. //... experiment code ...// let jsPsych = initJsPsych ({ extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ return new Promise (( resolve , reject )=>{ console . log ( params . demo ); // will output 'value' resolve (); // finish initialzing }) } }","title":"initialize()"},{"location":"developers/extension-development/#on_start","text":"on_start() is called at the start of the plugin execution, prior to calling plugin.trial . This is where trial-specific initialization can happen, such as creating empty containers to hold data or resetting internal state. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ console . log ( params . demo ); // outputs 'value' before the trial begins. } }","title":"on_start()"},{"location":"developers/extension-development/#on_load","text":"on_load() is called after the on_load event for the plugin has completed, which is typically when the plugin has finished executing initial DOM-modifying code and has set up various event listeners. This is where the extension can begin actively interacting with the DOM and recording data. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ] }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ ... } on_load ( params ){ // replaces the contents of the display with 'value'; this . jsPsych . getDisplayElement (). innerHTML = params . demo ; } }","title":"on_load()"},{"location":"developers/extension-development/#on_finish","text":"on_finish() is called after the plugin invokes jsPsych.finishTrial() . This can be used for any teardown at the end of the trial. This method should return an object of data to append to the plugin's data. Note that this event fires before the on_finish event for the plugin, so data added by the extension is accessible in any trial on_finish event handlers. The params object is passed from the declaration of the extension in the trial object. You can use params to customize the behavior of the extension for each trial. //... experiment code ...// let trial = { type : htmlKeyboardResponse , stimulus : \"You're awesome!\" , extensions : [ { type : myAwesomeExtension , params : { demo : 'value' }} ], on_finish : ( data ) => { console . log ( data . awesome ); // will output 'value'. } }); //... extension code ...// class MyAwesomeExtension { initialize ( params ){ ... } on_start ( params ){ ... } on_load ( params ){ ... } on_finish ( params ){ return { awesome : params . value } } }","title":"on_finish()"},{"location":"developers/extension-development/#static-info","text":"The info property for the class must contain an object with a name property that has a unique name for the extension. class MyAwesomeExtension { } MyAwesomeExtension . info = { name : 'awesome' }","title":"static .info"},{"location":"developers/extension-development/#optional-methods","text":"The extension can also include any additional methods that are necessary for interacting with it. See the webgazer extension for an example.","title":"Optional methods"},{"location":"developers/extension-development/#advice-for-writing-extensions","text":"If you are developing an extension with the aim of including it in the main jsPsych repository we encourage you to follow the contribution guidelines . In general, extensions should be able to work with any plugin. They should make very few assumptions about what the DOM will contain beyond the container elements generated by jsPsych. If you are making an extension targeted at one or a small number of specific plugins, consider modifying the plugin code instead.","title":"Advice for writing extensions"},{"location":"developers/plugin-development/","text":"Plugin development \u00b6 Requirements for a plugin \u00b6 As of version 7.0, plugins are JavaScript Classes . A plugin must implement: A constructor() that accepts an instance of jsPsych. A trial() method that accepts an HTMLElement as its first argument and an object of trial parameters as its second argument. There is an optional third argument to handle the on_load event in certain cirumstances. The trial() method should invoke jsPsych.finishTrial() to end the trial and save data at the appropriate moment. A static info property on the class that contains an object describing the plugin's parameters. Templates \u00b6 Plugins can be written in either plain JavaScript or in TypeScript. Template files for both JavaScript and TypeScript are available in the jspsych-contrib repository . Plugin components \u00b6 constructor() \u00b6 The plugin's constructor() will be passed a reference to the instance of the JsPsych class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules. constructor ( jsPsych ){ this . jsPsych = jsPsych ; } trial() \u00b6 The plugin's trial() method is responsible for running a single trial. When the jsPsych timeline reaches a trial using the plugin it will invoke the trial() method for the plugin. There are three parameters that are passed into the trial method. display_element is the DOM element where jsPsych content is being rendered. This parameter will be an HTMLElement , and you can use it to modify the portion of the document that jsPsych controls. trial is an object containing all of the parameters specified in the corresponding TimelineNode . on_load is an optional parameter that contains a callback function to invoke when trial() has completed its initial loading. See handling the on_load event . The only requirement for the trial method is that it calls jsPsych.finishTrial() when it is done. This is how jsPsych knows to advance to the next trial in the experiment (or end the experiment if it is the last trial). The plugin can do whatever it needs to do before that point. static info \u00b6 The plugin's info property is an object with a name and parameters property. const info = { name : 'my-awesome-plugin' , parameters : { } } The parameters property is an object containing all of the parameters for the plugin. Each parameter has a type and default property. const info = { name : 'my-awesome-plugin' , parameters : { image : { type : jspsych . ParameterType . IMAGE , default : undefined }, image_duration : { type : jspsych . ParameterType . INT , default : 500 } } } If the default value is undefined then a user must specify a value for this parameter when creating a trial using the plugin on the timeline. If they do not, then an error will be generated and shown in the console. If a default value is specified in info then that value will be used by the plugin unless the user overrides it by specifying that property. jsPsych allows most plugin parameters to be dynamic , which means that the parameter value can be a function that will be evaluated right before the trial starts. However, if you want your plugin to have a parameter that is a function that shouldn't be evaluated before the trial starts, then you should make sure that the parameter type is 'FUNCTION' . This tells jsPsych not to evaluate the function as it normally does for dynamic parameters. See the canvas-* plugins for examples. The info object should be a static member of the class, as shown below. const info = { name : 'my-awesome-plugin' , parameters : { image : { type : jspsych . ParameterType . IMAGE , default : undefined }, image_duration : { type : jspsych . ParameterType . INT , default : 500 } } } class MyAwesomePlugin { constructor (...) trial (...) } MyAwesomePlugin . info = info ; Plugin functionality \u00b6 Inside the .trial() method you can do pretty much anything that you want, including modifying the DOM, setting up event listeners, and making asynchronous requests. In this section we'll highlight a few common things that you might want to do as examples. Changing the content of the display \u00b6 There are a few ways to change the content of the display. The display_element parameter of the trial method contains the HTMLElement for displaying jsPsych content, so you can use various JavaScript methods for interaction with the display element. A common one is to change the innerHTML . Here's an example of using innerHTML to display an image specified in the trial parameters. trial ( display_element , trial ){ let html_content = `<img src=\" ${ trial . image } \"></img>` ; display_element . innerHTML = html_content ; } jsPsych doesn't clear the display before or after each trial, so it is usually appropriate to use innerHTML to clear the display at the end of a trial. display_element . innerHTML = '' ; Waiting for specified durations \u00b6 If you need to delay code execution for a fixed amount of time, we recommend using jsPsych's wrapper of the setTimeout() function, jsPsych.pluginAPI.setTimeout() . In 7.0 the only advantage of using this method is that it registers the timeout handler so that it can be easily cleared at the end of the trial using jsPsych.pluginAPI.clearAllTimeouts() . In future versions we may replace the implementation of jsPsych.pluginAPI.setTimeout() with improved timing functionality based on requestAnimationFrame . trial ( display_element , trial ){ // show image display_element . innerHTML = `<img src=\" ${ trial . image } \"></img>` ; // hide image after trial.image_duration milliseconds this . jsPsych . pluginAPI . setTimeout (()=>{ display_element . innerHTML = '' ; }, trial . image_duration ); } Responding to keyboard events \u00b6 While the plugin framework allows you to set up any events that you would like to, including normal handling of keyup or keydown events, the jsPsych.pluginAPI module contains the getKeyboardResponse function , which implements some additional helpful functionality for key responses in an experiment. Here's a basic example. See the getKeyboardResponse docs for additional examples. trial ( display_element , trial ){ // show image display_element . innerHTML = `<img src=\" ${ trial . image } \"></img>` ; const after_key_response = ( info ) => { // hide the image display_element . innerHTML = '' ; // record the response time as data let data = { rt : info . rt } // end the trial this . jsPsych . finishTrial ( data ); } // set up a keyboard event to respond only to the spacebar this . jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_key_response , valid_responses : [ ' ' ], persist : false }); } Asynchronous loading \u00b6 One of the trial events is on_load , which is normally triggered automatically when the .trial() method returns. In most cases, this return happens after the plugin has done its initial setup of the DOM (e.g., rendering an image, setting up event listeners and timers, etc.). However, in some cases a plugin may implement an asynchronous operation that needs to complete before the initial loading of the plugin is considered done. An example of this is the audio-keyboard-response plugin, in which the check to see if the audio file is loaded is asynchronous and the .trial() method returns before the audio file has been initialized and the display updated. If you would like to manually trigger the on_load event for a plugin, the .trial() method accepts an optional third parameter that is a callback function to invoke when loading is complete. In order to tell jsPsych to not invoke the regular callback when the .trial() method returns, you need to explicitly return a Promise . As of version 7.0 this Promise only serves as a flag to tell jsPsych that the on_load event should not be triggered. In future versions we may make the Promise functional so that the trial operation can be an async function. Here's a sketch of how the on_load event can be utilized in a plugin. Note that this example is only a sketch and leaves out all the stuff that happens between loading and finishing the trial. See the source for the audio-keyboard-response plugin for a complete exampe. trial ( display_element , trial , on_load ){ let trial_complete ; do_something_asynchronous (). then (()=>{ on_load (); }); const end_trial = () => { this . jsPsych . finishTrial ({...}) trial_complete (); // not strictly necessary, but doesn't hurt. } return new Promise (( resolve )=>{ trial_complete = resolve ; }) } Save data \u00b6 To write data to jsPsych's data collection pass an object of data as the parameter to jsPsych.finishTrial() . constructor ( jsPsych ){ this . jsPsych = jsPsych ; } trial ( display_element , trial ){ let data = { correct : true , rt : 350 } this . jsPsych . finishTrial ( data ); } The data recorded will be that correct is true and that rt is 350 . Additional data for the trial will also be collected automatically. Simulation mode \u00b6 Plugins can optionally support simulation modes . To add simulation support, a plugin needs a simulate() function that accepts four arguments simulate(trial, simulation_mode, simulation_options, load_callback) trial : This is the same as the trial parameter passed to the plugin's trial() method. It contains an object of the parameters for the trial. simulation_mode : A string, either \"data-only\" or \"visual\" . This specifies which simulation mode is being requested. Plugins can optionally support \"visual\" mode. If \"visual\" mode is not supported, the plugin should default to \"data-only\" mode when \"visual\" mode is requested. simulation_options : An object of simulation-specific options. load_callback : A function handle to invoke when the simulation is ready to trigger the on_load event for the trial. It is important to invoke this at the correct time during the simulation so that any on_load events in the experiment execute as expected. Typically the flow for supporting simulation mode involves: Generating artificial data that is consistent with the trial parameters. Merging that data with any data specified by the user in simulation_options . Verifying that the final data object is still consistent with the trial parameters. For example, checking that RTs are not longer than the duration of the trial. In data-only mode, call jsPsych.finishTrial() with the artificial data. In visual mode, invoke the trial() method of the plugin and then use the artificial data to trigger the appropriate events. There are a variety of methods in the Plugin API module to assist with things like simulating key presses and mouse clicks. We plan to add a longer guide about simulation development in the future. For now, we recommend browsing the source code of plugins that support simulation mode to see how the flow described above is implemented. Advice for writing plugins \u00b6 If you are developing a plugin with the aim of including it in the main jsPsych repository we encourage you to follow the contribution guidelines . We also recommend that you make your plugin as general as possible . Consider using parameters to give the user of the plugin as many options for customization as possible. For example, if you have any text that displays in the plugin including things like button labels, implement the text as a parameter. This allows users running experiments in other languages to replace text values as needed.","title":"Plugin Development"},{"location":"developers/plugin-development/#plugin-development","text":"","title":"Plugin development"},{"location":"developers/plugin-development/#requirements-for-a-plugin","text":"As of version 7.0, plugins are JavaScript Classes . A plugin must implement: A constructor() that accepts an instance of jsPsych. A trial() method that accepts an HTMLElement as its first argument and an object of trial parameters as its second argument. There is an optional third argument to handle the on_load event in certain cirumstances. The trial() method should invoke jsPsych.finishTrial() to end the trial and save data at the appropriate moment. A static info property on the class that contains an object describing the plugin's parameters.","title":"Requirements for a plugin"},{"location":"developers/plugin-development/#templates","text":"Plugins can be written in either plain JavaScript or in TypeScript. Template files for both JavaScript and TypeScript are available in the jspsych-contrib repository .","title":"Templates"},{"location":"developers/plugin-development/#plugin-components","text":"","title":"Plugin components"},{"location":"developers/plugin-development/#constructor","text":"The plugin's constructor() will be passed a reference to the instance of the JsPsych class that is running the experiment. The constructor should store this reference so that the plugin can access functionality from the core library and its modules. constructor ( jsPsych ){ this . jsPsych = jsPsych ; }","title":"constructor()"},{"location":"developers/plugin-development/#trial","text":"The plugin's trial() method is responsible for running a single trial. When the jsPsych timeline reaches a trial using the plugin it will invoke the trial() method for the plugin. There are three parameters that are passed into the trial method. display_element is the DOM element where jsPsych content is being rendered. This parameter will be an HTMLElement , and you can use it to modify the portion of the document that jsPsych controls. trial is an object containing all of the parameters specified in the corresponding TimelineNode . on_load is an optional parameter that contains a callback function to invoke when trial() has completed its initial loading. See handling the on_load event . The only requirement for the trial method is that it calls jsPsych.finishTrial() when it is done. This is how jsPsych knows to advance to the next trial in the experiment (or end the experiment if it is the last trial). The plugin can do whatever it needs to do before that point.","title":"trial()"},{"location":"developers/plugin-development/#static-info","text":"The plugin's info property is an object with a name and parameters property. const info = { name : 'my-awesome-plugin' , parameters : { } } The parameters property is an object containing all of the parameters for the plugin. Each parameter has a type and default property. const info = { name : 'my-awesome-plugin' , parameters : { image : { type : jspsych . ParameterType . IMAGE , default : undefined }, image_duration : { type : jspsych . ParameterType . INT , default : 500 } } } If the default value is undefined then a user must specify a value for this parameter when creating a trial using the plugin on the timeline. If they do not, then an error will be generated and shown in the console. If a default value is specified in info then that value will be used by the plugin unless the user overrides it by specifying that property. jsPsych allows most plugin parameters to be dynamic , which means that the parameter value can be a function that will be evaluated right before the trial starts. However, if you want your plugin to have a parameter that is a function that shouldn't be evaluated before the trial starts, then you should make sure that the parameter type is 'FUNCTION' . This tells jsPsych not to evaluate the function as it normally does for dynamic parameters. See the canvas-* plugins for examples. The info object should be a static member of the class, as shown below. const info = { name : 'my-awesome-plugin' , parameters : { image : { type : jspsych . ParameterType . IMAGE , default : undefined }, image_duration : { type : jspsych . ParameterType . INT , default : 500 } } } class MyAwesomePlugin { constructor (...) trial (...) } MyAwesomePlugin . info = info ;","title":"static info"},{"location":"developers/plugin-development/#plugin-functionality","text":"Inside the .trial() method you can do pretty much anything that you want, including modifying the DOM, setting up event listeners, and making asynchronous requests. In this section we'll highlight a few common things that you might want to do as examples.","title":"Plugin functionality"},{"location":"developers/plugin-development/#changing-the-content-of-the-display","text":"There are a few ways to change the content of the display. The display_element parameter of the trial method contains the HTMLElement for displaying jsPsych content, so you can use various JavaScript methods for interaction with the display element. A common one is to change the innerHTML . Here's an example of using innerHTML to display an image specified in the trial parameters. trial ( display_element , trial ){ let html_content = `<img src=\" ${ trial . image } \"></img>` ; display_element . innerHTML = html_content ; } jsPsych doesn't clear the display before or after each trial, so it is usually appropriate to use innerHTML to clear the display at the end of a trial. display_element . innerHTML = '' ;","title":"Changing the content of the display"},{"location":"developers/plugin-development/#waiting-for-specified-durations","text":"If you need to delay code execution for a fixed amount of time, we recommend using jsPsych's wrapper of the setTimeout() function, jsPsych.pluginAPI.setTimeout() . In 7.0 the only advantage of using this method is that it registers the timeout handler so that it can be easily cleared at the end of the trial using jsPsych.pluginAPI.clearAllTimeouts() . In future versions we may replace the implementation of jsPsych.pluginAPI.setTimeout() with improved timing functionality based on requestAnimationFrame . trial ( display_element , trial ){ // show image display_element . innerHTML = `<img src=\" ${ trial . image } \"></img>` ; // hide image after trial.image_duration milliseconds this . jsPsych . pluginAPI . setTimeout (()=>{ display_element . innerHTML = '' ; }, trial . image_duration ); }","title":"Waiting for specified durations"},{"location":"developers/plugin-development/#responding-to-keyboard-events","text":"While the plugin framework allows you to set up any events that you would like to, including normal handling of keyup or keydown events, the jsPsych.pluginAPI module contains the getKeyboardResponse function , which implements some additional helpful functionality for key responses in an experiment. Here's a basic example. See the getKeyboardResponse docs for additional examples. trial ( display_element , trial ){ // show image display_element . innerHTML = `<img src=\" ${ trial . image } \"></img>` ; const after_key_response = ( info ) => { // hide the image display_element . innerHTML = '' ; // record the response time as data let data = { rt : info . rt } // end the trial this . jsPsych . finishTrial ( data ); } // set up a keyboard event to respond only to the spacebar this . jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_key_response , valid_responses : [ ' ' ], persist : false }); }","title":"Responding to keyboard events"},{"location":"developers/plugin-development/#asynchronous-loading","text":"One of the trial events is on_load , which is normally triggered automatically when the .trial() method returns. In most cases, this return happens after the plugin has done its initial setup of the DOM (e.g., rendering an image, setting up event listeners and timers, etc.). However, in some cases a plugin may implement an asynchronous operation that needs to complete before the initial loading of the plugin is considered done. An example of this is the audio-keyboard-response plugin, in which the check to see if the audio file is loaded is asynchronous and the .trial() method returns before the audio file has been initialized and the display updated. If you would like to manually trigger the on_load event for a plugin, the .trial() method accepts an optional third parameter that is a callback function to invoke when loading is complete. In order to tell jsPsych to not invoke the regular callback when the .trial() method returns, you need to explicitly return a Promise . As of version 7.0 this Promise only serves as a flag to tell jsPsych that the on_load event should not be triggered. In future versions we may make the Promise functional so that the trial operation can be an async function. Here's a sketch of how the on_load event can be utilized in a plugin. Note that this example is only a sketch and leaves out all the stuff that happens between loading and finishing the trial. See the source for the audio-keyboard-response plugin for a complete exampe. trial ( display_element , trial , on_load ){ let trial_complete ; do_something_asynchronous (). then (()=>{ on_load (); }); const end_trial = () => { this . jsPsych . finishTrial ({...}) trial_complete (); // not strictly necessary, but doesn't hurt. } return new Promise (( resolve )=>{ trial_complete = resolve ; }) }","title":"Asynchronous loading"},{"location":"developers/plugin-development/#save-data","text":"To write data to jsPsych's data collection pass an object of data as the parameter to jsPsych.finishTrial() . constructor ( jsPsych ){ this . jsPsych = jsPsych ; } trial ( display_element , trial ){ let data = { correct : true , rt : 350 } this . jsPsych . finishTrial ( data ); } The data recorded will be that correct is true and that rt is 350 . Additional data for the trial will also be collected automatically.","title":"Save data"},{"location":"developers/plugin-development/#simulation-mode","text":"Plugins can optionally support simulation modes . To add simulation support, a plugin needs a simulate() function that accepts four arguments simulate(trial, simulation_mode, simulation_options, load_callback) trial : This is the same as the trial parameter passed to the plugin's trial() method. It contains an object of the parameters for the trial. simulation_mode : A string, either \"data-only\" or \"visual\" . This specifies which simulation mode is being requested. Plugins can optionally support \"visual\" mode. If \"visual\" mode is not supported, the plugin should default to \"data-only\" mode when \"visual\" mode is requested. simulation_options : An object of simulation-specific options. load_callback : A function handle to invoke when the simulation is ready to trigger the on_load event for the trial. It is important to invoke this at the correct time during the simulation so that any on_load events in the experiment execute as expected. Typically the flow for supporting simulation mode involves: Generating artificial data that is consistent with the trial parameters. Merging that data with any data specified by the user in simulation_options . Verifying that the final data object is still consistent with the trial parameters. For example, checking that RTs are not longer than the duration of the trial. In data-only mode, call jsPsych.finishTrial() with the artificial data. In visual mode, invoke the trial() method of the plugin and then use the artificial data to trigger the appropriate events. There are a variety of methods in the Plugin API module to assist with things like simulating key presses and mouse clicks. We plan to add a longer guide about simulation development in the future. For now, we recommend browsing the source code of plugins that support simulation mode to see how the flow described above is implemented.","title":"Simulation mode"},{"location":"developers/plugin-development/#advice-for-writing-plugins","text":"If you are developing a plugin with the aim of including it in the main jsPsych repository we encourage you to follow the contribution guidelines . We also recommend that you make your plugin as general as possible . Consider using parameters to give the user of the plugin as many options for customization as possible. For example, if you have any text that displays in the plugin including things like button labels, implement the text as a parameter. This allows users running experiments in other languages to replace text values as needed.","title":"Advice for writing plugins"},{"location":"extensions/list-of-extensions/","text":"List of Plugins \u00b6 These are the extensions that are included in the jsPsych release. Additional extensions may be available in the community contributions repository . For an overview of what extensions are and how they work, see our extensions overview . Extension Description mouse\u2011tracking Enables tracking of mouse events and recording location of objects on screen. record\u2011video Record video data from the participant's webcam during a trial. webgazer Enables eye tracking using the WebGazer library.","title":"List of Extensions"},{"location":"extensions/list-of-extensions/#list-of-plugins","text":"These are the extensions that are included in the jsPsych release. Additional extensions may be available in the community contributions repository . For an overview of what extensions are and how they work, see our extensions overview . Extension Description mouse\u2011tracking Enables tracking of mouse events and recording location of objects on screen. record\u2011video Record video data from the participant's webcam during a trial. webgazer Enables eye tracking using the WebGazer library.","title":"List of Plugins"},{"location":"extensions/mouse-tracking/","text":"mouse-tracking \u00b6 This extension supports mouse tracking. Specifically, it can record the x and y coordinates, along with the time of mousemove events , mousedown events , and mouseup events . It also allows recording of the bounding rectangle of elements on the screen to support the calculation of mouse events relative to different elements. Parameters \u00b6 Initialization Parameters \u00b6 Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionMouseTracking , params : {...}} ] }) Parameter Type Default Value Description minimum_sample_time number 0 The minimum time between samples for mousemove events in milliseconds. If mousemove events occur more rapidly than this limit, they will not be recorded. Use this if you want to keep the data files smaller and don't need high resolution tracking data. The default value of 0 means that all events will be recorded. Trial Parameters \u00b6 Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionMouseTracking , params : {...}} ] } Parameter Type Default Value Description targets array [] A list of elements on the page that you would like to record the coordinates of for comparison with the mouse tracking data. Each entry in the array should be a valid CSS selector string that identifies the element. The selector string should be valid for exactly one element on the page. If the selector is valid for more than one element then only the first matching element will be recorded. events array ['mousemove'] A list of events to track. Can include 'mousemove', 'mousedown', and 'mouseup'. Data Generated \u00b6 Name Type Value mouse_tracking_data array An array of objects containing mouse movement data for the trial. Each object has an x , a y , a t , and an event property. The x and y properties specify the mouse coordinates in pixels relative to the top left corner of the viewport and t specifies the time in milliseconds since the start of the trial. The event will be either 'mousemove', 'mousedown', or 'mouseup' depending on which event was generated. mouse_tracking_targets object An object contain the pixel coordinates of elements on the screen specified by the .targets parameter. Each key in this object will be a selector property, containing the CSS selector string used to find the element. The object corresponding to each key will contain x and y properties specifying the top-left corner of the object, width and height values, plus top , bottom , left , and right parameters which specify the bounding rectangle of the element. Examples \u00b6 Record mouse movement data and play it back Code Demo var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; margin: auto;\"></div>' , choices : [ 'Done' ], prompt : \"<p>Move your mouse around inside the square.</p>\" , extensions : [ { type : jsPsychExtensionMouseTracking , params : { targets : [ '#target' ]}} ], data : { task : 'draw' } }; var replay = { type : jsPsychHtmlButtonResponse , stimulus : '<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; margin: auto; position: relative;\"></div>' , choices : [ 'Done' ], prompt : \"<p>Here's the recording of your mouse movements</p>\" , on_load : function (){ var mouseMovements = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. mouse_tracking_data ; var targetRect = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. mouse_tracking_targets [ '#target' ]; var startTime = performance . now (); function draw_frame () { var timeElapsed = performance . now () - startTime ; var points = mouseMovements . filter (( x ) => x . t <= timeElapsed ); var html = `` ; for ( var p of points ){ html += `<div style=\"width: 3px; height: 3px; background-color: blue; position: absolute; top: ${ p . y - 1 - targetRect . top } px; left: ${ p . x - 1 - targetRect . left } px;\"></div>` } document . querySelector ( '#target' ). innerHTML = html ; if ( points . length < mouseMovements . length ) { requestAnimationFrame ( draw_frame ); } } requestAnimationFrame ( draw_frame ); }, data : { task : 'replay' } } Open demo in new tab","title":"mouse-tracking"},{"location":"extensions/mouse-tracking/#mouse-tracking","text":"This extension supports mouse tracking. Specifically, it can record the x and y coordinates, along with the time of mousemove events , mousedown events , and mouseup events . It also allows recording of the bounding rectangle of elements on the screen to support the calculation of mouse events relative to different elements.","title":"mouse-tracking"},{"location":"extensions/mouse-tracking/#parameters","text":"","title":"Parameters"},{"location":"extensions/mouse-tracking/#initialization-parameters","text":"Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionMouseTracking , params : {...}} ] }) Parameter Type Default Value Description minimum_sample_time number 0 The minimum time between samples for mousemove events in milliseconds. If mousemove events occur more rapidly than this limit, they will not be recorded. Use this if you want to keep the data files smaller and don't need high resolution tracking data. The default value of 0 means that all events will be recorded.","title":"Initialization Parameters"},{"location":"extensions/mouse-tracking/#trial-parameters","text":"Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionMouseTracking , params : {...}} ] } Parameter Type Default Value Description targets array [] A list of elements on the page that you would like to record the coordinates of for comparison with the mouse tracking data. Each entry in the array should be a valid CSS selector string that identifies the element. The selector string should be valid for exactly one element on the page. If the selector is valid for more than one element then only the first matching element will be recorded. events array ['mousemove'] A list of events to track. Can include 'mousemove', 'mousedown', and 'mouseup'.","title":"Trial Parameters"},{"location":"extensions/mouse-tracking/#data-generated","text":"Name Type Value mouse_tracking_data array An array of objects containing mouse movement data for the trial. Each object has an x , a y , a t , and an event property. The x and y properties specify the mouse coordinates in pixels relative to the top left corner of the viewport and t specifies the time in milliseconds since the start of the trial. The event will be either 'mousemove', 'mousedown', or 'mouseup' depending on which event was generated. mouse_tracking_targets object An object contain the pixel coordinates of elements on the screen specified by the .targets parameter. Each key in this object will be a selector property, containing the CSS selector string used to find the element. The object corresponding to each key will contain x and y properties specifying the top-left corner of the object, width and height values, plus top , bottom , left , and right parameters which specify the bounding rectangle of the element.","title":"Data Generated"},{"location":"extensions/mouse-tracking/#examples","text":"Record mouse movement data and play it back Code Demo var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; margin: auto;\"></div>' , choices : [ 'Done' ], prompt : \"<p>Move your mouse around inside the square.</p>\" , extensions : [ { type : jsPsychExtensionMouseTracking , params : { targets : [ '#target' ]}} ], data : { task : 'draw' } }; var replay = { type : jsPsychHtmlButtonResponse , stimulus : '<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; margin: auto; position: relative;\"></div>' , choices : [ 'Done' ], prompt : \"<p>Here's the recording of your mouse movements</p>\" , on_load : function (){ var mouseMovements = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. mouse_tracking_data ; var targetRect = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. mouse_tracking_targets [ '#target' ]; var startTime = performance . now (); function draw_frame () { var timeElapsed = performance . now () - startTime ; var points = mouseMovements . filter (( x ) => x . t <= timeElapsed ); var html = `` ; for ( var p of points ){ html += `<div style=\"width: 3px; height: 3px; background-color: blue; position: absolute; top: ${ p . y - 1 - targetRect . top } px; left: ${ p . x - 1 - targetRect . left } px;\"></div>` } document . querySelector ( '#target' ). innerHTML = html ; if ( points . length < mouseMovements . length ) { requestAnimationFrame ( draw_frame ); } } requestAnimationFrame ( draw_frame ); }, data : { task : 'replay' } } Open demo in new tab","title":"Examples"},{"location":"extensions/record-video/","text":"record-video \u00b6 This extension records video from the participant's webcam during a trial. This extension encodes the video data in base 64 format . This is a text-based representation of the video which can be coverted to various video formats using a variety of online tools as well as in languages like python and R. Parameters \u00b6 Initialization Parameters \u00b6 Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionRecordVideo , params : {...}} ] }) Parameter Type Default Value Description None Trial Parameters \u00b6 Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionRecordVideo , params : {...}} ] } Parameter Type Default Value Description None Data Generated \u00b6 Name Type Value record_video_data base64 string Base 64 encoded representation of the video data. Examples \u00b6 Record video data during a trial Code Demo const init_camera = { type : jsPsychInitializeCamera }; const trial = { type : jsPsychHtmlButtonResponse , stimulus : `<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; position: relative; margin: 2em auto;\"> <div class=\"orbit\" style=\"width:25px; height:25px; border-radius:25px;background-color: #f00; position: absolute; top:calc(50% - 12px); left:calc(50% - 12px);\"></div> </div> <style> .orbit { transform: translateX(100px); animation: orbit 4s infinite; } @keyframes orbit { 0% { transform: rotate(0deg) translateX(100px); } 100% { transform: rotate(360deg) translateX(100px); } } </style>` , choices : [ 'Done' ], prompt : \"<p>Video is recording. Click done after a few seconds.</p>\" , extensions : [ { type : jsPsychExtensionRecordVideo } ] }; Open demo in new tab","title":"record-video"},{"location":"extensions/record-video/#record-video","text":"This extension records video from the participant's webcam during a trial. This extension encodes the video data in base 64 format . This is a text-based representation of the video which can be coverted to various video formats using a variety of online tools as well as in languages like python and R.","title":"record-video"},{"location":"extensions/record-video/#parameters","text":"","title":"Parameters"},{"location":"extensions/record-video/#initialization-parameters","text":"Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionRecordVideo , params : {...}} ] }) Parameter Type Default Value Description None","title":"Initialization Parameters"},{"location":"extensions/record-video/#trial-parameters","text":"Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionRecordVideo , params : {...}} ] } Parameter Type Default Value Description None","title":"Trial Parameters"},{"location":"extensions/record-video/#data-generated","text":"Name Type Value record_video_data base64 string Base 64 encoded representation of the video data.","title":"Data Generated"},{"location":"extensions/record-video/#examples","text":"Record video data during a trial Code Demo const init_camera = { type : jsPsychInitializeCamera }; const trial = { type : jsPsychHtmlButtonResponse , stimulus : `<div id=\"target\" style=\"width:250px; height: 250px; background-color: #333; position: relative; margin: 2em auto;\"> <div class=\"orbit\" style=\"width:25px; height:25px; border-radius:25px;background-color: #f00; position: absolute; top:calc(50% - 12px); left:calc(50% - 12px);\"></div> </div> <style> .orbit { transform: translateX(100px); animation: orbit 4s infinite; } @keyframes orbit { 0% { transform: rotate(0deg) translateX(100px); } 100% { transform: rotate(360deg) translateX(100px); } } </style>` , choices : [ 'Done' ], prompt : \"<p>Video is recording. Click done after a few seconds.</p>\" , extensions : [ { type : jsPsychExtensionRecordVideo } ] }; Open demo in new tab","title":"Examples"},{"location":"extensions/webgazer/","text":"webgazer \u00b6 This extension supports eye tracking through the WebGazer library. For a narrative description of how to use this extension see the eye tracking overview . Parameters \u00b6 Initialization Parameters \u00b6 Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer , params : {...}} ] }) Parameter Type Default Value Description webgazer object undefined You can explicitly pass a reference to a loaded instance of the webgazer.js library. If no explicit reference is passed then the extension will look for a global webgazer object. If you are loading webgazer.js via a <script> tag you do not need to set this parameter in most circumstances. auto_initialize bool false Whether to automatically initialize webgazer when the experiment begins. If set to true then the experiment will attempt to access the user's webcam immediately upon page load. The default value is false because it is probably a good idea to explain to the user why camera permission will be needed before asking for it. The webgazer-init-camera plugin can be used to initialize the camera during the experiment. round_predictions bool true Whether to round the x , y coordinates predicted by WebGazer to the nearest whole number. This greatly reduces the size of the data, as WebGazer records data to 15 decimal places by default. Given the noise of the system, there's really no need to record data to this level of precision. sampling_interval numeric 34 Sets the interval between gaze predictions. Because the underlying code is partially asynchronous, this interval is only approximate. The sampling interval will not be faster than this, on average, but the time between samples may fluctuate. Setting the interval too fast will create performance problems and produce redundant data, as the video feed from most webcams only updates about 30 times per second. Trial Parameters \u00b6 Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionWebgazer , params : {...}} ] } Parameter Type Default Value Description targets array [] A list of elements on the page that you would like to record the coordinates of for comparison with the WebGazer data. Each entry in the array should be a valid CSS selector string that identifies the element. The selector string should be valid for exactly one element on the page. If the selector is valid for more than one element then only the first matching element will be recorded. Data Generated \u00b6 Name Type Value webgazer_data array An array of objects containing gaze data for the trial. Each object has an x , a y , and a t property. The x and y properties specify the gaze location in pixels and t specifies the time in milliseconds since the start of the trial. webgazer_targets object An object contain the pixel coordinates of elements on the screen specified by the .targets parameter. Each key in this object will be a selector property, containing the CSS selector string used to find the element. The object corresponding to each key will contain x and y properties specifying the top-left corner of the object, width and height values, plus top , bottom , left , and right parameters which specify the bounding rectangle of the element. Functions \u00b6 In addition to the jsPsych webgazer-* plugins, the jsPsych webgazer extension provides a set of functions that allow the researcher to interact more directly with WebGazer. These functions can be called at any point during an experiment, and are crucial for building trial plugins that interact with WebGazer. All of the functions below must be prefixed with jsPsych.extensions.webgazer (e.g. jsPsych.extensions.webgazer.faceDetected() ). start() \u00b6 Performs initialization of webgazer, including requesting permissions from the user to access the camera. Returns a Promise that resolves when the camera is initialized and fails if the camera cannot be accessed, e.g., because the user denies permission. This is handled automatically if using the webgazer-init-camera plugin or setting auto_initialize to true in the extension parameters. isInitialized() \u00b6 Returns true if start() has been successfully called at some point, and false otherwise. faceDetected() \u00b6 Returns true if WebGazer is ready to make predictions ( webgazer.getTracker().predictionReady is true ). showPredictions() \u00b6 Turns on WebGazer's real-time visualization of predicted gaze location. hidePredictions() \u00b6 Turns off WebGazer's real-time visualization of predicted gaze location. showVideo() \u00b6 Turns on a display of the webcam image, guiding box for positioning the face, and WebGazer's estimate of the location of facial landmarks. hideVideo() \u00b6 Turns off the camera display. resume() \u00b6 Turns on gaze prediction. The extension will automatically handle this for you in most cases. You probably only need to use this if you are writing your own plugin that interfaces directly with WebGazer. pause() \u00b6 Turns off gaze prediction. The extension will automatically handle this for you in most cases. You probably only need to use this if you are writing your own plugin that interfaces directly with WebGazer. resetCalibration() \u00b6 Clears all calibration data. startMouseCalibration() \u00b6 Turns on mouse movement and mouse clicks as calibration events. While the webgazer-calibration plugin can also be used to run a parmeterized calibration routine, this calibration function call allows you to continuously calibrate WebGazer to any mouse movements or clicks throughout the experiment. For example, any *-button-response trial would also function as a WebGazer calibration event. stopMouseCalibration() \u00b6 Stops WebGazer from using mouse movements and mouse clicks as calibration events. calibratePoint(x, y) \u00b6 Instructs WebGazer to register the location x , y (in screen pixel coordinates) as a calibration event. Can be used for passive viewing calibration, i.e., instructing participants to fixate at a particular location. setRegressionType(regression_type) \u00b6 Change the method that WebGazer is using to perform feature -> location regression. Valid options are ridge , weightedRidge , and threadedRidge . See the WebGazer docs for more information about these options. The extension uses the default mode specified by WebGazer (currently ridge ). getCurrentPrediction() \u00b6 Get the current predicted gaze location from WebGazer. This returns a Promise that resolves once WebGazer has finished computing the gaze prediction. The Promise has a single parameter with an object with x , y , and, t parameters. t will be the value of performance.now() at approximately the time that the video frame was recorded. startSampleInterval(interval) \u00b6 Starts sampling gaze predictions every interval milliseconds. If interval is left undefined then the default value at extension initialization is used. Every sample will trigger an onGazeUpdate callback, as well as side effects that result in data storage within the extension. stopSampleInterval() \u00b6 Stops the sampling started by startSampleInterval() . onGazeUpdate(callback) \u00b6 Subscribe to gaze updates. The callback will be invoked every time a new gaze prediction is generated. The first argument of the callback will be an object with x , y , and, if currently in a trial with the extension turned on, the time t in ms since the start of the trial. t will be the value of performance.now() at approximately the time that the video frame was recorded. If currently in an active trial then t will be relative to the start of the trial. This function returns a close handler. When you no longer need to subscribe to gaze updates, call the close handler. Example: var cancelGazeUpdateHandler = jsPsych . extensions . webgazer . onGazeUpdate ( function ( prediction ){ console . log ( `Currently looking at ${ prediction . x } , ${ prediction . y } ` ); }); cancelGazeUpdateHandler (); You can add multiple handlers. Handlers are not closed automatically, so be sure to cancel them when no longer needed.","title":"webgazer"},{"location":"extensions/webgazer/#webgazer","text":"This extension supports eye tracking through the WebGazer library. For a narrative description of how to use this extension see the eye tracking overview .","title":"webgazer"},{"location":"extensions/webgazer/#parameters","text":"","title":"Parameters"},{"location":"extensions/webgazer/#initialization-parameters","text":"Initialization parameters can be set when calling initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer , params : {...}} ] }) Parameter Type Default Value Description webgazer object undefined You can explicitly pass a reference to a loaded instance of the webgazer.js library. If no explicit reference is passed then the extension will look for a global webgazer object. If you are loading webgazer.js via a <script> tag you do not need to set this parameter in most circumstances. auto_initialize bool false Whether to automatically initialize webgazer when the experiment begins. If set to true then the experiment will attempt to access the user's webcam immediately upon page load. The default value is false because it is probably a good idea to explain to the user why camera permission will be needed before asking for it. The webgazer-init-camera plugin can be used to initialize the camera during the experiment. round_predictions bool true Whether to round the x , y coordinates predicted by WebGazer to the nearest whole number. This greatly reduces the size of the data, as WebGazer records data to 15 decimal places by default. Given the noise of the system, there's really no need to record data to this level of precision. sampling_interval numeric 34 Sets the interval between gaze predictions. Because the underlying code is partially asynchronous, this interval is only approximate. The sampling interval will not be faster than this, on average, but the time between samples may fluctuate. Setting the interval too fast will create performance problems and produce redundant data, as the video feed from most webcams only updates about 30 times per second.","title":"Initialization Parameters"},{"location":"extensions/webgazer/#trial-parameters","text":"Trial parameters can be set when adding the extension to a trial object. var trial = { type : jsPsych ..., extensions : [ { type : jsPsychExtensionWebgazer , params : {...}} ] } Parameter Type Default Value Description targets array [] A list of elements on the page that you would like to record the coordinates of for comparison with the WebGazer data. Each entry in the array should be a valid CSS selector string that identifies the element. The selector string should be valid for exactly one element on the page. If the selector is valid for more than one element then only the first matching element will be recorded.","title":"Trial Parameters"},{"location":"extensions/webgazer/#data-generated","text":"Name Type Value webgazer_data array An array of objects containing gaze data for the trial. Each object has an x , a y , and a t property. The x and y properties specify the gaze location in pixels and t specifies the time in milliseconds since the start of the trial. webgazer_targets object An object contain the pixel coordinates of elements on the screen specified by the .targets parameter. Each key in this object will be a selector property, containing the CSS selector string used to find the element. The object corresponding to each key will contain x and y properties specifying the top-left corner of the object, width and height values, plus top , bottom , left , and right parameters which specify the bounding rectangle of the element.","title":"Data Generated"},{"location":"extensions/webgazer/#functions","text":"In addition to the jsPsych webgazer-* plugins, the jsPsych webgazer extension provides a set of functions that allow the researcher to interact more directly with WebGazer. These functions can be called at any point during an experiment, and are crucial for building trial plugins that interact with WebGazer. All of the functions below must be prefixed with jsPsych.extensions.webgazer (e.g. jsPsych.extensions.webgazer.faceDetected() ).","title":"Functions"},{"location":"extensions/webgazer/#start","text":"Performs initialization of webgazer, including requesting permissions from the user to access the camera. Returns a Promise that resolves when the camera is initialized and fails if the camera cannot be accessed, e.g., because the user denies permission. This is handled automatically if using the webgazer-init-camera plugin or setting auto_initialize to true in the extension parameters.","title":"start()"},{"location":"extensions/webgazer/#isinitialized","text":"Returns true if start() has been successfully called at some point, and false otherwise.","title":"isInitialized()"},{"location":"extensions/webgazer/#facedetected","text":"Returns true if WebGazer is ready to make predictions ( webgazer.getTracker().predictionReady is true ).","title":"faceDetected()"},{"location":"extensions/webgazer/#showpredictions","text":"Turns on WebGazer's real-time visualization of predicted gaze location.","title":"showPredictions()"},{"location":"extensions/webgazer/#hidepredictions","text":"Turns off WebGazer's real-time visualization of predicted gaze location.","title":"hidePredictions()"},{"location":"extensions/webgazer/#showvideo","text":"Turns on a display of the webcam image, guiding box for positioning the face, and WebGazer's estimate of the location of facial landmarks.","title":"showVideo()"},{"location":"extensions/webgazer/#hidevideo","text":"Turns off the camera display.","title":"hideVideo()"},{"location":"extensions/webgazer/#resume","text":"Turns on gaze prediction. The extension will automatically handle this for you in most cases. You probably only need to use this if you are writing your own plugin that interfaces directly with WebGazer.","title":"resume()"},{"location":"extensions/webgazer/#pause","text":"Turns off gaze prediction. The extension will automatically handle this for you in most cases. You probably only need to use this if you are writing your own plugin that interfaces directly with WebGazer.","title":"pause()"},{"location":"extensions/webgazer/#resetcalibration","text":"Clears all calibration data.","title":"resetCalibration()"},{"location":"extensions/webgazer/#startmousecalibration","text":"Turns on mouse movement and mouse clicks as calibration events. While the webgazer-calibration plugin can also be used to run a parmeterized calibration routine, this calibration function call allows you to continuously calibrate WebGazer to any mouse movements or clicks throughout the experiment. For example, any *-button-response trial would also function as a WebGazer calibration event.","title":"startMouseCalibration()"},{"location":"extensions/webgazer/#stopmousecalibration","text":"Stops WebGazer from using mouse movements and mouse clicks as calibration events.","title":"stopMouseCalibration()"},{"location":"extensions/webgazer/#calibratepointx-y","text":"Instructs WebGazer to register the location x , y (in screen pixel coordinates) as a calibration event. Can be used for passive viewing calibration, i.e., instructing participants to fixate at a particular location.","title":"calibratePoint(x, y)"},{"location":"extensions/webgazer/#setregressiontyperegression_type","text":"Change the method that WebGazer is using to perform feature -> location regression. Valid options are ridge , weightedRidge , and threadedRidge . See the WebGazer docs for more information about these options. The extension uses the default mode specified by WebGazer (currently ridge ).","title":"setRegressionType(regression_type)"},{"location":"extensions/webgazer/#getcurrentprediction","text":"Get the current predicted gaze location from WebGazer. This returns a Promise that resolves once WebGazer has finished computing the gaze prediction. The Promise has a single parameter with an object with x , y , and, t parameters. t will be the value of performance.now() at approximately the time that the video frame was recorded.","title":"getCurrentPrediction()"},{"location":"extensions/webgazer/#startsampleintervalinterval","text":"Starts sampling gaze predictions every interval milliseconds. If interval is left undefined then the default value at extension initialization is used. Every sample will trigger an onGazeUpdate callback, as well as side effects that result in data storage within the extension.","title":"startSampleInterval(interval)"},{"location":"extensions/webgazer/#stopsampleinterval","text":"Stops the sampling started by startSampleInterval() .","title":"stopSampleInterval()"},{"location":"extensions/webgazer/#ongazeupdatecallback","text":"Subscribe to gaze updates. The callback will be invoked every time a new gaze prediction is generated. The first argument of the callback will be an object with x , y , and, if currently in a trial with the extension turned on, the time t in ms since the start of the trial. t will be the value of performance.now() at approximately the time that the video frame was recorded. If currently in an active trial then t will be relative to the start of the trial. This function returns a close handler. When you no longer need to subscribe to gaze updates, call the close handler. Example: var cancelGazeUpdateHandler = jsPsych . extensions . webgazer . onGazeUpdate ( function ( prediction ){ console . log ( `Currently looking at ${ prediction . x } , ${ prediction . y } ` ); }); cancelGazeUpdateHandler (); You can add multiple handlers. Handlers are not closed automatically, so be sure to cancel them when no longer needed.","title":"onGazeUpdate(callback)"},{"location":"overview/browser-device-support/","text":"Browser and Device Support \u00b6 Desktop and Laptop Browsers \u00b6 Supported jsPsych supports recent versions of the four most commonly-used web browsers: Chrome Firefox Safari Edge This means that jsPsych should work on these browsers. If something doesn't work as you expect on one of the browsers above, it might be a bug that should be fixed. You can search for and report bugs on the jsPsych GitHub Issues page . We're very grateful for anyone who takes the time to report bugs - it helps improve the library for everyone! Unsupported There are many other web browsers that are available, but that are not commonly used. The most well-known of these are Internet Explorer and Opera. jsPsych is not tested on these and other browsers not listed in the Supported section above. jsPsych experiments might work in these browsers, but they might not . If you want to give participants the option to use unsupported browsers, then we recommend carefully testing your experiment to make sure that everything works as expected. Otherwise, we suggest asking your participants to only use a supported browser, or incorporating browser, device, and/or feature checks at the start of your experiment. jsPsych offers built-in methods for exclusion based on minimum browser size and WebAudio API compatibility . You can incorporate other browser/device/feature checks into your experiment by adding custom JavaScript code. Mobile Devices \u00b6 In general, jsPsych experiments can be run on mobile devices (smartphones and tablets). However, certain plugins will not work on mobile. For instance, any plugin that requires a keyboard response without a text input box, such as the *-keyboard-response plugins, will not work. Even plugins that do work on mobile might work differently than they do on desktop and laptop computers. For instance, on mobile devices, a text input box will cause an on-screen keyboard to pop up, which affects the visible content on the screen. If you plan to run an experiment that allows people to use mobile devices, we recommend doing some extra testing to make sure that everything works as expected. In particular, you may want to check that: * Font sizes are readable on smaller screens * Stimuli sizes are large enough and appropriate for the task * Page is laid out as intended (e.g. elements are centered and do not overlap) * Response options are touchscreen-friendly (e.g. buttons rather than key presses) * Response options (e.g. buttons, text boxes, radio buttons) are large enough and far enough apart to be easily selected with a finger tap It's possible to use your browser's developer tools to emulate mobile devices ( this page shows how to do it in Chrome ), which is useful for getting a sense of how your experiment will look on mobile devices. Just be aware that there are limitations to emulator tools, and there are some aspects of mobile devices/browsers that a desktop browser will not be able to simulate. Mobile Browsers \u00b6 The browser options for mobile phones and tablets are slightly different than those for desktop and laptop computers. In addition to mobile versions of Chrome, Firefox, Safari, and Edge, other notable mobile browsers include Opera Mobile, Samsung Internet, UC Browser, and Dolphin. Because of the greater diversity of mobile browsers and volatility in their usage statistics, jsPsych does not officially support any particular set of mobile browsers. However, we do anticipate that most experiments should work in most mobile browsers, especially the mobile versions of browsers that we do support in Desktop mode. If you run into a problem using jsPsych in mobile browsers, please report it on the jsPsych GitHub Issues page ! We do our best to fix browser incompatibilities that are not specific to a single experiment.","title":"Browser and Device Support"},{"location":"overview/browser-device-support/#browser-and-device-support","text":"","title":"Browser and Device Support"},{"location":"overview/browser-device-support/#desktop-and-laptop-browsers","text":"Supported jsPsych supports recent versions of the four most commonly-used web browsers: Chrome Firefox Safari Edge This means that jsPsych should work on these browsers. If something doesn't work as you expect on one of the browsers above, it might be a bug that should be fixed. You can search for and report bugs on the jsPsych GitHub Issues page . We're very grateful for anyone who takes the time to report bugs - it helps improve the library for everyone! Unsupported There are many other web browsers that are available, but that are not commonly used. The most well-known of these are Internet Explorer and Opera. jsPsych is not tested on these and other browsers not listed in the Supported section above. jsPsych experiments might work in these browsers, but they might not . If you want to give participants the option to use unsupported browsers, then we recommend carefully testing your experiment to make sure that everything works as expected. Otherwise, we suggest asking your participants to only use a supported browser, or incorporating browser, device, and/or feature checks at the start of your experiment. jsPsych offers built-in methods for exclusion based on minimum browser size and WebAudio API compatibility . You can incorporate other browser/device/feature checks into your experiment by adding custom JavaScript code.","title":"Desktop and Laptop Browsers"},{"location":"overview/browser-device-support/#mobile-devices","text":"In general, jsPsych experiments can be run on mobile devices (smartphones and tablets). However, certain plugins will not work on mobile. For instance, any plugin that requires a keyboard response without a text input box, such as the *-keyboard-response plugins, will not work. Even plugins that do work on mobile might work differently than they do on desktop and laptop computers. For instance, on mobile devices, a text input box will cause an on-screen keyboard to pop up, which affects the visible content on the screen. If you plan to run an experiment that allows people to use mobile devices, we recommend doing some extra testing to make sure that everything works as expected. In particular, you may want to check that: * Font sizes are readable on smaller screens * Stimuli sizes are large enough and appropriate for the task * Page is laid out as intended (e.g. elements are centered and do not overlap) * Response options are touchscreen-friendly (e.g. buttons rather than key presses) * Response options (e.g. buttons, text boxes, radio buttons) are large enough and far enough apart to be easily selected with a finger tap It's possible to use your browser's developer tools to emulate mobile devices ( this page shows how to do it in Chrome ), which is useful for getting a sense of how your experiment will look on mobile devices. Just be aware that there are limitations to emulator tools, and there are some aspects of mobile devices/browsers that a desktop browser will not be able to simulate.","title":"Mobile Devices"},{"location":"overview/browser-device-support/#mobile-browsers","text":"The browser options for mobile phones and tablets are slightly different than those for desktop and laptop computers. In addition to mobile versions of Chrome, Firefox, Safari, and Edge, other notable mobile browsers include Opera Mobile, Samsung Internet, UC Browser, and Dolphin. Because of the greater diversity of mobile browsers and volatility in their usage statistics, jsPsych does not officially support any particular set of mobile browsers. However, we do anticipate that most experiments should work in most mobile browsers, especially the mobile versions of browsers that we do support in Desktop mode. If you run into a problem using jsPsych in mobile browsers, please report it on the jsPsych GitHub Issues page ! We do our best to fix browser incompatibilities that are not specific to a single experiment.","title":"Mobile Browsers"},{"location":"overview/data/","text":"Data in jsPsych: permanent and non-permanent data. \u00b6 There are two very different kinds of data storage: data stored in memory and data stored permanently . Data stored permanently exists even after the browser running jsPsych closes, typically in a database or in a file on a server. Data stored in memory exists only as long the browser window running jsPsych is open. jsPsych has many features for interacting with data stored in memory, but few for permanent data storage. This is a deliberate choice, as there are dozens of ways that data could be stored permanently. jsPsych does not lock you into one particular solution. However, saving data permanently is obviously a crucial component of any experiment, and the second half of this page contains a few suggestions on how to accomplish permanent data storage. Storing data in jsPsych's data structure \u00b6 jsPsych has a centralized collection of data that is built as the experiment runs. Each trial adds to the collection, and you can access the data with various functions, including jsPsych.data.get() , which returns the entire set of data. In most cases, data collection will be automatic and hidden. Plugins save data on their own so it is not uncommon to have the only interaction with the data be at the end of the experiment when it is time to save it in a permanent manner (see sections below about how to do this). However, there are some situations in which you may want to interact with the data; in particular, you may want to store additional data that the plugins are not recording, like a subject identifier or condition assignment. You may also want to add data on a trial by trial basis. For example, in a Stroop paradigm you would want to label which trials are congruent and which are incongruent. These scenarios are explored below. Adding data to all trials \u00b6 Often it is useful to add a piece of data to all of the trials in the experiment. For example, appending the subject ID to each trial. This can be done with the jsPsych.data.addProperties() function. Here is an example: // generate a random subject ID with 15 characters var subject_id = jsPsych . randomization . randomID ( 15 ); // pick a random condition for the subject at the start of the experiment var condition_assignment = jsPsych . randomization . sampleWithoutReplacement ([ 'conditionA' , 'conditionB' , 'conditionC' ], 1 )[ 0 ]; // record the condition assignment in the jsPsych data // this adds a property called 'subject' and a property called 'condition' to every trial jsPsych . data . addProperties ({ subject : subject_id , condition : condition_assignment }); Adding data to a particular trial or set of trials \u00b6 Data can be added to a particular trial by setting the data parameter for the trial. The data parameter is an object of key-value pairs, and each pair is added to the data for that trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.jpg' , data : { image_type : 'A' } } Data declared in this way is also saved in the trials on any nested timelines: var block = { type : jsPsychImageKeyboardResponse , data : { image_type : 'A' }, timeline : [ { stimulus : 'imgA1.jpg' }, { stimulus : 'imgA2.jpg' } ] } The data object for a trial can also be updated in the on_finish event handler. You can override properties or add new ones. This is particularly useful for cases where the value depends on something that happened during the trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.jpg' , on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , 'j' )){ data . correct = true ; } else { data . correct = false ; } } } Aggregating and manipulating jsPsych data \u00b6 When accessing the data with jsPsych.data.get() the returned object is a special data collection object that exposes a number of methods for aggregating and manipulating the data. The full list of methods is detailed in the data module documentation . Here are some examples of data collection manipulation. All data generated by the image-keyboard-response plugin: var data = jsPsych . data . get (). filter ({ trial_type : 'image-keyboard-response' }); All data generated by the categorize-image plugin with a correct response: var data = jsPsych . data . get (). filter ({ trial_type : 'categorize-image' , correct : true }); All data with a response time between 100 and 500ms: var data = jsPsych . data . get (). filterCustom ( function ( x ){ return x . rt >= 100 && x . rt <= 500 }); Applying filters consecutively to get all trials from a particular plugin with a response time above 100ms: var data = jsPsych . data . get (). filter ({ trial_type : 'image-keyboard-response' }). filterCustom ( function ( x ){ return x . rt > 100 ; }); Getting the data from the last n trials: var n = 3 ; var data = jsPsych . data . get (). last ( n ); Getting the data from the last n trials with a correct response: var n = 3 ; var data = jsPsych . data . get (). filter ({ correct : true }). last ( n ); Getting the data from the first n trials: var n = 3 ; var data = jsPsych . data . get (). first ( n ); Counting the number of trials with a correct response in a data collection: var count = jsPsych . data . get (). filter ({ correct : true }). count (); Selecting all of the response times from a data collection: var response_times = jsPsych . data . get (). select ( 'rt' ); Calculating various descriptive statistics on the response times in a data collection: jsPsych . data . get (). select ( 'rt' ). mean (); jsPsych . data . get (). select ( 'rt' ). sum (); jsPsych . data . get (). select ( 'rt' ). min (); jsPsych . data . get (). select ( 'rt' ). max (); jsPsych . data . get (). select ( 'rt' ). variance (); jsPsych . data . get (). select ( 'rt' ). sd (); jsPsych . data . get (). select ( 'rt' ). median (); jsPsych . data . get (). select ( 'rt' ). count (); Storing data permanently as a file \u00b6 This is one of the simplest methods for saving jsPsych data on the server that is running the experiment. It involves a short PHP script and a few lines of JavaScript code. This method will save each participant's data as a CSV file on the server. This method will only work if you are running on a web server with PHP installed, or a local server with PHP (e.g., XAMPP ). This method uses a short PHP script to write files to the server: <?php // get the data from the POST message $post_data = json_decode ( file_get_contents ( 'php://input' ), true ); $data = $post_data [ 'filedata' ]; // generate a unique ID for the file, e.g., session-6feu833950202 $file = uniqid ( \"session-\" ); // the directory \"data\" must be writable by the server $name = \"data/ { $file } .csv\" ; // write the file to disk file_put_contents ( $name , $data ); ?> The file_put_contents($name, $data) method requires permission to write new files. An easy way to solve this is to create a directory on the server that will store the data and use the chmod command to give all users write permission to that directory. In the above example, the directory data/ is used to store files. To use the PHP script, the JavaScript that runs jsPsych needs to send the filedata information. This is done through an AJAX call. function saveData ( name , data ){ var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); // 'write_data.php' is the path to the php file described above. xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . send ( JSON . stringify ({ filedata : data })); } // call the saveData function after the experiment is over initJsPsych ({ on_finish : function (){ saveData ( jsPsych . data . get (). csv ()); } }); Danger The example above has minimal security and should probably not be used without additional security measures put in place. The risk is that someone can write arbitrary data using the saveData() function and store it to a file on your webserver. If they can guess the file name generated by the PHP script, or access a directory listing containing all of the filenames, then they can potentially write executable code to your server and run it. One fix is to store the CSV files outside the web directory on the server. This requires changing the path in the PHP script above from /data to a folder that is not accessible on the web. You should only use this solution if you have access to more than just the web directory on your server. You can also configure your web server to block access to the folder you are storing data in . The MySQL option below is more secure. Storing data permanently in a MySQL database \u00b6 Another solution for storing data generated by jsPsych is to write it to a database. There are dozens of database options. MySQL is one of the most popular relational databases , is free to use, and relatively easy to install . This code will assume that you have a MySQL database installed on your server that is hosting the jsPsych experiment, and that your server is able to execute PHP code. If you are trying to run on a local machine, you'll need to install a local server environment like XAMPP . You'll need two PHP scripts. The first is a configuration file for your database. Save it as database_config.php on your server. Within this file are configuration options for the database. You'll need to change these according to how you have configured your MySQL installation. <?php $servername = \"localhost\" ; $port = 3306 ; $username = \"username\" ; $password = \"password\" ; $dbname = \"database\" ; $table = \"tablename\" ; ?> The second PHP file will write data to the database. This script reads the database to discover what columns are in the table, and then only allows data to be entered in that matches those columns. This is a security feature. Save this file as write_data.php on your server. <?php // this path should point to your configuration file. include ( 'database_config.php' ); $data_array = json_decode ( file_get_contents ( 'php://input' ), true ); try { $conn = new PDO ( \"mysql:host= $servername ;port= $port ;dbname= $dbname \" , $username , $password ); $conn -> setAttribute ( PDO :: ATTR_ERRMODE , PDO :: ERRMODE_EXCEPTION ); // First stage is to get all column names from the table and store // them in $col_names array. $stmt = $conn -> prepare ( \"SHOW COLUMNS FROM ` $table `\" ); $stmt -> execute (); $col_names = array (); while ( $row = $stmt -> fetchColumn ()) { $col_names [] = $row ; } // Second stage is to create prepared SQL statement using the column // names as a guide to what values might be in the JSON. // If a value is missing from a particular trial, then NULL is inserted $sql = \"INSERT INTO $table VALUES(\" ; for ( $i = 0 ; $i < count ( $col_names ); $i ++ ){ $name = $col_names [ $i ]; $sql .= \": $name \" ; if ( $i != count ( $col_names ) - 1 ){ $sql .= \", \" ; } } $sql .= \");\" ; $insertstmt = $conn -> prepare ( $sql ); for ( $i = 0 ; $i < count ( $data_array ); $i ++ ){ for ( $j = 0 ; $j < count ( $col_names ); $j ++ ){ $colname = $col_names [ $j ]; if ( ! isset ( $data_array [ $i ][ $colname ])){ $insertstmt -> bindValue ( \": $colname \" , null , PDO :: PARAM_NULL ); } else { $insertstmt -> bindValue ( \": $colname \" , $data_array [ $i ][ $colname ]); } } $insertstmt -> execute (); } echo '{\"success\": true}' ; } catch ( PDOException $e ) { echo '{\"success\": false, \"message\": ' . $e -> getMessage (); } $conn = null ; ?> To send the data, we use an XMLHttpRequest request in JavaScript. function saveData () { var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); // change 'write_data.php' to point to php script. xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . onload = function () { if ( xhr . status == 200 ){ var response = JSON . parse ( xhr . responseText ); console . log ( response . success ); } }; xhr . send ( jsPsych . data . get (). json ()); } It's important that the XMLHttpRequest is able to complete before the experiment is closed. If you invoke the saveData() function at the end of your experiment and the participant closes the window before all of the data has been transferred you will lose that data. To mitigate this risk, you can use the call-function plugin's async option to prevent the experiment from progressing until the request is complete. var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . onload = function () { if ( xhr . status == 200 ){ var response = JSON . parse ( xhr . responseText ); console . log ( response . success ); } done (); // invoking done() causes experiment to progress to next trial. }; xhr . send ( jsPsych . data . get (). json ()); } }","title":"Data Storage, Aggregation, and Manipulation"},{"location":"overview/data/#data-in-jspsych-permanent-and-non-permanent-data","text":"There are two very different kinds of data storage: data stored in memory and data stored permanently . Data stored permanently exists even after the browser running jsPsych closes, typically in a database or in a file on a server. Data stored in memory exists only as long the browser window running jsPsych is open. jsPsych has many features for interacting with data stored in memory, but few for permanent data storage. This is a deliberate choice, as there are dozens of ways that data could be stored permanently. jsPsych does not lock you into one particular solution. However, saving data permanently is obviously a crucial component of any experiment, and the second half of this page contains a few suggestions on how to accomplish permanent data storage.","title":"Data in jsPsych: permanent and non-permanent data."},{"location":"overview/data/#storing-data-in-jspsychs-data-structure","text":"jsPsych has a centralized collection of data that is built as the experiment runs. Each trial adds to the collection, and you can access the data with various functions, including jsPsych.data.get() , which returns the entire set of data. In most cases, data collection will be automatic and hidden. Plugins save data on their own so it is not uncommon to have the only interaction with the data be at the end of the experiment when it is time to save it in a permanent manner (see sections below about how to do this). However, there are some situations in which you may want to interact with the data; in particular, you may want to store additional data that the plugins are not recording, like a subject identifier or condition assignment. You may also want to add data on a trial by trial basis. For example, in a Stroop paradigm you would want to label which trials are congruent and which are incongruent. These scenarios are explored below.","title":"Storing data in jsPsych's data structure"},{"location":"overview/data/#adding-data-to-all-trials","text":"Often it is useful to add a piece of data to all of the trials in the experiment. For example, appending the subject ID to each trial. This can be done with the jsPsych.data.addProperties() function. Here is an example: // generate a random subject ID with 15 characters var subject_id = jsPsych . randomization . randomID ( 15 ); // pick a random condition for the subject at the start of the experiment var condition_assignment = jsPsych . randomization . sampleWithoutReplacement ([ 'conditionA' , 'conditionB' , 'conditionC' ], 1 )[ 0 ]; // record the condition assignment in the jsPsych data // this adds a property called 'subject' and a property called 'condition' to every trial jsPsych . data . addProperties ({ subject : subject_id , condition : condition_assignment });","title":"Adding data to all trials"},{"location":"overview/data/#adding-data-to-a-particular-trial-or-set-of-trials","text":"Data can be added to a particular trial by setting the data parameter for the trial. The data parameter is an object of key-value pairs, and each pair is added to the data for that trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.jpg' , data : { image_type : 'A' } } Data declared in this way is also saved in the trials on any nested timelines: var block = { type : jsPsychImageKeyboardResponse , data : { image_type : 'A' }, timeline : [ { stimulus : 'imgA1.jpg' }, { stimulus : 'imgA2.jpg' } ] } The data object for a trial can also be updated in the on_finish event handler. You can override properties or add new ones. This is particularly useful for cases where the value depends on something that happened during the trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.jpg' , on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , 'j' )){ data . correct = true ; } else { data . correct = false ; } } }","title":"Adding data to a particular trial or set of trials"},{"location":"overview/data/#aggregating-and-manipulating-jspsych-data","text":"When accessing the data with jsPsych.data.get() the returned object is a special data collection object that exposes a number of methods for aggregating and manipulating the data. The full list of methods is detailed in the data module documentation . Here are some examples of data collection manipulation. All data generated by the image-keyboard-response plugin: var data = jsPsych . data . get (). filter ({ trial_type : 'image-keyboard-response' }); All data generated by the categorize-image plugin with a correct response: var data = jsPsych . data . get (). filter ({ trial_type : 'categorize-image' , correct : true }); All data with a response time between 100 and 500ms: var data = jsPsych . data . get (). filterCustom ( function ( x ){ return x . rt >= 100 && x . rt <= 500 }); Applying filters consecutively to get all trials from a particular plugin with a response time above 100ms: var data = jsPsych . data . get (). filter ({ trial_type : 'image-keyboard-response' }). filterCustom ( function ( x ){ return x . rt > 100 ; }); Getting the data from the last n trials: var n = 3 ; var data = jsPsych . data . get (). last ( n ); Getting the data from the last n trials with a correct response: var n = 3 ; var data = jsPsych . data . get (). filter ({ correct : true }). last ( n ); Getting the data from the first n trials: var n = 3 ; var data = jsPsych . data . get (). first ( n ); Counting the number of trials with a correct response in a data collection: var count = jsPsych . data . get (). filter ({ correct : true }). count (); Selecting all of the response times from a data collection: var response_times = jsPsych . data . get (). select ( 'rt' ); Calculating various descriptive statistics on the response times in a data collection: jsPsych . data . get (). select ( 'rt' ). mean (); jsPsych . data . get (). select ( 'rt' ). sum (); jsPsych . data . get (). select ( 'rt' ). min (); jsPsych . data . get (). select ( 'rt' ). max (); jsPsych . data . get (). select ( 'rt' ). variance (); jsPsych . data . get (). select ( 'rt' ). sd (); jsPsych . data . get (). select ( 'rt' ). median (); jsPsych . data . get (). select ( 'rt' ). count ();","title":"Aggregating and manipulating jsPsych data"},{"location":"overview/data/#storing-data-permanently-as-a-file","text":"This is one of the simplest methods for saving jsPsych data on the server that is running the experiment. It involves a short PHP script and a few lines of JavaScript code. This method will save each participant's data as a CSV file on the server. This method will only work if you are running on a web server with PHP installed, or a local server with PHP (e.g., XAMPP ). This method uses a short PHP script to write files to the server: <?php // get the data from the POST message $post_data = json_decode ( file_get_contents ( 'php://input' ), true ); $data = $post_data [ 'filedata' ]; // generate a unique ID for the file, e.g., session-6feu833950202 $file = uniqid ( \"session-\" ); // the directory \"data\" must be writable by the server $name = \"data/ { $file } .csv\" ; // write the file to disk file_put_contents ( $name , $data ); ?> The file_put_contents($name, $data) method requires permission to write new files. An easy way to solve this is to create a directory on the server that will store the data and use the chmod command to give all users write permission to that directory. In the above example, the directory data/ is used to store files. To use the PHP script, the JavaScript that runs jsPsych needs to send the filedata information. This is done through an AJAX call. function saveData ( name , data ){ var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); // 'write_data.php' is the path to the php file described above. xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . send ( JSON . stringify ({ filedata : data })); } // call the saveData function after the experiment is over initJsPsych ({ on_finish : function (){ saveData ( jsPsych . data . get (). csv ()); } }); Danger The example above has minimal security and should probably not be used without additional security measures put in place. The risk is that someone can write arbitrary data using the saveData() function and store it to a file on your webserver. If they can guess the file name generated by the PHP script, or access a directory listing containing all of the filenames, then they can potentially write executable code to your server and run it. One fix is to store the CSV files outside the web directory on the server. This requires changing the path in the PHP script above from /data to a folder that is not accessible on the web. You should only use this solution if you have access to more than just the web directory on your server. You can also configure your web server to block access to the folder you are storing data in . The MySQL option below is more secure.","title":"Storing data permanently as a file"},{"location":"overview/data/#storing-data-permanently-in-a-mysql-database","text":"Another solution for storing data generated by jsPsych is to write it to a database. There are dozens of database options. MySQL is one of the most popular relational databases , is free to use, and relatively easy to install . This code will assume that you have a MySQL database installed on your server that is hosting the jsPsych experiment, and that your server is able to execute PHP code. If you are trying to run on a local machine, you'll need to install a local server environment like XAMPP . You'll need two PHP scripts. The first is a configuration file for your database. Save it as database_config.php on your server. Within this file are configuration options for the database. You'll need to change these according to how you have configured your MySQL installation. <?php $servername = \"localhost\" ; $port = 3306 ; $username = \"username\" ; $password = \"password\" ; $dbname = \"database\" ; $table = \"tablename\" ; ?> The second PHP file will write data to the database. This script reads the database to discover what columns are in the table, and then only allows data to be entered in that matches those columns. This is a security feature. Save this file as write_data.php on your server. <?php // this path should point to your configuration file. include ( 'database_config.php' ); $data_array = json_decode ( file_get_contents ( 'php://input' ), true ); try { $conn = new PDO ( \"mysql:host= $servername ;port= $port ;dbname= $dbname \" , $username , $password ); $conn -> setAttribute ( PDO :: ATTR_ERRMODE , PDO :: ERRMODE_EXCEPTION ); // First stage is to get all column names from the table and store // them in $col_names array. $stmt = $conn -> prepare ( \"SHOW COLUMNS FROM ` $table `\" ); $stmt -> execute (); $col_names = array (); while ( $row = $stmt -> fetchColumn ()) { $col_names [] = $row ; } // Second stage is to create prepared SQL statement using the column // names as a guide to what values might be in the JSON. // If a value is missing from a particular trial, then NULL is inserted $sql = \"INSERT INTO $table VALUES(\" ; for ( $i = 0 ; $i < count ( $col_names ); $i ++ ){ $name = $col_names [ $i ]; $sql .= \": $name \" ; if ( $i != count ( $col_names ) - 1 ){ $sql .= \", \" ; } } $sql .= \");\" ; $insertstmt = $conn -> prepare ( $sql ); for ( $i = 0 ; $i < count ( $data_array ); $i ++ ){ for ( $j = 0 ; $j < count ( $col_names ); $j ++ ){ $colname = $col_names [ $j ]; if ( ! isset ( $data_array [ $i ][ $colname ])){ $insertstmt -> bindValue ( \": $colname \" , null , PDO :: PARAM_NULL ); } else { $insertstmt -> bindValue ( \": $colname \" , $data_array [ $i ][ $colname ]); } } $insertstmt -> execute (); } echo '{\"success\": true}' ; } catch ( PDOException $e ) { echo '{\"success\": false, \"message\": ' . $e -> getMessage (); } $conn = null ; ?> To send the data, we use an XMLHttpRequest request in JavaScript. function saveData () { var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); // change 'write_data.php' to point to php script. xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . onload = function () { if ( xhr . status == 200 ){ var response = JSON . parse ( xhr . responseText ); console . log ( response . success ); } }; xhr . send ( jsPsych . data . get (). json ()); } It's important that the XMLHttpRequest is able to complete before the experiment is closed. If you invoke the saveData() function at the end of your experiment and the participant closes the window before all of the data has been transferred you will lose that data. To mitigate this risk, you can use the call-function plugin's async option to prevent the experiment from progressing until the request is complete. var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ var xhr = new XMLHttpRequest (); xhr . open ( 'POST' , 'write_data.php' ); xhr . setRequestHeader ( 'Content-Type' , 'application/json' ); xhr . onload = function () { if ( xhr . status == 200 ){ var response = JSON . parse ( xhr . responseText ); console . log ( response . success ); } done (); // invoking done() causes experiment to progress to next trial. }; xhr . send ( jsPsych . data . get (). json ()); } }","title":"Storing data permanently in a MySQL database"},{"location":"overview/dynamic-parameters/","text":"Dynamic parameters \u00b6 Most trial parameters can also be specified as functions. In a typical declaration of a jsPsych trial, parameters are known at the start of the experiment. This makes it impossible to alter the content of the trial based on the outcome of previous trials. However, when functions are used as the parameter value, the function is evaluated right before the trial starts, and the return value of the function is used as the parameter value for that trial . This enables dynamic updating of the parameter based on data that a participant has generated or any other information that you do not know in advance. Examples \u00b6 Providing Feedback \u00b6 Here is a sketch of how this functionality could be used to display feedback to a participant in the Flanker Task. var timeline = []; var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' }, on_finish : function ( data ){ // Score the keyboard response as correct or incorrect. if ( jsPsych . pluginAPI . compareKeys ( data . response , \"f\" )){ data . correct = true ; } else { data . correct = false ; } } } var feedback = { type : jsPsychHtmlKeyboardResponse , trial_duration : 1000 , stimulus : function (){ // The feedback stimulus is a dynamic parameter because we can't know in advance whether // the stimulus should be 'correct' or 'incorrect'. // Instead, this function will check the accuracy of the last response and use that information to set // the stimulus value on each trial. var last_trial_correct = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. correct ; if ( last_trial_correct ){ return \"<p>Correct!</p>\" ; // the parameter value has to be returned from the function } else { return \"<p>Wrong.</p>\" ; // the parameter value has to be returned from the function } } } timeline . push ( trial , feedback ); Note When scoring a participant's response, the jsPsych.pluginAPI.compareKeys function is only needed to compare keyboard responses. For other kinds of response types, such as button presses, you can compare the participant's response and correct response values directly, e.g. if ( data . response == 0 )){ data . correct = true ; } else { data . correct = false ; } Or: data . correct = data . response === data . correct_response ; Randomizing a parameter value \u00b6 Here's an example of using a dynamic parameter to randomize the inter-trial interval (ITI) duration. This time, the dynamic parameter is created using a named function instead of an anonymous function. var random_duration = function () { var rand_dur = jsPsych . randomization . sampleWithoutReplacement ([ 500 , 600 , 700 , 800 ], 1 )[ 0 ]; return rand_dur ; } var trial = { type : jsPsychHtmlKeyboardResponse stimulus : '+' , post_trial_gap : random_duration // if you use a named function for a dynamic parameter, then just use the function name (without parentheses after it) } Storing changing variables in the data \u00b6 The trial's data parameter can be also function, which is useful for when you want to save information to the data that can change during the experiment. For example, if you have a global variable called current_difficulty that tracks the difficulty level in an adaptive task, you can save the current value of this variable to the trial data like this: var current_difficulty ; // value changes during the experiment var trial = { type : jsPsychSurveyText , questions : [{ prompt : \"Please enter your response.\" }] data : function () { return { difficulty : current_difficulty }; } } It's also possible to use a function for any of the individual properties in the trial's data object, for instance if you want to combine static and dynamic information in the data: var trial = { type : jsPsychSurveyText , questions : [{ prompt : \"Please enter your response.\" }] data : { difficulty : function () { return current_difficulty ; // the difficulty value changes during the experiment }, task_part : 'recall' , // this part of the data is always the same block_number : 1 } } Nested Parameters \u00b6 Dyanmic parameters work the same way with nested parameters, which are parameters that contain one or more sets of other parameters. For instance, many survey-* plugins have a questions parameter that is a nested parameter: it is an array that contains the parameters for one or more questions on the page. To make the questions parameter dynamic, you can use a function that returns the array with all of the parameters for each question: var subject_id ; // value is set during the experiment var trial = { type : jsPsychSurveyText , questions : function (){ var questions_array = [ { prompt : \"Hi \" + subject_id + \"! What's your favorite city?\" , required : true , name : 'fav_city' }, { prompt : \"What is your favorite fruit?\" , required : true , name : 'fav_fruit' }, ]; return questions_array ; } } You can also use a function for any of the individual parameters inside of a nested parameter. var trial = { type : jsPsychSurveyText , questions : [ { prompt : function () { // this question prompt is dynamic - the text that is shown // will change based on the participant's earlier response var favorite_city = jsPsych . data . getLastTrialData (). values ()[ 0 ]. response . fav_city ; var text = \"Earlier you said your favorite city is \" + favorite_city + \". What do you like most about \" + favorite_city + \"?\" return text ; }, required : true , rows : 40 , columns : 10 }, { prompt : \"What is your favorite fruit?\" , required : true , name : 'fav_fruit' } ] } When dynamic parameters can't be used \u00b6 Note that if the plugin expects the value of a given parameter to be a function, then this function will not be evaluated at the start of the trial. This is because some plugins allow the researcher to specify functions that should be called at some point during the trial. Some examples of this include the stimulus parameter in the canvas-* plugins, the mistake_fn parameter in the cloze plugin, and the stim_function parameter in the reconstruction plugin. If you want to check whether this is the case for a particular plugin and parameter, then the parameter's type in the plugin.info section of the plugin file. If the parameter type is ParameterType.FUNCTION , then this parameter must be a function and it will not be executed before the trial starts. Even though function evaluation doesn't work the same way with these parameters, the fact that the parameters are functions means that you can get the same dynamic functionality. These functions are typically evaluated at some point during the trial, so you still get updates to values within the function during the trial.","title":"Dynamic Parameters"},{"location":"overview/dynamic-parameters/#dynamic-parameters","text":"Most trial parameters can also be specified as functions. In a typical declaration of a jsPsych trial, parameters are known at the start of the experiment. This makes it impossible to alter the content of the trial based on the outcome of previous trials. However, when functions are used as the parameter value, the function is evaluated right before the trial starts, and the return value of the function is used as the parameter value for that trial . This enables dynamic updating of the parameter based on data that a participant has generated or any other information that you do not know in advance.","title":"Dynamic parameters"},{"location":"overview/dynamic-parameters/#examples","text":"","title":"Examples"},{"location":"overview/dynamic-parameters/#providing-feedback","text":"Here is a sketch of how this functionality could be used to display feedback to a participant in the Flanker Task. var timeline = []; var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' }, on_finish : function ( data ){ // Score the keyboard response as correct or incorrect. if ( jsPsych . pluginAPI . compareKeys ( data . response , \"f\" )){ data . correct = true ; } else { data . correct = false ; } } } var feedback = { type : jsPsychHtmlKeyboardResponse , trial_duration : 1000 , stimulus : function (){ // The feedback stimulus is a dynamic parameter because we can't know in advance whether // the stimulus should be 'correct' or 'incorrect'. // Instead, this function will check the accuracy of the last response and use that information to set // the stimulus value on each trial. var last_trial_correct = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. correct ; if ( last_trial_correct ){ return \"<p>Correct!</p>\" ; // the parameter value has to be returned from the function } else { return \"<p>Wrong.</p>\" ; // the parameter value has to be returned from the function } } } timeline . push ( trial , feedback ); Note When scoring a participant's response, the jsPsych.pluginAPI.compareKeys function is only needed to compare keyboard responses. For other kinds of response types, such as button presses, you can compare the participant's response and correct response values directly, e.g. if ( data . response == 0 )){ data . correct = true ; } else { data . correct = false ; } Or: data . correct = data . response === data . correct_response ;","title":"Providing Feedback"},{"location":"overview/dynamic-parameters/#randomizing-a-parameter-value","text":"Here's an example of using a dynamic parameter to randomize the inter-trial interval (ITI) duration. This time, the dynamic parameter is created using a named function instead of an anonymous function. var random_duration = function () { var rand_dur = jsPsych . randomization . sampleWithoutReplacement ([ 500 , 600 , 700 , 800 ], 1 )[ 0 ]; return rand_dur ; } var trial = { type : jsPsychHtmlKeyboardResponse stimulus : '+' , post_trial_gap : random_duration // if you use a named function for a dynamic parameter, then just use the function name (without parentheses after it) }","title":"Randomizing a parameter value"},{"location":"overview/dynamic-parameters/#storing-changing-variables-in-the-data","text":"The trial's data parameter can be also function, which is useful for when you want to save information to the data that can change during the experiment. For example, if you have a global variable called current_difficulty that tracks the difficulty level in an adaptive task, you can save the current value of this variable to the trial data like this: var current_difficulty ; // value changes during the experiment var trial = { type : jsPsychSurveyText , questions : [{ prompt : \"Please enter your response.\" }] data : function () { return { difficulty : current_difficulty }; } } It's also possible to use a function for any of the individual properties in the trial's data object, for instance if you want to combine static and dynamic information in the data: var trial = { type : jsPsychSurveyText , questions : [{ prompt : \"Please enter your response.\" }] data : { difficulty : function () { return current_difficulty ; // the difficulty value changes during the experiment }, task_part : 'recall' , // this part of the data is always the same block_number : 1 } }","title":"Storing changing variables in the data"},{"location":"overview/dynamic-parameters/#nested-parameters","text":"Dyanmic parameters work the same way with nested parameters, which are parameters that contain one or more sets of other parameters. For instance, many survey-* plugins have a questions parameter that is a nested parameter: it is an array that contains the parameters for one or more questions on the page. To make the questions parameter dynamic, you can use a function that returns the array with all of the parameters for each question: var subject_id ; // value is set during the experiment var trial = { type : jsPsychSurveyText , questions : function (){ var questions_array = [ { prompt : \"Hi \" + subject_id + \"! What's your favorite city?\" , required : true , name : 'fav_city' }, { prompt : \"What is your favorite fruit?\" , required : true , name : 'fav_fruit' }, ]; return questions_array ; } } You can also use a function for any of the individual parameters inside of a nested parameter. var trial = { type : jsPsychSurveyText , questions : [ { prompt : function () { // this question prompt is dynamic - the text that is shown // will change based on the participant's earlier response var favorite_city = jsPsych . data . getLastTrialData (). values ()[ 0 ]. response . fav_city ; var text = \"Earlier you said your favorite city is \" + favorite_city + \". What do you like most about \" + favorite_city + \"?\" return text ; }, required : true , rows : 40 , columns : 10 }, { prompt : \"What is your favorite fruit?\" , required : true , name : 'fav_fruit' } ] }","title":"Nested Parameters"},{"location":"overview/dynamic-parameters/#when-dynamic-parameters-cant-be-used","text":"Note that if the plugin expects the value of a given parameter to be a function, then this function will not be evaluated at the start of the trial. This is because some plugins allow the researcher to specify functions that should be called at some point during the trial. Some examples of this include the stimulus parameter in the canvas-* plugins, the mistake_fn parameter in the cloze plugin, and the stim_function parameter in the reconstruction plugin. If you want to check whether this is the case for a particular plugin and parameter, then the parameter's type in the plugin.info section of the plugin file. If the parameter type is ParameterType.FUNCTION , then this parameter must be a function and it will not be executed before the trial starts. Even though function evaluation doesn't work the same way with these parameters, the fact that the parameters are functions means that you can get the same dynamic functionality. These functions are typically evaluated at some point during the trial, so you still get updates to values within the function during the trial.","title":"When dynamic parameters can't be used"},{"location":"overview/events/","text":"Event-related callback functions \u00b6 jsPsych offers the ability to call arbitrary functions in response to certain events occurring, like the end of a trial or when new data is saved. This page summarizes the different opportunities for callback functions and how to specify them. on_close \u00b6 The on_close callback can be declared in the initJsPsych method. The callback triggers when the user leaves the page, but before any content on the page is removed from the browser's memory. This can be used, for example, to save data as the user is leaving the page. initJsPsych ({ on_close : function (){ var data = jsPsych . data . get (). json (); save_data_to_server ( data ); } }); on_data_update \u00b6 The on_data_update callback can be declared in the initJsPsych method. The callback triggers at the end of a data update cycle. This happens after every trial, after the on_finish (trial) and on_trial_finish events execute, allowing you to modify the data in those callbacks, and then use this callback to store the data. The function will be passed a single argument, which contains the data that was written. initJsPsych ({ on_data_update : function ( data ) { console . log ( 'Just added new data. The contents of the data are: ' + JSON . stringify ( data )); } }); on_finish (trial) \u00b6 The on_finish callback can be added to any trial. The callback will trigger whenever the trial ends. The callback function will be passed a single argument, containing the data object from the trial. This data object is editable . Any changes made in the on_finish function will be stored in the internal data collection. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_finish : function ( data ) { if ( jsPsych . pluginAPI . compareKeys ( data . response , 'j' )){ data . correct = true ; } else { data . correct = false ; } } }; on_finish (experiment) \u00b6 The on_finish callback can be declared in the initJsPsych method. The callback will trigger once all trials in the experiment have been run. The method will be passed a single argument, containing all of the data generated in the experiment. initJsPsych ({ on_finish : function ( data ) { console . log ( 'The experiment is over! Here is all the data: ' + JSON . stringify ( data )); } }); on_load \u00b6 The on_load callback can be added to any trial. The callback will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_load : function () { console . log ( 'The trial just finished loading.' ); } }; on_start (trial) \u00b6 The on_start callback can be added to any trial. The callback will trigger right before the trial begins. The callback function will be passed a single argument, containing the trial object. If any of the parameters of the trial are functions or timeline variables, these will be evaluated before on_start is called, and the trial object will contain the evaluated value. The trial object is modifiable, and any changes made will affect the trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_start : function ( trial ) { console . log ( 'The trial is about to start.' ); trial . stimulus = 'imgB.png' ; // this will change what stimulus is displayed in the trial } }; on_timeline_finish \u00b6 The on_timeline_finish callback can be declared in a timeline node. The callback will be triggered when the timeline ends during the experiment. If timeline_variables , conditional_function , loop_function , or sample options are used, this function will execute when all trials have finished. If a loop_function is used, then this on_timeline_finish function will be triggered before the loop function. If the repetitions option is used, this function will be triggered at the end of every repetition. var procedure = { timeline : [ trial1 , trial2 ], timeline_variables : [ { stimulus : 'person-1.jpg' }, { stimulus : 'person-2.jpg' }, { stimulus : 'person-3.jpg' }, { stimulus : 'person-4.jpg' } ], on_timeline_finish : function () { console . log ( 'This timeline has finished.' ); }, loop_function : function () { console . log ( 'This loop function will execute after on_timeline_finish.' ); return false ; } } on_timeline_start \u00b6 The on_timeline_start callback can be declared in a timeline node. The callback will be triggered when the timeline starts during the experiment, including when timeline_variables , loop_function , or sample options are used. If a conditional_function is used, then the conditional function will execute first, and the on_timeline_start function will only execute if the conditional function returns true . If the repetitions option is used, this function will be triggered at the start of every repetition. var procedure = { timeline : [ trial1 , trial2 ], conditional_function : function () { console . log ( 'This conditional function will execute first.' ) return true ; }, on_timeline_start : function () { console . log ( 'This timeline has started' ); } } on_trial_finish \u00b6 The on_trial_finish callback can be declared in the initJsPsych method. The callback will trigger at the end of every trial in the experiment, after the trial object's on_finish callback has been run. The callback function will be passed a single argument, containing the data object from the trial. If you want a callback to trigger only for the end of certain trials, use the on_finish callback on the trial object instead. initJsPsych ({ on_trial_finish : function ( data ) { console . log ( 'A trial just ended.' ); console . log ( JSON . stringify ( data )); } }); on_trial_start \u00b6 The on_trial_start callback can be declared in the initJsPsych method. The callback will trigger at the start of every trial in the experiment, before the trial-specific on_start callback is executed. The function receives a single argument: a modifiable copy of the trial object that will be used to run the next trial. Changes can be made to this object to alter the parameters of the upcoming trial. var current_score = 0 ; // a variable that is updated throughout the experiment to keep track of the current score. initJsPsych ({ on_trial_start : function ( trial ) { trial . data . score_at_start_of_trial = current_score ; console . log ( 'A trial just started.' ); } });","title":"Events"},{"location":"overview/events/#event-related-callback-functions","text":"jsPsych offers the ability to call arbitrary functions in response to certain events occurring, like the end of a trial or when new data is saved. This page summarizes the different opportunities for callback functions and how to specify them.","title":"Event-related callback functions"},{"location":"overview/events/#on_close","text":"The on_close callback can be declared in the initJsPsych method. The callback triggers when the user leaves the page, but before any content on the page is removed from the browser's memory. This can be used, for example, to save data as the user is leaving the page. initJsPsych ({ on_close : function (){ var data = jsPsych . data . get (). json (); save_data_to_server ( data ); } });","title":"on_close"},{"location":"overview/events/#on_data_update","text":"The on_data_update callback can be declared in the initJsPsych method. The callback triggers at the end of a data update cycle. This happens after every trial, after the on_finish (trial) and on_trial_finish events execute, allowing you to modify the data in those callbacks, and then use this callback to store the data. The function will be passed a single argument, which contains the data that was written. initJsPsych ({ on_data_update : function ( data ) { console . log ( 'Just added new data. The contents of the data are: ' + JSON . stringify ( data )); } });","title":"on_data_update"},{"location":"overview/events/#on_finish-trial","text":"The on_finish callback can be added to any trial. The callback will trigger whenever the trial ends. The callback function will be passed a single argument, containing the data object from the trial. This data object is editable . Any changes made in the on_finish function will be stored in the internal data collection. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_finish : function ( data ) { if ( jsPsych . pluginAPI . compareKeys ( data . response , 'j' )){ data . correct = true ; } else { data . correct = false ; } } };","title":"on_finish (trial)"},{"location":"overview/events/#on_finish-experiment","text":"The on_finish callback can be declared in the initJsPsych method. The callback will trigger once all trials in the experiment have been run. The method will be passed a single argument, containing all of the data generated in the experiment. initJsPsych ({ on_finish : function ( data ) { console . log ( 'The experiment is over! Here is all the data: ' + JSON . stringify ( data )); } });","title":"on_finish (experiment)"},{"location":"overview/events/#on_load","text":"The on_load callback can be added to any trial. The callback will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_load : function () { console . log ( 'The trial just finished loading.' ); } };","title":"on_load"},{"location":"overview/events/#on_start-trial","text":"The on_start callback can be added to any trial. The callback will trigger right before the trial begins. The callback function will be passed a single argument, containing the trial object. If any of the parameters of the trial are functions or timeline variables, these will be evaluated before on_start is called, and the trial object will contain the evaluated value. The trial object is modifiable, and any changes made will affect the trial. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_start : function ( trial ) { console . log ( 'The trial is about to start.' ); trial . stimulus = 'imgB.png' ; // this will change what stimulus is displayed in the trial } };","title":"on_start (trial)"},{"location":"overview/events/#on_timeline_finish","text":"The on_timeline_finish callback can be declared in a timeline node. The callback will be triggered when the timeline ends during the experiment. If timeline_variables , conditional_function , loop_function , or sample options are used, this function will execute when all trials have finished. If a loop_function is used, then this on_timeline_finish function will be triggered before the loop function. If the repetitions option is used, this function will be triggered at the end of every repetition. var procedure = { timeline : [ trial1 , trial2 ], timeline_variables : [ { stimulus : 'person-1.jpg' }, { stimulus : 'person-2.jpg' }, { stimulus : 'person-3.jpg' }, { stimulus : 'person-4.jpg' } ], on_timeline_finish : function () { console . log ( 'This timeline has finished.' ); }, loop_function : function () { console . log ( 'This loop function will execute after on_timeline_finish.' ); return false ; } }","title":"on_timeline_finish"},{"location":"overview/events/#on_timeline_start","text":"The on_timeline_start callback can be declared in a timeline node. The callback will be triggered when the timeline starts during the experiment, including when timeline_variables , loop_function , or sample options are used. If a conditional_function is used, then the conditional function will execute first, and the on_timeline_start function will only execute if the conditional function returns true . If the repetitions option is used, this function will be triggered at the start of every repetition. var procedure = { timeline : [ trial1 , trial2 ], conditional_function : function () { console . log ( 'This conditional function will execute first.' ) return true ; }, on_timeline_start : function () { console . log ( 'This timeline has started' ); } }","title":"on_timeline_start"},{"location":"overview/events/#on_trial_finish","text":"The on_trial_finish callback can be declared in the initJsPsych method. The callback will trigger at the end of every trial in the experiment, after the trial object's on_finish callback has been run. The callback function will be passed a single argument, containing the data object from the trial. If you want a callback to trigger only for the end of certain trials, use the on_finish callback on the trial object instead. initJsPsych ({ on_trial_finish : function ( data ) { console . log ( 'A trial just ended.' ); console . log ( JSON . stringify ( data )); } });","title":"on_trial_finish"},{"location":"overview/events/#on_trial_start","text":"The on_trial_start callback can be declared in the initJsPsych method. The callback will trigger at the start of every trial in the experiment, before the trial-specific on_start callback is executed. The function receives a single argument: a modifiable copy of the trial object that will be used to run the next trial. Changes can be made to this object to alter the parameters of the upcoming trial. var current_score = 0 ; // a variable that is updated throughout the experiment to keep track of the current score. initJsPsych ({ on_trial_start : function ( trial ) { trial . data . score_at_start_of_trial = current_score ; console . log ( 'A trial just started.' ); } });","title":"on_trial_start"},{"location":"overview/exclude-browser/","text":"Exclude Participants Based on Browser Features \u00b6 Changed in 7.1 Online participants will use many different kinds of browsers. Depending on the experiment, it may be important to specify a minimum feature set of the browser. As of v7.1 of jsPsych, the recommended way to do this is using the browser-check plugin . This plugin can record many features of the participant's browser and exclude participants who do not meet a defined set of inclusion criteria. Please see the browser-check plugin documentation for more details. The prior approach of using the exclusions parameter in initJsPsych() is deprecated and will be removed in v8.0 . You can find the documentation for it in the 7.0 docs .","title":"Exclude Participants Based on Browser Features"},{"location":"overview/exclude-browser/#exclude-participants-based-on-browser-features","text":"Changed in 7.1 Online participants will use many different kinds of browsers. Depending on the experiment, it may be important to specify a minimum feature set of the browser. As of v7.1 of jsPsych, the recommended way to do this is using the browser-check plugin . This plugin can record many features of the participant's browser and exclude participants who do not meet a defined set of inclusion criteria. Please see the browser-check plugin documentation for more details. The prior approach of using the exclusions parameter in initJsPsych() is deprecated and will be removed in v8.0 . You can find the documentation for it in the 7.0 docs .","title":"Exclude Participants Based on Browser Features"},{"location":"overview/experiment-options/","text":"Experiment-wide settings \u00b6 There are several options that can be set when calling initJsPsych() to initialize the jsPsych experiment. Options are specified in the object passed to initJsPsych . For example, to specify a default inter-trial interval, a minimum valid response time duration, and a maximum width for all of the experiment's page content, the object would contain: initJsPsych ({ default_iti : 250 , minimum_valid_rt : 100 , experiment_width : 800 }); Controlling where jsPsych renders on the page \u00b6 By default, jsPsych will render the experiment in the <body> element of a page. It is possible to display the experiment in a different element (e.g., a <div> ) by specifying the display_element parameter. < body > < div id = \"jspsych-target\" ></ div > </ body > < script > initJsPsych ({ display_element : 'jspsych-target' }); </ script > This option is useful if the experiment needs to be rendered on a page with other content (e.g., a demo version of the experiment with annotation text), or if additional control over the display element is desired. Custom CSS rules can be applied to position, size, scale, etc. the display element. Experiment events \u00b6 Several experiment-wide events can trigger functions. This is documented in more detail on the event-related callback functions page . The events that trigger functions are: on_finish : Called at the end of the experiment. on_trial_start : Called at the beginning of every trial. on_trial_finish : Called at the end of every trial. on_data_update : Called whenever new data is added to the jsPsych data object. on_interaction_data_update : Called whenever new interaction data (e.g., the participant enters or exits fullscreen mode) is added. on_close : Called right before the page closes, such as when a participant closes the experiment early. Specify exclusion criteria \u00b6 Exclusion criteria can be specified based on features of the user's web browser, such as the display size and whether certain features are reported. See the page on excluding participants based on browser features . Display a progress bar \u00b6 An automatic or manually updated progress bar can be displayed at the top of the screen. By default, the text next to the progress bar is \"Completion Progress\", but this text can be changed with the message_progress_bar parameter in initJsPsych . See the progress bar page for more details. Choose the method for playing audio files \u00b6 Specifying the use_webaudio parameter in initJsPsych() allows you to choose whether to use the WebAudio API or HTML5 audio for playing audio files during your experiment. By default, jsPsych uses the WebAudio API to play audio files. Among other features, the WebAudio API allows for more precise measurement of response times relative to the onset of the audio. However, loading files through the WebAudio API causes errors when running an experiment offline (i.e., by double-clicking on the HTML file, rather than hosting it on a web server). This is due to the cross-origin security policy implemented by web browsers. For this reason, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline, and automatically uses HTML5 audio to prevent errors, even when use_webaudio has been explicitly set to true . For more information, see the section Cross-origin requests (CORS) and safe mode on the Running Experiments page. initJsPsych ({ use_webaudio : false }); Set the default intertrial interval \u00b6 By default the next trial in a timeline will begin immediately after the conclusion of the previous trial. An experiment-wide delay can be specified using the default_iti parameter to initJsPsych() . initJsPsych ({ default_iti : 500 }); This parameter is specified in milliseconds. A blank screen will display between each trial for the duration of the ITI. Specify the maximum width of the experiment \u00b6 The experiment will, by default, take up 100% of the display element. Usually the display element is the <body> , and the experiment is the full width of the screen. (This can be overridden by specifying the display_element parameter described above). Specifying the experiment_width parameter will set a maximum width for the display. The parameter is specified in pixels. initJsPsych ({ experiment_width : 750 }); Specify a minimum valid response time \u00b6 By default, jsPsych will treat any keyboard response time as valid. However, it's possible to specify a minimum valid response time (in ms) for key presses. Any key press that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to keyboard responses , and not to other response types such as buttons and sliders. The default value is 0. // ignore any keyboard responses that are less than 100 ms initJsPsych ({ minimum_valid_rt : 100 }); Choose whether you want keyboard choices/responses to be case-sensitive \u00b6 JavaScript keyboard events make a distinction between uppercase and lowercase key responses (e.g. 'a' and 'A'). Often the researcher just cares about which physical key was pressed, and not whether the key press would result in an uppercase letter (for instance, if CapsLock is on or if the Shift key is held down). For this reason, jsPsych converts all key choice parameters and key responses as lowercase by default. This makes it easier to specify key choices (e.g. choices: ['a'] , instead of choices: ['a','A'] ), and it makes it easier to check and score a participant's response. There may be situations when you want key choices and responses to be case-sensitive. You can change this by setting the case_sensitive_responses parameter to true in initJsPsych . // use case-sensitive key choices and responses, // i.e. uppercase and lower case letters ('a' and 'A') will be treated as different key choices, // and will be recorded this way in the data initJsPsych ({ case_sensitive_responses : true }); Note that this setting only applies to key choices and responses that use jsPsych's keyboard response listener, such as in the * -keyboard-response plugins. This does NOT apply to responses that are made by typing into a text box, such as in the survey-text and cloze plugins. Override 'safe mode' when running experiments offline \u00b6 By default, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline (via the file:// protocol) in order to prevent certain errors. Specifically, in safe mode, HTML5 audio is used to play audio files (even when use_webaudio has been explicitly set to true ) and video preloading is disabled (both automatic and manual preloading). For more information, see the Cross-origin requests (CORS) and safe mode section on the Running Experiments page. It's possible to override this safe mode feature by setting the override_safe_mode parameter to true in initJsPsych . This is something you might do if you've disabled certain security settings in your browser for testing purposes. This parameter has no effect when your experiment is running online (on a server), because it will be using the http:// or https:// protocol, which does not trigger safe mode. initJsPsych ({ override_safe_mode : true }); Add extensions \u00b6 Extensions are jsPsych modules that can run throughout the experiment and interface with any plugin to extend the functionality of the plugin. One example of an extension is eye tracking, which allows you to gather gaze data during any trial and add it to that trial's data object. If you want to use extensions in your experiment, you must specify this when you initialize the experiment with initJsPsych . The extensions parameter in initJsPsych is an array of objects, where each object specifies the extension that you'd like to use in the experiment. Below is an example of adding the webgazer extension. initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] });","title":"Experiment Settings"},{"location":"overview/experiment-options/#experiment-wide-settings","text":"There are several options that can be set when calling initJsPsych() to initialize the jsPsych experiment. Options are specified in the object passed to initJsPsych . For example, to specify a default inter-trial interval, a minimum valid response time duration, and a maximum width for all of the experiment's page content, the object would contain: initJsPsych ({ default_iti : 250 , minimum_valid_rt : 100 , experiment_width : 800 });","title":"Experiment-wide settings"},{"location":"overview/experiment-options/#controlling-where-jspsych-renders-on-the-page","text":"By default, jsPsych will render the experiment in the <body> element of a page. It is possible to display the experiment in a different element (e.g., a <div> ) by specifying the display_element parameter. < body > < div id = \"jspsych-target\" ></ div > </ body > < script > initJsPsych ({ display_element : 'jspsych-target' }); </ script > This option is useful if the experiment needs to be rendered on a page with other content (e.g., a demo version of the experiment with annotation text), or if additional control over the display element is desired. Custom CSS rules can be applied to position, size, scale, etc. the display element.","title":"Controlling where jsPsych renders on the page"},{"location":"overview/experiment-options/#experiment-events","text":"Several experiment-wide events can trigger functions. This is documented in more detail on the event-related callback functions page . The events that trigger functions are: on_finish : Called at the end of the experiment. on_trial_start : Called at the beginning of every trial. on_trial_finish : Called at the end of every trial. on_data_update : Called whenever new data is added to the jsPsych data object. on_interaction_data_update : Called whenever new interaction data (e.g., the participant enters or exits fullscreen mode) is added. on_close : Called right before the page closes, such as when a participant closes the experiment early.","title":"Experiment events"},{"location":"overview/experiment-options/#specify-exclusion-criteria","text":"Exclusion criteria can be specified based on features of the user's web browser, such as the display size and whether certain features are reported. See the page on excluding participants based on browser features .","title":"Specify exclusion criteria"},{"location":"overview/experiment-options/#display-a-progress-bar","text":"An automatic or manually updated progress bar can be displayed at the top of the screen. By default, the text next to the progress bar is \"Completion Progress\", but this text can be changed with the message_progress_bar parameter in initJsPsych . See the progress bar page for more details.","title":"Display a progress bar"},{"location":"overview/experiment-options/#choose-the-method-for-playing-audio-files","text":"Specifying the use_webaudio parameter in initJsPsych() allows you to choose whether to use the WebAudio API or HTML5 audio for playing audio files during your experiment. By default, jsPsych uses the WebAudio API to play audio files. Among other features, the WebAudio API allows for more precise measurement of response times relative to the onset of the audio. However, loading files through the WebAudio API causes errors when running an experiment offline (i.e., by double-clicking on the HTML file, rather than hosting it on a web server). This is due to the cross-origin security policy implemented by web browsers. For this reason, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline, and automatically uses HTML5 audio to prevent errors, even when use_webaudio has been explicitly set to true . For more information, see the section Cross-origin requests (CORS) and safe mode on the Running Experiments page. initJsPsych ({ use_webaudio : false });","title":"Choose the method for playing audio files"},{"location":"overview/experiment-options/#set-the-default-intertrial-interval","text":"By default the next trial in a timeline will begin immediately after the conclusion of the previous trial. An experiment-wide delay can be specified using the default_iti parameter to initJsPsych() . initJsPsych ({ default_iti : 500 }); This parameter is specified in milliseconds. A blank screen will display between each trial for the duration of the ITI.","title":"Set the default intertrial interval"},{"location":"overview/experiment-options/#specify-the-maximum-width-of-the-experiment","text":"The experiment will, by default, take up 100% of the display element. Usually the display element is the <body> , and the experiment is the full width of the screen. (This can be overridden by specifying the display_element parameter described above). Specifying the experiment_width parameter will set a maximum width for the display. The parameter is specified in pixels. initJsPsych ({ experiment_width : 750 });","title":"Specify the maximum width of the experiment"},{"location":"overview/experiment-options/#specify-a-minimum-valid-response-time","text":"By default, jsPsych will treat any keyboard response time as valid. However, it's possible to specify a minimum valid response time (in ms) for key presses. Any key press that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to keyboard responses , and not to other response types such as buttons and sliders. The default value is 0. // ignore any keyboard responses that are less than 100 ms initJsPsych ({ minimum_valid_rt : 100 });","title":"Specify a minimum valid response time"},{"location":"overview/experiment-options/#choose-whether-you-want-keyboard-choicesresponses-to-be-case-sensitive","text":"JavaScript keyboard events make a distinction between uppercase and lowercase key responses (e.g. 'a' and 'A'). Often the researcher just cares about which physical key was pressed, and not whether the key press would result in an uppercase letter (for instance, if CapsLock is on or if the Shift key is held down). For this reason, jsPsych converts all key choice parameters and key responses as lowercase by default. This makes it easier to specify key choices (e.g. choices: ['a'] , instead of choices: ['a','A'] ), and it makes it easier to check and score a participant's response. There may be situations when you want key choices and responses to be case-sensitive. You can change this by setting the case_sensitive_responses parameter to true in initJsPsych . // use case-sensitive key choices and responses, // i.e. uppercase and lower case letters ('a' and 'A') will be treated as different key choices, // and will be recorded this way in the data initJsPsych ({ case_sensitive_responses : true }); Note that this setting only applies to key choices and responses that use jsPsych's keyboard response listener, such as in the * -keyboard-response plugins. This does NOT apply to responses that are made by typing into a text box, such as in the survey-text and cloze plugins.","title":"Choose whether you want keyboard choices/responses to be case-sensitive"},{"location":"overview/experiment-options/#override-safe-mode-when-running-experiments-offline","text":"By default, jsPsych switches to a 'safe mode' when it detects that the webpage is running offline (via the file:// protocol) in order to prevent certain errors. Specifically, in safe mode, HTML5 audio is used to play audio files (even when use_webaudio has been explicitly set to true ) and video preloading is disabled (both automatic and manual preloading). For more information, see the Cross-origin requests (CORS) and safe mode section on the Running Experiments page. It's possible to override this safe mode feature by setting the override_safe_mode parameter to true in initJsPsych . This is something you might do if you've disabled certain security settings in your browser for testing purposes. This parameter has no effect when your experiment is running online (on a server), because it will be using the http:// or https:// protocol, which does not trigger safe mode. initJsPsych ({ override_safe_mode : true });","title":"Override 'safe mode' when running experiments offline"},{"location":"overview/experiment-options/#add-extensions","text":"Extensions are jsPsych modules that can run throughout the experiment and interface with any plugin to extend the functionality of the plugin. One example of an extension is eye tracking, which allows you to gather gaze data during any trial and add it to that trial's data object. If you want to use extensions in your experiment, you must specify this when you initialize the experiment with initJsPsych . The extensions parameter in initJsPsych is an array of objects, where each object specifies the extension that you'd like to use in the experiment. Below is an example of adding the webgazer extension. initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] });","title":"Add extensions"},{"location":"overview/extensions/","text":"Extensions \u00b6 Extensions are jsPsych modules that can interface with any plugin to extend the functionality of the plugin. A canonical example of an extension is eye tracking. An eye tracking extension allows a plugin to gather gaze data and add it to the plugin's data object. Using an Extension \u00b6 To use an extension in an experiment, you'll load the extension file via a <script> tag (just like adding a plugin) and then initialize the extension in the parameters of initJsPsych() . < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-example@1.0.0\" ></ script > </ head > initJsPsych ({ extensions : [ { type : jsPsychExtensionExample , params : {...} } ] }) To enable an extension during a trial, add the extension to the extensions list for the trial. Some extensions may also support or require an object of parameters to configure the extension: var trial = { extensions : [ { type : jsPsychExtensionExample , params : {...} } ] } List of Extensions \u00b6 Extension Description jspsych\u2011ext\u2011webgazer.js Enables eye tracking using the WebGazer library. Writing an Extension \u00b6 See our developer's guide for extensions for information about how to create a new extension.","title":"Extensions"},{"location":"overview/extensions/#extensions","text":"Extensions are jsPsych modules that can interface with any plugin to extend the functionality of the plugin. A canonical example of an extension is eye tracking. An eye tracking extension allows a plugin to gather gaze data and add it to the plugin's data object.","title":"Extensions"},{"location":"overview/extensions/#using-an-extension","text":"To use an extension in an experiment, you'll load the extension file via a <script> tag (just like adding a plugin) and then initialize the extension in the parameters of initJsPsych() . < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-example@1.0.0\" ></ script > </ head > initJsPsych ({ extensions : [ { type : jsPsychExtensionExample , params : {...} } ] }) To enable an extension during a trial, add the extension to the extensions list for the trial. Some extensions may also support or require an object of parameters to configure the extension: var trial = { extensions : [ { type : jsPsychExtensionExample , params : {...} } ] }","title":"Using an Extension"},{"location":"overview/extensions/#list-of-extensions","text":"Extension Description jspsych\u2011ext\u2011webgazer.js Enables eye tracking using the WebGazer library.","title":"List of Extensions"},{"location":"overview/extensions/#writing-an-extension","text":"See our developer's guide for extensions for information about how to create a new extension.","title":"Writing an Extension"},{"location":"overview/eye-tracking/","text":"Eye Tracking \u00b6 jsPsych supports eye tracking through the WebGazer library. WebGazer uses computer vision techniques to identify features of the participant's eyes via a webcam and predicts gaze location. The system is calibrated by having the participant click on or look at known locations on the screen. These locations are linked to eye features. Gaze location is predicted using regression. Getting Started \u00b6 Load webgazer.js \u00b6 The official version of WebGazer is currently not supported by jsPsych. Our fork of the library contains some minor improvements aimed at the kind of experiments that jsPsych is typically used for, e.g., situations in which the timing of display screens needs to be accurate. You must include the webgazer.js file in your experiment via a <script> tag. However, the webgazer.js file is not part of any of the jsPsych NPM packages and is therefore not available via the unpkg.com CDN. Instead, it can be found on the jsdelivr.net CDN at: \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\". < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > </ head > Note A copy of our forked webgazer.js file is also included in the jsPsych release, in the /examples/js/webgazer folder. So if you prefer to download and host all of your jsPsych files (i.e. set-up option 2 in the Hello World tutorial), then another option is to load that file rather than using the jsdelivr link above. Assuming you downloaded the release and copied the webgazer.js file into a folder called js/webgazer in your root project directory, then you would load the file like this: < script src = \"js/webgazer/webgazer.js\" ></ script > Load the jsPsych webgazer extension \u00b6 The webgazer extension adds functionality to jsPsych for interacting with webgazer. Load it like you would a plugin file. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-webgazer@1.0.3\" ></ script > </ head > To use the WebGazer extension in an experiment, include it in the list of extensions passed to initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }) Initialize the camera \u00b6 To help the participant position their face correctly for eye tracking you can use the webgazer-init-camera plugin . This will show the participant what the camera sees, including facial feature landmarks, and prevent the participant from continuing until their face is in good position for eye tracking. This plugin will also trigger the experiment to request permission to access the user's webcam if it hasn't already been granted. var init_camera_trial = { type : jsPsychWebgazerInitCamera } Calibration \u00b6 To calibrate WebGazer, you can use the webgazer-calibrate plugin . This plugin allows you to specify a set of points on the screen for calibration and to choose the method for calibrating -- either clicking on each point or simply fixating on each point. The location of calibration points is specified in percentages, e.g., [25,50] will result in a point that is 25% of the width of the screen from the left edge and 50% of the height of the screen from the top edge. Options for controlling other details of the calibration are explained in the documentation for the plugin . Note that instructions are not included in the calibration plugin, so you'll likely want to use a different plugin (e.g., html-button-response ) to display instructions prior to running the calibration. var calibration_trial = { type : jsPsychWebgazerCalibrate , calibration_points : [[ 25 , 50 ], [ 50 , 50 ], [ 75 , 50 ], [ 50 , 25 ], [ 50 , 75 ]], calibration_mode : 'click' } Validation \u00b6 To measure the accuracy and precision of the calibration, you can use the webgazer-vaidate plugin . Like the calibration plugin, you can specify a list of points to perform validation on. Here you can specify the points as either percentages or in terms of the distance from the center of the screen in pixels. Which mode you use will probably depend on how you are defining your stimuli throughout the experiment. You can also specify the radius of tolerance around each point, and the plugin will calculate the percentage of measured gaze samples within that radius. This is a potentially useful heuristic for deciding whether or not to calibrate again. Options for controlling other details of the validation are explained in the documentation for the plugin . var validation_trial = { type : jsPsychWebgazerValidate , validation_points : [[ - 200 , 200 ], [ 200 , 200 ],[ - 200 , - 200 ],[ 200 , - 200 ]], validation_point_coordinates : 'center-offset-pixels' , roi_radius : 100 } The validation procedure stores the raw gaze data for each validation point, the computed average offset from each validation point, the percentage of samples within the roi_radius for each validation point, and the number of samples collected per second. { raw_gaze : [...], percent_in_roi : [...], average_offset : [...], samples_per_sec : ... } We recommend performing calibration and validation periodically throughout your experiment. Adding eye tracking to a trial \u00b6 To enable eye tracking for a trial in your experiment, you can simply add the WebGazer extension to the trial. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<img id=\"scene\" src=\"my-scene.png\"></img>' , extensions : [ { type : jsPsychExtensionWebgazer , params : { targets : [ '#scene' ] } } ] } This will turn on WebGazer at the start of the trial. The params property in the extensions declaration allows you to pass in a list of CSS selector strings . The bounding rectangle of the DOM element that matches each selector will be recorded in the data for that trial. This allows for easy alignment of the gaze data and objects on the screen. webgazer_targets : { 'selector' : { x : ..., y : ..., height : ..., width : ..., top : ..., left : ..., right : ..., bottom : ...} 'selector' : { x : ..., y : ..., height : ..., width : ..., top : ..., left : ..., right : ..., bottom : ...} } Gaze data will be added to the trial's data under the property webgazer_data . The gaze data is an array of objects. Each object has an x , a y , and a t property. The x and y properties specify the gaze location in pixels and t specifies the time in milliseconds since the start of the trial. Note that establishing the precision and accuracy of these measurements across the variety of web browsers and systems that your experiment participants might be using is quite difficult. For example, different browsers may cause small systematic shifts in the accuracy of t values. webgazer_data : [ { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...} ] Tips for Improving Data Quality \u00b6 These are some anecdotal observations about factors that improve data quality. The quality of the camera feed is essential. Good lighting makes a big difference. You may want to encourage participants to perform any eye tracking experiments in a well-lit room. Participants need to keep their head relatively still during and after calibration. The calibration is not robust to head movements. WebGazer's click-based calibration can be used throughout the experiment. You can turn this on by calling jsPsych.extensions.webgazer.startMouseCalibration() at any point in the experiment. If you use a continue button to advance through the experiment and move the location of the continue button around you can be making small adjustments to the calibration throughout. Computing the gaze predictions consumes more computational resources than most other things that jsPsych is typically used for. The sampling rate that WebGazer is able to achieve will depend on the computing power of the participant's device. You may want to ask the participant to close any non-essential software and browser windows prior to completing the experiment. You may also want to check that the sampling rate is sufficiently high as part of validation. If you have tips based on your own experience please consider sharing them on our discussion forum and we'll add to this list! Example \u00b6 Tip Additional example experiments using WebGazer are available in the /examples folder of the jsPsych release. See webgazer.html , webgazer_image.html , and webgazer_audio.html . Example Here's an example of putting all of the pieces above together. This example also shows how to use data from the validation to decide whether or not to recalibrate. You can try this experiment here (opens in new tab) . <!DOCTYPE html> < html > < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.3\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-webgazer@1.0.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" /> < style > . jspsych-btn { margin-bottom : 10 px ; } </ style > </ head > < body ></ body > < script > var jsPsych = initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }); var preload = { type : jsPsychPreload , images : [ 'img/blue.png' ] } var camera_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>In order to participate you must allow the experiment to use your camera.</p> <p>You will be prompted to do this on the next screen.</p> <p>If you do not wish to allow use of your camera, you cannot participate in this experiment.<p> <p>It may take up to 30 seconds for the camera to initialize after you give permission.</p> ` , choices : [ 'Got it' ], } var init_camera = { type : jsPsychWebgazerInitCamera } var calibration_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Now you'll calibrate the eye tracking, so that the software can use the image of your eyes to predict where you are looking.</p> <p>You'll see a series of dots appear on the screen. Look at each dot and click on it.</p> ` , choices : [ 'Got it' ], } var calibration = { type : jsPsychWebgazerCalibrate , calibration_points : [ [ 25 , 25 ],[ 75 , 25 ],[ 50 , 50 ],[ 25 , 75 ],[ 75 , 75 ] ], repetitions_per_point : 2 , randomize_calibration_order : true } var validation_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Now we'll measure the accuracy of the calibration.</p> <p>Look at each dot as it appears on the screen.</p> <p style=\"font-weight: bold;\">You do not need to click on the dots this time.</p> ` , choices : [ 'Got it' ], post_trial_gap : 1000 } var validation = { type : jsPsychWebgazerValidate , validation_points : [ [ 25 , 25 ],[ 75 , 25 ],[ 50 , 50 ],[ 25 , 75 ],[ 75 , 75 ] ], roi_radius : 200 , time_to_saccade : 1000 , validation_duration : 2000 , data : { task : 'validate' } } var recalibrate_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>The accuracy of the calibration is a little lower than we'd like.</p> <p>Let's try calibrating one more time.</p> <p>On the next screen, look at the dots and click on them.<p> ` , choices : [ 'OK' ], } var recalibrate = { timeline : [ recalibrate_instructions , calibration , validation_instructions , validation ], conditional_function : function (){ var validation_data = jsPsych . data . get (). filter ({ task : 'validate' }). values ()[ 0 ]; return validation_data . percent_in_roi . some ( function ( x ){ var minimum_percent_acceptable = 50 ; return x < minimum_percent_acceptable ; }); }, data : { phase : 'recalibration' } } var calibration_done = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Great, we're done with calibration!</p> ` , choices : [ 'OK' ] } var begin = { type : jsPsychHtmlKeyboardResponse , stimulus : `<p>The next screen will show an image to demonstrate adding the webgazer extension to a trial.</p> <p>Just look at the image while eye tracking data is collected. The trial will end automatically.</p> <p>Press any key to start.</p> ` } var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : \"NO_KEYS\" , trial_duration : 2000 , extensions : [ { type : jsPsychExtensionWebgazer , params : { targets : [ '#jspsych-image-keyboard-response-stimulus' ]} } ] } var show_data = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trial_data = jsPsych . data . getLastTrialData (). values (); var trial_json = JSON . stringify ( trial_data , null , 2 ); return `<p style=\"margin-bottom:0px;\"><strong>Trial data:</strong></p> <pre style=\"margin-top:0px;text-align:left;\"> ${ trial_json } </pre>` ; }, choices : \"NO_KEYS\" }; jsPsych . run ([ preload , camera_instructions , init_camera , calibration_instructions , calibration , validation_instructions , validation , recalibrate , calibration_done , begin , trial , show_data ]); </ script > </ html > Below is example data from the image-keyboard-response trial taken from the experiment above. In addition to the standard data that is collected for this plugin, you can see the additional webgazer_data and webgazer_targets arrays. The webgazer_data shows 21 gaze location estimates during the 1-second image presentation. The webgazer_targets array shows that there was one target, the image-keyboard-response stimulus, and tells you the x- and y-coordinate boundaries for the target (image) rectangle. By comparing each of the x/y locations from the webgazer_data locations array with the target boundaries in webgazer_targets , you can determine if/when the estimated gaze location was inside the target area. { \"rt\" : null , \"stimulus\" : \"img/blue.png\" , \"response\" : null , \"trial_type\" : \"image-keyboard-response\" , \"trial_index\" : 4 , \"time_elapsed\" : 30701 , \"internal_node_id\" : \"0.0-4.0\" , \"webgazer_data\" : [ { \"x\" : 1065 , \"y\" : 437 , \"t\" : 39 }, { \"x\" : 943 , \"y\" : 377 , \"t\" : 79 }, { \"x\" : 835 , \"y\" : 332 , \"t\" : 110 }, { \"x\" : 731 , \"y\" : 299 , \"t\" : 146 }, { \"x\" : 660 , \"y\" : 271 , \"t\" : 189 }, { \"x\" : 606 , \"y\" : 251 , \"t\" : 238 }, { \"x\" : 582 , \"y\" : 213 , \"t\" : 288 }, { \"x\" : 551 , \"y\" : 200 , \"t\" : 335 }, { \"x\" : 538 , \"y\" : 183 , \"t\" : 394 }, { \"x\" : 514 , \"y\" : 177 , \"t\" : 436 }, { \"x\" : 500 , \"y\" : 171 , \"t\" : 493 }, { \"x\" : 525 , \"y\" : 178 , \"t\" : 542 }, { \"x\" : 537 , \"y\" : 182 , \"t\" : 592 }, { \"x\" : 543 , \"y\" : 178 , \"t\" : 633 }, { \"x\" : 547 , \"y\" : 177 , \"t\" : 691 }, { \"x\" : 558 , \"y\" : 174 , \"t\" : 739 }, { \"x\" : 574 , \"y\" : 183 , \"t\" : 789 }, { \"x\" : 577 , \"y\" : 197 , \"t\" : 838 }, { \"x\" : 584 , \"y\" : 214 , \"t\" : 889 }, { \"x\" : 603 , \"y\" : 218 , \"t\" : 937 }, { \"x\" : 606 , \"y\" : 221 , \"t\" : 987 } ], \"webgazer_targets\" : [ \"#jspsych-image-keyboard-response-stimulus\" : { \"x\" : 490 , \"y\" : 135 , \"height\" : 300 , \"width\" : 300 , \"top\" : 135 , \"bottom\" : 435 , \"left\" : 490 , \"right\" : 790 } ] }","title":"Eye Tracking"},{"location":"overview/eye-tracking/#eye-tracking","text":"jsPsych supports eye tracking through the WebGazer library. WebGazer uses computer vision techniques to identify features of the participant's eyes via a webcam and predicts gaze location. The system is calibrated by having the participant click on or look at known locations on the screen. These locations are linked to eye features. Gaze location is predicted using regression.","title":"Eye Tracking"},{"location":"overview/eye-tracking/#getting-started","text":"","title":"Getting Started"},{"location":"overview/eye-tracking/#load-webgazerjs","text":"The official version of WebGazer is currently not supported by jsPsych. Our fork of the library contains some minor improvements aimed at the kind of experiments that jsPsych is typically used for, e.g., situations in which the timing of display screens needs to be accurate. You must include the webgazer.js file in your experiment via a <script> tag. However, the webgazer.js file is not part of any of the jsPsych NPM packages and is therefore not available via the unpkg.com CDN. Instead, it can be found on the jsdelivr.net CDN at: \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\". < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > </ head > Note A copy of our forked webgazer.js file is also included in the jsPsych release, in the /examples/js/webgazer folder. So if you prefer to download and host all of your jsPsych files (i.e. set-up option 2 in the Hello World tutorial), then another option is to load that file rather than using the jsdelivr link above. Assuming you downloaded the release and copied the webgazer.js file into a folder called js/webgazer in your root project directory, then you would load the file like this: < script src = \"js/webgazer/webgazer.js\" ></ script >","title":"Load webgazer.js"},{"location":"overview/eye-tracking/#load-the-jspsych-webgazer-extension","text":"The webgazer extension adds functionality to jsPsych for interacting with webgazer. Load it like you would a plugin file. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-webgazer@1.0.3\" ></ script > </ head > To use the WebGazer extension in an experiment, include it in the list of extensions passed to initJsPsych() initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] })","title":"Load the jsPsych webgazer extension"},{"location":"overview/eye-tracking/#initialize-the-camera","text":"To help the participant position their face correctly for eye tracking you can use the webgazer-init-camera plugin . This will show the participant what the camera sees, including facial feature landmarks, and prevent the participant from continuing until their face is in good position for eye tracking. This plugin will also trigger the experiment to request permission to access the user's webcam if it hasn't already been granted. var init_camera_trial = { type : jsPsychWebgazerInitCamera }","title":"Initialize the camera"},{"location":"overview/eye-tracking/#calibration","text":"To calibrate WebGazer, you can use the webgazer-calibrate plugin . This plugin allows you to specify a set of points on the screen for calibration and to choose the method for calibrating -- either clicking on each point or simply fixating on each point. The location of calibration points is specified in percentages, e.g., [25,50] will result in a point that is 25% of the width of the screen from the left edge and 50% of the height of the screen from the top edge. Options for controlling other details of the calibration are explained in the documentation for the plugin . Note that instructions are not included in the calibration plugin, so you'll likely want to use a different plugin (e.g., html-button-response ) to display instructions prior to running the calibration. var calibration_trial = { type : jsPsychWebgazerCalibrate , calibration_points : [[ 25 , 50 ], [ 50 , 50 ], [ 75 , 50 ], [ 50 , 25 ], [ 50 , 75 ]], calibration_mode : 'click' }","title":"Calibration"},{"location":"overview/eye-tracking/#validation","text":"To measure the accuracy and precision of the calibration, you can use the webgazer-vaidate plugin . Like the calibration plugin, you can specify a list of points to perform validation on. Here you can specify the points as either percentages or in terms of the distance from the center of the screen in pixels. Which mode you use will probably depend on how you are defining your stimuli throughout the experiment. You can also specify the radius of tolerance around each point, and the plugin will calculate the percentage of measured gaze samples within that radius. This is a potentially useful heuristic for deciding whether or not to calibrate again. Options for controlling other details of the validation are explained in the documentation for the plugin . var validation_trial = { type : jsPsychWebgazerValidate , validation_points : [[ - 200 , 200 ], [ 200 , 200 ],[ - 200 , - 200 ],[ 200 , - 200 ]], validation_point_coordinates : 'center-offset-pixels' , roi_radius : 100 } The validation procedure stores the raw gaze data for each validation point, the computed average offset from each validation point, the percentage of samples within the roi_radius for each validation point, and the number of samples collected per second. { raw_gaze : [...], percent_in_roi : [...], average_offset : [...], samples_per_sec : ... } We recommend performing calibration and validation periodically throughout your experiment.","title":"Validation"},{"location":"overview/eye-tracking/#adding-eye-tracking-to-a-trial","text":"To enable eye tracking for a trial in your experiment, you can simply add the WebGazer extension to the trial. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<img id=\"scene\" src=\"my-scene.png\"></img>' , extensions : [ { type : jsPsychExtensionWebgazer , params : { targets : [ '#scene' ] } } ] } This will turn on WebGazer at the start of the trial. The params property in the extensions declaration allows you to pass in a list of CSS selector strings . The bounding rectangle of the DOM element that matches each selector will be recorded in the data for that trial. This allows for easy alignment of the gaze data and objects on the screen. webgazer_targets : { 'selector' : { x : ..., y : ..., height : ..., width : ..., top : ..., left : ..., right : ..., bottom : ...} 'selector' : { x : ..., y : ..., height : ..., width : ..., top : ..., left : ..., right : ..., bottom : ...} } Gaze data will be added to the trial's data under the property webgazer_data . The gaze data is an array of objects. Each object has an x , a y , and a t property. The x and y properties specify the gaze location in pixels and t specifies the time in milliseconds since the start of the trial. Note that establishing the precision and accuracy of these measurements across the variety of web browsers and systems that your experiment participants might be using is quite difficult. For example, different browsers may cause small systematic shifts in the accuracy of t values. webgazer_data : [ { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...}, { x : ..., y : ..., t : ...} ]","title":"Adding eye tracking to a trial"},{"location":"overview/eye-tracking/#tips-for-improving-data-quality","text":"These are some anecdotal observations about factors that improve data quality. The quality of the camera feed is essential. Good lighting makes a big difference. You may want to encourage participants to perform any eye tracking experiments in a well-lit room. Participants need to keep their head relatively still during and after calibration. The calibration is not robust to head movements. WebGazer's click-based calibration can be used throughout the experiment. You can turn this on by calling jsPsych.extensions.webgazer.startMouseCalibration() at any point in the experiment. If you use a continue button to advance through the experiment and move the location of the continue button around you can be making small adjustments to the calibration throughout. Computing the gaze predictions consumes more computational resources than most other things that jsPsych is typically used for. The sampling rate that WebGazer is able to achieve will depend on the computing power of the participant's device. You may want to ask the participant to close any non-essential software and browser windows prior to completing the experiment. You may also want to check that the sampling rate is sufficiently high as part of validation. If you have tips based on your own experience please consider sharing them on our discussion forum and we'll add to this list!","title":"Tips for Improving Data Quality"},{"location":"overview/eye-tracking/#example","text":"Tip Additional example experiments using WebGazer are available in the /examples folder of the jsPsych release. See webgazer.html , webgazer_image.html , and webgazer_audio.html . Example Here's an example of putting all of the pieces above together. This example also shows how to use data from the validation to decide whether or not to recalibrate. You can try this experiment here (opens in new tab) . <!DOCTYPE html> < html > < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.3\" ></ script > < script src = \"https://cdn.jsdelivr.net/gh/jspsych/jspsych@jspsych@7.0.0/examples/js/webgazer/webgazer.js\" ></ script > < script src = \"https://unpkg.com/@jspsych/extension-webgazer@1.0.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" /> < style > . jspsych-btn { margin-bottom : 10 px ; } </ style > </ head > < body ></ body > < script > var jsPsych = initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }); var preload = { type : jsPsychPreload , images : [ 'img/blue.png' ] } var camera_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>In order to participate you must allow the experiment to use your camera.</p> <p>You will be prompted to do this on the next screen.</p> <p>If you do not wish to allow use of your camera, you cannot participate in this experiment.<p> <p>It may take up to 30 seconds for the camera to initialize after you give permission.</p> ` , choices : [ 'Got it' ], } var init_camera = { type : jsPsychWebgazerInitCamera } var calibration_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Now you'll calibrate the eye tracking, so that the software can use the image of your eyes to predict where you are looking.</p> <p>You'll see a series of dots appear on the screen. Look at each dot and click on it.</p> ` , choices : [ 'Got it' ], } var calibration = { type : jsPsychWebgazerCalibrate , calibration_points : [ [ 25 , 25 ],[ 75 , 25 ],[ 50 , 50 ],[ 25 , 75 ],[ 75 , 75 ] ], repetitions_per_point : 2 , randomize_calibration_order : true } var validation_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Now we'll measure the accuracy of the calibration.</p> <p>Look at each dot as it appears on the screen.</p> <p style=\"font-weight: bold;\">You do not need to click on the dots this time.</p> ` , choices : [ 'Got it' ], post_trial_gap : 1000 } var validation = { type : jsPsychWebgazerValidate , validation_points : [ [ 25 , 25 ],[ 75 , 25 ],[ 50 , 50 ],[ 25 , 75 ],[ 75 , 75 ] ], roi_radius : 200 , time_to_saccade : 1000 , validation_duration : 2000 , data : { task : 'validate' } } var recalibrate_instructions = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>The accuracy of the calibration is a little lower than we'd like.</p> <p>Let's try calibrating one more time.</p> <p>On the next screen, look at the dots and click on them.<p> ` , choices : [ 'OK' ], } var recalibrate = { timeline : [ recalibrate_instructions , calibration , validation_instructions , validation ], conditional_function : function (){ var validation_data = jsPsych . data . get (). filter ({ task : 'validate' }). values ()[ 0 ]; return validation_data . percent_in_roi . some ( function ( x ){ var minimum_percent_acceptable = 50 ; return x < minimum_percent_acceptable ; }); }, data : { phase : 'recalibration' } } var calibration_done = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Great, we're done with calibration!</p> ` , choices : [ 'OK' ] } var begin = { type : jsPsychHtmlKeyboardResponse , stimulus : `<p>The next screen will show an image to demonstrate adding the webgazer extension to a trial.</p> <p>Just look at the image while eye tracking data is collected. The trial will end automatically.</p> <p>Press any key to start.</p> ` } var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : \"NO_KEYS\" , trial_duration : 2000 , extensions : [ { type : jsPsychExtensionWebgazer , params : { targets : [ '#jspsych-image-keyboard-response-stimulus' ]} } ] } var show_data = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trial_data = jsPsych . data . getLastTrialData (). values (); var trial_json = JSON . stringify ( trial_data , null , 2 ); return `<p style=\"margin-bottom:0px;\"><strong>Trial data:</strong></p> <pre style=\"margin-top:0px;text-align:left;\"> ${ trial_json } </pre>` ; }, choices : \"NO_KEYS\" }; jsPsych . run ([ preload , camera_instructions , init_camera , calibration_instructions , calibration , validation_instructions , validation , recalibrate , calibration_done , begin , trial , show_data ]); </ script > </ html > Below is example data from the image-keyboard-response trial taken from the experiment above. In addition to the standard data that is collected for this plugin, you can see the additional webgazer_data and webgazer_targets arrays. The webgazer_data shows 21 gaze location estimates during the 1-second image presentation. The webgazer_targets array shows that there was one target, the image-keyboard-response stimulus, and tells you the x- and y-coordinate boundaries for the target (image) rectangle. By comparing each of the x/y locations from the webgazer_data locations array with the target boundaries in webgazer_targets , you can determine if/when the estimated gaze location was inside the target area. { \"rt\" : null , \"stimulus\" : \"img/blue.png\" , \"response\" : null , \"trial_type\" : \"image-keyboard-response\" , \"trial_index\" : 4 , \"time_elapsed\" : 30701 , \"internal_node_id\" : \"0.0-4.0\" , \"webgazer_data\" : [ { \"x\" : 1065 , \"y\" : 437 , \"t\" : 39 }, { \"x\" : 943 , \"y\" : 377 , \"t\" : 79 }, { \"x\" : 835 , \"y\" : 332 , \"t\" : 110 }, { \"x\" : 731 , \"y\" : 299 , \"t\" : 146 }, { \"x\" : 660 , \"y\" : 271 , \"t\" : 189 }, { \"x\" : 606 , \"y\" : 251 , \"t\" : 238 }, { \"x\" : 582 , \"y\" : 213 , \"t\" : 288 }, { \"x\" : 551 , \"y\" : 200 , \"t\" : 335 }, { \"x\" : 538 , \"y\" : 183 , \"t\" : 394 }, { \"x\" : 514 , \"y\" : 177 , \"t\" : 436 }, { \"x\" : 500 , \"y\" : 171 , \"t\" : 493 }, { \"x\" : 525 , \"y\" : 178 , \"t\" : 542 }, { \"x\" : 537 , \"y\" : 182 , \"t\" : 592 }, { \"x\" : 543 , \"y\" : 178 , \"t\" : 633 }, { \"x\" : 547 , \"y\" : 177 , \"t\" : 691 }, { \"x\" : 558 , \"y\" : 174 , \"t\" : 739 }, { \"x\" : 574 , \"y\" : 183 , \"t\" : 789 }, { \"x\" : 577 , \"y\" : 197 , \"t\" : 838 }, { \"x\" : 584 , \"y\" : 214 , \"t\" : 889 }, { \"x\" : 603 , \"y\" : 218 , \"t\" : 937 }, { \"x\" : 606 , \"y\" : 221 , \"t\" : 987 } ], \"webgazer_targets\" : [ \"#jspsych-image-keyboard-response-stimulus\" : { \"x\" : 490 , \"y\" : 135 , \"height\" : 300 , \"width\" : 300 , \"top\" : 135 , \"bottom\" : 435 , \"left\" : 490 , \"right\" : 790 } ] }","title":"Example"},{"location":"overview/fullscreen/","text":"Fullscreen Experiments \u00b6 You can run your experiment in fullscreen mode by using the jspsych-fullscreen plugin. var jsPsych = initJsPsych (); var timeline = []; timeline . push ({ type : jsPsychFullscreen , fullscreen_mode : true }); timeline . push ({ type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will be in fullscreen mode.' }); // exit fullscreen mode timeline . push ({ type : jsPsychFullscreen , fullscreen_mode : false }); timeline . push ({ type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will NOT be in fullscreen mode.' }); jsPsych . run ( timeline ); For security reasons, web browsers require that users initiate an action to launch fullscreen mode. The fullscreen plugin displays a button that the user must click to change the display to fullscreen. Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari.","title":"Fullscreen Experiments"},{"location":"overview/fullscreen/#fullscreen-experiments","text":"You can run your experiment in fullscreen mode by using the jspsych-fullscreen plugin. var jsPsych = initJsPsych (); var timeline = []; timeline . push ({ type : jsPsychFullscreen , fullscreen_mode : true }); timeline . push ({ type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will be in fullscreen mode.' }); // exit fullscreen mode timeline . push ({ type : jsPsychFullscreen , fullscreen_mode : false }); timeline . push ({ type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will NOT be in fullscreen mode.' }); jsPsych . run ( timeline ); For security reasons, web browsers require that users initiate an action to launch fullscreen mode. The fullscreen plugin displays a button that the user must click to change the display to fullscreen. Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari.","title":"Fullscreen Experiments"},{"location":"overview/media-preloading/","text":"Media Preloading \u00b6 If an experiment uses image, audio, or video files as stimuli, it is a good idea to preload the files before running the experiment. You can preload files at any point in your experiment using the jsPsych preload plugin . Preloading files means that the participant's browser will download the files and store them in local memory on the participant's computer. This is important because displaying or playing a media file is much faster if it is already in memory on the participant's computer. Without preloading, there will be noticeable delays in the display of media, which will affect any timing measurements (such as how long an image is displayed, or a participant's response time since first viewing an image). For particularly large files, like video, preloading content avoids lengthy pauses in the middle of the experiment that can be disruptive to the flow of the experiment. Warning Note that video preloading will not work when you run your experiment offline (e.g., by double-clicking on the HTML file), but it will work once your experiment is running online (hosted on a server). The Cross-origin requests (CORS) and safe mode section on the Running Experiments page contains more information about this. Automatic Preloading \u00b6 jsPsych can automatically preload audio, video, and image files that are used as parameters for the standard set of plugins, based on the timeline that is passed to jsPsych.run . You must initiate this preloading using a preload trial. You should add this preload trial into your timeline when you want the preloading to occur, and set the auto_preload parameter to true . // the \"auto_preload: true\" setting tells the plugin to automatically find // stimuli to preload based the main experiment timeline (used in jsPsych.run) var preload = { type : jsPsychPreload , auto_preload : true } // this image file can be automatically preloaded var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' } // the sound file can be automatically preloaded var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'audio/hello.mp3' } // the video file can be automatically preloaded (as long as the experiment // is running on a server) var video_trial = { type : jsPsychVideoKeyboardResponse , stimulus : [ 'video/sample_video.mp4' ] } jsPsych . run ([ preload , image_trial , sound_trial , video_trial ]); Manual preloading \u00b6 If you are using media files in your experiment but they are not being passed directly as parameters to the trials (e.g., because you are using functions as parameters that return the media files, you are using timeline variables, or you are embedding the media files in an HTML string), then these files will not be detected when you use the auto_preload option, so you must manually specify them. The preload plugin allows you to add these files using the images , audio and video parameters. // this image file cannot be automatically preloaded because it is embedded in // an HTML string var image_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<img src=\"img/file1.png\"></img>' , } // this audio file cannot be automatically preloaded because it is returned // from a function var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : function () { return 'audio/sound1.mp3' } } // these video files cannot be automatically preloaded because they are passed // into a trial using the jsPsych.timelineVariable function var video_trials = { timeline : [ { type : jsPsychVideoKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'video' ) } ], timeline_variables : [ { video : [ 'video/1.mp4' ]}, { video : [ 'video/2.mp4' ]} ] } // to manually preload media files, create an array of file paths for each // media type var images = [ 'img/file1.png' ]; var audio = [ 'audio/sound1.mp3' ]; var video = [ 'video/1.mp4' , 'video/2.mp4' ]; // these array can be passed into the preload plugin using the images, audio // and video parameters var preload = { type : jsPsychPreload , images : images , audio : audio , video : video } jsPsych . run ([ preload , image_trial , sound_trial , video_trials ]); Combining automatic and manual preloading \u00b6 It's possible to combine automatic and manual preloading. For instance, you may want to automatically preload all of the media files based on your experiment timeline, while also manually preloading any files that can't be automatically preloaded. Any duplicate file names across all preloading methods will be removed before preloading starts, so including the same file names in multiple preload parameters will not affect the preloading duration. // this file can be preloaded automatically var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' } // this file can be preloaded automatically var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'audio/hello.mp3' } // these files must be preloaded manually var video_trials = { timeline : [ { type : jsPsychVideoKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'video' ) } ], timeline_variables : [ { video : [ 'video/1.mp4' ]}, { video : [ 'video/2.mp4' ]} ] } var video = [ 'video/1.mp4' , 'video/2.mp4' ]; var preload = { type : jsPsychPreload , auto_preload : true , // automatically preload the image and audio files video : video // manually preload the videos used with timeline variables } jsPsych . run ([ preload , image_trial , sound_trial , video_trials ]); Preloading in batches \u00b6 Some experiments use many and/or large media files. This can cause problems when participants have slow and/or unreliable internet connections, because it increases the chances of loading errors during preloading. This can also cause problems with file caching, i.e. ensuring that the preloaded files remain in the browser's memory, because loading all stimuli at once may exceed the browser's cache limits. One option for mitigating these problems is to load the media files in smaller batches throughout the experiment. Files should be preloaded as close as possible to when they will be needed. For instance, if you have several blocks of trials, then right before each block, you can preload the stimuli that are needed for that block. Here is an example with trials where the stimuli files can be preloaded automatically. In this case, the trials parameter is used to tell the preload plugin to preload the stimuli from a specific part of the timeline. // these image files in these trial blocks can be automatically preloaded var block_1 = { timeline : [ { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' }, { type : jsPsychImageKeyboardResponse , stimulus : 'img/file2.png' } ] } var block_2 = { timeline : [ { type : jsPsychImageKeyboardResponse , stimulus : 'img/file3.png' }, { type : jsPsychImageKeyboardResponse , stimulus : 'img/file4.png' } ] } var preload_1 = { type : jsPsychPreload , trials : block_1 // automatically preload just the images from block_1 trials } var preload_2 = { type : jsPsychPreload , trials : block_2 // automatically preload just the images from block_2 trials } jsPsych . run ( // add each preload trial onto the timeline before the appropriate trial block [ preload_1 , block_1 , preload_2 , block_2 ] ); Below is an example with trials where the stimuli files cannot be preloaded automatically, because the stimuli files are passed to the trials via jsPsych.timelineVariable . In this case, we create separate arrays for each batch of files, and then pass those arrays to the each preload trial. // these trial blocks cannot be automatically preloaded because // the media files are passed to the trial parameters with timeline variables var block_1 = { timeline : [...], timeline_variables : [ { stim : 'file1.png' }, { stim : 'file1.png' } ] } var block_2 = { timeline : [...], timeline_variables : [ { stim : 'file3.png' }, { stim : 'file4.png' } ] } var images_block_1 = [ 'file1.png' , 'file2.png' ]; var images_block_2 = [ 'file3.png' , 'file4.png' ]; // preload trial for preloading the block 1 stimuli var preload_1 = { type : jsPsychPreload , images : images_block_1 } // preload trial for preloading the block 2 stimuli var preload_2 = { type : jsPsychPreload , images : images_block_2 } jsPsych . run ( // add each preload trial to the timeline before the appropriate trial block [ preload_1 , block_1 , preload_2 , block_2 ] ); Preloading progress bar \u00b6 By default, the preload plugin will display a progress bar while files are being preloaded. This progress bar represents all files that are being preloaded during the trial, regardless of whether the file is being preloaded automatically via the auto_preload or trials parameters, or manually via the audio , images , and video parameters. You may wish to turn the preload progress bar off if you are only loading a small number of files, as it will appear and disappear so quickly that the participant may be confused about what it was. You can control whether the preloading progress bar appears by setting the show_progress_bar parameter in the preload trial. var preload_trial = { type : jsPsychPreload , auto_preload : true show_progress_bar : false // hide progress bar } Loading time limits \u00b6 It's usually a good idea to set a time limit for file loading, to ensure that participants aren't waiting for an unreasonable amount of time. Time limits can be specified in milliseconds using the max_load_time parameter. If you set a loading time limit and all files haven't finished loading before this time, then the preload trial will either stop an error (if continue_after_error is false, the default) or the trial will end and the experiment will continue (if continue_after_error is true ). If max_load_time is null (the default), then there is no time limit. var preload_trial = { type : jsPsychPreload , auto_preload : true max_load_time : 60000 // 1 minute } Loading and error messages \u00b6 It's possible to specify custom messages to be shown on the page while the media files are loading, and in case of one or more file loading errors. The message parameter allows you to customize the loading message using an HML-formatted string. If show_progress_bar is true , then this message will be shown above the progress bar. var preload_trial = { type : jsPsychPreload , auto_preload : true message : 'Please wait while the experiment loads. This may take a few minutes.' , } A preloading error will occur when either (a) one or more files produces a loading error, and/or (b) all files have not finished loading before the max_load_time duration. The error_message parameter allows you to customize the messsage that's shown on the page in these cases. This message will only be shown if continue_after_error is false (the default). var preload_trial = { type : jsPsychPreload , auto_preload : true , error_message : 'The experiment failed to load. Please contact the researcher.' } In addition to the error_message parameter, it's also possible to show more detailed error messages on the page about any files that failed to load. You can control this with the show_detailed_errors parameter. Detailed error messages will appear below the general error message. This only applies if continue_after_error is false (the default). Detailed error messages can be useful when testing and debugging your experiment. If show_detailed_errors is true , then if one or more loading errors occurs before the max_load_time is reached, then the error page will also contian a list of the file(s) that produced an error, along with error information (if there is any). Note that this may not be a complete list, because it will only report any errors that occurred before the max_load_time was reached. If there are no file loading errors but preloading hasn't finished before the max_load_time , then detailed error message will just tell you that loading timed out. var preload_trial = { type : jsPsychPreload , auto_preload : true , // show details of any file loading errors and/or loading time out show_detailed_errors : true } Options for handling errors \u00b6 If continue_after_error is true , then the experiment will not stop if one or more files fails to load. Instead, the trial will end and the experiment will continue. However, the preload trial data will contain a property called success , which is whether or not all files were loaded successfully, timeout , which is whether or not the files loaded successfully before the max_load_time . The preload trial data will also contain lists of any image , audio , and video files that failed to load. This gives you the option to continue the experiment after preloading fails and use the preload trial data decide what to do next. For instance, you may decide to skip the trials that use the stimuli files that failed to load, or try loading the failed files again. Another option is to simply end the experiment when preloading fails, but send the data back to your server so that you have more information about the loading failure. var preload_trial = { type : jsPsychPreload , auto_preload : true , message : 'Please wait while the experiment loads...' , // don't stop the experiment if there are file loading errors or if loading times out continue_after_error : true } var save_data = { type : jsPsychCallFunction , async : true , func : function ( done ){ var data = jsPsych . data . get (). json (); save_data ( data , function () { done ()}) } } // the experiment will stop here, since there are no valid key choices or trial duration var fail_message = { type : jsPsychHtmlKeyboardResponse , stimulus : 'The experiment failed to load. Please contact the researcher.' , choices : \"NO_KEYS\" , trial_duration : null } var if_loading_fails = { timeline : [ save_data , fail_message ], conditional_function : function () { if ( jsPsych . data . getLastTrialData ()[ 0 ]. values (). success ) { // preloading was successful, so skip this conditional timeline // and move on with the experiment return false ; } else { // preloading failed, so run this conditional timeline: // save the data to the server and show the fail message return true ; } } } // ... rest of experiment jsPsych . run ([ preload_trial , if_loading_fails , ... ]) The preload plugin's on_success and on_error callback functions provide another way of tracking preloading progress and handling file loading errors. These functions are called after any file either loads successfully or produces an error, respectively. These functions receive a single argument, which is the path of the file (string) that loaded or produced an error. var file_load_count = 0 ; var file_error_count = 0 ; var preload_trial = { type : jsPsychPreload , auto_preload : true , on_error : function ( file ) { file_error_count ++ ; console . log ( 'Error: ' , file ); }, on_success : function ( file ) { file_load_count ++ ; console . log ( 'Loaded: ' , file ); } }; Note that there's no guarantee that any/all files will trigger one of these two callback functions, because they are cancelled after the preload trial ends. For instance, if a file takes longer to load then the max_load_time , then the preload trial will end due to timing out, and the on_success and on_error callbacks for any in-progress files will be cancelled.","title":"Media Preloading"},{"location":"overview/media-preloading/#media-preloading","text":"If an experiment uses image, audio, or video files as stimuli, it is a good idea to preload the files before running the experiment. You can preload files at any point in your experiment using the jsPsych preload plugin . Preloading files means that the participant's browser will download the files and store them in local memory on the participant's computer. This is important because displaying or playing a media file is much faster if it is already in memory on the participant's computer. Without preloading, there will be noticeable delays in the display of media, which will affect any timing measurements (such as how long an image is displayed, or a participant's response time since first viewing an image). For particularly large files, like video, preloading content avoids lengthy pauses in the middle of the experiment that can be disruptive to the flow of the experiment. Warning Note that video preloading will not work when you run your experiment offline (e.g., by double-clicking on the HTML file), but it will work once your experiment is running online (hosted on a server). The Cross-origin requests (CORS) and safe mode section on the Running Experiments page contains more information about this.","title":"Media Preloading"},{"location":"overview/media-preloading/#automatic-preloading","text":"jsPsych can automatically preload audio, video, and image files that are used as parameters for the standard set of plugins, based on the timeline that is passed to jsPsych.run . You must initiate this preloading using a preload trial. You should add this preload trial into your timeline when you want the preloading to occur, and set the auto_preload parameter to true . // the \"auto_preload: true\" setting tells the plugin to automatically find // stimuli to preload based the main experiment timeline (used in jsPsych.run) var preload = { type : jsPsychPreload , auto_preload : true } // this image file can be automatically preloaded var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' } // the sound file can be automatically preloaded var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'audio/hello.mp3' } // the video file can be automatically preloaded (as long as the experiment // is running on a server) var video_trial = { type : jsPsychVideoKeyboardResponse , stimulus : [ 'video/sample_video.mp4' ] } jsPsych . run ([ preload , image_trial , sound_trial , video_trial ]);","title":"Automatic Preloading"},{"location":"overview/media-preloading/#manual-preloading","text":"If you are using media files in your experiment but they are not being passed directly as parameters to the trials (e.g., because you are using functions as parameters that return the media files, you are using timeline variables, or you are embedding the media files in an HTML string), then these files will not be detected when you use the auto_preload option, so you must manually specify them. The preload plugin allows you to add these files using the images , audio and video parameters. // this image file cannot be automatically preloaded because it is embedded in // an HTML string var image_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<img src=\"img/file1.png\"></img>' , } // this audio file cannot be automatically preloaded because it is returned // from a function var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : function () { return 'audio/sound1.mp3' } } // these video files cannot be automatically preloaded because they are passed // into a trial using the jsPsych.timelineVariable function var video_trials = { timeline : [ { type : jsPsychVideoKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'video' ) } ], timeline_variables : [ { video : [ 'video/1.mp4' ]}, { video : [ 'video/2.mp4' ]} ] } // to manually preload media files, create an array of file paths for each // media type var images = [ 'img/file1.png' ]; var audio = [ 'audio/sound1.mp3' ]; var video = [ 'video/1.mp4' , 'video/2.mp4' ]; // these array can be passed into the preload plugin using the images, audio // and video parameters var preload = { type : jsPsychPreload , images : images , audio : audio , video : video } jsPsych . run ([ preload , image_trial , sound_trial , video_trials ]);","title":"Manual preloading"},{"location":"overview/media-preloading/#combining-automatic-and-manual-preloading","text":"It's possible to combine automatic and manual preloading. For instance, you may want to automatically preload all of the media files based on your experiment timeline, while also manually preloading any files that can't be automatically preloaded. Any duplicate file names across all preloading methods will be removed before preloading starts, so including the same file names in multiple preload parameters will not affect the preloading duration. // this file can be preloaded automatically var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' } // this file can be preloaded automatically var sound_trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'audio/hello.mp3' } // these files must be preloaded manually var video_trials = { timeline : [ { type : jsPsychVideoKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'video' ) } ], timeline_variables : [ { video : [ 'video/1.mp4' ]}, { video : [ 'video/2.mp4' ]} ] } var video = [ 'video/1.mp4' , 'video/2.mp4' ]; var preload = { type : jsPsychPreload , auto_preload : true , // automatically preload the image and audio files video : video // manually preload the videos used with timeline variables } jsPsych . run ([ preload , image_trial , sound_trial , video_trials ]);","title":"Combining automatic and manual preloading"},{"location":"overview/media-preloading/#preloading-in-batches","text":"Some experiments use many and/or large media files. This can cause problems when participants have slow and/or unreliable internet connections, because it increases the chances of loading errors during preloading. This can also cause problems with file caching, i.e. ensuring that the preloaded files remain in the browser's memory, because loading all stimuli at once may exceed the browser's cache limits. One option for mitigating these problems is to load the media files in smaller batches throughout the experiment. Files should be preloaded as close as possible to when they will be needed. For instance, if you have several blocks of trials, then right before each block, you can preload the stimuli that are needed for that block. Here is an example with trials where the stimuli files can be preloaded automatically. In this case, the trials parameter is used to tell the preload plugin to preload the stimuli from a specific part of the timeline. // these image files in these trial blocks can be automatically preloaded var block_1 = { timeline : [ { type : jsPsychImageKeyboardResponse , stimulus : 'img/file1.png' }, { type : jsPsychImageKeyboardResponse , stimulus : 'img/file2.png' } ] } var block_2 = { timeline : [ { type : jsPsychImageKeyboardResponse , stimulus : 'img/file3.png' }, { type : jsPsychImageKeyboardResponse , stimulus : 'img/file4.png' } ] } var preload_1 = { type : jsPsychPreload , trials : block_1 // automatically preload just the images from block_1 trials } var preload_2 = { type : jsPsychPreload , trials : block_2 // automatically preload just the images from block_2 trials } jsPsych . run ( // add each preload trial onto the timeline before the appropriate trial block [ preload_1 , block_1 , preload_2 , block_2 ] ); Below is an example with trials where the stimuli files cannot be preloaded automatically, because the stimuli files are passed to the trials via jsPsych.timelineVariable . In this case, we create separate arrays for each batch of files, and then pass those arrays to the each preload trial. // these trial blocks cannot be automatically preloaded because // the media files are passed to the trial parameters with timeline variables var block_1 = { timeline : [...], timeline_variables : [ { stim : 'file1.png' }, { stim : 'file1.png' } ] } var block_2 = { timeline : [...], timeline_variables : [ { stim : 'file3.png' }, { stim : 'file4.png' } ] } var images_block_1 = [ 'file1.png' , 'file2.png' ]; var images_block_2 = [ 'file3.png' , 'file4.png' ]; // preload trial for preloading the block 1 stimuli var preload_1 = { type : jsPsychPreload , images : images_block_1 } // preload trial for preloading the block 2 stimuli var preload_2 = { type : jsPsychPreload , images : images_block_2 } jsPsych . run ( // add each preload trial to the timeline before the appropriate trial block [ preload_1 , block_1 , preload_2 , block_2 ] );","title":"Preloading in batches"},{"location":"overview/media-preloading/#preloading-progress-bar","text":"By default, the preload plugin will display a progress bar while files are being preloaded. This progress bar represents all files that are being preloaded during the trial, regardless of whether the file is being preloaded automatically via the auto_preload or trials parameters, or manually via the audio , images , and video parameters. You may wish to turn the preload progress bar off if you are only loading a small number of files, as it will appear and disappear so quickly that the participant may be confused about what it was. You can control whether the preloading progress bar appears by setting the show_progress_bar parameter in the preload trial. var preload_trial = { type : jsPsychPreload , auto_preload : true show_progress_bar : false // hide progress bar }","title":"Preloading progress bar"},{"location":"overview/media-preloading/#loading-time-limits","text":"It's usually a good idea to set a time limit for file loading, to ensure that participants aren't waiting for an unreasonable amount of time. Time limits can be specified in milliseconds using the max_load_time parameter. If you set a loading time limit and all files haven't finished loading before this time, then the preload trial will either stop an error (if continue_after_error is false, the default) or the trial will end and the experiment will continue (if continue_after_error is true ). If max_load_time is null (the default), then there is no time limit. var preload_trial = { type : jsPsychPreload , auto_preload : true max_load_time : 60000 // 1 minute }","title":"Loading time limits"},{"location":"overview/media-preloading/#loading-and-error-messages","text":"It's possible to specify custom messages to be shown on the page while the media files are loading, and in case of one or more file loading errors. The message parameter allows you to customize the loading message using an HML-formatted string. If show_progress_bar is true , then this message will be shown above the progress bar. var preload_trial = { type : jsPsychPreload , auto_preload : true message : 'Please wait while the experiment loads. This may take a few minutes.' , } A preloading error will occur when either (a) one or more files produces a loading error, and/or (b) all files have not finished loading before the max_load_time duration. The error_message parameter allows you to customize the messsage that's shown on the page in these cases. This message will only be shown if continue_after_error is false (the default). var preload_trial = { type : jsPsychPreload , auto_preload : true , error_message : 'The experiment failed to load. Please contact the researcher.' } In addition to the error_message parameter, it's also possible to show more detailed error messages on the page about any files that failed to load. You can control this with the show_detailed_errors parameter. Detailed error messages will appear below the general error message. This only applies if continue_after_error is false (the default). Detailed error messages can be useful when testing and debugging your experiment. If show_detailed_errors is true , then if one or more loading errors occurs before the max_load_time is reached, then the error page will also contian a list of the file(s) that produced an error, along with error information (if there is any). Note that this may not be a complete list, because it will only report any errors that occurred before the max_load_time was reached. If there are no file loading errors but preloading hasn't finished before the max_load_time , then detailed error message will just tell you that loading timed out. var preload_trial = { type : jsPsychPreload , auto_preload : true , // show details of any file loading errors and/or loading time out show_detailed_errors : true }","title":"Loading and error messages"},{"location":"overview/media-preloading/#options-for-handling-errors","text":"If continue_after_error is true , then the experiment will not stop if one or more files fails to load. Instead, the trial will end and the experiment will continue. However, the preload trial data will contain a property called success , which is whether or not all files were loaded successfully, timeout , which is whether or not the files loaded successfully before the max_load_time . The preload trial data will also contain lists of any image , audio , and video files that failed to load. This gives you the option to continue the experiment after preloading fails and use the preload trial data decide what to do next. For instance, you may decide to skip the trials that use the stimuli files that failed to load, or try loading the failed files again. Another option is to simply end the experiment when preloading fails, but send the data back to your server so that you have more information about the loading failure. var preload_trial = { type : jsPsychPreload , auto_preload : true , message : 'Please wait while the experiment loads...' , // don't stop the experiment if there are file loading errors or if loading times out continue_after_error : true } var save_data = { type : jsPsychCallFunction , async : true , func : function ( done ){ var data = jsPsych . data . get (). json (); save_data ( data , function () { done ()}) } } // the experiment will stop here, since there are no valid key choices or trial duration var fail_message = { type : jsPsychHtmlKeyboardResponse , stimulus : 'The experiment failed to load. Please contact the researcher.' , choices : \"NO_KEYS\" , trial_duration : null } var if_loading_fails = { timeline : [ save_data , fail_message ], conditional_function : function () { if ( jsPsych . data . getLastTrialData ()[ 0 ]. values (). success ) { // preloading was successful, so skip this conditional timeline // and move on with the experiment return false ; } else { // preloading failed, so run this conditional timeline: // save the data to the server and show the fail message return true ; } } } // ... rest of experiment jsPsych . run ([ preload_trial , if_loading_fails , ... ]) The preload plugin's on_success and on_error callback functions provide another way of tracking preloading progress and handling file loading errors. These functions are called after any file either loads successfully or produces an error, respectively. These functions receive a single argument, which is the path of the file (string) that loaded or produced an error. var file_load_count = 0 ; var file_error_count = 0 ; var preload_trial = { type : jsPsychPreload , auto_preload : true , on_error : function ( file ) { file_error_count ++ ; console . log ( 'Error: ' , file ); }, on_success : function ( file ) { file_load_count ++ ; console . log ( 'Loaded: ' , file ); } }; Note that there's no guarantee that any/all files will trigger one of these two callback functions, because they are cancelled after the preload trial ends. For instance, if a file takes longer to load then the max_load_time , then the preload trial will end due to timing out, and the on_success and on_error callbacks for any in-progress files will be cancelled.","title":"Options for handling errors"},{"location":"overview/mturk/","text":"Integrating with Mechanical Turk \u00b6 A common use of jsPsych is to build an online experiment and find participants using Mechanical Turk . Once an experiment is available through a web server and data is being saved on the server , connecting the experiment with Mechanical Turk takes only a few additional steps. jsPsych has some built-in functionality to assist with this process. The jsPsych.turk module \u00b6 The jsPsych.turk module contains functions that are relevant for experiments running on Mechanical Turk. Creating an advertisement page \u00b6 When potential participants view your experiment on Mechanical Turk, they will be able to see a single webpage before deciding whether or not to accept the HIT (start the experiment). This first page is often used as an advertisement for the experiment, similar to posting a flier in a department hallway. The important thing to remember about this page is that potential participants will be able to interact with it even if they haven't accepted the HIT. Therefore, it can be useful to change the content of the page depending on whether the HIT has been accepted or not. This is relatively easy to do: < div id = \"experiment_link\" > You must accept the HIT to begin the experiment </ div > . < script > // jsPsych has a method turkInfo() which can determine whether or not the // HIT has been accepted. var turkInfo = jsPsych . turkInfo (); // turkInfo.previewMode is true in two cases: when the HIT has not been // accepted yet OR when the page is viewed outside of mechanical turk. // The second property, outsideTurk, is true when the page is viewed // outside of mechanical turk, so together, the statement will be true // only when in Turk and when the HIT is not accepted yet. if ( ! turkInfo . previewMode && ! turkInfo . outsideTurk ) { document . querySelector ( '#experiment_link' ). innerHMTL = '<a href=\"link_to_experiment.html\" target=\"_blank\">Click Here to Start Experiment</a>' ; } </ script > One important issue with advertisement pages is that they must be served using the https protocol, which requires having an SSL certificate on the web server hosting the page. Instructions for how to do this vary depending on what kind of server you are using, so the best advice is to simply Google for instructions on how to acquire and install an SSL certificate on your particular server. Getting the worker ID \u00b6 Every account on Mechanical Turk is given a unique identification string. Recording this ID is a useful way to keep track of who is doing your experiment. In particular, while Turk has built in tools for preventing the same person from doing a HIT more than once, there may be cases where you don't want participants to complete related experiments. If you store the worker ID of every person who starts an experiment in a database, then you can exclude people by running a query on the database to check for the ID. jsPsych can get the workerID, assignmentID, and hitID with the turkInfo method. var turkInfo = jsPsych . turk . turkInfo (); // workerID turkInfo . workerId // hitID turkInfo . hitId // assignmentID turkInfo . assignmentId Recording the workerId at the start of the experiment is also a good way to track dropouts. Submitting results to Mechanical Turk \u00b6 If you are running a HIT on Mechanical Turk using the ExternalQuestion template, then you'll need to provide a way for participants to indicate that they have completed the HIT. (If you are using another template, then the template will provide this code for you). jsPSych makes this a relatively easy task. A common strategy for external HITs is to display an HTML page on the Mechanical Turk website that links to your HIT. Participants click the link, which opens the actual experiment content in a new browser window or tab, allowing the experiment to take up the whole browser window instead of just the iframe that displays content on Mechanical Turk. On this page, you might include a submit button for workers to indicate that they have finished the experiment. The page would look something like this: < p > Enter the code you were given: </ p > < input type = \"text\" id = \"code\" ></ input > < button onclick = \"sendData();\" > Submit HIT </ button > < script > function sendData () { jsPsych . turk . submitToTurk ({ code : document . getElementById ( 'code' ). value }); } </ script > When workers click the button, the contents of the code text field will be sent to Mechanical Turk, and you'll be able to view the participants and the codes that they entered in the Mechanical Turk GUI. You can then approve or reject work using the Mechanical Turk website. Limitations \u00b6 jsPsych is not designed to communicate with the Mechanical Turk API in a comprehensive manner. If you are looking for software to help you post and manage HITs, then you may want to look at PsiTurk . jsPsych and PsiTurk complement each other nicely, and there is an example of combining the two platforms on PsiTurk's experiment exchange.","title":"Integrating with Mechanical Turk"},{"location":"overview/mturk/#integrating-with-mechanical-turk","text":"A common use of jsPsych is to build an online experiment and find participants using Mechanical Turk . Once an experiment is available through a web server and data is being saved on the server , connecting the experiment with Mechanical Turk takes only a few additional steps. jsPsych has some built-in functionality to assist with this process.","title":"Integrating with Mechanical Turk"},{"location":"overview/mturk/#the-jspsychturk-module","text":"The jsPsych.turk module contains functions that are relevant for experiments running on Mechanical Turk.","title":"The jsPsych.turk module"},{"location":"overview/mturk/#creating-an-advertisement-page","text":"When potential participants view your experiment on Mechanical Turk, they will be able to see a single webpage before deciding whether or not to accept the HIT (start the experiment). This first page is often used as an advertisement for the experiment, similar to posting a flier in a department hallway. The important thing to remember about this page is that potential participants will be able to interact with it even if they haven't accepted the HIT. Therefore, it can be useful to change the content of the page depending on whether the HIT has been accepted or not. This is relatively easy to do: < div id = \"experiment_link\" > You must accept the HIT to begin the experiment </ div > . < script > // jsPsych has a method turkInfo() which can determine whether or not the // HIT has been accepted. var turkInfo = jsPsych . turkInfo (); // turkInfo.previewMode is true in two cases: when the HIT has not been // accepted yet OR when the page is viewed outside of mechanical turk. // The second property, outsideTurk, is true when the page is viewed // outside of mechanical turk, so together, the statement will be true // only when in Turk and when the HIT is not accepted yet. if ( ! turkInfo . previewMode && ! turkInfo . outsideTurk ) { document . querySelector ( '#experiment_link' ). innerHMTL = '<a href=\"link_to_experiment.html\" target=\"_blank\">Click Here to Start Experiment</a>' ; } </ script > One important issue with advertisement pages is that they must be served using the https protocol, which requires having an SSL certificate on the web server hosting the page. Instructions for how to do this vary depending on what kind of server you are using, so the best advice is to simply Google for instructions on how to acquire and install an SSL certificate on your particular server.","title":"Creating an advertisement page"},{"location":"overview/mturk/#getting-the-worker-id","text":"Every account on Mechanical Turk is given a unique identification string. Recording this ID is a useful way to keep track of who is doing your experiment. In particular, while Turk has built in tools for preventing the same person from doing a HIT more than once, there may be cases where you don't want participants to complete related experiments. If you store the worker ID of every person who starts an experiment in a database, then you can exclude people by running a query on the database to check for the ID. jsPsych can get the workerID, assignmentID, and hitID with the turkInfo method. var turkInfo = jsPsych . turk . turkInfo (); // workerID turkInfo . workerId // hitID turkInfo . hitId // assignmentID turkInfo . assignmentId Recording the workerId at the start of the experiment is also a good way to track dropouts.","title":"Getting the worker ID"},{"location":"overview/mturk/#submitting-results-to-mechanical-turk","text":"If you are running a HIT on Mechanical Turk using the ExternalQuestion template, then you'll need to provide a way for participants to indicate that they have completed the HIT. (If you are using another template, then the template will provide this code for you). jsPSych makes this a relatively easy task. A common strategy for external HITs is to display an HTML page on the Mechanical Turk website that links to your HIT. Participants click the link, which opens the actual experiment content in a new browser window or tab, allowing the experiment to take up the whole browser window instead of just the iframe that displays content on Mechanical Turk. On this page, you might include a submit button for workers to indicate that they have finished the experiment. The page would look something like this: < p > Enter the code you were given: </ p > < input type = \"text\" id = \"code\" ></ input > < button onclick = \"sendData();\" > Submit HIT </ button > < script > function sendData () { jsPsych . turk . submitToTurk ({ code : document . getElementById ( 'code' ). value }); } </ script > When workers click the button, the contents of the code text field will be sent to Mechanical Turk, and you'll be able to view the participants and the codes that they entered in the Mechanical Turk GUI. You can then approve or reject work using the Mechanical Turk website.","title":"Submitting results to Mechanical Turk"},{"location":"overview/mturk/#limitations","text":"jsPsych is not designed to communicate with the Mechanical Turk API in a comprehensive manner. If you are looking for software to help you post and manage HITs, then you may want to look at PsiTurk . jsPsych and PsiTurk complement each other nicely, and there is an example of combining the two platforms on PsiTurk's experiment exchange.","title":"Limitations"},{"location":"overview/plugins/","text":"Plugins \u00b6 In jsPsych, plugins define the kinds of trials or events that should occur during the experiment. Some plugins define very general events, like displaying a set of instructions pages , displaying an image and recording a keyboard response , or playing a sound file and recording a button response . Other plugins are more specific, like those that display particular kinds of stimuli (e.g., a circular visual search array ), or run a specific version of particular kind of task (e.g., the Implicit Association Test ). Part of creating an experiment with jsPsych involves figuring out which plugins are needed to create the tasks you want your participants to perform. Plugins provide a structure for a particular trial or task, but often allow for significant customization and flexibility. For example, the image-keyboard-response plugin defines a simple structure for showing an image and collecting a keyboard response. You can specify the what the stimulus is, what keys the participant is allowed to press, how long the stimulus should be on the screen, how long the participant has to respond, and so on. Many of these options have reasonable default values; even though the image plugin has many different parameters, you only need to specify the image stimulus in order to use it. Each plugin has its own documentation page, which describes what the plugin does, what options are available, and what kind of data it collects. Using a plugin \u00b6 To use a plugin, you'll need to load the plugin's JavaScript file in your experiment's HTML page. All jsPsych experiments also need to load the \"jsPsych.js\" file. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" type = \"text/javascript\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" type = \"text/javascript\" ></ script > </ head > Once a plugin is loaded, you can use JavaScript to define a trial that uses that plugin. All jsPsych trials need a type parameter, which tells jsPsych what plugin to use to run the trial. The trial's type is similar to the plugin name, but it always starts with \"jsPsych\" and is written in camel case rather than with dashes between the words. The trial's type parameter should NOT be a string (i.e., no quotes around the type value). Here are some examples of plugin names and types: Plugin name Type image-keyboard-response jsPsychImageKeyboardResponse fullscreen jsPsychFullscreen webgazer-init-camera jsPsychWebgazerInitCamera The following JavaScript code defines a trial using the image-keyboard-response plugin to display an image file. This trial uses the default values for valid keys, stimulus duration, trial duration, and other parameters. var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'images/happy_face.jpg' } You can override any default parameter values by adding them into your trial object. Here's an example of overriding the default values for trial_duration and post_trial_gap : var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'images/happy_face.jpg' , trial_duration : 3000 , post_trial_gap : 2000 } Parameters available in all plugins \u00b6 Each plugin specifies its own set of parameters. Check the documentation for a plugin to see what parameters are available and what they do. There is also a set of parameters that can be specified for any plugin: Parameter Type Default Value Description data object undefined An object containing additional data to store for the trial. See the Data page for more details. post_trial_gap numeric null Sets the time, in milliseconds, between the current trial and the next trial. If null, there will be no gap. on_start function function(){ return; } A callback function to execute when the trial begins, before any loading has occurred. See the Event-Related Callbacks page for more details. on_finish function function(){ return; } A callback function to execute when the trial finishes, and before the next trial begins. See the Event-Related Callbacks page for more details. on_load function function(){ return; } A callback function to execute when the trial has loaded, which typically happens after the initial display of the plugin has loaded. See the Event-Related Callbacks page for more details. css_classes string null A list of CSS classes to add to the jsPsych display element for the duration of this trial. This allows you to create custom formatting rules (CSS classes) that are only applied to specific trials. For more information and examples, see the Controlling Visual Appearance page and the \"css-classes-parameter.html\" file in the jsPsych examples folder. save_trial_parameters object {} An object containing any trial parameters that should or should not be saved to the trial data. Each key is the name of a trial parameter, and its value should be true or false , depending on whether or not its value should be saved to the data. If the parameter is a function that returns the parameter value, then the value that is returned will be saved to the data. If the parameter is always expected to be a function (e.g., an event-related callback function), then the function itself will be saved as a string. For more examples, see the \"save-trial-parameters.html\" file in the jsPsych examples folder. The data parameter \u00b6 The data parameter allows you to add additional properties to the trial data. This can be useful for storing properties of the trial that are not directly apparent from the values that the plugin records. The data parameter value must be an object that contains key-value pairs. A simple example is the Flanker Task . In this experiment, participants respond to the direction of a central arrow by pressing a key to the left for a left-pointing arrow (<) and a key to the right for a right-pointing arrow (>). The arrow appears in the center of flankers , or arrows that the participant should ignore. Those flankers can be congruent (>>>>>) or incongruent (<<><<). A trial for the Flanker Task written with jsPsych might look like this: var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' } } Note the use of the data parameter to add a property stimulus_type with the value congruent and a property target_direction with the value left . Having these properties recorded directly in the data simplifies data analysis, making it easy to aggregate data by stimulus_type and/or target_direction . The post_trial_gap (ITI) parameter \u00b6 The default inter-trial interval (ITI) in jsPsych is 0 ms. This can be adjusted at the experiment-wide level by changing the default_iti parameter in initJsPsych() . The ITI can also be controlled at the trial level through the post_trial_gap parameter. Setting this parameter to a positive integer x will cause a blank screen to display after the trial for x milliseconds. Setting this parameter for a trial will override the default_iti value set in initJsPsych . var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'There will be a 1.5 second blank screen after this trial.' , post_trial_gap : 1500 } The on_start parameter \u00b6 Immediately before a trial runs, there is an opportunity to run an arbitrary function through the on_start event handler. This event handler is passed a single argument containing an editable copy of the trial parameters. This function can therefore be used to alter the trial based on the state of the experiment, among other uses. // when this trial runs, the on_start function will change the trial's stimulus and data parameters, // so the trial will display an incongruent Flanker stimulus with a right-facing central arrow var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' }, on_start : function ( trial ){ trial . stimulus = '<<><<' ; trial . data . stimulus_type = 'incongruent' ; trial . data . target_direction = 'right' ; } } The on_finish parameter \u00b6 After a trial is completed, there is an opportunity to run an arbitrary function through the on_finish event handler. This function is passed a single argument containing an editable copy of the data recorded for that trial. This function can therefore be used to update the state of the experiment based on the data collected, or modify the data collected. The on_finish function can be useful to calculate new data properties that were unknowable at the start of the trial. For example, with the Flanker Task example above, the on_finish function could check the response and use to this information to add a new property to the data called correct , which is either true or false . // in addition to all of the standard data collected for this trial, // this on_finish function adds a property called 'correct' // which is either 'true' or 'false' // depending on the response that was made var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' , correct_response : 'f' }, on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response )){ data . correct = true ; } else { data . correct = false ; } } } The on_load parameter \u00b6 The on_load callback function will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. This can be useful for changing various aspects of the page elements and their properties that would otherwise require modifying the plugin file. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_load : function () { // this will change the src attribute of the image after 500ms setTimeout ( function (){ document . querySelector ( 'img' ). src = 'imgB.png' }, 500 ); } }; The css_classes parameter \u00b6 The css_classes parameter allows you to add an array of CSS class names to the jsPsych display element on that specific trial. This allows you to create custom style and formatting rules that are only applied to specific trials. If you want CSS rules that only apply to specific elements during a trial, you can use additional CSS selectors. < style > . flanker-stimulus { font-size : 500 % ; } . flanker-stimulus # prompt { font-size : 18 px ; } . fixation { font-size : 80 px ; } </ style > < script > var fixation_trial = { type : jsPsychHtmlKeyboardResponse , choices : \"NO_KEYS\" , stimulus : '+' , css_classes : [ 'fixation' ] }; var flanker_trial = { type : jsPsychHtmlKeyboardResponse , choices : [ \"ArrowLeft\" , \"ArrowRight\" ], stimulus : '>>>>>' , prompt : '<span id=\"prompt\">Press the left or right arrow key.</span>' , css_classes : [ 'flanker-stimulus' ] }; </ script > The save_trial_parameters parameter \u00b6 The save_trial_parameters parameter allows you to tell jsPsych what parameters you want to be saved to the data. This can be used to override the parameter values that the plugin saves by default. You can add more parameter values to the data that are not normally saved, or remove parameter values that normally are saved. This can be especially useful when the parameter value is dynamic (i.e. a function) and you want to record the value that was used during the trial. var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<p style=\"color: orange; font-size: 48px; font-weight: bold;\">BLUE</p>' , choices : function () { return jsPsych . randomization . shuffle ([ 'Yes' , 'No' ]); }, post_trial_gap : function () { return jsPsych . randomization . sampleWithoutReplacement ([ 200 , 300 , 400 , 500 ], 1 )[ 0 ]; }, save_trial_parameters : { // save the randomly-selected button order and post trial gap duration to the trial data choices : true , post_trial_gap : true , // don't save the stimulus stimulus : false } } Note You cannot remove the internal_node_id and trial_index values from the trial data, because these are used internally by jsPsych. Data collected by all plugins \u00b6 Each plugin defines what data is collected on the trial. The documentation for each plugin specifies what information will be stored in the trial data. In addition to the data collected by a plugin, there is a default set of data that is collected on every trial. Name Type Value trial_type string The name of the plugin used to run the trial. trial_index numeric The index of the current trial across the whole experiment. time_elapsed numeric The number of milliseconds between the start of the experiment and when the trial ended. internal_node_id string A string identifier for the current TimelineNode. Creating a new plugin \u00b6 See our developer's guide for plugins for information about how to create a new plugin.","title":"Plugins"},{"location":"overview/plugins/#plugins","text":"In jsPsych, plugins define the kinds of trials or events that should occur during the experiment. Some plugins define very general events, like displaying a set of instructions pages , displaying an image and recording a keyboard response , or playing a sound file and recording a button response . Other plugins are more specific, like those that display particular kinds of stimuli (e.g., a circular visual search array ), or run a specific version of particular kind of task (e.g., the Implicit Association Test ). Part of creating an experiment with jsPsych involves figuring out which plugins are needed to create the tasks you want your participants to perform. Plugins provide a structure for a particular trial or task, but often allow for significant customization and flexibility. For example, the image-keyboard-response plugin defines a simple structure for showing an image and collecting a keyboard response. You can specify the what the stimulus is, what keys the participant is allowed to press, how long the stimulus should be on the screen, how long the participant has to respond, and so on. Many of these options have reasonable default values; even though the image plugin has many different parameters, you only need to specify the image stimulus in order to use it. Each plugin has its own documentation page, which describes what the plugin does, what options are available, and what kind of data it collects.","title":"Plugins"},{"location":"overview/plugins/#using-a-plugin","text":"To use a plugin, you'll need to load the plugin's JavaScript file in your experiment's HTML page. All jsPsych experiments also need to load the \"jsPsych.js\" file. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" type = \"text/javascript\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" type = \"text/javascript\" ></ script > </ head > Once a plugin is loaded, you can use JavaScript to define a trial that uses that plugin. All jsPsych trials need a type parameter, which tells jsPsych what plugin to use to run the trial. The trial's type is similar to the plugin name, but it always starts with \"jsPsych\" and is written in camel case rather than with dashes between the words. The trial's type parameter should NOT be a string (i.e., no quotes around the type value). Here are some examples of plugin names and types: Plugin name Type image-keyboard-response jsPsychImageKeyboardResponse fullscreen jsPsychFullscreen webgazer-init-camera jsPsychWebgazerInitCamera The following JavaScript code defines a trial using the image-keyboard-response plugin to display an image file. This trial uses the default values for valid keys, stimulus duration, trial duration, and other parameters. var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'images/happy_face.jpg' } You can override any default parameter values by adding them into your trial object. Here's an example of overriding the default values for trial_duration and post_trial_gap : var image_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'images/happy_face.jpg' , trial_duration : 3000 , post_trial_gap : 2000 }","title":"Using a plugin"},{"location":"overview/plugins/#parameters-available-in-all-plugins","text":"Each plugin specifies its own set of parameters. Check the documentation for a plugin to see what parameters are available and what they do. There is also a set of parameters that can be specified for any plugin: Parameter Type Default Value Description data object undefined An object containing additional data to store for the trial. See the Data page for more details. post_trial_gap numeric null Sets the time, in milliseconds, between the current trial and the next trial. If null, there will be no gap. on_start function function(){ return; } A callback function to execute when the trial begins, before any loading has occurred. See the Event-Related Callbacks page for more details. on_finish function function(){ return; } A callback function to execute when the trial finishes, and before the next trial begins. See the Event-Related Callbacks page for more details. on_load function function(){ return; } A callback function to execute when the trial has loaded, which typically happens after the initial display of the plugin has loaded. See the Event-Related Callbacks page for more details. css_classes string null A list of CSS classes to add to the jsPsych display element for the duration of this trial. This allows you to create custom formatting rules (CSS classes) that are only applied to specific trials. For more information and examples, see the Controlling Visual Appearance page and the \"css-classes-parameter.html\" file in the jsPsych examples folder. save_trial_parameters object {} An object containing any trial parameters that should or should not be saved to the trial data. Each key is the name of a trial parameter, and its value should be true or false , depending on whether or not its value should be saved to the data. If the parameter is a function that returns the parameter value, then the value that is returned will be saved to the data. If the parameter is always expected to be a function (e.g., an event-related callback function), then the function itself will be saved as a string. For more examples, see the \"save-trial-parameters.html\" file in the jsPsych examples folder.","title":"Parameters available in all plugins"},{"location":"overview/plugins/#the-data-parameter","text":"The data parameter allows you to add additional properties to the trial data. This can be useful for storing properties of the trial that are not directly apparent from the values that the plugin records. The data parameter value must be an object that contains key-value pairs. A simple example is the Flanker Task . In this experiment, participants respond to the direction of a central arrow by pressing a key to the left for a left-pointing arrow (<) and a key to the right for a right-pointing arrow (>). The arrow appears in the center of flankers , or arrows that the participant should ignore. Those flankers can be congruent (>>>>>) or incongruent (<<><<). A trial for the Flanker Task written with jsPsych might look like this: var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' } } Note the use of the data parameter to add a property stimulus_type with the value congruent and a property target_direction with the value left . Having these properties recorded directly in the data simplifies data analysis, making it easy to aggregate data by stimulus_type and/or target_direction .","title":"The data parameter"},{"location":"overview/plugins/#the-post_trial_gap-iti-parameter","text":"The default inter-trial interval (ITI) in jsPsych is 0 ms. This can be adjusted at the experiment-wide level by changing the default_iti parameter in initJsPsych() . The ITI can also be controlled at the trial level through the post_trial_gap parameter. Setting this parameter to a positive integer x will cause a blank screen to display after the trial for x milliseconds. Setting this parameter for a trial will override the default_iti value set in initJsPsych . var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'There will be a 1.5 second blank screen after this trial.' , post_trial_gap : 1500 }","title":"The post_trial_gap (ITI) parameter"},{"location":"overview/plugins/#the-on_start-parameter","text":"Immediately before a trial runs, there is an opportunity to run an arbitrary function through the on_start event handler. This event handler is passed a single argument containing an editable copy of the trial parameters. This function can therefore be used to alter the trial based on the state of the experiment, among other uses. // when this trial runs, the on_start function will change the trial's stimulus and data parameters, // so the trial will display an incongruent Flanker stimulus with a right-facing central arrow var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' }, on_start : function ( trial ){ trial . stimulus = '<<><<' ; trial . data . stimulus_type = 'incongruent' ; trial . data . target_direction = 'right' ; } }","title":"The on_start parameter"},{"location":"overview/plugins/#the-on_finish-parameter","text":"After a trial is completed, there is an opportunity to run an arbitrary function through the on_finish event handler. This function is passed a single argument containing an editable copy of the data recorded for that trial. This function can therefore be used to update the state of the experiment based on the data collected, or modify the data collected. The on_finish function can be useful to calculate new data properties that were unknowable at the start of the trial. For example, with the Flanker Task example above, the on_finish function could check the response and use to this information to add a new property to the data called correct , which is either true or false . // in addition to all of the standard data collected for this trial, // this on_finish function adds a property called 'correct' // which is either 'true' or 'false' // depending on the response that was made var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], data : { stimulus_type : 'congruent' , target_direction : 'left' , correct_response : 'f' }, on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response )){ data . correct = true ; } else { data . correct = false ; } } }","title":"The on_finish parameter"},{"location":"overview/plugins/#the-on_load-parameter","text":"The on_load callback function will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred. This can be useful for changing various aspects of the page elements and their properties that would otherwise require modifying the plugin file. var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'imgA.png' , on_load : function () { // this will change the src attribute of the image after 500ms setTimeout ( function (){ document . querySelector ( 'img' ). src = 'imgB.png' }, 500 ); } };","title":"The on_load parameter"},{"location":"overview/plugins/#the-css_classes-parameter","text":"The css_classes parameter allows you to add an array of CSS class names to the jsPsych display element on that specific trial. This allows you to create custom style and formatting rules that are only applied to specific trials. If you want CSS rules that only apply to specific elements during a trial, you can use additional CSS selectors. < style > . flanker-stimulus { font-size : 500 % ; } . flanker-stimulus # prompt { font-size : 18 px ; } . fixation { font-size : 80 px ; } </ style > < script > var fixation_trial = { type : jsPsychHtmlKeyboardResponse , choices : \"NO_KEYS\" , stimulus : '+' , css_classes : [ 'fixation' ] }; var flanker_trial = { type : jsPsychHtmlKeyboardResponse , choices : [ \"ArrowLeft\" , \"ArrowRight\" ], stimulus : '>>>>>' , prompt : '<span id=\"prompt\">Press the left or right arrow key.</span>' , css_classes : [ 'flanker-stimulus' ] }; </ script >","title":"The css_classes parameter"},{"location":"overview/plugins/#the-save_trial_parameters-parameter","text":"The save_trial_parameters parameter allows you to tell jsPsych what parameters you want to be saved to the data. This can be used to override the parameter values that the plugin saves by default. You can add more parameter values to the data that are not normally saved, or remove parameter values that normally are saved. This can be especially useful when the parameter value is dynamic (i.e. a function) and you want to record the value that was used during the trial. var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<p style=\"color: orange; font-size: 48px; font-weight: bold;\">BLUE</p>' , choices : function () { return jsPsych . randomization . shuffle ([ 'Yes' , 'No' ]); }, post_trial_gap : function () { return jsPsych . randomization . sampleWithoutReplacement ([ 200 , 300 , 400 , 500 ], 1 )[ 0 ]; }, save_trial_parameters : { // save the randomly-selected button order and post trial gap duration to the trial data choices : true , post_trial_gap : true , // don't save the stimulus stimulus : false } } Note You cannot remove the internal_node_id and trial_index values from the trial data, because these are used internally by jsPsych.","title":"The save_trial_parameters parameter"},{"location":"overview/plugins/#data-collected-by-all-plugins","text":"Each plugin defines what data is collected on the trial. The documentation for each plugin specifies what information will be stored in the trial data. In addition to the data collected by a plugin, there is a default set of data that is collected on every trial. Name Type Value trial_type string The name of the plugin used to run the trial. trial_index numeric The index of the current trial across the whole experiment. time_elapsed numeric The number of milliseconds between the start of the experiment and when the trial ended. internal_node_id string A string identifier for the current TimelineNode.","title":"Data collected by all plugins"},{"location":"overview/plugins/#creating-a-new-plugin","text":"See our developer's guide for plugins for information about how to create a new plugin.","title":"Creating a new plugin"},{"location":"overview/progress-bar/","text":"Automatic Progress Bar \u00b6 jsPsych can show a progress bar at the top of the experiment page indicating the participant's overall completion progress. The progress bar is rendered outside the jsPsych display element, and it requires the jspsych.css file to be loaded on the page. As of version 6.0, the progress bar looks like this: To show the progress bar, set the show_progress_bar option in initJsPsych to true : var jsPsych = initJsPsych ({ show_progress_bar : true }); The progress bar updates after every node on the top-level timeline updates. This avoids distracting updates in the middle of trials that are composed of multiple plugins, or confusing updates due to looping or conditional structures that may or may not execute depending on the actions of the participant. This also allows some flexibility for the programmer; by nesting timelines in a deliberate manner, the timing of progress bar updates can be controlled. Manual Control \u00b6 The progress bar can also be manually controlled using the function jsPsych.setProgressBar() . This function takes a numeric value between 0 and 1, representing the proportion of the progress bar to fill. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Almost done...' , on_finish : function (){ jsPsych . setProgressBar ( 0.85 ); // set progress bar to 85% full. } } You can also get the current value of the progress bar with jsPsych.getProgressBarCompleted() . var proportion_complete = jsPsych . getProgressBarCompleted (); If you are going to use manual progress bar control, you may want to disable the automatic progress bar updates by setting the auto_update_progress_bar property in initJsPsych() to false . var jsPsych = initJsPsych ({ show_progress_bar : true , auto_update_progress_bar : false }); Here's a complete example showing how to use these functions and initJsPsych() settings to manually update the progress bar: var jsPsych = initJsPsych ({ show_progress_bar : true , auto_update_progress_bar : false }); var n_trials = 5 ; var start = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press any key to start!' , on_start : function () { // set progress bar to 0 at the start of experiment jsPsych . setProgressBar ( 0 ); } }; var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is a trial!' , on_finish : function () { // at the end of each trial, update the progress bar // based on the current value and the proportion to update for each trial var curr_progress_bar_value = jsPsych . getProgressBarCompleted (); jsPsych . setProgressBar ( curr_progress_bar_value + ( 1 / n_trials )); } }; var trials = { timeline : [ trial ], repetitions : n_trials }; var done = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Done!' }; jsPsych . run ([ start , trials , done ]); Custom Text \u00b6 By default, jsPsych adds the text \"Completion Progress\" to the left of the progress bar. You can specify custom text using the message_progress_bar parameter in initJsPsych . // support for different spoken languages var jsPsych = initJsPsych ({ show_progress_bar : true , message_progress_bar : 'Porcentaje completo' }); // no message var jsPsych = initJsPsych ({ show_progress_bar : true , message_progress_bar : '' });","title":"Automatic Progress Bar"},{"location":"overview/progress-bar/#automatic-progress-bar","text":"jsPsych can show a progress bar at the top of the experiment page indicating the participant's overall completion progress. The progress bar is rendered outside the jsPsych display element, and it requires the jspsych.css file to be loaded on the page. As of version 6.0, the progress bar looks like this: To show the progress bar, set the show_progress_bar option in initJsPsych to true : var jsPsych = initJsPsych ({ show_progress_bar : true }); The progress bar updates after every node on the top-level timeline updates. This avoids distracting updates in the middle of trials that are composed of multiple plugins, or confusing updates due to looping or conditional structures that may or may not execute depending on the actions of the participant. This also allows some flexibility for the programmer; by nesting timelines in a deliberate manner, the timing of progress bar updates can be controlled.","title":"Automatic Progress Bar"},{"location":"overview/progress-bar/#manual-control","text":"The progress bar can also be manually controlled using the function jsPsych.setProgressBar() . This function takes a numeric value between 0 and 1, representing the proportion of the progress bar to fill. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Almost done...' , on_finish : function (){ jsPsych . setProgressBar ( 0.85 ); // set progress bar to 85% full. } } You can also get the current value of the progress bar with jsPsych.getProgressBarCompleted() . var proportion_complete = jsPsych . getProgressBarCompleted (); If you are going to use manual progress bar control, you may want to disable the automatic progress bar updates by setting the auto_update_progress_bar property in initJsPsych() to false . var jsPsych = initJsPsych ({ show_progress_bar : true , auto_update_progress_bar : false }); Here's a complete example showing how to use these functions and initJsPsych() settings to manually update the progress bar: var jsPsych = initJsPsych ({ show_progress_bar : true , auto_update_progress_bar : false }); var n_trials = 5 ; var start = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press any key to start!' , on_start : function () { // set progress bar to 0 at the start of experiment jsPsych . setProgressBar ( 0 ); } }; var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is a trial!' , on_finish : function () { // at the end of each trial, update the progress bar // based on the current value and the proportion to update for each trial var curr_progress_bar_value = jsPsych . getProgressBarCompleted (); jsPsych . setProgressBar ( curr_progress_bar_value + ( 1 / n_trials )); } }; var trials = { timeline : [ trial ], repetitions : n_trials }; var done = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Done!' }; jsPsych . run ([ start , trials , done ]);","title":"Manual Control"},{"location":"overview/progress-bar/#custom-text","text":"By default, jsPsych adds the text \"Completion Progress\" to the left of the progress bar. You can specify custom text using the message_progress_bar parameter in initJsPsych . // support for different spoken languages var jsPsych = initJsPsych ({ show_progress_bar : true , message_progress_bar : 'Porcentaje completo' }); // no message var jsPsych = initJsPsych ({ show_progress_bar : true , message_progress_bar : '' });","title":"Custom Text"},{"location":"overview/prolific/","text":"Integrating with Prolific \u00b6 Prolific is a participant recruitment service aimed at research. Integrating a jsPsych experiment with Prolific requires capturing the participant's ID and sending the participant to a completion URL at the end of the experiment. Capturing the Participant ID, Study ID, and Session ID \u00b6 When creating a study on Prolific you must provide the URL to your study. You can host your jsPsych experiment however you'd like - some options are discussed in the Running Experiments documentation page. Once you've got a URL to your experiment, you can enter that in the study link section of Prolific. Then, click the option to record Prolific IDs via URL parameters. This will append information about the participant's prolific ID ( PROLIFIC_PID ), the study's ID ( STUDY_ID ), and the session ID ( SESSION_ID ) to the URL that participants use to access your experiment. We can capture these variables with jsPsych, and add them to jsPsych's data. This can be done anywhere in your code. This code does not need to run as part of your experiment timeline. < script > var jsPsych = initJsPsych (); // capture info from Prolific var subject_id = jsPsych . data . getURLVariable ( 'PROLIFIC_PID' ); var study_id = jsPsych . data . getURLVariable ( 'STUDY_ID' ); var session_id = jsPsych . data . getURLVariable ( 'SESSION_ID' ); jsPsych . data . addProperties ({ subject_id : subject_id , study_id : study_id , session_id : session_id }); // create the rest of the experiment var timeline = [...] jsPsych . run ( timeline ) </ script > Completing the Experiment \u00b6 When the experiment is complete, Prolific requires that you send the participant to a specific URL that marks the session as complete on Prolific's server. The link is provided to you by Prolific in the study completion section of the setup. You can accomplish this in a couple different ways. Warning It's important that you've saved all the data from your experiment before the participant returns to Prolific. Make sure that any server communication has completed prior to redirecting the participant. One way to do this is by using the async features of the call-function plugin ( example ). Participant clicks a link \u00b6 One option is to create a trial that contains a link that the participant clicks to end the experiment and return to Prolific. For example, the html-keyboard-response plugin can be used to display text that includes a link. This could go on a debriefing page. Here's an example trial that could be used. Note that choices is set to \"NO_KEYS\" , which will prevent the participant from continuing past this point in the experiment. var final_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : `<p>You've finished the last task. Thanks for participating!</p> <p><a href=\"https://app.prolific.co/submissions/complete?cc=XXXXXXX\">Click here to return to Prolific and complete the study</a>.</p>` , choices : \"NO_KEYS\" } Automatically redirect \u00b6 A second option is to automatically redirect the participant to the completion URL when the experiment is finished. You could do this in a number of places in the jsPsych timeline. Here's an example using the on_finish event for the entire experiment. var jsPsych = initJsPsych ({ on_finish : function (){ window . location = \"https://app.prolific.co/submissions/complete?cc=XXXXXXX\" } });","title":"Integrating with Prolific"},{"location":"overview/prolific/#integrating-with-prolific","text":"Prolific is a participant recruitment service aimed at research. Integrating a jsPsych experiment with Prolific requires capturing the participant's ID and sending the participant to a completion URL at the end of the experiment.","title":"Integrating with Prolific"},{"location":"overview/prolific/#capturing-the-participant-id-study-id-and-session-id","text":"When creating a study on Prolific you must provide the URL to your study. You can host your jsPsych experiment however you'd like - some options are discussed in the Running Experiments documentation page. Once you've got a URL to your experiment, you can enter that in the study link section of Prolific. Then, click the option to record Prolific IDs via URL parameters. This will append information about the participant's prolific ID ( PROLIFIC_PID ), the study's ID ( STUDY_ID ), and the session ID ( SESSION_ID ) to the URL that participants use to access your experiment. We can capture these variables with jsPsych, and add them to jsPsych's data. This can be done anywhere in your code. This code does not need to run as part of your experiment timeline. < script > var jsPsych = initJsPsych (); // capture info from Prolific var subject_id = jsPsych . data . getURLVariable ( 'PROLIFIC_PID' ); var study_id = jsPsych . data . getURLVariable ( 'STUDY_ID' ); var session_id = jsPsych . data . getURLVariable ( 'SESSION_ID' ); jsPsych . data . addProperties ({ subject_id : subject_id , study_id : study_id , session_id : session_id }); // create the rest of the experiment var timeline = [...] jsPsych . run ( timeline ) </ script >","title":"Capturing the Participant ID, Study ID, and Session ID"},{"location":"overview/prolific/#completing-the-experiment","text":"When the experiment is complete, Prolific requires that you send the participant to a specific URL that marks the session as complete on Prolific's server. The link is provided to you by Prolific in the study completion section of the setup. You can accomplish this in a couple different ways. Warning It's important that you've saved all the data from your experiment before the participant returns to Prolific. Make sure that any server communication has completed prior to redirecting the participant. One way to do this is by using the async features of the call-function plugin ( example ).","title":"Completing the Experiment"},{"location":"overview/prolific/#participant-clicks-a-link","text":"One option is to create a trial that contains a link that the participant clicks to end the experiment and return to Prolific. For example, the html-keyboard-response plugin can be used to display text that includes a link. This could go on a debriefing page. Here's an example trial that could be used. Note that choices is set to \"NO_KEYS\" , which will prevent the participant from continuing past this point in the experiment. var final_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : `<p>You've finished the last task. Thanks for participating!</p> <p><a href=\"https://app.prolific.co/submissions/complete?cc=XXXXXXX\">Click here to return to Prolific and complete the study</a>.</p>` , choices : \"NO_KEYS\" }","title":"Participant clicks a link"},{"location":"overview/prolific/#automatically-redirect","text":"A second option is to automatically redirect the participant to the completion URL when the experiment is finished. You could do this in a number of places in the jsPsych timeline. Here's an example using the on_finish event for the entire experiment. var jsPsych = initJsPsych ({ on_finish : function (){ window . location = \"https://app.prolific.co/submissions/complete?cc=XXXXXXX\" } });","title":"Automatically redirect"},{"location":"overview/record-browser-interactions/","text":"Record browser interactions \u00b6 Participants in an online experiment have the freedom to multitask while performing an experiment. jsPsych automatically records information about when the user clicks on a window that is not the experiment, and about when the user exits full screen mode if the experiment is running in full screen mode. This data is stored separately from the main experiment data, and can be accessed with jsPsych.data.getInteractionData() . Each time the user leaves the experiment window, returns to the experiment window, exits full screen mode, or enters full screen mode, the event is recorded in the interaction data. Each event has the following structure. { event : 'focus' , // 'focus' or 'blur' or 'fullscreenenter' or 'fullscreenexit' trial : 12 , // the index of the active trial when the event happened time : 1240543 // time in ms since the start of the experiment } You can specify a custom function, in the initJsPsych() method, that is called whenever one of these events occurs initJsPsych ({ on_interaction_data_update : function ( data ) { console . log ( JSON . stringify ( data )) } });","title":"Record Browser Interactions"},{"location":"overview/record-browser-interactions/#record-browser-interactions","text":"Participants in an online experiment have the freedom to multitask while performing an experiment. jsPsych automatically records information about when the user clicks on a window that is not the experiment, and about when the user exits full screen mode if the experiment is running in full screen mode. This data is stored separately from the main experiment data, and can be accessed with jsPsych.data.getInteractionData() . Each time the user leaves the experiment window, returns to the experiment window, exits full screen mode, or enters full screen mode, the event is recorded in the interaction data. Each event has the following structure. { event : 'focus' , // 'focus' or 'blur' or 'fullscreenenter' or 'fullscreenexit' trial : 12 , // the index of the active trial when the event happened time : 1240543 // time in ms since the start of the experiment } You can specify a custom function, in the initJsPsych() method, that is called whenever one of these events occurs initJsPsych ({ on_interaction_data_update : function ( data ) { console . log ( JSON . stringify ( data )) } });","title":"Record browser interactions"},{"location":"overview/running-experiments/","text":"Running Experiments \u00b6 You can run your jsPsych experiment: Offline , by opening the HTML file directly in the browser using the file:// protocol. Online , by hosting the files on a web server using the http:// or https:// protocol. The way that you run your experiment will have consequences for certain aspects about how the experiment works, and what your experiment will be able to do. This page explains what you need to know about both of these options. Info If you are looking for a tool to automate deployment-related tasks, check out the jsPsych Builder CLI utility. It automatically bundles scripts and style sheets, configures media preloading, and yields a zip file that contains all files for deployment (online or offline). jsPsych Builder can also directly build JATOS experiment files (.jzip) that you can upload to a JATOS server (see this section below for more info about JATOS and other server options). Offline \u00b6 You can run your jsPsych experiment offline by opening the HTML file directly in a web browser, for instance by double-clicking on it. This uses the file:// protocol. It's usually the fastest and easiest way to run through an experiment, and is very useful while writing and testing the code. At some point you will need to move your experiment files onto a server and send the data to a database, since this is how you will ultimately collect the data (unless you're planning to collect data on your local computer). There are some important differences between the way the experiment runs offline compared to online via a web server. Note that, unless noted, here we're using the word \"server\" to mean either a local server (which runs on your computer and only makes the experiment files available from within that computer, and is often used during development), or a remote server (which does not run on your computer and does share your experiment files over the internet). Cross-origin requests (CORS) and safe mode \u00b6 Web browsers have a security policy called cross-origin resource sharing (CORS) that determines whether the webpage can request files that come from a different origin (i.e. protocol, host/domain, and port). This isn't a problem when your study runs online , because in that case your experiment files all have the same origin. However, when you run your experiment offline , the CORS policy blocks some jsPsych features that require loading local files . If your experiment uses these features, then CORS errors will prevent the experiment from running. To prevent these errors, jsPsych uses a 'safe mode' when it detects that the HTML page is running via the file:// protocol, and if so, automatically disables the features that don't work in that context. Specifically, when a jsPsych experiment runs offline: Web Audio is disabled (even if use_webaudio is set to true in initJsPsych ). The WebAudio API option is used by default because it allows more precise measurement of response times relative to the onset of the audio. But because WebAudio doesn't work offline, audio will be played using HTML5 audio instead. This is equivalent to setting use_webaudio to false in initJsPsych . Video preloading is disabled (both automatic and manual preloading via the preload plugin). Videos will still play when you run your experiment offline, but they will load during the experiment, which might cause noticeable delays before video playback starts. This safe mode feature is controlled by the override_safe_mode parameter in initJsPsych , which defaults to false . If you leave this setting as the default, then you won't need to worry about CORS errors while running your experiment offline, or remembering to change your initJsPsych settings when you move the experiment online. It's possible to override jsPsych's safe mode by setting override_safe_mode to true in initJsPsych . One reason you might do this is if you've disabled web security features in your browser (see here and here for instructions in Chrome), which is safe to do if you know what you're doing. If your experiment does not use Web Audio or preloaded videos, then jsPsych's safe mode feature will not have any effect. The override_safe_mode parameter also has no effect when your experiment is running online a web server, because the page will be loaded via the http:// or https:// protocol. Media loading \u00b6 While running your experiment offline, any media files are likely to load very quickly because they are stored on your own computer's disk. Therefore you may not notice problems with file loading delays while running your experiment locally (either offline or on a local server) because the files will load fast enough that they never cause disruption. However, when your experiment is hosted on a remote server, the files will need to be transferred over the internet, which means they will take longer to load - in some cases much longer. Loading delays are most noticeable with media files: images, audio, and video. As explained on the Media Preloading page, loading delays during your experiment can cause problems for stimulus display and response times. It is important to test your experiment to ensure that any media files are preloading successfully and not being requested again during the experiment. You can use the Network tab in your browser's developer tools to see when files are loaded and to simulate a slow internet connection (see here for Chrome Network tab documentation). If you are preloading many and/or large files, such as videos, you may want to increase the max_load_time parameter in the preload plugin so that participants with slow/unreliable internet connections will be able to take part in your experiment. Permanent data storage \u00b6 As explained in the Data Storage, Aggregation, and Manipulation page, jsPsych stores information in the participant's browser. While running an experiment offline, you won't be able to send the data to a database. However you can still see the data that jsPsych collects by saving it as a local file (using jsPsych.data.get().localSave ), displaying it in the webpage at the end of the experiment (using jsPsych.data.displayData ), or printing it to the browser's console (using console.log ). Permanent data storage is also necessary when the code that runs the experiment depends on information that can't be known in advance, and that changes throughout data collection. Some common examples of this in cognitive behavioral research are version counterbalancing , where the experiment code needs to access and update the history of version assignment in order to determine which version should be assigned, and multi-session/training studies , where the experiment might need to access and update information about each participant like their current session number, task difficulty level, etc. Doing these things in an automated way requires the use of a server. While developing and testing your experiment offline, you might choose to simulate some of these things and then implement them properly once you move your experiment online. For instance, you could randomize instead of counterbalancing version assignment: var versions = [ 1 , 2 ]; var random_version = jsPsych . randomization . sampleWithoutReplacement ( versions , 1 )[ 0 ]; And use URL query parameters to pass in variables like session number and difficulty level: // add the variables onto the end of the URL that appears in the browser when you open the file // e.g., file:///C:/my_experiment.html?id=1&sess=2&diff=3 var participant_id = jsPsych . data . getURLVariable ( 'id' ); var session = jsPsych . data . getURLVariable ( 'sess' ); var difficulty = jsPsych . data . getURLVariable ( 'diff' ); Online \u00b6 Hosting the Experiment and Saving the Data \u00b6 jsPsych is a front-end JavaScript library that runs entirely on the participant's computer. To run a jsPsych experiment over the internet, the files need to be hosted on a public web server so that participants can access the experiment using a web browser. When the participant completes the experiment in the browser, all of the data that jsPsych collects is stored on the participant's computer in the browser's memory. To get access to this data, it needs to be sent from the participant's browser back to the web server and stored in a database or a file. To be maximally flexible, jsPsych doesn't provide a single built-in solution for the web server component of your experiment. This makes jsPsych compatible with a wide range of hosting services and tools, allowing researchers to choose the web server option that best suit their needs. Some options for running your jsPsych experiment online include: Cognition.run - A free service designed specifically for hosting jsPsych experiments, with an easy-to-use interface. JATOS - A free program that runs on your own server and provides a GUI for setting up experiments and accessing the data. Offers lots of features for creating more complex experiments and managing multiple researchers. Pavlovia - A paid hosting service for web-based experiments, run by the PsychoPy team. Experiment files are managed on a GitLab repository. Participants will access the experiment through a link to Pavlovia. PsiTurk - Python-based program to help you host your experiment on your own computer and collect data from MTurk (see Recruiting Participants below). Relatively easy for a DIY option. Pushkin - A set of tools to help you set up your own virtual laboratory for online experiments. This option differs from the others in that it helps you set up a complete website that may contain many different experiments, information about the laboratory, participant logins, and other features that are targeted at hosting large-scale data collection efforts. Full DIY - You can setup your own web server and database and handle the communication yourself. Traditional web server 'stacks' include LAMP / LEMP (Linux operating system, Apache or Nginx server application, MySQL database, and PHP programming language). Other common web server frameworks include Flask (Python) and Node.js (JavaScript). Recruiting Participants \u00b6 Once your experiment is running online, you could recruit participants in the same way that you would for lab-based studies. For instance, if your institution uses SONA, you can advertise your web-based study link on SONA. SONA allows you to automactically embed a unique ID in online study URLs, which you can then save in your data using jsPsych's URL query parameters function . SONA will also generate a completion URL that you can redirect participants to at the end of the study, and this will mark them as having completed the study in SONA. To take full advantage of hosting an experiment online, many researchers advertise their experiments more widely. Social media and other media outlets provide one option for reaching a large number of potential participants. There are also some commercial platforms that you can use to advertise your study and pay anonymous online participants. These recruitment platforms charge a fee for use. The advantages of these platforms are that they handle the participant payments and allow you to specify pre-screening criteria. The most commonly used recruitment platforms in online behavioral research are: Prolific : An online labor market designed specifically for web-based research. Amazon Mechanical Turk (MTurk) : An online labor market designed for advertising paid 'human intelligence tasks'. This service was designed for use by commercial businesses but has been used by behavioral researchers for many years. Like SONA, Prolific and MTurk use URL query parameters to get participant information, and redirection to specific URLs to mark participants as having finished the study. jsPsych includes convenience functions for interacting with MTurk participants . Information about integrating with Prolific can be found in the researcher support section of their website.","title":"Running Experiments"},{"location":"overview/running-experiments/#running-experiments","text":"You can run your jsPsych experiment: Offline , by opening the HTML file directly in the browser using the file:// protocol. Online , by hosting the files on a web server using the http:// or https:// protocol. The way that you run your experiment will have consequences for certain aspects about how the experiment works, and what your experiment will be able to do. This page explains what you need to know about both of these options. Info If you are looking for a tool to automate deployment-related tasks, check out the jsPsych Builder CLI utility. It automatically bundles scripts and style sheets, configures media preloading, and yields a zip file that contains all files for deployment (online or offline). jsPsych Builder can also directly build JATOS experiment files (.jzip) that you can upload to a JATOS server (see this section below for more info about JATOS and other server options).","title":"Running Experiments"},{"location":"overview/running-experiments/#offline","text":"You can run your jsPsych experiment offline by opening the HTML file directly in a web browser, for instance by double-clicking on it. This uses the file:// protocol. It's usually the fastest and easiest way to run through an experiment, and is very useful while writing and testing the code. At some point you will need to move your experiment files onto a server and send the data to a database, since this is how you will ultimately collect the data (unless you're planning to collect data on your local computer). There are some important differences between the way the experiment runs offline compared to online via a web server. Note that, unless noted, here we're using the word \"server\" to mean either a local server (which runs on your computer and only makes the experiment files available from within that computer, and is often used during development), or a remote server (which does not run on your computer and does share your experiment files over the internet).","title":"Offline"},{"location":"overview/running-experiments/#cross-origin-requests-cors-and-safe-mode","text":"Web browsers have a security policy called cross-origin resource sharing (CORS) that determines whether the webpage can request files that come from a different origin (i.e. protocol, host/domain, and port). This isn't a problem when your study runs online , because in that case your experiment files all have the same origin. However, when you run your experiment offline , the CORS policy blocks some jsPsych features that require loading local files . If your experiment uses these features, then CORS errors will prevent the experiment from running. To prevent these errors, jsPsych uses a 'safe mode' when it detects that the HTML page is running via the file:// protocol, and if so, automatically disables the features that don't work in that context. Specifically, when a jsPsych experiment runs offline: Web Audio is disabled (even if use_webaudio is set to true in initJsPsych ). The WebAudio API option is used by default because it allows more precise measurement of response times relative to the onset of the audio. But because WebAudio doesn't work offline, audio will be played using HTML5 audio instead. This is equivalent to setting use_webaudio to false in initJsPsych . Video preloading is disabled (both automatic and manual preloading via the preload plugin). Videos will still play when you run your experiment offline, but they will load during the experiment, which might cause noticeable delays before video playback starts. This safe mode feature is controlled by the override_safe_mode parameter in initJsPsych , which defaults to false . If you leave this setting as the default, then you won't need to worry about CORS errors while running your experiment offline, or remembering to change your initJsPsych settings when you move the experiment online. It's possible to override jsPsych's safe mode by setting override_safe_mode to true in initJsPsych . One reason you might do this is if you've disabled web security features in your browser (see here and here for instructions in Chrome), which is safe to do if you know what you're doing. If your experiment does not use Web Audio or preloaded videos, then jsPsych's safe mode feature will not have any effect. The override_safe_mode parameter also has no effect when your experiment is running online a web server, because the page will be loaded via the http:// or https:// protocol.","title":"Cross-origin requests (CORS) and safe mode"},{"location":"overview/running-experiments/#media-loading","text":"While running your experiment offline, any media files are likely to load very quickly because they are stored on your own computer's disk. Therefore you may not notice problems with file loading delays while running your experiment locally (either offline or on a local server) because the files will load fast enough that they never cause disruption. However, when your experiment is hosted on a remote server, the files will need to be transferred over the internet, which means they will take longer to load - in some cases much longer. Loading delays are most noticeable with media files: images, audio, and video. As explained on the Media Preloading page, loading delays during your experiment can cause problems for stimulus display and response times. It is important to test your experiment to ensure that any media files are preloading successfully and not being requested again during the experiment. You can use the Network tab in your browser's developer tools to see when files are loaded and to simulate a slow internet connection (see here for Chrome Network tab documentation). If you are preloading many and/or large files, such as videos, you may want to increase the max_load_time parameter in the preload plugin so that participants with slow/unreliable internet connections will be able to take part in your experiment.","title":"Media loading"},{"location":"overview/running-experiments/#permanent-data-storage","text":"As explained in the Data Storage, Aggregation, and Manipulation page, jsPsych stores information in the participant's browser. While running an experiment offline, you won't be able to send the data to a database. However you can still see the data that jsPsych collects by saving it as a local file (using jsPsych.data.get().localSave ), displaying it in the webpage at the end of the experiment (using jsPsych.data.displayData ), or printing it to the browser's console (using console.log ). Permanent data storage is also necessary when the code that runs the experiment depends on information that can't be known in advance, and that changes throughout data collection. Some common examples of this in cognitive behavioral research are version counterbalancing , where the experiment code needs to access and update the history of version assignment in order to determine which version should be assigned, and multi-session/training studies , where the experiment might need to access and update information about each participant like their current session number, task difficulty level, etc. Doing these things in an automated way requires the use of a server. While developing and testing your experiment offline, you might choose to simulate some of these things and then implement them properly once you move your experiment online. For instance, you could randomize instead of counterbalancing version assignment: var versions = [ 1 , 2 ]; var random_version = jsPsych . randomization . sampleWithoutReplacement ( versions , 1 )[ 0 ]; And use URL query parameters to pass in variables like session number and difficulty level: // add the variables onto the end of the URL that appears in the browser when you open the file // e.g., file:///C:/my_experiment.html?id=1&sess=2&diff=3 var participant_id = jsPsych . data . getURLVariable ( 'id' ); var session = jsPsych . data . getURLVariable ( 'sess' ); var difficulty = jsPsych . data . getURLVariable ( 'diff' );","title":"Permanent data storage"},{"location":"overview/running-experiments/#online","text":"","title":"Online"},{"location":"overview/running-experiments/#hosting-the-experiment-and-saving-the-data","text":"jsPsych is a front-end JavaScript library that runs entirely on the participant's computer. To run a jsPsych experiment over the internet, the files need to be hosted on a public web server so that participants can access the experiment using a web browser. When the participant completes the experiment in the browser, all of the data that jsPsych collects is stored on the participant's computer in the browser's memory. To get access to this data, it needs to be sent from the participant's browser back to the web server and stored in a database or a file. To be maximally flexible, jsPsych doesn't provide a single built-in solution for the web server component of your experiment. This makes jsPsych compatible with a wide range of hosting services and tools, allowing researchers to choose the web server option that best suit their needs. Some options for running your jsPsych experiment online include: Cognition.run - A free service designed specifically for hosting jsPsych experiments, with an easy-to-use interface. JATOS - A free program that runs on your own server and provides a GUI for setting up experiments and accessing the data. Offers lots of features for creating more complex experiments and managing multiple researchers. Pavlovia - A paid hosting service for web-based experiments, run by the PsychoPy team. Experiment files are managed on a GitLab repository. Participants will access the experiment through a link to Pavlovia. PsiTurk - Python-based program to help you host your experiment on your own computer and collect data from MTurk (see Recruiting Participants below). Relatively easy for a DIY option. Pushkin - A set of tools to help you set up your own virtual laboratory for online experiments. This option differs from the others in that it helps you set up a complete website that may contain many different experiments, information about the laboratory, participant logins, and other features that are targeted at hosting large-scale data collection efforts. Full DIY - You can setup your own web server and database and handle the communication yourself. Traditional web server 'stacks' include LAMP / LEMP (Linux operating system, Apache or Nginx server application, MySQL database, and PHP programming language). Other common web server frameworks include Flask (Python) and Node.js (JavaScript).","title":"Hosting the Experiment and Saving the Data"},{"location":"overview/running-experiments/#recruiting-participants","text":"Once your experiment is running online, you could recruit participants in the same way that you would for lab-based studies. For instance, if your institution uses SONA, you can advertise your web-based study link on SONA. SONA allows you to automactically embed a unique ID in online study URLs, which you can then save in your data using jsPsych's URL query parameters function . SONA will also generate a completion URL that you can redirect participants to at the end of the study, and this will mark them as having completed the study in SONA. To take full advantage of hosting an experiment online, many researchers advertise their experiments more widely. Social media and other media outlets provide one option for reaching a large number of potential participants. There are also some commercial platforms that you can use to advertise your study and pay anonymous online participants. These recruitment platforms charge a fee for use. The advantages of these platforms are that they handle the participant payments and allow you to specify pre-screening criteria. The most commonly used recruitment platforms in online behavioral research are: Prolific : An online labor market designed specifically for web-based research. Amazon Mechanical Turk (MTurk) : An online labor market designed for advertising paid 'human intelligence tasks'. This service was designed for use by commercial businesses but has been used by behavioral researchers for many years. Like SONA, Prolific and MTurk use URL query parameters to get participant information, and redirection to specific URLs to mark participants as having finished the study. jsPsych includes convenience functions for interacting with MTurk participants . Information about integrating with Prolific can be found in the researcher support section of their website.","title":"Recruiting Participants"},{"location":"overview/simulation/","text":"Simulation Modes \u00b6 Added in 7.1 Simulation mode allows you run your experiment automatically and generate artificial data. Info For a detailed description of the motivation behind simulation mode and a discussion of different use cases of simulation mode, see de Leeuw, J.R., Gilbert, R.A., Petrov, N.B., & Luchterhandt, B. (2022). Simulation behavior to help researchers build experiments. Behavior Research Methods , https://doi.org/10.3758/s13428-022-01899-0 . A pre-print version is available on PsyArXiv . Getting Started \u00b6 To use simulation mode, replace jsPsych.run() with jsPsych.simulate() . jsPsych . simulate ( timeline ); This will run jsPsych in the default data-only simulation mode. To use the visual simulation mode you can specify the second parameter. jsPsych . simulate ( timeline , \"data-only\" ); jsPsych . simulate ( timeline , \"visual\" ); What happens in simulation mode \u00b6 In simulation mode, plugins call their simulate() method instead of calling their trial() method. If a plugin doesn't implement a simulate() method, then the trial will run as usual (using the trial() method) and any interaction that is needed to advance to the next trial will be required. If a plugin doesn't support visual mode, then it will run in data-only mode. data-only mode \u00b6 In data-only mode plugins typically generate resonable artificial data given the parameters specified for the trial. For example, if the trial_duration parameter is set to 2,000 ms, then any response times generated will be capped at this value. Generally the default data generated by the plugin randomly selects any available options (e.g., buttons to click) with equal probability. Response times are usually generated by sampling from an exponentially-modified Gaussian distribution truncated to positive values using jsPsych.randomization.sampleExGaussian() . In data-only mode, the plugin's trial() method usually does not run. The data are simply calculated based on trial parameters and the finishTrial() method is called immediately with the simulated data. visual mode \u00b6 In visual mode a plugin will typically generate simulated data for the trial and then use that data to mimic the kinds of actions that a participant would do. The plugin's trial() method is called by the simulation, and you'll see the experiment progress in real time. Mouse, keyboard, and touch events are simulated to control the experiment. In visual mode each plugin will generate simulated data in the same manner as data-only mode, but this data will instead be used to generate actions in the experiment and the plugin's trial() method will ultimately be responsible for generating the data. This can create some subtle differences in data between the two modes. For example, if the simulated data generates a response time of 500 ms, the data.rt value will be exactly 500 in data-only mode, but may be 501 or another slightly larger value in visual mode. This is because the simulated response is triggered at 500 ms and small delays due to JavaScript's event loop might add a few ms to the measure. Controlling simulation mode with simulation_options \u00b6 The parameters for simulation mode can be set using the simulation_options parameter in both jsPsych.simulate() and at the level of individual trials. Trial-level options \u00b6 You can specify simulation options for an individual trial by setting the simulation_options parameter. const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>Hello!</p>' , simulation_options : { data : { rt : 500 } } } Currently the three options that are available are data , mode , and simulate . data \u00b6 Setting the data option will replace the default data generated by the plugin with whatever data you specify. You can specify some or all of the data parameters. Any parameters you do not specify will be generated by the plugin. In most cases plugins will try to ensure that the data generated is consistent with the trial parameters. For example, if a trial has a trial_duration parameter of 2000 but the simulation_options specify a rt of 2500 , this creates an impossible situation because the trial would have ended before the response at 2,500ms. In most cases, the plugin will act as if a response was attempted at 2500 , which will mean that no response is generated for the trial. As you might imagine, there are a lot of parameter combinations that can generate peculiar cases where data may be inconsistent with trial parameters. We recommend double checking the simulation output, and please alert us if you discover a situation where the simulation produces inconsistent data. mode \u00b6 You can override the simulation mode specified in jsPsych.simulate() for any trial. Setting mode: 'data-only' will run the trial in data-only mode and setting mode: 'visual' will run the trial in visual mode. simulate \u00b6 If you want to turn off simulation mode for a trial, set simulate: false . Functions and timeline variables \u00b6 The simulation_options parameter is compatible with both dynamic parameters and timeline variables . Dynamic parameters can be especially useful if you want to randomize the data for each run of the simulation. For example, you can specify the rt as a sample from an ExGaussian distribution. const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>Hello!</p>' , simulation_options : { data : { rt : ()=>{ return jsPsych . randomization . sampleExGaussian ( 500 , 50 , 1 / 100 , true ) } } } } Experiment-level options \u00b6 You can also control the parameters for simulation by passing in an object to the simulation_options argument of jsPsych.simulate() . const simulation_options = { default : { data : { rt : 200 } } } jsPsych . simulate ( timeline , \"visual\" , simulation_options ) The above example will set the rt for any trial that doesn't have its own simulation_options specified to 200 . This could be useful, for example, to create a very fast preview of the experiment to verify that everything is displaying correctly without having to wait through longer trials. You can also specify sets of parameters by name using the experiment-level simulation options. const simulation_options = { default : { data : { rt : 200 } }, long_response : { data : { rt : () => { return jsPsych . randomization . sampleExGaussian ( 5000 , 500 , 1 / 500 , true ) } } } } const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>This is gonna take a bit.</p>' , simulation_options : 'long_response' } timeline . push ( trial ); jsPsych . simulate ( timeline , \"visual\" , simulation_options ) In the example above, we specified the simulation_options for trial using a string ( 'long_response' ). This will look up the corresponding set of options in the experiment-level simulation_options . We had a few use cases in mind with this approach: You could group together trials with similar behavior without needing to specify unique options for each trial. You could easily swap out different simulation options to test different kinds of behavior. For example, if you want to test that a timeline with a conditional_function is working as expected, you could have one set of simulation options where the data will cause the conditional_function to evaluate to true and another to false . By using string-based identifiers, you don't need to change the timeline code at all. You can just change the object being passed to jsPsych.simulate() . In an extreme case of the previous example, every trial on the timeline could have its own unique identifier and you could have multiple sets of simulation options to have very precise control over the data output. Current Limitations \u00b6 Simulation mode is not yet as comprehensively tested as the rest of jsPsych. While we are confident that the simulation is accurate enough for many use cases, it's very likely that there are circumstances where the simulated behavior will be inconsistent with what is actually possible in the experiment. If you come across any such circumstances, please let us know ! Currently extensions are not supported in simulation mode. Some plugins are also not supported. This will be noted on their documentation page.","title":"Simulation Modes"},{"location":"overview/simulation/#simulation-modes","text":"Added in 7.1 Simulation mode allows you run your experiment automatically and generate artificial data. Info For a detailed description of the motivation behind simulation mode and a discussion of different use cases of simulation mode, see de Leeuw, J.R., Gilbert, R.A., Petrov, N.B., & Luchterhandt, B. (2022). Simulation behavior to help researchers build experiments. Behavior Research Methods , https://doi.org/10.3758/s13428-022-01899-0 . A pre-print version is available on PsyArXiv .","title":"Simulation Modes"},{"location":"overview/simulation/#getting-started","text":"To use simulation mode, replace jsPsych.run() with jsPsych.simulate() . jsPsych . simulate ( timeline ); This will run jsPsych in the default data-only simulation mode. To use the visual simulation mode you can specify the second parameter. jsPsych . simulate ( timeline , \"data-only\" ); jsPsych . simulate ( timeline , \"visual\" );","title":"Getting Started"},{"location":"overview/simulation/#what-happens-in-simulation-mode","text":"In simulation mode, plugins call their simulate() method instead of calling their trial() method. If a plugin doesn't implement a simulate() method, then the trial will run as usual (using the trial() method) and any interaction that is needed to advance to the next trial will be required. If a plugin doesn't support visual mode, then it will run in data-only mode.","title":"What happens in simulation mode"},{"location":"overview/simulation/#data-only-mode","text":"In data-only mode plugins typically generate resonable artificial data given the parameters specified for the trial. For example, if the trial_duration parameter is set to 2,000 ms, then any response times generated will be capped at this value. Generally the default data generated by the plugin randomly selects any available options (e.g., buttons to click) with equal probability. Response times are usually generated by sampling from an exponentially-modified Gaussian distribution truncated to positive values using jsPsych.randomization.sampleExGaussian() . In data-only mode, the plugin's trial() method usually does not run. The data are simply calculated based on trial parameters and the finishTrial() method is called immediately with the simulated data.","title":"data-only mode"},{"location":"overview/simulation/#visual-mode","text":"In visual mode a plugin will typically generate simulated data for the trial and then use that data to mimic the kinds of actions that a participant would do. The plugin's trial() method is called by the simulation, and you'll see the experiment progress in real time. Mouse, keyboard, and touch events are simulated to control the experiment. In visual mode each plugin will generate simulated data in the same manner as data-only mode, but this data will instead be used to generate actions in the experiment and the plugin's trial() method will ultimately be responsible for generating the data. This can create some subtle differences in data between the two modes. For example, if the simulated data generates a response time of 500 ms, the data.rt value will be exactly 500 in data-only mode, but may be 501 or another slightly larger value in visual mode. This is because the simulated response is triggered at 500 ms and small delays due to JavaScript's event loop might add a few ms to the measure.","title":"visual mode"},{"location":"overview/simulation/#controlling-simulation-mode-with-simulation_options","text":"The parameters for simulation mode can be set using the simulation_options parameter in both jsPsych.simulate() and at the level of individual trials.","title":"Controlling simulation mode with simulation_options"},{"location":"overview/simulation/#trial-level-options","text":"You can specify simulation options for an individual trial by setting the simulation_options parameter. const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>Hello!</p>' , simulation_options : { data : { rt : 500 } } } Currently the three options that are available are data , mode , and simulate .","title":"Trial-level options"},{"location":"overview/simulation/#data","text":"Setting the data option will replace the default data generated by the plugin with whatever data you specify. You can specify some or all of the data parameters. Any parameters you do not specify will be generated by the plugin. In most cases plugins will try to ensure that the data generated is consistent with the trial parameters. For example, if a trial has a trial_duration parameter of 2000 but the simulation_options specify a rt of 2500 , this creates an impossible situation because the trial would have ended before the response at 2,500ms. In most cases, the plugin will act as if a response was attempted at 2500 , which will mean that no response is generated for the trial. As you might imagine, there are a lot of parameter combinations that can generate peculiar cases where data may be inconsistent with trial parameters. We recommend double checking the simulation output, and please alert us if you discover a situation where the simulation produces inconsistent data.","title":"data"},{"location":"overview/simulation/#mode","text":"You can override the simulation mode specified in jsPsych.simulate() for any trial. Setting mode: 'data-only' will run the trial in data-only mode and setting mode: 'visual' will run the trial in visual mode.","title":"mode"},{"location":"overview/simulation/#simulate","text":"If you want to turn off simulation mode for a trial, set simulate: false .","title":"simulate"},{"location":"overview/simulation/#functions-and-timeline-variables","text":"The simulation_options parameter is compatible with both dynamic parameters and timeline variables . Dynamic parameters can be especially useful if you want to randomize the data for each run of the simulation. For example, you can specify the rt as a sample from an ExGaussian distribution. const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>Hello!</p>' , simulation_options : { data : { rt : ()=>{ return jsPsych . randomization . sampleExGaussian ( 500 , 50 , 1 / 100 , true ) } } } }","title":"Functions and timeline variables"},{"location":"overview/simulation/#experiment-level-options","text":"You can also control the parameters for simulation by passing in an object to the simulation_options argument of jsPsych.simulate() . const simulation_options = { default : { data : { rt : 200 } } } jsPsych . simulate ( timeline , \"visual\" , simulation_options ) The above example will set the rt for any trial that doesn't have its own simulation_options specified to 200 . This could be useful, for example, to create a very fast preview of the experiment to verify that everything is displaying correctly without having to wait through longer trials. You can also specify sets of parameters by name using the experiment-level simulation options. const simulation_options = { default : { data : { rt : 200 } }, long_response : { data : { rt : () => { return jsPsych . randomization . sampleExGaussian ( 5000 , 500 , 1 / 500 , true ) } } } } const trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>This is gonna take a bit.</p>' , simulation_options : 'long_response' } timeline . push ( trial ); jsPsych . simulate ( timeline , \"visual\" , simulation_options ) In the example above, we specified the simulation_options for trial using a string ( 'long_response' ). This will look up the corresponding set of options in the experiment-level simulation_options . We had a few use cases in mind with this approach: You could group together trials with similar behavior without needing to specify unique options for each trial. You could easily swap out different simulation options to test different kinds of behavior. For example, if you want to test that a timeline with a conditional_function is working as expected, you could have one set of simulation options where the data will cause the conditional_function to evaluate to true and another to false . By using string-based identifiers, you don't need to change the timeline code at all. You can just change the object being passed to jsPsych.simulate() . In an extreme case of the previous example, every trial on the timeline could have its own unique identifier and you could have multiple sets of simulation options to have very precise control over the data output.","title":"Experiment-level options"},{"location":"overview/simulation/#current-limitations","text":"Simulation mode is not yet as comprehensively tested as the rest of jsPsych. While we are confident that the simulation is accurate enough for many use cases, it's very likely that there are circumstances where the simulated behavior will be inconsistent with what is actually possible in the experiment. If you come across any such circumstances, please let us know ! Currently extensions are not supported in simulation mode. Some plugins are also not supported. This will be noted on their documentation page.","title":"Current Limitations"},{"location":"overview/style/","text":"Controlling Visual Appearance \u00b6 Your experiment's style and formatting comes from the CSS (cascading style sheet) rules that are stored in the jspsych.css file, and the browser's defaults. There are a few ways to change the style and formatting in your experiment. The method that you choose is partly a matter of personal preference. It might also depend on whether you want the style/formatting change(s) to apply to specific trials , to the whole experiment (HTML page), or across different experiments . This section discusses the different ways of incorporating CSS into your jsPsych experiment. You can also see this page about adding CSS to web pages to learn more. Inline CSS \u00b6 Whenever you're using a parameter that accepts an HTML-formatted string, you have the option to include inline CSS. Inline CSS is a way of adding style and formatting directly into a specific HTML element using its \"style\" attribute . This is a good option for when you want to make few and/or simple style changes to an HTML trial parameter. To change an element's style using inline CSS, you can set the element's \"style\" attribute to a string that contains the CSS parameters that you want to change, along with the values that you want to use. The syntax is \" <parameter-name> : <parameter-value> ;\". In the example below, the stimulus font size is set to 30px and the text color is set to red. These changes will only be applied to this stimulus text in this specific trial. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size:30px;color:red;\">hello world!</p>' } You can also use a dynamic parameter to combine inline CSS and trial-specific variables. This allows you to easily apply the same inline CSS to multiple trials. Here's an example using a dynamic stimulus parameter and timeline variables : var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var stim = '<p style=\"font-size:30px;font-weight:bold;\">' + jsPsych . timelineVariable ( 'text' ) + '</p>' ; return stim ; } } var trial_procedure = { timeline : [ trial ], timeline_variables : [ { text : 'Welcome' }, { text : 'to' }, { text : 'the' }, { text : 'experiment!' } ] } Adding CSS rules \u00b6 You may want to add a lot of different CSS changes to your experiment, re-use the same change(s) across lots of different trials, and/or separate the style/formatting from the HTML string. In these cases, you might find it useful to create CSS rules rather than using inline CSS. Creating CSS rules is a lot like using inline CSS, except that you also need to use a CSS selector . This is because your CSS rules aren't attached to any specific HTML element (unlike inline CSS), so you need to tell the browser which element(s) the style rules should apply to. The syntax is \"css-selector { <parameter-name> : <parameter-value> ; }\". In the example below, the CSS selector \"p\" tells the browser to apply the font size change to any text that is inside of a <p> element. p { font-size : 30 px ; } You can make more specific changes using CSS rules. The specificity will depend on the CSS selectors that are used. In addition to using the tag name (e.g. \"p\"), other common CSS selectors include the element's ID or class . If you are selecting an element using it's ID, then the CSS selector needs to have a # in front of the ID, e.g. \"#stimulus\". If you are selecting elements based on their class, then you need to include a . in front of the class, e.g. \".large-text\". In the example below, the \"#stimulus\" CSS selector means that the width change will only affect elements with the \"stimulus\" ID, and the \".large-text\" CSS selector means that the font size change will only affect elements that have the \"large-text\" class. # stimulus width : 300px ; } . large-text { font-size : 200 % ; } It is possible to create even more specific CSS selectors, for instance by combining tags, IDs, and/or classes. For example, let's say that you are showing feedback text to participants, and that this text is inside of a <p> tag. You could add the ID \"correct\" to the <p> element for correct response feedback, and the ID \"incorrect\" to the <p> element for incorrect response feedback. Then you can define separate styles for correct and incorrect feedback text like this: p # incorrect { color : red ; } p # correct { color : green ; } See this page about CSS selectors for a complete reference of CSS selector patterns and their meanings. With style tags \u00b6 You can add CSS rules to your HTML page by putting them inside of <style> tags. These rules will be applied to your whole experiment . This method can be useful for making general changes to the way that your experiment looks. In the example below, the default font size is set to 25px throughout the experiment. This will overrule the default font size of 18px that is set in the jspsych.css file. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < style > . jspsych-display-element { font-size : 25 px ; } </ style > </ head > With a stylesheet \u00b6 CSS rules can also be applied to your experiment with a link to an external CSS file. This is the same method that is usually used to apply the style from jspsych.css to an experiment. These rules will be applied to your whole experiment . You may find it useful to use a custom stylesheet when you want to re-use the same CSS rules across multiple experiments (HTML files). This example shows how to add a custom CSS file in addition to the styles provided in jspsych.css. In this example, the custom CSS file is called \"my_experiment_style.css\" and it is located in the same directory as your HTML file. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < link rel = \"stylesheet\" href = \"my_experiment_style.css\" > </ head > Below are the some example contents of an external CSS file, like the \"my_experiment_style.css\" from the example above. This CSS will (1) change the page background color to black, (2) change the default font to 25px and white, and (3) limit the width of the page content so that it can only take up to 80% of its normal width. body { background-color : black ; } . jspsych-display-element { font-size : 25 px ; color : white ; } . jspsych-content { max-width : 80 % ; } Note <style> tags are not used inside of an external CSS file. Using the css_classes trial parameter \u00b6 CSS rules can also be applied in a trial-specific way using the css_classes parameter. This parameter will apply one or more class to the <div> element that holds all of the jsPsych page content during that specific trial. This way you can treat CSS styles just like any other trial parameter. You can use a static css_classes parameter value if you always want to apply the same CSS rules to the trial. In the 'fixation' example below, separating the style rules from the stimulus string makes the code a little bit 'cleaner', and this makes it easier to re-use the same style rules in other parts of the experiment. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < style > . fixation { font-size : 90 px ; font-weight : bold ; color : gray ;} </ style > </ head > < script > var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 , css_classes : [ 'fixation' ] } // ... </ script > You may want the css_classes parameter to vary across trials. If so, you can turn it into a dynamic parameter or use timeline variables (see examples below). One thing to note about the css_classes parameter is that it only adds the class(es) to the jspsych-content <div> element, which is the \"parent\" element that contains all of the experiment content. Often you'll want your CSS rules to be applied to other elements inside of this jspsych-content div. Sometimes your CSS rules will be \"inherited\" by all of the other jsPsych content inside of this parent <div>. For instance, in the fixation example above, the CSS rules that change the font size, weight and color are applied to the parent <div> and automatically passed on to the stimulus text through inheritance. There are two reasons why a CSS rule like the one above for fixation may not work the way you expect: Not all CSS properties are inherited from the parent element. When a CSS property is inherited from the parent element, it will affect all elements in a given trial. In these cases, you can change your CSS selector to make it more specific: add a space after class name, then add more CSS selectors to select the specific element(s) that you want to change. Tip To find out this more specific CSS selector, you can right-click on the element and select Inspect . In the inspector window, right-click on the property corresponding to the element and copy the selector. You might need to increase the trial's trial_duration to give yourself enough time to inspect the elements on the page. See more tips for working with CSS below. In the example below, the CSS selector .left-align #stimulus selects the element with the ID \"stimulus\" that is inside of an element with the class \"left-align\". < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < style > . left-align # stimulus { text-align : left ; width : 600 px ;} . right-align # stimulus { text-align : right ; width : 600 px ;} </ style > </ head > < script > var trial_procedure = { timeline : [{ type : jsPsychHtmlKeyboardResponse , stimulus : '<p id=\"stimulus\">This is the stimulus.</p>' , prompt : '<p>This text will not be affected by the CSS classes ' + 'because it does not have the \"stimulus\" ID.</p>' , css_classes : jsPsych . timelineVariable ( 'css_classes' ) }], timeline_variables : [ { css_classes : [ 'left-align' ]}, { css_classes : [ 'right-align' ]} ] } // ... </ script > It's also possible to pass multiple class names to the css_classes parameter. This can be useful for creating conditions that involve crossing different style-related factors. This example shows you to combine two text alignment and two text color factors to produce four different stimulus conditions: < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < style > . left-align # stimulus { text-align : left ; width : 600 px ;} . right-align # stimulus { text-align : right ; width : 600 px ;} . teal # stimulus { color : teal ;} . purple # stimulus { color : purple ;} </ style > </ head > < script > var trial_procedure = { timeline : [{ type : jsPsychHtmlKeyboardResponse , stimulus : '<p id=\"stimulus\">This is the stimulus.</p>' , prompt : '<p>This text will not be affected by the CSS classes ' + 'because it does not have the \"stimulus\" ID.</p>' , css_classes : jsPsych . timelineVariable ( 'css_classes' ), data : { condition : jsPsych . timelineVariable ( 'condition' )} }], timeline_variables : [ { css_classes : [ 'left-align' , 'teal' ], condition : 'left-teal' }, { css_classes : [ 'right-align' , 'teal' ], condition : 'right-teal' }, { css_classes : [ 'left-align' , 'purple' ], condition : 'left-purple' }, { css_classes : [ 'right-align' , 'purple' ], condition : 'right-purple' } ] } // ... </ script > See the \"css-classes-parameter.html\" file in jsPsych's examples subfolder for more explanation and examples. Tips for working with CSS \u00b6 Your browser's developer tools contain very useful features for exploring and debugging your experiment's style and formatting. Open your browser's developer tools and click on the Element Inspector button or go to the Elements tab. Once you have selected an element on the page, you can see all of the information that can be used to select it, including: tag name, e.g., \"div\", \"p\", \"img\", \"button\" ID, if it has one class(es), if it has any You can then use this information to create a CSS selector to modify that element's style. As you can see, jsPsych adds its own IDs and classes to many elements. You can use the developer tools to determine what IDs and classes already exist for the elements that you want to modify, as you may can often just use these instead of adding your own. For instance, in the \"html-keyboard-response\" plugin, the stimulus will always be shown in a <div> with the ID \"jspsych-html-keyboard-response-stimulus\". So you can create a CSS rule that is applied to all \"html-keyboard-response\" stimuli like this: # jspsych-html-keyboard-response-stimulus { color : white ; background-color : blue ; width : 100 px ; border : 4 px solid black ; } As another example, most jsPsych buttons have the class \"jspsych-btn\", so you can use this class to change the default button styling: . jspsych-btn { padding : 20 px 20 px ; font-size : 25 px ; border-color : black ; } You can also use the developer tools to change an element's CSS and immediately see the effect that the changes will have on the page. These changes are just temporary, so you will still need to use one of methods described above to add the CSS changes to your experiment. However, making changes in the developer tools is very useful for figuring out which CSS properties to change and which values to use. This area of the developer tools also shows what styles are currently applied to the element and where those style rules are coming from. There are a few things to be aware of while debugging problems with CSS. When there are conflicting CSS rules, some CSS rules will take precedence over others . For instance, inline CSS usually takes precedence over other CSS rules, and more specific CSS selectors usually take precedence over less specific ones. When there are conflicting CSS rules that have the same level of precedence, the last rule will override any earlier rules . For that reason it's important to add your own custom stylesheet after the default jspsych.css stylesheet. See this page about CSS precedence for more information. If one CSS style rule is overridden by another one, the rule that is overridden will appear in strikethrough text in the element's \"Styles\" section. Also, if you are using an incorrect CSS property name or an invalid value, then that will show up here as an error, indicated by both strikethrough text and a little yellow warning symbol.","title":"Controlling Visual Appearance"},{"location":"overview/style/#controlling-visual-appearance","text":"Your experiment's style and formatting comes from the CSS (cascading style sheet) rules that are stored in the jspsych.css file, and the browser's defaults. There are a few ways to change the style and formatting in your experiment. The method that you choose is partly a matter of personal preference. It might also depend on whether you want the style/formatting change(s) to apply to specific trials , to the whole experiment (HTML page), or across different experiments . This section discusses the different ways of incorporating CSS into your jsPsych experiment. You can also see this page about adding CSS to web pages to learn more.","title":"Controlling Visual Appearance"},{"location":"overview/style/#inline-css","text":"Whenever you're using a parameter that accepts an HTML-formatted string, you have the option to include inline CSS. Inline CSS is a way of adding style and formatting directly into a specific HTML element using its \"style\" attribute . This is a good option for when you want to make few and/or simple style changes to an HTML trial parameter. To change an element's style using inline CSS, you can set the element's \"style\" attribute to a string that contains the CSS parameters that you want to change, along with the values that you want to use. The syntax is \" <parameter-name> : <parameter-value> ;\". In the example below, the stimulus font size is set to 30px and the text color is set to red. These changes will only be applied to this stimulus text in this specific trial. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size:30px;color:red;\">hello world!</p>' } You can also use a dynamic parameter to combine inline CSS and trial-specific variables. This allows you to easily apply the same inline CSS to multiple trials. Here's an example using a dynamic stimulus parameter and timeline variables : var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var stim = '<p style=\"font-size:30px;font-weight:bold;\">' + jsPsych . timelineVariable ( 'text' ) + '</p>' ; return stim ; } } var trial_procedure = { timeline : [ trial ], timeline_variables : [ { text : 'Welcome' }, { text : 'to' }, { text : 'the' }, { text : 'experiment!' } ] }","title":"Inline CSS"},{"location":"overview/style/#adding-css-rules","text":"You may want to add a lot of different CSS changes to your experiment, re-use the same change(s) across lots of different trials, and/or separate the style/formatting from the HTML string. In these cases, you might find it useful to create CSS rules rather than using inline CSS. Creating CSS rules is a lot like using inline CSS, except that you also need to use a CSS selector . This is because your CSS rules aren't attached to any specific HTML element (unlike inline CSS), so you need to tell the browser which element(s) the style rules should apply to. The syntax is \"css-selector { <parameter-name> : <parameter-value> ; }\". In the example below, the CSS selector \"p\" tells the browser to apply the font size change to any text that is inside of a <p> element. p { font-size : 30 px ; } You can make more specific changes using CSS rules. The specificity will depend on the CSS selectors that are used. In addition to using the tag name (e.g. \"p\"), other common CSS selectors include the element's ID or class . If you are selecting an element using it's ID, then the CSS selector needs to have a # in front of the ID, e.g. \"#stimulus\". If you are selecting elements based on their class, then you need to include a . in front of the class, e.g. \".large-text\". In the example below, the \"#stimulus\" CSS selector means that the width change will only affect elements with the \"stimulus\" ID, and the \".large-text\" CSS selector means that the font size change will only affect elements that have the \"large-text\" class. # stimulus width : 300px ; } . large-text { font-size : 200 % ; } It is possible to create even more specific CSS selectors, for instance by combining tags, IDs, and/or classes. For example, let's say that you are showing feedback text to participants, and that this text is inside of a <p> tag. You could add the ID \"correct\" to the <p> element for correct response feedback, and the ID \"incorrect\" to the <p> element for incorrect response feedback. Then you can define separate styles for correct and incorrect feedback text like this: p # incorrect { color : red ; } p # correct { color : green ; } See this page about CSS selectors for a complete reference of CSS selector patterns and their meanings.","title":"Adding CSS rules"},{"location":"overview/style/#with-style-tags","text":"You can add CSS rules to your HTML page by putting them inside of <style> tags. These rules will be applied to your whole experiment . This method can be useful for making general changes to the way that your experiment looks. In the example below, the default font size is set to 25px throughout the experiment. This will overrule the default font size of 18px that is set in the jspsych.css file. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < style > . jspsych-display-element { font-size : 25 px ; } </ style > </ head >","title":"With style tags"},{"location":"overview/style/#with-a-stylesheet","text":"CSS rules can also be applied to your experiment with a link to an external CSS file. This is the same method that is usually used to apply the style from jspsych.css to an experiment. These rules will be applied to your whole experiment . You may find it useful to use a custom stylesheet when you want to re-use the same CSS rules across multiple experiments (HTML files). This example shows how to add a custom CSS file in addition to the styles provided in jspsych.css. In this example, the custom CSS file is called \"my_experiment_style.css\" and it is located in the same directory as your HTML file. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < link rel = \"stylesheet\" href = \"my_experiment_style.css\" > </ head > Below are the some example contents of an external CSS file, like the \"my_experiment_style.css\" from the example above. This CSS will (1) change the page background color to black, (2) change the default font to 25px and white, and (3) limit the width of the page content so that it can only take up to 80% of its normal width. body { background-color : black ; } . jspsych-display-element { font-size : 25 px ; color : white ; } . jspsych-content { max-width : 80 % ; } Note <style> tags are not used inside of an external CSS file.","title":"With a stylesheet"},{"location":"overview/style/#using-the-css_classes-trial-parameter","text":"CSS rules can also be applied in a trial-specific way using the css_classes parameter. This parameter will apply one or more class to the <div> element that holds all of the jsPsych page content during that specific trial. This way you can treat CSS styles just like any other trial parameter. You can use a static css_classes parameter value if you always want to apply the same CSS rules to the trial. In the 'fixation' example below, separating the style rules from the stimulus string makes the code a little bit 'cleaner', and this makes it easier to re-use the same style rules in other parts of the experiment. < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < style > . fixation { font-size : 90 px ; font-weight : bold ; color : gray ;} </ style > </ head > < script > var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 , css_classes : [ 'fixation' ] } // ... </ script > You may want the css_classes parameter to vary across trials. If so, you can turn it into a dynamic parameter or use timeline variables (see examples below). One thing to note about the css_classes parameter is that it only adds the class(es) to the jspsych-content <div> element, which is the \"parent\" element that contains all of the experiment content. Often you'll want your CSS rules to be applied to other elements inside of this jspsych-content div. Sometimes your CSS rules will be \"inherited\" by all of the other jsPsych content inside of this parent <div>. For instance, in the fixation example above, the CSS rules that change the font size, weight and color are applied to the parent <div> and automatically passed on to the stimulus text through inheritance. There are two reasons why a CSS rule like the one above for fixation may not work the way you expect: Not all CSS properties are inherited from the parent element. When a CSS property is inherited from the parent element, it will affect all elements in a given trial. In these cases, you can change your CSS selector to make it more specific: add a space after class name, then add more CSS selectors to select the specific element(s) that you want to change. Tip To find out this more specific CSS selector, you can right-click on the element and select Inspect . In the inspector window, right-click on the property corresponding to the element and copy the selector. You might need to increase the trial's trial_duration to give yourself enough time to inspect the elements on the page. See more tips for working with CSS below. In the example below, the CSS selector .left-align #stimulus selects the element with the ID \"stimulus\" that is inside of an element with the class \"left-align\". < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < style > . left-align # stimulus { text-align : left ; width : 600 px ;} . right-align # stimulus { text-align : right ; width : 600 px ;} </ style > </ head > < script > var trial_procedure = { timeline : [{ type : jsPsychHtmlKeyboardResponse , stimulus : '<p id=\"stimulus\">This is the stimulus.</p>' , prompt : '<p>This text will not be affected by the CSS classes ' + 'because it does not have the \"stimulus\" ID.</p>' , css_classes : jsPsych . timelineVariable ( 'css_classes' ) }], timeline_variables : [ { css_classes : [ 'left-align' ]}, { css_classes : [ 'right-align' ]} ] } // ... </ script > It's also possible to pass multiple class names to the css_classes parameter. This can be useful for creating conditions that involve crossing different style-related factors. This example shows you to combine two text alignment and two text color factors to produce four different stimulus conditions: < head > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link rel = \"stylesheet\" href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" > < style > . left-align # stimulus { text-align : left ; width : 600 px ;} . right-align # stimulus { text-align : right ; width : 600 px ;} . teal # stimulus { color : teal ;} . purple # stimulus { color : purple ;} </ style > </ head > < script > var trial_procedure = { timeline : [{ type : jsPsychHtmlKeyboardResponse , stimulus : '<p id=\"stimulus\">This is the stimulus.</p>' , prompt : '<p>This text will not be affected by the CSS classes ' + 'because it does not have the \"stimulus\" ID.</p>' , css_classes : jsPsych . timelineVariable ( 'css_classes' ), data : { condition : jsPsych . timelineVariable ( 'condition' )} }], timeline_variables : [ { css_classes : [ 'left-align' , 'teal' ], condition : 'left-teal' }, { css_classes : [ 'right-align' , 'teal' ], condition : 'right-teal' }, { css_classes : [ 'left-align' , 'purple' ], condition : 'left-purple' }, { css_classes : [ 'right-align' , 'purple' ], condition : 'right-purple' } ] } // ... </ script > See the \"css-classes-parameter.html\" file in jsPsych's examples subfolder for more explanation and examples.","title":"Using the css_classes trial parameter"},{"location":"overview/style/#tips-for-working-with-css","text":"Your browser's developer tools contain very useful features for exploring and debugging your experiment's style and formatting. Open your browser's developer tools and click on the Element Inspector button or go to the Elements tab. Once you have selected an element on the page, you can see all of the information that can be used to select it, including: tag name, e.g., \"div\", \"p\", \"img\", \"button\" ID, if it has one class(es), if it has any You can then use this information to create a CSS selector to modify that element's style. As you can see, jsPsych adds its own IDs and classes to many elements. You can use the developer tools to determine what IDs and classes already exist for the elements that you want to modify, as you may can often just use these instead of adding your own. For instance, in the \"html-keyboard-response\" plugin, the stimulus will always be shown in a <div> with the ID \"jspsych-html-keyboard-response-stimulus\". So you can create a CSS rule that is applied to all \"html-keyboard-response\" stimuli like this: # jspsych-html-keyboard-response-stimulus { color : white ; background-color : blue ; width : 100 px ; border : 4 px solid black ; } As another example, most jsPsych buttons have the class \"jspsych-btn\", so you can use this class to change the default button styling: . jspsych-btn { padding : 20 px 20 px ; font-size : 25 px ; border-color : black ; } You can also use the developer tools to change an element's CSS and immediately see the effect that the changes will have on the page. These changes are just temporary, so you will still need to use one of methods described above to add the CSS changes to your experiment. However, making changes in the developer tools is very useful for figuring out which CSS properties to change and which values to use. This area of the developer tools also shows what styles are currently applied to the element and where those style rules are coming from. There are a few things to be aware of while debugging problems with CSS. When there are conflicting CSS rules, some CSS rules will take precedence over others . For instance, inline CSS usually takes precedence over other CSS rules, and more specific CSS selectors usually take precedence over less specific ones. When there are conflicting CSS rules that have the same level of precedence, the last rule will override any earlier rules . For that reason it's important to add your own custom stylesheet after the default jspsych.css stylesheet. See this page about CSS precedence for more information. If one CSS style rule is overridden by another one, the rule that is overridden will appear in strikethrough text in the element's \"Styles\" section. Also, if you are using an incorrect CSS property name or an invalid value, then that will show up here as an error, indicated by both strikethrough text and a little yellow warning symbol.","title":"Tips for working with CSS"},{"location":"overview/timeline/","text":"Creating an Experiment: The Timeline \u00b6 To create an experiment using jsPsych, you need to specify a timeline that describes the structure of the experiment. The timeline is an ordered set of trials. You must create the timeline before launching the experiment. Most of the code you will write for an experiment will be code to create the timeline. This page walks through the creation of timelines, including very basic examples and more advanced features. A single trial \u00b6 To create a trial, you need to create an object that describes the trial. The most important feature of this object is the type parameter. This tells jsPsych which plugin to use to run the trial. For example, if you want to use the html-keyboard-response plugin to display a short message, the trial object would look like this: var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Welcome to the experiment.' } The parameters for this object (e.g., stimulus ) will depend on the plugin that you choose. Each plugin defines the set of parameters that are needed to run a trial with that plugin. Visit the documentation for a plugin to learn about the parameters that you can use with that plugin. To create a timeline with the single trial and run the experiment, just embed the trial object in an array. A timeline can simply be an array of trials. var timeline = [ trial ]; jsPsych . run ( timeline ); To create and run a simple experiment like this complete the hello world tutorial . Multiple trials \u00b6 Scaling up to multiple trials is straightforward. Create an object for each trial, and add each object to the timeline array. // with lots of trials, it might be easier to add the trials // to the timeline array as they are defined. var timeline = []; var trial_1 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 1.' } timeline . push ( trial_1 ); var trial_2 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 2.' } timeline . push ( trial_2 ); var trial_3 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 3.' } timeline . push ( trial_3 ); Nested timelines \u00b6 Each object on the timeline can also have it's own timeline. This is useful for many reasons. One is that it allows you to define common parameters across trials once and have them apply to all the trials on the nested timeline. The example below creates a series of trials using the image-keyboard-response plugin , where the only thing that changes from trial-to-trial is the image file being displayed on the screen. var judgment_trials = { type : jsPsychImageKeyboardResponse , prompt : '<p>Press a number 1-7 to indicate how unusual the image is.</p>' , choices : [ '1' , '2' , '3' , '4' , '5' , '6' , '7' ], timeline : [ { stimulus : 'image1.png' }, { stimulus : 'image2.png' }, { stimulus : 'image3.png' } ] } In the above code, the type , prompt , and choices parameters are automatically applied to all of the objects in the timeline array. This creates three trials with the same type , prompt , and choices parameters, but different values for the stimulus parameter. You can also override the values by declaring a new value in the timeline array. In the example below, the second trial will display a different prompt message. var judgment_trials = { type : jsPsychImageKeyboardResponse , prompt : '<p>Press a number 1-7 to indicate how unusual the image is.</p>' , choices : [ '1' , '2' , '3' , '4' , '5' , '6' , '7' ], timeline : [ { stimulus : 'image1.png' }, { stimulus : 'image2.png' , prompt : '<p>Press 1 for this trial.</p>' }, { stimulus : 'image3.png' } ] } Timelines can be nested any number of times. Timeline variables \u00b6 A common pattern in behavioral experiments is to repeat the same procedure/task many times with slightly different parameters. A procedure might be a single trial, but it also might be a series of trials. For example, a task might involve a fixation cross appearing, followed by a blank screen, followed by an image for a short duration, followed by a prompt and a text box to report on some aspect of the image. One shortcut to implement this pattern is with the nested timeline approach described in the previous section, but this only works if all the trials use the same plugin type. Timeline variables are a more general solution. With timeline variables you define the procedure once (as a timeline) and specify a set of parameters and their values for each iteration through the timeline. What follows is an example of how to use timeline variables. The simple reaction time tutorial also explains how to use timeline variables. Suppose we want to create an experiment where people see a set of faces. Perhaps this is a memory experiment and this is the phase of the experiment where the faces are being presented for the first time. In between each face, a fixation cross is displayed on the screen. Without timeline variables, we would need to add many trials to the timeline, alternating between trials showing the fixation cross and trials showing the face and name. This could be done efficiently using a loop or function to create the timeline, but timeline variables make it even easier - as well as adding extra features like sampling and randomization. Here's a basic version of the task with timeline variables. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'face' ), choices : \"NO_KEYS\" , trial_duration : 2500 } ], timeline_variables : [ { face : 'person-1.jpg' }, { face : 'person-2.jpg' }, { face : 'person-3.jpg' }, { face : 'person-4.jpg' } ] } In the above version, there are four separate trials defined in the timeline_variables parameter. Each trial has a variable face and a variable name . The timeline defines a procedure of showing a fixation cross for 500ms followed by the face and name for 2500ms. This procedure will repeat four times, with the first trial showing 'person-1.jpg' , the second 'person-2.jpg' , and so on. The variables are referenced within the procedure by calling the jsPsych.timelineVariable() method and passing in the name of the variable. What if we wanted to add an additional step to the task where the name is displayed prior to the face appearing? (Maybe this is one condition of an experiment investigating whether the order of name-face or face-name affects retention.) We can add another variable to our list that gives the name associated with each image. Then we can add another trial to our timeline to show the name. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychHtmlKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'name' ), trial_duration : 1000 , choices : \"NO_KEYS\" }, { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'face' ), choices : \"NO_KEYS\" , trial_duration : 1000 } ], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ] } Using in a function \u00b6 Continung the example from the previous section, what if we wanted to show the name with the face, combining the two variables together? To do this, we can use a dynamic parameter (a function) to create an HTML-string that uses both variables in a single parameter. The value of the stimulus parameter will be a function that returns an HTML string that contains both the image and the name. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychHtmlKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'name' ), trial_duration : 1000 , choices : \"NO_KEYS\" }, { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ var html = ` <img src=\" ${ jsPsych . timelineVariable ( 'face' ) } \"> <p> ${ jsPsych . timelineVariable ( 'name' ) } </p>` ; return html ; }, choices : \"NO_KEYS\" , trial_duration : 2500 } ], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ] } Random orders of trials \u00b6 If we want to randomize the order of the trials, we can set randomize_order to true . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true } Sampling methods \u00b6 There are also sampling methods that can be used to select a set of trials from the timeline_variables. Sampling is declared by creating a sample parameter. The sample parameter is given an object of arguments. The type parameter in this object controls the type of sampling that is done. Valid values for type are \"with-replacement\" : Sample size items from the timeline variables with the possibility of choosing the same item multiple time. \"without-replacement\" : Sample size items from timeline variables, with each item being selected a maximum of 1 time. \"fixed-repetitons\" : Repeat each item in the timeline variables size times, in a random order. Unlike using the repetitons parameter, this method allows for consecutive trials to use the same timeline variable set. \"alternate-groups\" : Sample in an alternating order based on a declared group membership. Groups are defined by the groups parameter. This parameter takes an array of arrays, where each inner array is a group and the items in the inner array are the indices of the timeline variables in the timeline_variables array that belong to that group. \"custom\" : Write a function that returns a custom order of the timeline variables. Sampling with replacement \u00b6 This sample parameter will create 10 repetitions, sampling with replacement. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'with-replacement' , size : 10 } } Sampling with replacement, unequal probabilities \u00b6 This sample parameter will make the \"Alex\" trial three times as likely to be sampled as the others. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'with-replacement' , size : 10 , weights : [ 3 , 1 , 1 , 1 ] } } Sampling without replacement \u00b6 This sample parameter will pick three of the four possible trials to run at random. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'without-replacement' , size : 3 } } Repeating each trial a fixed number of times in a random order \u00b6 This sample parameter will create 3 repetitions of each trial, for a total of 12 trials, with a random order. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'fixed-repetitions' , size : 3 } } Alternating groups \u00b6 This sample parameter puts the \"Alex\" and \"Chad\" trials in group 1 and the \"Beth\" and \"Dave\" trials in group 2. The resulting sample of trials will follow the pattern group 1 -> group 2 -> group 1 -> group 2 . Each trial will be selected only one time. If you wanted group 2 to sometimes be first, you could set randomize_group_order: true . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'alternate-groups' , groups : [[ 0 , 2 ],[ 1 , 3 ]], randomize_group_order : false } } Custom sampling function \u00b6 Any sampling method can be implemented using the custom type sampler. The order of trials will be determined by running the function supplied as fn . The function has a single parameter, t , which is an array of integers from 0 to n-1 , where n is the number of trials in the timeline_variables array. The function must return an array that specifies the order of the trials, e.g., returning [3,3,2,2,1,1,0,0] would result in the order Dave -> Dave -> Chad -> Chad -> Beth -> Beth -> Alex -> Alex . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'custom' , fn : function ( t ){ return t . reverse (); // show the trials in the reverse order } } } Repeating a set of trials \u00b6 To repeat a timeline multiple times, you can create an object (node) that contains a timeline , which is the timeline array to repeat, and repetitions , which is the number of times to repeat that timeline. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will be repeated twice.' } var node = { timeline : [ trial ], repetitions : 2 } The repetitions parameter can be used alongside other node parameters, such as timeline variables, loop functions, and/or conditional functions. If you are using timeline_variables and randomize_order is true , then the order of the timeline variables will re-randomize before every repetition. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true , repetitions : 3 } Looping timelines \u00b6 Any timeline can be looped using the loop_function option. The loop function must be a function that evaluates to true if the timeline should repeat, and false if the timeline should end. It receives a single parameter, named data by convention. This parameter will be the DataCollection object with all of the data from the trials executed in the last iteration of the timeline. The loop function will be evaluated after the timeline is completed. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial is in a loop. Press R to repeat this trial, or C to continue.' } var loop_node = { timeline : [ trial ], loop_function : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . values ()[ 0 ]. response , 'r' )){ return true ; } else { return false ; } } } Conditional timelines \u00b6 A timeline can be skipped or not based on the evaluation of the conditional_function option. If the conditional function evaluates to true , the timeline will execute normally. If the conditional function evaluates to false then the timeline will be skipped. The conditional function is evaluated whenever jsPsych is about to run the first trial on the timeline. var jsPsych = initJsPsych (); var pre_if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'The next trial is in a conditional statement. Press S to skip it, or V to view it.' } var if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'You chose to view the trial. Press any key to continue.' } var if_node = { timeline : [ if_trial ], conditional_function : function (){ // get the data from the previous trial, // and check which key was pressed var data = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]; if ( jsPsych . pluginAPI . compareKeys ( data . response , 's' )){ return false ; } else { return true ; } } } var after_if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is the trial after the conditional.' } jsPsych . run ([ pre_if_trial , if_node , after_if_trial ]); Timeline start and finish functions \u00b6 You can run a custom function at the start and end of a timeline node using the on_timeline_start and on_timeline_finish callback function parameters. These are functions that will run when the timeline starts and ends, respectively. var procedure = { timeline : [ trial_1 , trial_2 ], on_timeline_start : function () { console . log ( 'The trial procedure just started.' ) }, on_timeline_finish : function () { console . log ( 'The trial procedure just finished.' ) } } This works the same way with timeline variables. The on_timeline_start and on_timeline_finish functions will run when timeline variables trials start and end, respectively. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true , on_timeline_start : function () { console . log ( 'First trial is starting.' ) }, on_timeline_finish : function () { console . log ( 'Last trial just finished.' ) } } When the repetititons option is used (and is greater than 1), these functions will run once per repetition of the timeline. var repetition_count = 0 ; var procedure = { timeline : [ trial_1 , trial_2 ], repetitions : 3 , on_timeline_start : function () { repetition_count ++ ; console . log ( 'Repetition number ' , repetition_count , ' has just started.' ); }, on_timeline_finish : function () { console . log ( 'Repetition number ' , repetition_count , ' has just finished.' ) } }","title":"Creating an Experiment: The Timeline"},{"location":"overview/timeline/#creating-an-experiment-the-timeline","text":"To create an experiment using jsPsych, you need to specify a timeline that describes the structure of the experiment. The timeline is an ordered set of trials. You must create the timeline before launching the experiment. Most of the code you will write for an experiment will be code to create the timeline. This page walks through the creation of timelines, including very basic examples and more advanced features.","title":"Creating an Experiment: The Timeline"},{"location":"overview/timeline/#a-single-trial","text":"To create a trial, you need to create an object that describes the trial. The most important feature of this object is the type parameter. This tells jsPsych which plugin to use to run the trial. For example, if you want to use the html-keyboard-response plugin to display a short message, the trial object would look like this: var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Welcome to the experiment.' } The parameters for this object (e.g., stimulus ) will depend on the plugin that you choose. Each plugin defines the set of parameters that are needed to run a trial with that plugin. Visit the documentation for a plugin to learn about the parameters that you can use with that plugin. To create a timeline with the single trial and run the experiment, just embed the trial object in an array. A timeline can simply be an array of trials. var timeline = [ trial ]; jsPsych . run ( timeline ); To create and run a simple experiment like this complete the hello world tutorial .","title":"A single trial"},{"location":"overview/timeline/#multiple-trials","text":"Scaling up to multiple trials is straightforward. Create an object for each trial, and add each object to the timeline array. // with lots of trials, it might be easier to add the trials // to the timeline array as they are defined. var timeline = []; var trial_1 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 1.' } timeline . push ( trial_1 ); var trial_2 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 2.' } timeline . push ( trial_2 ); var trial_3 = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is trial 3.' } timeline . push ( trial_3 );","title":"Multiple trials"},{"location":"overview/timeline/#nested-timelines","text":"Each object on the timeline can also have it's own timeline. This is useful for many reasons. One is that it allows you to define common parameters across trials once and have them apply to all the trials on the nested timeline. The example below creates a series of trials using the image-keyboard-response plugin , where the only thing that changes from trial-to-trial is the image file being displayed on the screen. var judgment_trials = { type : jsPsychImageKeyboardResponse , prompt : '<p>Press a number 1-7 to indicate how unusual the image is.</p>' , choices : [ '1' , '2' , '3' , '4' , '5' , '6' , '7' ], timeline : [ { stimulus : 'image1.png' }, { stimulus : 'image2.png' }, { stimulus : 'image3.png' } ] } In the above code, the type , prompt , and choices parameters are automatically applied to all of the objects in the timeline array. This creates three trials with the same type , prompt , and choices parameters, but different values for the stimulus parameter. You can also override the values by declaring a new value in the timeline array. In the example below, the second trial will display a different prompt message. var judgment_trials = { type : jsPsychImageKeyboardResponse , prompt : '<p>Press a number 1-7 to indicate how unusual the image is.</p>' , choices : [ '1' , '2' , '3' , '4' , '5' , '6' , '7' ], timeline : [ { stimulus : 'image1.png' }, { stimulus : 'image2.png' , prompt : '<p>Press 1 for this trial.</p>' }, { stimulus : 'image3.png' } ] } Timelines can be nested any number of times.","title":"Nested timelines"},{"location":"overview/timeline/#timeline-variables","text":"A common pattern in behavioral experiments is to repeat the same procedure/task many times with slightly different parameters. A procedure might be a single trial, but it also might be a series of trials. For example, a task might involve a fixation cross appearing, followed by a blank screen, followed by an image for a short duration, followed by a prompt and a text box to report on some aspect of the image. One shortcut to implement this pattern is with the nested timeline approach described in the previous section, but this only works if all the trials use the same plugin type. Timeline variables are a more general solution. With timeline variables you define the procedure once (as a timeline) and specify a set of parameters and their values for each iteration through the timeline. What follows is an example of how to use timeline variables. The simple reaction time tutorial also explains how to use timeline variables. Suppose we want to create an experiment where people see a set of faces. Perhaps this is a memory experiment and this is the phase of the experiment where the faces are being presented for the first time. In between each face, a fixation cross is displayed on the screen. Without timeline variables, we would need to add many trials to the timeline, alternating between trials showing the fixation cross and trials showing the face and name. This could be done efficiently using a loop or function to create the timeline, but timeline variables make it even easier - as well as adding extra features like sampling and randomization. Here's a basic version of the task with timeline variables. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'face' ), choices : \"NO_KEYS\" , trial_duration : 2500 } ], timeline_variables : [ { face : 'person-1.jpg' }, { face : 'person-2.jpg' }, { face : 'person-3.jpg' }, { face : 'person-4.jpg' } ] } In the above version, there are four separate trials defined in the timeline_variables parameter. Each trial has a variable face and a variable name . The timeline defines a procedure of showing a fixation cross for 500ms followed by the face and name for 2500ms. This procedure will repeat four times, with the first trial showing 'person-1.jpg' , the second 'person-2.jpg' , and so on. The variables are referenced within the procedure by calling the jsPsych.timelineVariable() method and passing in the name of the variable. What if we wanted to add an additional step to the task where the name is displayed prior to the face appearing? (Maybe this is one condition of an experiment investigating whether the order of name-face or face-name affects retention.) We can add another variable to our list that gives the name associated with each image. Then we can add another trial to our timeline to show the name. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychHtmlKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'name' ), trial_duration : 1000 , choices : \"NO_KEYS\" }, { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'face' ), choices : \"NO_KEYS\" , trial_duration : 1000 } ], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ] }","title":"Timeline variables"},{"location":"overview/timeline/#using-in-a-function","text":"Continung the example from the previous section, what if we wanted to show the name with the face, combining the two variables together? To do this, we can use a dynamic parameter (a function) to create an HTML-string that uses both variables in a single parameter. The value of the stimulus parameter will be a function that returns an HTML string that contains both the image and the name. var face_name_procedure = { timeline : [ { type : jsPsychHtmlKeyboardResponse , stimulus : '+' , choices : \"NO_KEYS\" , trial_duration : 500 }, { type : jsPsychHtmlKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'name' ), trial_duration : 1000 , choices : \"NO_KEYS\" }, { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ var html = ` <img src=\" ${ jsPsych . timelineVariable ( 'face' ) } \"> <p> ${ jsPsych . timelineVariable ( 'name' ) } </p>` ; return html ; }, choices : \"NO_KEYS\" , trial_duration : 2500 } ], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ] }","title":"Using in a function"},{"location":"overview/timeline/#random-orders-of-trials","text":"If we want to randomize the order of the trials, we can set randomize_order to true . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true }","title":"Random orders of trials"},{"location":"overview/timeline/#sampling-methods","text":"There are also sampling methods that can be used to select a set of trials from the timeline_variables. Sampling is declared by creating a sample parameter. The sample parameter is given an object of arguments. The type parameter in this object controls the type of sampling that is done. Valid values for type are \"with-replacement\" : Sample size items from the timeline variables with the possibility of choosing the same item multiple time. \"without-replacement\" : Sample size items from timeline variables, with each item being selected a maximum of 1 time. \"fixed-repetitons\" : Repeat each item in the timeline variables size times, in a random order. Unlike using the repetitons parameter, this method allows for consecutive trials to use the same timeline variable set. \"alternate-groups\" : Sample in an alternating order based on a declared group membership. Groups are defined by the groups parameter. This parameter takes an array of arrays, where each inner array is a group and the items in the inner array are the indices of the timeline variables in the timeline_variables array that belong to that group. \"custom\" : Write a function that returns a custom order of the timeline variables.","title":"Sampling methods"},{"location":"overview/timeline/#sampling-with-replacement","text":"This sample parameter will create 10 repetitions, sampling with replacement. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'with-replacement' , size : 10 } }","title":"Sampling with replacement"},{"location":"overview/timeline/#sampling-with-replacement-unequal-probabilities","text":"This sample parameter will make the \"Alex\" trial three times as likely to be sampled as the others. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'with-replacement' , size : 10 , weights : [ 3 , 1 , 1 , 1 ] } }","title":"Sampling with replacement, unequal probabilities"},{"location":"overview/timeline/#sampling-without-replacement","text":"This sample parameter will pick three of the four possible trials to run at random. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'without-replacement' , size : 3 } }","title":"Sampling without replacement"},{"location":"overview/timeline/#repeating-each-trial-a-fixed-number-of-times-in-a-random-order","text":"This sample parameter will create 3 repetitions of each trial, for a total of 12 trials, with a random order. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'fixed-repetitions' , size : 3 } }","title":"Repeating each trial a fixed number of times in a random order"},{"location":"overview/timeline/#alternating-groups","text":"This sample parameter puts the \"Alex\" and \"Chad\" trials in group 1 and the \"Beth\" and \"Dave\" trials in group 2. The resulting sample of trials will follow the pattern group 1 -> group 2 -> group 1 -> group 2 . Each trial will be selected only one time. If you wanted group 2 to sometimes be first, you could set randomize_group_order: true . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'alternate-groups' , groups : [[ 0 , 2 ],[ 1 , 3 ]], randomize_group_order : false } }","title":"Alternating groups"},{"location":"overview/timeline/#custom-sampling-function","text":"Any sampling method can be implemented using the custom type sampler. The order of trials will be determined by running the function supplied as fn . The function has a single parameter, t , which is an array of integers from 0 to n-1 , where n is the number of trials in the timeline_variables array. The function must return an array that specifies the order of the trials, e.g., returning [3,3,2,2,1,1,0,0] would result in the order Dave -> Dave -> Chad -> Chad -> Beth -> Beth -> Alex -> Alex . var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], sample : { type : 'custom' , fn : function ( t ){ return t . reverse (); // show the trials in the reverse order } } }","title":"Custom sampling function"},{"location":"overview/timeline/#repeating-a-set-of-trials","text":"To repeat a timeline multiple times, you can create an object (node) that contains a timeline , which is the timeline array to repeat, and repetitions , which is the number of times to repeat that timeline. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial will be repeated twice.' } var node = { timeline : [ trial ], repetitions : 2 } The repetitions parameter can be used alongside other node parameters, such as timeline variables, loop functions, and/or conditional functions. If you are using timeline_variables and randomize_order is true , then the order of the timeline variables will re-randomize before every repetition. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true , repetitions : 3 }","title":"Repeating a set of trials"},{"location":"overview/timeline/#looping-timelines","text":"Any timeline can be looped using the loop_function option. The loop function must be a function that evaluates to true if the timeline should repeat, and false if the timeline should end. It receives a single parameter, named data by convention. This parameter will be the DataCollection object with all of the data from the trials executed in the last iteration of the timeline. The loop function will be evaluated after the timeline is completed. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This trial is in a loop. Press R to repeat this trial, or C to continue.' } var loop_node = { timeline : [ trial ], loop_function : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . values ()[ 0 ]. response , 'r' )){ return true ; } else { return false ; } } }","title":"Looping timelines"},{"location":"overview/timeline/#conditional-timelines","text":"A timeline can be skipped or not based on the evaluation of the conditional_function option. If the conditional function evaluates to true , the timeline will execute normally. If the conditional function evaluates to false then the timeline will be skipped. The conditional function is evaluated whenever jsPsych is about to run the first trial on the timeline. var jsPsych = initJsPsych (); var pre_if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'The next trial is in a conditional statement. Press S to skip it, or V to view it.' } var if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'You chose to view the trial. Press any key to continue.' } var if_node = { timeline : [ if_trial ], conditional_function : function (){ // get the data from the previous trial, // and check which key was pressed var data = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]; if ( jsPsych . pluginAPI . compareKeys ( data . response , 's' )){ return false ; } else { return true ; } } } var after_if_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is the trial after the conditional.' } jsPsych . run ([ pre_if_trial , if_node , after_if_trial ]);","title":"Conditional timelines"},{"location":"overview/timeline/#timeline-start-and-finish-functions","text":"You can run a custom function at the start and end of a timeline node using the on_timeline_start and on_timeline_finish callback function parameters. These are functions that will run when the timeline starts and ends, respectively. var procedure = { timeline : [ trial_1 , trial_2 ], on_timeline_start : function () { console . log ( 'The trial procedure just started.' ) }, on_timeline_finish : function () { console . log ( 'The trial procedure just finished.' ) } } This works the same way with timeline variables. The on_timeline_start and on_timeline_finish functions will run when timeline variables trials start and end, respectively. var face_name_procedure = { timeline : [...], timeline_variables : [ { face : 'person-1.jpg' , name : 'Alex' }, { face : 'person-2.jpg' , name : 'Beth' }, { face : 'person-3.jpg' , name : 'Chad' }, { face : 'person-4.jpg' , name : 'Dave' } ], randomize_order : true , on_timeline_start : function () { console . log ( 'First trial is starting.' ) }, on_timeline_finish : function () { console . log ( 'Last trial just finished.' ) } } When the repetititons option is used (and is greater than 1), these functions will run once per repetition of the timeline. var repetition_count = 0 ; var procedure = { timeline : [ trial_1 , trial_2 ], repetitions : 3 , on_timeline_start : function () { repetition_count ++ ; console . log ( 'Repetition number ' , repetition_count , ' has just started.' ); }, on_timeline_finish : function () { console . log ( 'Repetition number ' , repetition_count , ' has just finished.' ) } }","title":"Timeline start and finish functions"},{"location":"overview/timing-accuracy/","text":"Timing accuracy \u00b6 Wondering if jsPsych can be used for research that depends on accurate display times or response time measurement? For most purposes, the answer is yes. Display timing is somewhat less accurate in JavaScript than in standard experimental software that runs on a desktop. Desktop software can have closer integration with the graphics devices of the machine than JavaScript currently permits. If a one or two frame (17-33ms) difference in display timing matters for your experiment, then you'll want to be careful with JavaScript-based experiments. It is possible to achieve this level of control in JavaScript, but it often requires code that is more tailored to your experiment and some restrictions about which browsers can be used to run the experiment. Tip If you are hoping to run an experiment with the best timing that jsPsych can offer, we currently recommend using the jspsych-psychophysics plugin developed by Daiichiro Kuroki . Kuroki, D. (2021). A new jsPsych plugin for psychophysics, providing accurate display duration and stimulus onset asynchrony. Behavior Research Methods , 53 , 301\u2013310. https://doi.org/10.3758/s13428-020-01445-w Response time measurements in jsPsych (and JavaScript in general) are comparable to those taken in standard lab software like Psychophysics Toolbox and E-Prime. Response times measured in JavaScript tend to be a little bit longer (10-40ms), but have similar variance. References \u00b6 See the following papers for extensive work on display and response timing in browser-based experiments. Note that browsers are updating frequently and the JavaScript language specification is also changing. It's possible that the results from these papers do not apply to current versions of web browsers. Future updates to JavaScript APIs will likely improve the ability of online experiments to provide more accurate display timing and response time measurement. Bridges, D., Pitiot, A., MacAskill, M. R., & Peirce, J. W. (2020). The timing mega-study: Comparing a range of experiment generators, both lab-based and online. PeerJ, 8 , e9414. Anwyl-Irvine, A., Dalmaijer, E. S., Hodges, N., & Evershed, J. K. (2020). Realistic precision and accuracy of online experiment platforms, web browsers, and devices. Behavior Research Methods, 53, 1-19. Pronk, T., Wiers, R. W., Molenkamp, B., & Murre, J. (2020). Mental chronometry in the pocket? Timing accuracy of web applications on touchscreen and keyboard devices. Behavior Research Methods, 52 (3), 1371-1382. Pinet, S., Zielinski, C., Math\u00f4t, S. et al. (2017). Measuring sequences of keystrokes with jsPsych: Reliability of response times and interkeystroke intervals. Behavior Research Methods , 49 (3), 1177-1178. de Leeuw, J. R., & Motz, B. A. (2016). Psychophysics in a Web browser? Comparing response times collected with JavaScript and Psychophysics Toolbox in a visual search task. Behavior Research Methods , 48 (1), 1-12. Hilbig, B. E. (2016). Reaction time effects in lab- versus web-based research: Experimental evidence. Behavior Research Methods , 48 (4), 1718-1724. Reimers, S., & Stewart, N. (2015). Presentation and response time accuracy in Adobe Flash and HTML5/JavaScript Web experiments. Behavior Research Methods , 47 (2), 309-327.","title":"Timing Accuracy"},{"location":"overview/timing-accuracy/#timing-accuracy","text":"Wondering if jsPsych can be used for research that depends on accurate display times or response time measurement? For most purposes, the answer is yes. Display timing is somewhat less accurate in JavaScript than in standard experimental software that runs on a desktop. Desktop software can have closer integration with the graphics devices of the machine than JavaScript currently permits. If a one or two frame (17-33ms) difference in display timing matters for your experiment, then you'll want to be careful with JavaScript-based experiments. It is possible to achieve this level of control in JavaScript, but it often requires code that is more tailored to your experiment and some restrictions about which browsers can be used to run the experiment. Tip If you are hoping to run an experiment with the best timing that jsPsych can offer, we currently recommend using the jspsych-psychophysics plugin developed by Daiichiro Kuroki . Kuroki, D. (2021). A new jsPsych plugin for psychophysics, providing accurate display duration and stimulus onset asynchrony. Behavior Research Methods , 53 , 301\u2013310. https://doi.org/10.3758/s13428-020-01445-w Response time measurements in jsPsych (and JavaScript in general) are comparable to those taken in standard lab software like Psychophysics Toolbox and E-Prime. Response times measured in JavaScript tend to be a little bit longer (10-40ms), but have similar variance.","title":"Timing accuracy"},{"location":"overview/timing-accuracy/#references","text":"See the following papers for extensive work on display and response timing in browser-based experiments. Note that browsers are updating frequently and the JavaScript language specification is also changing. It's possible that the results from these papers do not apply to current versions of web browsers. Future updates to JavaScript APIs will likely improve the ability of online experiments to provide more accurate display timing and response time measurement. Bridges, D., Pitiot, A., MacAskill, M. R., & Peirce, J. W. (2020). The timing mega-study: Comparing a range of experiment generators, both lab-based and online. PeerJ, 8 , e9414. Anwyl-Irvine, A., Dalmaijer, E. S., Hodges, N., & Evershed, J. K. (2020). Realistic precision and accuracy of online experiment platforms, web browsers, and devices. Behavior Research Methods, 53, 1-19. Pronk, T., Wiers, R. W., Molenkamp, B., & Murre, J. (2020). Mental chronometry in the pocket? Timing accuracy of web applications on touchscreen and keyboard devices. Behavior Research Methods, 52 (3), 1371-1382. Pinet, S., Zielinski, C., Math\u00f4t, S. et al. (2017). Measuring sequences of keystrokes with jsPsych: Reliability of response times and interkeystroke intervals. Behavior Research Methods , 49 (3), 1177-1178. de Leeuw, J. R., & Motz, B. A. (2016). Psychophysics in a Web browser? Comparing response times collected with JavaScript and Psychophysics Toolbox in a visual search task. Behavior Research Methods , 48 (1), 1-12. Hilbig, B. E. (2016). Reaction time effects in lab- versus web-based research: Experimental evidence. Behavior Research Methods , 48 (4), 1718-1724. Reimers, S., & Stewart, N. (2015). Presentation and response time accuracy in Adobe Flash and HTML5/JavaScript Web experiments. Behavior Research Methods , 47 (2), 309-327.","title":"References"},{"location":"plugins/animation/","text":"animation \u00b6 Current version: 1.1.3. See version history . This plugin displays a sequence of images at a fixed frame rate. The sequence can be looped a specified number of times. The participant is free to respond at any point during the animation, and the time of the response is recorded. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of the array is a path to an image file. frame_time numeric 250 How long to display each image in milliseconds. frame_isi numeric 0 If greater than 0, then a gap will be shown between each image in the sequence. This parameter specifies the length of the gap in milliseconds. sequence_reps numeric 1 How many times to show the entire sequence. There will be no gap (other than the gap specified by frame_isi ) between repetitions. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key(s) to press). render_on_canvas boolean true If true, the images will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive images in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value animation_sequence array An array, where each element is an object that represents a stimulus in the animation sequence. Each object has a stimulus property, which is the image that was displayed, and a time property, which is the time in ms, measured from when the sequence began, that the stimulus was displayed. The array will be encoded in JSON format when data is saved using either the .json() or .csv() functions. response array An array, where each element is an object representing a response given by the participant. Each object has a stimulus property, indicating which image was displayed when the key was pressed, an rt property, indicating the time of the key press relative to the start of the animation, and a key_press property, indicating which key was pressed. The array will be encoded in JSON format when data is saved using either the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-animation@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-animation.js\" >< /script> Using NPM: npm install @jspsych/plugin-animation import animation from '@jspsych/plugin-animation' ; Examples \u00b6 Displaying a single sequence multiple times Code Demo var animation_sequence = [ \"img/happy_face_1.jpg\" , \"img/happy_face_2.jpg\" , \"img/happy_face_3.jpg\" , \"img/happy_face_4.jpg\" ]; var animation_trial = { type : jsPsychAnimation , stimuli : animation_sequence , sequence_reps : 3 , frame_time : 300 , prompt : '<p>Watch the faces.</p>' , }; Open demo in new tab","title":"animation"},{"location":"plugins/animation/#animation","text":"Current version: 1.1.3. See version history . This plugin displays a sequence of images at a fixed frame rate. The sequence can be looped a specified number of times. The participant is free to respond at any point during the animation, and the time of the response is recorded.","title":"animation"},{"location":"plugins/animation/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of the array is a path to an image file. frame_time numeric 250 How long to display each image in milliseconds. frame_isi numeric 0 If greater than 0, then a gap will be shown between each image in the sequence. This parameter specifies the length of the gap in milliseconds. sequence_reps numeric 1 How many times to show the entire sequence. There will be no gap (other than the gap specified by frame_isi ) between repetitions. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key(s) to press). render_on_canvas boolean true If true, the images will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive images in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych.","title":"Parameters"},{"location":"plugins/animation/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value animation_sequence array An array, where each element is an object that represents a stimulus in the animation sequence. Each object has a stimulus property, which is the image that was displayed, and a time property, which is the time in ms, measured from when the sequence began, that the stimulus was displayed. The array will be encoded in JSON format when data is saved using either the .json() or .csv() functions. response array An array, where each element is an object representing a response given by the participant. Each object has a stimulus property, indicating which image was displayed when the key was pressed, an rt property, indicating the time of the key press relative to the start of the animation, and a key_press property, indicating which key was pressed. The array will be encoded in JSON format when data is saved using either the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/animation/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-animation@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-animation.js\" >< /script> Using NPM: npm install @jspsych/plugin-animation import animation from '@jspsych/plugin-animation' ;","title":"Install"},{"location":"plugins/animation/#examples","text":"Displaying a single sequence multiple times Code Demo var animation_sequence = [ \"img/happy_face_1.jpg\" , \"img/happy_face_2.jpg\" , \"img/happy_face_3.jpg\" , \"img/happy_face_4.jpg\" ]; var animation_trial = { type : jsPsychAnimation , stimuli : animation_sequence , sequence_reps : 3 , frame_time : 300 , prompt : '<p>Watch the faces.</p>' , }; Open demo in new tab","title":"Examples"},{"location":"plugins/audio-button-response/","text":"audio-button-response \u00b6 Current version: 1.1.3. See version history . This plugin plays audio files and records responses generated with a button click. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, you will need to manually preload the audio. The trial can end when the participant responds, when the audio file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the audio has finished playing. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Path to audio file to be played. choices array of strings undefined Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. trial_ends_after_audio boolean false If true, then the trial will end as soon as the audio file finishes playing. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before the button choices are enabled and a response is accepted. Once the audio has played all the way through, the buttons are enabled and a response is allowed (including while the audio is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-button-response import audioButtonResponse from '@jspsych/plugin-audio-button-response' ; Examples \u00b6 Displaying question until participant gives a response Code Demo var trial = { type : jsPsychAudioButtonResponse , stimulus : 'sound/tone.mp3' , choices : [ 'Low' , 'High' ], prompt : \"<p>Is the pitch high or low?</p>\" }; Open demo in new tab Using custom button HTML to use images as buttons Code Demo var trial = { type : jsPsychAudioButtonResponse , stimulus : 'sound/roar.mp3' , choices : [ 'lion.png' , 'elephant.png' , 'monkey.png' ], prompt : \"<p>Which animal made the sound?</p>\" , button_html : '<img src=\"%choice%\" />' }; Open demo in new tab Note : if you want the images to look more like jsPsych buttons, i.e. with borders and different styles for hover/active/disabled states, then you can also embed the image element inside the default button_html string: button_html : '<button class=\"jspsych-btn\"><img src=\"%choice%\" /></button>'","title":"audio-button-response"},{"location":"plugins/audio-button-response/#audio-button-response","text":"Current version: 1.1.3. See version history . This plugin plays audio files and records responses generated with a button click. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, you will need to manually preload the audio. The trial can end when the participant responds, when the audio file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the audio has finished playing.","title":"audio-button-response"},{"location":"plugins/audio-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Path to audio file to be played. choices array of strings undefined Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. trial_ends_after_audio boolean false If true, then the trial will end as soon as the audio file finishes playing. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before the button choices are enabled and a response is accepted. Once the audio has played all the way through, the buttons are enabled and a response is allowed (including while the audio is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/audio-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on.","title":"Data Generated"},{"location":"plugins/audio-button-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/audio-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-button-response import audioButtonResponse from '@jspsych/plugin-audio-button-response' ;","title":"Install"},{"location":"plugins/audio-button-response/#examples","text":"Displaying question until participant gives a response Code Demo var trial = { type : jsPsychAudioButtonResponse , stimulus : 'sound/tone.mp3' , choices : [ 'Low' , 'High' ], prompt : \"<p>Is the pitch high or low?</p>\" }; Open demo in new tab Using custom button HTML to use images as buttons Code Demo var trial = { type : jsPsychAudioButtonResponse , stimulus : 'sound/roar.mp3' , choices : [ 'lion.png' , 'elephant.png' , 'monkey.png' ], prompt : \"<p>Which animal made the sound?</p>\" , button_html : '<img src=\"%choice%\" />' }; Open demo in new tab Note : if you want the images to look more like jsPsych buttons, i.e. with borders and different styles for hover/active/disabled states, then you can also embed the image element inside the default button_html string: button_html : '<button class=\"jspsych-btn\"><img src=\"%choice%\" /></button>'","title":"Examples"},{"location":"plugins/audio-keyboard-response/","text":"audio-keyboard-response \u00b6 Current version: 1.1.3. See version history . This plugin plays audio files and records responses generated with the keyboard. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to manually preload the audio. The trial can end when the participant responds, when the audio file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the audio has finished playing. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Path to audio file to be played. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. trial_ends_after_audio boolean false If true, then the trial will end as soon as the audio file finishes playing. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before a keyboard response is accepted. Once the audio has played all the way through, a valid keyboard response is allowed (including while the audio is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. If no key was pressed before the trial ended, then the value will be null . rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant made a key response. If no key was pressed before the trial ended, then the value will be null . stimulus string Path to the audio file that played during the trial. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-keyboard-response import audioKeyboardResponse from '@jspsych/plugin-audio-keyboard-response' ; Examples \u00b6 Trial continues until participant gives a response Code Demo var trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'sound/tone.mp3' , choices : [ 'e' , 'i' ], prompt : \"<p>Is the pitch high or low? Press 'e' for low and 'i' for high.</p>\" , response_ends_trial : true }; Open demo in new tab Play a sound with no user response; trial ends after sound plays Code Demo var trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'sound/tone.mp3' , choices : \"NO_KEYS\" , trial_ends_after_audio : true }; Open demo in new tab","title":"audio-keyboard-response"},{"location":"plugins/audio-keyboard-response/#audio-keyboard-response","text":"Current version: 1.1.3. See version history . This plugin plays audio files and records responses generated with the keyboard. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to manually preload the audio. The trial can end when the participant responds, when the audio file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the audio has finished playing.","title":"audio-keyboard-response"},{"location":"plugins/audio-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Path to audio file to be played. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. trial_ends_after_audio boolean false If true, then the trial will end as soon as the audio file finishes playing. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before a keyboard response is accepted. Once the audio has played all the way through, a valid keyboard response is allowed (including while the audio is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/audio-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. If no key was pressed before the trial ended, then the value will be null . rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant made a key response. If no key was pressed before the trial ended, then the value will be null . stimulus string Path to the audio file that played during the trial.","title":"Data Generated"},{"location":"plugins/audio-keyboard-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/audio-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-keyboard-response import audioKeyboardResponse from '@jspsych/plugin-audio-keyboard-response' ;","title":"Install"},{"location":"plugins/audio-keyboard-response/#examples","text":"Trial continues until participant gives a response Code Demo var trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'sound/tone.mp3' , choices : [ 'e' , 'i' ], prompt : \"<p>Is the pitch high or low? Press 'e' for low and 'i' for high.</p>\" , response_ends_trial : true }; Open demo in new tab Play a sound with no user response; trial ends after sound plays Code Demo var trial = { type : jsPsychAudioKeyboardResponse , stimulus : 'sound/tone.mp3' , choices : \"NO_KEYS\" , trial_ends_after_audio : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/audio-slider-response/","text":"audio-slider-response \u00b6 Current version: 1.1.3. See version history . This plugin plays an audio file and allows the participant to respond by dragging a slider. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to manually preload the audio. The trial can end when the participant responds, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the audio has finished playing. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Audio file to be played labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider max integer 100 Sets the maximum value of the slider slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before the slider is enabled and the trial can end via the next button click. Once the audio has played all the way through, the slider is enabled and a response is allowed (including while the audio is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant's response. stimulus string The path of the audio file that was played. slider_start numeric The starting value of the slider. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-slider-response import audioSliderResponse from '@jspsych/plugin-audio-slider-response' ; Examples \u00b6 A simple rating scale Code Demo var trial = { type : jsPsychAudioSliderResponse , stimulus : 'sound/speech_joke.mp3' , labels : [ 'Not Funny' , 'Funny' ], prompt : '<p>How funny is the joke?</p>' } Open demo in new tab No response allowed until audio finishes; participant must interact with slider to continue Code Demo var trial = { type : jsPsychAudioSliderResponse , stimulus : 'sound/speech_joke.mp3' , labels : [ 'Not Funny' , 'Funny' ], prompt : '<p>How funny is the joke?</p>' , response_allowed_while_playing : false , require_movement : true } Open demo in new tab","title":"audio-slider-response"},{"location":"plugins/audio-slider-response/#audio-slider-response","text":"Current version: 1.1.3. See version history . This plugin plays an audio file and allows the participant to respond by dragging a slider. If the browser supports it, audio files are played using the WebAudio API. This allows for reasonably precise timing of the playback. The timing of responses generated is measured against the WebAudio specific clock, improving the measurement of response times. If the browser does not support the WebAudio API, then the audio file is played with HTML5 audio. Audio files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the audio stimulus, then you will need to manually preload the audio. The trial can end when the participant responds, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the audio has finished playing.","title":"audio-slider-response"},{"location":"plugins/audio-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus audio file undefined Audio file to be played labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider max integer 100 Sets the maximum value of the slider slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to listen to the stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the audio is playing. If false, then the audio must finish playing before the slider is enabled and the trial can end via the next button click. Once the audio has played all the way through, the slider is enabled and a response is allowed (including while the audio is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/audio-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first began playing until the participant's response. stimulus string The path of the audio file that was played. slider_start numeric The starting value of the slider.","title":"Data Generated"},{"location":"plugins/audio-slider-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/audio-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-audio-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-audio-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-audio-slider-response import audioSliderResponse from '@jspsych/plugin-audio-slider-response' ;","title":"Install"},{"location":"plugins/audio-slider-response/#examples","text":"A simple rating scale Code Demo var trial = { type : jsPsychAudioSliderResponse , stimulus : 'sound/speech_joke.mp3' , labels : [ 'Not Funny' , 'Funny' ], prompt : '<p>How funny is the joke?</p>' } Open demo in new tab No response allowed until audio finishes; participant must interact with slider to continue Code Demo var trial = { type : jsPsychAudioSliderResponse , stimulus : 'sound/speech_joke.mp3' , labels : [ 'Not Funny' , 'Funny' ], prompt : '<p>How funny is the joke?</p>' , response_allowed_while_playing : false , require_movement : true } Open demo in new tab","title":"Examples"},{"location":"plugins/browser-check/","text":"browser-check \u00b6 Current version: 1.0.3. See version history . This plugin measures and records various features of the participant's browser and can end the experiment if defined inclusion criteria are not met. The plugin currently can record the following features: The width and height of the browser window in pixels. The type of browser used (e.g., Chrome, Firefox, Edge, etc.) and the version number of the browser.* Whether the participant is using a mobile device.* The operating system.* Support for the WebAudio API. Support for the Fullscreen API, e.g., through the fullscreen plugin . The display refresh rate in frames per second. Whether the device has a webcam and microphone. Note that this only reveals whether a webcam/microphone exists. The participant still needs to grant permission in order for the experiment to use these devices. Warning Features with an * are recorded by parsing the user agent string . This method is accurate most of the time, but is not guaranteed to be correct. The plugin uses the detect-browser package to perform user agent parsing. You can find a list of supported browsers and OSes in the source file . The plugin begins by measuring the set of features requested. An inclusion function is evaluated to see if the paricipant passes the inclusion criteria. If they do, then the trial ends and the experiment continues. If they do not, then the experiment ends immediately. If a minimum width and/or minimum height is desired, the plugin will optionally display a message to participants whose browser windows are too small to give them an opportunity to make the window larger if possible. See the examples below for more guidance. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description features array of strings [\"width\", \"height\", \"webaudio\", \"browser\", \"browser_version\", \"mobile\", \"os\", \"fullscreen\", \"vsync_rate\", \"webcam\", \"microphone\"] The list of browser features to record. The default value includes all of the available options. skip_features array of strings [] Any features listed here will be skipped, even if they appear in features . Use this when you want to run most of the defaults. vsync_frame_count int 60 The number of frames to sample when measuring the display refresh rate ( \"vsync_rate\" ). Increasing the number will potenially improve the stability of the estimate at the cost of increasing the amount of time the plugin takes during this test. On most devices, 60 frames takes about 1 second to measure. allow_window_resize bool true Whether to allow the participant to resize the browser window if the window is smaller than minimum_width and/or minimum_height . If false , then the minimum_width and minimum_height parameters are ignored and you can validate the size in the inclusion_function . minimum_height int 0 If allow_window_resize is true , then this is the minimum height of the window (in pixels) that must be met before continuing. minimum_width int 0 If allow_window_resize is true , then this is the minimum width of the window (in pixels) that must be met before continuing. window_resize_message string see description The message that will be displayed during the interactive resize when allow_window_resize is true and the window is too small. If the message contains HTML elements with the special IDs browser-check-min-width , browser-check-min-height , browser-check-actual-height , and/or browser-check-actual-width , then the contents of those elements will be dynamically updated to reflect the minimum_width , minimum_height and measured width and height of the browser. The default message is: <p>Your browser window is too small to complete this experiment. Please maximize the size of your browser window. If your browser window is already maximized, you will not be able to complete this experiment.</p><p>The minimum window width is <span id=\"browser-check-min-width\"></span> px.</p><p>Your current window width is <span id=\"browser-check-actual-width\"></span> px.</p><p>The minimum window height is <span id=\"browser-check-min-height\"></span> px.</p><p>Your current window height is <span id=\"browser-check-actual-height\"></span> px.</p> . resize_fail_button_text string \"I cannot make the window any larger\" During the interactive resize, a button with this text will be displayed below the window_resize_message for the participant to click if the window cannot meet the minimum size needed. When the button is clicked, the experiment will end and exclusion_message will be displayed. inclusion_function function () => { return true; } A function that evaluates to true if the browser meets all of the inclusion criteria for the experiment, and false otherwise. The first argument to the function will be an object containing key value pairs with the measured features of the browser. The keys will be the same as those listed in features . See example below. exclusion_message function () => { return <p>Your browser does not meet the requirements to participate in this experiment.</p> } A function that returns the message to display if inclusion_function evaluates to false or if the participant clicks on the resize fail button during the interactive resize. In order to allow customization of the message, the first argument to the function will be an object containing key value pairs with the measured features of the browser. The keys will be the same as those listed in features . See example below. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value width int The width of the browser window in pixels. If interactive resizing happens, this is the width after resizing. height int The height of the browser window in pixels. If interactive resizing happens, this is the height after resizing. browser string The browser used. browser_version string The version number of the browser. os string The operating system used. mobile bool Whether the browser is a mobile device. webaudio bool Whether the browser supports the WebAudio API. fullscreen bool Whether the browser supports the Fullscreen API. vsync_rate number An estimate of the refresh rate of the screen, in frames per second. webcam bool Whether there is a webcam device available. Note that the participant still must grant permission to access the device before it can be used. microphone bool Whether there is an audio input device available. Note that the participant still must grant permission to access the device before it can be used. Note that all of these values are only recorded when the corresponding key is included in the features parameter for the trial. Simulation Mode \u00b6 In simulation mode the plugin will report the actual features of the browser, with the exception of vsync_rate , which is always 60. In data-only mode, if allow_window_resize is true and the browser's width and height are below the maximum value then the reported width and height will be equal to minimum_width and minimum_height , as if the participant resized the browser to meet the specifications. In visual mode, if allow_window_resize is true and the browser's width and height are below the maximum value then the experiment will wait for 3 seconds before clicking the resize fail button. During this time, you can adjust the window if you would like to. As with all simulated plugins, you can override the default (actual) data with fake data using simulation_options . This allows you to test your exclusion criteria by simulating other configurations. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-browser-check@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-browser-check.js\" >< /script> Using NPM: npm install @jspsych/plugin-browser-check import browserCheck from '@jspsych/plugin-browser-check' ; Examples \u00b6 Recording all of the available features, no exclusions Code Demo var trial = { type : jsPsychBrowserCheck }; Open demo in new tab Using the inclusion function to mandate the use of Chrome or Firefox as the browser Code Demo var trial = { type : jsPsychBrowserCheck , inclusion_function : ( data ) => { return [ 'chrome' , 'firefox' ]. includes ( data . browser ); }, exclusion_message : ( data ) => { return `<p>You must use Chrome or Firefox to complete this experiment.</p>` }, }; Open demo in new tab Setting a minimum window height & width, with the option to resize the window Code Demo var trial = { type : jsPsychBrowserCheck , minimum_width : 1000 , minimum_height : 600 }; This demo only works in a resizable window. Please open it in new tab Open demo in new tab Custom exclusion message based on measured features Code Demo var trial = { type : jsPsychBrowserCheck , inclusion_function : ( data ) => { return data . browser == 'chrome' && data . mobile === false }, exclusion_message : ( data ) => { if ( data . mobile ){ return '<p>You must use a desktop/laptop computer to participate in this experiment.</p>' ; } else if ( data . browser !== 'chrome' ){ return '<p>You must use Chrome as your browser to complete this experiment.</p>' } } }; Open demo in new tab","title":"browser-check"},{"location":"plugins/browser-check/#browser-check","text":"Current version: 1.0.3. See version history . This plugin measures and records various features of the participant's browser and can end the experiment if defined inclusion criteria are not met. The plugin currently can record the following features: The width and height of the browser window in pixels. The type of browser used (e.g., Chrome, Firefox, Edge, etc.) and the version number of the browser.* Whether the participant is using a mobile device.* The operating system.* Support for the WebAudio API. Support for the Fullscreen API, e.g., through the fullscreen plugin . The display refresh rate in frames per second. Whether the device has a webcam and microphone. Note that this only reveals whether a webcam/microphone exists. The participant still needs to grant permission in order for the experiment to use these devices. Warning Features with an * are recorded by parsing the user agent string . This method is accurate most of the time, but is not guaranteed to be correct. The plugin uses the detect-browser package to perform user agent parsing. You can find a list of supported browsers and OSes in the source file . The plugin begins by measuring the set of features requested. An inclusion function is evaluated to see if the paricipant passes the inclusion criteria. If they do, then the trial ends and the experiment continues. If they do not, then the experiment ends immediately. If a minimum width and/or minimum height is desired, the plugin will optionally display a message to participants whose browser windows are too small to give them an opportunity to make the window larger if possible. See the examples below for more guidance.","title":"browser-check"},{"location":"plugins/browser-check/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description features array of strings [\"width\", \"height\", \"webaudio\", \"browser\", \"browser_version\", \"mobile\", \"os\", \"fullscreen\", \"vsync_rate\", \"webcam\", \"microphone\"] The list of browser features to record. The default value includes all of the available options. skip_features array of strings [] Any features listed here will be skipped, even if they appear in features . Use this when you want to run most of the defaults. vsync_frame_count int 60 The number of frames to sample when measuring the display refresh rate ( \"vsync_rate\" ). Increasing the number will potenially improve the stability of the estimate at the cost of increasing the amount of time the plugin takes during this test. On most devices, 60 frames takes about 1 second to measure. allow_window_resize bool true Whether to allow the participant to resize the browser window if the window is smaller than minimum_width and/or minimum_height . If false , then the minimum_width and minimum_height parameters are ignored and you can validate the size in the inclusion_function . minimum_height int 0 If allow_window_resize is true , then this is the minimum height of the window (in pixels) that must be met before continuing. minimum_width int 0 If allow_window_resize is true , then this is the minimum width of the window (in pixels) that must be met before continuing. window_resize_message string see description The message that will be displayed during the interactive resize when allow_window_resize is true and the window is too small. If the message contains HTML elements with the special IDs browser-check-min-width , browser-check-min-height , browser-check-actual-height , and/or browser-check-actual-width , then the contents of those elements will be dynamically updated to reflect the minimum_width , minimum_height and measured width and height of the browser. The default message is: <p>Your browser window is too small to complete this experiment. Please maximize the size of your browser window. If your browser window is already maximized, you will not be able to complete this experiment.</p><p>The minimum window width is <span id=\"browser-check-min-width\"></span> px.</p><p>Your current window width is <span id=\"browser-check-actual-width\"></span> px.</p><p>The minimum window height is <span id=\"browser-check-min-height\"></span> px.</p><p>Your current window height is <span id=\"browser-check-actual-height\"></span> px.</p> . resize_fail_button_text string \"I cannot make the window any larger\" During the interactive resize, a button with this text will be displayed below the window_resize_message for the participant to click if the window cannot meet the minimum size needed. When the button is clicked, the experiment will end and exclusion_message will be displayed. inclusion_function function () => { return true; } A function that evaluates to true if the browser meets all of the inclusion criteria for the experiment, and false otherwise. The first argument to the function will be an object containing key value pairs with the measured features of the browser. The keys will be the same as those listed in features . See example below. exclusion_message function () => { return <p>Your browser does not meet the requirements to participate in this experiment.</p> } A function that returns the message to display if inclusion_function evaluates to false or if the participant clicks on the resize fail button during the interactive resize. In order to allow customization of the message, the first argument to the function will be an object containing key value pairs with the measured features of the browser. The keys will be the same as those listed in features . See example below.","title":"Parameters"},{"location":"plugins/browser-check/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value width int The width of the browser window in pixels. If interactive resizing happens, this is the width after resizing. height int The height of the browser window in pixels. If interactive resizing happens, this is the height after resizing. browser string The browser used. browser_version string The version number of the browser. os string The operating system used. mobile bool Whether the browser is a mobile device. webaudio bool Whether the browser supports the WebAudio API. fullscreen bool Whether the browser supports the Fullscreen API. vsync_rate number An estimate of the refresh rate of the screen, in frames per second. webcam bool Whether there is a webcam device available. Note that the participant still must grant permission to access the device before it can be used. microphone bool Whether there is an audio input device available. Note that the participant still must grant permission to access the device before it can be used. Note that all of these values are only recorded when the corresponding key is included in the features parameter for the trial.","title":"Data Generated"},{"location":"plugins/browser-check/#simulation-mode","text":"In simulation mode the plugin will report the actual features of the browser, with the exception of vsync_rate , which is always 60. In data-only mode, if allow_window_resize is true and the browser's width and height are below the maximum value then the reported width and height will be equal to minimum_width and minimum_height , as if the participant resized the browser to meet the specifications. In visual mode, if allow_window_resize is true and the browser's width and height are below the maximum value then the experiment will wait for 3 seconds before clicking the resize fail button. During this time, you can adjust the window if you would like to. As with all simulated plugins, you can override the default (actual) data with fake data using simulation_options . This allows you to test your exclusion criteria by simulating other configurations.","title":"Simulation Mode"},{"location":"plugins/browser-check/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-browser-check@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-browser-check.js\" >< /script> Using NPM: npm install @jspsych/plugin-browser-check import browserCheck from '@jspsych/plugin-browser-check' ;","title":"Install"},{"location":"plugins/browser-check/#examples","text":"Recording all of the available features, no exclusions Code Demo var trial = { type : jsPsychBrowserCheck }; Open demo in new tab Using the inclusion function to mandate the use of Chrome or Firefox as the browser Code Demo var trial = { type : jsPsychBrowserCheck , inclusion_function : ( data ) => { return [ 'chrome' , 'firefox' ]. includes ( data . browser ); }, exclusion_message : ( data ) => { return `<p>You must use Chrome or Firefox to complete this experiment.</p>` }, }; Open demo in new tab Setting a minimum window height & width, with the option to resize the window Code Demo var trial = { type : jsPsychBrowserCheck , minimum_width : 1000 , minimum_height : 600 }; This demo only works in a resizable window. Please open it in new tab Open demo in new tab Custom exclusion message based on measured features Code Demo var trial = { type : jsPsychBrowserCheck , inclusion_function : ( data ) => { return data . browser == 'chrome' && data . mobile === false }, exclusion_message : ( data ) => { if ( data . mobile ){ return '<p>You must use a desktop/laptop computer to participate in this experiment.</p>' ; } else if ( data . browser !== 'chrome' ){ return '<p>You must use Chrome as your browser to complete this experiment.</p>' } } }; Open demo in new tab","title":"Examples"},{"location":"plugins/call-function/","text":"call-function \u00b6 Current version: 1.1.3. See version history . This plugin executes a specified function. This allows the experimenter to run arbitrary code at any point during the experiment. The function cannot take any arguments. If arguments are needed, then an anonymous function should be used to wrap the function call (see examples below). Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description func function undefined The function to call. async boolean false Set to true if func is an asynchoronous function. If this is true, then the first argument passed to func will be a callback that you should call when the async operation is complete. You can pass data to the callback. See example below. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value value any The return value of the called function. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-call-function@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-call-function.js\" >< /script> Using NPM: npm install @jspsych/plugin-call-function import callFunction from '@jspsych/plugin-call-function' ; Examples \u00b6 Calling a simple function Code Demo var myfunc = function () { return 'you called?' ; } var trial = { type : jsPsychCallFunction , func : myfunc } Open demo in new tab Using an anonymous function to pass variables Code Demo var myfunc = function ( data ){ // data contains all the experiment data so far, // so this function could implement code to write // the data to a database. console . log ( data . values ()) } var trial = { type : jsPsychCallFunction , func : function (){ myfunc ( jsPsych . data . get ()) } } Open demo in new tab Async function call: wait for data to be saved to a server Code There's no demo for this code, because it requires a server to communicate with. var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ // can perform async operations here like // creating an XMLHttpRequest to communicate // with a server var xhttp = new XMLHttpRequest (); xhttp . onreadystatechange = function () { if ( this . readyState == 4 && this . status == 200 ) { var response_data = xhttp . responseText ; // line below is what causes jsPsych to // continue to next trial. response_data // will be stored in jsPsych data object. done ( response_data ); } }; xhttp . open ( \"GET\" , \"path_to_server_script.php\" , true ); xhttp . send (); } } Async function call: simulate waiting for an event to finish Code Demo var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ // generate a delay between 1500 and 3000 milliseconds to simulate // waiting for an event to finish after an unknown duration, // then move on with the experiment var rand_delay = ( Math . floor ( Math . random () * ( 3000 - 1500 + 1 ) + 1500 )); jsPsych . pluginAPI . setTimeout ( function () { // end the trial and save the delay duration to the data done ( rand_delay . toString () + \"ms\" ); }, rand_delay ) } }; Open demo in new tab","title":"call-function"},{"location":"plugins/call-function/#call-function","text":"Current version: 1.1.3. See version history . This plugin executes a specified function. This allows the experimenter to run arbitrary code at any point during the experiment. The function cannot take any arguments. If arguments are needed, then an anonymous function should be used to wrap the function call (see examples below).","title":"call-function"},{"location":"plugins/call-function/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description func function undefined The function to call. async boolean false Set to true if func is an asynchoronous function. If this is true, then the first argument passed to func will be a callback that you should call when the async operation is complete. You can pass data to the callback. See example below.","title":"Parameters"},{"location":"plugins/call-function/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value value any The return value of the called function.","title":"Data Generated"},{"location":"plugins/call-function/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-call-function@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-call-function.js\" >< /script> Using NPM: npm install @jspsych/plugin-call-function import callFunction from '@jspsych/plugin-call-function' ;","title":"Install"},{"location":"plugins/call-function/#examples","text":"Calling a simple function Code Demo var myfunc = function () { return 'you called?' ; } var trial = { type : jsPsychCallFunction , func : myfunc } Open demo in new tab Using an anonymous function to pass variables Code Demo var myfunc = function ( data ){ // data contains all the experiment data so far, // so this function could implement code to write // the data to a database. console . log ( data . values ()) } var trial = { type : jsPsychCallFunction , func : function (){ myfunc ( jsPsych . data . get ()) } } Open demo in new tab Async function call: wait for data to be saved to a server Code There's no demo for this code, because it requires a server to communicate with. var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ // can perform async operations here like // creating an XMLHttpRequest to communicate // with a server var xhttp = new XMLHttpRequest (); xhttp . onreadystatechange = function () { if ( this . readyState == 4 && this . status == 200 ) { var response_data = xhttp . responseText ; // line below is what causes jsPsych to // continue to next trial. response_data // will be stored in jsPsych data object. done ( response_data ); } }; xhttp . open ( \"GET\" , \"path_to_server_script.php\" , true ); xhttp . send (); } } Async function call: simulate waiting for an event to finish Code Demo var trial = { type : jsPsychCallFunction , async : true , func : function ( done ){ // generate a delay between 1500 and 3000 milliseconds to simulate // waiting for an event to finish after an unknown duration, // then move on with the experiment var rand_delay = ( Math . floor ( Math . random () * ( 3000 - 1500 + 1 ) + 1500 )); jsPsych . pluginAPI . setTimeout ( function () { // end the trial and save the delay duration to the data done ( rand_delay . toString () + \"ms\" ); }, rand_delay ) } }; Open demo in new tab","title":"Examples"},{"location":"plugins/canvas-button-response/","text":"canvas-button-response \u00b6 Current version: 1.1.3. See version history . This plugin can be used to draw a stimulus on a HTML canvas element , and record a button click response and response time. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. One or more button choices will be displayed under the canvas, and the button style can be customized using HTML formatting. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., what question to answer). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-button-response import canvasButtonResponse from '@jspsych/plugin-canvas-button-response' ; Examples \u00b6 Drawing circles based on parameters Code Demo function filledCirc ( canvas , radius , color ) { var ctx = canvas . getContext ( \"2d\" ); ctx . beginPath (); ctx . arc ( 150 , 150 , radius , 0 , 2 * Math . PI ); ctx . fillStyle = color ; ctx . fill (); } var circle_1 = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , 100 , 'blue' ); }, canvas_size : [ 300 , 300 ], choices : [ 'Red' , 'Green' , 'Blue' ], prompt : '<p>What color is the circle?</p>' , data : { color : 'blue' , radius : 100 } }; var circle_2 = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , 150 , 'green' ); }, canvas_size : [ 300 , 300 ], choices : [ 'Larger' , 'Smaller' ], stimulus_duration : 1000 , prompt : '<p>Is this circle larger or smaller than the last one?</p>' + '<p>Stimulus will be hidden after 1 second.</p>' , data : { color : 'green' , radius : 150 } }; Open demo in new tab Using an anonymous stimulus function Code Demo var lines = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { var ctx = c . getContext ( \"2d\" ); // first line ctx . beginPath (); ctx . moveTo ( 200 , 10 ); ctx . lineTo ( 200 , 250 ); ctx . lineWidth = 10 ; ctx . strokeStyle = 'MediumBlue' ; ctx . stroke (); // second line ctx . beginPath (); ctx . moveTo ( 20 , 100 ); ctx . lineTo ( 100 , 250 ); ctx . lineWidth = 10 ; ctx . strokeStyle = 'MediumPurple' ; ctx . stroke (); }, canvas_size : [ 300 , 300 ], choices : [ 'Blue line' , 'Purple line' ], prompt : '<p>Which line is longer?</p>' , data : { line1_color : 'blue' , line1_length : 290 , line2_color : \"purple\" , line2_length : 170 } }; Open demo in new tab Using the canvas stimulus function with timeline variables, and recording the correctness of responses Code Demo function filledCirc ( canvas , radius , color ) { var ctx = canvas . getContext ( \"2d\" ); ctx . beginPath (); ctx . arc ( 150 , 150 , radius , 0 , 2 * Math . PI ); ctx . fillStyle = color ; ctx . fill (); } var circle_procedure = { timeline : [ { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , jsPsych . timelineVariable ( 'radius' ), jsPsych . timelineVariable ( 'color' )); }, canvas_size : [ 300 , 300 ], choices : [ 'Red' , 'Green' , 'Blue' ], prompt : '<p>What color is the circle?</p>' , data : { radius : jsPsych . timelineVariable ( 'radius' ), color : jsPsych . timelineVariable ( 'color' ), correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = data . response == data . correct_response ; } } ], timeline_variables : [ { radius : 80 , color : 'red' , correct_response : 0 }, { radius : 100 , color : 'green' , correct_response : 1 }, { radius : 50 , color : 'blue' , correct_response : 2 } ], randomize_order : true }; Open demo in new tab","title":"canvas-button-response"},{"location":"plugins/canvas-button-response/#canvas-button-response","text":"Current version: 1.1.3. See version history . This plugin can be used to draw a stimulus on a HTML canvas element , and record a button click response and response time. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. One or more button choices will be displayed under the canvas, and the button style can be customized using HTML formatting.","title":"canvas-button-response"},{"location":"plugins/canvas-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., what question to answer). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/canvas-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter.","title":"Data Generated"},{"location":"plugins/canvas-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-button-response import canvasButtonResponse from '@jspsych/plugin-canvas-button-response' ;","title":"Install"},{"location":"plugins/canvas-button-response/#examples","text":"Drawing circles based on parameters Code Demo function filledCirc ( canvas , radius , color ) { var ctx = canvas . getContext ( \"2d\" ); ctx . beginPath (); ctx . arc ( 150 , 150 , radius , 0 , 2 * Math . PI ); ctx . fillStyle = color ; ctx . fill (); } var circle_1 = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , 100 , 'blue' ); }, canvas_size : [ 300 , 300 ], choices : [ 'Red' , 'Green' , 'Blue' ], prompt : '<p>What color is the circle?</p>' , data : { color : 'blue' , radius : 100 } }; var circle_2 = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , 150 , 'green' ); }, canvas_size : [ 300 , 300 ], choices : [ 'Larger' , 'Smaller' ], stimulus_duration : 1000 , prompt : '<p>Is this circle larger or smaller than the last one?</p>' + '<p>Stimulus will be hidden after 1 second.</p>' , data : { color : 'green' , radius : 150 } }; Open demo in new tab Using an anonymous stimulus function Code Demo var lines = { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { var ctx = c . getContext ( \"2d\" ); // first line ctx . beginPath (); ctx . moveTo ( 200 , 10 ); ctx . lineTo ( 200 , 250 ); ctx . lineWidth = 10 ; ctx . strokeStyle = 'MediumBlue' ; ctx . stroke (); // second line ctx . beginPath (); ctx . moveTo ( 20 , 100 ); ctx . lineTo ( 100 , 250 ); ctx . lineWidth = 10 ; ctx . strokeStyle = 'MediumPurple' ; ctx . stroke (); }, canvas_size : [ 300 , 300 ], choices : [ 'Blue line' , 'Purple line' ], prompt : '<p>Which line is longer?</p>' , data : { line1_color : 'blue' , line1_length : 290 , line2_color : \"purple\" , line2_length : 170 } }; Open demo in new tab Using the canvas stimulus function with timeline variables, and recording the correctness of responses Code Demo function filledCirc ( canvas , radius , color ) { var ctx = canvas . getContext ( \"2d\" ); ctx . beginPath (); ctx . arc ( 150 , 150 , radius , 0 , 2 * Math . PI ); ctx . fillStyle = color ; ctx . fill (); } var circle_procedure = { timeline : [ { type : jsPsychCanvasButtonResponse , stimulus : function ( c ) { filledCirc ( c , jsPsych . timelineVariable ( 'radius' ), jsPsych . timelineVariable ( 'color' )); }, canvas_size : [ 300 , 300 ], choices : [ 'Red' , 'Green' , 'Blue' ], prompt : '<p>What color is the circle?</p>' , data : { radius : jsPsych . timelineVariable ( 'radius' ), color : jsPsych . timelineVariable ( 'color' ), correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = data . response == data . correct_response ; } } ], timeline_variables : [ { radius : 80 , color : 'red' , correct_response : 0 }, { radius : 100 , color : 'green' , correct_response : 1 }, { radius : 50 , color : 'blue' , correct_response : 2 } ], randomize_order : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/canvas-keyboard-response/","text":"canvas-keyboard-response \u00b6 Current version: 1.1.3. See version history . This plugin can be used to draw a stimulus on a HTML canvas element and record a keyboard response. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-keyboard-response import canvasKeyboardResponse from '@jspsych/plugin-canvas-keyboard-response' ; Examples \u00b6 Draw rectangle and wait for response Code Demo function drawRect ( c ){ var ctx = c . getContext ( '2d' ); ctx . beginPath (); ctx . rect ( 30 , 30 , 200 , 50 ); ctx . stroke (); } var trial = { type : jsPsychCanvasKeyboardResponse , canvas_size : [ 300 , 300 ], stimulus : drawRect , choices : [ 'e' , 'i' ], prompt : '<p>Is this a circle or a rectangle? Press \"e\" for circle and \"i\" for rectangle.</p>' , data : { shape : 'rectangle' } } Open demo in new tab Draw circle, no response allowed Code Demo function drawCirc ( c ){ var ctx = c . getContext ( '2d' ); ctx . beginPath (); ctx . arc ( 100 , 75 , 50 , 0 , 2 * Math . PI ); ctx . stroke (); } var trial = { type : jsPsychCanvasKeyboardResponse , canvas_size : [ 300 , 300 ], stimulus : drawCirc , prompt : '<p>No key response is allowed.</p><p>The stimulus disappears after 3 seconds.</p>' , choices : \"NO_KEYS\" , trial_duration : 3000 , data : { shape : 'circle' , radius : 50 } } Open demo in new tab","title":"canvas-keyboard-response"},{"location":"plugins/canvas-keyboard-response/#canvas-keyboard-response","text":"Current version: 1.1.3. See version history . This plugin can be used to draw a stimulus on a HTML canvas element and record a keyboard response. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.","title":"canvas-keyboard-response"},{"location":"plugins/canvas-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/canvas-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter.","title":"Data Generated"},{"location":"plugins/canvas-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-keyboard-response import canvasKeyboardResponse from '@jspsych/plugin-canvas-keyboard-response' ;","title":"Install"},{"location":"plugins/canvas-keyboard-response/#examples","text":"Draw rectangle and wait for response Code Demo function drawRect ( c ){ var ctx = c . getContext ( '2d' ); ctx . beginPath (); ctx . rect ( 30 , 30 , 200 , 50 ); ctx . stroke (); } var trial = { type : jsPsychCanvasKeyboardResponse , canvas_size : [ 300 , 300 ], stimulus : drawRect , choices : [ 'e' , 'i' ], prompt : '<p>Is this a circle or a rectangle? Press \"e\" for circle and \"i\" for rectangle.</p>' , data : { shape : 'rectangle' } } Open demo in new tab Draw circle, no response allowed Code Demo function drawCirc ( c ){ var ctx = c . getContext ( '2d' ); ctx . beginPath (); ctx . arc ( 100 , 75 , 50 , 0 , 2 * Math . PI ); ctx . stroke (); } var trial = { type : jsPsychCanvasKeyboardResponse , canvas_size : [ 300 , 300 ], stimulus : drawCirc , prompt : '<p>No key response is allowed.</p><p>The stimulus disappears after 3 seconds.</p>' , choices : \"NO_KEYS\" , trial_duration : 3000 , data : { shape : 'circle' , radius : 50 } } Open demo in new tab","title":"Examples"},{"location":"plugins/canvas-slider-response/","text":"canvas-slider-response \u00b6 Current version: 1.1.3. See version history . This plugin can be used to draw a stimulus on a HTML canvas element and collect a response within a range of values, which is made by dragging a slider. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider. step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must click the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., what question to answer). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-slider-response import canvasSliderResponse from '@jspsych/plugin-canvas-slider-response' ; Examples \u00b6 Draw two squares Code Demo var colors = [ '#FF3333' , '#FF6A33' ]; function twoSquares ( c ) { var ctx = c . getContext ( '2d' ); ctx . fillStyle = colors [ 0 ]; ctx . fillRect ( 200 , 70 , 40 , 40 ); ctx . fillStyle = colors [ 1 ]; ctx . fillRect ( 260 , 70 , 40 , 40 ); } var trial = { type : jsPsychCanvasSliderResponse , stimulus : twoSquares , labels : [ '0' , '10' ], canvas_size : [ 150 , 500 ], prompt : '<p>How different would you say the colors of these two squares are on a scale from 0 (the same) to 10 (completely different)</p>' , data : { color1 : colors [ 0 ], color2 : colors [ 1 ]} } Open demo in new tab Draw two squares with additional parameters Code Demo var colors ; function twoSquares ( c , colors ) { var ctx = c . getContext ( '2d' ); ctx . fillStyle = colors [ 0 ]; ctx . fillRect ( 200 , 70 , 40 , 40 ); ctx . fillStyle = colors [ 1 ]; ctx . fillRect ( 260 , 70 , 40 , 40 ); } var trial = { type : jsPsychCanvasSliderResponse , stimulus : function ( c ) { colors = [ 'darkred' , 'cyan' ]; twoSquares ( c , colors ); }, labels : [ 'Exactly<br>the same' , 'Totally<br>different' ], canvas_size : [ 200 , 500 ], prompt : '<p>How different would you say the colors of these two squares are?</p>' , on_finish : function ( data ) { data . color1 = colors [ 0 ]; data . color2 = colors [ 1 ]; } }; Open demo in new tab","title":"canvas-slider-response"},{"location":"plugins/canvas-slider-response/#canvas-slider-response","text":"Current version: 1.1.3. See version history . This plugin can be used to draw a stimulus on a HTML canvas element and collect a response within a range of values, which is made by dragging a slider. The canvas stimulus can be useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.","title":"canvas-slider-response"},{"location":"plugins/canvas-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus function undefined The function to draw on the canvas. This function automatically takes a canvas element as its only argument, e.g. function(c) {...} or function drawStim(c) {...} , where c refers to the canvas element. Note that the stimulus function will still generally need to set the correct context itself, using a line like let ctx = c.getContext(\"2d\") . canvas_size array [500, 500] Array that defines the size of the canvas element in pixels. First value is height, second value is width. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider. step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must click the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., what question to answer). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/canvas-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. Note: the canvas stimulus is not included in the trial data because it is a function. Any stimulus information that should be saved in the trial data can be added via the data parameter.","title":"Data Generated"},{"location":"plugins/canvas-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-canvas-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-canvas-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-canvas-slider-response import canvasSliderResponse from '@jspsych/plugin-canvas-slider-response' ;","title":"Install"},{"location":"plugins/canvas-slider-response/#examples","text":"Draw two squares Code Demo var colors = [ '#FF3333' , '#FF6A33' ]; function twoSquares ( c ) { var ctx = c . getContext ( '2d' ); ctx . fillStyle = colors [ 0 ]; ctx . fillRect ( 200 , 70 , 40 , 40 ); ctx . fillStyle = colors [ 1 ]; ctx . fillRect ( 260 , 70 , 40 , 40 ); } var trial = { type : jsPsychCanvasSliderResponse , stimulus : twoSquares , labels : [ '0' , '10' ], canvas_size : [ 150 , 500 ], prompt : '<p>How different would you say the colors of these two squares are on a scale from 0 (the same) to 10 (completely different)</p>' , data : { color1 : colors [ 0 ], color2 : colors [ 1 ]} } Open demo in new tab Draw two squares with additional parameters Code Demo var colors ; function twoSquares ( c , colors ) { var ctx = c . getContext ( '2d' ); ctx . fillStyle = colors [ 0 ]; ctx . fillRect ( 200 , 70 , 40 , 40 ); ctx . fillStyle = colors [ 1 ]; ctx . fillRect ( 260 , 70 , 40 , 40 ); } var trial = { type : jsPsychCanvasSliderResponse , stimulus : function ( c ) { colors = [ 'darkred' , 'cyan' ]; twoSquares ( c , colors ); }, labels : [ 'Exactly<br>the same' , 'Totally<br>different' ], canvas_size : [ 200 , 500 ], prompt : '<p>How different would you say the colors of these two squares are?</p>' , on_finish : function ( data ) { data . color1 = colors [ 0 ]; data . color2 = colors [ 1 ]; } }; Open demo in new tab","title":"Examples"},{"location":"plugins/categorize-animation/","text":"categorize-animation \u00b6 Current version: 1.1.3. See version history . The categorize animation plugin shows a sequence of images at a specified frame rate. The participant responds by pressing a key. Feedback indicating the correctness of the response is given. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of the array is a path to an image file. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. key_answer string undefined The key character indicating the correct response. text_answer string \"\" A text label that describes the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). frame_time numeric 500 How long to display each image (in milliseconds). sequence_reps numeric 1 How many times to show the entire sequence. allow_response_before_complete boolean false If true, the participant can respond before the animation sequence finishes. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus or the end of the animation depending on the allow_response_before_complete parameter. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). feedback_duration numeric 2000 How long to show the feedback (milliseconds). render_on_canvas boolean true If true, the images will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive images in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array Array of stimuli displayed in the trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-animation.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-animation import categorizeAnimation from '@jspsych/plugin-categorize-animation' ; Examples \u00b6 Basic example Code Demo var animation_trial = { type : jsPsychCategorizeAnimation , stimuli : [ 'img/happy_face_1.jpg' , 'img/happy_face_2.jpg' , 'img/happy_face_3.jpg' , 'img/happy_face_4.jpg' ], prompt : `Press the P or Q key.` , choices : [ 'p' , 'q' ], key_answer : 'q' , }; Open demo in new tab Giving feedback with %ANS% string Code Demo var images = [ 'img/happy_face_1.jpg' , 'img/happy_face_2.jpg' , 'img/happy_face_3.jpg' , 'img/happy_face_4.jpg' ]; var animation_trial = { type : jsPsychCategorizeAnimation , stimuli : images , choices : [ 'p' , 'q' ], prompt : `Press the P or Q key.` , key_answer : 'q' , text_answer : 'Dax' , // the label for the sequence is 'Dax' correct_text : 'Correct! This was a %ANS%.' , incorrect_text : 'Incorrect. This was a %ANS%.' }; Open demo in new tab","title":"categorize-animation"},{"location":"plugins/categorize-animation/#categorize-animation","text":"Current version: 1.1.3. See version history . The categorize animation plugin shows a sequence of images at a specified frame rate. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.","title":"categorize-animation"},{"location":"plugins/categorize-animation/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of the array is a path to an image file. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. key_answer string undefined The key character indicating the correct response. text_answer string \"\" A text label that describes the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). frame_time numeric 500 How long to display each image (in milliseconds). sequence_reps numeric 1 How many times to show the entire sequence. allow_response_before_complete boolean false If true, the participant can respond before the animation sequence finishes. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus or the end of the animation depending on the allow_response_before_complete parameter. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). feedback_duration numeric 2000 How long to show the feedback (milliseconds). render_on_canvas boolean true If true, the images will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive images in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych.","title":"Parameters"},{"location":"plugins/categorize-animation/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array Array of stimuli displayed in the trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise.","title":"Data Generated"},{"location":"plugins/categorize-animation/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-animation@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-animation.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-animation import categorizeAnimation from '@jspsych/plugin-categorize-animation' ;","title":"Install"},{"location":"plugins/categorize-animation/#examples","text":"Basic example Code Demo var animation_trial = { type : jsPsychCategorizeAnimation , stimuli : [ 'img/happy_face_1.jpg' , 'img/happy_face_2.jpg' , 'img/happy_face_3.jpg' , 'img/happy_face_4.jpg' ], prompt : `Press the P or Q key.` , choices : [ 'p' , 'q' ], key_answer : 'q' , }; Open demo in new tab Giving feedback with %ANS% string Code Demo var images = [ 'img/happy_face_1.jpg' , 'img/happy_face_2.jpg' , 'img/happy_face_3.jpg' , 'img/happy_face_4.jpg' ]; var animation_trial = { type : jsPsychCategorizeAnimation , stimuli : images , choices : [ 'p' , 'q' ], prompt : `Press the P or Q key.` , key_answer : 'q' , text_answer : 'Dax' , // the label for the sequence is 'Dax' correct_text : 'Correct! This was a %ANS%.' , incorrect_text : 'Incorrect. This was a %ANS%.' }; Open demo in new tab","title":"Examples"},{"location":"plugins/categorize-html/","text":"categorize-html \u00b6 Current version: 1.1.3. See version history . The categorize html plugin shows an HTML object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus html string undefined The HTML stimulus to display. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. key_answer string undefined The key character indicating the correct response. text_answer string \"\" A label that is associated with the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). force_correct_button_press boolean false If set to true, then the participant must press the correct response key after feedback is given in order to advance to the next trial. show_stim_with_feedback boolean true If set to true, then the stimulus will be shown during feedback. If false, then only the text feedback will display during feedback. show_feedback_on_timeout boolean false If true, then category feedback will be displayed for an incorrect response after a timeout (trial_duration is exceeded). If false, then a timeout message will be shown. timeout_message string \"Please respond faster.\" The message to show on a timeout non-response. stimulus_duration numeric null How long to show the stimulus for (milliseconds). If null, then the stimulus is shown until a response is given. feedback_duration numeric 2000 How long to show the feedback for (milliseconds). trial_duration numeric null The maximum time allowed for a response. If null, then the experiment will wait indefinitely for a response. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-html@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-html import categorizeHtml from '@jspsych/plugin-categorize-html' ; Examples \u00b6 Categorizing HTML content Code Demo var categorization_trial = { type : jsPsychCategorizeHtml , stimulus : '<p>B</p>' , key_answer : 'p' , text_answer : 'letter' , choices : [ 'p' , 'q' ], correct_text : \"<p class='prompt'>Correct, this is a %ANS%.</p>\" , incorrect_text : \"<p class='prompt'>Incorrect, this is a %ANS%.</p>\" , prompt : \"<p>Press p for letter. Press q for number.</p>\" }; Open demo in new tab","title":"categorize-html"},{"location":"plugins/categorize-html/#categorize-html","text":"Current version: 1.1.3. See version history . The categorize html plugin shows an HTML object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.","title":"categorize-html"},{"location":"plugins/categorize-html/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus html string undefined The HTML stimulus to display. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. key_answer string undefined The key character indicating the correct response. text_answer string \"\" A label that is associated with the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). force_correct_button_press boolean false If set to true, then the participant must press the correct response key after feedback is given in order to advance to the next trial. show_stim_with_feedback boolean true If set to true, then the stimulus will be shown during feedback. If false, then only the text feedback will display during feedback. show_feedback_on_timeout boolean false If true, then category feedback will be displayed for an incorrect response after a timeout (trial_duration is exceeded). If false, then a timeout message will be shown. timeout_message string \"Please respond faster.\" The message to show on a timeout non-response. stimulus_duration numeric null How long to show the stimulus for (milliseconds). If null, then the stimulus is shown until a response is given. feedback_duration numeric 2000 How long to show the feedback for (milliseconds). trial_duration numeric null The maximum time allowed for a response. If null, then the experiment will wait indefinitely for a response.","title":"Parameters"},{"location":"plugins/categorize-html/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise.","title":"Data Generated"},{"location":"plugins/categorize-html/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-html@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-html import categorizeHtml from '@jspsych/plugin-categorize-html' ;","title":"Install"},{"location":"plugins/categorize-html/#examples","text":"Categorizing HTML content Code Demo var categorization_trial = { type : jsPsychCategorizeHtml , stimulus : '<p>B</p>' , key_answer : 'p' , text_answer : 'letter' , choices : [ 'p' , 'q' ], correct_text : \"<p class='prompt'>Correct, this is a %ANS%.</p>\" , incorrect_text : \"<p class='prompt'>Incorrect, this is a %ANS%.</p>\" , prompt : \"<p>Press p for letter. Press q for number.</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/categorize-image/","text":"categorize-image \u00b6 Current version: 1.1.3. See version history . The categorize image plugin shows an image object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path to the image file. key_answer string undefined The key character indicating the correct response. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. text_answer string \"\" A label that is associated with the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). force_correct_button_press boolean false If set to true, then the participant must press the correct response key after feedback is given in order to advance to the next trial. show_stim_with_feedback boolean true If set to true, then the stimulus will be shown during feedback. If false, then only the text feedback will display during feedback. show_feedback_on_timeout boolean false If true, then category feedback will be displayed for an incorrect response after a timeout (trial_duration is exceeded). If false, then a timeout message will be shown. timeout_message string \"Please respond faster.\" The message to show on a timeout non-response. stimulus_duration numeric null How long to show the stimulus for (milliseconds). If null, then the stimulus is shown until a response is given. feedback_duration numeric 2000 How long to show the feedback for (milliseconds). trial_duration numeric null The maximum time allowed for a response. If null, then the experiment will wait indefinitely for a response. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-image@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-image import categorizeImage from '@jspsych/plugin-categorize-image' ; Examples \u00b6 Categorizing an image Code Demo var categorization_trial = { type : jsPsychCategorizeImage , stimulus : 'img/blue.png' , key_answer : 'b' , text_answer : 'Blue' , choices : [ 'r' , 'g' , 'b' ], correct_text : \"<p class='prompt'>Correct! The color is %ANS%.</p>\" , incorrect_text : \"<p class='prompt'>Incorrect. The color is %ANS%.</p>\" , prompt : \"<p>Is the color of this circle (R)ed, (G)reen, or (B)lue?</p>\" }; Open demo in new tab","title":"categorize-image"},{"location":"plugins/categorize-image/#categorize-image","text":"Current version: 1.1.3. See version history . The categorize image plugin shows an image object on the screen. The participant responds by pressing a key. Feedback indicating the correctness of the response is given.","title":"categorize-image"},{"location":"plugins/categorize-image/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path to the image file. key_answer string undefined The key character indicating the correct response. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. text_answer string \"\" A label that is associated with the correct answer. Used in conjunction with the correct_text and incorrect_text parameters. correct_text string \"Correct.\" String to show when the correct answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). incorrect_text string \"Wrong.\" String to show when the wrong answer is given. Can contain HTML formatting. The special string %ANS% can be used within the string. If present, the plugin will put the text_answer for the trial in place of the %ANS% string (see example below). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). force_correct_button_press boolean false If set to true, then the participant must press the correct response key after feedback is given in order to advance to the next trial. show_stim_with_feedback boolean true If set to true, then the stimulus will be shown during feedback. If false, then only the text feedback will display during feedback. show_feedback_on_timeout boolean false If true, then category feedback will be displayed for an incorrect response after a timeout (trial_duration is exceeded). If false, then a timeout message will be shown. timeout_message string \"Please respond faster.\" The message to show on a timeout non-response. stimulus_duration numeric null How long to show the stimulus for (milliseconds). If null, then the stimulus is shown until a response is given. feedback_duration numeric 2000 How long to show the feedback for (milliseconds). trial_duration numeric null The maximum time allowed for a response. If null, then the experiment will wait indefinitely for a response.","title":"Parameters"},{"location":"plugins/categorize-image/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean true if the participant got the correct answer, false otherwise.","title":"Data Generated"},{"location":"plugins/categorize-image/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-categorize-image@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-categorize-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-categorize-image import categorizeImage from '@jspsych/plugin-categorize-image' ;","title":"Install"},{"location":"plugins/categorize-image/#examples","text":"Categorizing an image Code Demo var categorization_trial = { type : jsPsychCategorizeImage , stimulus : 'img/blue.png' , key_answer : 'b' , text_answer : 'Blue' , choices : [ 'r' , 'g' , 'b' ], correct_text : \"<p class='prompt'>Correct! The color is %ANS%.</p>\" , incorrect_text : \"<p class='prompt'>Incorrect. The color is %ANS%.</p>\" , prompt : \"<p>Is the color of this circle (R)ed, (G)reen, or (B)lue?</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/cloze/","text":"cloze \u00b6 Current version: 1.2.1. See version history . This plugin displays a text with certain words omitted. Participants are asked to replace the missing items. Responses are recorded when clicking a button. Responses can be evaluated and a function is called in case of either differences or incomplete answers, making it possible to inform participants about mistakes before proceeding. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description text string undefined The cloze text to be displayed. Blanks are indicated by %% signs and automatically replaced by input fields. If there is a correct answer you want the system to check against, it must be typed between the two percentage signs (i.e. % correct solution %). button_text string OK Text of the button participants have to press for finishing the cloze test. check_answers boolean false Boolean value indicating if the answers given by participants should be compared against a correct solution given in the text (between % signs) after the button was clicked. If true , answers are checked and in case of differences, the mistake_fn is called. In this case, the trial does not automatically finish. If false , no checks are performed and the trial automatically ends when clicking the button. allow_blanks boolean true Boolean value indicating if the answers given by participants should be checked for completion after the button was clicked. If true , answers are not checked for completion and blank answers are allowed. The trial will then automatically finish upon the clicking the button. If false , answers are checked for completion, and in case there are some fields with missing answers, the mistake_fn is called. In this case, the trial does not automatically finish. mistake_fn function function(){} Function called if check_answers is set to true and there is a difference between the participant's answers and the correct solution provided in the text, or if allow_blanks is set to false and there is at least one field with a blank answer. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response array of strings Answers the partcipant gave Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-cloze@1.2.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-cloze.js\" >< /script> Using NPM: npm install @jspsych/plugin-cloze import cloze from '@jspsych/plugin-cloze' ; Examples \u00b6 Simple cloze using default settings (no check against correct solution, no custom button text) Code Demo var cloze_trial = { type : jsPsychCloze , text : 'The %% is the largest terrestrial mammal. It lives in both %% and %%.' }; Open demo in new tab Cloze example using default settings with completion checking and custom error handling Code Demo var cloze_trial = { type : jsPsychCloze , text : 'Science notebooks have a %%-colored front cover. Math notebooks have a %%-colored front cover.' , allow_blanks : false , mistake_fn : function () { alert ( 'Please fill in all blanks.' ); } }; Open demo in new tab More elaborate example (with check against correct solution, custom error handling and modified button text) Code Demo var cloze_trial = { type : jsPsychCloze , text : 'A rectangle has % 4 % corners and a triangle has % 3 %.' , check_answers : true , button_text : 'Next' , mistake_fn : function (){ alert ( \"Wrong answer. Please check again.\" ) } }; Open demo in new tab","title":"cloze"},{"location":"plugins/cloze/#cloze","text":"Current version: 1.2.1. See version history . This plugin displays a text with certain words omitted. Participants are asked to replace the missing items. Responses are recorded when clicking a button. Responses can be evaluated and a function is called in case of either differences or incomplete answers, making it possible to inform participants about mistakes before proceeding.","title":"cloze"},{"location":"plugins/cloze/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description text string undefined The cloze text to be displayed. Blanks are indicated by %% signs and automatically replaced by input fields. If there is a correct answer you want the system to check against, it must be typed between the two percentage signs (i.e. % correct solution %). button_text string OK Text of the button participants have to press for finishing the cloze test. check_answers boolean false Boolean value indicating if the answers given by participants should be compared against a correct solution given in the text (between % signs) after the button was clicked. If true , answers are checked and in case of differences, the mistake_fn is called. In this case, the trial does not automatically finish. If false , no checks are performed and the trial automatically ends when clicking the button. allow_blanks boolean true Boolean value indicating if the answers given by participants should be checked for completion after the button was clicked. If true , answers are not checked for completion and blank answers are allowed. The trial will then automatically finish upon the clicking the button. If false , answers are checked for completion, and in case there are some fields with missing answers, the mistake_fn is called. In this case, the trial does not automatically finish. mistake_fn function function(){} Function called if check_answers is set to true and there is a difference between the participant's answers and the correct solution provided in the text, or if allow_blanks is set to false and there is at least one field with a blank answer.","title":"Parameters"},{"location":"plugins/cloze/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response array of strings Answers the partcipant gave","title":"Data Generated"},{"location":"plugins/cloze/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-cloze@1.2.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-cloze.js\" >< /script> Using NPM: npm install @jspsych/plugin-cloze import cloze from '@jspsych/plugin-cloze' ;","title":"Install"},{"location":"plugins/cloze/#examples","text":"Simple cloze using default settings (no check against correct solution, no custom button text) Code Demo var cloze_trial = { type : jsPsychCloze , text : 'The %% is the largest terrestrial mammal. It lives in both %% and %%.' }; Open demo in new tab Cloze example using default settings with completion checking and custom error handling Code Demo var cloze_trial = { type : jsPsychCloze , text : 'Science notebooks have a %%-colored front cover. Math notebooks have a %%-colored front cover.' , allow_blanks : false , mistake_fn : function () { alert ( 'Please fill in all blanks.' ); } }; Open demo in new tab More elaborate example (with check against correct solution, custom error handling and modified button text) Code Demo var cloze_trial = { type : jsPsychCloze , text : 'A rectangle has % 4 % corners and a triangle has % 3 %.' , check_answers : true , button_text : 'Next' , mistake_fn : function (){ alert ( \"Wrong answer. Please check again.\" ) } }; Open demo in new tab","title":"Examples"},{"location":"plugins/external-html/","text":"external-html \u00b6 Current version: 1.1.3. See version history . The HTML plugin displays an external HTML document (often a consent form). Either a keyboard response or a button press can be used to continue to the next trial. It allows the experimenter to check if conditions are met (such as indicating informed consent) before continuing. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description url string undefined The URL of the page to display. cont_key string null The key character the participant can use to advance to the next trial. If left as null, then the participant will not be able to advance trials using the keyboard. cont_btn string null The ID of a clickable element on the page. When the element is clicked, the trial will advance. check_fn function function(){ return true; } This function is called with the jsPsych display_element as the only argument when the participant attempts to advance the trial. The trial will only advance if the function return true . This can be used to verify that the participant has correctly filled out a form before continuing, for example. force_refresh boolean false If true , then the plugin will avoid using the cached version of the HTML page to load if one exists. execute_script boolean false If true , then scripts on the remote page will be executed. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value url string The URL of the page. rt numeric The response time in milliseconds for the participant to finish the trial. Simulation Mode \u00b6 In visual simulation mode, the plugin cannot interact with any form elements on the screen other than the cont_btn specified in the trial parameters. If your check_fn requires other user interaction, for example, clicking a checkbox, then you'll need to disable simulation for the trial and complete the interaction manually. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-external-html@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-external-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-external-html import externalHtml from '@jspsych/plugin-external-html' ; Examples \u00b6 Loading a consent form \u00b6 This content would be in a file called 'external_page.html' \u00b6 < div id = \"consent\" > < p > This is a demo experiment, with this minimal consent form being loaded as an external html document. To continue, click the checkbox below and hit \"Start Experiment\". </ p > < p > < input type = \"checkbox\" id = \"consent_checkbox\" /> I agree to take part in this study. </ p > < button type = \"button\" id = \"start\" > Start Experiment </ button > </ div > jsPsych code to load above page. Code Demo // sample function that might be used to check if a participant has given // consent to participate. var check_consent = function ( elem ) { if ( document . getElementById ( 'consent_checkbox' ). checked ) { return true ; } else { alert ( \"If you wish to participate, you must check the box next to the statement 'I agree to participate in this study.'\" ); return false ; } return false ; }; // declare the block. var trial = { type : jsPsychExternalHtml , url : \"external_page.html\" , cont_btn : \"start\" , check_fn : check_consent }; Open demo in new tab","title":"external-html"},{"location":"plugins/external-html/#external-html","text":"Current version: 1.1.3. See version history . The HTML plugin displays an external HTML document (often a consent form). Either a keyboard response or a button press can be used to continue to the next trial. It allows the experimenter to check if conditions are met (such as indicating informed consent) before continuing.","title":"external-html"},{"location":"plugins/external-html/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description url string undefined The URL of the page to display. cont_key string null The key character the participant can use to advance to the next trial. If left as null, then the participant will not be able to advance trials using the keyboard. cont_btn string null The ID of a clickable element on the page. When the element is clicked, the trial will advance. check_fn function function(){ return true; } This function is called with the jsPsych display_element as the only argument when the participant attempts to advance the trial. The trial will only advance if the function return true . This can be used to verify that the participant has correctly filled out a form before continuing, for example. force_refresh boolean false If true , then the plugin will avoid using the cached version of the HTML page to load if one exists. execute_script boolean false If true , then scripts on the remote page will be executed.","title":"Parameters"},{"location":"plugins/external-html/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value url string The URL of the page. rt numeric The response time in milliseconds for the participant to finish the trial.","title":"Data Generated"},{"location":"plugins/external-html/#simulation-mode","text":"In visual simulation mode, the plugin cannot interact with any form elements on the screen other than the cont_btn specified in the trial parameters. If your check_fn requires other user interaction, for example, clicking a checkbox, then you'll need to disable simulation for the trial and complete the interaction manually.","title":"Simulation Mode"},{"location":"plugins/external-html/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-external-html@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-external-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-external-html import externalHtml from '@jspsych/plugin-external-html' ;","title":"Install"},{"location":"plugins/external-html/#examples","text":"","title":"Examples"},{"location":"plugins/external-html/#loading-a-consent-form","text":"","title":"Loading a consent form"},{"location":"plugins/external-html/#this-content-would-be-in-a-file-called-external_pagehtml","text":"< div id = \"consent\" > < p > This is a demo experiment, with this minimal consent form being loaded as an external html document. To continue, click the checkbox below and hit \"Start Experiment\". </ p > < p > < input type = \"checkbox\" id = \"consent_checkbox\" /> I agree to take part in this study. </ p > < button type = \"button\" id = \"start\" > Start Experiment </ button > </ div > jsPsych code to load above page. Code Demo // sample function that might be used to check if a participant has given // consent to participate. var check_consent = function ( elem ) { if ( document . getElementById ( 'consent_checkbox' ). checked ) { return true ; } else { alert ( \"If you wish to participate, you must check the box next to the statement 'I agree to participate in this study.'\" ); return false ; } return false ; }; // declare the block. var trial = { type : jsPsychExternalHtml , url : \"external_page.html\" , cont_btn : \"start\" , check_fn : check_consent }; Open demo in new tab","title":"This content would be in a file called 'external_page.html'"},{"location":"plugins/free-sort/","text":"free-sort \u00b6 Current version: 1.0.3. See version history . The free-sort plugin displays one or more images on the screen that the participant can interact with by clicking and dragging with a mouse, or touching and dragging with a touchscreen device. When the trial starts, the images can be positioned outside or inside the sort area. All images must be moved into the sorting area before the participant can click a button to end the trial. All of the moves that the participant performs are recorded, as well as the final positions of all images. This plugin could be useful when asking participants to position images based on similarity to one another, or to recall image spatial locations. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of this array is an image path. stim_height numeric 100 The height of the images in pixels. stim_width numeric 100 The width of the images in pixels. scale_factor numeric 1.5 How much larger to make the stimulus while moving (1 = no scaling). sort_area_height numeric 800 The height of the container that participants can move the stimuli in. Stimuli will be constrained to this area. sort_area_width numeric 800 The width of the container that participants can move the stimuli in. Stimuli will be constrained to this area. sort_area_shape string \"ellipse\" The shape of the sorting area, can be \"ellipse\" or \"square\". prompt string null This string can contain HTML markup. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). prompt_location string \"above\" Indicates whether to show the prompt \"above\" or \"below\" the sorting area. button_label string 'Continue' The text that appears on the button to continue to the next trial. change_border_background_color boolean true If true , the sort area border color will change while items are being moved in and out of the sort area, and the background color will change once all items have been moved into the sort area. If false , the border will remain black and the background will remain white throughout the trial. border_color_in string '#a1d99b' If change_border_background_color is true , the sort area border will change to this color when an item is being moved into the sort area, and the background will change to this color when all of the items have been moved into the sort area. border_color_out string '#fc9272' If change_border_background_color is true , this will be the color of the sort area border when there are one or more items that still need to be moved into the sort area. border_width numeric null The width in pixels of the border around the sort area. If null , the border width will be 3% of the sort_area_height . counter_text_unfinished string You still need to place %n% item%s% inside the sort area. Text to display when there are one or more items that still need to be placed in the sort area. If \"%n%\" is included in the string, it will be replaced with the number of items that still need to be moved inside. If \"%s%\" is included in the string, a \"s\" will be included when the number of items remaining is greater than one. counter_text_finished string All items placed. Feel free to reposition items if necessary. Text that will take the place of the counter_text_unfinished text when all items have been moved inside the sort area. stim_starts_inside boolean false If false , the images will be positioned to the left and right of the sort area when the trial loads. If true , the images will be positioned at random locations inside the sort area when the trial loads. column_spread_factor numeric 1 When the images appear outside the sort area, this determines the x-axis spread of the image columns. Default value is 1. Values less than 1 will compress the image columns along the x-axis, and values greater than 1 will spread them farther apart. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value init_locations array An array containing objects representing the initial locations of all the stimuli in the sorting area. Each element in the array represents a stimulus, and has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. moves array An array containing objects representing all of the moves the participant made when sorting. Each object represents a move. Each element in the array has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location after the move. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. final_locations array An array containing objects representing the final locations of all the stimuli in the sorting area. Each element in the array represents a stimulus, and has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to finish all sorting. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-free-sort@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-free-sort.js\" >< /script> Using NPM: npm install @jspsych/plugin-free-sort import freeSort from '@jspsych/plugin-free-sort' ; Examples \u00b6 Basic example Code Demo var sort_trial = { type : jsPsychFreeSort , stimuli : sorting_stimuli , stim_width : 80 , stim_height : 60 , sort_area_width : 500 , sort_area_height : 500 , prompt : \"<p>Click and drag the images below to sort them so that similar items are close together.</p>\" }; Open demo in new tab","title":"free-sort"},{"location":"plugins/free-sort/#free-sort","text":"Current version: 1.0.3. See version history . The free-sort plugin displays one or more images on the screen that the participant can interact with by clicking and dragging with a mouse, or touching and dragging with a touchscreen device. When the trial starts, the images can be positioned outside or inside the sort area. All images must be moved into the sorting area before the participant can click a button to end the trial. All of the moves that the participant performs are recorded, as well as the final positions of all images. This plugin could be useful when asking participants to position images based on similarity to one another, or to recall image spatial locations.","title":"free-sort"},{"location":"plugins/free-sort/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined Each element of this array is an image path. stim_height numeric 100 The height of the images in pixels. stim_width numeric 100 The width of the images in pixels. scale_factor numeric 1.5 How much larger to make the stimulus while moving (1 = no scaling). sort_area_height numeric 800 The height of the container that participants can move the stimuli in. Stimuli will be constrained to this area. sort_area_width numeric 800 The width of the container that participants can move the stimuli in. Stimuli will be constrained to this area. sort_area_shape string \"ellipse\" The shape of the sorting area, can be \"ellipse\" or \"square\". prompt string null This string can contain HTML markup. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). prompt_location string \"above\" Indicates whether to show the prompt \"above\" or \"below\" the sorting area. button_label string 'Continue' The text that appears on the button to continue to the next trial. change_border_background_color boolean true If true , the sort area border color will change while items are being moved in and out of the sort area, and the background color will change once all items have been moved into the sort area. If false , the border will remain black and the background will remain white throughout the trial. border_color_in string '#a1d99b' If change_border_background_color is true , the sort area border will change to this color when an item is being moved into the sort area, and the background will change to this color when all of the items have been moved into the sort area. border_color_out string '#fc9272' If change_border_background_color is true , this will be the color of the sort area border when there are one or more items that still need to be moved into the sort area. border_width numeric null The width in pixels of the border around the sort area. If null , the border width will be 3% of the sort_area_height . counter_text_unfinished string You still need to place %n% item%s% inside the sort area. Text to display when there are one or more items that still need to be placed in the sort area. If \"%n%\" is included in the string, it will be replaced with the number of items that still need to be moved inside. If \"%s%\" is included in the string, a \"s\" will be included when the number of items remaining is greater than one. counter_text_finished string All items placed. Feel free to reposition items if necessary. Text that will take the place of the counter_text_unfinished text when all items have been moved inside the sort area. stim_starts_inside boolean false If false , the images will be positioned to the left and right of the sort area when the trial loads. If true , the images will be positioned at random locations inside the sort area when the trial loads. column_spread_factor numeric 1 When the images appear outside the sort area, this determines the x-axis spread of the image columns. Default value is 1. Values less than 1 will compress the image columns along the x-axis, and values greater than 1 will spread them farther apart.","title":"Parameters"},{"location":"plugins/free-sort/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value init_locations array An array containing objects representing the initial locations of all the stimuli in the sorting area. Each element in the array represents a stimulus, and has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. moves array An array containing objects representing all of the moves the participant made when sorting. Each object represents a move. Each element in the array has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location after the move. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. final_locations array An array containing objects representing the final locations of all the stimuli in the sorting area. Each element in the array represents a stimulus, and has a \"src\", \"x\", and \"y\" value. \"src\" is the image path, and \"x\" and \"y\" are the object location. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to finish all sorting.","title":"Data Generated"},{"location":"plugins/free-sort/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/free-sort/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-free-sort@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-free-sort.js\" >< /script> Using NPM: npm install @jspsych/plugin-free-sort import freeSort from '@jspsych/plugin-free-sort' ;","title":"Install"},{"location":"plugins/free-sort/#examples","text":"Basic example Code Demo var sort_trial = { type : jsPsychFreeSort , stimuli : sorting_stimuli , stim_width : 80 , stim_height : 60 , sort_area_width : 500 , sort_area_height : 500 , prompt : \"<p>Click and drag the images below to sort them so that similar items are close together.</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/fullscreen/","text":"fullscreen \u00b6 Current version: 1.2.1. See version history . The fullscreen plugin allows the experiment to enter or exit fullscreen mode. For security reasons, all browsers require that entry into fullscreen mode is triggered by a user action. To enter fullscreen mode, this plugin has the user click a button. Exiting fullscreen mode can be done without user input. Warning Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description fullscreen_mode boolean true A value of true causes the experiment to enter fullscreen mode. A value of false causes the browser to exit fullscreen mode. message string <p>The experiment will switch to full screen mode when you press the button below</p> The HTML content to display above the button to enter fullscreen mode. button_label string 'Continue' The text that appears on the button to enter fullscreen mode. delay_after numeric 1000 The length of time to delay after entering fullscreen mode before ending the trial. This can be useful because entering fullscreen is jarring and most browsers display some kind of message that the browser has entered fullscreen mode. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value success boolean true if the browser supports fullscreen mode (i.e., is not Safari) rt number Response time to click the button that launches fullscreen mode Simulation Mode \u00b6 Web browsers do not allow fullscreen mode to be triggered by a script to avoid malicious usage of fullscreen behavior when the user is not wanting it. In visual simulation mode, the trial will run normally and the button will get a simulated click, but the display will not change. If you want the display to actually enter fullscreen mode during the simulation, you should disable simulation for the fullscreen trial and manually click the button. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-fullscreen@1.2.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-fullscreen.js\" >< /script> Using NPM: npm install @jspsych/plugin-fullscreen import fullscreen from '@jspsych/plugin-fullscreen' ; Examples \u00b6 Entering and exiting fullscreen Code Demo var enter_fullscreen = { type : jsPsychFullscreen , fullscreen_mode : true } var trial_in_fullscreen = { type : jsPsychHtmlButtonResponse , stimulus : 'This trial will be in fullscreen mode.' , choices : [ 'Continue' ] } var exit_fullscreen = { type : jsPsychFullscreen , fullscreen_mode : false , delay_after : 0 } var trial_after_fullscreen = { type : jsPsychHtmlButtonResponse , stimulus : 'This trial will NOT be in fullscreen mode.' , choices : [ 'Continue' ] } Open demo in new tab","title":"fullscreen"},{"location":"plugins/fullscreen/#fullscreen","text":"Current version: 1.2.1. See version history . The fullscreen plugin allows the experiment to enter or exit fullscreen mode. For security reasons, all browsers require that entry into fullscreen mode is triggered by a user action. To enter fullscreen mode, this plugin has the user click a button. Exiting fullscreen mode can be done without user input. Warning Safari does not support keyboard input when the browser is in fullscreen mode. Therefore, the function will not launch fullscreen mode on Safari. The experiment will ignore any trials using the fullscreen plugin in Safari.","title":"fullscreen"},{"location":"plugins/fullscreen/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description fullscreen_mode boolean true A value of true causes the experiment to enter fullscreen mode. A value of false causes the browser to exit fullscreen mode. message string <p>The experiment will switch to full screen mode when you press the button below</p> The HTML content to display above the button to enter fullscreen mode. button_label string 'Continue' The text that appears on the button to enter fullscreen mode. delay_after numeric 1000 The length of time to delay after entering fullscreen mode before ending the trial. This can be useful because entering fullscreen is jarring and most browsers display some kind of message that the browser has entered fullscreen mode.","title":"Parameters"},{"location":"plugins/fullscreen/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value success boolean true if the browser supports fullscreen mode (i.e., is not Safari) rt number Response time to click the button that launches fullscreen mode","title":"Data Generated"},{"location":"plugins/fullscreen/#simulation-mode","text":"Web browsers do not allow fullscreen mode to be triggered by a script to avoid malicious usage of fullscreen behavior when the user is not wanting it. In visual simulation mode, the trial will run normally and the button will get a simulated click, but the display will not change. If you want the display to actually enter fullscreen mode during the simulation, you should disable simulation for the fullscreen trial and manually click the button.","title":"Simulation Mode"},{"location":"plugins/fullscreen/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-fullscreen@1.2.1\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-fullscreen.js\" >< /script> Using NPM: npm install @jspsych/plugin-fullscreen import fullscreen from '@jspsych/plugin-fullscreen' ;","title":"Install"},{"location":"plugins/fullscreen/#examples","text":"Entering and exiting fullscreen Code Demo var enter_fullscreen = { type : jsPsychFullscreen , fullscreen_mode : true } var trial_in_fullscreen = { type : jsPsychHtmlButtonResponse , stimulus : 'This trial will be in fullscreen mode.' , choices : [ 'Continue' ] } var exit_fullscreen = { type : jsPsychFullscreen , fullscreen_mode : false , delay_after : 0 } var trial_after_fullscreen = { type : jsPsychHtmlButtonResponse , stimulus : 'This trial will NOT be in fullscreen mode.' , choices : [ 'Continue' ] } Open demo in new tab","title":"Examples"},{"location":"plugins/html-audio-response/","text":"html-audio-response \u00b6 Current version: 1.0.3. See version history . This plugin displays HTML content and records audio from the participant via a microphone. In order to get access to the microphone, you need to use the initialize-microphone plugin on your timeline prior to using this plugin. Once access is granted for an experiment you do not need to get permission again. This plugin records audio data in base 64 format . This is a text-based representation of the audio which can be coverted to various audio formats using a variety of online tools as well as in languages like python and R. This plugin will generate a large amount of data, and you will need to be careful about how you handle this data. Even a few seconds of audio recording will add 10s of kB to jsPsych's data. Multiply this by a handful (or more) of trials, and the data objects will quickly get large. If you need to record a lot of audio, either many trials worth or just a few trials with longer responses, we recommend that you save the data to your server immediately after the trial and delete the data in jsPsych's data object. See below for an example of how to do this. This plugin also provides the option to store the recorded audio files as Object URLs via save_audio_url: true . This will generate a URL that is storing a copy of the recorded audio, which can be used for subsequent playback. See below for an example where the recorded audio is used as the stimulus in a subsequent trial. This feature is turned off by default because it uses a relatively large amount of memory compared to most jsPsych features. If you are running an experiment where you need this feature and you are recording lots of audio snippets, you may want to manually revoke the URLs when you no longer need them using URL.revokeObjectURL(objectURL) . Warning When recording from a microphone your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. recording_duration numeric 2000 The maximum length of the recording, in milliseconds. The default value is intentionally set low because of the potential to accidentally record very large data files if left too high. You can set this to null to allow the participant to control the length of the recording via the done button, but be careful with this option as it can lead to crashing the browser if the participant waits too long to stop the recording. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. show_done_button bool true Whether to show a button on the screen that the participant can click to finish the recording. done_button_label string 'Continue' The label for the done button. allow_playback bool false Whether to allow the participant to listen to their recording and decide whether to rerecord or not. If true , then the participant will be shown an interface to play their recorded audio and click one of two buttons to either accept the recording or rerecord. If rerecord is selected, then stimulus will be shown again, as if the trial is starting again from the beginning. record_again_button_label string 'Record again' The label for the record again button enabled when allow_playback: true . accept_button_label string 'Continue' The label for the accept button enabled when allow_playback: true . save_audio_url bool false If true , then an Object URL will be generated and stored for the recorded audio. Only set this to true if you plan to reuse the recorded audio later in the experiment, as it is a potentially memory-intensive feature. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The time, since the onset of the stimulus, for the participant to click the done button. If the button is not clicked (or not enabled), then rt will be null . response base64 string The base64-encoded audio data. stimulus string The HTML content that was displayed on the screen. estimated_stimulus_onset number This is an estimate of when the stimulus appeared relative to the start of the audio recording. The plugin is configured so that the recording should start prior to the display of the stimulus. We have not yet been able to verify the accuracy of this estimate with external measurement devices. audio_url string A URL to a copy of the audio data. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-audio-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-audio-response import htmlAudioResponse from '@jspsych/plugin-html-audio-response' ; Examples \u00b6 Simple spoken response to a stimulus Code Demo var trial = { type : jsPsychHtmlAudioResponse , stimulus : ` <p style=\"font-size:48px; color:red;\">GREEN</p> <p>Speak the color of the ink.</p>` , recording_duration : 3500 }; Open demo in new tab Allow playback and rerecording; save data to server immediately Code Demo var trial = { type : jsPsychHtmlAudioResponse , stimulus : ` <p>Please sing the first few seconds of a song and click the button when you are done.</p> ` , recording_duration : 15000 , allow_playback : true , on_finish : function ( data ){ fetch ( '/save-my-data.php' , { audio_base64 : data . response }) . then (( audio_id ){ data . response = audio_id ; }); } }; This example assumes that there is a script on your experiment server that accepts the data called save-my-data.php . It also assumes that the script will generate a response with an ID for the stored audio file ( audio_id ). In the example, we replace the very long base64 representation of the audio file with the generated ID, which could be just a handful of characters. This would let you link files to responses in data analysis, without having to store long audio files in memory during the experiment. Open demo in new tab Use recorded audio as a subsequent stimulus Code Demo var instruction = { type : jsPsychHtmlButtonResponse , stimulus : ` <img src='img/10.gif' style=\"width:100px; padding: 20px;\"></img> <p>Make up a name for this shape. When you have one in mind, click the button and then say the name aloud.</p> ` , choices : [ 'I am ready.' ] } var record = { type : jsPsychHtmlAudioResponse , stimulus : ` <img src='img/10.gif' style=\"width:100px; padding: 20px;\"></img> <p>Recording...</p> ` , recording_duration : 1500 , save_audio_url : true }; var playback = { type : jsPsychAudioButtonResponse , stimulus : ()=>{ return jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. audio_url ; }, prompt : '<p>Click the object the matches the spoken name.</p>' , choices : [ 'img/9.gif' , 'img/10.gif' , 'img/11.gif' , 'img/12.gif' ], button_html : '<img src=\"%choice%\" style=\"width:100px; padding: 20px;\"></img>' } Open demo in new tab","title":"html-audio-response"},{"location":"plugins/html-audio-response/#html-audio-response","text":"Current version: 1.0.3. See version history . This plugin displays HTML content and records audio from the participant via a microphone. In order to get access to the microphone, you need to use the initialize-microphone plugin on your timeline prior to using this plugin. Once access is granted for an experiment you do not need to get permission again. This plugin records audio data in base 64 format . This is a text-based representation of the audio which can be coverted to various audio formats using a variety of online tools as well as in languages like python and R. This plugin will generate a large amount of data, and you will need to be careful about how you handle this data. Even a few seconds of audio recording will add 10s of kB to jsPsych's data. Multiply this by a handful (or more) of trials, and the data objects will quickly get large. If you need to record a lot of audio, either many trials worth or just a few trials with longer responses, we recommend that you save the data to your server immediately after the trial and delete the data in jsPsych's data object. See below for an example of how to do this. This plugin also provides the option to store the recorded audio files as Object URLs via save_audio_url: true . This will generate a URL that is storing a copy of the recorded audio, which can be used for subsequent playback. See below for an example where the recorded audio is used as the stimulus in a subsequent trial. This feature is turned off by default because it uses a relatively large amount of memory compared to most jsPsych features. If you are running an experiment where you need this feature and you are recording lots of audio snippets, you may want to manually revoke the URLs when you no longer need them using URL.revokeObjectURL(objectURL) . Warning When recording from a microphone your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems .","title":"html-audio-response"},{"location":"plugins/html-audio-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. recording_duration numeric 2000 The maximum length of the recording, in milliseconds. The default value is intentionally set low because of the potential to accidentally record very large data files if left too high. You can set this to null to allow the participant to control the length of the recording via the done button, but be careful with this option as it can lead to crashing the browser if the participant waits too long to stop the recording. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. show_done_button bool true Whether to show a button on the screen that the participant can click to finish the recording. done_button_label string 'Continue' The label for the done button. allow_playback bool false Whether to allow the participant to listen to their recording and decide whether to rerecord or not. If true , then the participant will be shown an interface to play their recorded audio and click one of two buttons to either accept the recording or rerecord. If rerecord is selected, then stimulus will be shown again, as if the trial is starting again from the beginning. record_again_button_label string 'Record again' The label for the record again button enabled when allow_playback: true . accept_button_label string 'Continue' The label for the accept button enabled when allow_playback: true . save_audio_url bool false If true , then an Object URL will be generated and stored for the recorded audio. Only set this to true if you plan to reuse the recorded audio later in the experiment, as it is a potentially memory-intensive feature.","title":"Parameters"},{"location":"plugins/html-audio-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The time, since the onset of the stimulus, for the participant to click the done button. If the button is not clicked (or not enabled), then rt will be null . response base64 string The base64-encoded audio data. stimulus string The HTML content that was displayed on the screen. estimated_stimulus_onset number This is an estimate of when the stimulus appeared relative to the start of the audio recording. The plugin is configured so that the recording should start prior to the display of the stimulus. We have not yet been able to verify the accuracy of this estimate with external measurement devices. audio_url string A URL to a copy of the audio data.","title":"Data Generated"},{"location":"plugins/html-audio-response/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/html-audio-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-audio-response@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-audio-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-audio-response import htmlAudioResponse from '@jspsych/plugin-html-audio-response' ;","title":"Install"},{"location":"plugins/html-audio-response/#examples","text":"Simple spoken response to a stimulus Code Demo var trial = { type : jsPsychHtmlAudioResponse , stimulus : ` <p style=\"font-size:48px; color:red;\">GREEN</p> <p>Speak the color of the ink.</p>` , recording_duration : 3500 }; Open demo in new tab Allow playback and rerecording; save data to server immediately Code Demo var trial = { type : jsPsychHtmlAudioResponse , stimulus : ` <p>Please sing the first few seconds of a song and click the button when you are done.</p> ` , recording_duration : 15000 , allow_playback : true , on_finish : function ( data ){ fetch ( '/save-my-data.php' , { audio_base64 : data . response }) . then (( audio_id ){ data . response = audio_id ; }); } }; This example assumes that there is a script on your experiment server that accepts the data called save-my-data.php . It also assumes that the script will generate a response with an ID for the stored audio file ( audio_id ). In the example, we replace the very long base64 representation of the audio file with the generated ID, which could be just a handful of characters. This would let you link files to responses in data analysis, without having to store long audio files in memory during the experiment. Open demo in new tab Use recorded audio as a subsequent stimulus Code Demo var instruction = { type : jsPsychHtmlButtonResponse , stimulus : ` <img src='img/10.gif' style=\"width:100px; padding: 20px;\"></img> <p>Make up a name for this shape. When you have one in mind, click the button and then say the name aloud.</p> ` , choices : [ 'I am ready.' ] } var record = { type : jsPsychHtmlAudioResponse , stimulus : ` <img src='img/10.gif' style=\"width:100px; padding: 20px;\"></img> <p>Recording...</p> ` , recording_duration : 1500 , save_audio_url : true }; var playback = { type : jsPsychAudioButtonResponse , stimulus : ()=>{ return jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. audio_url ; }, prompt : '<p>Click the object the matches the spoken name.</p>' , choices : [ 'img/9.gif' , 'img/10.gif' , 'img/11.gif' , 'img/12.gif' ], button_html : '<img src=\"%choice%\" style=\"width:100px; padding: 20px;\"></img>' } Open demo in new tab","title":"Examples"},{"location":"plugins/html-button-response/","text":"html-button-response \u00b6 Current version: 1.1.3. See version history . This plugin displays HTML content and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. stimulus string The HTML content that was displayed on the screen. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-button-response import htmlButtonResponse from '@jspsych/plugin-html-button-response' ; Examples \u00b6 Displaying question until participant gives a response Code Demo var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<p style=\"font-size:48px; color:red;\">GREEN</p>' , choices : [ 'Red' , 'Green' , 'Blue' ], prompt : \"<p>What color is the ink?</p>\" }; Open demo in new tab","title":"html-button-response"},{"location":"plugins/html-button-response/#html-button-response","text":"Current version: 1.1.3. See version history . This plugin displays HTML content and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting.","title":"html-button-response"},{"location":"plugins/html-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/html-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. stimulus string The HTML content that was displayed on the screen.","title":"Data Generated"},{"location":"plugins/html-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-button-response import htmlButtonResponse from '@jspsych/plugin-html-button-response' ;","title":"Install"},{"location":"plugins/html-button-response/#examples","text":"Displaying question until participant gives a response Code Demo var trial = { type : jsPsychHtmlButtonResponse , stimulus : '<p style=\"font-size:48px; color:red;\">GREEN</p>' , choices : [ 'Red' , 'Green' , 'Blue' ], prompt : \"<p>What color is the ink?</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/html-keyboard-response/","text":"html-keyboard-response \u00b6 Current version: 1.1.3. See version history . This plugin displays HTML content and records responses generated with the keyboard.The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The string to be displayed. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The HTML content that was displayed on the screen. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-keyboard-response import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; Examples \u00b6 Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size:48px; color:green;\">BLUE</p>' , choices : [ 'r' , 'g' , 'b' ], prompt : \"<p>Is the ink color (r)ed, (g)reen, or (b)lue?</p>\" }; Open demo in new tab Showing a 1 second fixation cross; no response allowed Code Demo var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size: 48px;\">+</p>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; Open demo in new tab","title":"html-keyboard-response"},{"location":"plugins/html-keyboard-response/#html-keyboard-response","text":"Current version: 1.1.3. See version history . This plugin displays HTML content and records responses generated with the keyboard.The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time.","title":"html-keyboard-response"},{"location":"plugins/html-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The string to be displayed. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/html-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The HTML content that was displayed on the screen.","title":"Data Generated"},{"location":"plugins/html-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-keyboard-response import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ;","title":"Install"},{"location":"plugins/html-keyboard-response/#examples","text":"Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size:48px; color:green;\">BLUE</p>' , choices : [ 'r' , 'g' , 'b' ], prompt : \"<p>Is the ink color (r)ed, (g)reen, or (b)lue?</p>\" }; Open demo in new tab Showing a 1 second fixation cross; no response allowed Code Demo var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p style=\"font-size: 48px;\">+</p>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; Open demo in new tab","title":"Examples"},{"location":"plugins/html-slider-response/","text":"html-slider-response \u00b6 Current version: 1.1.3. See version history . This plugin displays HTML content and allows the participant to respond by dragging a slider. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The string to be displayed labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The HTML content that was displayed on the screen. slider_start numeric The starting value of the slider. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-slider-response import htmlSliderResponse from '@jspsych/plugin-html-slider-response' ; Examples \u00b6 Displaying question until participant moves the slider Code Demo var trial = { type : jsPsychHtmlSliderResponse , stimulus : `<div style=\"width:500px;\"> <p>How likely is it that team A will win this match?</p> <div style=\"width:240px; float: left;\"> <p>TEAM A</p> <p>10 wins, 5 losses, 6 draws</p> </div> <div style=\"width:240px; float: right;\"> <p>TEAM B</p> <p>6 wins, 4 losses, 11 draws</p> </div> </div>` , require_movement : true , labels : [ '100% chance' , '50% chance' , '0% chance' ] }; Open demo in new tab","title":"html-slider-response"},{"location":"plugins/html-slider-response/#html-slider-response","text":"Current version: 1.1.3. See version history . This plugin displays HTML content and allows the participant to respond by dragging a slider.","title":"html-slider-response"},{"location":"plugins/html-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The string to be displayed labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to end the trial. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/html-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The HTML content that was displayed on the screen. slider_start numeric The starting value of the slider.","title":"Data Generated"},{"location":"plugins/html-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-slider-response import htmlSliderResponse from '@jspsych/plugin-html-slider-response' ;","title":"Install"},{"location":"plugins/html-slider-response/#examples","text":"Displaying question until participant moves the slider Code Demo var trial = { type : jsPsychHtmlSliderResponse , stimulus : `<div style=\"width:500px;\"> <p>How likely is it that team A will win this match?</p> <div style=\"width:240px; float: left;\"> <p>TEAM A</p> <p>10 wins, 5 losses, 6 draws</p> </div> <div style=\"width:240px; float: right;\"> <p>TEAM B</p> <p>6 wins, 4 losses, 11 draws</p> </div> </div>` , require_movement : true , labels : [ '100% chance' , '50% chance' , '0% chance' ] }; Open demo in new tab","title":"Examples"},{"location":"plugins/html-video-response/","text":"html-video-response \u00b6 Current version: 1.0.2. See version history . This plugin displays HTML content and records video from the participant via a webcam. In order to get access to the camera, you need to use the initialize-camera plugin on your timeline prior to using this plugin. Once access is granted for an experiment you do not need to get permission again. This plugin records video data in base 64 format . This is a text-based representation of the video which can be coverted to various video formats using a variety of online tools as well as in languages like python and R. This plugin will generate a large amount of data, and you will need to be careful about how you handle this data. Even a few seconds of video recording will add 10s of kB to jsPsych's data. Multiply this by a handful (or more) of trials, and the data objects will quickly get large. If you need to record a lot of video, either many trials worth or just a few trials with longer responses, we recommend that you save the data to your server immediately after the trial and delete the data in jsPsych's data object. See below for an example of how to do this. This plugin also provides the option to store the recorded video files as Object URLs via save_video_url: true . This will generate a URL that stores a copy of the recorded video, which can be used for subsequent playback during the experiment. See below for an example where the recorded video is used as the stimulus in a subsequent trial. This feature is turned off by default because it uses a relatively large amount of memory compared to most jsPsych features. If you are running an experiment where you need this feature and you are recording lots of video clips, you may want to manually revoke the URLs when you no longer need them using URL.revokeObjectURL(objectURL) . Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the camera because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. recording_duration numeric 2000 The maximum length of the recording, in milliseconds. The default value is intentionally set low because of the potential to accidentally record very large data files if left too high. You can set this to null to allow the participant to control the length of the recording via the done button, but be careful with this option as it can lead to crashing the browser if the participant waits too long to stop the recording. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. show_done_button bool true Whether to show a button on the screen that the participant can click to finish the recording. done_button_label string 'Continue' The label for the done button. allow_playback bool false Whether to allow the participant to listen to their recording and decide whether to rerecord or not. If true , then the participant will be shown an interface to play their recorded video and click one of two buttons to either accept the recording or rerecord. If rerecord is selected, then stimulus will be shown again, as if the trial is starting again from the beginning. record_again_button_label string 'Record again' The label for the record again button enabled when allow_playback: true . accept_button_label string 'Continue' The label for the accept button enabled when allow_playback: true . save_video_url bool false If true , then an Object URL will be generated and stored for the recorded video. Only set this to true if you plan to reuse the recorded video later in the experiment, as it is a potentially memory-intensive feature. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The time, since the onset of the stimulus, for the participant to click the done button. If the button is not clicked (or not enabled), then rt will be null . response base64 string The base64-encoded video data. stimulus string The HTML content that was displayed on the screen. video_url string A URL to a copy of the video data. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-video-response@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-video-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-video-response import htmlVideoResponse from '@jspsych/plugin-html-video-response' ; Examples \u00b6 Simple recorded response to a stimulus Code Demo var init_camera = { type : jsPsychInitializeCamera } var trial = { type : jsPsychHtmlVideoResponse , stimulus : ` <p style=\"font-size:48px; color:red;\"> <-- </p> <p>Turn your head in the direction of the arrow</p>` , recording_duration : 3500 , show_done_button : false , }; Open demo in new tab Allow playback and rerecording Code Demo var init_camera = { type : jsPsychInitializeCamera } var trial = { type : jsPsychHtmlVideoResponse , stimulus : `<p>Make a sad face</p>` , recording_duration : 3500 , show_done_button : false , allow_playback : true }; Open demo in new tab Use recorded video as a subsequent stimulus Code Demo var init_camera = { type : jsPsychInitializeCamera } var record = { type : jsPsychHtmlVideoResponse , stimulus : `<p>Make a sad face.</p>` , recording_duration : 1500 , show_done_button : false , save_video_url : true }; var classify = { type : jsPsychVideoButtonResponse , stimulus : () => { return [ jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. video_url ]; }, choices : [ \"Happy\" , \"Sad\" , \"Angry\" , \"Surprised\" ], prompt : \"<p>What emotion is this?</p>\" , } Open demo in new tab","title":"html-video-response"},{"location":"plugins/html-video-response/#html-video-response","text":"Current version: 1.0.2. See version history . This plugin displays HTML content and records video from the participant via a webcam. In order to get access to the camera, you need to use the initialize-camera plugin on your timeline prior to using this plugin. Once access is granted for an experiment you do not need to get permission again. This plugin records video data in base 64 format . This is a text-based representation of the video which can be coverted to various video formats using a variety of online tools as well as in languages like python and R. This plugin will generate a large amount of data, and you will need to be careful about how you handle this data. Even a few seconds of video recording will add 10s of kB to jsPsych's data. Multiply this by a handful (or more) of trials, and the data objects will quickly get large. If you need to record a lot of video, either many trials worth or just a few trials with longer responses, we recommend that you save the data to your server immediately after the trial and delete the data in jsPsych's data object. See below for an example of how to do this. This plugin also provides the option to store the recorded video files as Object URLs via save_video_url: true . This will generate a URL that stores a copy of the recorded video, which can be used for subsequent playback during the experiment. See below for an example where the recorded video is used as the stimulus in a subsequent trial. This feature is turned off by default because it uses a relatively large amount of memory compared to most jsPsych features. If you are running an experiment where you need this feature and you are recording lots of video clips, you may want to manually revoke the URLs when you no longer need them using URL.revokeObjectURL(objectURL) . Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the camera because of potential security problems .","title":"html-video-response"},{"location":"plugins/html-video-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus HTML string undefined The HTML content to be displayed. recording_duration numeric 2000 The maximum length of the recording, in milliseconds. The default value is intentionally set low because of the potential to accidentally record very large data files if left too high. You can set this to null to allow the participant to control the length of the recording via the done button, but be careful with this option as it can lead to crashing the browser if the participant waits too long to stop the recording. stimulus_duration numeric null How long to display the stimulus in milliseconds. The visibility CSS property of the stimulus will be set to hidden after this time has elapsed. If this is null, then the stimulus will remain visible until the trial ends. show_done_button bool true Whether to show a button on the screen that the participant can click to finish the recording. done_button_label string 'Continue' The label for the done button. allow_playback bool false Whether to allow the participant to listen to their recording and decide whether to rerecord or not. If true , then the participant will be shown an interface to play their recorded video and click one of two buttons to either accept the recording or rerecord. If rerecord is selected, then stimulus will be shown again, as if the trial is starting again from the beginning. record_again_button_label string 'Record again' The label for the record again button enabled when allow_playback: true . accept_button_label string 'Continue' The label for the accept button enabled when allow_playback: true . save_video_url bool false If true , then an Object URL will be generated and stored for the recorded video. Only set this to true if you plan to reuse the recorded video later in the experiment, as it is a potentially memory-intensive feature.","title":"Parameters"},{"location":"plugins/html-video-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The time, since the onset of the stimulus, for the participant to click the done button. If the button is not clicked (or not enabled), then rt will be null . response base64 string The base64-encoded video data. stimulus string The HTML content that was displayed on the screen. video_url string A URL to a copy of the video data.","title":"Data Generated"},{"location":"plugins/html-video-response/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/html-video-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-html-video-response@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-html-video-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-html-video-response import htmlVideoResponse from '@jspsych/plugin-html-video-response' ;","title":"Install"},{"location":"plugins/html-video-response/#examples","text":"Simple recorded response to a stimulus Code Demo var init_camera = { type : jsPsychInitializeCamera } var trial = { type : jsPsychHtmlVideoResponse , stimulus : ` <p style=\"font-size:48px; color:red;\"> <-- </p> <p>Turn your head in the direction of the arrow</p>` , recording_duration : 3500 , show_done_button : false , }; Open demo in new tab Allow playback and rerecording Code Demo var init_camera = { type : jsPsychInitializeCamera } var trial = { type : jsPsychHtmlVideoResponse , stimulus : `<p>Make a sad face</p>` , recording_duration : 3500 , show_done_button : false , allow_playback : true }; Open demo in new tab Use recorded video as a subsequent stimulus Code Demo var init_camera = { type : jsPsychInitializeCamera } var record = { type : jsPsychHtmlVideoResponse , stimulus : `<p>Make a sad face.</p>` , recording_duration : 1500 , show_done_button : false , save_video_url : true }; var classify = { type : jsPsychVideoButtonResponse , stimulus : () => { return [ jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. video_url ]; }, choices : [ \"Happy\" , \"Sad\" , \"Angry\" , \"Surprised\" ], prompt : \"<p>What emotion is this?</p>\" , } Open demo in new tab","title":"Examples"},{"location":"plugins/iat-html/","text":"iat-html \u00b6 Current version: 1.1.3. See version history . This plugin runs a single trial of the implicit association test (IAT) , using HTML content as the stimulus. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The HTML-formatted stimulus to display. html_when_wrong string <span style=\"color: red; font-size: 80px\">X</span> The content to display when a user presses the wrong key. bottom_instructions string <p>If you press the wrong key, a red X will appear. Press any key to continue.</p> Instructions about making a wrong key press and whether another key press is needed to continue. force_correct_key_press boolean false If this is true and the user presses the wrong key then they have to press the other key to continue. An example would be two keys 'e' and 'i'. If the key associated with the stimulus is 'e' and key 'i' was pressed, then pressing 'e' is needed to continue the trial. When this is true , then parameter key_to_move_forward is not used. display_feedback boolean false If true , then html_when_wrong and wrong_image_name is required. If false , trial_duration is needed and trial will continue automatically. left_category_key string 'e' Key press that is associated with the left_category_label . right_category_key string 'i' Key press that is associated with the right_category_label . left_category_label string ['left'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the left side of the page. right_category_label string ['right'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the right side of the page. stim_key_association string undefined Either 'left' or 'right'. This indicates whether the stimulus is associated with the key press and category on the left or right side of the page ( left_category_key or right_category_key ). key_to_move_forward array of strings \"ALL_KEYS\" This array contains the characters the participant is allowed to press to move on to the next trial if their key press was incorrect and feedback was displayed. Can also have 'other key' as an option which will only allow the user to select the right key to move forward. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML-formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean Boolean indicating whether the user's key press was correct or incorrect for the given stimulus. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-iat-html@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-iat-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-iat-html import iatHtml from '@jspsych/plugin-iat-html' ; Examples \u00b6 Displaying IAT question using html Code Demo var trial = { type : jsPsychIatHtml , stimulus : 'Joyous' , stim_key_association : 'left' , html_when_wrong : '<span style=\"color: red; font-size: 80px\">X</span>' , bottom_instructions : '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>' , force_correct_key_press : true , display_feedback : true , trial_duration : 3000 , //Only if display_feedback is false left_category_key : 'e' , right_category_key : 'i' , left_category_label : [ 'OLD' , 'GOOD' ], right_category_label : [ 'YOUNG' , 'BAD' ], response_ends_trial : true } Open demo in new tab","title":"iat-html"},{"location":"plugins/iat-html/#iat-html","text":"Current version: 1.1.3. See version history . This plugin runs a single trial of the implicit association test (IAT) , using HTML content as the stimulus.","title":"iat-html"},{"location":"plugins/iat-html/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The HTML-formatted stimulus to display. html_when_wrong string <span style=\"color: red; font-size: 80px\">X</span> The content to display when a user presses the wrong key. bottom_instructions string <p>If you press the wrong key, a red X will appear. Press any key to continue.</p> Instructions about making a wrong key press and whether another key press is needed to continue. force_correct_key_press boolean false If this is true and the user presses the wrong key then they have to press the other key to continue. An example would be two keys 'e' and 'i'. If the key associated with the stimulus is 'e' and key 'i' was pressed, then pressing 'e' is needed to continue the trial. When this is true , then parameter key_to_move_forward is not used. display_feedback boolean false If true , then html_when_wrong and wrong_image_name is required. If false , trial_duration is needed and trial will continue automatically. left_category_key string 'e' Key press that is associated with the left_category_label . right_category_key string 'i' Key press that is associated with the right_category_label . left_category_label string ['left'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the left side of the page. right_category_label string ['right'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the right side of the page. stim_key_association string undefined Either 'left' or 'right'. This indicates whether the stimulus is associated with the key press and category on the left or right side of the page ( left_category_key or right_category_key ). key_to_move_forward array of strings \"ALL_KEYS\" This array contains the characters the participant is allowed to press to move on to the next trial if their key press was incorrect and feedback was displayed. Can also have 'other key' as an option which will only allow the user to select the right key to move forward. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/iat-html/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML-formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean Boolean indicating whether the user's key press was correct or incorrect for the given stimulus.","title":"Data Generated"},{"location":"plugins/iat-html/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-iat-html@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-iat-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-iat-html import iatHtml from '@jspsych/plugin-iat-html' ;","title":"Install"},{"location":"plugins/iat-html/#examples","text":"Displaying IAT question using html Code Demo var trial = { type : jsPsychIatHtml , stimulus : 'Joyous' , stim_key_association : 'left' , html_when_wrong : '<span style=\"color: red; font-size: 80px\">X</span>' , bottom_instructions : '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>' , force_correct_key_press : true , display_feedback : true , trial_duration : 3000 , //Only if display_feedback is false left_category_key : 'e' , right_category_key : 'i' , left_category_label : [ 'OLD' , 'GOOD' ], right_category_label : [ 'YOUNG' , 'BAD' ], response_ends_trial : true } Open demo in new tab","title":"Examples"},{"location":"plugins/iat-image/","text":"iat-image \u00b6 Current version: 1.1.3. See version history . This plugin runs a single trial of the implicit association test (IAT) , using an image as the stimulus. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The stimulus to display. The path to an image. html_when_wrong string <span style=\"color: red; font-size: 80px\">X</span> The HTML to display when a user presses the wrong key. bottom_instructions string <p>If you press the wrong key, a red X will appear. Press any key to continue.</p> Instructions about making a wrong key press and whether another key press is needed to continue. force_correct_key_press boolean false If this is true and the user presses the wrong key then they have to press the other key to continue. An example would be two keys 'e' and 'i'. If the key associated with the stimulus is 'e' and key 'i' was pressed, then pressing 'e' is needed to continue the trial. When this is true , then parameter key_to_move_forward is not used. display_feedback boolean false If true , then image_when_wrong and wrong_image_name are required. If false , trial_duration is needed and trial will continue automatically. left_category_key string 'e' Key press that is associated with the left_category_label . right_category_key string 'i' Key press that is associated with the right_category_label . left_category_label string ['left'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the left side of the page. right_category_label string ['right'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the right side of the page. stim_key_association string 'undefined' Either 'left' or 'right'. This indicates whether the stimulus is associated with the key press and category on the left or right side of the page ( left_category_key or right_category_key ). key_to_move_forward array of characters \"ALL_KEYS\" This array contains the characters the participant is allowed to press to move on to the next trial if their key press was incorrect and feedback was displayed. Can also have 'other key' as an option which will only allow the user to select the right key to move forward. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML-formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean Boolean indicating whether the user's key press was correct or incorrect for the given image. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-iat-image@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-iat-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-iat-image import iatImage from '@jspsych/plugin-iat-image' ; Examples \u00b6 Displaying IAT question using image files Code Demo var trial_block = { type : jsPsychIatImage , stimulus : 'img/iat_old_face.jpg' , stim_key_association : 'left' , html_when_wrong : '<span style=\"color: red; font-size: 80px\">X</span>' , bottom_instructions : '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>' , force_correct_key_press : true , display_feedback : true , trial_duration : 3000 , //Only if display_feedback is false left_category_key : 'e' , right_category_key : 'i' , left_category_label : [ 'OLD' , 'GOOD' ], right_category_label : [ 'YOUNG' , 'BAD' ], response_ends_trial : true } Open demo in new tab","title":"iat-image"},{"location":"plugins/iat-image/#iat-image","text":"Current version: 1.1.3. See version history . This plugin runs a single trial of the implicit association test (IAT) , using an image as the stimulus.","title":"iat-image"},{"location":"plugins/iat-image/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The stimulus to display. The path to an image. html_when_wrong string <span style=\"color: red; font-size: 80px\">X</span> The HTML to display when a user presses the wrong key. bottom_instructions string <p>If you press the wrong key, a red X will appear. Press any key to continue.</p> Instructions about making a wrong key press and whether another key press is needed to continue. force_correct_key_press boolean false If this is true and the user presses the wrong key then they have to press the other key to continue. An example would be two keys 'e' and 'i'. If the key associated with the stimulus is 'e' and key 'i' was pressed, then pressing 'e' is needed to continue the trial. When this is true , then parameter key_to_move_forward is not used. display_feedback boolean false If true , then image_when_wrong and wrong_image_name are required. If false , trial_duration is needed and trial will continue automatically. left_category_key string 'e' Key press that is associated with the left_category_label . right_category_key string 'i' Key press that is associated with the right_category_label . left_category_label string ['left'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the left side of the page. right_category_label string ['right'] An array that contains the words/labels associated with a certain stimulus. The labels are aligned to the right side of the page. stim_key_association string 'undefined' Either 'left' or 'right'. This indicates whether the stimulus is associated with the key press and category on the left or right side of the page ( left_category_key or right_category_key ). key_to_move_forward array of characters \"ALL_KEYS\" This array contains the characters the participant is allowed to press to move on to the next trial if their key press was incorrect and feedback was displayed. Can also have 'other key' as an option which will only allow the user to select the right key to move forward. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can use this parameter to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete.","title":"Parameters"},{"location":"plugins/iat-image/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus string Either the path to the image file or the string containing the HTML-formatted content that the participant saw on this trial. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. correct boolean Boolean indicating whether the user's key press was correct or incorrect for the given image.","title":"Data Generated"},{"location":"plugins/iat-image/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-iat-image@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-iat-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-iat-image import iatImage from '@jspsych/plugin-iat-image' ;","title":"Install"},{"location":"plugins/iat-image/#examples","text":"Displaying IAT question using image files Code Demo var trial_block = { type : jsPsychIatImage , stimulus : 'img/iat_old_face.jpg' , stim_key_association : 'left' , html_when_wrong : '<span style=\"color: red; font-size: 80px\">X</span>' , bottom_instructions : '<p>If you press the wrong key, a red X will appear. Press the other key to continue</p>' , force_correct_key_press : true , display_feedback : true , trial_duration : 3000 , //Only if display_feedback is false left_category_key : 'e' , right_category_key : 'i' , left_category_label : [ 'OLD' , 'GOOD' ], right_category_label : [ 'YOUNG' , 'BAD' ], response_ends_trial : true } Open demo in new tab","title":"Examples"},{"location":"plugins/image-button-response/","text":"image-button-response \u00b6 Current version: 1.1.3. See version history . This plugin displays an image and records responses generated with a button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path of the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ratio boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null, then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true, the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. stimulus string The path of the image that was displayed. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-button-response import imageButtonResponse from '@jspsych/plugin-image-button-response' ; Examples \u00b6 Displaying question until participant gives a response Code Demo var trial = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.png' , choices : [ 'Happy' , 'Sad' ], prompt : \"<p>Is this person happy or sad?</p>\" }; Open demo in new tab","title":"image-button-response"},{"location":"plugins/image-button-response/#image-button-response","text":"Current version: 1.1.3. See version history . This plugin displays an image and records responses generated with a button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. The button itself can be customized using HTML formatting. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images.","title":"image-button-response"},{"location":"plugins/image-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path of the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ratio boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. choices array of strings [] Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null, then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, the trial will wait for a response indefinitely. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true, the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images.","title":"Parameters"},{"location":"plugins/image-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. stimulus string The path of the image that was displayed.","title":"Data Generated"},{"location":"plugins/image-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-button-response import imageButtonResponse from '@jspsych/plugin-image-button-response' ;","title":"Install"},{"location":"plugins/image-button-response/#examples","text":"Displaying question until participant gives a response Code Demo var trial = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.png' , choices : [ 'Happy' , 'Sad' ], prompt : \"<p>Is this person happy or sad?</p>\" }; Open demo in new tab","title":"Examples"},{"location":"plugins/image-keyboard-response/","text":"image-keyboard-response \u00b6 Current version: 1.1.3. See version history . This plugin displays an image and records responses generated with the keyboard. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path of the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ratio boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null , then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true , the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false , the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The path of the image that was displayed. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-keyboard-response import imageKeyboardResponse from '@jspsych/plugin-image-keyboard-response' ; Examples \u00b6 Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/happy_face_1.png' , choices : [ 'e' , 'i' ], prompt : \"<p>Is this person happy or sad? Press 'e' for happy and 'i' for sad.</p>\" , }; Open demo in new tab Displaying image for a fixed duration; no response allowed Code Demo var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/happy_face_1.png' , choices : \"NO_KEYS\" , prompt : \"<p>Study this face for 5 seconds.</p>\" , trial_duration : 5000 }; Open demo in new tab","title":"image-keyboard-response"},{"location":"plugins/image-keyboard-response/#image-keyboard-response","text":"Current version: 1.1.3. See version history . This plugin displays an image and records responses generated with the keyboard. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically if the participant has failed to respond within a fixed length of time. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images.","title":"image-keyboard-response"},{"location":"plugins/image-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path of the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ratio boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null , then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null , then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true , the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false , the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images.","title":"Parameters"},{"location":"plugins/image-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The path of the image that was displayed.","title":"Data Generated"},{"location":"plugins/image-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-keyboard-response import imageKeyboardResponse from '@jspsych/plugin-image-keyboard-response' ;","title":"Install"},{"location":"plugins/image-keyboard-response/#examples","text":"Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/happy_face_1.png' , choices : [ 'e' , 'i' ], prompt : \"<p>Is this person happy or sad? Press 'e' for happy and 'i' for sad.</p>\" , }; Open demo in new tab Displaying image for a fixed duration; no response allowed Code Demo var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/happy_face_1.png' , choices : \"NO_KEYS\" , prompt : \"<p>Study this face for 5 seconds.</p>\" , trial_duration : 5000 }; Open demo in new tab","title":"Examples"},{"location":"plugins/image-slider-response/","text":"image-slider-response \u00b6 Current version: 1.1.3. See version history . This plugin displays and image and allows the participant to respond by dragging a slider. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path to the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ration boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to advance/submit min integer 0 Sets the minimum value of the slider max integer 100 Sets the maximum value of the slider slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null, then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true, the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The path of the image that was displayed. slider_start numeric The starting value of the slider. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-slider-response import imageSliderResponse from '@jspsych/plugin-image-slider-response' ; Examples \u00b6 Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychImageSliderResponse , stimulus : 'img/happy_face_1.png' , labels : [ 'happy' , 'sad' ], prompt : \"<p>How happy/sad is this person?</p>\" , }; Open demo in new tab","title":"image-slider-response"},{"location":"plugins/image-slider-response/#image-slider-response","text":"Current version: 1.1.3. See version history . This plugin displays and image and allows the participant to respond by dragging a slider. Image files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the image stimulus, you will need to manually preload the images.","title":"image-slider-response"},{"location":"plugins/image-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus string undefined The path to the image file to be displayed. stimulus_height integer null Set the height of the image in pixels. If left null (no value specified), then the image will display at its natural height. stimulus_width integer null Set the width of the image in pixels. If left null (no value specified), then the image will display at its natural width. maintain_aspect_ration boolean true If setting only the width or only the height and this parameter is true, then the other dimension will be scaled to maintain the image's aspect ratio. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. button_label string 'Continue' Label of the button to advance/submit min integer 0 Sets the minimum value of the slider max integer 100 Sets the maximum value of the slider slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). stimulus_duration numeric null How long to show the stimulus for in milliseconds. If the value is null, then the stimulus will be shown until the participant makes a response. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. render_on_canvas boolean true If true, the image will be drawn onto a canvas element. This prevents a blank screen (white flash) between consecutive image trials in some browsers, like Firefox and Edge. If false, the image will be shown via an img element, as in previous versions of jsPsych. If the stimulus is an animated gif , you must set this parameter to false, because the canvas rendering method will only present static images.","title":"Parameters"},{"location":"plugins/image-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus string The path of the image that was displayed. slider_start numeric The starting value of the slider.","title":"Data Generated"},{"location":"plugins/image-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-image-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-image-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-image-slider-response import imageSliderResponse from '@jspsych/plugin-image-slider-response' ;","title":"Install"},{"location":"plugins/image-slider-response/#examples","text":"Displaying trial until participant gives a response Code Demo var trial = { type : jsPsychImageSliderResponse , stimulus : 'img/happy_face_1.png' , labels : [ 'happy' , 'sad' ], prompt : \"<p>How happy/sad is this person?</p>\" , }; Open demo in new tab","title":"Examples"},{"location":"plugins/initialize-camera/","text":"initialize-camera \u00b6 Current version: 1.0.0 See version history . This plugin asks the participant to grant permission to access a camera. If multiple cameras are connected to the participant's device, then it allows the participant to pick which device to use. Once access is granted for an experiment you do not need to get permission again. Once the camera is selected with this plugin it can be accessed with jsPsych.pluginAPI.getCameraRecorder() . Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description device_select_message html string <p>Please select the camera you would like to use.</p> The message to display when the user is presented with a dropdown list of available devices. button_label sting 'Use this camera.' The label for the select button. include_audio bool false Set to true to include an audio track in the recordings. width int null Request a specific width for the recording. This is not a guarantee that this width will be used, as it depends on the capabilities of the participant's device. Learn more about MediaRecorder constraints here . height int null Request a specific height for the recording. This is not a guarantee that this height will be used, as it depends on the capabilities of the participant's device. Learn more about MediaRecorder constraints here . mime_type string null Set this to use a specific MIME type for the recording. Set the entire type, e.g., 'video/mp4; codecs=\"avc1.424028, mp4a.40.2\"' . Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value device_id string The device ID of the selected camera. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-initialize-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-initialize-camera import initializeCamera from '@jspsych/plugin-initialize-camera' ; Examples \u00b6 Ask for camera permission Code Demo var trial = { type : jsPsychInitializeCamera }; Open demo in new tab","title":"initialize-camera"},{"location":"plugins/initialize-camera/#initialize-camera","text":"Current version: 1.0.0 See version history . This plugin asks the participant to grant permission to access a camera. If multiple cameras are connected to the participant's device, then it allows the participant to pick which device to use. Once access is granted for an experiment you do not need to get permission again. Once the camera is selected with this plugin it can be accessed with jsPsych.pluginAPI.getCameraRecorder() . Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems .","title":"initialize-camera"},{"location":"plugins/initialize-camera/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description device_select_message html string <p>Please select the camera you would like to use.</p> The message to display when the user is presented with a dropdown list of available devices. button_label sting 'Use this camera.' The label for the select button. include_audio bool false Set to true to include an audio track in the recordings. width int null Request a specific width for the recording. This is not a guarantee that this width will be used, as it depends on the capabilities of the participant's device. Learn more about MediaRecorder constraints here . height int null Request a specific height for the recording. This is not a guarantee that this height will be used, as it depends on the capabilities of the participant's device. Learn more about MediaRecorder constraints here . mime_type string null Set this to use a specific MIME type for the recording. Set the entire type, e.g., 'video/mp4; codecs=\"avc1.424028, mp4a.40.2\"' .","title":"Parameters"},{"location":"plugins/initialize-camera/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value device_id string The device ID of the selected camera.","title":"Data Generated"},{"location":"plugins/initialize-camera/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/initialize-camera/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-initialize-camera@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-initialize-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-initialize-camera import initializeCamera from '@jspsych/plugin-initialize-camera' ;","title":"Install"},{"location":"plugins/initialize-camera/#examples","text":"Ask for camera permission Code Demo var trial = { type : jsPsychInitializeCamera }; Open demo in new tab","title":"Examples"},{"location":"plugins/initialize-microphone/","text":"initialize-microphone \u00b6 Current version: 1.0.3. See version history . This plugin asks the participant to grant permission to access a microphone. If multiple microphones are connected to the participant's device, then it allows the participant to pick which device to use. Once access is granted for an experiment you do not need to get permission again. Once the microphone is selected with this plugin it can be accessed with jsPsych.pluginAPI.getMicrophoneRecorder() . Warning When recording from a microphone your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description device_select_message html string <p>Please select the microphone you would like to use.</p> The message to display when the user is presented with a dropdown list of available devices. button_label sting 'Use this microphone.' The label for the select button. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value device_id string The device ID of the selected microphone. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-initialize-microphone.js\" >< /script> Using NPM: npm install @jspsych/plugin-initialize-microphone import initializeMicrophone from '@jspsych/plugin-initialize-microphone' ; Examples \u00b6 Ask for microphone permission Code Demo var trial = { type : jsPsychInitializeMicrophone }; Open demo in new tab","title":"initialize-microphone"},{"location":"plugins/initialize-microphone/#initialize-microphone","text":"Current version: 1.0.3. See version history . This plugin asks the participant to grant permission to access a microphone. If multiple microphones are connected to the participant's device, then it allows the participant to pick which device to use. Once access is granted for an experiment you do not need to get permission again. Once the microphone is selected with this plugin it can be accessed with jsPsych.pluginAPI.getMicrophoneRecorder() . Warning When recording from a microphone your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the microphone because of potential security problems .","title":"initialize-microphone"},{"location":"plugins/initialize-microphone/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description device_select_message html string <p>Please select the microphone you would like to use.</p> The message to display when the user is presented with a dropdown list of available devices. button_label sting 'Use this microphone.' The label for the select button.","title":"Parameters"},{"location":"plugins/initialize-microphone/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value device_id string The device ID of the selected microphone.","title":"Data Generated"},{"location":"plugins/initialize-microphone/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/initialize-microphone/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-initialize-microphone@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-initialize-microphone.js\" >< /script> Using NPM: npm install @jspsych/plugin-initialize-microphone import initializeMicrophone from '@jspsych/plugin-initialize-microphone' ;","title":"Install"},{"location":"plugins/initialize-microphone/#examples","text":"Ask for microphone permission Code Demo var trial = { type : jsPsychInitializeMicrophone }; Open demo in new tab","title":"Examples"},{"location":"plugins/instructions/","text":"instructions \u00b6 Current version: 1.1.4. See version history . This plugin is for showing instructions to the participant. It allows participants to navigate through multiple pages of instructions at their own pace, recording how long the participant spends on each page. Navigation can be done using the mouse or keyboard. participants can be allowed to navigate forwards and backwards through pages, if desired. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description pages array undefined Each element of the array is the content for a single page. Each page should be an HTML-formatted string. key_forward string 'ArrowRight' This is the key that the participant can press in order to advance to the next page. This key should be specified as a string (e.g., 'a' , 'ArrowLeft' , ' ' , 'Enter' ). key_backward string 'ArrowLeft' This is the key that the participant can press to return to the previous page. This key should be specified as a string (e.g., 'a' , 'ArrowLeft' , ' ' , 'Enter' ). allow_backward boolean true If true, the participant can return to previous pages of the instructions. If false, they may only advace to the next page. allow_keys boolean true If true , the participant can use keyboard keys to navigate the pages. If false , they may not. show_clickable_nav boolean false If true, then a Previous and Next button will be displayed beneath the instructions. Participants can click the buttons to navigate. button_label_previous string 'Previous' The text that appears on the button to go backwards. button_label_next string 'Next' The text that appears on the button to go forwards. show_page_number boolean false If true, and clickable navigation is enabled, then Page x/y will be shown between the nav buttons. page_label string 'Page' The text that appears before x/y pages displayed when show_page_number is true. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value view_history array An array containing the order of pages the participant viewed (including when the participant returned to previous pages) and the time spent viewing each page. Each object in the array represents a single page view, and contains keys called page_index (the page number, starting with 0) and viewing_time (duration of the page view). This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to view all of the pages. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-instructions@1.1.4\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-instructions.js\" >< /script> Using NPM: npm install @jspsych/plugin-instructions import instructions from '@jspsych/plugin-instructions' ; Examples \u00b6 Showing simple text instructions \u00b6 Showing simple text instructions Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'This is the second page of instructions.' , 'This is the final page.' ], show_clickable_nav : true } Open demo in new tab Including images \u00b6 Including Images Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'You will be looking at images of arrows: ' + '<br>' + '<img src=\"con2.png\"></img>' ], show_clickable_nav : true } Open demo in new tab Changing Button Text \u00b6 Changing Button Text Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'This is the second page of instructions.' , 'This is the final page.' ], button_label_next : \"Continue\" , button_label_previous : \"Return to the dark side\" , show_clickable_nav : true } Open demo in new tab","title":"instructions"},{"location":"plugins/instructions/#instructions","text":"Current version: 1.1.4. See version history . This plugin is for showing instructions to the participant. It allows participants to navigate through multiple pages of instructions at their own pace, recording how long the participant spends on each page. Navigation can be done using the mouse or keyboard. participants can be allowed to navigate forwards and backwards through pages, if desired.","title":"instructions"},{"location":"plugins/instructions/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description pages array undefined Each element of the array is the content for a single page. Each page should be an HTML-formatted string. key_forward string 'ArrowRight' This is the key that the participant can press in order to advance to the next page. This key should be specified as a string (e.g., 'a' , 'ArrowLeft' , ' ' , 'Enter' ). key_backward string 'ArrowLeft' This is the key that the participant can press to return to the previous page. This key should be specified as a string (e.g., 'a' , 'ArrowLeft' , ' ' , 'Enter' ). allow_backward boolean true If true, the participant can return to previous pages of the instructions. If false, they may only advace to the next page. allow_keys boolean true If true , the participant can use keyboard keys to navigate the pages. If false , they may not. show_clickable_nav boolean false If true, then a Previous and Next button will be displayed beneath the instructions. Participants can click the buttons to navigate. button_label_previous string 'Previous' The text that appears on the button to go backwards. button_label_next string 'Next' The text that appears on the button to go forwards. show_page_number boolean false If true, and clickable navigation is enabled, then Page x/y will be shown between the nav buttons. page_label string 'Page' The text that appears before x/y pages displayed when show_page_number is true.","title":"Parameters"},{"location":"plugins/instructions/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value view_history array An array containing the order of pages the participant viewed (including when the participant returned to previous pages) and the time spent viewing each page. Each object in the array represents a single page view, and contains keys called page_index (the page number, starting with 0) and viewing_time (duration of the page view). This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to view all of the pages.","title":"Data Generated"},{"location":"plugins/instructions/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-instructions@1.1.4\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-instructions.js\" >< /script> Using NPM: npm install @jspsych/plugin-instructions import instructions from '@jspsych/plugin-instructions' ;","title":"Install"},{"location":"plugins/instructions/#examples","text":"","title":"Examples"},{"location":"plugins/instructions/#showing-simple-text-instructions","text":"Showing simple text instructions Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'This is the second page of instructions.' , 'This is the final page.' ], show_clickable_nav : true } Open demo in new tab","title":"Showing simple text instructions"},{"location":"plugins/instructions/#including-images","text":"Including Images Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'You will be looking at images of arrows: ' + '<br>' + '<img src=\"con2.png\"></img>' ], show_clickable_nav : true } Open demo in new tab","title":"Including images"},{"location":"plugins/instructions/#changing-button-text","text":"Changing Button Text Code Demo var trial = { type : jsPsychInstructions , pages : [ 'Welcome to the experiment. Click next to begin.' , 'This is the second page of instructions.' , 'This is the final page.' ], button_label_next : \"Continue\" , button_label_previous : \"Return to the dark side\" , show_clickable_nav : true } Open demo in new tab","title":"Changing Button Text"},{"location":"plugins/list-of-plugins/","text":"List of Plugins \u00b6 These are the plugins that are included in the jsPsych release. Additional plugins may be available in the community contributions repository . For an overview of what plugins are and how they work, see our plugins overview . Plugin Description animation Shows a sequence of images at a specified frame rate. Records key presses (including timing information) made by the participant while they are viewing the animation. audio\u2011button\u2011response Play an audio file and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. audio\u2011keyboard\u2011response Play an audio file and allow the participant to respond by pressing a key. audio\u2011slider\u2011response Play an audio file and allow the participant to respond by moving a slider to indicate a value. browser\u2011check Measures various features of the participant's browser and runs an inclusion check to see if the browser meets a custom set of criteria for running the study. call\u2011function Executes an arbitrary function call. Doesn't display anything to the participant, and the participant is usually unaware that this plugin has even executed. It's useful for performing tasks at specified times in the experiment, such as saving data. canvas\u2011button\u2011response Draw a stimulus on a HTML canvas element , and record a button click response. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). canvas\u2011keyboard\u2011response Draw a stimulus on a HTML canvas element , and record a key press response. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). canvas\u2011slider\u2011response Draw a stimulus on a HTML canvas element , and ask the participant to respond by moving a slider to indicate a value. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). categorize\u2011animation The participant responds to an animation and can be given feedback about their response. categorize\u2011html The participant responds to an HTML-formatted stimulus using the keyboard and can be given feedback about the correctness of their response. categorize\u2011image The participant responds to an image using the keyboard and can be given feedback about the correctness of their response. cloze Plugin for displaying a cloze test and checking participants answers against a correct solution. external\u2011html Displays an external HTML page (such as a consent form) and lets the participant respond by clicking a button or pressing a key. Plugin can validate their response, which is useful for making sure that a participant has granted consent before starting the experiment. free\u2011sort Displays a set of images on the screen in random locations. Participants can click and drag the images to move them around the screen. Records all the moves made by the participant, so the sequence of moves can be recovered from the data. fullscreen Toggles the experiment in and out of fullscreen mode. html\u2011audio\u2011response Display an HTML-formatted stimulus and records an audio response via a microphone. html\u2011button\u2011response Display an HTML-formatted stimulus and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. html\u2011keyboard\u2011response Display an HTML-formatted stimulus and allow the participant to respond by pressing a key. html\u2011slider\u2011response Display an HTML-formatted stimulus and allow the participant to respond by moving a slider to indicate a value. html\u2011video\u2011response Display an HTML-formatted stimulus and records video data via a webcam. iat\u2011html The implicit association task, using HTML-formatted stimuli. iat\u2011image The implicit association task, using images as stimuli. image\u2011button\u2011response Display an image and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. image\u2011keyboard\u2011response Display an image and allow the participant to respond by pressing a key. image\u2011slider\u2011response Display an image and allow the participant to respond by moving a slider to indicate a value. initialize\u2011camera Request permission to use the participant's camera to record video and allows the participant to choose which camera to use if multiple devices are enabled. Also allows setting the mime type of the recorded video. initialize\u2011microphone Request permission to use the participant's microphone to record audio and allows the participant to choose which microphone to use if multiple devices are enabled. instructions For displaying instructions to the participant. Allows the participant to navigate between pages of instructions using keys or buttons. maxdiff Displays rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. mirror\u2011camera Shows a live feed of the participant's camera on the screen. preload This plugin loads images, audio, and video files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and to avoid disrupting the flow of the experiment. reconstruction The participant interacts with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time. resize Calibrate the display so that materials display with a known physical size. same\u2011different\u2011html A same-different judgment task. An HTML-formatted stimulus is shown, followed by a brief gap, and then another stimulus is shown. The participant indicates whether the stimuli are the same or different. same\u2011different\u2011image A same-different judgment task. An image is shown, followed by a brief gap, and then another stimulus is shown. The participant indicates whether the stimuli are the same or different. serial\u2011reaction\u2011time A set of boxes are displayed on the screen and one of them changes color. The participant presses a key that corresponds to the different color box as fast as possible. serial\u2011reaction\u2011time\u2011mouse A set of boxes are displayed on the screen and one of them changes color. The participants clicks the box that changed color as fast as possible. sketchpad Creates an interactive canvas that the participant can draw on using their mouse or touchscreen. survey\u2011html\u2011form Renders a custom HTML form. Allows for mixing multiple kinds of form input. survey\u2011likert Displays likert-style questions. survey\u2011multi\u2011choice Displays multiple choice questions with one answer allowed per question. survey\u2011multi\u2011select Displays multiple choice questions with multiple answes allowed per question. survey\u2011text Shows a prompt with a text box. The participant writes a response and then submits by clicking a button. video\u2011button\u2011response Displays a video file with many options for customizing playback. participant responds to the video by pressing a button. video\u2011keyboard\u2011response Displays a video file with many options for customizing playback. participant responds to the video by pressing a key. video\u2011slider\u2011response Displays a video file with many options for customizing playback. participant responds to the video by moving a slider. virtual\u2011chinrest An implementation of the \"virutal chinrest\" procedure developed by Li, Joo, Yeatman, and Reinecke (2020) . Calibrates the monitor to display items at a known physical size by having participants scale an image to be the same size as a physical credit card. Then uses a blind spot task to estimate the distance between the participant and the display. visual\u2011search\u2011circle A customizable visual-search task modelled after Wang, Cavanagh, & Green (1994) . The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. webgazer\u2011calibrate Calibrates the WebGazer extension for eye tracking. webgazer\u2011init\u2011camera Initializes the camera and helps the participant center their face for eye tracking. webgazer\u2011validate Performs validation to measure precision and accuracy of WebGazer eye tracking predictions.","title":"List of Plugins"},{"location":"plugins/list-of-plugins/#list-of-plugins","text":"These are the plugins that are included in the jsPsych release. Additional plugins may be available in the community contributions repository . For an overview of what plugins are and how they work, see our plugins overview . Plugin Description animation Shows a sequence of images at a specified frame rate. Records key presses (including timing information) made by the participant while they are viewing the animation. audio\u2011button\u2011response Play an audio file and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. audio\u2011keyboard\u2011response Play an audio file and allow the participant to respond by pressing a key. audio\u2011slider\u2011response Play an audio file and allow the participant to respond by moving a slider to indicate a value. browser\u2011check Measures various features of the participant's browser and runs an inclusion check to see if the browser meets a custom set of criteria for running the study. call\u2011function Executes an arbitrary function call. Doesn't display anything to the participant, and the participant is usually unaware that this plugin has even executed. It's useful for performing tasks at specified times in the experiment, such as saving data. canvas\u2011button\u2011response Draw a stimulus on a HTML canvas element , and record a button click response. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). canvas\u2011keyboard\u2011response Draw a stimulus on a HTML canvas element , and record a key press response. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). canvas\u2011slider\u2011response Draw a stimulus on a HTML canvas element , and ask the participant to respond by moving a slider to indicate a value. Useful for displaying dynamic, parametrically-defined graphics, and for controlling the positioning of multiple graphical elements (shapes, text, images). categorize\u2011animation The participant responds to an animation and can be given feedback about their response. categorize\u2011html The participant responds to an HTML-formatted stimulus using the keyboard and can be given feedback about the correctness of their response. categorize\u2011image The participant responds to an image using the keyboard and can be given feedback about the correctness of their response. cloze Plugin for displaying a cloze test and checking participants answers against a correct solution. external\u2011html Displays an external HTML page (such as a consent form) and lets the participant respond by clicking a button or pressing a key. Plugin can validate their response, which is useful for making sure that a participant has granted consent before starting the experiment. free\u2011sort Displays a set of images on the screen in random locations. Participants can click and drag the images to move them around the screen. Records all the moves made by the participant, so the sequence of moves can be recovered from the data. fullscreen Toggles the experiment in and out of fullscreen mode. html\u2011audio\u2011response Display an HTML-formatted stimulus and records an audio response via a microphone. html\u2011button\u2011response Display an HTML-formatted stimulus and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. html\u2011keyboard\u2011response Display an HTML-formatted stimulus and allow the participant to respond by pressing a key. html\u2011slider\u2011response Display an HTML-formatted stimulus and allow the participant to respond by moving a slider to indicate a value. html\u2011video\u2011response Display an HTML-formatted stimulus and records video data via a webcam. iat\u2011html The implicit association task, using HTML-formatted stimuli. iat\u2011image The implicit association task, using images as stimuli. image\u2011button\u2011response Display an image and allow the participant to respond by choosing a button to click. The button can be customized extensively, e.g., using images in place of standard buttons. image\u2011keyboard\u2011response Display an image and allow the participant to respond by pressing a key. image\u2011slider\u2011response Display an image and allow the participant to respond by moving a slider to indicate a value. initialize\u2011camera Request permission to use the participant's camera to record video and allows the participant to choose which camera to use if multiple devices are enabled. Also allows setting the mime type of the recorded video. initialize\u2011microphone Request permission to use the participant's microphone to record audio and allows the participant to choose which microphone to use if multiple devices are enabled. instructions For displaying instructions to the participant. Allows the participant to navigate between pages of instructions using keys or buttons. maxdiff Displays rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. mirror\u2011camera Shows a live feed of the participant's camera on the screen. preload This plugin loads images, audio, and video files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and to avoid disrupting the flow of the experiment. reconstruction The participant interacts with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time. resize Calibrate the display so that materials display with a known physical size. same\u2011different\u2011html A same-different judgment task. An HTML-formatted stimulus is shown, followed by a brief gap, and then another stimulus is shown. The participant indicates whether the stimuli are the same or different. same\u2011different\u2011image A same-different judgment task. An image is shown, followed by a brief gap, and then another stimulus is shown. The participant indicates whether the stimuli are the same or different. serial\u2011reaction\u2011time A set of boxes are displayed on the screen and one of them changes color. The participant presses a key that corresponds to the different color box as fast as possible. serial\u2011reaction\u2011time\u2011mouse A set of boxes are displayed on the screen and one of them changes color. The participants clicks the box that changed color as fast as possible. sketchpad Creates an interactive canvas that the participant can draw on using their mouse or touchscreen. survey\u2011html\u2011form Renders a custom HTML form. Allows for mixing multiple kinds of form input. survey\u2011likert Displays likert-style questions. survey\u2011multi\u2011choice Displays multiple choice questions with one answer allowed per question. survey\u2011multi\u2011select Displays multiple choice questions with multiple answes allowed per question. survey\u2011text Shows a prompt with a text box. The participant writes a response and then submits by clicking a button. video\u2011button\u2011response Displays a video file with many options for customizing playback. participant responds to the video by pressing a button. video\u2011keyboard\u2011response Displays a video file with many options for customizing playback. participant responds to the video by pressing a key. video\u2011slider\u2011response Displays a video file with many options for customizing playback. participant responds to the video by moving a slider. virtual\u2011chinrest An implementation of the \"virutal chinrest\" procedure developed by Li, Joo, Yeatman, and Reinecke (2020) . Calibrates the monitor to display items at a known physical size by having participants scale an image to be the same size as a physical credit card. Then uses a blind spot task to estimate the distance between the participant and the display. visual\u2011search\u2011circle A customizable visual-search task modelled after Wang, Cavanagh, & Green (1994) . The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. webgazer\u2011calibrate Calibrates the WebGazer extension for eye tracking. webgazer\u2011init\u2011camera Initializes the camera and helps the participant center their face for eye tracking. webgazer\u2011validate Performs validation to measure precision and accuracy of WebGazer eye tracking predictions.","title":"List of Plugins"},{"location":"plugins/maxdiff/","text":"maxdiff \u00b6 Current version: 1.1.3. See version history . The maxdiff plugin displays a table with rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. The same alternative cannot be endorsed on both the left and right response columns (e.g. 'most' and 'least') simultaneously. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description alternatives array undefined An array of one or more alternatives of string type to fill the rows of the maxdiff table. If required is true, then the array must contain two or more alternatives, so that at least one can be selected for both the left and right columns. labels array undefined An array with exactly two labels of string type to display as column headings (to the left and right of the alternatives) for responses on the criteria of interest. randomize_alternative_order boolean false If true, the display order of alternatives is randomly determined at the start of the trial. preamble string empty string HTML formatted string to display at the top of the page above the maxdiff table. required boolean false If true, prevents the user from submitting the response and proceeding until a radio button in both the left and right response columns has been selected. button_label string 'Continue' Label of the button. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the maxdiff table first appears on the screen until the participant's response. labels object An object with two keys, left and right , containing the labels (strings) corresponding to the left and right response columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response object An object with two keys, left and right , containing the alternatives selected on the left and right columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-maxdiff@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-maxdiff.js\" >< /script> Using NPM: npm install @jspsych/plugin-maxdiff import maxdiff from '@jspsych/plugin-maxdiff' ; Examples \u00b6 Basic example Code Demo var maxdiff_page = { type : jsPsychMaxdiff , alternatives : [ 'apple' , 'orange' , 'pear' , 'banana' ], labels : [ 'Most Preferred' , 'Least Preferred' ], preamble : '<p> Please select your <b>most preferred</b> and <b>least preferred</b> fruits. </p>' }; Open demo in new tab","title":"maxdiff"},{"location":"plugins/maxdiff/#maxdiff","text":"Current version: 1.1.3. See version history . The maxdiff plugin displays a table with rows of alternatives to be selected for two mutually-exclusive categories, typically as 'most' or 'least' on a particular criteria (e.g. importance, preference, similarity). The participant responds by selecting one radio button corresponding to an alternative in both the left and right response columns. The same alternative cannot be endorsed on both the left and right response columns (e.g. 'most' and 'least') simultaneously.","title":"maxdiff"},{"location":"plugins/maxdiff/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description alternatives array undefined An array of one or more alternatives of string type to fill the rows of the maxdiff table. If required is true, then the array must contain two or more alternatives, so that at least one can be selected for both the left and right columns. labels array undefined An array with exactly two labels of string type to display as column headings (to the left and right of the alternatives) for responses on the criteria of interest. randomize_alternative_order boolean false If true, the display order of alternatives is randomly determined at the start of the trial. preamble string empty string HTML formatted string to display at the top of the page above the maxdiff table. required boolean false If true, prevents the user from submitting the response and proceeding until a radio button in both the left and right response columns has been selected. button_label string 'Continue' Label of the button.","title":"Parameters"},{"location":"plugins/maxdiff/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the maxdiff table first appears on the screen until the participant's response. labels object An object with two keys, left and right , containing the labels (strings) corresponding to the left and right response columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response object An object with two keys, left and right , containing the alternatives selected on the left and right columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/maxdiff/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-maxdiff@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-maxdiff.js\" >< /script> Using NPM: npm install @jspsych/plugin-maxdiff import maxdiff from '@jspsych/plugin-maxdiff' ;","title":"Install"},{"location":"plugins/maxdiff/#examples","text":"Basic example Code Demo var maxdiff_page = { type : jsPsychMaxdiff , alternatives : [ 'apple' , 'orange' , 'pear' , 'banana' ], labels : [ 'Most Preferred' , 'Least Preferred' ], preamble : '<p> Please select your <b>most preferred</b> and <b>least preferred</b> fruits. </p>' }; Open demo in new tab","title":"Examples"},{"location":"plugins/mirror-camera/","text":"mirror-camera \u00b6 Current version: 1.0.0 See version history . This plugin shows a live feed of the participant's camera. It can be useful in experiments that need to record video in order to give the participant a chance to see what is in the view of the camera. You must initialize the camera using the initialize-camera plugin prior to running this plugin. Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the camera because of potential security problems . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description prompt html string null HTML-formatted content to display below the camera feed. width int null The width of the video playback element. If left null then it will match the size of the recording. height int null The height of the video playback element. If left null then it will match the size of the recording. button_label string \"Continue\" The label of the button to advance to the next trial. mirror_camera bool true Whether to mirror the video image. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt int The length of time the participant viewed the video playback. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-mirror-camera@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-mirror-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-mirror-camera import mirrorCamera from '@jspsych/plugin-mirror-camera' ; Examples \u00b6 Show the camera feed Code Demo const init_camera = { type : jsPsychInitializeCamera , } const mirror_camera = { type : jsPsychMirrorCamera , } Open demo in new tab","title":"mirror-camera"},{"location":"plugins/mirror-camera/#mirror-camera","text":"Current version: 1.0.0 See version history . This plugin shows a live feed of the participant's camera. It can be useful in experiments that need to record video in order to give the participant a chance to see what is in the view of the camera. You must initialize the camera using the initialize-camera plugin prior to running this plugin. Warning When recording from a camera your experiment will need to be running over https:// protocol. If you try to run the experiment locally using the file:// protocol or over http:// protocol you will not be able to access the camera because of potential security problems .","title":"mirror-camera"},{"location":"plugins/mirror-camera/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description prompt html string null HTML-formatted content to display below the camera feed. width int null The width of the video playback element. If left null then it will match the size of the recording. height int null The height of the video playback element. If left null then it will match the size of the recording. button_label string \"Continue\" The label of the button to advance to the next trial. mirror_camera bool true Whether to mirror the video image.","title":"Parameters"},{"location":"plugins/mirror-camera/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt int The length of time the participant viewed the video playback.","title":"Data Generated"},{"location":"plugins/mirror-camera/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/mirror-camera/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-mirror-camera@1.0.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-mirror-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-mirror-camera import mirrorCamera from '@jspsych/plugin-mirror-camera' ;","title":"Install"},{"location":"plugins/mirror-camera/#examples","text":"Show the camera feed Code Demo const init_camera = { type : jsPsychInitializeCamera , } const mirror_camera = { type : jsPsychMirrorCamera , } Open demo in new tab","title":"Examples"},{"location":"plugins/preload/","text":"preload \u00b6 Current version: 1.1.3. See version history . This plugin loads images, audio, and video files. It is used for loading files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and avoid disruption to the experiment flow. We recommend using this plugin anytime you are loading media files, and especially when your experiment requires large and/or many media files. See the Media Preloading page for more information. The preload trial will end as soon as all files have loaded successfully. The trial will end or stop with an error message when one of these two scenarios occurs (whichever comes first): (a) all files have not finished loading when the max_load_time duration is reached, or (b) all file requests have responded with either a load or fail event, and one or more files has failed to load. The continue_after_error parameter determines whether the trial will stop with an error message or end (allowing the experiment to continue) when preloading is not successful. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. While there are no specific parameters that are required, the plugin expects to be given a set of files to load through one or more of the following parameters: auto_preload or trials (for automatic loading), and/or images , audio , video (for manual loading). To automatically load files based on a timeline of trials, either set the auto_preload parameter is true (to load files based on the main timeline passed to jsPsych.run ) or use the trials parameter to load files based on a specific subset of trials. To manually load a set of files, use the images , audio , and video parameters. You can combine automatic and manual loading methods in a single preload trial. All other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description auto_preload boolean false If true , the plugin will preload any files that can be automatically preloaded based on the main experiment timeline that is passed to jsPsych.run . If false , any file(s) to be preloaded should be specified by passing a timeline array to the trials parameter and/or an array of file paths to the images , audio , and/or video parameters. Setting this parameter to false is useful when you plan to preload your files in smaller batches throughout the experiment. trials timeline array [] An array containing one or more jsPsych trial or timeline objects. This parameter is useful when you want to automatically preload stimuli files from a specific subset of the experiment. See Creating an Experiment: The Timeline for information on constructing timelines. images array [] Array containing file paths for one or more image files to preload. This option is typically used for image files that can't be automatically preloaded from the timeline. audio array [] Array containing file paths for one or more audio files to preload. This option is typically used for audio files that can't be automatically preloaded from the timeline. video array [] Array containing file paths for one or more video files to preload. This option is typically used for video files that can't be automatically preloaded from the timeline. message HTML string null HTML-formatted message to show above the progress bar while the files are loading. If null , then no message is shown. show_progress_bar boolean true If true , a progress bar will be shown while the files are loading. If false , no progress bar is shown. continue_after_error boolean false If false , then the experiment will stop during this trial if either (a) one or more of the files fails to load, and/or (b) all files do not finish loading before the max_load_time duration is reached. The trial will display the error_message , as well as the detailed error messages if show_detailed_errors is true . If true , the experiment will continue even if loading fails or times out, and information about loading success/failure will be stored in the trial data (see \"Data Generated\" below). error_message HTML string 'The experiment failed to load.' HTML-formatted message to be shown on the page after loading fails or times out. Only applies when continue_after_error is false . show_detailed_errors boolean false If true , and if continue_after_error is false , then a list of detailed errors will be shown below the error_message . This list will contain the file paths for any files that produced a loading failure, as well as a message indicating that loading timed out, if that was the case. This setting is intended to help the researcher with testing/debugging. If false , and if continue_after_error is false , then only the error_message will be shown if loading fails or times out. max_load_time numeric null Duration to wait, in milliseconds, for all files to load before loading times out. If one or more files has not finished loading within this time limit, then the trial will stop with an error (if continue_after_error is false ), or the trial will end with information about the loading time-out in the trial data (see \"Data Generated\" below). If null , the trial will wait indefinitely for all files to either load or produce an error. on_error function null Function to be called immediately after a file loading request has returned an error. The function receives a single argument, which is the file path that produced the error. This callback is cancelled as soon as the trial ends. See example below. on_success function null Function to be called immediately after a file has successfully loaded. The function receives a single argument, which is the file path that finished loading. This callback is cancelled as soon as the trial ends. See example below. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value success boolean If true , then all files loaded successfully within the max_load_time . If false , then one or more file requests returned a failure and/or the file loading did not complete within the max_load_time duration. timeout boolean If true , then the files did not finish loading within the max_load_time duration. If false , then the file loading did not timeout. Note that when the preload trial does not timeout ( timeout: false ), it is still possible for loading to fail ( success: false ). This happens if one or more files fails to load and all file requests trigger either a success or failure event before the max_load_time duration. failed_images array One or more image file paths that produced a loading failure before the trial ended. failed_audio array One or more audio file paths that produced a loading failure before the trial ended. failed_video array One or more video file paths that produced a loading failure before the trial ended. Simulation Mode \u00b6 In visual simulation mode, the plugin will run the trial as if the experiment was running normally. Specifying simulation_options.data will not work in visual mode. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-preload.js\" >< /script> Using NPM: npm install @jspsych/plugin-preload import preload from '@jspsych/plugin-preload' ; Examples \u00b6 Automatically preloading based on other trials Code Demo var preload = { type : jsPsychPreload , auto_preload : true } var trial_1 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.jpg' , choices : [ 'Next' ] } var trial_2 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_2.jpg' , choices : [ 'Next' ] } var trial_3 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_3.jpg' , choices : [ 'Next' ] } The stimulus parameter from the image-button-response trials will be automatically preloaded. Open demo in new tab Manually preloading an image Code Demo var preload = { type : jsPsychPreload , images : [ 'img/sad_face_1.jpg' ] } var trial_1 = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Study this face</p> <img src=\"img/sad_face_1.jpg\"></img> ` , choices : [ 'Next' ] } Because the image is embedded inside HTML from the html-button-response plugin, it will not be automatically preloaded. Instead we can preload manually. Open demo in new tab Loading files in batches Code Demo var jsPsych = initJsPsych (); var trial_1 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.jpg' , choices : [ 'Next' ] } var trial_2 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_2.jpg' , choices : [ 'Next' ] } var trial_3 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_3.jpg' , choices : [ 'Next' ] } var block_1 = { timeline : [ trial_1 , trial_2 , trial_3 ] } var trial_4 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_1.jpg' , choices : [ 'Next' ] } var trial_5 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_2.jpg' , choices : [ 'Next' ] } var trial_6 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_3.jpg' , choices : [ 'Next' ] } var block_2 = { timeline : [ trial_4 , trial_5 , trial_6 ] } var preload_block_1 = { type : jsPsychPreload , trials : [ block_1 ] } var preload_block_2 = { type : jsPsychPreload , trials : [ block_2 ] } jsPsych . run ([ preload_block_1 , block_1 , preload_block_2 , block_2 ]) You can put trials using the preload plugin throughout your experiment to distribute when files are loaded. In the example above, there are two blocks of trials and the images for each are preloaded just before the corresponding block. Open demo in new tab Showing a detailed error message for debugging loading issues Code Demo var preload = { type : jsPsychPreload , images : [ 'img/bad_file_path.png' ], show_detailed_errors : true } Open demo in new tab For more examples, see the jspsych-preload.html file in the /examples folder of the release and the Media Preloading documentation page.","title":"preload"},{"location":"plugins/preload/#preload","text":"Current version: 1.1.3. See version history . This plugin loads images, audio, and video files. It is used for loading files into the browser's memory before they are needed in the experiment, in order to improve stimulus and response timing, and avoid disruption to the experiment flow. We recommend using this plugin anytime you are loading media files, and especially when your experiment requires large and/or many media files. See the Media Preloading page for more information. The preload trial will end as soon as all files have loaded successfully. The trial will end or stop with an error message when one of these two scenarios occurs (whichever comes first): (a) all files have not finished loading when the max_load_time duration is reached, or (b) all file requests have responded with either a load or fail event, and one or more files has failed to load. The continue_after_error parameter determines whether the trial will stop with an error message or end (allowing the experiment to continue) when preloading is not successful.","title":"preload"},{"location":"plugins/preload/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. While there are no specific parameters that are required, the plugin expects to be given a set of files to load through one or more of the following parameters: auto_preload or trials (for automatic loading), and/or images , audio , video (for manual loading). To automatically load files based on a timeline of trials, either set the auto_preload parameter is true (to load files based on the main timeline passed to jsPsych.run ) or use the trials parameter to load files based on a specific subset of trials. To manually load a set of files, use the images , audio , and video parameters. You can combine automatic and manual loading methods in a single preload trial. All other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description auto_preload boolean false If true , the plugin will preload any files that can be automatically preloaded based on the main experiment timeline that is passed to jsPsych.run . If false , any file(s) to be preloaded should be specified by passing a timeline array to the trials parameter and/or an array of file paths to the images , audio , and/or video parameters. Setting this parameter to false is useful when you plan to preload your files in smaller batches throughout the experiment. trials timeline array [] An array containing one or more jsPsych trial or timeline objects. This parameter is useful when you want to automatically preload stimuli files from a specific subset of the experiment. See Creating an Experiment: The Timeline for information on constructing timelines. images array [] Array containing file paths for one or more image files to preload. This option is typically used for image files that can't be automatically preloaded from the timeline. audio array [] Array containing file paths for one or more audio files to preload. This option is typically used for audio files that can't be automatically preloaded from the timeline. video array [] Array containing file paths for one or more video files to preload. This option is typically used for video files that can't be automatically preloaded from the timeline. message HTML string null HTML-formatted message to show above the progress bar while the files are loading. If null , then no message is shown. show_progress_bar boolean true If true , a progress bar will be shown while the files are loading. If false , no progress bar is shown. continue_after_error boolean false If false , then the experiment will stop during this trial if either (a) one or more of the files fails to load, and/or (b) all files do not finish loading before the max_load_time duration is reached. The trial will display the error_message , as well as the detailed error messages if show_detailed_errors is true . If true , the experiment will continue even if loading fails or times out, and information about loading success/failure will be stored in the trial data (see \"Data Generated\" below). error_message HTML string 'The experiment failed to load.' HTML-formatted message to be shown on the page after loading fails or times out. Only applies when continue_after_error is false . show_detailed_errors boolean false If true , and if continue_after_error is false , then a list of detailed errors will be shown below the error_message . This list will contain the file paths for any files that produced a loading failure, as well as a message indicating that loading timed out, if that was the case. This setting is intended to help the researcher with testing/debugging. If false , and if continue_after_error is false , then only the error_message will be shown if loading fails or times out. max_load_time numeric null Duration to wait, in milliseconds, for all files to load before loading times out. If one or more files has not finished loading within this time limit, then the trial will stop with an error (if continue_after_error is false ), or the trial will end with information about the loading time-out in the trial data (see \"Data Generated\" below). If null , the trial will wait indefinitely for all files to either load or produce an error. on_error function null Function to be called immediately after a file loading request has returned an error. The function receives a single argument, which is the file path that produced the error. This callback is cancelled as soon as the trial ends. See example below. on_success function null Function to be called immediately after a file has successfully loaded. The function receives a single argument, which is the file path that finished loading. This callback is cancelled as soon as the trial ends. See example below.","title":"Parameters"},{"location":"plugins/preload/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value success boolean If true , then all files loaded successfully within the max_load_time . If false , then one or more file requests returned a failure and/or the file loading did not complete within the max_load_time duration. timeout boolean If true , then the files did not finish loading within the max_load_time duration. If false , then the file loading did not timeout. Note that when the preload trial does not timeout ( timeout: false ), it is still possible for loading to fail ( success: false ). This happens if one or more files fails to load and all file requests trigger either a success or failure event before the max_load_time duration. failed_images array One or more image file paths that produced a loading failure before the trial ended. failed_audio array One or more audio file paths that produced a loading failure before the trial ended. failed_video array One or more video file paths that produced a loading failure before the trial ended.","title":"Data Generated"},{"location":"plugins/preload/#simulation-mode","text":"In visual simulation mode, the plugin will run the trial as if the experiment was running normally. Specifying simulation_options.data will not work in visual mode.","title":"Simulation Mode"},{"location":"plugins/preload/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-preload.js\" >< /script> Using NPM: npm install @jspsych/plugin-preload import preload from '@jspsych/plugin-preload' ;","title":"Install"},{"location":"plugins/preload/#examples","text":"Automatically preloading based on other trials Code Demo var preload = { type : jsPsychPreload , auto_preload : true } var trial_1 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.jpg' , choices : [ 'Next' ] } var trial_2 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_2.jpg' , choices : [ 'Next' ] } var trial_3 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_3.jpg' , choices : [ 'Next' ] } The stimulus parameter from the image-button-response trials will be automatically preloaded. Open demo in new tab Manually preloading an image Code Demo var preload = { type : jsPsychPreload , images : [ 'img/sad_face_1.jpg' ] } var trial_1 = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>Study this face</p> <img src=\"img/sad_face_1.jpg\"></img> ` , choices : [ 'Next' ] } Because the image is embedded inside HTML from the html-button-response plugin, it will not be automatically preloaded. Instead we can preload manually. Open demo in new tab Loading files in batches Code Demo var jsPsych = initJsPsych (); var trial_1 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_1.jpg' , choices : [ 'Next' ] } var trial_2 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_2.jpg' , choices : [ 'Next' ] } var trial_3 = { type : jsPsychImageButtonResponse , stimulus : 'img/happy_face_3.jpg' , choices : [ 'Next' ] } var block_1 = { timeline : [ trial_1 , trial_2 , trial_3 ] } var trial_4 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_1.jpg' , choices : [ 'Next' ] } var trial_5 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_2.jpg' , choices : [ 'Next' ] } var trial_6 = { type : jsPsychImageButtonResponse , stimulus : 'img/sad_face_3.jpg' , choices : [ 'Next' ] } var block_2 = { timeline : [ trial_4 , trial_5 , trial_6 ] } var preload_block_1 = { type : jsPsychPreload , trials : [ block_1 ] } var preload_block_2 = { type : jsPsychPreload , trials : [ block_2 ] } jsPsych . run ([ preload_block_1 , block_1 , preload_block_2 , block_2 ]) You can put trials using the preload plugin throughout your experiment to distribute when files are loaded. In the example above, there are two blocks of trials and the images for each are preloaded just before the corresponding block. Open demo in new tab Showing a detailed error message for debugging loading issues Code Demo var preload = { type : jsPsychPreload , images : [ 'img/bad_file_path.png' ], show_detailed_errors : true } Open demo in new tab For more examples, see the jspsych-preload.html file in the /examples folder of the release and the Media Preloading documentation page.","title":"Examples"},{"location":"plugins/reconstruction/","text":"reconstruction \u00b6 Current version: 1.1.3. See version history . This plugin allows a participant to interact with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time. The stimulus must be defined through a function that returns an HTML-formatted string. The function should take a single value, which is the parameter that can be modified by the participant. The value can only range from 0 to 1. See the example at the bottom of the page for a sample function. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stim_function function undefined A function with a single parameter that returns an HTML-formatted string representing the stimulus. starting_value numeric 0.5 The starting value of the stimulus parameter. step_size numeric 0.05 The change in the stimulus parameter caused by pressing one of the modification keys. key_increase string 'h' The key to press for increasing the parameter value. key_decrease string 'g' The key to press for decreasing the parameter value. button_label string 'Continue' The text that appears on the button to finish the trial. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value start_value numeric The starting value of the stimulus parameter. final_value numeric The final value of the stimulus parameter. rt numeric The length of time, in milliseconds, that the trial lasted. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-reconstruction@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-reconstruction.js\" >< /script> Using NPM: npm install @jspsych/plugin-reconstruction import reconstruction from '@jspsych/plugin-reconstruction' ; Examples \u00b6 Make a block larger and smaller Code Demo var sample_function = function ( param ){ var size = 50 + Math . floor ( param * 250 ); var html = '<div style=\"display: block; margin: auto; height: 300px; width: 300px; position: relative;\">' + '<div style=\"display: block; position: absolute; top: ' + ( 150 - size / 2 ) + 'px; left:' + ( 150 - size / 2 ) + 'px; background-color: #000000; ' + 'width: ' + size + 'px; height: ' + size + 'px;\"></div></div><p>Press \"h\" to make the square larger. Press \"g\" to make the square smaller.</p>' + '<p>When the square is the same size as the previous one, click Continue.</p>' ; return html ; } var match_item = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"display: block; margin: auto; height: 300px; width: 300px; position: relative;\">' + '<div style=\"display: block; position: absolute; top: ' + ( 150 - 210 / 2 ) + 'px; left:' + ( 150 - 210 / 2 ) + 'px; background-color: #000000; ' + 'width: 210px; height: 210px;\"></div></div>' , choices : [ 'c' ], post_trial_gap : 1250 , prompt : '<p>Study the size of this square carefully. On the next screen you will have to recreate it. When you are ready, press \"c\".</p>' } var reconstruction = { type : jsPsychReconstruction , stim_function : sample_function , starting_value : 0.5 , } Open demo in new tab","title":"reconstruction"},{"location":"plugins/reconstruction/#reconstruction","text":"Current version: 1.1.3. See version history . This plugin allows a participant to interact with a stimulus by modifying a parameter of the stimulus and observing the change in the stimulus in real-time. The stimulus must be defined through a function that returns an HTML-formatted string. The function should take a single value, which is the parameter that can be modified by the participant. The value can only range from 0 to 1. See the example at the bottom of the page for a sample function.","title":"reconstruction"},{"location":"plugins/reconstruction/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stim_function function undefined A function with a single parameter that returns an HTML-formatted string representing the stimulus. starting_value numeric 0.5 The starting value of the stimulus parameter. step_size numeric 0.05 The change in the stimulus parameter caused by pressing one of the modification keys. key_increase string 'h' The key to press for increasing the parameter value. key_decrease string 'g' The key to press for decreasing the parameter value. button_label string 'Continue' The text that appears on the button to finish the trial.","title":"Parameters"},{"location":"plugins/reconstruction/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value start_value numeric The starting value of the stimulus parameter. final_value numeric The final value of the stimulus parameter. rt numeric The length of time, in milliseconds, that the trial lasted.","title":"Data Generated"},{"location":"plugins/reconstruction/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-reconstruction@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-reconstruction.js\" >< /script> Using NPM: npm install @jspsych/plugin-reconstruction import reconstruction from '@jspsych/plugin-reconstruction' ;","title":"Install"},{"location":"plugins/reconstruction/#examples","text":"Make a block larger and smaller Code Demo var sample_function = function ( param ){ var size = 50 + Math . floor ( param * 250 ); var html = '<div style=\"display: block; margin: auto; height: 300px; width: 300px; position: relative;\">' + '<div style=\"display: block; position: absolute; top: ' + ( 150 - size / 2 ) + 'px; left:' + ( 150 - size / 2 ) + 'px; background-color: #000000; ' + 'width: ' + size + 'px; height: ' + size + 'px;\"></div></div><p>Press \"h\" to make the square larger. Press \"g\" to make the square smaller.</p>' + '<p>When the square is the same size as the previous one, click Continue.</p>' ; return html ; } var match_item = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"display: block; margin: auto; height: 300px; width: 300px; position: relative;\">' + '<div style=\"display: block; position: absolute; top: ' + ( 150 - 210 / 2 ) + 'px; left:' + ( 150 - 210 / 2 ) + 'px; background-color: #000000; ' + 'width: 210px; height: 210px;\"></div></div>' , choices : [ 'c' ], post_trial_gap : 1250 , prompt : '<p>Study the size of this square carefully. On the next screen you will have to recreate it. When you are ready, press \"c\".</p>' } var reconstruction = { type : jsPsychReconstruction , stim_function : sample_function , starting_value : 0.5 , } Open demo in new tab","title":"Examples"},{"location":"plugins/resize/","text":"resize \u00b6 Current version: 1.0.3. See version history . This plugin displays a resizable div container that allows the user to drag until the container is the same size as the item being measured. Once the user measures the item as close as possible, clicking the button sets a scaling factor for the div containing jsPsych content. This causes the stimuli that follow to have a known size, independent of monitor resolution. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description item_height numeric 1 The height of the item to be measured. Any units can be used as long as you are consistent with using the same units for all parameters. item_width numeric 1 The width of the item to be measured. pixels_per_unit numeric 100 After the scaling factor is applied, this many pixels will equal one unit of measurement. prompt string '' HTML content to display below the resizable box, and above the button. button_label string 'Continue' Label to display on the button to complete calibration. starting_size numeric 100 The initial size of the box, in pixels, along the largest dimension. The aspect ratio will be set automatically to match the item width and height. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value final_width_px numeric Final width of the resizable div container, in pixels. scale_factor numeric Scaling factor that will be applied to the div containing jsPsych content. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-resize@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-resize.js\" >< /script> Using NPM: npm install @jspsych/plugin-resize import resize from '@jspsych/plugin-resize' ; Examples \u00b6 Measuring a credit card and resizing the display to have 150 pixels equal an inch. Code Demo var inputs = { type : jsPsychResize , item_width : 3 + 3 / 8 , item_height : 2 + 1 / 8 , prompt : \"<p>Click and drag the lower right corner of the box until the box is the same size as a credit card held up to the screen.</p>\" , pixels_per_unit : 150 }; Open demo in new tab","title":"resize"},{"location":"plugins/resize/#resize","text":"Current version: 1.0.3. See version history . This plugin displays a resizable div container that allows the user to drag until the container is the same size as the item being measured. Once the user measures the item as close as possible, clicking the button sets a scaling factor for the div containing jsPsych content. This causes the stimuli that follow to have a known size, independent of monitor resolution.","title":"resize"},{"location":"plugins/resize/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description item_height numeric 1 The height of the item to be measured. Any units can be used as long as you are consistent with using the same units for all parameters. item_width numeric 1 The width of the item to be measured. pixels_per_unit numeric 100 After the scaling factor is applied, this many pixels will equal one unit of measurement. prompt string '' HTML content to display below the resizable box, and above the button. button_label string 'Continue' Label to display on the button to complete calibration. starting_size numeric 100 The initial size of the box, in pixels, along the largest dimension. The aspect ratio will be set automatically to match the item width and height.","title":"Parameters"},{"location":"plugins/resize/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value final_width_px numeric Final width of the resizable div container, in pixels. scale_factor numeric Scaling factor that will be applied to the div containing jsPsych content.","title":"Data Generated"},{"location":"plugins/resize/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/resize/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-resize@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-resize.js\" >< /script> Using NPM: npm install @jspsych/plugin-resize import resize from '@jspsych/plugin-resize' ;","title":"Install"},{"location":"plugins/resize/#examples","text":"Measuring a credit card and resizing the display to have 150 pixels equal an inch. Code Demo var inputs = { type : jsPsychResize , item_width : 3 + 3 / 8 , item_height : 2 + 1 / 8 , prompt : \"<p>Click and drag the lower right corner of the box until the box is the same size as a credit card held up to the screen.</p>\" , pixels_per_unit : 150 }; Open demo in new tab","title":"Examples"},{"location":"plugins/same-different-html/","text":"same-different-html \u00b6 Current version: 1.1.3. See version history . The same-different-html plugin displays two stimuli sequentially. Stimuli are HTML objects. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined A pair of stimuli, represented as an array with two entries, one for each stimulus. A stimulus is a string containing valid HTML markup. Stimuli will be shown in the order that they are defined in the array. answer string undefined Either 'same' or 'different' . same_key string 'q' The key that participants should press to indicate that the two stimuli are the same. different_key string 'p' The key that participants should press to indicate that the two stimuli are different. first_stim_duration numeric 1000 How long to show the first stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant presses any key. gap_duration numeric 500 How long to show a blank screen in between the two stimuli. second_stim_duration numeric 1000 How long to show the second stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant responds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array An array of length 2 containing the HTML-formatted content that the participant saw for each trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the answer for this trial. answer string The correct answer to the trial, either 'same' or 'different' . Additionally, if first_stim_duration is null, then the following data is also collected: Name Type Value rt_stim1 numeric The response time in milliseconds for the participant to continue after the first stimulus. The time is measured from when the first stimulus appears on the screen until the participant's response. response_stim1 string Indicates which key the participant pressed to continue. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-same-different-html@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-same-different-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-same-different-html import sameDifferentHtml from '@jspsych/plugin-same-different-html' ; Examples \u00b6 Two text choices Code Demo var trial = { type : jsPsychSameDifferentHtml , stimuli : [ '<p style=\"font-size:30px;\">Climbing</p>' , '<p style=\"font-size:30px;\">Walking</p>' ], prompt : `<p>Press 's' if the activities require the same amount of physical exertion.</p> <p>Press 'd' if the activities require different amount of physical exertion.</p>` , same_key : 's' , different_key : 'd' , first_stim_duration : 800 , answer : 'different' } Open demo in new tab","title":"same-different-html"},{"location":"plugins/same-different-html/#same-different-html","text":"Current version: 1.1.3. See version history . The same-different-html plugin displays two stimuli sequentially. Stimuli are HTML objects. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example.","title":"same-different-html"},{"location":"plugins/same-different-html/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined A pair of stimuli, represented as an array with two entries, one for each stimulus. A stimulus is a string containing valid HTML markup. Stimuli will be shown in the order that they are defined in the array. answer string undefined Either 'same' or 'different' . same_key string 'q' The key that participants should press to indicate that the two stimuli are the same. different_key string 'p' The key that participants should press to indicate that the two stimuli are different. first_stim_duration numeric 1000 How long to show the first stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant presses any key. gap_duration numeric 500 How long to show a blank screen in between the two stimuli. second_stim_duration numeric 1000 How long to show the second stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant responds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press).","title":"Parameters"},{"location":"plugins/same-different-html/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array An array of length 2 containing the HTML-formatted content that the participant saw for each trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the answer for this trial. answer string The correct answer to the trial, either 'same' or 'different' . Additionally, if first_stim_duration is null, then the following data is also collected: Name Type Value rt_stim1 numeric The response time in milliseconds for the participant to continue after the first stimulus. The time is measured from when the first stimulus appears on the screen until the participant's response. response_stim1 string Indicates which key the participant pressed to continue.","title":"Data Generated"},{"location":"plugins/same-different-html/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-same-different-html@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-same-different-html.js\" >< /script> Using NPM: npm install @jspsych/plugin-same-different-html import sameDifferentHtml from '@jspsych/plugin-same-different-html' ;","title":"Install"},{"location":"plugins/same-different-html/#examples","text":"Two text choices Code Demo var trial = { type : jsPsychSameDifferentHtml , stimuli : [ '<p style=\"font-size:30px;\">Climbing</p>' , '<p style=\"font-size:30px;\">Walking</p>' ], prompt : `<p>Press 's' if the activities require the same amount of physical exertion.</p> <p>Press 'd' if the activities require different amount of physical exertion.</p>` , same_key : 's' , different_key : 'd' , first_stim_duration : 800 , answer : 'different' } Open demo in new tab","title":"Examples"},{"location":"plugins/same-different-image/","text":"same-different-image \u00b6 Current version: 1.1.3. See version history . The same-different-image plugin displays two stimuli sequentially. Stimuli are images. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined A pair of stimuli, represented as an array with two entries, one for each stimulus. The stimulus is a path to an image file. Stimuli will be shown in the order that they are defined in the array. answer string undefined Either 'same' or 'different' . same_key string 'q' The key that participants should press to indicate that the two stimuli are the same. different_key string 'p' The key that participants should press to indicate that the two stimuli are different. first_stim_duration numeric 1000 How long to show the first stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant presses any key. gap_duration numeric 500 How long to show a blank screen in between the two stimuli. second_stim_duration numeric 1000 How long to show the second stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant responds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array An array of length 2 containing the paths to the image files that the participant saw for each trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the answer for this trial. answer string The correct answer to the trial, either 'same' or 'different' . Additionally, if first_stim_duration is null, then the following data is also collected: Name Type Value rt_stim1 numeric The response time in milliseconds for the participant to continue after the first stimulus. The time is measured from when the first stimulus appears on the screen until the participant's response. response_stim1 string Indicates which key the participant pressed to continue. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-same-different-image@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-same-different-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-same-different-image import sameDifferentImage from '@jspsych/plugin-same-different-image' ; Examples \u00b6 Identifying emotional expressions Code Demo var trial = { type : jsPsychSameDifferentImage , stimuli : [ 'img/happy_face_1.jpg' , 'img/sad_face_3.jpg' ], prompt : `<p>Press s if the faces had the same emotional expression.</p> <p>Press d if the faces had different emotional expressions.</p>` , same_key : 's' , different_key : 'd' , first_stim_duration : 800 , answer : 'different' } Open demo in new tab","title":"same-different-image"},{"location":"plugins/same-different-image/#same-different-image","text":"Current version: 1.1.3. See version history . The same-different-image plugin displays two stimuli sequentially. Stimuli are images. The participant responds using the keyboard, and indicates whether the stimuli were the same or different. Same does not necessarily mean identical; a category judgment could be made, for example.","title":"same-different-image"},{"location":"plugins/same-different-image/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimuli array undefined A pair of stimuli, represented as an array with two entries, one for each stimulus. The stimulus is a path to an image file. Stimuli will be shown in the order that they are defined in the array. answer string undefined Either 'same' or 'different' . same_key string 'q' The key that participants should press to indicate that the two stimuli are the same. different_key string 'p' The key that participants should press to indicate that the two stimuli are different. first_stim_duration numeric 1000 How long to show the first stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant presses any key. gap_duration numeric 500 How long to show a blank screen in between the two stimuli. second_stim_duration numeric 1000 How long to show the second stimulus for in milliseconds. If the value of this parameter is null then the stimulus will be shown until the participant responds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press).","title":"Parameters"},{"location":"plugins/same-different-image/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value stimulus array An array of length 2 containing the paths to the image files that the participant saw for each trial. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the answer for this trial. answer string The correct answer to the trial, either 'same' or 'different' . Additionally, if first_stim_duration is null, then the following data is also collected: Name Type Value rt_stim1 numeric The response time in milliseconds for the participant to continue after the first stimulus. The time is measured from when the first stimulus appears on the screen until the participant's response. response_stim1 string Indicates which key the participant pressed to continue.","title":"Data Generated"},{"location":"plugins/same-different-image/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-same-different-image@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-same-different-image.js\" >< /script> Using NPM: npm install @jspsych/plugin-same-different-image import sameDifferentImage from '@jspsych/plugin-same-different-image' ;","title":"Install"},{"location":"plugins/same-different-image/#examples","text":"Identifying emotional expressions Code Demo var trial = { type : jsPsychSameDifferentImage , stimuli : [ 'img/happy_face_1.jpg' , 'img/sad_face_3.jpg' ], prompt : `<p>Press s if the faces had the same emotional expression.</p> <p>Press d if the faces had different emotional expressions.</p>` , same_key : 's' , different_key : 'd' , first_stim_duration : 800 , answer : 'different' } Open demo in new tab","title":"Examples"},{"location":"plugins/serial-reaction-time-mouse/","text":"serial-reaction-time-mouse \u00b6 Current version: 1.1.3. See version history . The serial reaction time mouse plugin implements a generalized version of the SRT task (Nissen & Bullmer, 1987) . Squares are displayed in a grid-based system on the screen, and one square changes color. The participant must click on the square that changes color. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target array undefined The location of the target. The array should be the [row, column] of the target. grid array [[1,1,1,1]] This array represents the grid of boxes shown on the screen. Each inner array represents a single row. The entries in the inner arrays represent the columns. If an entry is 1 then a square will be drawn at that location on the grid. If an entry is 0 then the corresponding location on the grid will be empty. Thus, by mixing 1 s and 0 s it is possible to create many different grid-based arrangements. grid_square_size numeric 100 The width and height in pixels of each square in the grid. target_color hex color code #999 The color of the target square. response_ends_trial boolean true If true, the trial ends after a mouse click. Feedback is displayed if show_response_feedback is true. pre_target_duration numeric 0 The number of milliseconds to display the grid before the target changes color. trial_duration numeric null The maximum length of time of the trial, not including feedback. fade_duration numeric null If a positive number, the target will progressively change color at the start of the trial, with the transition lasting this many milliseconds. allow_nontarget_responses boolean false If true, the user can make nontarget response. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which keys to press). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value grid array The grid representation. Each inner array represents a single row. The entries in the inner arrays represent the columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. target array The [row, column] target location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. response array The [row, column] response location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. correct boolean Whether the response location matches the target location ( true ) or not ( false ). Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-serial-reaction-time-mouse.js\" >< /script> Using NPM: npm install @jspsych/plugin-serial-reaction-time-mouse import serialReactionTimeMouse from '@jspsych/plugin-serial-reaction-time-mouse' ; Examples \u00b6 A classic version of the SRT Code Demo var grid = [ [ 1 , 1 , 1 , 1 ] ] var trial_1 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 0 ] } var trial_2 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 1 ] } var trial_3 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 2 ] } var trial_4 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 3 ] } Open demo in new tab A 2x2 grid with extra space and different colors Code Demo var grid = [ [ 1 , 0 , 1 ], [ 0 , 0 , 0 ], [ 1 , 0 , 1 ] ] var trial_1 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 0 ], target_color : '#006738' } var trial_2 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 2 ], target_color : '#F78F1E' } var trial_3 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 2 , 2 ], target_color : '#13B24B' } var trial_4 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 2 , 0 ], target_color : '#E74921' } Open demo in new tab","title":"serial-reaction-time-mouse"},{"location":"plugins/serial-reaction-time-mouse/#serial-reaction-time-mouse","text":"Current version: 1.1.3. See version history . The serial reaction time mouse plugin implements a generalized version of the SRT task (Nissen & Bullmer, 1987) . Squares are displayed in a grid-based system on the screen, and one square changes color. The participant must click on the square that changes color.","title":"serial-reaction-time-mouse"},{"location":"plugins/serial-reaction-time-mouse/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target array undefined The location of the target. The array should be the [row, column] of the target. grid array [[1,1,1,1]] This array represents the grid of boxes shown on the screen. Each inner array represents a single row. The entries in the inner arrays represent the columns. If an entry is 1 then a square will be drawn at that location on the grid. If an entry is 0 then the corresponding location on the grid will be empty. Thus, by mixing 1 s and 0 s it is possible to create many different grid-based arrangements. grid_square_size numeric 100 The width and height in pixels of each square in the grid. target_color hex color code #999 The color of the target square. response_ends_trial boolean true If true, the trial ends after a mouse click. Feedback is displayed if show_response_feedback is true. pre_target_duration numeric 0 The number of milliseconds to display the grid before the target changes color. trial_duration numeric null The maximum length of time of the trial, not including feedback. fade_duration numeric null If a positive number, the target will progressively change color at the start of the trial, with the transition lasting this many milliseconds. allow_nontarget_responses boolean false If true, the user can make nontarget response. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which keys to press).","title":"Parameters"},{"location":"plugins/serial-reaction-time-mouse/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value grid array The grid representation. Each inner array represents a single row. The entries in the inner arrays represent the columns. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. target array The [row, column] target location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. response array The [row, column] response location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. correct boolean Whether the response location matches the target location ( true ) or not ( false ).","title":"Data Generated"},{"location":"plugins/serial-reaction-time-mouse/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-serial-reaction-time-mouse@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-serial-reaction-time-mouse.js\" >< /script> Using NPM: npm install @jspsych/plugin-serial-reaction-time-mouse import serialReactionTimeMouse from '@jspsych/plugin-serial-reaction-time-mouse' ;","title":"Install"},{"location":"plugins/serial-reaction-time-mouse/#examples","text":"A classic version of the SRT Code Demo var grid = [ [ 1 , 1 , 1 , 1 ] ] var trial_1 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 0 ] } var trial_2 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 1 ] } var trial_3 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 2 ] } var trial_4 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 3 ] } Open demo in new tab A 2x2 grid with extra space and different colors Code Demo var grid = [ [ 1 , 0 , 1 ], [ 0 , 0 , 0 ], [ 1 , 0 , 1 ] ] var trial_1 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 0 ], target_color : '#006738' } var trial_2 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 0 , 2 ], target_color : '#F78F1E' } var trial_3 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 2 , 2 ], target_color : '#13B24B' } var trial_4 = { type : jsPsychSerialReactionTimeMouse , grid : grid , target : [ 2 , 0 ], target_color : '#E74921' } Open demo in new tab","title":"Examples"},{"location":"plugins/serial-reaction-time/","text":"serial-reaction-time \u00b6 Current version: 1.1.4. See version history . The serial reaction time plugin implements a generalized version of the SRT task (Nissen & Bullemer, 1987) . Squares are displayed in a grid-based system on the screen, and one square changes color. The participant presses a key that corresponds to the darkened key. Feedback is optionally displayed, showing the participant which square the key they pressed matches. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target array undefined The location of the target. The array should be the [row, column] of the target. grid array [[1,1,1,1]] This array represents the grid of boxes shown on the screen. Each inner array represents a single row. The entries in the inner arrays represent the columns. If an entry is 1 then a square will be drawn at that location on the grid. If an entry is 0 then the corresponding location on the grid will be empty. Thus, by mixing 1 s and 0 s it is possible to create many different grid-based arrangements. choices array of strings [['3','5','7','9']] The dimensions of this array must match the dimensions of grid . Each entry in this array is the key that should be pressed for that corresponding location in the grid. Entries can be left blank if there is no key associated with that location of the grid. grid_square_size numeric 100 The width and height in pixels of each square in the grid. target_color hex color code #999 The color of the target square. response_ends_trial boolean true If true, the trial ends after a key press. Feedback is displayed if show_response_feedback is true. pre_target_duration numeric 0 The number of milliseconds to display the grid before the target changes color. trial_duration numeric null The maximum length of time of the trial, not including feedback. show_response_feedback boolean false If true, show feedback indicating where the user responded and whether it was correct. feedback_duration numeric 200 The length of time in milliseconds to show the feedback. fade_duration numeric null If a positive number, the target will progressively change color at the start of the trial, with the transition lasting this many milliseconds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which keys to press). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value grid array The representation of the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. target array The representation of the target location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the target. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.4\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-serial-reaction-time.js\" >< /script> Using NPM: npm install @jspsych/plugin-serial-reaction-time import serialReactionTime from '@jspsych/plugin-serial-reaction-time' ; Examples \u00b6 A classic SRT Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : '<p>Use the S, F, H, and K keys to respond.</p>' , choices : [ 'Continue' ] } var grid = [ [ 1 , 1 , 1 , 1 ] ] var response_map = [ [ 's' , 'f' , 'h' , 'k' ] ] var trial_1 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 0 ] } var trial_2 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 1 ] } var trial_3 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 2 ] } var trial_4 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 3 ] } Open demo in new tab 2x2 grid with feedback Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : '<p>Use the R, I, V, and M keys to respond.</p>' , choices : [ 'Continue' ] } var grid = [ [ 1 , 1 ], [ 1 , 1 ] ] var response_map = [ [ 'r' , 'i' ], [ 'v' , 'm' ] ] var trial_1 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 0 ], show_response_feedback : true , feedback_duration : 500 } var trial_2 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 1 ], show_response_feedback : true , feedback_duration : 500 } var trial_3 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 1 , 1 ], show_response_feedback : true , feedback_duration : 500 } var trial_4 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 1 , 0 ], show_response_feedback : true , feedback_duration : 500 } Open demo in new tab","title":"serial-reaction-time"},{"location":"plugins/serial-reaction-time/#serial-reaction-time","text":"Current version: 1.1.4. See version history . The serial reaction time plugin implements a generalized version of the SRT task (Nissen & Bullemer, 1987) . Squares are displayed in a grid-based system on the screen, and one square changes color. The participant presses a key that corresponds to the darkened key. Feedback is optionally displayed, showing the participant which square the key they pressed matches.","title":"serial-reaction-time"},{"location":"plugins/serial-reaction-time/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target array undefined The location of the target. The array should be the [row, column] of the target. grid array [[1,1,1,1]] This array represents the grid of boxes shown on the screen. Each inner array represents a single row. The entries in the inner arrays represent the columns. If an entry is 1 then a square will be drawn at that location on the grid. If an entry is 0 then the corresponding location on the grid will be empty. Thus, by mixing 1 s and 0 s it is possible to create many different grid-based arrangements. choices array of strings [['3','5','7','9']] The dimensions of this array must match the dimensions of grid . Each entry in this array is the key that should be pressed for that corresponding location in the grid. Entries can be left blank if there is no key associated with that location of the grid. grid_square_size numeric 100 The width and height in pixels of each square in the grid. target_color hex color code #999 The color of the target square. response_ends_trial boolean true If true, the trial ends after a key press. Feedback is displayed if show_response_feedback is true. pre_target_duration numeric 0 The number of milliseconds to display the grid before the target changes color. trial_duration numeric null The maximum length of time of the trial, not including feedback. show_response_feedback boolean false If true, show feedback indicating where the user responded and whether it was correct. feedback_duration numeric 200 The length of time in milliseconds to show the feedback. fade_duration numeric null If a positive number, the target will progressively change color at the start of the trial, with the transition lasting this many milliseconds. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which keys to press).","title":"Parameters"},{"location":"plugins/serial-reaction-time/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value grid array The representation of the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. target array The representation of the target location on the grid. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the second stimulus first appears on the screen until the participant's response. correct boolean true if the participant's response matched the target.","title":"Data Generated"},{"location":"plugins/serial-reaction-time/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-serial-reaction-time@1.1.4\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-serial-reaction-time.js\" >< /script> Using NPM: npm install @jspsych/plugin-serial-reaction-time import serialReactionTime from '@jspsych/plugin-serial-reaction-time' ;","title":"Install"},{"location":"plugins/serial-reaction-time/#examples","text":"A classic SRT Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : '<p>Use the S, F, H, and K keys to respond.</p>' , choices : [ 'Continue' ] } var grid = [ [ 1 , 1 , 1 , 1 ] ] var response_map = [ [ 's' , 'f' , 'h' , 'k' ] ] var trial_1 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 0 ] } var trial_2 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 1 ] } var trial_3 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 2 ] } var trial_4 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 3 ] } Open demo in new tab 2x2 grid with feedback Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : '<p>Use the R, I, V, and M keys to respond.</p>' , choices : [ 'Continue' ] } var grid = [ [ 1 , 1 ], [ 1 , 1 ] ] var response_map = [ [ 'r' , 'i' ], [ 'v' , 'm' ] ] var trial_1 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 0 ], show_response_feedback : true , feedback_duration : 500 } var trial_2 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 0 , 1 ], show_response_feedback : true , feedback_duration : 500 } var trial_3 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 1 , 1 ], show_response_feedback : true , feedback_duration : 500 } var trial_4 = { type : jsPsychSerialReactionTime , grid : grid , choices : response_map , target : [ 1 , 0 ], show_response_feedback : true , feedback_duration : 500 } Open demo in new tab","title":"Examples"},{"location":"plugins/sketchpad/","text":"sketchpad \u00b6 Current version: 1.0.4. See version history . This plugin creates an interactive canvas that the participant can draw on using their mouse or touchscreen. It can be used for sketching tasks, like asking the participant to draw a particular object. It can also be used for some image segmentation or annotation tasks by setting the background_image parameter to render an image on the canvas. The plugin stores a base 64 data URL representation of the final image. This can be converted to an image file using online tools or short programs in R , python , or another language of your choice. It also records all of the individual strokes that the participant made during the trial. Warning This plugin generates a lot of data. Each trial can easily add 500kb+ of data to a final JSON output. You can reduce the amount of data generated by turning off storage of the individual stroke data ( save_strokes: false ) or storage of the final image ( save_final_image: false ) if your use case doesn't require that information. If you are going to be collecting a lot of data with this plugin you may want to save your data to your server after each trial and not wait until the end of the experiment to perform a single bulk upload. You can do this by putting data saving code inside the on_data_update event handler . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameter Type Default Value Description canvas_shape \"rectangle\" or \"circle\" \"rectangle\" The shape of the canvas element. canvas_width int 500 Width of the canvas in pixels when canvas_shape is a \"rectangle\" . canvas_height int 500 Height of the canvas in pixels when canvas_shape is a \"rectangle\" . canvas_diameter int 500 Diameter of the canvas in pixels when canvas_shape is a \"circle\" . canvas_border_width int 0 Width of the canvas border. canvas_border_color string \"#000\" Color of the canvas border. background_image image path null Path to an image to render as the background of the canvas. background_color string \"#fff\" Color of the canvas background. Note that a background_image will render on top of the color. stroke_width int 2 Width of the stroke on the canvas. stroke_color string \"#000\" Color of the stroke on the canvas. stroke_color_palette array of strings [] Array of colors to render as a palette of choices for stroke color. Clicking on the corresponding color button will change the stroke color. prompt string null HTML content to render on the screen. prompt_location \"abovecanvas\" or \"belowcanvas\" or \"belowbutton\" \"abovecanvas\" The location to render the prompt content. save_final_image bool true Whether to save the final image in the data as a base64 encoded data URL. save_strokes bool true Whether to save the individual stroke data that generated the final image. key_to_draw key string null If this key is held down then it is like the mouse button being held down. The \"ink\" will flow when the button is held and stop when it is lifted. Pass in the string representation of the key, e.g., 'a' for the A key or ' ' for the spacebar. show_finished_button bool true Whether to show the button that ends the trial. finished_button_label string \"Finished\" The label for the button that ends the trial. show_clear_button bool true Whether to show the button that clears the entire drawing. clear_button_label string \"Clear\" The label for the button that clears the entire drawing. show_undo_button bool true Whether to show the button that enables an undo action. undo_button_label string \"Undo\" The label for the button that enables an undo action. show_redo_button bool true Whether to show the button that enables a redo action. Note that show_undo_button must be true for the redo button to show up. redo_button_label string \"Redo\" The label for the button that enables a redo action. choices array of keys \"NO_KEYS\" This array contains the key(s) that the participant is allowed to press in order to end the trial. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"NO_KEYS\" means that no keys will be accepted as valid responses. Specifying \"ALL_KEYS\" will mean that all responses are allowed. trial_duration int null Length of time before the trial ends. If null the trial will continue indefinitely (until another way of ending the trial occurs). show_countdown_trial_duration bool false Whether to show a timer that counts down until the end of the trial when trial_duration is not null . countdown_timer_html string '<span id=\"sketchpad-timer\"></span> remaining' The HTML to use for rendering the countdown timer. The element with id=\"sketchpad-timer\" will have its content replaced by a countdown timer in the format MM:SS . Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt int The length of time from the start of the trial to the end of the trial. response string If the trial was ended by clicking the finished button, then \"button\" . If the trial was ended by pressing a key, then the key that was pressed. If the trial timed out, then null . png base64 data URL string If save_final_image is true, then this will contain the base64 encoded data URL for the image, in png format. strokes array of stroke objects If save_strokes is true, then this will contain an array of stroke objects. Objects have an action property that is either \"start\" , \"move\" , or \"end\" . If action is \"start\" or \"move\" it will have an x and y property that report the coordinates of the action relative to the upper-left corner of the canvas. If action is \"start\" then the object will also have a t and color property, specifying the time of the action relative to the onset of the trial (ms) and the color of the stroke. If action is \"end\" then it will only have a t property. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-sketchpad@1.0.4\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-sketchpad.js\" >< /script> Using NPM: npm install @jspsych/plugin-sketchpad import sketchpad from '@jspsych/plugin-sketchpad' ; Examples \u00b6 Basic sketchpad with a prompt Code Demo var trial = { type : jsPsychSketchpad , prompt : '<p>Draw an apple!</p>' , prompt_location : 'abovecanvas' , canvas_width : 300 , canvas_height : 300 , canvas_border_width : 2 } Open demo in new tab Image segmentation with different colors Code Demo var trial = { type : jsPsychSketchpad , prompt : '<p style=\"width:380px\">Circle the mouth using red. Circle the eyes using blue.</p>' , prompt_location : 'abovecanvas' , stroke_color_palette : [ 'red' , 'blue' ], stroke_color : 'red' , background_image : 'img/sad_face_4.jpg' , canvas_width : 380 , canvas_height : 252 } Open demo in new tab Draw an image in a time limit, then display the image and ask for a label. Code Demo var draw = { type : jsPsychSketchpad , prompt : '<p>Draw the first animal that comes to mind. You have 30 seconds!</p>' , prompt_location : 'belowcanvas' , trial_duration : 30000 , show_countdown_trial_duration : true , } var label = { type : jsPsychSurveyText , preamble : () => { var imageData = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. png ; return `<img src=\" ${ imageData } \"></img>` ; }, questions : [ { prompt : 'What animal did you draw?' } ] } Open demo in new tab","title":"sketchpad"},{"location":"plugins/sketchpad/#sketchpad","text":"Current version: 1.0.4. See version history . This plugin creates an interactive canvas that the participant can draw on using their mouse or touchscreen. It can be used for sketching tasks, like asking the participant to draw a particular object. It can also be used for some image segmentation or annotation tasks by setting the background_image parameter to render an image on the canvas. The plugin stores a base 64 data URL representation of the final image. This can be converted to an image file using online tools or short programs in R , python , or another language of your choice. It also records all of the individual strokes that the participant made during the trial. Warning This plugin generates a lot of data. Each trial can easily add 500kb+ of data to a final JSON output. You can reduce the amount of data generated by turning off storage of the individual stroke data ( save_strokes: false ) or storage of the final image ( save_final_image: false ) if your use case doesn't require that information. If you are going to be collecting a lot of data with this plugin you may want to save your data to your server after each trial and not wait until the end of the experiment to perform a single bulk upload. You can do this by putting data saving code inside the on_data_update event handler .","title":"sketchpad"},{"location":"plugins/sketchpad/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameter Type Default Value Description canvas_shape \"rectangle\" or \"circle\" \"rectangle\" The shape of the canvas element. canvas_width int 500 Width of the canvas in pixels when canvas_shape is a \"rectangle\" . canvas_height int 500 Height of the canvas in pixels when canvas_shape is a \"rectangle\" . canvas_diameter int 500 Diameter of the canvas in pixels when canvas_shape is a \"circle\" . canvas_border_width int 0 Width of the canvas border. canvas_border_color string \"#000\" Color of the canvas border. background_image image path null Path to an image to render as the background of the canvas. background_color string \"#fff\" Color of the canvas background. Note that a background_image will render on top of the color. stroke_width int 2 Width of the stroke on the canvas. stroke_color string \"#000\" Color of the stroke on the canvas. stroke_color_palette array of strings [] Array of colors to render as a palette of choices for stroke color. Clicking on the corresponding color button will change the stroke color. prompt string null HTML content to render on the screen. prompt_location \"abovecanvas\" or \"belowcanvas\" or \"belowbutton\" \"abovecanvas\" The location to render the prompt content. save_final_image bool true Whether to save the final image in the data as a base64 encoded data URL. save_strokes bool true Whether to save the individual stroke data that generated the final image. key_to_draw key string null If this key is held down then it is like the mouse button being held down. The \"ink\" will flow when the button is held and stop when it is lifted. Pass in the string representation of the key, e.g., 'a' for the A key or ' ' for the spacebar. show_finished_button bool true Whether to show the button that ends the trial. finished_button_label string \"Finished\" The label for the button that ends the trial. show_clear_button bool true Whether to show the button that clears the entire drawing. clear_button_label string \"Clear\" The label for the button that clears the entire drawing. show_undo_button bool true Whether to show the button that enables an undo action. undo_button_label string \"Undo\" The label for the button that enables an undo action. show_redo_button bool true Whether to show the button that enables a redo action. Note that show_undo_button must be true for the redo button to show up. redo_button_label string \"Redo\" The label for the button that enables a redo action. choices array of keys \"NO_KEYS\" This array contains the key(s) that the participant is allowed to press in order to end the trial. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"NO_KEYS\" means that no keys will be accepted as valid responses. Specifying \"ALL_KEYS\" will mean that all responses are allowed. trial_duration int null Length of time before the trial ends. If null the trial will continue indefinitely (until another way of ending the trial occurs). show_countdown_trial_duration bool false Whether to show a timer that counts down until the end of the trial when trial_duration is not null . countdown_timer_html string '<span id=\"sketchpad-timer\"></span> remaining' The HTML to use for rendering the countdown timer. The element with id=\"sketchpad-timer\" will have its content replaced by a countdown timer in the format MM:SS .","title":"Parameters"},{"location":"plugins/sketchpad/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value rt int The length of time from the start of the trial to the end of the trial. response string If the trial was ended by clicking the finished button, then \"button\" . If the trial was ended by pressing a key, then the key that was pressed. If the trial timed out, then null . png base64 data URL string If save_final_image is true, then this will contain the base64 encoded data URL for the image, in png format. strokes array of stroke objects If save_strokes is true, then this will contain an array of stroke objects. Objects have an action property that is either \"start\" , \"move\" , or \"end\" . If action is \"start\" or \"move\" it will have an x and y property that report the coordinates of the action relative to the upper-left corner of the canvas. If action is \"start\" then the object will also have a t and color property, specifying the time of the action relative to the onset of the trial (ms) and the color of the stroke. If action is \"end\" then it will only have a t property.","title":"Data Generated"},{"location":"plugins/sketchpad/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/sketchpad/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-sketchpad@1.0.4\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-sketchpad.js\" >< /script> Using NPM: npm install @jspsych/plugin-sketchpad import sketchpad from '@jspsych/plugin-sketchpad' ;","title":"Install"},{"location":"plugins/sketchpad/#examples","text":"Basic sketchpad with a prompt Code Demo var trial = { type : jsPsychSketchpad , prompt : '<p>Draw an apple!</p>' , prompt_location : 'abovecanvas' , canvas_width : 300 , canvas_height : 300 , canvas_border_width : 2 } Open demo in new tab Image segmentation with different colors Code Demo var trial = { type : jsPsychSketchpad , prompt : '<p style=\"width:380px\">Circle the mouth using red. Circle the eyes using blue.</p>' , prompt_location : 'abovecanvas' , stroke_color_palette : [ 'red' , 'blue' ], stroke_color : 'red' , background_image : 'img/sad_face_4.jpg' , canvas_width : 380 , canvas_height : 252 } Open demo in new tab Draw an image in a time limit, then display the image and ask for a label. Code Demo var draw = { type : jsPsychSketchpad , prompt : '<p>Draw the first animal that comes to mind. You have 30 seconds!</p>' , prompt_location : 'belowcanvas' , trial_duration : 30000 , show_countdown_trial_duration : true , } var label = { type : jsPsychSurveyText , preamble : () => { var imageData = jsPsych . data . get (). last ( 1 ). values ()[ 0 ]. png ; return `<img src=\" ${ imageData } \"></img>` ; }, questions : [ { prompt : 'What animal did you draw?' } ] } Open demo in new tab","title":"Examples"},{"location":"plugins/survey-html-form/","text":"survey-html-form \u00b6 Current version: 1.0.3. See version history . The survey-html-form plugin displays a set of <inputs> from a HTML string. The type of input can be freely chosen, for a list of possible input types see the MDN page on inputs . The participant provides answers to the input fields. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description html string undefined HTML formatted string containing all the input elements to display. Every element has to have its own distinctive name attribute. The <form> tag must not be included and is generated by the plugin. This string can contain other HTML elements besides the input fields. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' The text that appears on the button to finish the trial. dataAsArray boolean false Retrieve the data as an array e.g. [{name: \"INPUT_NAME\", value: \"INPUT_VALUE\"}, ...] instead of an object e.g. {INPUT_NAME: INPUT_VALUE, ...}. This might be useful if you omit naming your inputs. autofocus string empty string The HTML element ID of a form field to autofocus on. The focused element is the element that will receive keyboard events. For elements like <input type=\"text\"> or <textbox> , autofocus means that the cursor will appear in the text input area when the trial loads. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each input. The object will have a separate key (variable) for the response to each input, with each variable being named after its corresponding input element. Each response is a string containing whatever the participant answered for this particular input. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-html-form.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-html-form import surveyHtmlForm from '@jspsych/plugin-survey-html-form' ; Examples \u00b6 Fill in the blanks Code Demo var trial = { type : jsPsychSurveyHtmlForm , preamble : '<p>How are you feeling <b>right now?</b></p>' , html : '<p> I am feeling <input name=\"first\" type=\"text\" />, <input name=\"second\" type=\"text\" />, and <input name=\"third\" type=\"text\" />.</p>' }; Open demo in new tab Using the autofocus parameter Code Demo var trial = { type : jsPsychSurveyHtmlForm , preamble : '<p>What is your favorite bird?</p>' , html : '<p>My favorite bird is <input type=\"text\" id=\"test-resp-box\" name=\"response\" size=\"10\" /></p>' , autofocus : 'test-resp-box' }; In this example, the browser will focus on the element with the ID test-resp-box when the trial loads. For <input type=\"text\"> elements, this means that the cursor will appear inside the text box. Open demo in new tab","title":"survey-html-form"},{"location":"plugins/survey-html-form/#survey-html-form","text":"Current version: 1.0.3. See version history . The survey-html-form plugin displays a set of <inputs> from a HTML string. The type of input can be freely chosen, for a list of possible input types see the MDN page on inputs . The participant provides answers to the input fields.","title":"survey-html-form"},{"location":"plugins/survey-html-form/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description html string undefined HTML formatted string containing all the input elements to display. Every element has to have its own distinctive name attribute. The <form> tag must not be included and is generated by the plugin. This string can contain other HTML elements besides the input fields. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' The text that appears on the button to finish the trial. dataAsArray boolean false Retrieve the data as an array e.g. [{name: \"INPUT_NAME\", value: \"INPUT_VALUE\"}, ...] instead of an object e.g. {INPUT_NAME: INPUT_VALUE, ...}. This might be useful if you omit naming your inputs. autofocus string empty string The HTML element ID of a form field to autofocus on. The focused element is the element that will receive keyboard events. For elements like <input type=\"text\"> or <textbox> , autofocus means that the cursor will appear in the text input area when the trial loads. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-html-form/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each input. The object will have a separate key (variable) for the response to each input, with each variable being named after its corresponding input element. Each response is a string containing whatever the participant answered for this particular input. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response.","title":"Data Generated"},{"location":"plugins/survey-html-form/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/survey-html-form/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-html-form@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-html-form.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-html-form import surveyHtmlForm from '@jspsych/plugin-survey-html-form' ;","title":"Install"},{"location":"plugins/survey-html-form/#examples","text":"Fill in the blanks Code Demo var trial = { type : jsPsychSurveyHtmlForm , preamble : '<p>How are you feeling <b>right now?</b></p>' , html : '<p> I am feeling <input name=\"first\" type=\"text\" />, <input name=\"second\" type=\"text\" />, and <input name=\"third\" type=\"text\" />.</p>' }; Open demo in new tab Using the autofocus parameter Code Demo var trial = { type : jsPsychSurveyHtmlForm , preamble : '<p>What is your favorite bird?</p>' , html : '<p>My favorite bird is <input type=\"text\" id=\"test-resp-box\" name=\"response\" size=\"10\" /></p>' , autofocus : 'test-resp-box' }; In this example, the browser will focus on the element with the ID test-resp-box when the trial loads. For <input type=\"text\"> elements, this means that the cursor will appear inside the text box. Open demo in new tab","title":"Examples"},{"location":"plugins/survey-likert/","text":"survey-likert \u00b6 Current version: 1.1.3. See version history . The survey-likert plugin displays a set of questions with Likert scale responses. The participant responds by selecting a radio button. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, labels and required parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value is undefined . The strings are the question that will be associated with a slider. labels : Type array, default value is undefined . Each array element is an array of strings. The innermost arrays contain a set of labels to display for an individual question. If you want to use blank responses and only label the end points or some subset of the options, just insert a blank string for the unlabeled responses. required : Type boolean, default value is false. Makes answering questions required. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. scale_width numeric null The width of the likert scale in pixels. If left null , then the width of the scale will be equal to the width of the widest content on the page. button_label string 'Continue' Label of the button. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. The responses are recorded as integers, representing the position selected on the likert scale for that question. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-likert@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-likert.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-likert import surveyLikert from '@jspsych/plugin-survey-likert' ; Examples \u00b6 Single Question Code Demo var trial = { type : jsPsychSurveyLikert , questions : [ { prompt : \"I like vegetables.\" , labels : [ \"Strongly Disagree\" , \"Disagree\" , \"Neutral\" , \"Agree\" , \"Strongly Agree\" ] } ] }; Open demo in new tab Multiple questions in a random order Code Demo var likert_scale = [ \"Strongly Disagree\" , \"Disagree\" , \"Neutral\" , \"Agree\" , \"Strongly Agree\" ]; var trial = { type : jsPsychSurveyLikert , questions : [ { prompt : \"I like vegetables.\" , name : 'Vegetables' , labels : likert_scale }, { prompt : \"I like fruit.\" , name : 'Fruit' , labels : likert_scale }, { prompt : \"I like meat.\" , name : 'Meat' , labels : likert_scale }, ], randomize_question_order : true }; Open demo in new tab","title":"survey-likert"},{"location":"plugins/survey-likert/#survey-likert","text":"Current version: 1.1.3. See version history . The survey-likert plugin displays a set of questions with Likert scale responses. The participant responds by selecting a radio button.","title":"survey-likert"},{"location":"plugins/survey-likert/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, labels and required parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value is undefined . The strings are the question that will be associated with a slider. labels : Type array, default value is undefined . Each array element is an array of strings. The innermost arrays contain a set of labels to display for an individual question. If you want to use blank responses and only label the end points or some subset of the options, just insert a blank string for the unlabeled responses. required : Type boolean, default value is false. Makes answering questions required. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. scale_width numeric null The width of the likert scale in pixels. If left null , then the width of the scale will be equal to the width of the widest content on the page. button_label string 'Continue' Label of the button. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-likert/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. The responses are recorded as integers, representing the position selected on the likert scale for that question. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/survey-likert/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-likert@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-likert.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-likert import surveyLikert from '@jspsych/plugin-survey-likert' ;","title":"Install"},{"location":"plugins/survey-likert/#examples","text":"Single Question Code Demo var trial = { type : jsPsychSurveyLikert , questions : [ { prompt : \"I like vegetables.\" , labels : [ \"Strongly Disagree\" , \"Disagree\" , \"Neutral\" , \"Agree\" , \"Strongly Agree\" ] } ] }; Open demo in new tab Multiple questions in a random order Code Demo var likert_scale = [ \"Strongly Disagree\" , \"Disagree\" , \"Neutral\" , \"Agree\" , \"Strongly Agree\" ]; var trial = { type : jsPsychSurveyLikert , questions : [ { prompt : \"I like vegetables.\" , name : 'Vegetables' , labels : likert_scale }, { prompt : \"I like fruit.\" , name : 'Fruit' , labels : likert_scale }, { prompt : \"I like meat.\" , name : 'Meat' , labels : likert_scale }, ], randomize_question_order : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/survey-multi-choice/","text":"survey-multi-choice \u00b6 Current version: 1.1.3. See version history . The survey-multi-choice plugin displays a set of questions with multiple choice response fields. The participant selects a single answer. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, options, required, and horizontal parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value is undefined . The string is prompt/question that will be associated with a group of options (radio buttons). All questions will get presented on the same page (trial). options : Type array, defualt value is undefined . An array of strings. The array contains a set of options to display for an individual question. required : Type boolean, default value is null. The boolean value indicates if a question is required('true') or not ('false'), using the HTML5 required attribute. If this parameter is undefined, the question will be optional. horizontal :Type boolean, default value is false. If true, then the question is centered and the options are displayed horizontally. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' Label of the button. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. The responses are recorded as the name of the option label selected (string). If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-multi-choice.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-multi-choice import surveyMultiChoice from '@jspsych/plugin-survey-multi-choice' ; Examples \u00b6 Vertical Question Alignment Code Demo var trial = { type : jsPsychSurveyMultiChoice , questions : [ { prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true }, { prompt : \"Which of the following do you like the least?\" , name : 'FruitDislike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false } ], }; Open demo in new tab Horizontal Question Alignment Code Demo var trial = { type : jsPsychSurveyMultiChoice , questions : [ { prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true , horizontal : true }, { prompt : \"Which of the following do you like the least?\" , name : 'FruitDislike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false , horizontal : true } ], }; Open demo in new tab","title":"survey-multi-choice"},{"location":"plugins/survey-multi-choice/#survey-multi-choice","text":"Current version: 1.1.3. See version history . The survey-multi-choice plugin displays a set of questions with multiple choice response fields. The participant selects a single answer.","title":"survey-multi-choice"},{"location":"plugins/survey-multi-choice/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, options, required, and horizontal parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value is undefined . The string is prompt/question that will be associated with a group of options (radio buttons). All questions will get presented on the same page (trial). options : Type array, defualt value is undefined . An array of strings. The array contains a set of options to display for an individual question. required : Type boolean, default value is null. The boolean value indicates if a question is required('true') or not ('false'), using the HTML5 required attribute. If this parameter is undefined, the question will be optional. horizontal :Type boolean, default value is false. If true, then the question is centered and the options are displayed horizontally. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' Label of the button. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-multi-choice/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. The responses are recorded as the name of the option label selected (string). If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/survey-multi-choice/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-multi-choice@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-multi-choice.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-multi-choice import surveyMultiChoice from '@jspsych/plugin-survey-multi-choice' ;","title":"Install"},{"location":"plugins/survey-multi-choice/#examples","text":"Vertical Question Alignment Code Demo var trial = { type : jsPsychSurveyMultiChoice , questions : [ { prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true }, { prompt : \"Which of the following do you like the least?\" , name : 'FruitDislike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false } ], }; Open demo in new tab Horizontal Question Alignment Code Demo var trial = { type : jsPsychSurveyMultiChoice , questions : [ { prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true , horizontal : true }, { prompt : \"Which of the following do you like the least?\" , name : 'FruitDislike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false , horizontal : true } ], }; Open demo in new tab","title":"Examples"},{"location":"plugins/survey-multi-select/","text":"survey-multi-select \u00b6 Current version: 1.1.3. See version history . The survey-multi-select plugin displays a set of questions with multiple select response fields. The participant can select multiple answers. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, options and horizontal parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value of undefined . The string is the prompt/question that will be associated with a group of options (check boxes). All questions will get presented on the same page (trial). options : Type array, default value of undefined . The array contains a set of options to display for an individual question. horizontal : Type boolean, default value of false. If true, the questions are centered and options are displayed horizontally. required : Type boolean, default value of true. If true, then at least one option must be selected. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' Label of the button. required_message string 'You must choose at least one response for this question' Message to display if required response is not given. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. For each question, the responses are recorded as arrays containing any response options that were selected (strings). If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) were submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-multi-select@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-multi-select.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-multi-select import surveyMultiSelect from '@jspsych/plugin-survey-multi-select' ; Examples \u00b6 Multiple Questions on a Page Code Demo var trial = { type : jsPsychSurveyMultiSelect , questions : [ { prompt : \"Which of these colors do you like?\" , options : [ \"Red\" , \"Yellow\" , \"Green\" , \"Blue\" , \"Black\" ], horizontal : true , required : true , name : 'Colors' }, { prompt : \"Which of these foods do you like?\" , options : [ \"Apples\" , \"Bananas\" , \"Carrots\" , \"Donuts\" , \"Eggplant\" ], horizontal : true , required : true , name : 'Foods' } ], randomize_question_order : true }; Open demo in new tab","title":"survey-multi-select"},{"location":"plugins/survey-multi-select/#survey-multi-select","text":"Current version: 1.1.3. See version history . The survey-multi-select plugin displays a set of questions with multiple select response fields. The participant can select multiple answers.","title":"survey-multi-select"},{"location":"plugins/survey-multi-select/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, options and horizontal parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value of undefined . The string is the prompt/question that will be associated with a group of options (check boxes). All questions will get presented on the same page (trial). options : Type array, default value of undefined . The array contains a set of options to display for an individual question. horizontal : Type boolean, default value of false. If true, the questions are centered and options are displayed horizontally. required : Type boolean, default value of true. If true, then at least one option must be selected. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' Label of the button. required_message string 'You must choose at least one response for this question' Message to display if required response is not given. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-multi-select/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. For each question, the responses are recorded as arrays containing any response options that were selected (strings). If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) were submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/survey-multi-select/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-multi-select@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-multi-select.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-multi-select import surveyMultiSelect from '@jspsych/plugin-survey-multi-select' ;","title":"Install"},{"location":"plugins/survey-multi-select/#examples","text":"Multiple Questions on a Page Code Demo var trial = { type : jsPsychSurveyMultiSelect , questions : [ { prompt : \"Which of these colors do you like?\" , options : [ \"Red\" , \"Yellow\" , \"Green\" , \"Blue\" , \"Black\" ], horizontal : true , required : true , name : 'Colors' }, { prompt : \"Which of these foods do you like?\" , options : [ \"Apples\" , \"Bananas\" , \"Carrots\" , \"Donuts\" , \"Eggplant\" ], horizontal : true , required : true , name : 'Foods' } ], randomize_question_order : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/survey-text/","text":"survey-text \u00b6 Current version: 1.1.3. See version history . The survey-text plugin displays a set of questions with free response text fields. The participant types in answers. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, placeholder, required, rows, and columns parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value of undefined . The string is the prompt for the participant to respond to. Each question gets its own response field. placeholder : Type string, default value of \"\" . The string will create placeholder text in the text field. required : Boolean; if true then the user must enter a response to submit. rows : Type integer, default value of 1. The number of rows for the response text box. columns : Type integer, default value of 40. The number of columns for the response text box. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' The text that appears on the button to finish the trial. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. For each question, the response is a string containing whatever text was in the response box when the responses were submitted. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) were submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-text@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-text.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-text import surveyText from '@jspsych/plugin-survey-text' ; Examples \u00b6 Single question and response Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'How old are you?' } ] } Open demo in new tab Multiple questions, with an optional placeholder and a required question Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'What is your date of birth?' , placeholder : 'mm/dd/yyyy' , required : true }, { prompt : 'What country do you currently live in?' } ] } Open demo in new tab Naming questions to improve readability of the stored data Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'What did you eat for breakfast?' , name : 'Breakfast' }, { prompt : 'What did you eat for lunch?' , name : 'Lunch' } ] } Open demo in new tab Using the preamble and a longer textbox response Code Demo var trial = { type : jsPsychSurveyText , preamble : `<img src=\"img/navarro_burst_03.jpg\" style=\"width:400px;\"></img>` , questions : [ { prompt : 'Describe your reaction to the image above' , rows : 5 } ] } The artwork in this demo is by Danielle Navarro Open demo in new tab","title":"survey-text"},{"location":"plugins/survey-text/#survey-text","text":"Current version: 1.1.3. See version history . The survey-text plugin displays a set of questions with free response text fields. The participant types in answers.","title":"survey-text"},{"location":"plugins/survey-text/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description questions array undefined An array of objects, each object represents a question that appears on the screen. Each object contains a prompt, placeholder, required, rows, and columns parameter that will be applied to the question. See examples below for further clarification. prompt : Type string, default value of undefined . The string is the prompt for the participant to respond to. Each question gets its own response field. placeholder : Type string, default value of \"\" . The string will create placeholder text in the text field. required : Boolean; if true then the user must enter a response to submit. rows : Type integer, default value of 1. The number of rows for the response text box. columns : Type integer, default value of 40. The number of columns for the response text box. name : Name of the question. Used for storing data. If left undefined then default names ( Q0 , Q1 , ... ) will be used for the questions. randomize_question_order boolean false If true, the display order of questions is randomly determined at the start of the trial. In the data object, Q0 will still refer to the first question in the array, regardless of where it was presented visually. preamble string empty string HTML formatted string to display at the top of the page above all the questions. button_label string 'Continue' The text that appears on the button to finish the trial. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form.","title":"Parameters"},{"location":"plugins/survey-text/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response for each question. The object will have a separate key (variable) for each question, with the first question in the trial being recorded in Q0 , the second in Q1 , and so on. For each question, the response is a string containing whatever text was in the response box when the responses were submitted. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) were submitted. question_order array An array with the order of questions. For example [2,0,1] would indicate that the first question was trial.questions[2] (the third item in the questions parameter), the second question was trial.questions[0] , and the final question was trial.questions[1] . This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/survey-text/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey-text@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey-text.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey-text import surveyText from '@jspsych/plugin-survey-text' ;","title":"Install"},{"location":"plugins/survey-text/#examples","text":"Single question and response Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'How old are you?' } ] } Open demo in new tab Multiple questions, with an optional placeholder and a required question Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'What is your date of birth?' , placeholder : 'mm/dd/yyyy' , required : true }, { prompt : 'What country do you currently live in?' } ] } Open demo in new tab Naming questions to improve readability of the stored data Code Demo var trial = { type : jsPsychSurveyText , questions : [ { prompt : 'What did you eat for breakfast?' , name : 'Breakfast' }, { prompt : 'What did you eat for lunch?' , name : 'Lunch' } ] } Open demo in new tab Using the preamble and a longer textbox response Code Demo var trial = { type : jsPsychSurveyText , preamble : `<img src=\"img/navarro_burst_03.jpg\" style=\"width:400px;\"></img>` , questions : [ { prompt : 'Describe your reaction to the image above' , rows : 5 } ] } The artwork in this demo is by Danielle Navarro Open demo in new tab","title":"Examples"},{"location":"plugins/survey/","text":"survey \u00b6 Current version: 0.2.2. See version history . The survey plugin displays one or more questions of different types, on one or more pages that the participant can navigate. This plugin is built on top of the SurveyJS library. The supported question types are: \"drop-down\" for presenting a question with a limited set of options in a drop-down menu. The participant can only select one option. \"likert\" for presenting a prompt along with a discrete rating scale. \"likert-table\" for presenting a prompt along with a table of statements/questions (rows) and repeated response options for each statement/question (columns). \"multi-choice\" for presenting a question with a limited set of options. The participant can only select one option. \"multi-select\" for presenting a question with a limited set of options. The participant can select multiple options. \"ranking\" for presenting a question with a limited set of options, where participants respond by dragging and dropping (ordering/ranking) the options. \"text\" for presenting a question with a free response text field in which the participant can type in an answer. There is also an \"html\" type for adding arbitrary HTML-formatted content (without any associated response field) in the question set. Warning Development on this plugin is ongoing and we plan to incorporate more of the features that SurveyJS provides. Prior to release of version 1.0 of the plugin, we expect the parameters and implementation of this plugin to change. We recommend performing a little bit of extra testing with any experiments that utilize this plugin. CSS \u00b6 This plugin uses an additional stylesheet called survey.css . You can load it via: < link rel = \"stylesheet\" href = \"https://unpkg.com/@jspsych/plugin-survey@0.2.2/css/survey.css\" > If you are using a bundler such as webpack , you can also import it in JavaScript as follows, depending on your bundler configuration: import '@jspsych/plugin-survey/css/survey.css' Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Survey parameters \u00b6 Parameter Type Default Value Description pages array undefined An array of arrays. Each inner array contains the content for a single page, which is made up of one or more question objects. button_label_next string 'Continue' Label of the button to move forward to the next page, or finish the survey. button_label_back string 'Back' Label of the button to move to a previous page in the survey. button_label_finish string 'Finish' Label of the button to submit responses. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. show_question_numbers string \"off\" One of: \"on\", \"onPage\", \"off\". If \"on\", questions will be labelled starting with \"1.\" on the first page, and numbering will continue across pages. If \"onPage\", questions will be labelled starting with \"1.\", with separate numbering on each page. If \"off\", no numbers will be added before the question prompts. Note: HTML question types are ignored in automatic numbering. title string null If specified, this text will be shown at the top of the survey pages. required_error string \"Please answer the question.\" Text to display if a required question is not responeded to. required_question_label string \"*\" String to display at the end of required questions. Use an empty string (\"\") if you do not want to add a label to the end of required questions. Question types and parameters \u00b6 Parameters for all question types \u00b6 Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description type string undefined The question type. Options are: \"drop-down\", \"html\", \"likert\", \"likert-table\", \"multi-choice\", \"multi-select\", \"ranking\", \"rating\", \"text\". prompt string undefined The prompt/question that will be associated with the question's response field. If the question type is \"html\", then this string is the HTML-formatted string to be displayed. If the question type is \"likert-table\", the prompt is a general question or title presented above the table. required boolean false Whether a response to the question is required ( true ) or not ( false ), using the HTML5 required attribute. name string null Name of the question to be used for storing data. If this parameter is not provided, then default names will be used to identify the questions in the data: P0_Q0 , P0_Q1 , P1_Q0 etc. Question names must be unique across all pages within the trial. Drop-down \u00b6 Present a question with a limited set of options in a drop-down menu. The participant can only select one option. In addition to the parameters for all question types, the drop-down question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of multiple choice options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. correct_response string null String from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ). HTML \u00b6 Present arbitrary HTML-formatted content embedded in the list of questions, including text, images, and sounds. There are no response options. The only available parameters are those listed for all question types with a default value of undefined ( type and prompt ) and name . The name parameter is optional and used to identify the question in the data, with a response value of null . The required parameter will be ignored. Likert \u00b6 Present a prompt along with a discrete rating scale. The scale values are presented as buttons that can be selected and de-selected. The scale is specified by the likert_scale_values parameter, which is an array of text labels and associated values, or it is generated using the likert_rating_min / max / stepsize parameters (along with optional maximum/minimum descriptions). In addition to the parameters for all question types, the likert question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description likert_scale_values array of objects null Array of objects that defines the rating scale labels and associated values to be stored in the data. Each object defines a single rating option. The objects must have a value property, which is an integer or string value that will be stored as the response in the data. The objects can optionally have a text property, which is a string that will be displayed for that rating option (example: [{value: 1, text: \"A lot\"},{value: 2, text: \"Somewhat\"},{value: 3, text: \"Not much\"}] ). If no text property is specified then the value will be displayed (examples: [{value: 1},{value: 2},{value: 3}] , [{value: \"Yes\"},{value: \"Maybe\"},{value: \"No\"}] ). If provided, this parameter will override the likert_rating_min / max / stepsize parameters. likert_scale_min integer 1 If the likert_scale_values array is not specified, then this parameter will define the minimum scale value. likert_scale_max integer 5 If the likert_scale_values array is not specified, then this parameter will define the maximum scale value. likert_scale_stepsize integer 1 If the likert_scale_values array is not specified, then this parameter will define the step size that should be used for generating rating options between the minimum and maximum values. likert_scale_min_label string null Description for the minimum (first) rating option. If provided, this text will be shown inside the first rating button, before the rating text/value. This parameter is meant for defining the scale's minimum when integer values are used for the rating scale buttons. likert_scale_max_label string null Description for the maximum (last) rating option. If provided, this text will be shown inside the first rating button, after the rating text/value. This parameter is meant for defining the scale's maximum when integer values are used for the rating scale buttons. Likert-table \u00b6 Present a prompt along with a table of statements/questions (rows) and repeated response options for each statement/question (columns). In addition to the parameters for all question types, the likert-table question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description statements array of objects undefined This array contains one or more objects representing the statements/questions to be presented in the table rows. Each object must have a prompt , which is the statement/question text. The objects can optionally include a name , which is how the statement should be identified in the data. If no name is provided, then the default values of \"S0\", \"S1\" etc. will be used. options array of strings undefined This array contains the set of multiple choice options to be presented in the table columns. randomize_statement_order boolean false If true , the order of statements/questions in the statements array will be randomized. Multi-choice \u00b6 Present a question with a limited set of options. The participant can only select one option. In addition to the parameters for all question types, the multi-choice question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of multiple choice options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. columns integer 1 Number of columns to use for displaying the options. If 1 (default), the choices will be displayed in a single column (vertically). If 0, choices will be displayed in a single row (horizontally). Any value greater than 1 can be used to display options in multiple columns. correct_response string null String from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ). Multi-select \u00b6 Present a question with a limited set of options. The participant can select multiple options. In addition to the parameters for all question types, the multi-select question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. columns integer 1 Number of columns to use for displaying the options. If 1 (default), the choices will be displayed in a single column (vertically). If 0, choices will be displayed in a single row (horizontally). Any value greater than 1 can be used to display options in multiple columns. correct_response array of strings null Array of one or more strings from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ). Ranking \u00b6 Present a question with a limited set of options, where participants respond by dragging and dropping (ordering/ranking) the options. It is ideally used with a short list of options (up to about 7 items). It supports mouse responses, touch responses (mobile devices), and keyboard responses (Tab and Shift-Tab to select, and Up/Down arrow keys to re-order). In addition to the parameters for all question types, the ranking question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of to-be-ranked options for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. correct_response array of strings null The same array of strings used for the options array, but listed in the order that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ). Text \u00b6 Present a question with a free response text field in which the participant can type in an answer. In addition to the parameters for all question types, the text question also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description placeholder string \"\" Placeholder text in the text response field. textbox_rows integer 1 The number of rows (height) for the response text box. textbox_columns integer 40 The number of columns (width) for the response text box. validation string \"\" A regular expression used to validate the response. input_type string \"text\" Type for the HTML <input> element. The input_type parameter must be one of \"color\", \"date\", \"datetime-local\", \"email\", \"month\", \"number\", \"password\", \"range\", \"tel\", \"text\", \"time\", \"url\", \"week\". If the textbox_rows parameter is larger than 1, the input_type parameter will be ignored. The textbox_columns parameter only affects questions with input_type \"email\", \"password\", \"tel\", \"url\", or \"text\". Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response to each question. The object will have a separate key (variable) for each question, with the first question on the first page being recorded in P0_Q0 , the second question on the first page in P0_Q1 , and so on. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. The response type will depend on the question type. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Note that, if any questions use the other option ( add_other_option: true ), then the response value will be the other_option_text (e.g. \"Other\") and any text written in the textbox will be saved as \"(question name)-Comment\". rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey@0.2.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey import survey from '@jspsych/plugin-survey' ; Examples \u00b6 Basic single page Code Demo var trial = { type : jsPsychSurvey , pages : [ [ { type : 'html' , prompt : 'Please answer the following questions:' , }, { type : 'multi-choice' , prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true }, { type : 'multi-select' , prompt : \"Which of the following do you like?\" , name : 'FruitLike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false , } ] ], }; Open demo in new tab Multiple pages, more customization Code Demo var trial = { type : jsPsychSurvey , pages : [ [ { type : 'text' , prompt : \"Where were you born?\" , placeholder : 'City, State, Country' , name : 'birthplace' , required : true , }, { type : 'text' , prompt : \"How old are you?\" , name : 'age' , textbox_columns : 5 , required : false , } ], [ { type : 'multi-choice' , prompt : \"What&#39;s your favorite color?\" , options : [ 'blue' , 'yellow' , 'pink' , 'teal' , 'orange' , 'lime green' , 'other' , 'none of these' ], name : 'FavColor' , }, { type : 'multi-select' , prompt : \"Which of these animals do you like? Select all that apply.\" , options : [ 'lion' , 'squirrel' , 'badger' , 'whale' ], option_reorder : 'random' , columns : 0 , name : 'AnimalLike' , } ] ], title : 'My questionnaire' , button_label_next : 'Continue' , button_label_back : 'Previous' , button_label_finish : 'Submit' , show_question_numbers : 'onPage' }; Open demo in new tab Single and multiple item Likert-style scales Code Demo const trial = { type : jsPsychSurvey , pages : [ [ { type : 'likert' , prompt : 'I like to eat vegetables.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, { type : 'likert' , prompt : 'I like to eat fruit.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, { type : 'likert' , prompt : 'I like to eat meat.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, ], [ { type : 'likert-table' , prompt : ' ' , statements : [ { prompt : 'I like to eat vegetables' , name : 'VeggiesTable' }, { prompt : 'I like to eat fruit' , name : 'FruitTable' }, { prompt : 'I like to eat meat' , name : 'MeatTable' }, ], options : [ 'Strongly Disagree' , 'Disagree' , 'Neutral' , 'Agree' , 'Strongly Agree' ], } ] ], }; Open demo in new tab Response scoring Code Demo const trial = { type : jsPsychSurvey , pages : [ [ { type : 'multi-choice' , prompt : 'During the experiment, are allowed to write things down on paper to help you?' , options : [ \"Yes\" , \"No\" ], correct_response : \"No\" , required : true }, ] ], }; Open demo in new tab Adding data to trial When adding any data to a Survey trial, you should add it via the data parameter at the whole-trial level (not inside the question objects), even if it only relates to one question out of multiple questions/pages contained wihtin the trial. Code Demo const question_info = [ { 'fruit' : 'apples' , 'Q1_prompt' : 'Do you like apples?' , 'Q1_type' : 'regular' }, { 'fruit' : 'bananas' , 'Q1_prompt' : 'Do you NOT like bananas?' , 'Q1_type' : 'reverse' }, ]; const survey = { type : jsPsychSurvey , pages : [ [ { type : 'multi-choice' , prompt : jsPsych . timelineVariable ( 'Q1_prompt' ), options : [ 'Yes' , 'No' ], name : 'Q1' }, { type : 'text' , prompt : function () { return `What's your favorite thing about ${ jsPsych . timelineVariable ( 'fruit' ) } ?` ; }, name : 'Q2' } ] ], // Add data at the whole-trial level here data : { 'Q1_prompt' : jsPsych . timelineVariable ( 'Q1_prompt' ), 'Q1_type' : jsPsych . timelineVariable ( 'Q1_type' ), 'fruit' : jsPsych . timelineVariable ( 'fruit' ) }, button_label_finish : 'Continue' }; const survey_procedure = { timeline : [ survey ], timeline_variables : question_info , randomize_order : true }; Open demo in new tab","title":"survey"},{"location":"plugins/survey/#survey","text":"Current version: 0.2.2. See version history . The survey plugin displays one or more questions of different types, on one or more pages that the participant can navigate. This plugin is built on top of the SurveyJS library. The supported question types are: \"drop-down\" for presenting a question with a limited set of options in a drop-down menu. The participant can only select one option. \"likert\" for presenting a prompt along with a discrete rating scale. \"likert-table\" for presenting a prompt along with a table of statements/questions (rows) and repeated response options for each statement/question (columns). \"multi-choice\" for presenting a question with a limited set of options. The participant can only select one option. \"multi-select\" for presenting a question with a limited set of options. The participant can select multiple options. \"ranking\" for presenting a question with a limited set of options, where participants respond by dragging and dropping (ordering/ranking) the options. \"text\" for presenting a question with a free response text field in which the participant can type in an answer. There is also an \"html\" type for adding arbitrary HTML-formatted content (without any associated response field) in the question set. Warning Development on this plugin is ongoing and we plan to incorporate more of the features that SurveyJS provides. Prior to release of version 1.0 of the plugin, we expect the parameters and implementation of this plugin to change. We recommend performing a little bit of extra testing with any experiments that utilize this plugin.","title":"survey"},{"location":"plugins/survey/#css","text":"This plugin uses an additional stylesheet called survey.css . You can load it via: < link rel = \"stylesheet\" href = \"https://unpkg.com/@jspsych/plugin-survey@0.2.2/css/survey.css\" > If you are using a bundler such as webpack , you can also import it in JavaScript as follows, depending on your bundler configuration: import '@jspsych/plugin-survey/css/survey.css'","title":"CSS"},{"location":"plugins/survey/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable.","title":"Parameters"},{"location":"plugins/survey/#survey-parameters","text":"Parameter Type Default Value Description pages array undefined An array of arrays. Each inner array contains the content for a single page, which is made up of one or more question objects. button_label_next string 'Continue' Label of the button to move forward to the next page, or finish the survey. button_label_back string 'Back' Label of the button to move to a previous page in the survey. button_label_finish string 'Finish' Label of the button to submit responses. autocomplete boolean false This determines whether or not all of the input elements on the page should allow autocomplete. Setting this to true will enable autocomplete or auto-fill for the form. show_question_numbers string \"off\" One of: \"on\", \"onPage\", \"off\". If \"on\", questions will be labelled starting with \"1.\" on the first page, and numbering will continue across pages. If \"onPage\", questions will be labelled starting with \"1.\", with separate numbering on each page. If \"off\", no numbers will be added before the question prompts. Note: HTML question types are ignored in automatic numbering. title string null If specified, this text will be shown at the top of the survey pages. required_error string \"Please answer the question.\" Text to display if a required question is not responeded to. required_question_label string \"*\" String to display at the end of required questions. Use an empty string (\"\") if you do not want to add a label to the end of required questions.","title":"Survey parameters"},{"location":"plugins/survey/#question-types-and-parameters","text":"","title":"Question types and parameters"},{"location":"plugins/survey/#parameters-for-all-question-types","text":"Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description type string undefined The question type. Options are: \"drop-down\", \"html\", \"likert\", \"likert-table\", \"multi-choice\", \"multi-select\", \"ranking\", \"rating\", \"text\". prompt string undefined The prompt/question that will be associated with the question's response field. If the question type is \"html\", then this string is the HTML-formatted string to be displayed. If the question type is \"likert-table\", the prompt is a general question or title presented above the table. required boolean false Whether a response to the question is required ( true ) or not ( false ), using the HTML5 required attribute. name string null Name of the question to be used for storing data. If this parameter is not provided, then default names will be used to identify the questions in the data: P0_Q0 , P0_Q1 , P1_Q0 etc. Question names must be unique across all pages within the trial.","title":"Parameters for all question types"},{"location":"plugins/survey/#drop-down","text":"Present a question with a limited set of options in a drop-down menu. The participant can only select one option. In addition to the parameters for all question types, the drop-down question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of multiple choice options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. correct_response string null String from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ).","title":"Drop-down"},{"location":"plugins/survey/#html","text":"Present arbitrary HTML-formatted content embedded in the list of questions, including text, images, and sounds. There are no response options. The only available parameters are those listed for all question types with a default value of undefined ( type and prompt ) and name . The name parameter is optional and used to identify the question in the data, with a response value of null . The required parameter will be ignored.","title":"HTML"},{"location":"plugins/survey/#likert","text":"Present a prompt along with a discrete rating scale. The scale values are presented as buttons that can be selected and de-selected. The scale is specified by the likert_scale_values parameter, which is an array of text labels and associated values, or it is generated using the likert_rating_min / max / stepsize parameters (along with optional maximum/minimum descriptions). In addition to the parameters for all question types, the likert question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description likert_scale_values array of objects null Array of objects that defines the rating scale labels and associated values to be stored in the data. Each object defines a single rating option. The objects must have a value property, which is an integer or string value that will be stored as the response in the data. The objects can optionally have a text property, which is a string that will be displayed for that rating option (example: [{value: 1, text: \"A lot\"},{value: 2, text: \"Somewhat\"},{value: 3, text: \"Not much\"}] ). If no text property is specified then the value will be displayed (examples: [{value: 1},{value: 2},{value: 3}] , [{value: \"Yes\"},{value: \"Maybe\"},{value: \"No\"}] ). If provided, this parameter will override the likert_rating_min / max / stepsize parameters. likert_scale_min integer 1 If the likert_scale_values array is not specified, then this parameter will define the minimum scale value. likert_scale_max integer 5 If the likert_scale_values array is not specified, then this parameter will define the maximum scale value. likert_scale_stepsize integer 1 If the likert_scale_values array is not specified, then this parameter will define the step size that should be used for generating rating options between the minimum and maximum values. likert_scale_min_label string null Description for the minimum (first) rating option. If provided, this text will be shown inside the first rating button, before the rating text/value. This parameter is meant for defining the scale's minimum when integer values are used for the rating scale buttons. likert_scale_max_label string null Description for the maximum (last) rating option. If provided, this text will be shown inside the first rating button, after the rating text/value. This parameter is meant for defining the scale's maximum when integer values are used for the rating scale buttons.","title":"Likert"},{"location":"plugins/survey/#likert-table","text":"Present a prompt along with a table of statements/questions (rows) and repeated response options for each statement/question (columns). In addition to the parameters for all question types, the likert-table question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description statements array of objects undefined This array contains one or more objects representing the statements/questions to be presented in the table rows. Each object must have a prompt , which is the statement/question text. The objects can optionally include a name , which is how the statement should be identified in the data. If no name is provided, then the default values of \"S0\", \"S1\" etc. will be used. options array of strings undefined This array contains the set of multiple choice options to be presented in the table columns. randomize_statement_order boolean false If true , the order of statements/questions in the statements array will be randomized.","title":"Likert-table"},{"location":"plugins/survey/#multi-choice","text":"Present a question with a limited set of options. The participant can only select one option. In addition to the parameters for all question types, the multi-choice question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of multiple choice options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. columns integer 1 Number of columns to use for displaying the options. If 1 (default), the choices will be displayed in a single column (vertically). If 0, choices will be displayed in a single row (horizontally). Any value greater than 1 can be used to display options in multiple columns. correct_response string null String from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ).","title":"Multi-choice"},{"location":"plugins/survey/#multi-select","text":"Present a question with a limited set of options. The participant can select multiple options. In addition to the parameters for all question types, the multi-select question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of options to display for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. columns integer 1 Number of columns to use for displaying the options. If 1 (default), the choices will be displayed in a single column (vertically). If 0, choices will be displayed in a single row (horizontally). Any value greater than 1 can be used to display options in multiple columns. correct_response array of strings null Array of one or more strings from the options array that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ).","title":"Multi-select"},{"location":"plugins/survey/#ranking","text":"Present a question with a limited set of options, where participants respond by dragging and dropping (ordering/ranking) the options. It is ideally used with a short list of options (up to about 7 items). It supports mouse responses, touch responses (mobile devices), and keyboard responses (Tab and Shift-Tab to select, and Up/Down arrow keys to re-order). In addition to the parameters for all question types, the ranking question type also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description options array of strings undefined This array contains the set of to-be-ranked options for the question. option_reorder string \"none\" One of: \"none\", \"asc\", \"desc\", \"random\". If \"none\", the options will be listed in the order given in the options array. If random , the option order will be randomized. If \"asc\" or \"desc\", the options will be presented in ascending or descending order, respectively. correct_response array of strings null The same array of strings used for the options array, but listed in the order that should be considered correct. If specified, the data will include a correct property that indicates whether the response was correct ( true ) or not ( false ).","title":"Ranking"},{"location":"plugins/survey/#text","text":"Present a question with a free response text field in which the participant can type in an answer. In addition to the parameters for all question types, the text question also offers the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description placeholder string \"\" Placeholder text in the text response field. textbox_rows integer 1 The number of rows (height) for the response text box. textbox_columns integer 40 The number of columns (width) for the response text box. validation string \"\" A regular expression used to validate the response. input_type string \"text\" Type for the HTML <input> element. The input_type parameter must be one of \"color\", \"date\", \"datetime-local\", \"email\", \"month\", \"number\", \"password\", \"range\", \"tel\", \"text\", \"time\", \"url\", \"week\". If the textbox_rows parameter is larger than 1, the input_type parameter will be ignored. The textbox_columns parameter only affects questions with input_type \"email\", \"password\", \"tel\", \"url\", or \"text\".","title":"Text"},{"location":"plugins/survey/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response object An object containing the response to each question. The object will have a separate key (variable) for each question, with the first question on the first page being recorded in P0_Q0 , the second question on the first page in P0_Q1 , and so on. If the name parameter is defined for the question, then the response object will use the value of name as the key for each question. The response type will depend on the question type. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Note that, if any questions use the other option ( add_other_option: true ), then the response value will be the other_option_text (e.g. \"Other\") and any text written in the textbox will be saved as \"(question name)-Comment\". rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the questions first appear on the screen until the participant's response(s) are submitted.","title":"Data Generated"},{"location":"plugins/survey/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/survey/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-survey@0.2.2\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-survey.js\" >< /script> Using NPM: npm install @jspsych/plugin-survey import survey from '@jspsych/plugin-survey' ;","title":"Install"},{"location":"plugins/survey/#examples","text":"Basic single page Code Demo var trial = { type : jsPsychSurvey , pages : [ [ { type : 'html' , prompt : 'Please answer the following questions:' , }, { type : 'multi-choice' , prompt : \"Which of the following do you like the most?\" , name : 'VegetablesLike' , options : [ 'Tomato' , 'Cucumber' , 'Eggplant' , 'Corn' , 'Peas' ], required : true }, { type : 'multi-select' , prompt : \"Which of the following do you like?\" , name : 'FruitLike' , options : [ 'Apple' , 'Banana' , 'Orange' , 'Grape' , 'Strawberry' ], required : false , } ] ], }; Open demo in new tab Multiple pages, more customization Code Demo var trial = { type : jsPsychSurvey , pages : [ [ { type : 'text' , prompt : \"Where were you born?\" , placeholder : 'City, State, Country' , name : 'birthplace' , required : true , }, { type : 'text' , prompt : \"How old are you?\" , name : 'age' , textbox_columns : 5 , required : false , } ], [ { type : 'multi-choice' , prompt : \"What&#39;s your favorite color?\" , options : [ 'blue' , 'yellow' , 'pink' , 'teal' , 'orange' , 'lime green' , 'other' , 'none of these' ], name : 'FavColor' , }, { type : 'multi-select' , prompt : \"Which of these animals do you like? Select all that apply.\" , options : [ 'lion' , 'squirrel' , 'badger' , 'whale' ], option_reorder : 'random' , columns : 0 , name : 'AnimalLike' , } ] ], title : 'My questionnaire' , button_label_next : 'Continue' , button_label_back : 'Previous' , button_label_finish : 'Submit' , show_question_numbers : 'onPage' }; Open demo in new tab Single and multiple item Likert-style scales Code Demo const trial = { type : jsPsychSurvey , pages : [ [ { type : 'likert' , prompt : 'I like to eat vegetables.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, { type : 'likert' , prompt : 'I like to eat fruit.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, { type : 'likert' , prompt : 'I like to eat meat.' , likert_scale_min_label : 'Strongly Disagree' , likert_scale_max_label : 'Strongly Agree' , likert_scale_values : [ { value : 1 }, { value : 2 }, { value : 3 }, { value : 4 }, { value : 5 } ] }, ], [ { type : 'likert-table' , prompt : ' ' , statements : [ { prompt : 'I like to eat vegetables' , name : 'VeggiesTable' }, { prompt : 'I like to eat fruit' , name : 'FruitTable' }, { prompt : 'I like to eat meat' , name : 'MeatTable' }, ], options : [ 'Strongly Disagree' , 'Disagree' , 'Neutral' , 'Agree' , 'Strongly Agree' ], } ] ], }; Open demo in new tab Response scoring Code Demo const trial = { type : jsPsychSurvey , pages : [ [ { type : 'multi-choice' , prompt : 'During the experiment, are allowed to write things down on paper to help you?' , options : [ \"Yes\" , \"No\" ], correct_response : \"No\" , required : true }, ] ], }; Open demo in new tab Adding data to trial When adding any data to a Survey trial, you should add it via the data parameter at the whole-trial level (not inside the question objects), even if it only relates to one question out of multiple questions/pages contained wihtin the trial. Code Demo const question_info = [ { 'fruit' : 'apples' , 'Q1_prompt' : 'Do you like apples?' , 'Q1_type' : 'regular' }, { 'fruit' : 'bananas' , 'Q1_prompt' : 'Do you NOT like bananas?' , 'Q1_type' : 'reverse' }, ]; const survey = { type : jsPsychSurvey , pages : [ [ { type : 'multi-choice' , prompt : jsPsych . timelineVariable ( 'Q1_prompt' ), options : [ 'Yes' , 'No' ], name : 'Q1' }, { type : 'text' , prompt : function () { return `What's your favorite thing about ${ jsPsych . timelineVariable ( 'fruit' ) } ?` ; }, name : 'Q2' } ] ], // Add data at the whole-trial level here data : { 'Q1_prompt' : jsPsych . timelineVariable ( 'Q1_prompt' ), 'Q1_type' : jsPsych . timelineVariable ( 'Q1_type' ), 'fruit' : jsPsych . timelineVariable ( 'fruit' ) }, button_label_finish : 'Continue' }; const survey_procedure = { timeline : [ survey ], timeline_variables : question_info , randomize_order : true }; Open demo in new tab","title":"Examples"},{"location":"plugins/video-button-response/","text":"video-button-response \u00b6 Current version: 1.1.3. See version history . This plugin plays a video and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the video has finished playing. The button itself can be customized using HTML formatting. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. choices array of strings undefined Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before the button choices are enabled and a response is accepted. Once the video has played all the way through, the buttons are enabled and a response is allowed (including while the video is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-button-response import videoButtonResponse from '@jspsych/plugin-video-button-response' ; Example \u00b6 Responses disabled until the video is complete Code Demo var trial = { type : jsPsychVideoButtonResponse , stimulus : [ 'video/fish.mp4' ], choices : [ '0-5' , '6-10' , '11-15' , '16-20' , '21-25' , '25+' ], prompt : \"<p>How many different fish are shown in the video?</p>\" , response_allowed_while_playing : false }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"video-button-response"},{"location":"plugins/video-button-response/#video-button-response","text":"Current version: 1.1.3. See version history . This plugin plays a video and records responses generated by button click. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a button response from being made before the video has finished playing. The button itself can be customized using HTML formatting. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information.","title":"video-button-response"},{"location":"plugins/video-button-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. choices array of strings undefined Labels for the buttons. Each different string in the array will generate a different button. button_html HTML string '<button class=\"jspsych-btn\">%choice%</button>' A template of HTML for generating the button elements. You can override this to create customized buttons of various kinds. The string %choice% will be changed to the corresponding element of the choices array. You may also specify an array of strings, if you need different HTML to render for each button. If you do specify an array, the choices array and this array must have the same length. The HTML from position 0 in the button_html array will be used to create the button for element 0 in the choices array, and so on. margin_vertical string '0px' Vertical margin of the button(s). margin_horizontal string '8px' Horizontal margin of the button(s). prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before the button choices are enabled and a response is accepted. Once the video has played all the way through, the buttons are enabled and a response is allowed (including while the video is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/video-button-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric Indicates which button the participant pressed. The first button in the choices array is 0, the second is 1, and so on. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/video-button-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/video-button-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-button-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-button-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-button-response import videoButtonResponse from '@jspsych/plugin-video-button-response' ;","title":"Install"},{"location":"plugins/video-button-response/#example","text":"Responses disabled until the video is complete Code Demo var trial = { type : jsPsychVideoButtonResponse , stimulus : [ 'video/fish.mp4' ], choices : [ '0-5' , '6-10' , '11-15' , '16-20' , '21-25' , '25+' ], prompt : \"<p>How many different fish are shown in the video?</p>\" , response_allowed_while_playing : false }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"Example"},{"location":"plugins/video-keyboard-response/","text":"video-keyboard-response \u00b6 Current version: 1.1.3. See version history . This plugin plays a video file and records a keyboard response. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the video has finished playing. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before a keyboard response is accepted. Once the video has played all the way through, a valid keyboard response is allowed (including while the video is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-keyboard-response import videoKeyboardResponse from '@jspsych/plugin-video-keyboard-response' ; Examples \u00b6 Show a video and advance to next trial automatically Code Demo var trial = { type : jsPsychVideoKeyboardResponse , stimulus : [ 'video/fish.mp4' ], choices : \"NO_KEYS\" , trial_ends_after_video : true }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"video-keyboard-response"},{"location":"plugins/video-keyboard-response/#video-keyboard-response","text":"Current version: 1.1.3. See version history . This plugin plays a video file and records a keyboard response. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent a keyboard response from being recorded before the video has finished playing. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information.","title":"video-keyboard-response"},{"location":"plugins/video-keyboard-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. choices array of strings \"ALL_KEYS\" This array contains the key(s) that the participant is allowed to press in order to respond to the stimulus. Keys should be specified as characters (e.g., 'a' , 'q' , ' ' , 'Enter' , 'ArrowDown' ) - see this page and this page (event.key column) for more examples. Any key presses that are not listed in the array will be ignored. The default value of \"ALL_KEYS\" means that all keys will be accepted as valid responses. Specifying \"NO_KEYS\" will mean that no responses are allowed. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before a keyboard response is accepted. Once the video has played all the way through, a valid keyboard response is allowed (including while the video is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/video-keyboard-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/video-keyboard-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/video-keyboard-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-keyboard-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-keyboard-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-keyboard-response import videoKeyboardResponse from '@jspsych/plugin-video-keyboard-response' ;","title":"Install"},{"location":"plugins/video-keyboard-response/#examples","text":"Show a video and advance to next trial automatically Code Demo var trial = { type : jsPsychVideoKeyboardResponse , stimulus : [ 'video/fish.mp4' ], choices : \"NO_KEYS\" , trial_ends_after_video : true }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"Examples"},{"location":"plugins/video-slider-response/","text":"video-slider-response \u00b6 Current version: 1.1.3. See version history . This plugin plays a video and allows the participant to respond by dragging a slider. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the video has finished playing. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information. Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. button_label string 'Continue' Label of the button to end the trial. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before the slider is enabled and the trial can end via the next button click. Once the video has played all the way through, the slider is enabled and a response is allowed (including while the video is being re-played via on-screen playback controls). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. slider_start numeric The starting value of the slider. start numeric The start time of the video clip. Simulation Mode \u00b6 In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-slider-response import videoSliderResponse from '@jspsych/plugin-video-slider-response' ; Example \u00b6 Rate enjoyment of a video clip Code Demo var trial = { type : jsPsychVideoSliderResponse , stimulus : [ 'video/fish.mp4' ], labels : [ \"Hated it\" , \"Loved it\" ], prompt : '<p>Please rate your enjoyment of the video clip.</p>' }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"video-slider-response"},{"location":"plugins/video-slider-response/#video-slider-response","text":"Current version: 1.1.3. See version history . This plugin plays a video and allows the participant to respond by dragging a slider. The stimulus can be displayed until a response is given, or for a pre-determined amount of time. The trial can be ended automatically when the participant responds, when the video file has finished playing, or if the participant has failed to respond within a fixed length of time. You can also prevent the slider response from being made before the video has finished playing. Video files can be automatically preloaded by jsPsych using the preload plugin . However, if you are using timeline variables or another dynamic method to specify the video stimulus, you will need to manually preload the videos. Also note that video preloading is disabled when the experiment is running as a file (i.e. opened directly in the browser, rather than through a server), in order to prevent CORS errors - see the section on Running Experiments for more information.","title":"video-slider-response"},{"location":"plugins/video-slider-response/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description stimulus array undefined An array of file paths to the video. You can specify multiple formats of the same video (e.g., .mp4, .ogg, .webm) to maximize the cross-browser compatibility . Usually .mp4 is a safe cross-browser option. The plugin does not reliably support .mov files. The player will use the first source file in the array that is compatible with the browser, so specify the files in order of preference. prompt string null This string can contain HTML markup. Any content here will be displayed below the stimulus. The intention is that it can be used to provide a reminder about the action the participant is supposed to take (e.g., which key to press). width numeric width of the video file The width of the video display in pixels. height numeric heigh of the video file The height of the video display in pixels. autoplay boolean true If true, the video will begin playing as soon as it has loaded. controls boolean false If true, controls for the video player will be available to the participant. They will be able to pause the video or move the playback to any point in the video. start numeric null If given a value, the video will start at this time point in seconds. stop numeric null If given a value, the video will stop at this time point in seconds. rate numeric null The playback rate of the video. 1 is normal, <1 is slower, >1 is faster. min integer 0 Sets the minimum value of the slider. max integer 100 Sets the maximum value of the slider. slider_start integer 50 Sets the starting value of the slider step integer 1 Sets the step of the slider. This is the smallest amount by which the slider can change. labels array of strings [] Labels displayed at equidistant locations on the slider. For example, two labels will be placed at the ends of the slider. Three labels would place two at the ends and one in the middle. Four will place two at the ends, and the other two will be at 33% and 67% of the slider width. slider_width integer null Set the width of the slider in pixels. If left null, then the width will be equal to the widest element in the display. require_movement boolean false If true, the participant must move the slider before clicking the continue button. button_label string 'Continue' Label of the button to end the trial. trial_ends_after_video bool false If true, then the trial will end as soon as the video file finishes playing. trial_duration numeric null How long to wait for the participant to make a response before ending the trial in milliseconds. If the participant fails to make a response before this timer is reached, the participant's response will be recorded as null for the trial and the trial will end. If the value of this parameter is null, then the trial will wait for a response indefinitely. response_ends_trial boolean true If true, then the trial will end whenever the participant makes a response (assuming they make their response before the cutoff specified by the trial_duration parameter). If false, then the trial will continue until the value for trial_duration is reached. You can set this parameter to false to force the participant to view a stimulus for a fixed amount of time, even if they respond before the time is complete. response_allowed_while_playing boolean true If true, then responses are allowed while the video is playing. If false, then the video must finish playing before the slider is enabled and the trial can end via the next button click. Once the video has played all the way through, the slider is enabled and a response is allowed (including while the video is being re-played via on-screen playback controls).","title":"Parameters"},{"location":"plugins/video-slider-response/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value response numeric The numeric value of the slider. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. stimulus array The stimulus array. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. slider_start numeric The starting value of the slider. start numeric The start time of the video clip.","title":"Data Generated"},{"location":"plugins/video-slider-response/#simulation-mode","text":"In data-only simulation mode, the response_allowed_while_playing parameter does not currently influence the simulated response time. This is because the audio file is not loaded in data-only mode and therefore the length is unknown. This may change in a future version as we improve the simulation modes.","title":"Simulation Mode"},{"location":"plugins/video-slider-response/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-video-slider-response@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-video-slider-response.js\" >< /script> Using NPM: npm install @jspsych/plugin-video-slider-response import videoSliderResponse from '@jspsych/plugin-video-slider-response' ;","title":"Install"},{"location":"plugins/video-slider-response/#example","text":"Rate enjoyment of a video clip Code Demo var trial = { type : jsPsychVideoSliderResponse , stimulus : [ 'video/fish.mp4' ], labels : [ \"Hated it\" , \"Loved it\" ], prompt : '<p>Please rate your enjoyment of the video clip.</p>' }; Stock Footage provided by rjt98, from Pond5 Open demo in new tab","title":"Example"},{"location":"plugins/virtual-chinrest/","text":"virtual-chinrest \u00b6 Current version: 2.0.3. See version history . This plugin provides a \"virtual chinrest\" that can measure the distance between the participant and the screen. It can also standardize the jsPsych page content to a known physical dimension (e.g., ensuring that a 200px wide stimulus is 2.2cm wide on the participant's monitor). This is based on the work of Li, Joo, Yeatman, and Reinecke (2020) , and the plugin code is a modified version of their implementation . We recommend citing their work in any paper that makes use of this plugin. Citation Li, Q., Joo, S. J., Yeatman, J. D., & Reinecke, K. (2020). Controlling for Participants\u2019 Viewing Distance in Large-Scale, Psychophysical Online Experiments Using a Virtual Chinrest. Scientific Reports, 10 (1), 1-11. doi: 10.1038/s41598-019-57204-1 The plugin works in two phases. Phase 1 . To calculate the pixel-to-cm conversion rate for a participant\u2019s display, participants are asked to place a credit card or other item of the same size on the screen and resize an image until it is the same size as the credit card. Since we know the physical dimensions of the card, we can find the conversion rate for the participant's display. Phase 2 . To measure the participant's viewing distance from their screen we use a blind spot task. Participants are asked to focus on a black square on the screen with their right eye closed, while a red dot repeatedly sweeps from right to left. They press the spacebar on their keyboard whenever they perceive that the red dot has disappeared. This part allows the plugin to use the distance between the black square and the red dot when it disappears from eyesight to estimate how far the participant is from the monitor. This estimation assumes that the blind spot is located at 13.5\u00b0 temporally. Parameters \u00b6 Parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Descripton resize_units string \"none\" Units to resize the jsPsych content to after the trial is over: \"none\" \"cm\" \"inch\" or \"deg\" . If \"none\" , no resizing will be done to the jsPsych content after the virtual-chinrest trial ends. pixels_per_unit numeric 100 After the scaling factor is applied, this many pixels will equal one unit of measurement, where the units are indicated by resize_units . This is only used when resizing is done after the trial ends (i.e. the resize_units parameter is not \"none\"). adjustment_prompt HTML string \"Click and drag the lower right corner of the image until it is the same size as a credit card held up to the screen. You can use any card that is the same size as a credit card, like a membership card or driver's license. If you do not have access to a real card you can use a ruler to measure the image width to 3.37 inches or 85.6 mm.\" This string can contain HTML markup. Any content here will be displayed below the card stimulus during the resizing phase. adjustment_button_prompt HTML string \"Click here when the image is the correct size\" Content of the button displayed below the card stimulus during the resizing phase. item_path string null Path of the item to be presented in the card stimulus during the resizing phase. If null then no image is shown, and a solid color background is used instead. An example image is available in /examples/img/card.png item_height_mm numeric 53.98 The known height of the physical item (e.g. credit card) to be measured, in mm. item_width_mm numeric 85.6 The known width of the physical item (e.g. credit card) to be measured, in mm. item_init_size numeric 250 The initial size of the card stimulus, in pixels, along its largest dimension. blindspot_reps numeric 5 How many times to measure the blindspot location. If 0 , blindspot will not be detected, and viewing distance and degree data will not be computed. blindspot_prompt HTML string \"Now we will quickly measure how far away you are sitting. Put your left hand on the space bar. Cover your right eye with your right hand. Using your left eye, focus on the black square. Keep your focus on the black square. The red ball will disappear as it moves from right to left. Press the space bar as soon as the ball disappears. Press the space bar when you are ready to begin. This string can contain HTML markup. Any content here will be displayed above the blindspot task . redo_measurement_button_label HTML string 'No, that is not close. Try again' Text for the button on the viewing distance report page to re-do the viewing distance estimate. If the participant click this button, the blindspot task starts again. blindspot_done_prompt HTML string \"Yes\" Text for the button on the viewing distance report page that can be clicked to accept the viewing distance estimate. blindspot_measurements_prompt HTML string 'Remaining measurements: ' Text accompanying the remaining measurements counter that appears below the blindspot task. viewing_distance_report HTML string \"Based on your responses, you are sitting about <span id='distance-estimate' style='font-weight: bold;'></span> from the screen. Does that seem about right?\" Estimated viewing distance data displayed after blindspot task. If \"none\" is given, viewing distance will not be reported to the participant. The HTML span element with id = distance-estimate returns the distance. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Note: The deg data are only returned if viewing distance is estimated with the blindspot method (px2deg, win_height_deg, win_width_deg, item_width_deg). Name Type Value rt numeric The response time in milliseconds. item_height_mm numeric The height in millimeters of the item to be measured. item_width_mm numeric The width in millimeters of the item to be measured item_height_deg numeric Final height of the resizable div container, in degrees. item_width_deg numeric Final width of the resizable div container, in degrees. item_width_px numeric Final width of the resizable div container, in pixels. px2deg numeric Pixels to degrees conversion factor. px2mm numeric Pixels to millimeters conversion factor. scale_factor numeric Scaling factor that will be applied to the div containing jsPsych content. win_width_deg numeric The interior width of the window in degrees. win_height_deg numeric The interior height of the window in degrees. view_dist_mm numeric Estimated distance to the screen in millimeters. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-virtual-chinrest.js\" >< /script> Using NPM: npm install @jspsych/plugin-virtual-chinrest import virtualChinrest from '@jspsych/plugin-virtual-chinrest' ; Example \u00b6 Measure distance to screen and pixel ratio; no resizing Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"none\" }; This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab Resizing based on centimeters per pixel Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"cm\" , pixels_per_unit : 50 }; var resized_stimulus = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>If the measurements were done correctly, the square below should be 10 cm x 10 cm.</p> <div style=\"background-color: black; width: 500px; height: 500px; margin: 20px auto;\"></div> ` , choices : [ 'Continue' ] } This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab Resizing based on degrees of visual angle per pixel Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"deg\" , pixels_per_unit : 50 }; var resized_stimulus = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>If the measurements were done correctly, the square below should take up about 10 degrees of visual angle.</p> <div style=\"background-color: black; width: 500px; height: 500px; margin: 20px auto;\"></div> ` , choices : [ 'Continue' ] } This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab","title":"virtual-chinrest"},{"location":"plugins/virtual-chinrest/#virtual-chinrest","text":"Current version: 2.0.3. See version history . This plugin provides a \"virtual chinrest\" that can measure the distance between the participant and the screen. It can also standardize the jsPsych page content to a known physical dimension (e.g., ensuring that a 200px wide stimulus is 2.2cm wide on the participant's monitor). This is based on the work of Li, Joo, Yeatman, and Reinecke (2020) , and the plugin code is a modified version of their implementation . We recommend citing their work in any paper that makes use of this plugin. Citation Li, Q., Joo, S. J., Yeatman, J. D., & Reinecke, K. (2020). Controlling for Participants\u2019 Viewing Distance in Large-Scale, Psychophysical Online Experiments Using a Virtual Chinrest. Scientific Reports, 10 (1), 1-11. doi: 10.1038/s41598-019-57204-1 The plugin works in two phases. Phase 1 . To calculate the pixel-to-cm conversion rate for a participant\u2019s display, participants are asked to place a credit card or other item of the same size on the screen and resize an image until it is the same size as the credit card. Since we know the physical dimensions of the card, we can find the conversion rate for the participant's display. Phase 2 . To measure the participant's viewing distance from their screen we use a blind spot task. Participants are asked to focus on a black square on the screen with their right eye closed, while a red dot repeatedly sweeps from right to left. They press the spacebar on their keyboard whenever they perceive that the red dot has disappeared. This part allows the plugin to use the distance between the black square and the red dot when it disappears from eyesight to estimate how far the participant is from the monitor. This estimation assumes that the blind spot is located at 13.5\u00b0 temporally.","title":"virtual-chinrest"},{"location":"plugins/virtual-chinrest/#parameters","text":"Parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Descripton resize_units string \"none\" Units to resize the jsPsych content to after the trial is over: \"none\" \"cm\" \"inch\" or \"deg\" . If \"none\" , no resizing will be done to the jsPsych content after the virtual-chinrest trial ends. pixels_per_unit numeric 100 After the scaling factor is applied, this many pixels will equal one unit of measurement, where the units are indicated by resize_units . This is only used when resizing is done after the trial ends (i.e. the resize_units parameter is not \"none\"). adjustment_prompt HTML string \"Click and drag the lower right corner of the image until it is the same size as a credit card held up to the screen. You can use any card that is the same size as a credit card, like a membership card or driver's license. If you do not have access to a real card you can use a ruler to measure the image width to 3.37 inches or 85.6 mm.\" This string can contain HTML markup. Any content here will be displayed below the card stimulus during the resizing phase. adjustment_button_prompt HTML string \"Click here when the image is the correct size\" Content of the button displayed below the card stimulus during the resizing phase. item_path string null Path of the item to be presented in the card stimulus during the resizing phase. If null then no image is shown, and a solid color background is used instead. An example image is available in /examples/img/card.png item_height_mm numeric 53.98 The known height of the physical item (e.g. credit card) to be measured, in mm. item_width_mm numeric 85.6 The known width of the physical item (e.g. credit card) to be measured, in mm. item_init_size numeric 250 The initial size of the card stimulus, in pixels, along its largest dimension. blindspot_reps numeric 5 How many times to measure the blindspot location. If 0 , blindspot will not be detected, and viewing distance and degree data will not be computed. blindspot_prompt HTML string \"Now we will quickly measure how far away you are sitting. Put your left hand on the space bar. Cover your right eye with your right hand. Using your left eye, focus on the black square. Keep your focus on the black square. The red ball will disappear as it moves from right to left. Press the space bar as soon as the ball disappears. Press the space bar when you are ready to begin. This string can contain HTML markup. Any content here will be displayed above the blindspot task . redo_measurement_button_label HTML string 'No, that is not close. Try again' Text for the button on the viewing distance report page to re-do the viewing distance estimate. If the participant click this button, the blindspot task starts again. blindspot_done_prompt HTML string \"Yes\" Text for the button on the viewing distance report page that can be clicked to accept the viewing distance estimate. blindspot_measurements_prompt HTML string 'Remaining measurements: ' Text accompanying the remaining measurements counter that appears below the blindspot task. viewing_distance_report HTML string \"Based on your responses, you are sitting about <span id='distance-estimate' style='font-weight: bold;'></span> from the screen. Does that seem about right?\" Estimated viewing distance data displayed after blindspot task. If \"none\" is given, viewing distance will not be reported to the participant. The HTML span element with id = distance-estimate returns the distance.","title":"Parameters"},{"location":"plugins/virtual-chinrest/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Note: The deg data are only returned if viewing distance is estimated with the blindspot method (px2deg, win_height_deg, win_width_deg, item_width_deg). Name Type Value rt numeric The response time in milliseconds. item_height_mm numeric The height in millimeters of the item to be measured. item_width_mm numeric The width in millimeters of the item to be measured item_height_deg numeric Final height of the resizable div container, in degrees. item_width_deg numeric Final width of the resizable div container, in degrees. item_width_px numeric Final width of the resizable div container, in pixels. px2deg numeric Pixels to degrees conversion factor. px2mm numeric Pixels to millimeters conversion factor. scale_factor numeric Scaling factor that will be applied to the div containing jsPsych content. win_width_deg numeric The interior width of the window in degrees. win_height_deg numeric The interior height of the window in degrees. view_dist_mm numeric Estimated distance to the screen in millimeters.","title":"Data Generated"},{"location":"plugins/virtual-chinrest/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/virtual-chinrest/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-virtual-chinrest@2.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-virtual-chinrest.js\" >< /script> Using NPM: npm install @jspsych/plugin-virtual-chinrest import virtualChinrest from '@jspsych/plugin-virtual-chinrest' ;","title":"Install"},{"location":"plugins/virtual-chinrest/#example","text":"Measure distance to screen and pixel ratio; no resizing Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"none\" }; This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab Resizing based on centimeters per pixel Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"cm\" , pixels_per_unit : 50 }; var resized_stimulus = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>If the measurements were done correctly, the square below should be 10 cm x 10 cm.</p> <div style=\"background-color: black; width: 500px; height: 500px; margin: 20px auto;\"></div> ` , choices : [ 'Continue' ] } This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab Resizing based on degrees of visual angle per pixel Code Demo var trial = { type : jsPsychVirtualChinrest , blindspot_reps : 3 , resize_units : \"deg\" , pixels_per_unit : 50 }; var resized_stimulus = { type : jsPsychHtmlButtonResponse , stimulus : ` <p>If the measurements were done correctly, the square below should take up about 10 degrees of visual angle.</p> <div style=\"background-color: black; width: 500px; height: 500px; margin: 20px auto;\"></div> ` , choices : [ 'Continue' ] } This demo requires a larger viewing area to complete. Please open the demo in a new tab Open demo in new tab","title":"Example"},{"location":"plugins/visual-search-circle/","text":"visual-search-circle \u00b6 Current version: 1.1.3. See version history . This plugin presents a customizable visual-search task modelled after Wang, Cavanagh, & Green (1994) . The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. Here is an example using normal and backward Ns: Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. The set of images to display must be defined in one of two ways: The target , foil and set_size parameters: the combination of these parameters can be used to construct a 'classic' visual search task, where there is a single foil/distractor image that makes up all of the images in the set, with the exception of the target image if it is present. OR The stimuli parameter: this array that can be used to present any arbitrary set of image files, with or without the target image, with any number of different foils/distractors, and with any number of repeated images. The target_present and fixation_image parameters must always be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target string null Path to image file that is the search target. This parameter must specified when the stimuli set is defined using the target , foil and set_size parameters, but should NOT be specified when using the stimuli parameter. foil string null Path to image file that is the foil/distractor. This image will be repeated for all distractors up to the set_size value. This parameter must specified when the stimuli set is defined using the target , foil and set_size parameters, but should NOT be specified when using the stimuli parameter. set_size numeric null How many items should be displayed, including the target when target_present is true . The foil image will be repeated up to this value when target_present is false , or up to set_size - 1 when target_present is true . This parameter must specified when using the target , foil and set_size parameters to define the stimuli set, but should NOT be specified when using the stimuli parameter. stimuli array of images null Array containing all of the image files to be displayed. This parameter must be specified when NOT using the target , foil , and set_size parameters to define the stimuli set. target_present boolean undefined Is the target present? This parameter must always be specified. When using the target , foil and set_size parameters, false means that the foil image will be repeated up to the set_size, and true means that the target will be presented along with the foil image repeated up to set_size - 1. When using the stimuli parameter, this parameter is only used to determine the response accuracy. fixation_image string undefined Path to image file that is a fixation target. This parameter must always be specified. target_size array [50, 50] Two element array indicating the height and width of the search array element images. fixation_size array [16, 16] Two element array indicating the height and width of the fixation image. circle_diameter numeric 250 The diameter of the search array circle in pixels. target_present_key string 'j' The key to press if the target is present in the search array. target_absent_key string 'f' The key to press if the target is not present in the search array. trial_duration numeric null The maximum amount of time the participant is allowed to search before the trial will continue. A value of null will allow the participant to search indefinitely. fixation_duration numeric 1000 How long to show the fixation image for before the search array (in milliseconds). Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value correct boolean True if the participant gave the correct response. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. set_size numeric The number of items in the search array target_present boolean True if the target is present in the search array locations array Array where each element is the pixel value of the center of an image in the search array. If the target is present, then the first element will represent the location of the target. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions. Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-visual-search-circle.js\" >< /script> Using NPM: npm install @jspsych/plugin-visual-search-circle import visualSearchCircle from '@jspsych/plugin-visual-search-circle' ; Examples \u00b6 Identical distractors Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : `<p>Press J if there is a backwards N.</p> <p>Press F if all the Ns are in the normal orientation.</p>` , choices : [ 'Continue' ] } var trial = { type : jsPsychVisualSearchCircle , target : 'img/backwardN.gif' , foil : 'img/normalN.gif' , fixation_image : 'img/fixation.gif' , target_present : true , set_size : 4 } Open demo in new tab Variety of different distractors Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : `<p>Press E if there is an elephant in the group.</p> <p>Press N if there is no elephant in the group.</p>` , choices : [ 'Continue' ] } var trial = { type : jsPsychVisualSearchCircle , stimuli : [ 'img/elephant.png' , 'img/lion.png' , 'img/monkey.png' ], fixation_image : 'img/fixation.gif' , target_present_key : 'e' , target_absent_key : 'n' , target_present : true } Open demo in new tab","title":"visual-search-circle"},{"location":"plugins/visual-search-circle/#visual-search-circle","text":"Current version: 1.1.3. See version history . This plugin presents a customizable visual-search task modelled after Wang, Cavanagh, & Green (1994) . The participant indicates whether or not a target is present among a set of distractors. The stimuli are displayed in a circle, evenly-spaced, equidistant from a fixation point. Here is an example using normal and backward Ns:","title":"visual-search-circle"},{"location":"plugins/visual-search-circle/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. The set of images to display must be defined in one of two ways: The target , foil and set_size parameters: the combination of these parameters can be used to construct a 'classic' visual search task, where there is a single foil/distractor image that makes up all of the images in the set, with the exception of the target image if it is present. OR The stimuli parameter: this array that can be used to present any arbitrary set of image files, with or without the target image, with any number of different foils/distractors, and with any number of repeated images. The target_present and fixation_image parameters must always be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description target string null Path to image file that is the search target. This parameter must specified when the stimuli set is defined using the target , foil and set_size parameters, but should NOT be specified when using the stimuli parameter. foil string null Path to image file that is the foil/distractor. This image will be repeated for all distractors up to the set_size value. This parameter must specified when the stimuli set is defined using the target , foil and set_size parameters, but should NOT be specified when using the stimuli parameter. set_size numeric null How many items should be displayed, including the target when target_present is true . The foil image will be repeated up to this value when target_present is false , or up to set_size - 1 when target_present is true . This parameter must specified when using the target , foil and set_size parameters to define the stimuli set, but should NOT be specified when using the stimuli parameter. stimuli array of images null Array containing all of the image files to be displayed. This parameter must be specified when NOT using the target , foil , and set_size parameters to define the stimuli set. target_present boolean undefined Is the target present? This parameter must always be specified. When using the target , foil and set_size parameters, false means that the foil image will be repeated up to the set_size, and true means that the target will be presented along with the foil image repeated up to set_size - 1. When using the stimuli parameter, this parameter is only used to determine the response accuracy. fixation_image string undefined Path to image file that is a fixation target. This parameter must always be specified. target_size array [50, 50] Two element array indicating the height and width of the search array element images. fixation_size array [16, 16] Two element array indicating the height and width of the fixation image. circle_diameter numeric 250 The diameter of the search array circle in pixels. target_present_key string 'j' The key to press if the target is present in the search array. target_absent_key string 'f' The key to press if the target is not present in the search array. trial_duration numeric null The maximum amount of time the participant is allowed to search before the trial will continue. A value of null will allow the participant to search indefinitely. fixation_duration numeric 1000 How long to show the fixation image for before the search array (in milliseconds).","title":"Parameters"},{"location":"plugins/visual-search-circle/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value correct boolean True if the participant gave the correct response. response string Indicates which key the participant pressed. rt numeric The response time in milliseconds for the participant to make a response. The time is measured from when the stimulus first appears on the screen until the participant's response. set_size numeric The number of items in the search array target_present boolean True if the target is present in the search array locations array Array where each element is the pixel value of the center of an image in the search array. If the target is present, then the first element will represent the location of the target. This will be encoded as a JSON string when data is saved using the .json() or .csv() functions.","title":"Data Generated"},{"location":"plugins/visual-search-circle/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-visual-search-circle@1.1.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-visual-search-circle.js\" >< /script> Using NPM: npm install @jspsych/plugin-visual-search-circle import visualSearchCircle from '@jspsych/plugin-visual-search-circle' ;","title":"Install"},{"location":"plugins/visual-search-circle/#examples","text":"Identical distractors Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : `<p>Press J if there is a backwards N.</p> <p>Press F if all the Ns are in the normal orientation.</p>` , choices : [ 'Continue' ] } var trial = { type : jsPsychVisualSearchCircle , target : 'img/backwardN.gif' , foil : 'img/normalN.gif' , fixation_image : 'img/fixation.gif' , target_present : true , set_size : 4 } Open demo in new tab Variety of different distractors Code Demo var instructions = { type : jsPsychHtmlButtonResponse , stimulus : `<p>Press E if there is an elephant in the group.</p> <p>Press N if there is no elephant in the group.</p>` , choices : [ 'Continue' ] } var trial = { type : jsPsychVisualSearchCircle , stimuli : [ 'img/elephant.png' , 'img/lion.png' , 'img/monkey.png' ], fixation_image : 'img/fixation.gif' , target_present_key : 'e' , target_absent_key : 'n' , target_present : true } Open demo in new tab","title":"Examples"},{"location":"plugins/webgazer-calibrate/","text":"webgazer-calibrate \u00b6 Current version: 1.0.3. See version history . This plugin can be used to calibrate the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description calibration_points array [[10,10], [10,50], [10,90], [50,10], [50,50], [50,90], [90,10], [90,50], [90,90]] Array of points in [x,y] coordinates. Specified as a percentage of the screen width and height, from the left and top edge. The default grid is 9 points. calibration_mode string 'click' Can specify click to have participants click on calibration points or view to have participants passively watch calibration points. repetitions_per_point numeric 1 The number of times to repeat the sequence of calibration points. point_size numeric 20 Diameter of the calibration points in pixels. randomize_calibration_order bool false Whether to randomize the order of the calibration points. time_to_saccade numeric 1000 If calibration_mode is set to view , then this is the delay before calibrating after showing a point. Gives the participant time to fixate on the new target before assuming that the participant is looking at the target. time_per_point numeric 1000 If calibration_mode is set to view , then this is the length of time to show a point while calibrating. Note that if click calibration is used then the point will remain on the screen until clicked. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value No data currently added by this plugin. Use the webgazer-validate plugin to measure the precision and accuracy of calibration. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-calibrate.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-calibrate import webgazerCalibrate from '@jspsych/plugin-webgazer-calibrate' ; Example \u00b6 Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"webgazer-calibrate"},{"location":"plugins/webgazer-calibrate/#webgazer-calibrate","text":"Current version: 1.0.3. See version history . This plugin can be used to calibrate the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview .","title":"webgazer-calibrate"},{"location":"plugins/webgazer-calibrate/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description calibration_points array [[10,10], [10,50], [10,90], [50,10], [50,50], [50,90], [90,10], [90,50], [90,90]] Array of points in [x,y] coordinates. Specified as a percentage of the screen width and height, from the left and top edge. The default grid is 9 points. calibration_mode string 'click' Can specify click to have participants click on calibration points or view to have participants passively watch calibration points. repetitions_per_point numeric 1 The number of times to repeat the sequence of calibration points. point_size numeric 20 Diameter of the calibration points in pixels. randomize_calibration_order bool false Whether to randomize the order of the calibration points. time_to_saccade numeric 1000 If calibration_mode is set to view , then this is the delay before calibrating after showing a point. Gives the participant time to fixate on the new target before assuming that the participant is looking at the target. time_per_point numeric 1000 If calibration_mode is set to view , then this is the length of time to show a point while calibrating. Note that if click calibration is used then the point will remain on the screen until clicked.","title":"Parameters"},{"location":"plugins/webgazer-calibrate/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value No data currently added by this plugin. Use the webgazer-validate plugin to measure the precision and accuracy of calibration.","title":"Data Generated"},{"location":"plugins/webgazer-calibrate/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/webgazer-calibrate/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-calibrate@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-calibrate.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-calibrate import webgazerCalibrate from '@jspsych/plugin-webgazer-calibrate' ;","title":"Install"},{"location":"plugins/webgazer-calibrate/#example","text":"Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"Example"},{"location":"plugins/webgazer-init-camera/","text":"webgazer-init-camera \u00b6 Current version: 1.0.3. See version history . This plugin initializes the camera and helps the participant center their face in the camera view for using the the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description instructions string too long to put here Instructions for the participant to follow. button_text string Continue The text for the button that participants click to end the trial. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value load_time numeric The time it took for webgazer to initialize. This can be a long time in some situations, so this value is recorded for troubleshooting when participants are reporting difficulty. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-init-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-init-camera import webgazerInitCamera from '@jspsych/plugin-webgazer-init-camera' ; Example \u00b6 Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"webgazer-init-camera"},{"location":"plugins/webgazer-init-camera/#webgazer-init-camera","text":"Current version: 1.0.3. See version history . This plugin initializes the camera and helps the participant center their face in the camera view for using the the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview .","title":"webgazer-init-camera"},{"location":"plugins/webgazer-init-camera/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description instructions string too long to put here Instructions for the participant to follow. button_text string Continue The text for the button that participants click to end the trial.","title":"Parameters"},{"location":"plugins/webgazer-init-camera/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value load_time numeric The time it took for webgazer to initialize. This can be a long time in some situations, so this value is recorded for troubleshooting when participants are reporting difficulty.","title":"Data Generated"},{"location":"plugins/webgazer-init-camera/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/webgazer-init-camera/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-init-camera@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-init-camera.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-init-camera import webgazerInitCamera from '@jspsych/plugin-webgazer-init-camera' ;","title":"Install"},{"location":"plugins/webgazer-init-camera/#example","text":"Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"Example"},{"location":"plugins/webgazer-validate/","text":"webgazer-validate \u00b6 Current version: 1.0.3. See version history . This plugin can be used to measure the accuracy and precision of gaze predictions made by the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview . Parameters \u00b6 In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description validation_points array [[10,10], [10,50], [10,90], [50,10], [50,50], [50,90], [90,10], [90,50], [90,90]] Array of points in [x,y] coordinates. The default grid is 9 points. Meaning of coordinates controlled by validation_point_coordinates parameter. validation_point_coordinates string 'percent' Can specify percent to have validation point coordinates specified in percentage of screen width and height, or center-offset-pixels to specify each point as the distance in pixels from the center of the screen. roi_radius numeric 200 Tolerance around the validation point in pixels when calculating the percent of gaze measurements within the acceptable range. randomize_validation_order bool false Whether to randomize the order of the validation points. time_to_saccade numeric 1000 The delay before validating after showing a point. Gives the participant time to fixate on the new target before assuming that the participant is looking at the target. validation_duration numeric 2000 If calibration_mode is set to view , then this is the length of time to show a point while calibrating. Note that if click calibration is used then the point will remain on the screen until clicked. point_size numeric 20 Diameter of the validation points in pixels. show_validation_data bool false If true then a visualization of the validation data will be shown on the screen after the validation is complete. This will show each measured gaze location color coded by whether it is within the roi_radius of the target point. This is mainly intended for testing and debugging. Data Generated \u00b6 In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value raw_gaze array Raw gaze data for the trial. The array will contain a nested array for each validation point. Within each nested array will be a list of {x,y,dx,dy} values specifying the absolute x and y pixels, as well as the distance from the target for that gaze point. percent_in_roi array The percentage of samples within the roi_radius for each validation point. average_offset array The average x and y distance from each validation point, plus the median distance r of the points from this average offset. samples_per_sec numeric The average number of samples per second. Calculated by finding samples per second for each point and then averaging these estimates together. validation_points array The list of validation points, in the order that they appeared. Simulation Mode \u00b6 This plugin does not yet support simulation mode . Install \u00b6 Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-validate.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-validate import webgazerValidate from '@jspsych/plugin-webgazer-validate' ; Example \u00b6 Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"webgazer-validate"},{"location":"plugins/webgazer-validate/#webgazer-validate","text":"Current version: 1.0.3. See version history . This plugin can be used to measure the accuracy and precision of gaze predictions made by the WebGazer extension . For a narrative description of eye tracking with jsPsych, see the eye tracking overview .","title":"webgazer-validate"},{"location":"plugins/webgazer-validate/#parameters","text":"In addition to the parameters available in all plugins , this plugin accepts the following parameters. Parameters with a default value of undefined must be specified. Other parameters can be left unspecified if the default value is acceptable. Parameter Type Default Value Description validation_points array [[10,10], [10,50], [10,90], [50,10], [50,50], [50,90], [90,10], [90,50], [90,90]] Array of points in [x,y] coordinates. The default grid is 9 points. Meaning of coordinates controlled by validation_point_coordinates parameter. validation_point_coordinates string 'percent' Can specify percent to have validation point coordinates specified in percentage of screen width and height, or center-offset-pixels to specify each point as the distance in pixels from the center of the screen. roi_radius numeric 200 Tolerance around the validation point in pixels when calculating the percent of gaze measurements within the acceptable range. randomize_validation_order bool false Whether to randomize the order of the validation points. time_to_saccade numeric 1000 The delay before validating after showing a point. Gives the participant time to fixate on the new target before assuming that the participant is looking at the target. validation_duration numeric 2000 If calibration_mode is set to view , then this is the length of time to show a point while calibrating. Note that if click calibration is used then the point will remain on the screen until clicked. point_size numeric 20 Diameter of the validation points in pixels. show_validation_data bool false If true then a visualization of the validation data will be shown on the screen after the validation is complete. This will show each measured gaze location color coded by whether it is within the roi_radius of the target point. This is mainly intended for testing and debugging.","title":"Parameters"},{"location":"plugins/webgazer-validate/#data-generated","text":"In addition to the default data collected by all plugins , this plugin collects the following data for each trial. Name Type Value raw_gaze array Raw gaze data for the trial. The array will contain a nested array for each validation point. Within each nested array will be a list of {x,y,dx,dy} values specifying the absolute x and y pixels, as well as the distance from the target for that gaze point. percent_in_roi array The percentage of samples within the roi_radius for each validation point. average_offset array The average x and y distance from each validation point, plus the median distance r of the points from this average offset. samples_per_sec numeric The average number of samples per second. Calculated by finding samples per second for each point and then averaging these estimates together. validation_points array The list of validation points, in the order that they appeared.","title":"Data Generated"},{"location":"plugins/webgazer-validate/#simulation-mode","text":"This plugin does not yet support simulation mode .","title":"Simulation Mode"},{"location":"plugins/webgazer-validate/#install","text":"Using the CDN-hosted JavaScript file: < script src = \"https://unpkg.com/@jspsych/plugin-webgazer-validate@1.0.3\" >< /script> Using the JavaScript file downloaded from a GitHub release dist archive: < script src = \"jspsych/plugin-webgazer-validate.js\" >< /script> Using NPM: npm install @jspsych/plugin-webgazer-validate import webgazerValidate from '@jspsych/plugin-webgazer-validate' ;","title":"Install"},{"location":"plugins/webgazer-validate/#example","text":"Because the eye tracking plugins need to be used in conjunction with each other, please see the example on the eye tracking overview page for an integrated example.","title":"Example"},{"location":"reference/jspsych-data/","text":"jsPsych.data \u00b6 The jsPsych.data module contains functions for interacting with the data generated by jsPsych plugins. jsPsych.data.addProperties \u00b6 jsPsych . data . addProperties ( properties ) Parameters \u00b6 Parameter Type Description properties object Object of key: value pairs to add to the data. Return value \u00b6 Returns nothing. Description \u00b6 This method appends a set of properties to every trial in the data object, including trials that have already occurred and trials that have yet to occur. You can use this to record things like the subject ID or condition assignment. Examples \u00b6 Assigning a subject ID and condition code \u00b6 jsPsych . data . addProperties ({ subject : 1 , condition : 'control' }); jsPsych.data.displayData \u00b6 jsPsych . data . displayData ( format ) Parameters \u00b6 Parameter Type Description format string Specifies whether to display the data in 'csv' or 'json' format. Return value \u00b6 Returns nothing. Description \u00b6 Outputs all of the data collected in the experiment to the screen in either JSON or CSV format. This is a useful method for quick debugging when developing an experiment. Examples \u00b6 Using the on_finish callback function to show data at the end of the experiment \u00b6 var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData ( 'csv' ); } }) jsPsych.data.get \u00b6 jsPsych.data.get() Parameters \u00b6 None. Return value \u00b6 Returns the data collection of all data generated by the experiment. Description \u00b6 This function is the standard starting point for accessing the data generated by the experiment. It returns a DataCollection object, which has several methods that can be used to further filter, aggregate, and view the data. These methods are described under the DataCollection section on this page. Example \u00b6 // select all trials var all_data = jsPsych . data . get (); // get csv representation of data and log to console console . log ( all_data . csv ()); jsPsych.data.getDataByTimelineNode \u00b6 jsPsych . data . getDataByTimelineNode ( node_id ) Parameters \u00b6 Parameter Type Description node_id string The id of the TimelineNodes to get data from. Return value \u00b6 Returns a DataCollection of all of the data generated in a specified TimelineNode. Description \u00b6 Get all the data generated by a specified Timeline. Example \u00b6 var current_node_id = jsPsych . getCurrentTimelineNodeID (); var data_from_current_node = jsPsych . data . getDataByTimelineNode ( current_node_id ); jsPsych.data.getInteractionData \u00b6 jsPsych . data . getInteractionData () Parameters \u00b6 None. Return value \u00b6 Returns a DataCollection object with all of the interaction events. Description \u00b6 jsPsych automatically records a few different kinds of user interaction events. blur events occur when the user clicks on another window or tab during the experiment, indicating that they are no longer interacting with the experiment. focus events occur when the user clicks on the experiment window after having clicked somewhere else first (i.e., generated a blur event). fullscreenenter and fullscreenexit events are triggered by the browser entering and exiting fullscreen mode. However, fullscreenenter events only occur when the script switches the browser to fullscreen mode, e.g., with the fullscreen plugin . Manually entering fullscreen mode does not trigger this event. fullscreenexit events occur whether the user manually exits fullscreen mode or the script exits fullscreen mode. This method returns the DataCollection containing all interaction events. This is useful for tracking whether the participant completed the task without diverting attention to other windows. Events are in the form: { type : 'focus' or 'blur' or 'fullscreenenter' or 'fullscreenexit' , trial : 10 , // the trial number when the event happened time : 13042 // total time elapsed since the start of the experiment } Example \u00b6 var interaction_data = jsPsych . data . getInteractionData (); // log data to console in json format console . log ( interaction_data . json ()); jsPsych.data.getLastTimelineData \u00b6 jsPsych . data . getLastTimelineData () Return value \u00b6 Returns a DataCollection. Description \u00b6 Gets all of the data generated in the same timeline as the last trial. Example \u00b6 var lasttimelinedata = jsPsych . data . getLastTimelineData (); jsPsych.data.getLastTrialData \u00b6 jsPsych . data . getLastTrialData () Return value \u00b6 Returns a DataCollection. Description \u00b6 Gets the data collection containing all data generated by the last trial. Example \u00b6 var lasttrialdata = jsPsych . data . getLastTrialData (); jsPsych.data.getURLVariable \u00b6 jsPsych . data . getURLVariable ( var_name ) Parameters \u00b6 Parameter Type Description var_name string Which variable to get the value of. Return value \u00b6 Returns the value of a variable passed in through the query string. Description \u00b6 For extracting a particular variable passed in through a URL query string. Example \u00b6 // if the URL of the page is: experiment.html?subject=1234&condition=test console . log ( jsPsych . data . getURLVariable ( 'subject' )) // logs \"1234\" console . log ( jsPsych . data . getURLVariable ( 'condition' )) // logs \"test\" jsPsych.data.urlVariables \u00b6 jsPsych . data . urlVariables () Return value \u00b6 Returns an object (associative array) of the variables in the URL query string. Description \u00b6 For extracting variables passed in through a URL query string. Example \u00b6 // if the URL of the page is: experiment.html?subject=1234&condition=test var urlvar = jsPsych . data . urlVariables (); console . log ( urlvar . subject ) // logs \"1234\" console . log ( urlvar . condition ) // logs \"test\" jsPsych.data.write \u00b6 jsPsych . data . write ( data_object ) Parameters \u00b6 Parameter Type Description data_object object Object of key: value pairs to store in jsPsych's data storage as a trial. Return value \u00b6 Returns nothing. Description \u00b6 This method is used by jsPsych.finishTrial for writing data. You should probably not use it to add data. Instead use jsPsych.data.addProperties . Example \u00b6 // don't use this! data should only be written once per trial. use jsPsych.finishTrial to save data. var trial_data = { correct : true , rt : 487 } jsPsych . data . write ( trial_data ); DataCollection \u00b6 All data is stored in the DataCollection object. Using methods like jsPsych.data.get() and jsPsych.data.getLastTrialData() return DataCollections containing the experiment data. This is a list of all of the methods that are available to call on a DataCollection object. .addToAll() \u00b6 Adds a set of properties to all items in the DataCollection. Similar to jsPsych.data.addProperties() , except that it can be applied to a subset of the whole DataCollection by filtering down to a smaller DataCollection first. jsPsych . data . get (). addToAll ({ subject_id : 123 , condition : 'control' }); .addToLast() \u00b6 Adds a set of properties to the last trial in the DataCollection. jsPsych . data . get (). addToLast ({ success : true }); .count() \u00b6 Counts the number of trials in the DataCollection. jsPsych . data . get (). count () .csv() \u00b6 Generates a CSV string representing all of the data in the DataCollection. console . log ( jsPsych . data . get (). csv ()); .filter() \u00b6 Returns a subset of the DataCollection based on the filter. The filter is an object, and trials are only kept in the returned DataCollection if they contain the key: value pair(s) in the filter object. For example, the code below selects all of the trials with a correct response. var correct_trials = jsPsych . data . get (). filter ({ correct : true }); The object can have multiple key: value pairs, and the trials must match all of them in order to be included in the returned collection. // keep only correct trials from the practice phase var correct_practice_trials = jsPsych . data . get (). filter ({ correct : true , phase : 'practice' }); The filter can also be an array of objects. In this case each object in the array acts as an OR filter. As long as the trial has all the key: value pairs of one of the objects in the array, it will appear in the returned collection. // select trials from block 1 and block 5. var trials = jsPsych . data . get (). filter ([{ block : 1 }, { block : 5 }]); The filter method returns a DataCollection object, so methods can be chained onto a single statement. // count the number of correct trials in block 1 var block_1_correct = jsPsych . data . get (). filter ({ block : 1 , correct : true }). count (); .filterColumns() \u00b6 Selects the set of columns listed in the array. This is the opposite of the .ignore() method. // Get only the subject, rt, and condition entries for each trial. const subset_of_data = jsPsych . data . get (). filterColumns ([ 'subject' , 'rt' , 'condition' ]) .filterCustom() \u00b6 This method is similar to the .filter() method, except that it accepts a function as the filter. The function is passed a single argument, containing the data for a trial. If the function returns true the trial is included in the returned DataCollection. // count the number of trials with a response time greater than 2000ms. var too_long = jsPsych . data . get (). filterCustom ( function ( trial ){ return trial . rt > 2000 ; }). count () .first() / .last() \u00b6 Returns a DataCollection containing the first/last n trials. If n is greater than the number of trials in the DataCollection, then these functions will return an array of length equal to the number of trials. If there are no trials in the DataCollection, then these functions will return an empty array. If the n argument is omitted, then the functions will use the default value of 1. If n is zero or a negative number, then these functions will throw an error. var first_trial = jsPsych . data . get (). first ( 1 ); var last_trial_with_correct_response = jsPsych . data . get (). filter ({ correct : true }). last ( 1 ); var last_10_trials = jsPsych . data . get (). last ( 10 ); .ignore() \u00b6 Returns a DataCollection with all instances of a particular key removed from the dataset. // log a csv file that does not contain the internal_node_id values for each trial console . log ( jsPsych . data . get (). ignore ( 'internal_node_id' ). csv ()); .join() \u00b6 Appends one DataCollection onto another and returns the combined collection. // get a DataCollection with all trials that are either correct or // have a response time greater than 200ms. var dc1 = jsPsych . data . get (). filter ({ correct : true }); var dc2 = jsPsych . data . get (). filterCustom ( function ( trial ){ return trial . rt > 200 }); var data = dc1 . join ( dc2 ); .json() \u00b6 Generates a JSON string representing all of the data in the DataCollection. console . log ( jsPsych . data . get (). json ()); .localSave() \u00b6 Saves a CSV or JSON file on the computer running the experiment. If conducting an online experiment, this will download the file onto the subject's computer, and is therefore not a recommended data storage solution for online data collection. Warning: This function may not behave correctly in older browsers. Upgrading to the latest version of any major web browser should solve the problem. // first argument is the format, second is the filename. // the format can be either 'csv' or 'json'. jsPsych . data . get (). localSave ( 'csv' , 'mydata.csv' ); .push() \u00b6 Add a new entry to the DataCollection. This method is mostly used internally, and you shouldn't need to call it under normal circumstances. var data = { correct : true , rt : 500 } jsPsych . data . get (). push ( data ); .readOnly() \u00b6 Creates a copy of the DataCollection so that any modification of the values in the DataCollection will not affect the original. // this line edits the rt property of the first trial jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt = 100 ; // readOnly creates a copy that can be modified without affecting the original jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt // outputs 100 jsPsych . data . get (). readOnly (). first ( 1 ). values ()[ 0 ]. rt = 200 jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt // still outputs 100 .select() \u00b6 Returns a DataColumn object (see documentation below) of a single property from a DataCollection object. var rt_data = jsPsych . data . get (). select ( 'rt' ); rt_data . mean () .uniqueNames() \u00b6 Generates an array of all the unique key names in the set of trials contained in the DataCollection. This is especially useful when setting up a relational database (e.g., MySQL) where the column names need to be specified in advance. console . log ( jsPsych . data . get (). uniqueNames ()); .values() \u00b6 Returns the raw data array associated with the DataCollection. This array is modifiable, so changes to the array and values of objects in the array will change the DataCollection. var raw_data = jsPsych . data . get (). values (); // was response in first trial correct? if ( raw_data [ 0 ]. correct ){ console . log ( 'correct!' ); } else { console . log ( 'incorrect.' ); } DataColumn \u00b6 DataColumn objects represent all the values of a single property in a DataCollection. They are generated by using the .select() method on a DataCollection. Once a DataColumn is generated, the following methods can be used. .all() \u00b6 Checks if all values in the DataColumn return true when passed to a function. The function takes a single argument, which represents one value from the DataColumn. // check if all the response times in the practice phase were under 1000ms jsPsych . data . get (). filter ({ phase : 'practice' }). select ( 'correct' ). all ( function ( x ) { return x < 1000 ; }); .count() \u00b6 Counts the number of values in the DataColumn. // count how many response times there are jsPsych . data . get (). select ( 'rt' ). count (); .frequencies() \u00b6 Counts the number of occurrences of each unique value in the DataColumn. Returns this value as an object, where each key is a unique value and the value of each key is the number of occurrences of that key. // get frequencies of correct and incorrect responses jsPsych . data . get (). select ( 'correct' ). frequencies (); .max() / .min() \u00b6 Returns the maximum or minimum value in a DataColumn. jsPsych . data . get (). select ( 'rt' ). max (); jsPsych . data . get (). select ( 'rt' ). min (); .mean() \u00b6 Returns the average of all the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). mean (); .median() \u00b6 Returns the median of all the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). median (); .sd() \u00b6 Returns the standard deviation of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). sd (); .subset() \u00b6 Filters the DataColumn to include only values that return true when passed through the specified function. // below results will be less than 200. jsPsych . data . get (). select ( 'rt' ). subset ( function ( x ){ return x < 200 ; }). max (); .sum() \u00b6 Returns the sum of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). sum (); .values \u00b6 The raw array of values in the DataColumn. // note that this is not a function call. jsPsych . data . get (). select ( 'rt' ). values ; .variance() \u00b6 Returns the variance of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). variance ();","title":"jsPsych.data"},{"location":"reference/jspsych-data/#jspsychdata","text":"The jsPsych.data module contains functions for interacting with the data generated by jsPsych plugins.","title":"jsPsych.data"},{"location":"reference/jspsych-data/#jspsychdataaddproperties","text":"jsPsych . data . addProperties ( properties )","title":"jsPsych.data.addProperties"},{"location":"reference/jspsych-data/#parameters","text":"Parameter Type Description properties object Object of key: value pairs to add to the data.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-data/#description","text":"This method appends a set of properties to every trial in the data object, including trials that have already occurred and trials that have yet to occur. You can use this to record things like the subject ID or condition assignment.","title":"Description"},{"location":"reference/jspsych-data/#examples","text":"","title":"Examples"},{"location":"reference/jspsych-data/#assigning-a-subject-id-and-condition-code","text":"jsPsych . data . addProperties ({ subject : 1 , condition : 'control' });","title":"Assigning a subject ID and condition code"},{"location":"reference/jspsych-data/#jspsychdatadisplaydata","text":"jsPsych . data . displayData ( format )","title":"jsPsych.data.displayData"},{"location":"reference/jspsych-data/#parameters_1","text":"Parameter Type Description format string Specifies whether to display the data in 'csv' or 'json' format.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_1","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-data/#description_1","text":"Outputs all of the data collected in the experiment to the screen in either JSON or CSV format. This is a useful method for quick debugging when developing an experiment.","title":"Description"},{"location":"reference/jspsych-data/#examples_1","text":"","title":"Examples"},{"location":"reference/jspsych-data/#using-the-on_finish-callback-function-to-show-data-at-the-end-of-the-experiment","text":"var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData ( 'csv' ); } })","title":"Using the on_finish callback function to show data at the end of the experiment"},{"location":"reference/jspsych-data/#jspsychdataget","text":"jsPsych.data.get()","title":"jsPsych.data.get"},{"location":"reference/jspsych-data/#parameters_2","text":"None.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_2","text":"Returns the data collection of all data generated by the experiment.","title":"Return value"},{"location":"reference/jspsych-data/#description_2","text":"This function is the standard starting point for accessing the data generated by the experiment. It returns a DataCollection object, which has several methods that can be used to further filter, aggregate, and view the data. These methods are described under the DataCollection section on this page.","title":"Description"},{"location":"reference/jspsych-data/#example","text":"// select all trials var all_data = jsPsych . data . get (); // get csv representation of data and log to console console . log ( all_data . csv ());","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatagetdatabytimelinenode","text":"jsPsych . data . getDataByTimelineNode ( node_id )","title":"jsPsych.data.getDataByTimelineNode"},{"location":"reference/jspsych-data/#parameters_3","text":"Parameter Type Description node_id string The id of the TimelineNodes to get data from.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_3","text":"Returns a DataCollection of all of the data generated in a specified TimelineNode.","title":"Return value"},{"location":"reference/jspsych-data/#description_3","text":"Get all the data generated by a specified Timeline.","title":"Description"},{"location":"reference/jspsych-data/#example_1","text":"var current_node_id = jsPsych . getCurrentTimelineNodeID (); var data_from_current_node = jsPsych . data . getDataByTimelineNode ( current_node_id );","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatagetinteractiondata","text":"jsPsych . data . getInteractionData ()","title":"jsPsych.data.getInteractionData"},{"location":"reference/jspsych-data/#parameters_4","text":"None.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_4","text":"Returns a DataCollection object with all of the interaction events.","title":"Return value"},{"location":"reference/jspsych-data/#description_4","text":"jsPsych automatically records a few different kinds of user interaction events. blur events occur when the user clicks on another window or tab during the experiment, indicating that they are no longer interacting with the experiment. focus events occur when the user clicks on the experiment window after having clicked somewhere else first (i.e., generated a blur event). fullscreenenter and fullscreenexit events are triggered by the browser entering and exiting fullscreen mode. However, fullscreenenter events only occur when the script switches the browser to fullscreen mode, e.g., with the fullscreen plugin . Manually entering fullscreen mode does not trigger this event. fullscreenexit events occur whether the user manually exits fullscreen mode or the script exits fullscreen mode. This method returns the DataCollection containing all interaction events. This is useful for tracking whether the participant completed the task without diverting attention to other windows. Events are in the form: { type : 'focus' or 'blur' or 'fullscreenenter' or 'fullscreenexit' , trial : 10 , // the trial number when the event happened time : 13042 // total time elapsed since the start of the experiment }","title":"Description"},{"location":"reference/jspsych-data/#example_2","text":"var interaction_data = jsPsych . data . getInteractionData (); // log data to console in json format console . log ( interaction_data . json ());","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatagetlasttimelinedata","text":"jsPsych . data . getLastTimelineData ()","title":"jsPsych.data.getLastTimelineData"},{"location":"reference/jspsych-data/#return-value_5","text":"Returns a DataCollection.","title":"Return value"},{"location":"reference/jspsych-data/#description_5","text":"Gets all of the data generated in the same timeline as the last trial.","title":"Description"},{"location":"reference/jspsych-data/#example_3","text":"var lasttimelinedata = jsPsych . data . getLastTimelineData ();","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatagetlasttrialdata","text":"jsPsych . data . getLastTrialData ()","title":"jsPsych.data.getLastTrialData"},{"location":"reference/jspsych-data/#return-value_6","text":"Returns a DataCollection.","title":"Return value"},{"location":"reference/jspsych-data/#description_6","text":"Gets the data collection containing all data generated by the last trial.","title":"Description"},{"location":"reference/jspsych-data/#example_4","text":"var lasttrialdata = jsPsych . data . getLastTrialData ();","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatageturlvariable","text":"jsPsych . data . getURLVariable ( var_name )","title":"jsPsych.data.getURLVariable"},{"location":"reference/jspsych-data/#parameters_5","text":"Parameter Type Description var_name string Which variable to get the value of.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_7","text":"Returns the value of a variable passed in through the query string.","title":"Return value"},{"location":"reference/jspsych-data/#description_7","text":"For extracting a particular variable passed in through a URL query string.","title":"Description"},{"location":"reference/jspsych-data/#example_5","text":"// if the URL of the page is: experiment.html?subject=1234&condition=test console . log ( jsPsych . data . getURLVariable ( 'subject' )) // logs \"1234\" console . log ( jsPsych . data . getURLVariable ( 'condition' )) // logs \"test\"","title":"Example"},{"location":"reference/jspsych-data/#jspsychdataurlvariables","text":"jsPsych . data . urlVariables ()","title":"jsPsych.data.urlVariables"},{"location":"reference/jspsych-data/#return-value_8","text":"Returns an object (associative array) of the variables in the URL query string.","title":"Return value"},{"location":"reference/jspsych-data/#description_8","text":"For extracting variables passed in through a URL query string.","title":"Description"},{"location":"reference/jspsych-data/#example_6","text":"// if the URL of the page is: experiment.html?subject=1234&condition=test var urlvar = jsPsych . data . urlVariables (); console . log ( urlvar . subject ) // logs \"1234\" console . log ( urlvar . condition ) // logs \"test\"","title":"Example"},{"location":"reference/jspsych-data/#jspsychdatawrite","text":"jsPsych . data . write ( data_object )","title":"jsPsych.data.write"},{"location":"reference/jspsych-data/#parameters_6","text":"Parameter Type Description data_object object Object of key: value pairs to store in jsPsych's data storage as a trial.","title":"Parameters"},{"location":"reference/jspsych-data/#return-value_9","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-data/#description_9","text":"This method is used by jsPsych.finishTrial for writing data. You should probably not use it to add data. Instead use jsPsych.data.addProperties .","title":"Description"},{"location":"reference/jspsych-data/#example_7","text":"// don't use this! data should only be written once per trial. use jsPsych.finishTrial to save data. var trial_data = { correct : true , rt : 487 } jsPsych . data . write ( trial_data );","title":"Example"},{"location":"reference/jspsych-data/#datacollection","text":"All data is stored in the DataCollection object. Using methods like jsPsych.data.get() and jsPsych.data.getLastTrialData() return DataCollections containing the experiment data. This is a list of all of the methods that are available to call on a DataCollection object.","title":"DataCollection"},{"location":"reference/jspsych-data/#addtoall","text":"Adds a set of properties to all items in the DataCollection. Similar to jsPsych.data.addProperties() , except that it can be applied to a subset of the whole DataCollection by filtering down to a smaller DataCollection first. jsPsych . data . get (). addToAll ({ subject_id : 123 , condition : 'control' });","title":".addToAll()"},{"location":"reference/jspsych-data/#addtolast","text":"Adds a set of properties to the last trial in the DataCollection. jsPsych . data . get (). addToLast ({ success : true });","title":".addToLast()"},{"location":"reference/jspsych-data/#count","text":"Counts the number of trials in the DataCollection. jsPsych . data . get (). count ()","title":".count()"},{"location":"reference/jspsych-data/#csv","text":"Generates a CSV string representing all of the data in the DataCollection. console . log ( jsPsych . data . get (). csv ());","title":".csv()"},{"location":"reference/jspsych-data/#filter","text":"Returns a subset of the DataCollection based on the filter. The filter is an object, and trials are only kept in the returned DataCollection if they contain the key: value pair(s) in the filter object. For example, the code below selects all of the trials with a correct response. var correct_trials = jsPsych . data . get (). filter ({ correct : true }); The object can have multiple key: value pairs, and the trials must match all of them in order to be included in the returned collection. // keep only correct trials from the practice phase var correct_practice_trials = jsPsych . data . get (). filter ({ correct : true , phase : 'practice' }); The filter can also be an array of objects. In this case each object in the array acts as an OR filter. As long as the trial has all the key: value pairs of one of the objects in the array, it will appear in the returned collection. // select trials from block 1 and block 5. var trials = jsPsych . data . get (). filter ([{ block : 1 }, { block : 5 }]); The filter method returns a DataCollection object, so methods can be chained onto a single statement. // count the number of correct trials in block 1 var block_1_correct = jsPsych . data . get (). filter ({ block : 1 , correct : true }). count ();","title":".filter()"},{"location":"reference/jspsych-data/#filtercolumns","text":"Selects the set of columns listed in the array. This is the opposite of the .ignore() method. // Get only the subject, rt, and condition entries for each trial. const subset_of_data = jsPsych . data . get (). filterColumns ([ 'subject' , 'rt' , 'condition' ])","title":".filterColumns()"},{"location":"reference/jspsych-data/#filtercustom","text":"This method is similar to the .filter() method, except that it accepts a function as the filter. The function is passed a single argument, containing the data for a trial. If the function returns true the trial is included in the returned DataCollection. // count the number of trials with a response time greater than 2000ms. var too_long = jsPsych . data . get (). filterCustom ( function ( trial ){ return trial . rt > 2000 ; }). count ()","title":".filterCustom()"},{"location":"reference/jspsych-data/#first-last","text":"Returns a DataCollection containing the first/last n trials. If n is greater than the number of trials in the DataCollection, then these functions will return an array of length equal to the number of trials. If there are no trials in the DataCollection, then these functions will return an empty array. If the n argument is omitted, then the functions will use the default value of 1. If n is zero or a negative number, then these functions will throw an error. var first_trial = jsPsych . data . get (). first ( 1 ); var last_trial_with_correct_response = jsPsych . data . get (). filter ({ correct : true }). last ( 1 ); var last_10_trials = jsPsych . data . get (). last ( 10 );","title":".first() / .last()"},{"location":"reference/jspsych-data/#ignore","text":"Returns a DataCollection with all instances of a particular key removed from the dataset. // log a csv file that does not contain the internal_node_id values for each trial console . log ( jsPsych . data . get (). ignore ( 'internal_node_id' ). csv ());","title":".ignore()"},{"location":"reference/jspsych-data/#join","text":"Appends one DataCollection onto another and returns the combined collection. // get a DataCollection with all trials that are either correct or // have a response time greater than 200ms. var dc1 = jsPsych . data . get (). filter ({ correct : true }); var dc2 = jsPsych . data . get (). filterCustom ( function ( trial ){ return trial . rt > 200 }); var data = dc1 . join ( dc2 );","title":".join()"},{"location":"reference/jspsych-data/#json","text":"Generates a JSON string representing all of the data in the DataCollection. console . log ( jsPsych . data . get (). json ());","title":".json()"},{"location":"reference/jspsych-data/#localsave","text":"Saves a CSV or JSON file on the computer running the experiment. If conducting an online experiment, this will download the file onto the subject's computer, and is therefore not a recommended data storage solution for online data collection. Warning: This function may not behave correctly in older browsers. Upgrading to the latest version of any major web browser should solve the problem. // first argument is the format, second is the filename. // the format can be either 'csv' or 'json'. jsPsych . data . get (). localSave ( 'csv' , 'mydata.csv' );","title":".localSave()"},{"location":"reference/jspsych-data/#push","text":"Add a new entry to the DataCollection. This method is mostly used internally, and you shouldn't need to call it under normal circumstances. var data = { correct : true , rt : 500 } jsPsych . data . get (). push ( data );","title":".push()"},{"location":"reference/jspsych-data/#readonly","text":"Creates a copy of the DataCollection so that any modification of the values in the DataCollection will not affect the original. // this line edits the rt property of the first trial jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt = 100 ; // readOnly creates a copy that can be modified without affecting the original jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt // outputs 100 jsPsych . data . get (). readOnly (). first ( 1 ). values ()[ 0 ]. rt = 200 jsPsych . data . get (). first ( 1 ). values ()[ 0 ]. rt // still outputs 100","title":".readOnly()"},{"location":"reference/jspsych-data/#select","text":"Returns a DataColumn object (see documentation below) of a single property from a DataCollection object. var rt_data = jsPsych . data . get (). select ( 'rt' ); rt_data . mean ()","title":".select()"},{"location":"reference/jspsych-data/#uniquenames","text":"Generates an array of all the unique key names in the set of trials contained in the DataCollection. This is especially useful when setting up a relational database (e.g., MySQL) where the column names need to be specified in advance. console . log ( jsPsych . data . get (). uniqueNames ());","title":".uniqueNames()"},{"location":"reference/jspsych-data/#values","text":"Returns the raw data array associated with the DataCollection. This array is modifiable, so changes to the array and values of objects in the array will change the DataCollection. var raw_data = jsPsych . data . get (). values (); // was response in first trial correct? if ( raw_data [ 0 ]. correct ){ console . log ( 'correct!' ); } else { console . log ( 'incorrect.' ); }","title":".values()"},{"location":"reference/jspsych-data/#datacolumn","text":"DataColumn objects represent all the values of a single property in a DataCollection. They are generated by using the .select() method on a DataCollection. Once a DataColumn is generated, the following methods can be used.","title":"DataColumn"},{"location":"reference/jspsych-data/#all","text":"Checks if all values in the DataColumn return true when passed to a function. The function takes a single argument, which represents one value from the DataColumn. // check if all the response times in the practice phase were under 1000ms jsPsych . data . get (). filter ({ phase : 'practice' }). select ( 'correct' ). all ( function ( x ) { return x < 1000 ; });","title":".all()"},{"location":"reference/jspsych-data/#count_1","text":"Counts the number of values in the DataColumn. // count how many response times there are jsPsych . data . get (). select ( 'rt' ). count ();","title":".count()"},{"location":"reference/jspsych-data/#frequencies","text":"Counts the number of occurrences of each unique value in the DataColumn. Returns this value as an object, where each key is a unique value and the value of each key is the number of occurrences of that key. // get frequencies of correct and incorrect responses jsPsych . data . get (). select ( 'correct' ). frequencies ();","title":".frequencies()"},{"location":"reference/jspsych-data/#max-min","text":"Returns the maximum or minimum value in a DataColumn. jsPsych . data . get (). select ( 'rt' ). max (); jsPsych . data . get (). select ( 'rt' ). min ();","title":".max() / .min()"},{"location":"reference/jspsych-data/#mean","text":"Returns the average of all the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). mean ();","title":".mean()"},{"location":"reference/jspsych-data/#median","text":"Returns the median of all the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). median ();","title":".median()"},{"location":"reference/jspsych-data/#sd","text":"Returns the standard deviation of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). sd ();","title":".sd()"},{"location":"reference/jspsych-data/#subset","text":"Filters the DataColumn to include only values that return true when passed through the specified function. // below results will be less than 200. jsPsych . data . get (). select ( 'rt' ). subset ( function ( x ){ return x < 200 ; }). max ();","title":".subset()"},{"location":"reference/jspsych-data/#sum","text":"Returns the sum of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). sum ();","title":".sum()"},{"location":"reference/jspsych-data/#values_1","text":"The raw array of values in the DataColumn. // note that this is not a function call. jsPsych . data . get (). select ( 'rt' ). values ;","title":".values"},{"location":"reference/jspsych-data/#variance","text":"Returns the variance of the values in a DataColumn. jsPsych . data . get (). select ( 'rt' ). variance ();","title":".variance()"},{"location":"reference/jspsych-pluginAPI/","text":"jsPsych.pluginAPI \u00b6 The pluginAPI module contains functions that are useful when developing plugins. All of the functions are accessible through the pluginAPI object. In this documentation we've divided them up based on different kinds of functionality. Keyboard Input \u00b6 cancelAllKeyboardResponses \u00b6 jsPsych . pluginAPI . cancelAllKeyboardResponses () Parameters \u00b6 None. Return value \u00b6 Returns nothing. Description \u00b6 Cancels all currently active keyboard listeners created by jsPsych.pluginAPI.getKeyboardResponse . Example \u00b6 jsPsych . pluginAPI . cancelAllKeyboardResponses (); cancelKeyboardResponse \u00b6 jsPsych . pluginAPI . cancelKeyboardResponse ( listener_id ) Parameters \u00b6 Parameter Type Description listener_id object The listener_id object generated by the call to jsPsych.pluginAPI.getKeyboardResponse . Return value \u00b6 Returns nothing. Description \u00b6 Cancels a specific keyboard listener created by jsPsych.pluginAPI.getKeyboardResponse . Example \u00b6 // create a persistent keyboard listener var listener_id = jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : [ 'p' , 'q' ], rt_method : 'performance' , persist : true , allow_held_key : false }); // cancel keyboard listener jsPsych . pluginAPI . cancelKeyboardResponse ( listener_id ); compareKeys \u00b6 jsPsych . pluginAPI . compareKeys ( key1 , key2 ) Parameters \u00b6 Parameter Type Description key1 string or numeric The representation of a key, either string or keycode key2 string or numeric The representation of a key, either string or keycode Return value \u00b6 Returns true if keycodes or strings refer to the same key, regardless of type. Returns false if the keycodes or strings do not match. Description \u00b6 Compares two keys to see if they are the same, ignoring differences in representational type, and using the appropriate case sensitivity based on the experiment's settings. If case_sensitive_responses is set to false in initJsPsych (the default), then the string key comparison will not be case-sensitive, e.g., \"a\" and \"A\" will match, and this function will return true . If case_sensitive_responses is set to true in initJsPsych , then the string key comparison will not be case-sensitive, e.g., \"a\" and \"A\" will not match, and this function will return false . We recommend using this function to compare keys in all plugin and experiment code, rather than using something like if (response == 'j')... . This is because the response key returned by the jsPsych.pluginAPI.getKeyboardResponse function will be converted to lowercase when case_sensitive_responses is false , and it will match the exact key press representation when case_sensitive_responses is true . Using this compareKeys function will ensure that your key comparisons work appropriately based on the experiment's case_sensitive_responses setting, and that you do not need to remember to check key responses against different case versions of the comparison key (e.g. if (response == 'ArrowLeft' || response == 'arrowleft')... ). Examples \u00b6 Basic examples \u00b6 jsPsych . pluginAPI . compareKeys ( 'a' , 'A' ); // returns true when case_sensitive_responses is false in initJsPsych jsPsych . pluginAPI . compareKeys ( 'a' , 'A' ); // returns false when case_sensitive_responses is true in initJsPsych // also works with numeric key codes (but note that numeric keyCode values are now deprecated) jsPsych . pluginAPI . compareKeys ( 'a' , 65 ); // returns true jsPsych . pluginAPI . compareKeys ( 'space' , 31 ); // returns false Comparing a key response and key parameter value in plugins \u00b6 // this is the callback_function passed to jsPsych.pluginAPI.getKeyboardResponse var after_response = function ( info ) { // score the response by comparing the key that was pressed against the trial's key_answer parameter var correct = jsPsych . pluginAPI . compareKeys ( trial . key_answer , info . key ); //... } Scoring a key response in experiment code \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], prompt : 'Press f for left. Press j for right.' , on_finish : function ( data ){ // score the response by comparing the key that was pressed (data.response) against the // correct response for this trial ('f'), and store reponse accuracy in the trial data if ( jsPsych . pluginAPI . compareKeys ( data . response , 'f' )){ data . correct = true ; } else { data . correct = false ; } } } getKeyboardResponse \u00b6 jsPsych . pluginAPI . getKeyboardResponse ( parameters ) Parameters \u00b6 The method accepts an object of parameter values (see example below). The valid keys for this object are listed in the table below. Parameter Type Description callback_function function The function to execute whenever a valid keyboard response is generated. valid_responses array An array of key codes or character strings representing valid responses. Responses not on the list will be ignored. An empty array indicates that all responses are acceptable. rt_method string Indicates which method of recording time to use. The 'performance' method uses calls to performance.now() , which is the standard way of measuring timing in jsPsych. It is supported by up-to-date versions of all the major browsers . The audio method is used in conjuction with an audio_context (set as an additional parameter). This uses the clock time of the audio_context when audio stimuli are being played. audio_context AudioContext object The AudioContext of the audio file that is being played. audio_context_start_time numeric The scheduled time of the sound file in the AudioContext. This will be used as the start time. allow_held_key boolean If true , then responses will be registered from keys that are being held down. If false , then a held key can only register a response the first time that getKeyboardResponse is called for that key. For example, if a participant holds down the A key before the experiment starts, then the first time getKeyboardResponse is called, the A will register as a key press. However, any future calls to getKeyboardResponse will not register the A until the participant releases the key and presses it again. persist boolean If false, then the keyboard listener will only trigger the first time a valid key is pressed. If true, then it will trigger every time a valid key is pressed until it is explicitly cancelled by jsPsych.pluginAPI.cancelKeyboardResponse or jsPsych.pluginAPI.cancelAllKeyboardResponses . Return value \u00b6 Return an object that uniquely identifies the keyboard listener. This object can be passed to jsPsych.pluginAPI.cancelKeyboardResponse to cancel the keyboard listener. Description \u00b6 Gets a keyboard response from the participant, recording the response time from when the function is first called until a valid response is generated. The keyboard event listener will be bound to the display_element declared in initJsPsych() (or the <body> element if no display_element is specified). This allows jsPsych experiments to be embedded in websites with other content without disrupting the functionality of other UI elements. A valid response triggers the callback_function specified in the parameters. A single argument is passed to the callback function. The argument contains an object with the properties key and rt . key contains the string representation of the response key, and rt contains the response time. This function uses the .key value of the keyboard event, which is case sensitive . When case_sensitive_responses is false in initJsPsych (the default), this function will convert both the valid_responses strings and the response key to lowercase before comparing them, and it will pass the lowercase version of the response key to the callback_function . For example, if valid_responses is ['a'] , then both 'A' and 'a' will be considered valid key presses, and 'a' will be returned as the response key. When case_sensitive_responses is true in initJsPsych , this function will not convert the case when comparing the valid_responses and response key, and it will not convert the case of the response key that is passed to the callback_function . For example, if valid_responses is ['a'] , then 'a' will be the only valid key press, and 'A' (i.e. 'a' with CapsLock on or Shift held down) will not be accepted. Also, if valid_responses includes multiple letter case options (e.g. \"ALL_KEYS\" ), then you may need to check the response key against both letter cases when scoring etc., e.g. if (response == 'ArrowLeft' || response =='arrowleft') ... . Examples \u00b6 Get a single response from any key \u00b6 var after_response = function ( info ){ alert ( 'You pressed key ' + info . key + ' after ' + info . rt + 'ms' ); } jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : \"ALL_KEYS\" , rt_method : 'performance' , persist : false }); Get a responses from a key until the letter q is pressed \u00b6 var after_response = function ( info ){ alert ( 'You pressed key ' + info . key + ' after ' + info . rt + 'ms' ); if ( jsPsych . pluginAPI . compareKeys ( info . key , 'q' )){ / jsPsych . pluginAPI . cancelKeyboardResponse ( listener ); } } var listener = jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : \"ALL_KEYS\" , rt_method : 'performance' , persist : true }); Media \u00b6 getAudioBuffer \u00b6 jsPsych . pluginAPI . getAudioBuffer ( filepath ) Parameters \u00b6 Parameter Type Description filepath string The path to the audio file that was preloaded. Return value \u00b6 Returns a Promise that resolves when the audio file loads. Success handler's parameter will be the audio buffer. If the experiment is running using the WebAudio API it will be an AudioBuffer object. Otherwise, it will be an HTML5 Audio object. The failure handler's parameter is the error generated by preloadAudio . Description \u00b6 Gets an AudioBuffer that can be played with the WebAudio API or an Audio object that can be played with HTML5 Audio. It is strongly recommended that you preload audio files before calling this method. This method will load the files if they are not preloaded, but this may result in delays during the experiment as audio is downloaded. Examples \u00b6 HTML 5 Audio \u00b6 jsPsych . pluginAPI . getAudioBuffer ( 'my-sound.mp3' ) . then ( function ( audio ){ audio . play (); }) . catch ( function ( err ){ console . error ( 'Audio file failed to load' ) }) WebAudio API \u00b6 var context = jsPsych . pluginAPI . audioContext (); jsPsych . pluginAPI . getAudioBuffer ( 'my-sound.mp3' ) . then ( function ( buffer ){ audio = context . createBufferSource (); audio . buffer = buffer ; audio . connect ( context . destination ); audio . start ( context . currentTime ); }) . catch ( function ( err ){ console . error ( 'Audio file failed to load' ) }) See the audio-keyboard-response plugin for an example in a fuller context. getAutoPreloadList \u00b6 jsPsych . pluginAPI . getAutoPreloadList ( timeline ) Parameters \u00b6 Parameter Type Description timeline array An array containing the trial object(s) from which a list of media files should be automatically generated. This array can contain the entire experiment timeline, or any individual parts of a larger timeline, such as specific timeline nodes and trial objects. Return value \u00b6 An object with properties for each media type: images , audio , and video . Each property contains an array of the unique files of that media type that were automatically extracted from the timeline. If no files are found in the timeline for a particular media type, then the array will be empty for that type. Description \u00b6 This method is used to automatically generate lists of unique image, audio, and video files from a timeline. It is used by the preload plugin to generate a list of to-be-preloaded files based on the trials passed to the trials parameter and/or the experiment timeline passed to jsPsych.run (when auto_preload is true). It can be used in custom plugins and experiment code to generate a list of audio/image/video files, based on a timeline. This function will only return files from plugin parameters that are marked as parameter type AUDIO / IMAGE / VIDEO , and only when the preload flag of the corresponding parameter definition has not been set to false , and the trial's parameter value is not a function. When a file path is returned to the trial parameter from a function (including the jsPsych.timelineVariable function), or when the file path is embedded in an HTML string, that file will not be detected by the getAutoPreloadList method. In these cases, the file should be preloaded manually. See Media Preloading for more information. Example \u00b6 var audio_trial = { type : jsPsychAudioKeyboardResponse stimulus : 'file.mp3' } var image_trial = { type : jsPsychImageKeyboardResponse stimulus : 'file.png' } var video_trial = { type : jsPsychVideoKeyboardResponse stimulus : 'file.mp4' } var timeline = [ audio_trial , image_trial , video_trial ]; jsPsych . pluginAPI . getAutoPreloadList ( timeline ); getMicrophoneRecorder \u00b6 jsPsych . pluginAPI . getMicrophoneRecorder () Parameters \u00b6 None Return value \u00b6 A MediaRecorder object connected to the MediaStream for the active microphone. Description \u00b6 Provides access to the MediaRecorder created by initializeMicrophoneRecorder() . If no microphone recorder exists, it returns null . Example \u00b6 const recorder = jsPsych . pluginAPI . getMicrophoneRecorder (); initializeMicrophoneRecorder \u00b6 jsPsych . pluginAPI . initializeMicrophoneRecorder ( stream ) Parameters \u00b6 Parameter Type Description stream MediaStream The MediaStream object from an active microphone device. Return value \u00b6 None. Description \u00b6 Generates a MediaRecorder object from provided MediaStream and stores this for access via getMicrophoneRecorder() . Example \u00b6 const stream = await navigator . mediaDevices . getUserMedia ({ audio : { deviceId : mic_id } }); jsPsych . pluginAPI . initializeMicrophoneRecorder ( stream ); preloadAudio \u00b6 jsPsych . pluginAPI . preloadAudio ( files , callback_complete , callback_load , callback_error ) Parameters \u00b6 Parameter Type Description files array An array of audio file paths to load. The array can be nested (e.g., if images are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the files have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error. Return value \u00b6 Returns nothing. Description \u00b6 This function is used to preload audio files. It is used by the preload plugin, and could be called directly to preload audio files in custom plugins or experiment. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the files are loaded. Thus, it is possible that an audio file would be required for playing before it is done preloading. The callback_complete function will only execute after all the audio files are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below. Examples \u00b6 Basic use \u00b6 var sounds = [ 'file1.mp3' , 'file2.mp3' , 'file3.mp3' ]; jsPsych . pluginAPI . preloadAudio ( sounds , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); } Show progress of loading \u00b6 var sounds = [ 'file1.mp3' , 'file2.mp3' , 'file3.mp3' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadAudio ( sounds , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / sounds . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of audio files' ); } function startExperiment (){ jsPsych . run ( exp ); } preloadImages \u00b6 jsPsych . pluginAPI . preloadImages ( images , callback_complete , callback_load , callback_error ) Parameters \u00b6 Parameter Type Description images array An array of image paths to load. The array can be nested (e.g., if images are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the images have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error. Return value \u00b6 Returns nothing. Description \u00b6 This function is used to preload image files. It is used by the preload plugin, and could be called directly to preload image files in custom plugins or experiment code. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the images are loaded. Thus, it is possible that an image would be required for display before it is done preloading. The callback_complete function will only execute after all the images are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below. Examples \u00b6 Basic use \u00b6 var images = [ 'img/file1.png' , 'img/file2.png' , 'img/file3.png' ]; jsPsych . pluginAPI . preloadImages ( images , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); } Show progress of loading \u00b6 var images = [ 'img/file1.png' , 'img/file2.png' , 'img/file3.png' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadImages ( images , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / images . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of images' ); } function startExperiment (){ jsPsych . run ( exp ); } preloadVideo \u00b6 jsPsych . pluginAPI . preloadVideo ( video , callback_complete , callback_load , callback_error ) Parameters \u00b6 Parameter Type Description video array An array of video paths to load. The array can be nested (e.g., if videos are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the videos have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error. Return value \u00b6 Returns nothing. Description \u00b6 This function is used to preload video files. It is used by the preload plugin, and could be called directly to preload video files in custom plugins or experiment code. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the videos are loaded. Thus, it is possible that a video would be requested before it is done preloading. The callback_complete function will only execute after all the videos are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below. Examples \u00b6 Basic use \u00b6 var videos = [ 'vid/file1.mp4' , 'vid/file2.mp4' , 'vid/file3.mp4' ]; jsPsych . pluginAPI . preloadVideo ( videos , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); } Show progress of loading \u00b6 var videos = [ 'vid/file1.mp4' , 'vid/file2.mp4' , 'vid/file3.mp4' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadVideo ( videos , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / videos . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of videos' ); } function startExperiment (){ jsPsych . run ( exp ); } Simulation \u00b6 clickTarget \u00b6 jsPsych . pluginAPI . clickTarget ( target , delay ) Parameters \u00b6 Parameter Type Description target Element The DOM element to simulate clicking on. delay number Time to wait in milliseconds. The click will be executed after the delay. Return value \u00b6 None Description \u00b6 Simulates clicking on a DOM element by dispatching three MouseEvents on the target : 'mousedown' , then 'mouseup' , then 'click' . If delay is positive, then the events are scheduled to execute after the delay via setTimeout . Example \u00b6 const target = document . querySelector ( '.jspsych-btn' ); jsPsych . pluginAPI . clickTarget ( target , 500 ); ensureSimulationDataConsistency \u00b6 jsPsych . pluginAPI . ensureSimulationDataConsistency ( trial , data ) Parameters \u00b6 Parameter Type Description trial object Parameters for the trial, e.g., those passed to the plugin's trial() method. data object An object containing data for the trial. Return value \u00b6 None. The data object is modified in place by this method. Description \u00b6 Performs some basic consistency checks on the data based on the parameters specified in trial . For example, if trial.choices is \"NO_KEYS\" but data.response is a key string then data.response and data.rt are set to null . Example \u00b6 jsPsych . pluginAPI . ensureSimulationDataConsistency ( trial , data ); fillTextInput \u00b6 jsPsych . pluginAPI . fillTextInput ( target , text , delay ) Parameters \u00b6 Parameter Type Description target HTMLInputElement The input element to fill in with text. text string The text to input. delay number Time to wait in milliseconds. The text will be inserted after the delay. Return value \u00b6 None Description \u00b6 Sets the value of the target HTMLInputElement to equal text . Example \u00b6 const target = document . querySelector ( 'input[type=\"text\"]' ); jsPsych . pluginAPI . fillTextInput ( target , \"hello!\" , 500 ); getValidKey \u00b6 jsPsych . pluginAPI . getValidKey ( choices ) Parameters \u00b6 Parameter Type Description choices \"NO_KEYS\" or \"ALL_KEYS\" or array of strings Representation of the valid keys allowed for a keyboard response used by the getKeyboardResponse method. Return value \u00b6 A valid key given the choices parameter, chosen at random from the possible keys. Description \u00b6 Picks a random key given a set of options. Currently it only picks letters and numbers when choices is \"ALL_KEYS\" . Example \u00b6 const random_key = jsPsych . pluginAPI . getValidKey ( trial . choices ); keyDown \u00b6 jsPsych . pluginAPI . keyDown ( key ) Parameters \u00b6 Parameter Type Description key string The .key property of the corresponding key on the keyboard. Return value \u00b6 None. Description \u00b6 Dispatches a 'keydown' event for the specified key . Example \u00b6 jsPsych . pluginAPI . keyDown ( 'a' ); keyUp \u00b6 jsPsych . pluginAPI . keyUp ( key ) Parameters \u00b6 Parameter Type Description key string The .key property of the corresponding key on the keyboard. Return value \u00b6 None. Description \u00b6 Dispatches a 'keyup' event for the specified key . Example \u00b6 jsPsych . pluginAPI . keyUp ( 'a' ); mergeSimulationData \u00b6 jsPsych . pluginAPI . mergeSimulationData ( default_data , simulation_options ) Parameters \u00b6 Parameter Type Description default_data object An object containing data values for the simulated trial. simulation_options object The simulation_options specified for the trial. Return value \u00b6 An object of data. Description \u00b6 This method merges the default_data with any data specified in simulation_options.data , giving priority to values specified in simulation_options.data . It returns the merged data. Example \u00b6 const default_data = { rt : 500 , response : 'a' } const simulation_options = { data : { rt : 200 } } const data = jsPsych . pluginAPI . mergeSimulationData ( default_data , simulation_options ); data . rt === 200 ; // true Timeouts \u00b6 clearAllTimeouts \u00b6 jsPsych . pluginAPI . clearAllTimeouts () Parameters \u00b6 None. Return value \u00b6 Returns nothing. Description \u00b6 Clears any pending timeouts that were set using jsPsych.pluginAPI.setTimeout(). setTimeout \u00b6 jsPsych . pluginAPI . setTimeout ( callback , delay ) Parameters \u00b6 Parameter Type Description callback function A function to execute after waiting for delay. delay integer Time to wait in milliseconds. Return value \u00b6 Returns the ID of the setTimeout handle. Description \u00b6 This is simply a call to the standard setTimeout function in JavaScript with the added benefit of registering the setTimeout call in a central list. This is useful for scenarios where some other event (the trial ending, aborting the experiment) should stop the execution of queued timeouts. Example \u00b6 // print the time console . log ( Date . now ()) // print the time 1s later jsPsych . pluginAPI . setTimeout ( function (){ console . log ( Date . now ()) }, 1000 );","title":"jsPsych.pluginAPI"},{"location":"reference/jspsych-pluginAPI/#jspsychpluginapi","text":"The pluginAPI module contains functions that are useful when developing plugins. All of the functions are accessible through the pluginAPI object. In this documentation we've divided them up based on different kinds of functionality.","title":"jsPsych.pluginAPI"},{"location":"reference/jspsych-pluginAPI/#keyboard-input","text":"","title":"Keyboard Input"},{"location":"reference/jspsych-pluginAPI/#cancelallkeyboardresponses","text":"jsPsych . pluginAPI . cancelAllKeyboardResponses ()","title":"cancelAllKeyboardResponses"},{"location":"reference/jspsych-pluginAPI/#parameters","text":"None.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description","text":"Cancels all currently active keyboard listeners created by jsPsych.pluginAPI.getKeyboardResponse .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example","text":"jsPsych . pluginAPI . cancelAllKeyboardResponses ();","title":"Example"},{"location":"reference/jspsych-pluginAPI/#cancelkeyboardresponse","text":"jsPsych . pluginAPI . cancelKeyboardResponse ( listener_id )","title":"cancelKeyboardResponse"},{"location":"reference/jspsych-pluginAPI/#parameters_1","text":"Parameter Type Description listener_id object The listener_id object generated by the call to jsPsych.pluginAPI.getKeyboardResponse .","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_1","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_1","text":"Cancels a specific keyboard listener created by jsPsych.pluginAPI.getKeyboardResponse .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_1","text":"// create a persistent keyboard listener var listener_id = jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : [ 'p' , 'q' ], rt_method : 'performance' , persist : true , allow_held_key : false }); // cancel keyboard listener jsPsych . pluginAPI . cancelKeyboardResponse ( listener_id );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#comparekeys","text":"jsPsych . pluginAPI . compareKeys ( key1 , key2 )","title":"compareKeys"},{"location":"reference/jspsych-pluginAPI/#parameters_2","text":"Parameter Type Description key1 string or numeric The representation of a key, either string or keycode key2 string or numeric The representation of a key, either string or keycode","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_2","text":"Returns true if keycodes or strings refer to the same key, regardless of type. Returns false if the keycodes or strings do not match.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_2","text":"Compares two keys to see if they are the same, ignoring differences in representational type, and using the appropriate case sensitivity based on the experiment's settings. If case_sensitive_responses is set to false in initJsPsych (the default), then the string key comparison will not be case-sensitive, e.g., \"a\" and \"A\" will match, and this function will return true . If case_sensitive_responses is set to true in initJsPsych , then the string key comparison will not be case-sensitive, e.g., \"a\" and \"A\" will not match, and this function will return false . We recommend using this function to compare keys in all plugin and experiment code, rather than using something like if (response == 'j')... . This is because the response key returned by the jsPsych.pluginAPI.getKeyboardResponse function will be converted to lowercase when case_sensitive_responses is false , and it will match the exact key press representation when case_sensitive_responses is true . Using this compareKeys function will ensure that your key comparisons work appropriately based on the experiment's case_sensitive_responses setting, and that you do not need to remember to check key responses against different case versions of the comparison key (e.g. if (response == 'ArrowLeft' || response == 'arrowleft')... ).","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#basic-examples","text":"jsPsych . pluginAPI . compareKeys ( 'a' , 'A' ); // returns true when case_sensitive_responses is false in initJsPsych jsPsych . pluginAPI . compareKeys ( 'a' , 'A' ); // returns false when case_sensitive_responses is true in initJsPsych // also works with numeric key codes (but note that numeric keyCode values are now deprecated) jsPsych . pluginAPI . compareKeys ( 'a' , 65 ); // returns true jsPsych . pluginAPI . compareKeys ( 'space' , 31 ); // returns false","title":"Basic examples"},{"location":"reference/jspsych-pluginAPI/#comparing-a-key-response-and-key-parameter-value-in-plugins","text":"// this is the callback_function passed to jsPsych.pluginAPI.getKeyboardResponse var after_response = function ( info ) { // score the response by comparing the key that was pressed against the trial's key_answer parameter var correct = jsPsych . pluginAPI . compareKeys ( trial . key_answer , info . key ); //... }","title":"Comparing a key response and key parameter value in plugins"},{"location":"reference/jspsych-pluginAPI/#scoring-a-key-response-in-experiment-code","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : '<<<<<' , choices : [ 'f' , 'j' ], prompt : 'Press f for left. Press j for right.' , on_finish : function ( data ){ // score the response by comparing the key that was pressed (data.response) against the // correct response for this trial ('f'), and store reponse accuracy in the trial data if ( jsPsych . pluginAPI . compareKeys ( data . response , 'f' )){ data . correct = true ; } else { data . correct = false ; } } }","title":"Scoring a key response in experiment code"},{"location":"reference/jspsych-pluginAPI/#getkeyboardresponse","text":"jsPsych . pluginAPI . getKeyboardResponse ( parameters )","title":"getKeyboardResponse"},{"location":"reference/jspsych-pluginAPI/#parameters_3","text":"The method accepts an object of parameter values (see example below). The valid keys for this object are listed in the table below. Parameter Type Description callback_function function The function to execute whenever a valid keyboard response is generated. valid_responses array An array of key codes or character strings representing valid responses. Responses not on the list will be ignored. An empty array indicates that all responses are acceptable. rt_method string Indicates which method of recording time to use. The 'performance' method uses calls to performance.now() , which is the standard way of measuring timing in jsPsych. It is supported by up-to-date versions of all the major browsers . The audio method is used in conjuction with an audio_context (set as an additional parameter). This uses the clock time of the audio_context when audio stimuli are being played. audio_context AudioContext object The AudioContext of the audio file that is being played. audio_context_start_time numeric The scheduled time of the sound file in the AudioContext. This will be used as the start time. allow_held_key boolean If true , then responses will be registered from keys that are being held down. If false , then a held key can only register a response the first time that getKeyboardResponse is called for that key. For example, if a participant holds down the A key before the experiment starts, then the first time getKeyboardResponse is called, the A will register as a key press. However, any future calls to getKeyboardResponse will not register the A until the participant releases the key and presses it again. persist boolean If false, then the keyboard listener will only trigger the first time a valid key is pressed. If true, then it will trigger every time a valid key is pressed until it is explicitly cancelled by jsPsych.pluginAPI.cancelKeyboardResponse or jsPsych.pluginAPI.cancelAllKeyboardResponses .","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_3","text":"Return an object that uniquely identifies the keyboard listener. This object can be passed to jsPsych.pluginAPI.cancelKeyboardResponse to cancel the keyboard listener.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_3","text":"Gets a keyboard response from the participant, recording the response time from when the function is first called until a valid response is generated. The keyboard event listener will be bound to the display_element declared in initJsPsych() (or the <body> element if no display_element is specified). This allows jsPsych experiments to be embedded in websites with other content without disrupting the functionality of other UI elements. A valid response triggers the callback_function specified in the parameters. A single argument is passed to the callback function. The argument contains an object with the properties key and rt . key contains the string representation of the response key, and rt contains the response time. This function uses the .key value of the keyboard event, which is case sensitive . When case_sensitive_responses is false in initJsPsych (the default), this function will convert both the valid_responses strings and the response key to lowercase before comparing them, and it will pass the lowercase version of the response key to the callback_function . For example, if valid_responses is ['a'] , then both 'A' and 'a' will be considered valid key presses, and 'a' will be returned as the response key. When case_sensitive_responses is true in initJsPsych , this function will not convert the case when comparing the valid_responses and response key, and it will not convert the case of the response key that is passed to the callback_function . For example, if valid_responses is ['a'] , then 'a' will be the only valid key press, and 'A' (i.e. 'a' with CapsLock on or Shift held down) will not be accepted. Also, if valid_responses includes multiple letter case options (e.g. \"ALL_KEYS\" ), then you may need to check the response key against both letter cases when scoring etc., e.g. if (response == 'ArrowLeft' || response =='arrowleft') ... .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_1","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#get-a-single-response-from-any-key","text":"var after_response = function ( info ){ alert ( 'You pressed key ' + info . key + ' after ' + info . rt + 'ms' ); } jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : \"ALL_KEYS\" , rt_method : 'performance' , persist : false });","title":"Get a single response from any key"},{"location":"reference/jspsych-pluginAPI/#get-a-responses-from-a-key-until-the-letter-q-is-pressed","text":"var after_response = function ( info ){ alert ( 'You pressed key ' + info . key + ' after ' + info . rt + 'ms' ); if ( jsPsych . pluginAPI . compareKeys ( info . key , 'q' )){ / jsPsych . pluginAPI . cancelKeyboardResponse ( listener ); } } var listener = jsPsych . pluginAPI . getKeyboardResponse ({ callback_function : after_response , valid_responses : \"ALL_KEYS\" , rt_method : 'performance' , persist : true });","title":"Get a responses from a key until the letter q is pressed"},{"location":"reference/jspsych-pluginAPI/#media","text":"","title":"Media"},{"location":"reference/jspsych-pluginAPI/#getaudiobuffer","text":"jsPsych . pluginAPI . getAudioBuffer ( filepath )","title":"getAudioBuffer"},{"location":"reference/jspsych-pluginAPI/#parameters_4","text":"Parameter Type Description filepath string The path to the audio file that was preloaded.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_4","text":"Returns a Promise that resolves when the audio file loads. Success handler's parameter will be the audio buffer. If the experiment is running using the WebAudio API it will be an AudioBuffer object. Otherwise, it will be an HTML5 Audio object. The failure handler's parameter is the error generated by preloadAudio .","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_4","text":"Gets an AudioBuffer that can be played with the WebAudio API or an Audio object that can be played with HTML5 Audio. It is strongly recommended that you preload audio files before calling this method. This method will load the files if they are not preloaded, but this may result in delays during the experiment as audio is downloaded.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_2","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#html-5-audio","text":"jsPsych . pluginAPI . getAudioBuffer ( 'my-sound.mp3' ) . then ( function ( audio ){ audio . play (); }) . catch ( function ( err ){ console . error ( 'Audio file failed to load' ) })","title":"HTML 5 Audio"},{"location":"reference/jspsych-pluginAPI/#webaudio-api","text":"var context = jsPsych . pluginAPI . audioContext (); jsPsych . pluginAPI . getAudioBuffer ( 'my-sound.mp3' ) . then ( function ( buffer ){ audio = context . createBufferSource (); audio . buffer = buffer ; audio . connect ( context . destination ); audio . start ( context . currentTime ); }) . catch ( function ( err ){ console . error ( 'Audio file failed to load' ) }) See the audio-keyboard-response plugin for an example in a fuller context.","title":"WebAudio API"},{"location":"reference/jspsych-pluginAPI/#getautopreloadlist","text":"jsPsych . pluginAPI . getAutoPreloadList ( timeline )","title":"getAutoPreloadList"},{"location":"reference/jspsych-pluginAPI/#parameters_5","text":"Parameter Type Description timeline array An array containing the trial object(s) from which a list of media files should be automatically generated. This array can contain the entire experiment timeline, or any individual parts of a larger timeline, such as specific timeline nodes and trial objects.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_5","text":"An object with properties for each media type: images , audio , and video . Each property contains an array of the unique files of that media type that were automatically extracted from the timeline. If no files are found in the timeline for a particular media type, then the array will be empty for that type.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_5","text":"This method is used to automatically generate lists of unique image, audio, and video files from a timeline. It is used by the preload plugin to generate a list of to-be-preloaded files based on the trials passed to the trials parameter and/or the experiment timeline passed to jsPsych.run (when auto_preload is true). It can be used in custom plugins and experiment code to generate a list of audio/image/video files, based on a timeline. This function will only return files from plugin parameters that are marked as parameter type AUDIO / IMAGE / VIDEO , and only when the preload flag of the corresponding parameter definition has not been set to false , and the trial's parameter value is not a function. When a file path is returned to the trial parameter from a function (including the jsPsych.timelineVariable function), or when the file path is embedded in an HTML string, that file will not be detected by the getAutoPreloadList method. In these cases, the file should be preloaded manually. See Media Preloading for more information.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_2","text":"var audio_trial = { type : jsPsychAudioKeyboardResponse stimulus : 'file.mp3' } var image_trial = { type : jsPsychImageKeyboardResponse stimulus : 'file.png' } var video_trial = { type : jsPsychVideoKeyboardResponse stimulus : 'file.mp4' } var timeline = [ audio_trial , image_trial , video_trial ]; jsPsych . pluginAPI . getAutoPreloadList ( timeline );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#getmicrophonerecorder","text":"jsPsych . pluginAPI . getMicrophoneRecorder ()","title":"getMicrophoneRecorder"},{"location":"reference/jspsych-pluginAPI/#parameters_6","text":"None","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_6","text":"A MediaRecorder object connected to the MediaStream for the active microphone.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_6","text":"Provides access to the MediaRecorder created by initializeMicrophoneRecorder() . If no microphone recorder exists, it returns null .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_3","text":"const recorder = jsPsych . pluginAPI . getMicrophoneRecorder ();","title":"Example"},{"location":"reference/jspsych-pluginAPI/#initializemicrophonerecorder","text":"jsPsych . pluginAPI . initializeMicrophoneRecorder ( stream )","title":"initializeMicrophoneRecorder"},{"location":"reference/jspsych-pluginAPI/#parameters_7","text":"Parameter Type Description stream MediaStream The MediaStream object from an active microphone device.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_7","text":"None.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_7","text":"Generates a MediaRecorder object from provided MediaStream and stores this for access via getMicrophoneRecorder() .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_4","text":"const stream = await navigator . mediaDevices . getUserMedia ({ audio : { deviceId : mic_id } }); jsPsych . pluginAPI . initializeMicrophoneRecorder ( stream );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#preloadaudio","text":"jsPsych . pluginAPI . preloadAudio ( files , callback_complete , callback_load , callback_error )","title":"preloadAudio"},{"location":"reference/jspsych-pluginAPI/#parameters_8","text":"Parameter Type Description files array An array of audio file paths to load. The array can be nested (e.g., if images are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the files have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_8","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_8","text":"This function is used to preload audio files. It is used by the preload plugin, and could be called directly to preload audio files in custom plugins or experiment. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the files are loaded. Thus, it is possible that an audio file would be required for playing before it is done preloading. The callback_complete function will only execute after all the audio files are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_3","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#basic-use","text":"var sounds = [ 'file1.mp3' , 'file2.mp3' , 'file3.mp3' ]; jsPsych . pluginAPI . preloadAudio ( sounds , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); }","title":"Basic use"},{"location":"reference/jspsych-pluginAPI/#show-progress-of-loading","text":"var sounds = [ 'file1.mp3' , 'file2.mp3' , 'file3.mp3' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadAudio ( sounds , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / sounds . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of audio files' ); } function startExperiment (){ jsPsych . run ( exp ); }","title":"Show progress of loading"},{"location":"reference/jspsych-pluginAPI/#preloadimages","text":"jsPsych . pluginAPI . preloadImages ( images , callback_complete , callback_load , callback_error )","title":"preloadImages"},{"location":"reference/jspsych-pluginAPI/#parameters_9","text":"Parameter Type Description images array An array of image paths to load. The array can be nested (e.g., if images are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the images have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_9","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_9","text":"This function is used to preload image files. It is used by the preload plugin, and could be called directly to preload image files in custom plugins or experiment code. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the images are loaded. Thus, it is possible that an image would be required for display before it is done preloading. The callback_complete function will only execute after all the images are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_4","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#basic-use_1","text":"var images = [ 'img/file1.png' , 'img/file2.png' , 'img/file3.png' ]; jsPsych . pluginAPI . preloadImages ( images , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); }","title":"Basic use"},{"location":"reference/jspsych-pluginAPI/#show-progress-of-loading_1","text":"var images = [ 'img/file1.png' , 'img/file2.png' , 'img/file3.png' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadImages ( images , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / images . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of images' ); } function startExperiment (){ jsPsych . run ( exp ); }","title":"Show progress of loading"},{"location":"reference/jspsych-pluginAPI/#preloadvideo","text":"jsPsych . pluginAPI . preloadVideo ( video , callback_complete , callback_load , callback_error )","title":"preloadVideo"},{"location":"reference/jspsych-pluginAPI/#parameters_10","text":"Parameter Type Description video array An array of video paths to load. The array can be nested (e.g., if videos are in multiple arrays to help sort by condition or task). callback_complete function A function to execute when all the videos have been loaded. callback_load function A function to execute after a single file has been loaded. A single parameter is passed to this function which is the file source (string) that has loaded. callback_error function A function to execute after a single file has produced an error. A single parameter is passed to this function which is the file source (string) that produced the error.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_10","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_10","text":"This function is used to preload video files. It is used by the preload plugin, and could be called directly to preload video files in custom plugins or experiment code. See Media Preloading for more information. It is possible to run this function without specifying a callback function. However, in this case the code will continue executing while the videos are loaded. Thus, it is possible that a video would be requested before it is done preloading. The callback_complete function will only execute after all the videos are loaded, and can be used to control the flow of the experiment (e.g., by starting the experiment in the callback_complete function). The callback_load and callback_error functions are called after each file has either loaded or produced an error, so these functions can also be used to monitor loading progress. See example below.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#examples_5","text":"","title":"Examples"},{"location":"reference/jspsych-pluginAPI/#basic-use_2","text":"var videos = [ 'vid/file1.mp4' , 'vid/file2.mp4' , 'vid/file3.mp4' ]; jsPsych . pluginAPI . preloadVideo ( videos , function (){ startExperiment (); }, function ( file ){ console . log ( 'file loaded: ' , file ); } function ( file ){ console . log ( 'error loading file: ' , file ); } ); function startExperiment (){ jsPsych . run ( exp ); }","title":"Basic use"},{"location":"reference/jspsych-pluginAPI/#show-progress-of-loading_2","text":"var videos = [ 'vid/file1.mp4' , 'vid/file2.mp4' , 'vid/file3.mp4' ]; var n_loaded = 0 ; jsPsych . pluginAPI . preloadVideo ( videos , function (){ startExperiment (); }, function ( file ) { updateLoadedCount ( file ); }); function updateLoadedCount ( file ){ n_loaded ++ ; var percentcomplete = n_loaded / videos . length * 100 ; // could put something fancier here, like a progress bar // or updating text in the DOM. console . log ( 'Loaded ' + percentcomplete + '% of videos' ); } function startExperiment (){ jsPsych . run ( exp ); }","title":"Show progress of loading"},{"location":"reference/jspsych-pluginAPI/#simulation","text":"","title":"Simulation"},{"location":"reference/jspsych-pluginAPI/#clicktarget","text":"jsPsych . pluginAPI . clickTarget ( target , delay )","title":"clickTarget"},{"location":"reference/jspsych-pluginAPI/#parameters_11","text":"Parameter Type Description target Element The DOM element to simulate clicking on. delay number Time to wait in milliseconds. The click will be executed after the delay.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_11","text":"None","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_11","text":"Simulates clicking on a DOM element by dispatching three MouseEvents on the target : 'mousedown' , then 'mouseup' , then 'click' . If delay is positive, then the events are scheduled to execute after the delay via setTimeout .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_5","text":"const target = document . querySelector ( '.jspsych-btn' ); jsPsych . pluginAPI . clickTarget ( target , 500 );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#ensuresimulationdataconsistency","text":"jsPsych . pluginAPI . ensureSimulationDataConsistency ( trial , data )","title":"ensureSimulationDataConsistency"},{"location":"reference/jspsych-pluginAPI/#parameters_12","text":"Parameter Type Description trial object Parameters for the trial, e.g., those passed to the plugin's trial() method. data object An object containing data for the trial.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_12","text":"None. The data object is modified in place by this method.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_12","text":"Performs some basic consistency checks on the data based on the parameters specified in trial . For example, if trial.choices is \"NO_KEYS\" but data.response is a key string then data.response and data.rt are set to null .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_6","text":"jsPsych . pluginAPI . ensureSimulationDataConsistency ( trial , data );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#filltextinput","text":"jsPsych . pluginAPI . fillTextInput ( target , text , delay )","title":"fillTextInput"},{"location":"reference/jspsych-pluginAPI/#parameters_13","text":"Parameter Type Description target HTMLInputElement The input element to fill in with text. text string The text to input. delay number Time to wait in milliseconds. The text will be inserted after the delay.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_13","text":"None","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_13","text":"Sets the value of the target HTMLInputElement to equal text .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_7","text":"const target = document . querySelector ( 'input[type=\"text\"]' ); jsPsych . pluginAPI . fillTextInput ( target , \"hello!\" , 500 );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#getvalidkey","text":"jsPsych . pluginAPI . getValidKey ( choices )","title":"getValidKey"},{"location":"reference/jspsych-pluginAPI/#parameters_14","text":"Parameter Type Description choices \"NO_KEYS\" or \"ALL_KEYS\" or array of strings Representation of the valid keys allowed for a keyboard response used by the getKeyboardResponse method.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_14","text":"A valid key given the choices parameter, chosen at random from the possible keys.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_14","text":"Picks a random key given a set of options. Currently it only picks letters and numbers when choices is \"ALL_KEYS\" .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_8","text":"const random_key = jsPsych . pluginAPI . getValidKey ( trial . choices );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#keydown","text":"jsPsych . pluginAPI . keyDown ( key )","title":"keyDown"},{"location":"reference/jspsych-pluginAPI/#parameters_15","text":"Parameter Type Description key string The .key property of the corresponding key on the keyboard.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_15","text":"None.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_15","text":"Dispatches a 'keydown' event for the specified key .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_9","text":"jsPsych . pluginAPI . keyDown ( 'a' );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#keyup","text":"jsPsych . pluginAPI . keyUp ( key )","title":"keyUp"},{"location":"reference/jspsych-pluginAPI/#parameters_16","text":"Parameter Type Description key string The .key property of the corresponding key on the keyboard.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_16","text":"None.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_16","text":"Dispatches a 'keyup' event for the specified key .","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_10","text":"jsPsych . pluginAPI . keyUp ( 'a' );","title":"Example"},{"location":"reference/jspsych-pluginAPI/#mergesimulationdata","text":"jsPsych . pluginAPI . mergeSimulationData ( default_data , simulation_options )","title":"mergeSimulationData"},{"location":"reference/jspsych-pluginAPI/#parameters_17","text":"Parameter Type Description default_data object An object containing data values for the simulated trial. simulation_options object The simulation_options specified for the trial.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_17","text":"An object of data.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_17","text":"This method merges the default_data with any data specified in simulation_options.data , giving priority to values specified in simulation_options.data . It returns the merged data.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_11","text":"const default_data = { rt : 500 , response : 'a' } const simulation_options = { data : { rt : 200 } } const data = jsPsych . pluginAPI . mergeSimulationData ( default_data , simulation_options ); data . rt === 200 ; // true","title":"Example"},{"location":"reference/jspsych-pluginAPI/#timeouts","text":"","title":"Timeouts"},{"location":"reference/jspsych-pluginAPI/#clearalltimeouts","text":"jsPsych . pluginAPI . clearAllTimeouts ()","title":"clearAllTimeouts"},{"location":"reference/jspsych-pluginAPI/#parameters_18","text":"None.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_18","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_18","text":"Clears any pending timeouts that were set using jsPsych.pluginAPI.setTimeout().","title":"Description"},{"location":"reference/jspsych-pluginAPI/#settimeout","text":"jsPsych . pluginAPI . setTimeout ( callback , delay )","title":"setTimeout"},{"location":"reference/jspsych-pluginAPI/#parameters_19","text":"Parameter Type Description callback function A function to execute after waiting for delay. delay integer Time to wait in milliseconds.","title":"Parameters"},{"location":"reference/jspsych-pluginAPI/#return-value_19","text":"Returns the ID of the setTimeout handle.","title":"Return value"},{"location":"reference/jspsych-pluginAPI/#description_19","text":"This is simply a call to the standard setTimeout function in JavaScript with the added benefit of registering the setTimeout call in a central list. This is useful for scenarios where some other event (the trial ending, aborting the experiment) should stop the execution of queued timeouts.","title":"Description"},{"location":"reference/jspsych-pluginAPI/#example_12","text":"// print the time console . log ( Date . now ()) // print the time 1s later jsPsych . pluginAPI . setTimeout ( function (){ console . log ( Date . now ()) }, 1000 );","title":"Example"},{"location":"reference/jspsych-randomization/","text":"jsPsych.randomization \u00b6 The jsPsych.randomization module contains methods that are useful for generating random lists of trial variables. jsPsych.randomization.factorial \u00b6 jsPsych . randomization . factorial ( factors , repetitions , unpack ) Parameters \u00b6 Parameter Type Description factors object The factors object should contain a property for each different factor. Each property-factor should have a value of an array, with each element of the array corresponding to a level of the factor. repetitions integer The number of times to repeat each unique combination of the factors in the output sample. unpack boolean If true then the output will be an object with a property for each factor in the original factors object. The value of each property-factor will be an array containing the levels of the factor in a random order. The order will be consistent across each property-factor (e.g., the first element of each property-factor will specify one unique combination of the factors). If false , then the return value will be an array of objects where each property-factor contains only a single value. Return value \u00b6 The return value depends on the unpack parameter. See description of the parameter above, and examples below. Description \u00b6 This method takes a list of factors and their levels, and creates a full factorial design by creating each unique combination of the factors. The returned set of combinations is in a random order. Examples \u00b6 Create full factorial design \u00b6 var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 1 ); /* output: full_design = [ {stimulus: 'a.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 100}, ] */ Create full factorial design with repeats \u00b6 var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 2 ); /* output: full_design = [ {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'a.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 200}, ] */ Create full factorial design, unpacked \u00b6 var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 1 , true ); /* output: full_design = { stimulus: ['a.jpg','b.jpg','b.jpg','a.jpg'], ms_delay: [200, 100, 200, 100] ] */ jsPsych.randomization.randomID \u00b6 jsPsych . randomization . randomID ( length ) Parameters \u00b6 Parameter Type Description length integer The length of the randomly generated ID Return value \u00b6 Returns a string of length length where each character is randomly selected from the numbers 0-9 and all lowercase English letters a-z. Description \u00b6 Generates a random string that is likely to be unique. If length is undefined, then the string length is 32. Example \u00b6 console . log ( jsPsych . randomization . randomID ()); // outputs: \"t7dwz0e713pc8juuaayyfvpkdd9un239\" console . log ( jsPsych . randomization . randomID ( 8 )); // outputs: \"3xtpcbck\" jsPsych.randomization.randomInt \u00b6 jsPsych . randomization . randomInt ( lower , upper ) Parameters \u00b6 Parameter Type Description lower integer The smallest value it is possible to generate upper integer The largest value it is possible to generate Return value \u00b6 An integer Description \u00b6 Generates a random integer from lower to upper Example \u00b6 console . log ( jsPsych . randomization . randomInt ( 2 , 4 )); // outputs: 2 or 3 or 4. jsPsych.randomization.repeat \u00b6 jsPsych . randomization . repeat ( array , repetitions , unpack ) Parameters \u00b6 Parameter Type Description array array The array of values to randomize & repeat. repetitions integer or array The number of times to repeat each element of the array in the final sample. If this parameter is defined as an integer, then each element of array is repeated the same number of times. This parameter can also be an array of the same length as array , in which case each element of array will be repeated the number of times defined in the corresponding position of the repetitions array. unpack boolean If each element of array is an object with an equivalent set of properties, then setting unpack to true will make the return value an object with a property for each of the unique properties among the elements of the array . Each property in the output object will be an array containing the values for that property in the randomized order. The order will be consistent across properties. If this is false then the output is just an array containing a randomized order of the original array elements. Return value \u00b6 The return value depends on the unpack parameter. See description of the parameter above, and examples below. Description \u00b6 This method takes an array of values and generates a new random order of the array, with the option of repeating each element of the array a specified number of times. If the array elements are objects with the same set of properties, then this method can optionally return a single object where each property is a randomized order of the properties defined in the original set of objects. This is useful for randomizing sets of parameters that are used to define a jsPsych block. Examples \u00b6 Shuffle an array, no repeats \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 1 ); // output: shuffledArray = [3,2,4,1,5] Shuffle an array with repeats \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 ); // output: shuffledArray = [1,3,4,2,2,4,5,1,5,3] Shuffle an array of objects \u00b6 var trial1 = { stimulus : 'img/faceA.jpg' , correct_key : 'p' , person_name : 'Joe' } var trial2 = { stimulus : 'img/faceB.jpg' , correct_key : 'p' , person_name : 'Fred' } var trial3 = { stimulus : 'img/faceC.jpg' , correct_key : 'q' , person_name : 'Mary' } var myArray = [ trial1 , trial2 , trial3 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 ); // output: shuffledArray = [ trial1, trial3, trial3, trial2, trial1, trial2 ] Shuffle an array of objects, with unpack \u00b6 var trial1 = { stimulus : 'img/faceA.jpg' , correct_key : 'p' , person_name : 'Joe' } var trial2 = { stimulus : 'img/faceB.jpg' , correct_key : 'p' , person_name : 'Fred' } var trial3 = { stimulus : 'img/faceC.jpg' , correct_key : 'q' , person_name : 'Mary' } var myArray = [ trial1 , trial2 , trial3 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 , true ); /* output: shuffledArray = { stimulus: ['img/faceB.jpg','img/faceA.jpg','img/faceC.jpg','img/faceA.jpg','img/faceC.jpg','img/faceB.jpg'], correct_key: ['p', 'p', 'q', 'p', 'q', 'p'], person_name: ['Fred', 'Joe', 'Mary', 'Joe', 'Mary', 'Fred'] } */ jsPsych.randomization.sampleBernoulli \u00b6 jsPsych . randomization . sampleBernoulli ( p ) Parameters \u00b6 Parameter Type Description p number Probability of sampling 1 Return value \u00b6 Returns 0 with probability 1-p and 1 with probability p . Description \u00b6 Generates a random sample from a Bernoulli distribution. Examples \u00b6 Sample a value \u00b6 if ( jsPsych . randomization . sampleBernoulli ( 0.8 )){ // this happens 80% of the time } else { // this happens 20% of the time } jsPsych.randomization.sampleExGaussian \u00b6 jsPsych . randomization . sampleExGaussian ( mean , standard_deviation , rate , positive = false ) Parameters \u00b6 Parameter Type Description mean number Mean of the normal distribution component of the exGaussian standard_deviation number Standard deviation of the normal distribution component of the exGaussian rate number Rate of the exponential distribution component of the exGaussian positive bool If true sample will be constrained to > 0. Return value \u00b6 A random sample from the distribution Description \u00b6 Generates a random sample from an exponentially modified Gaussian distribution. Examples \u00b6 Sample a value \u00b6 var rand_sample_exg = jsPsych . randomization . sampleExGaussian ( 500 , 100 , 0.01 ); jsPsych.randomization.sampleExponential \u00b6 jsPsych . randomization . sampleExponential ( rate ) Parameters \u00b6 Parameter Type Description rate number Rate of the exponential distribution Return value \u00b6 A random sample from the distribution Description \u00b6 Generates a random sample from an exponential distribution. Examples \u00b6 Sample a value \u00b6 var rand_sample_exg = jsPsych . randomization . sampleExponential ( 0.01 ); jsPsych.randomization.sampleNormal \u00b6 jsPsych . randomization . sampleNormal ( mean , standard_deviation ) Parameters \u00b6 Parameter Type Description mean number Mean of the normal distribution standard_deviation number Standard deviation of the normal distribution Return value \u00b6 A random sample from the distribution Description \u00b6 Generates a random sample from a normal distribution. Examples \u00b6 Sample a value \u00b6 var rand_sample_exg = jsPsych . randomization . sampleNormal ( 500 , 250 ); jsPsych.randomization.sampleWithReplacement \u00b6 jsPsych . randomization . sampleWithReplacement ( array , sampleSize , weights ) Parameters \u00b6 Parameter Type Description array array The array of values to sample from sampleSize numeric The number of samples to draw weights array The relative weight of each element in array . This array is normalized, so the values do not need to sum to 1. The length must match the length of array . Return value \u00b6 An array containing the sample. Description \u00b6 This method returns a sample drawn at random from a set of values with replacement. The relative probability of drawing each item can be controlled by specifying the weights . Examples \u00b6 Sample with equal probability \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithReplacement ( myArray , 10 ); // output: sample = [3, 1, 2, 2, 5, 1, 4, 3, 1, 5]; Sample with unequal probability \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithReplacement ( myArray , 10 , [ 6 , 1 , 1 , 1 , 1 ]); // output: sample = [3, 4, 5, 1, 2, 1, 3, 1, 1, 1]; jsPsych.randomization.sampleWithoutReplacement \u00b6 jsPsych . randomization . sampleWithoutReplacement ( array , sampleSize ) Parameters \u00b6 Parameter Type Description array array The array of values to sample from sampleSize numeric The number of samples to draw Return value \u00b6 An array containing the sample. Description \u00b6 This method returns a sample drawn at random from a set of values without replacement. The sample size must be less than or equal to the length of the array. Examples \u00b6 Sample without replacement \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithoutReplacement ( myArray , 2 ); // output: sample = [3,2]; jsPsych.randomization.setSeed \u00b6 jsPsych . randomization . setSeed ( seed ) Parameters \u00b6 Parameter Type Description seed string A seed for the random number generator Return value \u00b6 Returns the seed value. Description \u00b6 This function will override the behavior of Math.random() to produce a seedable pseudo random number generator. It uses the seedrandom package . Note that calling setSeed() will change how Math.random() behaves for the entire document. If you have non-jsPsych components on the page that use Math.random() they will be affected. Using setSeed() without passing in a seed will generate a random 32-bit seed. The seed value will be returned from the function call, allowing you to save it in the data for the experiment if needed. Examples \u00b6 Use a random 32-bit seed and save to data \u00b6 const seed = jsPsych . randomization . setSeed (); jsPsych . data . addProperties ({ rng_seed : seed }); Use your own seed \u00b6 jsPsych . randomization . setSeed ( \"jspsych\" ); jsPsych.randomization.shuffle \u00b6 jsPsych . randomization . shuffle ( array ) Parameters \u00b6 Parameter Type Description array array The array of values to shuffle Return value \u00b6 Returns an array with the same elements as the input array in a random order. Description \u00b6 A simple method for shuffling the order of an array. Examples \u00b6 Shuffle an array \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . shuffle ( myArray ); // output: shuffledArray = [3,2,4,1,5] jsPsych.randomization.shuffleNoRepeats \u00b6 jsPsych . randomization . shuffleNoRepeats ( array , equalityTest ) Parameters \u00b6 Parameter Type Description array array The array of values to shuffle equalityTest function A function to use to evaluate the equality of neighbors in the array. The function should accept two parameters, which are the two elements to be tested. It should return true if they are equal and false if not. The default function, if none is specified, is to use the === operator. This will work for primitive values, but fail for Objects and Arrays. An example function is given below in the examples. Return value \u00b6 Returns an array with the same elements as the input array in a random order, with no repeating neighbors. Description \u00b6 Shuffle an array, ensuring that neighboring elements in the array are different. Warning: if you provide an array that has very few valid permutations with no neighboring elements, then this method will fail and cause the browser to hang. Examples \u00b6 Basic example \u00b6 var myArray = [ 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . shuffleNoRepeats ( myArray ); // output: shuffledArray = [2, 3, 5, 1, 2, 4, 1, 5, 4, 1, 3, 5, 4, 3, 2] Custom equalityTest \u00b6 var myObjects = [ { color : \"blue\" }, { color : \"red\" }, { color : \"yellow\" }, { color : \"orange\" } ]; var repeatedSet = jsPsych . randomization . repeat ( myObjects , 3 ); var shuffled = jsPsych . randomization . shuffleNoRepeats ( repeatedSet , function ( a , b ) { return a . color === b . color }); // console.log(JSON.stringify(shuffled)) // \"[{\"color\":\"red\"},{\"color\":\"yellow\"},{\"color\":\"blue\"},{\"color\":\"yellow\"},{\"color\":\"orange\"},{\"color\":\"red\"},{\"color\":\"yellow\"},{\"color\":\"orange\"},{\"color\":\"blue\"},{\"color\":\"orange\"},{\"color\":\"red\"},{\"color\":\"blue\"}]\"","title":"jsPsych.randomization"},{"location":"reference/jspsych-randomization/#jspsychrandomization","text":"The jsPsych.randomization module contains methods that are useful for generating random lists of trial variables.","title":"jsPsych.randomization"},{"location":"reference/jspsych-randomization/#jspsychrandomizationfactorial","text":"jsPsych . randomization . factorial ( factors , repetitions , unpack )","title":"jsPsych.randomization.factorial"},{"location":"reference/jspsych-randomization/#parameters","text":"Parameter Type Description factors object The factors object should contain a property for each different factor. Each property-factor should have a value of an array, with each element of the array corresponding to a level of the factor. repetitions integer The number of times to repeat each unique combination of the factors in the output sample. unpack boolean If true then the output will be an object with a property for each factor in the original factors object. The value of each property-factor will be an array containing the levels of the factor in a random order. The order will be consistent across each property-factor (e.g., the first element of each property-factor will specify one unique combination of the factors). If false , then the return value will be an array of objects where each property-factor contains only a single value.","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value","text":"The return value depends on the unpack parameter. See description of the parameter above, and examples below.","title":"Return value"},{"location":"reference/jspsych-randomization/#description","text":"This method takes a list of factors and their levels, and creates a full factorial design by creating each unique combination of the factors. The returned set of combinations is in a random order.","title":"Description"},{"location":"reference/jspsych-randomization/#examples","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#create-full-factorial-design","text":"var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 1 ); /* output: full_design = [ {stimulus: 'a.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 100}, ] */","title":"Create full factorial design"},{"location":"reference/jspsych-randomization/#create-full-factorial-design-with-repeats","text":"var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 2 ); /* output: full_design = [ {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'b.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 200}, {stimulus: 'b.jpg', ms_delay: 200}, {stimulus: 'a.jpg', ms_delay: 100}, {stimulus: 'a.jpg', ms_delay: 200}, ] */","title":"Create full factorial design with repeats"},{"location":"reference/jspsych-randomization/#create-full-factorial-design-unpacked","text":"var factors = { stimulus : [ 'a.jpg' , 'b.jpg' ], ms_delay : [ 100 , 200 ] } var full_design = jsPsych . randomization . factorial ( factors , 1 , true ); /* output: full_design = { stimulus: ['a.jpg','b.jpg','b.jpg','a.jpg'], ms_delay: [200, 100, 200, 100] ] */","title":"Create full factorial design, unpacked"},{"location":"reference/jspsych-randomization/#jspsychrandomizationrandomid","text":"jsPsych . randomization . randomID ( length )","title":"jsPsych.randomization.randomID"},{"location":"reference/jspsych-randomization/#parameters_1","text":"Parameter Type Description length integer The length of the randomly generated ID","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_1","text":"Returns a string of length length where each character is randomly selected from the numbers 0-9 and all lowercase English letters a-z.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_1","text":"Generates a random string that is likely to be unique. If length is undefined, then the string length is 32.","title":"Description"},{"location":"reference/jspsych-randomization/#example","text":"console . log ( jsPsych . randomization . randomID ()); // outputs: \"t7dwz0e713pc8juuaayyfvpkdd9un239\" console . log ( jsPsych . randomization . randomID ( 8 )); // outputs: \"3xtpcbck\"","title":"Example"},{"location":"reference/jspsych-randomization/#jspsychrandomizationrandomint","text":"jsPsych . randomization . randomInt ( lower , upper )","title":"jsPsych.randomization.randomInt"},{"location":"reference/jspsych-randomization/#parameters_2","text":"Parameter Type Description lower integer The smallest value it is possible to generate upper integer The largest value it is possible to generate","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_2","text":"An integer","title":"Return value"},{"location":"reference/jspsych-randomization/#description_2","text":"Generates a random integer from lower to upper","title":"Description"},{"location":"reference/jspsych-randomization/#example_1","text":"console . log ( jsPsych . randomization . randomInt ( 2 , 4 )); // outputs: 2 or 3 or 4.","title":"Example"},{"location":"reference/jspsych-randomization/#jspsychrandomizationrepeat","text":"jsPsych . randomization . repeat ( array , repetitions , unpack )","title":"jsPsych.randomization.repeat"},{"location":"reference/jspsych-randomization/#parameters_3","text":"Parameter Type Description array array The array of values to randomize & repeat. repetitions integer or array The number of times to repeat each element of the array in the final sample. If this parameter is defined as an integer, then each element of array is repeated the same number of times. This parameter can also be an array of the same length as array , in which case each element of array will be repeated the number of times defined in the corresponding position of the repetitions array. unpack boolean If each element of array is an object with an equivalent set of properties, then setting unpack to true will make the return value an object with a property for each of the unique properties among the elements of the array . Each property in the output object will be an array containing the values for that property in the randomized order. The order will be consistent across properties. If this is false then the output is just an array containing a randomized order of the original array elements.","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_3","text":"The return value depends on the unpack parameter. See description of the parameter above, and examples below.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_3","text":"This method takes an array of values and generates a new random order of the array, with the option of repeating each element of the array a specified number of times. If the array elements are objects with the same set of properties, then this method can optionally return a single object where each property is a randomized order of the properties defined in the original set of objects. This is useful for randomizing sets of parameters that are used to define a jsPsych block.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_1","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#shuffle-an-array-no-repeats","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 1 ); // output: shuffledArray = [3,2,4,1,5]","title":"Shuffle an array, no repeats"},{"location":"reference/jspsych-randomization/#shuffle-an-array-with-repeats","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 ); // output: shuffledArray = [1,3,4,2,2,4,5,1,5,3]","title":"Shuffle an array with repeats"},{"location":"reference/jspsych-randomization/#shuffle-an-array-of-objects","text":"var trial1 = { stimulus : 'img/faceA.jpg' , correct_key : 'p' , person_name : 'Joe' } var trial2 = { stimulus : 'img/faceB.jpg' , correct_key : 'p' , person_name : 'Fred' } var trial3 = { stimulus : 'img/faceC.jpg' , correct_key : 'q' , person_name : 'Mary' } var myArray = [ trial1 , trial2 , trial3 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 ); // output: shuffledArray = [ trial1, trial3, trial3, trial2, trial1, trial2 ]","title":"Shuffle an array of objects"},{"location":"reference/jspsych-randomization/#shuffle-an-array-of-objects-with-unpack","text":"var trial1 = { stimulus : 'img/faceA.jpg' , correct_key : 'p' , person_name : 'Joe' } var trial2 = { stimulus : 'img/faceB.jpg' , correct_key : 'p' , person_name : 'Fred' } var trial3 = { stimulus : 'img/faceC.jpg' , correct_key : 'q' , person_name : 'Mary' } var myArray = [ trial1 , trial2 , trial3 ]; var shuffledArray = jsPsych . randomization . repeat ( myArray , 2 , true ); /* output: shuffledArray = { stimulus: ['img/faceB.jpg','img/faceA.jpg','img/faceC.jpg','img/faceA.jpg','img/faceC.jpg','img/faceB.jpg'], correct_key: ['p', 'p', 'q', 'p', 'q', 'p'], person_name: ['Fred', 'Joe', 'Mary', 'Joe', 'Mary', 'Fred'] } */","title":"Shuffle an array of objects, with unpack"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsamplebernoulli","text":"jsPsych . randomization . sampleBernoulli ( p )","title":"jsPsych.randomization.sampleBernoulli"},{"location":"reference/jspsych-randomization/#parameters_4","text":"Parameter Type Description p number Probability of sampling 1","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_4","text":"Returns 0 with probability 1-p and 1 with probability p .","title":"Return value"},{"location":"reference/jspsych-randomization/#description_4","text":"Generates a random sample from a Bernoulli distribution.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_2","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-a-value","text":"if ( jsPsych . randomization . sampleBernoulli ( 0.8 )){ // this happens 80% of the time } else { // this happens 20% of the time }","title":"Sample a value"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsampleexgaussian","text":"jsPsych . randomization . sampleExGaussian ( mean , standard_deviation , rate , positive = false )","title":"jsPsych.randomization.sampleExGaussian"},{"location":"reference/jspsych-randomization/#parameters_5","text":"Parameter Type Description mean number Mean of the normal distribution component of the exGaussian standard_deviation number Standard deviation of the normal distribution component of the exGaussian rate number Rate of the exponential distribution component of the exGaussian positive bool If true sample will be constrained to > 0.","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_5","text":"A random sample from the distribution","title":"Return value"},{"location":"reference/jspsych-randomization/#description_5","text":"Generates a random sample from an exponentially modified Gaussian distribution.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_3","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-a-value_1","text":"var rand_sample_exg = jsPsych . randomization . sampleExGaussian ( 500 , 100 , 0.01 );","title":"Sample a value"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsampleexponential","text":"jsPsych . randomization . sampleExponential ( rate )","title":"jsPsych.randomization.sampleExponential"},{"location":"reference/jspsych-randomization/#parameters_6","text":"Parameter Type Description rate number Rate of the exponential distribution","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_6","text":"A random sample from the distribution","title":"Return value"},{"location":"reference/jspsych-randomization/#description_6","text":"Generates a random sample from an exponential distribution.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_4","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-a-value_2","text":"var rand_sample_exg = jsPsych . randomization . sampleExponential ( 0.01 );","title":"Sample a value"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsamplenormal","text":"jsPsych . randomization . sampleNormal ( mean , standard_deviation )","title":"jsPsych.randomization.sampleNormal"},{"location":"reference/jspsych-randomization/#parameters_7","text":"Parameter Type Description mean number Mean of the normal distribution standard_deviation number Standard deviation of the normal distribution","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_7","text":"A random sample from the distribution","title":"Return value"},{"location":"reference/jspsych-randomization/#description_7","text":"Generates a random sample from a normal distribution.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_5","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-a-value_3","text":"var rand_sample_exg = jsPsych . randomization . sampleNormal ( 500 , 250 );","title":"Sample a value"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsamplewithreplacement","text":"jsPsych . randomization . sampleWithReplacement ( array , sampleSize , weights )","title":"jsPsych.randomization.sampleWithReplacement"},{"location":"reference/jspsych-randomization/#parameters_8","text":"Parameter Type Description array array The array of values to sample from sampleSize numeric The number of samples to draw weights array The relative weight of each element in array . This array is normalized, so the values do not need to sum to 1. The length must match the length of array .","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_8","text":"An array containing the sample.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_8","text":"This method returns a sample drawn at random from a set of values with replacement. The relative probability of drawing each item can be controlled by specifying the weights .","title":"Description"},{"location":"reference/jspsych-randomization/#examples_6","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-with-equal-probability","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithReplacement ( myArray , 10 ); // output: sample = [3, 1, 2, 2, 5, 1, 4, 3, 1, 5];","title":"Sample with equal probability"},{"location":"reference/jspsych-randomization/#sample-with-unequal-probability","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithReplacement ( myArray , 10 , [ 6 , 1 , 1 , 1 , 1 ]); // output: sample = [3, 4, 5, 1, 2, 1, 3, 1, 1, 1];","title":"Sample with unequal probability"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsamplewithoutreplacement","text":"jsPsych . randomization . sampleWithoutReplacement ( array , sampleSize )","title":"jsPsych.randomization.sampleWithoutReplacement"},{"location":"reference/jspsych-randomization/#parameters_9","text":"Parameter Type Description array array The array of values to sample from sampleSize numeric The number of samples to draw","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_9","text":"An array containing the sample.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_9","text":"This method returns a sample drawn at random from a set of values without replacement. The sample size must be less than or equal to the length of the array.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_7","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#sample-without-replacement","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var sample = jsPsych . randomization . sampleWithoutReplacement ( myArray , 2 ); // output: sample = [3,2];","title":"Sample without replacement"},{"location":"reference/jspsych-randomization/#jspsychrandomizationsetseed","text":"jsPsych . randomization . setSeed ( seed )","title":"jsPsych.randomization.setSeed"},{"location":"reference/jspsych-randomization/#parameters_10","text":"Parameter Type Description seed string A seed for the random number generator","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_10","text":"Returns the seed value.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_10","text":"This function will override the behavior of Math.random() to produce a seedable pseudo random number generator. It uses the seedrandom package . Note that calling setSeed() will change how Math.random() behaves for the entire document. If you have non-jsPsych components on the page that use Math.random() they will be affected. Using setSeed() without passing in a seed will generate a random 32-bit seed. The seed value will be returned from the function call, allowing you to save it in the data for the experiment if needed.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_8","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#use-a-random-32-bit-seed-and-save-to-data","text":"const seed = jsPsych . randomization . setSeed (); jsPsych . data . addProperties ({ rng_seed : seed });","title":"Use a random 32-bit seed and save to data"},{"location":"reference/jspsych-randomization/#use-your-own-seed","text":"jsPsych . randomization . setSeed ( \"jspsych\" );","title":"Use your own seed"},{"location":"reference/jspsych-randomization/#jspsychrandomizationshuffle","text":"jsPsych . randomization . shuffle ( array )","title":"jsPsych.randomization.shuffle"},{"location":"reference/jspsych-randomization/#parameters_11","text":"Parameter Type Description array array The array of values to shuffle","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_11","text":"Returns an array with the same elements as the input array in a random order.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_11","text":"A simple method for shuffling the order of an array.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_9","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#shuffle-an-array","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . shuffle ( myArray ); // output: shuffledArray = [3,2,4,1,5]","title":"Shuffle an array"},{"location":"reference/jspsych-randomization/#jspsychrandomizationshufflenorepeats","text":"jsPsych . randomization . shuffleNoRepeats ( array , equalityTest )","title":"jsPsych.randomization.shuffleNoRepeats"},{"location":"reference/jspsych-randomization/#parameters_12","text":"Parameter Type Description array array The array of values to shuffle equalityTest function A function to use to evaluate the equality of neighbors in the array. The function should accept two parameters, which are the two elements to be tested. It should return true if they are equal and false if not. The default function, if none is specified, is to use the === operator. This will work for primitive values, but fail for Objects and Arrays. An example function is given below in the examples.","title":"Parameters"},{"location":"reference/jspsych-randomization/#return-value_12","text":"Returns an array with the same elements as the input array in a random order, with no repeating neighbors.","title":"Return value"},{"location":"reference/jspsych-randomization/#description_12","text":"Shuffle an array, ensuring that neighboring elements in the array are different. Warning: if you provide an array that has very few valid permutations with no neighboring elements, then this method will fail and cause the browser to hang.","title":"Description"},{"location":"reference/jspsych-randomization/#examples_10","text":"","title":"Examples"},{"location":"reference/jspsych-randomization/#basic-example","text":"var myArray = [ 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 ]; var shuffledArray = jsPsych . randomization . shuffleNoRepeats ( myArray ); // output: shuffledArray = [2, 3, 5, 1, 2, 4, 1, 5, 4, 1, 3, 5, 4, 3, 2]","title":"Basic example"},{"location":"reference/jspsych-randomization/#custom-equalitytest","text":"var myObjects = [ { color : \"blue\" }, { color : \"red\" }, { color : \"yellow\" }, { color : \"orange\" } ]; var repeatedSet = jsPsych . randomization . repeat ( myObjects , 3 ); var shuffled = jsPsych . randomization . shuffleNoRepeats ( repeatedSet , function ( a , b ) { return a . color === b . color }); // console.log(JSON.stringify(shuffled)) // \"[{\"color\":\"red\"},{\"color\":\"yellow\"},{\"color\":\"blue\"},{\"color\":\"yellow\"},{\"color\":\"orange\"},{\"color\":\"red\"},{\"color\":\"yellow\"},{\"color\":\"orange\"},{\"color\":\"blue\"},{\"color\":\"orange\"},{\"color\":\"red\"},{\"color\":\"blue\"}]\"","title":"Custom equalityTest"},{"location":"reference/jspsych-turk/","text":"jsPsych.turk \u00b6 The jsPsych.turk module contains functions for interacting with Mechanical Turk. jsPsych.turk.submitToTurk \u00b6 jsPsych . turk . submitToTurk ( data ) Parameters \u00b6 Parameter Type Description data object The data parameter is an object of key: value pairs. Any pairs in the data parameter will be saved by Mechanical Turk, and can be downloaded in a CSV file through the Mechanical Turk interface. Important : the data parameter must contain at least one key: value pair, even just a dummy value, or the HIT will not be submitted correctly. Return value \u00b6 Returns nothing. Description \u00b6 This method will submit a HIT to Mechanical Turk, causing the HIT to finish. This method will only work when called from within the mechanical turk website. If you are using an external HIT to send workers to your own server, this method will not work on an externally hosted page. It will work if your external content is loaded in the iframe on the Mechanical Turk website. Example \u00b6 < p > Enter the code you were given: </ p > < input type = \"text\" id = \"code\" ></ input > < button onclick = \"sendData();\" > Submit HIT </ button > < script > // this content must be loaded in the iframe on the mechanical turk website. // usually, this means that the content is part of your 'recruitment ad', the // page the workers can see when they are deciding whether or not to accept a HIT. // one option is to include a simple form on this page that workers submit, with a // special code that they get at the end of the experiment. function sendData () { jsPsych . turk . submitToTurk ({ code : document . getElementById ( 'code' ). value }); } </ script > jsPsych.turk.turkInfo \u00b6 jsPsych . turk . turkInfo () Parameters \u00b6 None. Return value \u00b6 Returns an object with six properties: .assignmentId contains the assignment ID string of the HIT. .hitId contains the HIT ID. .workerId contains the worker ID of the worker completing the HIT. .turkSubmitTo contains the URL for submitting the HIT. This parameter is used in the jsPsych.turk.submitToTurk method, and is probably not useful outside of that context. .previewMode is a boolean value indicating whether or not the worker has accepted the HIT yet. If the page is viewed inside Mechancial Turk and the worker has not clicked 'Accept HIT' then this will be true. If the page is viewed outside Mechanical Turk or the worker has acccepted the HIT, then it will be false. .outsideTurk is a boolean value indicating if the page is being viewed within Mechanical Turk, or if it is being viewed from another source (e.g., someone directly going to the page URL instead of going through mturk). Description \u00b6 This method returns basic information about the current Mechanical Turk session, including the worker ID, assignment ID, and HIT ID. Example \u00b6 var turkInfo = jsPsych . turk . turkInfo (); alert ( 'Worker ID is: ' + turkInfo . workerId ); alert ( 'Assignment ID is: ' + turkInfo . assignmentId ); alert ( 'HIT ID is: ' + turkInfo . hitId ); // true if the page is viewed within Mechanical Turk, // but worker has not accepted the HIT yet. // false if the page is viewed outside Mechanical Turk, // OR the worker has accepted the HIT. alert ( 'Preview mode? ' + turkInfo . previewMode ); // true if the page is viewed outside mechanical turk, // false otherwise. alert ( 'Outside turk? ' + turkInfo . outsideTurk );","title":"jsPsych.turk"},{"location":"reference/jspsych-turk/#jspsychturk","text":"The jsPsych.turk module contains functions for interacting with Mechanical Turk.","title":"jsPsych.turk"},{"location":"reference/jspsych-turk/#jspsychturksubmittoturk","text":"jsPsych . turk . submitToTurk ( data )","title":"jsPsych.turk.submitToTurk"},{"location":"reference/jspsych-turk/#parameters","text":"Parameter Type Description data object The data parameter is an object of key: value pairs. Any pairs in the data parameter will be saved by Mechanical Turk, and can be downloaded in a CSV file through the Mechanical Turk interface. Important : the data parameter must contain at least one key: value pair, even just a dummy value, or the HIT will not be submitted correctly.","title":"Parameters"},{"location":"reference/jspsych-turk/#return-value","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych-turk/#description","text":"This method will submit a HIT to Mechanical Turk, causing the HIT to finish. This method will only work when called from within the mechanical turk website. If you are using an external HIT to send workers to your own server, this method will not work on an externally hosted page. It will work if your external content is loaded in the iframe on the Mechanical Turk website.","title":"Description"},{"location":"reference/jspsych-turk/#example","text":"< p > Enter the code you were given: </ p > < input type = \"text\" id = \"code\" ></ input > < button onclick = \"sendData();\" > Submit HIT </ button > < script > // this content must be loaded in the iframe on the mechanical turk website. // usually, this means that the content is part of your 'recruitment ad', the // page the workers can see when they are deciding whether or not to accept a HIT. // one option is to include a simple form on this page that workers submit, with a // special code that they get at the end of the experiment. function sendData () { jsPsych . turk . submitToTurk ({ code : document . getElementById ( 'code' ). value }); } </ script >","title":"Example"},{"location":"reference/jspsych-turk/#jspsychturkturkinfo","text":"jsPsych . turk . turkInfo ()","title":"jsPsych.turk.turkInfo"},{"location":"reference/jspsych-turk/#parameters_1","text":"None.","title":"Parameters"},{"location":"reference/jspsych-turk/#return-value_1","text":"Returns an object with six properties: .assignmentId contains the assignment ID string of the HIT. .hitId contains the HIT ID. .workerId contains the worker ID of the worker completing the HIT. .turkSubmitTo contains the URL for submitting the HIT. This parameter is used in the jsPsych.turk.submitToTurk method, and is probably not useful outside of that context. .previewMode is a boolean value indicating whether or not the worker has accepted the HIT yet. If the page is viewed inside Mechancial Turk and the worker has not clicked 'Accept HIT' then this will be true. If the page is viewed outside Mechanical Turk or the worker has acccepted the HIT, then it will be false. .outsideTurk is a boolean value indicating if the page is being viewed within Mechanical Turk, or if it is being viewed from another source (e.g., someone directly going to the page URL instead of going through mturk).","title":"Return value"},{"location":"reference/jspsych-turk/#description_1","text":"This method returns basic information about the current Mechanical Turk session, including the worker ID, assignment ID, and HIT ID.","title":"Description"},{"location":"reference/jspsych-turk/#example_1","text":"var turkInfo = jsPsych . turk . turkInfo (); alert ( 'Worker ID is: ' + turkInfo . workerId ); alert ( 'Assignment ID is: ' + turkInfo . assignmentId ); alert ( 'HIT ID is: ' + turkInfo . hitId ); // true if the page is viewed within Mechanical Turk, // but worker has not accepted the HIT yet. // false if the page is viewed outside Mechanical Turk, // OR the worker has accepted the HIT. alert ( 'Preview mode? ' + turkInfo . previewMode ); // true if the page is viewed outside mechanical turk, // false otherwise. alert ( 'Outside turk? ' + turkInfo . outsideTurk );","title":"Example"},{"location":"reference/jspsych/","text":"jsPsych \u00b6 initJsPsych \u00b6 var jsPsych = initJsPsych ( settings ); Parameters \u00b6 Parameter Type Description settings object The settings object for initializing jsPsych. See table below. The settings object can contain several parameters. None of the parameters are required. Parameter Type Description display_element string The ID of an HTML element to display the experiment in. If left blank, jsPsych will use the <body> element to display content. All keyboard event listeners are bound to this element. In order for a keyboard event to be detected, this element must have focus (be the last thing that the participant clicked on). on_finish function Function to execute when the experiment ends. on_trial_start function Function to execute when a new trial begins. on_trial_finish function Function to execute when a trial ends. on_data_update function Function to execute every time data is stored using the jsPsych.data.write method. All plugins use this method to save data (via a call to jsPsych.finishTrial , so this function runs every time a plugin stores new data. on_interaction_data_update function Function to execute every time a new interaction event occurs. Interaction events include clicking on a different window (blur), returning to the experiment window (focus), entering full screen mode (fullscreenenter), and exiting full screen mode (fullscreenexit). on_close function Function to execute when the user leaves the page. Can be used, for example, to save data before the page is closed. exclusions object Specifies restrictions on the browser the participant can use to complete the experiment. See list of options below. This feature is deprecated as of v7.1 and will be removed in v8.0. The browser-check plugin is an improved way to handle exclusions. show_progress_bar boolean If true , then a progress bar is shown at the top of the page. Default is false . message_progress_bar string Message to display next to the progress bar. The default is 'Completion Progress'. auto_update_progress_bar boolean If true, then the progress bar at the top of the page will automatically update as every top-level timeline or trial is completed. use_webaudio boolean If false, then jsPsych will not attempt to use the WebAudio API for audio playback. Instead, HTML5 Audio objects will be used. The WebAudio API offers more precise control over the timing of audio events, and should be used when possible. The default value is true . default_iti numeric The default inter-trial interval in ms. The default value if none is specified is 0ms. experiment_width numeric The desired width of the jsPsych container in pixels. If left undefined, the width will be 100% of the display element. Usually this is the <body> element, and the width will be 100% of the screen size. minimum_valid_rt numeric The minimum valid response time for key presses during the experiment. Any key press response time that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to keyboard responses , and not to other response types such as buttons and sliders. The default value is 0. override_safe_mode boolean Running a jsPsych experiment directly in a web browser (e.g., by double clicking on a local HTML file) will load the page using the file:// protocol. Some features of jsPsych don't work with this protocol. By default, when jsPsych detects that it's running on a page loaded via the file:// protocol, it runs in safe mode , which automatically disables features that don't work in this context. Specifically, the use of Web Audio is disabled (audio will be played using HTML5 audio instead, even if use_webaudio is true ) and video preloading is disabled. The override_safe_mode parameter defaults to false , but you can set it to true to force these features to operate under the file:// protocol. In order for this to work, you will need to disable web security (CORS) features in your browser - this is safe to do if you know what you are doing. Note that this parameter has no effect when you are running the experiment on a web server, because the page will be loaded via the http:// or https:// protocol. case_sensitive_responses boolean If true , then jsPsych will make a distinction between uppercase and lowercase keys when evaluating keyboard responses, e.g. \"A\" (uppercase) will not be recognized as a valid response if the trial only accepts \"a\" (lowercase). If false, then jsPsych will not make a distinction between uppercase and lowercase keyboard responses, e.g. both \"a\" and \"A\" responses will be valid when the trial's key choice parameter is \"a\". Setting this parameter to false is useful if you want key responses to be treated the same way when CapsLock is turned on or the Shift key is held down. The default value is false . extensions array Array containing information about one or more jsPsych extensions that are used during the experiment. Each extension should be specified as an object with type (required), which is the name of the extension, and params (optional), which is an object containing any parameter-value pairs to be passed to the extension's initialize function. Default value is an empty array. Possible values for the exclusions parameter above. Parameter Type Description min_width numeric The minimum width of the browser window. If the width is below this value, a message will be displayed to the participant asking them to maximize their browser window. The experiment will sit on this page until the browser window is large enough. min_height numeric Same as above, but with height. audio boolean Set to true to require support for the WebAudio API (used by plugins that play audio files). Return value \u00b6 Returns a jsPsych instance, which all jsPsych methods on this page are called on. Therefore it is not possible to call any of the jsPsych methods listed on this page until this initJsPsych function is called and a jsPsych instance is created. Description \u00b6 This function initializes jsPsych with the specified experiment settings. Example \u00b6 var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); }, show_progress_bar : true , default_iti : 500 }); For more examples, see the HTML files in the examples folder . jsPsych.addNodeToEndOfTimeline \u00b6 jsPsych . addNodeToEndOfTimeline ( node_parameters ) Parameters \u00b6 Parameter Type Description node_parameters object An object defining a timeline. It must have, at a minimum, a timeline parameter with a valid timeline array as the value for that parameter. Return value \u00b6 None. Description \u00b6 Adds the timeline to the end of the experiment. Example \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is a new trial.' } var new_timeline = { timeline : [ trial ] } jsPsych . addNodeToEndOfTimeline ( new_timeline ) jsPsych.endCurrentTimeline \u00b6 jsPsych . endCurrentTimeline () Parameters \u00b6 None. Return value \u00b6 None. Description \u00b6 Ends the current timeline. If timelines are nested, then only the timeline that contains the current trial is ended. Example \u00b6 End timeline if a particular key is pressed \u00b6 var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); var images = [ \"img/1.gif\" , \"img/2.gif\" , \"img/3.gif\" , \"img/4.gif\" , \"img/5.gif\" , \"img/6.gif\" , \"img/7.gif\" , \"img/8.gif\" , \"img/9.gif\" , \"img/10.gif\" ]; var trials = []; for ( var i = 0 ; i < images . length ; i ++ ) { trials . push ({ stimulus : images [ i ] }); } var block = { type : jsPsychImageKeyboardResponse , choices : [ 'y' , 'n' ], prompt : '<p>Press \"y\" to Continue. Press \"n\" to end this node of the experiment.</p>' , on_finish : function ( data ) { if ( jsPsych . pluginAPI . compareKeys ( data . response , 'n' )) { jsPsych . endCurrentTimeline (); } }, timeline : trials } var after_block = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>The next node</p>' } jsPsych . run ([ block , after_block ]); jsPsych.endExperiment \u00b6 jsPsych . endExperiment ( end_message , data ) Parameters \u00b6 Parameter Type Description end_message string A message to display on the screen after the experiment is over. Can include HTML formatting. data object An optional object of key-value pairs to store as data in the final trial of the experiment. Return value \u00b6 None. Description \u00b6 Ends the experiment, skipping all remaining trials. If the on_finish event handler for jsPsych returns a Promise then the end_message will not be displayed until the promise is resolved. Example \u00b6 End the experiment if a particular response is given \u00b6 var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'image1.jpg' , choices : [ 'y' , 'n' ] prompt : '<p>Press \"y\" to Continue. Press \"n\" to end the experiment</p>' , on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"n\" )){ jsPsych . endExperiment ( 'The experiment was ended by pressing \"n\".' ); } } } jsPsych.finishTrial \u00b6 jsPsych . finishTrial ( data ) Parameters \u00b6 Parameter Type Description data object The data to store for the trial. Return value \u00b6 Returns nothing. Description \u00b6 This method tells jsPsych that the current trial is over. It is used in all of the plugins to end the current trial. When the trial ends a few things happen: The data is stored using jsPsych.data.write() The on_finish callback function is executed for the trial The on_trial_finish callback function is executed The progress bar is updated if it is being displayed The experiment ends if the trial is the last one (and the on_finish callback function is executed). The next trial, if one exists, is started. Example \u00b6 // this code would be in a plugin jsPsych . finishTrial ({ correct_response : true }); jsPsych.getAllTimelineVariables \u00b6 jsPsych . getAllTimelineVariables () Parameters \u00b6 None. Return value \u00b6 Returns an object with all available timeline variables at this moment in the experiment, represented as key: value pairs. Description \u00b6 This function can be used to get all the timeline variables at a particular moment in the experiment. Can be useful for annotating data, such as in the example below. Example \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Just a demo' , on_finish : function ( data ){ // merge all timeline variables available at this trial into the data for this trial Object . assign ( data , jsPsych . getAllTimelineVariables ()) } } jsPsych.getCurrentTimelineNodeID \u00b6 jsPsych . getCurrentTimelineNodeID () Parameters \u00b6 None. Return value \u00b6 Returns the ID of the TimelineNode that is currently active. Description \u00b6 Gets the ID of the active TimelineNode. The ID is a string that follows a specific format: \"0.0\" is the ID of the first top-level TimelineNode \"1.0\" is the ID of the second top-level TimelineNode \"2.0\" is the ID of the third top-level TimelineNode, and so on... If a TimelineNode iterates multiple times (using the loop function, for example), then the iterations are indicated in the second number: \"0.0\" is the ID of the first top-level TimelineNode during the first iteration \"0.1\" is the ID of the first top-level TimelineNode during the second iteration \"0.2\" is the ID of the first top-level TimelineNode during the third iteration, and so on... If TimelineNodes are nested in other TimelineNodes, then the hierarchical structure is shown with \"-\" : \"0.0-1.0\" is the ID of the second TimelineNode on the timeline of the first top-level TimelineNode. \"0.0-2.0\" is the ID of the third TimelineNode on the timeline of the first top-level TimelineNode, and so on... The rules about iterations apply throughout the hierarchical ID: \"0.2-1.3\" is the ID of the second TimelineNode, executing for the fourth time, on the timeline of the first top-level TimelineNode, executing for the third time. Example \u00b6 var id = jsPsych . getCurrentTimelineNodeID (); console . log ( 'The current TimelineNode ID is ' + id ); jsPsych.getCurrentTrial \u00b6 jsPsych . getCurrentTrial () Parameters \u00b6 None. Return value \u00b6 Returns the object describing the current trial. The object will contain all of the parameters associated with the current trial. Description \u00b6 Get a description of the current trial Example \u00b6 var trial = jsPsych . getCurrentTrial (); console . log ( 'The current trial is using the ' + trial . type + ' plugin' ); jsPsych.getDisplayElement \u00b6 jsPsych . getDisplayElement () Parameters \u00b6 None. Return value \u00b6 Returns the HTML DOM element used for displaying the experiment. Description \u00b6 Get the DOM element that displays the experiment. Example \u00b6 var el = jsPsych . getDisplayElement (); // hide the jsPsych display el . style . visibility = 'hidden' ; \u00b6 jsPsych.getInitSettings \u00b6 jsPsych . getInitSettings () Parameters \u00b6 None Return value \u00b6 Returns the settings object used to initialize the experiment. Description \u00b6 Gets the object containing the settings for the current experiment. Example \u00b6 var settings = jsPsych . getInitSettings (); // check the experiment structure console . log ( JSON . stringify ( settings . timeline )); jsPsych.getProgress \u00b6 jsPsych . getProgress () Parameters \u00b6 None. Return value \u00b6 Returns an object with the following properties: Property Type Description total_trials numeric Indicates the number of trials in the experiment. Note that this does not count possible loops or skipped trials due to conditional statements. current_trial_global numeric Returns the trial index of the current trial in a global scope. Every trial will increase this count by 1. percent_complete numeric Estimates the percent of the experiment that is complete. Works as expected for experiments without conditional or looping timelines. For complex timelines, the percent is an approximation. Description \u00b6 This method returns information about the length of the experiment and the participant's current location in the experiment timeline. Example \u00b6 var progress = jsPsych . getProgress (); alert ( 'You have completed approximately ' + progress . percent_complete + '% of the experiment' ); jsPsych.getProgressBarCompleted \u00b6 jsPsych . getProgressBarCompleted () Parameters \u00b6 None. Return value \u00b6 Returns a value between 0 and 1 representing how full the progress bar currently is. Description \u00b6 Used to get the current value of the progress bar. Works for automated and manual control. Example \u00b6 var progress_bar_amount = jsPsych . getProgressBarCompleted (); jsPsych.getStartTime \u00b6 jsPsych . getStartTime () Parameters \u00b6 None. Return value \u00b6 Returns a Date object indicating when the experiment began. Description \u00b6 Get the time that the experiment began. Example \u00b6 var start_time = jsPsych . getStartTime (); jsPsych.getTotalTime \u00b6 jsPsych . getTotalTime () Parameters \u00b6 None. Return value \u00b6 Returns a numeric value indicating the number of milliseconds since jsPsych.run was called. Description \u00b6 Gets the total time the participant has been in the experiment. Example \u00b6 var time = jsPsych . getTotalTime (); console . log ( time ); jsPsych.pauseExperiment \u00b6 jsPsych . pauseExperiment () Parameters \u00b6 None. Return value \u00b6 None. Description \u00b6 Pauses the experiment. The experiment will finish the current trial, but will not execute any additional trials until jsPsych.resumeExperiment() is called. Example \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press p to take a 30 second break. Otherwise, press c to continue immediately.' , choices : [ 'p' , 'c' ], on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"p\" )) { jsPsych . pauseExperiment (); setTimeout ( jsPsych . resumeExperiment , 30000 ); } } } jsPsych.resumeExperiment \u00b6 jsPsych . resumeExperiment () Parameters \u00b6 None. Return value \u00b6 None. Description \u00b6 Resumes the experiment after a call to jsPsych.pauseExperiment() . If the post trial delay ( post_trial_gap ) has not yet been reached, then the experiment will not continue until the delay is finished. For example, if post_trial_gap was 10,000ms and jsPsych.resumeExperiment() was called 6,000ms after the previous trial finished, then the experiment would not continue for another 4,000ms. Example \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press p to take a 30 second break. Otherwise, press c to continue immediately.' , choices : [ 'p' , 'c' ], on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"p\" )) { jsPsych . pauseExperiment (); setTimeout ( jsPsych . resumeExperiment , 30000 ); } } } jsPsych.run \u00b6 jsPsych . run ( timeline ) Parameters \u00b6 Parameter Type Description timeline array An array containing the objects that describe the experiment timeline. See Creating an Experiment: The Timeline . Return value \u00b6 None. Description \u00b6 Start the jsPsych experiment with the specified timeline. Example \u00b6 var timeline = [ trial1 , trial2 , trial3 ]; jsPsych . run ( timeline ); jsPsych.setProgressBar \u00b6 jsPsych . setProgressBar ( value ) Parameters \u00b6 Parameter Type Description value numeric Proprotion (between 0 and 1) to fill the progress bar. Return value \u00b6 None. Description \u00b6 Set the progress bar to a custom amount. Proportion must be between 0 and 1. Values larger than 1 are treated as 1. Example \u00b6 jsPsych . setProgressBar ( 0.85 ); jsPsych.timelineVariable \u00b6 jsPsych . timelineVariable ( variable , call_immediate ) Parameters \u00b6 Parameter Type Description variable string Name of the timeline variable call_immediate bool This parameter is optional and can usually be omitted. It determines the return value of jsPsych.timelineVariable . If true , the function returns the value of the current timeline variable. If false , the function returns a function that returns the value of the current timeline variable. When call_immediate is omitted, the appropriate option is determined automatically based on the context in which this function is called. When jsPsych.timelineVariable is used as a parameter value, call_immediate will be false . This allows it to be used as a dynamic trial parameter . When jsPsych.timelineVariable is used inside of a function, call_immediate will be true . It is possible to explicitly set this option to true to force the function to immediately return the current value of the timeline variable. Return value \u00b6 Either a function that returns the value of the timeline variable, or the value of the timeline variable, depending on the context in which it is used. See call_immediate description above. Description \u00b6 Timeline variables are a powerful technique for generating experiments with repetitive procedures but different parameter values. This function fetches the current value of a particular timeline variable. It must be used in conjunction with a timeline that has timeline variables. See the timeline variable section for details. Examples \u00b6 Standard use as a parameter for a trial \u00b6 var trial = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'image' ) } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] } Invoking immediately in a function \u00b6 var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ return \"<img style='width:100px; height:100px;' src='\" + jsPsych . timelineVariable ( 'image' ) + \"'></img>\" ; } } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] } Prior to jsPsych v6.3.0, the call_immediate parameter must be set to true when jsPsych.timelineVariable is called from within a function, such as a dynamic parameter : var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ return \"<img style='width:100px; height:100px;' src='\" + jsPsych . timelineVariable ( 'image' , true ) + \"'></img>\" ; } } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] } jsPsych.version \u00b6 jsPsych . version () Parameters \u00b6 None. Return value \u00b6 Returns the version number as a string. Description \u00b6 Gets the version of jsPsych. Example \u00b6 var version = jsPsych . version (); console . log ( version );","title":"jsPsych"},{"location":"reference/jspsych/#jspsych","text":"","title":"jsPsych"},{"location":"reference/jspsych/#initjspsych","text":"var jsPsych = initJsPsych ( settings );","title":"initJsPsych"},{"location":"reference/jspsych/#parameters","text":"Parameter Type Description settings object The settings object for initializing jsPsych. See table below. The settings object can contain several parameters. None of the parameters are required. Parameter Type Description display_element string The ID of an HTML element to display the experiment in. If left blank, jsPsych will use the <body> element to display content. All keyboard event listeners are bound to this element. In order for a keyboard event to be detected, this element must have focus (be the last thing that the participant clicked on). on_finish function Function to execute when the experiment ends. on_trial_start function Function to execute when a new trial begins. on_trial_finish function Function to execute when a trial ends. on_data_update function Function to execute every time data is stored using the jsPsych.data.write method. All plugins use this method to save data (via a call to jsPsych.finishTrial , so this function runs every time a plugin stores new data. on_interaction_data_update function Function to execute every time a new interaction event occurs. Interaction events include clicking on a different window (blur), returning to the experiment window (focus), entering full screen mode (fullscreenenter), and exiting full screen mode (fullscreenexit). on_close function Function to execute when the user leaves the page. Can be used, for example, to save data before the page is closed. exclusions object Specifies restrictions on the browser the participant can use to complete the experiment. See list of options below. This feature is deprecated as of v7.1 and will be removed in v8.0. The browser-check plugin is an improved way to handle exclusions. show_progress_bar boolean If true , then a progress bar is shown at the top of the page. Default is false . message_progress_bar string Message to display next to the progress bar. The default is 'Completion Progress'. auto_update_progress_bar boolean If true, then the progress bar at the top of the page will automatically update as every top-level timeline or trial is completed. use_webaudio boolean If false, then jsPsych will not attempt to use the WebAudio API for audio playback. Instead, HTML5 Audio objects will be used. The WebAudio API offers more precise control over the timing of audio events, and should be used when possible. The default value is true . default_iti numeric The default inter-trial interval in ms. The default value if none is specified is 0ms. experiment_width numeric The desired width of the jsPsych container in pixels. If left undefined, the width will be 100% of the display element. Usually this is the <body> element, and the width will be 100% of the screen size. minimum_valid_rt numeric The minimum valid response time for key presses during the experiment. Any key press response time that is less than this value will be treated as invalid and ignored. Note that this parameter only applies to keyboard responses , and not to other response types such as buttons and sliders. The default value is 0. override_safe_mode boolean Running a jsPsych experiment directly in a web browser (e.g., by double clicking on a local HTML file) will load the page using the file:// protocol. Some features of jsPsych don't work with this protocol. By default, when jsPsych detects that it's running on a page loaded via the file:// protocol, it runs in safe mode , which automatically disables features that don't work in this context. Specifically, the use of Web Audio is disabled (audio will be played using HTML5 audio instead, even if use_webaudio is true ) and video preloading is disabled. The override_safe_mode parameter defaults to false , but you can set it to true to force these features to operate under the file:// protocol. In order for this to work, you will need to disable web security (CORS) features in your browser - this is safe to do if you know what you are doing. Note that this parameter has no effect when you are running the experiment on a web server, because the page will be loaded via the http:// or https:// protocol. case_sensitive_responses boolean If true , then jsPsych will make a distinction between uppercase and lowercase keys when evaluating keyboard responses, e.g. \"A\" (uppercase) will not be recognized as a valid response if the trial only accepts \"a\" (lowercase). If false, then jsPsych will not make a distinction between uppercase and lowercase keyboard responses, e.g. both \"a\" and \"A\" responses will be valid when the trial's key choice parameter is \"a\". Setting this parameter to false is useful if you want key responses to be treated the same way when CapsLock is turned on or the Shift key is held down. The default value is false . extensions array Array containing information about one or more jsPsych extensions that are used during the experiment. Each extension should be specified as an object with type (required), which is the name of the extension, and params (optional), which is an object containing any parameter-value pairs to be passed to the extension's initialize function. Default value is an empty array. Possible values for the exclusions parameter above. Parameter Type Description min_width numeric The minimum width of the browser window. If the width is below this value, a message will be displayed to the participant asking them to maximize their browser window. The experiment will sit on this page until the browser window is large enough. min_height numeric Same as above, but with height. audio boolean Set to true to require support for the WebAudio API (used by plugins that play audio files).","title":"Parameters"},{"location":"reference/jspsych/#return-value","text":"Returns a jsPsych instance, which all jsPsych methods on this page are called on. Therefore it is not possible to call any of the jsPsych methods listed on this page until this initJsPsych function is called and a jsPsych instance is created.","title":"Return value"},{"location":"reference/jspsych/#description","text":"This function initializes jsPsych with the specified experiment settings.","title":"Description"},{"location":"reference/jspsych/#example","text":"var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); }, show_progress_bar : true , default_iti : 500 }); For more examples, see the HTML files in the examples folder .","title":"Example"},{"location":"reference/jspsych/#jspsychaddnodetoendoftimeline","text":"jsPsych . addNodeToEndOfTimeline ( node_parameters )","title":"jsPsych.addNodeToEndOfTimeline"},{"location":"reference/jspsych/#parameters_1","text":"Parameter Type Description node_parameters object An object defining a timeline. It must have, at a minimum, a timeline parameter with a valid timeline array as the value for that parameter.","title":"Parameters"},{"location":"reference/jspsych/#return-value_1","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_1","text":"Adds the timeline to the end of the experiment.","title":"Description"},{"location":"reference/jspsych/#example_1","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'This is a new trial.' } var new_timeline = { timeline : [ trial ] } jsPsych . addNodeToEndOfTimeline ( new_timeline )","title":"Example"},{"location":"reference/jspsych/#jspsychendcurrenttimeline","text":"jsPsych . endCurrentTimeline ()","title":"jsPsych.endCurrentTimeline"},{"location":"reference/jspsych/#parameters_2","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_2","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_2","text":"Ends the current timeline. If timelines are nested, then only the timeline that contains the current trial is ended.","title":"Description"},{"location":"reference/jspsych/#example_2","text":"","title":"Example"},{"location":"reference/jspsych/#end-timeline-if-a-particular-key-is-pressed","text":"var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); var images = [ \"img/1.gif\" , \"img/2.gif\" , \"img/3.gif\" , \"img/4.gif\" , \"img/5.gif\" , \"img/6.gif\" , \"img/7.gif\" , \"img/8.gif\" , \"img/9.gif\" , \"img/10.gif\" ]; var trials = []; for ( var i = 0 ; i < images . length ; i ++ ) { trials . push ({ stimulus : images [ i ] }); } var block = { type : jsPsychImageKeyboardResponse , choices : [ 'y' , 'n' ], prompt : '<p>Press \"y\" to Continue. Press \"n\" to end this node of the experiment.</p>' , on_finish : function ( data ) { if ( jsPsych . pluginAPI . compareKeys ( data . response , 'n' )) { jsPsych . endCurrentTimeline (); } }, timeline : trials } var after_block = { type : jsPsychHtmlKeyboardResponse , stimulus : '<p>The next node</p>' } jsPsych . run ([ block , after_block ]);","title":"End timeline if a particular key is pressed"},{"location":"reference/jspsych/#jspsychendexperiment","text":"jsPsych . endExperiment ( end_message , data )","title":"jsPsych.endExperiment"},{"location":"reference/jspsych/#parameters_3","text":"Parameter Type Description end_message string A message to display on the screen after the experiment is over. Can include HTML formatting. data object An optional object of key-value pairs to store as data in the final trial of the experiment.","title":"Parameters"},{"location":"reference/jspsych/#return-value_3","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_3","text":"Ends the experiment, skipping all remaining trials. If the on_finish event handler for jsPsych returns a Promise then the end_message will not be displayed until the promise is resolved.","title":"Description"},{"location":"reference/jspsych/#example_3","text":"","title":"Example"},{"location":"reference/jspsych/#end-the-experiment-if-a-particular-response-is-given","text":"var trial = { type : jsPsychImageKeyboardResponse , stimulus : 'image1.jpg' , choices : [ 'y' , 'n' ] prompt : '<p>Press \"y\" to Continue. Press \"n\" to end the experiment</p>' , on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"n\" )){ jsPsych . endExperiment ( 'The experiment was ended by pressing \"n\".' ); } } }","title":"End the experiment if a particular response is given"},{"location":"reference/jspsych/#jspsychfinishtrial","text":"jsPsych . finishTrial ( data )","title":"jsPsych.finishTrial"},{"location":"reference/jspsych/#parameters_4","text":"Parameter Type Description data object The data to store for the trial.","title":"Parameters"},{"location":"reference/jspsych/#return-value_4","text":"Returns nothing.","title":"Return value"},{"location":"reference/jspsych/#description_4","text":"This method tells jsPsych that the current trial is over. It is used in all of the plugins to end the current trial. When the trial ends a few things happen: The data is stored using jsPsych.data.write() The on_finish callback function is executed for the trial The on_trial_finish callback function is executed The progress bar is updated if it is being displayed The experiment ends if the trial is the last one (and the on_finish callback function is executed). The next trial, if one exists, is started.","title":"Description"},{"location":"reference/jspsych/#example_4","text":"// this code would be in a plugin jsPsych . finishTrial ({ correct_response : true });","title":"Example"},{"location":"reference/jspsych/#jspsychgetalltimelinevariables","text":"jsPsych . getAllTimelineVariables ()","title":"jsPsych.getAllTimelineVariables"},{"location":"reference/jspsych/#parameters_5","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_5","text":"Returns an object with all available timeline variables at this moment in the experiment, represented as key: value pairs.","title":"Return value"},{"location":"reference/jspsych/#description_5","text":"This function can be used to get all the timeline variables at a particular moment in the experiment. Can be useful for annotating data, such as in the example below.","title":"Description"},{"location":"reference/jspsych/#example_5","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Just a demo' , on_finish : function ( data ){ // merge all timeline variables available at this trial into the data for this trial Object . assign ( data , jsPsych . getAllTimelineVariables ()) } }","title":"Example"},{"location":"reference/jspsych/#jspsychgetcurrenttimelinenodeid","text":"jsPsych . getCurrentTimelineNodeID ()","title":"jsPsych.getCurrentTimelineNodeID"},{"location":"reference/jspsych/#parameters_6","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_6","text":"Returns the ID of the TimelineNode that is currently active.","title":"Return value"},{"location":"reference/jspsych/#description_6","text":"Gets the ID of the active TimelineNode. The ID is a string that follows a specific format: \"0.0\" is the ID of the first top-level TimelineNode \"1.0\" is the ID of the second top-level TimelineNode \"2.0\" is the ID of the third top-level TimelineNode, and so on... If a TimelineNode iterates multiple times (using the loop function, for example), then the iterations are indicated in the second number: \"0.0\" is the ID of the first top-level TimelineNode during the first iteration \"0.1\" is the ID of the first top-level TimelineNode during the second iteration \"0.2\" is the ID of the first top-level TimelineNode during the third iteration, and so on... If TimelineNodes are nested in other TimelineNodes, then the hierarchical structure is shown with \"-\" : \"0.0-1.0\" is the ID of the second TimelineNode on the timeline of the first top-level TimelineNode. \"0.0-2.0\" is the ID of the third TimelineNode on the timeline of the first top-level TimelineNode, and so on... The rules about iterations apply throughout the hierarchical ID: \"0.2-1.3\" is the ID of the second TimelineNode, executing for the fourth time, on the timeline of the first top-level TimelineNode, executing for the third time.","title":"Description"},{"location":"reference/jspsych/#example_6","text":"var id = jsPsych . getCurrentTimelineNodeID (); console . log ( 'The current TimelineNode ID is ' + id );","title":"Example"},{"location":"reference/jspsych/#jspsychgetcurrenttrial","text":"jsPsych . getCurrentTrial ()","title":"jsPsych.getCurrentTrial"},{"location":"reference/jspsych/#parameters_7","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_7","text":"Returns the object describing the current trial. The object will contain all of the parameters associated with the current trial.","title":"Return value"},{"location":"reference/jspsych/#description_7","text":"Get a description of the current trial","title":"Description"},{"location":"reference/jspsych/#example_7","text":"var trial = jsPsych . getCurrentTrial (); console . log ( 'The current trial is using the ' + trial . type + ' plugin' );","title":"Example"},{"location":"reference/jspsych/#jspsychgetdisplayelement","text":"jsPsych . getDisplayElement ()","title":"jsPsych.getDisplayElement"},{"location":"reference/jspsych/#parameters_8","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_8","text":"Returns the HTML DOM element used for displaying the experiment.","title":"Return value"},{"location":"reference/jspsych/#description_8","text":"Get the DOM element that displays the experiment.","title":"Description"},{"location":"reference/jspsych/#example_8","text":"","title":"Example"},{"location":"reference/jspsych/#var-el-jspsychgetdisplayelement-hide-the-jspsych-display-elstylevisibility-hidden","text":"","title":"var el = jsPsych.getDisplayElement();\n\n// hide the jsPsych display\nel.style.visibility = &#39;hidden&#39;;\n"},{"location":"reference/jspsych/#jspsychgetinitsettings","text":"jsPsych . getInitSettings ()","title":"jsPsych.getInitSettings"},{"location":"reference/jspsych/#parameters_9","text":"None","title":"Parameters"},{"location":"reference/jspsych/#return-value_9","text":"Returns the settings object used to initialize the experiment.","title":"Return value"},{"location":"reference/jspsych/#description_9","text":"Gets the object containing the settings for the current experiment.","title":"Description"},{"location":"reference/jspsych/#example_9","text":"var settings = jsPsych . getInitSettings (); // check the experiment structure console . log ( JSON . stringify ( settings . timeline ));","title":"Example"},{"location":"reference/jspsych/#jspsychgetprogress","text":"jsPsych . getProgress ()","title":"jsPsych.getProgress"},{"location":"reference/jspsych/#parameters_10","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_10","text":"Returns an object with the following properties: Property Type Description total_trials numeric Indicates the number of trials in the experiment. Note that this does not count possible loops or skipped trials due to conditional statements. current_trial_global numeric Returns the trial index of the current trial in a global scope. Every trial will increase this count by 1. percent_complete numeric Estimates the percent of the experiment that is complete. Works as expected for experiments without conditional or looping timelines. For complex timelines, the percent is an approximation.","title":"Return value"},{"location":"reference/jspsych/#description_10","text":"This method returns information about the length of the experiment and the participant's current location in the experiment timeline.","title":"Description"},{"location":"reference/jspsych/#example_10","text":"var progress = jsPsych . getProgress (); alert ( 'You have completed approximately ' + progress . percent_complete + '% of the experiment' );","title":"Example"},{"location":"reference/jspsych/#jspsychgetprogressbarcompleted","text":"jsPsych . getProgressBarCompleted ()","title":"jsPsych.getProgressBarCompleted"},{"location":"reference/jspsych/#parameters_11","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_11","text":"Returns a value between 0 and 1 representing how full the progress bar currently is.","title":"Return value"},{"location":"reference/jspsych/#description_11","text":"Used to get the current value of the progress bar. Works for automated and manual control.","title":"Description"},{"location":"reference/jspsych/#example_11","text":"var progress_bar_amount = jsPsych . getProgressBarCompleted ();","title":"Example"},{"location":"reference/jspsych/#jspsychgetstarttime","text":"jsPsych . getStartTime ()","title":"jsPsych.getStartTime"},{"location":"reference/jspsych/#parameters_12","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_12","text":"Returns a Date object indicating when the experiment began.","title":"Return value"},{"location":"reference/jspsych/#description_12","text":"Get the time that the experiment began.","title":"Description"},{"location":"reference/jspsych/#example_12","text":"var start_time = jsPsych . getStartTime ();","title":"Example"},{"location":"reference/jspsych/#jspsychgettotaltime","text":"jsPsych . getTotalTime ()","title":"jsPsych.getTotalTime"},{"location":"reference/jspsych/#parameters_13","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_13","text":"Returns a numeric value indicating the number of milliseconds since jsPsych.run was called.","title":"Return value"},{"location":"reference/jspsych/#description_13","text":"Gets the total time the participant has been in the experiment.","title":"Description"},{"location":"reference/jspsych/#example_13","text":"var time = jsPsych . getTotalTime (); console . log ( time );","title":"Example"},{"location":"reference/jspsych/#jspsychpauseexperiment","text":"jsPsych . pauseExperiment ()","title":"jsPsych.pauseExperiment"},{"location":"reference/jspsych/#parameters_14","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_14","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_14","text":"Pauses the experiment. The experiment will finish the current trial, but will not execute any additional trials until jsPsych.resumeExperiment() is called.","title":"Description"},{"location":"reference/jspsych/#example_14","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press p to take a 30 second break. Otherwise, press c to continue immediately.' , choices : [ 'p' , 'c' ], on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"p\" )) { jsPsych . pauseExperiment (); setTimeout ( jsPsych . resumeExperiment , 30000 ); } } }","title":"Example"},{"location":"reference/jspsych/#jspsychresumeexperiment","text":"jsPsych . resumeExperiment ()","title":"jsPsych.resumeExperiment"},{"location":"reference/jspsych/#parameters_15","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_15","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_15","text":"Resumes the experiment after a call to jsPsych.pauseExperiment() . If the post trial delay ( post_trial_gap ) has not yet been reached, then the experiment will not continue until the delay is finished. For example, if post_trial_gap was 10,000ms and jsPsych.resumeExperiment() was called 6,000ms after the previous trial finished, then the experiment would not continue for another 4,000ms.","title":"Description"},{"location":"reference/jspsych/#example_15","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Press p to take a 30 second break. Otherwise, press c to continue immediately.' , choices : [ 'p' , 'c' ], on_finish : function ( data ){ if ( jsPsych . pluginAPI . compareKeys ( data . response , \"p\" )) { jsPsych . pauseExperiment (); setTimeout ( jsPsych . resumeExperiment , 30000 ); } } }","title":"Example"},{"location":"reference/jspsych/#jspsychrun","text":"jsPsych . run ( timeline )","title":"jsPsych.run"},{"location":"reference/jspsych/#parameters_16","text":"Parameter Type Description timeline array An array containing the objects that describe the experiment timeline. See Creating an Experiment: The Timeline .","title":"Parameters"},{"location":"reference/jspsych/#return-value_16","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_16","text":"Start the jsPsych experiment with the specified timeline.","title":"Description"},{"location":"reference/jspsych/#example_16","text":"var timeline = [ trial1 , trial2 , trial3 ]; jsPsych . run ( timeline );","title":"Example"},{"location":"reference/jspsych/#jspsychsetprogressbar","text":"jsPsych . setProgressBar ( value )","title":"jsPsych.setProgressBar"},{"location":"reference/jspsych/#parameters_17","text":"Parameter Type Description value numeric Proprotion (between 0 and 1) to fill the progress bar.","title":"Parameters"},{"location":"reference/jspsych/#return-value_17","text":"None.","title":"Return value"},{"location":"reference/jspsych/#description_17","text":"Set the progress bar to a custom amount. Proportion must be between 0 and 1. Values larger than 1 are treated as 1.","title":"Description"},{"location":"reference/jspsych/#example_17","text":"jsPsych . setProgressBar ( 0.85 );","title":"Example"},{"location":"reference/jspsych/#jspsychtimelinevariable","text":"jsPsych . timelineVariable ( variable , call_immediate )","title":"jsPsych.timelineVariable"},{"location":"reference/jspsych/#parameters_18","text":"Parameter Type Description variable string Name of the timeline variable call_immediate bool This parameter is optional and can usually be omitted. It determines the return value of jsPsych.timelineVariable . If true , the function returns the value of the current timeline variable. If false , the function returns a function that returns the value of the current timeline variable. When call_immediate is omitted, the appropriate option is determined automatically based on the context in which this function is called. When jsPsych.timelineVariable is used as a parameter value, call_immediate will be false . This allows it to be used as a dynamic trial parameter . When jsPsych.timelineVariable is used inside of a function, call_immediate will be true . It is possible to explicitly set this option to true to force the function to immediately return the current value of the timeline variable.","title":"Parameters"},{"location":"reference/jspsych/#return-value_18","text":"Either a function that returns the value of the timeline variable, or the value of the timeline variable, depending on the context in which it is used. See call_immediate description above.","title":"Return value"},{"location":"reference/jspsych/#description_18","text":"Timeline variables are a powerful technique for generating experiments with repetitive procedures but different parameter values. This function fetches the current value of a particular timeline variable. It must be used in conjunction with a timeline that has timeline variables. See the timeline variable section for details.","title":"Description"},{"location":"reference/jspsych/#examples","text":"","title":"Examples"},{"location":"reference/jspsych/#standard-use-as-a-parameter-for-a-trial","text":"var trial = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'image' ) } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] }","title":"Standard use as a parameter for a trial"},{"location":"reference/jspsych/#invoking-immediately-in-a-function","text":"var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ return \"<img style='width:100px; height:100px;' src='\" + jsPsych . timelineVariable ( 'image' ) + \"'></img>\" ; } } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] } Prior to jsPsych v6.3.0, the call_immediate parameter must be set to true when jsPsych.timelineVariable is called from within a function, such as a dynamic parameter : var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : function (){ return \"<img style='width:100px; height:100px;' src='\" + jsPsych . timelineVariable ( 'image' , true ) + \"'></img>\" ; } } var procedure = { timeline : [ trial ], timeline_variables : [ { image : 'face1.png' }, { image : 'face2.png' }, { image : 'face3.png' }, { image : 'face4.png' } ] }","title":"Invoking immediately in a function"},{"location":"reference/jspsych/#jspsychversion","text":"jsPsych . version ()","title":"jsPsych.version"},{"location":"reference/jspsych/#parameters_19","text":"None.","title":"Parameters"},{"location":"reference/jspsych/#return-value_19","text":"Returns the version number as a string.","title":"Return value"},{"location":"reference/jspsych/#description_19","text":"Gets the version of jsPsych.","title":"Description"},{"location":"reference/jspsych/#example_18","text":"var version = jsPsych . version (); console . log ( version );","title":"Example"},{"location":"support/migration-v7/","text":"Migrating an experiment to v7.x \u00b6 The release of version 7.0 changes a number of core components of jsPsych. We made these changes to improve jsPsych's compatibility with modern JavaScript tools like package managers and bundlers and to improve the developer experience for people contributing to jsPsych's codebase. We hope these changes will improve the long-term viability of the project and encourage more developers to contribute to jsPsych. Our aim was to accomplish these goals with minimal changes to the user experience of jsPsych. However, we did have to change a few critical things. This guide is aimed at users who are familiar with v6.x of jsPsych and would like to understand what's changed in v7.x. Loading jsPsych \u00b6 There are now three different ways you can load jsPsych into your HTML file. We've updated the hello world tutorial to walk through each of the three options. If you are looking for the option that is most similar to the version 6.x experience, check out option 2 . The biggest difference from what you are used to is that the directory structure of the downloaded library is slightly different and plugin files are named a little bit differently. Initializing and running jsPsych \u00b6 We've removed jsPsych.init() and split the features into two different functions. At the start of your experiment script, you'll now call initJsPsych() to get a new instance of jsPsych and store it in a variable called jsPsych . This is where you will pass in the variety of parameters that used to go into jsPsych.init() , with the exception of the timeline parameter. var jsPsych = initJsPsych ({ use_webaudio : false , on_finish : function (){ jsPsych . data . displayData (); } }); Once you've created your timeline, then you'll launch the experiment by calling jsPsych.run() , passing in the timeline as the only argument. This is the point in your script where you've used the jsPsych.init function in jsPsych v6.x. Because the jsPsych.run function only needs the experiment timeline, this argument should be an array (rather than an object like {timeline: timeline} in jsPsych v6.x). var timeline = [...] jsPsych . run ( timeline ); The type parameter for trials \u00b6 The type parameter now expects the value to be a plugin class rather than a string. For example, if you load the html-keyboard-response plugin from the CDN... < script src = \"http://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.0\" ></ script > ... or from the plugin-html-keyboard-response.js file in the release archive... < script src = \"plugin-html-keyboard-response.js\" ></ script > ... then a global variable defining the plugin's class called jsPsychHtmlKeyboardResponse is available. To create a trial using the plugin, pass this class as the type parameter. The plugin classes are named starting with jsPsych , followed by the plugin name written in camel case (rather than with dashes between words). See the \"Using a plugin\" section of the Plugins overview page for more examples. Note that the value is not a string . var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello, version 7.0!' } The choices parameter for keyboard response trials \u00b6 The choices parameter for keyboard response trials no longer supports jsPsych.NO_KEYS and jsPsych.ALL_KEYS , and they have been replaced by the strings \"NO_KEYS\" and \"ALL_KEYS\" respectively. For example, if you load the audio-keyboard-response plugin, you can prevent any user input like... var trial = { type : jsPsychAudioKeyboardResponse , choices : \"NO_KEYS\" , stimulus : 'example.ogg' , trial_ends_after_audio : true } Using extensions \u00b6 Like plugins, extensions are now also referenced by their class. Extensions are initiliazed in initJsPsych() instead of jsPsych.init() . Extension classes are named similarly to plugins, except that they start with jsPsychExtension . var jsPsych = initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }) The class is also used in trials that use the extension. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello, version 7.0!' , extensions : [ { type : jsPsychExtensionWebgazer } ] } Custom plugins \u00b6 If you have custom plugins that you would like to upgrade to be compatible with v7.x we recommend using our plugin template . The new template implements plugins as a class, but the core components are essentially unchanged. Anything in plugin.info from a v6.x plugin should be moved into the info object. Note that the type argument for the parameters follows a slightly different syntax in the v7.x plugins. This object is then assigned as a static property of the class . Anything in plugin.trial from a v6.x plugin should be moved into the trial method inside the class. The new template has a constructor() function that accepts an instance of jsPsych. You do not need to adjust this portion of the plugin. There are a few changes to be aware of that may affect your plugin code. We removed the registerPreload function and we now auto-detect media to preload via the type argument specified in the info object. If a parameter is listed as IMAGE , AUDIO , or VIDEO , it will be automatically preloaded. If you wish to disable preloading you can set the preload flag to false for the parameter. If you invoke any functions from jsPsych, like jsPsych.finishTrial() , note that jsPsych is no longer a global variable and you must use the reference to jsPsych that is passed to the constructor. To do this, simply prefix all jsPsych references with this. , e.g., jsPsych.finishTrial() becomes this.jsPsych.finishTrial() . If your reference to a jsPsych function is inside of another function, then in order for the this keyword to appropriately reference the jsPsych instance, you must also use a JavaScript arrow function expression for the outer function. For example, this: function end_trial () { // ... jsPsych . finishTrial ( data ); } Would be re-written as: const end_trial = () => { // ... this . jsPsych . finishTrial ( data ); } Need help? \u00b6 If you encounter issues migrating code to v7.x, feel free to post in our support thread for migration .","title":"Migrating from 6.x to 7.x"},{"location":"support/migration-v7/#migrating-an-experiment-to-v7x","text":"The release of version 7.0 changes a number of core components of jsPsych. We made these changes to improve jsPsych's compatibility with modern JavaScript tools like package managers and bundlers and to improve the developer experience for people contributing to jsPsych's codebase. We hope these changes will improve the long-term viability of the project and encourage more developers to contribute to jsPsych. Our aim was to accomplish these goals with minimal changes to the user experience of jsPsych. However, we did have to change a few critical things. This guide is aimed at users who are familiar with v6.x of jsPsych and would like to understand what's changed in v7.x.","title":"Migrating an experiment to v7.x"},{"location":"support/migration-v7/#loading-jspsych","text":"There are now three different ways you can load jsPsych into your HTML file. We've updated the hello world tutorial to walk through each of the three options. If you are looking for the option that is most similar to the version 6.x experience, check out option 2 . The biggest difference from what you are used to is that the directory structure of the downloaded library is slightly different and plugin files are named a little bit differently.","title":"Loading jsPsych"},{"location":"support/migration-v7/#initializing-and-running-jspsych","text":"We've removed jsPsych.init() and split the features into two different functions. At the start of your experiment script, you'll now call initJsPsych() to get a new instance of jsPsych and store it in a variable called jsPsych . This is where you will pass in the variety of parameters that used to go into jsPsych.init() , with the exception of the timeline parameter. var jsPsych = initJsPsych ({ use_webaudio : false , on_finish : function (){ jsPsych . data . displayData (); } }); Once you've created your timeline, then you'll launch the experiment by calling jsPsych.run() , passing in the timeline as the only argument. This is the point in your script where you've used the jsPsych.init function in jsPsych v6.x. Because the jsPsych.run function only needs the experiment timeline, this argument should be an array (rather than an object like {timeline: timeline} in jsPsych v6.x). var timeline = [...] jsPsych . run ( timeline );","title":"Initializing and running jsPsych"},{"location":"support/migration-v7/#the-type-parameter-for-trials","text":"The type parameter now expects the value to be a plugin class rather than a string. For example, if you load the html-keyboard-response plugin from the CDN... < script src = \"http://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.0\" ></ script > ... or from the plugin-html-keyboard-response.js file in the release archive... < script src = \"plugin-html-keyboard-response.js\" ></ script > ... then a global variable defining the plugin's class called jsPsychHtmlKeyboardResponse is available. To create a trial using the plugin, pass this class as the type parameter. The plugin classes are named starting with jsPsych , followed by the plugin name written in camel case (rather than with dashes between words). See the \"Using a plugin\" section of the Plugins overview page for more examples. Note that the value is not a string . var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello, version 7.0!' }","title":"The type parameter for trials"},{"location":"support/migration-v7/#the-choices-parameter-for-keyboard-response-trials","text":"The choices parameter for keyboard response trials no longer supports jsPsych.NO_KEYS and jsPsych.ALL_KEYS , and they have been replaced by the strings \"NO_KEYS\" and \"ALL_KEYS\" respectively. For example, if you load the audio-keyboard-response plugin, you can prevent any user input like... var trial = { type : jsPsychAudioKeyboardResponse , choices : \"NO_KEYS\" , stimulus : 'example.ogg' , trial_ends_after_audio : true }","title":"The choices parameter for keyboard response trials"},{"location":"support/migration-v7/#using-extensions","text":"Like plugins, extensions are now also referenced by their class. Extensions are initiliazed in initJsPsych() instead of jsPsych.init() . Extension classes are named similarly to plugins, except that they start with jsPsychExtension . var jsPsych = initJsPsych ({ extensions : [ { type : jsPsychExtensionWebgazer } ] }) The class is also used in trials that use the extension. var trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello, version 7.0!' , extensions : [ { type : jsPsychExtensionWebgazer } ] }","title":"Using extensions"},{"location":"support/migration-v7/#custom-plugins","text":"If you have custom plugins that you would like to upgrade to be compatible with v7.x we recommend using our plugin template . The new template implements plugins as a class, but the core components are essentially unchanged. Anything in plugin.info from a v6.x plugin should be moved into the info object. Note that the type argument for the parameters follows a slightly different syntax in the v7.x plugins. This object is then assigned as a static property of the class . Anything in plugin.trial from a v6.x plugin should be moved into the trial method inside the class. The new template has a constructor() function that accepts an instance of jsPsych. You do not need to adjust this portion of the plugin. There are a few changes to be aware of that may affect your plugin code. We removed the registerPreload function and we now auto-detect media to preload via the type argument specified in the info object. If a parameter is listed as IMAGE , AUDIO , or VIDEO , it will be automatically preloaded. If you wish to disable preloading you can set the preload flag to false for the parameter. If you invoke any functions from jsPsych, like jsPsych.finishTrial() , note that jsPsych is no longer a global variable and you must use the reference to jsPsych that is passed to the constructor. To do this, simply prefix all jsPsych references with this. , e.g., jsPsych.finishTrial() becomes this.jsPsych.finishTrial() . If your reference to a jsPsych function is inside of another function, then in order for the this keyword to appropriately reference the jsPsych instance, you must also use a JavaScript arrow function expression for the outer function. For example, this: function end_trial () { // ... jsPsych . finishTrial ( data ); } Would be re-written as: const end_trial = () => { // ... this . jsPsych . finishTrial ( data ); }","title":"Custom plugins"},{"location":"support/migration-v7/#need-help","text":"If you encounter issues migrating code to v7.x, feel free to post in our support thread for migration .","title":"Need help?"},{"location":"support/support/","text":"Support \u00b6 For questions about jsPsych, the preferred method of support is GitHub Discussions . Questions are most likely to be answered when they include a reproducible example of the problem. If you can make your code available online and link to the experiment, that will make the question easier to answer. Please consider searching through the archive of Q&As before posting a new question. If you have identified a problem with jsPsych, such as a bug in the code or an error in the documentation, please open a new issue on GitHub. If you have a suggestion for fixing the problem, feel free to contribute to the project ! Inquiries for paid consultation to develop experiments using jsPsych or to create new custom jsPsych features can be sent to josh.deleeuw@gmail.com .","title":"Getting Help"},{"location":"support/support/#support","text":"For questions about jsPsych, the preferred method of support is GitHub Discussions . Questions are most likely to be answered when they include a reproducible example of the problem. If you can make your code available online and link to the experiment, that will make the question easier to answer. Please consider searching through the archive of Q&As before posting a new question. If you have identified a problem with jsPsych, such as a bug in the code or an error in the documentation, please open a new issue on GitHub. If you have a suggestion for fixing the problem, feel free to contribute to the project ! Inquiries for paid consultation to develop experiments using jsPsych or to create new custom jsPsych features can be sent to josh.deleeuw@gmail.com .","title":"Support"},{"location":"tutorials/hello-world/","text":"jsPsych \"Hello world\" experiment \u00b6 In the long tradition of \"Hello world!\" examples, this tutorial creates an experiment that outputs the phrase \"Hello world!\" to the browser. Though useless as an actual experiment, the process is helpful for learning the basics of using the jsPsych library. Choose your own (setup) adventure \u00b6 Starting with the release of version 7.0 of jsPsych there are three different ways that you can add jsPsych to your project. Which approach you choose will depend on what your goals are. I want the simplest possible setup . This approach involves using scripts that are hosted on a CDN. You do not need to download or install anything to start using jsPsych. The limitation is that you cannot customize the library. For most experiments, this approach will be sufficient. I want to be able to do some customization, but have a simple setup. . This approach involves downloading a bundle of scripts that make up jsPsych. If you used jsPsych prior to version 7.0, this will feel like the most familiar approach . Having your own copy of the scripts means that you can make modifications to the library such as tweaking plugin behavior. I want to use modern JavaScript tooling, like npm and import statements. You can install jsPsych, plugins for jsPsych, and extensions for jsPsych from NPM. This approach allows you to integrate jsPsych into your favorite JavaScript frameworks and get the benefits of TypeScript, bundlers, and more. Option 1: Using CDN-hosted scripts \u00b6 Step 1: Create an HTML file \u00b6 Tip To edit jsPsych code you'll need a programming-friendly text editor. A great free option is Visual Studio Code (Windows, OSX, Linux). Create a new file called experiment.html . There's some basic code that (nearly) all HTML documents have in common. Here's a typical bare-bones HTML document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > </ head > < body ></ body > </ html > Add the above code to the experiment.html file and save it. If you open the file in a web browser, you should see a blank page and the title of the page will be 'My experiment'. Step 2: Load the jsPsych library \u00b6 To use jsPsych, add a <script> tag to load the library. We'll load the library from a CDN , which means that the library is hosted on another server and can be loaded without having your own copy. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > </ head > < body ></ body > </ html > Note that the URL for the jsPsych library includes the version number, which ensures that the behavior of your experiment won't change with any future updates to jsPsych. You may also want to import the jsPsych stylesheet, which applies a basic set of visual styles to the experiment. This requires adding a <link> tag to the <head> section of the document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > </ html > Step 3: Create a script element and initialize jsPsych \u00b6 To add JavaScript code directly to the webpage we need to add a pair of <script> tags after the <body> tags. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > To initialize jsPsych we use the initJsPsych() function and assign the output to a new variable. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Step 4: Use a plugin to print a message \u00b6 For this demo we want to show some text on the screen. This is exactly what the html-keyboard-response plugin is designed to do. To use the plugin, we need to load it with a <script> tag. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Once the plugin is loaded we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to jsPsychHtmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } </ script > </ html > Step 5: Run the experiment \u00b6 Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } jsPsych . run ([ hello_trial ]); </ script > </ html > Once you've saved the file, open it in a browser. You should see \"Hello world!\" printed on the screen, and if you press a key on the keyboard, the text should disappear (ending the trial). Option 2: Download and host jsPsych \u00b6 Step 1: Download jsPsych \u00b6 Start by downloading the latest release of jsPsych. Here's a direct link (jspsych.zip) . The most recent version can always be found at the top of the GitHub releases page . Note that even the releases that are for a particular plugin or extension will contain the full set of files needed to run jsPsych locally in the dist archive (zip) release asset. You should download the zip file for whatever the most recently released package is. This will ensure that you have the most recent version of all the packages associated with jsPsych. Step 2: Create a folder to store your experiment files \u00b6 Create a folder on your computer to put the experiment files in. We'll call this \"MyExperiment\" for the tutorial. Add a subfolder called jspsych . Once you've created the folder, open the downloaded archive from step 1 and copy the contents of the dist folder into the jspsych folder. It should look like this: \ud83d\udcc2 MyExperiment -- \ud83d\udcc2 jspsych ---- \ud83d\udcc4 jspsych.js ---- \ud83d\udcc4 plugin-animation.js ---- \ud83d\udcc4 plugin-audio-keyboard-response.js ---- ... Step 3: Create an HTML file \u00b6 Tip To edit jsPsych code you'll need a programming-friendly text editor. A great free option is Visual Studio Code (Windows, OSX, Linux). Create a new file called experiment.html in the MyExperiment folder. The directory structure should look like this: \ud83d\udcc2 MyExperiment -- \ud83d\udcc4 experiment.html -- \ud83d\udcc2 jspsych There's some basic code that (nearly) all HTML documents have in common. Here's a typical bare-bones HTML document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > </ head > < body ></ body > </ html > Add the above code to the experiment.html file and save it. If you open the file in a web browser, you should see a blank page and the title of the page will be 'My experiment'. Step 4: Load the jsPsych library \u00b6 To use jsPsych, add a <script> tag to load the library. Set the src attribute to the path to the jspsych.js file. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > </ head > < body ></ body > </ html > You may also want to import the jsPsych stylesheet, which applies a basic set of visual styles to the experiment. This requires adding a <link> tag to the <head> section of the document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > </ html > Step 5: Create a script element and initialize jsPsych \u00b6 To add JavaScript code directly to the webpage we need to add a pair of <script> tags after the <body> tags. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > To initialize jsPsych we use the initJsPsych() function and assign the output to a new variable. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Step 6: Use a plugin to print a message \u00b6 For this demo we want to show some text on the screen. This is exactly what the html-keyboard-response plugin is designed to do. To use the plugin, we need to load it with a <script> tag. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Once the plugin is loaded we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to jsPsychHtmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } </ script > </ html > Step 7: Run the experiment \u00b6 Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } jsPsych . run ([ hello_trial ]); </ script > </ html > Once you've saved the file, open it in a browser. You should see \"Hello world!\" printed on the screen, and if you press a key on the keyboard, the text should disappear (ending the trial). Option 3: Using NPM \u00b6 If you are electing to use npm to install jsPsych we will assume that you already are familiar with Node.js and generally know what you are doing with web development. We will also assume that you are using a webpack or a similar bundler. Info You may want to check out the jsPsych Builder CLI utility. jsPsych Builder allows you to automate the experiment setup, spin up a development server, and transpile and bundle scripts and styles using webpack. Using jsPsych Builder will automate some of the steps in this tutorial, so if you prefer that option, you may want to switch to the getting started instructions on the jsPsych Builder GitHub page. Step 1: Install jspsych \u00b6 Run npm install jspsych . This installs the core jsPsych package. Plugins and extensions are installed separately. Step 2: Import the initJsPsych function and create a new JsPsych instance \u00b6 We create a new instance of the JsPsych class by calling initJsPsych . The instance can optionally be configured via a variety of options , passed as an object to initJsPsych . import { initJsPsych } from 'jspsych' ; const jsPsych = initJsPsych (); Step 3: Static markup and CSS \u00b6 jsPsych requires nothing but a body element in your HTML document. For the jsPsych stylesheet, depending on your bundler setup, you can either directly import 'jspsych/css/jspsych.css' into your JavaScript file or add a link tag (like <link href=\"path/to/jspsych.css\" rel=\"stylesheet\" type=\"text/css\" /> ) to your HTML document's head. Step 4: Install and import a plugin \u00b6 Install the html-keyboard-response plugin with: npm install @jspsych/plugin-html-keyboard-response Then import the htmlKeyboardResponse plugin class. import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); Step 5: Create a trial \u00b6 Once the plugin is imported we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to htmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); const trial = { type : htmlKeyboardResponse , stimulus : 'Hello world!' , } Step 6: Run \u00b6 Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); const trial = { type : htmlKeyboardResponse , stimulus : 'Hello world!' , } jsPsych . run ([ trial ]);","title":"The Basics: Hello World"},{"location":"tutorials/hello-world/#jspsych-hello-world-experiment","text":"In the long tradition of \"Hello world!\" examples, this tutorial creates an experiment that outputs the phrase \"Hello world!\" to the browser. Though useless as an actual experiment, the process is helpful for learning the basics of using the jsPsych library.","title":"jsPsych \"Hello world\" experiment"},{"location":"tutorials/hello-world/#choose-your-own-setup-adventure","text":"Starting with the release of version 7.0 of jsPsych there are three different ways that you can add jsPsych to your project. Which approach you choose will depend on what your goals are. I want the simplest possible setup . This approach involves using scripts that are hosted on a CDN. You do not need to download or install anything to start using jsPsych. The limitation is that you cannot customize the library. For most experiments, this approach will be sufficient. I want to be able to do some customization, but have a simple setup. . This approach involves downloading a bundle of scripts that make up jsPsych. If you used jsPsych prior to version 7.0, this will feel like the most familiar approach . Having your own copy of the scripts means that you can make modifications to the library such as tweaking plugin behavior. I want to use modern JavaScript tooling, like npm and import statements. You can install jsPsych, plugins for jsPsych, and extensions for jsPsych from NPM. This approach allows you to integrate jsPsych into your favorite JavaScript frameworks and get the benefits of TypeScript, bundlers, and more.","title":"Choose your own (setup) adventure"},{"location":"tutorials/hello-world/#option-1-using-cdn-hosted-scripts","text":"","title":"Option 1: Using CDN-hosted scripts"},{"location":"tutorials/hello-world/#step-1-create-an-html-file","text":"Tip To edit jsPsych code you'll need a programming-friendly text editor. A great free option is Visual Studio Code (Windows, OSX, Linux). Create a new file called experiment.html . There's some basic code that (nearly) all HTML documents have in common. Here's a typical bare-bones HTML document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > </ head > < body ></ body > </ html > Add the above code to the experiment.html file and save it. If you open the file in a web browser, you should see a blank page and the title of the page will be 'My experiment'.","title":"Step 1: Create an HTML file"},{"location":"tutorials/hello-world/#step-2-load-the-jspsych-library","text":"To use jsPsych, add a <script> tag to load the library. We'll load the library from a CDN , which means that the library is hosted on another server and can be loaded without having your own copy. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > </ head > < body ></ body > </ html > Note that the URL for the jsPsych library includes the version number, which ensures that the behavior of your experiment won't change with any future updates to jsPsych. You may also want to import the jsPsych stylesheet, which applies a basic set of visual styles to the experiment. This requires adding a <link> tag to the <head> section of the document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > </ html >","title":"Step 2: Load the jsPsych library"},{"location":"tutorials/hello-world/#step-3-create-a-script-element-and-initialize-jspsych","text":"To add JavaScript code directly to the webpage we need to add a pair of <script> tags after the <body> tags. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > To initialize jsPsych we use the initJsPsych() function and assign the output to a new variable. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html >","title":"Step 3: Create a script element and initialize jsPsych"},{"location":"tutorials/hello-world/#step-4-use-a-plugin-to-print-a-message","text":"For this demo we want to show some text on the screen. This is exactly what the html-keyboard-response plugin is designed to do. To use the plugin, we need to load it with a <script> tag. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Once the plugin is loaded we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to jsPsychHtmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } </ script > </ html >","title":"Step 4: Use a plugin to print a message"},{"location":"tutorials/hello-world/#step-5-run-the-experiment","text":"Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } jsPsych . run ([ hello_trial ]); </ script > </ html > Once you've saved the file, open it in a browser. You should see \"Hello world!\" printed on the screen, and if you press a key on the keyboard, the text should disappear (ending the trial).","title":"Step 5: Run the experiment"},{"location":"tutorials/hello-world/#option-2-download-and-host-jspsych","text":"","title":"Option 2: Download and host jsPsych"},{"location":"tutorials/hello-world/#step-1-download-jspsych","text":"Start by downloading the latest release of jsPsych. Here's a direct link (jspsych.zip) . The most recent version can always be found at the top of the GitHub releases page . Note that even the releases that are for a particular plugin or extension will contain the full set of files needed to run jsPsych locally in the dist archive (zip) release asset. You should download the zip file for whatever the most recently released package is. This will ensure that you have the most recent version of all the packages associated with jsPsych.","title":"Step 1: Download jsPsych"},{"location":"tutorials/hello-world/#step-2-create-a-folder-to-store-your-experiment-files","text":"Create a folder on your computer to put the experiment files in. We'll call this \"MyExperiment\" for the tutorial. Add a subfolder called jspsych . Once you've created the folder, open the downloaded archive from step 1 and copy the contents of the dist folder into the jspsych folder. It should look like this: \ud83d\udcc2 MyExperiment -- \ud83d\udcc2 jspsych ---- \ud83d\udcc4 jspsych.js ---- \ud83d\udcc4 plugin-animation.js ---- \ud83d\udcc4 plugin-audio-keyboard-response.js ---- ...","title":"Step 2: Create a folder to store your experiment files"},{"location":"tutorials/hello-world/#step-3-create-an-html-file","text":"Tip To edit jsPsych code you'll need a programming-friendly text editor. A great free option is Visual Studio Code (Windows, OSX, Linux). Create a new file called experiment.html in the MyExperiment folder. The directory structure should look like this: \ud83d\udcc2 MyExperiment -- \ud83d\udcc4 experiment.html -- \ud83d\udcc2 jspsych There's some basic code that (nearly) all HTML documents have in common. Here's a typical bare-bones HTML document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > </ head > < body ></ body > </ html > Add the above code to the experiment.html file and save it. If you open the file in a web browser, you should see a blank page and the title of the page will be 'My experiment'.","title":"Step 3: Create an HTML file"},{"location":"tutorials/hello-world/#step-4-load-the-jspsych-library","text":"To use jsPsych, add a <script> tag to load the library. Set the src attribute to the path to the jspsych.js file. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > </ head > < body ></ body > </ html > You may also want to import the jsPsych stylesheet, which applies a basic set of visual styles to the experiment. This requires adding a <link> tag to the <head> section of the document. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > </ html >","title":"Step 4: Load the jsPsych library"},{"location":"tutorials/hello-world/#step-5-create-a-script-element-and-initialize-jspsych","text":"To add JavaScript code directly to the webpage we need to add a pair of <script> tags after the <body> tags. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > To initialize jsPsych we use the initJsPsych() function and assign the output to a new variable. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html >","title":"Step 5: Create a script element and initialize jsPsych"},{"location":"tutorials/hello-world/#step-6-use-a-plugin-to-print-a-message","text":"For this demo we want to show some text on the screen. This is exactly what the html-keyboard-response plugin is designed to do. To use the plugin, we need to load it with a <script> tag. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); </ script > </ html > Once the plugin is loaded we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to jsPsychHtmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } </ script > </ html >","title":"Step 6: Use a plugin to print a message"},{"location":"tutorials/hello-world/#step-7-run-the-experiment","text":"Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"jspsych/jspsych.js\" ></ script > < script src = \"jspsych/plugin-html-keyboard-response.js\" ></ script > < link href = \"jspsych/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > const jsPsych = initJsPsych (); const hello_trial = { type : jsPsychHtmlKeyboardResponse , stimulus : 'Hello world!' } jsPsych . run ([ hello_trial ]); </ script > </ html > Once you've saved the file, open it in a browser. You should see \"Hello world!\" printed on the screen, and if you press a key on the keyboard, the text should disappear (ending the trial).","title":"Step 7: Run the experiment"},{"location":"tutorials/hello-world/#option-3-using-npm","text":"If you are electing to use npm to install jsPsych we will assume that you already are familiar with Node.js and generally know what you are doing with web development. We will also assume that you are using a webpack or a similar bundler. Info You may want to check out the jsPsych Builder CLI utility. jsPsych Builder allows you to automate the experiment setup, spin up a development server, and transpile and bundle scripts and styles using webpack. Using jsPsych Builder will automate some of the steps in this tutorial, so if you prefer that option, you may want to switch to the getting started instructions on the jsPsych Builder GitHub page.","title":"Option 3: Using NPM"},{"location":"tutorials/hello-world/#step-1-install-jspsych","text":"Run npm install jspsych . This installs the core jsPsych package. Plugins and extensions are installed separately.","title":"Step 1: Install jspsych"},{"location":"tutorials/hello-world/#step-2-import-the-initjspsych-function-and-create-a-new-jspsych-instance","text":"We create a new instance of the JsPsych class by calling initJsPsych . The instance can optionally be configured via a variety of options , passed as an object to initJsPsych . import { initJsPsych } from 'jspsych' ; const jsPsych = initJsPsych ();","title":"Step 2: Import the initJsPsych function and create a new JsPsych instance"},{"location":"tutorials/hello-world/#step-3-static-markup-and-css","text":"jsPsych requires nothing but a body element in your HTML document. For the jsPsych stylesheet, depending on your bundler setup, you can either directly import 'jspsych/css/jspsych.css' into your JavaScript file or add a link tag (like <link href=\"path/to/jspsych.css\" rel=\"stylesheet\" type=\"text/css\" /> ) to your HTML document's head.","title":"Step 3: Static markup and CSS"},{"location":"tutorials/hello-world/#step-4-install-and-import-a-plugin","text":"Install the html-keyboard-response plugin with: npm install @jspsych/plugin-html-keyboard-response Then import the htmlKeyboardResponse plugin class. import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych ();","title":"Step 4: Install and import a plugin"},{"location":"tutorials/hello-world/#step-5-create-a-trial","text":"Once the plugin is imported we can create a trial using the plugin. To declare a trial that uses the html-keyboard-response plugin, we create an object with the property type equal to htmlKeyboardResponse . We can specify the other parameters of the plugin in the same object. Here we use the stimulus parameter to include a message. You can see the full set of parameters for each plugin on its documentation page . import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); const trial = { type : htmlKeyboardResponse , stimulus : 'Hello world!' , }","title":"Step 5: Create a trial"},{"location":"tutorials/hello-world/#step-6-run","text":"Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the jsPsych.run function and passing in a timeline . For a simple experiment like this one, the timeline is just an array containing the list of trials to run. import { initJsPsych } from 'jspsych' ; import htmlKeyboardResponse from '@jspsych/plugin-html-keyboard-response' ; const jsPsych = initJsPsych (); const trial = { type : htmlKeyboardResponse , stimulus : 'Hello world!' , } jsPsych . run ([ trial ]);","title":"Step 6: Run"},{"location":"tutorials/rt-task/","text":"Summary of Tutorial Content \u00b6 This tutorial will work through the creation of a simple response time task. The task is to press one key for a blue colored circle and another key for an orange colored circle. Despite this simple task, the tutorial covers many of the key features of jsPsych, including: Using a plugin to create a standard trial. Combining plugins together to create new kinds of trials. Using timeline variables to maximize code reuse. Preloading media. Randomizing presentation order. Manipulating, filtering, and aggregating data. Using dynamic content to change the experiment parameters based on the participant's responses. Part 1: Creating a blank experiment \u00b6 Start by setting up a new HTML file with jsPsych, the html-keyboard-response plugin, and the jspsych.css file loaded. If you are unsure how to do this, follow the Hello World tutorial . You should have an HTML document that looks like this: Info: Loading jsPsych This tutorial assumes that you are using the CDN-based method of loading jsPsych . If you are using another method then everything is the same except for how jsPsych is loaded. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > This will be our starting point for building the rest of the experiment. Part 2: Display welcome message \u00b6 First we have to initialize jsPsych. We can do this using the initJsPsych() function , and saving the result to a variable called jsPsych . var jsPsych = initJsPsych (); All jsPsych experiments are defined by a timeline. The timeline is an array that contains the set of trials we want to run in the experiment. We can start by defining an empty timeline array. We'll add trials to this array as we create them. var timeline = []; Let's greet the participant with a simple welcome message using the html-keyboard-response plugin. First, we create a trial that uses the html-keyboard-response plugin and contains a simple string to show the participant. As explained on the plugins documentation page , the trial object must have a type parameter that tells jsPsych which plugin to use. The value of type is similar to the plugin name, but starts with jsPsych and is written in camel case rather than with dashes. So to use the html-keyboard-response plugin, we need to write jsPsychHtmlKeyboardResponse as the trial type. var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; Next, we push the welcome trial to the timeline, which adds it to the end of the array. timeline . push ( welcome ); Finally, we tell jsPsych to run the experiment by calling the jsPsych.run() function and passing in the array that defines the experiment timeline. jsPsych . run ( timeline ); After each step in the tutorial you can view the complete code up to that point by clicking on the expandable box below. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 3: Show instructions \u00b6 We can use the same basic structure from part 2 to create a new html-keyboard-response trial that shows instructions to the participant. The only difference in this trial is that we will use HTML formatting to control how the instructions display and we will add a two second gap after the trial using the post_trial_gap parameter. The trial definition looks like this: var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; Tip In JavaScript there are three different ways to define a string . You can use single quotes ' , double quotes \" , or backticks ` . Using backticks has two advantages over the other approaches, especially when you are creating long strings with HTML. You can extend the string across multiple lines and you can use template strings to easily incorporate variables. Notice that the HTML includes <img> tags to display the images that the participant will be responding to. You'll need to download these image files. Right-click on each image below and select Save image as... . Put the images in a folder called img in the experiment folder you created in part 1. Don't forget to add the trial to the timeline: timeline . push ( instructions ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 4: Displaying stimuli and getting responses \u00b6 Creating trials to show the stimuli is conceptually the same as creating a trial to show instructions, except that now we are displaying an image instead of text or html. This means we need to use a different plugin: image-keyboard-response . We need to start by loading this plugin by adding a <script> tag to the document. < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > For now, we will just show each image once. The path to the image file should be set as the stimulus parameter. We will also set the option for which keys the participant is allowed to use to respond ( choices ) so that only the 'f' and 'j' keys are valid responses. var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; As usual, we need to add the trials to the timeline. timeline . push ( blue_trial , orange_trial ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define test trials */ var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; timeline . push ( blue_trial , orange_trial ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 5: Preloading media \u00b6 Whenever we use media elements (images, audio, or video) in an experiment it is a good idea to preload them prior to needing them for a trial. By preloading media we ask the participant's browser to download the media ahead of needing it, so that when we do need to display or play it there is no lag from needing to download it. We are going to use the preload plugin to preload the two images. The media preloading section goes into a lot of detail about various options for preloading and different ways that you can use this plugin. Here we are simply going to give the plugin a list of the files that we want to be preloaded. First we need to add the preload plugin to our <head> section. < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > We'll put this trial at the very start of the experiment, so add this code before the welcome trial. var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; As always, add the trial to the timeline. timeline . push ( preload ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define test trials */ var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; timeline . push ( blue_trial , orange_trial ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 6: Timeline variables \u00b6 In the full experiment, we will want more than two trials. One way we could do this is to create many more objects that define trials and push them all onto the timeline, but there is a more efficient way: using timeline variables. The parameters for showing the blue and orange circle are very similar. The only difference is which image is displayed. Timeline variables allow us to define the procedure for showing the stimulus once, and then repeatedly use it with different variables. We'll see how, even in this relatively simple case, this can save us a lot of lines of code. To start, let's make an array that contains all the different trials we want to run in the test phase. There are only two for the experiment: blue trials and orange trials. var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; Instead of just showing the blue and orange circles, let's also set up the experiment to show a fixation cross (+) in between trials. We can define a trial to show the fixation cross for a fixed amount of time by using the trial_duration parameter of the html-keyboard-response plugin and setting the choices parameter to the special value \"NO_KEYS\" , which means that no responses will be accepted as a valid response and the trial will last however long the trial_duration parameter specifies. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; To show the circles, we'll set up another trial with the image-keyboard-response plugin, but we'll use the function jsPsych.timelineVariable() to indicate that we want jsPsych to substitute the value of the parameter in from the timeline variables. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] } To link the variables that we declared in the test_stimuli array with the call to jsPsych.timelineVariable() we need to create a new timeline and set the timeline_variables property: var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli } We have to add the test_procedure to the main timeline array, but the fixation and test trial do not need to be added to timeline because they already exist on the test_procedure timeline. timeline . push ( test_procedure ); What happens when the experiment reaches the test procedure? jsPsych will run the test_procedure timeline one time for each entry in the test_stimuli array (two times total, in this case). The first time through, jsPsych will substitute the timeline variables from the first array entry (blue image), and the second time through the second array entry will be used (orange image). Notice that the fixation trial occurs before both the orange and the blue circles, because the entire timeline of the test_procedure is repeated for each entry in the timeline_variables array. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] } timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 7: Parameters for timelines with timeline variables \u00b6 Right now our experiment is a measly two trials long. Even worse is that the order of the stimuli is the same every time! When we use timeline variables, we get access to some methods to randomize the order and repeat the trials. To randomize the order, simply set randomize_order: true on the object with the timeline_variables : var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true }; We can also easily make the test phase longer by setting the repetitions parameter. This parameter controls how many times the experiment will loop through all of the entries in the timeline_variables array. For example, if we set repetitions: 5 , then the experiment will loop through the two entries in the timeline_variables 5 times, for a total of 10 test trials. var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; Info: Randomizing timeline variables In a timeline variables procedure, when randomize_order is true and repetitions is greater than 1, the trial order will be re-randomized on each repetition through the timeline_variables array. This means that there will be some constraints on the randomization of all trials in the procedure. For example, if a timeline_variables array contains one trial per stimulus, then the same stimulus could occur twice in a row (since it could be at the end of one repetition and the start of the next one), but it could not be repeated more than twice in a row, regardless of the number of repetitions . If you want to repeat your timeline_variables array but randomize across all trials, you could use the sample parameter with the fixed-repetitions option: this will combine all the repeitions of your timeline_variables array into one larger array, and then randomize the whole thing. You can read more about the randomization, repetition, and sampling options for timeline variables in the Timeline Variables documentation . The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 8: Using functions to generate parameters \u00b6 One aspect of the experiment that could be improved is the duration of the fixation cross. As the experiment stands right now, the timing of the circles appearing is very predictable. We can change that by using a different value for the trial_duration parameter in the fixation trial for each trial. But how can we do that and keep the simple code structure we have now where we only have to define the fixation trial once? One option would be to add another timeline variable, like \"fixation_duration\" and use that to control the timing. But another option is to specify the trial_duration parameter as a function. If a parameter is a function, jsPsych will execute the function every time the trial runs. That means that if the function returns different results probabilistically, we can get a different parameter value every time the trial runs. To do that here, we'll use one of the built-in randomization methods in jsPsych's randomization module . jsPsych.randomization.sampleWithoutReplacement() takes an array of items to sample from and generates a new array of length N by sampling without replacement. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } } In the code above, we replaced the trial_duration: 1000 parameter in fixation with a function. Inside the function, we take a sample from the array [250, 500, 750, 1000, 1250, 1500, 1750, 2000] of size 1 (second parameter to jsPsych.randomization.sampleWithoutReplacement ). The return value from calling jsPsych.randomization.sampleWithoutReplacement is an array of length 1, so we add the [0] selection at the end to get the value out of the array. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] } timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 10: Displaying the data \u00b6 We have created a complete, if simple, experiment at this point, so let's take a look at the data being generated. jsPsych has a built-in function called jsPsych.data.displayData() that is useful for debugging your experiment. It will remove all of the information on the screen and replace it with the raw data collected so far. This isn't terribly useful when you are actually running an experiment, but it's nice for checking the data during development. We need the displayData function to execute when the experiment ends. One way to do this is to use the on_finish callback function . This function will automatically execute once all the trials in the experiment are finished. We can specify this function in the experiment settings when we initialize jsPsych with the initJsPsych method. var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 11: Tagging trials with additional data \u00b6 All trials in jsPsych can be tagged with additional arbitrary data. This data will get stored alongside the data that the plugin normally generates, which allows experimenters to record properties of a trial along with the data from the trial. When might you use this feature? In this experiment, it would be nice to tag each trial with a circle as a response trial, so that the resulting data can be easily filtered to look at only the critical trials. We can do that like this. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' } }; We also could tag the test trials with a property that indicates what the correct response should be (F for the blue circles, J for the orange). In our current code, we are using the timeline variables feature of jsPsych to choose which circle gets presented on a trial. Since we want to tag the trials differently based on which circle is presented, we need to add the tagging data to the test_stimuli array, and then use the jsPsych.timelineVariable() function to get the value and assign it to a property in the data of the trial. We start by adding a \"correct_response\" property and value to each object in the test_stimuli : var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; Now we can use timelineVariable() in the data parameter of the test trial to get the appropriate \"correct_response\" value for each trial. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) } }; Another kind of tagging that would be useful is to mark each fixation trial as such, to make removing the data from fixation trials easier. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 12: Manipulating data during the experiment \u00b6 Now that the data from the test trials has a tag that describes the correct response, it would be easy to analyze the data after the fact and calculate whether the participant responded correctly. But, we can also do this in jsPsych as the experiment runs to save time later and enable a limited set of data analysis directly in the experiment code. To do this, we'll use the on_finish event of the test trial. We can assign a function to on_finish , and that function will receive an object containing the data generated by the trial. This object can be manipulated inside the function, and any changes made to the object will be stored in jsPsych's internal representation of the data. For this example, we'll determine whether the participant responded correctly, and add a new correct property to the data object. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; The data.response value is a string representation of the key the participant pressed. We can compare this with the data.correct_response value, and assign this computed value to a new property data.correct . Info: The compareKeys function Here we are comparing the values of data.response and data.correct_response using a jsPsych function called jsPsych.pluginAPI.compareKeys . We're using this function because it allows us to compare keys in either a case sensitive or case insensitive way, depending on the case_sensitive_responses parameter in the experiment settings . The participant's key response will be recorded in a case-sensitive way in the data (e.g. 'f' or 'F'), but in most cases, we don't care if their response corresponds to an upper or lower case letter (which is why the case_sensitive_responses experiment setting is false by default). Using the jsPsych.pluginAPI.commpareKeys function here means that the response will be scored correctly, even if the participant holds down Shift or has Caps Lock on. This function is only relevant for keyboard responses; for other kinds of responses, such as button presses, you can simply compare the response and correct response values directly, e.g. data . correct = data . response === data . correct_response ; The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html > Part 13: Data aggregation \u00b6 jsPsych provides a limited set of analysis functions to allow you to calculate things like mean response times for a selected set of trials. In this part, we'll use these functions to add a final trial to the experiment that tells the participant their accuracy and their mean response time for correct responses. We'll use the html-keyboard-response plugin. Because the text that we want to display changes based on the participant's performance in the experiment, we need to use a function for the stimulus parameter and return the desired text. Info: Dynamic parameters Using a function as the value of a 'normal' parameter (i.e. a parameter that isn't usually a function) provides lots of flexibility in jsPsych experiments, because it allows you to dynamically change the parameter's value based on the participant's earlier responses, and any other information that you don't know before the experiment has started. For more information and examples, see the dynamic parameter documentation page . Here's what the code looks like, and a description follows below. var debrief_block = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trials = jsPsych . data . get (). filter ({ task : 'response' }); var correct_trials = trials . filter ({ correct : true }); var accuracy = Math . round ( correct_trials . count () / trials . count () * 100 ); var rt = Math . round ( correct_trials . select ( 'rt' ). mean ()); return `<p>You responded correctly on ${ accuracy } % of the trials.</p> <p>Your average response time was ${ rt } ms.</p> <p>Press any key to complete the experiment. Thank you!</p>` ; } }; timeline . push ( debrief_block ); To create the variable trials , we use jsPsych.data.get() which returns a jsPsych data collection containing all of the data from the experiment. We can then use .filter to select only the trials where task is 'response' (a benefit of tagging the trials in part 11). trials contains all of the data from the trials where a circle was shown. To get only the correct trials, we can use .filter() again to select only the trials from the trials data collection where the property correct is true . To calculate accuracy, we can use the .count() method to determine how many trials were correct and how many trials there were total. We also use Math.round() to avoid extra digits after the decimal. Finally, to calculate the mean response time on correct trials, we use the .select method on the correct_trials data collection to select only the 'rt' property of those trials. We can then use the .mean() method to find the mean of all the RT values. The final code \u00b6 This code is available in the /examples folder in the jsPsych release download. It is called demo-simple-rt-task.html . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , repetitions : 5 , randomize_order : true }; timeline . push ( test_procedure ); /* define debrief */ var debrief_block = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trials = jsPsych . data . get (). filter ({ task : 'response' }); var correct_trials = trials . filter ({ correct : true }); var accuracy = Math . round ( correct_trials . count () / trials . count () * 100 ); var rt = Math . round ( correct_trials . select ( 'rt' ). mean ()); return `<p>You responded correctly on ${ accuracy } % of the trials.</p> <p>Your average response time was ${ rt } ms.</p> <p>Press any key to complete the experiment. Thank you!</p>` ; } }; timeline . push ( debrief_block ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Demo Experiment: Simple Reaction Time Task"},{"location":"tutorials/rt-task/#summary-of-tutorial-content","text":"This tutorial will work through the creation of a simple response time task. The task is to press one key for a blue colored circle and another key for an orange colored circle. Despite this simple task, the tutorial covers many of the key features of jsPsych, including: Using a plugin to create a standard trial. Combining plugins together to create new kinds of trials. Using timeline variables to maximize code reuse. Preloading media. Randomizing presentation order. Manipulating, filtering, and aggregating data. Using dynamic content to change the experiment parameters based on the participant's responses.","title":"Summary of Tutorial Content"},{"location":"tutorials/rt-task/#part-1-creating-a-blank-experiment","text":"Start by setting up a new HTML file with jsPsych, the html-keyboard-response plugin, and the jspsych.css file loaded. If you are unsure how to do this, follow the Hello World tutorial . You should have an HTML document that looks like this: Info: Loading jsPsych This tutorial assumes that you are using the CDN-based method of loading jsPsych . If you are using another method then everything is the same except for how jsPsych is loaded. <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > </ script > </ html > This will be our starting point for building the rest of the experiment.","title":"Part 1: Creating a blank experiment"},{"location":"tutorials/rt-task/#part-2-display-welcome-message","text":"First we have to initialize jsPsych. We can do this using the initJsPsych() function , and saving the result to a variable called jsPsych . var jsPsych = initJsPsych (); All jsPsych experiments are defined by a timeline. The timeline is an array that contains the set of trials we want to run in the experiment. We can start by defining an empty timeline array. We'll add trials to this array as we create them. var timeline = []; Let's greet the participant with a simple welcome message using the html-keyboard-response plugin. First, we create a trial that uses the html-keyboard-response plugin and contains a simple string to show the participant. As explained on the plugins documentation page , the trial object must have a type parameter that tells jsPsych which plugin to use. The value of type is similar to the plugin name, but starts with jsPsych and is written in camel case rather than with dashes. So to use the html-keyboard-response plugin, we need to write jsPsychHtmlKeyboardResponse as the trial type. var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; Next, we push the welcome trial to the timeline, which adds it to the end of the array. timeline . push ( welcome ); Finally, we tell jsPsych to run the experiment by calling the jsPsych.run() function and passing in the array that defines the experiment timeline. jsPsych . run ( timeline ); After each step in the tutorial you can view the complete code up to that point by clicking on the expandable box below. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 2: Display welcome message"},{"location":"tutorials/rt-task/#part-3-show-instructions","text":"We can use the same basic structure from part 2 to create a new html-keyboard-response trial that shows instructions to the participant. The only difference in this trial is that we will use HTML formatting to control how the instructions display and we will add a two second gap after the trial using the post_trial_gap parameter. The trial definition looks like this: var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; Tip In JavaScript there are three different ways to define a string . You can use single quotes ' , double quotes \" , or backticks ` . Using backticks has two advantages over the other approaches, especially when you are creating long strings with HTML. You can extend the string across multiple lines and you can use template strings to easily incorporate variables. Notice that the HTML includes <img> tags to display the images that the participant will be responding to. You'll need to download these image files. Right-click on each image below and select Save image as... . Put the images in a folder called img in the experiment folder you created in part 1. Don't forget to add the trial to the timeline: timeline . push ( instructions ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 3: Show instructions"},{"location":"tutorials/rt-task/#part-4-displaying-stimuli-and-getting-responses","text":"Creating trials to show the stimuli is conceptually the same as creating a trial to show instructions, except that now we are displaying an image instead of text or html. This means we need to use a different plugin: image-keyboard-response . We need to start by loading this plugin by adding a <script> tag to the document. < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > For now, we will just show each image once. The path to the image file should be set as the stimulus parameter. We will also set the option for which keys the participant is allowed to use to respond ( choices ) so that only the 'f' and 'j' keys are valid responses. var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; As usual, we need to add the trials to the timeline. timeline . push ( blue_trial , orange_trial ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define test trials */ var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; timeline . push ( blue_trial , orange_trial ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 4: Displaying stimuli and getting responses"},{"location":"tutorials/rt-task/#part-5-preloading-media","text":"Whenever we use media elements (images, audio, or video) in an experiment it is a good idea to preload them prior to needing them for a trial. By preloading media we ask the participant's browser to download the media ahead of needing it, so that when we do need to display or play it there is no lag from needing to download it. We are going to use the preload plugin to preload the two images. The media preloading section goes into a lot of detail about various options for preloading and different ways that you can use this plugin. Here we are simply going to give the plugin a list of the files that we want to be preloaded. First we need to add the preload plugin to our <head> section. < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > We'll put this trial at the very start of the experiment, so add this code before the welcome trial. var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; As always, add the trial to the timeline. timeline . push ( preload ); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define test trials */ var blue_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/blue.png' , choices : [ 'f' , 'j' ] }; var orange_trial = { type : jsPsychImageKeyboardResponse , stimulus : 'img/orange.png' , choices : [ 'f' , 'j' ] }; timeline . push ( blue_trial , orange_trial ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 5: Preloading media"},{"location":"tutorials/rt-task/#part-6-timeline-variables","text":"In the full experiment, we will want more than two trials. One way we could do this is to create many more objects that define trials and push them all onto the timeline, but there is a more efficient way: using timeline variables. The parameters for showing the blue and orange circle are very similar. The only difference is which image is displayed. Timeline variables allow us to define the procedure for showing the stimulus once, and then repeatedly use it with different variables. We'll see how, even in this relatively simple case, this can save us a lot of lines of code. To start, let's make an array that contains all the different trials we want to run in the test phase. There are only two for the experiment: blue trials and orange trials. var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; Instead of just showing the blue and orange circles, let's also set up the experiment to show a fixation cross (+) in between trials. We can define a trial to show the fixation cross for a fixed amount of time by using the trial_duration parameter of the html-keyboard-response plugin and setting the choices parameter to the special value \"NO_KEYS\" , which means that no responses will be accepted as a valid response and the trial will last however long the trial_duration parameter specifies. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; To show the circles, we'll set up another trial with the image-keyboard-response plugin, but we'll use the function jsPsych.timelineVariable() to indicate that we want jsPsych to substitute the value of the parameter in from the timeline variables. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] } To link the variables that we declared in the test_stimuli array with the call to jsPsych.timelineVariable() we need to create a new timeline and set the timeline_variables property: var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli } We have to add the test_procedure to the main timeline array, but the fixation and test trial do not need to be added to timeline because they already exist on the test_procedure timeline. timeline . push ( test_procedure ); What happens when the experiment reaches the test procedure? jsPsych will run the test_procedure timeline one time for each entry in the test_stimuli array (two times total, in this case). The first time through, jsPsych will substitute the timeline variables from the first array entry (blue image), and the second time through the second array entry will be used (orange image). Notice that the fixation trial occurs before both the orange and the blue circles, because the entire timeline of the test_procedure is repeated for each entry in the timeline_variables array. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] } timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 6: Timeline variables"},{"location":"tutorials/rt-task/#part-7-parameters-for-timelines-with-timeline-variables","text":"Right now our experiment is a measly two trials long. Even worse is that the order of the stimuli is the same every time! When we use timeline variables, we get access to some methods to randomize the order and repeat the trials. To randomize the order, simply set randomize_order: true on the object with the timeline_variables : var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true }; We can also easily make the test phase longer by setting the repetitions parameter. This parameter controls how many times the experiment will loop through all of the entries in the timeline_variables array. For example, if we set repetitions: 5 , then the experiment will loop through the two entries in the timeline_variables 5 times, for a total of 10 test trials. var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; Info: Randomizing timeline variables In a timeline variables procedure, when randomize_order is true and repetitions is greater than 1, the trial order will be re-randomized on each repetition through the timeline_variables array. This means that there will be some constraints on the randomization of all trials in the procedure. For example, if a timeline_variables array contains one trial per stimulus, then the same stimulus could occur twice in a row (since it could be at the end of one repetition and the start of the next one), but it could not be repeated more than twice in a row, regardless of the number of repetitions . If you want to repeat your timeline_variables array but randomize across all trials, you could use the sample parameter with the fixed-repetitions option: this will combine all the repeitions of your timeline_variables array into one larger array, and then randomize the whole thing. You can read more about the randomization, repetition, and sampling options for timeline variables in the Timeline Variables documentation . The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : 1000 , }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 7: Parameters for timelines with timeline variables"},{"location":"tutorials/rt-task/#part-8-using-functions-to-generate-parameters","text":"One aspect of the experiment that could be improved is the duration of the fixation cross. As the experiment stands right now, the timing of the circles appearing is very predictable. We can change that by using a different value for the trial_duration parameter in the fixation trial for each trial. But how can we do that and keep the simple code structure we have now where we only have to define the fixation trial once? One option would be to add another timeline variable, like \"fixation_duration\" and use that to control the timing. But another option is to specify the trial_duration parameter as a function. If a parameter is a function, jsPsych will execute the function every time the trial runs. That means that if the function returns different results probabilistically, we can get a different parameter value every time the trial runs. To do that here, we'll use one of the built-in randomization methods in jsPsych's randomization module . jsPsych.randomization.sampleWithoutReplacement() takes an array of items to sample from and generates a new array of length N by sampling without replacement. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } } In the code above, we replaced the trial_duration: 1000 parameter in fixation with a function. Inside the function, we take a sample from the array [250, 500, 750, 1000, 1250, 1500, 1750, 2000] of size 1 (second parameter to jsPsych.randomization.sampleWithoutReplacement ). The return value from calling jsPsych.randomization.sampleWithoutReplacement is an array of length 1, so we add the [0] selection at the end to get the value out of the array. The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych (); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] } timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 8: Using functions to generate parameters"},{"location":"tutorials/rt-task/#part-10-displaying-the-data","text":"We have created a complete, if simple, experiment at this point, so let's take a look at the data being generated. jsPsych has a built-in function called jsPsych.data.displayData() that is useful for debugging your experiment. It will remove all of the information on the screen and replace it with the raw data collected so far. This isn't terribly useful when you are actually running an experiment, but it's nice for checking the data during development. We need the displayData function to execute when the experiment ends. One way to do this is to use the on_finish callback function . This function will automatically execute once all the trials in the experiment are finished. We can specify this function in the experiment settings when we initialize jsPsych with the initJsPsych method. var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" }, { stimulus : \"img/orange.png\" } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ] }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 10: Displaying the data"},{"location":"tutorials/rt-task/#part-11-tagging-trials-with-additional-data","text":"All trials in jsPsych can be tagged with additional arbitrary data. This data will get stored alongside the data that the plugin normally generates, which allows experimenters to record properties of a trial along with the data from the trial. When might you use this feature? In this experiment, it would be nice to tag each trial with a circle as a response trial, so that the resulting data can be easily filtered to look at only the critical trials. We can do that like this. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' } }; We also could tag the test trials with a property that indicates what the correct response should be (F for the blue circles, J for the orange). In our current code, we are using the timeline variables feature of jsPsych to choose which circle gets presented on a trial. Since we want to tag the trials differently based on which circle is presented, we need to add the tagging data to the test_stimuli array, and then use the jsPsych.timelineVariable() function to get the value and assign it to a property in the data of the trial. We start by adding a \"correct_response\" property and value to each object in the test_stimuli : var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; Now we can use timelineVariable() in the data parameter of the test trial to get the appropriate \"correct_response\" value for each trial. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) } }; Another kind of tagging that would be useful is to mark each fixation trial as such, to make removing the data from fixation trials easier. var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 11: Tagging trials with additional data"},{"location":"tutorials/rt-task/#part-12-manipulating-data-during-the-experiment","text":"Now that the data from the test trials has a tag that describes the correct response, it would be easy to analyze the data after the fact and calculate whether the participant responded correctly. But, we can also do this in jsPsych as the experiment runs to save time later and enable a limited set of data analysis directly in the experiment code. To do this, we'll use the on_finish event of the test trial. We can assign a function to on_finish , and that function will receive an object containing the data generated by the trial. This object can be manipulated inside the function, and any changes made to the object will be stored in jsPsych's internal representation of the data. For this example, we'll determine whether the participant responded correctly, and add a new correct property to the data object. var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; The data.response value is a string representation of the key the participant pressed. We can compare this with the data.correct_response value, and assign this computed value to a new property data.correct . Info: The compareKeys function Here we are comparing the values of data.response and data.correct_response using a jsPsych function called jsPsych.pluginAPI.compareKeys . We're using this function because it allows us to compare keys in either a case sensitive or case insensitive way, depending on the case_sensitive_responses parameter in the experiment settings . The participant's key response will be recorded in a case-sensitive way in the data (e.g. 'f' or 'F'), but in most cases, we don't care if their response corresponds to an upper or lower case letter (which is why the case_sensitive_responses experiment setting is false by default). Using the jsPsych.pluginAPI.commpareKeys function here means that the response will be scored correctly, even if the participant holds down Shift or has Caps Lock on. This function is only relevant for keyboard responses; for other kinds of responses, such as button presses, you can simply compare the response and correct response values directly, e.g. data . correct = data . response === data . correct_response ; The complete code so far <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , randomize_order : true , repetitions : 5 }; timeline . push ( test_procedure ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"Part 12: Manipulating data during the experiment"},{"location":"tutorials/rt-task/#part-13-data-aggregation","text":"jsPsych provides a limited set of analysis functions to allow you to calculate things like mean response times for a selected set of trials. In this part, we'll use these functions to add a final trial to the experiment that tells the participant their accuracy and their mean response time for correct responses. We'll use the html-keyboard-response plugin. Because the text that we want to display changes based on the participant's performance in the experiment, we need to use a function for the stimulus parameter and return the desired text. Info: Dynamic parameters Using a function as the value of a 'normal' parameter (i.e. a parameter that isn't usually a function) provides lots of flexibility in jsPsych experiments, because it allows you to dynamically change the parameter's value based on the participant's earlier responses, and any other information that you don't know before the experiment has started. For more information and examples, see the dynamic parameter documentation page . Here's what the code looks like, and a description follows below. var debrief_block = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trials = jsPsych . data . get (). filter ({ task : 'response' }); var correct_trials = trials . filter ({ correct : true }); var accuracy = Math . round ( correct_trials . count () / trials . count () * 100 ); var rt = Math . round ( correct_trials . select ( 'rt' ). mean ()); return `<p>You responded correctly on ${ accuracy } % of the trials.</p> <p>Your average response time was ${ rt } ms.</p> <p>Press any key to complete the experiment. Thank you!</p>` ; } }; timeline . push ( debrief_block ); To create the variable trials , we use jsPsych.data.get() which returns a jsPsych data collection containing all of the data from the experiment. We can then use .filter to select only the trials where task is 'response' (a benefit of tagging the trials in part 11). trials contains all of the data from the trials where a circle was shown. To get only the correct trials, we can use .filter() again to select only the trials from the trials data collection where the property correct is true . To calculate accuracy, we can use the .count() method to determine how many trials were correct and how many trials there were total. We also use Math.round() to avoid extra digits after the decimal. Finally, to calculate the mean response time on correct trials, we use the .select method on the correct_trials data collection to select only the 'rt' property of those trials. We can then use the .mean() method to find the mean of all the RT values.","title":"Part 13: Data aggregation"},{"location":"tutorials/rt-task/#the-final-code","text":"This code is available in the /examples folder in the jsPsych release download. It is called demo-simple-rt-task.html . <!DOCTYPE html> < html > < head > < title > My experiment </ title > < script src = \"https://unpkg.com/jspsych@7.3.4\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3\" ></ script > < script src = \"https://unpkg.com/@jspsych/plugin-preload@1.1.3\" ></ script > < link href = \"https://unpkg.com/jspsych@7.3.4/css/jspsych.css\" rel = \"stylesheet\" type = \"text/css\" /> </ head > < body ></ body > < script > /* initialize jsPsych */ var jsPsych = initJsPsych ({ on_finish : function () { jsPsych . data . displayData (); } }); /* create timeline */ var timeline = []; /* preload images */ var preload = { type : jsPsychPreload , images : [ 'img/blue.png' , 'img/orange.png' ] }; timeline . push ( preload ); /* define welcome message trial */ var welcome = { type : jsPsychHtmlKeyboardResponse , stimulus : \"Welcome to the experiment. Press any key to begin.\" }; timeline . push ( welcome ); /* define instructions trial */ var instructions = { type : jsPsychHtmlKeyboardResponse , stimulus : ` <p>In this experiment, a circle will appear in the center of the screen.</p><p>If the circle is <strong>blue</strong>, press the letter F on the keyboard as fast as you can.</p> <p>If the circle is <strong>orange</strong>, press the letter J as fast as you can.</p> <div style='width: 700px;'> <div style='float: left;'><img src='img/blue.png'></img> <p class='small'><strong>Press the F key</strong></p></div> <div style='float: right;'><img src='img/orange.png'></img> <p class='small'><strong>Press the J key</strong></p></div> </div> <p>Press any key to begin.</p> ` , post_trial_gap : 2000 }; timeline . push ( instructions ); /* define trial stimuli array for timeline variables */ var test_stimuli = [ { stimulus : \"img/blue.png\" , correct_response : 'f' }, { stimulus : \"img/orange.png\" , correct_response : 'j' } ]; /* define fixation and test trials */ var fixation = { type : jsPsychHtmlKeyboardResponse , stimulus : '<div style=\"font-size:60px;\">+</div>' , choices : \"NO_KEYS\" , trial_duration : function (){ return jsPsych . randomization . sampleWithoutReplacement ([ 250 , 500 , 750 , 1000 , 1250 , 1500 , 1750 , 2000 ], 1 )[ 0 ]; }, data : { task : 'fixation' } }; var test = { type : jsPsychImageKeyboardResponse , stimulus : jsPsych . timelineVariable ( 'stimulus' ), choices : [ 'f' , 'j' ], data : { task : 'response' , correct_response : jsPsych . timelineVariable ( 'correct_response' ) }, on_finish : function ( data ){ data . correct = jsPsych . pluginAPI . compareKeys ( data . response , data . correct_response ); } }; /* define test procedure */ var test_procedure = { timeline : [ fixation , test ], timeline_variables : test_stimuli , repetitions : 5 , randomize_order : true }; timeline . push ( test_procedure ); /* define debrief */ var debrief_block = { type : jsPsychHtmlKeyboardResponse , stimulus : function () { var trials = jsPsych . data . get (). filter ({ task : 'response' }); var correct_trials = trials . filter ({ correct : true }); var accuracy = Math . round ( correct_trials . count () / trials . count () * 100 ); var rt = Math . round ( correct_trials . select ( 'rt' ). mean ()); return `<p>You responded correctly on ${ accuracy } % of the trials.</p> <p>Your average response time was ${ rt } ms.</p> <p>Press any key to complete the experiment. Thank you!</p>` ; } }; timeline . push ( debrief_block ); /* start the experiment */ jsPsych . run ( timeline ); </ script > </ html >","title":"The final code"},{"location":"tutorials/video-tutorials/","text":"Video tutorials \u00b6 Warning Most of these videos are using version 6.x of jsPsych. Using version 7.x requires a few changes that are not covered in these videos. We recommend starting with the tutorials on this website to understand how to work with 7.x and then watching these videos for additional information. Much of the content covered in the videos still applies to 7.x , but you'll need a solid understanding of how to use 7.x in order to make use of the examples in the videos. YouTube Channel \u00b6 A variety of video tutorials are available on Josh de Leeuw's YouTube channel . Some tutorials walk through creating a basic version of an entire experiment, like the tutorial on creating a dichotic listening experiment aimed at new users. Others focus on specific features of jsPsych, like how to use functions as parameters to create experiments that change in response to participant input or how to create a new plugin . Workshops \u00b6 Moving Research Online (2020) . Recordings from a Summer 2020 workshop on conducting online research are available on the workshop's YouTube channel . Session 1 provides an overview of jsPsych suitable for brand new users. Session 3 covers some more advanced features of jsPsych. This workshop was funded by the National Science Foundation. babySTEP (2021) . The Centre for Comparative Psycholinguistics (CCP, University of Alberta Department of Linguistics) hosted a two-part jsPsych workshop in 2021 as part of their annual STEP program . Day 1 covered the basics of creating a jsPsych experiment, with an emphasis on audio stimuli. Day 2 was organized around pre-submitted questions. The video demonstrates how to create a more complex experiment involving reading a sentence and hearing different audio options for completing the sentences, and answers several questions about timing accuracy, recording participant generated audio, embedding jsPsych into course (or other) websites, and some (non-empirical) advice about attention checks.","title":"Video Tutorials"},{"location":"tutorials/video-tutorials/#video-tutorials","text":"Warning Most of these videos are using version 6.x of jsPsych. Using version 7.x requires a few changes that are not covered in these videos. We recommend starting with the tutorials on this website to understand how to work with 7.x and then watching these videos for additional information. Much of the content covered in the videos still applies to 7.x , but you'll need a solid understanding of how to use 7.x in order to make use of the examples in the videos.","title":"Video tutorials"},{"location":"tutorials/video-tutorials/#youtube-channel","text":"A variety of video tutorials are available on Josh de Leeuw's YouTube channel . Some tutorials walk through creating a basic version of an entire experiment, like the tutorial on creating a dichotic listening experiment aimed at new users. Others focus on specific features of jsPsych, like how to use functions as parameters to create experiments that change in response to participant input or how to create a new plugin .","title":"YouTube Channel"},{"location":"tutorials/video-tutorials/#workshops","text":"Moving Research Online (2020) . Recordings from a Summer 2020 workshop on conducting online research are available on the workshop's YouTube channel . Session 1 provides an overview of jsPsych suitable for brand new users. Session 3 covers some more advanced features of jsPsych. This workshop was funded by the National Science Foundation. babySTEP (2021) . The Centre for Comparative Psycholinguistics (CCP, University of Alberta Department of Linguistics) hosted a two-part jsPsych workshop in 2021 as part of their annual STEP program . Day 1 covered the basics of creating a jsPsych experiment, with an emphasis on audio stimuli. Day 2 was organized around pre-submitted questions. The video demonstrates how to create a more complex experiment involving reading a sentence and hearing different audio options for completing the sentences, and answers several questions about timing accuracy, recording participant generated audio, embedding jsPsych into course (or other) websites, and some (non-empirical) advice about attention checks.","title":"Workshops"}]}
\ No newline at end of file
diff --git a/7.3/sitemap.xml b/7.3/sitemap.xml
old mode 100755
new mode 100644
index 986b83ab64..9288832719
--- a/7.3/sitemap.xml
+++ b/7.3/sitemap.xml
@@ -2,482 +2,482 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
     <url>
          <loc>https://www.jspsych.org/7.3/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/about/about/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/about/license/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/developers/configuration/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/developers/contributing/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/developers/documentation/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/developers/extension-development/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/developers/plugin-development/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/extensions/list-of-extensions/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/extensions/mouse-tracking/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/extensions/record-video/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/extensions/webgazer/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/browser-device-support/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/data/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/dynamic-parameters/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/events/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/exclude-browser/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/experiment-options/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/extensions/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/eye-tracking/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/fullscreen/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/media-preloading/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/mturk/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/plugins/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/progress-bar/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/prolific/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/record-browser-interactions/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/running-experiments/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/simulation/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/style/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/timeline/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/overview/timing-accuracy/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/animation/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/audio-button-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/audio-keyboard-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/audio-slider-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/browser-check/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/call-function/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/canvas-button-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/canvas-keyboard-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/canvas-slider-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/categorize-animation/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/categorize-html/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/categorize-image/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/cloze/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/external-html/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/free-sort/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/fullscreen/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/html-audio-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/html-button-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/html-keyboard-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/html-slider-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/html-video-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/iat-html/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/iat-image/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/image-button-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/image-keyboard-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/image-slider-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/initialize-camera/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/initialize-microphone/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/instructions/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/list-of-plugins/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/maxdiff/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/mirror-camera/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/preload/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/reconstruction/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/resize/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/same-different-html/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/same-different-image/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/serial-reaction-time-mouse/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/serial-reaction-time/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/sketchpad/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/survey-html-form/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/survey-likert/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/survey-multi-choice/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/survey-multi-select/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/survey-text/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/survey/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/video-button-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/video-keyboard-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/video-slider-response/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/virtual-chinrest/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/visual-search-circle/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/webgazer-calibrate/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/webgazer-init-camera/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/plugins/webgazer-validate/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/reference/jspsych-data/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/reference/jspsych-pluginAPI/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/reference/jspsych-randomization/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/reference/jspsych-turk/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/reference/jspsych/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/support/migration-v7/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/support/support/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/tutorials/hello-world/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/tutorials/rt-task/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>https://www.jspsych.org/7.3/tutorials/video-tutorials/</loc>
-         <lastmod>2023-05-17</lastmod>
+         <lastmod>2023-11-15</lastmod>
          <changefreq>daily</changefreq>
     </url>
 </urlset>
\ No newline at end of file
diff --git a/7.3/sitemap.xml.gz b/7.3/sitemap.xml.gz
old mode 100755
new mode 100644
index e21e6c2f95..f948721fed
Binary files a/7.3/sitemap.xml.gz and b/7.3/sitemap.xml.gz differ
diff --git a/7.3/support/migration-v7/index.html b/7.3/support/migration-v7/index.html
old mode 100755
new mode 100644
index 714875625a..44a4cc7703
--- a/7.3/support/migration-v7/index.html
+++ b/7.3/support/migration-v7/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/support/migration-v7/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1999,16 +2002,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/support/migration-v7.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="migrating-an-experiment-to-v7x">Migrating an experiment to v7.x<a class="headerlink" href="#migrating-an-experiment-to-v7x" title="Permanent link">&para;</a></h1>
 <p>The release of version 7.0 changes a number of core components of jsPsych. 
 We made these changes to improve jsPsych's compatibility with modern JavaScript tools like package managers and bundlers and to improve the developer experience for people contributing to jsPsych's codebase. 
@@ -2025,19 +2030,19 @@ <h2 id="initializing-and-running-jspsych">Initializing and running jsPsych<a cla
 <p>We've removed <code>jsPsych.init()</code> and split the features into two different functions. </p>
 <p>At the start of your experiment script, you'll now call <code>initJsPsych()</code> to get a new instance of jsPsych and store it in a variable called <code>jsPsych</code>. 
 This is where you will pass in the variety of parameters that used to go into <code>jsPsych.init()</code>, with the exception of the <code>timeline</code> parameter.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">use_webaudio</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">use_webaudio</span><span class="o">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 <p>Once you've created your timeline, then you'll launch the experiment by calling <code>jsPsych.run()</code>, passing in the timeline as the only argument. 
 This is the point in your script where you've used the <code>jsPsych.init</code> function in jsPsych v6.x. 
 Because the <code>jsPsych.run</code> function only needs the experiment timeline, this argument should be an <em>array</em> (rather than an object like <code>{timeline: timeline}</code> in jsPsych v6.x).</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[...]</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[...]</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 </code></pre></div>
 <h2 id="the-type-parameter-for-trials">The <code>type</code> parameter for trials<a class="headerlink" href="#the-type-parameter-for-trials" title="Permanent link">&para;</a></h2>
 <p>The <code>type</code> parameter now expects the value to be a plugin class rather than a string. </p>
@@ -2052,39 +2057,39 @@ <h2 id="the-type-parameter-for-trials">The <code>type</code> parameter for trial
 The plugin classes are named starting with <code>jsPsych</code>, followed by the plugin name written in camel case (rather than with dashes between words).
 See the <a href="../../overview/plugins/#using-a-plugin">"Using a plugin" section</a> of the Plugins overview page for more examples.
 Note that the value is <em>not a string</em>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello, version 7.0!&#39;</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello, version 7.0!&#39;</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="the-choices-parameter-for-keyboard-response-trials">The <code>choices</code> parameter for keyboard response trials<a class="headerlink" href="#the-choices-parameter-for-keyboard-response-trials" title="Permanent link">&para;</a></h2>
 <p>The <code>choices</code> parameter for keyboard response trials no longer supports <code>jsPsych.NO_KEYS</code> and <code>jsPsych.ALL_KEYS</code>, and they have been replaced by the strings <code>"NO_KEYS"</code> and <code>"ALL_KEYS"</code> respectively.</p>
 <p>For example, if you load the <code>audio-keyboard-response</code> plugin, you can prevent any user input like...</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;example.ogg&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_ends_after_audio</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychAudioKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;example.ogg&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_ends_after_audio</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="using-extensions">Using extensions<a class="headerlink" href="#using-extensions" title="Permanent link">&para;</a></h2>
 <p>Like plugins, extensions are now also referenced by their class. 
 Extensions are initiliazed in <code>initJsPsych()</code> instead of <code>jsPsych.init()</code>.
 Extension classes are named similarly to plugins, except that they start with <code>jsPsychExtension</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">})</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">})</span>
 </code></pre></div>
 <p>The class is also used in trials that use the extension.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello, version 7.0!&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span><span class="w"></span>
-<span class="w">  </span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello, version 7.0!&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">extensions</span><span class="o">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="p">{</span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychExtensionWebgazer</span><span class="p">}</span>
+<span class="w">  </span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <h2 id="custom-plugins">Custom plugins<a class="headerlink" href="#custom-plugins" title="Permanent link">&para;</a></h2>
 <p>If you have custom plugins that you would like to upgrade to be compatible with v7.x we recommend using our <a href="https://github.com/jspsych/jspsych-contrib/blob/main/packages/plugin-template/index.js">plugin template</a>.</p>
@@ -2099,31 +2104,40 @@ <h2 id="custom-plugins">Custom plugins<a class="headerlink" href="#custom-plugin
 <li>We removed the <code>registerPreload</code> function and we now auto-detect media to preload via the <code>type</code> argument specified in the <code>info</code> object. If a parameter is listed as <code>IMAGE</code>, <code>AUDIO</code>, or <code>VIDEO</code>, it will be automatically preloaded. If you wish to disable preloading you can set the <code>preload</code> flag to <code>false</code> for the parameter.</li>
 <li>If you invoke any functions from jsPsych, like <code>jsPsych.finishTrial()</code>, note that <code>jsPsych</code> is no longer a global variable and you must use the reference to jsPsych that is passed to the constructor. To do this, simply prefix all <code>jsPsych</code> references with <code>this.</code>, e.g., <code>jsPsych.finishTrial()</code> becomes <code>this.jsPsych.finishTrial()</code>. If your reference to a jsPsych function is inside of another function, then in order for the <code>this</code> keyword to appropriately reference the jsPsych instance, you must also use a JavaScript <a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Functions/Arrow_functions">arrow function expression</a> for the outer function. 
     For example, this:
-    <div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">end_trial</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="c1">// ...</span><span class="w"></span>
-<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+    <div class="highlight"><pre><span></span><code><span class="kd">function</span><span class="w"> </span><span class="nx">end_trial</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="c1">// ...</span>
+<span class="w">  </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div>
     Would be re-written as:
-    <div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">end_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="c1">// ...</span><span class="w"></span>
-<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+    <div class="highlight"><pre><span></span><code><span class="kd">const</span><span class="w"> </span><span class="nx">end_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">()</span><span class="w"> </span><span class="p">=&gt;</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="c1">// ...</span>
+<span class="w">  </span><span class="k">this</span><span class="p">.</span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">finishTrial</span><span class="p">(</span><span class="nx">data</span><span class="p">);</span>
+<span class="p">}</span>
 </code></pre></div></li>
 </ul>
 <h2 id="need-help">Need help?<a class="headerlink" href="#need-help" title="Permanent link">&para;</a></h2>
 <p>If you encounter issues migrating code to v7.x, feel free to post in our <a href="https://github.com/jspsych/jsPsych/discussions/2179">support thread for migration</a>.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../support/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Getting Help" rel="prev">
@@ -2182,7 +2196,7 @@ <h2 id="need-help">Need help?<a class="headerlink" href="#need-help" title="Perm
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2191,7 +2205,7 @@ <h2 id="need-help">Need help?<a class="headerlink" href="#need-help" title="Perm
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2204,11 +2218,13 @@ <h2 id="need-help">Need help?<a class="headerlink" href="#need-help" title="Perm
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/support/support/index.html b/7.3/support/support/index.html
old mode 100755
new mode 100644
index 7284762161..f6a2c8c835
--- a/7.3/support/support/index.html
+++ b/7.3/support/support/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/support/support/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1869,32 +1872,43 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/support/support.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="support">Support<a class="headerlink" href="#support" title="Permanent link">&para;</a></h1>
 <p>For questions about jsPsych, the preferred method of support is <a href="https://github.com/jspsych/jsPsych/discussions">GitHub Discussions</a>. Questions are most likely to be answered when they include a reproducible example of the problem. If you can make your code available online and link to the experiment, that will make the question easier to answer. Please consider searching through the archive of Q&amp;As before posting a new question.</p>
 <p>If you have identified a problem with jsPsych, such as a bug in the code or an error in the documentation, please <a href="https://github.com/jspsych/jsPsych/issues/new">open a new issue</a> on GitHub. </p>
 <p>If you have a suggestion for fixing the problem, feel free to <a href="../../developers/contributing/">contribute to the project</a>!</p>
 <p>Inquiries for paid consultation to develop experiments using jsPsych or to create new custom jsPsych features can be sent to <a href="mailto:josh.deleeuw@gmail.com">josh.deleeuw@gmail.com</a>.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../../developers/extension-development/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Extension Development" rel="prev">
@@ -1953,7 +1967,7 @@ <h1 id="support">Support<a class="headerlink" href="#support" title="Permanent l
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -1962,7 +1976,7 @@ <h1 id="support">Support<a class="headerlink" href="#support" title="Permanent l
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -1975,11 +1989,13 @@ <h1 id="support">Support<a class="headerlink" href="#support" title="Permanent l
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/tutorials/hello-world/index.html b/7.3/tutorials/hello-world/index.html
old mode 100755
new mode 100644
index 4c4c4a902b..3d75c98ad9
--- a/7.3/tutorials/hello-world/index.html
+++ b/7.3/tutorials/hello-world/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/tutorials/hello-world/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2245,16 +2248,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/tutorials/hello-world.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="jspsych-hello-world-experiment">jsPsych "Hello world" experiment<a class="headerlink" href="#jspsych-hello-world-experiment" title="Permanent link">&para;</a></h1>
 <p>In the long tradition of <strong>"Hello world!"</strong> examples, this tutorial creates an experiment that outputs the phrase "Hello world!" to the browser. Though useless as an actual experiment, the process is helpful for learning the basics of using the jsPsych library.</p>
 <h2 id="choose-your-own-setup-adventure">Choose your own (setup) adventure<a class="headerlink" href="#choose-your-own-setup-adventure" title="Permanent link">&para;</a></h2>
@@ -2294,7 +2299,7 @@ <h3 id="step-2-load-the-jspsych-library">Step 2: Load the jsPsych library<a clas
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-<span class="hll">    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="hll">    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </span>  <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2305,8 +2310,8 @@ <h3 id="step-2-load-the-jspsych-library">Step 2: Load the jsPsych library<a clas
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-<span class="hll">    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="hll">    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
 </span>  <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2317,11 +2322,11 @@ <h3 id="step-3-create-a-script-element-and-initialize-jspsych">Step 3: Create a
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-<span class="hll">  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
+<span class="hll">  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
 </span><span class="hll"><span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </span><span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2330,12 +2335,12 @@ <h3 id="step-3-create-a-script-element-and-initialize-jspsych">Step 3: Create a
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="hll"><span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="hll"><span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 </span><span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2345,13 +2350,13 @@ <h3 id="step-4-use-a-plugin-to-print-a-message">Step 4: Use a plugin to print a
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-<span class="hll">    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-</span>    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="hll">    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+</span>    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2360,18 +2365,18 @@ <h3 id="step-4-use-a-plugin-to-print-a-message">Step 4: Use a plugin to print a
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="hll"><span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">hello_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-</span><span class="hll"><span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-</span><span class="hll"><span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span><span class="w"></span>
-</span><span class="hll"><span class="w">    </span><span class="p">}</span><span class="w"></span>
+<span class="hll"><span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">hello_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+</span><span class="hll"><span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+</span><span class="hll"><span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span>
+</span><span class="hll"><span class="w">    </span><span class="p">}</span>
 </span><span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2381,20 +2386,20 @@ <h3 id="step-5-run-the-experiment">Step 5: Run the experiment<a class="headerlin
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">hello_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">hello_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span>
+<span class="w">    </span><span class="p">}</span>
 
-<span class="hll"><span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">hello_trial</span><span class="p">]);</span><span class="w"></span>
+<span class="hll"><span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">hello_trial</span><span class="p">]);</span>
 </span><span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2466,7 +2471,7 @@ <h3 id="step-5-create-a-script-element-and-initialize-jspsych">Step 5: Create a
     <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;jspsych/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-<span class="hll">  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
+<span class="hll">  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
 </span><span class="hll"><span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 </span><span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2479,8 +2484,8 @@ <h3 id="step-5-create-a-script-element-and-initialize-jspsych">Step 5: Create a
     <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;jspsych/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="hll"><span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="hll"><span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 </span><span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2495,8 +2500,8 @@ <h3 id="step-6-use-a-plugin-to-print-a-message">Step 6: Use a plugin to print a
 </span>    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;jspsych/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2510,13 +2515,13 @@ <h3 id="step-6-use-a-plugin-to-print-a-message">Step 6: Use a plugin to print a
     <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;jspsych/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="hll"><span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">hello_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-</span><span class="hll"><span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-</span><span class="hll"><span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span><span class="w"></span>
-</span><span class="hll"><span class="w">    </span><span class="p">}</span><span class="w"></span>
+<span class="hll"><span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">hello_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+</span><span class="hll"><span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+</span><span class="hll"><span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span>
+</span><span class="hll"><span class="w">    </span><span class="p">}</span>
 </span><span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2531,15 +2536,15 @@ <h3 id="step-7-run-the-experiment">Step 7: Run the experiment<a class="headerlin
     <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;jspsych/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">hello_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
+<span class="w">    </span><span class="kd">const</span><span class="w"> </span><span class="nx">hello_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span>
+<span class="w">    </span><span class="p">}</span>
 
-<span class="hll"><span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">hello_trial</span><span class="p">]);</span><span class="w"></span>
+<span class="hll"><span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">hello_trial</span><span class="p">]);</span>
 </span><span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
@@ -2560,9 +2565,9 @@ <h3 id="step-1-install-jspsych">Step 1: Install jspsych<a class="headerlink" hre
 <h3 id="step-2-import-the-initjspsych-function-and-create-a-new-jspsych-instance">Step 2: Import the <code>initJsPsych</code> function and create a new <code>JsPsych</code> instance<a class="headerlink" href="#step-2-import-the-initjspsych-function-and-create-a-new-jspsych-instance" title="Permanent link">&para;</a></h3>
 <p>We create a new instance of the <code>JsPsych</code> class by calling <code>initJsPsych</code>.
 The instance can optionally be configured via <a href="../../reference/jspsych/#initjspsych">a variety of options</a>, passed as an object to <code>initJsPsych</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="p">{</span><span class="nx">initJsPsych</span><span class="p">}</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;jspsych&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="p">{</span><span class="nx">initJsPsych</span><span class="p">}</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;jspsych&#39;</span><span class="p">;</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 </code></pre></div>
 <h3 id="step-3-static-markup-and-css">Step 3: Static markup and CSS<a class="headerlink" href="#step-3-static-markup-and-css" title="Permanent link">&para;</a></h3>
 <p>jsPsych requires nothing but a body element in your HTML document.
@@ -2571,10 +2576,10 @@ <h3 id="step-4-install-and-import-a-plugin">Step 4: Install and import a plugin<
 <p>Install the <code>html-keyboard-response</code> plugin with:</p>
 <p><code>npm install @jspsych/plugin-html-keyboard-response</code></p>
 <p>Then import the <code>htmlKeyboardResponse</code> plugin class.</p>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="p">{</span><span class="nx">initJsPsych</span><span class="p">}</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;jspsych&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="k">import</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-keyboard-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="p">{</span><span class="nx">initJsPsych</span><span class="p">}</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;jspsych&#39;</span><span class="p">;</span>
+<span class="k">import</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-keyboard-response&#39;</span><span class="p">;</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 </code></pre></div>
 <h3 id="step-5-create-a-trial">Step 5: Create a trial<a class="headerlink" href="#step-5-create-a-trial" title="Permanent link">&para;</a></h3>
 <p>Once the plugin is imported we can create a trial using the plugin.
@@ -2582,41 +2587,50 @@ <h3 id="step-5-create-a-trial">Step 5: Create a trial<a class="headerlink" href=
 We can specify the other parameters of the plugin in the same object.
 Here we use the <code>stimulus</code> parameter to include a message.
 You can see the full set of parameters for each plugin on its <a href="../../plugins/html-keyboard-response/">documentation page</a>.</p>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="p">{</span><span class="nx">initJsPsych</span><span class="p">}</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;jspsych&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="k">import</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-keyboard-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="p">{</span><span class="nx">initJsPsych</span><span class="p">}</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;jspsych&#39;</span><span class="p">;</span>
+<span class="k">import</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-keyboard-response&#39;</span><span class="p">;</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span><span class="p">,</span>
+<span class="p">}</span>
 </code></pre></div>
 <h3 id="step-6-run">Step 6: Run<a class="headerlink" href="#step-6-run" title="Permanent link">&para;</a></h3>
 <p>Now that we have the trial defined we need to tell jsPsych to run an experiment consisting of this trial. This requires using the <code>jsPsych.run</code> function and passing in a <a href="../overview/timeline">timeline</a>. For a simple experiment like this one, the timeline is just an array containing the list of trials to run.</p>
-<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="p">{</span><span class="nx">initJsPsych</span><span class="p">}</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;jspsych&#39;</span><span class="p">;</span><span class="w"></span>
-<span class="k">import</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-keyboard-response&#39;</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="k">import</span><span class="w"> </span><span class="p">{</span><span class="nx">initJsPsych</span><span class="p">}</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;jspsych&#39;</span><span class="p">;</span>
+<span class="k">import</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="w"> </span><span class="kr">from</span><span class="w"> </span><span class="s1">&#39;@jspsych/plugin-html-keyboard-response&#39;</span><span class="p">;</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<span class="kd">const</span><span class="w"> </span><span class="nx">trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">htmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;Hello world!&#39;</span><span class="p">,</span>
+<span class="p">}</span>
 
-<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">trial</span><span class="p">]);</span><span class="w"></span>
+<span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">([</span><span class="nx">trial</span><span class="p">]);</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../.." class="md-footer__link md-footer__link--prev" aria-label="Previous: Introduction" rel="prev">
@@ -2675,7 +2689,7 @@ <h3 id="step-6-run">Step 6: Run<a class="headerlink" href="#step-6-run" title="P
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2684,7 +2698,7 @@ <h3 id="step-6-run">Step 6: Run<a class="headerlink" href="#step-6-run" title="P
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2697,11 +2711,13 @@ <h3 id="step-6-run">Step 6: Run<a class="headerlink" href="#step-6-run" title="P
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/tutorials/rt-task/index.html b/7.3/tutorials/rt-task/index.html
old mode 100755
new mode 100644
index 0022a90276..ab9bddba1f
--- a/7.3/tutorials/rt-task/index.html
+++ b/7.3/tutorials/rt-task/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/tutorials/rt-task/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -2083,16 +2086,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/tutorials/rt-task.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="summary-of-tutorial-content">Summary of Tutorial Content<a class="headerlink" href="#summary-of-tutorial-content" title="Permanent link">&para;</a></h1>
 <p>This tutorial will work through the creation of a simple response time task. 
 The task is to press one key for a blue colored circle and another key for an orange colored circle. 
@@ -2117,41 +2122,41 @@ <h2 id="part-1-creating-a-blank-experiment">Part 1: Creating a blank experiment<
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>This will be our starting point for building the rest of the experiment.</p>
 <h2 id="part-2-display-welcome-message">Part 2: Display welcome message<a class="headerlink" href="#part-2-display-welcome-message" title="Permanent link">&para;</a></h2>
 <p>First we have to initialize jsPsych. We can do this using the <a href="../../reference/jspsych/#initjspsych"><code>initJsPsych()</code> function</a>, and saving the result to a variable called <code>jsPsych</code>.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 </code></pre></div>
 <p>All jsPsych experiments are defined by a timeline. 
 The timeline is an array that contains the set of trials we want to run in the experiment. 
 We can start by defining an empty timeline array. 
 We'll add trials to this array as we create them.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
 </code></pre></div>
 <p>Let's greet the participant with a simple welcome message using the <a href="../../plugins/html-keyboard-response/">html-keyboard-response</a> plugin.</p>
 <p>First, we create a trial that uses the <code>html-keyboard-response</code> plugin and contains a simple string to show the participant. 
 As explained on the <a href="../../overview/plugins/">plugins documentation page</a>, the trial object must have a <code>type</code> parameter that tells jsPsych which plugin to use. 
 The value of <code>type</code> is similar to the plugin name, but starts with <code>jsPsych</code> and is written in camel case rather than with dashes. 
 So to use the <code>html-keyboard-response</code> plugin, we need to write <code>jsPsychHtmlKeyboardResponse</code> as the trial type.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>Next, we push the welcome trial to the timeline, which adds it to the end of the array.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
 </code></pre></div>
 <p>Finally, we tell jsPsych to run the experiment by calling the <a href="../../reference/jspsych/#jspsychrun">jsPsych.run() function</a> and passing in the array that defines the experiment timeline.</p>
-<p><div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<p><div class="highlight"><pre><span></span><code><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 </code></pre></div>
 After each step in the tutorial you can view the complete code up to that point by clicking on the expandable box below.</p>
 <details class="example">
@@ -2160,28 +2165,28 @@ <h2 id="part-2-display-welcome-message">Part 2: Display welcome message<a class=
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
 
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
 
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
 
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2191,8 +2196,8 @@ <h2 id="part-3-show-instructions">Part 3: Show instructions<a class="headerlink"
 <p>We can use the same basic structure from part 2 to create a new <code>html-keyboard-response</code> trial that shows instructions to the participant. 
 The only difference in this trial is that we will use HTML formatting to control how the instructions display and we will add a two second gap after the trial using the <code>post_trial_gap</code> parameter.</p>
 <p>The trial definition looks like this:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">    &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">    of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -2206,9 +2211,9 @@ <h2 id="part-3-show-instructions">Part 3: Show instructions<a class="headerlink"
 <span class="sb">    &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">    &lt;/div&gt;</span>
 <span class="sb">    &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">  `</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<span class="sb">  `</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="p">};</span>
 </code></pre></div>
 <div class="admonition tip">
 <p class="admonition-title">Tip</p>
@@ -2221,7 +2226,7 @@ <h2 id="part-3-show-instructions">Part 3: Show instructions<a class="headerlink"
 <p><img alt="blue circle" src="../../img/blue.png" />
 <img alt="orange circle" src="../../img/orange.png" /></p>
 <p>Don't forget to add the trial to the timeline:</p>
-<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
 </code></pre></div>
 <details class="example">
 <summary>The complete code so far</summary>
@@ -2229,29 +2234,29 @@ <h2 id="part-3-show-instructions">Part 3: Show instructions<a class="headerlink"
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
 
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
 
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
 
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -2265,13 +2270,13 @@ <h2 id="part-3-show-instructions">Part 3: Show instructions<a class="headerlink"
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
 
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2283,29 +2288,29 @@ <h2 id="part-4-displaying-stimuli-and-getting-responses">Part 4: Displaying stim
 We need to start by loading this plugin by adding a <code>&lt;script&gt;</code> tag to the document.</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-<span class="hll">  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-</span>  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="hll">  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+</span>  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>For now, we will just show each image once. 
 The path to the image file should be set as the <code>stimulus</code> parameter. 
 We will also set the option for which keys the participant is allowed to use to respond (<code>choices</code>) so that only the 'f' and 'j' keys are valid responses.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">blue_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-
-<span class="kd">var</span><span class="w"> </span><span class="nx">orange_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">blue_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="p">};</span>
+
+<span class="kd">var</span><span class="w"> </span><span class="nx">orange_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>As usual, we need to add the trials to the timeline.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">blue_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">orange_trial</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">blue_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">orange_trial</span><span class="p">);</span>
 </code></pre></div>
 <details class="example">
 <summary>The complete code so far</summary>
@@ -2313,30 +2318,30 @@ <h2 id="part-4-displaying-stimuli-and-getting-responses">Part 4: Displaying stim
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
 
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
 
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
 
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
 
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -2350,28 +2355,28 @@ <h2 id="part-4-displaying-stimuli-and-getting-responses">Part 4: Displaying stim
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
 
-<span class="w">    </span><span class="cm">/* define test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">blue_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* define test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">blue_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
 
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">orange_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">orange_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
 
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">blue_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">orange_trial</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">blue_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">orange_trial</span><span class="p">);</span>
 
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2386,21 +2391,21 @@ <h2 id="part-5-preloading-media">Part 5: Preloading media<a class="headerlink" h
 <p>First we need to add the preload plugin to our <code>&lt;head&gt;</code> section.</p>
 <div class="highlight"><pre><span></span><code><span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-<span class="hll">  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-</span>  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+<span class="hll">  <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+</span>  <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
 <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
 </code></pre></div>
 <p>We'll put this trial at the very start of the experiment, so add this code before the <code>welcome</code> trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>As always, add the trial to the timeline.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
 </code></pre></div>
 <details class="example">
 <summary>The complete code so far</summary>
@@ -2408,38 +2413,38 @@ <h2 id="part-5-preloading-media">Part 5: Preloading media<a class="headerlink" h
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* preload images */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
+
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="w">    </span><span class="cm">/* preload images */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -2453,27 +2458,27 @@ <h2 id="part-5-preloading-media">Part 5: Preloading media<a class="headerlink" h
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">blue_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">orange_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">blue_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">orange_trial</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">blue_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">orange_trial</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">blue_trial</span><span class="p">,</span><span class="w"> </span><span class="nx">orange_trial</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2485,34 +2490,34 @@ <h2 id="part-6-timeline-variables">Part 6: Timeline variables<a class="headerlin
 <p>The parameters for showing the blue and orange circle are very similar. 
 The only difference is which image is displayed. Timeline variables allow us to define the procedure for showing the stimulus once, and then repeatedly use it with different variables. We'll see how, even in this relatively simple case, this can save us a lot of lines of code.</p>
 <p>To start, let's make an array that contains all the different trials we want to run in the test phase. There are only two for the experiment: blue trials and orange trials.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span><span class="w"></span>
-<span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span>
+<span class="w">  </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span>
+<span class="p">];</span>
 </code></pre></div>
 <p>Instead of just showing the blue and orange circles, let's also set up the experiment to show a fixation cross (+) in between trials. We can define a trial to show the fixation cross for a fixed amount of time by using the <code>trial_duration</code> parameter of the html-keyboard-response plugin and setting the <code>choices</code> parameter to the special value <code>"NO_KEYS"</code>, which means that no responses will be accepted as a valid response and the trial will last however long the <code>trial_duration</code> parameter specifies.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>To show the circles, we'll set up another trial with the image-keyboard-response plugin, but we'll use the function <code>jsPsych.timelineVariable()</code> to indicate that we want jsPsych to substitute the value of the parameter in from the timeline variables.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>To link the variables that we declared in the <code>test_stimuli</code> array with the call to <code>jsPsych.timelineVariable()</code> we need to create a new timeline and set the <code>timeline_variables</code> property:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>We have to add the <code>test_procedure</code> to the main <code>timeline</code> array, but the <code>fixation</code> and <code>test</code> trial do not need to be added to <code>timeline</code> because they already exist on the <code>test_procedure</code> timeline.</p>
-<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span>
 </code></pre></div>
 <p>What happens when the experiment reaches the test procedure? jsPsych will run the <code>test_procedure</code> timeline one time for each entry in the <code>test_stimuli</code> array (two times total, in this case). The first time through, jsPsych will substitute the timeline variables from the first array entry (blue image), and the second time through the second array entry will be used (orange image). Notice that the fixation trial occurs before both the orange and the blue circles, because the entire timeline of the <code>test_procedure</code> is repeated for each entry in the <code>timeline_variables</code> array.</p>
 <details class="example">
@@ -2521,38 +2526,38 @@ <h2 id="part-6-timeline-variables">Part 6: Timeline variables<a class="headerlin
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* preload images */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
+
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="w">    </span><span class="cm">/* preload images */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -2566,40 +2571,40 @@ <h2 id="part-6-timeline-variables">Part 6: Timeline variables<a class="headerlin
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define fixation and test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define test procedure */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">];</span>
+
+<span class="w">    </span><span class="cm">/* define fixation and test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="cm">/* define test procedure */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2607,19 +2612,19 @@ <h2 id="part-6-timeline-variables">Part 6: Timeline variables<a class="headerlin
 </details>
 <h2 id="part-7-parameters-for-timelines-with-timeline-variables">Part 7: Parameters for timelines with timeline variables<a class="headerlink" href="#part-7-parameters-for-timelines-with-timeline-variables" title="Permanent link">&para;</a></h2>
 <p>Right now our experiment is a measly two trials long. Even worse is that the order of the stimuli is the same every time! When we use timeline variables, we get access to some methods to randomize the order and repeat the trials. To randomize the order, simply set <code>randomize_order: true</code> on the object with the <code>timeline_variables</code>:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>We can also easily make the test phase longer by setting the <code>repetitions</code> parameter. This parameter controls how many times the experiment will loop through all of the entries in the timeline_variables array. For example, if we set <code>repetitions: 5</code>, then the experiment will loop through the two entries in the timeline_variables 5 times, for a total of 10 test trials.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span>
+<span class="p">};</span>
 </code></pre></div>
 <details class="info">
 <summary>Info: Randomizing timeline variables</summary>
@@ -2633,38 +2638,38 @@ <h2 id="part-7-parameters-for-timelines-with-timeline-variables">Part 7: Paramet
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* preload images */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
+
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="w">    </span><span class="cm">/* preload images */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -2678,42 +2683,42 @@ <h2 id="part-7-parameters-for-timelines-with-timeline-variables">Part 7: Paramet
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define fixation and test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define test procedure */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">];</span>
+
+<span class="w">    </span><span class="cm">/* define fixation and test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="cm">/* define test procedure */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2722,14 +2727,14 @@ <h2 id="part-7-parameters-for-timelines-with-timeline-variables">Part 7: Paramet
 <h2 id="part-8-using-functions-to-generate-parameters">Part 8: Using functions to generate parameters<a class="headerlink" href="#part-8-using-functions-to-generate-parameters" title="Permanent link">&para;</a></h2>
 <p>One aspect of the experiment that could be improved is the duration of the fixation cross. As the experiment stands right now, the timing of the circles appearing is very predictable. We can change that by using a different value for the <code>trial_duration</code> parameter in the <code>fixation</code> trial for each trial. But how can we do that and keep the simple code structure we have now where we only have to define the fixation trial once? One option would be to add another timeline variable, like <code>"fixation_duration"</code> and use that to control the timing. But another option is to specify the <code>trial_duration</code> parameter as a function. If a parameter is a function, jsPsych will execute the function every time the trial runs. That means that if the function returns different results probabilistically, we can get a different parameter value every time the trial runs.</p>
 <p>To do that here, we'll use one of the built-in randomization methods in <a href="../../reference/jspsych-randomization/">jsPsych's randomization module</a>. <code>jsPsych.randomization.sampleWithoutReplacement()</code> takes an array of items to sample from and generates a new array of length <em>N</em> by sampling without replacement.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">}</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">}</span>
 </code></pre></div>
 <p>In the code above, we replaced the <code>trial_duration: 1000</code> parameter in <code>fixation</code> with a function. Inside the function, we take a sample from the array <code>[250, 500, 750, 1000, 1250, 1500, 1750, 2000]</code> of size 1 (second parameter to <code>jsPsych.randomization.sampleWithoutReplacement</code>). The return value from calling <code>jsPsych.randomization.sampleWithoutReplacement</code> is an array of length 1, so we add the <code>[0]</code> selection at the end to get the value out of the array.</p>
 <details class="example">
@@ -2738,38 +2743,38 @@ <h2 id="part-8-using-functions-to-generate-parameters">Part 8: Using functions t
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* preload images */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">();</span>
+
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="w">    </span><span class="cm">/* preload images */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">}</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -2783,44 +2788,44 @@ <h2 id="part-8-using-functions-to-generate-parameters">Part 8: Using functions t
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define fixation and test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define test procedure */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">];</span>
+
+<span class="w">    </span><span class="cm">/* define fixation and test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="cm">/* define test procedure */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2829,11 +2834,11 @@ <h2 id="part-8-using-functions-to-generate-parameters">Part 8: Using functions t
 <h2 id="part-10-displaying-the-data">Part 10: Displaying the data<a class="headerlink" href="#part-10-displaying-the-data" title="Permanent link">&para;</a></h2>
 <p>We have created a complete, if simple, experiment at this point, so let's take a look at the data being generated. jsPsych has a built-in <a href="../../reference/jspsych-data/#jspsychdatadisplaydata">function called <code>jsPsych.data.displayData()</code></a> that is useful for debugging your experiment. It will remove all of the information on the screen and replace it with the raw data collected so far. This isn't terribly useful when you are actually running an experiment, but it's nice for checking the data during development.</p>
 <p>We need the <code>displayData</code> function to execute when the experiment ends. One way to do this is to use the <a href="../../overview/events/#on_finish-experiment"><code>on_finish</code> callback function</a>. This function will automatically execute once all the trials in the experiment are finished. We can specify this function in the experiment settings when we initialize jsPsych with the <code>initJsPsych</code> method.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">});</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">});</span>
 </code></pre></div>
 <details class="example">
 <summary>The complete code so far</summary>
@@ -2841,42 +2846,42 @@ <h2 id="part-10-displaying-the-data">Part 10: Displaying the data<a class="heade
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">});</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* preload images */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">});</span>
+
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="w">    </span><span class="cm">/* preload images */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -2890,44 +2895,44 @@ <h2 id="part-10-displaying-the-data">Part 10: Displaying the data<a class="heade
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define fixation and test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define test procedure */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">];</span>
+
+<span class="w">    </span><span class="cm">/* define fixation and test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="cm">/* define test procedure */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -2936,45 +2941,45 @@ <h2 id="part-10-displaying-the-data">Part 10: Displaying the data<a class="heade
 <h2 id="part-11-tagging-trials-with-additional-data">Part 11: Tagging trials with additional data<a class="headerlink" href="#part-11-tagging-trials-with-additional-data" title="Permanent link">&para;</a></h2>
 <p>All trials in jsPsych can be tagged with additional arbitrary data. This data will get stored alongside the data that the plugin normally generates, which allows experimenters to record properties of a trial along with the data from the trial.</p>
 <p>When might you use this feature? In this experiment, it would be nice to tag each trial with a circle as a <code>response</code> trial, so that the resulting data can be easily filtered to look at only the critical trials. We can do that like this.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>We also could tag the test trials with a property that indicates what the correct response should be (F for the blue circles, J for the orange). In our current code, we are using the timeline variables feature of jsPsych to choose which circle gets presented on a trial. Since we want to tag the trials differently based on which circle is presented, we need to add the tagging data to the <code>test_stimuli</code> array, and then use the <code>jsPsych.timelineVariable()</code> function to get the value and assign it to a property in the <code>data</code> of the trial.</p>
 <p>We start by adding a "correct_response" property and value to each object in the <code>test_stimuli</code>:</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="p">];</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">  </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">},</span>
+<span class="w">  </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">}</span>
+<span class="p">];</span>
 </code></pre></div>
 <p>Now we can use <code>timelineVariable()</code> in the <code>data</code> parameter of the <code>test</code> trial to get the appropriate "correct_response" value for each trial.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>Another kind of tagging that would be useful is to mark each fixation trial as such, to make removing the data from fixation trials easier. </p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixation&#39;</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixation&#39;</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <details class="example">
 <summary>The complete code so far</summary>
@@ -2982,42 +2987,42 @@ <h2 id="part-11-tagging-trials-with-additional-data">Part 11: Tagging trials wit
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">});</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* preload images */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">});</span>
+
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="w">    </span><span class="cm">/* preload images */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -3031,51 +3036,51 @@ <h2 id="part-11-tagging-trials-with-additional-data">Part 11: Tagging trials wit
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define fixation and test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">      </span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixation&#39;</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define test procedure */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">];</span>
+
+<span class="w">    </span><span class="cm">/* define fixation and test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">      </span><span class="p">},</span>
+<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixation&#39;</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="cm">/* define test procedure */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
   <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -3086,25 +3091,25 @@ <h2 id="part-12-manipulating-data-during-the-experiment">Part 12: Manipulating d
 <p>But, we can also do this in jsPsych as the experiment runs to save time later and enable a limited set of data analysis directly in the experiment code.</p>
 <p>To do this, we'll use the <code>on_finish</code> event of the test trial. We can assign a function to <code>on_finish</code>, and that function will receive an object containing the data generated by the trial. This object can be manipulated inside the function, and any changes made to the object will be stored in jsPsych's internal representation of the data.</p>
 <p>For this example, we'll determine whether the participant responded correctly, and add a new <code>correct</code> property to the data object.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">    </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">  </span><span class="p">},</span><span class="w"></span>
-<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">    </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">);</span><span class="w"></span>
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">  </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">  </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">    </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span>
+<span class="w">    </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span>
+<span class="w">  </span><span class="p">},</span>
+<span class="w">  </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">    </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">);</span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
 </code></pre></div>
 <p>The <code>data.response</code> value is a string representation of the key the participant pressed. We can compare this with the <code>data.correct_response</code> value, and assign this computed value to a new property <code>data.correct</code>.</p>
 <details class="info">
 <summary>Info: The <code>compareKeys</code> function</summary>
 <p>Here we are comparing the values of <code>data.response</code> and <code>data.correct_response</code> using a jsPsych function called <a href="../../reference/jspsych-pluginAPI/#comparekeys">jsPsych.pluginAPI.compareKeys</a>. We're using this function because it allows us to compare keys in either a <em>case sensitive</em> or <em>case insensitive</em> way, depending on the <code>case_sensitive_responses</code> parameter in the <a href="../../overview/experiment-options/#choose-whether-you-want-keyboard-choicesresponses-to-be-case-sensitive">experiment settings</a>. The participant's key response will be recorded in a case-sensitive way in the data (e.g. 'f' or 'F'), but in most cases, we don't care if their response corresponds to an upper or lower case letter (which is why the <code>case_sensitive_responses</code> experiment setting is <code>false</code> by default). Using the <code>jsPsych.pluginAPI.commpareKeys</code> function here means that the response will be scored correctly, even if the participant holds down Shift or has Caps Lock on. </p>
 <p>This function is only relevant for keyboard responses; for other kinds of responses, such as button presses, you can simply compare the response and correct response values directly, e.g.
-<div class="highlight"><pre><span></span><code><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">;</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="w"> </span><span class="o">===</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">;</span>
 </code></pre></div></p>
 </details>
 <details class="example">
@@ -3113,42 +3118,42 @@ <h2 id="part-12-manipulating-data-during-the-experiment">Part 12: Manipulating d
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">});</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* preload images */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">});</span>
+
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="w">    </span><span class="cm">/* preload images */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -3162,54 +3167,54 @@ <h2 id="part-12-manipulating-data-during-the-experiment">Part 12: Manipulating d
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define fixation and test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">      </span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixation&#39;</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">      </span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">);</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define test procedure */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">];</span>
+
+<span class="w">    </span><span class="cm">/* define fixation and test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">      </span><span class="p">},</span>
+<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixation&#39;</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span>
+<span class="w">      </span><span class="p">},</span>
+<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">        </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">);</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="cm">/* define test procedure */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
@@ -3223,22 +3228,22 @@ <h2 id="part-13-data-aggregation">Part 13: Data aggregation<a class="headerlink"
 <p>Using a function as the value of a 'normal' parameter (i.e. a parameter that isn't usually a function) provides lots of flexibility in jsPsych experiments, because it allows you to dynamically change the parameter's value based on the participant's earlier responses, and any other information that you don't know before the experiment has started. For more information and examples, see the <a href="../../overview/dynamic-parameters/">dynamic parameter documentation page</a>.</p>
 </details>
 <p>Here's what the code looks like, and a description follows below.</p>
-<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">debrief_block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
+<div class="highlight"><pre><span></span><code><span class="kd">var</span><span class="w"> </span><span class="nx">debrief_block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">  </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">  </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
 
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">});</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">correct_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">trials</span><span class="p">.</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">accuracy</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">round</span><span class="p">(</span><span class="nx">correct_trials</span><span class="p">.</span><span class="nx">count</span><span class="p">()</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">trials</span><span class="p">.</span><span class="nx">count</span><span class="p">()</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">);</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">rt</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">round</span><span class="p">(</span><span class="nx">correct_trials</span><span class="p">.</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">mean</span><span class="p">());</span><span class="w"></span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">});</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">correct_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">trials</span><span class="p">.</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">accuracy</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">round</span><span class="p">(</span><span class="nx">correct_trials</span><span class="p">.</span><span class="nx">count</span><span class="p">()</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">trials</span><span class="p">.</span><span class="nx">count</span><span class="p">()</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">);</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">rt</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">round</span><span class="p">(</span><span class="nx">correct_trials</span><span class="p">.</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">mean</span><span class="p">());</span>
 
 <span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="sb">`&lt;p&gt;You responded correctly on </span><span class="si">${</span><span class="nx">accuracy</span><span class="si">}</span><span class="sb">% of the trials.&lt;/p&gt;</span>
 <span class="sb">      &lt;p&gt;Your average response time was </span><span class="si">${</span><span class="nx">rt</span><span class="si">}</span><span class="sb">ms.&lt;/p&gt;</span>
-<span class="sb">      &lt;p&gt;Press any key to complete the experiment. Thank you!&lt;/p&gt;`</span><span class="p">;</span><span class="w"></span>
+<span class="sb">      &lt;p&gt;Press any key to complete the experiment. Thank you!&lt;/p&gt;`</span><span class="p">;</span>
 
-<span class="w">  </span><span class="p">}</span><span class="w"></span>
-<span class="p">};</span><span class="w"></span>
-<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">debrief_block</span><span class="p">);</span><span class="w"></span>
+<span class="w">  </span><span class="p">}</span>
+<span class="p">};</span>
+<span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">debrief_block</span><span class="p">);</span>
 </code></pre></div>
 <p>To create the variable <code>trials</code>, we use <code>jsPsych.data.get()</code> which returns a jsPsych data collection containing all of the data from the experiment. We can then use <code>.filter</code> to select only the trials where <code>task</code> is <code>'response'</code> (a benefit of tagging the trials in part 11). <code>trials</code> contains all of the data from the trials where a circle was shown.</p>
 <p>To get only the correct trials, we can use <code>.filter()</code> again to select only the trials from the <code>trials</code> data collection where the property <code>correct</code> is <code>true</code>.</p>
@@ -3250,42 +3255,42 @@ <h2 id="the-final-code">The final code<a class="headerlink" href="#the-final-cod
 <span class="p">&lt;</span><span class="nt">html</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">head</span><span class="p">&gt;</span>
     <span class="p">&lt;</span><span class="nt">title</span><span class="p">&gt;</span>My experiment<span class="p">&lt;/</span><span class="nt">title</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.2&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
-    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.3/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-html-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-image-keyboard-response@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">script</span> <span class="na">src</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/@jspsych/plugin-preload@1.1.3&quot;</span><span class="p">&gt;&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
+    <span class="p">&lt;</span><span class="nt">link</span> <span class="na">href</span><span class="o">=</span><span class="s">&quot;https://unpkg.com/jspsych@7.3.4/css/jspsych.css&quot;</span> <span class="na">rel</span><span class="o">=</span><span class="s">&quot;stylesheet&quot;</span> <span class="na">type</span><span class="o">=</span><span class="s">&quot;text/css&quot;</span> <span class="p">/&gt;</span>
   <span class="p">&lt;/</span><span class="nt">head</span><span class="p">&gt;</span>
   <span class="p">&lt;</span><span class="nt">body</span><span class="p">&gt;&lt;/</span><span class="nt">body</span><span class="p">&gt;</span>
-  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* initialize jsPsych */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span><span class="w"></span>
-<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">});</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* create timeline */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* preload images */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define welcome message trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define instructions trial */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
+  <span class="p">&lt;</span><span class="nt">script</span><span class="p">&gt;</span>
+
+<span class="w">    </span><span class="cm">/* initialize jsPsych */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">jsPsych</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">initJsPsych</span><span class="p">({</span>
+<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">displayData</span><span class="p">();</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">});</span>
+
+<span class="w">    </span><span class="cm">/* create timeline */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">timeline</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[];</span>
+
+<span class="w">    </span><span class="cm">/* preload images */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">preload</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychPreload</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">images</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;img/blue.png&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;img/orange.png&#39;</span><span class="p">]</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">preload</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define welcome message trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">welcome</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;Welcome to the experiment. Press any key to begin.&quot;</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">welcome</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define instructions trial */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">instructions</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
 <span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="sb">`</span>
 <span class="sb">        &lt;p&gt;In this experiment, a circle will appear in the center </span>
 <span class="sb">        of the screen.&lt;/p&gt;&lt;p&gt;If the circle is &lt;strong&gt;blue&lt;/strong&gt;, </span>
@@ -3299,87 +3304,96 @@ <h2 id="the-final-code">The final code<a class="headerlink" href="#the-final-cod
 <span class="sb">        &lt;p class=&#39;small&#39;&gt;&lt;strong&gt;Press the J key&lt;/strong&gt;&lt;/p&gt;&lt;/div&gt;</span>
 <span class="sb">        &lt;/div&gt;</span>
 <span class="sb">        &lt;p&gt;Press any key to begin.&lt;/p&gt;</span>
-<span class="sb">      `</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">];</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define fixation and test trials */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span><span class="w"></span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span><span class="w"></span>
-<span class="w">      </span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixation&#39;</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span><span class="w"></span>
-<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span><span class="w"></span>
-<span class="w">        </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span><span class="w"></span>
-<span class="w">      </span><span class="p">},</span><span class="w"></span>
-<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span><span class="w"></span>
-<span class="w">        </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">);</span><span class="w"></span>
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define test procedure */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span><span class="w"></span>
-<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span><span class="w"></span>
-
-<span class="w">    </span><span class="cm">/* define debrief */</span><span class="w"></span>
-<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">debrief_block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span><span class="w"></span>
-<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span><span class="w"></span>
-
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">});</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">correct_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">trials</span><span class="p">.</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">accuracy</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">round</span><span class="p">(</span><span class="nx">correct_trials</span><span class="p">.</span><span class="nx">count</span><span class="p">()</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">trials</span><span class="p">.</span><span class="nx">count</span><span class="p">()</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">);</span><span class="w"></span>
-<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">rt</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">round</span><span class="p">(</span><span class="nx">correct_trials</span><span class="p">.</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">mean</span><span class="p">());</span><span class="w"></span>
+<span class="sb">      `</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">post_trial_gap</span><span class="o">:</span><span class="w"> </span><span class="mf">2000</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">instructions</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define trial stimuli array for timeline variables */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">[</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/blue.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;f&#39;</span><span class="p">},</span>
+<span class="w">      </span><span class="p">{</span><span class="w"> </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;img/orange.png&quot;</span><span class="p">,</span><span class="w">  </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">}</span>
+<span class="w">    </span><span class="p">];</span>
+
+<span class="w">    </span><span class="cm">/* define fixation and test trials */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">fixation</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;&lt;div style=&quot;font-size:60px;&quot;&gt;+&lt;/div&gt;&#39;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="s2">&quot;NO_KEYS&quot;</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">trial_duration</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(){</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">randomization</span><span class="p">.</span><span class="nx">sampleWithoutReplacement</span><span class="p">([</span><span class="mf">250</span><span class="p">,</span><span class="w"> </span><span class="mf">500</span><span class="p">,</span><span class="w"> </span><span class="mf">750</span><span class="p">,</span><span class="w"> </span><span class="mf">1000</span><span class="p">,</span><span class="w"> </span><span class="mf">1250</span><span class="p">,</span><span class="w"> </span><span class="mf">1500</span><span class="p">,</span><span class="w"> </span><span class="mf">1750</span><span class="p">,</span><span class="w"> </span><span class="mf">2000</span><span class="p">],</span><span class="w"> </span><span class="mf">1</span><span class="p">)[</span><span class="mf">0</span><span class="p">];</span>
+<span class="w">      </span><span class="p">},</span>
+<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;fixation&#39;</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychImageKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;stimulus&#39;</span><span class="p">),</span>
+<span class="w">      </span><span class="nx">choices</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="s1">&#39;f&#39;</span><span class="p">,</span><span class="w"> </span><span class="s1">&#39;j&#39;</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">data</span><span class="o">:</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">,</span>
+<span class="w">        </span><span class="nx">correct_response</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">timelineVariable</span><span class="p">(</span><span class="s1">&#39;correct_response&#39;</span><span class="p">)</span>
+<span class="w">      </span><span class="p">},</span>
+<span class="w">      </span><span class="nx">on_finish</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">(</span><span class="nx">data</span><span class="p">){</span>
+<span class="w">        </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">pluginAPI</span><span class="p">.</span><span class="nx">compareKeys</span><span class="p">(</span><span class="nx">data</span><span class="p">.</span><span class="nx">response</span><span class="p">,</span><span class="w"> </span><span class="nx">data</span><span class="p">.</span><span class="nx">correct_response</span><span class="p">);</span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+
+<span class="w">    </span><span class="cm">/* define test procedure */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">test_procedure</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">timeline</span><span class="o">:</span><span class="w"> </span><span class="p">[</span><span class="nx">fixation</span><span class="p">,</span><span class="w"> </span><span class="nx">test</span><span class="p">],</span>
+<span class="w">      </span><span class="nx">timeline_variables</span><span class="o">:</span><span class="w"> </span><span class="nx">test_stimuli</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">repetitions</span><span class="o">:</span><span class="w"> </span><span class="mf">5</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">randomize_order</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">test_procedure</span><span class="p">);</span>
+
+<span class="w">    </span><span class="cm">/* define debrief */</span>
+<span class="w">    </span><span class="kd">var</span><span class="w"> </span><span class="nx">debrief_block</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
+<span class="w">      </span><span class="nx">type</span><span class="o">:</span><span class="w"> </span><span class="nx">jsPsychHtmlKeyboardResponse</span><span class="p">,</span>
+<span class="w">      </span><span class="nx">stimulus</span><span class="o">:</span><span class="w"> </span><span class="kd">function</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
+
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">data</span><span class="p">.</span><span class="nx">get</span><span class="p">().</span><span class="nx">filter</span><span class="p">({</span><span class="nx">task</span><span class="o">:</span><span class="w"> </span><span class="s1">&#39;response&#39;</span><span class="p">});</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">correct_trials</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nx">trials</span><span class="p">.</span><span class="nx">filter</span><span class="p">({</span><span class="nx">correct</span><span class="o">:</span><span class="w"> </span><span class="kc">true</span><span class="p">});</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">accuracy</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">round</span><span class="p">(</span><span class="nx">correct_trials</span><span class="p">.</span><span class="nx">count</span><span class="p">()</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nx">trials</span><span class="p">.</span><span class="nx">count</span><span class="p">()</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mf">100</span><span class="p">);</span>
+<span class="w">        </span><span class="kd">var</span><span class="w"> </span><span class="nx">rt</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nb">Math</span><span class="p">.</span><span class="nx">round</span><span class="p">(</span><span class="nx">correct_trials</span><span class="p">.</span><span class="nx">select</span><span class="p">(</span><span class="s1">&#39;rt&#39;</span><span class="p">).</span><span class="nx">mean</span><span class="p">());</span>
 
 <span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="sb">`&lt;p&gt;You responded correctly on </span><span class="si">${</span><span class="nx">accuracy</span><span class="si">}</span><span class="sb">% of the trials.&lt;/p&gt;</span>
 <span class="sb">          &lt;p&gt;Your average response time was </span><span class="si">${</span><span class="nx">rt</span><span class="si">}</span><span class="sb">ms.&lt;/p&gt;</span>
-<span class="sb">          &lt;p&gt;Press any key to complete the experiment. Thank you!&lt;/p&gt;`</span><span class="p">;</span><span class="w"></span>
+<span class="sb">          &lt;p&gt;Press any key to complete the experiment. Thank you!&lt;/p&gt;`</span><span class="p">;</span>
 
-<span class="w">      </span><span class="p">}</span><span class="w"></span>
-<span class="w">    </span><span class="p">};</span><span class="w"></span>
-<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">debrief_block</span><span class="p">);</span><span class="w"></span>
+<span class="w">      </span><span class="p">}</span>
+<span class="w">    </span><span class="p">};</span>
+<span class="w">    </span><span class="nx">timeline</span><span class="p">.</span><span class="nx">push</span><span class="p">(</span><span class="nx">debrief_block</span><span class="p">);</span>
 
-<span class="w">    </span><span class="cm">/* start the experiment */</span><span class="w"></span>
-<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span><span class="w"></span>
+<span class="w">    </span><span class="cm">/* start the experiment */</span>
+<span class="w">    </span><span class="nx">jsPsych</span><span class="p">.</span><span class="nx">run</span><span class="p">(</span><span class="nx">timeline</span><span class="p">);</span>
 
 <span class="w">  </span><span class="p">&lt;/</span><span class="nt">script</span><span class="p">&gt;</span>
 <span class="p">&lt;/</span><span class="nt">html</span><span class="p">&gt;</span>
 </code></pre></div>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../hello-world/" class="md-footer__link md-footer__link--prev" aria-label="Previous: The Basics: Hello World" rel="prev">
@@ -3438,7 +3452,7 @@ <h2 id="the-final-code">The final code<a class="headerlink" href="#the-final-cod
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -3447,7 +3461,7 @@ <h2 id="the-final-code">The final code<a class="headerlink" href="#the-final-cod
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -3460,11 +3474,13 @@ <h2 id="the-final-code">The final code<a class="headerlink" href="#the-final-cod
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
diff --git a/7.3/tutorials/video-tutorials/index.html b/7.3/tutorials/video-tutorials/index.html
old mode 100755
new mode 100644
index c0519f006b..a1d1247675
--- a/7.3/tutorials/video-tutorials/index.html
+++ b/7.3/tutorials/video-tutorials/index.html
@@ -11,7 +11,7 @@
         <link rel="canonical" href="https://www.jspsych.org/7.3/tutorials/video-tutorials/">
       
       <link rel="icon" href="../../img/jspsych-favicon.png">
-      <meta name="generator" content="mkdocs-1.3.0, mkdocs-material-8.2.15">
+      <meta name="generator" content="mkdocs-1.5.2, mkdocs-material-8.5.10">
     
     
       
@@ -19,16 +19,18 @@
       
     
     
-      <link rel="stylesheet" href="../../assets/stylesheets/main.c382b1dc.min.css">
+      <link rel="stylesheet" href="../../assets/stylesheets/main.975780f9.min.css">
       
         
-        <link rel="stylesheet" href="../../assets/stylesheets/palette.cc9b2e1e.min.css">
+        <link rel="stylesheet" href="../../assets/stylesheets/palette.2505c338.min.css">
         
           
           
           <meta name="theme-color" content="#4cae4f">
         
       
+      
+
     
     
     
@@ -41,7 +43,7 @@
       
     
     
-    <script>__md_scope=new URL("../..",location),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
+    <script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
     
       
   
@@ -51,12 +53,15 @@
   
 
 
-  <script>window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),"undefined"!=typeof location$&&location$.subscribe(function(e){ga("send","pageview",e.pathname)})})</script>
-  <script async src="https://www.google-analytics.com/analytics.js"></script>
+  <script id="__analytics">function __md_analytics(){window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-50563838-1","auto"),ga("set","anonymizeIp",!0),ga("send","pageview"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){var e;this.value&&(e=document.location.pathname,ga("send","pageview",e+"?q="+this.value))}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");ga("send","event","feedback","click",t,e),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){ga("send","pageview",e.pathname)})});var e=document.createElement("script");e.async=!0,e.src="https://www.google-analytics.com/analytics.js",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script>
 
+  
+    <script>"undefined"!=typeof __md_analytics&&__md_analytics()</script>
+  
 
     
     
+    
   </head>
   
   
@@ -65,7 +70,7 @@
     
     
     
-    <body dir="ltr" data-md-color-scheme="" data-md-color-primary="green" data-md-color-accent="orange">
+    <body dir="ltr" data-md-color-scheme="default" data-md-color-primary="green" data-md-color-accent="orange">
   
     
     
@@ -85,9 +90,7 @@
     </div>
     
       <div data-md-component="outdated" hidden>
-        <aside class="md-banner md-banner--warning">
-          
-        </aside>
+        
       </div>
     
     
@@ -136,7 +139,7 @@
       </label>
       <nav class="md-search__options" aria-label="Search">
         
-        <button type="reset" class="md-search__icon md-icon" aria-label="Clear" tabindex="-1">
+        <button type="reset" class="md-search__icon md-icon" title="Clear" aria-label="Clear" tabindex="-1">
           <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
         </button>
       </nav>
@@ -160,7 +163,7 @@
         <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -204,7 +207,7 @@
       <a href="https://github.com/jspsych/jsPsych" title="Go to repository" class="md-source" data-md-component="source">
   <div class="md-source__icon md-icon">
     
-    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
+    <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M439.55 236.05 244 40.45a28.87 28.87 0 0 0-40.81 0l-40.66 40.63 51.52 51.52c27.06-9.14 52.68 16.77 43.39 43.68l49.66 49.66c34.23-11.8 61.18 31 35.47 56.69-26.49 26.49-70.21-2.87-56-37.34L240.22 199v121.85c25.3 12.54 22.26 41.85 9.08 55a34.34 34.34 0 0 1-48.55 0c-17.57-17.6-11.07-46.91 11.25-56v-123c-20.8-8.51-24.6-30.74-18.64-45L142.57 101 8.45 235.14a28.86 28.86 0 0 0 0 40.81l195.61 195.6a28.86 28.86 0 0 0 40.8 0l194.69-194.69a28.86 28.86 0 0 0 0-40.81z"/></svg>
   </div>
   <div class="md-source__repository">
     jspsych/jspsych
@@ -1929,16 +1932,18 @@
               </div>
             
           
-          <div class="md-content" data-md-component="content">
-            <article class="md-content__inner md-typeset">
-              
+          
+            <div class="md-content" data-md-component="content">
+              <article class="md-content__inner md-typeset">
                 
+                  
+
   <a href="https://github.com/jspsych/jsPsych/edit/main/docs/tutorials/video-tutorials.md" title="Edit this page" class="md-content__button md-icon">
+    
     <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20.71 7.04c.39-.39.39-1.04 0-1.41l-2.34-2.34c-.37-.39-1.02-.39-1.41 0l-1.84 1.83 3.75 3.75M3 17.25V21h3.75L17.81 9.93l-3.75-3.75L3 17.25Z"/></svg>
   </a>
 
 
-
 <h1 id="video-tutorials">Video tutorials<a class="headerlink" href="#video-tutorials" title="Permanent link">&para;</a></h1>
 <div class="admonition warning">
 <p class="admonition-title">Warning</p>
@@ -1950,16 +1955,25 @@ <h2 id="workshops">Workshops<a class="headerlink" href="#workshops" title="Perma
 <p><strong>Moving Research Online (2020)</strong>. Recordings from a <a href="https://www.movingresearchonline.info">Summer 2020 workshop</a> on conducting online research are available on the <a href="https://www.youtube.com/channel/UCBZ5F1UysHWlplUNDRwbsWA">workshop's YouTube channel</a>. <a href="https://www.youtube.com/watch?v=BuhfsIFRFe8">Session 1</a> provides an overview of jsPsych suitable for brand new users. <a href="https://www.youtube.com/watch?v=LP7o0iAALik">Session 3</a> covers some more advanced features of jsPsych. This workshop was funded by the National Science Foundation.</p>
 <p><strong>babySTEP (2021)</strong>. The Centre for Comparative Psycholinguistics (CCP, University of Alberta Department of Linguistics) hosted a two-part jsPsych workshop in 2021 as part of their annual <a href="https://ccp.artsrn.ualberta.ca/portfolio/step/">STEP program</a>. <a href="https://drive.google.com/file/d/1_bd_Tz1IoyGaZzuPoR_Qb6Rtd5wg4t4D/view?usp=drive_web">Day 1</a> covered the basics of creating a jsPsych experiment, with an emphasis on audio stimuli. <a href="https://drive.google.com/file/d/1dIw1xIVY1lCHwFKGRaUnWMguwHfdkbGK/view?usp=drive_web">Day 2</a> was organized around pre-submitted questions. The video demonstrates how to create a more complex experiment involving reading a sentence and hearing different audio options for completing the sentences, and answers several questions about timing accuracy, recording participant generated audio, embedding jsPsych into course (or other) websites, and some (non-empirical) advice about attention checks.</p>
 
-              
-            </article>
-          </div>
+
+  
+
+
+
+
+                
+              </article>
+            </div>
+          
+          
         </div>
         
       </main>
       
         <footer class="md-footer">
   
-    <nav class="md-footer__inner md-grid" aria-label="Footer">
+    
+    <nav class="md-footer__inner md-grid" aria-label="Footer" >
       
         
         <a href="../rt-task/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Demo Experiment: Simple Reaction Time Task" rel="prev">
@@ -2018,7 +2032,7 @@ <h2 id="workshops">Workshops<a class="headerlink" href="#workshops" title="Perma
       
     
     <a href="https://github.com/jspsych" target="_blank" rel="noopener" title="github.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
     </a>
   
     
@@ -2027,7 +2041,7 @@ <h2 id="workshops">Workshops<a class="headerlink" href="#workshops" title="Perma
       
     
     <a href="https://twitter.com/joshdeleeuw" target="_blank" rel="noopener" title="twitter.com" class="md-social__link">
-      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.1.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
+      <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2022 Fonticons, Inc.--><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg>
     </a>
   
 </div>
@@ -2040,11 +2054,13 @@ <h2 id="workshops">Workshops<a class="headerlink" href="#workshops" title="Perma
     <div class="md-dialog" data-md-component="dialog">
       <div class="md-dialog__inner md-typeset"></div>
     </div>
-    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.2a1c317c.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
+    
+    <script id="__config" type="application/json">{"base": "../..", "features": [], "search": "../../assets/javascripts/workers/search.16e2a7d4.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.config.lang": "en", "search.config.pipeline": "trimmer, stopWordFilter", "search.config.separator": "[\\s\\-]+", "search.placeholder": "Search", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version.title": "Select version"}, "version": {"provider": "mike"}}</script>
     
     
-      <script src="../../assets/javascripts/bundle.a6c66575.min.js"></script>
+      <script src="../../assets/javascripts/bundle.5a2dcb6a.min.js"></script>
       
     
+    
   </body>
 </html>
\ No newline at end of file
